{ "cells": [ { "cell_type": "markdown", "id": "08b09aa6", "metadata": {}, "source": [ "\n", "\n", "> **Download this notebook:** [`00_getting_started.ipynb`](https://raw.githubusercontent.com/sablier-ai/sablier-flow/main/examples/00_getting_started.ipynb) (right-click \u2192 Save Link As)\n", "> \u00b7 [View source on GitHub](https://github.com/sablier-ai/sablier-flow/blob/main/examples/00_getting_started.ipynb)\n", "> \u00b7 Or `pip install sablier-flow && sablier-flow notebook` to copy a fresh local copy from the wheel.\n" ] }, { "cell_type": "markdown", "id": "637dedfc", "metadata": {}, "source": [ "# sablier-flow in 20 minutes\n", "\n", "Walks an analyst from cold install to a working overfit-detection verdict end-to-end. The canonical 7 steps for backtest augmentation, then forward forecasting, then bonus sections covering the rest of the SDK surface:\n", "\n", "**Backtest augmentation (Steps 1\u20137):**\n", "1. **Load your data** \u2014 any DataFrame with a `DatetimeIndex` and one numeric column per feature\n", "2. **Pick the backtest window** \u2014 the slice you actually want to evaluate against\n", "3. **Fit a model on the full history** \u2014 80/20 train/test split + embargo, all server-side\n", "4. **Validate on the held-out OOS** \u2014 zero-config, server uses the slice it kept aside\n", "5. **Generate paths matching the backtest window** \u2014 `like=window` derives length, index, and anchor\n", "6. **Visualize + backtest** \u2014 plot the alternative histories, run your strategy on each\n", "7. **Robustness verdict** \u2014 percentile rank + Deflated Sharpe under two nulls\n", "\n", "**Forward forecasting (Steps 8\u20139):**\n", "8. **Generate forward paths** \u2014 same `fit`, same backtest function, anchor at \"today\" instead of a past window\n", "9. **Calibrate predictive validity** \u2014 `sf.predictive_rank_score` tells you how much to trust the forward ranking on your model + universe\n", "\n", "Then bonus sections covering everything else:\n", "\n", "- **Async workflow** \u2014 `fit_async`, `fetch_result`, `list_jobs`, `cancel_job`, cross-process handles\n", "- **Model management** \u2014 `list_models`, `get_model`, `delete_model`\n", "- **Account + pre-flight** \u2014 `whoami`, `credits`, `usage`, `estimate_cost`\n", "- **Intraday data** \u2014 same API, sub-day cadence\n", "\n", "**Prerequisites:**\n", "- Python 3.10+\n", "- A Sablier account at (new accounts get 500 free credits \u2014 enough for ~1.5 full cycles of this notebook). You'll authenticate interactively from the SDK in Step 0 below; no manual API-key paste required.\n", "\n", "**Cost:** the `fit` step dominates by a large margin; `validate` and `generate` are a handful of credits each. Use `sf.estimate_cost('fit', real_data=df, features=cols, horizon=252)` for a deterministic estimate on your own data. Wall-clock depends on queue depth and GPU availability \u2014 poll progress with `sf.list_jobs()` once the job is running." ] }, { "cell_type": "markdown", "id": "e6124787", "metadata": {}, "source": [ "## Setup" ] }, { "cell_type": "markdown", "id": "8446493c", "metadata": {}, "source": [ "### Recommended: run this notebook in an isolated environment\n", "\n", "Running `!pip install` against your system Python is risky if you share that kernel with other research. Spin up a fresh venv (or conda env) first:\n", "\n", "```bash\n", "python -m venv .venv\n", "source .venv/bin/activate # macOS/Linux \u2014 Windows: .venv\\Scripts\\activate\n", "pip install jupyter\n", "jupyter notebook 00_getting_started.ipynb\n", "```\n", "\n", "### What you'll need\n", "\n", "- `sablier-flow` (pinned below so this notebook installs the shipping wheel \u2014 bump the floor explicitly when you want a newer build).\n", "- `matplotlib` (only used by Step 6 to plot the synthetic alternatives).\n", "\n", "Everything else (`pandas`, `numpy`, `pyarrow`, `httpx`, `cryptography`, `pydantic`) comes transitively with `sablier-flow`. No `yfinance` or other vendor data libs \u2014 the demo dataset ships bundled inside the wheel." ] }, { "cell_type": "code", "execution_count": null, "id": "cc326849", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:15:29.499336Z", "iopub.status.busy": "2026-06-01T19:15:29.499069Z", "iopub.status.idle": "2026-06-01T19:15:29.916855Z", "shell.execute_reply": "2026-06-01T19:15:29.916169Z" } }, "outputs": [], "source": [ "# Install (one-time in your venv). Pinned to a known-good wheel floor so this\n", "# notebook reruns identically when you (or a reviewer) replay it later.\n", "# Bump the floor explicitly when you want a newer build.\n", "!pip install --quiet --no-cache-dir 'sablier-flow>=1.1' matplotlib\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "f4ce1088", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:15:29.918872Z", "iopub.status.busy": "2026-06-01T19:15:29.918735Z", "iopub.status.idle": "2026-06-01T19:15:30.770226Z", "shell.execute_reply": "2026-06-01T19:15:30.769810Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "sablier-flow 1.1.0\n" ] } ], "source": [ "import os\n", "import warnings\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "\n", "import sablier_flow as sf\n", "\n", "# Pandas 2.x emits FutureWarnings on .fillna/.ffill downcasting of\n", "# object-dtype arrays. We don't rely on the implicit downcast and the\n", "# warnings clutter the synthetic-path comprehension below, so silence\n", "# them at the source.\n", "pd.set_option('future.no_silent_downcasting', True)\n", "warnings.filterwarnings('ignore', category=FutureWarning, module='pandas')\n", "\n", "print(f'sablier-flow {sf.__version__}')" ] }, { "cell_type": "markdown", "id": "685601c4", "metadata": {}, "source": [ "## Step 0 \u2014 Authenticate\n", "\n", "Three ways to give the SDK an API key, resolved in this order:\n", "\n", "1. **`sf.login()`** \u2014 interactive: opens https://sablier.ai/auth/device in your browser, you click Authorize, the SDK writes the minted key to `~/.sablier/credentials` (mode 0600). Recommended for notebooks + Jupyter.\n", "2. **`SABLIER_FLOW_API_KEY` env var** \u2014 for CI, containers, or shared kernels where popping a browser isn't ergonomic. Set it in your shell before launching Jupyter.\n", "3. **Explicit `api_key=` kwarg** \u2014 `sf.fit(..., api_key='sk_live_...')`. Wins over env var and credentials file.\n", "\n", "Run the cell below to log in. If you already ran `sf.login()` once on this machine, the credentials file is still there and the call is a no-op \u2014 just re-runs the device flow if the key was revoked." ] }, { "cell_type": "code", "execution_count": 3, "id": "cb899dcd", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:15:30.771323Z", "iopub.status.busy": "2026-06-01T19:15:30.771211Z", "iopub.status.idle": "2026-06-01T19:15:37.364333Z", "shell.execute_reply": "2026-06-01T19:15:37.363404Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "To authenticate, open this URL on any device where you're signed in:\n", " https://sablier.ai/auth/device\n", "\n", "and enter this code:\n", " X7W7-GQDD\n", "\n", "(Or open the pre-filled link: https://sablier.ai/auth/device?code=X7W7-GQDD)\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Waiting for approval...\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Logged in as you@example.com.\n", "API key prefix: sk_live_A5cM...\n", "Endpoint: https://flow.sablier.ai/v1\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "logged in as: you@example.com (tier: pro)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "credit balance: 10000 credits available\n" ] } ], "source": [ "# Interactive login. Opens a browser, prompts you to confirm a short code,\n", "# writes the minted key to ~/.sablier/credentials. Subsequent sf.Client() /\n", "# sf.fit() / sf.generate() / sf.validate() calls pick it up automatically.\n", "#\n", "# CI alternative: set SABLIER_FLOW_API_KEY in the environment and skip this\n", "# cell \u2014 the SDK reads env vars before the credentials file.\n", "if not os.environ.get('SABLIER_FLOW_API_KEY'):\n", " sf.login()\n", "\n", "# Sanity check: whoami() confirms the key resolves on the server side.\n", "me = sf.whoami()\n", "print(f'logged in as: {me.get(\"email\") or me.get(\"user_id\")} (tier: {me.get(\"tier\")})')\n", "print(f'credit balance: {sf.credits().available} credits available')" ] }, { "cell_type": "markdown", "id": "d06e4a9b", "metadata": {}, "source": [ "## Step 1 \u2014 Load your data\n", "\n", "Any `pd.DataFrame` with a `DatetimeIndex` and one numeric column per feature (ticker, yield, vol-surface point, factor returns \u2014 whatever your strategy trades). Load it however you load data today: `pd.read_parquet`, ArcticDB, kdb+/PyKX, Bloomberg BQuant, Snowflake, your internal warehouse, yfinance.\n", "\n", "Below we use the bundled demo (`us_equities_macro_2010_2023`: 4 equity ETFs + VIX/10Y/DXY macro series, 2010-2023, no network) so the notebook runs end-to-end with zero setup. Replace this line with your own loader once you've seen it work \u2014 the macro features are conditioning signal that helps the model capture vol regimes; if your strategy already trades a richer universe, drop those in instead.\n", "\n", "**On `data_types=`.** every `fit / generate / validate` call requires a per-column annotation telling the SDK how to transform that column (log-return for 'price' columns, difference + z-score for 'level' columns, identity for 'return' columns). The allowed values are `{'price', 'return', 'level', 'price', 'level'}`. The bundled demo attaches the canonical map on `df.attrs['data_types']`, so the simplest call is `sf.fit(df, features=df.columns.tolist(), data_types=df.attrs['data_types'], ...)`. For your own data, build the dict explicitly: `{'AAPL': 'price', '10Y_yield': 'level', ...}`." ] }, { "cell_type": "code", "execution_count": 4, "id": "59d8ce45", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:15:37.366755Z", "iopub.status.busy": "2026-06-01T19:15:37.366329Z", "iopub.status.idle": "2026-06-01T19:15:37.614780Z", "shell.execute_reply": "2026-06-01T19:15:37.614344Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "shape: (3522, 7) index: 2010-01-04 \u2192 2023-12-28\n", "columns: ['IWM', 'QQQ', 'SPY', 'TLT', 'VIX', 'TNX', 'DXY']\n", "data_types: {'IWM': 'price', 'QQQ': 'price', 'SPY': 'price', 'TLT': 'price', 'VIX': 'level', 'TNX': 'level', 'DXY': 'price'}\n" ] }, { "data": { "text/html": [ "
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date
2010-01-0451.36655840.29079184.79638755.92865420.0400013.84177.529999
2010-01-0551.18994140.29079185.02084456.28984819.3500003.75577.620003
2010-01-0651.14175440.04775285.08070455.53631619.1600003.80877.489998
\n", "
" ], "text/plain": [ " IWM QQQ SPY TLT VIX TNX \\\n", "date \n", "2010-01-04 51.366558 40.290791 84.796387 55.928654 20.040001 3.841 \n", "2010-01-05 51.189941 40.290791 85.020844 56.289848 19.350000 3.755 \n", "2010-01-06 51.141754 40.047752 85.080704 55.536316 19.160000 3.808 \n", "\n", " DXY \n", "date \n", "2010-01-04 77.529999 \n", "2010-01-05 77.620003 \n", "2010-01-06 77.489998 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "real = sf.demo_data() # bundled demo\n", "# real = pd.read_parquet('my_prices.parquet') # your own data\n", "# real = arctic_lib.read('US_EQUITY_DAILY').data # ArcticDB / BQuant\n", "\n", "TICKER = 'SPY' if 'SPY' in real.columns else real.columns[0]\n", "print(f'shape: {real.shape} index: {real.index[0].date()} \u2192 {real.index[-1].date()}')\n", "print(f'columns: {list(real.columns)}')\n", "# The SDK requires a per-column `data_type` annotation on every\n", "# fit/generate/validate call so the right transform is picked per column.\n", "# The bundled demo ships the canonical map on `df.attrs['data_types']` \u2014\n", "# pass it straight through and there's nothing else to configure.\n", "print(f'data_types: {real.attrs[\"data_types\"]}')\n", "real.head(3)" ] }, { "cell_type": "markdown", "id": "84e6d2f8", "metadata": {}, "source": [ "### Schema contract \u2014 what sf.fit expects\n", "\n", "Before fitting, `sf.fit` enforces these locally so an expensive training run never starts on a broken DataFrame:\n", "\n", "| Field | Requirement |\n", "|---|---|\n", "| `df.index` | `pd.DatetimeIndex`, monotonic increasing, no duplicates |\n", "| `df.columns` | numeric dtype on every column listed in `features=` \u2014 NaNs are passed through to the model (it masks); columns whose post-ffill NaN fraction exceeds 0.7 are rejected with an explicit error naming them |\n", "| values | raw prices, returns, rates, index levels, or volatility series \u2014 the server applies the right transform per column based on the `data_types=` annotation |\n", "| length | \u2265 200 rows on `fit` (shorter for `like=` / `anchor_data=` / `holdout_data=`) |\n", "| `features=` | **must match `df.columns` exactly** \u2014 every numeric column in `df` must appear in `features`, and vice versa (raises `ValueError` on mismatch; silent column subsets were a frequent footgun) |\n", "| `data_types=` | **required dict** mapping every column in `features=` to one of `{'price', 'level', 'return'}`. Tells the SDK the right transform per column \u2014 log-return for `'price'`, difference for `'level'`, identity for `'return'`. Missing the kwarg raises `TypeError`; unknown values raise `ValueError`. The bundled demo ships the canonical map on `df.attrs['data_types']` so you can pass it straight through. |\n", "| row cadence | auto-detected from the median \u0394t of `df.index`. Any uniform cadence is accepted (daily, intraday 5-min / 1-min, weekly, monthly, quarterly). Irregular indices raise. |\n", "\n", "Run `sf.validate_data(df)` to check just the schema with no network round-trip:\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "2cecc1bd", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:15:37.615890Z", "iopub.status.busy": "2026-06-01T19:15:37.615826Z", "iopub.status.idle": "2026-06-01T19:15:37.617724Z", "shell.execute_reply": "2026-06-01T19:15:37.617394Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "schema OK \u2014 3522 rows \u00d7 7 columns, index 2010-01-04 \u2192 2023-12-28\n" ] } ], "source": [ "# Pure local check \u2014 schema validation without any API call.\n", "sf.validate_data(real)\n", "print(f'schema OK \u2014 {real.shape[0]} rows \u00d7 {real.shape[1]} columns, '\n", " f'index {real.index[0].date()} \u2192 {real.index[-1].date()}')" ] }, { "cell_type": "markdown", "id": "55741ede", "metadata": {}, "source": [ "## Step 2 \u2014 Pick the backtest window\n", "\n", "You probably don't want to backtest over the entire history \u2014 pick the window your strategy will actually be evaluated against. We'll generate synthetic alternatives matching this exact window." ] }, { "cell_type": "code", "execution_count": 6, "id": "efd73b77", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:15:37.618765Z", "iopub.status.busy": "2026-06-01T19:15:37.618700Z", "iopub.status.idle": "2026-06-01T19:15:37.624199Z", "shell.execute_reply": "2026-06-01T19:15:37.623799Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "backtest_window: 249 bars, 2023-01-03 \u2192 2023-12-28\n" ] } ], "source": [ "BACKTEST_START = '2023-01-01'\n", "BACKTEST_END = '2024-01-01'\n", "\n", "backtest_window = real.loc[BACKTEST_START:BACKTEST_END]\n", "print(f'backtest_window: {len(backtest_window)} bars, '\n", " f'{backtest_window.index[0].date()} \u2192 {backtest_window.index[-1].date()}')" ] }, { "cell_type": "markdown", "id": "987141ce", "metadata": {}, "source": [ "## Step 3 \u2014 Fit a flow model on the full history\n", "\n", "`fit` trains a Sablier flow model on our hosted GPU. Pass the list of columns you want the model to learn as `features`. Every listed column is co-generated jointly \u2014 there is no target / conditioning split. Constraints and downstream analytics can address any column.\n", "\n", "By default `fit` does an 80/20 train/test split with a 21-bar embargo \u2014 the server holds out the last 20% (minus embargo) as a true OOS slice and persists it encrypted next to the model. Subsequent `validate(model_id)` uses it automatically.\n", "\n", "**Cost:** ~280 credits with this configuration (use `sf.estimate_cost('fit', ...)` for a deterministic estimate on your own data). Wall-clock varies with queue depth + GPU availability \u2014 `sf.list_jobs()` shows live progress once the job starts.\n", "\n", "The default `horizon=252` (\u22481 trading year) matches the backtest window we picked above. Longer horizons (e.g., 504) are supported but stress the model's tail calibration \u2014 see `validate(model_id)` for the quality check." ] }, { "cell_type": "code", "execution_count": 7, "id": "409a8ed2", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:15:37.625289Z", "iopub.status.busy": "2026-06-01T19:15:37.625231Z", "iopub.status.idle": "2026-06-01T19:19:27.495452Z", "shell.execute_reply": "2026-06-01T19:19:27.494192Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "sablier-flow: fitting 7 feature(s) over 3522 bars [row cadence: daily (median \u0394t=1 days 00:00:00)]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: estimated cost 177 credits (use sf.estimate_cost(...) to preview before charging).\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: actual cost 0 credits (remaining balance: 10000).\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "model_id : 53807b7d-1bf1-4c7e-8d40-88d6ff0394b0\n", "training : 2010-01-04 \u2192 2021-03-11\n", "OOS held out : 2021-04-13 \u2192 2023-12-28\n", "training_loss : 0.9470 (training_proxy)\n" ] } ], "source": [ "FEATURES = ['SPY', 'QQQ', 'IWM', 'TLT', 'VIX', 'TNX', 'DXY']\n", "\n", "fit = sf.fit(\n", " real,\n", " features=FEATURES, # all columns are co-generated jointly\n", " data_types=real.attrs['data_types'], # per-column transform annotation\n", " horizon=252, # 1y forecast; matches the backtest window above\n", " train_split=0.8, # 80% train, 20% OOS held out\n", " embargo_days=21, # 1-month gap between train end + OOS start\n", " seed=42,\n", ")\n", "print(f'model_id : {fit.model_id}')\n", "print(f'training : {fit.training_start_date} \u2192 {fit.training_end_date}')\n", "print(f'OOS held out : {fit.holdout_start_date} \u2192 {fit.holdout_end_date}')\n", "print(f'training_loss : {fit.training_loss:.4f} ({fit.loss_source})')\n", "# loss_source = 'validation' \u2192 number is true held-out inner val loss\n", "# loss_source = 'training_proxy' \u2192 val slice too short for windows; number\n", "# is best train_loss instead. The real OOS\n", "# check still happens in sf.validate() below." ] }, { "cell_type": "markdown", "id": "575e67cf", "metadata": {}, "source": [ "## Step 4 \u2014 Validate on the held-out OOS\n", "\n", "Zero-config OOS check: server uses the slice it kept aside at fit time. Same full structural-validation suite the Sablier platform's `flow_validate` runs \u2014 temporal preservation (autocorr, vol clustering, leverage effect, cross-correlation), distribution shape (CRPS, non-elliptical, tail dependence), extreme events, and per-observation calibration. Two top-line signals matter here:\n", "\n", "- **`memorization_risk`** \u2014 `'low'` is good; `'high'` means the model is reproducing training samples and synthetic paths would be biased toward in-sample\n", "- **`overall`** \u2014 `'pass'` is good (weighted quality EXCELLENT or GOOD), `'warn'` is acceptable (quality ACCEPTABLE), `'fail'` (quality POOR) means the synthetic distribution drifted from the OOS slice's structural fingerprint\n", "\n", "**Cost:** 1 credit (full suite, not the quick check).\n", "**What this verdict means / doesn't mean:**\n", "\n", "- The `pass / warn / fail` label measures whether the synthetic distribution matches the OOS slice along ~20 structural axes. **Verdict labels were consistent across N=3 seed-perturbation tests in our spot checks** \u2014 same panel + same hyperparams, different seeds, same label \u2014 but the synth Sharpe distribution shifts slightly per seed (~\u00b10.1 median, ~\u00b10.2 CI), so a strategy whose Sharpe sits exactly at the 95th-percentile boundary could flip on a different seed.\n", "- `memorization_risk='low'` \u2260 the model is good at *everything*. Read the per-metric breakdown below for the structural axes that matter to your strategy.\n", "- `memorization_nn_distance_ratio` may sit in the borderline 0.8\u20131.0 range for universes with > 10 jointly-modeled columns (curse of dimensionality on NN search). We saw 0.91 on a 14-col panel vs 1.13 on a 7-col one with identical hyperparams. Consider partitioning large universes into per-regime / per-asset-class sub-models if you see this." ] }, { "cell_type": "code", "execution_count": 8, "id": "09a90f49", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:19:27.500477Z", "iopub.status.busy": "2026-06-01T19:19:27.500266Z", "iopub.status.idle": "2026-06-01T19:21:03.122462Z", "shell.execute_reply": "2026-06-01T19:21:03.118770Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: estimated cost 1 credits (use sf.estimate_cost(...) to preview before charging).\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: actual cost 0 credits (remaining balance: 10000).\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "overall : warn\n", "memorization_risk : low\n", "memorization_nn_distance_ratio: 1.135833093331699\n", "holdout (true OOS?) : True\n", "\n", "Per-metric breakdown:\n", " [pass] acf_returns quality=good ACF of returns error: max=0.0702, mean=0.0536. Returns shoul\n", " [pass] copula_distance quality=excellent Copula CvM distance: mean=0.0297, max=0.0606. Compares depen\n", " [pass] correlation_breakdown quality=acceptable Correlation breakdown error: max=0.3402. Stress: 0.3402, Cal\n", " [pass] coverage_50 quality=good 50% coverage: mean=0.420 (expected 0.500). Mean err=0.0914, \n", " [pass] coverage_90 quality=good 90% coverage: mean=0.854 (expected 0.900). Mean err=0.0514, \n", " [pass] coverage_95 quality=good 95% coverage: mean=0.926 (expected 0.950). Mean err=0.0414, \n", " [pass] cross_correlation quality=acceptable Cross-correlation error: max=0.7196, mean=0.2888. Lead-lag r\n", " [pass] crps quality=acceptable CRPS (normalized): mean=0.5546, max=0.5744. Worst: DXY (0.57\n", " [fail] drawdown_distribution quality=poor Max drawdown KS: max=0.9309, mean=0.5377. Compares distribut\n", " [pass] energy_distance quality=excellent Normalized energy distance: 0.0000. Raw: 0.0000, scale: 0.24\n", " [pass] leverage_effect quality=good Leverage effect error: max=0.1253, mean=0.0740. Corr(r_t, vo\n", " [pass] marginal_ks quality=good Max KS statistic: 0.0958, mean: 0.0651. Worst: TLT (0.0958)\n" ] } ], "source": [ "report = sf.validate(fit.model_id, data_types=real.attrs['data_types'])\n", "print(f'overall : {report.overall}')\n", "print(f'memorization_risk : {report.memorization_risk}')\n", "print(f'memorization_nn_distance_ratio: {report.memorization_nn_distance_ratio}')\n", "print(f'holdout (true OOS?) : {report.holdout}')\n", "\n", "# Per-metric breakdown. Each entry has `passed` (bool), `quality`\n", "# ('excellent'/'good'/'acceptable'/'poor'), and a one-line `interpretation`.\n", "if report.metrics:\n", " print()\n", " print('Per-metric breakdown:')\n", " for name, m in list(report.metrics.items())[:12]:\n", " if isinstance(m, dict):\n", " q = m.get('quality', '?')\n", " status = 'pass' if m.get('passed') else 'fail'\n", " interp = (m.get('interpretation') or '')[:60]\n", " print(f' [{status}] {name:<32s} quality={q:<10s} {interp}')\n", "\n", "if report.overall == 'fail' or report.memorization_risk == 'high':\n", " print('\\nWarning: model failed OOS validation \u2014 interpret the verdict below with caution.')" ] }, { "cell_type": "markdown", "id": "444296b6", "metadata": {}, "source": [ "## Step 5 \u2014 Generate synthetic paths matching the backtest window\n", "\n", "Pass `like=backtest_window` and the server derives everything from it:\n", "- **Length** = `len(backtest_window)`\n", "- **Index** = `backtest_window.index` (synth paths overlay onto your window directly)\n", "- **Anchor** = the bar in training data right before `backtest_window.index[0]` \u2014 synth continuations start from the real price level at that date\n", "\n", "**Cost:** ~2 credits, regardless of N." ] }, { "cell_type": "code", "execution_count": 9, "id": "76018bfc", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:03.125325Z", "iopub.status.busy": "2026-06-01T19:21:03.125132Z", "iopub.status.idle": "2026-06-01T19:21:13.045867Z", "shell.execute_reply": "2026-06-01T19:21:13.045205Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: estimated cost 5 credits (use sf.estimate_cost(...) to preview before charging).\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: actual cost 0 credits (remaining balance: 10000).\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "generated 100 paths, each (249, 7)\n" ] }, { "data": { "text/html": [ "
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SPYQQQIWMTLTVIXTNXDXY
date
2023-01-03363.091370259.151855164.33082689.70986222.8968703.742697104.797699
2023-01-04361.565582258.310181164.32208389.59706924.3322073.724985105.037865
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" ], "text/plain": [ " SPY QQQ IWM TLT VIX \\\n", "date \n", "2023-01-03 363.091370 259.151855 164.330826 89.709862 22.896870 \n", "2023-01-04 361.565582 258.310181 164.322083 89.597069 24.332207 \n", "2023-01-05 360.829803 257.004700 163.526657 90.804298 24.640303 \n", "\n", " TNX DXY \n", "date \n", "2023-01-03 3.742697 104.797699 \n", "2023-01-04 3.724985 105.037865 \n", "2023-01-05 3.664825 106.166328 " ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "paths = sf.generate(\n", " fit.model_id,\n", " n_paths=100,\n", " like=backtest_window, # synth paths match length + index of backtest_window\n", " data_types=real.attrs['data_types'], # same per-column annotation as fit\n", " seed=42,\n", ")\n", "synth_dfs = paths.as_dataframes() # list[pd.DataFrame], each shape == backtest_window.shape\n", "print(f'generated {len(synth_dfs)} paths, each {synth_dfs[0].shape}')\n", "synth_dfs[0].head(3)" ] }, { "cell_type": "markdown", "id": "de17f626", "metadata": {}, "source": [ "## Step 6 \u2014 Visualize the alternative histories\n", "\n", "Real backtest window in bold black; 30 synthetic alternatives in transparent blue. Each synthetic shares the statistical fingerprint of the real series (volatility regimes, correlations, fat tails) without reproducing the specific bars." ] }, { "cell_type": "code", "execution_count": 10, "id": "a3d59366", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:13.047584Z", "iopub.status.busy": "2026-06-01T19:21:13.047461Z", "iopub.status.idle": "2026-06-01T19:21:13.179382Z", "shell.execute_reply": "2026-06-01T19:21:13.178538Z" } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(12, 5))\n", "for df in synth_dfs[:30]:\n", " ax.plot(df.index, df[TICKER], color='steelblue', alpha=0.18, linewidth=0.8)\n", "ax.plot(backtest_window.index, backtest_window[TICKER], 'k', linewidth=2.0, label=f'{TICKER} (real)')\n", "ax.set_title(f'{TICKER}: real vs 30 synthetic alternative histories')\n", "ax.legend(loc='upper left')\n", "ax.grid(alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "0d59e7df", "metadata": {}, "source": [ "## Step 7 \u2014 Backtest on each + robustness verdict\n", "\n", "Your existing backtest function. Pure pandas below; substitute backtrader / vectorbt / your in-house engine \u2014 sablier doesn't care. Run it on the real window once and on each synthetic path. Compare with `sablier_flow.robustness`.\n", "**`robust` \u2260 profitable.** The verdict measures overfit only \u2014 it's *orthogonal* to whether the strategy made money. A money-losing strategy can be `robust` (consistently bad, but not overfit); a money-making strategy can be `overfit` (alpha is realization-specific noise). The `summary()` string below makes this explicit when the real value sits outside the synth 5\u201395 CI; always read the sign of the metric separately from the verdict." ] }, { "cell_type": "code", "execution_count": 11, "id": "d629ae10", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:13.181642Z", "iopub.status.busy": "2026-06-01T19:21:13.181501Z", "iopub.status.idle": "2026-06-01T19:21:13.233822Z", "shell.execute_reply": "2026-06-01T19:21:13.231989Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "real Sharpe : +1.566\n", "synth median : +0.045\n", "synth 5/95 pct : -1.263 / +1.489\n" ] } ], "source": [ "def my_backtest(df: pd.DataFrame) -> dict:\n", " \"\"\"Trivial 10/30 SMA crossover on TICKER. Replace with your own engine.\"\"\"\n", " px = df[TICKER]\n", " fast = px.rolling(10).mean()\n", " slow = px.rolling(30).mean()\n", " # shift(1, fill_value=False) avoids pandas' fillna deprecation warning\n", " # (\"downcasting object dtype on .fillna\") which would fire once per\n", " # synthetic path in the comprehension below.\n", " pos = (fast > slow).shift(1, fill_value=False).astype(int)\n", " rets = px.pct_change().fillna(0.0) * pos\n", " sharpe = float(rets.mean() / rets.std() * np.sqrt(252)) if rets.std() > 0 else 0.0\n", " return {'sharpe': sharpe}\n", "\n", "real_result = my_backtest(backtest_window)\n", "synth_results = [my_backtest(df) for df in synth_dfs]\n", "\n", "print(f'real Sharpe : {real_result[\"sharpe\"]:+.3f}')\n", "print(f'synth median : {np.median([r[\"sharpe\"] for r in synth_results]):+.3f}')\n", "print(f'synth 5/95 pct : '\n", " f'{np.percentile([r[\"sharpe\"] for r in synth_results], 5):+.3f} / '\n", " f'{np.percentile([r[\"sharpe\"] for r in synth_results], 95):+.3f}')" ] }, { "cell_type": "code", "execution_count": 12, "id": "646937ab", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:13.237079Z", "iopub.status.busy": "2026-06-01T19:21:13.236922Z", "iopub.status.idle": "2026-06-01T19:21:14.394050Z", "shell.execute_reply": "2026-06-01T19:21:14.393635Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Highly overfit: sharpe of +1.566 exceeded 96% of alt-histories (CI [-1.263, +1.489]). Do not deploy without re-validating on out-of-sample data. This label assumes the strategy was selected from a search (one of many tested). If you ran a single fixed strategy with no parameter tuning, treat this as 'real outperformed alt-histories' (skill OR luck), not evidence of overfit \u2014 for multi-strategy overfit detection use sf.evaluate_family (CSCV-PBO). Under the realistic null, you'd need sharpe \u2265 +1.489 to clear the 95% significance bar.\n", "\n", "verdict : highly_overfit\n", "overfit_score : 96% (fraction of synth that did worse than reality)\n" ] } ], "source": [ "verdict = sf.robustness(real_result, synth_results, primary_metric='sharpe')\n", "print(verdict.summary())\n", "print()\n", "print(f'verdict : {verdict.verdict}')\n", "print(f'overfit_score : {verdict.overfit_score:.0%} (fraction of synth that did worse than reality)')" ] }, { "cell_type": "markdown", "id": "143b59da", "metadata": {}, "source": [ "## Step 8 \u2014 Forward forecasting: from realized backtest to deployment forecast\n", "\n", "Everything above is **backtest augmentation** \u2014 synth paths parallel to a past backtest window, used to ask \"would this strategy have looked overfit if history had gone differently?\"\n", "\n", "The same generator also runs **forward** from your most recent bar, used to ask \"what's the distribution of P&L I should expect when I deploy this strategy live?\"\n", "\n", "Same `fit`, same backtest function, same `as_dataframes()` loop. The only thing that changes is where the synth paths *start*:\n", "\n", "| Use case | Call | Anchor (where synth starts) |\n", "|---|---|---|\n", "| Alt-history (Steps 5\u20137) | `sf.generate(model_id, like=backtest_window)` | start of your past backtest window |\n", "| Forward forecast (Step 8) | `sf.generate(model_id, horizon=N, anchor_data=real.iloc[-200:])` | the last bar of your data \u2014 \"today\" |\n", "\n", "Pass `anchor_data` = the tail of your DataFrame (must be at least the model's `obs_length`, ~200 daily bars). The server conditions on those bars and starts the trajectory from `anchor_data.index[-1]`. Your existing backtest function doesn't know the data is forward-looking \u2014 it just sees a `pd.DataFrame` with the right columns.\n", "\n", "**Cost:** same as a regular `generate` call \u2014 ~2 credits." ] }, { "cell_type": "code", "execution_count": 13, "id": "2d381742", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:14.395447Z", "iopub.status.busy": "2026-06-01T19:21:14.395319Z", "iopub.status.idle": "2026-06-01T19:21:21.438846Z", "shell.execute_reply": "2026-06-01T19:21:21.436888Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: estimated cost 2 credits (use sf.estimate_cost(...) to preview before charging).\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: actual cost 0 credits (remaining balance: 10000).\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "generated 200 forward paths, each (60, 7)\n", "forward index runs 2023-12-29 -> 2024-03-21\n", "real ends on 2023-12-28; forward starts the next bar (continuation)\n", "\n", "expected sharpe over the next 60 bars:\n", " median : +0.277\n", " 90% CI : [-2.998, +4.800]\n", " pct above 0 : 55%\n" ] }, { "data": { "image/png": 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PfvCD6pLA6UWNJFxS1Jhpx72GuLTWLCR8UcvnW9/6lgb3P/vZz7TuEwIHoikiFaIU63/Xu9619RkEK0QAakFRPwt3EyIGdX067Y+ViG5LXQvzi+vmP/7jP7T4NaIBQgiuROfKosvl2972NnUSIRjiZqMWVSc3lt/J5ae9aPxiLHWM5dyD6wHri9sTEZIOkbgQEQZZW+ZqJSz3Grk3nJC4kjVZ7l7sFj7PdzliHd+BiEoIVXyX+68VV+HLXvayjsfgfw+AAv8ch5pvOBh5MGb258c+9rEVj9EwDMPYmJgoZRiGYZw2nLupkwBxunFpMARIiwlkuBAQKXBKIVC0OyBWwlve8hYVBnCWUYTZDy4D3D6kuywl3OFIIo2GoNTv5MCV1A24LNrPwWsE46slGrpUPOfSIOCmWD0pa+386Ec/UmdQpyLnS8FcfPOb3zypSPp1113X+ns34IAiQMYpxhpQeJwxI1Y5UYrX/AIBBbQREN/xjnfMc33heOt27G5P+R01pF/hUEM8XArGiEjAg2Lmb3rTm7QAOUKVW0vENcQ0HFK4cSiQ/Z73vEdWykrdQ8u9B5dzLu4fRF7ui+VC2izOMcQSf3op+2EpFhrfcq5xNeh2Ly537ejwiXvQpfDdcMMNWsC8/VppQNDNdfKPF6RY8kDMwj31/ve/X/76r/9a3Z+GYRjG5sFqShmGYRhrDoFvJwcFaXfLSSdbDrRN57FScO0QvBK8E/y341rXO/Gh/fpcJ6nlgnBC/SgEAwK9djgftbQIkDsF1m5cQL0t3Fb+lvWkZi2U9reW+Mflh65yBMB3u9vd5rmn6BLmF6YQ0uiI1ymVrBuYC0Qkf3t6IIWU85Mq1A0uLY/6ZjjSnIuI1xEnGbM/dc+tWfv+QOxhPN2Kt4gp//iP/6jpr46PfvSjXQlbpJe2g5ulU5oktdtwT7F/6djW7bx0IpVKdS28nco96M4FS50PcY776t///d87Cp+LOb1YR/aKf92oW4eAvBQLjW8517gadLsXu51PB05BrgWHFIItolL79xeOUmoLIuq1w3noLAjUuWpfM+f+7JTWaxiGYZzZmFPKMAzDWHNIGUEMoe08zh8Ca9Ld+Fd16hCR9rHa4AiB5RQ790OgSH0dgnQEE9JTEAZwj5ACdb/73U8FDt5HOg/F2wkqqYFCUI+DZSWQNsV5qB/0yU9+ct7fSH2hrhFOKoQ+am9RFJt6XAgPFCpG1HIiBH9jjKS9kGqGw4k0IX8b+fXijW98o9aoIqWR2jeMEWEN8Yn94Xc/4Iogpe+yyy6Tl7zkJZoihbuHayd9cCXguKD+E2IfewJ3EetE8W9SmfwFoheDcZJmhUjGuB3sgZe//OX6vF2UIgWOeUfAYq0IzFknRJ9u4PqpY4QTBacUNaLYXzh0uqkp9brXvU7T95hPXFfU7iH9DDcUDi8/FJ8nvYqabxTU5twr5e53v7veQ4ydecMNtFDtpFO5B925gEL2iCOIL7y/EwhArD3F7KlpRl0x3JqkEf/f//3fgvXrmD/2IXuYeWIeabDAtVEraTEQARkTYiauQJxWzAVz0u01rgbd7sXFxrsQ7EvSitlbrEH7PJLyS2MLxkB6MmtGQfPf/OY3KpxzX5LuR+0zvh84H3uUmmoIZ4zJ1YAzDMMwNhGnu/2fYRiGsfmhzfwzn/nMxoUXXtjo6enR1uXnnntu48orr2wcP378pFbql112WdfHptV7p3b3HIfHUrj29J3awwMt0R/+8Idre/Z4PN4455xzGk9/+tMbP/3pT1vvOXToUOOxj32stnbnfY9//OMbR44cOakVvTvXrbfeumB7df6+0MPfnp15u+KKKxp79uxpRCKRxvbt2xsPechDGh/4wAfmjf/2229vPOYxj2kkk8nG8PCwtlv/2te+tmC796VgrP5W993y9a9/vfH7v//7jZ07d+p40+l04373u5/OSb1eP+n9Bw8ebPzxH/+xtoZnz/DZG2+8sesxXnLJJSe9nslkGi960YtaYzjvvPMab3vb2046P3PD3C4E68t7PvOZz7ReK5fLOsfs7UKhMO/909PTjWc84xk6/1wL++m6667T/emfy6X24t///d83zj777EYsFmvc4x73aHz3u989af904lvf+lbjD/7gD/S6GR8/n/zkJzduuOGGju9/1KMepeP4/ve/f9LfFhoje6l9Tx07dkzvZdaav7lxLucY3d6D1WpVv09GRkYagUBAj+Novw/dfXH55Zfr+5nP/fv365qXSqVF5/LDH/6w7hs+w/cZ1+K+g/y0ry188IMf1POEQqGTrrOba+R4qVSq47gW2rPt4+h2Ly423oX23NzcXCORSOh7P/nJT3YcJ/fgVVddpd//7EXGcd/73rfx9re/Xe8h+PznP9+49NJLG6Ojo/qevXv3Np773Oc2jh492vGYhmEYxplNgP93uoUxwzAMwzAMY2OAoxH3yk033XS6h2IYhmEYxibHakoZhmEYhmEYCmlspI2RTmYYhmEYhrHWWE0pwzAMwzCMLQ41qqj59aEPfUjrSFG/yjAMwzAMY60xp5RhGIZhGMYW5zvf+Y66oxCnPvaxj2kxd8MwDMMwjLXGakoZhmEYhmEYhmEYhmEY6445pQzDMAzDMAzDMAzDMIx1x0QpwzAMwzAMwzAMwzAMY905Iwud1+t1OXLkiKTTaQkEAqd7OIZhGIZhGIZhGIZhGEaTRqMhmUxGdu7cKcFgcHOJUghSe/bsOd3DMAzDMAzDMAzDMAzDMBbg4MGDsnv37s0lSuGQchfX29t7uoez5cG5Nj4+LiMjI4sqoIaxGLaPjLXC9pZh+8hYNcplkXe8w3v+//6fSDR6Soez7ydjrbC9ZdieMU43c3NzaiZy+s2mEqVcyh6ClIlSG+N/9IrFoq6FiVKG7SNjo2HfUYbtI2NVRalYzHvOP4yugihl/w1lrAW2twzbM8ZGYamSS2ZrMQzDMAzDMAzDMAzDMNadM9IpZRiGYRiGYRjrTigk8qhHnXhuGIZhGMYpYaKUYRiGYRiGYXQDQtS97mVzZRiGYRirxKYWpWq1mlQqldM9jC2Rs848UxNhM9SUikQiErJ//TQMwzAMwzAMwzCMNWVTilKNRkOOHTsmMzMzp3soWwLmG2Eqk8ksWcTsTKG/v1+2b9++aa7HMAzDMIxVoF4XOXDAe753r8gm+Mc4wzAMwzidbEpRyglSo6OjkkwmTVhYB1GqWq1KOBw+4+eaa8nn8zI2Nqa/79ix43QPyTAMwzCMjUK1KvLRj3rPX/nKU+6+ZxiGYRhbnfBmTNlzgtTQ0NDpHs6WYDOJUpBIJPQnwhT7yFL5DMMwDMMwDMMwDGP12XSeY1dDCoeUYawUt3+sJplhGIZhGIZhGIZhrA2bTpRybAbHjnH6sP1jGIZhGIZhGIZhGGvLphWlDMMwDMMwDMMwDMMwjI2LiVKGfPjDH5ZLL7103RxIX/rSl/T5bbfdpr//8pe/XLPzffSjH9VOeo5//Md/lEc/+tFrdj7DMAzDMAzDMAzDMLrDRKkNwvj4uDzvec+TvXv3SiwWk+3bt8vDH/5w+d73vtd6z1lnnaUiDo9UKiV3u9vd5HOf+5yUSiW55JJL5DnPec5Jx33Zy14mZ599tmQymY7nLRaL8td//dfy6le/WtabPXv2yNGjR+UOd7jDup3zmc98pvz85z+X//3f/123cxqGYRiGYRiGYRiGcTImSm0QHve4x8kvfvEL+djHPiY33HCDfPnLX5YHPehBMjk5Oe99r3vd61TI4b33vOc95YlPfKL87Gc/k49//OPqCvqv//qv1nt/+MMfyjvf+U59PZ1Odzzv5z//eent7ZX73e9+C46tXC7LWkBXO8Q3uvatF9FoVP7kT/5E3v3ud6/bOQ3DMAzD2CSEQiIPe5j34LlhGIZhGKeEiVIbgJmZGXXu/O3f/q383u/9nuzbt0/uda97yVVXXSWPecxj5r0XcQkh5/zzz5f3ve99kkgk5N///d/l7ne/u/zVX/2VPOtZz9Lj4YB6xjOeIVdeeaU88IEPXPDcn/70p09KZ3v6058uf/iHfyhvfOMbZefOnXLBBRfo6wcPHpQnPOEJmg43ODgof/AHf6ApeI6f/OQn8rCHPUyGh4elr69Pz4sraSHa0/c4r3OC+R/f/va39e84wl7ykpfIrl271Cl273vfu/U3BwIcbjO65z32sY89SdQDrhfRr1AoLLEyhmEYhmEYPhCi+Ic8HiZKGYZhGMYpY6LUBqCnp0cf1FpCeOkWHEaRSKTlZEKUQrD6y7/8S3nVq16lgs6b3vSmRY/xf//3f3KPe9zjpNe/9a1vyfXXXy/f+MY35Ctf+YpUKhVNJ0QUQ0AjrZAxP+IRj2idnxTBpz3taXpMXFrnnXeePOpRj1owdbCdv/u7v1MXmHu84AUvkNHRUbnwwgv1789//vPlBz/4gQppv/71r+Xxj3+8nv/GG2/Uv//oRz9SUY73IXQh8L3hDW846Txcb7Va1fcbhmEYhmEYhmEYhnF6WFbe1Gte8xp57WtfO+81XDTXXXfdvNcajYaKEV/72tfki1/8orpuHAcOHNDaSf/zP/+jogYixpvf/OY1T+FCiDh27JisJwhEP/3pT5d8H9eOw+fZz362FuKmVhQuoyc96UlypzvdqeNnEILe8Y53yOzsrDz4wQ9uHYc0PlxT9XpdhaN4PL7geXFU8XncUO3gRPrQhz6k6W7wyU9+Uo/Ja4hd8JGPfERdU7iVGAMP9zf4wAc+oH//zne+I7//+7+/5DzgruIB//qv/yrvf//75Zvf/KbOI/uG8/HTjRfXFHuM1xHfELUQqaijBbjJvv/97+t7/OCi4jy33377kmMyDMMwDMNoUa+LHD3qPd+xQyRo/75rGIZhrB6NRmNeTL0VWLYSREFthILWATqISe9617s6TmStVpPLLrtMRQbEAtwwl19+ubp9lnL0nCoIUocPH5aNXFOKucGFhMvoP//zP+Wtb32rikCktTle/vKXqwuK9DxEvbe85S36OcfFF1+sx0Jw6uSA8uPS1zoJV3e84x1bghT86le/kptuuumk2lSM4+abb1ZB6vjx41o0HZFqbGxM1zufz6uQtByol/XUpz5V3vve97ZqXf3mN7/R4yE0+cFZNjQ0pM9/+9vfasqen/vc5z4niVJA2iNjMwzDMAzD6JpqVeSDH/Sev/KVFKu0yTMMwzBOiVq9LrlSVfKlqhTLNdk70iPBLSRMLVuUQoRCVFoI0qZw8OAQ2sG/IPn4+te/Ltdee62KWtu2bZO73OUu8vrXv16FFlxYfhFktVlszBvlnIhD1GTigbjzZ3/2Z9oVzy9KvfSlL9XfEaSYw07iH2vUjfMMMYfPT09Pd3RK+clms+rA+tSnPnXSe6khBYyLGk44lqiLRRdBRKHlFEpHPKSOFtdOKp7//BRGp6g7P/0wF8tlampKRkZGlv05wzAMwzAMwzAMwzhV5vJlyRQrUq7UJBoJSSoWlsGe2JYSpFYkSlG/h/QpBBQEB1LvKCwNOE/obEYB7k6CDPWAcOAgpjioU0Q63zXXXCN3vetdO54TN4y/1tLc3Jz+JJ2Mhx9+x/LmHv4i3KcD/xiWy0UXXaR1pvzHQEg655xzujr+UufGoYazirlHCFvs86zNZz7zGRVy6NbXDjWnSBdk7R/5yEe2CqNPTEyctBbt6+Oe47qieDo1pBA2/Z9BwMQphRvrAQ94QMexMl/UifJ/DtdZ+7Xg7OJcHHOhOXJj6rTHjLXB3bs234btLWMjYt9RRnMjSMD99wv/fXCK/41g+8pYK2xvGbZnNr47anw2L8O9cUn2xiTkSwffLPFQt9exLFGKbmfUPqKOFKl31JdCILj66qs1retFL3qR3Pe+91VhYSEXjF+QAvf7YvWeEL7aa1nB+Pi4igvt4ggXTyFrHmcCuIue/OQna30tRDvmEkfQ2972Nu0U578Od22L4YSUbq4fMYqUQYqDL/b5Jz7xiToe1hb3Fh3wSMtDNHvxi1+srrhzzz1XPvGJT6jYQ3HzV7ziFZom134sxCX/+rjnz3nOc1TIIt2O/eWg09/+/ftbc0SXQs6B4PXf//3fOmfUMPuLv/gLrcVF2iPzRpF2l7rnPz81rjgebq6F5ojXGTdrg3hnrD3MNzXOEKaCVqPDsL1lbDDsO8pQymXpyeX0aXZs7JTT92xfGWuF7S3D9szGplCuyVy+IqlAXArd9QU74+i24dmyRCnngAEKcCNSEdh/9rOfVQcNAgH1gFabq666SoUPv1Nqz549HV07iFRcfLcpbBsBioEzl+95z3vUxYOwxvWRwvbKV75y3nUQrC91Xbynm/cB57jnPe8puVyuVWS80+eZ5+9+97sqND3hCU/QOUaYopYU7i1S6j784Q/Lc5/7XL0Wxv/GN75R0w3bj8V7/evjniOOIUbd+c53njdG9tWDHvQgFUTppke6J/XBSBv8nd/5HU334/PUn6K4uivI/9CHPlQ7EvIZ//nZr1z3YvPD3xg317ZYsXhjdf/jiXRS7msTpYzVxPaWYfvIWDXKZQk0SxwkR0dXRZSy/+0z1gLbW4btmY3NVLYkyd66jPQmZLPSbRwdaJxKfpmIChoE/xTNfve73z0vmMQRw++4qSh+/Td/8zfy5S9/WetOOW699VZ1rfz85z9fMH2vHUQpBBRcFZ1EKY559tlnm5jQJY9//OO14x/i30pgC+EsQsjZ6J0CSFVESLvhhhtaIlwnbB+dnv94okD+6OioiVKG7S1jw2HfUYZCnUzXnGcVCp3bvjLWCttbhu2Zjc3R6byk4mHpTWzehhmL6TZ+TqmPLcWncfaQuoWD5te//rUKTu4B73znO+UjH/mIPqcGFV3UCDwdpFgxQGobGacH0vJWUiz8TAQn1sc//vFFBSnDMAzDMAzDMAzDWAswdZQqNYlH5jfw2qosK7/tJS95idbqIWXvyJEjWluIVCxq/ZBy06m4OUXQcS3BpZdequLTU5/6VK37Qx2pV73qVXLFFVdopzbj9HDWWWfJlVdeuSWmH1efYRiGYRjGiqAD8IMedOK5YRiGYSyTctUrAB4N2/+OLFuUOnTokApQFH9GhLr//e+v3c143g0IWF/5yle02x6uqVQqpYWrX/e619lGNgzDMAzDMM4cUcowDMMwVoC5pE5BlPr0pz+9bFtaO7isvvrVry7rOIZhGIZhGIZhGIZhGGc6xUpNYpa6tzo1pQzDMAzDMAxjy8A/uFIblcep9QoyDMMwtiiIUvGope45TJQyDMMwDMMwjG6oVET+/u+9B88NwzAMYxlUa3V9WD2pE5goZRiGYRiGYRiGYRiGsQ71pKLhoISCAZvrJiZKGYZhGIZhGIZhGIZhrEfqXmRZpb03PSZKGYZhGIZhGIZhGIZhrDFW5PxkTJTahDzoQQ+SF77whad7GIZhGIZhGIZhGIZhaK+MhpS1857JMH5sNjYQJiYZhmEYhmEYhmEYxuajVK1LMBiwIudtmChlGIZhGIZhGIZhGIaxhhTLVYlFQjbHbZgotUF4+tOfLt/5znfk7/7u7yQQCOjjtttu09fuda97SSwWkx07dsgrXvEKqVarrc/lcjm5/PLLpaenR//+jne846Rjf+ITn5B73OMekk6nZfv27fInf/InMjY21rIQnnvuufL2t7993md++ctf6hhuuummdbh6wzAMwzCMM4BQSOS+9/UePDcMwzCMZXTei5sotcVFqXJ54YdP6FnyvZXK0u9dJohR97nPfeTZz362HD16VB+RSEQe9ahHyT3veU/51a9+Jf/wD/8gH/7wh+UNb3hD63MvfelLVbj6t3/7N/n6178u3/72t+XnP//5vGNXKhV5/etfr8f40pe+pGIXIhggPD3zmc+Uj3zkI/M+w++/+7u/q4KVYRiGYRiG0RSlLr3Ue5goZRiGYSwDE6U6s7V6Eb7pTQv/7bzzRJ7ylBO/v+1tJ4tPjrPOwtp04vd3vUskn5//nte8ZllD6+vrk2g0KslkUt1M8Fd/9VeyZ88eee9736vi0YUXXihHjhyRl7/85fI3f/M3ks/nVaT65Cc/KQ95yEP0Mx/72Mdk9+7d846N6OTYv3+/vPvd71ahK5vNqsMKgYrj/fjHP1ZXFiLWP//zP5/knjIMwzAMwzAMwzAMY3lUanWp1RsSNafUFndKnWH89re/VfcUgpTjfve7n4pJhw4dkptvvlnK5bLc+973bv19cHBQLrjggnnH+dnPfiaPfvSjZe/evZrC98AHPlBfP3DggP7cuXOnXHbZZfJP//RP+vu///u/S6lUksc//vHrdKWGYRiGYRhnAI2GyMyM9+C5YRiGsWkpV2ta7ma1XFLRcEiCvtje2IpOqVe+cuG/Bdv0uZe+dOH3tm+kF75QNirUnHr4wx+uj0996lMyMjKiYhS/I2g5/uzP/kye+tSnyjvf+U5N3XviE5+ori3DMAzDMAyjCS56HPLuvyujUZsawzCMTchcoSwTc0Uh8o+EgyooRUL8DOrvPPebR7pK3YtaLcJObC1Rajn/4bBW7130MFGp1Wqt3y+66CL5whe+oOqs2/Df+9731O1Eih6uKOpO/ehHP1IXFExPT8sNN9zQckNdd911Mjk5KW95y1s0FRB++tOfnnRualelUimtW/W1r31Nvvvd767KNRmGYRiGYRiGYRjGmQLx90yuLCO9CRWScExVqnUpV+uSL1X1d1ChKnxCqHLClaNaq0uxUpNiuSbZYkWGe+On8ao2LltLlNrgnHXWWSowUYicWk9/8Rd/Ie9617vkyiuvlOc///ly/fXXy6tf/Wp58YtfLMFgUN/zrGc9S4udDw0NyejoqNah4m8OxCrErve85z3y53/+53L11Vdr0fN2QqGQ1pa66qqr5LzzztO0QcMwDMMwDMMwDMPYSuRKXhO0nnhYzSEqNMXmi1bUiHJCFQ9EJ37X94eDUnM1pMIhFbZG+uKSikVO30VtYKym1AbiJS95iYpDF198sabZUXD8q1/9qhYgv/Od76yiEiLUq171qtZn3va2t8kDHvAArRn10Ic+VO5///vL3e9+99bfOc5HP/pR+dznPqfHxTG1UAFzjk1K3zOe8Yx1uV7DMAzDMAzDMAzD2EjM5ErSn4wumJ7H64hNqXhEBnpiMtqXkN1DPXLWaFp2DialLxmVkb6E7BtNy66hlAylTZBaDHNKbSDOP/98+cEPfnCSewpRaiFwS33iE5/QhwPnlJ8nP/nJ+vDTqWDb4cOHNR3w8ssvP4WrMAzDMAzDMAzDMIwzD9LzcDj1JJbvanJiFQ+je0yUMrTT3vj4uLzmNa/Rjnvbtm2zWTEMwzAMwzAMwzC2nEsKp5N1yVs/LH3PkH/5l3+Rffv2yczMjLz1rW+1GTEMwzAMwzAMwzC2FMUyRczrkk5YZ9X1xJxShhY452EYhmEYhmEsAs1k7nnPE88NwzCMTcNMviy9yYiEgp1rSRlrg4lShmEYhmEYhtHVfzmHRS67zObKMAxjk1Gu1qRQqspIb8/pHsqWw/6JxzAMwzAMwzAMwzCMNaVSq2/YGZ7JlTVtL2Qu2HVn04pS9frG3fDGxsf2j2EYhmEYJ0H34lzOe3ToZGwYhmF0plCuysGJrDqSNhJ0pZ/NlyVXrEhfympJnQ42XfpeNBqVYDAoR44ckZGREf2d1ozG2t7I1WpVwuHwGT/XXEu5XNZuhOwj9o9hGIZhGIZSqYi87W3e81e+kv/wtIkxDMPoIsaamCsKkWKxUpNoOLQh5oyxTMwV9N8Ytg8kJRLatJ6dDc2mE6UQEs4++2w5evSoClPG+nzJ4Cxi7s90UcqRTCZl7969ek2GYRiGYRiGYRjGysCJRJiIE6lYrklv4vTOZK1el6lsSXLFqvSnotKXNCPL6WTTiVKAuwVBAfdOrbax7IGbEQSpyclJGRoa2hQiTigU2hSuL8MwDMMwDMMwjNNJtVbXek3b+xNC0vP4bOG0jqfeaMihyZzEIiHZNZQyd9QGYFOKUoCgEIlE9GGsvSjFPMfj8U0hShmGYRiGYRiGYRinDo6kZCws8WhYBaFavaEFz09Xqly2WJFwMCjb+5On5fzGyZiCYBiGYRiGYRiGYRjGqhc3z5eqMtgT88SHQEAdSqTwnS4yhYqkE2Zc2UiYKGUYhmEYhmEYhmEYxqrWHZ7MFLVmU9jniopHQypWnQ7o/Fep1iUVN1FqI7Fp0/cMwzAMwzAMwzAMw1h9walUqWn3Oh48p3xONBxsPkIqANHVjiLifuKRsEwUi6dlSebyFU0lDAWtdvBGwkQpwzAMwzAMw+gGamfe5S4nnhuGYWwB6FanAlTZE6B4BIMBiUdC+uhPxVSoKlfrKkbRba9Wq8tIX+Kk5lE4pfgbBdD9Dqq1hnpW1JOi4LqxsTBRyjAMwzAMwzC6+i/nsMgf/qHNlWEYmxoKkSNAFStV/ekKkyMopRNRGe713FDtJOabojpCXalohBS+mqQT6ydK5YpVdUhRcN3YWNiKGIZhGIZhGIZhGMYWBuFpIlOSQiBDL3sVjnBBDaZj+jO0iu5QjofgtZ4FxzOFsvS2pRIaGwMTpQzDMAzDMAyjGyiQUql4zyMRkba0FMMwjDOVqWxJf27rS0giFjkp7W41wXE1lfHOtx6QUkjK4TZL3duQWDK8YRiGYRiGYXQDgtSb3uQ9nDhlGIZxhoNoky9VtVMe6W1rKUi5YueVZl2p9SBTqGjHvdV0exmrh62KYRiGYRiGYRiGYWxRprMlSccjEl6nrnTUdoqFSeGrrfm5Gs0C5+uZKmisoSj1mte8RlVT/+PCCy/Uv01NTcmVV14pF1xwgSQSCdm7d6/85V/+pczOzs47xoEDB+Syyy6TZDIpo6Oj8tKXvlSq1eoyh20YhmEYhmEYhmEYW49iuSrjcwW5bSyjj0OTWTk2nZeJuaLM5EpSqzdW5JJaT0jho4j6WpMrVVW3SFiB881TU+qSSy6Rb37zmycOQBcSETly5Ig+3v72t8vFF18st99+u/z5n/+5vvb5z39e31Or1VSQ2r59u3z/+9+Xo0ePyuWXXy6RSETehA3aMAzDMAzDMAzDMIyTxCM6yGWKFanXG9ITj8j2/oQEgwFNhavVGlKt11VgIl1t+0BSO+YtxUyurB31wl28dzWh2Pl0rrTmLqm5fFl6zSW1uUQpRChEpXbucIc7yBe+8IXW7+ecc4688Y1vlD/90z9VJxSf+/rXvy7XXnutilrbtm2Tu9zlLvL6179eXv7yl6sLKxq1aviGYRiGYRiGYRiGUavXW0JUuVKTZCwsQ+mYJNvqPkXDoXlCDEXLD0/mVLSiRtTiQldFdg/3rPtk45Qqz9b1Gtei1hNusbHZgvanQHQzNi7LXv0bb7xRdu7cKfv375enPOUpmo63EKTu9fb2ttxUP/jBD+SOd7yjClKOhz/84TI3NyfXXHPNSq/BMAzDMAzDMAzDMM54EJUQio7N5OXAeFYFKeo97R1Jy7b+pKSW6IzH34bScRlMx+TYTEHmCuVFXVI9iUhXjqrVBiEqGg6elMJXbzS0Ux5i1UqhgPrR6Zw2SN0xmNQaVsYmcUrd+973lo9+9KNaN4rUu9e+9rXygAc8QK6++mpJp9Pz3jsxMaEuqOc85zmt144dOzZPkAL3O39biFKppA8HIhbU63V9GKcX1oAvT1sLw/aRsRGx7yjD9pGxil8oEuCf3Qkc+W/QU/zvUPt+MtYK21tnZp0oBCjS74KBgKbnDQz6U/CIt7qvFdUTC0soIOoWKpW9mlF+RxIuqUyhLLuHUq24er1jumgoKPlSReKRoBTKNcmVKuoMQ0ziWhHYSCuMhAI69nAooPMRbj46iU0IWsdnC+omw1WGVQqhy1h/ut1LyxKlHvnIR7ae3+lOd1KRat++ffLZz35WnvWsZ80TjagdRW0p0vJOlTe/+c0qgLUzPj4uxWLxlI9vnPpmwxXHl1jQ2mwato+MDYZ9Rxm2j4xVo1qV+K5d+rQ4MUFdi1M6nH0/GWuF7a0zh2yxKnPFqoowyVhIUrGwxMJBqeRFpvOnfvwIrqHjFbmtWtfjJqMhSURDMpOvCJLOtBRO256hCDnjOKiSm+i1Mz4cVHVpSLXakFq5IeU69bIa6oDyfnpCE+IdQhVdA0PNx1yhKr2JsMTrERk3qeC0kslkunrfKf0vaX9/v5x//vly0003zTvxIx7xCHVOffGLX9Qi5g5qUf34xz+ed4zjx4+3/rYQV111lbz4xS+eJ3rt2bNHRkZGND3QOL3wBYaKzXqYKGXYPjI2GvYdZdg+MlaVP/sz/bEa/wVq30/GWmF7a+NDcXK65YWDdTl3NKaCzGJpeafCzmZKGyIQbqRipS7xHlGXlHNinY49Q92n3lxJO+MhlC3n+mtOpKrVvULvzd+3b4uoy8w4/cTj8bUXpbLZrNx8883y1Kc+tSUWUSMqFovJl7/85ZMGcZ/73EeLn4+Njcno6Ki+9o1vfEOFJVxVC8HxeLTDzWIiyMaALxBbD8P2kbFRse8ow/aRsVGx7yfD9tbWAifSbL7s1XOig95AbF1qHkWp4RQJy0BPvCXmxCLh0/p9xGlG+pIr/mzEV+Dd2Hh0u4+WJUq95CUvkUc/+tGasnfkyBF59atfLaFQSJ785CerIHXppZdKPp+XT37yk/q7q/2E2sr7+DviEyLWW9/6Vq0j9apXvUquuOKKjqKTYRiGYRiGYRiGYZyJNaKo50SBJE0tU8EnIJVqXVPPluqMt5a4mkyGsRFY1l1w6NAhFaAmJydVaLr//e8vP/zhD/X5t7/9bfnRj36k7zv33HPnfe7WW2+Vs846S4Wpr3zlK/K85z1PXVOpVEqe9rSnyete97rVvSrDMAzDMAzDWG3KZZE3vcl7/spXikStzbhhGNKx2Dad7wZ6Yl59pHpD08sQo2KRkPQmFu+gZ2xN6o2GpnTSPXErdQxclij16U9/esG/PehBD1Ir4lLgsvrqV7+6nNMahmEYhmEYhmEYxoaHrnZHp/Pa7Q5BCmcUNY8qzZQ5QJiKRyz1zJjPVKYok3MFGe7trhbTZuH0+AUNwzAMwzAMwzAMYxOB8HRsOq/d4DKFiszlyxKNhLSYOMW86RSHSHWsKVr1JaOr6pjCjZUplCWdiG4pp81mETPH54q6X+gquJUwUcowDMMwDMMwDMMwTgFcULccn1PRifS8/p6YpOMd0vRiogLV8dmCFMo1GemNr0p9J0SwqWxRXPJSf8pqNp9JTNCJMRSQvuTWWzcTpQzDMAzDMAzDMIxN7UKZy1dkMB1bdRcK7qTZXEkFKcSls7f1LlkzivS93UMpFSIOTea09hTuKq/7XUAwOQVbzwNLXttkpiSVak2G017a12S2tOouLGPtyBYrKmrSTTAV33oSzda7YsMwDMMwDMMwDGPLMJ0tqSupVK1p17tQl63qF4JayvlyVbKFiszmyzJXqMhAT1zOGu3p+tiITaN9CRUkcDlR5JqC6By73vCKXgOy0mJiVb5UlXQiosciZY/PT2aK+noqHjml6zTWnlrdW6+eeET3wVasNWailGEYhmEYhmEYhrEpwUmEQLN7uEcLSR+Zysv2gaTWeVoJuVJFJueKKEVayByBaP+2tAz2rKw4NWIEj3b84pQ+p4OfPhd9riJWoyE7BpLqvHIgYPUmoyqUmSi18ZnJlSQaDrGdJBkLb0l3m4lShmEYhmEYhtENOCDOO+/Ec8MwNjwzOa/wNyIUbiJS3Y5O5VSYQgzollq9rp9F4BpKUwcqIMdnCjLSm9BUudUGcSIUEAmpV2p5cL0zuawKcp2usVSpqUMrFQtLPGqSwOmC9ckUKrJzMCljswWtA4bomYxuLXHKdqBhGIZhGIZhdPVfzmGRpzzF5sowzqCgP1esqEsKCPSHe+MynQ2oY4oaU6G24L9ZJ3weHGMqW1JH0mBPrClQlfVYnVxOpxvS+KhNRGohopkDxxUiHa8noiE5NlNQpxc1sJLR0NJurUbzNXVqub97D8QvCrhb17/u0/botpdOePuHAvnsz/HZguwb8fbrVsFEKcMwDMMwDMMwDGPTgQBDClt7qh6FxUOhgLpUFoPi06RXlap1GUhFVZTKlarqXcJ1RbrVRgX31uHJnIpo1LlCoEMEafhS/rQ2Vqmq80Bdo7mZopSCWU1N1PpWvuNpLatAs75Vs64Veh7P+ck8IajgvGJeeKw0RXKt4bortboKQfwsV+u61q5zof/KmTuEthOPoLrk/L8vl2Klps6oaCioe3FORcKwFMvUAdtaLinYuHeRYRiGYRiGYRiGYawAxAYcTruGUh3/3puI6mMhnFCzYyAlQziqzrCUXToB8kCIoni2l8YYUZEKEGH4O6Idj3KlKofLWXV/hUNejaNuOwD657xQqqrQRf2uod74onO8kIOIz2tR9+a5EX+WM47Fjkt6HGNE+EE0i4SD+lPrOfHG5ikCElBxis9pPa96Q9Mea/WqPtfXGw19uxOn9GdTsIrhHIuFW2MmXZJ14Cdr0Z+KaroeMK6eeFimc2UVO7caJkoZhmEYhmEYRjeUyyJve5v3/KUvFYmufh0ZwzBWh9mmS2o5daOcsEIhc5xFI31xScU2XnreYg6gI9N5KVdq6vXBeYO4hjBH10FcTLh0ENtwCe0ZplugJ5ogUJHSh2MnuEIBTkWeZFQLrRfKVa25xfwvp6McY2OMjMsJQv5OhIhTKlL5BDPnWlIByOlWTbMTny2WazoexoITCWFuufuiExzbCVS1Wr31vFqva7pndbag88mwEJwQtRCjqGfm5qRWr+vrvUlvn1n3PcMwDMMwDMMwFqayeLqPYRinH1xAmUJ5QZfUQpBGhZiAcLGr74Rgc6aAAIUwxXXj3GH4BydzMpCKSSQckvG5guSKVU3tKwiCVbnl1lltEGMQf47P5GXXYEpFr6VARNNOiUMnv985k/xClXMw8ZwUPH5v0XI8icSjIXVtrXY6oQpjIRxXqsh1FDizhYrcfHxOYmHv3MlYZJ7wlCtVJRoJSb5U0/pkWy11D8wpZRiGYRiGYRiGYWwaKORNOla3bhhcURNzRanWG7KtP6GCypmGV8S8JIPp+Lzrpoj5ZLYk9bqXxodghTgTK3kiFQLVWgkhOKZK1Zo6pnYMJjVtTtPkOpyP8U9kiioIIioiCPrfp24oaQpAZwjMM3sLkW1bX0JFKgrsk6rn9lieOYmGZDZfUQfVVuTMu9sMwzAMwzAMwzAMY0GXVEWLeS8FQggClqu3tL0ndkp1i04nmWJFRZxUW/H1dCKq6WvpdGReKiLiEEIPn1tu3aflMJyOy9HpvNxybE7T7XADjfTGdayNpsPJK/ydV5faaG9ChRpWgfRL1mU1Uu1OB+xDrg1RiuvlOuj4SJFz91qhVJV4JKZzsxVT98BEKcMwDMMwDMMwDGPNIc2KFDmECH+RaVK1VitVDmGD2kh0l1sM142OlC9Xb+lMxXNJlTVdrt2FxLwu5MDpS8bUXbWWohTjoY7S7eMZ2Tuc1vPxQJyilhJ/p5tdoVyT83f2S3/SGwu/UxQcZxF/5/08ukkDXAzS/WbzJanWmul/zTRAoBMe51gNtDZZpqh1yfxF8nubIuH4bFEFt3AoqPOAe2qrsnWv3DAMwzAMwzAMw1g3MQpXEkF4MhrWoD1frmrBbf6OeOIXqtxz3t+te8lfk2gxEAGOzZBG5XWjO9Pr+KhLCmdRm0tqKbTjW7aoHekSK3DpuJpJiEc4gDoVhWdtJzMl2b+tV11DdKVjH+AaIpWQnziHtvcntfaV38nFg89TB4tzTKvgGJaeRET/tlxXm+fIoq5WRdM0w5FQq3C6E5G4ntWoP0U6KKmIneZkKB2Xm47NyoGJrDr62LO7epZX/2wzYaKUYRiGYRiGYRiGsSYOnrlCRZ0x4WBQhns7d7PDvYIogEBVqdXUSYUQwWuIEmEEq3BIhYK+VLSjYOBqEuHKWcxN47rC4YqhntKZjnNJIegsV1zj/dR9olNhoj/R1WdYK0QsxBvEvUQsrK407XbYYW0RehB9RvsSrfGRYkmXQNLbkrHGokIiwhOOIh58DnGK/YTogzDF66S9LXbtbo4Qw+hyx3EQt/y1w7h6xj+VLcrhyZzuo5XU26Kb3rGZglSqNdnWn+74d0S6QENUdJ2YK6yoS+RmwkQpwzAMwzAMw+gGgpOzzjrx3DCMRZnOlSRbrC4oRs0rYh0MNWvqzH8fAgKPcq2uaU9HpnJaNLo93Q7BodGQRYUmHDKk7OFUQczYDDC/sNL0L2pOIdjgIlpM1HHpdMwhAgpuJdxGpKYhVB2cyGpKpF9c8d7vCU5+cQfREIfQ0amcClMIhN2k5fEeugXyQBDj+DifXIc99g/iJUIWp+MnoiYCFmN0dca4XhXU2vYQ+3CkNyHpBIXvC3p8HFxLjY1zZAtlFaM4V0ivLzHPyYXLayZfUscg5x3pS8iOUFAOTWRkJl/W68BZhWjVm1ibjogbFROlDMMwDMMwDKMbIhGRpz/d5sowugCBYi7vFRxfqr7TYiAI8IhrPR7RoJ7g3y8sIVohNCCSLORs4XPUm6LGz2IC2ZkEYhHC30pcUn4hhnlE1At0WENEI4Qoqi6R7uhS7tqPgWuJ9R7u9f6Gyw2BhqLmnUQd3G7UuuL4dAjsBsQfz03nueoQmnDRZYpVGZsrSrlSk8GeuCRiIRUoeT9oEft0XEUirsW7tvqC59EuhYMpdTQdnsqpMNW+hzk3rjtcW9SHKlaqKq5dvGdAz3dwIqeOMvYaTrCbj8/qMUgXjUXCKgKWC2UVpPjcrcfn9LzFak3uvn/klGtnnUmYKGUYhmEYhmEYhmGsKlMZr5j1qQhSnSDdjLQnUvAQTRCnEJsQRdqdLw4cL7znTC9ovtouKQfuMgqRx2qe0JMtlrVOFSIPqWXDvQktHr+Y8MUx6LKHwELNeuf84fMLgbg1lD55fyA6sbYUIz8hQtWkWm+osOSvO8a6Mz5qiXN+BKA9wz36PkQ7ZCm/Y4lj8TtOqcXgWnH4hXMBPS7iGm6sXKkq+aInRiEs8b7R/rg6rPxiHeITohbnuv7wtIpTFHL3F/RHKA2HgiqAUV/t17dOys6hpZ1Zm43Nc0cahmEYhmEYhmEYpx3cKKVqTVOU1gLEp52DSRWmMsWMNOoNFSI60XLs9CEqbI7wF+Eog8smV1ZR7lQLtSOCUCT9yPGylEJZnSfcPqn+ZNddEREfEYlYe1xICEKMbbngnCJ1zhW555iIW9GQJ0b6O9kB6W7MA5+LhoMym6/ITUdnVVCi0127wMPcIWQhVPJ8qetDWCV18dpD0xILByURi0itVpdwOCh7+hIqxnUSkZi/w1NZ71pCQTlvR99J52IM6aZox7ztGExKKOClQ65WN8ozgc1xVxqGYRiGYRjGWlMui7zrXd7zF75QJHrmF0k2znxwlBDc9qxisWTnMOFn3cuA6robmddtraiOmdUMrDluoVRVtwzjInBHhKCWUf8C5+J947MFnZvNkLLHNbsuhlw76YoLucOWC+s1N0PaWlLi0ciKXWzU/EKgIs1vud3xXDoizqelan75xSgcTC5NlHsgX/KEMfYGTi3EMbc/ECmZMzo1cu/w3HOHVaReZ797DzL/1LFFx8BISIbTce3YyOt7R3qkN7nw/mZspPRxz8xVKrJzYL77yRXlJ+00FQ9rmp+rvbXVXFJgopRhGIZhGIZhdEs+b3NlbBhIQSJQJhCfzeXUAUIR6EgoMC8AJkCn/g1BdqvWTvOn+90JUE6QcrgjDTWdJ0tBWhOFnrt571IgFpCORdCOIOXcM4gdLo3rnO19kimWNVUKd4wfxBuOMZg+swtHr6UY5UBAobbTqQiboVBABcmLdvd3LWL6ITVuqXTEhcQoB931EJhIp+O9uOnYQ/76Y+FQQKKRkN4/3BOkmjKv7Cf2FWITP5mLeCSoaZL87cJdA5raWKp0rkdFOh8ONgQm0h13D6fVuVXzvZ17bWymINV6XXYOeh0HcfIhnG1FQQpMlDIMwzAMwzAMwzjDwOlBwW9a1yNEEWwjWlD/JhqmoHNVGrOFVgBNAE/g7XUmO9Gd7MTPgApQ/t8xgvCToJ4aQQghi4kN/uLmqylE4XSiRs9Cggmd4OjkNpML6FwAggPiBcW0l+vYWU9YMzqz4ZjhOil27dLxlitGsSecOLfatbyWAgFoYrag812p+WXN7kHQ7E9GO6YjtotRnMfr1jgf9gh7hnQ4nFsItexL19WROlXhZgrgAVx2qVjH4vfsH+4l5hGBi+NAXyqqotLR6Zxs62dveSmHPFgv1tAJZYhNPEcUZm0Y17HpggSDAdkxkFLx6/hMXq9js3SDXAkmShmGYRiGYRiGYZxBOJEIB5BzJOGywG2BSIXIMVmuyVA4KAM9ca2Fcyp1hwjIEU1ckL3axc1bQlSxoo4uhAXOt5gQ1amT25GpvNYc4rPMD/V+OgkXGwWum7VizRBLGDOrRE0nUslw3nQjRrm0NwRBFUMyRS2evRgINauZ7okjiXFzLYcnc1JLk97WvfMHEVJFnTZxplsxyg/3xGy+pKIU1zhXKDePRdpnXWZzZZnJliQUCGjKXCfRkvlk+Ah8fiGW9472xeXQVE5+ffuk9MTCmspH+iP3iTsW58GxRe0z9jZrghORsVM0nfuRaypWajqGrYyJUoZhGIZhGIZhGGcIBLqIQwTLCEDtIAQg5lR7Y+oCCS5DGFiMwZ64HJ7MqnOHYL8d0raWU9wcgQAhgk5mfiGKNMGVpH7xecQbxJFsMaRuFASSjQzCCV3lKKSN2Ndfi6owdWgyK7VaQ/p7oiqsLVabi/QzPoMwhACCOHloIquCx0LuG4QwRJdYOKRr2W33PlfLiwfpZ4yR5wgrpKWxJxFlEKc4v3OtdQPCE9fqF3WWK0Y52EfsR8YViwSlPFdrjr3eEu7O2pZWEZP01VaOajO9DsHq5mNzsr0/qXOJgMRnAgGvGyDOJ/boUDomlWpD0x7buwwyds+d6ArAV6UnHtL7yK0bYxzpo97V1kzbc5goZRiGYRiGYRiGsQEhiCb9jlQiBB9+EkSP9p1IJ1ovEEYQnBB9ErETaXz1ZjFxAnVq5CwkoPA+ikYjFCDCkM5EXR+6vq1UiGoHNxHCCME+YznVrnRrCemWCCSBIKmWFXUXIVQgfly0e0AFGBw2iJAzk6VWGiMPhCcV9YoVmcqWVHxCiHTXO5iOy1SmqOJMuwuIeScdkOLbrBkpc1PZojp++J1zkvCJUwv3lopPCFE17ycaDmvMgzQ46kh56WeeIAWINKwBIlM3a8CYEHvS/VE9B2NSMSqyPDHKwTiYJwRU7hXGwLUxpkqtpmITcxgOBlrFzhGtOCdiHXt0e39Cztneq/fgdLasc8Ra8JlIOKTnYK1CgYbcNpaR0f6EFkPnXF53xIqOHXiNwu8OzkUK4GYpwH+qmChlGIZhGIZhGIbRxBVHTieip63OiwvMCaoJngl+CZypt4OQc7pqJDEGfxofc0XdHZxOCBi/vHVC6+wQuHvChSc0IaYR/ONe4loQ1NrTolYLJ9xsdHDSBMQrLl8u12SuUJGLdvVJwidS4L7h4dIbKaJNdzvmmi2Ay6mTQOkEGRxRpHQ6OI6mffbE1M0Uj3rH4NgzuaKMzZVEYkWJhMMt4Yk11/UMBZtClFdvbDEYz0TGW3fO081cUKAc4fLYNCmYgRWJUX44npdG6NXXms4WVcBjPhCXtONeqSKlyZqk41Ep1+pqmEJYmsmXtVkA+1yFqFBA9/U5ceYlqKISAiKCMfua++Cmo3NycDyr4pQTrBYaP+MAnFaGiVKGYRiGYRiG0R0EYjt3nnhubEpo5Q44I0gvo/7LeqbX4LDg3Ag2uCtWs+5Ptd5oFjM/UcR8pWl8pDWNzxW0YxoBPCIe9YBImSMo1xSvZtsxikMTpK+FCHUmgpCBwITYEao3ZLQ/LsVKXSr1hiQ6rBviDsIfbh9EQUrSN5pupoUy+xBfELAQVt0eYr0QNdvTLxGR4pGkBMsJGR3qOeWUT/YVgkyxC1GKa+N9PYmwikjtrq+VwjVzrYhKzOEtYxntiMccOrdZIhLWfcr1p0Oe4IYr6vbxjGzvS0o6GekojjE2Pb7Oa0TnevdQjxycyOq19CWiHVNcAXcb9zj39kZ28q0n5pQyDMMwDMMwjG6IRESe85wtMVcEcpp+0u+lvmwVcCfhmPCKRDe0k9nBiZwKU+01Y1YbgtnJuaLUqM2TXt3zkR41xrFrdRUzHO0C1fxufPNfU5dMM+WJ9L1rDkxJMhbRVChcJIgJ1EKiePRaz9WZjqs3VCzXdE7jkbAkYwFNuUMwYc5Zs2zR60LIOqV8Xd0cOHkQBTsJP7wPoZDi8wgrOKdIn9w11LMu18j5EZy6uedgYq40r3D/akBqKB32JuYoIO8VKEfwGkonWmOkayOup7mC5/ZDMKQ2177h9LK++1jHfaNpdaJxL6c7vIfzjM8V9fukk0BbrtY0tdKlAW4VTJQyDMMwDMMwDGNekKipRQE6YlGcd2sIDIgAXDeBv1cXiSA2oQIdgWSmWJFkNKy1feiItlruKdxEpPOQQoXLCIfFaqXn4RChjo5XdNormg2kjPE30qWoUYVQ5f+99XrztXrdc7SwH3CWUEMKx87Zo73adczVkSLIJyA3UWphmEfWOhnzUjLHZr1i23tHemR8tiG3j2V0Plkj7r1tfYkF3UYIW3SSWwjWBveOu6cRmRcrmr6a4C5CCFuMUqUqh6dympZKDbBuUv26gT3LvFAfqlSuyv7RtNQa0rx3Qzof7GXcZ+OZot5zFGXHSXVoMteqQ7VcuG9ZL85LGmLYOQjjESmUKjLR7E7Zfn80KK6eK6sghbjbVnt902OilGEYhmEYhmEYTQGDYK2iwgziAkHSVhClqAnjau34nSjA9ROsEjQiJpTzdRWSvC5jXnv3lQhULnBmjkkfoi08bouVrl17EF2q1jXgD4VC6vzwpwGG9K2BFc8Vjqsdg6Q1zQ8n6eZGsG8sDAIkgh7d2Kh7RC0p9hLOM9wz+XJVztvRrx3xlhJG2Jdjs9Q0anQUm3iNPT2RKbbqSK0XpM6RLsq90mlfs2dvVQEuKHtG0quS2skxuZ94cDyKue8b6dFzHBjPaFc9REHEZRxZiE/RUFBFKQRC50o7lVpWrBkprohcrDFpmpNzBXUqss7DvfPrSBXKVXW88bd2J9xWwUQpwzAMwzAMw+iGSkXkfe/znl9xhZfOt0lAIEGUIYDEsUBAh6uAQslaF2aTB0rUkSJgX6gODEGtv2A080W3MIJf6uCM9i+vKDN1ZSazJU11O9WCzqwPtYPghMOqoelQ+/cMyEDP6qYCaVc0imS3CVJAQO2KOBsyryC2dlCs1PT3RDSqLhrEiHypoi6pXKEqe0fTKlTSIS4QWPr7hX3JvVqsVBfs4obzhgLzpLKtJ+xFHIVcc7so5Qqas5foNHiqgpQ/1ZGOgCO984u/sw65clUOT+fkXueMzLsnEM8YI6IU48HZtBr3C9fP3POgyPrhqbym5f320Ix+zwykYjoPxXJNHW10LORevuXYrJy1rfe0NTM4HZgoZRiGYRiGYRjdQI7NzMyJ52cQBGXa1r3upWO1njd/EtQS4O4YSLUcFy6oIgUn3tdefnkT1pHqO9GyfSlcdy2cFnyeABvRaqlufdSMwY3GT9wUq9HdD4ELNxeBLesM6k6pxNStsZqCFMdnP/gFOj+IELyH61utAu1nCohNbv4RGnDAFMq11rywXyj4jgB5ZNqrY3TzsVk5b2ef7B1O6z6iphhdCen+iJOnG+ccYgrnW0iUYv1Pl9uxUzon3zfHZvIqJI30JVY8NvYYqbWIUXyPLZTqyPsQ3CvVmvQnojLYrCflYD0ofo4DsFCqLri3TwUEaNJnER+Zj7GZgq73UE9cBgaiuk9wNZJqu5XEKIeJUoZhGIZhGIaxCSDIczV/nNhE0ex6U4gCAh7X6j3ofgYCGgAjkLQLGPyLPl3Wqj2xFaeWnVl1pJYPwg8CDIGvJzadLAQR8NLViyCaeUbMWq3aPqQUck6/24Ri5GuxXqSWgd+FclJXsmaQf7pEKYQhAn/EmvUCh81t43NeemelrmvBHJGm53W2C0s0EtT0RvbAkam8pu71J2Oya9ArPE69L+5fjuHSRRGolmKpulKnE0SpbKHS+h2xFEGKvUkKHQXzlwNCHiIsc0hRcuZ2KB3TY3USX3Ey4vZkruORlNx8fE5f5/vQiT/sU9bPOQBXu0Mk3zETs0W5cHe/inM8+M6gLlu2VJG5AkXvw3oNxWaqsH5dbyFtykQpwzAMwzAMw9gEEMS6IFUFp8DJ4tNyXTMEaASOBHdr4SDYqHWklgvBMXWbcLggLDDfzLTrXIcTgnWhDfxqBr2IYAT6yw3uV8pcvqJC5WL7COGFdKjT4c7RNNSZgopnrCvB/1qDcwznUyQUkot2pVVUYH6cIxGBjvlASEFUocMedchQHnpT0dbe4zO8jmDFvUbHOJxVS+2XpepKnU5wIdH9zznIjk7n9XoHUlEtKI5Tqpv7lNpMzJ9Ls2NduecWchVxT5AaiQOS4u6IPhQfl7rI8Zm8Cn+7h3t0bmORoK4L33G4F1cT1gQHFOKkPzWYdSJtl3TDaDik4yAFN+j1w9xw67jWmChlGIZhGIZhGJsABAocOKtdzJjOWMdmCpoetplSS8aWqCO1XAguEZ1IpfK61lHZyeti5woprzaeq2bh4Hy19xeuj9G+xQN3RAfcH+sNAgCCA1Dgmj1LSupqpEguBEIGIpPnNvTqB7ULdgnf9qJ+FGIVogqfwx3lXzv2EGlepHYhZODy4Z4+1bpSpwsnqHmpjd4aIbwhoCOkLuTmY47Y27isSINkT2l6nnYPXFykQ+ihRhyiFSm5TuDJFsq6LzluKBSUcqWm4+N4jXpDClXSDFf3HkVYxK1KjatO96hbr7lCWQU3NKnNJv53g4lShmEYhmEYhnGGQ7BHpyuKk682LqWFAHG1BJzTDUE/gfLoMupIdQOB50KpbWsBAfZ6OZJwSZF6tJQooM6TjFdfaTXrWS3lpjk2jQgVkNF+TwBAwMC5xmuruSbca7h2xucKWh8sFg7qOnDvHZzISn9PTNLx+eIUzh0KwPO+oZ7YosXiXRofIg6CDGLFUk6+pepKdYPXbbMiw6S2yerAHLi6Uq62FtCRbqhDaiJzy73J/FAInr3N+7pxF3IOXGvMMWmP7r7gPqdWF4X/cU0hCGrxeUQo8d7TaC7Vaoq7CE2MibS8xfZfrY57rqTnRqjb7E0lOrGs/faa17xGN5b/ceGFF7b+XiwW5YorrpChoSHp6emRxz3ucXL8+PF5xzhw4IBcdtllkkwmZXR0VF760pdKtWptQw3DMAzDMAxjpRBkebWi1qbuE2IUrpDNVEeKoshncpoMAby2t18HEcwJMd2Ikn53zHqA4EPKG6IQQpQTFhBqECdI0XSiyKk6xXBi3Xh0Rg5NZiVfrMq529M6J5fsGZCzR3tlMB3X+k4HJ3MqrOD4we1EqhrsHsK5E9SUWh6dxCaXxkfKJ3Wo+PxSkBqKKLVSqNNEsX4tuD2Z03tktUCkZJ9Sa4vr5Rwk8yHWOBAwEaMQ9ehqSY233UM9KiAtJkixL/leYj0YP2s/0hdvdRPleDxCIW9Oh/sSLZGPtEqHS7VdLdgrCE2kA3I9i6XXTqoghatSNOV0K7Lsb7BLLrlEvvnNb544QPjEIV70ohfJf/zHf8jnPvc56evrk+c///nyR3/0R/K9731P/16r1VSQ2r59u3z/+9+Xo0ePyuWXXy6RSETe9KY3rdY1GYZhGIZhGMbqQ9AyMnLi+QaCwGe1C/T66YmHZSpL+/rqujqBNnIdqdMNa0G613oUoEe0YH914+LQYudh0snWvgMf4sOR6bzWVRpOx09yZuGWcWl9CB3djofjIlogLmTyZe2ehsjEniG9biDldTvkGiOhWkus43ypWFg7wlHDiPQtCr9TP4i5c+IL+298riix3s5r59L4ELjq0lDH1GLpn/66Uuxx1qpbl5orBo6Yk2jEJN5M1+VaBtOnnrLLnHF8rwug9z3i6jjhBtM6W1lPmCFVsZvvF0SzuUJF9yV7TesyhRuaupdtvoZQ1xOP6/kRnw+MZyQdjch0rtyc2xMinqbarlJDVdaY9EFSObkm7s9O382IqezLYqUm4WBQx7QZm0l0w7L/FwURClGpndnZWfnwhz8s//zP/ywPfvCD9bWPfOQjctFFF8kPf/hD+Z3f+R35+te/Ltdee62KWtu2bZO73OUu8vrXv15e/vKXqwsrGt0cdmDDMAzDMAxjExKJiFxxhWxECJ7XUgAINDv0EWi7Qs5nGgSLq11H6nRCfaL1cUnVZSZfloFlFA1XJ0qlLtKhHBJOFR6d6i8tF9K1EByo2bMQpMMhACAC7RpMnbQnEEWcAOX9bD7XcdYF8yEpefu39c4rro1wNTPtFSX3XwfPuTYEmFK1Pk/IQ6zi7+Gwdw8tds9qGl+xKuVaTUWbXYPhJetKTWYLki10X+R9MlNUEQfRLBoKSC4Q0PP2JKLaHU6LkffGT6kemit8T3ox64WDiBTLYtmr/8X6sbeYr8X2A/vQdcmr1uvaYRJ3XKWGEFfV1NLRvqjOd/txWGfOz/oxl/yjAr9zTHxSAWnoOq9GsXhEPmrJsQYTGa+2Fbj9xV7kPZPNQuzRcFAddpvhO2mlLHt33XjjjbJz506Jx+Nyn/vcR9785jfL3r175Wc/+5lUKhV56EMf2novqX387Qc/+IGKUvy84x3vqIKU4+EPf7g873nPk2uuuUbuete7djxnqVTSh2NurtnKsV7Xh3F6YQ20mKOthWH7yNiA2HeUYfvI2ArfT6VKVdNh1vK/x9KJsOSKZTk2nVNHw5kmTOFQKVeqsnMwdcb/dyv7BpdI70Ck47Ws1t5CsCEtCpEpGQ12fbxIKKCBd70+P9BmTMdncs3aQUV1G620DhLHmM7SyS6x5LgQPFh/MnfcvsW9g9jGbwgDCBx0rAySSNVoqFNo1yDikk880wL2nqWG46FfINIudH6EHv/fZnNFPV6hVJFYeP7fOjGU9rrUZSs4tsIqvCwEwsqhiazsG05rEfV4xHMQLejmmSuqWETKoxun2zOIXNRfQkQ62uweRyraSgQbPlJnvTNF6e+Jyr7RlOwcOLmWG+d2Xfr84BJzYhRz78YQCgRVLEv1hOe5Hjsdx3NlNXQs7E2+B0IBz3EFOJT4W75UPqW6XF7aXlFdeZwPl10yGpKDExl1s7KNcHjxN+Y9FQvJ9UdmpVqrzdtbm4Vuvy+WJUrd+973lo9+9KNywQUXaOrda1/7WnnAAx4gV199tRw7dkydTv39/fM+gwDF34CffkHK/d39bSEQvjhXO+Pj41rHyjj9mw2nnN7oa1THwNj82D4ybG8ZGxn7jjI2+r46NlOUwVREitm1TZcKkgqVKcnEZECGe6JnjDBFisxEpiyjvTGZnPAcGmcy1OWhLlZSCmu2t3B1jGdKmo4WS0ZkfDzT9WdxgxybLUm4kp23RyikXUAI6Y1JrlCTGya8tMD+ZKRVBLtbOFaRej2NgmSXeC/zMDVdlGgtp+ebyXtpXnSWRHApFesyW6xKvlxTMScdD0s0EJJCRvTRDiLLkZmiDKejMjbm1YvqZj7H5kqysz8u03muOyCB8lIjF6kXK1qkOzc3Izv6T05RdALdbeM5vc4bchnpiYXkuplp2dYX6+gamsyW1Sk0ko7JzFR+0T0TJc1srCKHj9ZlIEUXyeV/x0xP5XQ/1MsxCffGZKyy+JxxPRR7ny1UtVYWl4AYxbkRefgZqQWlmmcfdFnEPVeRcSnIXK4smVnR6y/lgq21YZ7ymYDuxZWggutsSVMTxypZmc5V5PB0QXYOxLXwPV34MgXSMIPSl4hIo1SVY7NVidZrMjdTlBvymRWfe6OSyWRWX5R65CMf2Xp+pzvdSUWqffv2yWc/+1lJJBZvVXkqXHXVVfLiF794nlNqz549MjIyIr29vWt2XqM7+ALTgnwjIyZKGSvG9pGxVtjeMmwfGatGpSLywQ96z5/9bC+dbwN8P/Gv67lGRnaN9KxZoXM/I6MNOTaTJ0rU1J6NLkyRooPb5Ny9sVaKDHNG4Iu4oD8bbc8bjSWLLK/HuHFX4AJpn+OJuaKkekULea/F3qJeFbW3zt490FUaWCcq4Yz09Xu1lJyLJC952TuQbDlbtFB1rqTukZi6cWJd7WE+V5jMyu6+RNepZZVwTuv2IOjFg1VJpXE7lSVbaEgiGpXRES+Faqk1V1EnU5Kd8bRs709Kt7Bme3oa6uwqT2S7TosbaTQkPpXzRMjeHkknTnafHZ3Oy9m7e7RIOWt39siACi2RmDenfuga2BummDiF/oNd7ZmdzY55pL4FYst3TU2WpyVWycq2kT7ZO5I+qU4Vex3xCedWvlyVqUJJGo2QJHqSsj2JWy2qaXArvR9xWUWSFRkdSEpCXVdlnXvSALnvXd2pTJH3pFoOLZxifanYorXUmH/GTffHWiQk0WRU6nR8DNXlDoODsme4RwXQaw9OS2+Pt/ddDlgsFZB9u5IqurGGCTo3tq3vmQzZdd1wSknIuKLOP/98uemmm+RhD3uYlMtlmZmZmeeWovueq0HFzx//+MfzjuG683WqU+WIxWL6aIebxZw5GwO+wGw9DNtHxkbFvqMM20fGKm0CkYmJE89XQQBaje+nSqUmoRCFftenADlDJQWOIArHxUYQpkgVI9CkNo1LcfLSfspyfMZzE0XCIZklBahOxRcPAlECZDqhuecE6o06wltBRYfFCqKTFrQawlW12aKeOkzeT68GD+OhYDPpkv5AHufHcG9i0X2z0r1FAI/oMtqf1FSzlZKIRqRaa0gw5p1/OlfUAD/hS49iaMN9SenrqWva0+GpggpHiEOLFdieyVMbLCKpePcBPLXExuaKug+oA3XTsTl1sLDu7Anu6dAi84VQydxoF8pGQ+sw+d/LGi5UqJrP4sLiurhvED92D/d0vTbbB1KSLdbUaZVOzi8+jngYCAZlR39Cfn37tDp1ipW67BxMaldC6kM5UYUaUqVqQ+/fTmNdbM/0peI634hrXMNQb7zrVLdCxRO8epNxCYdCet8gQnGPspeZOy1OHgkLTRsHUnEZSJPaGV4VoZ3lZd25LjrhIa71R0NSyHnF4QfS7DeRqWxZx8n4xudKKoRRhy7ZFPeYs3pThNKxN4U0joGAheBGTS7SJg9P5bS2GN81Nx+f0/miQyNLxzlYQf/35o6BlH7nRCPhU6rhtZHodn+f0tVms1m5+eab5alPfarc/e531y563/rWt+Rxj3uc/v3666+XAwcOaO0p4Ocb3/hGGRsbk9HRUX3tG9/4hrqdLr744lMZimEYhmEYhmFsSXBELDf16VQhUKRuCsEpAR5B/ukCBw71gXqTEQ26cZQQDDKuWlMoIOBjjuaLT4sLadQM4vroStYp+J4rlDVAJ4BESOk2kHQFjwlm3U/cFtQ0IpjV4+HYadYDokMX46DGD/PO+wmyV5JGtRRcM/NHvZtTDYyjKo7UhLwWxJxKtabiWicQ9rb1J7XGD4IYAT7FnzuJYrhq5vJece5uYX5ZL+pwXbInLbePZ3T9942m9dysCdeNo469gzvM7Q8EEz7LOXkv4gRiiV9Q4LjHZwuyrS/Rse4TThmERleYnTU8NJHT62Pf+ms/aU2k5k+vK5z3c7AnquIG696XjHkOnWpN52zXUEprRHlFw+Pahc518KNgOX+nkx/j3LGAINUNfI55Zz7oMJeLVfXeX+xeYv6yxbKKPpyfAv2IOHQl1K6Jvg557JNcKSC7h1Kr6vr0i8fMC+dCMC2UqhIKed0i+U5gTUkbRCBFXKLmGXuD+++ag3mv018kKJEg3f3C0pOIyFDa66Q4lO7V97s9qvW6+hK61xDaEKQWm/d4NKxziYiOu+pUC66fSSzrm+YlL3mJPPrRj9aUvSNHjsirX/1q/VeZJz/5ydLX1yfPetazNM1ucHBQhaYrr7xShSiKnMOll16q4hMi1lvf+latI/WqV71Krrjiio5OKMMwDMMwDMMwFqdSq6mgsd4QNCIyHG4G8mvZ/W8xEDG0fX1PXMUEAv8bjsyqY4RUmP3DPYu6nRbCpe8RfNd6Gid1xyLIR6CgNjGBJGuACNAuYCEaEOg6EQoxgbkiuEXcIJB1QXEnEP8Ieg9PecIU6Vlr0QHRdWLjfCuZr3Y4Rr5UUgFiKkv9paVTvgjMdw2FVZxAGMCVRKDuT59CPOL3xVKq2kUR3ES43/qTMcmWKjKRKckFO/vmCRXsZdYIgfPgRLYl+ul8x8I694yvHYQ31oc9OJn13DXta3N4Iid1acie/h493lkjvSposFdxM/F29pETpBzOTeOmDX/N9Udm5MKdAyqmsGfUsRUIyMGJnJw10iPlWkPP0ergV6rK0am8CjO4p1bD2UcnThor0F3u0GRW00gXck0hdHJRkVBI52rviHc/tu93xsceRARe7TRk9iC1nBw49tjrdO7zipx7Y+GeZO3Zc6wPbifExBBiZDqmIlagITLQE9fvPGBvsy7c+458qaZdB2ebTs077B3oSghMJyISDi0tmG9pUerQoUMqQE1OTmqu6f3vf3/54Q9/qM/hne98p1q0cErRLY/Oen//93/f+jwC1le+8hXttodYlUql5GlPe5q87nWvW/0rMwzDMAzDMIwtAELH6Ur3IJgneEMoWMgFs5a0O3Cc24EgmQCP4PdUBBZcLwSIpNUQNDsHDU4U0ngI+jlfXyqqAgPOqUy4ok4j0u8QVqhhhGCBQIZQhiiwHEGJ93J9BL8IGLi9SFNcLVwnNgQD0rpWKlowH6Q0IShQxJugnL05kSno88U6x7XD2lGAHOGP7n8ufYppY80RzroBZw7XxrH2jPSoE+rW43My3BPrWCuLvcJalmbyctt4Rse9e6hH3TCd1ow9gZMNYZG9gECLkOaOzdwemc5rl7+77h/S9DREL/aCCmt9CRVMOI7TIdwe5vf2cyJA/eq2Sd2D/npWY7N5rY901ra03HxsToVQ5w4ivRZRjjlbTeFYXVP9SV0PzklHvU41zqYyJX0vYhvfFZ2+q5gnxsh9cird79rBsZQrVnVf+kUj9hfrUKRraSzcGkO2UFERkzmbzpW0GyOuJb+ghJiFC5P7nX2Fgw6xj7Vy52MPIHDdfHRO9086Eet6v05kivqZrSRMLet/vT796U8vWcjqfe97nz4WApfVV7/61eWc1jAMwzAMwzCMBSDw702cvoLcCCQE+7hMVsNh0y0EgCecFYF5qXwLuVpWAsch6ETcODCeUXGFFCSEBycaICTwO24qnCOkWYWDQQ14SUVaabqUH5xgHIcgPxlb/jwTRFNEmjpKzs2DIIIYgKC0azC5YoeKuoVwIzWdPhyXOaGodqUak/3bTzSnYo0491LiF59H7HGpmOwxPkONraX2GdfD3kAgQGBgzRgboiE/77A3Pe/9KkiomOA5u3qTMa35VHTOqcmq7vOe+AkXFO9DkEJEQZACxCsETK0l1PDcZxNzBTl7NK2ClCuKPdx74trZu6Fgd+uJqLR3uEduHcvIcC81jkJ6TNw9uwdJUQ1rza56oyiFEsW9ceF5wtpawLkRfKKhoByYyJyUishak+rHNTPuhWQWRG2OhRtpNWDd2O+IPDgYj0x5Re6dIMbeYs0YMw4+3RsZL/0RYYw1Zj+wnu33riechVW0uu7QjNaj8lL+SjoX7M3eREQOTuX0PiN1shuy2mWxqAL0VhKkYHNU0DIMwzAMwzCMLQjBtysSfLogaHPOg+XU+VmNtD1SrJyzQh0/s0Udy2oJUg4C7V2DKQ2yERpIpSNlh/n3zu09dD2qFO0uqRBDwLuakDbFY7mwRxB2XIoZAThOHS8VMKwumsUKiy8Ec85xccsQ9DvnmNuXQGAebrrLcJVo4M58dhmss78I1BEa6NTn6vYsRKlSVedOMhaZJwiWa3UViO64b6gliCEsUQwfAUMdb8mounncXKRiQU1TQ6BAhEC04vy8hpiH8IhwAbiTqAPGoW88OqvXGIuGJR2PtsQWjsN5TsWxxFwgfOHkOnd7v4qlpOztGPTuPdaVFLBMsari2lrh3E04sqjNdd3hGU1VY86dcMe+IF2S+lE7qXs164mCfgcY84azCOF3JXvQD3tsJlvWMfE9wB7jmKwvY6GRAG4u951VLNVkcq6oe5VC9Oft6FU3IgIRxe9Z5wXPVaxKLBrU905nprUxgHMaHp7KquvqLmcPdXVNWZ8g5ZxbW4mtd8WGYRiGYRiGsRIILlyX6dPcbc5BMEXQsxpOnFMBlxBuDQSH9UglREzhQQDsQDTAp0Oa11rhFUkOynk7+vQ6uV4v3crrJBcOeAW76ZZGwI4raT3dYw4C8GlSKpu/I6QR7Lr0KoL0W47PqSizvT+oATapSMsRBZw7is8gKPiFFl5zhbYZy8HJnKp2OMkQcUhzQ+Bbjjij6W6+lLVO4Mi59XhGKtTuinqpc7ibWKurb5/U1EcEi2MzeRUdXJOAxTrJIaAgYHAcrgXxgFniWIgQznF2y1hG8ogZfKYhsnt3j9RwjjVriLki8jj7TgXOd+72XvnlrZOyrZ+59VxSzuXG9eAOwiW0ViA6js0U9LoRNLW+XG9c5prdCfk+0OLy+bJe8132Den8jktR59zdE3qc2UKzrtqp3Sdufrn//cIiohdi7K6hHr0PcNxxPsZWqtbl2Gxekgncg6SbegXYPTfiybXBOBadE6czJRVjz96W1mOpW20yJz+5aUwqlbreSwhcuOO663ZZXJXmAmcqW/OqDcMwDMMwDGO5RCIiL3zhhpo3ArzTUeS8HdJNECAI1HYNrm2IQSCL08e1aD+RrnOitstaioAE+6R24YhwxY47wXzQke1U0uJWggtysyVa1delWKlrXas9w6nWXLFOFJymixsuDRxAfMarfbW4kIYQgQDQ7o7qBEE25/OnDALPOe9gz+oJdggGOIjYEyN9CRULKEzNeW4fn5bD0wU5f0evOtoYlyecBbsWDRk7ohqCBy4YrsEJH1qUPVdWkQKBgnHcdGxWOwjSSRHhhfF1KiLvrVFNXTnd7l3SERExfntwWsU1f40txB32Jtfe7kpaDN7L2nZz/+GI4ifOSJdqhisLkQdhiPnlXsHNyF93D6f0+AiRLsXNiYgoui79cSW41Duut10cBWq7UaicceJE4v5FwKYG1wU7e+XqQ9Oajse9MJ31xNsjc3k5p7e3NUb2EJ9jdri2QDAg5+/sUwGL+4b1JYUvSWppMiq9qWhXbk1SG6cypS0tSMHWvXLDMAzDMAzDOMPx3CanX5QCAnZcEqTQdFus2KV54V6hRTsBOrV7FgukcTgQYLpueASlpOAgkJyK28IV6i6UahqIbh+gtsv8ueX66MTWTTFw3CIcZ2y2qDWu1lIscxA8O9dFZjag4kmmVFMBj2thbUihcoW5gZ88EEZIZTs6nW8Jbq7Qu0O74mWLOs+dBIB2EB8QAtodWAg7CBaDq1TqyF3XYA/CKAWoPacMP3kw7nN3BGXvSFrX8FREEI7r78TInjkyndP5cMXH6d5GlzxSCecKXtc8XFWdHI2k3yGoIJxo+mDbnC/EvpEeTZltr1nG9wFphQhE3Fed1oi9jtOQ97q/s3eOzhRlYLAqyXjn+UG0wmXGHLSnfOIOmswE1NFGLTH+NJUraAodta8QMrUT4HS+VQhe69CdwveXc2whMC00v3y/+O9XapIF8gGvG2alLtuaxebZ74iz3DP5ckVqNa9WF3/zXIZ8H4im9yFQBaShgm+92dXxgl0Deu18Hx0Yz6obkM/xfeYv8s+YmWu+x/jO27bFBSnY2ldvGIZhGIZhGGcwpCmdjvSwBQtTp3AblFquDwI0nAonhCdPfHLPXUFsauAQOBJIE1D7g34/LiWIoN+B4ECa1EqEBs+5UdMAHScLwgCuCS9or0naV0Deqz9UUYGpW3DsEJzinEFsIEVorVxTOV9dmnjEK7KOANCXimvqWSt9rFn4u2N6XCQhQ2kvaHaOKxV2YmEVc1gz5p5r6barH8E/Hcz8sD/G60Wd81Ot/+Xq8XBdpNQhhnAtflhf6johwnDPrBZcG64hrsdf6wqhZ99IWsflamJ1So1ETCuWa+paYx8yx153vojeA4uJn7h2OG5fWxdBro8z1ZsOrE6iFOvKnCCoIIAhtGaoqxUU3avbB7z94wfB+Nh0QUKhgAo57SIr18e+qDfqUqs05JbxOXWluVps7L09Qz1yy/FZ3YsIU1765Mq+v9iLzD1rvmOA2lEIRjn9G98FzpnHdw3fLyeuvaT77vrDs3Lu9rTO/VSmLLsG69pM4Ne3TaiwiZtQxdxQQNcIN5bWRct53z8ckXRYroP9xvcDc4ogh0OSe067L07lJBYNyUAqrvPAfcV41HXXFE/9LDetdTNgopRhGIZhGIZhdEOlIvKRj3jPn/EML53vNENQR3v5jQLB9Ey+rLV8CNJqzWLXiD0E2ARjCANa/Lr5mt8V4tqtc5xOziKcFqgOLmDmHLyfOj3dOJEQmwgwtSZVuarjw6XA8ah1dCIYLGq7eH96HmMjVXI5IopzlKgzolCWiTmvQyHn47Fawac6hRBm+uJ6XASJaCggx0gNGkjJ0elmulUXXQnVCdQsqO6CaCdOka7lgmjmfiFHTyvFiz1Qx1FSmycUsVYE5NTn6XY+CfARbVgTJ+whlFDXijpeXLeOs82lx1iYn32jXsqlc+edah02V5uqLxmRmVzjJCGMlEXmZ6G0PO0QOFdUgYPr6YnziLQ6xx2ayOo1IbD458jNAyIP5yTlzNUD4/r5rNfxri6lck0kcbJ4SQ0xHFYIOghr3A+ILsVCReLJqlx9gHpVSRVcuF9ZZvYX84cQttC9xtrQfZL5pu4S+01rSc0WtTOfuvKyMU1Z41jsL8a+XPgc4hnXjxjJeLSzohan9/bBZNZLC1Thvimicu3HpvMSjwbl7NEeFaEms0Wp1LyUVvbrVK4kyXhYRSVe41JZBzrq4RLkehgzPzkf8z1Wqeme4vOzhbKKVZVqTQvfs/9J7Ryb8e7Pxe7B2aYoiYi7lTrwmShlGIZhGIZhGN3AP/sfOXLi+WlGXUikpmyQ9D0gOCToIrD2RChSiQLd18qh1Xq2pF3KOtVrIrijRo87Hu8lHWexdEHEA4JuUqRItUIgQyhAhHK1hdrhdYJ0N884uOj85ndodQtzQHDPQ7t8NYu0M3b+RoBLp7h2UWN5Bcc9p5B/HmZyFQkGYioQ7hlKLVr7aSEQzYbSoZOuG6EKRwjz2N/jOUXmOWpwsCDIDSZVLEAMaL8+UvgQCIbTS9c94piIXAgoBPluPLiLGKMTKTkPaVbz5qdcVQGIueE8Wm+JfRAMatqXFqpv7l10AH4yHP/v7XvEcw1RRD0iiRhpX5WTBEY+10kgYx8i8Ln1b9/n6ljrS0i1J6YiBXPJmPtSUb2XcPpQ0B+BkPfixKGmFeWgmB/qnfH3aw5MyW1jGf2cGxv7T8XLZgc6t9cjTSdROOyJxAhRNx+flf5ETM/NvcA+3TmQ1PO7Yur89Dv/EMk5PkLQ9n7vHMw143FpuSoCR0Ne575qXcWv+XOLiFnVa+vkKnS1w9jPzp2G6MuDVEGdq2RUBWzmjznR+mLlqlxzcEodSuwRhLkdpPyFg3LdwRktGI8Qy73C/XlwMiPnbOvXvcUevuHIlOf8GkqpsI3oxxgRmV3KJSLledv7dF64PpfO6b6DWHN/3S6/sDvbFKT8dbq2CiZKGYZhGIZhGMYZCIGOC7I3EgTAK3UAcT2IN6T34FTwixUElVwzYoa/ADFBoh8VkSo1DUoJBAnEcSYQXHopXIuPDeEAlWImW1Rxgtoy4NxNpwJBOkExDydQME4EDufI0EfTXbOYG8ldK24bgnCXkud1NMvL4ZminL27VwUvV8NnNWh1C+vzxEfPeUJ6EnWrApoySFDuHDUE7BNzBU2F8q8nAT1OHdaoUzphuyuG2kME7IhT/c1z8dlE7ETRbOL9RHT++maKVb1HmGfeg5hGoWvGy3owhyw588ZK+3/34xeuGs3xc02ICVx/N7DepHYN1urqsGnfu34YG+IbggqpdbeNzUmm4BVL99eRYk//5vYpfS91phBySBXb3p/Sa0BsoeYRTh8EI3X5+OabPXb7eE6va+9gUoZH0sKWp7YStZHypbKOgXmdzpelkS2pW5FjMyfcT1x/rdqQcDggwz1xmcl74gvOIdbIdSl0684YcSPdeiwjZzVI7fXGgsOPtVaHZbMQPR3sODf3MN8BCERcMwKS2x+avtkXb30Xun2nbrwCRfnLWguKz1yws1/X36U9s4bbBxPSl4iq+FapNeT4XEHqtYbEwhGZzhW9BQ+InLOjT3piNAI4UYtLmnuGfR9rzgWCFQKdu3+dUIZTFAGZ17k2PjPcm9C5dILUSsXpMxkTpQzDMAzDMAzjDEQ7720wQWo1QIwiJQkRwV+7CJcUKUDOtUIAye/MAUEh6Xi4HwhcwYlQC7mhXJ0r3BrMpfe8pjWweD9xaFACsm0wsSY1XvyFuBk/Ag8BPE4U6i1BtkgNqITWpup0Da16WqmounfoQEixZoQiAuezRtIa5HNtq7FX/IXUmVfGToF5UskIsIE1w4XmRAgEBeaS62sv6JxupvAtJEqxlohQuImcO4pgHpGBIJ/5QpwZSHnih7/DH3PKHrr1+JwUm045hAjGTt2ydodOJzgGQpf30xOrnHCFeMC5ELq6FRJYB0SKm47Oas2pbvYVe5M5QmjaPYQwU5NDk7mm6EKqWknnEcHD7RHnZNJOhL0JnZvfHprRazhvZ99JdaLKTYeVFDM6pmDQS62dLVSkUCT1Md1y+nn3DXXhajo25/zTYuHhqJRrnjOKOcqUKnJBKjav7h3PnVsMEesXt07KcDquY0eY4f5j/8Sa41fBJleSyWOz6lCiRhVzyPm4XBxJWpQ/FvEckaTlNgWxcq2u6YSudh3F6FkDRCOXNohAhpiEUMweZZ9x79x8dE6qtZpcsmdQXZJcfzIeUcHMXTf18ZgPV2+K6+AYCHyk+iEg+vc2Ywz1B7TOXKFSldG+pBwYz+icMP9bUZACE6UMwzAMwzAM4wwEMWUjpe6tFvPdUl5A51rJj/T1nBBjanXpTyU14Dw8mZVsqarBOel9BJx0/CIwdsITP1V8aj4n2CXojVLbKuyl0UVDUX1OoDqVjWjQuR5Fh11aE4+hNKk8Jbl9LKtjuW08ox3G9m1Lt9whTlDQYszpqNboQTDiehGp+ByCBUIRQT4iDvVzVqOgeHu3MOaKQB5ximC/3U3m0tj4fLsohettZqLU0RFGXSSuy++KAQQ43GGs3fhsXvLlmhaQRyRg3zjXCXuEY5Kid86OXnWhQLjgiVrdwNi9zLaF3WqIEN0W2Wf/IY7wYJ0Ww38dzK1Lv+xPefeDEwIRPc7f2adpmri2mAP3vaCurobXCRLnk+daK8pUoHSiplcEQSYiiUhYCp4WqkIbxx5JxyU10qPPGQ97iHn3dtLJQuLkXEFdenkt4M73E+OdPzcIMFyXpv+FQhKN01zAE9VIrd016K0TKbyMuVCtavos9yEOsUYjoPuiUitouiZrzDlwnnE/cF1aqy4SkHqxIjv6kypeIUQiMCIIMfMIX45oJCRzhYqUql566Dnb+mRizhPIcJrRpQ/3GMfnfJqW3KyR16h5e/cOewfV1cVz7kNq6x2ezsm52/vmCcpcP8XTq0Wv3lq5Wlex61S6EJ7pmChlGIZhGIZhGGcgBKYbpfPeaoPzAXcE7gMCVoJtBAwEEK+4uVcgmufU1CHIHaLgMXWmcmWZpEBx81guxZEgmJ/UrXLPF6tlhIBCEe3FIPhcbp2mpUDkmM6W5extvToP1NA5OJGTq2+f0gLKpMUhMhAg40jhvQTCCBD0XRvuiUlQGhKKxmRkICmHpnJy87E5ie0OLZomt9g1IhD4HVKd0JSsWOfAeqH6UawBggDigr/jIudCjOl0PvbD0Wperjk4rTWWmCNq+SCqILDgrGLM1DZjnXHK+NMXcREhBKwGKm7WGwveh/xdC/7XeZ9o7ScEkXN39GqHN7e/22HNx+aKuq64e9qFUX5nHzSaRb6BNDDmmDX29raoexAnEYKH6xRHitzx2aJce2ha9m9L6+u3j2U07azQOjfOoGhr3nD8cGwErsXqqiHcIMIcm8nJBMXNVSSUprDnwVi8zowFFXXO2d4nNx+bVVfbHfcOtupIIcKxtio4FxEew+qEZC+xLxAhXb0o3F5HZ/IqQPF39gHncGl6jJt5ZK4Q19q7/rEnSKsrVaqeYynqFTpnf4UCQblgV28z7XB+fTy+g3En0sHPv468hznj+wNBmfG6z+GqogD6xXsGVFy7YHe/CoVOUNyKmChlGIZhGIZhGGcg/vpKmw0COIJS12EMxwT1dwgCER0INAm8EaQITCnc7K9bQ+Cp6T3N2jwrgXNwjIVS3xCPxmbysmto9TplcS0E/9S5wbnF74yDlKvtAwk5NJGT28ezatxxKVx0f/PqMoX1cwTgOFa0U2AkpCLBbw9Oa9COcMP7+Nxi88J140xzqVlMKyLIQoLUUiBEMI+4Thgf56ZoNuvlUvhcnS0CeZwxncQYdaDkyjr3pXJF9u7sVwfW4am87B9Nq5jFMRAEcKdkimUVgfzjZl68/UEq3am5U0gnQ1RrFyZJ6UI0dE4eamdxLoSXPcMp6U2S3hhUMSI+5LlrgHE51xtiC3WgFhM922t0IbjecGSmJeQyT5x3W1PgxH3G/LEIo71e1z9S91zdI00hnSmowOUXCVkHioLjmKrVC62Od+3XzPXyvkQ0Imdv99xLiDC4Ebk2HpyH99Jd8I5nDen5I6GQDCQ9B5WrReYK5jPGi/cMquhK6iJzc9vxjEznS5qeqml35ZrcYc+ACmC46PiucB0K+R5hP7jxsi/a0+RI30O8ozA/tcZcuh/78OxtffPSiB28h+8irefWJiyyT7lv+5IxdepRy4vrYv65n0hB5B5w7r3RPk9QZJ9u1n9oWAwTpQzDMAzDMAyjW5JL16FZDzQtre1f+zcbBJsElWOzRQ3WuF6CO1KNCCIJkHFaeHWCTgSdoClSfnvGCuAYWv+mXJWIL33MgWBUbbq2qNtzqhDQk6qX0FQiL5jX6wgGNFAmMCYN7Sc3Hpef3VKQnf0pdWgQGCNguBQygl6El2DtRBCOG0a7qqkryesC5rqGIVIR+LsOYTxwy3AM3CkEzohKK3GEcUxqgeEIKpQrUquHtRg3gg3Xx7zh7EFMYp4RZDiNqxvkB0GDwJ2fZ4/2eJ3VqjhoIlKp1PR4BPc7BlKtdKlcoapCnF+A42/8jlsmEV2+KKWF16fzOmecH1HNoXWUChW9PuaO9XHCF0KMpqA29woiEfMy2Rw3f2N/485xXeSWC2tEvSZNB42EdayMkdQ00mGd2Et6HfuXfcY0sxcQpCYyZTlvX3yeIOWINIVEXGkIOE48cnDd3Kek1YYQlWqeMEyRdo7nCtNzrvFMUY7NFuSsfFnyxaoKrqS+HZ3O6Rzg0kKQQjzyC2DMqTq6ylXZEUvqmG+6ZVxGexMSjcT1/YeLHKOgtcRIN/QXhV8I7iEKmt/tnGGvTli5qvWocEm52lPtULyfOWlPT2ROEcYSsbAKUpwf0fT4TF5FNRx87eOJq4AV1XGz91fbfbnRMVHKMAzDMAzDMLohGhV52cs2xFwR7AMB7GYF8YCAj6CdoE1b2ffFNeAlYEWcInWG4HilbqilIMjGhdFJcyLgR9RB5Eknui92DQTriALugaMH8Q2nU18q1mo1TyBP6hxpSFpjixpM+Ype7wU7+zQFzHX28o9LxcpmRzNgnKQ0qgMm4RVFx33G3N58vKxiCm4WgnjOgYh1qoXREVxIiUJIYI0Ixo9Oey43OvcdnsppAM94EBdvPjoro/3Jji4cxocQAjjicMsM0fkuV5Y9wz2e8JIva1Fqv5ildZQ6uAm5VkTODlrjorhaS8w3dYGOHs5JsVJV5xodE6kjxNpyvVw392mwmeLJ8/Z9yrWSmonIhcDC+ncShLodG/Ny3o4+PdfRak0OTFLbqSbVal3O2d6r42Kf4SiijhECFr8jglFni9pciGULwfi9VL6CCjmj/V4BftaHtURwQzAqVmsqpHItOOPYTwhSCInaDTMUlLNH03LWaK862dxe49jML3Wf+GynVEHcZezvkd6YHJkuyP5tpNZ5Bd8RxCYyXsocRcdJm0M4DgUXTrNFZKMj4iV7B6VQqqnrSWtehYJ6DMS29pph3Iu4qPwCEvOv3fuae1EbM6hg5aXyHZ3KqXhMamAn+lOeWHjrWEbOGk13bGywWTFRyjAMwzAMwzDOMJxLarP/izouGoJGhAyXzkUAry6TYlWFqfbC2qsJnePmZjsXxcZpg6BCPZqJRRwOBOy8l6BV084qtZZAgfiEI4lPXbirT4bSJ6tfXCv1bUhxu20sI9EQdZS8TmGIEAgKfji+1k0qnXiNOULUI31MOxU2HVG4sBCIOD+FtxF3giWvbk4wRsrZCtxR1ZrWQyKwJ/2MtXPpc4hPnBeRDIEEYQORIluoSiAY0Nc6geDAnkeQIlhHTKEj4Y1HZlXoCofppucJIv70J+bMpUj5iaygrhTzzd5ztZYQnwbTcRXb8qWaCnwIYPxNx1iuqsDCDLJvS1UKdzPvFRWwmAOca+r8KVU17W2l3dfqTdFOa4zlEJfCKvBlSlUdH+dj7Q+MZ3UtEEm0JlOZ+mUl2Tuc8lJAu7iXcH4xpzh/WD9X34k9w3kZh9eEwCt874rKI1oh7uAsnCmU9VztNZo4tqa55Su6jnyGml0IW1wjYg8CLeL0r2+f0s8P9MSlXPXex97vS0RVEIrFwuoQq9a8+nKIXNw3bk9zHyAikQKMew/hDDEsnQjrdw6uMD7DuvrTKFlXHJzMoesCyDXp91FT0GNv4tSKRUN6PyBE7R1JLzqvgUBAeuJROXxkWjszLlJbf9NhopRhGIZhGIZhnGEQIG/GznvtEKwTvDsxAhcQ1y4Br3Meboy1hMBYW8s799FJwmBQouGwuikWKlSMGOTSlmg1n4p7TigCcAQZuqYRWC9WQNp1sCNVbGTvkNw+ntEAmrRFv6NJO7YRkIcDMj1TlFIw2wqmZ3JF7YyGkDKQiqqw0C6CIJaRRqi1gOYKmoLE/CM2OOeG1gaiXlfAExGAwJyOgdOZkqZmIXZRdNp1WnNOE46FkMZPxBGC+hsOz8pFu/t13Kxt+5hwpeC6Yg+4zmakQY30hiVXrki5VtN6UrFwWMftutRxLV563ckhL2vJOLqFdEbceX4nEw4p5p70QR7S7Enn0M6IWhssonWTDkyQsljQ9EL2CscTZKSGc4J5NYU4vqaoRsItMUaaP1u/N9eBp1wvwg/zxGcRS7g+9tbByZzX6a8p2CDE4SzjNUQhXudeYqzMWbcd4FgH9s/Rqbxcf2RGnUpcKw48hJ7dQ94YGB/n1NRFuiMOpnSN6KhIdzvXMZNrQdTRNM9SVe9t1g5XJPuMsXEMRCbEIu43rhXBjT3I9Xj7kfc11B2FEMd7gfsPFxtiEiIvD55z3XTr5D7is+xzmgIA9wn392Q2oIIee5YxILoxfv7mOv4hLJKCOEPx+mJFHWOs5ZHpnDZg4Ho4PtPNHHlj9Irkp5qF6YFrxvm1WjXqzhRMlDIMwzAMwzCMbqhURD71Ke/5U54iEjk9RcYJ3AnKcA5tdpzQ4wQRAkktQFyZnzqzVnB8XA5a0NonShGcatHmZq0l0rAQGdoLiBNkkxpEUWmvK9iJotYEpzhpcGMtJkg5EFEQEYpVT2xgDAS8uEkCggOpoulq09minLMtLYFURMcVbApHvJeAGUEHAUDdUAFPoHF4NXJi+kCI432IHRQfd53L/BDQ41JCeFK3Vb0h52zr1XO5tC4KsztRjwCc93LtdA3keDuHUjomUscYv1+U4pqdK8UF7p7bDBdSXed7OJ2QoXRM9wrKhBMQEJLYHrEO6VKeU8qX37gIOGNwBCFE4IxzsCcQIxxcF2vMOFl31gfhhHlgzYvlupyzo0/2DadbhdARophSRDyEK64BkZJrJMUwlQhLbxyRKqr7kGM7ASbc7ER58/FZPffuoR6tX+SEQvYhxyiWqnKsUFGhiH3CeV09KK0bFg2rkLRrMCmNYldTonPHWPmJ6BQKkMrqiYLVaq3l+HNF5RkfIg17VK+DDnx10a5/CMsch9dYN+6F9tRRrvNw09HE+RABKUreKcVtMkO9K+pNVVXE0kLkWjstovM6myvJb26fkr5UVM+zbQBhyzsOc8dcbO9PqejEHLHHuacioYCOIRgIah0sxk7dKUQ19jmOKuZkZ39SxaX+nqhcd2RG0vE5yfryf91+YH20W2i2pGNDiEQ82wrf6+2YKGUYhmEYhmEY3UD0eNttJ56fBrSV+mxBU2M2c5FzIEAjoCXYBS/NC+FBVIhYqzpS7SAaIUz4a/0QGHN+FxQTaOOyODSZ1RQhascg5txwZFaDbkQHinhXagXPXRUKqbMonURUWVqQqtfrcmAio4WXh5NRnRPOWa+L5CrePCEuDPd56YDUjhorZvQ9TpQC3FbOaaRd6yZzmkJGYE1g7HdosL+iPSG9FlxHfM4TRDwxCzHs+sMz2t7+3O29ekycVf6i7+q+aRbR5niIAJyP8zInzgFHClUEYa1SUYGJzyEqUT+IVC2Xkoc4cXAiK/kywTtd3sIqTnA7qusl5XWdc44sTY/ssE94jWMt1YGPPYgzBqGkvdYSziPW2r2P9WZOEHwQGnTdm/uD6+BcrDXiBaIy++X8nf0d72P2urqf8mUVerjnWUf2ohNZ2H+RsKiwyX4ija79WjjOZLasAi4aXLVWk0PU8sqXPZdd2Bsf66sd5xbZg5r2Wa5qah1rgwDHGpwVDqogyzXxE0HKzbkWlWfv50p67XyWcZIGuXu4R51W3DN3OXtInWELgWsPgc05vnYuIEi5DoAcO1klZdUTit2+Zj+E03E5MJFVEZD7xHXO0+8Xuh5qaqaXbksdNgQz9ifdAgPBoDrMJrN1GUzFmo6pUCt9krQ7f6c+1h13FPWztBtoU5DyU6nVde/cfHROnyPAbjVMlDIMwzAMwzCMMwQCb4L59sK7mxECZ5wpzg2lThh1gCxejHm1QdjBreOH4BFxyQ9dum48OiupWFmDWIJP6tTgHHLXQLCL+4igmPQd1vJQNaeOG1xUiA7tYhufwW2E8HGnfYNaPPzcHX1eAN0TmxfkMkeIPovhav/wqKU99xS1lxBLeA2hhXH4XWh+YYdrJ9hGhKJ4No4h3CV0W6NAczukLPqLxXvd36oq9LixI1QcmcqrAwrhg/Npulw61hINtHj3dF6vmzlFFg5I3RMn1PEV1M/NVT3RBJcMQh3nwrmEcOWKqKtTJRjQFMzQAh34XKF21tAvNDiBBtFiuDfY2qu4yzjuLcfmJBQKqhAEiDWMGScM6V2M1dVHWwhNTe2J68Nde75YkdlCWTJ53HAlrcGFCLa9L6nCHMW9qUvFHCCwkDZaa3gpk4hfwOuk2R2azMmRKa++FPul0RxnOVeSaIp0NNIHSTnzhCAEMuaTSUScHaXhgE8A4xwIR8zDhbu8czlcLShEJUQgJ2zyGQ6B026xAkraZbFSUyGOefTSOIMLvpc9zBy4B+fmPnFwLIRbXr9g10DrdeaLz7KGONjYj+w/9mkAx99ETnb1x1XAJbXP3RNcH+Ia31Xt+wRx7Be3TGhR9IXqhUVCQRVyXXol9axciuVWwUQpwzAMwzAMwzgD8KftbfYC57gTcCchCACBMUEkpalxMqzn9bs6O/66Ut7zE4FxtSnUnDWSlkqt5gXwIrJnqGfeWHmOAOQ6g+GiIM0I0QaBYWKupoIGASxCFSlaCD65Zle1cpVOYhT1jknm6KyKLwTrDgLb2DIcdATgXg2jqF4TQT/iAiIFATbin7tmgm8KSBP4I8DtGfbEAQSaaw5Oq5uLdfKfnvGwjvx0Rcw5bnvwzjlY65uPzcpUpigNYVyRVrocY8NdQ+Fo1r8n4RWg9otluKkI6hkzfzs8mdXris0VdI5y5WqrFhEwVupfsUbtePPgubScKOZgHlyReMbt36vMJ4IHNYMQMpknxkIK2G3jGUnFvJpPyxUctMNiyuvM6Nbh4GRWRTdEJdIeSVvEuUYdJRXkYmHZvy0tNx+faznCELsQVBj7bw9NyUBPQveatw9Z/6qMVOuSK3l10LguxFPmYKg3JgPJmDrj2uFcpKlSyJ618cM8cqzR3Qk9x4labDgQvQ6WvO4vUO/gdS+9Ldz67luoKyTnaE9rRoBD3GTOuEe9ouRel77+Hi9tEGHOdcFEDDo4kdEC8IEeOuLR4bGkXf5gSIXC2EnXh6bGudrhPkd3PTaVk7O29S64vrV6XeeF8yOWbvbv93ZMlDIMwzAMwzCMDU59C6XtAcGlS1Hyfi9r/Rava9n6hjBaVyriBdAnRKl6y63G2uBuIHB3IhriCkKBP8mT91GbCEECQUodOwEvpc4JH7wHgQqhis979XNCUk9EVaDBgeUKMBO2asc0n8BDkE0AvxK4tkHS9VKxlgCKW8Qr5o0oUFbBrL1AOu9FWKDzGOPjvQg/3p4tqkPm8KR3nP4UrqNwx6Bb60P1xuUXt07KXc8elsGmSwixgPnl+rVYdN0T03AP+Tsv4jRD2KObIKKMlzbV26rXlYh6qXjMDwINwhPrUavW1XXEkFgbHEnT+bK6ekg3w91EZ0KKUruaWsyFE7d4TyIW8orEl7wx4cg6PuvVGEIkYy75KMWwT8UB0/AJg3uHe1pdAFn33mZ3wFvGMipgsj8RlfhMuyOMsVerntsrFo5IJBiQgtaG8grWBwM45TxRBbGIqybdjVpmzD3CZzTiOZGkuQ8Rb7xaVSfGynwzVmpBsWGZB1LV+pKeq4w5QXxFXG13fyLUjDU7b+IupKj5Qt99zL1Ls/S/B5cjIhKCFMdh3an3hHDFuRkPopQrsO/qvNHREnfT0emc3DaW1VpdrCvn8cN+Y44Xqm+nYmtfUsVPuiEu1Ck0W/QaIbA3cGz5XYRbAROlDMMwDMMwDGODM70F0vacIIPgQrCI+HEiEC9p6hAB5ulwERA4E3y6+SfIJyB3gTfBLrWQXKDK3/aOpuX4TF4DVk0Jmino+7muha4h6Eutc3B85yYh4qemDZ+nfhMCAu3n3fwhYi3HKdUJPXaUVEKvOxtpbIgOpJJ1Spv0ajlFVSBJJ6PqaLvl+Jyu4b7hHg3GK3VqcIVUkMA55E8P9LLvvKLoczkKZSMw5FWARDShLhDzzv73xEpvbpzjxr9GOM1432AqKhOJ6LzxMqecdzLjiSfMZ7Fak+lcqdnprqFCFSIKwpwWhS9V1BkUbjqg4iEvNSyTLzdFrbzcejyjRa0RTrRw+2BKj0fhcMaLmMWe4PfF6lctBcITggXj9Kf/sbfcerEGiCqIK+DmR0UXX8F39hmus0zB6xCIc6jQrPtF57pQoK7Xy3sQA52LiTFwTTzGMwW9ZvYI742EQjqXt41lWgXZ+Z0UTwQg1xlRa5pVEDxzekw+h+DbDoImsAdwrPnHLyeJvflWV7122r8z2X9OBGauvO+dqtbXIv0WMUqaY2fv4wikiDyCFHWlKj0xvT7GRZ04BObF6tsNpWLadZHv8IVFqUrL4cd+2UqCFJgoZRiGYRiGYRgbmM2etudq1iAGELziZEA8cG4cXAS5ck3S8bAKMgS1XprY4gG+trtvBu2rVVeq7nPMEIgjyCCOIESwNgSuBKou7QuHBvVm6k3PFALVcpwyXg2qijo3CNJJA3N7gGCb1zgnQTKClBaWDgU1lW410PS+pkurE4zNdZkD55xhnSikTeBOxzItMB0KauqaS+fz9wtoCN3LSloD6eLd/XJoKi/xaF4KJYTAmFcsvVyVEOlh8YjOC2vg3wMqhDS72JEiyWfanTU4UKinhAjAqS/ePaDHQ6RCNGE973zWkFdEvpnyxXqzlxBrOC/7YK5YVvEPsY61Pmu0V244MqPz5QQPBCjWCkEK0S7Rlga4HNzYEC4QkRb7HhhIRTVlzXMjBb1xlqsqWPlh/+JA295fk6Mzeb3OkZ6I7N/ZL6GQN98TmZLcMDOrC0VqHsdCcHOuNuZYa3PV6pouibjEHme+KtqZr6pzi+OO7zDcZ55zqlfTRGlcUKp44/SnxyJeko6obq3ek1Mo/eAg5fOd0ufa4Rx8f7jOelwTwhrd9aZzZb3m7YMprfGE240OkU4cZ3/hSsSphjhOuqKu6wJimUNrieVL2nmQ62pfhzLzxP0Q97rv4craapgoZRiGYRiGYRjdElm/AtsOBBuCwM2WtkfAT4BKsEqQSCCI2+XXt09q4OhSaqZzRQ2KKcBNYK6CQkNUqFmovgwcm85pkId7h+LEuBRWKuq5Lm6MlZ+IIQgrztGFo4LglqCWcbogeqgnJr+enFKhjXo0FDh3LeFPPDheQAWV1u/N55oa1nQsUduHjmcOXm8ERIWbCDWhFqjLs1awRlO+LnPONYY4tmuop7U2pJRlSxVJNLurOVePH4J1BA/S7ViifKUmEzMFuXDPwLxufg6ELeaoXeBjnZyI2ymN0SsgHvNcOvWGChmITFPZos61PzWRY/vvOUQq6gexLqQXkvrHfupLeg4X1sEJGMBewB3Dawgni+3VhUAEwx3F2uLIWUoA0TmIhvUacNGRAsm+5z7wQ92zTLEsR6bzct7Ofi2QnoiEZGZ6SsdcrnmuO+f0qTbqUq54aY7co4iQ/uvRVDwJ6N53db2yjYaKW8lYpNkYIKQpp8yj6yK4Yyglx6YLEo9SY4paaUm9Zq3T1BQRFxJE3b7hPuS7oJt7u1Spaw0u916+V9kLNx/PyDnb6ZzXo9fmHE2M3Q9jxl1VqlZ1vO0CUyc4H6ml8ZgnbLMH/TXVcpq6F1RnFgLcenUV3UiYKGUYhmEYhmEY3RCNivzVX63rXGkbdooEN1O0NhqIJYxxOYGUa4FOzSRS0PxCAOIOrdYJDLWwdSQoYzNF7dLl0l+YC4QpAn2cN52CUU21mcypAEH1JVq7E9xrke1EZMFOWItBihbnZMwIajiASDU7OpXTwJNj467wzwXuCwLNnc1xEpAzZyoy1TznjVcTyPvpfncuL9jen9RgluDcL8IgPgSaAg3zhfDV3hHQD2INATyCwGoInLiRGCUCBHuA4B6R8YJd/fPS1Lj+zFhZ16/TerGWXB9/Y+7YA8wraYkIPa5Itx8vde/ka0CUcwW6h9KdHSfUvjo44aWr4Xxh3DiJ6Oi3kKjHvCG4MT6cLIiiXA/F00lRRIzZM9LTWjfmg/2Gk4ZC+ewXnEnLgXlAnEGIQuRbjuOPIt7cP4go3DOM1e/M+e2hGQkHQrILEa3R0NpRiHzj43Wtn+XukfY5Zl4R/EhjY1zpZETTLHFIISoiBDJuzsleYK7dOdkn7HOX2sdzOgcO98Tl1rE5nV/mGUca53A1sxaCdXb7ptu0SI7vv/dZp2sPTmuXvXO29el3xmLfDerY04Lwdblo94nOfYvBHJIaSHdK7gUnbDqBMdN0G3ZqALBVMFHKMAzDMAzDMDYoLs1pJSLKWqL1fwpea3og2FoqoCIwJYgk5QsxAHeDC3o5HsEoqTEILASjBK8/unFMhZyLdg3Mq91CcHh4MqfHa++GBRRI5r04LTgf6XUEfgSABOsEhQTJjHkpQQ2BC7cajgbSorgOHDY4R3YOpfQcnVwwBOcu7TLYDJpD6pLqbn6dgKUpjb7udS6FEG8KiW/U00EEcKlBvLfR8NLbHATSXDeiFd3tKFiOmECBblwcy01xZHwz2ZIWXUdkQqzzUsZIraMmzon3Mr87B1Lyq9smNSXLv080RWyuqNfmFbSuqJiDIEFhe/bH2GxRi1z7xazKAiIPQh3un0aby0XdU/myCl0ch3nAfcQ1MN6+VGRBQcqlziEwIfJwLFxSmrrXG5d9I2k9JoINYwcEGYbL+xkrf+/WKcW64bxiv7G3OtVJWgrt3ojzKVdWEZX0OdxgKq7N5CUQDGqnNzYXaZPn7xzQ/bS9P67ONLdf22nVGkvHdG9PzhVlEldZU2RhHyLyaTe9cEjFOp577kCXoucdm7EgYjGvpDhq6tpwj97XXLOr0bZUYfPluAMRbl2NKdYI52IiHtJ7lNRRb28sfDzPcdbQue3WdMn1cu1MKWIqY2b/IKaxT7O4+mKhVkH+rYiJUoZhGIZhGIaxQSGIP5W0s7XAqzVDwWVRMYF6QNQ2IsjsVO+G9xMca6AaDckQHeqana8qNa8mE4IRQT2FzrcNJFQooLg5ndv2b0+rqOSHIJdzk0pD0O0X7QjqESZwtBDoMU7eR+BJwD2U9txn2aaoRjCNM4R5dk4kRBfmnjEyfv6Gm4IAGpfJcJpC2VVNC+wkNnA9zEl7N7Bu8TrzeQIWwbcnTJA+VlKBjGDWuU2yBYSegtayQkzg2jQ1crYkIyN1qdQaKkixNq4rHvPMfPOZao30Ka8IONfZzXhdYWoEJuYQYQwRgXpDnL/9GIiQOM0QLM7f2a+vIVAgZDGvXne/iooxrCspYgfGszKUjqhohSjkD9rZM52KRuNKonseOPEDAeOag1M6LvYfa0Yq5FBfXOdg/7ZenWNPTDuxd/mdukfsa0Qx5ghXF+NxNZXS8RM1vtgHzDv7gv3uCtq7ovjdUHSOrGBgyfTUbt1SXn2zsNx2PKPXixPqrJG0jpV1IW3M62ro7xW5OIgsCKAIPLjMuJcQh9gLiNWsFal4MJWlppbXAa9cDej72IOsC8IVc0Qdqp/dMiGlsidUhZv1uFZS2LyTOIxLiXt6miL7kZBMVmpyaDKr87JnqKcl/C4m/jshbNdgjwqVXLOrpbYYWuetWZvN7Qu+R6jnxeulSk3OGk1vueLmfkyUMgzDMAzDMIxuqFZFPvMZ7/kTnygSXvv/lMY5QnHgjQBBOqIBwb1zjbjAMToU0kDx6HRNg3UVlXCY8P6ylzJGAFovee3pEZtw0HjOC69uViAQ1i5XgHPihqOzKqRUmwFle5BKcMs4vEDR63AHjJHzj/Z5QTHj4T3UriEg5H0uVYZA2UsfK3lpNdR20gDUEygIekf7aM9+QhxgGJPZoooiFDseqNbnubVcbSX+vhKXy0kurWJZ+hJROTiRU7HGiRVePSNq3ORUVEOQIrgFCp1fm5mRw5N5rTtFbSEXQPs7/A2lvXOQJoe4QNDMNCLAeN3qOruomDMEDYJzXFKIPTsGUupEQVzqlHZFGuLtYxmda+bepZcRrLPerpOZS2tytZB4DacPggHnBFxUfU3RifQ+l5qI2MZxSaVz3RF/e2haIsGgbOtLyMGJrBYlR6TY2Z+UkT5vP0RznlPHrZcThxC2mG/Wn/2M6OLSR3GJ8RknZrGfmVtcMFyfEzgWcnWd5DzLecX+2++tlaJuKbpGaudEhL+I1pnCIUe6KfchIhXn4T5YiSbCZ6mfhqjD/cOa7d/GHgy0BCQcXzjKuFcQsFPxuIqpbs50rNGw1l87NJX1uv0lFhaHvPS3kwube6JXXb8X3J5lbeh6iXDN/iBlk+56fN8w7l1DSd1bjJe9vND9qvd0c115D0vjCs93s06ItOwN1pb7hT3FXr3p2KwKhAt15dsqbO2rNwzDMAzDMIxuoaPZjTeeeL7GEBhjXkDQ2QgQtBFg40BywSTBGiAA4GYiYLzmwLQWUkYkoQg2YkU0Qst47+GCOD5LEE4wjjuC92nB5GZ9Is5z0e5Brd2EYNKpAxfiB8Gdc9gA6T9enZkTwaILihHOEKacI4rrICAkeEZwmMl5dZIIPncPpU9K7fNqv4Q15Ymgn/MjqHA4J8RwPQTD2wdOPR2HeZjLlSUeDrfcOn40dSkQkNk8KUDz/0a3QrqqjfYnWylLndB1QRxKRlsF5r16PSUNoBEwEDIIwJkPV+eM31nvYCigDjTtxBYKaEpXpzpQHIN5ZX4QdbgWxBIn9rRfH+8dnyuo+MD6kRqHuMN4VWAoeYXEGS/ikTs/KZUIYEBHPIQKOuqxT24+Nqs1wBAfuS63R7QWUrGi18R1M0YEBLem/kLoOOe4foSFcjWvY3GiglcbrNYSV91rizme2FMq2DQaum9Xs1g99x8uwT3D3r2JMEwKI3giDIJgRbJFr2bZSnCFyV3HSZcqqm7DYlXXBDGxMJ5RZ1BswKv7xVj8cP9S02mqdnKHOgdrg5CGUIyTkblnfnHdcc9xX3upf/GWSwpBiP3A9fIcRx9ryPq5AuyId4ipC809zlB0NpdSyL2GKMV1OKF0Mdi3jJPPM26vIYBXoH3nFuy2146JUoZhGIZhGIaxASFI3iipewSYuAtwbTmhBmGBwIy0H4J6AlyCwbFZguBedZK0d0dzELiSGoWm1S5GIDAhVNxx36AGjaVKVY5O1bTeDOlZ7fOBEwrhiqCTFDcC4Yv3zC9CzGcIegmWcTy44JD3EhwSWCI47N/mjYOgkbSm9s5vnsPDE0AI5nEmIZ4Q+LuUOsaudaSWsW7Mr3etXoDNeZjHbLEqF+3uV6dTJxhHJBTQVEdXVNobZ00msmU5a8eoFMs4QzzBZSmYJ393PAQTBEGC79lJz0kSDQe87m0FUXEnGQ63RC/mBrGHuW0XOXjd6zwW1vphCE1OAPIXu3c4MZZUQdbH1XLCbcMaqhMtHlEnlRPAEEdIrcSxddt4RmbyFbnTvkEVhUJxT7Bgbb1uiifOx/ERHg5PZrW2kBsP68LrCGCsKWNwxbU5JmNEJGEsiDPcs1yXXxBlXRdzwrDfEWtwbS1nz3QD+wPBhf3JfYoI4heEEX9UGM6vXJRCrFMXW1M05jmX73VBLKv4xP3JOiKOaedKaktF2kRL3HvxsK4xcwmIxSo6VWo6ziPTORXajs94AqUWV4954ibCpCtI79KIub9dx0pNH44EdbysN2IU9wXzwz5yKYjt8B4VIQdPdPhzLkVPUF/6vvLOhXgd0O+eX94yKTsGk9pt0jBRyjAMwzAMwzA2JAT2pLRsBLROUb2hAlG9Qfe8sga5Az1xDQ4J6BB8qKdD0OlcNwg1fhEJNwPuFgStTmlKiCm3HJ/TbmMEozO5oga71IgKTeckIAENegk0XcFszofgRDB6YDyzYB0nBDBSmOj0dXgqq84s1/69PUUNQY0OY4zPfyzGh8hAYeyZbFmPiROEMV13aFrFIwpIL1aXSQPtpsOD4JyC6RzXFeDms1oEOhaWC3f1a52mhWDcyaiXRufqPHEsRAg+P9qLQFPXQB/xhDVxtX66Qdcy4aXYMSaEupuPZVQ8O2d7r84FDhk/nJf90i5yILh4rhTPMYX7yBWC7zRfzAfvY69oTa+eWLP2T1VddIgE7eRLFd2T1x6c0rm969nDLYHNS5+KybHZvLrb/EauGh0hKdqfisnZ23q9GkvNNEyEOVyAiBqkGCKiOvGCIvEcC3DP9STCEg536hTY2SmFY8eJNastSDnYw9ccmFLh5vCUJ05xbQhhCIT8nXuyMdh9TSmHS9NlTvxwnyFYs+84PmtH8Xp3n7Hnuf/9uDlF877x6KyKT4yIzzA37BeKynMsv+PSD2utYlSpqvdksemq0nNWSSOOymTe6wIJrCn7lD3Jfdu+Bux5REN/kwUHAifzxn3l9thC8B3JveLVKSvKaHO+2uuYbVXMKWUYhmEYhmEYGwwCKIJHaqFsBHAFEZxff2RWO22ds613XlFzAkAKVt98dFZTDqnT4rq/eZ23AiecE5GQDDWdPziBEAc4DgHakcmshEKe04JzOscKf9NglELWpaqmlfnrHfEcMYr27sO9gZZbgj9TRwbHBC4WxI+9wykVQ3i+kHuIoBfnF4G1SwUDhA4tEB2LqmuMYsXUvOKaEJBIoyP49NfAYi0Zs4pQFU/UYty4PHCL9KWiLTGKz2kHt4DIjsGUzmWnelp+cHrg1uA8pCtRYB3XVLEWbs0NAsBNR2f1p1eLa/lip7duMbnu0JS6jBAPL9w1cHKaXiyswTrr3x7kM1bS6JgH1gNxYDEBD1EKl01vMqIZs8xXvRGUSPjk+WB/sU8QpqidtHc4rWvYfn7WKxIOqWOGlEJXy4l1Zm+zNhyHVE9AvERsdV0C/a4+jndkqiIHJ7PSqDdkW19SXUcO9grzsFD63mS2pKJN+xyuJpwfNyFpexTP5xrdPcm+Yq8gHiFeLhfuZ+7J9rRS5uWGI9PSm4jJ3mZ9L4RT7gP2s3bha3MlMRZWlX3RPxTT+2Qfnw2Hmum8PV11qON6uL+Ze+87IthyXJV8qZ5OHI73eeNoF51wa5FWyT3TSXRiDtmXdAxdSpTinOwp6r9xHgRVjo1bdLTZEXIrszH+V84wDMMwDMMwjBaIKKQGrZV7YjkQkCO+4DrAMULA6dwr/mAMEY2AiyDUBYK85lL1CBIJ/AlQVaCaqzSLU3spdEhY6FjDaS/9CUePv+YP5+Q1RAwVmUqVeW6cYzM5Pfe5O/r0fD+7eVwDQcbrdQNLqIMD+pIxDXSnsl4R8E4M9HjFxRmrSy0jsPbqKonOBQ6xdG/khHMmGlZRiXQ6BBXO7+aK9/AaKURuflznQVfD6SjiQNkrTI24BOyDxQJXjuvV52nIzUfnZN9oWorlikxkSrJju/ceHGFeQeuG1tzyimAvLxTkWq49NC3lWkPO39mr10Hwj9vGfyzWJxQKqoOkvQ4YwfltYxkVYhDdcOtw/bjw9Kc+Gtodzz1HHOJYfIb7gb3INXMsxDj2EwIGqXcITQg95+7oV4FDi4z7xAaELfYsaaDsPQQvby291DkKobvuks6Bx/tYC9Ly/Gl4zAf7AQEOh9SO4R7d73zWCXKcn+N0WjvEFxxaiJJriVf/K9qxJhvEonSdFE1RXA5cI2Ieglc7zGE0Epb923tb8896zeQ8hyDz4V53a8R648QLh0Jywc5+vY/GZlkHT0RrL2y+EM7BxLq5sfGc7xKaLrjjlJuvdRIMXWdIVzduIdiTdIlUkW0RcdV9jyMKUnCf62c/cS8emKALYES/4zjfVhSoTJQyDMMwDMMwjA0GgstK3CyrDcElqTQhivz2xFWIIcDCNXL94Rl1SRDwIpwQ5BF4tlwfjYam3EzMlSQcxlUQ1QAUkYdA0EuN8xxCxIW4jAjUh3rjJ6V+IeY49xXnJ31PW7I331etUW+oKHfY69WSonse9XOoFdNoBua4QSLhkooSpJghUhF4urSudrgOnBB0EOS6AdGD1ziGCjsn1UGixXxKA2qcRIyXtCDEEwQor9NfvZXKw7m13lEooIE07erP3darQhrnx61B10BcFS6YbQehhPmgwDjHYS5xoDEHJ9axpk4ZAnJEoasPTMkFu/slHY92vQ9wybHuCAZuPiLhss6h53gKav0pV+cH4dAvhHAt1IKi+DrCASmGiDKMEnEKIUvnQlMSw3otYdYggQusrq458FLPgnpNzFm4KWhkqOfUF1chizkn7QrRyO+uQWDleKR38d5CqaYOv5ZoEAzIzcfmNL0KcdSlPnIMVzsIpw/zy95m7+4ZSem6cwyKvqsY1ewC5zpNtsMxEM/61c23tiIEYpMrbt4JBDocaHPFsiynzyf3H/OlKYz5sro6WT8EGsTKS/YMzBOtcTwhPnrFx7054XOsEwIlQjKiMX4pJ9qwFkeni3KXs4e6Fmu4bxCycDkiUjtRin3D3eoaAng1pk4WkpzbkO8nf1fNhc7F9x9uO9dooRPc6wiWzLO7Dj7LPi02nZy4P3FGcj8jpm2Ef5BYL0yUMgzDMAzDMIwNBIIFwexSKSFrCUEzQR1OCMQEBKmpXFlFBVLYCD4RdRCSeC8BFGIDAWpDsnoNmv7UwPEUl3TCK0RMyg4/XcDFZ0nTG5tFLAppkNaeRgME/wSaiEsIVLhzEIucy+LoNOl8IZ0zuqshIPjFCEQnAkPEFQQJr9uZV7/GawnfkP7UyY4PHFVz+ayeV89frspgT3TB4saII64O0YW7B/RaCLyZR9d9kKAz7BNgGBfuH8bInPqDUQJXxBj+jjiCWNKp7g1BLYXgmZPbx7My2huXQ2WEqbrEgp5riflh7i7e3S83HptTVxWBNPWznLjmpVZ5ta7Yg3ps0uFyZV27vSPpeemMiIIE24wPgWsmX1KHEtePcIPggdhEmteBiZzOd0+MVDxS3WISZl2baWQLwRzhYOKYngBFkfSYCgrsTWoyuS1Dx8do0BuPt7fKKoY6N4x2youGtSYW4off5eOll1YkEKRbo+eQok4aQh4imlfsv9JKz0O0Yh/wGtfXXj+I8WnnvQ71pNjzuJMQTdcST4zx0msXgrln7XAaBip5CSe97ned7sP53w/F1tqQEugV+E9pbS3mvN05pGJjzOtcyZyydnzH8Fm6InK/sm/Zv+47kM9wTBxTXkfN7tIcA4Gg7jG3q7RLX6Wu95fba4ia7enRrvA++8LVrFsKRGocT9WehecMMZr7J1PAtXbCVTW/sUBc9yAi4lYSpMBEKcMwDMMwDMPohmhU5DWvWbW54l/u6Q7Wqy3lTwQzuIX89ZJOB9Tk+eWtE14HMg20GVNIU4346YLDkd66tnFHaKLr2a6hpLoMcKCcs61PO00hFHTCpUkhDhEsLiXC4bphbhgTYgPB9nSWtKqEHJ/Ny3CalDzEnegCzievNb0TlAhUEZtwFP3mwLRs70tqMEqg6rr88RncEs4Vg4BCwaeFuqkRmBNQIhC5wDK+qIOiro4hgtmFnFCMASHICVN+4QpXCq+5IBrREAGK68qXanLb2JwM9yZVOHECDOtBTbBbxzI6nzhVEAYQa1q1fQIIS3QErOm5EAu9eT+5Q5kT/K45OKnukkv2Durc3nR0TqZzZe2WR1COABYLBeTYLGOsqcjZTT0d5ob0QMRExEit0dQUetiHPXHSwjzHVL5Y0bG79WdufntwSjvbMX7GhQuNPcIecuvIfCEm0hENAQ4hDlcY78OFxvERF5knBBXcNq16atGQTMx5ThyvmLvnFhKJqLhCWtb8NfeK/a9VLSHWHxFO56PkiZHzmw3UdZ/yN/Y04+XPXPdIIiiVak2FJu4T1rN9vbmmI5M53bd0n3QCIULv7WMZrRHXm0xq0wHqrvnrtrEupLtxzyJOxSN04vPSVy/YGdf0PdYEkQ9XIp9nzXEecr5uhCkEM65RC+43U0jZf3yPuRpjvAcByDmhXC03vpM4RycH1UIwh4yZOe1U88p1OqQem5fKfMJ52U68g/tyK3BKFdXe8pa36AZ/4Qtf2Hrt2LFj8tSnPlW2b98uqVRK7na3u8kXvvCFeZ+bmpqSpzzlKdLb2yv9/f3yrGc9S7LZ7KkMxTAMwzAMwzDOKAhMqXGCo4h/afeEFtJbqtoavT3IWk8OjOc0UCXlpj8ZlTyul4gnyviDQgJfgk6EKQIzr5NcXc7d0aspQ50EKecmIu0LIYVOat24wgjuVTyY80SNRqMutxzPyNW3T2p3vlqN+lCxrtMeuR6C0v3beuUuZw02047K6o4hKCf4BtK9cF2MzeY1gEe0WkgwROTBJdKN00HrIE1xzNCCgpSD8xEssxcYH2NlHnmuwkmzSx2OL+YfIWhnf1zrZfE7hbgJ6kndQzg4NOnVwUEYQGiMU/i7UPa6ADbrgyEG7BnyanRRy4uAul1gmVfAvFLT4Pu28YwG+N715fRRLFW1zla5TvHqtM4hThi375dCa4oVKvoZ9mD7/Gp3yJrnMmH+EQd4XLi7X3oSUUlGQyq+IQggrLGnea+m/alTzxP2mC+65912fE5TyRBMEVFwopFWSrFt5tq/Vs7xhuAFrCdzrmtMraE29wwCF3tvIWHzVFDXXXP/st6Ivjh0uD7WluunTprX/c5zLzJW6o8hvDI3iGWkvqr7cTqvtdfY1wg2HOfgeEYdcefv7NMi8AiGzAfzPZkt6pySisb1cUzX8ABU7NUC6SVdM75LnBvKK07e0O8+3Ep8r/BwqXzMq6Z8LvBdqI0SpnJ67fV6XQUtjsn7Od5AioLy3rq5e9ulETphjHEsR5By9KVizXOd3MGQ73NgPvi+cXvOWAVR6ic/+Ym8//3vlzvd6U7zXr/88svl+uuvly9/+cvym9/8Rv7oj/5InvCEJ8gvfvGL1nsQpK655hr5xje+IV/5ylfku9/9rjznOc9Z6VAMwzAMwzAM44yCAI/AZCQdVRdKOhmRTL7iFc0l+PcFrKS4UFdovUD4cK4EAtTzd/VJKhHRFKnfHpppBXQO3BQEffWa5zZwAWSn4xKQI2ABYhSBcbduEY5JAeyZrNcpbf92xJKEVBA6hnpk51BKBYmVQHohBcKJKTkmgSnOEWB8Az1xTfnynDmd03oQZfg8zpSlQCAgzRB3UreOGUQCUvmYB0QmOg0yHuawlTZYb8hob0JrLiEY8hmX1uilLlZUvGKsrBuCFkIF2iEijFfzp6r7kaAetwzHQFhACHTXrp3JZvIqOnCsY1N52d6PmOGJNlyXdjir12UwGZN0Mqr7gq59OI4Qz9gP/N+ECpQLiw2A28XrLlhVodQPn3NOJ1KpSKvzf45zUW+K9EvmeiaLAFNS5wziHGIVa864mce5fKlV3wzXEX9DpFmoUDggzJAOBl5dJW9MzKc/fc/VW+q2aPdyYbxa52qYjnfUfiuoexAx8qZjdMZs6H3NPuJ62TusCyId4iNjJs2SYyDScRx0nOsOT8svbp3U/YMAM5CKndQgANFwuDcm45mSCtoImcwF97yD745knG56ea/uWKmq+4zjIU7izOtLRFWM8s+RE6a8VN38SeKPV3str0421lrTI4MBFR7Zb5zXXx+KtWJ/uvtOHXSI7oukLC4Gn0Xg8qdxOhBqudc4V7Ap3nHfdBKwGs3vSL+QtxVY0azjakJY+uAHPygDA14xQcf3v/99ufLKK+Ve97qX7N+/X171qlepG+pnP/uZ/v23v/2tfO1rX5MPfehDcu9731vuf//7y3ve8x759Kc/LUeOHFmdqzIMwzAMwzCM1aZaFfnsZ70Hz1cIAQfiDYIAQZa2Fk9ENfAlWCRIc24kgliCKmr8rJdbSlu3aw0iz6lQrjbULRSLhKXWaKgTwY+XooRQktH3d6q3RLCLGIUggniBOLDcAJCADWHIK6buBXjREA6Ysuwb7T3lGlwE6QTCpHzhamCsbs65LtK4EBgWcrggYhAIk4LEWBeCAJjAmuN16ly2GF5QG9Ni4hQCL1WrLddZrlDR4JeUKkQRdazMFTRNj/W7eM+AXLJnUM7f1a81wnC/ZUte+h5d/1gPBB2C/2yhqulXM81r8VwtpKaFPLfWTEEDf5xLOK+uOTSt+wW4NvYrRaYJ/BExKI6OYLVrMKXiX0/cC9K99NCAOpFw8DCHnXCpl+xN525pzXuJNNCC1qfaPZzW47J2zAvXQBojwhtuIO49RCaKm1NkHYedpmxqnamqdhck9ZT7knQrnDPd7CucYghCXk2umnYCJKWU/eTuZedsQzhbiRunGzRdL+aJK64GGA4hOiX2J2NeCmXbuZk/bkWEob1DSTk2ndPxO9dgsVKXs0d75eI9/br+Nx2b0+8BBDf/d4C37wOysz+hDjNEUAQY0vCckM2+DAW8wv4IM9xX7AHuKdaY9/Kc9L52oZbfGT9rw7icqHMiBdYTrhAPcfghBrEPcL1xb/uFcn9HTXdPnuqa4DjknP57nzngHvGnMLKPuX9xyraTKVKfrNKqhbVVWJEodcUVV8hll10mD33oQ0/6233ve1/5zGc+oyl6KOOITcViUR70oAfp33/wgx+oSHWPe9yj9RmOg7X3Rz/60alci2EYhmEYhmGsHQgU117rPU5BICIYQbxAQGiHQMkfwBBMe0WDvW5j6wHpVmmKUTe8YIpgm3ER8O4ZSqpokymecAQQRKm41ize7ccVPPdcLFEVJXCVrAQCPgpDE+O7gNSlsZFq1g7BaruraykYI2IhYoUWys6fEElKZc9dtFBqHqlS1DSiwDeiTScnBEEqATTHaXeadAspd3DhrgHZPpDStLgbj8yoAOLEPtaNemWkhzJniJ6IgtcempJDE1kdGx3P7nr2iDzwkp3qPOtviiUIDjrWak07CP6G9MipfMslhcuIPeCld3qdznb0J3TeUCNwwJDmpsJhMHhSTSPmj3F6gmddRTZcPbjgmBv2Sqe5I4VP65u17THdj4WKnLe9V8+JkIbQpiJFX0Iu2t2vjiDOhwDDOSlgjzPonO29WpcMkQMnUCgQkDvsHVRBzS+6LIWrV4Vgi1jHfOucNlNJnXCCG22l694JvwDixEPOATxnLRDiWA9N6/QLJs3C7rePZ4RsQwq483tfKiK/PTyj3TURuJgLiuEzZwhXOI64XvYR9zZ7ms6PiHqxphCm4q4692jYENIC/IDTqlCpqfjJ/ex3L1HvCbfUYqmvTphibV0aK/OK4MTrXtH7gI7XS7UMy9UHZ3QeXNF+zqHfaT5HI3+jM96pgBjGuRGWHMwp+679mhBFEcxcymfLJZUt6ZysRa2xjcyy/xcBkennP/+5pu914rOf/aw88YlPlKGhIQmHw5JMJuWLX/yinHvuua2aU6Ojo/MHEQ7L4OCg/q0TpVJJH465uTn9iejFwzi9sAbcRLYWhu0jYyNi31GG7SNjFb9QJNAM6hr8N+gK/jtU6+7kSrJz0KsPtNh/QxG0EHSN9sX1PV4B9BOBFJ9di+CFuiz9PVGthUP9HoQWAi6t05JOqqh227E5uWiPlzFBGho1gvaPJtT9QG0fxo2IRpBIkLVr0HN/uWteLohLBLY4yRAcsoWyzoUX2EalUPbG6OAc1Guipg/OC8Smbp1UAfGCQ45xZDonZ4+mm/V1spKMhdRFQqBPmiUiBwE4AsAtx+bkgl190psIa9rQoYmMunKcQ8OlmCHCEKgu9d/OnANnEON2Lg72xO3jc3rO28fmNABmX+DSiEVPzC/BeCqGe6eic4VzhPdSK2rXQMonfDZ0jQdTdM4rq2iIq8rNOWvImiKOpmI41Bpy09FZ3ZOkZ1FfiK6Ld9w7qOvMZw9O5qRSrWpa3vZeLy1LBasm7A2Eu0DzPuI6cNQEm2l2OHQm57waT6yd7nCKr+POqdVU/JjKsMfqKjIw73uHvbTBfKnS2id+J0waQatQl3Q8pqIrc4LQW6vWNbUNJxHCGkKG1xEtpOJWX7K7DmzMIXPuXD9HpaF7jxpKrrsiYtpAaul17wbXtdIbo1fYH3GIOmvRUEBqtZretz2xkJRIQeyjvlJZ9wrjw0HnpRfSYZG/x6VSCcm1R4rSiJZlJE1ttqjuP+pxuT08lS3IcI93PvZHJl+W6w9P632uDsjeWGv/ZYue0yoQaKjzjv14jM6YMS+tU0XCQrnlrNSvNtJES5UFu1s6vKYGOfnVrRPqZhvS7wD2hVenjuOzb7waeCLTKoo1WjWsKLCOEMr7WJ9ypSrRkPc9eyogAM9ki9JDfT3STYsV2TOUOum4jIs9SZ26nQNJ3XN8lwHzvVni6m6vY1mi1MGDB+UFL3iB1oKKxzsrvH/9138tMzMz8s1vflOGh4flS1/6ktaU+t///V+54x3vKCvhzW9+s7z2ta896fXx8XF1YRmnf7PNzs567YC7bNNpGLaPjPXCvqMM20fGqlEuS0/Oq4eUHRvzuvEt5/uo0ZDjsyUNymamCot+PyEeHJ0tqntlYjyvQR/Ol3rR+29wnhNMEYytJpliVY5PTktPICm5YFmOlDIyNluSZJQCxQEZbxQkXKvKTUfmpJCbU2fJWKYkl+zqlfxcXm46guuiIQkcN/WGBliZuYAcIZ0o5HUmIzhXh80yuguSekXgNicFKRQqMjVV14B/Zqagwe3th0oaqLZqYs0UtfMbAlApFJQjx2s6VoJlhKWF3BgUPB6fK0lf3GvfTpB89FhBjswUpVxrSLVAnZqgOt0QBHLFmhw9XpNZ6oP1xqScz8hNU9NaK6xQqcvVE5O6Rqz9dK6iokSB/8ssfr3MnZdu5j3XzofJiNw27u2/Wjiuwg4paLtIAWyU5bZDWSn04ToKqpsqk5mTUqOoBbrz2ZqKOj2RkNx84Ihs74vrNcxb+0xJrp+dbs2jg96BO1INOXJsXG6fzMuu/rjE0nWZmy7IsfE5Gc+UpTgYlLG8t4dnpwty3dy0zhdnOD5XkkC5V9cLprJejR/GiTxZLlXl2okp6VNHicg06V7VutxCSmUirAG+Fl9vePdQfs7tH/ZFWaL1usQaITl2rCTH5koqxLBPPBvDifspUKvLTKYmoWpdrrsVkci7/lCFIuw12Zmsy/i4V7uN84xNF0VK2ZPSBRcjVxBhheayZcnOkZYb1vnhCMPpqIyXllj4LnDfBcB+vmXS23u8zl4Za3iNAKjz1ihRAL8qk4GiFHJluX2OGQ+ooMdn5jIl6YmGJDdXlXFqSUlZgtWC5MoFqZWCkoqGWnuYteFaKKA/lvPmDideKc/9EpZwtS6TE4UTovB0UYVGHElzuYp8++i459pCqI0EdV5vOTingpi7rnqpIDcfLOn+XAy+Y+jySQH9I5WcTE2G9N5F6IlUwzo+RLuJbFlGEw1JBoqSaNRFMCbVRBoVkYli5sQ/FGTLOkenCtc9MVOUWiGjjjD09ynpXA+QuZicK2mGGd8LfO8gDo+Neff4ZiCTyay+KEVdqLGxMe2o50CFpVD5e9/7Xi1wzs+rr75aLrnkEv37ne98ZxWk3ve+98k//uM/alc+juGnWq3qYvC3Tlx11VXy4he/eJ5Tas+ePTIyMqId/IzTiyrRFJ8bGTFRyrB9ZGw47DvKsH1krBrlsgRSXivvJM7/ZYpSODhGIjUtNMx/Oy32/aRuj1ha3wsEm/XxjAw206IKdJhqiAwNe7+vFjNHZ2VksC5Dw71aiFxb28crUqs11AWCMygQbcjISFiLrw+ko7JvV6/Uo2FNWYsmeqQnHJTzd/a3ivuSukQtKI5FMMxPAsgKNaHCIRUrKF6NWwWhot39haOjECjoeHA6DNXpJpdTN8220ZTsG+7Rmkj9g0mtTYQLpBgQueO5o54LolqXs/voQoe7pCylGsFrRItv+1PBGCfuqv17BtQJghODEB5308hwUi7ePdBKYcNdMnFgSvoHwjIUDEhkpiBnbUtrYWhSoHCYnLMjpe4NXEZc0YWjia46rjE/pKSl+5ISCQe0aHml1tC0uVwjKvfYPyy5Uk2Ge0QdMATzuNd29XiunKG+hGQbGdkfD8t4MayOl1AoqC4oUvtw7bBnqNvjZ2jYu/5EikLT0ZMLSeenZHAgInt29stof1L3b3i6LhcORCWaSqrbCSqhrJ6jtzeme6AeyUownpTBvoTn/qrnZEcv6WAnzsE8Mc+8hqttKlOS6VxRg3rS0agVxDri2iItDufY0emczNbycs5wSq+FOm3b4w39+0LgfNsVj+r1XHdkRovCDw2F0Gm0Ppm/xlcw7tXZWklR8miqpM4lHF5DUW9M3XRkXGpfsAckUJOzB2N6v4zNFiUWKMtEuS6RQER2jCS1KD/zl+r1hI/+gaC62NKlivz2yKyMpOPq1GQ+K6GCjo31uvicfpmempRGNKVd8BCcRkbSsiMU1D1crNXlrN2DrflgPPmpvFy0f/ikIvD8rRDIqyiMQDo6EpbbjmekUm9If9ORhihKumNvX0JTenFyhZN04KtLui+xoLORv2sjhu1pvTdwujUiQblkX3/LUcjc56Ugu3u4d2gcEdH0vk5oN8Se+oJ/Xy6xnpIKgfFoXee5U9MHx+hoQ52fer/0JWXf9s2lbSxkZDolUeohD3mIdtTz84xnPEMuvPBCefnLXy75fF5fa/8f1VDohAXtPve5jzqpELjufve762v//d//rX+n8HknYrGYPtrhPObM2RhoNwFbD8P2kbFBse8ow/aRsSrw37jNwDLA82U4xPnX+GyppkEK/2282PeTdugqVr227MGgijI8YhRjrpKy19BjRAMB/dd46tesBvwrP8IANW8okpyIRXQcdEwrlitSb9RUjKA+y2AuLtOZsjTqAX0/QRj1jShmTTt4XEI9DQJ979oibVGHpr81BSra02dLVZnOefECKW8uIGVMOJ4G0wmJhL3XOJ7WSJrISU9CJKkiQ0FuPDqntWQI/u+wd6jViQ/BBoea100srQErLgrqJJF2iBCC4IbrhvNyLhhIx+XmY7OaMkfxeYQa1osx3Xw8q0Ia4hDrxHEoBH90uqACigpFubIGugTciCvdFFJGnLl9PKexEQIY52SeipWKHJ3Nq7tsivnoias44Ak1ZR0L50CoPDJNoXZcRyGp5UmJq8m5O3ok2lyE0b6k1pdi7/jFBOaVlDwEMdbeBdO4mm44MqeC4P0u2qn1gxBDWDveR+F0rjudqOu1TmZLum/O3zWotX+Kx+py/ZFZLZjNLmePMVjeQ5c+6hZxnF1DIU33qje8WlCIhrwXgU9rWiUiWiQcga5QKes8nbOjV7b1JT2xsVpX4XKx+JASY9xH3MXJaETHu2Mgpfvx8GRO3V0u7Y/zI6gMryATJB6NqNONY3FPnIpwjIA2naXeU1n39LZ+TyxmnajzxD156/E5TUvsTVKrKKdCB/sSEXn3YEq/t+YKVc04Hur17qXxuZzuL7rl8TkKolfyEent75Hjs0XJl+ty8/E5uctZw/qZaw5Otbplss/G5qh/FNfOle0gBDG3fam4ri2uplKNtD6K+ydbe5Ei+IyLe5h15x5KxQK6h0kF1a52kZCKxwiE7EUEaDx4iMyNUEPuuG9IU0+5LzxB0nMZIpJyD6bjUf3cQvuC/cR9v1q6Atc8V8jqdbMPFkMddL2kJJel1hDvu24T1ZTqdk6XJUql02m5wx3uMO+1VCql9aN4vVKpaO2o5z73ufL2t79dXyd9j3S/r3zlK/r+iy66SB7xiEfIs5/9bHVO8ZnnP//58qQnPUl27ty5nOEYhmEYhmEYxoYHEQOhBsfKYv9q7iAQ9oqbh9QVQGCOq4A6ODgDgIBNu4w1iyqvBgT2iF8Edk4U0hbzoaCKaohFBJWIPLP5iooRBKp8BucRAowWIu5P6HsQEkitw6XR7hLhdwJOFQB8BgVcRgTbTpjSTlQB73r988k5OQ/OIJxRzFM47HXlIk2P8dayJRWCdN4jQS8wrtS8guDRsFR7vHpHzC/CE2M6b2df6zwcm05sFNgGJ0jh7qBWDEWyOSb1oyhcTPFmUqZwjLkaWKwZgTvnD9UCi3Yc5DooLM5cUieHPeDmbZyi4qGQ7N+WVhcLx0cIxDnE9SEuIEpEggG5ZSwrd9zTL3OFuswVa7IXl4xv/rTLXm9c3S/xoVCrOxww5wg/OFEQKXCeHZrKqahC9z66hlGviTpinA9HHELCQLOwNaOdyVVk20BKx37DkVkVVXgdMZC0O+oYzRYrKqxm6xUtNA64yHjM5kv6GcQ955oieucY7AdETOYKZxqClDqIcOP0neha2QnWkwcCB0IXc+zcMSEJ6DxOzBXUUcZaI5iN14sndWrrBlLT2AvnNouv+/cua9fN94CrG8W9RAocIhOfY6+yduw5d++zJjibBnvjej6voHtNjk97taxct8p9I4iyXndBfjIW1hwBx5lIEJN2D3tOJvYja8jf92/r1fd7wqF3jf5C5X783ewY83BvTI7NhNT9Fov0t97H+A/kKLxf133BTOXK3tiPTFekWq2LNyovFZS54JZAJNvRn9R7GdEKxyDfGziOAg1pzQH7hL3PvUJh/05uNcRMJ2CvBp4LMa57vRtm815xc1xlfBcdnea7NrmqDtiNzqn1TW0jEonIV7/6VXnFK14hj370oyWbzapI9bGPfUwe9ahHtd73qU99SoUonFeoZ4973OPk3e9+92oOxTAMwzAMwzA2BFOLdNtrhwCYgI5gmaCUQB9RhKDwwHhDbh2b04BnuLdXgzOEDxVkFhE7uoVAN0anNAk0u1VROFlkKlfS4zMGHBgIMji+xmYKGtgHA57DxkHgx3sJBjkmXbqoa9Se4tMJJ54QYFJMmzbzCCieO4OCyV73LNLqEEj427WHpjXNkc5gCELUqCFoxkXEewntKJw8wvGyJTk2Q6pOvJmaFdfgmuPidsJ9xRgIKBE6zhrtkZuPzUlf0nOsIQgwB/u39+l4elMROTCekz3DnpBBcMmDNRlMxeTwdE7i0arkSp4zDKcTQTQiB0E7ATuBPilIrCWiE84Xf/DMeRgXosBZo2kVujgWHfe4OPYVe2W0Ny43HJ1VMcVznlU8V1mHfYe4yDqyPm7tGIemSpboHpjXvzPGkabDzAXJniOroXOOEAeMAUEHB9aOAS+VjhpikWBQLtkzqOehO2M0GJBkJCyDqbg6f3DeIIKw77lPqBVUqdS0mDrPOcfZ29K61hzzwERWz3PXs4dl50DKq6E06wkPS6VGcn1e4WsEi0qrM56Da2B9KTjtHEEck3lYriiltbKquIXmNybgGjiH133ROwfjQvz1i8uMj/3HNuC7wF0bqWaIXf7XgPRYCmrzGV7nvlCX0faQrj81uvjJd4uK3AHvHKQ9sr7tIFqRYseV/PLWCZnKxuU+F2zX8d5wZEY/i0NpIUrV+Q7OfKnmFSBveF0qdw32tARS1pa/54tVyZYq/z977wEnaVaV/5/KsXOYPDuzs3kXYUEJChgAQYKICgoKqH9EBBUREQT9KUkRUUEMgKjoTxB/KDlKECSDhN11d9ll0+SZzl051//zPbdu9dvVVdVV3dU9PdP3gfpMdXXV+9733nPf7fPUc56j13bwoGmiQAywl/B8uvX0gr7GnuVuRyzcez4tPj/3Ar/G6nIWxVxVOwBCukFaQnDfdN+8nJ7Lyr7x+Kp7pZJhPZKE/WA9o3bv+VO5spKKjIH7Kfei3URIDYSU+uxnP7vq5yuvvFL+4z/+o+tn6LT3rne9a7OndnBwcHBwcHBwcNg+hEIiL3/5yvMeYNuuQ+L0UpJBIktyRVIC+UEiq53JfD4lPk7MprWU5/BUXT1wUDmQ5LYm2P2CxPjEHKa0lMsV1AQ6RYKeLamS5X5HJuTEbEbHd3TPsP5brdfl2oNjSk6h2GltdW+TLK4fUiIdKuu1eH2c2gGCoS50eUup0XUZZUwhr8oHPkvJEskcP5OMk1iTbJ+cy8plU8lVCSHzRykdc8Q4UVPRoe3ErFVOQMZBPg3p52xpXypV0BIy7aAWCko0GFRCUM+fMIQCnkamG+LaboJK4pHs+1AIVVV9o0RFudokHlHEzafzup6UsF2ND1ebdYSEYb5NOVZZZlImLiAeWHeIJIiKvWMxHQrm8pwDg/H9eyaURGoHPn/vTFoq85mG+bUpuUJ19T2XReW7Z5Yl4K/JZVMjzSRZzfqXcjrvvMZ5rKoO4pV3QQ6iWILYG0tEdb6IAd4P8TSSjCj5xvqp4icZUSIFAoL54Xo5D+QQSh/WA+N85gg/Y0gE4kq72i3mevZ94voocyTWIWlaPYvYn5RpckxigbWGSGE8/ZZUocRC3QcJY8F6s+6MnRJIlIQQpcwN1wopM5IIqdKMsTKP7AWr0GPuiGOIOm8pKHNF3KJugugjFlhbVG4QwUoGN6YHoop4YN05NmrDTtfFeh2eHFKC+J5zaY330YQhuyBemScIzVbCTtVglZp6XlmkCyWdC4gxyn73j610DrXdANmf7EOv1xlhBxHHeOmwCDFr1XCch5iBPGeP5UoV47dXqipBS1kr18dcQUJDXuETx5jt/BHHVkl2IcBaRa1itEHoD1K1tSuVUg4ODg4ODg4ODg6XLEii+jA3105Mqd7L9gDJHModyAdLZlnVDMlYPBrSbmSUV5Fc4bND0rZRUooEnc+fnc8qOXNgIq4qDr65D6Ty2vL9sukhTZCPz6aVAEBtMpMxahJUOYwRhVKpklOVQ2uJjFWxQFzh28N8WBP0TkCpxa9R3hyfSStZwDis+oLr5/c2SaekjoQ/2Jg7q/jBW4kEnfNXh6L6O5QIEH43H59X8u3QxAqRBSmjHlANddbJuaKWsZ1Zyqqig6QfDyJIM1U+NdRWKD04VysgMyhzg4CApCH5JS5IorUNfTAgR/cklbyBZIHwoVOcGsBDTgZElVoYqJM8o3Jh/k8v5OXyvUOawPLgelCNjCbDGifVSlUtzyhxShUqq8bEPDEPkBaQQCTGx/YMmzVvJOeQKoGATw3SWz3HIFAYG+QVP0O48TlUQJR0qgm6ZOX8Yl7XhnFDWKGUglB7wJEJnVsIH9aQEkhK0bhmlHGc88bLp3QfoKphzg1hyJzVtSsiMcv8c2xbNrpurDfej/IJQqodEQE5YIiogo4d0rHemDPioheYsruSjgmvJ0ocTUyyn43ZPHsGkom4gFSBPGG+8HCixA6VkpcIpPyX6+XzraQucc4xLYnGHmO/QlR5jduBJbhml3Ny3aED65qvQ/pwDGL/luMLSkbd/8ik7idiBGKK39sGADrPGHc11FYAgi2VLckw+z4W1niGQIIsM6RxRY/DsYmDlTksy8xyTs9DrO8dTay5FvZvKBAWLx9OfJ5dyq0ieyAjuedYk3TUYcSUt8xwu8F1c4/f12hmsZvhSCkHBwcHBwcHBweHLQAJNtqRXsr2ViXOQeN/RLLnJbNIMiMeH5f7ZlJaPmUNw/spQSE5g4wg4VdVVqZgygKHYprkk6ih7GAsR6cp3UL1EtEEmWQapZItteO8EBPqh7IAWRZbU05ou70NxaqqEiEZ4/o6ddhibJAiJJ00MSMZpzQJlQcJMCVskDiocCh9w1CbMd9075x6YpFwYnoOucA4rfoMUosHKqg7Ti9qCRAJMMfF2NomsSS8eS2hKijxxzkpBWKeOM4951K6VnpdDbXLRH2tmoafSTohrbRjX7qgSTbjJSkNBgKS9IdUNcSUcTw+U6qYUkHIA4ydSfDPzGdlOW9Kt67aP6zkDAk48QVxRjxQLkb53Km5tHpTUfq5mMOk3iT/zD2KFUgFCDPUV8wRJU+WBIG0YY0hqiAGIJu4BogRY64dbnYVqy0bogoCqVo1PlBWgQIRZWOSeSV+S40YtoCY8I2IqrJ8qsxJriIsiRl81LjOvdq1LSHL/1tQguS6Q+M9E1LA+idxfV4SpRXsr9PzGV1TYocxmm5qvaXOzAdzZRUvd51d0vOiZLL7gjFb1eAtJzJKxI3idQaJmEPtVNT1Ya0gKiHGtElCG88sCB7W05YHQuDyGeazlcBiDhZzJSW3O+09L1BKJqOYq8dlVmO3KOcWs1q+yvVxPVwve8Hel1h74sGuC+Qn5BYkNvEAcZzOlXVeWVclvkZiGj9cnzVx5x4FQXv5npGO3lXtgELtxGxVyVsL5sGO0d5fGTtx38s8DBr2GomByAUixXYSHCnl4ODg4ODg4ODg0AsqFZFG8x554hNFGt3g2oFv4PEK6bVsb+VzFcmX6trRqjVxhiCAaKHUhYSOb//NeUoyE7QeMO0BgUOSB9lBZyqUC+rnEg4okQSxBYkASHDPLOaUFCHph+BBCUVpGYkdSgOUO16VBYQGpAGkC8qgTkQccwFRQsJ/99mUlmSRrNrkGQUSSeLJ+YwMafeqoHbnYi5QT51eyMktx+clXSgrEUNSC5nEMbiexYzxULLKMZI/VESQWl6gpIKcetT9Dugx8e5C3cKcQuZA7nz3nOk4x7WSWEMyojzi+JQBaRc5ERmNm/K0dmoaiAKUK8fnMk3fIoiOpUxRu78lo0FNvHOVihJ96tdUMyQZCTOmz3gyTWAUvZCT/bGEJLRkk851AVWf6TLUKceLGaPoQlnNytPLdCwL6DoxNsgnb0mYBYkxJAzXj6k9xAZEG9fCfKBCu+vckprbTyajcnASZZRZL4hF5oLueqw/r3PNnI/PWpB4o3qDFMBY2gKijHhERUOMQp617hc+A0FJDELUcE2ojqKhFeKjFxC7hAVjgzjtBGKZOSGW2QusEfHRjnT0glhjjpkP9iIxSIwslgoS8xml4xr4RIk4OiJacoLz8bkTc2WNBbzO2ikQvbGM0TdEInO/ZywulWpV55X59Xay5LiUQgZ84XUN3IlHo0RkXxeVeKYkj86LiKHofMj8qFISQ/WgUWrZEmTOzb9z6bxR1jXuZ8Qt+zdRKCv5DOHJe+aWaTYgci5liN9KlU6c8Q2pQNm/1Wq9SdYrKdVQcHHvzEereu8gFti/2wntILiYazQo6K0M/FKHI6UcHBwcHBwcHBwcegHdqb79bfPc08SnFUaxYBQl/aiXSMjnM8bYm05MXpCwkyBiHo1CBiNfiA3UFagsKBOCUEABAflEhza6WTWfV/FgKmsJVDwaVKUQiRtJ9N6RmAxHQ1ryomNIF9WcHDNi3kMyz4MEyhqde7vhWZCwo2yBJCPhbZ0TL0znrrC2cscvhrmi+xeECJ4wpN8T+6OymC5qEp0poOjyS65kEnUSeUqrSFi9XlYk4CTI/Gs670XkVN50y7Mleih2MDynXI33oASDgOA98UhAySAUUQz5iv3DuoaBuF/nxiaREGD431DCBpmnhtjF1WoazsNx1Xw8EpQE7eHrdX0f5xwbMiWCJOLmX1NaBclAwgxReMXeES1p4jmdACHISNh5DyQZ64JSDMKOpL9UrcntpxZ1PvkM6wWhgzKEEqx2fjUcD0Lr9EJGlX2UkpG4s4asJfOxnC0qsWeM7VfIEZ5DRHCeK/YN62s6D6GAxiwJOIQA88KeuObgmM5zqUEoQvZBOhFPzc5uNUN2eQGBqCWCywUlYDKFoMYrROl6JWg2/tgD2vlOVXPdfc2IFYgTrgv1F2cgLjuZqXNsSvEgbcaGIg3zeAg2kWv2jyqhByEEcecltii9I4a8ahntVjcUlTvOLDXnotM1skbEKXvdW+5rFXqocYhz1sOSVuwbiOH1DNxZH/Y/ZDikJ+t7ej4nV+4blnvOp+XO00varZLxMl+QUMQCRA/7D+JFfcTSRbli30jzumOQQqWK3rNQvrGvKpW63gtQLqo6KxZSAnIjhBTKMXzgIPe4n+ynhBQvOSSXDaCwpCyYcxMPnWDjd1CA6CPGmafN+gBeSnCklIODg4ODg4ODg8MWlO3xTXhfn8sUlTTCs6hVkbGUKyoJRYKJ4TlJIgSDdm4ajWmCWahUpZwzLe9JBvF74jAQGNlCXcvPILFsIkpypOWCqEHiIRkuhlXNQhkNZV3qYRUJqpoB5Q3JLkQLCSiER6eyE/U56vGaD0wwvrLcdS6lx4aomjmzLA+7co+cT+WlWq9JLl+Vr9x5Xs/LGCDkAPPbmthxbRAyECAoO3j/WNJ0DURxAqGF6oWE11uqBwkAuTS7ZLodksTqexokk1XPeMkAEktb8gaJg38Y7yHxhNhj3vH/olwNHyU+A3GRDFM2ZDrdMVeMEQKHNTYEQF1f3zNqiBhd/2xRCTH7M+vCg2OcWcwq4QDRh6/Vsb3DWt4YSxqCgE56Pp9fvuey8Y7roD5mhYoSm8TWqfmMkplcIwSayJDGVTulEGqt/eMxNeouJYwChXWx6jFN6lnHUlU7EjJm1GMQF8SZTfohNzCfJy4hcJQM8pyPOY5OGmN/1pNSRM6F+ms9WJVMsVRVAq8XEBPsB9aN2OO8nUgpxgHZw54ZilrjbJ/6Q4FIOKgKKkhKa+RtTfhbY5j54fr5rC01433tyClILd6DH5wt91XyrVLT+whjZj7ZK1oy21CAjcRDcnwmo+du561FPHJvYa4YD3vJGspDHt1weExuP7Uk34GY2jei5BX3L66Je4MInlFBHTuxy/3Dwi8+NTVnbOyPTKCshBFkJh5SdFVkXL12sGuFMXgP6jEyhazuKe5VzIuFvUcyf50IP8bNvuI+wX40PncbN0SHAEPtx1i89xIHR0o5ODg4ODg4ODg4DAwbLdujzMR0s4qt+Wae32EOPDUUVfUDCTBKA9QtS9mMJtwkYCSSlPnYBEi9aTLGlJrxeFU8lGuhSiDZRDUFSYCpeSgU0KQObxsMwUleF0oVmRpJqtIKVQZkAc85rvoxNRQzG4GOM1/WEprYWFzuObcs0xBEAb/6OU2PJJT0kJop5eHckaAxqe5EEJCAk0iTUJL8QeZQmobah0S4wRcosWE7sdmEFb8bEmmICEPGGDC3JN0k1xAPvN/bXQxCAv8fxqzd4sIBVYGgROM5nlLMGQk8BJB2zMuVVMnh89VF6j4lzUj6W5Nf1p/keXJybXkmc4Caao2nWF3k9FJFrp6OKBGWKxtj81BiLbHEtWFiT/K9iJfXYk72jceVkFpvXZlPjntowhAoxBSfIU4hJ9gPHIfjolyxBucoe1DDGD+vlZI9Yp9YRWUDedhatsa68x4eKJJOz2U0dtbba6wn3lT8q10RewAkDCou1hDCB9WRd6wWxAJ7jTk7t2iUSa3gGvA6o3smc3ZkakjnhkN5yV2II+LSax4emQhonLBHrd8b6817iWvIQ4g5+34ILKMGM352ELHsBT7LWCGQfMJc1NR7qrW01YyjpNcKUQTpbb2w2EsoyAqlmpaVoua688yyHJ5KNNcbUrZYrivhCCGqJcfLBVXgcY8jHjkGCibUgoydvQWRPJGMyYEuZcjrwSoNWQPmnPuFVYsR5zzYhxCaqC+ZK15rJeaYX+1oORrXewTzx7pw/aj2Wj3z1oPpWplvjslhNZxSysHBwcHBwcHBwWEA2EzZHgkL/kqU8rRCS7AaCiESYsglEibyKFQ9fKMfCgTk+Fxak0KS3uWGmTYJFIkvahqSV6uc4UGb9NzZitx0fF4VWhAuER/t28uavELo4F0EeQARky0U9TnXZoyYTZt7CAaSt42VsuR1fJBgJ2cpp/FJIhaS755Z0mSRMj3IDn532eRQRyJqTRnhCF5HucZ5zHXjRcX4D44nDEET8KtaZyi2QnTwWcZ1fDajZJs3SUfRxb+QSiSXqhzz+PKUq1U5MVvQpJoxo5j7zulFfV4or6hNAKosEmHOxfgwZea4XoNoC9Z6qEsiDDFBkg2BYlU3lH8uLgTk7vNp7Rp5cIIOiRACWfXgMobqxtOJUk2j6knK0WRSyQ7KRH09xDtkAteXsJ5f81ldI+YG8oT5AkqKDMe0/FKNsAPGvBxCkONwDOLKzEFA1UTEvSFqV7oCAt5LfDKfN903r2OA+LAwJatGyWfnEmNt9oPPb47fKygrhJxlf7Bmtmtc6/pwzaVyo1Sxg4KQ9SP+UAUSXBzP+172FMeCmPaab/M5iCGu87tnl/U6oiG6RPr1vhAK+1eV+7KmqCQtiAvuE1w3688Y2A8QoNwrOK7XSNyU8BZ0DlFbeclsqyqENOSYdBa891xKTsxyf6lpHFPuOd7oJsn948bLJ2Q5W5b7zqe1I+RIwnipQVxCtkJKLeeLXeeuV0AyESr2OMwjZB1ksU9Md0tIJgg6o84qavkrse/dX9zX+Jy933BPh+xir+Gxxuuop3oxSbddNQGxvBm11aUKR0o5ODg4ODg4ODg4DAAklKDfsj2UGCREJJvtEmY8WUg6bWJuu5dBrEBq3HMurSoNfk/5C4TABF2mAn6pYjpdqirBAqkCabaUK8vhySFNBjW5ioWMYkk9ZoKNNusB/R3JKYoHfk9SZjuA0V3MtDQ318zv/f0qwyhlCRoy6LYTC+p9dMNlY+oh9blbzyjpQOJbrpjyKQiLXmGIjagmnnyOMiESb47ZzRAeWHNzyBoSSi4LAkU7wQV8msRC3ISClDOasVlz8lqD6KnVDSHCvFy9f1QJPtaApBZVDcdFdYHKibW3ygwta6P0iE6A4aAm0JRm0rmtHVh/4oNrQ6HFeCDkOPcQhvJ1v5SqVbnrXFqu3Dus8YDRNAoYlHEQZyTwEGmm619d4+rb9y3o/DE24gqVET483iQcwgEPK1M2GFSiA98qFGP6POSX+bQhiPAJunzvsJKvzKNXTcQ1cv0QVHyOueU15h3VIdd3YCKu58Y83ZKHjAsCB5UXvmocg+vnfPb3xgDfp8dDIRTvg5BqkjDDhoRB8WZKw1ZIKc7FHmBfoGZq59nlRblSV4KJ+WKtWWMtuavhGWb2l/ceYEv8DClqSmfTuaJeT6Ua1GuD7GOcvGbf16rW4piWnEUZaTpA+pUIJ7bDIb/uO8DPrNehqWTb64HsM0SPKSc+umdITs5n9ZhnF7MaY6NHw9pAgXsLhv7cV247aYgu9hZrzHGIecp251N4lsWV0Or3XmJh9lBxTdkfnmwn59I6RhoVHN0zrNfOOl5/yJRonpzjvh3RfaTxV6k2VacWtmTWzjMlloyTOfKW8nrBnEMGQx7aOL8Q3f52OtyMODg4ODg4ODg4OGwClJeRyOApxDfhqELIqayaRk2s/d6fTRkSCSeJfdBvDKxR9rQr3UsXTIJoYRLQqtxzPqVJIY+RGAbndVW3kCRxfOtVVCiVZSZVaCa1ECGU7HiVJKfm06r0ODBuyCwSZhJlkjASWogRjmkTZmtkjDoGfyQ1UO/Rq4ckFEJKk/xiRZP5vSN0dcPE269zyb+MAyUHaq9KI6Hup2xG1TuNbmAkv9ceGJWFjDFhX0+RwbkpgeK6IZMgZbyqCZJQ1GeQMCTxAC+n8/flBf4IsoGOYrbDIeQPBIuq1xqf9ybezKuWVyUjejzmB0UQySzX0MlsGUWHNXxHTQWJSJI9OWS8f/xRTMSN91jdJ7rGd59PydHpYUPaJCOqhvEm1JQd4imF2iYZoyueKXGEUEJNZz2cuKYIpFXApyQG47ZlUhCtkAyAeUAVRKxAXKCuaZ1rvT6PtZL1JppIVpXowAyfa2SU7DHtplapqeoNQuOus0saPxAQECBcDnsLkoI5YQ5QyxzbOyL9QjvHqWKqhHX5KtKEuILsIq4o0RyJmz3bzn/LkhIj8Yh22WTuUSvSuIBjsidtfPM+Yh+VFkDdNBaKKEFVi2BoX9U4DlR9cmImLeFwUOq1usYoRF27+GbfcXzGztxCnvMvpBvldXtHozrvGIAPxyOqiOoEyBtixDYQQGkEqXXTfQUlKU/N53S/XnPQrDUzAcGcjBgDc87L/cp29iT+pobpwod/1lo1WicwbxCFkL3EA9ff2vlTy3MrxnSfMTAHPOdaIUitPx7HCATw9ivptbcjmQBrS3MF9gExxudQm7Gn2R/2Hsm+4R7J+/kd5ajcgx0ptRaOlHJwcHBwcHBwcHDYBEjGUCDh8UQyRaJE16xKvdZ4blQ0KAjq9mcS71pNFnNluX6vMTDWzmAtaiAS/YDPJDVekPRTYIWahUTr3vNpGY4FNcnCKwaFUKlsElceJIITiYjUfT59zmuU6dE2nfNCDEGK2GQQ4oRzW78ZEmTOY4EK5sRcXg4cmVQSiWSrF1KK46CygsiA5GB+rto/0iQ6mB9IPggI5sh0GIya9u0opqQ/82NTOmNKKkm0sY5S9VcbH51WMOcoIjiG15iYZBuSAqIKMubo3mElXE7OZmU5V5R0wXRTOztPQhrQ95AIt5ZltQPv41zGKLyk8zU9tFqxYcGc84BEAiTRrOFStqAkzsn5vFx12agpJwxAXIWbRArXwFyzvq3JN7E4PYI/Uk7jIEpMRIxSBHWILZHic5VKVXIlQzBQjmV9xmwJKT/PLOVU+YWvlDWCF+lOCkLo8FlLCBmyApVJQNePfQKZAKnxoGOTSgRzzpFGlz7A56IhvxJh7AcIHoi+jQASBgKG46iBfaPLJaQXRKNZO5+Sf+VqUeNaCcmgX9eS6+DztpzsXGNOklHzWPFXK+k4WR/mm7JE9azyGOBDZDHfd51dNveXukghW9L5h2DqVB7G2K2iDaIEU/x0Pqelt7zG2s4tFaQUiKn6qVuZGXM87mkgoMrEkaiUayIPOzalew2yiU0MYcPehbim2QLrBvdGSStEKtdM50jmDyKULpPrkVLWU4sHn+M4rWqlcmN9mE98xPCL4xr3jCb0eiGduUZIQt7HPYiOgHof7MFkXdWIsZA+1EswX9IvFlSZGQsZwjJkFJtGFRrQOXBYC0dKOTg4ODg4ODg4OPSCUEjkJS9Zed4AJBBJFERHr34htkV9rJ5vlmlBBrQqgVB3jCZNhzYLLR1ZygnpDa3ZKbfDuDybDEu2iOE1/a1MqRiNsEiaIAhQJZG4krzbckGSZYgpCCzTxt6ARJoEnqSKxBdCwOs7Y0ukOAYlQCh21gOJH4qMumAcXNFysEMTyVVGzyT8KDogzqwa5/AUCiqfliH2C8hCEnBLyHBO5o9klnnpBnxvTsylVd1hk1RMklGdzUKMBAJyZNp0pYP0OikZnXsST36ORoJybM+Qdv/rF7b0rFPbeNYEooZ5Yi2ZNxQmnBsCIBYKyv7RqBxh7gIBXSf1foqYBBrjfLx+OinPWHfmh/Wypv0QD5BYJ2YzqhLj2Chiju0bUhLLxqjx9DKm1pBI7A/URMwTpAnn71UJ0zxew2PKlouWKuZ1+3vILo5P8m/N7QFKFn5W/6ZwoC8VjhdaEjsclaWzKd1XECAQw+wl5sQaiEPUAO2AVzUdFq3/kvonJaPGqLxsPKoA74O44b2qqomFlIyCxOIcthOkNcDn2HgUUVYLGcNhOAbkK9dvyy5bwflZF+ZACb+gXwlyPsvx88WynFsuyvddu0eViutBTc8bKiHmOFuoiq9eV+INZaPe38KmNBGiGWKef43XVFnJQtYCJSjHYo4hzYjrbqoozqkxFA2pMq9VFQbpCSGkx4+GVEFnuu359XX16PP7lCSy+3wxUzANBTCJ77PEEzCfU6GYjCfrOj5zbUGdF1NWWtH10u6mbYzVdzscKeXg4ODg4ODg4ODQC0iCE2sVNiSNUxHj69IrrOdNMzGtGJNkL0heKMG6Yt/qkiMIBRI/89m6nFnKabI3lynKkSnIIr+SXqgSSEKrjaQXbyOvabGFtoxveFBZMDZKngDJsrd0z3SwqppEtKEaqVbzazvAtRjAo1IgsSQ5PTSZUGWZJTJ4D4kmJBS+QSST6s1UY678+lqmWOl5ftVrKVNUVYaXLOR8JPyQfRAF3bxrbJlTKIEfT00TfpRQmIAzvtF4RGpSN10Lg8YE+0HHpuWO00tqhsycbbSt/XpgPXWN4qZkjyRfS5fU94nuaiIzvvyqrnbEWLZe1sSb+adsLBbuPD6IitMLWU3kLSHJMQDqNsrm9o7FZO9ooiOpBRFJXPgkooQUa2pL0vqFSfA5f934t7UsHXPBXoScobwV5QsEEoQW8QdxgA8S14BSULvfNQhYxtpt/6oZe6MU887TS1IoVtSjiHngs5zTS+oa0tcY6TMuSCRignLImga1Cp+UuIG0Yr4gjDkPBLKJz7Wki/UoQuXkJSzZd5AekFismddUH7AGKKq0wyKlZo3r5XOqnIqi+AnLRDLcJIR7AWtKqa9Rs+X1flOq1qWQL+pr6qXWIJPw0rL3Hzyb7myYthcrqAnLOg/MFfcr773Eq4oi5u1xWS5LcJnOekaxx/0KgpD58N6PiA3UpMQgc2/Vj8wD5+V+QVdEzgOJ3Qsx1wuZzHraBhGGtDZl1A4rcKSUg4ODg4ODg4ODwybQWlq3ESj50VJahIcNSgbKfGwrer6Fv+PMoiY1uVxZE2USrAcem2p29MI3CJUOR0vlilr6g7l3O0KKBIkEndIbL0jyrCkvig3vNULMkOBDfuQKFSWveJ9VGaj/VKOTFiQUhuHnl3MS8kM2BVVZYsuIODefU4Kg0TUL5QbH1uRQjYdLTXNuftfJX8mOm/FRRkViSiLcqkrgWlAymA6CnVVM2WZJYl1mGoTUJCVLmaKSG4ZU9CtZhl8MxyLRpfznjjNLcsXeoQ2pLtaDTdJRMHEd9rn3XEp8eABBofNXqelaM88n57Jdyy6tQgmygPdwDK6ThJ2kG9PubiWbEFkk+pB7lC5qrIYC2inQxnO/4Hx2zIvpoirtvCAOmQsUKX6f8U/iXJA1xBAEAUbXXD/7iniBCCUWiDXKyIgxVEW5hvLM/st763VDInFdEDIQUcQGXkLdPIiIOeKevTGfMt5CEFVKWERDOm7GyLkhXfCYa1U7cR0Qu5SNervtrS67jClpBRnnjW1L1Nh7jSW62MfsPcYAUYQ5fj/rQsxB6EBsQ/ZMj9Kxs6xKMGvOX7B723P/0X2TL5sOoEUaLARkJB5SEh7CUT35/JRDlvT+wO/N5/069yImriyxz79qyB/wtVVPmXWg/55R1TGPlCBbWEN3FI7EuPpKDfevcGwFRBnXCUEG7H3SkVKr4UgpBwcHBwcHBwcHh15QqYh84hPm+WMfKxIMDpRoIKFSVQlt3gN0Lis2lDBFJY9ImL74nbOynCvLw67eK3PLebnp+II89Ko9sn8sqQbF1Zops0NJwRf9qCbwnkJ5QaIdjwa1ZMYm0CR4HNerCiCpRH1DEo56g4SWYxqFFGU3ZSV7SAZRXUA84SuDUiLdINJQZZDgnluGzDGlLCT8XA8kGR5WloQyZS4RTXC5TpI2W+KCcbWWMFmD5oYfTisYgzXbJtHulJhakJhCLqAO6URyQVTsHYlrqZpR+4jcfGJBfYoOTgxpWaEtSfru2WV5ykPG9XMQJpQs1XAW3wKYLm/G2J71Yy3WI7+sgsjrG6Zzmy7IwXCio2KMuSQ+6OoIGULJF9eH8oi1olSsEzgmpVGVariZ9DNO4gZz/PXM5tuBcxPL06MxOTWXVSKk1aeLc0DonF3MSDAQ0G6JEBKQTgVMr2t1CdZMSart+kcc335qSUsfISuIC4jRaNCUuRGjXA+xvZgryvnFvFx7cFT3F+WvKIRawV5hziHxUApR/sceIO4m6yLHZ1N6HUmhvLao5C6Kmk5rwbpzfjptdiOOlFhZyqtSzL5PiZBGUwI7R8AafIOCqpP8G/bbYj25hrOLeb1v2H3V2rEQcH9hPKiqUI9lUUIVKrJPSWRRbybGRpwfGE8a0/8G8WTJqH5JTe5xfJZrPNxC+vG6VTepQnA+u8q0fKOAMLYdFoGa4vdQ6rzb4EgpBwcHBwcHBwcHh16A+uTrXzfPH/OYTc0ZqgdUAOeWC5L3pbU0jMSdkip+B3lA4k/CjXqCMrH//PYJmcuU5JHX7pXDk0Pqg0IyGPb7NMk7smdI34+BMGbBx2cyWsaEQoNEDAKFc6JUMeV/Jlm1ZUech9+RmJOYQU6R0BvzalFigmQtHsGAOmnIs6BfE3ree24xL9cdGlMFytxyTv77trNKPKn5shhFA2STl4RqxTKqqEhQVT0oRjA+Rm1AMk4iiuqincqAMUBQeEuEuoFrsgSHt+zKSygoMYYh+2Je5xSFTcCHQsqvahwlD8z/ZSwRVoUK88rnUOVQmgVx08t4eoWOq0qXsYjON3Pby/EhCFSREl5RFkEgoOKwnkDtwLVAzpxeoOyvorFEDECeoP5Yrxsi675/PLlm7nVeNkBKqTdQ45yo7tgj7AUvODadMCEzbzw6qQQhZOWJuawqyNgre0ZiGmOocrg+vJ5QkKEiIpaJd163XfQwitfObNmSHJkclnqN+jsTG6h9WlVSELlnFowSjX0KefiAo5NKSjGnhA5E8oGJeE+eY6xRoTH/3UpOATHIePDTYg+ZDpwVjRVVTHnmHQKulKrqvKCw3AgpxXgw06c8ETI8k09JYu9KTBJ3XtKO+SWWIEUhn7jXQP5x7tMLOSU6J4diq7zmBgVbxtpNqWTVX5BHkNubvcdDRlrQGbJczeu9odPeSedRpvanWLvY4UgpBwcHBwcHBwcHh20CiQpJByockmVIoWNDRoVEuQtJC8TD3WeXlRB6xHV71cj4+HxWouGQ7BkxZArlMhBYECrfPZ+SH7x+f1MxgiqBBJNkiOSbRFtNsMvGS0UTM7xs5rJ6PkpZSAgZF0kqRBBJMEqce2dSMq0dvUQNrnkdMmtmGbWOUWSgtLhsakhKlYrce25ZipW6nF3ISjBozITxXjq2b2TdznOUUeGXdWgC4+i6KhcopUFpQXpGwms8hVaDuWPstvtbp3lHvUUpHv/yM4kfahuunU5cdS1ZxM/GGDNbdQqJPfkjbe9J7pk7yrlIXm13rwdfOSXzabpvZaUEaRQ2qjA+T3e8QSWYqMEg9WYaCpxeS0eDfp/GGoohLyAHIWus+oRrI2Fm/tX4uYySiBLLiuma5pOG8Xz7hFr9iYIrZXPa+bGl1Iz4gqRh3ZjbftUoXD+kKyQLpCLd46zKDtKIMVDKiq8SZMiJ2bSSA3isMQ/EFOSMluzRGS9oSka5ZuJHS9mqNY07xG6TmKgH/do1ciIZNWbtlaqWpELmsY+9ZaXMFXvK+GrhkYTpd133NKWsqJWI8T0jIcn1YN5PbJtOmPFVRAbrZLpihtao/VBLaVe7hhk518V7DEm6Mt/MG7Fp/dpa46NXGK+4usYKasy6hyC0XlaAeYIshACk/FK9tyDMVXUXk2jIqCjVp65m1mOQpuCsI2NYD8QFJFuvXUXbAVKQufWqxKzBOvsi2YaUyhUreu9JRlcTuZc6HCnl4ODg4ODg4ODgsB1kVKEsS5miJiqYbeMZRVKWymMkTmlUI1nUkjDTah4iAPVAAvXDsE+9olB33HR8UQ5OxuXQeFwKDXNfS/pAatkklqSTxM52I7MdpubTeS1jQvWEkiFbMB4ukC2JKF3SjBcTJXmUQBWKZU2AL987bFqcL+Y0wYNr4RpI3GeW63J+qSDhsE8T9yN7hlW5xLWQaHYqM0MJhWLixFxGCTCIBRJo1C6UjJEgnl3MKnGkhEMLbNLdSkjh2cM4SZBtkgxIcVFeVRpKhtvPLMoI5EGtrgQgpuoQVZBgtTrqkYCkUxU1MJ9J5eXyPSNKbLA+x+fSsm8c03bKHOnAFtQEm1Ix6491cj6ja0M51XrKIu+ckLii6rDm8Fw7JCDKEhL/Tp352gFigONQeim+spIkloDKFcpyd7bYNIRHXcfvIVtIyBPDUSWSeD+ll7zHlktStkl5G68Rg6jFgJIkPnzRzPu9gKxjfjkWqivmbBhVXKO73HpQ/6U0iTv+UsaLic8xP5AxEG2QIZaAyJXKSgRRKmcJKAjbTLGs6455OeOxqijvnoVYYIxLOfyrEhr72u0vGZV7zqdUpYXiDBJq/1i8uUaQVZCsKKPwSbr20JjGA/PD/tOOfTVTftmtGxsElyq7PHuHa2N/Q1ZBJmFOfqhFLYaSjWPnGu+F8AF2jrxgXKxTOOQXX3ljBJAlI1nTqaGo3kcglqwvG3NmPbF4HTK8VDGdR+s1sz/5PfcpiHHucawx8cmaQaQZXylIqv7VXBbs2V5IKS0dTkZ0vKFGbOgjaAzsIe/WGwf3lta5BrYLZDtCOZUraTztJpUUcKSUg4ODg4ODg4ODwyaAOobE0ra912//1XTX+KBAmsymC5p8UXJEkoXi6PRCRgKYMKfzMhwz/i8knMdn00oAkYR9+755mRyKSKnik1y5qqVLHPd+h8fUyBjigOSYb9dRTJDbzi4XlBRqRwDxGmNkTNcdNIkyiSvkF8QDx2DMJJnfPbukn0H1MpsqyZHpIbn24Jj+TMnRt++d1eQSJcxsOi+TIzH1l0GhQTIG8QPZRBkUaSdKK2tyDkg4SZhJ/ChDvPbAqJJ1t55c0Dm95sCoJuMkuswR7wkl/EqsMQbmwXYrs0m3BaTJ7acX1VwdD6iqslIQPIagIZ1EoYGSbCkXkPFERDvXMTf8fhkFVLGsRtok/9cdGFOlGYkkSh0S/q9/d0Z8fp9cs39UE1Q7d1wfJAfkA0n2d04vqcrqVMOnZiQeWUVCWFN55tw+ICy021sooNdKjqrKFz6fCLdNdruBeII0UiImHtbjhhvxWRyOyr0zaSVPiAdDYgYb17E6hrim2eWcFMoQiVmddxJ1NXAum3IxyDeURCiLqgJRmVOjfS8gI3hUhzCyL6t5PCQEnycp70besc8oYYTJILZYa8olKXnlethbEF+QepAtdIq0paD23BBqU0OxVaVV7cC6QJIcnR5SYos1JMajkYBeI6TlWBIfpZwSr8wx+4H1RzWEGos5M4b7eBmtkEcQG8xdJ4KCc1uCi3VhniAtIFU0fHyUYFKCWpSpkdUeasbPKyRnF0xnP9aSzxFrkLtesN6QrJBb1Y01RtSYtWoxyFLmF0BKWVN2iCb2K/PDdej9smaIQ8oj+dd0qDNrCbQEloYIJdOZs7RszmFIKmLI3M96Becplnu7SGKIuWFckMNqgN9QShoC2+chqsz9iD3Fv4yb90EOdiJVW1FqKBJbm07sBjhSysHBwcHBwcHBwWETICmGFCLxrdchdOjWVZGlHG3M6STlUyKA7lIoYEiKSVanh2OSSxclU4JkMYkSqhoUQ5AeD75iSgkZ06WOLnchVSRFQsGm1wlJTMjv10QOZRGKGsbRrayLRBHCiDExtnaeRBA9JNFX7R9VMuje2ZQ86IrJZlkWii+SZUzYI4GAnM/m5QFHJuSW4wt67Kv3j+pxSOSZCy2xq5Tl5uPzMpGM6DWgyLHE3TUHx3TMXMNSpiRX7x/TpA6yDBIIIo+kH8LDdFbzaVkchJolgrxACQZpcvWBUYmF8NjxqxKMZJ5/VblBNzUtbfOrlxVJKKQC186a4oeEsTrv3zsWk69+d0bPCbFG2eT/Hq8pUWi0VxAEIfUG4xyUjXF+VDwobCC6bDLOa5AprBnzY/1lUBwZc2eURKvLlkhY+Wy7rmzrgXlkzjg/RCZzhek9JBTJPqdhXrUEcjzR1esJUu3m4wu6JhAHqElIsiG9ICBZW85ByVI6VNbyNcbdqdse6wKJwYO5h3ijbAoFFuRUu9Ip1p5zMm9wU0emk6t9fPKGpGRP8pz4vXzPcPM9jP3u8ym5Yu9Ix+skXiFL2a+U1Zoul6ZMlJJBzj0WR5EFiVjTubD+SIzbNgpYyJb0vZ2UL7abYOt+5bzEkjGKr+k9wRrHF8qmIcK+0bjGb76U1jERl15ALN55ZkluODymP3MfgZBq9aQi5li//WMxyeWlb7BXtDy4VJXJCUrwAjLTIFi4F0AG8tyqNzk79zVixXbUhDhmr7eSoMQ6ZW52ftQfS++vVV3buVRV94mSnA0lVbdyUIhAyELmohfPqnYKTHvNFQ9ZxYP7/lLFEMqA+2s7/y9LqrZ2Ek3lTCnmZpRgFyscKeXg4ODg4ODg4OCwCWhnOD+eM4Vm5zvSkv1RVDGjmgQjdbFePXTaIqlC3YGnTFFM8sbrd51LSTISUMPw8aGYDMUNkUFiBEECVeJtVa6Kl5BJmH1ivrEnMe4E3gfhRXlZp0SZhA3ihGORNONttWc4rgmYRExpIQkVih+IGAiF+qm6Eh8kmxAn9tiaKIYC+h5UUHjq3HVuWcdNKZRRkcQ1SaOTGcn14amEHJxMKHFHuRPJNgkenfxOLWZkLBFV0oExMo7WMjau8Rt3zUkyGpbvOTyh5XidQJILAYDvEGoslBSQbVw3ifC959OaBC8Ei5IrVpX0A6YzYFSm/D5VySgZEUfhQ9JbU/UE70dlw/HOLObk9pOLmnTynrl0UVUVlJSNJ+M9lAKZhLVfQoqYw0yf8e4bTej8LqSNWghijHHbJB7TcO042Mb4HUAuEuN0SIMwgSAlflHNkYcfGDOeR8QxJBcKF/YDRI5VwXQDc66dC7VMsKTjIY6IMePrtXLtvI9yWMgB1s/+jtcsSZkpBHRd8XRirBYo5CCqOpESED5cH2onr7G4jiVuuvKxJyD5KAGFeIakRA1n416JzVpdko3rQfGEWsqWPtpjQthwLi9px+9RFTJ/7AsIOOKd96CwYT9BjnLN1ncJkrHV/6hUMepN3mPWr9qWcAwH8Rur9B1bdqyn5zPNbpqM0ZbBolhjPJwe1ZyNNeaejcTveC+EGNfIvIt090hjbSE8rU8T51fSvlRVgsuWPbNO7F8vKWQ9zk41fN8gEiEQNwLTxa89AabeWi2EU+tndc34QqFx/mpjHvDF241wpJSDg4ODg4ODg4PDJkCyBcFCwnjPubT6/VDuQ1LUSvyQRJHcUwZHzlLOp6VSCaiP0lfuOKeJ7FAsLrGISd5IjNVMuVrT5NcqZUwybkq8IGxQvVxzIKGqn25+JCTt/Bavm1a/KxI7kjZK10jajo0PK0nBeK8/PKZG3nqMfFkVDyhJIB9QPeFH9PW7Z41fTEsHL5JNSne4HpLFH7xun8ykCkpCTQ9F1a8HJQhKMspdIHsAZBOfhczZNxaTbKEk1XBQjkziGxSVu84uacJLgu69Ft6fKZTk+67c05WQskkuXlAo3GiueMWBITWUt35CEFIQB3hJ7RmhJBK/m2LTDHv/+JAqL5gLU4YV1jFD3qDDggSCCKCECWPyVLakhCDd+jg+JUmQWFxzJ4USpIsqWfAPK5tzkbx2K1vSMaSKcja3qPECYWE6MEJUBDXOeI011yaCyigYHy5izcYuL5NEE2uQDBAxxBjJP8dC3cL78TGDNOOBj5e9FvVqCvpVTdSroTnjRW011lRPmQ6BHBuCSgm1SFDVSKjYmL9A2L/iydMobVRT81ROu9x51YCQu1wfc9TabY4YhWBhT0GotVsLSCSIZy0nq9R0jF5ijDViHHyeeaYr5sxSQY/L+CEx+Z0towQo5lDKcX7Kcfn5yNSQlmpyXK6V80BIe1VVxK96yakPXUHikWST9CJOIdXYr+wlYpk59V4Lx4Zr1ntKg7zqFXh13X5ySeYzBb0HjsdNx05iA9KV+Lxi77CSiyi07LqwnsNNlaZRbrE+7J9+YVVz1k+Pa2cMzD9ljVoOGg83lYEAIor9yO+J036N9tcD17XeMbVLaqkqtuo4nS9pLG5Fx8GLAY6UcnBwcHBwcHBwcOgFoZDIb/7myvMG+Oadbmgki1fsH9YEiEQQJUCgQRCZ8o6qzCzlNDky6oW6+t2MDyfVyPzTt5yRq/ePaNIWCxtfKpJTElFKpiAibCtzEirUJCSlJHPpRuJO8mkObUrTSNJ4Um8koZg2q+eLllSRDFdkLmUIBhQyqiip11X9QpKEUojypaFYRBYzJU2Y8XoiGYQMsMk+SW25XJNQAiXIigKJMWl5UizULIPSsiv1xfEpOaVeVQdGGx3fjLdVE3VRr6JbTiwosXFgPKKldgf9hpwzhEBd1RFcA4QBBNcV+0bW7UxnO4FBKu2fiMtYMaIllyPiU2VLvlhWAubAZEKTSMbLGkIq8FlKCpn/QDgoByYSSkSxJlwf8aDd0vx+VWTYeYKIgFTiOqdHojov+O9A5KhyiU5vLWQTKimSZ85/bjGrSe88xvEdVBXMA+OfyxTlwN5hJXgg1Sgj9PkNMWXN0+2/9jVIC1XJQbCo8qURQyJ6HcQ0xBXkKN3pWGuIFJ6jBLIlVJwf4oixMk+9qGBaoZ3LGkQXnyfGrYIJUof1x9fp5Jzx6mKcvIf9ooqdhrH7jUdWe/QwVkjN1rI5LffLldXTx9sxzYI4Y+2tyg+y9h7tThlrEj8AMohxscZ4lqG+o/yThgU0NyAWIE4YB2NlTm1JIPcGruuag+N6nZB99pyHJo06qhXsF+KS8xF/5xfzGkvMAY0DUDBCOvN79gnj4x7D+SBtuM9AUrdrIuAFawCRwrzNLOfk+GxGPfIoDxyNR/WclhCHfIMY4hyQgAcanmLWO816RkHeEEu8vpxb34B8PbBHIJ142JJBykGZS4gzVKunfea8QzHTXROD+q02FrdfIjDXnIu5Si2XPCWnZS1n3K1wpJSDg4ODg4ODg4NDLyBxGTVeSV5gkq1lKtW6pCEQUDnly3L7KQyXUd2Ybm8kTMu5shyeTMpIIiJ0X19YWFBSYjgRlsOUrOUKSr6YFMmUoqgpbl1k31iimcSQrEIioRRB2URydWo+pyVjqnxpJPVWBcPPmUZiao3MSYQwgmaMjJ/yF96vLdzDfvXI4b1eE3GSY5QQtqsfv4d84rogSfBTIQGjWx4kE0mv1wcJMgefG9QkqMmYE87LNUM+RD3VNNplDK+nmCEcRmt1VVwF/eUGIedvlvFhiM4ccN6xIVO6oyqkqiEGWpNOklWjvsEbKWl8aUIBNSXnHCi/0kFjXu4lKLhmo9JaViLLQscyEtUEeDFTkGsPjWp5IwQOJYqWlGLeUK8wZgjC6dG4EizME+OlvBFlB6oqjqld7nIlJbAwo+Y4nP/UfEbJIEtStl4b8zOeCMuxPcOSK5lSy1gbomVNLCsZGTAdFduYgLPWkBIQjLwP3yxUPLzfXiPJ/01zGTkaM6beEAJ8ZjPgXBNDpgwUVQmkF10jWcMR9SiLqvIOYO7NvqhUKlKr4q20ElSQHzwot4McNGScKV1kb9iOlWuvG8Izp9dpO/Dtn0jIHWeWldhN5X2mjJXSu7m0/sv7rDqItYRUvum+OZkO+JXEhAA7a7tYQtkF/RrrEDhK2C5zjYZAs90z2wHyjzVn3u88syylMj5Ndd13lBUzBsrnIIk4j8ZQMqLnYy8TszxHSWWv3Krg2KfWL4pYZD8V2K+VmpYYH90z3NY3ibhUhVuW0kZjQA8YJ3vO65fGc2IEAstb2rhZWAVVa3dDSF8IdfYd8ct+b6eK2wyMwhR/KVOybYldS6hCJPLfBGKxjFStUc64W7F7r9zBwcHBwcHBwcFhAIjjXVKiRKmqyRpJMc8teSdJQlEAAPTJSURBVHT59JBMNMiTA5GgTGJwXqzIuXReVUoLpbLceGxSiYhT83R8o5TLryV0kCMkVpBWNrEiUQRWmRAeiWmyx/PDUyahbQVJEcknyTBJGQQOJAyJqy21guT435MLSqJZpRNlLhAx/I60CpUUqpC7zy0rscZ7MDuHPONnElaIqdFwsEmsANsl786zxk+Kzn+25CZeLKvKiCSYhM2UzpXlu2eXdayQbxBDqWhJSbTZdFE79F25d0QVXfedT8ld58pKRBgfn7Aqaq7aP6LJOc9JjJkXkkDWgTHymh0DUPUYpUwhPF/8aqLMe1ph/I18SkBODRvDYz7L2Ej4rz803iRoKPOypVwWjAOliHpm4Uc1ZMyxIdhQUhmiAEWbITSYA0r9gCVEII8ggzhPqyH6XEOJ5W/MOb5PqnzqEXSkgzDDVLvVBJ+1Z/0YEwTKfCigXSSv2mfMtO14GZONU1Py2F2F0ys4LuQPRBOEAsb64XBA9wKJPvHMe4jJr51ckLHk6hJa9h0kDgQA0wZ5BznEmNlr3rn07h3IRVSPXoKT2IEsJHYPTBiPIIgy9v9Drpxe43WGSoZ1hqRgfRkDnftYW9aJPQbZl86VlIzl+JSmruf1xP5lSNxraBRAjFRrVSWgINsoFT2zUNNYtGpFC/YWew0CGB+r8XBFaks59aPSY4cDWlbI3spBgoZpOkBJZsCQ4h0IJFsWCeFt9xixiToM4m/tuvqb6stBl7C1rikEHGvA+dhzEIPERDeD/15BrHB/IfZH42EJ0GFR9wPXZ/aP8eszZdYQV5lGWfNWq7V2Mhwp5eDg4ODg4ODg4NALqlWRT3/aPH/Uo0QCJolBrWE6SJmyHutxRAJCMnv76SUZXcxKQFUWMSV0UAYlowGJhP1C4707TqW0G933X7NPyQ3MmK+aSqrCpRUkdpA0Nomx7d9JbCkdbKeegRghOSPpI4mGWEFZYY9BQkwinytUNJGs4LfTMCiHJJrPGPNqkiuIk9E4SouAJtfAmmYXI0FN9ElmLSGlx84UlICjPBCFlDcB41pC434lj2zLdRI1jnHVvlFN4JQ8yBvi6fBEQo7PpdWDiuspVqtaOhgJB1T1QBKMKmV6JK5JIsTP2YWsJp4QEFz73mSkmVDzHpQkEIpX7h+WmeVCs/ysXbmUafUeVEUNpVGUIjLnEH6tKhuIB4gC22HPC+aWBJxzlcqGAAw3kn3mgRJNysCIK0gDFFZ23rgG5ghiCyUNJCKkxD3nUqo8gzhgHrgmjs95SJT5HO/vBpJoCDGIS2LZu1ac08Ykr1MedtvJRduAUAEhBmlE2RZEBHECCWgVKxC2XB9z1s0Xqxusso3xFUsQjcZzys7xcCyo+/LIVFLPZ8v0Wsd/97mUXDY1tGoveEHsU4oJMKVvfc/+MdRSi3oOFI/fOY3/WVz2NlSNXtjuchii89ysn1EvqRH9WFzL+NjHrBPv5Tn7gGvtZoZP/HC9HIN1T0TqqkiC9FioG1KU0rXW+bbKpKv2jahKsFAsyrSq8Vgbn2TwYsoUdd+hnINA89V8GqPtCDwL5on9ABG3ojTL672jk98SRBbzstW+SsRItmxIXs6lsb6c1/F6STbGzPr3agCvhvbLeV3PA+PtmxeoAXujtPFEOiOL2YKS6Cj3djMcKeXg4ODg4ODg4ODQKyn1pS+Z5z/0Q01SyqhC6kq+QESRyFjLYIgdyJyb7ptXUgCVAIksCV6tRkvxuhwcT8hN9y3KlftHNTmZGDKtxtsRUlZ9hWJjjXFuGXNrDLZllVeOdmBbzClxQFKJcgKQQJHQz6YpGVxJ0lAfcY50uqI+NpBBao7eKCEiAYc0owwR5YntCgbhRgIN4QDxVUnUNKnFs4kEDwKDkqd2yT+JKkoVOrcl/abkEY8iPrecK+j5rcopGQ+pYuO2k0s6lssmk5IpliVTqMr1h0ZNp7LGcUkySchJuEnArzkwZrohthhXiyeRhLShVKtTF0MSfczdGR/ziaKoE2FAbDCnkAte5Zh33UiGIT7o0Me6kgSb1yFWCs3SSJsccx0QPpAGqFtIcHVdGgTQgQSkYVgKmSVVZEGAYhRPAECSchzIgW7g95Cf3tIm4guFCWRH8/oClDgGZTFdaMakkl8NggiihJiGnCAOJAgJR1mo+R2qFe2mFjUkX68gFiB1Dkwm5fZTizKfzsvVB1bUWgvZkib/yVhY55A1taVSEIWsB+P0KuXaenMt59WbCrKnnSoI4hLjemKeWGQ/POjYVNvj8XujajIxwYMYy/HZhmIGBdxV+0c1fk3jAUNO2m5uhqAKqpKP40BioYZi39NlENIj4EdhGde12zce1z0D2QPpuWYe2cuUz4WChlT2GZN31HUzy0UdBz5ndAqdaZyDWOxGSFlYAkyJveW8EqWtZXLW1404DW/Qe6xf0PVyqbriX6XXW+SelTfeeJWajgMilavEbB4CuVtZIWtLXKMstGrGTuA4HI/Yv+P0kqQLJVU9MjcbJWkvdjhSysHBwcHBwcHBwWETINGkfI1EW42vGw8SExJxDI6P7hlSUocObyTgxqeF7m5VOX0uJeGQX64+MCL3nFtWj5v7XTbe9ly2JKpVTUCyWkvXJB4Lq/qDMUGWVOsiJ+fSmtii0BhrqGS0bXmlJtlSWfaNxtUPibKjsaGIEgqMnSQL9RSeSPzeJlr8bJN5NU6GFKnXjbmymG5WkFy3nszKsb3DEowEVclBgtwtsWPOSMo5L0k3ZBjJIvPFWCH8KNm6KjqqXkyYQUO43X0+JeEAa2DIEBJwCAmuEZ8m1FEQaCTgKIuM6sSU8kFIWYWbvT5IC5QgXE87sHb8zqrG1gNJLQQMRAhJJ2u3UhblV6XVUDykiTtliapIC5jXIeUo92SMXA/jP79c0PNjIA7RxRxAzkBs8TNkBNdfyBjyhs+xJqpsGo0rQck4unnY8F7K+HivJYzwcoLs9K4hxBVG9Wfmc41udoaU5Pp4L0oyYtYQDhhx01ES4++4XhvvhcxdXiipGgfCUL3F1lHLUOJIORpjolyRMqlj+0Yk0nBFQhmHKg8V1K0nF+XQJKV1eHvhiWY62dlSP66ROZwaMSWegDmzRA9j7RS3upYhUwoIkQPB6PWw8oJ5aN23zDPzwLzYMk6LUMzfJIJ5DwQVRFUqV9R9CRHL+yE3HnBkQm49tSiHpxI6HvYK66bE1Bgd+EzstRsTxLm9loViVdcMQLbZLp3EZj+ElBeMFfJ3z/ha9RjrQAwQ14PwHusFEE+sN2tsfPd8uvYQQxC+7Av2EQQv4yYOMoWs3iPakZi2YyOfaS3Z7AbKTSHjxpIR3UeUzLLeHKPfOb7Y4UgpBwcHBwcHBwcHh02AcinruWS7mPHNOYkhiiOS4T0jUfH7/JIqFOW7Z5aEL+oxE7/15JKEwhG57uCEhANBOTQRlBPzWS3hq0tZk1GOZwkb1BTe0j1z/rLp4LaUl8OhgPrcLGVKSoLwOVRHP3DtXv08YGyoE8DR6eFGe/KKjt8SUoBkiYTedK1aUS+g7LDJMwnnmYWMJsLMA6QC7y9VTJkY5tMc8/DUUNfyIwuSZ1RKyWhYhmLGEJpEPFsoaGdCRkbyfvX+UUOcLeeVcLKqFpJwrpfrhgjCS8maV9v3QEKMJEJa8gWp1M7kuBthw1yRxPYKxqAligGjpKEUkTLJQqWqZEYsHJJYJCDJSEgCMUPyQaiQsJJA84DwofMh6wzJhXLHXtPJ+ayqPCAhTOncCnGkJWMNdQ6A7GFdIBk6mXpb8F6OxRrjrUXizHlbVXuQmqi18OaBBGK9SKwZN6WgrAOEAwQhQBEHWCOIKx7EuCGoKro+zAukE9dk1UXe+Se2DdGGgi8oWIVjPs9r+DSxztfsx2w+LMlIUE37CT/ITeabMVjlGWWREKGMH/UbcQrJwD5hjroRBJCnELP8D/6oW2kk4x5qiRvIEQhj29mwExgDMUQsmfk1jRHopsjnGCG/iwSDTZUbMUC8ETudyBLiwxKAEHYolywxwpxblROvQ271S5YQF8QIc9yO2GN83Eu4V6LgNEqprUXQ43lmSSbrXdeKgD+g3flMKXZe5xrFmb2XQaZxz+nUsbEbmN+Dja6EiYjpfshewfvPEqa7BY6UcnBwcHBwcHBwcNgEUvmiZPIkgVohpYkW5TiUDkHWDMeqmvCgfCmWg5qgFUsVqfCtfDgkU2NxuerAqBITQI2z8yUZioabptEQQXRcQ6WETw7JIm3eISlI6ElEIZg4PwkTHQBPzKb1cwfGMTc2ShftuFcoa3kXJBVKHduSnGTUm/zbrn3e1AjlAMlTfNT4HGHsTJkhRBGlRIsZUy4HMWC9tvB8gnBACaOdCClvrBtSw/i2mNfoVHV8Ji2TQzFVJfBZFC+QZTbpg0jKl0xXL6NYCsr+vcP6XggJOp9BKIwkjXG4N9Hneigxg9w5eSKjpu39KBsASTNj7tX3hqTcqHqCqmiZCEdlOuBTAgFOhMZbVjHHvAJIPMohuSaUKefmMnJiLqNqqusOj0m+aEu9DFnDXEFskNyjJIPIa44XdY6HeCK21BQ8YjrnrUc0EBMoZ+hqCPnivW6vao/joMizJWKowACxcXo+o2uLkovxt/PogbDQMr6IUbhxbIgV0yHPkIQQVKw3BvjMK8b6vA4Rg5cagPjifHxmz5jxgKJUFiKQmMHPjHJCL0Fi/ZyIG1SNlHfRZAAyYj0ild9TyomKiTI/222vFcx7pU3c2NhYr/Ma+2OpofqD6BtLxFftVVMeGtGYsdcMycacoQCChGtXUmZ9xgBzf2DMmO1bQoo5MYRU/wop9UXLFJXoa6fS4pqI/ckGAbOcL+u5WrvlbQUgQiGaupVvWjAXrCtrxFziowfxztwxfuZmED5YkZBREHKP2U2EFHCklIODg4ODg4ODg8MmQHt1EmO8a/jWHLXQgb1JTfznU0XZOzYk6UJFiQYSe3xoIGhKlYpcvS8h+bpRQJB0QgHtH08qceBVXZAUzSznlEiAhCCh0g5PiYiW6ZE4kWBBPKFswV8IBdHp+ZyquO45v2xaj+NnEg8ruYXCBlhl15X7RlZdl/EDMp5EJJgkShALqF5UTZItaPJPuRUEF2VnEGVq1pwvKWGGAgSS7vZTS3osklMIAfJjxmyfh/x+Wc4W1aych03WKV2zXQYBxEwpXZW5dF7JNls+xzlqFA/6fXJsz5DAZNkOYKuuKWtMm636geS0VyPjFT+pwLpt60msSWBJWknKW7vYWcAXeUvVSEiZb1QrqHsgIomtqw+MNuPB7yvLfKrQVL6t+E8V9TnkHH5lAKPzobg5N+o4yBmg5vXpopq6QyR188Bh7e89b7oZegkDr+E+8ck8QmCpcqdxPN4LSUmXPOatFzWJjWUekxJtEFRlJVkgKVnD+x+ZkKnhuJaJ4lNG/FJGSFxCxBUbiijAeYupmhwcTyp51umcxOpd55blzHxGrr9soue4gIBbSFeMUqkDOaGle8HVcUPM8rCNETpBPdpSBZ3LTuo2SErWkTVhbRkHZBPxRzkw+xKyE9JHmwNArlZrOlftjmcJKeLREFJr5wKCGqWV8WCCdDOEkqo7GwpPyLFOsQ+RyBxbY33GyH2JMaJQGhTYF8yFdz35mXK56lC0ZwKIz0No8iXEnaeX9Gf2xKCN2cN9eKtdKnCklIODg4ODg4ODg0MHVCoVmZubk5mZGZk7c0ambrlFstmsjN1xh1x9v/vpe+bTJU34J4cjalYOI0L53J1nltW/5o4zS5r4QCoEwnRXi8n4UEwCPpFbvluWSohEp6SJHB2+KGOxpU6tiTNqKBLQEzNpObJnWJPGhcxKyYsamScjei6SsWP7gpokUhKCcujonuFVSRilNZZoIrm0CRHHtQkz57Od4E4vZGRqKKafO72IYiCqiacdH2odDo8q5Mq9I5qQehNckrp2SSCEHYbrhyaSqrrCb6UdUUJiT2kb6imvnxMEE9dHkq2kRiSo5TbWx8rbYQ/VCIkwY8JcHIKqVwJiPXNsO3ecm2OiWuqlbNGC+edB0sxcUv5Iwu69VuZmrlEOZhN+o3Yr6Ry0joU5g7RhHSkLsqqVI9N1JTlNSVL3sjPiGDUOhAHzGWrEC0QjgFgbjke0U5sa4fvxQwqrUof4wzONNWvXhbAbuC4+w7z7VDEVkhsOj8lYMqZripIKZR0kJWpAVRy1dJ+E7OC9mPZ3g5YZBvxyxf5RJf0I015INIzCIVMmhkyst4tb5sRLXjAeYh7FTaf5YN6Y92xjTw+3KBlZW9YEEpy4RwXIe4lx1oPPnJqvSCiIIXpRH9ZfjPXjvXTFZI8HPDFtGheYdYQEszEA8WQehjhifGqS3jge+8LrqWc99joBFadViFnFH/ci1JfreYr1CtaUeynz7Y1x3WehgJKdndRt7cC1L2XLcmDCqLsgdUcTtaa6zGFjcKSUg4ODg4ODg4ODgwfpdFre9a53ydve9jb51re+pUkaID19eeM9x5761CYpNT0aNR3W8iW5+b55Tfq1JMZn/HNsssLrkD8oYVDRRGClfD45NjUkt5xcUs+bw6GkqmRKy6vLWNS/p2BUN3Soo/SPY8TCq8tyrDcNSeO5pWxDMRGWB14+KYuZkpIQEAkkjDbhJVnjClXl1UjoIXk4ju3URskbCR7JItfwte/OyHgiIodo+96SVHMcr0LCJpzq57SUW9XJzHbUg3y5bHJoVelZO2BoHQ8YI2drrA1hwVyRnGv3rGpNE/iFakmTXMhCzMFbW7UzV3MNYoox9dL5CtXKcAc/KUv8MDbmDDJpI4kq4zcqq6qSTJCBkIqsBwk0yT9kCWSLnWP8vJhTbxkYZE4tYBRjqIyISe81ElvEAoosS4S1gnml6xpeUZSiEiscF3KCRN9LHjDnxCnEo5agqiG38S6jM96tJxaMoXeHroat59VyU0z0fXhPBfWYkGoQUoDfQYagACKWiYfWMjjeA9nrNRBvBy2Ny2MKbpRIsVBAO0hWk51L8izy5Zp6S/E5W0baCtYSLzDv+Zj/dnMOIEsgrSAU2RPedTPESEnfg+pPy1gbsc/1o0BiXYgHCFyIO1RU3As4jo3JxYBf1xAvOmI1GTHk5b0zaSXZDKmVXUM+YaJvyFOjetwoGKfXm424Zj4Yr1UBbgZqoJ8racwy38Sddz9yrnSud1IKIp6Y8PrQce+ZS+V139uGBA79w5FSDg4ODg4ODg4ODiJy8803y1ve8hb5l3/5FyWmWlEWkb9pPH/J/HzzdTx+IHX2jsTFNwo5UZFbTixo0oUK4fDUsCZ9NlklcSVJzRVLmuyN0Ao8SKe+miqdSJx4HXUCJBGJPq/DT9ERCk8TutqREJKItvoicXxajZerdTk6nWgSTXtGA6oauPtsSgkzyu0YH2PHMwiyjMQLJQ7ECgQYILEjqeM42s0NC/ZKTRKxsCa1XjDmSrWuZXFeWD8nEmBURGrGnjWkAyQRySmqpvVAUg0hwlgY48TQSlc41FnMCWRZOl9R0gmfo1tOGDUUP7eSRJBnECeUheHn0ql0xpTj5c05G34yxkTekIUkpbzHdO7rXK7Xq28QCiOUPZZAY02ZK+aOOUBNxvPJIaPMYY1ak2sUM+GI6WjG5yGLWsH1QkzpcYP+NUk1c4N6iGNDkhgFTKBtyRKkoJKZWm5pDLchObguCAeIkfNLWVUCdiLriC+un/mE9KADIMQM4+MYkJt2rrhmSDvi0ZTDmpJFC9aIMlCIYeLOKohaYeJ7hZDSa4mGtAMiBujMXSclmXqmlc0+RSFJ7LcuPWPluuy57TVyvtZ5gHhjnpk3zundR5wLYhiyBWLo4GRSYwKiGQUkYI4g18bE3BOsXxUxgMrMez7ITkukQBjjQTczl5XR0ZCSfxBdSkQ1fO3aQbsCNjzRLEHYCxFr4mJ16aol+O8+m9b7UL/G4V4wxyghiRfWhjU2nTxXjsnxVQHapitiK/g8c8/9wrsmjJ/44vcY9PM7CKvd5gm1WThSysHBwcHBwcHBYVfi+PHj8vnPf16+8IUv6L+33XbbmvfccMMNcvToUZmampLp6enm43u/93ub71FfJE2CK9pVDV+a2XRejk4NSbUucnI+I8tZOomFNHlW8/CmesqnnfZQNKBmOT6TkkNTQ0p0kJRjnkxJFGU2e0bicmouIz41Zk6YVuTLeVVpQF4oeZUv63tJyq47NL4q6SOBhEzy+UWwHCKJJHnivFwDyZkmckNRo2BK5yXoJ2HNyZGpIe0KRxKM4uoBRyfVHwuVjZeEsYbp7RQUSkyNxuTuc8tKgkFSQQShjOCcjJ9zkASTJLYra+I6K9WKEnEoFCD7VEE2Fleij5IcWtkzrljYr10OIVV03jsky5ZwYB68xIQFCTdjzBfLOsblXFkqNdrc13UtSd5JREn+N6ocYS0hgCBC2hknMyeMU9Urc8bIWw3wixX9DOvaSgRCSiYDfpnPFLsmyhAZ/B4CxtuVjjHZEk7mrrKOCTUxAJnhnWfvdUwko2YvNEy5vdCuhDljXs8+sXMAocO6oJCDYLDH5r1WGUTc0n1PPdM8fkczSzm9LsbFPqDErZUEUQN0zLjbzDnvZRyYnxNbEIGMh71DHDBOPgthxxggefBVagW/Y87svKLOY4+0ns9riq8ldR5CErKSvc05IaNWlFPGFN4qxPBfm01VV60TZOC5xbwcn03rPQXFG+8jnvGXYxxcK58ZjYfkey4bl3CoM03A9bBO2tCBUs2AKd3DQ26pMR+oM7sRM6ZJwequimb8IYlHDQkZDJhySu5TVpnF81783CAhIUUtCQVZBmHqJaUYH/PG651IKVPKWNBrJUbakZpcA/HMsVX1OZ/Rveo9l0N3OFLKwcHBwcHBwcHhggFD5mq1KqFQaMvPc/vttyv5ZB8nT55s+95EIiE/93M/J8973vPkxhtvXPfY5aop21pI59UXiaTpAUcmNVGhdIjSqrlMQUvXSJC1E1sAwqQmZ5cLkq4uyVUHxjT5IfmEaCHZ+8Y9c3L1/lElclByQHRBXBybHlaTXkAJ160nljRZYgyoRkicTac6SCVDyECYoc6gDIqSO1rJ83uSKBI9YxLtU4XV2fmsJuskguTFdAgMJY0iizzT7/M3vXBInCFs8FixREanEjyILsy1GRMECqov3s9xULlAiJEcZmqU5tVULcbPkD62/AoSz3aQQ6NFEs+4uX4UU6a80CSw985kNLlPRpOqJqHEq1NZEEkk69ZKTFmFhFG6GSWRJVRsWedmvGTsnPAvY+tUzmVhSvRCmiRrBzFKuHymDKyVBGAOISyCgYAm5d1AAm+9sFCsEbdWaWLJFP7VzotdOsV1IyK0lDQa0lhm7MQlRAtzTMyyxnRZtGQM88t4uD6vys2qpKyXGeSoP+CTYsWYfAM+x16zXlycGyIE0hLyij2LkhGClfJO4tCW+kEEe826uXecWs4pkYqij9hg77JXeR9EHHHI8flMK5gzS9qyR+nsB8FhAekEuYzSz5bfAuKcuSKuITjYV62EKeov1sUSNTw3+2nF+4z55LOMGXKN0rzZVF7JtkQ0bJomlCpy3aExWZw3JJMXjIPPcH08mGL2H2otxut9PwonJaeyJY1JSMF2JBL3xHaxzn0R0uzgRFwJZWukzhzYklHOpwRVYC1Zpf51y8Yjz5bYAc7FerV6mlFyCoEF4dg6Ts7HlwQc++BEcl0vNMbDvYP55F5uSvpW4tmhMxwp5eDg4ODg4ODgcEGQyWTk8Y9/vHzlK1+R9773vfLEJz5xYMcul8vyzW9+s0lAoYZaWFjo+P5AIKDqp2c+85n6GB425TCrUK2KfP7z5vkjHsGHmgnwnWeWNHlB/QPZsm80LsEg+g3zLbrPZzqEUYaHka8v6NPyufMk2SLaWQ8iiaTRlCrRfS8CxSTH8XgplqVUq8n8clEOjdeUBNJOfuGA3HUupUnVkT1Dap6u6iWSXp9R+cw2SpdoJc/YIEG07KZSlXvPp5UoIJmGuCL5+9a5lHzfFdOaSCfCAVUGQdZcf2jcKK18JvkFJP0QJBA3XD/Jf2vi7C1LIzmcHhlShcd9M2kli/aNGxLLq7iyHQF5UGLDMSGEUAWRvAOIDUpmLAnGe5lTwFhICkk6/X6/zodVhLWqdCxIYn2N+YMIhKTgmKqiCfplaTaz6rObIaOYfzMnpuyO5L4doWN9s7yAtCDpJQGen8mr5xKdFluRp7NaqSJHpteWibUDaj38tSAqiQfO41V7MP/dSCnrA9VpflkTxsFc4i+F0TXkAaoaYtAQdHReY6ymOyAECCSZdn+kW2PDVBxi05Z3kfSH/D4lMWxpLGPZO7ZCQOLTRumqlplBpgZ86gGXiNEJ08Sy9Uji/JxH/22c83Ldo3mNf0M0+NQ/znZvZG7mq6Z8rxWMB2IVwoQSOa7OEiDMJ2Q117K3QYwYPy6jSuxERgGuldJhyhvZL/aYqIsYZ6uNFvOUiPIIKUEFEc16Qcoc2zukhDNgnFYJxb+QM+xrynrxU+N5p3jiOvQ+Vq6qWTz3hdbSR9YG1Vq8jTebKsr8PlWjmQ6Mq3/P3HDd1nAd8rzsIav4PLG7v3FPsVA1V0MV5SWruN9YxaFXacj83HF6UY+N8hLPO9sRkntuN4KKexydV9lHeHKxr5xqqjscKeXg4ODg4ODg4HBB8Ou//utKGIFXv/rVmyKl6IgHuWVJKJ7ncrmO74/FYvKwhz1MHv7wh8sjHvEIeehDHyrJ5NrEfg0p9dnPmuff//1NUoqk5tpD41qCdm7Z+IqgBIjVjSrKGoaDPY2EB4JmKVuQYrUul4/G1Ux6OBGWWi2ivx+JxyRXqspipixnFrPik7pEgkH5viunoENUiWC9bPCXqjZ8nCBpSKI4J4ktRr6oO1oVCySelFLdeHRCE8yFdEE/PzEcU6UDHkyU8ODJhG8PqgiUM9ZE3AuSdG2vXq/LdEv3N5QTJKetZWmQc6bM0CS8lI15wVhtEmgJnL0QfY3MGWIq1iAartg3YhJdPINQUNXxuamqumkhU9KxQ4TweSWm/KZLYDtYQoX3kYRDCDAWrp115jibhS0Zg2joRDgArhkFDvPvVZVwjSTeXGcJD6OAMaH2Qj2o8hU5uC/cs78VcQAxiFoOauWaA2Orfm/VRp1AYs94icl2pvHe1zD9vmwqqTGmaiRVJHFNZn+g5KH8cDIZVTWVeY9IuVJVwgNCxQvdXw1CipggJr3xThwdnR7Sa1QF1nJexhJRvd5eyUUIZ4gyiFTIT6P2Mk0BmBv2YLvyPcbL/uOa2Pf4qUGocL3WZJy447opteR4xHa32OAaIMkghSFfIU/s3tLOiDB0HaDKqLLZH5BoNxwe13XFqy6TKkpOMoZoCwd1XIylX7UPJB2qNwhevMa8MaiKtWBnYoffmb289ndWCdaOrOIzqqKMGKKpFewh7kWtDQjU8DyPitTsMY5x32xa5/SGy8Y1bk3JoiHB5lIrJYvMjSW2vGC+8HBjbbh38N8D7b7qvKYGT0q97nWvk9/93d+VF77whfLGN76x+fqXv/xlecUrXiFf/epX9VunBzzgAfKJT3xC/+MP+JaKP0I+9KEPKTP9Uz/1U/KmN71p/T8EHBwcHBwcHBwcLgm8853vlHe84x3Nn7/2ta9pOd2hQ4d6+nylUtG/Lz/zmc+oCgpVFK91wvj4eJOA4vHABz5wYCWDfCtPwjJDIo0Jd2TFL4akRM2igwE1r4Ys4rlp8R6U9HJE26+TZEO0kLCRVJ5dysnx2Yz+fHA8ISfmMnLtwWE5Mj2sr918fEHVMShsSNhRHd16Yl6WG/5U982kBMcjnpOg8q09eZj6X/lMYooX04EJ042OxMyYjvvkEdfu0zLEaLiqHlnTh2JN3xzbXW5NyU04oJ41R6aSKx3kUgVNflFxWRKIsaN80pKkSEjud3hCk2tIGq+CwQsSb7rPWdUQxFS1kYSSSOLlox3CGuWEpoxRtGOcNSC2iTJJJD+TQqLQaQcScbtOzC3KNY6/f7w3xVEnqHokXdBjraee4H1cB+THYqagsWNJFv5lvik503I1n5lvkmlIBsgNPsMccZ5+YOeRw6Kc85pNE9MQZZ2AAtD8W2mWzXnB3DGnxCgm7p2MrIkH1gYSs5UMwfeKWG4layA9Ia3wQaP8q92x7dpBnLFP2bf9rCfvhewKZn2qVINkYE4YL+QWewdPJchPC2IW1Os1ued8Wi5rkGmQwIVyTfcGMcx6s69Y13aeYq3gGghy1JTEP+vfJKUCflWhdevsyPpQumjLBY3isSynC2mN82h48/dGe5+DcKeM1sYv8RGLdL4+7n+tpvXrwZJV3QDJPKf3oNVqP+593H+YG0aIWpDSTu7JNs7UlwzvNYE8NKpSS4CW1NfP3FsgqrjP2LhibfWes5STe84v6z070sWva7diwzPy9a9/Xd761rfK93zP96x6HULqcY97nJJVb37zmyUYDMpNN93UlEUCavTPnj0rn/zkJ1Va/Yu/+Ivy3Oc+V1vvOjg4ODg4ODg4XNq466671K+pFe9///v1i8v1Sv7+/u//Xr8Qve+++zq+7/Dhw0o+WSLq2muvXfX36CBBsoKqSTvWjcQb5IAxhSapoWyOMj5IHRROKHVQD8RCflVXlKXabFdOEgsZldBOYzHt0AdJwms26ST54vOVRuKGkqSoPjFF2TMaVSKFkjNDBBllCK9BNNiyOBJTCAvKf2r1iioASMZUiYQROl3lisYThbImoC3lg34lerg+6wmkXc4aHcPuOZ9SQoGEjYTsUKMsjeuCjOK9zEe5FlTja5I4knAUFRyvHZnB9XJM5s562KCiYb75mTGo6XXYlEhZDyirtAKMjXOr709d5JbjC0pKqBF2aG03OesbhJKFZJr53KjKwXTuM2bJXB8qoU5mzeqJkzJzyfgswYB6zUvakVSfb3T74pruO5+SSDio68dccK59o9G2iqVOMH48K2QLz0PjxrfHzIlf1T0k763HNSVfZs07kVIKnyndsuvSCggn1ml/CyFFPBojdFNOCeHp9WXiuilvXcyW5PrDnYUOxAwPiJeNrqdRD0FamnJEYg1ias9YTL57ZlmfW6WW8fTyy32zmWZnRkq6eM81B0eVPLOd4ToZabfCEsMoqTg/a+E1edf90YbUsX5Lukaliu5DLznDuYeihowdFIgDyFP2PnPCGOy1doISlzlKN01nyUGBYxlVVGnVdRNnqKu4bxQa9wfGjeK0HYgbW6bY6rnF/LLf+W8CQ7dEsfqgZUsyEyqoB5nDAEgp/hiAWPq7v/s7ec1rXrPqdy960YvkN37jN+RlL3tZ87Wrr766+RyDyY9//ONKatmuJZBX+Am84Q1vkP37929kSA4ODg4ODg4ODhcBSqWS/OzP/qz+PQl+8Ad/UD73uc/p8/e9730dSakzZ87o34xvectbZGlpac3vr7vuuqYKigek1HaBJI9E8cp9Iw0T6rImKdqxrFaTTAGCikQec2D+/PZpgv3dpawsLhfk6MERJVnoondoIqlt2oulihp1S92nfibD8aDMp/OqOCDJg6DAZwoFEckbflK5kikjwpS3W9kP5BMqIsgHkublbFHVJVfsGdbPkbhBomGijTcKhJUtv1HPHZ/P+OtgGuw3KimSL9rSoxQZS1KqF9GxqDJj2RAyHJdSQhJOEmlbksY5SVJVweTDfHgtoQGRQ9e5csNgHcKM5G/fWEx9sfggygbKZFBJtRp7MxYeJJuUYS1kKC0yZZGmh54pi7MlOawd44F48JpsbwSoi5gHSIRuJBHXw7ySwBrSxLyXdWIszJdVg0DAUeqFET6JtNdXCgJQTd+D7ZPqTkD1wWx4CVJIOUorrb+SllY1fJm8II6YIggaLeVsdH/jur0kFSQs5GM7Us4Qd2X1GLPXSbxCwDCHqKHw+mIMp+YzuudsyRXvT6lpvjG976ZUYz2tCg5FjjHvN90ZeyWqvCQmJBXHYTzWMP5sw5cMcjadxwS9KlfsHTE+TeyF6AqpAQHJdfRCSGlXTAzoR1YIx3CLsgjimP3YSupAfrEu/J55Hk10JoYGCfY8MYHaz46nWxkshBH3R/bCZvdeKyC3uY9wP/aSnuwtFJFDDcJuvNH4oBcY0nzlfsYase4A7zLWiffwLwo3R0oNiJR6wQteIE94whPk0Y9+9CpSamZmRkv2IKy+//u/X+6++2655ppr5LWvfa1+S2WVVKOjo6va6HIcvrnis095ylPWnK9YLOrDIpVK6b90QuDhcGHBGug3cG4tHFwcOexAuHuUg4ujnQW+uPzGN76hz6+66ir54Ac/KA960INUPQU5xd+Tk5OTqz5z6623yiMf+cg1ZNRjH/tY+eVf/mX93cTExKrfbcnfJbWa+Brdveocv3EONQUumJIkNROOmITXmgXzMD5HZZlL5bRsLoTnynBMAlVK/qqaJNJZDuARNJsrydFpusblJFssyVg8KGcX83KLzEuxWpMxym9yRfXcOTw1pMenvTukljH7bX/92jGMbofRoLYuJyHGI2oP/i+LOfW7IWGHFEGZRMe6784vG7NmyBr+5k/lJBkJyqHJoaZ3FWVIqFsi+K+UKjISC8rsck5S6tWCGipmFB3VqhJXqKO8Y+Sap4cjcnYprwlrK+nB1ECQ0eGQOU7n6O5lFEclrocug1LX30MMMB+2E1s7jCXCekyIGK4dRgVyJ1soyXyqqp/l+Go2v86x1oN6f+E74+scl5AIEEDEAKQZ82zfy9xEQ34lJYkZUCpTngXpYCg1fqZkj7leypQkHvaLFHvfB1w768K62+slnljLc4vZpvcS44MMJRa8yGrnQ78qlli6XMGYdKeyRY05xsG6MBcB39q8wZq+a8leY54geVCvwA1QxrhS7liX8URY4ysSNHuuUjV7aCwZVXUhqhTAmPk8JCtEJgQS4+T4HJvY1SN61pfPGOJshazS536OsvI74sOSWONJ1FJVbVgQCSUMSXWuqHsfltQo8iCYIaui6k3FPEJucV+IJSPrrhX3FMjJZCQgsVCg+X7mi3m1P7MPjCLSeDeZGDRqRggium6q+XhDQbnVOR3jG41D+jT8pUL+rnuKGZ0eiej9js/QAXJQxBRjgcSDiPca8jOfe0eInYrGcFx92zY2D3yefbgK9bqMJUJaVl0qQ54OTo22k9HrHPZNSr373e/Wmn2UTq2455579N8//MM/VNUTXlL//M//LI961KPkf//3f+XKK6+Uc+fOyfT09OpBBINa58/v2uGP//iP5ZWvfOWa12dnZ6VQKPR7CQ5bEGzLy8t6Y9kqWbzDpQ8XRw4uthx2Mtw9ajD48Ic/LH/xF3+hz8PhsPz1X/+1mpFDLkFKMc94TT396U9f9bmXvvSlTUIKHyj8SH/lV35Fv/wEkCyQWVuOUkmS2aw+zXC+sFF/zGdKmqzPz+Xbfsyn5VdlWcwZz51o0C8B8cvCfEbmllMSyBSlWsho4g8oQcLAOlKLyPx8WjLFilw+nZTRcEVymWXTfS4QlXi9KrlMUeZ9BVViYGrO804gMT0xj/+JX2b9Pi3VgVyq5H1yerGiKqMlWX0NQ766LNXykktXJNMoAYzW6lIr+iSzXBb0bueWCjIUC8pMOWvMm5cLcua8uc6ReEjqBb8sFtJ6vNl0UZVWyy3nscilinI8n1pjpg5Q3ZxbLspwNKi+REGItJxPFheyqv64r5KV5XxFQpWI5NO9JbHlfFluX1hQQgwijL9kY3UMq+tSKxRkdgCpBvMznghJIdM+EeW6KL1EKUPiOjdrVIReMB6OU8hElLTDh8xfrsrJM5RE1mQ4GpATZzJKHkIEHhyLSr2U7envc12zVFHjYWkh36bkqyipJb8SeRjUZ0tVqeRXq7AYG+Vg9UJacrmypJfrMpEMayxAAty9uKjXNp+GBKrLuWCpqURJFyra4ZE14PzEMuvLuIgDSN4sZK7RJTSRSRflzvSynuf4XE6JvaVyTpYWF/RzdKGzZav1BllQrOcFAaJ44haiBIWYlrcyH1V+Mso1pf4aJuv2X45p5jy4inxglqNSlGKmKjTh476AynASwilYku8eN/lSrB6RbKoopwppvbZzC3nxl2OSXUelxfGIg9BQWGbyK5MBATaTKkqoYu5NOqdLBTlbyih5yDnZNxAtp3MpfT9jyKW2979zqVRRZspVXa+ZorkfdEOgVpez80VZmPcr6TcoFIoVmclXJD8cWaWMs/eXPcMRmSmv3YODQD6blu8eL8tEh9LASw3p9Prr3DcphfkkpuZ4QUWj0Y5MGH8k4BMFbrzxRvn0pz8t//AP/6Dk0kaAP9Vv/dZvrVJKYYI5NTXVvl2vw7aCdYe9Zj0cKeXg4shhp8HdoxxcHF1Y8AXiv/3bv8nf/M3fyP/8z/80X//TP/1T+ZEf+RF9/oxnPEMJKvCpT31K/960uO222+RjH/uYPsfmAWX9BbN7KJXElzBd4uJ8ydogpaamzDf+3m/zSexI4ElK676aHB4JyQ3xsJZxUN6BWipTKMlSviK+YFTmS345OjSqCW+4XpTLJ5N6jGTWL4FSVY4dnpITsxlNSjHZveLwhB4HJdXkVFJVTfHhWlNJ44X14zlxLiUjIyOqrNISvcZ4+X15MSdTU6Gm+TcJOcoT/Tma1wTfehpRPriUK8n0eEIVNnlfXktSLMkwNmGURq1d37R0yWdKEDt184oNlYxXVEs3PotgPK8G3olhYzCP+uPySFKKjfKlY5ORjgbm7cBX5RwD4m/PWHxds+R+wTxkJSP7OpTuUVKGGuSyA2Mdjd4tYknKwCoyNhKTrGTlUKPr4dRwQNcUUJ5G2VMEI/RUXcUA6/19Tle4PRFKIduXc01M1rTUMZaMyui4X2NuairZjB+SeR3PpFHpDZcq2t1ufDwu2XpWDk8lde0puduLqo8YGTVm3pQZ5n1FuX5fXF9HvSS+qhweC6u5frcSqvGJmpa2BqMhGRkNq4ppOY/yLb5uiZTuQaGMdSVu+wHKLmKO8rJVxw1kZSwZ1tI89TfLGrUUqjPKLW3shxNFJYm13C9QkP3rjFd9kHxFLaVsjVHOUw6kZXwiuVL2GM7p/uP4xFjBn1PSG/XRkfF42/Lerf57ifVS763R3v28pqZqpmNmOKieVIMA88UxmRf2pJb24iFXrMhlCf/AztMOR6oRvYdPT4/KbkC0DWe0aVIKqTXfQtGtxIJvpv77v/9b/uqv/kruuOOOZk2/FxhLnjhxQp/v3bt3zTdZdEqhIx+/a4dIJKKPVrBZHAmyM2Bkrm49HFwcOexMuHuUg4uj7Qcm5H/7t3+rpuTz8/OrfveTP/mT6h1lk9qHPvShSjThGwUphd+U/eIR8srixS9+sRw8eFAuGCChnvtcferjeZvEDa8S2r5DRpHsjsQjkoyFViW+NF8KheoSqgS0JC2WiGrZGqU9kD18i06HJggGzKul8XdWOBSUWqmipR8Yq+NDE9T26ZhP1zUR9v5tbMdCiRJkBmO5ct+wvkdJJy1XM/5XePEkYxEtTQKL2YJ+rlw1ZUok4RONYzOmStpYayxmyzKSwOdpJcmNRdbOi0nQSzIxFJNQsHMKkoyFZSFTUkVKO4JoPBnVhJJSSQrXMkVjfM11oPQajhs/pH4wORKXeiov55cLq7ycBgHID9a+XcctysmMsbjpbrgexoaikp3LyFyqqGvPetJ1MRAMN9c9X67JZdPDWqZ068Liun+fM4Z8qWa6o3V4X8Tvl+nRuI6VMkyNnzplheb9xUJFvdR4nU5wsQiEZ1FShapEIyFd75FgUE4v5nV8EKJwiFXtXlbWUjLUXcQhaqu9Y8bDaj2E/X6dOzrhEYOY7NP5jhhaL0cslMtaDrjRMqp4NCwpyJKW80D2EJe8rqbepZqOjdifGok3Yz/B5/M5VURCHnUbL+QV88S8cA9oh1AoaNakcRzeV62ZfLlUKeuaLOfM/ujWWW8r/15ibAcnh/r+zP6JpJxdyDbuH4MhjBgH90Dmlke+XFVSdGKY+B6ch1UriIE7Ti81ykq37jw7Bb3GUV/RRhneLbfcIt/+9rebD7yh8JDi+eWXX65/UFhyyuLOO++Uyy67TJ8/7GEPU/m19RIAtPKFmX3IQx7Sz3AcHBwcHBwcHBx2EPh7joY2T3rSk/Tvwte//vWrCCm+2ISkQjnl/YOcP1ytryhG6B/96Ef1+fHjx5vdmbF6oFvzBQV/YB84YB4tf2yT2KACQM3EcxRLqDWs2oPSItRKKE54j7Z/125XIU0Sp4djspAtqlm4mjDXamo0TqkbM3ViLqOJOok7BAKEFUkVhtcoMTinNV9GuYIZ8sm5rL6OcgMD74OTSckWMa/OyYnZtBJN1j8Kc3RLBPAZxodyRk3bixXt5sVxgVX8zCyb2jb8ftYDBBdLbs2AOwFCiOtQL5424HfMG8djPu3PqIwY70YTPToRUmZ2btF0zxoUtFNdG1Nnxg7Jg2F1L4QUII7wTIL4scbhSnbWVwgmatAoR+OcKOCIu06AtCROUIaspxCD8GTtIMQoVUVlYoH3E+Qbpvt4HkEO4jWGAo34BIwF3x5eR0FI7PFeTou/EutOXEM69tMVj7lTNVCpomPEpN1r+t0JjNEajW8E1qibveIFhAZm7oC9ynpQUkmcWlN2YDtassdR6XQCsYjqzHaT7IRwS8c91t/uV9bKlBxyL7j4ysa432B+r138MoOz7iHOiEd77/DeA7cKNGxgLbi/OmxQKTU0NCQ33HDDqtcSiYQaS9rXX/KSl8gf/MEfyP3vf3/1lPqnf/on+c53viP//u//3lRNPe5xj1NTSrqnlMtl+bVf+zXtwuI67zk4ODg4ODg47CxgmxAIBPRvvk5YXFyUd7zjHVqihzeUF3hHPfWpT9W/9/gCshNpgHrKlvDRhY+/DfEoRVEPUFYlkzuzlTblT5TjkXTSYc2WxmhZU0PBQ8cyElOSIBJp00a8og+fr6TvUbVTOKAkED9n82Ut1QsFMfguKvnAMUlUOd/d55ZVGcL5jRLLdG/jnKhAIJvIse4+l1Ll0cwS3eQC2gWL5L1dCQ/qDpQnKFZIgkkGUSmQfNsuaqarYF1LrY7tG16XCFKvn2ypaZa9Hhi7UT2FOyZ2qKU4FNcPuH5/wyh+I2BclGLRgYtyOtRXGynragXt4FvL9qzBNvPRWuK4HkwHPp9+jjiABKnVDfmApxiqNmPMbbp+QdB0EsZAirHGXrLE659U9/xsya5MvqykGMqvWrSu5NK951Ma95Rl4ctEDOK1ROmaLSskzumed2A8LnecWZZbTy4oETAc53Phjt0i1wMJPqQYZB3kdqChDFovHtmP8dEN9fxSMMd0a+S6vJ34WBs6bgIlVn2GnIJwa/d5iDv2YiewtyGcvKbc7QAJxVpDNEIWcw+BwCGEIcIhvylP3WrSxQvIb5RN3TpO9gqOwZ7UUj6fb9352KnQsSfD+qVCr2T0bsDGd2IH/OZv/qZ6B7zoRS/SkjzIKTyojh071nwPBpb8YYLyipsHZpV/+Zd/OeihODg4ODg4ODg4bBAodfj7DG9Pnv/4j/+4POtZz9IvFzEbByjlIZL42y6fX22QjP/n8573PHnOc56zpslNO9BBDzUUfz9+5CMfUeuHt7/97fo7CDFIqQuOalXkK18xzx/6UPp961PUTHS1ImlHMUKiDmnEc1QQwaBPwsGQKhlMNzGTkKK2mByKyOms8YaCYKF0jbxxJpXXhHTfWEIVTmcXs/KdU4uqmCDnnRyO6GduP7Wg3jZ0bCMZJUEmeSNBRQXDMSCQLp8e0rKmdgkiRBdkA8fmG3zIDpv02WTwu2eXlZyClCLxxQ9rcijWE5lAG3TIuF4JGKuyYRwk0db7xSbUECl0LuN43dQjGyKm1HcnZ7xvBtCOnjVv+vw0CD8IAwjDjRIx9pohLCGUMAQ3ZXgVVV5ZoGgiBllf1DoQixAyVqmxnCvK9Ehcjs+mjRl4g4hqzoe3e52Pjo51JaROzqZ1ji6bGtJuisT+kekVn1+UJ5bItBwIBA37A9JoPBHRjpOoqEjMNzoPgLm0JAV7jkETN8RopzJMCE9iZ7MEjYnDioiHbwoqKWaIdEgh5nP/2FofKMBeRTXWSSnFfQTy7MDE+mQ8+wPVFR0cMXSfGI5IFiLQ59MxsUYQU9sFS2LHwobIHgSIE4hM7nvgYiWmiH9KtY/uudAj2TnY9F38s5/9bNtWvzw6gT84rBTbwcHBwcHBwcFhZ4GOyL/wC78gn/jEJ5qvoXrngQnuT//0T8vNN98sX/ziF9d8li8dX/CCF2gJHx2WewXvhfhCcZXNZvVLS9tlmbI9lPk7gpT65CfN8+/7viYpRZJ/99llCYf8mgSiXiEh5t9CpSqhuilJw1uKUimbhGvb+2W6muHJ5JeldFGNm217+6nhuFy+d1gTziNTQzK3XJBAwCfjQxFNxCeHY2oefdN985ocTwxHldg6t2gIG0qEKFGijNCr5rCAhEDBhGpHy6vCfiWQUAx5VUKM9+j0kHzrnjlZSOelWKnLUBQyYX0FBGVVJKetSpFu4Ho5J5+DOEBxYcZh5jEaCirRRrI9aHDdzCGlaJB9lAZuBhBCKNOYX4guSCEM2gdhqA7RxPpyTAhIFGbEHaRMJk/nt4oUZ9IynixLuFHmGI8GpVIxCqdje0eUKFLPsgbxZHialZ/bxQyeZyidIEYLpbWlcpAQM8u5hll+pbmWxBWfh2S8ev+oEqeU8EF6bnSeUUlZpRd7AxbINBOoaTy3A0pCrzpso6CzHSQz12TnijFwfNRjrMm1B0c7lqwyXFRV7cgx9o2qC3tUN6GUQuGHWg0CijgeipbE54fAjm47gcO6+BrXMShSyktMWcXUxag2Gh+Kyl3nUroPNnt/uVQwcKWUg4ODg4ODg4PDxQtUSnRRnp2dbb4GIWS9oXgdA/NWi4dnP/vZ8vznP1+tGjYKSvggpYDt1Icqy9uFeSeC0rpiuSLzmYqqEUiaIIVIOFBEtVNsQCRAHMyli3LZgVFJF0JqTLxnNCZ3nl6SQqWmpJYtxYN02jceV9IKlQuJHknZoYmknJ7LytmlnFzdMMyGaOB3KAogsNoRUqhqSJqVhBmLyxxG30uUc5kSw1ZgZL1/IiF3nU8rOQRJhYl6N5Cs4xeEAqtfEgYiB/UPiS2fH46FVX1BIoeJPEk26h7InkGU2XkBCcA8kFD3mzQyZuIBYg2iAMVXJLiSRKN8G1QJlXbiS9DNyy+ZYlkSDQKPWEElRQldLBaWI9NDTdKENSEuIC82Yhrta5ChxBmxy6ryczsVETFKd0D2AmvFXEJOEde6P8LGDgtiij3TLk67gbXneNYnCZISkof4NKTU2s+goCKOWrvmbYRsRDmG4guCDyNxjk1JJB5Q+0YNoUxZYSdgiI5aspX8NCV4eb2uXuOP7nzsjemRaHM/EIOZPGWw26eQsrDlt5BTg4ZVgxI33CC4N1xMMCXUIb03QFC3xtVsnx0KLwUM/usFBwcHBwcHBweHiw4kq3S3e+ITn9gkpOiMjFoK5RRk1c/8zM+s6oh8/fXXq4/U6dOn5c1vfvOmCCnwmMc8Zo13FSWDF7TjXg8gyQ6HA3K/Q+Pq24LyhITcKlcsKKVCWUGijhIHImE4FtLEFZIl7PdpwkwpFGodEi/UMKfmMlpiRVt5Sj80GWshcGIRPIZMokwZE+fIlcpKDnBefsca24QX7ySSRsrISHz5HGRPN6ICAmQ8YYyl6YQFacMxOwHyDOJgI0oJNcTOl3WO8EmC1GI+Gd+B8YSWjqnxewdD9EEkvl4z716BrxNEJONX0qRUkXShZMogR2N9JZqsG2tlDau9YB0hpYxvWUnJGUuiUe5JsjueoCPe6vOhvqFIr5uPUS8gaSaphvzhelsJV8oWr9o/rDF1ej6j8wGhRYmZt4yM2NByv8XcGtPw9cA1Q/xZ5SFzi4eXIaXaH4u9wdpuRqlmrikrM6mClsid4vlSTglYCGGaFqCYWq9cjusltlk3C/YTZbiQdr3uG9Nd0xBtDTsrBXMDSYqycDvBdXE/YV25PXRai82AOGc/QQBfjKbh7D9UqV7UlDDO6prtIj5K4ZRSDg4ODg4ODg4O2vHuz//8z5szQfkdnfIo1wOPf/zj9UEX5c997nP6Ol2VB9nWOhqN6jne85736M8c+3d+53d2/OpA7uTLFbl3Nt0080bRNDUc1eckwpTjYRiNAof3xyMBVQHNlLN6DJJTSoognNTM2u+TPSPm23JUWN+8Z079fCjRO7uQ08QYhQDESa5UlWPTw0raQBJAVkA6TQxFlNQgQYQ6QnVFAscYSBj5mfeirFjOl5U46JasM0aSQZJ6EvA757NaKtSuNIjSLVsKuJEYgWgguYXw6GSUzHyhxOC6Bw1IAQicfmCJIkghYzJuujBCoPV3HFNeZ7sLEhOQTCStHJN5wZtqUUmQkKrYrhle7e9FaaiWsTXUF/wO8gMCAyJys/s2FqLrY1mT61alGgQJ5YLJaERjGPUW74CAhUSk06EXkC+QMWf7VEx5S/cARFChXNc45jo7EVntlIC9gDES0+wha1IPUctehCj1vqdUrilR3A2sJXuY+RptcPHEHKTeHvvCOuNBkQTRDYGNeTZr7Z0/2/lvO8G6MMfEhZK7xMMmfMM6gflHWcq9DhJnK+4DWwXuv3zZYL3P6sT/QlaJXvbAboMjpRwcHBwcHBwcHOTd7353cxb+6I/+SP1B2yWuo6Oj8uQnP3nLZowSPktK4V111VVX7fjVgXihxGwpU5TjsxkpVWvik7rcfmpRVRN4OlHiBBnknVOIAwvIp0Q8JDMnFlTdgvkxSaYaVVdq2q48V6ya8rooRuBGlcG/vBffGHyWIMIgxK7cN9Isa+IYlIT4osZfimQOogqSw/47lggrcdANjDHQMNnmfAuZqH6zz3hbS2hIlK1iaKOoCUbnnUkyFGJL88WmIfogQVmVnbteE2rIR8gYS6Kxbv12HoPg0LVST6CQrg1m9drJjI6JoYCOJxIIyNE9Q2pU3g22lA1CFBPsTl0X+wVhjCn//rG1v4OswsTcdkok4Y5HQ2qWH+tAfFpiE2KqFxN41hyCy6v40vI9JeD8ahAOQeg1wtfPlIz3Wr/gs6wDa0qnQbuu7Me5VLUZg6xbqVqV4bApr+0EQzDWZHw0oqQKcwQ5ZUnDTp+11wC5xr8okTC3hyxmTIzPew6O0+ve0JJeym3HIYM3riSDKIMQB4wL4nzFBn+wYH25fsomuYFB0l4M4H7JPqBD5eRQTM4v59T8/LKp5IaJ/IsZjpRycHBwcHBwcNjlKBaL8sEPflCfj4yMaBnfhfqjGCLqU5/6lHbf+4u/+Au5GIA6gYSyWucbcErbihL0B1Qlg2rixHxG9o/FpVILabLempRrV7ZUQarVupJYJNQ2yYR4skQHZR2QQFL3SSSCsTFkRVbVKCT9KGo4N9AuffW6kkMoO/CV2Te+VtViAVFFCVI/gPQikUXR4yWlUPKgliB53yg4biSEF1F9lZG0FxAX1kS7k5n0RoCCDCWSdv7rQ+XBNXtLtogLSqg6gd9b0pE1gvRAYcNaoUpj/fj80T3DMp8qqCoIZRqg/LMXZQifZ30gQFivQRlDm66CdPdbXT5pyZWRBsnEuhBznHs5a8aBeo8yzFayxBJTeF6tR0xZA3XvexgPpA2vQTyxP9gH9rj2M/0ShawTJuIQpCjWvONmL/OgE6IlRMrlmkRHuscM88BxULn5/QXtwgcJzby0XjcxYkioqqrdWFPIXrpDokSye8MSkBbcT3rtBWD83wpKXkKOMGc8+iV7bemeJSUh7VLL/SkO+wXzXh+qy8m5rKrxvM0kdjLGbAlfXeTe82k5Oj2shBT3cOZ+0F55OxmOlHJwcHBwcHBw2OX45Cc/KalUSp+jggqHL5xxLF343v72t8vFBIgfkmESRRKiy/0+JZlIIG+4bFzmlvP6HpJbyAWbVEaDfn3tDCbYfr8cnhqS5VxZlnJFTTit0smbfE0ko3LHmSXZNz4hM0t5ObOUVxUVJBY5DIk/iTNeRpyLhLkX5QmJOkqrfozDOaYpJ6s1y1CYB0gHSrL6Tf69gKSZaJYYVjsqrtQQHTJoQKQUZXOUUDEFzEOvKg8UOiTklBNZQBAwB8wJpAVEDq/xL+sOEYDKDGVRuVLXhJT4QfnWSsKR5KOAQ0kDUcn5evIKqhuS58r9IwPrgsa4ia/rDo5pGadXqcYcMHRr0K3EUdKoZSBQiEXUfWcXs21N372KKcqYOsWtaQCw+vqJP+KX8UCS8lmIVsYEmQep2/qZ9cC4IaR07w1F2pKjqHXyxZVOiEqMNTpzdgJjYp3t52k0QHdO4tgSexCzqI6qVUzbg7ruxEenfaXEdWGFJGRPoh7rRUloyh19MjUUlrHxuCxly9rZk/JExtTrlxS2dM++nzWHpOpHcdgLmCMM4rnHWrKOYD8xm1HF1P6xjRPi2wWaUNx5ZllVXsf2DGkJJmuOl954F4P8SxGOlHJwcHBwcHBw2OX493//91VKJYcOCAZFfuEXVp430K6TF69BcJBwkGAkY0YNQxkf+RrKh/PZvMwuFeTowVF9HbUE+SYpJ4oFS/S0thMn6aOci9/tG43psfg50UgG+aYdhQ9JT6+dqUhaIWEgTHr1oEGZgQc3/5IYJiI+JaQg3VCobBRcd7ahtKI8CTKhEymFesiQgmvnqt8kd7ZBJEKGkKRzzF7NzknGUZt5xwBBASkAmUSKHvGo31D1MGcQYMQH69qNxINcxFwcNRyEBuq59YgGkvZ8paj+ZYMipACEFGdGjTSfKeq12+PnWkrmvN3hIIQgJiDuiBNilrluJUFtZ8VOxFSnMjwbwyYWAkqMEUMYh2NMznr0Y/DOdUEuj6+jMItFAkq0NT2rokE1k+8Gs4ZmvYkHq4BiTti7LG28QYQxn70QxXzemuIzR5DMlNBy3cxHJzBfxOHUcETSS1md771jId13kI5KEA9FNL77Kd0D3I9s04DNklIQW5asY46sEov545wcH58mLQG9CEgpCD+/+OTwdFL2NsZL/KznRXYpYvddsYODg4ODg4ODQxOlUkk+8IEP6POhoSH50R/9UTc7nQDhcORIz/NDck1CRhkRagOSW0pkIGwgrarJsISqOS3ZIRnhd1fsG5FbTyxqyRWdxNrxFHTmI6knScRT6MA4JseQA0YlAYFzaDLRN0ljk9p+SCkSXjWwVsVCRRNclFqbKf8kCebaTOv0us7fSLx9UgtZw3hRiGy0NI0xG18f0bFzTAgiVd1Uq4ZcWkf11e78dJqD2EDd4lU+ME8QYJwPgqYdidMOkCwc684zS6o46gb1EUsV5ejBMTWxH6TvFutDeSHrEQ0GNFabpFSxssb4nnlkflCCAGKD+Mfjinm3zQG8sCrBdsQUZInXu8sLrpFrXfnZdD2EqEXR1ysxspApSCpX1nGu54uGYq1czWucQMpAlHrH0Gl9Eo1OpryT9zNHECwb9f0iRplrxoEij5+Zj/X2NPcOyB3iMO15XU30w8Y0nrWKN8bWaS+0lu5ZcFxIpOG13H0PZdGGgLL+WewBiDYIHe4/rXGzZywmx+fSksoXZTi2uQ6TWw1i88FXTa8iHFtJvd0CR0o5ODg4ODg4OOxifPrTn9aOeuDHf/zHJdJIlBwGAxIy1BqUAJX8fk1y8StCOUB5Gl32jCKh1EyAISowhS5X23fO4pg2ca03khs+CyEA79CLoqEdWo2S1wPnVXWK36/lWPgpQeps1gsF0sOSElwrhAclaJ2UX7YL30ZIKcgBEm6MzSnxsmMn4VXyg6515aoku5BSHIOHl7xAJQdxeL/DE03VGGQBxKPpthbW6+qXvONawwG/ztHUcGeiCa8aDq1dFouUDlabJvWbgXYY1MTZeEJBEECAoPQJNuKnlWQjLvW9nljmuolzSCfmqZ25M2NHcdRKTFnyph0YA2SuFxy313IoNZZfzqvKrJeyV8C1KTFahEAx5GS3fWRNzu3epuQW1VevqsZOIHZ1Daoo/CrN+e42Fu3eWax09H9j7iAZiTti6tR8VuMWA/vWfd5aumdBjKT78JWye5KyReaIeBpu8c/qhFAgoLF5bjG/40kp4J3DUqXaLNXcbdi4xtXBwcHBwcHBweGih+10B1zp3jqoVkW+9jXz4HkfZI8ha0QJKTrkwSZB5KBuosSPDlKW1CBBJ0FBqdEOqEQozanW66tIK/Wp2kRCE/aU//T+GUibiixlSlqCtp6iaD2Q1KMa8ZIOkBMQGJTpQWCQ1HtBeRpqnXyx/Xx1AuoLyK5kFCJwdRmZqsaUOPA3S4U6AZKEubcEEcQTxIbtykhpICQVCT1J9cGJhCb6G1GTMQeU90ASMBccux3RcGIuI4VyzeP91d+6dgJkmC1DZL74F9IhlS9rCZh3Hryfaef5xedRMTE29kU7QCbxWcoWNWmnpLJk1EjtYJRSG7tWSMOzCzmNP9SH/aiVUBqxNqoeo2SuyxisybkxSK/qnut0Pf0CwpK4JWYZx3p7mljtxf+NsRLPqN0gsYhlSmy9gJRr59lFvDCnvd5buO9BqF02PaT3TfY/97Ve98tkQ3kKSXYxIdco3dtNBucWjpRycHBwcHBwcNilKJfL8v73v1+fJ5NJeexjH3uhh7SzARH10Y+aRx+kFCDRgPhATUTJEkQInjGLOVPe5W1lzjflo/GI+st09nKqa+LpJaVS+ZISLRtFv0opOxbGQdlMK1m0EUButDNWVsXZeEKJA/yBUDFB9KCioesWCfFd51K9J775kq4Dqop2KhqbpOMJBenWDZSGQQ6hhjs+m9ax4BFmiQYUJiTIJPQk9hsl7iAQFjMFJSTHklGdC+3e1Uq0zWfVaBtuyHbwK1b6i9euHQY9ih6uJRYKGIP4XHGNOT9j7E4i+VUFhfqK62sH1odOgxBTEF+Qsp3mEK+uVqVUL6D0jM6WzBXj6bf0lfhkriHlrLl4J5Q8JueQqbZD4SDA+CG9uB6IHaucagfIQpQ5qJ56hfXpgmyFSDzbIAsLHUr3ANfGfaqXexP7iL29mTkhVvDrYm+0I213KnL4ke1ClRRwpJSDg4ODg4ODwy7FZz7zGVlcXNTnT3ziEyUW69P0w6FvkLSjipprGCMfGIu2Tdj3jcfUZJmErxVWoULCBSkEUIdgtmwNlzcCr1FyryB5pFMgXQHXUxT1Qnh066RHgg1hgBqDzoIk3yiqSJLpLgeR1Uk9ZMHvID+YJ1Q6nc7FsZgPuAnO045kIBG/6+yyUdfUjSKJuTjUKIWyxBbXBLHiLV/r34Q9b/xmhmN6XNvpD2KBh56nWFaizXaB5H22TGwQSinOCeHjVcOwJswVx4dCaFUXYXzO+bsRcfwOwo71h9xqB8hDyAb8jbqpiiCEuqmU2oH1gVyh7K5dGWEvYG1RPzE31teqUxyq6XfI3zT0H1TnSMCaM490dWQtOhHNEGgQnKgbN0L+UGpI10/uP5DEKAPble5ZoNrq5f5AjOn7N7hXAPHG5yFE7d7Y6ajW6nrt6/mXXarYnVft4ODg4ODg4OCwquveU5/6VDcj2wRUUaFxv5xdyEoqU5K9e9a+ZyxBcpyS+VRR9rUxtSYZJJm0CSXJetijkujVrLyTUXKvah4SXx7+UkVSffjGrCWKjJpoejTWtWzK+gO1qpt4nRIqEn2US+3UT1wbpBVJOkTWeiVLjAMuypJA3oSR88ws5TT5v2LfsKrgvIDcM+tR1WMwto3OjY65WpP9DeLG11BVjDRIFH7PmhEDlIZCBMX9gUYJYlVikVDfCrh2IMGHdPGSGFyjkiA+swaM10tMlMq9Gedrx7fRuJJDzGk7fyWIKesx1AmBgE+qfSilVOFF57mR1WrFfsE1H55MNucAoGgLBXwdTc69hv6DAmtOnCcac2R/bu1OCTEbCgY2VTYI+caaQKoxh9083TCDnyu0V8J5QTlzN3KrFxCfsXBIfGLKZpMDVKJtFfKlisbBZsufL1bszqt2cHBwcHBwcNjlqFQq8r73vU+fx+NxedzjHnehh7SrQAKCXwq+P+3UUHgZQTrMLBuPm1ZQ+mcVK/weHxZUDySZlKZt2CjZT/lT/wQGygRy8XbX0g2QLfg6UV4GUbRRYgDiiCSbBJm5aC0V4pooz7Id9tYjpIAl+UxL+9XHo3ueKoD8vlXlbM3rqtT0HPhNQUhtJMm2hs+ok1CIkbCqOiwaanpvkcBTSkXyDUHF7zBSh+yAEOH9VlXXrwrOCz7fWroHGBNzoWWJfp+e2wvWtVeClPehXkPF1upXZEF8d+siGOhDKUXpHA9V322CkLKwa8y/zEW7fQtBpLER9GupKp0rBwkb19Zbzu5pLymJoo64VG+7Ad3LWP9u6iaUUpQKrheDuWJ5IP5ads8RD6zxdsMoG8v9le5Fdq9eyJFSDg4ODg4ODg67EJ/97Gdlfn5enz/hCU9QYsphe0FyHQ74tFV9u98NxyNS1BKUtUkV5Atm2YCky5asDMdDmnCu15K+EyB2ShsgL3xN35jeSSmIB0p/SFhRAfVCFHUDfizwEXQmpJzIGl5TLnV6IatqDUiPbqTGWn+earOlvQUEkCGrgtr9sJ0KiuSbz5tks78km8+ifmJu8EiitM2qXCAXSF45tiXeiIPDU0P6Op8l+VeT6waJZUsR+yUMvci26aDn9YzC4wrCykuIKhFWMYqxXgGZgmoJomsj/miWDOrFSwil0mgysiFV4XpgvViHVtj1UHKm4UE1SEASsk7emGRPlxvqMfYEZcGUd26nKgdyDC+wbiV8xBG3rc2U7nnjyHa5RMW10fvhRgAZRWyx93tBvV5vmpzvVjhSysHBwcHBwcFhF8KV7u0MkLBbHxUvSBj5XTISkvPL+Y6fJ9mibGusYVasPjKNkqrtMju3IBHu1cxYO9SlTCdCSoA2U67Ten7KiCAaOD7zgEE2xA2JeD/nsXMRDkIcVnXcEFwkuRjVQ05NDa/1ICLxt6bvEEG9Eg8QPCgsTs1l9OeDk0k9vpdEs2WBKHu8Sa99D4bhJOT+FiKKuNjounI9xFg77yOSb5tMUybF+e21W1VMv2Qj10ZM4I/FfPcD5sHXKJ3rBuZlkF3v1owDw/U2Y2B+iId0zqjOBhH3raCM0FsSCLFZbjRmoNMnJOtWXXc3QDZ1axpgu/cNYk4iDSI00CDp1mtWMCjUGqXIEOSUrvaCYrkqXPIgyLiLFY6UcnBwcHBwcHDYZchms/Le975Xn2Nu/vjHP/5CD2l3k1IdzMx5jA+FJdPlW3dUVBzDlusA/Hjaqau2yuzcgjGghOimUtFyvcWcvk/L9QaYHKMOMqbkNe1+R5czVCEobyiF7BeWTCFJxueINcBHCvKLEkEItXaEE+QPih2ukTlZT5kFGcU4T85ltLyQeaEcqpXMYe6YW17nvIynda4h5axKhvI9OqIxH53Iz27gWCi2TsxmNBZbSSmUbpyfeOMaGBckgCUmtXQwaIzQ+wXnoikAhGI/Ci9TsoWvVPcYhkxjDrfKa8h04Fs7BtaMeTLk6dYQQ63zbclVFJXMJYTfhQBkWDclJfE0iDJKr8cc6iuuvx+fsc1gOVuSgN63IzrXvSj2sru8dA/s7qt3cHBwcHBwcNiFhNSTnvQkmZ2d1Z8hpBIJ0y3MYR0EgyLPeMbK8wGAb/SLFaOsaU2QUTjEwyFVTeEthReSVUBAUJBknpjLaPJOeRqJOKViY8mwzKfrmpB5yapeQAKX2qCixqoTrA9Tu7IWlBqoNCaGIgNXiVAyFQmaEkLOQdkb2KiRNOOzCiNUDMyxLVG03eDagVIpSqbWSzYhLVBdqdooHFAyqttYSXItycM44LoYiz0HCTA/jzTKOo2fkCnh47i9dCJjTLajHzHJPHYa10KmqAo03gspZUzITYkW5IIa7m/CxBsikfFATBH7vZabQYx1U0pZfyyIv60CxBh7lAcEJWvGHJk1pEsf3ljbow9R/6pcSWNjTx/lq4MG8QFJ2s4/yZbubbQhQCcSjD3IfbTfjowbAWuNopD7DvvFdqVcrzw0V6xoyfFuhiOlHBwcHBwcHBx2GSH1X//1X/rz8PCw/MEf/MGFHtbFA5LIq64a6CFJtMs+upQZVc2q33E+n6gihzImDMFRV4wlIrKQLmiXOYggfibx5b2LmaKcW4KoCKiRct+kVNCvyXNrF7VewPtRK6EC8SZiHAsCA/KCErqtLB2y5+ccg+hqZkrgIA2Nl9TkUEwmhk3HsU6gVIrlINnketuXXBZVbcV4MdruxdfIlBKuvA8C0pvgQ24CYsIqNKxZe6LhN9WO/ATMGeuDWoWYgejkM51igHjkOpgHnlt1HUQA8wSMKfvm0k26KMIn0JVv//iKt1Y3rGfWT3dCrqpbF79BlO+l8xU5OWe6JbJuKCKZJ1+xqt5m24VQg6SD5NvKa14PkGHsB9R3rKU3lgdZumdBWSllwpTz0ixgq8G5uAZbhmdVsN32NiRlpVrb1X5SYHdfvYODg4ODg4PDLiakPvnJT8r97ne/Cz20XQ/jtbKWlFJfmmpNRhJhKS0XZHIoqt/Ep/OZZhnQ/slEk5Qgcef9ECiFUl2fo0jqR5Gh5FbTu6h/Uoekl7GNNsR3jAFPLEiS1kR0K8D559Lrt57vFbbsDdLGkjXrlQJCHmk5W9C/qgTPdEks6Rqy5igq+vGRsZ30LEiAMXQXiTbVJrbrmCWl1Li+UtUxQ0YxNpske1VRlmBaT63l7ZJG3GmnOfUssqRUQGaWTQkl8zYIBQgxPJuqy7nFfMP03VwfewZTf/yCIHeZS1WQdeh8Z0E5LP5XWwkIZfYBqjWIGEjnU/OZJnHbL1m8GRAzrMNGSlgHDchi4gK/MNRvVrUFGUrJ7SBhy0lRSW21UAoVKArBQ5MrqmNiUX2lulwW6rVYwwNuN8ORUg4ODg4ODg4Ou5SQevCDH3yhh3ZxAbPgW24xzyHzAoMhWEhe2pqd+42/03gyJIVYVZVRqGpQGkBuHJxIrqhkylVDAgxFtSSMJG8+Y0rlDkwkex6L7dS2cVIqoGotW0rGWCFPKHfbjsTL23p+s938AHPBNUB4XLlvpCelCecmEcZrCaBOYr1YF9YalcxGSAkIJdRLFoxJCUgIzUZZoff3llRLFyqrVFOsDSo6YoTxrKeKagdDPBrCKRQgfk1pIAQo5+H4nKefznudwLhQC0JknF/KKQHF+RkuZYIoBZlz4p95Zp8Qa4yvtVQNsorPHkhubckyRB2KrD2jpqsk46Bb43YQs+3mz67VTgAEGbGMqf/e0bjG76BL9yw4piodt7D7nmncUNTr8n4BwDp7u1G2A7GY2OUqKeBmwMHBwcHBwcHhEkQqlZLPfOYz8rGPfUw++tGPyqlTp/R1R0htkpR6//vN8+uuGygplSmYkqdWpVShXF+VyGGITTJ++Z5hJRMsbHc0iJChaEh/5pv7m4/P63H2jMR7Jh1I+otlyIty36V2xktFlMix3kvdSt0GDcgI4/tUkVCDFNoMIBRQXl1/aKzn0idUMdV6XcvrAOVsJJ/4+Wy0fIrE13pKWbCexvC8rOQPSqnWckFet133WJu5VF4/148qqhXqlVSpNa8FQ/Wyx4yc1+kut1GT83bgONOjMY1/CJ5uKjPKtfBaIwYhAL1jgIgLhwJbTgwxRlPGataLvYiCa7sJqZ0IJRlHYurRtpApqLm/Vd0NGuorVUCpKVuGpYa5eet9jrUvpzuXQkOQttuzuxGOlHJwcHBwcHBwuATAH74333yzfPzjH1ci6otf/KJUKqs7tjlCamcCEgXPF0q+vGbOKKWsN45N5CgBQol03aGx5nshCUi2D04mVykj7ndZSGr1mnzn1JJ+k3/F3pGevIsgYs4tZiVXqsr9Do/39JnWRBDVyoVQhdjzQwIMohoIFYdffD2X2bFehYaiyX4GpcZQbHN+PrY8rlX9RTIP6RUNBbVUqfX3/My9gc/jR4aSrF9VVCsg2LxdBYlD4tcm35yDDot7BmwkDuHYizk5806pGuoY4t6b9FOqOLRFXe9aCQeIELtH1fvrAvo57TQosTgaU588sFWm8yilWAuEUvw7aJN3r7l5u66Hdu+1uw/astPQABSdFzvcznBwcHBwcHBwuEixuLioZXgQUTzOnj3b9n3hcFh++Id/WF73utfJAx7wgG0fp8P6ybb1LlpFSgVWe+OQUEFuUMaEkskmOrQhp5tXa3LDsY7uGVbfneVsUb5175xcPj0skyPdS+nwA0JlEo+GVMmwb6y/UidKrcBWKB96TURTy93LZjqBJJKyK+bMliKOD0fUKLmXbvVauleFlFp5syEbNzcXWo7YRnkE0YWvFGVC7cqfbDkmKivGNAiSsLV7GnGmflWN5BuCDAXIheryxnggpKbGouqzFs75VT3FHJh5MF0ZtxKQoqyNLRtDzTZoz6SLHcTK1EhUFtLFLSnda3bkDJnOk+zDgD+wpebma7p34ivV0qDAIl9c6Zy52+FmwcHBwcHBwcHhIkGtVpNvfvObTTXUV77yFX2tHY4dOyY/9mM/Jo973OPkh37ohySR2FoPFYfNgcQJVQ7kkjehwo/I+w0/pWGHJxOaDEF0kOzQ3h6vqXaAxIK0uvrAqMymC3LfbFoWswXZN57QMr9WkoPzLefK2slvNBFWUmZqOLaKLFsPF4qM8s4lKhUIiF5JGBJWY/ptyCzW4cRcVg2MJ5NRJQy9a9ONjOBY3mQTQmuzaojWznsWxAWqJS0P7KA24XNawjcAW6FOJUfW7Jxz2VjdSh+fbiBWGQNjxdPp3GJOiTn174mGtoUs070cCaqCjDjcKs+kix0QpV4CdytATNbqJfV5i8jg1oB4ajU3b0WErovlatsyaMhvmlc4OFLKwcHBwcHBweGiAETUc57zHDl9+nTb38diMVVDWSLqiiuu2PYxOmzSVypvzKItSJ5RoKBc4ht+kmx8aijT418UUyT+kbDpOtYOkCG0G88UKrJ/LKGeUydm03JyLqMlTsbkeiVhgoSy501GQpKpl7U8BW+oiwVaQtYw/l6PlGIeMccmwUTZMjEc1TIr6BQIKpLGhUxe7pstqidQN8No1gfzZsgIS0CYboibJ6WM2qL9MTif7Q7YDtbgfBBQr66WroLNEr6qIaGIV1X5baWRzzpgLhjreDKqsctegSuFYN0OcG6ISWusTknjhSZrdyuI/3oNS8DBxSOKSrzmWs3N15w75FfVZSsgKmnIQFw4OFLKwcHBwcHBwWHH493vfrc885nPXOMRdc011zRJqEc+8pESjV48xIHDakCiUMbSaooLQUSyD9+AaodyEAgBTLxJtm45vqDkUmtJlRcY8M6nCqp84hv7Y3tH5NxSTksASdZj4bImV4aIKev742FTDmhLX9p1MtvJINmDGGBuWgFRAOFkO8RxvQeHkquIFsodQ8GAmpMnY0H1voGcg3zpZP6+nCvqWqEismuopXt+36YJCS07i7ZfX9Q/rF2n9YFEYg0HgU5xxtxZQ3XiaigaVlXfhQIEo+18xvoyf/iubYdaiXNZ8271GCtXt9Xs32E1IKarYjpiDgrcC9qZm7dTSi2U1zaxgDAnRrejI+nFAFe+5+Dg4ODg4ODQBdVqVT70oQ8p4fOYxzxm2+fqrW99q/zqr/6qJs8A8unpT3+6ElFHjhzZ9vE4bA0sIdJqimtMpE0yxTfu3vbhpXJNy/ZQP6kHVCQoE0Nrv7lH+TPfKBdBFQXRdHAiIecaSiu4jNPzGfH7/UpcZYsVNYP2NUgOQ2qUtrytPGUumHZj6L7ZZI2Ej65YXpIPcgBVFOQEcwAR1870G+KFz0JIAdYDYon3UzbJsVsJINRBi5mSdjpkDi1K6gW1OSJEzZI7lO8BxtKOfPMmxpAjnbqA9TMO5gZT53bxy+8sKUOyzs/9lFAOEpBPc6lqs/QVtRSqwO1QK1HSRXyxbyAfIOfiW2Tk7dC7UmpQakHu0dwf2pmbtz13w+zcS3rnUWY6P6kmHCnl4ODg4ODg4NAB/DGJQulf//Vf9efrrrtOfumXfkl+/ud/Xvbs2bPl84Yx+e/+7u82f6Z87y1veYsEAk7yf0EQDIo89akrzwcIkhvrK+VN4tUbp4qvVE29fKyJOLHJt/UQRapsigSVMDk5l9UE3PsNPsfG6DmdKzdL9SCu9o/FtQRFvVHK+N5U5cB4XEv4RuIhIYWCtErEg0rmMD6IsUG3MLfXYkkkCJTNEhmMlXwRUoDjoZpBxcS8HJhItD0+517MFiWVK+sc2m55JJN2fSB4mJ/WOWDs5WpV18N77EGZnAOIsY0g2Bg/SXm/nRS9IEaY03amzpzDjhNykfPgowRBcyFIKcbDgw5nNua3S5WCQg9SjD2WLxU1ZvrxZHMYLJh7YpBYHAQW0gW93/bSkVPNzoMBJSYtKUU5r5aWDm0tyX8xwe0OBwcHBwcHB4cO+Mu//MsmIQVuu+02+e3f/m05ePCgPPnJT5YPfOADUi4PpiymNTl+2ctetoqQeslLXiJve9vbHCF1IYEC6frrzaOLj8hGEQn51yROEBoopSCDSPS9LeaJk2SjpIvXMXWGtFrMFLTrGCoVC0rOSIQscWATJjx2IFLwS+L8qKTw46GDGibNTeNqn09OL2SV3LGKmEEA0gbFFqV0KA+83kSbBUkjZYrpQllG4hE5PJVUsqkdSQLpxziY5/3j8TVlOSSUkDp4TmEsD0HjvQbM5CE9WtVkgzQ534zKZxC+Ut1KRFEFWTVWsTFeiBnUeRcKkIqDIiL6AbFB7Fky0nVYu/CIRUw572bBHoDoRpHaK/CVKnruxcRkoEGUORg4UsrBwcHBwcHBoQ0+//nPKwFlcf/737/5HG+nD37wg/ITP/ETSlDxvltvvXVg8/i3f/u38id/8ifNn//oj/5If3ZGuZc2IJ28RBII+v2qlIII8XoZocxB/dQaE/gLHZgw/kj4IFEOB1EA2UNyjOKpFZR+Xb1/VImo2VRBS9qs8oWECjIDgmE+XZSxhClhU/KhXFXS59xSVsuk+gVldKfms0p6UU5oEvmVcsXNAgLqwHhCH5BMnZQyJKt2HJ1UVJAukEPMK+V5c6l8s6SWtWDMdDpsVU/Yz2wGzD/n3wxUrdESW/0CwrITwWJVXMQM5BQEJ+QmCbidpwvhK7bdpJT1k2Iv2xJPR0pdeJjGB5sjpYjj+R7MzVuBUo5S61YlncMKHCnl4ODg4ODg4NCCs2fPytOe9rSmsfhLX/pS7X73ne98R17+8pfL/v37m++dmZmRP/uzP5MbbrhBHvKQh2h53dLS0obn9Ny5c6sUUn/zN3+jPztCagcAsgTykccATXO9iRMEhJfgwaOIEiQIIGt0zbf1kCCQUu1AMkx5GcojyCwUTqg3eD8/tyMJiC8SpYVMQc+jypqy8eQpNv6NBPl233gH3XlmWU7NZdTLCvLr5Fxaywt7AeUrdKmDAEPZNe3xkLLlioMABNd65WqQdpi9Q7Z5x9FeaWQIDuvfRMkhJAwG53zM6yVloV4ymySUjC/TZkmpFSPyjY6BUk5b0tguflB/oDSDoCJpJ17MZwe/V3oB8YxCZSOE6Wb9pJgPyEgIjM2UTDoMBvFISPciisiNgv3OPu/XtJ7mFF6llCoOO+yj3QpHSjk4ODg4ODg4eEA5HoQU5BB41KMeJa961av0+ZVXXimvfe1r5cSJE/Kxj31MnvrUp0o4vJKIfu1rX1NT8n379snP/dzPyac+9Smp9flHMGV6qVRKn//iL/6iHs9hhwCS8j3vMY+WToiDAIk8RIpX0UJCrR3yIphrmz/d8T2CGFnPIweSC5UQCqtziznTmrxuFC/tgNG5r3FOlDWQNBicQzzlCmXZP56Q88t54U2qOvD51Gh931hCOTrK3/Bb6qaMgeA6PZ9VggR1FMquduWKWw2ukTmhbFDN4rsYha8ojcy4IBwmh6KqkKKroem0FlpD2JAAQ8Bt1k9oEMSWl1TbCEikUR51i7lwwK+kJ0m4nSfbBfFCgP3CdfdKlg4CXhUM17/VzQEcegP3QsjujZYGo/5jv7Pv+/2CiBjkfsMxrJIQFaHDCtxsODg4ODg4ODh48Du/8zvyhS98QZ9TmoenVLDF1Bqjcbrf8Zifn5d3vetd8o//+I/yrW99S39fKBT0NR579+5Vkioej0sikdAH5NaLX/ximZ6eXnXcz372s/Iv//Iv+nxsbGxVCZ/D7kmeIG4gQSB4+HY+Eg40Dc7VF6pSk+Gx7iSKhU2MjRF6Uf2VSIyu2Dey5r0k7xNDEFEYfQeUMDo4npDP3XZWgoGEHNkz3CyDu+XEAgUt6klFkkX5G+bo2WJZfYToCAg5BSkDacO/qJKWciUZioaUKIPg0vfUeJ8pj4EwG473p0ToF6jGZpZySp5A2rV20uuUWHKdlO/QxY2kkmtAJSUdVVKm8xvXjQ8N182c9nK+Xjvv9Qo6AOIRZrvR9QqILM5PTIy0uUYvIN9Ye2+ZKUQdhNZoQi4IOD9z30p+bmVsjTgiaseB/Qunny8bb75+MW/NzTdAJvkbqjlV7VXrq0o7HQwcKeXg4ODg4ODg0Ej+3vCGN8gb3/hGnQ8UUP/xH/8hU1NTXdVOExMT8uu//uv6+Pa3v63kFMTSwsJCsxzPqq68eM973iMf/ehH5ZprrtGfS6WSPP/5z1/VeY9zO+wukLDg+6RkVDCg5tyUyRkyQRqd8dZXSbUCUgNFEEn6rSfm1fMHhZNV8UC4QIbtHYvJ7LIhXjhHOBRUggmBAYkZhAMm6ocnk0o22FbnkGaU42ESDoGBwgrzdI6BYmgxW9J/IblI7Hjd+Kev/MslnV3IyXK2LDLZ37xZ8mQ98oF5ZQ4hkfpRsTBP+E3NpQq6HmPJqHbP4ppQX9gOb14wp9r5L1fW80EIMoeMkXlEUbOe6oL5taVgmwFJMGV15UpVAm0Sa0hDlGCUbPJvsTGf3BeJHRRP7a7RC2vsjQ+ZhZaENjzILkQJMuNeSBe3109qk6o2h8FDVXvBoBSKVZF4f5/liwCIzUOTic35BZZrGiPOY2wtHCnl4ODg4ODgsOthCaG///u/X9V578EPfnBfc/OABzxA3vSmN8nrX/96+dCHPiT/8A//IF/5ylckk8ms6dJ37733yvd///fL+9//fnnkIx+pZNjtt9+uv+O8z3nOc3b9uuxGkMQv54xJt1Wc4NUDKYWSCcJgz2hvKql2gBy5fO+wEkeom/C8Qf0EwUTiBPGwGChqGRZkFOQSCpmJZFRJq0y+LJPDMf0MZX0QPJT5QbSgckKNBfllgXIKkouyF3yu1iPTIHrwwILs6dVMWEvxlvJSrdYkUaw0z8O5IQmYR96DObkSb6OxDSkeIGcoYWRuIFpSeUzoa7pW7VAsVbU88NjeYZ1LSDCSUuYeTy1mIhkzBFUnJZSanG+SkPKOn+MFA4Z0skky3fIgzyCuIEIpFYT4RF3CuXslk2yJIcfwnpPjoiDq5Ee1lcC8v1zN6/VttoyyHz8ph50H9jxKqX4AmQoRPdanuXkrTBlpVfeBK+lci03dGfgGD+PNF77whc1vFb0L+PjHP15NQd/3vvdpdxoLfBjwR/iv//ovSSaT8uxnP1v++I//eI003sHBwcHBweHSBH8n5HI5VRMtLi52fOCthBLp6NGjqx6UwA0KnOenfuqn9O8Si1e+8pXy3Oc+d8PHjEQi8tM//dP6sICUymazaqL+9Kc/XW666SY992Me8xj9m4pzWl8fzM3512H3gSQeFZIXEAOocSBDIAs2W/qByqdYrsnUSLRZ0seehDgBSkblylpuhrIIFRSlaCirTGc1QzpAaEFskWhRdgg5A6HEZyCtUAXhYwVJ5C3p6gZUBJAH+Ld0IntaAdmEn9HkWLxhvJ5t+GGVjSl81ZSfhRpqp80kl4BrYZyU5RXLvo7Kh/PLOTU0tvNq15fSSOYO9QWkHx5bzCkEFaSgd321e9+AlDcomObSBfGlDYHEWDgvXQNRzm12XvR4QdNBsZUMYB0uBClliTZiNLnFpJTrqrazEY8E9B66EXPz4T7NzVvBPlvIFE08OuP7NdjwneHrX/+6vPWtb5Xv+Z7vaft7SKp2LHG1WpUnPOEJ6q/wpS99Sf8we9azniWhUEjbHTs4ODg4ODhc2uC//7/0S78kd9xxx4aPQVmbl6S6/PLLm88PHz6sf1cAuuD9z//8j3z1q19VE/Ll5WU5duyYXH311foYHx9XRdKdd97ZJJMov4M0GjQY0+joqD4+//nPq0n6Jz7xCVVp/dZv/VbzfSi2HvSgBw38/A4XL0hksoWyqnwgWzYLCCRKrahKxWwccoUSM0uuQI6QQEFYcW6+2Yc4gSvxJlSQD/g/LWeLEh2N63unh6OqWqIEkZ8hgfpR+kCMQGgxJltCuF7SyLxYsgmVFkbwdASEJOCabj25KMf2DMue0diGVSwotyhbRHmlY/KZf7lGSuxalU6QYJliRa7ev9a7CzAOxsYDFRfrCxFIqRmvMQeQOCiZBpXEjsQjSnqh2tgKNY8l/VrB9SxnS3KhYM3WeyVGNwJIXecntbMBOUqJcb/m5igrN7tf7P3hQhCzFwM2NCtI0Oko83d/93fymte8Zs3v8VOgNTJ/BGLs6cV//ud/ym233abdaPbs2aMy91e/+tXaavkP//APV3WwcXBwcHBwcLi4gPLn5MmTcr/73a/tH3H/9E//pAokiJjNYHZ2Vh8QTa1AYYRBOQTTd7/73TW//9znPteR6KKUjpK6rcbQ0JCW90FAvf3tb2++zt9G/F3k4OAFBNLSgFRSFqh3UnmjaBrHHym5okqCbCGB5/cYmZNQsZ8p/WolSFACzeTzqxI/VEB4FDHejSRzlALifUSpYLeueJAAlA+SNFqVD+fjWiBIbrovI9FQQq7YN6ylMxh9hxq+R/0CxZc5dkTq/E+N2RlDRQk7xklpJOOApEIlNhILSSS0frrFmvJ5Hra8D8UX58MEHiXTIMB5Av7BEFz9lqTOLFf7Kskc7PmDqhBrRySZmNj8mCBGgfOT2rkgDilb5d7Uiycf9xdiYxCd8th7HMv5SbXHhmb4BS94gaqdHv3oR68hpZDiP+MZz5C//uu/VjVUK7785S/rH6r80WXx2Mc+Vsv5br31Vrnxxhs3MiQHBwcHBweHCwi+sPrzP/9z9VKiRO3+97+/vOxlL9PyNcrzUUpT8v+nf/qnzc9cf/31qlaiy1ynx/DwsMzMzKj/kn3cc889+u+ZM2fatp7HlByrgH7AWD784Q/LkSNHZLuAcuptb3ubqrte8YpX6Gv4UaGkctihCARErCUFz7cJQb9fk6h2Hd42Cogf1FAk0+2UOCigIFeSUZMu8J5276WDHYm917OnG5HUawIXjpjSQUizttUXtboSN8xJu6QR8gMV2KHJpD6HJELpdGAcRVf/JAR+WbZszwvGB/nGXJ6cy+p4KFXjfSS//RIe3vI+OtlZr6+LGcw36izKFZNR/wVRSuH9ZU35LfD7Ii6IWwgLCFZiaSPEb7ax5s5PaueCfVSvGUN/1KLrwdzTBqcopAnEhSBlL0lS6t3vfrd885vf1PK9dnjRi16k3zA++clPbvt7us94CSlgf27XmQYUi0V9WOAvYf/o7NYNx2F7wBqYdr5uLRxcHDnsPLh71NaiUqmomTd+SN7/juOXRAkcZAulaR/72MfkIx/5SPP3fBn1F3/xF80yu2646qqr5OEPf/ia1/nb4Pjx402y6r777lPCin/5OZ1OqyL7+77v+9Q4nAdfmKGeolzPPlBIvepVr5KRkZGO/y3byjiCvOMLOq7noQ99qPvv6U4G5IjXumKT8dBrXEVDfpkYCqsx9qBikGPFwng3FVQN1Qo6te0Zier4eKAwypfKTZKq9b35Ynndzne9gjwwHMAcuyaZfKntcWeWckKTN7xe2s1JoVQ2ptONORtLhFV9dXYhK3vH4n11L0ThkyuWZSIZbnuuYKNskRIxyCnmayQekmyhJD5hfdeS570gFgroQzZwjJ32375o0K/zEQ9fGIItFPRJrgDJGV4VI8NRQ0TRRACCihiBaEVdBVEFedEL0YQ3GGb+O2W+N4KdFjODBlwjezVXKEo4sL5fnXaq9A32nnupzm0n9Hq9fZFSyPExNf/kJz8p0ejahfzgBz8on/nMZ+Rb3/qWDBKYoFvzTy+Q7RcKvdeFOmxdsOHRwU3MmbI6uDhy2Glw96itAfd8/h5AMe0tkUMVhb+T9WiCJPq1X/u15u8DgYB+5hd+4Re01G+zQFWEyrqd0rpdC3KIHzyneKD49r6OIutCxdGBAwf0325jcLj00G9cZQd8fhQDM6miVHNR8a+jDkHlspwrS72wNgfIZEqSS/tkND4YUmqx4T+EYuWexaqSY94xL+XKqs7aOxyRmZlM22PMpYvGO6m4MibmeT5dksXFBZlM9l5amClUVAmzICtlip0Qapzn/ExalTgz9fU/sxv+20f8sK71wuY80VDIbUjJlCvL8mJdiUXAvNxxLqPldgfHY6qg4jcBvKGyVUkt1VQZCBfIe1Bb8S8x1Qq6F86lihKpRiVzEXfe22kxsxXIZlJy6mxRSsORdd87my4qKVnJOx+ojYIvB3tBXzP8jW98Q/9YeuADH9h8DTn+f//3f8tf/dVf6beed9999xrZOR1tHvGIR8hnP/tZ/Yay1f/h/Pnz+m+7cj+A3N9rAIpS6tChQ/rNJrJ+hwt/A+M/6qzHpXoDc9h6uDhycLF18QC1NF6Qrd5MT3nKU7RpyZVXXqn/zf+TP/kTJa4sKMf7f//v/8mP/MiPyMUGd49yaASCyF13medXXIGB2UUfV/5oVuLR0JqSu2yxrD5K1lidUpbaXEYmp4bWqIxiQyUlbqbH4gMZU5iudpWaKk9OzmVkeCyuSq3FTEnKhbLs3xOSkQQt2jsTAEV/Rrv3tZbbTU7V5exiVgKhoHYF7AXVxZxMTAa1TK9XYNQeH6oNxJj+Yo2tVeNBgTObkdHx+BpT+F4AUQKplc2VZHokqobt/WCoVJG5VEGmJ5OqfDu3lJNo3CeXTSYlX67KSIcOkXh8QaihgsOXrOb3qYIKJVWiUa63kC5INFlvqzi8mLDTYmYrsFgJa0ne9HT7BgRelIOmHLffWHNYQTsh06ZJqUc96lFyyy23rHrtF3/xF+Waa67RP04nJyflV37lV1b9Hv8o5PlPetKT9OeHPexh8trXvlbJrenpaX2NP1ghl6677rq258WolEcr2CyX6oa52MANzK2Hg4sjh50Kd48aDFA9vfzlL5d/+7d/W/U6/21/wxvesMognL8ZeFDyj08S35ZBUkFYXaxwceQglQpeFmYiXv5ypIEXfVyNJKKynCvKqMfoHEKFrlMQCXXrCeT3SygYkEq1rqoRL2KRkCxmy3otg/DUCYeCki+X9HyQT5TE2fPiEbUeqYGaplpnXME188qP+8aTcmYhq0omOgt2P1ZN1Vl7RsN9rRHnpwzsQuYqFzq2vGAE8UhIShXWsb/xYDg9u5xXMpTyu1yxKkOx9ZUuXmA4z5rgK3V+uSB+n1+mRmOydzyh3l2zywUd28RQZFUMM9ZoOCRjng57EFQQZD6f6RSZK9f0czthni+lmNkKUApMl8terq9aw+Nt7T3EoXf0OnfBfjvF3HDDDateSyQSMjEx0Xy9ndoJiTwmnuBHf/RHlXx65jOfqWao+E/83u/9npqntyOeHBwcHBwcHC4s5ufnteSOJiblcrn5OgTT6173OlVIdUpEUVfTcc/BwWFnIhENqpcOnjqQKCT/qJT2jcXlPM/LNYlHTGLB70nKW43FrXk0Cf9GVDCtwPcFY2qAOonj4qnVazt1vGA4RidTYca7dzSuxueYXLdTyFhQtsd1WxP3XqEkWg+d93YTUBhBAPVqhA8pSndFuhGiWLGxQLfDfsv4WD86r52YyyqBFAkGlHjlv10oYcITdAjMy5mFnEyPmnK+VvBe4zUVVIIMnzHK+fD7wiTdYecjFgrKfLW4qjFDR2VfvT5Qo3OHzth22g8vCbrb8C/frP78z/+8POtZz1KDUQcHBwcHB4edg3w+r+qmY8eOyRvf+MYmIYW0n7J9uub+5E/+pOs25OBwEcOoT0KaoKMewkOHDnWYhOOnQvmShfm51jZZJzmHwNosUKMEAn4lHXgebBBIvRJSAFINIqkbuD5K6yjpgpDrhFyhomVa/QJijJJDhxWwhpTAteuaumbeixU5NZ9VXye6lqFoM3EW0Aflpf0AMjWVLclwLCzjyajGccjjDwUJtX8srmo8SK/1jk9ZKGV9GczbXde9iwasOfc8CMpugLTifa5b3vZg05QunhHd0O6mc9lll8lHP/rRzZ7awcHBwcHBYYvIKLyffv/3f1+bnFjEYjF58YtfLC95yUucp6ODwyUESCkIAJQo48mV8iVDNFVXkQpL2ZxkC2s77UHy8F6OtVFkCmUliSDFyCAgpjaiVGAcKGHWA2TC+FBEzi3llfhoVXlxfkq1Jnr0nvLmPxix96uuutSh3RB9Zn1a1XbeOUe5BylFLLZTVSVjdDasKMHUK4hZPmdLTyFbGY8XxD0+ZLxOOV8hVl21H7wgVhBqzaeLcmA80fM4HC4sIJlYtzLkeqS70nEjhvoOG4PTGTo4ODg4OOxy0LSEzrmf+tSn9PGFL3xBu9F5PQHwkKQTru0S5+DgcOmABPuyqeQaVQDJOb5L3p+nRqKasJOoe03EUVGhttooUvmSLKSLmjCidCIhNMRO/8eCcOhV3QSxgSpCiamx+CoiCWKEuWlXytUN5YbKwpFSawGxicKoHSkFcTSXLiiheHAi0XH+WFvMxdcrwfKCtWStlYxodHHEn6odKOeEkNVyPu3+GGt7HlQ385miepc5XByA5Obe1U7x6UWlVut73ztsHG4HOTg4ODg47DJoK+w77pBPf/rT+kD1vLi42Pa9j3/847WEr9VT0sHB4dJCuzIVEnMSf69/j3aiGhZN2PeMxppldRBWkEH4sLR251sP1lh972hMPZwo8Qr6KeEjcQz0fF/j3CSc5R7K97ygnKtSzcv5pbzsG483x28UYRso3VOyxKks2gGlEh5RYx6ZCuuMQg6yCqXSemo7CCJILZR16xnV2/UgjnkvKi3ixPifdSYdICP3jydUtYWKkFLP1k6OFATVNxDvDhcO3MfYml4FaDsQLwG3h7cNjpRy6Irl5WUt0ehkYFsqleQDH/iA3HzzzeoR9gM/8AMyMrJ+i00HBwcHh+0Haii8oD7+8Y/LmTNnOr6PMvtHP/rR6vv4Qz/0Q9s6RgcHh51FVGEYDtnk9XSidA/vKUgciCQIAogCP+/tUprVDhhZL+dKaqwOsQUBtpgt6vGqtEvrEZRRYTw9PhTVv1v7VTlMDUdVLTWzZMg2rm8jpXu29MeppNoDQ/D5VKFJdEJQQfxA+ByaTPTs4YOaKZUr9URK5YsVjUklxAplJS17UbLxnqnhmERDZSVhh+MhGWt4W1kyDYWglov2QYI6XDiw5kEtS650JdDZw04ptX1wpJRDWxQKBfnlX/5l+Zd/+RftnvjkJz9ZfuInfkIe8YhHSCgUkjvvvFPe/va3yzve8Q6ZnZ1tfo6bNN+m0xYcgooHnRcH0R7YwcHBwaF/1Go1+djHPiZ/9md/Jv/1X//V9j3j4+Pywz/8w/KYxzxGyajLL7/c3bcdHNohEEA+uPJ8FyDcSLpbjcZRs9SlrkTOXgyiQwFNzNt15+sEyAjULl4/J6O4onQmoCU0vQDSLJ0vaRnV6YVs1256ncDfqqhhzi5mtYSMznkbKd0DkB4uoe1CCgT8uu6QRawdJaGqwOsDkFhzqbx+fr2Oj5Tu0fmPNUEBQzx3U0m1gliPhPxKwmLmPz0SVVIN4mIsGdXjO1Lq4gAkFPcW4oZY6BQ7/K6f5goOm4ObaYe2rb8hoPAUASdOnJA3v/nN+hgbG9MW4F/72tfazhwS1ltuuUUfb33rW/W1vXv3NgkqHjfeeKMSW5cCbrvtNvm///f/yi/90i/pvDg4ODjsJPzrv/6rvPrVr5bbb7991evxeFwe+chHyqMe9Sj5kR/5EXnAAx6gvlEODg7rACLqwQ/eVdOEv08n/xU1mq6LnFvMqbqoU3e+dn8vQvxQrkWJlJfAsaRFrU7JVW/3JUr/MLGeHIpqGRhldxsByh06/dGFECPt0UTvRtqtCW1rqZfDCpgbCEnIngMjeJn1/+U1n+E4kFvjyc6kFGoYFG8Y2hNXPo9XWD/g/QcmEhpflPMR65CgkGkotsaS6yu2HHYGuN/QfQ9isROMn50TVWwX3N3SYRXuuece+bEf+zFVQoFoNKoGuLYNOJ4jXkIKcukpT3mKPOQhD9HPfulLX5KbbrpJv5m3OHfunPzHf/yHPmz3pgc/+MFNkoqyP8iui7G0kbIWlGKUMNIa3SnCHBwcdgq4Hz/jGc9Y9Rrk+Yte9CJ59rOfrcSUg4ODw3oIh4yqpRPojsbfP6hIIBlQSq1HSM2mCqpWaTUWt7AlUcp4rQPeB8mAMTbjGImbzmz4VPVS2tUKxoPyCwVYa4fBVrLDdolDYeVVVZSqNRnpQ4mz20CXR+aWdd4MICIp2xxPdn4P/mSBgL9JQmFOrmWZQ9ENqWxYa0go1n6qse4otvoxXXe4sLBeUZ1IKe5RVbee2wpHSjk08dWvflWe9KQnNcvxUDh9+MMfliuuuEL9R97//vfLRz7yEUmn03LVVVfJc5/7XHnWs54lExMTMjMzI9PT0/pNeyaT0WN98Ytf1MeXv/xl/Yy31fjnPvc5fVhcd911q9RUx44d2/EEz+tf//rmXKFC+O///m/5wR/8wQs9LAcHBwcFJXsWD33oQ+VlL3uZ3uOdIsrBYRPgS7cTJ8zzw4dpTbkrlFKYQnfzX4GMYirOLeYlVypLtRZv6w1Esnd+2STwlOx18g+CrOhV7YQnFeeHEOD4lFQdnEiqEgsCot+yMACBcXiyM9MB8YbHEH5bECwQcihleO4S2vVh1HAyEH+q2VrBlIx2ILggDXmf99zLWTzMNr53IWIxwLfxS+medveLb0xZtxl4mxA49AaaKJh7Ra3jnEJXsb8dtgeOlHJQQKg87nGPU8IIXHvttZrQYHYLfuZnfkYftAhfWFhQwsqSRl5VFEgmk1oSwgOgtPrf//3fJknF4/jx42vK4Hj83d/9nf5M+eC//du/STi8/Tf3XnDq1Cn58z//81Wv4bHlSCkHB4edAjrqWfz7v/+7HDhw4IKOx8HhkkClIvKOd5jnL3+5yA79O2WQIIkP9GBgDvmzf9wnN907r4TNvrHEqt9DakHe8C+/65ZIk+RDLol0LwUslCpKSKBYAZBn/H0KYeDzRWV2uSD+UZ8SFoP4spNEFhP2VI6ub+GmEot5mVnKqWrLlvy5hHbrYdc6ky93JqVUFbWimAv4fFq6FdokK+YlVCkjvBCkFPGPom9yOLohH7XdClOW5+uolNLSPb9vxwskLiVc+l/vOPSEl7zkJU1CipI0iCNLSHkRiURk3759fW3SQCAg97///eX5z3++vPOd75T77rtPSR1Ip9/4jd+QBz3oQfoeL1BlvfKVr9y21cM3C7KtV/z+7/++msF7QdLXqaW6g4ODw3aC+7kttUZ56ggpBweHzaqlij14RVHKhO8OZBDlcxYkf2cXc/qcLnvrKTswoVYirFpTjypKpTAmbsV8hhK9cPN4mFCjjjJkRUh/BxF2fDajvleMCRILcqlfcA1nFnJKPqDy8pYGQohw3SgvuE7KxVxCuz0YioYkWyy3XVNihjIsb2klGhjeO0h1EaQUJYEQrq3opMbZLIhDCCn8kTi3Q5+EIiV6nUipak33sMP2wc22g6qWbPJCGR2lelvt8USC9LSnPU3e9KY3yf/8z//I0tKSfPrTn5Y//MM/lGDQ/Ifjda97XdNsfSvAf5C4Vkx+IeBI3BjLesAz65/+6Z/0+ejoqDzzmc/U55BU73rXu7ZsvA4ODg694itf+YqUSqXmFw0ODg4Om/WVMh5P64MSNnydUBSl85Ty1ZQQQqGCGXqnEkAvIHQwkaaLXaZQ0uOcns/KbMO7B0BE8NyrToGEgECzgDg6Mj2kJBLHg5BiLEpSLRmSqtgjSUWZoN/vkwPjibYm2SS6EG4oVrzlYg5bC1RqqPlQ57Wuo+m6F1wVc7xl0IQh8RBsIYeIRQjKk3OZtmTVZkDsc70opEaT4Z73psOKUqru6+wpxX3Fdc/cXjhSyqFpQA6e/vSnqxpqu0HJH+TQH/zBH8irXvWqZlkghE8qlRrouTBtR7FFtylM3W2LdIgx/FZQTXXDS1/60uZ/9F7xileoysyC8sONfPvm4ODgMEh4PftcWbGDg8NgOvD1lvhSeoeCCULp5Fxa7jmf1iSwV0LKqz6C0IKQGo6H5OBkUgkFOp+hnIIkGktEVh0TVRUEWjvSALKMznqXTSWVPOL4kFRnPSTVcq7U9johNxYyhUZZYOdr4HcYaEMWOGwPWC9ETxA1mJ57QXfH1i6ISko1vpweJDgPBvsQUMQKqjoUfxCZvXSk7BU0HUCJODViSvZsx8tuneQcVkMN6WudPaUoHXY+XdsLR0o5yHve857mLDz1qU+94DPyO7/zO/Lwhz9cn1Pq98IXvnAgx8WAHWUWxu0///M/LzfffHPzd5aIo1PgE57wBO2s1w6f/OQn5ROf+IQ+R131a7/2a3K/+91Puw9aFdU3v/nNgYzXwcHBYRB+Uo6UcnBw2CzCoYCSTL0k8iTidDyDnDq7mJezi1kto+tXncLn8YgiCY9HQqpcoPMZhJIZizFY9wLFiFcp1Q6Mg2OjorIkFd32SO7zxYqSCffNpFVRdXohK/fNpOTm++b1muZTBfXx2WmACOnWIfFSBUo31guaiXhYyhWbZaOQNKwVCrnWucJPitgaJBINXylIU8gw4hSCMtwHobseUvmSzKUKSvBaA38UeuyNQnnzccmc9VKme7FD/aKULGy/LpWa66S43XCk1C7HyZMntcwD3HDDDXL11Vdf6CGpv9Q///M/y9DQkP78jne8Y5Waq1/QGRAPqMOHD8tv/uZvrlJCQSa9973v1dcgqwCm7JBzKKq8wLDdq4p67WtfK9Go+SbsOc95zirDcwcHB4cLBUqJ7X39yJEjeu9zcHBw2AxIeiFzelF8YBJMy3VUCNceHJWxZFT+9+SiFPtMmiGOSuWalLUkz7/qdUikQ5PJVUQXJAOkGaRYP+AYUUtSja2QVJAZqKtI/vn5hsvGtcMeapydpopHoUM511b5F+00sNZnFrKSypdl72isSQDVa6LzgLoOQgpFTGsZFjEcCw+elCIuleyMh7XEk+eAeIRE3SxQ8S2ki3q9Xo8sEA0HlDTdLFB4zaaKAy833GnQ8uBwUOes3V5mHxkzdIftgiOldjm8ZM9OUElZHD16VP7qr/6q+fNzn/tcOXPmTF/HuOuuu+RXf/VXVdH0mte8ZpUJ+ROf+ETtOPjlL39ZnvKUp8j09LR89KMflfHx8aYi6gUveIHeqDBA/8AHPiD/3//3/6kSCjzwgQ/UUkcLOhMmEqbLDL5S2Wx203Pg4ODgsBHgEUinVOD8pBwcHAYFkmy6lq0HEr3ReERJgv3jCbn+0JgmgN++b0HSBeN11wson4FzImXsRWVFd0Brcr4ZWJIKQgryIlusqEKLMkFeq9brkt5hqiTrZcRYL3VYfzEUSAcnEs2OkJCK06MxqrLk9EJG5tKFNaV7kA0QLrxuujsODsQN5FhrBz5icrPle6i/KFdVRV8bv7JoKLhpXymjSqzovmOOL3Xg+4ZSChK9FcRG0NNd0WHr4WZ7l2Onle55gZ/UT//0T+tziCH8nm677bZ1P/f1r39dr+Wqq66St7zlLc0ueRioP/vZz5ZbbrlFPvShD8kjHvGIVX+4XHnlldr1L9xo74w/FMeYnJyUn/iJn2iam4M3vOEN4vfcrFB1/ezP/qw+xwOLTnwODg4OFwLOT8rBYQtBt+DHPMY8WjoHX+pA8YFyaT1QRoTfje1OB5lz7YFRmRiKyB2nl2V2Od+zEsNHWVaP+TyETKuCZLNAFQUxZckN9YxKRpQg2CkePnyBStkY/kKXcgkf14mXGGoeSEJ8u1o9ykYaKqVazXiPtfoCQQ6hnILQGoR6qRdwrs0QRlwvKinM+iFL2yHSaESwGQUfxBcliDQp4Hw7TQ04aKCEhJBq3cfcm3io75TDtsHN9i7GqVOn5Etf+pI+v/766+Xaa6+VnQT+ww+ptH//fv0Zr6Ybb7xRXv3qVze7Snn9oiCCfviHf1ge/OAH63N7M8VE/cUvfrHce++9WgpImWInQFT94z/+4yq1VetN+fnPf76epxUoqSxcCZ+Dg8OFgvOTcnDYQkBE/cAPmMcuI6V6VUrhp4Nyo/VvuqPTw0pMnV/Oa+nVej47toSmHYFFAk7ibIEherZQXuMxtVn1EWQPii8vEtGQEg3Wu+hCw3oAMbeoxQZdlrYTQAwQN6wH6rtWBZQXxAAlmGOJsMaIt6SRmINchZjarlJHzsf4idF+AQmXyZdVgdWu4+PKOQJqqL5R8ktVUvmyer/FQn41gr/UVXemkUJdy4O9IC4gO53R+fbC9SvdxcBLycIqknYaJiYm5MMf/rCqkO68804lo/7P//k/qvB64xvfKMePH5f3ve99Wm5nFVEWe/bsUQ+p5z3veTI6OtrzOZ/xjGeo19bLXvYyVUPRpQ+jYB4YsDOmdnjoQx8q1113naq5vvCFL2jJHwqqXC6n5Xy9/Mvj8ssv17LD7/3e7930/Dk4OOwucI+kLBkcOnRIPaUcHBwcBqeUMmqMTiVyJHQ8rJ+OFyR5ByeScno+I9VqXQ2q8WhC3dIOEBAjibB6BJHUW1VMsdExj3GgDrLlRpQ1dUvc+wHnw1CaJL2dYgICiBIyCJBBnXOjwJwdkgbDa5RikHNWpXYpgHiiMyLXByHVC1kAcXjdoXGNHcis/WPxpica66UldbntIaWIW2LIeFn1pgchtik/VMP08cQaX6x2sN0k25X39aSSapCtzBN7cjlb0v11qYI1CQf8kitVZCgWXl265/ykth2OlNrF2Mmle16gjsLL6VWvepW8/vWvV8NxSvAe9ahHtX0/JXcYktNhzxqR94uXvvSl+nlUViMjIz19hps4hue/9Vu/pT9T8rdRlcM//MM/yA/8wA9o50E8ryg9dHBwcOilfDmfzzf9pDbrreLg4NAC1A5nz5rn+/aJ7CLfEZuwoqroRMQUGt3vOhEHJNf7xhJKKg3FgrKcLSqpQrkfpIMXJItjiYgSC0XtohZqElKQRZSqoWai5AjDa8rqBgEIgfNLeU1aOxFmXD+J7AI+P6NxuZCAvLM+RhALqVzpkiGliKfzSzk1m4cI7Pe/aVPDUTmzmJPZlCn5o2SPeGFtIbu6EayDJnSJ3V7KSxkT4+X9kGm9lpFBBDNfG1VJHZgw3rggGQvJUs7sr0GXxO4kQObmChWRkRaF5i66r+8UuBnfpcA0/Itf/KI+p2yP8r2dDMilP/qjP9KEC5KqFfv27VNF1H/+53/K7bffruTQRgkpiwMHDvRMSHl9sGKxmAwCrM/TnvY0VU69853vHMgxHRwcLm04PykHhy1GpYLppHnwfJfBJNe1ribndAJbL3mGhErnKzIxHFMzc/x/IFe8iTnHQokEyUUpUaFBSKGugnSBqEAVBHklDfPqQQBCoFary57RWFfCYiwZ1jFak/ELAUrCKKmMR8ycMweUqK1XGnkxANLxnBKQEfWP2gh5xGfoVkcnPnzAmBdUUtpNskHIbAdUZdiDh5USost5HSceUv34GqGQ2kgHPubFqqQs/B611KXuK6X3Dw8qtZp2D3XYXly61KfDul33rFfSTi3dawcIqa9+9avypje9ST74wQ9qyRxKooc85CGrjMcvFDBF/8hHPqIqtFAoJPF4XLvydfq39bVAIKCf5fpuvfVWPSalhKi2IKce9rCHXehLdHBw2MFwflIODg5bCQglQ3iEOpqcQxqtBwilapISubyWZJFMo4iChBpPRrRsCbFVJBTUZBtvIDqDecv9MHfmdQgkVEuDULzg4QP5dWA8vsZEuxUouxgPZX50gbsQytRc0SrTzN/AKNQgprKFihpWX6ygnGwpW1LykljZDJgbutZRLgpsKZxRS9VlO4RAED75Yml936wlU6qKmrBfT6NI0O/xzeqtpBRSDmL34GRyze+G4yE5MWuIvAtdorpVQDUHCe1VzJmYuPA55W6DI6V2Kbzd4XZy6V47QPb89m//tj52IjBBb2eE3it++Zd/WZVen/70p7VcEb8s8Hu/93v6moODg0M7lMvlZvMKGkQcO3bMTZSDg8NAQXK6nCt2VO2gBunUIawVlJyRFKN+ggSKhOIyu1xQ8gDCIN4gIxJRQ7Icmow1CSnUHal8SVUNuVxZrhqJDYQIQZ1jfIt6S0qHY6bjHWV8rYbo2wEtr2qopCzwAWI8FyMpZUvXUDahFBoUGcJxILhQ41nyAcXU9iqlOvuxQUShCgOYmq9HiLYDx7UlfL3Om1VJtfOsYg9oGV+2pKWPlyIoTcTsvOi5b1G+dymXLO5UOBpwB+Izn/mM+hHx71bg7Nmz8vnPf16fX3311V270TlcGPAflkc/+tGqurKJJfGwVTHh4OBw8eMb3/iGNk0Azk/KwcFhKwBBhJLAW2pngdqJ5LtXQgdA5KDwQCFCYgwRgULk7GK2SbbEw0EtpbOEFMk9CintEFYo67+bbd+OUTrJN/5QvZhKe/9ew7eIz0OkbCcgOFgHS955S5I00d5gJ7YLBUhNCEqIIvyNBq3OQXE1NbxCrrDOeExtB2xMdSLB8AGjfmXvBgkpC9SDvZbwWZVUN2Uje473bFenwu1GIEApp2/V3q3U6vqaw/bCkVI7DCQUP/VTP6Wd2+g4xzffg0KtVpOPfexj8jM/8zPN0j1UUs4Id2erwl75ylc2f0YtZdfOwcHBwQvnJ+Xg4LDVIGHGZHwxu1YtpZ2/Qv0rDKZGYpqQU75nOn/hFVXBJkoB4eRN1OfTRVUD0ZkPMgj7hs38bZQtlrVsD+KrXdfA9QB5QmI/gxfVNv6NhrrDW7ZlwVyZEr7B5RBgK4kJiMbTC3TY86lSqB9iczNE0XaRLcQ1cdKJBMMzjdLVzRBSgP3Xq9k58QGB2Y2EZcy8BxL4UgTxhqm59YXjPlKt4inlKJLthtOm7TD88z//sywtLenz2dlZVcY89rGP3TTRxXHxKbrjjjtW/Q6CymFnA3ISk/fbbrtNW71/9KMflSc84QkXelgODg5bgK997Wvyile8QkqlkoyNjfX8CIfDzk/KwcFhW0DZHaqi1s5cKDQgivqFv2FGDSkBOUSiOD0ak4V0QY/Pz9YkmlI5CAzKiSCTrCExqiC8p/oFCTwlgxhpb6ZkB0UJqiXG71XjbCXoWgj51O7LZRRts8t5GVRBoZrML2S11Atl2CC/0CaOUMrhYTSe3L4SSMr3Srna9p6P7n8tr0OMlcpVSYxuPm4gVTmedpBbh1hhL/XSpXE0HpZzS3klXjdLmu00BP0+CYcC6s0GUBjWG687bC8cKbWDgJLpL//yL1e99q//+q8bJqUwyP7rv/5redvb3iaLi4urfodp9v/5P//Hle5dBMD8/NWvfrUq6Kxa6sd+7Md2hLG7g4PDYPH85z9fy/D6BY0SCoWCPt+zZ49cddVVbmkcHBy2VC2Fb9GBcZNKGF8WlFKBjZtRj8aaZtR7lHSqyELGEFMQPpwD0oeSP4gqVFKU20Fq8N5+SSnILXx8MFZHebURoKygDEo9i4aj2kUwHilv2py7F9A1bDjWngSk5JGxWTXVZgDBMbNkuuBBBNIdDlJwEAQFZWvWjwul0HYC0gZVTCefp63pXLlWxURsQyYNQh3GvrDn6UZKEfuotnohYtlXEGrsN1tCe6nA+HCZMk7mhKYJEFKuimj74bLaHQQMrb/zne+seu1973tfM9HoFXSne/rTny5Hjx6VP/mTP1lFSOEz8v73v1/uvPNOefaznz2wsTtsLegw+KAHPUiff/vb39buiQ4ODpcWjh8/viFCCuRyOf1iAzg/KQeHLUQgwCYzD57vUqhJeaXWLHuxSfBmvJ0gdiCm4AcoGUK9RBlfmQS6WpNT8xk9D8kjpX6cf/+Y0Z30W14E0QIhhTqHa9ko0oWynJ7PNq8fcoVufPgjbSXUVL5clXiLybmFz5bwtfH+6gcQNpBQEBMoZegKR+LO3EESbua4EIwQUqz5dhNS4lHDbJ/ZOZ0r157L+IINTifSSwkf+4pz9trhD7XUcrZ4SVqIUL7H3kXpiZ+UK927MHBKqR0EyussLrvsMk1QUqmUfPzjH1fj826oVCry3ve+V974xjdqiZcXlHVAUr3whS+UG2+8ccvG77B14I+L17zmNaqQAqjcfvInf1JVVA4ODpcGPvjBDzaf//7v/74873nP0y8V1ntQ8m2fj4+Pa/mfg4PDFpNSuxxNb6lMUWLjwUYp3+b/JoH8uGxqqPkzKqb5TFEVLRAY+8ZiAt+DD471gBpLRFXJ02vresiUc0s5Jb42Wy6WK1Q0iYWIwqQdcsV4VBW3tGNZXk3lu6trUH+d7tH0uhPohAdQgQFIDMy4IQUxo0epthEici5Nh72qGpr3Yyw/6L+tGTvG/dvRbA0FEwQYvmNWZcZz9s740PpldL0iGg7Icra0buleN4PzVkBgzWd8SnJuVFW4U2Hj13QtxPjcaXYuBBwptUOA1xMm5JaQouzuiU98YrOErxMpRRLy9re/Xd785jdruZ4XU1NT8qu/+qv62Lt37zZchcNWgjLOhz/84fKFL3xBFXXvfOc75VnPepabdAeHSwSoWC2e9rSnyf79+/Xh4ODgsBMxFFvxliKh61RKthmgYiIRLtTrcuW+kbaJ9FgiLGcWslpeNDG0mpQi6UfcYRUh/3975wHeZnl+/dvalvfMIAk7YUNpyyql7JaZsqGUVVZZZXysMP4UKIUCZaessFoom0IJFAhQNrTs1bADCVl24inJmtZ3nVt+FdmWrGnN88ulK6813/HolZ6jc597EM6fHo9ORFvrshOkIG5h2yGsQKTBvsD6ocwNTqLxLAuDu8boTpgIlFLCzIRj47SnP9GG+0y3r7lm2HZAUEF5JQSrJd0emdJSk1YpX9+AX9cfz5tt18RsQVlavpxSRmA/HH5GoD5ywXB9LjsN4rh3ohQtRvyKBeItxm467iwc/4hbyl92olTk3FCl7xPsr1TdYyS3UAosEiAqGZx88smy6667Smtrq/795JNPisvlGnZ/fNAhZ2jq1Kly9tlnDxOkNt54Y7njjjtk4cKF2rmNglR5gA+Eyy67LPo3jq1RrkMIKW26urqi3fPWXntt2XDDDQu9SoSQeEDh6OiIXMqwlCUdMHkzsqVQSgaHxniAMj4EbCcKUYe7qs5pVbfSSDfIohUu+a6zX/+HGPXNsj7NvspFWDccUQhJjuRJVauIgwm/0Q0vF3lOiYBYhNyoscD2wb3myaALH54fLrgJCZxQeG51giG3KsVubwAT/64hF1mhBSkAVwyOWb6AEye2hM+d49I9gP0KsQ15XfHA+wKvmW4mWG21VQU8o2S3nM5jcBzCjekNBOmUKhCFPxsQLb24++67o2G1Rx99tFitVtl///31uoGBARWmYsH9UcKFznoGcFa98MIL8uGHH8pvfvMbcTjy18GC5IfttttOdtxxR13+5ptv5L333uOuJ6QMeOqppyQUinwxhjOWIZuEFCmBgMhf/hK5YLnCgVsKzg9M7Mar7AXPmyxYu73eqaHomDRDZFjaHenkh4yn1dtqtTwKDp2+gYCEB0UWrXCruwr3cXsDmjGVSelezZCgAOcL8qnQyQ9g0g8XzHgAEQh6qOG2GQunzZx2rhT2IbrhYZ8lC66HIJiqSIEcrEhgui2rToe5BNsHh923Hf2yuMs95HjzqeCIcZTrDKVIrlTksx7PDccYBNdcAxcgnHvxxrUrZtymA95/GOPJSgNLDZy7cCyMzC+joyfJLxSlioA777wzKi4hfBztvcHBBx8cvQ9K+Ay+/fZbzYcyQO4Iyv8gXEGw4GSmvEFZj8HTTz9d0HUhhKQOsv8SfcGNLd2bOXMmdyshpGQmdMh9Go+JdTo0OK1itZhlYWe/dvCDkDWlpVZLjeCC8AcGxW4xyyarN8taE+s1/wnOD5Q4dbt9snCFSx8LNxVECa8/qLclK92L3e6mGrs+Bo4puMbQHW/cSvds5pS+76OzGNY1VTeQUd6I/ZZKOSa2E9lQycBnX0evV4U0lDcWCzh+a7bX6XhAZ7mIc2pQXWIIsIdYhYB9iFW4Di6jbMSqWKcUXGM4hIazLpdALIQwiuyukYImguqRp5YJ2EcY9/l0l+WlC+NgOOr0jBXXsZ0jHZhkfCgOmbqCwS/jsaV7v/vd76LLP/3pTzVPZMmSJRp2jvyohoYGOfLII6W/v1/vc9RRR8nNN99ckHUnhWH33Xcf5q6AY44QUlx89NFHmv+GHwyMC5pXrLfeevLvf/9bJkyYEL0v3LA4xwOUbW+zzTYFXHNCCEmPbLrX5QoINJMaq1WQmtTsHBa6jjImCEUQHoySMbgiNMenepUYgwk7LhALcH/oDpOanHEdSUbpXuwEFuvQ1lCteVLtDQ4tacRkN9cZNRC7Us3vgrsFAgS6rdlqkzurOnsHVMRrSTF4G46nlX3ehPlFBijxhGsH+VvFBo5bdDzEAOEJrjG9BOHAG1RBEH/jNstQ2H46eVAQpbrdoWFd98bLTIBjCEcgxmqN3ZpV6Z4BxgbEXLiwxjPIP5/g/Ymuew1Ws/QObaMBjhEclsiKY9bU+EJRqsDA3QTnE/jFL36hExYDk8kkBx10kFx77bUSCATkH//4h/T29kZzRxCIjm57pLJAjhhywz7++GN5++23paOjQ9rb2wu9WoQQEVm8eLHm/P3973+Puz/mz58v/+///T+59957o9eh7Nrj8ejy3nvvza6ahBCSAau11Gq5HsrVIiLIgApKEBMmJhEPVLyxWYaVlaEcEE4TBHKPVbo3shwMHfh6PYGhNvO5Lc9CCRzEruqG1IUQrCfKFpN1W4NDDDlYqzU7UxZKIMphsg4xL1FJHvYBSuQgCmYqhhRcrBqx6yCwwT1ldEFMFbj5IFTiOGKcpir+ZQLEFZRgohMkjg32fS5eE24puMiCtfaiyAXLFoxfuMc0m64azspVY3SVqw3v9/IKeC82Sn8klTjXX399dDm2JM8gtoQP4tSsWbOG5UrV19fnYS1JsbHHHnvo//ilxnBYkMIyd+5c2WKLLbRRAcq0xgO4JufNm6ciBtw2EKhfffVVDckmhcXn88kVV1whM2bMiCtI4Vxt5Pyhc+bzzz8ft3QvUadVQgghycHEEsLU1NZamdJaq4IQBClcny4oM0P4MQSVWCAojCzdG/44mwoxFnOViha5xBBB0hEDIEjA6TNWlzm4aeB+QVe9WKdIKiTLlYIgVuOw5KzDHDLAIOwUEux/lHulE/IOIHhYTFXqXNMyunHO1oKjDq+pJalDpXvJAvKTgeMI9x0cROUAxrtRqouGBbFgn0F4TaVElWQHRakCghK8lStX6jImMui4N5If//jHstZaa+nyJ598ohMfcPrpp8v222+f5zUmxVjCx1ypwgJh8Oqrr1aHC5xrs2fPVqdMrst8//jHP6o7EueJnXfeWfPjcA5A+D2uX7BgQU5fkyQHJdVvvvmm3HrrrdotDz8aGPmALS0tctVVV8lLL70kS5cu1YYWsaXaJ554oni9Xj22//znP6ONLnBsCSGEZA8mk3B1ZCJIAThLIHDBMRUrgsBtMrJ0b+QkF4IVHpPrXCnNk7KnJ+5AlID4ATEnHsjNQUA7uhymEp6eTq4UviOhJDBSDpmdkAThAO6k5b0D0tk3IIUGGWUQ+9IFYwciEfZbPpxj6DTZ54Ho6MtZuWCj06bPOVbuWqmA90fVkNgcC/6GIw5dP8ut42AxwvK9AlJXV6ed8jBpweQE5XojwYkDbilMSA3WX399ueyyy/K8tqSY2HrrraWxsVEnus8++6w6cywWvp3zjd/vl5NOOknmzJkz7Hq4Gn/0ox/Jr371q6xfY9GiRXLYYYdFy3bj4XK5VBiBU4fklsHBQfn++++17O6zzz6L/o/L8uXLR90f5/ETTjhBLrnkEmlubh52G7qiwuH6+uuvy5dffqnHCyJUZ2dntIS7uro8MhoIIaQcgLgEpw8m9BCogDuF7mUoA1raDREokkuUq86EmBzDzZQuTodFHV8jQ8YhnKHTHrqqIdw8E8bKlYKzCy4sOGsg0GVaAgVxAOsJ9WBKS40s64l0yStkaLpVQ8sjoefpCD3IlYK42JSncjA4myIlpX6Z2OjMyXNC6MX2Y0xB+C11zENh5/FcUnivI+x8PPLhyCo4iy0wOIntsMMOY94nVpSC8PC3v/2NE5cKB+Pg5z//uTz44IMqTMGtgWB8kj9QMrf//vtrGV2sg81wrh1zzDHqntl0000zfo1HHnlEjjvuOHXkGOcLPC8yxCCWQIy85ppr1G2DkjCcJ+KJ2yQ1EEaOrLZYAQrXGXlPyYBrDW6oTTbZJO7tODa33HKL/OAHP9Bjd/nll8sHH3wQvZ2le4SUAGaziNGMAMuk7EEGDzJ0jLwZlObBfZJMqMGE1hcMyYAvKNYcTNwxSYYxJRM3EybWEI4g7hilf4aLCeuJzoGZMlau1Mr+SMc9CBf9nlWB2+lud0ePR4UQ7Hd8F2ofCpRHhlemTrhswXZjXSA6phd2HrmvM03HWzYYeWKxDQBy4ZbC8a2vtpZ853eM35GiFMYzxi6cjxASc50PR4aT1ewFv/JiEJ522mnRSdopp5yipWj4tXfatGnaTQ7h3LEsXLhQM3FQqoDJ1VlnnTVuGSzlAEKtDz/8cLHb7XLDDTfID3/4w0KvEimiXCmjCx/JH+iiBreaIUjhvYkcIeRKwQ1jdFTbZ599Msp7QgkYxKcDDjggKkgh4B6uyttuu03+8Ic/qAB15ZVXqrsGwM2D20lmoOQSjSawz9HREsfz/fffTyhIoXvez372M/ntb3+rDSdeeeUV3f+JBCmDjTbaSIPODafdE088octms3nYe5oQUqRAiELcAi4UpSoCiAjoMAi3hHaxs6aW6QQRCyJQrkr4IG5lWn6FiTUm2HDoGHS7fSqooGNgtqJCvFwpFb36BqS1vlpFKdw+Vq5VPNAtDuIT9n97zHpCjGqutWs538iyq3yBdYFbyBdI/PrYB+j+GAuEIbju0s3uygajFDWX4hHGogyFp5c6lrii1KCOM+CwYnwzV2o8yVhaRnYKykViv4AjhBcX5KtssMEGOnHDF3Zch1/8AX7RxxfviRMnyhtvvKFZGxBcrFbrsBI1Mpx77rlH7rzzTnZlIlEgRuDDBR94cOewdCs/LFu2TEuuvvrqK/0bwjqCqiFSAWRKGZ0RkfOEEj6IhhAdUuHdd9/Vx3zxxRfR6yCU4Hzb1NQ06v4o7TNESbgokTVF0gOuKDjO4jmb1l57bRWrcEHptLEc71ikyoUXXigPPPCAfkbGuqxGlvsRQggpDuA0+X6FS7v6JetiFytKLe8R6R+IBIhnKwhA3EJwdabA5QEBAQIPxB5kAqEjXi5KkpCP5BoRCO/yBtVtAncTRDyIGBBojDLIZCDLC+sIMUoFkBFgO9RF1evVMPtCuHWQK4USPpH4DhpsPzo4onzRKOGEGFUOJW/Y33BL9br9GZd+Fgs4JhCQRx47CJ+GkAgRl4wfGUm0yC859NBD5fbbbx/2xRy/AD/66KOy11576Rd5TI6QffTkk09GnVDPPfec/O9//9N22Jtttpnstttucumll+pEDr8ak8SkOqkllUFbW5t2ewMQQeBAJOMLXEsIGjcEqenTp8t///vfqCAF0GEN50EcH4DMr/PPPz/pc6McD8HYeC5DkKqpqVExGmWaiUQQBKwbXTgh/qdaakZWgeODH0zAIYccIg8//LA2lsC+xLFAEDlcaUcddZQen2wEKeO43nTTTcOuY+keISUC6qd6eiKXMgj5Jak7TZrrHJqblCxPKnai21TrUHdSul3aRgI3kD8QyqrkC8IOSpDgWILrq63BkbOOeCjbwzbGBl939EYcTsZrYBkZRMnCsXH7sh6PiloQzeIJUgYIZ4eYgM6BhQBlXf4xws4Nd022x79Yqa22qvut1IPA0Skz1illZIXh+BpOQBznQrnyKoGMnFII9oXbCW4BlJGMBUr3MGEyQpiRfYNyNJQ+GCAbB8Gwn376qWZtjAQd54yuc6Cvry86icOFFBYcA7xxeSzyD0Td//znP7oMt8zxxx8vpUqxjyOI8ciMggAI0PFu3rx5MmXKlFHrvNpqq6kTBgIWxI4//elP0tDQIOecc07c54ab9Mgjj5QXXngheh2C0iHer7vuurpfEnWtQengfvvtJ3fddZeu4z/+8Q8VVkhqY+utt96Sxx57TJfh4IUjDaJR7GPHA4wllHfieEHInDlzZtGOfVIa5yiSJ/x+qbr2Wl0Mz5olYsvO8cBxVTo4bWZZrdkpMBaleh6otZslGAqpW8qY4GYCOudh4gwvUKqvPXJsmasik+8lXW5pqrFJtdWcs/MZnhtGpQGEmtss+roQpdae2BB9DbvFJKaqsPR7/Ooii0dgKNAc7q1JjdX6f7J1bKu3y5Iuj9gskS6D+QT70+sPJFxHjy8gVRLW/YLxU+xkcj6qdVik2+UVe45C1AsBjlEgGIput+bAWSLVKBpkrxliVfo+LHVXWL5JdSyl/c7FROu9997T0pRkrFixQl1QCOqNLX2JFaSA8TduiwfCYC+++OJR16NjEbrWkcIPNoiPeNMyZDm/bLXVVtFllJBhkluqFPM4wnkGZcYQMABcUMgcstls0tHREfcxKGHG+e+8887Tv/E/xHWUNMfyzDPPyBlnnDEszBzCP7L2xnr+WPbcc08VpQCcVTvttFPW21xOJBpb+PvMM8+M/o18ROR54ZIP/vznP2sJPH6ogbiYyrEmhaOYz1Ekj/j9Ujt0jnDhPZsDUYrjqrzxut3ylcclobZVP3iky0qXXwWajqA7q7Hl8wbV8eEXm3Tk+KPO7fKL14WSLqs6l3q63RKsF+kYiJgJgN8blG+70EHQEb/UzeXXUqkmp1VWrnCl/NqD3qB8tqBLJjYgqyl/ZXxwdXV2DYg15NFcoliw35d2e1W06esJSWggtbLFQpLJ+QgOoyU9Xgl67FkJr4UEjrZeT0DMgcgx6nL71R3ZEVj1JnG5/dLfK9JcU/qll/mkv78/96IUWpOfeuqp6g7AL7tjATcT3FSYmP3+97+XbJg1a5ZO2mKfG6G/mBgaZSuksCcwTKRxPPhFPb9AfICoi9b0r732mr4fkr03k4HSNAQ2o1EBnD6VPo5QFnnyySfLq6++qn83NjZqGXKyQGsAZxS2CecwAHG9paVFRSeUhkEQgTPHYPLkyZofl24uFEr4cLywri+//LJ+mRgp/lcyicbWv/71L3XvAjjSIEoh3zCfIFSdlAbFeo4iBXBKDbkpne3tORGlOK7KG5NjQL5e3ictrW0ZCSb4TB+ocsmERmc0eDnTsdUu40d1nV/6vQFpb6qRlYu7ZZ1pdTJxQsOw+7QMhmXRCpc0NDmHdRGEk8zT75O1p9q1zC9dsF2R0POwtOU5XypocUljrWNUmSHyrrwmj0xqcsriLo+0tdUWfZe6TM9HFueA/t9WXy2liJZX9nikva1O/w50uTX3K9YVVeMLSLfLJ+0ttQVc09Ij1XlpWqIUAnjxS+7mm28evQ6lKeg6hHwMuACQewRFDCHMdXV1WpoQ+yUf5RHIYIkFE2rjtnjgF2RcRoI3C78YFgc4gfF45B/sc5QBwSUDkQPCCcph0wFd4iBkICwdk3QjLwmgu9z2228vlTaO8AUQjRiuv/56Le0y8oZQ1oV9hDy8VDn33HMlEAhExQd0JIXLE/lP8+fPH5YpNGfOHBWt0gX769e//rU2i8C6IoPK6IpK4o8tfPEyXGwA+YfxPmcIKcZzFCkgOPZDE8sqLOdgLHBclTct9U75Znm/CjbNten/cAhxo6rKpKVp6Yoa+RxbTodNulx+CQ6GpccVkE3WaBn1uviz3mkXly8o1Xarft9CeDyypiY112RVftfe6JTFK93S7w1KY834fJ6rQOgPaYYSLugs6LBZdZtHbqs/GNBtxO0IekeTPoe1+D87MhkzyE7Dvsd+yFVOWT6xWkRQpKcNpCA0hsJ67GL3gdNuk84+nyB6KpXumyRCquPIlK4rA3kqH3zwQfSC3BOEnmMZghRcTHBXoOwE4bAj1TGExOI5YssU4LyCwwOuKkJIekCUMoCAkih7KBYITzfeeKM+Fh2/kE2Fv2MFKXD33XdX1OFAswV0sPvxj38s2267rQZeG4JUbW2tPPHEE8NKJtPptnbBBRdE/0ZZnyFIVVdXq1sKxy4TQSq2C58BtoGMDcovP/roI13G59j+++/PXUYIISTnwB2FkPRvlvXJ9ytd6uhZ2e+VHrdPu+BB3ECw8siW9AbIt4ELp9hdNuguh22FOOGwmRLmRtU7reL2BjU/alnPgG7/ai3ZCVIA5Vbo1IfSQQS65woEqaNrIMLXv+t0yYq+Ae1xAGHCyAqLF3bu9Yei2wRXWLmGnQMIUXC44dhjjMNRVMzbi7kSwv6N0H3DwYj3IBoKmExV0W6JBrgPjqMRXk9yS1rvfjif0GEvFjgHMJHC9YYgBccGAnrxtxFKDhsgRCvcDvEJEyh0M0KOFCZrKGfhr9SEpM8uu+yijQTQ4fK2226T999/X84++2zNlzI6NhpuKLh8cPnyyy/jPhfu/5Of/ERdkcjVgQgDoQYiczkDtyaEoZtvvnlUtl17e7s2YkAWVCI3Zypccsklui9x3jOA4wriyPrrry/Zst5666m48s4772juH7qcUuiPD1y9sSIhguiL/cs+IYSQ0mWtifWysLNffIFB7d4H/QmTdnTmg7tkEBfk+KhLpUrziSB6YCLs9gWlaZycP7kGXcq+XtYrU8YocYKAASEnIl6ZZVJTTc5yoCAaNNfaVfiD0IUOiJkIFjg22O8QzALBQX1eCIN4bsMJBOELolpbvUOdXiOfAw63ptrIcUPZZSFFGqxPt9un42i8vu+01DnUoYZ9hkDwXo9fx/LkJmfROYtwbPsG/HpMDcEXYxDvRd/Q8Y4HjqM3EEwouJLMyWmLAkyEjE5g66yzzrDbFixYIGussYZOeufOnauTPLimIGodccQROmEjhKQPuroddNBBct999+nfaEJwwAEHyNprry2/+tWvVGBCGR6EqXggxwhOKVzQURPPB/cjxJKenh55/vnnh7mxygkIeCjRu//++1UwigVlysjQw77NhWCOD7wrrrhCxf077rhDDjzwQD3v5VKMh9gPUcpwS6FJBBnN7bffLt99950u44eSdDO8CCGEkHSwmEyyelu9dr4LDYq01o8u44NLAy3n8T/Kh4xlTIRH5hUVK9A7sM7xti8WiDsQbZDbk2uRBI6dgSHBCAIghL5ISRq6BFaJ2WxS0S/2dbGvPT6IhHCuoVxS1OUEEQdCWzzRDNebhrYXri9DVASGc8oI/obI0TdCuMonEMTgILNbzFIzjt3jsJ+Qw4QLhDB0RcRxri0yUap3KMgcApPx3sJ7FOMA+ypRdhvGxIp+NlkbD6rCqdT6FBlwX2HijO4ADDovPMhmQTkmHCXM2SgMcEk99NBDctVVV2kp7VgYbihDiEJg98gvBLGd/I488shoZ7dyGEcox4MDDGIU8vBiwevuu+++KkZhH5Waewb7DyIjthHNIL799lu+J+OMLRxbZIYBiLaxOYmEJIKfdUQJBkWefTayjAxHS3ZiAcdVZQHxYmmXW4WT8co9KuTYQlni0m6PbDStWQoJhCKUR+J/iEVwomHGC9EBbhh8uzPEKVzvC4YibihbxDmTyCkTb3vxGhDBYoPo4RJC2eXEJmd0fb7r7JdprbUFcQ1hX6CkDqKKsU75GDNwrFnMVRllqY0XhsMNLjY4uiY3RxpXLOv26LHv8fjV/RavnBRj6buOfpnSWjuqvI9kp9uUhuxOCBkTlO/BFXXIIYeoswklYvjfYNKkSSpAwfFkuKHGAmHpyFByuVwqUKG0rdRL+FCOiPI8NGUwXDIG6Kh37LHHahnx6quvLqUKvkSgycRTTz2l3VLhAIPrjawCjTiMZhszZsygIEUISQ+IUHvswb1GMgITWYgCcJCgtKzcyoAgvqw2NMkvJHDsoJwsHvBjQJhCVhQcaRFXlDmjUj+4jiBmRHKlVjlsIFKhNDF2fXAfiF+5FKWwLct7B1TgHKszI9xfuA/EKQij+RJUdJuLLFsKohNyzXDMu/q9ug8jTroqdbhhXCQKa4e7yoYSPn9IrNUUpXIJRSlCygicVJExhcuHH36orinkFsVzQ40Fwrf33nvvaAnfCy+8oKJWqYIPHHS3ixXqjBwmuKJQ9oZS4nLg9NNPV1EKzJo1S51fOJ4kAjpUwlkIWLZHCCEk32DCO6GxWpb3DKhYUSqleamgpVrjWB6WC/B92GoeHWSdCRCCIGaEwgjIHhQZ+roF0WKkEw7uK1xfY8/d/kEpGXLJUHqWSJQyMrJa6uwqnCGcPV/OJYz1kXlbhQTbDwdba13EsYZjhwwp7Ds4ulwDgWhgfyIgZkF0LDdBudBQ4iOkTNl00001rw3/Z1KGhlwqA5QGljKvv/76MEEKAtszzzwjn376qQaYl4sgZXRJNTLA4Ja67rrrCr1KRQUE1th9RQghaYFaH7c7cim9BAxSJKA0CLlLKG+CkFMORLKwEodElyvIrQoGB9UFZQgfwD6UJ2WQ6w58COqGINVa5xDPGN0G8ZqYBkAgqqu2qfCSr/QeOKXgzCqWtKA+T0DdbYZbTYPLh/YdhD046JKNX7x3c9ndkUSgKEUIGbOED6CEb2QQeDxuueUWWWuttdR5NH/+/KLZs7Nnz44u33nnnfL000/r9pVrBhrKN41tQ9g58gHIcFEKQu3222/P3UIISY9AQOSqqyIXLBOSIXAUNdbYZHmPRyfupQ7Ej2Quk3I9jigDNAQnuKEgbIz8QRgCCMrDciHQQMjs6vdJe0O11FZbJRQajIph8e5ruKjg8gFjiVi5RN1IVVVFMb4hmrq8AQ3XH+ZeGzpuxrgdqwzSeAyeK9H+JplRnjMyQkjWoORrr7320mWjhG8sHnzwQe2qiU6b9957r2y44YaacQU3UiFZunSpPPLII7rc1tam2VvlDvY9MrKMDKWLLrqo0KtUFKxYsULLWgHKWltaWgq9SoQQQioYlHhB1EA4OEK4SxmIMpXmkgLYZpvVpO4ZiC+xIlAsRk6R0ZkvUzBOOno8KmjCtQPRB//DNZUoT8oI7YZQBrdUvyd/grpV87YKP7ZRtohjFTtG0UERImKsKJVsDGN/x4pZJDeUTxEzISTnoIQPYdng4YcfTpgrhU5mKBWMBb8EPfDAA3pBnhPym+x2+6gLAtTxv9VqlYGBAZkwYYIKYsZtcF4Zjq1MuP3226MZQsccc4w+byVw8cUXy3333adh9bfddpuccsopssEGG0gl8+9//zu6zNI9QgghxQACuUODA7Kse0AmNTt10luqolR1GeVjpQPyhdBxzx8Iad5QfUP8LE+jhC9T8Q7frTt6vfr42Mwq5JK5fUFprEmcJxW7rvkMPMdrRFxFhctgwn7o8/ilpX54lpZRYon1g3gGZxdKDpMRKeELSX0OIls7+wbUeWW87/E/Fptr7SXXBTwbKvPMQQhJCXRyG9mFD+JRLN98842KTj6fT/8+8sgjZf3115err75aOjs79To8NlPq6urknXfekenTp6f92EAgoOsMUM6G/KhKAeIegs7PP/98bfF71llnRQPQK5UXX3wxukxRihBCSLGAFvRoU9/RM6Ah6KU4GYVzpLG2Mn74i1/CNyj93oAMjpFLZLeaZGW/T0Wh9kZn0lKxkXS5fPo6q7XURMUUX2BQBRVvf1DFjdjySYR4G3lSBhBeIB4iW6opD8erGDrwubxBfU8hZB77yO0N6HiFIGwE0Nc7bTKtNbUfwVEG2debPNYkGTh+bm9QjwOEM1R2hvEvHHG1VRIs3yOEJASOpT333FOXu7u7R5Xwoaxvjz32iIpP6GYGV87ZZ5+tZXx//vOfVRzJBpSf3XjjjRk99oknnpAlS5boMroJTps2TSoJdOKbMmWKLiNHa2T3wUp1SlksFtl2220LvTqEEEKIggko8oGCg4PS2ectub1ihFmPDPeuFCD6OKwWWdkfcTElFBTCIst7PeK0W2VZt0fcvtTL6CCkQJSCK2pFn1cWdvbL4pVudQChk6MfpYMjsqLwdzzhC24plLPlI4Ac+2as8j0IMyhfHc+Mpm63VyymKlnW49H9BvEQ+8YbiOyfdEvxcIwhPma7ziitxOs3OG3qfIM4hc6IEMsqDTqlCCFjcuCBB2oJnlHCt/POO8vKlSs1n+fUU0+Vzz77TG9DeR6ymwwnFTranXHGGXLiiSfKRx99JG63W91UCEzH/yMvXq9Xurq6VDCAwwnXzZkzR69HCSEELpTzpcNNN90UXT7ppJMqUlT84x//KIcffrj+feaZZ8r7779fcb++gMWLF8uXX36py1tttVVWJaGEEEJIroHDZWKjU5Z0uaXL5dXJaakAJ4xtLDGmAoCg8P1Kl0xqciYU7rrdfqlxWPS+cNt09nolVBeW+ur432/hioJwAeFp4QqXNDitkTJJm0XqGqpV0MA+h2D11dJeWbTCJdNXa4yWguGx6A44EqfNIiuHAs/hHhpP4OLCdkAAGzk+cB32AYAwhfGf61wydClc0uWRyc1OqbfbVPBBSSGEvQFfSI9Hf196GVvYDiOPKtaFli4DvqA4hsLnKx2KUoSQlEv47rrrLu1eNxIEiKM0rKmpadRtDodDtthii6R7GSVm6BLX3t4e7RwH8QuCFP6H0wdlgqnyySefyMsvv6zLM2bMqNhyrUMPPVSuv/56effddzXk+6WXXpIddthBKo3XXnstulypY4EQQkhxg9KqiU0Qpjzaoh4lRaWA5iRlMTkvBxA8/tXSUFxhDiVj6LKI+0Ckwf6qcVhViETZJkQbiJAIMYeQhFwq/I+uehgTKPdDaVmizDE811oT6+WLJb3y/Uq3uu7gWhuZJ2UQDTwfCIy/KGU26etBlBsp4PS4/VqutlpzjWZyQZhC+aoRzJ4Lvuvs13ymaa11w66vtpu1g2FznV33c3BoX6cKREXND8vwPQpBDg4tvD5h+R4hJI0Svng2XwSHo0wOgeS5JjY8/a9//Wtaj/3LX/4SXYZbq1J/vYPAB4eUgZGxVcmiFMpMCSEkI/CjyWabRS5DP6AQkkswcYcwhVItOGBKAW+Fdt6LBULKmu110uPyaWmeURIWcQMNqMgIcQTuJiNjCW4bOHiQeYSysu86XdLr9qvwBDFpWludZjK11lfr/cYKwUeuFVxADotJXx8laiPzpGKBQwhOnXyU8MXrwIfSNwhRbfWRDDWUr2H9UYqYq3G/ss8rfZ6ArNE+XJACKLeEUIYyPOyjdEv4cOwgHGYKXs8U5/gEQoPqjKs06JQihCTlkksuka+++kpzpVpbW9UZhQtcTSgNG6+ubnC0TJo0SZYuXSpz585Vx1RLS8uo+6G7Hj7QzObIib23tzcqYqGMcGRnwEpjn3320eOGksvHHnss6kirFPCFyxClnE6nlu8RQkhGWCwiabh2CckECBdtDQ4tbYKbBhPgYv6MRdc5ez1F2imttep2gtgCYQjH0WSKuIQmN9dEyr6sZvH4VmU/QZRYrdmpIgWEktigcjikIGAh2DzZj6u4He4dlFEOhiMupLGC1PG6eAzC0NMNXM/ELRWIEaWMsr16p3WYmImsK2j9uA37DC6kTLtRDobDsqCjT6a11sQV5rCf8dqa62SLhJ1D2EuV2M59mZTwwWVlvK9Dg4MaeO7yBqLlmbXYFxX0gzrPHoSQpKy77rry9ttvqzD11ltvyZNPPqllfFdcccW4CVIA+VIoPwPImTKyrWLBdSgvRJYVBCt06dtyyy01wwocdthh0tDQIJUM3GxHHXVUdD/efffdUkl8/vnnsmzZMl3+6U9/mnY2GSGEEJJvUFYFZ41R3lWswAEDcSObbJ1ywqyOKIdMhRhihUMopM43Q2xSASSArnmhYY/B8Y4VpCBaQFia0IjHpjZlR1c991BOUa/bl1TMhBgFQXG8gdsrNhQcoh3K9ppqRpeuYT9gf0GgWdjpko7egVEB7qmwtMuNXHmZ3FybtAQvEnae3msYAmOmbinkWSG0Htu3sNOl2wtRbFpbrW5/JQlSgKIUIaSoGauE75tvvpFjjjlGQ9HxqwuC0hFmDRGikgPO43HcccdFl9EhERleldZ1DzBPihCSFSh18fsjlzyUvZDKBk4RuDkwYS0kyERCAHu8EieIK+PttCllcWpKS606hQwg3iFbCmIE3DzxgEsIZWzIG0qnLBIB5upas5qkbyAgDuvYU308d7pla9l24IM4BbHNKNuLB8YT9tukIXEGwixC3OEcS0WghdC0pNsja7TVDRP6RgJHknYotEXWD+M8HfA4vFa6wBnlU4eVSd/bq7XUqJMO7/dUBchyozK3mhBSMmy00Ubygx/8QJf/+9//Rrv9hUIhFawMR9Saa64pa6+9tjQ2NkYfe/TRR+vjicg666wTFWS+/vprefHFF3O2WyAKosTzyiuvzEs2Qbq88MIL0WXmSRFCsiIQEPnjHyMXLBMyziD7B6U9hWRlf6ScCtlIIz/nmSeVPg0oSzNVSbfLN+o27N+OngF1zSTqypcIBHVDAPL4InlFyb6SQZSKdWyNZ6ZUIBjSrCiIcSPL9sZav9Z6h6zeVqsdC+FKgji1rMcjbl8g7ndOCH2Lu9xSbbVIc93YHSwhfkGIwgX7Lt19ERG1Qml/98V2oDEANDCIZja6DClKEUJK0y11zTXXRHOCELL+0UcfRXOvUKLW19cnc+bMKdg6FyPHH3/8uASen3322XLRRRfJOeecE7fEspBAvETHQYDukJshnJgQQggpEVDOBHdJbPlTPoGQgAwkdEiDa6XbPVxIwUQeZWokdeAQQoc8dL8b6bRZ0e8VqZK4XfNSAV3lEJQN4StZaRkcVRAb03UIpeMI6hvwq6i5tGdAxSQIOfHK9pLtL4h0cE4htwuCzsp+nyxc4dLnNt4bEIdW9HlVxEWnwrFcUsbzOoaEpUxK+OB0AiND3JOB9xNcVsjZinXRVTLcC4SQoueQQw7RfCnwt7/9TT788EO54IILoh8oyEhCrpQB7ltXN7rTRqUzc+bMaMD5448/Hs1ZyoZXXnlFbrjhhujfOD7FxAcffKBCJdh+++2jYfiEEEJIKYCJNbJnCuGWQqlUZ59X2uod6iSBawXdzAwRAGIGRA2W76UPxAiU58F9ZohCEHAgWExoSFzalkoJH54NpWDJSstQKpaJQygVsE2LVrhVeMP4WK3JqflY6LCXTUds7De4pqa11qqwh9dZvNIt33X2y5fLenUf1tgtWiKZCtFcqaGw83SIiFrDS/g0+D8Y0u1OVGqIkkG8pwOhkLrICEUpQkgJACFlt9120+Xvv/9edtllF/Ejz0NEzjzzTA2vJslBwDdKGo2OhXfddVdWuw2lk7/5zW+GXTdv3jzt8lcsPP3009Fllu4RQggpReASKUSuFAQpTJ5rhrqSoZwKpVe43ph8Q9So1BycbEF5Hrrlwe2DMsiufp8KLdinmYJjpIJXrV3FpkS5VQYQjMZDlOof8KuTCA67xhq7OB3WYR34cgFcV9hfbQ3Vkc51vsh2QLRKdUzCKaUd+BD6HhxU9xVKDJFfBfEo2f7DNna5vHpZ2u2R7zpdsqTLo4+HM2zk4/GegQaJ16NTahU8gxBCSoLDDz88utzZ2an/Iy8KWUYkdY499tjoL1S33357VoHn5513nuZTAcOBBLHrkUceKYpDMjAwILNnz9ZlbLMhbBJCCCGlBLqqwRGSj/yf2A5pcEHB2RILSq8GB8N6O0POswcuNDhtlnV71N0DoSUb8H1namutONHNz2xK6v7RXKkcl4ZCiMH4gBiVqANfLoAwilwulOxNa62TjddoUQcVRKlUsQ85laAdYb+11jl0XSESQpz6foUrKizh9XA9tk275q1wSWevVzp6vCowwaGFEkNkYE1pqdFjAcExFkMAw214f9EpFYGiFCGkJNhzzz2HhZhbrVYtFXM4xg4xJMNBIPyuu+6qywsWLFBnU7ZlezgGf//736O33X///UWx21HWuXz58uj4wbYTQgghpQaynOBYypdbCuIBJvvt9Y5RuTyYTENIQQc1lBSm0x2OjAaOHnSiq6u2DhNxcoFRmpbvsHOUrllMJh2zBhBf0s1eSpZXha58eE9Mbnbq/gMIDcf7JZMSPKNUFsdhYqNTRSq8F75e1qvh6d929MvyHo/eF8IV3gfrTGqQiU1OaaixR7tl4jlxQRkm3iOx79sBX1BFZghcdEqtgqIUIaQkgPCBbCmD3//+9wytzkHg+S9/+UtZb731tCQSpX3Yr3feeaeKVZ9//rl4PJ6kZXuXXXaZHHDAAfo84NVXX9Uyy0ICxxa6ARqccsopBV0fQgghJNsSPoSOjzfa/W2oQxpKm+KB67E+cNhQlMoeCCEjHWm5wOgONxYQV+B8g2snV+On1+0blekEsQgZS7no0oyyOuRIQUSa3FyTdfc65HCNDIXHei7vHZAqU5UKSxD4ELK+eludClYQrrB/sQ64Des0EpRhtjU41MmF/Ws4rXD/4FCOGIPOI2TnDySEkDzyhz/8QXp6emSNNdbQjm8kM+AaWm211WTx4sXi9XpVfMIlES0tLTJ16lSZNm2a/r9w4cJo2d4222wjp556qv4idPDBB6uohQ/dhx56SM4444yCHSJ0Afz22291Gc6wjTfeuGDrQggpI5BTssEGq5YJyROYyGIai8lvIrEoF3S5fFIlVUk7pBklUkb5EynOMdPRG1JXUaKMJbiKIOrALeW0Ze966/cG9DuhkUNmAPHFKFnLRkRCVhNcesjMgjMpF8AphTI7fH/FOhrCbCgUljXa6ofypULSXBt/H0KccvuC0lgTv3umtzokHT0D+p6B8RDbj0B7iFbZhL6XE1XhXMiVeQat3hsaGqS3t1fq6+sLvToVDzJpOjo6NIzaxC9oJEM4jvLLa6+9JpdffrmW8EFkgvspE/cautvNmDFD//7iiy+iyz/60Y/k7bfflkKNpU022UQ+/fRT/fvFF1+U9ddfn+cokvW44mcdyTUcVyQd4LgIS1jLvcZjbEHwQkkUyqGydZ+Q4uD7lS519cDZNta4gjbSVGPL6nMOssKilW4VNI1yuljgboKDaqRglQrIVOvsG9ASQISb57rj48LOfg1Mh8AEQQple8iHgpiHTClkSzXVOuJuF+6LcHNkScUTmbBfcHtwcDAazo5cKpQBwnVVzqSq29ApRQghFci2224rTz311KqgyO5uWbRokQpU8f5HOV4oNNzaDFHLEKHA9OnTZfPNN5f33ntP3nnnHfnyyy9l3XXXzfu2zZ07NypIwcm13XbbRcPxCSGEkFKl1mFR0ai1LuLoyCWY9GMyDgcKBanyASIIxI+xRCmUYKJbXrbALWSM03gYuVJxDEVjYoSOG938Ruac5YJIF75I/hNcYxBmDXcZ3GQor1zRH+lGOfL18X7B21GD/+O4GPFebW+sVlHOyNlintRwKEoRQkiFgw/L5uZmvWy66aZx7wNBaunSpVGhCiV9O++886j7IfcLopRRQnfhhRdKPoHABrHMYNasWbRGE0IIKQsw4cV82OMPallQLkH5EibXuSqJIsUjSkFMGQu71SQr+7PPe0KZW6PTlvB7F0SldEPV+zx+LSmFwyrXQfCj9lPfgHYsnDzkkIoF7i4EuKMBQGu9I4H4F1+UMsoXEZxuCFooY6xJIN5VIiwCJoQQkhSz2SxTpkyRrbfeWg466KC4ghTAbbFd+PJdIf7yyy/LW2+9pcvIkdpjjz3y+vqEkDLH70enjcgFy4TkGUyOEbycS+AOQcZNvMk2KW2QlxQKDY4ZZG4447LpjocQfgSmxytvi3VKpRqojpI5uKMgdE1srB5XQQo47WYVlFCyh6yneLTUO/S9AufWSIwOfmMR67AKBENiS/A6lQj3BCGEkJyBIPSf/vSnujx//nz56KOP8rp3Y11S5557Ll1ShBBCygpM+iEg5epHH3REQ6YQ2tsnmoyT0gWlZyjPSyaY4D7pupgAQtThHoIbq6HGPub3LohfKFtLNnYxJlHqhpLS1VpqxjXY3wDOKAhSY3XDw20NTpusRLbbiG1wDO0/iGnJwH3QfQ8i3UgC2PauyLZXEjzzEEIIySnowhfrlsqnS+q5557T5bXWWksOPPDAvL02IYQQkg8MV0uqjpNkdPZFcnIyCZ8mpQFKy9A9LlkJny+YuigFAQZOpoWdLl1G+D4Em7GI7cCXLJsKAikcUom6BhaKhhqbhMJhLeUb+b6EEyoVYQ/CHMTCkds2GA7L8h6P2Ieeq5IorqNMCCGk5DnggAO03M/IlcpHCR+C2GNLB88++2yxWFirTwghpPzA5B4T22xBBzAIBCzbK2+qbak6pcYeU/g+h/I1OHmWdntUWIGTaWKTMxrgnYxIrtRg0i6QWOdch/nnAmxza51Dc67gEosXlp4MvOdGuqTCQ+WKEKpa6sa3VLEYoShFCCEkp7S1tUUzp7777jt55ZVXxnUPDwwMyD777CPLly/Xv3faaSc5+uijx/U1CSGEkEKRTjZPItDGHmVX7fUOnWiT8gWCExhLMIE7BzlH8crPIL4g22nRCpeKMejkh9BuiJnpdmrE/TH2xgKZTSiHK1YgwEE0W9nvixt2nox4nfe63T69vr2huijFuPGGohQhhJCcc8QRR0SXZ8+ePW57GL8sHX/88fLOO+/o32uuuaY8+OCDdEkRQggpW+A2ySaU2nBl1DutecnrIYUFIgeEpJElZ7GgXA6d52LHFcSjzr5IiR7EFgR9T22p0TK9TMvLbCgTHKPEDWIrAtMNIa1YaalzaLYbXF2xYef+FHKlsI14Dxv0DwSkzxOQCVquWHmCFKAoRQghJOfst99+MmHCBF1+7LHHZPHixeOyl6+77jr529/+pstOp1Mef/xxaWlpGZfXIoQQQsqhfA9ulyqpkqZx7mhGigeIUhBRxhJMjLBzdNJb0uWWJV0evR4leggBr7Fbs3bxwJE1lqCK7CubtThL90aKeI01Ng14N2IqrEPCXrL8rlinFFxhK/u96pBK13VWTlCUIoQQknNsNps6mEAoFJJbbrkl56/x/PPPy5lnnhn9+5577pFNNtkk569DCCFREEy77rqRS5EF8JLKIZvyPZRwwZnR1uAo+ok/yR0QnCzmKnF7E5fwYTR83+2VlS6flqihRA8B5rkUS+AQgoiTaPx6A8GiLt2LxQh2RzabAdY9Wa6UkSmljsUejzTV2lPO5CpX+GlKCCFkXIAoZYSN33bbbeLzDa+9z4Z58+ZpoPrgUMjk+eefL/vvv3/Onp8QQuKCc9qhh0YubKZACgRcFmNN7BOBNvOdvQPSXGuvaFdGJbulEFSeCAhCEKYanTZprLGPSykZhFDNlUpQwgeXEcrgSgFsC8r4etx+CQ69F7XT4Rjlibgf3Gp4D+N+8Fg1JOlaWAlQlCKEEDIuTJ48Wfbdd19d7ujokEceeSTr54QI9Yc//EF+/vOfS09Pj1635557yiWXXJL1cxNCCCGlMhm2ZFDC1+fxi9VilnpOgitWlEIGkiGgxILSPlShrd7i1PLOsYSVbIFLyBcn7ByB6hBaS8UpZYhQcDmhBC/yd6QEEgJwPLB9eO/iPYx9jpJIQlGKEELIOHLyySdHl2+66aasnqu7u1v23ntvufDCC6P1+7vvvrvcd999YmIZDSGEkAoikxI+CA01FV4mVMlADIGIEs8thU6McOzUOCxaToaysnjiVa5KCf2BwbjjU3OZSuw7XUudXYPgITJhH0dcUPFL+CAk24bypJDdVellewZZHfErrrhCVb7TTjstep3X65WTTjpJg2Zra2s17NZo022wcOFC2WOPPTSUtr29Xc466ywJBseuvSSEEFJ6bLvtttGcp7feeivaJS9d3n//ffnhD38oTz31lP6Nz55LL71UnnzySamvr8/pOhNCSEL8fpHLLotcsExIgcDEF93RUgU/5sDBUSqlUWR8qK0e3YUP4ghcSoaDDuIUujIu7x1I2kkuE+yW+GO3lEr3YoGIhpJYuKXwPsM2JAo7N/Kk8F6EmQrOKpKFKPX222/LrbfeOipU9vTTT9dJwsMPPywvv/yyLFmyJFq+YQTeQpDy+/3yxhtvaDDt3XffLf/3f//H40EIIWUGxKNYt9Ts2bPTfo4777xTtt56a1mwYIH+jR89nnnmGbngggvokCKE5J9AIHIhpIAglyed8j3DVWV0/SKVCZxyKC0zyvMgoqBcDxlSppjg+7Z6h/6/oi9SlpZL0F0vOBhWISwWrJPDWprOobpqq+4/hJ5rrlQiUWqo8x5cVXBJsdlAhIzOSi6XSw499FC5/fbbpampKXp9b2+v3HHHHXLNNdfIjjvuqL9q33XXXSo+4Rdy8Nxzz8n//vc/uffee2WzzTaT3XbbTX/txkQFQhUhhJDyAp8XjY2Nunz//ffLihUrUnocnLfHHnusHH300dGQ9C222ELee+892XXXXcd1nQkhhJByKt/DJBllU5wEVzY4/ijRcw25pVzeoIZtQ1QZeb+JjdWaQdXjzl2jGgDxBsKML6aED+IYws9L0SkVDT2vj4Seo8shMrPi5Ur5h5xSbh9L97IWpVCeB7fTzjvvPOz6d999VwKBwLDr11tvPZk2bZq8+eab+jf+33jjjWXChAnR+yCwtq+vTz799NNMVocQQkgRg1JtCEsA4hJ+vEgGXFE/+clPZM6cOdHrTjjhBHnllVf0M4UQQgipZDCpx6Q3UaDySOBCsVvpkiIQoGyaK4Wx0+32aelZPLESZWkTGp0qtMDZk/NcqZgSPpSzmUwRsapUQUA7BD/sL5vFJAP+4fsMpZBGThccU3BUkQhp74kHHnhAf6VG+d5Ili1bJjabLfqLuAEEKNxm3CdWkDJuN26LByYxsa3EIWAZXZiMduCkcOAYQN3msSAcRyQRxx9/vLpoca644YYb5MADD5TVV1897n3/9a9/yWGHHabB5qC6ulpuvvlmvc445/AcRfINP+vI0ECQqqGMlTDORVl+D+W4IpkCCcFUJeLzBzT/J9nY8voDGmDN7+vEZq4SU1VYlnW7YVGSaqspOq8eOaezmqukudYmy3vcMqnJqWWjucBiEhVt6occWh5fQIWcUh+fjU6bfL/SpY4vhMWbGquj708V4cJhGfAFVCCuEuzr3Gd2FROpHs+0RKlFixbJqaeeKvPmzROHI1Jnmg8uv/xyufjii0dd39nZqeUdpPCDDaWbOImxAxbhOCLxqKurk1122UVLuJE1uNVWW2nXvI022mhY5iCEq2uvvTbaXW/NNddUt9QGG2wgHR0dPEeRgsHPOqL4/VLrduuiC+ckWyQYmOOKFIK+Pp8EPWapdVjG/H4OCWtZ94CYA9XihpJFKh7vQEB6PAFpq7NLZ6c76eeczxOQ+d3dMqHero6mbEG3um5PQKp8EU2hs9+nTqMqX3/JH5uQNyhLuwL6vvxfV5e01dnUGebxh6RvICD9fVVSA9HK75Jyp7+/P/eiFMrzMCnYfPPNh00iUE6BVt/PPvus5kL19PQMc0uh+97EiRN1Gf//97//Hfa8Rnc+4z4jmTVrlpxxxhnDnFJTp06VtrY2dl0qAnACg+UTx4OiFOE4Iom47bbbNAvqiy++0M+SffbZRx555BEVq5Azdfjhh+uPHgYzZ87UXMKGhgaeo0jB4WcdUfx+qaqp0UVne3tORCl+hyKZYnJ41S3VXOcYc2wNBEIy0eqTSS213NlEaYEA5Qlo6V4q56N2zNl7PNoxrq2xOuNsMoSboywQ/w92uqSltU7MpioZqOrXUkEIU6UO9tWSLrdmR01oN8vKfp/UNVaLDSW0NUHxBgZlakuNWEq4VDFVUjUypSVK7bTTTvLxxx8Pu+6oo47S3KhzzjlHhSKr1SovvPCC7Lfffnr7559/LgsXLtTOSQD/X3bZZTohaceHuYhOQtDSG7+Ex8Nut+tlJHizUAQpDnBi4vEgHEdkLFCu9/rrr8vee++t+YJomrHnnntq91W4ofBZAXAugUP2rLPOylkgK89RhOOI5ASzGRbOyHkFyyMmbpnA8xPJFJQFIesn0XzIGFuBUFAcNivnTSQKxkVrvSWt81F7Y40s7Xarw6oljhCaDATzL1rpkaYau5aSWi1mzbVSL1+VSTOWyiWIf2JTjQpTdqtF2hqc0tnn1QB0iHp439pKtMtguqSq1VjSLb+ILbUANTU12p7buB5htnA1NTc3q9B0yimnqBCFUg2AX8khPiEb5Morr9QcKbT1Rnh6POGJEEJI+dDa2irPP/+8duR7/PHHJRgMqihlgB8rkF24ww47FHQ9CSEkLlaryJFHcueQogBODL8neWYLupzV2CtjEkzGDzia4GZavNKt2VIjO/Ylw+1FlpJZ+gf8Gvpts5rFF4Q7KxJ8Xi6CFIALCvtqabdH2uodKuJ19g0IJLj66uwctuVIzj1jyALBL99wSm233XZakvfYY49FbzebzTJ37lz9H2LVr3/9ay3ZuOSSS3K9KoQQQoq0Gx/K9k488cRh1+MzAY00KEgRQgghyUGnMnTzwgQ/EcgHQmczBC8TkosxN6GxWlb2e7WjYzr0DwSkwWmTSc014vYFVZzy+oPi9ZdnZ0gIbW0NEKO8KiBPbnZKVVjESYF4FFlL5i+99NKousHZs2frZawSjqeffjrblyaEEFKi4IcJZBFOnz5dbrnlFs2Pwo8T6OBKCCGEkNTcGKaqKhWmEnVFQ8mUISYQkgtQZocsKmRMrdacWjYShFGU6kGQwZid3OSUBcv7ZGmPR5prHdKaxyZq+aTGbpVgbVj3VWNNpGQxVx0Mywn6OAkhhBQE2LTR0RUXQggpCfx+keuuiyyfdlrWQeeE5KSEL5hYlIq4UMqrNIoUnnqnTXzBkCzvGZBJzU4VmsbC5Q1EBSkAIWtqW518uGCFBIKRMVquwB0WCA6quwzLZDSUzAkhhBBCCEkVjydyIaQIgAMKE95EQDgox9IoUnha6xyaB7Wizzvm/VBCijypWsfwDCp02mtrqFanFPKqypmWOrsKUunmcFUKPEMRQgghhBBCSAlis6C73hiiVKC8XSikcMB9h3wp5EL1uH0J74fsKaSeVcfJNYMwZTaXtyBl7CuEnbN0Lz4s3yOEEEIIIYSQEi3fQ2lUPAYHwxIID+rEn5DxwGxa1WUOYxEZSvECzuGSildCCsHUHxgUqRYN7Hd7IwHoyElDiSAuyUoDSelDUYoQQgghhBBCSrh8DyVSIyf9vuCgWKtNKhwQMl5AWGqtd0hnr1dsLeZhofoQmjy+oExqcsZ9LJxDvR6flgBCXLWYq6Su2qb/97j9emmsQdmbrexL/CoZilKEEEIIIYQQUoIYAkBwMCxW82hRqokuKZIH4IRCqSi6zE1urom6myBIQUxKVELqsJmlyxUW/JvY5Bzm6oPrasAflG6XT8WphiHnFMWp8oOyOSGEEEIIIYSUIHBHRTrwhUbdhq58drafJ3miudauYlRs8LkrTsD5SFF19bY6aauvjltmWm2zqMil2VWBkCxa4ZIul1dCg4lz1EjpQVGKEEIIIYSQVMCv/5MnRy7MOSFF3IEP5XwqStEpRQoQfN7n8UtoMCwDvqDU5qDjHMQplABObKzWDKpFK9yysp/iVLnA8j1CCCGEEEJSwWoVOe447itSVFjjdOBD6Z7RnY+QfIH8svZGpyzr9qizyWYdnjGVLQ6bRSbaLPrc6PgHcaqu2qqlfZYcvg7JLxSlCCGEEEIIIaREQVg0Jui4INcHglQgEJRqmzluxzNCxhOU4aGUb0W/V1rrHOP2GhMbnTreu1WccmkYOkLRKU6VHhSlCCGEEEIIIaREMUr0MEHHMsKgLaYqWVm1KtuHkHyCMQhBtMYxvnKDfUicQqYaAtEhTtU4Is4plq6WDhSlCCGEEEIISYVAQGT27MjySSdFyvkIKTAoj5rSUjvsukEGQZMCg7K6fLoFJwyJU32egCzt9mjpKsSxGruFjsEih6IUIYQQQgghqRAOi/T0rFomhBBSNECcaq03S1OtXfoH/NLl8klXv1cmNdfkNNuK5BYeGUIIIYQQQgghhJQFZlOVNNbYZWpLjZjNJvH6Q4VeJTIGFKUIIYQQQgghhBBSViDXCmV8gRBFqWKGohQhhBBCCCGEEELKDpTtBYKDhV4NMgYUpQghhBBCCCGEEFKWOVN+ilJFDUUpQgghhBBCCCGElB1Wi0mCoUEJF7g5RTGsQ7FCUYoQQgghhJBUqKoSaWuLXLBMCCGkqLGYIufqQKiwJXxLutzi9gULug7FiqXQK0AIIYQQQkhJYLWKnHRSodeCEEJIGmHncEtBlEIpXyHwB0MSHAyLxxeUWoe1IOtQzNApRQghhBBCCCGEkLKk0GHnXn9IzKYqFaVYwjcailKEEEIIIYQQQggpS+CQKmT5njcQkvpqmy77GLo+CopShBBCCCGEpEIgIDJ7duSCZUIIIUUPyvcK2YFvwB+UaptZnHaLDDBXahTMlCKEEEIIISQV0Dmps3PVMiGEkKKnkOV7yJPCx4XdapbqUFj6PH5pqrUXZF2KFTqlCCGEEEIIIYQQUrZOqcFwWEKD+RemBvwhcVjNGrjutJvFFwwVZD2KGYpShBBCCCGEEEIIKUtMVVViMVUVxC2F0j2HLdL1z2wyid1iFo8vlPf1KGYoShFCCCGEEEIIIaRssVrM4s9z2Dk67aHzXrVtVWqS5kr5g3ldj2KHohQhhBBCCCGEEELKlkLkShnh6jbLKtml2m4Rjy+oghWJQFGKEEIIIYQQQgghZQuEoXyLUkbpHvKkDOxDApWvgN0Aiw123yOEEEIIISQVMLFobFy1TAghpGTCzv2e/ApBWrpnHy65RALP4ZYKaAA6oShFCCGEEEJIalitIqedxr1FCCElWL4XDA1q2Vysc2lc86QCIWmus4+6DRlTfR6/SO24r0ZJwPI9QgghhBBCCCGElC0Ws0m78AXyFHaO8jxoXzbLaDeU024WXzAkoUGW8AGKUoQQQgghhBBCCClr8hl27kWeVILyPLPJJHarWTy+UF7WpdihKEUIIYQQQkgqBAIit90WuWCZEEJISeVK5cspNYA8KVviCG+nzaJB6ISiFCGEEEIIIamBFt5LlkQubOdNCCEl14HPn4ZTKjQYzjxPaqjzXiIQgO7xBfW+lQ677xFCCCGEEEIIIaTsy/fc3vjuJH8wJL7A4ND/IRWvBsNhzaGymHExicVkWrVsNonVXKWleCNBwLnZVBU3T8rAbjHpfZZ0e6S1zqHlfJUKRSlCCCGEEEIIIYRUZPme2xeQjp4BsVnNYreYpa7apq4qCE8II8djQqGw/g/Byu0Laic/OKnQx88QqVSwMsGNFRLHGKV7AB0AV2upkR63T5Z2e6Su2ipNtXYVwSqNtDKlbr75Ztlkk02kvr5eL1tvvbX861//it6+bNkyOeyww2TixIlSU1Mjm2++uTz66KPDnqOrq0sOPfRQfXxjY6McffTR4nK5crdFhBBCCCGEEEIIISOcUnA/QVAygLC0ss8rLfUOWa25RlrrHSoQwblkuJ1q7Fapd9qkpc4hExqder/V2+pkjfY6FZZwfY3DovdXAWswLLUOa9J9DwGqudYhk5udKnZ9v8Ilbm/l5RWmJUpNmTJFrrjiCnn33XflnXfekR133FFmzpwpn376qd5++OGHy+effy7//Oc/5eOPP5Z9991XDjzwQHn//fejzwFBCvefN2+ezJ07V1555RU57rjjcr9lhBBCCCGEEEIIIUPuJDiaYt1S3S6fWC1mqa+2pb2PICpBtHLaLfp4CEztDdUyublGr0sVm8Wsj2mqdUi325dxllVFiFJ77bWX7L777rLuuuvK9OnT5bLLLpPa2lp566239PY33nhDTjnlFNliiy1krbXWkgsuuEDdUBCxwPz58+WZZ56ROXPmyJZbbinbbrut3HjjjfLAAw/IEgRGEkIIIYQQQgghhIwDNohSQ2HnyH5yeQPSUmcvin1dV22VKS216riqJDLOlAqFQvLwww+L2+3WMj6wzTbbyIMPPih77LGHilEPPfSQeL1e2X777fX2N998U6//0Y9+FH2enXfeWUwmk/znP/+RffbZJ+5r+Xw+vRj09fXp/4ODg3ohhQXHAF0DeCwIxxEpRniOIhxHJIcnFJHq6lXLWX4P5fmJjBccW4RjJj4Wk2hnvBq7WTp63FJfbRWLqYpz2XEgVX0gbVEKZXkQoSA2wSX1j3/8QzbYYAO9DSLUQQcdJC0tLWKxWMTpdOrt66yzTjRzqr29ffgKWCzS3NystyXi8ssvl4svvnjU9Z2dnboepPCDrbe3V4UpCIyEcByRYoLnKMJxRHLKEUdE/u/pyfqpeH4i4wXHFuGYiY/LGxSPPyTdXSYZCITEWm+XDndlOZPyRX9///iIUjNmzJAPPvhARYhHHnlEjjjiCHn55ZdVmLrwwgulp6dHnn/+eWltbZXHH39cM6VeffVV2XjjjSVTZs2aJWecccYwp9TUqVOlra1NA9NJ4T/0UJ+L40FRinAckWKD5yjCcUSKFZ6fCMcWKRYq5XxU7w/K8t4BCYdFpjU5NdCcjA8Oh2N8RCmbzRZ1Pv3whz+Ut99+W66//no5++yz5aabbpJPPvlENtxwQ7190003VUFq9uzZcsstt2hXvo6OjmHPFwwGtSMfbkuE3W7Xy0jwZinnN0wpgRMYjwfhOCLFCs9RhOOIFCs8PxGOLVIsVML5yG6zSFiqpKHGJtX25B3ySOakOo5MuVBUkffk8XjivrDZbI7WEqLsD04qI/gcvPjii3o7gs8JIYQQQggpWgIBkbvvjlywTAghpKQwm0zSWu+QptriCDcnaTqlUEa32267ybRp07Q+8O9//7u89NJL8uyzz8p6662nDqrjjz9err76as2VQvnevHnzZO7cufr49ddfX37xi1/Iscceq86pQCAgJ598shx88MEyefJkHg9CCCGEEFK8oN7j229XLRNCCCk56qtthV4FkqkohdK7ww8/XJYuXSoNDQ2yySabqCC1yy676O1PP/20nHvuubLXXnuJy+VSkeqee+6R3XffPfoc9913nwpRO+20k7qq9ttvP7nhhhvSWQ1CCCGEEEIIIYQQUkmi1B133DHm7euuu648+uijY94HnfbgsCKEEEIIIYQQQgghlUv5JpgRQgghhBBCCCGEkKKFohQhhBBCCCGEEEIIyTsUpQghhBBCCCGEEEJIcWdKEUIIIYQQUtFYrYVeA0IIIaRsoChFCCGEEEJIKthsIuefz31FCCGE5AiW7xFCCCGEEEIIIYSQvENRihBCCCGEEEIIIYTkHZbvEUIIIYQQkgrBoMiDD0aWDzpIxMKv0oQQQkg28JOUEEIIIYSQVBgcFPnyy1XLhBBCCMkKlu8RQgghhBBCCCGEkLxDUYoQQgghhBBCCCGE5B2KUoQQQgghhBBCCCEk71CUIoQQQgghhBBCCCF5h6IUIYQQQgghhBBCCMk7Jdl9LxwO6/99fX2FXhWizWcGpb+/XxwOh5hM1DlJZnAckfGCY4twHJGc4feL+HyRZXwPtdmyejqen8h4wbFFOGZIoTH0GkO/SURVONk9ipDvv/9epk6dWujVIIQQQgghhBBCCCEJWLRokUyZMqW8RCko/0uWLJG6ujqpqqoq9OpUPFBAIRJisNXX11f8/iCZwXFExguOLcJxRIoVnp8IxxYpFng+IrkGUhMqqiZPnjxmRVVJlu9hg8ZS2khhgCBFUYpwHJFihecownFEihWenwjHFikWeD4iuaShoSHpfRgARAghhBBCCCGEEELyDkUpQgghhBBCCCGEEJJ3KEqRrLHb7XLRRRfp/4RwHJFig+cownFEihWenwjHFikWeD4ihaIkg84JIYQQQgghhBBCSGlDpxQhhBBCCCGEEEIIyTsUpQghhBBCCCGEEEJI3qEoRQghhBBCCCGEEELyDkUpQgghhBBCCCGEEJJ3KEqVMZdffrn8+Mc/lrq6Omlvb5df/vKX8vnnnw+7j9frlZNOOklaWlqktrZW9ttvP1m+fHn09g8//FAOOeQQmTp1qlRXV8v6668v119//bDneO211+QnP/mJPgfus95668m1116bdP2Qsf9///d/MmnSJH3czjvvLF9++eWw+7z33nuyyy67SGNjoz7/cccdJy6XK+t9Q8pjDD322GOy66676uOqqqrkgw8+GHWfZOtHCkM5jK3bbrtNtt9+e6mvr9f79PT0ZLVPSOWNo66uLjnllFNkxowZ+rzTpk2T3/3ud9Lb28vhUCFjK5bXX39dLBaLbLbZZjn5DnXZZZfJNttsI06nU79HkeKg1MfWt99+K0cffbSsueaaevvaa6+tXbj9fn/G+4SU95gBe++9t37GORwOvd9hhx0mS5Ys4aEnCkWpMubll1/Wk9Nbb70l8+bNk0AgoF+O3W539D6nn366PPnkk/Lwww/r/XFy2HfffaO3v/vuu3ryu/fee+XTTz+V888/X2bNmiU33XRT9D41NTVy8sknyyuvvCLz58+XCy64QC+YsI3FlVdeKTfccIPccsst8p///Eef5+c//7meVAHWBSe1ddZZR29/5plndB2OPPLIcdlfpPTGENZj2223lT/96U8J75Ns/UhhKIex5fF45Be/+IWcd955We8PUpnjCOuCy9VXXy2ffPKJ3H333fpZhwkfqYyxZQBR+/DDD5eddtoppfVL9h0KQCQ44IAD5IQTTsh6f5DcUepj67PPPpPBwUG59dZb9bUh0OO+/CwcP0p9zIAddthBHnroIRXTHn30Ufn6669l//33z3rfkDIhTCqGjo6OMA75yy+/rH/39PSErVZr+OGHH47eZ/78+XqfN998M+HznHjiieEddthhzNfaZ599wr/+9a8T3j44OBieOHFi+Kqrropeh/Wx2+3h+++/X/++9dZbw+3t7eFQKBS9z0cffaTr9+WXX6a41aRcx1AsCxYs0Nd8//33h12f6fqR/FNqYyuWf//733qf7u7ulJ6TjB+lPI4MHnroobDNZgsHAoGUnpuUx9g66KCDwhdccEH4oosuCm+66aZjrksq36Fiueuuu8INDQ0pbyvJL6U8tgyuvPLK8Jprrpl0W0luKIcx88QTT4SrqqrCfr8/6faS8odOqQrCKAdobm6OKuZQ2uFGMkBJAqyVb7755pjPYzxHPN5//31544035Gc/+1nC+yxYsECWLVs27LUbGhpkyy23jL62z+cTm80mJtOqYQpLqFFKQSp7DKVCputH8k+pjS1SnJTDOMJroyQUZROkMsbWXXfdJd98842WQKVCKt+hSOlQDmMr2TmT5JZSHzMoXb/vvvu0vNhqtab0OqS84TeeCgE229NOO00zMTbaaCO9DicQiD4jcwYmTJigt8UDX8IffPBBeeqpp0bdNmXKFOns7JRgMCi///3v5Zhjjkm4Psbz47USvfaOO+4oZ5xxhlx11VVy6qmnqkX13HPP1duWLl2a9j4g5TWGUiGT9SP5pxTHFik+ymEcrVixQi699FLNTySVMbaQu4LvNq+++mrKQmQq36FIaVAOY+urr76SG2+8UcuQyfhTymPmnHPO0XJBxB9stdVWMnfu3BS3mpQ7dEpVCKhDRl7FAw88kPFz4PEzZ85U5Rx1zCPBCeydd97ReuLrrrtO7r//fr0eSjgC94wL7pcKG264odxzzz3y5z//WUM6J06cqKGKOMnFuqdIfijFMURKA44twnEk0tfXJ3vssYdssMEGKniR8j9HhUIh+dWvfiUXX3yxTJ8+Pe7j+PlX3pT62Fq8eLFmKyK77Nhjj814G0hljJmzzjpLncbPPfecmM1mza1CSDohzJSqAE466aTwlClTwt98882w61944YW4OSjTpk0LX3PNNcOu+/TTTzXf6bzzzkvpNS+99NLw9OnTdbmvr08zoIyLx+MJf/3113HzNbbbbrvw7373u1HPt2zZsnB/f3/Y5XKFTSaTZm6Qyh5DqeS1pLN+pDCU6tiKhZlShafUxxEev/XWW4d32mmn8MDAQEqvT0p/bOGxeA6z2Ry9IGPFuA6vkYvvUMyUKk5KfWwtXrw4vO6664YPO+ywYfmvZPwo9TETy6JFi/Rxb7zxRhZ7hJQLFKXKGATP4eQ1efLk8BdffDHqdiMU75FHHole99lnn40Kxfvkk0/05HXWWWel/NoXX3xxePXVV08ainf11VdHr+vt7U0ainfHHXeEnU4nA4XzRDGPoXSCzpOtH8k/pT62YqEoVTjKYRzhs2+rrbYK/+xnPwu73e6UX5+U/tjCRP7jjz8edjnhhBPCM2bM0GX8EJeL71AUpYqLchhb33//vQpSBx98cDgYDGa1P0hljJmRfPfdd7p++A5FCEWpMgYnEnRbeemll8JLly6NXmJ/wf3tb3+rKvqLL74Yfuedd/SXWlwMcBJqa2vTDkOxz4GuDwY33XRT+J///KeeJHGZM2dOuK6uLnz++eePuX5XXHFFuLGxUbsvoKvezJkztXNH7K/EN954Y/jdd98Nf/755/o61dXV4euvvz7n+4qU5hhauXKlTvKeeuop/WB74IEH9G88f6rrRwpDOYwtLOO622+/Xe/zyiuv6N94LMkPpT6O8MV9yy23DG+88cbhr776atjrc6JXGWNrJKl0u0r1OxQmfRhvEFBra2t1GRc4z0nhKPWxBUFqnXXWUWcnlmNfn4wPpT5m3nrrLZ3T4fzz7bffqutqm222Ca+99tphr9eb9f4hpQ9FqTIGX4DjXfCLmQFOFmgH2tTUpA4ktLiO/VDBySjec8T+OnzDDTeEN9xwQ318fX19+Ac/+EH4L3/5S1IrL5T1Cy+8MDxhwgRV0/HhBvEpFliCm5ubtT32JptsEv7rX/+a031ESnsMYT3iPTdeM9X1I4WhHMZWoteP3QYyvpT6ODJcdvEucFeR8h9bmU4CU/kOdcQRR8R9fToTCkupj61E5zVcyPhQ6mMGQtUOO+ygczrcvsYaa6iIBlGTEFA1NNAJIYQQQgghhBBCCMkbbGFGCCGEEEIIIYQQQvIORSlCCCGEEEIIIYQQkncoShFCCCGEEEIIIYSQvENRihBCCCGEEEIIIYTkHYpShBBCCCGEEEIIISTvUJQihBBCCCGEEEIIIXmHohQhhBBCCCGEEEIIyTsUpQghhBBCCCGEEEJI3qEoRQghhBBCCCGEEELyDkUpQgghhBBCCCGEEJJ3KEoRQgghhBBCCCGEkLxDUYoQQgghhBBCCCGESL75/0SKb4xfUKGcAAAAAElFTkSuQmCC", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 1. Generate N forward paths anchored at the last bar of `real`.\n", "FORWARD_HORIZON = 60 # bars to project forward\n", "ANCHOR_LOOKBACK = 200 # last N bars = today's conditioning context\n", "\n", "forward_paths = sf.generate(\n", " fit.model_id,\n", " n_paths=200,\n", " horizon=FORWARD_HORIZON,\n", " anchor_data=real.iloc[-ANCHOR_LOOKBACK:], # the tail of `real` = today\n", " data_types=real.attrs['data_types'], # same per-column annotation as fit\n", " seed=42,\n", ")\n", "forward_dfs = forward_paths.as_dataframes()\n", "# Attach a business-day DatetimeIndex continuing from real.index[-1].\n", "forward_dates = pd.bdate_range(start=real.index[-1] + pd.Timedelta(days=1), periods=FORWARD_HORIZON)\n", "for df in forward_dfs:\n", " df.index = forward_dates[:len(df)]\n", "print(f'generated {len(forward_dfs)} forward paths, each {forward_dfs[0].shape}')\n", "print(f'forward index runs {forward_dfs[0].index[0].date()} -> {forward_dfs[0].index[-1].date()}')\n", "print(f'real ends on {real.index[-1].date()}; forward starts the next bar (continuation)')\n", "\n", "# 2. Run YOUR backtest on each forward path. Same f(prices) -> dict.\n", "forward_results = [my_backtest(df) for df in forward_dfs]\n", "forward_sharpes = np.array([r['sharpe'] for r in forward_results])\n", "\n", "# 3. The deployment-forecast distribution \u2014 pure numpy, you own the analytics.\n", "print()\n", "print(f'expected sharpe over the next {FORWARD_HORIZON} bars:')\n", "print(f' median : {np.median(forward_sharpes):+.3f}')\n", "print(f' 90% CI : [{np.percentile(forward_sharpes, 5):+.3f}, '\n", " f'{np.percentile(forward_sharpes, 95):+.3f}]')\n", "print(f' pct above 0 : {(forward_sharpes > 0).mean() * 100:.0f}%')\n", "\n", "# 4. Plot the forward equity-curve fan against the realized recent history.\n", "fig, ax = plt.subplots(figsize=(12, 5))\n", "recent = real[TICKER].iloc[-90:] # last 90 bars of real to give context\n", "ax.plot(recent.index, recent.values, 'k', linewidth=2.0, label=f'{TICKER} (realized)')\n", "for df in forward_dfs[:30]:\n", " ax.plot(df.index, df[TICKER], color='steelblue', alpha=0.18, linewidth=0.8)\n", "ax.axvline(real.index[-1], color='red', linestyle='--', alpha=0.5, label='today')\n", "ax.set_title(f'{TICKER}: realized + 30 forward synthetic alternatives')\n", "ax.legend(loc='upper left')\n", "ax.grid(alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "8166a04c", "metadata": {}, "source": [ "## Step 9 \u2014 How much to trust the forward forecast: sf.predictive_rank_score\n", "\n", "The forward forecast above gives you a *distribution* \u2014 useful for sizing risk, deciding capital allocation, knowing what range of P&L outcomes is plausible. But it doesn't tell you whether the *ranking* of strategies on synth data is preserved on real data.\n", "\n", "There's a two-axis quality definition for synthetic financial paths:\n", "\n", "1. **Distributional fidelity** \u2014 does the synth match the structural fingerprint (vol clustering, fat tails, leverage effect, cross-correlation)? `sf.validate` answers this.\n", "2. **Predictive-rank validity** \u2014 does the ranking of strategies on synth match the ranking on real? `sf.predictive_rank_score` answers this.\n", "\n", "A generator can pass (1) and still fail (2) \u2014 produce paths whose distribution looks fine while the strategy-ranking on those paths is uncorrelated with (or worse, inverted relative to) the real ranking. That failure mode is silent under distributional checks alone, and a customer who trusts it deploys the wrong strategies.\n", "\n", "`sf.predictive_rank_score` runs the calibration on **your own model + your own strategy family**, so you can tell whether to trust the forward forecast on your universe before deploying capital on it. The verdict bands:\n", "\n", "| Spearman \u03c1 | Verdict | What to do |\n", "|---|---|---|\n", "| \u03c1 \u2265 +0.50 | calibrated | Trust the forward ranking \u2014 picking the highest-Sharpe synth strategy matches picking the highest-Sharpe real strategy |\n", "| 0 < \u03c1 < +0.50 | weak | Treat synth ranking as a soft prior, not a deployment trigger |\n", "| \u03c1 \u2264 0 | uncalibrated / inverted | Do NOT use synth ranking \u2014 at \u03c1 < 0 the model is actively misranking |\n", "\n", "Below we use a **24-variant family** (6 fast \u00d7 4 slow SMA crossovers) \u2014 the empirical floor at which Spearman \u03c1 tightens enough for a deployable verdict. Smaller demo families produce wide bootstrap CIs and the metric will flag itself as `uncalibrated`; production audits use the same 20+ floor." ] }, { "cell_type": "code", "execution_count": 14, "id": "085e6e63", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:21.441951Z", "iopub.status.busy": "2026-06-01T19:21:21.441784Z", "iopub.status.idle": "2026-06-01T19:21:44.302791Z", "shell.execute_reply": "2026-06-01T19:21:44.302383Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: estimated cost 13 credits (use sf.estimate_cost(...) to preview before charging).\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "sablier-flow: actual cost 0 credits (remaining balance: 10000).\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Weakly calibrated: Spearman \u03c1 = +0.43 (95% CI [+0.07, +0.70]) across 24 strategies. The synth ranking signal is present but not unambiguous \u2014 treat as a tiebreaker, not a deploy gate. Magnitude bias (mean |value_real - value_synth|) = 0.35 \u2014 the rank can be right while the absolute number is biased, so do not read synth medians as point forecasts.\n", "\n", "verdict : 'weakly_calibrated'\n", "spearman rho : +0.434\n", "95% bootstrap CI : [+0.069, +0.702]\n", "mean |delta SR| : 0.346\n", "n_strategies : 24\n" ] } ], "source": [ "# Define a small strategy family \u2014 keep it cheap for the demo.\n", "# Production audits should use ~24 variants for a tight bootstrap CI on rho.\n", "# 6 fast x 4 slow = 24 distinct SMA-crossover variants. The Spearman \u03c1 \n", "# bootstrap CI tightens at larger N; >= 20 is the recommended floor for a \n", "# stable rank correlation. The earlier preview ran a 6-variant cheap demo \n", "# and the cell rendered 'uncalibrated' on its own bundled data \u2014 the demo \n", "# was too small, not the metric.\n", "STRATEGIES = {\n", " f'sma_{fast}_{slow}': (\n", " lambda df, f=fast, s=slow: _sma_crossover_backtest(df, f, s)\n", " )\n", " for fast in (3, 5, 7, 10, 15, 20)\n", " for slow in (20, 30, 50, 100)\n", "}\n", "\n", "def _sma_crossover_backtest(df: pd.DataFrame, fast: int, slow: int) -> dict:\n", " \"\"\"Same shape as my_backtest above, parameterised by SMA lookbacks.\"\"\"\n", " px = df[TICKER]\n", " fast_ma = px.rolling(fast).mean()\n", " slow_ma = px.rolling(slow).mean()\n", " pos = (fast_ma > slow_ma).shift(1, fill_value=False).astype(int)\n", " rets = px.pct_change().fillna(0.0) * pos\n", " sharpe = float(rets.mean() / rets.std() * np.sqrt(252)) if rets.std() > 0 else 0.0\n", " return {'sharpe': sharpe}\n", "\n", "# A realistic OOS reference: align with the slice sf.fit held out at train\n", "# time so the calibration runs on truly unseen data. A naive last-N-row\n", "# slice (e.g. the last trading year) would overlap the held-out OOS\n", "# slice (the server keeps the last 20% minus embargo) and bias the\n", "# rank-correlation read.\n", "real_oos = real.loc[fit.holdout_start_date:fit.holdout_end_date]\n", "anchor_end_pos = real.index.get_indexer([real_oos.index[0]])[0]\n", "ref_anchor = real.iloc[anchor_end_pos - 200:anchor_end_pos] # 200 bars before holdout start\n", "\n", "# Generate forward paths anchored at the START of real_oos so the synth and the real run on the same calendar.\n", "calibration_paths = sf.generate(\n", " fit.model_id,\n", " n_paths=100,\n", " horizon=len(real_oos),\n", " anchor_data=ref_anchor,\n", " data_types=real.attrs['data_types'], # required per-column annotation\n", " seed=42,\n", ")\n", "calibration_dfs = calibration_paths.as_dataframes()\n", "\n", "# Real Sharpe per strategy on the OOS year + mean synth-forward Sharpe per strategy.\n", "real_sharpes = {\n", " name: bt(real_oos)['sharpe'] for name, bt in STRATEGIES.items()\n", "}\n", "synth_sharpes = {\n", " name: float(np.mean([bt(df)['sharpe'] for df in calibration_dfs]))\n", " for name, bt in STRATEGIES.items()\n", "}\n", "\n", "# Pure analytic \u2014 no path generation, no strategy execution by Sablier.\n", "calibration = sf.predictive_rank_score(real_sharpes, synth_sharpes)\n", "print(calibration.summary())\n", "print()\n", "print(f'verdict : {calibration.verdict!r}')\n", "print(f'spearman rho : {calibration.spearman_rho:+.3f}')\n", "print(f'95% bootstrap CI : [{calibration.ci_95[0]:+.3f}, {calibration.ci_95[1]:+.3f}]')\n", "print(f'mean |delta SR| : {calibration.mean_abs_metric_gap:.3f}')\n", "print(f'n_strategies : {calibration.n_strategies}')\n", "\n", "# UI gate: only trust the forward forecast if the verdict is acceptable.\n", "if not calibration.acceptable:\n", " print()\n", " print('WARNING: predictive_rank_score is uncalibrated/inverted on this universe.')\n", " print('Do NOT use forward-forecast Sharpe ranking to pick strategies for deployment.')" ] }, { "cell_type": "markdown", "id": "a9af68b5", "metadata": {}, "source": [ "## Bonus \u2014 Deflated Sharpe Ratio under two nulls\n", "\n", "The robustness percentile is intuitive; the DSR is the academic-grade significance test from Bailey & L\u00f3pez de Prado (2014). Sablier returns it under two nulls side-by-side:\n", "\n", "- **`realistic`** \u2014 empirical CDF of Sharpe in the synthetic distribution (regime-aware)\n", "- **`analytical`** \u2014 Bailey-LdP IID-Gaussian null (no volatility clustering, no autocorr, no fat tails)\n", "\n", "When the analytical null says \"significant\" but the realistic null says \"not significant,\" your Sharpe is plausibly explained by the regime your model learned \u2014 i.e., you're overfit to the regime, not to noise." ] }, { "cell_type": "code", "execution_count": 15, "id": "f85a615f", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:44.303938Z", "iopub.status.busy": "2026-06-01T19:21:44.303867Z", "iopub.status.idle": "2026-06-01T19:21:44.306112Z", "shell.execute_reply": "2026-06-01T19:21:44.305737Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DSR under realistic null (Sablier): 0.960\n", "DSR under analytical null (Bailey-LdP IID): 1.000\n", "\n", "Sharpe threshold for DSR=0.95 (realistic): +1.489\n", "Sharpe threshold for DSR=0.95 (analytical): +0.155\n" ] } ], "source": [ "dsr = verdict.deflated_sharpe(n_trials=1)\n", "print(f'DSR under realistic null (Sablier): {dsr.realistic:.3f}')\n", "print(f'DSR under analytical null (Bailey-LdP IID): {dsr.analytical:.3f}')\n", "print()\n", "print(f'Sharpe threshold for DSR=0.95 (realistic): {dsr.threshold_sr_realistic:+.3f}')\n", "print(f'Sharpe threshold for DSR=0.95 (analytical): {dsr.threshold_sr_analytical:+.3f}')" ] }, { "cell_type": "markdown", "id": "33104be9", "metadata": {}, "source": [ "## Shareable report\n", "\n", "`to_html()` writes a single-file, self-contained HTML report. Renders identically in email previews, GitHub READMEs, Notion, Confluence." ] }, { "cell_type": "code", "execution_count": 16, "id": "1e577426", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:44.307035Z", "iopub.status.busy": "2026-06-01T19:21:44.306978Z", "iopub.status.idle": "2026-06-01T19:21:44.312377Z", "shell.execute_reply": "2026-06-01T19:21:44.312032Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "wrote audit.html\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "SPY 10/30 SMA crossover \u2014 audit \u2014 sablier-flow\n", "\n", "\n", "\n", "

SPY 10/30 SMA crossover \u2014 audit

\n", "
\n", " Primary metric: sharpe ·\n", " 100 synthetic paths\n", "
\n", "\n", "
\n", " HIGHLY OVERFIT\n", "
96.00%
\n", "
\n", " Fraction of synthetic backtests the real strategy exceeded on\n", " sharpe.\n", " 0.50 = consistent with the data-generating process; >0.85 = overfit signal.\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " min -1.73\n", " max 2.63\n", " real: 1.57\n", "\n", "
\n", "\n", "
\n", "

Distribution on primary metric

\n", "
\n", "
Real backtest\n", " +1.5657
\n", "
Synthetic median\n", " +0.0452
\n", "
Synthetic mean\n", " +0.0883
\n", "
Synthetic std\n", " 0.8754
\n", "
95% CI\n", " [-1.2631, +1.4895]
\n", "
Min / max\n", " -1.7263 / +2.6309
\n", "
\n", "
\n", "\n", "

All metrics

MetricMedian5%95%Std
sharpe (primary)0.0452-1.26311.48950.8754
\n", "\n", "

Deflated Sharpe (Bailey-LdP)

Null distributionDSRE[max SR]SR threshold (DSR=0.95)
Sablier realistic (regime-aware)0.960+0.0883+1.4895
Bailey-LdP analytical IID-Gaussian1.000+0.0000+0.1549
Realistic null is the empirical distribution of synthetic-best Sharpes; the analytical null is the closed-form Bailey-LdP IID expression.
\n", "\n", "
Notes
  • Single-strategy overfit verdicts assume the strategy was selected from a search. If you tested ONE fixed strategy with no parameter tuning, this label conflates skill, luck, and overfit \u2014 read it as 'real outperformed the alt-history distribution', not 'real is overfit'. Use sf.evaluate_family for true overfit detection on a strategy family (CSCV-PBO is luck-safe).
\n", "\n", "
\n", " Generated by sablier-flow.\n", " Methodology: synthetic samples drawn from a generator trained on the\n", " same window as the real backtest; an overfit strategy exploits\n", " realization-specific noise that's by construction not in the learned\n", " distribution.\n", "
\n", "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "verdict.to_html('audit.html', title=f'{TICKER} 10/30 SMA crossover \u2014 audit')\n", "print('wrote audit.html')\n", "from IPython.display import HTML, display\n", "display(HTML(verdict.to_html(title=f'{TICKER} 10/30 SMA crossover \u2014 audit')))" ] }, { "cell_type": "markdown", "id": "45fe245b", "metadata": {}, "source": [ "## Bonus \u2014 Async workflow + cross-process handles\n", "\n", "A full `sf.fit(...)` call blocks the kernel. For long-running notebooks or pipelines that want to kick off a fit and walk away, every sync method has an async sibling that returns a `JobHandle` immediately:\n", "\n", "- `sf.fit_async(...)` \u2192 `JobHandle`\n", "- `sf.generate_async(...)` \u2192 `JobHandle`\n", "- `sf.validate_async(...)` \u2192 `JobHandle`\n", "- `sf.fetch_result(handle)` \u2192 `FitResult` / `GenerationResult` / `ValidationReport` (dispatches on `handle.kind`)\n", "- `sf.list_jobs(status=...)` \u2014 see what's in flight (`'pending'` / `'running'` / `'completed'` / `'failed'`)\n", "- `sf.cancel_job(handle_or_id)` \u2014 cancel queued or running jobs (idempotent on terminal jobs)\n", "\n", "The handle carries the `job_id`, the kind, and the one-shot AES key needed to decrypt the result. It's persistable via `to_dict()` / `from_dict(d)` so you can fire-and-forget from one process and pick up the result from another." ] }, { "cell_type": "code", "execution_count": 18, "id": "e6e94812", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:44.322319Z", "iopub.status.busy": "2026-06-01T19:21:44.322255Z", "iopub.status.idle": "2026-06-01T19:21:45.179871Z", "shell.execute_reply": "2026-06-01T19:21:45.179043Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "sablier-flow: fitting 2 feature(s) over 400 bars [row cadence: daily (median \u0394t=1 days 00:00:00)]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "opened async job: 6a2ded21-0a7d-40cf-95bf-9a28715dee82 (kind='fit')\n", "handle persists as: {\n", " \"job_id\": \"6a2ded21-0a7d-40cf-95bf-9a28715dee82\",\n", " \"kind\": \"fit\",\n", " \"result_key_b64\": \"KaDVZMWQUfD5mX/IkbBiK/g5Vv1f...\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "jobs currently running on your account: 1\n", " 6a2ded21-0a7d-40cf-95bf-9a28715dee82 kind='fit' created=2026-06-01T19:21:44.476857\n" ] } ], "source": [ "# Kick off a second fit asynchronously and observe state mid-flight.\n", "import json\n", "\n", "# Use a smaller universe to keep this demo cheap (~5 credits, ~3 min).\n", "demo_features = ['SPY', 'QQQ']\n", "demo_real = real[demo_features].iloc[-400:] # last ~1.5y, 2 features\n", "# The schema-required data_types map is just the SPY/QQQ slice of the\n", "# demo's bundled map \u2014 both are tradeable ETF prices.\n", "demo_data_types = {col: real.attrs['data_types'][col] for col in demo_features}\n", "\n", "handle = sf.fit_async(\n", " demo_real,\n", " features=demo_features,\n", " data_types=demo_data_types, # same kwarg as the sync sibling\n", " horizon=60, # shorter horizon \u2014 quicker fit\n", " train_split=0.8,\n", " seed=42,\n", ")\n", "print(f'opened async job: {handle.job_id} (kind={handle.kind!r})')\n", "\n", "# Persist the handle. You could write this to disk, paste it in a\n", "# Slack channel for a teammate, or pickle it \u2014 anything serializable.\n", "handle_blob = handle.to_dict()\n", "print(f'handle persists as: {json.dumps(handle_blob, indent=2)[:120]}...')\n", "\n", "# Check what's in flight on the server side without polling the handle.\n", "in_flight = sf.list_jobs(status='running', limit=10)\n", "print(f'jobs currently running on your account: {len(in_flight)}')\n", "for j in in_flight[:3]:\n", " print(f' {j.job_id} kind={j.kind!r} created={j.created_at}')" ] }, { "cell_type": "code", "execution_count": 19, "id": "7571a40b", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:45.182381Z", "iopub.status.busy": "2026-06-01T19:21:45.182145Z", "iopub.status.idle": "2026-06-01T19:21:57.702580Z", "shell.execute_reply": "2026-06-01T19:21:57.700850Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "resumed handle for 6a2ded21-0a7d-40cf-95bf-9a28715dee82 \u2014 blocking on completion...\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "async fit complete \u2014 model_id = 7cc5dd23-51fa-4058-aac6-9982d319d734\n", "features = ['SPY', 'QQQ']\n", "training_loss = 0.5869\n" ] } ], "source": [ "# Reconstitute the handle in a different 'process' (here, just a new\n", "# variable) and block on the result.\n", "resumed = sf.JobHandle.from_dict(handle_blob)\n", "print(f'resumed handle for {resumed.job_id} \u2014 blocking on completion...')\n", "\n", "fit_async_result = sf.fetch_result(resumed)\n", "print(f'async fit complete \u2014 model_id = {fit_async_result.model_id}')\n", "print(f'features = {fit_async_result.features}')\n", "print(f'training_loss = {fit_async_result.training_loss:.4f}')\n", "\n", "# Cancellation is a no-op on already-terminal jobs (silent \u2014 by design).\n", "sf.cancel_job(resumed) # idempotent \u2014 nothing to cancel now\n", "\n", "# Tidy up the throwaway model so it doesn't sit in your list_models output.\n", "sf.delete_model(fit_async_result.model_id)" ] }, { "cell_type": "markdown", "id": "edb78324", "metadata": {}, "source": [ "## Bonus \u2014 Model management\n", "\n", "Once you've fit a model, the server stores the checkpoint for ~30 days. You can list, inspect, and delete them without re-running a fit." ] }, { "cell_type": "code", "execution_count": 20, "id": "0384bd2c", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:57.705754Z", "iopub.status.busy": "2026-06-01T19:21:57.705516Z", "iopub.status.idle": "2026-06-01T19:21:58.151770Z", "shell.execute_reply": "2026-06-01T19:21:58.150547Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10 model(s) on your account:\n", " 53807b7d-1bf1-4c7e-8d40-88d6ff0394b0 features=['SPY', 'QQQ', 'IWM', 'TLT', 'VIX', 'TNX', 'DXY'] status='ready'\n", " d3634680-f783-410a-9ca6-4b404c47a8b6 features=['IWM', 'QQQ', 'SPY', 'TLT', 'VIX', 'TNX', 'DXY'] status='ready'\n", " 82b0900d-592e-4fcd-adbe-b27680693152 features=['IWM', 'QQQ', 'SPY', 'TLT', 'VIX', 'TNX', 'DXY'] status='ready'\n", " f2f4edf2-8ef5-4f59-aae2-58f1fb45b30b features=['IWM', 'QQQ', 'SPY', 'TLT', 'VIX', 'TNX', 'DXY'] status='ready'\n", " fda0045c-2b6a-4a59-a11a-2cd9df98d7dc features=['SPY', 'QQQ', 'IWM', 'TLT', 'VIX', 'TNX', 'DXY'] status='ready'\n", " 3661cecd-f6a3-4d41-b77d-8ec4bc3c8b93 features=['SPY', 'QQQ', 'IWM', 'TLT', 'VIX', 'TNX', 'DXY'] status='ready'\n", " 44a76ca7-39cb-4385-a3f5-9674573328db features=['SPY', 'QQQ', 'IWM', 'TLT', 'VIX', 'TNX', 'DXY'] status='ready'\n", " 69489d7c-6be6-45aa-8bc0-7dfcc91011a8 features=['SPY', 'QQQ', 'IWM', 'TLT', 'VIX', 'TNX', 'DXY'] status='ready'\n", " 3e3c27cc-2f14-4023-89dc-4cba7d9d7472 features=['SPY', 'QQQ', 'IWM', 'TLT', 'VIX'] status='ready'\n", " 709654c9-b40f-450c-86f2-faabdc825f89 features=['SPY', 'QQQ', 'IWM', 'TLT', 'VIX'] status='ready'\n", "\n", "current fit : status='ready' n_assets=7\n", "training_horizon=252 train_split=0.8\n" ] } ], "source": [ "# List every model you've fit on this account (most-recently-used first).\n", "models = sf.list_models(limit=10)\n", "print(f'{len(models)} model(s) on your account:')\n", "for m in models:\n", " print(f' {m.model_id} features={m.features} status={m.status!r}')\n", "\n", "# Get the full metadata for one specific model (same fields as FitResult\n", "# plus lifecycle: status, created_at, last_used_at, train_split).\n", "current = sf.get_model(fit.model_id)\n", "print()\n", "print(f'current fit : status={current.status!r} n_assets={current.n_assets}')\n", "print(f'training_horizon={current.training_horizon} train_split={current.train_split}')\n", "\n", "# Delete an old model when you don't need it anymore. Idempotent \u2014 already-\n", "# gone models return success without error.\n", "# sf.delete_model('some-old-model-id')" ] }, { "cell_type": "markdown", "id": "acb0ac75", "metadata": {}, "source": [ "## Bonus \u2014 Account, credits, usage, cost estimates\n", "\n", "Before kicking off a full fit, you may want to know what it'll cost or what you've already spent. The SDK exposes the same metering surface the web dashboard uses. Credit estimates are **deterministic** (formula based on dataset shape \u00d7 horizon \u00d7 n_paths) and are reconciled against actual usage on job completion." ] }, { "cell_type": "code", "execution_count": 21, "id": "1aae9777", "metadata": { "execution": { "iopub.execute_input": "2026-06-01T19:21:58.155431Z", "iopub.status.busy": "2026-06-01T19:21:58.155054Z", "iopub.status.idle": "2026-06-01T19:21:58.743549Z", "shell.execute_reply": "2026-06-01T19:21:58.742758Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "available credits : 10000\n", "monthly allocation : 10000 (used: 0)\n", "purchased pool : 0\n", "tier : pro\n", "\n", "this month spent: 0 credits (period 2026-06-01 \u2192 2026-06-01)\n", " validate {'n_jobs': 13, 'credits': 0.0}\n", " generate {'n_jobs': 45, 'credits': 0.0}\n", " fit {'n_jobs': 34, 'credits': 0.0}\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "estimated fit cost: 177 credits (band: 150\u2013212)\n", " - Heuristic estimate; real charge is based on actual worker wall-clock time and is reconciled on job completion.\n" ] } ], "source": [ "# Current balance + tier.\n", "balance = sf.credits()\n", "print(f'available credits : {balance.available}')\n", "print(f'monthly allocation : {balance.monthly_allocation} (used: {balance.monthly_used})')\n", "print(f'purchased pool : {balance.purchased}')\n", "print(f'tier : {balance.tier}')\n", "print()\n", "\n", "# Usage rollup over the current month (also accepts since=/until=/kind= filters).\n", "summary = sf.usage_summary(period='month')\n", "print(f'this month spent: {summary.total_credits:.0f} credits '\n", " f'(period {str(summary.period_start)[:10]} \u2192 {str(summary.period_end)[:10]})')\n", "for kind, stats in summary.by_kind.items():\n", " print(f' {kind:<18s} {stats}')\n", "print()\n", "\n", "# Pre-flight: deterministic credit estimate before paying for it.\n", "# Returns {estimated_credits, low, high, notes} \u2014 wall-clock is NOT\n", "# returned (it depends on queue depth + GPU availability; use\n", "# sf.list_jobs() for live progress once a job is running).\n", "est = sf.estimate_cost(\n", " 'fit',\n", " real_data=real,\n", " features=FEATURES,\n", " horizon=252,\n", ")\n", "print(f'estimated fit cost: {est[\"estimated_credits\"]:.0f} credits '\n", " f'(band: {est[\"low\"]:.0f}\u2013{est[\"high\"]:.0f})')\n", "for note in est.get('notes', []):\n", " print(f' - {note}')" ] }, { "cell_type": "markdown", "id": "7c6b62ff", "metadata": {}, "source": [ "## Next steps\n", "\n", "- **Swap demo data for your own:** edit Step 1's loader.\n", "- **Try different backtest windows:** edit Step 2. The same `model_id` from Step 3 handles any window \u2014 no need to refit.\n", "- **Run a strategy family:** `sablier_flow.evaluate_family({...})` evaluates M variants and reports CSCV-PBO directly (the right test when you grid-searched).\n", "- **Monitor live drift:** `sablier_flow.consistency_check(realized_sharpe, baseline=verdict)` once deployed.\n", "- **Fire-and-forget pipelines:** combine `sf.fit_async` + handle persistence (from the Async bonus) with a cron + `sf.fetch_result` to run nightly audits without holding a kernel.\n", "- **Forward forecast pipelines:** combine Step 8 + Step 9 in a nightly job \u2014 generate forward paths from each evening's data, run the strategy family, archive the predicted distribution + calibration verdict. When you eventually realize the actual P&L, `sf.consistency_check` tells you whether the live result drifted from the predicted distribution.\n", "\n", "Full API reference: [`SDK reference`](https://docs.sablier.ai/SDK/) \u2014 every method, kwarg, and return type. The same content is shipped inside the wheel so an LLM agent calling `pip install sablier-flow` has the docs locally." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.12" } }, "nbformat": 4, "nbformat_minor": 5 }