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nnsvs_test_ofuton_p_utagoe_db
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "nnsvs_test_ofuton_p_utagoe_db",
"provenance": [],
"authorship_tag": "ABX9TyN1Ws4d+Z29PzdF16SU/V55",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/taroushirani/30f28aae1e27a28708c30a6acf036085/nnsvs_test_ofuton_p_utagoe_db.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "XpoUEOtIWx9X",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 122
},
"outputId": "69ad8e11-18c2-453f-c87e-0e7752835de0"
},
"source": [
"# google driveの設定\n",
"from google.colab import drive\n",
"drive.mount('/content/drive')\n",
"#symbolic linkを張る\n",
"!ln -s \"/content/drive/My Drive\" /content/gdrive"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
"\n",
"Enter your authorization code:\n",
"··········\n",
"Mounted at /content/drive\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "FCY9PjEUXT5i",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 430
},
"outputId": "807ffb04-e44d-4ef3-862e-57b3c8cf7cd3"
},
"source": [
"! pip install -U numpy cython pyworld\n",
"! rm -rf hts_engine_API sinsy pysinsy nnmnkwii nnsvs"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Collecting numpy\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/93/0b/71ae818646c1a80fbe6776d41f480649523ed31243f1f34d9d7e41d70195/numpy-1.19.0-cp36-cp36m-manylinux2010_x86_64.whl (14.6MB)\n",
"\u001b[K |████████████████████████████████| 14.6MB 207kB/s \n",
"\u001b[?25hRequirement already up-to-date: cython in /usr/local/lib/python3.6/dist-packages (0.29.20)\n",
"Collecting pyworld\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/25/cb/355cc45aa3dcc8d0e19c0d6156d8406676a17621984604115adf29260fb2/pyworld-0.2.10.tar.gz (73kB)\n",
"\u001b[K |████████████████████████████████| 81kB 8.8MB/s \n",
"\u001b[?25hBuilding wheels for collected packages: pyworld\n",
" Building wheel for pyworld (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for pyworld: filename=pyworld-0.2.10-cp36-cp36m-linux_x86_64.whl size=611055 sha256=d365aa9d0fe993cdb3f5aab6f54699ec7835dcadbbb69854a6d687f9421e09fb\n",
" Stored in directory: /root/.cache/pip/wheels/7d/11/e0/b197a0bafe9a34ade04f4b85a43fd8754b853f4a59e24a9022\n",
"Successfully built pyworld\n",
"\u001b[31mERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.\u001b[0m\n",
"\u001b[31mERROR: albumentations 0.1.12 has requirement imgaug<0.2.7,>=0.2.5, but you'll have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
"Installing collected packages: numpy, pyworld\n",
" Found existing installation: numpy 1.18.5\n",
" Uninstalling numpy-1.18.5:\n",
" Successfully uninstalled numpy-1.18.5\n",
"Successfully installed numpy-1.19.0 pyworld-0.2.10\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"application/vnd.colab-display-data+json": {
"pip_warning": {
"packages": [
"numpy"
]
}
}
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "iV4ghgxzXaNt",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "d561940b-c1f2-49c9-9442-6249f6750ee4"
},
"source": [
"# hts_engine_APIとsinsyのビルド(pysinsyに必要)\n",
"! git clone -q https://github.com/r9y9/hts_engine_API\n",
"! cd hts_engine_API/src && ./waf configure --prefix=/usr/ && ./waf build > hts_engine_API_build.log 2>&1 && ./waf install\n",
"! git clone -q https://github.com/r9y9/sinsy\n",
"! cd sinsy/src/ && mkdir -p build && cd build && cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON -DCMAKE_INSTALL_PREFIX=/usr/ .. && make -j > sinsy_build.log 2>&1 && make install"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"\u001b[32m\u001b[0mSetting top to :\u001b[0m \u001b[0m\u001b[32m\u001b[32m/content/hts_engine_API/src\u001b[0m \u001b[0m\n",
"\u001b[32m\u001b[0mSetting out to :\u001b[0m \u001b[0m\u001b[32m\u001b[32m/content/hts_engine_API/src/build\u001b[0m \u001b[0m\n",
"\u001b[32m\u001b[0mChecking for waf version in 1.7.11-2.1.0 :\u001b[0m \u001b[0m\u001b[32m\u001b[32mok\u001b[0m \u001b[0m\n",
"\u001b[32m\u001b[0mChecking for 'gcc' (C compiler) :\u001b[0m \u001b[0m\u001b[32m\u001b[32m/usr/bin/gcc\u001b[0m \u001b[0m\n",
"\u001b[32m\u001b[0mChecking for header stdlib.h :\u001b[0m \u001b[0m\u001b[32m\u001b[32myes\u001b[0m \u001b[0m\n",
"\u001b[32m\u001b[0mChecking for header string.h :\u001b[0m \u001b[0m\u001b[32m\u001b[32myes\u001b[0m \u001b[0m\n",
"\n",
"hts_engine_API has been configured as follows:\n",
"\n",
"[Build information]\n",
"Package: hts_engine_API-1.0.9\n",
"build (compile on): x86_64-linux\n",
"host endian: little\n",
"Compiler: gcc\n",
"Compiler version: 7.5.0\n",
"CFLAGS: -O2 -Wall -fno-common -Wstrict-prototypes\n",
"\n",
"\u001b[32m'configure' finished successfully (0.558s)\u001b[0m\n",
"\u001b[32mWaf: Entering directory `/content/hts_engine_API/src/build'\u001b[0m\n",
"\u001b[32m\u001b[0m+ install \u001b[01;34m/usr/include/HTS_hidden.h\u001b[0m (from lib/HTS_hidden.h)\u001b[0m\n",
"\u001b[32m\u001b[0m+ install \u001b[01;34m/usr/include/HTS_engine.h\u001b[0m (from include/HTS_engine.h)\u001b[0m\n",
"\u001b[32m\u001b[0m+ symlink \u001b[01;34m/usr/lib/libhts_engine_API.so\u001b[0m (to libhts_engine_API.so.1.0.9)\u001b[0m\n",
"\u001b[32m\u001b[0m+ symlink \u001b[01;34m/usr/lib/libhts_engine_API.so.1\u001b[0m (to libhts_engine_API.so.1.0.9)\u001b[0m\n",
"\u001b[32m\u001b[0m+ install \u001b[01;34m/usr/lib/libhts_engine_API.so.1.0.9\u001b[0m (from build/lib/libhts_engine_API.so)\u001b[0m\n",
"\u001b[32m\u001b[0m+ install \u001b[01;34m/usr/bin/hts_engine\u001b[0m (from build/bin/hts_engine)\u001b[0m\n",
"\u001b[32m\u001b[0m+ install \u001b[01;34m/usr/lib/pkgconfig/hts_engine_API.pc\u001b[0m (from build/hts_engine_API.pc)\u001b[0m\n",
"\u001b[32mWaf: Leaving directory `/content/hts_engine_API/src/build'\u001b[0m\n",
"\u001b[32m'install' finished successfully (0.054s)\u001b[0m\n",
"-- The C compiler identification is GNU 7.5.0\n",
"-- The CXX compiler identification is GNU 7.5.0\n",
"-- Check for working C compiler: /usr/bin/cc\n",
"-- Check for working C compiler: /usr/bin/cc -- works\n",
"-- Detecting C compiler ABI info\n",
"-- Detecting C compiler ABI info - done\n",
"-- Detecting C compile features\n",
"-- Detecting C compile features - done\n",
"-- Check for working CXX compiler: /usr/bin/c++\n",
"-- Check for working CXX compiler: /usr/bin/c++ -- works\n",
"-- Detecting CXX compiler ABI info\n",
"-- Detecting CXX compiler ABI info - done\n",
"-- Detecting CXX compile features\n",
"-- Detecting CXX compile features - done\n",
"-- Configuring done\n",
"-- Generating done\n",
"-- Build files have been written to: /content/sinsy/src/build\n",
"[ 95%] Built target sinsy\n",
"[100%] Built target sinsy-bin\n",
"\u001b[36mInstall the project...\u001b[0m\n",
"-- Install configuration: \"Release\"\n",
"-- Installing: /usr/lib/libsinsy.so.0.9.2\n",
"-- Installing: /usr/lib/libsinsy.so.0.9\n",
"-- Installing: /usr/lib/libsinsy.so\n",
"-- Installing: /usr/bin/sinsy\n",
"-- Set runtime path of \"/usr/bin/sinsy\" to \"\"\n",
"-- Installing: /usr/include/sinsy\n",
"-- Installing: /usr/include/sinsy/sinsy.h\n",
"-- Installing: /usr/include/sinsy/ILabelOutput.h\n",
"-- Installing: /usr/include/sinsy/LabelStrings.h\n",
"-- Installing: /usr/lib/sinsy/dic\n",
"-- Installing: /usr/lib/sinsy/dic/japanese.macron\n",
"-- Installing: /usr/lib/sinsy/dic/japanese.utf_8.conf\n",
"-- Installing: /usr/lib/sinsy/dic/japanese.euc_jp.table\n",
"-- Installing: /usr/lib/sinsy/dic/japanese.utf_8.table\n",
"-- Installing: /usr/lib/sinsy/dic/japanese.shift_jis.conf\n",
"-- Installing: /usr/lib/sinsy/dic/japanese.shift_jis.table\n",
"-- Installing: /usr/lib/sinsy/dic/japanese.euc_jp.conf\n",
"-- Installing: /usr/lib/pkgconfig/sinsy.pc\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "UdRQ5pMuYtFj",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 187
},
"outputId": "630707bf-1cf8-42ea-dbb8-15ad3159988e"
},
"source": [
"# Python dependencies\n",
"! git clone -q https://github.com/r9y9/pysinsy\n",
"! cd pysinsy && export SINSY_INSTALL_PREFIX=/usr/ && pip install -q .\n",
"! git clone -q https://github.com/r9y9/nnmnkwii\n",
"! cd nnmnkwii && pip install -q .\n",
"! git clone -q https://github.com/r9y9/nnsvs \n",
"! cd nnsvs && pip install -q ."
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
" Building wheel for pysinsy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
"\u001b[K |████████████████████████████████| 419kB 2.8MB/s \n",
"\u001b[K |████████████████████████████████| 368kB 13.3MB/s \n",
"\u001b[?25h Building wheel for nnmnkwii (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for pysptk (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for bandmat (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
"\u001b[K |████████████████████████████████| 81kB 2.3MB/s \n",
"\u001b[K |████████████████████████████████| 1.6MB 8.3MB/s \n",
"\u001b[?25h Building wheel for nnsvs (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for librosa (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "4d3gou5qfhRv",
"colab_type": "code",
"colab": {}
},
"source": [
"! cd nnsvs/egs && git clone -q https://github.com/taroushirani/ofuton_p_utagoe_db.git"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "_QhtzUCKfvjc",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "d4f767f2-57e2-4c5f-acd2-5c3eff6f7294"
},
"source": [
"! cd /content/gdrive && unzip /content/gdrive/OFUTON_P_UTAGOE_DB.zip"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Archive: /content/gdrive/OFUTON_P_UTAGOE_DB.zip\n",
" creating: OFUTON_P_UTAGOE_DB/\n",
" inflating: OFUTON_P_UTAGOE_DB/Note.txt \n",
" inflating: OFUTON_P_UTAGOE_DB/PhonemeList.pdf \n",
" inflating: OFUTON_P_UTAGOE_DB/ReleaseNote.txt \n",
" inflating: OFUTON_P_UTAGOE_DB/SongList.pdf \n",
" creating: OFUTON_P_UTAGOE_DB/akai_kutsu/\n",
" inflating: OFUTON_P_UTAGOE_DB/akai_kutsu/akai_kutsu.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/akai_kutsu/akai_kutsu.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/akai_kutsu/akai_kutsu.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/akai_kutsu/akai_kutsu.wav \n",
" creating: OFUTON_P_UTAGOE_DB/akatombo/\n",
" inflating: OFUTON_P_UTAGOE_DB/akatombo/akatombo.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/akatombo/akatombo.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/akatombo/akatombo.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/akatombo/akatombo.wav \n",
" creating: OFUTON_P_UTAGOE_DB/amefuri/\n",
" inflating: OFUTON_P_UTAGOE_DB/amefuri/amefuri.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/amefuri/amefuri.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/amefuri/amefuri.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/amefuri/amefuri.wav \n",
" creating: OFUTON_P_UTAGOE_DB/antagata_dokosa/\n",
" inflating: OFUTON_P_UTAGOE_DB/antagata_dokosa/antagata_dokosa.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/antagata_dokosa/antagata_dokosa.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/antagata_dokosa/antagata_dokosa.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/antagata_dokosa/antagata_dokosa.wav \n",
" creating: OFUTON_P_UTAGOE_DB/aogeba_tootoshi/\n",
" inflating: OFUTON_P_UTAGOE_DB/aogeba_tootoshi/aogeba_tootoshi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/aogeba_tootoshi/aogeba_tootoshi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/aogeba_tootoshi/aogeba_tootoshi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/aogeba_tootoshi/aogeba_tootoshi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/arupusu_itimanjaku/\n",
" inflating: OFUTON_P_UTAGOE_DB/arupusu_itimanjaku/arupusu_itimanjaku.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/arupusu_itimanjaku/arupusu_itimanjaku.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/arupusu_itimanjaku/arupusu_itimanjaku.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/arupusu_itimanjaku/arupusu_itimanjaku.wav \n",
" creating: OFUTON_P_UTAGOE_DB/chatsumi/\n",
" inflating: OFUTON_P_UTAGOE_DB/chatsumi/chatsumi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/chatsumi/chatsumi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/chatsumi/chatsumi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/chatsumi/chatsumi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/chouchou/\n",
" inflating: OFUTON_P_UTAGOE_DB/chouchou/chouchou.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/chouchou/chouchou.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/chouchou/chouchou.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/chouchou/chouchou.wav \n",
" creating: OFUTON_P_UTAGOE_DB/daikokusama/\n",
" inflating: OFUTON_P_UTAGOE_DB/daikokusama/daikokusama.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/daikokusama/daikokusama.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/daikokusama/daikokusama.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/daikokusama/daikokusama.wav \n",
" creating: OFUTON_P_UTAGOE_DB/donguri_korokoro/\n",
" inflating: OFUTON_P_UTAGOE_DB/donguri_korokoro/donguri_korokoro.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/donguri_korokoro/donguri_korokoro.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/donguri_korokoro/donguri_korokoro.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/donguri_korokoro/donguri_korokoro.wav \n",
" creating: OFUTON_P_UTAGOE_DB/furusato/\n",
" inflating: OFUTON_P_UTAGOE_DB/furusato/furusato.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/furusato/furusato.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/furusato/furusato.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/furusato/furusato.wav \n",
" creating: OFUTON_P_UTAGOE_DB/genkotsuyamano_tanukisan/\n",
" inflating: OFUTON_P_UTAGOE_DB/genkotsuyamano_tanukisan/genkotsuyamano_tanukisan.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/genkotsuyamano_tanukisan/genkotsuyamano_tanukisan.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/genkotsuyamano_tanukisan/genkotsuyamano_tanukisan.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/genkotsuyamano_tanukisan/genkotsuyamano_tanukisan.wav \n",
" creating: OFUTON_P_UTAGOE_DB/haruga_kita/\n",
" inflating: OFUTON_P_UTAGOE_DB/haruga_kita/haruga_kita.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/haruga_kita/haruga_kita.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/haruga_kita/haruga_kita.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/haruga_kita/haruga_kita.wav \n",
" creating: OFUTON_P_UTAGOE_DB/haruno_ogawa/\n",
" inflating: OFUTON_P_UTAGOE_DB/haruno_ogawa/haruno_ogawa.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/haruno_ogawa/haruno_ogawa.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/haruno_ogawa/haruno_ogawa.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/haruno_ogawa/haruno_ogawa.wav \n",
" creating: OFUTON_P_UTAGOE_DB/haruyo_koi/\n",
" inflating: OFUTON_P_UTAGOE_DB/haruyo_koi/haruyo_koi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/haruyo_koi/haruyo_koi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/haruyo_koi/haruyo_koi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/haruyo_koi/haruyo_koi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/hato/\n",
" inflating: OFUTON_P_UTAGOE_DB/hato/hato.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/hato/hato.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/hato/hato.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/hato/hato.wav \n",
" creating: OFUTON_P_UTAGOE_DB/hato_low/\n",
" inflating: OFUTON_P_UTAGOE_DB/hato_low/hato_low.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/hato_low/hato_low.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/hato_low/hato_low.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/hato_low/hato_low.wav \n",
" creating: OFUTON_P_UTAGOE_DB/hiraita_hiraita/\n",
" inflating: OFUTON_P_UTAGOE_DB/hiraita_hiraita/hiraita_hiraita.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/hiraita_hiraita/hiraita_hiraita.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/hiraita_hiraita/hiraita_hiraita.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/hiraita_hiraita/hiraita_hiraita.wav \n",
" creating: OFUTON_P_UTAGOE_DB/hotaruno_hikari/\n",
" inflating: OFUTON_P_UTAGOE_DB/hotaruno_hikari/hotaruno_hikari.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/hotaruno_hikari/hotaruno_hikari.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/hotaruno_hikari/hotaruno_hikari.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/hotaruno_hikari/hotaruno_hikari.wav \n",
" creating: OFUTON_P_UTAGOE_DB/issunboushi/\n",
" inflating: OFUTON_P_UTAGOE_DB/issunboushi/issunboushi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/issunboushi/issunboushi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/issunboushi/issunboushi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/issunboushi/issunboushi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/kagome_kagome/\n",
" inflating: OFUTON_P_UTAGOE_DB/kagome_kagome/kagome_kagome.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/kagome_kagome/kagome_kagome.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/kagome_kagome/kagome_kagome.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/kagome_kagome/kagome_kagome.wav \n",
" creating: OFUTON_P_UTAGOE_DB/kagome_kagome_low/\n",
" inflating: OFUTON_P_UTAGOE_DB/kagome_kagome_low/kagome_kagome_low.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/kagome_kagome_low/kagome_kagome_low.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/kagome_kagome_low/kagome_kagome_low.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/kagome_kagome_low/kagome_kagome_low.wav \n",
" creating: OFUTON_P_UTAGOE_DB/kamomeno_suiheisan/\n",
" inflating: OFUTON_P_UTAGOE_DB/kamomeno_suiheisan/kamomeno_suiheisan.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/kamomeno_suiheisan/kamomeno_suiheisan.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/kamomeno_suiheisan/kamomeno_suiheisan.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/kamomeno_suiheisan/kamomeno_suiheisan.wav \n",
" creating: OFUTON_P_UTAGOE_DB/katatsumuri/\n",
" inflating: OFUTON_P_UTAGOE_DB/katatsumuri/katatsumuri.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/katatsumuri/katatsumuri.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/katatsumuri/katatsumuri.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/katatsumuri/katatsumuri.wav \n",
" creating: OFUTON_P_UTAGOE_DB/kintaro/\n",
" inflating: OFUTON_P_UTAGOE_DB/kintaro/kintaro.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/kintaro/kintaro.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/kintaro/kintaro.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/kintaro/kintaro.wav \n",
" creating: OFUTON_P_UTAGOE_DB/koganemushi/\n",
" inflating: OFUTON_P_UTAGOE_DB/koganemushi/koganemushi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/koganemushi/koganemushi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/koganemushi/koganemushi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/koganemushi/koganemushi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/koinobori/\n",
" inflating: OFUTON_P_UTAGOE_DB/koinobori/koinobori.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/koinobori/koinobori.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/koinobori/koinobori.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/koinobori/koinobori.wav \n",
" creating: OFUTON_P_UTAGOE_DB/momiji/\n",
" inflating: OFUTON_P_UTAGOE_DB/momiji/momiji.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/momiji/momiji.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/momiji/momiji.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/momiji/momiji.wav \n",
" creating: OFUTON_P_UTAGOE_DB/momotarou/\n",
" inflating: OFUTON_P_UTAGOE_DB/momotarou/momotarou.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/momotarou/momotarou.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/momotarou/momotarou.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/momotarou/momotarou.wav \n",
" creating: OFUTON_P_UTAGOE_DB/morobito_kozorite/\n",
" inflating: OFUTON_P_UTAGOE_DB/morobito_kozorite/morobito_kozorite.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/morobito_kozorite/morobito_kozorite.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/morobito_kozorite/morobito_kozorite.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/morobito_kozorite/morobito_kozorite.wav \n",
" creating: OFUTON_P_UTAGOE_DB/mushino_koe/\n",
" inflating: OFUTON_P_UTAGOE_DB/mushino_koe/antagata_dokosa.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/mushino_koe/mushino_koe.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/mushino_koe/mushino_koe.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/mushino_koe/mushino_koe.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/mushino_koe/mushino_koe.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_1/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_1/my_grandfathers_clock_1_1.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_1/my_grandfathers_clock_1_1.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_1/my_grandfathers_clock_1_1.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_1/my_grandfathers_clock_1_1.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_2/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_2/my_grandfathers_clock_1_2.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_2/my_grandfathers_clock_1_2.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_2/my_grandfathers_clock_1_2.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_2/my_grandfathers_clock_1_2.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_3/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_3/my_grandfathers_clock_1_3.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_3/my_grandfathers_clock_1_3.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_3/my_grandfathers_clock_1_3.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_1_3/my_grandfathers_clock_1_3.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_1/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_1/my_grandfathers_clock_2_1.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_1/my_grandfathers_clock_2_1.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_1/my_grandfathers_clock_2_1.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_1/my_grandfathers_clock_2_1.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_2/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_2/my_grandfathers_clock_2_2.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_2/my_grandfathers_clock_2_2.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_2/my_grandfathers_clock_2_2.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_2/my_grandfathers_clock_2_2.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_3/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_3/my_grandfathers_clock_2_3.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_3/my_grandfathers_clock_2_3.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_3/my_grandfathers_clock_2_3.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_2_3/my_grandfathers_clock_2_3.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_1/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_1/my_grandfathers_clock_3_1.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_1/my_grandfathers_clock_3_1.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_1/my_grandfathers_clock_3_1.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_1/my_grandfathers_clock_3_1.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_2/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_2/my_grandfathers_clock_3_2.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_2/my_grandfathers_clock_3_2.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_2/my_grandfathers_clock_3_2.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_2/my_grandfathers_clock_3_2.wav \n",
" creating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_3/\n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_3/my_grandfathers_clock_3_3.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_3/my_grandfathers_clock_3_3.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_3/my_grandfathers_clock_3_3.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/my_grandfathers_clock_3_3/my_grandfathers_clock_3_3.wav \n",
" creating: OFUTON_P_UTAGOE_DB/nanatsunoko/\n",
" inflating: OFUTON_P_UTAGOE_DB/nanatsunoko/nanatsunoko.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/nanatsunoko/nanatsunoko.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/nanatsunoko/nanatsunoko.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/nanatsunoko/nanatsunoko.wav \n",
" creating: OFUTON_P_UTAGOE_DB/oborodukiyo/\n",
" inflating: OFUTON_P_UTAGOE_DB/oborodukiyo/oborodukiyo.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/oborodukiyo/oborodukiyo.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/oborodukiyo/oborodukiyo.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/oborodukiyo/oborodukiyo.wav \n",
" creating: OFUTON_P_UTAGOE_DB/sakura_sakura/\n",
" inflating: OFUTON_P_UTAGOE_DB/sakura_sakura/sakura_sakura.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/sakura_sakura/sakura_sakura.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/sakura_sakura/sakura_sakura.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/sakura_sakura/sakura_sakura.wav \n",
" creating: OFUTON_P_UTAGOE_DB/seikurabe/\n",
" inflating: OFUTON_P_UTAGOE_DB/seikurabe/seikurabe.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/seikurabe/seikurabe.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/seikurabe/seikurabe.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/seikurabe/seikurabe.wav \n",
" creating: OFUTON_P_UTAGOE_DB/shabondama/\n",
" inflating: OFUTON_P_UTAGOE_DB/shabondama/shabondama.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/shabondama/shabondama.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/shabondama/shabondama.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/shabondama/shabondama.wav \n",
" creating: OFUTON_P_UTAGOE_DB/shoujoujino_tanikibayashi/\n",
" inflating: OFUTON_P_UTAGOE_DB/shoujoujino_tanikibayashi/shoujoujino_tanukibayashi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/shoujoujino_tanikibayashi/shoujoujino_tanukibayashi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/shoujoujino_tanikibayashi/shoujoujino_tanukibayashi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/shoujoujino_tanikibayashi/shoujoujino_tanukibayashi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/tetsudou_shouka/\n",
" inflating: OFUTON_P_UTAGOE_DB/tetsudou_shouka/tetsudou_shouka.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/tetsudou_shouka/tetsudou_shouka.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/tetsudou_shouka/tetsudou_shouka.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/tetsudou_shouka/tetsudou_shouka.wav \n",
" creating: OFUTON_P_UTAGOE_DB/tombi/\n",
" inflating: OFUTON_P_UTAGOE_DB/tombi/tombi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/tombi/tombi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/tombi/tombi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/tombi/tombi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/tooryanse/\n",
" inflating: OFUTON_P_UTAGOE_DB/tooryanse/tooryanse.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/tooryanse/tooryanse.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/tooryanse/tooryanse.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/tooryanse/tooryanse.wav \n",
" creating: OFUTON_P_UTAGOE_DB/urashima_taro/\n",
" inflating: OFUTON_P_UTAGOE_DB/urashima_taro/urashima_taro.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/urashima_taro/urashima_taro.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/urashima_taro/urashima_taro.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/urashima_taro/urashima_taro.wav \n",
" creating: OFUTON_P_UTAGOE_DB/usagi/\n",
" inflating: OFUTON_P_UTAGOE_DB/usagi/usagi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/usagi/usagi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/usagi/usagi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/usagi/usagi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/usagito_kame/\n",
" inflating: OFUTON_P_UTAGOE_DB/usagito_kame/usagito_kame.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/usagito_kame/usagito_kame.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/usagito_kame/usagito_kame.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/usagito_kame/usagito_kame.wav \n",
" creating: OFUTON_P_UTAGOE_DB/warewa_uminoko/\n",
" inflating: OFUTON_P_UTAGOE_DB/warewa_uminoko/warewa_uminoko.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/warewa_uminoko/warewa_uminoko.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/warewa_uminoko/warewa_uminoko.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/warewa_uminoko/warewa_uminoko.wav \n",
" creating: OFUTON_P_UTAGOE_DB/yuki/\n",
" inflating: OFUTON_P_UTAGOE_DB/yuki/yuki.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/yuki/yuki.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/yuki/yuki.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/yuki/yuki.wav \n",
" creating: OFUTON_P_UTAGOE_DB/yurikagono_uta/\n",
" inflating: OFUTON_P_UTAGOE_DB/yurikagono_uta/yurikagono_uta.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/yurikagono_uta/yurikagono_uta.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/yurikagono_uta/yurikagono_uta.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/yurikagono_uta/yurikagono_uta.wav \n",
" creating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi/\n",
" inflating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi/zuizuizukkorobashi.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi/zuizuizukkorobashi.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi/zuizuizukkorobashi.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi/zuizuizukkorobashi.wav \n",
" creating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi_low/\n",
" inflating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi_low/zuizuizukkorobashi_low.lab \n",
" inflating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi_low/zuizuizukkorobashi_low.mid \n",
" inflating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi_low/zuizuizukkorobashi_low.musicxml \n",
" inflating: OFUTON_P_UTAGOE_DB/zuizuizukkorobashi_low/zuizuizukkorobashi_low.wav \n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "m-TVJk1SGW_n",
"colab_type": "code",
"colab": {}
},
"source": [
"RECIPE_ROOT=\"/content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/\""
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "hT4crM1wgCd7",
"colab_type": "code",
"colab": {}
},
"source": [
"! sed -i 's#[$]HOME\\/data#\\/content\\/gdrive#g' $RECIPE_ROOT/run.sh "
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "Veas7tJiGj8E",
"colab_type": "code",
"colab": {}
},
"source": [
"# stage -1の実行(data のダウンロード)\n",
"! cd $RECIPE_ROOT && bash run.sh --stage -1 --stop-stage -1"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "eQ044vyvjG2p",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "89e85a78-f64d-424e-8a60-dee3a8427671"
},
"source": [
"! pip install -q jaconv"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
" Building wheel for jaconv (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "8Ce6Fq2fGt17",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "3cefeff6-fc93-4910-8be9-5a712520c0c6"
},
"source": [
"# stage 0の実行(data preparation)\n",
"! cd $RECIPE_ROOT && bash run.sh --stage 0 --stop-stage 0"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"stage 0: Data preparation\n",
"akai_kutsu.lab 0.0\n",
"akatombo.lab 0.0\n",
"amefuri.lab 0.0\n",
"antagata_dokosa.lab 0.0\n",
"aogeba_tootoshi.lab 0.0\n",
"arupusu_itimanjaku.lab 0.0\n",
"chatsumi.lab 1.0\n",
"chouchou.lab 0.0\n",
"daikokusama.lab 0.0\n",
"donguri_korokoro.lab 0.0\n",
"furusato.lab 0.0\n",
"genkotsuyamano_tanukisan.lab 0.0\n",
"haruga_kita.lab 0.0\n",
"haruno_ogawa.lab 0.0\n",
"haruyo_koi.lab 0.0\n",
"hato.lab 0.0\n",
"hato_low.lab 0.0\n",
"hiraita_hiraita.lab 0.0\n",
"hotaruno_hikari.lab 0.0\n",
"issunboushi.lab 0.0\n",
"kagome_kagome.lab 0.0\n",
"kagome_kagome_low.lab 0.0\n",
"kamomeno_suiheisan.lab 0.0\n",
"katatsumuri.lab 0.0\n",
"kintaro.lab 0.0\n",
"koganemushi.lab 0.0\n",
"koinobori.lab 0.0\n",
"momiji.lab 0.0\n",
"momotarou.lab 0.0\n",
"morobito_kozorite.lab 0.0\n",
"mushino_koe.lab 0.0\n",
"my_grandfathers_clock_1_1.lab 0.0\n",
"my_grandfathers_clock_1_2.lab 0.0\n",
"my_grandfathers_clock_1_3.lab 0.0\n",
"my_grandfathers_clock_2_1.lab 0.0\n",
"my_grandfathers_clock_2_2.lab 0.0\n",
"my_grandfathers_clock_2_3.lab 0.0\n",
"my_grandfathers_clock_3_1.lab 0.0\n",
"my_grandfathers_clock_3_2.lab 0.0\n",
"my_grandfathers_clock_3_3.lab 0.0\n",
"nanatsunoko.lab 0.0\n",
"oborodukiyo.lab 0.0\n",
"sakura_sakura.lab 0.0\n",
"seikurabe.lab 0.0\n",
"shabondama.lab 0.0\n",
"shoujoujino_tanukibayashi.lab 0.0\n",
"tetsudou_shouka.lab 0.0\n",
"tombi.lab 0.0\n",
"tooryanse.lab 0.0\n",
"urashima_taro.lab 0.0\n",
"usagi.lab 0.0\n",
"usagito_kame.lab 0.0\n",
"warewa_uminoko.lab 0.0\n",
"yuki.lab 0.0\n",
"yurikagono_uta.lab 0.0\n",
"zuizuizukkorobashi.lab 0.0\n",
"zuizuizukkorobashi_low.lab 0.0\n",
"akai_kutsu.lab: segment duration min 8.68, max 13.41, mean 9.69\n",
"akatombo.lab: segment duration min 6.84, max 10.55, mean 8.64\n",
"amefuri.lab: segment duration min 16.53, max 16.94, mean 16.73\n",
"antagata_dokosa.lab: segment duration min 6.59, max 15.54, mean 11.64\n",
"aogeba_tootoshi.lab: segment duration min 8.21, max 12.59, mean 9.01\n",
"arupusu_itimanjaku.lab: segment duration min 9.03, max 12.41, mean 11.12\n",
"chatsumi.lab: segment duration min 7.77, max 8.75, mean 8.46\n",
"chouchou.lab: segment duration min 9.06, max 14.09, mean 10.45\n",
"daikokusama.lab: segment duration min 21.41, max 21.61, mean 21.54\n",
"donguri_korokoro.lab: segment duration min 21.61, max 23.82, mean 22.72\n",
"furusato.lab: segment duration min 6.46, max 14.34, mean 10.32\n",
"genkotsuyamano_tanukisan.lab: segment duration min 6.67, max 9.39, mean 8.03\n",
"haruga_kita.lab: segment duration min 8.47, max 13.25, mean 9.48\n",
"haruno_ogawa.lab: segment duration min 8.89, max 13.79, mean 9.67\n",
"haruyo_koi.lab: segment duration min 6.31, max 9.42, mean 8.18\n",
"hato.lab: segment duration min 6.24, max 9.26, mean 8.40\n",
"hato_low.lab: segment duration min 4.42, max 9.03, mean 6.55\n",
"hiraita_hiraita.lab: segment duration min 8.99, max 17.62, mean 11.49\n",
"hotaruno_hikari.lab: segment duration min 8.84, max 15.36, mean 9.82\n",
"issunboushi.lab: segment duration min 9.31, max 11.88, mean 10.54\n",
"kagome_kagome.lab: segment duration min 21.20, max 21.20, mean 21.20\n",
"kagome_kagome_low.lab: segment duration min 5.92, max 8.58, mean 7.66\n",
"kamomeno_suiheisan.lab: segment duration min 6.54, max 14.29, mean 8.94\n",
"katatsumuri.lab: segment duration min 6.64, max 9.45, mean 8.10\n",
"kintaro.lab: segment duration min 16.70, max 16.84, mean 16.77\n",
"koganemushi.lab: segment duration min 8.41, max 18.19, mean 13.51\n",
"koinobori.lab: segment duration min 6.46, max 9.83, mean 7.51\n",
"momiji.lab: segment duration min 37.64, max 42.24, mean 39.94\n",
"momotarou.lab: segment duration min 6.96, max 9.37, mean 8.46\n",
"morobito_kozorite.lab: segment duration min 8.53, max 14.49, mean 12.25\n",
"mushino_koe.lab: segment duration min 6.60, max 18.75, mean 8.91\n",
"my_grandfathers_clock_1_1.lab: segment duration min 10.02, max 23.39, mean 14.00\n",
"my_grandfathers_clock_1_2.lab: segment duration min 9.22, max 13.64, mean 11.30\n",
"my_grandfathers_clock_1_3.lab: segment duration min 9.26, max 13.55, mean 11.22\n",
"my_grandfathers_clock_2_1.lab: segment duration min 9.05, max 13.40, mean 11.13\n",
"my_grandfathers_clock_2_2.lab: segment duration min 9.02, max 13.35, mean 11.12\n",
"my_grandfathers_clock_2_3.lab: segment duration min 5.11, max 13.53, mean 9.54\n",
"my_grandfathers_clock_3_1.lab: segment duration min 9.19, max 13.53, mean 11.30\n",
"my_grandfathers_clock_3_2.lab: segment duration min 9.37, max 13.46, mean 11.26\n",
"my_grandfathers_clock_3_3.lab: segment duration min 9.38, max 13.60, mean 11.25\n",
"nanatsunoko.lab: segment duration min 8.78, max 13.59, mean 9.71\n",
"oborodukiyo.lab: segment duration min 6.67, max 11.46, mean 7.49\n",
"sakura_sakura.lab: segment duration min 6.35, max 9.15, mean 7.42\n",
"seikurabe.lab: segment duration min 6.29, max 10.55, mean 7.11\n",
"shabondama.lab: segment duration min 52.56, max 52.56, mean 52.56\n",
"shoujoujino_tanukibayashi.lab: segment duration min 6.25, max 18.41, mean 12.24\n",
"tetsudou_shouka.lab: segment duration min 6.31, max 9.18, mean 7.95\n",
"tombi.lab: segment duration min 3.99, max 13.41, mean 7.57\n",
"tooryanse.lab: segment duration min 7.02, max 13.92, mean 9.69\n",
"urashima_taro.lab: segment duration min 6.69, max 9.61, mean 8.01\n",
"usagi.lab: segment duration min 16.59, max 16.59, mean 16.59\n",
"usagito_kame.lab: segment duration min 6.42, max 9.11, mean 7.95\n",
"warewa_uminoko.lab: segment duration min 7.17, max 12.01, mean 8.36\n",
"yuki.lab: segment duration min 21.38, max 21.58, mean 21.48\n",
"yurikagono_uta.lab: segment duration min 8.60, max 13.27, mean 9.64\n",
"zuizuizukkorobashi.lab: segment duration min 6.29, max 8.72, mean 7.17\n",
"zuizuizukkorobashi_low.lab: segment duration min 6.39, max 9.09, mean 7.30\n",
"akai_kutsu.lab: segment lengths: 9.11, 13.41, 8.68, 8.90, 8.78, 9.28, \n",
"akatombo.lab: segment lengths: 10.04, 6.84, 10.55, 6.96, 10.40, 7.06, \n",
"amefuri.lab: segment lengths: 16.53, 16.71, 16.94, \n",
"antagata_dokosa.lab: segment lengths: 15.54, 12.79, 6.59, \n",
"aogeba_tootoshi.lab: segment lengths: 10.43, 12.59, 8.70, 8.70, 8.41, 8.37, 8.50, 8.60, 8.22, 8.48, 8.21, 8.88, \n",
"arupusu_itimanjaku.lab: segment lengths: 12.41, 11.04, 12.01, 9.03, \n",
"chatsumi.lab: segment lengths: 8.66, 8.75, 8.53, 7.77, 8.62, 8.72, 8.73, 7.89, \n",
"chouchou.lab: segment lengths: 9.06, 14.09, 9.07, 9.59, 9.20, 13.88, 9.12, 9.61, \n",
"daikokusama.lab: segment lengths: 21.41, 21.61, 21.61, \n",
"donguri_korokoro.lab: segment lengths: 21.61, 23.82, \n",
"furusato.lab: segment lengths: 9.95, 6.46, 14.00, 10.59, 6.48, 14.04, 10.50, 6.48, 14.34, \n",
"genkotsuyamano_tanukisan.lab: segment lengths: 6.67, 9.39, \n",
"haruga_kita.lab: segment lengths: 13.25, 8.66, 8.47, 8.64, 8.99, 8.83, \n",
"haruno_ogawa.lab: segment lengths: 13.79, 8.89, 9.15, 9.11, 9.12, 8.98, 9.08, 9.24, \n",
"haruyo_koi.lab: segment lengths: 6.31, 8.98, 7.01, 9.15, 9.42, \n",
"hato.lab: segment lengths: 9.03, 9.26, 9.08, 6.24, \n",
"hato_low.lab: segment lengths: 6.59, 6.68, 4.42, 9.03, 6.01, \n",
"hiraita_hiraita.lab: segment lengths: 8.99, 9.09, 12.63, 9.12, 17.62, \n",
"hotaruno_hikari.lab: segment lengths: 15.36, 8.93, 8.84, 9.21, 8.96, 8.89, 8.93, 9.46, \n",
"issunboushi.lab: segment lengths: 11.54, 9.33, 11.83, 9.31, 11.88, 9.34, \n",
"kagome_kagome.lab: segment lengths: 21.20, \n",
"kagome_kagome_low.lab: segment lengths: 8.46, 8.58, 5.92, \n",
"kamomeno_suiheisan.lab: segment lengths: 6.54, 14.29, 6.80, 9.22, 7.12, 9.06, 9.58, \n",
"katatsumuri.lab: segment lengths: 6.64, 9.41, 6.89, 9.45, \n",
"kintaro.lab: segment lengths: 16.70, 16.84, \n",
"koganemushi.lab: segment lengths: 13.94, 8.41, 18.19, \n",
"koinobori.lab: segment lengths: 9.83, 6.46, 6.75, 7.02, \n",
"momiji.lab: segment lengths: 42.24, 37.64, \n",
"momotarou.lab: segment lengths: 9.01, 9.21, 6.96, 9.14, 7.08, 9.37, \n",
"morobito_kozorite.lab: segment lengths: 13.08, 14.49, 8.53, 14.41, 8.55, 14.43, \n",
"mushino_koe.lab: segment lengths: 6.60, 6.91, 6.69, 7.13, 18.75, 7.34, \n",
"my_grandfathers_clock_1_1.lab: segment lengths: 11.36, 11.43, 13.79, 23.39, 10.02, \n",
"my_grandfathers_clock_1_2.lab: segment lengths: 11.28, 11.19, 11.25, 11.19, 13.64, 9.22, \n",
"my_grandfathers_clock_1_3.lab: segment lengths: 11.11, 11.05, 11.23, 11.13, 13.55, 9.26, \n",
"my_grandfathers_clock_2_1.lab: segment lengths: 11.12, 10.95, 11.35, 10.92, 13.40, 9.05, \n",
"my_grandfathers_clock_2_2.lab: segment lengths: 10.92, 11.04, 11.05, 11.31, 13.35, 9.02, \n",
"my_grandfathers_clock_2_3.lab: segment lengths: 10.99, 11.00, 5.63, 5.11, 11.21, 13.53, 9.29, \n",
"my_grandfathers_clock_3_1.lab: segment lengths: 11.18, 11.21, 11.33, 11.33, 13.53, 9.19, \n",
"my_grandfathers_clock_3_2.lab: segment lengths: 11.10, 11.30, 11.19, 11.12, 13.46, 9.37, \n",
"my_grandfathers_clock_3_3.lab: segment lengths: 11.14, 11.01, 11.32, 11.05, 13.60, 9.38, \n",
"nanatsunoko.lab: segment lengths: 13.59, 8.87, 9.10, 8.78, 9.03, 8.88, \n",
"oborodukiyo.lab: segment lengths: 11.46, 6.92, 6.67, 7.11, 6.72, 6.71, 6.82, 7.49, \n",
"sakura_sakura.lab: segment lengths: 6.62, 6.69, 9.04, 6.59, 6.35, 9.15, 9.07, 6.78, 6.44, \n",
"seikurabe.lab: segment lengths: 9.97, 6.39, 6.35, 6.32, 6.63, 6.67, 10.55, 6.36, 6.39, 6.29, 6.43, 6.94, \n",
"shabondama.lab: segment lengths: 52.56, \n",
"shoujoujino_tanukibayashi.lab: segment lengths: 18.41, 12.49, 11.83, 6.25, \n",
"tetsudou_shouka.lab: segment lengths: 6.60, 9.06, 7.32, 9.06, 9.18, 7.09, 9.00, 6.31, \n",
"tombi.lab: segment lengths: 13.41, 8.64, 6.84, 6.35, 3.99, 8.66, 8.81, 6.83, 6.39, 5.75, \n",
"tooryanse.lab: segment lengths: 8.95, 13.92, 9.06, 9.49, 7.02, \n",
"urashima_taro.lab: segment lengths: 6.69, 9.04, 7.15, 9.01, 9.61, 6.85, 9.04, 6.70, \n",
"usagi.lab: segment lengths: 16.59, \n",
"usagito_kame.lab: segment lengths: 6.52, 9.11, 7.15, 9.11, 9.11, 7.15, 9.04, 6.42, \n",
"warewa_uminoko.lab: segment lengths: 11.06, 7.32, 7.31, 7.22, 11.71, 7.34, 7.17, 7.32, 12.01, 7.22, 7.22, 7.42, \n",
"yuki.lab: segment lengths: 21.38, 21.58, \n",
"yurikagono_uta.lab: segment lengths: 8.97, 13.27, 9.08, 8.60, 9.12, 8.79, \n",
"zuizuizukkorobashi.lab: segment lengths: 6.38, 8.06, 6.40, 8.72, 6.29, \n",
"zuizuizukkorobashi_low.lab: segment lengths: 6.39, 7.97, 6.54, 9.09, 6.49, \n",
"Segmentation stats: min 3.99, max 52.56, mean 10.11\n",
"Total number of segments: 321\n",
"Prepare data for time-lag models\n",
" 0% 0/57 [00:00<?, ?it/s]akai_kutsu: Global offset (in sec): -0.045\n",
"akai_kutsu_seg0.lab offset (in sec): -0.01\n",
"akai_kutsu.lab: 1/10 time-lags are excluded.\n",
"akai_kutsu_seg1.lab offset (in sec): -0.049999999999999996\n",
"akai_kutsu.lab: 3/22 time-lags are excluded.\n",
"akai_kutsu_seg2.lab offset (in sec): -0.034999999999999996\n",
"akai_kutsu.lab: 1/18 time-lags are excluded.\n",
"akai_kutsu_seg3.lab offset (in sec): -0.06\n",
"akai_kutsu.lab: 4/16 time-lags are excluded.\n",
"akai_kutsu_seg4.lab offset (in sec): -0.034999999999999996\n",
"akai_kutsu.lab: 1/17 time-lags are excluded.\n",
"akai_kutsu_seg5.lab offset (in sec): -0.034999999999999996\n",
"akai_kutsu.lab: 1/16 time-lags are excluded.\n",
"akatombo: Global offset (in sec): -0.04\n",
"akatombo_seg0.lab offset (in sec): -0.02\n",
"akatombo_seg1.lab offset (in sec): -0.04\n",
"akatombo_seg2.lab offset (in sec): -0.03\n",
"akatombo_seg3.lab offset (in sec): -0.04\n",
"akatombo.lab: 1/17 time-lags are excluded.\n",
"akatombo_seg4.lab offset (in sec): -0.06\n",
"akatombo_seg5.lab offset (in sec): -0.03\n",
"akatombo.lab: 1/17 time-lags are excluded.\n",
"amefuri: Global offset (in sec): -0.105\n",
"amefuri_seg0.lab offset (in sec): -0.11\n",
"amefuri.lab: 3/40 time-lags are excluded.\n",
"amefuri_seg1.lab offset (in sec): -0.095\n",
"amefuri.lab: 3/40 time-lags are excluded.\n",
"amefuri_seg2.lab offset (in sec): -0.105\n",
"amefuri.lab: 2/40 time-lags are excluded.\n",
"antagata_dokosa: Global offset (in sec): -0.11\n",
"antagata_dokosa_seg0.lab offset (in sec): -0.105\n",
"antagata_dokosa.lab: 2/37 time-lags are excluded.\n",
"antagata_dokosa_seg1.lab offset (in sec): -0.11499999999999999\n",
"antagata_dokosa.lab: 2/40 time-lags are excluded.\n",
"antagata_dokosa_seg2.lab offset (in sec): -0.08499999999999999\n",
"antagata_dokosa.lab: 3/12 time-lags are excluded.\n",
"aogeba_tootoshi: Global offset (in sec): -0.06999999999999999\n",
"aogeba_tootoshi_seg0.lab offset (in sec): -0.075\n",
"aogeba_tootoshi.lab: 2/8 time-lags are excluded.\n",
"aogeba_tootoshi_seg1.lab offset (in sec): -0.06999999999999999\n",
"aogeba_tootoshi.lab: 1/22 time-lags are excluded.\n",
"aogeba_tootoshi_seg2.lab offset (in sec): -0.095\n",
"aogeba_tootoshi.lab: 1/15 time-lags are excluded.\n",
"aogeba_tootoshi_seg3.lab offset (in sec): -0.034999999999999996\n",
"aogeba_tootoshi.lab: 2/15 time-lags are excluded.\n",
"aogeba_tootoshi_seg4.lab offset (in sec): -0.095\n",
"aogeba_tootoshi.lab: 1/15 time-lags are excluded.\n",
"aogeba_tootoshi_seg5.lab offset (in sec): -0.06999999999999999\n",
"aogeba_tootoshi_seg6.lab offset (in sec): -0.06999999999999999\n",
"aogeba_tootoshi_seg7.lab offset (in sec): -0.045\n",
"aogeba_tootoshi_seg8.lab offset (in sec): -0.09\n",
"aogeba_tootoshi.lab: 1/15 time-lags are excluded.\n",
"aogeba_tootoshi_seg9.lab offset (in sec): -0.08499999999999999\n",
"aogeba_tootoshi.lab: 3/15 time-lags are excluded.\n",
"aogeba_tootoshi_seg10.lab offset (in sec): -0.04\n",
"aogeba_tootoshi.lab: 2/15 time-lags are excluded.\n",
"aogeba_tootoshi_seg11.lab offset (in sec): -0.02\n",
"arupusu_itimanjaku: Global offset (in sec): -0.065\n",
"arupusu_itimanjaku_seg0.lab offset (in sec): -0.065\n",
"arupusu_itimanjaku.lab: 1/31 time-lags are excluded.\n",
"arupusu_itimanjaku_seg1.lab offset (in sec): -0.055\n",
"arupusu_itimanjaku_seg2.lab offset (in sec): -0.055\n",
"arupusu_itimanjaku.lab: 1/28 time-lags are excluded.\n",
"arupusu_itimanjaku_seg3.lab offset (in sec): -0.075\n",
"chatsumi: Global offset (in sec): 0.015\n",
"chatsumi_seg0.lab offset (in sec): 0.024999999999999998\n",
"chatsumi_seg1.lab offset (in sec): 0.005\n",
"chatsumi.lab: 1/14 time-lags are excluded.\n",
"chatsumi_seg2.lab offset (in sec): 0.024999999999999998\n",
"chatsumi_seg3.lab offset (in sec): -0.06\n",
"chatsumi.lab: 1/12 time-lags are excluded.\n",
"chatsumi_seg4.lab offset (in sec): 0.034999999999999996\n",
"chatsumi.lab: 1/13 time-lags are excluded.\n",
"chatsumi_seg5.lab offset (in sec): 0.02\n",
"chatsumi_seg6.lab offset (in sec): 0.01\n",
"chatsumi.lab: 1/14 time-lags are excluded.\n",
"chatsumi_seg7.lab offset (in sec): 0.049999999999999996\n",
"chatsumi.lab: 2/12 time-lags are excluded.\n",
"chouchou: Global offset (in sec): -0.105\n",
"chouchou_seg0.lab offset (in sec): -0.145\n",
"chouchou.lab: 1/6 time-lags are excluded.\n",
"chouchou_seg1.lab offset (in sec): -0.09\n",
"chouchou.lab: 2/24 time-lags are excluded.\n",
"chouchou_seg2.lab offset (in sec): -0.11\n",
"chouchou.lab: 4/15 time-lags are excluded.\n",
"chouchou_seg3.lab offset (in sec): -0.09\n",
"chouchou.lab: 2/15 time-lags are excluded.\n",
"chouchou_seg4.lab offset (in sec): -0.055\n",
"chouchou_seg5.lab offset (in sec): -0.11\n",
"chouchou.lab: 4/24 time-lags are excluded.\n",
"chouchou_seg6.lab offset (in sec): -0.075\n",
"chouchou_seg7.lab offset (in sec): -0.09\n",
"chouchou.lab: 3/15 time-lags are excluded.\n",
"daikokusama: Global offset (in sec): -0.09999999999999999\n",
"daikokusama_seg0.lab offset (in sec): -0.095\n",
"daikokusama.lab: 3/49 time-lags are excluded.\n",
"daikokusama_seg1.lab offset (in sec): -0.095\n",
"daikokusama.lab: 2/49 time-lags are excluded.\n",
"daikokusama_seg2.lab offset (in sec): -0.11\n",
"daikokusama.lab: 2/49 time-lags are excluded.\n",
"donguri_korokoro: Global offset (in sec): -0.075\n",
"donguri_korokoro_seg0.lab offset (in sec): -0.08\n",
"donguri_korokoro.lab: 1/49 time-lags are excluded.\n",
"donguri_korokoro_seg1.lab offset (in sec): -0.075\n",
"donguri_korokoro.lab: 3/49 time-lags are excluded.\n",
"furusato: Global offset (in sec): -0.09\n",
"furusato_seg0.lab offset (in sec): -0.08499999999999999\n",
"furusato.lab: 1/11 time-lags are excluded.\n",
"furusato_seg1.lab offset (in sec): -0.11499999999999999\n",
"furusato_seg2.lab offset (in sec): -0.08\n",
"furusato.lab: 3/28 time-lags are excluded.\n",
"furusato_seg3.lab offset (in sec): -0.075\n",
"furusato_seg4.lab offset (in sec): -0.15\n",
"furusato.lab: 2/10 time-lags are excluded.\n",
"furusato_seg5.lab offset (in sec): -0.06999999999999999\n",
"furusato.lab: 4/27 time-lags are excluded.\n",
"furusato_seg6.lab offset (in sec): -0.065\n",
"furusato.lab: 2/11 time-lags are excluded.\n",
"furusato_seg7.lab offset (in sec): -0.095\n",
"furusato_seg8.lab offset (in sec): -0.06999999999999999\n",
"furusato.lab: 6/27 time-lags are excluded.\n",
"genkotsuyamano_tanukisan: Global offset (in sec): -0.12\n",
"genkotsuyamano_tanukisan_seg0.lab offset (in sec): -0.105\n",
"genkotsuyamano_tanukisan.lab: 1/12 time-lags are excluded.\n",
"genkotsuyamano_tanukisan_seg1.lab offset (in sec): -0.12\n",
"genkotsuyamano_tanukisan.lab: 3/26 time-lags are excluded.\n",
"haruga_kita: Global offset (in sec): -0.09\n",
"haruga_kita_seg0.lab offset (in sec): -0.06999999999999999\n",
"haruga_kita_seg1.lab offset (in sec): -0.09\n",
"haruga_kita.lab: 1/16 time-lags are excluded.\n",
"haruga_kita_seg2.lab offset (in sec): -0.095\n",
"haruga_kita.lab: 1/16 time-lags are excluded.\n",
"haruga_kita_seg3.lab offset (in sec): -0.075\n",
"haruga_kita.lab: 1/16 time-lags are excluded.\n",
"haruga_kita_seg4.lab offset (in sec): -0.08\n",
"haruga_kita.lab: 1/16 time-lags are excluded.\n",
"haruga_kita_seg5.lab offset (in sec): -0.09999999999999999\n",
"haruga_kita.lab: 1/16 time-lags are excluded.\n",
"haruno_ogawa: Global offset (in sec): -0.095\n",
"haruno_ogawa_seg0.lab offset (in sec): -0.08499999999999999\n",
"haruno_ogawa.lab: 2/16 time-lags are excluded.\n",
"haruno_ogawa_seg1.lab offset (in sec): -0.08\n",
"haruno_ogawa.lab: 2/16 time-lags are excluded.\n",
"haruno_ogawa_seg2.lab offset (in sec): -0.105\n",
"haruno_ogawa.lab: 1/16 time-lags are excluded.\n",
"haruno_ogawa_seg3.lab offset (in sec): -0.095\n",
"haruno_ogawa.lab: 2/16 time-lags are excluded.\n",
"haruno_ogawa_seg4.lab offset (in sec): -0.095\n",
"haruno_ogawa.lab: 2/16 time-lags are excluded.\n",
"haruno_ogawa_seg5.lab offset (in sec): -0.049999999999999996\n",
"haruno_ogawa_seg6.lab offset (in sec): -0.09999999999999999\n",
"haruno_ogawa.lab: 1/16 time-lags are excluded.\n",
"haruno_ogawa_seg7.lab offset (in sec): -0.12\n",
" 25% 14/57 [00:00<00:00, 128.28it/s]haruyo_koi: Global offset (in sec): -0.09\n",
"haruyo_koi_seg0.lab offset (in sec): -0.125\n",
"haruyo_koi.lab: 1/11 time-lags are excluded.\n",
"haruyo_koi_seg1.lab offset (in sec): -0.08499999999999999\n",
"haruyo_koi_seg2.lab offset (in sec): -0.095\n",
"haruyo_koi.lab: 1/12 time-lags are excluded.\n",
"haruyo_koi_seg3.lab offset (in sec): -0.08\n",
"haruyo_koi.lab: 1/24 time-lags are excluded.\n",
"haruyo_koi_seg4.lab offset (in sec): -0.09\n",
"hato: Global offset (in sec): -0.11\n",
"hato_seg0.lab offset (in sec): -0.145\n",
"hato.lab: 1/8 time-lags are excluded.\n",
"hato_seg1.lab offset (in sec): -0.12\n",
"hato.lab: 2/26 time-lags are excluded.\n",
"hato_seg2.lab offset (in sec): -0.09\n",
"hato.lab: 1/21 time-lags are excluded.\n",
"hato_seg3.lab offset (in sec): -0.105\n",
"hato_low: Global offset (in sec): -0.09999999999999999\n",
"hato_low_seg0.lab offset (in sec): -0.105\n",
"hato_low_seg1.lab offset (in sec): -0.095\n",
"hato_low_seg2.lab offset (in sec): -0.11\n",
"hato_low.lab: 3/13 time-lags are excluded.\n",
"hato_low_seg3.lab offset (in sec): -0.105\n",
"hato_low.lab: 1/21 time-lags are excluded.\n",
"hato_low_seg4.lab offset (in sec): -0.08\n",
"hiraita_hiraita: Global offset (in sec): -0.09\n",
"hiraita_hiraita_seg0.lab offset (in sec): -0.11\n",
"hiraita_hiraita_seg1.lab offset (in sec): -0.105\n",
"hiraita_hiraita.lab: 1/22 time-lags are excluded.\n",
"hiraita_hiraita_seg2.lab offset (in sec): -0.08499999999999999\n",
"hiraita_hiraita.lab: 2/22 time-lags are excluded.\n",
"hiraita_hiraita_seg3.lab offset (in sec): -0.08\n",
"hiraita_hiraita_seg4.lab offset (in sec): -0.06\n",
"hiraita_hiraita.lab: 1/34 time-lags are excluded.\n",
"hotaruno_hikari: Global offset (in sec): -0.09999999999999999\n",
"hotaruno_hikari_seg0.lab offset (in sec): -0.105\n",
"hotaruno_hikari.lab: 2/15 time-lags are excluded.\n",
"hotaruno_hikari_seg1.lab offset (in sec): -0.12\n",
"hotaruno_hikari_seg2.lab offset (in sec): -0.095\n",
"hotaruno_hikari.lab: 1/15 time-lags are excluded.\n",
"hotaruno_hikari_seg3.lab offset (in sec): -0.075\n",
"hotaruno_hikari_seg4.lab offset (in sec): -0.09999999999999999\n",
"hotaruno_hikari.lab: 1/15 time-lags are excluded.\n",
"hotaruno_hikari_seg5.lab offset (in sec): -0.08\n",
"hotaruno_hikari_seg6.lab offset (in sec): -0.11\n",
"hotaruno_hikari.lab: 1/15 time-lags are excluded.\n",
"hotaruno_hikari_seg7.lab offset (in sec): -0.06\n",
"hotaruno_hikari.lab: 1/15 time-lags are excluded.\n",
"issunboushi: Global offset (in sec): -0.09999999999999999\n",
"issunboushi_seg0.lab offset (in sec): -0.105\n",
"issunboushi.lab: 1/29 time-lags are excluded.\n",
"issunboushi_seg1.lab offset (in sec): -0.08499999999999999\n",
"issunboushi.lab: 1/25 time-lags are excluded.\n",
"issunboushi_seg2.lab offset (in sec): -0.09999999999999999\n",
"issunboushi.lab: 2/29 time-lags are excluded.\n",
"issunboushi_seg3.lab offset (in sec): -0.105\n",
"issunboushi.lab: 4/25 time-lags are excluded.\n",
"issunboushi_seg4.lab offset (in sec): -0.095\n",
"issunboushi.lab: 1/29 time-lags are excluded.\n",
"issunboushi_seg5.lab offset (in sec): -0.08499999999999999\n",
"issunboushi.lab: 2/24 time-lags are excluded.\n",
"kagome_kagome: Global offset (in sec): -0.065\n",
"kagome_kagome_seg0.lab offset (in sec): -0.065\n",
"kagome_kagome.lab: 2/51 time-lags are excluded.\n",
"kagome_kagome_low: Global offset (in sec): -0.075\n",
"kagome_kagome_low_seg0.lab offset (in sec): -0.09\n",
"kagome_kagome_low.lab: 1/17 time-lags are excluded.\n",
"kagome_kagome_low_seg1.lab offset (in sec): -0.065\n",
"kagome_kagome_low.lab: 1/27 time-lags are excluded.\n",
"kagome_kagome_low_seg2.lab offset (in sec): -0.06999999999999999\n",
"kamomeno_suiheisan: Global offset (in sec): -0.095\n",
"kamomeno_suiheisan_seg0.lab offset (in sec): -0.125\n",
"kamomeno_suiheisan_seg1.lab offset (in sec): -0.075\n",
"kamomeno_suiheisan.lab: 2/43 time-lags are excluded.\n",
"kamomeno_suiheisan_seg2.lab offset (in sec): -0.16999999999999998\n",
"kamomeno_suiheisan_seg3.lab offset (in sec): -0.095\n",
"kamomeno_suiheisan.lab: 4/28 time-lags are excluded.\n",
"kamomeno_suiheisan_seg4.lab offset (in sec): -0.065\n",
"kamomeno_suiheisan_seg5.lab offset (in sec): -0.13499999999999998\n",
"kamomeno_suiheisan.lab: 1/21 time-lags are excluded.\n",
"kamomeno_suiheisan_seg6.lab offset (in sec): -0.06999999999999999\n",
"kamomeno_suiheisan.lab: 1/32 time-lags are excluded.\n",
"katatsumuri: Global offset (in sec): -0.065\n",
"katatsumuri_seg0.lab offset (in sec): -0.09\n",
"katatsumuri.lab: 1/13 time-lags are excluded.\n",
"katatsumuri_seg1.lab offset (in sec): -0.049999999999999996\n",
"katatsumuri.lab: 1/27 time-lags are excluded.\n",
"katatsumuri_seg2.lab offset (in sec): -0.055\n",
"katatsumuri_seg3.lab offset (in sec): -0.06\n",
"kintaro: Global offset (in sec): -0.055\n",
"kintaro_seg0.lab offset (in sec): -0.065\n",
"kintaro.lab: 3/45 time-lags are excluded.\n",
"kintaro_seg1.lab offset (in sec): -0.04\n",
"kintaro.lab: 2/45 time-lags are excluded.\n",
"koganemushi: Global offset (in sec): -0.06999999999999999\n",
"koganemushi_seg0.lab offset (in sec): -0.06\n",
"koganemushi_seg1.lab offset (in sec): -0.06999999999999999\n",
"koganemushi.lab: 1/15 time-lags are excluded.\n",
"koganemushi_seg2.lab offset (in sec): -0.06\n",
"koganemushi.lab: 1/41 time-lags are excluded.\n",
"koinobori: Global offset (in sec): -0.055\n",
"koinobori_seg0.lab offset (in sec): -0.024999999999999998\n",
"koinobori.lab: 1/13 time-lags are excluded.\n",
"koinobori_seg1.lab offset (in sec): -0.065\n",
"koinobori.lab: 1/13 time-lags are excluded.\n",
"koinobori_seg2.lab offset (in sec): -0.08\n",
"koinobori.lab: 1/14 time-lags are excluded.\n",
"koinobori_seg3.lab offset (in sec): -0.034999999999999996\n",
"koinobori.lab: 1/13 time-lags are excluded.\n",
"momiji: Global offset (in sec): -0.075\n",
"momiji_seg0.lab offset (in sec): -0.065\n",
"momiji.lab: 9/60 time-lags are excluded.\n",
"momiji_seg1.lab offset (in sec): -0.08\n",
"momiji.lab: 2/60 time-lags are excluded.\n",
"momotarou: Global offset (in sec): -0.09\n",
"momotarou_seg0.lab offset (in sec): -0.055\n",
"momotarou.lab: 4/14 time-lags are excluded.\n",
"momotarou_seg1.lab offset (in sec): -0.09\n",
"momotarou_seg2.lab offset (in sec): -0.12\n",
"momotarou.lab: 1/10 time-lags are excluded.\n",
"momotarou_seg3.lab offset (in sec): -0.095\n",
"momotarou.lab: 1/25 time-lags are excluded.\n",
"momotarou_seg4.lab offset (in sec): -0.11\n",
"momotarou_seg5.lab offset (in sec): -0.08499999999999999\n",
"momotarou.lab: 2/24 time-lags are excluded.\n",
"morobito_kozorite: Global offset (in sec): -0.065\n",
"morobito_kozorite_seg0.lab offset (in sec): -0.09999999999999999\n",
"morobito_kozorite.lab: 3/15 time-lags are excluded.\n",
"morobito_kozorite_seg1.lab offset (in sec): -0.065\n",
"morobito_kozorite.lab: 1/45 time-lags are excluded.\n",
"morobito_kozorite_seg2.lab offset (in sec): -0.075\n",
"morobito_kozorite.lab: 1/15 time-lags are excluded.\n",
"morobito_kozorite_seg3.lab offset (in sec): -0.049999999999999996\n",
"morobito_kozorite.lab: 4/45 time-lags are excluded.\n",
"morobito_kozorite_seg4.lab offset (in sec): -0.08\n",
"morobito_kozorite.lab: 1/15 time-lags are excluded.\n",
"morobito_kozorite_seg5.lab offset (in sec): -0.04\n",
"morobito_kozorite.lab: 3/45 time-lags are excluded.\n",
" 53% 30/57 [00:00<00:00, 136.11it/s]mushino_koe: Global offset (in sec): -0.045\n",
"mushino_koe_seg0.lab offset (in sec): -0.095\n",
"mushino_koe_seg1.lab offset (in sec): -0.06\n",
"mushino_koe.lab: 1/28 time-lags are excluded.\n",
"mushino_koe_seg2.lab offset (in sec): -0.04\n",
"mushino_koe_seg3.lab offset (in sec): -0.049999999999999996\n",
"mushino_koe_seg4.lab offset (in sec): -0.024999999999999998\n",
"mushino_koe.lab: 4/68 time-lags are excluded.\n",
"mushino_koe_seg5.lab offset (in sec): -0.045\n",
"my_grandfathers_clock_1_1: Global offset (in sec): -0.09\n",
"my_grandfathers_clock_1_1_seg0.lab offset (in sec): -0.095\n",
"my_grandfathers_clock_1_1.lab: 3/21 time-lags are excluded.\n",
"my_grandfathers_clock_1_1_seg1.lab offset (in sec): -0.095\n",
"my_grandfathers_clock_1_1.lab: 2/22 time-lags are excluded.\n",
"my_grandfathers_clock_1_1_seg2.lab offset (in sec): -0.049999999999999996\n",
"my_grandfathers_clock_1_1.lab: 2/27 time-lags are excluded.\n",
"my_grandfathers_clock_1_1_seg3.lab offset (in sec): -0.08\n",
"my_grandfathers_clock_1_1.lab: 5/41 time-lags are excluded.\n",
"my_grandfathers_clock_1_1_seg4.lab offset (in sec): -0.08\n",
"my_grandfathers_clock_1_1.lab: 1/13 time-lags are excluded.\n",
"my_grandfathers_clock_1_2: Global offset (in sec): -0.065\n",
"my_grandfathers_clock_1_2_seg0.lab offset (in sec): -0.06\n",
"my_grandfathers_clock_1_2_seg1.lab offset (in sec): -0.06\n",
"my_grandfathers_clock_1_2_seg2.lab offset (in sec): -0.04\n",
"my_grandfathers_clock_1_2.lab: 2/23 time-lags are excluded.\n",
"my_grandfathers_clock_1_2_seg3.lab offset (in sec): -0.049999999999999996\n",
"my_grandfathers_clock_1_2.lab: 3/17 time-lags are excluded.\n",
"my_grandfathers_clock_1_2_seg4.lab offset (in sec): -0.065\n",
"my_grandfathers_clock_1_2_seg5.lab offset (in sec): -0.065\n",
"my_grandfathers_clock_1_3: Global offset (in sec): -0.08499999999999999\n",
"my_grandfathers_clock_1_3_seg0.lab offset (in sec): -0.06999999999999999\n",
"my_grandfathers_clock_1_3.lab: 1/21 time-lags are excluded.\n",
"my_grandfathers_clock_1_3_seg1.lab offset (in sec): -0.065\n",
"my_grandfathers_clock_1_3_seg2.lab offset (in sec): -0.075\n",
"my_grandfathers_clock_1_3_seg3.lab offset (in sec): -0.09\n",
"my_grandfathers_clock_1_3.lab: 1/17 time-lags are excluded.\n",
"my_grandfathers_clock_1_3_seg4.lab offset (in sec): -0.075\n",
"my_grandfathers_clock_1_3.lab: 2/27 time-lags are excluded.\n",
"my_grandfathers_clock_1_3_seg5.lab offset (in sec): -0.095\n",
"my_grandfathers_clock_2_1: Global offset (in sec): -0.049999999999999996\n",
"my_grandfathers_clock_2_1_seg0.lab offset (in sec): -0.049999999999999996\n",
"my_grandfathers_clock_2_1_seg1.lab offset (in sec): -0.045\n",
"my_grandfathers_clock_2_1_seg2.lab offset (in sec): -0.02\n",
"my_grandfathers_clock_2_1.lab: 1/23 time-lags are excluded.\n",
"my_grandfathers_clock_2_1_seg3.lab offset (in sec): -0.055\n",
"my_grandfathers_clock_2_1.lab: 3/17 time-lags are excluded.\n",
"my_grandfathers_clock_2_1_seg4.lab offset (in sec): -0.049999999999999996\n",
"my_grandfathers_clock_2_1.lab: 2/28 time-lags are excluded.\n",
"my_grandfathers_clock_2_1_seg5.lab offset (in sec): -0.09\n",
"my_grandfathers_clock_2_1.lab: 1/13 time-lags are excluded.\n",
"my_grandfathers_clock_2_2: Global offset (in sec): -0.065\n",
"my_grandfathers_clock_2_2_seg0.lab offset (in sec): -0.04\n",
"my_grandfathers_clock_2_2_seg1.lab offset (in sec): -0.03\n",
"my_grandfathers_clock_2_2.lab: 1/22 time-lags are excluded.\n",
"my_grandfathers_clock_2_2_seg2.lab offset (in sec): -0.049999999999999996\n",
"my_grandfathers_clock_2_2.lab: 1/23 time-lags are excluded.\n",
"my_grandfathers_clock_2_2_seg3.lab offset (in sec): -0.08\n",
"my_grandfathers_clock_2_2.lab: 1/17 time-lags are excluded.\n",
"my_grandfathers_clock_2_2_seg4.lab offset (in sec): -0.06999999999999999\n",
"my_grandfathers_clock_2_2.lab: 2/28 time-lags are excluded.\n",
"my_grandfathers_clock_2_2_seg5.lab offset (in sec): -0.13499999999999998\n",
"my_grandfathers_clock_2_3: Global offset (in sec): -0.08\n",
"my_grandfathers_clock_2_3_seg0.lab offset (in sec): -0.06999999999999999\n",
"my_grandfathers_clock_2_3.lab: 2/21 time-lags are excluded.\n",
"my_grandfathers_clock_2_3_seg1.lab offset (in sec): -0.055\n",
"my_grandfathers_clock_2_3_seg2.lab offset (in sec): -0.095\n",
"my_grandfathers_clock_2_3.lab: 1/13 time-lags are excluded.\n",
"my_grandfathers_clock_2_3_seg3.lab offset (in sec): -0.06999999999999999\n",
"my_grandfathers_clock_2_3_seg4.lab offset (in sec): -0.075\n",
"my_grandfathers_clock_2_3.lab: 1/17 time-lags are excluded.\n",
"my_grandfathers_clock_2_3_seg5.lab offset (in sec): -0.09999999999999999\n",
"my_grandfathers_clock_2_3.lab: 1/28 time-lags are excluded.\n",
"my_grandfathers_clock_2_3_seg6.lab offset (in sec): -0.06\n",
"my_grandfathers_clock_2_3.lab: 1/13 time-lags are excluded.\n",
"my_grandfathers_clock_3_1: Global offset (in sec): -0.03\n",
"my_grandfathers_clock_3_1_seg0.lab offset (in sec): -0.06999999999999999\n",
"my_grandfathers_clock_3_1.lab: 3/21 time-lags are excluded.\n",
"my_grandfathers_clock_3_1_seg1.lab offset (in sec): -0.01\n",
"my_grandfathers_clock_3_1.lab: 2/22 time-lags are excluded.\n",
"my_grandfathers_clock_3_1_seg2.lab offset (in sec): -0.01\n",
"my_grandfathers_clock_3_1_seg3.lab offset (in sec): -0.024999999999999998\n",
"my_grandfathers_clock_3_1.lab: 1/17 time-lags are excluded.\n",
"my_grandfathers_clock_3_1_seg4.lab offset (in sec): -0.015\n",
"my_grandfathers_clock_3_1.lab: 1/27 time-lags are excluded.\n",
"my_grandfathers_clock_3_1_seg5.lab offset (in sec): -0.065\n",
"my_grandfathers_clock_3_1.lab: 1/13 time-lags are excluded.\n",
"my_grandfathers_clock_3_2: Global offset (in sec): -0.075\n",
"my_grandfathers_clock_3_2_seg0.lab offset (in sec): -0.045\n",
"my_grandfathers_clock_3_2.lab: 1/21 time-lags are excluded.\n",
"my_grandfathers_clock_3_2_seg1.lab offset (in sec): -0.04\n",
"my_grandfathers_clock_3_2.lab: 2/22 time-lags are excluded.\n",
"my_grandfathers_clock_3_2_seg2.lab offset (in sec): -0.06999999999999999\n",
"my_grandfathers_clock_3_2.lab: 1/24 time-lags are excluded.\n",
"my_grandfathers_clock_3_2_seg3.lab offset (in sec): -0.08499999999999999\n",
"my_grandfathers_clock_3_2_seg4.lab offset (in sec): -0.08499999999999999\n",
"my_grandfathers_clock_3_2.lab: 3/28 time-lags are excluded.\n",
"my_grandfathers_clock_3_2_seg5.lab offset (in sec): -0.09\n",
"my_grandfathers_clock_3_2.lab: 3/13 time-lags are excluded.\n",
"my_grandfathers_clock_3_3: Global offset (in sec): -0.04\n",
"my_grandfathers_clock_3_3_seg0.lab offset (in sec): -0.04\n",
"my_grandfathers_clock_3_3.lab: 1/21 time-lags are excluded.\n",
"my_grandfathers_clock_3_3_seg1.lab offset (in sec): -0.04\n",
"my_grandfathers_clock_3_3.lab: 2/22 time-lags are excluded.\n",
"my_grandfathers_clock_3_3_seg2.lab offset (in sec): -0.01\n",
"my_grandfathers_clock_3_3.lab: 3/23 time-lags are excluded.\n",
"my_grandfathers_clock_3_3_seg3.lab offset (in sec): -0.01\n",
"my_grandfathers_clock_3_3.lab: 2/17 time-lags are excluded.\n",
"my_grandfathers_clock_3_3_seg4.lab offset (in sec): -0.06\n",
"my_grandfathers_clock_3_3.lab: 2/27 time-lags are excluded.\n",
"my_grandfathers_clock_3_3_seg5.lab offset (in sec): -0.024999999999999998\n",
"nanatsunoko: Global offset (in sec): -0.075\n",
"nanatsunoko_seg0.lab offset (in sec): -0.08499999999999999\n",
"nanatsunoko.lab: 1/18 time-lags are excluded.\n",
"nanatsunoko_seg1.lab offset (in sec): -0.075\n",
"nanatsunoko.lab: 1/17 time-lags are excluded.\n",
"nanatsunoko_seg2.lab offset (in sec): -0.095\n",
"nanatsunoko.lab: 2/15 time-lags are excluded.\n",
"nanatsunoko_seg3.lab offset (in sec): -0.095\n",
"nanatsunoko.lab: 3/13 time-lags are excluded.\n",
"nanatsunoko_seg4.lab offset (in sec): -0.045\n",
"nanatsunoko.lab: 4/18 time-lags are excluded.\n",
"nanatsunoko_seg5.lab offset (in sec): -0.04\n",
"nanatsunoko.lab: 1/16 time-lags are excluded.\n",
"oborodukiyo: Global offset (in sec): -0.065\n",
"oborodukiyo_seg0.lab offset (in sec): -0.08\n",
"oborodukiyo.lab: 3/16 time-lags are excluded.\n",
"oborodukiyo_seg1.lab offset (in sec): -0.075\n",
"oborodukiyo_seg2.lab offset (in sec): -0.034999999999999996\n",
"oborodukiyo.lab: 2/17 time-lags are excluded.\n",
"oborodukiyo_seg3.lab offset (in sec): -0.04\n",
"oborodukiyo.lab: 1/16 time-lags are excluded.\n",
"oborodukiyo_seg4.lab offset (in sec): -0.055\n",
"oborodukiyo_seg5.lab offset (in sec): -0.065\n",
"oborodukiyo_seg6.lab offset (in sec): -0.08499999999999999\n",
"oborodukiyo.lab: 1/17 time-lags are excluded.\n",
"oborodukiyo_seg7.lab offset (in sec): -0.045\n",
"oborodukiyo.lab: 1/16 time-lags are excluded.\n",
" 74% 42/57 [00:00<00:00, 127.76it/s]sakura_sakura: Global offset (in sec): -0.03\n",
"sakura_sakura_seg0.lab offset (in sec): -0.075\n",
"sakura_sakura.lab: 1/3 time-lags are excluded.\n",
"sakura_sakura_seg1.lab offset (in sec): -0.049999999999999996\n",
"sakura_sakura.lab: 2/12 time-lags are excluded.\n",
"sakura_sakura_seg2.lab offset (in sec): -0.03\n",
"sakura_sakura.lab: 1/17 time-lags are excluded.\n",
"sakura_sakura_seg3.lab offset (in sec): -0.04\n",
"sakura_sakura.lab: 1/12 time-lags are excluded.\n",
"sakura_sakura_seg4.lab offset (in sec): -0.01\n",
"sakura_sakura.lab: 2/10 time-lags are excluded.\n",
"sakura_sakura_seg5.lab offset (in sec): -0.034999999999999996\n",
"sakura_sakura.lab: 2/16 time-lags are excluded.\n",
"sakura_sakura_seg6.lab offset (in sec): -0.034999999999999996\n",
"sakura_sakura.lab: 1/17 time-lags are excluded.\n",
"sakura_sakura_seg7.lab offset (in sec): 0.0\n",
"sakura_sakura_seg8.lab offset (in sec): 0.0\n",
"seikurabe: Global offset (in sec): -0.09\n",
"seikurabe_seg0.lab offset (in sec): -0.08499999999999999\n",
"seikurabe_seg1.lab offset (in sec): -0.125\n",
"seikurabe.lab: 2/12 time-lags are excluded.\n",
"seikurabe_seg2.lab offset (in sec): -0.09\n",
"seikurabe.lab: 1/12 time-lags are excluded.\n",
"seikurabe_seg3.lab offset (in sec): -0.09\n",
"seikurabe.lab: 1/12 time-lags are excluded.\n",
"seikurabe_seg4.lab offset (in sec): -0.095\n",
"seikurabe_seg5.lab offset (in sec): -0.09\n",
"seikurabe.lab: 1/14 time-lags are excluded.\n",
"seikurabe_seg6.lab offset (in sec): -0.08\n",
"seikurabe_seg7.lab offset (in sec): -0.09\n",
"seikurabe.lab: 1/12 time-lags are excluded.\n",
"seikurabe_seg8.lab offset (in sec): -0.09\n",
"seikurabe.lab: 1/12 time-lags are excluded.\n",
"seikurabe_seg9.lab offset (in sec): -0.09999999999999999\n",
"seikurabe.lab: 2/12 time-lags are excluded.\n",
"seikurabe_seg10.lab offset (in sec): -0.065\n",
"seikurabe.lab: 1/14 time-lags are excluded.\n",
"seikurabe_seg11.lab offset (in sec): -0.06\n",
"seikurabe.lab: 1/14 time-lags are excluded.\n",
"shabondama: Global offset (in sec): -0.08499999999999999\n",
"shabondama_seg0.lab offset (in sec): -0.08499999999999999\n",
"shabondama.lab: 8/73 time-lags are excluded.\n",
"shoujoujino_tanukibayashi: Global offset (in sec): -0.04\n",
"shoujoujino_tanukibayashi_seg0.lab offset (in sec): -0.04\n",
"shoujoujino_tanukibayashi.lab: 4/55 time-lags are excluded.\n",
"shoujoujino_tanukibayashi_seg1.lab offset (in sec): -0.03\n",
"shoujoujino_tanukibayashi_seg2.lab offset (in sec): -0.049999999999999996\n",
"shoujoujino_tanukibayashi.lab: 4/31 time-lags are excluded.\n",
"shoujoujino_tanukibayashi_seg3.lab offset (in sec): -0.02\n",
"tetsudou_shouka: Global offset (in sec): -0.12\n",
"tetsudou_shouka_seg0.lab offset (in sec): -0.125\n",
"tetsudou_shouka.lab: 4/11 time-lags are excluded.\n",
"tetsudou_shouka_seg1.lab offset (in sec): -0.11\n",
"tetsudou_shouka.lab: 1/25 time-lags are excluded.\n",
"tetsudou_shouka_seg2.lab offset (in sec): -0.11\n",
"tetsudou_shouka_seg3.lab offset (in sec): -0.11\n",
"tetsudou_shouka.lab: 1/25 time-lags are excluded.\n",
"tetsudou_shouka_seg4.lab offset (in sec): -0.09999999999999999\n",
"tetsudou_shouka.lab: 1/25 time-lags are excluded.\n",
"tetsudou_shouka_seg5.lab offset (in sec): -0.12\n",
"tetsudou_shouka_seg6.lab offset (in sec): -0.13\n",
"tetsudou_shouka.lab: 4/25 time-lags are excluded.\n",
"tetsudou_shouka_seg7.lab offset (in sec): -0.11499999999999999\n",
"tombi: Global offset (in sec): -0.075\n",
"tombi_seg0.lab offset (in sec): -0.049999999999999996\n",
"tombi.lab: 3/17 time-lags are excluded.\n",
"tombi_seg1.lab offset (in sec): -0.06\n",
"tombi_seg2.lab offset (in sec): -0.11\n",
"tombi.lab: 4/14 time-lags are excluded.\n",
"tombi_seg3.lab offset (in sec): -0.08\n",
"tombi.lab: 2/12 time-lags are excluded.\n",
"tombi_seg4.lab offset (in sec): -0.08499999999999999\n",
"tombi.lab: 1/7 time-lags are excluded.\n",
"tombi_seg5.lab offset (in sec): -0.04\n",
"tombi.lab: 1/17 time-lags are excluded.\n",
"tombi_seg6.lab offset (in sec): -0.065\n",
"tombi.lab: 2/17 time-lags are excluded.\n",
"tombi_seg7.lab offset (in sec): -0.09999999999999999\n",
"tombi.lab: 2/14 time-lags are excluded.\n",
"tombi_seg8.lab offset (in sec): -0.049999999999999996\n",
"tombi.lab: 1/12 time-lags are excluded.\n",
"tombi_seg9.lab offset (in sec): -0.075\n",
"tombi.lab: 1/7 time-lags are excluded.\n",
"tooryanse: Global offset (in sec): -0.075\n",
"tooryanse_seg0.lab offset (in sec): -0.12\n",
"tooryanse_seg1.lab offset (in sec): -0.08\n",
"tooryanse.lab: 1/36 time-lags are excluded.\n",
"tooryanse_seg2.lab offset (in sec): -0.075\n",
"tooryanse_seg3.lab offset (in sec): -0.06\n",
"tooryanse.lab: 1/28 time-lags are excluded.\n",
"tooryanse_seg4.lab offset (in sec): -0.034999999999999996\n",
"tooryanse.lab: 1/16 time-lags are excluded.\n",
"urashima_taro: Global offset (in sec): -0.08\n",
"urashima_taro_seg0.lab offset (in sec): -0.105\n",
"urashima_taro_seg1.lab offset (in sec): -0.065\n",
"urashima_taro.lab: 3/24 time-lags are excluded.\n",
"urashima_taro_seg2.lab offset (in sec): -0.075\n",
"urashima_taro_seg3.lab offset (in sec): -0.065\n",
"urashima_taro.lab: 2/25 time-lags are excluded.\n",
"urashima_taro_seg4.lab offset (in sec): -0.065\n",
"urashima_taro.lab: 6/26 time-lags are excluded.\n",
"urashima_taro_seg5.lab offset (in sec): -0.11\n",
"urashima_taro.lab: 3/12 time-lags are excluded.\n",
"urashima_taro_seg6.lab offset (in sec): -0.09\n",
"urashima_taro.lab: 2/25 time-lags are excluded.\n",
"urashima_taro_seg7.lab offset (in sec): -0.075\n",
"usagi: Global offset (in sec): -0.06\n",
"usagi_seg0.lab offset (in sec): -0.055\n",
"usagi.lab: 2/31 time-lags are excluded.\n",
"usagito_kame: Global offset (in sec): -0.13499999999999998\n",
"usagito_kame_seg0.lab offset (in sec): -0.13499999999999998\n",
"usagito_kame_seg1.lab offset (in sec): -0.12\n",
"usagito_kame.lab: 2/25 time-lags are excluded.\n",
"usagito_kame_seg2.lab offset (in sec): -0.13999999999999999\n",
"usagito_kame_seg3.lab offset (in sec): -0.13\n",
"usagito_kame.lab: 3/26 time-lags are excluded.\n",
"usagito_kame_seg4.lab offset (in sec): -0.13\n",
"usagito_kame_seg5.lab offset (in sec): -0.13\n",
"usagito_kame.lab: 1/12 time-lags are excluded.\n",
"usagito_kame_seg6.lab offset (in sec): -0.13499999999999998\n",
"usagito_kame.lab: 1/24 time-lags are excluded.\n",
"usagito_kame_seg7.lab offset (in sec): -0.125\n",
"warewa_uminoko: Global offset (in sec): -0.08499999999999999\n",
"warewa_uminoko_seg0.lab offset (in sec): -0.06999999999999999\n",
"warewa_uminoko_seg1.lab offset (in sec): -0.105\n",
"warewa_uminoko.lab: 3/13 time-lags are excluded.\n",
"warewa_uminoko_seg2.lab offset (in sec): -0.11\n",
"warewa_uminoko_seg3.lab offset (in sec): -0.095\n",
"warewa_uminoko.lab: 2/12 time-lags are excluded.\n",
"warewa_uminoko_seg4.lab offset (in sec): -0.045\n",
"warewa_uminoko.lab: 3/13 time-lags are excluded.\n",
"warewa_uminoko_seg5.lab offset (in sec): -0.065\n",
"warewa_uminoko.lab: 3/13 time-lags are excluded.\n",
"warewa_uminoko_seg6.lab offset (in sec): -0.09999999999999999\n",
"warewa_uminoko.lab: 2/12 time-lags are excluded.\n",
"warewa_uminoko_seg7.lab offset (in sec): -0.075\n",
"warewa_uminoko.lab: 3/13 time-lags are excluded.\n",
"warewa_uminoko_seg8.lab offset (in sec): -0.105\n",
"warewa_uminoko_seg9.lab offset (in sec): -0.09\n",
"warewa_uminoko.lab: 2/12 time-lags are excluded.\n",
"warewa_uminoko_seg10.lab offset (in sec): -0.08499999999999999\n",
"warewa_uminoko.lab: 2/13 time-lags are excluded.\n",
"warewa_uminoko_seg11.lab offset (in sec): -0.09\n",
"warewa_uminoko.lab: 2/12 time-lags are excluded.\n",
"yuki: Global offset (in sec): -0.065\n",
"yuki_seg0.lab offset (in sec): -0.065\n",
"yuki.lab: 3/55 time-lags are excluded.\n",
"yuki_seg1.lab offset (in sec): -0.065\n",
"yuki.lab: 2/54 time-lags are excluded.\n",
" 95% 54/57 [00:00<00:00, 123.85it/s]yurikagono_uta: Global offset (in sec): -0.06999999999999999\n",
"yurikagono_uta_seg0.lab offset (in sec): -0.04\n",
"yurikagono_uta_seg1.lab offset (in sec): -0.06999999999999999\n",
"yurikagono_uta.lab: 1/25 time-lags are excluded.\n",
"yurikagono_uta_seg2.lab offset (in sec): -0.055\n",
"yurikagono_uta.lab: 2/18 time-lags are excluded.\n",
"yurikagono_uta_seg3.lab offset (in sec): -0.06999999999999999\n",
"yurikagono_uta.lab: 1/15 time-lags are excluded.\n",
"yurikagono_uta_seg4.lab offset (in sec): -0.06999999999999999\n",
"yurikagono_uta.lab: 1/18 time-lags are excluded.\n",
"yurikagono_uta_seg5.lab offset (in sec): -0.06999999999999999\n",
"zuizuizukkorobashi: Global offset (in sec): -0.075\n",
"zuizuizukkorobashi_seg0.lab offset (in sec): -0.09\n",
"zuizuizukkorobashi.lab: 1/15 time-lags are excluded.\n",
"zuizuizukkorobashi_seg1.lab offset (in sec): -0.11\n",
"zuizuizukkorobashi.lab: 2/23 time-lags are excluded.\n",
"zuizuizukkorobashi_seg2.lab offset (in sec): -0.045\n",
"zuizuizukkorobashi.lab: 3/19 time-lags are excluded.\n",
"zuizuizukkorobashi_seg3.lab offset (in sec): -0.055\n",
"zuizuizukkorobashi_seg4.lab offset (in sec): -0.065\n",
"zuizuizukkorobashi_low: Global offset (in sec): -0.08499999999999999\n",
"zuizuizukkorobashi_low_seg0.lab offset (in sec): -0.09\n",
"zuizuizukkorobashi_low_seg1.lab offset (in sec): -0.105\n",
"zuizuizukkorobashi_low.lab: 4/23 time-lags are excluded.\n",
"zuizuizukkorobashi_low_seg2.lab offset (in sec): -0.08\n",
"zuizuizukkorobashi_low.lab: 1/19 time-lags are excluded.\n",
"zuizuizukkorobashi_low_seg3.lab offset (in sec): -0.075\n",
"zuizuizukkorobashi_low.lab: 2/27 time-lags are excluded.\n",
"zuizuizukkorobashi_low_seg4.lab offset (in sec): -0.075\n",
"zuizuizukkorobashi_low.lab: 1/18 time-lags are excluded.\n",
"100% 57/57 [00:00<00:00, 129.19it/s]\n",
"Prepare data for duration models\n",
"100% 57/57 [00:00<00:00, 609.01it/s]\n",
"Prepare data for acoustic models\n",
"100% 57/57 [05:00<00:00, 5.28s/it]\n",
"train/dev/eval split\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "tmI-uuTPGxxO",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "5af5d64f-9c79-4f96-c89d-ba22d7c86eab"
},
"source": [
"# stage1の実行(言語特徴量, 持続長, タイムラグ, 音響特徴量の展開)\n",
"! cd $RECIPE_ROOT && bash run.sh --stage 1 --stop-stage 1"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"stage 1: Feature generation\n",
"[\u001b[36m2020-06-28 15:36:26,523\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - acoustic:\n",
" enabled: true\n",
" f0_ceil: 700\n",
" f0_floor: 150\n",
" frame_period: 5\n",
" interp_unvoiced_aperiodicity: true\n",
" label_dir: data/acoustic/label_phone_align\n",
" mgc_order: 59\n",
" num_windows: 3\n",
" question_path: null\n",
" relative_f0: true\n",
" subphone_features: coarse_coding\n",
" use_harvest: true\n",
" wav_dir: data/acoustic/wav\n",
"duration:\n",
" enabled: true\n",
" label_dir: data/duration/label_phone_align\n",
" question_path: null\n",
"log_f0_conditioning: true\n",
"out_dir: dump/ofuton_p/org/train_no_dev/\n",
"question_path: ./conf/jp_qst001_nnsvs.hed\n",
"timelag:\n",
" enabled: true\n",
" label_phone_align_dir: data/timelag/label_phone_align\n",
" label_phone_score_dir: data/timelag/label_phone_score\n",
" question_path: null\n",
"utt_list: data/list/train_no_dev.list\n",
"verbose: 100\n",
"\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:26,562\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/train_no_dev/in_timelag\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:26,563\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/train_no_dev/out_timelag\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:26,563\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/train_no_dev/in_duration\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:26,563\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/train_no_dev/out_duration\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:26,563\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/train_no_dev/in_acoustic\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:26,563\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/train_no_dev/out_acoustic\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:26,572\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Timelag linguistic feature dim: 420\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:26,573\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Timelag feature dim: 1\u001b[0m\n",
"100% 311/311 [00:03<00:00, 91.65it/s]\n",
"[\u001b[36m2020-06-28 15:36:29,978\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Duration linguistic feature dim: 420\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:29,979\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Duration feature dim: 1\u001b[0m\n",
"100% 311/311 [00:06<00:00, 49.21it/s]\n",
"[\u001b[36m2020-06-28 15:36:36,322\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Acoustic linguistic feature dim: 424\u001b[0m\n",
"[\u001b[36m2020-06-28 15:36:39,370\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Acoustic feature dim: 199\u001b[0m\n",
"100% 311/311 [21:39<00:00, 4.18s/it]\n",
"[\u001b[36m2020-06-28 15:58:20,541\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - acoustic:\n",
" enabled: true\n",
" f0_ceil: 700\n",
" f0_floor: 150\n",
" frame_period: 5\n",
" interp_unvoiced_aperiodicity: true\n",
" label_dir: data/acoustic/label_phone_align\n",
" mgc_order: 59\n",
" num_windows: 3\n",
" question_path: null\n",
" relative_f0: true\n",
" subphone_features: coarse_coding\n",
" use_harvest: true\n",
" wav_dir: data/acoustic/wav\n",
"duration:\n",
" enabled: true\n",
" label_dir: data/duration/label_phone_align\n",
" question_path: null\n",
"log_f0_conditioning: true\n",
"out_dir: dump/ofuton_p/org/dev/\n",
"question_path: ./conf/jp_qst001_nnsvs.hed\n",
"timelag:\n",
" enabled: true\n",
" label_phone_align_dir: data/timelag/label_phone_align\n",
" label_phone_score_dir: data/timelag/label_phone_score\n",
" question_path: null\n",
"utt_list: data/list/dev.list\n",
"verbose: 100\n",
"\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,576\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/dev/in_timelag\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,576\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/dev/out_timelag\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,576\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/dev/in_duration\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,577\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/dev/out_duration\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,577\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/dev/in_acoustic\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,577\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/dev/out_acoustic\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,586\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Timelag linguistic feature dim: 420\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,586\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Timelag feature dim: 1\u001b[0m\n",
"100% 4/4 [00:00<00:00, 69.80it/s]\n",
"[\u001b[36m2020-06-28 15:58:20,661\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Duration linguistic feature dim: 420\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:20,662\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Duration feature dim: 1\u001b[0m\n",
"100% 4/4 [00:00<00:00, 31.87it/s]\n",
"[\u001b[36m2020-06-28 15:58:20,821\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Acoustic linguistic feature dim: 424\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:24,616\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Acoustic feature dim: 199\u001b[0m\n",
"100% 4/4 [00:18<00:00, 4.59s/it]\n",
"[\u001b[36m2020-06-28 15:58:44,533\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - acoustic:\n",
" enabled: true\n",
" f0_ceil: 700\n",
" f0_floor: 150\n",
" frame_period: 5\n",
" interp_unvoiced_aperiodicity: true\n",
" label_dir: data/acoustic/label_phone_align\n",
" mgc_order: 59\n",
" num_windows: 3\n",
" question_path: null\n",
" relative_f0: true\n",
" subphone_features: coarse_coding\n",
" use_harvest: true\n",
" wav_dir: data/acoustic/wav\n",
"duration:\n",
" enabled: true\n",
" label_dir: data/duration/label_phone_align\n",
" question_path: null\n",
"log_f0_conditioning: true\n",
"out_dir: dump/ofuton_p/org/eval/\n",
"question_path: ./conf/jp_qst001_nnsvs.hed\n",
"timelag:\n",
" enabled: true\n",
" label_phone_align_dir: data/timelag/label_phone_align\n",
" label_phone_score_dir: data/timelag/label_phone_score\n",
" question_path: null\n",
"utt_list: data/list/eval.list\n",
"verbose: 100\n",
"\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,568\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/eval/in_timelag\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,568\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/eval/out_timelag\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,568\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/eval/in_duration\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,568\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/eval/out_duration\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,568\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/eval/in_acoustic\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,568\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - mkdirs: /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/dump/ofuton_p/org/eval/out_acoustic\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,577\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Timelag linguistic feature dim: 420\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,577\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Timelag feature dim: 1\u001b[0m\n",
"100% 6/6 [00:00<00:00, 109.65it/s]\n",
"[\u001b[36m2020-06-28 15:58:44,649\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Duration linguistic feature dim: 420\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:44,649\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Duration feature dim: 1\u001b[0m\n",
"100% 6/6 [00:00<00:00, 60.86it/s]\n",
"[\u001b[36m2020-06-28 15:58:44,795\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Acoustic linguistic feature dim: 424\u001b[0m\n",
"[\u001b[36m2020-06-28 15:58:47,295\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Acoustic feature dim: 199\u001b[0m\n",
"100% 6/6 [00:11<00:00, 1.99s/it]\n",
"[2020-06-28 15:59:00,136][nnsvs][INFO] - list_path: train_list.txt\n",
"out_path: dump/ofuton_p/org/in_timelag_scaler.joblib\n",
"scaler:\n",
" class: sklearn.preprocessing.MinMaxScaler\n",
" params: {}\n",
"verbose: 100\n",
"\n",
"[2020-06-28 15:59:00,291][nnsvs][INFO] - data min:\n",
"[ 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
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" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 1. 0. 0. 0. 0.\n",
" 0. 0. 1. 0. 0. 0.\n",
" 0. 0. 0. 1. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 4.4116693 4.4116693 4.4116693\n",
" 1. 1. -1. -1. -1. -1.\n",
" -1. 1. 1. 1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. 0. 1. 7. 3. 0.\n",
" 0. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1. ]\n",
"[2020-06-28 15:59:00,294][nnsvs][INFO] - data max:\n",
"[ 0. 1. 0. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 1. 1.\n",
" 1. 1. 0. 0. 1. 0.\n",
" 0. 0. 0. 0. 1. 0.\n",
" 0. 0. 0. 0. 1. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 1. 1.\n",
" 0. 0. 1. 0. 1. 0.\n",
" 0. 1. 0. 0. 1. 0.\n",
" 0. 0. 0. 0. 1. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 1. 0. 1. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 1. 0. 0. 0. 0. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 0. 0. 1.\n",
" 0. 0. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 0. 1. 1.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 0.\n",
" 0. 1. 0. 0. 0. 0.\n",
" 0. 0. 1. 0. 0. 0.\n",
" 0. 0. 0. 1. 0. 0.\n",
" 0. 0. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 0. 0.\n",
" 0. 1. 1. 1. 0. 0.\n",
" 1. 0. 0. 1. 1. 1.\n",
" 0. 0. 1. 0. 0. 0.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 0. 0. 1. 1. 1.\n",
" 0. 0. 1. 5.855726 5.855726 5.855726\n",
" 1. 4. -1. 2. 4. 1.\n",
" 1. 4. 1. 1. 4. 1.\n",
" 1. 11. 11. 1. 187. 66.\n",
" 11. 11. 1. 215. 75. 0.\n",
" 0. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. 11. 11. 1. 215. 75. ]\n",
"'dump/ofuton_p/org/in_timelag_scaler.joblib' -> 'dump/ofuton_p/norm/in_timelag_scaler.joblib'\n",
"[2020-06-28 15:59:01,108][nnsvs][INFO] - list_path: train_list.txt\n",
"out_path: dump/ofuton_p/org/in_duration_scaler.joblib\n",
"scaler:\n",
" class: sklearn.preprocessing.MinMaxScaler\n",
" params: {}\n",
"verbose: 100\n",
"\n",
"[2020-06-28 15:59:01,280][nnsvs][INFO] - data min:\n",
"[ 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 1. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 4.4116693 4.4116693 4.4116693\n",
" 1. 1. -1. -1. -1. -1.\n",
" -1. 1. 1. 1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. 0. 1. 7. 3. 0.\n",
" 0. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1. ]\n",
"[2020-06-28 15:59:01,283][nnsvs][INFO] - data max:\n",
"[ 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 0. 1. 1.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 0. 1. 1.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 1. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 0. 1. 1.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1. 0.\n",
" 0. 1. 0. 0. 0. 0.\n",
" 0. 0. 1. 0. 0. 0.\n",
" 0. 0. 0. 1. 0. 0.\n",
" 0. 0. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 0. 0.\n",
" 0. 1. 1. 1. 0. 0.\n",
" 1. 0. 0. 1. 1. 1.\n",
" 0. 0. 1. 0. 0. 0.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 0. 0. 1. 1. 1.\n",
" 0. 0. 1. 5.855726 5.855726 5.855726\n",
" 4. 4. -1. 2. 4. 1.\n",
" 1. 4. 1. 1. 4. 1.\n",
" 1. 11. 11. 1. 187. 72.\n",
" 11. 11. 1. 419. 168. 0.\n",
" 0. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. 11. 11. 1. 215. 75. ]\n",
"'dump/ofuton_p/org/in_duration_scaler.joblib' -> 'dump/ofuton_p/norm/in_duration_scaler.joblib'\n",
"[2020-06-28 15:59:02,090][nnsvs][INFO] - list_path: train_list.txt\n",
"out_path: dump/ofuton_p/org/in_acoustic_scaler.joblib\n",
"scaler:\n",
" class: sklearn.preprocessing.MinMaxScaler\n",
" params: {}\n",
"verbose: 100\n",
"\n",
"[2020-06-28 15:59:03,186][nnsvs][INFO] - data min:\n",
"[ 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 1. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 0. 0. 0.\n",
" 0. 0. 1. 1. 1. 1.\n",
" 1. 0. 0. 0. 0. 0.\n",
" 0. 0. 0. 4.4116693 4.4116693 4.4116693\n",
" 1. 1. -1. -1. -1. -1.\n",
" -1. 1. 1. 1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. 0. 1. 7. 3. 0.\n",
" 0. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1. -1.\n",
" 0.04404987 0.45900714 0.04404987 1. ]\n",
"[2020-06-28 15:59:03,188][nnsvs][INFO] - data max:\n",
"[ 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 0. 1. 1. 1.\n",
" 1. 1. 0. 1. 1.\n",
" 0. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 0. 0. 1. 1.\n",
" 0. 0. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 1. 1.\n",
" 1. 1. 1. 0. 1.\n",
" 1. 0. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 0. 0. 1.\n",
" 1. 0. 0. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 0. 1.\n",
" 1. 1. 1. 1. 0.\n",
" 1. 1. 0. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 0. 0.\n",
" 1. 1. 0. 0. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 1. 1.\n",
" 1. 1. 1. 0. 0.\n",
" 1. 0. 0. 0. 0.\n",
" 0. 0. 1. 0. 0.\n",
" 0. 0. 0. 0. 1.\n",
" 0. 0. 0. 0. 1.\n",
" 1. 0. 1. 1. 0.\n",
" 1. 1. 0. 0. 0.\n",
" 1. 1. 1. 0. 0.\n",
" 1. 0. 0. 1. 1.\n",
" 1. 0. 0. 1. 0.\n",
" 0. 0. 0. 0. 1.\n",
" 1. 1. 1. 1. 0.\n",
" 0. 1. 1. 1. 0.\n",
" 0. 1. 5.855726 5.855726 5.855726\n",
" 4. 4. -1. 2. 4.\n",
" 1. 1. 4. 1. 1.\n",
" 4. 1. 1. 11. 11.\n",
" 1. 187. 72. 11. 11.\n",
" 1. 419. 168. 0. 0.\n",
" -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1.\n",
" -1. -1. -1. -1. -1.\n",
" 11. 11. 1. 215. 75.\n",
" 0.99733615 0.99733615 0.99733615 820. ]\n",
"'dump/ofuton_p/org/in_acoustic_scaler.joblib' -> 'dump/ofuton_p/norm/in_acoustic_scaler.joblib'\n",
"[2020-06-28 15:59:03,986][nnsvs][INFO] - list_path: train_list.txt\n",
"out_path: dump/ofuton_p/org/out_timelag_scaler.joblib\n",
"scaler:\n",
" class: sklearn.preprocessing.StandardScaler\n",
" params: {}\n",
"verbose: 100\n",
"\n",
"[2020-06-28 15:59:04,184][nnsvs][INFO] - mean:\n",
"[0.73342518]\n",
"[2020-06-28 15:59:04,184][nnsvs][INFO] - std:\n",
"[8.84255003]\n",
"'dump/ofuton_p/org/out_timelag_scaler.joblib' -> 'dump/ofuton_p/norm/out_timelag_scaler.joblib'\n",
"[2020-06-28 15:59:04,980][nnsvs][INFO] - list_path: train_list.txt\n",
"out_path: dump/ofuton_p/org/out_duration_scaler.joblib\n",
"scaler:\n",
" class: sklearn.preprocessing.StandardScaler\n",
" params: {}\n",
"verbose: 100\n",
"\n",
"[2020-06-28 15:59:05,179][nnsvs][INFO] - mean:\n",
"[54.91732528]\n",
"[2020-06-28 15:59:05,179][nnsvs][INFO] - std:\n",
"[60.16458363]\n",
"'dump/ofuton_p/org/out_duration_scaler.joblib' -> 'dump/ofuton_p/norm/out_duration_scaler.joblib'\n",
"[2020-06-28 15:59:05,975][nnsvs][INFO] - list_path: train_list.txt\n",
"out_path: dump/ofuton_p/org/out_acoustic_scaler.joblib\n",
"scaler:\n",
" class: sklearn.preprocessing.StandardScaler\n",
" params: {}\n",
"verbose: 100\n",
"\n",
"[2020-06-28 15:59:07,510][nnsvs][INFO] - mean:\n",
"[ 4.48926286e+00 2.97738155e+00 -2.91884945e-01 6.45235902e-01\n",
" -1.00614775e-01 6.54349805e-01 6.34388516e-02 -8.30964667e-02\n",
" -9.20893713e-02 2.71247570e-01 -1.00649429e-01 -6.77840504e-02\n",
" -1.41360167e-01 1.63447164e-01 -5.64226461e-02 -2.03896975e-01\n",
" -5.75325741e-02 8.86676556e-02 -5.90037380e-02 -7.32930201e-02\n",
" -1.78592527e-02 2.05292001e-02 -7.26582866e-02 1.19229324e-01\n",
" -8.19775023e-02 4.74537804e-02 -3.24075710e-02 3.08261003e-02\n",
" 4.12904096e-02 1.43013676e-02 -2.96003808e-02 7.67341694e-02\n",
" -6.02285109e-02 3.67615707e-02 1.78320143e-02 -2.81091364e-02\n",
" 3.91657386e-03 9.85617921e-03 -2.86082749e-02 3.10848263e-02\n",
" -2.30870027e-02 4.24013389e-03 -1.17542802e-02 1.88583942e-02\n",
" -1.38665788e-02 5.44744954e-03 -3.11447554e-03 1.48186223e-02\n",
" -1.19160509e-02 -2.75431900e-04 1.29378540e-02 -6.11846726e-03\n",
" -1.49864954e-03 7.06798926e-03 -4.81458815e-03 3.74347837e-03\n",
" -1.44612219e-03 5.23740129e-04 -5.59670536e-03 8.01284669e-03\n",
" 1.57268045e-04 1.32559408e-04 5.50871281e-05 4.34797274e-05\n",
" 1.68756348e-05 4.93717621e-05 1.98767606e-05 -4.66752920e-06\n",
" 8.59068062e-06 3.25091861e-05 1.61273339e-06 -4.45396267e-06\n",
" 4.00147813e-07 2.38012813e-05 7.64756097e-06 -1.06114406e-05\n",
" 1.55647913e-05 1.51681867e-05 1.42526293e-07 4.63573998e-06\n",
" -6.53584903e-06 -1.03769077e-05 -7.01639191e-06 3.92296501e-06\n",
" -5.75906031e-06 -6.83822294e-06 -5.89954444e-06 4.66451417e-06\n",
" 5.72005987e-06 -7.07712378e-06 -4.60696814e-06 5.15718574e-06\n",
" -4.80055142e-06 2.41557779e-06 9.52538261e-08 -4.66958504e-06\n",
" 1.17861852e-06 -2.42326697e-06 -4.13439283e-06 -3.43042102e-06\n",
" -1.69875148e-06 -3.30997166e-06 -2.17783666e-06 2.54081858e-06\n",
" -1.72423759e-06 -1.33102531e-06 1.30597727e-06 1.67030843e-06\n",
" -2.10995412e-06 2.86645623e-07 2.43354550e-06 -1.59007966e-06\n",
" 6.54938133e-07 3.84398823e-07 -2.74632212e-07 7.95648174e-07\n",
" 6.96134620e-07 7.39473353e-07 -9.34550047e-07 -4.26649085e-07\n",
" -1.32312427e-03 -1.84876271e-03 -3.05418120e-04 -6.41706284e-04\n",
" -1.99452853e-04 -4.32408685e-04 -2.31824128e-04 -6.56324357e-05\n",
" -1.43100662e-04 -1.26032882e-04 1.32927659e-05 -4.27734088e-05\n",
" -5.22294892e-06 -7.09492448e-05 1.74572146e-05 6.71909170e-05\n",
" 2.30302999e-06 -4.92426447e-05 3.22425786e-05 1.67978747e-05\n",
" 2.78223923e-05 1.55220879e-05 5.43268106e-05 -5.03140257e-05\n",
" 5.62128735e-05 -1.80580397e-05 3.46641936e-05 -1.71242010e-05\n",
" -4.87179974e-06 2.16595603e-06 3.10293087e-05 -4.71190397e-05\n",
" 3.79820273e-05 -2.66634695e-05 9.18557222e-06 2.86063706e-06\n",
" 1.00459601e-05 -7.07226702e-06 2.77563873e-05 -1.43094832e-05\n",
" 2.32335454e-05 -8.94884925e-06 1.73407378e-05 -1.58240729e-05\n",
" 9.67414741e-06 -5.85404009e-07 3.25312214e-06 -1.18162865e-05\n",
" 1.16396230e-05 -6.30235149e-06 -5.05632170e-08 -1.66738750e-07\n",
" -1.10338438e-06 2.27707375e-06 -2.31321337e-06 1.50078330e-06\n",
" -4.51007713e-06 3.27121809e-07 2.99135481e-06 2.72827903e-07\n",
" -5.79674038e-03 5.44635917e-06 2.10636908e-05 8.41008758e-01\n",
" -1.41878815e+01 -9.26621885e+00 -7.28834103e+00 -5.09372915e+00\n",
" -4.36185330e+00 3.63857417e-04 1.56232293e-04 1.43463933e-04\n",
" 2.08561030e-05 4.26869365e-05 4.00363858e-03 3.18195146e-03\n",
" 3.31092074e-03 2.90256445e-03 2.96820442e-03]\n",
"[2020-06-28 15:59:07,512][nnsvs][INFO] - std:\n",
"[1.79201074 0.97229052 0.43389168 0.31486011 0.30160703 0.34802819\n",
" 0.38400011 0.34369319 0.31528761 0.22169372 0.17668416 0.19605052\n",
" 0.20236178 0.16200776 0.17534768 0.17599711 0.17294366 0.15149844\n",
" 0.14371782 0.13197993 0.13875385 0.13511918 0.14427937 0.12884297\n",
" 0.11039449 0.11870753 0.10421255 0.11494491 0.10825022 0.1083141\n",
" 0.10188893 0.09607891 0.09453858 0.09706703 0.10103088 0.09474976\n",
" 0.09115526 0.09024867 0.08478478 0.08111446 0.07632886 0.07762267\n",
" 0.07521336 0.07316142 0.07224926 0.07016255 0.06800952 0.06545666\n",
" 0.06351626 0.06335577 0.06347015 0.0623366 0.06058766 0.05858666\n",
" 0.05664507 0.05542949 0.0544544 0.05340965 0.05243242 0.05148207\n",
" 0.34197671 0.10535069 0.0858115 0.06805183 0.0698238 0.06371546\n",
" 0.06492903 0.06390249 0.06014709 0.05665489 0.05383046 0.05511184\n",
" 0.05362892 0.05077423 0.04980198 0.04972662 0.04679259 0.04604398\n",
" 0.04430617 0.04339124 0.04279286 0.04149237 0.04069633 0.03955876\n",
" 0.03845222 0.03805506 0.03721631 0.03657307 0.03595842 0.03523453\n",
" 0.03464097 0.03417351 0.03334314 0.03282699 0.03234205 0.03174121\n",
" 0.03113692 0.03061703 0.03015665 0.02963262 0.02914003 0.02866706\n",
" 0.02821198 0.02784697 0.02743659 0.02699947 0.02660914 0.02626353\n",
" 0.02601805 0.02566573 0.02531606 0.02503787 0.02470106 0.02444943\n",
" 0.02409506 0.02379527 0.02346215 0.02321056 0.0229619 0.02264629\n",
" 0.95067789 0.22741301 0.22452869 0.18614215 0.19832816 0.1854116\n",
" 0.17620564 0.18682531 0.17289661 0.16924965 0.15571504 0.15983521\n",
" 0.1554852 0.14910783 0.14280538 0.1431537 0.13258551 0.12967116\n",
" 0.12432488 0.12078882 0.11890827 0.11524051 0.11160263 0.1088205\n",
" 0.1050244 0.10339223 0.10091265 0.09868278 0.09679328 0.09467894\n",
" 0.09345121 0.09228151 0.08969745 0.08858049 0.087493 0.08559784\n",
" 0.08416775 0.08298582 0.08200882 0.08077635 0.07904161 0.07770294\n",
" 0.07662254 0.07584374 0.07478761 0.07336304 0.07203313 0.07133429\n",
" 0.07064425 0.06963421 0.06852607 0.06757136 0.06686524 0.066193\n",
" 0.06525083 0.06430101 0.06349325 0.0627604 0.06208101 0.06138205\n",
" 0.10327463 0.01551749 0.02162095 0.36566792 8.00330603 6.07410643\n",
" 4.68184088 3.10054723 2.47154248 1.53122039 1.6307418 1.70622076\n",
" 1.40898576 1.33588955 3.67739233 4.25948026 4.55921912 3.93342993\n",
" 3.82205952]\n",
"'dump/ofuton_p/org/out_acoustic_scaler.joblib' -> 'dump/ofuton_p/norm/out_acoustic_scaler.joblib'\n",
"[\u001b[36m2020-06-28 15:59:08,330\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/train_no_dev/in_timelag/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/train_no_dev/in_timelag/\n",
"scaler_path: dump/ofuton_p/org/in_timelag_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 311/311 [00:00<00:00, 1323.15it/s]\n",
"[\u001b[36m2020-06-28 15:59:09,436\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/train_no_dev/in_duration/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/train_no_dev/in_duration/\n",
"scaler_path: dump/ofuton_p/org/in_duration_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 311/311 [00:00<00:00, 1235.52it/s]\n",
"[\u001b[36m2020-06-28 15:59:10,551\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/train_no_dev/in_acoustic/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/train_no_dev/in_acoustic/\n",
"scaler_path: dump/ofuton_p/org/in_acoustic_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 311/311 [00:03<00:00, 89.23it/s]\n",
"[\u001b[36m2020-06-28 15:59:15,145\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/train_no_dev/out_timelag/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/train_no_dev/out_timelag/\n",
"scaler_path: dump/ofuton_p/org/out_timelag_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 311/311 [00:00<00:00, 1668.93it/s]\n",
"[\u001b[36m2020-06-28 15:59:16,225\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/train_no_dev/out_duration/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/train_no_dev/out_duration/\n",
"scaler_path: dump/ofuton_p/org/out_duration_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 311/311 [00:00<00:00, 1284.01it/s]\n",
"[\u001b[36m2020-06-28 15:59:17,317\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/train_no_dev/out_acoustic/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/train_no_dev/out_acoustic/\n",
"scaler_path: dump/ofuton_p/org/out_acoustic_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 311/311 [00:15<00:00, 20.52it/s]\n",
"[\u001b[36m2020-06-28 15:59:39,778\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/dev/in_timelag/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/dev/in_timelag/\n",
"scaler_path: dump/ofuton_p/org/in_timelag_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 269.44it/s]\n",
"[\u001b[36m2020-06-28 15:59:40,645\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/dev/in_duration/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/dev/in_duration/\n",
"scaler_path: dump/ofuton_p/org/in_duration_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 142.92it/s]\n",
"[\u001b[36m2020-06-28 15:59:41,501\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/dev/in_acoustic/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/dev/in_acoustic/\n",
"scaler_path: dump/ofuton_p/org/in_acoustic_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 88.19it/s]\n",
"[\u001b[36m2020-06-28 15:59:42,391\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/dev/out_timelag/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/dev/out_timelag/\n",
"scaler_path: dump/ofuton_p/org/out_timelag_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 170.10it/s]\n",
"[\u001b[36m2020-06-28 15:59:43,248\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/dev/out_duration/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/dev/out_duration/\n",
"scaler_path: dump/ofuton_p/org/out_duration_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 154.28it/s]\n",
"[\u001b[36m2020-06-28 15:59:44,140\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/dev/out_acoustic/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/dev/out_acoustic/\n",
"scaler_path: dump/ofuton_p/org/out_acoustic_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 89.28it/s]\n",
"[\u001b[36m2020-06-28 15:59:45,024\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/eval/in_timelag/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/eval/in_timelag/\n",
"scaler_path: dump/ofuton_p/org/in_timelag_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 217.01it/s]\n",
"[\u001b[36m2020-06-28 15:59:45,881\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/eval/in_duration/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/eval/in_duration/\n",
"scaler_path: dump/ofuton_p/org/in_duration_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 428.30it/s]\n",
"[\u001b[36m2020-06-28 15:59:46,735\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/eval/in_acoustic/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/eval/in_acoustic/\n",
"scaler_path: dump/ofuton_p/org/in_acoustic_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 96.81it/s]\n",
"[\u001b[36m2020-06-28 15:59:47,632\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/eval/out_timelag/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/eval/out_timelag/\n",
"scaler_path: dump/ofuton_p/org/out_timelag_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 225.94it/s]\n",
"[\u001b[36m2020-06-28 15:59:48,495\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/eval/out_duration/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/eval/out_duration/\n",
"scaler_path: dump/ofuton_p/org/out_duration_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 225.95it/s]\n",
"[\u001b[36m2020-06-28 15:59:49,355\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/org/eval/out_acoustic/\n",
"inverse: false\n",
"num_workers: 4\n",
"out_dir: dump/ofuton_p/norm/eval/out_acoustic/\n",
"scaler_path: dump/ofuton_p/org/out_acoustic_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 113.81it/s]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ulblx4TgbU_d",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "3a4ae3e8-c15a-4f7a-dc2f-d1bcb6293352"
},
"source": [
"! cd $RECIPE_ROOT && bash run.sh --stage 2 --stop-stage 4"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"stage 2: Training time-lag model\n",
"+ nnsvs-train data.train_no_dev.in_dir=dump/ofuton_p/norm/train_no_dev/in_timelag/ data.train_no_dev.out_dir=dump/ofuton_p/norm/train_no_dev/out_timelag/ data.dev.in_dir=dump/ofuton_p/norm/dev/in_timelag/ data.dev.out_dir=dump/ofuton_p/norm/dev/out_timelag/ model=timelag train.out_dir=exp/ofuton_p/timelag data.batch_size=8 resume.checkpoint=\n",
"[\u001b[36m2020-06-28 15:59:58,097\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - cudnn:\n",
" benchmark: false\n",
" deterministic: false\n",
"data:\n",
" batch_size: 8\n",
" dev:\n",
" in_dir: dump/ofuton_p/norm/dev/in_timelag/\n",
" out_dir: dump/ofuton_p/norm/dev/out_timelag/\n",
" num_workers: 2\n",
" pin_memory: true\n",
" train_no_dev:\n",
" in_dir: dump/ofuton_p/norm/train_no_dev/in_timelag/\n",
" out_dir: dump/ofuton_p/norm/train_no_dev/out_timelag/\n",
"model:\n",
" has_dynamic_features:\n",
" - false\n",
" netG:\n",
" class: nnsvs.model.FeedForwardNet\n",
" params:\n",
" dropout: 0.5\n",
" hidden_dim: 128\n",
" in_dim: 420\n",
" num_layers: 2\n",
" out_dim: 1\n",
" stream_sizes:\n",
" - 1\n",
" stream_weights:\n",
" - 1\n",
"optim:\n",
" lr_scheduler:\n",
" name: StepLR\n",
" params:\n",
" gamma: 0.5\n",
" step_size: 20\n",
" optimizer:\n",
" name: Adam\n",
" params:\n",
" betas:\n",
" - 0.5\n",
" - 0.999\n",
" lr: 0.001\n",
" weight_decay: 0.0\n",
"resume:\n",
" checkpoint: null\n",
" load_optimizer: false\n",
"train:\n",
" checkpoint_epoch_interval: 20\n",
" nepochs: 50\n",
" out_dir: exp/ofuton_p/timelag\n",
" stream_wise_loss: false\n",
"verbose: 100\n",
"\u001b[0m\n",
"[\u001b[36m2020-06-28 15:59:58,097\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - cudnn.deterministic: False\u001b[0m\n",
"[\u001b[36m2020-06-28 15:59:58,097\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - cudnn.benchmark: False\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,755\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 23, 420]), torch.Size([8, 23, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,756\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 47, 420]), torch.Size([8, 47, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,769\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,771\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 42, 420]), torch.Size([8, 42, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,777\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 26, 420]), torch.Size([8, 26, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,782\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,789\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 27, 420]), torch.Size([8, 27, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,789\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 37, 420]), torch.Size([8, 37, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,801\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 41, 420]), torch.Size([8, 41, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,804\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 51, 420]), torch.Size([8, 51, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,815\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 21, 420]), torch.Size([8, 21, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,815\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 44, 420]), torch.Size([8, 44, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,829\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 52, 420]), torch.Size([8, 52, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,829\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 36, 420]), torch.Size([8, 36, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,842\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,843\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 28, 420]), torch.Size([8, 28, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,854\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,855\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 41, 420]), torch.Size([8, 41, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,870\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,871\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 65, 420]), torch.Size([8, 65, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,880\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 30, 420]), torch.Size([8, 30, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,880\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 23, 420]), torch.Size([8, 23, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,895\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 64, 420]), torch.Size([8, 64, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,896\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 46, 420]), torch.Size([8, 46, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,903\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 42, 420]), torch.Size([8, 42, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,905\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 47, 420]), torch.Size([8, 47, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,914\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 35, 420]), torch.Size([8, 35, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,918\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 51, 420]), torch.Size([8, 51, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,925\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 48, 420]), torch.Size([8, 48, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,932\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 46, 420]), torch.Size([8, 46, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,935\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 37, 420]), torch.Size([8, 37, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,948\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,948\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,960\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,960\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 38, 420]), torch.Size([8, 38, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,983\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 52, 420]), torch.Size([8, 52, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,983\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 31, 420]), torch.Size([8, 31, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,988\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 25, 420]), torch.Size([8, 25, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:07,989\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([7, 28, 420]), torch.Size([7, 28, 1]), torch.Size([7])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:08,074\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([4, 49, 420]), torch.Size([4, 49, 1]), torch.Size([4])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:08,105\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Start utterance-wise training...\u001b[0m\n",
" 0% 0/50 [00:00<?, ?it/s][\u001b[36m2020-06-28 16:00:08,745\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 1]: loss 0.8766254660410758\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:08,830\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 1]: loss 0.5543361306190491\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:08,838\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.5543361306190491: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/timelag/best_loss.pth\u001b[0m\n",
" 2% 1/50 [00:00<00:35, 1.37it/s][\u001b[36m2020-06-28 16:00:09,278\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 2]: loss 0.7319812530126327\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:09,361\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 2]: loss 0.4849509596824646\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:09,364\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.4849509596824646: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/timelag/best_loss.pth\u001b[0m\n",
" 4% 2/50 [00:01<00:32, 1.49it/s][\u001b[36m2020-06-28 16:00:09,788\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 3]: loss 0.6996632585158715\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:09,871\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 3]: loss 0.47765660285949707\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:09,875\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.47765660285949707: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/timelag/best_loss.pth\u001b[0m\n",
" 6% 3/50 [00:01<00:29, 1.61it/s][\u001b[36m2020-06-28 16:00:10,316\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 4]: loss 0.6715908447901408\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:10,396\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 4]: loss 0.5092870593070984\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:00:11,432\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 6]: loss 0.5392448306083679\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:00:14,675\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 12]: loss 0.49948588013648987\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:00:16,214\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 15]: loss 0.5369619131088257\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:00:18,832\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 20]: loss 0.5137125849723816\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:18,835\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/timelag/checkpoint_epoch0020.pth\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:00:28,200\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 38]: loss 0.5843889713287354\u001b[0m\n",
" 76% 38/50 [00:20<00:06, 1.92it/s][\u001b[36m2020-06-28 16:00:28,634\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 39]: loss 0.3878770738075941\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:28,724\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 39]: loss 0.5373384952545166\u001b[0m\n",
" 78% 39/50 [00:20<00:05, 1.91it/s][\u001b[36m2020-06-28 16:00:29,151\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 40]: loss 0.37616001948332173\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:29,235\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 40]: loss 0.5588184595108032\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:29,238\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/timelag/checkpoint_epoch0040.pth\u001b[0m\n",
" 80% 40/50 [00:21<00:05, 1.92it/s][\u001b[36m2020-06-28 16:00:29,673\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 41]: loss 0.3583420545626909\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:29,763\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 41]: loss 0.5684723258018494\u001b[0m\n",
" 82% 41/50 [00:21<00:04, 1.92it/s][\u001b[36m2020-06-28 16:00:30,192\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 42]: loss 0.3643591610284952\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:30,275\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 42]: loss 0.5455981492996216\u001b[0m\n",
" 84% 42/50 [00:22<00:04, 1.93it/s][\u001b[36m2020-06-28 16:00:30,705\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 43]: loss 0.35222015166893983\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:30,797\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 43]: loss 0.5729848742485046\u001b[0m\n",
" 86% 43/50 [00:22<00:03, 1.93it/s][\u001b[36m2020-06-28 16:00:31,237\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 44]: loss 0.34880908253865367\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:31,324\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 44]: loss 0.5542305707931519\u001b[0m\n",
" 88% 44/50 [00:23<00:03, 1.92it/s][\u001b[36m2020-06-28 16:00:31,751\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 45]: loss 0.3509776301873036\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:31,844\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 45]: loss 0.5562002658843994\u001b[0m\n",
" 90% 45/50 [00:23<00:02, 1.92it/s][\u001b[36m2020-06-28 16:00:32,267\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 46]: loss 0.3436629061515515\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:32,349\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 46]: loss 0.5618273019790649\u001b[0m\n",
" 92% 46/50 [00:24<00:02, 1.94it/s][\u001b[36m2020-06-28 16:00:32,782\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 47]: loss 0.34328524348063344\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:32,873\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 47]: loss 0.5903031826019287\u001b[0m\n",
" 94% 47/50 [00:24<00:01, 1.93it/s][\u001b[36m2020-06-28 16:00:33,309\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 48]: loss 0.33947039185426175\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:33,401\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 48]: loss 0.5833054184913635\u001b[0m\n",
" 96% 48/50 [00:25<00:01, 1.92it/s][\u001b[36m2020-06-28 16:00:33,835\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 49]: loss 0.33880421824944323\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:33,923\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 49]: loss 0.5692306160926819\u001b[0m\n",
" 98% 49/50 [00:25<00:00, 1.92it/s][\u001b[36m2020-06-28 16:00:34,358\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 50]: loss 0.33721103194432384\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:34,444\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 50]: loss 0.5748363733291626\u001b[0m\n",
"100% 50/50 [00:26<00:00, 1.90it/s]\n",
"[\u001b[36m2020-06-28 16:00:34,448\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/timelag/checkpoint_epoch0050.pth\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:34,450\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - The best loss was 0.47765660285949707\u001b[0m\n",
"+ set +x\n",
"stage 3: Training phoneme duration model\n",
"+ nnsvs-train data.train_no_dev.in_dir=dump/ofuton_p/norm/train_no_dev/in_duration/ data.train_no_dev.out_dir=dump/ofuton_p/norm/train_no_dev/out_duration/ data.dev.in_dir=dump/ofuton_p/norm/dev/in_duration/ data.dev.out_dir=dump/ofuton_p/norm/dev/out_duration/ model=duration train.out_dir=exp/ofuton_p/duration data.batch_size=8 resume.checkpoint=\n",
"[\u001b[36m2020-06-28 16:00:36,126\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - cudnn:\n",
" benchmark: false\n",
" deterministic: false\n",
"data:\n",
" batch_size: 8\n",
" dev:\n",
" in_dir: dump/ofuton_p/norm/dev/in_duration/\n",
" out_dir: dump/ofuton_p/norm/dev/out_duration/\n",
" num_workers: 2\n",
" pin_memory: true\n",
" train_no_dev:\n",
" in_dir: dump/ofuton_p/norm/train_no_dev/in_duration/\n",
" out_dir: dump/ofuton_p/norm/train_no_dev/out_duration/\n",
"model:\n",
" has_dynamic_features:\n",
" - false\n",
" netG:\n",
" class: nnsvs.model.LSTMRNN\n",
" params:\n",
" bidirectional: true\n",
" dropout: 0.5\n",
" hidden_dim: 64\n",
" in_dim: 420\n",
" num_layers: 2\n",
" out_dim: 1\n",
" stream_sizes:\n",
" - 1\n",
" stream_weights:\n",
" - 1\n",
"optim:\n",
" lr_scheduler:\n",
" name: StepLR\n",
" params:\n",
" gamma: 0.5\n",
" step_size: 20\n",
" optimizer:\n",
" name: Adam\n",
" params:\n",
" betas:\n",
" - 0.5\n",
" - 0.999\n",
" lr: 0.001\n",
" weight_decay: 0.0\n",
"resume:\n",
" checkpoint: null\n",
" load_optimizer: false\n",
"train:\n",
" checkpoint_epoch_interval: 20\n",
" nepochs: 50\n",
" out_dir: exp/ofuton_p/duration\n",
" stream_wise_loss: false\n",
"verbose: 100\n",
"\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:00:36,126\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - cudnn.benchmark: False\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:38,982\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 146, 420]), torch.Size([8, 146, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:38,982\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 91, 420]), torch.Size([8, 91, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:38,992\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 37, 420]), torch.Size([8, 37, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:38,995\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 109, 420]), torch.Size([8, 109, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,002\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 52, 420]), torch.Size([8, 52, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,005\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 69, 420]), torch.Size([8, 69, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,011\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 77, 420]), torch.Size([8, 77, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,026\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 114, 420]), torch.Size([8, 114, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,026\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 54, 420]), torch.Size([8, 54, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,045\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 42, 420]), torch.Size([8, 42, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,045\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 44, 420]), torch.Size([8, 44, 1]), torch.Size([8])\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:00:39,064\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 85, 420]), torch.Size([8, 85, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,074\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 41, 420]), torch.Size([8, 41, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,077\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 73, 420]), torch.Size([8, 73, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,091\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 74, 420]), torch.Size([8, 74, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,091\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 44, 420]), torch.Size([8, 44, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,106\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 95, 420]), torch.Size([8, 95, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,107\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 96, 420]), torch.Size([8, 96, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,121\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 76, 420]), torch.Size([8, 76, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,122\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 56, 420]), torch.Size([8, 56, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,132\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 44, 420]), torch.Size([8, 44, 1]), torch.Size([8])\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:00:39,168\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 114, 420]), torch.Size([8, 114, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,171\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 39, 420]), torch.Size([8, 39, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,180\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 46, 420]), torch.Size([8, 46, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,184\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 110, 420]), torch.Size([8, 110, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,213\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 94, 420]), torch.Size([8, 94, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,214\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 53, 420]), torch.Size([8, 53, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,222\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 73, 420]), torch.Size([8, 73, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,222\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 47, 420]), torch.Size([8, 47, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,230\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 72, 420]), torch.Size([8, 72, 1]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,231\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([7, 49, 420]), torch.Size([7, 49, 1]), torch.Size([7])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,320\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([4, 99, 420]), torch.Size([4, 99, 1]), torch.Size([4])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:39,358\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Start utterance-wise training...\u001b[0m\n",
" 0% 0/50 [00:00<?, ?it/s][\u001b[36m2020-06-28 16:00:40,294\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 1]: loss 0.7893602305497879\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:40,385\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 1]: loss 0.5551377534866333\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:40,393\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.5551377534866333: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 2% 1/50 [00:01<00:50, 1.03s/it][\u001b[36m2020-06-28 16:00:41,291\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 2]: loss 0.44769512078700924\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:41,385\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 2]: loss 0.3659795820713043\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:41,394\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.3659795820713043: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 4% 2/50 [00:02<00:49, 1.02s/it][\u001b[36m2020-06-28 16:00:42,308\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 3]: loss 0.2864604508265471\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:42,401\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 3]: loss 0.3221222162246704\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:42,410\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.3221222162246704: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 6% 3/50 [00:03<00:48, 1.02s/it][\u001b[36m2020-06-28 16:00:43,402\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 4]: loss 0.2188294768715516\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:43,494\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 4]: loss 0.28356117010116577\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:43,502\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.28356117010116577: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 8% 4/50 [00:04<00:47, 1.04s/it][\u001b[36m2020-06-28 16:00:44,419\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 5]: loss 0.16854481437267402\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:44,514\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 5]: loss 0.24250537157058716\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:44,523\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.24250537157058716: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 10% 5/50 [00:05<00:46, 1.04s/it][\u001b[36m2020-06-28 16:00:45,422\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 6]: loss 0.12920475827577788\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:45,528\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 6]: loss 0.1996624916791916\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:45,537\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.1996624916791916: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 12% 6/50 [00:06<00:45, 1.03s/it][\u001b[36m2020-06-28 16:00:46,438\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 7]: loss 0.10513140729222542\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:46,530\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 7]: loss 0.15593434870243073\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:46,539\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.15593434870243073: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 14% 7/50 [00:07<00:43, 1.02s/it][\u001b[36m2020-06-28 16:00:47,442\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 8]: loss 0.0881927079306199\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:47,535\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 8]: loss 0.14858749508857727\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:47,544\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.14858749508857727: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 16% 8/50 [00:08<00:42, 1.02s/it][\u001b[36m2020-06-28 16:00:48,464\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 9]: loss 0.08609085778395335\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:48,556\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 9]: loss 0.12414755672216415\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:48,564\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.12414755672216415: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 18% 9/50 [00:09<00:41, 1.02s/it][\u001b[36m2020-06-28 16:00:49,494\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 10]: loss 0.07298835023091389\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:49,593\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 10]: loss 0.1127069741487503\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:49,602\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.1127069741487503: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 20% 10/50 [00:10<00:40, 1.02s/it][\u001b[36m2020-06-28 16:00:50,531\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 11]: loss 0.07079098965877141\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:50,635\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 11]: loss 0.08600255101919174\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:50,646\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.08600255101919174: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 22% 11/50 [00:11<00:40, 1.03s/it][\u001b[36m2020-06-28 16:00:51,596\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 12]: loss 0.06259679507750732\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:51,695\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 12]: loss 0.08884229511022568\u001b[0m\n",
" 24% 12/50 [00:12<00:39, 1.04s/it][\u001b[36m2020-06-28 16:00:52,622\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 13]: loss 0.07036568148013873\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:52,721\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 13]: loss 0.11745447665452957\u001b[0m\n",
" 26% 13/50 [00:13<00:38, 1.03s/it][\u001b[36m2020-06-28 16:00:53,633\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 14]: loss 0.0617066567333845\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:53,732\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 14]: loss 0.09540620446205139\u001b[0m\n",
" 28% 14/50 [00:14<00:36, 1.03s/it][\u001b[36m2020-06-28 16:00:54,649\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 15]: loss 0.057204233148159124\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:54,748\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 15]: loss 0.11233750730752945\u001b[0m\n",
" 30% 15/50 [00:15<00:35, 1.02s/it][\u001b[36m2020-06-28 16:00:55,665\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 16]: loss 0.0534531941685157\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:55,775\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 16]: loss 0.09462113678455353\u001b[0m\n",
" 32% 16/50 [00:16<00:34, 1.02s/it][\u001b[36m2020-06-28 16:00:56,700\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 17]: loss 0.05268562714067789\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:56,806\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 17]: loss 0.07201354950666428\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:56,815\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.07201354950666428: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 34% 17/50 [00:17<00:33, 1.03s/it][\u001b[36m2020-06-28 16:00:57,737\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 18]: loss 0.049918875289268985\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:57,838\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 18]: loss 0.06981083750724792\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:57,847\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.06981083750724792: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 36% 18/50 [00:18<00:32, 1.03s/it][\u001b[36m2020-06-28 16:00:58,776\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 19]: loss 0.047724454496533446\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:58,872\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 19]: loss 0.062374331057071686\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:58,881\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.062374331057071686: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 38% 19/50 [00:19<00:31, 1.03s/it][\u001b[36m2020-06-28 16:00:59,825\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 20]: loss 0.04411990114320547\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:59,922\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 20]: loss 0.05997408181428909\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:59,931\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.05997408181428909: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
"[\u001b[36m2020-06-28 16:00:59,938\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/checkpoint_epoch0020.pth\u001b[0m\n",
" 40% 20/50 [00:20<00:31, 1.04s/it][\u001b[36m2020-06-28 16:01:00,842\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 21]: loss 0.03929724907263731\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:00,936\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 21]: loss 0.05850750207901001\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:00,945\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.05850750207901001: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 42% 21/50 [00:21<00:29, 1.03s/it][\u001b[36m2020-06-28 16:01:01,890\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 22]: loss 0.03802924311886995\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:01,989\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 22]: loss 0.058730240911245346\u001b[0m\n",
" 44% 22/50 [00:22<00:28, 1.03s/it][\u001b[36m2020-06-28 16:01:02,911\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 23]: loss 0.037059047569831215\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:03,006\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 23]: loss 0.06125376373529434\u001b[0m\n",
" 46% 23/50 [00:23<00:27, 1.03s/it][\u001b[36m2020-06-28 16:01:03,915\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 24]: loss 0.034873673119224034\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:04,011\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 24]: loss 0.05991495028138161\u001b[0m\n",
" 48% 24/50 [00:24<00:26, 1.02s/it][\u001b[36m2020-06-28 16:01:04,943\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 25]: loss 0.03410642675291269\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:05,038\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 25]: loss 0.05163317546248436\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:05,047\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 0.05163317546248436: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/best_loss.pth\u001b[0m\n",
" 50% 25/50 [00:25<00:25, 1.03s/it][\u001b[36m2020-06-28 16:01:05,953\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 26]: loss 0.03722425803351097\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:06,048\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 26]: loss 0.07335181534290314\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:07,044\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 27]: loss 0.06877624243497849\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:11,982\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 32]: loss 0.057342082262039185\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:12,988\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 33]: loss 0.06413683295249939\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:13,997\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 34]: loss 0.06952328979969025\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:15,004\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 35]: loss 0.06674788892269135\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:18,009\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 38]: loss 0.05884600430727005\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:19,041\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 39]: loss 0.0545690692961216\u001b[0m\n",
" 78% 39/50 [00:39<00:11, 1.01s/it][\u001b[36m2020-06-28 16:01:19,947\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 40]: loss 0.028092657908415183\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:20,052\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 40]: loss 0.07021024078130722\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:20,060\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/checkpoint_epoch0040.pth\u001b[0m\n",
" 80% 40/50 [00:40<00:10, 1.01s/it][\u001b[36m2020-06-28 16:01:20,999\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 41]: loss 0.02640522892276446\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:28,166\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 48]: loss 0.059377241879701614\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:29,165\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 49]: loss 0.05665117874741554\u001b[0m\n",
" 98% 49/50 [00:49<00:01, 1.01s/it][\u001b[36m2020-06-28 16:01:30,082\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 50]: loss 0.023882144106886327\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:30,183\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 50]: loss 0.05678744986653328\u001b[0m\n",
"100% 50/50 [00:50<00:00, 1.02s/it]\n",
"[\u001b[36m2020-06-28 16:01:30,192\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/duration/checkpoint_epoch0050.pth\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:30,197\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - The best loss was 0.05163317546248436\u001b[0m\n",
"+ set +x\n",
"stage 4: Training acoustic model\n",
"+ nnsvs-train data.train_no_dev.in_dir=dump/ofuton_p/norm/train_no_dev/in_acoustic/ data.train_no_dev.out_dir=dump/ofuton_p/norm/train_no_dev/out_acoustic/ data.dev.in_dir=dump/ofuton_p/norm/dev/in_acoustic/ data.dev.out_dir=dump/ofuton_p/norm/dev/out_acoustic/ model=acoustic train.out_dir=exp/ofuton_p/acoustic data.batch_size=8 resume.checkpoint=\n",
"[\u001b[36m2020-06-28 16:01:31,646\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - cudnn:\n",
" benchmark: false\n",
" deterministic: false\n",
"data:\n",
" batch_size: 8\n",
" dev:\n",
" in_dir: dump/ofuton_p/norm/dev/in_acoustic/\n",
" out_dir: dump/ofuton_p/norm/dev/out_acoustic/\n",
" num_workers: 2\n",
" pin_memory: true\n",
" train_no_dev:\n",
" in_dir: dump/ofuton_p/norm/train_no_dev/in_acoustic/\n",
" out_dir: dump/ofuton_p/norm/train_no_dev/out_acoustic/\n",
"model:\n",
" has_dynamic_features:\n",
" - true\n",
" - true\n",
" - false\n",
" - true\n",
" netG:\n",
" class: nnsvs.model.Conv1dResnet\n",
" params:\n",
" dropout: 0.1\n",
" hidden_dim: 128\n",
" in_dim: 424\n",
" num_layers: 6\n",
" out_dim: 199\n",
" num_windows: 3\n",
" stream_sizes:\n",
" - 180\n",
" - 3\n",
" - 1\n",
" - 15\n",
" stream_weights: null\n",
"optim:\n",
" lr_scheduler:\n",
" name: StepLR\n",
" params:\n",
" gamma: 0.5\n",
" step_size: 20\n",
" optimizer:\n",
" name: Adam\n",
" params:\n",
" betas:\n",
" - 0.5\n",
" - 0.999\n",
" lr: 0.001\n",
" weight_decay: 0.0\n",
"resume:\n",
" checkpoint: null\n",
" load_optimizer: false\n",
"train:\n",
" checkpoint_epoch_interval: 20\n",
" nepochs: 50\n",
" out_dir: exp/ofuton_p/acoustic\n",
" stream_wise_loss: false\n",
"verbose: 100\n",
"\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:31,646\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - cudnn.benchmark: False\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:34,781\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 1820, 424]), torch.Size([8, 1820, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:34,880\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 3073, 424]), torch.Size([8, 3073, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:35,313\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 4282, 424]), torch.Size([8, 4282, 199]), torch.Size([8])\u001b[0m\n",
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"[\u001b[36m2020-06-28 16:01:38,332\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 4074, 424]), torch.Size([8, 4074, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:39,078\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 10513, 424]), torch.Size([8, 10513, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:39,079\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 3319, 424]), torch.Size([8, 3319, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:40,486\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 3116, 424]), torch.Size([8, 3116, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:40,487\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2883, 424]), torch.Size([8, 2883, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:41,435\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 1921, 424]), torch.Size([8, 1921, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:41,435\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2819, 424]), torch.Size([8, 2819, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:42,907\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 3525, 424]), torch.Size([8, 3525, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:42,907\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2226, 424]), torch.Size([8, 2226, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:44,263\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2670, 424]), torch.Size([8, 2670, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:44,263\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2719, 424]), torch.Size([8, 2719, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:46,300\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 3682, 424]), torch.Size([8, 3682, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:46,513\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 8449, 424]), torch.Size([8, 8449, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:48,097\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 3638, 424]), torch.Size([8, 3638, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:48,136\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 4323, 424]), torch.Size([8, 4323, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:49,348\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2228, 424]), torch.Size([8, 2228, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:49,549\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2558, 424]), torch.Size([8, 2558, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:50,693\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 3128, 424]), torch.Size([8, 3128, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:51,066\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2807, 424]), torch.Size([8, 2807, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:52,897\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 7529, 424]), torch.Size([8, 7529, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:52,897\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2238, 424]), torch.Size([8, 2238, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:54,456\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 1831, 424]), torch.Size([8, 1831, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:54,743\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 4074, 424]), torch.Size([8, 4074, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:55,541\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2250, 424]), torch.Size([8, 2250, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:56,521\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 3751, 424]), torch.Size([8, 3751, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:57,268\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([8, 2757, 424]), torch.Size([8, 2757, 199]), torch.Size([8])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:57,635\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([7, 2729, 424]), torch.Size([7, 2729, 199]), torch.Size([7])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:57,844\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - torch.Size([4, 4240, 424]), torch.Size([4, 4240, 199]), torch.Size([4])\u001b[0m\n",
"[\u001b[36m2020-06-28 16:01:57,881\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Start utterance-wise training...\u001b[0m\n",
" 0% 0/50 [00:00<?, ?it/s][\u001b[36m2020-06-28 16:02:13,494\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 1]: loss 0.9730821328285413\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:13,973\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 1]: loss 1.3360713720321655\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:13,995\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.3360713720321655: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 2% 1/50 [00:16<13:09, 16.11s/it][\u001b[36m2020-06-28 16:02:22,233\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 2]: loss 0.9371264974276224\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:22,518\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 2]: loss 1.3328170776367188\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:22,543\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.3328170776367188: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 4% 2/50 [00:24<11:04, 13.84s/it][\u001b[36m2020-06-28 16:02:30,950\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 3]: loss 0.9299546403762622\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:31,236\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 3]: loss 1.3265281915664673\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:31,261\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.3265281915664673: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 6% 3/50 [00:33<09:38, 12.30s/it][\u001b[36m2020-06-28 16:02:39,259\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 4]: loss 0.9284112484027178\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:39,546\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 4]: loss 1.3239598274230957\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:39,576\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.3239598274230957: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 8% 4/50 [00:41<08:30, 11.11s/it][\u001b[36m2020-06-28 16:02:47,788\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 5]: loss 0.9264073020372635\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:48,071\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 5]: loss 1.3199527263641357\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:48,096\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.3199527263641357: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 10% 5/50 [00:50<07:44, 10.33s/it][\u001b[36m2020-06-28 16:02:55,982\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 6]: loss 0.9248234920012646\u001b[0m\n",
"[\u001b[36m2020-06-28 16:02:56,268\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 6]: loss 1.3237388134002686\u001b[0m\n",
" 12% 6/50 [00:58<07:06, 9.68s/it][\u001b[36m2020-06-28 16:03:04,099\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 7]: loss 0.9254452815422645\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:04,394\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 7]: loss 1.320690631866455\u001b[0m\n",
" 14% 7/50 [01:06<06:36, 9.22s/it][\u001b[36m2020-06-28 16:03:12,237\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 8]: loss 0.9170629611382117\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:12,530\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 8]: loss 1.3104521036148071\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:12,554\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.3104521036148071: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 16% 8/50 [01:14<06:13, 8.90s/it][\u001b[36m2020-06-28 16:03:20,564\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 9]: loss 0.9150652671471621\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:20,856\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 9]: loss 1.3129819631576538\u001b[0m\n",
" 18% 9/50 [01:22<05:57, 8.72s/it][\u001b[36m2020-06-28 16:03:28,565\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 10]: loss 0.9109955781545395\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:28,861\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 10]: loss 1.315433382987976\u001b[0m\n",
" 20% 10/50 [01:30<05:40, 8.51s/it][\u001b[36m2020-06-28 16:03:36,926\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 11]: loss 0.9116371136445266\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:37,216\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 11]: loss 1.3102811574935913\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:37,245\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.3102811574935913: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 22% 11/50 [01:39<05:30, 8.47s/it][\u001b[36m2020-06-28 16:03:45,284\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 12]: loss 0.9134743595734621\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:45,571\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 12]: loss 1.3116958141326904\u001b[0m\n",
" 24% 12/50 [01:47<05:20, 8.43s/it][\u001b[36m2020-06-28 16:03:53,517\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 13]: loss 0.9118199929212912\u001b[0m\n",
"[\u001b[36m2020-06-28 16:03:53,805\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 13]: loss 1.3133529424667358\u001b[0m\n",
" 26% 13/50 [01:55<05:09, 8.37s/it][\u001b[36m2020-06-28 16:04:02,195\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 14]: loss 0.9068477535859133\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:02,482\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 14]: loss 1.310837984085083\u001b[0m\n",
" 28% 14/50 [02:04<05:04, 8.46s/it][\u001b[36m2020-06-28 16:04:10,325\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 15]: loss 0.908034683802189\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:10,611\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 15]: loss 1.300913691520691\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:10,638\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.300913691520691: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 30% 15/50 [02:12<04:52, 8.37s/it][\u001b[36m2020-06-28 16:04:18,631\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 16]: loss 0.9044079169248923\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:18,930\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 16]: loss 1.3043524026870728\u001b[0m\n",
" 32% 16/50 [02:21<04:43, 8.35s/it][\u001b[36m2020-06-28 16:04:26,788\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 17]: loss 0.9022238758894113\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:27,079\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 17]: loss 1.3043022155761719\u001b[0m\n",
" 34% 17/50 [02:29<04:33, 8.29s/it][\u001b[36m2020-06-28 16:04:35,193\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 18]: loss 0.9019133784832098\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:35,488\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 18]: loss 1.3003778457641602\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:35,514\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.3003778457641602: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 36% 18/50 [02:37<04:26, 8.33s/it][\u001b[36m2020-06-28 16:04:43,654\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 19]: loss 0.9006432814475818\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:43,953\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 19]: loss 1.3155581951141357\u001b[0m\n",
" 38% 19/50 [02:46<04:19, 8.36s/it][\u001b[36m2020-06-28 16:04:52,183\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 20]: loss 0.9006762993641388\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:52,481\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 20]: loss 1.3191540241241455\u001b[0m\n",
"[\u001b[36m2020-06-28 16:04:52,506\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/checkpoint_epoch0020.pth\u001b[0m\n",
" 40% 20/50 [02:54<04:12, 8.42s/it][\u001b[36m2020-06-28 16:05:00,421\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 21]: loss 0.8965625396141639\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:00,713\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 21]: loss 1.2991719245910645\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:00,740\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.2991719245910645: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 42% 21/50 [03:02<04:02, 8.36s/it][\u001b[36m2020-06-28 16:05:08,681\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 22]: loss 0.8940858810375898\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:08,967\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 22]: loss 1.2986249923706055\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:08,993\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.2986249923706055: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 44% 22/50 [03:11<03:53, 8.33s/it][\u001b[36m2020-06-28 16:05:16,963\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 23]: loss 0.8922415880056528\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:17,246\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 23]: loss 1.2960630655288696\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:17,274\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.2960630655288696: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 46% 23/50 [03:19<03:44, 8.32s/it][\u001b[36m2020-06-28 16:05:25,138\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 24]: loss 0.8930388536208715\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:25,424\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 24]: loss 1.2993806600570679\u001b[0m\n",
" 48% 24/50 [03:27<03:34, 8.27s/it][\u001b[36m2020-06-28 16:05:33,466\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 25]: loss 0.891362074093941\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:33,753\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 25]: loss 1.2982372045516968\u001b[0m\n",
" 50% 25/50 [03:35<03:27, 8.29s/it][\u001b[36m2020-06-28 16:05:41,567\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 26]: loss 0.8902617998612232\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:41,863\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 26]: loss 1.2988324165344238\u001b[0m\n",
" 52% 26/50 [03:43<03:17, 8.23s/it][\u001b[36m2020-06-28 16:05:49,868\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 27]: loss 0.8913056269670144\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:50,155\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 27]: loss 1.296610951423645\u001b[0m\n",
" 54% 27/50 [03:52<03:09, 8.25s/it][\u001b[36m2020-06-28 16:05:57,906\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 28]: loss 0.8901863082861289\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:58,196\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 28]: loss 1.293143630027771\u001b[0m\n",
"[\u001b[36m2020-06-28 16:05:58,224\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.293143630027771: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 56% 28/50 [04:00<03:00, 8.20s/it][\u001b[36m2020-06-28 16:06:06,268\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 29]: loss 0.8901309325144842\u001b[0m\n",
"[\u001b[36m2020-06-28 16:06:06,552\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 29]: loss 1.3021363019943237\u001b[0m\n",
" 58% 29/50 [04:08<02:52, 8.24s/it][\u001b[36m2020-06-28 16:06:14,360\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 30]: loss 0.89155135399256\u001b[0m\n",
"[\u001b[36m2020-06-28 16:06:14,651\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 30]: loss 1.2975348234176636\u001b[0m\n",
" 60% 30/50 [04:16<02:43, 8.19s/it][\u001b[36m2020-06-28 16:06:22,530\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 31]: loss 0.888202387552995\u001b[0m\n",
"[\u001b[36m2020-06-28 16:06:22,808\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 31]: loss 1.2962653636932373\u001b[0m\n",
" 62% 31/50 [04:24<02:35, 8.18s/it][\u001b[36m2020-06-28 16:06:30,612\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 32]: loss 0.8870242986923609\u001b[0m\n",
"[\u001b[36m2020-06-28 16:06:30,896\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 32]: loss 1.3019574880599976\u001b[0m\n",
" 64% 32/50 [04:33<02:26, 8.15s/it][\u001b[36m2020-06-28 16:06:38,762\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 33]: loss 0.8873790915195758\u001b[0m\n",
"[\u001b[36m2020-06-28 16:06:39,045\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 33]: loss 1.2969142198562622\u001b[0m\n",
" 66% 33/50 [04:41<02:18, 8.15s/it][\u001b[36m2020-06-28 16:06:47,029\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 34]: loss 0.8865961218491579\u001b[0m\n",
"[\u001b[36m2020-06-28 16:06:47,322\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 34]: loss 1.29703688621521\u001b[0m\n",
" 68% 34/50 [04:49<02:11, 8.19s/it][\u001b[36m2020-06-28 16:06:55,210\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 35]: loss 0.8867124640024625\u001b[0m\n",
"[\u001b[36m2020-06-28 16:06:55,496\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 35]: loss 1.293186902999878\u001b[0m\n",
" 70% 35/50 [04:57<02:02, 8.19s/it][\u001b[36m2020-06-28 16:07:03,623\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 36]: loss 0.8874195707149994\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:03,915\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 36]: loss 1.2962807416915894\u001b[0m\n",
" 72% 36/50 [05:06<01:55, 8.26s/it][\u001b[36m2020-06-28 16:07:11,767\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 37]: loss 0.8849135209352542\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:12,055\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 37]: loss 1.2947921752929688\u001b[0m\n",
" 74% 37/50 [05:14<01:46, 8.22s/it][\u001b[36m2020-06-28 16:07:20,086\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 38]: loss 0.885059498823606\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:20,373\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 38]: loss 1.3008335828781128\u001b[0m\n",
" 76% 38/50 [05:22<01:38, 8.25s/it][\u001b[36m2020-06-28 16:07:28,431\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 39]: loss 0.8823877542446821\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:28,719\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 39]: loss 1.2948994636535645\u001b[0m\n",
" 78% 39/50 [05:30<01:31, 8.28s/it][\u001b[36m2020-06-28 16:07:36,532\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 40]: loss 0.8851539477323874\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:36,825\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 40]: loss 1.2924460172653198\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:36,852\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.2924460172653198: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:36,875\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/checkpoint_epoch0040.pth\u001b[0m\n",
" 80% 40/50 [05:39<01:22, 8.25s/it][\u001b[36m2020-06-28 16:07:44,740\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 41]: loss 0.882985056974949\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:45,025\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 41]: loss 1.2935642004013062\u001b[0m\n",
" 82% 41/50 [05:47<01:13, 8.21s/it][\u001b[36m2020-06-28 16:07:52,634\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 42]: loss 0.878272261375036\u001b[0m\n",
"[\u001b[36m2020-06-28 16:07:52,924\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 42]: loss 1.2949244976043701\u001b[0m\n",
" 84% 42/50 [05:55<01:04, 8.12s/it][\u001b[36m2020-06-28 16:08:00,670\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 43]: loss 0.8801607183921032\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:00,954\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 43]: loss 1.2903530597686768\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:00,982\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.2903530597686768: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 86% 43/50 [06:03<00:56, 8.10s/it][\u001b[36m2020-06-28 16:08:09,018\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 44]: loss 0.8791994009262476\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:09,307\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 44]: loss 1.2930080890655518\u001b[0m\n",
" 88% 44/50 [06:11<00:49, 8.17s/it][\u001b[36m2020-06-28 16:08:17,338\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 45]: loss 0.8788928160300622\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:17,625\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 45]: loss 1.2901395559310913\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:17,656\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [Best loss 1.2901395559310913: checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/best_loss.pth\u001b[0m\n",
" 90% 45/50 [06:19<00:41, 8.22s/it][\u001b[36m2020-06-28 16:08:25,557\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 46]: loss 0.878524552553128\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:25,847\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 46]: loss 1.297964096069336\u001b[0m\n",
" 92% 46/50 [06:27<00:32, 8.21s/it][\u001b[36m2020-06-28 16:08:33,679\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 47]: loss 0.8782817339285826\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:33,970\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 47]: loss 1.2918516397476196\u001b[0m\n",
" 94% 47/50 [06:36<00:24, 8.19s/it][\u001b[36m2020-06-28 16:08:41,904\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 48]: loss 0.8768784312101511\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:42,200\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 48]: loss 1.2930206060409546\u001b[0m\n",
" 96% 48/50 [06:44<00:16, 8.20s/it][\u001b[36m2020-06-28 16:08:49,744\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 49]: loss 0.8763432273497949\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:50,035\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 49]: loss 1.2906670570373535\u001b[0m\n",
" 98% 49/50 [06:52<00:08, 8.09s/it][\u001b[36m2020-06-28 16:08:57,661\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [train_no_dev] [Epoch 50]: loss 0.8758722161635374\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:57,957\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - [dev] [Epoch 50]: loss 1.2948033809661865\u001b[0m\n",
"100% 50/50 [07:00<00:00, 8.40s/it]\n",
"[\u001b[36m2020-06-28 16:08:57,982\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Checkpoint is saved at /content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/acoustic/checkpoint_epoch0050.pth\u001b[0m\n",
"[\u001b[36m2020-06-28 16:08:57,997\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - The best loss was 1.2901395559310913\u001b[0m\n",
"+ set +x\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "YnPWRwTgqUhg",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "cf341f37-1cd7-4d5f-8fed-f26983f49bcf"
},
"source": [
"! cd $RECIPE_ROOT && bash run.sh --stage 5 --stop-stage 6"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"stage 5: Generation features from timelag/duration/acoustic models\n",
"+ nnsvs-generate model.checkpoint=exp/ofuton_p/timelag/latest.pth model.model_yaml=exp/ofuton_p/timelag/model.yaml out_scaler_path=dump/ofuton_p/norm/out_timelag_scaler.joblib in_dir=dump/ofuton_p/norm/dev/in_timelag/ out_dir=exp/ofuton_p/timelag/predicted/dev/latest/\n",
"[\u001b[36m2020-06-28 16:09:56,551\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/norm/dev/in_timelag/\n",
"model:\n",
" checkpoint: exp/ofuton_p/timelag/latest.pth\n",
" model_yaml: exp/ofuton_p/timelag/model.yaml\n",
"out_dir: exp/ofuton_p/timelag/predicted/dev/latest/\n",
"out_scaler_path: dump/ofuton_p/norm/out_timelag_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 339.50it/s]\n",
"+ set +x\n",
"+ nnsvs-generate model.checkpoint=exp/ofuton_p/duration/latest.pth model.model_yaml=exp/ofuton_p/duration/model.yaml out_scaler_path=dump/ofuton_p/norm/out_duration_scaler.joblib in_dir=dump/ofuton_p/norm/dev/in_duration/ out_dir=exp/ofuton_p/duration/predicted/dev/latest/\n",
"[\u001b[36m2020-06-28 16:10:01,221\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/norm/dev/in_duration/\n",
"model:\n",
" checkpoint: exp/ofuton_p/duration/latest.pth\n",
" model_yaml: exp/ofuton_p/duration/model.yaml\n",
"out_dir: exp/ofuton_p/duration/predicted/dev/latest/\n",
"out_scaler_path: dump/ofuton_p/norm/out_duration_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 81.04it/s]\n",
"+ set +x\n",
"+ nnsvs-generate model.checkpoint=exp/ofuton_p/acoustic/latest.pth model.model_yaml=exp/ofuton_p/acoustic/model.yaml out_scaler_path=dump/ofuton_p/norm/out_acoustic_scaler.joblib in_dir=dump/ofuton_p/norm/dev/in_acoustic/ out_dir=exp/ofuton_p/acoustic/predicted/dev/latest/\n",
"[\u001b[36m2020-06-28 16:10:05,959\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/norm/dev/in_acoustic/\n",
"model:\n",
" checkpoint: exp/ofuton_p/acoustic/latest.pth\n",
" model_yaml: exp/ofuton_p/acoustic/model.yaml\n",
"out_dir: exp/ofuton_p/acoustic/predicted/dev/latest/\n",
"out_scaler_path: dump/ofuton_p/norm/out_acoustic_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 4/4 [00:00<00:00, 28.02it/s]\n",
"+ set +x\n",
"+ nnsvs-generate model.checkpoint=exp/ofuton_p/timelag/latest.pth model.model_yaml=exp/ofuton_p/timelag/model.yaml out_scaler_path=dump/ofuton_p/norm/out_timelag_scaler.joblib in_dir=dump/ofuton_p/norm/eval/in_timelag/ out_dir=exp/ofuton_p/timelag/predicted/eval/latest/\n",
"[\u001b[36m2020-06-28 16:10:10,701\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/norm/eval/in_timelag/\n",
"model:\n",
" checkpoint: exp/ofuton_p/timelag/latest.pth\n",
" model_yaml: exp/ofuton_p/timelag/model.yaml\n",
"out_dir: exp/ofuton_p/timelag/predicted/eval/latest/\n",
"out_scaler_path: dump/ofuton_p/norm/out_timelag_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 640.66it/s]\n",
"+ set +x\n",
"+ nnsvs-generate model.checkpoint=exp/ofuton_p/duration/latest.pth model.model_yaml=exp/ofuton_p/duration/model.yaml out_scaler_path=dump/ofuton_p/norm/out_duration_scaler.joblib in_dir=dump/ofuton_p/norm/eval/in_duration/ out_dir=exp/ofuton_p/duration/predicted/eval/latest/\n",
"[\u001b[36m2020-06-28 16:10:15,326\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/norm/eval/in_duration/\n",
"model:\n",
" checkpoint: exp/ofuton_p/duration/latest.pth\n",
" model_yaml: exp/ofuton_p/duration/model.yaml\n",
"out_dir: exp/ofuton_p/duration/predicted/eval/latest/\n",
"out_scaler_path: dump/ofuton_p/norm/out_duration_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 157.66it/s]\n",
"+ set +x\n",
"+ nnsvs-generate model.checkpoint=exp/ofuton_p/acoustic/latest.pth model.model_yaml=exp/ofuton_p/acoustic/model.yaml out_scaler_path=dump/ofuton_p/norm/out_acoustic_scaler.joblib in_dir=dump/ofuton_p/norm/eval/in_acoustic/ out_dir=exp/ofuton_p/acoustic/predicted/eval/latest/\n",
"[\u001b[36m2020-06-28 16:10:19,966\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - in_dir: dump/ofuton_p/norm/eval/in_acoustic/\n",
"model:\n",
" checkpoint: exp/ofuton_p/acoustic/latest.pth\n",
" model_yaml: exp/ofuton_p/acoustic/model.yaml\n",
"out_dir: exp/ofuton_p/acoustic/predicted/eval/latest/\n",
"out_scaler_path: dump/ofuton_p/norm/out_acoustic_scaler.joblib\n",
"verbose: 100\n",
"\u001b[0m\n",
"100% 6/6 [00:00<00:00, 10.79it/s]\n",
"+ set +x\n",
"stage 6: Synthesis waveforms\n",
"+ nnsvs-synthesis question_path=conf/jp_qst001_nnsvs.hed timelag.checkpoint=exp/ofuton_p/timelag/latest.pth timelag.in_scaler_path=dump/ofuton_p/norm/in_timelag_scaler.joblib timelag.out_scaler_path=dump/ofuton_p/norm/out_timelag_scaler.joblib timelag.model_yaml=exp/ofuton_p/timelag/model.yaml duration.checkpoint=exp/ofuton_p/duration/latest.pth duration.in_scaler_path=dump/ofuton_p/norm/in_duration_scaler.joblib duration.out_scaler_path=dump/ofuton_p/norm/out_duration_scaler.joblib duration.model_yaml=exp/ofuton_p/duration/model.yaml acoustic.checkpoint=exp/ofuton_p/acoustic/latest.pth acoustic.in_scaler_path=dump/ofuton_p/norm/in_acoustic_scaler.joblib acoustic.out_scaler_path=dump/ofuton_p/norm/out_acoustic_scaler.joblib acoustic.model_yaml=exp/ofuton_p/acoustic/model.yaml utt_list=./data/list/dev.list in_dir=data/acoustic/label_phone_score/ out_dir=exp/ofuton_p/synthesis/dev/latest/label_phone_score ground_truth_duration=false\n",
"[\u001b[36m2020-06-28 16:10:25,189\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - acoustic:\n",
" checkpoint: exp/ofuton_p/acoustic/latest.pth\n",
" has_dynamic_features:\n",
" - true\n",
" - true\n",
" - false\n",
" - true\n",
" in_scaler_path: dump/ofuton_p/norm/in_acoustic_scaler.joblib\n",
" model_yaml: exp/ofuton_p/acoustic/model.yaml\n",
" num_windows: 3\n",
" out_scaler_path: dump/ofuton_p/norm/out_acoustic_scaler.joblib\n",
" post_filter: true\n",
" question_path: null\n",
" relative_f0: true\n",
" stream_sizes:\n",
" - 180\n",
" - 3\n",
" - 1\n",
" - 15\n",
" subphone_features: coarse_coding\n",
"device: cuda\n",
"duration:\n",
" checkpoint: exp/ofuton_p/duration/latest.pth\n",
" has_dynamic_features:\n",
" - false\n",
" in_scaler_path: dump/ofuton_p/norm/in_duration_scaler.joblib\n",
" model_yaml: exp/ofuton_p/duration/model.yaml\n",
" out_scaler_path: dump/ofuton_p/norm/out_duration_scaler.joblib\n",
" question_path: null\n",
" stream_sizes:\n",
" - 1\n",
"frame_period: 5\n",
"ground_truth_duration: false\n",
"in_dir: data/acoustic/label_phone_score/\n",
"label_path: null\n",
"log_f0_conditioning: true\n",
"out_dir: exp/ofuton_p/synthesis/dev/latest/label_phone_score\n",
"out_wav_path: null\n",
"question_path: conf/jp_qst001_nnsvs.hed\n",
"sample_rate: 48000\n",
"timelag:\n",
" allowed_range:\n",
" - -20\n",
" - 20\n",
" allowed_range_rest:\n",
" - -40\n",
" - 40\n",
" checkpoint: exp/ofuton_p/timelag/latest.pth\n",
" has_dynamic_features:\n",
" - false\n",
" in_scaler_path: dump/ofuton_p/norm/in_timelag_scaler.joblib\n",
" model_yaml: exp/ofuton_p/timelag/model.yaml\n",
" out_scaler_path: dump/ofuton_p/norm/out_timelag_scaler.joblib\n",
" question_path: null\n",
" stream_sizes:\n",
" - 1\n",
"utt_list: ./data/list/dev.list\n",
"verbose: 100\n",
"\u001b[0m\n",
"[\u001b[36m2020-06-28 16:10:28,038\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Processes 4 utterances...\u001b[0m\n",
"100% 4/4 [00:15<00:00, 3.95s/it]\n",
"+ set +x\n",
"+ nnsvs-synthesis question_path=conf/jp_qst001_nnsvs.hed timelag.checkpoint=exp/ofuton_p/timelag/latest.pth timelag.in_scaler_path=dump/ofuton_p/norm/in_timelag_scaler.joblib timelag.out_scaler_path=dump/ofuton_p/norm/out_timelag_scaler.joblib timelag.model_yaml=exp/ofuton_p/timelag/model.yaml duration.checkpoint=exp/ofuton_p/duration/latest.pth duration.in_scaler_path=dump/ofuton_p/norm/in_duration_scaler.joblib duration.out_scaler_path=dump/ofuton_p/norm/out_duration_scaler.joblib duration.model_yaml=exp/ofuton_p/duration/model.yaml acoustic.checkpoint=exp/ofuton_p/acoustic/latest.pth acoustic.in_scaler_path=dump/ofuton_p/norm/in_acoustic_scaler.joblib acoustic.out_scaler_path=dump/ofuton_p/norm/out_acoustic_scaler.joblib acoustic.model_yaml=exp/ofuton_p/acoustic/model.yaml utt_list=./data/list/dev.list in_dir=data/acoustic/label_phone_align/ out_dir=exp/ofuton_p/synthesis/dev/latest/label_phone_align ground_truth_duration=true\n",
"[\u001b[36m2020-06-28 16:10:45,611\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - acoustic:\n",
" checkpoint: exp/ofuton_p/acoustic/latest.pth\n",
" has_dynamic_features:\n",
" - true\n",
" - true\n",
" - false\n",
" - true\n",
" in_scaler_path: dump/ofuton_p/norm/in_acoustic_scaler.joblib\n",
" model_yaml: exp/ofuton_p/acoustic/model.yaml\n",
" num_windows: 3\n",
" out_scaler_path: dump/ofuton_p/norm/out_acoustic_scaler.joblib\n",
" post_filter: true\n",
" question_path: null\n",
" relative_f0: true\n",
" stream_sizes:\n",
" - 180\n",
" - 3\n",
" - 1\n",
" - 15\n",
" subphone_features: coarse_coding\n",
"device: cuda\n",
"duration:\n",
" checkpoint: exp/ofuton_p/duration/latest.pth\n",
" has_dynamic_features:\n",
" - false\n",
" in_scaler_path: dump/ofuton_p/norm/in_duration_scaler.joblib\n",
" model_yaml: exp/ofuton_p/duration/model.yaml\n",
" out_scaler_path: dump/ofuton_p/norm/out_duration_scaler.joblib\n",
" question_path: null\n",
" stream_sizes:\n",
" - 1\n",
"frame_period: 5\n",
"ground_truth_duration: true\n",
"in_dir: data/acoustic/label_phone_align/\n",
"label_path: null\n",
"log_f0_conditioning: true\n",
"out_dir: exp/ofuton_p/synthesis/dev/latest/label_phone_align\n",
"out_wav_path: null\n",
"question_path: conf/jp_qst001_nnsvs.hed\n",
"sample_rate: 48000\n",
"timelag:\n",
" allowed_range:\n",
" - -20\n",
" - 20\n",
" allowed_range_rest:\n",
" - -40\n",
" - 40\n",
" checkpoint: exp/ofuton_p/timelag/latest.pth\n",
" has_dynamic_features:\n",
" - false\n",
" in_scaler_path: dump/ofuton_p/norm/in_timelag_scaler.joblib\n",
" model_yaml: exp/ofuton_p/timelag/model.yaml\n",
" out_scaler_path: dump/ofuton_p/norm/out_timelag_scaler.joblib\n",
" question_path: null\n",
" stream_sizes:\n",
" - 1\n",
"utt_list: ./data/list/dev.list\n",
"verbose: 100\n",
"\u001b[0m\n",
"[\u001b[36m2020-06-28 16:10:48,444\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Processes 4 utterances...\u001b[0m\n",
"100% 4/4 [00:16<00:00, 4.04s/it]\n",
"+ set +x\n",
"+ nnsvs-synthesis question_path=conf/jp_qst001_nnsvs.hed timelag.checkpoint=exp/ofuton_p/timelag/latest.pth timelag.in_scaler_path=dump/ofuton_p/norm/in_timelag_scaler.joblib timelag.out_scaler_path=dump/ofuton_p/norm/out_timelag_scaler.joblib timelag.model_yaml=exp/ofuton_p/timelag/model.yaml duration.checkpoint=exp/ofuton_p/duration/latest.pth duration.in_scaler_path=dump/ofuton_p/norm/in_duration_scaler.joblib duration.out_scaler_path=dump/ofuton_p/norm/out_duration_scaler.joblib duration.model_yaml=exp/ofuton_p/duration/model.yaml acoustic.checkpoint=exp/ofuton_p/acoustic/latest.pth acoustic.in_scaler_path=dump/ofuton_p/norm/in_acoustic_scaler.joblib acoustic.out_scaler_path=dump/ofuton_p/norm/out_acoustic_scaler.joblib acoustic.model_yaml=exp/ofuton_p/acoustic/model.yaml utt_list=./data/list/eval.list in_dir=data/acoustic/label_phone_score/ out_dir=exp/ofuton_p/synthesis/eval/latest/label_phone_score ground_truth_duration=false\n",
"[\u001b[36m2020-06-28 16:11:06,368\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - acoustic:\n",
" checkpoint: exp/ofuton_p/acoustic/latest.pth\n",
" has_dynamic_features:\n",
" - true\n",
" - true\n",
" - false\n",
" - true\n",
" in_scaler_path: dump/ofuton_p/norm/in_acoustic_scaler.joblib\n",
" model_yaml: exp/ofuton_p/acoustic/model.yaml\n",
" num_windows: 3\n",
" out_scaler_path: dump/ofuton_p/norm/out_acoustic_scaler.joblib\n",
" post_filter: true\n",
" question_path: null\n",
" relative_f0: true\n",
" stream_sizes:\n",
" - 180\n",
" - 3\n",
" - 1\n",
" - 15\n",
" subphone_features: coarse_coding\n",
"device: cuda\n",
"duration:\n",
" checkpoint: exp/ofuton_p/duration/latest.pth\n",
" has_dynamic_features:\n",
" - false\n",
" in_scaler_path: dump/ofuton_p/norm/in_duration_scaler.joblib\n",
" model_yaml: exp/ofuton_p/duration/model.yaml\n",
" out_scaler_path: dump/ofuton_p/norm/out_duration_scaler.joblib\n",
" question_path: null\n",
" stream_sizes:\n",
" - 1\n",
"frame_period: 5\n",
"ground_truth_duration: false\n",
"in_dir: data/acoustic/label_phone_score/\n",
"label_path: null\n",
"log_f0_conditioning: true\n",
"out_dir: exp/ofuton_p/synthesis/eval/latest/label_phone_score\n",
"out_wav_path: null\n",
"question_path: conf/jp_qst001_nnsvs.hed\n",
"sample_rate: 48000\n",
"timelag:\n",
" allowed_range:\n",
" - -20\n",
" - 20\n",
" allowed_range_rest:\n",
" - -40\n",
" - 40\n",
" checkpoint: exp/ofuton_p/timelag/latest.pth\n",
" has_dynamic_features:\n",
" - false\n",
" in_scaler_path: dump/ofuton_p/norm/in_timelag_scaler.joblib\n",
" model_yaml: exp/ofuton_p/timelag/model.yaml\n",
" out_scaler_path: dump/ofuton_p/norm/out_timelag_scaler.joblib\n",
" question_path: null\n",
" stream_sizes:\n",
" - 1\n",
"utt_list: ./data/list/eval.list\n",
"verbose: 100\n",
"\u001b[0m\n",
"[\u001b[36m2020-06-28 16:11:09,195\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Processes 6 utterances...\u001b[0m\n",
"100% 6/6 [00:23<00:00, 3.99s/it]\n",
"+ set +x\n",
"+ nnsvs-synthesis question_path=conf/jp_qst001_nnsvs.hed timelag.checkpoint=exp/ofuton_p/timelag/latest.pth timelag.in_scaler_path=dump/ofuton_p/norm/in_timelag_scaler.joblib timelag.out_scaler_path=dump/ofuton_p/norm/out_timelag_scaler.joblib timelag.model_yaml=exp/ofuton_p/timelag/model.yaml duration.checkpoint=exp/ofuton_p/duration/latest.pth duration.in_scaler_path=dump/ofuton_p/norm/in_duration_scaler.joblib duration.out_scaler_path=dump/ofuton_p/norm/out_duration_scaler.joblib duration.model_yaml=exp/ofuton_p/duration/model.yaml acoustic.checkpoint=exp/ofuton_p/acoustic/latest.pth acoustic.in_scaler_path=dump/ofuton_p/norm/in_acoustic_scaler.joblib acoustic.out_scaler_path=dump/ofuton_p/norm/out_acoustic_scaler.joblib acoustic.model_yaml=exp/ofuton_p/acoustic/model.yaml utt_list=./data/list/eval.list in_dir=data/acoustic/label_phone_align/ out_dir=exp/ofuton_p/synthesis/eval/latest/label_phone_align ground_truth_duration=true\n",
"[\u001b[36m2020-06-28 16:11:34,919\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - acoustic:\n",
" checkpoint: exp/ofuton_p/acoustic/latest.pth\n",
" has_dynamic_features:\n",
" - true\n",
" - true\n",
" - false\n",
" - true\n",
" in_scaler_path: dump/ofuton_p/norm/in_acoustic_scaler.joblib\n",
" model_yaml: exp/ofuton_p/acoustic/model.yaml\n",
" num_windows: 3\n",
" out_scaler_path: dump/ofuton_p/norm/out_acoustic_scaler.joblib\n",
" post_filter: true\n",
" question_path: null\n",
" relative_f0: true\n",
" stream_sizes:\n",
" - 180\n",
" - 3\n",
" - 1\n",
" - 15\n",
" subphone_features: coarse_coding\n",
"device: cuda\n",
"duration:\n",
" checkpoint: exp/ofuton_p/duration/latest.pth\n",
" has_dynamic_features:\n",
" - false\n",
" in_scaler_path: dump/ofuton_p/norm/in_duration_scaler.joblib\n",
" model_yaml: exp/ofuton_p/duration/model.yaml\n",
" out_scaler_path: dump/ofuton_p/norm/out_duration_scaler.joblib\n",
" question_path: null\n",
" stream_sizes:\n",
" - 1\n",
"frame_period: 5\n",
"ground_truth_duration: true\n",
"in_dir: data/acoustic/label_phone_align/\n",
"label_path: null\n",
"log_f0_conditioning: true\n",
"out_dir: exp/ofuton_p/synthesis/eval/latest/label_phone_align\n",
"out_wav_path: null\n",
"question_path: conf/jp_qst001_nnsvs.hed\n",
"sample_rate: 48000\n",
"timelag:\n",
" allowed_range:\n",
" - -20\n",
" - 20\n",
" allowed_range_rest:\n",
" - -40\n",
" - 40\n",
" checkpoint: exp/ofuton_p/timelag/latest.pth\n",
" has_dynamic_features:\n",
" - false\n",
" in_scaler_path: dump/ofuton_p/norm/in_timelag_scaler.joblib\n",
" model_yaml: exp/ofuton_p/timelag/model.yaml\n",
" out_scaler_path: dump/ofuton_p/norm/out_timelag_scaler.joblib\n",
" question_path: null\n",
" stream_sizes:\n",
" - 1\n",
"utt_list: ./data/list/eval.list\n",
"verbose: 100\n",
"\u001b[0m\n",
"[\u001b[36m2020-06-28 16:11:37,776\u001b[0m][\u001b[34mnnsvs\u001b[0m][\u001b[32mINFO\u001b[0m] - Processes 6 utterances...\u001b[0m\n",
"100% 6/6 [00:24<00:00, 4.03s/it]\n",
"+ set +x\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "w_Wy9DNLQhLv",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "cdc8211e-d3c6-40b2-ba78-dd93dd1939be"
},
"source": [
"import IPython\n",
"from IPython.display import Audio\n",
"from glob import glob\n",
"from os.path import join\n",
"sample_rate=48000\n",
"synthesized_wav_paths = sorted(glob(join(RECIPE_ROOT, \"exp/**/*.wav\"), recursive=True))\n",
"\n",
"for wav_path in synthesized_wav_paths:\n",
" print(wav_path)\n",
" IPython.display.display(Audio(wav_path, rate=sample_rate))"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"/content/nnsvs/egs/ofuton_p_utagoe_db/00-svs-world/exp/ofuton_p/synthesis/dev/latest/label_phone_align/kagome_kagome_low_seg0.wav\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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2Q/bP9zv3o/Qb+Fv79/eH91v3G/bP9pf2o/d39G/4m/hH+7P3V/dX9xP2g/Yb9iv24/f/9OP5A/jL+F/7e/aj9jf19/WX9Yf2L/eP9Mf4t/vn90/3I/bX9lP1p/VP9ev20/eP9A/70/bv9kf2Q/ZH9d/1v/Zb9yv3l/fj9+v3n/cb9nf2G/ZD9oP2Z/aD9y/3v/fj98v3S/cX9z/3B/av9r/3J/dr9zv28/bz9wv3L/cv9xv2+/bv90P3y/fr93f2//bP9u/3F/bD9mv2c/cH99/0V/hP++v3Z/cX9x/3B/Z/9c/1v/aj98f0Y/hP+Af7u/c79s/2u/av9mP2K/aT9z/3r/eX90f3e/dz9xv20/ar9vf3Q/db9zv3C/b79xP3L/cL9tf2t/bv9z/3Y/SL+AgCDAmAEGAbwB+sJsQukDN0MPw0YDi0PzxAvE8wVMBg4GukbXh1ZHoUeNx4oHm8esx61Hksewx1bHaYcbRvLGRgYtRaTFY8UnhOdEmwRERCNDtsMEQspCS4HkQVsBIMDxwItArgBYAH7AGMAoP/j/kj+0/1p/f78oPxY/DL8CfzO+5/7fPtp+3P7g/uj+8L7rft9+0z7E/va+pn6avp2+p361voT+0P7evuh+6b7o/u2+9z7BPw+/Ib81/wM/Sn9O/01/Tv9V/17/aH94/0r/mX+t/7g/tD+pv5q/jv+Lf4m/v393v3h/dD9xf3S/cj9vv3I/br9nf2i/Z/9hv1Z/Qb95/wI/S/9TP1Y/Yf97v1A/kz+U/5R/kH+Zv6N/rD+0v7d/gP/Vv+z/9H/tv+Z/6H/zP/w/wAAAQAFABQAFAD+/97/rP9v/0//Rf9F/0X/Lf8N//n+0f6f/mb+D/7D/Zb9i/2Q/YD9WP0l/QH96fzR/Lz8nfxw/FH8U/xp/Hz8cPxF/Bz8FPwb/CD8OPw4/ED8Yvx3/H/8hfyd/LH8uPyv/Kn8u/zD/Mb84/wA/Rn9N/1O/WX9eP14/XD9Yv1B/Tr9WP1y/Y79r/3U/e797P3Y/cz9w/2s/aX9tP28/b/90P3p/QP+DP70/ej97f3Y/cT9yv3e/fH93v3M/eP9Bf4E/tr9r/2U/Zn9qP2s/bD9wf3l/QD+Bv78/eH9uP2W/YH9jf2X/Y39pv3J/eb98/3s/ff99/3X/bz9wf3c/dn9tf2z/dT99/37/ef97/0B/v/93/3I/b79uv27/bb9yv3f/dv90P3Y/d/91P26/av9tP2o/YD9ef2a/bD9uf2v/aj9w/3c/cX9m/2S/Y39iP2V/bH91f3k/cf9u/3N/c39wf2Y/XT9gv2v/dL95f3j/dr93P3s/QP+4v2u/ZL9j/2o/cn90/3P/db92P3q/e/92f3D/cT9v/29/dX92v3X/d79zv2x/aD9pP3J/fD9A/4A/vn9+/3q/cb9nf18/Wv9ff25/ej9BP4R/gX+DP4U/uf9pf2L/ZH9pP3M/df9wf2+/cj93P3s/eP9wP2y/dX9+P39/fX97P3b/dL9yf2v/a79rP2e/bL91P3g/er9/P32/fP99P0N/qb/IQL+A7AFqQfFCa0LtAzwDDwNAw4rD84QEBOfFQkYLhoNHHodPR5aHigeNB6nHgofDB/LHmAeuh3RHIYb4xk2GLkWmxXZFCMUHxPqEZcQ7w4WDTULQgl2B/4FvgTIAyEDlgIVApABAAFzAN3/Kf+C/vf9iP1E/e78nfxu/CX84Pum+2X7RftF+zv7PPtb+3/7ofuj+2D78vqT+lX6KPoT+iz6Zvq2+hf7g/vY+wr8GPwD/Pz7F/w9/GH8g/yn/N/8GP1S/ZX90/0L/jX+Uv57/p/+ov6O/nj+WP5P/mL+T/4t/h/+HP4X/gb+6v3Y/cn9uf3C/dj91v21/YX9V/1L/U79P/0//WH9oP3V/f79Jf5D/mP+Y/5Y/nv+p/7M/vz+KP9i/6T/uf+t/7X/yf/T/+D/6v/v/wwAJgArADAALwAPANn/pf99/13/Qf8n/xL/Ev/6/sn+nP5s/kH+Bf7Q/bT9jP1g/VD9Qv0p/Qn9uvxt/Gb8bvxe/FD8Tvxm/HX8Xfw5/C78Ovwh/Pn7+/sN/CP8PfxM/GL8d/x1/Hn8nvzG/Of87vzj/O/8+Pzl/M783vz8/Br9Ov1I/W79tf3V/cP9vf26/Zn9e/10/Xf9iv2v/dX96P31/f79DP4J/vH92/3N/b39s/3L/eX99/0Z/iz+Lf4U/uH9wP23/bT9qf2p/cf99v0N/hr+LP4g/uv9vP2k/ZP9rf3S/eT95/3U/db95P3d/c/9xP3E/dT91P3e/fj98v3t/eD9w/3F/dz94f3Y/dT9yf3U/dj9w/3H/eX9CP4N/u/92v3c/dv9zf2//cb9zv3K/cD9t/3D/c/9xv2y/bf91/3v/fL91v2x/Zv9if15/Xz9i/2h/br90v3j/ej9zf2R/XP9iP2q/bX9of2U/a39z/3Y/cj9uf2m/ZH9qP3V/fP98f3a/b/9wv32/RL+4/21/bX9wv3W/eH93P3m/fr9CP4l/jT+Fv7n/bH9mP27/c79sv2q/c39AP4m/h3++P3k/dP9t/2v/a/9uv3J/cz91f3k/en94v3U/cj9wP3B/dD9zP3a/ev94v3i/d392/3f/c/9vf3F/cb9wP3A/cT91v3h/d395/37/f796P3L/cn90f3M/b79s/2s/az9tP3J/aP++AAzA9sEnwaiCLsKPwy5DL4MLA0eDmcPQBG2E0QWghiOGnMc3h2cHoweHx4ZHlceXh4DHoAdCB2EHLwbmxouGawXYhZHFTUUIBPfEWkQAg+aDQEMOgpKCI4GUwVPBFcDmgICAoUBIgG2AC8Ak//z/l/+9f2m/Tb9o/w0/AD84vu++4D7T/tY+4T7pfut+5f7WfsI+9z6q/pz+lH6M/pC+mr6jvrC+vb6Gfsl+zv7dPu0++r7Cfw3/IX8vfzH/MD83fwX/U/9dv2o/fD9LP5b/nn+mP7B/rz+hv5n/mP+Vv46/hv+Gv4m/hH+7f3v/ST+Ov78/an9jP2k/bP9n/2S/ZD9lP25/db92P3U/cf90P0Z/mv+g/6h/t7+C/80/1T/PP8V/zb/df+p/9r/9f8dAF4AhQB1AEMAFQDq/7//sP+3/8X/3P/o/+j/9P/i/5v/NP+0/kj+J/4h/g3+Ef4h/in+Jv7v/Xv9Df22/Hz8c/yF/J78tvzO/NT8wvx3/Av8x/uj+6j7zvsG/E/8jvyx/K38hvxU/Db8IPwI/BT8S/ye/OP8/vwX/Sv9Ff3+/Oj81/z3/BT9Iv1X/Zr9uP2y/Zz9lf2m/ar9kf2E/Zv9tv3Z/fn9Cv4e/hf++v3y/e/97/3y/eP92/3m/fT9+/37/Qj+D/4I/gr+E/4M/u/9yf21/cH91/3c/dX9z/3l/f39A/7+/dz9yf3L/dT94P3h/dv9zv29/cL95f39/e395f3z/Q3+KP4J/sv9u/3K/eP97/3j/ev9+v0R/jL+Lv4L/t79u/2y/cP90f3Z/fT9EP4z/kr+NP75/bv9mf2T/Yr9gP2N/cr9B/4p/kH+Ov4Q/sj9kf16/Xz9h/16/Yb9t/32/Rj+Bv71/d/9xP27/ab9jP2O/Zn9xf3l/d392v3b/e79+v3l/bL9m/2n/bv95v0L/v395P33/QP+8P3O/af9n/22/d397v3y/Q7+Gf4a/gn+7f3U/a79mP2b/b794/3g/c792/34/RX+If4A/tn90/3W/db90f2+/ar9tv3a/e39+P0H/g3+Ev4L/vv9/P3p/b/9sf3J/dX9w/2x/cH97/0S/hj+Bv4B/gD+4/3E/b39w/2//bj91P30/f/9+P3n/dv93v3b/dX93P3D/hwBQQPoBJ8GiQicChUMmAzFDDsNBA47Dx8RjBMOFlMYYxo7HKIdMx7jHW8dWh2HHZIdVB32HJscNxxwGxgahxjfFkoVDxQWEzISQREEEIMO/AxyC78J7AccBpYEjQPXAkkC1QFkAfEAdQDu/2j/2f5B/q39R/0b/fn8qvwy/Mf7kvuU+5r7dftM+0b7YPuO+4/7W/sY+7b6avpg+lr6Qfo2+kv6m/oI+0z7Vftl+5j71vsO/Cn8NPxc/Jn80fwX/Uf9Vf1m/Yb9t/0J/l7+ff6H/qj+yP7Z/rr+eP5M/jH+Gf77/fv9Kf5Q/lL+O/4v/hr+5f2n/WT9V/2F/Yz9hf2s/eT9/v3z/ef97f0C/gD+7f0h/oj+3/4O/x7/Pv9z/4v/i/+f/63/uf/F/+D/JQBqAHcARAAvAFAAVwBMAC4A///n/77/nv+v/7b/iv9W/zf/IP/3/qP+Tf4a/vn90f2n/Zj9j/1y/V/9XP0r/dr8m/x6/HP8Xfw2/Cj8Kfwp/CD8IfxE/Ef8JfwV/BX8I/wy/DH8Rvx6/JH8kvyd/KX8ofyI/Gn8b/yP/Mz8F/1V/YP9lv2Y/aP9mP1f/SD9Cv0r/WT9jf2S/bD9+/0m/ir+Ev73/dz9u/23/cz94f3q/dz93P0X/kT+Lf4C/tL9v/3e/fj97P3w/RP+Jv41/jX+FP7l/bv9pv2n/b793/33/Qz+HP4q/ib+C/7h/aj9jv2x/df97P3+/f39A/4S/gj+6f3S/cf9s/3A/eD9+f0S/hn+Df7+/QL+Bf72/d79y/2+/cv92/3l/ff98v3u/QD+Ef4H/uT90f3V/cz9qv2T/Zf9p/29/cz90/3r/QT+/P3b/cf9x/2u/YT9cf2F/aL9sf3T/e79+v3+/eH9yv2+/cL9uP2e/av9wP3g/fP97/3x/e/95f3K/bv9yf3Z/dr94P3z/QH+/f3x/eX95P3p/eX90P22/bH92/0W/hD+7f3g/fj9Iv4r/hH+5v3A/an9ov2q/bX9wP3O/QH+Qf5T/j3+EP7k/cD9rv2P/Xb9mv3J/fv9Mf4u/gb+5P3E/bL9v/3K/cD9z/3w/RP+KP4D/sr9rv2i/aL9of2z/eT9Df4m/i/+Lv4C/r/9lv2U/an9sf3F/e39J/5P/kP+Kv59/kcAYAIIBNgF/Ac1CvYL0Qz6DEYN9A3WDlIQmhJDFcYX8xnhG24dNB4MHoEdRh1wHY0dXx0THdYcdxyiG1QawRgdF4YVMRQwE1USdhFJENwOZw3fCxEKFAg0Bq4EoAP0AmYC6QGeAVIB8QBsALb/7v5G/sn9Y/0p/Q395Py5/JL8WPz9+5D7Qvsu+0H7XPuC+577t/u2+1774/p8+hT62PnN+fH5UPrE+iz7i/vU++H72/vi+/D7G/xG/GL8nPzs/Cj9XP18/YL9n/3b/Qn+Qv6Q/sr+4/7v/t7+sf5+/iz++v3w/eP96/33/QH+Hf4t/hj+AP7i/br9mv2T/ZT9i/2Y/aP9ov2t/b791f0B/iD+Mf5m/qT+zf7o/hP/Rv9l/2D/aP+O/7//4//u/wEAJABAAEUARABNAEsAOgAgABcAJwAmABUA9f/E/4n/U/80/wv/3P6u/oP+hP59/lL+Hf7x/b/9d/1F/RX97PzY/M38ufyd/I/8hfx2/Fn8Ovws/CX8DPz1+wH8L/xT/EH8Jvww/EP8P/w0/Ef8Yvxn/GX8k/ze/AD96/zV/N787Pz4/O/84vz//C39R/1o/Zr9tf2u/aX9qv2j/Y79cf11/Z39sv2z/cP96/0a/hr+Af7u/er99f3z/ff97v3d/dL91v33/QP+5v3I/dz9EP4f/gP+/v0S/in+Kv70/cT9qP2c/af9v/3Y/db94P0S/kv+WP4r/uX9tf2q/ar9qf2o/cD97f0H/hf+Hf4R/vn95P3d/eD92/3Z/fD9/f36/fT95/3q/eH90/3g/er98f3i/dX93v3g/eT97f3x/eb9zP3C/c39yf24/af9pf3C/dn9z/3C/cL9wP26/c392v3L/cH9sP2r/an9ov2m/bb9yf3Q/dv98P38/fP96f3R/Z/9kP2j/bD9y/3u/QD+Ef4b/gn+8/3e/c39wP2y/bL9qP20/eL9+/38/fX99v0D/gv+Df4G/uv9yP2i/Yz9oP2v/bv9zv31/ST+Kv4e/gf+8v3t/eH9xv21/bv9xf3M/dD9xv27/cr94/0M/in+H/4S/g3+AP7U/aj9kv2k/bj9sf3T/QD+D/4P/gv+Dv4M/uH9rv2k/a/9wP3L/c793f36/QH+7f3u/fj91v2c/Yf9m/3D/Qv+vP8/AioE2QWfB4UJSQs+DFwMpQyMDbMOYhCiEjgV0BcLGt4bQR0nHloeKh4SHigeXR5ZHgMeoR0zHXQcQxvEGSsYxxaOFVsUShMxEgIRwA8wDngMtwrSCBoHsQVjBFcDmQIPArkBcAESAaMAJQCO/+r+VP7L/VX99Pyg/GT8SfxH/EL8IvwG/P776vvH+5H7UvsZ++r6x/qm+qP6oPqL+pH6ovqp+rj6wfrN+v36Tvud+9j7EvxL/H38m/ya/JP8qvzd/Bj9V/29/SH+df6x/rH+lP51/kH+EP7//fb9A/4//n7+k/6V/oD+Q/7//bj9a/1V/Vj9U/1t/Zn9yf3i/db9u/23/b79q/2Z/bL97v0q/ln+hP61/tf+6P71/hX/Wf+F/5j/y/8NADsARQAtABgAHgAhAA4AAQARADIAVAByAG8ATQAIAMb/o/9z/yn/4P6s/pn+lv6K/n3+X/4p/uj9vv2Y/Vj9FP3b/MT8yvzG/Kn8mPyK/Fv8MPwX/Pn76fvd++j7LPxz/H78WvxB/DX8Gvz9+9z7zPvw+yz8aPyz/P/8EP35/OL82vzZ/ML8rvy4/OD8FP01/VD9bf2A/Y79kf2I/Yj9jv2j/bv9vf3I/c39uv2u/aP9oP2+/dz96v0K/i/+N/4x/iH++P3K/bD9pv2z/eT9Ev4c/hf+E/4Q/vX9z/2w/bj93f3v/fP9//0Y/gj+1P26/a/9lP1//Yb9sf31/RP+Ef4Z/i3+LP4F/sv9q/2b/Zb9rf3J/ez9C/4Y/h/+KP4f/gf++P3l/dj93/3k/er9/v35/ej97f3c/a/9qf3F/dv96f3m/er9+P3t/c/9vv2y/ZX9f/2L/bv90/2+/b/92P3u/ez9v/2N/Zb9uf27/a39o/2p/c397P3u/en92v3B/bD9mP2Y/a39qv2n/cX98f0I/gL+6/3V/c39wf2z/aX9qv3K/e/9+v3u/dD9wv3b/ej94f3X/dP91/3h/fD98v3r/eD90P3d/fL93f22/af9uP3Z/fr9+f3w/Qb+Hf4T/tr9p/2U/Zn9q/23/dL9Cf4k/g/+//32/dX9p/2T/a/93v3z/eD98P0O/gr+9/3W/cr9wf20/a/9vf3t/fj94v3t/QH++/3r/dn9y/3C/aP9f/2S/c/9+P32/Qv/cgGAAx0F1AbNCN4KVQzBDO4Msw3ADhkQEBKPFDYXohmYGzIdfh4hHw4frR5/HsQeAB/QHmoe7R02HSEcpxrwGF4XExbgFMQT0xLSEZEQAw8jDSkLRwl6B8YFaARzA9YCeQIlAsQBWgHAAPX/Pv+h/hn+r/1T/R/9GP0M/d78hPw0/PH7r/tv+1P7bfuV+6T7iftx+1T7Avt/+hz6BvoU+jD6Yvqy+hf7Yft2+2/7ffuS+5H7ovvp+1H8vvwN/TD9VP2H/ZP9if2s/dT9Fv5m/o/+uv7J/sL+oP5x/kX+D/70/fT9Cf4o/kH+RP40/hf+0v2M/Wv9S/01/Ub9Yv2L/cX95/3y/e792/3B/cP99P0Y/jz+g/7N/hL/Mv8u/zz/aP+Q/7H/3P8AABwANQBEAEgASgBIADoANgBOAFQAQAAtABQA7f/L/6r/gf9f/1L/OP8I/9b+nP50/kv+Bf7E/aL9g/1P/R79Bv0D/QX98/y4/If8evx1/F78LPwK/OX7y/vd+/L7D/wd/Aj8Dfww/Ez8VPw//Cj8K/w//Fr8afxn/Gb8g/yz/NX86vzm/OH88fwT/Sr9Iv05/Vf9T/1g/Yr9k/2P/X/9Yf1p/Yn9n/2s/bf90/0A/hn+BP7k/dH90/3S/bz9wP3a/fD9/P0B/gn+Ff4X/vH91f3a/eP94/3a/dX95P3y/d390/3r/QD+7/3N/br9uP28/cT9vv2z/cX9x/3U/fX9BP4A/vD97P3t/ez93/3J/cL90f3q/fP98v3y/Qr+I/4W/vf92v3Z/eD96P3w/e/99v3y/e/98v3g/aX9ef2L/bP9zP3Q/dX97P0Q/hr+/P2u/Xj9eP11/XX9gP2f/bj9y/3q/fn97v24/Xb9f/28/cj9uf2u/bf92v3Z/bT9mP2S/ZD9kf2p/dX9BP4S/vX92/3V/dT9vP2M/YH9sf3i/fL9+P0D/vz92P29/b390P3L/br9zv3//Rv+Cv7t/c79wf3I/cv92/3j/eT96/3w/fH93v3G/cH9w/3Z/e798/3z/eT94f3Q/bn9qv2k/b792f3g/ef96/3v/er9zf2z/Z79n/2z/cv92f3W/ef9//31/eD9zv22/az9u/3M/dH90f3e/e39Bf4h/gT+zP2l/Zz9rP23/bH9r/3h/TH/owGeAy4F7QbDCKgKGAyiDNgMiQ2hDhgQORLDFDgXchmHG1sdoR4NH9kerx7WHg8fDB+/HkMesx0FHQkcuhofGWkXBxbzFAAU9BKtET0QrQ4ADScLPAlhB7EFWgR2A9UCQAKzAUAB9ACtACwAhf/q/mr+C/6i/S/90vyN/Gn8Svwv/Bb89Pvx+wP86/vM+6/7evtG+yn7A/vP+p76XvpF+mD6e/qc+sX6/fpW+6f70/vx+yH8Vfxz/IH8jvyp/ND8Df1V/Yf9t/30/Tf+dv6d/q7+t/61/q/+i/5c/lb+Uf4z/hP+/v3t/d79z/3H/d796f3O/cz91P3D/a79hv09/Rz9Jf0l/Uj9nv3u/Sr+cP6d/qr+rv6d/pP+q/7F/uL+Mv+l/wAANwBHADEAIgAJAOD/4v8WAFUAfwCWAKYAqAB8ACMAwf9v/0r/Pf89/1L/bf9i/zD/7/6S/iL+vf16/Vb9Vv1f/UT9Lf03/TH9Bv21/Fj8Dfzt+/j7+vsA/Aj8+/sG/Dn8SPwl/P374/vs+wT8APwA/Br8MPxU/IP8mvyV/If8jPyu/MT8vfzB/OP8Ev04/TL9Lf1J/U79S/1a/Wv9dP15/YX9nf2v/a/9rv3E/ev9/P3j/cv90f3L/dD93f3O/cj9z/3t/Rn+Jv7+/d397P0B/vz90v3B/dv94P3c/db9yP3c/er95/3y/ff98/3l/dT90f3K/bT9pv2y/eL9AP72/e/9Av4N/vL9vP2f/Z39mv2x/dz9+f0L/g7+Df4S/gD+xv2c/ZH9mP28/fT9Bf7x/fr9Ev4C/tj9o/2D/ZD9sf3g/Q3+EP7n/cX9yP3E/af9ev1n/ZH9zf3+/fr90f2+/a39mv2E/Xb9h/2r/dH95f35/d/9rv2Y/Xv9d/14/YP9pv3O/QP+Jf4Z/ub9rv2K/YL9gf2J/ZX9t/39/Sf+JP4T/vb92v27/ZT9kf3A/fv9Dv4A/vX97/3d/bf9nf2k/cP97P0C/g/+F/4N/vX91f20/Yb9d/2h/eD9+v3x/fL99v3u/e794v3S/db91f3g/er91P21/bP9xv3O/cL9u/3d/RL+H/77/dj9yv2o/ZP9of2u/cP9z/3S/fX9FP4G/sn9m/2d/aP9rv26/cP92/0D/hb+Ev4A/t/9uP2k/fb90P8wAhYEBAY0CIYKVAweDTcNbA0WDhAPmBDwEsMViBj3GgIdkh5iH1of8x6iHpYevh7FHoYeMh7GHewcfhuxGegXYBYJFdUTzRL2ERQR1w8zDlcMXApHCDwGdQQhA1QC3QGZAZEBkQFWAccACQBK/43+3f1G/fv8+vz0/Nv8yPyq/G/8FPy7+5P7mPuy++D7/fv6+9L7hPsf+6f6RfoE+v35Pfqa+gD7avuu+9X7/vsU/A78/vv/+x/8bvzU/Cf9WP10/az95/0M/iP+Kf48/mD+g/6e/rz+yP6a/mX+Yf5Z/jH+/P3l/e798P3a/bb9sP2o/Y/9iv10/Wj9c/13/XP9c/13/W/9fP2b/bL93/0e/lD+ev6n/sz+7P4Y/0P/Wv9w/5v/t/++/9P/7f8XADEAQgBlAH8AnACmAIgAUwAWAMn/gf9o/2r/Zv9e/2X/ev93/zX/1v55/iH+y/1+/Vf9Vf1U/UX9QP0w/QP9z/yU/Gz8Tvwj/A38I/w4/DH8JPwd/Cj8Hfzo+8773Pvp++b7/vs9/Gj8gvyW/Kf8t/yj/G78W/x6/JT8lPyt/Ov8H/05/Vn9df1x/Vj9PP1D/WH9ZP1I/U79kP3E/bn9qv3J/eH91f27/bn92f3s/dP9vv3T/f39CP7w/df90f3s/f/98/3b/d/99v31/ef95P38/fj9xv2k/af9xf3Y/dP91v3x/Qv++P3W/bv9qv2r/aD9mP3K/Qn+Gv4S/hH+/v3q/dD9nP2e/cv96/0I/iT+Iv4Z/hz+9f3L/a/9m/2p/c399/0E/gn+HP4M/uz93P26/Yn9fv2S/av9yf3V/dP95f32/e790v2o/Yn9hv2S/aD9qP2V/Zj9uf3J/c39sv2e/bb9wv2q/Zj9lf2L/Yn9j/2V/bP9yP3L/dz94v3P/bL9mP2H/Yv9pf22/c/98P39/fD92v3L/cX9zP3L/cb92v0L/iL+A/7M/aH9o/25/cX9zf3m/Qz+Kf4n/gz+4v23/ar9rP3H/ej9+P3z/d/94v3v/eD9t/2c/bn9/f0t/hn+5v3a/dr9w/2t/aD9p/3A/dT95v39/fv92P25/a39zv3l/cn9s/28/eL9Bv4E/sj9mP2e/a/9vf3B/cj92P3y/QX+Bv4K/vD9tv2H/YX9mv2f/Zr9cf77AHIDIAW9BqUItgozDKMMswxQDVsOqg+uEWsUPheXGXEbGx1/Hhwf3R6EHqUeDx8+H/8ekx4OHkYdEByEGugYVBfvFdQU8RMNEwASoBDlDvoM/QoSCUQHkwU2BEADugJqAgACkgEnAa8AJQCL/+D+P/7S/YT9Pf0M/eD8r/yQ/Ir8efxS/Cr8F/wV/Af84/ut+2r7MPsS+/v60vqa+pL6yPoI+yT7E/sj+237rfvV++r7BPxF/Hv8pfzX/O/8C/0v/WX9xP3//QX+E/5O/pP+tf6w/pL+df55/oD+XP46/iv+Ev74/fD95f3l/fb97f3G/Zr9h/15/Vb9M/0r/Tv9Tv1e/Xb9nf3M/er9AP4T/iP+TP5s/oH+oP67/uL+FP9O/4//u//c/w0AOAA2ABsACwALACMAPgBEAEkASgA9ACcAEwD1/8z/ov94/1r/SP8x/xn/4P6P/ln+Lv4A/tP9p/2F/W39Uf0y/RT97fy8/IX8Y/xM/Db8I/wP/BX8Kfwz/Cb8CPz2++777fvl+9/78PsD/C78V/xs/IX8ifx6/HP8bvxo/H/8ovy9/N78D/09/U/9SP08/S39J/0t/Tf9UP15/Zj9qf3D/dD9yP29/ar9nP2t/cz92v3t/ff97P3l/eP93P3D/cb94/34/Qj+Gv4f/gj+6P3L/bn9uP2z/aL9t/3y/ST+JP7x/cf9wP22/Zv9hv2L/bP94/32/f/9Ev4R/vL9u/2O/Yr9lf2N/Z/94/0d/iv+KP4Y/v/94f29/aX9o/2m/cX98v0Q/iH+Hf74/cb9sf2p/a39uv3N/fb9IP4r/hH+5v2+/Yj9YP1k/Yv9tP3M/dz99P0U/hL+2P2L/WX9Yf17/Zb9mv21/dH97/3x/cD9lP18/XX9fv2c/br90v3o/fb9AP7w/bL9cf1k/Xz9nv27/dj98/0C/hb+AP7G/Y/9dP2B/ar90f3r/RP+L/4l/gr+0/18/UP9Qf1w/bb97v0S/jH+X/5o/jX+5f2d/Xz9df1u/YP9vf3f/fL9DP4d/hT+Bf7m/db96/3W/bD9q/2//cb9wf2w/a/9xv20/ab9w/3n/fL95v3d/d/93P3d/dD9s/2j/aD9pP2o/bz91/31/f396P3h/f39Cf7s/df9xP2//cr9uP2f/aj9vP3p/lcBdgM3BTYHYwlqC8EMHA0sDbINkA7XD+cRjRRGF9kZIBwLHlcfuB9XH+ge2B7xHtIeaB7/HagdHh0pHKca5RhCF9UVnRSGE3sSVRH/D2wOqQzdCvQIAAdOBfcD+gJQAuABpQF5ATcBygA4AIz/6/5h/uP9dP0S/d780PzE/MT8qPxy/FD8N/wb/Pn76/v9++37uPtx+0D7IPvk+pT6W/p1+rP67fok+2X7xPsS/Eb8UfxA/ED8Uvxt/JP8zPwE/T/9dP22/QX+Pf5m/mv+cP6O/qT+n/5+/ln+Of4Y/vD92P3p/ff99v3z/fD98v3R/aL9b/1G/Uj9OP0h/RT9Kf1V/Wr9gf2X/bH9x/3T/fb9Nf5t/oL+f/6N/s7+D/83/1X/df+t/+v/EQAiAB8AJQAlABYAIQApADQAWABlAFUARgAiANv/lf9R/yf/Pv9T/zv/FP/d/p7+dP49/uH9mf1s/WP9bf1o/VH9Gv3K/ID8R/wz/C78KfxA/Fr8bfxy/Er8CvzS+7H7uPvV+9r75PsX/Fn8g/yD/Gz8ZPxr/F/8VPxy/LT81vzp/PX8A/0W/QP94/zr/AP9B/0l/Wv9yP0J/vT90/2v/W39L/0B/RP9ZP2x/fH9LP5O/k3+Jf7d/Zf9cP1Z/Wz9vv0V/k7+SP4O/tn9rv2c/ZH9hf2k/e/9Kv5I/kT+Ff7d/an9b/1W/Wr9if22/QD+NP5A/i/+6f2x/Zr9jv2D/YL9nf3E/Rf+Tv5J/hP+3/3B/ZT9iv2R/Zb9tf3x/Sn+Vv5V/iP+8P3P/b/9lf13/X/9pf3n/Rb+If4Q/v794/28/ZX9hP2J/ZP9u/3o/ff99v3q/bn9jP13/Wv9df2H/ZL9wf0D/gD+4/3J/ab9i/19/Xf9f/2v/c790v3j/fP99f3P/aP9mf2Z/Z/9qv24/db9/v0F/vn9/P3x/d790v3A/az9lf2Q/aH9vP3o/QL++P3v/Q7+Hv4G/tr9m/2F/aH9uv21/bb9wP3C/dT96/30/eT90/3T/e/9Ef4G/t/9rv2g/aL9nf2i/a39wP3U/ff9IP4t/gr+4P3A/cL95P3a/b39pf2d/bb9xf29/bX9xf3X/ev9Bv4B/ur91P29/aj9kv2O/aT9rf20/cT92P3o/dL9uP2w/b390v3w/Xb/3gHLA5EFjwe4CacLygwVDVsNFA4ND4IQwBJxFSUYphrOHH8ehB+tH0cf4h69Hrceph5rHiMe1x06HRwcdBqiGPkWdBUgFAET7hHKEIIP+w1ZDJwKtAjdBjgF3gPnAkAC3gGJASIBywCBACgAlf/n/mz+Jv7W/Wf9A/3Q/MP8pPxi/DT8IPwQ/Bb8IPwk/B/8APzE+4H7Sfvv+pv6ZfpI+mj6u/oV+2T7q/vc+w78KPwi/CP8MPxe/Jv8yfwI/VH9hv2l/cD90P3q/Sb+Xf5u/oL+rP7B/sP+n/5c/jH+G/4E/tz9tP2t/br9vf3B/dD91v27/Yb9W/1W/Vf9Lv3//Ab9QP13/ZL9qv3K/e39E/4e/if+Wv6K/rL+2/4O/1P/g/+P/4X/jP+m/8L/1P/t/xkAOwBQAG0AegBbADEAEwDo/7r/j/9r/2f/X/9O/zL/Gf/6/rr+h/5e/in+7/2//Zv9cv1E/Rz9+/zM/Jv8gvx9/Hj8ffyG/H/8Wvwq/BH8BPzs+8X7ufvb+w78LPwu/ED8Zvx1/GT8Sfwz/EL8Zfx5/Ij8ovzE/OX8CP0n/Rb99vzU/M78/fwj/Tv9U/18/bj90f2r/Xr9WP1P/Vj9Yf2D/bT93f36/Qb+Dv7y/aD9Zv1x/af9zP3J/df9D/4v/g3+0f2q/aX9ov2a/Z/9wv3s/fP93/3Y/eT94v3A/Zr9rP3W/d390/3O/dn96f3Z/cD9xv3U/df90v3G/d39Cv4M/vz97P3f/eP92/2+/br9wP3U/fj9AP4B/gj+9f3Y/dD9xf23/bH9sP2+/en9/v3i/c79zf3D/bn9sv2j/ar9s/22/cr9zf24/aP9pP21/bD9nf2T/Z/9rP2j/Z79lP2X/ar9uv3D/a79lv2S/Yr9kP2d/Zb9nv2+/c/94/3p/bz9if15/Xv9lP2y/br9y/31/Rf+E/7q/bz9l/2R/ZP9hv2S/bn94P37/QX+Ev4O/uX9u/2d/ab9tf2k/Z79tv3S/d794f3R/dL90f2//bn9xP3Y/ef96f3X/cb9u/22/a39n/2f/br91P3t/Qb+Av7l/dP9xP2t/Z79mv2i/bj90/3X/db91P3H/bD9qf3F/eT93v3H/bz9x/3Y/cP9of2p/cH91/3h/dv96v30/dP9mv2f/RH+7f9MAiwEFAYzCFUKDQzpDBkNeQ1ADkkPFhGuE3wWGBlOGy0dsB5/H20fAB/iHh4fZR9pHy0fyR4mHhEdixvUGRAYahYXFQsULhNgEjYRnQ/TDf8LEgoYCEgGyQS4A/0CcgL7AZABLQGuACIArP8//+X+nP44/tL9kf1T/f/8mvxB/Bz8Ivwt/CT8OvxS/EL8NPwJ/Lr7Z/sQ+8X6l/qc+p76tvr6+jr7dvum+8v73/vt+/77Gvxa/Jv82PwZ/VD9iv2y/cH9wf2+/cn99P0v/m3+tP7P/sr+0P60/oD+QP7q/az9tP3T/dX9yv2z/Zz9n/2h/XP9Kf0I/RL9Nf1W/VL9R/1X/XL9fv2A/Yz9pf3C/dz9Af5D/o7+y/4N/1f/kP+q/5f/e/97/5L/kP+L/8X/IwBvAI8ApQCmAG8AGgDY/7X/rv+Y/3T/cv+L/4D/Qv/3/rD+gf5V/ib+Hv4c/vj9s/1b/S39H/3u/JX8Y/x4/Jr8mvx//Fv8P/ws/Af86/vs+wL8+vvz+wz8DPz2+9n7zfvp+yL8UPxr/JD8pfyb/I/8gPxi/FT8V/x1/MH8Ev1F/Vb9Wf1M/Tb9Hf0M/Q39Jv1Q/Yb9uP3I/cL9sP2l/Yb9Z/1q/YD9q/3K/fP9Dv4A/uP9v/2s/af9qf2t/c799f32/en93/3M/aH9f/1//Zr9z/0B/hP+Iv4n/v/9sP1z/VD9U/2H/av90f0H/jD+Nf4T/t39sv2i/Yn9gf2s/ej9+P3u/e395P3U/bX9oP20/cr91f3i/eT93/3Y/cb9sP2h/aP9tP29/cf91P3S/cf9uf2i/Yj9gP2S/bT9xP3I/dH92/3T/bD9iP1n/Vn9XP1t/Y39rv3N/dj90f3N/a79f/1j/VD9UP19/Zn9nf2n/bD9u/3F/bj9mv2V/ZX9mv2u/cL9z/25/Z79pv3B/dD9wv2t/bb94f3+/fX91f2x/aH9q/2x/bP9qv2h/bj93f39/Q3+/P3P/a39o/2e/ZX9kv2N/Zn9yv0C/hv+B/7k/cn9sv2e/Yv9fP2J/an9u/3n/Qr+Af7t/dj9uP2P/Yb9lP2f/bj9yP3O/dD9xf2y/Z39l/2i/az9u/3k/fj96v3J/Z/9i/1p/Vv9ef2g/cv99f0Z/hD+8f3H/Yb9cP15/X79y/20/1YCbwRcBmMIggpdDFMNWw1/DVMOlA9dEcoToBZsGekb8B1pHzcgMSCkH0kfbx+9H88flh82H6YerR0vHFoadxjUFpgVnBS3E74SihEHEDYOLwwSCv8HPQbtBPsDdAMRA5ACCAJyAc0AIwCM/wn/nv56/mL+Nf4A/qr9PP3D/FH8/fve++z7Ifxg/Ir8ivxg/Bz8t/tB+9z6lPpq+nf6rfr++lL7h/uc+637t/ut+7375fsV/Gv8xfwC/TP9Xv1z/XL9ef2O/cT9DP5C/nj+pv68/qn+dv5B/g7+9f37/Qn+Gv4W/vj94P2x/XT9UP0w/Q79/PwY/Uz9dv1z/Ub9Ff37/Pz8CP0Y/Uz9k/3L/QX+P/5r/nX+Uv5I/nf+xf4J/zj/cf+1////IgAGANr/uf/A/+T/DAAqADQAPAA7AC8AGgD0/6L/Sv8z/0H/SP8u//j+2v6+/n/+Lv7x/bv9ff1b/VP9QP0r/Qz95vzd/MD8hPxO/DD8H/wJ/Pb79fsA/Pz77vvr++z7//sB/Pv7C/wY/CL8M/xO/E78Nvwe/Bf8LvxV/Hz8ovzI/O38Cv0U/Rr9Hf0T/fj87vwH/SH9Mv09/UT9U/10/ZL9o/26/dD91v3P/bf9mP18/WT9Wf18/bT90/3k/ef97/3w/cL9mP2K/ZX9o/2p/dD97v31/er9uP11/U79Sv1a/Yr9u/3q/RL+Hf4g/gT+t/1m/S79Hf1H/YX9qP3E/d/9+P0T/hf+3f2M/YX9qf3T/ez91P24/bT9yf3A/aT9k/1//Zb96v0t/j3+Fv7Y/cX9zf28/YX9Vf1Q/Xn9rf3L/cr9tP2Z/Zv9sf20/aD9hP2O/a79u/23/Zz9d/1l/Vz9W/1m/Wr9gf2e/cH93/3l/dX9o/16/Wr9ZP1t/Xb9gP2e/b39zP3N/bb9l/2A/X39gv2L/bz97P38/fD91f23/ZH9cP1R/Uz9Zf2g/e39JP48/ib+A/7Z/Zz9ZP1A/Tj9Vv2Z/dr9E/4v/hT+7f3L/aT9f/1t/Wj9d/2q/eT9BP4A/tb9pP2b/aD9kf2E/ZD9u/3V/dD9yv2+/a/9p/2W/Y/9pf27/dX95v3J/an9mv2F/Xz9hP2U/bz91f3g/fj99f3P/Y79Zf1t/XD9Zv1t/Zf91P0D/vL9v/28/Q3/aQF4A2sFiAfFCe4LbA0HDkcOxw6VDwoRWxMoFvgYgxu2HXsfmCDzILUgXyBYIHkgiiBxIBogbB93HjgdfBuHGbYXPRZAFWYUbhNUEvwQTA9bDUcLLAk+B5gFSgRuA/UCkQIyAtIBSQGnABEAhv8T/8L+dP4v/gD+1v2L/Qn9gvwT/NP73vsP/EP8dPyK/In8afwb/JX7/fqQ+lf6Rvpt+sL6D/tC+3r7pfuv+7T7uvvL+wX8X/yr/Of8E/03/Vb9bv2H/Yr9hv2Z/dr9NP53/pv+t/7D/rv+rv6C/jj+7v2r/Xj9Wf1Q/WH9eP2E/ZP9q/2i/XP9Nv0K/QD98fzL/MD83/wJ/Sb9TP1//aL9yP3v/RT+PP5Y/mj+d/64/gn/M/9T/4H/tf/c/9j/tP+v/8L/y//n/xAAPQBiAGMARwAkAPj/ov9I/xT/Ev8j/x3/Df/+/t3+mv5G/vD9q/1k/SH9IP1M/XL9bv09/QH9wvx2/Br8zvut+7H7yfvj+x38Yfxv/F38Lfzx+8j7sPuR+4b7vPv0+y/8bPx4/G/8X/xC/D/8Uvxa/Hb8rfzW/A39MP0P/eP8wvy3/ML8yfze/Cr9fv29/dz9zv3C/aT9bv1D/TD9LP1A/WD9fv2z/fH9Gv4b/gL+6P3P/ab9eP1x/YD9fv2G/aL9vv3c/d79w/3D/c39sP2Y/Y39g/2T/ar9qf2m/az9pP2k/aT9kf2D/X79hP2c/cn94f3q/fj95P29/ZL9Yv1P/WP9eP2R/cn9/f0f/jH+EP7S/aX9e/1i/XX9hf2R/ab9vf3Q/dv9yv2p/ZD9kP2m/a/9p/2V/YD9fP2M/Y79ff1g/VT9dP2e/bX9m/11/Wv9eP2T/av9qv2K/XX9g/2N/Xv9Vv1G/WL9hP2r/c792f3e/dX9vP2k/YT9U/1C/U79a/2j/cX9vP2w/cX93P3F/Yb9WP1u/ab9xv28/bP9vv3H/bH9hv1x/Wr9af2C/bn96v35/QD+9P3N/ab9d/1c/WT9d/2h/c391v3O/cf9s/2g/Yz9df1//af92P0A/gT+7f3L/Yz9UP0r/Sr9Vv2O/cn9BP4n/ir+Ef7i/aT9Tv0b/Rz9MP1s/bf97P0F/gv+9P3C/ZT9bP1D/UH9Wv1v/Zr91v37/fn92P2o/W793f0PAIECdQSLBuUIYQtpDVEOXw6cDlIPYxAWEqIUwhexGiodWR/6ILMhhiH8IMUg3SDaIJogViAYII0fcB7ZHAUbHBlmFxcWIxVOFEUT/RF/EKcOkAxlCjsIWgblBMgDEgOwAnkCWwISAooB4QAhAHj/7f51/hD+uP1j/Sv9GP3y/L38h/xT/D78Q/xA/D38Qfwq/P37r/tN+wT7xvp9+kX6SfqE+tz6Mft9+8T7Bfws/DD8OfxI/Eb8RPxk/J383fwo/Xn9uP3r/SL+O/5P/nX+gP51/nT+cv5j/lf+K/7y/eL90/2l/Y/9oP2s/bj9sv2b/YP9Vf33/LT8rvys/L387/wG/SH9Xv2L/Z79j/11/WT9fP2//Q3+UP6T/tH+/P4q/1H/ev+K/3X/cP+O/8v//v/6/+z/CAA1AEgAPgAYAAQA/P/O/6T/eP8//wj/2f7T/uT+1P6I/kL+Iv7+/c39ff0p/fn83fze/OL8zPyq/H78YvxT/C/8BPzm+837wvva++375fvZ+9T74/sI/Bj8+/vq+wf8Jvwg/Az8BPwN/Cj8RPxe/Hv8jPyO/Jz8vvzW/Mb8svzP/Pj8Ev0m/S39N/1E/Tz9LP0e/Rz9OP1W/W79l/3F/dr94P3d/dH9sP1v/UT9Zv2U/ZP9g/1//Zv9xf3N/bP9oP2t/bb9vP3R/cH9mv1t/Vv9YP1g/Vn9Vf18/bL9z/3e/d/9yf2l/Xv9af19/YT9gf2T/b792/3M/a/9mf2N/YH9cv2H/cD96/31/en95/3q/cn9jP1f/Uj9Zv2a/av9rv21/bb9s/28/bH9iv12/Yb9pv23/aL9bP1N/Uv9S/1b/WL9bf2G/ab9x/3M/Z/9af1N/UX9SP1E/Ub9Xf15/ZD9pP2r/ZD9cP12/ZH9kf1s/VP9Yv11/YL9jP2F/YL9kP2Y/bD91P3F/ab9qv2p/Y39dv1p/Wv9fv2H/Yr9ov3a/f/9//3r/dH9u/2X/XD9V/1e/XD9gP2j/cD91v3X/cj9s/2a/Yz9ff16/Y39mv2v/bv9sf2g/Yf9cf1g/Wz9hv2S/Zz9oP2p/b79vf2o/Z79mP1//Xz9pv24/Zn9df1r/YD9nP2h/Zj9pP28/b/9wP28/aP9k/19/W/9fP2J/Yv9i/2a/bP9w/2z/Z79kP2a/fD+bAGhA6oF1gcdCmsM8g1QDnAO8w7FDzwRmhOaFrYZfhzfHr0g1yEGIm8hzCCrINQg/iARIfwgrCDxH6EeyBysGoYYsBZnFYAUvhPXEqMRGRA1DgoMyAmZB7sFVQRrA/cCyAKiAlwC6wFFAXoArP/d/kv+FP74/e/95v3C/Xn9Hv25/E78BPzI+7D74fsv/Gb8bvw8/OP7cvvf+lz6LPo2+lz6mvr5+mz7uvve+937zvvP+9b79ftD/KX88vwl/VL9dP12/Vf9Tv2U/f/9Uv6N/sH+6/7h/qH+Rf7h/Yv9X/1r/Zn92/0L/hn+DP7a/Yj9Gv20/IP8d/yT/MX86/wX/UH9Vf1M/TD9A/3e/Pv8Tv2i/e39Kv5o/qP+xP6//rH+xf7b/v/+Uf+v/wYAKAANABAAMwAmAN7/qv+x/9f/8//s//H/9v/J/5D/Sf8S/+v+s/6E/nn+gv5n/iv+4P2g/Xj9Rv0A/cL8rvyz/L38wvyu/IT8Vvwo/AL85vvF+7X7t/u++9r75fvi++D79/sJ/Pb76Pvj+wn8Nfwu/CH8Jfwz/Dn8P/xN/GD8gPym/ND8Af0T/f/8+vwD/fT8zvyy/LX83vwP/Un9gP2T/Zv9pP2p/Zn9Yv0o/RX9Iv1Q/Yn9rv3V/en95f3c/cL9j/1a/Uz9Wv18/aj9w/3e/QL+/f3P/aL9c/1K/TD9J/07/WX9of3T/ef99/0E/uL9qP1q/TD9DP0K/ST9Uv2b/dr9A/4f/hT+3f2k/Xb9Sv0x/T39ZP2L/cL99f31/db9qP15/XD9cf15/Y79p/3G/dr90/2z/Yn9X/0+/S/9RP10/ab9u/2//cb9t/2U/V/9PP0//VX9ZP1s/Yf9kv2I/X79gv1j/TT9Q/1Z/X/9vP3G/a79lf1//Wf9UP1C/TD9Nv1p/aX9yf3T/cr9u/2l/Yz9WP0z/T/9S/1//cH9z/3D/bD9nv2c/Yv9YP1T/W79mP3D/eH92f26/Zj9df1r/VX9L/09/YX90v33/f396v3L/aj9b/1J/S/9Kf1B/XT9vf3i/eH91P3N/bT9dv1J/Uz9bf2a/a39uf3I/bf9k/15/Vj9Qv1U/XX9p/3X/e/99/3i/bv9gf1A/Rz9GP0s/WX9lv20/dr99/34/cv9h/1U/UD9Tv1Z/U79tP3l/6QCxATMBuYIKQspDRsOVw7FDo0PrhCCEi0VQhgxG6cduh9jIUgiXCLcIW8hgiHGIdEhfiHsID0gWB/6HRocHhphGOwWuxW9FMETkBIQESgPGw0uCyQJHwdwBSwEVQPQAmsCIALoAZIBFAFyAL//Hv+Y/i/+0P16/Tr9EP3q/ML8jPxL/Cn8IPwx/D78Pvw1/Bb84ft8+wP7i/pC+kz6bPqP+sj6Eftg+6D7wfvN++f7EPxB/Hf8u/zv/PT87fz0/AL9H/1K/Yj9CP6Q/tL+5/7h/sn+j/4q/s/9o/2b/Y/9q/3r/Q7+DP7N/Zb9cf0x/d78pPyi/Kv81fwI/ST9Qv08/RD96/zd/N387fwN/UT9o/0E/kz+dv6O/qb+tv7H/uj+Dv8t/1b/lv/a//b/3f/N/+r/BAAaABwAGwAeAAEA3//E/7n/m/9V/wz/7P4B//f+s/5z/lX+O/4K/sz9hP1c/Tr9//zY/L38l/xc/Dr8Vfxr/FD8Gfzs+9770fu/+7H7nPur+8370/ve++v74fvM+8P7xPvQ+/L7K/xm/In8hPxp/Ff8Qvw5/DX8SvyE/Kv81/wi/Ub9Mv0Q/fH86vzq/Ov8+fwc/VX9a/1u/Wv9X/1t/XX9ev2P/Zz9rP2x/Zv9l/2T/W39Sv1H/WP9lP2s/b391/3l/df9r/2Y/YX9XP00/Sv9RP1k/W79ff2p/cT9uP2Y/Y/9jf19/Wf9Vv1m/Yf9kv2O/Y39lf2M/YD9hv2D/YT9nP24/cj91v3a/dH9vP2d/Xz9af1e/U39Wf2J/cP90f2+/cr93/3S/Z79W/1B/VX9ZP1z/YL9ff13/YD9gv2C/Yn9fv1k/Wb9hf2J/XD9Wv1U/Wv9ef1o/WD9a/1t/XT9hv2A/Wn9Vv1g/Yr9nP2E/XL9dv11/XL9Z/1v/Zf9p/2f/Zj9h/1m/WT9eP17/Xj9c/18/an91P3a/b/9jf1X/VX9aP11/YX9gv2G/aL9rv2r/aD9oP2h/ZD9gf1w/Vf9SP1X/XT9l/2s/a/9p/2c/Z39lP10/VX9P/1O/YX9tf3I/cT9s/19/Ur9MP0z/WL9ef18/ab9zv3Z/cb9mP1s/VH9OP0u/T/9af2J/ZX9r/2+/bf9mP1z/XX9jf2F/WX9V/1b/X39pv2u/aD9iv1r/YH+IQFwA2UFmwcACngMQg7eDv4OaQ8cEFUReRNXFn0ZehwXH00h1CJQI+4iQSLoIdYhtyGDITwh6yBtIHwf+B0NHAAaGhiTFmQVXxRPEwASYhCaDrUMrwqjCK4GBAXDA+sCcwIvAhAC3AF7AQABXwC0/xT/df7m/YT9O/0B/dv8wvy//LP8lfx2/Ev8Gvz8++373fu0+3T7Mvv4+sH6mPqM+pP6lvqc+sP6FPtw+6X7yfv0+yL8TfxY/Hf8q/zT/Pf8Jv1j/aL93P33/R7+T/5T/j7+Qv5i/nH+dv5p/lr+Vf4j/tP9nf2L/XX9Uv02/SL9N/1R/UH9Jv0A/dD8ofyf/L380/zx/BL9QP1m/Xj9dP1m/XX9jv24/Qj+Z/66/gL/SP+D/5D/Yv9C/1D/df+Z/7n/7v8mAEMAMgAbAAsA5/+p/3b/fv+m/7T/kv9e/z//Bf+T/hL+0P3J/c/90/3L/cj9yv2Y/S79x/xv/Cr89fvf+/j7Lfxb/F78RPwN/Nv7sPt4+037VfuE+8j7/fsI/Af8DPz0+8n7vfu6+8v79/sr/G38k/yT/H78c/x7/ID8ffyA/KD84vwZ/RX9+/zz/Pr8Gf0t/SD9Lf1f/YD9hv1u/Tz9LP1E/VL9V/10/YP9jv2l/bL9v/2q/X/9Sf00/Vv9av1l/WD9av2P/ab9pP2O/Yj9kf19/U/9PP1W/XL9ef1z/X/9mf2U/XH9WP1i/X39cP1W/W79nf3F/b79nP2H/YD9c/1N/Tr9Sv1l/YP9pP29/dH92f3I/cP9tP2C/Uj9I/0i/UT9Z/1y/ZL9wf3d/eT90f2r/XH9OP0q/UD9Uv1W/V39cv2M/Y79eP1j/VP9Q/1H/WL9b/1m/Vb9Uv1f/Vf9SP08/TD9PP1C/T/9Uv1k/WD9Yf1v/XT9eP1//Xf9Yv1U/Wb9gv2C/X79dv1l/XD9hf15/Wb9df2N/a/92P3b/bv9n/2D/VP9Ov1I/Vj9X/11/Zz9w/3h/db9nf1x/W79cv1f/V/9cf2I/aX9nf2K/Xb9Wf1P/Vr9bv17/Yn9j/2e/b39s/2a/X79V/00/S/9Sf1P/VH9Xv2U/cr9wv2o/Zr9n/2D/UD9HP0p/Vj9gf2S/aj9vP2m/ZH9hP1p/Vn9Qf1H/Xf9rv3G/bb9nv2F/Wf9rf2k/0gCggTBBjkJzgv8Df8O+g72DpQPwhCVEkcVjhjOG54e4yCtIrMjiyOsIgsiCyJLIkki/yGjIT8hayDjHu8c7BoPGY4XcRZ1FWcUExN2EZ8Pmw1zCz0JKgd1BUoEkwMwA98CgwIfAp4BCQFqAL//Kv+k/iz+1P2I/Uf9Dv3K/Ir8XfxB/Cj8Jfww/Dr8Qfwa/OT7ofs++9z6f/o6+hf6D/oy+nr60vok+2j7tPv4+xz8GfwQ/C78VPxj/Hn8mfzG/BL9aP22/Q7+c/6r/rX+oP5//mL+NP72/cj90f34/Sb+Mf4d/gj+3P2A/Rz96Pzg/On86fz3/Bv9N/0t/fT8t/yL/HX8gfyw/Of8Lf2M/dX9Bf4V/g3+Ev4p/lT+hv6y/uD+HP9R/3D/kP+t/8D/zv/b/wgANAA2AA4A1/+x/5H/df9f/1T/Uv9q/4f/fP9M//T+hP4d/tH9n/15/Wj9Y/1l/Wj9Tv0S/cf8ffxB/B/8FfwH/AX8DPwP/Az84vuX+2f7YPt3+6L7ufu/+9f78fsI/Bz8CPzf+8n7u/u9+9X7+/sl/E/8dfyT/K78vvzB/MD8tPyj/Jf8mvyh/MD8D/1X/W79V/04/TT9N/0w/SD9Lv1N/WP9kf3B/cb9uv2q/X/9Wv1C/Sz9Uf2R/an9wP3O/bn9p/2h/Y79bv1D/S79Of1R/Wn9g/2m/cP9vf2Q/XH9b/1i/T79Hv0T/SP9S/14/ab92/3u/bz9g/1v/WP9VP0//Tz9Xv2H/av9sv2f/ZL9eP1d/Vb9Wv1z/aH9xv3V/dP9pf1Z/S39Cf0I/Sf9Q/15/a79zP3H/a/9fv0//RX9Cf0r/Vb9bv2J/aT9pP1y/UD9Gv0E/Qf9IP1Y/ZL9s/2//bn9of15/UH9FP0F/fT89/wo/WP9jP2d/az9wP21/Yr9Zf1R/T79H/0c/T/9b/1+/WX9ev2j/a39nf16/W39ef18/W/9f/2S/ZT9gv1m/Wz9gP1w/Ub9S/18/aD9pv2f/bD9vP2i/Xb9Vv1J/T/9H/0V/Ub9iP2w/bn9uf2//bP9iv1n/W39X/0t/Sj9Sv17/Yf9WP06/Vb9lP28/cb9wP27/br9qP1w/R/95PzX/AL9Qv2B/cD93/3a/cr9sv2T/WD9J/0c/UX9Y/16/ZL9kf2W/fn+kAHSA+oFMwi4CjgNxg4zD2oPEhAREZES1hTMF+savB0kIBcibCPMI1kj4CLvIjsjRyP/IpYiCCInIbgfth2WG60ZIxj2FvsVGBUPFLIS2xCzDm4MIgoPCDkGrgS0AzMD3wKjAmIC8QFhAbAA9f9b/9n+Tf7Y/Zz9bf1I/RP9uvxs/E38OPwZ/P775/v0+wL8/vvX+4L7CvuQ+jr6C/oL+h/6Ufqd+vT6Uvub+7j7xPvW++n7+fsD/Cb8f/zj/Bv9Nv1S/Yj9wP3g/fn9LP5e/nb+jf6k/q7+h/5A/gz+3v2m/WH9Of1K/XP9lP2s/aH9ev1P/Rv92/yd/F38Nfw8/Gz8wPwD/Tf9Xv1s/Wz9W/1s/Y79qv3Y/RL+Xv6i/tv+//4c/z7/Tv9k/4D/mP+q/8f/AgAfABIA/P/e/8z/w/+m/3v/Yv9R/0//Uv9O/yb/0f6I/lD+D/7k/cD9of2X/YP9Z/1B/ev8jPxS/Df8MPwd/BL8MfxR/En8G/zd+6P7fPtX+0T7Y/uQ+6b7u/vJ+8T7wvu/+8j71/vy+w38E/wv/EL8IvwK/A78IPw1/Fb8hfzE/An9D/3y/Pj88/ze/Nj84/z3/AD9Hv1I/Wn9bv1X/Uv9Yf1q/Ub9O/1a/Yf9nv2Y/Y/9jv2J/Wb9VP1d/WT9Z/1q/Yj9tv3K/an9cP1T/VD9S/0//Tv9Xv2U/bf9xv2+/Zr9av1E/Rv9F/0x/Uf9bv2W/bD9x/3C/Zz9c/1O/Tj9Ov1B/Vb9ff2n/cj9yf2w/ZT9hf1v/Vf9Pv0u/U/9ff2n/dH90f23/az9jf1l/UT9K/02/UX9T/10/af9s/2Q/Wz9Y/1t/WX9RP1A/VT9bf1q/VD9Rf03/Sr9Lf08/Vf9Yf1U/WD9ev2A/Wv9Qv0w/Tn9Ov04/SP9CP0l/U39Yv12/X/9g/2B/YP9e/1i/U79Nv02/Uf9Vv1u/X79iv1+/Wf9a/12/XD9aP1z/Xr9eP2F/ZX9kv1+/V79Pv0+/T/9Lf0s/VT9kv29/bz9qv2d/ZP9ef1F/SH9J/1B/Vf9av2T/bn9t/2U/W79YP1y/Yf9hP1//W/9a/1y/Wz9cv1p/VX9T/1f/XD9cv1g/Ur9Vf1y/Yr9jP1+/W79ZP1X/Uj9L/0N/RT9QP2C/aj9ov2K/YH9ZP7NAEEDUAWZBwwKggx2DlAPdw/KD5QQ5hEcFCcXdhp/HQ0gNCLSI3YkJiR2IwgjGCM8IxAjtCJVItQhzSAjHygdLxtqGeEXjRZoFT8UxhL+ECAPKg0QC/gIEgeBBVcEkQP7AocCJwK3ATEBjADo/1//8/6Z/jr+3/2K/Sv9z/x2/Cv8+PvZ++H7Ivxo/Gz8Sfwi/Mn7SPux+if69Pnw+QT6Sfqg+uv6J/tQ+3n7kPuG+3b7i/vR+yb8cfyc/NL8DP03/Wz9i/2d/br93f0S/lj+jf6j/qr+pv6a/nD+Jv7v/cv9lf1t/WT9bv2B/Xr9Yv1Q/UL9E/3e/LL8n/yy/Lz8tvy6/M38z/zX/Of8+Pwc/Vj9lP3a/Sn+T/5i/oj+s/7S/u3+/f4k/3z/v//M/7b/nP+Y/6f/yf/8/xoAGwAbADcANgDf/23/Cv/E/qj+l/6I/pP+of6q/pz+Yv79/Yb9Kf3f/Kz8jPxx/Gz8h/yU/IT8a/w6/O77nftw+3D7e/t8+3X7lPvN++r7zfup+6n7ofuS+4L7hPur+9j77PsL/En8Wfwz/CP8OvxS/FX8V/xf/H38tvzV/OL86PzV/M782fzd/N/88fwR/T39W/1i/V79RP08/UT9P/1L/V39Y/10/Yj9kP2O/Xf9V/1e/YD9jP19/X39k/2S/XT9W/1Q/UD9Q/1a/YH9n/2g/ZD9dv1k/Tv9Dv0H/R79VP1+/ZD9nP2g/aX9iv1F/Rj9FP0g/T/9Xv2G/bf9xf26/aP9f/1h/UP9Lv0v/Ur9bf2D/Z79q/2w/aj9iP1d/TT9Lf00/U79YP1j/Xn9j/2O/YP9a/08/Sr9K/0z/Tr9PP1O/WX9gf2M/XH9Sf01/R79CP0L/SL9Mv1C/W39i/2J/XD9Of0V/f785Pzs/A39RP2I/a79r/2Z/W/9Lf0I/Qj9A/0N/Sv9Zv2g/a/9sP2c/XL9VP1D/Uf9Wf1l/W39ff18/WT9TP1U/XX9iv2W/aH9qv2l/Yv9b/1j/U39OP0//WP9jv2j/aP9lP2G/Wn9Pv1C/Vz9X/1Z/Xr9s/22/YT9Tf09/T39Jv0c/Sv9Tv12/Yz9l/2X/Yr9fP1o/WL9bP1f/U/9Wf1k/VH9Qf1A/UH9Wf1u/Yf9q/2y/Zv9dv1h/Vb9Of0R/QL9GP2o/fb/xwIKBU0HswkkDDYOPA9ZD6APdhCsEZ4TeBbBGegcrR/xIbUjvSSjJP4jpiPOIw0k6CN6IwojcSJXIbEfuB3OGw8aeBgqFzgWRhXgEwES3A/KDa0LcQlUB6cFlwTRAy0DrwJIAuQBWAG/ACYAh//8/nz+F/7k/a/9UP3g/I78WPwf/PD71vvQ++z7Fvwh/A/82vuC+zP72fpf+uL5sPnc+SL6XfqP+uH6QfuO+637sPvW+/r7Dfws/Fn8jvzO/P/8Kf1r/aX9y/31/R7+XP6V/p7+k/6U/oP+Xv5D/g7+2/3F/ab9g/1o/Vr9UP1P/Ur9Iv3+/O78zPyv/Kz8q/yW/I/8ovy8/NT85vwK/Sn9VP2G/bH93v0K/kj+g/66/uL++f4V/y//Vf92/3j/kP+//9j/6f8DAAsA/v8HAA0A+v/i/7f/gP9l/0f/B//D/pD+ef5m/kb+NP4n/g3+5v2k/U79Ef3K/HP8Qfwy/Cr8Ivwf/Ar8APz8+9r7u/uW+3T7d/uO+6L7kPtt+2T7bPtw+2j7Z/uB+6f7y/v7+xf8D/wI/Bf8LPwy/BH85/sM/GX8nfyY/In8ofzN/O/87/zh/OP87fwI/Tz9Xv1U/TX9Fv0U/SL9Jv0i/TP9ZP2W/b/9zf20/ZL9ef1c/Ub9Lv0v/U39Xv1n/W79hP2T/YD9Y/1f/WT9ZP1j/U39L/0k/TT9UP1k/W/9bf1z/YP9ev1c/Uf9JP3+/BT9UP1//aH9r/28/dX9sP1V/RH9B/0L/RP9MP1j/bj9+P3z/c79rP2C/UD9BP3q/Ab9Rv1x/Z/90f3V/a79cP05/SL9Gv0S/R39Sv12/Y39nP2f/X/9P/0K/fT8+/wQ/TH9Wf1x/Xz9df1a/UH9Gv37/P38GP0//Vr9bP1v/V79Xf1W/S39/Pzc/AX9VP2F/Yn9e/2B/Yv9hP1d/TD9E/0B/QH9Jf1U/XD9jf22/dX90v2k/W79Pv0S/Qn9DP0R/Sb9UP2F/bf91/3I/aP9if1w/WH9VP0t/Q79HP0s/Sn9Nf1M/Xv9t/3Y/dD9rP18/Ub9FP34/Ov89/wp/V/9mP3K/dz9xf2L/VL9JP0K/Q39Hv09/V/9kP2y/bz9sP2K/WH9QP0v/Sf9J/0Y/RP9Sf2S/bL9pv2Y/aH9pv19/V794P6TAeYDGwabCGILBA6UD/oPMBDQEMwRWBO5FcAY9BvxHo4hwSMbJVEl0iRXJEQkWSQ4JOAjbiP1IkMi4CDuHtccxBoIGbwXkhZbFQ8UjhLPEOMOswxUCiIISQbTBMQDCgOSAj8C3gFoAeUAVADB/zn/uf5M/vj9pv1U/QP9nPw3/Pf7zPu++9D7Afwl/Cn8Hvz3+5v7Cft6+hX63vnc+fb5G/pY+p364/oR+yX7LPs0+1z7pvsG/F/8qvzp/A79LP1I/Tz9JP03/YT97/1K/pD+zP4E/xD/8P6q/kv++v2i/Wj9bf2F/Yf9gP2T/aX9hf03/f381/yo/IX8c/yE/K38wfzU/PD8//z0/OT84/zx/CD9df3T/R3+XP6e/tH+9P4G//7+Af8V/yX/WP+g/8f/3f/3/wMAGgAyABQA4v/Q/8T/rP+B/0D/E/8H/wD/6f7E/qz+kP5Z/hL+zP2N/Un9CP3b/L78q/yZ/JT8ifxc/Cz8Cvzn+8T7lvtt+2P7b/t2+3n7e/uV+7D7sfuk+4j7dvtn+1n7ZfuP+8T77/sU/Dn8SfxP/Dz8Bvzs+/v7C/w6/IL8rfzV/PX87/zl/OH8xfy8/Nb88/wY/Sf9Kv1H/VL9QP0t/TL9S/1h/WX9Y/19/Z79kv1r/VT9T/1p/Yb9a/1I/UT9SP1a/Wf9Wf1Q/U/9T/1l/Yb9iv1l/Tf9KP06/Ub9KP0C/Qf9NP1l/Xr9aP1j/Yj9lf1+/Vb9Nv0n/Rf9G/02/VL9V/1L/Vz9jf28/cD9lv1o/V79cv1m/S/9FP0W/Sb9VP14/ZP9vv3Z/cD9nf2J/VD9EP3z/P38Lf1P/VH9X/16/X39c/1T/T/9Mv0Z/RH9I/02/Tr9Ov0j/RL9Ef0T/SD9Nf1Q/VT9S/1T/VH9Q/07/Tn9Kf0f/TT9R/1Z/WX9YP1i/V79Rf06/VL9a/1p/Wf9Zv1r/XP9Vv0+/UH9Tf1a/Vj9Zv2L/Zf9hv1g/Uf9Tf1I/S79N/1r/Zf9pv2Y/YX9fv1f/Sf9Ef0U/R79PP1h/Y79t/2w/ZP9g/1e/TD9C/30/AL9Gv0//XX9lv2c/ZH9g/1j/S39A/39/Cr9TP1c/W39cf16/YP9Y/0s/Rr9Hv0t/Uv9Wf1e/XL9ff1i/UT9QP00/R/9MP1Z/X39e/2P/j8B7wMqBlEIqAogDfQOsQ/zD5oQphEfE3gVohgCHP4eeCGPIx4lsSVZJcIkfyScJKYkdyQoJKkj3CKxIQ4gBx7aG9YZThgoFwoWrhQLEzYRNA8eDfkKzQjoBmUFMQRtAwYDlgIVAosB6AA0AIj/6f5d/iH+Cf6//W39Mf3j/I78N/zr+7f7kPuR+8b7A/wG/ML7V/vx+o76K/rX+cX5AvpY+p36sPq9+tH62/rX+t/6FPtw+9j7RPzH/CL9Jf3w/Nb89/wl/V39pP0K/nX+vf7V/rj+lv5s/j3+Hv4M/g3+GP4L/vv95P2i/Vv9FP3d/Mz82vzm/N/86/zo/NL8wfyh/H38efyR/K/84fwY/Uz9kf3H/cz9x/3u/Rj+Qv6F/t7+Nv9t/47/pP+p/5j/jv+N/5L/xf8KAD8AVwBEACkA/f+g/0r/Gf8I/wX/Bf8F///+6v6k/kj+5/2U/Vr9OP0g/Qv9//zq/Lz8g/xH/Av81/u4+7b7tvvK++j73vus+3b7Ufsy+xj7Ffsx+2b7mPup+7n72fvN+6P7mPub+5z7r/vH+/j7NfxN/E/8YPx2/HD8VvxN/GL8k/zH/PH8/vz8/Bf9Gv0D/fH80/y//MP8/fxa/Zj9qP2f/aP9mf1g/Rn98vzw/P78Gf1U/Z/90P3H/aX9mf2N/WX9Ov0i/RT9E/0Q/Rf9O/1e/XD9bv19/aL9rP2J/UX9A/3g/O78C/0S/Rv9O/1h/YX9nP2M/W39R/02/Vr9df1c/Tf9Mv1M/Wv9bf1H/Tf9Xv2E/YT9g/2G/X39b/1z/YP9e/1i/T39O/1n/Wj9Ov0f/TH9Vv1i/U39Rf1W/WH9XP1B/Sv9Ov07/SX9Jv01/S79Gf0P/Qj9Ef0f/Rv9Iv1C/WT9cP1v/Wf9T/0w/Qn98vz4/A79G/0v/Vv9d/17/W39W/1Y/Ur9Jv0Z/T79av1v/Wz9bf1g/Uv9Kf0V/SL9Lf00/U/9ff2v/bT9j/18/X39Vf0X/ff8BP0j/TP9Pv1N/XP9m/2b/Z79pv2G/V/9Pf0S/Qn9B/0B/Sn9W/16/ZT9pf2c/YP9X/0t/Qr9+fwM/Tr9a/2E/YD9jv2W/Xz9Q/0S/Q39Gf0q/TT9Uf2C/Zv9iv1q/Vn9Pv0Q/QD9Gf1E/Wj9dP16/X39bv1V/dP9AgCkAvYEcQckCvwMQQ9DEGMQpBBTEXQSZRQ6F7saQh45IZojbSVOJikmbiW1JI8krySpJJIkZCTvI90iEiHSHoocYhqAGAgX6BUHFf0TfhKSEGgOIwzVCY0HcAXNA9cCWQIdAgYC1gFfAcoAOACW/+3+Q/63/Vr9Bv3J/Kn8evxH/Af8zPvD+7f7mvuR+6r7wvug+0T71vpy+if66vm6+b/55/kT+lP6s/oS+0j7Wftd+3D7rPvt+yn8bfy7/AX9Mv1H/VT9c/2Z/b/94/0X/mj+rP7k/v3+3P6b/lP+Bv6//ZD9f/2D/ZP9nP2X/YL9Tv0C/cj8r/yX/IX8iPyp/Oz8G/0Q/eL8vfy4/ML81Pz2/C/9eP3E/SL+lP70/iL/Jf8s/zb/OP80/yv/Ov9Y/4D/tP/7/0YAZwBeAEUAOQAfAND/bf8p/wf/Av/6/tj+tf6M/mP+Qv4i/vD9qf1u/Ub9Lf0P/eT8pfxS/BX86Pu8+6P7lvul+8373fvQ+7D7kvuL+277LfsF+wH7G/tD+177iPu6+8r70Pva+9L7vPup+6n7xPvp+wT8Ffw+/HH8lPys/KD8e/xk/Gr8nfzH/NX86fz9/Bn9Kf0Y/QH9+Pz3/AH9Gf1N/Xb9e/2O/ZX9g/1g/Sn9Bf0H/ST9Qv1h/Xn9mP2y/a79lv1s/Tn9Fv0P/RX9Jv0//UT9TP1n/Wf9Tv1G/U39YP1o/Vv9R/1A/Tn9JP0m/Sf9LP09/Uj9a/2U/Z39dv1P/VH9ZP1k/VD9Tv1h/Wv9Vv0//Uf9TP1H/VD9aP2P/aD9hf1k/VT9T/02/Qv98vwC/TT9ZP2E/W/9SP08/TH9Lv0n/Qr9+/wX/UD9Rv02/Sr9Gf0W/Rn9Ev0Y/Sf9Iv0x/V39U/0K/c782PwS/TH9I/0g/U/9ff2E/Wj9VP1D/fr8vvzP/BX9XP1k/VP9ev3B/c39fv0m/Qr9Dv0W/RX9I/1T/Yb9mP2i/aj9hP0+/Q39Fv1B/V39Rv1F/XT9jP2E/V39Nf0p/Sb9Mv1R/X39mP2J/XL9aP1a/Sn9/Pz1/BX9Uf1z/Yb9p/2z/ZX9Vv0j/RL9A/33/Bv9Z/2U/ZL9jf2M/X79VP0i/Q/9IP0r/Sv9Pv1f/Xb9eP1r/WD9VP1K/U/9Sf0t/Qz9BP0f/Tv9iv2M/3gC6QQyB4wJDgxaDpQPyg8OEPgQVBJOFC8XmBroHbYg6yK0JOglHCaQJSwlWyWyJbglWCXNJBIk3SIeIQof/RwqG50Zbxh2F1UW2xT8EssQdw4XDMEJnAfUBZQEzwNWA94CWQLbAUQBmADm/0D/wv5k/hT+zP2N/T791vxj/Pb7tvuI+3L7lfvG+/j7GPwN/NX7YvvV+k/62PmB+WL5dfm4+Rz6dPrA+hf7Wftj+1z7bfuk++f7GPxO/H/8pfze/Cn9a/2B/X79p/0g/qD+3P7f/tj+1/63/nv+N/7x/az9h/2d/cP9tP2B/WT9Z/1l/Uf9Fv3i/ML8svyr/Kr8iPxY/FX8cPyg/OL8D/05/YT9p/2r/dT9/f0p/l7+cv6T/uT+Gv81/0r/T/9n/4v/p//I/wIAJwAxADgAHAD8/8P/cf9C/zf/K/8l/x7/A//j/sv+qP5c/gL+t/2D/Wv9S/0d/Qb97Pyz/Gn8KfwC/Or71/u9+6/7wPvV+9D7rftz+0H7Lfsk+x37LftD+1v7gPud+637qfuE+2D7avud+7j7rvu8+/f7RPxl/FL8OPxH/GD8Sfw6/Er8b/yV/LL83/wl/VT9Sf0n/RP9GP0G/cz8q/zO/B39T/1Y/Xf9ov2m/YD9T/0z/Sb9Gv0U/TD9aP18/Xf9cP1J/ST9FP0C/Q79Kv1G/X79r/2r/Yb9Xv09/RD95vzY/Pb8H/1Q/Xz9h/2B/XX9Uf0o/SD9L/1C/WL9ev1//Xj9Wf00/Rf9Cf0L/RX9Pv2P/dL93P2y/XT9Pv0Z/Qj98Pz//Db9Rv1I/XD9l/2N/U/9GP0i/UX9Rf0z/TH9Lf0a/QT99/z8/BH9Mf1F/V79df1g/S79/vzw/Pv8Af34/Pn8If1V/Xv9eP1Q/Sn9F/0N/RT9K/0n/Sj9Nv1O/Wz9Xf07/T79SP08/SL9BP0a/Vb9b/1q/W/9dP1h/Ub9OP0x/Q/96/wP/VP9j/2p/aP9pP2j/XX9J/0D/f38/fwd/Uj9hP3H/c79lv1y/V/9JP3q/M786fw5/XT9jP2Z/Zv9iP1a/Sv9Cf34/Pr8Ef0y/VT9dv10/Vv9Ov0h/Tr9W/1X/Uv9VP1z/XX9Sf0M/e/86/zk/AL9Q/2M/bL9nP15/W/9ZP03/ff82/wB/Tz9Xf10/dn+nwEsBF4GsghHC98Nuw9xEMQQaxFkEuETNhZWGa0cuB9iIqEkTyb8Jq0mIibsJQsm/yWRJfskXySDIxwiSyBRHkocZxrtGMsXqBZBFYQTeBFtD0gN8AquCKkGGQX3AyQDiQIgArEBHwGnACwAsf8u/4b+D/7c/ZL9LP3O/Gn8CPy1+2j7RftP+2n7gfuj+9H74vu0+0D7tPoy+sf5d/lL+Vf5kPnk+Uz6tfoK+0H7Xft/+7v7/fsf/EH8dvyx/OX8/PwL/SX9Tf15/cL9Ov6r/uv+AP8V/xr/3/5q/vv9u/2b/YH9Zf1o/X/9jP16/Vv9TP0t/Qn95/zV/MP8n/yD/HX8bfxk/Hv8ovzU/BL9NP1q/b798v3//Rv+Uf6M/sL+0f7r/iH/Of81/0n/fv+w/83/4f8AADwAWQA7ABYA+P/L/4T/Qv8a/wn/6v66/qL+q/6r/pP+af4u/uv9mv05/c38fvxR/EP8VPxe/GL8XvxM/DD8//uw+0r7+vrx+hr7RPtb+2X7dvug+6r7bPs1+yf7J/s3+1L7bPuU+8r78vsJ/Br8D/zc+8H71fv6+xr8MPxM/IX8u/zU/NP8uPyu/Lj8u/y4/LX8wPz5/Eb9bf1u/WT9UP0z/Sf9LP0n/RD9EP0+/Xr9rf3F/cL9tv2Y/Wj9Nv0X/Qv9DP0b/Sz9Tv15/Y79lv2Q/Xf9T/0t/Qz97/zr/Pr8Ff00/Vn9bv1q/Wb9Vv04/RD9+fwA/R/9U/13/ZD9pf2S/V/9IP36/Pb8+vwP/T39eP2t/c/9wv2Q/VT9Ff3u/Nv89fwt/VX9cP1//YT9fP1p/Tj9Ff0M/fn8/PwV/Tn9Wf1b/UD9Nf03/RL97vzz/Ab9H/0c/Qf9Gf1K/Vr9R/01/SD9D/0U/Rf9DP0T/RD9BP0L/Sn9Qf1I/Vn9bP11/Xn9YP0k/Qf9/fzl/OP85/z4/EH9mv3J/cD9nf1u/T/9I/31/NL84PwJ/Tr9Y/2A/YH9cv1f/Tj9Jf0p/Sz9WP2R/aH9i/1b/Sf9CP0H/QH9/vwi/VD9iP24/bv9mP1k/Tr9J/0Z/Qn9HP0z/UH9U/1E/Sb9F/0j/TH9Q/1p/Xz9fP18/XL9VP0l/f384vzh/BL9SP1W/Vn9df2L/XP9Tv1H/Uj9R/1E/T/9R/07/R390v1cAC8DeAXWB3sKTQ2VD5sQwhALEdoRLxNiFWsYvxv1HschRSQ7JiQnDSd/Ji4mTyZoJiUmoyX9JDIkByNFIRof6xwFG5IZdBhVF/8VahSHEmcQEA6TCxsJ3gYtBRsEbgPsAnwCHQLGAT8BcwCT/9X+S/7x/bT9iv1j/R79tvxS/PP7ivsl++/6D/uC+/H7EPwE/NL7W/u++hX6XPnO+LH4/PiJ+Sf6rvoM+1D7bPtR+yv7DPsM+1H72ftw/NX8Gf1O/WT9Yf1U/V79kv3p/VP+uv4Z/1f/Mv+8/k3+8/2t/XT9WP14/a79yf26/aX9kv1Z/e78fvxd/Hn8kvyV/Kf8xfzJ/Lf8lvyS/LH8zfzi/Bn9jv0N/ln+ev5//o3+sf7K/rv+xf77/lT/uf/u//3/BAAUACIAHwAWAPf/zf+2/8P/4v/B/3v/PP8O/wT/4f6Q/mH+WP4//hX+5f2o/WH9Iv3k/J38ZPw8/BT8APwQ/BT8APzj+7v7ovuV+3r7TPsn+xD7BPsT+yj7OvtP+2P7gvuo+7D7n/uX+677yPvH+6H7d/uE+7n75/sF/Bf8Lfxi/J38vPzH/Ln8pvyc/Jb8ifx0/HT8gvyz/PL8FP0f/TT9WP1x/Xr9Zv08/Rj9FP0w/U/9Wv1R/UD9NP1N/W39YP1K/Uv9Xv2A/ZP9iv1w/V/9UP0z/SL9E/0H/Qv9Gv01/Tj9KP0k/Tj9XP1b/VP9WP1b/V79R/0m/Rv9G/36/Nz89Pwh/U39dv2O/av9zf24/Xb9Tf1G/Tn9D/3Y/NL8B/1D/Wj9hv2p/b/9qv1+/Vz9PP0L/dH8rvzW/C79aP2B/Yb9gv1q/Tj98fy9/Lj8zvwV/Vb9f/2U/YH9Xv02/fn8qvx4/Ib8zPwr/Xr9lv2Q/Xb9Uv06/Qj9y/yv/Lj89vw4/U39Uv1N/Ur9Vf1Q/Tj9Hv0U/RT9Mv1Z/WD9Rv0m/R/9LP05/TP9I/0t/UT9Z/2V/Zb9W/0f/QP9Bf0U/Q39DP02/Wv9lf2Z/XP9QP0E/eD81vz0/Cv9UP13/Zv9pP2K/U39Dv3r/Nn80vzu/Cr9ZP2L/Yf9ev1z/Un9GP0B/f/8Bf0O/SL9RP1Z/Uj9NP1H/Vb9MP0K/RD9IP0r/Tn9Sf1Y/Vf9SP0q/R/9H/0R/RL9Gv1z/Xb/WALYBE4H7AmDDL4OExCPEPsQtRG+EpEUeRcAG2ceYiH1IxombyeIJ/ImdiZvJpYmYybqJXkl7CTdI0oiWiA0HikcXxrvGM0XmxYGFRET+BDVDosMEAq6B+gFngS5AwwDhgIeArYBOwGjAO7/Ov+c/g3+tP2H/U398/yP/EL8Efzk+6T7cvtn+377k/ub+6f7kfs3+7X6QfrV+Xf5MPkS+UT5sPkc+nb61/os+2D7Z/tV+1b7ZPt7+6j7EPyN/Of8LP14/cL98v0O/hL+If5M/l7+d/6h/rT+p/5q/i/+Hf4B/sT9hf1k/Wz9c/1V/Sn9DP0M/Q797vy9/Jb8efxn/Gv8c/xz/Hn8k/za/E39n/20/bn9yP3s/Sn+Zf58/oT+rf4K/2T/if+B/3T/mv/Q//T///8DACkATAA9AAgAvP9t/0T/J/8E//v+Av8E//3+4/63/nP+Bv6M/TT9Cv30/NP8q/yf/Kb8gvxB/BT89vvX+6j7ePtw+4b7gvt6+2j7Svs4+yH7Gvsk+yj7I/sn+0n7c/um+7f7t/vP+9j70/vJ+677mfu0++H7D/wv/Db8T/x7/KH8rPyb/Jn8svzP/Nr82fza/OD84fzN/M383/z7/B39JP1E/XL9dv1r/WD9Yf1o/VL9Lv0o/Tn9Ov0z/Tj9SP1c/XL9kP2S/X79Zv1S/VD9Pv0R/QP9G/03/U/9W/1q/XL9Vf0Z/ff8A/0F/fH88vwo/XP9nf2a/Xr9Yf1V/TL9+/za/OT8/Pwd/U/9df2E/XT9Zv1p/XL9aP03/RL9Iv1K/Vn9Pv0P/Qv9L/03/Sn9Iv0m/T79T/1Z/V79Vf07/Sn9OP0p/e/8ufyu/Ov8Jf0c/Qf9IP1O/WX9Tv0r/R79Df38/P78AP3w/OX8+/wV/R79Dv38/BX9T/1w/XP9Zf1W/Uv9RP04/Rv9Av30/Pf8Df02/VT9Xv1l/Wf9d/16/Uv9I/0p/UL9S/09/Sv9MP1L/Un9Kf0k/Sj9Hv00/VX9eP2d/Zf9fP1k/T79Gf0B/fL89Pz//BX9Rf15/Y79if19/Vv9N/0d/QH98vz9/A/9G/09/Vn9W/1I/S/9HP0n/UX9Sv1C/Tz9Qv1L/U39Lf0L/Q39Fv03/Wz9gP16/X39Zv1B/Sj9AP3W/OL8HP1V/Yb9tP5nARgEUgabCBcLsA2uD34QxhB9EbMSUxSfFosZ2BwSIOUiSyUYJ+kn1CdXJwkn/CbSJjkmdCXVJBgkEyOGIZ4fuR3sG0AanRj6FkIVdhOZEZgPfw1mC0UJPgeEBSMEFgNYAssBZAEqAe4AdwDl/zn/gf7f/Uv94Pyc/HL8Wfw0/AD81fuk+2v7Svs3+zv7V/td+zD74fp1+gv6oPk6+QH5DPlT+cH5P/qk+un6HPsz+z37Uvt6+6j7zvsW/H785fw6/Wj9g/2q/dH99v0f/kX+hP6t/qb+s/7I/rL+i/5M/u39u/2p/XT9R/1G/Uj9Q/00/RL9D/0K/c38n/ye/LD8pvx8/HT8oPzT/Oz89/wZ/WP9sP3u/Sf+Xv55/nP+fv6t/vf+Iv8t/2P/tf/j//b/AgD///f/7P/k/93/vP+c/6f/uP+j/4P/Uv8c//7+zf6J/kv+Bv7O/a79oP2V/W79Kf3Z/KD8cPw3/Av87vv4+wn88fvY+7v7f/tA+wr79PoF+xr7L/tj+6H7ufub+177Hfvq+tf68Pou+3n7uvv5+z/8Uvwd/OD7ufue+6D7vvv2+1j8svzL/Mv81vy4/Ib8dfyK/LT81fzx/Br9Sf1I/SH9C/3//Pn8+fwC/Sb9Uf14/Yv9hf11/Vr9Kf3//AL9EP0b/TH9QP1b/Xn9kv2E/V39N/0F/ej86/wG/Tb9Wv1X/UT9V/1t/Vj9I/3x/Pf8Hv0z/UH9W/2A/Yj9Xf0p/RP9Gf0Y/RD9Iv1K/W39a/1e/Wv9bf1S/SX9Bv0H/Rf9H/00/VX9U/0+/SH9B/0D/QT9/vwN/Tn9Zf2F/YP9Yv0v/fL8vfyJ/Gz8ivzo/F39rP3D/cT9nf1F/ef8nPxz/Gr8hfzP/Ef9rP2//Yj9Pf3+/M38rPyX/LP8DP13/bT9p/1z/S/97vy6/Jv8nvzP/Bn9b/3J/fr94v2P/Sv96PzL/Lr8tfzS/Cb9k/3G/b/9nv15/Uv9Cv3n/Of8+PwQ/Tz9fP2s/aH9ZP0m/f/86fzW/OH8EP1W/Yb9pf2x/Z39f/1O/QH9wvy4/M789fwr/Vr9g/2q/bf9pf1u/Sj9+vzj/NT8yvze/Bj9Wv2C/Zb9j/1s/Tf9Af3i/N386vzz/Af9Lv1i/Yr9bP0r/Qr9B/0W/Rf9CP1x/bP/pgIHBXcHFwq5DA4PdRD1EGIRJhI2ExcVDBiFG+weBSLHJPkmQihtKMQnGifFJp0mfiZFJu4leSWsJEcjTiHzHpMcexrMGGkXChalFBATPBE0D/AMkQo0CAgGWQQ+A4ICBgKuAVkBDwGwACMAdv+6/g7+jf0k/cP8bvxB/DD8AvzQ+6n7hvtp+077O/s1+y77CvvV+pj6QfrV+X75Svk5+UX5Yfmc+Qr6hPrE+u/6Ivte+7D74Pvm+wH8TvyP/LX84vwh/V/9qP0I/mT+u/7d/tj+3P7N/pn+WP4f/vP96v3y/fn99/3f/Zv9a/1h/Sj94fyq/Kr82Pz8/O/8vvyW/Gr8Uvxg/HT8kvzK/Aj9YP3O/Rr+Kf4f/if+Qv5z/ov+iP6t/gD/T/+J/7L/zP/1/yIARwBLADMA8P+l/4//jf95/17/Q/81/0T/W/9I/wb/rv5M/vj9uP1w/Sj9DP0M/Qz9Bv3r/LD8XvwF/L77jfto+0D7Ovt8+7v72fvJ+5X7a/sy++n6z/ra+uX67/oh+4D7xfvT+7r7p/um+5n7eft++6L7rPu7++f7GfxK/FP8OfxC/Gb8cPx7/H38ify1/M38yvzD/Lz8w/zQ/OH8CP0a/SX9Sf1e/WP9XP01/Q39/fwB/R79TP1R/Uz9af2G/Yf9Wv02/Sj9KP0s/S39Nv0//U/9Vf08/Sf9Iv0K/f78EP01/VH9RP1G/WH9a/1B/ff80fzb/PT8DP0o/VD9e/2R/ZT9d/0+/fz83/z5/BP9Lv1Q/Xf9qv22/Y/9Rv38/NL83vwB/Rv9Pf1g/YP9i/1z/T79B/3j/Mj8u/zT/Ab9I/0x/Tr9Rv1O/Sn94fy//Nj8+vzw/OH8+Pwl/Uv9Uv1C/S39If0F/dz80/zv/Aj9EP0z/Vr9dv14/Uf9E/3+/On81Pzi/A/9Rv1x/Xn9aP1g/UL9/vzW/Nf86fwV/U39gv2t/a39f/1E/RT97/zV/M78/PxL/YD9lP2S/YD9Wf0Z/eL84/wP/R/9Jf1T/Y/9u/2V/Sn95fzb/NT84PwD/S39XP1n/W39iP2B/U79Cv3m/PH8B/0C/fz8IP1X/Wn9Tf0p/SX9Pv1L/Tv9MP0w/S79Jv0b/ST9IP0P/QX9B/0v/Vf9Yv1v/Xr9Y/0+/SL9BP0F/RX9Mf7nAKMDJAbYCJwLUA5QEBQRNhGrEZASFxSZFswZKB1vIIEjGSbfJ4coNCiIJyUnICcZJ9ImYSbdJSAl7iMnIvIfpR2IG8IZXxgWF7IVIhRYElsQIQ6xCygJ3wYJBaIDxAI+Au0BxAGSAS8BlwDW//r+Jf57/fv8m/yD/Ib8ZfxJ/DX8D/zQ+3L7E/vm+ur66Prl+uD6rfpj+gX6svmO+Wj5R/lL+X755vlS+pb6vfrg+hL7Rvt2+8D7/vtG/KH87fxL/Yb9g/1//Yv9xf0o/mH+bv6M/sf++v4G/8/+Yv7+/br9rP2p/Yz9ev1h/VL9W/1A/ff8uvyP/In8q/zA/Mf8xvy6/MX8y/y8/LT8ufzb/C/9jP3a/Sn+cf6i/q/+xP7Z/u7+D/8j/0j/jP+4/8z/3P/j/+n/4//L/9D/3//d/9P/yP/E/6j/Wf/4/rr+eP4+/if+Ef79/eT9xf2p/YT9Of3e/Jb8X/xK/EH8J/wG/OH7uvuV+1L7A/v1+g77N/tl+377g/t4+1f7MfsH+8z6qPq++hX7ePur+8P72vvl+9X7qPuE+4n7qvve+yb8bfyY/KX8lvx+/HL8Xvwz/Cz8afzD/AP9E/0W/S79RP0x/f384Pzs/Ob80vzh/B39Uf1l/V79Vf1u/XT9Sv0y/R39Cf0K/Q39JP1f/Yr9i/2F/Wf9P/0f/fn87Pz7/Bj9Of1K/Uj9QP1G/Tf9/fzP/Nj89vwX/UX9c/2X/Yz9Rv38/N780/zJ/NH88Pwo/Wb9mf2+/cT9mf1U/RP92/y0/LP85fww/WT9av1v/X79cf1Q/R79+/z3/PT8+vwO/R79Jf0u/Rr9+Pzu/P38Hv1M/Wf9Wv05/Qf91/zA/MX80fzU/O/8Lf1r/Yf9av0o/fD83/zQ/LD8sPzQ/Bj9Z/10/VT9Mv0H/QT9Gv0P/QX9Af0D/SH9Uv1i/Ur9I/0E/Rr9Rf1M/Tv9L/0z/Un9Rf0m/ST9Mv01/T39Qf0r/Rb9F/0o/UH9Uf1S/VP9Wv1e/UL9G/0B/e388fwV/S39Lf1T/X/9iP12/Un9Df3u/PT8C/0Y/R79Kf05/WH9hf1z/UH9Iv0W/Q/9B/37/Pn8GP1G/Wr9gf12/Vn9Q/0x/Rz9+vzW/Mn88/w3/Vb9Y/1o/Vv9Uf1B/RP96/wh/RH/HwLIBDUHzwmvDGgP8RApETQRzxH8EuIUvhdjGygfgCI4JV8nvijmKA0oIifXJvwmCSfQJpAmUiaVJfIjsiE3H9UcwBr1GJ4XkxZpFdQT5hG9D1ENvwoqCM4FBwTrAlMCHgILAu4BqwEhAUUATv9+/sL9KP3R/KL8l/yV/HL8NPzv+6L7QvsL+w37Kvtf+277UfsS+4766/lX+e74xfjY+An5cPkC+of62/rq+t365vr1+uv6DPtg+9f7avzb/Bf9R/10/Yf9rf3j/Rr+Tf5w/qn+8P4c/wD/q/5c/if+AP7I/Zn9kP2b/aD9m/2H/Wj9RP0V/eT8tvyN/HD8a/xz/IP8nPyk/Kb8sPzO/BH9Zf2p/dT9Bv5E/nn+iv6F/of+nf6//t7+Ev9t/9P/EgA4AFQAWABBABIA1/+b/3T/XP9W/2z/d/9k/1L/Pv8N/9b+i/4p/uX9vP2W/Wz9Pv0V/eP8rPyM/GP8Kvzz+9P7zvvW+837sPuL+2j7Ufsr+wD73Pq4+rb65voo+2L7iPuZ+4n7Y/s1+/v61/rj+hz7afuv+//7PvxI/DP8Cvzl+8z7vvvU+x78ffy7/Nn86Pzg/Mv8sPyc/Jr8t/zl/AP9H/1A/U79QP0s/R79H/0p/ST9J/1B/V79Wv1N/Tv9I/0k/Sf9Lv07/U79Vf1I/T79Pv05/TD9G/3x/OP8/fwK/R39Pv1H/U79SP0v/Rz9JP0Q/eX84/z4/Br9K/0s/Uj9bP11/Vj9J/0V/RP9Cf0N/Rr9HP0i/TH9SP1m/Wj9Uv1C/Tb9Nf0m/RD9B/0D/Qb9Df0e/TL9NP0q/Sz9P/04/Rn9B/3//A39H/0j/S/9Kf0T/QX99vzs/Pv8Cv0R/Rn9H/0u/U39Sf0h/Qr97PzY/N384vzr/O78+fwI/Rn9Kf0b/RP9FP0W/R/9Hv0X/QT97vz0/Av9Ff0I/fr8Iv1W/Wv9b/10/Xf9Yv08/RH9B/0Y/S39Kv0v/WH9hf2O/YH9Xv1J/Tz9Jv0b/Tr9Xv1h/Ur9Ov1L/WL9Tf0V/ff8BP0c/S/9Mf01/UP9TP1o/Xr9df1X/S39/fze/OL83vzU/Or8NP2P/cP9vP2S/Vv9KP3w/Lj8ovy1/Oz8PP11/Yf9lf2M/Wb9Kv3j/LL8rfzd/BP9L/1J/VD97v1mAEMDngX9B40KWw3ED/QQJhGEEW8S0xMOFjQZ0xxJIGojHyYdKAUpsCjcJ2wnaCdxJ00n9iaFJvIl2iQlI/ognx5uHJsaOBn8F4kW2RTzEsoQdA7vC28JSweWBUcEYQPaAnkCGQKgAQYBYwCb/7/+Fv6g/UX99vzM/LL8fvwo/Mv7qPuN+0P7B/sO+0b7Yfs2++v6n/pC+rr5NPnp+Nv4//g++ZX5Ffp8+p76mvqy+vn6J/tC+3L7xvse/F78lvzF/Pn8M/1w/bX9H/6I/s3++P7l/qz+e/5E/h/+Ef4N/hr+M/5A/iH+4P2Y/WH9I/3d/Lf8tPzL/OP85/zh/Nr8x/ye/H/8kPyq/MH85fwX/WH9p/3D/eP9If44/kv+jf7d/jf/dP99/5D/qf+j/4b/ff+W/8L/7/8MADsAXQBbACoA4P+S/zj/7P7A/qv+s/68/qL+bf4k/ub9rP1b/Qb90vy+/KT8f/xa/C38BPzS+437bftt+2H7VPtK+0f7NfsE+9760/rh+hT7TPtn+3f7ePtd+0r7PvsS+/H6/fow+4P70/sD/CX8UPxi/Eb8GPz3+/X7+/v7+wv8PfyG/Mn86vz4/Ar9//zb/Ln8svzL/Ov8Bv0Y/TX9W/1g/UH9Ff34/Pf8/fwG/Sv9ZP2P/ZH9fv1n/U/9Gv3x/PL8A/0n/UH9TP1O/Un9Tv1S/Tj9Df3y/Pf8GP07/UX9SP1V/VH9Qf0w/SX9Hv0R/e/80/z8/ET9Zf1l/WP9cv1//W39Pf0i/ST9IP0R/Q39Hf0v/Tr9Ov01/T/9Tf0//Tj9S/1S/Tj9AP3f/Of8A/0T/Qb9Df0s/UT9Q/0q/Rn9AP3h/Nn84Pz8/A/9Cf0M/RX9Gf3+/Mz8xvz3/Cf9I/0S/RD9CP0M/QP92Py4/Lz82PwR/UL9Tf1T/Vr9Vv1A/RD95vzi/O/8+/wf/UD9Rf1B/U39a/1x/Uf9D/33/Av9Lf1J/Ur9N/0h/RP9Ff0Z/SP9J/0j/SH9Mv1Y/WP9Rv0U/fD88fz8/Ab9F/0y/UD9QP1I/Uz9Pv0Z/QL9CP0a/Sb9H/0c/Tz9Vv0//Rn9D/0e/Sj9Gv0b/T79T/1M/Tv9KP0l/Rn9Cf0B/RX9LP1C/Vj9Sf07/Tv9Kf0P/QP99fwD/R/9KP00/Tr9L/0Z/Rz+1wC7AzkGuwiAC2AOeRA8EUURpBGqEjYUlxbdGaQdQSFUJOMmsChaKe0o+ydeJ14nbScjJ6YmQSbBJbgkASPLIIcedxyYGuIYcxcRFloUUhIOEMwNnAtbCTIHcAUsBFADwQJGAsUBZQHrADkAff+5/gj+fv0X/cv8sPyb/FP8Dfzm+8X7mftd+yX7/Pru+vj68fq7+mH6+PmX+VH5D/no+A/5ZPmz+fT5Lvpw+p/6ufrg+gv7Pft8+8j7Mfyg/Ov8Ff09/Xj9tv3v/Rv+TP6V/r3+vf6s/pb+of6s/of+U/5J/kH+Df60/Vj9MP0f/er8tfzJ/A39Ov0z/RL98Py0/HT8QPwn/Dr8YvyT/PD8Yv2u/eH9//0a/j/+Wv5i/nX+qP7l/ir/Y/99/4P/lv/R/wYABwDk/9X/2//b/97/1v/N/7n/k/9x/0z/Iv/O/mn+J/4H/vn96f3M/bP9mv19/U/98Px3/BX81Pu0+7T7w/vN+8/7yPuu+5L7Y/sR+7z6jvqq+uv6HvtK+2D7cPuD+2/7Ovvr+q76vvr8+k37ovvf+wz8Ifwm/Ar83vus+4f7pPvt+0H8hvyw/Nj88PzX/KH8f/xt/Gv8lPzH/Pv8O/1U/Uj9Qv07/Tj9H/0G/Qn9JP0+/Tz9Qv1X/WX9Xv1Y/Vv9V/1I/TX9LP01/SX9+vwI/UD9VP0+/Rb9E/0s/Sb9//z0/Ar9Ff0i/S/9I/0V/Qb96/zx/Bf9G/0I/Qr9MP1e/XX9V/0g/RP9K/0r/R/9HP0h/TL9R/1I/Uj9Tf0w/Rj9K/1R/W79dP1Y/Tz9N/0i/fD8vfym/M/8Iv1P/VX9bP2L/Yb9T/0F/cr8s/y3/L78yvz2/BP9Af3//Br9JP0c/Rv9If0r/TL9D/3Q/Lj8rfya/JD8qvzr/DL9Z/16/XD9TP0f/fL81vzj/PT8//wI/RH9Jv04/UH9M/0e/SH9Jv08/Vz9bf1u/V79Rv0y/ST9Dv0B/Q39FP0U/Rn9Lf1W/W/9bf1z/Wf9Qv0h/RH9Cf38/Ob86/wR/TH9Sv1H/Tz9Sf1D/ST9Bv39/Az9G/0p/UH9Uf0//RT99fzr/Ob80vy//OT8Jv1m/aD9sP2X/Wr9Kv3T/Jv8gfxx/Jn88fxD/YX9tP2r/Yb9cv1F/QL91vy6/M38F/2w/pUBPgSpBkoJFQzTDscQhRHWEX8SfxMVFYQXrBohHm8hXiTjJqsoVykcKZQoVChPKPonTie0JkMmoCVPJFIiHCALHiMcTxqqGDIXthX5EwASABDxDaMLKwntBjIF7APcAv8BgwFuAWUBCAFgALH/Bv9S/qj9FP2o/Gz8TPw9/C38I/zz+5n7QPvz+sr6vPqj+on6gvpx+i76xPlh+R35/Pjw+P74M/mM+eX5N/qX+t76C/s3+177kvvg+yn8Zvy4/Pz8Lf1w/cH9AP42/mP+k/7c/gH/9/7Z/rP+dv40/gn+7v3Y/db93P3c/ej92P2G/Sr94/y6/JL8aPxu/Jb8vPzW/N783vze/MH8p/zK/B/9b/2l/eP9PP6B/nr+Vf5i/pf+wf7x/jv/oP/1/xEAGQAhABQA3P+c/4H/nP/E/9T/yf+s/5D/b/89//f+vP6a/n/+Uv4S/uz9zP17/R392vyy/J78gPxc/E/8R/wU/MD7jfuH+2/7Svs/+0b7Tfs++x77//rw+uH6y/rU+gX7LvtF+1j7aPuC+4j7cPtS+037bvuK+5D7mfu8++P7Dvwv/EP8Z/xv/Gf8a/xn/Gf8bPxv/Ib8vPzu/A/9Iv0n/Rv9+Pzi/NX80Pzr/CD9QP1E/WP9fv2E/WT9KP0W/Rr9Gf0Y/R/9Of03/RP9Ef0u/Uj9UP1D/Uj9bP1w/Ub9EP3a/Lv8vPzN/Pj8Ff0h/U39df16/Wn9Jv3y/Az9Jf0q/SX9Dv34/Ov88vwK/RX9HP03/Wr9sv3j/bT9Xf0w/Qr90vyl/Jv8u/zs/CD9Uf16/ZP9hf1o/Vf9Tf0t/fv83Pzc/Oj83vyu/IX8nvzg/P/8D/0v/VX9fv1//VP9KP35/Kr8c/xo/Gf8dvyY/N78N/12/YP9gf2I/X39Uf36/Kz8kfyb/LX8zPzp/BD9Mf1Z/Xf9df1U/Rj98fwX/T/9QP0p/RP9Kf1C/TL9+fzU/OX8E/1D/WL9e/2O/Zj9hv1i/TT9+fzO/NP87/wN/Sn9Q/1Q/Uj9Tv1P/Tn9Fv0B/Qj9Lv1F/SD9Dv0S/QX96vzf/Pf8H/1C/UP9UP1x/Vf9IP33/Or89/wK/SH9Ov1e/W79Sv0Y/fb81/zD/NX8Ef1K/Wv9hf2D/XP9R/3t/KD8fvyW/OD8Gv09/Xv9Rv9BAscEAwd1CS0M2Q6kEF0RxhF9EokTOBXoF0Mbtx7mIeEkhidAKbMpJCl1KDcoKyjUJzAnmiYqJn0lMSRNIh4g/R0QHGMa5BheF8MV+RPyEcYPWQ2/CloIcQYFBfUDLAOVAi0C3AF6Ad0A/v8P/0v+wf1+/WH9Kf3Y/Jj8XfwM/Kz7SvsM+wT7BfsR+yr7LfsI+6/6QvrS+Wr5D/nN+Mj4+PhA+Y751/kg+mn6nvrG+vH6Ivtb+4f7vfsU/ID87fww/Vf9lv3Y/Qr+Nv5Y/nf+mv6u/rT+0/7i/rX+bv49/iH++/3A/X79W/11/Yj9WP0v/RL94/y3/Ib8aPxb/Fj8aPyd/Pr8JP0U/RT9OP1T/Uv9Pv1U/Zr99f1F/pT+7P4+/3z/lP+Y/5j/h/94/3z/kP+7//D/+/8HABoABQDY/5f/bP9g/0z/Kv8U/wb/4P6a/kr+9P2Z/U/9Ef35/Af9Cf31/NP8p/xv/Dn89fuY+z77EPsI+x37Mfsv+y37MvtI+0f7K/sW+wX78frn+u76+/oC+/P6+fo7+3f7i/uO+6D72fv5++v74vvt+/r76/vj+wD8JfxB/En8XvyU/Mr83fzj/Pr8HP0S/ef8xfyz/ML80vzZ/P38PP1i/W/9eP19/XP9R/0V/Q39MP08/Tb9Ov0+/VP9WP06/Rn9Fv0m/Sr9I/0r/T/9Of0l/ST9Mv1B/Sr99vzn/Af9H/39/NL82vwN/UL9YP1j/W39h/16/Uv9F/3g/LP8nPyp/On8Mv1c/XX9mv3A/cH9iv0v/eP8wvyw/KH8pfzQ/Bn9Wf12/Xn9bf1J/Sr9Bv3W/Mb8xvzY/Ar9Ov1K/TX9Ev3y/Nb8vPyy/Lv85vwz/WX9Zf1b/VD9Nf37/Lb8ifyF/Kz87fw0/WP9WP1K/Vj9T/0d/cv8n/zS/Af9G/01/UP9Uv1R/TH9EP3v/Mb8tfzf/CT9Yf1x/Vj9W/11/Wv9Jv3R/Kr8yvwF/Sz9P/1f/W39W/1M/S79Bf3o/Ob8Bv1A/X39gP1V/S/9Df3p/L78kPyH/Mz8Nf2L/bf9tP2c/W/9Iv3V/Jz8ivyd/Mf8Ff1f/Yz9of2a/XT9Ov0E/dT8vfzT/P38Nf1s/YD9cf1L/Sj9Bf3i/Nf8zvzl/Bv9S/1//Yr9Yv00/Qv92/wB/e7+6wGcBC0H9wn6DKIPKxGLEbwRcBJ0ExMV1hd3GzwfmCKAJewnfinfKSwpYSgjKAMomycSJ6EmSyapJV8kcCI5IBMeBRwoGo8YCxdpFZITkRF1D0kNCAuuCJIG/wTjAwUDWQL3AbEBVAGqANb/Kf+Q/gD+mP1L/Q390vyJ/ED89fuP+yn75PrO+vr6Kfs7+zv7FvvJ+lX6svka+b/4m/iy+On4R/nB+R76Vfp3+pf6s/rJ+u36KvuU+wn8afy1/O38F/05/Vz9i/3Y/Sn+ev7C/vH+Dv8D/9L+i/5P/hb+4v3S/eb9//3q/cX9pP15/Vn9Jf3n/Lf8i/yD/KH8w/zM/LL8mvyj/M387/wD/Rz9Rv2R/dP9Af4m/jL+N/5V/pT+3/4m/2D/mf/M//r/BwDL/4f/df95/6T/3f/2/wIAEwAXAP3/s/83/8D+ff5u/nr+bP43/hj+Bv7c/ZH9M/3c/Jz8dPxf/GX8Wvww/Pv7zfug+2P7I/vi+sD63foF+yr7TvtU+0/7Qfsw+xP77/q7+qr61voB+zP7avuP+6n7tPur+7P70/vR+7771PsE/Dj8UPwt/BH8IfxD/E/8Sfxh/Kf8Cf09/Tf9G/3+/OP8v/yi/I78lvzR/AX9L/1l/Y39nf2R/WX9Of0l/RP9Dv0I/Q/9Iv0h/S/9Ov03/T/9Q/1L/Vn9Wf1G/ST9//z7/Af9+vzo/OL88vwi/Uj9S/01/RX9BP0d/UL9RP0m/Qf9Df0c/Qr9+fz//CH9Of00/Tj9Vv1Y/T39Jf0g/Tf9Pf0t/Tf9VP1H/RL94/zT/Nr81fzW/Br9dP2h/Zf9X/00/RX96fy0/IX8dfyO/ML8Av06/U/9Nf0M/RL9J/0c/fz89fwC/RH9C/3Z/Lv8wPzV/OD83fzs/BL9M/1I/Vn9Vf1J/Sj9B/0B/fr86fzP/Ln8uPzZ/Ab9J/1E/XT9j/2E/W/9UP0g/ff81vzD/OT8A/0R/Sv9Uf1s/W/9Wf03/TH9Ov0x/Rv9DP0D/QX9G/0h/Sf9Of00/Tj9Sf1B/TP9Fv33/PP8EP06/Ub9MP0t/Tv9Lv0R/fn89PwO/R/9Hv0z/T79MP0k/Rb9Df0I/fH87fwf/V39Yv05/Qr97Pz8/BP9Fv0Y/SH9Mf04/Tr9Mv0d/QH96vzu/AT9b/1+/2IC7wRjB/YJwgw+D6UQHxGlEZcSyhOTFWUY+RuaH9AiiCW5JwgpNymrKEYoQSg9KAwonScoJ78m3yVQJC0iwR96HZUbCBqmGEMXvhXvE9sRpg9XDfEKkAhyBsUEsAP6Al8C6QGZAU0B0AAWAE7/qP4n/qr9K/3C/Hr8QPwH/Nj7qfuB+2n7QfsM+/L69frw+sr6bvoD+qv5V/kL+cf4r/jS+Av5Tvmz+Rv6d/rC+tr69fov+2H7h/u++wH8V/zC/A79Q/2O/ef9Nv5t/nf+hf6r/sn+2P7I/rf+l/5o/kn+Ff7e/bn9hv1f/WD9dv1x/Ur9Jv0N/fL8s/xu/FT8afyK/Jb8m/y1/PL8MP1H/Un9U/1n/av9BP48/m3+mv7P/h//YP9v/2z/dv+K/6D/qf+m/6T/t//j/wgAJgApAAAAzv+5/5z/RP/P/mf+RP5R/kP+KP4Q/uv91P24/Xj9Mf3e/IH8QfwU/PL74/vU+8D7tvvF+7r7hPs++wH79vr9+un65foB+zn7cft0+0z7Gvvu+sf6wfra+gT7S/uP+7b72Pvy+/b7yfuL+3T7jvvB++37HfxP/G38e/yC/H38d/yF/Iz8oPy+/Mb82fzy/Pj8+PwR/ST9HP0c/SH9Pf1T/UT9NP0r/Tb9UP1N/Un9Sf09/S79Gv0i/TL9Ov0+/UH9TP1V/Vf9Nv0E/fb8Bf0O/Q39CP0O/Sv9Qv0//S39F/0c/TP9Nf03/TX9Hf0J/QT9AP37/AH9Cf0s/Wj9h/19/Vj9Q/1A/Sb99/zK/Mj86PwK/Tb9Zf19/XX9W/1P/Uj9L/0L/eT8yPzK/O78GP0j/Rf9Cf0J/Sr9P/0z/SD9H/0c/fr8zPy1/Mf8y/zJ/PT8N/1h/VD9N/0y/Sr9/Py6/KT81PwZ/SL9E/0k/Sn9IP0I/eH84/wC/Rz9Pv1e/VD9If37/OP81vzS/Nb86/wY/V/9kv2D/Ur9Hv0S/RD9Af3v/P/8Lv1S/VH9SP1H/Sb9/vzw/Aj9PP1W/Uf9Qv1g/WL9L/34/Mz8vvzK/NT89/wu/Vj9YP1W/WT9Zv0//QT90fzE/O38Dv0K/Rn9Nv1c/XD9U/0t/Sn9JP0L/Rj9Lv0y/S/9HP0d/S39FP33/On8//wu/Tn9O/1O/VD9N/0P/eP80vza/BH99f4IAtcEgwdFCgsNlw8eEWQRgBEpEl4TXxVCGMgbgR/hIrYl/CdZKYEp5yhGKAsoLSg2KNknRyetJsAlPyQqIrofZh17GwQa0hiRFwkWLxQbEvcPow0CC1oIHQaaBKwD9AJqAh8C2gF+AfIAPACH/9P+EP5t/Sz9D/3K/F38+vvL+6b7Vvv8+sz6yPrh+gP7DPsH++X6dfrN+TP52viU+FT4VfiP+BD5x/lO+pr65vo6+1b7SftC+1P7nfsB/E/8pPwQ/XX9w/34/Rn+Rf56/pf+t/7r/hz/Hv/5/rv+d/5G/vf9j/1c/WL9hP2i/Zf9gf13/Vn9G/3Q/I78bfxt/Hf8hfyV/LT8zvzU/Of8Cv0x/V/9kv3b/Ub+mv6s/rj+0v7V/tX+0v7d/hj/cv/B//P/JABGAEIAKwD5/7H/hP9//3j/bv9e/zX/Ef/r/q7+c/5F/hr+Bv7u/cn9nP1Q/e38mvxd/CT89vve+9z72vvf+9/7svtx+yz7CfsT+xj7/frq+vv6+/r5+v76AvsK+wj7Kvto+4T7f/th+0H7QftR+1b7X/t6+6b78Ps7/Fj8Vvw6/DT8O/wp/DT8Ufxg/Hj8mPy4/Nn85vzl/PX8Cf0N/Rv9Ef0P/S39OP0+/VD9U/05/S39If0Z/Rb9F/0m/T39aP2P/Zf9jv10/UP9H/38/Nb80Pzj/AP9Lv1L/Uf9Nv0p/Sf9JP0c/RP9E/0U/Qv9Af0C/fr80fzB/OL8Fv1E/Uv9S/1Y/VT9PP0V/eT82/zx/Az9K/1D/Uv9Of0j/Rn9E/0G/fL8+/wq/Vj9a/1W/SX99/zt/Oj8w/yu/MT89/ws/VD9V/1I/TL9Gf3u/MT8xPzM/ML80fwC/Sb9Sv1e/Uf9Gf3p/MH8qfyy/Mz87/wX/Tf9U/1X/TH9AP3d/MP8s/y9/Of8Kf1n/Xn9ZP1I/R796vzT/Nf86vwG/R/9Tv2E/Yr9Xv06/Sz9Ff36/On8+fw2/V39Wf1X/UL9IP0B/fD8/vwY/Sz9Pv1S/Wz9dv1O/Qv91/zO/Oz8+Pzy/Bj9X/2L/ZH9av07/R/9A/3v/PL8A/0A/fH8AP00/W39d/1R/TH9KP0+/T39D/3o/M781fzr/Pf8/fz//Bb9Lv1B/VH9Rv0p/Q/9Dv3+/Nn8yPzI/Oj8G/1a/R//JALZBDoHugl2DAcPvhBbEaURcBKiE24VNhirGyEfOiL6JF4nFSmhKSopmShvKIIoXijWJyInZiaFJSYkNSIPIPwdFhx7GiIZvhcZFioUAhLFD2wNBAu5CMAGMAUGBCwDgwIRAr0BVQHDACUAj//3/nn+AP51/fT8oPxY/Ab8uPtl+z77S/tY+0z7N/sq+wn70fqD+hr6mPkO+bL4nfjI+PT4DvlU+bf5Dvo7+lD6gvrE+hT7afvF+0H8nPy7/MT82/z0/Af9RP2b/Qz+lv4H/2f/pf+G/xX/nP5C/gf+1P2u/bb93v0A/gD+4f2u/V79D/3H/KL8tvy8/Lz8yfzk/PD8xfyT/Hv8fvym/Mn88/xL/a799/0w/nL+q/68/q7+uP7v/hb/Fv8t/2//tv/I/7n/2P8RAB0AAQDi/9H/0f/C/43/YP9C/xT/5/6m/m3+Yv45/vP9x/2t/Xz9P/0W/QD97fyr/E38E/z7+9z7o/tj+0z7Yvti+0n7QvtU+1L7LvsJ+wL7E/sM+/b6+voQ+xz7EPsG+yj7W/tn+1L7UPuA+7D7vfuz+7f72vv8+wr8Ffwn/DD8NPw2/EP8Yvx6/JL8sPzX/AX9Fv35/NT80/zr/AD9AP0D/Sr9XP1h/UH9Hv0S/RH9B/0R/TT9Zf1w/WL9YP1N/Sn9BP3b/NT8A/0i/TP9Tf1Q/S39DP39/OT83fzs/Pb8H/1O/Vz9Yf1L/R/97/zI/MD8xvy+/Nj8FP1O/X79g/1o/Vr9T/1E/Sz9BP3g/M780vzb/Pv8Mf1K/Uf9Uf1y/Yz9eP1U/S79/fzp/OX84/zo/OD86PwR/Tz9Qv0t/Rz9HP0q/SX9Ev31/Nf81vzj/Of84PzW/Nb87Pz//AX9FP0e/RP9AP38/P78+fz6/Pz8/PwF/fz84vzj/Pr8Df0T/Rn9M/1D/Un9O/0a/Q/9DP37/PT89vz3/BH9NP1E/UD9OP00/UH9Q/01/Sr9IP0k/Sf9Jv0t/TT9K/0t/Sn9FP0S/Rv9IP0t/UH9XP1q/WL9VP03/QH9w/yd/J78zvwD/Tn9hf24/cP9qP1m/Rz92/yZ/GD8Z/yx/Av9V/2E/Y/9nv2u/Yz9NP3t/M78xPy5/LH8x/z1/CX9Sv12/aX9kP1O/SX9Av3t/M38ofyq/OT8T/0i/xECogQAB3MJFAysDnAQHxGBEU4SdhNEFe4XQBvCHgci6CRHJ/UoiikmKX8oKCgmKA4oqCcfJ60mCibBJNkioiBlHk0cchrXGHUXBRY6FC8SGRDxDagLSAkTB2MFIAQsA34CHALfAXUB1QAeAIT/Cf94/s39Qf3x/L38jPxB/Pf7t/tx+0n7JvsH+/L63/rR+rr6fvoO+pT5OPkA+db4w/jT+PH4Jvl4+dn5JPpb+oD6r/oH+2P7ofvg+zr8gvzE/A/9Qv1x/a399f0w/l/+lP7O/vT+8v7x/u3+1v6k/lj+FP7o/dL9tP2E/Vr9R/1A/UD9Q/02/Rr97Py4/Jf8gPxy/G78fPyg/Mn8DP1I/Wj9gP2Q/bb97v0N/if+bP7Y/in/Qf89/zz/Sf9D/0b/fP/L//7/DQAsAFYAVQAGAI7/JP/0/u7+/v4P/xr/Hf8E/8r+ff4S/qD9OP3u/OH89vzz/NP8uPyZ/Gz8KfzY+5j7eftw+2X7WvtG+zL7Mvsq+xX7B/sQ+y77Pfss+x37GfsK+/r6+Pod+0/7Zvt++5r7t/vL+7X7jPuW+8f78PsE/Bb8IPw2/Gb8bPxW/EX8SfyG/Nb8+/zi/NL84fz7/Af98PzZ/OL8+/wY/UL9Uv01/Rb9Jv1K/VL9O/0m/TL9Wf1r/VL9LP0R/RD9F/0Q/Q/9Cf32/An9K/01/Tr9J/0b/SX9J/0V/RH9F/0N/fn85fz2/Bj9Hv0I/Qv9Mv1c/XL9eP17/XX9Yf0k/eT80PzP/ND85fwW/Vj9oP2x/Y39dv1b/Rz9z/yX/J780PwF/Sj9P/1b/VT9OP0s/RP9+/zt/M78z/wI/S/9J/0L/f38Bv0a/RT9+fz3/A79DP3u/Nr84/zo/Ob87PwR/Tz9Of0f/QH98Pzy/N78vvzI/Oz8CP0s/Uv9V/1F/Rv9+vzk/OP85Pzk/AT9N/1N/U39V/1U/Un9M/0G/fH8BP0R/RL9If05/VT9Xf1L/S79Gf0M/f/8CP0V/SH9Qv1m/YD9ef1O/SP9+vzK/Kr8tvzS/O38Lv2H/cH9x/2L/T39Iv0W/dL8lPyQ/MH8EP1V/Xv9g/2A/U/9GP0a/RP97/zL/MX8/vxC/Vf9R/07/Tr9Kf0I/cz8uPzf/P38Fv03/WL9iP2C/Ur9Ff39/PD8E/67AIADKQbuCNcLtQ7CEIERmREIEvoSohQrF10a6x1dIXAk9CadKD8p/ihlKA0oGCgoKOoneyf7Jjgm6ST1Ip8gSB40HIkaGxnOF3wW0xTYEr8Qgw4eDK8JZgePBUQEaQO2AisC2gGMARoBggDU/zj/sf4v/sL9WP3t/ID8GPzN+6L7fftD+w/7CPsv+0v7PPvy+oL6HPqt+Tj53fii+Ib4qfj0+D75mfng+Qz6RPqD+tH6Ivtc+5v78fs+/HT8nvy+/O78Of2I/e39bP7Z/ib/OP8r/x//Bf/L/mv+KP4d/hn+G/4n/ib+E/7f/Zj9Yf08/Qb9vPye/Kn8yPzS/Lz8ufy0/Jr8jfyX/L/8Bf0v/Vb9oP3y/Sv+Nf4m/jj+eP7B/gj/P/9k/4z/mf+U/5b/h/9o/2n/nv/v/y8APwAaAPD/0/+R/yL/mP47/kP+bP59/mH+LP4F/uX9rv1r/TX9/Py6/Iv8c/xj/CP8tfte+0b7Yftf+zj7Qft7+6f7jfs/+xP7APvn+sz6x/rj+vT67/rx+hj7Tftj+1z7YPuE+7D7svuu+8D70vvP+8n74/sE/BH8DPwd/En8b/yK/J/8wvzt/Pv8+fzn/MH8qfyx/L381PwK/T39Wv1z/YH9df1K/SD9B/0W/Tv9Rv1W/Wj9eP10/Un9B/3q/Pv8Bf0Y/Ur9dP15/WD9OP0i/Qv96Py1/Jf8uPzr/B79QP1M/VT9Tv09/TD9IP3+/Nb8yvzQ/PL8Gf0l/UH9VP1c/XL9af1A/R39Cf0H/RD9Cv3+/AD9Ev07/V39UP0t/SH9Jv0q/S/9Jv0I/fL8/PwH/Qz9Df0C/f/8DP0d/R/9FP0D/QH9Ff0a/Qr9+/z8/A/9FP3//OT81fzb/OT89PwP/SD9K/0r/Sf9HP0B/e786Pzo/Oz89vwL/SH9LP08/U79Pf0S/ff8BP0n/Tj9NP00/T39RP0//Sb9F/0K/fH87PwI/Tf9Xf12/Xn9af1P/SP9//zg/L38uvzr/DX9Zf1y/Xz9jP2I/VH9C/3W/MX8y/zV/Pf8OP1m/Wz9Wv1K/UL9JP3y/Nb87Pwb/UX9TP08/TH9Jv0J/d/8yvzO/OH8HP1g/YL9hP1w/VP9L/0D/dr8vPzE/Or8G/1J/Vn9Vf0//S79K/0n/Rr9DP0Z/QP+twCPA7MF5Qd2ClENrw/NEDAR5BEOE4sUthbNGUgdaSAbI7Il7ycYKfkoTygNKDIoKCi2JxYnnCYRJv4kXSNrIVAfLh09G6QZSBjEFt8U1hLdENQOlQw9Cg8IVQYCBe4DGQODAhsCqgEmAZsA/v9h/8P+M/7I/Wn98vx//D78D/zY+6L7evtm+1/7T/sh++76tfpX+ur5jPk8+Qr59fjy+Ar5LPlE+V75f/mo+fP5Tvql+v76Wvu3+wP8NPxa/Hn8lfzV/CL9eP3Y/UX+q/7p/gf/Af/v/t/+sf59/mH+Vf5G/jP+Gv4A/vz90P19/T79F/0A/eD8ufy0/Nn8/vwC/fv88/zo/M/8ovyJ/I78tPzu/Eb91P1a/qn+xv7a/uX+4f7H/pf+of7h/if/dv/D//v/HAAbAO3/w/+x/5X/iP+T/43/ev9p/0j/Cf/G/oX+Pf4O/vb98P3w/d/9rv1h/Rj91/yE/DH8CPz9+/T73/vV+9X7uvt5+zn7JPsj+xn79/rp+gz7Mvs9+yj79PrI+tb68PoO+y77MPs8+3L7svvQ+8X7k/tq+3v7pfu++9P77/sY/Fj8h/yE/HX8dvx9/IP8jvyS/KD8t/zC/OH8DP0d/QT97Pz2/BL9Jf0p/TL9N/1E/Vv9Yf1W/VL9Pf0X/RD9HP0n/Tv9WP2A/ab9q/1z/Sv9Cf35/Or82/za/AP9Q/18/Z39iP1E/fv80PzA/MP82Pz//Dn9e/2Z/X79SP0G/cj8pPym/NL8IP11/bD9y/22/W79Hf3Y/KP8m/y6/Pj8Qf2F/bf9r/14/TH98Py9/Jj8nvzM/BL9Uf1n/Vv9Mf0S/fb8rfyE/KD81/wM/Tr9YP1f/Un9Iv3x/NL8t/yk/LX87fwg/UT9Vf1O/UL9N/0r/Rb9C/0B/fX87Pzp/On88/wF/Q/9Lv1n/YT9av1N/Ub9N/0J/cj8tfzT/PP8Hf1a/Y39k/1w/Ur9SP1A/Qb92Pzu/BT9MP08/T39Sf02/Rf9Gf01/T79Nv06/Uf9Wv1R/Sv9Cf31/OD85vwP/SH9Iv03/Vv9dv2A/Wf9N/0a/f784vzW/M/81Pzt/BL9Qv1v/W39Sf0y/S/9K/0M/e785/z0/AL9Ff0p/Rz9Cf0C/Rn9Rv1P/Ur9V/1i/Uz9I/35/N786/xM/Vr/ZQIHBXcHIAr6DHsP6hA8EWgRPRKlE6UVaxjJGzofVCIKJTYnjyjfKHMoCSgKKC0o7CdbJ78mGyYpJZ4jjSFPHzEdXhvmGasYVBenFccT2hHAD2kN4gp9CIUGBwXuAyUDnwI6At8BkQEpAXkAq//y/mv+Fv6+/Uf92fyT/FD8DPzE+2X7FPv2+v/6Gvs0+y777/qf+jz6rPkY+aP4V/hN+Hr4z/hB+bD5IPp6+rD60vr8+iT7Q/uP+/X7UPyI/LL89/xI/Yz9vP3t/VL+2P4f/zL/RP81//j+pf48/uT9vf2v/bb90P3z/Qf++v3d/Z39Pf3Z/IX8Sfwp/Dz8X/yB/Mb8EP08/U79Qf0U/f38Dv01/Wr9pP3p/TX+j/7d/g7/HP8U/xv/NP9h/5r/y//h/+T/3P/b/9j/tf+E/2r/ef+d/67/f/8//yP/A//K/nz+Jv7k/cT9uf2l/YX9TP31/Lr8lPx1/FX8Ivz8+/X76vu/+4/7evtd+yn7+Prl+gr7N/tB+zH7KPsq+yT7H/sU+wf7D/sT+yf7XvuW+5/7lful+7b7wPvI+7v7xPvw+w38Hfww/E78b/xy/GH8avyS/K38rvy4/Mb82fzx/Pj89fz1/PD85/wB/R39Jf0i/RX9Lv1b/Wr9VP0p/R79Mf1N/VL9QP1G/Uj9Pv1G/UH9KP0W/Q39If1V/Xv9d/1g/VT9Q/0h/fH8xPyz/ND8Cf0+/W/9if2M/XT9RP0M/df8wPzH/N/8E/1a/ZL9nf1+/V39PP0D/bP8mPzL/Af9P/1m/YL9pv2k/W/9Iv3i/K78hvya/Nb8Af0o/UP9Uf1n/Wr9Rv0N/dT8sPzD/Pb8AP3y/Pf8DP0q/Sv9Cf3v/PL8DP0n/TL9Lv0j/Rj9Ef0Q/Qf99fzt/Or8+/wg/Tn9PP0p/Sr9Pf1C/UD9L/0J/en82/zj/PH87vz3/B79Yf2K/Wj9Pf0w/SL9DP3+/Oj84Pzr/AL9LP1Z/Vz9P/0x/UD9TP07/Sb9D/0K/R79If0P/RX9Kf01/Tr9N/0y/Tj9R/1H/UP9TP1R/UH9MP0s/Rf9+Pzk/Oj8/PwL/S/9WP16/Yf9bf0+/R79DP3t/Nj8zvzQ/Pf8Gf0s/Uv9Vf1Q/U39Pv01/S/9Lv0i/Rn9Jv0d/Qv9Af31/AD9Kv2V/lwBDwSUBj0JBgy4DokQFxE7EckRxBJRFMQWDBq0HSwhPSTaJpgoKynLKBMoqieGJzwntCZHJvUlVyU9JJQieSBNHj8cbRrdGGkX3BUrFFUSVRA5Du4LnAmDB8AFXARSA6QCRQIJAsMBXAHlAGkAxf8J/13+zv1Q/cr8Ufz8+8X7n/uY+6z7vPu4+5D7XPsi+8f6RPqs+Sz52Pi7+Mj4+Pg1+VX5Z/mX+dv5DPoc+j/6ufpX+9H7JPxP/GT8dfx+/IX8tfwT/Yr9Iv7H/lP/oP+L/zL/wP5i/hj+0f3M/fz9P/53/oD+Tf4K/sD9UP3h/KT8lfyt/OD8/fwL/Qv93fyi/Hz8ZPxg/H38z/xA/aP94/34/Qr+J/4p/g/+/v0j/nv+3f40/4X/y//1//P/2f+6/5n/c/9d/4D/tf/E/7//w//C/4//Q//8/sD+kv5p/lL+Uf5U/ir+yP1q/Sz93PyI/F/8Wfxc/Fz8XvxN/Cn8/fu2+137Ifvw+tz6/voj+0j7VftK+0b7LvsJ+/v6/vr7+hD7OvtR+2T7evuE+377YPtQ+2z7sPvt+/37Fvw//Ff8V/xL/Dv8L/w4/Ej8afyn/ND84vwD/R79Jf0Z/fb80fzJ/Nf88fwT/Sb9Lf1U/Xz9i/2B/Uv9Hf0N/Qz9FP0e/SD9Hf0l/TT9SP1U/T/9Kv00/WH9dv1X/TD9Hf0I/dP8pvyw/N78G/1H/VT9YP1+/YT9Vf0a/ev8yvzN/Or8Bv0f/TL9R/1h/V/9Uf08/Rb9Ef0i/Sr9Pv1L/UT9P/09/UX9Rv0h/fT87/wO/Tb9TP1L/Ub9Qf07/S/9Fv3//Ob83fz7/Bj9JP0e/QX9Ev0u/Rb96vzX/O78JP1U/VD9Kv0M/fr88/zn/M78s/y7/O38LP1k/W79XP1Y/U39P/0Y/cj8mfyo/OL8C/0K/Rb9Mf1k/ZD9h/1Q/Q397Pzc/N/89vwR/Rn9Mv1W/WH9Yf1E/R/9E/0Z/Rr9If0z/U39bP16/Vn9Iv3y/Nf87Pwc/Ub9VP1Q/VH9V/1P/Sj9+/zt/PD8Af0h/UT9YP1n/U/9G/36/Pb87fzs/BP9Sf1v/XH9Sf0v/TT9Jf35/OH85vz4/CL9Sv1q/W79Rf0k/RH9AP33/Ov8+Pwx/Vz9Yf1V/UD9OP0g/e/8h/0AAPQCeQUICNIKrw3gD8UQ8xBwEVsSmhOkFcYYhhwQIAIjfCVpJ2IoSyifJyonIicqJxEnxyZzJvIlzyQNI+Egmx6AHIka4xicF3YWHhVzE4YRWw8QDa0KVwhdBtgEwAMLA7ACdAIpAsgBQAGKAMr/Lv+t/jr+0v2B/T/98PyF/Bf8v/t3+zX7Bfv9+iL7P/st+/z6uvpa+tz5SPmx+GL4bfii+Mz4Cvl3+Qb6mvoE+037e/uH+4L7n/vi+yX8WfyL/O/8gv0H/lX+fP6i/tD+8f7j/sD+tf66/rv+mf5p/jn+9v2//aX9ov2d/Xr9Tv0w/Sn9Hv3p/J/8Z/xP/Ev8Wfxz/Kf86PwH/Rb9K/05/Uv9Wv1r/Zz95f0l/mD+qP7i/hH/PP9O/0X/Rv9o/5D/qf/C/9P/2f/i/9b/tv+Y/3j/UP8s/xn/E/8M/wD/6f65/nH+If7V/YH9Qv0Z/fr89/z1/OP8y/yU/EX8CvzF+4n7cftt+3f7ifuY+4H7W/sy+/X60PrZ+uz6Afso+1X7fPuR+4H7U/sg+wH7Cvso+0b7dfu2+wP8P/xG/DX8CvzY+8b7y/vf+wL8Ovx7/L38Bv0r/Rz94vyi/IP8e/yN/LD83fwU/Uv9dv2F/XD9Rv0e/Qv9D/0G/Q39Mv1g/X79df1j/Vn9R/01/Tj9Nf0w/Tr9Mf0Z/Rr9FP0R/Rj9HP0u/UP9Pf0s/Sf9H/0V/fz8yPzN/Az9HP0c/S39NP1C/VD9Pv05/UX9Of0l/R79KP0s/Sv9KP0w/T/9Rv1A/Tv9R/1A/Sn9Ff0U/Tf9S/07/Sz9J/00/TL9BP3X/Nj87/z9/A/9Jf07/Ur9Pv04/Tn9F/3Z/Lv80fzj/N385fz9/B39Of04/TD9L/0n/RH99vzc/M381/z1/Ab9B/0B/ff8Df0o/S/9KP0U/Qv9Jf1G/Uf9I/3r/Nn88fwO/RX9C/0W/UX9ef2C/Wn9R/0V/fj8C/0h/Sb9GP0J/Rr9RP1c/Uj9MP0q/TD9UP1t/WL9Qv0l/Q/9BP38/Of85Pz5/CX9Y/2H/Yn9f/1l/Tn9Gv0I/eb8xfzE/Nr8B/0v/UX9Zv13/W39ZP1n/WP9S/0X/d/82vz2/Aj9Ev0p/Tz9Uv1p/Xv9df1T/TH9G/0P/Qr9/fz4/BP9IP0f/Un9Ev/9AZsECAeLCTMMug5hEOkQQxEbEkUT8RSJF+oach6pIVcklCYiKKAoVCjcJ6QnkidWJ9omSCakJcUkiSPZIeAf3x3vGysaqBhEF70V+BP0EcwPpQ2JC3QJegfSBZIEqQMRA6sCSgL4AaABIQF6AL//Ef+L/g/+kP0d/cX8hvxC/BH8+fvU+6b7evtK+zb7F/vE+mX6Dvqm+TD5yfih+Mz4Bfkf+Uj5pfkM+lL6ePqa+tn6J/th+5X77PtW/Kv83/wl/XL9q/3b/fj9KP6E/tT+2f7G/tL+3f7b/q/+Zf4j/vH9yv2f/XT9XP1e/Vz9T/1C/TH9AP2//Iz8ffx6/Gr8Yvxx/Kb85/wS/RX9BP0O/UP9i/3a/Rj+OP5r/qL+xP7i/ub+3P71/jL/bf+Y/7P/zf/9/xQA9f+//5L/d/9r/1v/Tv9D/yX/+f7e/tP+q/5l/ij+BP7Y/ZL9Sf0q/Qj92Pyo/HD8a/xz/Ez8E/zV+6v7kvtj+y/7J/s7+0T7R/tO+0/7MvsG++j6/Pov+0P7Mfsw+1P7gft++0n7LPs2+1/7nfvO+/H7G/wk/Bb8HfwX/Pr70vva+xz8ePy2/Lr8vPzO/Nz8yfyk/Jr8pvzO/AH9Nf1i/XD9Yf05/Q/99vzj/OH8C/1Q/ZH9uf28/aL9d/1C/Qj93Py9/MT8BP1S/YD9g/1w/Vb9PP0K/dT8zfzs/BP9HP0n/UX9Sf0p/f386fzt/OX80/zx/Dr9X/1a/UP9Qv1Q/UH9Ff0B/Qr9CP0L/Qf9Bf0f/S79Nv1D/U39VP1Y/Vj9Qv0q/R/9FP39/Of88vwQ/TP9Mv0N/Q39MP1L/Uf9MP0W/Qj9BP0R/Rv9EP0G/fr8DP0v/S/9Ff3x/NP81/zx/AT9Gf0l/Tn9Z/1z/UP97Pyq/Jv8r/zE/ND88/wq/Vr9ev1l/UH9Ev3a/NP85fz2/A79Gf0p/Tr9O/0j/fX85vz0/Bf9O/0+/Uf9X/1r/WP9T/0f/ej83fzt/An9Mv1B/Ur9XP1x/XL9W/0//TD9Lf0j/Rz9Gf0d/Sz9Mf09/Vj9Xf1M/UT9Mf0d/Qj97/zo/P/8JP1E/WL9Z/1b/Uv9Hf3n/MD8sfzI/OP8Af0n/UD9Wv1i/VD9H/31/OX84Pzy/AD9EP0n/TD9KP0e/RD99fzi/Oz9ugCjAxAGhwg8C/0NCxDWENwQOBExEs4TWRarGTgdniCvIzMm6CeCKB8ocCcOJxYnOicrJ+YmgCbXJbMk+SK3IEUeKhx5Gg8Z1BeCFvYUNhMvEfMOoQxIChAIQwbtBPoDagP6ApQCOQLFATQBoAAAAFf/wP5C/sr9Xf36/JP8SPwM/M/7oPuO+437e/th+y374PqM+hf6l/kt+er4wvi++Nb4//hR+aH55vkg+lv6pvrv+jf7fPvG+wr8SPyB/Kv84/wx/Xb9wf0c/nr+vf7g/gH/Ev8S/+z+nP5U/iH+CP70/dD9qf2W/ZL9ef1S/TD9B/3j/M78svye/JX8g/xv/GD8Z/x0/IH8oPzb/B39UP15/a393/37/Q7+Lf5j/pP+tP7Q/vP+I/9U/3P/iv+j/7b/wv/G/83/0f/B/5//ff9y/2X/Tf8r//n+5P7j/tL+m/5c/iv+9v3A/YD9Pv0B/db8wvy4/Kj8kfxw/D/8BfzU+5b7X/tP+0j7RftT+2f7cvtc+zj7JPsU+wz7//oH+yP7OftC+0b7XPtj+1/7Yvtl+437xvvf+9/77Pvv+/T7//vn++X7Dvw3/FD8dPyp/Mv83vzo/N/84vzf/ND82Pzl/Oz88fz4/A39Nf1J/TT9Ov1h/Xf9dP1f/VL9Vf1V/T/9F/33/OH83vwO/UT9Wv1d/WH9b/1q/Uf9Av3H/ML81/zt/AH9I/1S/V/9Pv0k/Qf94/zJ/NX8CP02/VX9X/1m/WD9S/0m/fz89/wE/Qv9DP0W/TX9UP1U/Tj9G/0k/UX9Yv1o/Uz9KP0S/f783/zN/MT8z/wA/TX9aP2P/Yn9Yf01/f38y/yw/KL8qPzW/Bv9Uv1w/XD9Uf0s/fz8zvy6/Lr81vwA/Sb9M/02/T39Mf0K/dr8xfzP/PD8Bf0F/RT9Kv0p/Rz9Ef0e/SD9B/0G/RT9J/0m/RD9Bf0b/T39Q/0y/Tj9RP06/Sz9H/0Y/RT9Bv0H/Rn9RP1Y/TD9Gf0k/Tb9RP0o/Qf9FP0c/Rv9Ff3+/P38Cf0X/Tv9av1v/U79SP1D/S39/Py7/Kf81fwX/TL9P/1W/W/9fP1c/TL9FP30/Or87Pzw/AT9D/0R/R/9MP0u/Sb9J/07/Vf9W/1E/SD9EP0K/fj86/zn/PP8EP0w/VD9Zv26/aH/VgK4BBoHsgl2DAQPmBAcEZARURJZExgV2xdUG9Me/yHUJDgnuCj3KFIorCdnJ0En5iZ2JicmyiUeJdgjEyIGINUdwRv8GX8Y/BZdFZsTwRHSD7oNfAtECWIH2QWhBMADKgPCAmMC9AF6AekAPwCX//v+aP73/Zj9N/3c/JD8TfwQ/NH7gvte+1z7Uvsy+/L6n/pH+uT5Z/nn+KD4lvim+Nb4G/lt+cH5CPo/+mz6mPq8+vX6Yfvo+1T8i/yu/OD8Kf1v/ZH9r/3u/VT+wv4K/yP/Ff/5/tT+of5f/ib+B/7i/cL9sP2O/WH9Of0I/eT88PwR/Q797vzW/ML8pPyC/GH8T/xV/Gf8nvwE/XH9qv2s/bn98v0y/kT+Rf5y/sD+Dv85/0D/Pv9H/1H/TP9e/37/o//K//j/NQBLACQAxf9e/x7/6v6h/mH+UP5h/oP+jv6B/mH+NP7x/ZL9Kf3C/HP8RPw6/ET8PvwV/O375vv+++37m/tM+yH7KPtG+1T7O/se+x/7KPsy+yz7+PrR+vT6NPtb+2L7bPuK+7n7xvuq+5P7dPtb+3j7v/sD/DX8SfxQ/Hb8lPyF/GL8SPxD/F38i/y3/OP8Dv0r/Tj9J/0D/en84fzj/PD8FP03/Uz9Xv10/Yj9d/1A/QP98fz+/BT9Nf0//Un9YP1f/U39Nv0h/Rr9H/0v/TT9LP0o/Sb9GP0B/ev84Pzt/Az9Qv1w/XL9VP0y/SL9F/37/PD88fz2/AT9CP0U/S79Rf1L/Vb9bf15/W/9Pv0S/QP98/zY/NL8+vwy/VL9Tf1L/Vr9Tf0b/fz88/wH/Rb9EP0T/Rn9Dv3s/ND84PwD/f/87fzy/Az9K/02/S/9Mf1B/Uv9NP0S/fb8x/yZ/In8nfzJ/BP9Yv2Z/cL9vv2H/Uj95fx0/EL8T/yG/Nb8MP1v/Zf9sv2f/Xv9K/3J/Jb8m/zO/P/8Mf1Y/XD9f/1x/VD9JP3y/Mb80/wR/UL9WP1h/Wz9b/1q/Un9DP3d/NP85vwI/Sr9O/1J/Uz9Rv1B/TT9G/0a/SH9Gv0c/R39J/0d/f38/vwc/TD9Lv02/Uf9SP1D/Sz9DP0H/Qr9CP0U/T/9Yf1X/U39M/0I/fX87/wA/R79Lf0x/U79bf1d/TX9C/3o/OH87fwF/R79LP0r/sgAfAPOBUcI7wqnDeAP+RBOEdYRwBIZFGEWfhnkHCogGCOkJaUnrSiJKNMnZydjJ2YnLSe7JjAmgSVtJMUisSBwHlgclxofGd4Xjxb4FC4TPxEYD8oMbwonCEIG5wQBBHQDGAPDAmwC/gFyAcMA/P9H/7D+K/60/Vb9Ev3N/Hv8F/y5+3/7X/tQ+0/7V/s3++X6cvrw+Xf5CPmw+IT4kPjP+Bz5Xfma+dD5+Pkk+k76hvrp+lf7wvs0/IP8svzQ/OH8Cf09/YD91P0t/o7+4v4c/zT/Kf/5/rf+cv4p/u/9uP2f/ab9mf2H/YX9e/1j/UD9Cv3S/LH8j/x4/G/8bfx6/Jn8s/zN/O/89fwG/UH9gv28/en9//0a/lf+mv7A/sP+w/7t/i//Z/95/3f/mv/H/8//0P+y/5D/mP+i/5T/fP9b/yD/+/7r/tL+xf6z/n3+Tv48/h/+2f12/RP94PzT/LH8kPya/KX8hfxY/CL84PuY+1f7Svtc+2L7XPtT+1T7a/tY+yL7Afv4+vT69/oV+zz7W/to+2f7Zvtq+2H7XPt5+5r7pvuw+8/7Afwm/Df8MPwa/Bf8LvxD/Ff8e/ya/Lb81/zu/On8zPyv/K/80Pzf/OD8AP05/XH9fP1g/Uf9LP0L/fP89fwY/Tn9R/1S/WP9cP1r/Un9KP0k/RX9GP0w/Uz9V/09/TL9Qv1S/Sf94PzQ/AH9R/1d/Uj9N/00/Sz9KP0m/f/81fzY/BX9ZP2T/Y39Vf0y/TL9G/3q/K38p/z3/Fn9lP2X/ZD9hP1r/UX9CP3K/K78vfzf/Bz9Vv1g/Vn9S/0x/SP9+/zN/NX8Cf0k/Rb9Gf0y/Ub9NP0A/dT8wfy//MD8y/z4/DD9Rf1E/U79Wf1P/Rj90/y9/Ln8tfy//Nn8Cv02/VH9Tf09/UX9Qv0u/Q/99Pzu/Pf8Af3s/OT8/fwL/SD9O/0+/Tr9Pf1D/UT9N/0R/er87PwX/Tr9NP0R/fT8Bv0r/Tb9HP0B/Sj9Wv1p/Wj9ZP1V/S399PzZ/Or87PzY/OT8K/13/ZL9hP1t/Vn9RP0S/dT8wfzW/Pr8Kf1d/YP9iP1u/Tv9BP3t/Nv82fz5/Bv9Vv2d/a/9j/1U/Rj9+vza/L78z/wE/SH9Ov1p/Yr9hv1Q/Q79C/0m/R39Kv3q/tIBdgTwBnwJQAztDqYQMhGDEUESShPbFFIXihoUHnAhSSStJl0o5yhrKLUnSycXJ84mPCa2JW8l+yT2I0IiISD/HQocOBp/GOcWVhWsE/ERKxBIDkAMFQoKCGIGEwUJBCwDkwJRAiMC1QFgAckAIACD//r+a/7O/Tb9tfxW/CH8B/zR+4v7afta+077KfvV+nn6MPrf+Wb55PiX+ID4i/ih+ND4LPl8+bb5APpi+rr69foi+1H7sfsk/Fz8c/y7/Bn9XP2S/bz9AP5r/sP+2P7o/vT+3P6v/nz+W/42/hL+8f3J/b39u/2P/VP9Kv0G/eD8uPyQ/I78tvzi/OD80PzO/MX8xvyw/In8hfyp/P38cv3b/TX+jP7J/tb+0v64/pL+jP6j/tP+NP9//7H/6P8AAAIA7f+7/3//Zv9t/3H/ff+Q/4D/Wv8k/9H+gf4y/vr90v3F/db93/3U/aD9XP0V/bv8Zvwr/Pb74/v++xT8Dfzj+537WPs++y37EPsT+zj7Wvt/+577i/tN+wn75vru+vf67voC+z/7iPu8+8P7svu3+8v73vvv+/D77Pv++w38DfwS/Ab8Cvw6/HT8mfzB/Or8Bv0s/Sf9+/zV/Lj8oPyj/Kv8ufz7/D/9cP2I/YP9ev19/Wb9Lf0T/Qj99vz8/CP9Qf1L/TT9Fv0l/T79QP01/SP9Ef0Y/Sf9GP39/OP80/zs/A79Hf0n/Sf9Iv0K/e788Pz4/Pj8B/0u/V39dv1y/Vv9Nf0M/e782/zw/Bz9OP1M/W39lP2S/V/9G/3m/Ov8Ev0a/Sf9Vf1o/Vz9QP0c/Qf98vzI/K783/wq/UP9Pf1K/Wz9a/0s/dj8r/yy/K78rPzD/AL9Qf1c/Wv9bv1U/Rj9zvym/KL8nPyt/OX8K/1s/Xb9Vf1C/TD9Gv32/NH81/z1/BX9N/0+/UL9Rv0q/RT9B/0O/Sb9Pv1S/V/9cP1t/Uz9Fv0A/fz84/zf/Oz8Fv1b/Xr9e/2B/XL9Uv0v/f789Pz+/Pv8+/z6/Ab9JP08/Tj9OP1G/T/9Ov04/Tj9Pv0y/Rr99vzT/Nr89Pz//AX9HP1K/Wn9Yf1H/Tn9IP3v/NX81Pzq/AX9Gv05/VT9VP0s/QP95/z2/BH9Fv0u/Uz9Y/1p/VT9LP0B/eD80Pza/P/8Av6lAHMD5AVoCPUKgQ2HD3sQxBA5ER0SkxPzFRUZcBy2H60iQiU4Jw4o6ydZJ/4m9CbnJrkmTCa8JRYlJyTBItsgqx6aHPwanxk8GLcWEBVQE2ARSA8iDf4K/QhEB9YFygQfBJkDGAOYAjQC5gFsAaQA3P9F/7/+Mf6a/Q/9r/xe/BD86/vd+8z7rvt1+zr7Cfu7+kf6qvkR+cH4lvh2+HT4p/j4+Fb5lfmh+bP54fke+mj6xPos+5H78vtG/H/8nfy6/N/8Af1G/bj9QP7E/hj/O/87/wn/rv5K/vj90v2//af9r/3a/f39Av7e/aL9Yv0T/cP8lPyF/ID8hfyG/JX8ufzB/LD8u/zl/Ar9H/1E/ZX92v3s/Qf+OP5d/mn+Vf5b/qH+9/5B/2z/kf+7/9f/7f/l/7D/ff9V/0X/Zf9+/2b/P/81/0T/S/8e/9D+hP5N/ir+Df7x/a79Yv1B/UH9Rf0a/bz8cfxQ/EH8HPzq+9L71Pvp+/v74Put+3P7MvsD++D6yPrN+vH6J/tn+6H7u/um+2b7Ifv7+gH7EfsR+yr7fvvc+w/8DPz9+/r73/u2+7D70/sL/ED8avyn/OD89fzq/MT8nvyH/IP8hvyP/Lv8Bv1K/W79ev12/Wv9ZP09/Qz9/Pz4/AT9If03/Un9Xv1z/YH9b/1H/SD9Ef0d/Sn9KP0u/Tb9Qv1I/Tb9HP0B/ef84Pzz/Bn9O/1O/WD9cP1i/Sj99Pzd/NX83Pz4/Bn9SP2A/Yf9YP08/Rz99PzZ/Nn88/wb/UP9bP2R/ZX9YP0U/eT84/z4/AL9A/0U/TD9SP1L/Sz9Cv3s/N787vwU/TH9PP1I/U/9T/0l/dX8hfxz/K786/wC/Rb9Of1e/X79f/1F/en8qfyZ/LL81Pzb/PD8Fv06/UP9Hf30/O/8/fwJ/R79Lf1A/UT9Nf0k/Q397fy+/LD81fwh/W/9i/2J/Xb9X/1K/R394fzQ/Ov8Ef0n/Tj9Tv1g/Wz9S/0c/Qj9Bv0T/SD9NP1N/WL9WP0r/Q79Cv0H/fD84fz6/B/9R/1W/VH9W/1d/Tf9Cf30/Of81/zY/PL8If1I/UD9Nf07/UT9Pv0f/QP9+/z0/Pz8Jf1B/TT9Fv0K/Q79Gv0g/Qz9DP0q/T39Uf1b/Uj9Kf0I/fr8Bv0H/Rz9zv6+AYIEGwerCUkMzQ5sEOUQFxGuEaYSTBT1Fm4aEh5WISIkdyb+J1Qosif4JrgmwyazJmQmEybBJSgl8SMGIsMfkR2jGwUavRibF0sWxxT7EvQQ1A55DAwK5AczBgYFSATdA50DawMiA7MCFwJEAV4Ae/+8/jT+uv1N/fr8xfyT/FL8B/y6+3D7K/sA++v6wfqH+jb6xPlQ+d74ePg6+Cj4OviC+PD4WfnD+R76cvrM+vj6Cfsq+2f7vPsS/GP8rPzz/ED9nv3z/TH+af6N/qb+1P75/uf+rv5u/kD+Kf4K/uD9w/2h/YP9df1a/Un9M/0C/eH81PzF/Lr8uvym/JP8nPy3/M/85/wE/R/9SP14/aT90P36/R7+Sv55/rL+4/7t/vf+Gv88/17/fv+G/4j/k/+d/6X/rP+m/5r/m/+k/6H/c/80//X+sP6E/l7+UP5I/j7+Nv4a/vH9p/1O/e78lPxf/FD8Wfxi/GX8V/wy/P/7vvuD+2X7PPsS+xb7LvtG+0f7MPsd+xL7CfsD+xD7Nfth+3b7Zvtd+2X7Tfsx+yv7Pft4+6j7wPvw+yv8Qfw4/DX8Nvwn/A/8C/wv/GL8ePxu/IT8vPzl/PT8+PwI/Q798PzV/OH8/vwS/Rf9H/1I/Wn9ZP1V/UD9Nv0x/SD9IP0//Vf9Y/1x/Xz9cf0//Qj9Bv0g/RT98/z0/Cn9WP1T/Tz9Jf0T/QL98vzs/Pz8Df0L/Rf9RP1d/Tr9Bf3x/PX8CP0U/Rf9Mf1T/WX9Vf0w/Rj9CP3v/N386vwd/Vj9cf15/X39av0y/fH8yvy0/ML84/wM/Uz9dv10/Vj9PP0g/fv8xfyS/JT8yvwS/UT9Uv1G/T/9O/0Q/cf8mfyR/K/80vz7/Ef9Z/1R/TH9Jv0P/dn8tPym/Lv87Pwb/UT9WP1I/Rr97vz3/Ab98vzn/O/8Ev08/T/9Kf0X/f785/zz/Bj9NP0x/RT9F/0v/Tf9G/3x/On8Dv1E/Vn9TP0v/R39Ev0P/Qn9B/0T/SX9QP1O/Uv9Rv0y/ST9Dv3v/PT8BP0H/R39QP1O/Tr9Ev0S/TD9QP0g/e385Pzy/AL9+/zx/Bn9PP03/UH9Qf0s/R79Cv3u/NP8wPy9/OT8Jf1J/Uf9PP0z/TD9K/0h/Qj9+Pzs/Ob8+PwD/eL9fQBNA7EFIAi5CnUNvQ/MEAARWxE/EqsTzRXJGEccuR/FImMlZSd3KGwotScoJwMn5SZ+JggmyyWfJf4khyOLIXEfUx1LG3YZ3Bd8FhQVcBPKEQ8QFA7mC6gJogcIBtEE5QNTAxAD7AKtAjQCiQHIAAAASf+g/gP+if0e/dH8mvxO/P/7vPts+yP7Afvw+t36q/pT+vP5j/kT+Y74N/gu+FP4kvj7+HH52/kq+k36c/q0+uj6GftW+6v7L/ye/Mr8+/xL/Yr9rf3Y/Rn+af61/uL+7P7x/un+rP5c/hj+5/29/ZP9Y/1U/W39iP2F/VP9Kv0K/dn8n/xu/FD8RfxQ/HT8q/zi/A79Hv0m/UH9X/1m/XD9of3l/Rr+SP5v/qH+5f4S/x7/Nf9f/3f/hP+B/33/kP+i/5r/jf+a/6H/kf9x/03/MP8R//b+2v7T/sf+qf52/if+3v2K/TH9AP3//Af9/vzu/Nv8t/yI/Dz80vtu+zr7PPtZ+2z7Z/tn+3D7Yvst++76v/qw+rj61voJ+zL7Pfs6+0L7R/sz+xD7+voU+1r7kvu+++P79/v/++37xvvK++n76/sA/Db8gPzT/PD8y/yw/Kf8mfyJ/Hv8l/zM/Pr8IP1H/Vj9Nf0K/fT8//wX/Q/9Bv0g/Uj9bf1p/Uf9Iv3//O789PwS/Rr9Dv0W/Sr9P/1C/Uj9Rf02/Sn9Gv0A/ez82fzK/Mz81fz1/BT9Pf1t/YH9a/1H/SP9/fzb/K38p/zW/Aj9Lf1Q/XX9hf14/Un9Ev3w/Nr8z/zY/A79Q/1O/VH9Rf0k/RD9BP3y/OL81/zm/BD9O/09/R79D/0N/f785/zX/Nr83vzW/Nj8/Pwj/R39B/34/PT89vza/K78qfzJ/Or8CP0i/TL9Mf0P/dj8vvzA/K38mfy7/BL9T/1o/W39Vv0t/Qj96vzO/Lz8tfzQ/Br9bf2L/XP9T/06/Sr9Cv3t/Nv81vzt/Bz9TP1r/WH9Mf0f/TP9JP3s/Mb80/wL/Tz9Nv0Y/RP9G/0f/R/9Hv0n/Sj9Hv0a/RT9Cv39/OL8yPzT/Pr8MP1K/Un9U/1K/Sj9+/zU/NT85/zW/M386PwI/Sb9Pf1P/VX9P/0O/er85Pzn/NX8zvzs/Bj9Tv1v/Vj9Mf0S/e78v/yc/Jr80/xI/QX/6wGVBO4GUgnTC08ODhCmEPoQwxEaEw0VuhcNG4UetCGHJN8mXyjYKHoo6ie6J8UntCd6Jy0n0SZHJjclaCMeIeAe4BwqG7oZVBjeFlMVkROHEV8PLg3lCsgIGwffBQAFbwT7A3wD/AJYAogBsQDr/zf/xf56/h/+wf1S/cf8RPzd+4X7K/vS+pz6mfqt+qn6e/od+qb5SPn1+KL4d/ho+G34k/jO+Cb5hfnT+TT6svox+6D73vv5+zH8f/yy/Mn83/wQ/Wj9z/0q/nb+yP4F/wL/8/7u/tf+nP5B/uz9tv2e/Xf9MP0b/UD9X/1i/UP9FP3h/K78ffxF/A784/v0+0b8ovzh/Av9Nf1i/WX9Q/07/UX9V/2J/eX9Pv6I/t3+HP9S/3H/Yf9L/zr/OP9H/2D/f/+n/8L/yP/U/9b/r/9+/0r/Kf8n/xb/4/6y/ov+e/5j/hX+wP2H/WT9TP03/Rv97Py4/Ir8Xfw1/Pn7pfti+1r7avth+1P7Ofs1+0H7MPsJ+9n6pfqK+pj6wPr4+hn7HPsv+177YPs0+w775frk+hT7O/to+6777/sZ/DX8OfwU/Pb77fvn+//7KvxJ/HT8rPzN/N781/y1/Kr8t/zD/N78BP0k/Tz9Sf1J/Tj9CP3Z/Lb8xPzy/A/9KP0//Wf9hP2E/Wb9I/3l/Mj8yfzh/PP89Pz4/P38E/0w/SH9/fzj/Nb86/wU/SX9If0L/f/8Cv34/Nr8ufyk/Lj85/wY/Sj9Mv1H/VT9XP1J/RH90fyx/ML88vwg/TL9KP0z/U/9Vv0u/eP8s/y0/Of8Hf00/VT9Z/1f/U/9F/3G/Hf8WPx//Lr89vwe/TX9RP1d/Vj9F/3Q/JT8kPyz/Mz82vzc/OT83vzn/PP83fzg/Pf8CP0V/R79EP3p/M/8rfyp/L78xfzW/Pf8Hf1B/Uv9Jf0N/QT97Pza/N789fwH/Q/9Df0R/S/9O/0f/Qj9+fzx/P/8FP0y/Tz9LP0X/RH9DP0H/f783vzY/Pj8Jv05/TX9L/0n/Sn9Jv0I/eH8v/yy/Nv8D/0Z/Rb9HP0w/VH9Vf0o/er8yfzK/Nb86fz6/BD9If0k/Sj9JP0C/dL8vvzW/AX9GP0g/Sn9QP1e/UP9+/zE/Kj8rvzY/Pb8CP0u/V/9ef1q/T79Fv04/RX/9AGTBD0HBwrwDJ4PWBHqESsSvhLYE8UVlBgFHJAf4SLZJTkosSkGKowp9yjBKM8oqihDKNYnZyfAJoYliSNCITMfTh2HGxAashggF1cVTxMtERIPzwyDCnkI4QbLBfQENgSPA/cCYAK1AfoAPwCd/wz/gP4W/rn9P/2v/BD8efsL+8n6pfqe+pP6ifqD+mb6Kfq0+RX5iPgs+Pv38fca+HL41fgs+YH52/k0+nL6nvrY+iz7iPvb+zb8g/zJ/A39WP2v/fL9Jf5b/pr+yv7m/uD+rv5//mj+XP5N/jP+E/71/ez9yf1//SL9yfye/I78ivyL/Jz8xfzr/Ov81fyl/F/8Nvwy/FL8kfzV/BD9V/3A/R3+Of4w/i3+If4m/lf+h/6q/tX+F/9f/5z/wP/E/6//nv+O/3r/aP9O/0b/Uv90/4r/e/9f/zj/+f7D/or+O/7m/Yv9cP2g/cr9sf1h/SL99PzA/Gb8/vvH+577hvuf+7j7rvuN+0/7FvsB+9/6tvqs+sP65Pr4+vf66PrO+rf6u/rT+uT65/r1+iL7Wvtx+277W/tM+1/7dvuD+5n7vvvf+wL8MfxZ/HP8d/xx/IT8mPyC/Gv8bfx7/JX8ufzY/AD9Nf1G/UL9R/1J/Tj9HP0L/QD9A/0Q/RX9MP1G/T/9Pv1E/T79Lv0N/fv8Ef0g/RT9A/0X/Tz9Sf08/Qz90vyt/J38mfy0/OP8Af0r/Vz9gP2D/UH96/y7/KP8nfyh/Lr88Pwi/UH9Sf1D/TX9E/3u/Ov8Bf0u/T/9Nf0t/Rn9+vzJ/LP8wvzT/N38+fxD/X/9jv10/S397fzc/Mj8nvyN/J/8r/zL/Ar9S/1h/Tv9Cv0A/Q/99vyy/H/8g/yt/Nr8+fz2/PT89vzj/Nr8zfy//L78y/z1/Cn9Sf0//Qz91vy3/KT8gPxq/I/87fxN/XX9gv2P/Xr9M/3v/Mn8uPyz/LH8y/z//EL9av1o/Uf9Jf0k/Sv9I/0V/Rj9IP0Z/RH9CP3q/MX8sfzO/Af9MP1D/VL9Z/1Z/S39/vzP/Kf8m/yx/OX8Lf1F/SL9+/z7/Ab9/vzk/Nr8+/ww/Vf9Zv1P/Qv9xfyh/JD8gPyR/Nn8Lv1w/ZD9if1n/Sn98/zQ/Kb8lfyK/Jn83/wn/UD9L/0n/Sb9Gv1M/Tr/NQL2BIkHKQoHDaoPRhG+EQcSxhLwE9EVuRhwHD4gkiNrJr4oJCplKsUpEinOKMwoqyhmKC0o4Cc+J/cl+SOXIT0fLB1jG88ZaBgKF3sVrBOOETgP2QyHCl8IlgZIBVkEsAM7A+oCkALzARoBOwCD//z+bP61/Rb9ofwj/Kr7TfsI+936tvqQ+nr6gPqB+lb68/lx+fn4jvgX+LT3rvf091z41/hV+cz5O/qI+rf69voi+yz7U/uq+yX8vfwv/Xn9w/36/Rz+S/6I/rz+2f71/iD/J/8A/8f+mv51/i3+2v2m/ZT9ff1U/Tr9Kv0c/f78wPyM/IP8gfxl/Dz8Kfw9/E78XPx6/KX8wvzB/M/8Bv1N/ZH9y/0J/lr+mf6S/nT+ef6X/sH+4/71/jD/nv/v/wcA/P/Q/5r/i/+F/2z/Yf9e/1f/XP9B/wP/uv5w/kr+SP5L/kL+NP4G/sP9fP0j/br8Q/z4+9L72fsJ/B/8IPwP/Nr7j/tS+x373fq4+qT6ofq4+sv62PrW+sj6v/rD+s/60vrT+uX6EPsq+zP7Nfsi+yD7PvtZ+2r7jfuu+837/Psl/Db8SfxN/Cj8Gvwv/EH8ZfyR/K/80vzn/N388fwZ/Rb99PzY/Nj8CP04/Sz9FP0M/Rf9Lf0o/Rf9If1A/Vb9W/1U/TL9Bv3p/OL85Pzi/Nz83fwG/Uj9aP1F/RL94/zL/Or87PzH/L380vzw/AT9+Pzj/Nz89/wZ/Sf9E/32/P38Ev0b/Qj97/zY/NX85/z9/Av9Bf3x/PL8Hf1U/Vj9Ov0g/Rj9H/0D/cb8lvyg/Lr82PwH/TT9Uv1a/Vr9Sv0n/ez8rfyY/K38r/yh/Lb84/wa/TH9LP0U/Qn9Bf3q/OT83vzH/K78q/yy/Lz8x/zL/Nz86/z1/A/9Hf0V/Qv9/fz1/O381vy4/Lr8z/zZ/PX8Df0a/S39M/0x/UH9Qf0d/fb87fwE/SL9Jv0V/QT9Av0Y/RL9C/0f/Sz9Of0y/Sz9N/05/Rj97fzh/OT88fz+/AT9E/02/Tr9Hv0P/fn84fzc/PH8Df0l/Sr9Hv0e/Tj9Of0I/ez86fzS/L78zvz1/CP9Qv1B/UD9R/07/RD93fzJ/Mf8sfyq/N38J/1Y/WD9Rf0s/Sj9Bf3A/KP8xvz//Bf9G/0w/Zf+gAEuBIcGGAnkC7QOyBCsERQSxxKuExUVhRfhGqEeJyIrJcQnpClMKtkpECmyKK8olShdKCwo8ydwJ0wmZyQYIqAfMh0vG6sZfRhQF9wVORRbEiMQpg0cC74ItAYXBe4DVQMgAwYDxwJFApcB0ADe/+T+Hv6N/S792PyP/GP8Jvy9+0f74Pp++iz69Pnj+QH6Mvos+vb5o/kc+ZT4MvgD+BD4S/in+DH53PmR+jH7nfva+/P7DPwu/Ef8ePzC/Bj9iv39/Wv+2f4k/z7/Pf8w/wf/0f6s/p3+lv5//mH+O/4d/gT+xv1j/QH90/y8/JX8c/xt/If8pvyo/J38fvxP/Cr8JPw1/ET8RPxa/Mb8Vv29/ef99v3+/Rb+Lv4y/jf+Qv5h/pf+5v4s/2D/kv+u/8T/zP+4/6H/if93/23/Wv81/wv//P7+/v7+7f7G/p/+bv5K/iX+5v2p/X39TP0I/eL81/y4/HT8IvzT+6r7nPtz+0z7Vvt7+5/7m/tg+yL75vqh+mz6Rvoq+jL6bfrJ+i37dPt8+1v7TPs++yL75/qf+pH6zvow+4j71vsU/E78dvxv/Ev8Efza+7v7zPsI/Ff8sPzq/BL9MP01/Qr9u/x8/HP8ofzV/Pv8Lf1r/Yj9d/1a/TD9Cv3q/Lv8ufz//EL9XP1Z/Vn9Xv1a/Tb9Bv3z/Ov88fz4/BP9O/1J/Tr9JP0k/Rv9Af3R/LP80vz+/B/9QP1X/VX9Rv0l/fv81Pyi/JL8qfza/CH9Wv12/X/9bv1I/ST97fyq/I38p/zb/BP9M/1O/XT9c/1R/ST97fy8/JP8fvyn/O78F/05/Un9Wv1t/UT99Py9/Jv8ifyX/Lb85/wT/R39IP0v/Sj98/y5/J38sfzN/N787vz8/Aj9B/37/OT8zfy3/Kn8vPzc/Oj86/zu/PX8C/0W/Qn9Ef0r/Sj9Hf0b/Q395vzA/K38qvzQ/A/9OP1W/XP9gP2E/YH9TP36/LX8jvyW/Ln80fzi/BD9Uf16/YH9ev1b/Sj98/zc/Nv80/zW/On8C/0z/Un9QP0y/R39A/0E/Q39KP04/Sf9GP0g/Sj9Dv3a/Kn8svzn/CX9Tf1I/Tz9Ov05/RP92Pyi/JH8wPwK/T/9S/07/S39JP0U/fn82fy9/Lj82/wY/UD9Qf0s/Tr95P7GAUwEvAaACXoMPw8YEcMRAxKpEsETbRX8F08b3x5UImcl8ieZKQgqjSnSKHcoZCgxKMMnSyf1JmYmLSVQIw4hwR66HPYaRRmwFzYWnRTQEs0QpQ5nDBcK8AcyBuME/ANXA8QCZQIjAroBFgFeALX/Cf9h/sT9Tv0E/bD8Sfzp+6r7nPt6+y774vq7+r/6yfqZ+in6vPlj+ST5/fjW+MX43vge+Y/5Jvqo+vD6I/tu+9n7Nfxi/HP8pvwO/X/9yf3p/RX+V/6l/ub+F/89/0//V/9N/yb/6v6P/iH+1/3C/bf9kf1U/Sn9Nv1E/QX9ofxc/EL8PPwp/AT8A/w0/FP8UPxV/GL8cfx2/HH8g/zK/Bz9Vv2e/QT+Yv6b/o7+af5l/n/+hv59/p/+5f5A/4P/nf+2/8r/r/9q/zv/LP8k/xr/DP8O/x3/Cf/P/oz+Y/5B/gT+xP2Y/ZX9nf2N/Vb9Bf3M/Jb8Wfwg/PL7x/ug+4r7k/uW+377T/se+xb7HPsQ++v60/rP+tf66Pra+sj6z/rr+hH7Ifso+yn7KPtK+177XPtp+3v7lPu1+8/78vsb/Db8Mvwh/DP8RPxG/E78X/yB/Kr80fzt/A/9Iv0N/ef82/zm/Oz84PzP/PL8Pv1t/Vz9Pf09/T/9Kf0D/eH82vzp/AT9Iv1G/V/9UP0s/RT9FP30/Lj8p/zP/AD9GP0h/Sr9Nf0v/Qv92fzH/Mz8z/zi/AT9Fv0b/Rj9Ff0K/f785vzO/OX8Bv0T/Rv9I/0v/Sv9EP3//P/8+/zy/AL9IP0w/Tb9Mv00/Tb9Hf3z/Nr81fzh/Pj8Ef05/VL9R/0p/Q398PzP/LL8l/yP/Lz8+vwf/Tz9OP0d/QD90vyp/Jf8ofy4/NT8+fws/Un9PP0k/Qn94vyx/Iz8m/zE/PL8Kv1b/XH9Zv02/Qj9Af3t/ML8svzK/Pz8Jv0s/Sj9NP07/Rb96Pzp/A79Gf0c/TH9Qv1D/R395vzN/Mv80Pzc/OP8/Pw5/Wv9Z/1V/T79Iv0F/dT8q/y3/NH82/zo/AT9Jf0v/Sz9Nv1H/U79Pf0d/RD9Cf3s/NH81Pzm/PP88Pz6/DT9bP1q/Un9Lf0p/S79FP3h/Mv81Pze/OP82vza/Ov8Ev02/U39S/0w/Sr9Kf0T/eb8sfyg/LT82PwW/vAA1wNvBhYJ7wvKDsgQgRGfETMSMBOPFMUW6hmpHVchgCQGJ/Uo0ymGKdMoXygvKOcnYifWJogmFSYAJUkjPiEcHwEdERtzGQcYexa6FNoS7BDZDpMMUgpGCHgGEwUgBHsDAwOQAhgCtQFZAbwA5v88/8v+cP4e/qj9Mv3b/JT8S/wH/N37svuB+2X7f/un+437IPuj+jv62vmB+UT5M/lS+Zn5BvqJ+gD7VfuT+877D/w//Gv8m/zV/DL9l/3h/Rv+Vf6R/sf+//4w/0D/PP82/xn/Af/x/r3+h/5k/jX+Av7A/XD9LP3l/J78ZPxI/ET8Nvw7/En8Q/w3/Cn8A/zV+8D7vfvQ+/H7F/xa/K38+vxH/YT9sf3V/eX96f33/R/+T/5//q/+2/4N/zr/S/8y/w3//P7+/hn/M/9T/2//bf9Y/zP/BP+5/lD+3/2g/bH91/3Z/cf9uP21/af9a/0N/bf8ffxP/CH87PvC+6b7hvt8+5H7nfuU+4/7hft9+3H7PPvo+qn6hvqN+rr67fom+0f7SvtR+1b7Q/sr+xP7FPtG+4P7rfve+wL8Dfz/+9z7xPu++9j7A/xB/Jb85PwP/Q79Av3s/Lr8h/xp/Fr8efyy/PP8S/2G/YT9Wf0t/Rz9Gf0C/dz80/z//CX9GP39/Pz8C/0K/e382fzy/Cn9Qv05/TT9MP0R/ev80fzG/MP8s/yi/LX83/z0/AH9Ev0j/TL9Lv0V/fn8/fz7/Oj8z/yn/Kf8zfzx/AP9F/0c/SH9MP0+/UL9Kf0R/Qr9DP0B/fD83/zL/Nb84/zn/P/8Hf0y/Uj9X/1c/UP9If3y/NL8vfyt/MH81vzd/Or8E/1E/VL9Pv0f/Qv99Pzc/MP8s/y9/Mr84Pz3/A39EP0H/fr83PzK/NH80PzA/NX8Bv0z/Ub9H/3z/PP87fzR/Lf8q/zC/O38J/1f/X39dP1B/RL9Bf3x/LX8hfyT/OX8Pf1u/XL9XP0//RX96PzB/Lb8wvzi/Az9Mv1L/T79Ev3s/Nj8zvzB/MD86/wf/UL9RP0x/R79B/34/Oj81vzo/AH9AP3//Az9Fv0X/Qr97vz8/B39K/06/Tb9JP0T/fv80/yy/LH8svzB/Or8Hf08/VP9a/1l/UP9//y//LH8sPyj/J78t/zz/DX9WP1e/VP9lf5eARQEjgYuCewLqw7CEKAR7hGAEmcT3RRUF7caWh7FIdckeydaKQ8qmynNKGkoOijsJ4UnGSevJh0mCiVsI2EhHR/yHP8aShm/FzUWmxTVEtsQqw5jDCUKEQhQBuQE1AMmA9wCvQJ+AhYCfQHbAFMAy/8d/3n+A/60/Xv9Qf37/K/8iPx3/Hj8h/x8/FP8GvzV+3z7EPuL+hD6t/me+bf58vlO+qH6Bvto+7j77PsF/Cz8Wvyd/Nr8Af1O/b/9IP5T/nL+t/4I/zT/O/84/0z/bf9c/xP/4v64/nv+P/4C/s/9lv1G/fP8xPyi/Gz8Ofwb/CD8Kvwb/OD7lPtw+2f7XftK+0n7g/vm+0/8i/yj/LT8wvzh/Av9Mf1s/bj98f0c/kT+b/59/of+nf64/u/+G/8v/1T/fv9+/0//D//v/vb+5f6h/oD+kP6d/on+Sv4W/hj+F/7i/an9ef07/f/8tPxt/E38L/wE/O/7/PsQ/B38CPzb+7X7mftb+/36s/qc+rH6xvrj+iH7ZfuF+377cPtY+yj77vrA+sH64/oa+0/7e/ut+9L73/vr+/P78/sP/B78E/wJ/Bb8Kvwv/D38TPxx/LL81/z0/Br9Mf0o/fT8zPzP/Nv81/zU/OD8Af0i/TH9Mf0p/Rj9Ev0c/Rf9Ef0L/fn85PzV/NT8zvy3/Kf8uPzk/Aj9Hf0d/f/88/zk/MH8r/yq/JP8iPyj/M/8+/z//On86/wF/Qv9CP38/PD87/zn/Nz84Pzf/M381vz8/CL9Nv0p/RD9Df0e/Rn9DP0P/Qb9Cv0J/f38Av0B/e/82vzY/N787vwY/TX9Lv0Y/Q39Cv3v/MH8lfyU/K78vfzC/Nz8B/0T/Q79D/0Q/fb8yfyi/Jf8q/y9/MX8zfzo/BX9Of0w/fP8y/y5/KL8qPy+/M786fwk/VH9Yv1V/Qb9ufye/JH8jvyX/LT89fxP/Zv9qP19/TL98/zH/JD8a/xw/Jf86PxH/Zj9tf2h/XH9MP36/Mz8ovyG/Jj82vwo/Wz9iP2I/Xf9Sf0H/c38m/yO/Kz84PwZ/UP9af1n/UP9C/3H/KH8i/yE/JH8yPwZ/UL9S/07/RT94Pyk/HD8cPym/Ov8Ev0Z/TD9Ov0W/dj8nvyM/JH8qPze/Bz9Sf1R/Tf9Dv3e/Kf8e/yA/BD9eP+dAlUF9AePCkoNzg9OEboR8xGmEgUULhYZGYAc5R8aI/slSii3KQgqmSkYKeEoxChlKLknDSdxJrElfSSbIlAgER4iHJYaHxmAF7cV0BPbEcsPhQ0hC+AI9QZwBVcErQNRAwwDrQIyArYBHwFaAKL/Gf/C/pX+aP4k/u/9wf1s/Qf9v/yL/FP8Lvw8/GL8f/xo/Pz7ePsQ+6H6Nvre+bP54flE+rf6Mvul+wD8VPyK/Kj8xvzZ/AX9VP2n/f39S/6C/q7+5f4V/yL/N/9W/3j/nP+f/4T/VP8T/6j+E/6J/ST92vyk/J38sfy4/KL8e/xR/BL8o/su+/H62/rk+vz6GvtM+377j/ue+8L75PsQ/En8jvzk/B79P/1N/WH9jP2x/eD9GP5f/rP+5/7y/gD/Bf/r/sn+tf7K/u3+Af8M/xT/EP/k/qP+Zv4g/tz9uf2//cj9y/27/aP9k/1e/Qr9qPxV/CL8A/z6+wf8D/wC/PD75/vS+6r7XvsI++/6+/oG+xL7Gfsj+zr7QftB+zn7JfsX+/f67Pr8+gr7MPtj+4n7p/uw+777zPvG+7f7ufvP++r7C/wk/Er8c/x4/H78hvx//IH8gPyP/K780Pzf/Nj83/z6/BT9GP0N/fr87/z9/P384fzK/Ln8vfzk/Bv9Nf0z/Tv9P/0k/ej8rPyE/HP8a/xz/Kj8+Pwu/Tb9I/0U/f38tvxz/Gb8cvx7/Ij8vPwM/T79Kf3v/NP80/zB/Jb8gPya/Nj8+/wB/Rj9F/0D/e381fy5/Lf8tvyy/M/88PwV/R39/vzq/OX84fzb/Mj8vPzL/Ov8Bf0O/Q/9CP3i/Lr8qfym/Kz8wPzX/O78EP0n/SL9A/3d/MP8qPyP/JD8oPy1/NP85/zq/PD89Pzl/N/84Pzi/OX86fzY/MD8uvyq/JL8kfyx/Nf88fwW/Sr9Of1F/RT90/yl/H/8gfyk/Mn83vz+/CH9Mv0n/fT8wfyb/Jr8tPza/P/8Fv0h/SH9Hv37/K38YvxU/Hf8pfzQ/Pf8If1A/VX9Tv0Z/dv8qPyG/ID8k/yf/Kv81/wQ/Sj9HP39/O38Af0D/eX80vzM/Mr81vzV/MP8sPyg/Lj83Pzn/O/8//wZ/SX9E/3s/ML8svyt/Jn8lfy1/Mv83vzv/Aj9KP0Z/eH8w/zU/Av91P7WAbQEhwdbCjMN+g/pEYYSqRIyE0IUFRbhGGscMyC+I9MmWin8KmMruSrmKZIpdykzKcAoRyjhJ0gnESYrJM8hVR/8HPwaaBkEGHQWlBSlEsIQwA57DA8K0AcNBrwExQMsA+ICqgJpAhwCsgEuAXwAwf8n/8H+ff4z/uT9m/19/Wz9Tf0V/cb8ifxp/G38ffxd/Aj8ivsK+6H6Wvop+vv5+flD+sH6XfvZ+yD8cPy1/OL88/z3/Cj9hP3v/VL+pv7o/hz/Rv9v/6D/uf+4/7v/xv/N/7n/aP/x/nr+EP6v/Uj9+/zc/Mj8qvyB/D38+/ux+1D7/frO+qv6kfqV+qr60PoB+wz79voI+yj7S/t8+6z7Bvxy/Mn8E/1N/XP9g/2A/Y/9tP3f/Rj+T/6R/uX+Fv8Y/xr/Gf/4/t7+yv6w/qn+p/6N/m3+bv5n/kD+CP7e/cz9tv2I/U39K/0d/ff8v/yJ/ET8Ffzy+9L73PvU+7P7pfuw+7H7dPsS+8f6uvq++sD6yvra+vT6C/sX+w/79vrM+qL6sPrQ+ur6Dvss+0j7Xvt/+4r7fPt5+4D7ofvQ+/L7AfwB/A78M/xe/Hb8ePxs/Gv8j/y7/ML8qfyM/ID8n/zB/ML8xvzU/Nz83fzt/Pz87/zO/Kn8m/yp/LL8ofyM/KT81vze/L/8m/yR/Jv8nPyR/IL8iPya/Kv8tPyv/LT8oPxq/Fb8ZPx0/Hf8fPyZ/MP84/zX/Mv81PzC/KL8j/yD/H78h/yo/M385vzv/Ov87vzn/NX8z/zQ/L78rvyz/MT83vzk/ND8xvzF/LP8q/zA/NP81fzY/M78wPyx/J38nvyb/JL8lvyn/L38zvy+/KT8p/yw/KP8j/yL/I78q/zC/K78m/yO/IX8kvyu/Lz8yPzM/MT8uvyu/KT8jvxt/Gf8ivyy/Mf8z/za/OX89/zn/Lf8jPx5/H38h/yS/J38sfzI/N787Pzw/OL8yPy2/KL8kvya/K/8tvy4/Mj81PzK/MD8svyp/LX8rvye/Kv8v/zJ/Mz80fzb/ND8rfyK/Ij8mPye/Jr8l/ym/MT82vzV/N/89/zc/Kf8hvyB/IP8fPx9/JH8vPzP/MX80fzt/OX8uvyF/H78m/yL/Hf8fvyd/L78svye/KL8s/y7/LH8rfzH/NL8u/yd/I/8Yv0IABID7wUUCWEMrw9wEswTEhREFL0UuRXOFxAb+h4II8wmLCrpLEwuAS7dLOQrRSvKKisqhylMKTMphSgUJ/QkWiKyH0IdIxtpGdcXIhZQFHMSehBPDu0LcAk5B44FYwSrA0IDAAPaArECTAKqAQYBdwDs/3P/Ev/J/o/+O/7U/Xz9PP37/LX8lfyV/KP8u/y7/I/8S/y8+/36Zvrz+cf53PkK+mr6/fqc+y78mvzs/ET9iP2k/cb9Cf5P/oj+xv4I/1r/k/+0/+f/JwBrAIIAaQA/AAAAmv8m/8n+Z/7j/WX9/Pyv/Hr8Mvzf+5/7XvsS+9D6lPpZ+iL66vnH+cn51/np+f75IPpO+oX6tPrO+gT7Vfue++z7RPyQ/Lj83vwd/WD9n/3L/eb9F/5X/nf+fv6H/n/+ff6Z/sj+8v7z/s/+ov59/k3+F/7p/bX9pP3E/eH98v3X/Xj9Fv3e/Ln8dPwu/Bb8LvxN/En8FvzF+5D7bvs++w77APv9+vr6D/sa+xX75vqU+k76Qvps+oP6hfqT+sL6APsS+/D6ufqi+rH6u/rI+u76Ivtc+5j7xvva+9X7rfuT+7v77/sP/A/8J/xl/JL8lvxu/Ez8TfxM/E/8f/zA/OH87/z+/P/84/yV/C/8AvwY/Cz8OPxf/LD8AP0M/eT8w/yi/Gj8HfzL+7779Pse/D78Zvyh/LL8ivxm/Fv8WPxB/BX8Bvwz/GD8avxn/GL8Zfxm/Ez8Lvwx/F78hvyZ/LP8qPyG/Hv8dfxw/Gv8cPxt/HH8lvyw/Kv8jvxr/GT8hvyp/K/8v/zP/Mn8svyH/FL8J/wW/B/8SvyR/MT81fzi/OX80vyk/FL8Bvzs+w38Qfxg/Hn8mfy+/Lv8kvx0/Gj8X/xG/EX8dfym/Kr8i/x9/H/8W/wb/AL8M/xv/JP8sPzZ/PP83vyl/Gr8ZPxc/Cz8E/w9/I/8yfzD/Jr8lPyk/Jj8cfxc/G38lPyi/Jb8ifx0/Gf8VPxQ/Hf8nPyT/IT8nPzC/Lv8hPxA/Bv8Mfxd/Hz8k/yr/Lr8w/yu/Iz8Zfw//Cv8JvxA/Gz8nfy5/MT8xfy3/KX8dPw+/C38MvxH/Gb8ffyX/LL8uPyr/JX8c/xY/E78VPxq/HP8fPx9/G/8dPxz/GP8c/yA/Ib8kvyT/JD8hPxe/Cv8GPwM/RYArAPyBkMKvw05Ee8THhVAFWsVDhZhF9sZlB3/IUgmKCrHLYEwljEUMc8v0y5pLgEuUy3MLI8sPSxvK9ApbyemJM4hQB8PHSobUhlxF4UVeRNWEf8OcwwCCuwHPwb7BBsEkQNbA0sDDQOSAgsCfgHiADgAj/8R/6z+R/7s/ab9df1S/UL9MP0m/Q79wfyC/F38/vtk+7T6F/qv+Yn5r/n4+VD6vvo8+737MPxv/IH8rvwD/Wj9vv0M/m/+6v5T/53/x//S/+P/BQBMAI4AkwBrADwA+f+q/zf/n/4Q/nn9+/yv/Hf8KvzK+1/7APvC+mv6+PmQ+Vf5Rfk2+Sf5JPkn+Sr5QPmG+dT58vno+QX6cvrp+jb7Xfuh+xH8hPzW/Bj9Uv1f/V39e/26/fH9B/4M/j/+s/76/uf+r/6G/oP+iP5x/jv+Df73/ef93/3P/aP9eP1X/Uv9Zf1w/TX92PyT/GH8Mvza+3L7Rvt2+7r7wvub+1n7Mvsa++L6l/pP+ij6OPpj+pz6uPqa+mv6Qfoq+ib6Ffr++Qf6Svqi+tH65PrW+sn66/oC+/X65frj+gj7RfuF+7n72/vi+9D73PsA/CD8JvwV/Bf8Rfx5/JX8jvxv/Er8MPwf/B38PvxQ/G38vPwC/Q/92/x5/Cb8/fvl+9L7y/vi+xH8SvyE/KD8ivxN/A387/v0+wf8Gvwh/Bv8Evz/+/H76vvK+7X7u/vg+zH8f/yu/MD8pvxs/Dj8BfzF+4/7bvuT+/z7Zvyz/OX8A/30/MT8gvwn/OH7xfvN+wn8XPyk/Lz8x/zG/Jf8ZPw4/Ar8A/wm/GH8p/zd/Oz8w/yM/E38BPze+9L73PsD/D/8gvyg/Lr8u/yG/FD8I/zp+8b7zPvj+w78Lfw3/Er8V/xM/Cn8D/wj/DX8LPwf/Cj8Vfxo/Fj8NvwG/PX7+/sE/Bb8M/xa/Ib8nvyX/HT8XfxZ/Dv8GfwK/BH8J/xB/GD8efx3/FT8M/wv/Fn8aPxF/D38V/xw/Hf8WPwq/Cj8Mvwc/P37BPwv/Fb8Y/xs/HL8b/xm/E78N/w2/CT89fvi+wP8MfxI/FT8WPxi/HL8bvxM/Cf8HvwV/Bb8Kfwp/Cz8T/xn/Ff8VvxR/ET8OPwe/A/8Gvww/EH8TvxX/Fr8XPxi/FT8QPwm/AP8+/sU/Df8r/37AH8E7weMC0UPxRJXFWwWrxY1F/4XUhnkG/AfuiRjKYQt/jCPM5w0GzTaMtoxSDGwMAAwly91LygvLi5HLKUpwybRI+0gkh6kHNUaARkQFwMVyBJHEI0N4QqgCPEGngWzBEMEJAQlBPMDUQOBAs4BHAFxAN7/Zf/s/nv+Mv4G/tX9fv0d/cv8m/yU/Hj8OPzs+4f7FPuX+gb6ePkn+Tn5l/n6+Uv60Pp1+wz8dPyi/NP8Dv1A/Yv9GP7B/j//gf+6/wsARwBKADgAQgBfAFYAKwAeAAMAqf8S/2z+6v1l/cX8K/zI+5z7ZfsK+5/6Qvro+Yz5RvkK+cj4hfhk+IL4yPj3+A35LPlj+aX56/ko+lL6g/rR+i/7h/vY+x78Yfyz/Ab9R/1i/WD9if3h/SX+Rv4+/i/+T/55/oj+c/5T/jT+If4l/hL+2v2c/Xr9hf2X/Yj9YP08/TH9Kf32/Iz8FPzA+5P7lPu2+7f7nvuN+4b7dfsw+7f6Mfri+ev5Ffo3+lj6iPqt+q/6g/oY+qT5YflK+Wf5rvnt+Sn6evq7+tv67/rT+pj6efp0+pb6vfrJ+tz6FvtP+3b7nvvJ+/n7Bvz9+wn8Dvz5++n75Pv2+yD8KPwQ/BX8O/xe/Hr8k/yS/IL8cPxi/Fj8Nvzk+6D7svvl+xX8Svxu/Hf8bPxM/Bn83/ug+4X7lPvI+/37B/wJ/BD8A/zq+7/7jvuK+7T76Psc/EL8N/wi/Bz8Dvzz+8r7pvul+9f7Dvwr/DL8Mfw//Gv8gfxr/EP8K/wy/D/8OfwO/OP75fsK/Dr8VvxP/FH8efyx/M38rPxg/BH80/vC+8n7zPu9+8D7DfyD/ML8ufx//E38SPwm/L37efuB+6L72/sT/Ev8cPxe/DP8KPwz/BH8zfue+637Bvxh/Gz8T/w//Cr8//vZ+7n7tvvh+xf8RPxm/IH8dPwx/P775/vM+7f7svvJ+xP8Zvx3/Fr8MfwD/OH70PvT++r7Fvww/Dj8Uvxq/Fj8KPzy+8370/vp+wH8LPxj/I78lfx6/FH8JvwJ/PT78Pv/+/n7APwo/Fn8f/x5/Er8KPwd/BH8Cfz4+/D7+vsQ/CL8I/wU/Ab8B/wQ/A78F/w2/EL8Qfw5/Cr8DPzi+7H7ofvT+xz8W/x//IX8gPxk/Bn83fu7+6D7mvvA+078v/6JAukFEQmWDEcQsRMDFucWYRczGF8ZSxtzHpciCSdVK1cv4TJDNQI2ZTVqNM4zVjOnMuMxVTHrMGEwPC8/LYoqgCeaJBoi7R/VHbcbnxmdF4UVLBOXEOoNSAv+CEYHDgZKBcsEgQRaBBsElgPVAv8BJwFnAL7/Hf+x/nX+Of79/az9X/0b/cn8evwi/N37tPuK+zT7uPpF+tP5c/k4+Sb5PPl++e75e/oe+8b7W/zV/B39T/2X/dT9A/5K/rL+JP+V/+//QgCYALoAlwBvAFcAMADq/4v/P/8H/6/+Gf5e/ar8GfyW+xr7vPqH+mn6Mvr7+d75rfk8+a34PvgV+DT4Svhm+Kb4+vhj+c75IPpT+nj6nfrb+j37jfu5+/H7N/yF/NP8CP02/YH91/0b/kv+Xf5X/lP+P/4T/vT95P3f/ev9Bv4f/kD+R/4Z/tD9h/1W/Rr9yvyj/KL8pPyU/Hb8Z/xO/Bj8vvtg+z37MfsS+976v/rJ+tj6r/pg+jH6IfoN+uf5wvnB+cH5sPm7+dL54vn1+ff56/kB+hj6BPrl+eX5A/ow+mP6nvrZ+gb7J/sp+zL7OfsR+/b6EftS+5D7vfvg+/37DvwM/BD8FPwD/Nv7x/v3+zv8RPwm/Bb8KPxE/Dj8IvwU/A78EvwC/AX8IPz9+8T71fv8+wT88vvL+8X76vvw+9z71/vW+9T7tvuc+577nvuc+6T7wPvk+xP8Mvw0/Cf8BvzT+6j7i/ty+3v7q/vy+0v8nfzB/Kb8V/wd/Pf7z/u8+6T7sPv/+1b8m/y3/I38Tvwg/AX8BfwL/P77A/wp/Ev8U/w+/Bb89Pvy+wf8I/xG/Fv8TPw2/CT8/fvB+4n7bPuD+8n7Ivxn/Hf8efxq/D/8APzJ+6L7gfuD+6v70fv4+yP8JvwO/A/8Fvwd/Cn8H/wf/Df8PfwW/O370Puy+5f7pfvp+zT8b/x+/Iz8p/yZ/Eb86fux+6j7vvvU+wX8S/yA/Ib8YPwv/BT89vvf++D76PsI/Db8Yfx7/Gj8PPwH/On7yfud+4T7kfvH+xv8d/yb/Jv8iPxg/DX87PuW+0/7Ofty++H7Pfxk/Hf8fvx7/GL8Jvzb+7j7tvvV+xX8L/wt/Cb8Ifwq/Cv8F/z1++P79/sp/FL8W/xW/EP8N/w7/DT8I/z9+837t/vQ+/n7BP0TAM0DgwdDCw0P9BIjFq4X9hccGKkY3xlAHPsfuyTQKXsulTLWNXI3IzezNU00gTP8Mlsy2jHPMfcxjTH0L1ItLCrWJqkjCiEAH0YdmxvJGesX8xWLE50Qew2XCk8IvQbGBUUFJAUwBRQFpgTNA6gCcgFOAFr/ov49/gn+4/26/YT9Kf20/Br8bfvr+qz6rvq6+qf6bvoQ+pX5Gfms+Gb4XPic+CH54Pm8+p77afzq/B79Nv1c/Xz9qf0W/qr+Q//Q/zkAiQDDANcAugCJAGMAOgAKAM7/j/9Q/+f+U/6q/ej8M/yx+0r7Bvvj+r36jvpJ+un5mfkz+Zr4FPjb9+z3KfiI+Pf4hvkO+j36Kfr7+d757PkW+lz6y/pi+wj8m/wV/U/9Qv0e/QL9FP1T/Zf9vv3t/T7+lP6g/mH+J/4A/uv94/3q/fH98/37/f79Bf7u/ZP9Lf3z/OP8yvyN/Gn8b/xr/Ef8FfzZ+6b7f/s5+/T60/q4+qf6nvp/+lH6GPrt+eb53Pm6+Yr5fvmo+cv5z/m/+aj5p/m9+dP53Pnw+RD6KfpD+lb6Zfpp+m/6mfrR+gv7O/tc+4n7svus+4/7dPtm+3D7e/uW+9X7IPxY/Hr8g/xf/CP8APz9+wv8/vva++r7OPxy/Gr8MvwB/AP8/PvZ++n7I/w0/DD8NPwy/DD89vuU+3z7oPuy+6b7wPsP/E38WPwy/AH85vvO+6H7kfuo+8z78PsH/Bj8KPwv/CP8Bvzu++H75/v9+xn8PfxR/F38XvxY/FT8R/wy/Av8AfwX/C38Mfwo/C/8WvyN/Ir8cPxk/GH8WPw2/AT81Pu2+7T72fsd/Ev8W/xb/Gb8e/xc/Ab8s/uJ+5v7yPvi+/n7Lvxf/GT8Sfwo/Pz7zPu2+8b7+PsZ/BT8JfxT/Gz8Rfzq+6P7pfvU+/v7GPww/Ev8X/xl/F38KvzP+5j7s/v5+zX8RPxN/HP8mfyB/Ef8H/z3+/L7E/wz/FD8YfxN/D38XPxs/E38I/wT/Ef8fvxl/CX8//v3+/377/vq+xX8Vfx8/In8l/yG/EL86Puk+5H7q/vI++r7O/yh/NP8zfyX/Ef8Dfzh+7L7jPuZ++D7M/xy/Jj8l/yD/HP8QfwD/N37uPuq+8L79vtE/HT8dvxb/En8TfxH/Az8s/uX+9j7Gfwr/EX8Xfws/QwAmAP3BoAKKg7sEUoVURcBGFoY8BgWGlwc6h9EJMMoAS3oMCQ0+DUCNuA0tTMTM7EyOjLSMawxgjHQMEAv1SzJKYsmgyPzIPkeah3qG1AamRihFkEUiRGgDuALhgmeB1AGmgU8BfYEnAQMBEEDXQJfAWQAl//X/if+mf0Q/XP8zPso+6b6U/r/+bT5i/mD+Y/5jPlG+c34QPjW97v30/cP+HP49/iV+Vb6FvuX++r7Vfzc/F393v1O/sX+Y//5/1IAdAB8AHsAfACBAIkAiwCNAH4AUAAEAJn/Ef9s/tj9Xf3o/H78GPzG+3n7Fvuv+jb6r/lD+Qv5Dfk0+VT5Wvlu+Yn5kPmB+W75c/mL+bT59PlG+p76Avtp+8H7Bvw5/Fj8jvzj/DH9V/1b/WL9cf2D/Yr9l/3H/fr9J/5S/nf+kv6O/mT+Kf7s/cb9o/13/Wj9gP2V/ZD9df1E/RH90PyN/GD8QvwW/Nv7sfun+7D7nvts+wz7sPp6+k76IfoD+gr6JfpF+k76TPot+ur5qfl8+W75aflo+X352fk++nL6fPpc+kn6SPo9+jH6S/qK+tf6HPtP+4D7q/u4+7D7ovub+537rPvH++D7FPxA/FD8YPx0/ID8gvx0/GD8YPxt/Gf8R/wx/DH8PvxS/FL8QvxD/FH8Zvx2/G78R/wb/AX8A/wH/Oj7yfvX+wH8KPwj/An8GPwv/BT8/PsG/A38DPzy+9j77vsL/Ab86Pvg+xP8T/xQ/Ej8Y/x9/G38LPzv++b7BfwZ/Bf8Nvxy/Jz8mvx8/GD8VPxB/Cb8Ivw+/Fz8Yfxj/Hb8cfxU/DT8EvwF/CT8P/xH/E/8Vfx2/Jj8kvxl/Dr8IfwT/PH72/vy+xD8N/xV/Gj8gvx+/Ej8MvxL/Ej8IPzx+/n7MfxS/D/8I/wZ/CH8MPw8/GL8ePxt/HD8evx//F78HPz3+/77Evwg/CT8NPxv/KL8pPyH/Gr8Zvx0/HP8WPxL/ET8MPwo/DT8OPwy/C78Mvxe/JH8nvyb/KP8qfyG/Ef8Fvz8+/z7BvwT/ED8evyX/Jf8pvys/Hr8NPwJ/Bv8SvxX/Eb8XfyK/IX8UPwf/AL88vv0+xj8Yfyt/NH8wfyr/Jj8a/wP/KP7ffuy+/37M/x4/Lz88PwJ/df8gPxK/CT89vvp+/r7HvxH/GL8dPyH/Jb8yv3NACsEXAe9CnYOOxIvFZUW7hZcFxEYIxkvG4oeuyIGJw0rsy6xMVwzUjNIMkoxmjDrLxwvjy50LnYu+i2jLLwqUSh1Ja4iSiBNHpIc5xpYGfcXbxZ5FBoSiQ8VDdIKxgg/B2MG3wVyBQAFggTdA/ECzQGrAKL/nv6Z/b/8PvzN+zf7ofom+rn5Tvn0+Mf4sfiP+F/4MfgB+Mf3kfdq94L31/dL+Nb4fPk5+uH6ePsN/Jb8Ef1h/bD9Of7V/lr/sf/j/x8AbACTAJgAmwChAK0AoQBqADwAEgC2/yr/nf4i/q79V/0H/an8dPw7/MT7Wvsr+/X6o/pH+vv59fkJ+gr6Afru+fz5L/pb+m76ePp++or6ufrs+hH7P/uD+9n7NfyE/MD88Pz+/PD8+PwR/Sf9L/08/YD95v0n/ib+GP4s/kv+Qv76/cH93v3v/c79rv2w/cf9uP2A/U79Q/0+/Q391/zC/Kb8Wfzz+8D7rPuX+2n7Mvsg+yv7L/sQ++T6sfpw+jr6Ffrv+dD5vPm/+fD5KPo0+iX6I/o3+k/6U/o0+hn6N/ps+pP6s/rN+tT62frt+g/7Lvs7+077iPvO+/77IPwh/Cb8Mvwf/AP86Pvj+wD8Lfxr/Jz8p/y8/Nv80vyf/Gz8Yfx+/JT8h/yI/Kn8wvyy/H38R/wr/B78JPxP/IP8sfy7/Jb8h/yB/Fb8A/zF+8H78fsw/FX8bPx7/Ib8dvxE/Bn8//v7+xT8RPxm/Gr8Z/xt/Hf8Y/xB/Dj8S/xv/JD8ovyv/Lr8nvxp/E78Uvxa/HH8nvza/P787PzD/KH8iPxb/CP8Cvw2/IH8rPzX/BH9IP0B/cz8f/xC/CH8EPwQ/Df8c/yn/Mf82vzd/Mf8q/x2/Dv8JPwz/Fj8afxm/Gz8bvxk/GT8cfx4/Hv8a/xf/IX8rvyY/Fn8M/w8/GD8cfxo/Gz8hvyr/Kv8hvx1/H/8f/x9/I38jvx5/HT8h/yl/LX8mvx0/ID8lPyN/HX8WPxX/Hj8mfy//Ov88vzm/Ov82Pyg/Fr8Dfzv+zX8j/yt/MD85/wV/R39Af3N/H78MPwF/A38VPyo/Lf8m/yr/PP8Bv3B/Fb8Fvw6/Hv8kvyV/Kv8xfzI/MD8uvyZ/FL8Dvwc/G38uvzL/Kr8o/zD/Nv8yvyR/Ev8NfxT/Hb8hfyN/Jj8qfzC/NP8Dv7NAJsDTwZiCc8MHhCPErYTGxSKFEUVdhZ2GHgbCB+bIhYmYinmK/csrSzgK2srXiswK9kq0CoZKz0rwSp8KaUnWCXZIo0gtB5IHSMcHBskGioZ4xcTFssTWRH1DswMDAu3CcQIJQiwBzgHlAa0BY4EPQP5Ac4A1P8J/2H+xv0j/Xb8yPs9+6L64flN+QT56/jf+L74jvhx+Gn4TfhB+Ej4YPi3+Cn5m/kR+n/68/px++77ZPza/Ef9pf0d/qL+A/9C/3X/k/++//3/BwDt/9P/vv+r/5v/eP9J/x//6/6//o/+Q/7f/Xb9Ev2//Hb8MPz5+9H7xfvH+8P7p/tw+0H7IfsH+/n68fr1+gT7KPts+637yfvM+8T7w/vQ+9P71Pvu+yv8ffze/DX9X/1u/Wj9Wv1H/SH97/za/AP9Qv2L/c395/0C/h3+Ef4C/uT9qP1s/Tv9Af3U/M38vPyu/L781vzz/Pv83vyn/GH8Bfyt+3f7S/se+wX7CPsd+x/7/vrT+r36sfqj+qP6nfqS+pb6jfqE+n36V/o3+j36X/qB+p76xPrl+vv69Prr+gX7Ivs1+0r7ZvuW+8X73/vf+8z7yvu7+6T7sPvd+yr8fPyz/Nj8Av0C/cn8f/w4/Bv8Nfxd/Hj8s/wG/UT9UP0O/bH8ePxq/HP8gvyr/N38Af0R/fz8z/yJ/C38Ffw6/HT8tfzW/Pn8H/0V/cH8W/we/A78IPw6/HH8tfzi/Pj8Cf37/Lz8dfwx/Cb8WfyN/KX8rfzd/BL9Ff3q/Kf8gfyO/Jv8oPy4/OP8BP0K/e/81fzG/Jr8cPyG/Mv8+Pz9/Pv8Ev06/RP9qfxi/FX8bPyO/Kn8yfz8/CH9K/0e/fn8uvx0/Ef8SPxw/In8nPy3/Nv8A/0Y/QT90/yw/Jv8k/yH/GL8Vfxy/Jj8xvzo/Pb8AP0E/f/88PzW/LH8hfx1/IX8pfzF/Mn80vz//Br9B/31/PX85/y//J/8jfyd/L780vzx/B/9M/0V/fz8+fzd/JX8UPxK/Ib8x/zw/CP9Yf2M/XH9G/3O/JH8Y/xF/Er8gfzL/Av9M/1Z/Wv9R/3u/I/8bfyB/Jv8ofyw/Nz8//wF/fH81/zQ/M/8xPzM/Or8Bv0K/fP82fzQ/Ln8g/xs/JL86fwo/Tr9O/00/Tb9FP29/Hf8Z/x//Kz84PwP/UX9Xf0//Qv90/yi/cT/7AErBMsGnQlZDHEOgQ/kDzQQnBBsEQETfBVuGFQbGB60INMiAiQmJMwjrSP4I1wkmiTiJFAluiW2JQgl0yNRIrsgUR9AHogdAx1hHJcbyhrNGXwYyBbQFOgSQRHrD94OCQ5JDYoMyQvhCsUJeggcB+IFygTUAwsDVgKsAQABOwB6/8L+6/0A/TD8ovtj+zf7CPvq+r76i/pb+i76G/oQ+vr59/ky+ov66vo3+3H7u/sE/Fb8rPzw/DP9j/3p/TH+YP5q/mz+jf7J/vX+EP8O/wr/I/85/yf/5P6i/nr+bf5d/j/+Kv4U/vP9tv2C/Uv9DP3b/L380vzc/Mz8ofx1/Hf8fPxZ/CT8E/wf/D/8ZPx5/Hn8g/x0/Fj8Y/x3/Hj8hfzD/P78GP0L/e/89Pwa/SX9+vzj/A79Uv2M/aL9lf2B/W/9Xf04/Rv9E/0L/RX9Mf1S/V79Qv0M/ef8zPyq/HH8MPwc/DL8UvxI/Bn87fvD+6L7hvtx+2T7UPs/+077XvtG+xT70/qz+rX6qPqh+sn6Bfsm+0L7RPsj+wf73frK+s36zfrh+hn7XvuP+6T7pfuk+637v/vF+8T7xfva+wL8LPw//DD8I/wt/En8Yvx3/JH8pPy+/On8E/0K/d/8vfyo/Kb8o/yZ/KD8xvwA/Tf9Tv1R/UP9Hv36/Ov84/zP/L/8yPzv/Az9D/3//PH88vzs/Nz81vzq/BL9Iv0Q/QH9//wE/e38wPyo/LL8y/zU/OD8Dv03/Tr9Kf0k/SP9JP0K/df8xfzI/Mz8zvzY/AH9OP1I/Vj9b/1Q/SP9+fzT/NH83fzh/OL8Af06/WL9a/1N/Sf9Dv0B/fr88vzr/PT8GP1F/VX9S/0n/QX9Af0F/Qv9+Pzp/Ov8Gf1T/Vf9Lf0C/f78FP0h/QP95/zy/BL9H/0Z/Q/9FP03/U/9R/04/SX9Cf0D/Qz9Av3v/Nr85vwf/Vr9ev1h/UX9Sv1G/Rz95PzM/OL8GP02/Sf9JP1L/W79bv1a/Ub9K/0Q/RD9Mf1R/T39Gv0b/UH9Uf02/SP9MP1B/UL9Of02/UL9Pf04/Tb9Lv0j/RX9Gf09/WL9Uf0t/SH9JP0d/Qb9+fz9/A/9Lv1S/X79o/2O/U39G/34/Oz82PzB/Nf8I/10/Zz9nv2U/Yv9Wf0M/c/8v/zN/Or8Gf1O/Xb9h/16/Vf9Rf01/R39Ff0V/R/9Mv0+/UX9Of2k/TD/0ABFAtIDkQV6BxcJ5wkyCqMKSQslDEYN0g6rEHMSKRTTFUAXPBiuGOsYcRk/GgcblBsQHLwcZx23HYYd9RxAHJkbChuVGkwaLRoWGvIZ0RmGGfQYCxjoFsoVuRS7E88SDBJmEcIQDRA9D10OdA2ADHQLeQqjCd4IIghoB6EGzwUEBSwESQN1Aq8BCAGOACQAw/9d/+7+fv4X/qz9M/3N/IP8Yfxh/G38efyG/Jz8n/x//Fb8RPxC/FH8ZfyA/Mb8E/1M/WL9Yf1l/V79Xf1b/Vz9ef2B/Yz9sv3e/fH91v2w/a39v/22/YD9Tf1P/W/9g/1//Xj9cv13/YL9ev1n/Uf9Hf0L/RT9I/0p/Sn9OP1Z/X/9if15/WT9V/1O/UH9PP1H/VD9b/2f/ar9o/2Z/ZD9iP12/Wn9cv2I/an9u/2t/aD9o/2b/Xv9af1k/U/9Mv0b/ST9QP1K/TX9GP0F/fz84vy3/Jv8g/x//Hv8Xfw8/Df8M/wh/Av86fvS+9f73PvW+9T7uPuI+1v7SftX+2j7dft0+3L7hvuY+337XftR+1T7ZPty+3P7k/u6+8n7yPu4+6b7i/t++5D7zfsU/D38RvxV/H78mPx9/Eb8KPwg/Cr8TPx7/K/85Pz3/Pb8+fzs/Mr8rPyp/M38/vwY/R/9OP1b/VP9J/31/Nr80vzW/O/8IP1a/YL9g/1v/XT9c/1G/Qf96vzx/AX9IP04/V79hv2L/XD9V/1G/TT9J/0e/Rr9Lf1O/W39hf2L/Xr9Yv1J/Tb9J/0W/Rj9Mf1N/W79hv2H/Yv9lf2G/WP9Pv0h/SD9MP1I/WX9fP2F/Yz9nv2b/YD9WP0z/Sb9NP1D/Uz9Y/2I/Zr9hv1q/Vz9Wf1b/UX9Jv02/WH9b/1n/Wv9cf1s/WL9W/1Z/Vz9U/1D/VD9Yf1l/WD9af2A/Y79if12/Wz9XP1O/Vv9Yv1l/XD9fP2O/Zj9i/1u/VP9Tf1W/Vr9Y/2C/ab9tv2m/ZL9if11/Vf9Qf1B/VD9Yf1s/Yn9rv28/aX9kP2d/ZX9ef1i/Uj9Pf1T/Wb9af1v/Xn9iv2r/bb9nv19/Vr9UP1S/VP9Tv1N/WP9f/2Q/Zr9gf1l/V39Xv1d/Ur9P/1O/Xn9nv2l/Y/9eP1+/Yb9bf1V/Ur9Rv1Q/V/9dv2G/Y/9jP2H/Y39jf2K/XP9cv2C/Xv9dv13/XP9e/2C/Xj9bv1p/W/9d/13/Xb9jP2g/Y/9dP1v/XX9d/1x/Rb+QP8rAPcA4AELA0MEAwU2BXAF/gWkBkEHAQgLCTYKPQsTDO8Mzg1pDsMONg/+D9oQexEBEqISYxP3ExcU9BPVE8QTsROaE6ATxxP7EysUUxRyFG8UNxTaE2wT8BJtEvERkBFPEQcRoRAhEJwPIw+rDhQObg3ZDE0MxwtPC9cKSwqxCQcJZgjdB1IHtgYeBpMFFgWkBCgEqQMtA8MCYgIHAqkBRwHvAKEAXQASAMz/jf9V/yT//P7h/sP+ov50/k3+Kf4D/t/9tf2W/Yv9hf11/XP9g/2D/XT9Wv02/R79Fv0S/f384/zb/Nj84vzq/Ob83PzP/ML8wfzG/M78zPzA/MD80Pzh/NT8vfyz/Lf8zvzS/ML8wPzb/AP9F/0Q/Q79Hf0s/SP9Gf0h/Sz9J/0d/TL9Vf1z/Wz9XP1l/XL9cv1i/VT9Vv1f/WL9dP2K/Zj9kf18/Wz9ZP1b/Ub9Ov0s/R/9IP0r/TH9I/0J/fX87vzm/NH8uPyz/Lj8sPyb/Iz8gfxq/FP8RPw5/Df8Lvwi/CX8J/wb/BH8BfwC/PX75/vt+/b79vvq+9771vvZ++D72/vL+8n70/vu+xD8Ifwh/Bn8Gfwq/C38D/z0+/H7Evw2/EH8QfxQ/HP8ivyQ/Ir8ffx9/I78mvya/Jr8mvyl/MT82PzR/Nf84fzs/Pj89fz1/P78CP0G/Q39Gv0Y/RT9E/0l/Tv9O/0y/TP9RP1K/Tz9Of09/T/9R/1V/WD9bP11/XL9Yv1R/Ub9Rv1R/VP9Yv12/Xz9gf2H/YH9eP1v/WP9Vv1O/Vn9Zv15/Y39if14/XD9dP17/YD9ev1s/W39cP1x/Xv9fP1v/WX9Yf1j/XH9av1p/YH9l/2N/W79Vv1N/U/9V/1e/V79Y/13/ZH9nf2W/Xj9Wf09/S79PP1H/U79Yv10/Yj9mv2T/Xf9Y/1g/VX9Rv1B/Uv9bv2N/Y/9gP16/Wz9Vv1M/UL9Pf1W/W39f/2a/ar9qP2S/XD9Uf1K/Uf9Q/1J/Vr9d/2F/Yj9dv1r/XL9a/1n/Wf9cf17/YX9kP2K/XL9UP1A/UL9SP1O/VT9av2N/aj9rf2U/XT9Wf1K/Uj9Qf1E/VT9Z/2G/Z/9mP14/WD9Wv1b/VP9Tf1d/W/9fP18/Xn9dv12/Wf9Rv1J/WT9cv1q/Wb9cv18/XT9Zv1o/Wz9bv1i/V39af1x/V39RP1P/WL9b/1v/WL9Yv13/Yb9fP1s/WD9Xf1a/VT9U/1T/V39af1w/XD9b/2W/Ur+Cf+V/yAA3wDTAbgCUwOoA/4DdgQGBZ0FSwYCB7YHfgheCUEKCgugCysM4gy9DYoOJw+vD00QBRGjEQISJRJBEnMStRLzEh8TUxOgE/cTQxSCFKgUsxSvFKUUjhRgFCsU9BPBE4sTRRPzEpwSSxL+Ea4RUxHrEIQQJRDGD1cP3A5SDsoNTw3LDDUMpAsjC6EKGwqGCfgIeQj+B30H+AZ9BhMGqwU2BcoEZAT+A5UDKgPEAmoCEgK0AV0BDwHJAIQAMwDz/7//h/9K/wL/x/6S/mP+NP4E/tr9rf1+/Vv9Rf0k/fr81Py8/K38oPyH/F38Ofww/C78IfwH/O375vvu+/j79Pvl+9f70fvh+/H77vva+8372Pvy+wz8Cvz++wX8G/wv/DH8K/wu/D38TPxd/HP8iPyS/Jn8pPyy/Lj8q/yb/KP8tvzI/NL81fzc/PD8+Pz3/Pj89vz1/O/87fzm/Oj85/zW/Mb8w/y+/Lj8uvy2/LH8rPyp/J/8kvyH/Hn8ZfxS/E/8R/w5/Cn8Ifwi/B38EfwF/P379vvs++P74Pvc+8/7vPu9+8f7wvu6+7D7qfuv+6n7nPuc+6z7sPur+6H7pfu3+737vvu++8b70fvW+877xvvH+8771vvd++H76fv5+xj8N/w3/Cn8IPwj/DH8Pvw8/DD8M/xO/G38ffyB/IL8h/yW/J78k/yI/In8kPyp/Lz8t/yw/L382Pzt/PH85fzT/NT86fzz/PL85/zi/Or8/vwQ/RH9D/0P/RL9F/0h/Sb9Hf0X/R79K/0v/SX9Gf0e/SP9If0e/R39JP0x/Tb9Of1E/Ur9Pf0r/R/9Hf0p/Sb9HP0Z/SP9Mv04/Tz9NP0g/Rf9H/0q/Sn9Hv0S/Rr9Of1G/Sv9EP0K/Rv9I/0R/QD9Bf0f/Sz9Mf0w/S39Hv0P/RL9Gf0P/fb89/wT/S/9L/0f/Rz9Kv0v/SD9Cf0C/RP9HP0T/QT9B/0Z/SP9Hv0X/RX9E/0Y/Rv9Gv0c/R79Gv0e/Sb9Jf0d/RL9DP0N/Q39Cf0B/Qb9F/0l/Sf9JP0i/Sf9LP0l/RX9DP0M/Qj9Cv0N/RL9FP0S/Rj9G/0X/RP9Gf0b/Rv9F/0L/Qr9F/0d/Rr9E/0O/Qr9DP0Q/Qn9Bf0I/RD9Fv0a/Rj9Df0G/QX9Bf0E/fj88/z+/BD9Iv0l/Rz9DP0C/f/8+Pzt/N784vz3/Aj9E/0U/RT9Fv0U/Qb99Pzl/N785fz0/AT9C/0J/f78+/z//Pr8AP2a/Xr+Kf/K/4QAdQF4AjIDgQPEA0UE9gSpBWgGMQf/B9YIugmmCoALMAzCDIANfA56DzwQ1xCOEWESIBOSE7sT2hMRFGEUtxQAFT4VfxXbFVMWwRbyFuQW0RbSFtQWrxZqFisWBhbqFbkVdRUeFcEUXRT0E40THROgEh8SuRFkEfsQahDEDyUPkw7+DUoNkQzlC1QL0wpLCrUJHAmRCAAIZgfGBigGkwUIBYYEDwSiAzwD0gJnAvsBjgEgAbMATgDw/5j/SP8B/8P+hf5E/gD+v/2L/VT9Gv3i/Kz8gvxi/Ev8N/wY/Pr76fvY+8T7nft4+2j7avts+1b7Q/tH+177Z/ti+1X7Tvtn+4H7h/uA+4b7l/up+7n7uvu4+8D71vvz+xb8Lfwo/B/8MvxT/Gv8cPxp/Gz8jPyr/LT8svyx/Lr8wvzH/MX8yvzV/Nz83fze/Of86/zq/Nz82/za/MX8r/yf/Jr8lPyD/Hn8e/yF/IT8bvxa/Ez8P/wp/AP84vvc+9f7yPu9+7L7s/ux+6L7jPtz+1b7Pfsw+yf7KPsq+yH7GPsZ+x77D/v3+uP60vrK+sz60/ra+uH65frl+uf67Pro+t362/rT+s361Pre+u76Cvsf+yb7JPsk+y/7Nfs0+zH7Kvsu+0T7Xft1+4D7fPt++5L7o/uu+7L7svu++8v7zPvP+9f74/vy+wD8AvwB/AL8EPwp/DP8LPwj/Cz8PfxQ/F/8WvxO/FH8Xvxm/Gr8Zvxe/GT8bfxv/HP8dvx9/JD8ovyf/Iz8fPx+/IL8iPx8/HH8ePyK/KH8qfyj/JT8ivyD/IH8efxw/HL8evyR/Jz8l/yS/I78kvyN/H38Z/xT/Fr8bfx+/IL8d/xz/IH8lfyV/Hv8XPxa/G38d/xo/FH8T/xk/Hv8e/xo/FX8Uvxn/HX8bvxg/FX8YPxz/Hf8b/xg/Er8S/xX/F/8WvxN/E/8Xfx3/Hj8Zfxc/F/8afxt/GT8Xfxa/F78X/xd/GD8XPxY/Ff8YPxr/HT8cvxw/G/8a/xg/Ff8X/xg/Fv8XPxb/Fr8X/xh/Gn8bPxn/F38Yfxz/HL8YvxT/FP8U/xZ/Gb8Y/xb/Fv8Yvxr/Gj8T/xE/FH8bPxu/FX8SPxT/GT8Z/xb/Er8SfxQ/E38SfxU/GD8U/xF/E38XPxa/Ev8PvxH/FL8RPwu/C/8SfxV/Fb8UfxH/D78QPxD/D78M/wj/CH8MvxA/ED8O/w4/EH8Rfw8/C/8J/wp/JH8qv2m/mT/OABOAZkCwgN0BNAEWwUrBg4HAwgTCS0KVwuHDMMN9w4EEN4QrxG8EvITCxXnFbMWmReQGFsZxxn1GR0aWRqmGvgaRhuJG9obOxyTHNocAh33HMUcihxSHA0cthtfGxYbwBpYGuwZcBnoGFUYthclF6AW/RVJFZ0U+RNXE5kSuhHWEPYPGw9FDoANugzkCw0LSAqeCe4IHQg3B3EGvwUNBVkErAMOA3wC7wFeAckAPAC6/z3/1f5+/iD+t/1Z/Q/9wfxm/Pz7pPtt+0n7JPv2+s76sfql+o76Yvow+hL6DPoB+vv58fnz+QT6D/oK+gv6EPoM+gz6Efoc+jH6U/p7+qn60fre+u76B/si+zf7Nfsz+1L7hfu2+8772vv4+xj8K/wm/Bn8KfxS/Hb8gvyO/J38qvy6/Mf8wvys/JP8iPyQ/Jj8mfyS/JP8n/yl/JT8c/xT/Ef8O/wT/O771vvQ+9b7y/uv+5T7fPtg+0T7J/sD+9j6vvq4+qv6kfp8+m/6bvpo+kH6FPrl+cD5tvmy+av5pPmf+aD5qPmr+Z35gPll+Vj5TvlL+Uz5UPlT+Vn5Yvlr+W35ZPlo+Xb5hPmG+Yj5kvme+an5sfm7+cT50/nd+eT57vn7+RX6L/o++kv6UPpb+nf6gPp7+oP6kfqn+rT6t/q5+s768/oH+wz7D/sP+x37M/tB+0T7Ofs5+0b7TvtW+137Wvtf+277ePuD+477lPuS+5L7mfuX+4r7g/uM+5j7m/uQ+477mfue+5f7ifuK+5z7mfuO+5D7k/uW+5P7jvuP+5P7jPt++3L7c/tx+2j7Y/ti+2r7dvuA+377fPt2+2z7Zfth+1X7SvtO+1f7Y/to+2H7WPtX+1r7VPtB+zD7M/tC+077WPtV+1j7aftr+1r7S/s7+y/7K/su+z37RvtS+1b7XPtn+2j7VPs6+zH7QPtO+0z7UPth+3L7b/tj+0v7O/s0+yr7M/tO+2n7eft/+3v7dPtq+1f7PPsn+xv7I/tA+2n7gvuA+3n7a/tp+177S/s1+y37PftT+2j7aPtn+2j7YPtS+0n7PPsu+zD7Rftj+277Zvti+2T7YPtR+zv7JPsa+yH7OPtM+077TftN+2L7bPtS+yz7G/sk+zH7NPsx+zL7Ovs++0b7R/s4+yj7FvsV+yH7LPss+y37Mvs7+0D7Mfsa+wf7CvsS+xX7EvsV+x37K/su+yj7HvsJ+wP7C/sh+wv8h/3C/uf/QQHuAroEIQb6BscH2wgsCpgLMw0VDxMRHxMtFT8XLhnGGiAcjh1GHwwhjSLWIy8lsiYfKBgpkinRKRgqaCqhKsUq9Co/K5sr6ysNLP0rtSswK4Aqvyn4KCYoUieRJuclOyVzJHQjUSI1ISEg9R6vHW8cTBtDGjcZCRi8FmMVDhSmEikRtg9WDgINvAuGCmIJRggYB+EFrQSMA3MCWgE/ADj/Yf6p/fn8O/x5+8T6Nvq1+SH5iPgG+Lj3gfdI9xT37fbH9p32evZa9kL2KPYI9v71E/ZJ9n/2jPag9ur2KvdA90r3WPd596r32fcA+EX4l/ja+CH5aPmo+eT5FPow+lv6m/rb+hL7Vfue++P7IvxL/G38i/yk/Kz8wvzy/Cb9Uv1u/YP9mf2v/ar9kv1//XX9a/1o/Wr9b/1o/Ur9J/0E/er8yfya/Gz8TPxB/Dj8DfzN+5/7gftO+/r6r/p/+mX6RfoU+uX5wPmd+W/5RvkT+dT4oPh3+FD4LPgC+Nr3uvel95L3gfdh9zT3H/ci9yf3EPfu9s32wvbW9uX24PbX9tv25vYB9xD3Affv9uz2/vYZ9yz3Sfd295j3rPfD99b34vfh99336PcH+C/4Tvhu+I34q/jR+Or4APkX+Sf5K/kz+VT5fvmL+YX5kPmw+dX56/nu+fn5HvpB+lX6V/pZ+l36WfpV+k76UPpW+mb6jPqw+rv6sPqp+qb6pfqf+oH6Y/pt+ov6rvq1+qT6ofqj+qD6jfpq+k36RPpK+mD6dPp2+m36dPqE+oP6d/pT+iP6CvoR+hb6DPoL+hP6J/pH+kr6KfoM+gP6CfoB+uj53fnp+QH6FvoV+gP68/no+dz51vnf+eD53Pnb+e/5CPoM+v/58/n5+Qr6B/rr+d/54/nk+d754/no+fD5AfoJ+hj6K/ow+iD6D/oK+gn6DPoF+vT57/n1+Q76JPoq+ib6MPpB+kn6Qfoo+hH6DfoS+hL6I/or+iv6L/oy+jf6Ofot+hj6GPoe+iz6N/o1+i36Lvo1+jD6Kfoi+hv6E/oT+h76Lfog+gr6DPoP+hr6JfoR+v/5//kJ+iP6L/oW+u/53Pnh+fD57PnW+dH57PkN+hf6EPoJ+vj53PnQ+cz5wPmy+bn52Pnx+fv58vno+er58vnk+cH5rfm8+dT51/nU+dP50/nb+d752PnQ+cX5xfnQ+dT50/nR+c753Pn0+fH51vkL+mj7Kv2p/j4AMQKGBOIGvQgBCj8LyAx3DloQrRJfFUEYShuFHtAh3CRbJ3EpqysiLmwwRjL3M+M1/zfrOTA75ztpPMw89TzwPOc82DzJPME8uzyUPB88OTv4OYk46DYcNS4zUTG5L0ouwSwaK3Yp4yc6Jl8kcyKLIKgewxzqGiAZVxeIFbMT1RHpDwMOMgx5CuQIYwfXBVEE8QKnAUgA4v53/RT80fqq+aD4tffc9hX2cvXs9Gz03vNb8wHzxfKM8lzyOvI28k3yavKQ8q/yxPLp8ijzafO18w70YvTF9Dn1pPX19Un2qvYH91n3oPfp9z34k/jl+D35lfnf+R76b/rK+in7dPuj+937Jvxy/Kn8xvzr/Cn9Uf1p/Xv9mv3F/ez9Df4l/j7+Uv5c/lv+Rf4q/gT+0v23/aT9jP1o/T/9Jf0R/ez8nfxH/Az81/uP+zn76fqv+oD6UPoX+tP5jfk5+d74kvhH+PH3pPdm90D3Iffr9qv2gPZV9g/2vvVw9S/1C/X39N70yPS+9LD0k/R+9G30T/Qe9PHz5PPx8wv0HvQx9FH0cvSF9Ib0hvR/9Hz0i/So9Mv0+fQr9Vb1iPW/9dz18PUF9hj2NvZh9or2pPbC9uv2I/dc93r3kPe099v36/f29wn4Jvg/+FP4d/io+Mj43Pjv+Af5JPkl+Qz5AvkZ+T/5V/lW+VT5Yvl5+Yn5jfmD+Xz5fflx+XL5g/mB+Xb5dvmC+Yf5gflq+VH5SvlO+UT5J/kc+S/5RflC+TL5LPkl+Rj5//jm+OP48Pj3+On41/jK+M/41PjC+LP4sfi8+Mj41fjo+OP4zviz+KH4o/il+Jb4g/iN+Lb44Pjo+Nn4yvjD+MD4uPim+JH4iPiT+Lr45Pj0+O/46Pj4+Pf42/i5+Jj4kPiq+Nb49vgD+Qj5G/kw+Sz5Dfnp+Nn41vjU+Ob4APkW+S75Nvkw+Sr5GPn8+PL48Pj2+P/4EPks+Tv5Pfk5+Sv5GvkL+ff44vjf+Pb4Gfkv+Sz5K/k1+UL5MfkE+eL44fjt+PL4AfkO+SL5QflG+TP5IvkH+d/4zPjW+On45/je+PH4IflJ+Tr5BPnd+OP47fjV+Lj4sPjO+PX4//j++AX5A/n0+Nz4yvi/+L34wfjP+OT45PjY+NT43Pjj+Nf4s/ik+LD4zvjl+NX4w/jN+Nr40/i/+Kf4m/io+Ln4u/iw+KX4pvi7+M/40vjG+Pv4bvpc/B3+9v8pAsgEgAefCRsLqwyBDn0QwhKPFcsYWxxBIGYkqSiTLMwvjzJwNX84SDuZPa8/EUKzRCFH/Eg6ShVLuUsZTCpMDkzUS59LcUspS6JKs0lNSINGfUQ2QrI/BD1oOhw4AzbwM8Mxdi8qLdoqZSi9JQQjYSD2HbobhBlRFyIVCRMCEfIOzAyYCmwIcAa7BCwDogEYAKT+Tf0G/LD6QPnU94X2YfVv9J7z7/Jd8tnxavET8c3wgfAv8Pjv8+8b8ETwbvC08BrxhPHf8SnydfLp8m7z7vN09A31rfVG9tD2VffM9y34evi8+A/5fvny+VT6tfoV+3372vsU/DL8U/x5/Jz8u/zc/An9Pv1w/Zf9wP3c/d/91/3V/dv96P3s/dv9zv3c/fP97v3H/Y79Vf0m/fH8sfx1/EX8Gvz7++D7q/tl+wr7nPo5+tv5cPkA+bD4evhH+Bn42feF9yf3xvZj9gj2s/Vj9RT12/S/9J30dvQ99PHzrvN48z3z/fLP8rnytPKr8pTyjfKR8oLyafJL8jHyKPI28kLySfJh8nnym/LA8tfy2fLi8vzyIPNC81/zgPOt8+jzJvRZ9Hz0nfSu9Mb0/fQ79Vn1Y/WK9db1LfZa9mP2cvac9tX26/bo9u32Cvc893X3mfe099H36vcB+Bz4K/gW+Ar4CvgP+Cr4TPhV+Ff4cfiW+Kr4mPh/+Gv4Yvhg+GL4W/hV+GP4ePiQ+JL4b/hT+ET4Ovgs+B74EvgT+Cb4Nfg9+Eb4QPgn+A34/vfo98P3qfeg96v3yfff99735Pf09+732vfC96f3h/d293z3jPeb96P3p/e899X3y/ey95r3kfeW95T3kPef97330vfc9+33Afj599D3ofeT96X3sffB9+n3E/gp+Df4Qvg3+Bf49vfc98z3zPff9/n3GvhB+F34WvhB+C/4IfgV+An4/vf69wX4Gvgx+EH4N/gs+CX4FvgF+Pn3//cQ+Bj4H/gw+DD4I/gU+Av4D/gJ+PL33/fr9wj4H/gV+AD4/PcJ+BD4DPgL+Af4CvgM+BL4FPgI+PP35Pfg9+L35vfs9/n3Cfgk+Cn4G/gK+PP36/fx9/H34vfZ9+f3/fcU+B34DPjk98n3zPfX99/36/fn9+r3Evgp+Cb4EPjp98b3xffE97f3vvfR9/X3Fvgk+B/4D/j69+b34vfp9+b3zvfM9+r3Efgg+Aj47vft9zL4oPmq+5v9u/9BAksFhwgdC+IMmA6VENgSXxVZGAQcTyD0JNcp9S7RM+o3VDugPhRCTkUBSGRKAU0QUBFTZlX0VgJYuVgSWQVZp1gkWJxXCFdhVpBVWlSZUj5QaU09SttGUEPQP448iznONh80VjGBLpwrqCiKJUAiAB/vGxQZdRbxE4kRUA8mDe0Ksgh8BlMEWgKNAP7+lv09/P760fml+Gb3Ffa39G7zUPJw8dPwXPAK8Mzvnu+N74PvX+8k7wLvAO8f73Xv7e978BHxq/FL8u/yk/Mc9IT0+/Sc9Uz2DffC92v4IfnL+VL6wfoc+1f7h/vB+wj8YPyy/Oz8KP1x/a/9zf3J/cD9uv2t/aL9mv2a/aL9n/2V/Zn9qP2z/bD9kf1v/VH9OP0l/fj8yPyb/Gz8Q/wf/PX7tftk+x776/qu+lj6+fmt+Wn5Ffmu+EH43Pd19wT3lvY69uL1e/Ua9cj0gPRA9Pzzq/Nb8xTzzvKJ8k/yEPLT8Z3xafFE8S7xCvHd8Lbwq/DB8MzwwvC/8M3w1fDf8NLwr/Cx8M3w5/AE8SfxWvGJ8bDx0/Hv8Q/yJ/JC8nbyu/IC8z7zcvOn8+DzFPQz9Dz0TfRw9Kr03/QR9U/1k/Xd9Rf2P/ZU9mL2Z/Zr9oD2oPbG9tf24/YH90n3efdx91f3W/d695v3qPeh95r3p/e097n3uveo95D3g/d+94T3kveZ94v3jPef95/3l/eE92X3VfdN9zX3F/cH9wD3+vbx9vz2F/cq9yv3GfcK9//29Pbc9sb2u/a59rT2xPb29h73FPff9rn2w/bd9tb2sfag9sH29vYj9zj3LfcO9/X28fbx9uP2wfaX9qn2+/ZB90n3Jvce9z/3W/dM9x/3/vYA9x73OfdG90f3QPc590X3XPdi91b3UPdn94X3jvd691b3UPdg92L3TfdH92j3kfew96X3gvdr92T3bPdj90j3Qvdd94n3qfey95b3dPdk92D3afde9zj3KfdO95T3wPew94H3bfd893r3Xfcu9yP3RPdr94/3pPee95T3ifdy91j3O/cq9yv3Tvd/9473gfeA94n3gPdg9zX3EfcL9yb3OvdB91T3Y/ds93j3a/dW90H3J/cf9yj3Jvcg9yL3I/c190b3Qfcz9zX3R/di93f3bfdb90/3SPc99y73JPcc9x33M/dP93D3efdu9173UfdU90/3Ofcz9zf3Tfdr9zX4PvqJ/Lb+LQFRBOEHMgvHDd8PMxLUFKEXwhqaHh4jDihgLRgz+zhjPupC+kYaSzBPtlKWVVpYeFvDXoVhi2MiZVBm7mYAZ6pmGmZVZU1kEGOsYRBg9F0oW8JX+lPbT3RL9UaYQoY+sjoSN4UzCjCfLBwpYiWQIdEdLhqjFj4TJxBhDeYKkwhRBhgEBwIbAD/+fvzk+nf5O/gx9zr2RvVM9FDzcfKl8c3w++9e7/vuz+627qXute7d7gvvO+9w77fvBfBM8LTwQfHQ8WHyAfOx83P0OfXu9aL2XPci+OX4nPlE+uH6bPvn+138vfwC/Un9nv3g/ST+W/57/pf+tv7I/rr+kf5Q/iP+IP4f/gD+z/2t/az9r/2P/Uv9//zG/JH8WPwy/AT81vu/+7T7svuc+0373/qO+l36J/rG+VD57fit+IP4Qfje92r3+vaQ9jP24PV/9Qf1k/Q99PHzlvMe85TyKPLw8bbxXvH58LPwnPCQ8GjwIvDe767vjO9g7zfvFO8F7xXvMe9E70HvQe9P72vvdO9173Lveu+d79PvC/Az8EzwbvC08A7xUfFg8XHxsvEL8j3yTfJt8q7y+/I683nzuvP88zP0YfSe9Of0EPUP9Sn1efW29cT11fX79TH2ZfZ39oD2j/af9qv2uPbW9uT26vYK9zD3Q/dA9yD3AfcF9wr3+Pbp9u/2/fYY9zH3L/ce9wf39fb49vz26/bY9sn2xvbZ9uX2yfaf9oH2e/aJ9pz2nPaL9pH2rPbG9tH2wPaR9lv2PvY79jX2KPYj9jL2Zfab9q32pvac9pX2hPZ29mX2TfZD9kf2XvZ79o72jPaC9oP2kfac9pP2hvaS9r324vbf9sP2uvbO9tn2yvav9pv2qPbR9vT2A/cK9/728fYQ9z/3Sfcl9/b2APc191L3NPcD9/72I/dA9zj3Kvcx90v3V/da92v3dfdZ90P3V/d+93n3OPcS9yr3UPdV9zn3LfdP92r3cfd994D3c/dS9zD3Jfci9wn39PYI9zb3UPdP91H3VvdL9yT39/bZ9s32wfbG9uz2IvdJ90j3Pvc89x334/at9qP2sva29rX23PYe90n3T/cp9wn3BPfu9rX2j/aZ9rz24Pb59hz3N/c69yT3Bvfz9tz2tPai9rL20fb89gr3CfcQ9xP3Affl9ub28vbw9vH2Dfcp9yv3EPf49vP26/bX9s325fYM9zb3SPcB+C76nPzE/ioBQQTpB3ELKw5WELQSeRVzGLwbvx+CJLUpQi9WNag7dkFQRodKzE41UxxXPVoeXVhg12MGZ3FpDWskbNZsCm3EbBxsMWsQasdoUWd1ZfZiwl/tW59XAlMkTi9JUES6P5A7mDeoM7UvuyuqJ34jRh8FG/IWORPLD5IMpQnzBnkEOAIGAOb97fsv+rP4afdC9kT1ZvSd8+fyK/Jp8a3wBfB77yfv8+7N7s7u8e4574Dvq+/P7/7vU/Cp8PbwZPH48ZXyNvPc83/0FfWe9Tv27/a093D4K/n++dH6ifsg/In85PxA/Xr9n/3a/Sb+bv62/gH/Rv98/5b/hv9b/zL/Bf/F/oH+Rf4e/gP+6v3S/aj9b/00/fX8tPx2/DP8Avzp+9L7qftu+x77xPp0+hb6svlQ+f34x/ii+Hv4Qfjr94n3JPew9ib2lvUc9bb0WfQD9KzzVPP58pPyIvKp8SfxwvCB8FPwO/AZ8PTv1++u72Tv9O587iXu8u3f7ebtCe5H7p3u4u4R7yjvDu/Q7p3uke6h7qrute7y7nHvD/B38JzwvPDw8CnxR/FE8U3xjPHk8ULyn/Lx8kTzjfPG8wr0QfRa9Gr0kPTZ9CP1WfV/9bn1AfZB9m32f/aC9oj2nPaj9rD2tvbB9ur2IvdH91P3VvdV91P3NvcU9/b23fbf9u72/PYL9xX3F/cp9yv3Avfa9sz2wva59qz2nfai9q32svay9qD2jPaD9n32gPaG9oH2cfZx9oX2kfaI9nn2ZfZV9ln2YfZV9kT2SPZX9mv2dfZz9n72mPao9qr2pPaF9mn2Y/Zx9nb2aPZ49pz2x/b69g73+fbc9uH26vbi9tD2tPa29vP2L/c79yP3CPcQ9x/3J/cW9wL3DPcw9273jvdz90v3Lvcj9yn3HPfz9un2GvdV93/3kfeA9233bPdh9z33EvcA9xT3NPdT92v3fPeB94T3e/dh90j3L/ce9yf3Svdw94D3ePeE9473evdg9zv3LvdB90P3Nvc090j3bPdz91T3Pfc09y/3Jvcb9yv3R/dG9yb3F/cw90n3K/fp9tb2Afct9yn3DfcF9x/3M/cl9xj3E/cO9w/3Gfcs9z33Jvf59u/2CPcf9xH36fbk9gv3OvdF9zX3LPcv9zD3J/cW9w33Avf19vT2B/ca9xD3C/cl90H3N/cW9wn3HPdJ91T3Pfcn9yz3PPcy91r36vhH+4v9EgAzA94GkAqTDcEP2BE1FKkWYxnxHHghnyY0LDsypzjjPjtEokjCTOhQolSyV4Van10FYU9kEGcqabJqqmsJbORrUmtoajJpzWdIZoVkQmJRX61bc1fRUt9NwUijQ8M+TTosNiwyKS4kKh0mBSK2HTkZ3BTWECINtwmnBvEDkAFr/2T9cPuR+c/3RfYG9Qz0PPN58s/xUfH38JLwA/Bt7/zut+6q7tLuHe9379LvNvCZ8OPwD/Es8VzxofEA8n/yJ/Px86r0QfXY9Yz2KPeX9/z3c/gX+dL5e/oV+7j7TfzC/C/9lf3g/RP+Of5y/sv+IP9P/1r/Y/95/4T/dv9W/yj/B//r/sj+sv6h/nr+N/7u/bX9g/0+/eP8i/xe/Dr8/Puh+1L7J/vm+pD6QPrr+Z/5TfnX+Hj4OPjf92P33/Z39h/2xPVc9fX0nPRM9PDzhfMf87zyXfL68ZTxOPHq8J3wSvAQ8OHvre9070HvGO8A7/bu1+627qnur+617rzuv+7B7sHuw+7Z7vjuFu8l7z7vfO/N7xbwVPB+8Kbw2fAS8UzxevGi8c/xEvJm8snyFvM782PzsPMD9D/0bPSa9NL0FfVj9an13vX39Qv2KvZh9pv2s/as9rT25/Yj9z73PfdS93X3iveR9573pfeb94X3bPdl92L3XfdN90j3ZPd793z3dfd79273Svcq9wz39fbd9sr2xfbT9uP29/YF9/326fbH9p72kfaW9oH2Z/Zx9pP2t/bT9tP2w/az9pr2ivaP9of2avZk9of2vfbm9uf22/bk9vL29fbi9tH20PbV9tj24Pby9v72B/cK9xX3Jvcn9x/3Hfc+9173UPc59zP3Nvc49y73FPcQ9zH3U/dv94L3gfeB94X3g/d290f3F/ci91j3hveR94f3hPeU96v3pfd791P3RvdV93P3mPef95T3o/e+9733ifdG9yr3UPeE94z3iPeX97v33/fc96f3c/dP9zn3OfdJ92b3eveO96f3x/fn98f3gPdb92X3dvdm9zX3IPdM94/3lvdx92z3fveE93j3a/dx93n3XvdO91/3Zvdb9zn3L/dd94z3g/di92j3j/ef94H3YPda91v3afdx93j3e/dx93L3gfeQ94T3Z/db92r3fPeE93X3YPdt94T3gPdy91r3O/dB92X3e/du91X3S/dl93z3bPdA9y33QvdQ93/30/gX+1X9of9RApwFKQkpDGAOcBDeEowVVRicG8EfpiT5KaUvvDXSO01B9kUwSnFOiFL1VcpYqVvWXhFi12TsZn1opGlTanZqKGqGaZloYGfTZfBjqmHEXh5b3VZAUmZNVUg2Qz8+oTlYNTYxES3gKKwkdSAiHK4XSxMjD0ELpwddBG8B1/6I/G/6ivjU9kH13PO58tXxFvF38NzvXu8P78DuY+4M7tPtvO3H7fftU+7S7k3vsO8Q8IPw6fAz8Wjxp/ER8pzyHvOS8xr0tPRH9cn1QPa79kX30vdm+Bj5yvli+uT6WfvZ+1b8pPzO/Az9Zf3P/T3+j/7T/iP/cf+q/8f/wP+n/53/pf+b/33/aP9Y/0z/Ov8W/+n+sv5i/gb+vf2D/UX97fyL/Er8EPzJ+2z79/qD+gn6jvkO+ZL4Jfi+92L3Bfeb9jf20/VM9br0NfTC82Dz+/KR8jHy8fG/8XTxAfGS8Djw++/N75LvbO9N7z7vOO8q7xXv8e6+7pHug+6P7p7uqu7R7h/vcO+l77nvu++/79Pv6O8C8CzwbPDA8CDxkPHy8S/yR/Jm8pHyvPLt8hzzXvPB8zj0lvTg9CP1T/Vy9Yj1nfWy9c31+PU89pf27PYZ9y/3Svdm93/3e/dX9z73Uvd996b3yvfW99T31vfV98P3pPeG9273a/eA95v3q/eu96X3nPef94n3UfcT9/X2AfcY9x73Efca9yv3L/cv9y73FPfu9tL2w/bT9tr2yPa99s723/bc9tH2xfbB9sH2vPa79sb2yfbI9t328Pb19un2zfa09rf2yPbI9s322fb39hf3Jvcj9xz3E/cN9wb3+fb79gf3HPcq90H3X/dr92T3Wfdf92P3X/dV90D3Tvdx94L3lfem9633qfeh95r3nPee95f3lPep98X30/fZ98/3x/fG97/3r/ex9773vffD99H32PfY99333/fV98P3ufe697H3nPeQ95P3ofet97H3tfe498L3xPfD97/3sPeR92X3T/de93f3dvd194b3q/fO9873s/eP93j3afdY91T3VPdh94f3pfe797v3nvd592X3ZPdb9073Uvdl94f3tvfP98D3n/eH93D3UPc19y73OfdT9373rffI98P3pfeE93P3aPdO9zD3Mvdb94r3p/er95n3ifd892T3V/dV90T3Q/dw96v3wfeq94H3Zvdk91r3O/dC95z4+fpd/cz/mgL2BX8JiAyyDpUQvxIsFekXUhuXH4Uk7inVLzI2jTwmQrpG6UoqTy1TflY/WRBcWF/NYstlG2jjaThrAGwzbOtrOWsoasFoIGdOZSBjO2B3XCNYeVOKTlNJ5UObPsY5YTUiMeosrShZJOcfVhu2FhwSnA1OCWUFCwIp/5n8Rvos+Ej2ivTz8n7xNvAp72Tu5e2c7WjtHe3P7KDsdewx7Pjr7usk7KDsQ+3m7Y3uM++z7xPwWfCH8Jjwo/DZ8Enx2PFu8v/yk/M39N70b/Xk9Uv2rPYg96z3QvjO+Ff56Pl0+vr6b/vW+zz8qvwf/aj9Of60/g//ZP+3//P/DgAKAAMACgAmAEsAaAB4AIUAfwBhADoA+v+W/yv/z/55/ib+1f16/R/90Pxw/Ov7U/vC+jH6p/kf+Yb48fd/9x73q/Yf9ov1AfV/9PTzZPPc8nPyDPKv8WrxKvHf8IPwL/Dj753vS+/u7qbuhu547mbuWu5l7nnugu6H7ojul+6d7oruiO6i7sLu4e4G7y3vcO/M7xjwXPCg8NXwCvFF8X7xs/Hn8SDyaPLB8hfzWvOi8+jzMfR29Kj01fQO9VT1lvXa9Qv2OvZs9p32y/bo9vj2//YU9zv3Z/d994j3svfs9wX49PfR97j3tve497j3tfe+98736/cb+Dj4HfjV95T3dvdo90z3IfcZ90P3e/ed96n3pPeR93f3TPcZ9+n2xvap9qf2xPbu9gL3/vb99vn2+fbx9s72oPaS9pj2mPac9qb2u/bH9sb2wPbF9tL2wPag9p/2tPbF9r72qva29uT2+/b29u724vbu9gD3+vYC9w33CfcV9yn3L/cv9yD3DPcV9yj3NvdB90b3W/dz94L3hfeB9373evdw92L3Z/dt9233avds94n3nfec95T3pPe797b3qfec9573oveb94j3g/eQ94v3dvds93f3hPd993z3kfei96P3mveE94f3lfeG92T3T/dV91f3SvdC90z3afeA9333c/eH96j3rPed94r3efds91v3TPdK90v3RvdK92f3kfen9533kfeW96D3m/d591j3U/dU91D3U/dO90r3Rvc/9033XPde91T3Vvdn93r3gfdt91f3TvdJ9zX3Fff69gH3Gvcy9zX3M/dT9373jPeE92/3WPdQ90b3PPc29yv3Ifcb9yz3R/dL90D3OfdR9xn4Jvp9/ML+XgGOBC8ImgssDhsQMBKtFGcXeRpIHgojiCiELvM0oTvhQShHukslUH5USlhIWwleO2HZZD1o/WolbeZuRXAOcTRx3nAjcANvjW3La5hpuWYUY9BeHVoOVcRPUUr5RPM/RzvVNmQy1i0oKWgkiB97GmAVZxDGC5wH2gNzAH/97PqS+GD2UfR58t/wfu9B7kftoewf7KjrQ+vy6rDqcOoy6hLqIupg6rjqKevA61vs4OxJ7Znt4+0i7lXue+6l7vHuZe/e70fwsfAr8bHxMvKj8g3zhvMd9MX0bfUQ9qv2OvfI91349/h2+eH5bfoh++b7nvxC/eD9jf42/7f/CwBKAH8AswDxADQBYAFzAYgBrQHLAcMBkwE/AfIAwgB+ABwAsv9S///+lP7z/Tr9hvzK+xb7Z/q/+Sv5mPgP+JL3E/d09rX18PQ99Irz3PJI8snxcfEc8b7wYvAJ8K7vP+/L7mjuIu7t7dbt2u3r7f/tBe4J7v7t2O2j7WjtTu1s7Zjtxu0P7nTu5u5F73rvkO+X76Xvwu/f7/7vPPCb8AbxdPHT8R7yWfKN8sDy+PI683jzs/MI9HD00vQX9Tf1R/Vn9Zv1xvXm9RL2VPal9vv2Pfdr94/3mveE93n3f/eF94P3i/eu99f3/fcO+BL4D/gK+P333ffC97T3qvek96/3t/e196n3kvdw91n3Q/cp9xz3GfcV9w/3Ffcb9yD3Fff09uD20Pa29qf2nPaU9pH2i/aH9o/2pfat9rL2s/av9qf2nfaO9nT2VfZB9lD2cfZ79mn2afab9tn24va49pf2mPah9pf2gPZ89oz2oPaz9tT2+/YA9+P21Pb19hb3Dffb9sn28/Yq90H3LPcg9zf3TPdG9zD3Jvcp9yj3MvdL92v3evd593n3ffeI94L3XfdA90L3Xvdz92r3Yvdl93n3k/eL92v3Wvdf92T3YfdQ90L3Svdd92n3YPdW90T3L/cn9y33LPcQ9/j2+PYY9zf3Qfcq9xr3NvdX90n3Fffo9s72zfba9tD2ufbP9gT3Pfdp93j3dPdZ9y73DPf09s32nfZ/9pv24/Yi9zv3Qvdg94z3k/dg9xb33fbJ9tD22fbj9vD2+/YZ90v3Z/dU9yT3//YF9xr3F/cH9xD3MfdI90X3IfcC9/f26Pba9t724/bx9g33Mvda92H3O/cS9wv3DvcH+B36c/wE//4BhQVfCeUMjA+tEekTZBYPGS8cOyBJJSIrdzE8OCQ/h0UHS9pPeFTFWF5cUF86YqxlZmm9bGVvnHGIc/x0sXWqdSx1UHQWc3pxk289bRpqMmbMYftcvFcEUhVMbUZDQW08rTf1MkQujym7JKEfVBr7FLYPugo3BiwCpf6O+9f4f/Zo9IHyvPAP74DtKuwg60zqmOkF6ajoe+hr6FvoP+gw6E7ojejc6ETpsekn6qzqNOuu6xLsUexs7KDs7+w67Xztvu0X7pHuI++27y7wmvAf8b7xVvLS8kvzzvNq9CX17vWu9m/3PPgB+cv5kvo7+9D7bvwg/dP9ff4h/9P/kAAxAa4BBwJDAnACkgKiAp4CggJfAkwCRAIwAv0BrwFbAfgAaQC6//3+SP6T/dX8Ivxx+7P6AfpP+Z344PcH9yz2afXP9Cr0bfO68hrymPEZ8YLw6O9l7wrvwu5/7jXu5e2j7XntX+017fvsuuyR7JXsvezZ7O3sCO0x7Xjtpu2m7Zvtq+3X7RHuSu587sTuIO96783vHPBb8ILwtfD68EfxjvHG8QjyZvLL8h/zXPOQ89nzIvRe9Jf0zvQL9Vz1pfXX9Qf2OPZw9pT2pfbP9gf3NfdV92f3gPeo98L3v/e298T31ffb9+v3BfgV+BP4D/gP+A749Pe393/3dveF94f3ePd394z3nPeg94X3Wvcv9/721fa89qv2jPZ89o/2ofaf9pD2gfaN9pj2dPZC9in2KPYj9hX2B/YC9gH2APYC9gH2A/b89fL1AfYa9ib2H/Yb9in2KvYZ9gf29/X19fv1B/YY9jj2VvZz9on2lfaY9pD2jvaB9m72XfZY9nT2mPag9q/21Pb+9hn3E/f99vn2//b39u72+fb69vT2+vYJ9xz3KfcZ9wj3MPdl9233WvdL9073YfdX9yP38fbp9vn2E/cs9zv3TPdj93z3gPdw90v3Gff29uX26vbx9vX2BPcg90n3XPdI9xT39/b99v324vbB9sP25vYM9xz3EPfx9uH25fba9sH2r/az9s728PYK9xD3CvcG9/724Pay9pn2hfZ59pT2vfbk9gj3Gvcx90T3Lvf09sD2pvaX9oz2gfaQ9sH28fYJ9wX3/fYA9/z24fbI9sf20vbb9t/26/bx9uP2wvav9rT2tfar9rL21/YJ9yH3FvcI9/n2Gvd++Nr6TP3i/wgD8QYmC64OERELE20VGhjvGlMewiI5KHAuSDWgPPJDX0qhT2RUMlmIXelgtmPYZrJqvG4hcrx0AncBeVB6vXqLevJ5A3m5dxl2H3SUcShu6GkPZbxf+VnNU5pN4Ue0QsY96TgINDUvXCoyJZ0ftxndE1gORwmfBF8Anvxw+cz2hfRf8kXwUu6Z7Cjr9+n66AXoMuet5lTmDOa+5WjlOeVd5bLlG+aZ5ijnxudt6ATpcOmq6b3p0ukG6jjqYOqe6gTrf+sD7IHs9+yD7Rbum+4i763vQPDb8HXxDvK08mnzKvT19ND1s/ai96L4m/mN+oD7Y/wn/eL9r/53/yUAsgAyAdABdQLyAjcDaQOjA+YDEAQCBNYDpQNpAw0DnwIgAo0B4QA8ALH/I/91/p/90vwi/Gr7efpo+Wn4jPfD9u31BvU+9Jrz/PJi8rvxIfGO8OnvTu/T7m3uAO6e7VjtOu0f7eLslexd7E7sT+w67BrsK+xr7Knsy+zv7BftOO1S7V/tbe2Q7cftBO5T7rruIe9+79XvKfB08LLw4PD88BfxTPGh8frxVvKv8g3zevPX8x30VPSG9Lj03/QE9Tb1cvWp9df1FvZm9qP2yPbd9v32Lvdg9333hfeR96f3xffU99j30/fC98L33ff59/339/f+9xP4Ivgc+Pn3y/eq95b3iPdt90b3Jfcr90P3TPc79x33CPf29tX2p/aA9mb2UPY19jP2Q/Y/9h32/PXm9db1yvW59bP1uvW99cv17/UD9vL1yvWg9ZH1jvV89Wj1YvWI9dL1FfY59jr2N/ZB9lX2TPYP9tH1vvXe9Rj2R/Zh9nn2m/bP9u322/as9n32cvaJ9qH2qva09sv2/PYi9yD3/PbU9sb20fbg9tj22vbz9iL3PPc59zD3IvcN9/L25Pbf9uD25/b79hL3I/cg9xL3FPcW9wf33vbC9tb28/YA9/v2+PYC9wj3APfq9sv2r/ae9p/2sfa/9rX2rfbC9uX28/bT9qb2oPa09rf2jfZh9lL2ZfaH9or2hvaS9qX2t/bC9sP2t/aa9nn2ePaJ9on2c/Zj9nb2ovbL9tH2tvau9sz20/a39pH2e/Z+9pf2rva09r32v/bB9tb24vbK9qD2hvaI9pz2r/ao9pf2qfbQ9t320/a19pP2j/ae9pz2hPZ89ob2qPYN98/4Yfvd/ZIA7QP0BwwMZw/LEfQThRZfGV8c+B+eJEcqzzADOI0/5EZvTQRTGFj/XEthpGR3Z5ZqXm5YctN1injbeu18a34Of9R++H3NfFx7gHkldyl0cnAQbCBnq2G7W2hVGU8qSbJDkj6DOVk0Ni8YKsIkAx/mGNMSGw3bBwEDov7b+rf3HPXH8pnwhu6Q7LjqGenA56fmtuXu5GrkPeQ15BTk0+Oi47Xj+ONM5KTkHeXQ5ajmbef951roo+jT6N/o5Ojo6AjpSum86VHq8+qt63DsJe287VPu6u5t7+bvdvAh8crxe/JA8yf0MPU69jD3N/hZ+Xr6i/uI/Hz9Wv4b/9D/egAlAcEBPgK8AkYDzAMwBHMEpwTIBNIEtAR6BCAEqwM0A7ACHAJ+AdAACQBE/5r+3P37/A78JftI+mn5f/h/93v2gvWf9NHzC/NU8qDx9vBv8AHwfu/h7kzuxu1P7e3sm+xN7BvsBOwC7AvsGewb7AjsBewX7DXsSexQ7GXsnezu7DPtZe2f7ertMu5u7pzu2+49757v9O9B8Jfw/fBT8Y7xwPHo8QfyPfKW8vPyTPOt8wH0bPTg9Cj1RfVV9W/1mfXC9eL1CvY29nv23PYu91v3c/d89333hPeT95P3jveh98j36vcS+DT4M/gY+Ov3z/fO98L3pveb95P3mfer96n3ifdi90H3J/cm9yL3DPfs9t/26fbl9rX2bPYp9gf2BfYH9gX2DvYr9kv2cPZ99lz2FPa99Xr1XPVF9Sf1KvVu9dP1JPY/9jX2LvYd9uj1ofVa9Tn1O/VY9Zz19/U09kj2WvZm9l/2M/b59dv15/X89Q72PPZv9pj2qvak9p/2jvZx9lX2WPaA9q72zfbn9gv3E/cG9/L2zfaw9pj2iPaO9rr28vYS9yT3Nvc49zD3Fffm9s32x/a09rH2xPbj9gP3E/cV9xT3Bvfo9s72vfaz9qX2ofaz9tz2//YE9/728vbf9sX2pPZ89nH2hPaU9qT2ufbN9tf25fbf9sX2sfal9pf2hPaG9pr2s/aq9pP2mvam9qD2jPZ/9oP2l/aa9pH2ofbA9tX2xPau9pb2dvZR9jn2RPZY9l72bfaZ9sP21/bL9rH2nvaO9nr2XPZO9lf2Z/Z99pX2qPac9ob2f/aO9pz2i/Z19n72rPbM9s72vfaw9q/2ufbv92j6HP31/1UDZgfTC80PlxKsFPUWmhlqHLYfDiSLKfIvJTf9Ps9G3k3EU91Ys10QYoJlRmgja55uh3I2dk555HsDfmt//3/ffxZ/t33ye/Z5w3cSdYhxI20qaNNi71xyVuBPmknMQ1k+IzkZNB0v/ymUJOseFhkcExkNawdcAvz9JPrJ9gj0yvG576TtrOva6Tno0eaX5abkCeSj41njLeMd4wPj2+LQ4vniRuOm4y3k6+TN5ZnmKueS593nCegI6PznBOgs6HXo6eiS6VjqIuvP63jsJ+207STume4o79bvlvBe8TfyL/NG9E71RfZI9134bPl1+pX7tvzB/bj+pP9+ADwB1gFbAtkCWgPUAz8EugQrBWkFhQWEBWEFGgWYBPQDVwPJAicCbwG2ABAAbf+p/s396Pzx++D6zPm/+NT38fbx9eX0A/RZ86HyzPH48Erwze9J76zuLO7R7XvtG+207GPsMuz266/rk+ux69Xr3Ovf6xLsZeyP7Jbsm+y+7ADtM+1T7Yrt+O1q7rfu+e4+73/vte/070zwr/AH8UjxnvET8n3yr/Kz8sryD/Nj85Tz3fNC9Kv0EPVb9Zr1y/Xi9eb18vUW9kj2bfaU9tP2I/dr9573uvfL98/3vPeu96f3tffN99n36/cE+CD4Mvgw+BT48vfV98b3xve696r3mfeY96v3rPeN92T3NfcM9/j24vbM9q/2kPaT9rH2zPbJ9p/2cPZt9nP2SPYC9tb10PXa9eH12PXm9Qv2G/Yd9iP2IfYM9uP10vXb9e715fXI9c71+fUh9iX2FvYK9iL2RvZB9i32PPZV9l/2XPZH9kj2avaB9nf2cPZ89qH2tvat9qL2p/bA9sb2wvbE9sr20vbg9u/2+Pb/9u322vbq9gb3EvcE99v20fbx9gv3A/fh9tv2/PYm9y73F/cA9/z29vbq9tn2uPai9qD2rvbL9uz2BfcL9wT3BPcC9/z23Pam9oL2ffaZ9qz2ofaa9r/26/b79uT2yPa/9rv2sfal9qH2ofac9pH2nfa29rz2oPaH9pT2rvbC9sD2ufbI9tf20/a39pn2h/Z89nb2f/ad9rf20fbo9gD3DfcB99v2rfaR9oT2gPZv9mX2ifbI9vH29Pbn9tv21fbF9p/2ePZi9lv2cPaU9rP2wPat9pX2nvap9o72ZvZw9vT32PrU/bcAAAT7B0wMHxDREtUU+RaEGYUcMCDOJFkqvTD3N98/sUeBThtUGFnpXTNigGUGaKVq/m3KcVd1RHifepZ8DH6vfnd+en3uewJ6z3dKdThybW74aQxlv1/2WbJTPU0ER0dB6DufNmgxVSxUJy4iuRznFv8QYgsZBhoBg/yM+FH10fKw8KPus+wA63vpBOij5lXlMuRW48fifOJY4jjiJuJP4qriD+Nh44rjy+Ni5Bblk+Xe5S3mluYk55vn0uf55znok+gG6YrpBOqH6inr2Oue7G7tJ+7V7p/vj/CH8V3yHPP08/X0E/Yo9x34Efkr+l/7lPy1/b7+pf+EAHABPALaAl8D6AN8BAIFUgVyBYwFsQXBBaAFYgX9BH8EBwSPAwkDaQKkAcsACABI/2T+Vv1E/Ef7UPpK+SP4Dfcr9mP1mPTW8x7zXvKf8e7wSvCq7+/uJ+6S7T3t/+yt7GLsRuxM7FjsPuwQ7O3r8Ov+6wnsIew+7Gbsouz87EXtbe2A7ajt9u1J7pLu1+4076nvIvB98MTwAfE08WXxlvHc8S7yevLT8kjzvfMh9F70fPS09Pj0KfVP9YD1yfUg9nb2v/by9h73Pvc59zX3Rvdk94D3mvfL9xX4Ufhp+Gj4Wfhc+E74Fvjb98f31ffq9/z3C/gU+Bb4FPj898z3jPdU9yn3Cvf/9vD26/YB9xj3IPcW9+v2p/Zu9kn2KPb59c/1zPX19Sz2TPZV9l32VvZA9hz26vW69Zj1ifWM9aX1ufXK9ef1H/ZX9mT2TPYz9jv2PfYf9vr15vXm9fL1DfYq9l/2l/a09sn24Pbo9sv2oPaF9on2lPaT9or2qvb39iz3Nfco9yP3IPcV9/328/YK9yj3Mfc090/3cfd391D3IvcK9wb3Bvf/9gr3LPdV93f3i/eV94j3WPcd9/v25/bH9qf2pvbS9hT3R/dN9z/3RvdZ91v3Mffr9rP2ofar9rX2ofaP9qb21fYL9yr3JPcP9xD3JPcg9/z2tvZ79nH2iPag9qD2lvas9ub2EvcV9wf39vbl9tn2xPax9qX2m/aO9o72rvbK9sr2u/bP9u726fbQ9rz2xvbY9sn2nfaa9sP22fbA9qH2qfbM9uH2zvaw9r320PbC9qz2rvbF9tD2w/au9r/20fbD9qj2n/a/9t722PYJ99X4sPuF/mABtQTCCBUNoxD+EgMVbxc6GjEdtyBRJQgroDHTOGVA3EdvTtRTnVg+XVlhd2TcZnFpy2yPcNpzXXZ4eFx6tXsafI97XnrTePx2xXQpcgZvN2u5ZrFhPlxiViNQxkm3Qyk+BDkYNCovMCopJQAgkRrMFP0OaAkvBHj/PfuQ95n0LfIE8PbtCOxJ6qDoFue75Z3ksuMF45jiVOIr4u7hp+GA4YPhqOHl4T3i0OKa43bkSuXm5UnmjOa15tbm6Obe5vHmVecS6PTo3unP6s3r0eyw7WbuDe+372TwGvHu8eTy//Ml9U72gPe7+PD5BfsL/Bj9Pv5X/1gATQEqAv0CvwNhBOUEXAW9BfwFKQZWBo4GrwaOBkEG/AXGBWwFywQABEYDqgIMAkMBRwBB/0v+Wf1a/D77F/oB+RX4T/eV9s318vQk9GTzm/K38b/wy+/77mnu+e2S7Snt3+zM7MzsqOxV7BHs3uu966Hrc+td63rrs+vp6yPsX+yP7L/s+Ow87Xntsu3u7UHuwu4674LvyO8d8Gnwq/DU8P/wUvHI8TDyh/L68oXz+fNP9Jz0z/T/9DD1SfVb9Yb1x/UV9nb22PYl9173l/fT9wT4Ffj+9+v3/vct+GD4cfhj+Gf4lvjH+Lj4efhQ+F74f/iU+IT4XPhT+HH4fPhX+Bb40PeT93T3c/dl9zr3FfcR9yr3S/c59/j2wPa/9tL2vvZ29iX2DPYO9gv29vXe9c712vX+9R72LPYh9gT2+PX49ez1zvWr9Zv1nPW49db16PXz9Qj2J/ZB9kb2MvYY9hP2LPY09j32VPZj9nv2j/aW9pz2kvaE9oT2k/av9sv24/b+9h33J/ca9wb39Pby9u325vbn9vH2Cvcn90/3Zfdh90n3Mfcq9x33Cvfr9u72Dvck9y/3N/c69yz3IPcJ9+n23fbQ9sz26/YY9yb3FvcI9wX3A/fh9q/2j/ac9sX25vb49g33Ifcc9wf35vbK9pr2efaP9sT27/YJ9xr3M/dF9yv37fav9oz2gfaX9rL2zvb29in3Wfd092D3G/fa9rP2pPac9pj2oPbI9vb2JfdJ90P3JfcC9+X22vbS9rj2r/bK9vP2D/cN9/P21/bH9rb2pvah9qX2s/bS9vb2EvcS9/T20/bD9rX2mfZ+9m/2hvaz9s/2Bfes+HH7PP7yAA8E6AcQDI4P2xHIExoW1hi/GzUfviNTKacvkjYHPnpFFExhUQ5WpVrOXgJiZGT9Zm1qQm6tcVZ0k3azeEN62XqMeql5XXi1dp90KHJDb7JrcWeeYnFd7VcKUvBLGUbOQN47+zb/MQMtFyj+InwdmxeuERkM+QY3At/9Lfot96X0X/Ix8Avu/+sO6jrom+Y+5R/kTuPK4nniQOIN4sDhdeFL4TfhSeGK4e3hi+Jl4zfk6+SJ5fvlSeZv5nvmiea25hvnr+d26G/ph+qe66vssO2a7l/vFvDD8IbxcvJy83z0ovXi9ib4Yfl8+oH7gfyC/Yv+kv+SAJMBjwKCA2cEIgWpBQ0GVAaKBrAGwQa5BrMGrAaZBnUGPAbiBXAF6gQ/BIYDtgLMAdgA7P/2/u/91/zH+9D63fng+Oj3D/dE9n/1pvS089Dy/PEh8UPwcu/F7jjus+087ePsnuxY7ATsw+uX63nrXus+6yLrIes/61XrZut565HrsOvY6wjsQOyO7ObsRu277Tfune7v7ibvXu+u7/vvM/Bn8MnwUfHi8VjyvfIn84zz4/Mf9FH0ifTG9AH1U/XM9TX2efa+9gn3SPdx93n3eveT97335vcR+Eb4fPiq+NT47/jv+Nv4tviW+IT4afhX+Gj4gviV+KD4pvib+Hv4TvgL+Mn3mvd492f3bPd093H3avdd90H3A/e69of2ZPZO9jv2OPZP9mH2XfZU9kD2Hfbs9an1ePVu9Xz1mPWz9dT1//UR9gb26fXA9Z/1i/V09WT1gPW79fD1EfYe9iv2M/Yv9hf2+/Xx9QL2JPY19kj2W/Z19pD2nvac9oP2bfZx9pf2uvbI9s723/b49g/3Fff69tv2zPba9vT2AfcO9xb3Gfc39173a/de9z/3Kfct90f3Qfcb9wP3DPcj9zD3P/dH90L3P/c991f3bfdQ9xX39vYO9yT3CffR9rr23vYD9wX3//YD9wj3C/cO9wr3/vbg9rb2rfbE9sv2r/aY9p72vvbZ9tr20/bP9tv25vbi9tT2t/ag9q72ufav9pn2kvaw9s320vbT9tz21PbN9sn2wfa69q/2n/aU9qb2vvbB9rv2tfbF9tn20/a89rH2vPbQ9tf2x/bA9tb26/bp9uD23Pbm9uf20/bB9sz26fb49gP3DPcW96r3rfk9/MH+dwG3BJcIiAzCDwUSDBRsFjEZTBwCIJEk/ilVMIM3Ej8dRhxMVlFOVvta1F6yYSpkJ2fbaqlu+nGxdBJ3IHmUei574nrreYl4/nY/dfhy/m9ibFJo7mMAX1dZM1MTTW1HPUI1PRs4FzNLLpkpryQ6H2AZeRPiDbsI9wOC/3v7IPh19T3z8fCB7jjsNep96PvmjeU95E3jtOJP4vbhfuHy4HPgHOD43/nfEeBV4PDg1OG74nnj/ONV5KTk5uQG5RjlT+W45V3mMucr6D/pSupU62PsaO1k7lvvQfA28U3ycPOW9L316fYW+E75jfrP+wj9O/5n/44AwwHqAuYDvAR8BSoGywZKB6sH/QdBCIMIuAjSCMMIkghTCAcInwcZB28GuwUIBUYEcgOEAngBYwBp/3P+b/1a/D77OPpD+Tz4GPft9dP01vPq8gryMvFu8MbvMe+j7v7tUe2x7Bbsj+sg67jqaOpB6ijqJOo06kPqQ+pF6lPqa+pv6mrqgeq36g7rUuua6/LrYuzU7DLtlu337Vjuq+4G73/v/u9e8L3wLfGs8SrydPK08hnzkvP781H0rfQh9Zr1BvZn9s32H/dB91z3kPfP9+z37vcD+EH4lPjZ+Ab5Kvlj+ZL5o/mq+Z75gPla+TT5GPn6+Nv4wPi8+M/42/jW+NT4z/jA+LP4h/hC+Pr3rvdx9z/3CPfb9s320vbc9u328vbj9sX2nPZm9jP2//W69Yz1jvWk9ab1m/WT9Zb1p/Wv9Z/1h/Vv9WH1YPVy9Xf1aPVg9WH1gfWh9Z/1g/V49ZL1wPXn9e317fX69R/2O/Y49iH2BPYF9iH2QvZt9pn2tfbY9gH3G/cX9/X2yfa29sv25Pbu9u/2Fvda95X3uPe59573e/dj91X3SPc29y33Qvdj94n3n/eZ95L3l/eP93D3T/dH91f3Zfdk9173YPdU9zH3GvcP9wH3+fbt9vb2JPdQ9133Tvc69yr3Cvff9rT2lvad9rj2z/bp9hL3IfcQ9wv3B/fr9r72m/ak9sv26fb39vz29/bz9u721Pav9pD2hfaY9rz23Pbv9vn2C/cZ9w336Pa59qP2n/ae9qT2uPbT9uP28Pb69vn27vbL9q72uvbf9v32+fb89iD3Pfcj9/X21fbG9sX2zvbd9vr2FfcZ9yv3i/dB+a/7CP6uAPcD0we4C+wORhF3E+UVahgiG48eAiNoKIkuUTWvPPxDZ0rbT95UmVmWXZNgJmMRZo1pHm1OcDRz63UyeLR5Z3preuZ54Hhfd5B1a3O2cFBtSmm/ZK1fD1oVVBpOdUgsQww+HDlkNMcv+SrLJTQgSxpRFHsO7Ai0Aw7/EPu39+v0dvIj8Nftnut36W3nheW/4zPi/+Ab4G/f+N6K3hrexd2Q3W3dWN1q3a/dGt6c3infyd9q4OvgQOGG4dzhPeKw4jvj5uPJ5ODlCuc16F3paepZ62Tsm+3f7g3wLPFy8gX0svU895D42Pk4+6b8DP5B/24ArwHxAjgEigW+BrsHnAhrCTQK3go7C1sLZguGC6QLnQtnCxcL0gqYCkgKtgnyCB8IUwd7BmsFOQQXA/oBzgCP/13+Q/0l/P/6zvmo+JD3aPY39SL0IfMj8jfxR/By78PuD+5X7ajs/etg69XqW+r16ZbpVeky6SjpIukG6fboD+k26T3pOulF6Wfpoenf6RnqXurD6jvrsush7JvsJO2c7QzujO4J73PvxO8p8LTwRvHN8T/yr/I/8+/zf/Tk9EL1t/U49qL27fY495D36Pc++I34y/j9+Df5c/m1+e35FvpC+mf6jfqj+p76ifpx+lz6PPom+iX6IPoX+iT6Nfot+g760vmO+VT5EvnD+Hn4P/gr+CX4CvgB+P/36vfG94/3Rvf89rv2evZE9iL2E/YN9gr2APb39fj1+vXf9a/1lvWC9Xf1WfU19Tb1TfVY9Uj1QPVJ9W71iPV79XD1hfWs9bj1qvWh9bH1vPW59cX14PX+9RL2JPZC9m72hvZ39l32bvah9r72tPax9s72APcl9zD3Nvc490b3UPdC9zH3OPc/90T3YfeF96P3uffK99T31ffV98H3l/d593T3fPeD94P3k/e/99P31vfV98b3tfef94b3dPd59373cPdx95L3oPeC92P3VfdN90j3QPcy9zX3Ovc790L3S/c89xv3Aff59vr27vbZ9sv24vYN9xj3C/f49vD27/bZ9r/2qPaq9r320/bq9vj2AfcC9/327PbT9rv2sfa19sL22Pbj9uj27/b49gH3BPfr9sH2uvbP9uH24vbY9uD2/PYR9w/38/bp9u726Pbf9uP2+Pb49uj28PYN9x33Gfd391n5D/y4/mYBpASPCHsMlQ+6EawT/BWUGGwbEB+vIy4pdC9xNuM9BkUuS19QKlWwWYNdb2DrYsNlRmn6bEZwCXN3dY93/niXeWR5mXhhd9N1BHTYcRZvjGtgZ8hitl0YWP9R1EsURtVA0jvXNvkxOC1hKDcjpB3FF90RDQx5BmwB6/zv+HL1evLp74PtJOvL6Jjml+TJ4i/h1d+93u3dVd3Q3FPc1dtb2+najdpw2pHa7dqK20bcA93I3ZPeO9+s3+jfG+Bh4NXgi+Fm4l/jiOTX5THnj+jc6RnrSeyE7dvuT/DG8SzzmvQp9sL3Qfmz+hj8gP0B/4QADwKfAwcFSAaHB7UItQl5CgULhAsODJoMBQ1GDXUNmA2ZDX4NQQ3TDD8MkQvqCkgKhwmXCI4HlgadBXYEFgOmAWkAVP8l/tr8mft9+mT5NPjz9r31n/R+81TyRPFa8H3vqO7b7STtluz66z3rk+of6tPpeekN6cPor+i46KzokOiK6JPon+ia6JDotuj86EXpmOkW6qfqGet76+3rceze7CPtcu3r7W/u6e5i7/7vuvBn8fnxjvIv88DzMfSS9Av1n/UU9l32uvZC98v3G/hT+Kr4Hfl9+bL56vlL+rD64vrp+gX7NftG+yz7Bfv/+hP7Dfvs+uD6AfsZ+//61vrQ+s36nvpS+gT60fmm+Wv5Jfnq+Mn4sPiD+En4JPj79773fvdM9yH3Cff09sf2qPaL9lz2FvbK9ZH1ZvVC9SH1GvU19V/1f/WA9W71X/VM9SL14fSo9JT0qvTF9Nz0C/VD9XX1nfWx9a31m/V39VT1VvV19an1y/Xn9Rf2W/aR9qb2nvaS9p32r/a89sP21Pbu9gr3J/dM92z3gPeC94f3tvfi9973vPe099H35ffX98f3vvfM9/j3Gvgi+Cf4IvgY+B74G/gA+OL3zffM99b34ffr9/L3+ffw99v3x/ew94z3dvdv91/3W/d495X3pPee93j3WPdL90P3F/fd9sv24fYG9xr3B/f09gD3DfcM9/P2zPay9rb20Pbo9uf2zfa+9sH2wPa59p/2ffZ69pn2wfbm9gX3F/cj9yP3HPf49rz2h/Zz9oj2pfa/9uL2EvdC92H3YvdO9zD3FPf+9vP24/ba9uv2B/cy90L3Mfcj9yb3MPc29yr3GPcU9wb4d/op/Zz/SAK7BccJig0yEAMSExS8FqkZyRyOIEwlBCuGMaE47z+oRmhMelFkVgNbsV5cYdFj7WafaiduBHFec6d1yHcveZF5J3lCeBh3nXWbc/RwrG3haadl8WCpW+NV5U8OSpBEWj84Og01/S8TKyAm6yBHG2IVmQ8fCvYEBQBm+0/32PP08GPu3Ot96V/neuXG4y/iquBO3y3eRN2C3MvbIduJ2i7aDtoM2iraZ9rF2lfbDdy33ELdtd0r3qXeHt+P3wvgruB24WLiYON95Ljl/OY76Ijp8epg7MXtJ++b8DPyyfNC9cf2WPjo+XL76fxg/uv/cQHjAk8EtwUQB1AIdAluCkYLDgywDCUNfA22Dd0N6w3rDdcNpA1PDfEMjAz7C1ALigqXCZoIpQeRBmEFIQTdAq0BfwA+/+39qPxy+0n6IPni96X2hPVi9ETzQfJM8VnwZu+B7rPtAO1V7Jvr7+pu6gvqpulH6QDpxuiW6GfoSehL6FHoQeg46FXomujc6ArpQOmT6QfqeOrZ6jHrkuv062Ps8+yA7QzuoO43797vj/Am8ZLx+PF28hDzofMZ9I70DfWm9U727fZu99r3S/ix+Ar5V/mX+cb58/kz+nf6xPr++jL7Y/ub+8/71Pu/+7D7sfun+3/7T/s6+zH7IvsK++762fq/+pP6Xfod+t75o/la+RX59PjM+JD4W/g0+BL46veo91v3Iff79tL2p/Z49k72LfYV9gH24fW69Yj1ZPVO9T/1JvUH9QD1B/UR9Qf18/To9On07fTp9Or04vTj9Pr0D/Uj9Tj1QPVO9WH1bPV59Y31ovXJ9Qr2K/Yo9kP2f/aw9sb2rvaQ9qv24vb69vb2FPdD9273lffB9+/38/fX98735fcA+Ob3sver99n3APj+9/T3+PcY+Cj4GvgP+CL4KPgT+An4DPgM+Or3ufeU94/3l/eM9333kPe298/33/fo9+r33Pe193v3SPcu9xv3/vbs9gT3LvdR92r3ePd292n3Ufcp9/z25Pbg9tL2yvbR9tf24fbw9uP22fbX9tP20fbK9sz23/bw9uz25/bs9vf23fa39qn2r/a89r32vvbc9hH3Lvc09zX3QvdG9yf3+vbw9vf29vbs9vX2Evct90f3Wvdq92r3V/dK9073S/c09x/3Fvck94b3UPnm+3n+OwGFBGIIWgyHD6oRmBPhFXUYQxurHhIjiSjPLrs1JD1gRLNKDVD0VJlZm12dYAljxGVFaQptU3AUc4R1vndweS96/3k5eRh4rnbvdLly7W9ybFRorWOOXvpY+VLHTOVGjEF0PFc3SzJqLZUohSMBHiYYPRJzDOUGpAHU/J34/vTh8S3vzeyT6l7oR+ZZ5J3iCeGa32neht3X3DDci9vt2m/aLdoU2hvaTNqn2i/b5duj3Ejd2N1S3rHeFN+D3/nfgOAe4d7h3uIU5EvldOag5/DoY+ra6z7tne4J8H3xBPOc9BX2dvfj+E361Pt9/R7/rgAtArUDUgXRBgcIDAnwCbsKfQsbDIwM5gw7DYMNtQ3UDeMNwg2CDTkN1QxKDJgLvgrFCcsIygevBmoFHQTiAsEBqwCA/0v+J/0f/Pv6rfld+B332PWH9EjzIPIj8Ujwc++n7gLubu3B7AfsZ+vS6kDqyOld6RTp2uin6Ifog+iE6HXoXuhQ6GLolOjf6BjpTums6Tjqxuoq63Hrr+sL7H/s7uxT7cntYe4Q78/vkvA08anxEPKM8iTznvPc8zf04PSt9WT2+fZw9973UPim+Nj48/gL+TT5jfkL+nz6yPoX+4L73fsA/OL7p/t9+3H7VPsn+w77CPsg+z/7V/tY+0X7J/sA+9v6mvo1+tb5jvlP+SD57fil+GP4TPhB+CH48/fG95r3dfdJ9wz3yvaN9lP2GPbi9af1hfWH9YH1d/Vw9WP1VvVh9WP1SfUl9Qn1APX+9Pj06PTa9Oj0D/U99VT1WPVe9XX1n/Wz9af1pfWv9cz19fUR9h/2MvZM9mP2fvaj9sH21vbw9gn3Ivc19zf3P/dV92r3c/d394z3uvfZ99b30ffs9w/4Evj599733/f69xP4D/j29/L3BPgN+A74A/jo99L31ffy9xH4Efjw99r34vfo98j3g/dJ90T3V/ds94D3l/es97r3tfeh94n3W/cQ99T21/by9vT28fYO9z33VvdB9yL3DfcA9+r2wfa09tX28vbq9tf21Pbi9tj2s/al9rr23fb09gn3I/c19zH3BvfY9rn2nPaC9oP2ovbp9kD3dPea97v3q/dq9yD33Pa49qn2nfap9uv2XPfD9+/35vfF96T3hPdH9/b2vfa49uf2MPdj91v4zPp6/fT/zgJDBhkKqA1QEFMSjRQkF9MZ0hyuIIAlGyuGMak4EED9Ru5MGlIVV6pbOF/IYSNkDGd8atltu3A+c6B1wnc0ebZ5YnlzeBt3b3VZc7ZwbW1/aQplL2DnWh9V9k7fSDhD8D3eON8z8S4aKj0lCSBdGm8Ufw6iCAMD4f1O+WD1GfJW7/bs7er66ALnHOVC43Dhwt9N3irdTtyi2xLbqNpz2lbaN9oe2jLahtoM26rbRNzd3JLdR97I3iXfZ9+n3wngmuBS4SriL+Nj5MPlPOe06ArqSuuU7OntOe938LjxGPOf9Df20Pdi+fz6tvxm/vj/gQELA4oE+QVAB1oIYAlGChYLuws/DLMMFA1uDcQNCA4lDhQO9A3NDW0N0QwIDCULOQpJCTQIBgfjBc0EuwOnApIBZQAq//f9xfx++yD6uvhW9xv2AvXh88zy1/H28CbwY++b7sbt/+xR7KzrDet06vHpnOlz6VjpH+nc6LPoo+iT6IHocOh/6LHo7+gu6ZLpBupG6nPqxOo565Xrz+sI7IvsUO0G7pPuGO/A72rw4vAw8aHxKPKS8vvylPNP9A31tvVA9sT2NfeL98v3Dvhq+ML4E/l8+Qr6kPrg+gX7Ivs/+1D7Rvsx+y/7S/uO++T7H/w2/DL8B/zQ+5X7Qvve+ov6XvpV+m36jPqN+m/6RPoQ+sj5Vvnj+In4Sfga+O73z/e+9633d/cn9+z2yfaQ9lL2KfYZ9hn2A/bf9bz1ovVs9SP19PT39Ab1+PTy9AP1H/U09TX1FPXs9Nf03fT79Bb1HPUb9UH1jvW59az1gPVg9W/1lvWz9cv17/Ue9mf2u/bv9uv2w/ak9qX2ufa79rX2y/YJ91f3qffh9/P37/fb99T30/fF96/3oPem99D3DPg0+En4Nfgf+Cz4Qfg3+Ab44ffn9w34HPgS+AH4/ff09+r34vfT98T3oPeI9573x/fS97P3kveY96/3qfdz9zr3Hvce9yP3Jvcy9zv3Sfdd92z3dfdk9yj3/Pbs9t/20/bC9rn20fYJ9zD3Mvcj9xr3D/cB9/f25PbN9sL2w/bP9vX2FfcN9/P26fb39gn3Cvfv9uL2APcp9z/3M/cp9y33OPc19x73BPf59gH3HPdN92n3Z/dm93r3lveb93r3SPcp9zH30Pfq+Y78E//5AZoFvAmVDW8QYhJbFMAWRxkLHJgfNiTDKTcwcjf6PvVF40sAUetVjFonXrVgCmPzZXhpAm0LcKNy/nQDd2R47XineLx3aXbKdORyiXB/bbFpPGVgYClbgVVdTyBJS0MSPiY5JTQZLx8qIyXoH0IaTRRdDqMIKgMc/qT5xvVf8l3vrexN6iPo8uXN4/ThZ+AF39Pd3twt3KvbKduZ2h3aw9mI2WbZcdm62UXaBdve277ckt063s7ea9/k3zTghOD/4Lzhr+K448rk/uVP567oGuqP6/TsT+667zvxxvI29H711vZk+Pn5b/ve/GH+CACzATsDqwQUBlkHfgiICXUKSQsBDJMMBw1gDZwNww3KDcANqQ1wDSMNwgxIDMQLJAtWCloJRAglB/cFpARDA/sB1ACw/3/+VP0z/Ar70/mp+Gv3KPbp9KDzcvJ98Zvwnu+n7t/tTO3F7CPsfev46pDqKOq36Urp9+iu6GfoPuhL6HLog+iK6LfoDOlm6ZTppenS6SLqduq+6gHrZ+vy64DsHu3B7V3u7e597wzwmPAN8WHxuPE38tnycPPw83f0FPXA9Wf27fZc98D3JviO+OL4IPlO+XT5q/kD+lH6jPrV+ir7cPur+9D71PvL+7T7j/tp+1r7UvtF+zH7H/se+xj7B/vc+qD6Xfok+gL63vmc+Vv5MPkQ+fr4wPhW+Pj3xfeJ90L3Dffq9t323Pbe9s72ovZZ9hb29PXI9YH1NfUQ9RP1IfUz9Tv1OvVE9VD1U/VD9R/17/Tl9A31KvUq9Sz1QfVg9Yj1lfWD9YP1nvW89dj1+PUU9jX2VfZm9nb2ivaU9p72qvbD9uv2A/cJ9xv3N/df93v3bvds94z3o/ei96T3tPfO9+L33vfY99337vf09+r35Pfl9+z37/fy9/f37Pfe99r34ffs9/L39ff09/r3+vfj98b3qPeJ93j3a/di93P3mve899L32/fR98H3sveG9033IPf09uf29/YM9yX3RPdj94b3oveS91/3J/cD9/D25vbe9sz2xPbj9iL3R/dA9xv38vbw9gb3Dff59u/2//Yk90T3Pfcg9wP37vbk9tn2zvbJ9tP2/PZD9333hPdo91L3RPcz9xD33Pa69rT20vb/9i33U/dt94P3kPd/91L3avcP+bD7R/71ADsERwh0DNIPIhIUFE4W1BiNG9geLyOaKMYusTVCPapEBktQUBxVu1myXXlgmGIeZYtoSmyXb1hyz3QNd7B4Y3kxeUR41XYadSxz83Apbo5qWWbVYfVcgFdvUSlLNEXBP6c6sjWzML4rzybGIXYcuBayEKwKCwX1/1f7L/eg86fwIe7Y65zpbudI5TfjROGe30jeJt1U3NbbfNso29vaddoj2gHa89n72ULa2tqs26jcr92Q3k7f89+C4PfgSOGd4Sfi8uL84zjlnOYZ6JPpDeuF7OrtLO9a8JDx5vJe9OH1cfcJ+aL6Kfyd/fj+SgCSAc8CLgSRBeYGNwhwCYUKbgsLDGwMpAy5DLoMtAyzDK8MrQy+DMMMkQwbDGgLkwqZCX4IQgf7BcYEtgPCAs0BwgCU/0v+DP3S+3L68vh/91T2U/Ve9G7zevKi8czw5O/r7urt3uzm6yTrlOot6tTpmemQ6ZPpd+k16fDor+hs6DToCugD6CToZujF6C3pl+n/6XTq8Opm67nr+OtM7LvsKe2M7fftf+4s793vevAL8aXxTfL08oDz+vNw9N30UvXI9Tz2sPYQ92T30/da+Nj4L/l4+dL5LPp4+pr6sPrR+gD7J/sw+yv7LPtD+1X7UPs9+zL7Ofs6+yn7EPv0+tr6rPpu+jn6+/mo+V75N/kp+Qr5y/ia+Iv4g/hX+Pr3lvdn90f3DvfO9qv2kfZk9kP2LfYJ9tP1o/WB9YD1hvVz9U/1UvV29X71ZfU29Rb1/PTj9N304fTg9O70EfVM9Y71uPXO9cT1t/W39a/1nPWH9YD1nfXP9Qj2PPZe9nz2oPbD9t323PbA9rb21Pb59h73OfdI92T3fPeO95b3f/dk92D3f/eq98r36PcV+Eb4Z/hu+FL4Jvj098n3sPep96r3uffk9xb4O/hZ+Gb4VPg7+BP42vem94P3e/eE95H3ovew97f3yPfR97D3c/dC9zn3Pfcy9xz3E/cZ9zL3SfdD9yn3E/cA9+/27Pbr9tT2tfav9sb23PbX9r/2sfbH9vH2DfcE9+P2zfbL9sb2uvaz9qb2kvad9tL2Bfce9xP3+fYB9yD3IPfz9r/2vfbj9gT3DfcS9x73KfdD91r3T/ck9/j26fb/9i73T/dK9zz3U/eB95b33ver+WT8IP8BAmkFdgmWDdwQGhMgFXIXAxrOHFcg/CSMKtcw0zdnP9BGB00BUpJWGFvyXqNhr2MgZn1pL21ZcNxyE3X9dj94tXhyeHZ33HXsc+5xvG/SbPdod2S4X8JaSlUvTwJJUkMsPko5ejSoL8wq3yW0IDYbbRWED78JYgSL/zr7afci9GPx/O6d7Dbq4Oe05a3jvuEW4MPeut383IXcH9y120rb5Nqa2njaatpu2rvaaNtI3Bfdyd2M3lPf+d+E4PXgbuEe4vziBeQu5VzmiOfh6Gbq3usx7V/uoO8o8dXyXvTA9SD3ofhJ+tf7Pv14/qD/8QBoAuYDNAVIBksHcQilCZ4KPwudC+wLSQynDNcMygyaDFwMKQwCDK8LHwtpCsUJNgmOCK0HlQZ0BUwELQMDArYAaf8h/t/8yPvJ+qn5ePhQ9zv2LPUS9ObyyPHR8PfvJO9Y7q3tEO1x7NTrN+um6hzqmekx6eXovuis6KzowejS6O/oFOkq6TbpRelS6XDpvOkS6l/qvOo268HrVOzf7F7t6O2A7hXvlu8h8J3wCPGG8Q3ym/IT83Lz1vNj9BL1vvVB9rH2P/fZ92H4u/jk+Pv4NPl1+Z75uvnc+RP6a/rZ+i77V/td+1z7a/t5+3L7P/v1+tP65fr7+uv6sfqE+nT6Z/o4+uT5nfl1+WP5Vfk3+Q753Pih+G34O/j19433J/fq9tP20fbA9qX2m/ae9ov2VvYe9uT1qvVz9VT1QfUt9TD1MfUz9UH1TPUw9RX1FPUV9Q71CvUR9SX1RPVg9XD1ZvVR9Vn1gPWW9ZX1rfXh9SL2SfZa9l/2WPZa9mf2ePaW9rn2yvbo9jD3f/eJ9173Tvds95H3kvdx92X3m/fm9/336/fx9xf4LvgW+O732Pfc9+L35fcC+C/4PPgm+Bf4Hvgd+Ob3mvd+9533xffG98f37/cW+Az43Pes95X3dvcz9wn3Evcx90r3Vfdn94T3k/d490/3LPcE98z2o/ar9t32/fby9un2/vYq9y/3+fay9oX2hfah9sX20/bP9tT2+/YU9xL36vat9pL2nfa49sz20vbQ9uv2JfdY91D3G/fq9t/2+vYK9/n28PYB9yf3U/dl92P3X/dT90L3Ovc/9zT3Kfc190D3TPdM90r3Xvd594z36Pip+4j+ZAG3BJ4Iwwx1EA0T9xQRF4YZPhyTH+cjMClELxI2mT0sRdJLKlHGVSJa+V3xYB5jPWUHaGlrrW5kca1zp3UUd8B3fHdgdtt093KzcC1uU2vzZ/djZ19pWhlVZU9jSW5D7T3ZOOMz/S5FKqUl3iCxGx4WehADC7kFmQDr++r3ffSB8fPusOx36jjoGuYt5GniqOAB36jd1NxJ3LHbHNuh2lXaFtrV2Z7ZmtnY2UDa4tq826XccN0g3uHeqN9P4MngQeH34ezi++MT5VTm5eec6Szrpewv7snvWfHF8iT0oPUx96/4G/qX+yD9mf73/1MBvwIrBHQFpwbtBzcJTQoEC5MLKAyhDNIMxwy2DK8MsQylDIwMaAwtDMkLNAuLCscJywidB3EGWgVSBDkDCALlAN3/v/52/TD8/vrD+Xr4Tfc99kX1TvRC80LyYvF88GzvX+517afs8utg6wLrwup+6i3q7em96XTpB+mU6FXoRehF6FToi+js6ELph+nM6Rzqbuqo6tjqJeuk6y7sr+w27c3tau727m3v4e9k8OPwUPHW8YjyRPPe82f09PSG9RL2fPbR9iv3j/fv90n4tfgf+W35sPn8+VP6rvro+gD7GftN+4n7o/uV+3r7ZPtZ+0/7Ovsp+xv7Gfsk+yn7Ffvx+rz6cvoy+gf61PmB+TD5+Pjd+NX4q/hZ+An45ffh98j3ivc59/b21vbE9pb2UPYO9uP12PXL9a/1mfWK9Xn1fPWF9W71MfX79PH0//QI9fn05/Ty9Cr1afWC9XH1T/U89UH1UfVh9Wj1Z/WG9cj1CfYy9j/2OfZC9l32gvaW9oj2gvaj9uT2EPcc9wj3/fYY90P3ZveI9533oPe499/3BPgK+Ov3u/ek97b3xvfF9733yff49zH4RvhB+DH4J/gf+Bb4APjP97D3ofed9633xvfJ97T3qPe899j3xPee94v3j/ec94b3V/c39zX3J/cK9wL3A/cD9wb3HvdJ9133PPcQ9wT3C/fy9rz2lfaN9qP2tfbE9tn25vbl9u72A/cA99b2qfav9tD22PbI9sT21Pbv9gX3+fbl9uj25/bo9vn2BvcS9xn3LPdF9z33HvcJ9w/3Hvcp9yn3H/cz91T3W/dM90D3M/cp9yX3LPc99zH3KvdY9//49/vb/pcB9ARGCeENsREnFBMWYhgMG9UdBiEiJVkqiTCVN1Y/E0faTVFTNFjpXN9ge2MTZdpml2nsbP1vY3JwdHt2H3jUeGl4GXc2dRBzwHAobgtrOGfnYkBeXlkeVElO/EfgQWk8ajeLMpotqyjgIzAfOxrQFCAPhwk5BEP/uvrD9mHzZ/C67V3rV+lo50TlDeMb4Y/fQN4B3eLbBdts2uvZZNnt2IvYRdgj2DbYitgQ2a/ZXdob2+rbptwt3aLdMt7k3p3fdOCG4d/iYuTh5Wfn9Oh/6vjrZO3S7lfw8/G885b1Y/c7+f/6lvwb/pr/+gA/AnUDugQaBn0HzQgBCiMLLwwADX8Nvg3rDQUO7w3BDZgNbw03DegMfAwDDGwLngqvCbwIwge8BpoFbQRVAz4CBAGe/y/+z/x7+yz63viy97D2yPXi9O7z9/IC8gfx8O/N7s3t+ew17HHr0+p26j7q/+m36WvpK+n36LDoZ+hD6DnoN+hB6HLovegF6TrpZOmp6QzqZuqr6gfri+s47O/shu0M7pvuGu957+vvePD48GLx3vGM8mHzL/TT9FL10vVj9t/2Q/eT99/3IPhz+O/4ZvnB+fP5LvqV+gP7SftQ+1X7bvuY+7/7vfua+2b7TPtY+2H7T/se+wX7Gfs4+zf7Afu4+nD6K/rh+Zb5OvnT+JX4jvig+I34R/gK+Pv38Per9zv32fae9nj2VPYs9vj1vvWm9a31pPWE9Vn1M/U49UX1MPUP9e704fTp9Ov04fTJ9Kf0q/TS9Pz0D/UP9R/1RfVx9Y31lvWQ9ZT1qPW39cr11vXZ9ev1GvZE9mD2evaW9sv2A/cn9zX3NPcp9yj3NPc890D3QPdM92v3l/e498H31vf89wj4/vf39+r34ffj99z33PfQ9673nfev98f3zffD97331vf89wn49ffd98X3oPdn9yf3+fbx9g33KvdN93b3lveo97D3nfdj9xH3w/aV9oL2ifag9q/2yfb+9jL3Sfcv9/z2zfa79rv2o/aC9nT2iPam9sX20Pa99qT2p/a+9s721PbO9sr23PYD9xH3+fbF9pr2lvan9rf2tvav9sn2Afct9zj3LfcT9wr3Gfcd9wz38fbd9tz28Pbp9tj2z/bW9vr2GPcx91P3Vvc69zP3VvfY+Lb7n/6UATYFtQmBDqoShxWrF/cZhBw8H3gixCYRLE4ymTm9QeZJ9VCXVm9bBWD2Y5dmMWj9acRsGnBLcwt2WnhFepx7E3yRezV6JnihdflyXHBvbc1pfmXRYOJba1ZbUOlJn0PqPaI4hDOdLvApSCVeIBobohUMEFcKtASN/w77Jfew86rwK+4A7MHpSOfR5JrileCu3vfcktub2gTagtn62IHYCdhy19LWVNYX1iXWadYI1+nX5djk2cDaa9v924rcAt1/3SneJN9q4PrhvuOh5ZPnfelA69/see4H8IbxBPOS9En2Ovg9+jP8FP7o/6wBUwPPBA0GHAcmCDoJYAp5C1YMDw3JDYAOCg9GDzAP5A6IDi4OxQ1HDbwMGwyCC/8KagqTCWcIIgfoBbcEbAPqAWUAGf8H/vj8yvuU+lv5IPjz9sj1j/Rf8yby/PAX8E/vge6q7d/sLuyS6/rqUeqw6TPp1eia6HXoTOgV6O3n2ufl5/Dn5efe5/znR+io6Afpa+nQ6TnqsOoQ63Tr8+tq7NzsZu0M7sXubu8E8JrwS/Hx8VTysvJK8+/zgPQJ9ZL1Q/b79nv3z/cz+Jj43PgM+U/5rfkJ+kj6hvrz+lz7dPtQ+0/7gfud+3v7VvtY+4D7qPue+3T7Uvsq++36sPpv+jD69fnR+d755/m6+XP5Kvn/+N34efju94z3YvdV9zb3DPf59uv20faV9jn24vWX9Uz1HvUa9Sb1K/Ur9T71bPVz9Sb1t/Ro9EX0OfQa9PvzJvR+9M70DPUy9Ur1YPVY9TX1EfX19Nv00/Tt9Cr1ffXB9fb1IvZO9nD2cPZe9lr2cfaI9pP2rPbV9g73O/c/9yn3DfcC9wn3HPcn90H3g/fR9wf4Hfgl+B34/ffC93P3QPc+9zL3Lfdp98z3GPgn+Az4Dvgn+Az4tPdb90D3P/cp9xX3Lvdl93L3Svc090r3RPcU9/D27Pb79gT36vbX9uT24/a49oX2gvaN9nr2YPZe9oX2sva99qP2lPac9pz2jvaF9n72bPZf9nP2jfaX9pz2hvZ89oj2kvaY9qL2tvbL9t322fbG9rr2q/ae9pn2jfaH9qD20fbr9u326vbv9vL24Pa+9qP2qvbA9s/20/be9vL2B/cJ9+n2yva+9sP2xPa49rv2PfeR+er8CAAxAwUHkAs5EPgTYBZhGMcajR2oIHMkICm6Lkw11zwBRcFMKVNgWDhd3mGmZRtozWnUa8VuIHIJdTp3F3nKeux7IHxle/R5DnjFdTJzenBnbZNpCGUmYBxbsFWnT1hJV0PyPd84zjPLLhwqkiWzIHAbDha8EGYLFgb9AGz8g/gP9d3x+e5p7A3qx+eH5XTjk+HF3yXeyNyz28XazNm52LDX59Zb1uHVcNVG1Y7VJ9bs1rrXhthN2erZcNr42mzb49uI3GndoN4s4OXhq+OF5YjnjOlv6xXtpu5A8OLxnfNj9S739fi6+pf8fv5KAPQBeAP2BHYG2wcLCRoKGAvzC6oMOg2yDQUOMw5XDnsOeQ5KDvkNkA0tDb8MEgwqC0wKagluCG8HXAY0BQQEwwJ3AT8ACv+3/Vz8HvsH+vf40Pej9oP1evRw8z/yDvHy7/ruKe5j7Z3s6OtR68zqVOrg6WXp6+h76C/oBejk57vnk+eF56Dnzufe59Xn5Oc16KfoD+ls6dnpXur36pDrEex67N3sQu207Ufu7+6H7xXwzfCq8X7yLvOw8yX0uPRI9a318vVW9uX2afff92P49vhu+bz5+Pk7+oP6p/qn+rb6/fpG+237jfun+7j7uPuV+2/7X/s7+/z60Prd+gH79fqv+m/6XfpN+vn5bfn7+MP4oPiH+HP4RfgX+Pn31fel91j30/ZK9gT26PXX9bz1mfWP9aH1ufWy9Xf1CvWs9I70gvRT9A/08/Ma9Gr0tfTU9MD0s/S+9Lz0oPSA9Gb0TfRS9JH05vQM9Rv1NfV29cD1zfWg9Xf1kPXS9fb18vUD9if2U/aH9rL2yfbJ9rr2v/bp9gz3A/f39hT3RPde93X3j/ed95/3mfeY95L3gPdh91X3dPeb96D3kfel97r3sveh95v3lveA9173Uvdp93b3WPch9x33Q/dN9yT3/vb+9hr3KPcK9+724vbg9tP2yfbI9tL2zvax9qX2ufbH9pr2VfZJ9n32nfaG9l/2afat9tT2rvZy9lj2TPY+9jP2OfZX9mj2bvaQ9sH2vPaH9lb2PfZD9jn2JPYr9mT2ufbs9vb2+vb19tf2pfZg9i72F/Yq9l72jvbW9hb3MfdC9033Pvfz9pX2aPZ19o72kPaA9pf24PYi9yT39/bL94v64P3wAFYEjwhyDR8SmBXgF+sZRxzUHsshxyXyKgIx3TetPw5IwE+4VVtasl7WYvplx2ctaXNr3G5zcll1jHdkech6WXvmeo15eXfvdGhyDXCybeZqWmc3Y9NeDlqBVDNOtketQUo8WTeRMgAusCl9JSwhfxxdF/kRlAxYB4QCMP5Z+gH3DvRv8f/uoOxM6u7nleVk42fhtd803uDcxNvN2tjZ6NgR2EbXiNbp1ZvVsdUQ1onWD9eu12rYNdnu2YXaD9u6257cv90W34XgE+LO457lfudt6UzrEu3n7s/wyfLU9Lz2evhG+if86f1u/9cARgK+A0IFswYICGAJoAqeC2QMCg2JDdIN5Q3WDccNxg2+DZINQQ3cDGEMywsYC0cKYAlwCIgHlgaLBW0EUgM2AgoBuf9S/v/8wfuU+mn5R/hE91z2aPVc9EvzQfIz8RzwDO8J7ibtZuzC607r9ep/6vrpkuk/6d7oX+jZ54jnhOeQ53HnZ+eX5/PnUeiZ6M3o/uhG6Znp++lU6p7qAuuT60Xs8OyE7Qzuqe5f7wbwmvAv8cTxP/LI8nnzDfSD9PT0cfX49XX21/Y397z3Rvil+Of4TPnP+Sr6T/pp+oj6l/qP+oL6f/qP+qr6w/rw+kr7gvtt+0D7I/sK+9L6YPrU+YH5efmB+XP5ZvlV+Uf5NPkD+cD4Z/jn92H3I/cl9yf37faZ9of2tfat9jf2qfVN9Sz1FvX69OX05PTw9AP1EvUT9fX0m/Qz9Ab0HfQo9An0AvRN9LP06vTp9NH0xvTJ9L/0ovSa9LD03fQY9Vz1pvXZ9dv1zfXZ9ez17/Xy9QH2GfZQ9pb2u/bM9uD25fbZ9tj26Pb69gP3E/c793v3qvep94z3efd392/3TPcu9zf3T/dp94n3r/fG98n3tPec9433gPdb9zL3J/cp9yT3F/cU9xv3H/ci9y73Mfcs9yD3Evf/9t32v/al9oP2YPZM9l32iPak9qv2t/bD9sr2sPZ69kz2NPYn9hj2HvY59lf2a/Z89oD2avZC9iD2DvYM9hb2I/Y59mX2h/aS9pD2dPZN9h/2/PX09e317/Uc9l/2mvbK9uH21Pa79qD2a/Yu9gv2BvYV9j/2gfbD9vj2BPf19vL24Pao9mr2SvZM9nX2qfa49sL24fb/9kX3Evkq/Ez/hAJ0BjsLSBCcFIgXoRnrG4seQCFrJJsoAi55NNo73kO4S35S6leCXKRgBGRFZspnhWkxbJZv03JedUF3pHhxeVB5HXgOdp5zRnEcb/hsqWrwZ61k5WB8XEtXbFE4Sw1FVz9HOq81bzGJLdwpCybgIT0dNBjwEqsNtgguBBUAg/yG+QX3xPRk8rzv9OxQ6ujngOUb4//gaN9d3o/dotyL23TaZ9lX2FHXcdam1RnVINXD1cfWzNeN2CTZ7tnn2rTbM9yN3DvdhN5A4CHiCeQC5hroYuqa7JfuSvDb8XXzOvU09xn50/p2/EH+OAAVApcDyATmBQ4HQghbCTQK3Qp8CyQMpgzrDB4NLw0PDeQMtQxpDPkLegv2CmUKrgnXCOcH8wYaBi0FDwTxAvoBBgH8/8T+f/1Z/D37EPrI+JT3hPaG9Z70vPPG8tnx6/Dt7/7uL+5b7XDssesk67HqVert6XrpLOnt6I/oKejr58Xnqeer58Dn7eco6G3os+j06DPpaOmm6QPqcuro6nDrCey07GDt8u1x7unuW+/E70DwyvBY8fbxtPJ78yv0yPRK9aT14fUk9nT2v/YQ93H32vde+Pn4bvmm+cH51/ns+e757Pn5+f35DPo9+nj6nvqh+oX6X/pG+iH65vmx+X35bfl3+XH5ZPlc+Tn5/Pi6+GT4EPjA92/3NPcJ9/X28Pbt9tb2q/aZ9n72Q/YF9sj1ivVG9QX13vTT9ML0qPSg9MP09/QN9fP03PTj9N70uPRx9Dj0I/Qb9Cj0WPSY9NP0DvVI9YX1mfVx9TD1+/Tw9P/0CPUU9Uf1r/UV9lH2ePZ79lz2RvYz9iH2H/Yp9jr2aPa/9hf3SvdK9zj3Lvcr9xn35Pa29sT2//Yw91f3f/eX96z3rfeO9233Tfcc9/f2+PYb90b3VfdN9173iveL91n3L/cJ99n2t/aw9rr20Pbq9vz2Fvct9yf3BPfT9pv2ZfY99hn2GvY+9mT2j/bE9u/28vbH9oz2T/Yb9vP1zPW29cr1CPZW9p72x/bP9r72i/ZU9iP28/XG9aj1uvUM9mn2lPaS9pz2vvbW9r/2bvYc9gf2JvY89jP2M/ZQ9nT2m/a99sD2qPaE9n/2pPa+9qr2c/ZP9mv2o/ap9mn2O/Zs9sX24/bR9sX2x/bP9sz3f/qX/YkAAwRlCIQNbxL+FUsYgxoxHQIg3SJIJr0qUjDyNlo+AUYDTcZSmVcNXBNgE2PtZHBmkWiRa8xuZHEwc5Z0n3X9dWB1xHOccWdvYm2Ma6lpemfeZM5hRl4eWidVdU99SclDrz4OOq81sjE5LgkroCe4I10fwRoGFjoRgQwDCAIElgC4/S77svgh9nvz6PBo7tPrI+mU5nnkzOJc4QTgv96a3YHcXNsy2h3ZKNhq1/3W9tZL19fXYdj12LnZm9px2xfcvNys3e/eR+Cd4TPjFuUV5wPp1uq17KnulfBx8jv09fW/95D5U/sA/YD+1/8hAX8CzgPwBP0FCAcSCBIJ8wmMCuoKDgsbCz4LRAsRC60KSwonCh0K0gk7CaAIGwh7B6oGtwW4BLkDsgKvAcMA5v/p/sH9qPzM++X6s/lm+ED3RvZe9Xf0gPOV8tvxIPFR8Hzvpe7J7ezsIOxd68LqVer66bPpkOmD6XnpYeko6fTovuiA6FLoUuh06Kro7ehH6c3pXurb6ibrZ+vD6yjsj+zz7Fnt0u1u7hjvpe8s8L/wRfG48SjynPIZ86LzGPR89Ob0YPXa9Tf2avan9gT3Xfeb99b3JPhz+LH46Pgj+Ur5W/lX+Un5Vfl1+YL5cflr+XT5e/lx+Vr5RPlB+T35Hvnu+MX4u/iu+If4Uvga+Nv3svej94P3QPf69s/2tPaZ9m/2RPYp9iT2IPYf9hf26vWg9Vj1OPUs9fn0nfRk9JT0+PQr9Sj1HPUi9TL1MfX89Kr0cvRd9HD0tvT79BX1LvVb9ZL1sfWN9UX1GPUc9UH1bfWc9cb1+PU69nX2h/Zi9iP2APYJ9h72L/ZR9pL24PYo91P3Q/cd9//26fbT9q72m/a69g33ZfeS95P3gPd092v3QPf59rT2rvbv9jj3bveJ94L3hfeg94f3Ife39oD2gfay9uj2/vYU90H3cPd990/3Afei9lf2TvZn9nj2i/an9sz2+fYS9/j2o/ZI9ij2M/ZA9j72P/Zu9qr2zPbC9oX2SPYq9hL2+fX39RL2PvZp9o32tPbE9qX2cvZP9jn2IfYM9hD2Q/aD9pz2o/a29sz2wPaF9j72GPY19mz2cfZn9pP22vYL9wn30faJ9lz2TfZS9lb2XPZ39qn29PY39zP38/ay9qD2rvaW9mP2jPeD+uj9JgGoBNEIeg3LEeUU+Rb3GD8byB3NIKMkVSm5LvY0BTwoQ1RJIk4zUkpWOFoyXSBf8WCmYydne2rqbIpuvW+VcNBwQXAPb4ttDGzMatBpxGguZ+9kL2ITX4pbRldYUlhNyEi2RAFBYz3JOVw2CzN3L4ErTyftIoweRRohFkUSzg6SC1IIEgXcAcD+oPtw+FL1d/Ld73PtQ+tJ6WznjOWv4+PhLuCF3uPcfNuJ2vbZjNk72STZTNmd2dzZBtpb2uLakdtb3DPdP96Y3wjhleJA5OHlfecp6fPq0uyb7jnwzPGH81b1AfeE+AP6lvsk/av+FQBXAX0ClwOqBJgFSgbTBl4H+geXCBsJZQmJCZ8JpAmSCWAJAwmLCBgIuAdlB/wGZwbDBSAFawSGA3ECYAFlAHD/hf6e/cT8Afwx+0P6VPlc+E/3MfYP9Q/0JPM08lvxuPAj8GvvqO797XPt6+xW7LrrPevu6qXqWuoi6vfpxemc6YHpgOmJ6X7pgem16QvqXOqQ6sPqE+uA6/LrTeyo7Bfthu3o7Vbu1u5C753vAfBy8PfwhfH48V7y1vJs8wP0bvS79AX1XfW/9Rb2SfZ59sn2Ifd497j36/cZ+FT4l/jD+N74/fgU+Sj5Tflh+Vj5SvlB+Tv5Nvkp+Qz58/j1+Af5DPn2+Mz4rvij+I/4UvgM+Nj3tveW93L3V/dL90b3M/cT9/324Pat9n/2XfZL9ij2/PXu9fr1FPYb9gP26/Xe9bz1m/WI9Xr1efV39Xz1qfXm9Qb2APb19e/16/Xq9cP1nPWp9c318vUj9lL2dfaT9qP2tfbI9rn2jPZn9mz2l/a+9tP25vYK90T3bPdx91r3Pvcm9xn3FfcO9xr3MfdL92X3iPei96z3p/eL92r3V/dW9073RfdE9073ePeg96P3nfee94L3Vvc89zv3QPc39zH3VPeQ97X3qveT94X3evdY9xz39fYB9xX3Evcm91r3e/d+94n3mPeL92b3K/cC9wn3GfcG9/z2J/dd93b3Z/dh92/3aPdB9yD3Jvc69zD3EPch92P3j/d790j3P/do9373Vfcl9x73K/c890j3TvdN90v3SvdG90/3WfdB9yn3Qvdt93P3UPc790D3Ovco9xP3Cvca9yr3OfdP92T3g/eR93b3U/dB9zr3LPcf9x73fPc8+bL7A/52AGMDzgZrCoYNtA+IEZoT7xVzGFkbxx65IjcnUCzFMfo2czs9P95CgUbOSX9Mw04oUSZUb1dUWpVcQF6HX5NgMmE5YdtgXGD5X89fuF9zX9Re0V1vXK5agVjmVeFSp0+VTNVJRkerRPpBSj+qPO058TapMyUwoSwuKb8lbSI+HyEcDxkCFu8Sxg+TDF4JNAYpAzkAZv3I+l/4BfbE86Txku+A7XLreunB50/m++TF48/iNuLa4XbhEOHJ4Kvgp+Cm4LPg8OBw4RXi2+Lb4/XkD+YZ5yboXOmh6srryezY7Sfvl/Dt8SLzWvSv9Qj3P/hS+Vf6Y/tp/Fn9OP4c//3/zQCKAS4CvgI8A6UD9gM5BHcEnwSxBL4EzgTSBK0EbgQ5BAkEywNlA98CaAIIAocB2QAiAHj/0/4h/m/9ufz3+zz7iPrk+Tv5cfiV99T2M/aM9dH0//NA87HyOfKv8RbxkfAa8K3vT+/l7njuK+7u7bbtje1x7VPtPO047TPtIO0W7RftIe017VDtie3R7RTuZ+7D7hXvVO+M78fvDvBL8HXwvPAp8ZPx8vFZ8sLyM/Oe893zFvRw9Mf0+PQj9Wf1xPUq9oD2t/bq9jL3cfel99f3/fcX+Dr4dPiy+OH49vj4+Pn4BPka+SP5EvkD+RT5QPli+Xj5dflv+XT5bPlU+SX59fjX+ML4s/i0+LH4mPiA+I74pfid+Hr4U/hC+D34MvgR+PT35ffT97z3pfea95n3jfd89373jfeY95n3kfeN9433hfd092L3Vvda91v3W/dy94v3mvec95/3rve897T3mveE9373lPev98H32vf69xv4OPhL+FX4Qvga+AP4+/cB+AP4C/gr+F34j/i0+Mr41/ji+NP4tviX+Hb4Zfhp+G/4f/ik+ND4APkg+Sb5FfkH+fj42fi9+Kb4kviX+MX48PgC+Qn5Evkl+Sb5C/nb+LP4t/jA+Mf42vjw+Ab5Gfkk+Sb5Dvne+Ln4rfiu+Kj4p/jF+Ov4A/kL+f345fjU+MH4qviY+If4kvi3+NP47fjv+Nn4yPi5+Kf4j/h2+HP4mfjD+Nn43/jk+Oz46PjI+Iv4Yfha+Gj4hPiq+NX4Avkb+RT5Afnv+M/4kvhb+Eb4XviP+Lf4z/jz+B35I/kV+f/40viw+Kf4p/i5+Nv46vjz+AL5EfkT+Qz5s/nr+jf8sv2H/7YBCwQ0BuUHUwnMCkIMqw1BDzURfhMUFukY6BvnHqghDSREJoYoqiqVLFouMzBKMok0lTYqOGc5cTpJO8o7/TsbPEc8ljwCPXI95T09Plc+Mj7HPR49MjwMO9Y5uTixN582djU7NPgyozEmMHAulSzLKhApSCdyJaEj3yEbIDoeLhwEGtUXpBVyE0IRJg8hDSoLRAlyB6IFxwPpARkAYf7H/ET7yfl0+Ff3V/Zd9V30Y/OR8uLxKPFs8NPvbu8z7/zuzu6y7qzusO6u7rnu4e4Y70fviO/y73rw9fBW8b3xO/LD8i/zhfPz84P0FvWR9QH2jPYv9733L/ik+Cf5rPki+oD63/pS+8L7E/xY/J783fwa/U39ef2h/b791v3q/fn9Bf4D/vX94P3L/cD9qf1//VP9Lf0F/cv8gvw5/Pn7rPtT+wD7u/p6+i363vmP+U75FfnH+Gz4H/jX94X3Ovf69rL2X/Ya9uD1r/WC9VH1IvX99On0zfSm9H70XvRA9CH0/vPa89Dz5vP88wP0CfQb9C70LfQc9Aj0BfQN9Bf0KfRN9H30tfTs9Bz1Q/Vh9Wr1X/Vm9X31lfW09eX1IfZi9p/20Pb59h33M/c890n3XPdw95X3z/cK+DP4V/h8+Jf4q/i5+Lz4w/jQ+N348PgI+S/5WPl2+Yb5jfmU+Zn5oPmc+Zb5nfmn+a35tvnD+c750PnM+dH52PnW+dH51Pni+e/57/nq+dz50fnM+cP5vfnC+cj5xvnH+c/53fnf+c/5tvmq+bD5svml+Zn5nfmz+dP55fnV+bn5t/m7+bf5tPmj+Yn5gfmT+bX5z/nU+c/5yPnW+en56PnV+b75ufnD+c75zvnM+cz52/nx+f/5//n1+er58/n/+ff59fnu+ev59fkK+h36KPoo+h/6FvoX+hr6FvoK+vr5Afoe+ij6Jvou+jn6QfpA+iv6EPoT+iT6LPol+h36Ivow+jr6N/o1+ib6DvoL+h76Mvow+ij6N/pY+nH6Z/o7+hf6Fvoc+hz6GPoN+g36KvpS+mz6aPpG+i76L/pB+kb6Nvoc+hn6NfpS+lP6MfoW+hr6Lfoy+iX6Hvon+jn6UfpW+kP6O/qv+nv7RfwP/QP+RP/AACECJgP/A+0E7AXnBuQH7ggaCnIL8QyHDhAQbxGnEugTURW6FvAXBBk1GqUbJB1pHlsfGSDRIIQhFCJxIr0iGCOUIzIk1iRiJc0lLyaJJs8m9CbjJrEmhyZuJlcmLibbJWgl6yRrJNMjEiM5Il0hkCDUHwkfKx5PHW8cfxt5GmIZNxj3Fq0VbxRBExQS2BCbD2kOSQ0xDAwL2gmqCIcHcQZsBXUEkQO4AuEBEwFVAKD/3P4T/lP9n/zz+0z7qfoY+pj5KPm/+F/4A/iq92H3Kvf69sT2iPZR9iz2FvYB9uP1zPXF9cf1yPXD9cL10/Xs9QD2FPYx9lf2h/a09t72C/c592D3hver98338vcT+DX4W/h/+KT4yPjx+Bv5RPlk+Xn5jfmt+dT58vkB+gf6EPol+jz6R/pB+jn6PfpB+kn6UPpU+lP6UvpQ+kf6Pfos+hr6B/r5+e352fnE+ar5nfmb+Y75dPlV+T/5Mfkj+RD57vjU+Mf4uvim+I34d/hm+Fn4S/g7+Cv4G/gI+Pn39Pfx9+H3xPeq96j3s/er95b3j/ea96n3qfec95r3o/en96T3oPeh96X3qfeu97r3yvfZ99z34ffz9wr4H/gt+Df4QvhQ+GD4cPh/+Iv4kPiU+KH4t/jR+Oz4A/kV+Sf5PvlV+WT5aflw+Xb5gfmN+ZX5pvm8+dv59/kL+hz6K/oq+iz6Nvo9+j/6Nvo4+kj6Yvp8+pH6oPqf+p/6ofql+q36tPqv+qr6svq8+r/6wPrB+sP6yPrI+sb6xvrL+tj66Pr0+u/64frW+tn63PrU+sv6wfq/+sX6zfrV+tj60frE+sP6zfrO+sb6xfrM+tv65/ri+s36wPq5+rb6sfqp+p76nfqq+sH61vrZ+tX60/rb+uD61fq++qv6p/qt+q/6rvqw+rj6x/rP+tL61frS+sj6xPrJ+s76yPq4+rn6zPrY+tT6yfrE+sX6zfrR+sb6vfq/+sr62vrn+uL62frZ+uP66Prc+sf6u/rE+tb63vrc+tX60/re+vH68frg+sz6yvrX+uX66frf+tX62vrt+vL64vrO+g37s/tn/AT9qf2R/rL/zQCqAVMC+gK4A30EPgUEBtIGsAehCKYJtQqzC5UMdw13DpkPuxDCEcUS8RM2FWoWYhceGMAYWhnoGWMa1hpLG9QbcRwlHecdpB5JH88fTiC/IBshZSGfIc0h/CEeIi0iJCIDIssheiEfIbQgRCDQH1kf5R5xHvsdfx31HFYcnRvXGg0aPxlhGHAXdxaFFaIUwBPREtARzRDSD+UOAg4XDSkMQwttCqsJ7QghCEkHcwalBdkEBgQrA1MCgwHFABgAav+8/hP+fP3z/HL86/tc+9b6afoN+rX5WPn1+Jv4VfgX+M73fvc39wH31/az9pP2ePZm9mH2Y/Zk9mD2VfZN9lr2b/Z99oL2ifaZ9rj21/bt9gH3G/c191T3dfeR96f3xPfp9wv4MfhO+Gj4jfi5+OD4//gX+Sz5Rflj+Xr5ivmc+a/5wvnb+fj5C/oY+iL6Lvo7+j76Nvoq+ij6Mfo8+kD6P/pC+kr6UfpK+j36Lfof+hL6Afru+eH53/nV+cz5xfm7+a35mfmC+W/5ZPlW+Ub5Pfk5+TT5LPkg+RH5A/ns+Mz4sPif+Jr4m/iY+Jb4mvil+K74qfiZ+In4e/hw+Gj4Yfhk+HD4gviQ+JT4lvid+KD4nvic+Jz4pvi4+Mv43fjv+Pz4BfkP+RX5FPkV+Rj5Jvk7+Un5VPlo+YL5m/my+b/5xfnK+dj55/nx+fv5A/oM+hb6KPo7+kn6U/pf+m76fvqM+pL6m/qn+rb6vPrA+sj60/ri+uz67/rx+vX69fr0+vb6+Pr/+g37Fvsb+x/7Jfsp+y77L/sm+yD7JPsr+y/7Mfsy+zX7Nfsr+yD7Hvsi+yP7JPsn+y37MPsz+zX7Ofs2+yX7GvsZ+xr7FfsT+xb7Hfsl+yX7IPsc+xz7F/sP+wj7AvsB+wn7EPsS+xj7Ifsj+x/7GPsU+xT7EfsN+wz7EPsN+wj7B/sN+w/7CvsF+wb7EPsS+xX7GPsX+xP7E/sX+x77HvsW+xL7FPsW+xf7EPsL+w37D/sR+xf7F/sW+xf7F/sb+x77GvsQ+xD7GPsi+yb7Ifsf+yD7Ifsd+xL7CfsN+2v7BfyS/Bb9vP2k/qn/iwAtAb4BZwIgA9QDgAQrBdoFnQZtB0IIEQnSCY4KZgtoDHUNcw5sD4AQtRHnEuwTvRRxFScW2xZ2F/UXcBgCGawZYBoPG7obYhwLHa8dSB7UHlAfxR86IKQg7yAaIS8hOyE3IRUh2iCVIE4gDSDMH38fKR/LHmoeDB6eHRodgBzjG0QbnBriGRYZRxh1F6UWzBXhFO0T+hIREjQRWhB2D5MOvQ3vDCkMXAuICqoJzAj2ByYHTgZtBZEEvQP0AigCWgGNAND/KP+P/vL9Vf3E/Dz8w/tQ+9j6Wvrl+Xn5HPnN+Hv4JfjU95T3W/cm9+v2sPaI9nL2XvZG9jb2N/ZC9k32TvZJ9k/2WvZj9m72f/aV9q/2yPbm9gj3KfdG9133efeb97734vcL+Df4ZfiO+LL40/j3+Bf5N/lX+XP5i/mn+cn56/kH+h36M/pJ+lr6Z/pz+nr6f/qI+pT6oPqs+rb6wPrD+sT6xvrB+q36m/qU+pX6mvqV+ob6d/pv+mj6W/pE+if6DvoB+vj58Pni+dP5zfnI+cH5rPmP+W/5WvlO+UD5LvkY+Q35DPkU+RT5Bfnw+OD42/jX+M74wfi1+LD4t/jB+L/4ufiz+LX4vPi9+L34wvjO+NX43Pjo+Pn4BvkG+QD5AvkS+R/5I/kl+S/5R/li+Xb5fvmJ+Zz5tPnF+dL53fnl+e/5/vkS+iH6JPoi+iz6R/pf+m76dPp++pb6rPq4+r76yvrV+t766frz+v/6CPsP+xP7Gfsg+yD7G/sk+zT7PftD+0v7WPtm+237bPts+2/7cPts+2b7Zftp+2n7aftq+3H7ePt4+3P7cPt2+3n7dftw+3L7ePt5+2/7Z/tt+3X7cPtf+1f7Xvtj+2D7VPtQ+1f7XftV+1D7VPtb+1z7WPtX+1f7VPtP+0z7S/tJ+0D7N/s2+z37RPtI+0L7PftA+0f7R/tD+zv7OPs++0P7RPs/+0D7SPtM+0P7Ofsw+yr7Kvsq+y77NPs8+0n7U/tY+1L7S/tI+0b7Qfs4+zP7Nvs/+0b7SvtK+0f7Q/tC+0T7RPs++zr7PvtN+1r7W/tv+9/7afzi/Ff98f3B/qf/bgAHAZoBPwLrAowDIwSyBEQF5QWVBkwHAgizCGsJQgo6CzgMKQ0TDg8PJhA7ESwS8RKlE1IU/BSaFSQWpBYrF8EXZhgUGcEZZhoNG7cbXxz2HHkd7R1bHsEeFR9QH2wfcR9kH1IfNR8CH78efR5BHggeyB2EHTwd8RyUHCQcqhsjG5Ia9xlOGZgY2xcXF1UWkhXEFOoTCRM0EmQRkRDAD/IOKQ5tDbEM6QsVCz4KbgmeCMoH6wYOBjgFbwSxA/ICMQJuAa4A/P9d/7/+H/6F/fj8fvwM/Jj7Jfu3+kz65vmH+Sz50Ph1+Cb46Pey94H3Tfcb9/j24/bS9rr2pPaW9pr2oPak9qf2sPa/9tD22vbi9vP2Cvcj9zr3Ufds95D3tvfX9/z3JvhQ+Hb4ofjM+PL4F/k8+Wn5lPm0+c756PkJ+in6Q/pW+mj6e/qS+rD6yvre+un6+foS+yz7Ovs8+zz7RvtW+1v7V/tQ+0r7RPtA+zr7KfsU+wr7BvsD+wD79frq+t/62PrM+r76rfqV+n76avpY+kf6Mvob+gX69fns+d/5zPm6+az5pPmd+ZD5gfl0+Wv5ZPld+VP5Qvky+Sr5Kfkn+SL5GfkU+Rn5H/ki+SD5Hfkd+SX5Mfk5+Tb5M/k3+UT5Vflc+Vn5X/lx+YX5lPmZ+Zv5o/m0+cj52/nm+ez5+PkO+ij6N/o9+kL6Tfpj+nj6hPqK+pD6ofq4+sr60vrY+uH68voB+wz7Ffsd+yn7OftJ+1L7Vfta+2D7aPtx+3T7evuB+4n7lPuf+6v7rPuq+6n7qvut+7P7tfuy+7H7tvu/+8f7y/vF+777v/vF+8v7wfu3+7b7v/vE+8L7u/u4+7z7vvu9+7n7tPuu+637svuz+7H7rPul+6X7rPus+6P7nfud+5v7nPuc+5v7mfuZ+5r7nvuj+5/7l/uT+5H7j/uJ+4H7ffuD+4r7j/uQ+5b7m/uY+5X7kfuP+5D7kPuM+437jvuN+4/7k/uT+4z7hvuI+5D7lPuV+5b7m/uh+6P7oPuf+577mvuW+5b7lPuS+5L7k/uZ+5/7nfu1+y/8t/wn/Zn9Nf4H/+P/iwAAAXsBEQKtAjADpwMdBKEENQXMBWIG8gZ/BxUIzwioCYUKUAseDA4NHQ4gD/UPnxA5EdwRehL9EmMTxxM8FMcUXRXsFXkWCxeeFzQYyRhKGbgZHRqFGukaORtmG24bbBtqG1wbNRvyGqYaYRosGvYZtBluGSgZ5RiaGEQY3hdtF/cWdhbqFVAVrhQEFE0TkRLYESMRahCmD+cONQ6MDeAMKgx0C8YKHwpwCbQI+wdRB6MG8AU1BXwEzAMbA28CuwERAXMA3v9K/8L+SP7W/Wj9+PyK/CX8zPty+xf7vvpv+ir64vme+V35I/nw+L/4jfhk+EX4Lvgf+BT4CvgI+Af4BvgL+BH4FfgU+Bj4Ifgz+Ef4Wfhs+IH4ovjC+Nz47vgE+SL5Rvln+YH5n/nE+ev5D/ot+k36Y/pv+oT6oPq6+tH64vr0+hD7MftK+1D7U/tc+2v7d/t8+3v7ffuM+5/7q/us+6X7oPud+5z7lfuM+4b7fft3+3b7c/to+1X7Qvs2+yz7HfsI+/j68vrm+tT6xPq6+q36nvqM+nz6cfpq+l36R/o2+ir6IPoW+gn6+fnu+ej54fnd+dj5y/m9+bv5wvnK+cX5u/m5+b75w/nC+cH5vPmw+ar5sfm++cj5yPnD+c/56fn8+f/5/vkG+hH6H/oq+jD6OPpC+kv6XPpv+nn6c/pv+n/6l/qq+rH6tvrG+t/69/oC+wv7FPsd+yf7K/sx+zr7QftG+1H7W/tk+2r7b/t8+4z7mPuc+6P7rvu1+7v7wvvI+837z/vP+9T71/vU+9P72/vg+9v71fvb++f77fvu++378/v9+wD8+fvx+/L79Pvv++X75vvo++n77fvw+/P78/vo+9/74/vm++P72/va++P77vvy++/77vvs++j74fvY+8/7yvvJ+8770/vU+9L70/vU+9X71fvP+8r7yPvL+9T74fvi+9v71vvZ+9z71PvH+7/7wvvB+8H7xfvL+9P72fvf++H74fvf+9j71fvV+9n71fvS+9P71/vd+9772/vU+8/7zPvM+9T72fs7/AX9u/1c/gr/8v8CAe0BhgL3AnwDFASnBCcFpgUlBqoGOwfIBzsIpQgVCZsJVQo1CxkM8QzbDfIOEhATEdQRXhLgEmgT6RNFFIQUyRQqFaAVFhaBFtcWNhejFwkYYhiqGO0YLRlnGZYZrxmsGYMZOxnrGI4YIBidFxMXmRYzFtQVbBUFFZ8UORTNE1wT3hJOErYRGhGDEOMPNQ93DrUN9AwsDGELhwqwCesILgh9B9oGRga2BSEFkwQKBIED7AJFAqcBFAGDAPL/Yf/V/lj+4f1p/fb8g/wl/NP7hvtE+wj71fqv+pD6Z/o9+hr6+/nW+a75kPl3+WX5U/lE+UH5P/k7+TX5PPlK+Vr5bvmH+aX5yPnq+Qf6Jfo++lT6aPp9+oz6mPqp+sD64/oB+xL7JftA+2D7efuM+5/7rvvH+9777Pv6+wv8Fvwc/B/8Hvwa/BT8EPwM/Av8BvwM/A78CfwK/A38DfwC/O/70/u5+637pvug+5X7h/t++3b7a/tb+0P7KPsL+/D63PrO+sj6w/q5+rH6pPqT+nv6YfpL+jv6Mfop+hv6D/oV+h76Jfoh+g76+Pnm+eD53PnT+cj5xPnK+db55vno+eP55vnt+fX5+/n1+fP5//kN+hL6FfoW+hH6Gvow+j/6SfpP+k/6VPpq+oX6kPqV+pf6pPq5+tD61/rU+tb62frs+gL7E/sU+xL7Ivs5+0/7WPtQ+0n7Vvtu+4b7kfuI+4j7nPu0+7r7rPub+5r7q/u2+7n7uPu5+8v75fv0+/b77vvp++j75vvo++X74/vo++779vv7+/j78vvs++L74vvm++b76fvw+/n7APwD/AT8/fvz++776Pvl++b75vvn++P73/vg++D73vvc+9f72/vj++z77fvj++H75Pvo++v73PvD+737yPvc++b74/vc+9z74vvp++v74vvS+8n72Pvi+9z70/vY++n78fvq+9j70Pvd++X74Pvd+9774/vo+/T7/vv9+/H74/vX+9f72vvV+9P71fvj+/b7+fvv++/79fv7+/b7L/xu/ff+MACAASoDHQUAB1MIDAm2CYgKQQvOC0QMxQxnDQ8OpA4nD4IPtw8AEJsQjBGhEs4TIxW5FnwYHhpgGz0c0Rw/HYsdlB11HWkdeh2cHbwdyB3OHcsdsh2KHVMdDx3UHKgcdBw2HOAbXRuuGtQZ1xizF4IWVBU2FDQTThJ3EZwQ0A8DDzQOVg1bDF0LawqACZYIqAeoBp8FiARoA0ACHQEAAOP+3f38/Ef8uvtA+7v6O/rY+Xj5Ffmw+D743PeW91r3Ivfw9rz2i/Zx9mT2UvY49i/2Q/Zv9qD2xvbv9ib3afez9wr4V/iX+NX4I/mK+eD5Dvo4+nn6yvoj+3L7tvv7+078vPwh/Wb9kP22/eb9Gv5E/lP+cf6h/tT+A/8h/zL/Ov8s/yL/K/8g/wb/6f7N/sX+1P7H/qT+gP5m/kz+I/74/cH9k/1x/Ur9Gf3s/L78jfxX/B386/u0+3X7OPsB+9H6s/qY+nj6Ufor+hj6Ffr++cj5mvlz+Vj5Sfkt+Qn58fje+NT44Pjg+M34wPi7+L/4yvjR+NT44/j9+BD5GPkT+Rz5Lfku+S75OPk4+Uv5ePmT+aj5zfn1+QP6D/os+kn6W/ph+mj6evqZ+q76uPrT+gD7HvsW+xH7Hvs3+1P7V/tR+1n7dPuP+6n7x/vN+8j7y/vV+9373/vX+8X7xfvR++D76fvl++77/vsN/BH8+Pvk++L75Pvl+9771vvc++37BPwP/A38Afzg+8v7yfvF+777ufu1+737zPvX+9j70vvK+8D7vvu2+6j7pfuw+8r73fvW+8j7ufu1+7j7o/uM+4z7kvuh+7b7zfvb+9/73vvQ+8v7xfu4+7D7rvu7+9v75PvQ+8771vvY+9b7xPup+6b7ufvN+9v75vvt+/b7+/v2+/j7+/vy++77+fsD/AD88Pve++X79Pvj+8v7yfvI+9379fv3+/z7CPwS/A78CfwP/Af88vvs+/T7+/v5+/H78vv3+/T73fvJ+7/7vfvQ++b78vsL/Cn8MPwv/FP8vP0yAHACrwSCB/YKkQ5tESYTSBRKFfUVJRYpFlAWlhbuFmQXABiaGO0YFBl4GW8a3RtfHQMfISG1I1omqihiKl0rtCuUKxMrTSo7Kfsn6iYeJnUlwCTbI8witiGbIGMfCR6dHEIb/xnYGJsXKBagFO4SERE5D2kNlwvZCTwIywaCBTgEzwJRAdP/W/7h/E/7xPla+Pn2qvV79D/z8/G38Irvj+7K7RXtjexZ7HDstuz77DHtge3r7UPuje7t7lHvyu9Z8OHwdvEz8u/yfvMF9J30TPUM9s72m/d3+GL5Tvol+/f7zvyL/Sr+0v6G/0cAEgHGAWcCAwOXAyAEcASMBKcE1wQLBSgFNAUxBTYFSAVGBSsF8QSWBDgE9AO6A10D3QJjAvgBrwFcAdQAVwDm/3b/HP+v/g7+W/2+/ET87vuG++/6c/o/+iH61PlR+cf4WPjy93v39vaR9nj2evZt9mj2efaP9pb2e/Yx9gL2A/YC9gX2EvY09nj2y/YP90D3V/dX91v3gPe79/j3MPhl+Mj4VPnB+fX5BPoZ+jr6U/pW+lX6efq6+gX7V/uk+/f7QfyA/KP8jvyR/LP8t/y5/Mv81Pzr/An9Ff0V/Rj9Ev0D/en8z/zM/NL8yfy5/Mz87fz5/Nr8q/yX/Jr8hPxF/An88Pvy++H71/vd++j78vvp+837wPuw+477Zvs7+zb7RPtP+0P7NftH+2n7bvtA+wz7CPsY+xX7BPsH+yT7OvtN+0b7Svtm+1z7Ofst+0T7Xvtm+2n7gfue+6j7lvt/+5D7vfvL+7z7s/u8+9f76/vb+777qvux+8r71/vi+wD8H/ws/DP8MPwl/Bn8BPz5+w38JPwk/Bn8BfwH/Bj8G/wO/PP70/vR++/7EPwr/DD8L/wy/C78H/wD/O773PvJ+8v73/vn++P73Pv3+x38Ffzz+7r7nvvA++b76/vb+8375fsP/Bv8BfzR+6r7p/uz+7H7ofuj+7/76fv++/z7//v2+8/7xfvl++r7yfuq+6z7L/zK/tAClgZVCtkOORSfGaQdgR8CIC0g3x/WHpQdnxwOHOYbNxz/HMYd7x2sHdEdBx8TIUEjoiXNKNgsDDGGNK42TTezNik1uzLGL6MsdynBJs4kXCMIIncgjx6LHHkaNhiqFQATrBDCDhwNtgtJCoQImAavBLkCyAC//pL8ovom+eP3ifYI9VHzivHl7zLuTuxx6rvoMufz5f3kKuRs4/Xiz+L74orjZORt5Zjm2ucx6Zvq5Ov17PXt9e4V8FLxe/Ks8/T0M/Zp94X4dflX+j77Q/xw/Zr+zP8XAXECtwPABJEFZAY/B98HWgj3CK0JYQrwCksLqAvqC9QLegsfC98KfwrnCUQJ1gh3CMcHzAbcBRoFVQRXAzMCQQGWAPr/P/93/sz9JP14/ND7D/tP+p/56Pgp+Jr3D/de9rH1IPWh9D/0+fOL8wHzq/Kg8qLykPJm8lbykvLp8i3zXPOL88LzD/Rj9Kj08PQq9Xn19PV69uX2Qfek9xL4fPji+GL52vlH+rf6H/uN+wv8ZvyU/Mz8//wW/S79Wv2m/ff9Mv5d/pD+vv7Q/t/+4/7X/sr+wf7P/uj+4f7B/qn+k/5b/hH+3P25/X/9Nf0J/Q/9Gv3p/I38R/w6/Cb84fuR+2b7Zvti+0L7H/se+xL74/rG+rX6qvp/+j36L/pJ+lr6Q/o0+k76XvpF+ib6Q/pt+nD6aPpj+oH6wfrx+vr6+/oL+yT7OftC+zr7NftM+1z7aPt/+5r7tfvD+9n7D/wz/C38Jvwo/DT8UPxK/B/8E/wx/Fn8iPyf/JT8jvyc/LH8nvxe/Br8AfwP/Bf8L/xN/Fv8d/yM/Hr8Yfw0/Oz7yPvE+8z76vsX/ET8YvxV/Cj8C/z3+7X7XPsv+1P7pPvl+wv8J/w7/D78Ivzc+4H7MfsC+/76MvuF+7774fsZ/Ez8Sfwc/NT7hvtr+237avuG+8L7+/sY/BL8/fvn+8T7jvty+4H7k/uv+9T7B/w//EX8C/zE+6j7rvvG+8P7qvu8+wb8aPy9/nwDmQiWDQcTURkVIJYlOSh4KLknOCbmIxIhgB7AHOwb6RugHNMdtx4NH5UfOCH0IyMniiqMLlczQjhTPMk+Zj8/Pn87gjfwMlIu4inMJWYiwh+gHZAbORmzFjcUthEND2wMLQpmCOcGcQX1A40CGwFc/0v9MvtJ+X33uvX/80nyg/B/7jbs4OmL50fl9eKz4ATf5t1G3ezcxNz83Kjdwd4r4Nrh1+Mg5pToDOtd7TLvevCO8ZLylvOI9Ev1RPaj9z352/pn/NT9Hf9CAEsBcgLXA0YFmwbwB3IJDAtSDCkNuw0/DsQOMA9MDz4PQg9LD1oPQw/aDikOeA3EDNkLvQqECUII8QaRBTwE/ALbAcUAsf/X/kX+m/2T/Hz7hfqi+Zn4X/dJ9pH1AvVo9OfzffMH82byjvHA8CPwiu/17qHuwO4u75jv0e8T8I3w4fD28BPxYPHS8VTy6/LG89j0uvUt9m32+/a59yb4SviU+Ff5V/o9++z7cPwA/YD9vf3y/S/+Xf6e/hL/r/9SALQAwgDLAO0A8gCjACgA8v8MADcAPQA9AFwAZAAsANL/fP8X/5L+Ff7T/dL9s/1q/TL9Fv3k/Hz8AvyU+y37tPpF+gT6C/oY+tT5nPmu+dr5z/mL+Uj5Mfko+Q357/jo+CL5aflx+Wb5jPmy+bL5f/k8+S75Vvl8+Zr52/kr+nv6yPoY+0/7YftN+yL7Lftj+6j75fsB/C38evzV/Ab98fzO/J/8X/xD/Ej8U/xt/HX8g/zi/E/9W/0r/QD9/fwN/fr8sfxx/Gj8dvya/LH8tvyO/Ef8Lvw7/DH8BvzR+7f7yfvS+8H7xPvn+/P7zvuV+377mPuM+z379/rs+gD7CPsR+y/7dPum+777zvvE+7j7mftg+zb7Hfv3+t368foM+yX7NPtC+377qvuV+4/7tPvS+8/7s/un+8T77Pv2++/79PsE/Pz70Pul+5T7dftR+2P7lPvO+xX8MPwy/ED8TPwh/Nb7ofty+2D7hPvC+4H8SAB6BpcMfBLnGBMgTidpLNst0CwPK6MoOyWkIeceWR2iHLQcpB0JHxUgiSBQIY8jXifYK34wqzVvO/9AK0UWR5JGt0MMP1w5UjNyLRcoUyM7HxocpxlRF9YU+xHXDukLhQm1BxgGZgT7Ai4CnAGhAOz+rfxi+jX4C/bS837x/u5f7LrpHueK5MPhvt7j27LZPthW197WtdYe10zYA9oI3CreguBC4zfmJenf6zzuRfDy8UnzdvSB9Wr2Qvcq+G75BfuU/BT+pP9LAfACbwT5BcAHwgnBC4INLA/KECMSIhPAEwUUGRTsE6AThBOAEzgTsBIwEqMRwhBeD5gN4AtoCuIIQwfDBW0ESAMqAgsB+f/X/oj9EPy5+ov5R/j79tP1wvTf8wjzAPIQ8VbwtO8G70DuXu2X7C3s+Ouy62vrcuvF6z/sv+xA7bbtK+7J7nTvH/DA8GDxHvIC8/vz2vSW9Vv2QfcR+ML4avkL+r36cPsa/NL8mf1p/jP/5/91APkAgQHfAQwCLQJWAnUCfAJ2Ao4CqAKUAlUCBwLfAcUBfwESAcoAsQCeAG8AKgDw/53/J/+g/gH+ZP3F/Bz8evsA+676Yfos+hv6C/rT+Yj5Tvkj+db4UfjU96H3r/eu94X3hPfV9yr4Lfjm96b3vffg9+L39vcf+IT4DPl7+cL56Pnf+b/52fkS+ij6KfpM+qX6J/uo+/f7B/wN/Bv8SPyT/Lf8x/zm/B39fP3A/af9Yf0q/R39H/0l/Tj9Mv0l/Tf9Vf1s/Wb9Ff21/Ij8jfyn/MH83/zo/OD80/y0/HX8EfyS+yj7F/s5+0L7K/sv+2/7r/uh+zn7zvqp+o76fPqe+t76D/s1+2P7hPuN+1b70/pV+i36E/rx+Qb6RPqn+gL7Nvts+5L7fvtH+0L7Y/t2+3H7Z/uL+9X75fue+1f7N/sw+y77Gvsb+1/7o/vp+zz8S/w3/Dr8SvxT/Df8CPwQ/DH8KPzl+4z7ZvtO+yv7Hvsz+3v73Ps8/Mz8AwBEBvcMQxMGGtkhFyqfMC0zcTKbMPAt9ClPJUQhlR45Hfwc/B3eH6shwiLvI7EmRCtmMEc1fTqjQNtGdUtyTdpMFkpyRT4/MjgUMVAqLiTvHrEaJhfbE68QzA1BCw0JGQdcBREE9wLJAbEAhP/x/R38Dfq+91r14/JQ8K3tyOpV55Pj7t9z3BnZ49Um01PRh9B90MzQX9F00iPUTtaw2EvbYN7y4eblvuk37VLw5fK59OD1mvYR94b3E/j1+HX6ePyj/rYAzQLxBAcH9QjeCuYMKw+IEcMT4hXhF5wZpxrJGmIa4BljGbIYyBffFisWnhX5FO0TXhKMEKwOxgzaCu8IBwc1BagDVAL9AJz/G/5n/Kf6Dfm/95v2Q/W280TyJvEf8PLupO1h7IDr2uob6mjpwuhC6Ornuee258nnBeiO6FXpNOo16yjsz+xp7S/uDO/97/7wCvIz83n0ufXg9uP3yfiV+U76BPvg+//8Ev7y/tT/uwCKAS8CigKuAuUCRQO/AzYEiQS8BOUECQUfBQUFowQhBMkDnwOBA1QDCgOiAiECggHKAAwAT/98/qn9Df25/Jb8TfzQ+z/7ufpK+sH5B/lx+CH47Pfj99v3r/eR93L3Ivev9i72xvWG9Xn1lPW+9Rz2o/YT90n3Vfdk93v3n/e299b3I/iE+O/4cfnl+Sn6YPqA+sP6HftC+0/7Z/u1+zL8lPyx/MT8CP1y/bn94v31/eT9vv1//Wb9eP2H/Xj9VP1s/cv9Jf44/gn+y/2u/Z39V/3//NT8tvyg/Jb8gPxg/C782Pt4+0/7OvsK+836xfrv+hb7Jfsx+0z7QPsB+8v6uvqq+mj6//m5+cz5AvoH+g36O/qN+tD63Prg+uD6s/pz+j/6Jfo7+mH6YPpp+rX6FPtL+0T7Nvs4+077cvuC+3D7cfua+8b7/Pso/A78y/uu+7372/vK+237HPsT+z/7Zftn+3n7vfv9+yz8afyO/Hn8L/zx+/X78Pus+1b7SPul+6X9IwNsCocRzRj2IN8p8TFnNoA2SjQ4MR8tEyhKI/ofXB4WHvoe+CBlI0ElpybBKGMsSDGdNi88aELqSG5OqVEDUqxP60opREQ8TjTbLAomFCAuG00XBBTqEOwN/go7CO4FJwTNAt4BAgHs/6r+MP1U+/z4TvZr84Hwou286qDnPeST4Lfc6Ng21drRE88EzdTLi8v9yxHNq86i0AzT99VT2f7c9+AO5QTpyewl8NXy6fR99or3QPjw+M756/pS/AP+5//1ARkEQQaICAsLow08EOISnRVaGMAagRy1HZgeDh/sHj4eSh1xHKQboRqBGVgYHBecFacTdhFHDwcNqgpgCEoGngQiA4sBDgCu/lj95Pso+jz4Zvay9AfzbvHt75XuSO0B7MrqiulL6BfnE+ZK5bTkSuQE5P7jR+TO5HflaOZz527ohumu6uvrIe0d7v3uA/Ah8TvyOfMs9FH1ovbu9/343vnD+r77w/zV/en+/P8gATgCLwMCBMMEagXVBSMGaAaiBsUGwAaxBrYGsgZdBsIFHgWeBD8E0QM9A68COwLCAUoBxQAnAHn/vf7v/Tz9tvwu/Iz77Pp2+h36zvlC+Wb4kPcT99H2V/aW9fz02PT29PT0yvTM9Oz0BfUi9Tb1YPWq9c/18PVW9r/2+vYq90/3i/fk9yD4SfiA+On4b/nc+S36i/ro+jf7ifvS+y78f/yY/Lz8Gf2F/d79G/43/jv+RP5P/j7+I/4H/tn9v/3R/QT+NP4//jD+D/7x/aT9Ev2w/JT8ifyN/KX8z/zx/Oz8pPwu/MX7V/ur+vf51Pkf+mv6ofqm+p/6q/qu+mD65Pmb+Yv5s/kP+k76U/pj+nP6Qfr4+cX5hflm+XP5k/n5+Xv6s/qg+pT6jfp6+m/6Zfpr+q/6KvuY+9X75/va+8z7xvuZ+zn7/voB+xz7Sft3+6H73fv++/D7APwV/Ab84/u/+8P7yvu9+6j7jPud+7T7ovuN+377dfuA+4/7gPth+1v7YPs0/fQCqgpXEggaYSKcKx00zjiSOIY1qjEeLc0ntyIeH40dxB1cH+8hnyS5JjQoISroLVwzLTn6PkZFC0wZUqFVl1VqUtZMWEW8PAc0CywnJUQfaxq5Fq0TghAnDe4JGQflBC4DywHrAIoAFAAV/3L9N/uK+G31/PGO7mjrX+gp5bTh+t0D2uPVt9HmzezK5sjbx7/Hm8hdyrXMcc9+0t/Vddkq3Snhe+Xp6f3tS/Hs8/n1Xfcx+I/42PiI+aX6I/wL/lAA4AKPBUcIAwvKDaQQbhMiFuUYshs7HhkgUiH6ISAi3CEBIcQfmB5pHQUceBrjGFQXoRWfE2kRSQ9LDUMLIwkeB04FmAPhAQwAGf4b/Cr6TPh19qP03PIx8aHvDe5m7MXqQunH527mWeVw5I7jy+Jg4lvijuKq4rriEuPT48jkv+Wo5tDnJ+lj6pXr1+xF7o7vlPC08Qjzc/Su9bH21vdI+Zv6o/un/Mz9CP8KANEAxwEPA0EEDQWuBW8GRwfZB/oH4wfQB8AHjwc/B/cGuwZkBu0FgAUiBaIE6AMfA3kC4QE6AZQA5/9Q/8H+D/5L/Zf89/tb+6P64Pkf+Vf4sPcQ93H22PU/9dX0sPSu9JD0S/Q19GD0evRr9Ef0RfSU9PL0J/VJ9XT1qfW/9bX11fUi9m32t/Yc99r3zPiX+fX5Hfpx+sL69/oB+xb7cPvZ+0D8vvxQ/b/92f3K/cT94/0R/hP+Df4u/m3+jv5x/kf+If7s/bv9mf1x/Vb9Y/2O/bj9t/11/Rz92/y1/IH8KvzZ+6b7ePtk+1T79vqF+h/62Pnm+fv52Pmy+d75Tfqe+pX6MPrF+bL5vPmt+Xn5PPk++Xr5tPnS+d75u/l6+VP5XfmS+cb57Pka+mz60voZ+xb7+/rl+rT6n/qm+rv67fos+1z7ivuy+8T7xvuh+1T7Gfse+1H7i/uO+3L7jPvT+/z72/uJ+1L7aPuh+8f72fvS+8r72fvW+8D7k/sz++D61Prv+hr7r/0cBBYM+BMHHM8kGi7cNVk5jDiqNbsxryz0JgYiGx83Hs8ekSA7I/QlCijrKbksAzFRNho8gUKWSYhQ2FVrWOJXZ1Q4TgRG9jwWNPkr1CQKH48a9RbFE6QQoQ3dClcICwZFBFIDwgISAjABGACf/mP8U/m19f3xYu6+6tfm3eID3/zaq9Zp0mnO4coVyEbGqcU2xqPHhsnfy93OPtK21SzZzdzS4Dflkelv7b3wgfOf9fD2gPeb97/3QPg4+cj6Ef3q/wsDMAYrCToMbQ9zEiQV0hetGo0dKSBSIvMj3CQHJXUkRCPLIQsgDx42HKsaJhmQF/UVLhRFEkcQLQ70C8wJsQecBcAD/QE2AFT+a/x2+kb4CPbv8/3xFvA77lPsiOoG6Y7n/OV95DPjJOJx4f/gj+Au4B7gaODy4Hjh2+GC4ozjyeQ/5tPna+no6iXsSu2O7uHv8/DU8c3yF/S09Uj3qfjq+Tb7hPzO/RT/SgBpAYACxwMRBSsGAgd6B68H7QckCDgISghSCF0IZwhnCDYIsQcGB1cGhAW0BAQERwOwAkwC8gGBAeMACgAW/zL+N/0o/Bn7Hvpr+e74a/jc92b3Cfea9v71SPWs9Cr0tvNM8+3y0/IJ8zTzJ/Md8yXzP/Nq85PzxvML9Hj0BvWf9T32o/a29sT2IveW99L38Pc2+Ov4y/ls+q36y/ok+5n75PsQ/GL81Pw9/bH9Mv6G/pb+cv5J/kv+WP5K/jL+Uf6h/tH+of5M/vL9pf1u/Rv90fzC/OD8Cf05/VD9I/26/Df8vPtj+xH7rPpi+m36pPq1+n36NPr2+aX5YPk0+Q758Pjr+BD5afnC+bf5ZPki+RH5D/n2+NX4yfjl+Cr5avmI+ZP5o/mn+bn53/n/+TH6TPpi+pr6xvrF+rL6o/qW+qP6t/rL+tr65/rt+vb6FvsZ+xD7MPt2+8P7+Pv++xD8NPwK/I37EPvK+rn6qfqI+qr6KvuW+5/7ifuB+0n73vpq+hr6JPqz+lz+sAVSDsgWGB8VKKIxEjmAO5E50TV5MZEsWifWIhsgah9kIL0i4CWkKGMqLSytLzk1tjsqQuNIU1CcV+hcwV4EXWVYcFHESHU/bDY1Lh8nMyF2HLoYeBVFEi0PiAx7CgEJ9gcyB5wGDgYCBS0DwQDY/Wr6hvZR8hjuFuoc5rzh6dz81zzTx866ylzHA8W3w2DD+MNzxb7HX8oBzdTPTNOE1+zbEuAb5DfoNux275Lx0/KZ8zT0uPRA9Rf2a/dO+dH71f4FAjEFbQjKC1MPAhOcFgkaPx0UIH8ieCTOJTgmwiX3JC8kQSP3IUEgWh66HD0bURkCF78UrRLPEBYPNg1fC64JvQekBZwDegEm/7z8X/pH+Hf2kPSG8n3wWO4S7M7pouet5QLkd+In4U/gw99D39Xegt5Z3n/e6N583zngLOFU4rbjHuVa5nznl+i76QzrdezT7SzvevDG8SHzhvTV9SD3ePj5+Zn7Qv3u/oUAAQIlA+wDrgSUBV0G7gZiB+sHsAhiCaoJiwk6CdQIcAgKCJoHEQd4BvYFmQViBfQEEgQNAxkCSwGfANj/3/72/Tj9nfwc/E37CPrL+Af4kPf69hv2UfXi9LX0dvTo80vz7vKq8kzy/fHj8f3xMPJN8nDy2fJZ85nzpvO98//zYvS09Ob0MvWs9SH2ifb49oT3Kvip+On4Ovnd+Yz67/o7+6z7L/ya/ML81PwY/XX9mP2G/aj9Bf43/if+Hv5W/pj+e/4l/vj9EP4r/vn9pv1+/YP9Zv0K/cn8qPxn/Av8z/vW+937ivv0+pn6n/qZ+jb6s/mc+d75CPru+a/5l/mQ+UT50/iF+Ez4Gfj09xL4gvjl+PH40fjY+Av5Pfkt+e34zvjq+C75g/m2+bj5y/nX+cD5tvmh+Xn5bvl8+aL5D/qA+r764PoU+3f7u/uL+/36l/qe+sn6zPqz+rf6//pV+2j7Z/tj+yz7xPp6+oT6yfoE+yT7Pftx+5v7Y/vw+pD6K/rA+aD55vpdAOEIxxGaGggkWC7qN889lT7TO443QTIiLF4mViJoIGkgOyJ7JSopDywdLq0w+DT2OqRBbUjMT9RXGl/KY7dk3GH8W8pTBUqzP9o1Ky34JVEg/hucGLkV/RJlEDEOdQwgCwkKIglpCJYHWwZRBG4BDf4++gP2c/G67A7oe+O23pvZUNQcz2fKacZOwz7BUsBvwHrBdsMvxjfJSsySz0vTfdfd2xjgFOT153/rU+5B8GPx/vE+8o7yMfNc9DX2ifgm+0r+BgLeBYAJAA18EBoU7Re4GxwfFiK3JKwm3CdSKP0n4CZKJaQjCyJ/INUeEx2BG/8ZUxhZFgYUqhFwDy8NDAs5CYcHyQULBEkCXwBY/vv7OfmK9gD0hvEr7+Lsreqi6MPm/ORb49nhN+C83tLdaN1B3RLd69wp3eTdqt5M3wLg9+BG4qrjFeWp5lLoxenj6tnr9uwe7gDv3e8n8ezywvR79jv4IPr0+1v9e/6e/9AABwIvA2AEyAUhBwUIpAgqCXoJgAlDCdsIgAhJCBAI4Ae7B1EHoQYTBrgFYgXLBPUDLQO0AlkCkgFrADn/Gv4a/RX8Dfs8+pP5x/gH+Hr3/vZG9jT1PfSr83TzNfOv8lTybPK98sjyd/Ih8vXx2vGp8YzxofHu8V3y1PJ08y70y/Qn9Vj1q/UJ9jv2S/aH9in3+vfB+Ez5tflW+vv6U/tn+3D7mPvk+0f8mvzw/Hf99/00/lT+Wv47/hT+8v3d/er9DP7z/bH9mv3J/dz9jv0H/aX8tvzh/Mb8gvxW/Ez8L/zH+0775Ppg+tT5dvl8+bP5qvlS+Q/5PvmX+XD53Phv+Ff4fviE+Fr4U/ht+Gr4U/hj+In4k/he+BL4L/iu+PD4vfhv+IX4Bfld+UT5IflI+aH53fnR+a75pfmy+bP5wPnr+Sf6cfqz+gn7bPui+3r7F/vc+t/64fqo+lr6Ovpd+pX6pPp8+lf6Vfpz+qP6xvrt+hL7Nftk+4j7c/sA+3L6EPot+tj9oQWnDqMXGCHNKwM3dD84QhlA3TukNjkwVSnKI+EghCAYIjclPynwLHUvnTEwNdg6h0FfSMxPLViGYK9mA2lDZ/Rh0lmdT5xEDDqkMLsociLnHaUayRfYFAESpQ+tDegLjgrgCbIJSgkVCDkG3gOoAIz85Pf68gLuKOlq5Kjfv9qK1TjQW8tTx/rDSMGlv12/dMBNwnXE/cbeyRvN5tAc1XzZAt584tTm5+om7jTwMfGL8azxz/El8gXzvPQt9wj6Nv2aAOkDGgdKCpENLxE8FWgZdh1RIcwkhCcaKXMpuChnJ88l+yMSImEgAR/DHWYcsRqpGF8WABSTEUAPTA2WCw8KygidBz8GhQRTArn/+PxE+p33A/Wb8m3wUu407ALqyueo5ZTjr+E64Dnflt4u3u7d0N3Z3fzdCN4g3nHeJd9R4LLhMOPU5HTm1efq6K7pXupD617so+0E74/wSfIy9BX2kfe4+Nr58PoJ/Fv90/5pAAYCkAP/BFcGcgfZB70HrQfjB0IIfwhCCOYH0QfsB+YHTgdeBp4FHQWdBBYEpgM5A7sCHQJgAZoAsP+I/nD9nfz0+0b7f/rA+Sf5dPiT96n20PUU9WT0vPNG8xXzBfPZ8obySPIM8sXxpPGn8crxB/JQ8sLyU/PJ8+Xz0PPn8xz0QfRj9Lb0O/Xx9bT2Wvf194/48PgT+Tr5e/nJ+R76Zvq0+ib7r/ss/Hb8lfzM/Cz9h/20/a39s/3n/RL+A/7B/YD9b/1d/TP9Dv0E/Q/9/fyp/En8GvwA/Nv7mftr+477zvvT+377IfvW+m/65/k6+aH4dfiU+L34APk9+Uj5Q/ks+Qj53viB+Bz46Pfv9yT4Ufhj+GT4X/hm+Hr4fvhe+Dv4LfhW+KH4xPjY+PD4H/ln+Zz5u/na+eP52/nc+dX51fnu+Qv6EfoQ+iH6N/ow+gX69/kI+hX6Fvo4+pz6EPs0+xL7HPs/+yD7hPro+dP5FfpH+kb6Vvqj+u/63/qO+u76Uv+PB8UQEhoYJHgv/joaQzNFcEJnPTA36C98KNAiHSA6IH8iYSYMKwovrDEYNO43rj2HRJdLI1OgW9pjmGkla0Nox2HJWFdOWEPROJAvFih/InMeNxsEGL4UxhFiD5INRgxaC6gKGwprCSAI8wXKAsz+fPpW9kTyDu6u6SzlguBl27XVyc9Dyq3FQcIiwFa/279ewWHDt8UtyNvK1M0S0dnUP9kr3jfj3OfK693u/vDy8evxp/G+8XDyovM19X33kvro/fsAyAOcBrsJPw0IEfsUHhlEHRohVCS3JvwnFShxJ4cmbSUJJGIiyCBsH/4dOBwDGnoX7xR7EkYQZg7CDEoL+QnWCMEHQwYRBHwB7P6A/Bv6ufdr9T/zQfFW71TtLuvk6GbmDOQ84t7gqt+f3vHduN3c3QHeAN4T3nneM98q4Efhd+LE4yrlkea4567on+mQ6prrwuzy7SnvlvAr8pzz4PQk9lf3gvjR+Ub78/yr/k8A8wF1A74EkAXpBSkGZQakBtYGAAdYB70H8AfqB8YHbQeuBroF1AQiBLIDRgPFAmoCLgLVAVoBtAD4/zj/TP4+/U38gvuj+oz5bfih9yb3nfbn9Uj17vTM9JL0AvRW8+DynfI48t3x5PEr8oDytPLN8g/zavOO823zPvNP86Tz9PMw9Kf0WfUJ9of2v/b49kz3oPfJ9/L3XPj8+In5+vmb+nT7Kfxz/Hf8gPyd/JX8XPw2/E78kvzW/An9QP1v/XL9Wv1K/R/9w/xv/E78cvy2/NL80Pza/AD99/yP/Ar8cvvG+lr6Fvq4+Wb5UfmG+dP5CPoD+rr5gPlW+RT51fig+Gv4WPh2+Mv4Lvkp+cH4fPiC+G/4JPjB94f3zPcv+E34Xfii+Oj4AfkP+T35dPl6+W/5gPmk+Zn5UvkO+RT5Wvly+VP5Z/nW+Ur6m/qy+pf6iPpp+k76TPpU+lD6PvpB+nH6tfq7+pb6efpA+hr6G/oD+sr5mPm1+Sr6pPrb+vL6Nf4jBu8PeBnmIlAtfjh5QQ9FJ0NcPlc4LTGUKTgjmx/uHp4gLSTaKGgt6TDHM4I3Fz0KRElLs1LCWs5i/2iDa4Jpb2N7WrhPEkS6OM8u7CYSIe4cBRrGF7YVlxNkEWMP4g3CDMgL3gr5CeQIKAd7BLkAHvxv99byJO536dTkOuCx2/zW6tHNzCvIdMS5wRbAxr+nwJTCZ8WgyPTLbM/40prWWtpg3q3i4OaZ6pTtze9b8TvyZPIQ8tPxJvJQ80j15PcQ+63+fAJPBg4KrA07EcMUVRj3G3AffCLnJHUmDif3JlUmBSUcI/sgEB9wHd4bPBqQGNYWGBVHE1ERaA/ADTYMrQooCbQHPQZ3BEIC7P+5/Zj7Iflz9gj0+vH/763tMesB6TPneeWf4wDi+OBI4I7f6t613s3e2t7l3ibf5d/54ObhnuKI48XkEuY55yHoIulx6tLrKe1c7lzvTvBk8X/yevN09Jj1IPcC+eb6kfwk/rf/GAEsAgUDoQMtBMcEdQUtBsUGQgeNB6MHkQc9B54G1wU7Be0EvgRvBBAE1wOuA2QDrgKlAaoAzP/9/j3+i/0H/br8X/zd+0f7kfqO+XP4jPfc9jX2afWn9Dn0KvQZ9KXz+PKE8mbyUvIx8hnyGfJr8vLyTfOO89vzI/Rg9IP0j/SL9Kf09fRM9bj1Ova09jH3tPcL+Db4X/id+Nb46/gX+Zz5bfoV+5L7Gvyp/BD9CP22/I78nvyZ/Gz8XPyp/BL9Yv2Z/Zv9gf1I/dr8X/wf/O77ufus+6/7yfvV+6b7Xvsn+/v6zPqk+on6g/qS+rT6uPqH+h/6ffnf+Hf4WPhZ+E34Sfhz+K34vfiZ+Ef4/ffG96L3tfce+LL4KPl/+cL52vmk+Rz5efgd+PX32Pf292T4+vhS+Vf5SflP+V75QfkH+Q35Yfnj+Xz64Prq+rD6cfpe+lr6Nfrs+dH5E/qB+sD6l/pK+gH6q/mI+Zj5pvnC+Rr6o/od+0X7BPue+mH7qAChCXETSB2+J2wzqz6ZRe1FaEHqOo0zhisMJPweRx2+HpIi1SdTLYYx/DNYNn06WEDoRuhNvlV1XmtmKGtfaytnJF+WVPJIXj32Mj0qfSPvHi4cLRryF1kV0BKtEPsOyQ37DFgMywvSCgMJWga1Ai/+QPls9OfvxOu/54LjBN8d2rnUKs//yZbFQMJAwNC//8BMw//FnchQy0LOL9Eb1EHX2toZ38vjQOgL7P7u0/Cp8dXxj/H98KbwL/H58tv1Pfme/BIA1AOVBw8LSQ6cETwVAhnHHFAgbCO2JdQm8iZMJv0kNiMaIR4frx2HHFYb/hliGIYWbxQ9Eh8QFQ5IDOkK1Qn7CBoIxgYIBQwDfgBq/Xn6z/du9WDzU/Fb75zt0+vG6ZPnfeWK48vhfuCv30XfIN8l30Hfi9/53z3gd+Df4KTh5+JT5HzlfOa35x3pOurW6kTrB+wz7V/ua++Z8ArysvNE9aT2Bfh3+ev6TPyi/QL/bQC2AcACiAMjBL4ESwW0BQ8GYQavBt0G0gaNBjIG4QVbBaQELgQMBPcDxQNpAxgDywJNAm8BXQBl/4P+0P01/ar8Q/zB++76Gvp7+bP4n/eA9rX1S/UI9Z/0KvQF9Aj00PNO8+vy5PLd8rDysPIY85vzuvOM83LzofPB87Tzq/O+8wj0ffQc9dT1bPa69tr2PPfs91P4TvhL+K/4Z/kI+kH6QPqQ+ij7gfuL+6f78Psc/Db8YPyR/MT8yPyi/Kv88fwK/cb8hfyA/J38nPxm/C/8O/xt/Fb8CvzA+577ofuA+yL7p/pW+lD6Yvo6+tH5ivmQ+bX5ovlT+TD5Pvk1+RD54Pip+G74RPhM+H34k/h5+GD4e/in+Jj4Vvgw+ET4Wvhc+Gn4p/gI+Sn5C/n7+N34qvin+Nf4Cvks+Tz5avnN+Rn6Afqq+WD5PflC+Vf5e/nG+Tf6r/r6+hH79fqd+jr61Plx+Ur5RPlQ+aD5Fvp9+sn64frL+qD6Xfoe+2QApgnGE7kdNCjaMzk/WkaiRgxCszt0NGws6CTKHyAerB94I8Yobi7KMo81Fjj1O4FB6EfSTrNWZl9PZz5s1mz4aDVhl1afSq8+wjOaKqcj7R7+GwIaBhj0FfITyxG7D/UNpgzoC1ALLgpOCO8FvQKx/gv6EPU88HPrgOaN4a7crtdQ0s7M48ckxJ7BBsBlvxrAG8LZxKLHPMr8zAzQZNMA1/LaN9+K45TnA+uf7WfvV/Bw8A/w/e+m8M3xfPPi9Qz5vvx7ANQD8QZxClgOWBI3FiIaMB7qIdAkgyYpJxknSibKJPwiOyHXH6YeXh0THLMaEhkEF5MUPhJBEFgOhQwlC10K4AkECWEHQQUcA9cAGf4U+xP4UPUE8+fwzO7e7PTq0+ip5t3kTePg4ajgq98m3wzf/97I3qze4d5Q3+DfkuB94Zvi1OP65BHmM+cc6NzoqumM6qPr2+wi7ozvOfHD8vTzJfVn9sD3KPl6+rz7Hf2k/jQAnwG7ApkDYwQWBaYFIQZdBoUG1gYMB/QGvgZxBiEG8QWTBQsFoQRdBBkEmQPpAkcCwAEnAVIAX/+U/gT+hP3s/E/8u/vu+vL5BvlA+Ir3sPa49fH0sPS09I70KfS083nzVvMI84nyBfK98cXx8vEO8inygvL88lvzq/Pl8xL0ePTo9Az1G/Vs9eP1SPaK9qP24fZq9/j3Y/jS+E35r/kE+lX6jvrP+hf7Mfth+9T7XPzU/An9HP1A/Vr9Qf3x/JT8WfxL/GL8a/yG/Kf8m/yC/Gf8X/xf/B78qPtY+1b7WPsh+9f6nvqD+mP6JPrl+dv56fnM+Yr5W/lJ+Qb5o/hh+Ej4Xvhg+Dv4N/h++Lv4s/iM+G/4Y/hW+CP48PcV+E34cviC+IP4qPjV+Mn4mfiS+JX4gfic+Nf4Dfln+af5tvni+Rb6Hvri+Yj5Ofka+SD5IPkn+Vv5tPn/+T76UPpK+mz6i/p4+kv6Mfor+jT6LvoG+uf5zvmj+YL5WPxBBLoOQRmeI7EugTpeRE1IsEXNPwA5fzGxKUEj/R9sIJcjOCiNLY8yBDYaOKI6KD98RaxMV1S3XGNlZ2ylb/Ntq2coXqtSZkaWOlAwKChgIroeUhxWGi4YzhVZE+QQ4g5SDfULwQqbCVYIlgbyAzwA3/tV96jynu1N6N7iaN30123S9czmx7PDo8Dlvm2+4b79v5nBxcNyxkPJLMyIz4vTLdgZ3crh/eWw6XDs+O2q7tzu3u4E75rv4fDq8pj1qPgE/HH/0AJOBsEJUg1bEYMVnxmyHXchtyQsJ4Uo1SiTKOwnvib3JOEi+iA8H2sdexuRGbIX0RX1Ew8SaBAbD7QNKgyhChYJngcGBgAEtQE4/6L8CPpj97H0y/Hd7jTs2OnO5+Xl+uNG4gnhHeAk3znerd1x3V7dQd1T3dndqd5+3zTg+uAJ4ibjJuQ65WzmuucW6VbqkOvO7NvtrO6T77Lw7fFG87X0Hvaw96X5p/ti/dr+EgBWAeACVARLBewFlQY9B6MHqAdhBygHEwfkBo8GWQZABvEFewUFBYEEDwSmAwcDdwJGAjUC4gE7AV0AXv9I/j/9Ivz3+gr6Yfnv+Jr4QPiX97n21/Xg9PHzDfM58qTxcfGr8RDyWfJi8lryd/Kb8pHyU/IO8hHyd/Lj8iDzV/Og8+rzPvSK9MX0GvV+9cf1Gfa09kX3iPe29/f3bvgZ+ab59flU+u76dfu8+/T7J/xe/Jf8mPyD/Lv8FP1E/Tn99PzL/Nb8v/xj/AX86/v/+yL8LvwE/AH8OPw8/BP88fvI+4L7Mvvh+pv6ZvoV+pb5Ovki+RP57fjm+Ar5IfkR+db4m/hr+Dr4Cfjt9+H3zPep95b3xvf89/H33PfQ99j3GvhI+Er4XPhp+HP4j/ib+JT4lPi0+Or4DPka+Qf53/jJ+Kf4lvi3+Of4Kvl0+cn5Ifo8+jD6FPr2+eP52PnT+c75Cfp5+tL66Pqn+kL6APro+an5LPnG+M34IfkN+70B2gulFm0hfyxeOG5DuEkZSdpDOD30NeYtRyY1IRQgpiIuJ1YspTFONr450DzpQI9Gb00YVTJdkWUsbbdxeHFpbKdjiVg5TMw/ljSmKzol8yAgHjIcgxpzGNgVARNgECcOXQzbCoMJHwhSBtMDigB0/MT3u/Ke7Zboe+Mq3obYtdIqzQ7IfcO8v+a8bbuOu9e82L43warDV8aDyQbNydAD1aXZgt5c48LnUOvL7SzvjO9F7yTvge9V8M/xI/Rq91r7fv9pAw4HnwpaDjcSLBZAGjke9iFaJRIo9SnwKucq6ikuKD8mlyQNI1IhUR9QHcIbUhp9GCQWvRPJERgQbg6rDOsKUAm2B+QFzgOVARX/J/wr+YH29vNH8YTurOsG6dbmzeS44sfgLd8C3jrdotwp3N3byNv321ncr9zi3FHdSt6H35fgeOGF4tzjVOV75jjnIuhw6bjq7uta7RHv+PDr8r/0Yfb+94n55vol/FD9jP7s/2wB/QJsBLQFzwaKB8oHwQezB6kHhwdZB1YHnAfjB+UHuQd3BxUHYwZMBTkEiAMVA4cC1gE7AcEAKQA2/wX+vvx6+2/6oPn2+Ev4dvfM9oD2KvZ19VH0K/OR8l3yDfKH8TPxMfFC8Tbx/vDU8L7wp/CR8K7wM/HP8RfyIPJ58jXz1fP+877zzfOA9Ev1vPXf9SP2wPaA9yf4ofgC+WH5wvkZ+oP69/pJ+4n7wvsX/Ib83Pz2/Or89PwP/RT99/zI/Lz85/w//Yf9ev1I/TH9J/32/I/8Evyd+2T7d/uS+4D7LvvW+rD6k/pd+s75Ffm5+Mr4Dvk2+SH5+fjZ+LX4dPge+Mb3UPfo9uX2QPe19//36ffB98f3yveR9yv34vbp9iH3Wveu9xf4VPhZ+Dr4MfhL+B/42Pfr91X42/gt+Uv5aPma+a35Y/kO+Rn5Yfl4+VP5N/l5+fv5MPoH+tD5y/nv+Q36B/r0+fr5Ifo/+jj6BPrK+cT56vnu+VX61/4HCPkS8h3SKG80ZkAUSfhK+kY+QKI4qDACKWMjRCG6IuMmvCwcM4A46Ts/PnJBmkZSTZVUO1x5ZJ9spXJtdB1xUWl5XiNSu0VuOvswwCnAJJshvB8uHgccHRn2FfgSYhBgDrgMMAuECU0HbwQNAQ79Wfgv8wLuJOmp5DLgNNuC1XnPkckfxGy/wLtRuXS4Zrmsu5q+r8GYxIPHrsr9zZTRn9UF2sLel+MT6KrrDO5G74PvXe9l777vlvBM8iX19fhQ/bwB6wXtCd8N0RHXFdQZoh1dIQMlRyi0KuQr3ysWK/4pjCidJqAk8iJ2If4fQB5OHFgaDxh/FfoS0hAJD3kN8wtuCvgILAfnBDwCT/9l/IH5nfbe82rxHO+r7AnqeucX5ajiOOAX3nbcZ9vb2nraE9rC2ZfZltnw2aTaa9tI3IndS9824b7inOMd5NTk5eXx5srnzuhm6nDslO6B8PrxKvNh9Kr1IPfs+Nb6yfzh/hkBRwMeBU8G3gYmB2cHtQf7ByQIUgicCNEIwgibCF4I4QdgBwgH1AayBloGzwU6BZ8E0QPHAsoB7gAkAF7/iP7C/Rb9IfzA+jz54vfB9r710/RK9Bn03POU80/z5fJS8pTxrfD777Pvge9o75Tv/e+L8ArxaPGP8YzxkvGW8ZnxtfHa8Svyv/JG883zfvQ99ez1dvbO9iT3pfcq+ID44/iW+Uf61vpg++H7XPyi/KT8lPyR/Jv8h/x4/Jr81fwd/U39af2Q/ar9nv2P/Xv9Q/0V/f78yPxn/Bj8BPz7+6z7Dftx+kT6WPo9+t35iPmE+a35svmB+RH5bvjp95r3U/cF98z22/Y89873T/iA+GD42Pcj96z2f/ZU9g72/PVn9kX3HPiE+HX4MvjY92n3+/aq9qn25PZu90f4JPnU+Sn6HvrV+YP5K/m++F34NPhS+Mf4fvkV+mD6avpW+jP6Afqr+UL5FvlB+ZX57vlF+pn60frA+pf6ffpO+uf5UfkQ+zoC2Qy2F0UijS0pOrdFsEukSm5F3j5fN/ouiCc2I7IiWyUwKnMw9jYLPDk/PELkRvJMUFPEWR9hjWn/cAt1tnQYcONnIl0XUQFFDjraMMwpTyW2IsQgux6HHGgaFBhBFUYSoQ+GDW4LzgizBXMCFf8E+y32O/Fp7H/nUeLB3CfXv9EbzEbGEsEWvWu6zLj7t1m4HbqvvGG/DsIOxbTI48w20aHVVNoL3zzjpeZQ6Uzrc+zb7Antl+3M7pLw/PI29g36NP5dAncGtQr+DiQTPhdbG1sfICOOJlopWit4LKUs+SuvKgApGScwJWgj1CFtIA0fgB2dG38ZTxfzFHsS+A+YDawLEwqNCPgGFAXfAkUAH/2p+RT2mPJx74fs2emy5wrmaOSV4pbgiN6y3AfbeNlS2KjXZNe515DYjtlu2h7b2dvN3Nzdzt6s37XgC+KY4w3lXOa35yLpoupG7O3th+8c8cryuPSh9kX40PmL+339ZP8ZAawCTQTcBdkGSQelBwAIVAifCMQIEwm0CU0KqQq2ClAKkwmlCLMHwwa7BdAEQwQJBOgDnAP6AjUCWwE3ANv+gf1D/AD73/kL+Un4ivfK9uX1CPVB9EXzOvJs8dTwXvAK8OTv5u8B8CnwPvAw8AXwzu+d75PvmO+a77Xv+++K8Ezx/vGC8uTyQvPH81j0r/Tk9D311fWg9nP3JfjJ+H/5HfqH+tT6Avsd+xX7Eftj+/f7o/ww/aP9FP5V/lz+Pf79/ar9VP0a/S79aP14/WP9VP1B/QT9oPwu/Oj7wfuB+2H7hft6+wf7i/o++h/6+fmM+ez4n/i4+Kj4S/jX92/3NvdB90v3P/c89yb3Gfc69073Fvev9nD2fvbN9gr3CfcU90X3cPdq91v3YPdX90v3ave59xX4Mfjr98D3A/hR+Ef4HvhG+Ln4Rfmo+b351/kK+gP6u/mU+bf51/m7+aH5t/nv+ff5nflA+Tn5avmC+YP5sfkI+mf6nPp2+mT6q/3IBS8QxBpoJfYwez35R0xMA0paRKE9MTZ9LhYo4CSJJRQpWy5+NCE6BT6gQN9DBEmcT5ZW4F0KZpNubHU5eB92o2/xZZZa407KQxU6XDLyLIwpJyesJIghBR6eGl4XPxRlEQ0PQg2wC6oJuwYKA6D+qvl29BXvzOnb5BzgN9sJ1orQv8oCxdO/t7vbuPG2F7aktpW4artPvu/A0sNwx4bLrs/A0wPYgdyi4B7k++YK6TDquepT63/sJO4M8FjyefWT+Q3+SAI7BlwK6Q59E8MX3hvpH7Uj/iZqKeIqqSvNKz4rJSrEKF8nNSYcJaUjtyHBH/8dOhwmGskXdBWJEx4SoxCoDngMPgrTBx8FEwLr/sD7rvja9U3z6fBo7r3rF+mR5iHkveF134Td5duC2pLZMdkW2djYd9hg2LLYLNmc2SvaG9uE3AvecN/n4G3ix+PZ5OblIudk6IXprupE7C3uHPAJ8h/0cfaU+Fr6F/z//fX/jgG/AtUD8gQdBi4HAgipCCkJewnhCWIKegoMCoUJRAlOCTYJqQgECLMHlAdYB+gGMQZSBVcEKAP7Af4AAQDR/pX9ifzH+xX7Kvrw+Lj3wfbS9bz0sPP48mry4vFh8QPx/PAf8erwUfDb77Lvs++v72nv++7X7jHv2u9W8HXwj/D+8M/xk/Lg8uXyAPNq8yb09vSa9Rj2nPZL9y34Afl2+Zv5yPk7+sT6KfuI+/b7bvzc/Cn9Vf1k/Wr9Y/1g/Xb9if2V/Zf9nf28/bL9a/09/Ub9af14/Vn9Lf0b/Qf9p/zw+yP7k/o1+tH5avkW+QH5Nflh+Uv5DPmt+EL4BPj79+f3ifc39zv3l/fz98D3Uvc292L3T/fE9iv22/XQ9dX15/VE9uH2Wfeg9wP4gfin+FD4xPd093r3lPe09/L3dPgZ+YD5q/nO+dL5dvnm+KD4x/gF+R75Iflg+e35Wvpx+ln6Vvpa+j/6GfoX+ib6F/rl+cH52vkP+in6Ifox/PwCuwy1FoIg2SpbNhhBHkf1RhBD5j3QNxYxECtVJ7Um1ijDLL8x7DbqOps9lEAgRRBLgFE7WNFfDmgjb+tyZnL0bXlm0VwBUk9H3T0jNi0w4SvUKCkmJiOzHyQcwBiiFbMS8w/NDSwMOApvB+YDx/9P+5/2ofGN7NLnUuOc3pzZRdS0zjPJD8TBv5W8krqXuaq567rtvBa/N8GJw1TGrMluzXrR2dV32ubepOKc5efnXekH6njqVuvU7NLuVfGA9GP4sPzeALIEbAhIDDYQBBStF3MbRx/SIsgl+ydwKSQqESpbKU4o/SaIJTwk7SJmIb8fGh52HK8aqBhpFkYUfhLdEB4PPg09C+oIaQbVAxkBN/4Q+9H39fST8lXw3O0267zofeZv5HLiWeBH3pLcadvB2lHaydlI2TnZzNma2jbbrdtV3HfdzN7f38jg0eHn4hDkYOXM5lLo2elF67bsYO4g8LDxDfN39ET2T/hO+kH8Nv4iAPIBegOoBJsFWQb0BoIHIgjPCGUJ0gkQCjEKMQrdCTsJiQjtB2EH6waTBmIGWwY9BtkFIQVDBFcDRgIQAcv/nf6K/Y/8lfuK+pT5p/iJ90P2PPWc9Bf0h/MA87vypvJd8r7xEfGZ8ELw6u947zXvae++79zv6u8t8I7w4vAn8V/xufE38qTyDPOD8wT0dvTD9C/13vWF9hf3ovct+Mj4N/l3+cb5OPrI+lD7wvtE/OD8X/2k/cP9wf2q/X39Qv0Z/Sj9VP2A/bn95v0H/ij+Gf7M/Wn9Gf3h/Kz8bfwS/NH73/vU+3P74vpj+hP6wvlY+fj4yvjP+OH45PjZ+KP4SPgQ+BL4+/ex91n3IvdE92j3Kfe99pP2lvaR9o/2l/ay9t/2JPd198X39Pfr99r36Pcf+Cz4/Pfx9w34PPhj+Gj4gPjC+A35UvmG+aT5tPm7+bn5wPnD+cz56fnx+fb5Bvok+mH6kfqD+lr6WfqC+qf6m/pw+m76efqw+xUB0Ql9E0Uddie3MsM94USoRf1B1jwJN4AwJyr0JSMldyeYK2kwbTWAOeM71D0VQQpGBEylUi1ao2Kiar5vinBFbaZmal24UttH+z3pNc4vVisaKIol4SLVH4IcJhnXFccSZxCLDuQMDwuTCJAFHQIF/lr5b/R875bqvOXU4Mnbetbm0GLLbcZYwi2/Bb30u/e747xvvlTAdMLaxIrHgcrnzcLRztXR2ZDd7ODJ4/Xla+dv6Gfpoeo07CPufPBW88b2f/oc/sEBpQWxCb8NshGKFWkZHh1QIOoi+CRoJiEnOyfoJlUmmyWrJHcjIiLZIKQfNx6IHMMa7hg0F3YVgBNwEXcPkg2tC7UJjgc7BdsCSgBp/Yb6uffO9Mnx/O6P7Gjqf+iH5m3ko+I24dzfcd4W3Qbcedtw24zbmNvB2zHc49yg3UDe2t6I33ngseH04knkleXl5lDorukr69bsc+7072zx6fKY9Gb2CfiG+RX7z/yo/nEA/AFpA7sE0AWnBlAHzAcoCG8IqwgHCXoJvgmiCU8JEQnqCKYIIwhvB8AGWQYZBowFwgTzAygDbgKmAbUApP+r/sL90Pzg+8j6ffk5+EL3jvbq9Tj1efTW83zzQvPW8jXyivEP8cTwhvBc8D/wH/AS8DDwZvCk8OHw+PAo8Z3xCfJa8rbyQ/PB8yT0hvTz9I/1MfaZ9sj2A/eA9zX4w/go+az5UvoM+8n7XPy4/Of89vwU/Ur9df18/Xj9l/3W/S3+bP5q/j/+Bv7P/bX9t/2b/VH9Jf0q/Uv9Uf0D/ZT8Pfzc+1/7APu2+nT6M/r1+ev5BfoK+rz5Tvn5+Lf4cPga+Mz3lfd193X3nfe/98P3r/d29zn3Gffp9rT2pfas9uv2Vfe+9xf4YviU+Jz4e/gt+L73cvdv94/3w/ci+KP4OPnH+Rz6PPor+vP5svl1+U/5Tflz+dD5Rfqm+v/6Pvsz+/L6qvpZ+h76CPrp+eP5Hvpp+rv6Cv18A1sMjRXMHr0o3zMFPlJD5kJPP446xTQHLsgnGSSzI8clVCm/LUwy2DU1OKQ6oD5KRKNKZ1E0Wchha2npbQ9uGmrzYoJZqU6mQ8Q5pjFtK/AmxCM7Ib8e+xvuGAYWfBNFEWQP3g2aDEULYgmdBu0Cjf62+ZD0O+8A6vbk5t+j2irVvc+syhnGLcIuv1a9trwdvTC+sb+OwYfDpcUeyPrKXc4w0izWRtpj3vDhiuRE5mjnQujx6Jnpp+qD7BXvJvJ49f/4tvxMAMkDWQc/C18PehOGF4YbYB+MIsQkEia+JuQmeyazJbQktiOwIpohbiD5HikdFRsLGT8XoBUEFIYSbBFzEEIPuQ2tCzQJkAbGA+4AMP6K+/34ivZB9Ajyiu+87M/pFefO5ODiPuH03xvfoN5Q3vbdfd0d3dvcqdy13Cbd+90E3yjgP+FM4mfjX+Qd5drlz+bk5wvpa+r065HtOO/b8IPyUPQ39vH3oPmH+3/9Rf+8APUBGAMdBOgElgVVBiAHxAc0CLYIOwmBCY4JcgliCU4JHAnZCKEIcAgGCEcHZga1Bf0ECAQcA3cC/QFwAccABAAV/+H9ifw8+xn6FPn99xP3tvaI9hb2S/Vb9IjztPLj8T/x2fDB8PHwH/FX8azx0PGi8Ufx7/DD8NzwD/FU8c/xY/L88m7zufP78yv0ZvTM9F/1HPbQ9mf3Bfiy+EX5q/n2+Ub6qfoH+4j7MvzF/B39M/1X/ZD9sv2T/Wz9l/3h/Qf+Av4Q/jj+J/7S/ZX9rf3i/db9kv2E/cH90/1o/dD8SfzT+1X7x/po+mD6Y/o0+ib6Vvps+i36tPk0+ej4s/hC+MH3j/ex9+z3Hvg0+ET4Ufgd+L73jfde9xz35fa49vH2mvcc+D/4Q/hm+Kr4wvh4+Ar4zvfo9zP4hfjM+Aj5Tvmt+QP6Mfou+vL5ovmi+dL55/ns+QH6Sfqm+ur6//r5+vn64vqh+nT6cfpq+lv6cPqq/DcDMgxaFZweuCi9M3s9pkJQQpw+hzlRM2MsbCbUIushcSPcJn8rEjBNM081uTffO49B5kf5TktXNWANaNhsfW37ad1iMFk7TjBDATlVMH8pgCT/IDkemBvhGCgW0hMSEsIQ1g8SDzsOGw07C2sIvgRcAIb7cvY88SLsSudi4vLc69a90PXK78WTwRO+6LtRuwy8i71vv6PBCcSOxjvJDcwnz5nSP9YJ2r7dCeG/45/ltOZR567nJOj36AHqgOvg7QXxs/SI+G/8qAA9Bc8JBQ4bEk8WWBrPHZcg1iKoJLYl3CVyJdkkHiT1IoUhLyAWHxMevBwHG3AZIBjBFiYVixMyEhcR7A+KDhUNkQurCVEHtgTcAev+0Pt9+Hr17/Jw8OvtneuQ6abn1eUa5I3iR+Ei4Bvfhd5Z3k3eSN5W3rjeWd/Y3xfgV+D34MnhlOJU4w/k7+QK5mXn2ugv6mzr0+x07gjwmvEp86b0R/YU+AX67vuf/RT/fwAYApcDjgQpBc4FhgY1B6EH4QdECM4IIAkfCRwJLgkpCfgIqwhjCCgI1QdWB+cGlAb8BRAFHQRJA48CqAFoADL/W/65/df8nPts+oT5xfgC+DX3evb29aD1RvXH9Cj0bPOn8vDxPfGn8GrwjPDn8GDx2vEh8knyRPL68aXxcvFj8X7x6PG48sLzvvRd9aL18PUy9j32H/YP9oP2hfeZ+Iv5efpV+/P7QPw7/CH8Lfw2/C38e/wi/cP9Nv5f/jz+Bf7I/XT9O/1Q/Y79z/09/tf+Q/82/8H+K/6S/f/8ZvzS+4X7nPvq+x/8Ffy5+xr7fPoQ+qz5RPnx+Mv4IPnJ+Sr66flh+fb4jPjj9yD3tvbS9j33qPf692L4sPii+Df4yfeU93v3WPcu90/32vd1+KL4Wfgd+C74UPhL+D34i/gz+cT5CPoh+kL6Ufoo+vD5yvnG+QH6RPpH+lj6fPp5+lb6Jvr7+Qz6W/qt+hH7ePvl+/L+1wU9DqYWex9dKd0zjzxoQD4/rDsJN/IwIyqpJL4hfiFSI4MmqSrGLqcxrTOaNlk7ZkEhSMRPg1hyYXBox2sja81mUF91VadKZEBSN6gvmSkbJcshBB8kHBIZThYpFIASYxH6ENsQgBB3D5EN6gpfB9cCn/1a+HTzmO5N6ZTj691P2G3SlsxdxyXDM8CCvvC9gL7cv3jBNcMaxSvHf8lWzLDPcNOJ157bQt9F4l7kXeWP5WPlHOUV5bTlJ+dm6UfskO8l89n2fvoJ/pMBkgUxCgEPshMgGDscxB9YIrojCSSjI8simSFnIG0fqx79HSIdPxxKGyoa5xhqF/4V9RQiFEYTSxIwEeAPYQ6TDEgKvAdDBbwCEQCI/QH7afjE9Rbza/Dm7abreOl+5wvm++QI5CDjLuJL4ZzgF+CW30zfe9/m33vgS+FC4jDj7eNl5LvkReXp5W3m5Oa75xnpleoM7IDtBu/E8G7y4fNn9Rf30Phx+vb7m/1c/+QAKQI3AxsE4QRxBbYF6wU4BpUG/wZvB+sHVAiVCL4IwwiGCAEIbQf1BmcG2gWLBVAFFAWoBOYDFwNtAp8BdgAs/x7+Uf2a/OX7JPtl+pP5gvhk94z21PUD9S30pvOi88PztfN/803zNfMO863yNvL08dTxyPHY8fvxP/Jv8mjya/Kq8hzzjPPf80H07/TU9YL2uPbZ9jL3kPfk9xz4Tvjf+Kz5bPoJ+3z71fsd/GD8lPzC/PX8Gv1Y/bX96f3g/b79l/14/Wr9df2F/ZT9tf3X/fb9Fv4P/qb9MP3y/LX8ZPwR/Oz74PvD+4H7IvvX+o/6Rfr6+cX5u/mo+YP5avlo+VP5CPmr+FT4Dfjb97b3pPer99/3H/hB+FH4Q/gn+B/4H/gY+Pv35fcN+Fn4n/jD+N/4/Pjx+Nj4rPiE+JL4tvjT+AX5Xfm5+RP6Vvps+nf6hfqL+pz6w/rC+r761vro+uP6ofpG+g76GvpG+nX6HP3ZA1EMmBTmHPQlqC+/NzM7ADrLNgkzbC43KQAlByNDI/ckdyeJKoYtdS+fML4yJjdXPUFEzktRVDddjWRAaNxnA2ReXbRUGUu2QWs5njJFLVApYSbCI94grx2hGgIY2RUgFA8ToRJlEuQRuBCsDsML+QdQAx3+p/gF81rt1+dp4vXcj9ds0ufNRMp3xznFucMcwzjDCMQtxV7GBMhxymbNjtDQ0yrXjtqz3SfgxeHH4lbjdON048rjnuTn5Zznw+lu7LDvLvOS9gf6x/3QAeYF+AkODgwS2hUpGbQbth0zH/Ef+h97H7Eewh25HLYbwhrvGTAZdBjGFw8XGBb5FAMUDRP/EdoQmg90Dl0N7wsHCt0HlAUSA00Af/3P+lz4Fvbb89Px/+8b7hPsH+pk6NrmfuV45NfjaOMk4w7jBuMj4zrjGuME4yjjjOMb5M/kfuUY5tDmlec36LLoMukB6inrnuwo7pHvHPHr8sT0UfaF95r43Pk7+5L83f0a/2cAqAGLAiADnwMBBFcEuQQSBZQFQwbABhUHZAeAB0UHwQY9BtkFegUpBfIE2QTkBL0EFQQ1A08CUAFEAED/Sv6K/RX9wPxY/ND7IftP+mb5Zvhs94r2zvVX9RX19fTQ9JT0S/QD9MLzYvPj8n3ybvKx8vzyFPMZ82Dz2vMa9Af07fMK9Ff0mPSz9OP0YvUE9mP2mfb39nj3BviI+AH5g/kV+qD6+/pZ+8X79vvo+/D7K/xj/Hn8hvyk/Pn8Vv1w/Wf9Yf1s/XH9bv1q/Xr9mP2f/a/9zf3O/Y39GP2S/Cf80vtk+yb7NPtb+3j7cPtm+1T7+fpf+sf5Xvkt+QX53fjp+D35hfl0+TX5E/nx+Ln4e/gy+Az4IPhU+HX4Zvgj+N334fcJ+A749/cU+Iz4DflK+UP5OvlV+U35F/n8+Bf5Tfl3+Zb5xPkR+in69PnM+c753fkB+iP6V/rI+hj7Jfsy+zz7OPv++pv6Z/qR+k/9dgPrCoASdBoOI/orMTMiNv40BDJvLjgqxCVXIvcgyiEXJAEnFCrILIYusC++MYk13TozQV9IZlCiWGNf5mKVYsxefFi7UEVI+D/MODUzKC9SLB4q9iePJboicR9UHP4ZZxhJF3cW2xVEFU4UURIeDxgLjQayAcb86ffx8vztIuku5DHfRtqD1UbR2M1Ny7fJHck4ybTJbspuy9/MtM600MTSDdXA16DaOt0z34Pgb+H24Qzi5+Hy4X/io+Ne5ZvnOOoG7fjvHPN79hf6qP0wAQQFBgnUDDEQFBNnFSIXRBjTGB4ZTRkaGaEYcxh/GEMYhxenFgsWlxX7FEAUpxNBE8YSAhIWETAQHA94DaEL/QlnCKUGlARuAo4A0f6r/CX6v/er9abzr/EA8IDuG+3Y66nqk+my6O3nMeem5nnmdOZx5nrmk+bF5gbnNudL52vnyedV6NvobekE6pHqKevc66rsne3Y7jvwtPFo8yX1rPYD+Bj5DPr/+sr7ivxh/UL+Q/9bAEoB9QF0AsoC7wIcA14DiwPTA18E1QQSBVkFjgVwBREFjgQLBJ0DRgPbAmICDQKmARoBhgDP/w//Y/64/Sr9x/xW/M/7Rfui+vf5Rvlw+Kb3/fZy9ib2E/YI9uT1r/V79Wr1WvUa9br0cfRw9Jz0ufS99Mb06PQG9fj0APUo9Uv1X/WO9f31iPYQ9133qfdS+AL5Yvme+QD6avqT+ob6ePqV+sH6zPrW+hT7ivsP/Gr8rfzz/AL97/z2/AT9/Pzj/PP8R/2b/bX9hf0v/eX8ofxQ/Pv7xPuz+8f79vst/Eb8JPzB+1D7D/vU+of6Rvo4+lT6evp8+lP6FPqz+Uj5/Pjy+Af5AvkS+VL5pPnO+aD5O/ns+NL4u/iV+JL4wfj9+Dv5aflr+U/5Dvnl+Av5Qvlh+Y354flC+o/6lPpX+hv6Avr3+fn5DPoi+kH6ZfqV+tL67Pqu+m/6f/rK+iH7Mvv++vn6JftA+079jQL+CHoPcBYLHvoleiwKL9ktWCueKEkloSEKH34e6R94IjMlqCdlKSYqnCoxLIkvaTRwOnVBmknRUQFYzVoaWpRWF1EtSphCsjtZNqEyFzAoLl8sSyqyJ3kkBSHzHYsb/xlAGRYZIBnLGJ0XXhUbEvsNTgl6BOL/s/vJ9wX0RvBA7OTnduP+3p7a19bv0/7R89Bv0EfQmdBL0RDSwdKd0xnVH9dM2YDbrN2030zhMeJf4i7i/eHe4f/hv+JO5GDmkujw6oztUPAU8771gfik+yD/qAISBlUJUAzBDokQsBE/EpoSBxNfE7sTGxRdFJwUqRRAFJcT4xIvEoMR9BCpEJ4QoxBjEMcPBg8GDqIM9AopCXcHAgamBEADzgE6AHz+k/yP+oL4mPbU9BDzg/Fm8Kbv/u4t7jXtS+zB62fr8up16hHqAepN6q3q3+rj6tTq4OoV61brn+vh6zDstuxw7VHuMu/y757wXvFV8n7zvPTW9fT2RviZ+cX6kvso/MT8Zv34/Wj++P6p/0kA4QB9Af0BRgJYAkwCXQKbAsQCswK+AhADawOFA0wD3gJ9AkMC4wFBAZEA/P+S/0P/5/53/g7+rv1M/eT8c/z7+2b7tvoA+mD54/hn+Ov3gvdR92H3bvdg9zb3APfp9sj2fPYh9uH10fXZ9dv13vUB9jX2VvZg9mr2jPa+9vf2MPd099X3L/h8+OP4UPmm+eH5+/kO+jX6ZPp5+nb6c/qc+v36XPuu+xb8hvzd/Bf9LP0Z/eT8qPyU/KP8r/ye/JL8yvw1/W/9Nf3S/JH8Wfwm/BH8/vvs+//7Ffw4/GP8NvzW+5v7avsk+8P6cPpO+lL6Zvpd+kP6QfpZ+mf6Yvpc+j/6HPoD+tP5gvlI+Ub5SflN+Xv5svng+Rz6OPok+g/69Pm++Yf5gvmi+cr5Bfpb+qf6wvqs+nb6Uvo8+hH67/kL+l/6s/oS+277qfvU+9H7fvsJ+7P6i/qI+pH6m/rC+gv7FvwCAKoFCgtwEHoWJR1qIy8nqCc/Jm0kMiJtHxAdDxx+HPId7R8QIs4jpSTkJLUlMyhLLDUx2TaUPfpEW0sWT9BPDU5QSiVFVD+9OT81+DF0L5EtGyxNKscnoiRVIYAeNxx0GnMZPRltGUoZVRiDFu0TqhDqDBQJZgXzAcT+u/uh+CD1MPHf7HLoP+Rh4Dnd8dpi2XHY8dey15HXjdeR183XotgC2rzbq93C38DhReMc5ErkEOSr42TjTeON44zkH+bt59zp0+u/7bLvxfHo8yn22fjx+z//eQJSBcYHzwl5C6kMVw21DQgOgA4KD40P7Q8XECcQLBATENEPbw8YD+YOyw6oDm4OBA5xDcIM9gsWCwsK5gjMB8sGywWiBEcD2gF1AOz+LP1r++P5i/hT9yf2DvUf9E/zjPKw8bTw4O9J78juaO477jjuTe517p7utO7H7snuse6n7r3u2O7y7invm+8v8MTwS/Hf8bjyrvN/9EL1Hfb29sD3gvge+cL5lfp/+2D8Hv3B/Ub+vv4I/xv/Jv9L/5r/6v9BANEAbgH9AV4CSwIEAsIBbAEPAbkAlAClAKoApwC1AKwAhwAnAH7/3v5o/vj9df34/KP8cfwy/MT7U/sM+8n6a/r6+Yr5UPlF+SX51fiT+JT4sviy+Iv4YvhK+Cn45PeM91v3YfdK9x/3LveE9wL4UfiG+OP4W/nN+d75pfmY+cT50fmi+YL5tfkp+oL6s/rt+lX7uPu3+5j7qfvg+x78O/xl/MD8Hv04/Rb9BP0K/fP8vfyC/Gz8gPyD/Gr8ZvyO/KX8mvyk/ML86vz9/NP8sPyX/FH84/uB+2j7evt1+137ZvuG+4H7U/sV++T6yfqp+p/60voD+wL7/voY+yX7zfpA+u/5Afo5+k36V/qW+vz6KPsE+9X6xPqu+nv6T/pb+qv6Bfse+yf7T/tS+yD73/q++sP66fom+1j7lPvT+/r78/vO+637dfs8+zL7Vfub+9778/sC/CP8Yvyp/vgCXQfEC8YQVBbMG7cf8yA8IOkeLR0KGzsZjBgBGSMatxtzHesevh/WHxYgriHBJKIoOC3RMgQ5pT6DQgFEL0OnQAA9tjhsNOAwTy6BLBsruCkVKAgmdSN5IKAdWRvEGegYrRi6GL8YUhgEF9wUGRLqDpELYwiSBTID6wBg/pz7nPg39XTxle3P6ZbmJuRU4v3gLOCq3zzf69633pTesN5A3yrgauHo4lTkeeV25ifnPecK59/myubn5kXn5ufS6PLpJet/7B/u3e+k8Zvz2PVc+Pj6Yf2Z/6MBYQPSBBIGJwcHCMsIlQllCh0LjAvHC+8LBQz3C8MLsgvPC+cL8QsLDCcMFQyfC9EKJQq4CRsJOwh5B/sGrgY5BkEFGwQTA/gBuAB+/0P+E/0G/AT7FPo4+Tz4GvcQ9lj1zfRA9NTzt/Ow85Dza/M68//y0fKL8jTyG/JR8o3yq/K88sfy8/Ij8zDzRfNs873zTvQb9Qf24/aa9zH4zPhM+Y35yPkR+m769/qS+yr8zvxj/b79Hv6B/rD+vv7O/g3/ZP+0/+b/9f8oAEkAMQAwAEAASgBRADsACgDU/5P/Uv8q//3+uP5t/lj+gv6e/mn+9/2a/VL97fxY/Mr7Z/tA+1f7Yftd+0f7Cfvp+uP6rvpP+vn5uvmn+bv50fnu+Qz6B/r2+Qn6Gfr9+bX5Zflf+a357vn6+Rn6X/q8+hf7Ofsy+x379Pru+hT7SPt/+6r73fsb/Ef8afxo/Ej8PPxS/IP8wfz+/Bn9Iv0x/Tf9Jv3q/Kj8kPyc/Mr8A/0F/f/8LP04/SL9C/3u/Of8BP0g/SX9IP0T/fP8r/xX/PT7tvuk+7T70PvY++37HPxQ/HX8f/xb/Bb84vve+//7BPzB+4n7qvvu+/b7tftc+0r7jPub+1z7Ovtp+7776vvx+/77MvxY/DT86fvV+xL8Kvz++9X78fss/Db8Evzi++H7DvwX/Oz72/sL/E/8e/xq/Eb8S/xe/GT8b/yS/NH8qv4jApAF5wiXDI8QbxQ0FwQYvBdpF54WWBV6FFkUmxQkFfMV8xbwF3EYbxjOGGka9Rz8H6Ij1idCLDcw9jJSNE00ADOsMOotTCvcKKgm1yRWIxciyCAPHw8dHRtdGdEXoBbHFT8V9RSQFNMT0xKGEdIP2A26C4oJWwcwBQED2gCD/uP7Kfli9qXzG/G67qrsKevz6efoDuhh58vmc+Zz5qPmBueg51joT+lt6j3rsOv06/rr1+ul637rhuvn64bsQu0k7ibvMfAz8TXyR/Oc9DL24Pef+XD7Tv0F/3oArAGZAmYDKwTuBLwFkAZRB9AHIghGCDgIHAjwB6YHeAekB/kHSAiaCOMI+gjXCHwI8AdcB8cGEAZpBfQEpQRZBNwDNgOIAtcBBQERAOr+1/0P/XX85vta+9z6YvoH+rf5PvnE+Ff41Pdh9x735/az9qH2kPaZ9rr2tvav9rb2sPam9p32jPaS9s32CvdX98P3Gvhf+Lz4G/la+aP57vkc+lb6s/oi+6H7Dvxr/Nn8Lv1t/ZL9nf26/fL9I/41/lf+l/7e/iD/Qv84/yb/C//x/t3+0v7w/gD//P4l/2n/cf86/9/+i/5j/j3+/v21/Zb9nf21/bP9kf1Z/fz8nvxz/H78hvxw/GL8dPyJ/Ij8Ufz4+7z7l/tv+1H7S/te+4r7qPvH+/P79PvD+6b7uvvK+9r77vvt+/H7+vvz++/7+fsF/B78Sfxv/Kb83fwE/SP9Iv0M/fr89Pz//BD9Lf1B/Ub9Tf00/Q39B/0I/Qv9Q/2c/eP9H/4w/hj+FP79/aP9NP3o/ND83/wR/U39fv2d/Y/9c/1d/UP9M/0M/ev8+/wi/Vj9eP1b/Tn9Kf39/LP8c/xq/Jf8zfzx/AL9D/0W/Qb90/yQ/Fb8Lfwt/GD8s/wN/Uz9af1v/VL9Bf2d/E/8QPxk/K78Bf1T/ZP9tP2d/UH9zvxr/Bj8B/xG/Kz8MP2x/QD+MP4q/tT9Yv3+/Mn8qvyZ/NT8RP2U/br9nP7ZACwDJAU6B68JaQyoDp8Pmg+gD6cPMQ+RDmIOxA5gD+IPJRBxEMYQshCbEFER5hIUFbAXkxqNHVIgZCJ6I5Uj1yJ3IdIfWx4oHSscVxuWGsMZrhg5F4EV0BNLEgQRJhC9D6IPog+kD3sP7A7TDS8MbwrfCH8HJgbVBK0DpwJ6AfL/Jv4g/P35+/cp9pD0YvNs8pbxKPHm8HDw1e9q70bvV++W7+3vaPAP8bHxEfJO8nzyePJg8lrya/Ki8tHyBPN18w30f/Tg9Gv1K/Yc9w/4F/lW+q370Py5/aD+Xv/3/4EA/gCOASgCsQI4A9YDTAR3BJcEqASSBGwEUgRHBGIEowTUBPoEGQUJBc0EmQRaBOYDgANIAysDHgP2AqECVwIhAroBIgF5ANT/Pv/J/nL+Ef60/Xn9M/3U/IP8NPzg+5f7W/sr+xD7//rn+sr6ufq1+pD6Vfom+gX6D/oz+j/6T/qM+r/61Prc+tL6z/rW+tP68vo/+5H74/sy/IL8vPzI/K78jPyL/KX8x/wE/Wf92/1A/nf+gv5z/kf+HP76/db90v3w/Tv+pv7x/gv/FP8D/9j+of5f/jX+MP4k/iP+Uv58/n/+a/5J/if+Df7n/cL9sf26/cf9zf3a/eL9zP2e/Yv9h/1r/UH9I/0i/Sz9Mf0a/RH9Mv0//UH9Rv1P/Wb9gf2J/Xn9X/1T/VX9Z/1i/Uj9Q/1c/Xz9fv16/X79mP2n/aH9r/3e/f/96v3R/dT93v3c/dH91/3z/ST+R/4y/h7+IP4V/uj9y/3P/eD9+v0Q/jn+av58/mL+If7n/cv9rf2P/Yv9tv3u/Sf+Wf5q/mD+Q/4P/tD9nP2S/aT9qf3P/Rf+Nv47/jL+C/7S/aH9d/1d/WP9ef2o/dn9/v0O/hX+FP75/dr9xv3D/c/97P3+/Qj+BP4B/gT+4v2x/Z39rv3X/Qn+IP4d/iT+K/4T/t79rP2N/aL91P0G/jH+VP5s/nX+Yv4s/ur9yP3G/df9/f07/nP+mP6n/yEBIgInA38EDAapB80IPAmECeUJBArZCaAJkQnGCQ0KOAplCq0K2wr9ClgLFQwrDX0O4A9REfUSexSAFf8VGBbhFXEVxhT8EzYTghLrEU4RoRDuDxgPNw53DckMHQyJCwYLlgpOCgsKuAlCCbgIHAhlB50GugXRBO8D+ALqAfIA+v/m/sv9rPy2+8765/kH+UD4n/cf97f2V/Yg9hD2E/Yo9lj2lfbD9uv2A/cT9xv3EfcY9zH3Tvdt95337PdB+Hj4lvjB+AT5YfnB+SH6n/pT+xb8zfxw/fn9b/7k/lj/t/8JAE4AoAAFAWkBvgHzARwCOwJNAlYCYAJiAlUCVgJkAn0CjgKTAnUCVQJMAkUCOAIYAugBxQG7AaQBewFBAf0AxACDADoAAwDh/7n/jP9f/zH/+f63/ln++P3H/aX9eP1m/WD9Vv1f/WL9T/03/Rf9/fzo/Nr82/za/On8F/0x/Sf9Fv3//OL82fzO/Mj85vwJ/Sr9W/2W/cT9yv22/bX9yP3Q/cX9tP3O/Rf+TP5d/lv+bP53/nH+cv5w/mv+Zf5q/oP+qv7A/q3+n/65/tP+y/6c/nL+bf52/nr+Y/5P/mT+jP6y/tv+7v7W/sH+s/6N/mL+Qv4c/hr+Ov5R/mn+hP6A/mz+WP5A/iP+Ff4e/i3+Sv5o/oD+nf61/rX+n/57/mX+W/5R/lf+Wv5X/lH+Vf5a/l3+b/6H/p3+o/6l/qH+q/7E/r7+o/6I/oz+rv7G/sL+uf7E/sT+rv6d/oz+d/5t/nr+lv69/s7+xP7K/t3+7P7c/rj+nf6P/pT+j/6N/pf+ov6v/rL+vv7Q/tH+rv6N/nj+af5m/l7+bf6S/rP+yf7U/tD+wv6y/pb+d/5m/mT+ev6s/tn+5v7i/tX+tf6K/mn+Tv47/jz+Uf55/qD+zv7y/vf+7/7X/sX+rf6g/qT+p/6l/q3+tf6+/sb+tf6l/qD+kv6L/p3+s/6x/rL+yf7b/uz+9P7d/sr+0P7J/rL+yf6V/3gALgEEAucC2wO3BCYFQQVuBZEFfAVoBYcFyQUQBkAGWQaFBqkGsga5BvoGdwcXCNsIqAmOCm0LJwypDPQMAA3NDI4MRgzrC5ULQAvlCpMKOQrNCVEJ0AhSCNkHewcsB+EGoAZkBiwG6gWhBTwFvwRSBOIDYAPaAlQC0AFXAdMAOACT/+j+N/6C/eP8WPzc+2z7EPvX+rP6jfpk+j76IvoW+hH6Ffoo+kX6ZvqR+rv62Prm+uL61/rV+tb61/ri+gf7P/uF+9P7Cvw9/H38yPwS/WD9r/0F/mf+0P45/4X/wv/5/ycAVwCBAJYArwDXAP8AIQEsATcBQQFKAVEBUQFKAUUBTwFgAXQBeAFzAW4BawFpAVkBRAEvARYB9wDSALAAmgCBAGkASwAWAO3/0f+3/5D/Xv8x/xX/Av/9/vj+6/7s/uf+1v7K/rD+e/5Z/lj+V/5K/kf+Sv5Y/mr+Zf5S/kD+KP4N/vP9+v0Z/jD+R/5h/oj+pP6n/pP+dP5l/lr+U/5W/nb+kv6m/sv+3/7m/uT+0f7B/r/+wP7H/tj+5f7y/gT/D/8J///+9v7k/uX+7v7q/vf+Dv8S/xb/JP8l/yP/IP8H///+D/8b/w3/7f7d/uL+9/76/vf+/v4X/yf/K/8o/yP/I/8Z/w//B/8K/wr/Cv8V/yf/K/8Y//7+9f7+/gz/Cv8K/xj/Mf9D/0X/Qv87/zL/Jf8W/xb/KP8q/y7/Pf8//zj/NP8p/yX/MP8q/xr/G/80/z//OP8u/x7/Jf82/zb/IP8W/yv/Ov9B/0D/Nv8w/yv/Lv8x/yf/IP8j/yr/MP8r/x//Gv8g/yj/IP8g/xz/F/8b/xv/I/8o/zD/PP9I/0r/Pf81/zH/MP8r/xv/Dv8U/yX/MP81/zb/Mv8w/y7/Kf8k/xv/Hf8o/zT/Qf9Y/1z/XP9d/1L/Pv8o/yH/Ev8M/xj/KP82/0X/UP9P/07/Tf9I/0X/Mv8o/zX/Qv9J/1H/TP9F/0X/Rv9L/63/KQB0ANMARAHJAT0CewKVAq4C3QLyAvIC/QIhA0UDYQN2A4IDlgOcA7YD8AMzBIEE2QQ7BaMFBgZQBowGvAbQBsoGtgajBocGXwYxBgAGzgWjBW4FNAX/BMgEkARjBC4E7QO2A34DSQMcA+gCsAKEAk4CIQL4AbIBZAERAbgAXgAPAL3/ZP8S/8z+jv5N/gD+sP1w/UD9Ev3g/Lf8o/yn/LX8wvzN/Nr85vzt/Oz86vzr/Ov85/zx/Af9Gf01/T/9Sv1j/XL9gP2Q/af9zv0H/jz+c/6o/uL+Ev8x/1T/c/+R/6f/w//j/wYAMABPAGEAbQB8AIYAhwCNAJQAnAClALMAvwDIAMkAwwC5AKoAqQCnAKYApQCqAK8ArgCnAJgAgQBkAE0AOwAwABoABwABAAMA/P/r/8j/qP+R/3//df9r/2X/Xf9j/2z/bv9k/1P/Q/83/yX/F/8N/wb/DP8P/wn/Ef8a/xH/B/8J/wz/Bf/8/vH+8f75/gj/Cf8K/xn/Gv8h/yT/Iv8r/y7/Iv8e/yX/L/84/z3/Qv9D/z//N/84/0L/Q/9F/0X/UP9j/2v/Zf9f/2f/af9W/1D/WP9Z/2L/Y/9j/3P/gP94/2r/af9v/27/bf9r/27/gP+N/4z/if+H/3b/av9r/27/c/93/3f/g/+W/5T/i/+F/3//d/9v/2//ef+K/5f/lP+V/5//nf+J/3//ev93/3z/hP+K/5H/lv+T/4//h/+C/3T/cf91/4H/i/+Q/5X/lv+X/5D/iP9//3v/eP98/4P/hP+D/4j/iP+G/4T/gP98/4T/gP95/3z/f/+B/3//hv+H/4H/fP9+/4P/hP9//3X/ef+B/4T/hv+J/4j/jv+U/4v/gv+B/4P/ff9z/3D/ef+H/43/i/+P/5L/kf+U/43/ff92/33/hf+N/5P/lv+b/5z/lP+K/4j/if+A/3r/fP+F/5j/nP+Z/5f/mP+b/47/gP99/4D/if+X/5z/nf+k/6X/oP/M/xUAKwBSAI0A1AAhAVoBbgGHAagBtAG4AboBwgHLAdoB5wH5ARACJQI6AlcCfgKpAtMC/AIoA1kDiwOuA80D4QPpA+MD3wPTA7sDpQOKA24DVgM8Ax8DAQPiAskCqAKIAmoCRwIrAhAC9AHVAbIBlwF5AVwBPgEWAe4AyQCcAGsAOwAJANj/qP98/0z/Gv/0/tT+tP6S/nL+Wf5O/kX+PP44/jT+Nf43/j/+P/49/jr+Mv40/jr+O/47/j/+R/5R/mD+bf52/oL+kP6g/rX+zP7d/u7+DP8s/0j/Xv9s/3//k/+s/8H/y//b/+z//f8OABkAIwAqADEAPABCAEEARgBLAE8AUwBTAFcAXABgAF8AYQBiAFsAWQBaAFoAVwBTAEgAQwBFAD8AMwAiABgADgAEAP7/8//t/+r/4f/b/9z/2f/M/8L/u/+y/6v/pP+c/6D/ov+i/5//m/+X/5H/jP+E/3v/c/9v/23/cP90/3f/fP94/3b/cf9s/2v/av9t/3L/ef94/3f/ev+C/4L/ev92/3D/c/94/33/gf+D/4b/i/+K/4z/if+B/4H/if+M/4//lP+a/6D/pv+j/5r/mf+U/5H/lP+a/53/o/+r/63/rv+1/7n/sP+s/6r/rP+n/6P/qf+y/7v/v/+8/7v/wP++/7f/sf+y/7X/tP+w/6//uv/K/8v/w//E/8f/w/+8/7n/t/+7/7v/uP++/77/vf+//7z/uv+5/7T/tv+2/7b/uf+8/7v/uv+6/7v/vv+5/7n/t/+1/73/uv+y/6r/qf+r/63/q/+q/6//t/+8/7n/s/+1/7j/sf+s/6r/pP+r/7D/tv/A/7v/uv+1/7T/r/+r/6b/ov+v/7H/sP+5/8H/wP/D/7z/r/+x/67/p/+r/7T/t/+7/8P/yP/L/8b/vP+3/7L/sP+v/7L/sf+0/8P/yf/G/8f/xf+6/7X/tv+2/7v/wP/F/8b/xv/C/77/uP+5/7n/tf+8/73/wP/J//f/EwAfAEIAWwCBAJ0AswDDANEA5QDpAO8A9wAEAQUBEAEeASYBNAE9AUwBXgF7AZIBqQHFAd0B+gESAiUCLwI5AjoCOwI6AiwCJQIbAhMCCgIBAvgB6QHaAcgBuAGmAZQBgAFrAVwBTgFDATUBJAETAQEB8QDYAMEAqgCQAHwAXQBFACwAEAD3/9z/wv+o/4//ef9l/1j/Sf84/yv/Jf8e/xn/FP8P/w//Dv8M/wX/BP8E///+/f75/vj++f7//gL/A/8N/xL/Gf8k/y//NP87/0b/Uf9c/2v/df9//4r/lf+h/6z/tv+//8j/0P/b/+H/5//t//X/+v8AAAMACwAPABEAGAAdAB8AIAAeAB0AIAAjACYAJwAnAC0ALAArACoAKAAkACAAGQATABIAEAAPAAwABwAFAAMA/f/4//T/9//3//H/7f/m/+L/3v/W/9L/y//M/9H/z//R/87/yv/G/8H/uP+z/7H/r/+x/7T/uf+2/7X/tP+w/63/p/+j/6D/ov+h/6b/rf+v/7D/rv+s/67/rP+n/6j/pv+l/6z/q/+s/7H/sf+t/7H/tP+z/7H/r/+0/7b/uv+7/7r/vf+8/77/vf/A/8L/wf/C/7//wv/H/8r/yf/H/8n/yP/I/8v/zP/P/8//z//S/9T/0v/Q/9L/z//R/9X/1//W/9X/1P/S/9X/2P/U/9H/0//U/9n/2P/a/9j/2P/Z/9b/1//V/9P/0v/T/9P/z//O/9T/1f/V/9j/1v/V/9X/0v/T/9D/1f/T/87/zv/O/9D/zP/Q/8//zf/P/8z/0P/O/9H/0P/N/87/0P/Q/8z/0f/O/9D/0//P/8v/zv/N/8n/zv/N/83/zv/R/9T/0f/Q/87/zf/Q/87/zP/P/9L/0//V/9X/1P/W/9X/z//O/9H/0f/P/9D/0P/V/9X/1f/W/9T/1v/S/9L/0P/S/9f/1f/T/9L/2P/Y/9T/1P/W/9b/2P/Y/9X/1f/X/9n/1P/b//n/AAAQACcAPgBVAGUAcAB3AIQAiwCPAJgAnQClALAAswC6AL4AxwDNANMA3wDvAAMBEwEmATYBSQFYAWIBawFtAXABbgFpAWgBZQFiAVsBUwFTAUoBQwE5AS8BJQEYAQ8BBQH9APQA7gDlANsAzwDDALYAqACbAI8AgABzAGYAUwBEADMAIAAPAP//6v/f/9T/w/+5/67/pf+d/5L/jP+G/3//fP93/3T/cv9v/23/bP9o/2T/Yf9i/2X/Yf9e/2D/YP9l/2f/av9u/3T/ev99/4T/iv+P/5f/nf+k/6n/qf+y/7r/wv/G/83/0P/W/9v/3//k/+X/6f/t//T/9//4//3/AAABAAQABgADAAQACQAKAA0AEwASABMAFAATABQAEgANAAsACwAIAAgACAAIAAcACAAHAAIA/v/8//j/9f/z//n/+//3//T/8//w/+z/6f/j/+T/4f/c/9z/3//f/97/2P/X/9b/0//S/83/zP/S/9D/zv/K/8r/zP/N/8z/xv/H/8b/xf/F/8f/xv/I/8X/xv/G/8X/xP/F/8f/xv/H/8j/yP/J/83/yP/H/8v/yf/L/8v/zP/L/87/0f/R/9L/0v/U/9X/1P/X/9X/1f/T/9P/1f/W/9j/2P/d/9//3v/e/9//3//e/93/2//c/97/4f/j/+T/5f/i/+L/4//i/+H/3v/h/+D/5P/k/+P/5P/m/+n/4//l/+X/5P/j/+D/3//d/+D/4f/f/+X/5v/m/+b/4//k/9//4P/d/97/3//h/+P/4v/j/+H/4P/d/97/3P/b/93/3P/f/+D/4//j/+L/3v/f/9//3f/d/93/3v/d/9r/3P/c/9z/3v/h/+H/4f/i/97/3v/h/9//2//a/9v/3f/h/+H/4//h/+H/4v/f/97/2//f/+D/4P/g/+D/3//i/+L/5P/i/+H/4v/h/+T/4v/h/9//3f/e/9//4f/e/+L/4f/k/+f/5P/j/+H/4v/g/9//4v8AAAgADwAgACwAOgBDAEkATQBUAFkAXABmAG8AdgB8AH8AgwCFAIgAjQCUAJwApQCyAL8AzQDYAOAA6QDzAPYA+AD7APkA+AD3APUA8wDxAOwA6QDnAOAA1wDUAMwAyADDALsAtQCuAKkAoQCbAJIAjQCDAHsAdwBtAGUAWQBNAEQANgArAB8AFAAPAAMA+v/y/+n/4P/Y/87/yP/D/77/vP+1/7b/sv+t/6v/p/+l/6H/nP+c/53/m/+c/5v/nP+b/53/nf+f/5//nf+i/6P/pf+n/6v/sf+1/7n/vf/B/8X/x//I/8z/zf/S/9T/2f/g/+L/4//m/+j/6P/r/+r/6//y//T/9//4//n/+v/7/////f8AAP7/AQAAAAIABAACAAQAAAABAAIAAAD9//3//v/+////+//+/wAA/f/7//n/+v/4//X/8v/y//P/8f/u/+//7P/u/+v/6f/p/+n/6f/o/+j/5v/j/+D/4//g/93/2v/a/93/3f/d/9z/2v/c/9v/2v/W/9b/1//X/9j/2f/b/9b/1v/W/9b/1//T/9f/2P/Z/9f/1v/Y/9n/2f/Z/9j/2f/Y/9f/2v/c/9r/3f/d/97/3f/d/9//4P/c/+H/4f/h/+D/3f/j/+P/5P/i/+P/4//o/+X/5//m/+T/5v/m/+b/5//n/+f/5v/p/+r/5v/o/+r/6f/r/+r/7f/t/+v/6P/n/+j/6f/m/+r/6P/p/+r/6f/p/+f/6//q/+n/6v/q/+v/7P/r/+n/6f/l/+j/5v/m/+T/5v/p/+j/6f/q/+r/6f/p/+f/6P/l/+j/5f/k/+b/6P/m/+X/5//n/+n/5v/n/+b/6P/o/+b/5v/n/+f/5v/m/+b/5v/m/+j/5v/l/+b/5v/p/+b/5v/q/+f/6P/o/+j/5f/n/+T/5f/r/+f/6P/q/+f/6P/o/+v/5v/m/+j/5//n/+j/5v/n/+v/6v/s/+r/5//o/+z/5v/o/+b/6P/q//r/CgAFABgAIAAsADQAOQA9AEMASgBNAFIAVgBbAF8AZABoAGgAawBwAHMAewCDAIwAlQCbAKQArwC3ALoAvgC+AMIAwADAAMEAwwDDAL8AvgC5ALYArwCqAKYAogCfAJsAlwCUAI8AjACGAH4AegBzAGwAZwBhAFwAVgBPAEgAQgA7ADEAKAAhABUAEAAFAAAA/v/1//H/6P/n/+L/3f/Y/9T/0v/Q/83/y//L/8b/xP/C/8P/vv+//8D/vf++/7r/u/+7/77/vP+7/77/vf/D/8P/xP/F/8n/yf/M/8//0f/V/9P/2P/a/93/3P/c/+H/4v/k/+P/5//o/+r/7P/t/+//8P/v//D/8v/2//T/9f/2//j/+P/5//j/9//6//n/+f/6//r/+P/5//j/9//5//n/+v/6//j/9f/2//b/8//y//P/9P/z//P/8//x//H/7//t/+7/7v/t/+r/6f/q/+j/6f/n/+X/5//n/+j/5//m/+X/5P/k/9//5P/i/+L/4f/f/+H/3//f/97/3v/e/97/3//d/9//3//g/+D/4P/g/+D/3v/g/+D/3v/e/93/3//f/+T/4P/h/+L/4P/g/+P/4P/i/+X/4v/l/+b/5f/k/+b/5v/m/+f/5//m/+j/6f/m/+n/6v/p/+f/6P/q/+v/6v/p/+j/6//r/+z/7P/t/+7/7v/s/+z/7v/p/+v/6v/r/+3/6//r/+v/6//t/+//6//t/+v/7f/u/+3/7P/p/+v/6//s/+z/6v/s/+r/7P/r/+n/6//o/+z/6v/s/+3/6P/r/+r/7f/o/+r/6v/r/+z/5//r/+n/6P/p/+f/6P/o/+r/6//q/+v/6//q/+v/6v/q/+j/5//o/+n/6//q/+j/7P/r/+r/6P/o/+n/6P/r/+n/6//q/+j/6f/q/+r/6f/p/+n/7P/r/+n/6f/q/+z/6f/p/+n/6f/q/+r/6//q/+n/6v/q/+z/7P/q/+n/6//q/+n/6//q/+r/6f/r/+n/6//r/+n/7P/r/+r/6v/q/+r/7P/p/+n/6//q/+n/6//w/wcACQAJABoAIwAsADQANQA4AEIARgBHAE0AUQBUAFUAWABbAF4AYABiAGcAbgB2AHsAggCJAJAAlgCaAJoAoAChAKIAoQCgAJ4AnwCeAJkAnACWAJMAkQCMAIYAhAB/AHoAfABzAHEAbABlAGMAXQBaAFQAUQBKAEQAQgA8ADcALwAoACQAGwAaABMADgAKAAUAAAD3//T/7f/s/+f/5//m/+P/4//h/97/3f/a/9f/1P/T/9D/0f/U/9L/1P/S/9L/1P/T/9T/0v/S/9T/1f/T/9X/2P/X/9n/2v/b/93/3v/e/9//4//k/+L/5//k/+f/6f/p/+v/5v/q/+z/7f/t/+7/7//t//D/7f/v/+//7v/v/+//8v/w//L/8v/x//L/8P/w//L/8P/x//H/8f/x//D/7//v//H/7v/v/+7/7P/r/+z/7f/r/+v/6v/t/+3/6v/p/+r/6f/n/+f/5v/n/+X/5v/n/+X/5P/l/+T/4//j/+L/5P/h/+H/4v/g/+D/4f/i/9//4P/f/+H/4P/h/+D/3//g/9//3//d/97/4P/g/97/3//f/9//4P/f/9//3v/h/+D/4f/j/+P/4v/g/+P/4P/e/+L/4f/j/+T/4v/j/+b/5//k/+H/4v/k/+b/4//k/+f/5v/p/+r/5//m/+f/5//p/+X/5f/m/+b/6f/m/+n/6f/n/+j/6P/p/+n/6f/o/+j/6P/q/+n/5//o/+j/6f/p/+b/6P/n/+j/5//m/+r/6P/p/+j/6P/o/+f/5//n/+j/6f/l/+f/6P/n/+j/6P/p/+j/6P/n/+f/5f/o/+j/6P/k/+X/6f/m/+j/5f/p/+f/6v/p/+X/5//n/+n/5P/o/+b/5v/m/+b/6P/o/+b/5f/o/+b/6P/o/+b/6P/p/+b/5f/m/+X/5//m/+j/5//o/+n/6P/q/+X/5//n/+X/5f/o/+n/6f/p/+j/5f/n/+f/5P/l/+j/6P/p/+r/6P/n/+b/6v/n/+b/5f/l/+n/5v/n/+b/6f/o/+j/6f/m/+f/5v/o/+f/5f/n/+X/5//p/+f/6P/m/+b/5//n/+j/5//m/+f/6P/m/+b/5f8NAFAAUQBeAHkAlQCsALcAugC/AMoAywDWAOEA4QDUAMoAvQC2ALUAqQChAKQArAC5AMIAxQDQANEA0gDUANMA1wDTANMA0ADQAMwAyQDBALQAowCTAIkAgAB3AG8AZABfAFcASgA/ADgALQAgABkAFQAWABcAEAAQAAwACAABAPb/9f/w/+7/8P/v/+3/7v/o/97/2v/R/8f/wv/F/8n/xf/H/8v/xv/H/8n/xP/D/8D/xP/L/9T/2//Z/93/2v/Y/9X/1f/Y/9X/1//Y/+X/5//i/+H/4v/j/+D/4//c/9z/5P/p/+j/7v/t/+f/6v/r/+z/7//o/+z/6//p/+3/7//t/+7/9//2//H/8f/1//P/8f/w/+j/6f/y//P/8v/u/+z/8//1/+7/6//p/+v/6v/p/+3/8f/z//b/9P/4//X/6f/j/97/4v/m/+X/6v/t/+3/6//k/+T/3//e/+D/4v/j/+P/5//m/+D/4f/e/9r/2v/c/+D/3P/f/+H/2v/W/9n/1//U/9z/4f/j/+X/5f/h/+H/3P/X/9b/1//X/9f/4v/k/+X/4//g/9//2//Z/9z/4f/j/+n/4P/f/+P/4v/m/+H/4v/m/+r/5//l/+r/6f/j/+P/5v/j/+b/4v/h/+j/6P/o/+z/6//m/+n/6f/l/+n/6f/m/+b/5//r//D/6//p/+X/4//p/+f/6v/p/+n/7P/s/+3/5v/j/+f/5f/j/+j/5v/l/+v/7P/u/+3/6f/p/+j/4//n/+3/6f/k/+X/6P/s/+b/5v/m/+b/5//o/+n/6f/q/+f/6P/n/+n/6f/l/+j/6//q/+T/4//m/+3/7//o/+f/5//q/+f/4//f/97/6v/r/+f/5v/x//f/8P/o/+P/4v/i/+X/5f/o/+r/6P/u//L/6P/o/+j/5P/p/+j/5v/p/+v/7f/t/+j/6f/r/+j/5P/q/+f/5v/m/+H/6f/r/+//8v/z//L/6v/m/+b/6P/n/+X/5f/m/+z/7f/o/+z/6v/t//H/6v/m/+b/7P/t/+b/4//o/+3/6f/p/+j/6//w/+X/6P/r/+z/7//m/+X/hgDlAUECJAKXAgADWwOKA14DLAMvA0UDXQNoA0ED4QJYAu0BhQEXAeIAsACEAJIAnACUALEA1QDKANAA6AD6AA8B/ADsAPoAAwEBASIBJAHjAMEArwB4AC4ABQDc/6H/Zf87/z3/Mf/+/t7+6f7u/vL++f4E/wr/Fv9J/2X/X/+Y/8v/sP/G/wAA///N/7b/uP+p/6L/nf+y/8f/qv+U/5L/h/96/1//RP9G/37/n/93/4//2P8GABYA8v/j//j/9/8DABEABwAhADYAHQAeAEQARwAsAPP/1f8EACYAMgArAAQA7v/7/wEA/v8VAAQAyf/K/wAAJwAuABgADgA4AF0AQwASAA4ADAAAAAMABAAfADsAPwA3AD4ANAACAN3/u/++/9P/6P8kAEQAOQAZABsAIADi/6L/d/+S//r/LQAlABcACQAFANn/tP+p/67/zv/Z/+z//f8SABoA4P+p/53/mP+v/87/1P/m//H/7P/t/9b/v/+s/4D/jv/U/+P/5v8GAAYA+v/x/8T/j/+L/7H/sP+o/+v/PgBiACMAyv/J/+H/0P+y/6L/qv/g/yYALQAbABAA/f/r/8b/uv/J/6r/8f+MAMIAGQEyAa8AggDBALwAVgAPAAwABAAMAEQAXAASAIf/3v5b/hT+vv03/f78fP3G/aH9a/3m/Fv80vt1+0X7V/vA++z7Q/y8/Kb8lPzS/K38pPwE/V/9J/7z/nP/EgB2AI0AqwCbAGsAeQCjANoAHgF9AUkC+gIDA6gCdAJyAn0CqQKxAqgC9gKmA9YDIAO+ApsCNALiAZMBpgEjAnwCbAIQAuQBDALMARsBvwCLAGAAnwAFAQcBBwEsAREB8gCSAE8AdQBQAAgADQA7AEgADQBu/wL/8v6x/i3+7P18/m7/1//J//P/AADJ/2j/5f7T/hz/dP+3/+H/3P+f/77/JQDi/2D/YP9j/3L/hP+G/8j/MgBeABoAKACeAJ0ALgDr/+7/zv+P/7n/5f/m/63/6f6L/uv+Nv/L/jD+xv1d/ZP9//3v/ff9JP42/l3+rP6n/g7+2f0k/l3+t/7Q/nL+bP4I/5j/hv8p/yj/S/+S/y4AaABKAKkAkQEnAnsCBgMpA2cD2AOAA34DAwQlBLsD7wKrAoYC1gG5AM3/GP9m/nr+7/4Q/xX/Af+v/oT+zf4H//b+Q//7/9oAwwEaAuUB0wE+ArwC6wLXAqACuQI0A10D+AJoAgYClwHGAGwAVgDH/7H/3v95/z//h/+I/3n/Wf8Y//D/8gC7AFIAywBGAe8AfwD8/yX/3f7L/m3+xv6M/3D/kf7B/Y79yv30/fz97f1M/ln/CgDo/y0AUQCE/zP/W/+R/6T/Nv+C/mH+Kv9s/yX/Af+E/iD+d/7U/gD/P//5/oD+qf7k/tD+uP7c/lX/r//p/0UAcgBpAGsAPQCy/3//bgBIAfkA5AAvAf8AyQBoAJ//W/+C/9L/pgAkARwBFAHkAK8ACAE8AXsA1P8AAMIAgwHUAa4BGQGgAMEAJgEsAaYA6f/Q/50ABgGjAFYACACg/zj/tP6q/uH+zv6n/of+j/6H/iD+aP0A/Rf9Ov1W/YH9hP1s/Wj9Y/19/Vv9/vz//HP9UP45/2z/Xv+F/3n/m/+5/8H/PwDbADEBSwGKAesBrwEgAdsAkwA1AMv/lf/r/1cAdQBRAM3/Qv9E/1P/KP+S/z8A1QClAQgC5gHRAe8B6gFCAXcAlgBUAUcB7gDhAFIAZf9i/nL99fwT/RH9qfwH/cz98P2g/Sj9zPyx/B39xv2H/rD/wwA9ASwBQQE/AfYAFQEGAc8AJQGbAZ8BIQGdAPr/7f43/in+OP4T/gT+EP5X/lH/0f9t//7+lP6+/oD/HgBpAJ4AtwAvASIC9wHyAFwA8f/p/yYAnv8A/w3/Rf8q/8X+hP4u/iL+bf5m/k7+h/7u/gT/4P4B/4H/BwBAAPz/u//a/+P/4f9p/3/+bf7U/s7+kv45/sn9i/1s/VL9lv24/UX9Qv0r/un+AP+o/nf+Cf96/2L/Hv/7/pT/KwBWAIMAegAbAK3/gv+w/7j/Uf9B/9T/oAA7ARsBugDmAPcAZwDt/8H/xf8EAEQAlQDrAOAApABMAPn/yP/0/6wA+QAhAcEBKQJHAjwCHwLLAW8BXQFgAbMB6QGBAdcAXQBHAMH/4f6Y/o3+9/6W/0f/nP68/nL/xf83/1z+Ff6F/gD/yf58/uj+bv+E/0//K/8Y/7/+bf5e/s3+U/9j/xX/3P4g/07/T/9i/3//kP/7/9YAUgE8ARYBHwEPATcBhgFmAWcBoAFfAfkA5gCPALL/Gf8n/1H/ev+S/6b/IAAaAGv/9v7y/j//dP+H/3b/av92/0X/1/6M/oD+Sv6B/j//tf/d/4T/PP/L/0sAEACf/1f/Y/+E/1z/m/8LAPL/4v/+/wYA4/+D/x//Dv+P/+L/AAB4AM8AmwACAGr/2f5j/hP+m/1w/ef9V/5h/gj+mv1F/RP9Iv0T/fT8Hv2C/eb9ZP4x/5P/av8i//r+tf+tAIMAxf+x/2gA5QBwAN//+f/4/2n/Nf+O/7z/Zf+a/hb+mP6R/+n/vv+E/53/TADfAOsBiQTkBc4FawZgB3UIBAkpCAYH+QaLB9MH1QeJB/MGXQZ7BVcEkAP+AksC4gFIAtcCBgMpAwwDlAJNAigC4wHmATcCjwK9AsEC3QLcAmkC4QFcAd4AxgCoAFQALAD7/47/Cf+L/hP+fv3W/IX8xfz3/O38Dv1g/cn99v3K/ZP9oP0B/nj+xf7m/lb/5//x/4f/N/8x/9n+Zf5A/j3+ev77/mD/V/8d//H+y/69/sn+1f7a/gj/kf/9/xcAeQDCAGYA7P+H/2D/qv8UAG0AfABNAFsAmACPAEQADgDK/5j/sf/e/w4A9P+I/1v/Yv9g/2b/Lv/n/iL/f/+o/5H/RP8F/yr/a/9D/y3/Uv95/4D/Yv9Y/0r/IP///tr+5P4G/xj/Nf9D/03/Nf8z/zL/Av8B//H+1P7z/gf/8f7q/vT+1P7b/iD/LP8W/yz/L/8r/27/kP84/9v+5/4X/xT///70/hf/cv9p//z+3/4g/1v/Hv/F/tL+B/8q/yX/H/8b/xL/Jf8Q/+7+9/4H/xj/H/8b/xf/Pf9//23/J/8S/yL/F//e/qr+yf4f/zD/Df8P/zr/e/9Z/+/+yv7e/gT///7y/jX/dP+B/43/hP9U/yb/I/8f/xX/Rv+C/2//Vf+Y/9f/x/+R/0P/F/8q/yz/Ef8e/yz/Mf9c/13/Mf9N/33/U/8m/w7/2v7O/vf+EP8e/xb/DP9X/5L/Qv8B/xH/G/8x/1n/Yf9H/0j/YP9P/xX/x/5t/jH+Tv6u/hT/Lv/7/vz+JP8v/zP//P6d/nj+l/7s/lP/aP9H/3b/pv9M/9b+tP6a/pX+1f4T/xX/Jf9X/2//WP/P/j7+Nf6d/gX/Ef/N/rT+Cv9T/0L/3P6T/q/+1f4F/zX/Pv8Z/9X+/P5X/0L/Iv8M/9X+2/4C/+v+6/4X/yf/QP9a/2L/Qv/u/sb+2/4I/0P/Pv8P/wn/QP90/2H/Ev+y/rX+/f4Q/+H+2f4A/+j+tv6r/sX+5v7j/sL+s/7L/vf+C//u/uD++v7+/tr+2/41/2j/J//G/r/+//4I/9v+0/4P/yf/8f7j/m0AzALAA9gDVARYBWsGsAYdBs8FZAYqB6UHGwiMCLoIigguCAAI1gd+BxIHEwfQB5AItAh+CFUILAj3B44H7QaQBowGuAb7BicHNgc7ByQH2gZ7BjgGBgaoBVgFTAUzBeUEhQQYBI8DDAOSAgQCkgF1AXcBVwE+ASwB9ADKAL4AsQCUAGEAMgA9AHQAcAAmAPH/v/+B/1z/Of82/07/KP8I/zr/Z/83/9z+sP6X/oX+jv6d/rf+yf6//rX+1P7Y/sb+x/6n/qH+2P4B/x//T/9v/23/a/9Z/xr/7/7V/rr+0P7+/g///f7Y/rH+sf7F/sL+yP7W/s/+zP7g/uP+uf6O/nn+gv6k/r3+wP7M/sz+kf5k/oz+oP6I/n3+cP51/o/+of6a/mn+KP4O/h3+QP5G/k7+Z/5c/lP+Nf4a/i7+P/40/if+Lv4u/i3+N/5P/mX+Rv4U/gH+//0D/hj+Kv4g/iP+K/41/kr+R/4j/ur92v3m/fD9BP79/f39Jv5I/kD+Kv4c/h/+OP4p/v39+/0d/jn+Ov5B/k7+OP4U/vP98f0v/mf+WP5A/kz+X/5u/l/+L/4c/jL+Wf6D/pD+dP5g/k3+Kv4V/hD+Ff49/mL+gP7K/vn+y/56/kP+If4i/kb+Nv4Z/lH+kf6b/pT+jf59/mH+Rv5F/k3+Xv5s/nX+mP63/qX+W/4M/vD9Gf5N/mf+f/6L/qD+sf6W/lH+DP71/f79Df5I/pT+qv6m/qH+jP5h/iH+5/3d/Qr+Qf52/pP+lf6P/nb+Zv5O/hT++f0S/k7+gf5+/mr+b/54/lT+IP4C/hD+S/5f/lr+W/5Y/mL+Xf5Q/j3+H/4b/kf+dP6K/p3+fv4o/v39Av4N/h3+HP4k/lz+n/6//qD+VP4b/hT+Dv75/fP9IP5U/l/+Zf55/oD+Xv49/i3+J/41/i3+EP4S/i7+VP5q/k3+J/4s/j/+MP4l/if+F/4s/j/+KP4e/jT+Sv5L/kj+Lv4K/v79F/4n/iL+Jv4q/jT+XP6F/nj+Q/4f/v/90v3Q/fv9I/4r/jb+Z/59/nH+Vf4K/tn92f3a/eP9Dv5I/nf+gv5e/i/+Af45/lkA+QJzBJ0F+QZaCIcJAgqYCWsJEwrsCuoLQw2NDmAPuA+nD4MPiA9aDwYPPQ8VEBIRtxHBEX4RKhGjEOoPGQ91DjoOWQ6wDvwOFw8CD6IO9Q08DcAMXAzgC3oLLQvlCpsKHQpDCSAIAQfxBRsFuQR6BCME1gOiA24DSwPsAi4CgQEYAdwAswB7ACcAEAAfAOP/Zf/5/sP+l/53/nT+mv7H/q7+c/5Y/jn+7/2T/UH9Sv2W/bX9xP3o/QT+Ef7u/Zj9e/2R/ab96/1Z/rT+4v7R/o3+bv5o/kb+J/4k/kf+c/6q/tb+6P6//kj+yf2Q/cP9Iv5r/oj+jv6a/qH+gf49/v790/3F/dD9/P1A/mn+dv5j/jj+IP73/bH9o/3D/eX9Df4f/if+L/4X/t/9vv21/Xv9Nf05/Xv9z/3+/f398/3k/bX9d/1w/Xr9Vf0+/V/9mf28/an9av1O/V/9Nv0D/RT9Uv2a/az9bf0k/RT9Gv35/NT82vwJ/Tz9Yv2B/Xv9Sv0R/eH82fz5/An9Ev1L/ZP9mf1i/S79Cv35/AD9Bv0j/V79jP2z/cD9rf16/Tr9Ff0p/WH9hP2D/Xf9mP2+/cD9qv2L/Xb9hf2c/Zr9qP3K/db9zP21/Z39qf25/bH9uP3L/c79tv2U/Zn9wP3Y/dH91/0F/hf++v3N/ar9mP2B/XT9b/2k/fL9DP4Q/hD+Cf72/bj9d/1r/X79jP2O/aD93/0m/iD+1P2c/ZD9gP11/Xf9ev2j/dz9/v0P/iL+B/65/Xn9Vv1d/W79c/1//bX98/38/eL9vf23/c/9vP19/VP9gP3Q/d39xv27/a79pv2p/ZP9h/2r/df93v3Q/d390/2p/YP9dP16/Xz9jv2y/e/9L/44/u/9lf1e/Vn9Zf0+/Tb9bP26/fX9GP4i/gn+1/2N/WT9aP1v/X79mv3F/e796f25/aX9vP26/Yb9ZP1j/Y/9z/3V/bv9qv2d/ZD9lP2R/Yj9nv2z/an9of2b/X/9ef2S/av9tv2p/Zv9nP21/c79yv2t/Y39gf2M/Y79fv1//Yb9i/2Z/bz90/25/bb9yP2p/X39Wf1E/Vz9eP1x/Yv93P39/dP9qP2z/c/9sf1i/Tr9W/2Y/bP91/30/0MDsgV0B0cJPgsPDRAODg4/DisPGhAaEaYSjBRDFkEXZxdvF6kXmBc+F1kXKRgbGbcZwxlXGdoYGRjMFm0VXRSsE2cTXRN3E50TghMEEzcSPBFcELwPPA+xDgcORg1jDFQLHArUCKAHhAZ2BZ8EJQQEBNwDaQPUAisCigHpAC8Amv9F/xH/wv5g/i7+DP7Q/W/9Hf0a/Wb9qP2s/bX98f0h/u79hf0d/dv8zfy8/LX86/wy/Vb9cf2E/YX9kf2C/Vr9X/2i/fL9Qf6F/pD+gP5v/mn+WP4n/uf9v/3g/TD+df6e/pT+Uv4f/g7+8f27/X79RP1R/Zb9t/3O/eb94f2+/XL9Nv1H/V79V/1P/Wz9mv2u/Z/9h/2Y/ab9kf19/YX9qP20/an9jv11/Wn9Sf0u/Tj9cP2j/c/98P3m/cf9iv1H/Sv9Kf0d/SH9Vf2g/dz91P2a/Wn9J/3c/MH8z/zo/An9NP1V/Wv9S/3z/MD8s/yF/EX8N/xr/LP88Pzz/N783/zK/J38efx7/Jb8kvx1/H/8svzp/OP8pfyh/Mb8vPyj/Kj8uvzZ/Pj8+/z6/AX9Dv31/PH89/zp/Ab9G/0Y/R79Of1H/T39K/0k/Tf9Uf10/YT9gP11/Vz9Sf1I/VP9Yf1a/U/9Xv13/YL9ev1n/Vr9WP1N/VP9i/22/az9i/1t/Vn9Q/0H/ez8H/1d/XP9f/2i/cD9uP2B/Uz9QP07/SL9Jf1K/Xv9k/16/XP9cv1Z/Sn9Dv0o/U39Z/12/ZT9oP14/Vn9Yf1c/S79EP0P/TT9af1o/V39Zf1e/Wv9iP2F/Xb9d/14/Vv9Mv0f/SD9NP1K/VD9af2W/bP9qP16/Uj9Lv0r/Tv9af2B/Xz9ev2B/YX9fv1Q/QL9Av06/VP9bv2L/aj9wf2T/Uz9SP1l/VD9IP0H/Sv9hf20/ZL9UP04/U/9Uf0y/S79Qv1N/Vz9cP2G/aX9p/1y/U/9XP1V/S/9EP0D/TP9fv16/Wn9m/3F/a79f/1D/Rv9Jf0u/SD9MP1c/Vz9U/15/Zr9lf12/VH9Sv1G/TX9O/1P/VL9VP1R/VT9gv2j/Z39c/0//TP9Sf1E/Sj9Lv1l/Y79jf2T/Zf9hv1V/RL97fwB/TH9SP1X/Xr9m/2e/Yj9Vv1D/Rr/uQLcBUkI1QqCDeMPVRGKEWoR4hG+EvwTBxa8GDob7xzWHUkedR4EHv8cPxx5HD8d4h0YHvYdfh1lHJYagBiUFvcUxRMaEx8ThBObEzgTixKSETIQxg6dDaMMygsEC0sKoQnKCIwHMgYFBfADAgNBAtEB1QHaAZQBCwFHAGv/i/6q/f38rvyJ/Ib8s/zq/P/81/yW/Fn8N/xW/Kn8C/1+/fT9Nv4t/u39eP3u/H78T/yF/Oz8Xf3i/VP+hf5u/jr++f2D/Rj9K/2M/d39Nv6O/rj+uf5+/hn+rv1a/R39//w+/cj9Kv5M/mj+Vf4O/pn9+/yL/IL8qfzE/N/8G/1t/aP9nv1T/f/8xvyh/Kb83vw+/az9/f0j/h3+8P3A/Z/9a/06/Vn9ov3V/Rz+bf6H/n3+Uv4C/tn97f3g/av9p/3R/Q/+Kv4J/uX93v2x/Xf9b/1//Zb9kf1U/ST9Nv1M/UP9Ev3F/Jb8svzg/OT8wPx+/Dz8Mfw//Db8Lvw7/Dr8PPxp/Gv8MPzv+8P7zvv8+xn8JPxO/Jr8zPzY/Lb8a/w1/CH8EPwV/ED8cfzD/CX9Vv1S/Tf9Bv3J/K38qvyq/Mj8Cf1O/Yb9l/1+/U39Lf0Z/QP9/vwW/Uz9jP3H/ej9y/2A/Un9Ov1A/Sz97vz3/Ev9l/3G/c39uv2a/WX9F/33/An9GP0x/VP9fP2x/a39Vv0U/QL99PwB/SX9R/2A/ar9k/17/XD9Of3r/NT8Av1G/XX9dP1x/X/9X/0h/fH86vwX/VX9ff2r/dL9zP2i/UL96fzV/NT81fwF/Vv9p/3Q/c/9of1u/Vr9J/3m/Ob8Iv1j/Yj9m/2P/X39Z/0m/QT9F/0m/Tf9WP2J/bv9vP2D/UT9HP0Y/SP9Mv1X/Yb9vv3N/Zf9Sf37/Nr84/zt/AH9PP2I/bj9uv2n/Xz9T/0w/Qr9Av0i/Ur9Yf11/YH9bf1E/Rv9DP02/Xj9lf2B/XT9jv2R/Wv9Q/0e/Q/9I/0s/Tn9Yv15/Xb9ZP1H/Tf9Qf0+/Tf9V/1x/WL9XP1j/Ur9RP1p/YP9gv16/Vf9H/0e/S/9Jf04/T79RP17/bf9zv22/XP9L/0Z/SX9Lv0w/TT9Q/1w/Xn9ZP1T/Tj9P/1k/Yj9fv10/Y39pP23/Yb9G/3h/DP9lf97A/YG+AkGDfUPcRICFE0UJBRcFAcVXxazGLsbgB6KIOghrCLSIjQiFSEzIPgfLSBrIG0gFSBHH8cdhxvYGCoWzBPkEaoQThB/ELYQnhD3D8wOXg2xC98JKgjBBsQFEwWDBBEEvwM5AzsCKAFaAMb/Sf/k/pT+X/49/vT9d/3p/Fr8rvsP+8X6wfrM+uD6+vom+5D7Avwy/EP8bvyq/Pf8S/1W/Uj9Uv1d/XT9h/2U/bv96v0T/kn+h/6k/pP+a/5E/iP+FP4S/hP+Pv56/pn+i/5G/uX9lv1n/S39+vwS/V79wf0E/gP+5v3M/Zv9PP3h/K38o/yw/ML8CP1P/Wr9Xv1M/WL9gf1v/T79UP2f/dn94v3l/QX+Ov5Z/kX+Nv5a/mn+Wv5v/o7+pv7D/uT+4v7v/vH+x/63/p7+af5K/lD+V/5V/mH+X/48/hX++f3e/cj9q/2I/XL9Yv0+/Qj93/zX/M38tfyd/Hr8bfx4/G/8Ufwx/PT7qvui+8v70PvC+8L74vsr/FD8OfwG/NT7t/vJ++374PvP+/z7SfyZ/Or88Pys/Hn8efyo/Or88Py//K/81vwI/Tz9Xv0+/RP9Gv05/V39cf1j/Uv9ZP2i/cD9qP2N/Y39cf0t/f78D/1N/X/9kv2y/eX9Bf7t/ZD9Sv1F/Tv9KP0V/Sb9dv2r/ZH9ef18/XL9Uv0o/SP9SP1Y/Vv9Zv1+/ZT9Z/0X/QP9Gf0j/UD9Uf1Z/Xn9j/2a/Yj9X/1H/Tz9Mv04/V39hv2Y/Y79df10/Wv9U/08/UP9X/1j/W79ef2M/bP9pP1Y/Sr9G/0k/Vb9cf1j/Vv9X/1n/W/9cf1k/Uz9Nf09/Wf9dv1g/UP9Ov1P/WT9Zf1e/W79dP1d/Ur9Qv06/SP9A/0S/VX9hv2e/aL9pP2e/W/9RP02/S79L/0v/Ur9j/23/Z/9cf1X/U39Uv1d/Wn9dP2d/dv99f3c/aP9Rf3o/M787vwl/Wz9sv3c/fH9/P3W/Xf9Jf38/P/8Hv1C/ZT93/3x/eb9o/1C/e/81fzn/Az9R/2L/eD9G/4F/qv9Xv0x/Qr99Pzs/Ar9S/15/aX91v3R/Yf9L/0e/U39Y/1k/WX9Y/2D/Zr9Zv09/Uv9X/1n/Wf9cf1//Xf9XP1i/Xf9bf1l/WH9sf1tAKgEMwg2CzEOLBHQE0AVSBUYFWkVChZYF8QZ+hw1IK8iLyQdJXgl3iR3IxUiWSEgIeAgRCBVHxwedhw1GnQXuRRgEosQSQ+PDiwOvQ37DNELbQrwCGgH1gVhBDADNQKBAfMAawDx/3//Ev+2/ov+Z/4c/sf9ef0Z/Y78/PuT+1D7DPvP+rf61/oA+/b67PoP+zj7RPtN+5D7Bvx3/Nf8Jf1o/aD9uf2s/aP9sP2m/b39Dv55/uL+L/9B/yf/Ff/r/qb+Vf4u/lH+cf50/nv+ff5a/gv+r/1V/Rv9/vze/PP8OP1q/XH9a/1I/Qb91Pyv/J38ovys/Kj8vfz//Dj9Nf0i/Sf9Lv1O/Yb9xv0R/jL+C/7m/fX9B/4H/v79FP55/vL+Q/9x/3//Zv84//j+r/6M/or+qP7r/kj/gv+D/1n/DP/I/oP+NP4A/vn9AP4Z/kj+U/4c/sD9dv0r/dP8oPyR/I38ovzI/NH8vvyX/FH8Bfza+637cftn+5376vsf/CP8Fvwo/Df8CvzK+7P7vfvI+9r7CPxX/JP8jfyP/K/8sPyX/H/8lvzZ/P38/PwN/Sf9Mv1B/Uz9Wf1l/Tz9Bf0a/W79qf2x/bD9tf3E/dD9wP2b/XX9Zf1k/WP9Wf1m/ZT9w/3s/fX91P2s/YX9XP0z/Rn9Ff0J/Q39Pv2A/ar9qf2s/cX9sf1a/Rn9Df0a/TH9Pv1S/Xj9lv2Y/Yv9fP1e/VD9Vf1d/Wv9f/2r/dL91/2k/Vj9Mv0r/Sv9Pv1i/Yr9vv3E/bn9yf3A/Z39df1Q/Uv9X/1t/YP9oP2w/Y79V/1O/Wj9af1Q/V79e/2N/aP9m/2H/W39Q/0h/R39K/0Z/Rj9av3C/dL9rv2O/YD9cf1B/QD97fwQ/Tn9WP13/bD94v3Y/Z39Z/1e/Uj9D/0E/Tf9Yv1u/Xj9mP3G/dv9qP1d/UL9PP0x/S79Vv2f/dj94P3b/c79mf1F/f788fwT/S39Of1t/b/9+v0T/un9nP1t/Tz9Bv0V/UL9Uf1X/Wr9gv2N/ZT9h/1v/Wv9cP1+/Zf9wP3B/YP9X/1m/WD9OP0a/TD9a/2o/b39uf2+/bX9l/1s/V79e/1+/WL9f/29/bv9mf1w/VD9Wf1V/Tv9Q/15/cD96/3l/cf9nv2X/X79df2s/8gDnwf8CmoO7RENFc8WyhYzFiwWqBaUF6YZ/RyVIKoj8SVqJw0olif7JRUk2yI3IoghjiCPH5seVB1BG00YKhVhEggQRQ4pDY0MLwy8C+kKtQk/CHEGcQSLAu0AxP8W/7z+jf6M/pX+gP5I/ur9mf11/V39Mv0N/d78hfwC/GL70fp0+jT6Bvoc+pP6OPu6+xj8WPx5/I78gPxi/Fn8evys/Pj8e/3y/Sz+P/5H/lv+cP6G/rP+8v5G/53/tf9+/y//1P5r/hH+uf2D/aP97P0Z/ir+G/7N/Vn93Pxy/Er8W/xn/Hz8r/zK/OD83fym/HH8U/wt/Cv8Z/yp/Or8Ef0b/Sn9QP1G/VD9f/26/fj9I/45/lr+gP6k/rf+uf7P/ur+9P4M/yT/J/9A/1b/Xv9v/5b/y//b/73/jf9e/w7/sf53/nv+lP6k/qL+nP6v/qX+V/7u/aT9av0p/fj84vzp/BH9Hv3a/Hn8Ofwf/BX8Afzl+9v78/sg/FT8bvxM/BP82fuf+4T7bvt7+777Afw5/IH8vvzL/Lr8k/xx/GL8VPxc/Ib8zfwH/SX9Mv05/T79NP0Q/f78I/1n/ZD9pP3B/bT9nf2Q/XD9Xf1i/Vj9Pv1d/a392/3h/dX9w/2e/YD9b/1Q/UT9Sf1b/YD9nP2Q/YP9d/13/YP9cf1U/UL9RP1H/UX9SP1a/Xj9g/19/X79h/2L/YD9af1X/Vb9Uf1Y/YL9pP2R/Wv9Yv13/ZX9lP1//ZH9xf3m/dn9r/15/Vb9T/1U/Vf9Y/1+/ZP9q/3T/eb92v2z/Zv9of2X/X39WP0//U39Vv1U/Wr9jv2q/br91f3f/cT9k/1N/TH9OP0x/ST9J/1T/Zr9vf2s/aH9kv1+/XL9YP1O/Uv9VP1q/Yf9m/2X/Xr9Yf1i/Xr9cf1n/Wn9hv2n/a79t/2j/YT9dP1a/Tz9L/1J/YT9y/0D/g3+4v2k/YH9eP1h/Sb9H/1e/Zz92P37/fX9z/2H/Tr9If0j/S39Yf2j/eX9Df4H/tX9jv1D/fv86vwN/Tv9b/21/Q/+R/48/vb9jf0w/Qj9Ev0y/Vz9jv24/df9+f3r/aT9Y/1D/Tf9Rf1a/WT9hP20/cD9rv2o/af9gv1S/UL9Sv1b/Wv9Zv1i/XP9lv2t/br9bv8IA6IG1An8DDsQXRN8Fe8VlxWnFREW2hanGJ0bGR9RIskkhiabJ5wnXCaQJBMjKyJqIVcgNx8iHrwczRo9GEwVjBJHEH0ORg2GDPYLVAtpCgkJNAc/BW0DtQE1ACX/h/5Y/nf+of7H/tX+n/44/vD9y/2i/YH9VP0d/fX8ufxH/M/7Z/sY+wj7NPtz+8X7MfyS/OP8+/zX/JP8ePyQ/LL83PwE/Ur9qf3p/RD+Sf6F/rP+1/4B/0H/VP8X/8v+q/6m/pL+Y/4w/jD+YP5p/jP+3v1v/fr8q/yI/I78rfy7/MP86vwW/Q39t/w3/N77w/vP+/37J/xZ/Lv8KP1u/Xf9T/0r/Sf9Jv0k/TP9cv3N/S/+mP7d/ur+3/7W/s7+0f7I/sP+6v4w/3b/s//d/+v/5//H/5r/bv8y/wj/Cv8n/0f/Q/8l/yX/Mf8P/77+a/4s/vT9uf2M/Yb9nP2X/XT9VP0z/QP9ufxv/EH8LfwY/Pr7CvxP/ID8avw//DD8IPwC/Lz7f/ty+337pPvT+xX8YfyU/LT84PwI/er8kvxE/Cf8Tfxv/G78lvzj/DL9cP2J/YH9bv1g/U/9V/1i/Vr9Zf2A/Zn9q/21/Zv9cv1t/XH9hf2d/Zf9mv24/dn92f25/Yf9Xv1b/XH9ff1y/X39mP2e/a79l/1n/VX9P/0s/S39R/1v/Zb9t/3L/dD9uP2E/WT9X/1U/Un9QP1M/W/9pv3B/bH9vf3m/fD9wP2C/Wz9gP2Q/YL9fP2I/aX9uP26/df98f3U/Y39Xv1q/YT9hf2H/ar92v3b/b39pf2Q/XH9Of0C/Rr9Xf2N/b399P0z/jn+7f2b/Vr9Ef3h/N78//w7/Xv9m/3H/Rr+LP7y/aH9V/0v/Sj9Kf0y/Uf9Xf15/ZD9oP2m/Zn9ev1+/aX9tP2t/aD9k/2M/Yf9df1e/Uf9L/1C/Xv9rP2//dj9Cf4O/tj9m/1x/Un9Iv0j/U/9h/3F/eX9/v0l/hL+wP1x/U79RP1C/Vz9l/3Z/f797v3j/d/9rP1W/Q/9EP1G/XP9i/3A/f79Dv7s/af9cP1Q/Sb98vwE/V39l/2Y/aL90f0P/hT+yP2B/Wr9dv2A/Xj9dP1m/U39Sv1z/av9uv22/bb9zP33/fb91v2w/YD9c/0H/3UCDgZKCWMMjw+fEtYUixU6FQAVLhX+FdYXhhqBHV4g3SLUJAEmGCYZJYcjMiIuIRgg5B6jHUscxBr3GMYWNBSTEUQPgQ1ODGMLhAqOCXMIPQfWBT8EjQIAAcz/2v4n/s79y/3s/SL+Rv5P/nD+mP6e/qT+pP5n/v39hf0R/br8fPw9/Cz8XPye/Nj8Gf1X/X39cv00/fr84fzI/ML85/wZ/VH9hv2w/cf9yf3L/eD9EP5N/oX+wP7+/jr/S/8T/6b+Jf6k/UP9G/0T/R79RP2G/az9qf2O/T791Pxx/CP8//sL/Cb8Ovxf/G/8Svwi/An8C/wl/E78ifzi/Fr9uv3c/eL9zv2O/Uz9PP1j/cD9JP5t/tP+Pf9j/1f/Pf8g/wz/CP8Q/zT/iv/f/w4AFQDo/7D/Xv8O/+r+6P4M/zP/Rf9Y/27/Uv8M/8H+aP4n/gD+4P23/af9nf1//Vr9Kf3v/LX8mfyk/MH8zfyx/I/8efxn/Ez8FfzK+5T7mfvM+wH8K/xR/Gn8gPyS/H38Vvw+/Cr8JPw5/Ff8efyr/OT8Ef09/Ub9Jf0H/ff8+vwO/Rz9Jf0p/UX9gP2r/bP9kf1v/XL9cf1i/Wf9gv2a/ar9t/21/af9jf1r/Vb9XP1r/WH9Yf1+/bD95v3X/Zn9dv1u/WL9R/00/Sr9Mf1F/WX9kf2v/bD9j/2D/ZP9kf2E/Wz9Wf1o/YD9gf2C/Y/9jv2E/ZX9u/3b/dP9tf2q/bD9pf2D/WX9df2g/bH9uf3L/dj92f3S/bL9kf2M/Y79iP2O/ar9rf2p/a79kv14/Wn9ZP16/aH9uf3C/cb9t/2j/ZL9Y/1C/UD9Rf1o/Zj9vv3O/cz9s/2K/Vf9Kf0a/TD9Yf2J/bL90f3U/b79n/14/VD9Nf0r/U39ef2U/bD9zv3D/Yn9Z/1e/W79lP23/cv90/3I/ar9kf1w/Tv9Jv1I/Xr9pP3J/eL97P3X/av9bv1E/Tz9Qf1m/aj92v3W/b39wv3A/Zj9Vf0u/TL9Tf2G/bv93v36/f/91/2d/WD9FP34/CH9U/15/ar92f34/Qr+//3B/WD9Cv3y/Bj9U/2S/bv94/35/QP+/v3J/Xj9Nv0r/Ur9V/1W/Wj9pP37/RP+6/2u/X79bf1z/XT9Wf59AVIF0AguDIUPpxLnFJ4VQRX6FB8VtRU8F/kZhR0SIesj9CVIJ6knvCbKJNMicyF8IG4fLR7rHJ8bAhrbF1IVqhI9EDEOfQw4C1IKaQlSCPEGUAWzAywCuAB4/3r+zv2I/ZH91v0s/oD+n/6q/sT+0/7h/sr+jf5F/hH+4P2e/VP9//za/PX8L/2C/bz9wP29/c39xf2g/U/91fx4/Gb8pvzy/Bz9NP1Z/ZT90v38/QP+Bv4J/hD+Iv4y/iv+8v2n/XX9Wv1R/TL9/Pzu/AD9IP0e/fT8uvyP/GL8J/wV/AT81Puq+737BPxB/EX8G/wY/EX8Xvxg/HH8ovzl/CD9Uv2C/bz92v3e/en99v0Q/h/+MP5y/sX+9f4a/0T/dv+u/7X/p/+n/5f/d/9K/yr/L/9N/2v/fv+f/6v/k/9y/1T/IP/F/mT+J/4b/ir+Qv5M/ir+9/3Q/av9g/1T/Qj9wfyl/Kz8wfy+/Jn8hPyB/HL8U/wr/Bn8KPw6/DL8Ivws/EL8SfxD/D78Pvwq/Bf8Mfxz/Lj8zfzX/PT89fzb/KL8bvx9/KD8ufzb/Af9SP17/YX9cf1M/R79//wD/R39SP1g/Vj9Wf1x/Yf9df1K/S79M/1T/Xn9dv15/aT9m/1n/U79UP1j/XT9av1f/XT9gv1k/Un9Lf0h/UX9YP13/Z79uP22/cH9sP13/Vb9Nv0g/UD9gP2j/bn90P2v/X/9cf1f/U79Vf1W/Xn93f0g/hv+/v3O/Xf9Jf3p/Mr88/w+/Yn99v1T/lr+K/7p/ZT9Nv3s/ND88vwt/W/9yv0O/gj+yP19/UT9L/0g/Qr9Mf2a/ej98/3P/ZL9Vf0f/ez81/z4/Dz9hv3h/Sv+Lv7u/Y/9Nf3r/ML8sPzW/EP9qf3i/fv9B/7e/Yf9Qv0U/Qv9Ev0c/VL9nP3R/dL9nP1s/Vj9Q/01/UH9Uv12/Zf9o/3B/dH9rv2E/XX9c/1w/Wj9Yv1U/UX9Tv10/Zf9of2l/bn90/3n/dL9lP1M/S39Jv0T/RD9Nv2L/dL96f3a/b79kv1a/TX9G/0Z/S/9Vv2j/fn9B/7W/Z79Zf08/R/9Bv0R/VT9nf3N/ez99f3m/b79dv0o/QP9F/0z/VH9ff2g/b79rP13/Vn9WP2m/ikCPQbjCUcNlxC5E/sVphYlFqMVoRVzFpcY/xv4H6AjhiaYKNAp2il8KFUmVCT1IgwiKSEUINMeZx2aG0kZdBZmE58Qbw7oDOcLHQsiCtIISweoBfMDMQJdALr+qP02/SL9S/2X/e39T/6s/u/+Cv8B/93+p/5m/h7+uf03/dn8vfzY/Az9JP1A/Zf94P0G/gD+vv1x/R79u/xe/ED8OvxB/HX8zvww/W79gv2C/ZH9ov2t/bf9u/2//b/9uv2m/Xf9P/0E/dP8tvyn/KL8sfzJ/L/8l/xg/Df8E/zn+8v7q/ul+7b7s/u/++L78fvs++b7/vtA/IX8qfzA/OP8Ff00/Tb9PP1d/Zz94/0g/k3+jf7Q/v3+Gv8g/xn/D//+/gH/Gf8s/1//l/+7/+j/+v/y/+f/2P+l/1f/E//m/tL+0f7O/rv+qf6V/oL+ef5f/i7+//3L/Zz9h/13/U39C/29/IX8gPyH/HH8Yfxb/ET8Lvwi/CL8J/wn/Cv8QvxZ/Fv8QvwW/N/7r/ui+7n72fv4+0v8t/wS/Un9L/3o/Ln8gfxU/Gr8kfyo/ND89vwd/Vf9X/0q/fX84Pzx/CL9U/14/Zz9lf1b/TX9JP0D/er84fz4/ED9gv2S/Yf9gP1n/U39Rv1B/Uf9V/1p/XH9f/2G/VT9BP3j/Pf8Kf1c/W79cf2O/bj9r/2N/WD9I/38/Pb8Ef1C/Vv9Yv11/Y39r/2Y/Vb9Qv1V/XL9hP2U/Z39n/2Y/YL9dv1k/Tz9Iv04/W/9rv3c/ej93/2u/WH9LP0f/SL9GP0i/Vf9lf23/b/9sf2J/U39GP0F/Sr9VP1o/Xb9e/19/W79Tv0n/SL9MP0u/UD9aP2N/Zv9cP0v/R39Kf0x/TH9Tv2B/aX9n/1v/T79HP0M/Qf9Gv0//XD9lP2i/ar9rf2f/XX9Nv0F/Qb9Jv1E/Vj9af11/ZT9o/2I/Wj9Uf0+/TX9Pv1d/ZH9pP2O/Yr9iv1//U/9Bv3m/Pb8Hv1H/Yn91P30/en9vv2W/WX9HP3s/PP8CP0T/Tf9af2q/dn9yP2a/W/9Uv1B/UD9T/1f/WP9b/2S/aT9if1n/Ur9QP1F/TL9LP1P/X/9qv3C/bL9j/1v/Uj9Hv0U/Qf97Pzw/Bz9XP1a/qMB4QW5CTANcBCaEzAWSxf+Fn8WiRZhF1AZchxrIGck1SeDKi4sUiz3KsIoiSbvJL4joyKXIZEgeB8KHgocZBk8Fg0TZBCADhkN0wupCm8JCQhmBo0EwQIiAbz/of7i/Y79lf25/eL9C/4l/i/+Rf5m/oj+ov6H/kz+8P1V/bD8SPwn/EL8jvzu/GH95P03/iP+xP1D/Zv85/to+zv7YvvH+0r81Pw5/VX9Tv06/ST9JP0d/RD9Ef0p/VX9cP1f/ST93vyg/HL8Xfxv/Kj82vzZ/L78oPxp/BX8uPtr+0L7LPs5+3T7v/sB/C38RPw+/C78E/wE/DD8WPxh/KX8Df1F/WL9cv2Z/ef9Gv4Z/iv+Zv6q/tD+5P77/hD/Gf8U/0H/kP/A/8H/sf+j/6T/pf+T/4L/hP+h/8f/0f+3/4L/Pf/6/rL+Xv4c/gb+I/5T/nH+dP5f/iT+sP0l/cj8nPx1/Ff8Wvx2/J78y/y+/HD8H/zW+6T7lPuw++P7EPw8/E38Tvwx/P/7zPua+5H7pfvM+yL8ifza/AH9GP0P/bL8Tfwg/Bj8RfyO/Ln86/w6/WX9bv17/V39Hv3f/ML83/we/VP9VP1F/Tn9Lv0s/R39Ev0W/R39TP2R/av9lf1b/S79GP0U/Qn94Pzc/Bn9af2Y/ZT9ZP04/TX9Pf1H/V39Uv07/Tv9U/1w/X39X/0m/Sf9Q/1W/XH9lf2p/Z39a/1C/Vb9aP1f/VL9Uv19/aX9rf2Q/Wj9TP1B/Vn9bP11/Yb9pv3G/bz9kf1u/Ur9K/0W/Qv9IP1S/ZL9vv3S/db9sf1m/Sb9CP37/Pr8D/07/Wb9df15/Yj9kP2N/Xj9YP1O/UP9RP0+/TL9If0f/Sn9Mf1K/Wv9gf2R/Yv9bP1K/SL9C/3+/P/8Gf03/Wf9m/20/Z79dv1i/Tz9E/37/Av9Q/14/aP9vv3I/bD9ev0+/Rf9C/0V/Rv9JP1h/az93v3Z/bL9g/1N/Rn99/zx/Oj8B/09/Vn9lv3h/eX9t/2P/WX9Of0T/e/86fwH/R79Sf2M/cb94f26/XT9YP1r/VX9HP37/AX9L/1q/YH9e/11/Yb9p/2m/X/9UP03/S79L/04/Uv9VP1a/X/9rf24/Z79dv1H/TH9Sv1Q/3UDwQevC2EP5RIFFvYXTBitF0EXeReZGC4bDR9aIzAnICoxLDct2ywnK74oqyZlJW0kWyM+IhMhqB+tHQEbzheCFIsRLA+VDYsMmQt2CvoISgeRBagDkAF1/7H9m/wz/ED8gPzM/DD9m/23/Yj9af1r/WP9UP04/R/9+vyX/BL8wvui+4j7ivvZ+2H87fxY/YD9a/0c/Xj8wfth+0T7Rft0+7b7+vtU/KL8uPy8/Mn81Pzs/Cn9e/2p/Yv9Tv0N/bD8S/wD/O77+/s4/J/8/Pw1/R39s/xD/OX7iPtD+zz7iPvw+zf8Wvxd/Ev8J/zn+6r7pfvT+yb8tPxS/cz9C/4J/vP9yv2O/W39cv2k/RT+l/77/lf/mf+Y/4T/cP9S/0r/U/92/8//NABdACMA2//C/57/Zf81/zT/bf+y/8n/s/+S/0j/2P5m/gH+0P2+/cn94/3y/ef9tf1f/fv8vfyN/Ff8Svxu/JP8o/x//Cj83vu3+7/73Pvz+wP8I/xU/HH8WPwJ/Mr7qfuh+8j7Efxo/Mb8B/0A/cz8lPxO/Az8/vsl/Hr84vw8/Yn9vP2i/UX97/y+/Jr8d/yB/Mv8Q/2s/eH96f3Q/ZX9QP36/M38xPzS/Ob8Hf2W/fj9Cf7r/aj9Wv0U/e38y/zF/PP8Hv1T/ZX9yv3k/cf9hv1R/UP9QP01/SX9MP1x/aL9l/1n/U79ZP1//Xv9Y/1v/Z/9vv3M/bz9l/15/XL9d/1w/XX9dP1z/XH9ev2G/XD9Yv1l/Yz9vv3d/eD9vv2R/Vn9Hv32/Nn82vwU/Vf9jv3B/ef98/3I/Xb9QP0j/e78xvzZ/DH9if2Y/YT9hP2C/XH9a/1r/W39UP0h/R79Rv1p/Vr9IP0Y/Vv9kP2Z/YX9e/2H/Xb9L/33/AT9Kf1C/Uv9YP2U/a79lv16/Xr9ff1S/SH9Mf16/bL9m/1k/WH9gP1+/VL9Nv1D/Vr9eP2Z/cP92/3X/bb9ev1F/R798/ze/Pr8K/1b/Yn9u/3n/fL91f2Y/Vb9JP0Q/fr83fzm/Bz9d/3J/d391v3O/b39oP1x/UD9Ev0N/TT9V/18/aH9rv2T/W/9UP0+/Un9Tf1e/ZL9wP3J/aj9dP00/ff81PzV/PT8K/16/bn+cgLwBsUKHw5MEY0UOhdZGBcYvRfqF7cYmxrJHcUhpyXcKF4rJC2uLYMsJirPJyEm0SRbI64hHiDIHj0d+Rr5F9AU9BF7D3AN6Qu5CmgJuwfKBdsD/gH8//j9Tvw3+736xvoH+0H7ZfuH+6H7wfvj++r7+fsK/BH8AvzJ+2D76PqX+nD6kfrq+lD7tvs6/Lr89vzp/Iv8CvyR+zL78vro+if7cvvT+1b8w/z//Cn9SP1M/UL9K/0l/S79O/1F/Uv9Xv1d/UD9Ff30/Mz8mfx4/Gv8c/x//Ij8oPzG/Nr8v/x2/Cb87fu8+5j7mPu/+/X7Mfye/B79df2c/ZP9if2F/Wb9SP1N/Xb9q/3j/SX+bf60/vz+PP9n/2v/S/9V/5j/vP+z/5z/kf+0/9r/2f/A/6z/qf+a/4r/sf/P/6n/jf+W/5z/dP8P/5L+Q/4M/r79fv1h/Vv9cP2X/bv9tf2K/Tr92vyE/D38/vvK+6f7q/vc+xz8R/xQ/E38RPwq/Af87Pvp++H72Pv/+zT8YPyE/I/8kPyX/JL8cfxO/D38Ofxf/Kz83/wD/Tj9df2l/bP9bP31/LH8jfyG/KH8zfwD/V79vP3b/eT94P24/X/9RP0I/fL8EP0x/U/9cv2B/Xr9bf1e/Vr9VP1G/VL9gP2r/b39r/14/Uj9MP0n/ST9Ev0I/Sv9Z/2n/cr9y/2+/aD9dP1a/V79UP09/Tn9QP1m/Zb9sv2o/Zr9i/1//XT9Tv06/UD9Uf11/Zn9sP2+/cn9w/2o/Xn9Nf0J/Q39KP1W/Yf9sv3T/dL9r/2Q/Xr9Uv0Z/Qr9Kf1H/VX9Xf15/Zr9kf1s/V/9Vv01/R/9Hf0m/Tb9N/0y/Ub9cf2D/Xj9c/15/Xn9YP1I/VP9Tf03/Sz9I/04/V39eP2F/ZH9p/23/bD9kv1j/Sf97Pzn/Ar9O/1v/ZX9yv36/fv9x/2O/U/9CP3o/Or8DP09/XP9l/2z/dD91v2w/Xn9YP1j/Wb9Wf1A/Sr9Jv0p/UX9bv12/Wv9eP2u/eH91v2a/Vz9Pf0y/QX94/wE/Sz9R/1r/Zn9vP3G/a/9if1f/Sf9BP3+/Bn9N/1Z/Xj9f/2D/X39ZP1X/Uv9Mf03/Vf9bf11/ZT9vv25/bj91f8lBIwIdQwvEOETchfdGXAa/hmrGdcZ0ho/HfggIyX5KB8sji7lL5cvqS3xKpUovCb+JEIjiiH1H2IeaRzOGZ4WKhPYDxMNEgtvCdMHGAZSBKAC7AAx/1n9mfst+hb5bfhG+Hj4xPgi+Y757flT+sT6C/sf+yD7Dfvf+p76Qfr1+dv59fk7+pj6+vpg+9L7Q/yR/JH8T/zy+637gftP+0v7aPuP+8n7Ifym/CH9Y/2V/eX9Rv50/l/+NP4G/tH9hP0Z/dH80vza/OX8DP1B/Vn9UP0x/fj8u/xo/Br87fvj++377PvT+9D77/v8+wH8D/w2/Gz8svzy/Cv9aP2U/aj9of2f/br90/3h/f/9NP5v/qz+8/40/3f/oP+w/73/uP+0/7P/pv+k/7H/t/+w/7X/xP/U/9L/r/+a/4//dv9M/x3/Df8B/83+jP5U/ij+9P2o/V39QP1F/TP9Af3s/AL9FP0B/b38afwh/OP7nPt5+5772fsA/BL8JPxQ/Gr8NPzZ+6z7zvv3+/r7DPw5/Gz8ifx4/Ez8QvxO/Fv8m/zo/AX9FP0f/RX9DP3//OL8w/zA/Pz8Rv1u/Wj9Sv1H/Uj9Ov0t/S39MP1A/WL9cP1t/V/9Pv0d/Rz9IP0n/TL9NP1H/XD9iv1w/VT9K/0M/Rj9D/0M/Tr9Z/1+/ZD9i/1//YX9Y/0k/RX9LP0+/Vj9Yv1R/VX9Y/1X/VD9UP1R/Wr9jP2z/cf9w/2X/Ub9Bv31/P/8Gf0v/UT9g/3M/fn99/3B/XX9P/0I/dr87/wY/TP9Xv1+/Yj9kP1+/VH9JP0Z/R39Kf0+/U39XP1b/Tr9Cf3//An9DP0h/Uf9av2A/Yf9dP1N/R/9+vzo/Ov87vwA/TD9X/2D/aX9if1P/Tj9Lv0j/Rj9C/37/Bn9SP1b/WH9av1r/WT9Xf1C/Tv9Ov0y/TL9Mf02/UL9Tf1K/VX9dv2P/Yb9c/1j/Tv9E/0L/Qn9Dv0o/Ur9bP2J/Zj9hv1b/Tz9M/0p/Rr9Ef0m/XL9ov2L/VT9Jf0d/SX9F/3//Bv9af2c/Zr9e/1k/Uv9Ov0w/R79Lv1E/UP9Sf1d/Vj9I/3w/Pb8R/2U/aj9nP2Z/aT9gf0q/dX8nvyW/Mf8H/1z/aP9kf4yAiYHmQuLD1ITLRexGqkc4RySHJwcTh0mH3MixCY6KywvcjLNNIc1QjSQMYYu7yvUKd4n5CXuIywiXyDyHaMasxatEhIPMAzUCcYH8QU4BGgCcwCE/ob8dvp/+AX3UvY09lb2lfb69qb3efgL+Vf5nvnV+QL6Lvo8+i768vmJ+UP5PfmD+Qr6k/oW+6f7L/x8/In8Qvyy+xv7pvqU+tX6JvuG+wH8g/z+/FX9eP2I/a398/06/n3+l/57/kf+Cf7M/W/99fyj/L/8Hf1r/ZX9nv2B/Tz9vvwZ/Ij7Jvv3+gT7VPu4++j77Pvc++L75vvB+6T7uPsI/H/8Af1o/aD9oP2C/Xn9kf2u/b/9AP5p/tL+Ef8x/0D/Sv9r/4z/qP+7/8j/6/8SABcA8P+4/5X/i/+Q/5b/t//V/9z/5P/i/73/XP/n/pz+bf40/t79hf1l/YP9pv2T/Uz9Cv3e/Lz8ovx6/C/85PvC+7X7wvu++4f7avt7+5T7qfvK+9r74/v++w38Bvzw+8f7ofus++r7JPw9/FP8efyk/L78wfyq/In8hvyc/LL8ufzA/Mr82/zx/Oj81vzl/BD9M/06/TT9PP1I/Tv9Hv0O/Rz9Jv0d/Qr99fwF/Sv9QP1Y/Wb9hv2n/Zj9gv1m/TP94/ye/Ij8nPzp/Cf9Tf2o/e/90v2R/U79+PzD/K38mPzO/Cn9Rf1N/XL9if1Y/fb8p/yd/N/8Kv1A/VD9j/3F/aH9Qf3y/Mz8yPzH/ND8G/2C/ar9of2x/cH9hf0X/dD81Pz7/BD9FP0n/Vz9f/1r/UH9Hf0R/RL9Df0T/SL9J/0c/RT9Ef3x/MX80/wh/Vb9W/1X/Vb9Vv0r/cr8d/xv/JX82/w0/YL9wv3N/aj9df0p/bz8R/wU/FP85Pxg/Y39j/2i/cL9pP1G/en8q/ym/Nv8Jf1R/VP9R/03/Tr9Mv0A/dv87fwz/Xf9kf1+/Wb9Rf0I/d38wPyd/I78pfzu/FP9kv2p/aT9kP1e/RL92/yr/Iz8d/xx/Kr8BP1Y/ZL9q/2k/Yj9X/0d/eP8xvyu/K38yPzw/C79bf2E/W/9U/05/Sb9B/3e/OL8BP0W/TT9X/15/Wn9Mv39/OP86PzK/KT8yvww/Yn9oP2H/Xb+RgIzB6YL9w+BFCUZJB1lH9Qfzh/bHzQg5CF0JR4qyC7sMmA2HTlEOhc5MjbuMjMw3i2fK1gpQSdRJR0jRiCoHHwYMBRKEAkNbwpVCGUGRATnAZn/Z/0z+wn5Lvfs9Vf1OvVX9aP1HPaQ9tr2Dfdk9/z3kPjz+Ff5o/me+Vr5BPnP+NX4Cvlh+eP5hPoX+3b7ufvh+9r7k/sV+8P63/oj+1P7cfu4+zH8mPz8/GD9xv0y/nT+i/6h/qr+dP4g/u791P2l/Wb9L/0f/Sv9Kv0K/dL8mPxs/FX8SPwt/Oz7jftF+xf79frS+rj6z/oI+1P7tvsR/FP8h/yq/MX84Pzt/Or8Av1Y/bX9Ef5L/nT+v/74/gj/F/9E/3T/qP/j/wcADAAAAPT/9f8XADQAQABRAF8AWwA6ABMA3v+O/zT/9P77/j//Yv9B/xb/3v55/vj9cP0L/d380vzh/AL9G/0M/dP8cPzo+0/72fq4+uH6NvuX+/r7NPwt/Oz7evv/+qn6fvqF+sD6Ivuk+yX8d/yF/Fv8DfzG+537i/ub+837D/xh/K381fzX/Ln8sPy1/KX8pPyu/LD82vwE/ff84/zo/Oz8BP0o/Sz9JP0c/Rj9Gv0P/fH84Pzn/Or8/PwY/R79Ev0B/Qn9Jv06/Q79zfzX/AH9EP3s/Lb8qPzh/DT9Sf01/Rj98Pz5/Dj9Rv0N/dL8w/zd/Az9Hf3z/Mz84vwv/YH9pP2A/U39T/1f/Tf94/yg/KP80fz8/Bb9O/1Z/UD9Hv02/Wj9Yv0r/QH9BP0x/Tr96fyI/GX8bfyH/L38/PxC/Xz9kf2d/aT9Z/3d/Fr8D/wM/FH8l/y9/Pf8P/1r/XH9SP0E/cr8svyt/Kz8tvzG/OP89Pzx/OH8yfzB/NX8+vwm/Un9UP0+/Rz9A/3u/M/8xPzA/Lv87/xU/Xj9U/01/SH9AP3Y/Kj8iPzA/BP9L/1B/Vz9Tv0r/Q797PzB/KD8ePxv/L38Ef1E/Vv9WP1M/Vn9cP02/d38rPyn/MX82vzr/AD9Ef0b/S39Sf1M/TD9Dv0P/Sv9KP32/MH8qfyk/K78v/yz/KT8zfwX/X39qv1n/Rj96vzQ/L/8r/yO/G/8hPzQ/Cv9Xv1S/TP9O/1d/Vb9Fv3h/K79iQHmBuQLlBAsFcAZwB0cIIkgRyBdICQhJSPDJokreDDHNCg4jzp3O2A6sTeRNOwxzy/FLXsrNykWJ7skuSHVHW4ZBxX+EJgN/QrkCMwGiQQ0AvT/s/14+1f5Z/fm9e30ifSU9OD0UPXf9ZX2OPe29xv4hfje+OX4s/h9+FD4PPhG+G343fh2+dH5/PlF+o/6svqu+of6gPqs+tH6+foq+0n7TvtH+3H7zvsw/Jn8E/2g/Tr+of61/pL+W/4u/hf+Af62/Vn9Ev37/Pz81fyU/Ej8F/wJ/BT8N/wv/Of7oftw+zb78vq8+oz6g/q4+gX7c/vb+yD8YPyx/P38IP0q/UX9iv3U/fv9D/4t/kz+ef6k/sL+A/90/+L/CgAQADkAewCbAHMAOQAsAEQAPQAUAA8AJgAfANr/o/+z/9L/vP90/zv/Nf8w//z+lP4f/tX9h/0W/b78mPxn/Df8I/wa/Bn8D/zr+7f7lvt9+1T7Hfv1+t363frZ+rT6p/q3+tD6C/tN+237lPvR++/76/vj+7f7f/tb+0P7TfuI+937Kfx0/LT80/zN/Ln8lvxX/Cn8Ifw1/GH8q/z5/C39Ov0N/cP8lPyG/H/8hvyq/Oj8O/2O/bH9hP0a/bf8dPxH/DX8PvyF/Pb8Uv2C/Zn9jP06/dH8ffxS/Ev8aPyu/Bz9fP2N/W39RP0E/aP8RPwc/FP8xfwu/Xv9tv3I/af9b/0V/bv8avww/DX8gfzn/C79Rv1A/UX9TP1A/Sb9B/3u/OD87Pzz/Mr8jPxj/Gj8lvzI/AD9P/1u/X39V/0e/d78hvxL/EH8WfyQ/NH8EP07/TP9Af3H/KL8nvym/JP8lPzZ/CX9Of0W/dT8mPyB/Gv8cPyd/Lv8z/z9/Dv9Sf0P/bv8hPyN/Ln8zvzY/N/83/zk/Oj85Py+/I38lvzS/Bz9Uv1N/R39AP32/Nf8jfxK/Fb8qfwY/Wr9fv1e/Sv96vyw/JP8ePxV/F38q/wv/Yf9Z/0l/fz80fyh/Gv8P/xT/LD8Av0l/UT9Tf0l/fX83/zK/Kv8hPx4/K/8AP05/UL9HP3y/OP81PzL/L78nfx7/IP8yfwI/Rn9F/0h/TH9Jf3f/JH8hvyx/ML8tPyx/M/8Ev0z/RL99/zl/Pj8m//0BJoKzQ+2FIkZMR5/IUMiiSEdIX0h+SIRJssqZzDQNVI6sz2APxw/fjyzOEk1ojI4MLktSisoKT8n5iSIIUgdsBhSFIUQag3NCkgIrwX8AkoA1f2i+3r5Zve49cz0l/S19M/0BfWP9S72mfa79vj2hfcS+HL4ivht+EP4BvjV99j3DvhN+Kb4N/nv+Z76+/r6+sD6dfoQ+p35OPkR+VX5+fnM+qT7V/y9/Pf8Lv1h/Y39k/14/Xb9nf3r/Tj+K/7B/VL9/fzX/Ob83fzI/MP8vvyg/Ej8uvsW+6H6iPqZ+r366Pol+3v7u/vM+6j7Svv2+t36Efut+3H89vxe/eb9W/6I/mX+J/4L/hP+Nf54/vD+hP/w/xwATQCCAJMAbQAqACYAXgByAEkAQwB/ALUAmAA+AAsAAADa/4b/SP9Q/2n/R/8A/+X+zv5n/sn9I/2q/H/8XfwW/P/7KPxK/Ej8F/y4+1P7EfvO+pD6ePp7+nr6b/ph+oD6x/rS+q/6sPro+in7OPsf+yP7NPst+x37Efsm+2X7rfvV+wL8PfxV/En8NPwm/Cj8HvwY/C/8YPye/Mv84fzv/Pf83vy//J38iPyM/JH8nPy7/OT8Ef0r/Sn9Fv34/Nj8wfzB/MD8vfzP/Nn8wfyn/Jr8nvyi/KP8wfz1/B39J/0b/ef8tPyU/Ff8MPw2/GD8sfwL/VH9a/1b/S79/vzd/MP8o/yD/IL8rvz1/DX9S/1M/UT9Gf3k/M/8s/ya/J/8oPy3/Ov8D/0c/fj8yPy0/J78cPxH/E38kPzm/P385/zj/PD85PzD/Jn8dfxf/GX8kfzE/Pj8/vzU/MH8yfzE/Lv8rvyM/JH8wfzh/Nv8xPy0/Jn8ivyN/I38mfyo/L/8xPzB/Mv80vzO/Kn8m/yx/M38yfyX/H38mfy8/LH8m/ya/Lf83/zr/PX8Df0G/dX8tPyj/JD8i/yD/In8u/z4/B39Ov1F/RX90/yy/Kz8mfxz/GH8dvy1/OX8/PwO/Rf9Dv3n/M78xPyS/GD8TfxW/IT8pfzZ/Bv9Qf1V/Tv9Ef3s/KH8Tvwp/Cj8TfyP/Nv8Iv1X/Vz9Mv0V/er8lPxI/Br8Ivxo/Kj8yfza/OT8+/wT/RD94fyf/HL8W/xq/I38tv3/AdIHag2uEsgXwhz+IFwjjCPrIqoiQCNvJbMpVi8nNUo6Yj5DQVNC7UCCPY05NzaKMwsxli5eLHIqQygjJf4gFxz7Fm8SvA7DC1wJCQePBBYCi//2/F76wfdV9Yzzt/K68kTz/fPb9MT1dPbX9v72Bvc59333kfek98D31ffb9/L3JPhX+Jj48/hJ+bL5P/qo+tb6wvpK+qT5Qvkq+Tz5hvn3+Yn6UvtD/Aj9iv3C/aT9m/3O/fL97v3m/en9//0s/jD+3f13/SX92/yq/IH8Z/xc/Fb8M/zp+6f7aPsY+7T6YPov+ib6Tfp++qj65fo2+2v7tvsG/C78Y/y5/BP9Zf2y/cX9uP3R/fP9D/5E/pn+Ev+M/wkAfwDWAAoB6QCUAEkACgDI/7b/4f8gAGkAvgDvAOMAvACHAD8A2v9P/73+gf6U/pP+YP4u/hb+7v2Z/R/9qfxE/Pj7yPu5+7P7jPs/+/L61frV+rT6dPpP+mb6kfqs+qn6fvpc+jv6LPpV+o/6y/r++i/7VftS+zn7JvsW+xj7Nfto+7/7GvxZ/G78Z/xA/O/7pfuF+7D7FPx6/Nn8GP07/T39B/2y/Gb8JPz++xL8XPzK/Cn9XP1c/Tb9+Py6/Hf8Ofwh/Dn8gPzN/A79KP0v/ST98fyN/Dr8I/wb/Cz8SPxy/L78Bf0y/Tv9FP3d/KH8bvxy/I78hvyH/Kj8zfwE/R/9/fzk/OD80vzc/AL9Dv0E/ev82/ze/Nn8vfyE/FX8bPyq/Oz8Fv0T/Qr9Gv0k/fH8m/xF/AP8A/w6/Gr8hvzC/AL9Gf0l/fT8hvw5/Bj8HPxU/IT8e/yM/Nv8HP0i/dr8XfwI/BP8Sfxi/GP8ePyz/Pj8J/0j/ef8m/xg/Dz8Nvw4/Cz8MPxi/M38JP0z/Qr9zPy6/L/8qPx7/Fr8V/x3/Kz84Pzs/NT8wvy0/LL8w/zL/ND83vzv/P78E/3s/ID8IPwb/GP8jfyI/Iz8xvwd/UP9If3o/LP8efxK/Ej8bPyP/KL8oPyr/Lz8vfyv/KL8wPz5/BX9Bv3b/J78e/xr/Ff8QvxV/Kj8D/1R/UL9Gf36/Mn8Z/z1++f7I/x5/M385/wC/R39BP3R/L/8s/x5/Db8Lvxj/J78nfxt/G38tPzr/SACDQjVDUITghjFHUAimCS6JDMkPCRAJZ8nvytpMYU3Cj1yQYBEuUVCRI9AVTy2ONM1PDOXMCAuFyznKd4mwCKyHTUYBBOnDjYLcQjfBUgDxABh/gf8kfn89o70uPK48WnxpPE+8v/y6/Ph9L31bvbl9jL3d/ex98H3k/cz9/D27fYe95b3Pfjs+LL5ZvrO+tD6ffoB+n359fie+KX4CfnZ+cX6jPsb/HT8tPzu/C39g/3h/T7+pf4H/1X/Tv/Q/hj+gP09/Sj9B/39/Dn9c/1r/Rv9kfz3+0v7kPoQ+uX55/n2+QL6MfqI+rb6mvp8+pr60foB+1D7zvtA/Hb8mPzj/E/9rP3E/cT97v1V/r/+/v5G/5b/yf/z/z8AiwChAIoAZwBbAGsAaABNADoATwCGALUAwgC2AKEAcQAlANf/f/8f/7T+Sf4N/gj+A/69/WP9D/3F/H78JvzW+3v7Hfva+q/6pvqy+qX6g/pi+kv6Rfol+uD5qfmZ+a354vkr+nX6wPoX+2z7g/tT+wL7pfpt+nP6kvrc+m77+ftb/Kb8wPy1/Iv8Ivy0+5T7tfvx+0z8rPz5/Az91fyS/HT8cPxu/H/8u/wI/Uz9e/1p/Q39pvxH/P776fv8+zn8nvwF/VT9gf1k/Qn9pfxL/Pr72Pvq+wT8Qfyo/Pr8JP0m/eL8jfxk/EP8MPxK/Gz8kfzF/PT8Fv0r/Q79uvx//Gr8evyY/Kb8sfzD/Nb81/zK/LL8tPzf/AT9Df0B/fn86fy7/Gj8Kvwt/D78WPyS/O78WP13/UP99/yw/H78RfwJ/A38Q/xt/Jf8zPzz/Aj96PyO/Ef8Qfxc/F78Xvxz/JX8u/zS/Mf8t/yW/F/8Pfws/C38Ovw+/Fn8q/wV/Ur9Lv3o/K/8jfxQ/PT7yfv0+zz8dfy7/Av9Of0t/fD8pPx3/H38gfx1/Ib8o/yW/Hz8jfyQ/Hr8a/x+/Mf8Ef0c/Qz9Av3a/Jz8Yfw4/CT8Nvxp/L78Ff0i/QH94vza/Mn8pfxv/EP8Y/yb/LH8x/zd/Nv8x/yp/KT8tfzK/M78sPym/Lz8uPyP/HD8avxn/Gv8gfyn/M/84vz5/AX99PzK/In8Xfxf/GL8YPxo/Hz8svza/Nf82fzS/K78qvyw/Ij80v2FAqAIiA5DFMwZPB/MIyImXiYgJiYmziYuKb4tqjO7ORU/c0OWRqxHD0ZtQkc+jDpXN140djGuLv0rKCnaJa4huhxsF2USIA6zCuIHJwUuAiP/VPy/+UX35vTQ8mXxyfCy8BPx3/Gt8nTzP/T29Kn1Pvao9g73bfei95D3RPfz9tv2BfdT99z3lfhd+Rb6kfq8+rT6gPoI+k/5r/iR+Nz4XfkY+g/7BPzX/Ir9Af5W/pr+qf6g/rX+0/7l/tv+sv53/j/++/2Z/Uz9Lf0i/Qn9yPxo/AL8m/sk+6T6Nfrr+a/5mvm9+eT59fnt+dj58/lC+qL6H/uc+wv8cvzj/Ev9bf1W/TH9Pf2H/e39Qv67/oH/QgC0AMsAvAChAI0AawA3ACoANQBaAKgA/QAyATkBHgHfAJsAXwAnAO3/2v/U/7j/iv84/+H+ff4K/n/9/vzA/J78c/xf/Fv8Lvzs+6T7TPvh+m36BvrN+bv5nvl++ZP5y/kM+k36Zvpu+nn6bvpP+kn6Kfr1+fH5J/qM+vH6Pft++7j75fv4+//77fuv+2/7VPuS+wT8Tvxm/HH8jvy1/Lv8lvxm/Db8OPx9/M788/wC/Rj9CP3l/Lz8jvxm/Ej8OfxX/Lv8Gv1I/UX9G/0C/eb8pfxi/Dv8GfwX/Ev8ify8/ND80fzU/Pb8Gf34/LL8evxp/Hn8aPw2/CP8MvxS/JX89/xb/XL9Vf1L/Tj9DP2o/DT8A/wY/DT8VPyn/CH9eP2S/Xv9Xf09/ez8l/x3/IT8nfyZ/Ir8t/zs/NX8hvxN/GH8mPy9/MD80vwK/S39+Px2/AT8w/uK+4r73/tE/I/81PwQ/TP9Nf3c/Dn80vvV++77FvxZ/ID8q/zS/Nf8y/yt/Iv8Zvxo/H38gfyT/J38p/zB/MD8p/yH/H78kvyC/Fb8OPxa/J/8xfzQ/N78/vwP/dr8ePwx/Bv8LPw6/GX8u/wY/UD9OP0c/dz8hvw7/AP8+vs//Jz82vwn/VL9Jf3d/JL8S/wg/Cb8Ovx0/MX8Fv1T/Uf9+/yJ/D38P/xX/Gb8jPze/Cr9NP0H/dT8sfx6/DL8M/x//NX8AP36/Pz88/yt/Df89Pvz+yT8dfy8/P78J/0x/fn8oPxb/CH8/PsT/GP80Pwi/Sn9xP6fA5wJGA9nFPoZzB+wJP0m+SaIJoUmKCdSKa0tqjPtOW8/+UNBRyxIJkYVQo89sTlNNg4zEzCqLaAr/SgsJUkg3xp7FYAQUAwKCWUG/QOCAeL+IPxD+WT2lvNJ8envcu/J77Dw6PE980r00/Q89cL1TfbA9vj2HPdh97f33/fg99T30Pfu91r4/fiy+XH68PoL++j6kvoO+oL5HPnp+C359fnx+un7u/yF/U/+1v7h/rj+n/6z/tn+5/4O/0P/Qv/8/rT+lf5r/uX9Rf3p/MX8vfxz/PT7d/sB+3v66/mJ+UL5HPks+WT5zvlX+qj6wvrZ+t/62/rq+gz7W/vo+3v8/PyO/Rj+av6V/qT+s/7o/iX/W/+e/w4AjwDWANEAkgBtAHoAigCSAJsAqgDNAAUBFgEPAeIAmABQABAA6f+2/4f/WP8L/6X+Tv4T/rf9Uf0b/fz88vzF/F38+vua+wP7Wfrj+bT5w/nR+e/5Nfp4+pP6dfop+tr5oflr+U35ffnW+Sr6cfql+uf6Kfs8+yf7I/tJ+3H7kPuu+7P7w/vp+/T74PvO+9X7/vtR/LX8//wK/eD8zfzF/K38gPw//Av8KfyS/On8FP0l/S39Lf0O/dH8n/yI/JL8vPzm/Pr89Pzh/L38mvyB/EP8CfwY/F/8s/z7/DP9N/0b/ez8mfxJ/P/7t/uv++j7Pfyo/P38Nf1i/XL9Vv0N/av8Vfw1/DT8LPw1/GT8ufwA/ST9R/1b/VL9JP3b/Lb8yfzD/I78bfyI/KT8wfzV/Lj8mPyM/Iv8svzx/Af9A/0K/Qj97fzJ/Iz8PfwH/OX77fs4/Iz8svzE/P38Iv0A/dH8lvxW/EH8N/w1/Gj8lPx//Hj8hPyH/Hj8WvxV/HP8sfzs/Az9//zY/Lv8m/yF/H38ZvxQ/Fn8cfyc/PD8E/3a/JT8ofzF/Nn84vzV/Nj85/zp/Lz8a/wo/Pz7CfxE/Iv84Pws/WX9iv2C/Ur91Pw//Or73/v9+0T8o/wF/VT9Y/0v/ej8sfyK/Fr8NPxV/MX8Of1q/Vb9DP2x/GH8BfzP+/b7PvyQ/AD9dP2v/Yn9C/1x/CL8IPwf/P77FvyA/Pv8PP0N/bf8efw2/Ab8F/xg/MD8+vzz/OX89vzq/Jb8GvzY+/L7OvxB/mQDoAmFDxsVhxrxH0ok+CV2Jcok6yQSJtkoii2aM/45jj/SQ5lG8kZfRAhAwTtXOHQ1fzKDLwkt4yo7KF0kNR90Gd4TEQ9cC4EI9AVXA7sAQv69+//48vX78tHwr+9k78/vofC68TDzmvS49Xn21/YU93/35fcH+A74Gfg6+Hn4wfgb+Y358vlR+rD6DPtc+237UPsh++H6k/pT+k76ovoR+2z75PuS/F79Hf6w/hD/Tf+G/6L/tv++/4P/Gf+4/ov+Z/4P/pX9Rf0+/S796vx5/PX7bvvP+hv6nPlO+Q/56vju+ED5kvmj+aD5v/n8+RL6GPpY+sf6Q/u9+0z89fx+/cf9/v04/nj+pP68/t/+Hv9s/6r/AwB6AM0A+wAOARUBFgEAAdMApwCoALgArwCZAJoArgCqAH0AJQDL/5b/hf9i/zL/7v6Q/jf+0P1v/QD9fvwL/LT7kvuF+3D7OvsK++r6tfp3+ir6zvmH+Yf5p/m7+dP57/kD+hn6F/r4+ff5Evo5+m36ufog+337uvvZ+8f7k/tg+z77NPtA+3b72PtJ/Kb89/wq/Sz9CP24/Gv8QPwd/Az8Lvxy/Ln8/fw5/VH9U/1A/RD97vzY/Mj8tvya/In8lfyg/JT8jvyo/NL88Pz1/Ob8z/ya/Fn8QPxC/Dj8Ffz8+yb8mPzx/Nr8mPx6/In8rPy3/IX8bfyi/Nf86/zX/Kz8ifyB/JH8vvz1/BL9J/1R/Yn9lP1D/b38avxM/Fr8kPy6/N38D/1N/WD9TP0Z/cD8hvyP/Kr8zvzu/OP82PzN/Jv8Xfwz/A78Fvxh/M/8Mf1W/Tj9Af3k/Jr8LPze+7L72Psu/G38j/zB/Ob81/zK/Lv8rvyi/Hz8Vvxo/Ib8aPw8/Dj8YPyQ/LD8u/y7/Mf8tPya/I78e/x5/JL8tfzf/Af9D/0H/db8kPxi/Ev8SvxY/IT81Pwj/Tv9Mf0r/RP91PyI/GX8bfyM/Kb8u/zR/NL8xvyw/J/8lvyV/J38qPy3/NP89vwM/ff8tPxn/EH8Uvxq/Gf8Vvxj/Jf8w/zo/CT9Pf0X/eX8xvy3/Ib8Svwa/Cb8avyU/KX88/xj/Yv9if1j/QX9jPw9/Bj8L/yA/J38kvyx/AX9Pv1I/RD9pfxw/G38gvyQ/L/8TP+fBHgKChCOFSwbjyCEJAEmxiVqJXgljSaMKZIupjSGOps/xENZRlNGlkNMPyQ7vzejNH8xjC4SLLApoyZqIkwd3RenEhwOZwqCBxcFlwLu/zj9a/qP97n0QfKQ8OPvA/Cc8KPx7fIe9O/0hfUD9oX2IffI94z4Wfn0+Tv6Jvru+cD5evlb+Z/5Dfqb+kX75vtk/KP8dPzx+1n7z/pu+lL6n/o3+/j7y/ya/U7+/P6c/+T/xv+Q/2b/O/8g//L+tP5+/kr+Bv7L/ZH9K/2q/BX8i/sg+636Ifqy+X35ePlu+VD5NPkg+Q75/Pjb+Mn49vhL+cz5b/or++37ofwN/Vn9jf2B/W79dP2u/Rj+l/75/nP/HwC0AP4A8QDJAKcAdwA3AC4AQwBoANsASwGIAagBdQEDAZgAMwCx/yz/8f4S/2r/q/+3/3f/B/+A/uz9UP2s/Cb83vvg++77zfuL+0f7CPvC+nj6NPr++f35Ivo++lb6Tvoc+tX5rPmz+cn57/kK+j76rPoY+2H7hPt1+2H7ZPtj+177dPuS+6H7sPvZ+xn8XPyG/JX8mvyp/Lf8qPyo/Lj8uPyx/Lb8rfyr/Lv8yvzL/MT81Pzp/Pv8Bf3//AP9BP3r/LX8fvxk/Gv8cfx5/JX8u/zO/M78xPyr/Jj8YPwJ/Nn76/sg/Gj8tfzq/AX9Ff0B/dn8s/xv/CP8+vsS/EL8d/y4/Ab9Y/2i/aj9X/0C/cr8lvxl/FL8X/yG/M38Iv1m/X39a/0p/fH82fzA/LH8nfyi/Nz8G/0o/Qr91/yw/MD80vy5/KL8uvzi/PH83fy8/JX8YPwz/DT8b/yy/NT81Pzl/AP92Pxr/AH8yvvR+/b7H/xr/Nb8If0x/SX98/yu/Ij8TvwV/Bf8L/xW/Jb8zfzb/NL8sPyg/Nn8DP0H/fL86vzj/Mf8mPxh/DL8Kvw//HL8u/zz/BT9NP1i/Xj9Rv3L/GL8Nfwi/Cn8Tvxu/J/81/z+/Cb9S/03/eL8kPxd/GL8iPyW/Kz8wfzj/Oj8yPyy/KX8kvx1/Ir8vvz0/BL9Ff0Q/f383fyl/Gz8Xvx+/Jj8tvzF/MH8wvyx/Jv8mvym/MP89Pz//Of82/zN/Jf8Q/z4+9b78/tI/L78Ev06/W79hP1R/ev8d/w3/Cb+NgNDCTIPFhXkGnQgoiRNJg0mVyUKJesl0Ci/LcEzujkKP1tD9UXvRTNDDz8IO4k3YTRqMa4uPyzWKbYmdCJTHcsXZBKsDfoJPwcJBcgCRQB2/ZP6tffJ9CDyOvBU713vHvBb8ejyWPRW9Rb2rvZH9+H3X/jP+Fr56vkq+hb63Pmu+aP56Plk+uT6evsg/Kn86/yz/Bn8XPuz+jP6Afo/+s36mvtm/CD9x/1B/o7+xP71/hz/X/+n/9D/1f+p/zj/jP7+/ZT9P/30/L38ovx//Fr8Bvx/+9n6Mvqa+Sf59vjX+ML4xvjD+MX48vgj+Vf5nfkA+pf6Tfvx+2n8yvwJ/TD9P/1C/Wv9uP0Z/oj+I//X/1oAlwCwALQAoQCSAGoAQQBYAJ8A3gAFAQ0BAQHNAHsANwAQAAMACwAWACgARAAqAMn/Kf98/uj9Yv3x/L384vwO/Qf91PyN/Dj8qvv6+mL6G/oO+iX6W/p8+or6jfpc+g36wvmK+YL5q/kE+nD6yPr++i/7NvsC+9f6vPrE+gL7Vfux+x/8dPyC/G78Qfzv+7L7rfvT+zX8m/zW/Bf9af11/R39ofwk/Nf75Psq/Hf81vw1/X79nv16/Sf9v/xV/CD8Ifw3/Gv8w/wE/TP9QP0Q/bD8Vvw9/Ef8W/xm/G78n/zw/B398fyk/HD8YvxP/Bf8AfxC/Jb8ufzP/Nj83/z7/Pr85Pzp/MX8e/xr/J78zfzL/KH8lvza/Cj9TP1J/R79Dv0z/TD95/yg/I78svzb/O38+vwN/Qv99/zg/M78s/x6/Fj8j/zs/Br9G/3//Nr8rfxv/CX8/PsA/Az8K/xp/Lv8HP06/Qz9wfx1/Er8OPw0/DP8TPx2/Jv8v/zY/ND8qvyQ/Iz8rPzN/Mj80/zt/AP9+vy4/HH8Xvxw/Jn8xvzZ/On8+vz//P783vya/HP8WfxY/I381/wO/Sn9KP0T/ez8jvw1/CL8Rvxq/I78z/ws/Xv9d/06/ff8tvxo/CL8HPxb/Kj85/wk/Uj9L/39/Nb8k/xY/FD8Svx6/Nz8F/02/Ub9IP2//G/8R/w1/Cz8Nvxo/NX8O/1Z/VH9Nf33/J38UPw4/DX8OvxV/JT86vwi/Sz9H/0T/e78q/yD/If8g/yF/JD8nvzH/Nv8wvzv/MD/TQU3C9cQaRb7GzYhzCTpJX0l7CTZJP0lQymlLuQ0yTrNP8BD/0V3RSpCqD2CORI25jLZLwsteyrlJ8IkpSC+G10W+hBhDAoJpwZbBJcBgf6h+y/5yvZB9NnxN/DU72DwWvF78onzgPSO9Zz2evcr+Lr4W/km+tH6Fvvy+o/6Qfox+mz65fpi+9X7avwp/az9pf0b/UP8a/u3+k/6OPp9+h37zfur/L79qf4m/0T/Kv8R/wT/7v7Y/vP+Mf9K/03/NP/0/o7+7v0e/WH80/tp+y37HPsd+w370vpf+tn5ZPna+Dj4xve19xr4uvg2+ZD5H/rP+k77g/t9+6D7+/tg/Lb8HP2V/fX9PP6I/gD/Y/+O/6X/3/86AIkAsACpAKEApQCxAKIAjQCEAHIAiQDCANMApQBcACEA/P/M/5r/XP/8/rT+o/6e/or+RP6t/RX9z/yY/Ef8Avyy+377gPt6+0X78vqC+h368fnk+dj51Pn0+TD6jPrg+uX6sfps+in6B/r++Qf6RPqu+ib7k/vq+y78PfwL/Mn7j/tt+2f7dfu/+y38fPym/L38xvzB/Kv8ZPwv/C78U/yn/PT8CP36/Or87Pz8/NT8h/xi/HX8qvzk/AX9/fzs/Mz8uvzI/LL8afw2/EP8jPzJ/MX8lfyE/KL8svyh/Hb8WfxO/FH8bvyU/LX8u/yf/JT8wvzp/Ob8zfy5/Mb8zPy9/K78oPyf/Jv8o/zr/C79Ov0z/Rj9C/0T/ez8lvxW/Dz8Tvyb/Or8C/0B/e/89fz//Ob8qvxm/Ef8c/y3/Nb82fzE/Jn8ePxz/HP8Y/xe/G/8oPzk/BD9D/3s/Lv8gfxd/Ff8Vvws/Bn8VPyh/ND8xfyv/LL8zfzf/MX8s/zA/Mj8r/yF/Gn8X/xK/DL8Tvyq/Av9L/0l/Sn9Q/03/dH8Vvw0/FT8cfyE/KD82PwN/Q/94fzD/LH8ffxe/Iv8zvzs/Oz84Pzu/PD8ufxh/C38N/xK/GT8m/zp/Cj9R/0y/RL97fyk/Ff8O/xU/Gr8h/zH/A/9NP0q/Qf96Pyy/G38RfxK/Hf8qPzN/PP8KP01/fT8qPx9/GL8TPxQ/Fr8cvyg/ND8+/wD/eb8yfy3/KX8m/yN/IL8Zvw//EX8Y/x2/Hb8lfzr/E79bP0z/S394P8xBb0KCBB0FUQbxyCeJAQmxSU3JQMlByYMKRIu/jOuOd8+JEN/RfpEp0EYPdc4PDUIMvcuMCzxKdInASXtINAbQRb0EH8M+AgnBrkDegE//+D8YPqx9+v0p/Iv8Y7wzPCk8dfyU/Tm9Sn39PeI+Ab5pvlj+vH6Vvui+8n7rvtc+yT7Jvtj+9/7f/wt/d39Vv5N/tn9If03/FH7tfp/+rj6XPsv/Bn9AP7B/lj/qP/D/8n/yv+5/5z/h/94/1n/LP/8/rL+Q/7L/WD99PyW/Dn8u/tH++r6jvo++vj5jfnp+Fr4//fQ97r3wPfv91T46/h/+Q36ivrv+lP7svvQ+8/7APxU/Lb8OP2r/QT+dP7l/k7/xP8jAE0AWwBgAGsAeAByAF4AUwBVAFsAXQBLAFQAewB+AFcAFQDM/7H/rP+N/2L/Gf+h/jf+5/2P/Tb95/yd/IP8l/ye/Hv8NPyz+yr70Pp0+hz6+/kI+j76iPrC+s76o/pO+gH66Pn2+Q/6L/pq+r/6FPtV+3L7avtQ+xv7B/tM+6T73/sJ/C/8UfxK/Cf8HPwv/FD8TfxP/IL8v/zM/ML8tvyk/Jr8ffxV/GP8pfzA/Lb8rPyk/LL8wvyy/Jv8qvyz/K38nvxz/Fr8Wfxb/Fr8dfyc/KP8vPze/OT8v/xw/Bf89PsU/Cr8LfxB/Hn8yPwE/f/8wvyb/I38cPxP/Ef8W/x//KX8zfzw/PD8x/yg/KT8wPzL/LX8oPzD/P/8/vzg/Mf8uvzS/OL80vzH/Mv80fzI/Lj8wPyw/Jb8mvzI/A39MP0S/dj80PzH/IP8IPwC/C/8Wfx2/KD86/ww/Tv9Ev3t/MP8cvwU/N/77/sh/DL8SPyP/Nv8Bf0K/ez80vyy/G78Mvwf/CL8R/x4/Jj8x/zm/NX8m/xh/ET8Rvxk/Hf8nvz8/DT9K/3//L78k/xV/BL88/sg/IX88Pw5/UX9MP0B/dn8r/x//FL8S/x8/Lj85vzu/ND8rfyK/GX8Wvxk/Iz8t/z1/Df9N/3y/JH8R/ww/CT8G/w6/Hv81fwj/T79Mv0H/cD8Z/wr/Cn8S/x7/Lj86/wE/Q/9+vzA/Iz8ZPxN/GD8hvyV/Lv89/wE/ej8u/x3/FT8WPxs/I78pfyq/KX8svyz/Kv8qPyK/F/8Tvxk/K39JAIKCK8NNBOzGAgecCKkJKwk/yNzI8wjBCZlKkUwajboO4dA50PGRKdCoz4/OmY2GzP/LyEtziriKMAmoyNaHzoa4xQNECEMFwmVBi4EtgFm/0v9B/t1+Nn1rfNm8iHylPJ/8+n0l/Y3+HP5KvqU+s768PoO+zH7Tft4+6v71/sh/JD85PwI/Rv9Ov1+/b39tv2G/VT9CP2h/Db89vv8+zP8d/zg/IL9Q/7p/lz/3v9jAMIA4QDKAIoALwDe/5H/TP/j/lX+8P3G/Z/9Z/0O/Yj8+/tq+9z6T/qo+Q/5pvhV+Bj41Pd79173offu9zL4h/jc+D75wvk4+oD6rPrD+uj6TvvN+y78fvza/FL95P1w/s7+B/86/3b/wf8VADAACQDj/8//3f8MAC4AIQAgAFQAmQC/AK4AZAAEAMf/cv8G/7j+gP5K/hz+IP4l/v/9pf0e/bj8f/wr/Lz7WvsY+wj7E/sX+wH7vfpy+i/6BPoI+iL6SPpa+nD6qvrc+uD6ofpD+hv6Ofp9+s36Kvun+xT8L/wQ/OD7o/ti+077dvu/+xf8fPzT/PH8z/yH/EL8H/wa/DT8X/yv/Pn8G/0c/en8g/wd/Bf8UvyJ/Lz80vzw/Cb9GP3C/FX86/vO+/37P/yD/Lj80vzC/I/8W/wl/Nv7sfvd+zb8k/y6/J78kPyQ/Gb8Ffys+4v7y/sn/JD85fwO/QX93/ye/Gv8SPwX/P77Hvxx/Nn8IP0+/T79Hf3e/Ir8W/xe/Gz8ivy8/Af9VP1Q/fv8s/yR/H78YPw3/C/8TfyG/Nj8FP0a/ef8lPxg/GD8Xvwv/Pr7+Psh/E78hvy5/Mf80vzQ/Lf8lfxc/CD8+fv8+x/8RPxS/H/83Pwc/Q39wvyB/FX8KvwA/AT8M/xW/Gn8jPzU/Bj9KP3Y/IH8evx1/Eb8Ffwh/F78rfzd/Nf85vwB/fz8yPyA/FL8LPwW/Cf8Wvyo/Pn8CP3z/OP8sfxp/C78Ffwg/DX8PPxm/MT8FP0p/QP9vvx2/D38Bfz3+y38b/yL/Jr8wvz0/Aj9xfxa/Cr8F/wL/CD8R/yP/Of8+/zQ/MP8svxz/DX8DvwQ/ET8gvyd/Nb8H/0k/Qj95fyf/Gj8W/xQ/Gv8m/yZ/IL8ivyq/Nn81vyc/HX8ePyX/Ln8p/xn/ED8rv1vAoAILw7EE4IZRR/0I/klfSVdJL0jJCRLJoYqOTBnNjE8B0FdRBFFo0JIPsE57zWzMp0v1CyaKqwofSZUI/YeyRmVFBwQmQzhCZIHdgVYAwIBiv74+2n5+fbz9NXz1/Oo9Lf11/YF+Bz5+Plq+pz64foz+3/7y/sN/B78/fua+y77Jvtz+9D7QPzI/FH98P1b/iz+ff2u/Pj7e/tM+3j7DPzr/N390/6z/1IAoACxALcAwAC6AI0AZQBsAIIAcAAPAJn/N//T/lL+wf0v/aD8EvyV+zz71/pG+pD5/vib+CX4mfcx9yH3Tvd094/3xfcs+Ir4s/jU+Pf4OvmA+bn5KfrH+ln7yvsp/In8+/xP/XD9s/0h/m7+mf7e/lX/4/84ACMA5P/S/9r/y/+y/8j/8/8cAFEAgAB2AD0ABQCt/y3/l/4a/tL9yP3W/cr9rv2T/Xb9Pf35/I388vtQ+9z6tfqs+q76q/rB+vP6FfsA+5/6Lfr2+Q/6L/oa+vv5H/qC+vX6NPsY++b6y/rY+g77QPti+3r7gPum+9r70vuk+5L7vvsL/ET8RPxC/Gj8rvzJ/JT8RvwI/BP8T/yE/Kv8x/zS/Mr8t/yP/Ff8PfxK/Fz8b/xx/Gr8kvzN/N38rfw+/M77wvvz+xH8Lvww/Bz8IfxD/Er8L/wU/OT7wfvP+/j7I/xL/Gn8dvx9/Hb8U/wO/Nz7+fsq/EP8VfxX/HX8v/z+/Ar90vyG/Fv8WPx2/I/8ivxr/Fr8cPyd/Mb8yvyi/Iz8j/yQ/I/8hvxn/Fj8gPyW/IT8bPxd/GL8ffyA/F78Vvxo/GD8ZvyP/KT8oPxs/Cj8Ffwx/Fb8Vfwy/CT8QPxj/Hb8efxo/Eb8J/wK/Pj7BPwY/Cv8QPx2/MT82/y2/IT8W/xD/Dv8LfwV/Az8Mvx//M787vzl/MX8mvx1/Ef8NPw8/Ev8TPxb/Jf81fzL/H38Rvw6/CT8D/wS/DT8ffzD/Ov83Pyn/HP8Nvz/+/b7E/wg/CP8Vfyf/NH8yvyN/ET8Ivw5/E78Qvwx/ED8X/yK/Jb8Yvwu/CL8OPxU/Hj8dvxO/EL8U/yE/KH8bPw3/EH8cvyM/IL8afxe/HD8ePx9/HD8U/w2/Dr8gvy0/JT8aPxe/G38d/xf/Cj8D/wQ/Aj8LPxx/Iz8j/yH/Gr+ewOKCT8P6RTYGrAgIiXTJlomiiUzJeAlRyi4LKEy4DiXPnBDjkbHRg1Egj8FO303ZzRNMYkueizLKpgoPCWlIEwbARZpEfINSgsCCegG0wS9AoIA8/0o+4T4ifZ39TD1ofV39mz3a/hs+VD6zfre+uX6KvuV++374ft++wH7jPo3+hX6VPrN+m77Nvwn/f/9Qf7y/VT9n/z9+3D7Ifti+x38Hv1M/mP/GQCOAPcAUQGcAbkBfwFMAVQBRwH+AIkA+f9N/8T+XP4F/tb9lP0j/b/8U/yo+8T67Pk6+Zn4C/iA9wr3wvaa9oH2ifbG9hr3aPfT93P4+fgw+Rn5zvil+LX45fg3+dH5xvrL+6L8S/3S/R7+KP7y/an9pv3w/U/+uf5D/87/QQCJAIQAWAA5ABEA5v/H/8H/2v/v/+n/x/+D/zH/yv5Y/h7+Ff4U/uj9ov1l/Sb92fxM/Kr7QvsI+9H6wfrt+h37I/v6+sT6ovp/+iz62/m/+cv5+/kX+iH6Sfpu+nT6cPqA+ob6j/rH+gr7RvtZ+0/7Q/s1+0D7UftL+177iPu3+/j7K/xl/IH8WfxG/Hf8nvyN/Hj8efx9/G38Pvwj/D38Wfxm/JD8wPzb/NL8ofyD/Hn8PfzS+6371vv0+wf89/vn+wj8HPz2++j7Dfz9+777o/u+++L74vvF+8D76/sa/CT8BPzq+9L7xPvr+xz8K/wg/Bn8Rvyf/Lr8ePwc/O/7Afwo/Df8JPwZ/Dr8f/y2/Mn8t/yI/G38gvyX/Ij8Vfwj/Cj8YfyF/HH8VvxE/FL8ffyE/HH8hfyg/Kb8qPx1/D/8Pfwc/Mj7pvvD+/r7OfxL/E78d/yV/H/8SfwZ/A/8GfwD/OT78fsI/Ab85/vM++L7HPw//Dz8W/yh/Nb8vPxq/CH8+fvg+8f7wPvY+wj8T/yO/Jr8nvyN/FX8Nfw3/EH8R/xK/Ev8Wvxk/Dj8/fvX+8v72vsC/Dj8Y/yk/Oz88fzH/Iz8N/zl+7f7qfut++H7HPxK/Jv8xvy5/J38bvxC/C78L/w1/DT8N/xE/EP8Gvzx+837tvve+yX8ZfyO/LL80fzR/JP8G/yp+3L7b/uK+877LPx7/Kv81Pz9/Pr8qfwo/M37r/u/++b7B/wu/F78d/yK/KX8m/xb/Cb8Cfz9+wn8BPwO/Pf9+gILCfEO0BSrGlkg3iTtJsgmASZoJcYlMCjYLOsyTjknPxdEjUdVSAVGuEEVPQQ5kDWiMjswhC5ELY0ruSiyJKAfFRroFKIQbw0DC+8I7gYaBWUDVgHo/j78oPmW93j2K/aj9rf39vgr+jD7xvvo+837evsc+8r6X/rm+af5xPn9+Sf6UvqU+hH7tvtF/K785vzo/MX8hPwa/JX7Pftp+zP8T/1j/kf/EwAMAfQBQwL3AXYBMAFQAYUBgwFFAfIAogBUAOD/Qv+F/rX9P/0j/fr8ffyn+8b6+vlD+Yr4rPf99rT2tfbh9gn3H/cW9/z2/vb99u/26vYX93j37/d5+PD4X/ni+XP6yfr9+jz7dvu3+wv8gfwQ/ab9LP6k/hb/cv97/0X/IP8n/z//W/+F/+T/ZgCoAIwATQAgAOP/a//4/sP+rP6H/lL+K/4S/u/9ov00/eb8qfxX/Bb85PuW+zD7wvp7+mL6aPp6+nn6i/qp+o76TvoR+uf5t/l++Wb5hvni+Vv6uPrb+tf6wfq3+q76hfpm+ob6yPr7+jr7i/vG+9372PvY++P7y/um+7T7AvxA/Er8Tfxc/If8pPyG/Gz8dvxm/DX8G/wy/Fv8gvyO/JD8nvyA/D78GfwA/NT7p/uR+7H77PsY/DX8RfxE/Bn80vuY+2n7UvtP+3b70fsT/B38Jvwy/CT88Puh+1/7V/uF+8b7G/xp/JX8m/xt/CL84vuv+5j7qvvv+0j8l/zJ/NP8vvyT/E389Put+6L73/tE/Kv87Pz5/M38k/xi/Cv8+fvX+9b79Ps0/G38c/xt/GP8PPwb/A38AfwH/BT8LvxM/DD84/u1+7L72vsP/CH8NfxH/Eb8R/xR/Df89Pu4+6b7wPvt+yH8Xvye/Kj8gfxH/BX8+vvR+7j7xPv1+zT8WPxj/HD8cPxF/BD87/vn++H73/sP/FP8cfxS/BH89vv6+//7BPwR/Db8b/yc/J38gPxR/PX7mvt4+3/7sPsD/Fb8tPz8/AL9xfxh/P77nPtZ+1H7evvS+zn8kvzU/Oj8t/xc/OP7dfta+4H7ufsD/Fb8lPzT/Pb81/xz/M/7S/st+1H7n/vy+0b8qPz4/BH97vyG/Aj8pPt9+5X7ufvh+w/8Qvx3/Jz8cvwi/Pb7/fsl/FD8Wvw6/Bz8+/vb+7X7R/z9/+sFJAxPEmcYah6wI6sm5CbYJewkvSQrJvgpxi9cNqE8CUJWRpZIhUeTQ9E+szpoN3k0yjHbL7suoC13K/snhSNkHi4ZiBTrEFsOIgzFCaIHCgZ8BE4Clf/v/Pj6q/nI+Hj44vi3+YL6IPuB+6r7ivsm+7X6dPpV+g76yPmn+Y/5jvmH+YP5rvnl+Ur64vpv+9/7MvxN/B78yvuC+4T79vvB/Kv9o/66/84AogEaAkgCNwIGAsYBnQGsAc4BuQF5ATMB2QBeAJ//uf4G/qf9WP2r/Nz7Qvu7+h76T/l7+Pn3s/dn9xD30va49qb2hPZs9oT2r/br9jj3m/cE+D/4aPh8+KD43fgk+ZT5Mvrw+p/7Rvzj/D/9T/1V/Wz9bf1w/Zv9Cv62/kb/of///2AAjgBvABwAx/+O/1z/Ef/l/vX+Bv8X/yz/Lv8N/7z+W/4C/pf9Hv2q/Dv88Pu0+4r7ifuJ+3f7Uvse+/362vp/+hf6yvmh+Z35u/nt+R36Q/pM+kj6I/rS+YL5X/mC+er5Vvqd+ur6TPuO+4j7Tvv1+qz6kPqg+uX6N/uP+/37aPyj/Kj8k/xy/Fb8NPz5+9f77fsG/Cn8c/yt/Kn8kvyT/Kv8svyB/Cz8/fsC/BP8Cfz6+wr8Ffwh/Cn8LPwc/Aj8Afz/++P7kPtF+0D7ivu4+7z7yPv7+0X8SPwg/P773/us+1H7Efss+3L7sPv2+1f8qPy//K38l/x3/Dz86PuY+437v/vy+y78bPyt/Nz8xPyV/Hr8bfxS/D38HfwP/DP8Rvxa/IX8dvww/Az8Afz7+//7AfwW/Fj8kvyI/Fj8QPwp/Af84vuy+5X7nPu4++r7G/xJ/Fv8P/wx/ET8Rvwu/A382PvG+9n7z/vC+8r76fsi/G38ifx+/Hf8avxt/F/8E/y5+5T7o/vW+xL8Ovxh/Hn8bPxJ/Ef8NvwG/OH72/sJ/Ef8avxX/D78LPwa/Af86fvJ+8r7Cvxr/Lj8uPyM/Fr8Q/xE/Bn82vut+6v76fs4/Gz8YPws/AX8EPw9/DD86vvM++z7Hvw5/CH88/vq+/H7+PsP/BT8EPwd/C/8QfxQ/Dv8E/wP/C78SvxD/EP8RPw3/C/8H/wf/CX8EfwB/Bf8UPxz/Gj8Ufw0/Ab82PvH+9f7Afwa/Cn8Zfyb/I38R/wB/PL77f3SAqcIZA5RFHoacyD5JLwmKSYIJXgkGSV6J7wrdDG8N8w9+kJLRrVGTkQ5QNQ7Dzj9NFcyVTA3L5oupS1RK0AnJyL7HEYYVxQoEasO6AybC1QKyAjVBmkEqwH+/sn8Z/vY+sb69vpk+/P7VPw9/Lv7LvvW+pb6O/rH+VX52PhO+Mj3ZfdN93P3wfc3+P74Cfrt+mv7cPsb+8j6kfqN+ur6pfuu/Ob9UP+zALgBNgJDAjQCLwIVAu8B3gEEAksCcAJaAuABDgEoAE7/kf4L/ov9Ff3O/Jv8Rfyc+7L6uvnq+Cz4jfc19xH3LvdM90/3XPdn90r3Kvco90H3f/fF9w74ZfjA+PP4Lfl5+b75HPp5+tb6TPvV+0/8pfzr/EP9mf3N/f79Nv56/sf+Cf8y/1f/i/+r/6f/sv/N/9H/tP+I/4L/kP95/z3/9f6s/nv+KP6v/Wv9R/0A/aj8Z/xQ/FP8Lfzd+7D7j/s5+7z6Vvoy+if6DPro+fD5Ifoz+iX6F/oI+vL51fnR+fr5KPov+jv6fPqd+n36UPos+lX6w/oQ+0P7cvuY+7372Pvk+977rft4+5b79vtH/F78WPxY/IH8pvyE/FX8T/x9/Kv8rPyW/In8iPx//HP8Ufwp/Ar89/sO/EP8YfxV/ET8T/xe/EP8CPy2+4z7nvud+4r7e/uj+wL8Sfxh/FH8Fvzf+9L7wvuW+2r7VPuC++f7Pvxu/Gr8Z/x7/Hb8Yfw6/Pz71Pvr+yD8M/wu/DH8QvyK/NP83vzP/Kz8j/yD/Gv8Rfwk/BH8E/xG/H78mvyt/Kr8lvyR/IP8P/z6+/f7I/xY/H/8gfyD/IP8UvwO/OP73Pvq+/L7A/xO/Lj84fy//IT8MPzQ+4j7Z/uG+8H7+vs0/Hf8xvze/KL8Nfzs+9z71fvI+8D78/s7/F78evyA/Gb8PPwe/Bv8MfxP/FL8T/xP/GP8cPxl/FP8Qvwu/B/8G/wK/Bf8Pfxa/Gv8cPyP/Kr8kPxE/Aj87Pvt+wj8Gvw4/HT8xPzz/PD8rfw//PD7x/vR+/r7HPxE/JD83/z6/NX8fvwm/NX7mPuI+6v7+PtU/KH8yfzC/IH8MPz4++P72/vK++T7LvyX/Mn8pfxo/Ar8t/uP+5T7zvs5/J389vw//Tj95/xb/L/7ZvtO+1v7lPv4+5P8LP12/VL9Df60AcIG4wsoEaQWXBxoIUMkuCQpJKgjsyMaJWMoQS3YMkU4Mj0JQYlCFkGFPZo5czbKM0gxRC8WLpQt5ywiK9gnYiOEHu0ZCxYeExYRnQ+PDrANnwz8CpkIqwWyAisAOv7R/Aj8+ft0/Ab9Zf1U/b/86/se+036avmL+MP3J/e+9mz2K/YI9hL2Sfa89l/3D/i5+ET5qfn5+Tn6Wfp8+tX6i/uZ/Kr9eP4r//P/wABqAbUB2QEHAlACtQIFAwoDuQJDArABIQF3AKb/+v6D/kj+P/4r/uD9f/0B/WP8vfv3+gH6JPme+Gn4cPhn+Dr4L/hY+HH4cPhy+Fv4R/hg+Hv4lvjG+O34APkw+YT5x/kF+j/6k/oH+3373vsQ/F/81vxK/bz9BP4Y/iz+M/4f/iT+Qv5n/pL+8/57/+7/OwBKABMAwv9l/+D+Vf7u/bv9t/3W/RL+O/45/gX+oP0x/br8Rvzj+3z7Nvs0+2P7mfuD+zj7+vq0+mj6JvoB+vf5+/kQ+jr6hvrL+t76tvpo+kX6O/oe+gX6AvpI+sn6Lftz+8X7//sC/Nb7f/sv+w377vrw+k/7/fuu/BT9NP1D/Tf91fw2/Kf7Xvtn+7X7N/zc/IL96/3o/Z/9Pf2z/Br8qfuA+6D7+vt0/Nv8IP1C/TH9//yk/EP8Cfzm+9H72fv6+yL8T/xc/FX8U/xB/Cj8EPwJ/BH8GfwI/P37Ffwz/Ez8UvxI/EH8Pfw7/EH8TPw+/CL8Gvwx/Fz8e/yb/MH83vzr/Mf8l/xz/Ej8KPwh/Bz8Nvxo/KL86/wN/Qb96/zF/KX8gvxe/Eb8MvwW/Ar8Gvww/Fv8kfy2/NP84vzS/Kj8ifxw/Cn82Pu7+9P7D/xE/FX8d/zI/Pr85/y3/HX8RPw3/Bj87Pvj+wD8Nvxw/Kj8zfzR/LP8nPyT/HX8RfwL/Pr7JPxq/Kj8tPy1/Mj80fy9/IT8RPww/En8cfyB/Ib8qPzE/Lj8nPx9/FX8O/w//GD8q/zr/O78w/yP/HP8Z/xB/AT86fsD/Ff8v/wF/SP9Kv0O/c/8gPwg/Nv70vsD/EH8a/yh/O78Lv1G/ST9y/yB/Ez8Ffwf/F/8fPx+/Jj8tvzK/Mn8pvyH/Iz8nfyY/JX8pPyY/Ib8h/xu/D78JPwm/Fn8ovzI/Mf8ovyT/LH80vy7/HL8Rfz3/F0AQwUaCtgOjBNeGOsc3R90INMfTR+AH/MgyCOkJwYsejC6NC441jkZOYw2nzNKMX0vvi0CLMUqSCrXKYoo8yVfIlUeiBqBFzEVbhMNEuEQ4g8ND+cN/gtxCcsGaARnAr8Ac/+t/mz+VP4O/qf9Hf16/Kb7r/q++cT4x/fr9kT2z/WE9UX1PPWi9Sf2lPYL95r3OfjK+CD5Ufmi+Rz6vvpr+yn8Fv0B/sn+e/9BAAMBdQGXAaAB0QERAi0CIQIFAvMB1gGXAU0B/ACQAAsAjf87/wb/sv4i/o39Of0Q/dL8X/zJ+1z7I/vl+nz6A/qn+Xj5XvlU+WD5ivmj+ab5uPnU+dP5nPlR+TX5Z/ms+cb51/km+rn6VPu2++37J/xf/IL8lPy5/Ob8Av0s/Yz9B/5y/qL+qP7M/v7+Cf/o/sb+xf7n/vL+7/78/u/+v/6B/kD+Gv4G/r79YP0z/SP9JP0g/fH8sfx9/Fr8M/z0+7X7bfsf++n6z/rH+tn66/rh+vT6HvsV+976pvp7+mz6Y/pX+k/6dvrU+hb7JPsc+xr7H/so+xv7F/tY+6b72Pv1+xL8Kvwz/CD8CfwS/Br8K/xL/I787/wl/Q/99vz1/OD8v/yb/Jj8zvz//Pr86fzr/Ob82/zM/LH8p/y2/Mr8AP03/Rv9zPyB/FP8Pfwi/AP8B/xe/NL8B/31/Nv8vPyV/Fv8Fvzh+9X76/sT/Gr8svzI/LT8jfyD/Jf8l/yA/GT8XvyJ/Jf8kPyK/JD8rfzP/Nz80fzh/PX88vzh/MD8nPyR/J38uPzr/Pr86vzs/O381/ys/Hf8Uvxd/Ij8tvzh/PT8EP0b/QD93Pyh/Gf8VfxW/GL8g/ye/L/84Pz5/BH9Df3g/KP8gvxy/HP8cvxl/Hf8j/ye/Mv89Pzi/LT8lPx4/Gv8b/yE/Lr87vwF/Qf9+vzv/Nr8mfxU/ET8Tvxi/JP8zPz9/DX9S/03/Sz9G/3a/JT8dPxy/Gb8S/xH/HH80Pwm/Tz9Lv0e/Rn9CP3p/LP8b/w7/C38RvyC/NX8C/0c/Q/9EP0s/Rf9sfxB/CP8SvyN/Mb82fz4/Ef9eP1K/ef8kPxK/Bj8Ifxa/Kf86Pz+/B39Tf1R/f38hvxN/Gb8lvyl/KH8sfzQ/O386/za/Mf8tPy2/M387/z1/Mv8m/yV/JX8l/y6/OD8//zi/fkA7wSTCB8M1A+wEy0XRRnEGcoZBhqbGuQbOx58IfwkOSg6K7It+i6hLvAsJSvqKQQpFyg4J78mqCZlJkIlJSN1IIEdsRpeGJ8WbBWYFOsTUxOpEpwRCBABDrULcglrB6MFPAQ4A3YC5QFPAZoA4f8L/yv+Uv1M/Dz7Vfpt+ZD46fdg9wH34PbP9tz2SPfi92X4wfj/+Ev5qfn3+Sv6gvod+8j7bfwb/cn9Yf7U/hv/Z/+z/+b/FABVAK8AEQFZAU8BJQHtAKUAXAAHAKr/U/8x/y7/Mv8b//f+z/6J/hj+lP0X/bH8fPxc/Df8C/zb+5z7bvtI+w37v/p/+mD6avqr+tv60/q8+rn6rvqM+lz6OPpF+oH6yvoO+3f76/s+/Gn8fPyS/JX8dvxe/Hv8xfwf/XX9w/0O/kf+Y/5i/lP+N/77/cb91P3y/QD+Cv4K/gv+EP4F/tb9m/1e/SL94vyq/Ir8b/xi/GD8dfye/Jf8Wvwa/Oz7pvsx+9X6xfrr+hn7NPtu+9P7Dfzd+3r7OvsD+7/6kfp++qn6BPtI+4r73PsC/OT7s/uB+2L7Zftg+3L7wvsp/HX8lPyc/Kb8lfx6/F78M/wZ/CH8X/zG/Bv9Qv1P/U79VP1e/Tn94vyI/Fz8cvyW/Kf80/wU/U79hf2g/W79G/3X/J38ePxc/DT8M/xv/MT8Kf1t/X/9Z/0y/fr8uPx6/Ev8K/w5/HH8sfzk/AH9IP0j/fj8wPyc/KT8r/yk/KX8wvzj/P389vzf/M/8y/zK/MX8yvzU/OT8//wX/Sv9I/0L/f/8//wS/Q/95PzA/Mj82vzk/OX80vza/A/9Ov1J/UH9L/0S/fT81Pyr/H78Xvx9/Lv86PwA/Rv9Mv05/Tz9GP3a/Kj8mvyf/Kj8t/y2/Lf82fwM/RT9//zn/Nj85vz2/PX84PzS/OT8AP0P/RD9Bv30/PP88fzl/Nf8zPzO/Nz8E/0+/TX9Kf0s/Sn9//zC/Jf8kfyn/MT86Pwf/Wf9iv1s/S/9Bf3o/LL8fPxp/JT80vz4/CT9Xf16/Xb9T/0l/RX96vy5/Jn8pPzG/NX82/zx/CX9Uf1F/SD9E/0J/fP8+vz//Or82vzl/AX9Gf0b/Qf99PwB/QX95/zG/Of8G/0b/SD9Mf0+/Uf9H/3U/Lj8y/y3/Iz8k/zZ/DD9Yv1X/TH9Fv0G/er8vvym/Fv97v8UA/wF4gjkC+QOZRHcEjATOBOFEx0UXhWNFzwa5RxeH68hsCPDJJgktSMJIwAjMCM1IzwjjyMMJCAkdCMZIkogSR6DHEkblhovGs4ZaBkfGdgY9hdGFkoUVhJxELAOJQ32CyYLegqtCc8I5ge0BkcF5wO5AqoBnwCo/87+Lf6p/QD9T/y2+z773PqQ+mv6fPqL+n36Z/pf+m36cfp7+pv69Ppb+6H74vsn/Hz8xPzh/Ov8F/1Z/ZT90P0F/jj+a/56/nH+hv6l/rb+1v4A/w//C//y/q/+Yf4z/ib+Cv7j/d39//04/nD+Yv4J/pf9P/0B/bb8evxW/FL8a/yX/MH8z/yu/Fz8GPwF/Af89vvg++X7GPxb/Hb8ZvxN/ET8RPxN/Gf8gvyc/L/88fwi/VL9VP0c/f/8E/0n/TD9Nf07/Wr9i/1//Yb9jv15/VH9IP0R/TL9UP1Z/VD9MP32/Mb8s/yY/Gv8UPxd/IH8nPym/J78hfxV/A78vfuH+4T7fft8+6D7y/vT+8n7s/uh+6j7nPtt+0f7Tftu+5j7rfuv+537gvt3+4T7rfu++7z71fsC/Cn8Nfwz/ED8S/xT/Fb8QPw4/ED8ZPyI/Kf8xvzF/ML83fz//AL96vy9/Kr8uvzP/O78Cf0i/TL9Mf00/SX9F/0R/Qb99vwE/SD9Fv0f/Tb9O/00/Rb97vz5/B39Iv0c/Sb9LP0j/SX9Gv0T/RT9+fzd/Oz8Ev0P/f78Av0W/Sv9M/0o/SL9Pv1P/UL9LP0a/Q39/Pz2/AL9HP05/VH9bv2C/Xn9cf1n/Uz9Hv3h/Mr88vws/Vf9af1x/X39jf2C/VT9Kf37/ND84/wW/Tz9V/1s/Yf9mP2L/VH9Ff3x/O38A/0S/Q79Gf1I/XP9if17/U39Jf0G/eX81/zr/A79Hv0s/Vb9mv24/Yf9Qf0V/Qr9AP3k/Nf8+/xG/X39mP2U/Xv9XP03/RH9B/0L/RP9J/1C/Vn9bP1u/U/9M/0t/T79WP1v/Wn9Zv12/W39Sv0X/fz8Cf0n/UH9UP16/Z/9lP18/WP9Qv0z/S39Jv1A/Wv9f/11/XT9Zv08/Qn95Pz1/CX9Xv2H/aD9vP3N/ab9XP0q/e/8wfzI/O78I/1o/Z39pf2n/Zz9e/1E/Q399vwC/S79Tf1T/Vn9b/12/V79Qf0m/Sr9Q/1T/Vr9c/2G/Xv9av1e/VH9NP0Y/Rv9pv19/3UBAgO8BLsGxwiLCpEL6wtFDNUMiw15DsUPXBH4EpYUKBZ+F2AYsxjIGBUZthlDGooa3RqOG2Yc6xzgHGocwBsMG10arxknGcsYkBh5GHEYWxgGGGgXmxaiFXAUKBPzEdwQ+w80D1YOdw2zDP8LPgtLCiYJCAgWB0IGZAV6BKoDAANnAsYBGgF7APP/df8A/4j+GP6p/Ub9BP3K/H38Lvz5+/L7DvwU/Or7yvvD+777p/uD+3z7mfvJ+/v7Lfxd/In8nfyX/In8dvxg/E/8Zvyl/N/8C/0z/Vb9cv2B/Xv9Yv1N/VL9XP1s/Yj9nv2x/a/9of2a/ZH9gP19/Yj9mf2t/bH9rP2t/a/9rP2e/YP9cP10/Zr9vv3D/br9sv21/bz9sP2R/YT9jf2c/aX9p/2w/bP9tv3M/dv9z/21/an9s/3B/bD9g/1i/Vb9WP1V/U39U/1b/Wz9c/1N/Sn9Ef3w/Nf8zvzY/N/80/zI/NH8yfyQ/EX8B/z7+xD8I/wt/Dz8UPxS/En8NPwa/Pj70vu/+8j72/vf+9z72fvU+877v/u9+8/73fvx+w78Jvw9/Er8Pfwv/Br8BvwA/AL8FPwv/E78bPyL/KT8svy6/Lb8q/yu/Lj8vfzW/On89/wO/RL9CP0F/Qn9CP0L/Rb9Jf0t/T/9XP16/X79Yv1L/UX9Tv1e/V39ZP1z/X79fv11/XD9Yf1R/Un9Yv2P/ab9oP2d/bH9v/2r/X79ZP1f/WH9Y/1v/Xr9gv2Q/Zv9oP2i/Zn9iP2I/Y39jv2N/Y/9hv2F/Yv9fP1w/Wv9YP1i/XL9hv2e/bf9z/3Q/bT9mP18/WX9U/1B/T79Sv1p/Zb9vf3N/cT9qf2a/YX9Xf1D/Tj9Sv1w/Yn9l/2y/cX9yv20/Yj9Zf1I/TX9P/1e/X/9q/3Q/dz92v2//Zb9a/1F/S/9MP1J/XP9ov3U/fz9+f3U/bD9jf1n/Uj9R/1a/Xn9nf29/d797f3a/bX9mv2C/YD9hf12/Xn9p/3U/dT9xv22/bL9r/2Y/Xf9bP13/YL9kP2j/cf94v3a/cP9sf2o/Zn9eP1g/Wr9iP2X/ab9wv3Z/eP9z/2q/ZD9gP1t/Vz9Yv2K/bn9zP3L/cX9xv3I/ab9cP1N/Uf9bf2g/cH92/3u/ef9y/2f/Wz9Uf1Q/Vf9a/2T/bv92v3p/dz9xP2v/Zb9e/1v/XL9jP2s/a79lP2B/Y79p/2p/d/95v4CANcAqwGqAswDzwRfBZoF8QWDBiYHzgegCIcJXgooC+4LswxZDcoNJw69DpUPZhAFEYIRBxKhEiETQhMaE/MS5RLqEvES9BIDEyITQRNSE1oTShMaE9ESbBL7EZkRNhHEEE4Q4Q9sD90ORA6wDSYNlwz8C2QL5gp2Cu8JYQncCFoIxgccB3EG3AVaBckEOgSzA0QD5AJ7AhYCuwFlAQkBrgBYAAEAqP9j/y3/+f6+/oP+Tf4k/gv+7P3F/Z39df1V/Ur9Rv0y/RT99/zj/OH84PzP/MH8wPzF/Mf8xPzB/Mb81fzX/NL8yfy5/L38yPzR/NH82fzp/PP89fz5/Ar9Ev0N/Qb9Cv0W/SP9Kv07/VP9WP1R/Uf9Tv1b/WL9ZP1m/XD9i/2x/cf9xv25/b39wf23/Zr9h/2P/ab9vf3O/d/96v3v/ef93P3S/cX9pv2K/ZX9vP3X/cj9pf2a/Z39lv13/U/9M/0p/Sf9Nf1J/VL9S/05/SP9E/3//NT8rfyN/IL8i/yT/Jf8lfya/J38ofyQ/GT8R/xM/Fr8U/xK/E38TfxK/Ej8P/w5/Cv8FfwT/Cj8R/xb/Fr8Z/x2/Hb8afxW/FP8WPxd/GD8afyB/Kb8vvzF/Mr8xvzG/Mj8xfzA/Mb82/zw/AT9Ff0m/TH9M/0r/SX9H/0c/Rr9Jv1L/Wz9hf2S/Y/9if1//XD9V/1C/Tj9Qf1j/Zb9vf3X/eP94v3P/aj9hf1m/Vf9VP1m/ZP9x/3n/fP98v3h/cT9nf18/XH9c/2A/Zf9uv3b/ef93f3F/bf9r/2Z/YP9iP2Z/bT9y/3M/cL9wf29/bT9rP2b/Y/9mf2r/bn9w/29/bL9sv2x/bT9tf2r/aP9qf2z/bn9uf2q/Z79ov2k/aH9sv24/br9xP27/bb9t/2t/aH9lv2d/av9rv2u/av9s/29/cL9uv2s/aH9n/2l/an9qv2u/b/9wv3B/b/9uP2x/aj9pP2h/aD9pP2n/bf9yP3E/bz9uv27/bz9v/26/a79p/2t/bP9t/21/a79rv25/b/9uf2u/ar9tP2//bz9sf2z/br9xP2//bD9o/2V/Zr9p/2v/bj9vf24/bL9t/28/cD9wf2s/Z79ov2s/bf9sP2f/aD9qP22/cP9wv21/av9rv21/bH9pf2U/Yn9lv23/cn9wP26/bX9wP3M/bv9l/2K/Y79kv2c/az9uf2y/bH9tv24/bb99f2n/kn/1f9mACwBHQLmAk8DegPDAzMEsQQrBa8FRQboBqAHXwgSCaAJEgqLCi4L6wuODBYNpw1LDvgOhQ/LD9kP6w8TEEkQfhCbELwQ/BBdEbsR9hENEgkSAxLyEdERpxF1EUURFRHoELIQahAXELwPWw8ED6wORw7XDW4NHQ3ODGYM4QtbC98KYwrdCVIJzQhTCNoHYAfxBo8GKQa0BTcFwwRcBPYDjAMiA8ECaAIVAsABbgEgAckAdQA3AAkA1f+O/0j/GP/s/rb+cP4m/u39x/2j/YD9Yv1Q/T/9L/0d/Qj9+Pze/L38oPyM/IH8d/xq/F78W/xj/F78VfxX/Fr8VfxJ/Ej8U/xj/Gj8aPxt/H78hvyH/IP8hfyU/Jz8o/yl/LH8w/zX/On89Pz+/AP9CP0S/SD9Lv0z/TL9Nv0+/UL9RP1J/Ub9T/1m/XH9df12/Xv9j/2X/Yj9av1Z/WD9Yv1k/WH9Wv1Y/VT9UP1U/VP9QP0l/Rn9HP0Z/Q39/Pz9/Pr89Pzo/Nb80vzV/Mr8r/yb/In8hfx7/HT8cfxz/HX8cfxu/Gj8ZfxW/En8Pfw+/EP8T/xZ/Fz8YPxW/ET8K/wi/Cb8Lvwx/DD8Qvxq/IT8gvx6/Hj8fvx+/HD8Yfxj/Hn8jfye/KX8rPyy/LL8t/zC/Mf8vvy7/Mf85PwH/Rr9Fv0T/Rv9Jf0n/Rf9Bf3//Av9Iv00/Tr9P/1N/Vb9X/1g/Vr9V/1g/W79dP19/YT9gP1x/Wf9bP1u/Wr9Zv1v/Yb9m/2d/Zj9nf2k/aP9kv2D/Yj9kP2J/YT9jP2a/aL9n/2X/Y/9jf2L/Y39jf2Q/Zj9m/2g/af9qP2f/Y79ev1z/Xv9gP2B/YX9kv2b/aX9qf2j/ZT9i/2K/Xn9a/1t/Xf9gP2E/Y79nf2f/ZL9hP2J/Zf9kf1+/XT9gf2T/Zz9kv2C/YL9hv2H/YL9fP16/YH9if2P/Zj9mv2T/ZT9mf2X/ZD9gv19/Yb9jf2Q/ZP9k/2O/ZH9kf2I/Yb9if2E/Yf9mP2g/aH9n/2f/Zz9mv2X/Y79iP2F/Yf9if2P/Y39h/2Q/Zv9nf2T/YT9gf2P/Zv9nf2W/ZL9lf2Y/Zn9lP2H/Xn9cP1z/X/9iv2M/Yv9j/2X/Zb9iP2B/YH9g/18/Xz9gv2G/Yr9jf2Q/Y79if18/XT9cv10/XL9df19/Yn9lP2U/ZD9jP2K/Xv9bP1+/Rn+1P5g/97/iAB3AVkC6AInA3UD7gNxBOQEZgX4BZMGQAfxB6sIUAnUCVEK+grSC54MQw3cDZIOYA8ZEIwQxRDpEBURThGHEb0R9hFBEqASCRNqE64T0RPqE/8TBBTvE8kTrhObE4ETTRMGE78SdxImEsYRZhEGEasQTBDrD4oPJw/DDkoOyQ0+DasMGgyOCwQLdwrkCVQJzghUCNsHUgfCBjoGwwVaBewEZQTjA3sDIQPFAlgC3gFyASMB1wCAABsAuv9l/yL/6f6p/mT+Ev7W/a79jv1k/Sr99fzN/LL8kvx5/F/8QPwl/A38/vvw+9z7xvu3+7X7uvu1+7P7u/vL+9D7yvvE+8v70vvM+8b7yPvg+/r7B/wP/CT8OfxJ/E/8Ufxc/Gz8ePyB/JP8r/zC/ML8y/zZ/OP86fzp/PH8A/0a/ST9Kf0s/Tb9Qf1L/VH9Sv1D/Uf9UP1Q/Uf9P/06/Tz9Ov03/TD9Kv0n/SH9IP0e/Q79Af38/Pr87/zX/MH8tfy0/Kz8oPyS/Ib8ffx1/HH8ZfxS/EH8QPxL/E38Ofwb/An8B/wM/Af88vvc++P7+vsE/P376/vh+9/73vve+9/73/vf+9777fsB/AP8+Pvx+/j7BPwK/AL8+fsG/B/8Lvwz/Dj8OvxA/Ev8UPxW/Fz8X/xm/Hz8mPyg/Jv8nvyu/Ln8vvy1/K/8uvzN/OD86/zy/Pv8A/0K/Q79Cv0O/RH9F/0g/Sv9OP06/Tz9Of09/UH9PP04/Tn9Sv1c/WL9YP1h/Wr9bv1n/V/9Wf1e/V39U/1Y/Wf9dP1u/Wr9b/1y/XD9aP1m/Wj9b/1u/Wn9af1t/XL9ef10/V/9Uf1T/V79af1n/V/9Wf1d/Wr9dv13/XH9Yf1b/WH9Zv1k/VX9Sv1M/Vj9W/1S/U79Vf1j/Wr9Zv1e/V79Yv1n/WP9Vv1L/UD9Qf1H/U79Vv1c/V39W/1e/WT9ZP1b/Vf9Uf1K/Uv9Uf1c/Wv9cP1j/Vv9Wf1Y/VP9R/1B/Uj9WP1e/WX9cP18/Xn9af1Y/U39S/1N/Vf9X/1c/Vr9YP1n/Wv9af1h/VX9TP1J/U/9XP1k/WT9Yv1n/Wr9av1m/V79VP1J/UH9Sf1W/Vr9Vv1R/Vj9YP1l/WL9Wv1Q/VH9Xv1k/Vv9SP1B/Ur9VP1S/UX9Of1B/VT9Yv1i/VH9Rf1H/VH9WP1R/Ub9N/06/U79V/1Q/Z79Yf4e/8L/VwATAfIBwQJAA4UD2wNOBN4EegUgBrgGUAf2B68IaQkMCp0KLQvnC8QMng1gDggPqw9XEPMQVBGGEaYR2BEhEmcSqRL3Ek8TrBMAFEgUhBSjFLEUsRSrFJ0UihR6FFwULhTrE50TTxP8EpsSMxLHEWARBBGpEEkQ2g9fD+UObw7uDWANwgwhDIwL+gppCtEJPAmuCCIImQcRB4wGDAaIBQMFiQQYBKcDLwO4AkcC5QGLAR4BqgBGAPn/qP9N/+/+mv5b/h/+3v2k/XL9Pv0F/dH8qPyB/Fn8NvwV/P776vvZ+8b7t/uq+5v7hPts+2j7bvt6+3P7a/tt+3T7f/uE+4r7mPus+7r7wfvT++77/vv9+/P7+fsM/Bj8JPw8/FT8cPyO/Jv8m/yn/Lv8xfzP/NT81vzh/Pf8B/0P/RT9Ev0O/Qv9Ev0d/Sn9Jf0i/TT9TP1O/Tb9HP0Q/Rf9Ef36/Of85/zz/O/83/zN/MD8tPyh/Jj8lPya/JP8g/x7/G/8W/xA/CH8C/wH/AT8+vvw++777Pvl+9z70fvJ+7/7qfuX+537qfup+5v7ivuI+5X7mvuP+3/7dvt4+4L7ivuQ+5T7lfub+6T7p/uv+7b7tPu0+8P7zvvT+9n72/vl+/H7+/v7+//7Dvwe/Cn8Nvw9/EH8TvxX/FL8VPxl/HP8gfyI/If8ifya/K/8svyt/K78ufzE/NP84vzp/Oj84/zl/PH8/vz3/O788vwB/Qf9Av0I/RX9IP0d/RH9D/0X/Rz9H/0m/Sb9Iv0e/SP9KP0n/R79Ev0Q/Rj9HP0e/ST9L/0y/Sj9HP0W/SP9Jf0V/Qr9Df0c/SD9Hf0Z/Rz9HP0M/QL9A/0I/Qj9A/3//Ar9G/0d/RD9DP0X/RX9Bf3y/O388fz3/PX89Pz5/Pr8AP0O/Rf9EP0E/fr8+Pz5/PP88Pz0/Pb88Pzw/Pz8Bf0E/fr89Pz3/Pr8+vz3/P78Bv0E/f/8+Pz6/P38AP39/Pb89/z2/Pv8/fwB/Qj9Cv0K/Qb9Af39/Pb89fz7/P/8/Pz7/P38Av0P/Q/9Af31/PT89vz9/P/8+/z//Ab9Cv0F/QP9Cv0H/fj85vzf/OT86vzt/PP8AP0E/Qn9D/0T/Qj98Pzd/Nz86fzj/N385vz3/AL9/vzv/Or87fzp/OL84vzi/OL86Pzv/PL88vzt/N782/zb/Nn8OP0y/hb/u/9nAFwBhQJ4A/IDKwSQBDAF2gV3BiAH3wevCIUJXwowC+kLjAwsDfYN3w6wD18QCBHMEZoSOBODE6cT1BMJFDoUYxSLFNUUPBWfFe8VLhZeFn8WgxZhFjUWDhbtFcYVlxVeFREVsxRPFOsTgRP/Em0S5hFxEQsRkhD5D1oPzw5JDrENBA1KDJ8LAwtjCrcJEQl1CNYHOgeiBhwGigXdBDMEoQMdA5wCHQKjAUcB9wCVACwAzv9w/wf/j/4X/rX9Z/0l/ej8s/yJ/Gj8P/wN/Nn7q/t6+0v7KPsV+xb7FfsR+wr7DfsG++z61PrH+sf6xvrL+uH6CPsq+0H7TftW+137ZPtw+3v7gfub+8H73Pvz+wv8J/w5/Ef8U/xk/Hf8f/yD/KL8zfze/NT8zPzc/Pn8Dv0I/Qb9Ff0h/Sf9Lv0v/Sn9Jv0e/RT9Ef0O/QT9Bv0C/fT84/zT/ML8uPyx/J38jPx//HX8a/xg/E78LPwT/AD89vvp+9L7wfu6+6n7jft1+2T7VPtD+zr7M/sp+yH7JPsk+xP7+Prm+uD63PrW+s76x/q++rj6v/rD+sT6xPrE+sn60PrO+sb6xfrP+tz65vrm+u76A/sK+wT7C/sY+xP7DfsW+zb7U/tc+1v7afuL+5f7kfuU+6H7qvur+6v7t/vR++D73/vj+/v7EfwP/AH8/vsa/Dv8O/wz/EL8Xvxt/GH8TvxB/EP8SvxT/GL8dvyB/H38e/yG/I38ifxv/F/8a/x8/Iv8ivyA/IL8k/yg/Jf8ffxv/G78bfxz/Hn8fPyE/Ib8fvyC/Hn8Yvxa/Fz8XPxg/Gn8dfyF/I78ffxi/GH8aPxd/Ez8Qvw//ET8S/xJ/Ef8T/xg/Gr8afxm/F78UfxO/FP8Rfw3/DX8Nfw+/FD8WPxM/EP8PPxD/E/8TvxL/Eb8Sfxf/HP8a/xZ/E38RfxB/Dv8L/wq/Db8RvxW/Gz8dfxo/Fr8VvxU/Ez8N/wm/DX8VPxh/GH8XPxb/GH8WPxC/DH8Mfw0/Dv8RvxV/GD8X/xf/Fn8U/xK/Db8M/w5/DT8NvxD/EX8RPxB/D38QfxA/Dn8NPw//FD8UPxD/D/8Q/xF/Dr8L/wq/CH8Ifwo/Dj8P/w9/Dr8N/w0/DD8NPwr/Cn8LPwz/D/8PPwt/CD8Ifws/Cf8FfwP/Bv8M/w//Df8Jvwm/FH8Yf21/p//jgDHAVUD2wTSBUoG0AaiB5QIjwmaCsQLAg1cDsoPJhFOEisT/RMLFUkWYxdDGBUZ/BkLGwQckxywHKccuRzrHBkdIR0nHV0dvh0hHmIebx5YHiIe3x2WHTIdthwxHMMbYRvvGl0apxnnGCYYZBedFsIV6BQVFEITfRK3EdIQzA/FDtYN6QzpC9wK1gnpCAgIJQcxBjoFVwSSA9wCGAJcAa0ADABy/83+J/6M/fz8f/wK/Kz7ZfsX+7j6Zfom+uX5jvkv+f344/jF+KH4g/h7+JD4pPiR+Hv4cfiB+JT4lvig+MD45/gW+U35efmV+ab5vPnW+QT6LfpN+oL6zvom+2b7h/ul+8r77/sO/Cz8Sfxv/Jz81fwD/SH9Mf0//VP9Yf1q/WX9af1+/aT9wf3Q/df92/3c/c39rP2A/Vr9P/09/UD9P/1A/Tr9Kv0R/ff80/yZ/Ej8Hfwa/Bn8Afzd+7/7rvuc+2j7F/vP+qH6gPpr+mb6Z/pV+kP6Pvop+v/5wvl6+Ub5O/k8+TP5MPkr+S35Ofk5+Rv59vjh+Nn42vjS+NH46PgM+Sb5HPkX+R35GPkN+Qn5B/kR+Sv5Rflr+ZT5svm8+b35xvnO+d755fnk+QP6KPo9+lD6Yfp0+oz6nvqc+pz6sfrM+tn66voD+xX7Ivsy+z37RvtS+1j7VPtP+0/7Wvtu+4H7kPuP+5j7o/up+7P7rvuh+5r7kfuS+6X7sPuu+6j7pPue+5T7jvuO+5n7n/ub+5n7oPuf+5D7g/t++237VvtQ+137dvuA+3r7bvtr+3D7Z/tE+yj7J/s4+0v7TvtC+0j7W/th+1/7Svsk+w77CPsL+x37Mfs0+zT7O/tO+137Tvst+wr7AfsT+xv7IPss+zn7QvtN+1b7Q/si+xD7Evse+yr7K/ss+0n7aftu+177Pfsl+yP7Jfsn+zX7RPtN+1r7Zvti+0v7Nvss+zL7NPss+zf7Vftw+3r7a/ta+1z7WftG+yX7Fvsk+y77Mfs++1X7bPty+1z7TvtD+zT7LPsu+zH7LPst+zn7S/tU+0D7JPsS+xv7JPsi+xr7FPsp+0D7Q/sv+yD7Gfsd+yL7GPsD+/n6Bvsf+zr7M/sS+/j6+PoQ+xn7APvn+u76Fvs3+yn7EfsS+xL7CvsA++362/ro+vr6BvsO+xf7Hfts+878Y/62/ysB/AIhBUYH3gjICbMK9AtYDd0OpRCjEs8UMBfCGUkcZx7yHzAhryJzJP8lOydmKNUpiisHLegtJC4PLuUttC1sLRYt3yzNLPIsQy2ALWQt4CwLLP0qyil+KCQn1SXBJNwjECMlIgMh0R9/HvscUxurGRYYnxZOFQQUvxKREUoQvA4IDVELogn1B1IG0AR4A0sCOwEzACf/GP74/L/7n/qk+bf46fc797j2a/Yg9rX1TfX69Kb0TPT/88XzrvPC8+PzD/RH9Hn0mvS49Nb0/vQr9UP1Z/W09SP2m/b29jz3jffu90H4efik+OT4Qvmo+QT6V/q2+hr7cfu0+/X7Ofx0/Kz8/Pxk/bz99v0h/kn+ff6t/rj+rf61/sn+5f76/gP/GP8q/y//Nv8q//3+0f6h/mz+Q/4c/u39tv2Q/YL9ev1M/fL8nfxa/Cj87fui+2n7OfsG+9r6qfpy+ir62fmO+Uj5DPnF+Hn4PPgp+DT4H/jb94z3Yvdd90b3CPe39nX2YvZw9nL2XfZJ9jb2LvYy9i72J/Yi9iD2OvZt9o72h/Z39oT2qPa99qn2mvay9u72Ofdn94b3qPfO9/T3BfgF+A34IPhD+Hf4rvjZ+Pj4Gfk6+Uv5Qfku+UD5bPmf+dT5+/kg+kD6ZvqC+nL6Sfom+in6SPpb+mL6efqg+tH6+/oH+wD77/rW+r76s/qh+o/6jvqf+sv69/rz+s36wPrQ+sz6qPp5+mf6ePqE+oT6jfqa+pL6ePpl+mL6Xfo++gf6/fks+kj6R/o7+jz6S/o8+hf6+/ni+cj5w/nZ+fb5CvoL+v/5BvoR+vj5z/mz+bj5zPnb+eL55fnt+ff58/nd+dT50fnd+ef53/ni+e/5APr/+f75/Pnt+ez5/PkS+hb6D/oO+gz6Ffom+iH6DfoJ+h76PPpE+jP6Jvol+jD6Ovop+hj6Gvoo+kD6UPpU+lv6XPpM+jf6M/o6+jv6Mvom+ij6OfpQ+lj6SvpA+jb6IPod+i76SfpX+kr6RPpP+kr6LfoG+ub58/kM+g36C/og+jr6Q/o/+i76G/oG+uf50vnm+QP6C/oG+gP6DPof+iP6Bfrl+dP51fni+ez5+PkA+gj6F/of+hf6/Pnl+dL5w/nK+d757vn0+fn5BPoa+iT6DPrn+db51fnZ+dv51PnZ+YH6U/xB/vH/zgEuBOoGaQk+C6MMHg7PD7AR2hN9FoYZlByqHygjzSb2KVIsSi6CMPUyITXFNkU4FzoVPLY9xD5LP2M/MD/EPiw+lj0OPXA82TuCOy87ijpiOcA32jXSM7QxZi8YLQUrMimKJ+olQiR7Ipcglx53HFIaNxgjFgkUERJTELMOGQ1aC3YJkge9BfQDIAJIAJz+J/3g+7j6rPmp+I73dPZ09YT0lfOy8vjxevEx8Qjx4fDJ8NPw9fAE8f7wB/E08YDx4fFW8tXyYvPs83X0AfWE9e/1Rvae9hj3ovcZ+If4AvmV+SP6kfrU+g/7Wvuc+9b7FfxK/IX83PxC/Z394v0T/jr+Xf5s/mn+cP6Z/sz+5/7//i3/Yf+C/4P/bf9E/yD/Af/l/tX+t/6S/nz+Z/5G/g7+sf1G/fP8uPxt/BP82fus+4T7UvsD+6X6Pfrc+XX5GfnN+H34Kvju98X3mfda9/32pfZm9kH2Ffbk9cT1pPWG9V71GfXR9JL0V/Qj9A70DvQW9CX0PvRY9Gr0X/Qm9Ozzz/PS8+Lz+/Md9FH0mvTl9BX1F/UO9QL1BfUw9Vj1dPWn9Qb2bvbA9uv26/bs9vf2D/cu90L3WPeH9+n3Vfic+LD4pfij+Lb4z/i7+Kf4uvjh+DD5evmY+Z35o/mm+aj5qvmc+Yb5jfmu+c/52/nc+eb58fnx+dz5wvm4+cP5yPm9+bj5x/nO+cX5uPmu+aL5h/l5+Xr5dPle+Un5Uvlm+Wb5Sfkm+Rn5Mvk8+SH5Bvn/+Aj5EvkJ+f34AvkC+ff47fji+NH4zPjO+NP44vjj+OD45vgF+RX5/fjX+L34uvjI+Mj4vfjL+On4D/kh+SH5E/kD+fL40/i++MX41Pje+AP5KvlV+XD5Wvku+RP5E/kK+e/44vj9+C35SvlP+WP5e/l7+WD5Pvk6+Uf5Ofkr+T/5Wflw+Xv5dPlt+WX5R/k5+UX5RPk++Uz5cPmO+ZL5dvlZ+VX5S/kt+RT5IPlH+WH5ZPlt+Xj5dflW+S/5Hvke+Rf5FvlB+XL5h/l5+VH5P/lL+S/57PjM+PH4Nvlf+Wb5Zfl2+Xv5Rvn8+NL4z/jX+Ob4B/k7+Wv5c/lc+VD5RPkV+dL4oPiv+PD4IPks+Tr5Tflj+WH5L/n4+NH4zPje+O/4+PgV+Tv5R/lD+UH5JvoH/Nn9t/8iAhYFQAgJCxUN0A6jEIsSkBQKFyMaox1tIaElQSq3LmUyLjW6N3w6Hj0qP+BA2UIoRYJHcEmuSlhLgEsjS3RKiklrSD5HO0Z/ReJECESlQstAqD4qPD459DWUMnMvwyxvKiso8CXdI9whth9PHbQaBBhmFe8SoxCDDpIMuwr/CGgH1QUjBEkCYwCs/ir9uvtL+vz42Pfl9gz2OPVn9JLzvPL/8XTxEvG38GHwL/A08GXwq/Dk8B7xcPHP8T/yzfJr8/HzZ/T59L/1l/ZN99H3WPgH+bj5S/q3+hf7iPsE/G/8zvwm/Wj9of3Q/f39Lf45/iz+LP5F/mL+Z/5Z/lD+XP5j/k/+NP4q/ir+I/4M/vD98P0B/vr90f2e/YD9a/1B/Qv91fyv/Jn8d/xS/Db8BPy/+3z7LvvZ+nr6DPqq+WX5J/ne+JD4U/gc+Of3n/c99932g/Yx9vX1u/V+9Ur1I/UB9c30mfRY9BH02fO186jzmfOL83bzevON83nzQfMG8+by4vLf8sTyx/L98jHzS/Ng84XznvOY84LzgvOY87fzzvPi8yr0lPTe9Pf0CvVC9Xj1i/WT9bP15PUT9kf2ifbY9hj3Kfcl90T3d/eP95H3oPfY9xr4R/hh+Hv4jPiO+JL4m/ih+KH4pvi2+N749Pjv+Ob44/jr+Pb49/jr+O74+/gN+Rb5CPnt+N743/jX+MH4qfia+J74tPi3+Kj4q/ir+KH4l/iD+HT4bvhj+Fv4bPiC+G34R/gv+Dj4R/gx+Pz39Pcs+Fb4WfhY+Fv4W/hS+Dr4Jvge+Av4+PcL+DH4UvhY+E74U/hZ+Fn4Rfgp+CP4Ofha+HT4efh6+IL4e/hs+FH4RPhU+Gv4fviV+Lb4yfjC+K/4m/iP+Hn4VvhT+Hf4rPjR+OD49/gI+f741fip+JD4ffh2+Hz4nfjb+Ar5FvkK+fr44fiy+H34bPiF+K740Pjp+AP5Hfkj+RD53/ih+Hf4b/iC+KL4wfjW+O74CPkF+eT4xPio+If4fviL+J/4uPjG+M/43fjj+Mb4kfhy+Gz4ePiC+Iz4nPi0+L34qviV+I/4iPhu+Fj4Wvh9+LD4tfiU+IX4g/h/+Gz4Ufg/+ET4Xfhw+I74pvia+IT4gfiL+Ij4Z/hQ+Fv4d/iR+IX4gfiB+Hn4cvhd+Er4ufiU+gD9Uf/QAcoEIAhcC+gNnA86EUATmhVIGJUbkh8IJN4o9y0HM4s3FTvxPdRA2EOMRsVI2kpDTfxPe1I1VApVO1XsVBtU8VKyUWdQGE/lTeFMxUs4SgVIIUW/QRU+OjosNjwywy67KwgpkCYcJJAh3h7yG+oY5RX5EigQjQ1NC2IJsgcdBowE3wIWAT7/bP3C+1D6/fjV9wP3aPbW9T/1pvT08yTzNPJd8c/wbPAc8PTvHvCY8CXxhvHO8RzygvLh8h3zZ/Ph8430VPU99j73K/jr+Jb5Qfra+lb7q/sC/IX8IP2z/S/+nf7//k7/c/90/1f/OP8k/wL/5/7d/tP+w/6+/rL+j/5g/hr+zv2d/Wv9Iv3o/MT8t/yr/Iz8YvxG/EH8GPzL+5L7dvtY+yj79Pq2+oH6VfoQ+tb5tvlv+f34qvhv+C/45feM9zj39Pay9ln2/fWu9V/1//Si9Fj0KvT6887zuPOV82HzHfPf8qPyb/JG8i3yLPIz8jHyIPIv8kbyNfIG8tbxyvHY8d/x4fEF8kDycfKX8rXy1PLZ8s/y1vLo8grzLfNW85zz/fNS9IP0ofTJ9PT0EPUa9T71g/W89ff1PPaF9s/2+/YQ9yX3SPdc91r3ZveK97z36/cP+Cb4Qvhb+Fv4T/hG+ET4Ovg3+En4Yvh0+H/4gvh5+Hb4YPg1+CL4JPgr+Db4PPg2+D74R/g7+Cb4D/gE+Pn38vf59wb4EPgO+AH48Pfn99X3wPe197/34Pf69/739/f+9wL49ffV97H3n/el96P3vff39xb4Ivgm+C/4JvgH+NL3pvej98f39/cU+DT4U/ho+HH4Z/g6+AH42ffF9933Cvgs+Ez4d/id+Kb4oPh9+ET4Evj69wX4Hfgw+EL4W/iM+MT4xfic+G34T/hL+D/4P/hT+GX4e/iV+Kb4rvil+Hv4S/hB+Fr4a/hm+HH4nfjL+NP4tPiF+GP4R/gx+DT4Ufhw+H74k/in+Lz4w/ii+GT4Pfg1+C74LPhB+Gz4kfiS+H74dPh/+If4c/hN+Dj4P/hS+Fj4TvhI+EX4TPhS+FH4TvhQ+FP4VPhj+Gb4RPgc+BP4Hvg0+Dv4HvgS+C34Vvht+GL4RPg3+DT4J/ga+BT4Hfgl+B/4IPg0+Ej4UfhK+DX4LPgz+Dv4Ovg/+D34KPgc+CT4p/iX+gP9Uf/6ATQFzghNDAsP9RDMEvAUSxf5GVYdgyFNJocrJTHRNuY7CEBiQ3tGjUk2TEdOPVCOUjlV0FfLWfZacltgW7Nag1kBWDZWW1SsUiNRaE9ATbBKpEcfRBtArTseN7wyrS7vKoQncCSSIbQezRvkGNkVpxJyD2cMrAkzB+4E7AJEAeL/f/4M/Yr7LPr9+Nf3t/a99QD1c/T884/zLfPD8knyz/F18Sjx9PDe8PHwSfGl8evxQ/K08izzlPPn80f02vSI9TT26Pah92f4KvnX+YD6GPuY+xb8ofw2/c/9Uv66/i//rP8AACEAEwDi/8H/t/+j/3//Tf85/1H/bf9m/yz/1v5//h7+s/1M/ej8j/xY/FL8Y/xK/Af8xPuc+4T7QvvC+lL6HfoW+gv69vnf+bD5cvkp+dn4h/gV+JD3OPch9xf32PaD9lD2OfYH9oT12/Rm9Cb08vOv82fzR/M58xDz7fLO8obyMPLo8b/xtvGn8ZTxhfGf8cbxxPGf8XjxbfFq8Wzxb/F68Y/xtvHz8SXyPPI78jjySPJs8qDyvPLP8v/yP/N586zz0/Pp8wf0R/SW9MT06fQg9Wz1vPXm9fH1B/Yz9mD2fvaX9sz2GPdT93T3oPfO9+L33PfN99X33vfR98v38fcv+FX4YvhX+FX4b/ht+En4Hvj+9+337Pf/9xj4G/gT+Cr4U/hb+ED4IvgC+Pn38PfL96T3nPeu97X3u/fL99r36vf39/v3/Pfu99H3sPeT93f3aPd294T3i/ex9+T39vf39/H35PfC95z3hPd/95v3wffc9/z3M/hk+Fj4Hvjq99D3vvek95z3r/fg9yz4afiL+J34lfhi+CT4//fl98/3wvfZ9xD4Rvhv+Hf4cfhx+GD4Rvgt+Bv4Ivg2+EH4U/h4+Ir4hPht+Ff4RfhA+Eb4Tfhe+Gv4gvid+K74qfiF+Fn4UvhZ+FD4S/hU+HT4j/iU+IT4avhb+FL4Pvgu+Db4QfhG+F/4hPiR+H34ZPhW+E/4QPgk+Ab4EPg2+Eb4TPhb+Gj4avhs+GP4T/g9+DL4Ofg++Ej4UvhZ+FX4Tfg7+DH4Nfgw+Cv4LfhK+HP4ePhk+F74V/hD+CT4B/j89w34Hvgw+FX4efiP+HT4SPg5+Dj4KfgF+PT3DPgy+En4Vfhk+Hv4ffhi+IL4F/qB/M7+PgFDBPMHuQu/DtwQyRL5FEwX1hn7HPwgtCXmKo0wejYWPL9AaESyR/5K7U0yUBxSPFThVqRZ1ls8XftdGl6bXZdcHltdWXBXd1WhU9BRtk8QTcpJ/UW/QSM9SzhvM9cusyrzJoUjYSBjHWEaShcQFL8Qcg05Ci8HZATvAd7/JP66/If7Xvod+e/39vYW9jD1SPSE8wTzyPKk8nzyQ/IK8uPxz/G+8afxi/GA8bPxFfKQ8grzbfPi83z0FPWK9ev1SvbC9lf3+PeY+Cf5yPmO+mT7KfzG/Dz9n/0K/oj++v4+/2b/iv/S/ycAXgByAFwASABLAEUAHADK/3v/TP8v/wX/vf51/jr+A/7D/Xf9JP27/E78+vvI+6r7dfsi++T6y/qw+mr6B/qy+XH5JvnX+J34dvhC+Pj3r/dt9yf3xfZi9g72x/WD9Sn10vSh9IT0P/Tm85DzTvMR873yb/Iw8gzy7PHQ8bTxpvGX8XbxWvFL8TvxCvHn8O/wG/FG8U7xU/F78avxuPGu8aXxqvGw8bfx2fEd8l/yhPK18hvzh/Os86jzv/P08xv0F/QG9Df0n/Tu9B31WvW59Qz2O/ZY9nX2lfag9qX2wfYK91b3dveQ98f3BPge+AX43/fc9/73FPgV+B34P/h0+Jz4qfib+HH4R/gp+Bn4F/gp+C/4L/hL+HL4iPhw+D34+PfP98b3vPez97z35fcV+DX4OPgy+CD49/e794r3bfdq94L3jver99P37vf79/z37vfT9733p/ee9633wfe897n3yffb9+j35/fL97D3y/f09xb4LPg2+EX4Svg3+BH4+Pfq99735PcE+DD4V/h/+Kj4wviz+ID4Tfg0+C34Jfgc+Cv4Y/ie+Ln4xvjV+Mj4nfh9+G/4YvhF+DT4Vvic+Mn4v/ij+Kz4yPiz+IH4XfhV+Gn4cPh6+Jz4t/i0+Kb4l/iH+G/4S/g3+E/4dfh4+G74gfin+LD4kfhy+GH4W/hQ+Dr4OvhU+F34XPhc+Gb4ePh4+Gb4Xfhu+Gv4Ufg9+E34afh5+Gj4S/hS+Gn4dfha+EX4V/hr+Gn4Yfhm+Gj4VPhB+EX4WPhe+Ez4RPhl+Ij4gfhe+EH4P/hS+FP4R/hI+Eb4SfhR+Ff4VfhR+E/4Xfh3+Iz4mPiL+Hn4YvhX+E34UPh/+cD7Hv6mAKgDGAeyCtgNExDWEbkT4hU/GCMb5B5xI5AoJS4LNLc5pT6kQhhGX0lTTK5Op1DMUlhVCFhVWvFb6VxhXUddlVxMW4xZrlffVRVUKVLsTzdNBUpiRjhCkD2iOJEzxC54Kp8mDSOqH3McWhlWFiUTnQ/9C44IbgWdAhAA5v0k/Lj6fvlg+GD3YvZY9WT0p/MO847yJfLi8d7x7/Ht8dfxx/HN8c3xsfGt8evxTvK48hTzcfPw83304vQr9Wz1u/Ul9pb2KffW93j4Avma+UL64/pZ+5375PtX/Pf8e/3i/U7+zf5W/7n/6/8EAAsA9v/p/+v/6P/Q/6b/mP+6/93/y/+F/zv/F//5/qv+Kf6d/T39Bf3Q/IX8IvzU+6f7e/s9++36nPpR+gj6vPlu+RH5p/g1+Nz3rvdt9wD3j/ZV9kL2EPas9T/17vTA9Ir0JvTF83rzR/MM88XymfJ48lnyMfIL8u/xz/GV8VvxQPEy8SLxDvEA8R/xYPGL8Y7xjvGZ8aLxl/F+8XnxhfGi8dPxFfJj8rfy+/Im80TzVvNl83XzjPOv89vzHPR99Ob0M/Vz9ab1zPXc9eH18/UM9jX2a/a99h33bfen98X34fcH+An44ffF99X3Avgs+Ef4a/iW+Lf4xfjB+Ln4mfhj+EX4WPh4+Hz4c/h6+J34ufio+HL4P/gs+Cj4Ifge+BX4DvgP+CT4O/gv+AP45vfe9+X36/fh99n31vfi9/f3/vfq99L3ufex9773wPe198H34PcB+An4/Pf49+/33PfP98731ffd9/b3EPgr+EX4SfhA+DX4LPgf+A74CPgn+EL4QfhK+Gv4jvid+Jb4ifiM+I/4f/hu+Gf4Z/hz+ID4hfiN+Jr4rvjE+Mb4x/jC+K/4nPiM+HX4Y/hn+ID4ofi9+Nb45/jv+Of40fip+IH4ZfhU+Fn4e/ik+L740vjr+AH5+fji+L34lvh++Gj4U/hc+If4rfjD+NL42vjT+MH4ofh7+F74UPhT+Gj4ivio+LD4qPif+JT4gfhT+Cr4Jfg9+E/4XPhy+In4n/ie+Jj4hvhv+FH4M/gq+Dj4T/hP+FT4aPiJ+Jz4mPiP+JL4ivhz+HD4cPho+FL4RfhU+HL4h/iA+IP4lfif+I74b/hg+Fv4W/hO+Eb4Xvhv+G74f/in+dX7A/4vANUCKwbLCfQMLQ8FERITYBXCF4QaDh5nIlcnsSyEMmc4nj3PQW9FAklATLNOf1BhUslUbVe2WWZbnlxvXbBdQl1FXOVaLlksVx1VGlPVUP1NiUquRo5CGj5AOTE0ZS8GK/0mJyOCHxkcuhhBFbMRMA7DCl4HFQQjAZP+WPxh+p74JPfq9c30wfPW8jbyzvFs8Rrx6fDZ8MPwmvBl8EbwP/At8CrwXPDL8D7xofEO8pbyGvNn847zyfMg9HH0t/QW9Zj1IPai9hL3iPcG+ID48Phx+RP6uPpW++r7fPwA/Wr9x/0d/nT+v/75/j7/i//V/wMAKgBhAJcAsACtALAAtwCzAI0ATwAFAMr/lP85/+D+jP47/vn9v/2A/S/9yvxU/OH7dvsF+3z67fmD+Uf5FfnK+Fz44/d19w/3mfb+9Vv14vSb9HL0U/Qn9PbzwvOS82TzFPOh8h/ywfGT8X/xa/FE8TDxRPFl8WDxOvEQ8evw4vDp8PLw9/AO8Tnxb/Gg8a/xpPGO8ZHxrvHR8evxDfJO8rDyG/Ns85Tzq/PN8/DzD/Qk9EL0ffTG9Bf1YvWk9ej1JfZS9mv2ifa19uX2FfdF93/3vffq9/j3A/gd+DD4Mfg3+FX4eviY+K74vvjI+ND4w/iv+KP4oviu+LX4tfiy+LH4pPiV+IP4efhq+Fb4U/hT+Ff4UPhP+E/4QPgl+AH46ffc99j33Pfi9+j3+fcH+AT4+vf49+T3u/eX93/3e/eJ95f3qvfJ99v36Pfr9+L32PfL97b3nPeQ96j3wvfM99T34vf09/j37Pfc9+D37ff89wj4EPgk+C74Mfg0+Dj4O/g8+Dz4PfhU+Hn4iPh9+H74hfh7+Gv4Xfhl+Ib4ovis+Lb4zvjo+Pb41vig+ID4ePh2+Gz4dfiZ+Lr4xvjP+Nv42/i++IX4Xvhu+IT4b/hZ+HL4p/i6+JX4dPh3+HT4Wfgx+Cv4Wfh8+G34W/h2+JP4ifhd+D/4R/hY+EL4Jfgw+FP4YvhK+D34TPhd+FX4QfhN+GD4Y/hj+GL4XfhT+Dn4GfgO+B74Lfg2+E74Zfh8+In4e/hb+EL4NPgp+CL4IPgV+Cv4XPhs+Fz4Rfg4+D34UfhT+Ej4N/g7+Fr4afhf+D/4Kfgv+D74RPhE+FH4ZfiH+LH49Pkm/E3+hQA0A44GLwpMDX0PexHCEyYWlBhiGwQfaCNkKN4tyjPAOfk+OkMQR9RKKU6rUJRSpVQyV+lZNlzqXSVf8F9CYO5fAV+cXepbD1oqWChWwFPQUExNUEnuRCxADDu8NaIwBSzzJyckbiDUHG0ZCBZZEmUOagqZBgMDxv/r/Jn6yPg299D1n/Sh85fyg/GR8OXvdO8j7/Du6O4M7yzvJO8E7/Pu7u7s7vjuM++b7yTwtvBB8cDxGPJM8mXyevKT8rHy2fIn86jzPvTV9Gf15/Va9s32TffN9zL4jPgF+bb5cvoB+3b79/uT/Dn9tv0P/mv+3f5L/7P/GwBzAK4AzAD5ADEBUwE3AQUB/QASAQoBwgB7AEoAFQDN/23/Bf+W/hP+hf0L/Zr8Efxn+9L6a/oK+or59Phl+PT3fffm9kr2ufU19bX0TvT486XzUfPz8qHyYfIf8tDxgvFE8Q/x4/DB8K/wm/CB8HPwY/BV8FPwVfBW8FDwWfB98KjwuPC18LLw2PAO8SjxPfFm8bPx+PEk8lXyjPK08szy2vL68jvzbfOi8/fzZvTL9AP1J/VV9ZX1ufW39cf1/vVB9oH2vfYB91f3j/en97v30Pfd99T31vf49zH4V/hZ+Fv4ffit+L/4r/iU+IH4gfiR+Jj4jvh2+Gf4cviI+JL4fvhm+F34X/hR+D34H/j89+339vcQ+Bz4//fj9/H3B/gC+NT3nfeL95P3kveA92X3XPdw94/3pPeY94T3ffeK95z3ifdc9zj3NvdL9133VPdC90n3XveD96j3rvej95/3rvfO98X3nvdy91/3fPeW96b3s/fQ9/n3IPg3+Db4HfgJ+P737vfk9+T36ffw9xT4R/hZ+E74Qvg9+En4Svgv+CH4L/hF+FP4VfhZ+GP4WvhB+C74G/gU+CD4M/hM+Gj4f/iE+ID4ffhk+D74HvgN+Aj4Evgp+Ej4aPh6+Hz4cvhm+FH4O/gk+CL4M/g8+Dj4Mvg4+Er4Tvgw+An4//cQ+Br4Gvgc+Cr4O/g/+Cz4FvgC+Oj31PfL98v3z/fV9+T3A/gf+CX4Bvjq9+737vfb98P3vvfY9+v34ffU99T33vfm9+H32vfe99v34/cB+Bz4IfgA+OP33ffl9+P3zPe597/34PcH+Bv4Hfgq+C74mPhk+rb87/5uAaIEYwgNDOsO9hDkEhwVhRcbGlsdkSGSJi0sXDLdOPs+HkRkSF1MGFAqU3lVgVf9Wf5c719XYjZkvWXLZg5nj2aMZSBkbmKXYJxeXFyqWXJWs1JzTqZJT0TAPl05ZDTDL2YrRid6I9wfJBwuGOgTiA8uCwAHGwOK/2386vnx9172A/W884XyY/Fg8HnvrO787XTtGe3w7PLs9uzx7NjswuzG7N7sDe1M7ZztFO6b7g/vd+/A7+rvBPAH8AvwHPA+8HPwxfBF8d/xe/IS85vzG/Sm9DD1tfVA9tX2aPcM+L/4b/kh+tD6avsM/MD8bP0e/s7+bf8AAI4AAgFYAZUBugHfAQMCHQIgAiECJAIcAgECzwGDAS4B0QBZANn/UP+7/iT+kP36/F78t/sC+1j6u/kY+W/4yvc897P2JPaP9fH0XvTe81zzyvJE8trxffEy8QDxwvCJ8GfwS/Am8Pbvxu+V73LvS+8n7xXvEe8g7zbvX++P763vxO/j7wbwIfAl8B7wN/Bo8KDwxfDk8BPxWvG18fbxJvJa8o7yy/IE8zrzbPOi89rzHvRt9LX06/Qa9V/1qfXr9RH2K/Zg9p320/b89ij3UveB97/34/f/9x/4Kfgm+DH4MPgl+Cv4RPho+IP4mviq+Lf4wvi0+I/4X/gp+AL4+ff69/b3A/go+Ef4Tfg2+BT45vez94v3b/dd90L3Pfde94f3oPeY93n3Vvcz9xP3+Pbm9uL22vbp9g/3MfdC9yv3DvcI9wD37PbF9qr2u/bX9vT2CPcJ9xL3Hvcx9z/3MvcZ9wH3AvcV9yn3L/cr9zX3Sfdd9173YPdr94D3mveq96P3n/eg95f3jPd793T3dfd595X3wfff9+j38/f69/n36/e/96H3oveh95X3m/ey99r3+Pf79/f38/fk98X3r/ey98T3x/fH99D36vf89+v3y/ez96n3ofed96f3vffV9+r39/cC+PL3uPeD9233a/dr92b3cPeW98b37vf49+D3u/ed93/3YPdJ9zn3RPdn94z3n/et96r3mveP94L3cfdc91/3dPeN96b3q/eg95L3gPdc9zP3JPc89233m/e198T34Pf39+j3qfdZ9yr3Gfce9y/3Tvd/97b34/cC+AL43vep9273PvcY9wf3HviV+kT95v/iAm0GOgqCDbgPYBE4E3AVBRggGykfISTKKf4voDY2PQJDtUfLS9hPqlPIVk1Z5lsNX4xiv2U0aAZqa2s+bFVs0mvoaqBpJGiYZtJklGKwXxFc2VcpU/RNWkikQjs9Tji8M2cvNCsVJ/QisB4yGnAVmRDrC6EHtgMnABD9Zfoo+EH2f/TK8iTxrO+A7p3t6+xd7O7rtOul647rQevP6nnqVepO6lzqgurT6mDrD+yw7Cftcu2Z7bPt0+3e7cXtue3h7TTupO4c75DvCfCX8Dnx3PF58hXzsPNa9Cf19fWd9jz3+Pe8+HP5Jfrf+qT7dvxM/ST+/v7W/5cANQHGAVECsALXAu4C+gL5AucCxAKoAp4ChQJXAigC7gGlAT0BtgAHADv/YP6D/bP85PsS+1b6vfke+XX4y/cW92H2p/Xl9Dz0s/Mu86LyIPK/8Vzx3vBO8NLvee8w7+nute6j7qvuv+677rnuw+637ojuW
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