![](\"https://habrastorage.org/webt/ia/m9/zk/iam9zkyzqebnf_okxipihkgjwnw.jpeg\")
\n",
" \n",
"**
\n",
"\n",
"Prior to working on the assignment, you'd better check out the corresponding course material:\n",
" - [Exploratory data analysis with Pandas](https://nbviewer.jupyter.org/github/Yorko/mlcourse_open/blob/master/jupyter_english/topic01_pandas_data_analysis/topic1_pandas_data_analysis.ipynb?flush_cache=true), the same as an interactive web-based [Kaggle Notebook](https://www.kaggle.com/kashnitsky/topic-1-exploratory-data-analysis-with-pandas)\n",
" - [Visualization: from Simple Distributions to Dimensionality Reduction](https://mlcourse.ai/notebooks/blob/master/jupyter_english/topic02_visual_data_analysis/topic2_visual_data_analysis.ipynb?flush_cache=true), the same as a [Kaggle Notebook](https://www.kaggle.com/kashnitsky/topic-2-visual-data-analysis-in-python)\n",
" - [Overview of Seaborn, Matplotlib and Plotly libraries](https://mlcourse.ai/notebooks/blob/master/jupyter_english/topic02_visual_data_analysis/topic2_additional_seaborn_matplotlib_plotly.ipynb?flush_cache=true), the same as a [Kaggle Notebook](https://www.kaggle.com/kashnitsky/topic-2-part-2-seaborn-and-plotly) \n",
" - first lectures in [this](https://www.youtube.com/watch?v=QKTuw4PNOsU&list=PLVlY_7IJCMJeRfZ68eVfEcu-UcN9BbwiX) YouTube playlist \n",
" - you can also practice with demo assignments, which are simpler and already shared with solutions: [A1 demo](https://www.kaggle.com/kashnitsky/a1-demo-pandas-and-uci-adult-dataset), [solution](https://www.kaggle.com/kashnitsky/a1-demo-pandas-and-uci-adult-dataset-solution), [A2 demo](https://www.kaggle.com/kashnitsky/a2-demo-analyzing-cardiovascular-data), [solution](https://www.kaggle.com/kashnitsky/a2-demo-analyzing-cardiovascular-data-solution)\n",
"\n",
"### Your task is to:\n",
" 1. write code and perform computations in the cells below;\n",
" 2. choose answers in the [webform](https://docs.google.com/forms/d/1GXgR4TsqoTH_nQkrgluqWBElpK0emfhNzdZWZQObtnw).\n",
"\n",
"*For discussions, please stick to [ODS Slack](https://opendatascience.slack.com/), channel __#mlcourse_ai_eng__, pinned thread __#a2_bonus__. If you are sure that something is not 100% correct, please leave your feedback via the mentioned webform ↑*\n",
"\n",
"-----"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"from pathlib import Path\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"# if seaborn is not yet installed, run `pip install seaborn` in terminal\n",
"import seaborn as sns\n",
"\n",
"sns.set()\n",
"\n",
"# sharper plots\n",
"%config InlineBackend.figure_format = 'retina'\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Download the data [archive](https://drive.google.com/file/d/1C5nTzitvJ0ho2Crpqnghg9r2yq98Xxun/view?usp=sharing) (Archived ~ 114 Mb, unzipped – ~ 690 Mb). No need to unzip – pandas can unzip on the fly.\n",
"* Place it in the `\"../../_static/data/assignment2\"` folder, or change the path below according to your location.\n",
"* The dataset has information about carriers and flights between US airports during the year 2008. \n",
"* Column description is available [here](https://www.transtats.bts.gov/Fields.asp?gnoyr_VQ=FGJ). Visit this site to find ex. meaning of flight cancellation codes."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Consider the following terms we use:\n",
"* unique flight – a record (row) in the dataset\n",
"* completed flight – flight that is not cancelled (Cancelled==0 in the dataset)\n",
"* flight code – a combination of ['UniqueCarrier','FlightNum'], i.e. UA52\n",
"* airport code – a three letter airport alias from 'Origin or 'Dest' columns"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Reading data into memory and creating a Pandas ``DataFrame`` object**\n",
"\n",
"(This may take a while, be patient)\n",
"\n",
"We are not going to read in the whole dataset. In order to reduce memory footprint, we instead load only needed columns and cast them to suitable data types."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"dtype = {\n",
" \"DayOfWeek\": np.uint8,\n",
" \"DayofMonth\": np.uint8,\n",
" \"Month\": np.uint8,\n",
" \"Cancelled\": np.uint8,\n",
" \"Year\": np.uint16,\n",
" \"FlightNum\": np.uint16,\n",
" \"Distance\": np.uint16,\n",
" \"UniqueCarrier\": str,\n",
" \"CancellationCode\": str,\n",
" \"Origin\": str,\n",
" \"Dest\": str,\n",
" \"ArrDelay\": np.float16,\n",
" \"DepDelay\": np.float16,\n",
" \"CarrierDelay\": np.float16,\n",
" \"WeatherDelay\": np.float16,\n",
" \"NASDelay\": np.float16,\n",
" \"SecurityDelay\": np.float16,\n",
" \"LateAircraftDelay\": np.float16,\n",
" \"DepTime\": np.float16,\n",
"}\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"PATH_TO_DATA = Path(\"data\")\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# change the path if needed\n",
"flights_df = pd.read_csv(\n",
" PATH_TO_DATA / \"flights_2008.csv.bz2\", usecols=dtype.keys(), dtype=dtype\n",
")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Check the number of rows and columns and print column names.**"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(7009728, 19)\n",
"Index(['Year', 'Month', 'DayofMonth', 'DayOfWeek', 'DepTime', 'UniqueCarrier',\n",
" 'FlightNum', 'ArrDelay', 'DepDelay', 'Origin', 'Dest', 'Distance',\n",
" 'Cancelled', 'CancellationCode', 'CarrierDelay', 'WeatherDelay',\n",
" 'NASDelay', 'SecurityDelay', 'LateAircraftDelay'],\n",
" dtype='object')\n"
]
}
],
"source": [
"print(flights_df.shape)\n",
"print(flights_df.columns)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Print first 5 rows of the dataset.**"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Year Month DayofMonth DayOfWeek DepTime UniqueCarrier FlightNum \\\n",
"0 2008 1 3 4 2003.0 WN 335 \n",
"1 2008 1 3 4 754.0 WN 3231 \n",
"2 2008 1 3 4 628.0 WN 448 \n",
"3 2008 1 3 4 926.0 WN 1746 \n",
"4 2008 1 3 4 1829.0 WN 3920 \n",
"\n",
" ArrDelay DepDelay Origin Dest Distance Cancelled CancellationCode \\\n",
"0 -14.0 8.0 IAD TPA 810 0 NaN \n",
"1 2.0 19.0 IAD TPA 810 0 NaN \n",
"2 14.0 8.0 IND BWI 515 0 NaN \n",
"3 -6.0 -4.0 IND BWI 515 0 NaN \n",
"4 34.0 34.0 IND BWI 515 0 NaN \n",
"\n",
" CarrierDelay WeatherDelay NASDelay SecurityDelay LateAircraftDelay \n",
"0 NaN NaN NaN NaN NaN \n",
"1 NaN NaN NaN NaN NaN \n",
"2 NaN NaN NaN NaN NaN \n",
"3 NaN NaN NaN NaN NaN \n",
"4 2.0 0.0 0.0 0.0 32.0 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df.head(5)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Transpose the frame to see all features at once.**"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"| \n", " | Year | \n", "Month | \n", "DayofMonth | \n", "DayOfWeek | \n", "DepTime | \n", "UniqueCarrier | \n", "FlightNum | \n", "ArrDelay | \n", "DepDelay | \n", "Origin | \n", "Dest | \n", "Distance | \n", "Cancelled | \n", "CancellationCode | \n", "CarrierDelay | \n", "WeatherDelay | \n", "NASDelay | \n", "SecurityDelay | \n", "LateAircraftDelay | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "2008 | \n", "1 | \n", "3 | \n", "4 | \n", "2003.0 | \n", "WN | \n", "335 | \n", "-14.0 | \n", "8.0 | \n", "IAD | \n", "TPA | \n", "810 | \n", "0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
| 1 | \n", "2008 | \n", "1 | \n", "3 | \n", "4 | \n", "754.0 | \n", "WN | \n", "3231 | \n", "2.0 | \n", "19.0 | \n", "IAD | \n", "TPA | \n", "810 | \n", "0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
| 2 | \n", "2008 | \n", "1 | \n", "3 | \n", "4 | \n", "628.0 | \n", "WN | \n", "448 | \n", "14.0 | \n", "8.0 | \n", "IND | \n", "BWI | \n", "515 | \n", "0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
| 3 | \n", "2008 | \n", "1 | \n", "3 | \n", "4 | \n", "926.0 | \n", "WN | \n", "1746 | \n", "-6.0 | \n", "-4.0 | \n", "IND | \n", "BWI | \n", "515 | \n", "0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
| 4 | \n", "2008 | \n", "1 | \n", "3 | \n", "4 | \n", "1829.0 | \n", "WN | \n", "3920 | \n", "34.0 | \n", "34.0 | \n", "IND | \n", "BWI | \n", "515 | \n", "0 | \n", "NaN | \n", "2.0 | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "32.0 | \n", "
\n",
"\n",
"\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" 0 1 2 3 4\n",
"Year 2008 2008 2008 2008 2008\n",
"Month 1 1 1 1 1\n",
"DayofMonth 3 3 3 3 3\n",
"DayOfWeek 4 4 4 4 4\n",
"DepTime 2003.0 754.0 628.0 926.0 1829.0\n",
"UniqueCarrier WN WN WN WN WN\n",
"FlightNum 335 3231 448 1746 3920\n",
"ArrDelay -14.0 2.0 14.0 -6.0 34.0\n",
"DepDelay 8.0 19.0 8.0 -4.0 34.0\n",
"Origin IAD IAD IND IND IND\n",
"Dest TPA TPA BWI BWI BWI\n",
"Distance 810 810 515 515 515\n",
"Cancelled 0 0 0 0 0\n",
"CancellationCode NaN NaN NaN NaN NaN\n",
"CarrierDelay NaN NaN NaN NaN 2.0\n",
"WeatherDelay NaN NaN NaN NaN 0.0\n",
"NASDelay NaN NaN NaN NaN 0.0\n",
"SecurityDelay NaN NaN NaN NaN 0.0\n",
"LateAircraftDelay NaN NaN NaN NaN 32.0"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df.head(5).T\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Examine data types of all features and total dataframe size in memory.**"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"| \n", " | 0 | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "
|---|---|---|---|---|---|
| Year | \n", "2008 | \n", "2008 | \n", "2008 | \n", "2008 | \n", "2008 | \n", "
| Month | \n", "1 | \n", "1 | \n", "1 | \n", "1 | \n", "1 | \n", "
| DayofMonth | \n", "3 | \n", "3 | \n", "3 | \n", "3 | \n", "3 | \n", "
| DayOfWeek | \n", "4 | \n", "4 | \n", "4 | \n", "4 | \n", "4 | \n", "
| DepTime | \n", "2003.0 | \n", "754.0 | \n", "628.0 | \n", "926.0 | \n", "1829.0 | \n", "
| UniqueCarrier | \n", "WN | \n", "WN | \n", "WN | \n", "WN | \n", "WN | \n", "
| FlightNum | \n", "335 | \n", "3231 | \n", "448 | \n", "1746 | \n", "3920 | \n", "
| ArrDelay | \n", "-14.0 | \n", "2.0 | \n", "14.0 | \n", "-6.0 | \n", "34.0 | \n", "
| DepDelay | \n", "8.0 | \n", "19.0 | \n", "8.0 | \n", "-4.0 | \n", "34.0 | \n", "
| Origin | \n", "IAD | \n", "IAD | \n", "IND | \n", "IND | \n", "IND | \n", "
| Dest | \n", "TPA | \n", "TPA | \n", "BWI | \n", "BWI | \n", "BWI | \n", "
| Distance | \n", "810 | \n", "810 | \n", "515 | \n", "515 | \n", "515 | \n", "
| Cancelled | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "
| CancellationCode | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
| CarrierDelay | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2.0 | \n", "
| WeatherDelay | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "
| NASDelay | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "
| SecurityDelay | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "
| LateAircraftDelay | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "32.0 | \n", "
\n",
"\n",
"\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" count mean std min 25% \\\n",
"Year 7009728.0 2008.000000 0.000000 2008.0 2008.0 \n",
"Month 7009728.0 6.375130 3.406737 1.0 3.0 \n",
"DayofMonth 7009728.0 15.728015 8.797068 1.0 8.0 \n",
"DayOfWeek 7009728.0 3.924182 1.988259 1.0 2.0 \n",
"DepTime 6873482.0 NaN NaN 1.0 928.0 \n",
"FlightNum 7009728.0 2224.200105 1961.715999 1.0 622.0 \n",
"ArrDelay 6855029.0 NaN NaN -519.0 -10.0 \n",
"DepDelay 6873482.0 NaN NaN -534.0 -4.0 \n",
"Distance 7009728.0 726.387029 562.101803 11.0 325.0 \n",
"Cancelled 7009728.0 0.019606 0.138643 0.0 0.0 \n",
"CarrierDelay 1524735.0 NaN NaN 0.0 0.0 \n",
"WeatherDelay 1524735.0 NaN NaN 0.0 0.0 \n",
"NASDelay 1524735.0 NaN NaN 0.0 0.0 \n",
"SecurityDelay 1524735.0 NaN NaN 0.0 0.0 \n",
"LateAircraftDelay 1524735.0 NaN NaN 0.0 0.0 \n",
"\n",
" 50% 75% max \n",
"Year 2008.0 2008.0 2008.0 \n",
"Month 6.0 9.0 12.0 \n",
"DayofMonth 16.0 23.0 31.0 \n",
"DayOfWeek 4.0 6.0 7.0 \n",
"DepTime 1325.0 1728.0 2400.0 \n",
"FlightNum 1571.0 3518.0 9743.0 \n",
"ArrDelay -2.0 12.0 2460.0 \n",
"DepDelay -1.0 8.0 2468.0 \n",
"Distance 581.0 954.0 4962.0 \n",
"Cancelled 0.0 0.0 1.0 \n",
"CarrierDelay 0.0 16.0 2436.0 \n",
"WeatherDelay 0.0 0.0 1352.0 \n",
"NASDelay 6.0 21.0 1357.0 \n",
"SecurityDelay 0.0 0.0 392.0 \n",
"LateAircraftDelay 0.0 26.0 1316.0 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df.describe().T\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Count unique Carriers and plot their relative share of flights:**"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"20"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df[\"UniqueCarrier\"].nunique()\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"| \n", " | count | \n", "mean | \n", "std | \n", "min | \n", "25% | \n", "50% | \n", "75% | \n", "max | \n", "
|---|---|---|---|---|---|---|---|---|
| Year | \n", "7009728.0 | \n", "2008.000000 | \n", "0.000000 | \n", "2008.0 | \n", "2008.0 | \n", "2008.0 | \n", "2008.0 | \n", "2008.0 | \n", "
| Month | \n", "7009728.0 | \n", "6.375130 | \n", "3.406737 | \n", "1.0 | \n", "3.0 | \n", "6.0 | \n", "9.0 | \n", "12.0 | \n", "
| DayofMonth | \n", "7009728.0 | \n", "15.728015 | \n", "8.797068 | \n", "1.0 | \n", "8.0 | \n", "16.0 | \n", "23.0 | \n", "31.0 | \n", "
| DayOfWeek | \n", "7009728.0 | \n", "3.924182 | \n", "1.988259 | \n", "1.0 | \n", "2.0 | \n", "4.0 | \n", "6.0 | \n", "7.0 | \n", "
| DepTime | \n", "6873482.0 | \n", "NaN | \n", "NaN | \n", "1.0 | \n", "928.0 | \n", "1325.0 | \n", "1728.0 | \n", "2400.0 | \n", "
| FlightNum | \n", "7009728.0 | \n", "2224.200105 | \n", "1961.715999 | \n", "1.0 | \n", "622.0 | \n", "1571.0 | \n", "3518.0 | \n", "9743.0 | \n", "
| ArrDelay | \n", "6855029.0 | \n", "NaN | \n", "NaN | \n", "-519.0 | \n", "-10.0 | \n", "-2.0 | \n", "12.0 | \n", "2460.0 | \n", "
| DepDelay | \n", "6873482.0 | \n", "NaN | \n", "NaN | \n", "-534.0 | \n", "-4.0 | \n", "-1.0 | \n", "8.0 | \n", "2468.0 | \n", "
| Distance | \n", "7009728.0 | \n", "726.387029 | \n", "562.101803 | \n", "11.0 | \n", "325.0 | \n", "581.0 | \n", "954.0 | \n", "4962.0 | \n", "
| Cancelled | \n", "7009728.0 | \n", "0.019606 | \n", "0.138643 | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "1.0 | \n", "
| CarrierDelay | \n", "1524735.0 | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "16.0 | \n", "2436.0 | \n", "
| WeatherDelay | \n", "1524735.0 | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "1352.0 | \n", "
| NASDelay | \n", "1524735.0 | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "0.0 | \n", "6.0 | \n", "21.0 | \n", "1357.0 | \n", "
| SecurityDelay | \n", "1524735.0 | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "392.0 | \n", "
| LateAircraftDelay | \n", "1524735.0 | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "0.0 | \n", "0.0 | \n", "26.0 | \n", "1316.0 | \n", "
"
]
},
"metadata": {
"image/png": {
"height": 286,
"width": 373
}
},
"output_type": "display_data"
}
],
"source": [
"flights_df.groupby(\"UniqueCarrier\").size().plot(kind=\"bar\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**We can also _group by_ category/categories in order to calculate different aggregated statistics.**\n",
"\n",
"**For example, finding top-3 flight codes, that have the largest total distance traveled in year 2008.**"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"UniqueCarrier FlightNum\n",
"CO 15 1796244.0\n",
" 14 1796244.0\n",
"UA 52 1789722.0\n",
"Name: Distance, dtype: float64"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df.groupby([\"UniqueCarrier\", \"FlightNum\"])[\"Distance\"].sum().sort_values(\n",
" ascending=False\n",
").iloc[:3]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Another way:**"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Distance Cancelled\n",
" mean sum count sum\n",
"UniqueCarrier FlightNum \n",
"CO 15 4962.000000 1796244.0 362 0\n",
" 14 4962.000000 1796244.0 362 0\n",
"UA 52 2465.181818 1789722.0 726 8"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df.groupby([\"UniqueCarrier\", \"FlightNum\"]).agg(\n",
" {\"Distance\": [np.mean, np.sum, \"count\"], \"Cancelled\": np.sum}\n",
").sort_values((\"Distance\", \"sum\"), ascending=False).iloc[0:3]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Number of flights by days of week and months:**"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"| \n", " | \n", " | Distance | \n", "Cancelled | \n", "||
|---|---|---|---|---|---|
| \n", " | \n", " | mean | \n", "sum | \n", "count | \n", "sum | \n", "
| UniqueCarrier | \n", "FlightNum | \n", "\n", " | \n", " | \n", " | \n", " |
| CO | \n", "15 | \n", "4962.000000 | \n", "1796244.0 | \n", "362 | \n", "0 | \n", "
| 14 | \n", "4962.000000 | \n", "1796244.0 | \n", "362 | \n", "0 | \n", "|
| UA | \n", "52 | \n", "2465.181818 | \n", "1789722.0 | \n", "726 | \n", "8 | \n", "
\n",
"\n",
"\n",
" \n",
"
\n",
"
"
],
"text/plain": [
"DayOfWeek 1 2 3 4 5 6 7\n",
"Month \n",
"1 80807 97298 100080 102043 81940 67178 76419\n",
"2 81504 79700 80587 82158 102726 66462 76099\n",
"3 103210 81159 82307 82831 82936 86153 97494\n",
"4 82463 100785 102586 82799 82964 68304 78225\n",
"5 80626 79884 81264 102572 102878 84493 74576\n",
"6 104168 82160 82902 83617 83930 72322 99566\n",
"7 84095 103429 103315 105035 79349 72219 80489\n",
"8 82983 80895 81773 82625 103878 86155 93970\n",
"9 94300 91533 74057 75589 75881 58343 71205\n",
"10 75131 72195 91900 94123 93894 58168 70794\n",
"11 74214 72443 73653 68071 70484 76031 88376\n",
"12 92700 90568 85241 70761 74306 61708 69674"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.crosstab(flights_df[\"Month\"], flights_df[\"DayOfWeek\"])\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**It can also be handy to color such tables in order to easily notice outliers:**"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"| DayOfWeek | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "5 | \n", "6 | \n", "7 | \n", "
|---|---|---|---|---|---|---|---|
| Month | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
| 1 | \n", "80807 | \n", "97298 | \n", "100080 | \n", "102043 | \n", "81940 | \n", "67178 | \n", "76419 | \n", "
| 2 | \n", "81504 | \n", "79700 | \n", "80587 | \n", "82158 | \n", "102726 | \n", "66462 | \n", "76099 | \n", "
| 3 | \n", "103210 | \n", "81159 | \n", "82307 | \n", "82831 | \n", "82936 | \n", "86153 | \n", "97494 | \n", "
| 4 | \n", "82463 | \n", "100785 | \n", "102586 | \n", "82799 | \n", "82964 | \n", "68304 | \n", "78225 | \n", "
| 5 | \n", "80626 | \n", "79884 | \n", "81264 | \n", "102572 | \n", "102878 | \n", "84493 | \n", "74576 | \n", "
| 6 | \n", "104168 | \n", "82160 | \n", "82902 | \n", "83617 | \n", "83930 | \n", "72322 | \n", "99566 | \n", "
| 7 | \n", "84095 | \n", "103429 | \n", "103315 | \n", "105035 | \n", "79349 | \n", "72219 | \n", "80489 | \n", "
| 8 | \n", "82983 | \n", "80895 | \n", "81773 | \n", "82625 | \n", "103878 | \n", "86155 | \n", "93970 | \n", "
| 9 | \n", "94300 | \n", "91533 | \n", "74057 | \n", "75589 | \n", "75881 | \n", "58343 | \n", "71205 | \n", "
| 10 | \n", "75131 | \n", "72195 | \n", "91900 | \n", "94123 | \n", "93894 | \n", "58168 | \n", "70794 | \n", "
| 11 | \n", "74214 | \n", "72443 | \n", "73653 | \n", "68071 | \n", "70484 | \n", "76031 | \n", "88376 | \n", "
| 12 | \n", "92700 | \n", "90568 | \n", "85241 | \n", "70761 | \n", "74306 | \n", "61708 | \n", "69674 | \n", "
"
]
},
"metadata": {
"image/png": {
"height": 251,
"width": 162
}
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(\n",
" pd.crosstab(flights_df[\"Month\"], flights_df[\"DayOfWeek\"]),\n",
" cmap=\"seismic\",\n",
" interpolation=\"none\",\n",
")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Flight distance histogram:**"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"
"
]
},
"metadata": {
"image/png": {
"height": 266,
"width": 380
}
},
"output_type": "display_data"
}
],
"source": [
"flights_df.hist(\"Distance\", bins=20)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Making a histogram of flight frequency by date.**"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"flights_df[\"Date\"] = pd.to_datetime(\n",
" flights_df.rename(columns={\"DayofMonth\": \"Day\"})[[\"Year\", \"Month\", \"Day\"]]\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"num_flights_by_date = flights_df.groupby(\"Date\").size()\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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6oFuW8dXNPfj3vzwn0qZQrOCbv1zjOzSPv/g23nPGEbHzKpVtPPrCDuzeP4LLzz4S0zjNtwxcsGVOAXpBIluT8lediyUbb+11S3JaFrD0iFY/eAucXr4z2VhXg8VzW7D6DYJvH5Md8OgzaUnq0ZxpDdTvnb1fsjYjEWJm23ZClYXOOX4mprXW4bgFHf421iEXZQe8QIEX9Ihsjj6iPWQjyg6QWDK3FS8R2gP/PEcEcUuPaMNzrwdlUv2MQtEECgYGBnyYQGEKIJNOcR+SBnwMjhSxmqnXHhVclco2nuXUEPdMbMfBbx7bhH19Y7jqokUTdjjLFRur39iHXT0jOP/E2ehoqRXuazsOvn/PK1TzpN0xfTS27Br0hYeA69i9vHF/ZKDw3Lq9VLdZQCzGJPHM2t347ZNu063te4exY98w5hOruSxeeHOfHyQArpA0X6ygsU4cKPzi4TepVc+ewXATLRZ7+0bx/btf9WvXVxwHn718Wazd4Qpe9oz8zdRmMyiWgkyW99aCmc1oqgvoLXFO7wmLOiKyA2Gb9uYcFs1xr1uSfhllc+KiTvQS14iMmLksoh4xNKK2phz+7D1Hh/YjV+FdG3qRYVpbHY6d3475M5tCxxIV9LQ0ZnEkxyaOrtVYV4NZXQ14legrEaW3AFxx9lFzWrCKqE7l2xDnx9D/DAwMSJhAYQrAUI/UsOqNvRQnGgjoDTys3dLj1xWnbMY9jFc39+CR1a7Qs3+4gH+6+lTtua3f3of//P06v2PsW3uG8DdXnijcf9PbA6EOq3YMxee5deGgR8TB9uBVoCERd51t3T0Y0nKIKBwe/ueZbaFt0UFcBavfoIM+tpFV2MbGv9/1CtXBnOxAaxAGr9s7uSAhci6PX9ghWOnmZ+NOWux2JOY7yoxz3VqHqy46yt+XpfewNhecPAfLFnTi2Hkt+NXyDaF9vbHY30JkeVSGRpQTZCbZ+zNpc9yCDlx7xQnC/XkO/OI5LThqbitOWTLNz7Zxy6NG9GpIWRY3uBA5+rO7GtFQW4M09d24/xuNgoGBgQgmUJgCyKSNmFkFvZwV56gus89ynGQgOM9kd9Rt411QdVAoVfCD375GBSX7+qJ1EC9t7I58fyRfwrNr92Dh7BbMn9kMx3Hw4oawDemMb945gCdf2YUzjpmOY45sR75Yxrpt8TXx2XP48KrtnICMcMocl4JRl3NvI2OFMnZ0hyumOBHX8/a9w6GAJe7yX7+9L+T4GrZeNLgZBaJjcFHgHB6/sJPLaec5k7XZtK9niKMR/Z/zFuCyM4+k7Hl8e9LpPfO4mTjzuFno7h6iqhCR3z3PsR7Jl8ViZiajkMvyAwVWPxBnQx0Lh3q1YHYL/s95C8VjRGg0AJd2BPCDC5HN4rlu5saKCUg83UYcxdDAwODwgAkUpgDSpjyqEngPQtGq9VihTAUCZN1xz6aJqBwii3LFxhMv7YTtABeeNBuZdAovbewOZS7IeXX3j+HXyzeivTmHj1y8GBaAlzaGxb7k13/n8o1YuXYPctk0vv35M7F/IM8PlAg/6Jb7XkP/cBFPv7obP/m787F2Sy83E0DO7VePbsDzb+zFp993LC46dZ7fgCtkMz65UtnGjb9Yjb29Y/js5cfglKXTsG3PENdhj7qcVWr1e3hlU09oW1SgaMAPFPzuv2Wb24yrpSGLudMbqUo7vPr+Flzu+7tOnoPs+Ip8XPOw2mz40RNXHpW0ocqVEt89L4Bxxcz864PVG4i0Tmx51HyMTRz1iG8TvI6jES2Z1wpAEFxEZCFEc2N1GnF0QQMDg8MHJlCYAmDFzMbpiQbPGRA5oy9t7PZXE+d0NaIul8bG8UZP3kOykaG6lMoV1GSixdEvbujGr5ZvBOBSxy48aQ6eez2cuSCdmLse2+Q3PpozrRGL57RyMw5koLhyXFtRKFaw8rU9GBrjV0TyxnEcB/3DwT77B8a4wQgQrPTv7x/D8nH9wk13voSLTp2HnftHMDQarqbkTW3l2t3YOa4r+NH9a/Hzr1yIzUQjKMqGOJ6egTyK5QpmdrglGnkZHDIDsX9gDL/4w5toqKvBpy87Bpm0xW0eRZ7nvqECHl61HfNnNuP0Y6aH9p2qePOtPjz03Fs4aUkXzj9x9oQ+y3Ec37l1HEegUXD/Fzmjxy3oQMqy+NV4iN/guSfMwtXvXkrZcqvxEAF+LWcVns/RD2zqaslAIbCLzyiUhBoFx3Yox1omo8AGFzybOGFynE2cRmHOtEbXhhdcCEu3tnKPBYAvZPdQLFWAOn6TOgMDg8MLJlCYAsikTEZBBdxAQXDONu8MVqxPXdpFUXA8E/Z89w4WqKZEPPzy0YAjfccjG3DK0mlYu6U3cl4kZWjFy7uo8qTN9TUYHHfMRSvqQ6NFrCE+4/iFHX4lJ8+GdyxkidIlc1uxfkf/uI27jc2CVCo2N5tAjsPLarAla1mbnd3D+Kefr4LjAF/80Ak4fmFHbEbh18s34vXx72xWZwNOWtyFnsGwHoGUddz12EasGtc9zJnWSNWN9+Y5VijjmCPbqJXiA4m+oQK+/euXAABvvNWH04+e7lO6orCvfwyvbtqPU5dOQ0uj21tg1/5hXP/T55HNpPC3V50Iy7JCpVGBeMfy+IVu1Z/4lf6w02tp2PBpNIENeT5S4GcUeMcymi+LNQq2gwoRRPDmFZ4bvWrPs+Gt9BeI8qh8ulKwgs8LyAA3mPrT8xdydR1xwUVbU87/jNA4nIyCgYGBAWD6KEwJpI1GQQkq1KOdBGf+iBnNzEpkQL0gsZ/jiLLwOrZ6WP3GPn8O01rrgnkJvsuh0RJeJlb6T1oyLZiXwGbr7kE/A5HLpqnyjaKVwdVv7sPIeEDS1pSjKhZ582XPXd9QgaqjT8I7nlwNfetwHAebRBmF8c//9R83+qu/N939CsYKZezhVHginX4yG7Lytd0UjWxaG3GeiWNYRYijn3ltN/XZK156G//y3y/gu3e9jJWvhUXhPAwMF/DjB9biv/7wRlUqwjiOgzseWe//XbEdjEj0xugdzOPr/7Uav1q+ETf/9jV/+0/uew17ekexfd8wfr18I5VNoK5NgTMKAM0NWSyb7+kNgu+a13CNJwBOx1Tw4VGP4nQNZKBgEZcfefny7g2RGgVJMTM7Nyo7wLGh7jMI6xq41KMYAfRn33cMbvmbd+JPTp/Ht4koQ3vZmUdEjsNSj0yJVAMDAw8mUJgCYKlHJqMQjTHOg5DnXDuOQ5XdnNPVwH2wFsv05/VKVNBprmcCBaJc61nHBb0JRF9l/3DBX4G3AJy4qIOw4RuRjviR05uQJZx17/hLzLG8QmQTls5rFTgJtBO1t3eUqsQ0neOQs87Rvr4xDI+5zm19LkM78ePjDI7QtKm39gz53Pg5XeFusSwKxYrfawIATjqqK9aGdJp2dg/jO3es8cfc+HY/14aEbTv45/9eg1Vv7MOKV3bjxRjxOTnWTXe/gt8+uTmWSvjihu4QPSzuFmDbDm657zU/CCQzMy8S1+IL6/dRgQKZKeM5o9Pb6/Hpy47GP3zsJN8x59FbKBpRTi47UIih+MStjlMZBUrMTGQUOA5uuWJzq54B8mJmdiGnEJdRYSoShYIL7vEHr7nBVU0m9LvjZy4Cm8+892h8/v3L8L6zj+SOE3w39D3AZBQMDAw8mEBhCoAtj2oarkVDVqPQP1z0HYS6XAZtTTnm4e3+X2Iekiy1pVyxsentAeoB3MwIoMnMxTtIB5aYGLnKWLEd/3tub85RgmpvXqyDSQoyp7fXcSkEbHZkgNArzOgQBEqMc7Xq9T1+M7rWxixmEdQdb25spoSs575gVjPDa3f/Z52crXsC55btzcD7DeSLFWwnNA3HEZ1zRT8Zz6HtHy7gm79YTb0ns2r68Krt1PXQPxTf4yFfLOOrt67Cq5t78OCzb2H73nAlKBKPvbgztC2qUpQ3r627+RW6yOusXHGYQCEI4HidfNubcjj7uJmYTvQSYWk3AGIFwHHZARm6juPQ/QqojAIZvMSImQE3K8SDqzeI1k4A4SAmH0MjYm1spqSqrAA6NriI0XUsntOK046eTmmupDIKzHm8/6kt+Px3n8Cvx3VZBgYGhw9MoDAFYBquqSGOevTbJzfja7etwiOrt/vbZnc1uKt83IwCEygQGYXRfAn//N8v4Bt3rME/3/q8vz2ToX863sputiaFjuYcd16i6krT2+u5Tn9UZml6Wz3XgYtqojajvV5QWYW2WfFy4LgefUQbd/W2wIxDdr1eOLuFtvHoSoyjQzq682c2x9LvimXbP75sTcrn5Iv2B1zHcf32Pnzt56uwjdFDZGO6ee/pHcW9K7ZQ22Q0DXc/sZn6e3CUL0AH3O962x61yk+O4+DhVdupbeS5Y7UNVKDQVg/yCGymNCqXRsRb6dfIDlAOeZyj7DhuNabx05BJp6hyncLyqMJAQVAEgBUzy1CPHDajwNeSsOeNzlzEUK/GjylOCxEnmq7l6Fy4AUkE9eipV3fhdyu3oViysXzNjlBQYWBgcGjDBApTAJk0v3GOAR9RYuaegby/ivvwqh3++3PGV8V5DixL1/FWkAulCr5/z6v+ivDLG7tRGRdFijjPM0IOfPBd1gjqkk9vq+cGilEP5Glt9dwHPnss1Nza+XNjqVf7CcfyyJnN3Lrr7Ny2EkLm2Z0N3PKVrBNGlt2cO72RokR4AUm2hn/O2hpzUlm4odESbv7tq75QnETcqv0Lb+4L/RbjaEQbdvTjcSZDEBX4d/eN8YXGEcPs3D8SOh7y+OtDgUIQ+Ha11oacSxWnn7vSXSPnjObjHFh2XhEZCBXqEQAMjPADhYoTrzcAwuJsmeCCpfjoUK/i5sYNLjRs2AUGb65v7RnC7Q+Tze3imy4aGBgcWjCBwhSAySjIg13N8+A5C6LV29ldbjlBHmWBdfq9QOHOP270S6myNqxz7SGUHSA+WuTET2+vFzRBisoO1AloRGKbaW113LlFBSQzO/hZiFD3W4ID3taco23G58Y2cCJXutubapngwv1fVNe+tTHHnReLHfuGfUe8LpfBhafMDc3LA3td6fR4ePrV3aFtUTaiBn9RQYxQaD4+Tl2tOKPQ2VIXSYlhReqAqNSpAo3I8WhEapmLqHKq9O84eC0OFPjUI0dCOwCExdlxxw+EgyU1MbP7+yooZhRKZdv/jtIpC5l0OAMm083Zm+t9T20JBQbm8WRgcHjBBApTAGlWzGw0CkKIqAWiUqcevBKZMnSd3sECxgplPLM2XBXH+3xRXfbp7Ko9MR+WruPbtNVxnV5RMGKB5/SPO/CC1b6O5hxyNWnl4GKWpK6BRHtTLRX4eJczr6kT4DouLQ1Z7vGwFC8PrYzexAsUWaeGdLSOmtuKdywmBdDBfv/zzDZc8+9P4j9/97q/jRsoEEaDI0WsemMvVeZ2K49GREypb6iAtVt7/Hm+JQgUooILUmjOmxvrhJOlbDtbakMr13HZAYtznpVKndoOyhWHcmBrON9rKICJGIM3J3ZeJEjqEasVouk9fBpR1Ny0KiXxgitOEB8ntGadfjaw4FHleD172HuNRxNj6XqA0dAZGBxuMIHCFAArZo6jRBzOEDkCnpNUETjKs7vC1CPR6njFdvDky7u49KLAiRdQjwQr/Y7jCJ1rISVI4MC3N+dQk0nT1AbvWAQ2XrUbbldWQUCSy6aFAnBRtiPK6Reds5bGLFIpi0s9Ep2DMPUI4/uLA5ioIO7eFVvgOMBz6/Zib98o+oYKVOM6dhzbcfCtX72IHz/wOv7z925wUShWsGv/SMjGO5axQhnX/ex5fO+uV3DfU672gadP8D5ftH39dn5GwRFkyLzPamnIIluTDmkBaAc22oGvjIuM42g0KtkBf5yoFXjGgRdlk8hjIX1k8tojHXstpz+kUZATQCtlB8azMGrUI/o8y4isK7aDim2HOlfnSxWM5EtalD0DA4NDCyZQmALIpFKm4ZokeEJmgKARCQIFT0gsw9EHEBKLBjbu/yIHlqUeeeOUKw63Mk/KstDRUqtECZrWxnH6/eyImN7k2tDzAsRO/8z2+nCZxxjqVWtT2OkXNXXywG8EFX08rY1ZmqokEGaT6IrQj5AYGC5yV1LJcYZGS9g93gPCowK9tXeI+x1746x6Y69fTeoPz22H4zh4i6iIRJbcFS3avr1v2BfON9fXUCvzQRDHP2cdLbUAOCvdMXz7lGWFOiHHCZNZTr+yY+3EUY/4YmYyO9BKiN1JkMdYcdiMgmzVI4mSqoRNoVRhKEHxFK9yxSZoe3ybKF2HUDvB/G5497JCscLtcQIY6pGBweEGEyhMAWQy4ZrbHgZHi1i/vY/r1BSKFax6Yy/6JEo2kp+3Zv0+ocM91SHMKHjUk3L4PJFViLh8e86DUiR+jKP4TOc58bYjdHi7WmvdPho8Z1zg8PlOP8fpFYqsx20oSlBMQDKzw6NrBdtisx1NrjPKzSjEBAqs4287fCcGGKceSQZ9HkR0rZBWoVTBFlGgwPluimUbpbLNpSrR49Db9/WP+YFDY10NOlriG/WRtKMl89qkG24BLu0ICP8GVKv+hCv4xNBo2GZjElWC4sXMwWsHwbkiA5LWRn6VMXK+shkF1T4KrA2p4RHtHxJMK86LpZFJ06g4v8tCqYI9vYJAQSJSsG0HP3/wDXzh31fgiZfD5X8NDAwOHphA4QDDgnuzTzOraYC7en7dT5/Ht371Eu5jyjQOjBRxw3+txo8feB3fuP0FVGzxSqqHfLGMb9y+BrfctxY33/NqosdBolyxcevv1uKbv1hNlRpNAiInyHN6eRU5PnDuAv+1TO8BEnOnNaKxLljpjaou1FhX4+/L0miiMhDu/hwxs7CyUl34WGIpUe44LFUhymZmRzjocSSdfl52QJhRGF/5Zc+BKOgBxGLmSDE3Qz3y4gN2nOGxEpVRmDutkZoX71jGCmVxoOBXfaJvt9uI8rBHzmjiBmQkSmUbT7+6y/97KVO6NqrTMhBkFNjV8WKM0w/E0YLiK/iorsDHUY+E5VGJcVoa4jMKsk4/GyiR44jK7JI2Y/n4QCFK0yCT6WCDPqlxBJTIQrHiZ8xYyGgUfrl8A55+bTdGC2X873P87KyBgcHBARMoHGCk0ylYlgWLwzd/du0ev9vtg8++5b8/PFbCd+98yV/x6RksoG8wPqtw34qt2NfnVkARCSJZVGwb//WHN/GPP30Oa4mmWlG4848bcf+Tm7Hy1V14eLXcQ6JYquD+p7bgdyu3RjqIeVGHVY6Y9dgF7fjm587A2cfN9LfxRLZRJUVPWTpNWj9ANrNiV/qE2YE2TqAQ44xP49CIfH56hA6CN6+ocbyMAl2Ryf1ftHLf3sx3+t1xBHoDP7gIttkR5wzgZRTc/6OaqE0TUI/YcYZGilSPh4WzW/zXQRYmXPWJdPy9IMs9lnFbxr8itQZHzGiK7SNx/9Nb/E7jNZkUTlzUGTpnrH6AROd4xiLEa5cq9RnYFMtqNBpbWqNAH0tU1sLiBIkAvZAgzCiQ1CONIGaMuAflGM2HyIbMKPB6KADMb5P9XmSyMI6DfEHiu2TOHY+ul4/IKARamArueGQ9bn1wnf+cAtwu9WSJ4H1E1S0DA4ODDyZQOMDwytelUyTX2L0Ri+gv//PMNt9h8G1iVnn29I7i0Rd2RO7Dw+0Pb8CKV3Zhd88o/ocIVkTY3TNCdZrdIBGQOI6DHz/wOn63chvuf2ornlsXrjbkIU7MTFKCmuuzPp/fQ5yY+cMXHYXFc1zHsKUxi3ceP5N6sFYqYurRDFE3W1vswHrBhcrq+HQvo8ALLjhBViZtoaM5vJocR3Ga1RklgBY5/WF6i5eFiNUosILRqECBEUw7McdiWeBoQfjnefOuQd+xa6yrwbRWghIkyCjs6xvzHaJ0ysIRM5pCNqHeE0TFoxmhpnv0/LfuHqRWZj90/kJXaM4ES+WKI6SGeNQjluIVJ7L1jsnDKOMox1XWkRcMB/fAOI1CSiajINQoEPdaJ75XAcA4/fl4wXDIhjlncftLU6JCmQ7inOUkKE6RGYWwMN+1cf9//KVdeOzFnVj52h7cQzQZvOeJTdT+ZEbWwMDg4AN/mcJg0uCtxnFXegXO2JZdYYpDHG303ic3U3/z18BovLp5P1a8ElAdNuzoj9zfcRzc8cgGaltXW51g7wCPrt6Blzft9//2sh48xImZK0T1jljxH4d6c/ZxM3HxqXMxPFZCNpNyq8QwNinwdQ0ejQjgd5nlgU89wvi8wg/whtoMulrDgUKFcywejprT6u9rcRx4nk06ZQXjKOgn2j29AaeCS3xGgXF6BeesoTaDbE2acqTitRM5sRaEOc+bdg74r+dOa5TK9qzb1kvZZEmRsUA0vpMI9lubcoxgmP5Br35zn8/EP+bINlx48hwAHO58RHDVyRMzV8lRZu9nMhoFlYZrvIZ+AH0sLYKMAkkVqlTsWDE3EKE3iOjuTeo0dKhHUiLrKO2EKCCLKKnqYbRQpu7DbU05Xwvn/QaWEwtPK17ZhavfvRT5Yplq8GdgYHDwwwQKBxhpP6PAWelmHAvHcWBZFrepWJzAbAPTOCyOZWo7DtWREwBmjfciEGFv3xjeEDSDEmFf3yh+8zgdxJDnggXpPNRkUn42wDt8cqWf1wmZpuuM2xAOqdcJmFwFYx/GNlGNhMSRxCoyG1zwHOvGuhosmNkcHoPj9M6f2YyZHfU4c9kMbnDp0VtIGtXJi7swZ1ojzj5uBv9YIpz+aW11wTgKYua2Zo7Tb4+vdAuyXq2cQMGJEIC3+uJnYl4eJUhgE2RUSBv+sZDFATqaa7mVotjgihQ/z5veKKXrIGlyrTGdpkfzAbXjlCXT/M9na+IXIooUtHOySqyjKEO9kRHmhst2Eg6sYKU7SjAdVR5VlFFoFWkUiDmPEWNka+h+NqK5jU2hjELUeZbTgvB/y3t7R/0Fq9bGLOpzmSBQGD/hvF4Y+zlBQlw3cwMDg6kNEygcYGRSYWfMWx0eKdA1rMsVGzWZNIZ4gULEzdh2HAxz6mHbjiPk1w6PlvwOxR7ibvg84XJcALN+e39o7lHHQj7Y63MZDJSL1NxI5ysd05XUHq8h7j0QLYsfpLAOXIVxEs8+dgY6WmqxbH47MU7wvsOUIDz6iDZcdPIczJveiLpcJjQvnmO5bH47PvjOQJTNmxdAO7BLx8cR27j/8zjKi+e28m1iei9wqx45YqcfCMTMbBZCJMpt5Yifve9fRcjr+Mcvnlt7s0ALwYxDrr62NOQwTDj2vk3kOWB7T9Dvk98R6TSG+eb8MZrra3w7LYqL4up4ODsQvwrPOrDy5VH5GgVRRoE8RjIAi8oOkPfnUeK+LB0oyJyz8TK0juMu5IxJBGQqAnCujYDiR/ZVmNnRQD1zvHsAL1Do5ugRTDlVA4ODGyZQOMDwOs/yGq4NMhqF0UIF9QDGCuEbO+uQe9kHwH1I8Zxvx3HoZVkCvKxF3MLQZNiQzkN9bcbXcXjHTz7geA8ylrJAOvDZjIBvzQQXZAaisa4Gn37vMeFxGOeSdJQb6mpwEtEhGOCv2pOOJVsxh52Xw8lCcbvfxjRcu/LixQCAs46eFm3DCS68Zmvu8dA2ogyERyNy7UHbCKhHnkhVRTvhlR5V6QkBuKvw5G9LFCiRv9Wm+hpqBdm3KfLnls2kUJfLRGYURF192etZHCgFFMA0c95Uy6PKrI5HZwckRLaMMDccKND7Al5GRa2PAnkvjXb6g98S5fRHBhdEcFWQzEJYlr9QNCphE5kdku6jIL7+AWBGRz1GCLGyd2lmM+HP7+YsFpmMgoHBwQ0jZj7A8MXMHI0CK2YeK5QxOBLODADE6mixgn/57xfwpf94Fm+NiyV5GQggvGpJYogjpI4TTA8JshYeyhUba7f2UBUyuDYRS1B5JqPAjkPy2vkaBXpupNPPc6xdG+bBSjiJQhvq+7QpRzkXE8BUOM4476HMc5bIuWU543DLoxKOwkWnzMPH/uRov0EdeyyuYNbmNgX0mq25NvTc4oTM7DiOI9N3IdjmILr7dScnoxBHo/LG4paujXCuGutr+GVLI6hUbGM71rkSOYBstkMUKHjHD0SLWWVWrunVcf5aE9ugjabExK90hzsZx5dHpRuUpdBQyx+HyiiQ2YEa8boZeX+WoV5F2YgceIChOGnQlWSqS4W6TMcFCu31oWsGEFGPwhkFEycYGBzcMIHCAUZAPQqvjg4McwIFkdM/fjf+w/NvYfOuQfQM5vH9e14BEM5MeCCdEa/BlYfBGAd+f/8Yfvr71/Hgs9v8bXGUqDse2YDv3fUKbrhtlU8R4uotCJtS2cb67X2+Q08FCrVkfwP3/7JNBgrx2QE5p5+eG6VpENiwglHKged1v2UoMazTm+VkFNgxADCBDy+4iM4O8FYu2WtTVL6WcvolNBpAoDcIzS3CgfFWii2mY3CUDbfqU0zDOcAVQXMF4BHBRVN9VqDriDsewob5eBH3PErMSoIMFKJW+2V6AshQb9jAR4Z6Q+u07JiqR8Fr7z7GZi1qMikutZL8LcnMC9DMDihSjwCaLilDPYpqbBf13fg2EZk7DzM72Ipc/EDBcRwu9chkFAwMDm4kQj2qVCr49a9/jfvuuw9btmxBpVLB3Llz8Z73vAef+cxnkMvRKeDXXnsNt9xyC1577TWMjo5i0aJF+MQnPoHLL7+c+/lbt27FD37wA6xZswb9/f2YN28errjiCnz0ox+lUsIe9u7di1tuuQUrV65Ed3c3Zs6cife973348z//c2SzYd7q4OAgfvKTn2D58uXYvXs3Ojs7cckll+ALX/gCGhsbQ/snCV551IrjoFyxqZV3wH1wiJw07+ZNVmzpHw80eKv2pM3unhF8966XkU5Z+MpHT0ZbUy6WEvTfD6/H2q1upZd505tw3IIObkBC2ngVlHoGC1i3rQ/HL+zgZi5Im5vufgVvvNWHYxe042+uODFEPQpsvIyCStUjSDn9bAWXOGectWE1CjynP2VZsBCIzB2HptHEBRe8SlnccXhi3nI0XYENlMQVjwJnlD5+8Qp8OxVcsOOIqEd0FsKjaoiEmQDZlTha18GirakWKaKMqUxGoamuRpqu5R5PmErFOlfUqr8oo2A7KNnxgQJpUyhV/N9bJs3vicDOjap6FEO9scepgOp8+7DjT4LX24PWWrj9aWqzaWo13/2s4L4hQ+9x5xa8pqseiR+h4j4KcRQn9zikqkuxWRjF5nFRwaWHGe31dANJQV+QfLGC/TydmgkUDAwOakw4o1CpVHDNNdfg61//OrZs2YITTjgBp512Gvbt24ebb74ZH//4xzE2FqwyrFy5Eh/+8IexYsUKLFq0CKeffjo2bNiAv/u7v8O///u/hz7/zTffxJ/+6Z/iwQcfxKxZs3Duuediz549+Od//md86UtfCu2/Z88eXHHFFbjrrrvQ3NyM888/HyMjI7j55pvx6U9/GqUS7TQPDw/jYx/7GH72s5/Bsiycf/75sCwLt912G6688koMDQ2FxkgS6fEHM9twjefcjxUqwoyCd/PmPeiHxgSBwrjNbX94E72DBXT353H7w+sB8LMQ5A3fCxIA4NnX3b4HKjQiz+GPylyUK7ZfRWntll6UK3Y89ahCZhSiKT6OpNNvpcQrcKIsRBS9g0cjAqJX4Xk2fI1CNPWIV6tfKaPgOMKO0WSTsSgtCAnW6fdtbP4KfMqyMG96ELyH58av4NTZyhEze/0dBI5SbTaN+lpWO+D+H5WFcDMKHEc2jkoVoVGgVv1FGYUIjYLXPI+1GVNw+j1IU28ImxFSNCxT6pOtlBSqehQOqnjdkus4FZbIAFqG3gOIswPZrPgRKqIRReoaFMuwRoqZhTbB60pMoYFsJoX25lpuOdpQo8KxEroHDPXIwOBQw4QzCnfffTeeeOIJLFmyBD/96U8xffp0AEBvby+uueYavPTSS/jRj36Ev/3bv0U+n8ff//3fAwB+/vOf44wzzgAAbN++HR//+Mfx4x//GBdffDGOPfZYAO4D4Etf+hKGh4fx7W9/G+9///v9z7766qvx+9//HhdffDEuvfRSfz5f+9rXsGfPHvz1X/81rrnmGgDA6Ogo/uIv/gLPPPMMbr/9dvzZn/2Zv/9NN92E9evX44orrsANN9yAVCqFcrmM//f//h8eeOAB3HTTTfjqV7860dMkRIZbHhUYGAl3Wh4rlGOzA7ySoLxVewBwxtevNxGlU9du7XFtFCoreboAno0o7ew56FGZC9a5HCuUKYEjmVEggwsPfOpR8Jrtb8BbgXdt6IekXBaCGMemHVjROO7D2PFtiiV6hTS0f0zVI17gwzrWpN5A1GWXzQ6Q8+pqrcWSeW0oFCtUhSXZajwzyN4TEdzpc4+fifbmWhw5o8nvMMzOjT1nV124CC2NOSye2+pn7LgaDWGXaU4WQoJ61FhXEwpIXZuYKk7MOSNREGYUCBuHbrh1xPQm1GbTmDOtEUvmtfrbhTz4hGk0wlV4iS7DbuZOTKMhf9l+DxXinHnXsTtWcC9Npyyf7gnQ4n/e/YI3t4JE0A+IszAiehcgph6Jvpuo3gsyWhDH5ndm9jB9vBEgt7kh87vZ0zPi/y5y2aDPickoGBgc3JhwRuG+++4DAPy///f//CABANrb2/G1r30NAPDggw8CAB544AH09PTg8ssv94MEAJg3bx7+7u/+DgBw++23+9tXrlyJ9evX47TTTvODBPazyf23bNmCJ554AvPmzcPnP/95f3t9fT3+5V/+Bel0GnfccYe/fXBwEHfffTcaGxvx5S9/2acxZTIZXH/99WhpacE999yD0VF+K/skIGq4xuoTAGCsWBbqDTzHIsNxXIXBBWe136saxBNNi+73UU6/SJdcKtuRZVvdfegH0Wi+TFOPqIyCN/84MTPj9MeswLs2xNwYB6ZGFFywGgWKehS/0seu3HOpR0zQA8RTqcKOdXygFJUdaKitwZ+952j83w8cSwmgozIqi2a34Nj57Thz2QycslRcXYkMejpb6/D+c+bjhEWd9PGQlAjmPLc05nD6MdOFgumo8rCAuGO0ayPOQrjceHBsorMqom7D7Hh0eVR6gYHMKCyY1Ywvf/QkfPTixdR3qFrfH2A0CrJ9BBTpSroN17xzRQYK3nxZu0yG7pVAnmYR7QoQfzdRwQU5Dnn9i7KQ5LwB9pwJnP6IjJJM5qYSU/XIyxLyglg2WN62O8i+k93MTZxgYHBwY8KBQltbGxYsWIDjjz8+9N6RRx4JANi3bx8A4KmnngIAXHTRRaF9L7jgAqTTaaxYscLf5u3/rne9K7T/SSedhI6ODqxZswbDw8MAgKeffhqO4+CCCy4IaRdmzZqFY445Bjt37sSmTW6L+dWrVyOfz+OMM84IaREaGhpw5plnIp/PY/Xq1VLnQgfeg4Fd6WQrHgFyYmbeg2toTGTj/s9zKLkZBYHXX/KFyWKnn80slMo2RvNlbvUcntMLuE4N6TzU5cIZhVJMedQQvUVRb8A617wMDt9GtWwh7VyIdA3kGABixdmsCJSukiTnwBU5FI+ouTkO7ejO7KjH31x5Iv788mMo54ydG+UcS+hH2ICEq7fg9YSI6zJNbIuz8Rr18asrxVVx4lOPSAG5BTo4jcrCyGTItKg3sp2JFTMX5P7FcqCd4GW66AAxyMKxn8U6yzXplLCho6zTT885IrjQCEhEZWhl9AYVrapH0XqbGRGd41m7bYSWp4sIFAAjaDYwOJgx4UDhxz/+Mf7whz+gvr4+9N5rr70GAJgxw+0Mu3HjRgDA4sWLQ/s2NjZi2rRp6O3txf79+wHAd+h5+wPA/PnzYds2Nm/eTO1/1FFHcfdfsMBtWLVhwwal/devX899PwnUcPoouBkFAfVIWMHI/Z99CIn0Dq6Na8Rz9niBiuhmXy7bKJYqXH40rxEa4GZHRGVbg9Q2bTOSLzFVj8Ji5grZcI3zEA9lFBTFzLbjUN2fxdkBxoGVKcMa0+Mhegz3/7hxop1+uapPUnStUEZB8Zyxc5Op4CLhKMc1qSPByyg4AifJg5dV4TVPE5ZH9cTMHKE5O1Y2m6Y+O6rqkSjwU3VG2XHGJGhEQFg07UHkkJPfJXm98BonxmUUvLFrc/T8ajIpbq8UINrpFwUXvLnF2gi2A2KKl1jMHLxmKX6yVY9IG3ZuM8YzClyNAvO72bon6E7e1VrLLd9sYGBw8KFqDdccx8H3v/99AMAll1wCAOju7gYAdHV1cW26urqwe/du7N+/H52dnX4mImp/AH5g4e0/bdo0qf1l5gMAPT093PeTQEN9Fl1dTSgxD39ub6ZUCiMER7+5IetTkZqaa9HV1YQM44Q1NNWGqn54aGtrQGdrHWpzGarCUldXU6jiEvkeC8eyUFPH74KaTqf4n5dKISVIp2ezNejqasIA01jOSqf9gCNlAdM6gyxQpiaNrq4mWESg1NnREJpvU2NQ/aW2tgY5Yt6NDTnu8eWYzEWuNrBpbhTYEA/p5pY6qvZlF2dewDhtbDw+bGtrQJlwfGZOb0ZXOx2MZ4m5O4773VAdVWe0oLmB/l66CUpbOpNGQ1Ow8keWmyXn19wc7JPL1aCWoBg1Cc5ZA7FPfX2Oci7bWupiz3NTcx2sVHAOO9sjztk42tsa4BDr/9O7mkI2pMNrWRa6upqQEqzwHjG7FV1dTWjbNxKMN36dOeA7ex2t7rE1NdHXWVdXk7Bi2aL5ncjVpFFPfJ8NxHXVQwhE63IZ6pjIc9bcUof8zsBZa2vln+daMsAmzofo+gdoh5v8Lrs6+d8LANQQ9yLST5w+rdnXf5AQBV81mTQ1RldXE1qaB/y/s1n3nOwmKu7U5txz3sqMk8um0d4WXtQCgCbBbxkAmpvC8wXE1zIA1NfVcLd3CK5lgMmqEOeDdy0D9MIIW8Vt1owWblDeQywcpdMp6lpuacyhdzA4j0cv7EJXVxP1/Tc11XKvZ5IuO392K9Jr3vbvRx0dTaGFC9E5OBRwKB+bh0P5GA/lY9NB1foofO9738Pq1avR2dmJz3zmMwDgVz+qreXfdL3tniag2vt7/9fV1UntXw14GQCqPKpto28oXGZuZKxEZRrIh62INzo8VqKyAzyuKUs5yDMUH3//CGEyLwPi2ozvwzgBI8y8eOOwVA2yRneok60nZi5H04LCPQEkVtSZbI8M3zi00ktRYuJFhizfWKYaESBBVwqVRlQrwSgzL66NxEpniG9dkuC1M6uWceNw9Qai3gPj9AkVjYIXmHEbrnHGaayr8Y+NlyFi7eoiqv+w15lYNMzvI1CXE68bicS8IroeOzcSIuqNCiWI4tn72USCejRuwx5TTSYtpBFFahSEGQV1G56OLLAJ3iNX7EVZGPb3TC4UyJS6rdg2dQ8g+5oAwOyuxtA4Xp+XKMrS9I4GJutjMgoGBgcrqpJR+P73v4///M//RDabxU033YT29nYAQDqdhuM4wtSvB3s8V59Ouw+hqbJ/NVAuVdDdPYR+YhWnVLaxrzccnPQN5qlVG7LzaF//KLq7hzDEOOw7dvVjkLBpasj6n7G/ZxhWpQL2ebJ1e1D6tKE2g5FxZ6JScdDdHS4XO5YvYfvOfv/vxroaP4NQLJbR3T0U6tjZ2z+GnbuDVcFMOuVnC8bGiujuHkL3/mH6WIjUdrYmjSHinOUL7jijRBnG4eF8aL6jo8H5GRktoqcvOM922eYeX5kIJmzbQd9AYFMpV7g25Epfb+8Ihgma1dhogWtDLrt2dw9RD/ChgTEUGa0J6eRVKjb27hukVvkG+kcxxFzbg8TqdL5Yxt7u4ByTlwE5v9ER5pz1BivsonNWIL6HwcE8+oaCzyiPXxMsyCCvr2+UupYL49cEC9L/6O4exiiRuRoZzqO7Oziqrq4mykkqj899iFNhDABS9vj7g8E5K+RL6O4ewohA91OTcs/dGHGdDY8UsHvPAFeP09KQ9Y+rQKzUDw6O+dt3EdzvdMqizgN5bfb1jVJBRbFQ4p6zEhGA9RHXg2Pzv0uAvp7Jcz7C+Y1xdyTQ3zeCwmj4nIsWIlKWe8zeKp97nyN+++PfSW9fcF1WvOuSuXdbcDDMWYQBgILgfAHAqIAmKfwtAygV+Znc4UHxORMFS4ODY+gWUrbCpzplWejpGebuT94DisUKRaWsJ4LrtqYchgfHMAz3OeWhr38Ue/YOCjVrAFCborU9+7qH/ICY/B4PNRzKx+bhUD7Gw+HYdJBoRqFcLuOf/umf8KMf/Qi5XA4//OEPceqpp/rv19XVuSsRBf6DOZ93b+ANDQ3+/uT2pPb39BSq+1cDaU551IrtUM69h/0Def9hWp/LUJx673nIVgra3x/Y1OXStI2gpGo/MXYLUefeey6EmkGVbUoH0dIYUCj87rccYTIpfm4lbTh8ewDoJakF2TS3O2uZWoWL6yPA9FEQZBTSzKotWVJRSgDtxK/0AxyOfszc2CpJJebYeSu64UZw8cJktjOxnK6BXk2M60zt2gSvZao+seOENApcXQcxhqyYmdtHgb944GkUSBu2pCwJ8roXlUelswRMh2IdMTMlMo6vu+/ObWJ8exLC1XGm03bUGPRv3/2fX/WIySik6YpU9LzUNQrRWQjB/URLNK2mhZAdo8IUACCpimRflKjiDCxqMil0tdZxu8AbGBgcfEgsUBgZGcHnP/95v9HZrbfeivPOO4/ax9MOeNoAFqxmwNvf0xQktb+3n+rnVwN+eVTGSeTRcsgsQ1NDllvbmuWN7iVWzJvqs6EbPgAqXQ0Au4kV45YGkgfPH4OtxkTZQFDBKB9hIxinl1iVrs0KqEdxfRSYGuJ0UzNJYa6MMDkkzI0WJgP0wzjP0JvinH7blusyzQoMixI2IWecsBFRgiwmiKGpVzLnDHKVothuzuXocfg0orDT31Cb8WkrvN+MiHbhVz0KBTD8wIKkD/JKt7JjsccUJWbOicTMoqpHkn0USOg415GVgjjXOY/ew6O1kM6oL2Zmqx4x5VFJRFY90gmUJi0gCdtEH0vw2mb6KLQ3BwtDZJM+9r4R1XthZns9UikrVLrYwMDg4EQigcLAwAA+/vGP46mnnsLMmTPxy1/+ksokePCqC3lVikgMDw9j3759aG9vR2dnJ7W/V52IhOM42LJlC9LpNBYuXBi7PzmuV0VJdv8lS5Zw308C3g2dXuUrcx0R8l7bXF8T23ALAPaQwUV9DbeCC1uRaE9PYEOt9Nv8MfLFCvqH+E5/ULaUzSiUqApOVObCs2GyI6TIrjabZipxeMcSzdFlV61LMk6/hkMeDi7UVuGpTrwSYziS2ZFwfweJlf4oG0mNhkygxDp/BYkeD9F9IaK7WfNKyi6e24psTQrvPetIwiawtx3HzZAIMwr88qjkOWusq8Hsrga0NGRxwUmzg3E4gS8ARhPCahTouZG6DmGGSFD1KKoRmBavn+NcW5b4swC+o8xzei3G2QUk+yikU8JARbbUKWWjo2tQPH5APbiQPRY2O3D2cTMxvb0ebU05XCi4Nh1H3KQQAGZ1uQGGRZCPHJhIwcDgYMWEA4VisYjPfvazeP3117Fo0SLceeedwnKm5557LgBg+fLlofcee+wxVCoVKgvh7f/HP/4xtP+LL76I3t5enHzyyX4PBG//xx9/PKQr2LVrF9544w3Mnj0bixYtAgCceuqpqK2txbPPPhsSLI+MjODZZ59FfX09Tj75ZKlzoQNRwzUPokdKc0OWS1UIZRR6Az5qU12WW+aOdeLJ4KKlIXDgHYQdUg/7iMwFj67EipndjAKfruR3Zg6VR6VLOfJWh6mMAseJtRinX6aPgsU8WCkBtI6jLOGQ5yUcuJDIWmteaj0RyJr+0jZMrXaxmDl4zTrXMj0eSuWgy3TKsviUFV49eMIR/7P3LMWPrj0Pl542T2DjCkZFfPqmOk/MTBwLIzJubczixj87Dd/9i7Nx5IxmfztF8SIcK1GztdDcmIZrouBKVFlH1BOEtaG2K9JoohxeoQ3H6aWCyvH/eYECK/6uyaSobBcJnVKnst2cZW10ggt+FkaSesRQHLta6/Avf346vnPNWVRGIap0M4vZneOBAoceZmBgcPBhwoHCzTffjJdffhkzZ87E7bff7vdM4OHSSy9FR0cH7rvvPjz55JP+9h07duC73/0uLMvC1Vdf7W8/7bTTcNRRR2HlypX4zW9+42/v7e3FDTfcAAD41Kc+5W+fO3cuzj33XGzZssUvzQq4VYuuu+46VCoVav/6+np84AMfwMDAAG644QaUy65zVi6XceONN2JwcBBXXnllqBlbkgiqHvFv7I31/BJ7zfUs9cj9n13pIalHzQ013OAilFHoJW2yoRs+u9LP2nBpRKGMQpmiV1FZCM8m4mHUVF/DXR0mx8lwuc30A0/O6Q9eVxi6jqiCSZTTK6KEUIFCUc2BByC1as829qNW7WWzI6pZCF2Kl2KlpDy18s6vl8+rRlRkAh/WWQs36ROvpvoZhaieGDVuNix6HEGgwGoUmCxMXqKPAtUxmDj2SOdSg3ojmx2Is+HNi/19AXLUo0xkwzWd7ECyNqL3VIMLXnDljxGRuUxZlv+PBKs3iNIozPIDhfBvzcDA4ODDhKoe9fX14fbbbwcAtLe34xvf+IZw33/7t39DY2Mjvv71r+Ov/uqv8LnPfQ6nnnoqGhoa8Nxzz2FsbAzXXnstli5d6tukUil84xvfwCc/+Ul89atfxT333INp06Zh1apVGBgYwBVXXIELL7yQGuf666/Hhz/8Yfz4xz/GY489hvnz5+PFF19Ed3c33vnOd+LDH/4wtf+1116L559/Hvfffz/WrFmDY445BuvWrcOOHTuwbNky/OVf/uVETlEsPGdW9FDJZlLIZdOh0orNDVnqJi+iHpEi46b6LHiNitgMwe4ehq5kWX4JQpbX7mFvX5C54FKPGBvHAVUJqZVDPYpyyNqbarkrVmSJRJ4THxYAB/vL6g1o6pGkoyxDCyKOZ4wsWxpVTtGyuOU3RcfCZkfkKFHBa5bTLBNchUW2Et2cbUiNYwmdnvjvxeGImeMb20WvpjbyqEc23WxNrLcIZzsA+ntlBccs/VC1DC2JaEeZv13VuY5ykgF+Bbq4gD9SzMyURxWJ/EkbHsTnLFkbLV3HBMTMZCfnSOpZxMIHCy+jQAnOjZjZwOCgxYQChdWrV/uVgV5//XW8/vrrwn3/7d/+DQBw0UUX4fbbb8ctt9yCV155BY7jYMmSJbj66qvx7ne/O2R3/PHH4+6778bNN9+M559/Hhs3bsQRRxyBv/mbv8GHPvSh0P5z587191+xYgXeeustzJ07F5/4xCfwyU9+EpkMfcitra2488478cMf/hDLly/H448/jpkzZ+Izn/kMPv/5z/sVlaqFNEfMzL5fxwkUOpprsZ8oc+c75FGr8HU13BVVNqNAws0oWPAS/KyjzANJPRIFI0DwYLfG5+bbQGzjoa0pxz0WMqPA7aPArIyRzoUW9UaC4pNnHHiRAyHUKERyxwF7fNc8yU+XcOBZrr2Uc83wk+WcXnocoQCaLF1q2/51aSEqiAte006PnEYjdA54AmimUpRIyJyyLNRzBNCO46AooTmxmHE85CPoRKEgTmIcnY7BiXHntTIKcmJmGY1CTSYqo1D94wdidA0CPYa6rkMusCA1XaLfDMBU8XJAFTRg4fUf4VULMzAwOPgwoUDhkksuwfr165XtTjrpJNx6663S+y9atAg333yz9P4zZ87Ev/7rv0rv39raiuuuuw7XXXedtE1S8MXMliv9Yu+nXqq8nymXesSMJmx8u9//W6Q3INHUkOVWoiBX1Vk014/bVAKbqNUkgE8j4mUhPDTW11APT1EWgkRbU46vUYhpUsQ6ispiZkaYLLNyLyNMjrSJeICniCCOyihIBD1s8ziZQKnCBFcy58zNDsiU7Qxes4GSqNeJanDFOvAVO9AbpFMW18EKVYoSVTyqr/HnGar6VJZZ6adtPEQ1UYsujxofxJGIpreol/rkZwfUNQq8MXhiZj71iFMeNVHqkRolKNaGd87idB2SWZio/ePGCVPpxM8Ab19eVT4DA4ODD1VpuGYgD/LmnEpZoaZMmZSFTCbMs53ZUc9dHY1yrlsawmJmx3EiMwqtTbmQTdQYuZo0tYrnBzARNk31bAATH1y0MR1EbdvxHT8PvJW7yD4CEqvWbEZB5CinKadfNr3PtxGtwAPqAUmogpFiZ2rbcahgTNx7QexYiLssawRKguOXynTIBkrMORNlFJoIPZFO1aeJl0dlKiRJVIoiEcmdFzmXkXz7ZDIKsWJmDvVIpzyqltOvWPUJ0KlgFH3OJkI9kh0nXFaaf28mm4AaMbOBwaGBxPooGOiBvKGL0u51DM927rSGENdWhhI0o70+ZMP2UCBRn8ugmRUNxwQKM9rpACaKeuRhGtucR8Kmrak25MCRx5JOhQV5QNiB1csoyFT9CV6r0Ih8m4KcjUiYKFfqlaEEyTiwNnv8crqOwgSqPkUGSuR5LihSr4AJl2Dtaq31K5N53OyQjSOXUaHpHepi5nKFpmuJHNJkHWU1G62qRzFi5oB6RBYycMdhz1c6bQmDHj2nX52uFFldifNe3DmTpWt50MsoBK/ZBQYSC2a1+K+p8qgmUjAwOGhhMgoHGDVMRoFFOm2hjnnYHTHdbcUd5cCyqM2mx3n9wba4bMLMznq3OguzMhQ1zsyOcDAC8Csl6drksmnU5dIYGqVXuehma3LZgaKEMDlcHjVaBwFErI5HUI+oRljFeKcXoK+ZuK7E7P6ObCdf5pqhNArCngjB6wrz3ajqOuSzMDJdpt3uv57fQmVuZITpzDmb3dmID5y7AFt2DuLS0+fybWzZjErwWthHoUZMPZKna3E3a4qZ1RzlKEqMOzc5p5cK+L3/ORkF9vMqFUeLeqWj6+CNw6soxL4fGiMmC6NKPdI5FrbqEZm96Wypxf6BPDJpCx+9+CjCJrA3VY8MDA5emEDhAIN8CIpu+GxGYd4MN1AIly2NduBdJ4le6Yy24ZS5YyrlsJjRwWYU4rUTMzrquSuEooCkfZwOxVZ8ievKDIRXeqW6LDMcfTKAEVUwoilB8SJbgF1Rl3WUg9dURkFmdVw2OxJJ15Fx+unjl9MbSAZKwnGigwuvipcMxYl14NnjP3PZDJy5bAZjwwYXiudZmFFICW1kr7OkeiJYEK9OQ/CeHvWI73B74ImZRcFAuWInWuo0yY7JojnEBleqGQWdClah6zm4Js9cNgNnLJuO+toaSp/GyywbGBgcfDCBwgEG+eAQperZQMHPKIRWuqNW7RvCNnEZhY56rk1UcDGro4FZSXL/jwtIyNXAOBtPn8CKP8sxpVEBHt9eo0mZTHlU0oEtxK/0A2ypTzmnjwxIZCre0BkVuS7LbHCp3DxOQjsA0ALgsYKcjXCcmCyM51RKNbZjKxhJBVfBa1mNBk3VCLbT5VHFnZllysO6cxM4vYqr0Om0OOgTjRPlwKrY0GJm73/i9y8KFGy9jIJWFkYyO0K/n8w5ixQza4nZg9dsQYtsTYpqzubB9FEwMDg0YDQKBxikUE+2zN2cLq9OtdiBYeE7/czKfdRKvx9csNSjiBKsM1gakYSYOaxriLYJAgXagacyCoJls6hzJqwUxIqZSxJZCMFKr57TK0e9KRDlUaX1Fhor3XQHaEWNhuSx6NR3p8YRVBYKj6MuAC/IiKajRPOSug4PUfQwcpwxUtcRdfwJCXOTyg7EzY1f9Ug/o6BX6lSt1KzovThhsmqpU+E4GhoF2WpM0vcN5rlhYGBwcMIECgcYbNUjFum0hW6iMRkA1Iw7W2wJxriVfoClEUU78LPGgwuWeiTKXFgWML2tjqFERdOImutr0FhXw+WziihObU21AMIOHBUoyDQCC2UH5JxrqleDqOqRTgWfBDn6NdKN4NRKioYq+EhQj3QcWNlzJqJ4RQZXEWVYuWNEUO9khMmumDm+jwSbIePNka3iIzxnkloYarviKnTSlBhARL/kVC/jlHnm9VFgUanYeo6y1iq8OvWI36QuxoZbUlVsY1lk7ooYJ+K7YX8DMg0EecGcgYHBwQcTKBxgxFU9yqRTOPXoaf7fRx/R5r8OO3AR1KNONeqRBaCzpS48TkQWoqulDjWZdKhkI0D3N6Dm1RHOjng2ouZx7eMZBfZBRIuM+Q/KUB8FxexARbI8qiVyRiNX1Ekbdb651Op4xDUjouuQTlm5YvsOWcri9x1wbdQdWKqCkSRdiQpINAKyMYnMRZSYWbpSlEYZVg/Ud8T2UdAJLrVW1NVXulVFtuJxOBkFTkUdnpiZRX2uRiujotUxmevAJ1P1Kc5Gq6RqZKAUvGapdHLd2SOnY2BgMIVhAoUDjIyEmPmUJdNw7vEzcfzCDnz6sqO5+8cJk7taa0M2juOgLGi21lQfPFDZHgci6tEMjqYhjkYUUKI4NoKAhKtRsON7KABM99+K7a/cWpb4QUnRewhnLJMWVzCJEvOKIHKuRcEIoK5RoLI9YMuDJtjfQHD8sk6/Xu8JOUfZEtiI+w4Er8MZFbnsAL0CK0eL8+cY0UeBDkjVrzMSyhkFDQdWx1GObbjmZRQq/IzCp969FID7O3rv2UdqdWbm/cwtS3wu2TlEbYu3SZZ6BKh/N9FZRZNRMDA4lGHEzAcYcWLmdDqFTDqFT73n6NB7YTGzOFDwHjasCFDkjDc3BA3NZCslzfSpSsQYMdSjGT4limMjCEj8QIHNDsiULRU61hHlJEkHvkDqADRoNJI2MscCMFmIUjz1KFweVK33grQzTnwUGYyIKGHsOOR3L0vvkK6UJLKRXOkvRjjufBu5hmv0b9Ph2zJzFH030dQr0Yp6hNPL0yhoObAaGQUe9YinUXD4gcK5J8zCETOa0NqYQ3NDlso8xI0dOa+EnXF3HE7Vo9jyqOFtSQVkwRjk+ZZr1MhW5TMwMDg4YQKFAwzyhi6bdvfArlpGiZkDGzFdh0RLI1HmTrI8ansTL2vhjcO34VVWCpq0CcZpDo+jUx5VdtVeLMyVc3p1HGWZ7AgQEfjErPZ7TpVM7wkya0E6ySJ6lzeGB3IM2VVrGWG6O07wulSKPxbWhqxIJewJAfo6K8jQiBgqXbmiaOMHy/R3ymawRFkYUXlc1oaE7HUW7K9Db4mjK/HmFZdR8KhHwffPjj1vvFIca0si+VKnCZ2zWKc//L6WriHiu2FLUcsFvuHr2cDA4OCDoR4dYMSJmaMeXlbEKg+JxXOIbpmSGoWjCBuWShRXjYhdmXcgzlzMbOcIpmOyEA21bnzLVpahyqMKqUfBa5lmYwB9/CSnPTK4YHj9HrS630pWIymU5AIf1Tr6lDNeJo9FzhktlyWPXzBOFL1DFFzInmepPgok9Y7tZi1bKUo1CzE+BF0aNTwWaVOUzEIJqTfK1CP1jEI8XYnn9PLEzOGFBVrMHH3fVM0Q6AQ9vAylVhYmIV1H7Dgqi1KqDQRNoGBgcNDCBAoHGOlY6pHcw5utenTEjCbkatKozabxZ5SuAZQNuwpfk0lhZkc9Lj1tnsCGqaM/7pC2NGZx3MIO/twiaFHtLV52ANT+gJji5D2AWYGdVGdmkWMtyc+lqUdJlyAUbJcMFGjqTRQtiLNCC/GcKadMdl6TZEM6Y7LBBZkhkKIeRTSbkqn6FC6PKtevAWCDWU6gQBymdECmIebV0ijo9BGQFTPHlEdNWszLpV7p0Ki0bDRoRBqZm+jMHXk9AwWql4iM5iZyOgYGBlMYhnp0gEHenFXTwVECs8VzWvH3V70DmbRFORjsDb/kBDanLp2Oj12yGLVZmq8fKo9KOOSfee8xqNgOFs5qplaWUpYFe9zdY7MQ/+e8Bdj09gAuOGm2Px/2ocKKk+d0NeLt7mF88J0LBPNiaTTxTi85pyhKkEj8qtPUSpYHTEJ2pVeeSqW6mpjcschmR0hEHj/xFumLyFZwUe6jYLMaBQm9AdOZWdaGnR9bGpWdW6minu0hoewoxzmjXL2BugPPc5R5/HeZqkf++4olRat5LCS0sjA8p1+L4iQXkIerHhkxs4HBoQwTKBxgkDf0iWoUSEchW5NCfW3462Vv+HRPACvUBdodh1zpdVAiHhJN9TVYMq8tZm60U37a0dNx2ZlH0vNiqRqMWO76T52CvqGCX7IVCGdUVPsokBDVlmfHyctSj4TOmBwPmLaRc3rJZ7Gs5kJmXnp15/nbo2xkxOTSc5PNEEmIs8MZBdUmdWGtgYwNQGfveD0oaIqXnKMsLvWp6ChPVtUjXgaMQ1WceEZBja4Vrx2Q+5z4eU2SjUL2WuZ6NmJmA4NDA4Z6dIAR33BNzrF0bFr8K65gE7y2HYeiK9SkZToTM1xoycZecb0HqJXhUE+EFNKpFBUkuDb0+aIyBBJVj0jI8nOlqUcT1BvQc0vaiVdzLJI8Flnqkew4ouBKND47jkxJUfaj8oo0ogrb2E+ym7M7VnRpWZFgVK95mKqYOfmqR/zVcc79gnjtU48E5VFl5hZX6pR3ncVmBxLqo6BH14qjHvEyJFFZ1eC1wzwDTHlUA4NDGyZQOJBgHk780oByzph0JQpGBFiiVuH5Y4WyEDLdjJlxirGBAr2aWpJ4ELlzC14XJareTNSBHSuoVz0ioVqCMc4mqeBCNlCi56WTHVHLdLg2GscvreuQqHo0XlLWQ4HqAC1ThpcOLkVz5jn9hWI0ZSlJiltkeVQd6g03c6XmwIvmxcu+kIFSLPWIeV+HEpT0qr37mbzyqMkHFxMpj1qxbammk9SilOm4ZmBw0MIECgcQ7G1Z9YYfJWbWySjIONcOQwsSlWGMCi54wmFWBxEXWPDmRs5LRIvQc2AJp69EjjE5Tq/OKrxqBRudMbQoQUmPo2Ej1JxINnYryHTzJgOLUvS179tQmTtPzEwEJVzqUfx8w+Nwvn9L3DxQ9HlJN/US2fB+mxMWMzNv6wiz44XJGmVLdQISrn5EPSCTzSjlma7MUoFv5GwMDAymMkygcADBcrJVH0Y0B5Rx4CWaZzm2gxKRrpddGZIpw8gKrcsVNepRUbLUp2qTMi0HXjCGLKeXGifq+9Tg9ScVkKgGFrrzSjy4EB1/5HcTvKbpanLngCrDKnH90/vLBTDer5Is+cu7prW+Gx53vioVfDiOckLj0MLv8f8VAgX2fR1hdlygxPs9V0PMrCeAVgsuaPqlbHAdvDbUIwODgxcmUDiAYO/Vyqs8TNUfGUoQLRoGo1GQyQ7QNmIxZ/CaXulPcUWr7LwoYbZGN18ZB45EtMg2eE3qQPR4/Rp0pciVPv570TZJzUvO6aXHmaTMheTquE5fCKoMq0QWSL6PBB1cA/GN97RoRBor0FolOLl0JQ3ufEwGMtAoyJXH5b2v1zG6CsEV532tIEbnu5F81sj2n2H7/JDo7hvDnX/ciNVv7oucp4GBwYGHqXp0ABHKKEyANxqmHgkceKbLbEmm90CKfijL0ILUqRr0GKVS/LG4cwteUxkVifKoMtvDc1O3IaElMk16RT2p8qiK9BYgJiATbI904CdIV6IEwJJZCGpuIoobJzsAyK/0B92GCd49xzQpupYOJagqK92S1BteRZ0KJeZWC0hiAxgdHYBGSdmksgNJZxRoup5kv5YIMfNP7nsVz7++B9YLOzB/5pmhQhUGBgZTByajcADB3pZVV+BYx6Io0QSHTIc7EpQgIEw9ktJCEEbFkkSteopKwByLRkZBXB41OQdex4GdqhoFrVKnGtWYkq56lGS/BlWOftQ4Ew1IeRkFkbaAOy/FIE4noxBfWYczr4R0DbzmdEp9FBQzCinLCt2vdTIKMuOEbaqhBQlvkw2UZbqZA+xzg37v+df3AHCDvJc27I+cq4GBwYGFCRQOINhnAu+5I089ovsbiB1ycjUVUmJmS5AdyKTlhGwFiUZgbPM0mWCEtaMoTgLvVscZ1alGJPLTtFattRxlNSdeVvwra5PksUSXrRSMo1PFSYNKJQwIRGNElqAMZ67iePdaQZyGA5scXSkZ55peWHD/n0h51DjHGuAFF8lTr3jHqhWQJBz4qfYeAcQZBfLeDvBF+gYGBlMHJlA4gGCdD+WGawyvn1yFl1lRd1jqkaA8KlXqsaTeR6AgIUwOzUtCmM2OI5dR4H9O4r0KEnLg4+YmrOKk6PTqZEdkS/fS42g4/UlnB3QyFwL6i2pwIysY9alHMSU/tTI3XDH75FQw0qnvL91wTbKPBG9ucc441ybh7seuDU8APlm0KLnrX6abOcAXnANAd/8otR+5kGRgYDD1YAKFAwj2tqxcHjVUwUimj0LwOly2NL4RFNWVVrL7r1SgEEWjitIoEONIlUfVEjOrO2NJdb+NtRGuXKut9mtpFJKmUSX43STfAVptjIlS3HjdhlUyQaoZMh0xr5ZNQivdbMU3QJF6xC7SxBwL7zNj9QaSwmz6M9UWiwARXUn9u4maG/mbKUvo2th5kRmFPT10oDA0Voqcq4GBwYGFCRQOINibuepDItSrQMKJD1GPqPKoIuc6eC1DI2LHkQkUWNqFHvVIvzOzFo1Gozxq0o4yl45iWUJnWDROfPMseScVmHi/CtlxRG8lroXgOr1JHwvx27S9/2OoRwlpbpKukiOaW1KOMq/AAEU9UnSU41bggbDjH58dSCZQ0uqJEGPDzyrK/c7KElW/3DGC1zYVKIxQ+42YQMHAYErDBAoHEB3NtdTfvLSzbFMvt/uxokNu0xQfmYZrdGm8qGpEhAMv0XAqpLfQaLhWkhqH/zlJ02h0ylYmJeatzkov53OSbjiXZBZGi0qWnK5josElt+pRDAVHem4a14xOUy896o1cEBPbcC3CgeWNo0c9Sj64Ul3pn6xxqMAs5nN48yKLHrEZhWETKBgYTGmYQOEAoi5HV6dVpTdYjGNRkulvwKzykBkFoZhZUW8AsAJo0kZAiSKDHjCVkqIqawjKo8qUraQ/R8eBlTt+EpFVrDSCC97KfZwDx7MR9WOImptOedTkG64JbCIzKoLtqs61DiVKcgXW4WkUuMEK/7NUs1B6PQE0nFGtcXgBUvDaF37H6DlIhKlH6mLm2CzcAaRrJZ3tEGUIZYsgOBEZBRMoGBhMbZhAYQphIhoF6Y7JVHBBNzaTKY9akBSykQ8dGRuLKT9IBReS56AoYZNkI7Tkq/6ojS96L9ax0LDhBiQ6ugaNqk86QVzS1CPVgGyimQ6PelSZLOqRlmBWx4HVCEhjyqNym9MpOtcyGYUwXUkj6IkNlNSyyoCISpgsLUyv6WLwms4oGOqRgcHBBBMoTCGoVz0KXldYuo6ojwKzyiPTmVlUGi86oxC8lqFEAfTDWyYLwdpIaRS0Vq3523XoSqoObDoVozfQcsbC23SoJ1rZAcWgB9AL4hLvGs15S+f45Rv7yVGPksrcVKOPglYfAcmAjM1AOo5DdWaO+w1olUdlpqFVwSnh/gZAgudZp6RwVIaMae4JuN+TETMbGBxcMIHCFIJywzWSn085yVZE2cjgtW2z5VHjgwu6eZqcA1+QKFvKjlOQpR5Rc1OvxuEhcWGycEVZPVCIgipdbbLG0TlnOqVehQ6MRuCnLgBONnPDUgkBiUAhoYyCDg9e5/iTKsPKZiAdxNO0osbRq3qkE1ypZxR0hOZaGaKEqUe8TuPDYyWMFcrUfiajYGAwtZGJ38VgsqCcURCu9Ms58I5Dl7qTEQDnJTUKlABakq5EUZxKGlWPiLmJekIA7gPMZkp3R1fvSMYZi7XREZkm5sAm61gInXENulLkdyNyYCZBPyEjAGevM/k+Cu7/lTiNgjDoUeuLEVtZh0tVqYajLP8bsCzLz7w4jqNGPWI1CjHXP4CQjkc1ayEzjs454y8wqQf+WtSjqOCCU5mquz8f2q9YtlEsVZBKWfj18o3Yvm8IH3nXYsyf2Sz8bAMDg8mDyShMIaimqnUaobHp4JJEkzaRmDna6ec78JFzI8eRLcNKvEVW45iMjELiDdd0HAsteoNGQDKB1XHaJuFKSUkKoBVtVAWzcTZsXxRApjOzetCTFFVFj3qkdj2nLHF2lOXAk+VR476bMPUoPqOgasPXAagHStU4z6rXgOh0ypYu9gK6fUyzNQ/DYyXc8cgGPP7STmzeOYiHnn1L+LkGBgaTC5NRmEJQXU0in0PSq/YkvcF2mIxC/OpskXTgJcujylZKojMKkhQnUXUhxW7GeqVONZxeye9TZl6A5gpkYqUuNQTgOpkbnSBOUaMQ23uCxx2PCeJUrzMe9aiiWR5V9XrWckZ1VscVr7P4PjJBQEUFVYqBj1TVI+Yj42hU3N/zZFG8dIIYjSpu8lWP3P95GQUAeGnjfqx4ZZf/9/od/cLPJTE0WsQt963FaL6M//uBZZjZ0SBlZ2BgIA+TUZhCmEhta3mqTvDabWxGNlyLrxSUl6xGRAUxssJkkUZBMvAhIUvZ8hC90i//OXHzSpx6lJTTr0FViK7GxN+efJM60XY1pz9uBVq1QZVoDvLUo3FKjWZGQbkzt1agqHH8igGJbDBesR0/o2gJxqZs2YAk5vh5NnHHb1lWOAuhmOkAdIO4ZL9P4X1WMrjwMgp9g/xA4ZePbqD+ntVRL/xcEj+49zVs2NGPt7uH8fRru6VsbNvBild24YU391FlW6PgOA427xzAwHBBan8Dg0MJJqMwhaDMAxdSguSc8YpDZxRED2Vh5iKyv4EgoxAZXBA2GtWVSESXVOVs08ooaNgo6hriHR7eGBpVj2JXR9Uci6RWuoGYyio62YGkArJYm/A22QpOfsnPWI2CenClqoUSjaPDnVde6ZfMwMRlXkLjMMcjU/VIq1JSyqK1E3FOP+f92ICE85FJN2mbaNd07xSUbUnHXGKfff1j2PT2gP/3xh0DEXsHuOuxTXj0hR0AgL+96kQsO7I91ua+p7bgf555C/W5DL79f89Cfa1xnQwOH5iMwhQC6xDFlsYU0m7knFGyK3M6FVUpSeD0y4qZJbMdIuqRbBaChKy2w98/aU67Bkc/CU63a5O8A6daE16vUpTaZwGa2gHe8ccFZIrBpeh9VapGfHlU/mepV3BSX7WOo94kYROdGQxek1ormQpGqj0R3PHkgxiRTXxAFt4WKzTnVkrSCHwT/m2S17NshsyDzEL/757eSv09uyuedrRl16AfJADA9r1DsTY9A3n8zzNvAQBGC2Vs2S0XkExVOI6DVzf34KlXdlE+gIGBCCYsnkJgOc1xq0Ii3ya6EkXwuijtwJPBRXyVJNamKEkjIo9f1kbkxMvOzcOkiZkVsxA63V/jK56oOQmicXSyMDq9J6KDPt7+6sdfneBC/zrjlUdNrOFaQt+/3qq12jmL7H5OFGagMqM6NKIqUI/446hnFFT7NcQtMPHm5Y6T7GIJS3MF6BK2zQ1Z9A3xqTx2TKTQM5DHs6/vobbF0YjKFRu/+N83qW1xgSsA/P6ZbfQGuaSIMmzbwcOrtuOVzT34k9Pm4cSjOqXs3tozhLf2DuHUpdNQl4t26RzHwT1PbMYfnt8OABgrlHHJafMmPPdDAaP5En798JuY3lGP445oO9DTmVIwgcIUgnJVDS1ON98ZjxT/Eh8nm+JPCZx+2YCkKLlCKOTORpZHVXP6kuqjYCGaSjQZPPhkx9HQdSSdueHNK2EHHlCnXgEa1xnxFq/bsIhmJTs2+TmWRa/axjv94W2T0QhMtpgDGSjE0fX442hQjyScTNV7up7egNlfIzvijpOsmJnXQJC85prqa4SBAun09w7m8fCqHVgwqxmnHzMdgJsJYOMC20YkXt64Hzv2DQvH4WFf/xhWMtoH2ThhaLSI59ftxbL57bEi66HRIv7j/rV4c3s/AKBvKC8VKPxxzdv41aMb4ADYtmcIn7h0SeT+Dzy91Q8SAGCbREblUMDe3lEsf+FtHHNkG96xuIu7zwNPb/OzTV/95CmmPC8BQz2aQlCtxKFXjYfvjMt2TJbZDojFzNE82OB1uSzXZZU3hTiHnJve12rqpTaveCdJx4bnjGk4fQkHF1oOrOg6UwziYoXJCYl548ujyn0O7z2bQz1KSszszk1tdVwrC8HYxP0uATUHnrwmyxU5Sou/j+Lxq87Nt2E+VqfqkaqYWaYnBGtjWXFOP3+7bIbQz5CRGYX6rNCWdPp/++QWPPrCDvzn71/H/v4xAMDASDFkQzr92/cO4fZH1mPdtl5/2+6ekfA4jNdPPqsA4OlXd1HBujs3+m9esFGu2PjOr1/Gr5ZvxL/e8SIVyPLw0/9Z5wcJgLg6FIk/PP8WfjkeJADAtt2Dkfv3DuZD2RHyd3Mo4xf/+yb++OLb+I8H1mJY0OCPpKQ9+fIu7j7Vhm07ePrV3Xh9a2/8zpMIEyhMIfA0ClGYMPWoLCcynihHn7wZyT74ydtXpJhV4ChHpd65K7OToFHQ6YmgU6s/ntOcUHARI2bmvRvdaZy/XZWupUU90shCxJfHVJsbecY854MSMysFCqrOZXygqCoA5i18xFFiVOZF32PkFhZEc5PJDqgGV/xx1H+bqpllmZ4QbLCsQyOL2g4IqEeEk91UXyO0JZ1vz8F3HGBPr9uHoZ9TfYj03//rD2/i8Rd34j/uX+vz8PtjgotbH1yHv/jeCsqZ3tc3xrEJbH9472u49gdP45VN+6l9HntxJ97udrMXw2MlDI1Gd5/evHOA+pv9DvuHC5SDWyhV8MBTtEZjlOl43d0/RgU+u/aPhLIwEjE1Nu0cwAtv7osNdqYqSmUbG8dF7+WKw7122GCvsU58bVYTv3l8E37+0Bv47l0v4609UyfbYwKFKQTVG75eacTgvUIxvtkaIA5IdJzrybDR62SqnlGZDB64XgWj6q8Oi7ZR76vqGjTOsxaNSidQUswOCMeJPP7gtXR5VI3fJu99LedakUajJRiWpUSSzdYkqEc6Ddd0SqqqngMtobmGyFo1UNSluHngU4/ojAKpRSMzD6SzOzZeDS8uo7C7xw0oRvJlDI64DvbAcNjGG2d4rISVr+2B7ThYTqws90fYbNszhBc3dGNwtIRHVhM2QwU88PQW2iai2lOhWMFYQSwq3rCjH3//o2fwNz9cGQRKQwWKEQAAtURfo6de2YUv//hZfPk/nsHYeADBP5bg9c79I7j9kfV4dXMQ9LzdPYxv3L4GP7p/LR5/cadwjgcKjuPgd09vxd//aCUeWbWdu8/O/cN0VojzVbAUOJn7QdLYPzBGXUdbdg1E7D25MIHCFIJqanuijjWZUdASsmnw+iNXVBNyyONF4GoOrFazIS2qirrTK8qoKNtoOdfxq9Ayn+O/p3M983oi6GgUqkI9UnP66PKo7v+UJogXrGiI5nl2Ok6v6iq0Tq8C2ftSSVHMzK6oywRKKj0ePKje07kVjJQzCurZkWoXzvCpdIyYmcS86U3+azKgIItueE5vlNPvOA6lixsrejbiLESeWI0fGSv7QUfU6jO5wj80Gsznnsc2hhz/KC1E/whvjOD1mvXdqIw3R31pQ7dwXuS5Xf3mPgDA4GgJ68cpTQPccQKbXz6yfjwL87p/ntcTdKg33uoTHsOBwv88sw33P70VPYMF3MdUwfLArszzhPK79tO0tKjArVr4/cpt1N8y95fJwtSZiYEy13SilShKVdQoaAUXOpkLDQdWdRVeJ+jhHedklS2drIxCfGfe8DbVqkeWYHv0vOLOc3ibVvfbhIML8j3vAR5fHlX9HsCzk3N6FcdQdEZ5nyl7L6OpR8mvqAOa1CPF1f4kmqfpBDCTlVGIoh7Nm97ovxZmFLxAgeP0eh9dKtvUonF+3Onjrah78yoQz0LbcfzghB+QuP9TwQjhWK5/K8wv946nUKzgm798Ef/40+ewc9w55Y5hk8cfBDGj/vHzjiV4TZ6z0UJJaEOOs3s8W1EoVdAz3hiPDEh4wcmBxPPr9uI+gn5VKFa4ARkbKPBitnCgUA7vVEXs7RvFytfoKl5xlb8mEyZQmEJQrrmtwU+m+hsUZRuh8bfrONdJawF4JnF8Y/U+CvztqscfX7aUM0Y1Vse5QczkUJwSD/q0aETq2QG9DFF4m7T4k9Nwjfe7Fma7FGlheo6yqkZBJ6Mgdy+jqh5pHIts8zTKRkbXMMEsjE6pU6nMTVLPGsUqXqTrw/LA53SRgUKwvcgJFCKdfkaQPFZ0MwTc4GJ8oCLHZqxQDn0WOQ6Z6cgXA8eS5/h7P+MXN3Zjw45+7O4ZxRPjVB5u1kIwzmgkjSg4aXQWxj2GwZjggjoeP7iauoHCH55/K7SN51y/JVHZaVfPgQ0U1qzvDs09iq422TCBwhSCcmp/gg4sTT3SEDMnHFwkpYXQ6TKbdPM0vmOtEcBoiAyrUfVINbgC1M8z7/vXofdUhXqkEygpBheU+BOuo0BWf1H5vGroByZa6lNHMCxdtpmseqRRHlWH1y/DY57wOdOgEellVNTpmnFj0eVR3f/pKl4ptDfn/L+PmEFQj+ygShLJxc8XK7Adh+v0ep8dChQKZYzky9wKPw4nO+DZiBxj3jhjhQpBVwpXLPK1EISo2QtceIEFOTfVjApAP9u9ICYquALApWuRNgMjRSXndef+Edz/1BY8t25P/M4a6BngnGdGb12u2Nixjw4C+NSjUepvVhhebfQNhr9PttrWgYTpozCFEG64pr7KCcToAIi3yBunFvVIQ6OgxVFXHEdH25E0d56vHUjegeVnVKoxjsaKunLmJpnjr4bN5ARKbt0j71fpOCz1iDeGYGxVWtBkrI4nTAkir8mSYkZByyHXofiEqEfJVqPi28TPi/0962Tuora7YwSvHYTLo6ZSwKcvOwbLX9iBM5bNQAORYbD91XSO0z9W4jpRgdNPe4v5YoWrTyDHKXBsyIw7f5zgfdtxUCrbyBfLXH67HeH0CwMSx0EKFhUojeXFGg2y8EGRoh6J6UqeSbliU+c00IIEc3McYHC0iOnc2QYYzZfxi/9909dJAMDszkbMndYYYeXi5U378fy6vThuQTvOOnamcL9yxcZIPuzMs9SjXftHYqs1OY4Toh5NdqDAC/zIxY/ewTw2vj2A4xa0o7528isymUBhCkFVLJdkZSHZlTsSWp2JFZ3r+HE4+2v1K1DPqKjy7bUca53goiq9F3TmJvc5kWNUo6RsQk5/VcZJWf4D23YcRswsP4d46hEzryrw+nUcWJXgguqjINmgUTSOVNUjDQE4OY5lqV8zWtWYtDIdumJmyXLXDv2/9/7RR7Th6PEuuF6PBHe/MO0GcKseiVbgA6efdtRH82VuaVRyPmxAMlooUwJl7jjl8NwGRdkBj+JUDjvwvJV+d27hYInnwLPzAujAJ+9Tj8Ri5hJ7LIK5ydCPnnx5JxUkAMC+vtHIQGF4rITbHnoDL210Ky698OY+HL+wU1imVNQLgc0W8EqMsvsMjBRDgcFkU4/4QZw7z3LFxtd/8QIGRopoa8rh8+9fhqPmtFL7bdzRj9ldjVUr62qoR1MIqlzTiVKPqLE0HOXkS53yt0f5PDpVj9SpR6Ltya6OT15JVY7DqUHXie0joJxR4GybpOAq6QpGQhuFily27VAPNX55VP45jue10/OQWVEnP1NqDEUevDsveQeW3LVMUlokqEc6JUV1Mgrk58qu9JPD6FRj0sqOaFz/UdsBtuoRR5zP2JJz4q3AA251Il6VIEDs9OeLZYmMAmecoehAITROFF2JqzfwSr2KbCC0iesJQTr+Y0VXa8HPdHgBDBsoVFCu2CGHXHROSHilaelxom3uXbHFDxIAl3bDo5d5EL3HUo+4naeZuezcH27ENxUCBW+RaF/fmP9+31AB3/rlS3hpY7e/32+f3Ixv/eolXPez50MBX1IwgcIUAvvw0inzCejpAFSbWsWNk2TvgcjmaTzqURz1RNGB1TnP/Ool6qt2kxZcJJwdEM9NbgUy2F9jjBhHkT9OFXQdvHMW61wHr8PUI/lAIQ4TpbjIrNqzU0u66tFExMzsPUCvPKpacCFbm50M4rRE5hpBj24pbtlngDP+9ZDOLGtKBckRwmQyo9BQm+HYhJ1esQ5A7CiLHHiedsCbmyhQ4AUxY3lxfweAEFqXeRkFMY0oVB42XxY61lEaDd4Y7PH97/Pb8fc/egaPv/i2v60vpqHZWKGMLbsGqW1eczr6eGiPntxf1MCOtdnOySiwEgWWduTNcTIRVZGKvc5sx6EqJP3hObd/xOBIEc+v21uV+ZlAYQpBldM70apHJKKcax2RsZ5NQiu9iWcUdB6SnP21Sp2qcZplxuFNW6fUp5ajrHie4xxrth5+3Bii96cK9Yh0YG3HkSiPGv4MubKdavNix5fRNFiWxayoq89LlhKp2pk5CdGwqjhbZgyA/v60qjFJHQszZuy1LDc2CbLTuJ9RYKhH1P5MkAzwhMkVyqlqa8oRNuIKRiSFpoXo3+CtQLN6BDYgIYM8XnbAn9uQvBZilFNZiAQ3uCiUuSv97v4BVYX0hSPpWhFVn3jzIreVyjZ+8/gm9AzmcfsjG/zx2eZl5Djlio1/uvV5/PN/v4DfPhk0pesb5AmTPVpUBd/+1Yv40n88i627BwG4Wgnu8RBRQMW2sWNffAAyzAk6yhXH7+hdbeSLZa4exsso8N4TZQ6KVZqzCRSmECZllUeHEqTlKAtsJMvpycxL9L5Otag4GhHv3eiqT+or3VqOZWJ0peQzF6pz09JbTFIFI50mddzjVzgeVqPAu350siOAnnOpmlFgx9GhHklrFMiqRzo0Iq1VeDUbmTEANriIt0miJ0Rs4QytqkfBa7/qkSMOfHnlgYusA8/Qe1qJQEG0ApsvlKnsQCsvuChH04iogETgXMtRjwKbcsXGaL7si3LTKQt1uXTIhgwuorIWAV2LEWYzx1+XC7IwooxKvlDhaifIsdlz5jmv3EBhfJxXNvWgZ7zCz0PPveW+ZzuCikzu/39csxNvbu9Hz2Ae37vrZQDAkChDQvaF2D8aOi4eyixfaRyjHLF0NSCmUfGvZ/c9/pzZbElSvRiMmHkKQbWUnsgf0KIeaWQhEtco8JwxBaqGB52a4DJiXrbShmo1puoIk8PbqsKd1wkumPctzjZ6//C2yaJe6dGoNMZRuJ5ZjYLsvKvRCIy1kV0dJ23kVvoZ7UQkVS14TYqZ484xbx8th1zRRpZ6pKprSKJfhW7hjKj7M6/hGkkfYU3pjAJfMJxnVvrbGkmn3/0/vDpeoVZg25tyvshVTHGiHeW2plp09+fHbSCwiaceFRjnendvQHtpbsiOz7MybhMOYhzH5awH88r5jrkoozJaKIeyMB61htc8DhCXhyXPCZtRGcmXYTsOl7bj+bW8CkQDI0VuFSvvu9mya4AaA3A7TvNAfoyofwJbGanCKZsLuOethbi+qoXBEcGxRAUKAv/fO2cV28b373kVr2/pRTqdwvyZTfjWX56LmkyabxgDk1GYQlAtpSfubzBJ2YGEbXSoR/xVWw1HWYfXrqjriNUoJOXAaqwOxo/D2aY4N62eCFPF6U8q26EQxNqTqVGo1uq4KvVIO6NAUI80jl+V4mNBMiChsjA61COdoK8KYmadgg4MjQ6gxaZR9wehMLlQEa70C0udFmgxM51R8MYJV/0hV+HbOeNwdQ0iAbSfhaBt9hDC35aGLCMA9/QGtA0pFm5tDGdUWFpKnqEetTUG1CtHcM7GimWuRoPMFrDUnNF8iZtNcI/FHYf3O+sdCtOOKBtO6XZhRSrifrmNo08AwqvuokCBJ/6uBkRaGC/TwaMeifpZeMf25vZ+rN3SCwfuvXHj2wPC70YGJlCYQlB9eHt111mo6gDixhK9kzjFifOWjgOnl1HQWblXm5seJUa9bGlV9AaaWRh6f/XrebIaoek4SjrBlQpdyWHLowpsVTsm8z5LlXokzbdXtGEPUb4zM0E90llRlwpiiP3TqdiqT+wcZYMrZV2HBiUqqVLcstlrLvWI1ShwNA2sk+QgvKLOjsHLDpAr6lynn7EZGC76jmImnaLKTkZVV+I1W3Nt+OOQHYFbG3Mh+hWPi04GF1LHz1KvGuOPf6xQ4VY4oqlH9NxGC+XYQIG9XErlCrfZGBAI4Hn3ABkxM1kalRw2lFEQ0HgmS9DMEzIDQTCQ52YU+IGCZ8OjZokCIhmYQGEKQefhrcpRTqqpWdR2d1787UlnFHiHGicyTKo8pupqt84KtFbztJjrhi+ajh6Hl3FRdeKrwR3XCWB416ZWFkJLcyKvn7FtWswsOhehnggaHHXV76ZaGgW1qkfBa5JnLFP1SNVRdsdTP36d4EqdrqX+3NDRKExkUUqGekRexyKnF6Adq9bGeDHzwHAB+WLg9DdQTj+f3rG7l17pp7MdAi0Es3JP6w3c/1nnevd+MjuQDdGveBx7kq7Ey6iwNhXbwX6iizGl6/DnxaEecVa6h0ZLfvDCBjEjeXGg4AiOfzRfRi9HyEweD68ZbJyY2bYdbN8XBAozOxuCfRgbXsduYPKarpHXTHM90XRQoIUBxIGC19gwz8lCOGxdWAWYQGEKQU8sF96m0xMg6fKoYqdGLSCpRkaBdziqDrllSfDNFR04rQpGWueMM3Y1NAostUBiBZYNFrUCuFgdgHpwoZVRmWBwaTsOKhErsKLtk9ETQKbiD2uTtMha2HBtEjQKMs3WAPVACQBSxDHrOP1aWQiNbs5xY7E0GvJ/3hx45VGjxKiZdAqN9eFuzqwDT3bwbWnIMqv27v8svWcvESi0NrGUIFHVI5rX39IQDmLYDAkVkDTmQr9/Hu1kd0xGgedY7ukV2AgoUWzVJxJ941ShUJO2iEBB5PSOFsrojbFhr03HEfdY8M7B7t5R/5haG7NUpSvWXyYzCuT1nERGYevuQWzaORC5D60fqSXmJXb6RdQj79i4gcIEdM0mUJhC0Ll5q3KU+etCegJoLYqTIl1JqwSlhtOnnB3Q+G70KuuoV3DSGUcrc6E4jhwlhh2jCr0neOdZQ6MSq5+ZYHBlO3QVD9F4SfQEkHF8yXMg7fQSuyUtGKbEzFR5VI1ASTGIkc4OKAZK7n4W97XMGLJzC9PVqrAoxckoRDZc4+zPc5Q9tDZmQ78XgJ+FENmIqh5RNg05xgZcm9F8GYNUoECUYRWMs5cKFLLU89lx+PMinXFuRqEUDq56CXpPWyMnoxCjBWkmjsXLALBzG8mXuD0UqLnxMgoxdCWWKlQs2RT1qKWRLHfr7kv2TzhiehNTgYv+PDKjQB4nW/WoUKoIO0LzsOKVXfj6L17AN25fg5c37RfuNygo9xtd9Yj/Wd45yxc5QY4JFA4NhLqFyjQ1UnRGtHoviGwmga6kU4JSp9SfqkOuR++o7gq0P06VV7qlbTRWOtnvpir9DRISc1elDCv5QLOZ8qiSv8NqlQely6NqOMoaVMro/i7Be+TDnu06HTcvQKPUqXSgpBNcqdlMVJgO6C9Kyd7PeU5fVNUjv79BhNPf3lxLO/C+YyXOQrQ25bjzig4ucqGO6UA4iNk/kPcd74baDEWZEYmmqXEaclQwZnOEzCzaeNSrmFr6/PKw9DiFUsV3xi0A86Y3+u/1jtOYSiWORmGQH8R43w2XrkRQj8jrXURX6hsu+N9XJm2hsTacVSIzKHOmNVIXF+svk/dYssoRmVHY2zeKf/zpc/jizU/jhTf3IQ7b9w7hv/7wpv/3prcHhPuS+pG25mD8SkSwLNQoRGUUDPXo0EASK0O8z6H3lxs7bgxtm6jgIiEHTqePgvLquBa9Q92BrUp50AT0BlI2zNegU7ZSL1Cqgo3OOZtgcCXTcI23XSuIVRRAy1c9UuwyrJAdIXelMgpa1COJLAzpwOtkB6rUcI09XFVhNjumcBzVRSnOKnxkH4UUub+Yn+2hvZl1+hFr09aUY8bxbMQOeXsz7cCLnOt9fYFz2lSfDQUXbMdk7tyYcxYVwHg2wRjxx1KXyyBbE+7VEBVcNDVk0dkcUGJ6BryMQjg7QGYU2pvjMxejhRKVUeggxvHmxlZXIoMA3nkGaEe5sa6GW3rXA3nvoDIK44FCoVTBP/zkOfQOFmA7DlbFBAqlcgU/un8ttS3qe6SoR0Sg4omP+eVRRVWPIjQKJqNwaEBPlMb5HMmSglFj0zb87bJCw2CbFVkphJtR0BKMqtlYgs+hbBQdWNcmetzwvMLbdJxenf4bqlmIdCr6u+TaVKFjsFZjuwQCRUAvc6Fybdp2sAZkCT7PHYcZQ6PqkXpPgGpVPbKo+0DUtSzOKKgdi8zvn/1ceTE3f0zZuclm4VR7XOhkr7n3dMnnRkA9Ij8vfB/29x+3iXKwOtiMgkxw0VQr0BtEOPDNOaYik2vHro6Ttf2bG7IM3SXcMTk0t+Zw5iLKgU9ZFtoJx1omo9DRnKMLJkhlOrKoqw1abnm0Fh71qi/G6WeDi+HREkVxIo/H1zWUxfqR5vosVwRPUm9y2TQ3aPUQl1H45aMbqP27+8cQhde39VGVuQCgRvCbdByHLl3Lox5paRSSFWKbQGEKQefhrVpZRasngk5GQcexSsgZU+1ordWgqgolGJPLDmj0kVD8buQCJY2VbtVzltA1o9IITXpuE/w+ZZ3fJLJdqtSTamkUAHkBtDCjoEwjqp7egMyo6ARXehQvnd+Zrh5OTmzuOWck/SFMPbKY4CJmpb8pR137MjSi9mamBKmErqG9qTaU7WBpNyya62tC4uwoSlRNxi3Byo4Tl+mgqDpSNhrBFWPjOanlUKBU9MtyWmCF1vwgZlfPqH9tNDdkkSXoWkFGQRwoNNXXhLKwAP191mbpJmPhPgr8jMJYwa3I9PSru6n9W0lhNAe8Kk5kBqBUrmDdtl4UShWM5Mt+oFKbTVNdsyuRGgUR9Sgqo6CfUjCdmacQQunwKlSiEL0VmVHQCC5U5+XOLZngQjVQkFtNpP+uhjOWWH+Datgk4PTrBBdV6VWQFF1JK0MUJ84OPrNEPMBUaH4yTt+EG65pOdeSwUXKAsaDJPmMgn7DNemgR8MmrRNc6YyTsuD5YFJBXyh7HT+OqqCf58BFiZm9bR43247JKLgObPC3zOp4W1OOWsENHOVoh5zNQsRRgpobslQX4zjaUXtTLhQo2U60A9/VWufb+IFYjE1HM5NRkdB1dLTwA4VQqdeeET8MbG7IUs9hUcO5t7uH/dftDC0soFJFU4/IMqY86lFtTYYbHHkokxkFJlAg+1z4YxDm3f1j+OOat7H0iDacuKgTALgVmcjr/gf3voa1W3qxeE4LPv4nS6mxyftSVOCrp1HQh8koTCGEqUcyjhVnm6IDH2cjeivpjAJvajo2qs3TqlHBiGuj5Yxq6C2qwLe3tGr1a9gkkFGIP/7wtsnK3KgEPhXdQKEKFC92H53sQNJ9BMhzQgYKqloYaUqQIr0H0AuU0pSuQ3Ycwl6rm7P6bzPOjqcfiCqP6trQDp2SmFkmo8BSj3ynl29jIdwILc4ZB1xKDHv8cccCIHQ8UeVhO1vCNrbjoBBBPWIzKqIKTiQ6mumMSsXhBwrd/cFKOqu38L53Vm/w9j4iUBB8n6GMAkHraW4QZBQIRznHZhSY46MyCgT1aLRQxv7+cHaADDR+/uAbeGT1Dtx8z6s+7YrXQI0U86/d0gsA2PD2AF31igkUosujhjZRczNVjw5haImZeSvqGjQivT4Kao3dtJwxRR48oF7qU291XD240Krvr5Ud0OkJkPw506LEKDqwifVRqILTr1OG1qKcX6LiUcQxJZHtUm64ppId8Gx0dA1RjijxeiKdmavp9LPdnFXH0auUlGy/imCM8DbV8qh01SPebzd4bdvRznUHu9IfQdUA3OulJVQe1a2jL2q61dLoroyz4xQiHHjArSwUcvpjshZAuFJU1PF3ttaN29DjRNGi2ptr+f0qImw6W5jMjV/BSF40LspCkE5wm5BKxlQ9InQQoYCMl1HIpiPFzGTHYrLU6mi+TDWqY+cFAOt39Puv127tAcDPKHgm5IIGQOsdmpjGfjoN1zzwdA0mo3CIQKcShXLVIyGNKIJrqkE94n1cfHZAZwWW5/SqNQ/TyQ5I1Z3XoXeoZiGSongpOtfVoBEByTRcq4owOQG6ltQ4B4B6JCNMZ+cgzbfXWLmXDS4OBuqR1jmjjl9uHOXeC+z9TKN0LRCXvQ5e+1WPKOoRx4ZxFEUObG6cz81dHRfYNPtOv9wYgGilPz6jMKujIeTARq3atzepj9PV6tmQ46hlB2Q0Ch0ttQIHNk4LQcxLkB2gbVihdXxA0lTP76WRL7GBQvg68UBSj1iNwv6BsHBZpA/wAo6ojAIbKJGBSENtRiGjENDzqDlE2ExEo2AChSkEnQe+qqMk8gcinX7Fz9KZFyDgdGs4cLFVf7Q0CjqOMv23VtnCuIZjOtkBzgp0bAWjUHClQ9fSqMajc81o9JGoSnnYCf4GSLGgSvCvGpDqUIJky4NO3LmWu5eVJYMqnq1WIzQdp18jUNI5z9UotADoPGvCDinpq3DpqVRwIV5R7xhfGWed/igtgO+MM1VyoqlK3ko/G1xEBwozO+sZhzxeZB0ax44OYrpaxjMKksGVNw6PEhYZXLTUch3tKKe/q7WODi4kApKuljo6UPI0ChHjtDZmueMUyKpHNUxGgfkMWsxMVj2qUHSqYAz+XLyFnSiNAvvd9BCBQn2OFrN7HaN5+hGe5gcI7oO8QGEiMIHCFEK4zJ3EA4/rKKpRggD1LEScc8l/CFRjBTa8TbnqkcZDUnXV0v07eS1EEg6sFqddSvyoNi/e3OIoXnz6QvLnTC8LoTEOuUpuy62ST5RKp1W2s4or6rR+QO5eJkvT8lBPVBchSz9GgWygRdaij4JOpagJn2edgFyzM7O0mJmzAmoh+rcbJeb1HPhQlaCyuASpjtMfZBSCbXEVjNqacmiorWFKqkpmLpggJsqB7xqnHskGVxZ4egv+SreHbCaFpjq+DiAyUGhhm+EhchwgHJDIjNPZWhc6foBHPQofswfy3lGbTfuVl2zHwc79w2AhWpmvVNxAlZdRCIIrtklfkLGoq82EMjcuLY4TKNhhKh/gZhRElDXTR+EQguqDVZk3KnhPtgNq3OdE2WjVxNdw4OI5+mpjaNtoOOSqtCjesVaFepWAjU7mZrKqPlWD4jRR6hHJnY0yC3ezVgtIdZxRLRuNgCQyo0DsR5dHjT/+ztY6vPOEmWhuyOLdp8+TmtcxR7ZjelsdspkUzjluhpQNORd56pGGmFnx+2S/Cp3OzBZnG/U+ZxWXbrjGs6EdRZHT6znW7Op4XD8EMHOO1Q54wQUZkNjR48yd3uSOQxxfbEAiDGIEDnxNCk31bkfiUHAlcKxbm3JcvQUgPh7PeU/xbCKCmM7xikzksbjjxFRXIs+ZhNC8o7mWzqjY48ESI2Ymr9JwH4VgTpl0Cg11Qadn3nx5XcYBN6OQL1a4gY3o+FnqEfk7rNgOCkX++fISCRUmo1CpOFx9Am++KjDlUacYyDJ3+n0U5G7ecZ/jv6fj8CTkjOnYqFKPpBpUTZqYVy244GZUVDMKk1X1qQp0Ld67k+X0V7uKlbRGQUfbpLHST4uM1TUKWqJh6c7MpAMqF5Bc/e6j4TiOlD4DcCkM//LZM1AoVqh651E4YWEHfvf0VjgO/PKJcaA7M+sEV9UpjxsKSGNseI4i6avEiZkrFUcoMm4XOP1xFY/ccYNtth1fWYkdx0a0zbzxQIGl60StpgurHgnGaSY6ErPnuSQMrnhZGPd/kQPvNU2jnXGJlX5WAB3TDC5bw89cRImzW5tyqMmkQjZkVqkmk0I6RQdHURkFL1AgBdMsvLiCddILxQo3m+DNC4gWc9fnwhkF8jrL1aT9vwPqET1OZTxYSRpVySjce++9WLJkCV544QXu+y+//DI+97nP4bTTTsOxxx6Ld73rXfjGN76BgYEB7v6Dg4P4zne+g0svvRTHH388LrzwQnzzm9/E8HA4LQQA+XweP/nJT3DZZZfhhBNOwDnnnIPrrrsO+/bxW29XKhXceeed+MAHPoB3vOMdOOOMM3Dttddi69ateidgAiCfv1J9FHjpW0WnH4gJLngUCh16R+yDRW1e7ji8QEGt6o9MOUXW6dcR81aDrsTPqESPEx5D3UmoRnYA4FGP4p2REMVpknoixF03Wr1EyFVySqMgTydUvc6kufMaNJqutjr/9TTidRRmdTQAcGkA7UTTJhYTETPzPkMGKcuSDhIA12n8t784G9+55iwsnN0iPYYHneBKptBCEvohFVooX8wctie/j6jush2cjIKrA4imBLHjxgmGgywEPU6U0z93RlNoHNsRr/QC8K8pduVeVF2poTZY9WbnJrLxzxlDiQLEDnwHpwSrqDyqh8a6GtTlMqEsDCAOLjpb3AwEG8REdbPu4szNsZlswjhFkAramM+hMwoWFswK/07J37woOzBWKGNgmB9gyFSKqmeoRxUmUKjLBXTHKDGz6HczpahHL730Er7+9a8L31++fDk++tGP4oknnsCRRx6Jd77znSgUCvjFL36BD33oQ+jt7aX2Hx4exsc+9jH87Gc/g2VZOP/882FZFm677TZceeWVGBoaovYvlUq45ppr8L3vfQ8jIyM477zz0Nrairvvvhsf/OAHsWvXrtCcrrvuOlx//fXYs2cPzjnnHMyZMwcPPfQQPvjBD2LdunXJnBhJqD6MVXnQoueiqq5Ba9U2LrhIiAced95UV8YAzSyEVr8G1kZnpVtRo1G1Tq7Rn8FDmEaj8d1URQujc57pvy3FcSjevQKdUO7aVA8UPKcBcB/sMnjPGUfgXSfPwccvWeyvtMbhoxcvxnvPOhJ//afHRzrl5FdCBVWKzn+10dKQpbrUxmGiAmjV7x/Q69mjQiX1VnHjqUfBa3JltJGggwCB0x8W/8oIhoNtbt+BKOqRF5DIj+NTj0gHPqbqkQdqHIiDmMa64HchOzeRDgKIzyjwqh6JMhdBNSZOQCKw8XpChKhXMfqE0Nwc2lH2ujJHZRQqTEbh5KOnhcaa1hrc70RdpscKZQyOlrhzDfpViI+nvraG+k3ZTNBDBSuCQKFsO8KMwpQpj/rwww/j05/+NEZHR7nvl8tlXH/99bBtGz/4wQ/wm9/8Bj/60Y+wfPlyXHDBBXjrrbdwyy23UDY33XQT1q9fjyuuuAIPPfQQbr75Zjz88MN4//vfj02bNuGmm26i9r/jjjuwcuVKnH/++XjkkUdw88034/e//z0+97nPobu7GzfeeCO1/yOPPIJ7770Xy5Ytw6OPPoof/OAHuOeee3DDDTdgdHQUX/nKVybE7VKFagpZlUahk1FIqr5/NYIL7qqtogNXteZhk6BR0CsPqra/Ow5jU7WmThpzU1zp5GeuNHpPKP4GVAMlcqUrylSndK/OqvVZx87AxafMxbvPmIdTlnZJ2bQ25vCRixfjgpPmSO0PuAHJB9+5AEvmtUXuR66MkndoWf3EVEUrEVSQdd2jQJWh1Qn8NX7PKkUDAvFlsC1O+5YnOu6Sq6lAEDhQq8mgneRaptFWG1cAHZ1R8Dr1sqLpKOrR3Gnj1CPKgY3OdngIBReCcUgefUjQLRiHp4NwHAflih2i0XgIMgrBNlFPBA9dAgceEGcUOnii8ZiqT528uTl0gOk1WyOvtFB5VKoHSwonLZkeGovMhvodo5ljGWUyCmRwK6PRYKlHbEahnpPVcEIaBZp61EAWajjQ5VH37NmDL33pS/irv/or2LaNzk4+F3P9+vXYv38/li5diksuucTfnsvlcM011wAAVq9e7W8fHBzE3XffjcbGRnz5y1/20++ZTAbXX389WlpacM899/iBiW3buO2222BZFr761a8im3V/5JZl4Ytf/CLmz5+Pxx9/HDt27PDH+PnPfw4A+MpXvoKmpmDF66qrrsLZZ5+N9evX4/nnn0/iNElhomXugJhKIQInQjULocJPlRlDNM6kaBSqRKPRofgoaxQ0MiqqlYUAzrFo0LWqQT3i2VRFAJ1AFkJVZFqSLY/KvJVSvG/IrlrX5TL48LuOwofOX4SajFzVn2pCdNmqUI+mIt57zgIcO78d5x4/E8vmt0vZzOpy6VqZdIpa/RQhlFGQobkq/p5Zjj67+smlHhEuXZ6hkCyd1wrAbbQ2q7NhfIzAlm3QxmYhWhv5guEop987T+RM4yoYecFdKlT1SMDPJ6ppyQYXJI2NzZCIMheNXPFz9LEEFC/6uwSiaUTuOMS8bCey0zS/y3Q0VaeL03CO5fUHGYXw/N0xHOq6zKQttDblcOQMOvtJBgp+x2jm+xwtlDE4GmgUWokuzzIC8PraDPVcrTDZgVoiUHAcdx4hMTNDPaonAoUDnlG46aab8MADD+DYY4/FXXfdhQULFvAHG78Z9fT0oFymeVR9fX0AgJaW4AewevVq5PN5nHHGGWhsbKT2b2howJlnnol8Pu8HFxs2bMDevXuxdOlSzJlDr2ClUilceOGFAIAVK1YAcAORl19+Ga2trTjllFNC873ooouo/ScDRx/hrqJNa6vzU4VRUBVZivw71fKosatJWjSiia/aAvEPvclyYBOh0cTY8N5X7TI8Wc3jpM6ZzncTEvNWocsyLyBVvDZVA1Jt6pEi31y2J8BUg0hfMNWoR6qY2dmAv7nyRHzqPUdLVz264oJFeP858/HFDx2Ppvr4LIROwzVVKiFL96D0CQJb8nDHCIcnW5PGZ9+3DB9511H4mytP9OcbXukPHNHpjCbGtwkJhgmb9nrBvOSzEL7ImKT42GIneeZ40MPOjXX6/895C1CXS2PhrGZc8I7ZXJso/YSna2B1HeQY7LfCd+CjswOdrfzgIkr87GcuGOpNFFVHlLkg6Tq1NdHUowpzj/XmfPzCDmosMvgWCZPH8mUMDAeBAkk3lOk90cApj8pmyNiANaRRYDIK9YSWZSLEmESqHi1YsADf+ta38L73vS9ydXLRokWYOXMmdu/ejS996Uv44he/iK6uLrz88su44YYbkEql8KlPfcrff9OmTQCAo446Sjgu4GYqzjvvPOn9N2zYAADYvHkzHMfBwoULufNm958MXP3uo3H6MdOxYFaL1AOPd79NWsw8WQ2q9DIKnHEUKwVNVnlQOQeOnZtaHwGLM278vKq00q9z/DoiS1VKBC+40sjcKGcUFI9FtokYew3I8M11avVPNYhOycF6PBNBa2MO7z9nvvT+OlWPVK9nlm9PNVsTDEeLmemMQmtjDu86ZS4zp+A1u2rf3JDF59+/DM+v24tLTg3s2CwEafOORZ0YzpeweecAPnHpEr4Nk4WYP7MZW3cPuvaLA0oeuzpOOrCnLOnCC+u7YQH41LuXcm3YqkenLJ2GS0+bFwrqQhkFwua4BR14bUsPmutrsHhua3hejDPaVF9D8ey9VXGVsqVdfkaBDXqiaERhG8dxYisruTb03GjqkeviimiKJL2T/A0ct6ADv1u5zf+boh4JnP7RQplqttZK0AbjNBqZdAo1mTTS6eB9NqOQq0kjlbL8LIJth5u/sTYNVEbhAJdH/exnPyu1X01NDW6++WZ84QtfwIMPPogHH3zQf2/atGn42c9+hrPPPtvf1t3dDQDo6uLzYb3tPT09Vdl/2rRp1P5JI5vNoKsrLPCbNVOuOgYA5HI1oW3TpzWH0q4kLCscXXZ1NqGLWNkgUeBcX9lsmjt3D+t3DYa21eZqIm0aG8IZlMaGXKRN695w5atpXU3o6uAfCwA0N9Hj1NVlI8cA3LmTqK+XsaF/Xu3t9bE2LKWjq6sRHRHCUbYzYzqdih1jlCk5mMuFr0P275Zmeg71tfHH38CsbDY0qJ+z5ubaWBt2Rby9Lfo8d3Y0hrZ1tDVE2rR1j4S2TetqQkujWKTaxFxnmUz8d1NLrADVZINzkRPcKwCgrpa+NlMpK3acpsZgbnUxv8upBm+udXX8lfP2mO/yYEC150/y/wGgq7Mxdsxslv5tZmuinwE9I4HDmUmn0N5Br5zzbMn7X7omGK9J8Bwgg2nHAWqI+3RLcx0ue+ciXPbORZTNYCFwpNLpFDLEcbW11uEvLn1HaJyWlgH/NXseLj93AdZu6cHAcAF/ecWJANzvr4Ho8ltfn4VFOKIXnX4EPvHeZajLZTCDOC854v7X1FRLZRVnTm/mPgvIc9bYVOc/2zNpC1/+5Kl4+uWdOHZRJ+bMaAZAr6g7ABqags9sba7FWSfMxiPPbcMHLzgK06c3h47fe+aIStcuWdCJrs4GtLT0+9uy2QyamsXPsSULOtHalENDQ/CbrqvPor5BfH89an4nUimLug80NuZA5kVax58fdYQ/1NgYXEtDBFWohniOnHr8bMzoeAN7ekYxs7MB8+cFFEDv2t3RGzRLA9wqXSOEkz5rehOA3QCAzPhvJcvx1wCXFtbV1YQ6Yj4OgCxxPbQ21yJNBArtHQ0A4y9YqRQyRDPItuY6AH3BB2pi0vsozJs3D5dffjluu+02LFu2DB0dHVi7di327duHn/3sZ1i2bBlaW1sBwNce1NXxL7Da2lpqv6T3z+Vy1H5TEXxhZjyNghVoR60o6dWD59A7NMpW6tCVyA6qMjY69Bad7qcyNuz3oFrqVWZlkD1eKdqBzgpkEhoNjcyFFsVNp6Rq7HfD7K9MPSJLfsrrjmQyFzq1+qcadLrMG7hgr/dqFw2wdahHRDCTy/I1MSG9AafiTXgM2oZdteXaMKvW5GpyY30Nrv3wSdE2LCUmm8F8ThlOem605iKX5btr5DkYyxPnrCaNlsYcLjtnQWh/crGQDBqzNWn8xZ+egE9fvoxatKG48zGr415J5CgaDQtf18HSiCT0I2nmnBVLvKpHNA3KA3mPzRB+Qzpl4Wt/fiaeeXUXzjxuJjWG6PjHChX0Ep2WOwjqeFxjO1+cT50zG2PMNcOeU1ajUK7YGCMCYVL0PhGNwqQGCn19ffjIRz6CvXv34rbbbsPpp58OACgWi7jxxhtx99134wtf+ALuuOMOAEA6Hf6SebDH00fV3j9pFItlDAyMxe8YgQon/dfXO4LhCGc5ZbmpYBL9faOwBKnE/v7wHG3bRnf3EGdvF7xzWilVIm3GRsM1iAuFUqTN0GA+tK2/fxR2RA3uUaYpSrkcPS8gLFwqFsuxNmXGZmhoLNaGzRD0942gOMZv4iJC3Bj9/XTga1eC79JbaWE/Y2SYPs/lmO8SAAp5ulRcsSBxztiSc6PFWBs2PTY8nOfaeMfW3xfODgwORn83vOusr3cYY4KHNxC+zizEfzcl4rodIipoVCri881eZ5m0FTvOGLFyValE/5anCthrs1DglyIcjvkupzJEv7+kUWGeaYODY+iOCRhDzxrHiZwn+WwrFivo7g6yv5bFv0bJ+19PX3CfcgTPG2p13KFtRM8b8v5XKlXQPxjMsyS4rw8Tv8V8vkQFMfmxIvf+mSfuf0PDBQwT94OxkQJ3HPL3398/SgUXQwOjGBsOP9fJc7CnO8jkZzIp4feTsizf4d2zL9gnheDaIy2Hift/nDC5r9e9v5LPjNF8iRqHxf797rUxNhacs+GhArr3h+/VHoL7QHDOBgbHMEJ8hjN+byPvFYNDwfOhl7ivk1d/d/cQsgDOP36mOz/imeH5C909YTZD72BwnaQJ17ww/uzrG+T7e7nx74oMJMoVh7qe7XKFCr67u4fQyzSGKxTK6CWu7xTI38cBrnoki1tvvRVbtmzBNddc4wcJAJDNZnH99ddj/vz5WL16td+ozVvpz+fDD2lye319fVX2LxQK1P5TEToNt5IQQOuIbLW6OcfyzcPb4lbuE1nprlrvAXUbEjJrqYnoDapWHjWBuemU1NXS3Cg29lMUwMtrFNh5yXw3wWvZ8qhTDaIFnoNVnD2Z0Oo0r3jfYEWzdA8Fvi1d9YheHRfNifwkcgU6W8O/DkK1+kkbwQIbOQZbjSgrqADGCmhJTn9WlLlgMoreinHKsoTfETkO1WwsojIZaZOnROMS54wjMvZq/L/zhFn+NrYRmkwfCTYLE1X1yLdJ0eNwy6OyF+M4ykRgGnUfZAXjAIQdowE3k1FLfMd+7wWBTd24loAqj1phrs2aNN34znZCC4ts1SOqPOoEMKl31FWrVgEApUPwUFNTg7POOgsA/CZnnkZg//793M9jNQZJ7+91chZpGKYC2Bu+BZkbuJqjpFclJrxNpZyerI1eeVS1MQB1Z5Q3t2pVCiIh02k2iXnJlUdlPqNK1CO2O7mWAL4afRS0rrPgNckBjgqYJ6vh2lSDTgU3Axchp1/mvqFKPSIFpI5DrWiKaWPBaxlKEDsPknYhRSNinH4ZihMrMhaPQzvXVHAh4ZCTx5+tSUlV+WJtRBDZiIIL8pw5Dp1hr8tl8NVPnoI/v/wYXHVRoAcJi6yD429pyPpXx1UXBjYs9UiUtfjYJYu5c2NF47W+mJnex0NFsqM7GygB0c3TWhqyIZoQIC736lWkiqLF1WbTIWpauCfEFK56JIvBQTct5lF+WHjbSyU3TeRVL/KqGbHYvHkzAGDJErc6weLFi6X29/ZbtGgRUqmUv53Fli1bqP2nIvRWusPbVMovAvGOYlIN17TKVsY4SmwWRsuBrRZHP1TqU83pkfGRtGqoJxFcSK1a0n9X45zxsnCq15lMQD7RVduy5ENMK3ND2BysVYJ0KrgZ8KGzwKBSHtgt5Ui+Fz8PWadXtDou48CzTc1E2QG26g/ZzVnG6WdLqsoEMYVifAbCHSd4nZe2UTvPFvNdFpgszIz2esxgSsuyq/Ckkzx3eiP+v3MXoHcwjxMWdXJtbJuuLHTO8TPR2VILy7KEmQvbdpDn9lEI5iUqjxqZUWCOH4guderN07cZ/18UXHjN1FKMfoTS6TAZBZ5Gga16RDZpO+B9FGThlRt98sknQ+9VKhU899xzAIClS91yYaeeeipqa2vx7LPPhgTFIyMjePbZZ1FfX4+TTz4ZALBw4ULMnj0b69atw+7du6n9bdvGY489BsuycO655wKAb9vT04MXX3wxNKfly5cDAM4777yJHHZVoUXVUFy51+t+PPEVWB0by9Jx4NTLlsqdZx2bYB/LklvpIyH3wKf/1nHGZZq0TRr1SHEcvWtTY14TpJ5VJKlHOgHp/FnN/usFM5sj9py6MIFCcqjG/SxEPbIlMgqkA1uId/pDNhKOMuv0FhXpSg7Unf7wOPGZC1LIKqJEueMENqwDL7Qh3ipIzCtcUjW4N4mKh4TPM03Xmj+zGScvmUY56GxfDJKu1FCbwfvOno/LzzqSsmGpZLxMlKg8atmWzSgEr2Wap3W11YcoUYCYrkQ2RiOfE6OMoJ89P6E+CrZD/W6mVGdmWVx55ZUAgB//+MdYs2aNv71cLuPb3/42NmzYgKOOOgpnnHEGANeR/8AHPoCBgQHccMMNfpO2crmMG2+8EYODg7jyyiupZmxXXXUVKpUK/vEf/5EKLr7//e9j27ZtuPjiizFv3jx/+0c+8hEAwA033IDe3l5/+1133YVnnnkGy5Yto/QUUw1hp099dTjOjvf7mazsgKquQa5x0MRWYF2b6oxD3lxV9QmAmI4hGgOYvOxA1ZrUscFFXLZLI1BgaVST0XuiJEs9Yu8BEr+BOV2N+MpHT8Ln3rcM5xPNmw4mGOrRxHDi+EruglnNaGmIb9Km+ttkHTiKeiSwpVbUJZ3eqN4L3DGI12yTNlkakarT7zigsxCC46GcfknqlTg7EGEj0ILIZlRkjj90zsrx32cUXUnUDZ6aG1NdKsfNKASvqYZrqhqFyGZwtaFjASIyClSgQASLoYwCMXeORqFcsamMykFJPTrvvPPw2c9+Fv/5n/+Jj370ozjxxBPR3t6ON954A7t27UJnZyduuukmipp07bXX4vnnn8f999+PNWvW4JhjjsG6deuwY8cOLFu2DH/5l39JjXH11VfjiSeewMqVK3HJJZfgpJNOwtatW7FhwwbMnj0bX/3qV6n93/Oe9+CRRx7BH/7wB/zJn/wJTjvtNOzduxevvvoqmpub8a1vfWtSzo0u9IS54W1RvpUWPzspG0WnT6bU40TLVsrahB1yibKVE6SE6FAI9FbHq7WiHv0ZfBvFjIIi9Y47hsR3EwoupAKy4HU1qUcA/AZMByuEYmYTKEjh/37gWGx4ux+LOGU6eVAuQ8xmFAhPRfTdkffMkqwTR+ka4oW5LM9bSmRMHQujNxA5/VqZi+B1nulMLQKVHZDNQhBzk6Eesc3TyCBOlFFgHfiiBF2LpR7JBBchLQhx3uo8zQl5uZFiZvIeG1Uinjl+QCxMBtymc+yxuDb8LARJESK/m9G8OKPABt+AG/iQ32ddzu3mPBHaETDJGQUA+Nu//Vv8+Mc/xllnnYXNmzdjxYoVsCwLH/vYx3Dfffdh0SK6OUprayvuvPNOfPzjH0e5XMbjjz+OVCqFz3zmM/jFL36Bhga6sVY2m8Wtt96Ka665BnV1dXj88ccxMjKCK6+8EnfeeacvYCbxb//2b/iHf/gHTJs2DU8++ST27t2Lyy67DHfffbewy/NUgc4KbMiBTVmRDiYrFgXiV215b8fRVfg2asGFViffKjijvH3iOL3sXGQEwyxkTEJdWat0/ElQj3QyZNWhxallLXj7SAnASY1CWY56xPs9Hw4wGYWJoSaTwrIj24UCXhaqQTzbZZfWKAgyCsRrknoX9dMhn09lCc55lDBZhqNfsR3fwbQQQb0h5lwsVahGaKL7GnleqB4KkRoNQXYgQV0DW21HplIU68CXZLIDjENeUg7IQK2oe9c22yWbPBYPUc9nNugBYqhHrXWh69+1EWUUgpV/UUahlqNR4Fc9Evde0EVVMgq333575PsXXHABLrjgAunPa21txXXXXYfrrrtOav+6ujr89V//Nf76r/9aav9MJoOrr74aV199tfScpgqm7ApsAtkBqXG0Mgrqq8NJOMqqPGCtjILEPno0KvpvHTF3tQIyVf2IltA+ieBK8TojS/dFahQUA6VDBSajMLlQL0McvA5RjySCPNmMGjmOTElhel4Icee58yJes461ajWipGlEQo2CrA1V9UjCGbdZvYGkmFsmO8CsmJPUoBoZihdbHrWGQz0CmVGQy1rRVY/c/yMzCq116CF6NAQCaEFGoVaQUSCb4XGqHlXYjIJtI18MtnmVkljRsyoOjyfKIQw9B5b+O7YrbQLagWrZsFPT0yhIrFonwFFX1yjoZBTUHWstp19nRb1K5WFVV+6TENqrliDl/c23CV5TTk+URuEwzSiIDlNH22MQD9XMHesoyoiZ6apf6uWBKxK/GXall+rOK7hHkWOQq8JRC1OWwBmPduCD13lpMbO6DXlqZIILmuNP6w3E2YHgdVhvIMpCkOPQjrU4c0GPwy+PSkUKPsjGg5EZBU52QFzqNIP62kwoIAXiqx4B9P2b1EGwGQXHdsD2Ai5X6PPM0pV0Ye6oBzl0ePCqNbST6m8QK37jfY7qSq/G8VcrOxAOLtSCGB2HR8aB16Kraaxah5xrnSBGg66k1+NDsXlalahHVEZBWqNA/334BArxTp1BclDNXrPOpRT1iNhMOnGR1DtRcCEswRq8tm25eemVLQ5e04JhdRqRyBkP20gGJAKNgtiBp1f6i1IaBdqGdHqFDfTYzAWla4hvUsdSj3jlUUmtjLSYmUs94jv9Xa1uI19+cKEmZiaRY7JXFTtc9YjdP2VZWhRmFiZQOMiRCHc8jtPNebsaVY/0mlrR70tRjzQcK62mVhNcUdfLKMTvk4QwWUZvkUi/iipQfCzLUq7IlES/EtUshKxG4fClHvG3Hy6B0mRjImWI3eZQEmJm0hHSqPolk4WjS0yql22ltBOSAUxegxJEOpU1GbnjlxUzq3bADlOPVDUKYLIQcgEJfQ7ktBBFHs1LcPrI8qhRvgNb9chh5kbCDxSYcwaIxcwNhEZBdK+vqUlRvznbcfyyqzx4QZLJKBgkU42nCk4/735bDZvJOH5A04HVGIfcR0ejoLXSPVkCcKlKQTrj0H9XJbhI4JqRKw8bvKb4s1GBwmFKPTIahclF6LepkIl2HFp4KfqOaI2CnEaHXWWNsyGdZJupRS+ja9ChREk78IpBD0B/L6QzHt1ALHhNUlUykk4/WfVJpB0IV32Kzw5QWSjZgITKjpR9ZlE2k/LfE4qZJe+x7L2G1VyQmNZWFzqWuCxEXS44H7x5pFMWUpYVymxEaQ+8ICmJ+6EJFA5yqKaDeTYq9bBlbZLIDrg2apWSqtZHQYMSo1NdaOIaBbn9VDMXyZSUrVLvCUUqHTs3S8JG53fGOlZSVa9IioMtqVHQCMgOBYhOiaEeVQeqzw3ybTejQL4ncuJJG9mMAj+4EAcjwWvpjAIVwKiLrEsaQb9soERnO9QdX5njYZ1e1YyCI9lHIURxonpPxAcXpPi3lqjmRX2tJPWIDF4VquWxFZlI8KhHti3OQuSyaerZyPuuPb+GPqeIpB55wZjJKBiEnCRVZwSoDiUkMTFzrAOncfxaXZZ1VoeDfVJWdAnaYL/gtZYoUzJSoMqwVq3qU/RnJDYO65ArHs9kUaJUxymXJVdUNbQwhwJE58RkFKoD1es5lFEgqUeCS1SoXZB0yGXEzGwjOJlMBzWGRGDBvifbZV31WNj3ypK6DpEWSub8s+VRZcrDhmlEcnoDOQF0YDPG9B0gZuO/In1rWsguT8F2HIdqoEeiq6U2NC8HYqoSKWQG+Fo275nGdruO1ii4EzYZBYMJO7BAlUpQamQhkhBN62kHqtXNmRyjOg581JjR4wSvp5RGQyuI07Ahj1+npG6VKFHsg0A0Pj2O+nk+FMDr7wKYjEK1oNrRnaKROHIZAmGp0YjbDaU5ID9L5PQynHbKRnBIol4Nsk6/jDPOzk1vHHUbmcCHFeYWFbtMu1QdtYZr7gq8WjM4upMxUXKUCVo8yGZg2HFsW1z1SKRRKDJi7o7mHADg2Pnt9Di8jML4OSaDiIrtwBFXaE00ozCpnZkNkocWJUTDgXF/JAo/Kq3sgNznRL1fLeqRFkddg0akutLNQiZrwY6jpVFQpPe441Rn5V6VO83uozcv9fKoul3T42x1ztmhAN5hWpbc92+gDtUqXmxGgXRqZLQAsmMJtSrCYCR4TTrJlhUVqBAOWlWdftoRVB2HzkIITYQUJxntCCtmFmUH2EUPVb1BqOqRRBZCRD0SQVbMDIQzUaI+Cm3jAQCdUWFKnebSuP5Tp2HbnkEsnddG2fO+gxqPesSc0yiNgpeBSeJ+aAKFgxzJOL0aJVUnKaMQNzX2I7Uarkmcs7DeQLXUqboDL0OjYlE9jYL6qrUW9WaC51mW4sXSwlTnpUdXUg/Igu1im1AH8MOm6pH4gWqQPFR/zyynWyajoFPyVvSWKo1JVm9AumaRzjjl9MvSiILXeg3nJAMSIkMiR9cKXtuOQ/VekOmJIFvqlBydda5rhBmF4PWYIFCQEzOrUY/IuX3xQ8dj1Rv7cPaxM/zPCVVjYgKlxroaHDu/IzQON1DwnX5iDjHlUbMJiplNoHCQIwlKiCpVA5Bx+nmfoRFcxK1aTdbxT9DplQ4UFClBLER0jPA4xNyqVFKW5SFLlVRldlH9bvQoXho9ITSCHh1aoIytTqWoQwG8U3W4BEkHAuz5VnkGsOVRVTMKUcG/anAt+iSVggH+9sjfZfBauoKZIKMQefxUdkC2SSN/bsLgKsbpjZuXdKnTiMyFsAM0YTNWEHTApg6L7Mwsn1Fggw1SnL1sfjuOX9hJ709S4iSF2axdMDf32JU0CplwFkIX5q56kEOveRj9t9bqcByNiDOPeLqS3OdEzUMmo6DXZZmxUe2JIOnApIiToFMPX/aeQO5XtfKwCQRkqg657E3RUjz+JJr06QQXga1cZ1bZcQ4FRHF5DZKHauDL8s2pxmaKjrdK6cq4z+L1UYna37Xhb5evxqRe6pSE7PHL0pVYGk1gw98/HCjIrPSTNlDvvSDpXJM2VNdsYgy2S7iHioSQnfcZpbLtf046ZXHvz1RGxZHrIyGaB6/qkatRMFWPDCTAXgM6ZRtlOvepOkrJiZnlS5YBQEarBKcE9UrjnOlpFMjXGj9wSRO6DKsO337q9F6ggh4tjYa6A6/aEwHQy9zEbefN5XBZVedTjw6PIOlAQDXwpeg6jJhZmDnQEKirUo9cm/B70SvwOvPiO6dRTdq0fv+C91R0TbHbmZVs2umPd+BZp19c9Sh4TY6RTllS2Q5RQEY77Xwxc2zVI+Iz6K7ZoqpP9PGXJPpIAPRioT/G+H2NarhmI1KjkDVVjww8JLHSq+PAaJU61Qgu4seh/1YtjQlMzjnT0SjoVK+RFTNTjd00VtR1aDQyQZyWMFkjozAp5VE1jkWHeqQTkB0K4J2qw6Ur9YGAKv2UpV44EqvdMivaLGSqG4VsFJ81WpTAJB14nblJaiFkxqEcbcnsAB0o0hWMchJZiEIpvuKRO2f+duF5Jsuj2nI6EIC+zgqqfSQkK0WJ5pHhCJPZLB0LL4AzGQUDzY6xzN86WQjFlX6ZuXEf/IpZCCm+OXssGgJoVY2CtAOrkYWg7CVNVAMSvXMW/Rn8edF/qwZx8hoFxTG06GoTv85kxjt8qx6Fj9OImasHdrU/7vdMaRRsWkQaRQviIfmMQkJjJKidAJJZKJCxUQ2uQhWMVPUGoZ4I8ZWSyO7PUZx+YdUr4n4ryu5QYmaFhmtkp22Z7AgbXEVRj3jfW41IoyCTUdBhJrBzmvAnGBxQhB0r9QpGenQddae/KhkFDY2CTqDE7qJ6zmSbYOnYiOzlx9E5fnVHWafqkWrmQitzM0nHMpHyqJGOwmFLPQpvO1yO/UBAlX4Y1XBNmfqi41wrZiGi6T3qAXyiQU9kdkTdRvTNCcujMhoFerU/nnpUqdg+TcaC+DlNzqsgQe9hx6G2k8dCvCQ7Z5DVqOIWcmjqUXy2g73+SxJVn0LzHkeGU/XIth2qQAALk1Ew8DHRlW5pG0XnmnfDqU43Z/pvqT4KrGM1CY6i7Eo3KbSuJvVoohoFnetM5zyrrvZLB0qK2R7LotdT5TQa9N8TK48q71wczhmFTObwOPYDAdVnAPmuA9DUI8WAQG9FXTw31YyCOBiJGEOHRqUTXAhpXOo24kxD8JrVKIiyeOQYZAYinU5JHSftjKs51gB9H7SEnZkJjYJC4FtQ1WjYjrSYmfec9M4xeUyV2PKoRqNgMA4dekNIZKm4aitjo8oB5c1LZpxJq8ajtToc7CPbE0Gn9wIJ2Swj+dE6Va8mQ8ys0xNBL6MgW5FKbRyd4zflUeXBzShoZOEM5KB6D2SDa7a5GddGw+nVWlFXFTMrztedV4JOv1ZwITTRaFJHO72lkgT1iPiocllu5Z6tLOQh6vkpeou8Psl9hFWP4jIKJC2KpB4JMwrEmKCDpZxmeVRWIB4tZjYZBYNxJCLMrYLTo1UeVSu40HHG2HlVp5sztdIt+WNVFRmzkLVQXVHXu2bov6tV6lSnDK1OcEE1aatWcKkqzEP4uzlc6Dc8Z8eUR60eJrrAIlO6MyWqeqTo9FtWdHZVWcwsWrXW0ShoBD3Rv3+18SNtJAI123akKDsU9YbYHnnOiHHIQGHCGg2GBuSB7qMgr1Ggsh0RVY/IqVFZmEhxtvi+Rl6HjoNojYJHPTIaBYOJrnTL2qiKpnVoRNzyqIoXuVSVHK3jZ+aleJ6rudJNQpZ6pJrt0BLzal2bxP4azdPkqUd8+yTnlkTvBX+7woPycKEe8U6VETNXDzrXM2lCdScWUl/4nyPbmdj//Jj7AO/jkq9GpPZZ+uMIgpgEsx3sSnZZoqPxRO9lVHARlYUQUo/IPgrBdqGYWYHxkJegHgHqwYVoHp6mg6UzRVU9yhnqkYGH8KqtjJiZ+QyN1eF4kXF4W5zTr9NwTWf/JIIrdY2C5Eo3ZaP+A6/LyTVbVw1IkiiPqlpdS74nQvC6WmJmnbkloevwt0euwsl9xqEGrkbB9FGoGnQyhFQzsIq+mFm2M7Hs3LgZBZ0VeA2nXzXoidoeNY7qOXM/S7R/8Nq26Wo74iwE/7MiAzKRzQTPM7kHKWYmy6PGdmYWUY8inH5LECgoVz3idFmuxIiZeTa6MIHCQQ4dZyxc6jJ56k0SFYxkxpH5DBZa54w9fsVzJnsc09vquK+j8OnLjgbgPkw+/K6jpGzamnL+69bGbOz+euVRJxaQ6VGPJG00KF7KJWU1HCsd54K9zmSzSgc7+IGCeaRVCzpaGDqjoB8oqK6OR2kHAP7cValKos8JbARjT1JwEWkjGl8qo8BUCxJlh0THEpUd0Gm4JxKNk4ECRT0K9qlIZEb8zyM+Q6aPAjs3GQE0wA+KfDGzhkYhiYyC3PKjwZRFIpVldJzrGBudLss6AujQ/hK7T5bT21Rfw30dhZMWd+FPz1+IctnGGctmSNmcdewMTG+vR3NDFl2tcsHFB86dDwBYMq8VnRI2yWhhqhNcTVTXoEM9qlbmSuhcRD4o1c/ZoQDeuTKBQvUw0XsArVHg7691/StmB0Tj6DjjSVcj0mqeNgnjeMJ07xsUdUCWmpfGsejQwjJUoBBsJ13rSkUho0AGCpSYWY56JCOABvj+SMbvoxBsc+y4PgrJiZlNoHCQQ4dGxNroNM+qSqlTxZu37Lhx40jRSDQekkfNbcU7T5iFPT0juPS0ebH7A+4N4T1nHCG1rwfLsrBodouSzbzpTfirPz1eySZlWX45NrmSquzfatemdHaADC6qSVdSdMgnmoWibGUzCocR9caImScXIfqp4gIT6ZSpc+Sjxghvi6UecVauo8upqju9OtWIZFbHw+MIbKoQXHhUF1porDa+jjA76t4pcy2xPQ08UFWPYhcyg9d5yYyCqKRqMlWPEFkeNZcg9cgECgc5dMqj6nCnwx2Q5caxbRWxUAIZhWpRr3T45paFq9+9NHa/gwWpFGCP3+uqVl2LzA5IOv3kKot0dmCi1COd8rAyjpUojS+5OqgjgD9Ywc0oHEYZlclGqKCFIv2uIvEsSC6jEDMvRT2cltOfZHChQVdKvLoScf8vS4qAycUlmXlpZSEkrhkqo0BVPZp4eVRRwzV2brIaBd755OkNbMeBY4d2JeaVHPXo8HmqHKII0xskhKlgbdSdvqoIoHlZCEW+dbWqHulU/TnUMJGSqpaGTbW0AwDjXEvSVZSPn71mNPpV+LaRq4NqYxwq4GoUTEahatCqFkfYlGUEsFrONWebzqKU5G9swjYaNBqtCkYRp0DnPCcVkET5KFpZCMF7FPWI2E73UYjXWvDmRneNlssOyAcXvIyCFXqvYjuoSDRcM2Jmg0lzekM2Gg55fHnU8LbqUI/0sgMTmdehgLamWgBuZaXarPjm6MFSdKzZ/aQdeB3qkUbmgjwEmZVrvfKogu2y1KPD6LrkUo+MRqFq0LlvkiY21XBNlFFQd0Z1qh6p6hq0SpBq9IQQvRUV+OjcM4TjRJw2cdfm5L4bnYZ7MgGMSMxMdWaOuXdMlHpE2kQFF7IZhViNQoJ9FAz16CDHZPVR0HpIKM6Nd0GrXuMy+2sFSsQHp6zDp7IMiY9dshjLV+/AWcfNlHLItHQAFvlaw+nXohGpZyGqJmbWeFBSTfoOI0eZd0pqDqOMymRjootFVB8FkXOr5fSqOf2ujdoYQpGvxkq3jjA36R4Poux9ZElVwXlWtomal2B7VKZURm9BZRRAahTkOkYDbEZBsuoR8ZFkFiK6UpJ4AYR8y3YcoUYhk7b8zzFVjwxCaxZ6egP1OvpaHG3FQEGn1KNOedRqdQw+1LDsyHYsO7Jden86O1BNBz54rWWj09htkgJyGVuqv8NhdG2ajMLkQq+XSvCa6qMgsNXj6KvtLxpfJuPN+mVa2YGENQo6XaP5Yu645zNnWyydmDMvneBKgxKVoRquSWQU4sqjEnOTzQ6QNsVSEJREaxTC73nlUcMaBX6gQJZfNdQjA72MArOPHK8/+jOk5qa4yqNzgeuJmdUcuMOJBz4RUCvwkgGfFl1JR2+gmB1gbWRFs+oC6PjPmegYhwp4p8QECtWDTrljquqRRB8FHfqp6qo1IHCU44ILzvuJZweEWoioeYk+S22cuK8zKYpXkh2jXRvB2BT1KNhOaxQUxMzE27JOP3n8pYqcHoLbmdmjHhGfZ9viqkekBsKImQ00Vy3pv6vXPCv6M+LG0AkUpKhHloX2ZrfhWFtTTrIaTfBalgd/uEOPeqSRhSCDCw26UlX7NahmIbToCsR+h1EQa8TMkwu9BZbgtUxGgbc9LqusSiNy3w9vS7qbs4wDKzNGnE1U7wOVceLpWhoBmSr1SOf+J2FDBQok9YjqoyDf56ks6fST45apkrJqx+PNjRzLtsUN17JEbwejUTDgVFbRoRFJOMoaaWfV4CI0L40LPC596OHTlx2Dp17ZhXOOnylFbzIZBXXU52qQSVsoVxw0N8R3fwbo61m+J4KG068VxJA2spWSACiUlBWKPCUfLIcX9Si8La5pkoE+Qgs/ijRPskKL0LlV7G8g+qy4nwG3m3OMDflbDrapO7DR2QGdFXWdxQWd7IDcNup9xSyEVnZE4viF1COF8u3kHEinX/Y8ky69akbBox6Rx+FqFPifQVKPjEbBIKwDUHR6gSqKmZU1Cszfkhf42cfOwMq1e9BYV4PjF3ZI2Rx9RBuOPqJNal93buqryYc76mszuPLCo/D8G3tx+VlHStl0NNf6rztbaiP2DKCzoj5ZAmhVm4mWBzycxMxGozC50KviRQQKVMM1wf4a9BadlW4dR5k/jtr+cXPTc5STsYlbMNP7bsLb9LIDUZWF4j+L3IVquKbZmZn0z7WCRUUbbh8FO0KjQFCPkvBXTKBwkEOrCY5Gx9wQXUnD6VHt5izrjH3k4sVYekQbFs1poVJuSYKcm2nqJI+LTp6Di06eI73/zI4GfPzSJdi2exDvlQwuJu70yzmXE9VPyGXhRNvFtnO7GtFQm8FIvowTFnVKzetQAM/ZqzGBQtUw0fKoFYk+ClwaUawDq2HDG0cjuNBqBKYhTE66SRtvnGpoQZSrHk1woURkw8soOI5D0eFUOjNLz014PGoN14I+CsG2qKpHZFUlk1EwCF2IOvXdZeg6E60UxPs7NAbU9vdQl8vg7ONmSu2rC3IqJqNQXVzwjtnAO2ZL779sfrtfkeS4+XIZJbqbcRUzCtRq/wQyChEP/WxNGv/852fg7X3DOPeUeVLzOhRgcW5bJqNQPeiUlVYVM2sJk3WyA5z3kw4utMqWCrbrOMqRXaO1qh4lE1zIcvpl5yZHPQq2e1eh7QRqBcvSO/64uWkdDy9QEGQUZDQKSZRyN4HCQQ4duo5WwzGN1X7VLMRU7n7cWFfjO6PN9XJ8e4PJwcyOBnzr82ciX6xgTlejlA15rckLk4PXWroGDVpgMHa0bUtDFi3z26fUb6ba4IuZD5/jn2xMOKNQiRdz8nnw6g5cXGdmng+tJczVWenXcfo1RNPRJZXVxnBtNIILbnWlhIMrCRs6o+A61yrZBCCiDG3CGZIojQJbHlVc9choFAwI6K30039Xo4IRbx/VG/FUWrlvaczho5cuxfOv78H7JCkxBpOHzpY6pf0nWupU9tp0b9gl4nU0dFagDldwxcyHUXnYyYZqA02Avm6lqEcazqgeXWkyMgr87TrlQaM7MwtsImlRvPMs3H3chrMtrvcAN6Og1mwMiL5Hy+gayD0835ruyqzuA8WND+gFF3zqEb88qkijkMskq1Ewd9WDHOGVfonIGKyNzMqQRhaCsLEgcyNWn9dk4sqLl+B7XzwPy+bLNx0zmJqYsK5BUjR94UlzkE5ZOGPZdKnKTzrlAQ9X8CrkmPKo1QN7ZqWeG8R3RAYKwoBYcdVe9H41BNDKGQWN7IBWw0UNB5YfKOg4/eoBWeJdpkUBGXGPpqhHXkbBlqtcFDeHxIXmsoFCVNUjk1EwIBFyrnV6IlSpjwLVcEsj02FWUQ2qBZ2Sou1ERSayOlMU/uT0ebjwpNnSInsV7vbhDt4pMWLm6kE1QwzQjhJFPRKugvPGjR6D78DLzysYRyMLkfBKP48S5H5WxLx41KuI8d05qI3h2qgHcaoBmR6NKv6eyRMz0xkF9QVWmbklRj3yNQrBNtsRaxRqEs4omEDhIEfIuZbiQbOfoWEjM46iM5ZEHwUDAxkcc0QbHn9xJwDg6CPlMkTvO+dIAA6OnNGMmR0N0mOpVOISPvSM/xsCf+XN3DOqhYn236lI1KzXyihwfhtxGgWd4ELVudahHiXVRyHpoMd9P7xNp/dCHPXK0wLKzk1KzMx5n8ooaFSLjBsfiLqfq2YUrNB7tm00CgaS0MkohG/4Vap6ROyiU/HFZBQMqoWTl0zDP119CupyGUxvq5eymd5Wjz+/fFlV56VT9eRwhemjMLnQyShQYmaKeqQQKGg4/XGLTFqOsnIFH/WgXyejqCoYducW3hZ7zrR0DWrnzLOpMA6w1qo9RT0iHGyOmFlG26RVulUj28N+D5m05c+f1iiI+yjkTB8FAxJazdN0RGkTrJQkS50gVxOMc2RQTRw5o/lATyEEHR7s4QreKTGBQvXA3sKrImbmrdprOPDxpbjlPoey4bytIzJOnHqTkK4jtlKURnClJ063QLc0S0CjwdmH6sqsQb+O2w4kQ3Ej72m0RgERfRSSzSiYu+pBDp1KFHo3fB2bYB+dWvVxNy4Dg0MNOs2TDldwMwpGzFw1hBelZDLRwWtyBVfFiY5b6U6s6pFORkFRBxA3N6GuQVmYLNx9fG56K/0hmyoIzZVLqgreI+dG7hJkFEgxszqrIrBVC+Lijj/NLHZQgQJLPbLBBdWZOYFnh7mrHuRgrzmZC16vHjadHZBp4qEqZmb3MxoFg8MNvN+JZSXTNOdQA++UGI1C9cA+N2QuSVqjQIqZ4/f3t1Ujo6DhwKlqAXQqmOllFDhjxzrwCdkk7PSL5qGlUSAcbJ6YuaKaUZDJXEi8F3f87HdNCZMZCpWw4RqRUTDlUQ30KEFaegN1p5909GUzCuTUDN3C4HCDqvjvcAa34ZqhHlUNbIZYJnglvw0Z6pGOA6tHV+J9jkYWQiOjENnfQEHkHfWeVqlXDeqRTnClk7mI0hAIRcYiMfN4pFAmMgpyfRREgV/E3BI4/pqIjIIjFDObPgoGBELUIykxM/23aqBQTadfZxwDg0MFOg/wwxW857Ypj1o9pHTu58oahWQcy7jp6WUUOGMnrlFQDxQSq3qkcc4mq/fChKseMdx+QF3MrNNpWyeIZc9Phip1GmyfzM7M5q56kCNMPZJw+kPBhUz7crG9zDhxNxR/HI3MhYHBoQLeypbRJ/ARyqZalrlnVBE692aKelTRrHoU58BqCWZ5Y0ePo7pyr8Np16O38D5H/fiTLnUqstGqyBRznnnvUjacHcoJlUdVrXqkLmYmfndM1SNbSD0yGQUDAhOlEQHqdCVpYbKWmDl4bTIKBocbarMZNNXXUNvM74AP1hEz+oTqQkc/RomZbd2GaxrOaBXEzIkFF4rZAXduUfNKJgsT23tCRwDOpSupZyEm2heCHNHhlUeVWCzVK12r/t2ENAoRVY+EGgUyo2DEzAbhUqdqlSgAIFMljQJlI3mx0lkI8+A3OPwwi2nmZn4HfLCnxegTqgtqEUcyKBM1XFMpNVmd8qg6gUJCwYUOXUlVoxCbUVC30XLgE6IeTVQLEdeZWYeJ4dtG/Ba0hOahjIKORsGImQ0ITFZGgaQe6ZQ6ldc1qNsYGBxKmNVpAgUZhDIKpjRqVaGzWERlFKjyqPH788bl2+isQKuPo9c1mmcj3p/3cZYVI4Dm2VSFRqR2LIBu4Kcxt5jqSuTU/YwCST2S8YEEu6hSj5QzCgIakatR4H8GST0yGgWDEFQboQEaVY800s7yWQh1GwODQwmhQMFoFLhgT0uNoR5VFfW1Gf9Z0VKflbIhr11dMXM1qEdJjZO4AFpnNT2hFXidoCd2HM62pMvQ8mwsiz4eSsw8/j9dHnUC1CPF71NZzCyiHkVoFETBhS5MoHCQQxBQRkKn6pHOSr+ORoEaxzhIBochZnXUU3+bzBofrHMg87A30Ed9bQ2uuugoLJ7big9dsEjKhg4UghVcNTHzJNFo4sbh/A6T7vGgdSzccSNNElvpn6h2QNZGNdsRScHmVD3SYWIAbiAUTQsLb1OlXkVVPRJpFMjgIonnR2bCn2BwQKFzDeh02NThp+roDXTS2wYGhxJmmoyCFNjbgymNWn1cdPIcXHTyHOn9hdQjkUYhIWe0GtV4+A55skGMFo1IwxnXEY0n1s25ChkF9m12DHIeHvWILC0qR7+eeKZDxiYsZiZ8IiqjAEqjsHBWMzbvGsTCWc1oqM1wbXRhAoWDHE31WRxzZBvWbevDGcumS9mwF6pq1aNq9kRIaWghDAwOJbQ00LSOgdHiAZrJ1Ea46pEJFKYaKBEpsV1c9SgZp9eKuRR06DpJBSRxpT5D+0+RjAo/IIk+0VrnmXvOYiolxfk0xJ/edVghG65J+UC8eSUfKEmLmZk+Cl/44HHY0T2MRbNbEi8zbwKFQwDXXnECdnaPYM60Rqn9wyl7tWhalhKkk1EwfRQMDndYloXabBr5YgUAUBj/34AG+xDOZMz9YqpBdAsXb+c5sHFj6NB1ODSSmHF0HHKeTbQwWWc1PamMQqQJ31GODUh440wG9Yj+mydmLpMaBSlWhcZ3EyOy5iGy4VpIoxDsl8umcez8jtjP04FZgjkEkE6lMG96k3aKScZOR2RMfqxOpSQTKBgcrpjRXh+/02EO9rYl013VYHKh2s2WlwnQEQzHC4A5c9JweuMyF6pOrx4lSN1Ga6Vby1HmjVP9PgpR1CMvPrAlxPUkEqNexVxn7PmpicgoUAUCNMTWsjB31sMQotq7UdCiEU2wUpKhHhkcrjCBQjxMedSpD9FtX6xRmCQaTULc+cmoeqQlTJ4kMXd81aNJCkiYtyP398TMVNUjicXShDQKcUUXQgsgVNWjYDvbR0HY58EECgY6sDUCBR1KkFZnZg26koHBoYb5s5oP9BSmPMLlUc3jbKpBRYsg2j+2Y7CGTWLdfxN2yHV48FoZFW52RP1Y4jMqvG3qdJ04DUGITi0hZiY1Crp9FKpDC2PmniJf0xkF22QUDKoGjZqqWk7/BAXQptqLweGK80+cheltdQCAD7/rqAM8m6mJsOjP3C+mGkS3cBH9Qsfp5TmWWiv9cSvq3LHV6UpRzBtVTYM7RjJZiFi9QQLaARkbvQZ60YECCV/MbE+8PKoOxU11hV/kE1Vsh3LlVLN3KjBi5sMQGgkFveZpGsGFoR4ZGAA1mTS+/pnTMTBcREdL7YGezpQEe3cwVY+mHlRXOSetj4IGjUQno6BeHjUpxzqO3qKz0h3eVo0mbUnoJ9hxeWJm5UBhkiheUfuTc6A7nVvCgNJQjwy0oEM9mnB2wIiZDQyUkEmnTJAQgTi6gcGBh8h5EflKWs7oJDm9evX91Wz06C1y22JtpooAWmNu7DCsIJiiHo3/r9qZWSvbpXHOQuOSdGzi88oEdSoqLkyCmWEChcMQOhkFKjugIUzWKY9qHvwGBgayMAsLUw/KYmYtwSjnc2Id5UlyYBWPx7LC8t9qBDCJ9V6oRnChk4WIox5RGQX3fxl+PzWGznnW0GiEx+XbUoFCVJbKZBQMdKBT9YiiBEmm+PXEzHx7AwMDgyiYhYWpB+XyqFxnLHqMJASjMuPwneu4uTGfAXW6jhYlqipi7vC2uFKnOo5yEmVIw9QjIqPgi5kVqx4llFFR1igIMwrB/KOE6IZ6ZKAFjYTCAaEeyWYuDAwMDGSaJhlMLkS3faF2QYt2kkx2IL4DMu9zJubAyowTn1FQn9fkZWGSySiojsM6/uRfjl8eVbEzc0JBj3pGgfSj+PtEXbsmo2CghYlqFHRKncrTldSDCwMDAwOZVUGDyYVopVOlbKpOI7Sq6A00KDEhp1+jus5UpfdI2WiJs8PbVCtfsf5GnJi5eg3XONsSqnok+5kpDp1NFSZQOAyho1FobsgGr+uzEXsG0OmJQO5mqAQGBgayMPeLqYeUwEVJtOqRTjUajk1cGVKeu6Xae0CGCx9VR5+/f/xnyNhUY3Vch3rEDy7UujlHUo/G/6erHsW7wsl1pp4A9Uj4u5H/DB2Y8qiHIbz67Co4dn47zn/HbPQO5vGuU+ZI2VC6Bg0xs8koGBgYyMLcL6YeVKobibbrrNpOxqq13DhqTj9vn9j+BknpOrQyN+rj6GQh4uIrNmALUY9iMgq6nZn1vhvVjEL05wHxAetEF1FMoHAY4ugj2nD6MdPxxlt9+OSlS6RsUikLn5Dc17fR0ShoZCEMDAwMTEZh6kFVzMxd6ddxLCdLAB2buVDbHwhnLqoh/p2MUq8im9jsAKeCkWrTuTD1iMgo+BoF1YZr8XNlwQ1IFbWX5PUvMtWhjanABAqHISzLwufetwyO48T+ACcCLV2DKY9qYGCgAXO/mHoQ+YQqGgUtp1dHo6CzOqw4jpRGQbXqEXelP3kbXsBWHWGy2v4yNuRffqBAlBeVuXdwr82YCpA6xw8AszsbsHP/CADgmCPbqTmkLCukM4377kxGwUAb1QwSAL3sADklk1EwMDCQhWzZZoPJQ3RGISyWS8rp1aEeVaOPwqRUPdJwRpOqFKW1oq4YXOg48ey9gKIegdeZWU+jUK3yqH/xwePwv89vx9IjWjGtlaaKp1KAXYkfh8REfb2q3FnvvfdeLFmyBC+88AL3/ZGREdx8881497vfjeOOOw6nnXYaPv/5z+O1117j7j84OIjvfOc7uPTSS3H88cfjwgsvxDe/+U0MDw9z98/n8/jJT36Cyy67DCeccALOOeccXHfdddi3bx93/0qlgjvvvBMf+MAH8I53vANnnHEGrr32WmzdulXvBBgAAI6eH0TCR81plbKhMwrmwW9gYCCHJDqQGiQL0VeiVvUoboyksgMx43Ad8ri5qc2Lt48WJUhDzK0nzFUTGcuMo9NxPS64IOlc3IZrUmNwtlVJozCjvR5Xv3spzjhmhtRnVlujkLgn9tJLL+HrX/+68P3+/n58+MMfxi233IKRkRGcd955mDFjBh5//HF85CMfwauvvkrtPzw8jI997GP42c9+BsuycP7558OyLNx222248sorMTQ0RO1fKpVwzTXX4Hvf+57/+a2trbj77rvxwQ9+ELt27QrN6brrrsP111+PPXv24JxzzsGcOXPw0EMP4YMf/CDWrVuXzIk5DHHq0dPx91ediK989CQsndcqZdNYVxO8rjUJLwMDAzmY8qhTD+KAQLQ/Z5uGAxuva9AYh1P1SNVRlFsdVx2Ds60aK/0JBSSq4nStkrKK5VGr1XBN5zzHziMhCpjSmBOyZvDwww/j05/+NEZHR4X7/Ou//ivWr1+Pyy67DMuXL8cPf/hD/O53v8OXvvQlFItFXHfdddT+N910E9avX48rrrgCDz30EG6++WY8/PDDeP/7349Nmzbhpptuova/4447sHLlSpx//vl45JFHcPPNN+P3v/89Pve5z6G7uxs33ngjtf8jjzyCe++9F8uWLcOjjz6KH/zgB7jnnntwww03YHR0FF/5yle0OhkbuCsDRx/ZjsVzW6VTXxefOhcLZjXjzGUzsGReW5VnaGBgcKjAaBSmHoQBgeC70irBqUM90qHrMN6SZamXIZXKKChqFJISJsdNbbKoNzp0LXaXcNUjIqMw/j+pUZBpuJZU740JO+0a2bApkVHYs2cPvvSlL+Gv/uqvYNs2Ojs7ufvt2rULDzzwAObOnYtvfvObyGaDevyf/vSnsWzZMoyNjaG3txeASzm6++670djYiC9/+ctIjed+MpkMrr/+erS0tOCee+7xAxPbtnHbbbfBsix89atf9T/fsix88YtfxPz58/H4449jx44d/rg///nPAQBf+cpX0NTU5G+/6qqrcPbZZ2P9+vV4/vnnkzhNBhKYO60R133iFPz55ccYjYKBgYE0TKAw9SByjEXflV7ZzgNjo+P0x2U6APWqR0kd/2QIk2VsQqVOk6AeURkF9/+Ko0g9SigLU42Mgk5mR2nMCVmP46abbsIDDzyAY489FnfddRcWLFjA3e+RRx6B4zj46Ec/SgUJHu699148+uijaG93ue2rV69GPp/HGWecgcbGRmrfhoYGnHnmmcjn81i9ejUAYMOGDdi7dy+WLl2KOXPoWv+pVAoXXnghAGDFihUA3EDk5ZdfRmtrK0455ZTQfC666CJqfwMDAwODqQmzsDD1IFpxF4uceds0VtRjLoUkqDc63XzlnF523LgxeJ+hnoWJF8SGt+lkblTPs1zp0rhAgcgoeNSjiqKYWUs0Lvc5KuCZHxR9FBYsWIBvfetbeN/73uev+vPg8f2PO+44jIyM4KGHHsLatWuRyWRw5pln4qKLLqK+0E2bNgEAjjrqKOG4ALB+/Xqcd9550vtv2LABALB582Y4joOFCxdy583ub2BgYGAwNZExxQ+mHKLEzBXO9iR6FbjbdKg3ijQiLe58rIlycMFfYVabl+hzYm0Ux0lZEj0RQtSr+N816yhLlUdV7KOQFMVLtY9CaB4HIKOQSKDw2c9+Vmq/7du3A3AFzZdffjl27tzpv3fHHXfgzDPPxA9/+EM/e9Dd3Q0A6Orq4n6et72np6cq+0+bNo3a38DAwMBgasKImacelBuu6QhGeSLjKlBCQj0RJBy+ZIKLyVnpr0qlJI3jZ6eh0wwtmnrkBgi2csO1ZOhaEy3jzBszbh4TDU4mtayMV6HoH/7hHzB37lx897vfxVFHHYX169fjhhtuwLPPPovrr78e3/3udwHA1x7U1dVxP6+2tpbaL+n9c7kctV/SyGYz6Opqit/xIMaheHyH4jGxOJSP8VA+Ng+H8jGKjq2rs/GQOe5D5TiaGnPc7SmLf4y8wiEtLXWR52O4ZIe2tbc3RNo0twyEtnV1NaG5IUyJ9tDIHEsmnRJfi+Pb62prqO0yz/yaGtqRrK/PRtrwzllTU22kTT58ytDaWh9p09JcG9rW0R79m2tupn2rTNqKPf6Gevo7yNakY23q62ibpkb6+HMjRf+1ZY3PgfCdO5l7B2+83tESd66R56ylP7ytOfq7iUMmkw5ty+Wir6tsbmKu/qTmaotF98uqqanBf/3Xf+Ed73gHGhsbcfLJJ+PWW29FQ0MDHnzwQb9/QTrtnpC4VJVt25Oyv4GBgYHB1MH7znXpodPa63HykmkHeDYGLESr1FFVj1RX4XVWenkrrKp8c51SpzIru6paCB26FndVOiYjx18dV7ORWU1nbTISmcK474b8k1ceNaMxLyD+ePh0pQlmFHS+74Mpo+Ct6L/3ve9Fc3Mz9V5XVxcuvPBC/P73v8eqVaswf/58f6U/n89zP8/bXl9fDwCJ718oFKj9k0axWMbAwFhVPvtAw4tuu7uHYvY8eHAoHhOLQ/kYD+Vj83AoHyPv2N531hFYdkQr5nQ1ord35EBNLTEcat/f6GiRuz1lWcJjtGD53XMBYGQ4H3k++vrDGf+B/jF0R/ThGRoOP/P7eocxlhXb5MfoFWUHTmhe7PdXKtFKjIptx363pMgWAIqFcqxNyrJgE5mFsbFi9DnrC5+zocHo8zw8XAhtGxwYQ3e3+JyNMDYW4q/tQp4+z7YdPs8sisUy9Xc+X6JsRvPB+5XxzysS301//wgyjh35+xvoD/tqBWYcFiOc62x0pDCh37fNySCVy5XIz6xMcLF7UgMFr5rR7Nmzue972/v6+gAEGoH9+/dz92c1Bknv73VyFmkYDAwMDAwOHFKWJd313WDyIVrIjKrSkkoBNuFfV6PhGNdGUQugI4CVK6nK/i25ok74j1Upj6rVR0BtDN44OrqOSI3C+P+qVY+SalI30QpEB0KjMKnUo8WLFwMIHHAWniPf0dEBIKhe5FUzYrF582YAwJIlS6jPj9vf22/RokVIpVL+dhZbtmyh9jcwMDAwMDCQg1DMHOG4sDbxXZZ1aEQTF0BLOf2TFlwkQVeKm1f8uHHjSDn9LF1J4/hlxMzKnZm1yqOq28TOQycwngp9FGTxzne+EwCwfPlylMt0qqhYLPqNzU4++WQAwKmnnora2lo8++yzIUHxyMgInn32WdTX1/v7L1y4ELNnz8a6deuwe/duan/btvHYY4/Bsiyce+65AODb9vT04MUXXwzNd/ny5QCA8847b6KHbmBgYGBgcFhB5J9EOS6qdfT5FXzi5jVxjYJcoCDmysva6GghqtExOIkshJauQ8aJjwlIqMpYmuVR9Y4/vG3CDdcS0qQojTkha0WcddZZWLp0KbZt24ZvfOMbqFTc/KJt2/j2t7+Nt99+G2effbbfv6C+vh4f+MAHMDAwgBtuuMEPLsrlMm688UYMDg7iyiuvpJqxXXXVVahUKvjHf/xHKrj4/ve/j23btuHiiy/GvHnz/O0f+chHAAA33HCD3xEaAO666y4888wzWLZsGU4//fTqnRQDAwMDA4NDEOKMQpQNu2+MM8bbVoWGY6qr9u44rI2EaJb5WEvCS1MOrhJalY4NyGJW+rk2VaYe2X6gYAv350Ero6IRkMXOg2MfF7NOiT4Kskin0/je976HT37yk/jlL3+JJ554AkcffTQ2bNiA7du3Y+bMmbjxxhspm2uvvRbPP/887r//fqxZswbHHHMM1q1bhx3/f3t3Hh/T9f4B/DPZN6QiscUSVJSgscQudopYaytaW1Fb+VpaLaXoQlUJWpSiqGhS+9LEvoS2lii1xF5BEyGyi2zz+yO/GTNzb5J7b2Ymyfi8X6++msycO/eemSTOc895nhMVhTp16mDixIl67YcNG4Zjx44hPDwcnTp1QoMGDXD37l3cuHEDFStWxOzZs/Xad+3aFWFhYThw4AC6dOkCPz8/xMTE4NKlSyhZsiQWLlxo8veFiIjI0ojuIqvKu9Kg3IGiaDUamYN+SQNFKBnA5v296HmUXJvhcq18lxHJvyutbJM2ee3FziNl6ZFhMJXXzsyaKQX9fRQUVj0ywbK4fK9DSZWv4jSjAOQsD9q5cyeGDh0KADh+/DgyMzMxePBgBAcHw9PTU6+9q6srgoKCMHToUGRmZuLo0aOwsrLCqFGjsHHjRjg7O+u1t7Ozw7p16zBu3Dg4Ojri6NGjSElJwYABAxAUFKRNYNa1ePFizJw5Ex4eHjh+/DhiYmLQrVs3BAcH57rLMxEREeVObEAqewdkJYNemXfU87smsdeUtOGaglkIw0GZklwIkySAi4wW8xtgK1p6pOQ9y2/pke7KI82MQlbBlx4pSZo3RTKzqXMUTDKjsGnTpjyfL1OmDGbNmoVZs2ZJej1XV1dZ7R0dHfHhhx/iww8/lNTexsYGw4YNw7BhwyS1JyIioryZY4mP+KyFvDu9UkrbC/MA8j9G0R11JQGJ7KVH5plREM6OyF96pWTvBcPz6C89UiM7+2UBXpXI8eLXJX/myhRLj5RU7Cp2MwpERERk+YxRkUhJZRm5A2VFa+cVJTPLH/QrCi5MkJgsNuiVm8yrqOqRkgTofJKZ5VY8EjtHzrHyZlQAI5QqFc1RkP95yzpngY4mIiIiEqGkDKfsZTSKKvjIO4fYMUpyB6QFJAbfK6l6JHN5FyChDK3YYzIHqIpyQZQEZHktPYJ+IrPUO/zG+DmTc77cKAmMHfPYfFAKBgpERERkdMaova+ogk++A2X5d+0NB9L5DazFrkNKLoSifRSMkQBugmMU5RsYoVJS3snMQKbMzdbEziHl2pQM6vMjnqOQ9zFt3qwIeztrxec0a9UjIiIiejUoqfkud7mO+PKmfK5LQR6AsmVE+t9LGvQqSubN+zXya5/bY7qMsUmdkhkVJZuhiZ1HBd1dmeWVRgWMk2+T22NyiJepzfs1K3m4oEwZlzzb5HlOxUcSERER5UJsDwC5VY/yu3OvbEbBoL2kJTH6lA368z1E0XnkzkIoGvQbIUehMAMl3T5nyqx4lNtrKimPaooN16TMbkmZzcr1nIqPJCIiIsqFOXbzNcadbkkzCoJZiHwPKbzz5DejYqSqR3I3+jLVPgqCGQWRWQjdl8nUnVGQmMysqDyqyOdQ8BwFkdcsYLJyfhgoEBERkdGJD+LzOUbmQFlZfXsFd/oFd63zP0jRzIVhXoOC/Il8y3aKDTZlDnqtVCrZ1XZMN6OQf/9zDRSkzigoyVEQzA8ZYUZBwcxGQTFQICIiIqMTG77kP7g0/N4MS48U5Sjke4jCXAj97yXdUZcZkKhUwiGs/OBKftBjjFKnUs4jfm3iS4+kBHxi15X7efJ+vqAzCqLJzJxRICIiouLGKMuCZA7GFO2JYLTBqOExBuc10XmU9EduEKOo1KvhLISS2QElycwi+xvoNsnUKY9qY+byqAXeR0E0R6FAL5n/OU378kRERPQqEl2jbeREY8NnpZUglXcOsTZmG8ArCUhMUJFJ7qyF2HWYamM7SX3ReShLSTKzkcqjmmIfBc4oEBERUbGjZFAjd3CtUqn0BopSVpII7kBLGYwavoaCPRGULL0xxT4KosfILPVpspkbg8/PWMGF7meRkSV/wzVjLT3Kbzfn/Ij9fDNHgYiIiIod0Xr9+SUzF3DDMSVr2iVtnmaEsp1SZjsU7Was6C68zCVeigb9hn3Jf8hpjFkYseVKuk2yFFQ9EsvryC/AFF16xBwFIiIiIqX1+g2+lznoVZIwrGR5i6LBuITxnGAfCUnlQQ2/V3JMPtelaEZB/3tluyxLCS6knOflY0p2ZgbkB4tKytDmew0K91Eo0DlN+upERET0ShLdIdcUSbM6TaTlKBhjGU2+hxhluY7xqv4YHGNwfzz/JWF5fy9+jBFmB4y0xEkvmVlBeVRA/s+N2M9iQWcUxIICE8cJDBSIiIjI+JwdbAWPyc9RyP88uoMnZWvaJZzDGPkGipY45X9tBS3dqlJJKVtrjKVH5nnP8juP0kBB7syNKcqjiidVm3Yoz0CBiIiIjM7ZwUbwmNyqR9LW9et8bbLBqOE5jXOnW3htSvIN9L+XOyBXtGO00ZYEGR5jjFkY4bXpvq+ZCqoeGb6GlGNNkaMgvpypQC+Z/zlN+/JERET0KnJ2FJlRyGfUUdAKPnLvpks9h6IdkxUlZht8b6KSogVNADdV1SMlS4+kVErKLZlZzh1+2RW5RJfeST6dKNHlfMxRICIiouLGwc5aQblTna+hIJnZVAN4g+9NsWMyYJwZBbmzKpKqPglyFAov30DRMXrlUXVmFGSUK5U7QyI2OyJlhiwvYpurseoRERERFTsqlQrOjjaCx/KiO8iTerdXb+mRqe7aG2EWwmR7Iigp3aqb12GmQb/5KiXlfSdfd0ZB6s7MgJKqR3kfr4SSjd8KfE6TvjoRERG9slwMlh/ln6MgP1Awx4yCokG/ouAi79cw1rXpVj0y1S7TxknmNs6yKN1HMhUuPSpo1SNTBQrGeN08z2nSVyciIqJXlmHlIzm156UuqdBLzC3M5S15XBcg8e64uZbrWOl+baLZAUFf8h9yCgfjEpKmJVQjMkYys3C2I+9rE7xnRlgilN9siSkwUCAiIiKTMKx8JKfqkeSlR1bygouCrunPOUbCdRkmQEvojrKN3ZQco/ue5X9dijZ1M0JAZoqlR5nZujszm3DDNQXvWX7E8kkc7ITVxYyJgQIRERGZhGHlIzlVj6SOq/SW0ShZEiRpoKxkuZL+90oGvVKCC0WbwRWw6pGk90zJ3hOKdpnW//zF8mB0f0YyM3VmFGTcjjfcpE7u0iNj5BI42FnrfV+9Qkn4eJUu8OvmxbRhCBEREb2yBEuPZMwoSB1YyV9Go/+9yTYCM0IuhJJrk3uMtL0qlCw9kn9dBZ1RyO1zyX1GQcbSI5l7aSjJt8hPI28PHL/4COkZWXiraRX4169g8hwFBgpERERkEoKqR/ku13j5vNT68PrJzPLaAwqrEZmqgpGSgMSgjaSBv8zqUsJASX6+gemWHuXfPreqR/JyFGTOKBh8b4wZhddK2GP+SL8Cl1mVg0uPiIiIyCQKVPVI4mBIbgK0YHmPkSrrCI4prN2cpRyjM4yVuvRI7myPMRKgZZd6zTVQ0Fl6pJPMLGvDNZnXZvieGevOvzmDBICBAhEREZmI4dKj/Depkt5WQ+4AVlnugOFrmGjQryAXQvcQldRjdJdrKQnIzLAkSvoxEpYe6XydqXBGoaC7U5t6vwNTYaBAREREJiHccC3v9krKo+otV5KYB6DbStE+Ciar+qP/vbHW6BtSsl+F/OVK8u+oF7RSktwZhYLszCwp0Vzme1YUMVAgIiIik5C7j4Jekq3UQa/MzcNyziPvGCX7GygpWyqsemScO+p5nUfJjILkRHOZxyh6n3VGsrklJ+slMxshR8HaSry6Ul7nNcY+CoWBgQIRERGZhKA8an6VYpQMRnUHikoqJSnaq0DCORRVMFKyvCX3c0o6xkTvmeFrm2VGJZfr0p9RULj0SMHsgJLZnqKGgQIRERGZhIvs8qi6gz5p51CSAC23UpIxEqClBRcG38vMa1A2oyLpENkJ0IBh4Cdhl2WTLT16+bUxdmZWEijIKcValDBQICIiIpNwtNffICpLrc6lZQ65eyIAyu7aFjgxV2bCsPTzFCy4kDru1UsaVzQ7IO08sislKVh6pNsmt5wD3VcxRnlUqe8Zlx4RERER5cJw4Jv6PENye0XLaCTPQugeY5okW0UJ0ErKgypYrqUsr0H3uqQNH+UHZPL7X87NCaVL2gNArrsUGyOZWdHSIwtIZuaGa0RERGQWqWmZeT6vqIJPQdeOm6vqkaJcCHnXJjUBXG6lKMPXVjILoaQMrZTlSjbWVpg3ogkexCajhmcp0Ta6L6u3M3MBkplNdUxRw0CBiIiIzCIlLb8ZhZdfSx70635tor0XBLkDSgb9ZigPKj1H4+XXSga9SmYhpFUwkr/0CACcHGxQs5Jr7q+rO6OQ+TJQkLXhmpKfTb0gtngu4imeV01ERETFTko+S4+UDXoVLFfSvaOuZCM0c80oyMyfMO2gX8ESJ9lVj+S/z5KuQ+dllCYzq5T0X8FnU9QwUCAiIiKzyC9QUFL1SO+urYLgQm4JTqnnUbLLsO7rqiSep6D9lx5ciZ8zz2MK+D4ba3CtFyjoLT2SseEay6MSERERGZfuYCldZ9mHaFsFeyIoWq6ke4ykZGaD76WUVDU4SG5JVSXLqJQlJisILkw0UDZ8X40XKLx8nSzFMwryr4uBAhEREVEeDEuk5kVRYq6iwbW8mQth2VJ5g35AannQ3I/P9ZiC9t+US4/k5iiYaumRztcZuuVRZextUNClV1x6RERERGSgf9sa2q/f7fpGnm2V1apXsFxJ7p1uRTsmGwYX+V+XsnXwBcvRULbES9oxlTxcAACO9jYoXcIh/3OYLEdBd0ah4FWPTDVzVRSx6hERERGZTIt65ZGSlom09Ex0b1ktz7bmW0Yj7xjDMZ60ZUT638vdr0Hq8nn93AFpxyhbRqN7HmnHDOnkjarlS6J21ddgb5f/zJK1lQr2ttZ4kZEFR3sbow2ujbIzs4LZAZZHJSIiIsqDlUqFLk0qA8i5s5xfW7Gv81LgO+oKNkKTtDOzok3acj8+12OgoP+KNrbTHfRKi0heK2GPgOZVJbUFct6j3q28cPDcA+3PjDHk1kM5ycxKglglS7yKGgYKREREVCQomlFQUI1GbnBR0LKlUo9RtLxFwZ1u3WuTmguiZGM7JTr5VUYnP+MFCUDu+R6KcxQkB1c65yqmgQJzFIiIiKhIUDbof/m1omU0SmYHZJYtFfteTEGrHinZmflVWEaT28clZ2mTop9NMwVXpsRAgYiIiIoERcuIdCslKVpGI28AD8gf9BueM9fr0s03UNIXUy5XUrCPQlFhnBkFneNegeBKg4ECERERFQn6CbPSjtFf1y/1GJ3gQsl5pOyjYHAtcgMSk+4joWDQr+TaijqlOzNbSfzhLM7BlQYDBSIiIioSFCXZKlpGI35OY16bouVKZip1WtCZm+JW6jO390VpeVQlpWuLa3DFQIGIiIiKBEV31HWX0ZhwIyy5+QOG+QJyZyEkJxnr9V/inW4F73NxTszNdemRjKpHSmYHinNwpcFAgYiIiIoEJQNlZev6FRwj8zyGAyy5wYXkAbySzdP03meJx+gcJPWYIiO3GQWFVY+U7PFR3IIrjeL2URMREZGFcnGy1X5dwtE2j5YvKakUpGTQJ3e2Q1D1SGZwIX0ZUe7nzPWYAlc9Kl7Dx9zeezl5A0pmu5RUSipquI8CERERFQkNa3ogwvsJ0l5konX9CpKOKfAmbQoGytJ2ZtatxiStIpOSgaWiO92Kqh4V/2U0hmwU5igo+TmTM3tRlDBQICIioiLB3s4a43vXlXWMfqUkBZWCFC1XktteQQBjwk29VAqWa7m62Gm/fq2EvaRjiorc+ihrZ2adpopmYYppcMVAgYiIiIqtquVLAhcfAQC8ypeUdIydrbXO19IGiyqZS2+ULFWxtbES/TrP8yi4069kFuKtplWQkQ1ULlsCXuVLSDqmqJOzHKigOQpcekRERERkZs19ysHBzhrOjraoVkFaoOBfvwJuPUiAp4czqlcoJekYBztrJD/PgEoF2EsILvSTf6UNEqv8/yD8fkwyWtYrL+kYJRvO6S6DsbGWFpCUfc0JnwzzAwDExiZJOqaoyO1tUZrM/CqVR2WgQERERMWWjbUV/N4oK+uYRrU8UL+GG2ysrSQPrrs3r4qQY7fRom45ODnkn2htZ2MFG2srZGZlw0VCeyAnuJj1biM8f5Ep6RwA4OrychmQ1CVBDV53x8GzUbBSqVC/hpukY4ozsZkWlUperoVKSXlUJjMTERERFT+2Ntb5N9LRun4FtKpXXnJgYWdrjb7+1XDy0n/o3qyK5POoVCrJQQIA+HiVRme/SkhITkf7hp6SjqlesRQWj28BGyt55yq2RD4yuXf4C7r3BAMFIiIiIgsmNUjQ6OxXGZ39KpvoanJYWakwoN3rso8r6WSXfyMLIfa5yS3xqqhSloIytEVN8SqES0REREQkg9gQXf6MgvxjSzi+DMaKa2DGGQUiIiIislhiE0FylwJ5vOao/drd1TGPli91aOSJ/+JS4FbSAbWrlpZ1vqKCgQIRERERWSyxpGW5G6A1ruWB2Pg0ZGer0bS2tOT5sqWdMG2gr6zzFDUMFIiIiIjIconEBHJ2ZQZykt97tvQy0gUVH8xRICIiIiKLpRKJFIprFSJzY6BARERERBZLLEdBbtWjVxXfJSIiIiKyWKKBgswchVcVAwUiIiIislhiS4+sZe6J8apioEBEREREFoszCsoxUCAiIiIii2WMnZlfVXyXiIiIiMhiGWPDtVcVAwUiIiIisljiMwoMFKRgoEBEREREFkssJGCOgjQmCRS2b98Ob29vnDt3TlL7UaNGwdvbG3/++afo84mJifjmm2/QuXNn1KtXD+3atcPXX3+N5ORk0fZpaWlYvXo1unXrhvr166Nly5aYNWsWHj9+LNo+KysLQUFB6NWrF3x9fdG0aVNMmTIFd+/eldZhIiIiIiqSRJOZWfVIEqMHChEREZg/f77k9r/88gtOnjyZ6/PJyckYMmQI1q5dC5VKhTZt2kClUmH9+vUYMGAAkpKS9NpnZGRg3LhxWLJkCVJSUuDv7w9XV1cEBwejT58+ePTokeAcs2bNwpw5cxAdHY2WLVvC09MT+/fvR58+fXD16lXpnSciIiKiIkV06ZE1F9VIYdR3KTQ0FCNHjkRqaqqk9v/++y+++eabPNssXboUkZGR6N+/P/bv34/AwECEhoaiZ8+euHXrFpYuXarXfvPmzQgPD0ebNm0QFhaGwMBA7NmzB2PGjEFsbCzmzZun1z4sLAzbt29HnTp1cPDgQSxfvhwhISH4/PPPkZqaio8//hhqtVrW+0BERERERYPo0iPmKEhilEAhOjoaM2bMwKRJk5CdnY0yZcrke0xWVhY++ugj2NraombNmqJtEhMTERwcDBcXF3z00Uew+v9SVjY2NpgzZw5KlSqFkJAQbWCSnZ2N9evXQ6VSYfbs2bCzswOQE0lOnjwZXl5eOHr0KKKiorTn+OmnnwAAH3/8MUqUKKF9fODAgWjRogUiIyNzXRJFREREREUbk5mVM0qgsHTpUuzatQs+Pj7Ytm0bqlWrlu8xa9euRUREBGbPng03NzfRNmfPnkVaWhqaNm0KFxcXveecnZ3RrFkzpKWl4ezZswCAGzduICYmBrVq1YKnp6deeysrK7Rr1w4AcOLECQA5gcjFixfh6uqKRo0aCc7fvn17vfZEREREVLyI5igwUJDEKIFCtWrVsHDhQgQHB8Pb2zvf9tevX8fy5cvRuXNnBAQE5Nru1q1bAIDXX3891/MCQGRkpKz2N27cAADcvn0barUa1atX185W5NWeiIiIiIoX7sysnI0xXmT06NGS26anp2P69OkoWbIk5s6dm2fb2NhYAIC7u7vo85rHnz59apL2Hh4eeu2Nzc7OBu7uJfJvWIxZYv8ssU+GLLmPltw3DUvuoyX3TYN9LN4suW8axa2PTk72gsecnexF+1Hc+mZqRgkU5Fi2bBlu3LiBlStXonTp0nm21eQeODo6ij7v4OCg187Y7e3t7fXaEREREVHxIrbKiDMK0pg1UDh//jx++ukn9OjRAx06dMi3vbW1NQDxJBRd2dnZZmlvbOnpmUhIeG6S1y5smog8NjYpn5bFhyX2yZAl99GS+6ZhyX205L5psI/FmyX3TaO49vH58wzBY+kvMvX6UVz7JkVBZknMVkRWU2rU3d0ds2fPlnSM5k5/Wlqa6POax52cnEzS/sWLF3rtiYiIiKh4YTKzcmabUdi6dSvu378Pb29vwV4GmiTkVatWITg4GAMHDkSjRo20OQJPnjwRfU3DHANjt9fs5JxbDgMRERERFW1MZlbObIGCZp1/ZGSktkqRodOnTwMAmjdvjkaNGmmrF2kCCUO3b98GAG2lJc1+DPm117SrUaMGrKystI8bunPnjl57IiIiIipuxPZR4M7MUpjtXZo4caI2SDD8r1mzZgCAn3/+GZGRkejTpw8AoHHjxnBwcMCZM2cECcUpKSk4c+YMnJyc0LBhQwBA9erVUbFiRVy9ehX//fefXvvs7GwcOXIEKpUKrVq1AgDtsU+fPsWFCxcE13zo0CEAgL+/v3HfDCIiIiIyC7FVRlZceiRJkQ6nnJyc0KtXLyQkJODzzz9HZmYmACAzMxPz5s1DYmIiBgwYoLcZ28CBA5GVlYVPP/1UL7hYtmwZ7t27h44dO6Jy5crax9955x0AwOeff464uDjt49u2bcPp06dRp04dNGnSxNRdJSIiIiITECtaY8NAQRKzl0eVa8qUKfjzzz+xc+dOnD9/HrVr18bVq1cRFRWFOnXqYOLEiXrthw0bhmPHjiE8PBydOnVCgwYNcPfuXdy4cQMVK1YUJFJ37doVYWFhOHDgALp06QI/Pz/ExMTg0qVLKFmyJBYuXGjO7hIRERGREYmFBExmlqZIzygAgKurK4KCgjB06FBkZmbi6NGjsLKywqhRo7Bx40Y4Ozvrtbezs8O6deswbtw4ODo64ujRo0hJScGAAQMQFBSkTWDWtXjxYsycORMeHh44fvw4YmJi0K1bNwQHB+e6yzMRERERFX1iycxceiSNSq1Wqwv7Il5V3EeheLHEPhmy5D5act80LLmPltw3DfaxeLPkvmkU1z7uOX0PO07c0XtsaGdvtPWtqP2+uPZNimKxjwIRERERkbmJ7szMGQVJGCgQERER0SuFgYI0DBSIiIiIyGJZiSQpMFCQhoECEREREVkssfKo1tYcAkvBd4mIiIiIXiliswwkxECBiIiIiCyWaDKzNQMFKRgoEBEREZHl4s7MijFQICIiIiKLxQ3XlGOgQEREREQWi1WPlGOgQERERESvFFY9kobvEhERERFZLO7MrBwDBSIiIiKyXFx6pBgDBSIiIiKyWGLJzAwUpGGgQEREREQWSywkYNUjaRgoEBEREZHFUoktPWIysyR8l4iIiIjIYoktPeKGa9IwUCAiIiIii6USWXzEpUfSMFAgIiIiIovFZGblGCgQERERkcUSDxQ4BJaC7xIRERERWSzRZGbOKEjCQIGIiIiILJZYSGBtzUBBCgYKRERERGSxxGYUmMwsDQMFIiIiIrJYhnGCSgVYiSUukAADBSIiIiKyWIYzCkxklo7vFBERERFZLMO5A+YnSMdAgYiIiIgsluEqI2suO5KMgQIRERERWSzB0iPOKEjGQIGIiIiILJZgRoEVjyRjoEBEREREFksFw2RmBgpSMVAgIiIiIoslnFHg8FcqvlNEREREZLEEgQJzFCRjoEBEREREFsswmZm7MkvHQIGIiIiILJZgHwUGCpIxUCAiIiIii8WdmZXjO0VEREREFovlUZVjoEBEREREFotLj5RjoEBEREREFos7MyvHQIGIiIiILJbh0iNWPZKOgQIRERERWSzDGQUbJjNLxneKiIiIiCwWk5mVY6BARERERBZLBW64phQDBSIiIiKyWIIZBSYzS8ZAgYiIiIgsF5ceKcZAgYiIiIgslpVgZ2YGClIxUCAiIiKiV4Y1qx5JxneKiIiIiCwWZxSUY6BARERERBaLG64px0CBiIiIiF4ZrHokHQMFIiIiIrJYwqVHHP5KxXeKiIiIiCwXy6MqxkCBiIiIiCyWisnMijFQICIiIiKLZRgXMEdBOgYKRERERPTKsDYsg0S5YqBARERERBZLkMxszeGvVHyniIiIiMhyMZlZMQYKRERERGSxDJOZueGadAwUiIiIiMhiGYYFnFGQjoECEREREVksw9xlVj2SjoECEREREVks7sysHN8pIiIiInplcOmRdAwUiIiIiMhicWdm5RgoEBEREZHFEuQoMFCQjIECEREREVkszigox0CBiIiIiCyWsOoRh79S8Z0iIiIiIotlOH/ADdekY6BARERERBaLS4+UY6BARERERBaLyczKMVAgIiIiIoulAmcUlGKgQEREREQWi8nMyvGdIiIiIiKLxaVHypkkUNi+fTu8vb1x7tw50eePHz+OkSNHws/PDz4+Pmjbti0+++wzREdHi7aPiYnBZ599hvbt26NevXro3LkzVq5cifT0dNH2iYmJ+Oabb9C5c2fUq1cP7dq1w9dff43k5GTR9mlpaVi9ejW6deuG+vXro2XLlpg1axYeP36s7A0gIiIioiKByczKGT1QiIiIwPz583N9fs2aNRg9ejROnz4NLy8vtG7dGgCwbds29O7dG7dv39ZrHx0djf79+2Pbtm0oWbIk2rRpg5SUFAQGBmLkyJHIyMjQa5+cnIwhQ4Zg7dq1UKlUaNOmDVQqFdavX48BAwYgKSlJr31GRgbGjRuHJUuWICUlBf7+/nB1dUVwcDD69OmDR48eGemdISIiIiJzMwwLGChIZ9RAITQ0FCNHjkRqaqro87du3cJ3330HJycn/PLLL9i2bRu+//57hIWF4Z133kFcXBw++eQTvWPmzp2L6OhofPjhh9ixYwcCAwMRFhaG5s2b46+//sKmTZv02i9duhSRkZHo378/9u/fj8DAQISGhqJnz564desWli5dqtd+8+bNCA8PR5s2bRAWFobAwEDs2bMHY8aMQWxsLObNm2fMt4iIiIiIzEgwo8AcBcmM8k5FR0djxowZmDRpErKzs1GmTBnRdrt27UJ2djaGDx8OX19f7eO2trb45JNPULp0aVy8eBEPHz4EANy5cwfHjh1D5cqVMXbsWG17JycnfPHFF7C2tsbmzZu1jycmJiI4OBguLi746KOPYGWV0z0bGxvMmTMHpUqVQkhIiDaQyc7Oxvr166FSqTB79mzY2dkByPmBmjx5Mry8vHD06FFERUUZ420iIiIiIjMzzFGwMnyAcmWUQGHp0qXYtWsXfHx8sG3bNlSrVk20na2tLby9vdG4cWPR5zw9PQFAmxtw6tQpqNVqtG3bVjvo16hQoQJq166Nhw8f4tatWwCAs2fPIi0tDU2bNoWLi4tee2dnZzRr1gxpaWk4e/YsAODGjRuIiYlBrVq1tOfWsLKyQrt27QAAJ06ckPuWEBEREVERIKx6xEBBKqMECtWqVcPChQsRHBwMb2/vXNtNmjQJu3fvRrNmzQTPpaamagf85cqVAwDt96+//nqu5wVyBvxy2kdGRip6fSIiIiIqXriPgnI2xniR0aNHF/g1fvzxR6SmpqJu3booX748gJczCx4eHqLHuLu7AwCePHkCAIiNjdV7PLf2T58+VdTe2OzsbODuXsIkr11UWGL/LLFPhiy5j5bcNw1L7qMl902DfSzeLLlvGsWtj2q1GjbWKmRm5fy/XNmSgrwFjeLWN1MrEtkcx48fx+rVq2FlZYXp06drH3/+/DkAwMHBQfQ4zeOanAPN/x0dHU3SnoiIiIiKF5VKhW4tqsFKBXRt4ZVrkEBCRplRKIhjx45h0qRJyMrKwtSpU9GkSRPtc9bW1gCE2eqGsrOzzdLe2NLTM5GQ8Nwkr13YNBF5bGxSPi2LD0vskyFL7qMl903DkvtoyX3TYB+LN0vum0Zx7mPP5lXQuVFFONjZiF5/ce5bfgoyS1KoMwohISEYP348Xrx4gQkTJgiWMGnu9KelpYker3ncycnJLO2JiIiIqHhysCv0++PFTqG9Y9999x1WrVoFlUqFmTNnYtiwYYI2mtwETQ6CIU2Ogaad1Paa3AO57YmIiIiIXhVmDxTUajVmzZqFkJAQ2NnZYeHChejatatoW001Ik11IkOaXZxr1qwpq72mMpPmOKmvT0RERET0qjD70qOvv/4aISEhcHFxwbp163INEgCgVatWAICjR48K8gQePXqEa9euoWLFiqhRowYAoHHjxnBwcMCZM2cECcgpKSk4c+YMnJyc0LBhQwBA9erVUbFiRVy9ehX//fefXvvs7GwcOXIEKpVKex1ERERERK8KswYKJ06cwIYNG2BjY4PVq1fDz88vz/aVKlVCq1atcOfOHSxbtkz7eGpqKmbNmoWsrCwMHz5c+7iTkxN69eqFhIQEfP7558jMzAQAZGZmYt68eUhMTMSAAQP0NmMbOHAgsrKy8Omnn+oFF8uWLcO9e/fQsWNHVK5c2VhvARERERFRsWDWpUeBgYEAADc3NwQFBSEoKEi03QcffIDq1asDAObMmYNBgwZh1apVOHLkCLy8vHDhwgXExsaidevWGDRokN6xU6ZMwZ9//omdO3fi/PnzqF27Nq5evYqoqCjUqVMHEydO1Gs/bNgwHDt2DOHh4ejUqRMaNGiAu3fv4saNG6hYsSJmz55tgneCiIiIiKhoM1ugEB8fj8uXLwMAYmJisGfPnlzb9uvXTxsoVKpUCcHBwQgMDMSJEyfw77//olKlSnj33Xfx3nvvwcZGvwuurq4ICgrCihUrcOjQIRw9ehTly5fHqFGjMHbsWDg7O+u1t7Ozw7p167BmzRrs3bsXR48ehbu7OwYMGIAJEybkutkbEREREZElU6nVanVhX8SrivsoFC+W2CdDltxHS+6bhiX30ZL7psE+Fm+W3DcNS+7jq9A3JYrEzsxERERERFS0MFAgIiIiIiIBBgpERERERCTAQIGIiIiIiAQYKBARERERkQADBSIiIiIiEmCgQEREREREAgwUiIiIiIhIgBuuFaLsbDUyM7MK+zJMws4uZ8fs9PTMQr4S47HEPhmy5D5act80LLmPltw3DfaxeLPkvmlYch9fhb4pwUCBiIiIiIgEuPSIiIiIiIgEGCgQEREREZEAAwUiIiIiIhJgoEBERERERAIMFIiIiIiISICBAhERERERCTBQICIiIiIiAQYKREREREQkwECBiIiIiIgEGCgQEREREZEAAwUiIiIiIhJgoEBERERERAIMFIiIiIiISICBAhERERERCTBQICIiIiIiAQYKREREREQkwECBiIiIiIgEGCgQEREREZEAAwUiIiKiQqJWqwv7EohyxUDByIYOHQpvb29s3769sC+lQP788094e3tL+k9pX729vVG7dm0jX3nutm/frr3mli1bIjs7O8/2oaGh2vYff/yxma7SNG7cuKHty5o1awr7cmR5lT83XZbyt0WKgvZV8/dr2LBhxr0wGYrz71xenj17hqVLl6J3795o1KgR6tatizZt2mDy5Mk4duxYYV+eUWVlZWHnzp0YM2YMWrZsCR8fHzRq1AgDBw7E2rVrkZSUVOBzhIeHY9SoUUa42vxp/pb6+vriwYMHebatXbs2vL29zXJdxpDbmKV27dpo0KABunXrhvnz5+P27duFfanFjk1hXwAVbU5OTmjfvn2ebSpXrmymqzGe2NhYnD9/Ho0bN861zf79+814RaalGXDZ29sjODgY77//PlQqVSFflXyv2udGxZel/M7p+ueffzBixAgkJCSgYsWKePPNN+Hg4IBHjx7h999/x4EDBxAQEIBFixbByqp434eMiorCuHHjcOPGDVhbW6Nu3bpo0KABnj59iqtXryIiIgIbNmxAYGAgGjRooOgcMTExGDFiBCpWrGjkq89bamoqZs+ejfXr15v1vOZgOGbJyspCUlISrl+/js2bN+PXX3/FvHnz0Lt370K8yuKFgQLl6bXXXsPixYsL+zKMqmTJkkhMTERoaGiuA87U1FQcP34ctra2yMjIMPMVGldmZiZ2796NcuXKoXHjxtizZw9Onz6NFi1aFPalyfKqfW5UfFnK75yuzMxMfPjhh0hMTMSCBQvQt29fQZjc7AAAK8ZJREFUvWDg+vXrGDNmDPbs2QMfH59Cnc0pqJiYGAwcOBBPnjxB165d8fHHH6Ns2bLa55OSkrB27VqsXr0a7777LtatW4cmTZrIPk9hLjk6ffo0goOD0a9fv0K7BlPIbcyiVqsRFBSEBQsWYNasWShXrhyaNWtWCFdY/BTvkJ9IgZYtW8Le3h5hYWG5/qE+evQonj9/jlatWpn56ozv2LFjePr0KZo3b4633noLALBt27ZCvir5XrXPjYovS/md03X+/Hk8ePAAzZs3R79+/QQzBrVq1cKcOXMAAL/++mthXKLRfPTRR3jy5AkGDRqE7777Ti9IAIASJUpgypQpmD17NjIyMjBz5kwkJycX0tXKV65cOQDAwoULERMTU8hXYx4qlQqDBg3C5MmTkZmZiYULFzI3RCIGCmbw/PlzrF27Fv3790fjxo3h4+ODFi1aYMKECbh06ZJeW806u4ULF+LmzZsYN24c/Pz8UL9+fQwcOBCHDh0qpF5Ic/v2bUyfPl27nrNdu3ZYsGABnj59musxT548wUcffYQmTZrA19cXQ4cOxfHjx012jU5OTmjdujViYmIQEREh2mb//v1wcnJCmzZtBM9lZmYiKCgIQ4cORZMmTVCnTh00adIEI0eOxMmTJ/Xa6n6e69evR9OmTfHmm29i7NixpuiaqB07dgAAOnfujNatW8PV1RWHDx9GbGysoG27du3QqFEjpKamYt68eWjevDl8fX3Rr18/7N27V9Bes5b85s2bGDx4MHx8fNC6dWvB+2AM5vrcnjx5gjp16sDX1xfPnz8XvE5GRgaaNWsGX19fpKamGq1/ci1fvhze3t74/vvvBc+dO3cO3t7eGDp0qPaxBw8ewNvbG5MmTcJ///2H6dOno1mzZqhXrx569eqF4OBgc16+LHL7Wtjk/M7llas1bNgweHt7488//9R7PDU1FStWrEDnzp1Rr149tG/fHitWrEBUVJTJcnM0f8PzWj7VvHlzdO/eXTBzkpCQgG+++QadOnVC3bp10bRpU0yaNAnXr18XvIbmb0pcXByWLVsGf39/1K9fHwEBAdiyZUu+OUoF9ffff+PMmTMoXbo0Zs6cmWfbwYMHw9fXFw8fPsSuXbv0njt9+jTGjh2r/Rvas2dPbNy4Eenp6QByfqb9/f0BAA8fPjTrz3DLli3RoUMHJCUlYfbs2ZKPe/78Ob7//nsEBASgXr16aNCgAQYPHiz4t2HRokXw9vbGihUrRF9n8+bN8Pb2xoIFCwrUDyWGDx+OsmXL4tq1a7h48aL28czMTGzZsgV9+vSBr68vGjRogCFDhiAsLCzX1zpw4ADeffddNGnSBI0aNUK/fv2wc+dOk/+MmhsDBRNLS0vD4MGD8c033yAmJgaNGjVCixYtoFKpcPDgQbzzzju4fPmy4Ljr16+jf//+uHz5Mho2bIjq1asjIiIC48ePR2hoaCH0JH+nTp1C3759sXv3bri5uaFdu3aws7PDpk2b0LdvX0RFRQmOUavVGDx4MEJDQ+Hr64t69erh/PnzGD16NLZs2WKya9Xc5RN7L5OTk3HixAm0a9cODg4OgusdP3485syZg5s3b6J+/frw9/eHi4sLTp06hffff180mDty5AgWLlyIN954Az4+PmbL64iLi8Px48fh5uaGli1bwtbWFt26dUNmZiZ+++030WOys7MxZswYbNu2Dd7e3mjYsCGuXbuGqVOnYsmSJaLHTJgwAVFRUWjTpg2srKxMlqRujs+tTJkyaNWqFVJTU0U/yxMnTiAuLg5dunSBk5OTCXppWtHR0ejXrx9OnDiBevXqwcfHB9evX8esWbMscs2yuSn5nZPj+fPnGDFiBJYvX47k5GS0adMGbm5uWL58OaZOnWqEHojTJLaeOnUKq1atEr2D7uDggG+//Raffvqp9rFHjx6hb9++WLt2LTIzM9G6dWtUrVoVYWFh6NevH44ePSp6vk8++QTff/89PD090bx5czx48ADz5s3D9OnTTdPB/6f5ne/SpQvs7e3zbd+3b18AwJ49e7SPrV69GiNGjMCJEydQvXp1NG/eHDExMfjyyy8xZcoUZGdnw9vbGx07dgSQcxMkICAAzZs3N0GPxM2dOxelSpXC8ePHsXPnznzbx8XFoV+/fli2bBliY2PRqlUr+Pr64tKlS5g6dapeUNWzZ08AOQNpMZrAokePHgXviEw2NjbaGeczZ84AyLn5M3bsWMybNw8PHjxAw4YNtX2bOHEivvvuO8HrfPbZZ5g8eTIiIiK0Se63bt3CRx99hC+//NKsfTI15iiY2ObNm3HlyhV07twZS5YsgY1Nzluenp6OadOmITQ0FNu2bUPdunX1jjt9+jT69OmDuXPnav9YLV26FD/88APWrVuHzp07m70veYmLi8P//vc/ZGRkYMWKFdo/gGq1GqtWrcLSpUsxffp0BAUF6R2XnZ2N9PR07NmzB5UqVQIA/PXXXxg1ahS+/vpr+Pv7w9PT0+jX26ZNGzg4OCAsLExw1+jQoUNIT0/HW2+9hZSUFL3nfv/9dxw7dgy+vr7YsGGDdkCanZ2Nr7/+Ghs3bsSWLVvQoUMHvePu3buHTz/9FO+++662vTns3r0bGRkZ6NGjh/Znr2/fvtiyZQt+/fVXjB49WrCEICUlBVeuXMGmTZu0SXrXrl3De++9hzVr1qBDhw6oV6+e3jGZmZnYt28fSpQogezsbJMlMprrc3v77bdx9OhR7Nq1CwEBAXqvpblzWFyT4f7++2+0atUKS5YsQcmSJQEAwcHBmDVrFtatW4fhw4cX8hUWb0p+5+RYvXo1IiIi0LJlSyxfvlwbrO7fv9+kgUL16tXRp08fbN++Hd999x1WrlyJxo0ba/+rX78+bG1tBcdNmzYNUVFReP/99zFlyhRYW1sDyKn288EHH2D69OkIDQ2Fm5ub3nEnT57U+7fk4cOHGDp0KPbu3YuOHTuiS5cuJunn33//DQDw8fGR1N7Pzw9Azt9IALh8+TKWLl2KUqVKYd26ddrXSUpKwtChQ3Ho0CH8/vvv6Nq1K+rVq4eDBw8WSi6gu7s7Zs6ciY8//hhfffUVWrRoAXd391zbf/bZZ7h58yY6duyIRYsWaX/u/v33X4wcORLbt29HvXr1MGjQIHh7e6NWrVq4fv06bty4gZo1a2pf59GjR7h48SK8vLwE/46YS7Vq1QAAd+/eBQCsXLkSJ0+eRIsWLbBkyRK4uroCyJmFHT58OFatWoXGjRujZcuWAICwsDBs27YNnp6e2LBhg3bsEh0djQEDBmDTpk0ICAhA/fr1zd85E+CMgok5ODjA398fU6dO1f6jAQB2dnbo06cPAOC///4THGdvb49PP/1U747G4MGDAQA3b9408VW/pJkSze0/zZR4SEgIEhISMGTIEO0fdiBnmvqDDz6Aj48PIiIiRJeM/O9//9P+ogE5f3gHDx6M9PR0o9yBE+Ps7IzWrVvj0aNHguVfBw4cQIkSJdC6dWvBcdnZ2WjXrh2mTZumd9fayspKmxT26NEjwXF2dnYYOHCgXntz0FRe0fysAUCdOnVQq1YtPHz4EKdOnRI9bvz48XqVPN544w2MHz8earVadK117969UaJECQCm7Zu5Pjd/f3+4ubnh9OnTePLkifbxhIQEHDlyBJUqVcqz8lJRN3v2bG2QAOT8fDg6OiI2NhbPnj0rxCsr/pT+zkmRlZWFrVu3wtbWFgsXLtSb0erataveOU1h/vz5mDhxIhwdHZGeno7w8HAsXboUgwcPRpMmTTBjxgzcv39f2/7ixYs4f/486tSpg6lTp2qDBABo0aIFBg8ejKSkJISEhAjONWDAAL1/SypWrIhPPvkEAAQ3nIwpLi4OQM7MohSadmlpaUhISMC2bduQnZ2NiRMn6gUbJUqUwNSpU+Hl5SX6b0Rh6N27N1q3bo34+Hh8/vnnubZ78OABDh48CFdXV8HPXZUqVbR30NetW6d9XDNbYFiFbt++fVCr1YUym6Ch+dv37NkzpKenY/PmzbC3t8eiRYu0QQIAeHp6amfHdGdbt27dCgCYNWuW3tilXLlyGD9+PGrWrKkNQiwBAwUTGzJkCNasWYMqVapoH0tMTMS5c+dw4sQJANCuWdRVo0YNuLi46D1WpkwZqFQq0XXTpqKZEs3tP80fSU3AkFvlB00kfvbsWb3Hra2ttctJdLVt2xZAzvpjU9Gc9/fff9c+lpCQgPDwcHTo0AF2dnaCY7p164YffvgBjRo10j6WmpqKS5cuaZfDiFXbqVatmujrmdKVK1cQGRmJOnXq6N3RAV5Ol+eWYNmtWzfBY5qSc4afIZCTyGgu5vjcbG1t0aNHD2RlZemtv923bx8yMjLQq1evYlvq0tXVVe/vEZDze1i6dGkAMOvfF0tTkN85qa8fHx8PX19f0YGsqe6ya9jY2GDChAk4deoUFi9ejN69e2tLe6akpGDXrl3o3r07Dh8+DODlvwt+fn6ivy+aJSB//fWX4LmuXbsKHmvdujVsbW1x7tw5k83Kal5X98ZeXnTbqdVqbV80/4bpatWqFX7//Xez7Zsgxfz58+Hi4oKDBw/mWlpa8+9w69at4ezsLHjez88P7u7uiIqKQnR0NACge/fusLKyEiw/2r9/P1QqlWCm1pw0Yy6VSoUrV64gKSkJNWrUEP2datasGWxsbHD+/HlkZWVBrVbj7NmzsLW11Y5rdPXv3x979uxBr169TN0Ns+HSIzN4/PgxtmzZgj///BN3795FfHw8gLyTwjR3Z3WpVCpYWVkhKyvLVJcqIHVKVDMr8sEHH0hqp1G2bFnRP8iaqgyPHz+Weqmy6S5jmTFjBgDg4MGDyMjIEP1HSiMxMRFBQUE4efIk7ty5o73jnNfnWapUKeNevASaO5tPnjwRJMlpluYcO3YMMTExelU97OzstO+/rvLlywMQ/0zM2T9zfW59+vTB+vXrsXv3bm2px507d0KlUhXrfwTE/rYA0N7ttbREPHNS+jsnlebvZ4UKFUSfN1c9fhcXF+3NIiDnjvOxY8ewfv16PHjwANOmTcPhw4e117t+/fo88180g0tdhsEskPO3yc3NDdHR0YiPj9cGt8ZUtmxZ3L59W/LMmiZB3dHREa6urtrvxf6GFkXlypXDjBkz8Nlnn2H+/Plo2rSp4H3V/M3P6+fL09MTsbGxiI2NRbly5VC2bFk0a9YM4eHhuHr1KmrXro07d+7g6tWraNCggd6deHNLSEgAkPPvluZn9MqVK3luMJeZmak9LiMjA+XLlxddameJGCiYiGbw8ccff2Ds2LF4/vw5KlSoAD8/P1SrVg0+Pj6wsbHJtfpNcbtbqQle2rdvn2eCp+Gd5/ySxUz5i+jk5AR/f3+EhobiypUrqFOnDg4cOABXV9dck8pu3LiB9957D3FxcShTpgzq1q2L6tWro3bt2qhSpYr2rqEhc28+lJ6err0THhMTk2sJvMzMTISEhGD8+PHax3SXB+jSlJIT64s5f17N9bnVrFkTdevWxeXLl3H79m1YW1vj77//hp+fn0nyZqSS8l7nNdgvTn9bCtpXcyrI71xuDG8KZWZmAsi9z6Ys93jz5k3ExsaiSZMmgr8Rnp6eGDJkCHr27Im3334b9+7dw5EjR7TX+eabb+Y5MBQb8Cv5O2QMb7zxBk6fPo2LFy+ie/fu+bbXLIHUzCBpPqPiZMCAAdi/fz/++OMPzJ8/XzR5Nz+an1XdGd0ePXogPDwcBw4cQO3atbUzFppk58Kiqbbl7e2t/Rn19PSEr69vvsea80ZtUcFAQYFLly7hxx9/hLe3NyZMmKD3nGb5grOzM9RqNWbNmoXnz59jwYIFgo1Njhw5YrZrNjUPDw/cu3cPI0aM0FvekR+xcoFATm4EAEV33eTo0qULQkNDERYWhgoVKuCPP/5A3759c512nj9/PuLi4jB+/HhMnDhRbyATGRlp0muV4/Dhw4iPj0ezZs2wYcMG0TYHDx7EhAkTEBISgg8++ED7D+/z58+RmJiot4YdeLmGXzOzUJjM9bn16dMHly9fRlhYmHbgYsp14FL/tgAvB9Fi/3AlJiaa7BqNxdL6qvR3TqVSaZc0GAZGSUlJet9r/h6K5bUB4nfmjWXChAm4d+8eduzYkWtVsxIlSqBTp05Ys2YNEhIStMmx/v7+GDdunKzzxcTECAKI9PR0PH36FE5OTnpryY0pICAA69atw759+zB16lQ4Ojrm2V6TX6FZc+/u7o6HDx8iJiZGMPOTmZmJbdu2wcvLy6wVjqRYsGABevTogf379wuWnnp4eADImTnKjeY53eU7HTt2xNy5cxEaGoqpU6di//79sLW1FV1ubC5paWn4448/AOQsK9LM9FWqVEnS6on09HTY2triyZMnyMzMFPyb8+zZM4SGhsLb21tS4FEcMEdBgWfPniEsLAwXLlwQPKcZ+Hp4eCAuLg5RUVFwd3cX3f0wPDwcQNG5I1YQmuBAk3dhaObMmejbt6927apGcnKytsqELs26cSW7XcrRtm1bODo6IjQ0FIcPH0ZmZmaef8Q0d4/Gjh0r+Ee9KH2emjruYrkGGv7+/nB1dcWjR48En5vYPhaaz64o7C5rrs+te/fusLe3x8GDB3HkyBE4OTmZtOKY1L8twMtBtFiwLfY7VdRYWl+V/s5pZmB1k+aBnL+Nt27d0nvMx8cHzs7OuHjxojbpVldupUaNQTPoya9stSaJs0aNGnr/LojNdgQFBaF79+5YuXKl4Dmxv0HHjh1DZmamSQfZb7zxBjp06IC4uDjMnz8/z7bbt29HeHg4PDw8tIGC5n0S+7fwwoULmDdvnjaQLEqze5UqVcL//vc/ADmlU3U/r4YNG0KlUuHkyZOCinJAzsqJuLg4VK9eXa96lbOzMzp06IB///0XoaGhuH37Nvz9/QtlKa7G5s2bkZCQgNq1a8PHxwd169aFg4MDLl++LPo7FRkZiY4dO2LixIlQq9Wws7ODj48PMjIytOVVdR07dgxz5szB7t27zdEds2CgoICmDNzZs2dx48YN7ePHjx/HgwcPUKJECdSpUweurq5wcHDAkydP9P4xU6vV+O2337SZ8y9evDB7H4xtwIABcHR0xE8//YSDBw/qPbd9+3bs2LEDN27cEC0XNnv2bL1f0MOHD+PXX3+Fi4tLrkt5jMXR0RGtW7fG3bt3sW7dOri7u+cZnGjWnRoGPMeOHcPy5csBFP7n+fjxY5w6dQq2trbo1KlTru3s7Oy0g2vDKiLffvut3r4Xly9fxsqVK2Fra4tBgwaZ5sJlMNfnVrJkSXTs2BFXrlzBxYsXTb53gtS/LcDLpQ5hYWF6y1wiIiJMugeJsVhSXwvyO6fp26ZNm7Tt0tPTMWfOHEFhBAcHBwwYMAAZGRn45JNPkJaWpn3uxIkT2tc0xQB01KhRsLe3R0hICL744gvBbEdGRgbWrFmDQ4cO4fXXX0erVq3QtGlT1KpVCxEREfjuu+/0luVcvXoV3333HW7evCm6NvzHH3/EP//8o/0+KioKX331FQBoy0ybyrx581CuXDn89ttvmDJliiBAffHiBX744QfMmjUL1tbWWLhwoXYGdtCgQVCpVFi+fLleoJeQkICvv/4awMvZB80ynZSUlCKxS/CQIUPQsGFDxMbG6t04qVSpEtq3b4/4+Hh89NFHehtNRkVFYdasWQBeVmbUpemrpjJSYS07ys7ORkhICJYuXQobGxttNSMnJyf069cPycnJmDFjhl5uyrNnzzBz5kzcv38f5cuX1/5eafr5xRdf6P09io6ORmBgYKEnaxsblx4p4OrqihEjRmD16tXo168fmjRpgvT0dG21g+nTp2vX1g8dOhQ//vgjBg8eDD8/Pzg5OeHatWt48OABqlevrpdUWZyVK1cOX331FaZPn44JEyagZs2aqFq1Kv79919ERkbCysoKixYtElQVcHd3R1JSEjp37gw/Pz/Ex8fj3Llz2vJ/hrW1TeGtt95CaGgo7ty5gyFDhuS59nXYsGGYO3cupkyZgs2bN8PNzQ23b9/GrVu3tH9IEhMTkZ6ebvYqRxo7d+5EVlYWWrVqle+dm549e2Lr1q04ceKE3rIFtVqNgIAANG3aFBkZGfjjjz+QnZ2NuXPnwsvLy9RdkMRcn1vfvn2xd+9eqNVqk++dIOdvS9OmTVG7dm1cvXoV3bp1Q5MmTRAfH4/z58+jR48egp1iixpL6mtBfueGDx+OiIgIrF69GqdOnULFihURERGBtLQ0tG3bVjBLMH78eJw5cwZHjx5Fhw4d0KBBAzx58gQXLlxApUqVcP/+fckVe+SoUaMGAgMDMW3aNPz8888ICgpC/fr1UaZMGSQnJ+Py5cuIj49HpUqV8MMPP2h/H5csWYL33nsPq1evxq5du1C7dm0kJydrKxcNHTpUsO8MkJMwPWDAADRt2hS2trY4c+YM0tLSMHbsWJPPNLu5uSE4OBgTJ07E/v37ERYWhnr16sHDwwNJSUm4ePEiUlJS4O7ujsWLF6Np06baYxs1aoQJEyZg+fLl6NWrF/z8/GBnZ4eIiAjEx8cjICBAm/vg6uoKV1dXxMfHY9CgQahbt67eZnXmplKp8MUXX6Bnz56CGyfz5s3DvXv3cPDgQbRr1w6NGjXC8+fP8ddffyE9PR29e/fGO++8I3hNzf4M0dHRKFmyJNq0aWPSPjx79gzTpk3Tfp+dnY2EhARcv34dT548gZ2dHb7++mu9JdJTp07FlStXcPLkSXTs2BH16tWDjY0Nzp07h5SUFPj6+mLy5Mna9gEBATh9+jS2b9+OLl26wM/PD1lZWTh//jxSU1MxduxYvfLixR0DBYX+97//oVy5cggKCsKZM2dgb2+Phg0bYtiwYdoykgAwefJkuLu7IyQkRDvFXrlyZUyePBnDhw9H//79ERkZievXr5u1xKQpvPXWW6hatSrWrl2rrfDk7u6Ozp07Y/To0aIb2Li4uOCnn37CV199pV0C0qpVK0yaNMlsm7G0adMGTk5OSE1NzbNqDpBzt8jJyQkbN27EtWvXkJmZiYoVK2LUqFF4//33MXPmTBw5cgQnTpwQ/cfPHDRLIPLrC5AzTV61alXcu3cPwcHB2sdXr16Nn3/+GYcPH0ZWVhaaNm2K0aNHm/wfaDnM9bm9+eabsLKyQsWKFc2yd4LUvy3W1tZYv349li9fjrCwMBw/fhyVK1fGJ598gv79+xf64FkKS+lrQX7nJk6ciB9++AFr1qzR3kRq0qQJpk6dipCQEEGg4OLigs2bN2PlypUIDQ3FkSNHULZsWUyZMgVVq1bFpEmTBKW1jaVNmzYIDQ3FL7/8gvDwcNy5cwcXL16Es7MzvLy80KlTJ7zzzjt6e5VUr14dO3fuxI8//oijR4/i1KlTKFGiBBo1aoQhQ4bkOgPzxRdfIDw8HLt370Zqaipq166NESNG6O2tYEoeHh745ZdfsG/fPuzduxf//PMPLl26hNKlS6NOnTro0qULevToIVpFbMKECahduzY2btyIv//+Gy9evICXlxc++OADvWpYKpUKixYtwldffYV//vkHT548KdRAAQC8vLzw4YcfYtGiRXqPu7m5Ydu2bdiwYQMOHDiAEydOwNHREQ0bNsTAgQNzLc1rbW2Nbt26YcOGDejSpYvJb6Clpqbq7ZJtZWUFJycnVKpUCT169MDgwYMFxSgcHR2xceNG/PLLL9i9ezcuXLgAa2trVKlSBQEBARg0aJAgV+XLL7+En58ftm3bhr/++gtZWVmoWbMmhgwZUqyr4olRqYvCfBcRFQnt2rXDw4cPcfz48WJT3s/Udu7ciY8++giTJ0/Ot/wvkan9888/qFChgmiloA0bNuCrr77C3Llzi8QSQSWGDh2Kv/76C1u2bJFVGIOITIM5CkREBl68eAG1Wo2oqCgsX74ctra2ePvttwv7sogwZswYtGzZUlCtKyoqCuvXr4etrS38/f0L6eqIyNJw6RERkYEdO3bgiy++QEZGBtRqNd5//31tqUeiwjRy5EgsXLgQffr0ga+vL9zc3BAXF4eIiAhkZWVh1qxZuW7IRkQkFwMFIiIDNWrUgIODAxwdHdG7d2+9RDaiwjRixAhUr14dv/zyC65du4aLFy/C1dUV/v7+eO+99+Dn51fYl0hEFoQ5CkREREREJMAcBSIiIiIiEmCgQEREREREAsxRkCArKwtbt27Fjh07cOfOHWRlZaFSpUro2rWrdrdKXZpdbC9fvozU1FTUqFED7777bq479d29exfLly/H+fPnER8fj8qVK6N///4YPHiw6CZSt2/fxooVK/DHH38gMTERbm5uaN26NcaPH4/y5cub5D0gIiIiolcLcxTykZWVhXHjxuHYsWNwcnJC/fr1YWNjg7///huJiYmoX78+Nm7cqN2MIzw8HGPGjEF2djYaN24MR0dHvR0lp0yZovf6169fx+DBg5GcnIwGDRrAzc0Nf/75JxITExEQEIDFixfrtb906RLee+89pKamombNmqhSpQoiIyNx//59vPbaa9i6dWuR2TmXiIiIiIovBgr5CAoKwpw5c+Dt7Y0ff/wRZcuWBQDExcVh3LhxiIiIwOjRozF16lSkpaWhXbt2SExMxNq1a7Xbut+/fx9Dhw5FdHQ0fvvtN+0OxWq1Gj179kRkZCQWLVqEnj17al972LBhiIyMRGBgIDp37qy9nj59+uDKlSuYOXMmhg0bBiAnmJk3bx6CgoLQtm1brFq1yozvEBERERFZIuYo5GPHjh0AgE8++UQbJABA6dKlMXfuXADAvn37AAC7du3C06dPERAQoA0SAKBy5cqYNm0aAGDTpk3ax8PDwxEZGQk/Pz9tkGD42rrt4+PjceXKFbi6umqDBCBni/QPP/wQAHD27Fkj9JqIiIiIXnUMFPLx2muvoVq1aqhXr57guapVqwIAHj9+DAA4efIkAKB9+/aCtm3btoW1tTVOnDihfUzTvkOHDoL2mmVI58+fR3JyMgBo8xVSUlKQlJSk1/7Zs2cAgFKlSsnqHxERERGRGAYK+Vi1ahUOHDgAJycnwXOXL18GAJQrVw4AcPPmTQBAzZo1BW1dXFzg4eGBuLg4PHnyBABw69atXNsDgJeXF7Kzs3H79m0AQMmSJfHmm28iIyMDEydOxI0bN5CWloZLly5h6tSpAHJ27SQiIiIiKihWPVJIrVZj2bJlAIBOnToBAGJjYwEA7u7uose4u7vjv//+w5MnT1CmTBntTERe7QFoAwsA+OabbzBmzBicOXNGr4qSs7Mzvv32W3Tv3r2APSMiIiIi4oyCYkuWLMHZs2dRpkwZjBo1CgDw/PlzAICDg4PoMZrHU1NTFbUHAA8PD/Tu3Ru2trbw9vZGu3bt4OnpiZSUFPz000948OCBEXpHRERERK86zigosGzZMqxZswZ2dnZYunQpSpcuDSAnqVitVkOlUuV5fHZ2trY9AMnt09PTMXz4cPz9999YvHgxunbtqn1+xYoVWLlyJUaMGIG9e/fCzs6uQH0kIiIiolcbZxRkyMzMxGeffYbvv/8e9vb2WLFiBRo3bqx93tHREWq1Gi9evBA9Pi0tDUDOMiFNe93H82v/22+/4cKFCxgwYIA2SABykpwnTZqEpk2b4t9//8X+/fsL2FMiIiIietUxUJAoJSUFY8eOxbZt21CyZEmsW7cO/v7+em08PDwAvMxVMGSYw6Bpr5uDkFf7v/76CwDQokUL0fatW7cGAFy7dk1ap4iIiIiIcsFAQYKEhAQMHToUJ0+eRPny5bFlyxa9mQSN119/HQC0VYp0JScn4/HjxyhdujTKlCmj115T/UiXWq3GnTt3YG1tjerVqwMAEhMTAbxcsmRI83hGRobcLhIRERER6WGgkI/09HSMHj0aV65cQY0aNRAUFJRrOdNWrVoBAA4dOiR47siRI8jKytKbhdC0P3z4sKD9hQsXEBcXh4YNG8LFxQUAUK1aNQDA8ePHRc9/+vRpAECtWrWkdo+IiIiISBQDhXwEBgbi4sWLKF++PDZt2qTdM0FM586d4ebmhh07dugN5qOiovDtt99CpVLp7ajs5+eH119/HeHh4fj111+1j8fFxeHzzz8HAAwfPlz7+Ntvvw0rKysEBwfj4MGDeudev349jh8/jtKlS+vlLxARERERKaFSq9Xqwr6IourZs2do06YN0tLSUKdOHe0dfTGLFy8GkDM7MGnSJGRlZaFx48ZwdnbGH3/8gefPn2PKlCkYO3as3nGXLl3Ce++9h9TUVNSvXx8eHh7466+/kJCQgP79+2P+/Pl67bds2YIFCxYgOzsbb7zxBjw9PXHz5k3cu3cPTk5OWL16Nfz8/Iz/ZhARERHRK4WBQh7CwsIwceJESW0jIyO1X1+4cAErV67E33//DbVajRo1amDYsGF46623RI+9desWAgMD8eeffyI9PR1VqlTBwIED0a9fP9F8hPPnz2PdunW4cOECkpKSULp0abRo0QJjx45F1apVFfWViIiIiEgXAwUiIiIiIhJgjgIREREREQkwUCAiIiIiIgEGCkREREREJMBAgYiIiIiIBBgoEBERERGRAAMFIiIiIiISYKBAREREREQCDBSIiIiIiEiAgQIREREREQkwUCAiIiIiIgEGCkREREREJGBT2BdARESW5cGDB2jfvr3oc7a2tnBycoKnpydatWqFgQMHonz58kY9/+3bt1G9enWjviYR0atIpVar1YV9EUREZDl0AwUfHx/Y2dlpn8vIyEBcXBwePXoEtVoNZ2dnfPnll+jSpUuBzxsbG4svvvgCUVFR+O233wr8ekRErzrOKBARkcksW7YMnp6egsejo6OxaNEi7Nu3D9OmTUOpUqXQrFmzAp3r5MmTOHDgAOrUqVOg1yEiohzMUSAiIrMrV64cvv32W3Tu3BkZGRn49NNPkZGRUdiXRUREOhgoEBFRoVCpVJgzZw7s7e3x8OFD7N27t7AviYiIdHDpERERFRo3Nze0bdsWv//+O44ePYrevXtrn4uKisLPP/+MP/74Aw8fPkR6ejpcXV1Rv359DB06FE2bNtW2bdeuHR4+fAgAuHLlCry9vVGxYkUcOXJE2yY9PR2//PIL9uzZgzt37kCtVsPLywvdu3fHkCFDYG9vb76OExEVAwwUiIioUPn6+uL333/HuXPntI+dOnUK48ePR1paGkqUKIHKlSvjxYsXiIqKwqFDh3D48GEsXrwY3bt3B5CTNG1ra4t79+7ByckJtWrVgru7u/b14uPj8f777+PSpUuwsrJCpUqV4ODggMjISFy9ehX79u3DunXr8Nprr5m9/0RERRWXHhERUaGqWLEiAODp06fIyMhAeno6Zs6cibS0NAwbNgynT5/Gzp07ceDAARw7dgzNmzeHWq3G999/r32NwMBAjBkzBgDg5eWFrVu3IjAwUPv8xx9/jEuXLsHX1xehoaEICwvD7t27cfjwYTRq1AhXrlzBp59+at6OExEVcQwUiIioUDk7O2u/TkhIwD///IPU1FSULVsWM2bM0CuvWqZMGYwfPx4AcPfuXWRnZ+f7+pcvX8bRo0fx2muv4fvvv0flypW1z5UvXx6BgYFwcnLC4cOHcf36dSP2jIioeGOgQEREhUq32pFKpUKDBg1w/vx5hIWFwdraWtDe0dERAJCdnY0XL17k+/qHDx8GADRr1gylS5cWPO/m5qYtzXrixAlFfSAiskTMUSAiokKVnJys/bpEiRLarx0cHHDlyhVcvXoV9+/fx/3793Hjxg3cvXtX20bKjMLt27cBAOfOncOgQYNE2zx48AAA9F6biOhVx0CBiIgK1Z07dwAAnp6e2mVGZ8+exVdffYUrV65o26lUKlSpUgUBAQHYvXu35NfXBCKPHz/G48eP82yblJQk9/KJiCwWAwUiIipUERERAIA333wTAHDjxg2MGDEC6enpaNSoEXr27Alvb29Ur14dLi4uuHv3rqxAQbNUacaMGRg5cqTRr5+IyFIxUCAiokLz6NEjnDlzBgDw1ltvAQA2bdqE9PR0NGvWDOvWrRPkKURHR8s6R5UqVQC8nLkQc/XqVahUKlSqVAkuLi6yXp+IyFIxmZmIiArNggULkJ2djRo1aqBt27YAoN04zdvbWzSZOSQkRPt1VlaW9msrK/F/0tq0aQMACAsLQ1xcnOD5pKQkDBs2DL169cKBAwcU94WIyNIwUCAiIrO7d+8eJk2ahMOHD8PW1hbz58/XBgVVq1YFAOzfvx///vuv9piEhAR8+eWX2Lt3r/Yx3apHTk5OAHJyEdLT07WPN2nSBI0bN0ZiYiLGjBmj95oxMTEYN24cEhIS4O7ujoCAAJP0l4ioOFKp1Wp1YV8EERFZjgcPHqB9+/YAcnZM1t0H4cWLF3j8+DFiY2MBAC4uLvjmm2/Qrl07bZuoqCj06dMHiYmJsLGxgZeXF1QqFe7du4f09HTUqlUL0dHRiI+Px/bt21GnTh0AORWL3nrrLajValSoUAHlypXD1q1bAeQEBCNHjsTNmzehUqlQo0YNWFlZ4c6dO8jIyICLiws2b96MN954w1xvExFRkcdAgYiIjEo3UDBkY2ODEiVKoFq1amjVqhUGDBggurfBo0ePEBgYiHPnziE6OhoODg7w8vJCt27d8M477+Djjz/Gvn37MHHiREyYMEF7XEhICFavXo3//vsPrq6u2LlzJ8qUKQMAeP78ObZs2YIDBw5oAwQPDw+0bNkSo0ePhqenp2neECKiYoqBAhERERERCTBHgYiIiIiIBBgoEBERERGRAAMFIiIiIiISYKBAREREREQCDBSIiIiIiEiAgQIREREREQkwUCAiIiIiIgEGCkREREREJMBAgYiIiIiIBBgoEBERERGRAAMFIiIiIiISYKBAREREREQCDBSIiIiIiEiAgQIREREREQkwUCAiIiIiIgEGCkREREREJMBAgYiIiIiIBBgoEBERERGRwP8BhEvfBLWGGtYAAAAASUVORK5CYII=",
"text/plain": [
"
"
]
},
"metadata": {
"image/png": {
"height": 278,
"width": 389
}
},
"output_type": "display_data"
}
],
"source": [
"num_flights_by_date.plot()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Do you see a weekly pattern above? And below?**"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"
"
]
},
"metadata": {
"image/png": {
"height": 278,
"width": 389
}
},
"output_type": "display_data"
}
],
"source": [
"num_flights_by_date.rolling(window=7).mean().plot()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**We'll need a new column in our dataset - departure hour, let's create it.**\n",
"\n",
"As we see, `DepTime` is distributed from 1 to 2400 (it is given in the `hhmm` format, check the [column description](https://www.transtats.bts.gov/Fields.asp?Table_ID=236) again). We'll treat departure hour as `DepTime` // 100 (divide by 100 and apply the `floor` function). However, now we'll have both hour 0 and hour 24. Hour 24 sounds strange, we'll set it to be 0 instead (a typical imperfectness of real data, however, you can check that it affects only 521 rows, which is sort of not a big deal). So now values of a new column `DepHour` will be distributed from 0 to 23. There are some missing values, for now we won't fill in them, just ignore them. "
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"flights_df[\"DepHour\"] = flights_df[\"DepTime\"] // 100\n",
"flights_df[\"DepHour\"].replace(to_replace=24, value=0, inplace=True)\n"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"count 6873482.0\n",
"mean NaN\n",
"std 0.0\n",
"min 0.0\n",
"25% 9.0\n",
"50% 13.0\n",
"75% 17.0\n",
"max 23.0\n",
"Name: DepHour, dtype: float64"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df[\"DepHour\"].describe()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Now it's your turn. Answer the questions below."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 1. How many unique carriers are there in our dataset?**\n",
"\n",
"- 10\n",
"- 15\n",
"- 20 **[+]**\n",
"- 25 "
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"20"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df[\"UniqueCarrier\"].nunique()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 2. We have both cancelled and completed flights in the dataset. Check if there are more completed or cancelled flights. What is the difference?**
\n", "\n", "- Cancelled overweights completed by 329 flights\n", "- Completed overweights cancelled by 6734860 flights **[+]**\n", "- Cancelled overweights completed by 671 flights\n", "- Completed overweights cancelled by 11088967 flights" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "6734860" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cancelled_df = flights_df[\"Cancelled\"].value_counts()\n", "cancelled_df[0] - cancelled_df[1]\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 3. Find a flight with the longest departure delay and a flight with the longest arrival delay. Do they have the same destination airport, and if yes, what is its code?**\n", "\n", "- yes, ATL\n", "- yes, HNL\n", "- yes, MSP **[+]**\n", "- no " ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [], "source": [ "target_df = flights_df.groupby(\"Dest\").agg(\n", " {\"ArrDelay\": \"max\", \"DepDelay\": \"max\"})\n" ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "- 2 am\n", "- 9 pm \n", "- 8 am \n", "- 3 am **[+]**" ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DepHour\n", "3.0 0.000000\n", "13.0 0.000108\n", "12.0 0.000125\n", "9.0 0.000129\n", "10.0 0.000132\n", "Name: Cancelled, dtype: float64" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flights_df.groupby(\"DepHour\")[\"Cancelled\"].mean().sort_values().head()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 7. Is there any hour that didn't have any cancelled flights at all? Check all that apply.**\n", "\n", "- 3 **[+]**\n", "- 19\n", "- 22\n", "- 4 " ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{3.0}" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cancelled_hours = set(\n", " flights_df[flights_df[\"Cancelled\"] == 1].groupby(\n", " \"DepHour\")[\"DepHour\"].count().index\n", ")\n", "all_hours = set(np.arange(0.0, 24.0))\n", "all_hours.difference(cancelled_hours)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 8. Find the busiest hour, or in other words, the hour when the number of departed flights reaches its maximum.**
\n", "\n", "*Hint:* Consider only *completed* flights.\n", "\n", "- 4\n", "- 7\n", "- 8 **[+]**\n", "- 17 " ] }, { "cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "8.0 449145\n", "6.0 446657\n", "11.0 444643\n", "Name: DepHour, dtype: int64" ] }, "execution_count": 110, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flights_df[flights_df[\"Cancelled\"] == 0][\"DepHour\"].value_counts().sort_values(\n", " ascending=False\n", ").iloc[:3]\n", "\n", "# flights_df[(flights_df[\"Cancelled\"] == 0)].groupby([\"DepHour\"]).size().idxmax()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 9. Since we know the departure hour, it might be interesting to examine the average delay for corresponding hour. Are there any cases, when the planes on average departed earlier than they should have done? And if yes, at what departure hours did it happen?**
\n", "\n", "*Hint:* Consider only *completed* flights.\n", "\n", "- no, there are no such cases\n", "- yes, at 5-6 am **[+]**\n", "- yes, at 9-10 am\n", "- yes, at 2-4 pm" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DepHour\n", "0.0 70.750000\n", "1.0 111.812500\n", "2.0 122.562500\n", "3.0 95.812500\n", "4.0 3.375000\n", "5.0 -4.253906\n", "6.0 -1.629883\n", "7.0 0.102539\n", "8.0 1.760742\n", "9.0 3.753906\n", "10.0 5.460938\n", "11.0 6.683594\n", "12.0 7.902344\n", "13.0 8.812500\n", "14.0 10.351562\n", "15.0 11.875000\n", "16.0 11.882812\n", "17.0 13.210938\n", "18.0 15.343750\n", "19.0 16.875000\n", "20.0 22.781250\n", "21.0 23.031250\n", "22.0 38.031250\n", "23.0 60.000000\n", "Name: DepDelay, dtype: float16" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flights_df[flights_df[\"Cancelled\"] == 0].groupby(\"DepHour\")[\"DepDelay\"].mean()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 10. Considering only the completed flights by the carrier, that you have found in Question 4, find the distribution of these flights by hour. At what time does the greatest number of its planes depart?**
\n", "\n", "- at noon\n", "- at 7 am \n", "- at 8 am\n", "- at 10 am **[+]**" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ ""
]
},
"metadata": {
"image/png": {
"height": 251,
"width": 389
}
},
"output_type": "display_data"
}
],
"source": [
"ax = flights_df[(flights_df[\"Cancelled\"] == 0) & (flights_df[\"UniqueCarrier\"] == \"MQ\")][\n",
" \"DepHour\"\n",
"].hist(bins=24)\n",
"ax.set_xticks(np.arange(0, 24))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 11. Find top-10 carriers in terms of the number of *completed* flights (_UniqueCarrier_ column)?**\n",
"\n",
"**Which of the listed below is _not_ in your top-10 list?**\n",
"- DL\n",
"- AA\n",
"- OO\n",
"- EV **[+]**"
]
},
{
"cell_type": "code",
"execution_count": 111,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"WN 1189365\n",
"AA 587445\n",
"OO 554723\n",
"MQ 472362\n",
"US 447007\n",
"DL 445118\n",
"UA 438974\n",
"XE 364518\n",
"NW 344746\n",
"CO 294753\n",
"Name: UniqueCarrier, dtype: int64"
]
},
"execution_count": 111,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df[flights_df[\"Cancelled\"] == 0][\n",
" \"UniqueCarrier\"\n",
"].value_counts().sort_values(ascending=False).iloc[:10]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 12. Plot distributions of flight cancellation reasons (CancellationCode).**\n",
"\n",
"**What is the most frequent reason for flight cancellation? (Use this [link](https://www.transtats.bts.gov/Fields.asp?Table_ID=236) to translate codes into reasons)**\n",
"- Carrier\n",
"- Weather conditions **[+]**\n",
"- National Air System\n",
"- Security reasons"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"cancellation_map = {\n",
" \"A\": \"Carrier\",\n",
" \"B\": \"Weather\",\n",
" \"C\": \"National Air System\",\n",
" \"D\": \"Security\",\n",
"}\n"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 251,
"width": 454
}
},
"output_type": "display_data"
}
],
"source": [
"flights_df[flights_df[\"Cancelled\"] == 1][\"CancellationCode\"].map(\n",
" cancellation_map\n",
").value_counts().plot(kind=\"barh\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 13. Which route is the most frequent, in terms of the number of flights?**\n",
"\n",
"(Take a look at _'Origin'_ and _'Dest'_ features. Consider _A->B_ and _B->A_ directions as _different_ routes) \n",
"\n",
" - New-York – Washington (JFK-IAD)\n",
" - San-Francisco – Los-Angeles (SFO-LAX) **[+]**\n",
" - San-Jose – Dallas (SJC-DFW)\n",
" - New-York – San-Francisco (JFK-SFO)"
]
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"SFO-LAX 13788\n",
"LAX-SFO 13390\n",
"OGG-HNL 12383\n",
"dtype: int64"
]
},
"execution_count": 112,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"routes = flights_df[\"Origin\"] + \"-\" + flights_df[\"Dest\"]\n",
"routes.value_counts().iloc[:3]\n",
"\n",
"# flights_df[[\"Origin\", \"Dest\"]].groupby([\"Origin\", \"Dest\"]).size().idxmax()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 14. Find top-5 delayed routes (count how many times they were delayed on departure). From all flights on these 5 routes, count all flights with weather conditions contributing to a delay.**\n",
"\n",
"_Hint_: consider only positive delays\n",
"\n",
"- 449 \n",
"- 539 \n",
"- 549 \n",
"- 668 **[+]**"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Index(['LAX-SFO', 'DAL-HOU', 'SFO-LAX', 'ORD-LGA', 'HOU-DAL'], dtype='object')\n"
]
}
],
"source": [
"target_df = flights_df[flights_df[\"DepDelay\"] > 0].copy()\n",
"target_df[\"Route\"] = target_df[\"Origin\"] + \"-\" + target_df[\"Dest\"]\n",
"\n",
"five_routes = target_df[\"Route\"].value_counts().iloc[:5].index\n",
"print(five_routes)\n",
"\n",
"# unfinished\n"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"668"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum(target_df[target_df[\"Route\"].isin(five_routes)][\"WeatherDelay\"] > 0)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 15. Examine the hourly distribution of departure times. Choose all correct statements:**\n",
"\n",
" - Flights are normally distributed within time interval [0-23] (Search for: Normal distribution, bell curve).\n",
" - Flights are uniformly distributed within time interval [0-23].\n",
" - In the period from 0 am to 4 am there are considerably less flights than from 7 pm to 8 pm. **[+]**"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 266,
"width": 395
}
},
"output_type": "display_data"
}
],
"source": [
"ax = flights_df[\"DepHour\"].hist(bins=24)\n",
"ax.set_title(\"Number of flights by departure hour\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 16. Show how the number of flights changes through time (on the daily/weekly/monthly basis) and interpret the findings.**\n",
"\n",
"**Choose all correct statements:**\n",
"- The number of flights during weekends is less than during weekdays (working days). **[+]**\n",
"- The lowest number of flights is on Sunday.\n",
"- There are less flights during winter than during summer. **[+]**\n",
"\n",
"_Hint_: Look for official meteorological winter months for the Northern Hemisphere."
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Year', 'Month', 'DayofMonth', 'DayOfWeek', 'DepTime', 'UniqueCarrier',\n",
" 'FlightNum', 'ArrDelay', 'DepDelay', 'Origin', 'Dest', 'Distance',\n",
" 'Cancelled', 'CancellationCode', 'CarrierDelay', 'WeatherDelay',\n",
" 'NASDelay', 'SecurityDelay', 'LateAircraftDelay', 'Date', 'DepHour'],\n",
" dtype='object')"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df.columns\n"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 279,
"width": 364
}
},
"output_type": "display_data"
}
],
"source": [
"flights_df[\"DayOfWeek\"].value_counts().sort_index(ascending=False).plot(\n",
" kind=\"barh\", title=\"Number of flights by the day of the week\"\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 266,
"width": 370
}
},
"output_type": "display_data"
}
],
"source": [
"flights_df[\"Month\"].value_counts().sort_index(ascending=False).plot(\n",
" kind=\"barh\", title=\"Number of flights by the day of the week\"\n",
")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 17. Examine the distribution of cancellation reasons with time. Make a bar plot of cancellation reasons aggregated by months.**\n",
"\n",
"**Choose all correct statements:**\n",
"- October has the lowest number of cancellations due to weather. **[+]**\n",
"- The highest number of cancellations in September is due to Security reasons.\n",
"- April's top cancellation reason is carriers. **[+]**\n",
"- Flights cancellations due to National Air System are more frequent than those due to carriers."
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 686,
"width": 415
}
},
"output_type": "display_data"
}
],
"source": [
"target_df = flights_df[flights_df[\"Cancelled\"] == 1].copy()\n",
"target_df[\"CancellationReason\"] = target_df[\"CancellationCode\"].map(\n",
" cancellation_map)\n",
"\n",
"target_df.groupby([\"Month\", \"CancellationReason\"]).size().unstack(0).plot(\n",
" kind=\"barh\", figsize=(5, 12)\n",
")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Reminder on Cancellatoin codes:*\n",
"```\n",
"A - Carrier \n",
"B - Weather \n",
"C - National Air System \n",
"D - Security\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 18. Which month has the greatest number of cancellations due to Carrier?** \n",
"- May\n",
"- January\n",
"- September\n",
"- April **[+]**"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"CancellationReason Month\n",
"Weather 12 10042\n",
" 2 10034\n",
" 3 7520\n",
"Carrier 4 7312\n",
"Weather 1 6711\n",
"dtype: int64"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target_df.groupby([\"CancellationReason\", \"Month\"]).size().sort_values(\n",
" ascending=False\n",
").iloc[:5]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 19. Identify the carrier with the greatest number of cancellations due to carrier in the corresponding month from the previous question.**\n",
"\n",
"- 9E\n",
"- EV\n",
"- HA\n",
"- AA **[+]**"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AA 9609\n",
"WN 6554\n",
"UA 6352\n",
"Name: UniqueCarrier, dtype: int64"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target_df[target_df[\"CancellationReason\"] == \"Carrier\"][\n",
" \"UniqueCarrier\"\n",
"].value_counts().iloc[:3]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 20. Examine median arrival and departure delays (in time) by carrier. Which carrier has the lowest median delay time for both arrivals and departures? Leave only non-negative values of delay times ('ArrDelay', 'DepDelay').\n",
"([Boxplots](https://seaborn.pydata.org/generated/seaborn.boxplot.html) can be helpful in this exercise, as well as it might be a good idea to remove outliers in order to build nice graphs. You can exclude delay time values higher than a corresponding .95 percentile).**\n",
"\n",
"- EV\n",
"- OO\n",
"- AA\n",
"- AQ **[+]**"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((7009728, 21), (2320755, 21))"
]
},
"execution_count": 94,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target_df = flights_df.copy()\n",
"target_df = target_df[(target_df[\"ArrDelay\"] >= 0) &\n",
" (target_df[\"DepDelay\"] >= 0)]\n",
"flights_df.shape, target_df.shape\n"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [],
"source": [
"percentiles = target_df[[\"ArrDelay\", \"DepDelay\"]].quantile(q=0.95)\n"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(2188884, 21)"
]
},
"execution_count": 96,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target_df = target_df[\n",
" (target_df[\"ArrDelay\"] <= percentiles[\"ArrDelay\"])\n",
" & (target_df[\"DepDelay\"] <= percentiles[\"DepDelay\"])\n",
"]\n",
"target_df.shape\n"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [],
"source": [
"melted_df = target_df[[\"UniqueCarrier\", \"ArrDelay\", \"DepDelay\"]].melt(\n",
" id_vars=\"UniqueCarrier\"\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 1147,
"width": 1187
}
},
"output_type": "display_data"
}
],
"source": [
"sns.boxplot(data=melted_df, y=\"UniqueCarrier\", x=\"value\", hue=\"variable\")\n",
"sns.set(rc={\"figure.figsize\": (20, 20)}, font_scale=1.5, style=\"whitegrid\")\n"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "mlcourse_ai_bonus",
"language": "python",
"name": "mlcourse_ai_bonus"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
\n", "\n", "- Cancelled overweights completed by 329 flights\n", "- Completed overweights cancelled by 6734860 flights **[+]**\n", "- Cancelled overweights completed by 671 flights\n", "- Completed overweights cancelled by 11088967 flights" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "6734860" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cancelled_df = flights_df[\"Cancelled\"].value_counts()\n", "cancelled_df[0] - cancelled_df[1]\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 3. Find a flight with the longest departure delay and a flight with the longest arrival delay. Do they have the same destination airport, and if yes, what is its code?**\n", "\n", "- yes, ATL\n", "- yes, HNL\n", "- yes, MSP **[+]**\n", "- no " ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [], "source": [ "target_df = flights_df.groupby(\"Dest\").agg(\n", " {\"ArrDelay\": \"max\", \"DepDelay\": \"max\"})\n" ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n",
"\n",
"\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" ArrDelay DepDelay\n",
"Dest \n",
"MSP 2460.0 2468.0"
]
},
"execution_count": 104,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target_df.sort_values(\"DepDelay\", ascending=False).iloc[:1]\n"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"| \n", " | ArrDelay | \n", "DepDelay | \n", "
|---|---|---|
| Dest | \n", "\n", " | \n", " |
| MSP | \n", "2460.0 | \n", "2468.0 | \n", "
\n",
"\n",
"\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" ArrDelay DepDelay\n",
"Dest \n",
"MSP 2460.0 2468.0"
]
},
"execution_count": 102,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target_df.sort_values(\"ArrDelay\", ascending=False).iloc[:1]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 4. Find the carrier that has the greatest number of cancelled flights.**\n",
"\n",
"- AA\n",
"- MQ **[+]**\n",
"- WN\n",
"- CO "
]
},
{
"cell_type": "code",
"execution_count": 105,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"UniqueCarrier\n",
"MQ 18331\n",
"AA 17440\n",
"OO 12436\n",
"Name: UniqueCarrier, dtype: int64"
]
},
"execution_count": 105,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df.groupby(\"Cancelled\")[\"UniqueCarrier\"].value_counts()[1].iloc[:3]\n",
"\n",
"# flights_df[flights_df[\"Cancelled\"] == 1][\"UniqueCarrier\"].mode()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 5. Let's examine departure time and consider distribution by hour (column `DepHour` that we've created earlier). Which hour has the highest percentage of flights?** \n",
"*Hint:* Check time format [here](https://www.transtats.bts.gov/Fields.asp?Table_ID=236).\n",
"\n",
"- 1 am \n",
"- 5 am \n",
"- 8 am **[+]**\n",
"- 3 pm "
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"DepHour\n",
"8.0 449224\n",
"6.0 446737\n",
"11.0 444702\n",
"7.0 436700\n",
"13.0 435917\n",
"Name: DepHour, dtype: int64"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights_df.groupby(\"DepHour\")[\"DepHour\"].count(\n",
").sort_values(ascending=False).iloc[:5]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### **Question 6. OK, now let's examine cancelled flight distribution by time. Which hour has the least percentage of cancelled flights?**| \n", " | ArrDelay | \n", "DepDelay | \n", "
|---|---|---|
| Dest | \n", "\n", " | \n", " |
| MSP | \n", "2460.0 | \n", "2468.0 | \n", "
\n", "\n", "- 2 am\n", "- 9 pm \n", "- 8 am \n", "- 3 am **[+]**" ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DepHour\n", "3.0 0.000000\n", "13.0 0.000108\n", "12.0 0.000125\n", "9.0 0.000129\n", "10.0 0.000132\n", "Name: Cancelled, dtype: float64" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flights_df.groupby(\"DepHour\")[\"Cancelled\"].mean().sort_values().head()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 7. Is there any hour that didn't have any cancelled flights at all? Check all that apply.**\n", "\n", "- 3 **[+]**\n", "- 19\n", "- 22\n", "- 4 " ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{3.0}" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cancelled_hours = set(\n", " flights_df[flights_df[\"Cancelled\"] == 1].groupby(\n", " \"DepHour\")[\"DepHour\"].count().index\n", ")\n", "all_hours = set(np.arange(0.0, 24.0))\n", "all_hours.difference(cancelled_hours)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 8. Find the busiest hour, or in other words, the hour when the number of departed flights reaches its maximum.**
\n", "\n", "*Hint:* Consider only *completed* flights.\n", "\n", "- 4\n", "- 7\n", "- 8 **[+]**\n", "- 17 " ] }, { "cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "8.0 449145\n", "6.0 446657\n", "11.0 444643\n", "Name: DepHour, dtype: int64" ] }, "execution_count": 110, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flights_df[flights_df[\"Cancelled\"] == 0][\"DepHour\"].value_counts().sort_values(\n", " ascending=False\n", ").iloc[:3]\n", "\n", "# flights_df[(flights_df[\"Cancelled\"] == 0)].groupby([\"DepHour\"]).size().idxmax()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 9. Since we know the departure hour, it might be interesting to examine the average delay for corresponding hour. Are there any cases, when the planes on average departed earlier than they should have done? And if yes, at what departure hours did it happen?**
\n", "\n", "*Hint:* Consider only *completed* flights.\n", "\n", "- no, there are no such cases\n", "- yes, at 5-6 am **[+]**\n", "- yes, at 9-10 am\n", "- yes, at 2-4 pm" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DepHour\n", "0.0 70.750000\n", "1.0 111.812500\n", "2.0 122.562500\n", "3.0 95.812500\n", "4.0 3.375000\n", "5.0 -4.253906\n", "6.0 -1.629883\n", "7.0 0.102539\n", "8.0 1.760742\n", "9.0 3.753906\n", "10.0 5.460938\n", "11.0 6.683594\n", "12.0 7.902344\n", "13.0 8.812500\n", "14.0 10.351562\n", "15.0 11.875000\n", "16.0 11.882812\n", "17.0 13.210938\n", "18.0 15.343750\n", "19.0 16.875000\n", "20.0 22.781250\n", "21.0 23.031250\n", "22.0 38.031250\n", "23.0 60.000000\n", "Name: DepDelay, dtype: float16" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flights_df[flights_df[\"Cancelled\"] == 0].groupby(\"DepHour\")[\"DepDelay\"].mean()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Question 10. Considering only the completed flights by the carrier, that you have found in Question 4, find the distribution of these flights by hour. At what time does the greatest number of its planes depart?**
\n", "\n", "- at noon\n", "- at 7 am \n", "- at 8 am\n", "- at 10 am **[+]**" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "image/png": 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oe++9VzExMZo+fbp2795tCBVJSUnq1auXkpKS1KRJEzVt2lQ7duxQaGiotm3bps8++0wODg6W+vT0dD377LOKj4+Xj4+POnTooL1792rx4sXavHmzli1bpurVrf8HDQAAANzKSh0UwsPDFRUVJX9/f3366ae64447JEnnzp3T8OHDtXPnTn388ccaO3asJGn//v2SpFdffVUtW7a8btsmk0njx49Xenq6Zs2apZ49e1raHjhwoNauXavOnTura9eultdMnjxZSUlJGjVqlIYPHy5JyszM1EsvvaQtW7YoLCxMzz33nKU+JCRE8fHxCgoK0pQpU2Rra6ucnBy9/vrrioiIUEhIiIKDg0v7NQEAAEiSuo+NKNP2177fs0zbx+2j1GMUVq9eLUl6/fXXLSFBktzc3DR58mRJ0nfffWdZvm/fPtna2uqee+65YdvR0dGKj49X69atLSHh2rbDwsIsyxMSEhQVFSVvb28NGzbMstzZ2VkzZsyQnZ2dli5dalmelpam8PBwubi4aMKECZbbmOzt7TVp0iTVrFlTK1euVGZmZjG+EQAAAKDiK3VQqFWrlho0aKCAgADDurvvvluSdPr0aUlSdna2jhw5ogYNGsjZ2fmGbW/evFmS9OijjxrWBQYGqnbt2oqLi1N6erok6ddff5XJZFLHjh0NYxfq1aunJk2a6MSJEzp8+LAkKTY2VllZWWrTpo1hLEK1atXUtm1bZWVlKTY29obvFQAAAKhMSh0U5s2bpx9++KHAA/89e/ZIkurWrStJOnTokC5fvqz69evrww8/VLdu3RQQEKBOnTrpnXfeUVpaWr7Xmw/o/fz8Cuzbx8dHeXl5OnLkSL76Ro0aFVjfoEEDSdLBgweLVR8fH1/gegAAAKCyssqsRwUxmUyaPXu2JKlLly6S/jeQeePGjYqNjVWrVq1Ut25d7dmzR5999pk2bNigr7/+Wm5ubpL+dyXC3d29wD7My8+cOZOv3sPDo0j1KSkpRWr/7NmzRfrMxeXoaF8mMx8URXn1W9n6Kc++KuNnAgCUn7Latle2/SD728KV2XMUPvjgA8XGxqpOnToaPHiwpP8NZG7durV++eUXLViwQIsXL9ZPP/2ktm3b6ujRo5o0aZKljYsXL0qSqlatWmAf5uXmMQTFrTf/1zwj043qAQAAgNtFmVxRmD17thYsWCBHR0eFhIRYrhC89tpr6tevn9zd3fONCXBzc9M777yjxx57TD///LNOnz4tDw8P2dnZSZJsbGyu219eXp4klXm9tWVn5yg19WKZtF0Yc5It67mVK1s/5dlXRf5MFe1MCQBUZtbej1S2/WBF3t8WR82aTnJ0LNkhv1WvKOTk5OjNN9/Uxx9/rCpVqmjOnDlq1aqVZb2Dg4N8fHwKfIjZHXfcoSZNmshkMlluUTKf6c/KyiqwP/PyatWqFavePJ6iuPUAAADA7cJqQSEjI0PDhg3T8uXLVaNGDS1atEjt27cvVht16tSR9L9biMxjDcxjCq517RiDotab64rbPgAAAHC7sEpQSE1NVb9+/bR582Z5enrqyy+/zHclwWzatGl66aWXCh0c/Ndff0n63yxJ5tmIzLMTXc1kMikhIUF2dnZq2LDhDeslWWZHMs+iVNR6f3//AtcDAAAAlVWpg0J2draGDBmivXv3ytfXV8uWLSt0OtOdO3dq/fr12rBhg2HdwYMHtX//frm6uqpp06aSpHbt2kmSfvnlF0P9jh07dO7cObVs2dJyK5O5PjIy0jCu4OTJk9q/f7/q168vX19fSVKrVq1UtWpVbd261TBgOSMjQ1u3bpWzs/MNnyANAAAAVDalDgqhoaHatWuXPD09FRYWZrkaUJBevXpJkj788EPL2XpJOnfunF577TXl5uZq8ODBcnR0lHRldqRGjRopOjpaK1asyFc/ZcoUSdKgQYMsy728vNSuXTslJCRYpmaVrsxaNHHiROXm5uard3Z21hNPPKHU1FRNmTJFOTk5kq6MtZg6darS0tLUq1evAsdUAAAAAJVZqWY9On/+vMLCwiRdmblo5syZhda+9957euaZZxQdHa1169apZ8+euv/+++Xk5KSYmBhlZGSoW7dueu655yyvsbW11cyZMzVgwAAFBwdr5cqV8vDw0Pbt25WamqqgoCB16tQpXz+TJk1Snz59NG/ePG3YsEE+Pj7asWOHUlJS9PDDD6tPnz756kePHq2YmBitWbNGcXFxatKkifbt26fjx4+radOmevnll0vzFQEAAAAVUqmCQmxsrGVmoL1792rv3r2F1r733nuytbXV7NmztXz5coWHh2vnzp2ytbWVr6+vgoKC9PTTTxumKg0ICFB4eLhCQ0MVExOjQ4cO6a677tKYMWP0zDPPGPrx8vKy1G/atEnHjh2Tl5eX+vfvrwEDBsjePv9HdnV11bJlyzRnzhytX79ekZGR8vT01ODBgzVs2DDLjEoAAADA7aRUQaFLly6Kj48v1mtsbGzUu3dv9e7du8iv8fX1VWhoaJHrPT099dZbbxW53tXVVRMnTtTEiROL/BoAAACgMiuzJzMDAAAAqLgICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAzsrdFIbm6uvv76a61evVoJCQnKzc2Vl5eXHn/8cQ0ePFhVqlTJV79nzx7NnTtXe/bsUWZmpnx9fdW/f3917969wPYTExP10UcfKS4uThcuXJC3t7eCgoLUt29f2doas05ycrLmzp2r6OhopaSkyNPTUz169NALL7wgR0dHQ31aWprmz5+v9evX69SpU6pTp466dOmiESNGyMXFxRpfEQAAAFChlPqKQm5uroYPH65p06YpISFBzZs3V+vWrXX69GmFhoaqX79+unjxoqU+Ojpaffr00aZNm+Tr66sHHnhABw8e1Lhx4/Thhx8a2j9w4ICefvppfffdd6pXr57atWunpKQkTZ8+XePHjzfUJyUlKSgoSMuXL1eNGjXUoUMHZWRkKDQ0VM8//7wuX76crz49PV3PPvusFi5cKBsbG3Xo0EE2NjZavHixevXqpb///ru0XxEAAABQ4ZT6ikJ4eLiioqLk7++vTz/9VHfccYck6dy5cxo+fLh27typjz/+WGPHjlVWVpZeffVVSdJnn32mNm3aSJL+/PNP9evXT/PmzVPnzp3VrFkzSZLJZNL48eOVnp6uWbNmqWfPnpa2Bw4cqLVr16pz587q2rWr5f1MnjxZSUlJGjVqlIYPHy5JyszM1EsvvaQtW7YoLCxMzz33nKU+JCRE8fHxCgoK0pQpU2Rra6ucnBy9/vrrioiIUEhIiIKDg0v7NQEAAAAVSqmvKKxevVqS9Prrr1tCgiS5ublp8uTJkqTvvvtOkhQREaGzZ8+qe/fulpAgSd7e3ho3bpwkKSwszLI8Ojpa8fHxat26tSUkXNv21fUJCQmKioqSt7e3hg0bZlnu7OysGTNmyM7OTkuXLrUsT0tLU3h4uFxcXDRhwgTLbUz29vaaNGmSatasqZUrVyozM7NU3xEAAABQ0ZQ6KNSqVUsNGjRQQECAYd3dd98tSTp9+rQkafPmzZKkRx55xFDbsWNH2dnZadOmTZZl5vpHH33UUB8YGKjatWsrLi5O6enpkqRff/1VJpNJHTt2NIxdqFevnpo0aaITJ07o8OHDkqTY2FhlZWWpTZs2hrEI1apVU9u2bZWVlaXY2NgifRcAAABAZVHqoDBv3jz98MMPcnZ2Nqzbs2ePJKlu3bqSpEOHDkmS/Pz8DLUuLi7y8PDQuXPndObMGUmyHNAXVC9JPj4+ysvL05EjR/LVN2rUqMD6Bg0aSJIOHjxYrPr4+PgC1wMAAACVlVVmPSqIyWTS7NmzJUldunSRJKWkpEiS3N3dC3yNu7u7Tp06pTNnzqhOnTqWKxHXq5dkCRbmeg8PjyLVF+X9SNLZs2cLXF9ajo72cnevXiZt30h59VvZ+inPvirjZwIAlJ+y2rZXtv0g+9vCldlzFD744APFxsaqTp06Gjx4sCRZZj+qWrVqga8xLzePCSjrevN/nZycilQPAAAA3C7K5IrC7NmztWDBAjk6OiokJERubm6SJDs7O5lMJtnY2Fz39Xl5eZZ6SbdMvbVlZ+coNfXijQutyJxkU1LKdtrXytZPefZVkT9TRTtTAgCVmbX3I5VtP1iR97fFUbOmkxwdS3bIb9UrCjk5OXrzzTf18ccfq0qVKpozZ45atWplWe/k5CSTyaRLly4V+PqsrCxJVwYSm+uvXm6tevN4iuLWAwAAALcLqwWFjIwMDRs2zPKgs0WLFql9+/b5asxjB8xjA6517ZgBc715TIG16s11xW0fAAAAuF1YJSikpqaqX79+2rx5szw9PfXll1/mu5JgZp5dyDxL0dXS09N1+vRpubm5qU6dOvnqzbMTXc1kMikhIUF2dnZq2LDhDeuv7tc8i1JR6/39/QtcDwAAAFRWpQ4K2dnZGjJkiPbu3StfX18tW7as0OlM27VrJ0lav369Yd2GDRuUm5ub7yqEuf6XX34x1O/YsUPnzp1Ty5YtLc9AMNdHRkYaxhWcPHlS+/fvV/369eXr6ytJatWqlapWraqtW7caBixnZGRo69atcnZ2VsuWLYv0XQAAAACVRamDQmhoqHbt2iVPT0+FhYVZnplQkK5du6p27dpavXq1Nm7caFl+/Phxvf/++7KxsdHAgQMty1u3bq1GjRopOjpaK1assCw/d+6cpkyZIkkaNGiQZbmXl5fatWunhIQEy9Ss0pVZiyZOnKjc3Nx89c7OznriiSeUmpqqKVOmKCcnR9KVsRZTp05VWlqaevXqZXgYGwAAAFDZlWrWo/PnzyssLEyS5ObmppkzZxZa+95778nFxUXTpk3TyJEjNXToULVq1UrVqlXTtm3bdPHiRY0ePVqNGze2vMbW1lYzZ87UgAEDFBwcrJUrV8rDw0Pbt29XamqqgoKC1KlTp3z9TJo0SX369NG8efO0YcMG+fj4aMeOHUpJSdHDDz+sPn365KsfPXq0YmJitGbNGsXFxalJkybat2+fjh8/rqZNm+rll18uzVcEAAAAVEilCgqxsbGWmYH27t2rvXv3Flr73nvvSZIeeeQRhYWFae7cudq9e7dMJpP8/f01cOBAdevWzfC6gIAAhYeHKzQ0VDExMTp06JDuuusujRkzRs8884yh3svLy1K/adMmHTt2TF5eXurfv78GDBgge/v8H9nV1VXLli3TnDlztH79ekVGRsrT01ODBw/WsGHDLDMqAQAAALeTUgWFLl26KD4+vtivCwwM1KJFi4pc7+vrq9DQ0CLXe3p66q233ipyvaurqyZOnKiJEycW+TUAAABAZVZmT2YGAAAAUHERFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGJRqelQAAADcmtzdq5d5uykpf5dJH7g1cEUBAAAAgAFXFAAAACqh7mMjyqztte/3LLO2cevgigIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAADggIAAAAAA4ICAAAAAAOCAgAAAAAD+7JodNWqVXrttdf05Zdf6v7778+37tSpU+rQoUOhrw0MDNTXX3+db1lycrLmzp2r6OhopaSkyNPTUz169NALL7wgR0dHQxtpaWmaP3++1q9fr1OnTqlOnTrq0qWLRowYIRcXF0N9VlaWvvjiC33zzTf666+/VL16dXXo0EEjR46Uh4dHyb4EAAAAoAKzelDYuXOnpk2bVuj6ffv2SZL8/f3l5+dnWO/j45Pv30lJSerVq5eSkpLUpEkTNW3aVDt27FBoaKi2bdumzz77TA4ODpb69PR0Pfvss4qPj5ePj486dOigvXv3avHixdq8ebOWLVum6tWrW+ovX76s4cOHKzo6Wp6enmrfvr0SEhIUHh6uqKgorVixQvXq1Svt1wIAAABUKFYNCuvWrdNrr72mzMzMQmv2798vSRo8eLB69OhxwzYnT56spKQkjRo1SsOHD5ckZWZm6qWXXtKWLVsUFham5557zlIfEhKi+Ph4BQUFacqUKbK1tVVOTo5ef/11RUREKCQkRMHBwZb6pUuXKjo6Wh06dNBHH30kR0dHmUwmffjhh5o/f76mTp2qefPmlfQrAQAAACokq4xRSEpK0vjx4zVy5Ejl5eWpTp06hdaaryg0bdr0hu0mJCQoKipK3t7eGjZsmGW5s7OzZsyYITs7Oy1dutSyPC0tTeHh4XJxcdGECRNka3vl49nb22vSpEmqWbOmVq5caQkyeXl5Wrx4sWxsbBQcHGy5jcnGxkavvPKKfHx8FBkZqePHjxf/SwEAAAAqMKsEhZCQEEVERKhZs2Zavny5GjRoUGjt/v375ezsbLjFqCC//vqrTCaTOnbsaDnoN6tXr56aNGmiEydO6PDhw5Kk2NhYZWVlqU2bNoaxCNWqVVPbtm2VlZWl2NhYSdLBgweVnJysxo0b684778xXb2trq06dOkmSNm3adOMvAQAAAKhErBIUGjRooHfeeUfh4eHy9/cvtO7ChQs6efKkfHx8tHjxYvXo0UPNmzfXP/7xDwUHBys5OTlfvTkANGrUqNB+pSsH/MWpj4+PL1H7AAAAwO3CKmMUhgwZUqQ68/iEvXv36uDBg2rVqpXq1q2rPXv2aMWKFYqMjNSSJUssB+inT5+WpEJnHnJ3d5cknTlzRpKUkpKSb3lh9WfPni1RPQAAAHC7KJPpUQtjHp/g5+enjz/+WF5eXpKuDE4ODg7Wt99+q3HjxmnVqlWSpIsXL0qSqlatWmB75uXmMQfm/zo5OZVJvbU5OtrL3b36jQvLQHn1W9n6Kc++KuNnAgBULmW5/2B/e/OVa1AYOHCgunTpomrVqsnNzc2y3NnZWdOnT1dsbKz27t2rXbt2qUWLFrKzs5N0ZXDx9eTl5UlSmdcDAAAAt4tyDQp2dnaWqwjXcnJyUps2bRQREaG9e/eqRYsWljP9WVlZBb7GvNzZ2dnSRlnWW1t2do5SUy+WSduFMSfZlJS/6ecW7asif6aKdqYEAFA6ZbGvYn9rXTVrOsnRsWSH/FYZzGwt5mlVzbccmccmmMcgXMs8xsBcV9R689iD4tYDAAAAt4tyDQpz5szRyJEjLbMOXeuvv/6SJNWtW1fS/2YjMs9OdK0jR45IkuUJz0WtN8/MZH5dUdsHAAAAbhflGhTi4+O1bt06/fDDD4Z1Z8+eVXR0tBwcHPTAAw9Iktq1aydJioyMNIwTOHnypPbv36/69evL19dXktSqVStVrVpVW7duNQxAzsjI0NatW+Xs7KyWLVtKkho2bKj69etr3759OnXqVL76vLw8bdiwQTY2Npb3AQAAANwuyjUo9OrVS5K0ePFixcXFWZZnZGTo9ddfV3p6up5++mnLrT5eXl5q166dEhISNHv2bEt9ZmamJk6cqNzcXA0aNMiy3NnZWU888YRSU1M1ZcoU5eTkSJJycnI0depUpaWlqVevXvkexta7d2/l5ubqjTfeyBcuZs+eraNHj6pz587y9vYumy8EAAAAuEWV62Dmf/zjHxo0aJAWL16sZ599VoGBgapVq5Z+++03nT9/Xvfff78mTJiQ7zWTJk1Snz59NG/ePG3YsEE+Pj7asWOHUlJS9PDDD6tPnz756kePHq2YmBitWbNGcXFxatKkifbt26fjx4+radOmevnll/PVDxw4UFFRUYqOjlaXLl0UGBioxMREHTx4UPXr11dwcHCZfy8AAADArabcBzP/97//VUhIiAIDA7Vv3z5t3rxZ7u7uevXVV/X5558bnmng5eWl8PBwPfXUUzp37pyioqJUs2ZNjR07VnPmzJG9ff6s4+rqqmXLlqlfv37KyclRZGSkbG1tNXjwYH3xxReqVq1avnpHR0ctWrRIw4cPl5OTkyIjI5WRkaFevXpp2bJlhT7sDQAAAKjMyuSKQlhY2HXXd+vWTd26dStye56ennrrrbeKXO/q6qqJEydq4sSJRap3cnLSqFGjNGrUqCL3AQAAAFRmt9T0qAAAAABuDQQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAG9jf7DQAoe+7u1Uu1HgAA3H64ogAAAADAgCsKwG2k+9iIMm1/7fs9y7R9AABQfriiAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgFmPAAAAUCJl+Rwec9spKX+XWR+4Pq4oAAAAADDgigIAAABKpCyfz8OzeW4+rigAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAok6CwatUq+fv767fffitwfWJiosaMGaP27durefPm6t69u8LCwpSXl1dgfXJyst5880098sgjCggIUNeuXTV37lxlZ2cXWJ+WlqZ3331XXbt2VUBAgDp16qS3335b6enpBdZnZWVp/vz5+uc//6nmzZvrH//4hyZOnKjTp0+X7AsAAAAAKjirB4WdO3dq2rRpha4/cOCAnn76aX333XeqV6+e2rVrp6SkJE2fPl3jx4831CclJSkoKEjLly9XjRo11KFDB2VkZCg0NFTPP/+8Ll++nK8+PT1dzz77rBYuXCgbGxt16NBBNjY2Wrx4sXr16qW///47X/3ly5c1fPhwffDBB8rIyFD79u3l6uqq8PBwPfXUUzp58qR1vhgAAACgArFqUFi3bp2ef/55ZWZmFrjeZDJp/PjxSk9P16xZs/T1119rzpw5Wrdunfz9/bV27VqtW7cu32smT56spKQkjRo1SqtXr1ZoaKh++uknPfjgg9q+fbvCwsLy1YeEhCg+Pl5BQUH6/vvvFRoaqnXr1qlnz546fPiwQkJC8tUvXbpU0dHR6tChg3766SeFhoZq7dq1Gjp0qFJSUjR16lRrfkUAAABAhWCVoJCUlKTx48dr5MiRysvLU506dQqsi46OVnx8vFq3bq2ePXtalru5uWny5MmSlO/APyEhQVFRUfL29tawYcMsy52dnTVjxgzZ2dlp6dKlluVpaWkKDw+Xi4uLJkyYIFvbKx/P3t5ekyZNUs2aNbVy5UpLkMnLy9PixYtlY2Oj4OBgOTo6SpJsbGz0yiuvyMfHR5GRkTp+/Lg1viYAAACgwrBKUAgJCVFERISaNWum5cuXq0GDBgXWbd68WZL06KOPGtYFBgaqdu3aiouLs4wl+PXXX2UymdSxY0fLQb9ZvXr11KRJE504cUKHDx+WJMXGxiorK0tt2rSRi4tLvvpq1aqpbdu2ysrKUmxsrCTp4MGDSk5OVuPGjXXnnXfmq7e1tVWnTp0kSZs2bSruVwIAAABUaFYJCg0aNNA777yj8PBw+fv7F1pnPqD38/MrcL2Pj4/y8vJ05MiRfPWNGjUqtF/pygF/cerj4+NL1D4AAABwu7C3RiNDhgwpUp15FiF3d/cC15uXnzlzJl+9h4dHkepTUlKK1P7Zs2dLVG9tjo72cnevXiZt30h59VvZ+inPvm7W7wYAALeSst4fVsZjCGsp1+coXLx4UZJUtWrVAtebl5vHEBS33vxfJyenMqkHAAAAbhdWuaJQVHZ2dpKuDBa+HvPzFG61emvLzs5RaurFMmm7MOYkm5Ly9w0q6edm9VUW/VS0MxgAAJiV1X63Mh5DFKRmTSc5OpbskL9cryiYz9xnZWUVuN68vFq1asWqd3Z2Lpd6AAAA4HZRrkHBPNbAPKbgWteOGShqvbmurNovbAwDAAAAUFmVa1Awzy5knm3oaiaTSQkJCbKzs1PDhg1vWC/JMjuSeRalotabZ2Yyv66o7QMAAAC3i3INCu3atZMk/fLLL4Z1O3bs0Llz59SyZUvLMxDM9ZGRkYZxAidPntT+/ftVv359+fr6SpJatWqlqlWrauvWrYYByBkZGdq6daucnZ3VsmVLSVLDhg1Vv3597du3T6dOncpXn5eXpw0bNsjGxsbyPgAAAIDbRbkGhdatW6tRo0aKjo7WihUrLMvPnTunKVOmSJIGDRpkWe7l5aV27dopISFBs2fPtizPzMzUxIkTlZubm6/e2dlZTzzxhFJTUzVlyhTl5ORIknJycjR16lSlpaWpV69e+R7G1rt3b+Xm5uqNN97IFy5mz56to0ePqnPnzvL29rb+lwEAAADcwsp11iNbW1vNnDlTAwYMUHBwsFauXCkPDw9t375dqampCgoKsjwN2WzSpEnq06eP5s2bpw0bNsjHx0c7duxQSkqKHn74YfXp0ydf/ejRoxUTE6M1a9YoLi5OTZo00b59+3T8+HE1bdpUL7/8cr76gQMHKioqStHR0erSpYsCAwOVmJiogwcPqn79+goODi7z7wUAAAC41ZTrFQVJCggIUHh4uLp27apjx44pOjpa9erV05QpUzR58mRDvZeXl8LDw/XUU0/p3LlzioqKUs2aNTV27FjNmTNH9vb5s46rq6uWLVumfv36KScnR5GRkbK1tdXgwYP1xRdfWGZUMnN0dNSiRYs0fPhwOTk5KTIyUhkZGerVq5eWLVtW6MPeAAAAgMqsTK4ohIWFXXe9r6+vQkNDi9yep6en3nrrrSLXu7q6auLEiZo4cWKR6p2cnDRq1CiNGjWqyH0AAAAAlVm5X1EAAAAAcOsjKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADCwv1kdr1mzRhMmTCh0/bBhwzR69GjLv/fs2aO5c+dqz549yszMlK+vr/r376/u3bsX+PrExER99NFHiouL04ULF+Tt7a2goCD17dtXtrbGfJScnKy5c+cqOjpaKSkp8vT0VI8ePfTCCy/I0dGx9B8YAAAAqEBuWlDYv3+/JOmhhx6Sm5ubYf0999xj+f/R0dEaOnSo8vLy1KpVKzk5OWnr1q0aN26cDh8+nC9QSNKBAwfUt29fpaenKzAwUPfee69iYmI0ffp07d69W++9916++qSkJPXq1UtJSUlq0qSJmjZtqh07dig0NFTbtm3TZ599JgcHhzL4FgAAAIBb000LCvv27ZMkvfXWW7rjjjsKrcvKytKrr74qSfrss8/Upk0bSdKff/6pfv36ad68eercubOaNWsmSTKZTBo/frzS09M1a9Ys9ezZU5J07tw5DRw4UGvXrlXnzp3VtWtXSx+TJ09WUlKSRo0apeHDh0uSMjMz9dJLL2nLli0KCwvTc889Z/0vAQAAALhF3bQxCgcOHFCdOnWuGxIkKSIiQmfPnlX37t0tIUGSvL29NW7cOElSWFiYZXl0dLTi4+PVunVrS0iQJDc3N02ePNlQn5CQoKioKHl7e2vYsGGW5c7OzpoxY4bs7Oy0dOnSUn1WAAAAoKK5KUHh+PHjSktLU9OmTW9Yu3nzZknSI488YljXsWNH2dnZadOmTYb6Rx991FAfGBio2rVrKy4uTunp6ZKkX3/9VSaTSR07djSMXahXr56aNGmiEydO6PDhw0X/gAAAAEAFd1OCgnl8Qu3atTVt2jR17txZ9957r7p27aq5c+fq0qVLltpDhw5Jkvz8/AztuLi4yMPDQ+fOndOZM2ckyXJAX1C9JPn4+CgvL09HjhzJV9+oUaMC6xs0aCBJOnjwYLE/JwAAAFBR3ZQxCubxCatWrZKrq6sCAwN1xx136I8//lBoaKg2b96szz//XFWrVlVKSookyd3dvcC23N3dderUKZ05c0Z16tTR6dOnb1gvyRIszPUeHh5FqrcmR0d7ubtXt3q7RVFe/Va2fsqzr5v1uwEAwK2krPeHlfEYwlpu6hWFbt26KTIyUp988omWLl2qb7/9Vo0bN9bOnTsVEhIiSbp48aIkqWrVqgW2ZV6emZlZLvUAAADA7eCmXFEIDQ3V8ePH5e3tne8ZBXfeeafefvttPfnkk1q+fLnGjh0rOzs7mUwm2djYXLfNvLw8SZKdnZ0klVm9NWVn5yg19aLV270ec5JNSfmbfm7Rvsqin4p2BgMAALOy2u9WxmOIgtSs6SRHx5Id8t+UKwpVqlSRr69vgQ8yu+eee1S3bl1lZmbq6NGjcnJykslkyjdu4WpZWVmSpGrVqkmSnJyc8i23Vr2zs3ORPhsAAABQGdy06VGvp06dOpKu3BZkHjtgHqtwrWvHMJjrCxtTUNL6wsYwAAAAAJVRuQeF9PR0BQcHa+TIkcrJySmw5q+//pIk1a1b1zIbkXmWomvbOn36tNzc3Czhwlxf0HSmJpNJCQkJsrOzU8OGDW9Yf3W/hc2iBAAAAFRG5R4UqlWrpp9//lnr1q1TbGysYf3GjRt1/vx5+fn5ycPDQ+3atZMkrV+/3lC7YcMG5ebmqn379pZl5vpffvnFUL9jxw6dO3dOLVu2lIuLS776yMhIwziEkydPav/+/apfv758fX1L+IkBAACAiqfcg4KNjY2CgoIkSdOmTVNycrJl3Z9//qmpU6dKkl588UVJUteuXVW7dm2tXr1aGzdutNQeP35c77//vmxsbDRw4EDL8tatW6tRo0aKjo7WihUrLMvPnTunKVOmSJIGDRpkWe7l5aV27dopISFBs2fPtizPzMzUxIkTlZubm68eAAAAuB3clFmPhg8frt9++01xcXF67LHH1LJlS0lSTEyMsrOz9dxzz+nxxx+XdOWhatOmTdPIkSM1dOhQtWrVStWqVdO2bdt08eJFjR49Wo0bN7a0bWtrq5kzZ2rAgAEKDg7WypUr5eHhoe3btys1NVVBQUHq1KlTvvczadIk9enTR/PmzdOGDRvk4+OjHTt2KCUlRQ8//LD69OlTfl8OAAAAcAu4KUGhatWq+vzzz/X5559r7dq1iomJkaOjo1q0aKF+/fqpS5cu+eofeeQRhYWFae7cudq9e7dMJpP8/f01cOBAdevWzdB+QECAwsPDFRoaqpiYGB06dEh33XWXxowZo2eeecZQ7+XlZanftGmTjh07Ji8vL/Xv318DBgyQvf1N+ZoAAACAm+amHQE7OjpqyJAhGjJkSJHqAwMDtWjRoiK37+vrq9DQ0CLXe3p66q233ipyPQAAAFCZ3ZLTowIAAAC4uQgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAwICgAAAAAMCAoAAAAADAgKAAAAAAx45DAAAABuWe7u1cul/ZSUv8u0n4qIKwoAAAAADLiiAAAAgFtW97ERZdr+2vd7lmn7FRlXFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAY2N/sNwAAAADcbO7u1W/2W7jlcEUBAAAAgAFXFAAAAHDb6z42oszaXvt+zzJruyxxReEqW7ZsUf/+/fXAAw8oMDBQ/fr106ZNm2722wIAAADKHUHh/1u1apUGDRqknTt3KiAgQPfdd5927typF154QcuXL7/Zbw8AAAAoV9x6JCk5OVmTJk1S9erV9dVXX8nPz0+S9Pvvv2vQoEGaMWOGOnTooDvuuOMmv1MAAACgfHBFQdKXX36p7OxsDRw40BISJCkgIEAvvPCCLl26xFUFAAAA3FYICpI2b94sSXr00UcN68zLGKsAAACA28ltf+uRyWTS4cOHZWtrqwYNGhjW33333bK1tdXhw4dlMplkY2NzE96l9TFXMAAAAK7ntg8Kqampys7OlpubmxwdHQ3r7e3tVatWLZ09e1YZGRlycXG5Ce+y4iKQAAAAVEw2JpPJdLPfxM106tQpdejQQfXr19eGDRsKrOnUqZNOnDihTZs2MaAZAAAAt4XbfoyCrW3Rv4LbPFMBAADgNnLbBwVnZ2dJ0qVLlwqtycrKylcLAAAAVHa3fVBwcXGRs7Ozzp8/r5ycHMP6nJwcnT9/XlWqVFGNGjVuwjsEAAAAyt9tHxRsbGzk6+ur3NxcHT161LA+MTFReXl5+Z6vAAAAAFR2t31QkKR27dpJktavX29YZ17Wvn37cn1PAAAAwM1EUJD01FNPqUqVKvr000/1xx9/WJbv2bNHCxcuVNWqVfWf//znJr5DAAAAoHzd9tOjmn355ZeaOnWqHBwc9MADD0iSYmJilJOTo3feeUc9e/a8ye8QAAAAKD8EhatERkZq4cKF2rdvnxwdHeXv768XX3xRbdu2vdlvDQAAAChXBAUAAAAABoxRAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAULhNbNmyRf3799cDDzygwMBA9evXT5s2bSrTPletWiV/f3/99ttvVm87NzdXS5cu1b///W/dd999CggI0D//+U/NnTtXly5dsnpfS5YsUY8ePXTvvfeqdevWeu655xQVFWXVfq524cIFtWvXTv7+/mXS/po1a+Tv71/o/z788EOr9XXixAm9/vrrevjhh9WsWTO1a9dOwcHBSklJsUr71/scV/8vJibGKv1JUkREhIKCgtSiRQsFBASoZ8+e+uKLL5Sbm2u1Pi5fvqzPPvtMPXr0UEBAgB566CENHz5cu3btskr7N/r7TExM1JgxY9S+fXs1b95c3bt3V1hYmPLy8qzelySZTCb1799fnTt3Lnb7Re1n48aNev7559W6dWs1a9ZMHTt21JtvvqmkpKQy6at///4KDAxUixYt9NRTT2nJkiXF/h0p7nZ08ODBJfp9v14/p06duu7fVp8+fazWlyRlZGQoNDRU3bp1s2xzhw0bpj179liln379+hVpm/HRRx9Z7TPt2rVLQ4cOtfzuPfroo5o5c6ZSU1Ot8pnM1q9fr379+ikwMFD333+/+vTpo2+//bZIbRd3v7pnzx4NGzZMDz30kO677z4988wzWrt2rdX7udq2bdvUuHFjRURElMln+uabb9S3b1+1bNlSzZo1U5cuXfTOO+/c8OdU3H7WrFmjoKAgNW/eXIGBgerTp4/WrFlTpM9U3uxv9htA2Vu1apVee+01OTo6qk2bNsrLy1NMTIxeeOEFTZ06Vb169bJ6nzt37tS0adOs3q505Q9y+PDhioqKkrOzs5o3by57e3vt3r1boaGh2rhxo7744gs5OTlZpb/XXntNERERcnFxUdu2bXX58mVt375d0dHRGjlypF566SWr9HO1KVOm6PTp01Zv12z//v2SpIceekhubm6G9ffcc49V+tmzZ48GDRqkv//+W35+frr33nv1xx9/aMWKFdq2bZtWrlypmjVrlqqP7t27F7ruzz//1O7du1W9enV5eXmVqh+zWbNmadGiRXJ0dFSrVq1kZ2en3377TTNnztT27ds1Z84c2djYlKqP7OxsPf/889q+fbscHBwUEBAgJycnbd26VVFRUXrzzTfVu3fvErd/o7/PAwcOqG/fvkpPT1dgYKDuvfdexcTEaPr06dq9e7fee+89q/VlNmvWLMXExMjb27vIbRennwULFuj999+Xra2tAgICVLt2be3fv1/Lly/Xzz//rKVLl6phw4ZW6Ss8PFwTJ06Ura2t7r//flWrVk07d+7UjBkztHHjRs2fP1/29jfe/RZ3O/rVV19p8+bNRa4vaj/79u2TdCWU+/n5Gdb7+PhYra8LFy6of//+io+P1x133KH27dvrzz//VGRkpKKjo/Xll18qICCgVP08+OCDuuOOOwpcl5GRoQ0bNkgq+nbwRp9p/fr1GjVqlHJyctS8eXPVqVNHe/bs0RdffKGoqCgtW7aswO1wcfv54IMPNH/+fElS48aN5enpqT/++ENjx47Vr7/+qhkzZsjOzq7A1xZ3vxodHa2hQ4cqLy9PrVq1smyfxo0bp8OHD2v06NFW6edqR48e1bhx42QymW74XZWkrzfffFPLly+Xo6OjAgICVL16de3Zs0efffaZ1q9fr6+//lp16tQpdT8hISH65JNPDPuQCRMmKDY2VjNmzCjS5ys3JlRqSUlJpmbNmplatmxpio+PtyzfvXu3KTAw0HTvvfeakpKSrNrnjz/+aLrvvvtMfn5+Jj8/P1NsbKxV2//6669Nfn5+pu7du+d772fPnjX16tXL5OfnZ3rvvfes0td3331n8vPzM3Xt2tWUkpJiWX7w4EFTy5YtTY0bNzYlJiZapS+ztWvXWr47Pz8/q7Zt9uyzz5r8/Pys/rO/2qVLl0xdunQx+fn5mZYsWWJZnpWVZXr55ZdNfn5+pmnTppVZ/xkZGaauXbua/P39TVFRUVZpc//+/SZ/f39TmzZtTAkJCZblSUlJpo4dO5r8/PxMP/74Y6n7+fDDD01+fn6mjh075vu7PXXqlKl79+6me+65x7R///4StX2jv8+8vDxT9+7dTX5+fqY1a9ZYlp89e9ayvKifsSjbgqysLNNrr71mqXn00Uet/pkOHTpkaty4salFixamHTt2WJZnZ2ebJk+ebPLz8zMFBQVZpa9Tp06ZmjZtagoICDDt3LnTsjw1NdX01FNPmfz8/EwrVqwodT/XOnr0qKlFixaW+m3btlnl85hMJtNHH31k8vPzM0VERBSpzdL0NX78eJOfn59p9OjRpkuXLlmWL1y40LLdt0Y/hRk7dqzJz8/P9O6771rlM12+fNn04IMPmho3bmxat26dZXlWVpZp6NChJj8/P9PUqVNL3c+WLVtMfn5+pqZNm+br5+LFi6YxY8aY/Pz8TGFhYYW2X5z96sWLF01t27Y1NW3a1LR161ZL7bFjx0wPP/ywyc/Pz7Rnz55S93O17du3mx566CHL579622SNz7Rp0yaTn5+fqV27dqbDhw9bajMyMkzDhw+3/E6Wtp9du3aZ/Pz8TG3atMl37HD1PmTLli03/GzliVuPKrkvv/xS2dnZGjhwYL4zQQEBAXrhhRd06dIlLV++3Cp9JSUlafz48Ro5cqTy8vIKTN7WsHr1aknS66+/nu+skJubmyZPnixJ+u6776zS1zfffCNJGjduXL7P06hRI3Xv3l15eXmKjo62Sl+SlJycrKlTp+q+++4r9MyPNRw4cEB16tQp9KyaNXz//fc6evSounfvrn79+lmWV6lSRa+99prq1KmjxMTEMut/5syZSkxM1LPPPqv27dtbpc2tW7fKZDKpR48e+c6i3nHHHfrPf/4jSYqNjS11PytXrpQkTZs2Ld/fbd26dTVt2jTl5uYW67YIqeh/n9HR0YqPj1fr1q3Vs2dPy/Kr/77CwsKs0temTZv05JNP6v/+7/9KdMWnqP1EREQoLy9PgwYN0n333WdZ7uDgoNdff11ubm7atWuXTpw4Ueq+fvjhB12+fNlya5pZjRo1NHjwYEm67ln/kmxHc3NzNWHCBDk4OBR4xr+0/ZivKDRt2rRIbZe0r5MnTyoiIkJeXl56++235ejoaFn3/PPPq2nTprp48aLOnTtX6s9UkG+++UZr165V06ZN9corr1jlM8XHx+vMmTNq3LixunTpYllepUoVDR8+XNL1txlF7WfFihWSrnxPV/dTtWpVTZ06VW5ubpozZ45ycnIKfH1x9qsRERE6e/asunfvrjZt2lhqvb29NW7cOEmFbyOKu/++cOGCZsyYoYEDB+r8+fOqV69ege2Wti9z7ahRo/JdWXR2dtaMGTNka2urn3/+WdnZ2aXqx3xr1tChQ3X33Xdbaq/eh5T1beHFRVCo5Mw7pEcffdSwzrzMWr+UISEhioiIULNmzbR8+XI1aNDAKu1eq1atWmrQoEGBl5/Nf3jWum0nNDRUa9eu1cMPP2xYl5GRIUlWPaB/4403lJ2drXfeecdqbV7r+PHjSktLK/FOv6h++uknSdKgQYMM6zw9PRUdHa1FixaVSd+///67Vq5cKU9PT40ZM8Zq7ZpvKUpOTjasO3/+vCTJ1dW1VH2cO3dOKSkpqlq1qtq2bWtYb74NKTo6ulj3uxf17/N624zAwEDVrl1bcXFxSk9PL3VfL7zwghITE9WvXz/LLRPFUdR+HBwc5O/vr1atWhW47s4775R0/e1GUfsaMGCA1q9fr2HDhhnWmbcZ17vtqCTb0YULF2rnzp0KDg5W7dq1b1hf3H72798vZ2fnYt1iVJK+fvrpJ5lMJvXt2zdfSDBbtWqVfv7550Jv0ynNPig9PV2zZs2Sra2tpk+ffsNbw4ral63tlcOss2fPGg7SzduM691+WdR+Dh48KEnq0KGDYV21atXUrFkznT9/Xn/88UeBry/OftW8jXjkkUcMtR07dpSdnV2hxxXF3X+HhYVpyZIlql+/vr744gs98MADBbZb2r6qVaumRo0a5TuRYObq6qpatWopOztbFy5cKFU///3vf/XDDz/o3//+t6G2KNuHm+HWejewKpPJpMOHD8vW1rbAjcvdd98tW1tbHT58WCaTqdT3VTdo0EDvvPOOevToYdk4loV58+YVus482K1u3bpW6cvR0bHAM3SRkZH68ccf5ezsXOABVUmY7y8ODg7WXXfdZZU2C2Ien1C7dm1NmzZNmzZtUlJSkurVq6cePXpo8ODBqlKlSqn72bdvnxwcHNS4cWOdOnVKa9eu1Z9//ilXV1d16dKlSPcZl9TMmTNlMpk0btw4OTs7W63ddu3a6e2339aPP/6oBQsW6Omnn5a9vb1++uknLVmyRDVr1ixwB1Ac5sHCTk5OBf4d2djYyNbWVhkZGTp58mSRz8QX9e/z8OHDklTomWkfHx+dPXtWR44cUfPmzUvVV9euXfXSSy/J399ff/31V5E+R0n6GTlypEaOHFnguszMTMtnvt52o6h92draFvgzOXr0qD755BNJUo8ePUrdj9mBAwf00UcfqWvXrurevbv+7//+74avKU4/Fy5c0MmTJ9W0aVMtXrxYEREROnbsmKpXr66OHTtqxIgRN7wyWdS+zFcu7r33XmVkZOj777/XH3/8IXt7e7Vt21aPPPLIdfdTpdkHzZ8/XykpKerVq5eaNGlyw/qi9uXr6ytPT0+dOnVK48eP1yuvvCJ3d3ft2rVLU6ZMka2tbYEnU4rbj3m74eLiUuB68wmtI0eO5LvSZVac/eqhQ4ckFbyNcHFxkYeHh06dOqUzZ84YroAUd/9dt25dvfHGG+rdu7ccHR0tV1uLojh9XW/sx8mTJ3X27FlVqVJFtWrVKlU/9vb2BR6P7d69W1999ZXs7e31z3/+s9D2bgaCQiWWmpqq7Oxsubm5FXh2xt7eXrVq1dLZs2eVkZFR6AamqIYMGVKq15eWyWTS7NmzJSnfpVdrycrK0vjx43X48GEdOXJE9erV06xZs6xyi9WxY8f07rvvqm3bturbt68V3m3hzDvjVatWydXVVYGBgbrjjjv0xx9/KDQ0VJs3b9bnn3+uqlWrlriP7OxsnTp1SnXr1tWPP/6oN954QxcvXrSs//TTT/X8889r/Pjxpf4819q0aZN27twpX19fq29wGzZsqGnTpmnGjBl6//339f7771vW3XfffXrrrbfk6elZqj7c3NxUs2ZNnT9/XkeOHDEMsD1w4IDlzNP58+eLHBSK+vdpPvPl7u5e4Hrz8jNnzpS6r9DQ0CLVlbaf6/n000+VmZmpe++997o/u5L29d577+m3337T7t27VbVqVb355psFnvUtST/Z2dl69dVXVaNGDcstDkVV1H7MJxb27t2rgwcPqlWrVqpbt6727NmjFStWKDIyUkuWLLnu2fui9vXnn39KuhJOunfvnu9WsKVLl6pt27aaM2dOofuqkv6MLly4oLCwMDk4OOjFF18s0muK2peDg4NCQ0M1YsQIfffdd/luq/Hw8NDChQv10EMPlbofHx8fJSQk6LffflOjRo3yrbt06ZL27t0rSYXetlWYgvar5hnrrreNKCwoFKcfSXrmmWeK9X5L01dhQkJCJF25WuLg4GDVfl577TXFx8dr7969cnV11QcffKDGjRsXuY/ywK1HlZj5wOx6s/+YDwbNBx4V2QcffKDY2FjVqVPHci+wNZ08eVLr1q3TkSNHLMvi4+NL3a75/mJbW1vNnDmz1Fd2bsS84+/WrZsiIyP1ySefaOnSpfr222/VuHFj7dy507JhLCnzbSmpqamaMGGCHn30Uf3444+KjY3Vhx9+KFdXVy1atMhq42Ou9sUXX0i6soMti+8yMDBQbdu2lbOzs9q0aaMHH3xQ1apV0549e/TVV18VeUaOwtja2lrOOE+YMCHfbU5nzpzRm2++afl3QffLlpZ5u1FYUDQvz8zMtHrf5c08A5Gtra1effXVMuljzZo12rlzp/Ly8mRjY6PExERlZWVZpe3Zs2fr4MGDlnvQy4L5xIKfn59++OEHLV68WAsWLNAvv/yif/3rX0pJSbHcl15af//9t6QrB0+urq5atmyZ4uLi9NVXX8nf319bt27VpEmTrNLX1ZYvX66LFy+qZ8+epQ76BfH29lb37t1lZ2engIAAdezYUe7u7jp9+rQWLlxY4O0sxfXkk09KunJQu3v3bsvy7OxszZgxw3ICoLjbjIL2q2WxjSjr/XdJ+1q2bJkiIiLk5ORU6FXJkvZz6dIlrV692hLibG1tdfDgQatOs20NXFGoxIpz6bW0Bzc32+zZs7VgwQI5OjoqJCSkTHaadevW1bZt22Rra6stW7ZoxowZmjZtmjIzM0t1ZtN8f/H06dOLNVCrpEJDQ3X8+HF5e3vnu9J055136u2339aTTz6p5cuXa+zYscU6e3I1887o4sWL+sc//pFvOs3HH39czs7OGjp0qObOnaugoCCrHdAnJCQoOjpa9erV07/+9S+rtHm1Xbt26bnnnlP9+vX17bffqn79+pKujFkYMWKElixZIhcXF40aNapU/bzyyiuKi4vTnj179Nhjj6lFixaytbXV7t275e7urjZt2mjbtm1lci+r+RaFG/1MSvI8hVtJVFSURo4cqdzcXI0dO7ZY9z4Xh3kK4P379+utt95SWFiYjh49qoULF5aq3bi4OMtzNqx1+2NBBg4cqC5duqhatWr5tqvOzs6aPn26YmNjtXfvXu3atavAW1qKw7zdcHBw0Oeff64aNWpIklq2bKlFixapa9eu+u677zRixIgSj5e4Vl5enr766itJKpMD1PPnz+s///mPkpOTtXjxYsvvWXZ2tqZOnarw8HCNGDFCS5cuLVU/nTt31jPPPKPw8HD17t1bAQEBcnNz0759+5SWlqYnn3xSq1evLtY2vbD9qp2dXZFuVy7qNqI89t8l6WvFihWaMmWKbGxsNGPGjCJPn1zUfmxtbbV582Y5OTlZjgHmzJmjM2fOaMqUKSX6fGWBKwqVmPne7Os9wMR8Zsua93GXp5ycHL355pv6+OOPVaVKFc2ZM6fAAYvW4OzsrFq1aqlmzZrq1q2bZb78+fPnl/ghb+b7izt06FAml1gLUqVKFfn6+hZ4O9o999yjunXrKjMzU0ePHi1xH1efaSroYUwdOnTQHXfcoeTk5FL1c60ff/xRJpPJcvbO2mbOnKmMjAzNmDHDEhKkKzNWfPDBB7K3t9fnn3+e7zarknBxcdGXX36pYcOGyc3NTbGxsUpMTFTv3r0VHh5u+WzVq1cvVT8FMV+BLOyst3l5tWrVrN53eVm5cqVeeuklXbp0SSNGjCjT2ybr1q0rJycnBQYGatGiRXJ3d9fmzZu1c+fOEreZmZmp//73v3J3d1dwcLAV362RnZ2dvLy8CjzQcXJyssx6Yz4rWhrm7ca//vUvS0gwc3d3V6dOnWQymbR9+/ZS92W2Y8cOJSUl6b777rNa+LjaokWLlJCQoOHDh+cLo46Ojpo0aZJ8fHwUGxtrlQeTTp8+XdOnT5e/v7/27dunXbt26f7779eaNWssg2qLss240X7VyclJJpOp0P1eUbcR5bn/Lm5fc+bMsfxtTZs2rci3sRanHwcHB7m7u8vFxUXt2rXTwoUL5eTkpPDw8BI9BLKscEWhEnNxcZGzs7POnz+vnJwcw9nHnJwcnT9/XlWqVDFslCuCjIwMjRo1Sps3b1aNGjX08ccfl9lGpiAtWrSQt7e3jh07puPHj8vX17fYbXz44Ye6fPmyLl++bLh8bz4bY15unsaxrNWpU0enTp0q1cFu9erV5eDgoMuXL1tmlLlWvXr1lJycrPPnz1ttB71+/XpJKpPBYFlZWfr9999Vo0aNAgdie3l5ycfHR4cOHdKxY8dKfZ+ps7OzRo8eXeCDixISEmRjY1Mmt0l4eHho//79OnPmTIFn0G50f/Kt7sMPP9S8efNkY2Oj1157TQMHDiy3vmvUqKEOHTooPDxc+/btK3CGlaL4+uuv9eeff8rf319Tp07Nt848MHvevHmWs8v3339/qd97Ycz3oJc2HEuybN+uDuFXMy83zxZkDb/88oukstlmSLKEmoLGITg4OOjBBx9UYmKi9u3bZ5Wf0zPPPFPgSaeEhARJuuFV66LsVz08PJSWlqaUlJQCt+9F2UaU5/67OH3l5OQoODhYq1atkqOjo2bNmqVu3bpZvZ+CeHl56b777tOWLVsUHx9vtUlZSougUInZ2NjI19dXv//+u44ePWo4kE1MTFReXl6R592+laSmpmrQoEHau3evPD09tWDBAqt/DpPJpHfffVenTp3Su+++W+BtHuaz8oXNTX0j5ns4r/csBvO8y6+88kqpg0J6errlcfTmM+DXMs8+U5qNlJ2dnRo2bKgDBw4oOTm5wINm82DYok7neCNnz57V3r17dffdd8vf398qbV7t77//lslkuu4tfeYz/ZcvXy5VX4cOHdKJEyf04IMPGq78HDt2TKdOnVLDhg3L5Epgo0aNtHHjRh0+fNhwO47JZFJCQoLl51uRmEwmTZw4UStXrpSjo6PeeecdPf7441bvZ/ny5dq+fbuGDBlS4O9habcZ0v+2G/Hx8YWOk9qyZYukK08hLs0B6Jw5c3Tw4EHL7FTXssb2wszPz0/btm0rdJpa8wGotbYZ0v+mBy+LCTAkKS0tTVLh02hba5uRlJSkI0eOyNfXt8BZqGJiYmRjY3PdabGLul9t1KiRZVKPa4NCenq6Tp8+LTc3t0IHMpfH/rskfWVnZ+ull17Spk2bVKNGDc2dO1etW7e2aj8LFizQ3r179eabbxb4e2zePpT298GauPWokmvXrp2k/51pvZp5mbUeRlVesrOzNWTIEO3du1e+vr5atmxZmWxkbGxs9Msvv+j7778v8ED++PHjSkxMLNX84mFhYZad/bX/M+9AzP8u7Mx8cVSrVk0///yz1q1bV+BDfjZu3Kjz58/Lz89PHh4eperL/OyJH3/80bAuISFBJ06ckIeHR4ketFWQ33//XZJKfJb2RmrXri1XV1dduHDB0tfVkpOTdeTIETk4OJT6GSKffPKJhg4dWuDtCMuWLZMkPfbYY6XqozDmbYb5TOvVduzYoXPnzqlly5alniWtvL399ttauXKlXFxctGjRojIJCZL0xx9/6Ntvv1VERIRh3eXLl7V161ZJJX94mSS9/PLLhW43zM/eWLJkieLj4/XUU0+VuB/pyvZn3bp1+uGHHwzrzp49q+joaDk4OFhljId5m7F+/XpDkMrOzlZMTIykK2MWrCE9PV1HjhxR/fr1y+zhk+ZtwcaNGw3rcnNztW3bNkkq9RXIqKgoPffcc5bxFleLjIxUUlKS7r///kIP3ouzX73eccWGDRuUm5tb6HFFee2/S9LX2LFjtWnTJnl4eOjLL78sckgoTj/btm3Tjz/+WOB+MS0tTbt27ZJUuu2DtREUKrmnnnpKVapU0aeffprvQSt79uzRwoULVbVqVcvTACuK0NBQ7dq1S56engoLCyvTy3NBQUGSrtz7efU9g8nJyRozZoxycnL0n//8xyrPHSgPNjY2ls80bdq0fDPq/Pnnn5bbGIo6ReD19O7dW87OzlqzZo3lqoh05czLxIkTlZeXp759+1rtmRvm3+9mzZpZpb1r2dra6umnn5Z05cF4V393586d07hx43T58mX9+9//LvX9++YHGc2ePTvfzCHr16/XkiVLVKNGjTK7ZaZ169Zq1KiRoqOjLU97la58RvMAu+vN+34r2rRpkz7//HPZ29tr/vz5RT4AKIlnnnlGNjY2WrJkieXAVroyVmzy5MlKSEhQ8+bNrXawW9Z69eolSVq8eLHi4uIsyzMyMvT6668rPT1dTz/9tFVuRXvwwQfVuHFjHT16VDNnzrTM/pKXl6dZs2bpr7/+0kMPPWS1h3nu3btXJpOpzLYZ0v++v3nz5uX7/nJycjRr1iwdPHhQjRo1yveE45J4+OGH5eDgoK+++krHjh2zLE9ISLDMFHW9WXuKs1/t2rWrateurdWrV+cLQMePH9f7778vGxubQrdP5bn/Lk5fX3/9tX766Se5uLhoyZIlxQovxenHvP8NDQ21PI9CuhISxo8frwsXLqhbt25lcltpSXHrUSV35513asKECZo6dap69+5tOesTExOjnJwcvfPOO1a9jFvWzp8/b3k0vJubm2bOnFlo7dUz7ZRU//79FRMTo40bN6pbt24KDAxUbm6udu/erczMTLVv377UM9yUt+HDh+u3335TXFycHnvsMcsBS0xMjLKzs/Xcc89Z5Wxr/fr1NWPGDL366qsaN26cFi9eLA8PD+3atUvnz59XmzZt9Pzzz5e6HzPzLRDWeK5FYUaOHKnff/9d27dvV+fOndWqVSvZ2Nho9+7dSktLU4sWLTRhwoRS9/PPf/5TERER2rhxo7p06aIWLVooOTlZv//+u5ycnDRnzpwyG1dknqZ3wIABCg4O1sqVK+Xh4aHt27crNTVVQUFB6tSpU5n0XVbMz2uoXbu2li1bZrkqc60XX3yx1LdUBQQEaNSoUQoJCdGAAQPUokULubq66o8//lBKSoq8vLwUEhJS5tMgW8s//vEPDRo0SIsXL9azzz6rwMBA1apVS7/99pvOnz+v+++/3yq/89KV23A++OADDRgwQF9++aWioqJ0zz336ODBg/rzzz/l6elpGJNRGuWxzWjfvr2GDBmiBQsWqG/fvmrRooXc3Ny0f/9+nTx5UnXq1FFISEipJ1+oV6+eXnnlFb377rvq2bOnWrdurdzcXMXExFjGwBUWkIu7X3VxcdG0adM0cuRIDR06VK1atVK1atW0bds2Xbx4UaNHjy7wCkl57r+L09fbb7+tjz/+WNKVcRVz584ttPbasYLF/UyPPfaYgoKCtGLFCj355JNq2bKlHB0d9fvvv+vChQtq1qyZVX/HrYGgcBvo27ev6tWrp4ULF2rHjh1ydHRUYGCgXnzxRctl6ooiNjbWMqPC3r17rzvThjWCgoODgz755BN99dVXWrVqlWJjY2Vrays/Pz899dRTCgoKKtOnUJeFqlWr6vPPP9fnn3+utWvXKiYmRo6OjmrRooX69etn1Xt1H3/8cfn4+OiTTz5RbGysDh8+LC8vLz333HMaNGhQiadfLYj5QUJlOTC/SpUq+uyzz/TVV18pIiJCcXFxysvL0913360XXnhBAwcOLHA2qZIIDQ3VJ598orVr1yoqKkoeHh564oknNHToUKudUS1MQECAwsPDFRoaqpiYGB06dEh33XWXxowZU26zc1nLhQsXLE9HTU5Oznd161rPPPOMVcZevPjii2rSpIkWL16sPXv26NKlS7rzzjv173//W88//3yFmzziv//9r5o3b66lS5dq3759ysvLk7e3twYPHqwBAwZY9e+4YcOGWrNmjebNm6cNGzZo48aNcnd3V9++ffXiiy9adRC9eZtRFrOHXW3s2LEKDAxUWFiY9uzZoz/++EMeHh569tlnNXTo0FLf5mk2ePBg1apVS2FhYdq6dauqV6+uBx54QM8//7wefPDBQl9Xkv3qI488orCwMM2dO1e7d++WyWSSv7+/Bg4cWOjg3/Lcfxenr0GDBlnGxSQmJioxMbHQ2mvHCpbkM02bNk2tWrXSV199pd27d1v2IYMHD1b//v1vuTsUbEwVfQJ9AAAAAFZXsU6FAgAAACgXBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABgQFAAAAAAYEBQAAAAAGBAUAAAAABv8Pm1MS/I7VrGYAAAAASUVORK5CYII=", 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