{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Reading 10X Cell Ranger output directly\n", "\n", "If for whatever reason you've decided to skip the reannotation/preprocessing, you can read the files directly from the Cell Ranger output folder with `Dandelion`'s `ddl.read_10x_vdj`, which accepts the `*_contig_annotations.csv` or `all_contig_annotations.json` file(s) as input. If reading with the `.csv` file, and the `.fasta` file and/or `.json` file(s) are in the same folder, `ddl.read_10x_vdj` will try to extract additional information not found in the `.csv` file e.g. contig sequences.\n", "\n", "From Cell Ranger V4 onwards, there is also an `airr_rearrangement.tsv` file that can be used directly with `Dandelion`. However, doing so will miss out on the reannotation steps but that is entirely up to you.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import dandelion module" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "Lazy Dandelion object with n_obs = 994 and n_contigs = 2601\n", " data: cell_id, is_cell_10x, sequence_id, high_confidence_10x, sequence_length_10x, locus, v_call, d_call, j_call, c_call, complete_vdj, productive, junction_aa, junction, consensus_count, umi_count, clone_id, raw_consensus_id_10x, sequence, rearrangement_status\n", " metadata: cell_id, clone_id, clone_id_rank, locus_VDJ, locus_VJ, v_call_VDJ, v_call_VJ, d_call_VDJ, j_call_VDJ, j_call_VJ, c_call_VDJ, c_call_VJ, junction_aa_VDJ, junction_aa_VJ, junction_VDJ, junction_VJ, umi_count_VDJ, umi_count_VJ, locus_VDJ_main, locus_VJ_main, v_call_VDJ_main, v_call_VJ_main, d_call_VDJ_main, j_call_VDJ_main, j_call_VJ_main, c_call_VDJ_main, c_call_VJ_main, junction_aa_VDJ_main, junction_aa_VJ_main, junction_VDJ_main, junction_VJ_main, umi_count_VDJ_main, umi_count_VJ_main, isotype, isotype_main, isotype_status, locus_status, chain_status, rearrangement_status_VDJ, rearrangement_status_VJ" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import os\n", "import pandas as pd\n", "import dandelion as ddl\n", "\n", "# new function to setup tutorial data\n", "from dandelion.tutorial import setup_dandelion_tutorial_bcr\n", "\n", "setup_dandelion_tutorial_bcr()\n", "\n", "# change directory to somewhere more workable\n", "os.chdir(\"dandelion_tutorial\")\n", "# ddl.logging.print_versions()\n", "folder_location = \"sc5p_v2_hs_PBMC_10k_b\"\n", "# or file_location = 'sc5p_v2_hs_PBMC_10k/'\n", "vdj = ddl.read_10x_vdj(folder_location, filename_prefix=\"filtered\")\n", "vdj" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With `ddl.read_10x_airr`:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "Lazy Dandelion object with n_obs = 994 and n_contigs = 2093\n", " data: cell_id, sequence_id, sequence, sequence_aa, productive, rev_comp, v_call, v_cigar, d_call, d_cigar, j_call, j_cigar, c_call, c_cigar, sequence_alignment, germline_alignment, junction, junction_aa, junction_length, junction_aa_length, v_sequence_start, v_sequence_end, d_sequence_start, d_sequence_end, j_sequence_start, j_sequence_end, c_sequence_start, c_sequence_end, consensus_count, umi_count, is_cell, locus, rearrangement_status\n", " metadata: cell_id, productive_VDJ, productive_VJ, v_call_VDJ, v_call_VJ, d_call_VDJ, j_call_VDJ, j_call_VJ, c_call_VDJ, c_call_VJ, junction_VDJ, junction_VJ, junction_aa_VDJ, junction_aa_VJ, locus_VDJ, locus_VJ, umi_count_VDJ, umi_count_VJ, productive_VDJ_main, productive_VJ_main, v_call_VDJ_main, v_call_VJ_main, d_call_VDJ_main, j_call_VDJ_main, j_call_VJ_main, c_call_VDJ_main, c_call_VJ_main, junction_VDJ_main, junction_VJ_main, junction_aa_VDJ_main, junction_aa_VJ_main, locus_VDJ_main, locus_VJ_main, umi_count_VDJ_main, umi_count_VJ_main, isotype, isotype_main, isotype_status, locus_status, chain_status, rearrangement_status_VDJ, rearrangement_status_VJ" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# read in the airr_rearrangement.tsv file\n", "file_location = \"sc5p_v2_hs_PBMC_10k_b/airr_rearrangement.tsv\"\n", "vdj = ddl.read_10x_airr(file_location)\n", "vdj" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you are using non-10x data e.g. Parse Bioscience Evercode, BD Rhapsody, you can use `ddl.read_parse_airr` and `ddl.read_bd_airr` respectively. If you are using other sources of single-cell AIRR data that provides standard AIRR formatted files e.g. SeekGene Biosciences, or just a standard AIRR file, you can use `ddl.read_airr` directly." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will continue with the rest of the filtering part of the analysis to show how it slots smoothly with the rest of the workflow." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import modules for use with scanpy" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "6d2e077fe72c4507b8e514451d1c047a", "version_major": 2, "version_minor": 0 }, "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
PackageVersion
sc-dandelion1.0.0a1.dev36+dirty (1.0.0a1.dev36)
pandas2.3.3
scanpy1.11.5
ComponentInfo
Python3.12.9 | packaged by conda-forge | (main, Mar 4 2025, 22:44:42) [Clang 18.1.8 ]
OSmacOS-26.3.1-arm64-arm-64bit
CPU8 logical CPU cores, arm
GPUNo GPU found
Updated2026-05-02 05:38
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DependencyVersion
numpy2.3.5
natsort8.4.0
scipy1.15.2
more-itertools10.8.0
circlify0.15.1
presto0.7.6
toolz1.1.0
setuptools75.8.0
pickleshare0.7.5
six1.17.0
mizani0.13.1
python-dateutil2.9.0.post0
pure_eval0.2.3
session-info20.3
packaging24.2
zarr3.2.0
pyzmq27.1.0
coverage7.13.1
yamlordereddictloader0.4.2
llvmlite0.46.0
sphinxcontrib-serializinghtml2.0.0
PyYAML6.0.3
decorator5.1.1
prompt_toolkit3.0.48
joblib1.5.3
kiwisolver1.4.9
defusedxml0.7.1
donfig0.8.1.post1
numcodecs0.15.1
biopython1.86
typing_extensions4.15.0
polars-runtime-321.38.1
threadpoolctl3.6.0
sphinxcontrib-devhelp2.0.0
setuptools-scm9.2.2
wcwidth0.2.13
RapidFuzz3.14.3
h5py3.15.1
tornado6.5.4
pillow11.3.0
psutil7.2.1
sphinxcontrib-qthelp2.0.0
platformdirs4.3.6
ipykernel6.29.5
jupyter_client8.6.3
asttokens3.0.0
attrs24.3.0
nxviz0.7.6
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sphinxcontrib-jquery4.1
airr1.5.1
sparse0.17.0
numba0.63.1
patsy1.0.2
jaraco.text3.12.1
google-crc32c1.8.0
rich14.3.1
cloudpickle3.1.2
ipython8.31.0
jupyter_core5.7.2
networkx3.6.1
tqdm4.67.1
ipywidgets8.1.5
polars1.38.1
stack_data0.6.3
debugpy1.8.19
comm0.2.2
executing2.1.0
dask2025.12.0
tblib3.2.2
palettable3.3.3
jaraco.functools4.0.1
igraph1.0.0
Pygments2.19.1
wrapt2.0.1
scikit-learn1.8.0
traitlets5.14.3
sphinxcontrib-htmlhelp2.1.0
appnope0.1.4
Cython3.2.4
plotnine0.14.6
awkward2.8.11
pytz2024.2
texttable1.7.0
pyarrow22.0.0
statsmodels0.14.6
matplotlib3.10.6
legacy-api-wrap1.5
Jinja23.1.5
jedi0.19.2
seaborn0.13.2
sphinxcontrib-applehelp2.0.0
polyleven0.9.0
sphinxcontrib-jsmath1.0.1
jaraco.collections5.1.0
msgpack1.1.2
fast-array-utils1.3.1
changeo1.3.4
cycler0.12.1
MarkupSafe3.0.3
fsspec2026.1.0
leidenalg0.11.0
jaraco.context5.3.0
charset-normalizer3.4.1
xarray2025.12.0
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anndata0.12.6
pyparsing3.2.3
awkward_cpp51
\n", "
\n", "
\n", "
\n", " Copyable Markdown\n", " 
| Package      | Version                             |\n",
       "| ------------ | ----------------------------------- |\n",
       "| sc-dandelion | 1.0.0a1.dev36+dirty (1.0.0a1.dev36) |\n",
       "| pandas       | 2.3.3                               |\n",
       "| scanpy       | 1.11.5                              |\n",
       "\n",
       "| Dependency                    | Version     |\n",
       "| ----------------------------- | ----------- |\n",
       "| numpy                         | 2.3.5       |\n",
       "| natsort                       | 8.4.0       |\n",
       "| scipy                         | 1.15.2      |\n",
       "| more-itertools                | 10.8.0      |\n",
       "| circlify                      | 0.15.1      |\n",
       "| presto                        | 0.7.6       |\n",
       "| toolz                         | 1.1.0       |\n",
       "| setuptools                    | 75.8.0      |\n",
       "| pickleshare                   | 0.7.5       |\n",
       "| six                           | 1.17.0      |\n",
       "| mizani                        | 0.13.1      |\n",
       "| python-dateutil               | 2.9.0.post0 |\n",
       "| pure_eval                     | 0.2.3       |\n",
       "| session-info2                 | 0.3         |\n",
       "| packaging                     | 24.2        |\n",
       "| zarr                          | 3.2.0       |\n",
       "| pyzmq                         | 27.1.0      |\n",
       "| coverage                      | 7.13.1      |\n",
       "| yamlordereddictloader         | 0.4.2       |\n",
       "| llvmlite                      | 0.46.0      |\n",
       "| sphinxcontrib-serializinghtml | 2.0.0       |\n",
       "| PyYAML                        | 6.0.3       |\n",
       "| decorator                     | 5.1.1       |\n",
       "| prompt_toolkit                | 3.0.48      |\n",
       "| joblib                        | 1.5.3       |\n",
       "| kiwisolver                    | 1.4.9       |\n",
       "| defusedxml                    | 0.7.1       |\n",
       "| donfig                        | 0.8.1.post1 |\n",
       "| numcodecs                     | 0.15.1      |\n",
       "| biopython                     | 1.86        |\n",
       "| typing_extensions             | 4.15.0      |\n",
       "| polars-runtime-32             | 1.38.1      |\n",
       "| threadpoolctl                 | 3.6.0       |\n",
       "| sphinxcontrib-devhelp         | 2.0.0       |\n",
       "| setuptools-scm                | 9.2.2       |\n",
       "| wcwidth                       | 0.2.13      |\n",
       "| RapidFuzz                     | 3.14.3      |\n",
       "| h5py                          | 3.15.1      |\n",
       "| tornado                       | 6.5.4       |\n",
       "| pillow                        | 11.3.0      |\n",
       "| psutil                        | 7.2.1       |\n",
       "| sphinxcontrib-qthelp          | 2.0.0       |\n",
       "| platformdirs                  | 4.3.6       |\n",
       "| ipykernel                     | 6.29.5      |\n",
       "| jupyter_client                | 8.6.3       |\n",
       "| asttokens                     | 3.0.0       |\n",
       "| attrs                         | 24.3.0      |\n",
       "| nxviz                         | 0.7.6       |\n",
       "| Deprecated                    | 1.3.1       |\n",
       "| sphinxcontrib-jquery          | 4.1         |\n",
       "| airr                          | 1.5.1       |\n",
       "| sparse                        | 0.17.0      |\n",
       "| numba                         | 0.63.1      |\n",
       "| patsy                         | 1.0.2       |\n",
       "| jaraco.text                   | 3.12.1      |\n",
       "| google-crc32c                 | 1.8.0       |\n",
       "| rich                          | 14.3.1      |\n",
       "| cloudpickle                   | 3.1.2       |\n",
       "| ipython                       | 8.31.0      |\n",
       "| jupyter_core                  | 5.7.2       |\n",
       "| networkx                      | 3.6.1       |\n",
       "| tqdm                          | 4.67.1      |\n",
       "| ipywidgets                    | 8.1.5       |\n",
       "| polars                        | 1.38.1      |\n",
       "| stack_data                    | 0.6.3       |\n",
       "| debugpy                       | 1.8.19      |\n",
       "| comm                          | 0.2.2       |\n",
       "| executing                     | 2.1.0       |\n",
       "| dask                          | 2025.12.0   |\n",
       "| tblib                         | 3.2.2       |\n",
       "| palettable                    | 3.3.3       |\n",
       "| jaraco.functools              | 4.0.1       |\n",
       "| igraph                        | 1.0.0       |\n",
       "| Pygments                      | 2.19.1      |\n",
       "| wrapt                         | 2.0.1       |\n",
       "| scikit-learn                  | 1.8.0       |\n",
       "| traitlets                     | 5.14.3      |\n",
       "| sphinxcontrib-htmlhelp        | 2.1.0       |\n",
       "| appnope                       | 0.1.4       |\n",
       "| Cython                        | 3.2.4       |\n",
       "| plotnine                      | 0.14.6      |\n",
       "| awkward                       | 2.8.11      |\n",
       "| pytz                          | 2024.2      |\n",
       "| texttable                     | 1.7.0       |\n",
       "| pyarrow                       | 22.0.0      |\n",
       "| statsmodels                   | 0.14.6      |\n",
       "| matplotlib                    | 3.10.6      |\n",
       "| legacy-api-wrap               | 1.5         |\n",
       "| Jinja2                        | 3.1.5       |\n",
       "| jedi                          | 0.19.2      |\n",
       "| seaborn                       | 0.13.2      |\n",
       "| sphinxcontrib-applehelp       | 2.0.0       |\n",
       "| polyleven                     | 0.9.0       |\n",
       "| sphinxcontrib-jsmath          | 1.0.1       |\n",
       "| jaraco.collections            | 5.1.0       |\n",
       "| msgpack                       | 1.1.2       |\n",
       "| fast-array-utils              | 1.3.1       |\n",
       "| changeo                       | 1.3.4       |\n",
       "| cycler                        | 0.12.1      |\n",
       "| MarkupSafe                    | 3.0.3       |\n",
       "| fsspec                        | 2026.1.0    |\n",
       "| leidenalg                     | 0.11.0      |\n",
       "| jaraco.context                | 5.3.0       |\n",
       "| charset-normalizer            | 3.4.1       |\n",
       "| xarray                        | 2025.12.0   |\n",
       "| parso                         | 0.8.4       |\n",
       "| anndata                       | 0.12.6      |\n",
       "| pyparsing                     | 3.2.3       |\n",
       "| awkward_cpp                   | 51          |\n",
       "\n",
       "| Component | Info                                                                             |\n",
       "| --------- | -------------------------------------------------------------------------------- |\n",
       "| Python    | 3.12.9 | packaged by conda-forge | (main, Mar  4 2025, 22:44:42) [Clang 18.1.8 ] |\n",
       "| OS        | macOS-26.3.1-arm64-arm-64bit                                                     |\n",
       "| CPU       | 8 logical CPU cores, arm                                                         |\n",
       "| GPU       | No GPU found                                                                     |\n",
       "| Updated   | 2026-05-02 05:38                                                                 |
\n", "
" ], "text/markdown": [ "| Package | Version |\n", "| ------------ | ----------------------------------- |\n", "| sc-dandelion | 1.0.0a1.dev36+dirty (1.0.0a1.dev36) |\n", "| pandas | 2.3.3 |\n", "| scanpy | 1.11.5 |\n", "\n", "| Dependency | Version |\n", "| ----------------------------- | ----------- |\n", "| numpy | 2.3.5 |\n", "| natsort | 8.4.0 |\n", "| scipy | 1.15.2 |\n", "| more-itertools | 10.8.0 |\n", "| circlify | 0.15.1 |\n", "| presto | 0.7.6 |\n", "| toolz | 1.1.0 |\n", "| setuptools | 75.8.0 |\n", "| pickleshare | 0.7.5 |\n", "| six | 1.17.0 |\n", "| mizani | 0.13.1 |\n", "| python-dateutil | 2.9.0.post0 |\n", "| pure_eval | 0.2.3 |\n", "| session-info2 | 0.3 |\n", "| packaging | 24.2 |\n", "| zarr | 3.2.0 |\n", "| pyzmq | 27.1.0 |\n", "| coverage | 7.13.1 |\n", "| yamlordereddictloader | 0.4.2 |\n", "| llvmlite | 0.46.0 |\n", "| sphinxcontrib-serializinghtml | 2.0.0 |\n", "| PyYAML | 6.0.3 |\n", "| decorator | 5.1.1 |\n", "| prompt_toolkit | 3.0.48 |\n", "| joblib | 1.5.3 |\n", "| kiwisolver | 1.4.9 |\n", "| defusedxml | 0.7.1 |\n", "| donfig | 0.8.1.post1 |\n", "| numcodecs | 0.15.1 |\n", "| biopython | 1.86 |\n", "| typing_extensions | 4.15.0 |\n", "| polars-runtime-32 | 1.38.1 |\n", "| threadpoolctl | 3.6.0 |\n", "| sphinxcontrib-devhelp | 2.0.0 |\n", "| setuptools-scm | 9.2.2 |\n", "| wcwidth | 0.2.13 |\n", "| RapidFuzz | 3.14.3 |\n", "| h5py | 3.15.1 |\n", "| tornado | 6.5.4 |\n", "| pillow | 11.3.0 |\n", "| psutil | 7.2.1 |\n", "| sphinxcontrib-qthelp | 2.0.0 |\n", "| platformdirs | 4.3.6 |\n", "| ipykernel | 6.29.5 |\n", "| jupyter_client | 8.6.3 |\n", "| asttokens | 3.0.0 |\n", "| attrs | 24.3.0 |\n", "| nxviz | 0.7.6 |\n", "| Deprecated | 1.3.1 |\n", "| sphinxcontrib-jquery | 4.1 |\n", "| airr | 1.5.1 |\n", "| sparse | 0.17.0 |\n", "| numba | 0.63.1 |\n", "| patsy | 1.0.2 |\n", "| jaraco.text | 3.12.1 |\n", "| google-crc32c | 1.8.0 |\n", "| rich | 14.3.1 |\n", "| cloudpickle | 3.1.2 |\n", "| ipython | 8.31.0 |\n", "| jupyter_core | 5.7.2 |\n", "| networkx | 3.6.1 |\n", "| tqdm | 4.67.1 |\n", "| ipywidgets | 8.1.5 |\n", "| polars | 1.38.1 |\n", "| stack_data | 0.6.3 |\n", "| debugpy | 1.8.19 |\n", "| comm | 0.2.2 |\n", "| executing | 2.1.0 |\n", "| dask | 2025.12.0 |\n", "| tblib | 3.2.2 |\n", "| palettable | 3.3.3 |\n", "| jaraco.functools | 4.0.1 |\n", "| igraph | 1.0.0 |\n", "| Pygments | 2.19.1 |\n", "| wrapt | 2.0.1 |\n", "| scikit-learn | 1.8.0 |\n", "| traitlets | 5.14.3 |\n", "| sphinxcontrib-htmlhelp | 2.1.0 |\n", "| appnope | 0.1.4 |\n", "| Cython | 3.2.4 |\n", "| plotnine | 0.14.6 |\n", "| awkward | 2.8.11 |\n", "| pytz | 2024.2 |\n", "| texttable | 1.7.0 |\n", "| pyarrow | 22.0.0 |\n", "| statsmodels | 0.14.6 |\n", "| matplotlib | 3.10.6 |\n", "| legacy-api-wrap | 1.5 |\n", "| Jinja2 | 3.1.5 |\n", "| jedi | 0.19.2 |\n", "| seaborn | 0.13.2 |\n", "| sphinxcontrib-applehelp | 2.0.0 |\n", "| polyleven | 0.9.0 |\n", "| sphinxcontrib-jsmath | 1.0.1 |\n", "| jaraco.collections | 5.1.0 |\n", "| msgpack | 1.1.2 |\n", "| fast-array-utils | 1.3.1 |\n", "| changeo | 1.3.4 |\n", "| cycler | 0.12.1 |\n", "| MarkupSafe | 3.0.3 |\n", "| fsspec | 2026.1.0 |\n", "| leidenalg | 0.11.0 |\n", "| jaraco.context | 5.3.0 |\n", "| charset-normalizer | 3.4.1 |\n", "| xarray | 2025.12.0 |\n", "| parso | 0.8.4 |\n", "| anndata | 0.12.6 |\n", "| pyparsing | 3.2.3 |\n", "| awkward_cpp | 51 |\n", "\n", "| Component | Info |\n", "| --------- | -------------------------------------------------------------------------------- |\n", "| Python | 3.12.9 | packaged by conda-forge | (main, Mar 4 2025, 22:44:42) [Clang 18.1.8 ] |\n", "| OS | macOS-26.3.1-arm64-arm-64bit |\n", "| CPU | 8 logical CPU cores, arm |\n", "| GPU | No GPU found |\n", "| Updated | 2026-05-02 05:38 |" ], "text/plain": [ "sc-dandelion\t1.0.0a1.dev36+dirty (1.0.0a1.dev36)\n", "pandas\t2.3.3\n", "scanpy\t1.11.5\n", "----\t----\n", "numpy\t2.3.5\n", "natsort\t8.4.0\n", "scipy\t1.15.2\n", "more-itertools\t10.8.0\n", "circlify\t0.15.1\n", "presto\t0.7.6\n", "toolz\t1.1.0\n", "setuptools\t75.8.0\n", "pickleshare\t0.7.5\n", "six\t1.17.0\n", "mizani\t0.13.1\n", "python-dateutil\t2.9.0.post0\n", "pure_eval\t0.2.3\n", "session-info2\t0.3\n", "packaging\t24.2\n", "zarr\t3.2.0\n", "pyzmq\t27.1.0\n", "coverage\t7.13.1\n", "yamlordereddictloader\t0.4.2\n", "llvmlite\t0.46.0\n", "sphinxcontrib-serializinghtml\t2.0.0\n", "PyYAML\t6.0.3\n", "decorator\t5.1.1\n", "prompt_toolkit\t3.0.48\n", "joblib\t1.5.3\n", "kiwisolver\t1.4.9\n", "defusedxml\t0.7.1\n", "donfig\t0.8.1.post1\n", "numcodecs\t0.15.1\n", "biopython\t1.86\n", "typing_extensions\t4.15.0\n", "polars-runtime-32\t1.38.1\n", "threadpoolctl\t3.6.0\n", "sphinxcontrib-devhelp\t2.0.0\n", "setuptools-scm\t9.2.2\n", "wcwidth\t0.2.13\n", "RapidFuzz\t3.14.3\n", "h5py\t3.15.1\n", "tornado\t6.5.4\n", "pillow\t11.3.0\n", "psutil\t7.2.1\n", "sphinxcontrib-qthelp\t2.0.0\n", "platformdirs\t4.3.6\n", "ipykernel\t6.29.5\n", "jupyter_client\t8.6.3\n", "asttokens\t3.0.0\n", "attrs\t24.3.0\n", "nxviz\t0.7.6\n", "Deprecated\t1.3.1\n", "sphinxcontrib-jquery\t4.1\n", "airr\t1.5.1\n", "sparse\t0.17.0\n", "numba\t0.63.1\n", "patsy\t1.0.2\n", "jaraco.text\t3.12.1\n", "google-crc32c\t1.8.0\n", "rich\t14.3.1\n", "cloudpickle\t3.1.2\n", "ipython\t8.31.0\n", "jupyter_core\t5.7.2\n", "networkx\t3.6.1\n", "tqdm\t4.67.1\n", "ipywidgets\t8.1.5\n", "polars\t1.38.1\n", "stack_data\t0.6.3\n", "debugpy\t1.8.19\n", "comm\t0.2.2\n", "executing\t2.1.0\n", "dask\t2025.12.0\n", "tblib\t3.2.2\n", "palettable\t3.3.3\n", "jaraco.functools\t4.0.1\n", "igraph\t1.0.0\n", "Pygments\t2.19.1\n", "wrapt\t2.0.1\n", "scikit-learn\t1.8.0\n", "traitlets\t5.14.3\n", "sphinxcontrib-htmlhelp\t2.1.0\n", "appnope\t0.1.4\n", "Cython\t3.2.4\n", "plotnine\t0.14.6\n", "awkward\t2.8.11\n", "pytz\t2024.2\n", "texttable\t1.7.0\n", "pyarrow\t22.0.0\n", "statsmodels\t0.14.6\n", "matplotlib\t3.10.6\n", "legacy-api-wrap\t1.5\n", "Jinja2\t3.1.5\n", "jedi\t0.19.2\n", "seaborn\t0.13.2\n", "sphinxcontrib-applehelp\t2.0.0\n", "polyleven\t0.9.0\n", "sphinxcontrib-jsmath\t1.0.1\n", "jaraco.collections\t5.1.0\n", "msgpack\t1.1.2\n", "fast-array-utils\t1.3.1\n", "changeo\t1.3.4\n", "cycler\t0.12.1\n", "MarkupSafe\t3.0.3\n", "fsspec\t2026.1.0\n", "leidenalg\t0.11.0\n", "jaraco.context\t5.3.0\n", "charset-normalizer\t3.4.1\n", "xarray\t2025.12.0\n", "parso\t0.8.4\n", "anndata\t0.12.6\n", "pyparsing\t3.2.3\n", "awkward_cpp\t51\n", "----\t----\n", "Python\t3.12.9 | packaged by conda-forge | (main, Mar 4 2025, 22:44:42) [Clang 18.1.8 ]\n", "OS\tmacOS-26.3.1-arm64-arm-64bit\n", "CPU\t8 logical CPU cores, arm\n", "GPU\tNo GPU found\n", "Updated\t2026-05-02 05:38" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import scanpy as sc\n", "import warnings\n", "\n", "warnings.filterwarnings(\"ignore\")\n", "sc.logging.print_header()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import the transcriptome data" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "AnnData object with n_obs × n_vars = 10553 × 36601\n", " obs: 'sample_id'\n", " var: 'gene_ids', 'feature_types', 'genome', 'pattern', 'read', 'sequence'" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "adata = sc.read_10x_h5(\n", " \"sc5p_v2_hs_PBMC_10k_b/filtered_feature_bc_matrix.h5\", gex_only=True\n", ")\n", "adata.obs[\"sample_id\"] = \"sc5p_v2_hs_PBMC_10k_b\"\n", "adata.var_names_make_unique()\n", "adata" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Run QC on the transcriptome data." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n" ] }, { "data": { "text/plain": [ "AnnData object with n_obs × n_vars = 10553 × 36601\n", " obs: 'sample_id', 'n_genes', 'n_genes_by_counts', 'total_counts', 'total_counts_mt', 'pct_counts_mt', 'scrublet_score', 'is_doublet', 'filter_rna'\n", " var: 'gene_ids', 'feature_types', 'genome', 'pattern', 'read', 'sequence'" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ddl.pp.recipe_scanpy_qc(adata)\n", "adata" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Run the filtering of bcr data. Note that I'm using the `DandelionPolars` object as input rather than the pandas dataframe (yes both types of input will works. In fact, a file path to the .tsv will work too)." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Filtering contigs...\n", "Marking ambiguous contigs...\n", "Initializing DandelionPolars object...\n" ] } ], "source": [ "# The function will return both objects.\n", "vdj, adata = ddl.pp.check_contigs(vdj, adata)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Check the output V(D)J table\n", "\n", "The vdj table is returned as a `DandelionPolars` class object in the `.data` slot; if a file was provided for `filter_bcr` above, a new file will be created in the same folder with the `filtered` prefix. Note that this V(D)J table is indexed based on contigs (sequence_id)." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Lazy Dandelion object with n_obs = 984 and n_contigs = 2028\n", " data: cell_id, sequence_id, sequence, sequence_aa, productive, rev_comp, v_call, v_cigar, d_call, d_cigar, j_call, j_cigar, c_call, c_cigar, sequence_alignment, germline_alignment, junction, junction_aa, junction_length, junction_aa_length, v_sequence_start, v_sequence_end, d_sequence_start, d_sequence_end, j_sequence_start, j_sequence_end, c_sequence_start, c_sequence_end, consensus_count, umi_count, is_cell, locus, rearrangement_status, extra, ambiguous\n", " metadata: cell_id, productive_VDJ, productive_VJ, v_call_VDJ, v_call_VJ, d_call_VDJ, j_call_VDJ, j_call_VJ, c_call_VDJ, c_call_VJ, junction_VDJ, junction_VJ, junction_aa_VDJ, junction_aa_VJ, locus_VDJ, locus_VJ, umi_count_VDJ, umi_count_VJ, productive_VDJ_main, productive_VJ_main, v_call_VDJ_main, v_call_VJ_main, d_call_VDJ_main, j_call_VDJ_main, j_call_VJ_main, c_call_VDJ_main, c_call_VJ_main, junction_VDJ_main, junction_VJ_main, junction_aa_VDJ_main, junction_aa_VJ_main, locus_VDJ_main, locus_VJ_main, umi_count_VDJ_main, umi_count_VJ_main, isotype, isotype_main, isotype_status, locus_status, chain_status, rearrangement_status_VDJ, rearrangement_status_VJ" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vdj" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Check the AnnData object as well\n", "\n", "And the `AnnData` object is indexed based on cells." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "AnnData object with n_obs × n_vars = 10553 × 36601\n", " obs: 'sample_id', 'n_genes', 'n_genes_by_counts', 'total_counts', 'total_counts_mt', 'pct_counts_mt', 'scrublet_score', 'is_doublet', 'filter_rna', 'has_contig', 'productive_VDJ', 'productive_VJ', 'v_call_VDJ', 'v_call_VJ', 'd_call_VDJ', 'j_call_VDJ', 'j_call_VJ', 'c_call_VDJ', 'c_call_VJ', 'junction_VDJ', 'junction_VJ', 'junction_aa_VDJ', 'junction_aa_VJ', 'locus_VDJ', 'locus_VJ', 'umi_count_VDJ', 'umi_count_VJ', 'productive_VDJ_main', 'productive_VJ_main', 'v_call_VDJ_main', 'v_call_VJ_main', 'd_call_VDJ_main', 'j_call_VDJ_main', 'j_call_VJ_main', 'c_call_VDJ_main', 'c_call_VJ_main', 'junction_VDJ_main', 'junction_VJ_main', 'junction_aa_VDJ_main', 'junction_aa_VJ_main', 'locus_VDJ_main', 'locus_VJ_main', 'umi_count_VDJ_main', 'umi_count_VJ_main', 'isotype', 'isotype_main', 'isotype_status', 'locus_status', 'chain_status', 'rearrangement_status_VDJ', 'rearrangement_status_VJ'\n", " var: 'gene_ids', 'feature_types', 'genome', 'pattern', 'read', 'sequence'" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "adata" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The number of cells that actually has a matching BCR can be tabluated." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": true }, "outputs": [ { "data": { "application/vnd.microsoft.datawrangler.viewer.v0+json": { "columns": [ { "name": "has_contig", "rawType": "object", "type": "string" }, { "name": "Extra pair", "rawType": "int64", "type": "integer" }, { "name": "Orphan VDJ", "rawType": "int64", "type": "integer" }, { "name": "Orphan VJ", "rawType": "int64", "type": "integer" }, { "name": "Single pair", "rawType": "int64", "type": "integer" } ], "ref": "1d9d4c35-d15d-4108-8ecf-06a7702bdd58", "rows": [ [ "True", "81", "5", "16", "882" ] ], "shape": { "columns": 4, "rows": 1 } }, "text/html": [ "
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" ], "text/plain": [ "chain_status Extra pair Orphan VDJ Orphan VJ Single pair\n", "has_contig \n", "True 81 5 16 882" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.crosstab(adata.obs[\"has_contig\"], adata.obs[\"chain_status\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now actually filter the AnnData object and run through a standard workflow starting by filtering genes and normalizing the data\n", "\n", "Because the 'filtered' `AnnData` object was returned as a filtered but otherwise unprocessed object, we still need to normalize and run through the usual process here. The following is just a standard scanpy workflow." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "adata = adata[\n", " adata.obs[\"filter_rna\"] == \"False\"\n", "] # from ddl.pp.recipe_scanpy_qc\n", "# filter genes\n", "sc.pp.filter_genes(adata, min_cells=3)\n", "# Normalize the counts\n", "sc.pp.normalize_total(adata, target_sum=1e4)\n", "# Logarithmize the data\n", "sc.pp.log1p(adata)\n", "# Stash the normalised counts\n", "adata.raw = adata" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Identify highly-variable genes" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)\n", "sc.pl.highly_variable_genes(adata)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Filter the genes to only those marked as highly-variable" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "adata = adata[:, adata.var.highly_variable]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Regress out effects of total counts per cell and the percentage of mitochondrial genes expressed. Scale the data to unit variance." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "sc.pp.regress_out(adata, [\"total_counts\", \"pct_counts_mt\"])\n", "sc.pp.scale(adata, max_value=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Run PCA" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sc.tl.pca(adata, svd_solver=\"arpack\")\n", "sc.pl.pca_variance_ratio(adata, log=True, n_pcs=50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Computing the neighborhood graph, umap and clusters" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# Computing the neighborhood graph\n", "sc.pp.neighbors(adata)\n", "# Embedding the neighborhood graph\n", "sc.tl.umap(adata)\n", "# Clustering the neighborhood graph\n", "sc.tl.leiden(adata)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualizing the clusters and whether or not there's a corresponding BCR" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sc.pl.umap(adata, color=[\"leiden\", \"chain_status\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualizing some B cell genes" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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u8gU5zDvYoeAVnnzySQYOHEhqaiqlpaWMHz+eGTNmMHXqVACeeOIJdu/ezRdffAHA22+/TaNGjWjdujVut5uvvvqKiRMnMnHixOo/lBBCCCGOytt3jWb6uJlExkdUeVxRFTI2ZmKxWRi15NUajq5uC7ZvVtG2pskUPCGEECelotxiPn5oHOAvNn7erf0wmqt+r2KxWchYv7smwzslVHRygvlUx549e7juuusCxcQXLFjA1KlTGTBgAABZWVns3Lkz0N7tdvPwww/Trl07evfuzZw5c5g8eTKXXHLJMX1eIYQQQhzaihlr+Our2QAYzUY69muDaqicdtD3Dr3xur3kZxXWeIx1WXX6ZtXtnw0fPhxFUSp9EhMTD3/ifmQElBBCiJPS1hU7/LUDujXC3TKJRcUleN3eKts6Sp08MXAEk/LHYjAaajhSUV1jxow55PGxY8dW2n700Ud59NFHj2NEQgghhAjG4mkr0Hz+EenFucWsKyoPbP/X9jUZvHnbKEb89mRNhiiOQuvWrfnzz33lLgyG6vWrZQSUEEKIk1L7vq1RVAV3o1h0BXYrh15M1lHqZNq4f2ooulODpitBf4QQQghR97Xp3TLws9ftO2D003+tnrOedQs2Hu+wThnV6ZsdSf/MaDSSmJgY+MTHx1frfElACSGEOCmVFpahazqh87dh3FWI/s+Gw3Zy3rztY/78alYNRVj3Ha8h3kIIIYQ4Oa2dt6HStr3EwaG6AfYSBw+e8QzZ23OOc2SnhiOZgldSUlLpc6hFXzZt2kRycjJpaWkMGTKErVurt4KhJKCEEEKclGb9MB8A8/YCwqetx5RVEhji3bpXOg1aJAOgGlWadmoUOO/XUVPJ2ranxuMVQgghhKjr1v674cCdOqgGhQE39MUWGQpATHI0MUmRAPg8Pia8+jMuR/Cr3YpjJzU1lcjIyMBn5MiRVbY7/fTT+eKLL/jjjz/45JNPyM7OpkePHuTn5wd9L6kBJYQQ4qTk8/gOemzdgk1oHn8ySlVV9P1m5639dxMfP/QFw3985HiHWOf5UPEF8S7r4P+mhBBCCFGXqGrV/QLNp7N46jLKi+0AhFjNFOeVBo7/9tE0GrVO5cJ7zq2ROOuqYPtm/rZ+GRkZRETsW7HQYrFU2X7gwIGBn9u2bUv37t1p0qQJ48aNY+jQoUHdUxJQQgghTkqrZq+rtJ3QII6cnXkAaB6N0HArbpeHsCgbW5Zvr9R2y4rK2+LI6EHWD9ClBpQQQghR5zntLnaszQhsG00GUPy1oAAK9xSjGlRsUaFkbjlwNPrmZdtqLNa6Kti+WUVbgIiIiEoJqGDZbDbatm3Lpk2bgj5HpuAJIYQ46Yx6cCzzfl5UaZ8tKrTSdvcLuxIVH05RTnFgnyXUDEBxTsnxD1IIIYQQ4hShaRqP9n+O/MzCwD6vx0do+L7+mcFo4MonLsJR6qx88t58SUF2IeLk4XK5WLduHUlJSUGfIwkoIYQQJxVHmYMf35mMz1t5Ypeu6ZW2//pqFnm7K3dkXHY3igJer5etK3cc91jrOilCLoQQQgiAH978jXXzDxwJY7Tsm3Tl8/r4dsSPeN3eyo32duF2rNmF2+U5nmHWeUdShDxYDz/8MDNnzmTbtm0sWLCAyy67jJKSEm644YagryEJKGDMptncMe9LVufvru1QhBBCHIbZaiYkLOSA/TvW7ArqfF0Hj8vL7s3Zxzq0U45PV4P+CFEdTo+XYT9M46Fxv1BSZq/tcIQQQhxGu94tq1ztrmC/EVEoBJJNVcndlY+zzHnwBuKwqtM3q27/bNeuXVx11VWkp6dzySWXYDabmT9/Pg0bNgz6Gqd0j1DTdApc5by97k/m5W3mul+/YHdh8eFPFEIIUWsMBgNPfvPAAft1XcdoNnL7a9cx5LGLAvuNJkOldqpB4Zphl9Lzoq7HOdK6T0NBQw3iIyOgRHB0XUfXdf5Zt4VJS9Ywdf0Wbr7qVXT9EH9jEUIIUetanN6MQbf3r/JYXEoMQz+5k67ndjjo+WFRNp78+n4iYsOPU4SnhuD7ZtXvn40fP57MzEzcbje7d+9m4sSJtGrVqlrXOCWLkG8tKOCKz7/BVeTm4cHdSTZGs9tTgKsEtucVkRIdWdshCiGEqEJxXgk3Nr+PsqKDjIhQ4N9fFrNq9jrMISY8Hi/e/6yWp/l0Zv84nxufH1IDEQshgvXrtBW8/O0/WK0mbh/cjRCvjtvjo2DJDjwuD+YQc22HKIQQogr//rqY5y59HV3TqjwenRjFxw9/QXmxncj4CIpzD6zFWVZUzpp56+lzRY/jHa6oRadMAuq3XSt5dsUkIk1WOtOGfLMLUxMXb+yZgkFRUVUIb6yRUM/E9zvncm5SJ8JNVlbkZfHMgul0rVefYV3OQtd1FOXQmUKn14vFYDhsOyGEENWz9M+VB08+AV6XN7A6ntt58BoChdky2vVYCLZ+gNSAEgfz3GdT+H7HBrrVT6Fofh4eXcNjd/H+O9Mw17NgwEDzm85i6fKdFBfbGTCgLaqqMHnycn75aSlXDjmds/q1Dqp/5nK4sFirXlpaCCHEkZs8+s8DanPub9OSrYGfq0o+VZDyCEevOrWdaqN/dsokoMZunotX95LvLuWPnWsxYcCmGvABmu7P1MaHhnPvkk8p8ZSztGAru53rKfOWsakslhX5WThMO1hQsJYH0y9lUHK3Ku/z8+Z1PD7rJ9rGJ/LtoBswqKf0LEchhDimWpzeHJPFiMflPXzjqij+8gM3vSijn46FYOsH+GT6lDiIX9asxxMFs7N3kRCqYMrRsBqN6HYNTVfwKToxseE89eT36MCatTuZ8uM8dLMNr0Hlk69n8dV9n1CUU8yr05+hace0Ku/z9p2jmTx6Olc8cgG3vXJdjT6jEELUdT0u6MyC35ccsr7ToSiKgtlq4rZX5c/no1Wd2k610T87JbIjS/9ahbrWhaYp+DQFp9tHgsfKwmsfYljbwTzb7mI0l5V1uWWEGMpIspWwsWwVpb4idMVLVKgTNJ1/89fg0zUm7VjAx6sWUup2oZW+g5ZzJrrjNwD+zVrKDV1n0bnRd+ws21jLTy6EEHXLe/d8Wu3kU1TCftOqdX/fyGoLwe10H9vghBDV8vunfxFeqqC6wWiHEoNO/1ZJjH/nFu66tz+3dmqO7Y/VrHtrKppZxWdR+XnZJkrS4iiNViloY2FNjJPN9jJKiu18/cpPTP38H9weLw+9NomrHh3L1l15AMyeOB+ASe9OkRWWhBDiGLKXOvji+R8OnXyqYqBNSNi+Eam6rmOLDMVe4jj2AYoTSp0fAVVSWMat48Zi66nRPr6E7LJwMpNUIuJ3M3zFKDb/FsnGkHwcqToGxYfVVIhJ1XD5Siiw2zArOvmlIUSEOqmnxqIbdrK9aBvT1zvYVJTHq83Hgl7Oztz3GZtvoEP9bLKc/uGHBe6dpNGidr8AIYSoI9xON4umLqv2eQ1apVCUW7yvY6TDKze8z+fPTODLLe+jykjVI+YvdHn44dtShFz8159fzeSt2z+i9JqOGMutqF4dU7nG7FU7iCv7iRnj/qGofX1K+6djL7RjUhUUFYwa/tenISZ01f/fVb2+Lcnf6WRGjp1/XviOHK+Hucv90z2ef/xLBnVsimdgSwoUjdDVeZQWlhObGFVrzy6EEHXJqtnryN9dcOhGVSSnOvRpzfzJSwPbBVlF3N/jKfpc3p1hE4Ye4yhPHcH2zSra1rQ63+teXZ5LwYB4kluVE2Z20yi8iPiIMiJDnWx1rWJHaSaFoV40hwHVpxNudBFjthNtKqe9uw87dsQSE1NOy9RsrKEbibeV0LJeLr2abWZq5hrGZDUnwx3KxKIQfs+cwdLixdh9Jko8Fp5ftpaVhTtr+ysQQog6wRxi5rKhgzFZTNU676J7BxKTGH3A/pwduWRt3XOswjslaaj4gvhodb+7IappzdwNaAYFV6IV3QCKDpYCHVCZ8uUsCjWN4tQoNJsZT/0oNKsKioKyq4iGkREYHBCa6SU028eebDe6wYAzwYKjZzP+WLIZc0YBal4pGb8s5YN3fiUjzIhmM+NqXY+RD39FQXbhYWMUQghxeO3OaHnI1e0O5uphl6EaDuwfLPpj+dEHdQoLtm9WW/2zOt8jbJ2QRJzBSq7ThstnIKMskqLMcBTNAvYYfA3CiCYEPCquwhC8HgOhqot4cxl/bNiAriiYDf4RTR7dgL53+kaE1YHBXMx3hUkMy+rCMkccSeFlFHpMFPusrC5KJNObw4urfqzdL0AIIeqQO16/nrBoGwCqQeXhsfcw+K5zDto+xGahU7+2XPrgoAOORcZHEJkgq54KURsG3NAXuqRjLtZQfDqqE7wRBpTyYoy9WqJf3BqLVUHRwFBgx1BoB6cHa1EZu7OLUVQFc56LkEINRQdlRxb63gK42zdnY5mzEdv0NahlTlynNcHg0lG8OuYiL8smL+arF36o3S9ACCHqCGuYlae+fSAwzS4+NZbnf36M5l2aHPScRq3r0/L0ZnQe0O6AY43bNzxOkYoTQZ1PQEWaQ+jvbEyeM4ylOansLInG6wljxc9pLF0bRYFqp0hz80Tr3sQvMrL711SSzUUkWoq5+ew/ubDlBvpE9sDpiiWjKJoFWamUe414dCPN4nPxaAYKnSHkFITTyNKSMq+FfLcN1aigoLE2u5gPli6o7a9BCCHqhNLCMpKa1AP89QJev/EDZkyYc9D2znIXP74zme2rMg44VpxbwsZFW45brKeCikKXwXyE2F+rbs0xNYxFNyoYXQqqy0dYmJmC9vFsSdPJTDFQEA+3NEwmauJyQv5aRci0ZWQnw54uENLGRv+UKMxZOXhdpeiFJYROX41l8TZC5m4K3EdRFRJDLRhdYFuaRcj0lajF5UwZ8zcrZqypxW9ACCHqjpxd+YRHhwGQuyufZy58hcI9RQdtn7Ehi19G/UF5yYErG6+ZswFN045XqHVedfpmtdE/OyV6hP+74AycJRacTiNOhwmLFoItykFKqxwapO8hvEERC9zbeWBIH05v0g6w+k9UdKIjcnmkYx9aKX3ILI6g1B1KmScEn66iqjq6rpBTEsGmbcmsyvNhViKwGHzEhtgJ13XKCkKZmbGtVp9fCCHqimcvfpW1czcAoGv+ggKlBeUYjIZAG0WtPJ/9i+HfM/3LmSgKmEP2Td9TFIWW3ZrVQNR1l7Z3+HYwHyH+69YrusHev2OELNmBrms4knTsDcETqaO6dGJaNGTwXefQ48KuAJS3jQFVwVDfwrOf34vtzHQ8jeJwdG+ModSJ4vbgaRC9r+SbphO1aBsxU1YQsnQ7yt4C5F63VxJQQghxDJQWlvFAj2GUFpT5d+z9Azg3Ix9FqbrGkM/r4717PmXtvI0HTMOLSoiU+pxHoTp9s9ron9X5IuTPLfyT5XlZXNCoAz9vX0OiGsYZHZPJKYWdSj6KomMw6MzO28iD/fpSnuol134bMdYibIY1NApviQEbneolM2GjGVOkhzVZ9UiJLqHMa8HtVXFtTSAuWaeIPZicXpqavSiahdb1XDSM20DXiNTa/hqEEKJOcDuqXrnO5/URGR9BcW5JIDH1X7oObqdnv22dnB25NGwlf0YLUZOK7U4e/3YqqgLdsp1sXLmd1Ibx1OvdhHmlu9nlLkXxasQv9fHlyrl89/29fDZhHhec1YaMnCy2RZu5skUr3C4PHVqkkjl3Laa8MrwpUZSf2Rwd8EWHErshB6/DQ8bGLMr7t8QXG0byphycYTa8oSE0PrNNbX8VQghx0tN8Gh531auLGk0GVIOK6yD9t4rzjSYDXo9/GrW99MBRUaLuqNOpxazyEj5ft4RluZmYVCObrnmMIR3S+T13OUudOVxe/yxiDfXxek0kGmKZsmoDI5b8w+g16zErrcmwd2DEmg30+/sZfs2fxafnXkbTWDOhoV4ySyJwu414ii1oDYsINTmINjuJNZfSLDSPtNBM3HoequplTsEM3D5fbX8dQghx0mvZrflBj5Xkl1a532g2VNq+/OHBhNgsNO/ShKTG9Y5pfKcan64E/RGiwoy1W5m9fhsz123jguGX8tfW0divbcNPmzZi8Ri5sVlbWizyoPqgaUok730wlQm/LWHCjLXcetP5aGPX8cY7f9PvzGdI2ZzLgx2bE70mE294COigG8DRMYWcXk0wd2uJFhuOLzESTAay0uIpi7bhNhoY9fbk2v4qhBDipBcZF0FqekqVxzxub5XJp/+OVvd6fFz64CAMRpVzbz7ruMR5qqhO36w2+md1egRUvdBwzmuYzvK8TC5MawVAckgUAKrbQKq7EWvyV+LTFXJ9eYzaNheLwYwPjQbY+GbnBpRQjRCTRoZrC8OWfU1YRD6hFjNejwnmxOFrVYqqeGlffyUWow+X15/TM6g6Chpen0JWSTQ3LngLn6bxVudbSbbG1NZXIoQQJ7Uty7cHflYU/6imCoGRTwrYIkMpL/K/QQuLsmEKMZO7Mw9FgZ6XdOP2V6+vwajrropVVA7frupRaeLU1L1ZA9KT4jGoCqc19Y9ATAj1Ly7gKnDT0hvHdJ8ZQ5jGmrF/sio2DLVHC6LCreRu3M0egwoGFW9qLBNe/wVl739e5m15KK1ScCaE4NV1tBgbxU4vWsemGOw+fBYFT7QJj6Zj21qKxe7isnq30KxTGi/88jhGU53uFgshxHHh9XjZsXZfrU1ziKnSiPMKRpMBn8+Hrvn7bE07pZG5ORt7iYMQm4XbX7ueO9+4sQYjr5uC7Zv529Z8/6xOj4BSFYUP+17EH4NvwecCl9dLJ0MjQmdbMGf7eHXrTygGJ0aDF6NFwxLuQfE4iYsp5O1/vqdkfDmeAgLzWNslbaF11B5SQ4toGe/htPahmMtVeiZspUloLuEGBx6M7HDEMH9PQ/bkROPWjSRElpDj2k22K4fF+ZsOGbMQQoiqLZm+AqN5318QdR1Cwiyg+P9pDQ/ZewBc9n1v29wOD43bNQyc8/Zto9B1SYgcC5quBv0RokJCZBgTh17Le0POZ8/2AgB6RqZg3aNRkmfn0+9mA+BVFLQwC4Y9xZgnL8HxzWxeunU0pjw7xpwSLEu3B5JPuqKgtmtMcmgkDcstWPe4Cd1cgq6CZjVi9IDBvbexqmBctY3di7dQnFvC4j9WkLMzrza+CiGEOOlNGfN3pRHlOmAJNQMQVS8Sw94aT16PP/lUIbpeFCaLvzans9zFNy/J6vHHQnX6ZrXRPzslXvXcNPFHlmVmcUHLFrx27rmE9vbgsLhx6G6SzE5UNPaUh+N0mImMcmC0+ChsVk6eNZbw9RDaOx/QMRv9f6EJN/rIcJShpy6mQwMP6ZF7UBWdUNWFUfFR4LGhGFWi4stRFY1SN4CZSFMIfeu1rc2vQgghTkqOcidPD34Zj9tb6c2as8xV6Z8AYdE2ygrLAz9f9tBg0tqksuKf1TjLXWxfs4vtazJIa9Og5h9ECAFAYWE5t930CfZyFw89OoiWrZOwL1NBgRyvF7NLQzeCdlZbLGt3YVq/G91gwJVWH4OqkuDxsqe4lOKzGmFdm4up1IcnOoLsnBIUn06IT0fZXYBPLYC2DUDXsSzdjcGiY7C7MOaVV9Q/p8VpTUluklir34cQQpyMFv2xnHfv/gQA1aD660HtN/qpaE9x4Od6jeLZsz0XgMbtG9J9cGc6D2jHxw9/ga7p/DZqGlc8ciFmiwlRd9XpV5Izc1bx/Opvyfbkoys6BXYHRoNK5/ppAIQbIS60nJhQB1EmB6pTxVVswaaqmHUvaYl5hDTXiXbG4LEb2VEWTX6JlR1TLBh1jY4xu2gZswenZsKpGXFoZmLMDqxlPpwuE+FGJ+FGN2qeAX1nOLc2SmfCjvfZWZ5Vy9+MEEKcXMwWE5HxEQAkNa6Hatg3Z33/OgINWqbw+t/PEpMUBUB5sZ2xw8bz7EWvUa9RPAaj/9feZ099U3PB12EVw7yD+QhR4atxc/jwvWk47P7EcVGRnabJsSSE+6fhmT3gSjDhjjHhCVPQom0o8ZEYmqfgU3U0o4JFBfulLSnvmkzB5a1xtE7CUlACxWUoWXmQW4ReUILi8WKethzL1KWYtmZhXZeNeUdhIJb41DjS2jbk1Rvex+08eJFcIYQQB0pIjcVgMoACqenJlY4p+/XVzri8O8MnPhxY8W7Hml28e/enfDR0HK17pAOQn1XIb6Om1VzwdVR1+ma10T+r0yOgnl89HpfmwRFjIkSJ49l+fQF4rs2V7HEXEWcJ5ZaFj6GqXjRVITq1hChVQzU6aBOVi6pATmQJOa4I9GIzRgOUY6W0TQRhPjteXcWkaDg0M7uc0USbHZhUHyVaGGszk6gfVQiKji9GwxhaiMP1Lj5fKM8s387H3d7BYpDsrhBCBMNgNGAvdQCwY+2uSscCtZ9U2LluN2/dMRpHqXPvwX3tdm/MommnxmxYuJnU5pU7SeLIaBBUAUvtsC3EqWLtmt2MHTPTv+HTaJQWz2VXno6qwi83XUOpx8OWhVt58LcZoICh3IOh3Iu3Q1M0RUHf+xea3Ys2o9niIaoeimLAk56I6691mDKLAvdy92kLYVbU7ELUzZlobdKgsBR17Q4UwJcSx+5WDclavA3jiq1sXbmDj5a9VuPfiRBCnKxMFiO+vavXHdA/8+3rhM2ZtCAwOh1A0/b1DHRNIyzKhr3ETkozGY16tILtm1W0rWl1OgHVOaYJ8/LW49FUPKFl/JO7iREzZjEjYwvxSaGcmdqYl1s/w+2LX8Vs8uHzqth1DZsOPl1FVTRcXv9X5HQbKXeYSQgrISZMpUwzsaI4hYSQMjy6kSK3hR0lMdT3NGVuhgvdqDE/syGxoXYK3KFcnbiItiGZ+HSFKZmt+G77Eq5r0q2WvyEhhDg5ZG7Owl7iOHSjvb9FNyzcHNil6zpdB3ZkzZx1JDRM4LW/niF7aw6NZPqdELUiJSWa+IQI8nJLQNPJWLubtfM28OoN75FvNhPZvQXXXtWDe+o35Ktv52CIT8DdKBbV5cWgGfyF3HQd3F6ipmwhdE0+ztObonp8GArKK91L0XV0QFUV4ru3JFsDbCGomzPB7UFLjgGjAS05Fn3FVras2M621Ttleq4QQgTp+9d/C6qd5tVY+ufKwLau6XQ9tyMrZ62lfnoKwyc9iqPUKasTnwLqdALqlfY3sau8kH5/fICiwB871rF8exGaTSfbWcq3m1awtnANaqg/O+v1qJQ5LeiqwtrCRMryQik1GDEaNXxGA4mOWBLjdpMYUkrG7nTWlYXiCLMSF+ZCVX2EGHz8tcBLWKqHjo224lMMLMtJwmqCXFcYACVeKxllcTSNSKjNr0YIIU4qoZGhR3zu1lU7sZc62b56J39/M5dBt/U/hpGd2jRUtCCGbwfTRpwaIqNC+eLbu5n85Ww+GP4DWkExE175iZydebjPaIsjr5QxP86jYP0O9MR4nFEmPGEqaAbCJ6/B5Pai+3SUcv8oR8vOIiILVuMs829HxoZTnF+KwWRAX7ABLSYcJaeI3PBQtNOb4Yg1YmqTiG1pBoZNmfhUBTW7EAWIjI8gJjGq9r4cIYQ4ySQ1ObK/04aEWlg+YzUep4c/Pv+Hu968gShJPh0TwfbNKtrWtDrdI1QUhdSwGJ7veB4pSjTLl+Zj9qh0j0uhgc1Ggh7G1mw7bp+Kx6dSUGzFqRlxuo0Ul4Qxott1hBpD0FHom7iBM1OXYdQ1dB2M1hB0g8qWsmi2loQBCkXF/toFibF5xIWVU89WwhunnUFkeTLjt5zG48uvYGLuw0RaovDpMiFBCCGCZTIbK9USAP8yv2cO6XHQc+JTYwHI35Uf2NeghUy9O5Z8uhr0R4gKJpOBwdf35qKLO2E1wKKpy4hvEEebehHEx4ex2+SirHU9XAlmlL1TbBUdqJ9AvZgw7njucgC88WGUDGyNq186ukFBURW8Xi8APo8PxeXBkFWA4tNQi8pwaQ58NhPOzqm8+vezKHYnqkcnunkqaR0aEV0vEpdD6kAJIUSwGrXeN2K0os5mTFIUHc5qc9Bz4hvE4bS7AsXKzVYTBlOdHhdTo6rTN6uN/tkp8W96SOPOfPHHavB6sFpLuaHzz+i4WLrhDsb96yLHq/qX+g3X0DUoLA2lX73mvL3yb/qkLCHZVkx9SxEAuQUpzCtKw+F1oKgKCeYSetbbRrHTyg5fNM+fPxmPT2W+px5u3ciqwj2kxljYkauwujSOLZq/APlPO5fTK6FpLX4rQghx8jCYjETGRlCUU8yQxy+mUZtU5v+6mKiEKKLqRVKSV4rmq5zYz83Yl3gymg0M/eQu2vZuVdOhCyGqYDAauOedm/n1I3/B2dKCUop+XkD9Fil4LmhFRm4xRrsPS7GGwaGh+kANC6XzaWmMe2YCnvhw7ANa4Qs1kA/YGsZg2ZpPebHDX/otPBTKHSiajm4LwdssBXO+E1+cC9POAlYs3UxY24aURIVTqEFxRiFKfjGLpy7nPBklKYQQQQmLCkVVFXRd54Vfn2DN3A3kZuSiaxBis+ByuPfV6lQAHXJ35gXOj06M4rW/niUk1FI7DyBq3CmRgAK4tENrXvlrNh0buHBr/v/oL+1qYtpsK3kbFAyKjrWNSqFajtGgM6NgAyGqi37hxYBOiTeEUNVNtisGRdHRfWBRPDQML8Ri8JFgK2Nwgw2cH+uvPbJiRyJry+PIcsznlpTlvNJiN29v706R4VwK3OVc0/i0Wvw2hBDi5KFpGtPHzeCyoeeTszMPn9fHaze+j8+7L+HU65LTmPPjwsB2xVLAZquJkb8/RVq7hoRHh9VG+HWahoJGMEXIgyuGKU49Hfq2Zsn0lSQ2SmD76gy2rdzBM69fyzMPfokxIhqjQcHn8uLx+WDVFn6fswpnuxScnRr4C9xqOorHhzG3LHBNrVVDtNQElIISjIs24GuSjJ4YgwqEr8jBFWfmtaytKH0SMNp14rY46NCpEQZdo8dFXWvvyxBCiJNISUEpy/5ezS0vX0PWlj38/c1s/vxyVuB4WJSNiNhwcvYmnIxGA969BcvrN0/iqfEP0qBFCuYQc63EX1cF2zeraFvT6mwCKruolFCLiQhrCABJ1nAe6dWTq7q1ZUd5JJuKd/HI8jk0GaQRO78FjRs2YbJ3LbqmgMufni13WFmY2ZB6YSVszo0lJcxEiclDvNVOGB4iw5y4dSOFbivZpRG4neGUJazFpxtICs2jm8XO2vIkzojIwKL6ODd+IyN3N2NY20voGCMFLoUQIhgzJszj3Xs+PWSbHheextyfFoEOlz9yARPf/BWADme1pV2f1jUR5ikp2OHbMgVPVMjILCQxPgKTyYDb6abLOR0486qedB7Qnk8f/5oNNjOPffIX0TGhxNrLadYymVlfzarUYfXG+ZPJigrWuduIySrGXupCURV0TUcP9ff99KgwdFsIEV4PRbqOyevDUz8eTz0DqAo6oFkUyr12inOcPPPDQ0TFR9b8lyKEECehTx/7milj/jroca/HS69LTufHtydjsZq5dOj5fDPiRwAuf/hCmnZIq6lQTynVmVonU/COkTnrtnPvmJ+IT3Uw8Owd2Ejk/W/C0XUVXYXVxS1YpxppkbQIgE6DdN5dsgLF7AXNSAdrKqsKd4EJli9IJ9pWTr++y1EUcDuiKHKHYrL4awx4MbC2OJHM3clMvehOVHUYv2S8jdUyh1TcODQLo7d3okfMLiYUtsRJGR9u/o0zEtrW5lckhBBBGfv0eNYt3MQ979xMgxYptRJDXEoMiuIf3v1fRrOByLgIRj/6ZWCI95bl2wOjoyJjwms0ViHEwX301Sy+nLSQhMgQrDPWkdo0kaV/rkQ1qNz77s2U6zrbiv2rXRabjZzVNImpn/8TOL9hv5YsSlIw2DUMPlB0BQUCK2RW/Bmg7NiDHhsBqkpCt3TGTX6M9Yu38vxNH5KbWg/rLjfKrlK8jeJQdRWLL4Ttazbx/eu/MvSTO2v8exFCiOqwlzp46/aPUA0qD3x8B1ZbSK3EkdAg7qDHbFGhGE1Gpo2bAYDL4WblzDWB44lp8cc7PHGCqpMJqC178nGEa0Q2z6DEl0UJWURFdaOoKITft21khT0LPcxLXGQo8aFeGoS0wWybDUCz8Gj6xzdn+bYdKIAS4mX/qiKlLgt7ysPQNRXVpxPijiJhfRxPnt+XlLBIrp71KYXeQs5MMOFDxafApNymfL6zI+EhLsIjHJwRd/CibEIIcaLI3ZXP1yMmAvDogOd4a+YLtbI8brszWvHaX8/w/Zu/EV8/hmljZ+B2egixWQiNsJKfWVip/ZJpK/b9/OdKnhw0ggvvGcjp53Wq6dDrPB8qviDWMwmmjaj7tuzIxWdRyPS6MTaKxr7IX7bAFhnKB/d/Rnmvlvhiw3BHQFK+G6/XFzj3wnvOZV3rCFzZuwCInpaJwadg2paHbgsBh4uSsxpDqIWwPzeTYIC4pkk8+ej5OMtdPN7/OdxOD8bNWYCORQc9uRS9URLK7lxUg0q3wfJnhBDixDd30kJmTJgHQN7uAkZOHYbZYqrxOK59+jIiYsNY8PtSYpNjmPLpXyiKgsVmwWoLIW93QaX26xZuCvz82ZPf8EvKVO54/YZa6VvWZcH2zSra1rQ62SO8skd7whta2FQQT16ZjSahPXny4ou59Nx29G7SCMUHoWYPJZqVLWXhhJojaB5holfyVrokZPPGpLlgV0BT8CR5ybNamLOlKUvzUnB4UnGWmdHdCtmFkSSFN+C7YbdgN2fz9N8PYla2oxoVZhU0Y11ZEqEGD/0bbyatXh6q2YfF6OPfguU4fbLKihDixDbxrV8DP+fvLmTcsxNqLZb2fdvw4i+PM+C6PpgsJuqnJ+Msd1GQVURkfAT105MA0FWwtwyHKH89gYKsQhZNWc7HD42rtdjrMk1Xgv4IcdsNvSns7WPPmW6Ke4Vx4/NDuOnFq7j4f+fRrk9rFIcbZ6xCeYqBHb0T6HfPAIwmA4qisKnAwYopW1BdGiHbirEt2oF10Ta0js3x9WhDgwfOxt6+HvamUTjOTOeSXs348O3r+Orxr7ir06P49i5SoOi6f0U9QMnMQ523CmVHNppPC/yFTgghTlQuh4spY/4MbK+cuZaFvy+ttXguuPtcRvz2JI1ap2I0G2jdoznOMid5uwuISYomOjEKAN1kxB0RRkV3YMOiLcz9aRHfv/5LrcVeV1Wnb1Yb/bM6OQIqxGykBBcup41fV3dA8SYx3TkZlwHObdqUe/s1Zmf5HrbYC9DRiTHauaGJyqwCN6VsICymDWUbbbhbOf3V+kM0ij1WHC4DoaZCWqcWoShgNmncktCa1+4aTfGQf4hPzsXqMbOnoCmgklNqIzW0CIBoix2nxwpAjrMQu9dJiEEKrgkhTkzv3DWa3z6eXmnf8hlrDtK65sz/bQnlxXbKi+2YLEZ8Xo3i3BJiEqNQVIWcqxtQfGYCoXkeUh5bjjUsBEeZk54XycIPx4MW5Fs2rW6+7xLVZA/x4rL5E0GlaQqzl2xk5YdzALjphauwLt3KrrhI5lGK1WTCbDAQkxRNzs481i7bjiUhhqQ5DpR5a1F03b/anc2/ctKa3bnoDUJA14mODKde/9Y88ur3LPl5IYZS5yHjsljNuBxutq3aeTwfXwghjtrt7R4mc0t2pX0Lfl9Kr4tPr6WI/GZMmIvX7WP13A0YzUZ8Xh8FWYV0PbcDi6Yux927FXq4ldDsQrQFGwmPCcNZ7uI0GZ1+zAXbN6toW9PqZAIKoF9EY6bmb0JBYenb/6Bf3IioJhAeuYtfs7YCcHPj8+geFYZadg0ROFmndmBteRKmRC8XxrRgl6mQ5e5smoTGszo3mxiLBmY3Ov68lGbQeGrRzxQ1MtLDaSUeKPeZMeteNufHEmZzs60sBpPXh2NDc3694U5+yPiHZuGpxFgiavPrEUKIg9qwaHOluisV7CX2WoimsvPvGMBvH02jtLAcj8sb2O/z+jhzSE++tmUB4LUZALhl5DUMvutsVFUSIELUthZhcTTZY2RLnJcIr5FlX8zHAOjhoaxcsJElvy2BSfD23GcoWpfN/84fib1XE4zJYYQuziDCauKs8zqwKDubkrxSIpJj2FlajmK1gBrqv4kG9qnLeNyi41PA0K8FET8tD8Sgqwpa28boJhOGVVvoeW57rh9+JdPGzmDA9X1q5XsRQohgTHz7twOST0BglbnadO2wy3jq/JEAeN1eFNU/siapcT1ik6PZbfanHTSTgRCbhZFTh9GsU5r0z05BdTIB5fJ4mf/nNiIVA5E+MDdoSIsp6zjn21xQfZQUtyXLGUnv+HYkGneRWeZEUaAgO5wt7njKcqy4PU62/pZN/dhQVrfPxhem4fNopEfk4PQZ2ZAXT5HLRozNhDtUZ0FZKrnZoTSIKCQlogTybWTrBvLcYbjtJjp7mhNlDuPWJoNr++sRQohKvB4vs77/l8btG9GodSpv3v4RXrf3gHaOUid5mQXEJcfUQpR+m5dvx2nfN4U5sXECnQe0Z+e63WxZtp2EnVnE5PpQF+cAsGLGai6859zaCrfO03QVLYgVVIJpI+q+FX+vxvfyMkIvb0RUUgLuTg2I2OXE2TCJFR4jxjArac0TObNjOt//vRFXi3r4okPxRYdiXZqBrbCY2Z9Op3BPMfUaxZPh1dESonCFKfiMCrZdXqzztmAqcODz6jhMCqrZgm41ozj8f26ocRF446NBAV+z+nTs144m7Rtx11s31u6XI4QQ/1GQXcjiP1Zw+qBOKIrCR0P95QR0sxEMBhSnC3TI3LKnliP1j5JXVRVN849y7XnxaeiazrbVO/F6fZjnriOxe3P2LNiI0+Njw8LNpHdpUstR103B9s0q2ta0OpmAspiMtEiJYkVYFiGJuVi7QJk7DVR/xrgdzVmyUuP63Im0didwa4dn+Hf9KvZs6UnHtDCWaVn8Y98NsaB63OgG//9IaZEFxFj8K62syUlELzby1tlDuPufSfhUB/lOG/VspRgVnZ1OK0bFhy3CQ8P4As5sl4eu6yiK1MEQQpxYxj37HeNfnoTFasYabsVpr3q6SmiElbAoWw1HV9nk0dPxuDyB7dMGdmTyx9MDq961Ob0ZT7/9EKtmr2P+b4vRfDof3P8Zd7x+PUZTnfyVV6t8KPg4/O+1YNqIui+9axOcF6RhbxuNHS+hPerhLPYStlnD4/XRsU8rNmYWccM9n9GyYyqDerdlTkkxHZsmk3NfKDudTry/rsEI7NmeixobjsucgjfMP+JR03yYd+QTHhPG8/ddxBMvTETfUwJON7rNgqdtGordie7xoISY0VPiSG6WVLtfihBCHMSzF73K+oWbSWgYj7PMgcFkwKuo6F1agkGFNVtRCkqIS46u7VD57eNpgeQTQGLDeH5487fA9qBb+3HXWzcw4ZWfyd6Ww5I/V6AoMPiuc2oj3Dot2L5ZRduaVidfSa7bko293Xqu7T+HPm020KnbZmJaFLCkoAFzl7VkzDSdQls5uz3FTHdvYvgHKvde/CEP39KXv9Xl5KdmYze7cKYYGHbz2XQtSaZ3ZCxhEU58ukK5x0Sj6ELaNM3gkVVfEB0NTU1plJZamb22KdPXt6BQC8WZaSBcddAqLJtNpePZWDqztr8aIYQ4gMHg/1XgcropyinGWeaqsl1616aEhFpqMrSAnIw83E43sUkxgUT+WVf35s8vZwWSTwBOh4v4+rGcdVUvOvVrx8zv5vHTe1NY+PuyWolbCLHPrMVbcKgW0EB1gicEilNMZHdR8W3cyrKpyyiOjWabo4zf/12PLymaqW/fRcsuqcwNs7MrSqOsbSJpbRtw4wtXkVYvkqYl5aDroOsY95TiOKc9eWkJvHz287TKzCN6YwaKDt5mSWjxEWgNEiCnAE3RUQpKeGbwy+RlFhw+eCGEqGGq0Z9cz9mRS0l+GT6PD0xGMBpAUSDEgqIodBvUuVbi8/l8ZG3bg73UTmKjBACMZiNn39S3UvIJILpeFFablRufHwLAvJ8W8e49n1J+ApR3EDWrziWgyu0u7n52ApEheVQMNtI0BYvNQ5FuI8cdTpTPQpIehUFTCMkw0CjFP51kQ/EedEVHMYDJCld2asu5PVoy7n9Xc1X71rgxscsRTYknhLPi1tMvbj1NIrfSJnkhhC3E4TPjwYjmU1FLvTgiTGzKi8enKYCC1RBZe1+MEEIcRPppTbGGh4B+6HbL/lrF9C9rPpH+60fTuKbhXdze/iGmjPkLXdc596YzWTlzDfYSR6W25cV2dm/214Fq1SOdiNhwYpKiadoprcbjPhVUDPMO5lMdo0aNol27dkRERBAREUH37t2ZMmXKIc+ZOXMmnTt3JiQkhMaNG/PRRx8dzaOJY2z+8u28PPYfFKuNiC0KEZtB0QAVfOEmHDEqaS1TiPR6MGj+DlyjvdN9l2/fDYBugMisUq589CKueeoSXv9nOJ2aJBExaQWRE5dhLnCh20LwNYyn3OFm05JtlBfZcafFUd4+CVeUiiPESdGZyThiDejbMwmNsGKxyqIwQogTT+f+bQ+YPaOUO1DWbUfZuhuy/DNsPn3i6yprQx1vL139Dtc3uZdh578cWMThpheHMH3cgX3FHWsyKC0sA6DruR1RDSrt+7bGGhZSozGfCqrTN5MpeEdJ03W+37ICPRG2/5yG5UqFPLeRLHckoSYvVpeP8MxkzohJJjwqlq7tGvLIjilsdhezK6eI+RnZuO0mokwh9PA2xO0tYX1uFsN+n8GKzGzSmqQSEreHqJAyok3+v/QkhxRTTgix1nJ/EIoCTgNGoxGP0UWuI4zZu8/io96XkmRtWovfjhBCHEjTNJ656JXDJp8qTP9iJgOuq9lCvZuW+BeOyNyyB8WgoKDQ+7LuLP9ndaCNwWTAagshZ0ced3d+jPfmv0RCw3i+y/4ERVGkyOVx4iO44du+al63fv36vPzyyzRt6v+9OW7cOC688EKWLVtG69atD2i/bds2zjvvPG677Ta++uor5s6dy9133018fDyXXnppNe8ujrXCcjvTtm7GZwZjmU55UwWf24c114grFlSPRpu4evTt0wbVYCDutEaMmDybWVu2cpW3M5kj/iSsvpkWYZEkRUWx9t8NNO7YkKG9nqGsqByzQUXzabAtBy3ShiG/FGX/RQoi/asQ+ywK5Y3D/DsVnd6XnMaTwy4nPDqsNr4WIYQ4qIVTlvHl8z9UeUzJLTxg37K/VpHcJPF4h1VJRf9sy4rtKIpCeIyNlt2ao6oqPs3/mz/EZsFgNDD3p4UU5Rbz5Nf303dID864vBsms6lG4z1VBNs3q2hb0+pUAurOPyYyo3wddINB0S2ZkqthUH0YDDrlHgvxc+NwfryY77oVocWG8fmSZeRYXaDqfDd7BaXRbjxOEyXlMM+0FsXkZPqsJdgzYsCgsHWzDbY1Jjssloa9CwgxmHF80pDCxCyK4hoRGqkSZXaQWWIjIcFFsddLE1saY864jNiQ2q2bIoQQVVFVNejkE0CDlvWPXzAHcfnDg7GX2Fkxcw1FOSUkN0vktIEdeWv2C4x58hv++no2Po+PlGaJbFi0BXupg1taP0hCgzhGr3gdW6T8+XuyGTy48oIdI0aMYNSoUcyfP7/KBNRHH31EgwYNePvttwFo2bIlixcv5vXXX5cE1AngvHfHUeB1YmlholFcFKsdeYARj1PDlgEtnSa2/72WsX+tAUDr34yCNvEU7Mpm3a4cPNmlRK8pJUeBPTos/3s1v42ejrZ3+q3m8//TVOrA8M9q6jdPJifUjNvuJjIhEvOOfIrRweXBfVkTPCpc2L01zw4ZgEGS00KIE5BqqF5tnpikmq8Ddftr1zL9i1nM+3kRAL0v7UbbXi15b/5LvHfPp6xftBmXw01qegrlxXY2LNzMNY3upufFpzF84iM1Hq84MdSZBFS5x83S3EwIBRTonNqAP4rXEWGxE2ezk1seRlxqBFsviMLRAlwxHpo4w6HMhQmVMzs15aakGE5PTGX5pLXMidmKAugGnciv1uFsGoWrcxIek0J8vWgm7u6EApT0smE1JmN36/RJW0NMmJ2sgig0KygovNDmFkk+CSFOWHN/Whh0W1tkKPXTk/B5fRj21iU43nRd55kLX2HXxiy6nd+ZvN0FXPrg+QDEpcTy2Lj72LpiB1tX7mDPjtxK5+bszGPi25O5/tkraiTWU1F1V8ErKSmptN9isWCxHLqumM/n4/vvv6e8vJzu3btX2ebff//l7LPPrrTvnHPOYcyYMXg8HkwmectaW7av2UlJmQMtDFz4OLtFM1YvzgNFB1XFHQ0JViNb7ozHbo7C67bQcZuPwpwyYq0hNImP4fW/n2X532v48Z3JZG/3r3Cp7Vf7DQVURSE82kZxbimFOUW47W5ik6PJz/SPFLAW+uuMmN8sICwliufWPSALwwghTlgLJi8Num1a2wbU9B9nuzZlMfKad/G4vPS4sCuFe4q44G7/qsPNOjXmhV8f57KEWwACxcm9Hv94myXTVrBk+go6D2hfs0GfIk70VfDqzGufXzatx6EUE28rxap7eeb3f0jYE0+KrYwws4d61nLW5m/FcXEMnuYqvnCN4gQ3n191Cbf36sqVE8Zz7bdfcWXztmx6cQqRj60j8m8D8R/YScr3Efv7dm4qiuD3O6/nzf5D6B3WAt88Nx4Vyg0udKsbi8k/3Num7htOoErnRghxAivIOnAY98GUF9v54L7PuKPDw8cxoso0n0bebn+BYFtUKKOWvEr/a8+o1Oaed2+mzxXdAx2f/X353Pesmr2uRmI9Ffl0NegPQGpqKpGRkYHPyJEjD3rtVatWERYWhsVi4c4772TSpEm0atWqyrbZ2dnUq1ev0r569erh9XrJy8s7dg8squ3rET9inbsdb5iOO0zjs7/nYvKAuURFNyigKsyuvx33+VEofVRcDcJxX9mSrx+6mg5b7Vwcfh3fjPyJZl0aB5JPkXHhhEXZMIf4E4v/++A2vt4xivs/uoPmXRpTXuRPNlUknyrYokIxlHuwlngQQogTWX6Q/TNFVdi2aidPX/AKHz009vgGtZ/i3BLcTg+6rtP9gq68O+8lGrdrGDgeGRfB/z64lbOu7kXrHumVznWWu3jmwlfweWtjAljdV52+mU9qQB25rokpRMeUYzL7iIiwUxwZynalGGVPBIkpxdiWR9C4fQ7lkVbszjD2lIaSn+tkomkNm3Zl4Ut1sd6Qy8NTJ9J3SA9mfDuXu5uewfmvDcBR5mDH2l0079KEd5fN4+01szGZvbTvW0aCtovFzjSKnKEs/KcFafUcDG56Pm3TIwk1hpIaWvPTVYQQIljn3dYfe4mDcc99h8fpwRJqxmV3H/KcHWt31dgoKIPRwCvTnmbZ36s5/44BVbZpd0Yr2p3RCrfLw6+j/qBwT3HgWIjNQnxq7HGPUwQnIyODiIiIwPahRj+lp6ezfPlyioqKmDhxIjfccAMzZ848aBLqv6NZdF2vcr+oWa17t+T7f/aOTjT7KG7pBR2M2yzYygyELcjE47HjamQmxB1CmQbLd2SxvGVpoM7bjPFzaN+3JWltG5CfWcjIqcNo1qkxeZkFlBeV07BVKv/r8STr5m86aByR8REMG/8gRTnFtDi9mfx3IYQ4of3vg1sxmQz8M2Ee6Pt+p/2Xru3bv2buhpoKj9Y90nniq/9RWljOgOvPqLLN4LvOYfBd57BlxXamjZtRKdbUFik1NppenFjqTAJKc2i41thQ2pZgd5kB/9IqV6Vfwm1tT2NM5ONk6plkO8Mp2GajCU1YYt9Nj8YN6OgL4TlHFrpVxYLKo5/fy6Of3xu4tjXMSovTmgHwz85toED7lF10jPGvyuLak80/21vTt2lrRlx4DkZDnRlYJoSo4wxGA1c+dhGN2jVg2KCRh00+AaSmJ/P3N3MYcP3xKUa+bfVOXrn+PRq2qs+jY++lVfd0WnVPP+x5RTnFlZJPTTum8dykR0hoEH9c4hSgo6AFUehS39umYlW7YJjN5kAR8i5durBo0SLeeecdPv744wPaJiYmkp1deQWgnJwcjEYjsbGSgKxNpa3i8W2KIyRbxxcFvkj/6PDxtwyhmSWKIam345znJuT7Qnqeezp/tw7BqXrp2DCFlt2aBZJKkbERjF7xRqVrxyXHELd3pbytK3ZUOqaFhYCioJY6ePjzezjnhr418bhCCHFMRMVH8sTXDxCTHMMPb/x62PZGkwFNh22rdpLWtsFxienvb2bz1Qs/cN5t/bls6GDOurp3UOdtWb69UvJp0B0DuOvNG45LjCL4vllF25pWZzIlseGhKEWhFHtC8BpUrKFueqjJ3Nb2NBRFwWny/6XEmu9k63YjSqLCHw/cRHsllEsHdef9hH48EXkar513+SHv81Kvs2loisFiVCjzWtB02J4dj1qmEzVntySfhBAnnQmv/sywQQefCrU/1aCQsSGTV296/6Bv447Wn1/MZMvy7fz9zRwyNmQGfZ6z3EVk/L7kxuZl2xh57bvHI0SxV00O8dZ1HZfLVeWx7t27M3369Er7pk2bRpcuXaT+Uy1rlOAvjGtwKoTkGrhk2xreqteYjvVSsJfYcTs8KDoYsj1smLKKSzbBn3feiFrk5dW/hnPTiKt4/Mv76H1pt0Pe5443ridq7///WmQorrPa4TqrLb7YcEJlmW8hxEnoyfNG8MObh08+gb++0sZFm3ly0EvHLZ4f3vqNjA2ZTHj152qdFxEbVmk14skfT2f8yz8d4+hEBZmCV0NiI2x8NfQ6rl34Jj5dxe2ysOW9+axs2In2fVpzeYPHmLvhd+YtdZKTqpGzezsjP/qOzU9Op2Gr+ny6+q2g7tM6vh4zh9zB9vIdLM1fxbApK7GHqERsLiZ3c+lxfkohhDj25v2y6LBtDEYVn1fDYDSi+Tyoqso/4+dy1lW9jnk8Z13Tm4VTl9GgZX1S05ODOkfTNO7u8hgue+UExfY1Gcc8PrGPpito+uHfngXTZn9PPvkkAwcOJDU1ldLSUsaPH8+MGTOYOnUqAE888QS7d+/miy++AODOO+/k/fffZ+jQodx22238+++/jBkzhm+//bb6DyWOqd4t07ipT2c+XbiEe7ot4o6uS9FZh66dT0KDeIb/+AgzJsxl59rdbFmxnamj/2SjU2HL1lwuvKQL9z1xSVD3GXznOQy+8xxm/7iAfxdv4Zf1e5PXZiPbVu08bAJLCCFOJC6Hi8V/rKi0UnFFX2x/iqr4RxcpgA5ej5cNizaT3rXpMY/p4vvO48vnv2fQ7VWXRKjK2vkbePqCVw7Yv3HxlmMZmthPsH2zirY1rU4N18nxbaJ13B5aRe9BzTJj71CPUUPHMqT+7RSs8HJJ+3t4eug9dEhIollULOq2MrJvbMnqRiZ8vuoVQWtka8g5SWdjD1VBhcS2sdz/0e3H6cmEEOL4ue3la+g2uPMh21R0eDwuf/Fezacx8pp3yNySfajTjkiT9o34ZOWbPD1haND1Af76enYg+WQJtRAe4199tKywnDduHXXMYxTH1549e7juuutIT0+nX79+LFiwgKlTpzJggL/Tm5WVxc6dOwPt09LS+P3335kxYwYdOnTghRde4N133+XSSy+trUcQ+8ko9I9CVxT/36TcTje3tRvK3V0fo23vljz59QPc/9Ht1GsYT7fzO5OdVQTA2qXbqn2v3pecTu/uzTEt2oxpyRZOb9+QS4eef8yeRQghaoLFauG+92+hdc99JQj+m3yC/WpA7f1H0Z5iXrjizeMS04Dr+/DF5ve58tELgz7n82HjAz9HJ0ZhsflrPy6aupx5vyw+5jGKE1+dGQEFsCHX/6bbYNAISyqjpzmdVWN+AmDupAW0PL0ZkZYQfrrwWgCeME3BuX49zuawp6yc5Mjg6lJUsJnMPNulP3Ozt/Po4D40jJI6I0KIk0+bXi1p06sl835dzLcv/cCGRVsDHRqD2YDP7U/Qe9s2wJ0cjXnVToyZhYSEhfDtyEnc/faNWMOsRx2H1+Nl2riZ1G+eRLszqi40fTBpbVIDb/88bk+lkVB/fj2Lhz6966jjEwfyoeIL4l1WMG32N2bMmEMeHzt27AH7+vTpw9KlwS9bLWrOxt25aCq8u6orW7fa6FDckh1rFwIFbFi0hS5nt6fl6c34atuHAFzT7mHKS1yU7tlzRPfrck57Ljq/Ey6Hm3vfu4XQ8KP/80kIIWpaRRHvccMnMO/nxWxdsT1wzGIz4yr31+1UFKVSWQSfz8eEV3+uVqLoUAqyC5n1/XxOH9SJpMb1Dn/Cftr0asHyv/0LShRmFwX267rO+Fcm0eOCLsckRrFPsH2zirY1rU6NgBrS9ELySiPIskegRHu497pzueDuc2jdswUDbuwLQEZpMePWLiXHXsb5HVoRbrHQo1ED4sNsR3TPm1p24dMzL6O5JJ+EECe5HoO70PGsdpUKRVYknwBczRLRI6x4miYC4CxzMvWzv/nj8xnH5P7fvfYLb93+EY/2f57cXfnVOrdpx8aM2/QeQz+5E+0/bwi9Lm+1ryeCUzHMO5iPOHU9cE5PMOh4dQPTyzsy8I7bOW1QJ7pd14t2ffzJ5tVz1zNlzF94PV4GXt4NS04+/a/scUT3M5lN3D/qdh4de68kn4QQJ70bhl9Jpbl4EEg+wYEr5OXtKuDTx79ix9pjU4bg5eve44P7P+PpC16u9rk3DL+Sd+aN4NIHBx1wLHtbzrEIT/xHdfpmMgXvKNksVm5qfBWqO54B0afROC6WlGZJrJm7npeveRdd17l12o88M+8v7p8xmZ6NGrL0wbsZN+RSTAZZBlIIIQbe1g9bZCiq6cBfD6YNmSilDkyb/dPuzCEmrGEhtOze/JjcOyzK/yLAYjVjslR/gG5y40TOuKwbFqu50v7QcCtRCdUb4SqEOHYGdEnn0uR0Er0hPHnmGUQnRGIf2IrJIRrv/TyPvMwCHjlrOG/e9hETXv2Za5++jMn2b7jx+SG1HboQQpwQLn3gfIwmA0bT4f/OqhpU6jdPIj417pjcOywqFABb1JEN2GjVrTlnXH7gC4XU5sHV+RR1S52aggdwSaNuRMx188Mbv/Lt5bBjnT/zu3XlDn56fwrmev4sX7jJfKjLCCHEKSmpUT1+KhyH1+Plob7PsvbfjYFj5jW7MK/Z5d9Q4PKHLuCqJy/GYrUck3tfcPc5NGxdn4QGcUTFRx7RNWyRNu774FZev/nDwL7z7+iPySwroR0PGipaEO+ygmkj6rbhN53LmAlzmfLDChqGRLJ2h3963bKNu0j1mTCFhuAtLscWEVrLkQohxInn7Bv6cvYNfcnatof7ezxF4Z7iKtuZzEae/fERupzTHsMxGmDx2Bf3MfCWfrQ6iheOrbo157TzOrLw92WBfTe/dPWxCE/8R7B9s4q2Na3O9Qg/efRLXrnuPTZvyOTz4RO45aVruPCec0nv2pQP7/+cghkbCI3QaJN0bDLCQghRFxlNRt6ZO4Krn7yEEFsVCSYd/pkwlzVzN/Dxw1+QszP3iO+1bsEmzrNexQD1csYNn0BSWvXqC+xv6Z8rCY2w0rF/28C+qcdoiqA4kE9Xgv6IU5eu69z10Jd89eMCNm7L4atJC3jplvO4/Ix2FC7L4aPRMzGc1RHzoG407F29+m9CCHEqSUqrx9iN79Hr4tP8tS//w+P28u/Pi/h99J98+fz3uPcuHnMkJrz6E2cbruD8sGvZuGQrtsgjGwHl8/n46+vZDL7zbKIT971g/PGdyUccmzi46vTNaqN/VucSUCvnrMXXsB7e3u3Qe7Rm4ZRlbFu9E2t4CABF7UJxaz6mZKyv5UiFEOLEd9OLV3HmkF5VHjOYVJ6+4GV+ePNXPnpo3BFdX9d13r17NB6XF4BVM9dRXlx+RNfasGgzj539As9f9gaDbhvAZUMHA5DWtsERXU8IcWx4vD42b89BR0dToTirhJlzNpC7s4hQo390YnGJA4fTw9y5Gw9zNSGEOLWFhlt5+vuHqiwIriiQtT2Hd+/5lC+Gf8fUMX8f0T1K8kv58vkf/PWldPjlg6lHHO/3r//Ky9e9y/OXvcEHi16haac0ANLaSP/sVFSnpuC5HC7KCsrRw/3Dtz0mIx8//hWOwnIMRpUbnx+CqVdDfs7ZwM3pp9VytEIIcXK4f9RtnHvzmRjNRn77eDpTPv0LgIx1mcSlxJC3u4C0Ng2P6No71u5i87Ltlfatnb+Jrud0qPa1jGYjigK67q9Pdcfr1zPo9v4kNJRFIo6XYAtYShHyU9t2ewEF1/twOX1Ezgghq6iEDdOW47UpRCSG8Njtg9m+NZdt23K5+CJZEUkIIQ5HVVU+WPgyuzZmUVpQxtcv/sDafzei67B0+kqsYSG4nR4atEw5ouv//c2cSisKlxSUUVZUHqjXWR3K3i6AalT9I+znvEhORj71myUdUWzi0KpTXLw2+md1KgGVt7uAXRuzMFhMaB4vxR0iyL2tPWFzdmF2KMzcksnHrS/hijbSuRFCiGAZjAZadU8H4P5RjZj+5Uy8e0csXXz/efS48LQj6kTs2ZHLl89/d8Dywa/f/CFpbVMZcF1f+l3TO+jrrZu/CV33Tx9s2tH/dq2+FLg8rnRdRdMPP5haD6KNqLuW5GXgVLxgBUeChtdqRNNBMWrkNS1kpTmbR27rX9thCiHESSU8OoyWpzcDICohgnu6Pg6Aoiq88OvjpDRNJC4lttrXXf7Pav76elalfV6Pl/t7PEVqy2SueeoymnVqHPT1Ni7eAkB8/ViiE/xT8CT5dPwE2zeraFvT6lSPMKVpEkmNE1BcHrT8XEpbR+AJh7JeyeSdl8y/MR7mL9ta22EKIcRJy2Aw0LpHemD7k0e/4qd3fz+ia71912hmfT//gOWDC7IKWTJtJa/d9AE+ny/o63n21jnQdR2fN/jzhBDH17nJLTHuMWHYbcLnUilLUrAnga+VE1+qh3H5c/HpWm2HKYQQJ63mnZtgsvinNOuazsNnDmfd/E1HdK1hg19m/cLNgW1FVUCHnet3M3fSIkY/+mW1ruf1SJ9M7FOnElAAI6cOo+vADv5lIg0apDjwJThBUfCGwvwJc2s7RCGEOGn9/e0czrqqF6ph36+PNfM2HNG1VOXAYb+d+rclvr7/bV3Hfm2qtYLLhfeey1PfPsCbs54nsVHCEcUkqseHEvRHnLqiraF8ctYQum6LwOLd77+FfP+fI0q+yurNWbUUnRBCnNwc5U5+en8KF/9vYKX96+YfWU09i7XyysEGg0rLbs2IrucfvdTl7A7Vut7Dn93NQ5/exct/PH1E8YjqqU7frDb6Z3VqCh74R0GlXd6bP+YsQo30oIX70MLBuqqA0JWFbFL31HaIQghxUpr38yJGXvMOAHe8fj3rFmwCHa545IJqX+vvb+ewcMqyA/Zf+/TltO3dEke5k5DQKlbfOwRVVel7Zc9qxyKOnKYHVz9A0w/bRNRx3Zqm8t2iTEISrDjDQ0FX8HmsMN+CsUBnsXEL7ZsdWa0SIYQ4lX325Df89N4UQkIt3PvezSyaspyY5BiuePTCal9r+CWvUpJfVmmfajTwyvRnsNpCcJQ7sdpCqnXN8Ogwzr35rGrHIo5MsH2zirY1rc4loADmLdgMChgKDGhxHhS7iqFYI2zZHhrfeGZthyeEECelsGgbiqKgqApte7cMrDK3ZPoKvn/9F86/6+ygOyULfz8w+VRxXaDanRtRO7Qg6wwEW4tA1F2lhWWsnbcB22mtKWvkw1FPwWBXMJUp2LI9NEiOqe0QhRDipBQRGw5AaISVgbf048J7BqLrOlM+/QuTxcSA6/sEfa11CzYfsC82MSrQL5P+2Ykv2L5ZRduaVicTUPfe3o9vJy1g0Z9LyC+uh25U0GJV/vfBrQy8tV9thyeEECeldme0YtTSV1ENamDp3ILsQp4aNBKf10dJfim3jLwmqGvVb554wL6QUAtupxtziPmYxi2EqH1R8ZHc9eaNzP1jOb9bNVCNaCE60ZO2MeqrR2nTTpbjFkKII3Ht05fRtndLUlukBPpQs36Yz1t3fAxATFIUnQe0D+pa9RrGUZBVWGlf+N4ElxDHQp18Jdm5Y0Nef/4KWtkhdKsDc5GObUkOKP7VkYQQQhyZJu0bBZJPTruLsqJywmPCAIhPjQv6OrkZ+Qfsc5Q5GfvMhCOOrbyknLs6P8Jt7YYy64d/2bUx84ivJYKjoQT9EeKSBwbxxpSniJ6Xi+rWQVPI75dCcoL85UYIIY6Uoih0OLMNsUnRABTnlWANs6CqCkaTgeh6UUFfqzi35IB9GxdvYcn0FUcc3+q567km7S6ePG8ECyYvoSS/9IivJQ6vOn2z2uif1elsjLPEScQv29FsZgwlTrxuqcAvhBDHgtPu4vZ2D5G9LYd737uFFqc3pXnnJkGf3/W8jvz+6V8H7P/+9V84fVAn2vdpXe2YHh/wIpuXbQfghSvexBxi4vMN75JQjcSYqB6fruALos5AMG3EqaGkoJSIXV4cO33Y65tQXT5ZIUkIIY6RTUu38kCvYRhNRl787QlSmiWR3OTAUecH06Z3SzK3HFgz+YUr3uSbnR8RGm6tVjwlBaU8Negl7CUOcnbksWjqctLaNmD0ijeqdR0RvGD7ZhVta1qdHAFVwe10o/g0DCVOAJKb1KvliIQQom4oKywje1sOuq6TuSW7WskngNEPH3wJX7fTU61r6brOnZ0eYf2iynULPC4vboe7WtcSQhxf5cV2fHsKiF1cQvyfudQbt5rwaFtthyWEEHXCjrW7cDs92EsdaD6tWsknp93F9C9mVnnM5/Gha1q1Ysndlc+1je7GXuKotF9GQJ3a6vQIqOcmPcpXL/7A/N+WEBJqoUHL+rUdkhBC1AlxKbE89sV9bFq6laufvKRa525dtYOsrQe+XRt4y1n0uPA0up7ToVrXc5Q52bJ8+wH7Tx/UifrNk6t1LVE9UoRcVFdSWj2eGXs3E175iQ2zN9O0YyMs1VzxUgghRNX6XtmDrK17MIeYOe28TtU6d+Jbv6FXsSza9c9dQffzu2CLrN7Lgk1Lt+Iocx6w/7bXrqvWdUT1SBHyWtS0YxrDJz5CeXE5qkHFGla9IYNCCCEOrt81vel3Te9qn/fDm79V2u46sCMdz2zDhfcNxGwxVetaZUXlLPt7Fc27NGHj4i2VjjVsnUre7nziUmKrHaMIjoYS1FK/UgNK7K/3JafT+5LTKcwpJjzahqpKglIIIY4Fo8nIdc9cfkTn/vzB1ErbZ9/Qly7ndODMIT2rfa2sbXtw2V3YokIpL7JXOma1hVBeXF7thJYITrB9s4q2Ne2U+I1vi7RJ8kkIIU4Q8amVE0LNOqWhGlR2b8qq1nWyt+dweeItPH/ZG4Hkk2pUad61Cc27NOHHtydzfdP72Lx82zGLXQhx7EQnRMriMEIIcYKw2kICP1tsZhLTErCX2CnMKa7Wdf4Y+w/XN7mXl65+J5B8Cou20bhtA1r3bMGzF73KnR0fwe2UMgkns5EjR6IoCg888EC1zpPf+kIIIWrU3EkLKm1/M+JHwL+Kyx2vX8+lD54f1HX++nr2AYtLaF6NjYsqj4TK3pZD0w5pRxHx8aPrOrm78olLiUFVVSa9+zvFuSVc/dQlgaWUT2R6kCuo6DICSgghhDhh5e3OZ8/O3MC2q9zNF8O/A+Cjh8bxxozngq73+d2rPx+wr6ywnLLCcgxGAwC5uwpwlrtO2L6O2+mmtLCc2KRo7KUOvn5xIinNkjjv1n61HdphBds3q2h7JBYtWsTo0aNp165dtc+VBJQQQogaVVV9AfAnY74d+WPQCagWpzc76DGT2ciVj11ERGw4PS867YjirAlv3DqKPz7/h/7XncGAG/ry4QOfA+Aod3L5wxfwz7dz6XZ+J1LTU2o50qppepBT8GQVPCGEEOKEdrDf1M5yFz+8+StPfv1AUNdJbZnCzvW7qzwWmxLNgOv60OK0ZkTEhh9ZoMeZx+3hjo6PsGtDJkM/uZOcnXl895o/qZaYFk9ouJW18zZyzs1nYosIreVoDxRs36yibXWVlZVxzTXX8Mknn/Diiy9W+3xJQAkhhKhRF9xzLu/fOwYAg9mA5tPQfTqqUaVh61Syt+eQ2CjhsNdZt2DjQY953F5KC8q44bkrj1ncx1peZgF/fulfbWbW9//y55ezUI0qmlfjlw+msnnZVlbOXMfk0dMZu+HdWo5WCCGEEHVVXEosp53XmXk/LwTAaDYERplbQsyYQ8y4HC4s1kMvGuHz+aosPF4hZ0cezbs0odv5nY9d8MfY7IkL2LUhE4AP7v8cXd+3+t8nj37Fro2ZOMtd7Fy/mwc+ur22wjymSkpKKm1bLBYslqr/Xd9zzz0MGjSI/v37H1EC6pSoASWEEOLE0f+a3nTq3xZVVfC5feg+/4ioEKuFlTPX8vJ1h0+2LJ62gnFPTzhkm5nfzeOOjg8z5omvj0ncx9rOdbvxef2dGrfTA/inEAKERoQSsrcWQ0FWIZfG38yl8Texdr4/6Tb1s7/57ePp6HrVo8lqSsVKK8F8hBBCCHHiuu7Zy0hq4n8BuH+JA7fLwx+f/8O3Iycd9hqfP/UtS6evPGSbCa/8xO3tH2L2jwsO2a62bF+9M/Czy+7C7fCgqP6RQtH1IgPTBhdMXsLgiOu4vf1DlBSU4ihzMP7lSSz6Y3lthB1Qnb5ZRf8sNTWVyMjIwGfkyJFVXnv8+PEsXbr0oMeDISOghBBC1ChbpI3Y5Bi0/0zFM5r9dQHiUmIOew1n+cHfrqlGlXoN44mpF8WaeRvYumIH1z5z2WHf2tWk9+79lNk/LsASasFld6EaVDSfP/nUqntzWvdI5+9v5wDgKHMG3iZ+9cIPtDujJWOe+AaAyLhwel/arXYeApmCJ4QQQtQVTTuk4bJ7DthvCbXgLHcGtarwoUY/hUZYqd88iR1rd1FebOf713+m9yWnH1XMx5K91MFTg14iL7PAPx9RB1VV0DQdXdPpedFpNGpTnyV/+hNsebsLANi2aiffjPiRssIy/hg7A4PRwLe7PiY6IbJWnuNIpuBlZGQQERER2F/V6KeMjAzuv/9+pk2bRkhIyAHHgyUJKCGEEDWqMKeYsqLyA/Z/uuZtdm/KIr3r4Ytc9rr4dBLT4snelnvAMc2rcc2wy4hOiOTduz+hbe+WKMqJkwDRNI1fR/2BroNqUAL7KmxYvIW1/1Y9vXDRlGUsmrIMAINRJTaIZN3xpAVZ6LI2lvkVQgghRPD27Mg9YGS1wWRg7MZ3ydtdQHqXw/fPbn3lWn77eBqa78AR2vYSB2/NfpEJL//ElM/+4ozLuqNpGqp6YoySXj1nHavnrK+0r+L7UFWFuT8tZO5PC6s8d+JbvwV+joyPIMRWey89g+2bVbQFiIiIqJSAqsqSJUvIycmhc+d90yd9Ph+zZs3i/fffx+VyYTAYDnvPE+PfthBCiFPCmnkbuKbBnSzcm0SpEJ8aS0RsGG16tsBkNgV1rbOuPuOgx/78ciYWqxlN0/jzq1nc3v5hXA7XUcV+NFbMWMOyv1cBMGP8XCr6dwaTkZbdmmEN2+9NUpDT6m54YQgNWpyYxcmFEEIIcfKY8OrPXJt2NyV5lWsB9b2yB1EJEUElnwCsthAatz/4ysPTx83AGh6Co8zJxw9/wes3f3hUcR8Nn9fHzO//ZcfaDABmfPdv4FhMUjTt+rYOdMk0TT94lfb/ePzLezGaDp+IOdn069ePVatWsXz58sCnS5cuXHPNNSxfvjyo5BNIAkoIIUQN2r56Jx63F5/HV2l/QVYhA81X8dI1bwd9rdVz1h30WG5GPm/c9iG5GfkA7N6URWnhgaOuasLKWWt5+KzhPNr/eZ6+8GV2b84OHPM4PTRslUp616aBffsvc6waVFKaJXHW1b1JbpoIQGxyDKcP6sTYp75lSP07AlP1akPFMO9gPkIIIYQ4MW1ethUgUJuywpLpKzjPchWTR08P6jq6rrN15faDHv9t9HQ+H/YtZXv7ZOsXbj6ygI+Br174gRevfJM7Oj3Ce/d+ise1b/phQXYhjVrVJ6lpvcC+Tv3bBX62hoXQvEtjzriiB6ERVlSDSoOWyXQe0I5H+7/ATen3s2Pdrhp9ngrV6ZtVp38WHh5OmzZtKn1sNhuxsbG0adMm6OtIAkoIIUSNGXBDXzr1b3vAfp9PQ9d1/v15cVDXGfPkN6ycufagx3dvyiJrSw5Gk4G0tg14dNy9xCXXznS1isLhAPN/XcJfX8/ikc/vCRS0nPrZ3yz/ezUWq7+oZc+LT2fYhAfpfmFXvtr+IQOu78Pf38wmc2/iKj+zgILsIjRNx2V38fK175CfVVjzD4YkoIQQQoi64LZXrqVew/gD9hftKUHTdOb/tuSw1/D5fDzQ++nAgipV2bx0G26nB4vNQoczW/PI5/ccVdxH499f/X1On9vHLx/+gTXUwnm39vMf1OGXD/8ga/MeFFVBVRVufH4IQ568iPNu68+kwrGERoQy67t52EscaD6NrG25bF6+DfBPZ3zu0tdq5bmOVwLqWJEaUEIIIWqM2WLisqGDWf7PGn/do4rZZjq07N6cC+46J6jrLJyyNKh2JouJ0SveOMJoj42Q/xQ/1zUde6kD/T9F2FWjgSbtG9H70tP5X/cnKS+2k7lpEMW5e4fD7y2ICbBpydbAeYqq1mqtASGEEEKc3BIaxHPmkJ6Mf+WnSvtVg0KXczpww3NXHvYa5cV21s7bENT92vdtzYhfnziSUI+ZsGhbpW3VoJK948DaolZbCD0vPo2S/FK+e+UXoutFUl58daB/pigKuq7jcXoodu4bRbX/SoJ11YwZM6p9joyAEkIIUaO6ntuRr7Z9SIvTm1baH50QSf9rD17XaX93vXXjIZMuqlHFZDaiaRrfvfbzUcV7tM6/cwCXPzwYk8X/zicyLoJRD34eOB6dGEWn/u1wlDrYsmI7K2eupTivFK/Hx5YV2znv9v607NacnheeVuX1w2Ns2CJCa+RZ/utEfsMmhBBCiODdMvIaPt/wbmBENoDm0+lydgeadjx4XacKETHhXPv0ZYER3lUxhZgwmgysX7CJFTPXHJO4j9TjX/6P087rFNjeviaDJdNWBLabdkqjQcv62EsdzJ20kM3LtqH5NPIzC8nPLOTyhwaT3rUJ7fu2qvL6rXukH/dnqMqJPgJKElBCCCFqXExSFBsX+UfxqAb/r6Lq/KLu0LcN9753y0GPa14Nj9uLy+5mypi/ji7Yo2Q0Gbn91et5f+HL9L2yB+sXbg6sDtOqe3Ne+/NZygrLsEWF0u38zkTVi+SmF4cw5PGLGXR7f8aPnMS6+Rv599fFmPfrFFboe2WPmn6kgBO5gyOEEEKI6inIKsTlcANgNBkwh5ho1rlx0Off8NyV9Lmi+0GPe5wevB4fJXmlzJww76jjPRpxyTGM+O0JXvj1cVp1b86a/UZvXXDPudz5xg3YS+1Exkcw4IY+tOnRgovuG8j/PryNtDYN+PSJb9iwaAulBWVVXv+82/rV1KNUIgkoIYQQ4j8MBgOhEVb/z0aVz9a+zRWPXBj0+T6vL+ji232v6nVEMVZXxobd3NnpEZ656BXcLg+blm7l+zd+paSglPysQoadP5LZExdUWuI4OjGKd+/+hI1LtlJeZGfRH8t5evDLfD5sPM5yJxarhdY9WwDQrFMaUQkHLpHb86LTa+T5hBBCCFG3JTaKR9mbk2jQKoVvdn5Em739kGAU7ilizZzgpuFdcM+5RxJitc2eOJ8bmt/HF8O/A2DOpAX8/ulfaJrG4mkreOHyNyrV6wSw2iy8ceso8nYVUJxbws/vT+XhfsP55cM/iIr398Xa9PJ/L616pKMaD0yrtOnV8jg/2clJakAJIYSocXN/WhhYAcXj8vJI/+cYv2t00Of/+tE0lk5fCYDFag68rfsvg9HABXeeffQBB2HGhHlsWb6dLcu3s2nJFp4aNJLyYjtblm+jXZ9WgRX5QmwWOp7Vht1b9uDz+Fg5y19MvXG7hmxfkxG43h9jZ1BebOeBj27njMu6YQk1M/zi18jZkVfpvk07NqqR56uKDmhBrEusH7aFEEIIIWrbNy/9SMV7sq0rdvL+vWN4avyDQZ//zt2fkLsrH6PFiNflPWi7xMYJNGqderThBuWn96eQuTmb71//hdMHdeK5S18HQFUVFk5Zintv3aa4+rGkNE3EUepg7s8LydqyB4NRpU2vlqyY4Z8uqPk0Rg0dy+5NWQwb/yBF792C2WLkzy9n4ShzBu4Z3yAWRamd0d/B9s0q2tY0GQElhBCixo287t1K2/mZhcyffPgVVvZvD2A0G3A53CiqgtliOqDdgOvOILpe1FHFGqwzr+pFs86N6XnxaTTr3ISohEgALDYLk96bEmjnLHexeu4Gdq7dxeo56/ddQPGvQlPBUepg+hczmfndPCLjInjs7BdZMn3lvtpXCvS6+DTCo8Nr5PmqciIP8RZCCCFE8Ar3FDF59J+V9s384V/spfagztc0jZK8UoBAn8xQxcgggJtHXHUUkVbPxf87j9T0ZK587CJsUTZMe2MrKypn7k+LAu3Ki+2smLGGjUu2Ulrgf0nq82rEJEXT+ez2gXa5GfmMefIbivNK8Hm8XN/0PlwONwajAfAXbr/8oQtq7Pn+S6bgCSGEEPvRdR1XueuA/e/dOyao84vzSgKFxePrx+69KLhd+1Yeueh/A7npxau4860bjzrewyncU8SjA57n08e/4p53b+bBj+/AbDFxzdOXYrFZ+OOzv9m+aicAZqsZg8kQqBdQVlQeuM7WFTv4+OEvDrj+qAfHsnruOjYu3gJA045pRMSGgQ5zJi3kwT7PHPdnFEIIIUTdtnXljgP26ZrO50+ND+r8uT8tYtXsdQCoqj/N8N9RQNcPv5IHPrqdM688/uURVs1ex91dH2PDws08MvZernzsQuo3S2LAdWdgshj5+OEv0HwaANawEByljsC5gRWIgX++ncPSP1cccP2Xrn6beb8spiS/FM2ncfaNfQF/4fYP7/+cccMnHN8HPElJAkoIIUSNUhSFmOSoA/ZHxoYFdX6IzRJIPJ1z01lccPc5tOmVHjg24Po+3P7qdVz95CU1sjrc7IkLWPbXKuZOWsgDPYdxW9uhOO0uFk5eiqvchc/r79woCrgdbnyeysvyGowqzbo0Oej1SwvLebD3M3jd/qHsW1bs4OYRV2M0+d+0rZ69jvKS4N5OHmsn8hs2IYQQQgSvXsN4qpq5dahVh/eX2Cgek9mIyWLi9teu4/w7z8YWZQMgJjGK2165luueuYxBtw84lmEf1KR3J7NpyVbGv/IT/+v+JCOuehvwl4Hw/Gd64P7T5yrEpcQQHuPvm+ragddfNXsd793zaWB759pdXHz/eYHtn/cb/V6TTvQRUFIDSgghRI37aMlr3Hv6E+Ts9Nczuv7ZK7jgnnOCOtditfDx8tfIzyqiQYsUAJx2F/N/XUybXi2IS4k9bnFXpevADoTYLDj3juoqzivB7XBz+cMXsHjaCsoKyzEY1UAian+qUSU6MRqDWvl90NVPXcLOdbspyCqkIKuQ7O25gWOOUgdzJi3govsG8sObvxEaGRp05/BYC7bzIgkoIYQQ4sRWv3kyr/89nMcGPI/PqxESZuH+Ubdz5pCeQZ3frFNjxm1+H0WBuJRYBt7SjyGPXcT6hZvpPrgz5pADV/I9nnpdfDpzJi1E1/yVjnZvzgbg5pHX8M6do9F8GooCehWFkEwWExFx4ZQVlQdGrRtNBh4YfQfTPp9BiM3CoqnLK52zZt4Gul/QlbS2Ddi2aicNWtVMjav/qk5iSabgCSGEOCVE14uiKKc4sP3NyIm8/7/PuL/XMDYv33bY822RtkDyCSAk1ELfK3vWePIJ/EXQK5JPigJPfH0/EbHhNO/chNikaAB8vipenQGaVyNvVz7rF24CoMXpTelzZQ+mfvY3qS1SeGfuCB4aczfJTRM5c0hPGrauD4C9xMHPH/zh/7nYzq+jph3vx6w6/hP4DZsQQgghqscWGRp4YeYsczHmia955sJXeOaiVygvLj/M2f7SCPv3xeo1jKfP5d1rPPlUoSL5FBJm4ZnvhgL++qAVFLVy/0Q1+Lc9Lg9bV+wILPzS86KutOqezrhnJjDk8YsYMflJbhpxFfUaxXPt05dhDvHXldq4ZAvb9pZdWDN3PSWFZcf3Aatwoo+AkgSUEEKIWtHn8h6Bn71uHzPGz2XtvA21NmT5SEXXiyKxUUJgu3G7RoGf8zIL/D8EscxIvUYJDP/xUWZ99y8FWUV8+9KPOB0u9uzIpWnHNK55+jJe+/NZHv/yf6S1a4Bnv5pXoTUw1VAIIYQQdVuDFimkpicHtvN2FbDw92X8+8ti5v+2tBYjq74u53TAsLdcgclsIjHN31crzisJ1H7SfJU7aP/dVlSFrgM7ctF957Fy1lpyM/J549ZReDxeygrK6Ny/HVc8cgHvzR/J098NZduqynW0DAZJt/yXTMETQghR46aNm8H0L2dW2mcwqtiiwjjzquNfmPJY0HWdf39dTL2G8UTGh5O9PQddh3fuGs3GRVsYcEMfzhzSk98+mh7U9fZszyFzczbxqbGBqYmDbftWxdM1jWe+f5h6DeN4+bp9q9R0G9yFs6/vc2wfLki6rqAH8fYsmDZCCCGEqF1v3zmajA2ZlfaZLCaSGifQ/szWtRRV9dhLHSyYvJR2fVqh751fV1pQxgO9hpG5OZvLHr6QJu0bsmXFgUXX/0vXdJb/vZqhn9yJwWjA5/WRn1nI4PBr8bn9NT2bdEjjgrvP4cd3JpOxft93d+97N9dILdIDYg6yb1bRtqZJSk4IIUSNc9kPXAXP59Vo2yudTv3b1UJE1ffLh3/w7EWvcl+3J4lOjArs37J8O067i19HTQs6+VTh5w+mcM+7N1V5zGj2D+9euXeFGfAX9Rz+48PVD/4Y0VCC/lTHyJEj6dq1K+Hh4SQkJHDRRRexYcOGQ54zY8YMFEU54LN+/fqjeUQhhBDilOGson/mcXkYfOc5xCXH1EJE1ffqje/z0tVv88S5LxIREx7Yv3HxVsqK7Iwd9m1QyacKHpeHLcu3Mej2/oF9FcknRVWw7K3DuX7BpsDx/tedwYX3DDzaRzki1embVbd/dixIAkoIIUSNspc6+H3MX5itJkwWU6Vjjdo2POz5uzdn4ShzHLbd8VYxfBtd54pHLiLEZsFgVGnfpzXRSZFHdM2lf63i2Yteq/LYjAlzeePWUZTml/p3KFA/PZmSvNIjuteJbObMmdxzzz3Mnz+f6dOn4/V6OfvssykvP3z9iQ0bNpCVlRX4NGvWrAYiFkIIIU5um5ZuZcWMtYSGWyuthqeoCk07pR3yXJ/Xx871u/H5fIdsVxMq6j5pPo2bXhyCoipEJUTS9dwOmENNhzm7au//7zN++fCPKu/17t2fMGXMX4F6UkaTAYvVgqZVXf/zVCdT8IQQQtSo7at3snnpvkLjzTo1ZtPSrQDsXJvB2n830Kp7epXn/vLhH7x376ckN03kk1VvYrYcWUfiWLjw3nOJS4mhXqN4fv/kL5zlLlSjyrxfFmGLCm7IdVz9WEoLS3GVuwEozT+wWGVy00RydubidfuY+tnf9Lz4NP8BHVbOXMu4Z7+j58Wn0fWcDsfq0YJ2vFbBmzp1aqXtzz//nISEBJYsWcIZZ5xxkLP8EhISiIqKqtb9hBBCiFPdwinLKMkrCWx37NeWZX+tQtd0FkxeQmxSNEmN61V57oir3mL2xAUMuKEPj35+b02FXKVHx97DvJ8X07FfGx4+6zl0Tac4r4RFU5djCjl8v1E1qCQ3TWTXxsxADc/srTkHtEtukkjW1j24HW6+f+MXyovtAHg9PiaPnk5Cwzi6D+5CWpsGx/T5DkdWwRNCCCH2k35a00pL+hrNRroN7kxEXBizJy7ggV5Ps26/Ycz7277av7JI9rYcnOXOGon3YFRVpcu5HXj/vjH8ubeelbZ35ZjyIvthzzdbTUTEhOEqdweKZFalOLeYEFsI4TFhAKyes56u53UkOjGK0Agrk0dP58mBI1gxY80xeKrqqagzEMwHoKSkpNLH5TpwqH9Viov9KybGxBx++H/Hjh1JSkqiX79+/PPPP0f+cEIIIcQp5NybzyK1xb4C5M06pdGodSqRceGMf/kn7j39Cdz7LYCyv+2rMyr9szbZIm006dCIe09/gpyducC+UVEeZ9Xx7y8qIZLi3JLDLiBTWlhGTFIUllAzGeszCY8Oo/M57QkNtxIRG87nT33LAz2H4ajh/mp1+mZSA0oIIUSdZzAYuP216wgJ88+ZXzd/I4mNEvA4vYC/uLfPW/UQ7huev5IrH72QZ394uNK8/tqyY00G6+ZvwuVw0+PCrhgtwQ8sdjs8bF3pr0Hg8/zneffrD5QXOygrLCcs2gZAcW4Ji35fRmF2EfYS/1RERVEwmk/8Qc2pqalERkYGPiNHjjzsObquM3ToUHr16kWbNm0O2i4pKYnRo0czceJEfvzxR9LT0+nXrx+zZs06lo8ghBBC1EmxSdHc8tI1ge2Jb/1Gtwu6ULx36r/X40U/yLSyJ76+n8uGDuaRz++pkVgPZ+HvS8nPLMTj8nL2DX2rdW5BViGlBf4R6caDvCBUVIXSgjLyMwsD5SR2rN3F0ukrsZc6KNn7nakGFUWRhVj2d+L3VoUQQtQ5cSmxjJj8JA/1eRaAn96bEjjW65LTadAyJbCdsWE3Hz7wOaktUmjftzWD7hhAUlrVQ8BrwoqZa1j25yo6nNWanz/w1wOwhJpZMHkJMUnR5GbkH/J8o9mI1+09YL8l1LKvOLsOqlElpVkSzTs3ZtHU5WRt2UNqixR2bcxENaiVk1YKgRFSNam6U/AyMjKIiIgI7LdYLIc9995772XlypXMmTPnkO3S09NJT983dbN79+5kZGTw+uuvH3banhBCCCGg50WncemD5zPxrd/weTXGj5wUOHbVExdjMO5LyMyZtICf3ptC9wu6kNwkkauevLhWXw5O/exvSgvKSGmexD8T5gJgiwzlr69nExkf4R/VdDAVXZn/jHryen0YTIZKfS7VpNL+jNagwNq5GygvstOwdSo71mRgi7BStt8oeEuomZDQw/d1jqUTfQqeJKCEEELUioLMwgP2GUwG5vy4gA2LNvP5+newWC1Meud3Fv+xgsV/rGDSO7+jGhTe/Xck6V2a1HjMPq+Ppwa9hMvu5tuRP6LtHdLtsvtrOB0u+QRUSj6pqkpsij9p9d+VATWvRsa63WRt2UNkrL9DFxkXzojf3sNgVMnenss3L/3IkmkrQAef58Ck1vEW7PDtijYRERGVElCHc9999/HLL78wa9Ys6tevX+34unXrxldffVXt84QQQohTlaP0wIVeLKFmxjzxDZuXbWPY+KEAfPbkN2RsyAyUAIiuF8mXWz/AYq3ZhAvA6rnreePWUQfsr6jLdMjkExyQeDKHmLBFhVKYXXzAKHXNo7Hsr1UkN6mHy+Hv//W+5HQe//I+EhvFM/vHhUx8+zd2rM5A82noul6jo6CqM7WuNqbgSQJKCCFErdA1HdWgovk0FEXxT73b+0u+MLsIl8ONxWqh58Wn8dc3c7CX+DsRmk8nb1d+rSSgDEYD+t5OSkXySVEI7KuuM6/qyV9fzz5kG5/Xx/XPXcGsH+Zz4wtDAgVATRYTL/3+JLMnLiAqPoK0IFYQPFnous59993HpEmTmDFjBmlph15952CWLVtGUlLSMY5OCCGEqLt8Ps0/Imi/vk3Fi7as/Ypxn3V1b74eMTHwYq0krxSX3V0rCaiwKFv1Ttjv+Sr6oPvre2VPpo2bcehLqArXD7+CLSu2c+nQ8wmLtOH1eOl5YVf6XtGdGRPm0bZ3S5mC9x+SgBJCCFEr/h4/B83nryVQ8Ys/Njma827tR6seLdi4aAtR9SLpPKA9PxeN4933f2fV7HWc16slPS7sWmtxJzepx/bVGRiMKgmN4snavOegbSPjw4lNimbrSn/xdFtUqP9tnA6qQWHGd/MOe787XrueH9+ezI61u/C4vbzx93DevfsTfv1oGufedCYPjbn7mD1bdelBDvOu7hu2e+65h2+++Yaff/6Z8PBwsrOzAYiMjMRqtQLwxBNPsHv3br744gsA3n77bRo1+j975x0eRdXF4Xe2pfdOCYHQe+9NikhRQEARUBAVKYKNoiB2ih0BadIFQQQp0qT3XkOvCYSQkN7btu+PSSbZ7CYkSvPzvs+zDzt37ty5s6hzPOV3gqhRowbZ2dksW7aMNWvWsGbNmhI+lUAgEAgE/132rjpklRFUv0MtqjerQus+zdiz6hB12lRnwMTe9BjVmakDZpCRks5L43vh6vV4SvDc/VyR1BJmoxkPPzeSYlMUG9MWjZ+px8kdIRj1RsxmM3ZOdmSlyZno9o52bF+6t8j7qTUq3p03lA87fYk+20BwnSD6ftCDEY0+IOx8OGMWj6Dza+0f6DMWl+LaZrlzHzVChFwgEAgEj4WmXRugUqtAkjOLXDydGffLSF759EUuHrrMh50nMaz+WM7sOc/+E9dZcfAS51Xg0bTSY4smDaw8krDz4Xj4udH1zY5kphbdxc3Z3VlxPgGK8wnkTK7cjK9y1Uvj6e8OYNUieOev+0lJkMUwQ/Zc4M9Zf3H+4GUAjm4+zfCGY9n1a9FZVA8LM3L2130/JVx39uzZJCUl0bZtWwICApTPb7/9psyJjIzk9u283zY7O5vRo0dTu3ZtWrVqxYEDB9i0aRPPP//8g3lYgUAgEAj+AzTuXB9JklCpJNRaNaUrBzBh5bsM/OxFvh08i0l9f2BA+eFkpmfxy6e/c3TTSS4evkql+n8vW/mfEnnzHv3LDcdsMlO5QQXqtqtl0czFFtnZBovSulznE0BmepYSGG3YqQ7anAYzuWLjAEaDiY1ztqPPyf5a+tkqboSEEXY+HLPZzG9fr+ftFhMIPZ9npzwqim2b/Q377EEgMqAEAoFA8Fg4uuW0Ep0yGoykxKey7PPV1HuqFuFX7irzFnz4KxeuREDHmkiShJeb42PZb+i5W9y9LmfiJNxLYkOOALl3GU9i78RbiFRq7bS06tUErYOWiGuRyhquns4kx8nOJEkl4eTmSFZGNrcuRihzclsEq1QqTCYT107eVIwfgOlvzee54Z2o3CCY41tPc+1UKMsnraFdv1YP9wewgQkJ6X5WXs68klAwFd4WixcvtjgeO3YsY8eOLdF9BAKBQCAQ5JGWnM61Uzcxm82yvIDJSMTVSNbP3MrLH/ch7m48ANmZet6sO5q7N2S7SGuvxe4Ri23nsuaHjWTnaDFdPXmTqydvAuDi5UxKjs2Vi2eAO617NeXQhhMW4+6+biRGJwHg4GSPWZLtsRN/nUVSyTaMPktvcc2e3w7mNZAxw7stJ9L3gx5EhUaze6Usgr5xzjZGznz9wT90ERTXNsud+6gRGVACgUAgeOSc2nmOw+uPA+Ds4aR0cKvbtiYA7y8YTrPnGvLM4HbcvnQHdWI6jpvP4rDpDP6O9o9lz/7lfZV95o+Cefi7o7PTKgYKyEbK7pUHObD6qDJWtmop5p75lrfnDEGjU2M2mXHxdKZMZdsaRVWbVsy3ngE3n7y09rN7LjB64XB6vt0Vd19X7BztWDtj8wN7VoFAIBAIBP89fvtqHZE3ZWkBN19X7J3s0Oo01Ggud5mdtGk8tdtUp9d73eSgXE68yGw2P/Jub7m0699KzqgHC1usTuvqAGh0eZ374iMT2bp4N/FReY1wug19mmVhs+j4SlsAMtIyadKlHmqNvKbZZBkUq1gvKO/AbEajldc3ZBvJyshm3C8jadGzMR5+boRdCOdMjki7QEZkQAkEAoHgkeMf5IOjiwPZmdk0fqYe7r6uvDCuB17+HoBcf//5unEA1Gtfi68HzoC0LJzcHPEp4/VY9uzg7MC3uz/hu9fmEHYhL6X6xqlQRZA8P2aTWem+4uTmiH+QLxqdhvnjlmHIljOlom/FYjQYCaxWGr9yPhzfeka5/uKhq+jstWTnZESlxKdarG3QG+g7rgeH1h/n0pGrXDt5k5otqlKpfoWH8fg2KWkXPIFAIBAIBE8uQTXKIkkSHn5u1G1Xk2pNK/P0wLY4usj6i8F1gvhu92eYzWYyUjLZ/PMOAKo0rFjUsg+V6k0rM3rhcFZ9vZ6wC+HK+LEtpwEUmyuXXPkESSXh5u2CRqsm6uY9tv+yR5mz7/cjmM1mqjWtTGZaJqHn8uy+66fDcHZ3JDUxXemCl0tWRjZqtZpP14yhm/MAQvZe5MNnvmRL5ooH/NSFI7rgCQQCgUBQgFLB/iy9MZPlX65h7XQ5cye4bnlC9l4kJiKO934eil+gDwBNutZn0BcvERsRR7c3n35se753K4YJXaYQGxFvMW7L+VSQtKR0jm89w4Suk5X5GjsNhixZO8DR1ZE2LzSzcECBnOLu7ueGSi0RfzdRGb99OYJ+gUNp168VDk45EUcJXL0frfinySwhFcN4Ka4YpkAgEAgEgsdHu36tqNqkEt+8+hO7fj3Arl8PUK1pJRaO/xWfst68M2cIGq0GSZJ4cWx3nNwc0eo0vDDmuce25+NbTzNt6DyyM7JRaVSYDLK8Q24ArzDMJjOJ0cmsm7FF1nLKMed0DjqlpK9Ko2AS7yVZOKAAUhPTCajox73QaEzGPDtw09ztnN55jgETeysZVPZOjzYzrLi2We7cR41wQAkEAoHgsZCWlM66mVuU42ObT7H398MAvBL8FhNXvUftTnUY2v9b7u24RIC/B29Nf+1xbZddvx7Icz4VaE9cXNKTMxgwsRc/j12mOJ8ALh+9xvUzoTavSbyXZHM84V4Sa37YyJBvX6H+03Wo3aqa4rQTCAQCgUAg+DuE7L3I+QOXleNFH63k1I5zABzacIKfjk0hKz2b4Q3Hoc/S8/Sgp3Byc3pc22X1938qDqNc51NJMZvN1O9Qm1M7QpS1ANbN2KLILxSksC7Id69HMfOt+Xz46ztcPxVKlzceTze8JxWhASUQCASCv0VyXAoH1h4lPSWjxNfevhyBPktvoRcQdy9R+W4ymvhz9jb6fLSACxVcSOpShXu3YshIy3wQW/9btOjZmMBqpanSOBg7e53NOYV158s1Xu5cjWT+uOXKuIefO2WrlgbAkGXAI8Ad33IlcyLNG72Uejlp8o+aYndZeRxtVgQCgUAg+A8SfiWCY1tOF6uhR36MRiPXTt3E2cOy2Uv+ZiopcSks+GA5Q+uNVkS5D6w98s83/Q/o8noHfMp4UbdvS0yVy2DWWufYODjb1g+1d5Ltuc3zdnBqR4gy7hvojV+QbI+lxKdSsX557J3kNXL1pnJRa9UUJD0lk69enkG/Cc/jmSMv8agoiW32OOwzkQElEAgEgr/F+K6TuXLsOnYOOqb+9RE1W1Yr1nW7Vx5kcr9puHq5MGnzh5zcdg53H1fcfFw5v+8SAKUrBXDkTjRJlZxAI2HWqNDo1KjVjy9uEli1NAsuTKO372Cl5t/R1YH05DwHXK6xZ+9sT2ZqnrPMQr8p39u+fodaBNUsy87l+wk7H45apSIjx6HnX96X+MgEJYVca6dBny9rKhetnRZH18fTGVBoQAkEAoFA8OSQGJPEsPpjycrIxresNz+dmIq7j1uxrp0xfD6bft5BnbY1+HLTh5zff5lK9ctz+M8TRIVGA1CpQQUlWz2X0hVtN1N5VLR5oTkNujagW69pUD4AO2d7pJBQjIY87aeMHJtM56AlOyOvNC8zLbvgcgC0H9AaF3dHlnyyiqyMbHR2WjJzgqANOta2kEzQ6rRKF+T8uHq7oFI9ertVaEAJBAKB4P+O1d//ydXj1wFZcHHn8v3FdkDltuxNiU/lkx7fkBKfSufX2tO+f0teGNOdxJgkBn76Iv36fYsmE8xqE647r1O9WRV0hWQePQqWf7mGP+f8ZaH5lN/5lJ/8zicLCpTu7Vy+HwB7ZzsCq5Um8mY0+iw9ngEeBNcJUgw+wKbzSaNVI0lydLJMpcdrAAoEAoFAIHi8fPXKDCVIFh0ey9k9F2nTp1mxro3Isc/CLoTz8XNfYeeo4/m3u9Ljrc6YzWYCyvtRp11Nxjz1KSCLeJtNZlr0aPRQnqU4GPQGPu/zHaEXwlGV9sPkYIc+Nhm1wdohBFg4n4pixeQ/AAio4IvJaObi4asAVG5Qgbs38krvVGqV4pjKj9ZOgz5TT3R4LL5lvUv6WP/XCAeUQCAQCIqNyWTiwsErLBi/3CJt9+T2EO4U0wnS+71uqNUqdA46Zr+7GIAtC3ay/Ze9zAv5jrKVS/Fm3dFw4TaOiemoEtLQxGdYiX8/Cm5dDGfvqsO069+KDbO2Eh+VSPlagbTs1YQtP+8s+YKFpDpnpmZx+1KEcly3XQ0yUu5fbmjQG0Fv5PCGEzTpUr/k+/mHiAwogUAgEAgeP2lJaZz46ywn/jqrjEmSxNaFu2j2bINiBfDenz+MrQt2YTAY+e2rdWSkZLL8yzUcWn+cGUcmk56cwSsVR+YsLot4A8Tcjnsoz1QURzef4ubZWzR4uhaHN5wAoEOzKiSnZXLydvR9ri4+kTfltWSFBYlm3RuxbfFu5bzJaFtzSp9lIOZOHJeOXHvkDiiRASUQCASC/xumvTmXLQt2WY1H3rzHgTVH6PtBz/uuYedgp8xz8XRm1/L9nNh2FqPeyJBa7zFl60fcPHcLyQx2F/N0Bz5cNurBPUgx+bLvD4SdD2fTzztISUzDq5QH9TvWZl+B9POCqLUqjPrChTAlFZhzT+e++3OcU2MWDefHYT+TnamncsNgSlfyZ/eKg4WuVaVRML3ff7YET/XgEF3wBAKBQCB4/Axv9AF3r0cpx2qNCqPBxIm/znAz5BZVG1e67xr+Qb4M+qIv+mw9Ds727Pv9EDdDbhN6/javVnmbN78fmJftk2OzOHs4MXhyv4fxSIUSH5XAx92/kvVC53qjs9cSEOyHnVbNzUNXirxWq9PIHe9KiIOLA698+iJz3luMSiXRuGs9stL1nN19vtBr2r3UkqbdHn1w8EnvgidEyAUCgUBQbPb/cdTiuEbrarTo0ZhqTSvR5sXmyvjZvReY1G8aZ4p4MZvNZjq+3IYpWz+iYac6mM1mDHojN86EWQk8Vm9W2cJ4MugNJMelPKCnss2dq3eVVO2EqAT0mXpUKonjm08TE24Z7XP3c7U4Lsr5pNaq8pxPIBtx+TKjnD2cMeZ0cbl64gapiWlF7rPTq+1E+Z1AIBAIBP9REqKTLJxPAP0n9qZq44q07tOM4LpByvifs//i60EziQ6PLXQ9jVZD/wm9mLJlgtwYxQwxd+LQZ1nrJT3/dldcvVyU44zUDDJSS96cpiRcPHwVnb0WgJjbsWRn6vEt68P2X/aRcC/JwoZUqS0dLIU5n2wJiecnKz0LJzcHAEwmM8c2ncZsKrrj3hvfvIydg12Rc/6LCAeUQCAQCIrF3lWHFBHHXC7su0RGaiaSSsWdq3nZSjNGzGfPyoP8OGyezbV+/3YDz+j68u3rs9n+y14lZbxC7XJo7TWYDCYyq/mT2K8RGQ0CCb8cgSnnRa/P1jOi0Qf09n2NHcv2PaSnhe/fmMPdG1G4erko5YaJMSncvhyBSq1CZ6+l0TP10NprSIotvjMs1zmltddiq2neN4N+YuzSETi6yobOzbO3LM6rdSqkfG/vOe8voX/QMCKuR/KoeZK7rAgEAoFA8F9g+RerrcaWfrIKF09nUhPTiI9MBOTMoekj5rN96V5F46ggE5+bSleHfqz+YSNrZ2wh+lYMAE8PbMuBP45Zzb9xNkz5fvtyBH3LvMlLZYcSfiXCau6DICMtk8kvTSMzLYtyNcoo48e3nsZoMCKpJFw8nalQpxxaOw0mY+EGiKTKM8Lyl9JptGqLcwBGg4mdy/bTY2RnVCoJSYILBbKtnNydLI4HVnyLsR0/Q59dPN2pB8WT3gVPOKAEAoFAcF+S41KY/d5im10+zu45z8VDV/h10hpAdhDVfaomAPXa17a53r41RzAZTexYuoevB87Ew98dF09nXvn8RRaOXwFAdkUfzHYasir54OTmiNlsJvxKBMlxqYSeu43ZbObCwcsP6YmhbJVSgFzi9vLHfejwcmt8yngCsqGSnann+NbT6DMNmIswcApDn6lXXvw+Zb2U8dTENL56eaYicB53N8HiOmO2idYvNKdxl3oAZGdkE307lpPbQnjUyMaLVIzPI9+aQCAQCAT/95w7cJn1P221ee741jOc2h7C1oWydIK9kx0V65VHpVYpdlp+MtOzOLLxJPpsAz+P+4WVU9fh5u1C2aqladS5LgfXWjugnN2cyEzP4u6NKEJDbpGenEFaUjo3Q24/2AfNQWevxb+8LwBt+jSn06Cn6PZmR7R2srKQ2WQmKSaZm2dv2Wzekh9zvqYy+b8b9Ebl2NHFQRkP2XeRdTO2YDKZMZuxsonTEtN4e84QytcKBCA7U8/pnecVHalHRfFts8djnwkNKIFAIBDYJPZuPF+9MgOT0cTFQ1fQ2mlRqVUWUSJJJdF+QGsOrz9Ox5fbcGzLaT7t+TWB1cuwKnIeHn4eNtd+bXI/Vn2znmunQkmMTiI5NgWtnYZ9vx8iLSkdAPvT4WTWLk3jUj58fngy04f9zOb5O6nZqhq1W1fDxdOZ/hN7P5Bnlcv/DGh1WmXs7TlD6DGqC2UqByjjyXEpXDx6le8GzyYxOumB3Dt3XZ2DjuyczjWFiVrmsv/3I6yJWciY9p8RdiGcUsF+tOj56LvQCBFygUAgEAgeLWd2n+fncctwcLbn7J4LOLs7kZGWaeEQ8SnrhW85H6LDYmjevRELJ/zKiilr6fZmR77f+xkOzg5W69o72jHsh0EcXH+M8/vlAF9yXCoOLg4s/3KN1fwXx/VgwMReDG84jvDLEbR9sTmVGwZTs2VVWvZs/ECe1WgwggRqtVwip1ar+en4VGLuxBNYtbQyr9d7z3Ju/0WmD/tZbtDygHD3cyc9NQPM97fNAP5atIuxS95iXMcvyErPol6HWkpA81HxpIuQiwwogUAgECjos/Wc2hFCamIae1Ye5Myu84TsvYhBbyQjNRMPPzeL+QEV/HjjqwFUb16FQxuOc3SzHDm7cSaMjNSsQu9T96maTN48gR/2f0GL55tgNBjJTMuyKDfT3UnEdfMFWlUug4efO6Hn5WjapcNXObv3Ivdux+JdyrNYz/Rl3+8Z1Xw8d29EWZ3PztLzZp3RdHXox6vV3ibhXiIAKpWK8jUDUWvU/PL57yyeuBJHVwf2rDz4QJ1PIGdDZWdkW+gW5NdsKIjJaGLJJ78xafN4XD2duX0pgpVT1z3QPQkEAoFAIHgySIhO4szu85hMJlZ//ydXT9zg7J4LAGSmZaLWWP5vfb32tRgx7VW8Snuyc/l+jm05DcCxLadtOp9yef7trny36zO+2jaRgPJ+mM1mokKjrbvoSdBpUFtMRrOiP7Xnt0NcPXEDjUaNWlO0phJAZOg93m4xgc9f+I7sLOsytVsXw+npNYgu9v34rPe3mHPSdRycHQisWpqE6CRmjlzAX4t341vWi5VT1j5Q5xPA3euRFjqdOgcdpSsXrrt5+eh14iIT+GzdWPRZeo78eVLp0ieQERlQAoFAIADkKNMXL3zP4Q0nqFS/PEN/GETZqqVQa9SEnQ8HLMvBZhydTOSNe+xctp+jm04B8Nb0wTz1Ugsq1A6iVLA/CfcScfF0RqO1/bopUynAogC97YstCKt+iz2r8rrMbZy7nS3zd6K10/LssE6EX47gzO7zOOertV/zw0Yirkfx6pd9SY5LIe5uArVbVwfg2qlQ9uast3vFQfp/1MtiD/GRCYpz686Vu+xYvo9T20OoUDuIN74awJGNJ1n66SoAylYtTWgx0spb9W5CtaaVuXM5Eu8yHvw6eS2GQoQvmz3XgLO7L5KekoHJaMLBxZ4mXRuwZ2Xhne8A1s3YwroZW9DaydlZ90s1fxgU0E8vcp5AIBAIBIKSk5qUxrD6Y4i7m0CPUZ1p3qMR106F4u7jys2QW7LTJcfx4hPoxQe/jCIhKpE/pm3k8tFrXD56jY9Xv8+uXw/wzKtPYTKZiI9KLDKIV715FbLziY6PXTyCcZ2+JC4iXh4ww5z3lnD15E3qtK1BuRpl2LvqMPGRCTh5yPZZRmoGiz5aiZuPK/3GP8+lo9dwcnOkXDVZu2n3ioNcPHwVgF7vdKNG8yoWe7h05BoZKbL26IE/jrJ96V7+WrybrkM60u6llqyY/IdSflipQQWiQu9f6tb3w56oVBJZadmkJCazbcm+Qo2UPqOf5fdv/1SOfct64xfkw7n9l4q8x8RnpyJJEqacMj69Defaw6S4tlnu3EeNcEAJBAKBAIBJL/2gRGmunQrl/Taf4OTuiKOLA37lfIiLjMeQnRdZWvX1BvavOYKLhxPlaweiVqtp1bsp3d/qDMCfc7YxffjPVKpfnpnHpqJS5UXn0lMyuHbqJiq1pGgKaO00BNUKZM33f5KfUsH+nNwmi5S/8fXL2DvZcWb3eU7vPEf07RjSkjOY8/4SAOwcdGycu43MtCzenz+MZwa3o2LdIBp1rkfM7Vha9mpisfb+NUdYN3MLLp7OpMSnotaouHstihN/neXEX2fp8kZ7AquVwcnNEaPBSPlagYya9TrfvjqLO9esRb9dPJ0pXSmAXu8+y9j2n5GdqcevnE+hzieAwxtOMvvU13z4zJckRiejzzLgXbqIzC4JC4tBn6VnxPRXeWZw+8KveUiIEjyBQCAQCB4eGakZvFlntBIAXDd9CwCu3i4YDUYcnO0xGoxkZ8pOjri7Ccx+ZzHXT4dSrWklfMp4UaNFFVr0aEyr55sC8GXf79m76jC93unK0O8HWdwvOjyW+MgEzuw6r9wzsHoZLh25SkJUojJPa6chJSGNxOgkTu0IYdKmDzm3/xLxkQlsW7yHfh8+z9aFu1k7fbNyzeKJK9HqNMwL+Y4ylUvRqlcTdq88gHdpTyrWC7LYx6KPVnAun85nQAU/1vywkZsht4i8eY92L7WkauOKSJJEmcoBlKkUwFszXmPhRytITbDuHuxfwZfg2uWoUCuQyf1+RKVWyZ3vivDA7F5xgI9/f58vX/wBk8mEm48L6Sn37/BnNpkxY8bNx5X35g2lefdHK5HwpJfgCQeUQCAQCIgOj+XkdmsR67TEdNIS0+WOIrXKce10qCLMeOviHQCMRhPTD03G3tGy1eylo3JU68bZW2SlZ1mkfH/UbUpeBCnHoRJQwY9Pe3ytzKlQK5BZp74mOTaFrwfNxNnDmTptqpMUkwzI+gbOHs44uTniH+RDbEQ8QTXLKkZYaqJsgOjsdUzeNN7mcy8Y/ysR1yJx93XDzduFZwa3o1Hneuz9/TDBdcrhG+iNVqdl+a3ZrPpmPe+1+RjPAA+bzieAlPhULh+9xjstPlLG7uV0kCkMSSWx/MvVJEbLz2XINmAyFKEzkGMsla9djtCQW3iV8qDza+1Fq1+BQCAQCP7POLb5NNG3Y63Gk2NTSI5Nwc3HlbJVSnH+gOysMRlMipamg4sDv96eY3VtbtbRxSNXLcaTYpMZUvt95fpcfEp78t3reev0ercbQ755mYuHrjB3zC807dYAjVZDcO0grp8KVUS4KzcMRmevxdndCXsn2UbRZxvITJMlGspWKc3PId9b7S/mThy/5nTpK1M5gNTEdIZ+N5DwK3e5ez2K9v1bA9CuXytqt63B92/MoV/gMAzZetKSbTuIom5GExUazcF1x+XfyWi6r6aTSqNmzvtLlC7M106F8sxr7bhxJqzI6/zKeXPvViy1W1d75M6nfwPCASUQCAT/cUwmEws+WKZ0XbNFSnwqKfGpVKhTTtFpKlXBl77jelCxfnkr5xPAoM/7Ymevo07bGlZ6A/H5omi5DpXbl/Ja9qrUKtr1b8WZXedp0LEOU7bkOXQ6DGhNzZZVcfVyUbqTLLj0I9kZ2Ti7O+Ef5EvkzXt0fKXNfZ/d2d0JSYL6HWrz4bJRyvgfsYss5jm5OrJt8R7SktLJyrDWtnJyc7Qy2IrL0O8HMvudxXkDErTq1QST0ci6mVvR6DQ2M6ja9GnG7Ut3SEvOIOFeEv5Bvn/r/v8IUYMnEAgEAsFDITszm58/WFbknKSYZJJikqnfoRandpwDoMdbnXF0daDZcw1tXjNuyUh2Lt/PcyM6WYxnpmXZzPA5k6M1BeDh54ZfkA/hV+5Ss2U1ZhyerJx7b/5Q+n7Qg4AKfgDUaF6FVVHz0eo0aO20uHq54O7jSsV65Yt8JjsHHc4eTqQnZ9BvfC8Le+7Fsd0t5poMRo7n6FtRMJlHkvU8FUdTCWwRnb2WTq+245ccCQYAd19XXpvSj9CQW1w5fgM7Rzuy0rOsrnuqbwtWfrWe8Ct3i3/DB8kTXoMnHFACgUDwH2dK/x/Z89shAItObLaIuJYn4u1bzrtIJ49vWW/enj3E5rlxS0fyac+vLR1ROfgF+dDl9Q7M/2A5kiQx68RXVsZKfmdLWnI6ao1a0YSq07YGddrWsFr37J4LGI0m6revBcji41eOXwcgJT4FgMvHruFf3hd3H1ls/cKhK2z+eTtxkYnE3pV1D/KXIeaSkZqR1yGwQIlcUWh0auq2rWnhZGrZqynHt55h3cytlK7oz5glI5j7/lJcvV1IS0xXopzrZ27FqDdi1BtZ+ukqxi5+q3g3fZAUN81blOAJBAKBQFBsMlIzeLPumLws6vvYFrlZ6SCXzDV8uk6hcwuzk/zK+TB82qvM/2AZWemyLSipJKW7Xu021fEq5cGstxfh5u3Cqqj5FvIKKpWKMpXzOr4lxiTh4uGsCJJ3fNnaZjQajBxYe4xy1csQVKMsAKd2hihldKmJqWRlZHHtVChVGgUrXYm3LtrN2d3nuHkuny5nwd/HLGeBpSVal+Tdj4AKftRqWdVirPuIzkx9eQZXjt+gdZ9mtHq+Cb9O/oNqTStx+M8TJEQlkZ2pZ3eOTR12PpwT284W+XfxUChBCd7jsM9EFzyBQCD4j5Obil2maimLFr6AVTTJaMg7X6F2EAb93xO+jrwRpTifHJzt+XD5KFr0bEylBhWY+tdEyua01lWpVWjttYWuc+XEDfqWGkL/csOIvl14qdu5/ZcY3e5TxnX8nBM5elJ38kWmwi7c4bev1zOy6XiG1R9LdqZseH3/xmy2Ldkra1AVNGwkUOV0nTEZzfeNsGntLGM+kiRRs1U1FoxfjtZOg1+QL2qtmgOrj7Bi6loAIq5HsX/NMaYfmsx784bS4Ok6lK7kDyB368v5+ymOJoFAIBAIBIJ/B4nRyUTevAdmqNGiCphlu0GhgH2WlSHLD0gqiVIV/f72fW+cCVOcTwEV/Zjy1wQqNwymRY9GTNn6ES4ezgDYOdpZOJ8Ksm7mFvr4vc67rScq3ets8eukP/jyxe8Z1Wy8Ip1wLzTPnrt+JoxPn/+Gd1tNZOrLMwCIi0zgu9dmsWPZfovuybnktxvTkkrufNLoNNRpW4Mfh/+Mk7sjvoHeACz55DdO52SZ7V9zBHsnO+ad/S5HFL0Vjq5yVn7CvbxOyXeuPqYsqCcY4YASCASC/zhO7o4AJN5LsnAwATR+pp7FsUolUaNFFcpULsW0ofOY0G3K37pnvQ61cfeVs4zMmPl60E9gNjPr+FeoNSp0dhq+2/MZs09+pXRLscWN06FkpmeRHJfC7cvWL/n9a46wfNIasmxkdZWq6K88e0x4LOt/koU9k2JTlI4l1ZtVsboul25Dn8bT36PYz6zPMqDRqdHoNEiShNls5szO8xzbfJqMlEzi7sYrDkCzyawYUH/88CdXTtzgm1d/YsnHv2E0mGjYqa68qBkadKzNsAIioo8Ks7n4H4FAIBAIBMXDxdMZuxx5g0s5Wk25jhxnN0cCKvhbzPcr502F2uXw9PdgYMWRrMwJZJWUjq+0QaOVM5bSk9KZ0HkK7fu34tM/xnLzbBht+7bgyz8/YHq+0jtbXMgREL9y/IZVFzijwcjq7/9k68Jd1mVzQKPO9ZTxkD0XuHDwCgCxOR34XDycCKxWutB7j144DEmds0Ax7A9JJaFz0KJSq1CpVRiyDWyY9RcRVyNJS0yXA3455AYbzSYzUwZMJzk+hdFPfcqaHzZSp21NylUvq1QS9BzVhS6vP44GMU+2fSYcUAKBQPAf5urJG4SGyOnL+buG+JT1YsziEdy6JKd0Syr5RW7vZI+btysunnK527UTN/7WfT183ShdSY7QZaZmYdQbObT+BMkJqYxo9AEfPTuVM7vOU75WuSLXadu3Oe36taL/xF4kx6ewf80R5VzkzXt88cL3LJ64kkuHr/Lt7k/5esfHSiq0vaMdX2//mBotqiCpJGLC4wCYsPIdnNzk52vzQjO+3vExn6wejYe/m8W9N87eRuyduBI9tyHbiCHbgNlsRpVjHGl0mpxzcjaZ1l5LhwGtKVM5AJCNg7ebj0efc97d142WzzfGyc0Rr1IejJr1Bn7lfEq0jwdFbqeV4nwEAoFAIBAUjxVT1ir6QiZjnpegfofavPzZi8TesRQm12fpqVivPEmxckOTS8eu/a371mheRXF0JcWkyCVyfxzl/MHLjGo2gfdaf4y9sz1eAUUH4F4Y253m3RsxZtFwNv+8g6sn8+zFbUv2MHf0Ur57fTa1W1dn4qr3mHFksiKlUKF2Od6fP4ygGmWJCoshIzUTNx9XPvhlJCA74l755AXmnv2GQV/0tXJiTek3HbOxOJ4n+Q+zyUx2ht5KmDzX9tVnyfaXh78b/T/qhYOLPQDpyRm8XuNdHHL0SAOrlaZq44po7TTUaVudId+8jM5ed/99PGBKYpuJLngCgUAgeKRcO3nTaiy4bhADP3uRKQOmk5FT2pXb+S45LoVD649TpXEwKpVESmIa25bs4emBbQu9x9k9F9i98iDdR3SifK1y3LoYzp5Vh7h4KK/7SmC10jw3/Blibscq5WQFhR1BrvnXZ2bT9c2OqFQqpg+fz65f91Oqoh93r98DYOBnLzJgYm+c3B1x83YhMSYZDz831vywEbPJTHJcKq16NUGlUlG5QTBDvxvIyKZylzyfst6c/Oss4Zci8PB359vBs9DqNCy8/CNBNQJJiDpXrN/V4OeKwdcFuytRSDY0o/L/pgUFxo0GIzt/3a+cl8dM3DgThoOLA37lvJk+fD4mo4mWPZtQKtgyCioQCAQCgeDfzZ0rEVZjHV5uTXCdIGa/s8jq3O1LEdy+FEHtNtUJ2XuRE1vPEB0ei29Z70LvsXHudu5cieDlT/rg5ObE2T0X2Dx/B8bcTrwS1GpZjVe/fInzBy4rjqmCWqEZaZmsn7GFCnWCaNy5HvpsPZ89/y33bsVw40yYrGMlwcyjU6jSsCIBFfxQqVXo7LUkx6WwbuYWSlcKoPPgdkrm+TOvtiP6VgxhF8IBqNWqGr989jstn2/C/jVH2PHLPspWLc3Ci9NYMfkPm5nu9+U+Pqr8dphaqyYhKon1M7eSkZKpjCfcS8K7lCdObo5kpGbw1+Ld8v4Ht0ejFa4WW4hfRSAQCP6jnNx+lo1zt1uMNehUh4ZP1+Hj7l8pY5JKsngJA4SG3MaUM7Z+1tYiHVCT+/9IfGQCty6GM3bJWwxrMM4iHdvN24UfD07C2d2Jt5p8gFFvxNndiYFf9FXm/P7dn6z54U/i7iYAsPPX/bR5obnSmjjmTrwyd8knv+Eb6M3TA9sy/8IPJMWmcHb3eQ5vOAHAkY0neeOrAbwwRu6kkiuOCVC2SgB/ztkGQNUmFQHQ6w2c2nGOCrUCOb3z/g4os0ZFWvtqoFFhdrLD4Yi1k09+blcSY+RIJZKs7aBSqZQyyIr1y3P9VKgyPy0xHbPZzN5VhylV0Z+716Oo0ij4vvt5qJil4glYigwogUAgEAjui8lkYvvSvZzckWdvaO00tHmxOc5uzswdvbTI63P1LbMz9ez4ZS/9xveyOe/WpTv8OGweIAt1l64UwFevzLCY0+iZukzeNAF9tp4x7T8DZAHzRjnyDEaDkamvzOD0znMkxSQjqSQaPl2X7iOfUXQ+E6LlPzHD+20/YdaJr6n7VE0WX5mO1l7LrHcWcW7fJc7tu8TWBbtkJ1Uj2f7S5sseirkTx5Vj19n+y16qNa0kj4XHcvdGFEG1Arly7Pr9ftpi4+rlQnJcinIsqSTUahVGvZG05HRcPJxJSUhVzuc2qdk4ZzuOrg6YDCZFUP2xUFzbLHfuI0aU4AkEAsF/kDtX7/LhM5O4flp2cNg721G5UTCnd5xj3phfLOYWdD4BGAxGfMp4odGq6f1utyLvVbVxxZw/K2HINmAsIFz+5ncDcXZ3IvxKBFdzMrK8Snmgs8sTkfz92/Wy8ynnPXnh4BVmvb2IRp3roHXQos+01Be4fjqU41tPM7TeGFZOXUv9jrXxDfQmV7/z/MHLiqMnoIIfXqU8QIKk+BRF5PPKsZx0cTPMfX8Ja6ZtyrtBUe9roxkpJxInpVpncQGo1BLl65SjSqNgPPzd8fBzx2wyK3vS2mmo164mOgf5N2jbtwWeAe4AOLrYM37525SuHMCqbzfIIqWPiSdZY0AgEAgEgn8bW+bv5NvBs5QscN+y3vgG+rBj6T42/7z9PlfLupqOrg64eDjRunezQud5BXjgU9YLlVpF5YbBZKZZ2yujFwwHYNviPYp9UqlBBeX8nat32bPyIEk5wTSzyczxraf5pMfXvDpJDiJmZ+iVhi1Z6dncuXqXXz77nbdbTODwhhM81bclDs72yppn915UvtdsWRWNToNaq1a632GGy0dlZ1NmWhbvt/3EwvmUazf9XRyc7aneogqBNcri7uuKq7eLXKKXqUellrB3sqfXe10AUGtUdBnSAXsnWasruE45Plw2Cq29lp8/WPa3G/X8U4QGlEAgEAieOHQOljXpmalZXD1+A5PRlCOAXXSCrMlgIuZOHIuuTOepvi2LnPvx6vf59I/RhF+O4MLBy4ya/YYiQA6wd5XcrjYlPlVx/vR8p6vFGn1Gd8e/vC9SPs+PGZi+/iDxTctiyhHM7DuuB73e7Ub/j3qxbekeYiPi2b50L27eriwPm834Fe8CcHjDCSX768RfZ2TnlhlunAqj74c9CaxW2qJrS8EucxqtRjGoCiKZzbhsCsF5Ywj2561T6EHWczi94xxXjt8gISqRhJxIYS76LAO/f/sn2Tldbfb9fljJ/ho+7VXi7iYQcTWSqNBoTu86b/MejwRzCT4CgUAgEAiKxDmny1wu0eGxRFyLBOSsJo1d0fZZQlQSTm6O/BG3mDKVSxV+H3cnFl76kTemDmDj3G1UqBNIt6EdFeFzkDPGAZJzsn3UGhXPDeuknC9TuRRt+7bAp6yXxdpGvZF5o/OCmSaDiYGfvchrk/vRtFsDNszaSsK9JDbN20ar55uwIfkXug7pAMD8ccu4dVEuu9u5bH9O4NLI+QOX6DP6OXzKelsERnOFyZXnytHw/LtkpGZyZMMJbl8IJzE6meTYvEwok9FMRkoGv3+7UX5Og4nN83aQmZaFWqPiw+XvcHJbCCnxqZzaHqJoiz5ySmKbCQeUQCAQCB4FXgEe1O9QC5Xa9mtAn2kdtbFo/4ucpZMUk2Q1ryDZmXqWfbmGo5tP8d3rc5g+7GcSo/OuO7rpFEs/XcXbLT5Co9MwbulIur7ewWKNPu8/ywtjuls4hfSlXElvXJaMmv7QqCzepT3xLefN0O8G4ubtqgiJa7RqRUOgWpNK2OcYV545App3b1hmEDXoWJsFF6bxyqcvyJlYNqJpBr0BU45Ggr2THe36WzrhpGwj6viStf4t+Hfh5u2CdxlPAAtRzCvHb2AyGalYN4hmzzWkde+mJbqPQCAQCASCJ5PqzSrjH+RrZXPlYsi6f1aNpJJIS06/77y0xDTmjlnKsc2nebv5R2ycu91Cf3PRRyt5p9VHLPzwVwIq+DHtwJcEVPBTzqs1aib8+o5iT9nC3smO8rUCqd+hFn0/6IlKpcLZU3ayJUYnk5BjD9ZrV0uZ7+gqdyi+ffmOso6dox39JzzP/PPf06ZPM5w9nGwGAuPzBfQ8/N2p27aGxfnC7N6iKGgHBlYvjbaAI9BoMHHnehQunk6Uq16GF0Y/Z/FbCfIQDiiBQCD4D3Jyewgnt4dYODbyk9uhLT/5X8CSSkKfZWDWu0uKvE/I3gv08nrVQsvIVKCkT61RsWP5PkAWtiysbr5eO0sjQpuSgV22EQ3glmYgNiKe6cPnKxlBdjnaAQa9kc97fweAXzkf5l/4gdGLhjOp7/c8rXkBr1LuBNcrr6z79aCZPKN7kWObTrIsdBatnrfh4Mn3CJlpWexafqDI38HZ3VH5rnPQKfpS+anRvIry3S/Im9SkdGLvxFvNc3C154s+33P9TBgVapdTusY8Dp7kLisCgUAgEPzbWPvjJqLCoi0Cbvmx5ZfyKu1pcRx9K5bfv91Q5H0WTljBS2WHWg4WuKW7rysXDl6R17wdS9XGlWyu1aZAqZ9Gp0FSSTi42GMymQk9d5v3235CRpos3q3N6f4bdzeBue/LdmSbF5oz++TXdH69Pf0Ch9Ld/RV6jOyMq5fsrMpKz2Jg5VE87zUI33LerI1bjHepojvxJUQlcmbvBctHNFvavZ751nD2cMS3nKVou1qrxjcwr9Nw1aaVuHT4mtIZLz+hIWH88vlqbl28Q+Mu9Yvc28PkSe+CJxxQAoFA8B8kuG4QPmW9cHR1sDqn1qr56dhU6raraTGelZ7XYSQ3/Tm4TlCR99n08w70OV3e7Bxtt6J18XKhz3vP4uzuRIOna1Mxxxl0/K8zjO34ObtWyM6dxJi8NGgkkFL0+K8MwWPWEVLO5kXJknNaEL866SVqtqwKQEAFX+W8XzkfQkNuYzTI5YYzRizg+rlbZL3QgOR+jbibko7RYOLy8Rus/m4DB9cfs9ivq7dlenxxyDW6QHay2eo+eG7/JeX7vbBYjPoC3fNU4F3GkxrNq+Lq5aI8y2PnCUzvFggEAoHg30iDp+ugs9fi5uNqdS4g2I9V9xZY2SFxEdbBqgq1yxV5n80/b1ecXPnL+uzySTT4lPWm82vtcHJzpP9HeWLmv329ng+e+ZKbIbcASxtHpZYwZBuQJImMlEylY57RYFKyqz79YwzuOc+XP0uoYr3yHN9yGoD05AwmvTiN5PhUVGoVaq2apJhkjAYTa6dvYe6YpUQXKHGzaWea82U9SVDA/0R8jrwBQFpSBtG3Yi3OG/VGRdgd4PKRa1a30DloCa4bRFCNsqhUElo7Le5+blbzHilPaPkdCAeUQCAQ/CfxCvBg7OK3aNCxNlo7y9RiJ1dHUhLTuHTkapFrSBKMmP5qkXOeHdYJD3/5JZzfgVWpYZ6IZeK9JI5sOsna+MVM3TpRGV/00QpO7zynRMcO/HEkb+Gcl2ZGUgZSviyuPqOf4861u0zqN43TO8/RskcTAFISUjEa8xw6L47rgbuvK46uDhiNRowejqQ76zDaa6Ci7NRxcndkwfgVZBYQEk+OTcUWWjsNkiShs7cu2fP0t4zSKS2OS4IJYu/EM/vdxcw79z1zTn9D59fal3wdgUAgEAgETyQNOtbh9akDqN6sstW5wKql2bZ4Nyk2Svzzl+xVa1q5SAFygAET+yji2fnL+qrny8Y+vuU0ZauWYV3CEl7+uA8AacnpzP9gGSe3neW3r9cBsk5lLiajOefPPDtHa69l2LRBrPpmPZP7TcNsNit2YH5JBoDBU/pj72SHh787JpMJzPJaRr1RaQDj4GTH6u/+tHKg5Lcz85MbtHN0sQ66OuQbs9V0pzhkZ+i5cSaMwxtOsODiNBZd/pFy1cr8rbX+CwgHlEAgEPxH+enthexfcxSdvVaJGjXv3ohZJ77i21dnFfoiz0VnbzujKT81W1Rl/rkf8Ckrd8xr2bMxPUZ2JiPJUtS7oIMGoO0LzdHaaXmqbwsAjuVExfLzwtjuikEiSfDHj5tYPPE39qw8yMfdv+LMHrkcL+JaFD+PW8bnfb4l9m48V45dIzE6mfTkDFQqiZdebUdAchaa8ARU5yN5a8ZrNOxYR7mPRqe+77PqswyYzWaadKlndc6W0fN3cfVyxsPX7b7ZZ4+CJznFWyAQCASCfxsJ0UnMemcRhzeckJuvqCUklcRLH/Zk+I+vsuCD5TYdJflL9rIzi7bfAHqM7MyXGz9Ea6fFw9+dZs81YuDnL3L+wCWLeV45HXhzcXRxoOmzDbB3tKNlTznIF54vQwjAyc2Rti82V441Og2z3l7E79/+ye6VBxlabwxh52VtzmunQpnUbxo/jVqI0Wjk7O7zZKZlkRCViE9ZTwZ83Bt1TqMZtVrN/Is/oC2G/ZmfxOgk1Bo1LXo2tjrn6vXgZAzcvF0oU7nUY89Of9JL8IqW0RcIBALB/y0NOtYh7Hw4aUnp2DvZobPXErL3Akc2nkSjvb/DJSsjm8ib0ZSpFFDkPFcvFxZfmU52ph5ndycWf7ySOzkdXcpUDqDHqC6EX47g9uUIAquWVq57YUx3XhjTXTnu9W43pr05TzmWVBKdBz9FxNVIwi6EE3XznlXZ2sUjV0lsV4bMhv4s3XwYp/NxRIfHcedqnrGUnWng9683IKklXHIid0s/XUWVxhVp9Ew9SlcOYN30zff9PXLZ/8cxq7FbF+9YHEsqsHO0JzM102pufp4b3onrp0O5eFjORpPUEkE1yrJv9eH7RjcfCcVN4RZleAKBQCAQ3BdXT2eCapYl7Hw4UaHRaO20aLRqti3dS40WVYu1RkGHUGHUaVOD36N+RmunRWevY3ijcYq2Udu+LShbpRSh58NJT8lQAmmSJPHF+g8s1mnQoTbH/zqjHNs56Oj93rPcuxVDYkwykQWavWSmZWHQy/cJPX+bK8evA5Cemsm2xbuVeTHh8Sz7fLVybDQYmdhtKnWfqkF8ZAI+ZX3YvnRPsZ7VaDCyfcleq/F7YZYld45uDqQXCJIWRKNV8/y7Xdm1/IDShc+3nDfJ8ancDLl13/LHh05Jyuseg30mHFACgUDwHyMhOonlX6ymSqOKePi5kXAvicw0ucwsO1PPlgU7qd6silV3uIJIKomPnp3CSx/0pELtcty9HkXLXk1Qq62dVzp7nZIxFXlTXletVfPlxg8Z/dSnxEbEc3TTKRo9U5dbF+/w1ozXKF8z0GINRxdHi2Ozycyqb//k4DrZ4WNLmDM5NoWkVtUx69RIzQNwOh/HlWPX0eisX39mY95bODkuheNbTtOuX0teHPMcu5bvIznOsvROa69Fn6kv8jeyhaSScHSxJy2fgaO10+LgYm/R7hdg8887MORzqnn4uLFtyV52LNtPk671sXOwQyAQCAQCwb+fy8eusXXBLvpN6MWU/j9iNpnRZ+nRZ+nJSM3k9M4QvEp5EGOjQUl+JAlGNP6Ad+e+SWxEPA4u9tRpU8Pm3NyOwZCnJVWmcin6juvO0HpjAbn7rr2THRqtitELR1hldds5WdoiKQlpzHp3MZeOXLOZAa610yiOrlyNKIAzu88V+VwmrYqTnX044pXJrHf64JVssumAklTS3yqns3PQkZFiGRj0KetFbES8xXoGvZGtC3ZZ2IXpSRlsmb+T8MsR/LDvixLf+7+EcEAJBALBf4xfJ61h/U9bkSSJkbNeZ/qwnwE5ouMb6M2ti3dIT8lApZaUWv7sqqUwVPRHe/EO2pvRgOwAirgayeKJK0mKTUGfpeeNrwZYZC3Zote7z+Lu44qLpwtIEhXqlCM2Ip6o0Gj+nL0NgPUztvDO3DctrmvRszGNOtXlxtkwVGoVtVtXp02fZuxYuhe/IB86v96BCwcvExsRz9UTN3h6UFu8S3kya98xUut4U+ZqKmadBkO2AUO2ZfcStVatZE/ZO+rIzCk/DNl70aJLTGD1MtzOyWYym3L0DSRKFEEym8wWzidAMTALYiiQ0dW6TzPWzdhCxXrli1UC+fCRUGog7ztPIBAIBAJBYXz3+mzCzodz7sAlWj3fhH2rZe1LF09nHFzsWfPDJio3DL6vAyorPZurJ24w5/0lnN1zAUmSmHF0ClUaBhd6jdlsZsSMwZzZfYEKtQJxcnNSgpSnd4Yo81r3bkbbF1tYXPvmt68QfiWCtKR0JEnihTHdSYpJ5uKhKzTp1gBHF3v02XoOrjtOenIGI2e+zvZf9nJun1zuV752WcLO37ESAIe8YJ9aoyLLx56sQFnP6ceFG8mcc0KZV7VJRS4flTOptHYasjNKHiDMyrAuXYwpIHSeS37nk52Djhotq3J040mqNbHdKfDRUlzbLHfuo0U4oAQCgeA/RtXGlZCkrZSpHIA5RyRSpVHRvGcTYu/EcffGPSJv3KNmy6qcP3AZAENFf8wOOgwV/GQHVD6nS0p8qpJ9pNZYZz/NeW8xFw5f5e1Zb3D+0BV+GrlAiU4t+eQ3XvmkD0mxKVw5dh2v0p4Ysw20fqG51To6Oy2vfzUAtVbNmV3n2bJgJ/psPSvvziMhKpE3ar2H2Qz+5X15ZvBTvPH1y7h6upD4ZjKbp+3Au4IvkYU4nnq/2406T9Xk2qmbLJqwApDXiQqNtph/++IdZe+G7BznUEmDbAUcVnaOuvvqbeXy55xt/Hh4EpXrV7AQHH1siBI8gUAgEAgeCFUbVyLsfDhVm1QiM6eznKOLPe37t2L3yoMA3L0RhZO7E2mJ1kLkBYm7KzuqJAnUakvp59TENKa+PB2AD34ZxdSXp3N00ynFxpEkic/WjWHqyzNIT87A098dF09narWubnUfv3I+jPrpDUpX8mfRhJXsXnmQsUveouc7Xdg8dwcLxv8KQI0WVanbtgadXn2K9v1bMbzhOMKvRJCamF5oxtLHq0eTEpvCxcNX+HPudlz336V060qkrthn4ci4dipU+f53nE8A9k52SkUAyPqfiq1XBFkZ2dy+FM6vt2fjU8b7b937gSJK8AQCgUDwJNG+fyvqd6iFk5sjM0cuBOQOI/tWHbKYl+t8AtBevCNnQF3O0RXI98JSa9V8vf1j4qMSadqtgcUacZEJrJm2CYAPO0/CyU0uo8tvaBxaf5zv933O1ZM3qd6sMlqddRc5gLN7LzCm3Weo1CpMJhNmk5mJz36FSq1CkiBXfzMqNJqtodGYzTB6wXCSYpIBiLyZ50xSqSSCagbi4uHM2b0XkFQqGnWqS6NOdbF3tCMhKpGub3bklYpvWRlFRaV1O3k4kZZwH6PQbGnk5OoggOwINOV0yJNUEs2fa0i1plVYNHEFRr0Ro97I3PeW8OPBSUXfQyAQCAQCwb+K934eyiufvoB3aU8GVhoJyJnQ62ZsUeakJqYV22ngW86HkT+9gYOzPRXrlbc4d3TTKY5uOgXAu60ncvd6FJBn45jNZi4fu8GCCz8QGxFP1caFZ/b88tnv/PL577h6uZAcJ0sJDKo00sqhc+HgZS4cvExw3SBa9GxMWlI6JqOZmNt5WUZqrZrWvZsRsvcCidHJqCSJjq+0oUXPxjg42xNQwQ+v0p58krTDYg8FNUAL4ubnRtK9pCLnOLg6KPvNXyYIoLHTKN0C7Z3s6DCgNSajic3zdwIQeSOarQt3K90C/1+ZPXs2s2fPJiwsDIAaNWrw8ccf07lz52KvIbrgCQQCwX+Qe7diGNH4AzLSMmnSpT4B5f2KnK+9GY3DthA0dyxTkWu1rs60A19SpVFFmj3b0Corx8PPjbYvNkelkkiMTsJoMKLWqPEq5YGkkuf2fLsLDs4O1GlTo1DnE8DeVYcxm80YDUYcXeyVcZPRhDHHaVMq2D/v3r5ugOy4Kkjbl1pSoU455dzKqWvp7v4KYRfCuXryBqlJ6Ti6OvD9ns9o1r2h1fWFZR/d1/mUQ36DzKjPa1Wc63wCKFu1FAM+7kOnV9uy9PpMAoKL/jt6LJhL8BEIBAKBQFAokiRxdNMpXq36Ns27N6JWq2po7QrkixTnfSpBz1GdGb/8beq3r2WzLKxe+5oEVisDQNj5cMpUKQUSBFaTm8GotWq6j+yMd2mvIp1PAPvXyKWCGamW8gL5bR2vUnndjv2CfIgKjVYEvPMzatbrnNt3gbi7CRgNRiZ0nczQ+qOJuB5J+JW76LMMNHy6Dm/PGUK5GmWK8WPI3M/5BJCcE7AELJxPgOx8klAkIAZP7ke/Cb344cAXSuOegvIOj42S2GYltM/KlCnD1KlTOXHiBCdOnKBdu3Z0796dCxesbe3CEA4ogUAg+A+ydcEuws6Hs2flQY5uPkXkzXto7Qp3/hTGuX0XSUtKL/S8SqViwop3eXFcDxxdHeg5sgtbslYwcubrSpTtxF9ni3WvkBxnkZu3C/NCvlfGJQkqNZQje3dvRNHombpUbVyR6PA47t2KIaCCr9Vau5bv5/Yly8506ckZrPxqLTuX7WfjnG309n2NY1vPULqidZe//O2OHzQ6e9nYvH0xggldp/BSmTcZWGkkaq2agAq+RIfH8t1rsx7qHoqNWSr+RyAQCAQCQZH8/t0GIq5Fsn3pXs7tv0R6ctHdcm1iho1zt+PgbF/oFE9/D+ac/pp67Wvh4efGyJmvs82wivrtawNyRtE5GwG8giTcSyTsQjgA9dvX5tVJLynnHFwccPd1BeTMrYad6lC9eRX2/HYIdz83dPbWduePw34mJd4ymHfjzC2WfPwbRzaeZPZ7i+kT8HpOWaCH1fX/BGO+IKAtNFoNJqOJY1tO89GzUxhQfjgfdZ1C6coB+JXzYeev+/lzzrYHuqe/RUlssxLaZ88++yxdunShcuXKVK5cmUmTJuHs7MyRI0eKvYZwQAkEAsF/jP1/HOXmuVt4lfKgXsfaZDauQHrHmmTaMATsne1sdpfLT+j529wMuVXknMGT+vHx7++zY/k+fvt6PSnxqahy9Ah2rzyIyVT0S99oNBJUMxBnT2dKVfTnyvEb+AX5ANCgU128/D2VuVFh0Vw+dp1dv+7nlYpv4RXgabWeWq2iWtMqFmOSSo48OrrKHVvMJjMrJv/B6u/+BMBkr8Xg51pksEijVSuZXX+X7My8CFpyXAoGvRFDtoE7l+8SeTOa2DvxbF20m3u3Yv7RfR4EZnPxPwKBQCAQCApnySe/Yedoh1cpD6o2qQgUHvDKdezkR5MvW0qfbSD2bgKRoYV3NNbqtHy9/WOef6cbs95ZxIltZ8hMz3N4/fL56vtvWpKoWC8IVy9ZHLxa44pKp+FXv+hLZqqcBZWVnk3kzXtcPHSF37/dQN/SQwiuG2S1nF85b4JqlbUYU6lVhJ67rWSfpydl8PPYXzi9s+iuefnROfzzxi35M5zuXpd/17SkdG5duMO9WzHcC4th1Tfr//F9/iklsc1y//FKTk62+GRlZRV9E2TbfOXKlaSlpdGsWbNi76/EDqizZ8/y5ZdfMmvWLGJjLZXqk5OTGTx4cEmXFAgEAsEjZPa7i7h05BoJUYmcOnIVQ3lfTJ7OGMr7WM3NTM2ycB5Yldj5u7P6uz95s+5ovnjhu0IdSdlZeib3/5FrJ2+ycMKv/DBkDqYcAXR3PzdUKhVpSWkc23KajDTraN/2pfvYu+oQqfGpXDpyjckv/cD889+z+Op0pmyewIjpg6napCJqrZrwXJ0q5PK8IxtPWqzl4unMkhszyc6QX64anYZSFf0xm8ykJqTRfcQzvDtvKK37NEOdk1ZtVklkdKpF5lPVya5ZeMq3QW+00ohy83ahZsuqhV5TFLbSyx1c7Gk/oBW+gU+A0OVDYsqUKTRq1AgXFxd8fX3p0aMHV65cue91e/fupUGDBtjb21OhQgXmzJnzCHb7ZCDsM4FAIPj3EnE9kmVfrCY05BZxdxM4s6to50pidLLVmCFf2VjtNjUYUus9BlUexdrpmwtdJyrsHgs+XM61kzeZ9c5iti7crZzLzSCPDL3H6UL2M3f0Eq6fDiM5LoWjm0+xYuo6Vt+bz4rwOfQc1YWPfn8fv3LeSJJEVFhe4CwjJZNLR65ZrFWpfgUWXJhGak4GVHCdcrLup9FE9O1YJm36kBdGP0ezZ62lEe5Hto0Od637NEWty9c8pwTxQ1cvZ6sxFy9nnn+7a4n39iRQtmxZ3NzclM+UKVMKnXvu3DmcnZ2xs7Nj6NChrF27lurVrcXpC6NEDqht27bRuHFjVq5cyVdffUW1atXYvTvvH9KMjAyWLFlSkiUFAoFA8Ihp3btZjpC3GVIzKavVICVnoLHR/hZArVGh0WlQqSXLSJwE7fo2J/q2fN2+1Uf46e2FZGdZdx/57et1JMfKwpSOLg7UblsDJNkZNPhLOV37k57fMKHrZCb3m2Z1vW+gNyqVpGRNVWpQAXtHe6U8zj/IlzemDrASoXR0dVBq83Pp8kYHJEli29K9ALR9sTnxUYmAHCG7c/UudZ+qQefB7ahcv0JON1sJc+46WutOf4Wh0qhw9XJB/zd1AZJiUpTvaq2aT/8YzYakX/hg6ShUqicgifkhaQzs3buXESNGcOTIEbZv347BYODpp58mLa1wja3Q0FC6dOlCq1atOH36NOPHj2fUqFGsWbPmbz3avwlhnwkEAsG/G5+y3lRrWknpJpydabDQTbKFRqdBrVVjVyC7R2uvoX77WmRlZGMympj17iK2/7LX5hqf9/5O+e5VygOvUh6oNSp8Ar15bXI/UhJSGVZ/LGM7fM4fOU1l8uMfJDupcmUcajSvgpObE96lvQBo0rkebV9sKWt45rPRch04qnzd+d6aMZhdKw4QcT0KSZJo+1LLvGClryvHtpzmlc9eoG67GviXt5ZXKAl2jjrCzocTWLV03mAJbJWEHLsRwM3HlWVhs/gjZhE9R3X5R/t6IPwNDajw8HCSkpKUz4cffljo8lWqVOHMmTMcOXKEYcOGMXDgQC5evFjs7ZXIev30008ZPXo058+fJywsjLFjx/Lcc8+xdevWkiwjEAgEgsfI0O8GMu3AFwBIZnA5FUbZM7dR5xPQtnOyo3rzyji5OWA0mDBkGzAZC7yZzbBm2ma6vdkRVU7Z2Yaf/mJK/x+t7hl27rbyvdubHXl37ps4uzuREp/Kn7P/AlC0pGxpStVvX4ufz+fpPhkNRi4euaocL/54JeO7TAbAp6wXQTXKYu9kx5d/fsjcs99RrWklJbJVvWllIq5FKobQtVM3yUyVs66yM7LZv+YoYzp8xoedJ3Hp6DUwQ/22NXDcdQm7E6HoQsKL8SvLmAwmwq/c5cqx61aOsMJQ55uXkZKBs4cTAIM+e5EWPZoU+96PhIekMbB161YGDRpEjRo1qFOnDosWLeL27ducPHmy0GvmzJlDYGAg06ZNo1q1arz++usMHjyYb7/99p8+5ROPsM8EAoHg343OTsv0Q5PpP7GXMuZVyhMHZzuLeR7+7gTXLY+dgw5DtgGj3kh2tmXgT59pYOmnq3jqpRbygBm+HjiTrQt3Wd037m6C8n34D6/yxlcvYzSYiLkdy7bFezBkG5TsIVv22aDP+/LWjMHoc4KPqYlphF+JACAjLZMJ3Saz6pt1ANRsVQ1ndydKVfRn0eXpfPLHaLxKuQNg52iHb6A3p3fImVZms5kL+boxJ0Yns27GFt6o9R6z311CVKjc2bjTq22L+lkLJSs9m9uXIggNuX3/yTbwCPBAo1Wj1qj49I8x+AVaVxE8Nv6GBpSrq6vFx87OrtDldTodFStWpGHDhkyZMoU6derw44/Wtn9hlMgBdeHCBSWFW5IkxowZw7x58+jduzd//vlnSZYSCAQCwSPm7o0oPun5NcsnraFivfLUaC5rIN2+eIf4yASLuVlpWVw8dJW0pAxbS1kIRx7fcpqp2ycqx5ePWaZUH//rDFUbV0Jnr8Mn0JvUpDSG1Hmf1IQ0VCoVbV6QDaRP/xjDWzNeY/yv79i8Z6lgfyUSdu1UKG83n8AfP24iLSmN5V+uISvHQKrWtDJDvnmZmq2qkRKfyux35JLD3ChPzZZVqdeulhxp1KopX6sc/Sf0stC6ii6QDRay7yIOGdlor99DMhatV1UYhiJaBEvqvJvnjxCmJaWTmpDGsB8GsebHTfT2e419qw//rfs/CfwdjQGApCS5e42np7WeVy6HDx/m6aefthjr1KkTJ06cQK+3zsr7f0LYZwKBQPDv5eimk4zvMonDf56gTe9meJeRs4eunrhBRqrlezIhKpEbZ0IVmwfAnC9AmNs1z2Q0YTab6TPmOeVcfs0kfbaencv307qPrN1TtUklVn//J1Nfng7IDqEm3Rrg4efON7s+5d15Q+n7YQ+b+7dzzHNWyE6i97l26iYH1x7l2ObTipRDu5da0ndcD8pVL0Pc3Xi+GzybmHC5E567jyvepb0Y9sNA3P3c0Oq0NHi6Ng061ra4V+TNaIvjkH2XeZjYFyLkfvviHZw9nRnwcR/Gd5nEoKqjuH054qHu5UnFbDYX256DEjqg7OzsSExMtBh76aWXWLBgAX379mXt2rUlWU4gEAgEj5DV32/k0PrjLJ64kkUfreDCoftr6uRHUoFXgAeuXs68+e0rOLjIL+WI61FM6fcjlRpUAKD7iGeUa05sO8v4zpOYN/YXPl8/luSYZDbN3UFWumw46Rx0vDi2OwB+5XzoPuIZPPzc+Kz3twwoP5zzB/MMC41Ww2tT+lOxXnmlTD/sQrhFG99arasxbslbzBv7Cye2nmHSSz9YZErVbVcTF0857dtkktPB96w8SI+3O9tsU2zvJBtVRr2Rcvm0n7zL/PPOK46ueUZNfuMxV8gzPz+P/YXEe0kkxSQz651F//jeDwrJXPwPlExjIBez2cx7771Hy5YtqVmzZqHzoqKi8PPzsxjz8/PDYDBYaSL9vyHsM4FAIPj3Mnf0Uo5vPcOc95cw4635xN6JK9H1klrCw98Nn0Bv3l8wTMn43rPyEFeOXcfZwwmNTkP3kZ2Va5Z8/BtTX57OtsV7mLx5PJePXmP70rwyverNKlOnTQ1ALqvr8np7EqOTebPuaN5q8gFJsXkaVB0GtOapvi2oULscIGep374cQcydPPtswMTetHy+CfM/XM7hDSd4r80npCXnZVR1e7MjAE5uTqQnpaPP1rNtyV5GzX5DaQ6TH1VO4C7yRhQB+crx3HysxdlLSv6AZG6GPMgSEvlJvJfEko9/IyMlk4irkfz+BAiQQ8lsM8l8//XyM378ePbv309YWBjnzp1jwoQJ7Nmzh/79+xd7Dc39p+RRt25ddu/eTYMGDSzGX3zxRUwmEwMHDizJcgKBQCB4hDTt1oBti3dTuWEwHvdpXavWqq30lILrVeD6yZsAzHhrgdLlBCDhXhLDpr1K/fa1cPPOe/mnxOdpGOnsdZStVprrp0KVsYBgS4cBQPTtWA78cRSA3SsOULOFLOCdGJPEnt8Oos/SU7ttDUL2XmTL/J24ejoTXDeI0HO3uXMtkpM7QmjZswlh58PJztSTnamnVe+m9Bv/PBXrlgfg1sVwrhy7rtzzxYAhSnZVfjLT8iI6V4/fVL7HRiSgUkmyjlYOdg46i4hkQTQ6jUUHlcJaK+uzDbh6uyiaWWCZPXU/TYhHSnH1nfJpDLi65v3zUVSKdy5vvfUWISEhHDhw4L5zC4rk52qWFRz/f0PYZwKBQPDvpVWvpqz8ah2tezXlyokbRU+WkN+pOX9KKgl3b1cSouRM4a8GzrR4L5/bf4lfb8/BwdkeJ1dHZTy39E5SS/gF+eDgbE9GPmdLbhe+/Jz464zS9Thk3yVaPS/LAlw6co2QfRcpXzuQtKQ0om/H8dUrM3h71hs4uzuRmZbJwXXH6PBKa+q0qU7IvkukJsqyDy+M7U7fcT1w8ZCDg5vm7SA7U85avnbyJgMrjbRpZ+SXhYgMy8uKSopJRqNVW9hNKo2EyVC4sZIrdJ5LYZ17y9cux4WDhWdcla5SqtBzj5SSaG+W0AF17949Xn75ZSIjI3Fzc6N27dps3bqVjh07FnuNEjmghg0bxr59+2yee+klWUR23rx5JVlSIBAIBI+Ixp3r8WfqMiRJIjtLz4IPlmE0yC9cSSWB2ay8dHOdT9WaVpLL1yQU51MuBr2lsPY3r/5E8+caUqtVdao1rcSJv85yakcIIIuN12pVjZ4jO/PNq7OUa96Z/YbVPv2DfHlueCeunbpJ59fa8Vnvb7l+6ia+Qb7cOBMGwO1LeWnO4Vfu0qJHY26cCSMhMpHPnv/GQgSyfK1A3pkzBFfPvMyib1+bbXHPgs6n2m2rE7KnCEFFM5gKWChFOZ8AKjeswMVDV4ucA5CZlolKZTvlG6B26xr3XeNJJVdboLiMHDmSDRs2sG/fPsqUKbz7IIC/vz9RUVEWY9HR0Wg0Gry8vP7Wfv8tCPtMIBAI/r28+uVLDPqiL5IkcXD9MYtSuYKOoVyHQdXGFbl89DoqSSLhXlLe6QJ6nWaTmffafkzVRpXoOqQDybEpxITHsW/NEQBqtapGYNUyVG9ehZPbzgKyoPjAz1602mfz7o3Yt/owOnsd5aqX5s26o9Haa4kNjyMuMsFCTwqzbBdVqBNIyN5LhJ67zbstJ1KnTQ3MZjOSSqLjy214Y+oA5ZLUxDQWTVhhedMCDpKqTeTnLmpOQcmDopxPAP7lfbl7ParIOQA3zoais9cqDrKCVGtsnUn//8aCBQv+8RolckD17NmTnj17Fnr+pZdeUgwdgUAgEDx5SJJE7N141v64SXE++ZXz5vWpA/hm8CyrNrU1WlSlVqtqrPlhE0ZDAQ2jAu9zfaaevasOs3fVYcVgCqggZzgFVpO7jGRlWL60Xb2tnRGSJDFy5uuArFuVmw0VHS6npOePVKk0Khp2qs304XkvRKPBxOrvNyrHUWHRHN10ivodanN4wwmadK3H5aPXcu5lGenyKeNFzJ04ToTdI+vZ2uguRWJ3Pa9t8N/F2d2RWxfuoNKoMBmK1pAym8wW2lt12tag7YvNObv3IpIEL+TTc3jsFFdgvIQi5GazmZEjR7J27Vr27NlD+fLl73tNs2bNrPSOtm3bRsOGDdFqtYVc9f+BsM8EAoHg340kSdy+HMGyz39Xxlr1bkrlBsEs+HC5xVydvZbGXetTrlpZ/lq8u+BSVkTduEfk9XvsX3NEycT29HcnPiOb4DpBADi55ZWXObs7olZbN05x83ZlypaPANj88w4lGyr/M+RmHpcK9uPWxXBC9l5SzifcS2LPqkOAbOtcOnqVa6dvghlunAlDUmFRlpeLSi1h72RPenKGtfPpH1K2amnuXLmLxk6DIavojsWZ+fS41Fo1T/VtQbVmlTm68RRB1ctQq3W1B7q3v01Jmr+U0D57EJTIAQXw+++/s27dOvR6PR06dGDIkCEPY18CgUAgeAhEht7jjVrvKRpMSNBjZGdWTFlr5XxSa9Ws/s62gHHBCJCkknD1ciEpRtYEyI3WNe5SD69Snqz6Zj3ju0zi9K7zFut7ly5cVBogoIIf3d7syKWj15Tsp0r1yhMbEU9cZAJeAR78PG55kWtkpGTy9cCZ+JT1IiY8jqqNK1K3XU3O7r6Abzlv7oXJDiatnYbYu7JeQWbtMpg8HMmsU7ZQB5SDiwMZKbZF2gtSs1U1jvxZeAe3wqjUoDyfrBnNK8FvkZqYxqDP++Lh517idR4aJSzBKy4jRozg119/Zf369bi4uCiZTW5ubjg4yEbyhx9+SEREBEuXLgVg6NChzJw5k/fee4833niDw4cPs2DBAlasWFHoff6fEPaZQCAQ/HvZvfIgk/tNU4519lrqt6/Fkk9+s5pr72zP0o9XoXPQWYxLKgmtTmNhn7l4OZOWkIbZbJadTzmle29+N5DDG06w4aethIbc5tCG48o1jvlK9QqjeY9G7F19mOSYZK7n2GfNuzfi5PazZKZl4ebjyuafdxa5Rvjlu4xo9AEarQZ9lp5e73bDw8+d5Lhk7J3sla573mW8rJrDFIZKJcmmien+hoedkx2o5KDX/ZxPBXnpwx7UbVuL0e0+RZIkXvqwJypVieS1Hx4PsQTvQVCiX2nevHm8+OKLnDhxgitXrjBs2DA+/PDDh7U3gUAgEDxgom7ey3M+AfXb1+bnD5ZbRbEgrwxPpVZRuXFFjE0rk9W6Oh6V/FkV9TOe+bSIzCYzqQlpFtd3eb09w6e9yoWDl0lNSOP41jMWGkhGvZH9q48UuV9Jknh79hBmnfiKtn1b4F/el6HfD2TFnbk07lKPmPA4xdkVVDMQtcbytabR5UXwcsXK7Rzt+GbHJ2wzrmLhpR+Zfngy3+76lI9+e1cxWOyvRyNlZGN3xXZKtkotMfPoZFT57le2mu3a/77jenBi65lCnzGggh8anQbfctZlYtdOhvJuq4lKRHDpZ6ssREL/X5k9ezZJSUm0bduWgIAA5fPbb3mGeGRkJLdv57VPLl++PJs3b2bPnj3UrVuXL774gunTp9OrVy9bt/i/QthnAoFA8O/m1M4Qi+MmXevz47CfSYxOtpqbqxHp4GyPb6C3LKMAtH2hOT8emmRhm6TEpVroVWKGsUveot1LLTm84TgpCWmc3nXOYv3IG1H37ejm7uPGV39N5MtN46nUoAJVG1fknblDWBU1HzcfF1m+IYeK9QvPYjabzBiNsr3p7O7Eqsif2Zr9G0uuzWDGkclM2foRrXo2KXIv+SlVMYCfjk+1GPPwd1O+q9Q5v40Eg7/sS/hF288pSRLeZbzQ6jR42QiWLvt8DYs+kgNcZrOZCV2nEHrO2pYWWFMiB9SMGTOYMGECV65c4ezZsyxYsICZM2c+rL0JBAKB4AFTpXEldPZyOVKnQU8RXLfcfUvCTEYTl69Gkh3ggcnLBbsagag1apzdLCNkRoOR8rUDeWZwO3qM7MyQb15GpVLx4tgeePq74+TuSPXmlbFzyovYndl9ruDtbKJSqZjw6zv8cuMnarashiRJePi6yydz7Cpnd0eM+bScVGoVhuy8skGzyYydo47UxDSObDrJ0S2nuH46DN9AL4LrBuFT1getnfzb+Cdk4rbqJPbn79rcj85eh4uHM92GyKKLGq2amHDbXWvW/7TVSo8gP5kZWcw98w2VG1gLfgLcunhHcYyZjCb2rDpY6FqPHHMJPiVZ1my2+Rk0aJAyZ/HixezZs8fiujZt2nDq1CmysrIIDQ1l6NChf/fJ/lUI+0wgEAj+3eQKegOMXjicyJvRRcyWSU9OJ/p2rGIj6Bx0OHs4W2X/qDUqaraqytOD2vLalP50fLkNAC9/+gKOrg44ujlQpXFFpWGHyWQuliYSyN2RZx3/ihlHpuDu44aDkz32jpY6luWql7U4zt/EBsBkMOHs4cSlI1e5cOgyhzYcJyY8lrJVS1O+ViBBOd31dA46pcNfYTi7O1KpXgXK5AiCu/m4kngvz4lnIsdONMOc95cWuo7ZbKZmiyp8sGwUZSr625yTv5t0enI6J7eH2Jz3yCmJbfYYMqAks7kwnXdrnJycOHfuHBUqyK22jUYjDg4O3L59G39/238xtkhOTsbNzY2kpKQSiZEKBAKB4J8TdiGcm2fDaN2nGV8PmsnuFXkOjdz6/YJd2Kq1qMoZkxmzkx26Y9dwBtKTM3D2dCI1Pi/zqXrzKvx44EuL+2Vn6enq0A8Arb0GfWZeFtQ3uz6hbtua993zxSNXSYlPxbu0J/tWHybyxj3Cr95Fn6nn1sU7+fYvazqVpDwO5EwpnZ2Oib+/j5u3C2azmRHNJ5DYMRiTnQa3v66hTs9Labdz1KHP1KNzsCMzzXY3u2IjgZObI2mJ6Rb6Cc4eTlZZZS6ezny58UOqN638z+5ZTAp7X+eOl/32C1QOhQum52LKyCR89ETx3n9IPAj7TNhmAoFA8Hg5uf0sZjPUaF6ZwdXfJfZOXmArV//S09+d+KhEZbx0JX8iruU5ixxdHZQSvPxZ5/0n9GLQF30t7ndsy2kmdJ0sH+R210PW19yatfK+HWTNZjOHN5zAN9Cb6NuxXDp6jWunbpKZlsmNM2EWnYRzCSjvS2To/Z1rkNeROahGWd6ZOwSvUp7sWL6PJROtyxJzsXPUoc8yIKkkq27OJcXNx1WRlsivP+rq5UxyXKrF3OA65Zi6bSLuPm5W6zwMbL2zS2qbweOxz0qkAZWRkYGzs7NyrFarsbOzIz3dWixMIBAIBE8mQTXKElRDjkYd3nDC4pzZbObpQW3Zs1J2SlWoXY5yNcrw5revMLzBWOJz2vzm/lffw9fdwgEVXKecxXqndp7j897f4hvojdZeQ8TVPCOp17vdiuV8Cj1/m3dbfoTJZMbN24WkfI4xldrSOMoNqQTXDcKoN3DpyDW0dhrsHHQY9EZcPJ1JTUiz7CgDGLKNGLIziLkTR8On63DjbBhZpVzIrOwNQGZlb5zORCoOrtwyxpI6n9QalSL+nrdpyMox0vLHhNy8Xa0cUCnxqSTm63bz2HlIIuSCkiHsM4FAIPj306BjHQCunLhh4XwCOQO617vdWPPDRiSVRMV65WnStT6tezXlzXpjlKyn9GQ5+BZUowxhF/ICdMH1LMvglk9aw6+T1lCqoj9mk0nJuJJUElO3TLiv8wlgw6y/mDlyARqt2irT2zPAw8oBpVLLmVgZaVkkRifh7utGRmoGGq0Geyd7UhNTLWQich1Ity6GExDsh6efBzpd0U1FlOtL6HtSqSVMBToI5jqfIK9bslqjstkF787VSIqf1vOQ+X8TIZ8/f76FkWMwGFi8eDHe3t7K2KhRox7M7gQCgUDwwPnt6/VcOXGdIV+/zItju7Pkk1XKOZVaxbbFe5Tj6s2qsHHeNnavOMizIzoRGnILNy9XKtQux/pZWwm/HIGrlzP6LAMZqZlEhVlGtQ6tO0ZaUjppSen8dHwqIxp9AMiZVh1faVOs/Z4/cAlTzlvd0dXBwgGltdcpzhuLa/ZfIqCCL6MXDCMyNJrlX64BIDMtC3tnO6v5Tu5yBtKPw+ax97dDjFv6Fm0aVWXT3WRM9hrsQmX9qKKMC41ObVHyZ4uCxk0uBmPedZIk4eTuSMS1SJtz85cZCgS5CPtMIBAI/r1kpmcx+51FqDVq3vx+IFUaBXPl+A3lvEqtYs00ucOv2WSmdKUAln2+muVfrqH/hF6c3H6WcjXKotao2L5kL2EX7uDm40paYhoGvZGoAllHu37dT3amHpPRxOtT+vNl3x8AOfu6dpsaxdrz2T1yYxmzWbbPcp1fAIkx1sEyk9HE9qX7aN69Ea17N2Xrgl2c2XOBLLJJS0rHroCoOpIswWAymni1yig6DGjDK5+9wNqZm4kNj7eYqnPUkZ1u2UwnFyc3B4vuwrbJlwKWf1QF5hyzy8HZnoy0TIw27E6z2YzZJOyz4lCiErygoKD7ekMlSeLmzZtFzhFp3gKBQPB4iLkTR79AWRenYae6TNkyge7uryhGQ/7uds7uTvgEehOaK1Ce825WqVWUruhP+BVrfSRHVwf6jutJ9eaV+P6NuXiX9uTy0WuUqujPvLPfsXP5fo5sPMFzI56hdqvq993vzZAwhtYbq2QG5TcEnN2dcPV2ydMpKGg7SCAh0ey5Bhxab5npVRAPPzcS8mUWVaxXntem9ufDZ74sdn28c7PKxKokdBfCUSUWI/PEtq3D6EXD+XHYz+hzI2wqsLPX0fu9Z6nWtDJNutQv3oYeAPcrwQv8+stil+DdHvuReO8/JB6EfSZsM4FAIHh8bF+6l68Hydp9Q75+mRY9GzOw8kgwg1qtsgg+1WpdjYuHrmI0WAa9vMt4kpGSqXSPy09ABV+Gfj+I8Ct32ThnG57+7lw9eZMOA1rzzpwhLPtiNfduxTB48kt4l7JuilKQJZ/8xrIvVivHaq0Ko17eY82WVbl05KqS8W0r+9vJzRFXbxcib9wr8j5qjdriOV/55AXSktNY88OmQq+RVJKFDpa7jyuJMdZi7iXl8z/H8fGzX1mM+ZXzpvvIztRrV4uKdQsXW3/QFFWCV1zbDB6PfVYiEfKwsDBCQ0OL/NzP+SQQCASCx4eHnxs+ZWTD4uS2M9y5FknHV9rKJyWo2aoaDq7ySys1MS3P+YSsrwRyBKug88ndR35ppSdnsHDCr4zvPJm716MI2XuR7Ew9YefDSYxJpsOA1gz9fhCntoVw/uBlK+OpIPtWH7EoSzPns18klURKglyD7+BiT6NOdS0vNssRqft1cgFo0rWhhbCls4cTZ3aeUxxElRsGo9aora5zcJZ/K7ME0QEemPw90Fcrc9/75e7P5rDRjLt3nhHQd3R3sjOyWf7lmn+sZ/DAeYJFLv9LCPtMIBAI/t1Ua1YZjVa2M9ZM20ipYH9KVwoAwN7ZjmpNKynd7i4duWZhP+WKesfeibd0PkngVVruWBx5M5qpA6Yzf9wyokKjuXL8BoZsA5ePXkOtUTPwsxfpOqQjG2dv596tGO6Xo3Jsy2mL41znE8iNWXIdTmWrlsLVyyVvSznPkJ6SQXpK0TIGXmU8qVgvyGJMa6/l/IHLgOycqv2UdbaW2WS2sOkehPNJo9OQmZKJWptnC74wtjv3bsWy9ONVeAV4FHH1I+YJFyEvkQPqfsTFxTFt2rQHuaRAIBAIHiAarYbXvxoAyBlEzu6OXDuZk+JthlPbQ8hItm0QmIvILC74cs/NonLzcaV87XIE1SzL8S2nuXXpDm83n8DySWt4r83H9HAfSMi+i4Wu2+HlNlRpGGw1rrPXkhKfSkpcKmqNmmcGt+f4X2eU85JK4qXxPVGpVdy5Ipey5RoNZrUKfaAn7hV8KF3Jn1E/vc7WhTuVl3BABT8+XDaKs3svWNzPylkmwaif3pC/mkF9Nx5MJtQR8Th7OBX+Y9kguG6QvI4kMW/sL8TcicPOQUelBhUIv5anK5CdaTu9XCAoCmGfCQQCwZNNmUoBdMiRJiiV03UtLkIuM0tLyuDSkWtKVk9+cXFbxwpmiItIUA6zMvJKxyo3qkBAsB8uns5cOnqNA2uPMrrdpyyftIaBld7ilYpvkRRbuOOm3/jn8Qm0zpTS2mk4s1u2n1w9nalYr4JFhrmbtwutejXFbDKTFC2POxWwmXzKelOlUTA9R3S2KENs9XwTmndvqIiYGw1GjDae3cHFgZc+6Gk1Lqkl3LxdrMaLItc+c3C2Z3K/HzHqjbh6uVCjeRUlSGs0GO8bUBXkUaISPFuYzWa2bdvGggULWL9+Pa6ursTExBR5jUjzFggEgsfLX4t24xPoRVxEPKu+3UBUaDQanZbUhFSruZ4BHsRHJthYpXBUahVms5nP143j8IbjbJ6/E0mS8AxwJ+6u5VoDJvZm4GcvWq0RF5nAuI6fYzKaCK5bnj2/HbSao+yxlAfx+dfNjXwVKMnDDOktKmEI8ibQ353fvxmMyWRiXMfPObf/EoHVy9C4c32y0jJZN3Nr3qWqwh1w+TvXmXNuU6NFFS4cvGL7Ahv4l/fjuRGdqN26Ou+0/AhDtsFC1LPLGx1o3LkeLXo0LvaaD4L7luB9VYISvHGiBO9RUlL7TNhmAoFA8HjJzMjiz1l/0bx7I9b/9BdHNp0kPiIeJCzEuXMpecdfDYZsA44uDiy/PZsRDcdx98Y9gmoGEnb+ttX8b3d/Sh0belCndp5jSr9pVG4UTPTtWMLOhxd6z4LaUI4uDqQX2LOdo87i+Z4d1olRP71ObEQcbzX5kJSENCo3CKb9gFZsnLuNG6fD7vustkTFJZVE/Q61ObntrM1rbGl5VmtWmc6vtcfDz42Jz04FwNXHleScwOugL/rSoGNtqjaudN89PUiKLMErpm0Gj8c+K7EIeS5hYWEsXLiQxYsXExERQf/+/dm0aRNPPfXUg9yfQCAQCB4we1Yd5NvXZqFSSZhyomlOHo70n9iLFZPWWLWWLanz6bUp/WnfvxVmsxnfst6kxKeyZcEuKtQpZ9E6OJcOL7e2uc7ulQe4dVHu4FK9WRWLcwXr+3OdTzoHHQ2frkN8VCKXj16zXDB3ek4tockM+mw9y79cQ0J0EkaDidCQ24SG5Blhaq0aJ1dHkuNSKIz8cZxcv9eFg1cIrleeG6dDC70uP1Gh95g3eik9R3VRIpn5O8o07FTnkTufioOEnP1VnHmCR4OwzwQCgeDfycwR8/lr8R5++Xy14liq1boaFWqVY+Pc7VZZNlbOp0K0JUF2Pn2z42NcPJ3xKuWJs5sTNVpW5e6Ne9RqVZVbF8It7BkHZ3tqtapmtU52lp5N87aTGJPMsc2nad69kYUDSq1VW8gF5DqfPPzcaPZcI/b9fjhvuzm2XEHnmslgJOZOHCunriUtMZ3sjGzOH7jE+QOXlDnuPq6kJKQVmnlkq+mL2WTm9I5z2DvbkZmalw2Wuw9bjWQuHb7KlePX6fpGB2Us1/mktdPw3PBOuHg4W133OCmubZY791FTohK8rKwsVqxYQfv27alWrRrnz5/n+++/R6VS8cEHH9ChQwfUamuNDIFAIBA8Oexcth9AcT4BpCdlMPe9JVbOp4LUbFmV7/Z8SoOn5VbBuRpI+Tmx7QwJ0YmKKHLHV9qwOnoBFeqUIyG/A0qCZwa3o3TFAKs1ln2xmrnvL0Vnr0Wj1bBj+V4cXOxp8mwD3Hxc6TmyCw071bFYCyA7I5saLatSr31Ni/VU6rzXncORG7xYL5ivhnVm1TcbWP7lGm7ltCrOP8/Nx5Wg6mWLdD4VRVZaFtWaVcbNx5X+E3vT94Me971my8KdNsfz6ycIBAUR9plAIBD8uzGbzRzdLOsq5Xcsnd9/mfU/bS2yxEulVvH0K235Yd8XlKks21R2jpYd5Yx6IwfWHiM7U6/oMI1ZOIJfbv7ExcNXLZxPGp2aUbNeR6WydhWM7zyJfb8fxt7JDiQ4vvU07r6u1GtXAzdfVz7+fTRuOTqWufeRNynRsFNdylQplffMJrNFZ2KtTsNrU/rz2tR+TO7/Ixtm/UVmunXHOd9Ab5w9nP9W2ZvJZKL5s43wLeeNX5API2YMpmXPogN8JoOJXcsPWI2bzXJGl6BklKgEz9vbm+rVqzNgwAD69OmDh4cstqXVajl79izVq9+/oxGING+BQCB4XCTHpfBCwBsYDUYkCTxLeSoaA8WlTJVS3MkRIa/Vuhrn9l2yOU+tUVPnqRqMWTicxOhkhjUYa3Heu7QnK8Ln2rx2Ur9p7FlZeMmdSq3i5Y97s+STVTbPN+lan5jwOO7diiEjLROTwYRKLbfylfemws7BDs9SHsqzAHj6u6NSq7BzsuNeaLSShWTvZIebjyv3woouMbdAgtqtqzNx1Xss+3w163/aiqSWMNuIyhXGU/1aUrVhRZ5/p2vx7/sAuV8JXrmpk1DZF6MELzOTWx9MEO/9h8SDsM+EbSYQCASPj0Prj/NJz68BcHJ3IjsjC31WIdpOheDq5UxyXKoseVDag7g7tu07BxcHOr7cmuHTXuWPHzczb8xSi/MdXm7NuCUjbV7bx/91EqOTbJ4DKF0pgKCaZTm49pjN893feobDG06QmphmUZoHeZIGgdVKc+92DFlpcmaUpJIoUymA5PhU/Mv7cuXYdeUa/yBfEmOSyEyzdlQVhkanodOrT/H2rDd4o/b73LpQeAmhLRxc7GnduxmtejV9pJ2J81NUCV5xbTN4PPZZiTKgjEYjkiQhSZKIpAkEAsG/EJ2DDg8/NwAGfNIH30Bvm/PUWhWFdXVPvJeofL946Kry3cHFHq9SHngGuAOyKOOp7SH8OXsb3mU8lU55ubgWIQT55revUKF2uULPm4wmuQVvIXs8uukUN0NukZaUrkzxC/JRzhsNJtJTMiycTwDxUYnERsQTcTXSogQuMy2LnqO6FLofm5ghZO9F+pYewvpZsp5USZxPAB0HtH5szqdi8QR3WfkvIewzgUAg+HfjVcoDtUaNWqPmg6VvIRVi4OQ2VJFsGGm5Thiz2WzhfPIu44mzpxPeOV2QM1Iy2DDrL0L2XSS4TjnLTCXA3det0H1++scYnN0Lb7QScS2SO1fvFnp+/cytRN+OJT05A1XOfXPts9y8mPDLdxXnE8iZUuFX7pIUk2zhfAJIS02nVe+mhd7PFoZsA5vmbqerc//7Op8K/ja5+3xtSv/H5ny6L/9PXfAiIyMZMmQIK1aswN/fn169erF27Vqb/wIIBAKB4MnD3tGOuWe+ZfbJr3nl4xeUlr8F0eq02MqPlVQSfhX8lOP86c8ZKZnE3U2gx8jOvD61P35BPji5OdKocz3cfdxYcn0mz7/TVTGeNJrC/0fZu5QnM45O4ZM1o2n7QnMcXOzR2Wst5ugcdAz9bqCVE6pcjbIWx7mtgEcvHIbOXofWTkOLno2p3rwyKrVKMS4klURwvfJoC9wnlznvLVG+l6kcUOi8ghgNpmK94Ot1qGX1jBOfm0r4lYhi3Ufw30XYZwKBQPDvpkqjiiy8NI1Fl3+kZstqaHS2pZrVOVIB+UvXAOwcdPiUk4OKktryv/2xd+JJjU/jvXlv8uzQp3Fyc6Rs1dIE1w2ifofaLLv5E7Vb52XKFvXqqNG8CvMv/MAHv4wkuF4QLp7OVu8aDz93nh3eyWJMo9VQvnagxZjJZMbN24U+7z8HyBlcbfu2oGy10kCeLIKjqwNVGlW0uZ+U2NS88jhJFg0vLvoM/X3nmE1m2vZtbjGWmZrFiEbjin0fgSUlckDZ29vTv39/du3axblz56hWrRqjRo3CYDAwadIktm/fjtEoWhAKBALBk4yrlwulKwewce52nhncTtFzyo/KRsRHZ6/FbDJz41TRwtqJ0cm8OLYHy27OYl3CEmq2qArIDp6h3w1k6taP0OjUXD11k+N/nbG5xsqv1tG/3FAuHLzClRM3cPV0Yf6FH+j1TldqtJAFyeMjE1j00Uowg8nFgcwWVdBXCrAZzVKpJGq2qMa6xMX0XvoWh4wGzl2KwGQ00XlwO1759AUmb5mAyWBEn3l/g+TO1chizSsKM5DZvArpzzbE6OfO2d0XyC6wptFgYteKAxzddPIf3euh8QRH2P5LCPtMIBAI/v2UCvbHbDaze8UBXhrfk9ptrEXAtXayYyojJVMZc/ZyIisjm4grkUDh2daSSsWoWW+wLmEJCy9Ow9VTzkR38XLhuz2f0f+jXgBs/nknKTa6IptMJj7r/S0jGo0jKiyGyOv3qNSgAr+Gz6FlryYE15Ez18/sOs+fs/6yuNagN1g0eclF56Cj+4hnWBu/iJotq3Fw7VFu5zSgGTH9Vfp/1ItP1owm/HJEoVnvSjDULIuGP2gObzhhNZYUm8Ka7zcSeu7WA7/fP+b/KQMqP8HBwXz55ZfcunWLTZs2kZWVRbdu3fDz87v/xQKBQCB4rMx5fwk/DpvHN6/+ZLMdbXo+wyYX//K+Nteyd7KMwjXt1sBqzroZW3jO5WUmdJuCpJLkTiNmWPqptYbT5p93sODD5SRGJ7Pupy1E3rzHvVsxnD9wmaHfD6LrkI7K3OwMOd1cX7UUJn8P9LXLYbaRWWUymfl28CyMwM9rj5DiqCO7uiyEeW7/JQZM7E31ppWVrnu5FFUmaIvciKVdgd/EJnYaTAEeoNNgKO2p6FPl4uTmSJOuDVj2+WomPvcVN0OePCNHMhf/I3g0CPtMIBAI/r180HUK079Yx4LP/yBkr7XGZlpSgc53KshMsa1/lOusAjkI2NBGwPHTXt/wnMvLrPpmPcmxKTn3SGfTvB1Wc7988QcO/HGUuLsJrPpmPekpGZzaHgJmM5/8PhoH53yC3MVMwI0Jj+PQnye4cOgqh9Yft9C9Cr8UwaDP+5KdoSc9JcPCWVJUGaAtcrPdfcvZlp4oioJd+rxKeVClYTBzRi9hbIfPS7zew6YkttnjsM/+tgNKWUClonPnzqxevZo7d+4wfvz4B7EvgUAgEDxEom5Gy19K8OK5fcl2KVh+x0lgtdI22/ae3CE7uU7vCMHF0wmdg9ydpWzVUlZzz+69qHw35Bgi5WqUAbOZ7MxsqjbOS8POLRNURySA0YQqMgEXNwebpUfRt2Ox12lpVb8CktGE5nYcAPdux9DVsT+nd57jo5XvUred3EFPUkk0e64Rnv7uiiGV35izhSFb3q+dva7IeQBSlgHNxTuoo5OooLF+HVesG0SnQW2V+9rqOPjYeYIjbP91hH0mEAgE/z5S3N2hQhmoEVy8C0xydpEt3HzytJw6v9bO5pwTOZnoJ7efpUw+m8y7tKfV3Is52UVqjUoREG/eoxGh5+XM8+B6QXmTbbz3Pfzdbe4h5nYsVRoF41vOx2J866Ld9C0zhMDqpXltcj/KVpVL85zcHKnzVHWc3R2VuTrHwmURJJWEOafzc0KUpYC6tpBSR5Cf09lTdnTltyv7TXieoJpyOaHLk9il+P81A8oWPj4+vPfeew9ySYFAIBA8BJp3b2j7xH0iVgV1BVRqFdlZeWVjd65G8lqNdxlQfjh3rkUq4y4ezoBs0LxZZwzZGdmoVBL9xj9vdQ/7fK2D3X1ckSS4deEOXw/6iVnvLOKvRbutrtFExjOySUVqZenxKeWpCFkq4pES9B79LN+9Ppvyd5Nw+v0Y2nBZoDM7Q48+S88fP26iVa+mVG8q6weYTWb+WriL+KhE5QV9v440uW2Pk+NSipwHoNKocAuPxW7/JeJyygZdfVzQ6uQMrqsnb+IT6MWMI5OZe/Y7AiqIDBbB30PYZwKBQPDvIChH/whDCcqmzeDo5mgxpNGqib0TpxzvX3OU3r6DGdP+U8VuMxqMeAXIXVMjb95j9juLAfAMcKfDgNZWt7FzkJ08zu5OqLVqJEni0LrjjO88ib2/H+bq8RtW1zh7ONH5tfYE1SyLo41AmpO7Izo7DYsm/qaU8IEs+5CZlkXc3QR2LttP3w96KjqZaUnpHFx7nNTEdGV+dnrhsgj2zvaKA0mfZTlPn21t1/mU9cr5fUxKILRq07zg55+ztjHoixf5avvHTNv/RaH3Fdim6FBuASpUqFCseTdv3vxbmxEIBALBo6HjK22Z/e4SCxFx4L6RkIK6AgXLxkxGE3evRwFwansIZSoFABB6Tq77v3c7Nm+yJKHVWUesGnaqy9ZFuyldyZ9SFf05uvGUcu7oplPERthoK2yGTT/vyMvsykGr05CdqUej1TDx2algBo2dBkmSBTH9gny4c1V2lIXsvcjwhmN5YVwPVCoJk6nkYaGCado6By0qSUVmehaShIWwu0arJiNVLnXM7VxTpkopLh++BkBGaiZj23/O8luzFQfeE0dxo2ciA+qhIuwzgUAg+P+gR9danH/jZ0hLv//kfKQnWc7P38kXZJvCkG3gzO4LRIVGE1i1NOkpGUTm2E2R+ewnrZ3tbKLGneuzbuYWGnWpx5kd54m9m2ePLZzwq2L/5Sc1IY1zBy5ZdR1WqVWYjCYcnO35fshcAEpV9Afk4KNeb1B0MVdM/oPLx67RYUBrbpwJK87PYfnsyRlWYx7+biTFpFjZsWCpg5prn5UK9uNSjn0WdiGcz3t/y7e7PivxXh4JJclsegz2WYkcUGFhYZQrV45+/frh62tbC0QgEAgETz46e60iSmznqCOoZqBVa9tcAir4kRyXbK07YIPabWrgV86b9OR02r6Y1zVk5MzX2DDrL1LiUzm25TQqlYoPl4/Cr0C6NUDTZxsQVLMsN0NuEV7AYMnvfJJUEiq1CmOOkVXQ+QQw6Iu+uHm7cufqXVZMWQvIZX2vTx1Au34tebPO+xbzr50KZf2MLfQe8xyrvlpv8xl1Dlqyi+qcIpEvY0qPh587melZVl0FCxqHANeO37AwhgzZBqWs70mkuPoBQgPq4SLsM4FAIPj/QK1WQZKcRe3q5Yy7r5tNCQStvRa/QG8liHY/nh36NLcu3aF8zUDKVpFL7Vw8nHnv56Gc2XOeS0eucfd6FE5ujny761Obazw3ohPbl+1j72+HrDLC8zufVGoJJAlTThfigs4ngClbxxNzO549qw4Re0e27WLvxDHx9/fw9Pfg3VYTlbn6bAPHNp+mYr3yBNcJ4sbZMJv70+jUssZoMXBydyQp1na2+r1bsVZjJ/4KsTgujk38uCiJttPjsM9K5IBauXIlixYt4vvvv6dz584MHjyYLl26oFI90Eo+gUAgEDxkwi7eUZwkWenZXDl2HVdvZ5JjLbuelK8VyLvz3uTjHl9DgZdtuRpluHXBUrT74uErXDl2jW5vdsQ1X1189WZVcPVyYe7opYDcScXe0bamUVJsCjfP3l9w285ex6yTX7Fx7jY2z99JZmoWLXo25uDaY8qcY1tP8+6cN2nzQjNMRhO/fS07la6fDcVkMpGSmIaLpzPjlr7F/tVH2PnrAZJikwt1PgGK80mlUSnGVS46Rx2NO9flwBp5D2YzxEcm2lyn4LUgl/g5uNjz8sQ+OLg4EFSzLB5+7vf9LQT/bYR9JhAIBP8f5HeuJMelkhyXiqSWrDLQuw3pQLWmVfjm1ZlWziA3bxcr58quFQfIzsim25COFnpGzwxuh1cpDyVTPTMtCxdP21nXV47fIC0x7b7PEFQjkK+2T+TrgTM5vescBr2RVr2asn/1EWXO2T0X6ftBT2q3rc5PIxdydPMpsjP1JMemsG3RHgAq1gvijW9eYcG4Zdy6eIe9qw4Tca1wh1uu80mSJEWKIZdKDcoTdSuGlBw7NyEyyaYdVhhJMcmUrVqKvuN6kp6cQdNnrRvuCIqHZC74t1MMIiIiWLx4MYsXLyYtLY1XXnmF1157jUqVKhXr+uTkZNzc3EhKSsLV1bXEmxYIBALBP+O712ezdeEuizEXD2fSUzMwGU2KWCPYfpED2DvbkZlqu/OKi4cTf8Qtthh7p9VHXDh4BRcPZ176sCe933/Wplg4wPwPlinOoqLwKeNJzJ28rKhqTStxpUAWUamKfiy5OhOA5ZPWsH3pXisD5qfjX2HvZMdr1d+57z3zExDsT0CwH6dsdBJU7h/sx90b95Rj7zKexEUkoLHToM/U4+nvQXxUgsU1a2IWWjjwHheFva9zx8t/NhmV/f3F0U2ZmYR+Ml689x8y/8Q+E7aZQCAQPH76Bw0j+rZlBo6dow5DtgGTyWxhn9nC0dVBEQi3RdNnG/DF+g+U44zUDJ73ehWD3khQzbIM+rwvLXo0tnltdmY277f7jMtHrha5BzsHHSazGX1OCZ1KraJqk0pcPHTFYl7XIR15Z84QMtIymTliPkc2nyIlLlWxOR1d7FmbsISNc7Yz46351jfKl3FuMayChk/X5caZMFnH0wZaBy0qJLIyZOkE77JeJMcmk52pR6WSywMDKvgReTPPfnNydWBd4tIin/1RYeudXVLbDB6Pffa3QmOlS5dmwoQJXLt2jRUrVnD06FGqVq1KQkLC/S8WCAQCwWOnQu1yVmMpCakY9UbFuNHYyWLYhcUpCnM+yWulsW7GFouxslVkYU17Zzs2/byDkH0XbV0KwOtTB2DvZCcf2PBRtXy+CRqdxsL5BHDpyDWrev5cXYPlX65h8cSVVoYdwPqZmznwxxG8Snmg1qhQqYv3eoy8EUVsuPV6IDvuHFzsraJkrZ5vylszBtP6+aa88dUA+ox5llLBfmhyxMe1dtpCf/Mnjie4y8p/EWGfCQQCwb+bivXKWxyrtWqy0rMxGuTgYGGBu1yKcj4BnNh6hmun8vQAdfY6/ILk0u3MtCx++3qdVVAs/9x35w4pdG1HNwcadKxNVka24nwCWR+0oPMJ4NQOuazt4+emsm3pXpJjUyzsn/SUTDbO3c6ti+Fo7bQ4uBRwqhRiW5hNcHbPBbIys22el1QSLu5ONOxcTxmLj0hg0Od96TuuBx0HtmHUT6/Tuk8znNwc0OR0ygvI0ah64nnCu+CVqAQvP5mZmaxevZqFCxdy9OhR+vTpg6Oj4/0vFAgEAsFj57nhndg0dxu38ukKaOw0SrcPAENWCTqw2CD8iqVmwTtzh9BpUFvebf0xAFsW7KROmxpW1019eTp7Vx3KG7DxcjSbzYVqI+Vvt5vLtKHzSE2U066NBiM6e60ibglwckcI25bsRa1V0+DpOrzyyQsc2nCcxHtJbJ6/02KtghoDtrQZcveYkZLJ2h+3YO9kpwhZrp2+WZmz89f9gGxgvjN3CBtnbyfieiTrZ27lzO7zhJ67zadrx9j8nQQCWwj7TCAQCP69vD37DY5tPqXoRBr1RouS//sGqArJCsrFoDcSFRZDpfpy8wq1Rs2sE1+xZcFO5ry3hKjQaI5tOcMzrz5lcV1KQirvtf6YmDu2g24g616qter7P2QOiTFJbJj1F2Hn5U7ALp7OpCenW2R6LZrwK6mJ6XiV8qDRM/XoMqQDe387yJ2rkRzddMpiPa2dRilHzM7UW9h5+TGbzMRHJnJh/yVlzGQyMW/ML8rxXwvljsvB9crz9CutWfvjZuIi4tmyYBdLP/0NBxcHvt/7Ge4+bsV+XoFMiTOgjh49ypAhQ/Dz8+P777/n+eefJyIigpUrV2JnZ/cw9igQCASCB8z8D5ZbOJ8Axfnk6F78/1l18XQC5G4iHgHuOLo64BngTp/RzzHoi74Wc9VqNTVbVqP7iGcIqlGWbkM6Wq1nNpvZ89shDHojDi4OuHnLZWiSJOHul/eSz9V5UmmsX2Mvje/Js8M7KRlUZpOZTfO2U7lBMG4+rpiMJgujxMHVntQEWdPAqDdybPNpNv+8g2pNKnPr0h2r9YsrcJn/mSrWCypyjslg4rvBs7ly/DqpCWn8/u16zu2/RGpiGkf+PFmi+z1KcoUui/MRPFyEfSYQCAT/fsZ3mSw7n/IlOuU6n3QOtrvT5aKz1yrOJ1cvZ5DAN9AbdwBxJkQAAIjnSURBVF83HJztCaxWmuHTXqVlT8sSO0cXBzoNeor6HWpRq3U1mnStb7X2zZBbhF0IJy0pA78gHzQ5jiYXT2fUObaYPlMWCy+MYd8NpF3/1spxRkoms99dROfX2+PgYk9KfKqS6QXy3lNzuvvF3U1g68JdRN2Mxt3X3ULaIJeCWlj3Iz0lIy/bvhDCL0cw+90lRIXFkHAvibUzNhEbEU/45QiuHL9Rovs9Kkpimz3xIuQ1atQgOjqafv36sX//fmrXrv2w9iUQCASCh0hGamah5/QZep4e1JYdS/diuo/WQEq87LhJiEoCQK1VodVpCTt/G0cXB5vXvDXjtULXkySJ16b0Z96YpaTE5wmim81mEu8lUalhBUJDbilOIFsCkismr81ZK29MpVZxYO0xkmKSreY/N7QTv3/3pzLPZDSRGJPM92/MJuFeks2MqpKSv6OKLX0GlVrCaMi7R932tShXrQyh52/z3IhO/+jeD5Xipm8LB9RDRdhnAoFA8P9BbrZ07ntTklC66Dp7ONN0QAM2/7zD5rX5g2vJcbINlSs74F/eh9iIeFIT02yW8Tm7O/HVto8L3VfNllVp8HQdTm47y72wGMVBlhKfChJUbVKRy0dtd1POZfb7S9A56ABQa1QYDSYcXR3448fNZKXnPHe+DK4XxjzHzJELLdaICrvHwvErirxPccnO1CvPIUmg0qowZlvalfaOdmRn5JXyPf92N45vPY2jsz31O9R6IPt44JSktO4x2GclyoC6dOkSmZmZLF26lLZt2+Lp6WnzIxAIBIInmze/e4W3Z7+BV2nr/2brs/TsXXWI/h/3LvG6Rr2JpNhkjm89Q3Qh2kjKXIORjFRrrYKeozpTvlagzWsir0cx6PO+Ns/lYs5J3Tbl6xhjMpq4dUFO8UaCiavfp3KDYOq1r8WgL/ry2dqxvDT+ecXRdHzracXgq1C7HAMm9kb6mw3FPAPcefmTPnJbYmzrM3iW8uSpl1oqx1Gh0bw+dQCTNo4noLzf37ux4D+DsM8EAoHg/4MpWybw2pR+is2Qv+Iu/m4CUaHRVGkUXOJ1o0JjSE/OKNR5lZ+sjCz02Zbla2q1mremD87LGMrvuDCDo4sjjbtYZ04VJNeZY8zR60xJSFWcT/bO9oxf/jZlqpSi17tdeXZYJ4ZPe5XnhucF4nYuP6CU+T03ohMNO9W57z0llW3drHrta/H8213kRzCDWmVdPugX5EPlhhWU4/DLEUz87T3eXzAcra7ojDSBbUqUAbVo0aKHtQ+BQCAQPEIcnOzp9ubTnNl1nr2/H1bGc1v9ZqVnUyrYWmzRzlFHVrptUUeVWlKcPu5+rkU6TjLTsxjRaBx3r0fxyZoxNO2WJ9QdsvciddrU4NbFO5hMJgsjJzUxnQXjfy3WM9o72+Hm7cK9MNkRlp6S4/gxQ2pcKmMWj8DZwwmNVkPTbg1o2q0BN8+GcXTTKXQOOhKj5ayuG2fCGD7tVTxLeTJ92Lxi3RvALEkE1wpk3C8j+bz3txYOMUkli2TmEnM7lt23DyjH+Z1RTzTFTd8WGVAPFWGfCQQCwf8HARX86DuuJ799vYHUhFSr85ePXaPdSy0ty7+kHP1Lo+2XrdZOiz5Ldijdz3l1/Uwo77f5BDtHHT8d/wqfMl6AHDS8euIGtdtUt1lmd+NsmM0sc1t4BriTmZpFekqGhS2UmZpJlUYVGbfkLcpVL4NKpaLnqC6YzWb2rzlCwr0kEqISMOboY+1Yto/5535g+vCfObKxcLkCW1ns/Sb0onbranzwzJfKWK7uVn6unbypZNSr1Cpa92larGd8rJSktO5JL8EbOHDgw9qHQCAQCB4DoxeN4OSOEFIT0lBpVZj0eZbAD/9r776jo6q2B45/79T03iGh9967NEWKIoIVEQsWFLEgYld+ovLs2BEFaXapCiJKb9JD7yUJIYH0num/PyaZZEhCJpCEAPuz1iwy95577pl5b73Zb99z9nnsG+q1iiLu8FnMJjNunjryc0pPPgFYLTY8fT3IycglOzWH3Kw8p2V40yfMZvEXKxg9+S5639XNUbx73/qDjgTU/k2HeXHAFKd+1To1lmJ1l0oLJLwDvDDkGpymn+dnG8rcqS85IZVHW01A56ajfpsofIN8GP7sLfzfoklEr9nPtLEzyEm31x3w8vdkYr/JhNcLoU2/FuxZfaDM76CQOSoIU/v6HE3NZnyXVzBesBOLreTKQYewesGMfHl4ufeoEWQJXo0g8ZkQQlxbpix9kef7vInVYnUqBZCbmceWP3YQWMuftHMZWM1W/IJ9SD9fdvLHZDCh1qixmC0kxzvvHmw0mHih32RO7Yvl/xZP4uzxRHKz8sjNyuP0gThHAuqnqYuY8+YvTtcWH1dZyad6raM4tTfW6VhqQnqpbf1CfJk7+VdW/bCBgHB/QusEEdk4gpGvjeC7/Z+we/U+po76zNHe29+LkVFj6XN394s+IC3N0q9W8OM7C5yOXbiLcqHCWWg3je5Nk44NXb7HFXMtLcFTqVSo1eoSL39/f7p27crChQurapxCCCGqgJuHnl8TvuXrne8z8iXnpIcxz4jeXYfZZC/qeLHkUyFDwdRqlVqFVu/8jGPdb1uwmC2s/30LtRqGM/ajBxj4UF/ueP5WR5uty5yfYCkqxSn5VJbcrDyn5NOF99boiqZVqzVq5k3+zf4Z840c3nqcrct28fLAt0k5m0rMwTMknjoPgG+wD9lpOdisNs6eOIent2sF2q2hfqAomAK8MBZ8f4Mf7Y+nb+nX6z10xcauI/54gkv3ueJq8Da/1xOJz4QQ4trSskdTfj8/k+/2f0zj9vWdzqWcTSOoVqCjDubFkk+FLBZ7LHXhLJ/zMUkc3HKUvOx8ti7bRf9RN3DbuIHc+/LtdLjJXk/QarWydfmuEn26Uh/zwuSTonZeDld8eVxGUiarfrDvDpyakMah/46xcu463hz2PmaTmb9mrnbMfgqM8LPXogIObzvu2BTHVYWbzwDcOXFomcv0VGqV49+0xPQSDxRrpIrEZjV9BtTChQtLLVqWnp7Otm3bGDVqFHPmzOHOO++stAEKIYSoWitmrWHhtD+5Y8KtdB7czmlq9ZmjCfiFOD9Z8/B1Jy8rH0XBaVkZgNloT7boPfUl1saP/fhB/pq5ihHP3QLg+Le4P6f/4/S+MLjR6DQoSskdTgqfvlmKBVQN2tblRPRpp3Zunm7YPGzkZuY5PeGq07w2MQftO91ZLVZG1RvntMVx8Sd67fq14vDWY4B9p5nStvct/K40h+OxKQrq8+lgsaLVa4hoGEZOwW4uxWndNIREBRF3+Cxgry+wYtYaxrw7skRbIUoj8ZkQQlxbbDYbMybO5fD240z4dixvDHuf9HMZxRug0amddub1DvAkKzUHrV5Tcke4gtAmOCrI6XDtxhGMfGU4p/bHcvvTg3Hz0JfYLObknhhH/HMhrV6D9YI4rHgh8eJa9mrC/g1HnI55+nlgNpqxWW1OM5gCwvxITUwHIObgGe6OeMzxO6eoFFLOpjvaDhzTj9mv/QyAWqt2HksZxwqF1gkm5Wxqqcm0yKYRjtjMarGy7a/d7N94mPY3ykYfl6NCCahhw4aVee6BBx6gefPmfPjhhxLgCCHEVeT3j5Zy9sQ5vnlhLk07O08tzsvOZ3n+j+xdd5Cvn5vNyb0x5GXl2wt9Y9+6t0WPJuxdf9ApcGjetTHbV+ym08B2jmO97+xG7zu7XXQsfe7uzp/fOCehBj9yIw3a1eXzcd/ZDxQLbCIahBJ/LNGpfeHspVqNwjAazCTFJjuedD36wf38/L/FZKVkAfD4h6MxGkx8OnYGaecynJJPABq9GrOhMGixMfChfqxfsIX05KxSE1AZBf2qsvLQbysK1kwGM97+XvQa0YXYw/H2pFfBrXyDfBzbCbt56vEP9eOGO66CGgO4voXvldjm93oi8ZkQQlxbkuKSWfH9GsBeEqHwAV8hlVrFstwf+XfeOj594luM+SbHzsQmgxn/MH+adW3IliU7nGKbus1qcWpfDPVa1XEce+jtey86lsimEdRtGcnp/XFOx1/4fhzrf9/C1mW7nGIztUaFVq8jv9iOyxqdmv0bj6BSq2jZswl71x0CILtgzM/OeIzPnvgWq8WGm4eeL3e+x6r56/nuxR8cfdhsNvD2xOauh5R0sFhRFAWjwUSP2zuTeOp8iQeQQJnJJ4BzMUk8P/MJUhPSSDh13jGrCuwPFQsTUF5+ntRtGUmTzjV/CZ6rsVlh2+p2iXv6lG7AgAEcPXq0MrsUQghRxW64w54UysvK5/SBouBC566jTovanI9Jom3floTXDwGcp1znZuWxfUV0iXX3W5ft4pXB73Lwv4r9JkQ2rVXiWI/bO2HIKVbLqdiP5YXJJ8Axyyj+WCKtejYFIDDCn8Yd6/PtC/McySeAN29/n6n3fcbjH46mfus6aPUa2vVvhdbNPnurKPkEu1fv58epCzHmm8hOLVkYFCizACiAT6A3b/w2kd53dHf6DMlnUh3BUa1GYXQf2rHMPoS4FBKfCSHE1SWodiCNO9gLhp/aF+uUgHLz1BMYHoDZZKH/fTeg99CXuD4tMY3Ni7c7JZ8UBX5+bwnP3fBGiV3uylOvpfPuxP6hfrTu3ZzMwnioWFxjMVmdkk+AfaaWzT6TKPZQvGO34/D6ITRsV49pj81wzKrPzzUwMnIsf323mudmjCUgzA83Dz19H+gLzRtA/UgIC7bPgrfZ+HHKAjYt2ubYHa+iWnRvwgerJhNyweywfesPO/7uPqwTzbs1KZEIFBVXqQmovLw83NzcKrNLIYQQVWzkq8Op1yqqYH170fRuY56Rk3tiGNP8OZLjU9i9er9L/YXWDQbsT+f07rpyWhdZ+8smvn5uNoqi0GtEV1r2aIpao+LVIVNZ8uUKoprXLvNax7bAF7j9mcEERviTmpjOiT0xjuNqjT1IMRnMGHIN7F1/iMTT5wGFdv1bYrpgdpNaq3bUBzgfm+zyZyoUGOFP/LEEHmj0FP/9ucPpnKJS8A/1pVbjcCwWKwumLeN/939WRk9CVJzEZ0IIcXVRqVQ8+81jePl5gAL5xR7E5ecY2LhoK890f5X9mw6XulteaRoW1JLSe+hRqVxPA3z97GzW/LwJN089gx7pT50WkaSdS+eBRuOxmi14lFHfEsA70KvEsazUHB59/360ei2Jp5M4see0/YSCI4lks9qIP5ZAelIGaecz8PTzQKtRQWEZBbMFm9WGSlP0OY4W3xnwAmUlp9r0bcHn477j4ebPcnqfc70qDx93vAM8aXdjK/6dt55fP1jC3Mm/lnkP4ZpKTUB9++23tGvXrvyGQgghagx3L3dm7PmINn1blHreaDCx6ocN5GbmlduXSqOQkZTJhG/H8uX2/9GgTd0Kj0dRYNTrdzDu84exFBTYPBeTVOJpWmEtAK2bhuCWkRg6NsBcO8CpzcePTCflbFqJOlEWs/N07HW/bCI3Mw+TwcSanzaVGJPFZHGp2GZp+t/Xi6c+G8Os137i7IlzxB1NIKxeiON8QJhfwdbC6TRqZw8O617wpLHGqsFFLkURic+EEOLq06h9fX5N/K7MDUwST59n+bf/YivjN1Yp/v/0FcjJyOGN35/ny21THQ/iKsLD253nvnmcgQ/1BeyzmY5sPwFlxEe1m0SUujOdxWzh0ydmYDKY7CUdCq+3lVwu99sHS7BZbaScTeP8qfOw9wgcOA7n7A8DCwuxl8d6QdynqBSe/24s9ZpHsuL7NcQdjsfNyw3fYG9HG7PRTFZqDm7uekfcdlXEZ9dSEfIJEyaUejwjI4MdO3Zw4sQJNmzYUCkDE0IIUX2ObD9G9Kp9gH3L3JyMXM7H2H/cazUM47uXfsDdxw1DjtFRxLv49ruFrGYb+WYD8976nTnHKjaLp8/dPYg7epZzp84TVDsAY76JoFZRnNXrUMenOO1kB2Ar+NUMiwrhuKJgiQrEUjsA9ZlUCssxF+7KV5yiVkoslcspllxr06cFT057iC1Ld7D5jx0knrTXZ1JrVI6E2IXC6gaTnZHrqDUVWieIcwXfn0+gN18+M8sRJOVl5ZGXVXS/lLNp9j7qhfD8zCe49+XbiWgQ5tJ3dqVJDaiaQeIzIYS4Ns1/63dy0u2lBVrd0IyjO044kjp6Dx2rf9yIm4ceQ74B2wUhitN7G5w9fo7NS7bTa3jF6kw+Me1BTEYzIVFB2Gw2Gnds4CiArlKryM/LL/W6kDpBnDlyttRzJkPJJYClxVnZ6UWbtwx/ZjCDxvRj96p9rPt1M3kFDybdvd3Iyyp9DLUbh5MUl+KIBwsLi9usNvSebiz+coWjbVJciuNvrV7jqPUZ2bQWL//wNGnnMq6K+Kym14CqUAJq9+7dpR738fFh4MCBPPnkk9SpU6fUNkIIIWqutb9scTxBa9qpEX/NXGV/o0DqefuyvLzMfMd2tHDx7XeT4pKJPRRfoRlQORk5/Pj2AswmC2t/3YKiQGabeliDfbGG+HJ2+U4iGoWh1WqcinjHHT2Lqn4ologAVElZKNiX5NVpUZsj20pOx74w+RQY5kfquQzcvd3Izcxjzc+b6DG8Mws/XQaAb7APGUmZZSafABKLFa0EUGs1dBjQmt2r9rPos+UE1Q4s9/M/8+WjqNVqIpuUrIMlxMVIfCaEENemjYu2Of5u3L4++9bbi3d7+nmQEm9/gJWfa8DNU++0TK8s0WsOYDab0WhcTwPsXrWflXPWAvDbR0sx5pscMWDhQ8n2A1qzb/0hpxIGu1buLdFXnRa1yc82cC4mqcS54nGWolLwDfIm/XymY0e8hZ8uo22/lqyYtRoAD18PcjNyi5JPft5gtUJmjqOfM0cTnO5Rv1UdFEVF7KEzvHvvtBI7CRYq3EXQzVPPI/+7D0VRcPdyL/e7EuWrUAJqzZo1VTUOIYQQV1Cfe3qw4vvV+AR6c+P9NxQloGyQV2x2UGGgAaBz0zrtBOfu7UajdvU4sec0ORl5jOv4Iksy56J3L70+04V07jqCI4NIOHkOQ649iFKdz8Aa7IuqIAl29lgiHj7uqNQqp7FoT55DE5sMBVOs83MMpSafLqQo8NWu9zkXm8zXz87m0H9HyUjK5NXB7zraZCRlujT+4s4eT+TsiUS0Og1Wi5W+I3vw2/tLy2x/4/29ad69SYXvUyPI7KYrTuIzIYS4Nt3+9GC+enYWnQe3twctBXKKzQyCohpRGp2mRKFsv1Bf6jSvzb4Nh0g+k8KDjZ9m/smvXB5DaJ0gtHotJoOp1CV1ANGr9uMX4kNqQvpF+4o5cMalewZG+PNT7Des+nE9M1/+EYA9aw+wb/1BR5vcjGLfgZ8PNK1n/3v/Mch2/n4Krftti1M9qMGP3sjSL/8ucxzPfP2Yo+TDVaUGx2aVWgNKCCHE1alJxwYsSpnNnKOf0/qG5gwbP6jca4wXFOrOy8rn8Lbj5GTYE1YWi5VFny13eQxanZavd77H+C/GOGKsh+7rgd/afWiOJ2Do3wZT58bkZOU7JZ8KC1wqZguuhAiKSqHH8M54+How6s07CQjz59f3l3Dov6OOIMOYV/TZQusEOQqQV4itqE7V6vkbnGo4FBZqB/AJ8ubmB/tUvP+aoAbXGBBCCCGudrc8fhPL835i8oIXeOR/91G/zcVrEJW2S1v6uQz2rD3gKAVw7nSS067H5anXqg5zjn1Ov5E9AfvSv5Gv3O7Uxmqxlkg+lbY738XUahhGg7Z18Q324cU54wH44qlZJMWloNaq7fU8i82SimhYfDlcYR0pG2UWxSpgMVlw87QXYt+5co/T7H6/UF/H3826NKL1Dc0q9BlqhBpeA0oSUEIIIUrISnVtR5Xi3Dx1WCzOy9SiV+8nOT6ljCtK8vT1pOstHbjpgT607duSv79fS35GLtbwAHDXYw3xw1YsoLlpdG963Nap3H7b9W9FvVZRKIpCw3b1aNO7BbkZufz2wVKmjZ3hqCOgqEsmms7FJDummruaiPLwccfd2x1rwXUpZ9PIycilbb9W9L+vFy17NEHrpgUgMzmLt+740KV+hRBCCHF90mg1TrsVuyqiUViJRMNf363CZCxZh6kswbUDGfzojXS/rRONOzZgyUVmDaHApLlPEVYvuOw2Bbrf1snxUK7rrR0Jrx9KRlImXz49i8+f+g7/goTQhcXJwV66AQp2Qk7PgoMn7AXKc8reNMfdyw2fQC/ycwxYrVbijyVitVjpMqQ9Qx69kcYFOwUCHNp6jOnPzyn3M4iKqdASPCGEENe+49GnMJXyBA0gODLQqUhjcfm5Rpp3a8LBzUcA++yfnf/s5aNHvmbqX6+Ve9+czFyS41P5/tUf2bR4u9M5j9RMsv08UbLyUHLsySIPb3fGfzGGYf4PXrRfnbuO3QUF1t083WjTpwUrZ9uXLOXnGFg245+CdlqnmU+Fihe3vFjdK5VawWqx4enrzvv/vknjDg1YPnMVnzw63dHGzUPH9hXRZKZkAUWF3Otfwm6BNYEUIRdCCCGqx+al2wmODCLtnD0JVViOQFEUVGpViR1+CyXFJlOrURjxxxIdxxZ+uoyAcH/unnRbufdNjk/BZoM3bnuvxI7IWjetU90ngI43tcHL17Pc5XbBUYFsXmKP9+q2jMSYb+TItuMAnD4Q55il5RfqS/q5CxJvCuQULMFzzPrKLP3hqaIo2Gw26reO4uP1U/Dwduedez9h3a9bnPrau/4geVn5aHUaLGYLVquN+q3rXvQz1EQ1vQi5zIASQgjh5MWbprD+ty0UrmcLrx/Ci3PHU6dFJElxKTTv1pjOg0rZ0t2GI/kEOK4PCPcv954mo4nH20zkkRbPkZVWVDxSpVah0Wmwpmaj23IY7f4YxzK73Kw8Hmz6jNNyPIDGHeo7vTcW2wkvPyef3z/6g+O7T6PVaS5oZw+ggmsH0r5/a8fxsnZWuZC1oLi50WAmKT4VgMFj+uPhYy9aqdVr+O/PnY7kU0TDMBanzWH20c+YuuJVl+5R41TRFO/169dz6623EhERgaIoLF68+KLt165di6IoJV6HDx+u6CcSQgghapzj0ad4c9j7HN1RVN+yz13duf+NO/EO8AKbjRvu6IZviE+Ja00Gs1PyqbA8QEC4X7n3PbUvhtENn2J0w6fwCSrqW61R4e7tViL5BLBj5R4+G/dtieNRzZw3WUmKLXqgeXp/HH98vZKkMyl4+nk4tStMPjXqUJ+giIKY0oajeLi5jMRbIVvBkrystBxy0nNQFIVH3xvlOB9aN4T9Gw874r1ed3Tlj5wfmHPsc0a9fsdF+66RZAmeEEKIq4lvcEGAUfCjdNekYdw46gZSCpIqeg89Nz/cr9x+bFYbI54dwnPfPF5u21P74xw7oiSePu84brVYMRvNmEuZeg2QejatxLG7J92Gm5eb07FuQzuWaFd8lpdaU/Rz2O7GVljMpc8A8wn0ou+9PS/yScCUb+L90Z/z6wdLyMvJZ9QbdxAQ7o/JYCaySYSjXaueTdm5cg+1Goaj1Wkv2mdNVfiUzZVXReTk5NCmTRu++OKLCl135MgREhISHK9GjRpV7MZCCCFEDeTp44HOrShW0LnrePDte+h+WycyU7KwWKw0aFuXjje2Kbcvm83G679N4Kb7e5fbdsX3azAZzJiNZrS6ouLdFrP1og/oks+kOo/f14PbnxniXNBbgbqtSta0Kl5gvXjpgy63tMdaWn0nG4TVC6Ftv5YX/SxJcSm8PvQ9NizcilqjZshjN+LmpSctMc2exCtQq1E4x3efIqJB2EV6q7kqEpvJDCghhBBX3LSNU3h+5hOERAUB8NUzszgfl8zLPzxDrxFdGDimH39/v9qlvu59dQQabfmrvY25RVsHn49JRqt3vkbrVn4fikrhptG9WfbdKsKKFfm+aXRv3lr8IqNev4OGHerT+67uJa4tXoBy5ey17FlXtMuKT7C3IzDJTMnmzgm3Ou2gAqD31OHl7+noJzczj29fnM/k2z9gxsR5pCbYE2VJZ4qe9q2cs5a37vyI1T9tLPezXW8GDRrE22+/zfDhwyt0XUhICGFhYY6XWq0u/yIhhBCihguvH8q3+z7mwSn34OnrgTHPyJvD3qdhu3o8+v799Lu3J8GRgZw+FFtuXx7e7vQa3tWl+xbfQCXu8FlH/cpCgbUDyu1D567l5of6seH3Lejc7derVArPffM4n216m953daN5j8a07l2y4Hfx0gfz/+93p0LnTTo3cMRjORm5PPzuyBLXe/i6Fz1YBU7ujWHKnR/yfN/JLJvxL/nZBox5JkftU0WlMO//fuP53m9wPi653M8mKk4SUEIIIZz4BHgz8KF+3Pn8UADMJgurf9jA6f2xbFiwlQ8e/IJty3e71FfsoTMY80vfsre4lj2b8eLc8bgXzFwyGZxnIJnyi957+rgTGFFyWZ/NamPVDxvY9c9eTu+31w0IjPBnxIRbmfHCPIKjgjix6xR71uxnevT7+AZ5gwJRzWvx8Lsj8fb3LHVs+dn5vLXkRTx9PWjUoT61m0Yw/vMxTm2GPHITTTo1LLEc8MBm+xIwRVHQ6NSObZLb9G2BorL/BOvddeV+PzVWBad4Z2ZmOr0MBkNpvV6ydu3aER4eTv/+/VmzZk2l9i2EEEJcSRENwrjv1RG07dsCsBfhXv7dKk7uOc3qnzby0SNfc2J3TLn9KGqFY7tOunTPuyfdxug373S8v3DJXUqxmU51mjsvsStkzDOx6LNl7Pp3H0aD/fqew7vg7e/F7x//iV+ILwc3HUWlUvF/iyah1qjQaNV0HNCaYeMHOc38Ks4n0JtHpt6HWqOmz13dadqpIT1u7+w4r1KrePS9+0tsIKOoVY5Z9xqdxmlWVo9h9us1Wg0a7VX6EKuGL8GTIuRCCCFKNXTczXgHeLHm543MfOVHR6KkcM39hdRaddEuJQr4h/gy4YY36Dy4He/8+Uq59zsXk1Si+Hlh4cjiajWJICDMj5SzO1FrVPS9tyfblu8iMyUbq9WeANJo1ZhNFlIT0hnX6UUsJguefh7YbDbSkzLZvXo/M/Z9jM1qIzDcn92r99H7ru5Er93P2ePnHIkkvYeeWx67EW9/Tx753338NHURQ73vp06L2o7inwBLvlxRavFPQ649+Waz2VCpVICFfiN78vL8Zzi++xQ5mbm06d2i3O+mxnI1eCloExkZ6XT4zTffZPLkyZc9jPDwcGbMmEGHDh0wGAzMmzeP/v37s3btWm644YbL7l8IIYSoKSZ89wSdBrbjh3cW8Mlj0/EJtM/SLm2nOLDvElf4AKxw85NxnV7isQ9Gc+fzt170XoqicGJv+UktgJ7Du5KVtprUhDT0njqGPnEzC6ctw2K2onPTOmIigC1/7mD97/8BRbWoju0+hd5Dx09nvkGn1+Lp68nyb//lhju6sfOfPY7i6yjg7efJwIf64eXnyaPvj2LWqz/xx/SVTsvwrBYrnz/5rWNHYsdxc9HDQrPRbE9Q2eDZbx5nyKM3sv3vaELrBBMQVn4N0xqpIoklSUAJIYSoKVQqFf3v68Wh/44C4OXvid5TT2ZylqNN/TZ1OHM0AWOeEYvJgs5dh06voVGH+qQmppN2LoPzseVPYbaYLcx+/WegIOmEjVa9mhFWP5RV89YDOJI9Z48l0HlQO/77YycWs5WNC7fxQ8xX/PbBUmIOxbFl6U5HzSibzeYIyNw89HQd0oFVP2zgmwlzWTb9H4Y8dhMr567jVFIm1vQc2ndrzJkjCU7j6jG8C093f9Vp55eYA2fodltHtizZAQqlJp88/TzwCfAmtG4wKfGp3DlxKDo3Hd2HdQKgYbt6rv+HcY2Ii4vDx6doKrxer6+Ufps0aUKTJk0c77t160ZcXBwffvihJKCEEEJcU3wCvBny2E0s+mw5AM27N2Xbsp1OiZa6LSOJPRyP1WwlP8eAzk2Ll78nLXs2Y9OirQCcj00q9167V+9n06JtQFF8dtfzt7Lz332ciD6N3l2HoWCzlx0r99C4Qz3++zMNQ46R47tO8eX29/hn7jq2LdtJ3NEEbAUbthSf2d6ofX1SzqZyfPdpXrr5bW57ahDZ6dkc23GS2MPxALTs2bQoAWUDv1A/LGYLLw6Y4jTeQ1uPEhIV5Ig9L0w+gX0mmaJS8A32xmKycM+Lt6PSqOg+1B6fdbq5bbnfi7h0koASQghxUWM/foD2N7WmcYf6/PDOQv6cvhKwP0Vr2bMZdVvUZvWPmwD7jnPGPCO7V+3Hw8edB9+6h153lF9nQK1RO57K+QZ7c8eEW9F7uvHl+JmONnoPHVqdhuyMXOa/9bvjeH5OPvdGjsWUb6S02pS97+rG8d2nad6tMXvXF9V2OheTzNzJv5JZKxBzl8ZgMJF4PMHpWrPRzIQb3ih1zNGrD9j/sNmfLjZoU5cDBbsAqtQq7n/9TkY8dwsAHz3yNfPe+o3nZozF3dOt1P6uRq4WsCxs4+Pj45SAqkpdu3Zl/vz51XIvIYQQorp9sHoyh7YcpcOA1jzedqJjpzt3Lzduf3ow86f8TlKcvfakMd9EakI663/bQtMujehxWyduffLmcu9RfPVak04NuGl0b07sieFE9GkADHlGvAO8sFqsHNl23Ona3av3M67TS9hsthIlClDg5gf7sGfdIdr1a8m3Lxb9Xh/fddIRTxU6st2577jD8bw78tMS4zXkGEnOL1oW6Bvig7uXG4kn7RvcePi4M3HWk7Tq1YzM1Cxev/V/zJvyG1OWvlTud3G1qEhxcSlCLoQQosbRaDV0H9qJgHB/bnvyZqKa1wbsNZeWfrmC1T9tcrQtvs4+LzsfRaU47fxWlv+N/syxxC/9fCbfvfQDc9/8xamNIddIdnpuqdOFjXnOySd1sZ1aDmw6SvyxBP6Zu45zp4ue9j36/n0MeexGKNgBT63X8Oj7o3BzMUGUl1U0I8pkNDuWD+rctNxwRzdH4i03K48Vs1aTFJfCyjlrXer7qlGDawzs3r2b8PDw6r+xEEIIUQ38Q3zpfpt91s4zXz+Gp5+9YHhedj6fPPaNI/kE9rpPheIOn6Feqyg8vN0v2n9GciazXvvJUYPp8LbjfP7UTHav3ufULis1m5yM3NK6wGK2OCWf9B4FdS9tsGHBVhJPnmP683OxFC6LU+D5mWNp0Lau45rwBqEMGz+4xAYwZSl+P7VKRVaKvcC4d4AXtz4xgMadGgCwf8NhDm45ysk9MexYEe1S31eFGl4DShJQQgghXDL1vk95tPXz1G1em5CoINSagkCg2I+Xb1DR7Bab1cb3r/3EAPVdfPXs92X2m52ew6r5G8jPMTjtthIQ5sdD79xb4peqSccG9BvZo8z++t7Tg2U5PzDksZvwDfImMMKv1HZLv/yboU/ejFdcEtrdJ+kb6MVPb/0G2IoCpGK6De3IwDH9uf2ZwTzwf3fjF+rrSJpZTBaO7jgBgNFgYu0vmxhV70me7v4KWr2GuyfdRqP29bht3MAyxy2KZGdnEx0dTXR0NACnTp0iOjqa2Fj77j4vv/wyo0ePdrSfNm0aixcv5tixYxw4cICXX36ZBQsW8NRTT12J4QshhBDVIi87j0dbPc9LA6bQ567ueJWxoUqj9vUdf+dk5PHa0P8xUHcPm5dsL7PvvesPcXz3aYz5JqeC3O37typ1dnu3oR1p3ad5qX2p1Cqe/upRfjn7Lc26NiK8fmipbbDBL+8t5a4XhoICKHDT/TewcvaaMjeLGfXmnfS5uzv3v3knw58dglqjwifIG4DUxHRHciwrNZtf3lvCLR73Mf35ObTr35Kut3agXf9WdCtI5ImqJ0vwhBBCuKRwOnTi6SR+OP01GcmZ7N90mMm3f+BoY7GYcfdyIz/X4LR17tpfNvHktIdK7dfLz5N7Xrqd6DX7efide1EUhbzsfJp3a8ySL1bABbO2j+w4QdwRe00AtVaFxWQt0V9WajbnTp9H66bjxtG90erUHN8dQ36uAXdvd/Ky8jh7PJHl367CkJmPJjOfTTNXlzo+lVrBarGxd91B3v/ndX58dyEhkUHMO/EF7z/4Jdv/2u0o7mlvr8JqtmKz2jj03zFSzqbxyP9Guf5FX00qWITcVTt27KBv376O9xMmTADggQceYPbs2SQkJDiSUQBGo5GJEycSHx+Pu7s7LVq0YNmyZQwePLhiNxZCCCGuIhnJWSScPAeAp68ni1Jmk3DyHPOm/MY/c9Y52llMFhRFQaVW7LONbPaZQpsXb3PMorpQxwGt6XF7Z4z5Jh5+516yUrIxGkx0HNCGif0ml2i/ZekOvAPsSSKNToO52MYyVosV3yBv4g7Hk52ei5unnrsmjWLhp8uJO2SP6dw83cjNzOXY7pPEHj7jiB3mTv6t1PEpCthssH/9IW5/ZjDLv/2X258ezOBHb2TqqE/Jy8rHZCjatU+lUTkKkG9avI2xHz3AlCXXztI7BylCLoQQ4moXeyiOtMR0AMLrh2Aymti0aBtRzWox7rOH+fKZWWCDrJScEtdqtGqe+OTBi/Y/5t2RAESv2c+KWau5ZewAvPw9iT0cj1qjQqVW4ebpRlaqfRp1blY+gCP5pHPXoffQodFqUFQK99Z+3FGI/MvxswBo1rURedn5DH70RuKPJZJyNpWk+JQLh+IktE4Q3Yd1ZtGnyzHkGvjtw6VsWrydTYu3k5ORw4aCHVwK+Yf48urPz5KZms2/89fTuH0DwuqGXPQeV7OK1oByVZ8+fUrsfljc7Nmznd5PmjSJSZMmVewmQgghxFVuy9KiGUyRTcNJSUhj67Jd3PfaCHIz8xwFxAtrNlnMRb+tvkHe3P3SsDL7dvdyZ/KCFwD7br/Hd53kwbfvJe1cOtnpOSgqBQ8vd/Jy8x2JnazUnIL72GMw7wAvrFYrPoHe7Fqzn2Vfr3T0/+nYbwFo07s5udn5DH9mCDtX7sFmszmSamXpMqgdWRm5HNx8hMyULL56ZhbnYpI5H5uMX4gvJ3afdmrfrGtjnvnqEQ5sOcq25bsY/OiNF+3/albTa0BJAkoIIUS55v7fb46Ezrpft5CRlEX0mv1otGq+O/CJfVZRsV3i9B46TAYTVosNs8mCf5hfufewWCx88NAXnI9N4Xj0KZp1bsy6Xzfbz5mtRDT056F37uHM0UQyk7P4d946fIN9eGHWk3zw0JdkFOzOt/Srv0vtPzAigDd/nwjAz+8tZskXfwHQ4/bOJJw8x8k99m2GIxqEMurNOwkM88cnyJu/Z63m7km3Uad5JF88bS+KrtKoWPpVURCl1qixmC30HN6FNn3sWwD3Gl5+8XUhhBBCiEs1r9imLJ88+g31WtfhRPRp6n0XxQvfj3MkoABQwMPHg9yCJWk5mXmERAWVe48zR8/yRcGmMFarjfjjCZzeH1fQRy6DH72RiIahpCVmcHDLUQ79d5S2fVty46gb+OChL+3t0nOdkk/F9bqjm6NEwb/z17Nz5R68/D3pcXtnDv13lNSEdABuHNWLVr2a06JnU2IPnmH36n10HNAGT18Pvp4wG4Bzp5M4ta9ohrTOTYvZaGbEs0No0LYeDdrWY+gT5RdfF1VHElBCCCHK1apXc9b9usW+Ht+GY8mZ1Wrjtw+XOCWfwF4wvLhV89fTtiAxUxqL2cL4bq9wPtY+I8mQY2DF985L4kLrBPPV09/j7u3ON9Efcu/LtxMQ5seMSfMcyaeyqNQqRr95p+N93RaRKAqoNGo2LdqGVl/0c5ickMbMl38k5WwqGq19Cnm9VlHUblKL3ILPaTVbyUwpuqfVYmXG3o+o2yLyouO45lTREjwhhBBClK9NnxZsXLgVsMdkqoLNYM7FJLHsm3+cG9twJJ/AvtNv9NoDdBnUvsz+448nMK5z0TK1g/8d5cyRs05tstOy+O7Ff2napRHTNkwh5uAZwuqH8GSHF8sdf1DtAG59YoDjfb2WUexcuQdDroFNi7ahKbapzM5/9/Hfn7vIzzU4lvfd/vRg4o8nOOKM3CzneDSyaS3eXf4KAWH+5Y7lmlHDl+BJEXIhhBDlum3cQH45O4P3Vr7OA/93N2//+RIN2tTBarGybMYqet3RtaC2gP1nRVFA56F1XN+ovX3Hkb9nr2Fk1FjmveW8nj8nM5fju0453geE+zvtqKdSq9i2fBdmk8VR3ymqaS08fT3467tVJcbrHeCJb3BRQXSrxcqRnSf49sX57Fq1j663dGDM1PuwFMzqMhmK6hQYc42kxKeCDUeAYzKYWPjpn7Tr36rELiyKotCkc0OimtVCURSuJ4XTvF15CSGEEKJyvf7rBH468w0TZz3JuE8fZsqfL6PVa8nNzGPDwv9o1K4eULT7nEqtoPfUA/ZYrfD8tMe/YVS9J9m+YrdT/yf3xDgevgGE1Ql2Ou/mqWf971sL2p5GUSnUb12Ho9tPEH8socR4Q6KCUGuLUhApZ9PYu/4g306aR8Kpczz+4Wi6DGnviMvMRoujbVqifelf8dpSu/7dy9kT56jfpo5T3Fiow01trq/kExWLzWQJnhBCiBorIMyfgDB/2vdvzQ9vL+BEwZI1ALPJgs1mw2ax4RfqS/q5DIy5JhSVgqJAnea1mfXqjyz+4i/ysvJZ/Plf3P9G0YwknwBvGravx7GdJwE4sec0tZtEOApT1msVxYno0+jddbTs2ZTXh77H6Ml3cfvTg/EN9iEjKdNprDYbJY59/cxscrPy+P3jP1ie9yNeAV4X/bwePu4Y8430Gt6VNT9vAsA32MeRtLrpgT7o3bTcP/ku/IJ9UKmuw2c6MgNKCCGEuGJUKhVBEQHc/KB9444X+k92FN7OTMmmXqsowP6gTa1VYzFZMBTMYvfy98JkMPHGsPfYsnQHACu+X0Onge0c/Xcb2hGduxZjnr3P7IxcvAO8yErNdpo9HtEgFHcfD+6NHMsbvz1PVLPaKCrFaUMagKS4ZIqXeLRZbUy68S1sVhv/LdvJzAPTHHFWWTx93bFYrPS5qwcrZtlny7t56rFZbfgEe9Pp5rY0aF2XwY/2x9O39J3zrmlVNANq6tSpLFy4kMOHD+Pu7k737t157733aNKkSYWGJwkoIYQQFZZcWLxbgZCoYLYu2+k4l1ks8WOz2rABXz49i1P77Wvyvfw8ue/VESX6bNalkSMBpXPTOZJPN43uzQNv3c1Xz3xPSGQQ6xdsITs9h28mzmHdb5sx5hlL9FV81xMARa04pmVbLVasViubF5e99TBAbmYeoXWDefmHZ9DoNexZc4Dzscn2z+DvyfgvxuDu6XbRPoQQQgghqktyfCpg34UuokEoe9YeBOyxDxfkdbJSs5ly9ycc2XYcsM9OGvbUIKc2Gq2GsLohxBbEZImnzpGVmo1Gp+Hprx4jrG4QP767iFY9mzL3/+yz21/oP5m+d/cskXwCirauK+xfp3bMckpNTCc/18Cx3adKXldMTkYeA8f0Y8y7I4k5GEdaYgaJp88D9iV8L8192pWvSlTQunXrGDduHJ06dcJsNvPqq68yYMAADh48iKen64k+SUAJIYSosJGvjmDF96sxGy2cj0lyOqfSqLAWmzKtKAqn9sfi5qnHzdONSXOeotPNbUv0+eSnD3HDHd0wm8xsX7GbRZ8uR1GrWPXDBtb+stmRVPLy8wDshckPbDpCUO1A8rLznfoy5Bl5/OMH+HbiPKxWKx6ebuQUTCFXa9VodVpO7jldYgzu3m7kZRX1ZTaaURSFSd8/hclo4sWbpnB89yle+fFZST6BzIASQgghapC7XxzGR2O+xmw0E3c43vlkQR3P4o5sO46XnyeBEf5MXfEawbUDS/Q5bePbHPrvGCiw6LPl7FgRDdiY9vh0tHot+TkGdq/ah9ZNgynfjMlg5t/5651mThXy8vPg1icG8OM7iwBw83Qj22jfOS8wwp/kMyklZrBr9doSDxbzcwz4Bfvy2eZ3OXMsgYl930Sj0/Dy/Gcq/J1dc6poBtSKFSuc3n///feEhISwc+dObrjhBpf7uQ7XCwghhLhcnr4e2CMZu8imEUz4diwTvhvrtF6/VsMwfIO9AXuw8P4/r5eafAJQq9W06dOCTYu3s+CTZVitNiwmC1aL1SnwyE4vKqDpG+xD8pkUx/ugWgH2P2zYr7XatwXOycwjMMIfrV7j2P3k2emPOd2/w4A2WM32rYK9A7wIjgwkJCqY2wMe5PvXf0Kr0/LxurdYmjmvzM9wvVEq8BJCCCFE1QotVqPJZoNeI7rwf4sn0XN4Z6dkQ687uqDS2FMBNquV7/Z/UmryCcDb34vOg9rx1bPfFySf7LWZLGarY1MajVaNKb+oNlOtxuGO5JNKpaB3t9egykrLIS/L4GiXnZaDT5A3eg89D797H7UbRzDk8Zsc57VuGpp0aoDOTYtvsDde/h7UaxXJsV0nuCv8Ef77cye1G4Xz85kZzD/5FYHh11e9p9JUJDYrjM8yMzOdXgaDoWTHF8jIyAAgICCgQuOTBJQQQogK8/B2p/dd3Rzvn5z2EIPG9Gfjgq1O7fxCfUk/b3+S5R/mR3Dkxbf7TTh5jpT4FKdjao296LdWr2HEc0MAexFNFHudJ0Vt//ms07w2qYnpjuva9mtB8+5NHDvCtOzZlOV5P9GyZ1NeuPH/yMnIpdvQTo72O1fuwZBnJDcrl6zUbJLiUjj031Gy03P49f0lFfl6hBBCCCGqXbt+rQgpSEJp3bRMmjOe7kM7sXfdQUcbRQWn9sVhNdsf0rXt36rcfo/tOkl2eo7TMVWx+KtZ18aAvRYT4DT7qnbjCMeDRE8f+wyogDA/x/mHptzLkow5nNh9ipcGvs0tj99EQLj9vCnfzP6NhzHmmzDmm8lOyyXh5HnijyaSdi6DxZ8vr8jXI8oQGRmJr6+v4zV16tSLtrfZbEyYMIGePXvSsmXZu1yXRpbgCSGEuCR1m0cC4O7lRuOO9l3u9m08ZD+pwNiPRjN9wlxH+1seuxF3bzc+G/cdyfEpPDv9MaLXHGD3qn3c99oIMpIyeabHayiKfVvdA1uOcGpPDCbHTnRm+xTwwhsU1BCwWez/nj2RiNViRVGgSedG1GtZh083vk3SmRT2rT9It6Ed+XbSPH79cCkAe9YewD/E1zE+dx838jLzcfdyJz/HQK1GYZw9kYjZaGHouIFV9j1e1WQJnhBCCFGj1G4czvmYJBp3qI+bh56YQ3FkpmQD9gTRrWMH8NtHfzjaP/K/+0g+m8qnT8wgJDKIJ6Y9yI9vLyQ/J58Hp9zDki//ZsYLcwkI82PY04PYumwXiSfPYSuIw2IOnqFBmzoApe4GHFuQjFKpFAY+3I/IJrX45ey3HN15guQzqXQe0o7xXV9x1AE9uPmI08x3N089+TkGgmoFEHc4nubdmrDr373oPXTc/vTgqvkSr2aXsAQvLi4OH5+i3aP1ev1FL3vqqafYu3cvGzdurPDwJAElhBDiktw16TaimtWmVuNwfAK8yc3Kc9RPUmtUrP99m1P7eW/9Tn6ukT++/huARu3qM3/Kb1itNkwGE71GdMViti/fC4kKYtFnJZ9qGfNNjHr9Dtb+sokzR5239zUZ7PWabDYbaYnpfPbEt4z7/GHHsrx9Gw4TvfaAo73NaiPtXIbjvW+gD3mZ+VhMFpZmzkWj1WA2mVFUCmq1uhK+sWuPq1v4XoltfoUQQojr0eu/TGDnP3tp188+M+X0/jOOc+7e7vy3bJdT+8daT2TwI/357w/7hjLhDcKY95a9oHhUs9qcKyjwnZWajZevJwknztkvLPbb3qhjfTre3JZFX5Q9I8lqtbF71T5+fHchI18ZTq1G4RzZdpyj209wfFdR4fEL63qq1PZFW2F1g/l270eoNWqM+UZ0brqKfC3XDVdjs8K2AD4+Pk4JqIsZP348S5cuZf369dSuXbvC45MElBBCiEuiUqnoflvREjYPb3fCG4SScOIcFpOVg5sPo/fQYS6o42Sz2rCYLYQ3COV8TDJ5Ofk07tSQw1uP0aJHU7rf1olnpz+GolLR/76ebF22k73rD9l3bilwfPcpTu6NcTqm1WvRu+vQ6DSE1gniyPYTnItJ4u/Za2jZqxlqjYr3H/gCgOdnPkH06v2otWpO74+jaeeG/DVrNaZ8Ez1HdOH3D/8gLyefU/tiadS+Phqt/EwKIYQQ4urh5edJ7zuLyiS07t3csdtcWmI6aYnpaPVaFBUY80yYDCYim0Y4ls/5BHjhE+iNMd9Iw3b16DWiCwHh/jTt0ojAcD/+mbeOc6edN6BZMXMNnr4eGHOLZi4FRviTlphOw/b1OXf6PJmp2ZzcG8PJvTH0v68Xc//vV1bOXou3vyfPzRjLnnX7yUnPJT/XgM5Ny/a/duPm5UbnQe1Y+8tmju06hdVqRY1akk9XgM1mY/z48SxatIi1a9dSr169S+pHImshhBCV5r2Vr/PN83M4ER1D4unzGHKNANRrFUVWajatejXj2K6TJJw4x5/TV7IodTbZ6Tn4Btmfugx57CaM+Ua+eHoWIVFB1GsZyYk9MU73KJ58AvtOddM2TaFB67rYbDaO7T7FlDs+wmQw0bJHE8fUb41WTbOujRn4UD8AotfsZ9KNb6GoFP7392vkZefzO39gs9pK1DkQZZAleEIIIUSN5h/iy1uLX+TXD5dybOdJDLkGxxK32k0iAOh4c1u+fPp7bDYbGxdt5YeYr7FarHh4uwMw8pXhxB9PYMYL8+h/3w38+sESzEaz031yMnKd3mt0Gn5P/h4vXw/ysvPZumwnHz78FfXb1CUg3A9PH/uuxu7e7gx8uC+Dxtjjszlv/sL8Kb/jH+rHt/s/Zt7kXwHIz87HbLKg1Wmr7su6FlTRLnjjxo3jxx9/ZMmSJXh7e5OYmAiAr68v7u7uLvcjCSghhBCXbfPS7bw3+nOadm6ISq3ihju7MvTJm5l00xQST50n9lA8FrOFhZ8u4+YH+xJ78Aw33t8btUbtSD4Ven3o/9j17z4A+t7bg5N7Yx11Bgr5hfg4ipujwLiOL+Hh684rPzxLl8Ht+SHma2w2GyqVirW/bCYg3J/hzw6hTrOiqcKZKdnYbDZsFhsqtYqet3fh5flPo9FpaNev/IKcooAkl4QQQoga6buX5rPkixX0vrs72Gw89fnDBEcG8cZt72HINXLmyFkAVv+wkYEP92PL0u3cOOoG3DycawAZ84080WESeVn5bF6ynf739WTVD871f/zD/MhOz8GUb09unY9JZnjAg0Q0COOD1W/S956e3HBnN9RqNSajicRT5wmpE8Sk2U851Y7KSLbHd3nZeejddYyZOpLajSNo2qUh7p5uVfl1XTuqIDb7+uuvAejTp4/T8e+//54HH3zQ5X4kASWEEOKyrf99C7mZeY7E0Y6/95CRlMnZ4/anI26eerwDvBj4UD8GPNCHmx/sW2ZfGclZjr/X/bqFR98fxQ/vLiQnzT4rqUHbunQc0IZfCnams1ntv7K5GXm8c88nLM2ch6IoKIpCXnYev364lLysPDYv2c7dL9yGxWzho0e+ZvUPG6jTvDb3v3GnI+HUb2Svyv9yhBBCCCGugH/nryc/18CanzZizDcRfzwRDx93cjPzAPAP9cXN040et3emfus68O3YUvsxmywY8oyO91uX7+bxj0bzzfNFm830G9mTHSuiiTlorzlV+PDw7IlEPnlsOlP/es1RU3Pf+kNs+WMHALv/3Ueb3i1IO5fO67e9x5Ftx+k0sC0P/N/djkTYsPGDKvmbERV14cPgS6WqlF6EEEJc1+6aeBtNuzSiZc+mePi407x7E4JqBwKg1qgZ+/EDzDn2Od4BXuUub3vlx2fw8LVP5bVarMx+/RfufuE2tHoNigInok+z7rctpV6bl53Prx8u4cyxBA5sPsyDTZ4hPyef4NqBjHh2CAAr56zln7nrsFisxBw8QzsXth8WpSssdOnKSwghhBDV69H37qdeqyiad2+Czk3LDSO64hPoDYB3gBfvLHuFD1a9ScrZVKxWa5n9eHi789z0xx0FwbPTctiw4D+63tIeRaWgqBQWTltG/LGEUq/fv/EwW/7YweFtx1j/+xZeHfIuWr2Geq2i6Hef/eHf9OfncGTbcQCS41Np0qlhZX4V142KxGZXIj6TBJQQQojLFl4/hKM7T7B/42FMBhMHNx/BbLLw3srXmXviC84eS+SBRuN547b3eGPYe47r8nLyS/QV1bQ2U1e8htbNvsbfmG/EkGfgj+z5FD58Kdy9zifQm5fmP02Xwe0d1387aT4PN3uGZ3u+TmpCGjarjSGP38QNd9gLcobVC0GlVqFSq7jnxdsdgZi4BLYKvIQQQghRrXyCvDi1L5bo1ftRqVUs+XIFw54axLvLX2H67g/44Z0FPNT0GV4Z/C4/vL0AsM90yc81lOhrwIN9GPvxA1CwWu747lMMfLg/E2c+gc1qw2a14eZlXyIX2bQW30R/iG+wPcbKzzHw5u3vM77rK0y5+2PMJgsmg5lnpz9GVNNaANRqGA6Au5cbj30wuqq/mmtXRWKzKxCfyRI8IYQQlcJqtj85MxnsRSn3rjvAI1Pv49S+GH79cKmj3f4Nh3h54Nu07NWM2a//TJ97evDqj886zm9Y8B9v3fmRU98/TFnAytlr0bnrMOYZMeYbcfPUk5mSxYcPfcmitNksmLaM2a/9DBQty9NoNQx/dgi3Pz3Y0Ve7fq2YfeQzdO46AsP9q+S7uF64+vRMZkAJIYQQ1S87rWjWeX6OPal0fPcpHn5nJAunLWPTom2O8/Pe+g2tTsOuVfuIXr2fZ75+lCGP3eQ4/+XTs1j61d+O98Y8E5OHf0BInWAUlWLfxCUtB7VWTdzheL6eMJtv937MBw99yfYV0Y7YDBuENwjl9vGDad6tiaO/0ZPvoufwLoTXD8Hdy/Wi1sJZRWY2yQwoIYQQVyV3L3fuemEobp562vVtSWidYFLOpnF42zHCG4TRtHNDPH09CK0TjM0GO1buYfOS7QDs/DsaKFpbHnsovtR7JMWlYMwz4hPkjc1qcwRSFrOVEUEPE3MgDr8QXwAad6hPYC1/Hnr7Hh59bxQzXpjH/fWfZMfKPQCE1w+V5JMQQgghrml97+lJix5NcPd2o/ttHfEN9iF6zX6y0rJpd2Mr/EJ8Ca8fgkavwWa1Mf/t39mzZj82m42d/+516uvU/thS73E+Jgm1RuWYuW4xWQCIXr2fR1pNICgyEEVlnzbVoE1dwuuFMGHGWG4a3ZvnbnidJzpM4nxcMgD1W9eR5NM1ThJQQgghKsWj793PH1nz6TSoHedikjgfm8zy71ZxYNNhpm18m0Wps2nevehJV/3WdQiJCmLkayN4ttdrDPW+nx0r95CelFFq/z4Fu+VlFitS3rxbY2w2G8Z8E2t+2oTFYuF/K1/n861T+TluBne9cBt52Xksm/EPiaeTWDFrVdV+CdebGjzFWwghhBAwbcPbLM2YR1ZaDhlJmRz67xirf9xAfo6B3xK/Y/ruDwmrEwzYZzV1uaUDEQ3D6HtvT+6OeJT76z9J8tlUp01iCimKgneAF2ajxbH7nUqjwj/MD7DHbH99u4rWNzTny+3/Y/ruD5h74kva9m3J3vUH2b/xMMd3n2Lb8t3V9n1c82QJnhBCiOvJf8t2AvagZMfKPfz13Sr6j7qBWo3CWPPTRhSVwojnbmHJ539hMprZumwXBzYdAeC3D5cS0iAUa50wlIxslPRsR7/t+rVk2/Jd5GXnU6tROE9Oe4iweiE80+NVxxTz3PRcWvVqhkpV9HzF3cuduyYOZcfKPdw2TnZRqUyyBE8IIYSo+axWK/vWHwLsxcenPz8Xs9HMpDnj+HP6P5w5moCbl567Jw1jzhu/ALDul82kJqYDsPrHDRiL7YJXyGazcefztzDrtZ/BBt2HduT+yXdxZNtxvnxmlqMsQ36OgcYdGjhd27ZvS7oMaU9+joHut3Wswk9/fZEleEIIIa4r9748HN9gH7RuWtIS0gFY/cMGDmw8DNjrMzVsV482fVsA9ppMimKfmr3r371kBvhha1gLa9tG2IolkvasPUBetr1oefyxBHyDfdi77iARDUIZ/8UYBo3px5Q/X0atKfnT9uj79/NN9Ie06tWsKj+6EEIIIUSNo1KpuP+NO3HztBcJNxvtiaFvJ8137FyXn21gwOjeBNUKQO+uo27LKMf189/+3VEq4UK/vL/UMZNmx8o91G9dh6M7TtC0SyOe/uoRbnn8Jl6cN77E9R7e7rz9x8t8uHoyAWFSFuF6IQkoIYQQlarjgDZkp+VgzDOi1dsn2tpsNpp0aoB3gBeRTSLoNLAttRtH0K5/KwY80BvvAE/H9fmp9ineKouF0KhAoprVIiQyiPTzxZbmKfDe6M/5fNy3HN1xksVf/MXwZ2/hm+fncKvnKDYv3V6tn/m6VYOneAshhBCiSLv+rcjPyScrNRuV2p4GyEjKZOiTN6Nz19FzeBe8A7yo1yqKPvf0oPOgto4HhHmZ+Xj7e4GXJ/o64YQ1DKNuy0g8fNzJych13MOGjXGdXmT5d6vYt/4QsYfiadOnBc90f5V7Ix/nXEzSFfns15UavgRPElBCCHGdSj6byuw3fubgliOV3vdjH9xPix5NuPeV4Y4g58d3F5GVmo1/mB8HNh1h8ed/sXvVPj4b9x0jX73Dce2ub1ag2nYIthzg/OkkYg/Fk5laVHdApVaBDeIOx2Mt2FElODKI8V1fIebgGUxGs9QSqC41OMARQgghrkYHtxxh9hs/k3w2tVL7bda1EQMf6kungW0ZOKYfAFarjR/eWYAx30hU81p8/Og3bF8Rzd/fr+HM0bM069bYcf3xvTGo6kZi9vXjXI6V0/vj0LvrHOe9Azwx5Zs5vvu0033fuXcaWanZBZvTHK/UzyRKUcMTUFIDSgghrlNfjJ/JpkXbWPz5XyxOm1OpfQ9/ZgjDnxkCgCHXwA9vL3Cc27vuIOnJmY73hlwD/iE+aHQax5RwJSvXqb/CHe8ARjx3C2dPJBJ/LIEW3ZuSk5nLfa8O58mOLwFQp3lt7p50W6V+HiGEEEKI6vDqkKlkp+dw+kAckxe8UGn9arQanp/5pOP9qb0xHPrvGFaLPQvx49sLnUoVHNt1kq63tOfg5oIHlVYbmM2g04LJXnA87VzR7PRnvn6MX95fgpefB37BvgRGBNCiRxMWf/4XAN1u60S3oVLr6XonM6CEEOIacj4umUWfLyfmUBzvPfj5RZeiRdQPBSC84N+qUq9VVIljsQfP0PP2ztRpXptd/+7jo0e+ZsaeD7n3ldudnqYVVzgNfP/GQ9RpHsmZI2c5vvsk979xBxsWbqPTzW0Z/+UjfBP9YZV/JmFXWOjSlZcQQghxvdq/6TB/f7+G3av38t4Dn3Pm6Nky24bXDwGK4rSqUrdFpP0PpehYXnYebfq0JDgykN8/+pMtS3cw++hndBrYFrVGwXrsFJajJ7Elpzldp9FpWPXDBhq0qcvuVfvxD/Gl77092Pn3Hnrf1Z13l7/CW4smodNrq/QziYrFZlciPpMZUEIIcQ04sec0Cz9dxr/z1mO1WB3H/527ngVJM/EJ9ClxzaPv30+/kb2o1Ti8SscWEOaPothn+Q54sA+pZ9OIXnOAjYu2OdqYTRbcPfU8/PZIFk5b5jjeqH19sjOyMRnNTJgxlq+e/Z5D/x3j0NZjYIMj208wpvlzjvb129RBrVFX6ecRxbg6fVsSUEIIIa5DGxdt5c/pK9n5z16n4+t//49lOT+Ues1H694i/mgCDdrWrdKxhUQFA+Du6caAB/twbNdJDm4+6tTmfGwytRqG8+pPzzLM/0H7QYuFQY/0Y8vSHYTUCeHBKXfzysB32LJ0B4rKnpX66/vVLPxsuaOfW58YUKWfRRRTkaV1koASQghRUfs2HOLVW6aSl5VX6vnCYKDEcUWhYbt6VTk0UhLSmP3Gz+jc9RhyDaz8fq3TUrtCVouVz8bN5PyZFAy5Rdv8mk1mEk6cB+DXD5ZSr0UUZ44kOH4wfQK9yUyx14fSaNWyy50QQgghaoSf31vEzJd/LPWcyWAq8zp3T7cqj8/2rDvAml82ApCXnc+SL1agcys5Az3lbBpv3PYepw/EOh3fsWIP6eczST+fyfnYZALC/UhNSMdWUJtTrbY/DFQUhcAIf6Ka1qrSzyOuHpKAEkKIq9j052ez4JNlZZ7vPLg93v7e1TgiZ5sWbWPvuoNOxy5MPhXa8scOp/c6Ny3pyUW1BaJX78c7wAudmxZjvj1wy0zJwifIm6c+e5iut3bEvWB7YVE9FJsNpYxtmS9sJ4QQQlwvRjd+ioTj58o8/+K88dU4mpKWfPEXsQfjnY4Z840lGyol47NaDcOIP5HoeD/tsW8IrRvs1CY7PYe6LSN5bsZYGneoj0YraYfq4mpsVti2ukkNKCGEuAptXrqd2/zvLzP51KxrI344/RXv/PlyNY/MWddb2tOgbV1CooLKbKPVa/H0dXe8D6sbgqJSMOabMOU5J6uyUrMdyadCmclZaPVaST5dCTV4lxUhhBCiuk2fOIdBbveUnnxSYPBjN7Is70f639ur+gdXzMCH+xNWNxifQK9SzytqBb2HDpWqKF0QWtcey8UfT3TMcCp07nRSiT5O748jskmEJJ+qWw3fBU8SUEIIcZXZt+EQbw57n9yMfKfjbfq0AKDjzW34bPO7jrX9V1JIVDDTd31AVLOyp15r9RpyMoqWDybHpzimcHv5eVC/bZ1y71Onee3LH6yosJpc5FIIIYSoTr99tJQFH/+J2WhxHFNr1QRHBgLwyP9G8dz0x2tEIe7Og9ox7+RXjh3wLmSz2DAZzE51Rc/HpDj+Dq0XQv02F4/PNDoN7l7ycLC6SRFyIYQQlerVW94tceyhd+7lrolDObEnhnotI6/AqC7OJ6hkEfRCOjctuZlFCSizqShwSyx4oqZSq7BarKg1KvxCfBj0yI38OX0l6ecziWwSTmQTqS0ghBBCiCsjP9fAjBfmlTg++/CnePp5cu50UpXXdboUOnctpJd+TqvXYsg1YPZ1Q51thGLJqLPHEux/KIAN3Dz1BEcGcesTA/jqme8BuOXxm2T2kyhB/hshhBBXmbys/BLHYg7EodFqaNKxwRUYUfkykzOd3isqBS8/T4IjA2nZoylLv/r7otdbLVYmfv8k2//azYnoGDoOaEO/e3uyceE2+tzTvSqHLi5GdsETQgghOBF9utTju1fvZ9CY/nj7l77U7UrKy8nHZHAudeAT5IXFZKVtvxakJWaw3ZRDds86aJJyCPhhDxdua+Mb5M0Ls8Yxf8rvKCoV/e7tSWSTWpzeH8stY2XnuytCdsETQghRmXyCvMlMtu/8pnfXEdm0FkOfHHiFR3VxORm5AEQ0CMUn0JvD246TlZpNXlYeAx7o41Ifhjwj637dAsC0sd/y7d6PuPfl26tqyMIFrk7fliV4QgghrmVNOzd0eu8X4ku9VlF0G9rxCo2ofBaThfwcAwCtejUj9Vwa8UftxcVjDsZTr1UU5mz7D7jZ3x1UClidf9BzM/NY99sWDm87DsDvH/3BmKn30XFAm2r8JKK4iiytkyV4QgghyjV91/vMeGEebl5uPPT2PQSE+l/pIZXrtZ+fY/3v/9GufyteHDDFcdxssjB38q8AqNSKcy2CgmndhZJik1FUCjarjVa9mlXTyIUQQgghLk6tUfPev2+w4JM/adKxAfe9OgK1Rl3+hVeQl58n7//7Bsd3naJWozBevWWq49yZI2c5H5uElxo0+WY0p9JQCpJPiqJgK9g9zWQwExxZtNFM+5taV++HEFcdSUAJIcRVJrh2EK/+9NyVHkaFHN15kt2r9xEQ5kdWin32VmGCqbD+U4lCmAVvVWoVYXWDSYpLwS/Yh7RzGeRm5lbf4EXZZAmeEEIIAUD7fq1o36/VlR5Ghez+dx8n98VgsVgcG8AUMuaZUAOea085HS9MPuk9dITVDSE/O9/xgLC03fBENZMleEIIIa53Xz37PUlxKexbf4gbH+jNvvWHsFmsjiLjF+Ph487ZE+c4e+IcPkHegH1XGXHlyRI8IYQQ4uoUfzyBuf9nn4V+fPcpOg9qS/zxc6QkpJKfbSj3+pDIIGIOniHm4BnUGhUWq03isxpAluAJIYS47oXXDyUpLoW87Hz+mb0WWyk/eD7B3mQmZZU4rtVpCa4diMlo5o3fJ5B+LpMuQ9pXw6iFEEIIIa5NwZFBePp6kJORS+Kp8ySeOl9qO52bFmO+qcTxgDB/zsXYd/d7YtqDZKflSu0nUS5JQAkhhKhyHQe0Ze+6gwXvioo72RQw1PZCl5hbavLJplYw1/fix/UfolapUBSFpDMppJ/PICQquPo+gCidLMETQgghrko6vZZG7esTvWb/RduVlnwCCIzw54/s+ahUKgBiDsaRlZZdI3f8u67IEjwhhBDXuzsn3op/mB8bF/7H1mW7HMdTbqtPdqcw9DGZhM8oGQCdfboBx9v6cuOU/9F3n45bxg7g9aHvYbNa+WTDFJp2blSdH0OUQpbXCSGEEFenV358hrU/b+aP6X8Td+Rsha5d/dNGYg6doVmXRtRtGcUX42cSXDuQmYem4e7pVkUjFq6oybGZ6koPQAghxLVPo9XQeVBbp+QTgNlX7/Rvu/4tUamLfppM4fbjidY8Ni7axqdPzMBkMGE2WaTQZU1gs7n+qoD169dz6623EhERgaIoLF68uNxr1q1bR4cOHXBzc6N+/fpMnz79Ej+UEEIIcX3wD/XDN9i73ORTt6GdSj1+Ivo0f37zD//OWw9ASkIa+dn5lT5OUQEVic0qGJ9VBpkBJYQQolr4BHrj4ePu2PUOIHDJCbI6h+G5LxmA6NUHHLurAIR9cZLsLv74rE8BIKJBOHc+PxSzyUKvO7pW7wcQ1SYnJ4c2bdrw0EMPMWLEiHLbnzp1isGDB/Poo48yf/58Nm3axJNPPklwcLBL1wshhBDXq8YdGxSvjlCqrX/uuGgffe/pTufB7WjUvj7+oX6VOj5xbZEZUEIIIaqFRqvhjQUTHe9tCiTf3ZSsnrUx1rLvbme74EmMW2weQb+dxTvTxuBHb+S13yaQnpSJf6ivo+aAuHIKd1px5VURgwYN4u2332b48OEutZ8+fTpRUVFMmzaNZs2a8cgjj/Dwww/z4YcfXsKnEkIIIa4ftRtHMOypQRdtY7WW/kPuG+zD+C/G0OWWDhhyDfiH+VXBCEVFVCQ2uxJL9SR6F0IIUW069G+NT6C9OKVNq8IY7gmAIcr7otcZ8oz0vqsbiz5ZxtzJv/LOvdOIP55Q5eMV5bBV4AVkZmY6vQyG8rd5dsWWLVsYMGCA07Gbb76ZHTt2YDKVXjxVCCGEEHa3jB1QfqNSGHIN9L//Bj565Gt+eX8Jb90hD36uuIrEZpKAEkIIca0ym8y8fc8noCgAqIxWghYcw2tHIn6r4sq9/rUhU1Fr1QD4hfjiHSC7rFxtIiMj8fX1dbymTp1aKf0mJiYSGhrqdCw0NBSz2UxycnKl3EMIIYS4FiWfTeX9B77Ay9+zwtfm5xgY2/YFIuqHARDZtFZlD09cY6QGlBBCiGrx64dLWffrZqdjnvuSHfWfyjLk8RtZ9s2/mIxmgiMDmX30M7wDvPAJuPisKVH1FKv95Uo7gLi4OHx8fBzH9Xp95Y2lILFZqHA554XHhRBCCFHk5YFvc3p/+Q8Ci/Py96RVr2ZsWbqDc6eTuH/NnYyYcAu1GoVX0SiFq1yNzQrbVjdJQAkhhKgWC6f9WaH27t5uPDTlXoaNH0StBuEY8oz0u7cnao26ikYoKszV6dsFbXx8fJwSUJUlLCyMxMREp2Pnz59Ho9EQGBhY6fcTQgghrgVJZ1LKTD6pNCqs5pIZiqjmtXni4wdp3LE+P09dRIO29QiNCq7qoQpXVWRp3RVYgicJKCGEENUiN6vsbXl1blqM+c61evKy8tm6fBe3jL2JOycOrerhiatYt27d+OOPP5yOrVy5ko4dO6LVaq/QqIQQQoiaLSstu8xzVrO11CRU7MEzHN52nI4D2vDYB6OreojiGiM1oIQQQlSLqIvUBTAaSi8UvXPlHvZtOMzx3adIO5deRSMTl6qqdlnJzs4mOjqa6OhoAE6dOkV0dDSxsbEAvPzyy4weXRT0jh07lpiYGCZMmMChQ4eYNWsWM2fOZOLEiaV1L4QQQgjAP9QPra7sOSmePu6lHp/zxs8Y8o0c3HIEQ17lbCgiKofsgieEEOK6dz4umZfnP42nn0eJcyqNiqhmtUu9rl7rKGIPxvFEh0k82moC2ek5VT1UURE2m+uvCtixYwft2rWjXbt2AEyYMIF27drxxhtvAJCQkOBIRgHUq1eP5cuXs3btWtq2bcuUKVP47LPPGDFiROV9ViGEEOIaYrFYMOQaeO3XCaWe9wnwwmQ0l3pu4MP9+GjMVzzT4zXeGPZ+VQ5TVFRFYrMKxmeVQZbgCSGEqFKLP/+LL5+ZhX+oLznpuSXOt+zRlFP7Yku5ErQ6Ld++OB+ArNRscrPy8PKr+C4t4urSp08fRxHx0syePbvEsd69e7Nr164qHJUQQghx7Zhy50dsWrydwAh/bArkda6HzUOH+5aTqPJN3PPKcGZMnFviuqBaAez4O9qxfC8pVnabFa6TBJQQQogqdfC/owCkncsoeVKB5DMpZKUW1SDQummxWq00aluPw9uOA9C6d3PueuE2QiKDqmXMwjWuTt++ElO8hRBCCFG2A5uPAJByNg1LsDfGpmEAqJOyCE7I5PtXf3Rq7+7thsVsoW6rKHasiAbgxvt7c8+Lt1XruMXFVWRp3ZWIzyQBJYQQokr5h15k1zMbnD1xzumQqaAY+eFtx7ljwi2c3BfLc988TljdkKocprgUFdwFTwghhBA1g85N5/hbnZ6LKjUHm7sOzdl0slJLzljPK9hMJj87jx63d8bD253nZjyOViebfdQoNXwXPKkBJYQQokptWrTN5bY2RXH83XNEF7Yu382uf/byx9d/V8XQxGWqyUUuhRBCCFG6rLRskuJSHO8VkwWfP/bi++sONKUkn4q7cVRvdqzcw6ofNrBvw6GqHqqoIClCLoQQ4rrWqEN9l9oZ29Yjf1hnTAW75XUZ0oG4w/EA/Dt/Q5WNTwghhBDieqJ31+EX6ntJ1ybFp2LIMWC1WPlz+j+VPDJxrZMElBBCiCozfcJs4o8m4ulC4XBLmJ/931D7v9npOUQ0CgMFbhs3sApHKS5ZDd5lRQghhBAl5WTk8Obt7xMaFVzha/1CfVGrFdy93NDqNdw58dYqGKG4LLILnhBCiOvR5iXbWTBtmcvtdXtOY44KQnM8Eb2Hnm8mzAHg613vE9I8jPHb5qNWVLzTbgSeGn1VDVtUgBQhF0IIIa4uXz03hx1/77mka3Mz85g7+TfcPPUsyZzHqb0xPNPjVVrf0JwxU++r5JGKS1HTi5DLDCghhBBV4vvXf6pQe3VCGvqtx1CnZKFzKypomZedz9pzh1l//ghrzh1i0/ljlT1UIYQQQohrXnpSBitnr7nk660WKwBGgwmVorD48784uOUoP7+3mMyUrMoapriGSQJKCCFElWjbt+UlX5uVmo2bh54GbeqQn2OgS1B9GnqH0MQnjA6BdStvkOLy2CrwEkIIIcQV5R3gRYO2dZ2OKSql9MalMBvNePp60L5/a87FJNFvZC8Cwv3pc3d3vAO8Knm04pJUJDa7AvGZLMETQghR6c6eTOTPb+yFKf3CfElPzKhwH/m5Bk7sieGdez5hcdocFvQeX9nDFJdJluAJIYQQV4+Vc9ZxIvo0WjcN2MBkMGOzVuxHOicjlx1/RzNj0jwmL3iBX+JnVNFoxaWQJXhCCCGuO2t+2oTZaAa4pORTcc27NXb8vXnpdma/8TNZadmX1acQQgghxPXmz+krATDlmzEZzJfVV/Ou9vjMarWycNoyFn22HJtsOiLKITOghBBCVLqWPZqiKEqZgYhKrXLUEbgYvYeOZt0ak5uVhzHfyP+N+BCrxUpuZh5PTnuosoctKspqs79caSeEEEKIK6rDgNYc3XGizPN6Dx2GXGO5/dRpXhtPXw8ANi3axtcTZgMQWjeY7kM7VcpYxSVyNTYrbFvNZAaUEEKIStemTwsCwv3KPO9K8gnAkGtk7pu/8sOU33H3csMvxBeA//7cQV52XmUMVVyOGlxjQAghhBDObn6w70XPu5J8UmlUxBw8w7SxM9i+Yjdh9UJQq+1phTU/bayUcYrLUMNrQEkCSgghRKXb+c8e0pMySz2X3SGMpJHNMdRyvVhlWP1Q9O56Bj1sD5wSTp7n1L7YShmrEEIIIcT14O/Zay+7D6vZ/hBRpVIRVCuARu3r06RLIwA2L9l+2f2La5skoIQQQlQKm82G1WoPShZ//hcWk6VkGyD9proY6vmR2SvSpX7dvdy4dewAjAYT0WsPotVradatMSvnrCXm0JnK/AiighSKil1e9HWlByqEEEJcpyyWonhs0afLKq3f1n2aUa9VHc4cPUviqfO4ebrR6ea2zHhhLrlZMkv9SnE5NrtC8ZnUgBJCCHHZks6k8Ez3VzHmG/lkwxRU6tKfbyiAx4Fk8poF4nEw2bXOFXvx8UNbjnJg02EATkaf5tCWo8QfS+CDVZMr50OIirPZ7C9X2gkhhBCiWm37azeTh39AgzZ1+Hj9W2j0GsgxVErfxjwT/8xbx9Zlu0hNSANgU8EMKE9fT+57bUSl3EdUkKuxWWHbaiYJKCGEEJft6I4TJJ1JAeDApiOE1AkuOqngtMY84I/j8Mfxi/anqBTHtsB5Wfm8Oex9x7nGHRugc9Owf+MRGndsWGmfQVScq1v9XoltfoUQQojr3fa/dmMymDi87TipCel4enuQnZoDgFavuayd8A5uOcrBLUcB0Og1tO3TghN7TpORlEXD9vUqZfyi4lyNzQrbVjdJQAkhhLhsnQe349YnbsaUb6T33d2xFc842ey7ogTVCuDApiMu9We7yK4cR3ecIDgykJkHPiaqmWvL+IQQQgghrjd3PH8rKQmpNGrfgNA6wTTu1IBzMUkAmAxmug/rxM6Ve1wqPn4xZoOZHX/vofttnXh2+mP4h/pVwujFtUgSUEIIIS6bVqfl6S8fAey1BnKz8p1mMZ07nURqQnql3S8pLgU3L/dK609cIld3UJEZUEIIIUS1C60TzBu/TQQgMyULnbvO6fzmxZVUNLxgtvvp/bGSfLrSKrK7ncyAEkIIcbVb8sUKpj83u8Rxo1qFqU8rMFvQbj2CUkqR8ovRuekw5tuf0Kk1KkIigypjuOIyKDYbigv1A1xpI4QQQoiq8+GYr9iydEfVdF7wM68osu3IleZqbFbYtrrJLnhCCCEqlZunGwAqzQU/MREB2Lzcsfl5YfPzcrk/RaWgUqscyScAq0USGkIIIYQQrnLz1APg4VMJM8gL8kwXbjoju9+J8kgCSgghRKVq06c5ikrBarY6n4hNQjmfjio+BV1OyQDFL9Sn1P5s2NBo1U7HfEO9ObU/ttLGLC6RtQIvIYQQQlwxrW9oDkBuZtlJIncvtxLH1Dp1yYY2qNU4HKvF+Qe+Qbt6pJ3PuLyBistTkdjsCsRnkoASQghRKaaO+pQRwQ/xxfiZpRYRV1us6LYdRbv7BEaLhdx2EZiCPR3nM5IzS+/YCiaj8y4t6YmZPN31FdKTJMi5kgqnebvyEkIIIUT1ykjOZGz7F7i//jgWffZXue3zsvNLHLMYSy+ZkBKfVuLYjhXRvDH0fxUfqKg0FYnNKhqfrV+/nltvvZWIiAgURWHx4sUVHp8koIQQQly2vOw8Vv+4kcyUbHb8vafUNsWfkqUOb05G37qkjWiBrWAat+0iJaGKJ7T0HvYCmlarFclrCCGEEEKU7sDmI5yIPk3i6fPEHjpT4esvnIFeXH6Oc7LK09cDAItFpj1fq3JycmjTpg1ffPHFJfchCSghhBCXzd3LnXteGlaiFkBpzP5uGGt7Y1ODTWUDG3Qa2NblwpWGXCMoMGhMf9Qu3E9UIVsFXkIIIYSoVh1uak27fq0u6Vq1Vk3nWzu43D4nIxe9h57Bj9yIxVKxjWZEJapIbFbB+GzQoEG8/fbbDB8+/JKHJ5G7EEKIStFlSIcStQBKo8o2oknPB6sN79WnUIDtK6KxXTCdyTfYu+xObLDkyxW8efv7lzlqcVlsNtdfQgghhKhWenc9LXs1damtSu38INBisrB54bYS7ZzqRKnV4OeNTavG0Ks5GTe04JNXfmD+W79f1rjFZahIbFYQn2VmZjq9DAZDlQ1PElBCCCEqxar5611qpzJZCZ65m7AvtuFxOLnUNsPGDyQjKavktRcGR2Z5wiaEEEIIURpDnoF1v252qW15Owzr3LV0GNDGuU5Uk7ooTeqh79AUW4A36LVYQv0lPrvKREZG4uvr63hNnTq1yu6lqbKehRBCXDc2LPyPf+eVTEApSumTXxSrDcVgQe+px5Dj/JTFN9ibxZ+vKPU+tmITrLwDvGjbt6XjvdFgQqfXXtoHEJdEsdlfrrQTQgghRPWa9epPxB6Kr/B1ilrBViwhpdFpcPNwY+fKC+p8quzzWYzpeaizs7F56onASrOujR1NJD6rXq7GZoVtAeLi4vDxKdqNWq/XV8HI7GQGlBBCiMtydOcJ3rrjI/JzDbh7u3H/m3eiqOwzlcpbeXVh8gkodeYT2ItbFi7Tc/N0Iys1m5+mLiI3K4+ZL//AEPeRfP7Ud5f3YUTFyBI8IYQQokb6/vWfWDhtGQCRTSK46YHeLl9ru2A2lNloJjOllPjs6Gk8M9LgeAza/TF4Rp8k6fBZ5k/5HYvFwjM9X+NWr1Euz8ISleASluD5+Pg4vSQBJYQQosbKTs91/N24QwMGPtyP0LrBjmMaXdk7qFSEWmPvR1HsO69otGpa9WpK2rl0tv21G8Dxr6geitX1lxBCCCGqjyHX6Ph76LibGf7MEMeudjp3XeXcxGhCnZIOZguKWsFkMKPRqWnYti6Jp85zcPMRrBYrOy6cOSWqTEVisysRn8kSPCGEEJelff9WvDT/ac6dTuLWJwYwuuF4stOyHefNRuc6AIrKeSndxbh56cnPts+SKnzyptZpMBvMhNULYd+GwzzRfhKTZj/Fqh83MGhM/8r5UEIIIYQQV7GH37kXv1BfgiICCIkK4on2kxznvHw9SM0zOrVXVAo2q2szlrVuGkz5ZqBo5nrhrKlaDcNZ/t0qTu2PZdynD7N/0yFGvnLpu6aJmiM7O5vjx4873p86dYro6GgCAgKIiopyqQ9JQAkhhLhs/Uf2AuDU/lin5FNpXE0+AY7kU3FmgxmtXsPZk+cAMOQZadK5IT2Hd3G9Y1E5XF1eJ0vwhBBCiGqlc9Nxz6RhAMx582enc6mJ6SXau5p8AhzJpwv5BvsQc/AMYH9wOGz8IIaNH+Ryv6ISVKT0QQXjsx07dtC3b1/H+wkTJgDwwAMPMHv2bJf6kASUEEKISvH5U9/yxzf/VMu9TIaiwCcwwp+0c+noPXT4BHhXy/1FAVvBy5V2QgghhKhWRoOJZ3u+xvFdJ6vlfhlJmY6/W/RoxqGtx2jUvh4araQdqo2rsVlh2wro06ePox7rpZIaUEIIISrF0q9WlihaWRadm+u7oRQWNL9QeP1QtHoNDdvWY1ynl3iyw4uYjCaX+xVCCCGEuJbt23CIYztPujzRRaV1PT2g1pas8alSq/AJ8sbTz4PYQ2d4utsrfPDQly73Ka59kooUQghRKRRFKf+piALYwJjveqKocEq4zl1H3ZaRWExmajeO4NWfnkNRFD578lvAPp3cZDCj1clWv9VFsdlQXIhqXWkjhBBCiMrl7e9ZofZWk+t1Eiwme41PT193mnVtTOLpJAaN6cddE28D4OFmzwBwLiapQmMQl8fV2KywbXWTBJQQQojLkpeTzzv3TMM/1LfUmgJOXPidM4V6Ywn0RH/kPIrFHgipNSqMeUaO7TyJolI4ER3DuZhkvAO8GPvhaIJqB9K8W2M8vN0v/wMJ10kNKCGEEKJGOrbrJF89Oxudm7ZCD/4qws1TT05GHnvWHsBkMPPdi/PZtHg79VpE8tovE9i0eBs3jrqhSu4tylCFNaAqgySghBBCXJYPHvySrct2VkpfVr2GzCEtQK3C5uOG+3+nAbAUJKJsVptjRtThrccAaNG9Cfe9OqJS7i+EEEIIcS14ZdA7pBeryVRZVBoVVrM9LsvPsW8WU1ib02aDg5uPcHDzEQY82If737iz0u8vrm5SA0oIIcRlUZRiNZpKL9fkel9WK0rBlG5yim0PXOwBTWHNAbVWTVCtALoMac/KOWv54e0FGPOdtxQWVcwGWF14yQQoIYQQolo5/fReZnxWXGHy6UKFNTv1HjqadW1ErUZh/PD2AlbOWVt5NxflczU2u0LxmSSghBBCXJZH3x9VFNhc5g+ZYrLiu2APfn8dxH3f2VLbNGxXD4BG7evzU9w37Pp3Lx889CWz3/iZO0If4bkbXseQZ7i8gQiXFNYZcOUlhBBCiOrzyP9GFr2ppJ9hD5/SSx2otWoCwv0AuP3pIXy2+V0mj/iI2W/8zAcPfclQn/v5ZuKcyhmEuKiKxGZXIj6TBJQQQojLEn8soVKfoKhzjajPpJd5/si249RqFM7khRMB2L/xsONcXlYe+zce5vSBM5U3ICGEEEKIq0z80cRK7zM3M6/U4xaThZT4NLoP68QD/3cXAKf2xjjO52Xns/iLFZU+HnH1kQSUEEKIy+Lu7Y5aU00/JwUzreKPJfB42xfIzzUwevJdtOnTgtB6wQBodRoatqtbZhcmo4nzsbIjS6WwUVTs8qKvS+v+q6++ol69eri5udGhQwc2bNhQZtu1a9eiKEqJ1+HDh8u8RgghhLhW6dx11Xezgvhs8+LtvHbLVACe+nwMzbs3Qau3704c1azWRbvIycghPSmjSod5XXA5Nrv0+OxySBFyIYQQlyw/18DXz83GUkY9gMvlFeBJdmpO0YFiP5QZSZkc2HwEbDa6D+1E11s78O+89XQc2Ba1Wl1mn8/2fJ2jO07g6evBa79MoOOANlUy9utCFe6C98svv/Dss8/y1Vdf0aNHD7755hsGDRrEwYMHiYqKKvO6I0eO4OPj43gfHBxc4XsLIYQQV7OEU+dY9PnyKuu/RHxWzK5V+7DZbBjzTQx7ahChdYPZsSKaIY/fVGZ/52OTeLT18+Rm5hHRMIwP/n2DkCj5/b4ksgueEEKIa9XP/1vk2I2uKpQV3BTSu2l5vu9krBYrm5Zs46M1/3fR9ku//pujO04AkJORy0djvuKnuG8qbbzXHSuuFTa9hPzkxx9/zJgxY3jkkUcAmDZtGn///Tdff/01U6dOLfO6kJAQ/Pz8Kn5DIYQQ4hrx3ujPyUrJrrL+S8RnxfIYnj7u/DN3HZ88Nh2Ah965l9GT7yqzL2O+ke9e+sGxvO/s8US+f/0XXpzzVKWP+7rgamxW2LaayRI8IYQQlywkMggArV6LqiqX4ZXyQ6rWqnjuhjewWe1Rz951B0mKTymzizPHEvh83HdOx5LjU5n31q+VOlRRtszMTKeXwVB6sXij0cjOnTsZMGCA0/EBAwawefPmi96jXbt2hIeH079/f9asWVNpYxdCCCGuFsEF8VlhYfCqUri8rjir1cYHD33peP/7x39ctI+Vc9ax5udNTsf+nbeOUwdiK2eQokaRBJQQQohLNuiR/rh56DEZTGVuy1sZbh07gKjmtZ2OWUz2+9mKTR9+595P2PnvXjYv3U5mahZgn4b+x9d/Y7NZCawVAArUa1W0hGvu5N/Iyy69qKa4uIrushIZGYmvr6/jVdZMpuTkZCwWC6GhoU7HQ0NDSUwsvahqeHg4M2bMYMGCBSxcuJAmTZrQv39/1q9fX7kfWgghhKjhbht3MwCpCelVep9Rb4zAy8/T6diFhcqzUrJ5d9Q0juw4ztblu7BYLADs33SYlXPWElInCK1Og6evB4ER/o7rnu35epWO/VpV03fBkyV4QgghLklGciYHtxwlrH4wp/dX7a5zf81cjdloLrfdgY1HeGXQO1gtVpp2bsjn/03ltVumEnsoHv8wP9IS0+k+rDMajYpT+4qerG1dvos+d/Woyo9wbapgDai4uDin+kx6vf6ilymK89Q3m81W4lihJk2a0KRJE8f7bt26ERcXx4cffsgNN9xQ/hiFEEKIa0Ds4XiS4lLQeWgx5pqq7D4anYbvX/3ZpbZrftzE+l+3YDFbuefFYdz65M1M7DsZi9mCl58nJqOZu18cxn/LdpJyNg2A3IzcKhv7NU1qQAkhhLgWTbrpLU7uiUGjLbvg9yVTcKon4EryqZDVYp8ZlZFsnwHl7uUGgCHPCMCBjYfJSM50ukbv4XYZgxWu8vHxcUpAlSUoKAi1Wl1ittP58+dLzIq6mK5duzJ//vwKj1MIIYS4GiWdSeGJDpMw5hlRqSt/sZOiUhylDyoSmwGODWvSzmWg1WnQ6jVYzBZyChJNi79YQXZa1dWtEjWDJKCEEEJcksIp1maTxXHMplbIuKU5Fl832sbnEbfq4KV1XoEHMjo3LU988hAxh2L5d+56fIN8iD+eSMKpc8z9v1/pdUdXbrq/N027NGLtr5tJPHWejQu3Oq6v37YO3W7pcGnjvN5V0S54Op2ODh068M8//3D77bc7jv/zzz/cdtttLveze/duwsPDK3RvIYQQ4mplNpoxGeyzngofyF0oINyf1IS0S+q/MPnkilqNwhn/5Rh+eHshp/fF4O7tzvnYZNb+sonOQ9ozYsKtNGxbF0VR2LfhENtW7HZKQN09adgljfG6JzOghBBCXIve/+cNXrvVvrytkNnfA1MtXwCO5CbjUYX3V9QKHl7ueAd4kZ+Tz/YVe8hOzyU7vWDKtg3mv/UbNht4+3vy2/mZ/PzeYqfkE8CUJS9V4SivcVWUgAKYMGEC999/Px07dqRbt27MmDGD2NhYxo4dC8DLL79MfHw8c+fOBey75NWtW5cWLVpgNBqZP38+CxYsYMGCBRW+txBCCHE1Cq8fypSlL/HOvdPIyyq9vuWFs8Arm6JS8A/1RaVSyEjK4vB/RzEZzWSl2XfOM+QZee/+zzDmm+h+Wyf+b9EkPn3yW9IS0x19ePi488j/7qvScV6zJAElhBDiWhReP5RhTw3is2I7y2mScwg6k0WWyoZ+f+nFoiuLzWIjJyOXnIxc5k/53TGFuzh3H3dyM/Lw8PFApVIRfyzBca5R+3rc+sTNjp38RM1y9913k5KSwltvvUVCQgItW7Zk+fLl1KlTB4CEhARiY4vqeBmNRiZOnEh8fDzu7u60aNGCZcuWMXjw4Cv1EYQQQohq12Vwe1r1bMq2v3Y7HfcK8CI7NRtLsZnrVcFmtZGakE5qQjq/f/wHplKW6ikq+/JATz/7o8rsVPvMJ7VGRbNujXni4werdIziylFstupPe2VmZuLr60tGRoZLtSCEEELUTLlZedwV/giGXOMVHUf91nU4uS/GsXSveI0CtVbNu8tfoX3/1pw+EMu7Iz+lWZdGPDdj7BUc8dWhrN/rwuP9mzyPRn3xQuIAZouBVUc+kt/9GkxiMyGEuHYc3naM8V1fudLDoOPNbdnxd3Sp5wIjAvhy+1QCwwNY8f1qfv1gKXc+fyuDxvSv3kFehUr7za5obAZXJj6r/MpkQgghrhse3u68uWAiiqr0nckqSueuu6TrHpxyt1PdqOLPViwmCzNemAdA3RZRzNjzkSSfKklN3uZXCCGEuF417dyIW58YUGn9qTQVj/O8Azxp3KF+medTzqby24d/ADDwoX7MOjhNkk+VoCKx2ZWIzyQBJYQQ4rIs/uyvChWlvBhjXsmZVIqi4Bt88acyZ4otrfP088DTx7n6VGid4EoZnxBCCCFETWez2diwYGv5DV1kNZeM87R6LZ6+ZVf7NOYbiTtSVCc0MMK/xM58DdrUrbQxiquDJKCEEEJcMovFwo6Ve6r0Hp0HtXUUzFRpFO5+aRhc8CBuxsR5jr9z0nOd6kEFRwbw8o/PVOkYr1uFhS5deQkhhBCiWuxdd5D08xlVeo9eI7o44i2vAE963dHV6bwh1+SUBEs5m+a0M1//Ub24aXTvKh3jdakisZkUIRdCCHE1ObU3Fpu19G1+K4PeTceu1fsdy+usZhu//G9xhfp4+4+XcXN3bS28qCCrDRQXgpdKmiEnhBBCiPId3HKkSvsPqxvM6h83Ot5np+aw4ff/XL4+pE4Q4794pCqGJlyNzQrbVjOZASWEEOKS/fH131X68MSQb8SUb3K5vZunHkUpmh5lahjO009+h6GUHVhEJajBT9iEEEKI69Xy71ZVaf+Jp5Mq1N7N0/lB4PmYZF4dMrUyhyQK1fAZUJKAEkIIccn63dfLKeFTXTS60ifw5ucYHAXILUHemFtGkR7ix/LV+6tzeEIIIYQQV0y3Wztekftq9WXHZxc6sOmwU40ocX2QBJQQQohL1qZ3C+q2jKyy/tXa0n+mzEZzmUFOISXHAAYTKqBhXSlCXjVcfbomM6CEEEKI6nL3i8PQuWmrrP+ynj2aDOXHZ4X8Q30JCPOrvEGJAhWZ/SQzoIQQQlxlHn5n5CVfawOyb2xC2v2dMdYJKHHeYiq7vpTJcPFldao8I27/RvPh+IG0alrrkscoLqIGT/EWQgghrleB4f406dyoyvq/2M96efEZgLe/F1/teB9PX89KHJUAZAmeEEKIa9vmJdsu3uBivzRaNaaoAPu/dUsmoC7G5qbFEuqH7SJLAN/6dSKd+7asUL9CCCGEEFczq9VKRlI5u+BVfwUFh/mnvyKoVsXiPnFtkF3whBBCXLLcrDxWzFp98UYX2SRPMVlw3x6DKdwX/d6zpbdRSj6gsQGmni2wuelQnT6Hdn9MiesCa/nTrFvjcj6BuCxWF6dvyy54QgghRLXZsHArsYfKqa90hX6aOw1qh4e3+5W5+fXA1djM0bZ6SQJKCCHEJdNo1bh7u5ObmXfJfbjtO4vbPufkk02nwdS6DkqeEc2BuFIf0tlUBUdVJadY+QR58+6yV/EP8b3kcQkX2Kz2lyvthBBCCFEtwuqGXOkhAKCoFGzFkhzNuzfhpbnjr+CIrgOuxmaFbauZLMETQghxyeKOnC01+WRTFPJ6NiHnlnZYArwq3K+5bgiWyCDMjSOw+ZesD6AA2k2H0Ow5ieZA0eynyKa1CK8fQmZyFi8PfLvC9xVCCCGEuNod3HzkSg8BwJF86jCgNTo3LQc3H+HLZ2Zd4VGJK0kSUEIIIS6LSlVyfpLNS4+llj82Tz3mqMAK96lOygCTGSUzDyUrv/T75uSjjktGsRQ9vTlz5Cztb2wNgF+ozH6qcjW4yKUQQghxvbLVsN/dxJPnCYkKApDZ6VWthhchlyV4QgghLlmDNnX5eP0UJvabjNlotk9NsoGSlY/m+Dmsvu5oT5wrcZ1KrcJqcZ72q9Fp7H0AqrQc3P7cWeH6mDabjcGP3kjfe3vSoE3dS/pMogKkBpQQQghR49z+9GBsNivTJ8y1HyiIz8pzYd1NrV6LyWC65HEoioLNZiPtfAbzTn7J6f1xtOzZ9JL7Ey6o4TWgZAaUEEKIy9K4Y30CI/wBqNs8Ek9fDxRAv/s07puOoSplBtOFySfAkXwqVNHkk1qrpsOA1tRrFUWb3i3w8pOtfYUQQghx/VEUhU4D26PVa1Br1NRvFYVaqy73ugsnxFxO8snenw2du5bhzwzBJ8Cb1jc0R1VK7U5x/ZAZUEIIIS7Z+bhk1v6ymXOnkwA4fSAOsBcIN/VqBZ561HtOoo5PqZT7uXnqyc8xlHrOYrLw4Fv3oNVpK+VewgWuTt+uYUsBhBBCiGvZoa3HWDl7DSaD/eHeyb2xVXo/jVaN2WQp9ZzNauOB/7u7Su8viqnI0jpZgieEEOJq8vrQ/3FyTwyRTSKo16YOW5Zstwc7Wg146kFRsPl6QiUloMpKPnn5e9Lx5rY06lC/Uu4jXGTDxQRUlY9ECCGEEEBKQhrP934Dk9FMi+5N8A/zZePCbVV6z1KTT4q93tM9Lw+v0nuLC7gamxW2rWaSgBJCCHHJ9O46AGo1Dmfid08wfn8cMQfPoBhMqPecxObrifr42Sq5t2+wNxlJWQA8/90T9Ly9S5XcR1yEzIASQgghahS1RoVGp8FkNHPDnd1o178Vu1ftJycjt2IduVg36kI+gd5kpmSh02v5JvpD/EP9Kt6JuHQyA0oIIcS16u0/X2b/hsO069+SXf/uI+bgGcc5dXxKpc18AntAZTEX1Y7KSMpC767juW/HSvJJCCGEEALwC/blqx3vkXDqPB0HtOGzp76rePIJXE4+KSoFW7Fi1pkpWUQ2jeCleU9L8kmUIBXAhBBCXDKfAG+639YJdy93Ni7a6nROrSm/2GVF1GkRWeKYzWajw02tK/U+ogKsVtdfQgghhKgWtRtH0OnmtiiKwpYl26v0XnVLic/cvdxp3KFBld5XlKEisdkViM9kBpQQQohKkRTnPNvJYrbXA7hw5tKl8gv2dfz91Bdj0Gg1NGxb1+m4qGayBE8IIYSo0cqa/aR102LKv7xd7gD8w/w4tS8WnbuO1399npT4FLoMaX/Z/YpLJEvwhBBCXA9e/uEZpj3+Df/9udPpeGUknwBufrgvve/qjt5dR//7elVKn0IIIYQQ17K3/3yZr56dzck9p52OV0byCeC5GY+z/tcttOjRlBbdm1RKn+LaJUvwhBBCVIrAcH/+b/EkWvQoCj60+kt/zuEd6IVGW7SML3r1fgY/0l+STzVJ4VM2V15CCCGEqHZterfgrcWT8A3ydhwr3ETmUjRsV9fxt6IoHN1xgrteuE2STzVFRWIzmQElhBDiaqZSqZi24W3Onkhk7S+b6XhzG2IOnuHr52aTlZpd1FAp2Fzlgt89tUbFA1PuIeHEOUZPvoucjFxeGjCF5PhUtl4ws0rUAFYbLlUptUoCSgghhLhSQusE82vid+zfcIiD/x2j8+B27Fy5h+9e+gGrpdhM9TLis+DIQAY+3I/8HAOPvjeKjYu28dYdH2Kz2di0aBs3jOhWrZ9HXISrsZmjbfWSBJQQQohKF9EgjJGvDAegUfv6GHIN7F69n+O7TnH2RCLY7D+NDdvV4/juUwCoVArzTn5JcO0gRz9BEQE8N2Msv7y/mEFj+l+JjyKEEEIIcdVTqVS07t2C1r1bAPakVGZKNmePJ7Bz1T5y0nKK4rO2dTkefRqAiAahfLv/E3R6raOvXsO78PA7I9m9eh93Thx6BT6NuFpJAkoIIUSVWvPzJj594lunY/5hvjTr2pgXZo1j21+7WfrlCkwmM1uX7eaWx29yatt5UDs6D2pXnUMWLrLZrNhs5df4cqWNEEIIIarPN8/P5a+Zq9Bo1ZhN9o1jwuuH0vP2zoz5333MeeNXdv6zBzdPPUd3nKBlj6ZO19/78u3c+/LtV2Lo4iJcjc0K21Y3SUAJIYSoUj6B9poDKrWK2o0jUBR4Z9krhNYJBqDfvT1Z/9tmNi3ezvGdJxk0ph9qjfpiXYqawmZzbfq21IASQgghapTCmlBe/p72nYXb12PyghccMdjD79zLki//Ijczj+9f+4mP1vzflRyucJWrsVlh22omCSghhBBVquOANny983107jqimtYqtU23oZ34789ddL2lvSSfhBBCCCGq2EPv3EuHAW2o0yIS/xDfUtv0Gt6Vf+aupcewztU8OnGtkgSUEEKIKtewXb2Lnr/5wb7cNLo3KpVsznpVsblY6FJmQAkhhBA1ikqlom3flhdtM3HWk0z4bqzEZ1cTV2MzR9vqJQkoIYQQNYIEN1chqxUUF+oHSA0oIYQQ4qok8dlVxtXYDK5IfCYJKCGEEEJcGpkBJYQQQghRc9TwGVCSzhRCCCGEEEIIIYQQVUpmQAkhhBDiktisVmwuTPO+Etv8CiGEEEJcb1yNzeDKxGeSgBJCCCHEpZEleEIIIYQQNYcswRNCCCGEEEIIIYQQ1zOZASWEEEKIS2O1gSIzoIQQQgghagRXYzO4IvGZJKCEEEIIcWlsNsCF+gGSgBJCCCGEqHquxmaOttVLluAJIYQQQgghhBBCiColM6CEEEIIcUlsVhs2F6Z522QGlBBCCCFElXM1NoMrE5/JDCghhBBCXBqb1fXXJfjqq6+oV68ebm5udOjQgQ0bNly0/bp16+jQoQNubm7Ur1+f6dOnX9J9hRBCCCGuShWJzS4hPqtobHYhSUAJIYQQosb55ZdfePbZZ3n11VfZvXs3vXr1YtCgQcTGxpba/tSpUwwePJhevXqxe/duXnnlFZ5++mkWLFhQzSMXQgghhLj2VDQ2K40koIQQQghxSWxWm8uvivr4448ZM2YMjzzyCM2aNWPatGlERkby9ddfl9p++vTpREVFMW3aNJo1a8YjjzzCww8/zIcffni5H1MIIYQQ4qpQkdisovFZRWOz0lyRGlCFaw0zMzOvxO2FEEII4YLC3+myagSYbQaXpm+bMTn1V0iv16PX60u0NxqN7Ny5k5deesnp+IABA9i8eXOp99iyZQsDBgxwOnbzzTczc+ZMTCYTWq223HFezyQ2E0IIIa4OF4vPXI3NoGLx2aXEZqW5IgmorKwsACIjI6/E7YUQQghRAVlZWfj6+jre63Q6wsLC2Ji43OU+vLy8Svzuv/nmm0yePLlE2+TkZCwWC6GhoU7HQ0NDSUxMLLX/xMTEUtubzWaSk5MJDw93eazXI4nNhBBCiKtL8fjsUmIzcD0+u5TYrDRXJAEVERFBXFwc3t7eKIpyJYYghBBCiHLYbDaysrKIiIhwOu7m5sapU6cwGo0V6uvC3/zSZj8Vd2H70voor31px0VJEpsJIYQQV4fS4rNLic0K+6pIfFbR2OxCVyQBpVKpqF279pW4tRBCCCEqoPjMp+Lc3Nxwc3OrknsGBQWhVqtLPFE7f/58iSdvhcLCwkptr9FoCAwMrJJxXkskNhNCCCGuHqXFZzUtNiuNFCEXQgghRI2i0+no0KED//zzj9Pxf/75h+7du5d6Tbdu3Uq0X7lyJR07dpT6T0IIIYQQl+FSYrPSSAJKCCGEEDXOhAkT+O6775g1axaHDh3iueeeIzY2lrFjxwLw8ssvM3r0aEf7sWPHEhMTw4QJEzh06BCzZs1i5syZTJw48Up9BCGEEEKIa0Z5sZkrrsgSPCGEEEKIi7n77rtJSUnhrbfeIiEhgZYtW7J8+XLq1KkDQEJCArGxsY729erVY/ny5Tz33HN8+eWXRERE8NlnnzFixIgr9RGEEEIIIa4Z5cVmrlBsZe2tLIQQQgghhBBCCCFEJZAleEJcZ/r06cOzzz5b4vjixYsdOxjMnj0bRVFo1qxZiXa//voriqJQt27dEufy8vLw9/cnICCAvLy8Eufr1q2LoigoioKHhwctW7bkm2++cZxPSEhg5MiRNGnSBJVKVeo4hRBCCCGuJRKbCSGuF5KAEkKUytPTk/Pnz7Nlyxan47NmzSIqKqrUaxYsWEDLli1p3rw5CxcuLLVN4ZTNvXv3MmzYMMaOHcsvv/wCgMFgIDg4mFdffZU2bdpU7gcSQgghhLiKSWwmhLjaSQJKCFEqjUbDyJEjmTVrluPYmTNnWLt2LSNHjiz1mpkzZzJq1ChGjRrFzJkzS23j7e1NWFgYDRs25O2336ZRo0YsXrwYsD+F+/TTTxk9enSZW78LIYQQQlyPJDYTQlztJAElhCjTmDFj+OWXX8jNzQXs078HDhxIaGhoibYnTpxgy5Yt3HXXXdx1111s3ryZkydPlnsPNzc3TCZTpY9dCCGEEOJaI7GZEOJqJgkoIUSZ2rZtS4MGDfj999+x2WzMnj2bhx9+uNS2s2bNYtCgQY46AwMHDnR6Qnchs9nM7Nmz2bdvH/3796+qjyCEEEIIcc2Q2EwIcTWTBJQQ4qIefvhhvv/+e9atW0d2djaDBw8u0cZisTBnzhxGjRrlODZq1CjmzJmDxWJxavviiy/i5eWFu7s748aN44UXXuDxxx+v8s8hhBBCCHEtkNhMCHG10lzpAQghqpePjw8ZGRkljqenp+Pj41Pi+H333cekSZOYPHkyo0ePRqMp+T8bf//9N/Hx8dx9991Oxy0WCytXrmTQoEGOYy+88AIPPvggHh4ehIeHO3Z3EUIIIYS4HklsJoS4XsgMKCGuM02bNmXHjh0ljm/fvp0mTZqUOB4QEMDQoUNZt25dmVO8Z86cyT333EN0dLTT67777itR8DIoKIiGDRsSEREhAY4QQgghrnsSmwkhrhcyA0qI68yTTz7JF198wbhx43jsscdwd3fnn3/+YebMmcybN6/Ua2bPns1XX31FYGBgiXNJSUn88ccfLF26lJYtWzqde+CBBxgyZAhJSUkEBwe7NL7o6GgAsrOzSUpKIjo6Gp1OR/PmzSv2QYUQQgghrgISmwkhrheSgBLiOlO3bl02bNjAq6++yoABA8jPz6dx48bMnj2bO++8s9Rr3N3dcXd3L/Xc3Llz8fT0LLVYZd++ffH29mbevHlMmDDBpfG1a9fO8ffOnTv58ccfqVOnDqdPn3bpeiGEEEKIq4nEZkKI64Vis9lsV3oQQgghhBBCCCGEEOLaJTWghBBCCCGEEEIIIUSVkgSUEEIIIYQQQgghhKhSkoASQgghhBBCCCGEEFVKElBCCCGEEEIIIYQQokpJAkoIIYQQQgghhBBCVClJQAkhhBBCCCGEEEKIKiUJKCGEEEIIIYQQQghRpSQBJYQQQgghhBBCCCGqlCSghBBCCCGEEEIIIUSVkgSUEEIIIYQQQgghhKhSkoASQgghhBBCCCGEEFVKElBCCCGEEEIIIYQQokr9P9ZLFZVyiNCJAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sc.pl.umap(adata, color=[\"IGHM\", \"JCHAIN\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Save AnnData\n", "\n", "We can save this `AnnData` object for now." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "adata.write(\"adata2.h5ad\", compression=\"gzip\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Save DandelionPolars" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To save the vdj object, we have two options - either save the `.data` and `.metadata` slots with pandas' functions.\n", "\n", "\n", "\n", "
\n", "\n", "Polars backend update\n", "\n", "Since `vdj.data` is a Polars DataFrame in the polars backend, the pandas `.to_csv()` method is no longer available.\n", "Use Polars' `.write_csv()` instead (note the parameter is `separator=`, not `sep=`).\n", "\n", "
\n" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "vdj.data.collect().write_csv(\"filtered_vdj_table2.tsv\", separator=\"\\t\")" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "vdj.write_h5ddl(\"dandelion_results2.h5ddl\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Concatenating multiple bcr objects\n", "\n", "It is quite common that one might be trying to analyse data from multiple samples. In that case, `dandelion` has a `concat` function to merge the data.\n", "\n", "We will simulate a second object but reading in the same file." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "vdj1 = ddl.read_10x_vdj(folder_location, filename_prefix=\"filtered\")\n", "vdj2 = ddl.read_10x_vdj(folder_location, filename_prefix=\"filtered\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Before you merge the objects, make sure that the \"cell_id\" and \"sequence_id\" are distinct so that you can distinguish them later" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "vdj1.add_cell_prefix(\"run1_\")\n", "vdj2.add_cell_prefix(\"run2_\")" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Lazy Dandelion object with n_obs = 1988 and n_contigs = 5202\n", " data: cell_id, is_cell_10x, sequence_id, high_confidence_10x, sequence_length_10x, locus, v_call, d_call, j_call, c_call, complete_vdj, productive, junction_aa, junction, consensus_count, umi_count, clone_id, raw_consensus_id_10x, sequence, rearrangement_status\n", " metadata: cell_id, clone_id, clone_id_rank, locus_VDJ, locus_VJ, v_call_VDJ, v_call_VJ, d_call_VDJ, j_call_VDJ, j_call_VJ, c_call_VDJ, c_call_VJ, junction_aa_VDJ, junction_aa_VJ, junction_VDJ, junction_VJ, umi_count_VDJ, umi_count_VJ, locus_VDJ_main, locus_VJ_main, v_call_VDJ_main, v_call_VJ_main, d_call_VDJ_main, j_call_VDJ_main, j_call_VJ_main, c_call_VDJ_main, c_call_VJ_main, junction_aa_VDJ_main, junction_aa_VJ_main, junction_VDJ_main, junction_VJ_main, umi_count_VDJ_main, umi_count_VJ_main, isotype, isotype_main, isotype_status, locus_status, chain_status, rearrangement_status_VDJ, rearrangement_status_VJ" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vdj_merged = ddl.tl.concat([vdj1, vdj2])\n", "vdj_merged" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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cell_idis_cell_10xsequence_idhigh_confidence_10xsequence_length_10xlocusv_calld_callj_callc_callcomplete_vdjproductivejunction_aajunctionconsensus_countumi_countclone_idraw_consensus_id_10xsequencerearrangement_status
strboolstrbooli64strstrstrstrstrboolboolstrstri64i64strstrstrstr
"run1_AAACCTGTCATATCGG-1"true"run1_AAACCTGTCATATCGG-1_contig…true556"IGK""IGKV1-8"null"IGKJ4""IGKC"truetrue"CQQYDELPVTF""TGTCAACAATATGACGAACTTCCCGTCACT…913968"clonotype9""clonotype9_consensus_1""TGGGGAGGAGTCAGTCCCAACCAGGACACG…"Standard"
"run1_AAACCTGTCATATCGG-1"true"run1_AAACCTGTCATATCGG-1_contig…true802"IGK"nullnull"IGKJ1"nullfalsefalsenullnull887"clonotype9"null"GGCTGCTATCTTCTCTTTCTCTCAAGGAAG…"Unknown"
"run1_AAACCTGTCCGTTGTC-1"true"run1_AAACCTGTCCGTTGTC-1_contig…true565"IGH""IGHV1-69D""IGHD3-22""IGHJ3""IGHM"truetrue"CATTYYYDSSGYYQNDAFDIW""TGTGCGACTACGTATTACTATGATAGTAGT…416151"clonotype10""clonotype10_consensus_2""ATCACATAACAACCACATTCCTCCTCTAAA…"Standard"
"run1_AAACCTGTCCGTTGTC-1"true"run1_AAACCTGTCCGTTGTC-1_contig…true551"IGK""IGKV1-8"null"IGKJ1""IGKC"truetrue"CQQYYSYPRTF""TGTCAACAGTATTATAGTTACCCTCGGACG…567943"clonotype10""clonotype10_consensus_1""AGGAGTCAGACCCTGTCAGGACACAGCATA…"Standard"
"run1_AAACCTGTCGAGAACG-1"true"run1_AAACCTGTCGAGAACG-1_contig…true642"IGL""IGLV5-45"null"IGLJ3""IGLC3"truetrue"CMIWHSSAWVV""TGTATGATTTGGCACAGCAGCGCTTGGGTG…1316090"clonotype11""clonotype11_consensus_1""ACTGTGGGGGTAAGAGGTTGTGTCCACCAT…"Standard"
……………………………………………………
"run2_TTTGGTTTCAGTGTTG-1"true"run2_TTTGGTTTCAGTGTTG-1_contig…true640"IGL""IGLV2-23"null"IGLJ2""IGLC2"truetrue"CCSYAGSSTFEVF""TGCTGCTCATATGCAGGTAGTAGCACTTTC…649758"clonotype983""clonotype983_consensus_1""GGGGTCACAAGAGGCAGCGCTCTCGGGACG…"Standard"
"run2_TTTGGTTTCAGTGTTG-1"true"run2_TTTGGTTTCAGTGTTG-1_contig…true517"IGH""IGHV2-5"null"IGHJ4""IGHM"truetrue"CAHRFEYFDYW""TGTGCACACAGGTTTGAGTACTTTGACTAC…353033"clonotype983""clonotype983_consensus_2""ATATTTCGTATCTGGGGAGTGACTCCTGTG…"Standard"
"run2_TTTGGTTTCGGTGTCG-1"true"run2_TTTGGTTTCGGTGTCG-1_contig…true568"IGK""IGKV3-11"null"IGKJ4""IGKC"truetrue"CQQRSNWPRLTF""TGTCAGCAGCGTAGCAACTGGCCTAGGCTC…305822"clonotype984""clonotype984_consensus_2""GGGAGAGCCCTGGGGAGGAACTGCTCAGTT…"Standard"
"run2_TTTGGTTTCGGTGTCG-1"true"run2_TTTGGTTTCGGTGTCG-1_contig…true571"IGH""IGHV3-21"null"IGHJ2""IGHM"truetrue"CARDPGDYVEIEWYFDLW""TGTGCGAGAGATCCCGGTGACTACGTAGAA…102612"clonotype984""clonotype984_consensus_1""GAGAGAGGAGCCTTAGCCCTGGATTCCAAG…"Standard"
"run2_TTTGGTTTCGGTGTCG-1"true"run2_TTTGGTTTCGGTGTCG-1_contig…true362"IGH"nullnull"IGHJ6""IGHD"falsefalsenullnull1992"clonotype984"null"GGGACTTCCCAGGCCGACAGTGGTCTGGCT…"Unknown"
" ], "text/plain": [ "shape: (5_202, 20)\n", "┌───────────┬───────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬──────────┐\n", "│ cell_id ┆ is_cell_1 ┆ sequence_ ┆ high_conf ┆ … ┆ clone_id ┆ raw_conse ┆ sequence ┆ rearrang │\n", "│ --- ┆ 0x ┆ id ┆ idence_10 ┆ ┆ --- ┆ nsus_id_1 ┆ --- ┆ ement_st │\n", "│ str ┆ --- ┆ --- ┆ x ┆ ┆ str ┆ 0x ┆ str ┆ atus │\n", "│ ┆ bool ┆ str ┆ --- ┆ ┆ ┆ --- ┆ ┆ --- │\n", "│ ┆ ┆ ┆ bool ┆ ┆ ┆ str ┆ ┆ str │\n", "╞═══════════╪═══════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪══════════╡\n", "│ run1_AAAC ┆ true ┆ run1_AAAC ┆ true ┆ … ┆ clonotype ┆ clonotype ┆ TGGGGAGGA ┆ Standard │\n", "│ CTGTCATAT ┆ ┆ CTGTCATAT ┆ ┆ ┆ 9 ┆ 9_consens ┆ GTCAGTCCC ┆ │\n", "│ CGG-1 ┆ ┆ CGG-1_con ┆ ┆ ┆ ┆ us_1 ┆ AACCAGGAC ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ ACG… ┆ │\n", "│ run1_AAAC ┆ true ┆ run1_AAAC ┆ true ┆ … ┆ clonotype ┆ null ┆ GGCTGCTAT ┆ Unknown │\n", "│ CTGTCATAT ┆ ┆ CTGTCATAT ┆ ┆ ┆ 9 ┆ ┆ CTTCTCTTT ┆ │\n", "│ CGG-1 ┆ ┆ CGG-1_con ┆ ┆ ┆ ┆ ┆ CTCTCAAGG ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ AAG… ┆ │\n", "│ run1_AAAC ┆ true ┆ run1_AAAC ┆ true ┆ … ┆ clonotype ┆ clonotype ┆ ATCACATAA ┆ Standard │\n", "│ CTGTCCGTT ┆ ┆ CTGTCCGTT ┆ ┆ ┆ 10 ┆ 10_consen ┆ CAACCACAT ┆ │\n", "│ GTC-1 ┆ ┆ GTC-1_con ┆ ┆ ┆ ┆ sus_2 ┆ TCCTCCTCT ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ AAA… ┆ │\n", "│ run1_AAAC ┆ true ┆ run1_AAAC ┆ true ┆ … ┆ clonotype ┆ clonotype ┆ AGGAGTCAG ┆ Standard │\n", "│ CTGTCCGTT ┆ ┆ CTGTCCGTT ┆ ┆ ┆ 10 ┆ 10_consen ┆ ACCCTGTCA ┆ │\n", "│ GTC-1 ┆ ┆ GTC-1_con ┆ ┆ ┆ ┆ sus_1 ┆ GGACACAGC ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ ATA… ┆ │\n", "│ run1_AAAC ┆ true ┆ run1_AAAC ┆ true ┆ … ┆ clonotype ┆ clonotype ┆ ACTGTGGGG ┆ Standard │\n", "│ CTGTCGAGA ┆ ┆ CTGTCGAGA ┆ ┆ ┆ 11 ┆ 11_consen ┆ GTAAGAGGT ┆ │\n", "│ ACG-1 ┆ ┆ ACG-1_con ┆ ┆ ┆ ┆ sus_1 ┆ TGTGTCCAC ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ CAT… ┆ │\n", "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", "│ run2_TTTG ┆ true ┆ run2_TTTG ┆ true ┆ … ┆ clonotype ┆ clonotype ┆ GGGGTCACA ┆ Standard │\n", "│ GTTTCAGTG ┆ ┆ GTTTCAGTG ┆ ┆ ┆ 983 ┆ 983_conse ┆ AGAGGCAGC ┆ │\n", "│ TTG-1 ┆ ┆ TTG-1_con ┆ ┆ ┆ ┆ nsus_1 ┆ GCTCTCGGG ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ ACG… ┆ │\n", "│ run2_TTTG ┆ true ┆ run2_TTTG ┆ true ┆ … ┆ clonotype ┆ clonotype ┆ ATATTTCGT ┆ Standard │\n", "│ GTTTCAGTG ┆ ┆ GTTTCAGTG ┆ ┆ ┆ 983 ┆ 983_conse ┆ ATCTGGGGA ┆ │\n", "│ TTG-1 ┆ ┆ TTG-1_con ┆ ┆ ┆ ┆ nsus_2 ┆ GTGACTCCT ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ GTG… ┆ │\n", "│ run2_TTTG ┆ true ┆ run2_TTTG ┆ true ┆ … ┆ clonotype ┆ clonotype ┆ GGGAGAGCC ┆ Standard │\n", "│ GTTTCGGTG ┆ ┆ GTTTCGGTG ┆ ┆ ┆ 984 ┆ 984_conse ┆ CTGGGGAGG ┆ │\n", "│ TCG-1 ┆ ┆ TCG-1_con ┆ ┆ ┆ ┆ nsus_2 ┆ AACTGCTCA ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ GTT… ┆ │\n", "│ run2_TTTG ┆ true ┆ run2_TTTG ┆ true ┆ … ┆ clonotype ┆ clonotype ┆ GAGAGAGGA ┆ Standard │\n", "│ GTTTCGGTG ┆ ┆ GTTTCGGTG ┆ ┆ ┆ 984 ┆ 984_conse ┆ GCCTTAGCC ┆ │\n", "│ TCG-1 ┆ ┆ TCG-1_con ┆ ┆ ┆ ┆ nsus_1 ┆ CTGGATTCC ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ AAG… ┆ │\n", "│ run2_TTTG ┆ true ┆ run2_TTTG ┆ true ┆ … ┆ clonotype ┆ null ┆ GGGACTTCC ┆ Unknown │\n", "│ GTTTCGGTG ┆ ┆ GTTTCGGTG ┆ ┆ ┆ 984 ┆ ┆ CAGGCCGAC ┆ │\n", "│ TCG-1 ┆ ┆ TCG-1_con ┆ ┆ ┆ ┆ ┆ AGTGGTCTG ┆ │\n", "│ ┆ ┆ tig… ┆ ┆ ┆ ┆ ┆ GCT… ┆ │\n", "└───────────┴───────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴──────────┘" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vdj_merged.data.collect()" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (1_988, 40)
cell_idclone_idclone_id_ranklocus_VDJlocus_VJv_call_VDJv_call_VJd_call_VDJj_call_VDJj_call_VJc_call_VDJc_call_VJjunction_aa_VDJjunction_aa_VJjunction_VDJjunction_VJumi_count_VDJumi_count_VJlocus_VDJ_mainlocus_VJ_mainv_call_VDJ_mainv_call_VJ_maind_call_VDJ_mainj_call_VDJ_mainj_call_VJ_mainc_call_VDJ_mainc_call_VJ_mainjunction_aa_VDJ_mainjunction_aa_VJ_mainjunction_VDJ_mainjunction_VJ_mainumi_count_VDJ_mainumi_count_VJ_mainisotypeisotype_mainisotype_statuslocus_statuschain_statusrearrangement_status_VDJrearrangement_status_VJ
strstrcatstrstrstrstrstrstrstrstrstrstrstrstrstri64i64strstrstrstrstrstrstrstrstrstrstrstrstrf64f64strstrstrstrstrstrstr
"run1_AAACCTGTCATATCGG-1""clonotype9""306"null"IGK"null"IGKV1-8"nullnull"IGKJ4"null"IGKC"null"CQQYDELPVTF"null"TGTCAACAATATGACGAACTTCCCGTCACT…068null"IGK"null"IGKV1-8"nullnull"IGKJ4"null"IGKC"null"CQQYDELPVTF"null"TGTCAACAATATGACGAACTTCCCGTCACT…null68.0nullnullnull"Orphan IGK""Orphan VJ"null"Standard"
"run1_AAACCTGTCCGTTGTC-1""clonotype10""360""IGH""IGK""IGHV1-69D""IGKV1-8""IGHD3-22""IGHJ3""IGKJ1""IGHM""IGKC""CATTYYYDSSGYYQNDAFDIW""CQQYYSYPRTF""TGTGCGACTACGTATTACTATGATAGTAGT…"TGTCAACAGTATTATAGTTACCCTCGGACG…5143"IGH""IGK""IGHV1-69D""IGKV1-8""IGHD3-22""IGHJ3""IGKJ1""IGHM""IGKC""CATTYYYDSSGYYQNDAFDIW""CQQYYSYPRTF""TGTGCGACTACGTATTACTATGATAGTAGT…"TGTCAACAGTATTATAGTTACCCTCGGACG…51.043.0"IgM""IgM""IgM""IGH + IGK""Single pair""Standard""Standard"
"run1_AAACCTGTCGAGAACG-1""clonotype11""837""IGH""IGL""IGHV1-2""IGLV5-45"null"IGHJ3""IGLJ3""IGHM""IGLC3""CAREIEGDGVFEIW""CMIWHSSAWVV""TGTGCGAGAGAGATAGAGGGGGACGGTGTT…"TGTATGATTTGGCACAGCAGCGCTTGGGTG…4790"IGH""IGL""IGHV1-2""IGLV5-45"null"IGHJ3""IGLJ3""IGHM""IGLC3""CAREIEGDGVFEIW""CMIWHSSAWVV""TGTGCGAGAGAGATAGAGGGGGACGGTGTT…"TGTATGATTTGGCACAGCAGCGCTTGGGTG…47.090.0"IgM""IgM""IgM""IGH + IGL""Single pair""Standard""Standard"
"run1_AAACCTGTCTTGAGAC-1""clonotype12""562""IGH""IGK""IGHV5-51""IGKV1D-8"null"IGHJ3""IGKJ2""IGHM""IGKC""CARHIRGNRFGNDAFDIW""CQQYYSFPYTF""TGTGCGAGACATATCCGTGGGAACAGATTT…"TGTCAACAGTATTATAGTTTCCCGTACACT…8022"IGH""IGK""IGHV5-51""IGKV1D-8"null"IGHJ3""IGKJ2""IGHM""IGKC""CARHIRGNRFGNDAFDIW""CQQYYSFPYTF""TGTGCGAGACATATCCGTGGGAACAGATTT…"TGTCAACAGTATTATAGTTTCCCGTACACT…80.022.0"IgM""IgM""IgM""IGH + IGK""Single pair""Standard""Standard"
"run1_AAACGGGAGCGACGTA-1""clonotype13""796""IGH""IGL""IGHV4-59""IGLV3-19"null"IGHJ3""IGLJ2""IGHM""IGLC2""CARVGYRAAAGTDAFDIW""CNSRDSSGNHVVF""TGTGCGAGAGTAGGCTATAGAGCAGCAGCT…"TGTAACTCCCGGGACAGCAGTGGTAACCAT…1814"IGH""IGL""IGHV4-59""IGLV3-19"null"IGHJ3""IGLJ2""IGHM""IGLC2""CARVGYRAAAGTDAFDIW""CNSRDSSGNHVVF""TGTGCGAGAGTAGGCTATAGAGCAGCAGCT…"TGTAACTCCCGGGACAGCAGTGGTAACCAT…18.014.0"IgM""IgM""IgM""IGH + IGL""Single pair""Standard""Standard"
…………………………………………………………………………………………………………
"run2_TTTGCGCTCTAACGGT-1""clonotype980""907""IGH""IGL""IGHV3-43""IGLV2-8"null"IGHJ6""IGLJ3""IGHM""IGLC2""CARVSGSYQYNYYYGMDVW""CGSFAGSNIWVF""TGTGCAAGAGTAAGTGGGAGCTACCAATAT…"TGCGGCTCATTTGCAGGCAGCAACATTTGG…46163"IGH""IGL""IGHV3-43""IGLV2-8"null"IGHJ6""IGLJ3""IGHM""IGLC2""CARVSGSYQYNYYYGMDVW""CGSFAGSNIWVF""TGTGCAAGAGTAAGTGGGAGCTACCAATAT…"TGCGGCTCATTTGCAGGCAGCAACATTTGG…46.0163.0"IgM""IgM""IgM""IGH + IGL""Single pair""Standard""Standard"
"run2_TTTGGTTGTAGCCTAT-1""clonotype981""737""IGH""IGK""IGHV4-39""IGKV6-21"null"IGHJ2""IGKJ4""IGHM""IGKC""CARLWVFLTMVRGPDFDLW""CHQSSSLPLTF""TGTGCGAGACTTTGGGTATTTCTTACTATG…"TGTCATCAGAGTAGTAGTTTACCGCTCACT…56"IGH""IGK""IGHV4-39""IGKV6-21"null"IGHJ2""IGKJ4""IGHM""IGKC""CARLWVFLTMVRGPDFDLW""CHQSSSLPLTF""TGTGCGAGACTTTGGGTATTTCTTACTATG…"TGTCATCAGAGTAGTAGTTTACCGCTCACT…5.06.0"IgM""IgM""IgM""IGH + IGK""Single pair""Standard""Standard"
"run2_TTTGGTTTCAGAGCTT-1""clonotype982""275""IGH""IGK""IGHV7-4-1""IGKV3-11""IGHD3-10""IGHJ4""IGKJ5""IGHM""IGKC""CARVFRRYGSGSYYNLW""CQQRSNWLTF""TGTGCGAGAGTTTTTAGACGCTATGGTTCG…"TGTCAGCAGCGTAGCAACTGGCTCACCTTC"7373"IGH""IGK""IGHV7-4-1""IGKV3-11""IGHD3-10""IGHJ4""IGKJ5""IGHM""IGKC""CARVFRRYGSGSYYNLW""CQQRSNWLTF""TGTGCGAGAGTTTTTAGACGCTATGGTTCG…"TGTCAGCAGCGTAGCAACTGGCTCACCTTC"73.073.0"IgM""IgM""IgM""IGH + IGK""Single pair""Standard""Standard"
"run2_TTTGGTTTCAGTGTTG-1""clonotype983""199""IGH""IGL""IGHV2-5""IGLV2-23"null"IGHJ4""IGLJ2""IGHM""IGLC2""CAHRFEYFDYW""CCSYAGSSTFEVF""TGTGCACACAGGTTTGAGTACTTTGACTAC…"TGCTGCTCATATGCAGGTAGTAGCACTTTC…3358"IGH""IGL""IGHV2-5""IGLV2-23"null"IGHJ4""IGLJ2""IGHM""IGLC2""CAHRFEYFDYW""CCSYAGSSTFEVF""TGTGCACACAGGTTTGAGTACTTTGACTAC…"TGCTGCTCATATGCAGGTAGTAGCACTTTC…33.058.0"IgM""IgM""IgM""IGH + IGL""Single pair""Standard""Standard"
"run2_TTTGGTTTCGGTGTCG-1""clonotype984""31""IGH""IGK""IGHV3-21""IGKV3-11"null"IGHJ2""IGKJ4""IGHM""IGKC""CARDPGDYVEIEWYFDLW""CQQRSNWPRLTF""TGTGCGAGAGATCCCGGTGACTACGTAGAA…"TGTCAGCAGCGTAGCAACTGGCCTAGGCTC…1222"IGH""IGK""IGHV3-21""IGKV3-11"null"IGHJ2""IGKJ4""IGHM""IGKC""CARDPGDYVEIEWYFDLW""CQQRSNWPRLTF""TGTGCGAGAGATCCCGGTGACTACGTAGAA…"TGTCAGCAGCGTAGCAACTGGCCTAGGCTC…12.022.0"IgM""IgM""IgM""IGH + IGK""Single pair""Standard""Standard"
" ], "text/plain": [ "shape: (1_988, 40)\n", "┌───────────┬───────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬──────────┐\n", "│ cell_id ┆ clone_id ┆ clone_id_ ┆ locus_VDJ ┆ … ┆ locus_sta ┆ chain_sta ┆ rearrange ┆ rearrang │\n", "│ --- ┆ --- ┆ rank ┆ --- ┆ ┆ tus ┆ tus ┆ ment_stat ┆ ement_st │\n", "│ str ┆ str ┆ --- ┆ str ┆ ┆ --- ┆ --- ┆ us_VDJ ┆ atus_VJ │\n", "│ ┆ ┆ cat ┆ ┆ ┆ str ┆ str ┆ --- ┆ --- │\n", "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ str ┆ str │\n", "╞═══════════╪═══════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪══════════╡\n", "│ run1_AAAC ┆ clonotype ┆ 306 ┆ null ┆ … ┆ Orphan ┆ Orphan VJ ┆ null ┆ Standard │\n", "│ CTGTCATAT ┆ 9 ┆ ┆ ┆ ┆ IGK ┆ ┆ ┆ │\n", "│ CGG-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ run1_AAAC ┆ clonotype ┆ 360 ┆ IGH ┆ … ┆ IGH + IGK ┆ Single ┆ Standard ┆ Standard │\n", "│ CTGTCCGTT ┆ 10 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ GTC-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ run1_AAAC ┆ clonotype ┆ 837 ┆ IGH ┆ … ┆ IGH + IGL ┆ Single ┆ Standard ┆ Standard │\n", "│ CTGTCGAGA ┆ 11 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ ACG-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ run1_AAAC ┆ clonotype ┆ 562 ┆ IGH ┆ … ┆ IGH + IGK ┆ Single ┆ Standard ┆ Standard │\n", "│ CTGTCTTGA ┆ 12 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ GAC-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ run1_AAAC ┆ clonotype ┆ 796 ┆ IGH ┆ … ┆ IGH + IGL ┆ Single ┆ Standard ┆ Standard │\n", "│ GGGAGCGAC ┆ 13 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ GTA-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", "│ run2_TTTG ┆ clonotype ┆ 907 ┆ IGH ┆ … ┆ IGH + IGL ┆ Single ┆ Standard ┆ Standard │\n", "│ CGCTCTAAC ┆ 980 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ GGT-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ run2_TTTG ┆ clonotype ┆ 737 ┆ IGH ┆ … ┆ IGH + IGK ┆ Single ┆ Standard ┆ Standard │\n", "│ GTTGTAGCC ┆ 981 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ TAT-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ run2_TTTG ┆ clonotype ┆ 275 ┆ IGH ┆ … ┆ IGH + IGK ┆ Single ┆ Standard ┆ Standard │\n", "│ GTTTCAGAG ┆ 982 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ CTT-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ run2_TTTG ┆ clonotype ┆ 199 ┆ IGH ┆ … ┆ IGH + IGL ┆ Single ┆ Standard ┆ Standard │\n", "│ GTTTCAGTG ┆ 983 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ TTG-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "│ run2_TTTG ┆ clonotype ┆ 31 ┆ IGH ┆ … ┆ IGH + IGK ┆ Single ┆ Standard ┆ Standard │\n", "│ GTTTCGGTG ┆ 984 ┆ ┆ ┆ ┆ ┆ pair ┆ ┆ │\n", "│ TCG-1 ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", "└───────────┴───────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴──────────┘" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vdj_merged.metadata.collect()" ] } ], "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": 4 }