diff --git a/.github/workflows/publish_pypi.yaml b/.github/workflows/publish_pypi.yaml new file mode 100644 index 0000000..2634d07 --- /dev/null +++ b/.github/workflows/publish_pypi.yaml @@ -0,0 +1,41 @@ +name: Publish PyPI + +on: + release: + types: [published] + +jobs: + pypi-publish: + name: upload release to PyPI + runs-on: ubuntu-latest + environment: release + permissions: + id-token: write + steps: + - uses: actions/checkout@v4 + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.x' + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install build + - name: Build package + run: python -m build + - name: Check sdist install and imports + run: | + mkdir -p test-sdist + cd test-sdist + python -m venv venv-sdist + venv-sdist/bin/python -m pip install ../dist/thermox-*.tar.gz + venv-sdist/bin/python -c "import thermox" + - name: Check wheel install and imports + run: | + mkdir -p test-wheel + cd test-wheel + python -m venv venv-wheel + venv-wheel/bin/python -m pip install ../dist/thermox-*.whl + venv-wheel/bin/python -c "import thermox" + - name: Publish package distributions to PyPI + uses: pypa/gh-action-pypi-publish@release/v1 \ No newline at end of file diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml new file mode 100644 index 0000000..dfd8712 --- /dev/null +++ b/.github/workflows/tests.yaml @@ -0,0 +1,39 @@ +name: Tests + +on: + pull_request: + branches: [main] + push: + branches: [main] + +jobs: + pre-commit: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5 + with: + python-version: '3.10' + - uses: pre-commit/action@v3.0.1 + + tests: + name: Run tests for Python ${{ matrix.python-version }} + runs-on: ubuntu-latest + needs: + - pre-commit + strategy: + matrix: + python-version: ['3.10'] + steps: + - uses: actions/checkout@v4 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python-version }} + - name: Install dev environment + run: | + python -m pip install --upgrade pip + pip install .[test] + - name: Run the tests with pytest + run: | + python -m pytest --cov=thermox --cov-report term-missing \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..1213829 --- /dev/null +++ b/.gitignore @@ -0,0 +1,163 @@ +.vscode/ +.DS_Store + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/README.md b/README.md new file mode 100644 index 0000000..8e632c9 --- /dev/null +++ b/README.md @@ -0,0 +1,78 @@ +# thermox + +This package provides a very simple interface to **exactly** simulate [Ornstein-Uhlenbeck](https://en.wikipedia.org/wiki/Ornstein%E2%80%93Uhlenbeck_process) (OU) processes of the form + +$$ dx = - A(x - b) dt + \mathcal{N}(0, D dt) $$ + +To collect samples from this process, define sampling times `ts`, initial state `x0`, drift matrix `A`, displacement vector `b`, diffusion matrix `D` and a JAX random key. Then run `thermox.sample`: + +```python +thermox.sample(key, ts, x0, A, b, D) +``` +Samples are then collected by exact diagonalization (therefore there is no discretization error) and JAX scans. + +You can access log-probabilities of the OU process by running `thermox.log_prob`: + +```python +thermox.log_prob(ts, xs, A, b, D) +``` + +which can be useful for e.g. maximum likelihood estimation of the parameters `A`, `b` and `D` by composing with `jax.grad`. + +Additionally `thermox` provides a [`scipy`](https://docs.scipy.org/doc/scipy/reference/linalg.html) style suit of [**thermodynamic linear algebra**](https://arxiv.org/abs/2308.05660) primitives: `thermox.linalg.solve`, `thermox.linalg.inv`, `thermox.linalg.expm` and `thermox.linalg.negexpm` which all simulate an OU process under the hood. More details can be found in the [`thermo_linear_algebra.ipynb`](/thermo_linear_algebra.ipynb) notebook. + +## Contributing + +Before submitting any pull request, make sure to run `pre-commit run --all-files`. + + +## Example usage + +Here is a simple code example for a 5-dimensional OU process: +```python +import thermox +import jax +import jax.numpy as jnp +import matplotlib.pyplot as plt + +# Set random seed +key = jax.random.PRNGKey(0) + +# Timeframe +dt = 0.01 +ts = jnp.arange(0, 1, dt) + +# System parameters for a 5-dimensional OU process +A = jnp.array([[2.0, 0.5, 0.0, 0.0, 0.0], + [0.5, 2.0, 0.5, 0.0, 0.0], + [0.0, 0.5, 2.0, 0.5, 0.0], + [0.0, 0.0, 0.5, 2.0, 0.5], + [0.0, 0.0, 0.0, 0.5, 2.0]]) + +b, x0 = jnp.zeros(5), jnp.zeros(5) # Zero drift displacement vector and initial state + + # Diffusion matrix with correlations between x_1 and x_2 +D = jnp.array([[2, 1, 0, 0, 0], + [1, 2, 0, 0, 0], + [0, 0, 2, 0, 0], + [0, 0, 0, 2, 0], + [0, 0, 0, 0, 2]]) + +# Collect samples +samples = thermox.sample(key, ts, x0, A, b, D) + +plt.figure(figsize=(12, 5)) +plt.plot(ts, samples, label=[f'Dimension {i+1}' for i in range(5)]) +plt.xlabel('Time') +plt.ylabel('Value') +plt.title('Trajectories of 5-Dimensional OU Process') +plt.legend() +plt.show() +``` + +

+ +
+

+ + diff --git a/examples/README.md b/examples/README.md new file mode 100644 index 0000000..73b1d6b --- /dev/null +++ b/examples/README.md @@ -0,0 +1,6 @@ +# Examples + +You will find two Jupyter notebooks in this folder: + +- `diffrax_comparison.ipynb` runs a simple OU process using `thermox` and [`diffrax`](https://github.com/patrick-kidger/diffrax) and compares runtimes (showing a large benefit from using `thermox` for long simulation times) +- `thermodynamic_linear_algebra.ipynb` is a small tutorial on how to use functions from the `thermox.linalg` module. \ No newline at end of file diff --git a/examples/diffrax_comparison.ipynb b/examples/diffrax_comparison.ipynb new file mode 100644 index 0000000..74d08e4 --- /dev/null +++ b/examples/diffrax_comparison.ipynb @@ -0,0 +1,305 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from jax import numpy as jnp, random, jit\n", + "import thermox\n", + "import diffrax\n", + "from time import time\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We want to simulate an OU process\n", + "$$\n", + "dx = -A(x-b)dt + \\mathcal{N}(0, Ddt)\n", + "$$\n", + "and compare `thermox` and `diffrax` for a varying number of timesteps.\n", + "\n", + "\n", + "`thermox` simulates OU processes *exactly*, whilst [`diffrax`](https://github.com/patrick-kidger/diffrax)\n", + "is a differential equation library that uses discretization to\n", + "*approximately* simulate general ODEs and SDEs (thus `diffrax` has a broader scope but\n", + "still represents the most natural open source comparison for simulating OU processes\n", + "with JAX)." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Define dimension\n", + "dim = 100" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Master key\n", + "key = random.PRNGKey(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Function to generate a random wishart matrix\n", + "def sample_wishart(key, dim, df):\n", + " G = random.normal(key, (dim, df))\n", + " return G @ G.T" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Generate A from Wishart distribution\n", + "key, A_key = random.split(key)\n", + "df_A = 10\n", + "A = sample_wishart(A_key, dim, df_A)\n", + "\n", + "# Perturb to ensure it is positive definite\n", + "A += 1e-3 * jnp.eye(dim)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Generate x0 and b from normal distribution\n", + "key, x0_key, b_key = random.split(key, 3)\n", + "x0 = random.normal(x0_key, (dim,))\n", + "b = random.normal(b_key, (dim,))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# Identity D\n", + "D = jnp.eye(dim)\n", + "D_sqrt = jnp.linalg.cholesky(D)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Function to simulate from thermox\n", + "@jit\n", + "def simulate_thermox(rk, ts):\n", + " return thermox.sample(rk, ts, x0, A, b, D)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# Function to simulate from diffrax\n", + "@jit\n", + "def simulate_diffrax(rk, ts):\n", + " # From https://docs.kidger.site/diffrax/usage/getting-started/#stochastic-differential-equations-sdes\n", + " def drift(t, y, args):\n", + " return -A @ (y - b)\n", + " def diffusion(t, y, args):\n", + " return D_sqrt\n", + " brownian_motion = diffrax.VirtualBrownianTree(ts[0], ts[-1], tol=1e-3, shape=(dim,), key=rk)\n", + " terms = diffrax.MultiTerm(diffrax.ODETerm(drift), diffrax.ControlTerm(diffusion, brownian_motion))\n", + " solver = diffrax.ItoMilstein()\n", + " saveat = diffrax.SaveAt(ts=ts)\n", + " sol = diffrax.diffeqsolve(terms, solver, ts[0], ts[-1], y0=x0, saveat=saveat,\n", + " dt0=0.01, max_steps=10000000\n", + " )\n", + " return sol.ys" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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P9n5ElimLyZsmMzd+LpM6TqJdULv6C/4qKjYXM//EfH459gt55Xm1sk25TI5eqUev0qNX6nFTuaFX6XFTuqFT6VzPK5a7qdzQKasu06vOvFcpr9s0RSZJUu2mbVdZSUkJXl5eGAwGPD096zscQRCEcyQZkrhl4S0oZArW3rkWX60v4Oo+8M2hb/h438cA9Ivsx4yeM9ApdfUZ7kUT59+aiWMjCPXD6rDy1Lqn2JKxBTeVG98O/Jbm/s1rXL/cXs5PR37i28PfUm4vB6B/ZH+eaf8MkZ6RVyvsqyrZkMzco3P5++TfmB1mADzVngTqA89NSM5OZCpeO1+Co1Vokclk9fr5Lvb8K1qCBEEQ6tjSxKUAdAvtVpkAAchkMh5q9RBh7mG8suUV1qSu4f4V9/NJv0/w1/nXV7iCIAjXJbvTzgsbX2BLxha0Ci2f9fvsvAkQgE6p4+HWD3N7k9uZvW82C04uYHXqatanr2d009E80voRvDReV+kT1B1JktiVvYuf4n9iQ/qGyuWxvrGMazaOm6NvrtOuZ9ci0RIkCIJQhyRJYshfQ0g3pvN2z7cZ0mBItevtzdnLU+uewmAxEOoWymf9P6Ohd8OrHO2lEeffmoljIwhXl1Ny8vLml1mSuASVXMXsfrPpFtrtkreTUJTAe3veY0vGFgA81B483OphxsSOQa1Q13bYdc7msLE8eTlz4udUqUjaJ7wP45qPo0NQh3pvualtF3v+FUmQIAhCHdqfu597lt+DTqlj/Z3r0av0Na6bUpLCY6sfI7U0FQ+VB+/3fZ8uIV2uYrSXRpx/ayaOjSBcPZIkMXX7VP448QdKmZL3+7xP38i+V7TNrRlbmbVnFglFCQCEu4fzTPtnGBA14LpIGqob76NVaBnRaARj48ZWGSP1XyO6wwmCIFwDThdE6B/Z/7wJEECUZxRzh8zl6XVPsy93H4+uepTXur7GrY1vvRqhCoIgXHckSeLd3e/yx4k/kCFjRs8ZV5wAAXQL68b8kPksPLmQ2ftnk25M59kNz9I2sC3PdXiOVgGtaiH62pdkSGJu/FwWnVpUOd4nUBfImLgxjGoy6j/Rta+2iJYgQRCEOmJz2rjp95sothTzZf8v6RZ2cV0zLA4Lr25+leXJywH4v1b/xxNtnrjm7j6K82/NxLERhKvj0/2f8sWBLwCY2m1qndw0KrOV8d3h7/jxyI+VicXg6ME83f5pwtzDan1/l0qSJHZm7+Sn+J/YmL6xcnmcbxz3NLvnhhvvI1qCBEEQ6tnWjK0UW4rx0/rRKaTTRb9Po9Aws9dMwj3C+frQ13x18CvSS9OZ1n3addknXRAEoS58d/i7ygRocqfJddZqrlfpeaLtE9zR5A5m75vNolOLWJ68nNWpqxkbN5YHWz2Ip/rq3+ywOqwsT3KN9zledBwAGTJ6R/RmXLP/5nif2iSSIEEQhDpyuivc4JjBlzzfgVwm56l2TxHhEcHUbVNZlrSMbFM2H/X9CG+tdx1EKwiCcP345dgvfLDnAwCebvc0d8fdXef7DHYL5s0eb3J33N28t/s9dmTv4Psj37Pg5AIebf0oo5qOQiWv+xaXInNR5Xif/PJ8wFXlbkTDEYxtNpYoz6g6j+G/QHSHEwRBqANGq5E+v/fB4rDw69BfL1im9Xy2ZW5j4vqJGG1Gojyj+KzfZ9fE/BXi/FszcWwEoe4sPLmQV7e8CsBDLR/iqXZPXfUYJEliY/pG3tvzHkmGJACiPaOZ2H4ifSL61EkLTKIhsXK8j8VhAcR4n+qI7nCCIAj1aE3qGiwOC9Ge0TTza3ZF2+oa2pU5g+fw2JrHSClJ4e5ld/PxTR/TNrBtLUUrCIJwfViRvILXt74OwNi4sTzZ9sl6iUMmc3U76xbWjT9P/Mln+z8juSSZp9Y9RcfgjjzX4bkrPveDK9nakb2Dn478xKaMTZXL43zjGNd8HIOiBt1Q431qk7y+AxAEQfgvOj1B6rAGw2rljmAjn0bMGzqP5n7NKbYU8+A/D7IiacUVb/e/Ljo6GplMds7P448/Xu36P/zwwznrarXaqxy1IAjV2ZC2gRc3vohTcnJ749t5vuPz9T7mRSVXMTp2NEtvW8oDLR5ALVezK3sX/1vyP17a9BLZpuzL2q7VYWXhyYXcsfgOHlr5EJsyNiFDRt+Ivnw/6Ht+G/YbwxoMEwnQFRAtQYIgCLUsryyPHdk7AGqcHPVy+Ov8+W7Qd0zeNJl1aeuYtHESaaVpPNjywXr/InCt2rVrFw6Ho/L54cOHGTBgAKNGjarxPZ6enhw/frzyuTi2glD/tmdtZ+L6idglO0NihvBql1evqb9ND7UHE9pP4M6md/LR3o9YlrSMxYmLWZmyknHNxvFAywdwU7ldcDtF5iJ+P/47vxz7hQJzASDG+9QVkQQJgiDUsuVJy3FKTtoEtCHCI6JWt61X6fmgzwe8t+c95sTP4eN9H5NuTOeVLq9clQG515uAgIAqz2fOnEnDhg3p3bt3je+RyWQEBwfXdWiCIFykfbn7eGrtU1idVm6KuIk3e7yJQq6o77CqFeoeytu93mZs3Fhm7Z7F3ty9fH3oa/5K+IvH2z7OrY1urbZQTmJxInOOzmHxqcVnxvvoA7kr9i7uaHKHGO9TB0QSJAiCUMtOV4Ub2mBonWxfIVfwfMfnifCIYObOmfyV8BeZxkze7/M+HmqPOtnnf4HVamXu3LlMnDjxvHeQjUYjUVFROJ1O2rVrx/Tp02ne/PyFLSwWCxaLpfJ5SUlJrcUtCDeyIwVHeGz1Y5Tby+kW2o13e797XdzwaRnQkh9u/oE1qWv4YM8HpJamMnXbVOYdncezHZ6lR1gPJElie9Z25sTPOWe8z73N72Vg9MDr4rNer0R1OEEQhFqUWJzIiL9HoJQpWXvnWny0PnW6vw1pG5i0cRLl9nIaeTfi036fEuoeWqf7PO16O//+/vvv3HXXXaSmphIaWv0x2rZtGwkJCbRq1QqDwcCsWbPYuHEjR44cITw8vMZtT5kyhTfeeOOc5dfLsRGEa1FCUQLj/xmPwWKgXWA7vhjwBTqlrr7DumQ2h43fjv/G5wc+p8TqukHSOaQzheZCEooSACrH+9zT7B7aB7W/prr6XW8u9tokkiBBEIRa9PHej/n60Nf0Ce/DJ/0+uSr7jC+I54k1T5BXnoe/zp/ZN82+opLcF+t6O/8OGjQItVrN4sWLL/o9NpuNuLg4xowZw7Rp02pcr7qWoIiIiOvm2AjCtSalJIX7VtxHfnk+Lfxa8PXAr3FXu9d3WFfEYDHw1cGvmHdsHnanHXCN9xnZaCRj48ZeE1Mf/BeIEtmCIAhXmSRJLEtaBtRdV7jqNPNrxryh83hszWMkFCVw34r7eLvX29wUedNVi+Fal5KSwurVq/nrr78u6X0qlYq2bdty8uTJ866n0WjQaDRXEqIgCBUyjZk8uPJB8svzaeLThC8GfHHdJ0AAXhovJnWcxOimo5l/Yj6+Wl9ubXyrGO9TT0SJbEEQhFqyP28/GcYM3FRu9I6oeeB9XQh2C+anm3+ie2h3zA4zE9ZNYG783Ksaw7Xs+++/JzAwkKFDLy05dTgcHDp0iJCQkDqKTBCEs+WV5fHQyofINmUT7RnNlwO+/M8lCRGeEUzsMJH7Wtz3n/ts1xORBAmCINSSJadcBRH6Rfarl37r7mp3Pun3CXc0uQMJibd3vc2MHTNwOB0XfvN/mNPp5Pvvv+fee+9FqazaAWLcuHG8+OKLlc+nTp3KypUrSUxMZO/evYwdO5aUlBQefPDBqx22INxwisxF/N+q/yO1NJUw9zC+Hvg1/jr/+g5L+I8S3eEEQRBqgc1h45+UfwDXBKn1RSVX8VqX14j0iOT9Pe8z79g8MowZvNPrHfQqfb3FVZ9Wr15Namoq999//zmvpaamIpefuR9YVFTEQw89RHZ2Nj4+PrRv356tW7fSrNmVz/wuCELNSqwlPLzqYU4WnyRQF8jXA78m2E2UqhfqjiiMIAiCUAvWpa7jqXVPEaALYNUdq66JOSxWJq/kpc0vYXFYiPONY3a/2QTqA2tt++L8WzNxbATh4pXZynh41cPsz9uPr9aX72/+ngZeDeo7LOE6dbHnX9EdThAEoRacnhtocMzgayIBAhgYPZBvB32Lr9aXo4VHuWvpXZwoOlHfYQmCIFSyOCw8tfYp9uftx0PtwZcDvhQJkHBViCRIEAThCpVaS9mQvgGo365w1Wkd0Jq5Q+YS7RlNTlkO45aPY0vGlvoOSxAEAZvDxsT1E9mRvQO9Us/n/T8n1je2vsMSbhAiCRIEQbhCq1NWY3FYaODV4Jq8gEd4RDB3yFw6BHXAZDPx+JrHmX9ifn2HJQjCDczhdDB502Q2pm9Eo9Awu99sWge0ru+whBtInSZBGzduZPjw4YSGhiKTyVi4cGGV1yVJ4rXXXiMkJASdTkf//v1JSEioy5AEQRBq3dLEpYCrFehaneXbS+PFVwO+YniD4TgkB1O3TeX9Pe/jlJz1HZogCDcYp+Tkta2vsTJlJUq5kg/7fkjH4I71HZZwg6nT6nAmk4nWrVtz//33c9ttt53z+jvvvMPHH3/Mjz/+SExMDK+++iqDBg0iPj4erVZbl6EJgnCD+GFLEruSi/BxU+HrpsHPTY3vWT9+bmp83NSoFJd3TyjHlMPO7J0ADGkwpDZDr3UqhYq3erxFhEcEnx34jO8Pf096aTrTe0xHqxTnXEEQ6p4kSUzfMZ1FpxahkCmY1WsWPcJ61HdYwg2oTpOgwYMHM3jw4GpfkySJDz/8kFdeeYURI0YA8NNPPxEUFMTChQsZPXp0XYYmCMINYH9aMVMWx1/Uup5aJX7uGnz0ZyVL7urKpMnH7cxjPzcNOrWr+MHypOVISLQLbEeYe1hdfpxaIZPJeLTNo4R7hPPa1tdYlbKKVv6tuK/FffUdmiAI/3GSJPHBng/47fhvyJAxrfs0+kX1q++whBtUvc0TlJSURHZ2Nv37969c5uXlRefOndm2bVuNSZDFYsFisVQ+LykpqfNYBUG4/kiSxIxlRwHo2difthHeFJisFJqslb8LTVaKyqxIEpSY7ZSY7SRd5PZ1KgW+bmrMgb+BAsoLW/Pmknh83dX46iuSJXc1vm4afN3UeGqV11RXueENhxPsFswfJ/5gbLOx9R2OIAg3gC8Pfsn3R74H4NWurzK84fB6jki4kdVbEpSdnQ1AUFBQleVBQUGVr1VnxowZvPHGG3UamyAI17+1x3LZkVSIRinn7dtbEeqtq3Y9h1PCUG6j0GShwFiRHJVZKTRWTZYKTFaKKh5bHU7KbQ6yypJxU6QjSQp2Holgp7PmFEopl+HjpsbfXUPfpgHc2y2aIM/67YLWMbij6IcvCMJV8eORH/l0/6cATOowiVFNRtVzRMKNrt6SoMv14osvMnHixMrnJSUlRERE1GNEgiBca+wOJzOXHwNgfPeYGhMgAIVcVjk+qNFFzCMqSRJGi51Ck5UvDs5mSSo09ezIgEHtXMmS0UqhyUJhmSuxKjRaMVkd2J0SeaUW8kotHM0q4etNiQxrFcoDPWJoEeZVWx9dEAThmjP/xHxm7Z4FwONtHmdc83H1HJEg1GMSFBwcDEBOTg4hISGVy3NycmjTpk2N79NoNGg0mroOTxCE69gfe9JJyDXirVfxaJ+GtbptmUyGh1aFm0bBnoI1ADzcbhQDo2vej9nmqGxRSsw3MXdbCjuTC1mwL4MF+zLoHOPLAz1i6BcXhEJ+7XSZEwTh+rIpfROHCw6jV+rRKXWVP3qlHp1KV2XZ6R+lvG6/Ci4+tZhp26YBcH+L+3m41cN1uj9BuFj1lgTFxMQQHBzMmjVrKpOekpISduzYwaOPPlpfYQmCcJ0rs9r5YPUJAJ7o2wgvnapO9rM3Zy9ZpizcVe70juh93nW1KgWh3jpCvXW0CPPiltahHEwv5tvNSSw9mMWOpEJ2JBUS7adnfPcY7mgfjpvmumuoFwShHm3N2MoTa5+45LL3arm62gTp34nU6XXOXl75WFXN+koda9PW8sqWV5CQGN10NBPaTbimxkYKN7Y6vcoajUZOnjxZ+TwpKYn9+/fj6+tLZGQkEyZM4M0336Rx48aVJbJDQ0MZOXJkXYYlCMJ/2Hebk8gpsRDuo+OerlF1tp+lSa65gQZEDUCjuPTW6Vbh3nw0ui2TB8fy49YU5u1IIbmgjNcXHeG9lccZ0zmS+7pFE+JVc1c+QRAEgPTSdJ7f9DxOyUn7oPYEuwVTbiun3H7mp8xeVuX56WTJ6rRitVgxWAx1Ft+IhiN4sfOLIgESril1mgTt3r2bvn37Vj4/PZbn3nvv5YcffuD555/HZDLxf//3fxQXF9OjRw9WrFgh5ggSBOGyFBgtfLEhEYBJg5qiUSrqZD9Wh5V/kv8BYGiDoVe0rRAvHZMHx/LkTY34c286321OIrmgjC83JPLtpiSGtAzhgR4xtI7wroXIBUH4rym3l/PM+mcwWAy08GvBlwO+vOCNGUmSsDqtlNmqJkbl9vIqy85OnKpd9/Tr/0q4JKTKfQ1vMJw3ur2BXHZ5c7EJQl2RSZIkXXi1a1dJSQleXl4YDAY8PT3rOxxBEOrRlEVH+GFrMi3DvPj78e7I62h8zZrUNUxYN4FAfSArb1+JQl57yZbTKbH2WC7fbE5ke2Jh5fKO0T480COGAc2Cr5lxQ+L8WzNxbISrQZIkXt78MosTF+Or9eW3Yb8R7BZc7zGZHebK1iZ/nX+9xiPceC72/Cs6nQuC8J+QnG9i7vYUAF4cHFtnCRDA0kRXV7ihMUNrNQECkMtl9G8WRP9mQRzOMPDd5iQWH8xkV3IRu5KLiPDVMb5bDHd2jMBdjBsShBvaL8d+YXHiYhQyBe/2erfeEyBwFY85PSZIEK5lom1SEIT/hHf/OY7dKdGnaQDdGtXdnccSawnr09YDV94V7kJahHnx/v/asPmFm3i8b0O89SrSCsuZuiSertPX8NbSeNKLyuo0BkEQrk17c/by7q53AXim/TN0CulUzxEJwvVFJEGCIFz39qUWsfRQFjIZvHBzbJ3ua3XKamxOG428G9HEp0md7uu0IE8tkwbFsm1yP966tQUNAtwotdj5elMSvd9dz+Pz9rI3teiqxCIIQv3LLcvl2Q3PYpfs3Bx9M+OaiXl3BOFSib4UgiBc1yRJYkbFxKi3twsnLqRux18sSVwCuFqBrnalI51awd2doxjTMZINJ/L4ZnMiW04WsPRgFksPZtEu0psHejRgUPMglApxj0sQ/otsDhvPrn+W/PJ8Gnk34o1ub4iqa4JwGUQSJAjCdW3N0Vx2JhWiUcqZOKBuW2ayTdnszt4NuMYD1Re5XEbf2ED6xgYSn1nCd1uSWLQ/k72pxeydt5cwbx3ju0dzZ8cIPLV1M0+SIAj14+1db7M/bz8eKg8+6vsRepW+vkMShOuSuFUoCMJ1y+5wMnOFqxXo/h4xhHrX7UDcZUnLkJBoH9SeEPeQOt3XxWoW6smsUa3ZPLkvT93UCF83NRnF5by59CjdZqxl6uJ40grFuCFB+C9YeHIhvx3/DYCZvWYS6RlZzxEJwvVLJEGCIFy3/tiTzslcI956FY/0bljn+zvdFW5Yg2F1vq9LFeihZeLApmydfBMzb2tJ40B3jBY7321Jove763hkzh52Jxdync+KIAg3rPiCeKZtmwbAY60fo1d4r3qOSBCub6I7nCAI16Uyq533V50A4MmbGuOlq77blyRJSE4ncsWVlbI+XnichKIEVHIVA6IGXNG26pJWpWB0p0j+1zGCjQn5fLMpkU0J+aw4ks2KI9m0DvfigZ4NGNwiGJUYNyQI14UicxHPrHsGq9NK7/DePNz64foOSRDqzJaiUlLNVsaE+NXpfkQSJAjCdenbTUnkllqI8NUxtsu5XUKs5nIOrfmH3UsWgCQx5MnniGje6rL3tzTJNTdQr/BeeGm8Lns7V4tMJqN3kwB6NwngeHYp321OYsH+DA6kG3jql32EeGm5r1s0oztF1phACoJQ/+xOO89vfJ5MUyaRHpFM7zkduUzcwBD+ew6VljE9MYt1haXoFXL6+3kSoK6765NIggRBuO7kGy18uTERgOcGNkWjPNPKU24sZf+KJexdvgizsbRy+fw3X6HnXffRYditl1xJySk5WZa4DLg2u8JdSNNgD96+oxWTbm7Kz9tTmbM9mSyDmRnLj/HRmgTevr0Vw1uH1neYgiBU45N9n7A9azs6pY4P+36Ip7puK2AKwtWWVGbh7aQsFuYWA6CUwf+CfZFTt1UPRRIkCMJ155M1CRgtdlqGeTG8levLu7GwgN1LF3Jw9Qps5nIAvIND6Dj8djKOxxO/cS0b535HVsIxBj0yAY3+4isq7cnZQ05ZDh4qD3qG96yTz3Q1+LtreLp/Yx7u3YBFBzL5dlMSx3NK67ysuCAIl2dVyiq+O/wdAFO7TaWxT+N6jkgQak+2xcb7ydnMyyrAXjFc9bYgH56PCSZap6nz/YskSBCE60pSvomfd6QC8OKQWEpys9m16E+ObFiNw24HICAqhk4jR9GkS3fkcgUt+w0itEksa7//ioQdW8lPS+WWiS/iHxF1UftcmujqCjcweiAaRd2fmOuaVqXgzg4RjGofzpHMEhoFutd3SIIg/Mup4lO8svkVAO5tdi83x9xczxEJQu0ottn5NDWXb9LzKHe6sp9+vp682CCYFh5Xr+S7SIIEQbiuzPrnOHanxM2hToqWfs93WzchSU4AwmKb0WnkKGLadKjS5U0mk9F6wBACoxuy6IMZFGWmM+/lZxn4yFPEdjt/hSWLw8LK5JWAa4LU/xKZTEaLsGt/fJMg3GhKraVMWDeBMnsZnYI7MaH9hPoOSRCuWJnDybfpecxOzcVgdwDQ0dONlxqG0NX76t+ME0mQIAjXjX2pRezZtY/hhr1EJ6VwrGJ5TJv2dBo5ivC4Fud9f0jjptwz8yOWfvQOqYcPsPSjd8g6cYxeY+9Hoaz+dLgxfSOltlKC3YJpH9S+lj+RIAhCVU7JycubXya5JJlgt2De7f0uSrn4uiZcv2xOiV+yCngvOZscq6vHRqyblpcahDDAz/OSx+nWFvFXJQjCNU+SJJIP7GXhZ98yyuDqCodMRpMuPeg04g6CYi5+jiC9pxe3vzyVLb/NZefC+exdvojsxJMMn/AC7r7nluM83RVuSMwQUZFJEIQ6982hb1iXtg61XM0HfT7AV+tb3yEJwmVxShKLcot5OymLpHIrABFaNc/HBHNbkA+KGpKfZEMyNqetzsfAiSRIEIRrltPpIGHHNnYunE9u8ik8AQdymvToS+877sQnJOyytiuXK+g55l5CGjVl+afvk3k8njmTn2bYhBeIaNaycj2DxcDG9I3Af68rnCAI157NGZuZvW82AK90eYUW/udv3RaEa5EkSawvLGV6YhaHjK5CRX4qJc9EB3FPqB8aec03FHdn72bC+gnolDrmDZlHgD6gzuIUSZAgCNcch91G/KZ17Pr7T4qyMgCwy1Ucco+j5c23MPL2LrWyn0YduzB25ocsem86+anJzJ/2Mr3uuo/2FWW0V6Wswua00cSnCU18mtTKPgVBEKqTVprGCxtfQEJiVJNR3Nr41voOSRAu2R6DibcSs9habATAXSHnschA/i88AHfl+SctX3xqMa9tfQ27006kR2Sdd5MTSZAgCNcMm9nMobX/sGvJAowF+QBo3dxRtuzFB5mB6Dw8+Wxo7Y7L8QkO5a43Z7Hq6085umkdG+Z+R1bCcQY9+jRLEpcA1+fcQIIgXD/K7eVMWDeBEmsJrfxbMbnT5PoOSRAuyXGTmZmJWSzPNwCglskYH+7PU5FB+KnPn25IksTnBz7n8wOfAzAgagBv9XgLnVJXpzGLJEgQhHpnNhrZ989i9i5fjLm0BAA3H1/aDx1J414DGDB7B2aFhedvaoyntvZnj1ZptAx+fCKhjWNZ9+PXnNixhezUU5xsfACZu4zBMYNrfZ+CIAjg+gI4ZesUThSdwFfry3t93kOtUNd3WIJwUdLNVmYlZfN7diFOQA7cGezLczHBhGsv/P/Y6rDy+tbXK286jm8xngntJlyVMbgiCRIEod4YiwrZs3QhB1Ytr5zg1CsomI7Db6d5734o1Wo+WZNAXqmFCF8dd3eJrLNYZDIZbQYNJTCmIYs/nElJVjbDckPI6elDsFtwne1XEIQb27xj81iWtAyFTMF7vd8T5xvhupBvtfNJSg7fZ+RjlVxz/Qzx9+KFBiE0ddNe1DaKzcU8ve5p9ubuRSFT8EqXV7ijyR11GXYVIgkSBOGqK87JZvfiPzm8fjUOmw0A/8hoOo0cRdMuPZArXP2G840WvthwCoBJg2LRXKA/cW0IbRLL2BkfMvPVe/DOkRO+3sA6/df0unt8jWW0BUEQLsfu7N28u+tdAJ7r8BwdgjvUc0SCcH5Gu4Mv0/L4PC0Xo8M1R183b3deaRBCOy+3i95OSkkKj695nJSSFNxV7rzX5z26hXarq7CrJa7ogiBcNfmpyez8+w+Obd2I5HSdPEOaxNJ55J00aNfxnEGQH69JwGR10Crci2EtQ65anOmOHP5um0yHBD+an3Jn77K/yUlMYNiEybj7iHK1giBcuRxTDs9ueBaH5GBIzBDujru7vkMShBpZnE7mZBbwQXIOBTbXXD8t3XW83DCE3j4el1TEYE/OHp5e9zQGi4FQt1Bm95td5+WwqyOSIEEQ6lzmiWPsWPg7iXt2Vi6Lbt2ucoLT6k6eSfkm5u1wzQk0eXAscvnVm0xtSeISJDl4D2zHCLc7Wf7p+2Qci2duRRntC03KKgiCcD5Wh5WJGyZSaC6kqU9TpnSbUm8TRgrXL8kpgcOJZJeQ7E4km9P1+/SPzQlnP//Xepy1nuSQqt2HA4nFKjufaK1kyl3rRDpkTDCrGVQsQ56eQzE5Fx1zSkkKe7N3c480BF+tLz303dGuhyISzlnX51YxT5AgCNchSZJIObiPnQvnkxZ/yLVQJqNJp250GjmKoAaNzvv+d/85ht0p0bdpAN0a+l+FiF0cTgfLEpcBrrmBGkV2YeyMD1xltNNS+H3qS/S6ezzth44UX1oEQbgsb+98m4N5B/FQe/BB3w/qvAqWcG2R7E7K9uZiLzYj2aWqyci/khjJIUF1y+1OqCFxqZUYgY0BCj5trCFR7+qK7m928tApKyMybCglKL+M7fqjYTDdK587sosx1bCuSIIEQbiuSE4nCbtcE5zmJJ4EQK5QENezL51G3IFvaPgFt7E3tYhlh7KRy2Dy4Li6DrmK3Tm7yS3PxVPtSc+wngD4hIRx15vvserr2RzdvJ4Nc751ldF+5CnUOv1VjU+4NFOmTOGNN96osqxp06YcO3asxvfMnz+fV199leTkZBo3bszbb7/NkCFD6jpU4QaxIGEBv5/4HRky3u75NhEeEfUdknAVmU8VU7zwJPa8y0khzkMGMqUcmUoOSrnrsVJW8VtezWuu5zKFzLVcIef0fb1d2JglL2efzAGApyTjYUnLWJUGXawMYi8tNIfkYF3aeo4Xus67bQPb0TW0CzLq90aiSIIEQagVTqeDE9s2s/2v3yhId3VjU6o1tOo3iPbDbsXT/+JmfZYkiRnLjgJwe7twmgZ71FnM1TldpnNg9MAqZWpVWi2Dn3iWkCaxrP/xG05s30x+ajK3PPsyfuHiS8y1rHnz5qxevbryufI8BS62bt3KmDFjmDFjBsOGDWPevHmMHDmSvXv30qKF6AYpXJnD+Yd5c/ubADze5nF6hves54iEq8VhtGJYlkTZ3lwA5O4qdC38XYnI2UlJxWNU/0piVHJkimqSnIr3IJddce+Ew6VlTE/MYm2ha6JTnVzGg+EBPB4ZiLfq8lIGg8XAM+ueZo9iD4pABS91fombm9553vfs3buX0NBQPC9rjxdPJEGCIFwRp8PB8a0b2f7XbxRmpgOg0bvR9uZhtB18C3pPr0va3uqjuexKLkKjlDNxYJO6CLlGZruZ1SmuL8vVTZAqk8loO2gYQTENWfzBTAoz0/n55YkMeuRpmnbtcVVjFS6eUqkkOPjiyg5/9NFH3HzzzUyaNAmAadOmsWrVKmbPns0XX3xRl2EK/3GF5kKeWf8MVqeVvhF9eajVQ/UdknAVSE6Jsj05GJYn4SyzgwzcOofgNSgaue7a+Bp+3GTmw+RsFuQWA6CQwd0hfkyMDiZYc/lz86WWpPL4msdJLknGTeXGe73fo3tY9/O+p6CggCWLl+B0Sjz2+KMEBgZe9v4v5No4+oIgXHecDgdHN69nx4LfKMrKBEDr5k67oSNoe/NwtG7ul7xNu8PJzOWuVqAHesQQ4nV1+8lvSN+A0WYk1C2UtoFta1wvtEkc98z8iCUfvUPakYMs+XAmWQkj6XnXfaKM9jUoISGB0NBQtFotXbt2ZcaMGURGVj/n1LZt25g4cWKVZYMGDWLhwoXn3YfFYsFisVQ+LykpueK4hf8Ou9PO8xueJ9uUTbRnNG/1eOuqTAYp1C9bjomiBSexJrvOB6pgN7xva4Qmsq7bOC7M7pRYWWDgu/R8NhcbK5ePDPTm+ZgQGug1V7T9vTl7eXrd0xRbiglxC+HTfp9eVAW4lSvW4F4Yi16jIyDg4nqQXC5xtRYE4ZI47HbiN61lx4LfMeRkA6B196DDsFtpM2gYGv3lj5H5fXc6p/JM+OhVPNKnYW2FfNGWJi4FYEiDIRf8gqL38uaOl6ex+bc57Pr7D/YsXUj2qQSGPzMZN2+fqxGucBE6d+7MDz/8QNOmTcnKyuKNN96gZ8+eHD58GA+Pc7taZmdnExQUVGVZUFAQ2dnZ593PjBkzzhl7JAinfbT3I3Zk70Cn1PFh3w/xUF/dbr7C1SXZHJSsTaN0Yzo4JGQqOZ4DonDvHopMUb/Jb57VxrzMQn7KzCfD4pqnTw7c7O/FM9FBtPS48nGuyxKX8cqWV7A5bTT3a87sfrPx152/wJHkkNjz9x5yt+rROPQ4LRJ5pwwENvK+4nhqIpIgQRAuisNu48iGNexYMJ+SPFc5TJ2HJx2G30abgUOuuEBAmdXOB6tPAPDkTY3x1F5+E/zlKDYXsyljE1B9V7jqyBUKet11HyGNm7Li0w/IOHaEOS88xbBnJhMe27wuwxUu0uDBgysft2rVis6dOxMVFcXvv//OAw88UGv7efHFF6u0IJWUlBARIcaKCbAieQU/HPkBgDe7v0lD76t/g0e4eswniihaeBJHoRkAbZwv3rc0ROmjrde49paY+C49n0W5xVglV1U5X5WCsSF+DNfJyTsWj0xmwhARgZfXpXVjP02SJL46+BWz988GoF9kP2b0nHHe6odOsx3TrhyOrEhmd0E5SvTI5TYGdAzDL6huCw+JJEgQhPOy22wcWb+KHQvnU5qfB7haQToMv402A4ag0tbOif2bTUnklVqI9NUztktUrWzzUqxMWYndaSfWN/aSv6Q07tgVv+mRLH7fVUZ7/tSX6HX3/bQbcosoo32N8fb2pkmTJpw8ebLa14ODg8nJqTrnRU5OzgXHFGk0GjSaK+s+Ivz3JBQl8NqW1wC4v8X9DIweWM8RCXXFUWqleEki5Qdc10mFpxrvWxqibe5Xb9cBs8PJorxivkvPZ39pWeXyth56xof7c0uAN3JjPru/eJTg8mRO0ICFNEXv6UtERASRkZFEREQQFBSEQqE4775sDhtTtk1h0alFANzb7F6eaf8MCnn177MXWzBuzaBkexaHim0kW53IkGPTFHPXhJ4ExtRtVzgQSZAgCDWwW60cWreSnX//gbEgHwA3bx863nI7rfrfjEpTe3e18o0WvtxwCoBJg5qiVl797gKnu8JdbCvQv/mGuspor/zqE45t2cD6n74mK+EYAx95CrVWzAFyrTAajZw6dYp77rmn2te7du3KmjVrmDBhQuWyVatW0bVr16sUofBfUWIt4Zn1z1BuL6dLSBeebPtkfYck1AHJKWHamYVhRTKS2QEycO8WiufAKOSa+vmanW628lNGPnOzCii0ucpcq2UyRgR5Mz7Mn3aebmDIgNXvYd/xDd2crlarZpykP5vZXdKKXUdaceTIEQBUKhVhYWGViVF4eDg63ZnrmsFi4Jn1z7ArexcKmasC3J01VICzZhgp3ZRO+cF8yu1OdpkcFFXMd2RyS6HbyMZXJQECkQQJgvAvNquFQ2v+Ydfff2AsKgTA3ceXjiPuoGW/QajUtX+3++M1CZisDlqFezG0ZUitb/9CMowZ7M3diwwZg2MGX/gNNVBptQx58jlCm8Sy/qdvOL5tE3mpydzy7Ev4hYmuUfXhueeeY/jw4URFRZGZmcnrr7+OQqFgzJgxAIwbN46wsDBmzJgBwNNPP03v3r157733GDp0KL/++iu7d+/mq6++qs+PIVxnnJKTlza9REpJCqFuobzT6x2UcvGV67/GmmmkeMFJrGmlAKjC3PG5rTHqsEsvDHSlJEliS7GR79LzWZFvwFmxPEyj4t4wf+4K8cNfrYTcY7D2Yzj4OzhtKIEc/FA1G4pv+hrcSzLow3Z6yXaT5N6eDZbmpFq9SE5OJjk5uXJ/AQEBREREoA5U83H6x6SZ0mqsACc5JczHCzFuysCSaAAg1+Zkr8WJxSEhV0OR2yH0QRJduna5OgcMkQQJglDBZjFzcPUKdi36E1NxEQDufv50GnEHLfsORKlWX2ALlycxz8i8Ha55hSYPjkUuv/rdBpYlLgOgU0gnAvVXVo5TJpPR9ubhBMY0YskHMyjMSOPnlyZy86NP06SLKKN9taWnpzNmzBgKCgoICAigR48ebN++vbLqUGpqKnL5mZbHbt26MW/ePF555RVeeuklGjduzMKFC8UcQcIl+fLgl2xI34BGoeGDvh/goxXFUv5LnBYHJatTMG7JACfINAq8Bkbh1jUU2VW+hhntDubnFPFdeh4JZWcqVPbwduf+cH8G+nmhlMsgZRts+QhOLK9cJ0MZzXp7G/StRnDrbbeBwwZHF8P2z5Gn76Rh6Q4asgNraCdSQ4dxyBpOWnoGhYWF5OXlcbTkKNvyt2FVWNE79IxRjkFKkkixpxAaGooSOaa9uRg3Z1RODivJINlby8EkV+LoE6oj2bkZKyZGDBiFQi6nID0VQ14ODdp2rNNjJ5OkitFR16mSkhK8vLwwGAx4etZ/yUFBuN7YzGb2r1rG7sV/UWYoBsDDP4DOI0fRvM8AlKq6LVDw6Nw9LD+czU2xgXx3X92e8KojSRIj/h5BkiGJad2nMbLRyFrbtqm4iKUfvUNa/CEA2g+7lV533Yf8An2rrxfi/FszcWxuXBvTN/LEmieQkHiz+5uMaDSivkMSalF5fAHFi07hKHYlHLqW/ngPa4DC6+qOCUwwmfkhI5/fsgsxOlztPm4KOXcG+3JfmD9N3bTgdMKJFbDlQ0jbUfFOGcQOZae6O8sO5uLu7s5jjz2G/t+VXdN3w/bPIX4hOO2uZd5R0PkRTE1v49ejS5l9cjZ27PhYfOia0xWd40wXOblMjr/kQaDdiyCnF8EqXzzbRrArpZSUo64brXHdQyhQHODY3h34qhUEuenIPnmCVE0B5Z5yPpq5HHkNY4rO52LPv6IlSBBuUNbyMvavdCU/5aWuOQw8A4LofOudNO99Ewpl3Vdn25taxPLD2chl8MLNsbW+fYfdxsovPyEvORGf0HB8wyLwCwvHLzwSn5AwlGo1RwuPkmRIQqPQ0D+yf63u383bhzteeZNNv/zI7sV/sWfJAnJOJTBswguijLYg/AellqQyedNkJCT+1/R/IgH6D7EbLBQvOoX5SAEACm8N3iMboYv1vWoxOCSJVfklfJeRx8aiM3P7NNJrGB/mz53BvngoFWC3wr65sOVjyD/uWkmhhtajodtTZFrdWP711wAMHToUvV6P3Wmv2mUzvAPc8S0YpsKub2DP91CcAv+8iGrNFNR6NcGe7jRuMJC3ur1FcV4xyUdPkXz4FJmGHMqxkouBXKWBw4DC5obPGjMymwZkTrwCkzm5cx6ludnoATMQr7GzO66IpNAy1E4FablJRAU3qrPjKZIgQbjBWMrK2P/PEnYvWYDZ6GqO9g4KofOtdxLXs+9Vm+xTkiRmLHNNjHpH+3CaBtfuvBmS08k/n3/E0c3rAchLTa7yukwmxyswiJ2xBeAGbTVxlCSnowqPQKN3q7U45AoFvcfeT2jjWFZ8/gHpRw8zf9rLjJ76zmVNKCsIwrWpzFbGhPUTKLWW0iagDS90fKG+QxJqgeSQMG7LpGRlCpLVAXJw7xmOZ79I5Oqr06pfYLUzL6uAHzPzSTefmdtnoL8n94cF0NPH3VWBzlwCO35wteCUuiYxR+MJHcZD50fBMwS73c7Cr75CkiRatGiBxc/CA/88wN7cvYxrNo7H2jyGRnFWq5ZXGPR/HXpNwn5gHoXr3yTQVMQ9JRbGlpQi6XOx79mM7kQEMccVxNAEicaYQxXkhZWRknucvOMW5OUtkcmUOB0GbKbF5BTmVu7CqdeR3k7JFs8TWLAiQ8Ytsbfi5X3+uYWulEiCBOEGYTYZ2bdiMXuX/o3Z5LqD5BMSSudb/0dcjz5XvYvWqvgcdiUXoVXJeWZAk1rf/oafv+fo5vXI5HL6jHsIh91GYUYaBRlpFGakYTGZKMzJZF/zDAD0GzP45Y/nAFchCN+wiIqWo4rf4RHovbwvu9Rp487d8IuIZP7UlyhIT2XRrLe47aWpdd7dUBCEuidJElO2TiGhKAF/nT/v9XkPlUL8bV8rJElibWEpuwwmAtVKwrVqQjUqwrRqvJWKGs/r1vRSihacxJbhumaqIz3wua0xquDau1F2PgdKy/guPZ+FuUVYnGfm9rkrxI9xoX5E6iqSldIc2PEF7PoWLK7CA7gHQ5dHXQmQ9sy8P5s2bSI3Nxezp5nVnqt5Y/mZSZ6/O/wd69LWMbXbVNoEtqkSi0GyMbFwGzsD3OnuoeY1WQChWYeRnViO+sRyPJ0xlEt9SXOLpVBTTG5iIkVbslHq+6LUtAUZOGyJOCyrUXrrKZOHYdPoyPAzciDwCEaV6xgHOYIY5TuKLvou6OViniBBEK6A2Whkz7K/2bd8EZYyEwC+oeF0ue1/NO3Wq17Gp9gdTt5ecQyA+7vHEOJVuyWkd1V0PQMY9MjTNO/dr8rrkiRRZihmdfxyyhNmoJc0dA3sRLEtE1NRIcaKn9TDB6q8T+PmVpkY+YVF4Bvu+u3pH4hMfuGy3r6h4dw6eQq/TXmBtPhDrPjsA4Y++dxFvVcQhGvXnPg5LE9ejlKm5L3e711xgZXrncPhwGq14nA4cHNzq9f50pLLLbx8IoM1hSXVvq5XyAnTqAjTqAnTqgjVqAlVKPA5VIjn3jyCyiW0WiVeg6Nx6xhc54UPLE4nS3KL+S4jnz0lZ+b2aeWu4/5wf0YE+qBTVFwzCk7B1o9h/y/gqCiK4NcYuj8Frf4HyqrjlLKzs1m2bRmHAw6T7p4OWaCQKRjRaAQdgjrw/p73STIkMW75OO5pdg9PtH0CnVJHWmkaj695nCRDEnqVG7cFTcOy24sDRTvwVq8gTHcItTyJCF0SvlYVB3JCSC1uitrjf8iVwYBEZDMHnW+5Cf/I8TidEjM+n8FG5Uay9dkA6Jw6mhc0J9IYSVZqFgv2L6Bp06Z1eqxFEiQI/1HlpSXsWfo3+1YswlruqsriFx5Jl9v+R5OuPS5rsGFt+X13OqfyTPjoVTzSp3ZnT4/fuJaNc78DoNfd489JgMBVwc3N24edTtccCMNjRzL6vlcAV4tZYUZ6lVajwox0inOzsZhMZJ04RtaJY1W2p1Rr8AkNq2g1Cq9sPfIJCT1nbFVgdANumfgyf818neNbN+LpH0Cvu8fX6jEQBOHq2ZW9i/f3vA/ApI6TaBfUrp4jujSSJGG327FYLFit1sqfS3n+79fsdnvl9rt168bAgVd/ktgyh5NPUnL4LC0Xi1NCJZNxS6A3ZQ4nGWYrGRYbBTY7ZQ4nCWWWKpXVANADPVxdlv2UCsIUJYQfMROqPZ0wqV3Jk1ZNoFqJ/AoTvUyzlTmZBczJLCDf5jp+p2O+P8yfdp76M8lkxh7Y/KGrkhsV9c3COkCPCdB0KFRzYy3NkMazS5/laOhRqNjM4OjBPNbmMaK9ogHoFd6Ld3a9w6JTi/gp/ifWp61nXLNxfL7vM8gz0tEQTK/0WJKMf3LIXlyxZQ+08o609MmmrW82Hkoz4Z6+xDvvwSJ5oNXJGPBQayKb+bn+XWxlvL78dVZ6rMQpc6KQKRgbN5ZHWj+CZJFIS0sjLS0Nk8mEtpYmY6+JqA4nCP8xZSUG9ixZwL5/lmIzu5If/4goutw+hiadu9V7q4PJYqfPrPXklVp4fXgzxnePqbVtJ+3bzcJ3p+F0OGg/dCS973mgxjuQ5fZy+vzWhzJ7GT8N/om2gW3Pu22b1UJRZkZFcpRekRylUZSVgeOsC/7ZZHI53sGh+IW5ijJoQiNZ7B7InY1jUOzfzvJPXV+cbhr/MG1vHn5lH74eiPNvzcSxuTGcLDrJAysfoNBcyPAGw3mrx1v12uqRmZlJZmbmJScydflVUCaT8ciDDxMYGnRVjo0kSfyTX8KrJzNIM1sB6O3jwVtNwmikr/qlutzhJNNiJdNsI7XQROLBXNJNZrK1cnLdFGTr5ZRfxLFRyWQEa1SEaVRVutqdnSh5Ks+98ShJEtuKTXyXkcfyfAMVc4YSolExLtSPsaF+BKhVp1eGk2tcld6SN53ZSONB0P1piOoG1Rzf/PJ8vj74Nb8f+x07rmtVj+AeTOg4gaa+TbGa7exZnkzK4UIatQ+kea9Qtqau5tuVH6DOMRNQpMHfoEbpPPe7g19YBCFNYglpHEtok1h8AgPZ+/Nadu7UAjICVQkM8n4Xz4axSJ0f4R+NnHd3v0duuWs8UAv3FrzV7y0aeDe44DG+FKI6nCDcYMoMxexa/BcHVi7DZnHN/hwQFUPX28fQqGOXek9+TvtmUxJ5pRYiffXc3Tmq1rablXCcRR/MwOlwENejD73H3n/eC+6GtA2U2csIcw+jTUCbC25fpdYQGN2AwOiqJ2unw4EhN7tKYnS6BclaXk5RZjpFmelIu7azcNBdnIzx4a9tB9h5Uy96FOSz+defWPvDV7j7+tG4U7crPQyCINQxSZLYnrWdOfFz2JTh+jIa6xvLa11fu6Iv+ZJTQrI7we5EcrgeS3YnnPVYsktIjop17BXLHU4KDUVsPLGDtNRyZE4FZn1W5d3+S6FEgUqmdP2gcP1IrsdKSYFaUqCU5KicClSS6zXlv9Y7+/Fa1WFSFHks/mI+NzvbIterkOuVFT8qFJXPqy4/+7dMcfHXrqQyC68knOn6FqZR8UajMIYGeFX7b6NTyGmgURO4K48Gq1PpbXOCQoZH73A8+0aAUk6x3VHZcnT6d+ZZz7OtNmySRJrZ6kq6DKZqY/NQyAmtSIrCtWp8VUpW5Bs4ZjJXrtPN2537w/wZ5O+F6nS3O4cdjixwzfGT45puAbkSWtzh6vYW1Lza/RksBn448gM/H/2ZcrvrhmhAeQCPt3qc27vdjiRJnNiVzZb5CRiLsnDaUsk6nsXGOVlIzhLaowHOdKezKSV8vEKJa9WFiC5tCGnctEpxH7PJxrKv4kk94ure3rydip7eu1AcLeRExnZmbjjOLp0rCXWz6ejl7MOMsTNQVNMl/8PVJ2gU6M6wVqHVfrbaIpIgQbhO2awWCtJSyUtJIuvkcY5uWo/d6mrOD4xpSNc77qJh+071elfy3/JKLXy18RQAkwY1Ra2sncSsMDOdv95+A7vFQlSrtgx69OkLJn1LEpcAMCRmyBUdI7lCgU9IGD4hYdChc+VySZIwFhZUJkTzS22cDHB1/StQ65i0bBWfjhxFSX4uB1evYNnHsxj12luENom77FgEQag7FoeFZYnLmHN0DglFCQDIkNFd24lnpP+jfGk65f9KWHCcP3mR7FJF0uME56XHVIaFvcokjisy0ZrC8DS6phrwNofh4Z6LVoErWaEiQTn9WKpIVlCirHysQHY5mdPZ5IBcjkwho1AukWiPQinlk64oIM2RR0SpP85S6yVtUqZRVJscnf6t0KuwaOV8YTHxeXExVsnV9e3RiACejg7C7TzjXi0pJRQvSMCW7Rp7o47xxOfWxqgCzwzI91Ep8VEpaVFDAVO7UyLHaiOzIilKN1tdjytamDIsVgptDkodTo6bzBw/K+kB0MnljAr2YXyYP3HuZ42PtZpcZa63zgaDa0JxVG7Q/l7o8hh4R1QbT5mtjLlH5/LD4R8otbkqwAY5g2iS04QekT24rettZCZks+aHlRSkHsFhSwHJWGUbElDsbiXXx4KXNojjIfkkueWBLJVRTSKY2Ox/aNVnEqDclBJWfHmY0kIzCpWcPnc3JbZLCAZLKz4LCeK3xMU4kNA4nTxgKOEuQzbEdURhSAXfqr1BVhzO5sPVrr+vGH83mod6UVdEEiQI1wFTcRF5yYnkpiSRV/FTmJmO5Kx61Qxu2Jiud9xFTNsO11Tyc9rHaxIwWR20DvdiaMuQWtmmsbCAP6e/hrm0hOCGjbnl2ZcuOMdRkbmILRlbABjWYFitxPFvMpkMDz9/PPz8sTSM45fdx8Ep0U1mY6uk4m+3AIavXc2g+x/FWFhA4t5dLHhnGmOmvotvaFidxCQIwqXLL8/n9+O/89vx3yg0FwKgU+q4JXQoN+9sS3CRD2DBRFbt7VQGKOTIlDJkFb9Ryisf2+QO9ptPsd+UgF1yoDWF4m50tVIr5DIcNj3lxga0bR9AWKibazC/wpWcIJe5fitkyCoSFtfjit8K+b/WOfPeM+uc3o78zDpyWWXRgIzicp78ejvJBTI6KINoocxmZ2AabW6/CZnZibPMjrPMVuNvR5kdyWwHCSSLA4fFgaPIcs5hkoANAUrej9WQqXfd+OqSb+e542YaSOWU6jMxnZU0Kbw1aBt7o/TXUbIyBdNO16B8uV6J15AG6NsHXvK1UymXVXZ96+hVfdW4sopudxkVSVGG2Uq2xUacu45RQT54qc76Om4qgJ1fuX7KXf/f0PtD50eg4wOgr35eIovDwu/Hf+ebQ99U/j9t7NOYAdoBZG/JQuewE2Qt56vHnsRYmELlWCJAoVIRHNgQd5svS4N3sSPoFA4l3JZ+B+EZPWihVXAwbAUrDUuYf2I+mzI2MaXrFLqHdSd+cyYbfz2Bw+7EM0DH4Idb4BOq588Tf/LR3o8osrgmRh0Q0Zf+xwx0LN6IF1aInwvxP0PsUFcVu6juJBWUMWm+qyDR+DYBdZoAgRgTJAiXxVJWhrEwH7/wyFrdrtPhoDAznbyUJHKTEysTnjJDcbXraz08CYyKISAqhujW7Yhq1faaTH4AEvOMDPhgIw6nxC8PdaFrQ78r3qbZZOS3KZPJT03GJySU0VPfRe954ZPmr8d+5a0db9HMrxm/DfvtiuM4b4wOJ0P2nCDeZKa3tzuvaaw8eSqbeHdfYtIS+KZxKNHNW7Jg5uvknErAKzCIMdNmXReTqYrzb83Esbn+HS88ztyjc1mauBSb0zU3S7BbMHfF3sUw3QCsc9OQyu0oA3Ro4/zOSljkoJQhOytpcS2rSCSUFeuc9VimrEg0Tj+Wy6o9lzscDvbs2cOGDRswmVzdrkK0cdiTAwDoMCSapl2CWfnNEfJSXa0A7QZF0fmWGOSX0K3sSiTlmxj7zQ4yisvx0aswlZdzm/oQWpmd8FbdeODWARd1nZKcEs7y6pIk1+Mks4Xpagsbta6bgcEWiWdPWOiTabuk9ixd6wC8b2mIwq2eS5oXpcC2T2HvT1DRfQ3vKOj2JLQdC6rqq6janDb+Pvk3Xxz4gpyyHAAiPSJ5uOF4AlIVbFy8ELnRgNxRdeyqRh9I444dCNfE4J6kI09WxGsRn5GmyUYv0/F662m4H43h6NZM7FbXMc4PTmJDw1/Jc2ajcKgYW/AsulOuG5rRrfzpf18cx0zxTN8xnfiCeAAaeDVgcqfJBJQFMHfuXOQyGROGt8Izfi6cXF0ZjzOoJe+V9uPrwrY0MebxfsoSGi/8C9llVLC92POvSIIE4RIU52Szb/kiDq1bhc1cTr8HHqPNwCGXtS2zyUh+SjK5KWeSnfy0FBw227kry2T4hIQREBXjSnqiXYmPu4/fNZv0/Nujc/ew/HA2N8UG8t19Ha94ezarhT/feo2MY0dw8/ZhzLR38QoMvqj33rPsHvbn7WdSh0mMaz7uimM5n1cS0vkmPR9PnNy1fxMYiijW6pnf4SYcCiW3rPyVcCRQqdEnH0VmMaPw9Ma/50D07u7odLpzfrRabZXH1fWpvhrE+bdm4thcn5ySk03pm5gTP4cd2Tsql7fyb8U9ze6hf1R/7AklFMw9imRzUuBrZENgCaFNG9KiZXMa6rVnxnLUIkmSiI+PZ82aNRQWuu7y+/r60jKyO/H/GECC1v0i6H5HI2QyGQ6bky1/nuTQ+nQAQhp6MeCB5nj41m21rePZpdz9zQ7yjRaa+Cj5YHA4BeVOvl+1iyh7KmZJQW7ETUy9vS3hPpc3B8zpqm+fpuZW2/VNsjkrW5POTqBs2SbKD+XjNP7rGisDdZQn2lhfdLG+KIP0dX5dlZwSJ/fmolIrCPXMQL3nEzj8F0gO1wrBrVyV3uJGgKL6TltOycnypOV8tv8zUktTkTshtjyEAc72qFKN5Kck/esdauSqSDz8mtDjjpsIteop3ZSOZHZwSJfA9MhvKJaXEqgP5LN+n9HU11We2myyEb85k4Pr0jEVW7DJLRwMW09kYTMCTBFIOAnuo6D38BZ8uO9DFp1aBIC7yp1HWz/KmLgxyCU5X3zxBXl5eXTt2pVBgwa5Qso7Dju+QNr/C7KKxC/f6YnpuBp7th/h3/+GpsGlF08SSZAg1BJJksg4doQ9S//m5O7trgotFRRKJaOnvktww8Y1v9/pxJCX+6/ubImU5OVWu75KqyMgMtqV8EQ3ICAqBv+IKFR1XCqyLu1JKeL2z7cil8Hyp3vRNLiGztUXyel0sPj9mZzctQ21Ts//psw8p2BBTdJK0xjy1xDkMjmr71hNgD7gimI5nyUZuTx4wjVr9+BD24gqzMHT0xMvLy+WufuzJTAKj9Jixv/1BbbwhuB0oE8+htxhx+7uRXl4o2qr/fybRqM5JzmqLmH693K1Wn1FF3tx/q2ZODbXlzJbGYtOLeLnoz+TXJIMuOZP6R/Vn3ua3UPrgNau9fbnUvj7CXBK7PZMY3KLcIo9zvz7KiWJBjo1TT3caOqmpYmblqZuWhroNJedHCUnJ7Nq1SoyMlwTO7u5udGnTx98FJGs/CYeySnRvGcove9qes7f88k9uaybcxSr2YHWTUW/++KIbul/WXFUR5IkTEWFFGSkcejICRat34e+vJBAhwGN3Y5M7oHkKEDCSVlMc5xaHbLCAuxFRfj5ehMe5IvO3QONmztaNzc0bu5o9G5o3d3RnvVY4+aOWqtjZaGRV06mk252JTJ9fDx4s5qqb6fZC8opO5BH2YE87DkVc+4oQN82CLlOiflE0ZnlFRReGrSxPmhjfdE09Eaurt2bTNZyO6u+jyf5YD4AMhwEqk4Srj5IeLSc4IG3o2zSt8ZzvyRJrE9bzyf7PyErI4mwPC3RhZ6EFuiQrFVbexxaPQ69Nzp7Z3S6GDoNaUADrQLTxnScZXYsMitzo5fzp3YlEhJxvnF8ctMnBLkFnbNfh8PJqb257FyUhCHPlbCYlSZWNfmBDK8TKGVK7JJr/yMajmBC+wn461z/13bt2sXSpUvR6XQ89dRT6HS6ys9Stm0bc77/i+LAUsYpVhIqdyX5kkKN7NGt4F/z96uaiOpwgnCFHHY7J7ZtYs+yv8lJPFm5PLp1O9oPGcGB1cs5uWs7iz+YyT0zP0Lr7o7NYiY/LaWyZSc3OYn81KTKeXr+zcM/oEqyExAVg3dg8DVTya02SJLEjGVHARjVPuKKEyBJkljzzeec3LUNhVLJyEmvXHQCBLA0cSkAnYM711kCZDAYWL5tBy/KvUCloWX6KdrLHfQYOZKWLVuiUCgY43DSa3s86R7e7GjZlVEFKfR99BmyExPY+NXHKI0GGiocBHftjdlspry8vPLn9HOLxdVH3mKxVD6+FHK5HJ1Ox6233kqjRo1q+zAIwjUv25TNL8d+4Y8Tf1BidVUU81B5cHuT2xkTO4ZQ9zPVqYzbMiledAqn3cZcv1PM7tAOSSanWUYeMmsJScEhlOn0nDDbOGEuZnHemf2oZDIa6DU00buSotMJ0vmSo9zcXFavXs2JEydc21Cp6NatG926dSPnpJGlnx9Ecko07RxM7zGuu/Yr8w2YnRLDK6qhNWofSECkO/987eoet/TTg7QdGEnnEQ1QXEL3OKfDQXFOdmX1y6LM9IqiL+lYy8tA5oFcGUhzRSAyRQxyTSAyecWXT6kQq3ERmtw0yiObIPn44FmUiSO7mJTs5Ivaf5GnL2t6DCMpsgkA3uVGbk8+QCezgVPb3ck4K2lSybXIcu1IqVZkeQ7UCi0quRaFUomumR9eg6JR+ld0LRsK9iIz5mOFrp9TBhwGC6Yd2Zh2ZINSjrahF9pYX7Sxvih9ruxmZHFuGcs+P0hRVhkKrLgpCihxhJBja0qOrSl7joDihJyQhvsJj/UhvKkvAVEeyCv+j2xJ2cScFR9jS8yhRZ6O7qYz40cl7Og8vYhq1RaHLJj9WcdxqhS4GxrRvGUb2kV7YtmWRWlFYYqE4EzeC/6RFEsaACMbjeTFTi+iV1XfQieTySjKKqtMgDR6JenKNPL1rtZGu2RHgYLHWz/OQ20eqnyf2Wxm3bp1APTp06cyASrbu4+8Dz9k34ksZvV8HLtDiUbTiacHqZEf+hHsZvCr2+uSSIIE4V/KjaUcXL2C/f8swVhYAIBSpSauV1/aDxlROQ7Iwz+QzBPHKMnL4cdJj6PW6ijKykSSzi3xo1Aq8QuPqkh4XMmOf1QMOvcrSwiuByvjc9idUoRWJeeZAU2ueHvb/pjHwTUrQCZjyFOTiGje6qLfK0lSZRI0rGHtF0QoKChgy5Yt7Nu/n8XNO1PuqyHIYuLddrG0iruVLKud33KLaeGuo5WHnreaRnDvoSR2te5B8/n78FnwK0OefA4vvZ5F700n98h+GrdoyYDb/lft/hwOR2VC9O9E6d8J079/nE4nTqcTk8lUb93pBOFSZZuy+f7w90R4RHB33N2X3ZJ5OP8wP8X/xKrkVZV3r09vc2SjkbipzgxwlySJktWplK5JpdRcyKxIE9keLbl9WxmNcqwo7QpkMh/cNEbkxgTKLQUUustIC9CT0CiMk2EhlMkVlZXBLpQchUl2krdv4dD+/UiShEwmo3379vTu3RsPDw8yThSx/ItDOO0SDdsFcNO4WIocDp4/nsaSPAMAtwZ6Mys2AjeFAq8APbdPas+Wv05yaF06+1amknXSwMAHz+0eZzObKcysKPd/VqJTlJWJ02EHZMjkPsiUgcgVwcgULdF4BSKTVz9eRaGU47D74h7wAL3vasi2I6tISknB2aY36zJUOC1l6CUrXSP0tA5UYy8vw2IyYjaZsJiMlJrNrGvUlh0tu+JQKJE77HQ6sJnOezegtts4We1eq6dUa9AVeeJ2xBs3Hz/cfXxw8/bFreK3e29fPIcGociXYT1RjPlYIY5iC+bjRZiPF8Hfp1AG6V3d5pr6oo7ydBWIuEip8QWs/PowlnIHenkhQ7xnEtS5CyUtniIjx530Y0WkHyuirMRa+RgSUWnkKN0N5JXsQ154isb2csCVYMrkckKbxBHTpj3RrdvhsPuy8fcETpm24tQo0OPL6H5dURwuoPyEq0CBw0fO7y3WM7fgd5wWJwG6AKZ0m0Kv8F41xl5utLLq2yOkHXVtI6a7N6tC5rI6YxUAarsOpUNJmaaUjw98zLaje3lzwBRC/YPYtGkTZWVl+Pv706FDB8xHj5L34UcYN2ygRKVnet9nsCuUDGjkw4QHhuCQHHzj2IbKZmF8HXdLFN3hBKFCYWYGe5f9zZGNa7BX3FV38/ahzcChtBowuHLAvc1qYeUXH3Nsy4Zqt6Pz9Dqndcc3NByF8sa752B3OBn44UYS80w83rchkwbFXtH2DqxaxupvPgOg/4OP0XrApY3HOpJ/hNFLR6NVaFn/v/VVvuhciezsbDZt2kR8fDySJHEgvCHbGrZEI4Ol7ZqQYrHyc2YB6wpLK+vxdPFy46GIAH7JKmR1QQlRGacYtfh7uo+6m653jGHfP0tY+90XANz82DM0792vVmIF15c6m81WmRD5+Pig0Wgu/MZ/EeffmoljU7ssDgs/HfmJrw99XTnnyc3RNzOt+zS0you7O+9wOlibtpY58XPYl7uvcnmHoA7c0+weeof3RiGvekNAckrk/HGClO3ZnDIbSFPrcTdXbUGRyWVIzpq/SqktxajsRTjDPDHGRpIV6sVRrcQhyYqphvfJnU68yo1EK6BrZDhtA3xp6qZFn21m2ccHsFkcRLX0Y/DDLdlgMPLMsVRyrHaUFd8Z7RLEumn5rkUMDfRn/rZP7ctl7U/HsJbbUWllNG5nBSm1soWnNP+sDA0lMoUfckUgMmUgCmUQMoU/1d0/dyBh0Sto3SKAoChP/CPccQtWsOLkSpwrQyhKdl1T43oFsDlhAU7JyfDbR/P1fhMrjrgqtMX4uzH91pZ0beiHJEmsyDfw6smMyq5vPT20TPbTEmIzYzEZKTeUYEzMw5iUS1luEVa7GZvTjNVpxq60YZNbsdjKXS1Vl0Amk6P38sLN2we93huNpENdpkZtUqGVu6FTuqNTuKNz80Lf1M/VStTUt8bCCpIkcWBNGlv/PIkkQZDqOIP9PsTt1qnQ+n/nrJudmM+RjfGkHyvCZKg6V49rHRNuPhZiWgTSok8L/MN9MRksbPvrFMd3ZFOuy8TodRKFTMGd2l64Fbn+v8o91GR1M/Om4UNOGlzp49AGQ3mx04t4aWouKJSTVMKKrw5hLLKgVMtx9EjnO+uHWBwWFDIFo2NH80CTh0jcUcTXh79kp99KJJkTrc2dO2X3UZ6Ri9PpYEyvXrgtXkzp8hWu/zMKJdNumcwOyZtoPz2LnuyBExNfbhpNO3kCdgnC4z6lZdjNl/TvB2JMkCBcFEmSSD18gL3L/iZx767K5QFRMbQfOpKm3XqhVJ05sZUZiln47jSyEo6DTIZvSBhKjZbcpJPI5HJuefbla25unvr0844UXl5wGF83Nesn9cFTe/nVd07s2MLiD2aCJNHl9jF0v/PuS97G2zvfZu7RuQyOHsw7vd+57FhOS01NZdOmTSQkJFQu0zdrxccBDbDjmqX8iLGcfNuZftot3XUcNZVjPz0zuFpFns2GXYLhq34l9tRhhjz5HHE9+rBx3g/s+vsP5AoFt06eQnSrtlcc82mOUiuWZAPWpBI8B0Yh1156ki7OvzUTx6Z2nB7/8M6ud0g3urrdxPnGkVCcgN1pp4VfCz6+6ePzdm01Wo38lfAX847NI8PoGlejlCsZHD2Ysc3G0syvWZX1HTYnWYkG0o4UkLw1i8J/DaR3yMAzTEuLdiGEx/kSGOlBudFGUZaJouwyirJMFGaXUZRppKy0mkI3FdQ6BW6Behy+KlIxccRRQqq3hlR/d6wq9TnrBxXZGbeuFK1NojRci3RnJPvLzGwocs3x0livYXazKMwOJw8dSSbXYiW0rIQX3WXEGAsrEp10CjMNOOmNXOkqJGM378Zu3oVc4Y9MEYBKG45CFYTD4U51M64q1XL8w90p1cpZkJxHttxBh9aBfDCmXeXcb0arkcfWPMa+3H2oUHN/6WRkh10VQXUBTtJk2wkI9uWRRx5hZXwur/19mNxSV6I0uFM4BdFubDS4PleYRsXUxmEM8fcCp4Q5oZjyA3mUHylAsjrOxBWkR98mAH2rAJR+Z1qmnE4H1rJyLGVGykoMmIqKMBUXYqz4bSoqxFhUiKm4iLLi4mp7c9REI9ehVbijU7rj5umNR0ggnjEheEYF4+7rh87diz3/FHJip2sMcKxuDb1DFqC86ycI7wC4xg3nJJ4k+cBekg7sJSvh2FnTX8hwqgIo9wzDUx+HxhyMs+qwH7RuKqxmO06HhENuxhC0F4dkp6utCc0dEcjdlOh6hTDPfQnfHPkWu2THV+vLa11eo19UzTfXJEniyMYMNv2egNMhofaVWNn0e47hKmHdMbgjkztNponPmR4eDoeTVVu28O6J6eSq0umc05kmuT60PppAZFICOJ0gk+E5dCi/dhnFJ7vz0KrkLHisOzJ1Jn9uH0sXnau1SfLsyU3tvkEur7trk0iChBuS3Wbj2JYN7F26kLzUZNdCmYwG7TrSfshIIpq3PCeRKchIY8HMKRhyc9C6uXPLcy8T0aylq4vVR+9wfNsm3P38uWfmRxdVpvm/zmSx0/vd9eQbLbw+vBnju196hZfT0uIP8edbr+Kw22nV72b6P/T4JSeadqed/vP7U2Au4NN+n5636f98JEni1KlTbNq0iZSUFMDVV7p58+Y069KN0SmF5P5rcGqgWsnoYF/GhPgRo9eQbbHxY0Y+P2bmU2g7cxF3s1l48Ke30UlORr06ndAmsSyb/R7HtmxArdPxvylvX9L4p7NjdhRZsCQZsCQZsCaXYM8vx+a0UmTJpsn/9ce9+bkDYS9EnH9rJo7NlUs0JPLOznfYkuma0ytQF8jEDhMZEjOE3Tm7mbh+IsWWYgL1gcy+aTZxflUnGk4vTefnoz+z4OQCTDZXOWlvjTejmoxidOxoAvWBgOvvozDTRNrRQtKOFpKZUFxZEvi0PE8FiUFKZB7lvHlbRyL8L+4cbymzUZhlInfHUbK3HaE4pxyTLpByrR/Iqh+TI1eAe5AeyU9DqbeKTHcZ6TY7LTYVordIpPormdfLA5vqzDlQDkTKJcLMpQQU5uCdehLd8UO4m0rO3YHMHbkyBI17FyTOPy5S664iIMId/wgPAiI88I9wxytQz6+70nh54SEkCW5vF87bt7dEWTHGqMRawqOrH+Vg3sEqg+U7GwfQ/tgwnDZwKiwYvOK5+bbedOjQgRKzjbeWH2VuQTGOGA+Qy1ACj0UG8nRkIMo0E2UHcl3V3crOnF8VPhr0rQPRtwlAFXzlLftOp4PykhKMhQWYiosqkqNCTEVVH5uKiyq6B56HzA21+y3IlSHIcNDd4wci9DvY73s3Cr8o9J5e5CYnknJwH+WlVf+dDG420gPKyQgop3Xb3jzW4QmivaKx2xzkJJaQfryIU/tyKco6t5XLrjSiVJXTWRNCTJ9I8tuW8+rO1zla6BqbOyBqAK90eQVfbfXzDQHYrA42/Hyc4ztcrXTFoWn8GfYJNqWFIH0Qz3V8jkFRg2q8DlvtVj75+S0az99Lg8REFBVJXXF4W7weeoyslo14cM4eJAnev7M1bj4HOHjkOdrpXeOVvELG0T72tcu+oSySIEGoRlmJgQMrl7F/5dLKuXeUGg0t+vSn3eBb8AmpfpLKtCMH+fu9t7CYTHgFBXPb5Cn4hoZXvm4tL2Pui89QlJVBdJv23PbC6/+p4gaX46PVCXyw+gSRvnpWT+xdeYfwUuUmJ/LblMlYy8to1LErwydORi6/9DEsWzK28MjqR/DR+LDmzjWo5JfWKuV0Ojl27BibNm0iK8s1KaJcLqdNmzb4tuvIkjIHP2fmY6s4o8qA/n6ejA314yZfT1RyGXabjaR9uwiPa4HOw5Nyh5MFOUV8kZbLiTLXXdBGSfHc+s88lO4ejHvrfTz8/PlrxuukHTmIm48vd705C0//wPPGKkkS9twyLMklrqQnyYCtuByDNZ8CSxaFlkwKLVmU2AqQkBg1YRqRXS+9lUmcf2smjs3lM1qNfHnwS+bGz8Uu2VHJVYxrNo7/a/V/VQZtp5Wk8cTaJ0g0JKJT6pjRYwY3Rd7E3ty9zImfw7q0dTgr7uo38GrA2GZjGd5gOFqlFlOxpTLpSTtWRHmJtUoMGqUML4eJNeFW1rSJplQv5x5LCdMH9ryiEtj2oiIMC//myPKV7AtsQJlbCAq7HrVNi4fCG5tNi8Ne89cyuVJGcZCSUyozxTonBZ4K0gI9MOrP7c4qc0pEZRcRnV1KoMFJkFmDn0WLo6YaKjIIivYkqoVfZcLj5q0554voN5sSeXOp6wv1uK5RTBnevHLgvsFi4OFVD3Ok4AheGi++HPAlmcZMZu6YSW55Lj5lIdyW+CSqUjcknFj9U3nkpdFsMFmrdH2T55tRHjXQR6tlok2Ff+mZm0VydxX6VgHoWgegjvSol54XktNJubEUU5GrJakkMxfDqUxK0nIwFhRgdGgwq7uC3A2NrJRB3rMos2SyIrMJdunc65dKq8US7sYu3SlS/Y2YdA76hPfhibZPVJaqPq200MyWPxI4tdfVddFbq8BHLSfTVI7F8a9WE7lEjlsy6Z4nKPbP4MH+dzO40c3nPWbFOWWs+OoQBRkmJJnEzsgl7AtZjUqh4r7m9/FgywdrLJ4Arv/j+V9/Tf5Pc1DYXYniwWgZv/aSY9O1oE3ynfyp1VIuk7izbRgRjVaiyPmaplonTklGg8av0zDynov9p6iWSIIE4Sz5aSnsWfo3Rzevq5yHx93Xj7Y3D6dlv0HnLVAQv3Et/3zxMU6HnZAmsYyc9Gq1LT15KUnMe/lZ7DYrPUaPo/Otd9bZ57nW5ZVa6P3uOsqsDmbf1ZZhrUIv/KZqGHJz+OXV5zAVFxEW25w7Xp6GUn1uN5GL8dKml1icuJjRTUfzcpeXL/p9DoeDQ4cOsXnzZvLzXSVNlUolcR06ktOoGQuLyjhorFr9b0ywD883CCFEcybW3OREls9+j/y0FPzCI7nrzVmoda4LiSRJfJySw4ykbJAkV7e4xCOU+gbS6LkpDAvw5u+pL1a+d/Qb76B1d6/ctuSQsGUZsSS5kh5LcjGlhtMJTxYFliyKrTk4pKp3LjP9ykluaGdGn5k0ad/1ko+pOP/WTBybS+eUnCw+tZgP9nxAgdlVlKZ3eG8mdZxElGdUte8ptZYyacOkM61F+kByy85MP9A9tDtjm42lk29nMk8aKhKfIoqyTFW2o1TJCW3iTVi0J/qDuSSlbeOlfs3J8g9EY7MyM8CdMW2rdpu7HNnZ2axatYpTp04BoJIkYo/E0+ToUZQOBzJ3D5RDRuHsOpBSuRcZx3JJP27kQj20HJIJm85Oua+aMq0bqhIZ3sUO1NU0VjhlYPVVow/VExHpSXSgG/Fr0isnV23dP4KuIxui+NeNK0mS+HjNST5Y7apW90jvhrxw85my3EXmIv5v1f9xrPAYPhofvh74deUXeKPVyOz9s/nl2C8obWoGJN5LRIHreKZEK5nX3gO7UkaYSsmkcjUntmXyU5kJO6ADHlHquKtVGB5tA9E08L6kggRX29FNGaz/5ThOJ/gqUxniPQOLvStp5TdR7ijDojVjc7djVVnQR/hz2CuLX0qWUeZ0XUc6B3fmyXZPVpZlP81uc7B/VRp7lidjtznxUcroEKJHX2rFhJk/NNuxO+W0a9QDyaHjxOFMdGVVzz1KlZyQRl6Ex/oSHuuDf8SZynMAifvzWPNDPFazA7PayD+NviPL6xR9wvvwfMfnifCMqPFzO4xGCr//gcIffsBZMZFvQUAAjaa+ziK/U3x+4HNsdglz8mPYLWEE2WWMdZYR2vttvD0KcaCkTcvPCQy46Yr/DUQSJNzwJEki+cBe9ixdSMrBM4Nggxs2pt3QkTTp3P28xQokSWLbH/PY9scvADTp0oObH38GlbrmAeSH1q1k5RcfI5PJGfXqm5dUuey/QnJKfPDLAT4/lEGzcC8WPt79su7UlZUY+PW15ynKysA/Mpr/TZmJ1s39wm+sblu2Mvr83odyezlzh8w95+JSHZvNxr59+9iyZQsGg6viklqjwbtzdw76h7GiyIi5YlCzCkAmwyZJPBkZyMsNzyR9ToeDXYv+ZOv8eVW6TzTq2IVbJr5UpcVw/KEklucbCFbAiB/fxdNoIDmsIWtHjGechwqPr96hvKiAsNjm3DJ2Evb0MixJJZSczKLAmEGhJbMy8bE6zed8Jo3ejeBGTQhu2ISMIDPvpH+B1WllYvuJjG8x/pKPqzj/1kwcm0tzOP8wM3bM4GD+QQCiPKN4vuPzF+y2arAY+O34b3xz8BvKHa4vkXKZnFuib2GE12jI0JN2tIjsRANOx1lfd2QQGOlBeJwvEXG+hDTwwllkJu+L3fxZuIV3B/fDqlYTZizh+87NaRXod0Wfr7i4mHXr1nHggGs8hVwup0OHDvTu3RuN2Uzhn3+SuuBPCg1FlOg0GHQaSt39UHjciVzhg9NRiNW4BLlch6T0R+0RiV4bhN2ux2auuZVdppLjDNCQ6a3ggN5JpreSPC8FduWZc7JSBs20WvocLMNrbzEAgdGeDHqoOZ5+Z+ZzmbH8GF9tTATguYFNeLxvo8pze0F5AQ+ufJCTxSfx0/rxzcBvaORzbnnjIwVHmLptKkcKTtI2dwKdToUhB7K9Fchj3RibUI6uotEnUSHxnsbKgYpW8raR3sy8rdUVT7NQV5wO1wS1B9e6xq7FaLbTz/9rFP3fptzWDfOxQizJBjgrobXL7CRqMkjQplAe4KRnx/60a97lnCQv+VA+m35PoCSvHE85tPHX4lMxHkqSwxq/oySXZhISFoKmq4bZ+2djcVgIdkQw3ucJ/AujSD9eTYunXkloY2/CY30xFprZtyoVgCyPRFY1+Z4Afx9e6PgCPcN71vy5y8spmjePgq++xlFxrSzx82N/82Y0GzuWnr1cf8Mni05y94+LycluAgoTDULm81B4EoGeRdjNHtjSXqFlj75ENvO94tY9kQQJNyyb1cLRjevYs+xvCjNc9e9lMjmNOnWh/ZCRhDaNu+AfmN1mY9WXHxO/yVXbvuOIO+g5etwFu7hJksQ/n3/IkQ1rcPP24Z63P8bN26d2Pth1wFFqJeOnI8jTjJQhQYwnYR1Dzls5pzpWcznzp75E9qkEPAMCGTP1Xdx9L/9LyLLEZbyw6QUiPCJYeuvS8/77m81mdu/ezbZt2zBV3M3CywdTuy5sUXuQaD5zEWnqpuWuYF8W5RWzp6SMth56FrVrXNldpigrg+Wfvu8qpAE06tiVFn0HsPj96TjsdrrdeTddbx9Tub00s5VeO45S7pR43VdN2axXwWrhQFwHVvYaQXBBDnf9/TUKmwVvdSDuSh+KrNmY7IZzPodCqSQwuqEr6alIfHyCQ5DJ5axJWcNzG5/D7rTTN6Ivs3rPQq249BY2cf6tmTg2Fye/PJ+P937MgpMLANAr9TzS+hHGxo1Fpaj5nJFkSGJu/FwWnVqE2eFK+IPsEfjlRxJuaEpkaSxKW9UbVh5+WiIqkp7wpj5o3c9s35pWSvpH//CuVxYLeri+8PUsL+Gr/l3xUV9+QZfy8nI2bdrEjh07cDhcX1qbxcXRsmEDzAU55CadIjcpkfy0lKpjTGQ61B6jkCv8wV6M0bacvbFNcWvbkak9OxDudmb8i6XM5irIkG2qHCPiXzGOxztIX3mnv8Tu4P+OJLG+0FVwIFSjwux0VhmX2CTDyi07TOhsEja1jNLBIcS2CWT9znSWbEtDBrw2rBn39zgzxjOvLI8HVz5IoiGRQF0g3wz6hhiv6seASpLEsrwiJsWfpFBSE51jY9SWErQ2GSoZtHdTENnMD33rAHTN/UCt4OcdKby94jhGix2VQsajvRvyWN9GaFXXTml/s9HGP98crihrDR3dfqVj6FZkd82DkDM3Q53ldk7uPcSh7TtoUhiBj+Pcc4NMJUcV6o46zB27l5r9+/I4fqwYdzk091ARJKsoVyEDfdtAksNKWbRqCWWaMtKap3G46DDgagWd0m0KwW6uAhiSJFGYZaosv515ogir2XHO/g+GrGd/g5X8X5uHuKfZPTVeGySrlaL588n/4gscea5eEuoGDcjr348VBgNe3t488cQTqCqKS/25J51n5x8AJPQR36NwP4FGJjHcXUvI1uewGV3dvH2C9bTuF0HTzsEoL3OiWpEECTccY1Eh+/9ZyoHVyzFXDDJU63S06DuQdoOH4xUYfFHbMRuN/P3em6THH0Yml9P/wcdo1e/iSzTazGZ+fnkiBempRDRvxR2vTLusMSzXG0uSgdy58chM1fS/kIE62hNdnB/aOF9UATX3J3bYbSx8ZxrJB/ai9fBkzNR3qoy/uhyPrX6MTRmbeKT1Izze5vFq1zGZTOzYsYOdO3diNptxAoXhMWQ0ackup7yympteIefWQG/uDvGjraeeD1NyeDspGzeFnDUdmxKt07hKoq5cxoafv8NusaDW6blp/MM063UTMpmsssUQmYyRk16hYfvOlXF8lJzDjKQsAuRyvjyaxLZ13wASh1r0ZEWPQURmnOKOpT+hcDoo9PLDu6QIORK+oeGEVCQ7wY2aEBAVjUJ57pe3ZYnLeGnzSzgkB4OiBzGj54xLHh91mjj/1kwcm/OzOW38cvQXPj/wOUab60v5LQ1vYUK7CdVWepMkiSRDElszt7IhfQPbs7ajsekJK2lCi/LORJTE4jBUvUllU5oJa+pNXKtIwuN88QrQVXsDxJxQxKH3f2Zy+yCONHTNTv+kRuLFrm2QX+YdaZvNxs6dO9m0aRNmsytJ81DKcSvOxZSeAtV89dK6uRMY0wC/iCakHQ3DaFCgtJXQcc8sdBXdA3Xt2+Mz+n94DByI/DLK2jsliU9ScpmZlIUEtHLX8maTcHIsdvaXlnGgpIykrFIGbi4hvND1BXl7Ew1rWulxOiUaa9UMDPOljYee1h46VI5CHlr1ECklKQS7BfPtwG+J9Iysdt8ni8t4+VAKG+yulp3gcif/d7yY/IIdeBriUNlcfycdh8XQcUg0srO6aWUZynnt7yOsis8BoEGAGzNva0WnmJoH918tBZlGln12kJJ8M0pZOf29PqZhIyeM/hncz4zftDlsfHnwS7459A0OyYGvxpeXmj5PD0VHbOkmbOmlWDOMSJZzExNnxXxRp4+IpqkPXkNisOidzP50NkdURzgacBSrZEWv1DOp4yRub3z7eW/4OR1O0hLzWbp5HZnHDaisWvaFrSa2UygT20+sLBzyb5LdjuHvReR/+im2zEwAVGFh+D/xBLLevZj9+efYbDbuuOMOWrRoAcDRrBJu/WwLZpuTiJB/eLDJMv4oVpNsdX03au/XgZGmB8jd5sBWkZhp3VXcPqk93kE1f1+oiUiChP+UEmsJ3x/+niY+Tbg5uuqgvtzkRPYsXcixLRsr76R5BgTRbvBwWvQdiEZ/8X9AxTnZ/DVzCkWZ6ah1OoZPmEx0m/aXHG9Beho/v/QMNouZLrePpvudYy95G9cLSZIwbsqgeHkSMgmScPC5l8Q7I1vikWbEfLQQ27/73wfo0Mb5oWvmizrSs/JiJzmdLP/sA45uWodSo+HOV6cT0rhpdbu9aAXlBfSb3w+H5GDxyMVEe0VXed1gMLBt2zb27NmDzWajRKMnrUEsR4MiyT/r7NjeU8/dIX7cEuiNu9J14t5tMDFiXwIOCT6Ji2RUsC+lBfn888VHlV0wI1u0YtCjE84pZrD62885sHIpap2eMS++ja5MT8HhJFKOn+CJjg3I8XSnw8Ft9N26tPI9RR4+bO3g6i89dN2fAOzqMZRuQ4YzLjIYb9X5S4kuSFjA61tfR0Liloa38Ea3N1BeRvnR08T5t2bi2NRsa+ZW3t75NokGV9eqZn7NeLHTi7QJbFNlPYPFwI6sHWzN3MqWzC1km7KRO+W0yrqJBgWtCTBFIDurhLNcLiOogSfuMTJ+Kvmcg7Kd6FRa3un1Dr0jelcbi2lPBiu++IZXh/ai0MsHd4uFT5qGMTjm0m68SJKEqaiQnKRT7N+3l2MZ2ZVFUuTmMjS5GShMhspo3Xx8CYppSGB0AwJjGhIY3RDPgEBsFgcLPtxHfnIpJo2MOX3c6Vd4ikd2bUDatAkqWpMU3t543Xor3neOQhNz6ZU31xeW8Fh8CoU2B74qBZ83i6a3r6ubmVOSOFlazqa/TmLe7rrDn+Gj4K9u7hS7V72hp3QakVtO4SPl8UKrW+kfGEmg5sxNFcnupOh4AR8mZvO93o5NLkPllLgnycr/lanwbRXA72krSD+ZicoUjrfR9VmC49wZ+mBbtGf1IJAkiRWHs3lt0RHyKsppj+kUyeTBsXjpLr+17kok7s9j9ffx2CwOPBQ5DPGegX+H7jD8Q1CeSVKPFR7j5c0vc6LINZ5qUPQgXur80jkV2pwOJ0mbMjn5TzLuZjtBKjkauayaQuUg0ynJURSzXbGX/R5HSdCm0CC8CVN7TCXMvfoiT6fZHDb+SPiDLw58QaG5EHD9Hb7Q8QXaBbWr9j2S00npP/+Q9/EnWJOSAFAGBOD36CP43HEHMrWahQsXsn//fsLDw3nggQeQyWSUmG0M+3gTqYXl+Hsd5a2OX6CUS/j49uWgsiuf7v8Cs8OMTqnjyZZP0TynB/tXpqHSKBg7tWuVZPhiiSRI+M/IMeXwyOpHOFnsmtyrVUArXmj/PPo0M3uXLiQt/lDluqFNm9F+6AgadeiCXHFprS+ZJ46x8N1plJcYcPfz57YXXicg6vLLOh/dvJ5ln8wCmYzbJ0+5rGTqWuc02ymcfwLzEdddypXYWBai4osHOuHvfuYCYC8yYz5aSPnRAiyJBjirb75cr3RNNhfnx849C9iz/G/kCgUjJ71KTNsOVxzjvKPzmLFzBi38WvDLsF8qlxcUFLBlyxb279+PTYJkv2ASo5uQ6OZdOaGpj1LBqGBfxoT4EudedUb0EruDfruOk2a2cluQD7NjIzi+ZQNrvvsCS5kJpUpNz7vH03bQ0CrdKCVJwl5gpvhQKvsWLsZcVorRVkShJQtLxcDYpPBG/DHsPmROBw/8/S3hFiOm4kIUShUjJr2MPq41P/48B8U/fyEh4++Bo8lo3JL/BfvyYLg/DfXnTh7527HfeHPHmwDc0eQOXu3yKvIaSvReLHH+rZk4NudKL01n1u5ZrEldA4Cv1pen2z3NyEYjkcvk2J12Ducfrkx6DucfrqzuBuDm9GTIqYfwyz/T0qANkBER50fjFiGENfFBXTHflcFiYOL6iezM3okMGc92eJZxzcZVuYFWtHQ/n69ZxKdDhuBQKGlUbuTHXu1o6H7xN87Sjhxk95IFZJ1KoNTuxBIYjlPrer/MZkWTl4GfVkVQdAOCYhpVJj3VdZO2Wx3M/WAvpqRSytUy5t7kwd2tw5gQFYxKLsOWk0PxH39QPP8P7NnZle/Td+7sah3q1w/ZJRSOSTNbeeBwEgdLy5EDkxuE8ERkIHKZjHKrg4fn7iHjSAFDytRoJRkKrQLtLRHEh6nYWVzMMZMVZOdeZ4MdMpqbIc7gwKvExrdRKrJ1rnNNN4OT1/VeNGsdjCrI1aXPZDLx8ccfY7FYyFaWE5fRF6WkRuZp5/bHOxEU5V1l+4ZyGzOXH+WXna7u7oEeGqaOaM7NLUIu+rNfKckpsXt5MjsXu5KBMPUhBnnPQnfz89D1Caj4f2Zz2vjm4Dd8dfAr7JIdH40PL3d5mUHRg87ZZmGWiU2/nSD3eBGNNXJitApOH11VhAeaRl5I5Q6s6aX/z957h1dRre3/n5nds2t6L6SQBJLQewcBEbFg7w27Hj3qsR17770XxN6oKioKCEjvJZCQRkgjPdm9z/z+GAxEioDnfb/H3+t9XblmZ++ZNTNr9l5r3U+5H8WwGD50+S6aNWiTzWhTTGhSlK3KdOA7IckSi6oX8crmV7rqbqWZ07i5/81MSp902DlBlmVcy5bR8vIr+EtLAYWER199NZEXXoBoUObGhoYG3nnnHQBmzJhBSkoKsixz6Qcr+bXMQYS2nSeHP4NJ6yE56QJ69nwIUVRT46jhgdUPsKlpEwDDIsYwYOVZqFQqpt8xgKik45c+/5sE/Y3/X6Cqs4prF19Lo7uRKH0UQZ+P5GqRXtUWLB7F8iOIIj2HjmTA1NNJzD4xr0HZ2pX88NoLhIIB4jKyOPOuB/5UDspv+Pnd19i++EcMZguXPP0K5uiYP93mfwsCDS7aPi0h3OYjgMwr+GjLtvDWJQMx6o7sXZB8IXxlHQopKm1H9ireu1L7Ora1LwNg3OQrKDrrVNTW4w/3OBghKcSFCy+kpL2EuwffzUX5F9HY2MjKlSvZuXMnbQYTpQnpVCal4z4o/2B0pIkLE6OZEmtFd5g8MFmWuWHXXuY1d5Km1/JNXiIbPniLsnWKQlVCVg4n33gb0cmKkk7YGcBX0Unrlgo2rv+OFmcN7lDnIe2KooqYhDQS8/J4p+dAVqBjkCWC+X0ymff0w+zdvgVTZBQXPv4CpqhofnrvDYoX/0BYrebLqVdQn6goaE2IsnBNaiyjI00IgsBHOz/i2Y3PAnBR/kXcNeiu/4is7N/j75Hxd98cgDfk5f0d7/NB8QcEpAAqQcUFeRdwfd/rcQfcrGpYxeqG1azdtxZnwNnt2ERjIpG6SEJ2gT6bTiXam0RQ9LM2/RuqI3fg1in5cGatmSxrFlm2LHpYe5BlyyLdnM7M4pnMLp8NwPSc6dw35D7Uopqa1+fzb28TiwcOBWAqAV4ZPQDjMRrPQoEAK7/8mE0L5xPWGfDHpRA2Ks9ZJUBOUiJDhgwmMSvnmARdnL4Q77y0EX21B78alp4czSOjs+lvOXQBKIdCuFb8SueXX+JasaIrtE4VHY1t+pnYzjsfbcrRPQG/wReW+Hd5HZ/uU7wBJ8dYeKJHMrd+vIn1ezswqEVe6JeBY3MHrW1KWF9mlJoE0UGEZGKPWcMui4pdVhW7rCJ7jCLyYcaWJEngoaQ4Ts2NRzzMmLp69Wp++ukn9BF69iTtI2PDCCz+GMJiiF5nRHHSpEMNYmur2rh37g6qWpVIg0m94nnk9AISrIcagf6TCPhCLP2whMotikR1YcR3jIiZi+rsd6DnpK79drfv5r5V91HarhCHiekT+feQfxNt6L62CHhDbFi4h11L68jUCmTpRNT7+1CbbsEyKR19lq1r/0Z3Iw8tf5DmmjpyfOn0D/RmuHoAQmuwm+jCb1DZdGiTTWyJLuctz4fsdivFvaP10Vzf53qm95x+xJBo99p1tLz0Et6tWwEQjUairryCqMsuQ3WwQqksM2vWLPbu3UthYSFnnXUWAHd/u4QvVvkQhRD3Dn6JHtYaMjNvIyP9hm5zkCRLfFH6Ba9sfI0pW64jxpOCGN3KVQ+diVZz/F6+v0nQ3/jLY2vzVm5aehN2v51MYzrXuk+mctkKAh4l8dOvDlOV4WPAyadzxbDr0KuPf+CTZZmN385lxacfAJA5YDBT//EvtHrDHxx5bAgFAnx2/x20VFeRlNuLcx944qiKdH8VuDc20jG/EkIS+5C4Hw/5/RJ5+qyi46oHJIdlAnvtbP/uR1as+gSAPlFjybMqOTKaJOP+sLloNEnG41q4h6Uw96y8hx/2/IBOpWPmsJkUrytmZ0UllbHJlCSm02Q9MBklaDVckBjF+YlRpBuOTr6+amznHyU1qAR4wxCk4f2X8dg7EVUqhp51PoOnnk2wzoWvrBN/eQfBfW7q3eWsa11IUDpQpMNqjScyPom6yp2EwgEGn3Euoy64FIAGX4CR60vxhCVezkvjDKuOz+//F211NcRmZHL+w0+j1mr55vknqNy4DrXRRPElt/Adhi5PVq5RT0FwESsq3gPgqoKruKX/Lf+xuhp/j79Hxt99s18oZu8int/4PI1uxXMxKH4QkzImUe2oZlX9Kqod1d2OMWqMJBmTCEkh6px1BOUgsa40ppReTUTQgl/nRjp5L+q4EJX2Sqo6q6hz1XXzGB0Mg8qAVWel0aOcP9uazYw1fXiid18qUzNQSWHujTNzQ0HOMf8uWvbu4fvXnqelpppAbDKBGMUDoVKpGDRoEKNHjybiOMKwt3S4+fLNraTW+AmooOPsVO4anXlEQuYL+WjyNNHobqStuhTVt78Qu3Q7hk7FkxzUiBgevouc6Zcecqwclgg7g4QdfsL2AJLDT9gRoKLRSW2rC703zIseN7sJYwSeJYIi1EiyTIlPosKv9LNNJTAwQoVRLSCatKisWlRmLT6rlt0WkWI9FIthquUwE+Ks/CMjgQjVkeeGUCjE66+/TkdHB6NGjaI1toNtX7SQ3K4YNgO5TVx5zVSsxu6/JV8wzOu/VPDmskpCkoxZp+bOKXlcNDitm/TzfwqOVi/fv7mdtno3IiHGWN6iV3IVXPAFxOUBivfn/R3v8/a2twnJIWw6G/8eonh/Dv6OybJM2fom1s0pJ8EfJlsnot1/zZpkE9ZJ6eh6RnYdI8sy31Z9y1PrnsIZdCJKIkNDQ3nlslfQaXVIgTDBfW7FU1TnIlDnJNTqpUy3lw/i5rPVqAj0GMJ6zvNO4dzIM7GlxqJNNqNJNiIeZLz0bttG80sv4VmzFgBBryfq4ouIuuoq1JGHejFLSkr48ssvUavV3HTTTVitVh5Y8gkfL7YBIpfkf8HY1HXk5z9BUuLZR+zf72ZuZO96B161i7lFT/PR+PvIzp5y/M/pbxL0N/7KWFa7jH8t/xe+sI8+kYWcVpxJ7batANgSEkkcPZgv1cvZ3KnIjSYZk/jnwH8etYLx7yGFwyyZ+SbbF/8IQL+TpzH2shn/cRGDjsYGPrn7VgJeDwOnTWfMxVf+R9v/34QcDNOxoBLPRiU5dTVBHsPHBaN7cNfJeSc06ezZuon5zzyCFA7Tb9ypDMybiq+knUCNAw4anVRWrUKI8qPQZdkQjkK2JFni/lX3803lN6gEFadKp9LeFkNJQjoVcSkE9wsGqASYFG3lwsQoxkVZUB/D9e/x+Dlp427cYYmzWqvJnK0QjLSUAkaMOh9Nu5rAHjtyUNp/LWG2tS+nzLEBgPjULEZeeCkJubldFuKdy5fw4xsvAnDa7feSM3g4AK/tbeKxqn1Ea9SsHpIHHW18dt/teOydZA4YzOl3/JtwMMjXj/ybfRW7scTGM/Lfj/OpK8TnDW3I7V9jdCwAoDDtUp4b9g+S9H/Ou3Yw/h5/j4z/632zu303T61/io1NGwGwaC3ER8Szx76H0EH1qkREkkxJaFVaGt2NeEKebu30c41m8K4zEMIqrIl6Tr+5P+ao7gYvf9hPtb2aKnsVlZ2VVNmrqOqsYq9jb7dzIQMCSGIsnfG3YwxaGaFfxZAYK1m2LLKsWaRaUo9oFZcliY0L57Pqi48IhcME03rij1DyaAoLCxk/fjyRh1kgHgkhSeaV6kYqvqyk994AIRHSL81iQG+RRndjF9FpdDfS5G6i0aNsO/wdh7SlCsv0r5A5Y51ATr2SN2QfN5GsCTcguMKEnQHCdj+SO9htXD0Y7Uj8Ew+VSFgReFZtpCjKiMqiQ2XRYte6+WrXEvT1vVGH9Wj0IuMv6UX2gKMXbz5W/H4hHdQEeWfWPKw7MhEQabfU0//ieE4pnHjIPF/a6ODuOTvYWtsJwMD0SJ6cXkhO/H9OTrtudweL3inG5w5iEDuYYnuaxNx4OOdDiFBye8o6yrhv5X2UtCvFZCekTeC+ofcRYzgQBeJ2uyneWsr6X7Zjs0cwTEhAv987po6PwDoxHX3v6G732Opt5eHVD7OsbhkAkf5IBrUO4vbLbycp6fB1+PY69vLKxlf4qfYnADSoOdU9jnPrT8IW7t4vkizh1/swF6jxL52D5xdFGReNhshzzyX62mvQxB3+OYdCId544w3a29sZNWoUw0YP486lj/P9r4VIITPDE9cxo2gefYpeIzr68Ll5ALtXVLD4sxpAwpb0DN6iWGac9jGcQOH5v0nQ3/jLYk7ZHB5Z+wiSLDEqcSQTtsZTvWkjao2WyTfcSu7QkQiiiCzL/LDnB17Y9AJNHmVR3j+uP3cOvpPe0b2Peg6/x8N3Lz1F9bbNIAiMu3QG/U85/X/snsrWreLbF54E4PR/3U/2wCF/cMR/H0KtXto+LSG4z40EvIePjwnw76n5zBiVeUJt7ivfzVeP3kvI7yd/5Fim3HhbV/5M2BXAV9qh5BGVdXSRCgBBK6LPiUTfKxp9Xnf5bUmWeGTNI8wpn4OISJr3ZKqST6HNdKDAbYZBy0WJ0ZybEEW87thd7UFJZtrmcrY6PfRoaeDWRctI0meQGpmPOtTdwyeatYSSZVZs/5ymeqUw4oCppzPqwssPq9r2y6x32PzDN2j0Bi56/HmiU9IISBITNuym3OPniuQYnuyZQkNZKV89cg/hYJABU89g7KUz8DjsfH7/HXQ27iM+M5tzHniC53e8zuclHwHgsp2H13IqagGmxdq4OjX2sGE2x4u/x98j4/9q39j9dp7b+BwLKhYgH2G1HamLxKazYQ/Yu5Kyf4NJY2JwwmCGJA4lvjyf0h/aQYa03lFMnlGA1nDsnvSgFKTWUUuVvYrmtatYtdPBLz23oAq3AHrCohqV5Op2jFpQk2ZJI8uWRaY1k0xrJlm2LKKDRpa+9Tq1u3YgqdTIeX3xSEq9n9NOO42+ffse0/W0eFpodDeyzd7KG40RFK0V6F/lJyzIrCqcxy7j8mO6N4PaQIIxgfiIeBKMCSREJFBU04O09QaCW2YTrFqq3E/acPR9L0Y4WABFFFBZtAf96WjWwtUb97DX5UenU+HvG4XPpuXqlBgeyEqmqrOMq3+6mg5/B30MA5m25zpa9yhhaIXjUhgxPRuV5s/lGMqyzIcffkh1dTUFBQWcfbbiMfhh+a+Ufu1AGzLgVbtoGraZW0+/+pDk/7Ak8/Gaap5dtBt3IIxGJXDjuGyuH5uFTn3ixk1ZltmxrJ6VX5chSxCnLmdK5NOYhp4JJz8FKg0hKcTM4pm8ue1NQlIIq87KPYPv4ZQepyDLMg0NDVRUVFBeXk59fX239rPCCYwx9SFmUhaGPrHdhABkWebH6h95fN3j2P121IKaQmchGS0ZjBk1hgkTJhxyva3eVt7a9hZzyuYQkkMICJyaeSo39ruRRHU87pIWGtfvorGygra2vXR46+kMdyAdFEsnShIajRZ9ZBQ6kxlthAGtIQKdIQKtIQJthPJaozdQU19P8a4S9CYT486YyAvFr1JSPgynP5t4cxMPjvqQIf3fxmIpPGIft2/fxNdvNhOSdQyyzGXw5ZOg12kn/Mz+JkF/4y8HWZZ5Z/s7vLb1NQBO73EagzZGULFuDSqNhjPufICMon6HHOcNeZm1cxYzd8zEF/YhIHB69unc0v+WbtaX3+BobWHe0w/TWlONWqdj6s3/InvQ0P/x+/ttkaszGrnkqVewxsX/j5/zPwXvzlbavypD9odxifBvyc12lcTz5/bltD6Ht0L9Edob6vj8gTvxOR1k9OnPGXfef1hyACAHJXyVnfhK2vCWtCMdXPBNUOKmDfnR6PIjeabqRb7c/SUCAuneSWzIVZT5tILAtDgbFyZGMdxmOu6QMDkk8fCWPbzlcmIKhPl8tYdE/0E7qEV0PSzoe0aiz4mktmEXP7zxIj6nA12EkcnX39Ll4TkcwqEQcx6/n9pdO4hMTOLCx19AbzSxssPJ2VsrEYEfB/akyBxB6eoVLHz5GQBOmnEDfSaeQkdjA5/fdwdep4Nwho1P8rYhi3DXoLuJip3KO7UtrLUfUOkbaIng6tRYpsbYjskDdjj8Pf4eGf9/6htP0EODq+GwxS9BUZra3LyZD4o/YO2+tYTl7hK/WlFLnDGOYDjYZbD6DWpRTZ/YPgxLHMbQpKH0ju6NIIv8+kUZO39V5HcLxiQz6twcxKOEUx0JsixT/eEn3G4PsrqoP0LYQVbLy9gDZYiCyJiUMZi1Zqo6q6iyVx3iiUKGzAYjQ3dGoQ2JhAx6fNm9kEMiGp2Gs845i7zsPMJSmBZvy6EenP2vm9xNtHhbkJDxmcbjsl7A5G1hBpf7kZD4ueeH7IneCoBOpetGcLqIzkGvLVpL1xgWavXSPqcM/x47Vbo6RKuW6NLt8OtsBFlmX5KV+hnnMm3ExZijbYgRmm4L7epWNxe9t476Ti/JNgMfzxjMlw4nL+9VnlVBhICz+m48vjoKogt4a+JbmNRm1i2oYstPSnHN2DQzk68uwBr750LJ9+3bx9tvvw3AVVddRWqqklfZ2mTni1dXIrQakJDYkr6I4VPzuKzg0kM8dw2dXu6fX8yS0mYAsuNMPDW9kIEZxy+nHQ5KLP9iNyWr9gHQU7+ccba3UU99DAbNAKC8o5z7Vt3HrrZdAIxLHce/+vyLjvoOysvLqaysxOPp/r2KkkxEyyYqVE3IyMTGxnLeeecRE3NgzdLua+extY/x896fAciPymecbxxNO5uIiYnh2muv7arBA+AKuPhg5wd8vOtjvCElNHJU1DDO956EWLyPlppy2j3NOPAgHWbIF2T5sPlcfwoCaPUGdBEmtAbD/r/9ZCpCIVSqzmpKt4FXjiVa38aws/uiS85DZ4ggJjX9D+szHg5/k6C/8ZdCWArzxLon+KrsKwBm9J5B1io/u1evQKVWc/od9/2hUliju5GXNr/EwipFUjhCHcHVRUqxL51KCQFq2lPJ/KcfxtXRToTVxpl3PUjC/roQ/9MIh4J88eBdNFaUkZCVw3kPP4P6BBL+/jchhyXsi6pxrVAsV+Ua+FfQiVcr8vYlAxmZc2JCD672Nj5/4F84WppJyMrhnAeeOOY8LFmWCda78Ja049vV1iW/LSPzdvxsFkT9giAL9HdMYnGv8wmp1FyYEMUD2Ul/KCH9+/OEWr34yzrwlXfya5uDG/rpkQWBp7d6mdAUQhVvwJAbhT4nEl2GBUGjQgqHWfXVJ6yf/zUA8ZnZnHrr3djilTpVnU0ejJE6NIcpAudx2PnknltxtrbQo+8AzrjrAURRxXU7q5nf3El/SwTf9c9BFATWzv2SVV9+jCCKTL/7ITL69KeubBdfPHwXQkimLNXFSVffyDm553S1v93p4d26FuY3dRLcP/Qn6zQ82TOFSTHWQ67nj/D3+Htk/P+hb37ztj+78Vlava2cnnU69w65F4PaQI2zhlX1iqDBmn1rCIS7V6K3aq1EaCJo8bR0D0kDciJzGJo4lGGJwxgQP4AIzYH8Gb83xKJ3i6nd1Q4CjDw7h6LxKSeUxya53ax44jluLxpMfVwi2lCIx6IiOb9vKo+seYQFlUqo6Hm553HX4LtQC2qaPE1UdlYqYXVNZYQX7cJWrdxba6wOITYXrazFrXazKn4VHf4UcIxE1lWismxD1LYd8XrCohV39DX49YWM3+FlRIkiNGCc5CB9oLWL6Nh0tmO6X1mSca2qp/Hn3fwSsY7vo1ZSqVMU0/rH9eccqR+p/34frS9EQyS8e1kc15zyIOPTxne1sbvRycXvr6PF6SczxsgnM4aQZFPG4h9b7Nywa4/i8Qp30j/0A5+Pvw+z9kAoVfWOVpbMKsHnDqLVqxh3Sf6fDo9bsGABW7ZsITk5mauuuqpLSCEUCPPdR5uo36h47/ZEbqd6wBruG31AXj3gDeHs8OHq8LF6RzNLNjcg+iQskkCKXktSrJGx5/ckLv2Pf5Nuu58f3y6mscqOgMQw80f0jVqOcN5HkDmGkBRi1s5ZvLH1DYLhIClSCmfYzkBsEw/x9mi1WiIDNrIDUaRJ0Qgxa2gp+AwEGyW1faivj0ej0XP66afTu3dvluxdwiNrH6Hd145aUHN10dWM0Y3h6y+/RhAErrrqKlJSFBn3QDjAF6VfMHPTO4jtXqLtWjJbTaQ06wgegdioQ2GsXj9Wrx+boCYmNoHI9EzCcj9C2AhJAYKyH02RFU2BlUDAS8DrIeDx4Pfuf+31sreqko7WFkRBxkE7uqAWIahBKwURjxR3eRy49dN5RzSOHg1/k6C/8afQ4vRzx9fbqGxxcfP4bM4ekIrqfyDJEJR47rtW3MWSmiUICNw18E6ifmli16+/IKpUnHb7vd2KSf4RtrVs4+n1T7OjVZHOTjYlc8fAO+jRYmbhK88S9PuITklj+t0PYYn9z8QyHyscLc18fNc/8Lld9Dt5GuOvuPZ/9fzHg7DDT9tnpQSqlcKz3+nCPOt3E2nSMeuKQRQkH/+iGcDndvHlQ3fTWlNNZGIS5z/yLBGWE2sLINTpw7urjZd2v8ZX4ncAzGi+hPcLTqJZLzLCLzIrJQlTr+g/rDcgeYL4Kjrxl3fiK+8g3Km4ejo1cMFwIy16kYnVLTxiNZJ20kBUlu5ytK72Nha+8ix1JUrF7r6TpzLmkhldZHfDwj2s/3YPWoOa3CEJ9B6VRHRyd+Wopj2VfPHAnYQCfoaceS4jz7+URn+QEetKcIclXshN5cKkaCVM4o0X2bViKVpDBOc+/BQv7H2bHWt/YdymWEQEhp97EcPOuuCQ+2z2B5nV0MqH9W20BUP8OKAnfS3/cwXp/i/ir943ex17eWztY6zdt7bb+xatBb1aT7On+ZBjBATUopqgFOz2flxEXJenZ2ji0MN66AEcbV4Wvr6d9gY3aq3IxCt7k9n30MKpxwJ/RQUfvPYuT518Jj6dngSXh/cKejKwh3JuWZaZtXMWL256ERmZoYlDeW7Mc1h1yli0d/tWfnzzRVztbQiiSOLYkyhr6kCWZLBCTeY+NlQk42zpXvpAF9FEUnwj+Wk+smNtxBvjSYhIoCwUx8sNMp0hibG7vIzaoVjqx1zQk4Ixx18MOtjkZuPcxcz3L+IXy3q8KmWs0opaZOSuZ5BvzGLqgn0M3ODArYfnzlKRMmoS9wy+h8Z2LZfMXEenJ0hegpmPrxpCrPlAzuCW5i3M+OVBGm3XENamoBbgoexkrkqO6UbSnO0+fn5/J/sqFaW+wjHJDD87G7XmxELQnE4nr776KoFAgOnTp1NUVIQsy/g9IVwdPnatbGDH8jqQBfwqLx2GRmJUcRh8ZoL+wwtkHAxBJTDm/J70Gpl0RLLZvNfB92/uwN3pRyu4mWR7nvRkD1zwOURnUdlZyYO/PEh7QzsJngRS/CmIoe4ei/j4eLKzs7G0GrFtDWAUVMhI2AveoClxQ5eMNkAoaKSuPpvGfTl4EzR8o/oGWZDJtmXz+MjH6RHRgzfeeANvezsjemRSEBVJ3abNrG0vpkxtx+jRYHVpEA9TUUgTCmP1BYhUG4iJjSM+K4eo3Dx0PTLQZmR0EzqQfCFaP9pFoMre9Z46PoKoc3PR/m6uamlp4Y033kCWZVYkrCDZFGR9ya34w3qm55XxxDmXEwrIXeQp4PPi/+21vZXAhk+ob1RR4+8Nsp+ETAOiGMLv9VChN+NUaXjh/gf/8HkeDn+ToL9xwthc08ENn2ym0eHrei8vwcx9U3udsOX/SLD77fxj6T/Y3LwZjajhyRFPwk+lFP/yM4IoMu3Wu8kZcuQQoiNBkiUWVi3kpU0v0extJq/axJCSaAQZ0gr7ctpt96CL+PM5ESeCyk3rmf/MIwCceuvd5A4b+f/kOo4GX2Un7Z+XIrmCSBqRpwUvCwN+MqIj+OjKIaRFH/+CGRS1vDlPPEBdSTHGyCgueOTZPx0WKMsyr2x5hfd2KAIF41rGsjH7IqqsejJdYWau82AKgWzUYB2djGlwIuL+vAI5LBGodSqS3eWdBOuc3ZOGRWiXmrmzdwRbUxKJ97lYMrQ3MYdJft67fSsLX30Wr8OO1mBg4jU3kzd8dNfn25bUsvLr8kOOi+9hofeoJLIHxKPRKYuGrhpTwLR/3k3PoSN5q6aZhyobiNKoWDUkn0iNmlAwyOzH7qO+dCchs5rZg/cQ0ov8S3MR++YvA2Dy9bdSMPakw/adLyyxrN3JybEnRkL/Hn+PjL9q3/jDft7b8R7v73ifoBREK2rpF9ePDU0buimwCQhHzPkxaUwMShikeHuShpFhyfhDz0ZTtYOFb2zH6wgQYdUy9YaiY7LWHw6t3y3k4Q3FfD1WqcUyuMXFe2P7Ehd3qFT10pql3P3r3XhDXjIsGbw0+gVqvv2FzT98A4AtMZmEMZPZsG07APn5+fQbNYlbvy5m1z7FQDSp0IzdLbCx2klYOtAnRSlWJvROYJtR5nu34rE+ozpM4TplgTn8rGz6TUzjeOD1e1jw0xfMqZ9PqWFP1/vplnTO7Xkup2WdRkAKMGvnLL7e/TW+sDKPpzt0nLHUw6AymXdPFlmT1xt3zaX4ggJ9Um18eMUgbBEHjDobGjdw45Ib8Ya89E8YjibpTr5rVeTLp8dH8mxuSjf1unBYYv03e9i8aC8AMakmJl9dgC3uj+cKWZbxu0O4On24Ovy4OvyUbCunprIBrWgk0hSH2x4g5A//YVsAugg1pkgdRpseU6QOU6SOxmCQT7bVkdgaJieoXHfesARGX5B7iFd+97pGfvmklHBQIlJVxymRT2LLL0A68x1qWx3MWTOHvVV7sflt3Yr16nQ6MjMzycnJITs7G51XRc3MnRjsCkF169pwDHkch17Jg0tyWNB5PdRHBghoFQIlSSKtzWnUVkeRZE1ikq4Ab9UeyrdtweVx4dGIOAw63DpNNxL1G7QhiUi0RFuiievRg+RBA4gqKkKTmHjMYWVyWKJjbgWeTQeFrooClpPSMI9JRVAp55350UxqqmpoiGjAmrWOVbtupsGdSGG8nTk3nY1Wc4SaVY074IsLaWlRM7vtKSQ0DJueRf9J6UiyzL27tvFhk4SKIKuG9iH9MHXv/gh/k6C/cdyQZZlP1tXwyLc7CYZlsuNMnN4niXd/rcLhU8IZxufFce8peWTH/XnFlUZ3I9cvvp6KzgpMGhMvj3sZ+3fr2b74RwRB5JR/3NFtEXkicPldvPfqXYQ3KANzWYqLxDNGc/PAWw7R6v/fxIrPZrFhwWy0BgMXP/kSkYnHVtPhfxqyJONcUYdjUTXI4I/Ucq2zk4pQiKIUKzMvH9StCOrxQJLCfPvCU1RsWIPWEMH5Dz/9p4rRAgQDYV5a9Qof1cwEoE9rH6pSLqAqLhmDX+L2pU4KAjKpWqXqNoAsCmhTTAgaFcE6J/LvJlZ1XAS6HBv1jjKWLZrFuqxe/Dz6dDTILBzQk6LfCQpIUpi1c75gzZwvQJaJTcvg1H/eQ1TSgWdasrqBpR8ptSIGndqDhEwLu35tYM+2VqT9iyatXkXP/d6hmBQzyz5+n03fzUOj03PBY89hS0ln4sbdlLp9XJoUzTO5Sqx8Z2crb/1rBhpHiBZbgIl33sGErEn8+tks1i+YjahSceadD3Qr1hsKhfD5fHi9XrxeL3Fxcej1/3MTzf9F/BX7ZnX9ah5f9zg1TiXPY0TyCCakTuCRtY9g9MqIZhPukLdbAjWAChV94/syNFHx9BTEFKAWjz30tHJLM4tn7iIUlIhONjH1xqJDFOCOBVIgQMnzL3JbVCrbevYC4MoGHw+d1g+t+cjj1u723dy09CYa3Y3oQ2rGbIwmsV1P4UlTcEUlsH2HElUwbNgw3LG9uG/+TjyBMFFGLc+f24dxuUpEQbs7wKKdjXy3vYE1lW0cxIeQrBrOMlrI3qXkhgye1oNBU499/KuyV/Hl5s/4Zu+3uASlDZWsYkLKeM7rfT6DEgYhCAKyJBEKBJCkMO2eNr4s+ZL55XPxBryIMsR3wMQtMs3BASzsMRqzqZ3HT+tLhjURSZKQw2F2tu7k9U2vEQwHyLflM6PgStSoWNJiZ25jK7IkkaRRcXliFNFqJQRYliTlnA0uKjbuIxQIIaohoyiWvieNQW9OwtXpx9Xuw9Xpx93h7yI97g4/oeAfe3AA9EYNxv3ERm/U0FjZib1FIXq7Y9azKmMu/dKKuG/IfWRYM7od6/KHuOWzzTi3dTDKp0ZEIDrFxMnXKGRNkmTWzqtky8/K9z9dt5GJ1hdx5J7GCt1JlFVW4Pf6u7UZHRtNXs88cnJySE1NRaVSIQXCtP2wB++afYhAWJbpzNyCo8drBNQSqrBMnjiamD7P4i/Zieun1+jwb6CtQIUrRo23VY+nVY+vWo+3SY+Pw5MJtz5EpzlISkQSY3ImkjVxPLaM4/cqHg6yLONcUoNjcU2397WpZiLP7cmSvStY+91aJCRMBT+xqW4K6xoHEh0R4odbJxNnOcLvd8dsWHAT/oDAVx0v4wjGkFEUwynXF7Ji3w5uKq2hRVDuQe9ew7fDJlEYnXXc1/+XIUEPPfQQDz/8cLf3cnNzKd1flfaP8FecaP4b4QuG+fe8YuZsVioIn1KYwDNn98GkU9PhDvDyknI+WbuXkCSjEgUuGpLGLRNyiD7BBXFlZyXXLb6ORncjsYZY3pjwBvULlrF10XcgCJxy423kjxr3p+4p6PPx/WvPUbFBCedwDollTtRGEBRL5bVF13JR/kVoVP/7eTlSOMxXj9xLfelOYtN7cMFjz6HR/ueki0/omjxB2r8qw1eqWKma041cXNOIR5YZ3TOWNy/qf9QiqEeDLMssfu91ti/+EZVGw1n3PkJqryMrxRwOPneQ1joXrbVOWmqctNS6WCLOY32akgNW1FZEZ+Q0NmXkoZJkbq2QGRplYlu8Cs8+F5M32YkUQPyd9UzQiehyozD0jESXE4kn6GDRmy9RU7yN1shYPjn7JoIqFQ9nJ3FtavfwSXdnB9+/+hw1xYpUe+H4SYy74tpuz7JiUzM/vVeMLEOfk1IZcVZ2l1XcbfdTumYfu1Y24Gg94HmNy7DQa0QCxb+8S93OTVjjE7joiRfZGhI4c0sFArCwXzY9VEFuW3EbZdVbmbomEV1QJDa3N+kTTsHn81G99Adc1RWgUqPvOxS/WovX6yUY7B6udNlll9Gjx/ET0r/H3yPjr9Q3zZ5mntnwDIuqFwEQZ4jjzsF3UhRTxHlzzuSarxwkdsjMnCiyPVOxJhv8Mtn1MtG6SK49+UF6F45FOM4cR1mW2fpzLavnVexXgItm8tW90eqPf5wJNjTw45PPcs/4abTaojAEgjzeouH8swsQ/6A9SQqzeP5HPFX7Oi02P6IEVyddjLkxgT179iAIAhMmncy8Wn3XHDk0M4qXz+9H/GEWe76wxAM7a/h0az1iowdVe4DeARVTPBoEBKpjVfScmMLUoqSu/JvD3lM4yJKaJXy1+0s27JcaB4gPRTM95QzOGXURxqCGfRW72Vdexr6K3TRVluP3uI/Y5v8rqLQFqA0jEMQjR2AYzBqMNh2mSMWD4/Z3sq1kE6I2zEWXn0dCajTq33ltJElm/bdVbPpBMXQ2WfawKGcmIb2PGUUzuKrgKrSqAyQiLMk882Mp3y+pZppHi1EW0BpUjLkgl93rGqnZqcx//Y2zGWj6iu+EcWzjgNpsUAjSZmxjUMEgzh52NlbrAS+6LMv4StppnVOO4FbG2OZwGM3Yz2jWLwZBwOiRKezxIKHKSPY++CCdagG7QYfdoMMRocOrPfxvSNBJtJlgT7SddmsAhw3O6nM+M4pmdIVw/k/AvbGJjjllSoSECEgQVkks02xnj9yGOamCdp2aT0vPQSXIfHHtcAYdToAiHIIlD8PqV5Bl+CH4HHvaszBH6ym6zsyju79lNSOQVVYEyc8YbTHP9plEqiX1hK77L0WCZs+ezeLFi7veU6vV3RQyjoa/0kTz34radg/XfbKJnQ0ORAHunpLH1aMyDwlfqGpx8eQPpfy8S3GRmnVqbhqfzeUjMo5LfnJL8xZuWnITjoCDDEsGb530FuXzvmfTwgUgCEy+7pYjhu8cK9ydHcx7+hGaqspRaTScfP2t5I0Yw+amzTy94ekuFZc0cxp3DLyDsalj/2MFJI8VzvZWPr7rFrwOO4UTJjPpmpv/V89/MAJ1Tto+LSHc4Qe1wJZcCzfvVBJsp/dL5umzi9CcgDLTb1j99Wesmf0ZCIIS3jVkxFH3d9v9tNQ4FcJTqxCfg0kCwNbEpazNUBKbC9oLELUTWNJLEc94KTeVU+Js3FpczfcdSgjHTWV+Lt8TQEKRutYKHHjmVh3WMcnU+naz9OO3lUWEIYKvL7mDalHLuCgznxZldiNQtbt2sPDlZ3B3dqDW6Zh49U30+h1xr9nZxsI3tiOFZfJHJDLu4rxDiuUFAgE8bg81JW1UrG+jqdzNb1FHglomINbgFatQR4pYEpL4Ojad4sgEYpztxDQ8RpuhBZWkYkLFABIrmhGQ8cckEohNBlnCUFOO2uNEUmnw9MhD1hwgaDqdDoPBwGmnnUZm5vHLnP89/h4Zf4W+CUthvtj9Ba9ueRV30I0oiFyYdyE39r0RgLNnn8YVHzVSFwMfjxcJqwTUIZlT18ucuUbCcJAWgiyKaJOS0KaloklLQ5uahjY9DU1qGtrUFMTfFQ8NhyVWfFHGrv+AApxzxUremv0NL087l5BaTXqnh9d8VgaenY/wB7LN9uYmfnj9BSWkVJTZPlZgu15ZUGfbs+nv7M/wk6bx+MpOqlrciALcMqEnN43PPmye7A6nh5tKatjtVsarS5Kimd4Emz8vBxk260Is0Qf5LYpqQHokUwsTOaUwkQSrQqhqnbXMKZvDvIp5XRLioiwwxF7AJAaTmpJMS20V+yrKcLQ0HXINv4cgiIgqEQkBvxRGFkPI4m/BjDKSCGFRRiWqCRJCRiZCZyLVkopKpUYQRUSVqmsbBHa4/bSHZSRRJMdoIN9iRCWKCCoVoigiCCLNNW6aqxuQgkqJAEHUEpMxjrSC8VhiTPsJj25/6JrukBwiWZaZOXMmtbW19OnThzPPPPOI97hnWwuLP9hFwBcmqPPyffa77LNUkmHJ4P6h9zM4cXC3/b/aUMsTc3ZwilNDcvjAeUX8nGR9lUTDFr5kGrUk4Y/ws0ezhyZDE7mZuTw04iESjAnd2gu1een4phL/bqWGk0sKU2HrIK7/0zi1LQBEd2qpi5yBY95mfFWNdEToDxvSZlX7iDa6cMUbCafZWWP0siYoIO8PvjslfQy3DrrvkGv4n4KvrIO2T0uQ/WGCqhCasGJUqFe1si3/U57eeQlhWc19RyqX4WmH2VdClVJ7aGvcc6zanoWggoqxy5in1eG1TAUgik7e7p3BqLiMP3XNfykSNH/+fLZu3XpCx/8VJpr/Ziwva+Efn2/B7g0SbdTy6oX9GJ51dAK6urKVx74r6YqHTo0ycPfJ+ZxSmPCHRGJpzVLuXHEn/rCfotgiXhv3GjvmzmfDN3MAmHjNTRRNOPlP3VNr7V7mPf0wjpZm9GYLZ9xxH8l5vbo+l2SJbyq/4eXNL9PqbQVgaOJQ7hx0JzmR/ztKcb+hevsW5jzxAMgyU268jV6jx//xQf9ByLKMe30jnd9UQlhGFaljdqqO57cr1s5rx2Ry98l5f4ogbvv5exa/9wZwQM754PM7Wn3dCE9LrROvI3DYtiwxemJSzWyN/oXP3O8C0KujFzHyCL7pO5ogcENqHKfH27imuJq9vgAqSSa8f7Hyhi2a0/MTqK90UPLTXvQ1DtK0Ipr99xcI+6hybsMe1cmacy7hk04vMRo1SwflEre/npAsSaxfMJtVX36CLEtEJacy8fp/EhEd0xVi5vP5aK52UfK9GzkMEUkhTPkO/H5ft328Xi+S1D0MRAhr0Hvj0XsTUYcPWImDaie+iH10WBx8NmQsQbUWU/tMLI6VTHRMJF2TjtjWhLt4EwApoyeSWNgPtQA7vvoIV3MjlvgEpt5xP7aYWPR6fZfq0oni7/H3yPhv75vi1mIeWfNIV1HHwphC7h96P/nR+Wxu2sxti27ius86cRng5TOUReKo6MHcHDGVhCY/gZpa3HsqqN+9GXOLG13oaGcDdWysQo7S0iA5nbWNmexrVR23Atxmu5ubtm9ErYpgSmwiJy2Yzet++HH4WADG1bt51hBL8pk5RxVCkWWZXSuWsvSDtwh4vWj0BsZffg22nHzuWXAPW01bAUjXFVG262wCAS3xFh0vn9+PoZmHhlKHZZnXa5p5dk8jQVkmVqvm+dxUejYE+eGtHUiSTP7wRHqflsGPu5pYuH0fG/a2c2AFFiYvsw5N5Fr2erYiyzIWt5qMNht9WlKwOdW4/e1I0u/yYgSB6ORUErJ7kpidS2JOLraERESVWiEjooggCHyxvoZ75u1AluH0frEUWRbzUdUXtJuUC1BJEN4/HKSZ0/jslM+w6o/sYQhKMo9U1vNunTKHjo0080bvdKI0apAkcDVBZw3B9n00dgRYsehXGvcoOUzWuHjGXHwV2YOH/eEzr6+v5913lbH+6quvJjn5yKHjnU0efnxnB231bhBktmb+zNrYhSDAaVmncfvA24nSRyFJEg0NDXy7rpRvV/uZ7Naj3s9K49RlDIp6h205V1Fp9jOnYw4O0YFBbeC0rNPIj8rHFXThDDhxBpw4fA46G1vobG/HLXpwiR5coo88nYPLo/1IWhF/i5Z9O0xUN9qIdHWP+LAbg+j1NgYah5LcI5fEwjzMCQE8a+9hZvsmPrZYCe5/LgWGEKdagyRoZCyWvqSmXEpc3BRE8Qi5N/9BNO+po+WDHRgCerao9zAglIkTgStx0QJMKUjgjYv6H/o8G4vhiwuhcy9oItg3+C3mzTMjS/BT3o9syhtCSKeEu50dq+O5/Fz0f8Lg+hv+UiTo2WefxWq1otfrGTZsGE8++SRpaYdPFvT7/fj9B2IyHQ4Hqamp/7UTzX8rJEnm9V8qeGFxmRKmk2rjzYv6H9U1fzDCkszczXU899NumhzK8xiQHsl9U/Ppl3b4itmzy2bz6NpHkWSJMSljeHbMs2yeM5u1c78EYMKV19N38tQ/dV97d2zl2xeexO9xE5mYxJl3P0RkwuHr2LiDbt7b8R4f7fyIgBRAFETO6XkON/a9kUj94e/B5Q/x3bYGPt9Qy942N9OKkrh6VOYJCwUArP76U9bM/hy1TsfFT7xIdMrxJcqeKKRAmM55FXi2KCpP2rxInhb9zNnVCMD9p/biqpF/LmenfN1qvnnxSZBlhk4/n7xRZ9Bac8C701LrIuA9dPUkCGBLMBKbaiIm1UxsmpmYFBN6o4YvS7/ksXWPAZDXkUdmYAjfDplIuyQzOdrCqEgTj1TuIyDLJHkkntwVYNmkeD5ot2MQBeb1y+lSQmtvcPPrJz8iVOwmx1yIWWMD4NcYFf8coOxzp+wk3+/C5/PhtnfSvmElwVbF+hqOjMUTlwJidwumOmjC2l6EKKvxa9txRO4E4chDrSiKGAwG9Ho9BoNh/2sDuCLw1Glx1Mkg7ydqOhefjN5BfdRURMnN172tjEgo6Grrt1wglVrN2fc9Rkp+Ac62Vj6773Zc7W0k5/Xm7H8/ilr75yfO//aF/v9L/Lf2jSPg4JXNr/DV7q+QkTFrzdza/1bOyjkLf9jPy5tf5uviT/nXbAl9QObRC9UE1XBpr0v516B/HdKeJEvM3PE+n/z6KrEdEoW+aM41jcXc7CJQU0OgthbJfkBpyquLYnvR9biNSYhhP713fUB8cC/atLTuXqS0VDRp6ajjYpVcF1nm9eo9vLL5VbSuJZi9ai5ckcZXky+lPC0TUZK4oczHdenxRE85NJLhYHgcdha/9zrl61YDkJTbiyk33kZjRydz5swhGAziSHCyRP8LkhAk7I+jn/Z2Xj3nJKKMh/5u9nr93FxSw/r9dbhOibHyTG4q3koHC1/fTjgkkTMonpOu6IV4EDFrtPv4ausO5pbPxRn4lTh3gJhOLbGdOmI7DWgPQywjrDYSc3JJzM4lIbsnCVk5fyjy8/7KPTz6nRL9cPHQNB45rQBRFHBVlfPx81cyO6eD5sju/RUfEc8Dwx5gdMph8nLDIXDUg72WTXtLWL5nFwm+RrIDTfSR2tA5G+B3kumyDCXeHvzamIzLr5wrNSOJsedfSFzRCDhKWPrcuXPZvn07qampXHnllUd8tpIk4XJ4+PWLcqq3Kh4Zf0ILyyI/RxTBJJgoNBTib/Ij+SUM7lSMrgwEBGyqWlzhWELo8Wg7WdTzA5rM1Uft18ND5lKtj55hHfa9FhxVZvyuA98ZQZaJcnnxxhrpGNOLcUVTGNJ7ZJdYjy/k4/PSz3lvx3s4AoqhucAXpkf7YKI0JpJTyoiL2wsoXw6tNpbkpAtITr4Ane7E1W5/KW1m2e5mrhmTRfLv1oE7WnZw67JbkewBrqg7lyraSAjZ+FnKYpMkkobIx3mppJzdE5XpoN9H8VxYcCMEPWBLp3jcUyyZJaP2GljSq441vbORxQjMKoGX89M5JdZ2oBdlGcnpRHWCY+dfhgT98MMPuFwucnNz2bdvHw8//DD19fUUFxdjNh+afH+4HCLgv26i+W+G3Rvk9q+2srhEWfxeOCSNB6f1OqGKyp5AiHdWVPH28iq8QcVCdVqfJO48OZeUSGURKcsyb21/ize2Kt6AM7PP5IFhD7Bh3tes/upTAMZddjX9Tzn9T91X8S8/8/O7ryGFwyTn9eL0O+7DYP7j70Sds44XNr3QVZDMrDVzfZ/rOT/vfDSiBlmW2VZn54v1NXy7rQF3oLslThRgalES147OPCHZaEkKM+fxB6gp3kZUcioXP/Eimv1J6rIsE/SH8TqDeJ0BvK79W2dAec8V6PpMlmRElYhKLRzYqkVU3V4rW11QIm5PJ1pvCBnoyLBwb2cHxZ1u1ILAHQPSmZAeg6gWUKnEg7bd21epxd+dS9lKYYmSXzey+L0nkcIhTNEDkMSxSKFDhxtRLRCdZCI21aSQnVQz0Smmw9bRmVM2h4fWPARAz86eFHgHsXTkKZQHJXKNejINOn5oVRZcY5qC3F/sITBCS5PKyfOCmWK1AXM4yNV7i9E67bjsdkKSpLAuGVKlaJJUPbhtaBIdOpEL9ga4bHcLxepaqv1V6OrLEUNBZEHAl5BOyBrdFc6g0WjQ6/XoscCeDAip0NpCJA4PEWHSK5/t//uN6PxGfLRa7VEXbV5ngO/f+JaKvS6+L/yUtogm7PGPEdSlMkXQ8/bQ7K48ClmS+Palpyhftxq92cKFjz1HZEISLTXVfPHAnQS8HnoOHcmpt9x5QkXoDsZ/60L/vwH/bX0jyzIL9yzkuQ3P0eZTatmcmnkqtw+8nRhDDOv2rePB1Q/S3FnHHXMkEjtk7r1MhcsgMCFtAi+MfQFROPL3ZVPTJu5ccSfNnmb0Kj33DLmHM7PPRBAEwp2dBGpradhWy7K1anwhNTrJQ789HxNRu/2o1y3o9ahSUthmhEp9HU22AB4dFNT35pXzb8ZhMmP1BXhiR4jVsWrmZekZF2VmUrSVk6ItRGu75wPt2bqJRW++hLuzA1GlYvg5FzHo9LNYv34DP/74IwBxyel80ZpMnX8PEakfIagdROoieWncS/SP79+tvZ9b7Vy7sxqPJGNSiTyek8K5CZHsq7Tz7StbCQUkevSJYfI1Baj2W7gDfh9LNi5g5cbvsVfXEN2pxeI5lASEBBXN2ljE+HRyC3pz0phBpKcfe80kWZZ5dWkFL/xcBsC1ozO5e0p3z/7CrV/ivuthOswwd5hIQ4zymSDLJIZCXGDM5NyovkS4W6GzFjprwNkAsnTYcx54cCqwJIE5AZyNYFfCqwOSyIa2VDa2JROSVYBMoa2Z4T0FDPEZBK0Z+M1peCJScOkT8ch6Ojs7Wb58OZIkkZmZicFgwO/34/P5um0Dgf3ESwa9JwmTMxMBkZDKjSNyF2G1d//nIkZ7NhE+JZyst2ERoyzv8Zr/YuyOaURLImEhzJr0eZQlrcWms2DRmDCrIzBrIjBKWnRNEhEdMiZJiy6sxu0T0Ib92OQyWut0hLwHvnciKmI9QeJbW4lzB0g88wxiJsQjqgKg0oHOREij59vO3bxet4gmv0LgLAELI7x9eCJFJrR9NvOZTCnZaDRe+vR1YLVuIRBQQu0EQUNc3BRSUy7Dau17TN8PgE5PgIe/3cW8LUpdo3iLjg+vHExegjJmza+Yz6NrHiUgBZhoSsZaPAhZVtHp68d81OgFgXcwkimLiCYNkdNzMOTZYMkjsOolACp6jODN5CzUP+eR6Mrnm4ECuzIUQ/Ngq5E3eqWToj9AnnylpTQ98SRyOEz6Jx+fUCTKX4YE/R6dnZ2kp6fzwgsvcNVVVx3y+d+eoD+H0kYH1328ieo2D1q1yGNnFHDuwBNLPDsYjXYfz/20mzmb65Bl0KpFrhrZg2tHZ/DKtmf4ukwpHHlN0TXc1Pcm1i+YzcrPPwRg9MVXMmja9BM+tyzLrPryE9bNUzxKeSPGMPm6W47b0r2hcQNPr3+a3R27AUgzZzDQfBnrdsZR2ujs2q9HjJHzB6XSM97MB6urWVHW0vXZqJwYrh+TxbCs6CP+cBVSEziI2ASwN7exft6TBH0OzLF9sSaehs8VxOsKEj5G1ZxjRZJGoG+ECo0g4JNkfvWEeMPgo0Ulo5XhDLeW9NCJ1Xf4DVKohYDzSyCAqMlGYzwVQRDR6FTE/ObdSTUTm2YiMtHYtTg4GhZULOD+VfcjI5Ntz2aQZzDbxp/OcneASLUKo0qkzh9EDdxQ7qXv3ipKjA04A4p1NqBSM7/vKNpNVqJdds7YsgLNQaEloiiiNxiYmzOAamsU6Q4/H631YZSVa/OG3VQ6ttCgqqHPhReQ0COrG7FRqVQ4Wr3MfW4z7k4/sWlmzvhnP7SGExOT+D32uRq44IuzaNO4iAgYGdR0N7NHZAAwY7mLCdkx9B6VRGyamVDAz1cP30NjZTmRiclc+Njz6E0maoq3MeeJB5HCIQZMPYOxl874U9f037bQPxyefPJJ5s6dS2lpKQaDgeHDh/P000+Tm5t7xGNmzZrFFVdc0e09nU6Hz+c7whGH4r+pb/bY9/D42sdZ17gOoFuehCvg4oVNL/B12deoQzJ3zpXJapD496UqGqMECqILmHnyTAzqP44SaPe1c+/Ke1lVvwpQSNb9Q+8nQhNB5eZmFn9wqAKc5PUSqK0lWFNDoKaWQG0Nwb2KBynY0ADh7kansCjy+aRpfDDtXCRRJK/dy1M7AsyOmc3PPdJoMowBQRn7RZRF1uQYKyeZ9dTM+5StixQhlajkVE656XZiMzL58ccfWb9+PQCGpBzeq7YRlCAtKoJHpqfwZul97GrbhVpU88DQBxkYPYn1e9r5sayZnytakD0hUvvH8dmpRaQZdDTvdTD/xS0EfWFS8yMZPj2W5upy9pRspbxkE8HGDkTp0PnBrIsiWpOEWpfAnrQMlhki2brP1fW5KMCwrGimFiYxuXf8IcJEHoedZR++i8dhJ3/UOL7pjOHt1Qr5uH2iksckCAL4ndBZy5qSr1i640OSAkEmN2mxeBz8mqDlvTgzZTqlD3WSxNlON5fbHSQc/CxUWrCmgC0NrKn4LCl85DbwfdBGnT6e8em53J0aQ3V5OS6Xi6DHjtq+F52rBoO7FtHeSFmtRLVdMXZrxRBDYmrpH1mPWjywLPWgp5UoWomklSja9m87sCBx+HlKrVaj1+vRhW2IdWkQVCOoJALx62nRVBDbNB6NLwmBEKMt75EXsYjVegO3y5fR2TmayR4N+UFl3M7R/8pYyxtoxUN/+wFJZI8rigpnNJXuKILhA2O9WiWTrM8nSYzHsmU+Knc7og7SRrVgiDkgTCMDv0QYeDnSRtV+UYTYkEx6x0DSXOlcwjyyhTrQ6JGDflbLfVjMSGREYrVuJuVVYDfXYld1dLVpUSWREjGKeMtwRF0k6Eyg3f+nM4EmAgSBRTsb+fe8Ytq8ragjarCY3HTao4mQM3j74qGsaJvJpyWKofqK1Ay0JdG0tmRgNxqZ16akGDyAgTMGpRCocRJqUlQLI2zF2LwPU60N8lb2IH70NdCvbiLpjtOYO9xIq0UJPrw1PZ7bMxJQ7/eOhtrbaXn5FTq//hokCUGno8fsr9HlHH+awl+WBAEMGjSIk046iSeffPIP9/1vmmj+27Fgaz13z9mBNxgm2WbgrYsHUJjS3XMRCAdocDXQ4GqgtLYS0anjrAGnHbNcaXG9nccXlrCmqg2EIJa0L5EjihEQuHfIvZyfdz4bv53L8k8USeOR51/KkDPPPeF7CgUCLHrrZUpXLQdg6PTzGH7uxSecwxIKh3hx3ad8Uf4OARRXdMjVE6l1GlNy+3D+4DSG9Ijq1v62vR28taySRaVNXZKoWWYDp8ZFUqDW4neHupGeI0mBSsE6Aq6vARl1xETUugPqaWqNiMGsxWDWKFuTstWbNUSYtehNGlRqkXBIQgrLh26DEuFgGGN5B8Z6ZVL1mTRsT4jg8b37aAuGsKhEbkqII1mlQQpJhMMSUkhpIxyW9793+K0UPjCMSKEmAq75ILsxWDIomnQj8T2iiE01Y401/GHB0sNhYdVC7vn1HmRkMh2ZDPcOp/Pk6XzQ5kYtKDnGQRmSNCou3rgbX0cpAUEJFzAajRQUFGA0GulUabjdo8Kp1pJZW85Fm5dw0qVXkVnYF7Vazdu1LTxU2YBeFPgkPgnXT1VIJZvINmYQoVYma1kAQ1EsllHJaFMOeKvddj9zn9uMo8VLZEIEZ97RH4PpPxOr3eBq4KpFV1HnqsPs1zJxTQy90ofy3ajz+FkMEN8RYsbPDkRZqc/Re1QyyTkavn70LpxtLaT2LuKsex9GpdZ0q0E09tKrGTD1xD2wf4Xx9+STT+b8889n0KBBhEIh7r33XoqLi9m1axdG4+HDiGbNmsUtt9zC7t27u94TBIH4+GOvafVn+kaWZByL9xLRLw5N7ImH2vpCPt7d8S4fFH9AUAqiU+m4pugaLu99OVqVlpX1K3l4zcM0uhtRh2Qe/s5IRpmDRy5QsTtVIMmYxKdTPz1icdPDQZIlPij+gFe3vEpYDpNhzuBm1UOU/2g/LgU4T9DDP1c8R+X2OSR0hojvVJMcdRIrU6aQV6khwi+jVkFeQGZX9C42Gjbi1LWjsgqkZk2jUjOEXW5lDIhvqWfqktlEdyoGq+TxJzP98hnICMyZM4eyMsVT0mbL49tGEyBwalEiT0wvxKxTs6uxjfsWz2JHrY+wpwdyyHbI9QrAG+f3oyhC4JuXFuF316HVtSKHmvC5nYfs79dKaFJiyM8bTIY7nYg9erQqPSqbjsizctDnKJby2nYP3+/Yx8Id+9hedyCsUCUKDM+KZmphIpN7J+Dau5vvX30OV3tb1z5hUYVkjmBUvpERiV7Fi2OvBW/HIddzMGTgF72Rd2Kj2bn/MYmyTL7KyF2FN9IvaxIY4+B3nmRJlnllbxNP72lEBuKcnUzcuQ6z33vEc6k8TiKa9sJ+A4NeI9E3sZ1CUwMW2X7E42RBRcCUQsjWAykqGyG2J6q4PDSJvVCbDxTYdbe089Mry2loUdY6WsFNQDZiEO2cbHuGRO0ufjAaeDAmGp8oQvtg3I2n0zegZZxXKT4aqa7l5KgXsYmNeIMaKl1RlDut1HpMhOUDfaCOCBGV4iAvnE9c+BLUznW4Vn2K5A+iidKSdlEW2pgIENW4BYFtkoc3/XvZKimGOqsscKVXpLNlDA4pkn4Uczo/H3Lv1SQzm6m4MKIlwOn8RKqpirokA41xOuT9c6wmIJG8z0fKPh+6gLLu8AkC6zRWXtSOoFQnoDLUIGo6u/etLCD749ELXsLaDq7J6El8ewM7tk/BKWn4SRiA0x/m/JQobqpTfmOGPrGoVA5cm72AiEPVyhPJn7DNWEaiPYfkwG383MdISC0Qr1Xzeq90Rkbun1MDAdo/+4zW199Aciq/FfOUk4m/4w40R8kBOxr+siTI5XKRlpbGQw89xD/+8Y8/3P+vMAn/v0YwLPHE9yV8sKoaCDM4R+Sa8TYcoWbqXfXUu+ppcDVQ76yn2XtoFfDJu69koGE46QXRpBdEk5BpPaqCjyzLLNhRwcPr7yCkqUKW1ES6L+PRiRdiqVrLL7PeAWD4ORcx7OxDq9kfK7xOBwuee4z60l2IKhUTr76JgnETT6itNpefOZvr+GJDLVUtbhB96GKWoo1aBUIYlaDivNzzuCTtCuwVYWp2tdJS48DrkroKuHWKEht1IXZow4T2r/MjwwKD/Gp6B1RdiZcAKo3YRWQOJjbNVcuo2rQAUaXm5BsfITk3B4NZ21VE80QRsvtp/7SEQI0ywJjGpLAn38qVH22kwxOkR4yRj64cTGrUiS24ZFmmvrSEdfO+onqbIuUak5bBeQ89hd54aIHC48Gi6kXcteIuwnKYHo4ejA6MxjrtbO6v7+y2X1HQw8D1y9GGFE9xdGQUw0eOoKioCI1GQ1NVBd+/9jzFQZkvT7uKkFrDjAQbj+VnAIqq0ymbygnKMs/0TGGSt51vX3oaR0sToqghI/pMMvXpRKsPfPdVKSasY1IQMqzMf3EL7Q1uLDF6zrx9AKbI/4zkeY2jhqt+uopGdyMpphSeLXyYpY89Q9DvI3vaWdyZPhB7KMylrSKZy9sJh5TJTq0VSckNU7H2TUIBHwXjJjHp2psRBIH1C2bz62ezFLW+W++i59ATK9j7Vxx/W1paiIuLY/ny5Yweffg6ZLNmzeLWW2+ls7PzhM/zZ/rGsXgvjsU1qGw6Yq/vg9p6/N+llfUreXzt49S5FJGTkckjuXfIvaSaU7H77Ty74VkWVCrqiun6ZO77RoNlUwUvny6yupeIWWPmoykfkR2ZfdznBtjctJk7l91F7s7R9GpW1CCPRQFOCdv7iYfWPok/qCzoI2xjKEy+Hv+KToaU+fkjM0pYCOEzOLFEmwj5fARrt0PIjkcbZPHwUZRkZpFGiMk71qLqaENUqdhADjvcZnRqgWtHZ2GL0LKhup31e9ppc/9eqCWMytCJPy6ZaFFm8ObNENxHsr8Zc+jQhXtYlGmzBGi1+TGkxjNm8DSm9jsbodJH57xywnalfeOwRKwnZyAeoRRBTZuHhTv2sXBHA8X1ipFOkCWG2DcxsGMTAjKRhhA9IxooccThCB4wXsbqXBTaGsm3tqBXhbCLIg1qFarIHuRkjEfY79FxlTTQ8NQbhJ0BtD17UvvYVTxV/ib1rvqutvKj8nl85OPdhIS8Xi/bt29n48aNbA7BkvyB+DQ6IsJBzg7YGaUKY9bpFA/N77ZajYaaLRtYP+dz3J0KQUvtVcjYCy8mzhSC1nJoLaejYj2++h3E0IGGoyhxRERD9P5ra9qB5PeyxnkJWz1nABCj3sOUyCfRJURxZ2IyS50VAAyJ7c/Dg++musXE9V/uwuySOMOrJSIsIBJG519Ph2ctB1fUNpgkzFkdWDOcpKr8xJffg6FwNLK7mOYnH8AvBWkb1hPnPy6gKriPys5KKjoruvWnXqXnkl6XcEXBFaxZtobVq1djNpu54frrMIhhCLgg4FY8eAEXtOzGueYDZnfksxclkmdIjJuJqQGkUDv16mrqDc14VSFaQgI1fpEmh0CNX6BCpeH3TkhBlskKBkkJhijR6Wg6TGqETlJh9cVg9+XS4cqilzmTOTNGESwJ0jGvHCSQ1TtZaP2BgY7LSQgqhpMVKXt5P6onOxMVg+CEKAsv56cRsz9M1bV8OU1PPkWgulo5T698Eu65h4hBg478fI8BfxkSdMcddzBt2jTS09NpaGjgwQcfZOvWrezatYvY2Ng/PP6vOAn/TyIshWn2HCA35e01zN+xgzZ/I6K2A5XGfsQq379BI2sxeaMQZRVtxnosvmjO23ovKln50moNatJ6RZFeEE1a72giLN2t3Y3uRq77+Toq7ZXoRCPBhsuwd6RR4ChmXNuvAAw58zxGnHfiHpuOxgbmPfUQHfsa0EUYmXbbPaQX9j2uNiRJZmVFK19sqOHnXU0E93szIrQqphUmMr23FcFVyRdrPqSxtRKzV43FrSPaaUYTDAIiasNo1Pq+qNRiF5kJGURWhbws63TiDisL0ii9hvOLkrhwcDpxMQY0OtVh712WJOY98wh7tmzElpDIxU++jC7ixC3BAL7yDtq/KEVyhxD0KqLOyWWNKsQNn27GF5Tos78I6onUfJJlmbpdO1g798uuWjkIAvEDCpl02Q3Exf25wm1LapZw+7LbCcth0p3pTAhNoPf087iyqpnf0otEWWZI1U6K6pT6OfGylZGTx9F7aBGiKBIOhVg//2vWzv0CKRzGaItEdcUt3L8/ZvuZnimclRDJ5I1lVHj8nBxj4ea6naz4+H2kcAhrfALTbr2byKQMStc0smdxDXHeIMkaoUsy2ydApSdMs17FaXcMxBp7bAIjf4TKzkqu/ulqWrwtZFgyeG/Se8Qb4xXBiReeACBwwz28LBmxqEWWFOTQvrmVnb/W09GohCaEg1UEXQsAmeHnXsqws85FlmWWzHyLbT8tRKXRKAIKeb2PciWHx19x/K2oqCAnJ4cdO3ZQUFBw2H1mzZrFjBkzSE5ORpIk+vfvzxNPPEHv3sfeR3+mbwIOJ9sX3Yy1YgxmXSGx1/ZBZTy2GjxN7iae3vB0V45jXEQcdw++m5PSTkIQBH6p+YVH1z5Ki7cFAYFLss/njFkVhH5dw2djROYPF1ELat6c+CZDE4cCEA4Faa3ZizYiggiLFa0h4g/Hbr83xHdvbaFxtxMZidUZ80kdZuSB4Q9g1BzeA7fXsZf7Vz/OlqY1yhtCIgPi76G608T4DW6iXcp4Gq8X6WnWoBqRjCcs42zz4Wjz4mj14mz3dYmIHAlhEcKiF0QvPnWQUslEo6jBowWPGtqCYQ5mWjq1SF5kBLEOGXdwJztyPkIUPGTXpzFytwHZ3z1USlZbqIlrZZ/NRYvNjy9KxSnZp3JOz3PIj85H8gTp/K4Kz2bF6KiO1hN5Vk90mceeU1rd6ua7NSU0LniPSKdCdHtbG5mQUIlGlGiWrDSrMql2RFHRECS8P0xBUAlUxzkpSXUzedS53D7ojkOepXfHDmpvuIFwSyuqmBhS33idX0x1PLHuCeyBAyRvaOJQLk29lLbdbRQXFxMKKcREo9GQVNSXd20JVO0PrY5Uq7g4KZrLkmO65X8cjIDPy/r5s9n43VzCwSAIAoXjJzHyvEuIsNqQJIn333+fhvo6hhekM7FfRhdBorUM2ioUwYYj9VlgEK2BNPpEfEddj75com7HLvkxqA3cNuA2zs09F1EQkWWZLVtLeGPmPGI660jSDkGlUQSLQr5NqIOlpMdGoR+wCJLciMik1CYR6PEYtUledq6cS2nZampjBRqjhENIx2+IMcQwPnU81/a5lriIOOrq6nj//feRZZkLLrjgqCG7SBLhDTNZ+tNCVoX7ABBt8ZN98lAq/bVsb9nGjpatuEKHhvGpJR2aYDbT0vOYHJdGb30MxnCQnbUr2bx7HrpgkDnSBLaoLagMNWgNe5HEQyNYMgJBikIyqYFksjsuJseXSa2uiceT3+VG3/mI7nz+3cfAPoOISpK5LzOJazPiEAUBf1UVTU89hXuFsiZURUcT989bsZ55JoLqzxl94S9Egs4//3xWrFhBW1sbsbGxjBw5kscff5ysrGOrEPtXnIT/DCRZotXbSoOrgTpXneLB2U946p31NLobCclH1yrVilqSTEkkm5JJNiUrr83JqJpM7J7ngE4dGp2aIeencVvtVbR4W7g47ir675tIzc52fO6DCi0KEJdmJr0whvSCaByWJq5fcj1NnibiDHG8OfFN4nU9eOPtT9CuVWSwN1v7kjb5XG6blEvsUap4Hwl1pTtZ8Nzj+JwOLLFxTL/7oeNSVGu0+/h6Yy1z1lXibG3GEnRgCTnI0vvJ1PnRujtwt7cghQ4v0/x7FI4/mfFXXov6d4UC3f4Qn6+v4f2Ve9hnVwYik07NRUPSuHJkj8MW2QPFw/XxXbfgbGtREthvveuEyKIsyTiX1uBYUgMyaBKNRF+cz9w9rdwzdwdhSWZMz1jeOEwR1LAUxh6w0+nrpMPfcWDr76TD10GnrwNfxT4sm9oxtSieMEmQqUh2syPLjtMYQkAgJzKHfnH96BvXl35x/UgyJh3zvSyvXc6tv9xKSA6R5kpjkjSJ8edeyOml+/Dsl5U2+jxMLNlAgqOD9HAMhaF0ep0/hIg+ikpO3a5ifvnwXZqrlToVPYeO5KQZN2AwW3ixupGn9zSiEmBMpJml7U4SNGru2vQjDauXAZAzeDiTr7+lm/qSLMlUF7ex66e96OucZGhFdPvDD2RRwDggDvPIZDTxR1ds+iPsbt/NNT9fQ7uvnZzIHN6Z+E63sKRVX37M2rlfImp1fHvdg+wKSJybEMkr+enIssy+Sju7fm2gYnMzfucmQl6lRkNG/0sZcc5kYtONfPvCU9Tu3MZpt/2b9KK+x32Nf7XxV5IkTjvtNDo7O1m5cuUR91uzZg3l5eUUFRVht9t57rnnWLFiBTt37iQl5fDE/j+Zr1pZ+TzVe99ADBlJW38PJlsesVcXHtFDABCSQnxe+jmvbXkNT8iDSlBxYb5S88eoMdLh6+DJ9U/yw54fACUv6NHBDxL9+ExcS39hcR+Bd05RFh+PDH+EM3OUmiwd++qZ/8yjtDfUdZ1LpVZjsNqIsFi7/g7+H9HClp/8ONpCqLUi4sR9vN7xtBIeZ8nguTHPkRt1YIHnC/l4v/h93t3+PoaQmgGuItLEaSxJTCamJsCw3T4EQKWC4dk2MkckYugdc1hiGA6FWffdj6ydtxBBMiGrLbRG6TDpEokNJxNwyPyBHZAgMl6dgM6ixaxVE27zE/Yp49zK3noqLFs5adU3xNiV5xHQadGqCtGIaXRo4vkqphUh83VyY9I4L/c8TulxCiat4hH3FrfSMb8CyaXUCjKNTMYyMR3xMEIwR0PFhrUsev05fF4fGjHExIQKUq0e3gqewmdM4akLRzCpt5L473U6KFm5jOXff4HU7OhqwxqXQMG4ifQeOwFzVPeQx2BDA7XX34B/924EnY6kp5/GPHkSr295nZnFMwnKB9YBie5E8jrzyLPlMXDgQKJ6RPHmzjdZtPcXvOZJeM0nIamV9kVgSqyVK5NjGG4zHXY+cLQ0s/zTDyhboyyQtQYDQ6efT78pp9Gwbx8zZyrh9Ndeey2JiYkHDmwuhR/v7qpHg0oHsbkgh6GtEkI+ZAS+TuvNo6IdBIFBCYN4ZPgjJBuTaKwqp2L9GspWraSztbGrWRkBn2kykRolDyYiogXnsOdo0Dho9gm0S9HUhL0Epe5FqH+DRWshJzKHbFs22bZssmxZVNmrmF8+H1EQyY/OJ8+WR82iGhwdDoqKipg+/eh50oFwgNL2UnbUrWTl1q/ZGvbg0ngO2U+n0pGgS8bgczLQ2kCWPoRNJaPWRCJYR1Mj9KDU0UhZRxml7aUATEgewDmmJr7YlsW3e6YAYWL1lXTq21EZ9pJsLqFZdSi50kkacrzp9PQl0GnzMzvlIsKaaFI8Eo9vczM4sR5drwCti9fQuWIFkiaEbFQRcdIoIsYPRdKECYdchMJuwiEXkhygd6/nj9oPR8JfhgT9WfzVJuE/gizLdPg7qHfWU+9WiM3BRKfB1UBAOvriXC2oMaljaes0Eg5EEqWL55phA+mXlEWyKZloQ3Q3lZ9wWGL9N3vYvEgpEBedYmLyjN5EJhj5pvIb/r3y30SoI/juzO+I1sfQXO1gb3Ebe4vbaKk5EOu8z1zJj/nv4ld5Sdam8fbEN0mPSWPn8iX8+OZLIMt09hjKx3JfpXKyVsUN47K5amQP9JpjmwBKVy3nxzdeJBwKkZCVwxl3PoDRdng563AoiKOlGXtzEx1Njewo3UNFZQ2+jmYsQScG6RiSnAUTGn0klph4otMSaYpqZWHnYhrUHWQ2GBmwOxIBSCvow6n/vBuD6VBFw0BI4pttDby9vJLyZiUfR6sSmd4/mWtGZ5IZe2i4WENZKV8+dBdSOMz4K66l38nTjql/uu7dHaT9y934yzqQkZEHWZDGWpi5oYRPN5YgqNwUpakZkWvAEbArxOY3guPvxO4/gsdQhrQmA0UVVmIcCoENizJlKS6Ks+x4I2RsOhtqQX3Y0Mo4Qxx94vrQL64f/eL6kRuVi0Y8dCGzqn4VNy+5maAcJMWVwqniqUw46zxO2VmLZ7+JNqWtkcnlWxnUoyc5u0xYAwZMo5OxnZJJZ+M+Vnz6AeXrFQlcndHIhKtuIG/46K5JV5Zlbi6pYXaTEn4hAFf+Op+onRsRVWrGXHwF/aacdkTSFg5LfPPSVhrLO0nRCmTqVFhVB/bVZFqxjE5B3zMSQRQIBYOUr1tF2dpViiS21UaExUKExUaE1YrBYu16Xendy7VLrsMRcJAflc87E9/Bprd1fxSSxPxnH6Vq8wbs2QW8e9L5yMCCftkMsR34TvncQcrWN7L6q5m42zcAarTmc4lNzyJ3SCzxPWSSco7N6PR7/NXG3+uvv54ffviBlStXHpHMHA7BYJD8/HwuuOACHn300cPu859ULg2F3GzZehkOxxbUfhup6+/FnNyTmMt7I6gPDSXb3rKdR9c+2rWIKYot4oGhD3QRjUXVi3hi3RO0+9oRBZHLe1/O9b2upuWOu3EtWcKWHgJPnqfU7Lm68Gr+0V8JRd+7fSvfvfQUPrcLjU4x2gT9Rx83BVUCWtPpCKIRWXIRcM1HrXagMhlolNpwanwEdNAvYzD9MoZQE25kcdVS4lzR9A0UkB3uxfs5JlYaBU7d4CbGqRg80hMNDMyNROUJEe70oUkyYTslE9VBkQgeh52f33mVig1rAUjIzaNuZByfVW3F60xC7cwn4I/DKKmwSALW/X9RgkiMSo0hCBEB+YjhdrLkJuj9FSmgyE1LgprWuEQswkhs/kTsujY+M4ZxSWaiVW2ca7YzavQAevfujUlloPObSrzblbo66jgDkWf3RJd2nN+NYJAVbzzGltVKPbB4vZOp6TVEjrkSht/EHrcWtSgcEtr81ra3eH3L60TbtZzhHYyqtI2AV1k0C4JIRt/+FI6fRGb/wajUCrkLu9w03H47ruVKzq3+6hns7NmTbTu20yq3Umorpc5Y1+U1Gxg/EKvOyvLa5YRkxRA2OmU06xs30anJxWueRFB/oGZfvlHPlSkxTI+PxHgY639d6U6WffguTVVKuJotPpHRl1zJ1uo6du7cSUZGBpdddhmCuxWWPQmbZimER1QjD7qG9iEzaAh79huJa3G0lLCobhn1BDGoDdzS5x+MkHpTuXEtFRvWdsunElERaU5Gio3me6OfYnMz2V4TE2qnoA0b8Ggc/Jwzi33Wyq5j9GGRlKYwqS0yvQrHUTTpQnIic4gxxHTJvK+oW8GLG56n0rmn2732bu9Nnj0Pn8pHbWEtufG59IruRa/oXmRbs2nyNLGtdRs7Wnawo3UHpe2lhyVd5oCZKH8kQ3VGxo65kZlrNCwtUea4tOg2pvSaTa62FKtKIfVhGbZ5VfzqVLMnIHJd/hn0CS7H729ArY5icdW/mFMh4wkZAYHrRhiY3red70o/Y11bCR5ZwBUWcEgigcMsGdQqM/lqN5m6ABn6EClaCc1x2HTHjytDEI7fM/Q3CfoLYmPjRu5YfkeXfOmRIAoiCREJ3bw5yeZkkoxJxOgSeWlRE/O37gPg1KJEnj6r6BBL/29wtvv46b1iGqv269GPSWbE2dldlZslWeLi7y9mR+sOzsg+g0dHdF8AuDv97N3ZxsJdP/Kp+jXCYpB4ZwZTSq/BIJkwW/fSXDUHkOkzaSoTrryODdUdPLZwV1eSZ7LNwJ0n5zKtKKlbDYWD8VuBypVffARA9qChTLnxNvxeD/amRuzNTdibm3C0NHW9dra3wh98vQXRAIIFQbQiiBYElRWtPpLEnDQy+2WSXhCH9XeJyY6Ag7e2vcXnJZ+T2Khh9NYYNGERa3wiZ971ANHJh1fbkySZpaXNvLW8ko179y+8BZjcK4HrxmbRN9XWbf9NCxew7KN3EVVqLnjkGRKyex623bAU5ue9P1PeWU6nr5O2jhZa6xqwy07sahcOtZsw4cMe+0ewaC1E6iOxaayk1GuJ2uZE1aYsggSNmthhfeg5aQLxcWlE6iMxa81dBLvF08LWlq1sad7C1uatlLSVHOKlNKgNFMQU0DdW8RQVxRZR0l7CjYtvJCAFSHIncbrqdLTZvXhINhFSqUGWGdRQxT8SbQwpGoBnVjmhNh+6bBvm83uwbv5XbPnhG8KhEIIgUnTSZIafcxERVtvvb48qj49R60oJA4O3/MqYdYswx8Qy7da7Scw5ciiCLMn8/MEuyjc0odKITLqyN611TupX1JMSlkjQCF3kyWVwU2coo6xsLV6n44htHgxJkPFrJDBqyErKx2yNJsJqPYQwqTQaFr70NJ1N+1h5+hWsScwi36jn54G5XYo7vyEcCvHVww/SULYNQTSiNV+IIJpRa0TGXZpHz0HHX338rzT+3nTTTSxYsIAVK1bQo8fx178655xzUKvVfP7554f9/D+tXBoM2tm8+QJc7t1ovLGkrb8Xc3Y2URfmI+wn23a/nZc3v8zsstnIyFi0Fm4doNT8EQWRVm8rT6x7ois0LtuWzaMjHqW3NZe6f/4T1+Il7ImFe65QIakEpmRM4anRTyEgsOXHb1n20XvIkkRiTi6n3f5vTJFRBP0+vA4HHnsnHqcdj92uvHbYaamF5to0kFVAO0H3AsKBoyfh/wYZ2J1VwPIhUxi4R8Ow3T4UkTA/UeFSbKIHnWhEr4pAp4ogSpeANsKIbVomEf3j2LNlI4veepk2p499ESnIRePYK0RRss/RJVjzG7SECKAizqLhmbP6MTonFgGo2dXO2p+qaS07EPLl1Al0GmUM9i0Y21YhyIoRUqXtjdowEkFUPL4+tYu5iRvQeNKoC8cTQkWW2MpI9R6y5HiGh/LQy2oQwDw2Fcv4NATN8UnUt2/+kYVvvsZvzpwBMY2MmjoR1ZjbwXh48QpZlnlt62u8s13Jxf1Hv39wddHVBP0+ytauYsfSn6gv3dm1f4TVRq/R4ykYN5Ho5FT8Xi9l99yLer98+J4eGWwcOJDIuDgisyP5oOMDmoOHGrx6R/fmoWEPkRedR6u3lbe2vcXsstn41Yn4zJMImkYRQlmXWNUqLkiM4orkGNIN3aNDZEli54qlrPz8w658ocTcXuwJqwhqdAzPDyM0fEq9HKBeo6belkRDhI0GXyve0KGCDKqwwKhAb8b4etG0fSc+9wH1PUQRX6Se+jgfO5Kb6dS6Dzne4o1hctmVRHuSkQUJ9dAOcgYZMD7zPua1pag0GpKeeRrLlCndjtvQsJ5nVj5BqVchTZqgQEGVFbNHjS/GTEqoHwICa+LW0GBsOOyz/D0idZEUxhZSFFNEYUwh0ejY/PUnlHZYqZKi2RBMwYcWCKONWYo2ZhmCEEZEpsggcZJNRYr6gPdIrY0jFGgFJBSfHbiDOh5d+y9avDEUxRRzc793EQ9T806S4ddQPl/5RxIKNqD1l6MK1h2ynwqZZA30UMtkq/zkCEESZAl1WEYdllGFZdQhGRVawupoMs9chGj849SY3+NvEvQXgzfk5cwFZ1LvqkdAIDYitlu4WooppYv0xBvjD2s939vm5tqPN1Ha6EQlCtwzJY+rRvY4oiW7amsLSz8qwe8JoTWoGX9JHln9Dy22ta1lGxd/fzEAn0/9nIKY7nH0X+3+isfXPY4kSwyJHM5F/pvZt9NFa81Wgu6FgIxKW4gteSoZhTGkF8aQlGPjh9Imnv6xtCtUrE+qjfun5jMwI6qrbVmWqdy4jl8/n0V7vfKDssTGoVKrcbS2KHHDR0FQUONQm3GoLfh0Vmy6KKJ8ZsySDUFlQRB0CALE97CQmh9Faq9o4jPMR03c/Q0VHRU8vu5xKsu3MWFjHCafGpVexxm3/ZuMPv2PeuzG6nbeWl7ZVasJYGhmFNeNyWJMzwPFAb95/gkqNqzBEhvHJU+9gt7U3Wu0un41z216jvKO8j+8XjmsRQ4bSTRHkx0TT6QuEpvOppCcg7e6SGx6G1adFVESKFm5jPXzv6ZjnxJrrTUY6HfyNPqfcroS+nKM8Ia8FLcWs61lWxcx+q0Y3MEQEJCRsfqtjHWPo9KUzbLMQmRRBFnmBk2Quwb3QavR0vbhTny7O1DZdDQXtLFq/sddRCO9qB9jL7mKmLSMw15PWJY5c1MZ651eEptquWDBu3T2yOOuu/+N9Sj3Jcsyyz8vY+eKekRRYMr1hWQUKguQcFCifGMTu37ag9BQjMu3nWZfddexxggbvcdOxBgXhde5f/Fot+Nx2PE67Dg72wh5j12G+WBICLTFJOAymMiJi6FPYsKBcKX9oUoqrZaFLz9DW10NpuhkzHEX0dEY4sKHhhCZcPzhe3+F8VeWZW6++WbmzZvHsmXLyDkBudVwOEzv3r055ZRTeOGFF47pmP9E3/j9zWzadB5eXw1aVwpp6+/G3DcL2/RspebPxudo97UDcFrWadw24DaiDdHIssx3Vd/x9IansfvtqAU1M4pmcHXh1WgkgfrbbsP582JaLXDrNSoCGoF+sf14d/K7qGWRxe+9SfEvPwHQa/R4Jl5901FLDsiyzJafa1gzV1ngpRdEM2lGb9RaEX+HE2dtM87aZhwV+3Dua8HhbEcKBfCHPfjDHmpNWhYMG41fn8rp693EOvZbqf27CHqXgXyY0BuNkaHRU5F0SSyUS9nk9lCvT6RDG3XIvtE6ichQG/GCk3Y5gpJwPJqolejifmRq6hROCV5A3RoPnU2/eUagR99Yssck8Uv1Nupnf4TFqXhwOmyxaEzJ7DH0IkUtYnUqOUjeiH2Yo3WkFgxlRauOb7ftQwbOROJ2bAC0CU5WaEqo14tEJfdgUN8ihvVK/+NIiH3b2PnhwyzZ6iUoqzCogpw8pgeZFzyIpI0k2NBAsL5B2TY0IEZEYBo7Bm1ODi9veZmZxUr42O0DbufygssPab69oZ7iZT+za/mSLqIBYIhLxKk34TWYyK6sot/mLYiyjFBYSPbbb4PNzFe7v+KlTS/hDR9KOAqiC7i66Gp6RioGvFpnLTOLZ7J231ok9ITNwxEsJ2GXdSArHriRkSbOSYhisNWIO+imydNEo7uRpo4GnCuL0W1pRgwrpNkTZaU5yciK1LXIh1mYCzKkBmNI80YS6zRg6pBRNboheMAo6NdK7I1zU5PgZV+0l/BBj0KURRL8saQaNURFVBGvlTHLeubvvJxerX3psZ8/xbl3k7f5HbQmHamvv0bEwIFdbWysWsNzq55ip1QFKCQsv9rMFN1wsnv2pXj1ckqsAq1mD25jJ+6YAA3uPyZBIiKxhliMWiMhKUSrtxVPyIMUtBBRcwEtAcXQEyc4uM44i9ICC5GJ/ekZ2ZOekT3JsmURoYnA6SyhtnYWjU3zkX9npJRkgde2zmBbSyHR+jZu6fcmogi+sAqdqoV0QUt02hgkbQwzXX353JkBQIrfyXnFO0hyeVC1/kSFUEdltEB5ghq74dDcoihRR5FopNAfIrHJhapWoM6ueM9mfPjjCeUI/U2C/mJ4dcurvLP9HRKMCcw9bS5m7aFhVUfDL6XN3PLFFhy+EDEmLa9d2J+hmdGH3TcclFg9r4LtSxVSEZdhYfKM3lhijpzMfc+v9/Bd1Xf0je3LR1M+6lqkv7ntTd7c9iYAZ+WcxX1D70Mtqilfv5pvX3wKWZKwxPcnJI3rVihTpRZJ7mkjPj+S5T43szbUdBUhPaUwgbtPzkduKGP5JzNpqa464nUJooglJhZrXAKCOZoKn5Z1LdAQNuDQWPCKBnrIagq8ItnBAwpt5mg9ab2iSO0VRUpuJLqIY0s6/g11pTvZuWwJWoOBmmADyxt+JaVahdWtQQaKTp/GmDMu/sME4rImJ28vr2LB1npC+82V+YkWrhuTydTCREI+D5/ccyv2pkYyBwzmjH/djyAIVHRU8Pym51lZr+Q1WLQWxoaGYG7SYAmbiElMIHVML7RaG49/s5fN1QG0oo7nz+3DtD5Jf3h/oWCQnct+Zv2C2ThaFKKmN5npf8pp9Js87RAydiKQZIk99j1sad7CluYtrGtYR5O36dD9RCtBXQ5BXQ7XZY/gtrzhaFQa7D9V41xai6yC9b4fqa5ThBmiklIYc+lV9Og78Kh9//i2Ul5t96EJ+Ll8zhuU9h7Er4XDOTshmlfz04547Jp5FWxeVAMCTLqqNzkDD8gmO1qb2bH0J3Ys/Ql3R3vX+7H6THItfUmMyEIQRHRZVox94jAURCPu/+6tql/FLb/cQjDoZ7htMPcW3k7Y7esiSL9Z2z0OO167HY9DIVB/FJ50NOgijMSm92T0RRcf1fN1JPwVxt8bbriBzz77jAULFnRLNLZarRgMyph36aWXkpyc3FWW4ZFHHmHo0KFkZ2fT2dnJs88+y/z589m0aRO9evU67Hl+j/9U33i9tWzcdC6BQDP6zkzkHZfxTs5CtgSLAci0ZnLf0PsYlKCoKTW5m3h07aMsr1NCmPKj8nlkxCPkReUhB4PU334Hzp9+wqMXuOF6EY9eIMWUwmdTP0PnF/jmhSeoL92FIIiMvvgKBkw946i/o5A/xPKPSyndqIwTPTPM9E2KQOrwE2zzQuDwJQFcoodVllI+7mGgPKofo0qCjChRvD9anUDBUB2RKSF8XlfXd9/rsOO2d7KuTaREiqZBn4RDc2jf9ow3MbhHFH0SjdRtXY59314kWWBVMIN2fSL/OiWB7c1f07oxTK+m4ejCirdfrRfpPTKZXqOSWFe1l7VfzMLSqIS+efQRbOkzgsSwhrLULHrt3UGk10VYEChJ6kFRRxOSR/EcpKSk4Fb34sVShVDcJetJkz38rKvAIto52EnbLkcQNCeRkd2TIfkZDEiPxKzfPx81l+L99mGWrKhit0+xhserJAabE9G0OQg2NBBuPzDO/B6eGBPL091szBE4dfpdXFh06RH3BfD7fKz8bgE7ly0m0LLvQFigqCI2rzcDs3IRX3wV2e0mlBzHixdEsEGjrCNiDbGIgkiTRxnDRUFE+qOCqicAk0fFgNJIejQqRpuAWmJbtp2yVAcWt5Yoh5Zoh7KNdGrQhA81aLr0IfYmeKhJ8NAc6UcWICEQTbo/iXR/Ism+RLSuBDS6RHqNfodmFMVTm1PAmPoSVy+OoLbNyzSHg/xwNLKoJiLQxsnXFpI4JA9JCrNm/Q+8tu0NivVKnSZBgvymKM5JPpuIwSfz6fafKfYuQpJr4DBKd3HGFHKjCuhhSUOUg9S5ainvLKfR3Yg/7D9kf1mGkH0A/qZTkSUDoiAxSFtLLi1ohCAni6sZOG4awvCbQHVgvdPauoxtux6DkBKeV+/OJjbpVvKibNw5ayMb/JkIQghD+hsgyIRqLicQtpKs8/HR9Sehtuq5dudetjoVA8Jkj5r+C5sxEGLg2scweFpAEDEMPpnk5+6lSe9lw9oVbN61jhJdFZX6WkLC7yJVZLC5NMTbDbx4+SxSk/+P1Qk6HvwVJuE/QrW9munfTCcoBXlp7EtMSJ9wzMdKkswrS8t5eUk5sgz90my8edEAEqyHT7rvbPbw03s7u3J5+p6UytAzslAdJs78YDS5m5g2fxrekJenRz3NpIxJPLb2MeaUK2IH1/W5jhv63IAgCFRuWsc3zz+JFA7Ra9Q4Jt9wK+EQ1O/uoKa4jeriNpxt3Rduqjg968wSy9vtxHkbGdW+mgR/9wVxdEoa2YOGYY2PxxqbgDUuHo0lkh93NfPZupquEDMAowSFATWFARU2SUSjV5GSG7nf2xOl1Ks5QWU6R2sLH995c3c3+hEgiCIGswW9yYzeZMZgNqM3mtGbTPvfN6E3WXCj5ftyOwtKOukMawgKalKiIrh6VCbjYgLMffhOwqEQA887jxWJ1cwun40kS6gFNedlnMP0TcOJaFKBCNYpPTCNTKbZ6eeymespbXRi0ql555IBDM8+er2PoN/H9sWL2PjtHFz7F/ERVhsDTz2TPhOnoDX8OaW6I2F7y3au/OFK/LIfq9+KKZRErdWHEKpF+N0EoVPpyDfk0rM6gV7eLDy15TR3lqM3Wxh+zoUUTTi5K6b9SPjql1+4RbIiiyLT1/3IvWdMoyoujQu2VxKW4a4eCfwz49DwsE0/VrN2vkLKx16US+9RyUhSmOptm9n28w/s2bwRef/EH2G1UTh+Eul9RlO9zU/rukbSRYg7OARGFNDn2NiQXsa/6x8jKAUZkzKG58c+j051bKIhv4UnrZ37JduXLmLNgLEE1Tr6iCGGa2SFOP22iLR3Eg4dOuGefd9jx62uCH+N8fdIv/MPPviAyy+/HICxY8eSkZHBrFmzAPjnP//J3LlzaWxsJDIykgEDBvDYY4/Rr1+/Yz7vf7JvXK4y1mw8nx/aPSx1aggDOkHHdf2u47Jel6FRaZBlmXkV83h2w7O4gi40oobr+lzHFQVXoBE1CgG64184Fy0ipFZx/fVgNwmYNCa+OPULDO1h5j/7KM7WFrSGCE695U569FMs2pIvRLDZQ7jdR6jNR6hd+fO1elm7z0PLfgNXgUEkUysesc/3aVpZZ9rOeksly9Mm4zfkk9Ahcfp6N3F2ZSGU0T+K8Rf2OmyNrWBY4sFvdvLZupqu9wRZIjbQykAhglHaWAb2iKLHOXnYZTcff/IJnR0dBGQVS4PZpKVncN+wLPata6ZySwvyfsOTXdfCjsTllEdV0kN1DsbtTeQ1rUcjh5EEga29h7ClaASvpEURI8h89913hEIhhAgj2/oOZ7XGiDoc4lJ7A8bSHQT3RyhUBnryq2RFBM5yaemp0ZE1LZGdrVXs21OO2tOCwe/H6HZjdLsRXEFwB0kIuEh31+MOhtmUnIBHpwVZpmdjO1nNnYfkLIlGI5qkJOUvOYlgYyOdK1egDhxUDNpkwjhqJObx4zGNGoXKZuv6rL29nU2bNrFlyxY8HmUxK4aCJGoEwk11uNtau/Y1RkcSW1FFdn0nfo3EW+dbGHfaTZyXex4CAjOLZ/L29rcJSkHUghqtSktYDiPJkpKfKit/EocSJMUXpEIWuo/fIhIqJEQ5jCiF0QZFetSbyKu2EeFT7T9WRjhMNldIJWO3hui0hum0hvHEqIgyJpDSHEO6N5EMfxJp/gQMsh6HTkVpu5/GoEzuUD+mpHtxqZXIggxHLD1Omo9oSqDdHeClB99h+vdv4zcmsb3P9QTUFlQagaiejcz1vcuumBZkUbmntNBAcjMvpN6Wzob2etQdX6J3HxBmkUQjIW0mQW02IV0WQW0msuogQ7gcQgw7ESQnYtiBKDkw4MeqlokgQMjjobE0laBDMXCK+lr0SV+j07QzunkAkV4l/7GQEiZEVaE//WWC0VFs3/UYPpeixOgORvBN5cksrR2FLLoZoqtlnacXMgK6xNkMNW3ihpZGkgIxXKZ6miqniD7NRKC3DY8kY1Or+JfajO9DZX4s2v4GMe070RcMREw4FZUpCV22jeiL8/EHPez5dT3Cah+6cASVujrWqdazUbOFpkgvLr3y+9GKWtZeuBaN6viM1PA3CfrLQJZlrvn5GtbuW8vI5JG8MeGNY16c2z1Bbv1yC7/sVgrAXTI0nftP7YX2CISmfEMTv3xaStAXRm/UMOHy/K4wnmPB29ve5rWtrxEXEUduZC6/1v+KgMB9Q+/j3Fyl4OmerZtY8OyjhEMhcoeP5pSbb0cUu7syZVmmo9HD3h1t7N3Zyr5yO5IkI4Va8HiXog51l7hUx6cz5dL/j72zDpOrvNv/58i4z6x71rLJxrNRohCc4FK0UEoFarRvBUpLoZRSb2lLDWuLFHcCJCEQd9fdzbrLuM+R3x+zbBISrLztS69f7+uaa3ZmzzlzznOe8zzP1+77Gmqmzxxtm33dIR5e1cIrB/uIj+iiCDpUKiKTUjJVqkhBhWvU6Mkf40T6ECluHwRNVXnyzlvpPriP3LIKKqZMJxGJkIxGSMYiBAODhIb6ETMnHpA/LFRBIimaSIomVIOFHLOG6O9DE3Rem9XPgDfFLPsUrndeTul6FyQ0RIcB35XjMFW4aB6I8ukHN9MdTJDrMPHwdTOoL3rvFK9UPM7ON15h2yvPkwhn8+HtvhxmLL2IiaechsH4v6N5c9x1qiovb3mZOw/cSVpMk5vIJUe/jA1jZ5ARRAQ9jZRqZZqxizJa2TW4i2AqeNxx8vEwu2Ie04tmMDVvKuXO8hM+R5lUkpce+gu3FE4g5PQwY7CDJ85YOJrW97fuIb7VmPVs/qm+nPPyjpBu7Hmri9X/yIoqzr2wmtqZDvauWs7ula+NRssAyiZMYtKSs6ieMQtJPjJ4p+IZDqzv5dCKDjwJhWKjiEsSWOPYzk+KH0QVNBYwkx9NuBNnfT7iB4hJvhu6pvHCL+5mXVsHj1z0RXRB4JkpVZzkOTKZ6rpOOpEgHg6yf91bbHzyMQBmX3EVJ533qY/0e/CfP/7+K/G/2Taru1Zz14bb6Y1nF6OTBDtfa/4G484+CfusQnqiPfxg/Q/Y0Jtd0EzMmcidc+8c1fjRFSVrAL32GsgyX7lBoM+tIwkSD5z+AI62JMt+/0uUVAp3fhFnX3kztoyTTFeEdHcUZShxHKNaXNXZGFOIaCABDR4jBZIAyrGL21BOkpflVay2bqXT2IfiOQ+/4zxETWL+gQTz9mejPwk5wurKp1ArAvx84c+zVNKqSmR4iNBAH91dvfxoa4K90axBMDm8h/JEB4XpAYxqCovVyWzPOeQZS+k3hnjNuJuMkiaiGVmp1HLO2Eom9qgMtR8h8yke62HC4mJWRJv5y4b9ODqTLBhej0vJLnyHvfm8dPLFhHz5PDW+lP7NG9i+fTsAVVVVXHjBBYTuuYcHh6Pcd/E1XNCt8IXGCHs4TKPUgw6sVSo5rPow6ypfP7SdqlAXhZ4kpvgwmd5e9NQJvPpAW46LQ4U+NFHAlFGpjIn48orwVZXjrSwbMXiKMRQVITqdo+OdpmvcueFOXtr/NBPb4HPhqeTsaEMdPGLIIElYpk0lXl/PHrOZA0fpYTkcDqZPn87UqVNxuVxZGYQDe9n4+nO0b9mC8I4wtq5TEIpRGowx4ZvfwXvxRaPHaAm1cMf6O9g+sP0D+7bD6MAiW/An/Sha1kEzxl1PTcWNrI97GRzykzfcS95QDxN69pE/1Es69d5zq9lup3L6LComTyOvohJPYRGiKKGrOpE1XUTe7EA/KjopWmX0Wg9rdw4xFEwjGUTmnLuXIL9GkXQMGY3xxrPIWXgvjKxl/H9/hP677wZdZ3N+Hb9quIaLFCPeVDayvKdwO6vG92KwTidhG0dMF0BXsESWYw09h6hnUwc9mbEUD1YiZLIph4MeM0mzDV10EbfYiFltpI3v43jUdaSuOPKhEIKqo4ugVDsRyy0YhDiaEkDL+HEnoShqxZJOk58Z4szMW7SZhtnpzVBgjDEcGE9F3pc4d1oVP1p3H33dh+jtvYokBpy2fdxn+h0nxUMIrlK47BG6bGM5c+VeBj3Z+W2s0civUjG2/GMYRTRS3v46ddpO8r/9HeyLF5FqDNDx8Ca6ggfpUQ4zEO1A1zQEBMa6ZjDRswBRkMAk4LmolkSNyO7B3fTH+7m87p/TkvyvEfQfgtfaXuObb38To2jk+fOep9R54qL6d2N/T5gvPLKNDn8ckyxy9wUTuWj6idmOlLTKmqea2L8mm2daWO3itOvrsXtOHC16LySVJEufW0pfPEsdaRSN/GTBT1hSvgTIMgk999M7UDMZambN5ZyvfhvxQ+Ry9re08/off8dg+4Fjvu8zFbPO20CPuYgis5Gb5o5hYDjBCwf7aEsdYchzagKTUhIzrVYm1udSOs5LSZ0H84fU1fgoWP/UY2x4+jGMFgtX33Mv7oLC47bRdI3HX/4dXY+/jqwKRM0Kytwyzqs7H2NGJBEdMZqikSMG1FGfNfWIp15Hp7UwzrbaANMbPVT22kgYVcKWDFPT9czJOxdZNBJI9bN26HmsBW4kXyGvdUOX4MaaX8wfP7+EspwTp68lohF2LHuR7cteJBUbUa3Oy2fm+ZcwfsEpx9F+/28hlUqxY8cOXt78Mq/aXyUjZfAmczDmfp09nuwzYBEFEppOg9PK01OqMegqO158idDWAG2OIbYbd7Pf3cqQfLwau9fsZXLu5FF67rGesSQGhnnpV/fw19qZHKiZTL6aZvWCqbiMx17j7U3d/KlrELMo8OyUaqa5bBza1MeKh/aj6zo10zOkYztp3rIBTc16Ws02O/WLljBpyRl4i96fdSyTVtm5vIPtr7dz2L2J1yofRRd0Fodm8I2ea5CQQBYwj/VinZSDuc6H+CHFclPxOI/d9g2eqJzCzvpZ1FpNrJxRh+FdJAnrutdxz+Z7cOzwU9Fro+YzF3LdnC98qN84Gv/p4++/Ev8bbdMX6+Mnm3/Cio4VAOSaPSy1DzHRnMLdPZ/8A5/h0IIA3/XfTVyJY5JMfGnKl7hq/FXIYtaI1hWFnm99i/Cry0CWueOzdvZ5slHsu2fdhWvNMFtWPAtAgbOKOZ5zMIrHzg0xdFqsIiU+K0W5NgKKztsb+0imNcwizLLKuOVsHxMMIqYaD0MlMX4a+B1botmFcI6jjkbHF1BlH/kBhfM2x8gPZp+f4rEWjFWtvLD7b+jBBM6EgRItFz0UR1NVwrKDl/LPwm/0YtAynD6wnDphiFM+eyN55WN46Vf3MNzVgSAIFFbO55AhAYLOoGZjmz6W0zNO8oLZha8ki9TOzCdveg6vd/t5cmsnyeF+FgyvoyKRjTBpsoHmsdN4Yd45APym2E5g1Ur6+rJz36JFi5g/bx4Dd9xJ8KmnwORCqV6ANaOhJYaJZwIkLAo7KkrpySvgjXQt/boTVybKvW/+irzEUYKqgoCc60O2KBjoQ7NqbDSV0qm7AVBsTvoLx9Eq5NGuevDrVopcFmaM8TKzwktlgY5kGqAz0klHpIPdg7vZ2r8VURD54Uk/5Nyqc9E1jeTevUTefJPQ8hUoh48wmgGEnE4SE+opOPdcas4665j6r+HE8CipgZhWqeyx0zBYjDxwpAbInM5QO6aWGd++FXd+dk7UdI3H9j/NH9dtwuEMUJ1nO67OudBeiNOYfTaCiQAPrPk9a3cswxUU8YaNFEYsiMfbiNlm8/goq6zG5s1h674DyIko5ogf7WhCnEuvwiRaiG3uI7K6Cz15JDIm51txnFJGY2+cjS+0oGk6rnwDUxbfT7+WjdK4ojBh7E8xj80aeLqmMfCzn+N/6CEAItMn8tvcetaYpyPoAnOAuSEzAgLdXomn59oJ2ySMsa24/I+AniW98kSMTAhMx5ipJCmq9LKeGY0SFlVDsUsYJ5fD1k60VAbJZmPKNV/AO20mwxmVoYzCUFqh1R9j1dsdDPZmn2XZY0Kpd5E2i0iaiqQqSOrIu6YgqyqiqiKPfB79n6oiKzFkJYpOii5fBvHgBKJpCx4xxHrDV7AIGbYK9Rw46V7qp9Xx1aZOmuKprBHWEsHUHOY8f5RqMQ93pIXTFot4r74Sf38vzZs30Lxl46hMxTvIKSqnZu5cqmfMwW3KI/DEITIj2naWsQaMzgGEZAT7lVeeuAN8AP5rBP0HIJaJce5z5zKQGODGKTfyxclf/FD7Pbeji1ue3UMyo1HqtfCHK6czofjEXn5/T4zX79+LvycGAjScWcGMsys+VOH/u9EX6+PKV69kIJ71ev9i4S84reI0ADr37ebZe+5ASaeoapjN0pu/84EpSaGBfpb/5be07955zPfF46ZSUH0a/V1mlvcGWG/KEH/X6Yo61GoSSwq8LJlaSEW9D1feP5/i9mHQdWAvT95xK7qucdaXvsG4+Yvfd/vWw3t5+p7bEcMp0rLGxoYIF512A1eMu2J0gfJu6LpOJpUkGY2wrXsLv2v8C43x7OBhjllZuj4fW0bDbPKxtPAziILIQLqTdf3PkT4BEw6AwWwhp6QMX2k5OSMvm9vN/jWr2PnGq2SS2f28RSXMuuBS6k5a+KGM138G0WiUTZs2sWXLFvrVflYXriYtpXGmc4lX/IBe2ZmlHDcbaU+mKTYZWDa9htCurax+5CHq9dmU2GpJ6nGMF+dTNmMKgWTgGLKFvUN7T0gjL6sCGfM8hgo/h6BrnCW/yViLhtfsHSWG8Jg8uExuvtcS4c2gSo7RyIMmH1se2IGS3Ics7ScZHRw9ZlHtOCafeiY1s0/6yNGyR3c+zk92/Rgdnbr+2SztupzpNR68SQX1qHRRwSBirvNimZSDeaz3A/VE/D3dPHDHrdx33udIWGx8v6qIG8tGdJMiXfxsy894s/NNALwmL1+d/GXOr7vwGNr8D4v/5PH3X42P0zaKpvDogUf5/c7fk1ASSILE1eOv5ouTv0g0sIY9e78EaHjazsDdeBF3lP4RKi3cMfcOKlwVo8fJGkDfJvzqqyDLPPS5Spa5sukql8bOoHarSlcsG92sdTYw2bsYURCRXEYMxQ6MxXbWqXEe37AajxogqhuxJHMZGylAREQVNXx2kRqHicrxudjG+0iWCPxmz72jqdIOyYHFdR2HTJPQJCMnHUiyYF8cURfQ9QSZ2Eq0TON7tsWAtZCX884kJphwSwq3TtSZWpVP8djxoxHcTDLJ8vt/z879B0iPCDR3Kk7aE7WcHrdg1QUsTiP1C4oYzDPy1N4eVjcNIqkZZgS3MTW8C0nX0AWBtDeflprJvDz5JBBE6tqe4KROEYNmwGK1cPFFF1NZWUn/D39I4LHHweSA1PGOGMhGdHpLS9g8dQb/kKYR0i3kEOezPY3YU16KJ+cyf+I25F0PgpKkM+bi1YFJRJMgSBLO+qn0qiKqdiRyEdFNtKke2lQvw7oVEBCkKJKlHcnaimRtxWAZ4O75P+TsyrOBrD5Wc3MzW7dupampCWskQlFPD6V9/eT09SEcdXzJ48G+aBHGhXN51tPCA82PEleyi9P5xfP52vSvUeupZaCthT1vvsH+la+RfN3YnQABAABJREFUPirFtqx+EhOXnEGqsJqvPb2b1uGs4TFrjJerZpdzen0Boq4y3NXBQNthBlpbGGhrYbC9dXQuOhoaOqJNoXDMOFpLJrPc7KbNnU/SbMUqiVyc76F26xq6mhqpKMzHGwvStGkdAAbZzHjXHGoc05FGaJblXAueT9Whu02s/OsB2kYoy6tmZnCX3EpMDgKQO2xmX9mn6RIF/Ek/ocgQix/ezYTd2Sjh6vo6Hlh6Mj2FNWhBF4bdAQRVp0I0cE4kS7eeMKR4s/IR+h17MGZE7HGZmt4idGUigxkriiYgawoSKpKuYtAyGLU0Rj2DzSghZhKI6QSyrmIxGXA4HUhoxBIpwrEEoqYhoWKVQNJVVCXzgYy4HwRVEGm3lHLAWUf4pApmaQcgKvJyfz2q24Iy1gWSQK4s8aOmXbywqo2Vxdk04ZPjOt+aN0BfbyvN+5sJBY88F4IART4jFYYUleYoblMc2aUganFIRdDTKcLK5UTUiwEJiUHchnuRv/wKhrx/HWnPf42g/0P8bMvP+Nv+v1HmKOPZ8579wBqAtKLxo1f289cNWT2fhbW5/OZTU3Bbj8+d1nWdgxv6WP2PQyhpDYvTyKnXjad03PHMOR8GTYEmvrDiCwzEBzCIBjJahjMqzuBnC39G14G9PPPj21FSKcZMbeDcb3z3fSMIUf8wr/3xN7TvOipULgjUzJzLgiuuPSa6koimObBzkD+va+FNfxiXJHFaqZfLTypn3PjcD6xl+t9CIhrh79/6CpHhQcYvOJkzb/r6h9ovHg7xj5/cRqC5FQ2dreMCZKbm893ZtzE9f/oJ9+mMdPKrbb8apbW1yBaun3A9lcazePzV7Yzf8hCCrjDBPZ9UxXwKLx1LwxgPj7+5m/tfWo8nNcw4c5xqQ4RgT9cJa0COhtnuoGbmXMbNX0xueQVm28cnPXg3hoaGWL9+Pbt27UJVVcKGMGsK15CUkljUfPrLf0BKtJNrkJjqtPHGcBibJPJwvpnefzxE5/49jHfPYaJnAbqgk/uFSZjL3aPHz6Z5xYkMDxEY6mN3/y72BvZxMNFCCz3EpTSqnEeg4C500YI1+BS28Ivvf9K6SG7QxaQWG0UDEtI7I6VRwjq5koK50yioqMZr9o4aUO+Vu6xnNDJ9MdK9UZT+OPvCB3h14HX8coj6wqmMaTmJzpYoKmBxGJizqJhCUSCxd+hYg8goYh7ny0aIar3vSbHbsn0Ld77wEq8tuhCzrvHmrGqWNf2dh/Y+REpNIQkSl9ddzo1TbvzIJCxH4z95/P1X4+O0zX077xslnJmcO5nvzf7eqOaPqqk8t/2beMIvAJDTdBHuzrPJ/+xkzBVuINvf0t0h+n5wG/GNb4Io8dZZDdw3MastMy1Uy/wtTkLpQURBZPaEC6mfvRhDSdbwkRxGYimFH/3jLdItm7ELadDBEi/BHqkEIGUaJuI6SEIQiGhGUpqIjEImNYCcGsaWCmKRnayfsoQDNZPJCyqcvzFCfij7IKnpJjLxlaDHsbrcuPILcOcV4MzLZ7/SwjMDr9KnVRMeuhRdlxlf6OSBaxsodB1P4KOqKn/9xzN0NGVJDAzDfQhDQey2s/CaSvCaBDZ7BV7RMgzG06Dr1MQOc3J4I8YRA0axOUnml2Gsn8z9peNJKCoXdO0itzU73w6ZhmitaOUz0z/D7KcPEP7b4yAbQEmBbMZQUocgJxns7eLvZ17AwYpq4r4cfr2wgQaXjWVrtvDN1/tJ6DJFYohLxb1cKL5AmdiFpsO61Cw2txmzlpPXSv/JOTSb+ugJ9uCJeCiJlVCQKEDSjzhBooi0KT7a1RyGNAsOJYorE8bhMPGDz5zDuDwzO3bsYNu2bYRCR6JPY8aMYfr06dTV1SEkEsTWrCHy5iqiq1ejhY8wdqYl2Fsh0DO5iEWf+h9mTDrjuLZX0ml23vcb9i5/jWH7kXuTFE0ctNfS5ipDUyR8qWFy00MUKsO40wEE7XjZBtkgk2NTyaMH1Z7g5QIja30aqpSlf//8pM9zbs2lvDgY5YHuIQ7FsmOjMxHjU1tXImoa5884E3FnD1sOvkwwna0rtsseJnsXoy0oZFtVM+GuNLa3xmKIW1FFhcik+5gzZhe6QURWNHo6VX4iOVFHnKqeoJmvvyhRPBQnaTDw+KlncWBMNaZUEnMqgSkVxxH1YxxMYcyksetJ3GoKQc2A/h6hrH8XJAFEDUHSQYSEZsUkmdCUDLooIIsqHimMLkkMZNwYo0cMl4TJwsHqSeytnUpfXnHWkgGKw31c9+ITNOzcS9hRz58nnclWa3bdMCW0i3n+9dnqLkGj3Bag2jFMld2PVX5/Nl+ApDqBgPJVVD27Dsy7sR5j2Udft/7XCPqE45D/EJe9fBmqrvLHJX/kpOKT3nf7/nCSGx/dzraR4v+vnFzNV5fUIp1AVyedVHj78UM0bsoOACV1Hk79TD1W53tTnL4ftvZt5SurvkIkHaHSVck3Z3yTG1fciI7Oz+vv4NBvHyeTTFA+aSrnf/N770mlGg34ef0Pv6Zt1w7eSTAXRJGxcxew8KrPYPf8cwbavxq6rvPSL39M0+b1uAsKufqe33wkggBVybD8L79n31vZlJbG0ggb6/2cU3MuN0+/mRxLti4rnA7zl91/4dEDj5LRMoiCyAXVF/ClqV8ix5KDntHwP3WI/etWsXnoVXQEni84hy5LCWPzHRzqzw5eF00r4Z6LJmKQRFRFIdjXS8feXex9awWDbYf5oEfe4cslp/TYyJG3pPSfqgvq7Oxk3bp1HDx4cPQ7W7GNZ43PEiWKRCH9xd9Hl+zM99g5yW3nntY+BOArXXswvvIk6DqFtkrqXfNIKlGYaCHtSBP1DxP1DxHx+4kOD70nS5qOTtIo8tLV36Ld4GCcWeHLOV2EUgECyQCBd95H/o5EguS364ztcOCNHJUW4kxxqCxKS1EMRT5xG9oNdorlQsZlqqhOlVIayycv4sYZsSDqHxylVICkqpPUdXSTTE6NG7vHhOJPkumKosWOTCKCScIy3peNENV4jhPR3PDck9yUNNFTUE5uZBcEfg7AzIKZ3DLzltF6kY+D/9Tx99+Bj9M2wWSQq5ddzbX113JBzQWjUbqWUAu3r7udnYM7WWjPcIEn2x/y9l+Dt38J5rEeFH+SdG+U5JYHULo2gyDStehcvj7rZRCgMOPlnLX5ZBJxrA4X5/7PdymuO5bxbt2hHv76xAsUadk5RFdNjAmOI5bJXkfa1kPY2oQunbhPa8D+wgo2jxlPRjJw0oEEC/clss+AqJBTG2firDzySopx5eZjMB+bfqcpGj95cR0rNkfxIJBj7uOSeh/THRPQohm0uIK5zoN9ZiGhYJRf/fFhSA6h6dCc8DGlazOSGshee8kCnpPqRhdwY/QQZyU3IfZlI+yawUQqvwQ5p4CZp57Ot9ImAuEwFzRux+7PRn19dT5eEF/IslfqOtetlDljSxoBHdFZQu7Nd+K5bDaCKBBdu479d/2Ib196HQfG1GDUNH43vpxzCjys2LWLLz3RSVqXqJUGmCO3Ua124e9KoySyc3tTcZRN9f5jxhhJkCiyF1FhKqPIn4thyEgyrB7j9BcyaaSwn5jah0GTkWyl6HbXqJCp2Wxm6tSpTJ8+nZyc42uBdV1nVesKXnzuJxTv7KGhSacgeOw25vp67IsXIc2uJlEUIRrZRziym2j0APKhDMm/5/BK+XQ8+hB29XiNnaORFE2oniIqx9YydVwZ+QOv421+HBENRAPM+jz6/G+wxr+XX237Fc3BrGBqsb2Yr077KqeXn876UIwHuoZ4fSjEzMN7mdLVTMRsx+M6iaU9KQL+PewLrCU5ci49vgQRTwXj++ciagpxeQB7yTLcRhU1LUFMoD9mJoYNOWNESoGcyiCdwGD7qNCQSUgmkpIR1WolbTERtjvIyAY0UcJiMmI1mrBKBpRIhGhvH6Q1ZMmMOa+ElqEYftGOKsiogogmyqiIqIKUfTHyLhz5Tn+P6L7DLGKX04iZIDY5htMYIdc0yJsDc7EmY5wS20RVtJG4ctT8585l79gp7K+ZQtpgpKqjkZrW/VR2NGJQMuxwTmKtL7uObVAOcWfOW1SX2DHanNlo6ejLiW6wE9kaIXk4g44V3WRHS5rRsCC57NgXFqP0x9EVHe8lJ9ZH/CD81wj6BEPTNa597Vp2DOzg1PJT+eWi99ed2Nzq56bHtjMYSeEwy/zq0iksGZ9/wm0HOyO8cf8+gv1xBFFg5tIxTD+9HOE9REg/CCvbV/Kt1d8iraWZmjeV3578W1wmF3dsuIOnG5/GFzFx9pp8KiZM5vxv337ChXJ0eCTys/tI5EcQJcYvWMzCq6/HYv/nPdH/Duxa/ior7r8PUZK54q6fk1/50RePuq6z7ZXnWf3Ig+i6Tp83yappgxhtNr44+YsIgsCfdv9ptOh/TuEcvtHwjVHvrxbPMPS3/aTbwiAK7LSu4dCedWhmO48WXExQyHrgblxUxTdPHzuaFujv6WLz80+xf80q9JGUh5JxE2hYeiE2t4fhrg6GOttHX9GjWICOhiCIuAsKySktP2IclZXjKSg6LnUumUzS2trK+vXr6ezsHP2+traWyqmVfGPLNwjrYXSpkGDuLdiTOjc4DfhkkVszVjRBYNHG15mxc807P/6hQ/wmmw2HNwe714d95N3h8/GEp4wHQmncssTKGWMpNh9vqPe3NLNrxTIOrn171KDSBYmgp5jlM0qprHRwkosjhlMigB5W8ISs5EfcVCZKqEqVkp85MTV9SIpw2NxFq6kbgy7TYJtChVSGGkmjRdLomY9BJysJyLlWTBUOTGNcSG4zXXovv/3773li7rXookjNwJ/47qzzOL389P+1tNH/xPH334WP2zaqpiKNFGIrmsJf9/2V+3beR1pLYxWt3Gi8him0M5T7DOgChXs+j7NvNrquEd/2IMneraiyjHrRNdxU+hgJMY09beTc1QUY0wI2t4fK6bMQgHQyQToRJxmP0xaIk3S6EOSsMLHRH8Qen4pkKEPXdZTEW6ipHQDogohmNKGZLCStJhSzlaHcctbWTmPI4SY3pHDhhjB5IZAFEEwBdFsvmmBA0G1YRSsugw2v0YJHNGLXReSkCon3j16/g84CA8/638YmJsjoIi2pWi6qq+ewKU33qkcpD2XT7FqsFUSKT2ZO/w4S4Z3o6CCIpHwFpH0FTJg0icWnncanm/robW/ntINbMaVTmEwmzjvvPMaPH09SSfLw779A3mu7GdeaTdsSymYS+eZVNCxZgiAIaLrGQHyAtp79bH/yT/zDZ6bPK2JNd3ONv5lrgwG2Zabw+czX0RCZJncxSe4FTcU4PMhAbpr0TJkyJZeclB1HTEIOZ8j4w4T6+4j6jwip64JI2u5gOM9AnzfFkNXPkHmItJRG0AVqQ7WMC47DEEtgjvipqRxD7cy5VE6bgcVxbH/cNbiLX2795SiRgdvk5vMTP8d58nSiK14ismoV6r72Y8gxFI9OaqJGcpJGqkZnb6SBB3ddQihjwaSkuKH5BcbUeenobEW2KJi9ESw5Gkrh1bwVKOOtbmXUMC0XBrhKeoOLpdV4xi+GJXeAr+rIb2kKLzS/wO93/p7BRNYwrXHVcLn1fCoavWhDLp4tFhD6V2NW0qytnkhTQSVn9GZo6DnEdv/fqGw3jYjv/pPQddIGmaQJFINCnieP8pwqrA4nJpuduJRm1cAaDsabScsaScFKNLSAktAUFqbsGAUDUYvIMydZ6fBl5x9ZUZA0ldT7OBgFTUNKZNASOkJcwR3yM713C+ONKksvvxZrTjH+WJpgPE1fsI/mzpX0+TuJZmxE0jb8SQ8xxU5KMRPLmNB5/+yZOk8jPxPvpy7aw+9sF7AvlE9120EMStbh8k4THj2DRGxOmirGscczgXBPNppZWuLguxdN5KRcJw75XeRYmk581yDBFw+jv/OsyyKuMyqwzy5EkEWSsQzxcApv4T+XmfJfI+gTjOebn+d7676HRbbw4vkvUmA7sVK7rus8uK6Nu189gKrpjM138Kerp1ORc3x+pK7r7FvdzdqnmlEVDbvHxKnX11NU7f6nzlHXdR498Cg/2/ozNF1jUekifrbgZ5jlrMfu4MGtXLnuetKyxtmDE/nhlx48zpsXGhzgjT/eS8fenaPfiZJE/cJTWPTpGzCa31uX6JOCoY42Hr316yiZNAuvvp6Gcy74WMdr2bGFV37zU9KJBEm7wGtTuwk6jnj3K12V/E/D/zCveN7oQlXxJxl6aC/KYALBJOG7ehxSqYXHvvsNhjrbya8dj3/BZyjPdXDelGIABttb2fTckxzauHbUgCifNJXZF1xGyfgJx5/YCJKxKMOd7xhGbdn3jnaS0RPnvIuSjMXrQ3I4UQ1mYhpEddBlI2gasqZSVVpMRXERQ4l+fhx+gIghiS1h5uStZfgi2VSBIU8uj57/edImMxMPbOP0t587jlvPYnTgLCnA4TvawMnB7vFl//b6juuDAGsDES7ZeRgduL++gnPy3KP/yySTHNywmt3Ll9F3+IjgrGjIQZQnUlg7C8unx/H5Qx2UxzS+Z3UxNyWS6YmR6YmixU+8WEs7dKLeFEPOCD32IdosvXTRiz/lJ5gKcl7Vedw09abR7XVdR0+powZRcihB2+Z+/IdDmAQwi+CyGzGLoL/Hb74X4oLKgNVAWFKZXubD5DIjOY1g0FCHe8l0NuP51FJk74cXvn0H/4nj778LH6dtEpEw/q4u4r0BWtsP8XzvCwynB5EVkdJELpPDVdkaNy1N3NxJWgqjpkWI21EyabSRh0cTdN6cPkhXXgJzSuTs9QU4EidO2dRkA6n8MhRnlhFRTCWw9oUxyachSi50PY0p/QK54i5cxgQWh5UXfR66jCJGycYM7zxEaTZDoQzelE5lQKUwpmESwCSA+BENbxWduKiDRSZiitOUOURA9pMy6tQMNTBNdaKj86ZhL/vEAKqrgX6rg7VtI1IJus6czCGm97yNoGuj2nYAGYebVF4pDoePpReeS3VtDTftb6dtyyYa2g4gAvn5+Vx66aX4fFmnRu+ddxJ84llQUyDKpKeew3fnb6Xd0sd4TxVpHboi3STVIxFpg65zUSTKDcEweSMkKt1GMz80XcNrg4sAWKTto8I6ItKqZDAOdGMIDZ2QW1QTdMK5IsFSmT5PgnbjEAmOTbeSdAl1RHfFnLAza08uY4aOOFgEQaR43HiqG+Zgrivmgc7HRlKvdfKNRq4ccxKzvAUkYweJRPaijDDliREw7RUx7xYxHxARjiq7zBhNbMwZy6aC8QQnTOPLh5eTv245iCJ53/kOrisuZM/em/D71yAIBsaP+xnR5jSPvrmVp+NTiZBd0xglWDq5hKtmlzGl1I2OTm+sl+ZAM03BJg76D7KnezdTB6pZ6l9IefqI5t1O60FWmffiiHvISAYemXUqKUPW2BgTVJm5o4fyljfQlT6sThnBNIBkVhCM0GwaR5OpmpTJQtJkJmWyMLbtMJ9+9XmsqTS9XoGfXqyR9Fq5enw2QvtOGnE0HeWPu/7IIwceQdVV0ERS/oWkhxajiybUAgtFXitLdyTwRjUUETbWZBgf3M6FJnAlErSuXU+X3UlPUQmBs86ht7KG1kSKpmiSzPs8NoKu4SNEoTRMntZOvt5FPn3k00se/Zg4tjZW0wViGSvJmJV03Eoi7Sae8dIe8dCVLsRmC3Bh3fPoJjd/5VY2kE1Jm7ZnEws2LsOgHjv36IgkXVVsmjyHbfllaC4jYjCNYacfQdXRnAYy03zUeW00uGw0OK1M6E/jXdWD+o4wsVHMOgB1MNW48V05jt72CCse3o9slLj01hkYPiQx0NH4rxH0CUUoFWLpc0sJpALvqd4MEE8rfOeZPby4K8vodu7kIu65aCJW4/EF9al4hlV/P8jhHVkPScVEH6d8ejxm+z/H7NUf6+f29bezridbXHhx7cV8d9Z3R4v5B9tbefLOW9mW282WcQG8Ji+vXPgKdmPWYvf3dLPiL7+jc/+e0WOKksyExaey6NOf/ZfRLf9vI5NO8egtNzPc1UHFlOlc+O3bEcSPX4M01NnOkz/+HolhP2lZY/WUIbrysp7F86rO4+sNX8drzqYGprsiDD28Dy2aQXIZybluAoaC7ITh7+nikVtuJpNMMOuCy5j3qavpa25k43NPcnjrxtHfq2qYxawLLqWw+qOLYWqaRjAYpLutlc7Ggwx2tBHu6yEV8EMihvBeYnjvit7EzArLZvcTtSo4ozJnbMrHmsr2p6Tdyd/OvYGQ00NJTytXrvwHddNnMWbaDPStMaR2FavbQ+FXGrKL948Af0bh5M2H6EtnuKrQx8/rssxzQ53t7F7xGvtXv0lqROBQkmXGTJ3NcHcFxlQeJbkWJkzwog0kiPdGkZUTDJUiGPKsGIrsGArtGIpsGIvsiJbjn1Nd17ln8z08djBLS13trmZByQIWlixkUu6kE5JlBPvjrH+2mdZd2Qid0SLTcHo59TPyIKGgRtKo4TTpzkj2NRhD1D56lMc2S8JzwdyPvN9/2vj778THaZudf3+BlS//5WP9vo7OpglBDpaFkVSBMzbmkxsy4SksJm9MFSaLFYPFgpAWWdc8QNyQQBZB0yHXmMdMIcSOjimomBhv0Sg2CSSEJHYUTLoZ+OiaYYJJQrDJqEadGBmCmQTBTJRwOoI/k2Ktmkc3RsIoTJObKZazdSyqLhDWzYQwEBYzZIQMN6WqmKCVoKDxbcJsGvFwCwIsqMnl8pllTDCGWPnnexnqbB9pE8i4c0kXlDNBLWOaUom1wMFf59o5uPFNyvzZ9L+pU6dy1llnYRipbe382teJvv4G6CqCxYv9/K+QujzD9v7HIdGIV9bQdLJOIE0koxqp7tWZ2juEXckaKQHNwlvRWg73ORFUWOOdy07XZERd5ZzQKnxeE7ox68SRUkkKZJ3C/BxCuQIdVj+NWif7o42jJAXvwCpbmZo/lRn5M2goaKDOU8fa7rX8aNOPslETXUAamkLN4TJmMYDg7zlm/4w7haksSkVNAocvwrttVVE0YrePx+mciNMxEYdzEhaxiMTmrXS+/DqhlW/iioeO3gHLlCnomQzJPdk1gGncOKyzZjBUuJuBnM3oZqhtjlLamyTuqODFMd/noQ4Ph/qOECPY7MOIrnXo9i0IYobiVB7nBBZwamgONi3rQE0ISVa6NvOydzVjiqq4fv+5vB3dQ0CM4XFV81JeLUOeEBOH97O46W3G+xuxFCQYmqmDLNCjFPFL+Tv0CsUY0ilKe1sp725hSdMOZm/ai6jDrgqBey82snTiZdww6YbR9HVN13i55WV+vuWXBFLZCJ0SGUey/xxUUz7uWjvBHBvpkfa0JBSuW9GDL55dJxX2rqe26UkkLYPk8yFYTSid2XvTPX0iv5h4PvuDLjCKlBf0Mb1yJ3Gjkz4K6KeAPgpJCu//DOboAcpSXZQnOxkT76Yq2kUNGapKJ2NLBWHfczBCqLTbt5SDzgY6fV3cZzyXmMGJIZNmydqXqD+0AwHIN0QpdQboT1XSFbeia0fuu9njo8NXz6tSBQG3D2k4lTWErBKZ6Tno1iPzmyutMSmiM8NrZ+6EfMYNKST/cQg1pdIoSRwKpEAHV56Fc26ajDv/o481/zWCPqG4c8OdPNX4FNXuap5c+iQG8XhDpXUoxhf+vo1D/RFkUeC7Z4/j2rkVJ0xh6W8N8/r9e4kMJxElgTkXVDH5lNJ/Ot1lWesy7tp4F+F0GJNk4mvTvsaV464cPd5QZztP3nELiUiYvOoa/jGtkY5oB9fVX8dVvvNY+dAf6Tl0hOpalCQmnnwai675LPJ/iPHzDlbcfx+7lr+K1eXmmp/+Fpvb88E7fQD6Y/38dsdvef3AyyzankOB34wOxOcW8JRrEwjgNDr56rSvcra6mODjjegZDUOhjZxr65Fcx7bhgXVv8+q9PwOguG483QezhcEIArWz5zHr/EvIq6j8wPNSVRW/38/g4CBDQ0MMDg4yODjI8PDwqPDfcdB1XBYzToOESc2gx6Okgn4iA32j1NEmmw09x8Y/qvYQNicxKA68qUs4bcx4Lsz3sePNN7inaDzdhRW4wwF+qw+z6KylGIwmIm93ElrWlmWi+dwkTOUf7fnWdZ3P7mvjlcEQ1VYTr04eQ/fWjexavozug/sAMIpmSvLHMXbsHDzmYsKNYayafmKNIVlgv12gxSlz5sRCysZ4MOTb3pOc4N34y+6/cO+Oe4Fsjr+qH8kzd5lczCuex8KShcwtmovLdGxUpuugn3XPNDPUmaVDdeaYmXthNZVTcxEEgQPDB/jx5h+zq38XUyJVnN89noldJhjqQUsG0JUUosmBYHYhmJyIZheC2YVo9yFa3DhP8+A85cREHe+H/7Tx99+Jj9M2rz/1dzZu3EA67Set+HEY7NR5x+Py5mBy2zFZbRgtFowWK0aLBdlooOe+WzFuG0bSNcwzzuSlmQYeM70IOizakUN1wMtZN32DmllZYzfTH2PTC7t5pnMjLim7mEkJdi4/4xw6VzbR1mFDBGY4NAreg7RHRyFohD6zkYBBQEpqeAIKGRVUSaB6fjHlM/KR7EYkm+E9n5WtbX5u+NtWAvEMPqvElVUaxAYJ+f1oyQjSCYQ1BR1OykyiTsslgsaNxGlFwyAKnFRqZvrABtIHNmadMZKEKhuQRtJcSydN49Ql15N4o4cXLEGaM7txpBIIksS555wzKoqrp9O0ffo6kjuyaWJS3niUCyfSO+FRELPnpGYEAk0ukgETmbBMWTrCDFsPHmP2tyIZI5uGStkTLEA7KhVJR+eNktNoNFRjFVN8a+wqUkP59IRVBCG7LBuwDrDTs5OI8Ugk3mFwMC1/Gg35DVmjx1s36kDpjfTyjeU3E06HuLr+GvaG9vP84ecB0NIekr0XUgecbXkWqUci2muFo2oVjfYMObUGSidVUl4/G7dnMjZbLeK71im6rvP3je386JUDpDMKDekBvuUYwLdnC6kDx0pdnKjXpMt1UnU66RI7j1bVsjvVSSgVRkuWkg7MRglPAj37m7KQZqFB4zNpH+WMCKN6ZVxzSxmqSfLrvb/iYOublCkKlWlYHC7GrYTx6kG8hDEIx89fLeVWtiYK6VpXQMToQpFk3MkYBbMnIRzYxNSVbQC8NVGg+6bz+GLDlyi2F4/uv3dwH7esvpO2aHa+1VI5JAeXItjqMJdZGPIcWSsUD/Ryzto3OWPD27iiUdrLltAy5lwQRGx6D/UH78feP1J7J+s0O0r46dQr6HLmYyHJJeOeY0HJBgQBNEUkHZFRk2Y8RZUMaYP0CXb6KaAnXURrpIa4OYchs4uQ/P5pZPmpIcYkuqkQUngcZaxLmNhtdcFIHZHP38/5yx+j1t/L2JmLqb/uBhw2I/3r3+LZpyyomki98S+kU800RnJIa0eMnIy3iDVCDU32KtKiCasoMLfERWeBiQNOifS7agklAWYkReav8GOOZp+rsVNzWfDpcRg/ol7eO/ivEfQJxJ7BPVz56pXo6Dx8xsMnZAdbsb+fm5/cSSSpkOswcd+V05hRcTxhgK7p7FzZycbnDqNpOs4cM6d9dgL5Ff9cG4RSIX608Ucsa1sGwHjfeH4878dUuo8soIe7O3nyjluIh4LkV1Zz8W13sTmwnTue/DozD3rJCR3x0r9j/Cy4+nqMpo+mR/RJQNOm9bz4y7sBuOi7P6Ri0odXij8R4pk4D+97mIf3PUxixPNyZtkZzNnno2VNVpOgcPY0nh+znwOhQ5wdmM+NfZchIo6GiN9LPPMdYw2yRBPjTlrIzAsuxVd8vOZUOp0eNXKOfvf7/WjaiaM6oiji8/nIzc0lJydn9D0nJ2fUU3o0VEUhFvBjcTgZSA5z4YtXEdeHUKUc9MLb+F39JIyrXmXrK8/zyklL2Vs3DYuq8PyEMiYXZKmck00Bhh7cCzq4z6/GPvt4PaYPwuNdA9zc1IMn7OeHOx4j0pHBrHvwGPPxmPLJsZdi0k7cNwWrjLHYjqHIjrHIhqHIjuYx8ak9LWwIxigxG1g2vZZc44eLtj7T+Aw/2PADAL4949ssrVrKuu51vN31Nmu71xJOH2FkkgSJqXlTWViykAUlCxjjGpOtN9B0Dm3sZePzLcTD2TSHvDEWBjyv0HjoeSp7NKr7BCoGBUTl+ELesN3F3jFVpH3lnKmX4lg0E/tJNRhLHf+00+Q/afz9d+NjscO9fB8DW7NSBIIoUFVZRW1tLbW1tbjd7mO21TWN3tu+R+jZZ9FFCFynsLnGyoNBLSuLcMDNnEg153/ze+RVVJIZjON/o5WH928jIrchCxqqLmDJqaKCYgL7NdAFbCLMdOg4hey4rqAiI6Gg8raxiWfHeNlcVoEuShQHY1yxfhBzJHudZdUGFl8/40Np0b2ws5tvPrWbtKoxqcTF/dc0EExk+PPqFlZs62J+TKZGU0hJcQLGGAOmGJIcYtjST1veWn7U+WXqE1WEjBlutWjonVuZFdiMeYQmP+3ykc4tRjRbqPM66Fq3Ck1VceUXYp5/Bof270XSdTTZymXGBqounY6S04+/cQWRbz+I2JmNFBvGnkngwmHCpWsRdBNu42wcNHD4VT+R/iAWcQOzc1rIMWcjNXHFwM5kJa3mMUgOCPUkiPZlx1hbYYzyU3rImATu2fJleiIVGI1+rBW/RyJDXbCOqnAVIiIaGmFPC47i3Yx1SYyx+zAbczAYvRgNXiTNheA309zt5+7QiwRMR1KgStMGJrsF1iaTBLXs4jYdbED2L+a6cc8wOSeEPlCD/7BI36EB1KMcXma7g8ppM6ieMZuKSdNGU42Hoym+9fRuVh7M9s+Ftbn8/JLJ5DqyhnKmp4fIqlVEVr5JbNNmBPX903c1QafHK7C/TKBtaiHS1AmUmiYwtK+MNzs1ujUNGYViYYjTzH6WVmSozw0hBdvQh1vA34qgvzfrmKZDOGNGcWuoNsgfTKMBf2udxnDyqNICAWoGuqnpyRqv+8/Kp/qmK/GZbahKhIwSoWXYz+8PHaRFbQIBBFWmuK8ek20uu8ZOJWHKRqhkRWH+zs2cs/ZNpjTuR5Q1evJz6PP6iHitFJXo9PddRlpxARp5hi0UHXoLb0dWp0pF4IC3nKLoEPlTSvF9/2bs5ROJB1K8+Ms7GGjNbpc/dZDqikGczQKVqSBmKdvWOhBw19BWdymtpYtpNebR2r2f1kiYNlM+foP7fe/JO6jUmpkl7eTa+suZnFtPMpbhybu3EBlOUjnZxxmnhxAal5HZ9yrNXTH2h/Joj3nQR5I5BUGix1rJZnstw5YSLrLaOemcWnxVLrZF4mwJxdgajFFwKMbp22MYVUgYBV5usDGYZ2CG28bPp1WSc4IMqA/Cf42gTxhUTeXyVy7ngP8A51ady4/m/ei4bf6+sZ3vPb8XgIZyD/ddOY085/GTSCKaZuVfD9C+JxuCrZqWx+Kr6zCdIAXnw2Bt91q+v+77DCYGkQSJz036HDdMuuGYKFWgt5sn7riFWMBPbkUlF992F31Nh1j92MMMj6QaQNb4mbD4NBZceR0m60cPYX4SEB4a4G/f+jKpWIwZ517Egiuv+6ePpWoqLx5+kd/t+B0DieykMTl3Mt+c8U0m505G13V2LHuRt/72ALquUTR2PMXlM6lsyhJfvO5aT/eCFF+Z/hXcZvcJf0NJp1n18J8RZYnpZ52Pu6CQeDx+nKEzODh4DE3qu2E0GkeNm6MNHo/Hg/RP6Aa1DHVw8bLPkNH6USUvJWW3c0tG5eATfyUeCrJ58jzennMGIvDopEoW+7LPr+JPMvC7HWhxBWtDPp6Laj78Ij06AE3LaTu8gVPcVzD9YDtfPRiiwFKJSTpxDZrkEBhMCvSHMySMEvO+MBFPpeuEv+nPKJyzrYmWRIrpIyKulg/Q3FrZsZKvr/o6xoyVq4o+wzkF51FQ5cI2EtVTNIVdg7tY3bWa1V2rR1mQ3kGJvYSFpQtZUDSPSYlcUrv30/nqBhJ79+GIdCJpxy8AJJcL84QJmCdMwDJxAqa68ewbhrOH+9EEgXu3xZk7lDWUJLcJ93lVWMadmNDh/fCfMv7+X+DjtM13VjxAc3OcskAIZ+rYRaTs9WEtLcNeVozFZ8P4yFPY31yLJZ0kev0p9BS9zh97IqgijG23s7CzmqZz7UgZmfmtE/AMFbPMcBCrmI0q+jULjmgJRfFCdHQEBAoNOlOtEoYRbZV9lsN8v+T3/KTj21Sn8skIcPtEM8vzZc7c0c+0wxKCLmEQ4sxzPMg4y0qEgokw5XKYeAnY8467Rl3XuXdlM79akSUvOHVcHrOrfPxjcyeH+6NMT8nMTcoYEdDQ2WFUWWvJgJCmXmhnrrQTg3cDy1w+ftB+M6XpAvzqIG91PkJGT6OY7aTzi1GtDjpVFxsz5WC0coovyZi9zxFzuFCcWQdjOLeQKwy9qI79JB0dmA7pOB9JICQyYLBiarga6guRcSEmbBAHQY9gFJswCk1YpPUYxSzbnGqwk5n2OYyLv4ZodtHf0swr9/6UQG8PgiDgPHkuv/cESKtNiKlWNMVMvO2L6JkcRHMn+VUPU2ty4mpqwBv3gGEkXVdKU1q6j6LiA0jSsU6Ogx0SDylGUgaBkkGdOQc1XpkhEjdnx7CqiIbDamDnyH5axkmy73yuKl7Mt86sw5pnQ8mkaN+zi+YtGzi8bTPJyBHHjGwwUj55KpGKmfzmoMBQLINREvnOmXVcO7cCcYR4Sc1oHNzTxaZ1+4k06ZjiGp5gE7ZYD55EC9ZkC1IkgeEEZGuCqGOwKRgdKgaXhMljwOgWwZbELPlPGA080pdk4lo+3bpINJ3EH/PSl1OHX/DiDRykav5BTKKKK5ChqDeFRdHISCJBuwUlBnpUwJ7IYEQFERSTiGDRkCUNUddRNIFnLDbu87qIjEQzKwdzCHivonHMEWd20UAfSzes5ILG5RRbhjD70li8GWTz8eceVX28Ff4C7amG0e8K2UNZ53Kshw+P1oQZnRlshQrOUxqIlKfpj+1kaL+L9vZcYoqRfHOEs4oPYZMzxBQDjeEcOoUapt7wQ0rHjoUt98PaX6PHhuhP2jmkjGVnspQuwYTflcP2iXPozStB1EIY0mHGHd6MVjCbPTklR/NgUGUWqOvSKdgeYqxk4LJbZ2CyGt65ATB4EA6+gn/zDnYdzqU5EiCcOULkEZWsNNprOGSvIaeski8uqmJJVS6rHztEy0gpR6rUwuq5LrbqaRQBzKrOvnHV2Io/OnnWf42gTxgeP/g4d2+6G4fRwUvnv4TPcuyC4/kd3XztiZ0AXD27nO+dMx7jCTRwepqCvPHAPmLBFJIsMu/SGurnF/1Tntx4Js4vtv6CJxufBKDCWcGP5/+YCTnHFs4H+/t44o7vEB0ewldSxpQzzmHby88R7Osd3UZDp6k0ypWf/x4La5Z85HP5pEBTVZ6881a6D+6joKqGT935UyT5n6ut2tS7iZ9v/TkH/Vl66GJ7MTdPv5nTyk877n617tzGy7/+CelEHJvsYl7+RTROCHK7+CsQsmw9X5v2tWPoct9BKBSiqamJvr6+0TS2ePzYvPGjYbVaj4vq5Obm4nQ6PxZrmK7rJCIZwsMJtra18b2Ob6PQjSa6mZf/P8xeuRJ/W1aosXfKHB6dfRY6Aj+qKeb6klwAtLTK4B92kemNYSixk/f5ye+fbqbr0LsLGl9Ha3qNrs49tA9b2ZM8lelKFQX5c5BGUkV0TUWL9KCFOlFDnWjhDoRUO1FcRAwFqGYblVVhnFWlyJUTkaunIOcXIuXkIB5F+344nuTsbU0EFZXz89z8YXx5tuha04mFUoQGE9nXQIK2zm4a29twJnMwqkccGrJRZOpp5UxZUnpcuL8r0sXqzrfZuesNIrt3UNGjUNkLlX061uM1YFEkMxFHKVFXOb55DdRdvgBr1YnTZ793sJ2/9AbICYf5y6YuyuRy9LRG3k1TMJb+6yaa/x/xcdrmpwc28cs+E+g6nniE8uE+yof7yA/7j+F2ihtMdPjyafMV0OXJQ9ODePp+gKiFUA3jwXEteaoPg6bgScsMqxF0LYRJzSApKlrCSWnEhS+iURhUkHWBcVad6qP6+5A7wht5e+gZFtlaM53PtFk4rU8hquq8mUyjZ0YiDMYAimsXc6V1zGAPxncK9gUJqpdkDaLaM8FgJplR+PLjO1m+P5sG5DTLhJNZY680I7IkYSBnJHIxJCVI2HYw3riTKaZe6sZPxjhhKbS8BVseoDcj8kJgJqeYb8Ii2+lNtvFn2+PYrDUUG0somjiHXRE7bx8aQommKRfiTDAeQhQyCDrUxByMk704rTbkpBPlwNukD7wA6IiuUiwzv4hks2MQmrNGz4jhI4tH5j8ATbcQ1S9AOuNmrHNqANj08jOsf/zv6KpK2iqwavIAvZ5jx2ZNdFHe4aM1di0JzciScXn86eoGkpE0r/x+N929ncScLSiGrNFqFSQmmQ0U2ZJoBHijZzOP1ETQRYGJ7TqfEyRMdVbSW2ReSwZ4fRJkDNmxoLbPSMApMzhCxJAJTaas/zzuEguoKHKO1jRK+RYGQ+0c3rGJ5i0b8Q8MssEzix3uKQDkCXG+NdnAksWzsblzadrdw+b1Bwg36UjKkfnSLIQoMh6gIz0ZRbcgkyLH0c+kMYMUmTrQ+jejB1owiyoGs3pcPdIx7aQKxFM2+jJuWtQ8Doql7DFU45TzqU8144ruoC2UHWNtcgpzSS5tllp8whBf1B9B5sMvdXUVkkEDCb+BLaKF302x0JaT7Y/WlAd/3vVEXJMBkFSFkw9v5orulSxI70LKhEDR0HURuaAYuagUQTaCZEKXDBwYTLGnN0EamQKPg1TUSNA/jnBqAvpIup9XaKNy8HUcB/YgqNnzNtgUvGNjuMfEEQ1HrkXRBBKaEaOnEM1ZStvhbgIRhZhipNCeIt8wRGvUx75oMf7EkedaEiXWzTiVNZMbcAw/iDmxYfR/PrOPC8Zeidm1gBc6d7NLqUAVjtzXAlnmnAI3Z+a4mOWyI4sC6d4Y4eXtJPdnDR8djaRpPe39r3IobCWpHtk/bTKTtJbiEE7BolsRJYFZ51UydUkZgigQSymse6mRXiNcs3TcP7Uu+a8R9AnCUGKIc587l0gmwm2zbuOyusuO+f+K/f18/pFtqJrOtXMruH3p+ONuuqbpbH+tjc0vtaLr4M63cvoN9eSU/HP00jsHdnLr2lvpjGQpjK8adxVfnfbVUfa3dxAeHOAfP/g2kaFBrC4PgiAQC/qPbCAIjJ9/MrvHRXik8ymqXFU8fe7TJyzy/k/A+qceY8PTj2G0WLj6nnuPEW49GqquE1FU3Ibjr7M11Movt/6St7reArI53J+b9DmuGHcFRunEhf1aPMPhP77Fm9v+SlQJYjCYOPvmbxMskbhr412j0YFJOZO4ZeYtOOIOmpqaaGxsZGBg4ITHdLlcxxk6OTk52GwfXX0ZskZOMpohPJwkMpwkPJwgMpQc+ZwgMpxEyWikpDgvj7+PQXsnlrSDc/d9CXfcjq5FEMQE1uoyXnM6GbYInFTq4X8mlWJzmxAlgcATh4jvHES0G8j70lRk9wlqEVJRgodeoanpJZq6txHoTWHoMVDYKVLZK2AsnYOh/gLkkbqawVgLTcPPQKCN4qQJXwz0cPQjXbtktyDl+JDzi9FdXvokG2viEoropMTixSY48cdMpHQz7zmTC2D3mJANEsERZhyry8ispWOoqhRJ799HYs9eknuzL/UEUbuUDK350FIocLhQIFyZx+SxS7HsLoeDbgQErC4js8+rZOzswlEP7TuIKCpzN+xjUNGYt3kFN9gMzD/5SizjfP/Sieb/R3yctnl5y4PIG59mvdXDMocPv8GOJlgwamaKIwKlQZWSUArDUSmsqiAwYAnQZ2mlyynQU/JtdPEDGDh1nQX7Eizcl8QqwiSXTP5RNSLtVoGvzrIQVhNETRY0UUJWMtyxyk/Gb0AFRCBq6SHuPIw+UstiIEONLcpUUye5/s2oOuzWKtkp1rPFPIdNYR/qu1YeNg0WJQyMz2THVEmIMtPxKFMdbyOMPQ0mXAw1p4EhO0epSoZtTz/ExhdfJKOC25jHyUVXYhCMHDZ1ss9ymHHGWqqlcsSoghbVaBb6WGs4iCpo2HQTJ6cnkq9nxwk9HSex/UHUvt0AWCrK8E21Yra0ImvtCCeIRATSZiichmvy2fgPTSF5OHtRjYVdvN3+JM7ubJS2Iz/O2onDpI0a+dZ8GgoamJg7jecCeaxNuBB0nYuffYHXbNPIiDLXzCjj21V5xA4GWLepn+6EQso8QMrZRlrMGpc+ZBqVV3mrJlsvdMZwMXdc8SCD1gy/3vZrVnSsQFJ1JnfKWCQzG4qjaKKAoOsUDwt0+QABNMUG/Uv5Zng2SzhqfpIEDPlWujwGvtPWQ1Msa6RODO/lJP8GDHr2syB5sZpKsJnysMgGRGMf5ea9VIn7cEn9CLm1aGYvykALxvSJ56p3oAoiqpJLJmUiPZwh0ZckExZJR2WUhAgn4MwbNjsYdrgR7SqF9iEqfEO43XFSJgO/E64jgYVzWMEE4z4CThm/p4r4YBczghEUoHu/C2FAQhNtGMZOJtw+hNreTcii8veTRdbVjxBu6GbC3stI2heDIOEL+bks18EXZ0zBHQjQd/vtRN96CwDzpEkU/fhuTFVVx50vjKSAPr2btJLtUy6LgdsW11DYn2Hfmh6UdPZ7qznGmOBL5G7fiJjO9iVR1nBVxfGOS2E0fzQh1qQqk1aMqFGdZk8FK0ureMnQQliIIiFwYekS1vr30hvLGvh2g51Lai6gPLqefbqLLdo89kgNJI+6Dx5JZFEE5h+MMmtYxaSDdWoezlPKkH0WSMdQD62g+a3neG5nCjEaOyqqJyIbi1FyTJSceTHnLpqDxZg1BLVUmkx3N6bKMR/pGt/Bf42gTxBuXXMrL7W8RL2vnkfPenRU+wFgw+FhPv3QZtKKxoVTi/n5JZOPW7jEQilWPLSfroNZ6s+xswtY8Knaf6pgLKNmuG/XfTy490E0PTsg3zXvLmYXzj5u22BzE8t+cCu9qThIEvoxTGACY+fMY97ln8adX0AoFeKc584hmApyy8xbuGLcFR/53P6v0XVgL0/ecSu6rnHWl77BuPmLj/m/putsDcV4fiDIiwNBhjIKkxwWzsvzcG6eGzsx/rDrDzx16CkUXUESJC4deylfnPxFPOb3JlU4mgI7LafYrLxOd+sBEAQWXHEtk89eymO7H+OFTS/gjXjJT+Rj1I5MVoIgUFJSQnl5Obm5ueTm5uLz+TCZPhoRha7rpOIK4aHEiJFzlLEz8llJvb9oXK+9lRW1fyNm8mPK2Dlv7414k8Xvu0/2IsBikjBlNCwieCbm4Cp3YnZJhAzD9MV30TK0kqbQAaJ9EUo6RSa26Yzv0DGPZINJvhpMEy9FcpcDEMkEaLbsY9o3ruKljlf4064/oegKHpOH26Z9B+MyGx2bDmNWwjRMB0e8GaWrlczAAGl/HCUuoKU0BO3DD5GaIJOxuFDtLgaMGYZsGnqOk4UzluKuLMVYmI/gcNCxcjcdr6zD1N+CI9KB6aiaoFEYDJjHjsVYP46dvigPKqtp9iTRRAG3yT2qKfUOvLKPkuFxFPXWURyqpbDYx0kX11Ay9ti+93x/gC/sb0dWMlz3xL1cePGlTD1j6Ye+xqPxnzD+/l/h47SN/+2foP3uXtxVcWSzxk6zhR8XFrN/hPI2P2Pl8ldiVAZyCV96CYfjccLRYw17q2DDLuXSZBLot6TJGAzEJRMRzUeezYvNZ6Z6exhvR5Iig8BEm4QZgYwABh2GjAKfmWWlx3ok9pQXSnPexjAFwex3ObLAVIvEgKKzWesn7DrAicRYVB2iuol+zc42pZQUBgQ0CgkQ002MS9s5KSEjYgA0JljfYNakbsxTl8LYs9AlO4o/gTKUfbXu2s6mHc8RjmdZE32mIqb5TsVrOrHchILKBrmRQ3KWfcsl+PDaJlBhC5IOtOFqWoFjVyvEdQRRp2B6CHfVsREb3VKAUN5A1FrB8lfW0R02Me7U85lw2YU8cuARtvRuZmJjGad3TGbz4Msk1CiaoHNoikb+SVNpKMiyt5XYS47IH2g6tzZ18beerPd8/oZmtoSzhuuXMXEZJnRd50BapymhoqNiLe6kXWlifcFW+qx9AFxnP5ubL/wx2/q3cdPKm4grcURB5Pzq87lx8o3k2/Jpbt3GvW/dzSoxm34oajq2JESsI+uNUA2LtWv5ltGDPNCPkPKzTfCzVhjGRpQCIszS47gIIGmDmMQQFjGBWcrwUWQIVdFBMFPAcLqAkFpASCkAQw5a/WrEkl3Y7JVMnfJXzOYiNFWla/k2uh9/BsvBdZgiw6Dr2UiIliUKeC8IJo2Ex0y3rYSox4p52l4etwp06CJVvRo/ifsptieIDxppXzliEQIZCV6ZIfDUPJmMIZsgmrQvJua6GAErNW37mdq0i4unT2XqaWehrF5D34/uRguFEAwGcr7yZXzXXZfV2Xof7OgI8O1ndlOT7+D2c8ZnSx90nWTzNna+tJp9zRUkNTcAJiFCeXQVObs3YE6NzBWCgOP0U3Fdcha7N73K0L5N2OQ0DkMKs6Rgk9PY5Aw2KY1NTiO967lcbrXwvVwfMVEkV1H4+cAw01IpMs5ilpVP5kFtiMPxbP+SNJkZRpkluQF85nxilfezcsjE68NhQkfdAosGp7jtnF3i4xSfE+e79IH83WFu+90quoIHqIseIj89OPo/s5Qh35wkV/ZRmjSR2duIYLVSs2b1fyNB74dP+iS8pW8Ln3n9MwgIPH7249Tn1I/+b3dXkMv/vJFYWmXJuHz+cNU0DO+qL+jc72f5Q/tIRDLIRpGFl4+lbs5HLxIHaAw0cuuaWzkUOATAuVXn8u2Z38ZpPLbddF2n66EH2f3QX2jO96CM1INIqoag65TPnsv8yz+Nr6TsmP2eOPgEd226C6fRySsXvPKeNSyfRCSiEf7+ra8QGR6kfuEpnHHjzUC2LXZHEzzfH+DFgSDdqRMUYOoZLJE3cIRfRNeyE+eikkXc3HAzla73Z2Y7hgLbaSTnMxMQc0y8+dAf2b3iNQAMhaUEXHnoRw0EKTFFwB5g1sRZXDL3Euy2DycoloqPRHKGjjVuIsMJwsNJMskPVsa2uYxYfWZCNpEmg8YeUcFvE4hIryEmnkVAw5SxctpGD76ITNnEOUw57VJU2clv9nYT9icpSsNM0UQymCIaTKGdiH56BMZUEG/gIF7/QdzBA5jTxy72FF8JpoYrsVqyXre0lmJ/YD1qCZxywecQMlmP5mFLF99d912a/E3Ma72YCf3zQYCxswqQDeJoGlvUnzzC7q3ryEocUzqEMR3GmApjTgdwKL1YMkOkVBVVUbDHQ9iS76+Q/n7QEInZCtFKayg+fTY586ZjGlvL5uHt/HjTj2kJZdMIJ/gmcMusW5iUO4nB+CBrutfwdufbbOjdMEq4AdlJqyhUQ3mgnnmF8zj7gjmjNKO6rnPxzsOsC0apbj3Ahcsf55Lb7qK0ftJHPu9P+vj7f4mP0zaBJ5+k7/u3I9nNFCyUcToa0YBXbVZ+YfcyNGKYTJbK+bTvU/xx+x/ozdMpihVSHCvCk/Yd5zSPaUaKEuWcd/IsvNOKeOHebcSHM9RbRCpHdDhEgmi4EYwi+87K5fauFtpduUiITGpNsWR3HKMCgkFk/kXVVJhFgs9n6xd60xprM2k22XsYYziMTdBQhCMLwT7Nwap0NSlk7EKKJYZG3GK2CF1QDciKmRzBSF2+jbzcGmyaPVsOE8ygBrOUuUk1zo7hlXTEsqxcZsnGJM8iKuz1KIJKxhhDkqOY4lnHy07XNl617MQRzcWi2NDRiebIVJk6uVRvJWdwH8FGjb6tbnRVwGBTKD4pgOYS2UYtA3oNk7Vx2LSxaHjpK4Wte+4nFhimfNJUJn7hKm5880YG4gMIOkxucjG52Y0AOAxe5hSeR+UV87FNPb4mSvEnSTYGSDT5+WM6xu8rs46tut1B2npjCLrOT6tyWbq4FlOFiwPru2j56R9wDL3MTy+GjjwQNZGZgzMpTZZSWl/Kn6N/JkqUaXnT+N6s26i25EJ8GBKB7Ht8mH3DB/lN1yo2EATApGmcG4nx6VCYElXlo1d/ZpFSJRKqYeQlk9bMiORilosxS2PRKUXRi9DJZq/4FY0WFXoS6miimsk1gKf6NXJqWihQbya+fjMF8ZXkGxsRBZ20KiKL2qjRpaYF0hGZhN/A8LCTwbgLojqueAzxA9LfZKtC5ZmDSAad7u1uNg+OZflED+tn9qAasm2TMdYQ9V6DM+Nhwp5NTDi0DXsqia5l50kByAtFKfFHKC2toOSeezDV1Hy0hnsnpXvfs2h7n0IMZQ11RTewP7WIzdFLSCnZdHFRFijV2yhc/zDWxJGoWshl5pDXw5DDMpqJUODLo6R/GO+BJmRNQzToaF4jq675FC+YdtOjZp+hBsnJzzQvOTE/+Fsgk13DaMBbLi/32XI4ZEqOXu80q8Jpdguztn0HKVbITo/E6jo7qzwivcqR+kWDIDDPY+esXBen+5wMbh5k7ZNNKBmNA3adVw1JKkLtnBXdjDnRT+qo4IA9mabYH6E4FWfC449hqDqybv6w+K8R9AlARstwyYuXcDh0mMvGXsZts28b/V9Tf4RL/7SBQDzDnEofD103A7PhSCfQVI3NL7Wy7fWsSrOv2MZpn52At/CjpzKpmspf9/+V3+34HRktg8fk4ftzvs+S8uNrd9RolKYvf5WuA7vZVZ4tzrcn01QOBCkKRBABY1UV9vnzsS+Yj6WhYbReQtEULn35UpoCTVxedzm3zrr1I5/r/wV0XefFX9xN85YNeAqLuOrHv6ZVE3m+P8ALA0FaEkdCznZJ5MxcF+fneRhvM/Pb/S/y2qE/kklnc9szhnJinsuZlj+Tc/PcLM11k2c6cU1R4sAw/scOZimwC2w4rqihw99NY2MjTY2NJDsOY+rvRAAUix3H1NmMnTARxatwX9t9tISzC+OpeVP57qzvMtY7lnRCOcaoGTV2/EnCQ0nSH0KJ3eo04vCZcfrMOHIs2XefGbPHxHYyPOsP8cZQiORIhERUgxQM3UcmlaVGreixMnevj8KCChZd81kqJk9D13Vu3N/OcwNBXLLIz8sVYvFGmgJN9Pd0c/3W8zBkbGy0HGK1YTN1XRmqe8KU9vXjjvqPOT9VNBB0VRPMqcddOpNShwtJyBZPH47sYp9/DaqxjGL7mVgkCcuIXyFT6iCq6/S2BxAy7z/VyyYJV64Fd64FV54FZ44FV44Zl3EIe2wPQu8O6NmJ1ruLz1Z/i1dzF1AQG+DxTV/mfkknkDFQERG5Ri/HpLlQkhKxQIyB3n5ckTC9ObmYxtQxdtZ0LBMnsL/dyu71g1ljUIDyGS7eLnya1wZeBsBj8vC16V/j/Orzj6sJA0irabb2beXtrrd5u+ttuqPdx/zfGy9khnMOl8w7h4bSaTQnMpyy5SCKDpe99Qz/c+kl/zWC/pfxcdomunsfHd+/i2RbB5ogY50zE/csH/5X1zLULbF+nIGtYw2U97oQkOnKTyNqMgZVZmFoFrGMgbQYB10EXURAQNBFQETQRUTNiEMzMdNiwTNSe9qWStCUlFGBuCSg6TqSdnxgpy1X5qWZNkRJgMYQDX1pfqBbMAoCQ4rGmpjCco/GpLJhzhh6hC1KLdvUMazPVKAh4iHJhWI/4zBgxYYTEy7dilO3Ir2Hmr2u67TE9rJreCUZLTse2z2lCN5q4rKK5OqgYuw6rNaslzzn8Hn4Dl+Ajsbbhp00SwEsxLmYZVSRZdbSVOjf7iJ4ODunmgpchGuL2BYPEcyYkX3FHBx/ARv64DrFyHmawKq+x/GnetEsPuKXnsuywC+IKRHqDGNYvDufRGs2jWj83MVMNi1Ea8s6JmwzCnCeXk66M0KyMUCqKYgylDjmGl8rN/GDsUYUdPI3dxIKShjVDA9MNzC9tpC+22/nYLiZey6RCDgEbBkbt038AcGmIZqbs+nSghBhqXUVUwgjJgKgvfd4v9ls4jceN7vN2YwBl6ry2WCYT0WiKIj4NTdB3QWqE6PiIqk5CUgQs+jkuAopNVZjjHjJBExoOFA0GEi20xVroifeTEo7EkkTEPCaiiiwVFBgqcBrKhodx+KqTktaoz2loaLikzsoMW1nrHkNXrkDUTh+iRrOmIjaa3BOXYpkqiR2YJDYpi34Y1vYcnEhq7tmM9BcRHFkmPHRdqbE2nCGwjiiWW27mGzigLcC8ziFSwrXcFC2ckXJXDJCNkqmii4S7k8x1TKN8hXPU9x6AKvTyVlf/h/yK6vZ9ec/sG/1SoJHze02t4fxC06mftGSEzKzHtenMxm63roP3/4nsQb2jn6viDDkM7FKnMgve69hTFENN9UWM7hlkP7WdzIGdIyxgxR2r2RMz4HRpyZhNdGa46bDZQN06ruHKI0kUOvHsyMW4PGTT+Zw4VaMqawj/Nr6a/nqtK8eKV/IJKH1bTj4MhxaBrFBdGCr2cQDbhfrLEfKJcYbBa7NfIFTFl+NsdSBruvsiiRYNhTi1cEgTfEj6yZBh5KhDJNbQpw12MoMSw+BDesxdI88i8Cww0KXz0m/04r2zhwn6Cz59l1MnvrR2Xn/awR9AvDQ3of45bZf4jV7efH8F0e1Pzr9cS754wb6wkkml7h49IbZ2E1HPGYRf5LlD+6jtzlbE1A/v4h5l9QgGz+6j6Yz0slta29j+0BW52BRySJun3v7qODX0Yjv2kXzDZ8jpqTYWFWEJoqg6zgzLqYVleILdJHYuROOykMXrFZss2djXzAf+/z5bBe7+Owbn0USJJ5e+jTVnuqPfM7/buxa/ior7r8PQZKRbrqFFwwu9seOqH6bRYFTfS7Oz3dziteJWRLZtHs3r7yylkA8CAiYJTM+WzURIQd/WuWdcVvUdXwGmSKjgXyjAcOIarkSSJLpi6MDmhFCcoJEMpn1XenZSUMQBGR9gNTQ6+haCsngImfM5RjMeeiajj8ZwJ/wo+s6IiJ2xY2c+RApcBYV0akiOzUMLjB6BMweEYvbgM1rwGwyYZSMGCQDsiBzKCGxPKDyRiBFSDly76vMBqr732Tf0EOkDBlkRWDWfi8LbDOZMH4BJcX1dMQ7aY638KhkZINjPOgqroGfYBwxmAyazM9bv0Zlr8qQfyND/i2U9iXftfASEN3lkDuOjG8cSfcYJMmARxaQR7xe3VqE3T1PE84MkHBOxC2egnACY+FoqGKGYUsPIfMQhUU+Tp+0mPxCD85cC1an8cOF4DWN2FAzFxz0s1uRKey/GyXdhEdV+VtPPxUjnrGIZGXJlL/Rbs/FktJImERkReczK8KM0SXyKpy48iwMtIfobcpOdBkxxe6it6hZ5OXGGV84TjvovaDrOi2hFt7uepuVh1exJ7BrtFYDwC46WVg2nwH7ObwatlNikFgzp/4DWe5OhE/y+Pt/jY/TNo1v7mb5k0P/ojODIoPAFKuEQRBIaTrb4yoD7xONBUgLOqvtCpvrraildt5xx0vDSc7pDvOtfhMmTSSk6myJZsgd340iHmZLTx6PqBUALETi+1gxnaC2A0ATFGJymLAYJUiSYTVDQA0Q79+HGAsCoJosJAsr0Cw2ZDnFmMptFFjbMHYI2Pwa7mQaj5ikU7gVrzoNBZVtxhUsER/CIsQ4ZDDQmDZRtMqJu18HBIx1SxFdZRhyOlE/fRmv/u4XxENBDCYzi66/kaH8enb/6deoPXswimbcdTP4RdkTqEKGmo4K5jSZEdMJDGYLp372RsbNX4ymaARfPEx8c9+JG1QEY5kTc40Hc60HQ7GddaEon9nbSjit4tzcRzqk4UxF+dXbv6WnyM+950skDeBLFXL6vhvIEfLIOTfNHxp/xoKhUj6vvEkuxzqNMNrB4gWrF6y+o15edIuHN9OD/LrrTdpSWUce2SYBVeLsDVZO22dlZ30eyXPHs6ThNKbnTz+S0j/YiPb49WSGVBLadOLSBWgpA5quMZzqoTvWSHe8magSOPaUzFaKy+so9hZSkdmPO74BWesAVCThWMNN02Ewaac74aQn4cJafSpTLv883rKS0W10Xedw46O0d/0gu+LucKL8rYQNtjKWVcxiknuIYilMR8bJzkg+fqsbXQTy4XLD93nDmiIjCFliAvupXFpzDeO2rKfjjZcAKBk/gbO//E3MOvT94A4iy5cDkBo/luGF8zi0dweJ8JEazsKaOsbPXERVzXSklIQaTqOGUtlXOI0SSvHnkm7+VFxBMd3cPfx38gNejIlchlO5bIuUMiS5WTKzhNmTC4irEZp2bODA2v2EhguQjEdqjeREG2Pa3qC4f/do9CstibTmuunwOamZv4hTvvAVvrr1Nd5u/QWSFkLUZK5KL+QrV9/9niy+HXsH2PLnpxlj3Mx411bMaicHjAYedDl5w2ZFG5kfJznH8LmGr7OgZOExc2ZTLMkTuzo4uGEzpV37mX5wL3Xth5GOWj/qgkCzp4RtObV0lPo469SXcZnCBFucDB9yoySNfO63f8Nkyj3hOb4f/msE/R+jL9bHuc+fS0JJcNdJd3Fe9XkADESSXPLHDbQPx6nJs/Pk5+fgsR2p72jdPcTKv+4nFVMwmCUWX1VHTUP+R/59Xdd5pukZfrrlpySUBFbZyndmfofzq88/bnGXSSY59IPvI7zwEilZYl1NCWmDjNnupHrWVTRtMyEbJS765nS8Lo3Y+vVEV68hunYN6uCxE7WxqootY1ReyO3A3TCH+876y8diHPtX48DhJl79/rdAybBqzplsnXwSkA3lLvI6uCDfw2k+J/aR3FZVU3nwzceIPZuDQfv3iL9qqp9M9Hl0LQgYMNjORDK+t3GZkKNETH4ipuHsu9l/1OcAinQCirF3QZELSdnmkrTOQTMc6X+iEsTj38zE/bvQhFYOjMkW5bojBir7ncTKLaQEHU3V6DEOoAgqKctMwrlfBsA+/ACW6Com9TmZ22xlbosF80AnKMcWeIrOPAwVkzFVT8ZUOwXJ40I0yajxDKlDftRQ9hokp5F2bz/rVv0ZgEzDAq6/7PPEQhmigRTRQJKoP0W6O0KiL07fyEKv4axyJp9VzG93/Ja/7/87OjoFtgLunHsnc4rmfOh78w56kinOeOUr6NH1iKKZv836PpMTMejZQbprDxfZb2RLQQmOuMYtb23h8YYy9uQV4o2ofPaNEKZ3OWwVMY08UvdlssnMOreS+nlFiP+EoRJKhXhh82u8sucNDpv2kpKzHlpdMOEv/Ama7OP6PJUf1f9XLPV/Ex+nbQ6/8BKvLbMgkUFCgYyKoCqImoIsK4imDDFJpcOioogKBiGDK21D0mxoAqTRkMxWZteXY3Z5EIA96w6RDpoYb9GpMmX7Vj9R1tBKTEijCxq6KNLl8aKh4oyHWJUzHqU7SSIjoZDV1cy39lOUM0CkqJikWEdJHMpjGieFhpkyaEXUs2NlCp27SbCSbOe+GiM3jJg/ESFJSIgTlSJIvkbMhXtQbL1kLMO840HSNRjc46V3ay66IoKgYy834C60Iad1ysxB6hxJbKEBxGDnkXbHxtOcTadezCmZSVRouaTEND+cFOCwluG61XczaaOKLamDwYal4Xo6pW4qrGFKfvlLBFkmFgzwym9+Suf+PQDkV1bT39KMKEloi6bwN+Nz5PmNLNhXhHVE3DFgyePiL32TGslHqjFAsimAFj0+fdpU7cI+uwhTtfuE2m8HYwmu3HmYurdX0dNlptVZRI71ddKlq9BFmF04m7sbfsLah9roaQqioTJc9ge+qa3DpiSJCA6e008lIOWx8MwLmNJwfL2vrusMd0c5vH2QA1u76RhK8GLRRhIFyxFHUsHeQW2XzhdfUSlN2XCefTbuiy/CPHEiwr7n0F/8EqQShKUriCQvAU1CkzMEx75B2L4Vc6QUQzyfoKGRgVQvQp8D23CYAilIkTVMril2XD2RpksE1FKawlY6IyK9CScZ3YDNXM8E92yKTG4iOkRNMlFZJKzoZNzLyZvydwRRJ9w5nZ5NnwVNRlKSuOOt9FqDBIszCAK8aJhIqNCH5j2AJfoPJDVrNM5JJDiv7BpmTb6OV3/9EwY72kAQmH3hZcy56HKiy5fTd8edqIEASBLuy67DcdplaDGNTDBOe/NuGls30RNoRB8xRiTBQKltLGPsE8k1Z0XsUyLcOS3O674j82q1fohbuAMzKQTFjDVQizw0hlC3gc7uYYaTRwxpAci1liFJEwhKNegjNPa2WC9lnSvIH9qOqGTnR1UQ6PQ6+NsF9ezJ3YaAhkPMZ8kqGVdMxpWXz8k3fBnJ5WFgYIBMJsOUKVPQUiJP3LWFZCxDhVlisllEFjqxe3dgtWyhK7iHh1wOXnDYyYys76plB9dXXcJi+ynEN26l54WVSIf3ImnHrjc68wrZVjeBbeMmsrNmHCZLgmQXZHrBlwrw87OHaKiZg8MxkYFAjALfh3P+vRv/NYL+j3HzqptZ0bGCaXnTePiMhxEEgVA8w2V/3sDBvgglHgtPf2EuBa4j4cXtb7Sz4dms1kBumYPTb6jHlfvRtXYG44Pcvv521nSvAWB6/nTuOukuShwlx2wX9Q+z+9kn0e9/CG8wgiIKrKktJWEy4C4o4up7fo3BZOGVP+ymfc8wzhwzlx7FDa9rGqmDB4muXk109ZrjokRJA9AwiYrTL8A+fz6G4g9RIP9vwHBa4eXBIC9291P74C/ICQzQUlrDc2ddzTyvk/PzPJyZ68LzLua3nmgPdy67h+q3l2BR7CRyhpkxcxwOkyMrnCYICCPv73wOKAo7ghF2hGMMa7C0O8OEULaNNnkU2qUhxppEygoKKCwswOlynuA4kEnG2Pjs7xlsOwAITDzlYurmn4MoZCNGbeE2BrU+NEcKRUqT0TKk1XT2pWU/Z9TM6Oe0evw2Uc1Ij1hDvzSemHzkXglaEmtsO2NatzJzTw8GVeftKUMMu7ODmysiE7EqaCcIVErGOgbyvoUnHOFT215m6fa1mHvi6O+qPRJtVmxzZmJfdArW2XMwlhzbV5ThBKFXW0nsyxYQC2YJ5yllHPRvZvVjDwLQNn0Bv/jG/2A8gaHQuKWP5Q9kc6CrTSInfaoW+5wiALb1b+O2tbfRFe0C4LKxl/H16V/Havhwz56u69yz+R4eO/gYOhKh3G9wRdUi7qktITSY4OvL9vNqmYyk6vx41xquCt9OwOThtKl/oNucz9yBHYw7tIl4qpq8aBnO1PFRWgDJIFI6zkP19Dzyx7hw5Vo+koNBUzX2ruvi+ZUraTLtot2zjz5fMapcwN/nXMTcwhkf+ljv4JM6/n4S8HHaJtO2msbG28gLm3HuO4wYH8Z/yIH/oA0QECwqvzlbYm2NzOJYnF8NDI3WcoQEI10GSApQkVHANJUXem5CyHiYYZVwj6S/vVyi8FKeia/t7qZPGKJV9qMdJTqp6dCnOenUXEiyxKc9PZQi4kjnYE3kISeybIQnQgCNW/Q4ewUNSYfPGnVqgzZiqk5GD+HLWUmHzY2ejGIlgc+sMrEqh7IcK3IqSt/hVpZv9jOczJIEFFpCnF7YhM+UOOHvAeAZQ4trDs/0FBBL6xgNBiaNGYO1tZjaiEi/Uadry8+oaW1GAER3OdKs67m3ahmrXFuo947naw03j5IEaZrKhqcfZ+Mz/wBARyd5Tg3Lwm/TcNBD2UB2fJAEIyHPDHKc0zhDsBwT5RKMIqZKN8YyB4n9w2S6svWMttmFuM+pRDiBDEaqpYWO7/8AZesWBs12vnxVPVruNgAW7YLv5F5O4de/wbOHX2b1402cF42wyPlHJEFBL5pK4rwHeHb5htEUualTp3LWWWchyzL9bWFatg9yaHsP8WEFHZ19BpUV1gwZASQxTmXdMiLyfmKZIzWOogqfWq2ydJOOpIOYCzklIaxlufgNN6Mr2chEzLeHvvF/RbFknaMSJkqHZFz9fbiCaQzvpgQEQhkTPXFnNtITdzKUso2KbQIYHeUIwhIE6cSLYU/tcvKnZGU+Ip3T0Q5cixoKkM70Ujm3hllXn4NokHjilWX8OqbT4VKxB/5+JBtB9XF1TxFfU15BEaz8rbWBYELHYnWwaP6nyRN8hJ7/A+lDWQpp0VmCedp1SO4Tp7wllCjt0X20RHcTyRyJylksRiyVPh6ecTaHzBXY9AhfVn9Ns1TNAPlYMwkuE/6BUT6WkENNiUT7rDBQjHtoHPnNOlLbZvTEMCmji86SRXQXL0CVsmtJYypIWf96SsL7EIfagGy62dYagV2zJ/Op075K1+EWDu3eRVqQ0A3HMtY6nU58/nFEh0y4JJhvlzGXOHCeWo55bJYhmEgfyv6nad32c94IQNuQldp2mNCm436XOodqsyE35BOviRKu6CLotbOdGWxlJnuEKWSOZiRMqZiHU9wytZzr6goxih/d6fcO/msE/R9iTdcablx5I5Ig8dTSp6jx1BBPK1x1/ya2dwTJdZh4+gtzKPcdqe/Z9lobG5/P1nhMXFzCSRdWI72fPsp74I22N/jhxh8STAUxiAa+Ou2rXD3+6mPqCPqaG9m+7EWGX3uNie19mBQVRRBYMzZrAFmcLq780S9x5WU9FUerBFdMyuGsL0xEOAEdjBoKjUaJBt58DVPo2AnLWF2Fff4C7AvmY50+HcFoPO4Y/yqEFZVlgyGeHwiwOhBB1eHU1S8yZf9m0jYHOd+8i/Mqy05Yv6PrOi+3vMyvVv+O03bcgCPtxZCv8unvLMJkOX57TdPo6enJ1vY0NdHb24tRl1msTKVUdaII8MN6M68UZ/c1CgKLfQ7Oyzs26vRuqIrCqof/zK7lrwIwbt5iFp17HXp/mnRvFEOhDVtDwQnvzXshpqgsGwrxTH+At/2RUeJKSYDFXidLhBS+DStpWbsKJZXicFGUjRP8ZGQdgyozwT+R+QUn4ek3EoqEiJIiYVDR03EatD52DxgZ39hIRe+xNSqCLCF6xyLnjsN1wRK8VyxAOMGApyUVwqs6ia7tzlJMCWCbVYhzSRlbXn+WdU8+AsDWaYv44Zduotp2PCVw254hlv1hD5qmU1PuYFwwgSAIuM+rGjWE4pk4v9z2S5449ASQFSi9a95dTM//4OjIX3b/hXt33AvAFVNu515/NTrwFZOT4bd7eXSWFQSB7x5+jS93/Xh0v22uSZw7+Veogowt8BjO8Kt8OhTmmmEIp6vp18bTL0ynJ1qCqh7fJ0w2mfwKJ3kVTvJHXhbHBz9T6YTCttfb2bWik4A0QIfnAF9cch2T5pV94L7vxidx/P2k4OO0zZb9fyXcdycAYgTMW0XioQYCHR1UtQcxJ0YcKRMEZtYJ5MkxnHoE47tSiTpTk3g9+D/4ZCdTrCIGQUQgDNb76TNr+II3IWsWFE+At127CPUNEsZBRLdgedexnJoFp27Frpuw6WbsuhmbaETRFJoFKz0enZA3TjiTYkubhwEd7Drcpu1kmrgBixjGbYtgVzsR9BMQzACqLrB5qJRNw6WouohRVJif18Zkd+/xzPOyGcrmwPRr0Srms2brXt566y10XSc/P59LL72UuwZjvNo+zF83RilJgBrqJL7m5xhKGlDHnc1bgRdYU9LIvjFhFDm7FBonV/K5cZ9n1oQl9Lcc5qU7b0FVMwgIqIKOoIOIAIJIu3cib9imkhwRYjYAFYhM9Nk5c0YJsxqKcNqzGQO6qhNe3k7krWzUylBsx3dFXZZGGNCSSYb+9CeG738AMhmSDhO3faaADmt27Ez1n8ms3U6+s/Ux3jwjl/unDPM1f5DrwtlofFPiJJpLb+eUz05HNoqsXbuWVatWoes6dpMbR6gOJXhkfIgLKV52hWgfISqo9Sa4Y3aSHHGIYKSPl0J7eSXVSfooavC8qJ1bNk9iTCQHQTKAZEK05yI53ODTEA0gqDKCKiGqUTz6rzGO1NkcjZQoE3AZ6S2S6LeZGNxVxvBBF2rynT4nIhonYLDMQhBPLAMim2IUznwAW2E2WmcKVlG25TuI+rFzclxK8WpZN3/JaSWjtmBM7EJAQ9Al6oK1TAxNRE5Z+LT0EEVSF83pCawYOpcFjglYBptJ7XoUPRUBQcRYexbGsWchWs1ILiOiQ0KzxlFMfpKGbhJiC1H2kpQ7UeUY8QEL/kMuAoed9DpLeOGcK4iaHZzBS1yq/QNZPHHNlq6BrgoIks5xWd1JMLaB+bAZR2YWDu85qHIRh4eTHI6nSY2QkQhakrBpL3VNKxnb1jG6+7DXy6G6sXSVlKCPzLlGBWyCjGo1EU7FQBdwhqtYml9DyTlVmOuPSCiooRCxTZuIbdhAbN1aMh1dx56eAfaXCRwu0xmTE2duboJkjoFhn5GMQcThmIjPt5Ac30Ik6wRWBeIsG8rWGUfVI33NpKnMSIW475T571lX/X74rxH0f4SkkuSCFy6gK9rFtfXX8o2Gb5BSVD77162saRrCZTHwxOdnU1dw5Fy3Lmtj0wtZA2jm0jHMOPuj86KHUiF+vPnHvNLyCgB13jrunnc3NZ4sU4mmqjRtXs+2V1+g7+ABxvYNUzmYzWENm41sqiolI4MoyVzy/R9RUncsG8dAe5hnfrYNTdGZc0EV004vf9/ziaYi3PiHM6nYH+DsgUKcjb3HRIlEqxXrnDmjBAuGoqKPfM0fhLiqsXw4xPP9QVYOh0kf1dWX9DQx9cW/AnDRd39IxaQTF96FUiHu2ngXq5pWc96+r+BNFGL1yUyYFcHf00xu+RiK6+px5BfQ0tJKU1MTTU1Nx4iV2jUzZ+sNODImMAj4rh5PV7GVFwaCvDAQOKaA0CwKnOJzcl6ehyU+J9aRqIau6yjDSTJdEXaueJWNW55FR8NnKmJe/oWYpZHi3loP3ktrkezvvRhWNJ23AxGe6Q+wbDBE4qj7Mt1p5Xyfg3Gt+2hf/gp9h5sASMs622ekOejJhuVzkjn8P/b+O0qu6kr7xz83Vs7d1TmqW62cI0JCIEQ2wdjGGHDAZmAcZjzONvYMznFsj7PHEYwTweQkBEiAEMo5tdQ5p8rxxt8f1SjQAsPrd37vrPXlWatWVVffOvfec+895+y9n/3spaNLcZslb6haLFI2Nk752BjlY2OE4nHEVw0tzsZyPOeuxrXiYlJbBOw8uOaVEb5+xpSIhm3Z5HaOkNzQfZJS4mgJEryiGbnCzZa/3s22B0oGywtL13Hte27ipuqyKW3s3tDDtoc7sS2YtjTKRe+fReqpHjLPlwbu0w0hgK2DW/n3l/6d4ewwAgI3zbqJjy382JT6Wa/g/vb7uWPrHQB8btnnuGHmDfy0a4Svdg+BZaNYoMsC7xncyPePfxV8Vdhv+xFjz3+TaP9ufl91FZ+b/gkE2+JnNQWuSR+DrudLr0n5X9uGUb2ZHfn30pufi/0ayeMA/jLnKcOoKUB5nfc1cwlT43lefrCDrv3jvOeOFfjCZz/H18P/tvH3fxP+kb65594nCHZ+B2VGL9Zpa8BCQmVHRqV8o8YF20vfZd1u/rL4MnoXXszKGokGOY5XP0HX3n6s4YuY7ZJPqr+pwiHC6ncQMBnVvodpV6II7ZSrn0cUTo1DBVuhR6xkUGyjy2ikD+8Z6pRTYNv4hCwxU+V+fSkFVKJofFqAViTq5F8TljafNW5kqx5yziqOjErsHAyTLZYWcUGfyBXXXU7F9HngKSvlsSR6KOy/j+/GZI6oVZiCBJZIzWAafzwBwEhdMx2zFzNk2oxpBq29XXzrzt9TN+8WRGcAK5/gaHmQ2+cIjLlkTFHEsjI4M4/iyjyLQClKbagLufyFDNFYkc4ag2kDMuJkDaWk7OOx6CVMOMqwBbCDKkLWQNDOrCUkCjCr2s+yxgjLmkIsbQzjHsgS/+sxrJyB4JQIv2M6ZuIYw1/5CnpvabGaX7+cr6+N057pRBRUkurN2PsaEWxYVNxKYeZz3DExwLJiKdcmXvYhdndcgYKA2yHh86mYBYMhbYztjkMURR3ZllipzaTZLuMwFl+jwNBkec4P4OAmVKRXXaGElOavkSd5JLwZU5g8NxsuS6zm1pF3oNpnX5zKQi9lypeRxREs20PauBrNTnM0H+FE8Vw0pYxQhZt8pp1Y72Ys/ZXCsxKSYy6ycymC6MO2i9jmOJY5fvJdlOJULkpTNrf9lGGcvpi5c7/Bvr/9gRM9R0lGJWJVFoet4/SoQycplq+gKdPA3NhcFPMUpT3KOLfyRyQs7uMyDtptOIomgcQ4QRvKlyzE1+RC9Q+Ccoxc7hjF4tnzvQRBwuVqwuudjtfTxouFmXxxyM8c9nAjvyNKSdktH3eQG3VhhBWKZS5CQhwf6bO2eTbYNliWgm350Y0Q+YyfePcM9MGFUAxOXi4LU+qnru8Zpp/YfTInR3cHsKatwVd/Pg6lpC7bq2tsUo6gOUtzz9y5c7n8ooswDx0i+9JWslu3Ujh4EE6f2yURrUEmVRkkP0Njf/UoTxoORl6h6VkW70pluDGdpqxqMeKsqynWrWUiJxIbHCA22E98sJ/RwUH2Sh6eazufWG0FOCRkTefo2nl432S5D3jLCPp/hp/t/Rk/3/dzou4oj1z9CA7JxUf/tJsnDg7jViXu/tByFtWfqtux8/Eutj3cBcDyK5tYctmbN4BeGnyJL235EqO5UURB5INzPsg/z/9nFEkhn0lz4Jmn2PPUo2QmxnEXNRb2jhKYXHh3R/y0NzRgmKVF+8X//HHmrJ2qGgdw6IUBNv3xGIIAV3584ZT6I6/GQyce4otbvohH8fDwBX/CufvoZC7Ri5jjr8olapmGd815pSjRokX/x1GiomWxOZbmgZE4T02kyJ3mWWh1O7g6GuIiWWfzf3yKYjbL0iuvZc0NHzhrW9uGtnH7i7czkY5xxZGPUJluQlYM9OxfKWRHsFQnhjeI6Q1gur1nFMl0OBxMmzaNmZFmwi/p2FkDya8S+cAc1NMU/mzb5mi2wMOjiSlKdG4Ezjdl1o+aLDueRT1N2W04381Low+iW0XcjgDr196Cq0vB1i1En0L4uhk4W4Jn7GdPOsf9w3EeHE0woZ9qq9nl4O0VIS6gQPy5pziwbQsFCyyHE8vpJhWBF8q3kVEyYMPM+AwWD9QTHZugfHyM8rFx/KmpdW7SXi/DlZXUXX0l897xTqRgENuwGPvv/Wi9aZRKN+UfXoD4qkV6oSNB8tFO9KESHUMucxG4vAnnjDAAm//wG3Y99iAAm1ZcQuTCy/jdnKYzDKlcSuOhXx8g1l4y9Pc3qDyyzEPIoVCpykRSBqGhHOVFm4a2MhpmllHhUKhUFRzk+f7O7/HAiQcAaAo08bVVX2Ne+Znqac/0PsMnNn0Cy7b40NwP8a+L/pXkWJ4nf3WQ31SY7G8uGRWz08d5Ys9tqPXL6b/ka3xp34/ZNbyD9yXT/Gs8wcdn3M59FRcRleHpZbOpcCiTls/hkjHUuRl6tkAxRcqI8nLmRo4XVgMgCiahkIUhuEhOTPUqiqJApNY7GS3yUdEYIFTpPiNamE0U8ZytKO0bwP+28fd/E/6Rvjn48W8iPXkXBUWg/eJGpNYhAo3pMyrFF/YGqPyrgTtZchI82rSS38y+AkWC6woWNXqYpW6ZoFy61n+NPMXD4Sf54niceYnb0e1WJGGIiONT5AUTzVZRbY2AkKFoSowUvIwUvAznfQxpAbJKkHJfkbDXRJOdJPGTxEcSHyYy7UYZW40GbESiQpoL1BM4T4smSbaAYoHX5aF2WiWhfCeB7ifwWGkOjZXTEXMDArYkU6iox/CHCASDrF69mgULFiDLMpplcfPBbjZOlMabaCrG+sM78BXzGKLIC63zOVZ5ykF32Zbn+Ne//A7V0JEq5uFa8WEEQeSpSpkvznNOMexEYxRP4m84ci8h2DaNg26WHAvjLZTGqJws454UOxlxRdm4/B3obTUYikhcNxByJmK8iBDXEONFxPzUkgMNZR4uqglybb+Gd6I03ut929D7tyFHKhm+fAm3q79l3IoRIsDX9E8QitfyVCrDT/Q8NYzxkPp9ysQebFshpn+cvHXea95LWYo8px5kWEwAIBhV/MGoxkCkCoH/wMVMW8Isld7BtMEELNvCxMa2bUaVMf5a9QjbA/tOSq+7DSfv77mSueOtmJqJbRpYpkHYcZg5VXcjiwVydjmHM5+hUpkJwIG8SUfBxDK6MPIvY5uvGBESLuc8op5lVM6qIrTIQgl0Y4gHGes5xHD7MMleBT0jU3feIJ6KUr+lTdi9v4rOdAVjwRxj/hF0aWqU0ZTKCAmNXFuczjJ9JjN9bUh+B0cHdrJl+8PooojoC3BhzTCL0hvI2i5+KryXHK9FibZwOjO4XGm8XpNQyEtZWSUVldOorJiD19uCJJVqPP2gZ4T7Ol/kPdzJTEqU7EJBZWx3lImDXrAFoo3TGF65hv8MTEOxNT685fdctvUZzACYARuz2o0xowojLKLZE0AS6XVye21bIDs0l4ljF5Efazv5va/qOAH1cSKpIziSICVByrtwVa8irixmT74Bw7ZxmBvxpXuoGB6mfHwcyTzzPlaaGxDmV5Gfnme84iim80zDzelu5ajVzIO9h+guliiBim1zVTrDB5Jp6g2DsYKb3kSQ8WEP1phIMK/hyxcBkR8veDtPzF+D7ZZ46IImFs158+vit4yg/wfoTfVyzUPXoFka/3nef7K+YT2fu/8Af93ZhyqJ/Pb9Szm39ZS3esdjXWx/ZNIAuqqZJZc2vqn95Y08P9j1A/589M8ANPgb+Pq5X2d++Xwm+nvZ/cTDHH7+OQytNGA0FUzaugYRNQ1NEtlfFyXb2EohM4ap6yx529s578abX3N/tm3z7J1HOPryMC6fwnW3L3vdxZNlW9zw2A0cnDjINS3X8JVVJXqHbVkUjhwh+8ILZDY/T37fvrNHidaUqHNKVRUFo8D9x+8np+cIOUOEnWHCzjAhZwi/I8S+DDw0luDxsSRJ49QDW+9UuToa5OqKEDM9TmzL4p6vfIGBo4eonNbKu7/yHST5TG+WZmr8aPePuPPwnYiWyFUnPkLFRAu2XaCYugfdY2BW1qPLZxpqYjGPlEkiZ5IoxTyzGs9hlr0c0RaRok7KPzgPOTC1v8ysjj6QodiXYv9ImsfMAhvC4hlFCj2GzZoxg8t0hTVBD95aP1lHmkd//V3iQwPIDgcXXncbkWNhjNEcCOA7v46Jcyr521iC+0didOVPDZrlosCVTlhmFygeO0JfVweZoo6tOk4aczY2J/wnOBQ6QM24xdwemZUdAWqH07jzU7n5UkShb8YcNsxcwVP1bSwZ7qQ2NoLb7ebmm2+mrKyM+APHyW4bRnDKVHxswUkqCJTyfhKPd1E4mfcj47+wHu+KKgRZxLYsnvndL9m3oRTt3HjuFQwsOpdnl86gTC15jw3L5sEd/fT+tRNHzkSX4IlFHg42q5ivkb/waohAVFUIaPtIDf4Cw4gjILKi8Xqunfkhat0ehhP7+cxzH0azNN7e+nbuWHkHnXvHePauoxTzBvef5+NIZem+qiyM8SRb2NEyj69t/zY5I4dTcvLBuR/kZv9M9Af/hctb/oOj3mZWyFnuXXUOyqspjaYBQ3tL8qVdzzN8fIyXEu9hSJ8FgEtMsKjsOUIN5YyJixjJVDDSVySfmjpRKk6JaEPJIKpo9FPR5H/LCPofwD/SN+kthznyqQ+zqyFCzi6iuFx0rw+SUF9kidug1VmqlSIUwP+AgueF0v2SCYQ53PpO/KH5J9XfEgp8rbqdI45fg5jjjr7bWJqdQ4EcUdencJn9Jw2ewXyEnkKIovb6ywLd5cLT0EDD/EU81mmwZcxFRigtGFvNIuczga9cwPToZCYSGNbZK9tLmSTO4R5EfTKROxDGP28JyCoTExPoemlB6/V6Wb5yJXd6K3g0lsEpwMeLEyS3bcG2LByqTavrMH45Q6+jgm/X3cJt997NZS9tKu2nch7OxTcznjlOeWAOgiihLytDvLQZURCQTQ1p35+Rtv4IMRfjroFpjBSDRHKleSnrMHk5MpcT8nKWJ3YwL3UIERtRkpi95kJmzbwAcVYDx1N5eiZy7OmJkUwXUQ2bXEYnkdUYLhqMnjY3ScBtOLie0rMXw2Krdz+/rvk9BVGjvljFV/o+TIUeOfmbDcJ+3qZ+i3IhRd4OMVS4naQxHc0GzbbRBR3NAsMSEMUcopBDpIhpw1FngqSzFDkaszyMZJtYl1MRbQUTeTIm9PqIuYZ4btqfGPNN0qtsKMvWcvGxD+HTQsx2Pcka/68QBYtBbSZPxD9HwfbT5hSZ4Sy1vyexjfZ46bqIkkK9fyFzPEvwBUKE3z0D5/SpzlXLMuno/jnPH/sx3Rr0aCI9RZGYOTUqLhsiXq2S0bL55N3TEdQmbq8N8KG2uZiaTTo2jiCKvHTvnRx9cQsA4UYP09fkcd9znJmhUZxBg4FEHX8TP4VmqxhSHktNI7iT6LaNOdW2PXVdJYlQKEQwFOYAKaqDG5nj2jN5IjDaM4OJrQ6K6VNjc4VPYtXIAf7YcCV/vOTtRLIpLt32PFWqRCLgJ1Wc+vyIooGq5gmHbQKBNKI6xKA1hCnncSs6XsVDmZjHiNUzcfQiMgMLYZJF4Ix0EGl7Cm/1XoTTpVhzEvIQqAM2yoCAPCigDAoUcSMvmolzhY9kfS8p5dgZx2IW3RRis1C8Q6i+AYyckxOPNJBPCPSX5zkwLcVouHQOom2zPpvjg8kUM7XS863nRNL9TjIDTvKFcpxz5nFX4xrclRX8203nITr/51gKbxlB/5dg2zb/vPGf2TK4hVXVq/jZup/xzSeO8qsXuhAF+NkNi7hkzqkip9sf6WTHY90ArLi6mcWXNAJgWQaiOFUx5tXYP7af21+8ne5UqY13t72bjy/8V0YOH2H34w/Ts3/PyW0raupZNJFB2LYDgAmPk331FYTnLSM53EU2Ead50VKu+vQXESelL0eLOt/sHGJ3KkdYlShXFcoUmZAk0vvsIAznqS9zc81Ns6hwqngl8axJ2ntH93LTEzeVisVe8WdmR6YWvTITidMU56ZGiaRpTbxQm+Hp6glGgwKaDJoskHe3kPavpOhZjn1a0qTDzjJN7GeeI85sj0x40mgKOUMMbdjK4UceQ3W5uOlbPyJYeWbh2ePx43zuhc/RHm8HW+DaIx+iPDkH2zbIWxswajwUJxfTkiTR1NRES0sLEY+LzEAv/UcPlwwso45FkYsQBZHhfBdbRh4kUFNJbesc6ipnElYrEROg9WcwYwVeDVuAY40enq5TecptMWyfMhIDssTFbjeXFCTm9MR5YdPvGJ4splkTbqOl6VI2e708WaVw2A/BXIZQLk00l6bNyBPMpikkE7zWo+8URWrsIvGRLYR7RmkbsPG++hAFESlYgatV5ujy8/jzrAt4EtdJ9rgCfKe5gvRTjzA4OEgwGOQ9i69Ee2wABCh7/2ycbaXIjlUwSD3bR2bLZN6P+EreTwOSp2RIWJbJ0//9Ew4+9zQIAk+uuYoDM5fwp3nNXBDxM6bp3N0/zsGnelmwP4tow5hfYuzySq6fV805QS9x3WRE0xku6gxrOsMFnb6OGIPjWcacIhMBhTEsTie0CGYGb/wunLlSUqyh1JH1X4Uv9ltEO4foWUJNw2dQxg2s3iy+vEWsRmFvmYJs6ZRrcYacUSJMIPR9BsHWWFC+gK+f+3Xq/ZM5ONlxOh7+LBeX3UxG9nBbcT93XPAOUF9HmEEvYPdtp+vFg7y0K0qyWOrLkNTHOb47aXDsgvKZZKouZkRdwUiujtF+jdGeFMarKDsAF35gFm3LK197f6+B/y3j7/9G/CN9c2LHyzz2X9/F0Iu4q+s4NF1is3szAC2JVtL+Xj44fQnNygCZzGHUowLBu2XkhIJjzjtRm88HYJ8T/sPOkS+muUf9InHxBhoLa9HQuFv/HWYsgT/3iibymXBJASwpiilVIEiVgI1Z3Ield8Ck+pWrvIpnqi5jV7rkEDqnINOqiRyuknnfVW1cPrc0vh59rB1rSzdZoUCHlaevkID0HqTJelaWrFCoasT0vr4SlA3kFQflAT/Z8VK1+VmzZnHllVfizPQzvP33vDc+h4/8/k6m93UDAurMq3DMuYTCjl+jd+/Eveo6pPJ1AATf1ox31SkRlr179vHgT/8LX7pEV9IliwONBXa5z0HyDtLimmBdcga1HQoj6U7SikExWovp8eM3HUzTy5lu1eAVPGedD5NY7MdkHyb7MGjHYgUyX8TFs6FN/LLiPmzBxp1pZXX3+5mueSi3BAxboFrdzHLfT5AFnUNWA7dpn+J8xwTnSXuoVHupKXYTsOJTc6eAh82V3K7fTEDUWaN0ogomLtHgmsYs06uD4K3AckexXFFMVxTTEcGK9WI8+EXisdXkrHOwbBt8Ku5zqrlzYgsPZX6MpZSEHgQELjHKuaN/F27bpjOxiEMdK8C0sQQRzRqgrGY2rWUl5c1dY08i5jqZloviclejNNRRdvNqHK21CJNlJPoz/ewf28++kR1s799Ady41xZElAJViEN+wTXjMQVlc4eDMS9ixcC0A5ePDXLv1AWqk45hFgdy4E9s8vQ0bQbKpyqeZ2RHDoVk4QhqNF40jCrA9sI4B+zJiA/UUsqV1maRCwwKVypkqBUsnlckQi8VOvkzTRJI06uoPUlNzBFEsjbcjI810d87FSMuIWhG3IlGhJ+jPCeguN7bqwnI4T+bpvBper5eKigqi0SjRaJSKigrKyspQVZVtQ9v4zPOfIVaIYQlu0pFbuT6c45Liz7Gs0uStpSuIHVtPsvscbKs0r8quEUKNTxNq2YLoeu2aUoWCm1w2hCCaBAIjiKJNIV5DZmg+2aG5pAdTGLkXkd15Wt7Wi1vSEI4o5J4LE8qLeFNZTpQVeHClyO6WU+e3PK5xSy7JMi1/8sraDj9C60Uw43JouRCc/2fzyltG0P+f8XTP03xi0ydQRIUHrnqAR3ZqfG9DKSHwu9fO4sp5borFUYrFMY7tPEJ/eyeyM0l0mok7lEXTxtC0cSxLp672vbS0fBZBmOqZ0U2dX+z/Bb8+8Gss2yLqjnLH4i/hPZ5hzxOPEJ9MQBcEkZalK5jfOhv9xz9F7+vDQuB4ZYiOaJCFl17DYPtBRjpPEKmt5/qvfg+H241p29w5MM63OodImVMXS68FpygQUWTKVJkyRaFMlSlXZcoUmeePfosDQ0/TFpnPTy78LRFVmerpnoRtWRQOHyH7wqTi3KuiRGeDJitoiowmgSEZ6JKOLoMugT5pMOkySKZIedyFLYj0VxTJRhQUpxvF5UF1uonbWbry/RQkCwGRxd2rcQtzMUWJXHCArDOFKUnILhfzlyxh2erVeMPhVx2/TfKpbjKbSzknaXeS/mQ7joKDsKMKvxI5e7FLj0mhCrLlBolInngwR448BaOAHBcYTwQ5bJez0xMgdhp9LKBZXDCksWj3M6RGt4FtYYoSY7Ut6OEK/MXca2eQmAZSMY9b12hTnTQJEs7uboqHDiLoZ7q6dFkmHikjFJ6HLzybjvXNPDqnmUdjmTOSGWc6VGLH4iQ6kiyoCvBf187gob/eTTweJ2L7uLy4iLKLp+E/vx7bssnuGCa1oQcrO5n301rK+1EqTlEGLdPkiZ9+n6NbNiMIIpvXv5NtzXP5YE0Zb68I8duBcZ7piXHF1jRNo6WBXJ8b4JobZ9EQmCqUcMb1sm1ST51KVvZe0URxaQXDms5I8ZTBtH9oEwe7foppJE+W0dDVVhLRz4H4d6ibtg2CgGDEqEndRTGzC1l00hiaxYLyBayuXsLS8rk8//KDfNBeAMCv+n/F2y79OJT9/erjpmFx6LlOdjzWQ6FQeq5q1P2s8v2ecqUUaUYQoWoBVuN5xHxrGCk2MdpXYKQ7TWwww3VfXEakxvt39/Vq/G8Zf/834h+iw23bxhM/+DpMm0OXP8mLFS9gCzb+fISUc4ILGy7ke+f9J8/FMzyybwMLuh+iQR2hac9NKEojALm+J3hi2lG6rXrOGd1NpbyOJv8FWLbFlpG/MZjvOLVDWSWk1FDjqCXsqEQXoxwsOlCEGHXqPvzBGOORWRQLcxk4HsMo7CNlnuDR6PmMOioQbZOLkyeYP30mv87IjOdKXu55tQE+e8kMVrWUkXl5iNgDx+nPHmXHxEaMyWKa+brF3PCpW4k+9yWSx54vUexqLiBZewHJdIZEIsHA6BiCcSbNSRAELr74YpYvX44gCORMiy/87s9c/7Mf4M9lEVQvziUfwlnhISx9lVxPioy1gKpf3EN2Z5zUUz0ggPudrTyZSbDjoXuo6t+JhIWFzYm6DMcaTT49eiWzjVZEK4w4OZpmKLBDPkGHPDL14tkWSiaFO5PDZwpkTJWi6EKR3TQLJtZEDkPyUXBEiTur6JMdHGh6hMHyFwG4JL6K8PA1/BoDE1Cw+Ix6D7eIDwPQo/j5VPFf2aHNpJw4Dzj+g1qh5Di0LMgn3MgzzkOevoB8sJE79ge5r700ni+sC/K1y5rZ8nTJOQVw7rnncv755yNJp6039v6J3IN/IVH4EBalyIz3nGr8FzciTuaXHRpIcvND3yTrfgJhMl/IYVlcMdxMc/HTrLpyOlLPSzzzwJ9JFEvMgQXB82gLldT3CnvuRO8pRWJyDjhRJXCiQaGj0UF7uUFSmUpr84o2jQ6BRVVr8GdfokZOYRf8HDywjjHK2TR7GYO+0vEuPLiNtVufQDZfvbg/ZfTLpsmsgQlq4yU6V8ahsK8uyrzGIZaV9ZPRVX7fuZiipSAq05FdyxGlEpvHtjXM4j6Mwi5k1cTh9iA6VfJtaZpaj+ARS3TuZCxCZ/tCMsUKpqocTIUsSRSDEY6pbpIePx+dP4N10xpxn6Wej2Vb/Pbgb/nxnh9j2RaGUk+y7F/49PT5/FtjJZalkUrtJx5/mdjYiySTu9B1D/Hj64ifWIull+ZZUU7hkXcwu34Uq2mUjL8HS3j93CTbkiimyimOgxyz8cQ9+PsFXF0JpNhZfqsoOKdPZ3BRHfc3jvCMceiky3Get54P2n7Wdu1AzJacG6YdwBbcyB/fAMH/OdGe/88bQYXjcZQKD5L/zeWg2LaNYaTRtFHiuT5ueuaLjBdTvKtuLgskP10jvfgdaap9OSSSvOI5e6OIRi9j9qzvIYqnaCon4if4wotf4EisJO14ReRCzh9vpX3zZoq50gPncHuYc8FFLFh/GeZjTzD6/R+AaZBXHeytj5Dwebnwlo/Qs38P7VtfwOn1ceUnvwminyODKR49PkY+USSQtQhlDATLZCRo0R+26SuXyYbdoLrAELAKJlmHiKa8Ps1INGKEhz6NYGukIh+h6FmBBMiigIyAJApIgCQISEIpYCsJAkWzgD7Ry8KjR1l55BiLjh3Hk82gGvqUpPv/V9BcCrmAg6xfRXe5qdQbCYhVCM4AtsOH7AwhOAMgO096BjNWinh+mHhxiFhxmJg2hG4V0WSLQtiF019O2FFFnV1LS7EOt3VqIW8Ce4IiT5XnOOHI4M+lqEjHiWSSKIUcjuFe5FxpALJUB4WKeiRPhJDtIWR5CFgeXOkE8vAxXPkR3Pk4DA1MMTSTbuipAT3QxES4BS0QZZa6jK3TyniiTmXAODWx1DtVri4Pkjie4N7nu87Imaz0O/nhRQ1sevQeCmjUuyp57yc/hNGdKeX9DJ+W93NF8ykJzlfO19B57Eff5fi2lxAlia6r3ss90WlUqiWD+2CmQPOwztUvZ/AUbQRFZM17pjNn5RsX2ni1IRS4ohnfuVPl3E/ET3DD4zeQM0qLt1pnMzM6b0Q3KikEZJSGMR71VqGLCgEzhyYp5FHAKoKggCDiTj6EJ3nfWY5CQHXWowXexZhjHg6zwA9O/JBzV15H+byptb3OhmJOZ9eTPex/th/TsACbttp+lrvvxJfadebGkgq1y6BpDVrtGpSGxQjKm8/De8sIem38I33zs8e20/XyU5jOOJuqNqFLOrIRwpDjVHmquWzBz/jdQJbqrmNcsE9nml7JQreEIoroZCns+zV0HcIWbLLrLOKrvFQmLsU/tIIdQ7vo0PuQxUoUGvCqlSz3BgnKJQ98hzSGVVSYXn2Y6vCLiD0vnHFsSbuWR4vv49vWLFKigNMsctnIE9QUS8ntlW2zGK1dwm/6PLxSJmd1S4Tr3N30PfEwOa2Uz+NWyrCdF2LL1exvdlB+RR0fiz1OxTOfRzNV4qF1TMz9Ao906QwPZChPani1AqZUxBKLSLqHpVfVs+qiBZiGwZ13fIOV95Wo4WKoCdfSW3E1SHgGPorbX6KB2TZYjVegTfsAXXuC+Ify6LbF0yP3kc6XHAaDkSI7Zk4QUiv5Wu9HCJmnrl1OyvCS0k4P8ZMzukuawD3eT97yU3RHMV2nHDiCoSMnJ1CSE0jFqRRiXbLYvHCc/mjpf1cNnsutyesREOi0EtyVO8R7fQ+xxlHKJfmldhk/MK9ljthNl13NBAGq5BjfXNrH0mAzQ9+9i/srm8m63czefYj/WvoeBh1BRGxumx/m49cuRVUVDMNgw4YNbN9eUtdobGzk2muvxedUMB/+DxK7QuStUs08uUwl9M6ZOBrOvIdt2+bElj1oG9/Hf1Xk2eo+NU9FnBFuCF1J5u4XsYoaqsvFwkuuZPbc1aTuPkqvGueIs4uj6i6OuXrpcxewXzXESaZN0wi0jFtUzjeprTQp1wSiz8whEfMzRIqyOccRqvI8I6/l7sit5GUVRzHPJZseYHrX4cmWxNL4a2u8sg4LVjVw0cpzyf/k55hjYyAIyFdchnnFZWiGjp5NMPPgl3BrI/Q7F7JbuYhiPkcxmyWfCaFpM0GITPaDgVnch6diI5HVw/jdpehYPuFgaGs5qd6Sc8lGwFYcWKoDS3WefJctk8rqasxMivjxowiGxpIrr+WuOWt4PJbGK4k8sLCFub4zjaCUluL2F29nU98mAAqe1aRD7+dTzfV8qunMqL6WNzj0wiD7nu0gkH6ICtcGiq0wbp5L7MR6jFzpXES5QPWK/8ZbXVLcy405SA+60ZIqltOHWiPi9ibwuBPIytlzkoQCyIMCckIE3UJ0+2hZeQfh+ZcgniZw0Jfu485Dd/LA8QfQJmsJNQeaubnqPNb3F0jsnoVAgYovXot4FhXev4e3jKA3AFs3GbhjK5g2crkLR3MApcmFUGtgKAk0bYziZIRG08YoFkdPfta0MazJC/dwQuHZtEJEsvhsZQH1LMa+IEhgBsknPBiFAJGqWqoaG1EdUVS1HIdajqqWkUzt5ciRz2HbOsHgcubP+yWi5OEPh//Aj3b/CM3UaM6EuTw+n8yhbuxJmlSoqoaFl76N2eetQ0xnGPzc58ls2YIhuxgoa+B4VQ2Cq5zW5Rcx2rWNsa6NgIjqfQeiUjv1gF8DE16R7qhCT4VM3ajB0o4iaQf87sIASe9rc4rdyQfxJO/HlCLEqr4N4pvIQbBtHBZ4DRu/Di2KzPqQhysrfXhcAhg6tqZhFTVsrYhdLGIVi9iTf1uFInsffYDxzg68Ph9z1q5D03Lksym6+w7Rm+lFsixUHcqTKj4jhKK7ES0DhCzYeWxbQ7QMFKMkJym+yafGkCUyHpkxr8mY3yTjkZAlH2G7kgg1hOV6Ar5mnM7yKQveLHm63CMMe9LEhRyZfB5Tn0pK1mQJXBqhTBdSRwJ7kkYc9fhZlJ2OGuvFjB3Dzsam/Nb0u9hfZ/Byg8nRWoG5kXIiQ6tJGQ4Gypror2jlSPDUQOSTRK6MBnlXZRhnWueT9+7nxGhp8L92US3vP6eRf7tnL12jGX4seKgkw+OOPbgtlfWexYTipet/Mu9nZRXCq+r7GJrGIz/4Jp27dyDJMvYNt/Ft16nBXbBs1h0qsPJwaQERqfFy8S2zCVV6eLOwbZvUhh7Sz53dEMrqWT741Ac5NHGIoCNIoahRIIdoSVyQvppPqsd4T+27aPc0scgap6x4N3vGdmEj4ZAUUs7FpCO3AbDMncUj6vTEDxBPH0YotCMZJfqNjUgy+nl05wwkfRB34kEERyPlgTk0h2bQ5PZQ71JpcKo0uBzUOVVcr+q31Hielx/q5PiOkpdaUkQWnBtkUfMx1P5Npbyi1JmS5Vz5E1h005vut7eMoNfGP9I3P/jJQ4zEtvJs9SbyShZLCyOqMbBFUq7PErb9XLh3GzXDJvM9zbT6SsnPY4V+to4+jGHEmB8fIdo3mXhfaZN4r4HWANmRGaR6VpIeWEg5LhZ7BFRBIiPk+Xb174iX7+M6OcCF+y4iWL4XJfEiWKecHpvNeXxE/xcyuKmxk7w7W4SCjFHYi6Ufh0nvrjsYJt6wlMfHXKwdfY6QkZxsQWB25Bxm+lZS8Dh4fiiPZkPaKTARkKnLGkiZ1x5gHT6FbDGHrCnYgolrkU3Nht/TcKBEAVea1pYogW1uki/9FUQXSnkNsquc8XyAp2yJx2wNNdfJHYKfJncTRTPPkxP389jMffSVZ5mn1fHx/EoUdxzdNUrBNUpfxkVX/wx0vbTYjzvH2BM+gLMQ5pzBiynLVyIUA+hSkoJzkKI7hi2dlgNUsHAmM9jpLA6nSUFJ8visTmJ+DckUWL0vQuOwh1p3G0vLL8UppgkrX8YpdWFYAk8Pt3I4WYGJSF5yMa6Gebr8QgqSk4CRpFEewCwLMBH0kcuoZAclDFGhPBfn07v+zNyJTkSPB+e8ubgXLsS1YAGdTiePbtyIpml43S4ut8bwJ9Zh4wXBwre2Hv+6hin1jIa7khy99xGWpW/HLSVIWkHerb6b3qrNiPKp+kKBtMzFxUUsueIaDnbtZ2/3LtodPRTEqTkuNZ4a5rin0VJUCR/fSm1PDDUPmcttzJCFmIDIj2WUoVPHoskKP3vHjTx03kUATO8+wa33/oYyWcA/ezYVy1ZQveY8EimF3U+doH3PDgQzz6wTB6gdLlGchcpaar/7LbxLX1UOofdl+O0lgA03/g1a1p38l23b9BycYNsjnWTSB4guuBd3eUlJVc9LDO8oZ+JoENVhEHUKBMJBjLFu0jGVfFHBkERMp4rucKJrp/rCGy4jEytF9RoWLuEv572dFwsWZYrMI4taaXKX5s1jsWP826Z/oy/dhygoJEM3UfCs5RNNlXym6RTFPxMvsu/ZXtp37UVyd+EM9eAu78Md7sUWS85S25JI9S0hdvRiisk6BFGn5twf4/EYBOJrCE6oxPsM9mVmkXdIpIKHMJQsqppl9theqoxerBYnRr2E5s9gC2dn7ihKBJ9vFl7PdLzeNjzeNjzuFroScX659/c8O/ggmpVjUWYmXxi4BY/lZAid+Z9aiVr2+oyOs+EtI+gNID8yxKEtn0O3JjDUJIYjiaVk//4PT8Oo5eNbAyYWcEv1TIYGfMQLfubVN/Ou5fNxOKKoShm7Ho+x56kSRercd7Yyf93ZC20BxGJb2H/gw5hmBoe7hT8lImwZPEDTkIelA1U4J14JEwvUzlpOy7IL8YUbSMeLxA91M7HrKHnRQ8EZwXyVtK+ptaNnHwVAdq9HdsxFlyDpFkl6RFJuicTkZ9VlcXG0HLUvh9WdxRrOv1ppEhMTCQlDNZCvCFA2uxlFlhEoBZxFoVROz7SK/OfmG0gURlg77QMsbryJlGmRNkzShklKN8nkNJJ5naFckiwiOVklf5Zicq/AY9jMTpjMz5ks0EwW2DZhj4jklZB88uRL4fCBXWy87y+IksR7vnA7oepadr74LP914jccjpQGnEjKwfr8+cjJBjwTMxEQsCPjrHpHKy0zW0jqSZL94xjtKRwdBu5hAcEoYhVT2IUkdiGBXUhiFRLocgrLSiHkUgjxBORep8DfqyHKWE4PeYejVBHb7STncZN3uii4nORdLgpOJ5rLSUVlJWXlNrrxID7vCA5nBsECpV9APCYx0FVGvx0EQUAyLVpHYjSOJRERMCud5Gdk0Fos9laJ3Gmq5G0Bh2DzjrCJ4J7PC6xlD0swJ+sOiJgskrtY7zjOKtcITsnJwUGdl7sL5DUVp6GypiJEoGgRz8ksW38t2+8dYWXCJIPNUNikOSYiIWILNt4V1Wfk/ZwOvVjgoe99nZ79exAUhUNvv5nHQqeememGyLu25RD6S1GZ2WtqOPcdLa8pB/1GMMUQurwZ3+oadFPnw898mJeHXiaoBrlx4LMke3Q2T/sLvaHD2IAY+iijvuWEKeAduYN8cQAR8WS4v85XR13TF3ko4UYRBP4wr4m1YT+2bRM3TPbFh3hpaBcHx/fRleiiN/B+LCmII/sSvomfIwC2oKKrzeiO6RiOVnRHK7booVJVaHCppZfTMfnZgW+kyJFHuhg8Xlp8unwKy97WzKxzKhGT3dC1GevosxR2b8X1+Q0I5dPedJ+9ZQS9Nv6Rvrnjyz/lkYoH0ZzD+NJBwhmDspRMaKyaaFZDtXQ8cpBzolcRdpQcA8cyO5mIjFLWNI3RniEOjlawemyY+mOPQjGNLULmIpP0ZSbIgKHgG1uMf+gc/EYDT6zs5Oe9v6NoGQi2zTWZLB+LJygzLYzy+Qzai7inz8XPhZWYSKwQD/EL5YcEyDKkz2J/9nI68rPRiwcxiwfAfqVMwCn6kSH76AlexuJQI2sNcABZ02Zr1mBSg+BkboCpalQLJyiTesm2zCI49wLuP97Dnv4TRJQEF4w2UjueoOHAr5ALcZAUnAtuQq5bfkYRVwOblzB4DJ2XMYgURzk39hI1hSEkQeb8quuJOKoZlSf4t8bvMS1i8pGmuXicURQlwuiom+07EsRjpXHcZztZprfSIBziUfcAZv87EO1T447hiCMU4wRSY7jMYcZDMBYNnMz1EG0BNy6ejz5Pt6cXj2Xy7/1p5qQhZyrkDAVFDDLDP4gsJjFtP3tTV/DixABG8cwF5pga4f6qq9FFlRnpY1w4/uwZWTMp1YcdDDIzGSfYP4A7ncNT1HBpxkmadH7WLF6cO4OYoCDYsNiYxpJgHeEblqBWn0mRjQ9n2fZQJ8KRB1gX+BGyoJN1tiK97176pXI++ocXMAs/Yrim/2xpZifhkT202c20jlQzo9DE8ovXUbt4On39d9LR8R0sS0OWS/lhhpFE0wIcf24ezt4s/kQcbzZLwhfmJ9f/E901JTXA6596iJsfvhfZmuogTDbUc3T2bHp8PmxBIDwxwby9+yk65tDZ9DYUn5tpi6JMX1ZBdUvwlHrm45+B7b+EQD18+CVwlPTqNcPinpe3M9L/AxZEdwJgGQKj+8OM7o3gDGs018a40BhD0vPkxwUGXgqhZ2UQBSK33kr5hz+MJQh07dnJgec20LV750mn9ivwllfw2JUfYLvipd6p8siiVrb1P8FXt36VglnA56ygN/BhDEczH2+o4DON5eTzPQz27qT32HZyhSM4gr1I6tQ1iCDIOI0owq5xlE4TadhFx8zPMZKsQJCK1K3+Ee6ydvSjjfT13IyWrsKTHWR6z1840BplqK5EUQsrEjd86J+IVFRgWTq5XBeZ7DGymWMkU/tJJF7Gts+uJGHZAiO5cgbS1Qxky2lO1nHN+CokJA64jvON6rv5ydt+yfzKv08LfzXeMoLeAAwjw+bn50/5XrBkpGIAWQsgFwNIxQCqUoYzWIU7Wou7th5XoBpFifDBp29j9+huFkZW8/LLb0MzLN6+sIbvvXM+oliiF2x9oIM9G0pqKn/PADp1XgfZuv0DFMedDB1pIN1bjWIFEUQfohxEcZVjGir22Y3uM89HKBKuDqE6E/Ts+SWWqVO16EI2LrqITUaBnEM4Q965aqSPtxdifOG9NyGdlqRXzBsMHk8wcDRG94FhkmM6rx7pbGuCYNRi2uI65q9bgNt/KoT7ZPeTfHrzp3GKDu6dfRfhhBd9JIcxmkMfy4Ex9VYsiDDhsOlQNfapMhMBgeGgxOGAm9xZDKSmjMnchMm8hMW8hElj1kIEDEvDJoFhJdmqdPObxqeJOTMINqwab2Zaagma7sUfn4OARIV7D1eX/QKDGRS0heS1BZhW+ZnXSB9BJ0ZQbkISnNhSlsD0LXjLQS9WoGXC6Ck/xTEJfTyHVUhiF5PY+QR2MYlVSGKYCcxiArJJpMIbN5YswHALUGZi+cH2h6DfjdI/jGyd6seUU+VgbRmJySKiPtHBksjlRL2tpCpf4Je1j/BsthTBqVRcRMKXslNdR0Y49Sw12J2sZjMreZEgCUxdoBBzkJ9wnnyPJQL0SA30uOroddWRkz0syuzjC2oVlWoLGWy8k/dKnzjBNvk4q962lqVLl045Ny2f475vf4WhIwcxFJX7LrmRvppmAIKyxFfxkXywl2LWQHVKrL1xBq1LKt5w370ebHuyoOGzJUPId1kDX7d/whPdT+AUnVx19F8ITdTgcMmcv6KH/f2f5/NNN5EIXQe2QXDk6yjaiZPt+RQft86/letnXI8sKvzToW4eHUsiALfWlfO5piqc0tT7+PmJGO/e34OFwKzRu8jmNpI7S/jRUGrQHdPR1enojlYsOXrGs+wSBFaOWSzalcYV13Dnxwjb/dT7xvAPnUBrb2dU9bHszl/imjdvSvt/D28ZQa+Nf6RvPvXfH8Da10tZUsWhTzXsa90zWVp+CaqoUhBM0gu9WL4I7QcmGO9KlhbaYqnau6pnSO7/I/LAbgBy5Q5yN0ho0xMn21NsJxXjJsrgBL9QfTzhLUVTXZbIu8fXs3bsEv4oWNwvlBxwlyDzadGBKoCAjWDbYNvkTJvuokBnQSOX3TAZGTqFkFLJ9OAS6jwzkM6S8/pGYds2evfzFA/8FSwDwRPFtew2pECJ1WAJOh2OCR61NTbqHpKWgtfIsDK2jRnZyeKdIsyomuC5kMw79H+lVqtg3DFM23ubcU1bzPDwMBs2bKCzsyQ645RUFhQamWnW4G+Jc+T4FvYkLy21Fd7H0w1b6FW6aRoq8E9PmtSXUhswp0+j77ZLGersJj0uEueUV1sX8yyyj7DaPkhEjJH0qRw3BRZmCqhAToqSzH0D067E0RzAf20zRTtPPpUkl0yQSyV55Og4v+jyAALTs+0sTOzDZ6RxvYYiX+nUBdymhTuTI1JWjiuwnE6/QJ+jRFWszRe4uKaG0KJFuObPo2CqbH+siyNbBlnsuoflvhLt0Ghcj3z978DhIxOb4IHvfo3RzuMMBzQ2LsxiuEvtSbZIRA/S5m3lvAXruaDhAsqcZSQeOEF2xzCIkFyxkWFvqfi137+QVPIYCDlyCRcdj9ZhZk/dLwenL2Tj6ivQFQdBweaHNT6q9n6ObMc+5DGRiL4YcdSmN5vlcE01I5WnGASiaWJN5j+V+apRxurPKCLrDTloXVLB9OUVRMpB+Pk5kOiFpbdgXvpdHtp9lENHfsiyyueQJRPbhnh7gP5dFRQqPMyZewQts5iRnTfQ4niJaSOPo+0rlZeQq6uo+c53UFvnknlhgOyOYZxtIcLXzyATn+DQpmc48OwGUmOn5ZqJIhsvvYE9tc3Upf9MIfE0AE2RJQw719MoDnOVb5g2oZtU+jC2fRaDBxWvbwZ+32x8ky+Ppw1JcqAPDTF0+xfJvvQSliBxYM4tTETmIopF6tZ+H1dZJ7YtIMSWsGDBRwm3rCI1NsLffvsrenI6iCKiobFq3lzWvv2dIEr0TGQ5Npzm6HCa3rEuVoW+SMgRI1n0sn9sNuXuCWq8Q/jUyaCDLVB+7HrCvaWIXqLqJfa3/ZFxFG694BkcavA17+XXwltG0BuAbdv09f8eVYmgqmWojhItTdTcaN0pip1Jih3Jk3kLp0OucPNc7W6+kfsRDtFJvusTZHN+LpxZwc9vXIQiiSUD6G8d7Hm6ZACtvq6Veeef3QCyLZueQxMc2zbMxEia8eE4kv73ZQEFUcDjk1DHe1En+nAUY+RUhUFPAstO07JsPpd95F8oZDP88Qv/RiY2gT19Dv91/rvQX5WkN32sj4VbN7DEKfHuL38bRX19ylohqzNwLMa+Z08wdKLAFNePbeNy6lSVuakJeglpFp/xfJ2DrhOsTS7hs4NnynEXRZ1edYgh5wTl0dkcG0/yUEykA4VX23oz1FGuqTiKEnCwyzWNXe56up1TpTV9usXchMXcpMnsuMYh+WEeDD+FJdhUaBE+Nfg+5uRbSJk2L6QNDKBS1ljuKYDgp6Rz9gp0MnoHx5LdDOQ6CarlrIxehSKqJLRRnh++j7yZRhWd+JVI6aVOvitlOJQ0CamDcXGMYdFgCA9Z4ZSRKJomzkKBQCFNjR6jXM8S0Au4NQ1yFlpKR08VsXPa64o9G7KIUCbjicZ4rEXht00uGkZ8LDkawjm5oCrzN/PQvGMc95eSY9XwlQx4roHJqI+/qHGVJnBBfBT/iWPEU8MkizFS+SS5Qh4LgRFHlB5XPb2uOkYcZy6+ARYj8WkTaicLufZg8mOKeIPD1BZK/PvrrruOmTNnnvzNgbFxHvv2V1D6OikqDu6/7L2MVjeg2+CXRL477qB/Q4nKVV7v4+JbZhMofx0Vtf8DvGIIpZ7t5RcV9/JweBMSMpccvoW65AyiDR4urv8L/uO/5Znwcm6c8y1sQcQ78Rtc2U0AiILIO6e/kw8v+DBh5ynxjLxpcfvxfv40VKIktnmc/GRm/RS+N8Aveke5o2MQRYAH+n9EqOch9jgd7Kmdzz5FpCfdO+U3qhJEdc0gr7agFauZNqgzs6uT2V0nmNNxAnfx1FgWd3j5xdyr2FY1m+8vd3D5Oy570331lhH02vhH+uZbd92B8ljJw2wKNim/RkNVHjG/gJbiFUybzDsZocD2jI1lnKkoqkhZLvTIqKKXlHOCOv6VF3rnULNrELVYAEFEmL+SwiUdpCq70U/jcMuZINnxmdxjjbBTGsNIzceeOI+iVnI03IKD96KeEW05HbHiENvHniSplyieglQFogdb7+QVqpxD9NDin88030Jc8psT5DDTQ2jHHsPoL+Wz6BXziM15PxlJIbokwwtbtrBRbOBIoFRbRLE0lib3MD+5D3nSI33UM52t4SVEoncTq+ijQovw885P4bIDGOJunlUP0sskHVYQaVEaWJmqQ0VBXV/P7hMpOveUrJyl/vtZ6rqbgulg78AcgltLuVEpF/zhApGJZpP3ZRNcmMvzV7+XX3gbqc800pyuQ7JPzfER20W1fIhLzSdxU6SvfA5d592F3GVSs20UybApOkR2zg3S55PJ6yajpsGTbovcUBblcKLUHzP8BCJuLvFKHI4Noo8NE0pMEE6OU56cIJKawNanig4A6IEIhcoGEEXkYoGmgwcRqCUeXYUgB1kX/BVtrpJKISs+Ahd9FUSJ4Y7jPPTdr5KJx3B6fZRfdQtf2ZFDCzyNI7IZxKmRgCpPFbMis6jvczGtp5GWQg2ZuX9k2EjhKm9HUiyyI046n6jHLEo4vT4qFy3j7uoZbA2WKF/LHCK/WjyTCoeCZekcPvIZhocfYWysgbHRdcRipZQFQRCYESljvijgdTrZG4mwe98+rMlc2NammYTMaQzsz6IVTh1ruNrD4rYuph+5FYDfRK+gsnE3Tmep3fSAm87dDeypWsPKmZtp8xwlOKAyvPN9dBeXlRqxLcrH9zGtIoF23Y3Ih7NEe7NIp628H65U6K51EfY4CLtl3ONd5PduItW+r7SBaHFiSRGjfpA6h0WbN4yfOCpTr6NlqBQTdahyG3UtS6ltWorH04IovnZejW3bJO65l/QzGxFrGng2tYx0VgIsKhbdT6hlw+SWAtHoZTQ1fgSPZzqbn93Mc5s3IYhg2XBEj7JfqKdonjk2RJwxPr30R5S7YiS0So7p36Qp2kBruUalPID9WB6hpzQOjLc+yETjgyCAICisPe/A6x77a+EtI+j/IsysjtaVLBlFnQn04RxpMcc/TfsyCTnNzSNXszC2jiG/wmWXt+JrDSG4ZF66/wR7N5Y8ymvePZ25a6fm3hiaybFtw+x7po/4cG7K/21bQxRTKL4x3GUT1LWsprJ2Jr6wE2/YifHCBka//GWsXA5ddnOgYSbD3gQAK95+Hee88wYMQ+eeOz7HcMdxEqEod179T2iO0uArAFdFg8x9/jEKm57AHQhywzd+gC2I7D3ciSFIrF4xH1U+u9fONm2MWJ72p3ro3T4MAmiCRVwTyL7KchEAp6zxUvR5BgLtfCZyE4trF9EudfHl49+kM6/iz60gn5xBwjjlmakR41wxTWLd6jU805Hi7q09ZLXSQNUS9fLhtdO4cn41CdNidyrLzmSWHckMu2IpNGlS1lIfwjfxcxSttPgOsoy1qStZmlBpyDnYkYCiDWFJYKVXQn6dRHTD0tGFIk7Bg4BASotxIL6ZuDZCdpL3bgOWw4Xp8mC5PJhOL5bDOcVQEG2TCsapFYaoZZgahoiQeE0jR5cF9rf5SEkqUhJCB2x6+2uJ5zwkfH6OzZuBUK8yvdBHW66H6cEImZpmvps9xoHhoyw+FmR6nxcBAU222DWjwPaF70PzzEc2DZoHu1nSfYKFxXESAz1op9UDykhuel119Ljq6XfVUZDONJKn2SKrHQ7WhdzI40nqzNLCPmsb5OpGMC65kNv+vIeJbJHzXX002CPIsswNN97EYU+Au473UP+nn1I5Nkje4WLbtbewcNZsftU/hg18sN2kek+pf+ddUMs517QgKX9fbef/BLZt85MHvsd/p+8CYF37e2mdWMy8c/yck/4k0theOl11rF/ya7KiE2f6GXzx35/8vVNy8tlln+Xa1mvPKmqwYTzJJ472Ma4bKILApxor+Uh9FPk01UTbtvnQoW4eG0tSrcpsyP6Nspf+s/TPmiVMXPlD9hZH2Tu6l71Du8kcPURTv07roE3rgE3N1NQvdEVhrLyJTdEV3Fc3m7xUqhF/89pmvnTJzKk/+Dt4ywh6bfwjfdM5PMbn/vQ9RqWNJLwaby+20djxLhYJlSeLn7YXTI4WrBLZTCqilp0g5x8hruS5dmwZQb2aIjn6Cts55HBSpvhYka1G2/sXjKFS/owaVPAtXcJEQz3pqmNkonuwJZ1k0cemvnN5rm81aX3SSBE0KiIbuCBZQcvECiRKY/QrCwjb1snlXqJY2A3YiIJCtVKBX3SRlBqZkBowtMMYxX1gl4xxAZsWtciCincjym2ATkj+ES7p5VdaBWxsCzIDCrF2F4Vx5eT/1ICBrjq5t+3zbPdFOKoY6JPPkGTqXDbyAk2F4yfzFCKWwEzbgSgr/GBeBwdq8ggWvG1nBcvG22DaYg4oAxhCaX6pTw4wc7SMCtOLIUk8IIngnIFX9GJjkQ+PE44O03D8D1RsySAXSuNRbJHBXRfLvIyENTmauyyL/CSzYqHgoE2oY//Ra5gjJrDEOPYk11zCoM7Kc8BYwlOWjwwC9Yh8FRfTkDCx+S1Ffu+1KS6JgEOCvIFj6yiCbmMLoC+OYEsi3v0x5syJ0lGmMPoKTcy2WDE+wbv2DVEZj5PVR8m7Y6QsndTYKIbqIF87DVt1gm3hGOlHiY8iAB65SEjJ48wKuN11RFqmUwgH2b51M6auE66p48oPfw57S4aOI+P8BzmOCnkk5xCisx/J1Y/oHEByjJ31vo+aXqo8SeocZikKemgJC5dcyLTFyxgrr+aD+07Qa9gIlsVNZpJvrl+LNDm+aprGnj27ef75J8lO+nokCZYsWc7KlSsJBoNn7GtiYoJnnnmGw4cPT24rsXTpMuqDM+nZl6T7wDiWYWPbFusrb6dNOErOJbJtUYhcysGRg208VX45xqzp3GZ+hjJhHHVQZeJYI8WhADWHMgxWn89Y+UICErQ6JKoV4eR8sAeDCWwuRCGHzXvJMIyNKmrU+gZo8PfT7O1itucwvkAO8SxLsKLlwojXUxyvoxBvQEs3EG2dw/x1jdTW+RFfQ4X3tZBLaTxz5xF6J2v1AagumfM+5GU48zP07HMnv983voi/ta9nNFPBuUoX9VICgBNmhB16PU3lPmbXRZhR6aOt0kdzKEV3+/spFgdxu5tZtPCPSHk/E78/XAo0yCLhd03HNTdMLtdDNttOURujrvbN56rCW0bQ/yjMjMZXN3+F+8cfoqpYyS87v4DCaZ44ATSnTF+8yLhh03ZVM3PWN5zRRi6lcXBzPwc2D1CYlNCxKGIVDmAZA5h2iur5TZx/zXWUN9Vy4OBHiMVeQBAkZs74JlHfJYx89SskHyrJZsYDzeyti5CXYoiSzPp/+ihz1l6Ibdvc+4Nv0bdtC3mHi7vffhsJfxi3ofFuRedyyWD4hWfp3l+iSgi+EGY2XRIFmMSYqxJl/jouWrmK+S4XjOfRR3MYI1n0sXyptstZkBdshswig9kcSUPGEM5MbrMEEytssMscoM8K0ie4MCaf2TKSXOY9zpUrZrHovKsQT1Ouimc1fvdSN7/f0kWqUDrO+rCbD6+dxqWtfo489xQ7H32AfC7HaCTKgRaTwfA+bHQs0UM6/AE093IA3AWLmzemCGUtDKdAXVRlvqzgL3NjO2G8t5vccByn6MYleXFIZ4k6qCJGtcyEL8+QHWMgMcRYfALjLBLjglZEKmSR8lmkfAaxkEMSRYLl5YQryomUhwmXBYiEPIQDKoqgg5YFPUeuOMw++wlyQhrJlqgfa+Cb8tU8Ell11v5/BS5RYJrLgVEcZnjwv6kaPsaKg2HKUiUjJhWqorzuYqaPxTky/ASGPVm4EJERTy3D5bM4JlYwbp957n6HzKqIh/WWwtykiZrXERFOeogtbO5H47cUqUsf4da2cRbe8EVuvXsPR4eSrFNPUCsm0GSFx9sWc/Fz9xGdGMZwe1nwiS+yvG0G63YeY6Cos6hX4/KtGRxumQveO5PmBWdSE/9v4/72+7lj6x0ArOp6OwuHz2PNggQzE/8GhQRpbzVL5v+ApFyJXDxOcOQbNPlruXnOzTx44kF2j5aep1U1q/jyyi9T4ZlK1xvXDD7b3sdjYyXDbrHfzY9nNtDsPmVcpg2TS3a205Evsibk5c+OY0gP/TN6PE0+HaIQvJR8X5r8wYPYZylgOxSC49UCx2sE2qsFuoIR7NgNZFIlL3fUELgkr3LVu2ewePUbF0h5BW8ZQa+Nf6Rv2nv2cNujnyKabmPu8CpmmlUsdMsogkDRstmdM4nJSYxIJ8Ga3ZTV7kSWdbAFqvd9FN/oYkw5Q8fC70Jao6n7CpRCaZwQ7QGM/l1k9z8Leg5EGXXG21BbLmKXOMFf1Qm265WYk3kuIUectXUvUhHeznErz+G8hFH0MXdwJcs6milPJEHrZMg9QnFyGqyKp5k1MI7jtDFQU3wMVK+iv2oVBXEMo7gX2yhFdUVB4tzwZVT5Z2HbFrnxP2HzDE5FRxwVKHarGLlXVoE23poC4gx4JLSKe8y1dNqn1CAjhsH1qQfwJQfITBYi9RpFZo2NUzaRI62KfPsdEu21Aopu8/EHbSJmAwfnziE/KUMctfws7JwguPNvJ9tNe2rYP/c2is4wip5h7sH/Jpg8TWYcUP06VUuSOCo1ts0OMeyX2ZSU2ZxWsCb9NSI2S90ma3w6R4dW8+yJZfzI9T1Mo469zGaEU2Oby1bxiVWM+GsZCwa4YsxkXqw0522LSNw+z4lDlfmQw0u5InPvzn529cRBBL3Jh1XmRN0zgaBZqNVu1OkBJlQBe3IhPjuV4WNNPt42dx6SIKAVNfZtPMCuDXuZUAfQPZORu/QEymAPwuuUq5BsKPOUEVAb8EkRfI4w5Wtns6u2jK6JHH3xPIOjcfT+dhrErTQt3s6obNKriXSnFeLy2dcRDqIQvIpB37lYgog7m+KWvsN87rZbEQSBbDbLjh072LZtG/nJMdDhEKis3ENV9TEaG66lre3LZy05AtDf38/GjRvp7u4GwOl0cu655yL563j+wV/R1vIYwbIEK3YmcGoWu5V6PtzwJbqrW5mW7eXz7s/jEops6lvF/fvfxj/vf4gL+0pqnAON52LMeSdz5FNrnyHdYswhUueSCWUNbMFGsAVSoWFOLPo5brHvpOT46TAKIvlxF6O5cjY2XsZIPsoVf7kPWWnDcM7mkLuCY4qFIYJsgyoIBB0yAVXBr0j4VRmvIuGRJFySiEsScQgCqiCgICDZMHgsTj6tI0gC2kwfWncGT8YiK9j8xVvEHejnbc1PsaRy78njOhpfSK92Hf6ciN5XUpUTCnk8Q10sPv9CVr7jPTi9JUdKPt/Hrt3XUywOESyupnLXP2FnTESvQtn7ZqPW+V7z/nqzeMsI+h/EofFDXP/Y9djY5HpuYb57Pr88bzryQJZiZwJj9FWLEQGUKg+O5iD5oIN9x8bo2D0BkyHDvBRHyO6B/CEMqYiyrJn33/hFwmWneKyWpXHkyOcZHnkQpVcgelc59mACWxDorD+f9lAc207h8Hi48hO3U9nSSv/AAD+77z6qdr+IKYrce/n78GXTrNv+NM5M8lWHKOCUPLgkHy7Zi1PyIathQpKHgBLGp4SRhLMXcRUUETnqRixzcfjABGMpDd+0IOs/Nh9RFrEsk4Ejhzi46WW69g1SMMPonmq82pk1dgxsDDlGQ3iQZWtmUrNmHdLrJLqnCjp/2NrDb17sgvgQC5IHmJFtR5qkPORVk+3L83T5Sl6NaD7K3PgqnN655DxVnPA6WLQnR1XcJOEW+f06P2m3iATU63nCJw5ROdhF9XAvMyqiLL/wWtw7ZbSJHONCmkSDyZg7x9D4MKlUasrxqapKTU0NtbW1VFVV4Vdl8vEJYv19xAb6mBjoJzbYj/46uUC+snIiNXV4ylQy5gYUfwx/2Ekys4AvBG4kpgSRbJN/ye/iKkeajo7tHFOitHua6AzMZixtYWKTccRwpn6DZI5jI2Grl7B2V4GmvhMno07Nvvn4Q0t4scLgsORj/4RN3jhzMPapMrfMruJCt5vyiQJaVwq7eCbVISnkGBRjHJL6GK2Zxp+7VGxE2tLHuLHsIPUf+gaffeQ4Y71xLlGPETXjOPuPIxfyOANB3v3v3yBSW89tB7t4cCxJKG1yy4Yk9XV+LvrQbPyRN68U82bwdPdGPrn5k9hYLOxfz6Xpt7Oah6lx/DeCYLMnOo1rG24j516GaMSpGv8Gn174Qd4x/R3Iooxpmdx95O6SmqOl4VN9fH7Z57mi+YopUSHbtrlvJM4X2vtJmxYuUeTfW6p5f3Xk5LaHY0ku39dJHoEPHtvH+//yW4zh0SnHLXq9uObNw7VgPq7583HMnUuflGDf6D52De9l436L4f7FYCsgaDjKn6Za7WFh7DyueO8SLmi84E331VtG0GvjH+mb//zKd3EOLkYEZrtEmidrs4xrOV6OvUjOSKK6L0EQJyP6UhGHf4DZqpvaYh2WoKNVfY9Q3E8xfwMWQU4XKACw8gnyB36PNVjyhHcEqvjWkpvo90UBaBbHOK9uJ0sbN+NwnMlS6CmKHC5IdMRl5u8I44uVzs8hmMyO2FQGvciOAIojiOwMITvCiLKPXL7ARCpOX0xlLFdNQbcwi3swtaMIWCyKrKfFvxCA4d4NOPfcjzS5RNElkUyVj3xTOb8PrmaLOANrcmHrosjFwm7KE7W4UvuxjRJV1CnprCzrZX5oCEmwGZYkbq2M0qkqeA2LT57wMSotZlQuGR5+LcWyRIYG/40lZ07fnTC6kWHnPHZW3oYpOfEUhljc+RPc+XEsEyxDBBvMJhhZ08gMvYeq4hBZl8jTc2r5RdJiQBcRbXDnZDKeUw7GSxwNfOrENioMjaQo8gnpn7n+vBvIHT3M4YHjFOxTMsRRIcDc5lmYvhpqt8dxWpBwiVTfMItwS4kKXjRMbvvDLp47Voq0WC4JdXqAsv4875zQeBcu+twSf2qAh2udaJOF2WsdCu+WPZRvGCHTXwqjuIMqlS0H2dE/gIVESMhw4epzEQQPI/v3cmz3drJvII9VEkVUtwcbKGTTeGsylM1IoAY0EOD4julYFRJt8/fSr4mMjTczkIyyw9lL0VEgHfkQmruUO6rmduGL/RryTnzFJmbn66nJCydLZjg9fuYuXsrq5UtJJf7GsWP/DtiUl1/CnNnfP6PkyOmwbZuj7e1s2PA08YlxHI4MjQ27iFaW7iPLEDD2R7k0cwgTkcsX/oyylMR7q29HEix29ZzLpq1L+OyuPxPNJhAr58GyG/CIwdIOBBBbgozGCrjG8nheI0Iz2vpX4k1PYBl++jSRo3qGfl3EH1+Je2QtkeMP49QKpDx+HrzkBqaNh1m3/00IL70BjIkWj3g0JqSSKu+7sg4qTZGcaHN0louGhiCzy8eIin9Gy2zklVhwWdmFOB3X8tCDe8jl82CaOIe68GGx6p03MO/CSxAliXy+lyOPfp2yPe9CtFSkCgflH5iHHPz76R9vBm8ZQf9DMC2T6x+9gSPxQ+jJhZTl3899t51DZcCJbdu8cM9x2jf1E5EF5s0M4ckb6KM5xg2bjqLFyGnJ/5aaJK2/hCN2FLDxVHq5svwA1fWtMPMKaLsM/Kc8XJZpcPw/P4B55w4EU6DgCLBv2kom1C6wDRSHE395BZlEjG6Xn2PTZrP25RKXc/vCtSwazdCaLOKSvbgkL6ocwCO5cUteHJLnrEU8T4dhaaT0CSb0JIcklf2eKFUzKjh3cTWrp5fjVCTG+9Pc9+1dmLrFsrc1sfTyEi+7L5bj4X2DPLK3n3R3O77ABlI14zROTGdpxzwUqR5BPJMbLisildMC1LSFqG0LUd7gQzotidy2LLr27mLHow/Sf2jfye81QWakPMWWeTEKqoloicyLzeWK+HnMNxrx4sRySmwvWIwkNGS3DO9tYodQ5OWxOOPSafxT28ZbzNOSijN9eIxIJg56CvtVdZ8EQSAajZ40empraykrK0N8jerPp5q3SU+MExt4xTDqIzbQz8RAH/lU8jV/l3O6mQiVYwf8rJ/ezArPIFKik2wiQV9sgsfDS9lYfx5dwXrcqUdxJ+9HwEKxfFzSG6U1oTPhizDmCGMP5agYK+UG5UUnW8IrOOKdUSrwiU0ZNssFlRuqIjRkTKzUmfUBCmgMinEGxBjUuZh37iIA7r//fizLwqyZzx87ZCxEpmfaOZ8X+O0lHyU/KBNt7+Vdww+i6AVwOLnhK9+lsrGJP7QP8+mBYQTL5v3Ppnjb4hqWX9V8xvX/n8ALJ17iX178CIZgMGNkBR+t/hjnCt9GOv4oMVHkh4G5/LHuXLKhd4FtcKXyIt9bfjN+derY05no5PYXb+fgxEEAzq87n39f+e+UucqmbNtf0Pj4kV5ejKepGh/lHWP9vHt8APHgQQpHj/L0gmV84+aPAvCNn36HlYf34ajw4HIN4yrTcM2ZjfpPdyEEp9Y3OtCf5LP37+fwUMlQn1UrsnTuCbpyOzg0fgjN0vjz5X9mTtmcN91fbxlBr41/pG8e/u1zjO80WeZWT9Lfkt1b2V9MM6gcBEEHMQJlF+ItT9Lur+CqiQzNegtgIzGKSTm8qlRy0TVCPnyUXPgoo95unhubhfF8gJt2b8RjFCiKMptWzMF3+SCNof7XPcZEp4/+LZUYudJCWp8psvqmj7EwupzUyDDxkSESw4MkR4aJD5c+55KJM9oQpHIkxwJEuRFLO4Sd38WM0BLmhM4FYGBsG8XjT1JetQpP3Wq2ShrfFjRik7malYVhFuY6+KBnHn2pnXRmjk62LOH2tPGepR0EhBHIxTihJbi1PMCoLNOYd3PlyEwG7EYAHBRYw3aWsxcZk6R+PWnzBsBCDT5J38QwGaMMh5hmoecBhJzGsT4vRl8IZ+xUXoYUCiIubSBTf5z9rUn+O+0gaYp4RZsPRYooeyo51OugY5ZFjdrHN0fHcNs2XYrMF8JXsrX/UlR8fO9d87lsdpQjW/ezZ8duupIDp+hytkhAKmeOVU1LIYQoCvgvasS7uoZsIsZodydPHYvxq6MGca1070w3M1yfGaDCzCPSzUEhzz5fI6JbRLJMRMtCskxU3SCUNahxiCz0H2OJuJVBoYK/2FeSETxgW3jjo4hjg9h/p4j5G4WoCjj8eVSfRqRqOmXJZTjGVboqKvjKykomBAHBNvEPPomaf5yALTA9OZ3abO3J4rVxNcFRzxC9tgOjWINVqCUoN1LpAQ97KHONUx8JsHz2B/G7vfTH8/TFcvTGcvTF8vTGclgjXSzO7Wb5vANUtg0hiha2DYND07in50p2zV3GT/q/zbWjGxlQohxdZoEE8RNrGdn9HlQtw4ziALVlNSiuSQevLOCeV4bgkMnvG8PKlQxgQ8mQqNtIsvZ5/J2XUda/rqRIi80Wevmvpv8m44wjWQqrO99J0bOah5d5CCYneM/Df8CTm0CXZJ48/+3UZlpYeayAbRtgG4CJrEoobieyy4UlCphiycms2TZF26ZgWeRNi5xpkTFMMrqJjk1OhD43TKv00lbpo63ST0vARd/fukkO5fCGHFzzyUX4JyWrM9njdHf/lJGRRzlZgymwhiNHpnHiROlclYlhHKMDlNfVs/amDxGKRUqFioFM2V6SK55m4bLfoqpT58V/BG8ZQW8QD3c8TNARZE3tmje0/d2H/sy3d34D23TgHPkC9//TxTREPCUD6C/tHNhcCu+vuaGVQvMIW54/gLbLgyfzygW2qVJE/NYAR2MPU7RyiIjMrT6HgiPCfVQjkqWeYWrNQcpUA6/Hi2xKeJ/bhGeyyvNQwMPB2gr0yQlSFV3UutuQPOXcP28Ge/0G737o16iGjlC9lGsdF/B3tXgEEBwSgkNCdEgIDhnRLaNEXNghkSOdW9n1/GNok1GkgqhywDeHfYG5SG4/62ZGuXROFdVxkxf+eAwEUC+o5LHROHv7Eid3I2OwWtxDV9NDTKgGF8TKmH4gSjGvIMp1iEo9klIPr6LPKQ6JullhGucGycb3sf/ph4kPlfpDEEQaFy+nezTOFv8W2utLimeBYoAbh69kXW4xvrIAzplhHG0hNj/TT8eeMRSHxBUfmU3f4efY+cjfyGczZILlFOpbEAJhhFQS9SxF7obdOYZDGWxPBYK/ASHcjMNdgUNSkCdDzLI4+S4IKKKAIky+XvksiigCpe1FEVlg8r30O7OQY+jY/Yz0bcFMiehxhUTajy+TRrRMJMtEsQ0uKj9Kq2+CF4KLubfyYp4NL8MUZEQzgX/8ZyjFUnHdizN5/n1snGGrms3WfDZb89luzUBDoTo/yNqJ54nocWRBJepvYEEoTEhswrDPpHJaGIyICfrEOANinJQQZ55rgKXuQSqdxVIhTmeAQ9XXcd/zh7Btm+3+6RwZ9WEj0pI5waXFZ5j3/n/l8J13YSQnMBUH+frpVDZPp232hbwvPU5REbigvcg3V7XQMCfy9+7efxibdmznkwc+iiblaU7M4ztzP07bwVvRYh3cHQzy80CQlHs2yfJPgSDymToHn2h5/TwawzL43cHf8bN9P8OwDIKOIF9c8UUubrwYADOTpXDwAPm9+8jt20d8zx7URGJKO1Ikwo/f/8/c2zIbPzZPzWuiKRKEQw/AQx8DLQ3uMrj2VzCtFNHJaQbf39DOb7d0YdkQdCt86fJZvH1Rzckok2ZqHJ44zOyy2Sj/g8mn/1/EP9I3D37zKeYnXCiCgG4a5Hf9BmGwRLHpDtTQXyFS9ASJBBtwNSxmUdKNaE8VhgEoiDoHWzWeTO9HdvThV1OcSDazd3QemlWiGTcZfXzuwB+o7yklkhWaBEavKCdT72RPaDWb7FXEbQ9XK/tZ1vcLxna5SXZPRn+CRerOG8JbmcewoScjk+72Ih8MY6Smet5Fl4eY5GfM9qJ6wjQ43Sw63k55525ELcOI343Rtp4Z1ZchCAJ92aNsjb1El2cOTwSnYYgKrWqCbxjfZ0dXhLx1ZpFfj6ceTTkPSSjH6dC48KZaxmsKfGzTv6DlNRaOzqYm3wiCgCjAkrIC5/m6cWd7sSf6EY0ktg0J4yNkzUsBjXL1izjEw2fsxzZBL0gYeQlLdDN+UCE/WHqGdrUI/PAqkaIqUJcz+SxZjLaSsTi+t46q43HOjXYjCrDV6eRT0TJSkoiIQiG+AD1+Dp+54HxuXdOMIAgkYgnuenAT2b4TFO3MyWNwWQrTrWpazSoKhTG2Dj+EZhUA0AWZncFF7A4swBIkRNtkXuoAy+M7Ue2zCyNAKU/rvIpOFodLc+uhRJSnRmeSrZ6G6S3JVsuJcZzDvQhnyNPaKB4DZ7iIu0zHFS7iCOSxscmPuDARMLIyhaSDzHgQChKWPrXgpo3A9gWreWHZOmxRIpSKcfmGv1CeSyM1tpKxTxn2WW+Rw/6j9KonzqLLJGAVo1iFGsxCLWa+FqtYVYqEv3Iv2ibTsp0szOxl9rR2KhePIztLzIZYso6e7kVkkqX7fDAQYaQywL3HP45qmXTWu4h75zJ83wqk8lU0ud14pEkpeKAQdRMIOzBPJE4q3+rucWL1j5OseRGXtxkrdiNGZhGevEG0PYY42Z0PhzbxUHQLFw3czDG5moeXeUAQOG/U4vaonyPP30n/4VJe38sL13D1u29kQc8RDjz7FANHT92n3lCY2WvXM/eC9QSiZxZQPR2mZZPK6+R1k0q/c0ouUS6l8eD3dxMfzuEvc3LNJxfhDZ2K3GSzHXR3/5ThkUd4RfzEtmazb18d6XQ5cjGHq7eTZcELaPLNBcCx3Muxso9S1IfxeFpZtPCPqOr/vXn+LSPoDWDv6F7e/+T7AbjjnDu4uuXq191+KDPGpfddgSnkECau4Z73fIoZlX5sy+b5v7Sze0sHfcEjaPOGKfbItPYtxaMHAdDFIonGHhqXuvHt6qZ7R0nZJuiqYFnoMgKmRLpzA/mhXRQlyDlUdJcPyxPGbQhEuw8i6QVsUcaaeTldIQft6dKkWOeZwbKyy3m6xskP2xwUzCw33v9z/NkUEXcTF0Tf8XejPG8Upm3QkznE0eR20nppwhQEGdk7m0JgEQnFT0awKStIRPICBcHmz74iE6LFcvk4V7OJS6QdKFKB52ZfzOczB1FEhb9dcT/0JWjf+gLHt2+lkEkjiBFEpQ7F1Ywo12GZp8w429ax9E5koZ9582eTFVSeGdvIlsptpCbpBufGlnDB6DvZbSvsUWwuPLeBD6xq5ODD3Rx8fgBBgoYFMY4deJo8YknEwOmZIl4g2AIuyYdRVcWJCthd2ICZ3zmlb2wELCmIJUUw5TCWFDnjsylHsEX/lPb/J9CWeo588k/k7QIOXeWKkSryuRlsNhcyTPCMbWvFBG+X+llpaUS0WpxiE+IZ/GkLU+hnQIxzUDQZEZOYgkWIBMvYywIO42KqHKuFyNfLb0UfcyICO4NtHB7xYdkC85IHOC/2IgDuskoeKzuf+XQgCRaPzj2fwXCApozNE6tmEgz/42Fy2zBKnkvTBMs6+dm2LCzdYOMTO/jxxFcpyhlqik18Z9oVhLZ9la2SxV3+IGOSiKZUcHjOVzBkD1edGOdrFHHPLQPLxLbs0vsZ7VuT31kMpfq5v/0+RtJDqAbMmHAwfRDKzlJ7C1mmu6GZnfXNHGlqoWbJYj5/7mI8ssQ1e06wO5VjrtfFI4taS/LaEx1wz/tg5AAgwHmf5fnqm/nCg4foj09Wol9QzZeumEWZ98xFqa6nSKX2Eom8MSfQq/GWEfTa+Ef65tBzewg8laFDTPAZIU82L3BT18tcmZnAEZ6GEm1F8EyN+tlSDEu0kPSS02208kXis/+IJRbYPzabp3vP42is7eT2Dd4+LvRtY4aqoWcbCOyJ07DvJSRDQ1Nlfnn19Txw3iWlGje2zbwjOzl/6xOougbYBKclqV09jCbbWMCr62Vnik7cxmwi/jUcTc1hy94C0azEIlti5ngHdtcmjKG9vFLrQXCHMOatp6NqFUaqwBJvAEkQGcn38OLI38gKMO6aRVtoGTOSP+NQziZvlha1Do+H8romXGNOYt5q0ukGRFthpGwvjzfdTWOmmRnxNuTJKFJbWxvr16+nrKwM27SIP3CC3M4RoMhISx8Hu0+wrLgYn1SOZefwJj6PS+1FdpvITuusw7iRF/mNGeJns91YosDcLotPPGDhKYIQNUgvhrrqJJXZ0ni5K1GFceWXGKpx8Kf2ezgSO3KqrWwzK8uv4ptrr+CbL+/mRMcJohPDzErHKdo2ui8M8imKetQK0KAFyWkd4LaxRgsIhkBM8nBvoJkOuXRPeEWTi+wx6oeGEWwJWxDprHVyrNyBKht8IXU3K4ulhfQvg1ezr/6dvKOuEkfXMZ5/fjPFSBUIAj5BYKm/gCM0hFUzgab2Y5hTaeFn9I+ukHu2loYNYxSuzZFZaqOlVUL2Vbi859A7Mc5/+Wo54i/RE2ce38fa3c8jBMJYk4qI2DZyKoY6MYysFfGGI7giIUy/QtKpMSTHaTd7GZRj5Jwm9unXyRbACOHT3MwcctDUY1JZnaR6+SiOQMkw1O0oVdM+QqVjDo/ufJ5HR0LMHuxCnox8Lfdt4dL0dmwE+o+8DbvqOkTnZE0jEQY1C9WGytNEe/KBHmKNj5CJ7sLtaaS56d+IRi9FmFyXFYwCP9n4A67dtOJkfnnKMrnXJ/HzVV4QBN4dDPCDBY0IgoBlmbz457vY8fD9AHQ0zODKj32SS+qqmOjv48BzGzi8+Rny6VPXo37uAuatu5hpS1YgK2/e4ZVNFPnbf+4mNZYnWOHm6k8sxBM4cz7J5bro6v4pIyMPn6wNlEjUMti5kHNi66iwgli2xZ74MwTXNDL/0pUcOHIzmjaK19PGwoV/+L9mCL1lBL0B6JbOHS/dwcMdJXGBjy38GLfMveWsak6GaXHxHz/MqL0Fu1jD7y++myUNZfSn+vnNQ/fycmwLaTXGnJHVzBhdgWKVbg7TWaR8mcT6S5eSG+jlyZ/9kPTEGIIgUr/mEvbsH2Xe4b3MHT32urLHAIgyhJrZV+liQC55g6Z7F1JovYifzHBzLCAhGTo3Pfgbysf7UZUQbY3vJRDwEfI6CLpVJFFgrLeb2FA/gijSMG9BKWlNEEqelMl3YfLdNiysrI6Z1bEyOlZWx9YtLNtiMHecI8ltxIolSVABgTrPDGYEluNXo7yQMUiaEJIEzvUaKEISS0wRcxqUNS/GGQrxqcyX2V7YzXmhc/n+wu8gehVwCPS3H+TYyy9yYvtWCpN1bAQpiqS0IjtmgnjqWtuYjHk72Vv1PD2hI7hMka+2/AfnLb2Yx0+M8dPnTtA+kkHC4gKzyHQzh64mMZRxLGlqr3s8HiqdZYRHFCpMP9FQFN5exm9H7+bBEw9iTj7cbWVL0S2deH6EVGEM0zamtDXlEgoKTrUMh1qGqpajqmVISuklyhHAg5mJkbSTFCUZE5kJImSFUsKgVypFigzLwjCKaIJ0khdf41C4JuojO/JHHjqwGSPbhlqYTy4dPalQBKCis0TM866GJhaKbuT+zJS8noSZZiLbwXC+m1F9kGR5GYY/DIKAuzKKVlvJoNvBYC6HZmqoloFi6yffLxt/gXeNPAXAQ4Gr2JOaBraNo3kJD+yLccXQI3jMPDaw6sbLiLS9m3t/+RzbZhXZ3jwLxTR5fsUsmrz/5/k/tm2T3vA04z/5CcXjx//+D14HeYeDj3z6K3TV1DO7o53v//CrqMbfv95vBKOBSfGCaoHOOhlrWj3VkWkMOtewtdiEhUC5IvFfMxto8zhZv/MYMd3khqow/zmjVLAOPQ9PfJbYrr/xNf1G/matBqAm6OJrV8/h/BnRKfvV9SR79r6PTOYwc+b8mGj5xW/62N8ygl4b/0jf/OovjzP6wjD9ngrmiE6WCFBjn4p4mEqGorcfS+3BPbYW0XKQDR1EzVWhFCNYYpHh2b9ntHwPLw6s4JneNYzlS4tgEYvl6f2cPzaA7FxF3l2SG+4LCBxaGiAjxfnQ737GovbSQvhg0zS2tDUTSo7izZXG4qHyGgbq6zln7Hn8/hS+mhyuSB7dadJviCgiNKgWpw+vlg2SruI86sD7pIXSfSoaIbTV4bn2QnyXr8fpqUBRwiRHTZ7/4yHmjxVQBIF4cYR9sd9S5hijwplGsyT6cwFimouUXhon3v75L9M4byHDXR089MfnOGAM0x3dxqz4LDxmaRGtFjWcsUGampuomz2P2pbZSFuKFI8nsLD5XdkTuLpn4TFqUEyNC5Q0Tn8lVm4cc+RBApevw73uHIbGf0O8489ER/OUxXRkzeS74RB/CpTG6qsnsnx0e5F8v4P8hIqkWtSeG8ddrmFbcGIkyMu9TcS8Ti6qPcH0qMZWOcqTupP+tEAorRJOKbiLZ8/FVd1eHJUNZBUPKcE6udiXbJF6q4waK0ydZdAg/xJ99TquKl7JiT2jiLnSWF9lCLy3Nsq73jWDSLWX7v527L+8m6ZMB3lR5V+mf57Ho6uppp8LOx5nbmofznAB0xGhvWsZuu5CknRap2+lvLznlSuJIEglatZpsO3JNcUkZUrSHZhKESwI/kHCvU3iwOVX8ZVL38G4JOMUBW4RNZSNG8hN1qYSBYEKj5OAlic/PlJSstNeuxYSgCCJ4HOSdZuMKikmHDm8eZlpAx78ZUWqV4zgrSo5itKGwOMphW1Z6Yz50hZUAqafhclWIolKBASu4xFm0kHBmsa49n10FxjNDpwTAsJw6XhtbFLhQySnPUg+eAI9H8aYuI6mae+iZVEVDnfJEOlL9/HxZ/6N9uQxLo6fw8eHb8S2bQRBwAR+16xSOLeKb8ysQ3zV2vTQC8/x+M//C9E0mAhFufgTX+C86S0AGLpOx85tHHj2KXr27zn5G5fPz6w1FzD3gouJ1P79mpWnIx0r8MD3dpOOFQhVebjmEwtx+dQp2+Vy3XT3/Jzh4QdQMlFqdn8cNV+BLmjsUg/QfXQjAuAOBFl+3UVkHT8vGULeGSxc8AdUNTx1528SbxlBbxDZZIL/3voTfjvyVwCua7uOzy/7PJJ4etTB5pZ77mFb4WvYtsBNLZ/E5U6yqW8TxxPHqUg3Mm/wfJpi805yVF1RkeWXtDBjaTWWrfPin+5k9xMlY8sbiuAueGndvZ2Adiq0LZXPQKlbUfJOx7vQh3aBdiohtSgK7GquJuFxItg2c/vGqI2nyTmc9Ecr6S+PkqaIYmYwBIXBZe+lYc4sZlT5mVHpoyHi4egLz/Lkz34AwNs+8XmmLz+7sljWMPnj0AQTuslH6qP4T5PItjSTQqLAziNj7Dw8wnD7YULxnaj5npPbhN31tHrncUhvwUCkSRWZ555KyOtRh/hw89exBItv9PwLC3MzABBUEdGjgCKSm4iTyo6T1mOUOWoQFS97hWEGNAupGEYxT6mWGYJG8/wyZq9oIFgrMzg8QF9fH4eOd00an6+63W2boM9L64yZ1NXXUx2uxHpiGK2jRPkrzle5r/E57jlxL5pVCt2fV3seH1v4MdrCpzyqlm0xkZ9gODvMcG6YocwQw7nh0t+Tr/H8+JRcorPBKdgEJZuABH3yPMbkNhq81fxLyywWh+upSI/j+Mt7ID0EvmrMG+5l1N3CoweO8YuXnycWi2KbZ+ZXzUHgYnGYC+w0IbseizP5tylsdmKwRzBpmisznNqIoyODe7gfcXKicfqiXHTrR2lduui07rMZ1nSOZQu0Zwu0Z4u05woMFzQ+l9jA1bu+iWgW2ec+lwdySxELOdz9nQh6gTG1jF2B+VyUHMbju5CBgMrvLvRjiQJrj+5mhhLmix+4EvlN5gHZtk32xS2M/fCHFA4d+rvbW4AllpyEsiBgCBaaKGALYAlgivCD932SF+YuIZJO8Zvf/YjwRAI7Z4AgIvqdSD4HgiiCJJXeRREkEUGUSu/Cqf+ZImSrQ4w0BWivhnZxlJ5UDz2pHormmZO6rjaRjtyGqZRyA2uMvcxU0zxjnYuNwOfqHPxzUzOqqPLQ3kG+8uBuYkURAYv3O1/kUzdcgad19ZRz1vUEe/a8F6NPIziyltobrsQfmPWm+hneMoJeD/9I32z5/HcIP/C7kuMrHMWu8qHXCxRb4uTrRzBcGnI+TP32L6EUQ2juYZRcGQIyBecom6qf5LmRaezKzqIwSYT2ajku6d7GubERUrUXkvbWUVAEDjc5eKlJJh48tZhxZ9N86IG7WHD0AINhL0l3KRorCiKFlrm8VNGCJUmEVZGbokVmOBMYZppiepxcvo+MOchBI82wBeUOi1aniVMBJKAUVEIZFBAyYFTZmJWUnHCTj3recPDIkasojni4WOjgSrELl9iOKEyt2WcjkNJVTqQj/z/23js8rupc+/7tOr1oRhr1LtuS3HsD2xjTawIkkISQ3vtJO+ekV1JOQgIhlYQkpBAIvXdjbOPeLdnqvU/vu31/jLAsDIQk7znfd94v93Xta0Zbu6y9Zu21nno/jOUDrPvcz/HVzefHT/2Yrj1dBKYJeGRDZZ3RxByzjInsIO3RXUTz42wovRqfWkIu2s3+yaeI+K5GV72ouRiLjv6MYNCGY/lHsQw7SrkLrpqgo+/r5KaNfyUlF1BV92988fkv8/xkITf1k+EI77R8CCvfDcEm9K69mHt/jipkMfICfTuDjMS9xO0qMYeNiNtOVpUxXyViI+7UiHnyhGxJzhaiLFbieDxOBHcxuEqIyZXsG2/icDhPVJlt0PI7VXyeOqJ9Cg80l3LSFJC7EgiGhSDAtSur+bcFaYL3vwUhNUXO7uKvrSvQ3DHKrBFk4cwaP/mcg/b2s4nFCqyX5RXtNDTsQ5yO5zIRiWt+ItlS7PYmNi29gaAnSE/PrYyM3s1LypDNLMG/vYrfpBfwx/MvxxJFKqbGObfzMK5sQTZSTJEFZi3zpVpq3rP8FIOYZVmkY1Fi42PEJsaIj48RGx8lNl5QkOKT45jGmW1XPXnKV01Q1FTwkugWtGVE9qVlYoZAwpSYMh2YZhbhtPU6pAW4YuJcHGk/MamfD/M7bBbssd6NZK2ibNr7qgka42UvkGt4HM01StqQ2Ruu4vhgNYrmxq65cJguqirK8Neq/GbkZ2RIYddcbOm4gTcLCygGogr4p+0ESoWLwJvmoZS5zniewY4T/P7Gr6EmY2RtDjZ85NOcvWr1rGNi46McffZJjj77JMnITO2EinmtLNx8PvPWnIVif30RF7GJNPd+fz+pWJ7iajdXfGIpdtcre5bix04Qu3MIIa+Qd4wztPQmxnWDTHwj2UMRYsOFvMPy+SEqNhzGMCO43S0sW/p7FOWVw3tfL/6lBL0OjB3r4L7vfg0BAefHN/PdIz/AwmJLzRZu3HAjNsmGZVl8+cE9/HXs3xDVKLKgolt5BEugLryIxcPnUJasP3XNmtYAS7bUUNVShCAIjHae5NGf/IDw9I9dpkksau9ANgvdLth9KDXrEGvWEPNB45vORj+xk/HvfAszlUJTXbTNuY6Y00dUexzJymAJIj5NpX58krLJ8VPsOZ0hPyfLgwiWxcruEYqTGWKqiyF3MUOuEpJOJzW5DtKqhL72YpZccz3zyjwETwuRiWg6tw1OctvgBBG9MIFU2hR+3FLDaq+LHV1TPHhomMeOjZLIzlh7aoNOLg9MUXn0boaHE1jTlhS3HXLSZYhKI0eKu0gatfgRKRZFFvhdzPXYudt2B/dJT1CnVXJLz78jGa+8EFhY6BiMC3EmxThtzm6eC24no8vMmVhG8/gKFGtmDJiCTt42Rc4+Qd4WAcFCMBTkrI6WHuOEXMVBZyuXL2/gg5saKQvnCf/lBGZSI63meGTNPv4UuYe0XlBEl4eW8Ymy66gfNsgePoKRTOC/+mqcS5e+rvGmGRpj6bFTitJocoTR0QOMjuxjJBdlRJFJ/A0ihZcQMAzKUCitXM3U1Ep2HStDP63ffKLFNZadsyyZagRsvPy6eUThBE9LXu7Qg3SiszaYY603wsTI0Kmjsmoax8Qo3pEYpmUgCCJLz76Ys979jtc3aQ4fhL9cD9F+tmaWsqffh2Aa4A9xe+AyEpZKnSZySVbl9gvdTLltzE2nOGfPk2DBaHAJ333PJficr899n96/n4kf/JD03kK4ouh0EnjHO/Bf+2ZEhwNBFDEFkX2P9bP7iW4ebv4lQ0Ud+CQ3lyTj3GvjVC0PgFpvLctbvsPPRzQUQeCepU2s9BUWovgz/cSfKCj+3gtq8Z5T87ra+GowLZPR1Ci9sV564j30xfvojfXSHR+kS9lAxnth4Zm0MdTsMbKezWDl8Q/chDR0Fql4IXerzJvjI87fsiWxjVLTQtj8BVj/yYJiBuRTU5x86IfYO1uwJwptDr6tBceCvz8x9V9K0KvjnwqH++RGjENjiCkQctPbtKnftFvo1Q68zZ9HkSowrSSi4MbCYke4nd+pJsfcMxbemvgoV3S/wPLoJEMNbyDiraM3JHO40U5blYw2PS4E06Ch7wQrDu2gfGwAyTIRp4VAwbQoiyWZNxrGmf8/4wF9VYjT9xQsBJHpyARr+hMsQUZHAbeMvypBSfUEimMmN2USPw+JG+k1GwCwBB1XvAFnqpry8jQLHONIeReS5saMpqH/EPmBnYw7Kjje/HZMScWVGqI+/Si+c9dQcfGlFLnLGP/pAayUSSpwlMFlP0RWvQQCa4loGt89uZ++bAabZONb1Zdy/t4/F4xUgB5sRoh0I5l5Jgwb94y2kIy/MhWwZJh4Ab/fyURAxfTqjMsjvBiIM2ibecbVmSxviSfYkMyQG1eJDzhIDNrRcxKRoiKGKyoYLw0xWVxcCGU8DXm3lxG3yFjSwcnJcnQkvKT4lHwXV3if5egCN3G7izRO0rhI5l1EUz5yqgPNpZLBSQoXGcuBp1ekdKDgSYm43bzQNJ8pZxFZZfbaIJomi10G79K+TkA7hiUoWJZIGA8/4ROcFAq5lfOHulnbfRTZNBHyOdTwGOv8xTSXX402kkOwy5S8dyFqpZusZjAayzIUzRS2SIbhaIbhWOH7SDSNkkvg1RJ49Th+M8ra5r20tHYiSSYWAuVlb6TafxHaoV+TGHmGdk8l/xH4MsNiJTYzzbusm1iaGKWs92LKxlcjWgWv3EnrBF4lTIU+n8IvBhkxw3DVU1j1T2DYEqRNeCau8HxSJm+dGXFyOkoTdVyb/Agbz13CySKo++1JfBq01zlpHc8XCBUkAd80AYbwspydiclJbvnGl/GO9GEKIsve8g42X/aGM6KaTMOg5+A+jjzzBN37d58it1AdTprXbWDewrMonTsHtch5xj1OR2Q0xb0/OEAmnidU6+GKTyxFdcz2WCZ3jxC9rwtMC7naRnT9IwyF/wgU5MpkshK3cT5tDxwml05j8+dofuMIgpLB7W6dVoT8r9lvr4V/KUGvA+N9/dx6y3+hZrIk1Cl2rQozkStQS9okGx7VQyybIm9mTsX/yoZKy8RaFg1vwpMrWJhMwSBS08tE0wlyvjiiICJYEDyQwH8ghmCBquksGpgglEgDAlLZQtTas4j5AgxEDzBq60VvdRPaO0TLvoLCNOVroL3lXcSUBPn0Q6h6lqiniHsuejtTgULMbJVo8a1cPyXP/5FnOgpWsnn5cer6E0hnGs1mYcLhY8hVTLiojHxFNcNl5ewMFtNXWYbmc9DgtqObJgOjSeSRDK6JHNnTFJ8yr51LF5VzeWiMhe03I3Q/DUA0b2eXtpwjgwKCWeg4QSxCca0kt+VsHh6M0TM50zhVyeJq+h46KT655HNcPX4W8ecGwbCwsF61MvlLyKERFpJMiQkipk4ir5DL+BHNmYnYwsQSTARzmFUX+8nPW81PX+hje+cUEvA+bLwVGzkhzyM1O7nT9yhCJEbjiMWaSJB1sRC2jkHM2JmMba4NZ1PysY/jWDD/tTv8JZgGtD8EL9wEw4V6MmMldo41e8laJseMan5jXEO5TeJcb55MfqKgOIU7GM1Mkp2enMxcMdmRqzEydUhAixJls0PgglwV3hyz+s3CIqZkCC2vxdsaYtuJ5/j3HXlSlp150hhLbaOFvBYKYQutra2sXLmSquoqHuh+gAeevIOz95UQTRYUJKfTx5b3f5im1WtfMXx0FjIRBn/1Xu7dkSRvyugON5nqOSRp5r68H10Ap90kfFYlPj3J1nWt3Hv/s4x1HcOwBI44F/P9d26hKfTqleWzbW2M33QTqa3PF55BVSl6y1sIvu+9yIEZ13oqluPJ244xeDLM03N+T2fxflRBwq3lCU97O+2mSVYUuXbetaxofD/vODqIBXx3bhVvr3yZB+10Rej8Wryb/zlF6NWQ0TPcO9TDN/oyhI1CJW+7EUUbUJE7YggmIGioxU+jBp8/VWfCYZrUaTp19iDzq9/CosFGAiclpOnwIWRwLinFc3YlSumZVsa/hf9NStBPfvITvve97zE6OsrixYu5+eabWbVq1asef9ddd/HFL36R3t5e5syZw3e+8x0uvvji132/fypf9burmVoxOWufkH1JIRKQ5FIkfIh5CW2kh2GpmJP2SibEIrKGjaxuo3JqiuX9J6mOpwiXbaDXVs/ByhJebCxjzOM5lZsYDI+x+NguFpw8iO1liephxU+bu5mmSJyLYp34MbHrJlJex8hrhGWLpGQimhayaeDLGUiajqBnkQztlBIFYAkF9ivxv0Hi0IJOxLlp2kOtHLe3YgpSgXKbo5zDTgTZZCCxmuH8fJKlKZwrHpoR8rIQPn4h451XARau4j24au5GlDQE0UJSTex+DWe+ktq9/45o2ImV72B0wS+YMgRuHbcxNc0A9/6QzDz5LLL9FYR6H6eFg7x0m4SmcmfvQmJ6IXLBadOQQ1lcthz+CQH7IY2yWGrWajcZLMF91kZ+nivjWa+OWrYb2XGE5n6DtW0Wa0+COz3ToZJLwdXsJ5l1YxzvR5cEJkpKGKuopL++kqz8csOVRdxU6TRCjJgewg4X2dYgRvAV6uG9CmqmRtncvg+7rpGVFZ5pXk5/sJCEr+bzqHoeyaHxOb5OLX0kcfM9/pNecS6WaWIIIqquseHkAZomhvG7RczOHszIJBWROEv6xxEkG8o5n8furiQtWPynXWNPJvs32yYIUOqxMz80xcXVv8CvFIql+/xrmVf+Hjz7H4L9vwUjz9aiFbxv/jeISQ4qbDK/dGQp2t6JOjiTe6dPdWI40yjOFsRpggVZGCYvPcvvpHJkR5y6+iM0L1iFI3QVSdMkmosSy8WI5qKF75koY4MjRKNTZIQMS5Mt3FD1LmqvauXhcJwPHO/lvCGNbxzJgigQfOd8UtuHybYXPDhqnZfANXORX1YqYiKV5pvf/w7Vxwu54k0bt3DJez/8qvk/yfAUR556kqNPP048OlO8VkDAKXvxOIJ4PcX4ikrxh8opqqjAX1WJGnAi+WxEE3nu/9EhsimN8kYfl350MapdxjItYo/2kNxWkBUcS0oIXDUXQRHJZoc5dvy/CIcfOOU1FIW56EMLOPJQO6ovS9Pl/SgOHZerheXL7viHFaF/KUGvA51DndzxyztO/Z2SkvS7Bxh0DxJX4rPYRlw5HwtGN9A6tg7bdPhVVk5xrPQFjpZtI6MmTh0bCsts2VeMmlex6QZVU3EaJqIokhPRU45uU0lq46jxOGo+f4aN3gKG6jfSUfMGpuST2KeeRLRMhkorue+Ct5B2+hAsk0VyDxd6JiiJw8SvHsfMa5QthrI1bQgWNB9JEOgxyMQV9g9UYqZEPLqJwxBQ06+uIRmCyKgzQDRQyrC7hG7Jy7iziDFngAl/kPVL67lheTWrcjsQt990SpBHEGH+GzjWvIX3H72VXDzBiqFymvs86NNFzETZzdo3vhHnsg082RHj4SMjdE+kCPj2co5ziE2xlSxJz5slwEeEJD3iOL3SBIKSw6f5KTcCBE0PAcuN/Aq8dyYmcT1OOG8Qs3zETYgbheRd1SHTsLiYxuUhpgyN/H1dlMXj7NEf5URmBzVjGRpHLIKJMy6LoCjYmptxLFyImU4Te/DBQrI94N5yLiUf/Sj2efPOPBFAz8GhP8OOH8NUZ+G3lh30rlxNt1KgUT7Acn4t/Rufa2rk+opgIQbYsmDHzVhPfBXNKiNadQXbhIsY7M5RZolUIVIhCCjW7JFkqNBljTDAJGaFjTe9/Vp0UeWrDxxl28GTNMtj1EvhU+PPJWRY3lzHigvfgtfnm3WtRD7BbQd+ie2+EegfIq0XQgmqWhdxwQc+hr/01Zln+o4c5L7vfR09l6PaGcUWmscBR/X0dZt4UAyS102MIpXLxh5hqdXBG//9v7jnkT0M9XaStyS2Cgv41lvOYuPc2UVScz09TN58M/FHHi3skCT8V11F8Yc+iFI2u00D7WGe/PVx0vEcOxvv5XBoKzNR6gXvWkoQsNuL+MZZ36CueC0X7D1JTC/k33x/XvUrKnzxZ/tPUX56z6vFe+5/jyIEENN0vtA5xN0nx1GORRDjhXgJV7HKhzbEyQg99MZ76Y33MpgYxDJNlifnc1lkAytTMxTYWcc4TxTv5XhtlFCwnDfNexPNgea/uz3/W5SgO++8k7e//e387Gc/Y/Xq1dx0003cddddnDhxglDozHypHTt2sGHDBr797W9z6aWX8sc//pHvfOc77N+/nwULXh+V+D/TN9/92VpamsaxCfAKaYv/NCwTLE3E1CQMQ0YzZAxdxtAlTENBEp1IkpesZieblUFXkTUnQqIKJefDhoLNUhAEmTaPjXuqHbhSYbbs2sY5u3fgnA6hlXw+/FddirWuibv6DtAUPsKK+HGCuQiWBVjC9CdkBImY00bWA3GnTNIhY0gC8qiI15xLaPE1eIqWEH2wG20gihHuJDF2CDnSS8ecORyf34qmFkL6XMlhlml7WOQfJihkz1hjs4KdWMAk4lMZNeYQk30o7ilUzziCeGYI1UtwTi6k6sAnECyJ/uqH+az3IWKmQFCE9weyhF7ySOkWTW0ZaiOz6ytpso3x5s3oSy/GJomkD/2UPucIpiQgp210PxXCO57FnbYIRVMoGR3TEEjKTpKqhzQ2KmMTuE9jLI057byweD4vLj+bA3OWkprug2AsyucffooVe5+BTASAtN3BtpWr6WxspDwfRnsZs17eEhk1vQy7g/Q3VpBx2vHls7hSKTyJBO5MGlcmferTlUnjTqdRjTyRylJMW+F6DsvBhhUrWbF2EfG27Rwa/QxW0CCnu7nX/z2eD3uI2QpCfEk8wnlte0jYnbRXVWEvilCb78HdFWX8SCkXtu9l2dgJJFnFue4TSIFGclqG7ye62RqqoSLgosLvoNJvp9LvoGJ6q/Q7KPWqjI78nq6u72KaeWTZT3PNJwkdO4Cw/3dg5LGAXy/8NF8KXIphwfVZhU8MGljdM6QCOU4ihQXkwJyZvgoMEyu7hwW9T6KYBo9L69lpFIwqbvcUc+f1U1tbhsczH4+7BZfcjH7AIrl9GDNVmLcFRcTSCmNma4ubz9UI6MA1pX6+tC9N7tgUSpmLkg8vJnNwguiD3Vh5A0EV8V3SgGtV2aw1aTib4zO/+jVLXngE0bIom9vClf/2H7j8M6Fl+lSGzPEpMsenyPfGsUyL8Ww/3YlDDGe60M0zGfteQkFB8uFRinArRSjOKvrzDRiWSCigsnlDJfrJKNpwIZTRc0413vNrz1g3I5Eutm79ErJyFNOQ0XUVUWhkqtNPeCSOvzmFhYxl+nnnO29Etf39oXH/UoJeBx7qP8m3drbTODFI7dQIsjUjTMeVOIOuQVKCTtPEahqnliFN/z9mm6CtZAf54AkqDZmSpEgwAYGRFEVdMewJHYdmYNP0MybfV4RgIdtNFKeB4jIompPCWZLHsERieRsxzU6Po5znmjbR46qmX9KJpB7FMgax50Qu3V6OOyszHMzwzMoxri3Os8JVmMj3pYIc7oZ8RMajwWbPENVClozazHbnBfRNOKgcGqV6dJi6qTHKI+PYtNdONkzZHZg+lTJ5DNWlo3gElIVno258J4/Zx/jqke+hWwYLixfyo3N+hE9wse/hR3jxnr9iGgXNwuZ0sfScS2iuWU/ySAxxaLYFLCwk6ZHG6RHH0cVJZNJEmWENsTBRjThCXKPUULhgYTM2vYnkiIWQF5HFM5P1LCBpQUQziekWUcMilc/iixyhfHgXRZF2xNMoPy0ErNo6ipYtwbFoIfYFC7HNm4uozlw739fHxE9+QvzBhwrKCuC56EJKPvIRbI2NhYOycdj3G9h5KyRHC/vsfsxV72FX0RTpyIMAPM7FTLg+zNdKSgkmdfRwFmM8jt5xHD0hYlDMy+t+zBpGJFDFE8hKlFSDg4d7hxm1/NTWNXDdddexvSvMT/76DOXaEMXizOJcVeJjVeZZWpMvIGPA3Ivgku+Dr+qMe/TF+3jwvj9SvT1Pd3QfJiaCJLH6DW9i9RXXkM/CQFuYsd44WBAfb+fkzl9jmTr+8hY87g1MTLrIOIZJ+jpJKzbunrcJ40AEwbCozA1z6cgjeLxZ1l77IXYcHWIqPErKUng038r7z27hbcuqsabGSf72l6QefmBGCb3oYko++hFs9XWzJl3TtNj7SC97Hu4BCw60Pswu3xOn/u8yTVpzefbYbaypWMs3z/omLluQS/d10JbKsszr5N6lTdheI1Qx/uwA8cd7gf9eRSirGfz46Q5+9nw3pmlhyQL6XB9GlZPPNZTzybqC4memNeJ7hknsHEKIzgh1yeJDjFQ+w7eMk4waM3308y0/Z13lur+7Pf9blKDVq1ezcuVKbrnlFgBM06S6upqPfvSjfP7znz/j+De/+c2kUikeeuihU/vWrFnDkiVL+NnPfva67vnP9M1H/voXIgNbUfQkKgIVSRvlegbZ5ifnVEhLOUwphyrnUaQ8qpRHlXJIso4ka0iSjiRp05s+6/OfJafMZNzE4yHi8RLisRLSaT8v5yeWTB1FNHCLOVxmHAdZ7GRxvLQJGjZvMRGXnW25YfYrcXoVk7xgstzu4oriMXyvwAegKH4CRRtxdLUg7a6h30rwonyStFgQ3HzRKEsOHKRsbAwAwwapGgtXTQ5nXR6/mMeXzCO9TOrRZIGoVybqU4h6FVJ2D0gKhpiiwFssYBlKYR4bX0f5sfcAcEvpn9kXeo4PhrL4psUHWTNZeDxBIKZhAR0NLiJeidaTKTzTpARxl8Luxko6/RXE8BHHRwIvcXyn/k4abmo6xli5/yhnHdxLUXJGKI+53Gxbuopnl63h4NxWTOlMQ6DdSuMixbxYis8+1kXg2DaMyRMzfenVEFslnmxex6BRjpyTzwidszSTmuFBykdHKB0bQxBlBgJBDJtK3mkn7vHQP7eVF5as56SksLb7KAuHugEYF12o5QkuaHgMVZhCnBDpe3Q5/3Xl+5nwFYTaRQMdhMYmOVzRyHhpMbxC/qfLSBNMCywZ7OXsPTtYb1uN6q/FzMXJn/gdvgvX47vyStSa2XNuNjvM8bbPEonsBCAoN9EyHsTW9iQYhfGi1W7gPxd8kd8nFDaO6/zbgEn5VOF/FjppfwdqxIMivLQWmii1ecLNLzJs/RawqBzO0tyZxJAVHq27igM9JRhGYfAWFQ3RUNlB7eRafAPnIBkFxc90Z5FW6HhX1yN2+7h3Zz+fa1ExRIHLTYVbNzQj5AzGfrgPM6XjOaca3wV16OEs4btOku8pRKTY5xVRdNUcJO9MSkNnOssH732ITY/9GXs+iztYzCXXfwpP3Evm+BT62GzFXCl3YW8N4pgfRC5zko5GCXf3M9XXT2RwmOj4MLGpMeLxCXRjRkGyELAkCZQyZM+5KJJAk0NDkgq1AyN6GF0wQVUwVZG8aJBDJ2fmyRl5Xq/q8Z7rL6KqcfXfPvBl+JcS9DpwcuIo79t5iHbPfKom2zl7z32otiAO/LiTPuzZGgRrxkoo5TrxTT1F5chRAknrjIn0lWAJFjhMbE4Dm8NAcRrITgPltO+y3cQSBcJWkLRWgluM4xVHkV/DImUhELP5uberiXDCjuTUSawJc1xK0yOZnFtksNlbCF17LiFzf1Q5lafz8uvIgp0yUaXGFaK4qJEKzYN/1EAZSFMaMWnQTIyhAXJ93Vjxv12dOG2DbImHqjnLsFXVoFRWoFRWEtHdPHXniwTkFFXOGkodNbOomMfFKI8FtvGC5wDNkwtZmI/QLO3jSXE1pl6JgcEJ/wkWOnNcOjDOMyeDgMVV1QUvyo6JWkayhTHgt1VS4rsKj6hQIuTxKTKC9AqKkWWRMiFqWMS1HJo+xLiY4t68yUlfFVnZxvqmIB85Zw5rGgKvGvqV6+pi4pZbSDz6WGGHKOK94FxKVqmovX+BXGHSsjyVmMs+Tiq0hcNHfos/nMKWCpHLNOLNBxD11859SWMxhMkYGnXCYRZIuxGlEbKOFK58HzZzdv2HvGgnVr6ReyONDKRsp6zKoiSxaOFCVq1aRUVFBWhZeOEHsO0HYGqgumHzF2DV+0A8c4Hd1badxB/aGB04wFi24AURFT+S7RwkpZAjZ+Q70VIPASai0ojiugRBkAGL+Y5HsXv38NFF/8FAoJTAYBz9aIK8AOX5ES4ffhiHLYuzfDWjsgNTzhAxHexIVPHetudZ37cDcZqBaDK4gO76y0i6Z5Q2URKmt+k8mIxOXsqyc9WfaOMgAIJlcXkyzbAkcsDt4eNLP87b578dAYH3H+/jgfEoIVXm8RVzKbedOXZejvhzA8Qf6wX+exShHV2T/Mc9R+idKixim1tDpOZ52ZqeeSdvDoU4ty1J+uAE6NO0w3aReOV2JsrvRZBGWHY4jlFzPr1nf5T+9Ah0PM2azV9/xSKufwv/G5SgfD6P0+nk7rvv5sorrzy1/4YbbiAajXL//fefcU5NTQ2f+tSn+MQnPnFq35e//GXuu+8+Dh06dMbxr4R/Khzu8GHuu+eev+ucl8MCsCwkw0DVNATTxBAsTNlAlvJIooYi5nCg4RIM7JKBJBlIch5RzCFKeUQphyBpCLKO4NUQivNnKFGGJpOKBUgkSgjHy4gnSjDNv5+Ct9Bmi7yYRxM1JMXAr6bxqllkOY+s5FDkPLKcQxBNhoZaSSYKhjGHpeIxvIij9QTCbZTGdhEMH0PKnFacXLHItVjkFxqIlRLerIg3lac4E0U1Z+c5adgYE+fSZ1XTiY+OrJNsMoVkGMSdUWpLG3jb1GWYmGyX7yIuHyNjd2KX4ZrsYYJ6nLwocqzZTbi4MHeMU04yWsHVbdsp0gqW8gdKNvG1hg8yaC8YL0TDYHFHG5v2v8jZB/acofjsWzKfI8uaGJkbwC0l8BKb3uKnvvuI4SKFiImADYdQji3hw3NiDUpPFXrP82j9O08pAlAghzlWUUxvdTkxbxkJTzleRUMWZhdEVRQFTSusMTlR4kBtM2WLl/CN5lrGcxq39g2Sa3uUxpNTYEgoSoa583YwFi/nhdR5bG9egiYr2PM55rV1IeX9FAUCVPodhHKjjO28h9HScvJrFtAtOxm0yrBeRhbh1Sx+tStBQ0ogY2bpbP8dFd0H8S9Zgu8Nb8B9/vlMxh7mRMfX0a0MoglzupJUjmRnJKDaswif/XneFyvD1xblhp48Danp+jaCQcbXiZItRsm+ZHjNYVefYXLtOMP250/RP4dCF9NQ93Fcd30M+rZDwyZSb/wDz219mn37DmKaFljQZJaxXG9AdU0yVf8IidLdMC3fHZa38H3j/RiIXDis8dUjWWwhJ0VXz8GI5Qn/oQ0ECH1oCWq1B8sseJNij/eAbiE4ZIqubMK5eCZK4kAkyXuee5ELHruDYHQSSZBZVXwxNe4WEMFW78PRGsTeGkQuspPUDX58so/DPb1scduYr4pks1my2SyZTObU93QqRTqdJpfLYfwfKJYrWAIKEpqgodpSOBxxZKXwjquoqPkK3vzer6LY//b6+3L8Swl6HTDG+un59Hnc7TofXzxB41AfhtLEaPkm0q4CbahgGZSMH6Bm8Gm8if5Z51uChalaaDaRiOgkoyjkFZHGkimaSqYKSo7d5PR3eFiS6Fdk+hSFfkWmV1Hol2UGFRldELDlRC7YX0EgIuJUNDpXLscqcbFqtJ91+THKnZMoyT6sXILHRuZyPFaKTdR4S90hArYZYchwBogrEllbnIxDYkAq4s/KIvabBjHSiFYcyYgBf/vn/4x3IW9v3wa5OIYu8FDRZfzBdg6+qSmqI1NsysYwevdjn4jjf4UoO0F1I5cvQa5cgVQ8r8CYNY1McpjJyBGGE+2MO00e3xCnyzXG4myO+hxEU+cTzBWjCzqHfO2UTyyn2KynZPCvmPkMzUtaSYyPMjQcBsvCq+VYQJh8shU1FsGT7EeaXuAERxGirwbJX4MVqIWiauyvwkCStiymZIHdWp5dgs4JwaC+1s9HNjexcW4J26NJngsnOD/oZaXPdUo5yra3M/Ff3yW1vxPRVYLoKsFeUYQtVIah1mBoPqy/ISCIRJCFUWRhBEkYZZwcPzY3ss0qIYrFGnWQD5Vux1U0ScYdJueaBMFCEhy4sxuJ7+qghhEMQWW/1coJGnjJUusjzgrPJMvnVeNsWA01a8B9WjjQeDs89AnoL1jPqFgGl/0IyhedOiQ2kWHg+BT9RydxdIWx5Ts5GH6GjFFY2G2eeZQ3LaD34L1gmbgCCzCscwEJ2SZR0eTD7hA4IG/lB7UbkAyDq/Y/R3GumD+lS8hYFuX6GJcNPYRdyOJvncNYqog5J48w50QHql5YhKf8c+ipv5y4r+E1+9PE5GTFLnbXP0DaLCgQFZrGp8JRbgoUIQUb+c6G7zA/WMjpuqVvjG90j6AIAn9d0sgq/6vnIr0csxShLTV4t9S+9gmvA7G0xrceaePOvQMAlHptfO2KBVwwvwzLsvjzwCQ/PDJAv1PEnzf5w440pTkLpdyFbaWHdvMTpPLt2NRSlslX4Hzy+wUByFkCkgSJUXj3U1C98u9u2/8GJWh4eJjKykp27NjB2rVrT+3/7Gc/y9atW9m1a9cZ56iqym9/+1uuu+66U/tuvfVWvvrVrzI27WV4OXK5HLncjBc9Ho9TXV39D/VNx5HDHHzw59hz/dzjDDHlnMAQDPKpORjR5SyMj9E6tJucS6Ctbg4nG1bQX1aCJssYoohgwNzeLhYffZaqiVEky0I7TaAtykHVxBTlkdgpkp6XINj9KLXz8GxehWv1MnJ1c+iJ5dj+wgHs23/HSv8hbDUp0hUCyaJCyNosmBb2GIgjKpkRL/3ROgaNKmKik5TdSdZmx5JFbIKBio5N0LFbOtI/kCwkijqVFSdYmptD8dBmkmqYfTEb8YwHwdJw+R/FHTtO5eEwvvDM4mQiEPc1MBFcxH1nr2Bofp410UOsiR1mdewwAX12vZu8IHPA08K9/hoeldowLZ0Pj3+AS8OLyIrwoRVOfBzgl8e/jF9PMmAr4/oF32LK5eYCHmETT+GgkMMSt7xYYT8XnTyEQzPIoHInFxAZdHD2wT24kjNjKKvIDAX8REJnkQqtBsXCE5QYlMfJju1kRfNe7HOnS0hkwb5HROiTiQkmoU4B+/gMoYarNEtonZ8YnySfL0Xrf5F81+NY6cip+014nOxeuYW3XvAudpTZ+NWTe7FnpygX45QIqdkKsCAw4fYz6C9GDWR5c8UxSnLPoutx0mkPbW0bSaeK0ESJF5oWcaK8MBc2DfXx5V/8kEWXXkzoM59BEATS8Ri///zHSU5N0rx+Ixd/9NNYVp6OoXvZ2vcEbXk/3TTRLcxlgmK8eYuf7k0zL2EyYRP40FIFW3iAhUPH2FT5OP66wjvqjWvMP5HAmQUqV0DjOTDnfE64W/jTw+1c0pGhPDs97mwiujSCkHcj6YX8SEExcEp3M1HzJEO1Jub0OxQMnkNjwyfxeKbzgKe64KfrQM+in/19YmNnMXZkgH1yF11SoS2SKLJ4SSMLFoho+kkSieNsTdj4gflRDEFhrfUCX4r1U3z4IoSMDAK411dixHJkjkwilzgo/dhSBKUgP2ljKcJ/OYk2VPj97fODKI0+cp1R8p1RdrkFPrsALnzmLhoGCiUi5rWeR8OGN2CKIlreJJmMs3+ok9FoP6IZJeb0EEzG/na5ltOgygqKJmGzZCRLJqlLyArY1DBaMkE+HsPScgVCJMNAMHUEw0AwDLBMJCQc9iCx8gp0j0ZV1XEqKk4iSgW5bfXyx3D75vyNVpyJfylBrwPG1AQn128gr7gZqtjAYOUGNLXA2iLpGfzhHdhTz+MXMyTtPuL2ECmni4zTQdrppEiNIsSjxCbziLpGhSPGhRUnUSUHUaOcmF5B2CwhI2mMaUMcyeVIqBYhf5giX5SIJNGlyAwZXmxJiUBCZc6gC09GIScbPLHGR2bOpbx1chHy9smXoq2onR/AZd/N/qceQBAErrqklVpnGCI9EO6G9NRrPnda8SAG6lGDDWQ9ZcT0FOORHobCHYyaKSZlmXxcZv6LCqFRgbwMTsmkVFUQS2oRQ/Vk7E62Z3V6BImMzY4mTiIa+7lyzsXMdzdhxDNoUypmyoNlBU4VBQMwov3ow/vQhvZhpcZntW3UD596r4QuC2zoW0SJOQfMPEumdnK+eASbX+OugUUMZXx49CzOlIEvncWfzhLI5hD1M4ezqJjYizQSJU4erlV4tF5jygM2S+T6cC1vStVgVypI6XPIZ4pRX0VJSVoafUKGE2VOXix1M+wQKcuaLMporEvGaYzHkFMyhhmEV8hTOm3kIQkTBSVHHEN2ZFA8FpJfAbsNMw3ywJ9JyhFusa7m9vjF6Eg45QzXNd/N2vI9Z1hjJcmJYRQE/PHxOgYGNpJOzQg9fmJsUQ/Smj8wK1kZgEAD1KyF6tWFz0AjHPgdPPllyMXIWy6GGz9Hv7SF/vY4sYnZ3sAqj8w8MUdHeAcd8b2zaMDtxa1Y+vkIgkjVQj/n3TAfp9vGiVSWC/aeIGtavKfrAeTBQlsb5szhB10lRNMaFUxxWc+9NI+PMyccR8oVJsXRohJ+3HIlE3MX88sbVjAv5ME0LEzDIp3P0BXtoiN6ks5YJ53xTjrjHcS06Kk2rUtnuDiZ4hvFAS6edzWfW/k5nEohz++5cJy3HOrGBL4zt4obKv9+70hi6wCxR3uBf04RsiyLR46M8uUHjjE5LRi9bU0Nn72wGa9dQY/mSO0aIbVnlHRa492rnZzwSlSnTM512PnISi8Dx99FOt2FzVbGsqV34HTWw+G74IEPF3LUAOw+uOrXMGfL393GfylBM/jKV77CV7/61TP2/yN98+xtX+O+zgwPm2vQBQk1uBVbqOBlnjvsp3ZoHsfnraR9zhKytplQmOrxDIu6DrNg9CDueI54ZmZ+VUU7de4FNHgW4ZX8GJEejMnjiI4Mossk29eNOTh4KqwXQJBMPFVZfI0ZXMU5Xs7gbCCQLK8l4i8iatOI26JotjMT1qUpULtF1C4BtVsgP2Zn0FXKgCdU2NylDHlKCLt82BWoCaaxu46S1E8gGQKqqaKYbpxiCWWCiNfIIDrChKr2U+4qzHtSzkuw+zI8A2dzUJMZShWeIynHmQwdolnK4By3U7p/J+UTsw2aU74Sds+bw4G5zXRXVlFtTrA438WyXCfLUscp0cI877DzqVAxOVFkdSbL+xJFSJlPUJquJivlKRFuxynu56DXwXvnvBMtJ1E3ouNKpwlYSdY0j1NVtB/BmgIT1A4F93YJ51ENMzuzXhhOgexSndR8Oye7WolPJkEQWHbx21l71ZWoDhgY/C0dXT9CsNKYlsBIXytrO+qwnt2DEY3OXEsScNTVU9SiUeTejYCFXrSEROVNpPYlsUyT9NgBwifuwReZOCX8RopD1LzlzZyoqePmPWMczhUjY1IuxdlUZhIkQXhqNnGHKOp4vRP4gwla5i4kWHshP9zay9OuYqIuD1gWomnywQM7uPq2WwEo/tCHKP7Ih7n3u1+j58Beisoredu3f4jqmCFmME2NsbEH6O37Kel0DzF89IgLSIoXcfHzlZQnBcZsAt9b08FVtlsJEMZA5CHtSroHFrFYMVm9dDmL6opIdHyXkSPNlHcvpChfGB+mQ0L1yGjjKYTpQqWGHMa7rpzw1DsZKE1jyIWB7/evorHh3/D7V8x6dsuy0B/8Lsr+b2FaLkZzt2ISxN4cILVQYeuxF+nuLoQJ2mw21q1bz1Cogc+NTqIB6zjJB6wvIaEh5l2ETrwV30ghPDkvg2gKyKbFqFOm16ag5030vIGs6cwzLYpfqu14GrKmxV9LJH601M7Zu59k1aFCcXLLMQczsJC8PYKuJrCArpJKdjbMJ2V3Uj0ZZnF/L0m3yOLiItaFArgcDhwOB3a7fdam754k8UQ/WGCbW0R6SYhHbjuGaVjMXV3KuTe0ImCRCE8SGRkmOjpMZGSYyOgw0ZFhYuOjGNP19iwEcqFKtGAZipKhuvQQdmOSS697Gqd3do7y68G/lKDXgcRkkue/9Cf6zTrMaaFVFaJU2x7mq/MPklTzfG98kgtThUk2hYPjzOEYc+i1qjldEnXk8njzIYxcHUVVlTS1FFEx+htCg79iT7iMXZOFRPDeuS1EAi7ckyfxRKbwx0Xs2myBOeHQeWrlGDF3YXA06RZXuFZTEr2evsMWerYTLVUI4Vhx2Q1sfNs1s87PREa4/xsfwxXrRyxSEevtrModxJXRsedf24WZzctMHvMyPBjgj+ddwURRgHc89FeqJkb/Zn8Kqge5Yily5fKCx+flis/QXvLD+9CzkQJFpiAhiBY2UuimhWEKKAa0VYmcrLQwJRuN8QYau3pwTRMrGBIklQLhhF0/M1zQFEUS7lpSnnLmlb9ISWiEwYDATwJ+nnQVJlbZsrgqkeR90TihV6gjoJseRvLnMKmvRzObcEsqHvHMSea1kUMWRsEIk5+IkB8dxUxNYGbH0VtHmbigiLnrbiGYqSfTN0Vs+AjJTDua6wi6dw/HzCp+1fY2BpMFZpqloUO8reUu/LYETmcdbncLHvd8PJ4WFKWBxx7bTiL5F2prDyMIFtmsi6NtG9gXaaWpdTH//sZVeGwyRPthYFfB09O/C8aP83JvoOUIkC9ZwaTeRFePg7bIMnRmFiVRFChr9FHdGqCmNUBJtQcjkWf49weJdw+xb/IJJnODGI65OG2XYIoGO2vv52jZ8wiCgEv1M1L8ebJyBSVmL9dmH2DZoQl25ZcD4A9o/GpqLcmcQH18mBu3/Qyvlibtt3Nw4QoGKiroV6p4NmfD6Rrn4hUChjxER6SD/kQ/pvUKY9wCBNiYSlNmGDwSLOfL677CBXUzBUL7Mjku2HuSqG7wlvIA//UqRAivB4mtg8QeLTARec6twXfe36cIjcQyfPG+ozzVVhBiG0tc3HjVIlbUFpHripHaOUymrSBMAUhelclVJVwmJ8haFjYrw7f5LKUMY7OVs2zpH3Babnj2m4X8NMssEJm81FcX3ghrPvh3P+f/BiXofyoc7v+kJ+g3N93GV0cLIVILkbgGlax7J7dU/QVLMNFsc4kVfxJLcuNNGyzpyXBZZzf+ZDd9qePkzJm4/5C9klp3GX4limEO4suN4U/3otjzyA4TxWEg2U0EAUxdIBuW0bISss3EEdQQ5Zn5Qc+K6BkRKVSGsubNsOoD4JlNLBFODfLtI4+ixvcx3zxOSBk+oz6bkAWlp6AQqd0iao+AmBXQRIkRV5ABbym9NdX0NZYxVjTMpGMvmhQFQDEkFow4OFyewJLgiozGpmIda5oEUs4ECHZfTr5/HQeTFhlLxLJ0HMY+stIqRFPDntiLNwqGGfAAAQAASURBVPEi5VMZ/NFRBGbmDNOmItfU4GxsRA4EsXIZtknHubG+C12EDfEcPwiPYbPAtGxM5r9J3pohFcnlp0jn+/C6YSLSyeBINwktTU4Sceg6FUKK4vE0cuo05jyHhbM2S3FpGnPOXLqaLcLOUWTNJLfVy5Gugvyw4pplqFUvkk53ASDZ5vOD3ZdxeKyCqiIHv3n7MipHuhkYbudT3d9n2J3jDrWR+Z1bCzdadC1c/mOQbRy+7SGU4wYeZZrlVo0yIRxGe+h+fKlC7q4hivTX1NC7cj3PlZ3F7oGCN63InuKq+vtpUMaIRsuJRivI52ezlVmqSo83yGBRiKmyaip9Xg4m0pjAVc88ykfu+h0AAxdfxOGhkyiKylu++V+U1NbzSrBSE4y330Jv5H6SYqF9SsZNzd5PMlW7g2hNgZ02bJXyE+tjtEuziV7WT+h88Via4lxhTo/aBIp8dqzxGaNext+BWTmEbY2fvt4fo0uFceFxtdDY9DkCgbNmrQmWaZFtmyL+3CDaQJSQ+hlU8SR599noV91BSpaIT2SITWbo7e2mY+wgGaMQGp9S7fQ3ecjlati8w4WqJvBW78ZbtxNHoA/XxCJKj9+AkjstF9qyOJA2cIgC5YqIX37l9WlEMzlqCaCI7K5TeK46x+r2fTRMjmLaZ36nSbePbU1LGfP5Z52vahYrT2boqFDxVbr43rxq1pwWEWHpJpH7OknvLRiEXGvL8V/aiCAJdB+c4LFfHMUyLVrXl7Pprc0IooBpGkRGhpns72Wir5eJvm4m+ntJTE7MurfmKSJbXleoq6drvOtd76a64bWjPV4J/1KCXgeSfT38/tsdmMiE5A6WuB6gwb6Dj5YF2eZ0sCqd5YcnElhRyCcl8gmZjFjPfl8tfWIM3VuE7i3FcM7QTgqCQG1tDc3pPeSHD/BiuBppKo2FhSWIiK/Q3SYQ8xQxXF7LWLCcE0VBvNpNaErqpVLLAHgMk4ujxTj3FGGZOpK6CNl5LtUtAVZeUk9xo5e7RqbYd+t/Udl5lKTTw91v+jDXzGngzc4Bhk9+ELQocsLJWNs83JpGgCgBohSZUYQendGjPu5dfQG/veQq4u6CV0w18pzd+VccfY/R6qrjLbVvoGPkCFs7nsCrOWl2bqLMvoIiJTRL8dETg2SH92MM7kFMvLL19J+BBUy4i4n6K9E8ZeRdc4k652CJAiVyF3n7EM9XHGRXoBdTsBAsON+q5aO1q6iVHFi5BPrQMPpYAiMFgqUjCBqQRRbGkYQJLCtDj76UB+R3URSvoNQU8EkCfknAIZqY4iRDjjyH/QEOBwIMukQGHSJTsoU0kUUYziBOZXmXeDdXHNyJPCqgV1lkakQmm4uxqgyc7vFTQoJmyjzYdQGP9m7BtCQ8apYPrenj0oWleL0tuFzzkOWCqz6fz7Nr1y62bdtGPl+I7/Z4JpjTvB2XI4FpCYjed3HO8s8iiq9cdZxMFAb3oHW+gNaxA1vkIJI1mx1GtxSm9FpyhhtVTBFYsAj18u+AezZTm2VYhB/rZuTZX+KWnqIzdxEHhGXsnH8X/faTpwqBJv3XkvFegmDECYz8B6IZw26avGekltHsCmr6+inqHeArS99L1O6hJjHC27vvJuaRiNY7kRyFEITDgcN0+DrOeCSPINOIQmUux4SZ4aCqkhcFFmZziFhINeu48ewbKXeXnzonZRh/FxHC68E/ogiZpsUdu/r47mMnSOZ0FEngg5ua+OC6OozDkyR3DqOftmjbGny41pbjaA0iSCJPTMZ4+5HCPT9k/ZB5tHMg+H2+nDqM4/nvQHaa4n3+G2DLV6HtQdh3O7znKXD4/+5n/N+gBEGBGGHVqlXcfPPNQIEYoaamho985COvSoyQTqd58MEHT+1bt24dixYt+h8hRtj709u5rTvAVZKXZiTGZZ2rznKjWx14J36EaKWRrDI29L+HTUPdpLJHGM/OhHA5JIM5/ikW+wcIqenXuNMMLANMQ0CQrFlpgGnDy0ikkXCkhJKyMWo9h2eKSDqKYPF1sOwGCDWTNUzefqSb5yNJvLLIH4tUSu/4BftG9rNtfTPV/gGafL04lJd5i0xQRkSUTqa9RSJSeDbNf1aB/hLorBAYCgrkFGgaEmnJ+lHyKtrcSZRNGfAUDFtKuoRAxyWMHm/khFRQKP2RE7S2/x57LsLrxYQX/rxBYH+TyOIei488aGK3GThL8jhLcthKJDT7eSRTKzHtzQjSTCSBZZmY0X708eMYE8cxwt0wHZ5tCgJ5jwSlefRKC9NvodhMirNZinM5Eo0hTjRmMBUBaa/KeIkdf8O08K8EaGr8HOXlb6RvKsM7frOb3qk0PofCL65fzuqGIPce+z2Bhz7NxpeopDd/Ac7+NHo2z1PfvpljJ55DEmTWlb2BCvt0TSWPxCO+AXZHhrhs21PM6++Z+Yka3RxZ7OZm+a0M5QtzZ0vJJP9xfpC1LZvpHo/x8z0HmezvoyI6ic2YybOSZZmlS5bSuHQ5T+Us/jISZtWD9/DuB+4CQeB3F16O7YLz+cCalYRsCmCBrsHQXujeBr3bYPQIWCYWMFVko6/KQdItI5jSKfIK3/hGms/5AqLXS0c0zp6DeziU7WfVSCMbRgty2oQKopQlmCn8bWGSDO0nXPcY9vIAaaOHfL4gmDszFo0tX6Gk/vrZyo9ukjo4TvzZAcypQv9aIqRdI8zRPoiIzhPRT9GRnV2o2sTiUFMUr95FraODBQufwbIgGWtAi2zGbW3BbnMjOgbB9TSWuJ3ik+fhHzrnlQenAGK5C2VuEbamIrSjk2ReHMHCIuLLMTI3z8nhbqamTosOsizyep4XGxZwvL4VBAGHKPDR2lLOD3r5+L4ejlmFkPP6UY2yiM7uuXbeXBXkC40V+DWLqTvayHXHQAD/pQ2411fOataxF3p57g/dYIGveApL30F4sA9de2XmOU9xCSW19ZTU1FNSW4/s8/PoM88hCiLve//7kOVXkV9eA/9Sgl4PTJNHb3o/qjxKJhUnIjbxaKWNI8Y2RFPgim1llEZEzuqN4KxcTXeogbbsLgyj4ELsKPOw1XkVNywMMI9Regf6iZ/OXW9ZSKk4SjyMnIgimAZ52STszRN22CgymnAKq/jLxkaifjuCabJ2dJIjR/NoQhZXxR8QPQUqZbduoRkSl+4ox5ORSfkz+OuWIQ+cj2UWVqzhUoVRqY3WYw9giBKJ697PEpvMZG8PIyMj2O1xFix8GocjST5vY2jwjZSXr6UulUa94w62qS5+9sa30l9eGNBzzRih5AAveAuUsPXpPlaO/pxRxaJhqoGzE8tYmJ6DeNpC1WvP0yeMMGoMkhALfeE27czVy5jnLqOy/Ahixy08Zxk8oAZJoGPXwJ2D1TERNTEHSxfJCROElQmcWYG6ETs23UIyC/Uo3HkdaTopT5jXwv3LL+f4ZDmr8gomFuHqPEOhp9ktP40hFibilfFFLO67GDlZjsOjUFrvo6zBS1mDj1CtF1EzSB8YJ7VndJaQeaQkzVdaHPQ5vIimxbvbXuCs7gn6MyvIW27ARHLvIVXvZTC0jCOqjR47pNQZAdptxtggPMfZ1lZqhL5XHIr5nEpsrJif9VxPb+6lCcVEEkSKXCp+p4rfoeB3qnjtErlEmMmhfmxaglopgiRYREUvL2bLiQoK/77+EarsBeufz7eM+a0/xOGYIQ4wDJOxnjj9x6YYOB5mvD8BFoholCg9VDraqfd3UmwdQ9bCZzZYEAuhc0vfBjVrsPx1dO7qRXzkUzRKz546LO25AsdHf46gOsgZOZ6amOA9bZNYwOfK08xVIyTyCeK5GPbth2i540Xc4UL/9wbL+Lf17yMterGL41zX+zBuI8tkVRCbp2AtPOQ/xKAo4cr5WJOf5GPGduIy/Mbn5XGXE2N64WrJ5XBYAmtXf4L3Lnof0mlSnmVZfOB4H/ePRylRZZ54nUQIrweJ5weJPTKjCHm31Lyqd6ljLMHn7znCvr6CgLasxs83Ns2lvCNGev84Vq4g3AmqiHNZKe415WdUEM9mh/n07ju42zgflRzr4vv42omfMTc9Pe7KFsKF34G69TPPr2URXlbc8PXif4sSdOedd3LDDTfw85//nFWrVnHTTTfxl7/8hfb2dkpLS3n7299OZWUl3/72t4ECRfbGjRu58cYbueSSS/jzn//Mt771rf8xiuxtP7iP+vGCBXjELvC2tS5iqkDFlM7c/m4i3EL1KDQOuVD1wlgWsKh3h1noH6XeXZgTTrVFFJgS7JgpN5msSEJXSUqNSCs3MifXRqj3SWzSjGKgaTJdmXUc1y5gMlVF1dBW7PkYnU1XY1MStLqeZpH/OWzajHHLrF7NL0MXc6NjDYJk5+ZnHqD+rj9xf8NZ3Db/UnRJpkg2sS3wYISizKWdtam9tOSPQNGZBVj1lIK9E5wnTdRuAWVgpu7cq8FSLFJnmSQvtDA904UgU2W4Dm/kYN9ZZEQ7kp5hbsddhCIvgk0gK7jRLTeW6MKQFEpKVeRsAm10FCszsxaYAtibmnAuX45z5Woyk3YyR+NImowgSlj5JGY2gWXpCFiIjgCiu3R2+/QcxuRJ9PFjGBNtmNMFVV8VggVOC60IDC8YHtB0P4LZTN3Z52Erq0AOFZP2+PnCs33sH00wX+rmhtYsy0f+iD/ZRVYQ+GZZA3OW/AFxNMfUA79GTxZCs5wNmwhdeQ3OkSgNe6dwTRPz7HWM8dvVSTYNPcrarUdw7zcR9ELfG26Jw4tWc4tvM8M2P4IAG+eUcPaiUu5Pp8hMZWiJajSGI/iSkySMcaamPTeCBfVmKYv0WoqtVy4Y+z8FU8yTLD7E5Jy70VxjiJoTUykYDJSMn7LuVQSc12L4y8lZkNYtkikNxtIUJXLYpl8vzbLoyZl050xyFqxw3clqz5/JmF7uSf8UW0kZ3mIH7hI7t/t0HjAzKGaOn1qfxCHONg7ncg6ymeWUBK6kVmnF2W+QPTEJ2dnj3hCzpBfvw7+ylVDtFiTJiWmaDAwMcGTnQdrb20gyI4sKoshAUYiTxeUM+oLokkJeLYTRbjJSfH/9CqLhLH/c3U86b3BMMTnmFTAlAVEzKT6RIJPIUy6J/CChUqYXmvT7EpGDUp5cNks+lyOfy6Pl8+iGSaPuZEO+CAGBQ0qKnUoSSxIRJAVBkkCUsAQJSxAwLTAtC9MEw7IwXqpZCPTceMk/9Pv+Swl6HRgaaae9baaDxXGRp2SVPXnoUy7hhkdGsaXDeN01+Osa6D/6HABpSWG0OIZDEylJ2JFPI+QyFRXNE0D3FmE6ZgQUE5NJZZIuScZgARcPVtJR4eOhlU40WSRo5PnlggbWlRXTPZHk438+yJGhCLbQI6jBFxANuGxHOUUJlbhT46F1o+RVk6q8ydLJRRQPXYdNL7grTW2QpLuPnN+YxVwaDAapqwvi9d2OrnehRB1UPbWUtvYxbr36eva1LAQgIEt8tqGct5UHkfQsd+9+iB+HS1gadnLumM6yiD7LQqcHJXqkcfZF20lOKz6aKNFVUkkN5bx/zENpTRvCyFf4q0Pgtz4P49OavUOXaRndzKKJ+WR9PWiChEPy8OY3XcvH9r+Hnvwgc/rdrD9aEAi8xSHe9pUbSf7pTsK3346ZTtNffS6djW8kJ2X4a82TxEPbYJoydXFqLtdb1+IJLGK4P8HEQALzZXlDgihQXOWmrN5LaYOXgF1C64jwg1ScP1TLWIJAKGvy9fEM57u7sFs7MEaPs7X/QtrjawCoX2ajZW03qfBhYpl2DsuwU1zDDs4mKcyMyxqrh7OMfayOdVFxqBv38SjmsMKfqi7gnoZNmIKIKIAoCOjma7+aKjqXqG34xCwTpovH8vPwuxx88w0LuXBBGaOj99N+4ksYRhJJclNb8SVSI2sYOB5msD1MPjs7FDBY5aZmOsStvNGPpIgFT2S4ezp87kXofg5iA7POm9DqOZC5iuWOOwkqA5iWSLLoHDyRZxAEC90+F+lNPyBq87O5S2fEELhaDfMmcycnkwMkj3TT+tgI1cMFQShrEznRvICOOXOYJx7jy/rVZEw/HnGca/ofwqnlsCrKSPmqEDF4G/dSzwB77DZ+7fOy3Tnj7l+XzvDOWJzV2VxhxBbVw7yLYd5FBSVOkvlJ/zhf7xpGFuCvS5pY/XcQIbwezFKENlfjPW923YScbnDrs13c+lwnmmHhUiU+ubiKy6YMtNNqVcglDtxrynEuL0W0n2kZy2aH2b//raSyg3xX/DpHrGYa0/08tv/95EWFb9W/F8eyt/Mfc6pxSiKWZXHo0CH27NnDDTfcgKr+9zHw/H8Bt9xyy6liqUuWLOHHP/4xq1cXqFc3bdpEXV0dt99++6nj77rrLr7whS+cKpb63e9+93+sWOrTP7yfeWMBworAh5fKBMcsFnclKZ46hKLtIHWaRTVl1ykpSrHMnsWyOUkIbuKWmynNxVBoDUlzL88U7UIXTVRD5cJjDayL9zHfN0aNK4Y4rSyZyIQnismeyJEctmNaElrzSnxVRWhHDqGPjpBXPJyY+2YmSpYiYNDiO8jaObuxDT2NMM2YlcZOuN/FeIeHGxvfxu6yVgDWjhzlE/v/gtPIcdeWi7n9kqvJqyqiaeAlwlyhg7m0s1Q/Qqk0cKrg70vImwrhRIj8iIvibguhTSAfyyOjoVh5DFFAl8TCpw0cqwVcqyMwTRikxCuJH91C3+B6QKDae5D1n7gIyVnObb+6DWGgCluuBEkRufxji3k8cy/3P/wDVnSYnNfnwzsUndWehLuSvU0Sw3PdzFPXUNtvUTzUizC0r1AWARBsPqTyJag1axB9NbO8RACWnsdMTWDEB9Ej7Wj6SUxtEiFhIqZmSA1eF0QZweZFsis4PEO4QknUEpFPNhaz02PiGGvlvMMqAS2CLkg8WbyZfncdi+RhWqRx7Iiso4Y5uYJXKO8cYWTBr8j6uwjHgqQeC9G0Z5xgejpUTrZzomED/TWr8bhKmStI1CKdkQ1rYTEiRjgs9TEozRjUKo0Ai4xaKsyiv1kQ/R/B6YXWT30XwNIyZM2jDJ33Owzb7GKAUtZPsOcy/IMbEazX9j5YllVQjkQByy4juBUUvw1bQKG65+0oiRNYrW9AeNPtZA2TD7f18fBEgXTg5uJtFE3chKIEKQ19k/6BezDNF5Dl9PS1IRKuJDI8H//kUmqVMmqbatHHJ2C0oLwYcpLhltsZcU6RTK5hdMRJOj0zLyiiTJUWoM4oQXeE+NxSN0Mu6VTwe2U6zoYn7qRqtA9l3RX8bKqadH5GJjCdMtoCP1ZR4X6+yRw/O5ZnThZGMfksabqZ/Y6+HItyEhdkCuvKDpvGdseZxo6/hZ5vX/wPhaX/Swl6HTj46Day9/4HRvMI2fkWnDY/DVvlnMyupPSR4+QmZV5eB+F0mILFlFrEpBok4kuSDZ5gNJRAxUllqpKaZANe7bQKzBZEHCH21dfQGyxjtc/FzxfPoXjicCFe3+4jXzSPm3oq+en+DJJ3D1smtzJnyIWuWDg2reRp4RiDUgd5oTBo7abFinA1lYNvpihToOY11TihhRLNq2qor68/1T/5+AQnbryW2HNJbr/wGh5ZvxlTFFEFeE9ViI/VlODVQY/myPfESB+ZJNcbn9UDbV4LWdqJkjnAC9SRpWBJrvKVUR0Lcn9dJffUOqnJDPOm4XuQU89wt8dObLqeQYmuc11KZMHIcvamLiLs78QSDUqCZVy0aS07/3Q7h8JHeHTtGFjwzdo3EpT24/JUUl1zHYHAWRiRGPt+cA87w1UcLdvG4bJHyNgKL9ncTC1vHb+c3fkGyjfW8O4NDbhtMoZmMjGQYLQ7Nr3FSUVn10UaCkg8uNbNhLvQ1gsmTT59MEnRdF0V0a2gr+gn4nue3sNuBg+eC5aEPdBD5bpbUZzRl35mDGQOWcvYLV/Li2YN+nQvSgJs8rtZ+PyDPNjpZ8hZiKvfPHaE/1xTQv3115FXbETSecLJHPuPneDF/UcIJ3PkkEFxMFcJY89HyYt2DjqX0VJTyn9c3EzQXZi0tLxB7/FjDIz9B5bSBkCsdy1j+9+Cqduxu5RTeT3VrQFcPhuvC/ERePqrZA48zouJN5G3HGz2/hRFzJI37YiCjixBVmtBEXuRhAQaKpct+hIHi85GyQ/jG/sScwezXLvVZGFfYQrKKvDUCuhYrFObXYCWXQzAMnM/N+avYphiahjl8uEHIaejV9WR9RQjkacj9BwHXDPWxnMtD+9z1tDiCIHqgskO6Nk6ixYWu5+tLe/iOu/lmAh8e24V7/wHiBBeDxLbBok9fKYitLc3zOfvOULneIHhZ0OJh09lFYoT04uFAPaWIO615dia/K+6GGQyg+w/8Fay2UEclpvagykua72VYXuIS4wBKkP1/GJqOsfQaeO7NUH6nnuaEycKdUPOP/981q37v7dO0P8b+Gf65uHbvkl4ah39KQnX8ABkD2Nq7aeoeU0EBl0VtDWOMlLZjSCInOV/P2erixja8xTJl2QTy6I2VMKyi9dyz7MfY3m4my2pDM7Tlv3hTJCO/OV0ZDeRs7xU2CZpHnkEDhcIIwSbjaK3vAXX+nVE77mf5DPPEJeKiHvrUPNxHJlJnOIoJTVx/A1pVLfBDqOVT2gfZpwiVFPjfcfu59LRI6g1NahVVRxtWcAtDfPZa5sxFHokkY/UhMiaFo+Nj2KljzPPOs58/SgNYicOaXYInZETmWzzM3kkgJZWiMse4vYK1tjr6KyYg31UxWllKGp+ipI5T4IyXbA7UsXQkSuJjS7CoWTY9I6lOCslfvPr27GNNaLmAuyve5w95YUCzFf6r2XN8KVM7u+gaPgAxZOH8ce6ZkICAVOWEE/LURV9PjxbzsV74YW41qzh7qkE/3a8l7lRk2tTEpckBYzBJBizxa+0ESfOELmWZ8hV7EdIG0hxATEOvmEd+xTo0WqMiRKEXBohn0LIp0B79dIVht3FkfIcGF7ididZlx+r+WqiThkz3Y5diVES6qG4tB+vaxLn5ELKjr0LJVeEhcnDNQluaihnbtzknL4sSybCVOfAZvfPCn9/CVOYDCgCg3aBLsniRS1HOJVHALxCmnnyCNViGHF6KkuZMq3dJ1h14DCCADuvOY9b11/DBAXh2RJgidfJm0uLWGM8yUDPdzDNDJLgoir+ARxtS7DiWiEErOoJvOOrkfP+mT6tayOwuQW2dTD5hzsxh/uIXm+QWTsjwBuananjl5Ls2oTNtGEXBewCuCSBMkXEK82oadPppa8JRegkpH4KQTAZFL/MB5ZsYq9HRLHg+1qeUuW9GCRpCnyRoui5ZI9NkRuMMFH6IlNVzyAGuk9dK5dzMjraxNRkC5WVCyidcsFIhlEpSp84SV44PexQo6bGSeOC9dxnq6X/6BQ3dOf4TYONbSF5um2gWVAkCfxgop1HH9rKwyUXYIgyq2t9bG4pI5eMk45MkYxMsd9h43B9Lbok4tItbjgeJnzkSTJmFsEyURQFX3Ex/pIQ/tJS/CWl2AMlmJJCTjeJHw6T3V0Ix9NavaQanWQ1k4xmFLa8QSank0/EkcKTKPEI9kQMdyaOK5/jm/f+8F9K0Gvhn1lo8v2TdF60hYxk0bmwiscu72GxS6fVZiKdVgQoG1GJdnuJdnmJxjxMqsVMqMVMOVWStc8S94cxBLlguZq2Xsm6wKbAeiYSW9h3xGRd8gCN0hR5fyXIp2nPkkzLnAZa9TZ8x58jbQSpUffjlAqx+y+azfx08jwWTR3ExOKpleOMlQgYgfcw4VhESfgJimIPEVFnJsE5ySIahy6lJrwUEQlZiVE736TlrCY8HT0M/+SnPDJ/HS+u3kKRqVKWNVmqZ1klF6HGNYxoDit/JmFApzpAjwp/ai7hcLCQD7I2eoCvn7wFp2shRuIqHDEfitCD2/E0w/JW7nHDXz1uMtP5FTWmyFXCQtxt5zIRqyGnRkgEjmNhouT8VFLKVPcfAFAdDg5eYLA730GDzeCjJblTXBQ2WxlW8nr+vHOcvZWPk1YLlreqCYtrnzdZnVvOb1Zexp3TVJdBl8qHzmniratrsCuzbVXJSJbR7jgD3VF+k0/yZLmAJQi4MyaX7E0xd1hDEKHIo+K3D2BvuRMzdOTU+amxZoZ3fABDc6Hbs/SuO8rG4j/hIY6qFrN40S/xehcR1nQeGI/yl9Ew+8NJ5M44Ul+hSKxNMXnr5F6ufvYvCIAUDBJ473sYX7KEZ7dvZ2KiEKPscrk466yzGB0d5dChQ6iqyqalizj+1GP4Sss4++oPMNKZpv/4FMOd0YLXSzAobn2IYOvDCIKFaJZTX/0dauesQxD//snFMEyObh1i3wPtrFBuY5GrICxkLD9H1Ms5FKsgYvg4XvY8zaKdT8aOc195HR9v/g9ES2fxoX/nLU8PsaJz2gItWmSb85Q1x6lQNQQKC81TnMV2CrTNK809fEt/M0NmkGo3XDrxF7qUfuxF8wloxWSkDNsrd5DXFjExuBobJfzXNUu4ZNFM3g+5JHQ/CycehZOP0WcqXLjsF0QUH9eNPsoPtBcR5l0Mcy+Eon+e2vrlSGwbIvZwYXHLhRz8zMhw11Rh3AYkkY+bNjZbMgICokvGtbIc15oyZP9rh6plMgPs3/9WsrkhHFlYdiiMPWeyr/UdXBl6J5oFX22qYK7TzifbB3AM9bKh4xAOLY8oipxzzjmsW7cO6RUKLv4t/EsJenX8M33z8299i+xJFSN3BMuciecXXQJFi/xUrTqPefMuJuT18rVdX+WBrgcAeP+i9/PhJR/m4PZtPPH443ilKItpY6HVjkeYoYgelGy0p5bQNyQRzUsIYgC/cjbLGgVa3nEettpa0nv3Mv7Dm8js2/e62mwIAmmbiweWbeQPoY1YiDQJg9ys3EyzLYy14Cq2tbyDm5JedsYKbRGAVpedznSOnGWBZRGaGGZR2x4qJoYJRkaRDROwsPnzuMrSuMsyuCvSqJ5CCIZliqSnVnJrx2bak+UsyUmcm1ERgb4SmbvnqziPDfBvNc9RW/ssllwweulTdQwfvor0RDPNq4upXuviT3f+kTZHP8dKXwRgVd+lLBs+79QzOrwqgfki91vforGtixUdUN0pIOYtcNvwbDkP/yWX41q9GkFVsSyLW/rH+WZ3IeztjaVF3NRcjSqKWJpBrjdOtiNKriOCNjK7voQp5ojZukh6jqM3HiDvHgIBPAmNQFRhz7NlFKl55vvGqFBjGDkJIyui5VSy4gKSQ05y3Z1gzl7LDdWBWjwHrd5GcvEIyZYeXip6KCBT4rmQYu1ShD0B9JHXzidLGWnkyU4I92BE+0klR3kiNIeHGtYzb34Lm7IQ78hgzcnyvXof+RTYYhnKB4epFWM0ypFTtYjErMbSI4eo7uvjV+e8h8GNZxEJqHSi05wO807hVsodBwFwhlsoO/qeU3V8dEeciUV/xjZaTVHfBQjTRcXz9kn6Vn8F05ZE6QH1hEhmpYUZLDyvZQkIgoWp2Uhsux53Mosv5Ma//GpcgynoisJ0RIZS4cKzqRr7/CDkTYx4DiORx4jnMac/X/rbiOdxJ3+OR7yLSTnI+lW/RRfcfP9AhurS24hVP4ctXkvti18+1VYAtdqDvTUIjQmG0/cwMvpXTDN+qq3hcCUjI3OIhCt4qXC6asnUUUxR1VHkuscRp8kcDrOIP/F2BoV6TEAyLd7cr/GBjMI3WlSeQKMkrJHZN45uQn2ql8sS2xC0HKY+E960qGgjzoq1fHWBg8NFhTUiNDJO9eE+Bu1+0qqPoCSjayapnE5Gmz3ebHqes9IWy0w/AJPJdqToYQLZOMFMrPCZjeMwzswXMhCo270bt/fvj874lxL0OhAdG+V3n/wgeSPP46vHGA3mqB5zcN7hII7GHKHaKTzVKcTTFKKxRAk746vYnVvEhDqMT9qGrs8wpwVjKs1DPt59xRf54UEB/dBzLI0dQrU0Bmo388CmjdiNJC0TQyybHEVLn1aPwBSx5YIUaSGubHyC4tRz9I9r3DswHxB4vmQZHQt2IzmGkC2Lz04lOd8IMBmHbXmD5ypVjvpyuA0XJVoR9ZlSWiMrqUvOIaDr+LQYlqsIVXbMyuN5NYguhbgnw2O55xk24jjybgQEDEHgcFUD+2vnoUkqiqnxkYE/8rG+P2IzBfqVPLf5fTzkdqELL9Wn8ZHyXo5incNlO1IEkiZiSZRx+SiWZVJk9yL2LEQUJPKpR2lZH6L27BzHh//AN0ckNEvg0/M2sCYQYnjkfl4YcvFYQiRuL7jXS3Dztt5zWPfCENbgnoI/WRSJbTif74bWs3+auabCZ+fjW+Zw1bIq5NOqUx9OpPlYWz/tqYK18SKni3cmFNLdCUa742TTkxQveAB/w/MIoollSMS6N5CdWMBJWyOP1pZx4b40pTEDRI2yZX/EFeohfPjTGLkShGkKS0GAfjPOvfokY2aB9lGvdKLP84EiEkpkuGDns1y47XEqJsfJ2rx01W9iuGYlvqIgPr+PiXwnQ5njYIF9dAwlOhOeJsiVqO4rEYSCV8cTsFM9P0BtaxB3RRcdnZ8hmxtGECTq6z9OXe0HEITXL/wOtIXZ9pcO9PEeLvB9j1K1kLO2N/kGdiffivWyYIj9lU9S7/fwm+Yt+MJhvv/nGylvGwUEECx8dWlKFiRRXAYoTgi1QtkCKF2AFZrPE8en2Lm7IISttnbxrfybGbBKkNUotuqfY5OSbBrehFf3UhTwcu317+Fz97Xz3IkJHHKGT2yUuaQlg8NZTTBw1ql2pTSNy3Yf4XheZGm6m3v3vh/76YQQofmFkLl5F0PFUvg7SRJ0wySrm2TyBtnTLF4T+0Z54cUBHkAjPG1JvgSFD2PHi4CgiMhlLuxzi1DLXcilTuSAA+HltVimkcn0s3/P1WT1KRxpg2WHY9g9jXDBt2Du+dw2OMF/dgwhCfDHlmqGn3+GE8eOATDp8jK4fB3fXb2Eua7/u3OC/t/AP9M3t9z2K3JP3AeAJsmcbFzAoZYV5EodzBeO0spR5gvtNPibCAY2cc/YCL9uuxOAy2vO4ytKFfLhuxDGj5+6Zho7bcYC+s2LGZ5aAgiYxiTZ1F2IRgZLsjF3HOYMHse1bi3+a67BvXkz6d27Gf/hD8kdb0N0u1GqqkAUyQ8O8EzTfB5Zfw4jgRIWn7DRlswyMs0md4U1zNdW9OMZfZQnCHFTzfUc9LYAIFsmC7NRQh3H8fZ34Eol2LVsI21zCt5fXzzCec/fT/1gJ7pk4a+ooDhYjiCIZFMpJvt7cJROUL02h+KbYZcKTy0kefh80hPz6HRkiazbTX+wiRNTTcj7wyyRUny2/mlyNVuxpIKglx6bx8TRK8nFG3mm7g7ai/cCsL7nKhaObqC4RqZ2aRRv5SBxYz+Dky9QJJ0WA58HeVxAL7OQbG6qqt5GdfU7kZUgX+wY4tdDBSrpD1SX8KXGCsSXWbUty2J8/GG6jt2MPFKCa3I+7sgypKxz1nF5KUa25AiC4xD+3F5C0Qmk0+ypaVsFzvM/B61XkBsTmfpLO/tOPMjE6E4CqSw+PUMglkE9remC6kYI1UBNI6qvFVmpRhBfOSzWArpdAk+XK/T4Bfa6ZSI2kbekO/jEtrvQXjhJfnImquJAyRweqV+P5FtIpalQ5dnOnfNbOOmqA6AxPs57a6sY7ekmPdSOYBQaJuU0igbG6XYtw1fURI2/k3zdYxhyBsGU8A2eg318BUMeGavMSWlFF8nJZ/F1nYuaLXjyM64+ksUH0F0RdDWCOV1zBssiYI9S5p5AZT72X9jJbD6A1mRizxos6VhJxv9Fsu2xU6SptgYfnk3V2Oa8uif+ldAbj8LPzqYu3c+9ZRdTsfx71KZOcsx4HwgWDf3fxDHZhBy0Y28N4mgJIHlnojHS6TTt7Ufp7b0HhOfx+Wbyh7JZF6OjTYyNNpHPO7FZCtVmEMXlYrLlWcY8In/hrUSFQh3EFcog/2n4qHlWwsoaoIj8vFzk9/0F+Wl1tYv5e2/HlS6M1bwgE7OFOCewhfm2giHxdivNz+tsaHN8hVAW3aToyAg17X0Es3GC2WmFJlP4XpyNE8jGcU97KXtqL6Kn/lIA5p78M1XD287os5yskHM4MbwexEAAW1kpLV//Knb/K9dzfC38Swl6HeifjPOHz3+E3qJRdiwYQdRF1uxcTWNiFAmTjGJn2znn46lOccXEXZSFxmcpRCOawMG0THtKQBx2M7/Tjz+hUPzmC9i106SmfzsOM4uFwOGN1/PkvAJzWXnc4OptCXxJA11OkrNPkHNMYEozE4iaDZCxMrgHdiIbOsmqEEOlTeyKNFFS8hwVtglK9CLWJoIsyQQRraLpzY+I8kqPOwtZERJCFk2Lgm8SNdSBZp8iiZfJ7GrSok4mEkOMW0wICbTpsLu6ujo8Hg/HjxzAa4/w25Y1DHsLuUQN6QG+0/EDVsQOcLfHzW98HurKV3Kp51q2HS/mnjqZnCqi6hbvmxhFP1kIt3Dm0ojdbcj21SiOtfhqDlBz1r1o08rlVq2Je0eHKXeV85mVn+HmPTfTkyqEFjkNBxcG4qzzaKiGnWLHeZQ5N5H99ZMkn36m8LCyzMQ5l/AN/2pOaoUJvqHYxafOn8uW1lJuHhjnR31j6BYEFZnvzK3i0pAfANPMMTD4O3q6f4JhFsKt8pGVDO2+kli6lCeXODnYUJi43ph8mNUHVZJDBapnRA1OqzmUx2KHM86e6dyLMsJcls0S9c7jcJ2NtiqVvDIzyc7v6uTCnc+yaf+LSKad3rqL6K1uIB48CQLYRvtRI+MYgkqXu5WG5HFkK09eKUNdcQNXX7GQmjrfrIlb0+KcOPFFxsYfAgp1D+a3/hd2e8WrjhVDN+k9OsXuB7sJD6Wote1li+9H2MUkWdPNU9FP0JdfTk5KM+bpRbB3UpfzYETOwRTg0ZVxNu58iku2P3uK0MJTk6VkSz22FeeeUnooqj9D2bAsi8cff5wXX3wRsFhvvcg382+i1ypDVuNcEHyGmoOjyPMqcfhSlIZy1NU7GQu3YRNn17GoqX43jY2fI6dbfLi9n0em4hRJErfWVFAc78XV+yT+gafxT+5DtGasWUklSId/Pcfc6zlmX0rcUMjmjVnu/Oys7yZ5429X065E4LM4WIJEVACXBfZXMk5IAkqJA7nUhRJyopQ6kUNO8sYhDhx9NzkphzOts6zdxLb+87DyvSCrp/rvw2393DMWwaXluGrPM7j0PKGlK7jZV0XYtLCJAj9qruHK0v++heb/j/hn+qZzpI9Hv/lRhv2tHK9poas0xKSnBITZeQrl1hDzOcIS4wDq5El+ndMxBFiTyfDDsUncooLRcC4v9FVwaGg1klHw4FtYZINjPFJ+Byl5mAt3l+NNSViihFcqYc3BXSi6jhQI4HvDlfiuugrZ5yP24IOEf3M72tgYv7zyWv50wRUAvD0j8uDzA2QAmwWXRVJceei37G6u4M+XXEV/SYGdzW5kedvIQ3xw8M+EMlOcjBdzOFrGcMYLgsjIwlXcv3QDCUfBQNQ0eIQr972AMDJ0Rh8VV9Sy0X8NmtpLuPFxEsE9p1g2p6JV3N13LnvHl3DlAoNPXX4Bvzo0zO0Pn0Ax4fv0UtV8iGj1cyAaGBb8bijEISuJYAmck6/kLNmP0z+EzXcmxTeArJYT8C/F612ELLkZGPwtqVSBrVIUbbTbLuAnmYuYFEJ8tamC91eHzrhGMnmCEye/SjRaWAvt9mrmzvkCweBmjPEM2Y5IwVPUFQZj9tygCN2I6kGSxcfoNkY5frSMVXOqmbfw84Sf62Xn+P2MZnpwFGcpX2vD5QnjTZXjHKzDMVWHqtchTdNjvxxmNoqlZRAkFcHuRxAFRu0S32mxnwqrCuWm+En7N1gVbqczu5629Gby41A1tJXg1JFT9egmHD5GnQFEy0KgwNIqYBb+tixELExRYLKqlNH6avLTbLuirlPeN0RlVx/OTLZwLtPnTF/rpWuc2s/M36df/6VPgIykEqmvZPEVb8TWWE/+wXfRt3whrqHLcEVaT/WBfX4Qz8YqbDV//7x2JJHmukPd1E8e4P6DH0XEwnrrX9mfuI1odDeloUtZsOBHZ5yXSCRob2/n+PHj9Pb2crp4XlYGTXOGkaQ9M94hUyASrmZ4pIlIpIIxT4DtTYsY9xbm8lJrirdZP2epsA8BcBhNVLZ9GGm48P+96Hw9ZDFa78K+e5TyzBiC00eVZOOTmpsKbBiWSXvqCNlIG55UhLAkcuslV3K8vgmA5W1H+PQdv6AsPHu9PR2GIJBRZHrrL2O8/FwAatlFVVUeZ20dvjlz8M1rxl70yuPxH8G/lKDXgdHRKX748x/wdNXjyJrO2fvmUhYvuH97Sxp45PyrSHkKk7GaHeEDf/0xZWVJbK1hikuznE7RngnbiPR6edCZo82ls6K9jEWDSzCLWnhw3QJOlCiUxA1Wn8iysC8/7X2eiS61sNCVBDjHUWxJPLpCUTiOS3DisAVwOIpxWXYc/O3kZQuLNDly+UmkeJhDlWXsqq9m1C4wrhp4J4c4+7CHEsYR3G302UQCpX3MnbsDERGx+zz8vRdSMu2+1DHIhgSCS4sJOA9j7f8rjG1FJo8BvKXhEraVvxdTLrxYV489wZe7fkLASNErXswLw5eQNEtIBxSeOLcIYbiddV1HAVAiE9hG+3AXBVh77YWMxe9Cch8GwGarZN7cL+Lyr+eK+69gNDXjcVN1B+vDF/C+5EKMij3Ea7aTt81YSpzOBkpj6xH/2ElmV8GTIDgcDGy6lK+6ljGoK5huGWlZMRlHwXtxaYmPG+dWU6zKWJbFxMQTdHbdSCZTKKzndrfS0Pjv9MuLeSGc4LbBCcZ1A8ky+JrtD9Tl7seyBNJdn2Zg/1wASqrdrLq8kUPhBDdubWMkXRCOr1V38t4tF6EUN4MF4+MT7DlymJ2WSVtFKQNB/ylqdEXTOOvQHs5/cRvNA120t7Qy7HMgjY9yxLeQvd4l5CQbJbkJ3jD2EDYjy7hazFM1V/K2Ta285+x6PPbTaVstRkfv5cTJr2AYKWTZS3PztygNXQRAKpY7lS810hllvC9eKCuDwWr3n1ju/isAQ0YtPxMu4IQ3Rnm9j3XzV7IZByVPfBnCXZyIrmP76ByWHXsOm1aw8smlTZQv7sUd6AdBgi1fhnUfm1Vz63R0R7v5zdHf0Lenj8Z4LQ5HjOXOPWy3N+J0J6nxjhKwTbza6YSzfuKpYuqCBY/ViyMr+EXifeTmBcG0UPdMIkZnu+F9JNkkHuQ8aT8bxUN4hNPqSFgqL5gLecpcxjPGUibwv/KNXwMO4CpULkThETQeRiOGhSQIzCtystBtZ4Eg05q1KJ3KwcuJPMgiu39Px/Jt5GwizrTOwpGzEZd8AaW2BjloR5j2cuZyOR584km+KHiJuLzUpGL8ZXEDddXVjOY0Ptnez85okidWzPuHvEH/UoJeHf9M39z10L/T91AnuuHAVEWOV84lbReYcNuJeYvI+apJ2bycFTnA1WNPcPHkNpxmlm0OO/8WKiYjitSJMh/1vpfJg4uJjLxkYDPJqkOkvCOYchZJEjgWaKNTbWfzvhJKIzYsQcCoaGTJwDDVR46cUstFpxMzXVgf77jmbdy2+RLQTdaN6Ow/XvDGNDoMNg4fpbvCyYuLFxL1FcKV1HyWpUd3sf7oVlbYelgQGCekJk89b0oJcYK5PNdrkEs7eWHluexfuBZLFLFn05yz81HOTkxQ1jiH0tpGisQQ8k4dURfQgg52pQ3i8R4C8x7H37ANQZwWwDMBnuw7h474Jt7X3EhHV4TfTkwhWgafCe/m7LImEk3PcbN9N0eyEiIWbwvmWeacHdKjZ310GXk6dR3RVs9nzrqFUm/jrGMsy2Ry8mk6e28lnSisYQYipu9Czmr+GG7XTNV7XU/Q3fMjBgd/h2UZiKKN2toPUlvzXiRp+j2M9MGRv8ChO7Eme8mZreTMJWTNpWhW06x7m2KeTNEJwkIHkXGRyUSE4gqLkK8Ed74aW6IWJffKRg7RHEJI96KH+8kOD6JPDYE2EwZnKHbuvfg6fn3uuWQUCdm0uKE7zzVdWbpyeSayAoZVmG9E0aK2UaS5UcN5fBcT9zyEnIy/4n1fCaYg0F9TQ3tzM7EiPwCCaVLb10dzWzu++Ou/1uuFoNiQgs1IJc2IJY3oiyxq3nAVaqnrb5/8CnghkuAdR3pIGibz3XYeHLsN595fMFZTwdG6PKJoZ83qJzBzxRzojRB0m0TGe2lra2NgYDbpUGlpKS0tLbS0tBAKhRAEAcPIMT7xKP0DfyCZ2A9AhCLuMN/Fi1Ihr1PRNZb3nWDhUDdFHjulpWmczl243F28MLyKZNv1fAgHdgSSEvyyKkfFnge4uPMwombHsfKDiM4AZi5JdtetGOHOWe0yBIF7zrmQX11xLXlVxZHN8JZH7mL9gR0kHA7SRQFKqqsINjTgbWzEW1OLv6wcl6+IHX/t5tAzAyDAlne0Mm912Rl9qOs6mUyGXC5HcfE/lqf7LyXodeDue/fw877v4k4OsPp4AMUQ0SWZZ9ZfzKHmFchaN8XZI4x6LwNBpnzgdq57pAPJEpjTHGdxyUmOeotRyzOz6ioM5wWOJ9xk+95AzDyXYMKkIqyjnjav2gXwSAIeWcMlW3gkAZ+goPK3+dA1wWBKMOgVUoTdbUyok8SlHIsci3GoLpxdh/E9/wL3rN7EnVsuJT/tebAnt+GM3YVkRHDkXbSMr6d1bD3VZoK5rudxOMtwGWtOJRUalk7WTOKS/KffHbt4EFV8gWc9bfyyyEafzcAUHKT8V5N1bwFBxKul+HL3T7hu9BEsS2IyeCm+N/4nzx/rYcfOnQAoU6PIkyOUbtnC2vVxhkZ+j2VpWIbCVPsFeG3Xc+F7lyMIAo/3Ps6nt34axVRZMLyBs6fO41zZjSoKuNdV4L2wjlhqHyMjdzE2/iimWRBcBUGieHgxjnsS6McKNMGG18ct7/wE982dB6IAeZPmSZ3vrmtkVX2QeOIoHR3fOmWdQy6m3/8+HjXOYk88R2bamyFaBvMcAl9WfowRL7h2mxo/R03Ne+k5NMlTvzmOljPQ7SJ3KGkmJIsqYZzvFD/O+vd8H3xVjIyM8Oyzz3Ly5MnCNUURT9Vc9ovVvKCZZMvsWO4ZBaYoFuXcPdtZdXAfW/0LeaZqBTXFbjY3h/jtjl6KclO8aeJh5HyKSSXA/WWXoXp9vH9DIzesq8WpzoyvdLqXo8c+SWJ6wTbjWxjZ9yYSE2dqFE4xwrn+71GjFggW7vIG2bP4Ms6p2Mxa/2KcOTBSKcxkCjMeIbvzaSbuewohXfgdhkJNTNReztxFSymbilBkvxUn05665kvhip+cqlNjmjoHhh7niY7bmYodoUwxKVdMQjKnmKxeDst0kxgXSOgVpNN+goEyLr/iSzzxwCh9Tw/hq32RspW3I4omR83F/FD8DJzI4x3L4lAlHIqEXZFOfXcoEnZVwi2ZtOQPsyCxnbmxF/DmZhcNjgYWE60+l2Td+UzY69nXH2Vn9xQH+2MYp02tpV4bGwMeVvWmWOCI4N5czXBZkEPDJvsH4uzvjzAWz738sQi6VBaXeVnsc7JQklg8+TRq/MccWqCRs0k4UzLVez8KucUzJ4kCcrGDcW+Spyb2EM8liTrc3LtyMzlB5EPVIb7UVIFpmowd3crk7t/ScsMvkJX/u9nh/qfxz/TNzT/8PlOxJIKWR8znELUsQj6HmM9SJkyywDFAs3cctzyjwHc7Krk7dD7/D3tvHWXXed1/fw5exmFGjWDEkiVZlgyyLDMlThxyEjvQukmT/tI05dRp2jRNmjZtoOGGEzOjJFsyCCzmYeaZO5fxwPP+cccCS4bUb9e7+nuz15o10p1zDzznnOfZ372/+7vvCy8im/g5sh0HgtTFb6Zt1GKBmKK+qQRhOeg+foy06kToDoSiYGmCU4FuqoYz1E0XaVi5ijpKGlq5qH8A9/btIARqfT2PffQTPJwr4JmMMpWoICpcIAQrE4dxVsG+5RtI+oIAOHMZVh0/xPrDe5g33INiCyxZJu1z4a6WaPEMMd8/jSYX51TTluhJlnJKzGNkwY38umUl/WoRFFycl/irLoOq8expqlKm2sPLwwmySRvFkaB2w3coqRP4/SuZntqOZccASBtu9o6vxIrWUu2ZRisZoME3jCzg5yPVHFOnUJH4aEmOxXMAKB+vYnJoGZnB9ZCpIuacZOqq/fzTli/j1s6lqr1mY7kC7z/Si5Lez7ukh1kozjTWLS3dTEP9H5DJ9tHT8zUMo1jrVVZ2NfNa/6rYwiAbhROPwNH7YGjX+QdQHLD+M1jL/4jxw7tIHj2KN7IIySw5f9vXmcAmZ04x4BjixZIhBvVB7hjqp0EG1e1FcwdQnF6kSAp7MIIxHOOwo4V/ee8n6alrBGBJXzd/eSxNm7MIAOO5NPuzEigaDbpMrVvBV+1Fr/Gi1/hQyjSMvqNMHe7g+Cvj5KQQsmzTFkiie5KYjjimM0bBFSPvjiHpcZAEApgtVDGQaidWOOMkl7pHqfd1Ux9tIjhyJRIaQmTIDjxJaqKHV5ZcxPMXrWewqhZSJtJkjoapAv9guQig0OlX+Lp7lvb9R1g608OymT5c5usEN7wCbXkr5Vd+EPfadehNjW+bBvf4VIxPnRykIATrg15+uqQJRyoBP7qE/Ysy5JwK6bFb6Du6lpyIYehxLO3cWrCamprTwKek5Pz7agnBr8YifLV/nPZIH83WOL8NLicvFd+Ty8QLvCeyj9xwNf1xH9ZZa2anXcHuQlE4qxGLL5kOWtTis2yMHcIcP4Rz2QeQVCdmcpzpQz8gbUbJayo5TSGnqhguB1pFJa66WpJN8/lhxXw69GK5QdNEnot6Czy/2E08oPCp6jB3lvkQhTzZbJZsNksmk6FnZ4pItw2SwLcoge2Ln/57Pp9AVWdxu+PoDoOPf+xXvxdGeDN7JwvNL575Ffuf/DH1U8WHwHJ5yFY30VvhYcC3l6hSdJozvutIh96PZlt8M9nFwG9+BQicqkrOtFCcbsLzWwjUn8JTcRJJmUM7AszphYihDcjTi/BaHsJKAbesI0sXdjgsBElyGLkZMmaKuNtJUs+TknLIfgcXb9lAVU0pv/nrP6Unq7O9ZRWF6t8g6zEaZxx8aX8dO5wV/Pim24nM8SjXBjz8fWs1Ndk+Hjz5S+4b28mUOVeYKmRWxpfxnthlLM3OQ0LClmcZL9/HlDxNYERDNv0Ydi2mqMHEx6BjnE7nACklWyziFjIldgl1pQ28YPRzeN5y4nOL4PJ4L9/s+nsWZAawkTnKfF5iDeloFYJK0hUumtR+HBQdQKejGoeymKETORBQ3ugjXFWMyBwdO4E1qhO2fWz0qrg9GuHb2nC1nztRmGaSyamnGB9/gHj84Ol74TnlJ7a7ka9u/iAdjcVI2uLJKUZPFcjmJYKOOH+4aiut3peQEJjoPMnNPMrN5KUzssvrMt04jDR9jgr+dvZHlAQPUPC4WbToG6ezKQBPvzLEkd904zMlCggy3v38ycJdeD7wM6ZTBjt27ODEXH0GSEzplbyYLCMlivS60vwMG1MHUBx5jqzeRHdVIzn9DGe4eWSQzV0nuWPjGnxL29nWFeVvnuojVIhyR/QpRCZByhnivrIbSKteSr0O7l5Tz3qPk2jPFJGeKWIjU/gXb8WzfA+SBFbUR+GJtUjjLlSzgGrmcDFGBd0oBpimTEHxo5gqdjoN1vkCGmdbV10jJz94J+2xVoY7YgC0lTqZbxj4vFtx6D8g47JJlZaRalvHZH4AKzd8To+Ts00IJ4mEj0wmRK2Z41eT69iTWoZDcvG1y0vYf+8PyFQ0ARINUi2ZiaLcqy6n0cr7qVn/n8hqgVS2ibVLfkxl/e8ggCAETJ4oCit0PoUYPcgJ0chz1iq22qs4JRrP2byt3MsV892sqUrim9mDkXiJgn8IWz130RWWGwkP4MMQHpKmi6mszmhSI1VwkjFdBM0Mt4pXaFbH6GpxY+oKmGHKfT+ioRDGnMpiTGUwJzMYhQL71T6OK0MggVc4udRYyMnycv5iWfE5/uzAQd49/D3a7KI63PilX6dq0yff/ljM2e9B0BvbOxmb5x97ihcPvnr6/36SLKGDZZyinDNCCRnh5LjRyMlMDYNmCZOBMgYr6umtCSHlfoxqjmNLbhJln8VW51EzOUz9aB/1o71UTo+epqe+kQlZxtYcuD1efLrGTDSCyOc56lvMK+GLsWQVt5Wh3j9J16oVZObaQqhmgYbRSa7Z24svNY5tTSKsCKfRy1nmE3nqSydoL4lQp5xxCE2qiZlX84O6m/l+S5C8IqFagsVxi5wuU9BklNk8/rQgZMVpbnyORtcitIFV5LoGcbg6CDS9grusC/nsPhZzlrPh+9NO+gsymi3xN8MfZ5lUQaTlYZKV+4rXb0vEhlcxffI67GQd2bBG7cfnc1VtmJK5gJJl2CRnc4y74YPH+hnLG1ToKr9e1kKd3c3A4PeYnn72vOO7XE3Mb/s7SgJrofs5OPpb6Hr2XAXL0ybByg/DFX8FvjOgYHp6G0ePfYbOvquYsa+nLeFlVdRCs2HAI2HSS26ki0hmhlhhClMY2Ai2rplivDRHKKFx/a4q1Nf1X8prDl5es5mDi9eCJOPOZvnQM89x646ncBYSaA0bcCx+L5LmRJh5sgPPIxlZtJIFKOEWJLW4TuXdY6RKj2J4xim4p0i5JpFd0QvSC19vDr0a50Gb6CmbPtcSxv1VvMacKbcDLDMbqBobJhM5QODW66l43428nDX46dAMz8eSnNZMswWtEYPvHSsQNAQmgqNY/DUZ0rbF4tQ41/unWd9/HOXYEV6nzI5aVoZ73To8a9fgXrcOvbaWC9lPhqb4694xBLCuoPDhbov4aIJ4KkLN4t8QnneAQs7Fvv23YNtnBbsFaIUAjnwppaE61m2eT+vqclTt/FrdnbMJvtgzSme66C8pwGsr8MJsjNu897LAfO7MuWfKYXQ1PbMtPJH1cmiuyW27Ms5qdYRQLM7qbCUNwTVIZzVU3xeS+Pp8E7dsUq1I1OkKdU4H1R4XFU4HTsskPwda0tksT9kajzhCmLKMZpqs7zlF22QfygXe9+I125SY5fg0C803gVR6Cod3Gpc7gcNxJgtp2zKXXXoUXXddeD9vYr8HQW/Dth54isPf+A7YsL90AWqVYJ5R3EdOznEydIJmq4KrYhv4j0XtHCnTqJ/NcPvjz6HYJrJSiaRWISuh05mdgGYQ8kXxqwJXIYRiXjhiZCFISBmiUpIRfYaD4Tj9wRF8g30sOS4jSRILNn6SvmMucq4J0r5BhFycyF22iTTYRUVZGTf+7Vf5ykOvUPXMPVRkq/n+u++gu77YSLLBofG3rTVcX3ZuXUjByPPsrsf4be99HFU6kIREOFNNe2QVTZHluHJBOE/t/+2bLcGr8xzsWOzG0CRk2+ZDQ89wz/A3cdt5bCHRk7uEA+n3MGvW/077liS41KtQ3hwk/P75b6mclU73Mj7+ACPjj/CYsY77eT+GpOPJpfnMb37KVa++TKG6lH0fqqWm4QgOqTi5vMyl3MsHmZVKqdQ1Lg56WG+McGj4FI955uMhjY1EQoT48Ym/ZZ2RxAzdBv4GkoqTrw8pPDZu47ThPRmoNIsv8aI1HqaVbjp6urBlCSSJPivMYbOGhHAiSbC+xGJ15FXsvsMIIFvbiuULkhEqW8vW4ptXSr8qMORiH5/VAx2sHupEkmWqMwqJQ92ECklac6Mo+TwqEpJwopsFNDN3Tr3La5afZxP9qIkdAizwPabg3Sa/vT4VkoTsdiN7vcUfj4cu1cFPVq6nd90lbFuzAIcV4cC2nQx1H8LhH8MTGkP3jZ1Wanq9FWzIK2GqwhdRGVqJ19OGxzMPTSvniSee4NChQ0iSxFXVSb7c18Qp0UiJmuM7V/rpfeonTBZuxZEvptHX+/6Led5tfKrieyyMzrJi2TdRnSkKyTKsU3eybFULtRsuQpqrQ3gzK5g2e/sjbD05ybYTY4wlzjhXMjaLPD2sDh+lvaKDcGjqrbVU36FZtkzOcmHjRdX8OGQ3yWiaTAZMU6dEq6TaqiUWzzNp5Hm0qo2dFWvxmmmeOvRJ2jIj9BdWolzyJ9Rff/PvfPzfg6A3tncyNq/sHuSrfb3cMvkCV6S202SdPO04mih0iGaOSQvpoRHrQnO1kEhogj2VL5PUJgEZ1fF+Uv6NpJwuhCSjmQVqpwdoGO6jbriP8sgkkm296SOblR1sK9vEgLsRgGBIYmZpOeZc3ypnLsPSU/u4+OCL6Mb577Ykeyj1VlNW0AkWZIKSH3egEdlXhSQraFIPHuUZ3MpODNnkgH8RL4VWs7V0MyfcVYjfISLsF3HCzFDKNMs5wHIOEaLYEFYIOJl1sy1pMZBxcs2+MLXxAKvKP0qDK0jOO8R0671kyotBKmHLRAfWM3vyBoYc5fz6Mh+XmxqrR0zUzgRm1mImoPD8Yhf2PC+/Xt5KnbMY6CwUZuno/CLT00+fc34+RxONiVLKju5Byp5pVIunHHKxM2Co7VrYfA+ULzjn+0IInuwd4J4TvYz4i3OdL5/k08O/5nBwMU+XFhsi/+HQvdzR9SRDuTL6kmHSeUhKWR5ZP0zOYbNg0Mu6E8VAogC6GxeyfcMNpLzF+XBxf4YtR/J48kX1PmfiKIHZ3ZTl49S1vge9dD4A5tRJsod+Sr40RnKNm8IyA0rPzXK8ZrbhwEiV4vPU4vPWY8mTRHOvIGGRsry8NHMbl8wux9s9RemOH+DMJcks20znvEX0KJPYc+9CSFFYVVHBAq8X2bQQlgWWSTpf4FQ8xYlYkmiugGqZlORMNo3ncahuCnWLebzFyfeTQaysQCgSxrIwdWGF2w99i0smd6N3KWj9Gopxbm+bTEUlswuWMlvXTjQ8n3zBw8s+m5eadTz5LOu6JlkyPI2pJTC1FLozxerVj6IoFqdObWR2uo5ZV4hseSV19fUMFDxwLMPiwTza3NJccMoMLfTQMd/NjEMiYVokTevCXXmE4FPdeT7Sb/B8hcp3lk2yia1s4EXcFAGFbSvsn1rKzpFLKO/Ls1odYbak5DQNPWx7ucxcTIntYZ87wjb3IJpVwGEYOMwCb0cWKObysGP+SibmKLA10Smu7N1LuTKJ6k3j96Uo8aZx6lEUdRZJMt9wX6oaQpXqkEU9F63/B1T1d2+s+3sQ9DYsY2T427+/m96qYXo9RU5zSa6EldOr8ZteEODISLgTrdhKFRG/Ql3SIiRJRSqbLOFXiuBHe4PJ2cYm45zC9o9Q8I4SdY3RrY9z0ErQVZCYpgCSwJ1VWDjoo73Pj4zEkcVpNr/rTtYZV7Hzp13k8nkynmGyntHTMtwLWlu52DTpve9BvnvVTby8vCgnLFsZmgsneHLzBwnoZ0CYlTZIvzpBcvcokdk8M6ZgRGSJmRKKdW5mypYsTDlPxt2P5BhnVJMxkBAIdASVhkx5wo/XqMKnlOFQHOcsnrN6nBOeGbbPq6Wvutg1O5RN8He9P+d9kftPbzesN9JR8j7uF5cxaxabma31ulkva/QcjZBKGhgI9jtMchJ0aRYOl8IHNjTy/rUNVAbeuo6hL5PnM6cG2T9X77VUHOIT1nep2RNFGZVIb7ERweK2sWyIl5SN5HMawUKMhZ4cda4EMWMGS83hlZJoZ2JMnGAxj9vvYs1eDysmpjlhazzoKiOhqkhCcLU9zPusk0zGFzGjFRcLb3KI+qGtaEYaGwsLgaYKbLfCsF9mQjmz//GaxXj9TmwhUSMFud5r43DpJNwennYFODk+Qnn8TGR4LFDCzpZlLOrvpr2vm8W9nSwY7D1dk3O2FVSVnFMipRkI2YfDUYJx6zSivbggu8Y0mrYlcRRs5Oa1yJd8HCVYguzxzIGdIuCR3S6kswQN7h3u5rHuB6lnkC2eaeR8H6YZv+C9sW2ZiCFTnsrSnCjgSVuMBtqouvlXVAQb3+A7No899hiHDx9GkiSubg/x5QMKJ0QjVXaKP8qkSZiNCGySgVOsLn+Ve1f9EU8IF6VWip8f+Wdm24aQPCnMnI/hFz+LJwXLqg7SttSD2ry22EjVV4ltF5iJD7P95CDbO+PsHlBIF844nbqcZ3FpB8vLjrG07AQ+/cKLPgKUfAi3ezHh2iUMDf8IIQrIUhCv9EnyiVoyyQjZdIxcNoYtkihaBlnPoGhZZD1d/K1lUPQMipY5k3H+HcxE4SvcQ6e0iFoxyD3W36AVNILWn7P2ptt/5/39HgS9sb0jqvavv8Z1Pf+C2z4DJPZ4FvOg43KeMtaSimtoBRsdgYZAxUbBQpJMFMlEwS5+JhdIVD5F1lcs2C+bWUdpbDmWplHQdXJOnazDSdblJKer+DMJynNJ6mKTVEz045oeRQKSXj/PLr6WidkwwgAksOb5MBp9IEmEo9OsPfQiC3uOnM4uOb0+ymuaCAdrceZLUGZ8lMgeXMqFXSqzkOaUMsurIZv9VT6O1laSV8/tXRYopMkqOvPkkzTRh0tkMSSNCKXMUkKEUiKUYEgX6HkmBG10cIN4gFXS4dMfdxv1vBTfTHw8gDedoZkVrMVJbV7C4+hidN4jUFIEQ7alEu/byGTndZAJntk1Z+Id4Tov629uoW5RgLGx39Lb96+n579q5zqkTIRxurHnhsGdNmmccVChtiOPH4U5hS6qV8BVX4amjeddyt7pWf7qwAlOOIrOoVbIc9nENt5T8Vvc+FhT/kd8d9ri3/UiTXZzZBf/eerL+Ox8cW6bfy37AuXctf/LAHxxwZ9Rpy3mn+MWu+eElUJJi+sOpGmeNJHkHIrUh2l0YOSyCNuHR/ehK34a1Eqq6vJkKg+RLN+P6T6rQN4ER6eENiijToM6LaFMScgpkJAww4LYR0wK84puqPOIROBXKkrqjDchuUtxrvwoammxzjYxc5Rjmb30NNZizFH9XZkMbZ1dtPT2oplvryHnQFUNT665jKf9q7CSRQqeOT+A1eChnEneLe6lNTnMKyfeTXtnH/MHTlE13Y8sis+3LUlEQyEG65roa6gj53GhifNhSuvCXVSV9TKaq6f9YJalZhc/qH0PX265+5ztXHmbFX15VvfkCczVDlsSnKzTebXNyVjJ60olhMBp5PEm4yyIG/xLtx8Vif8sHeeQHsFtpVjg66CtpJuawBlhEWUS3K+6cNa+h8SqyxmdnqK/t5d8No9XOEjK5zIVXjNLliloOhlVJ6fq5DWNvKpT0GRcziQ+ZxS/PsuAo57d6gZMScMpsnyAn7GJrecFV2RZx+VqJDkZZnY4hJmpYu01G6lpaWf/ExGOPj+CosL7/nYdwYoLJxPezH4Pgt6GnTr5Ms9+O0lGSxBzTYAqM5MtRzMCLJDyVNtu/LL2NsGOYNgj0+tRGPZIlIzkcUVMKP0h3246iSHbKJJE4XWjHU5orBwIUjPq5rUM8USrzDPz+kGCel89d7d9mtQjYSIjaSw5R9o3QN41RV7VOFjXxvGaZixFQRaCYGIIEl9HEXF8NPPzG75LVcrH4LMDjJ2KEjFsZk1xXkRBSCbTvkH6AycZC/Qw7RnGlmwUoWLNZaAqDIVb9TjzKiWUOVUIISA368AYqcU3s5ZSczmlUlEFx8Rim3aMl8p1Xm5dQtpZfJA3GC/xpb5v0z5xpr7CqLmSl5TbmZmqZSaWYzsGx4TFB5IOymyZYdViuFKh0zKZyc5JacoSVy2s4I6LG1jfUoIkSQhhYRhRCoVZcvkZHhrrY9fMCG4Rx08CH3FCRKkWI3hJvWFB/VuZbTiQFBNJLjqi3fY89hzbzI7JBYBE2JK4JqNRY711Rk3YSczcq1j5Y/DandGayZcspBAqij2Uj5cQiKmoVh7ZKmDLOYaaLNJeCQQkpQAuKYkqbF5tXMjBhvmn9y9bFtVTo9SOD6Lmu5n2HiHqiyBkiZpYG5cMvItwtpgmt+UZmlp/hmfJKWxFQjVs9J4mJpKXouoOFF1HUTVUXUPRdFRNQ9G0Yj2JHqNT20WJ9Ao6rwddMm53Ix5PG4VCJSd2KBQmGsikg+xsfoDZkm6+7qlj9alnkIQNFUvgvT+DkhYuZLZp8Mivf8TRvklkbK4VW/nX7EdYnGolaMuoSoF46BTdpRpDJdUcqW1GEYJfBcq4bHk1halXOXDqT8kygW04GHnlj8hMLUJX49RUb4faA7xqzGff7GI6ZudhndU93K8nWFZ2nBXlx1gY7kK13BSybmTZRHVHkc8CsVqyjODYJnwTK6kRX0GXe6FsAakNd3E89wjpdLEWrK7uLlpbPo8sO6DrOQpP3UNyOknCqmDav4w+p498yo+VrcVIl2MWLCSlgKJlEa4Z8qFOcMZR1QJOoeOyPCh6Gt0RxaPP4tDiyHoOoRlM6yX8lfJPxKUQl4id3M1/sLjtv6isvfQtn9XX2+9B0BvbO2IpvPgkVz3/AfoctTxQvoUHqrYw5Ko6ZxspYyLFCshzP1LK4MIsIxtH+VPoJS8DUIiuIz9xE7yN+K4s2ajCQrMLpCU3SBLCrVBYFkb4dcpmxrn44A7mDXXhc3vxuwOEHeVUqPWE7TqUCwj5CCFI25CQcow0nuBIdZbDrgpOKG2klHMjvqFEnFXDR2kvxPDM1lJRdYBgy05U/dz+NRNU0kcLfbTSSysDNGFJLmqcGuW6hkdRkIF4boqRvr+jTIxyuV/mIncebU75dJwqnuZGXuTy0yBKsQWleUGJlcGj9lHm6KeECCErijbcxEz2Ul4qCTDhl3j/mET9sRRm3sJV0kPNxfeiugfQCjb1iSC1szrqREfxHmgSw3V+RmpcmHMRcWfOon4kS3W2DGXTPdD+rvPUMjtTWf5m/3FeEkWgolgmS7sOs2ximJqyHIuXbMO2Y+h6KaUlm9irbObvxsLkhcS8/Dg/P/ynNOXOOMQz3jIeUAyeKP8kxyqvIy9LyJZgfUeOjR1Zqqq8eMNOLNMmNpkhGckhBCBZuMu68NUcwltz6HSDcADJ0nFONuM4GMG9N85Z7M0zzwCC7Fqb+HsthAukPHgecOHY6wBZRUgyQlJw1q3DO/8aZNWBbRaId28jM3YARbWxNcFQXSU99XXkHMVgqG4WWDTZQfvkSQ77F9DlbcCWZTZH99CQH6PXU0c26aC6ewJlTsHTlGS+vP5OXi0ryrdXO3UuNnUqEzbusxw2WypgKRFkMYzhSJL2yNiv660m2TbeTBZVdzBRVkVPs8wf+v4FG4mvqf/Cpswsf7nn/2BLMl+/8pcMhNpxKjJeRcYly5xKpNk3Ms7CgTTLBqEs5cCW4FCzgxeWOMg6iutQa/9Jrtj1NMFkMWDpcHtYXnkljWIhtmqTu0pBETZfeuAYL3obqfONcLfrV1QuGEM453pCCY3y8qupqf0APt8qRkZGGBsf55fTSQ7mLZwOjb+uPIaW2Y5hdiDPiY3YSAitFiG7wU6gGJNIr/MoJ6ji+3yKLqk4po2il9W8ShIf49QwTjU5pZw6l4s6TWPpczM4+9OgSWQDMkrUQrNAs/Lc+a3N6M63Vjx+vf0eBL0N2/XgLk5tyxWzOm8zs2MhGPLIDLmgZHqIxPRBEoUZHlh/GYfnL6QycYj2rh5mnUPM+HrIKa+LSggokUJcatUQOp7EPkv501OVpqY1R0mlgz2awkPJKPE57fwFTh+XxnxUUYcpVHb5GnmyfCNptcjBbsv2cbevl3V1YZ4+eYqhqaP4cyUEM9V4s2UIWwUhI2yl+IMg64gx6O1nyNtH1DmDicASoFoymuRlsPTDpLQWfNHjbDyl0z6+AEmNs9DxCu6yPhJt46jB82UR7ely1IG1nEhXMiPnUJCY39jP0/UtPMN1CEnBg82fZdJ8+Oi/4co9f5rq8aK1hO/YN3JCbsChGCxxS2xImMjkaVsboHGVi2NDgxwbHiCZmcGnp/DpKcKuDCFnGoUkF+Kdv5VZBRdW3oeZ92HlvcyoAbpDYab0AEn8SDkny8ZmaUlM4Ry1qKjdQGjDQjLcy0ziQVSpeJ+GEjXM9C3g0vEsitCJ2iH6aCEp/AjJhccZRooLbEuAJLCMYxjJF3iN2SurDaiu9ZhuJ/HQ8WKWMNmAJ32mdsVU08RDx7GVPJKt4o8tRC+EyDknSQY7QcCsUs62lkXMhn3gPB+IqYUZGqds5k14qJsxKY2lsDMvsdi9lcsresl7ZI7O95PxF787czLI6O4KhHm+4+Quz1K+LEKgKXkaVI5nKvFO+Vh26YcorViF293MWHqKn538GY/0PILIy1zZfQcNsXYAGhywZkUFZRumkR7+OKSnweGHW74LC28s7lQImDwOR34Lxx7ATk3yMFdzQFlCXiqjcbIZ2VCIyTYPBApMrC1FBM44YXcNn+D9yS7MkllETYqCNk460wvYCCExfuADJPouL44xgpO6xX6HSUQRVLsmWBM4wQp/nAoRJDJZg2nNOQJ1B9BcZzJdmlJFdc0tlJibSP8sDQKCy0fx5n8FA6/AHB3RuvrL9JTMMjLyCwC8zmYWD+l4OorOKp5ykpf/AYdyv8Uwovi87axY8XNUNUA2aTA5HGHnizsZmOwEBJKt4E414MrUIL0FD2+wTOYXlwcQssSWri4+u3Q+qy5e9qbfuZD9HgS9sb2jsZnpobDja+gN6xCBegbc1WyddLC9P8EpxWLaryBe1+hYFxBIR/HFolTEDJriDkoMH7m8TR7oDu2kp+KxuTllId7R95ITKjkgL4EhJAxk7DcBR4GAyeSqWmpiE1zTc5BN8TTlchtBu/XCxctSFrRBZG0ARR5gxhljm2spz7ivoafMR9J97rF8ZoqLY0dYM3SExYc6sUcbGV26CvfS/QTq95zOfroyNt6IzAvOjfwk/H4m1SLbwI1Fha4StSRir5Opl41JglNfRbFmcChhtgQ+zUxcwqPs4PLSnXiVIrBKWV5eMDfzpH4zSfmt75tqm5RFZ1mEzbK2OlzjD9As30/9bIzKcYOSWAH5NSdRUqBlEyy9HQI1mDv/gZHCQYZqXRh6cSw0LUx93Z3U1HwITSsefyRX4B+OdfNoMo+QZCTbpr3nGCuHO3ErGovaFnL9LTciSVMcOvxRcrmR0+fXyzy+Kf8Vs8JPQLb5oXKSS3vvxezfw27XGv56wd10+Yt1Lo0zaa7bn6Mkfv69lGQDd3kHgYaDeKuPIGvJM2MrezA8GzjRu5Abjy3EaTmQ1Dwh13+hp54qxvZkgSRBVCnl5IIQRlWxR01mpoXYtk20HtyKUD2kWgJkl1XSlFxP2CjS/GYMk0NZQeYCfDCBTc41RdYzjKXOKXkKCUNUEXfUszZ7mGX5w3iVCF4lguTyE1n0N6T3dyHt3Y5r9CQCeKRlIz9cfCNCkmnNpLnaUsGRIe1KYmkJFLLnHTuvqBQklRWFHE29PfiOHDmdiRKSYPoLJmaDQB6fx4qqL6DMb0Pb/mc4+54i723gVPvfE5ueZnZ0hNnxURJTU4izsknDNSt4/pKrmQoXm4WWxU2uORLnIjVK8zIvFc01hKtrcQeCYAumvnMYYyxNNjfMv46f5OmmiwH46MCL3P3+jQQ3rGPwpV8yJR4nHxg4fRy3u4Wa6vdRXnEd8ew0f39iF3Z+kIXqJGucM+QyfVj2GzfOlSQNt7sRr3chblcTtqORWbmGX0UDPDCZwgIkW+DL2mQcMuZZ0sqqKWgdL3D1wQz+3Lm+myUJbv7DBhqWtfK72u9B0Nuw7qNduH49ecG/2XPRqqQliMopJh2jRJU4M0qeh1ZeTsTrpXpiiNahlyG3n8lQgll/kdp2tum2TjAXJFgIMu2apHTKYnF/gECqiOgloMyRpmzRNNqq7DmlODkbtic0XkiqmEhICFo8QQYCf8S4WtSzrxHDfJCfsozDv9O1v10zUOliASfFYjJTzTR1lVKdyCErBgF9hOqGLP4lDpK5k8RjJ9BcGWwhMzXdiGk6UNQCpaVDOBxZsCUK+VpGtQCmWkAnj8cq4DLTuOQUimKdt7D/d0wIiRReEpKflPDjinnwx3R03wTO8ACybCNsSI6uZObkDRSSVWBL6L4pxhumebqqjf5wsW9OKBHn9t1P0RYLEGUtr5EeVEBR4T5HnglPjKsadnBF/Uu45no9uTIWjUMZKqfzyAIyZStwXf23SC2b6Oga57nvHEApeBDCxsy+xLA0hlhxNe+6+lLqHQa/+u3PyRfyzGtewKUXXYVZsDEKFn39vbx68gVsTBTTiT+6GD0v487OkHGVECsZIO+aRjYdOKcNnvWF6fa1ogaz1DsniYQbmC6pPE+SWjYsFiW6uSa5izXx49QoHqTVf8yM8ThJ86niNqICd+79iHw5ppnHkE5he3aB88yCe5BVRKeWUfXcEQrpDO5AkIWfvJ0n0jvZOrgVe26CX1q6lDvb78J7pIEDTxclyEsUiY0XV1J9ox/pwY/BUFFFkFV3QqCO/IlH6E2l6PA0c8rTRIevjVOBRfhGdW7Zk0K1YSSs8LCnQC5ZQKgS4cUylSVjrFb2cBnbz4EGli3TE2vCpeao9xejEdtPvBupYwvV1lldvPUEDjNL0q5Ac8/gb9iLv34vjsD46W0UyU1lxfVUVt9GILASO2Uy+R8HsZMG7pXlhN7TVnQSs1F4/h9h3w+LX7zkT5hpX8XJU3+BIeWRLcG8/hw1TR8jtfImDp28uwiAfItZsfznxOMGnZ2dnDhxgrGxsXPuodfl5MryGRZGtlKIpUlYFcSpZUxbQ1+2gWzai2prpwHS7vlOti13I1uCT4yl+NKHz6fdvJX9HgS9sb2TsZl8+p+p2PuV8z7P2n6SVhlJZwmdpSEO+as45G3niKedpHK+pG91dphV+RE2FtIsTybpzw/z956DFCSLBblq7hn+QwJm0dE85ZX4ZYPEIW8ObzaLN5MhlMrgyuVQCjl8Zo6gnMMrh7kxswgP51LOFKbQ5H40qf/074SWZldoOS+FVvFycCV97rpzv2MJ6mZM5k/HuT3/AFcpu5FsF6emV3LCUY+rbTfequOntx/KNdFyX4Ta/hzli9N4SuOkVDe/rLqB71e9lwl3sQ+SM5fj8oO7Wdjfw3S4lOONfka8DyGJBKZaSbz8L7DVYu2CbFn4EjEu5kWudz1B2BEDwDYVpocvZWjsKso9OtOuKiadMoNOmxF3noRHEJN9iDdoNj0vPciyZAfLkx00RJOUyAupu/GjlFWo8PyX4dgcLVxxYK39GOPzmhgc/9VpAKMoXkqqPsCD+av40XQxYwEwb+AUa7qO4NN0XJKTazdfw9KNK08f17LyxGJ7iMy+xOzsyyRmR5lKt/Etz8cZdFYh24LNx1LEXCr7Wp0IWcJZsNl8JMvyvvzc7GDjc6YJVdj42yZRw4cosBtbnKH7alqI0tLNlJddTTi8Hll28NJski/t6uEvjmRYkCzO9a42B6JSYnzMZCy1H6ntJyjOBMKSEa8spH/yU5hCo27sWUovewK1fDXlnR9AMd3YksVR6wjHxl9EL5g4TQeLJgqg+Eh4Shguq0HxlKHqQWzhIi3FyHhGMPU5gCZAz5fiTtWhmReuK3HkZimd2Y9uddNZUU5nbQthJYP+eoUEIOr24aioZMAT5KjLj+Hx8Y0SjSWFNMcnp9hxsotAdzfzRoapqxvCeG8aKQvl92goyWK+JOnRqauLEqzMcoQKdkcbzzlGTncyVNXIqysvZ7yiCE5l22ZzXGbj3hSFeLFWTFYl2lZXsHRTHaU1bpLbtjP184dRq2/ja4rFUxhIQnB3q8affXzLOUGK7MkIY889RzS8lUTlnjeszT3XZFyuWpyOagSCfH6SbHaQs4PObncTZWVXU152NT7fEiRJKpYjnBxkf7IIopomDDadyDAQ1ihJWzSPG2ivG2pThheWuDg5z0nnlct/rw73ZvZOFprekR6kb40Sl/LEpBQpKU1USeIa7cTf0cv3l38QSQ9RYdk05iNEKvoZC3Yz5k0w7kmgWOdnQbz5ENWpRtoKtdgFcFoasmlSN5UinRqiYM/1S7Fs6iIJGmfiuAwT2efDsWE55kU+jNgU+bEhzOkJhCyYccLPmv2c8BcfVCE5ML3XcGU+xKWJUyiyia2lsPQEyBayZKOg4BI6MX2WjJ4A2UCRihLDCsWGv5okE9S8OKwMtpVHSGDLMrYszTUm+//WZEuALZO3PZiGB8nQsAoerLxvLmvjPf1vK+8jJvl5clEFJ8tD2JJC/ZTBTfsSNFXspLT9MVRncWJMTyxk6sh7ycfPqLxMBhSeX+qip7qYOdAtg3edeIIP/exRPJniuKcW6RxadCXH0pfj1Jw8J5vE55q/rc2r5BbLVDe/wNU8iZdiDwwp76O8X6Z1chTZNtieWMqxqQCKDap7E6qj2Gi2bkUp193ZTt7I8aMf/YhoNEpdXR0f/vCH0TSN2FSGJ+7fRs/UQZCKajKVoyU0DWyn3DhO4oYEhttB9PAlHKupw9JMHNkyfPEFaOkROpQMycoaFo89QcaOMFbRRHLpDSQWVHE0lyV9Hj9S4C0ILi8LcFlwGs/Yl/EbHUhoVJRfTSrVQTpT7B1gofIyG3mam/jsgkv4UHUJ0YlxvvW9P+VlXzfjpWc4xhtqNnDX4rtYXbH69MTWd3iabT8+gWHYOCXYsKEK/ZoQHc//O6eSKTo8TXR4muhz1WGepWCDEKzrzHHVkWKEbrDM5kRzjIsSAXZH0nQWNJxKjj9Z+T1aAwNkMn5i6RCnIgsZjC7hWKaSpFCQsHnf/IfY3PAiAFOpWzA73ktyIM3ZFG/NPUPJwqfwN+xBVg1kW1AaKVA5ladktoAsqVC1DFG7npnOK8lPqKgVbso/tRxZV845b176RtERAlAc5JUCJ+f7mA0Vn79QcB2J5EksK4HDMZ9M+pN0dg4TiZzLLZEkiabaKjZondQMP4xjTnY3Z6kcnK3m0Gw1ORFE81yLohVFSKzCSSz3OJlAC48vXcBoyMk9YT8fW/0/F237/6O9k7H5t3/9CiWz+6mRZqmXpqiTIjilC3P1oUhR6XbXs9+/mH3+xewPtNPjPl/50G8mWRDdzljmUfKSSY1hcWemnvtrPszL4TONIi+ZifKR/gwrZr1IyKQUwUltnBOiE0uycQqZzZZFM0PY0iiGPIEhGURlHwdDizlStpyDwQV062XniBlIwqZdM9gUcLAx4KE6qrLrgXESM8Vrq5rnwdZfwlX9JM5QMTgihMR+sZb+2NV85uk+kgMHeHSuR8+lqcOsq+kkWJ/BVBQeLdvEtyvfT0eo+HfZtll77HHG3A+RcdhUxzVuHN7AaOUCOsqr6SwtZ9Z5pt5AFha3TvyWa5SncJcVz8kWEtNTq1jYV0V58noETgwsjmULzJQex1q8m6OBRqYpZ1qUMyFqiCjn9zaRbUF5zKIlFmFN6iArkh3Uh1tR2t+FcJcgbLBtg4y5nYT5C2wxAEABnZ1s4uD0BpYfTVKStUDRKLF9LGhfiLPSjxACIYpUQ2ELskmD6ESa2GSGbLLocxgKPLHaw/HGc8Hr0tEkV0/0E00doFUa4kp9BtnfQ6RMIRLSsZUz909Xw5RXXE9Z2RaCwTXI8uvqVICD8TQfPtzL+09kuGPIQAZsJcdU22+J1+0o7idVTdWxP8CZPPOMClFkR0ivZSJVCTXsQnarpBCcSCXJ5NO4UjEWDPSiFrLkJIvBoBNDsjBti0PzlzFaVo87PUtN5BR5cSZb5SaEM14JuQB4U2ihArK3QNZMEEvMnncdBSETtVy0D3bRnBjgWEsr9669mbHyojqfYplsfvExlnQePL/eRbNY+L5eNLdF8vkArudVSlJZPIVzmUGSLDBqKulZtJxftS7iYNMCMm4fiiRhUSSsVjk0RvPFe7jU5eTPC25md00xNZBAtvJUTeyhaWIHenIKU5L5xuWfY0egEhn46vWLeO/GpvOuDcDOmsSe7CN5aIBk1W7iDTvJeQbRtDBudxMptZbfzPoYEdVcU7OMT81biSyfS28tFCLMzGxnavpZZmd3IcQZZUOHo5Kysi2Ul12N17+K73ZO8Y2JaQoS6IZg85EMK3vzp8fORlBbnsbQypgezaJ7VOb/wUIubSu74Pm/lf0eBL0Nm40mGL/sSkzNxaTuIqNLOBwCw6FTUE0iyjTPLahiojRLyhfBVs99gAUSllbPvKlqWqbbqEw24S2caUhmW1Gs3D6swileozupKlSUZKioGiMXspCDfsJVNUgeB7YwkGWdpqbPUBLeQOqVV9j/t1/kV5ddy5MbNiEbvfhmf4lq9AHgzQdZO3QjrTOrUK0C5flRkiVJBvxxXhP1Gvb2M1Z2HJcjS1gVBIWXkKzQHDSolW0MO/47Ke683ixbwTZc2HkvRs5HXipgCQlh6qiZCjDdCEvHNnVsSz/9b2HppBSdPS0Buso9FNBxZDU2HrZYMhFhufNx2t3bUeb40pOFeexLv4fB/Gpey8ZYEuQcErhUOpudbGtST8uo1nQkWZzYz+b2hyj3FSP2slxPXfnnCfguRVFlZEkw2fUM/z4xxcOl6xCSjCIsrs08x7s8+/A+GKV72ke3p4Feu57uYB0x57nRpFZkPi1LVOafZcas5Mft6zjUqrOZZ7nFeBSXVmzuZmTcTB0JEjnpwzZlPLpEw9q1VC74ELsf6kfYgtI6L8nwKUYm+wkGg3ziE58gE7E58Ew/R3r2kHUXI/++mJtV+/dTmujg1NU1BK/oQnbCrCkRVgWxiVKOdV4DkoQvNg9n7kwtgRAFrMzDmIVRNIeTD75vHYFD/0aHXsmr5ZfwStuH2JnRSb2OEeMSaW6UnuRKcQbgybKb/dp1/CS/hYxSyncXNXBNiY9tQ9v48dEfcSpa5L9LNjSNe7ilZAt33Pk3qHPFrEIIJgsmHeksB8cTPH9wnFG3xLRfOSddfrb5JZuFfh8LXA6ad0Ux9xWd/iZdYsJ/kiF1GkVSuOnWa/ir5/ZzYqYeh5znbv1R9hSWsM9uO0dNy49gla0x35BpbnqOksUPARAfXENqbCm+qi6y0Sri/Zdgzyn8qc4sLRcJ1lxUhj9+DIb2wOBuSBQjuHHjwySt9yKRobzi39FaWovFyA0XQ7ChmIUbeBke+iQk5viwugdx6/cZ8kzS2/s1xBxlLpsNcujg1VjW+bUVTqvAivhLXOLrwKsVF5+0qXEgUsPhWBWW5MBXugLDuhjb0lBUWHVNKcuvakOb49AnTIuZgkmz+wKF5G/Dfg+C3tjeydj85BcP8nX5PsxsPWamGStbT7ue4A/rBqlUkggzC4U0FDLY+TgiH0eyzyzlAomk4qbT00inu4lOTyPd7gYKSvE+y2YET+w+ZCuOkF3InmtAq2KeS+M2PzRoReVKW0hYOQkrA9L4DNmjOzluWJjOYtYpVZjkaL0CwTVMOauZ8oWxX1fHEkonKIuP0Cwl+UjbChY3NFFSUoI8t10+Y/Lsj18lZTxOeN42NE/RIbWFzvNiE0/KN7K2UMNnXopxn5XjPlEgf9b04FElbiqPcZf0KK2zW0FY7Ayt5ruNH2WXw0Fg6l+QRRaHXMHfxuCmyD5m9VV0yu/i2EQDs5KX8ZDKeFhlpExlMCCz8eBzbJp+jtLlUYJ1ZxzpkUIb83ouo27kYiRkni1N8rWFFcTd52eDJGGj2gKEjCVTVAN9nSmWIJSyqIhZVEdMaiImoyUquxY5WOA4yE08RCtFUQthyySG1hDpuJZCovp3ep4A4i6ZZ1a66ao9M5fUiQH+mnvwkWR/WsEtC9qc9jmN4J05i/LpPOUzBfxJE6mkFeZfC/Ovg7q1nN0ksZA16T00xaFdY8z2JAgpEs3lveRX/BDLWwwaB3supaTzZhTZi6To/E9KaM5KKY6pg/TIk4g5lo4iZKwLZHkk00DOplBTCYx8gWf9lzPqrka1Tf748INsGSrKpp9omsfWNRt4YfU6El4/5dNjLOg5StnsFFXhECsry/FW7cFwvIgqVdJc+R3c/hLc/gByLE52334ye/aQ3vE05py6qABeWLWO/7ztDmaCYQAu9rv4h/n1LPI4eWAyyt92jxIzLVQJPu/TuOHxJ8g98gBKrrgeZ3Q/96z/Q44Fy1GBL+Fiy7wySu9a/KaZlFx3lOiD3ZixHEI28K6sI3h9M7JL5ddjET7XWWzg+oP2Rm4qD77hfkwzyUxkB9PTzxGJ7MA0s+RmG0mNLic1tpJ8opKIV+bxNR6Gy4o1Pk0TBjfsSyPbNr+6zE+hVOcvqytw/3aQmeEUbr/Ou/5sJYGy/8uFEb7zne/w9a9/nYmJCZYtW8a3vvUt1qxZ87a++04Wmr7H/ovYr76KlIeUDINBie4Sic5yme4SKCgSZ7+gzrxg3phg/gjMm4SSRJCMM0jO4aRaHkPzCvJSkKgdZMoSpM9KHctyKYpjFbJjAZKkICkFdN84jsAYDv8YjsAYun8MzT2LNdxA6Ik6nqgp45fX3ELGVXwAFg7luOJolqhzH3vrHyXpTKBLgtZcJeuia6gxs1RldyBCWRK1LmS/ga5n37L4XxJgqBV0WuVMU4aVKqG104uUKMEsBFhwUSPLrmzF5XUxGjvBC6cexSgcpFHuQzmrIM4WEqlEKclkCSH/NMm+jRwY3sirsk5CLo6kw3uc2qqt1KmCZqFQ71A56VzIr323MKMXea/rxw0+cTxLRX6GKvdDlCvPocz1Edrp28T9y7/Cstog66r8hHSNL3QO8/xscaFa7Xfz1QbIDH6FZLzYwDRVcPNo77XsHNnA+tYK7lhbz0p7P9/pOMpPSjaTlx1g2qyYPkCbnSA2WsapMZspjw9JMkAykeTib0UyqJItau08jfl+Piauw4EfmymyyrfJrL2L+2vX8ZN4Gl3k+cjwb1gfegbdW5zszKxKpGMdsf7bEKaLoD6DpzTA5IwLs2AXO3+XdXPtddfSvzfF4KkpEsFTGI4oCGjrHGbp4V3sXe7kZxsK3N5cYIHTptfwYpffxVJxgGzsFYYGlzA4uBwZheD0ChTrzCQi7Bxq4lesq9jP8tCcOEXTZfDuH4O3GHU5MBnnn/f0czIxzObS7Vypb8ctFdPZs4R5hut5mcuwUMgLL5/sOsLG3U9hD3bhSRTwZiGvg/C6UXU3k4ZFX00do01tRBcvpz9YSo/LQ1y5cHNg1RTUpeOsCmRZFAyx4NiPWTDyAlVGBPPSL/LciSsYOF50lhY7ZVpcCo4VpWzNH6Rv8DhLl21DdSb57pE/4vjMueIKpSSpUNLUK1EqbQN/fD66EQTJpmzJQ4TnP3veO+PSl5OfuJ2hg1WkZov3UlYl2i6qYNmV9ZTWeiE2RHb3ISI7i4tYWPtn3MpL5+7IVwWhxjNUP81TlMK1DVKBBTxbtgVv+X2ocwEXIWBkuJ2RjlZM3VN0OGybtvQxbnG9iHtuu7Ttpt+zgXTzDYTqWwlV1tK1L8/hbUVgVlLr5eqPtxOqfB1lyrZh6iRULr7gfXgr+z0IemN7J2Nzx/2/YGvpkv+hM/vv24agh+usNNuPHqcrUMZ4oATzde+wL5umJjZNRXyC8vgYJbnza4ycTic1NbX4hRvbeB5PzQ4UvZjRNXM+9iWv5qdlN5CSfPxBdSnVE3n+c0cvsTlRnMUoVCJxQBNEjTMqiXXSJH/ueYprzefZ51T5dGVFsd7J0Ua87PMI2UVlPMuaDov2oQKqDbqUpt6zj/Y2g+rlbUTKLmLLvWNs7H2EhsQQZrWGb7OgzXn8dO1qKl3Hz+w/Z5e/GGAKZw30vETWaZPVoSCfH7T4XU0SAnfOoCyfoNQ5QtAxjpcUXlK4UmX4jYvwGLX4BHiRcRdsRN6mkLNIx/JEJzIIW2BLsL/NyY6lbvIyqBJcWxrgwMwA7fZuNkq7aRankM6iNc2aEiFFoGlBKpyrqEo48I31Iw/sAfss0RtXGHve1cy4N3JsaB7dxzJYho2k5AmW7yJctxWtfhpkkKMQ+IWGUXY5DR94H0q7RfexfyJ49Fr8k0V/L2EJugo2F90+j9JKD7ZhIwo2wrQRBQth2Iwmczw7EUWbibLp8H50IdO9YCkRTwCHDQs1DX/BwMwWMPIm2BI5DDrUUTqVMUzJQhEyWAaWzDkgDkCxLbyywOt08li2mWP5olT4hsgxvvDyL04rwJmywt7Fy9m6ZgO7lq6k0ufhj+sruMGf4PD+6xDCYNnSH1FaegUAccNkbzzNrliK3bEUEzPD/PSVvyQdc/APq+7mcEOxPrYiMs3dD/6Sy44fwLN8Id6rbsC76UpiZRV8/YVdlN9/L1v2voxuFu/DpKeUVxuu4MnGtQzqoAj4QN7BJ1wOZAHBW1rxrjtXVOX1ZuctEs8OkNpVDLQqfp3gu+bhWhDmi92j/GBkGpcs8ejKeSz1vTEgMQ2LkY4ofYcn6T8yQe4slT8kE3d5F57yo7xY2s6jJRswFOV0VqguI7hvhYuoT2Gd7uCWbXH8Ho0bPrUM3XVhP+HN7H8NCLr33nv58Ic/zPe+9z3Wrl3LN7/5Te6//346OzspLy9/y++/k4Xm4L/fSXTJi2/4d0uAaYFUADULekpCzoKcBykvIeVByoGclyAPSdnBlMNDSnZgGzKWIROazVM7kSQUzSPnwVJcGIobQ/Viam4M1YOhuTHnfqtGir7yDD+6+T1MlJbjFmkWxke5dnSUKn0Yp2uGoJrBds2Sdk2gaW/N5bQshXzeQy7rZkIU6FOTzOZ1EhNX8OnWebxUcy3fixdBxJKBPDfuS6MIWLS+ilXXNeJ1qeT7E8wc62fPi/czFDmBJcsMz1tEcnUpFd5+FnOUas6tUbAMJ5mp+WQmFzI0u4Bg62Kuu66Z/d2P8I+936QgmYQSGjecDBGsVNl70Q087VyPLSm4LZO7u3O8d1CgEcWrPkLO8RhxGWZ97yXpvoyX3Aa/9RXISQaqKHB5JkertJuEdhIDMGwJ1WjGytQzmzdImnkkOUPcZTChydi2gWQZyHYBgVHUrZ8DO2+nmRvAqn6Nz8X/hLCjCVFIk331exRmOvn32z/E45dfD8Blrz7DDZknqVoZRfIVF3qR10kfX0Ws8zLydjnxQBzdCKKaXgQCCQlLyRIPnsDSMiimxbrdu4kpY/z8SpmBSok1PgcfCEZBUlm39lk87kaEEPT3fZ/9zx2ke6QNQ0uhFnysrL+SwvBxRkYk/F6Za4L/TLnWjxCwd6YepeI2Fm7ajJ1OY85Mk0p2Mu3bTay8vzirAkbESc/QYp4OXcvJxjay0vmTYcPYCIt7O2kZHWKypJT+6jr6q+qYDl+4o7ls29ROjtM0NnzOT9X0FEJxIBwePLWl6CEvJZUnkLQZnoz9NVPGPGRhsSzbT32lim9TG47mcgynzSsnP46mj1MouKir/y4/OuKjZyzBAmFTNZnFkXRg6HGSgU5sJYfHE6W5pJdQVS/Cca6qnSbCtC/8d0qq1wNgWzZ9h2c4sn2Iib7E6e1qF4RYsrYS/dl+yFl4Lq4idFUYhvfC4K4i6Bk7fNqBEJJMpO46XrLXkJno4lbzAQyfycElAWxVIhELk487KGsoZjGTiRI6Ojbgygpul56kkmIto+WvR7r0c8jLPwhq0fFKzGR57scnmOwvnt+Sy2pYf1vrec337MwskV+/m8DYEaSPb0erXvG2nvmz7fcg6I3tnYzNT3f18U+zk8hCRSAw5AKmkseUDUCA0HCpLsIuH7qiIRU/xTRiGEYEIQSyrON0ViJLDiwhmMqnyZo2mrDQbBNdmDglm1mRJz8n+y+UILbyunMVApedIy87sKULAJpCnproFI2DnfimX2WyapKw2UJttlj/07KwheULlzM5Ocnw8DBjo2N4sait6SBYd+C02EE+U0rBvpIfihs44HeDbbPyQJKZXIGpTDHTOa/cy+evnMfa8TypHSPYCAZb/BxudPNSb4SDQ1FMW1Du3UOh5lEsWbA+k+ULcfhO5R/wYPUV5LWiQ+XN5bhuZCd/M/kDys1zqe2Wu4zdyWq86WnmuafxqAY5Xaa/xs2Pa27jfvl95CUXijB5z2wndx8twVM4E2BIuWYZaXyJsapjJFWNFF6yZilmYjlmbgFJ2UlUEkw6JKadMklNIqfwjlgZAA5D4DFsypM2i8YMKlWF5xa76ZlTwFvlVfh88DDe+KMkEofOvc3OBfj9i7jn+HMM522uD8JVvnOL4QOONmpylYSnYmj9B5ALZwRhDKHR425jpkrHKB9D6GdJ+B9x8+zMjTxx0VVk/Tp38FOum5ql8uSdqIVAsanzFXXs6onTfzSC7lJ51+dXUlLjveB15iybr/VPsPXlPbSODPL0JVcgCcF/tNVwW00ZHR0dPPvss8RiMQAa6utZt3wpuYkZxKsGpTk/hGTk60KkhMnETITB4RGGhoawzmoALgTsDiyna6qYufAGc/xb4ssE99l4h8+sFWmXix0r1rF17QaubXuMJWIfrsAG4nXfZHc8w65YihOp7HmSTV5FJmVZgIRTGPxBxyO877l7MYckzMy5jr/iUZCsAmZOBiROlTXwYONl7KpejMepk8qbOBSJO3Q/ofECzbrMEreCJYF9QzMNF1cjv0XNdb4/TvSBLsxIkQrqXlGO9/omPtI7zAuzSaodGk+vaqPCcUatLZc2GDw2Q/+RGQZPzmLmz4yfYmYpmT1BUDuC9+JxMgtioBefmaKC3Kfpkor9r5qmstxwoMDRFgcvtjrwGoI76sv50/lVeJQL1929mf2vAUFr167loosu4tvf/jZQ7AFSV1fHH//xH/MXf/EXb/n9d7LQPL3jUSZTf4mmWKiyhQuBU4b/xni/fSu8BqLOACk5B7YhM+Mqpa+iHjsgKGWacjGFSzpfkeT1ZgiVKcMmaklEDQXnbCu1Y8uY504w+OoOnPFSuhcuJzk3PjkpwcGy40w4pnCrX2CgvsgF33Aiw+XHc8xbWUJLjY09MIM2qyAloSO+l474XixRlGhoLVvFksuW0el4iCd7l3Kkcj7Rcp126ThLOEK7OIpPSp17nukwmZmFeJ3rcNQv5IuDX2LWiOAvOLhydwmBtMZUuILnr3o3w6FqEIKm/GGWxe9l0BpjxPz/5lHVbRldONBtHV0ouEQS3cjT55IwFIlgTuKzg+9mnb0JYVscmXiSzvwpdq28nFfWbAbgjicf4KNPPUBulU3qahuzek6mMgfWkQCvis0YOS91Q9XknM0YWpxk4CiWKtAKgsYek5Sapqc6iX9eOWsvXo8n9Q1yuWEaGu6mteXzAAyfmuWl+7qJjSaQ7AjT1R3YMiwPamxwlhDt3UG9YxsO1SBreXl68mL64zlApiLfQItyAOvSKfJLzoy13i3h3argOCHRW93AF/74L0n4PdxSeICgHqOb+XTYC5hS3pyiUWnkqBvtZv5UNwtmBmgeH6JuYgwtJ7AkH5apYWfyiPyFgX3aVc6xlXeT0cpxSgm2OL+KuWeaXLTo/NtOQeQzJkajwMzrHDl2NdlUiMBsO5oZPr0fWYZQ9SS69ze4mgfQvWdlbA2onMniTrkZaFAwdRM9U06b9C+UblyN4j9DG5voi3Nk+zC9h6YRc1QkrwzzKt2s/vwqdPeZhcKyLKbHhuh/7qek+16li3qmtDPRuVpvDy1Ld2GrEr6Yyezxy4kGlhDXO2hsfgVNK4ApsaAnQfVUHqlsIWz8U2i/tajQMWe9h6Z44Rcd5DMmuktl04cX0LLi3GCSEIJXD/+Ixqf/lopClpwkceCSP+CSzf/8pvfvQvZ7EPTG9k7G5smHnmPf0V0gwJWpwZ1qQBYqBSXHUPAkg6HjDAVPkdcyVLmauGneFjY3bGZ+aD6x2D6On/gshcIUEamW3aEv80g8SHauf49HJJCiD+NMv8jCUDP3XHwPD3Y/yP1dxUL9a2uuo8m/hf1ZwX7Lw6R04W7tXjPNp4Z/w4fGtjFsljBMFWMpD+nRKBFvlsEmKBeLCBoh3G43V266EiU3yujET3CGj53eTzrWwMBwC2PJBp5ZvI4JfwnKZJbQsRipufcqKMv8yZZW7ri0FWXOkUsfnCT6YDdYAr3eR8mHF5FRJb69535+M/A1hGShJFv59KTMHfJOHJJBXPHyL9Uf5he115LTi/fEo0jc4c5y99iDVPQ9C7EhXq8wmrcU7nNdwb8s/iMmfcWAznxxkrv4PrWMIJkOPKOXExzagisbRn6Nsq1kide8SLThOUxXkborWSr+8fWEBq/Gka455zhZGY4EZY6EVE76FXq8EpMu+TwhGwDdEqii2Jw8L785gHJYNh+emOS9swexXBEMZwTDFUErreRZrY1788uYkSr4y+YqGoy9/M0rf40syXxz/Z9SJ00yG3mJZOrEOfsUeR3ncAWBZB41PMVshUXuLCVSR9omNOShsuFO/Fd/lgPpHPtGttIw9k1aTl1DYHwDAH0eif9Y5aOxOcwmv5f0L3uZ6kvgCTp49xdW4QtfuBegEIKPnxjgyek4km3z5z//Hgtzacav2czA4CAAfr+fLVu20N7efpoSZs5kmfruYeyMiWtJKeH3L0Cae6YKhQJDQ0P09vbS29vLC4qbl+YtQx7Poh8vsjHqvKN8ZuX3iQ5U4HyxiTXjJxGTRUZFbqHN7B+b2LbEv0f+gv3lq88552aXg4sDHhQJHpuOEzOLgOHW8iB/01JNjUOD6ACibyf5Pc+Q2rWP9LAgM6PDWY3LhQrj5aW8XLmEx2o3EpH9OHWFn9+5hosaQ4z3xDm6fYjKniilqsyMaXPMobLkijoWrq/C4X5jyWm7YJHYOkjq5VEQIHs1HDc1c0s2Qncmz0q/m5/V1jB2fJb+I9OM9cRPr38AjnyU0pljlM4cpdydInTzDSiXX8eL2xKMds3iDA9St7IDT9UBMvlhnuVa7uODFCQHDjvPjcPHaR4p5WeLaoiXaOxcs4AG1+9O1/5fAYIKhQJut5sHHniAW2655fTnH/nIR4jFYjz66KNvuY93stAcO3mS3z5wH7IQXD/5BCV7EpgZtcgdLa1AX3wNUmUzE94Cz9RazBiDNJ/s4FhVM345waLCECEmi0XSmg1OCdmpoDhAVkxUOYfuKvy3e9G8ZkrBh5YtRc2VkJe9qNW1NMxbi9/ThNNZg6b56Zjt4Guvfo19k0Xeqqvg46Lh6xj39WGVHeKbHWMMp9vZFVhLbq4B3ZjPya5565jx+nnPjlN87JH/QNM01FAzWrgVOdTEmJLiSOxFMlYxU1RSWsulH/kgSc92uk5t59TJy7BtlYJu8GBhGcb8NLmyJoTsp4F+lnGIy/IvUq6NI8nn8nDz8XpG0iF2m9P0agYfzl2KMnCQmcooL5VW0Gvmkc2p09tLCFyopBU/luQASSUsJSmTomhSsWmgZTvIGl4yBR/JfJBkPoRpOxG2Vpw5hIqwNTQJauU49VKcZhFhoT1BvT1LyErjlzI4hIlDCFTbSaTwJQqiHZkEZfpfosnFCbZT0/lCWSt9jiLY2zS5ks9GP4IuNDqSu0lUbOPl1qX8uupDALy762E++upv0LIurCqV9MoURlUxAmvbMrlTpTT8JsqRxhvpnecFSeDIalzx/NMEkuc3WzAVHcvlQA1XopWUkI6ksSIR9EIC3Sie03BtLbs2XAJCcMvQUyxvKPalycxoDO2pYjCwnq4KBVf9ccqXzeKpeE1iFNyDJVRxNSWNm1DLStnv9vPh4ShZAUp+mMD0P9Ouz/LBsIlPsUhIpaQr/4I+bQ3dmTz1Tp0FLpUFkUPM77gXf9cTpzMhtoChdJBEzZUs+uQ3UD1n1dLl81jROEM/PcDhY2NgZAhrKt2eZgxZw2MluKH0y5Q6ehBCZmJ8KT3xxWRvPohSOYWZ9zC040+ZkqMYjhjYMmVT9VRHOglW70VZPILRciZaZZsSsWgd41PNxGYruVgc4gr2kHfB4SV+ck4FLS/TevRSPA2349myETV8xjFMRLLs++FxegaSp9vo6i6FikU6clmcycgos2MDlFljVDNJmBgdtNBrN+CToa4mR7j5CZDyBNIqCw5GeU7awlG7KFRQ7Rhmyfwdp3szVjhXsmD1j1D1wJlnwbDY9UAPx3YWa4wqmvxs+Vg7/tIz5ymEYMfwDk5u/xs+NnQChxD0hpx0LFnOhvW/Jui8cLbuzez3IOiN7Z2MTTKZ5Nlnn+X48aIymmI78MRbcOTPFNzb2Ez4+hgMH2cgdJy4a5oabw1X1F1BQ3g5j4zP8KKxAHtOvWyx18Gn6yu5vjTAc4NP80+v/hPxfBxVUrlr8V3ois63DxeDkdc2Xss/bPgHNFljJG+wP55mMpdntTXJ7EQXX8qU0qsU39nV8eN8peebLE0Va1eywsF4zsd4ykO37eZoZSmtgVrq60/iChafTyEkdPsy2pd/ipKylXTOzPLhk8MMzeRwdMYhXpwnHMJmXU5nRV5FkQ3kuinqF4eora2lubkZZwQivzyJlTaIujUer9nPveoPEZKgdXoVK/rfz3SJg6wnyob0vbxP2oZTMihIKt8reTf9wSbWJg9zRfRVKgqvK453l1KQdDpmZf685o85tGgNSDJekeR26ze07Gql1NVHeMEz5L1FN8oSCq9IG3mKm1kxluDWbANVVTUYfV3MTD8DS46ilw6ePkRucjGDU9eQiISoGj+JW2lFVeuQJYo/SBQUGAop9IdU+kMKA2G1CIxeZ7Kwqc3nqMpJHPc6SKvnb9OWsLhiyuSKSZOWlF2EahKkXAq9umDCKeMvcZHnVZ6Pv4Dph69t+Tci3RbdBztJpvfgqTyBp+IEqit5/jmYgtIJg9qZDMGEeabovfky+hbVMd03TOWJj6HlwwgELy708fd1EmcrcvsLgk+8kMQdM/FWurn9z1bh9JzrtAsh+JvuUX48OoME3JCM8Md/9SdopslwbS17Nmzgko0b2LhxI7p+PjUx3xdj+sfHwRL4NtUR2NJ43v7/pX+CbwwWM+7V0SmWHT/F7kwDOTQCepzPrPgBVizMi71XELRytIx1svzqndiVNp7tMoEHVbrqmti2dgMjl1zOldV1yHmLn6eTDMzViLtyNosiJgsdDir9TioDTqp1m4pdW1Efuhd7bBTdb+KusJFLfOQnU+TGFazcuZH6QlCjq62J1FU3ctttH8LnKgLHeF+M+I+OI9uCYxmLvoKN6lBYsK6SpVfUnk+PPnuMhhJE7+/CnC76BLkmP9/IZSgbK1ARP7dRtyc1StnMUUojRwlYM/ivuYbALTfjXr2a3kMz7PhVMTCn6jIbb29j4fpiADCd7mZ6+lmOTB7g3zJb6JSKAfl2cZQ7Yo/hlhdz45bP4HKH+V3tfwUIGhsbo6amhl27dnHxxRef/vwLX/gCO3fuZO/eved9J5/Pkz8rUpxIJKirq/tvLTS5XI5vf+3vSdk6krC5zXycyt5Jpk/4EEZxArFLW/EsfBdqSStWNsrQ2DZ26jF0M3a6HsZVMHlpzZW8tPpyqqVZ3n3kCNk5OUDZNAmEBmhpOIArXMAGBmhmX34Ng2oTmmLhJIuTHC4rQrAwRFvEwVLDQ6rpOQDKj92NCF2JsrIGd6UHj0PB61Bxaco5BW9CCF4YeoEv7ryHuCg20Qqnq3nPeD2f0h6FjZ+jy3kNDz99gLQyijLHbe33J0inXuWPHs+gmA6yqoOcopNRHRQUlbRTIeXSiLp1zPkqCxb3YmV99PesRhYyEZyY9Ru49aIGNi+sYDwzxucOPsK+fDWmo1iPoYs8N6WfYEvmJTyOOPjPUIksAT05mWNZhWM5hbh19uQtk3cupeBejeRYTFYrOmoLM918oPBrEnmb/kQ9A/EmBhMNJI3zo0ZCkRB+DdUH1xV28dnYb2kVY28JTnOqk2juHixzMUJKMxH+LmN6knE7xJhdQq9RQ0VUY8L3PMfqimCtKh3ii5OfojFfjWtpKd6by/jO0Cm+NlEUVLhWPMEH+S8kIJdzM9C/gqrqLgKB6eK52jA51cLI8GLEbAPe+CJcVoql8W04pnohHkPJJU93rX5TUxSUkjB7l7bQW9qAjxR38wsk/xqesm/hZ10JGtv6ub59D6qjCLJsUyLW106053akiJPq8VdoDs7y6q3X8FdlrViSgpbrwD/9bzitIMnxDVSKMB9Z9BCNc30HdK0Ur1pB46yX0NGXIX+GMkHlUsTS93J4zMnzDzwGQlDVOp8bPvcXeEMBhDCxbRMhDMx0lqmfHGF42uRYzItAwusqsPYDDgrpCN5T3yFQOIapSHTUlWL6CtimTqTjajS1BF/AZsYYIG2m8PunCIfHkOeAuBDAoBPXqzL+vSa2qXHgotUM1RcV1PwiymX687Q6I3TM00h5VRTTZunJJP5oEDO8AfXim1CWbmbm4Cz5x4YxhGC3O8bslIJkFcGHhEmDcy9rPA9SpvWfc3vslR8lcfFtHD75KSwrTTC4Fp/+Jzz+0MMkbQcSNpewn8vZg1J/EQPL2ulPPIEQFk5nLe3t/0owsIrYZIZnfnicyEgR+K7YUs/am5tRFHnuWgUvjb7EDw5+i5u6d/HuVIqpcge99UHyruJitmTJdykvu/qtn6nX2e9B0Bvb/xtj09PTw5NPPkk0WpzP9VwJ3kQLTocbI3vuHBBzTjEQOs5g+DgTvn4sxUPetYIqVwk3O4+wwWuzdMm3cLsbAZjJzvCVvV9h6+BWAFqDrWxp2MIPjv4AU5isqljFv1/x7wQcAV5vBdvmB8PT/OvABBlbIAmba6ae4Z96fkilWQQTpiIxWuVkuNpJfi5DIEyFxOh8nKXvZdNV78HpdHIqleX2lzuInoigTBfXdqcm856lpVxeYTDVPcnMEQdyoTi355xTpPy9CNmgOtxM0Kwj0SvYX/YirzQ9CMCS2CX8Ue3/YcHaGkprvZyInOCPnv1jmiZNPpOaZpk1jvK6bE9advFiaBXPh9cSqbucDy1aRsy0+OvOEaJzWbSN4gVuyDzEwwc+wsaJRpxCJqQMMa/1Oww1aASDZ1puHGIVWws303ywnvYhg6hHYme7g7C/j2ulx6kLHjhNu87Fapnt3ExyeA22rZxWSJOAClWi3q/ift98ok6J4ViWztk0x9JZ+g2DmGZi+SXy6rn05DIxyXvt35K3KjioXsERqRzrrEWvPie4YsLgigmD9rj9pvIEBVuQwSRRchSzaQ9GySGYEy1CzP2ctWw7ClCbKads1sI91ouwNKLWXWTNawFQShyE37sAR4OfnGWzK5ZiWyTBtkiCoVyBQNrio9sT+LOCyQod6X0NXFkRZF3QgyZJfLFnlB+OFCmM/8cNykvb8HT3sPGll1Bsm50r19L71/fwxfl1+NQLU3vS+yeIPlAE7uHb5+Oey5hbQvCJ4wM8NXNm3QooMh+tKcE5NctPnxsingVNLnDbvMewo2HGow001xxnY9t28jkHyf9cwKLeTtS55yar6XzjQ5/g+dXrEbIMlo3am0QZSJ3uqhLKJbip72Wu79+NzygCj7juYeeiy9g+fyPdeQ2wWa4Oc7d+nNLj+wmMRilEFM6uXZd0gdYapmTjxXhv/AC56Spij/YiZIkDusroxBmKY/2iMEs31VG/KHw6G/aaWabN6KkI8eeGCExnkIG8LTiatRgxBYYUZXHXdkpnjuLKz+K5+GICt96Cb/NmZJeLQs7kpXu76NhdzJKVN/i46q52ghUXrilKZ4b4Ts8Rvh2ppICGU+R4v/VrPrfoLymrefOapgvZ/7Ug6J577uFLX/rSeZ//t9ThDj/LNb+eYrU+TrmawRYwYjgxbBuRkpDjNm4jh24VCGg2XiWGWjjTG2TMUcWB4HLkvMJ1k/v4jw/dheHQqRt5nPXTCTxGEEWek6MOVXMq7ORAZR2z6pmod0DEWRcbZ0tfiHUzLhxnPcy9bb/BbHyWvKXzj3s/x2jqXLqRBLg1BZdDwaEqaArM5qbJFaZx+Y5DyQFstcjtdMbbcI5ehilamAhoCNvCkSuAJTBQ3rRB3ts1VQKHJuPQVHRFRkgFokaCvKQhVC/IEkKWcEgFqhnE7TpCRh8ioU1gSWf4tYqQKSdMo9pKdbKKoWkHu2pXk3D7UVIFaqMDZFMqsXzwvHPQMWhWxsmEfPRWNmEHdDSXzZ1jj/DZoV8SMJMkJTcpxUFa1knrGlmHgukA4bLAZSC7C1iKTvXRz+KJLMFSsgyv+hopxxBGUqOQKv7E+32kJ4ov9GhlmleWzZJRbDQh8/HJd3Nj9HKUCpnQR1u5N63wF93FKOjF42PcNvskw0k3ubwHjyfCkqVbyec9eL0xoOika3EXYwfuZDayAoU8tm8XP1YWcmv7I6z1nGTy2GKy+xupzmUQigPNzJB0G1z1j5/FU1OFEgwiDb5M/v5P8oPMFiKEqfYOsHTjNCXhDfQMPYAuxeYeJi9mbzUdLwvMrIpTXw+edQAcbtR44iIvQpZYEtnHB8wfUl/lxSlS5KzZ83pjnTYhcORtVKEinD5s3YWQpdNAxzLzWGYOSRZcoNQAIWC282qmj94GgLfmINVrf4SsGudv/DYtlQoxNdXE9FQjhTkOv2LbeONxAokECBirrsLUdSTbZtGpE8wrnCT9PolcRR7JFiw6laQyUqxRyFt1xK2PoUuD5JUDqPIQIZGgP7+GI+kbGTfOyA5XaCepd72CO3+AxaGisxQ1neww6skEGsg6VjAyJ2cbtGPcJJ6jWRmFtXfDtV8FIB4/xPET/4dcbhiQ8Wt3cvDBdZg5cPk0rvzoIhraS+bGT/DK2Ct89/B3mZ44xNejEbylCmNVTgytOOCyrFNRfiP19R/H6237ncfz9yDoje2djo1l5VAUJ4Zh8OKLL/LKK69g2zaSLeNONVLlb8FTbdN7YgY970c5a+3IKRmGQkXa3HDwFGg5FjpNlnk03r38SzTX3Hp622cHnuUre7/CbG4WRVLY0rCFF0dfJG2kaQ4085+b/5Nq7/lU13g+zude/ke2ZRvJe4o1cwFF4l3RI2yM/SfOqmmEWpwb9IJN3WiWmvEcmilICycTah2TDZfyrZlGDk/VkMWJIkncvqaOz145jwr/mYCWZdi8/HAHJ16YKAYwVAuTHKpZfIcPVm/l1YYnALhy5lK+vOGv8a2thlyck/v+k+5932VdOkWFdW4EW8z13wN4zLWBv6/7Q0YqaotpmLOsSoxxF9+jYaqXrhcWcdB/I52U8t6UjlfIuOVZkt5+CuWD1NWeoqRs8DTA6aaN7fmb2KWvwZorwl/YfYQrTz3B/KZZgvNHkbU5GetsgFjPFUT7LmPactMnW3RoFlNqUeDgjUwAlWUSC5v7kf0x/GKW0qkRjk6105tYym0Xzee2dfUczOV5aibGjtkk+bMoTFWqwtWqk3kTBRJjScryguqMRUU2g8MzQbzqFZJVe7H0M9kfR6IO//gl+MfXoRZ8EBBYngRZbYCcOoDhmsFwRnBmNCo6P4SwitLS3sAe/Hdch1zbfv51CEFPJs+2SILdXTMse3QSpyE4Vavx4MVeXKpMua4xkCvOv7dMDVB56jAA4XCYTaEQ0lf/GdmyeHL9Ffz2rrv510WNXBr2kUsZREZTmIZN9bwgmkMh9nQ/qZ0joEiUfXIpPSUqHzjcx6RhghDISYPKtE02Y5BKG5C3kXImUsY6BzR6tRRf2fBlPFqWn5+8nZ0jl+DPp9k4ephqV4KHr72ekYqiI3/RiSOsP3kU76JFXFExTn7WIrF7grJ9L6NYRWA57ivj/uZL2V6/moLyxtQ1BYt1xkneFd1H21gv+lgWu3D2YipwlIGrphI5uARp4XXkr1rD0R2jDBybOc36DFa4WXJ5Lc3LSxnridF/ZIah4xEKueL7ElBgpVvBPxdY21mq8E+LdD7/7G+5cckC/DfeiFZRcfqoE31xtv7kRFH6XoJV1zRw0Q1NpwNzb2Z9mTyfOd7D/rSBLATPLW5hcfnvPn/+rwBB/x063P+bmaCRAwfYcP8EMjYbtT6alCi2gJeNJvrsUhTbZH66mxXxI4SNYiTORqLb08LhwDKmHG8t3ACAVMxGIEsIRUKWJbzkCagRgmoEXSmgyyYuy4EqF8jZOinhImPpWLZFwVbJmU5ShgfDUjHFG78U55iSxlG6HS20B0myEULGiF5MfvpKsC+Mxov9wm0CaASQUIEcJjlHDAOJgumgYOlYb9FZ/MI7z6F6O1B9J1C9nUjyGU152/RgphZiJhdjpVvgbVyjhE2rPMoyqY92qZ8qbZYXGi/h17U3YshasSfFRCfhngmSWQdTIsgsPsQFzlsWFuH8LCVGhJCV4hOeRczXKjGEwdbIw8TTA8j2+a+KpNiULopSviJCTrf4zayDk3Op6tXpBXxu9KN49Bwjy/+Dp7XV/NT5QYQks3iyh0s6juMwM6yd2MHRqjXElVJ8/kkWLngZh/NMtCYz08zUofeRizaxMPQIjeEHiJ3y4HjViTzXndqsrEadKApT9DUv5cpffQ/nsR/DC/8IwmY8tI6f55ZQVXWKqupOZLl4LRmrlMe7L6E3sYB/uKmGme1b6Xq52P/H06Kzq/GjPDevmB1Z3pfnlq4uSlt24G/YjfKaKIcQqKY4PT6GJr/jprfClpk8+H5ifZcDEGzeQcmiJwAZYSsgFDSHjqxHEGRAgDdlolsyUvkiJH8tkqQiSyqSrKJrlTgcG0ilAkxPT5/+mZmZOacQ9kKmFQrUjQxQc/ExmJ8BIag/ZNA0k0F1mhf8Tl5yMxR30pdtZ8S6ipzUzmtIz7aiuBimwT2JR02hkmWQMnqVOmzZRklNo0bHkewcmpTBqyTxlpXgn7cWb0kpnhI3WfVhMtYrAGSmW7GnP8fmD12OJ+hACMHu8d185/B3ODp9hJulHLe48sTD2unaAqejmqrqD5LLXkRn5wluvPEDqOr/nALP/x/tnYxNLjfJqy9fR2PL3dQ1fgxJkpiamuKJJ55gaKjYP0cxPEyEF7NnVQ3TBYvW3gzzu7O0ZCVcZ9UP2JLFmL+HwdAJBkLHSTtnWBKo5Ib5d7Kp4SrK3eXM5mb56t6v8vTA0wDUemtJm2miuSilrlK+e+V3WViy8PQ+j04f5fM7P894ehxd1rlt2T08k6mjc45NWy/6+Qg/pj49xuzYPKqyTnxD+6hXk1Q4k6jyuXOpKWRGHc0E2y4h0LYBai8qqii+Ll0/NZhg+89OMTs2V8cnC15teYSDpTsAWBBdwOWxclbYEyx0jRIodJ6TNReaC6npcpi3GVqvAt0Le76L2Pt9pEKSgqTyly1/yq+rrilG7OcsKCKszh6i9qGjlKVmieq1SPW387JmsmlKImzLCGxi4SOYehKfWqC5pgN3/QnUuYzJGNXsnV2Ld0eEcLzAuKON6bxGLOCmdUE3lzbvJuAsZh9sUyc+sJ7Zrs3kU+WMqDY9qsW0Jigr97CoNURDqYf6sJuGEg91YRduvfj+CiEwLZMnj03xnzt66ZwsAhddlXnPqlr+4NIWwgEH22cTPDUdZ+tMnMxZa5srb6NJORZoh7iFB2ngDH1PSTvwdDXiG1iKy2xHCdeA9fb8EcVdICR9Dae1B2QNNn6uWNeovnG9R9fJGbZ+5xhYgqPzXTy6zHn6mdjYdYj28UFQVRauW88tl23EoWnEnniasS98Hsm22de+iUOLb6cxJVDSJlkJYrIgo4FW5UIq0blmymBewiImCT68VGes0gm2QDs6izL5xr25zrY7F/2KDbV7GUtW8V97P065nMblsDjV2sJAZbHuy59O8cnH7+O6nVtPAyhFt7HOAi3GovnYd34C14bL+K8X+vjtq0V5ar9TZfOiClRZ4smj46QL1mmcfrZb4hR5rovu5oqpQzRNjqNEz80WKw4LvUom2tbM9KIriBRWEOtRsQsXZpY4NYuyeAehnp2E4j245m1Bb7sOSVaIq/CtRS4+c+MiFs0pxtmWzYFnBtn35ADCFnjDDq66s53qecG3NY4AwrCZ/PFRfmHnSPpUvnjTEtTA/6U1QVAURlizZg3f+ta3gKIwQn19PZ/+9Kf/x4UROp/bxejzeQrAULqPo1VJSgsxAFzJcbTxMYRVHB4bhQRhpuQq0qqPgq8S01tOXlbIIoggSCMQioQpOKdnw/+USdg41TxOJY9DyeNUcziUAk41d/ozKV1KMhZisvppEoFTxe8JF8vUIMtVB4osQNikkgHiE7V45iJrAdvNCqueOsWFoxDGUjM8W7KDsXjxYWzt6mbFwYOYsoIhq8SdPo6WtzBUEUZrylHtn6LCMUvBNujE5JRWoE8vnBPNskQIQyzDsJZTnvbQnuijKjdNAZW0ppNSHaRVnZysYdgqllApcUWo0aYpRD18IP8iG5QTzAovP6m7le81vJ+UWjz/8MwMYgDKLUFAlwkrecKFGN6eY3gmBnGKHIpbRfhdWLk0Vj43N6Yy68tvotYzH9M2eGnyAaZyc037gLTixpAdOISBy0xhA1m3C2ddKeFF9ehhmQPJ/byY6sRCELA8fG70I6zKNzK6/Ns8F67g+3waIcnMnxzgk+JbDA2sJJ/3oKgFqlpO4Q0auNUsLmUSiezpCTM1sYjIyetR5ByNoR/j6svjt5qoes+f4b/8Sg787H7Ur30Zt1qg9NIs4dLigppYcSN99Tozsy+ejk7aloyCCZJSrIGbO4gQMLGvjIlDZey4+Gr2LysWr24a7+SSV/xgzfUZUbP4G3cTatmBI3AmO/q7mm1q5KL1ZCMtZGZayc60YBuuYv3WayclG7jLunCX9uAOD6L5xhFCQnEmUbSiqEPYtYi2A6fwzBQzLLEFFzG7+noU3Ysiu5BlHUlSQCpSTSRZRUJBCIlk0mAmkqbnZC+jPUOYkgtZUfFLGaIEMVGRsbiCVyhr6WS0phihbhjK0DKQIWeXkJ6xsWMmWIKI4qJPDdNXCFMQc8BC8uIvvxxLzMMyfneAWJymCyAKCJEHUUB1ZXCXxVH0LJJSwEqGKFgexqwxpqUJgt4Ui4IJ3OE0uieNouUoCS/CF3o/g4MKQ0OPEQieIBicpKzsByxbuul3Pq/fg6A3tne0Nu34M0bsYs+qYLadJZf/BN1Tim3b7DpwgG1bt0EhjwBOVDdxonERm53ge+UFRtJOxnONVBsOWgyFEvvcoM+sa/w0bW7KO8iS8iVsqtvElfVX0hvv5cu7v0wkF0FCIuAIEMvHcKtuvn7Z11lVvoqHex7mGwe+gWmb1Plq+cflHyQ9/DgZ6yDb2cL9vJ+MVFT1WpqMsOz4PjyFHEuWLmE0fYqd+7IITwnL5T5Wyt2sUrqo4vxmlXjKin1oai+CujVQvQI0F5Zp0/XqJLaweJifc2/PbwD4hFXBXaPdeK3YObuZlPz0BppZfPn/wd9+DWgXKLTPzLJr7338eaaabncx6LPEOEGt2sNuLiUmFdkbkmGx4uQe1hx9hRnfPC754MfY1zVD58EpcpLAVFIscA1wqraF/oZaXGqGq3mKLfZTuOUiQkxnXTw7dAXPj15K1jwTjFQkk8tKdrOp+WWqgsU5VQiJ1NgyZjuvIjszj9fmREWTWbyxmnW3tKDqF6Z7Adi24PmOKb67o4eDQ8VxUWSJaxdWcE3IT/5knJGBBH0VGp31Cl21Khn1TA2NS6RZxiHCZg9ieCef+naWYEkd4bvuJHjrrcguF8K0seJ5zFgeK5bHiubO/DuWx0obuJeWEri2CbkwBU9+HjqfLB6gdD7c9C2oX/uG19C9f5Jnf3SC7Utd7F5YpBlv7DpM+/gA3eW17GluJ+1w4bOgbcairi/D6oMvs/74L5AQ7Gi6gl8suoFZRXABtXacwHckD/OFQq9X5q5VTgrHZ5EzFh63RoXfSUvYzdJSH/VBF+V+BxV+JxV+Jw8f6OcHLzzPF9d9HVkSmL9t4Jl1f88DGQOzzY/QFBCCpeMDrO47QbvZxeWRl1EGTRKDTqyCApLAV5ujZH4KV6nBTs9KfpnexPO5ZVgoeBt8LFhVSVCS2PvcAMlkgbDfwd99YBntZT6Ugk08VWAinmU8nmMikeP4dIp9kwnCM2PcOrKDdROnKJ+MwtkxO0ngKi2Qr3QwVNZKVFtLorCEgsNDS7aTwJGn8cf6iplSTcN3+eUEbrkZx7yVzD7SjzkXiNhXobHhjiU4kNn6k5NM9BX9jnkXVXDZ+9veVITh9SZswexvO8genUFyKJTfvQztTeqW3sz+14Cge++9l4985CN8//vfZ82aNXzzm9/kvvvuo6Ojg4qz0mtvZO9koTn+yikCj8+cdjLH7AiPa4dQtOInjslhwokhVoSmcDvv4NBoiJa+RwjFi5FyW3Mi2jYj5l/L89Vunq5SORxSipEKIZAswYoTxyif6KF8agy7vISMXoYlZCxVpnVhJbJ0gGRmioKtkTd0TFtFVw2cah6HksOpFHCoeZxK7hzAo1NAsU2ELSMsCRkFWdLQJA1ZlslngowevZX0TBu7Fzg52Ozg0iP76Ch9iFl3cYItU21uDhq0Oy2cqVrKjn2MwazGQbWP3Bw9LeCf4or0RfTl4ahajAjpVpKqwgi1k1OUjs/iHM9D4YxjNxMUHFpps7dN5nhQxT4rmtdUMNicyXBpOsuwZwE/q3kvu8LrTxfv1mXHuWvsIa4ce4VHUzcxkN/IfGERLO/EGe4nN9tEcuT/Ye+/o+Mqz7V//LPL9CqNepesYkuWLPcCxoBtDKaFXtKAhBY4JCcJb3pykhySk4RU0ggQAgECoTdjwBjj3pssy5Zs9a4pGk2f2eX3xxayDabk5H1/a33X4l5rlkYze/Z+9rP3fp7nuu/rvu45gIBJ9nNl7jfJ1gO8kHsut834PqWxMFcGRqkPD5CKhogG/Uz4x8gkP1plD0FiUd7FlNvr0NDw1wSwVHtwZOdwcFzk6bYImzpDU5s7TCLxjIp+cmBch2pFZIY4wsHKJwg6jL6+JHg2N45eypCti/t98NaMuZQFRjivbQeSBjZbmIaZb2M7TbKpEAfdxhQmiI9VE+5ejG/665hdo4i6iMsxHdmWT6ajhca2diyqRiDLRFuNk/RJij3RaBZdXXPIpC00z147lSNzsilI/C74Vfb4DDrcxT1Pc03pk+gxKxPHlxDqO4dUvGBqe6fpKHnSBrKVgzhKqxmrXczjoy7GojFqvcdYUb4JWVSQ5SyyPZcSGfIR7LcT6ncRGfWgv2eRhqCCLoGgktv4PNm1b75PVOO0l0/XqeqOU9FnXOtxt8yhGS5Slg+Xe5QVDVdEwRVVcEcVXBEFe9I43gQOXmYFHVQBUMgwM0p3kKk0ctr8w+Uc6TgTXZ+kl6VTCOkkYiqBmE5ii0coUMbIywtgmZYiVWQjHJ1JbLwA/1A1mYyTHD1CgR5C0axkBBdpRxVpnKSTGdIJlf97I7SONbsLT+Vm3GW7JgGkYW7zV5l/5h3/8h4/AUEfbP9O30y8tY5jr3+T0IoQyCAHZDzC7TzfeDmPjYyjJhIs7jxE3YjhKRZUM1VZzZx7ZTNrXn+Vnv5BDqsFHNKKsWdEqjMSCyw2nBGFk9MJE3KEnina3BHKs0tZUryE7nA3mwaMGldWyUpSfa9HXMciytgFHZOgYBF0zIKAmHZjsdYzkLeadqoAAVnPUDa0mYrRfWiqmSPpIiKaC81mo0AMc87hjXj0NPlujWovNHnTuMY7ELT30F5FGQqaoHQBavFcfnjsKZ6PGEIv3/EHuTZi5MTpspV2OZ/9Sh5DykzG8U7toqSkhIaGBurr6/F4jFynQFrhR8cHeWrYAGI5JPl84k/Mtm5G1HQqBlz8NfEVniycSdRtLOhEVWX6sYNkejP0acVU5jjwx1KEfGaUaW6YHHOzg6Ms2/EGNYOt6I0S5TMHybIZi8SUaqa1r4GtgYswUUhx227KBtopjo6RXyuhXyiiZh86ca2C5QSPriTSP3fSSWSYzWWiYqaPspk+8srduHzW9xXH1HWdbR1+fr3mCLuGT+TjVmfgfHcnM2fux5y1A4UUbTSwi4Xs0RcTEr0n7USjKNXJt5qWcV5eFh7Tvx45nmwMHH4B1twNsTFAgAU3w/Lvg8V1ms11bnllPy87jXM6u7WT5kA36UQ1h5xuulwCoyYdLakixBSEuIKgwwXd27lr/zMAPFa3ksdnGDmPJpuMIAuIgkDSJZN2m8jJtvLI7iS5KZ0uEww15rBkUTHFpa4PLTSq6zrrt1wB6QPsHm7mie6rcZfa6CgxgLQQTmM6PM6Z+gC/cDxO8bghXBXDxpvqEnZnmunP9VHoGuPCiXdYEt2HOMlRG8TH3/Mu4rFpl+LPeDDv9iMkVTS7RHpeDpxUO8cpieSbTeRZZPLNJvLNJrJMErsn4rzlD6NnNLITGf6++QC+o+tJj3aghk9dE8k2FVtBmhZnFQeSVZzTvZfcmko8l1+G58ILkbNOpHHoqsbo+l7ib/dh0iAuCxxNqPTGVMxWibOuq6NuYQH/qo2v6SS6cQAkgZwbG7BWZ330jz7A/j8DggB+//vfTxVLbW5u5ne/+x0LF36wZ+Bk+7fU4Tb8ma3bZ9A8MkDX+C4G4h3oQDq3mHSOwd+cQwcX8wqaLvPG+Fc5LJSTl95GQ28fm7PyWD9/Cbvqm1BPkqmdNqFy3GXIWv7oL/cy+/BBttaUoEgirioIempJJo22Zmf3UVm1B3umCdXfhL9nEF2MgmkCTQiBFMbszGDPT2DP+eiaQLomEmxfgf/Qpai6mdfnWNldbXibrrUFaHwlxF7xCLtKXyVhnkykluu4+dgVVCZKUE0Z1uS8wUa1m+pIDZIuYSVCEmNwWpCpZqHeRbbpdwiCQWfTNDgcs/G65GRjroXOvFMXtZVj0OS3Uhz1ouIjqpjp9wq0l44QsYSJm5zIuZcy4TiDyGSoyKYmuHr4da4Yep5jbhe11b+na/sxgsPdJCNhjhT7eGfuLCrFAV44cBcmXeVRdRmj7fopRd9ONkmXMesmXMVlZFVV4c3PZSwW5vDx4yhInKXPokYrBFHA99kZ2Ga8Xy2rcyzK4zt6eXp3HxNJw61ilkRyTRrV4Qh1aSsedVKKXIzzxvS/Mugxki8rkkX8n8EbCSop9rvSaMkBBCDuy+Ubn70MsxQimRwkmRwgkRggvfcw+jNHkQ/FUHw60ZUq8TM0mFzTJ0Ol6LqALbsXdJ2SwSTTOmP4c8x0l9mJOd4zSek6mZSVPXsvJqPYKMs/SkHJdjp0mQFVJKELRFQbe5zfZsxag6jrnL/+WRo69jN75fnMTEDokUdQo1FC3jqGpl/IqLVqCgSaU+O4/Pv4VfUsRi2Gx84nitToIVZ6j6MHy0iFi+E9dESrAD5ZwJ1lpXMiSSqpo2txJGE9F//nFymqnYaqJlDVBIm+YY4c/B7xrDbQZPyHV5OO5uHKFWhY6sNkVbD07Cdv8/NImRSKxUrXnIUM2S0kkwnUWATHRJiseIysRAJvIokzffoco7hZYsJhJp7lolWpZf9AM6pqQhRUmnJCOOteRxA1Qv482g6dhSqeXkoYwJpI4J6YwB2eALPG8fIadEHEIWtcfMF5TK8shudugf6dxg9mXgkX/hLd6kHNaER2v86mp47Ql2oGILfUxowzS+kOdrHr2DZylQDZshlNsaIkbaTGXagpG7puR7Sl8ZbvwVux7ZSoXSbmI9y9hHD3YprOKmbRpWd+YPs/yD4BQR9s/27faOk0gy/+hiPmhxFcadK6iUeEL7KB5cxwWLmjPJ9ZsXFefPZFonFjYW3Xc7jimksZ8HexYcMGYqpIC+UcSWej6eASRD5XlU9dRmHwSAA1fYJmogoKA572KdqcyQ0pJUVC/RgOpNNYxlxJNOuzKJYaAKTMEM7Q3zEnWz7il0ZeqF22YEPErilY0wlsahqrrmPTdEKSyD6rFVHX+ZE/yKXmAqhZSbJyKf+n50XeHt6OiMhto9dSNV5Ol8XPsHZqtKm4pISRuiYe062MqwYyvC5X5vzw15FTHchYaDgcJ8dvOL7GtULePuOHPJLTzPaJE31iHZ1ACWioZU70yTHXGZ1g6c43qO84gOTJxb70coLBPrLHtzHU5KLSfZhSeicvNJhHzOzumcuLkbPp1o21h11JMjvHzzkNeym3b0ScnG/VlI9g+7mEjp2Jlnk/rd1kkcgusmNzWbA4ZLSMRtifJDgYRUlrjEgaHb5+Csu2s7hoF9nW8RPnIhbgOOhAeqoXMSjSVlHNE9fdwNaSylOoibIAS7NcrM71cH6Oh1zzx/f2T1k8CG98F/Y/bvzvLkFd/UvGXWfi748SHIzS3zPGg+4QByqNnLTz98SYeyzJK/Y0R80f7BjTJQHdLnPp8U18aasBhJ6++Dr+uOoieE9eyrs1thaPKfx6TxxZEDieUjmU0HDn2qhqzqVqVg75VZ731dkZG3uDgy23k8TJN4d+zFhBKYgClnSab5ZkUxZLEX/9Hi5TXkMWNDLIhBpvIjHtVrasGSbUm0Y3pdnr6mWrlkeOEOLT0ltcL63HIxiRliNaKdcp3yekOXC5zTSvqGBChpF0hpGUMiV9/3HMl9L455Y4nozOprwwyZ51zDiwHfdoGOEDdiPYbJiKizAVF2MuLsZ00qsraaX/jRHqI8aaa9wkUnJjA94q78du07sW3TrI+EvHAci6uhbHnI8OgnyY/X8KBP079u9MNA/+8xkmXngNXT2h6FJkm0adZwEDTpU9pk4A6rVhrhL/QRIzv3bfwKvFy+jxFZxSKbumt4szW/YxP1bAfPdM7quz8GilBXcqw0M/+zGZ+AD7KozBrfTcQSKmCvr7GtB1CVHMIOcdRg+KWI83IabG0ZRe0A3Q4/LlUlBVQ3btcVLODQiqifxDX0DUzCiTmv8pq59QWmKwbRWpcCkZCV5apnM414ega3yaR7gAI3F0vGsJffuvYE/hBloKN6CKKqIusDTaSF7SR9b4BE2OdfzcU8G80eWTqaM6jYRYmLwcAYmIMMQb3sc54h3iiCWJ/6TkeEGH0qCdBUd1lu2Pkh8+8V3cZmOwqIjB4iJG8vPRTirKlJA0jueXcqSkDr/txLWcNniM5gNbqezpYKCglHcWrWKwoBwAWyLGPbt/xvXaOyi6yLOjqwmo5SgZBzpOBNE9+XIiCO8fqHV0NDHNXKeZctGMDkRn5WKZ7sOZbcGZZcXmNL1POSWRVukOxPCYRHZv2k/3pgmkuEGzSEkJWgs2M2LexqrdcTzJBPevFpiw65hVE1cNXMJkviFtBRVsqmnibJONhxbVYDVJRN/eQOD++0kcOGBsJElwVimjZ7YjludhNdUQntiFIE1OikknZf5RHEmN3hLbiVoNCth2izjWi+Q2LaLwy3cg+Cpp6x/jqSf/CcCW/C0M24exCDpNjhzWmX5C2mVH1HT+0lBB8f7NrH/4fgBmnXchZ192DcFHHiX497+jx+MkLV5Gmq9gIGsOyUlnsYrOsJDCLpjJem+UBzC7hvE5RAomCvBJIq5sC8nmPNa/0UcqoeDKNqEkXiI02IYoySy/6TaaVpyPpim0Hv5PRkfXIGgyxfu+jJ59FlvaQiSjGawOE+fd3EDp9GwIdqE//XmEoQPowDEq8BEim/D72gOgecoQi2cblJvCZoYTDp755S9JxWMUVNdyxbd+RFJReP7Z5+jpMxYvZe4RSme+iSjrxEasDG2fRc1ZF2PNymf0yCCjw8OM6zHi0umH2MpUkiu++jWcubmTHafA5l/Bhv8BXQV3CVz2Z4Zp4o0HW4kEkogoLHb9nbqi/fxk2nQiSgtnOBWy5VOPoWswPlaKJmtkZw9O0SB1TUZINaL4ZzIxkEN8PE4ikuCCL11LeWPdadv5YfYJCPpg+3f6Rtd1doRj/KF3lG3+AW7jd8xmLwCxIz5qX7CTf9NteC6/HFUQeP3Vt9i9b4cx+OoizTPmM39pEy+99BIjIyMENRtt1hl0TBhjg89h5svnVjIt/go9B0eIDs0iEz01x9Vv75+kzbWScvVwjivDAruOJqqkdYF4wsX44AJ8hedS3JRHRkyTUBIklSTxTJyjo0E2Hh9g2FJCsnARusmgtbgiLeSMPYtVDmO2m4kqUaLpKJqunSxy9ZEmA/9TdD6r5twGvmn4E37ueOsODgcOY5Ws/GLZLzjDsgD/31pRg0niVoXR+QLtI50c8AfZWNPMkNeQHM9PxbnL3s007WeoWhSbtQwh+F+0vBplpn0tc1wvYWXcOLC3jL2Lvst/HrPQXlh2Su6QS0mzYPsbNB3ehSwIJH0FuGvqSWcyRCJGlH/+/PmINWU81r+FRayhnhP1d3ICKUy9LtYFF/K6Np9WvRwQcJoinFO6mXNKN+OxGPtJq1YGBpcyfugcLJGcqdpEH2SSOYKrbBee8m3YfN1Tn8czNnYPzWHz4ALolbm6fQNLhloQmpYgXnwdtsZGOmSNW0d7SWAyxibhxLwtAAs9Di7M9XJBrocS6/slqd9ruq4TDaUIDERJH15Hcft/4VANB83m9Jn8NvU5jstWRmu8KNOMiJ3cNs6lbWnqMzJpdJ50phCyzVTlOpmW62RarsN4n+ckYxZ4OxRlnX+Coicf46bnDcrkfVd9nufOPR8AjyyS1HRSmk6D08o/mqZhPuAn+pzB9GlJanQmT+SL2txmKptyqGrOpaQuC8QMO3acz9ZkDo/JX2V4UhFUHElgPhzk7rGX+FLZWoSUcd+8pc/jT/HrKUuUMU0x+i8q6LxpT3PMZCCQEpfEFaVJbJFe8sa24tVG+Hr6FoK4mS708Bvzn+m31hMqPY+80mkUFhbiyi8gZjIzksowmlYYSWUYSZ/6fiStMDFZk+i8oQw/OZhEEeDzi+wcdUuYMmmaO9q4sOVtzu7biTWcJBOTySSkj3wk07KFmDeHbDkb2eZDdOXiXNqA6+wGTCXFhkDTB0TTMprOSDpDsGWMrOc6EXTYNTeLtfVOhlIZ4qrGuvn/+rwEn4Cgj2XJWJTf3fJZRFVFtlYxXLqMGd58zhlTEYFWqY9tJiPcHnU7eKVhIePmE8fwxKPUjvZxw2APM196AS1sLLD6s8tINF7Nry9ops0jMT+g8Mu2zRziHboOZRBljcZpPTCazYGqJiJxYxHkdAaoqtiHGTNK0omAF7fFh4MsxKAFLWwiWPwOSecgQiIbue0qEik3gSQY2Sk6uqCRcki8fGYF3RYrsq7xucgBGqLHSGdiKJkEmXQaKVCLOtJMWI6yo+wljufsB8CkSTSPlzN9ooKMbifDCU/h9tztOAQ7ValCdrsO4jeNn+hMXSJLqGdO1hIuLj+DMruTZDJJcmQEbfce5L17sR5pQzzJ667IEiMF+QwUFTNYVETKYkFMxpAiYYacHvZPn8OxiulTCeX2eJS43eCam9QMixPHuCT5V3IsPTT3KhT4A4Sdeby64m6SkQQTL7yO6lcQhSws0+Zizq8jE4bYWBohbsasOBARabSJVFkkdF1nd1xlMPOeR0LSkZwaoktDmnrpjAejKC0uzIox+MVMYXor9lN/ZhHnDNhQfvMg8ugYCauVly44i+0lR6mKVJGXzENHp9lUheKo5eszraQkgYVDQX7y6G8Qu43IkWA2473yCmzXLWdP/03oukLzrL/i8y0jER9j65u/QrW8jGQ+1VNrMmVRUvJ5dgwv48DPH+bzbWsBsC5eyPbbz+ChnqfI78unZqKGtJQm/1wPxeIhfpq4mgGhFCGjYdob4Nx8Dw98bh5tG97kzQd+D7rOzHNWsvKWO9HGwwQeeojQ40+gJ41q8n9a/i2ytWxK1BMTpI7OqKTTL2n4TSqfnvECOVXrAPAOnMu0om8xYrey/vGjaIpOQZWH1V9qRJJVXv/jb2jfYST/Ny0/j4LFnYyOvYwgmKhz/g/6cz6jmNviQja3hhjrjSAIsPjyasrnOnn1hWep7/0bczl0Sv+oriLE0gUIRc1Q2AyFs+A0dQhGOo/xzD3fIxmN4MkrIK+8ivy+QsJOKzvkDlRBw+0aZmbjeiRZxWzOZe6cp7HbS43jRNJENg8Q2tZLKBNhXIgTtseJacPkbt1AaXcPlupplNx3H5bKyhMH7t8Nz34RQl3oCOyPfYrtketw5rioWxmgdssX8aaTJM0i+xvdkxE/L/rwdEZH4rhrurDZT6VVWq31lJdfT0H+Rcjy+ykn/1v7BAR9sP07ffP7nhH+u9NYFArA6hwXN0kvkRz6Awg68qBA1oMyNqGInFtvxXv5ZQwOB/nHo88QVQzpYKfFy2VXX0J3dxebN29G03QClgIOCFX0TdbhqclzcscZUTyJb5MYd5IYXoISWk2gV5+iYbpKdpE/7+/Ik+NMKlzEaMc5jHqKqFtazMLy+RQ4TlBf9veN87PXjrCt05Ddd1gkzNUehoqsU6prkqbS3NvBkkA/V11yCdU11bza+SoPvPM78tpSFI/Z0ERQJA3VaadyyWKmzZtDSktNAa35BfOnxBq6wl3cvu52BqIDZFuz+f25v6cxtxEANZom8Ohh0r0RkiaBJ84v4IFMlIwOJk1lblcbK9W11FVvRxB0EokSRo/eRPRYLpJmpfHsEs64pBBp/yOw5bcQM8ohJOxl/KJvIdtr5tJTWEVdTxvz92/EnEnTsGwFdSsu4LGn/jklvJKVlcUll1xC5eSzHlNUft49zPreLazmRebpOxAnnRWecIby/gSWQZnD46VsSjayreBcBh1eqt3bOK9iA8VO4/7QdIF9I7M4fGwFrrFpVGUkzJNLV0HM4ChswVOxDWdhC4JotEXXJKJDM5noWUx0sAldM6GhkxAgKeikBR2TLmDXAV1AEHRSJoF3GjOE3T4iFp2iJEQcJnqcpy5w6wSZc2x2VnlczMhyYLJKTIwlGBuIcqx7nKMDE3QF44yqCkFRJyhpqGKSr8rPcJP0GpKgE9Sd/CD7Vp5uvBgEgfzeGGfIVqb5HHh2jZMaiGN1mrjyG3Px5J5e5Oldi6saLff+CvfDDwHw58/eQvJTl/HaWJi0rrPE6+RvjZW4J6W0J9b3MvFGDwiQXlrC8eE43S0B0okTCTUmq4R76TYez/KwSzCUjYstJu507mXT60dYHzDUEj8vvc5383cQm/8D1u8sZKjtXYEtnbftCq02jZSqIeqwMCVz+9IqzrysGlEU2N01xo1/20MkpVJrGuNx8QfkTqq5pjBxkBnsYhaj5OB2uykqKpp6FRYW4nA40HWd5MGDTKx5jbG31rPTk80fr/gsd45ks2JEodsOj5xpJZqdxVhGZSSVIZJOcFP/M3y15xEc6QSpuMxrljNZb16AazxKQXCMQv8Y+YExcsMn0gM+yDJWG5H8fCZy8wnl5jGak0dflo9jXh9t7mxK01bu353AqsFzJSZ+Um85JerYdVYTto+hKvde+wQEfQwLxAL87eu3kMZFKqcUSTBTZomz07uU6WoWnS6JdmmQuZ37EYGO3GIOVVTxqcA6zji0n2MTZYwWGNEdn9XK8okIwiuvQtqI4KyvX8rPbr+NtCzyH0dTfL47zXDmKC2j20lN9LKkYwBNsrP/jDPpLXSi6e8uHjXeSxn6uBa2Oni1cTETdieWTJrzD22ncOI0SaeAoEm4wrVYUrkMuTrZUvlP/JM5LPaMnZmhmZQk85jIOUaHmmDIPkRaOqHoZtUszIs2EI41sHViGmgnEk6L3GmaC8ZoyOmkxnMQk96FlkpjaRewHhSxtohI4wIZUcDvsjPqtjPqdZART15AQzA/mwMNS2ipbCZtsiLoOnXDPRSMvckR9xZKrGm+nJfCrGg07AqTo6i86rDzzVzfaatsn2KawO3D13JJeCkaOv+07aSdMM6UF2c6C2fKiz3jnqrZ8EE2YfUjzA6xcsV8GuIuRn/xC2IbDT696vHw2llnEnM4Dd6gKKIIGXbk7SRhjvLViRsRpWy+UldK0mxh9tFW7vnL78hdegH5d9+GqTif/QduJBjcRE7OcmY1/eVE/2gaLfffS1t6EM+0TaBZkNOXU1xyJWUzCnF4LDy4qZP1D/6du/c8jVVRGcyGn10poRbls3xoOelwmsKKSv5SM4eBtEqWHuC6iYd5bNfVpFWJy2cXc+9VsziyZQNr//BrdF1j+hnLuOCOryJKEsrYGGN/eYAfHM7wRuk8bJkkvwrvJ2v+cvQ1TyF07+NvZ32GtQ5j4p+GyF1Fu3E0PALoxHtuoW/nfOO72bmsuLF+KtFX13V2vvA0m596lNJlg/jqwghINDb+gdzclUS3DzL+ghE+d15QwZ7uyFRNgrTdT9h5BJOY4kpepcaVQowY6nnINlh4C5zxldOCn3ePPXy8nb1rXuLI1o2g60z3LGBW9jmousLa0ScZzXWh2p3YbGGaZr2O2ZxCEMzMarofn++sqX2psQzRrYNEtwyiT1Io9Uwf8S1/RBsPIDqdFP38Z7jOPSFMkAgEGf3LnZSnjATikDSNpxvykWzHqCNDc8sEjrhKv1TArpJPEcp04cvvwuV6/7Muy27qZ/yc3NyVH3of/2/sExD0wfbv9E13IsXlb+5geV0lt5fmUWU3nFGh0A4OHfoy6cwYQlrA85iIfbeEXFRIzq234brkEl78x0YOde9EF417bVbjbJqaZ7JmzRoCgQCaLhAvmsO6YQvjCQMMnTnNwacqHyRL3AYIlOR/FSW8nMGxnyG63gEgGSxj6MiFbBaHOJj/Dhn5BD27zFVGnXc2Pf0F7G33oStuzJLIxfOK2ZAlMKCr+Ewy99QU89hggM3jBhXbmYyz5HgL104rY+WKFaiCymNtj/HEjr9S1S5T0+dEnowmyy4PS664ljkrL0A6Sclw/+h+7lx/J+FUmDJXGX9a8SfK3GWn9Kee0Xj5xTZ+ZEvRbzf2t9Ln5p6aQiY6f8rIiEHJGhmpoqN9EfrkXJzjzWfuwuYTOUSZBOz5G2z+DUSHCaTsPN7dTEYzth8x57K78Gwqayqx+o+QnRxEmpyGrr76aurr609tl6rxzj9a+YErTdg1wmpeYhkbkDGuiz2uUN6foGAkhZYQifk9ZM68iYFlN9M3th0l8jguYd/U/jpClazrPpd00sPCol00Fe7Bbj6hNBoIldHfu5BA/3ykpAerBjZdmAJN/xvz2wUOl5hpLzEzlCOfMu+6JhRyB5MkxxKEY2nUDzmM1yKxUDjMN/S/UCUY65C3shcysPx/+FzDnKnt0gmF53+1F39fFE+ujcvvnovd/eHRJ13XGf3FvQT/+ldeWrqC31x3E7ogcGGuhz/MKMd60iJb13VC/2wnvm8UwSqR96VmxGwrg+3jdB4Y4/j+MTYVJ3l7pp2kYEfUNVb4Rb7ujlI/8hukzje5X72InynXoiNSl0qyKuHFgoAggLchi/sCfoYSxlpKAFbKNmYZvgtKGrLJPa+YW5/YSySlMLc8i4dvnI+bOJk9j8HOBzCFT9Sc66GYXcyijWpUTqyfXIKAd2wM78Ag2cEgWaEQNpMJ28oVvHjOJSzbopGd1nmsUkabs4+l6adQMqPk5l5MVsktpJMy6qvfpbr3ZQBCgotHy2/hDfv5jOkCUauIatZwT/jJC4xREBijyD/K/L5RaodHIR5AT56eeXHKtZGtSHYf4axcdtYUkSgohKJCbCUl5JWXcXF1+Scg6MPs35lo1q59lu3bDoIgICgZYtkS3aUFtHrqCJhO5IM0DA1wZvtuBHTyFB9Z4z7KzNtx6j2khmoZKqtCNVuRdZEck0TWgbfRj2xF0OGVxWfzy8/diqTp/HVHjIYJo7uH4p0MD21mWstmBCCVXcKBJefQ5Uyftq2CoCEKGoKoIooKoqgiihpa2oESz0YUNQIFCs/VnU1CtuFNh/l0/7PkKmNk0jYScQ/uWBnFajYSEjo6AecABeJ+1LFCuqKr0RA4nr+ZvTXrCaoGwpcFCUU/ERI2q2Y0UUXQBb46+BnOjiwAoCtvB886ejgUqqEzXHESoDNU7CrcfczwHaUpf4RqS5pEv51Aa4rgUOKUDB5ZVcmJJLCpCY4XxNhdqxN054B0IW21ixEEGZuiYlYUZDUFcoQ8a5A8KcCMcA/fPPAkEjq/tc1jg6cWR1UJmUyc0Gg/WiqGpCVxOawU5Bdwbm8zCzqNUOsbDXs5VNqDruvoky3SdR00ASlhwRS3ISVsmOI2TDEbcsKOhETVgmxWLz8LUyTO2H33Mf7Pp0FVQZbRzj6LlywmUi6vkQwqCJhFkfTIQd6Z3oPfbfDHLvIvoXGfxHc+/TkSViuzA2l+sy+F0yQhNqc5av0ymiXNooWvTRU6BODtn6C/8zMOKY1siX4XNXnqROApshL09fKm+jJC/DB3P5ckZwJUh5WS3/6WdO107v/LX1AVha1VM4nVNvCbgkNEur7H/tEafr//FjRd5OallXznwnqObtvMmvt+gaaq1CxYwoVfvhtJNvHnd47zP68dQUTnhzv/xrxBg94hOBxIWfVY6i9js93Dz0kyjo4oQL51mNssA0S7jTyUhmUull0z7320Q13X2LXlViLp9egaDG+r49xrfklRreEBnnirl4k3DcEOy8UlvLRlH4lOA7gK8jirvT+h4oqvwOzPQOc7sP7H0G8kp2Jxw+I7YNGXwGqMHeMjw7Rtfpu2TRsIDQ1MtSPXWsbZBdcgCiK7/GtJFSuce9NtHBsY4q233kKSIjQ2rsPuMAb90tIvUlP9zVNoAFpSIbptiOjmAbRYBi05TnLPX1DHDPpFzpe+RM6ddzDYYdRYiIXTTLNvZ5n3N9i0FKoIx6ocHPdlEYssJzYSwpo7gC+n74TAhS7i8Z5Fefn1WC0ltLXdTSRqXI/i4k9TU/0tJOlE7pKu64xGUqfUZPlX7BMQ9MH27/RNqrOTzksuxX3eSny33oq17gQlJJX209r6FUKhbQA4dzlw/T2NoAiYiorw3XYrQyXzeOXlN4hbDKeAzWpn1fnnMTQ0NFV/z+rOJlAwnxdaQ2RU47k8v2aIlYX34bZEEUULmpYCRLIdN2LVPktVcyGKnGLvyF52jexi19AuDgcOo3FqQoFdKKSpcD5b1XKCch3lzlyenDWNCpsh4f7KWJgfHBtgMGUs9otDo1waGuT2Sy4kNzeXQCLAH/f/kVcOPcf0LifTe1yYFWMhZHa5WXL5tTStWMXGoc18Y9M3SKkpGnMa+f3y35NtPdWxMZrK8P1jA7wwOg5AXlLj620pVhVZGZ7+J/zBtwBwyV9k1zOzSchjKK4AyXdrqE3aKaIKdgvs+zts/jXdgzF2BEop9ak86r6KtfET18okaFziG8UV7cNqs3H7bbdNCTLouk7o2Q7iu0dQzSIvXVXGr4JBzGqQ1cJrnC+8jqwZYNGc1inrj1M8lERWdTRNRp+2AmnuNUSKyukbforhkZfQ9ffnN6r4mBCW448vZmRvmIm2o6QVjbQoo9idUFmFnl+EpoCe1FCTKsloGiWpYdHApoNVF7BpAjYdbIKCVRCwKmbeo3RO1CLQXmzmSImJrjwTmnRi/BMSCtJYkvyoRoPZQn2xm+p8F2VeM0NH93Ng93Y0TeNg2TTmi/v5as8jWPQMmByw4gcw/4sw6SSNhVM8+/M9RAJJ8spdfOqrczB9gADOeEahJZLgYCTO5j0HeDvLoH1esmszP2uqxrtq1fuFJBSNsQdaSPdMIPms5H2pGclh4kAkzt1H+jgYNaKi05Qezn/LzMXq4zTa1yAJKhoSvTkVPDh6A0+lppERwKcKfK2igKYV5Xz7zTYO9hvzhNsqT+UWz0hLrIqbGJI1nnWkUQSYUeDikZsWkHfy+Kzr0L0Jdj0Iba8Y9EQgLbtp1xrYGq9i0Hr68i0ulxlvVgaHfQhrzM28jotRgS8stKN62riJ+7GSJIQPxb0czXse1oFOlm36ITWKAbwOUcm3ar/CrsLm0x4DoDiu8f1DSeb4k+iJIMfFIG97JpAjfnz+UfIDfgoDY2RPjH/gPt61sm3bcGR5P3K799onIOhjWGjYzw8ffJiuwiKO5ZUQcJ6ojC2rChX+IZypBHVKIZd1+tkkt6AKGoVqFrXRBjqSIiYhSr7spNAkkWVSiZRuIFD1MkJoAtdLMtb9Ij/84pd5Z+4ickNh/rktgVO0Tz100cQIUsvzKIMG3ztTWI9Yuggh7ieSPsKjM47TnVfH4v7LyU68WzVXx1Wym+IlRlRgZN+1HC+ezgN59aQFiVrZz928yHhPiv6+LJyJPJZlZpCtGzSYMdcR7Lm/pXJ4APNkUt2LyUsZCF+LrlvRpAihynt5xRckIYrk6CrT7WAdmI8rXI7TFWCg/G02x0SuGFvN5/wXAzDqbSezZA2aPY+joRpaRorYO+ikJ6BRlByiIt5DRbyHLOVU70BWYTFFldWM7j1IcW8/BaNjiCfVbpmw29nZMJutTXM5UDOdoNv7gVGeO3sf57tdfyEhmrlg9p854pz2vm0sgsCtnWk+126AkKfnuNk/w4VLknDKRkEwl2y8d0kiblnCKUm4ZONz1+R7syiipVKE/v53/H++Hy1qTFj2c86mLT+bvX6/IbAxCYCKi4u5+sILif/zn4w+/ij/WKzx6lzjPMuSBZwZP4+HmlcQRaApqvPbHVFcCmhiCq0+QOnFn0JzibQH29m/6/fs63ydfVYLo7KMpMlUxGdwR843GG2PMj5wqoiGKigMyxNM7znA9MHtOBPDdP7wx9yXgcVH96MJItfeeCP1ZaWMh/fQ0nIHb3dV8tfWzwDwrQumc+uyaRzbvYNXfv1TVEWhas58LKtu4o6nDqLr8MNLGriuzETg/j8TWb8X84wrkHOMpGgtHmT46Cv8qqCGPQUNXBwzT/KidfJmP0lW7Q5mN92Hz7dsqs26rnO0/QcMDDwOiPj3zqR/V8bIE/rCbTQtPx9d1xl/+TixrUNoaLxhOsiYliE7VI2iObGYNVbeOnuqgCi6Du2vw/r/hhEjQTthyuFo9mW0DegMdhw9MQaYLVTOnoeQ1JkenI1NdtIdOcTB9GY+fc+v8OQZiZtjY2M8//zzjI52Ud+wAY9nFF0Hl3M6s2Y9gNV6otBkbyDOM7t6OUOXKWsJofijpFqeJtP1tnGdaueyNe9aMrId0TVGyeI/4LX1Mv1ojNB4MQes04gVZMjL78JiOeHhNUUFyp0LKTzzd5jNJxw4mpbi+PFf0ttnUEEcjhoaGn6DyzkdVdP53gstrG0/yHNfvIyKnH9divQTEPTB9u/0TfCRRxj56f9M/e8891xybrsVW1MTALqu0tn1O7q7/wDo2NKFeP+oIrSPAxiJy5+7nTe7bAwpLaiysWirqqpi1qxZvP3224yPG9tWNi1gSzSXNw6PIosZrql7mXNLN0weWaKu9r8oKbn+fW0MxzP86Z3jPLztMIq5E9neidfXS4LeKUfSu1burmJR4XwWFCxgXsE8sq3ZxFWN+3pG+EPPCGlA1DSahrr4dl05S+fNRRAEjo8f55e7f8n27s1M73HR0O3Gmp5c7NrN7KgY5mhphLPKz+bny36OTT4B8DVd59HBAD/pHGRCMarafaEkhzvHReJrdjMw6zek3D0IghmCX6HtTWOsqmj0sfyGetJqgra2NlpbW6dqM71rU4CodhqezpeNPL5Jmtx2vYnfKldwRK4hlDJq7602t5Ejxklbs1i06gqW1xegbh40HDgC+D5bj63eR08ixTfb+3k7GMGqJ7jGvIFV+svoGSNvWVJECvviVIzEsUzWdtElC8K0c0jVLqPfGaR/9Hk0LUVe7ioKCi/DGS0h+PAjhJ97Hn2yxqK5ooLsL9yE59JLEc2nj6KkFJXn9w7w53eO0x2IT3a5xJVzSxA97/DEyA4y7tuxZsyUaiKftzpxpSAVy5COZwgnFVqtOodsGp25JjKmE3O2UxI5J9tFfWKC2JYNKOOG07WneRGveQxq5b3ZcT6z50fQu22y0xcYctp50wEIDcd49hd7SMUUymf6uOD2RsZVjZZonIOToOdgJEFv8v2O5Zu2vMVnHnsQAXCecw4F3/8epsLCU7ZRo2lG/3gANZgkPc3FQ2f5eHgwgAbY9SjX8hj/x1aM+52/IiaNCHx3ci5bIjcyrhq1gUYkheddCSLI2LUMutVKIq3isZn45VWzWD4jj95gnB2dQbZ3BthzaJT+dAZVgLKMCOgMWqCxxMPCSh+LqrKZV5GN02JEQlOHtqOs+TmW8U3IZuM8dQ0m/A568+ZyvKwev6oTCOokEu8f35el66nRChmTU/wyv4eYKLKvajpJ66kiP5KucMPRZ/k/w49MCTY851zOEwu/htVTSJHFRIHFhEsS+V3PKGMZhSVuOw+nnETXdqGnNZBFPOeV4zijiIlkhom/tiL0hkiJE7TPlkgEhmFwEHl4GPvwEO6xESRFYd7e3ae9Pz/KPgFBH8P2j03AoyvosJfzj4LVbHc1kjsapHZ0nOmBXmQxhi7opCWZ/aXTWeW3EonsQxFU8jQPy9ONdBCkXYmiKzbMAnjyj+Ip3Yfd6UfsPhs6TEwc3c0PbvsKo9k5rNy+iXvCIRJCPlatFkmYDOun+0gceIXMwD4jMC3oMFnwLm7Lo7d0OX2Fc5iwRchKGouvvObnya5dw+vahfxdvBFdEKgciXDB0f1oegBRF5itVDJLrUBEQLeCY9Zx3J33IEeMAXtcd6AJItlESGhu3hz/T/rSzQB4i17DWfcc5/aEEASRA3Wz2dCyiExGYto0M3PPLOLlwVb6Dvq5q+967JoVv2Wc0CVm5k2bR++B/XTu2UnXgX1kkicWbCoig9ZCuuzldNvLkbx5LJnmozHXRNf210BPY7e68LYdZsHBvXhi0VOvuUNmtDiXgLeIvuwCBvKLCHkdmKuDZAQTX9v9NPOTR+i0FHNl/W8IW1xkZBPpSSGLz3em+I8OY8D4VZ2FJyo+OpHzdObWNRYf2sdZm9Yzr+0grtoauPpK3nzndYIqpIpO5HnUV1dz5tAQkX88iRY3+sJUWsq+ixr4nXM743IUWZNZODaf15tuIGGxU6fF+e89R/Cn0hy2H+ewvZN2ew9JTgU4kiAxTxEY0BKk3EUEE0FMGSvF4VqaUospDtWhvFd5W0vSWu7kWIGZpmQLzrEBfD4ft956K2azmVRqlJZDd/DUfi9Pd3wKgHuvbOSK5hI6t+/k5T/9DFXJ0G8r4eW887k8P4e7vR7UiTTqRBr9Xf60qKON7yX2zsOgpkma3WyZ+zUESw4ZdN6wxlhc8k8Wz96GoENez0JKvFdgqaujT3qa/qHHAIH6Gb/A513F2j/+ho6dWwFoWnE+86+8njVr1lLUKlOtFaKiYjXfg4NO1vJHRkZNIEDTOSXklblw+ay4fDYsFo3uNX/m8Ntr6AqYpwr/CgKUzZzFjKXnoqkqW578O/Ntq8i3lZOQYmwcf5Zx/xDu3Hyu/v49ePKMCVtVVbZs2cLGjeuoqd1ITk4fug6iaKau9vtgv5Tfv32cp3f3oWg6JkngBxfWc5ndRnTjAPHt60jufwy0DKo9l95zl2I67zmSaSu9o/WYNQlfdgce7+iJa5gRKBhNUZrIxjXYbYwbZ90N53znfU6CQGATh9vuJp0eQxTNlFfczbc3CRyIPotk6+Ur0x/ki4sW/MvPwCcg6IPt3+2b5JEj+O+/n8ja13k3QcexZAm+227FPn8+giAQCGyk9fDXyGSCyJKL0pELUO7bjDpmcGuEkgqOnnEnR6OjxJ29Rj6RLLNkyRIikQj79hlUKp/PR+XcKmLjPyfH2g/AjqF5yGKKufmHqa6+m7LSLyIIAsmMyt+2dvOnDccJT9Lp5pZn8c0LpjO/IpuHerr50aH1yKnDZGeOkkx2v+/cqr3VLChYwIKCBeR5mvifrhBvjRvjoi2d5PJkiB+uOAunw1i4bRvcxr277+W4v4OaPgczu7JwpEyga6g2iZXXfZFZ565Ckg3xm9ZogruP9rF3wtjnLJeNn9eVMstlJxJpZf/eL5BWxxBTLvw77mR0uAoEWHhxJXPPr3hfRHpiYuJDAVG2XaKk/WHmcwABUM1uhPN+zIHci3mtdZS3D3QyP7kXs6ByUCmgVStjgSZxDiYuWF1D4VmlU/vTdZ3nR8f5XscAgYyCrGe4O+sA81PPkIhP5otqAlntGSpHYniFk6I/gohethh9xsWkLc0E/v40E2tfN6jYgLWpCd8Xv4Br+XIE6fSRk/eaqum8dmiIP759nMNDhry2SRLw5R4n5N1KsvRWUqIXpyTyx/pyzsvxnPL7wY5xnr1vH8d9MsGFWRxwwUj6RH6NoGuUxiYo9mWzLWW089tVhdxVnm+0e89f4c3/gnTEKLJ61tfhzK8ypgls6PDz/NvdDHgkAgVm/B+g2l1mNdPkstHksrPE62SOVSZw/1/wP/AAZDKIdju5//mfZF1/3Sn9kh6O8o9nWrl3mokxqzFHLJNbuCbza6aPp6g/aDwralYN+6Xb2d5aybv4XzLHKTnrV0SsUe7Z+g2ik+kCxU4zT96+hFLfqaDkjdZh7nxiH2lVo1owcXFIQkTgHWuG3RZlSjREEmC6Kc3MoTbq23dRH+jEmp3EMTNFTqmCO3Viso9bRQaKrAzmWklHHGih6cQnCgnHHQRUEynBwhWphTiw0iL1ssPUQVYwSPZYkNGiHPqqHUSqzLhNYZwRmTKtkWkdr3Bu3Mgzjgt20ku/gXfZHSAZz15bNMFFezuIqRo3FOfw3zk5hJ7vINUxbtw7JU5Ei0TqeBjBJhu1gPJOn9elpdMfCNI/yj4BQR/D+lq3Uvr0BVP/9+h5PK0s4xn1LIJaFrnqMHVV+ZidLgiNkJPpoCtrOjP6j6Kg4NNcnJ9uRkRgv9zNYakfVdAQVQuyasFmjeLK7sOdc5RtR5byj6VXgCjyuZefoTgeoLt6Gn53HSl3PmNWiVGrQFSCC9sHuHPbISypNLqWASXJhL2IUd9MMqIJRdfoyDpIe94u0tPn8oa0HIBZwz2cffQwmq7gVR2cpcwki0lE7xgkT/4Z5tTxD+gNAfJmMK4VsbO/io7xVYCIJauHknkPMtN/jOIRlc7Z3+WxvWF0XWfVqlUsXryYcCrMC1ufpmG9j4JMDgkhyR+zHyc90EPFkB0RAZvbQ9Xs+VTOmYdSUMP2/jhbjvnZ3hkgnlZPaYluk1BzrGg+C40lLr6ZDpL1zktMvL0e31jifSF4AFUUCXtcxMuTWEo05thGcUoJDmam8XpPBWImjSYIVHsXMd9r5Gsczg/R3+zBlF+I7s4iqulEFJWoqjKhaERSaSbicSaSKeNzDaKiRML0fpU5p6YyJx4iZ+NrFAeHyZRUTy1E5wA1zz0PaQN4WWpr8d16C+5VqxBkmUA8wLee+yrbVCMaWJoo51D5baStJUjpXryj/4OonRjYXKrGrFSKBvd05PrVNB15kyVH1xMXBG4pyOOA1cLiwsXc3HQz8/LnATA+EqenNcibb3cjBTNYTmKvaEKGcN5eFCFFdUEtlyxcjphUUcIJQgO76OmTIJlLDgLeSbDQnuhm58izmHSFCWsRn8m/Cpt4UsheAPusXNwXVCK5zQx///v0v7qFg7PuIGnJwiSrbLaE2DipGDVHOsRnzvwHHksE22YBMSUQW240suDgHAqcq7DU1WGprWPvlrfZ9M/HUFxZpIsq0QQBSZC4hhnYE/kIRMlbnUBc/Ck2/rOdw5uMXCBd19GUfrR0G2qmY0p9EcBhsVJqz1DjCpGTpXNMyWdza4KZWWdR712CLkPBXXNJiDGe+e/vEBoaxOnL4erv3UNWYfHUfoaHh3n++WdxuV6hsMgQVWkdq+N3B25F0YwZutxnp2fSs3rFnBJuKBdof2qYaRMjWPfeTzodpq+8gqGzirCVdpGb24MkTeYS6eAaF6gYDpPjTyOVLobrn4btf4ANPzUaMedzcOGvQTp1RZBOB2g9/A029G/kzQmZvowx2UuCiR+f8UMunnbx+x+sj7BPQNAH2/+tvkl1dhL4ywOEX37ZoNoCtjlzyLn9NhxnnkkqNcyh1rsIhyfHj8LP49tZQuCBh1H9fnRgcOZlHC5YQsR1jIxlHICcnBxmz57N9u1b8Xh2Ul6x36BYC1k81nYd7/QaHvdq73GuqXueuZW1tMa+xB/e8TM8YUTRa/Od/J9V01k+w6Df/Kp7hF90GxS8awqyubeulFg6zJ6RPewc3snO4Z0cGz92yvkJCNRm1eLLOZ8tiUb8opH/VBQN872SbBpdNgKBAH6/n7a+Nvx+P1blPfRNXQd0NLOVPZUz2FtQji6ImFWFc0Z7WTgxikmScDqPk5P7AqKYIZ3KoW3nJaTiXkREiiu9ZJd5kCTplJcoiqf8n8lkGBoaYmBgAL/ff0ozzm/MZeHoPxAmo8yULoSLfo2eV8/aTbvZsd7I8XszXcuAZoAFsySytCaHCxoLWTkjH89kcclgRuFHxwZ5crJ+UaFJ4qeF3eSGn2B8fOfUMe2HobAtTZHPjFk80R5NheiAlfEuO1Qvx/fFW7AvmP+hdW8+zHRd5532Mf644Tg7u97NPdSRso7gmDePUdGLgAFg7izLO+U4R3cMs+7hwwB4m1JsSbbTnV1AT04hAcepz0aOSebTRT5W5bhpdtkRgGF/Ly0b/8KBiSgtzloOehoYNnlP284qm4XGScDT5LTR6LLh/YCaRqmODoa+/wMSk84A26xZFPzoR1jraulNpPhW+wBvBQ3gVxrT+LrpEDmmHyIpGot3hzAJHtrtN7HhyGLUydpNVbNzmX9hJc4sC+9sfZ7/2eWna6L8lOOeoZq5ob6IabPzyClxsr7Lz9efb0HRdFY3FvDLy2ex7ekO2rYauVGWcgst2iA7gyrjNpkKdy/TvF1M83RT6enBZYohxEAOCDhHVQojCXLFFPIkTVpTBSZ6rISOOUgGT4CKlNlMqnIBxTM+h67rrJV3MWAy1hqFg4M0HTiIOzpBpkojVaeSrtUx1dcxOLqS6gOP0iQY68kJ1zRcl/0KoepsAF73h7mhpQsd+GltCTcU+YjvGiH0ynGYjGAiQs4XGrFOO/11nGz4FAXyX7VPQNDHMU1j9JfzcehxrIlRJN1YaGi6wHZtBo+ry3lTm0eayQJpOuRrGcoc/dQJYUQ9g1ezc0F6NqJkpdeSYYtjlCO2OBGrlZjFRsxiI2o23ifNlg9rzSlWGVX574NJ6iKnF29PC/BfjVbeKDTadqX+BNcHDlO25xYkEqgUACIiYbymP2KXtpzy+6TuJWGqx+ydhepsQjUVw8gBhl2vMlh1nOhIPYPbb0ZLOxCkNLkzn6cmew0NHRH2uC9nbbAMQRA4d8Fckv3ddO7dRSQaYW7xRdRg0Aoey3mVt3K387nq67l24Q2Y5Pcj+rSi8Xz7CPfv7+NYbxghnOYktW1EAWbmu5kT05gT0ZgupAnVDzDSv53Izp04wynKxsD6Hiq0LTdF+TkBBBH6BusZ0evRLDUUOc8A4FBoM62hzVgUFXsqg0sDn82BBwlbKo0YDKGHTq98oooicauN3oppbL/+87yRW8To5GXKD/u5dP9mAyroOgt37qSiq9toU3MzvltvwXn22QiCQFpNczhwmP2j+9k7spfQsSEOm4+TFjPYNBujOZ8l6VyKKTXArO4HWGyxcdXg21RnEiTUcwhl7iJp+ynV+okJcUIU+FJxGfde+wYFjgJ0VUeLGdEZJZzil4Egf0rHKAkonNsapP74IBFnKWnLBOGsgyCAOzSDIiWPPJNArizglYRTJrS4oHOnmCAS6+PSkVcxaRlyfaWct/QazFoKLRZAS4xjravC1tyMqaCA/kOjvHrfHhTBgj0d4NLvLMVTmc9Dmzu59/WjpFUdq5Dkxsa/M6/gRB0Rz+MSji2nDoKZ/Hx2zZlN3yS33pJMcF3FEGVDa/Fn/pu0NgPRZSbrpjoSeoyj249xfPduAn17UdInUTFFF5J5BpJ5OqKU856rrFFqSjDH4QXAX+1FrsnC5bMhySneuP8nhAa7cXizuOp79+ArOZGIrSgKr697i+HBv1BRsR+AvQNzeGvwTP7jnAIumHcVf9nUyc/XHkXTIU8RuCRuIstzDDFnLxZPgNyCTuwnKbyJej5l9maKN7+INRYFsxPSkxFSXzVc/gAMHYBXv2rwIepWwxUPgdnwsCmawuvdr/PnA3+he8KQ/jcLOkucMncu/BF1xZec9l7/KPsEBH2w/d/um3T/AIGHHiT8zLPoGWPAszY04LvtVhznnEVn1wnao8c9m/rqn5N4YSOBBx9C9fsJeWs4NPOLRJwxYu5ONDGDxRJlztwDyLJxTwT8JYRCF7Pygmt58Wic+zceJ5kxBrcsyzihlBeAQo+Jr51Xz2Wzi5FEAUXT+WZ7P48NGYpwXynP5xuVBaddcAeTQXYP72bn8E52D+/mePiEY05HRrd/inDWahTJZAiSDHWxqKsNq3L6el7vWrevgM3VTUStxj1fNTbAkmMtONNJQKeouI2qqj0IAoRChbQdPgtV/d95mU9ndrud+fPnM6e5Cc+Rp+Dte4xnVJCM3MOzv8nLL77Jntb9mHQTqmsRG5Do9Mem9iGLAmdU57C6sYCV9QVkO8xsDkW4+2gfXZOJ9BfkePhu4RixoYcZG3uTd0MP5mMCnk0CeeEk3ooE1uyT+stVCLOuhebPQE71v32ue3qC/GnDcda1GZFpXQD3PC9j2YZT68r8LO6tK50SHNA0jRcf2MrgvjQ6GuGsQ9TOKea8887jD/4Yv+s19vNuzZ53zSwIiAIktfcvUwVdo1qP0JRXTG5QJ75uiPxxlVVX1TLzrOL3bf9Bpmsa4089xei9v0SLxVDMFl79xvf4c0k1SU3HJAjcqpu4ev0AQ4u/iWIdZ1pXHHH8Qt48fjFJzUgzqJyVw/yLKsktNf5fe2iYu585QCSpYJdj3NTwBEd2n8M6k9H/tWmR1XEz7SaV1+wZdAEaFJnLJTs2mwlZ0kgGwkSSZkDAYhmgrOJ+bOIwckBADghIfgE5AJJfQEye+qwJkoanPEFWTQxr1onIWyqdRcI0H6XobMzl0zAVlxA/BIkDIUSvme25x2npbTeISLpORXc3M1sO4ZhksGgmncw0nYH6cjps0/ms8hw+YVK2ve5SzKt/Ap4S7usZ4Z7OISQBnmyaxtJsF+E3uoms75tqi6nYSdaVtZgL30PVG2uHTfdCPACfefZjX8uT7RMQ9DFs4FgLxY99eIFATRfoEfLZbGpir206feYChq05hC0ezDaRhMVC3GIjafqYg+lkfog1leSMA7spCIyROx7EoqSJFthJVRfxbMkZhEx2ZFXj+rYkF3amMaPhUYKIQpIxu40fzS+mJduKpGn8oONNLlF+jX28lHjsyyj6ZA0dcSNe058RSZLWq0lrtaS1OtJaHSq5nFyUYdwRoLv5L9gcRk7EFpbydPyLrNitUT1sPEC23KOUz/ors3u7eCe8nAPCDARVxd59GDGdQjZbKG+cTZ1jAa4+IwK1xbWfXxY+Qq43n5ubbubCqgsxiQZw2xWO8dueEdYFTlSwXu52cKZmYvuWQwwPZyjATi0SNYiUI9GLSio6yqztv0WOjoPTwb7rVrJjopPSEZWKMR1vaBx3OEhF+Rh5TRE0RaD/0ErE6XcBkOpYS6rjFchkED7i9ldMJjRfFqbiYhw1tbhmzMBSVoaptAw5L5d9b65h4xOP0JtTxEhVPTWhMQRA0DSWbXiH/NFR+prnYvviF6lZ3MDhQAv7R/ezf2w/rf5W0tqpfOWGRDUxIU631YhepO1nEs6+AZsS4I29d1GTGmOnJYte5XZWp9djl7aj6wLD9s/ilfZhi7YQFEV+mbeULwW+jR7NgA4q8IsZFp4pM+7TW46luPl4Gi3cz8SuvxK05dI6czqj+RqCJpPln4M0Gb43m8DnibNbm2BDxsuIlEFFxqvE+cneBzmWJZKRJdzxFAs6BzGrpwL30dqVtBZdgo6IN9ZD474/4Jk7k7IHH0AwmTg6HOErT+2nbWiCS6at4dJpRqg9rTqYyd3YjsdJtR8leeQonZk0u+fMIS1LiJkUZZ2d5A0PkTKJZOwSKW8OCdFFQomR0d5fXNhid1C76EwqZ5+BI6uS6HiKSCDJUMcgfW1dqBkTouTCKlg42yVjFgU6UyotidM4I4QUWiaEKCWoXTCLvMp8BKfMy31+njgwgC0T5vqy12iq3Ywg6ESjWVitEXy+WYTGYmx85xrWaE7KTCMsKdhDRcFRsrKGTtT0SYtY9kl4D5XgzvsKFusELuk57NMUhKsegNFWeP52iAyCKMPZ3wJfLTx/MyhJKF1I5pq/89LgZh469BB9EWPy0VULnlQz36rvxqYaya7T6+6huPjaD30WTmefgKAPtv9XfZMZGSX48MOEnnoKPWHk+lhqqvHdcgup+Sba2r+JokQwmbJoqP8lWfYFhJ58isCDDxKLqhyq/wLj3hKsda9QVr8OWc6gqjKadjUH9jtIJJKIosiyZcuobpzHr9Yd49m9Bu3HYYpxUdXrnFu6jdLiS6is+BK6uYTbWrt5IzCBAPyktoQbi091KqiqSigUwu/3EwgEpiI7gUCAQCLAmG2MMavxipqjIPiQHbcxlG1Eo8xKisbYXi73WjmjbDGl+aVYLBZUVaU9EOLu1k72ywb4cUfGOXf7Whpi48w6bzXFdXX4g38gGjWiMDH/GXRsW4mOSH6Vi6qmbGIHR0kNR9EEDanchVzqQFXV0740TXvfZ+FwmMTktRAEgbq6OhbOKKXiyJ8R2l4CQHeV4E98gSfTGgExSllpGZ+/4fMc98dZ0zLEay3DHB054fiQRIHFVT5WNxZy1oxcHvOP8/veERTdyKn5VqGXVXueZ9D/BJEaP5O+WuQhcG92U1ywhKzSCPLYJoTESaqRpQuh+dPQcNmUIMz/1o4MT3DXs6/Q3ucCRJRSB8oMDwgCs112/tZYSWpkiDVr1jA8NIwrPB1rMg/ZInLlN+bxQHKC3/QYAKjcaiasKIwrp3f8CkCRxcRCp4nLep5hyb7f4dAS4CmDi3/NzrYqdr3ajSDA+bc2UtWc+y+dS2ZkhNf/cD/31DbTVWw4tRaKKvfa2ql553u0ZtcxXHkEUzyX8bfupC9h5HpWNPqYf1EleeVGX6YVjZ++1sbDW7oBmF3q5a75r6JFn0LSbez78xx+X3klqijhQyQwWR+rKSVyaWwUr6kVF53Y04NYE+NE49Uczb4ZRXZgTo3TeOgBPJHu055DyuwhbvURs/mYsPkI23yE7Fnk5MSYl7WN6WxCmlQeVGUPkbIrSEz/DN16Ad5XunBldAZVjV3xKLGsHuKycW0kQaA+maR2yxbk0bGp46mCyEszl1BSF+LT0jokQUeVbEjLvo6++E7+o2OEZ0ZCeGWJtVYf8rOGw8PWlEOyfdxQS5UE3OeU4jq7FCHQBht/Aa0vMAWH79gFubX/0rWET0DQx7L1r63jn22/pi5Zi1NyEXaA3w5Rq5Mxi5chSy5DllwisvNj7c+maBQkdfImX/ZkhtGYQk5axxtLYolGSVrg0bMrSJskFrcf4TNr/0ltezvyJM1hoLiIlpn1PLfkUjryjImkdjTB1eufQcxOILsVHmi8jD5HIU4lxkOHv89ZwQNMKNcTUS8HJBDGcZgewC3sRtNtjJln8OvoRRyjgplZDlZnedAHB7FldnGw0MSRkiSLXc/hEGIksPIwt9CrLOPcuMCzdpWa3jSr98UQVQFBTpI/65/MFN9kU9+F9FOER7dykWMRWeX5WAqcyLl2MiMxJtb1gqrTax3mB8V/YNgcoNhZzLKqz7JDm832CQMAmDSdGy0OPivayQmkSA1EUYZikFI/qKtpUZMER/YyUZxgXE/ijEapcblxeFxsjEXISGas8Si3JJ8kOztCRitlNP1rUsc2kTr09Ol3areRcTmJWM2MoDFilYm/p/CbyWIlr7KK/Mpq/H099B46ALpOQXkNx+wedEFA0DTOWbeOXQ2l/POMaQSd40YFcmX4fYd0mVwUOAowS2Yi6QgD0QGKkrk0xKexNsuI3mlSAeO5d1Kiyvz0wLd5zW/nDksfFeYIOiaCma+RUM9EIIbHcjdOoZcRSeId6TaWTFxAWoQfzLbzZo6EoMN3YzJXJ1Uea/ezI6IgpMN8a/f9SGNDvLViOUGfD/dEhqKebMazpqPKpyZJBkWNHllllvgGy9a9RULW2TmtiLQs4Ubk3IIKbE4XibY22uMVdFZcBEDe6B5mHHkUSTNAtaWujpzbb8c2uxndl8uT639Esfx3AN46fCb5yVGyGMcknIVFcTDQ3UlyIoygZD62oKssyNgEyM4roPG6zzBtzgLkkzjG8Ykw7/z9IQ5vXA+Aw5vFsk9/Ee9eO+pwEo1hAuorRFQfEVMNEXMtkajplJoRAGl09lkUdloUkpNqnnmayAU2G9OK1lFQ9U8kSSUS8TEx2EDg2NngayendB+5eV2YTCdJz1ubqKi4HvshCyPf+C/0RALB5sW24HakrEpElwnXmSU4FhYgahPwyn/C4RfQdRmteBl64+eJr/8FL1iSPJqtMSIZk55ZdVAbWMaS+DIura7ArCbolv5E3LeTpvInyZlxqnzvx7FPQNAH2//rvlFCIYKPPELoscenRFlMZWU4b72M3pJXicQOAwIVFV+iqvLL6IkUoSefYvgfD9J3pRlTjZHbEgnnc+ToYpJJF2VlZciyTGenERkqKirisssuYyRtZn/fOGdXjjE29HuCQaMEQETw8jvTzzicycEiCPyqKo+5WuoUkOP3+wmFQnzYUsPlcuHz+fD5fMhemUFxkGPpYxwc0ul0nU/I6QXAlhjENvEws11mLq+9Cr91CT/rGiauasgCnK/EqHjtSayDvQiaimhWqV49hj0/BAhMHL+ewT3LEGWRs66ppf7MIgRBQNd0Jt7oJrLBAHv25lyyrqxFkD+eNK+iKBw5coRdu3bR09Mz9XlWVhYryzWmdz6EOGE4ISLSQh4R5uBXrCxdupTly5dPbX9sNMraQ0OsaRmeyr8BgxGxsNLHnOlZvJEO0yIZY1jD8Xa+9sQDlCWHSH86n3D1AJrJeN4tLQLex2XklInsRbl4yiKYM8cQ3lXyM9mh/lIDEJWfAeLHO9f3WkbNcM3zd9ByLB8lPB8ly06mORtMItZ0hgtatpAXHSfpySZn7iJMGxRMg0nGHSIPrXATt556XFmAOoeVBqcNuygyllbYOxFn6KQagyKwwJLhvM5nOH/gZaoSA+hN17Bl4kYObE8gmUQu/XIzhdXej3UOoYzCPceHpiKZnliUL7/+V24UX8SWpZCwimybl40uQtG+u5BHZnOsyMWcS6eRX3ni2e4Lxrnzib0cmFR/u+WsKu5eVYckZNi77zOEw3uxaD56f+/jp9NuIGIy1pYXDW7jtj3PIamnf0bi1hxaGm8l5ihC0BQqg1tx6RMG4DFlE5WyiIpeNOnDnfFWIcwM+3oabK/jkUemPt+oNvKWcjnX6/NwIDAmC9TcNYdwJsSbb75Jd3c3ABaLhcUzZjB93M/E5pfI7DuGGNPp8BTz3MJlfMn7MgtEw5GekXNILfomV3uXofVO8KfdCUwaOBYX4r1kGlokQ+iFYyQPG31usvrJ0n6MWZyMDE+/yMj/Kpr9sa7he+0TEPQxbP/gEOcfHfnoDQFPJkJhaozC9BiFqTEKUmOUpEbxpiLsTM0mnbLgUdKcn56HT8/CQLGTBcuETkLS6/QxxojkY4dvHs83rkDQdL7w9gClQ2HKO5+kbOjY1OIubZJ59vzV/O28K0jLZrLT43y15xHuK/s0I5YcClJjPN7yDcrHLYxn7gKxBIBI3jaGax8nvMFMMmSmS89nSMsDBEqzrORkWzlkt7Mvv4qugnI+LT7KORgSod1KJRuPrqLwaIDcYABZFujJ9/DkqmtwJwQ+t2EYT8xYEDsKWiib9hj7jp9FBBelmpWV6SWnVK2e1HVA0CEpZfhp8d/YbztERaqIqsR0KmPzmZ4qoCIjcrpHN41OFxrtqHSgMoDGKk3iXMGCPEmz6NTSDPdupa7lacyqMUjG7Ta2L1rEWF4eM1Q7V4p/QhKChJKzeSGkM6gEEBUNdwJywzrlo+BOnKYBgO52k/ZlEbbIDGeSjMsiKatIQ9YoueYYw4NZTLjrOVRmeI5iUoQRbwvHsyNMKNH37U8xFZMx16Cay0GLYU4ewZRqQ+AE4LOLOjMEN8vHruZB1zMETWFAIuq9mmrTLJ7cdRc+3U9Ks/Bq4EsEOItsl0RuCtzeGKXyHfgyQfplE6PmW/mvyqXszClAVhW+88RDnL11AwBJycT3Ft/MoZwqsuNh7l//C7BKvL5qFYrJxMyWFuo7e4iVNhHy1dNhq0XTHKdWJhc08ssc5JRZadv4d+LjHWQXFXP5t3/M3rV+Dm8xOM11eUFKRt4gfKSNeCJO0iSTMskkTTJJk4RtSYycJQaffWB7HmMHTiicnc4EQcRhASdhHKYMir0cf08ARypNjiBTIHlxV12PxZ6L4m8nsfW3ZN/4WfK+/vXJRY9Gy9tvsunxh0nGoiAIzFq5mjOv/SyJdcPEtg0h2GTyb6lCPnw/bP8zZCZpK2VLSJ3xXSKOWQz1BrjvuQ1sFrzEJ3NwcnSRJXGZ2oyIMNlXcv5+ypc8iMmUIh53oWkyTucJumUq42FP3wLaB5cwPauGWxZVYPd3kt74D8LHLWiaHUw25PwZiNZJL7sAgkUCQUBPZUATiItJ1ng38ZzvLUKysYjKzni4IriC1aEzservp+QqpgmG8mQW/8eqD+3z09knIOiD7d/pm0OROD/tHKbcZqbcZqbCZqHMaqbMZsbxnoR2NRIh9PgTBP/2N9RJxTepOJ/ElwvwOw05+CzvIhoafkMk2krb4W+QzvhBFfAfuoix9tVkLMeJZo2i6jqSJFFbW0tnZyepVApJkli+fDmLFi1CFEXS6TQ9PVvZ2vEa98orGTPlYFVSXNi2g9zg6WvSAZhMJnw+Hzk5OVOA5933FssHU8UPDxzlv9/Zx+acKtKTjAtrdDuKuQDFXAHAfLeDn9eVMMNpI5FIsHXTJlrWP0H1/J3YslKoGYG+DQ3ERi/GnTudC25tOmXx+q7Fdg4TeuEYaDrmCje+z9YjOd6fA/phNjo6yu7duzlw4ACpSTU2CyoXay00iBsRUFElG+vU+eygmU9/9gamTXu/imm3P8aaQ0O8dnCI+OE2VvTu5uz+vbgycV5euoIHPnUtcZsdWdf5Ur6Hr06vQNZj9Bz5Ez0jD6ILKmJcxPOYiG3/ZK0lq4qnOk1WbQaT+aT5yVtugKHm68Bb9r62fJT1Rfq46qWriCQFcgJX0Z+YTnxOLrrTBKqGCchMUuNsKY2b3pwgO6bR55N5fVUW5+Z5mOWy0+iyM8NhPaVuDxj5SC3RBGv9Yd7wT3AoeuqEXRPrYVVgM+fFWhETy9nR0YzFbuLyu+eS/V6q1Xv2++xIiB8cGySQMRxb12Wb+G7rL/C1Pw9AWrGwZXoNWtEw8ZEZ1B26G7sqQp4Clw+jilEUJcrG4zK/3FRGNC3jNKe5c/5mZucfRVViKKqxja4bzi5pFJRf5/Hg9E8xPdjL1R3rDSqgqKNmCQjZDiyVVdhrm3FWzcJcWo6eW8CG5wfpOmDMk7NWlLLksmmIU5RDnXRCMV5J428qoeIPJmgfmKB3OMqQP8ZYPMOIrFBl3se18jrOFfdPFekdUhYQVb6NDZlEno1pX2pGsEgcO3aMdevWMTJirJfdbjfnnHMOMxtqGdr+AGNvP0H6cJx/iKsRKiW+bXqC/EmJ+VAoj4DrHqxKIS0FMsvvmI95MkdL791B4qUXGe9fgoYHUHEVHMJ95TKEksZ/+T482T4BQR/Djh4e5OzhESwZBXs6ga4GUDPjqJofM8PMt/Vxtn2IfDGIKxOHgTQlwymqTvJIjEoSWyweWlIXoqk5SCisUMspzUyf3OJE4VOz0ILH9CgWsY07pn+HZ/PPozQxxJrdt5HOWBkPWdDaFUwjKnrK+E1PQRE//sJ/cLykYuqYpRP9fHn9nyjLnEmFawmiIJJQouwJvoF56Vt4ymOkIzJHn6tETcrErXaOVczg6LSZ9BZVoUkSFXond/Brihg0ZOfbyhjfYkfQ3u9jb62Zy5rll4Gu87kjKcoORRE0EdEUwzvjGY6PlqBgokEbRUlfTB42yhCxvcdf/65sqnAaP34SnS5UWlFpR+OYrhBQk1jSMZypKI5MAr/NS58rn7JMmq/GJpjpqcAqGP00rCsMJY/T6OjDWVbEqLybrjEPjeGLsYmHyDF/BwEdPvVnkjMv45D/EPtG97FndA8HRvZjCkWpGNGpGIXyUZ2KESgM6afkJ71rillnvEShyyvTXrYQ2WqowB1zH+Ng9kH0yR/JgozD7EBRFaJKjIy5hpRjCSn7fHTphIKOWU/SYBlnZZZE2fB38OoBamq+SaH7U+y9/0l+6evmgHsMTcoiT/cwK2MhYCrguDSDcauVmEUAQSB3XOEzGyLkpoc4v/DLFGlpOqxFXDrnTyRUCz+6/1fMO3LIuAY2G3JeLum8Ir5WuJI20YNPVHgktpm+o4fYsWghgq7zuauvprKhgW3HA3z2oR2Iqs6N1QUMHvGTl5DI1t7rPUyjpnuRLU50vQDQEdlOYnwHun56mkNuY4DiJUbYfWhnLv7d2SQkGyPWHKKyA8EKs8tbMMsmpjd/hVmNTTjWfwOx7QWDBnbVIzDjIjr37uLV3/2CdCKOMyubi677MqyLo2dAGT5AYuf95H7lLjh/JW8++EcGjxqJurkVVay8+Q4Kq+uIHxgl+A/Dk+W7oQHb9MmaI9Ex2PxrozaDmiKtSzydfSv3TZzFcMw4L3cmzJLYAb71H5+hqLqeSDBJJJgk3B+mtXUfYrwb75xHka3G4kPXJGyjs8gZOAd7oOEji/J+mEXEOC9lv80L2W8TlQzudn7Gy6eCSygKnkMKM+hJcqOd6GqCjJZGN8dxVoWw5Acpbvgypc2L/+XjfgKCPtj+nb55djjIHW29p/0u1yxTYbVQbjNAUbnVQoXNTCkapheeY/yhv6KMGZSV5Dl2xq+IoYkZRNGKphmCBnZ7NfXT7mHsH228s89O0pKFxgTYdxNwGwuUrKwsbDYbg4MGNdfn85HJZJiYmMDv8LCmcTFxixVnMs7qlm1kxyOAhsMB+fml5OaWTIGcnJwcXC7X/zopX1VVXn5nI78dDtNWUD4lOiOoUa7MmuC3cy5APGnf4fA+Dhy8lUwmQDpupeu1EhJ+A8y4CkpYeePNVMyac9r2JDtCBB5rQ0+pyDk2fDc0YMqxvW+7j7J0Ok1LSws73tzC6KSEci5+LjNtoijTDcAwOayzXMild96Dy+U65ffK2Bjhl18h/MILpNrbpz4PWly8XTKb1+oW07WgDi3faFuZxcTPKvMp6W1Hk0cZVx8kGm0DIDs5B9/GYlJb9k7eGzo2XwZPVRx3WQLJNEnBRYCKsxDmfBZmXASmDz/vVCrF0aNHaWlpYcPQBrbnbgcdFg6eTdKylI1lZaRzJkUsNJ0SSabQZaGzP8KN6yawZXSq5+Zx3hca3qfI92HWl0zzhj/M6/4wW8ejKCfN0znpIGcEj+E9Vkx1ysv1X5+Hw2tB0xTC4T1Eo20oSpSupM69wTr2pg1RjzLBz/dH7mf1kTcRdR0NgcPxlRywLqTg7D+hawLys2XIZ8QpOfp95IyLSP4uemfezzMdF/Nm7zkAVHm6ubXpYXJsp+YUC0mw7hJIztfRrWDfJGLbKpCp0jGZs3DXLSHv/JtxVjV84Hnrms7OV7rYvaYbgNL6bM5zw+EtAAEAAElEQVT7QgPWjwDqibTKqy1DPLGjh72941Ofy6JAgT7C9dJ6rpHexidEiKrTGcr8FBsmoj4Ltf8xB9Eqo2kaLS0trF+/nnDYiHTl5uayYsUKqqurGPOvpafzj+zZK/BE3xV8Vn6LL0hrkQUVXTdxXLqCCxfewKqdW/je+C68+V2Y4sZcq5LNuP3HJIKTAhK5NvbOyWZEgpvPqvrI++F09gkI+hg2Ph7m3t/+FvmkxZkoKhQVHaWk9NAURWVkopDx0UKqwweQ1QnCGQvZaYF5YhiHYPw2iZkHxCsJaPmogoopaxpXjk7DrRiLfx0dcXKRMyG1EjWt4fYFX2LAVsAVI2/whyP3TLVB1yERMDHS7yU+YGFN41n86tM3o0+Gq0uDQf77YIqGlBFKHcgc5lB6A3EUFLOdyqX70NwSb0RW8U7iXMK5PrRJhQ1B17g2+RgXWF5GEjSiCSev7jufrpHiySC5MAVVdCApWRm25JOpcqPUegzq144gnxrMkJuZjN8U7mBsUmnrPGUcSZmDQBlFnF7VQ0dnTA6xw3mQFscxjlv7SJPhyuBKzgsswBQJoUeG0KIjaNFhtMgwWnSECUnkB2fczBFPGWZd5ec1MvYeMyVpE+5JMDQu6ATrvDTO9BB9thNBl+kyD6EIf+UcYRuqaEG49R3E/BlT7VE1lY7xDvaO7GXf6D72juxlNDGKKaOTMwHOpI6kgiLDuEMg5BRxKm5mBWeRm8xFQ+OA7wADzh40USfD6Rf75e5ypmdPp9o7nailgQOpLHaE00yclEMj6RnsQgpRdDGhqujCv7Ywzg/E+PyGFEn3EW50/oLCdJCDjmqe7m0kLxzBm5OPt7iErOJSsgqL8BYUIXhzufEfhzk6HKHYa+PxRoW3n/8nPSUlOJJJLrz4Sq5bFyScyHDxrCJ+d20zx0ajXPnnzehRnSXWERZZAsRGGyB9wqOr6xkysVfRMga1RhBFHN4snNk+nFk+hCNHMXkOYL7QAAWeoXlkb/SiHDjIgMXCMwtWsV6aTgIzkqBycdValpu3sXDYQl6iDV00IVz9KExfPXXM4OAAL9773wQH+pBkmVWX34lrnw0UDTVwnMSOP3Io30ZPtguTxcoZ13yG2edfjChJZEbjjP5+H3paw3VOKZ5VFe/rXyXUzwvPPc5vj+XRpxuTZ6Epxh1nFCPvWMN4ew85jmIWLL0cu+Ig0R9GiJ24vhlLgNGql7BFS/EMLUJSJqm2soholciI0BuJMa6LJNGodgSpmNGAYLOSbNlHdNPb6JkEpqI83Bdfy0h/kKeVV3glayMJyVjglgtOvjjWy4WRKKOaj68ptzMctXP+6JuYdAXJmkfhvHFy6ltBUACRGdN/SlHRlf/SvQafgKAPs3+nb3oSKTaFonQnUvQk0vQkjb9h5YMpwgBWUaDUYqJ4PEjOgX3kd3dS7W4jd/kxBNkY2T3u2TQ3P4o8mUMTHx3ntXs3MzxhR0fHGXuH4VKF5CRttKSkhJGRETKTYgz93hzemLmItCRTrKb5njlNqSNCLP4iqdRbk4V7RQryL6Gi4g4cjv/dIuZ01t3dzR/WvsmG3DIcqQRNvXsJmbo4e+7Z3LD0BiRJYmTkFQ633Y2mpVHjlXS9dTuZmIUUG9An2hEm53tPSTkrb7iF8sZZ7ztOZiSG/+FW1PEUol3G99l6LJWe9233UfZuMecxcYLOuihtfR2oSoZZHOY8NmHHiGgcdS6h5vbHQXYQXb+e8RdeILZ5y5QaoGAy4Vy+HM+nLiU8cy6vH/HzWssQu3tCqHlWMjO8YDXm28LOLs7cvo6zlsxjxqIRRoYeAjSsliJmzPg5jnAB8R07ie/cQWznLrTQKK6SJN6qOI78E7RcTbCilq1EPudOhPKFU8BTURSOHTtGS0sLR48eRVFOUIOPlB6hVW4ly5LFc5c+h1X0cu/OLl7aM0BgJGZU/jCLKJVObivOI+eFQTRNZ97qChZe8r+7T8IZhbeDEdaOhXhrLECEE4DArCrUhBRWlu5jRupJnGo/GWRe4jJe5nIyghmTnuJzkSf5ZuvfcU06uPvSjWye+AJBtYSq87+H2TWGfaOI90kZ3SKgXT4PT/ImBF3iZdsEP5sMTF09K8xti9NYzU5k2YkkOZA0M4kXNjHx12fRQuMkZ2oEbzckryscX6C04NOYy8tPd2ofaMf2jPLWI4dR0hqeXBurv9R02ojXkeEJ/rGjl+f2DRCZLMoqiQIrZ+Rz3cIyllbnEIyn2dkVZM+xAZYe+g5nq9tJqtX0Z36GFQs9ZtCvqmFRfR6yJJLJZNi1axcbN24kmZycc8rLWbFiBSUlJQQCb3Oo/UEe2l7P7WPlzJEfxCrtB6Dfks/3p93JisBWrh95zahpNJRNwr0Cy4KVjLmm849tfl7KJAmgYxYEtn/zHLI9/7oT4hMQ9DEsnU5z/Phx/P4AweAoydR63O53MJsNT2os5qG7ezbBQAknRAQ0PJYIBRYT6tggnvgAjdYeKmwB0sg8ySV0Uo6ESoO9i4R0E8vGjIcyKeqYNaboRHtNR7lnwSx6nCamt22nub+HHCFMl17Afq0aPx7UaS6UauO86o+3M1xQRtBhxaTp3Nka5sw1T7BeFtlWOJO2/EoyhQ7kIpGUx3nKArox0s6i4E6q3Hso8xoexj0jTTzSeh0x5dSHR0BHFkBCwyRo2CQBOa0TmuFjvMxJaUzjxqDAjIEUrkAajyRwyNzJfrkbURe4KD2XPN2YMAatAsfdEp5CJ3NkM8oew+MvOnXSylHWKNt5urQVv9WgGmUpbq4MrGR1aClW/VSSXJQkfc4JHvb62NofwyyJ/P662TR1RNi9o58iRPImgaaOjoBA2LeP/sYHCAb+g4Udv6OKPkLmQuTbNiK5nPRF+uiN9NI70XvK+5H4CLIm4067cWVcuDKuqfcOxTEVzVIElaA5QMAaoDW7DV10IYgecs2F+LJm4fBMRzLlkBJc+DMaIymFsUyGD6D+vs8kXcWdSlKe7sOVCdAhJZkghKiGEM1l3PXSMebuP0CqqYk7Pv8fBDSdGkVlSIECrZ8X992JT5mgN5XH813VKPrpgWnGkc0zeRfhx0G+WeVnFUF2HW0jZrNR3NvPG1ot8bnzuGO1QlekwyjY2hem58iloJtZVLiLmxoeZ/NAJQPdjZQES+lzbibqC3LN3M9y3syLcWRlIZ4kd9nf83eOHv8vADzbsmm+cx2q1cobb7zBnj17ADDpMgdDPnbYDYpGpbubO2of4bxjxwiv96H65mNrbp58zcKUn08qHmftH3/FsV3bAVh8xlWUjlUhZECL+Ylvv4/BeVXM+/FPcecYybNaWmX09/tRRuNYqjzkfKER4aRq55qm82rLEL9e107nWAwJaJYz3KLvZS4JNK2SjFiHfhq1KQ2NIUsAd5mPkuoqTIVOJLcZwSIhWiQEi4QgieDvgKc+Q3i0j//M3MF6rRmA6xeW8YOL67HIEtFNmxn4+tcZ08K8vMzOW02QmqRYVCaLuca/ijMjcwioeyi03U+hOIymC+web2Rn5DKyakcpmPMayJPA0z2Hiorbyck59+PdkO+xT0DQB9v/i74Zzyj0JNMGMHoPQBpIpU8ZV0Rd5VKe5TKeRkIjhRkLxr0yLM9jtOhHlDhzKbeaKbOa6Xq1k71vGlEfZ6QDxO10VZUZQj5WKw0NDQxW1vHf/jgZHZZ4nTw8swLPSfLDExMH6eq6D39g/butoCD/4kkw9H7K18c1dWKC5OHDJFtbCbW2siORoDsnh8xJ1EDJJFJZbsJieQ1v1hBJfxN9m7+ALDtY8fl6Sho8bNnwNntefg7GBqdEcbzlVZx34y2Uzph56jEjafyPHibTFwFJIPvKWuyz8z52m2N7Rgg9bURwvJ+qxrmokEQiwYEDB9i9ezdxfx8r2MQcWgFI6lZCB7yMHxF4d71ha27G86lLcV9wAdKkGqaqZOhva6Vr3y72721hb9ROu6eGvsY61DLHiRphqgZpjVq1jdutfyRPGkXTBbYlV7MreT0e2UaOSaIs7Ke6q5WC9oN4u3eTlTOMpzKB2XECcKczbsY8S9ifvYQWf2Jq8QuQnZ1NY2MjM2fOxJXl4vo119MR6mBR4SLuX3k/oiCSUlTufusoL27rRUga+812mPlCUS7sMqJkyz8/g+mLTy1Y+q9aWtPY2L6Jda07eNPexIC1YOo7QdeoETqJSzn0q14AFokD/PzIL6gdMiSyw2ohmyduoDs1n/wqKzXn7MEf+S2y7GFuwUP4f/hLEpNzU//ZtzLDOxeAe01pLrxuJivr86eOpysK4RdfYuwPv0cZNGjh5vJycr98F6GGQY4d/ykgUllxB1ZrEbLsQTa5MckeZNmDyeRGkpwfGD0d64uw5k8HiQZTmKwS593UQEVTDom0yisHB/nHzt5Toj6l2TaunV/GVXNLyHNbT7tPXVXwP/Of5LY9SlqrpD/9c8zYOILKj+0ZljYVcHFTEfMrskmlkmzevJkdO3ZMAeEZM2awfPlysr3ZjPx1K2qnzjgKu6XHuF5+AbNgbLfROwdTxE7uqz2kxjX25dXwauUSdhTUo02uW7MQuEgw8x9fWkBe6b8+fn4Cgj6m6brG6Ogajnf+ikTCSGi0mItIpVexZbNCRoWEaEPTwaEnkU7HjwK8hGlWDzFTOMI6cRlHqEZE5VJeJ+koQ47dSH7SaF9UAodqLNI1dF4pNvGXKjNjwzFMHYY6jC6AUu9FLTEASkFnlPs6FLwmmR/NtLIpz5h4FrTu5xuP/JnsSJiQ083WprlsmTWXPdMbKTH1soBtXNixnbFRN965PVisKRRVYt+xxfQP1SMZoqRIgoaEhoyGqOvIgoiMiEO34tOd+DQX2ZoLj+DFcRrKnKZrrDW1MCj7saFyk7oNn9hGmzSNPf6biKTLyLFFqJroIt8zA9FsR0uESOz4I6lID+/MMvH8Qo0xr7FvT8rMVbFlXCp+CvOEGS12goIo5Fh4yAV/7RpDEgV+fU0zyzWZ4aeP0qkp1CFNAc0MOq2ew4xMf4eAVMTN+x8hS8vwgsPD9/I8oINFteDOvB/s2NQP9j4MOrJoya9i2OxFsmvoLhMJrFNFNz/KRCBHkvBkwBZV8Ep7yLEfZyJazLzBTpZHN+LORHkh7xzu7HsSCY1O31kwdicPZK/llax1Rr+L+Xy1tZIbvvMrDiHxqb0dJCblRMsRaWz7Jr/yb8Wt6Qzqs+lv/i8EOcj48CDjw4OEhoeIBPyg60QlB88WfooJk5vsdJAr/K+TqZgGosD87TvoM0+wtUEg4lCYcChEHBki6RoS/Z8HRFaWv801tc9jc8/FUfJlfrTrl3SEjOJ+Z5eczXcXfZd8hzFJDA4+TduRbwLg2urG+VgCae481s6dQ2jCyGWZP38+K1aswGw28/y2Dr7/SgtRzYpZTHPVtBe5/PVt2A++J6m2sBBb8yxss2ZxOBZi56b1oOu4TNkszb8SlykLPZMgsecBin54J85ly9B1ndA/24nvG0V0mcm/azaSywAzuq7zVsswz67twBJMUovEdFFmGiLSaQN+GWJakJHYMIH0CG9VHEWb7eO/zv4hubZcMr29JA4cwLF4MXLuSepFbS8bSm/pCDgL0K76G384lsOv1rWj6zCrxMMfPzMXTfTzwI7f8XL/WpTJUy8Nmak95qZ+vJTpnkWUORuQBRGBBCb5fvJk416J2KwcarASt8vY8VDTeC+9fQ8zHt7JjOk/obDwio91755sn4CgD7b/f/dNRtMZSBkAqT/cgWPg+7jSBh1qF0t4gJuZxy5u4EHMpPGTw318jWOCobxkEwUKBQlTfwLvhErORIyGjrUoHp2404hYtueV8E7dbC4s8HHfjDIsH5BMPzHRQlf37/H7101+IpCffxGVFXficHy4RLMaiZBsPUyy9RDJ1lYSra1ket5PDVRFkZG8PDYsLEVxFGPRTkShJRQc4zY8tnIu/tKF5JVmTX2XTqfZuuFtdr/0LIwNTXEfsiqrOe/GWympO8ES0NIqoaeOkmg1krfdK8pwLS/7SFpf8lgI/19bQdNxLSvBc0HlKd/ruk7Xzp30PPooUqiV6bU95GGAgWjATrjgenKuuxNLlfG7eHiczn276dq7i+6De0knTuTEiJJMSf1MsmfO521HBU+qKlHLqdfFqif4NH/jXIzr0Ucpf+IueoSToi8ZDSGtYUkkyY6MUx3ro1ocoMw0TH4mSE4mRHZmnHDaTV+iiFGtFlNJA+aG2XhdNjw2Ex6biYg6wP/ZdhNJNclds+/i5qabeWIwwFeP9oGmc25Sor81QG/QcDavyFiYHRMRJYFLvtxMcW0W/4q9S3Pz+9/CH1hPPN4Fuk7xYJL0aBHrshazNudMDrrqpn6TJwv8KPgKl+77OQKQ0uzsjl7Nwfhq8qpyWHBJJflVItt3rCCTCVFb+wNKSz6HrmmMPfk0//NyC8+VL+ZWLHwWC7okkHdzI5YKD7quE3nzTcZ++zvSx40kfzk/n5w7voT3sssQTCZ0XefIkW8zOPTPjzg7EVl2YzK5DWB0MlAyedDSWex9voRArxnQSdeleDEZYjRmJqFYkcT/H3tvHWVXeb79f7YdP2fOnHF3i3uQhAQS3KU4LdBSaKEC5UsN2lKhpaXUW6zFrVDcLUSIy2QykknG3WeOy7bfH2cySUgCoe37vt/fWlxr7XVsny3P3vt5nuuW65ZYWZPF5YsLWVKejng0IYemmQz9fv9OEkYxvYlfo+CgGZ2biRDAJNtj48xZOZw9O5diN6xevZra2lpMMzmvPdd7POkDVgTJxOP7Pe5gMu9cNUVMUcRiaqiCxLbsS/jR4Mnsiex/dmeOtHJG+wZOMMBqcVH06M9QsrOPdLRHxOck6CgQ8jdT99E1RG3JZC/ZcJITW0mGuRRJsTOSSPBqUxPj0Sg6Eon0Wawd0hC0GClCjDxLkCqvBRJhQuGkJ0PApIhudGS6yUXA4GzeYy4NdCoLsEfOQtXnEhEl+uwC5eFk86sCvJEnUnxcDm/2dvK6mCDqyELSdU5v7eBH7RmICIxj8Ahx1hTY6K1yYUgirmic773+HstbOkBSEEQLKApmmkQiV0FPsyAiIxgWjISTaDAdQbciIyIiIiEgISIhoiAjH8FbsA8JwWSvW6LdYeAcbyFAAL+agXvcx4SvDl2J4JZD3MDDODUNwxSoj5zK5tBlxE0PHjPBsQ6wWZ2Yukpsx2NoPZvQJIGN51fwfPUEfXpyQPBYPGQ6MhkY6WNupJobBr6AT0/BxGRDhsTtwxOoUoRvnprKzGiEsg/dKKZMq6WfqBRlRjTZyevorHXW0mLbwMnhIUbwsU3OQjdSUYwjx9MamIyaLkZ0JxOmHb9pY8TnIzQnA6TDTABME4cZJjcxRnG4l+z4CFmJEdIkE1fuMVisi1DbY/jrJ4hPquM5c+ooWPonTF2kpn42ef53MQWZocqzyWpOJmc+nnMW36u4meKQwB+3R2lVmvhFwWMY5gQmEpdO/xoLii7muoZO1Mkn+rIcH19NjXD3S+fz14F+HKZJa+wYmnLv4tgLq/Dm2OkKdrF7qJG9HXX0dO2lry/MltD5xAU3FiPKNHmUOZZ+ZFXllLffwa8I1OdnYEx2porNRkf2fF4QZgFwYcVrnFHyDlZLHrPmPMyTre/wQN0DaIaGW3HznQXf4Vi3QFPTbYBJQf7VZEfOpvuLX0JMJGiurKT9xOWce+65lJZODtBaHJ67mr7dG7lV+xrr9WTM9DTfbo436ljZl0lGV0sybt74mDy3z0NtQQY6MLtqHtNSTkUfNjANnXjjP8n9ybUYeh4TL7aACGlXTUNQJBJ9QXqbxwh1BsjUTKTD5LEJFgkl14kl14XiHENpfxil+1kMdF7rraIlmIFsGpxywml4h8cIf/QRak9SfUrJy6Pw0Uex5GTBBz+Dj36f3GjR8XDRw+BOksUPm4f41jO1BPUeXFlrwLV9KreurFfgsjUaMztM+lPdjKxYxuspS2gaVbgYCxeYFgTnIFrOnygerMOimegiBNwyKX6NiYVnssO+CUFQOPaYd7HbCw45x0/D/3YS1NHRwc9+9jM++OADBgYGyM3N5corr+SHP/whlk+oRL58+XJWr1590HfXX389991331Hv+z9pG90wEeDoJi0HwDRNevueZu/euzCMKLLspqryp2RmnsWEptP00QZaNjyPb8ZqHK4QuinxqnYp/1LOxzjCxF40DGb1tLCovQkREyM1jVuvvRrPx3JYDodAsD7pGTqQDGWeSXHJTbicFUnC09hErD5JeGINDSQOUFc7EEpeHrYZM7BNn45t2jTMRJxYYxOhtlq2HrcWUfQxPFzISF8hmrC/Ar2k6+THYpR7U6maVoNn+nSspaVopsn6VR+w9eXnMUf6p55wX1klp335a+SUJevdmYaJ/60OQmsmlePmZpJ6YcURlePUgTBDf9uJGdexz87Ad0nVVL6LEYkQeOcd/C+9TGTTpskir7D1mIXkFI+wzNyEImhoSNS5ltPjXUGwvY2B1j1T6wI4UryUzF1A2bxFFM6cg9XhOOgYwrpOfWMjLzz+KMOCBTUjh7Rjl+MWdrIw9jucTKAh84p5CS8K52IIn70gZWrCT2rYj2sijBkxiekyE6KDCcGJpOzFmvIOghYC7XomCktAgOvy0/lpeR66YfLKzj7+vKqFtqEwZ0cUqlUZUxE4+zvzKCr+5NBDVfUzOrqakdFVjI58iBQZxxYzsMd0bHFIMdNwqVYs4RDx8RB2MUCfJYPXfCsxJY1LBt7CqwcxTYHG6MlsCl2Gp6iQRWeXUFDjQxAE9uz5Gd09j+B0VrBo4WuIopxUf3t6Bzu7JwC4YO+H3OQswJI7F8EC7hMkRu//PbFdyVp3UkoKaV/9KqlXXI5oO9j7YhgJursfIRRqRtX8aJofVQ2gaQE0zY9xmBIPh4OpSwzWXspE63IA3AWbyVn4KIKsIkluLFOkaR+R8iArKVNESpbdU+9t1mys1klv1s5nMF++EU3Loy/xKyTcdMsmt4oReg8ocF/oc3D27ByWFlhoq92IozHGAq0CMEhT7sIubcS0uNiZdSbXty7FYqr8yPEkJ+tbARg0vfyOq7DOvJALM3Vy6jYS2baN+N4WzFiMqq1bjqodPo7PSdBRIDbey/qPTgABXO9JOD8QEeMHDwQJRWHLooX0FCQnCFldvfSO2XmpdCmhyUKExf4+Lt/7HpXRXloKshlKS0W32hEcDjQ5eeOfxiqOoTa5X9JIaCsI6ytpt2Yh6RHy1OSAomIQkQUUU8BigPwJV6fVKfLD2TZa3MkO7OLOBN/cE8d2+JSUfwumGkWwxHDMK8Namk4iBerDw3x1MMq4opAeHOfc2nUoho6ccOOJ5jHubsEUNdyiweXOv5MTTIbeqIaVPUNLCNTG8Yb6sM//MnLOZDy2tZ+MLx+HtTAf1VB5dvez/KX2L4TU/Qo2Fd4KYpEI+SPpWE2FPsswPZZhIlKEymgRv+z6JlbDykZHPY/5XsehOcmL5ZAdy0Q1DXThyA3jVDRS1GGChoUWI4sdegmjpguVpMdNQidHDKLkSuyeVokpiNQYu5DGB2nunoEQFRHiGopjPbaMtxGkGLlxgYuG8igbr2IoPotRrfigfRqShpE7TuXC32KRR6noz6Zwb31yiltyAkL7GgD0E77Lutk38crwBK/1DiGrIvduj+KLBvha9TPEtWSleNU6jUDa9Uz35lEfimICt5Vk4w68yub1v+YvA8NYMNkdXc57/hvZm7WdjfmvErEEDjouPZ5BtOMbmIYFAYMvpTVBOIJvdJST3v+AWFoqDdNKGPX7p8QOtntm81HacQBcVfoMy8vXo00UsvCYJxi1R/jx+h+za2QX8xwaV/oSiALk5V2Jw/5lXnrpJRw7d3L8R+sBSP/RHWRcfnnyYLQ4/POLsOctkG0YlzzBI4Ml/OrNRhK6hEOOsDh7KwX5F/O95RWYuxuJ1tYS3VFLdOdO9IkJEpKILgrYVR1EGdu8L6HkL05ufmQPcnoFICDYJczo4XMuooqAq9CDo8CNkutCyXUh+2xTkxvN0Li/7n42b/wj39gbpLBToLcrFUtAP9g3qChIDge634+Sm03hORYsE8mwPY69CVb+BKQkKTdNk027V/OHbX+jXmucish1jWeyZLdAcSKd2ZKdtI82g2HQn5rHDxdcxYAjnbO1BGcsXIWS8RYIOpYYzKqTSYklZdoNU2bnTDtjPiv5uVdQVf3TIz4bn4T/7STorbfe4tlnn+Wyyy6jvLyc+vp6rrvuOq666iruueeeI/5v+fLlVFZW8tOf7m8Xh8Pxmc7xP2mbVc1DXPfoVnxOC+kuK+luK+lOS/LVNfndvsVtweewoGujNO3+HqOjHwJJRbhp036DzZZ70LZN0ySwcRVNTd8nXJxUmrLUSsjBLxC84Er6fBm0h2Js2ztKd0Jl3CWRUAQKRgc5s249iAIui4XLr76a3Nzcjx/6YREMNtDe8Dv8tR+idAkoXSL2XhdCf+Sw6yt5eUmyM306thlJ0iOnHuohiETaqd35ZaLRThK6zN9HJfZEJa5rnkeW30mn00nYtT/cW9R1sgYHKegfoMThwFtZgVJZyZ5wmM3bN6L5R6bIUFpFNad9+WtklyTD+EKb+pl4uQUMsJSkkH5VDaLjYAOa7o8z9NdadH8CS4mHjC/PBBEim7fgf+klAu+8gxnZf86ORYtIOe88bCeeyN+ffAJ1pJUzWUUFyfpdY6TwunYC3eMOctwOKuctpGzeQrJKyxGOQtJ6vL+XF+++k/H+Pix2B2ff8n1yqwvZ3Xw7w8PvAMmQWG/O7WxvC7GjrYPeYIioYiWmWInZ7AheHwmHm7Ck4NcSBE0B898QuJC7Qlxkc/H15WVUZiXnO7ph8saufv763l7mtank6iITkol0cjZfXlFOhtsKugbBPmKDmwn3vEd8aBv4u7DF9OQSNxA/ZRbbl6gmVe7DLu4f63riM1gXvBYpdxaLzimlcLpvysMXCu9l8+YzMU2duXMew+c7nncaBrj1uZ0EYhopdoV7vjCbY/rrGfj5r7BUfQnJW4Qe6COy5m4Ei0Da1V/Cd801SEdhLDgcdD2eJEaaH031o2kB1MnX/okhmnp76RsbRhFDOJUoSt804o1ngilh9XaSf/xfUZxHVms8EgoKrqG87LuIogIt78M/v4gaS6U/cTciHsYcIsNnFPHy3mHebRwkqibHTBmNXzp6OTaSVHXzyvchy++yXV6Icfy3aLGU8+i6NtrHk+RuubiDH1sep4TkmBQZtjCwLYX4xAHPlCBQVbsD8RPUI4+Ez0nQUcAIh2m779tYxp1IERFTVTETKqaamHxVMdQEpqrSmJbG9qIiTEHAEwoxd+sO3kudzoulJxCZVFApm+jhyt3vUO1voSE/g9a8QsYLK8lOJONnq+S9XKK9dtCkKG7MIKCfzNMZx1ARdTPTf+SJelxMLglRQBN0DF0jYho8UuHgraLJsLmgxoU7QyzQ28hN7wAlDmoC6w4DuV8FXUU3NUQtgaknQFcxdRWMBCoaHRkqu3JVYrJKVFZxRHUkHSRJxjNjNtoxp7FGKGFD2J5UkgFc0QTnbu4gOzCAaAxgWnMJ2UZBMHHHM1ia+xwLxnZMdVTBmJ2OpizGxqqx1FxEgS/p6vRbJBInZbDa9QZPNT9JVEu6/O2yfer9PkiGNBW+VhjJY0FwJkFiBMQIR7yhTQGv6SDVdOI1naSZIdzCNu40FtJiZhAwDw5/cwkx8kV/crEO0TsznVc9yZoOx5ur+Sp/QUYnPft6/rJtCe80JNVgXDKcIBrUjNgQjQMtbAaZciv51p3kWmrZldpNXbGVxekmmV0RZnYkB8dmRaFKVdGBx0vm0liyiEx7Jo4de5Df2sBwWg3tJ13KioEc5o2ofHXmFkYTTyGYCQzRhZhxLap9HhOT+3YkWrEN/4GVgV7uHRpBBj4yz+DNxPXIqoq/oAHP7ABVWeVUplbSPeDjlmeaptpxaZGD6f5NxGIxalpambV1K0puLjl//CNxXwrj/X1MDPTzYH2Et8Y9iBh8fc5DzM2sZ/dzZVQtOJ/FF1zMm22/xjvxPJIAW8I2bKGv4N8TwDRN3G43Z0UiGE8+BbJM4T/+jnPuLPjnVbD3HZBtcNnTUJbMXWkZCnHj4+/TPJwkqTW+3Vhslfz20uWUZyYHHdM0SXR0ENmxk1hDO2rXBFpQRLRnIaWVI8iH71j7JmXZ2wSDguo0zjqlnPTsI8dmd7fs4NnHvo+vrouZHSau2MG/h6wKIy47BceVUfO932JoIp2XXYLaN4ji1Cg6JYJyxZ9gxgVT8f7vbX+Fl/zv0pEyMbUd+1ghI/5zMGL5LC108KcvHYvLorD1/tcRHvgZnkSIkGKn/awFZJyyFcNMKvik+ZaTF70Oba2A3f88KfLDCIKKJtjZU5JKuZGH5ZLnwP7ZwlDgfz8JOhx+85vf8Le//W2qFs7hsHz5cubMmcPvf//7f3s//0nbPLe1m/95vu6o1xcAlyWEWwmQYg2Tl5ZPYWbNJGmyknEAYUpzWrHIIqZp0rbxLjpCD4NkIg2B7yEZX80ppF1/A7bp06j7oId1/2ohIoPbK+Pt20l72jBxu4BowrEzl1EzYzY2lwW7S8HmVJAUET0UmszhSebxxOrrSUzWGvk4zAwbjhlzcM0+ZtLTc3jC83GMj2+kbtfXkxPFSBpda25iVc4G6n3rEAWRu0+4m5NzTqR761Yaa2vZMzzMxIFtZhhkDA+T391Dfk8P9ngcLT2dIcEgKJoE7Bb8divuGbM57dobyC4uIbZnnNEn9yvHpV89HXlSOc6IaQzfV4c6EEbOsOM9M5XA268RePkV1EmFPQClqJCUc88l5ZxziVpk2nZsoW37Fjr2NBMsqABRZEZwK6c6t+EWk+PeLqp4h2XkVc9nwYIFlJaWIh5lXZ9oMMArv72LnqZ6BFFk5Ze/zswVp9LZ+TStbXcBUXRdpq11AQMD5YiiRHl5OTNmzKCqquoQ+XLdNBmLxRltW8fI7vcZGdzDiOxh1OJlRE5lQPcxRBojthQGfCnokoJvdBWVa/rYYzmBiGLjlGlZ3HhiObMLvKCrGP4e3tjQRtObJg5NpFvSecUd5mL7em4w/0k244c9t30wBQkhJT8p771vSSnY/96TS91b9Sirf0qa0sG20EUE9AwWu56lqMKCcP5fwJeMPDBNk9qd1zA2tpb09JXUTPsbd7+1m7+vSxLTOQVe/nz5XPJTHcRbWhj67W8Jb6jFsez7iPZUtOFG3Cs8+C679N9WQzzsdUzovDqZ67PjcLk+C/LRBqK8eX89sZCK3S2z/IvppBXGJ4lUYNLjFEBT/aiTHqd9xEpT/cTiyfs0JWUeM6b/EZstB/pq4ckvoAYtDCZ+CaQyZhep/vYCNLvEqvoextY/wvLBbQjqzYCCRXyFvZHtNAwX8ZG1nE2+amKT461FV1nWs4NpsW7+/NVruHboZW5texiroGGaMDGSQcRyCkphJZbCAjxnnnmIF+1o8DkJOkq8NDhOsd1Kjct2xPjmfejs7OT5558nGAyiKAoLFsaJGy/wXufJvN97MuFEsilz0mwIZS7avMlwi/mdzSzs3A1ATSp8YfwPiBgHVBICw7SzOmU5T+acwYhYxQ8bE+TE4c1sid9V2fBbTHImWogaGzhtdA3fHu6kS5/NBxyHjkxnagbvVy0gYbUimSqX8xin8ga7hqfx2pbTWTZQy/EDu8junTjIahKyOwg6nNhjUVLCoSMWoWwuLOHJ085l3eyFUyp1Ve0ttBYUo8kyi3dPcPJOIxnCYe0knN5HSFfBBM/ENApzt3KK/gjuRHxqH3u1IrbJp+KO1DBDKEUSJMaMId6I/gU1MkChnsY8VwX2hEJLdIJ+WWbcl0rElYImfEIImyji8Fqw6hLlo1n4DBdhdxfq/L+xqe0MUjpO4Rwc2CfpaBQ/f8PCm8TxikHyRT8Fsp+a/HRKSwQczi08HM3mFc4D4AzhHb6bp4OZoKfnMQDMyELWfnQVr2oCY1KygfM1kXNkJwumZ1BQ4yO73InW8RLK5gdx9dUStwhsWJBK5kiCaXuSHq8BWSZb04gJArdlpLHK6Tj0BCchmDLXTVzP6UPT+XXFOLvEBwiRDCVRHcuYSLsahCRJENURfP23clYowF3DY4iY/LHgCu4q/erktkzcgognZjC6rh9TN8kqTWHABlrC4FjRz4yuZELoCbvqyWloALudzF//mrSTVybbwDS59bk6/rW9B4uoc1zuBjKiw8g7E5QXD1B8YjsIBu3xHBq3L8SjJkMeSmtK+cI5X8Bms9H3ne8QeONNJK+X4ivSsYyuAdkOlz8DpcsPOn9VN7jnjVU8uD6MYUq4LQFclgQ3n7SMc7JSSHQGSXQGiHcGk5WpD0HyCTQweUeP8LoEe9GJGRqndmzm0j3vkSFq2CoqsNZUY6uuxlpVhaWgkFhjA6F16xhc9Q6W7oNrjYluN85jjsF5/HE4sjXWvvwoO/uSA8DKgj5mL1uK+tHTdL6XghqSkbIyUL/1DVo79rK+ex3b8ocYSI9PXheYEc3n0vwLWLb4bN7oSPDjlxtI6Aa5Tisnh2Ve1yOYiQnu2n4fhcPDmIJJ8Cwd84JSKipvJy1tafJsDZNo/QiR99fgGf8pFrEDgJg+G+m4y1FOv+GI99qR8P9HEnT77bfz1ltvsXXr1iOus3z5choaGjBNk+zsbM4++2zuuOMOHI4jP48fx3/SNqpuMBpKMBKKMxyKMxKMMzL5eTS0//1wMMZYODFlkDpaeGzyFEHyWqOYkdU4LUN4pCA5m8Nk1YbJnVlDxbVXEk8r560HG4hOhu8agkbA24RqnTT6+PPI7tfxBHtwBztxh7uxRkbQBQFNlNAFCU2cXFIz0YvKMIoyCGV0MuHdS8IqoZsSbs9i0jPOQVJyUA0TTTfQdJOEbiTfGyaxRJRofJxQpBct9A65rl58cQv+zdeSmV/AyV+Zxq8b7+KllpeQBInfLPsNJxedPHXew8PDNDY00FhXx+CBNY1Mk/SREfJ7koTIGd7vrYnLEn67BS0/n8oLLsJXNR//e0GMgJpUjvviNCwFbkYeaSDW0Ic+ugMzUkts186pbYguF57TT8d9ztmMO220126jbdtmRnsOznWS80sYd6chAFdefB4lHU8jbH4AAYMYFt7neLYyixSvj6qqKnJycojFYgQCAfx+P4FAgEAggNvt5sQTT5yqP6SpKu/e/0caPlqN5vLiqJjGeDSOxRKksmo9Xu9kSoA8j9mzfov3s9QKCo/Crn/CjidhcNfU15puZ+uQg/+Z7WRi0hl3apvKBb0KksuO4tQptPlJM0anFPtG1Xz+OfYbDNNGg6LxhkPFIiS4WPqQq51vkOUxEHxlWDMXoGTM2k923DkgyYc5uAMvscnG19vZ0zzGkpMKKFVfQ3j3jmT9N8UBK++EhV9hZOxDdtZdhyBYKKp+kVteGJ0Kf/vKkhJuO60aYbCf4T//Bf/LLydDsEUR57JzENwnI4gKidb3kb19ZP/4x1jy846+LQ+Dpv4AT2/u4sUDFN5kUeCU6VlctqiQ48sOzvUJjER5475djPaEECWBZZdVMW3J0Xlsh4ffpbHpf9C0IIriY8b03+PzHQ9j7fDEhagjUYYSv8QkjSAxcn3P4wq/hmGmMZT4NSZOEoGNvNlay2uFx9GUVjy17fzgEKd3bOCE8d1kFOSi5hZxj7uYt088ltzYEH+s/ylLwsn7R1UkAosuIGX5vcjKvzeufE6CjgJhXadizS4MklWKq512ZrntzHQ7mO2yU+OyY/9Y3kcoFOJf//oX7e1Jq0BJiZ+svDfYKazkjd4r6GieQJiU6DFTFGbOTueYgTqEretQM5MFTavTrVw8/kdEPYJmuFBlEbux3007bpxKm3ATv5pmRVB2cdbwh5w+so60xDh+HKQKyQ56WBL5h6uUaPxMiIko6ROsrp5DnTQneWzRbpR6ma6x/d4lTzzMsaO7WDCylwXdTdjU/ZKYQbuDlsISxlxu7PE45cP99Obm8vSSU9gybb+M6NIdm7n87Zep7mxjzewF/OHSa3HGIpyzdjuzOqKkjzWQ4m9j24J5tJeVIBgS3tE5OOx+aoL/IHNTD0ZCxDxAYEFMyce++EZERxqaGqZn7zP0W0IMZGUzluabIl4HwppQ8Uo+Uk0PHl3BZ7rx4OYlBJ5I/RAx6xUqoyVc0P0Vag2ZdXKAAS3pJXADNwvjnGamYOAFIIJKg9RFh2OQGTNFFMcqEuJe/sFX+VBIDqRfCLVxWm8BhqoQHIujW94je/7jiLJKPJBN35ab2OUq4K1QgLhuIokC1xxXzLdPrsRlPaCT7qulse4m1EAHsxqDySmMIIJpYNpSGDr3T3Sn5jEUHKDlhUfp72xkzA2haYWMuwWGIkPE9eRE+YzxpXx94GIMTJ7IeI3n0t7FFEwytQws6T9ghycdCajQtjDa90cuDqncMZxUq7m75Kv8rvCK5DHFdKwbhxDiBnqaFXVeWrJU+SRO2LODaf2dRBQr07ftZFHjTgxB4NFzL+Htsy7Aa1HwSCJdAyFGRqNIvWFEv8qs9AZunPMQsqizu7eGLXtW4hOiWOQA29O3MeIe4Wuzv8bVM65GSuh0XnEFsYZGrCkqRaeGkK75J5SccMj134ctO+t56sVm8mMpzESmMpkBd/BKsoiS48SS60TJdaEORAhv6EMDridE86QgyJnOOFcnmvA11xHfswcz/ulx2YYAfQUOSk65gNyTzsA+ayaCvP9am7rOh3/4Ads3JVWglme1UuiYoJ3FKO92Yw1H2FAt8/QyhUFfUgBEMkWWe4/lG8fdTFnm/oRe0zR54/12fvBeM34MMMFrG+e6mc9S7W4k5XkJ59qkB9B10onk3n33IeEYPd1P0rP+SSpbZHxqMu8lMesHWC747qee68fx/zcS1NLSwvz587nnnnu47rrrjrjeAw88QFFREbm5udTV1fHd736XRYsW8cILLxzxP/F4fKo4JiTbpqCg4P9Y24xPbKGx8VYi0V6CCTcu39VYvV9gLGIwEkySpH1kad8yGkqgGZ9tyLcbKmlOC3arHU3V0GJx1HicmGCQkGQMBDBMMEw0QUIXxc8s7f+fwi1LTC9IoSrbTXmmk9VDz7Bx9EUUWeW3y3/LSYWHqh+OjY3R1NREU1MTPZO5evuQruvk9/WTvWsXKYHAIf/FZkP2FiDYcxG9hVjyM4huX4vWXwvGpIiPKOI8/njsp53KSKqbtvqddNRuSxZnnoQgiuRVTUvm98xfRGpuPi+88AL19fXY7XaOO+44LKNNVDT/FV80OefoJYvXWEE/WYce18dQWVnJSSedxPj4OLt27WJ3UxPGAVO+7OxsZs6cQXpGLb29f8E0EyiKj+rqn5OZ8dmLJ9O/M0mGdv0TokmSHBAFfp/q5TlPsh/y6Tq3jY5zRjgy1UurpkzY5kS3R+lSZ7Gh9XuYSDSnDPGKkPyfIglcOC+fry8vpzDt6I0RAJGExpMbu7h/TRsjoTheh8LsfC+z02F216PMGn6FDCGAUbyEjRVBovFeDMeVfOet4wjENDw2mXu+MJuTshVG7r+fiaefwZyUjHefvJKMb30La3k5kdoBxp5JigHFdj6FNrCJjG9+E99VVx40JhzN8b5W13+I16fQ5+DSRQVcND+fTPeRvSNqXOf9R5to3Z5U4525LI/jL65AOlwe88cQDrXTsPZrxDtbkIcF0rTFOAKZ6H2tZOZsRPF4GU7chU4mstBDqnIPo/Ef0iWk8VJ0kDckgcBkqohoGmRFxkiJh8i2hSnwhJHk5FUvKill+UkruKF+hJ02E3STC+re4y71d3ijyRz7gNuKfOm/cOQtPeq224fPSdBRoDeW4IW7f8eWtEzemT73kN8lASodNma67cxyO5jlsjPdbccuCKxatYpXtu6gObuQluz8qfwgEjpZvTEibQFULUk+5helcnmZSM97zzBuTwFBIFMIcx1Po5hBNLGARNEMJrqGydG2IwgGbd7ZeC55kHS7HTb+Fb32GaRYslMZNd28L5bwYtYQ9XYLiilwnTWFisw+EOC1xAU8p1yCLsrYEzGWtTaRLafRFvOzc9BJXE9apa1agnkjezh+bDfzu+vxRvd3zglZYVv1DHYXl+GIRfGEQ5QNDVA0MojVP3FU7auLIquXL2M4MxNJt+AdmY+ISLbnTSrfeQs5aoJgIloMJtJT6copZ6xgFsOWONrH8ndkVccW1XEH/KQO91MyGiZr/k2Idi/6RBeRj+7FMDQUXxmJ9Ao+TC/kiXQ3I6YH7YC6AQImGUKIfGmCIl3jTGEtx4gSAe0CjMlBRRdj+As+ZLDoff5gvZat4iIE0+TMrWHmtiUOOi5BgOyaEbzT7sUUh5EkJ9On3UtCOZ6fvtrA2w1JC1uWx8rtZ07jrFk5CIKA319Ly/tnM2dXAOnjT6DigoXXYMy+mt6f3Eto1SqQJHJ/eRcp55wDTMb1JwIMR4YZigwR6B8ho99N5piHhtEG7vY8yIgygWjKuD0/pyU1D5dm8j+79zCgbuIERwsnDiQnwPFTfsUHodO4Y9VuRkwDtyCysjyT/IWZaC6ZxpEQ77eMIIo6F3VuxBMN0ZeWTUl9I+etfheAdxYt4Z4rr0NVDk42PybwITc4/4Yiamzun8eD9VdhTApvOBWwu4cJCLsQ7T1UZdu4e8m3KfvX7XQ8uBctJuFaPIv8fzyFMCmFaxom2lCEeEdg0ssTQB/7WPwZMIzOHhlmH5NP6ZwslBzXlOR1V+0gPLMHEfgNUV5BZYWmc63socDQ8V1ShbXYTmjtWoLvvENky1aMYPCg7Y+7YHuZwM4SgeJBk3M3mlg8KVhrarBVVWGtrsZWU421tBTBYsE0TdY++Q+2vPri1DYMTPrTQ+wuHqN7UnnXIihcWHkh18y4lhzXwXKx3bvH2PhiK0OdQTpknZfcUdTJtlxZ+CEXV71OSdFV+LYXMPzz32AmEliKi8n/85+wlicVuXQ9wvoNJ5FIDFNZ8SOy+jKJf/QQrm88jaAcWSjgSPh/RYK+973vcffdd3/iOk1NTVRXV0997u3tZdmyZSxfvpyHHnroM+3vgw8+YMWKFbS0tExZ1z+On/zkJ9x5552HfP/fbhvDSNDW/gc6O+8HTGy2PKZN+y2p3oVH8V8Tf1Td72EKJSa9TMmle3gvA+ND+BNugnE3qvnJRRiPFgLJ8VRCQMREwkAStOQiashSAkWOIYkakqgjCQayqCEJ+iGfBUMCzcpoMJf+aAZ+0TxiCLQg+5GsQ6won8aK8hoqslxUZLkPNkiRvEa7d++msbGRrq4uDpwWpbndpPoncGzfRlZfH55YAvkTiKS1ogL5xGUMZqTS2rKbvubdBxWKtjicZFRU4ykoRk7PIhyLH+TJObDuzv72M1jALlawDhsJDAQ2M5dVHEOc5HjucrmorKxk+vTpNDc3s2XLFg43vXM77KjdbUgTI+TkF3De/9yBy5dGKNRMQ+N3pgqs5mRfQGXlj5DlfyOnRYtD85tQ+yS0vAeShW1p+fzUZtAmJs9vfp/GDatV0gZEtJhIjzOD+qJiPMcLFBcsY/cHSWW84rMKeaJvhA1tSYU+SRQ4b04eN55YRmmG6xMPIxzXeGJjJw+saWM0nPjEdfOEUS4qeoVZlTuIqm5uXXMHMd3G7AIvfzynEseLTzP2yKMYkzldjmOOIfPmb2OffXCdqcCqbgJvd2CaBtH1f0QfbsQ2fTo5P/sptmnTPvEYprw+23sJxj/d6/NJME2TbW92sOmVJHnOq/Jy6nUzsFlAHRpC7etD7etD6+9H7etH7e9H7e1F7emZIngHQpQNUitDpE8PYQhZDCd+iU4mEVPnHiHOO+y/b3NSbFy2qJBLFxZgAq/X9fNqXR9NXcPMkvuokoaRhORzm5pfzhsVs6kzdIjreDb289e811g+8Cy6ImO5uQ3B+tnvwc9J0FEg1thI+0VfAMNAPvkU2r7+DWqtTnYGI9QFo4yohwuhgUxFRsNkTN2fRG1T4xyjrefS3ADnzv4RI6EE969u5fGNncQnydDCIi9LtUbGRnpAEHCGR/i67WWcUgDDkY94zm8wNz+I0P4hmAaULIfwCAzVAzBhOvm7cRaFi85lqa2OSPM/2CjG0Eqs5FmTl7G/v4S21mMYsaeybtoc+hxpAMzsaWFxWwMzpq1j0LRQNzCH+rZqBm0+IMnYa0Y7OGmimYW9u8gYH/psbalYGPN4CTkc5KlxnJ4MBsJuglYX9bNTSFgFHIYVx9AiAGRvC8X2N/AbTtqFAmIcnI9jMxVyDR+KKbFX6sfYJ01uCqSHizlFLMYhikRiQQZrn8U9Wo9VPTjJNiYp7E4tojG9mMHMTOI+D9WWGBWzXsXtGWFs+w8hVsxK+Zukqx2MKcuY4CKsoSJCEtwyz8Z2n4Jsmtwac7BUtCIrEpIiIisiVodMTrkXm1MhkRhhV/03mJjYDEBJybcpKb6RD/eM8JNXGugcTR7b8eVp3Hn2NOK7LqBqw1Zk3QRRBkMDdzZINpjoSJ6qKRDstjLWlkraj/6G+6QTj/p6jA8Pc+f6O3l/YjWmoKCm/Ri/o4i0uMHfN0XIj5q4lcdJkZ4F4B3nrdwxOp+IJHJ5QMGjJjvaqsXZLD63lA39E3ztye2kmCHOtu1GMA0WF5fgWrMG34YNSIqTkbxyNh13MpItBVN2M5Hbw3Hpv0YWVJqis1i7YyXBuIPRmMywmHJYRaJUYYL5QgtL/I0sWtOEYAikXnEjjsWnEe8MkOgKYMY+Jl4ggJLtRCl0sT2ygV83W9iT8CBgIAkmN58yja8tK2MgEOPvb+3hnNoJ0hB5iwSbazzccmoVhcN9DPzsGcyoH22oAcPfffAu7HYcCxfSUKbwZ2UtXT6dDNz8T/s0qrYPEW9rnypseBAUBWtZGbaqKixVVdT7h9iyaQ2dBXEaqiOMyElyZVMFTtmmc153FnPufxwlb38IxWBHgI0vtdKzO2kE6XWojFe+x6nFb/Fu54m83p602M4rcHDfVceS6bER3bWLnm9+C62/H8HhIPeuu/CcdirtHX+hre1ebLYC5s16g5eefZf27r1c97WrychKP+r7ax/+X5Gg4eFhRkdHP3Gd0tLSKQW4vr4+li9fzjHHHMMjjzxy1PkU+xAOh3G5XLz11luceurhLeT/NzxBodCeyYlqIwA52RdSWXnHvzdRPQLGxzdT3/At4vEh4roX254ljP+rk5AhIpkG1hQPjuJCHKXFOMtKGRkdYfWeZjRFxhGPcnK2h5JLTkTVB9ETPaiJbhLxbmKxHqLRXkzzkyejIIGpT8WKG9FCokMnEu6vITyaQjycJDDeLAenXjcDR6aNlqEQewZD7BkMJpeBIH3+Q40j+5DntVOV7aYiy0VVlpvKLDflmS5sikQoFKK5uZnGxkba29sxDlCctFut6CMDuPq6SRsdxRNTSTdlUmICZk0VvSXptPR3E/UfnMMiOFyorhQSdhe63bW/ls8RYLfbiU7KYOfn51NdXU1KSgpeOUFW7e+xNL8CgO7IZFvmxbzTbUOb7H8sFguKohCeVKydalVJYtGiRZx00kkMte7l5Xt+TjQYwJWWzgXf/TEZRSUYRpy29j/S2fkA+wqsTpt2D6mpiz/lmn0CtDiqEWN0fA2DQ+/zTNsq3prQ0RBQDJPzGk3OeQus6v52DtjcdCz+CiNCOaIkcN7Nc+mVDf74QQtr9gwDySCFs2blctNJ5VNCC/sQims8tqGDh9a2MzZJfgp8dm46sZyzZ+fSMhRiZ/cEtd1+6nomaBlO5tPdteRn2OU4/6i/go/6FuO1iRyvhCndtoryvj2U+PtxT68h85abcR533GFP1zRNxp/bQ2T7EIgGkfW/RR/YC5KE7+ovkXHTTYj2/fOdfV6fpzZ1UTsZdgdJr89liwq5aH5+UiDiKGCaJkYgkCQ4k+SmsyXM5oFiNGRsiXFm1f0NV6j3kzckyyi5uZiZFsLOPaRnBMhWYsiTZH5QzuflyErmG+eThUQvBt8kTHVlOlcsLuSk6mRh1Y+jeyzCq3V9vLO9lZTxZkqkZEhqTJR5ccEK/HY7QiCBZfMIK3N0fny8TuHc847q3D+Oz0nQUcCIRBj+y18Ye+RR0HVEt5vMW2/F+4WLQBAYSKjUBaPUBsKsHgvRGI4SO4IFyBMJkhmaoEJu4vTqLE6tvIIURWYoEOOvH7by1OYuEpNk6KSMKIXBJLGxhse4TnmRdEsA05mFcNULsOt5+Oh3U9sOmTYe0s/gDecF3HPVUmblezFNk+6ep9iz9ycIGMR1eGLcQlPYxqKR2eSEi9FEkbqSEjbnJ9U6ysLdXN/8LFlVtciOKOGJTLRXZlE/IrI5exqNacXJQlWmSWFwkJNGmqgWQuB0obs8mC432Oxo/gkSnV0YY6NIpoFs6CimzlPnX8yOskpcssi9dXFKxlW6VJMWNcBY6g4QTZBMxIQFQzrY0mBBpVjsp8Roo5QubM7LCI6dCqZATAlRK+6gQ9UwFYUzE/PxmHZG9Qi/0vrYYUkljkRRYJCZo63MGmll5kgbKYmDB4GEBL35dii04VwwCPmpKClujGA7i7ZPYFFNOnMLeChxK28VzKDbI+PUTH67I8osh0Te2TVYi458jxmGyt6WX9DT8zgAGeknM23ab9BMB/evbuOvH7YQ1wwqxF5esN2O24hPlnQ1k9LIlz4FVg/69n+RePo27O4DYtbzF8GxX4fqsw8b+7zvMT4wEdM0TV5pfYW7Nt1FSIdA9h2oSj45cZXfbxqiLOomRX4It/wypikypn6XkG0Z1jw3PeMx9rQH8esmVkWkeoadoUAvbeMaNnGUIXkQ0RQ4WZ1Frp6K9DFCE0ndTc+8ezGlBK6huWTvvJERi4KRopCX6WRooIWdrU20myItsp32lBz6dRupSMxCYiYSxyXi5MlOBPFjZMkiYi30YCnyYC3yYCl0I9r2t0lT69Pc+dpeNvYnC9lJgk6Kw0YgrPJbHMxHZkAB5WQXBZ0NhNetI7xly0GqTQByTgmeM1bgWno84eoCbt98Jxv6NwCwsnAlPznuJ6RYk3lNRjxOvKWF+O7dxHY3E29qItbcfJAHKWyFVbME3lgoMTKpAOuWXVwx/Uou9p2M/yvfQO3qQsnPp+ixRwmJKWx6uY3WHZODvgTyMXtxpj5MliP5ncNZw4BwGz96PUowrpHhtvKXy+exqMSHNjZG7y3fIbIxqT7nveYKmhf+k1jEgjj6c5rqA4w7k5Pp+VUncPZln71g6v8fwuF6e3s58cQTmT9/Pk888QSSdCj5/jR89NFHLFmyhJ07dzJr1qyj+s9/s21M06C751FaW3+NYSRQlFSqq35BZua/EbJ0FIgnRmhouJnx8aRiY07a+RREzsVeXo3g8xCL9RKNdRGL9hCNdeMfbWZgoB7FHkKWD7UiHwhBkLHZcrHbCrDZ87HbCrHb87HbC7HZ8lGUVMKRFjra/8zg0Osw6edJT19JSck3cNqnEY9o2F3KlDrj4RCIqewemOCXax+hvm8MEjk4zXImIocfw0UhOfGsnCRFldluilIUEqM9tOzZTUtLC/oBhg5BU5EDY8iBcaTowfm0piCgO9xoLi+aOwVT2T+JtdvteDweUlJSDnrd997tdqMoCjt27ODll19GEASuvvpqioqK9u+g9QN4/TswlhT30EtPYmfeVXzU2DtlHLDb7UybNo20tDRqa2sZGkoaNn0+HyeffDLZ3hRe/PVPGe/rQbHZOevbt1E6N+lNnJjYSmPj/xCNdQEChQXXUlr6HSTpkyfjpmkSjw8QibQRjrQRibQRCu3G79+Oae43Ko+aKfzL76IxmCSLlSkVfNM4BePFWty1m3GqUUwEdk3/CiMZc7AQ57QTEuScfgL1IYE/f7CX95r2G2pPn5HNTSeVU+hz8NiGTh5a28Z4JHkfFqU5uOnEcs6bm4dyhHCwYEzl7fXfIpW3afcXctemb2Nw6DirCDA938vs/BRmF3iZXeClJM15iHfG1AyGH9pFoiOAlKKgD71I8M0kcVXy80n54R3UZlWxqnmIV2v7DvH6XL6oiOPK0g7drqqiDg6h9e8nOVOEp78Pra9/ylN1IELOHOpmXE/MnoGkx5m25wlybSMoubkoObkoOTkouTnJ18JClOxshPgEbPgL5ub7EBIRDFPgA8ssnrJfzeqRbHTDJAuBP+MkB5ER0aTwprn4co/OINMyFOTFdfX0NGwiVZ8gaLXzr3nLiVmsSINR5NoxnBaJF75+HNXZnxdLPSL+GwNNrLGR/jt+RKwhGbNvnz+fnJ/eSW9OPs8OjPHcwBh98f0de75VodxpQwSawzF644fv9IvtFma6HMxy28lHYsP2Pl7a2ktCN8gR/ay0tCBhoET8fEl8gXzbRFLlxEx2tPuEE17Ujuflkh/xu0vnkeq0oKoBdjffztDQ6wAIoh3TiLIllsYT4ykI2gB54TwWjsxHMhR6fOmsrZqN3+LGpsf5Xvd9VOV9iCGLWHodhDcV4ts5DhMxtmVWsaV0Pluzaggc3hF2VFDQyBaD5IgBcqUgXuFgdTdMUNQUlLiXFEuIc6x/JV0YZbXrDPZO6NjNGNlkUWVegKIraDaRPRUiWY0x0nSZbnRuIsLo5ACpoFGiDbNQ38NZzo+YKzWza+wM7EPlWEf2oo3sgXgANc8gvMwgutDAnOzPRU2hNFRJUd1qOm3ZXHLs43QYFiwJgxu3BrksKEwVX5UKXXhPKsJWlXpE5Ze+vufZ3XwHppnA4Shn9qz7cDhK6BqN8IcX3uOWnm+TJ4xOXV+z5hyECx4ExYba10fXtV8m0dGBvdBO/uVVyN3vgT5pPU0phMXXw7yrCOJgVfMw7zQM8GHzMJVZLh65dhEe28EhLN2Bbr639nvsGO9iIutHGHIGTq2Pgq7fc5q6jAt6tlEpv49pyoyodxA35h9wmZI07eBLZ/K2spMeaZRUw8W5iQVIiJiJIEZ4hFDWdoaWvoMpJbCMTCOv9ptYjE9WdzFNA0Ew4DADjxGdQB1r4V/eHN5zptCOQWmWm1n5KcwqSA5I1dkeLAfU7Rgf38hD7/yVR+rPIqwms3Jv1EUuk1youkrfhj/iG2k+eD9eH5aqKsyuMNZZVyLZvVgrvOxePs7tW+9gLDaGTbLx3UXf5cKKCz9V+cc0TbS+PnbvWs2z3a/wttREbLLCqidsctZmg1N2QPqsBXjOPAPb3Ln0fuObqF1daN4sNtfcRMzqAwGqlkSJZf8Du1ALQExPYUb1bRTmfwFBkGgfCXPD49toHgwiiQI/OKOGa48vBl1n6N7fMfaPfxBy5tI+YwUjjoUk5DATvp0gmFQXz+ILV56HdIS6J5+E/+0kqLe3l+XLl1NUVMSjjz56EAHKnizA19vby4oVK3jsscdYtGgRra2tPPXUU5xxxhmkpaVRV1fHzTffTH5+/iG1gz4J/622icX6aGy6jfHxJAFPS1tGTfWvsFoz/+1tHg1MU6e9/U+0d/wZMLFac4DkJPfTkEjYEMZlMt0leGqW4rAXThEeqzULUTy6/IhwuIX2jr8wOPgq+8nQCkqKv4HHM/OotqHqKresvoUPuz/EJtn41XF/wkUFe4ZC7BkITnmP9k2aPw5ZFChOd1Ke4cAnxZFCQ8QG2rDroamUSUFLYBnuQ5IkbNl5pBaWkuLzHZbofFJ9qgNhmiYvvvgidXV1uN1ubrjhBpzO/XLfqLFkUct19ybHB9mGecJtdOWfi2YKFBUVIU/moRiGQW1tLe+///6Uh6i4uJjlS45n81MP091QhyCInHjNV5l76lkAaFqIvXt/MVXQ0+msZPq03+J2T0PXo0Qi7YQjrUQi7UQibUTCbUSi7ej64WXPHY5yMtJPIj19BSkpcwGRl1tf5p6t9+CP+xEQuLzmcq6t/Aprn1tD3+tvM7O7ka7qawm6i3BEBpi/83ekzJ6Ge+UKumYey/0NAd6s338/KpKAOpmTXZLu5KYTyzl3Tu5hvRL7kNAM/vL2a8yw3YIomDyz62a+su4dsrMa2ZtawE6jjFpxFnVSJf6PRyEAbpvMrPwUZud7mZXvZU6Bl+wUG3pYZegvtehjMZQiD/3eLsw//BrbRFKW/r2C+Tw44xwCVmfS67OwgAuqUkgJjqH29iVJzYGhav39aENDh9TCOxwkn2+K2Mg5OSg5uRhpuayts9Pfk7zPF55VwsIzig81JAQHYP2fYOs/QI0wYTp5zv4FHo0voifqnVptJhLno3C+fB9x/SI0M5cx0SD7hjlkFn5ynacDYRgGq7bsYt3qVfTJIq/OXoIhithaxpHbo7z/nWUUpTk/fUMfw+ck6DPC1DTGn3yS9vseYNW02bx17HLqyyqnfvfKEudnpXJJto/ZbvtBE6CRhMauYIS397SxtqeXIaeXoP3wFy3HEHB0hOlvnSDdDLDSsheLoGPGY3xRf44yxwi6aOFVy5lsCqTyc+XhZOzknCsRzvkTE4HtNDTcTCzehyDIlJbcTHbO+WzffhnRaCfdZj6/Ci5DDryBXRWYPzKf7Gg2EcXKppkLaHYnq9QvC2zgUvcDeAhQ0xwkZyDOcKeH0Z0uiIIuiDTPX87InGMZr2sk7A8SlxRikgXVl4FeXIqekU3UFIgkdCKBCEpgGI8UxCcGSBPCB+bUY5oQRcEhqOgmvJuo4Dj7OOVDJZiaHUGKMzf9cY7hDd4z5vJd9auM4SELgV/ioJL9k5c+DG4iTEIIky/6yRP9nO7u4dTIM9hJdsCREYWRejcbWUhs8bXMz97FRN5bxNI7prYj9wo414jYNyfrQ42dlM7XzvkJQ9Y08k2VJ2eUUtsR5KnXmjgtYeE0FJRJQiBmOUhZlo9jZgaCcmgH6/fXsmvX14knBpFlN9On/Y50+yzi9y3AGtzv4XlUO5kPS7/Dj8+ZRU5gkK5rv4w2MICcm0Ph3/+OtaQEgoOw5SHY+neGwhrv6vN5xzyG9cY0VPPgfS8q8fHYtYuwSiJGSEX3x9H9cWITYf7R/wT/SKxmLOt2TMmDJdqAZ/gefth9FefGP8AhrcUwrYwk7iRhzjjis6KaOp1mjDX2bRiCyvwZszj59NNp3vUO4413oBcnB1lro4DvPhl0AWxuTFceUuY05NRiZGcWktVzqJfnCDD1BEZklLAaJhILEItNEI0HiCSChOMBNEPFaVdwO6x4nFa8Lht2i8rg+Hb2jqdTKORSUvNFAKJbHkTr3YIqSjT4StiWVcW2zCo6PNmYgsjSsT3c3rIVx7xrEGQrHZY+flzwV1KzMvj1Cb+m1Fv6KUcLhmmwrncdTzY9yfq+9VPfl3vLuaTgHE5oEkm88S7RbdumfkvYUhicfT7pda9hj44QtaUxfOWtZJ74EaMTLyEIBqou06Oex1Urb8dqOdjiFklofP+FXbxcm5Q5PWtWDr+6YCYTHUE2PbGRgZEkEdWlKP6MWnRUqqqqOHbl2RR/Smz9kfC/nQQ98sgjXHPNNYf9bd/Q19HRQUlJCatWrWL58uV0d3dz5ZVXUl9fTzgcpqCggPPPP5/bb7/9/1qdoH0YGHiF5j0/RtMCiKKNioofkpd72X9VevfTMDq6lobGW1DV/f2WJDmx2/Kx2Quw2wuw25KvVmseGz7YyfodSQ9jXk8PJyFQ+Iufo2R9eiL/kRAOt9LR8RcGBl8FkpNAt3s6Lmc1LlcVTmclLlcVFkvGYdsmoSf49qpvs7Z3LXbZzl9X/JUF2QumfjdNk5FQYn843WAwGV43EJyy0n8ciggZNgOHGsBrBqmQhlmx9FhOOumkzxxueSTE43EefPBBRkZGKC8v5/LLLz902yN74fVbYLKuHOlVcMrPkmIyiv2Q7a1bt44NGzZM5R7NnjkTubeNPR8lCf68089h2Re/jCCIxOP99Pe/QGfXA+h6GBCQJBe6fnCO5IEQBBm7vRCHoxSnoxSHoxSvdxEOR9Fh1x+LjXHPlnt4te1VALIcWfxg8Q9Ykrucl7b38Pbza5g97kWSHHjHm5lT9xfESUOxOm0Wj809l5eiKWgHcIPqbDc/PXc6i0rSPrF9e8Yj3PTUdk7LvpOK1DZ6O8qZ85teFFNHSvWSd1kVjsCbCFoMU3HTueRX7PScyM4ePzt7Jqjv9U+lOxyILI+Vikw3HhOWtUWYaUqsQ+V36gRfbHqLc9o+QsQk5nAj1kzH5R9B6+/H+FgI42HbV1GSxCZ30oPzMbKj5GQfFG53IAzd4KN/tVD3QVIIpHRuBiu+VINFNqC/FnY9B9sexdTi1JplPGG5mNeiM4lPcj+HYrDU1c7l47MoQ8JxphdfVh/qMzczGr0DzcxnXNTxXTebvJLPVnLBMAx27drFb7c38E5xMnfq2MY6Hrr0TNLSPvk6Hg6fk6DPAMM0WT8R4pn+MV4bGic22SKiYbCoYy9XTi/nrIVzsR2FssbAQB+PP/4XRuMORt0evHPn4vflsSsUpT26PxZaiGpIrUEy+4c5RdmDTdAI6zJFE3X8034yXWIuKXaFp47tYfqG74BpECifx5acbhBM7PZCpk//PSmeZFJeNNrDtm0XE08MMihV84P4jSj+F7CFN1EaLGXW2CxEU2J3URXri2tQAZ8Q4Trjt8w2a5m7M0xqIIqhCYw2uRjd7cLUDxhMZNCL7UQrUgll+IgKTsbwMGE4CeoKcV3kYw4DJuxO+p0SY8Z6NEmiIjGTrJCCpEcxDIVR/yyc9gnKxQTqWDIJ0pdSz5nW36MJCX6hfZF1xkxkU+JGvJyAnVFU3k5pZHFRlCKXQfPuZpojbqLYkNBY6Rtg5sqriAVS8e9cxUDkbUZL+xDdkwOZIeEanMt4q4cHXZvI69GZ3mkiiVX88upbCTucVIfaeGTt94m9KWOdNgP7/AWsElN5fNDNcimN87Dg2HeyNgnn7Awc87OwFLgPGoDj8WF21X8dv387IFAybKekqWuqmdYWfI0vt51AQjexiHBx21ouqnsdd3EhhX9/CCUnmRjfPhLm7YYB3qnvY0e3/yA53DKhlxWpcSpSZ/CT9ihhw2SJbOHnuu2whXYb7K3cWfI+bXk3gmjDGt5IzuAj/Kr9JmaK95Mm1qGaVt7lGkadMk6HH58k4VOzsY/NxRZ1TJ1jtzjK25ZaAOakj+OqfhNB1DF1Adc7IimrUpE9FUhpZUi+csSUgkNIj6nF0MfaMAK9GNExTC2BaEtBdKQhONMRHekI9lSET1GbMtUoRmQEIzKKGRnBCI9gRkYxIiNgGjiW3oZgcRIbWMW4/QniNQaJChPdno1fK6crWMyuoVw29WQSUS0sG1jN95p24jzmRkR7KuNClB9JGlqWh4pMF2WZLioyk0nWhT4H0iTjDyaCvNzyMk/vfpquYFL+VkBgecFyrqi5gkXZiw66R9S+PkZfe4udawZpt81Cl+1YY+PM3/EbbHE/WjqMfjuB7oPN/fNwZX6Tm1YuOeIk2DRNHl3fwS9ea6IsLrJUt+CdSlMx8IVq6c0aIuR24LXaacpZxoct47x3yzIKfJ9NcQn+95Og/5f4jySyVT/NzT9icOg1ADzuWUyffi8OR8n/iUP9VCQSo/j9O7BYM7Db8lEU3ycSsdraWl556SUMIGV8gmW1tZR/9zY8Z5zxHx1HONw2SYZeYR8ZOhCKkjpJiCqniJHLWYksu4nrcb71wbf4qO8j7LKd+0++n7mZhwoiHQjTNBkIxGgeOIAYDQbZOxiaKhK5D24hxgplLwurCrjwwgux/Ru1TQ6HwcFBHnzwQTRNY+XKlSxZsuRwB5qcwL79AwgnQ2WRLJC/EIqXJJf8hVOkaGJigvfff59du3Yhiipud4SilBCRkTps3gSeHBnFHcUwoofuaxKy7MHprDiI7DgcpdjtBclCm58R6/vW87MNP6MnlJygryhcwfcXfZ90eyYvf9hO9/MdyAb4Yz3ktL/E3tQCXi5bSnjynHJiE2Q6ZHYZrqk747iyNL65ooJjSg+dRL/XOMh3nttJVcpGrp/1KEZCJOcnEorqwnftNfi+dDWSy5kkmS99HXqS+b6Ur4Sz/wgpeai6wZ7BIHU9fra0j7GpfYy+iehhhToKEEm1yRRWpnG6K0LZ3+/FbG46ZD0pNRUlJwc5N+eAULXcqXA1KS3tqArlfhJ2f9hI68uvky01UuDaQ4bUgqDHCJtWXtaP50npHBri+z3NNTkerjymkFOdDmJP7gYTRkteYbz6bWpqfkVWIovEY19mLHgbmlmAX9BwXjOL4srPTl5UVeWmDbW8rCvIhs7bC6qYnvLZjXSfk6CjwHBC5eHeEf45MEZPbL8rvNxh5Xz/MMfeezepHcmYW+8ll5D5nVuQjmIfodAIjz/+UwYHk6ID06fXcM455xETJepDUeqCUeqCEXaForSOhElrHuAM/04cgorfsLJHz8ShhalwRahctozpExvxbn8YBY0Jn0hkwemUl38Lm82DLMsoioIsy4TDe9m2/TI0bYK4cxG3xm8lGGrEPf4YKZEQC4cX4kv4GHV6WDtnCQNy0i1/mvkqX1Le4biCHyP1NBJu+gChrZZQrYEakfEURHEXRRlXUmmjgHYK6SCfGAd38i5CKNIgWz2jNKTa6cu7DUQrM4c38O3GN4jhIIyDLnLRUJA0G/ZQAZptlPTUYRJdx2PqFkQ5wnHevzNL+oBNwhxaKeIUczVuowBF7EQSDiNZOokIVkZTnYwUWBlLUaeImaxZ6e0qIrP7fKrjNQBosR7emfN37ndm0+v7JogWcsb28Hb9/5BpTjC2x8ng9gPcuqLIcFo221IrceYvYYE7j8wDcmF0j4heYUeo8WBJtWO1WpFlgd6euxnuf56ZjQHSxlVMQUA4588w90rahkPc/th61g8n778cNcidly4gOyeddxoGebthgL1D+1X7AOYUpLDCFWZJ/16y/ZnoZpIs1aJxCxESwGko/AAbktuCKmsE437G4xMME2VQCvNg8RD9xeeDIGMLvkNl/xt8wcjm7MA6sqNBErLA7mPn4Sg6jbS0E0hJmYcoWhjtHWXHPxsxOzW8kkCzbz0tagJZiTF/3mukBsvJ3H0FVjMPM3po6IAmjBN172FEGGaNmct7OfmokohomJSoEb6Sl463p536D94mHggkL5/XQb8nwunNKTgtaRgF5XhqFmHEBMyYiKke3YDQJYRYO3cH07N78cp7icfa4JDhSiQmplMXnMDWYrDiPTeeom8he4qJY/ILonzAwZZhiyxSkBlCSV3PkLkO1UwmZLsUNxdWXMAl1ZdQ4C445Hh01aB+bS/b3uwgGkxef68tSpH8d4yqnaQ+qiCPCER9Er868TJWVh/DdZeegKAceYKhxnWa1vex+a1O4v6k0UXFhNxdVM5+hoGhK+jqHYWEzsvqDMYlF7IocPeFs7hwfv5RteOB+JwEHRn/Sdu0tf+R9vY/IAgSxcU3UVz0tX9rYvn/Et3d3Tzz5JOEYzGssRjHr/uIssWLyf7RHUgpRx8uczjEYn0EAnWEwnsIhZoJh5uJRDo5HDECsFlzcbqqUOxl/HrPJraPtuJUnNx/8v3Mzph92P98EgzDpGc8yp7BIM2DQZ7a1EXvRBQFnWVKK7MzZS677DLS0z+72MjhsG3bNl599VUEQeCaa66hsPAIdXyi4/Dhr6DxZQj2H/STKVnQsquIZObj9zkZs8fwR9rQtCOLIAlI2B1FSYJjL0FVxxkceh3DiCJJDioqbic35+L/mmcyqkW5f+f9PNrwKJqp4VScfGvet7i48mK6G8Z5/m872WbR2GzV2GejzYn7+WLTmyzt2IaESZ8jjedmnMq7OXPQJ41ni4p9fGNFOUvK09EMk1+/tZsH17ZjERPcfdydeBxB3K9bKMq4mrTrv3posV5Dhw1/gQ9+DnocrClop/yCWt8ZrGkZZd3eYWq7JzgwZVwUwOuwoE8qMn4csihQbjdIlQywWBGtVrBaQBQxzSSvNTEnX4GPfTZNc/J13+8HfjYP3oaWgEQEU41gJqKYk+H1JmAiJBdBYggfYSPZz1hkkbNm5nDFMUXMK/Si9oUZvr8OM6Fjne2hq/JuJvybACjIv5ry1ItQH/0K46NfQzOLCAgqli/OpLwm4zPfB7ppcmVtC+kY3Du7EuUoFfEOxOck6CjQG0uwYEMjJuCRRc7LTOXSbB9zPUlrtz4xwdBvf8vEc88DIGWkk/3D23GfesqnPvSRSDcvvPgdWvZWAyLp6elccsklZGQcfEOENJ36UJQPmjrwv/MqdvPT65IcCbIsI0kCphlAFFUUi50RKZtRw8Q0xhD0AZyqHY/qQRclNpXPYldOMQA5iX6+HFnN8cUXoSi2ZCxxeJjRrt30DI7TNRadKga7D1ZUisx+SukgYu3lgTSTBlsy0SZN01lqVPL3sjswBIn/6fgH3+h8ki7yaKSCHUzH5ODJq88RwDE+nfh40tqZ7dnKadY/o3gcjEy7But4C/b+DdjDPUkxAUBDwkBAlHQGMq305NoIO/fHm3snVPL7omSMJqaKxEb1YxlXb8TAy2u5Ij+bbkcXRZaMbeR7e3+Ow4gxLZHstEZHi4gOZxPrC6IOTXysxQW0rBmIxUtwZc5AkpKdh2kajCT66DA6aVdGOcv+NsXWLiyaiS7CtrJcdkauQhAykUIhtIZGdouZvOmdT0Q4NF5cEmBurpNlGU5OUBXSu2KYwQM6VVHDJmxDFup508zkh/pSDETmiD3MVvoPEiLSTYH3EuX0m14sZT0EypOqP46Jf3K6+QZfLzmeig3rsQy1gSsLrnmTMSH1kHoaDkuUitJaXOlt1O44nXDYh09RuNB6MuZIfF/zoGQ7sRR7CLq20h77LZbUFHLfKSNVeh63rrHNUsPPym5kS/p0jEnr1tyonx+W5SLVb2XLKy+gxpLWSMEeY+XmXhQDas+s4NRfPILP5sNUdbTxOPp4DG08hjYWRxuLEh6OYIzHURIGE4LJV8wQA+wTkICFhVZOr5pgVmYfirmbCX8tauLgwqcAJMA2kYM9OhObv5Se1Jm8Yclgz3CI9vB28KxDdu3Z38bxTNSx4zCD8yhO8yU9RpkuyrPclGe4KE5z0LV9mM2vthOclPdOybQz98wEUflv+P1bAIj1u/H+QcYXCBOVLNj1BFJqKu5TTyHlzDOxz58/ZRGMBBLs+rCHXat7iIeTJM3ilNnjhtciQaKiyeWZu7AE4uiIvB6vZsx0Mn2kje8kGln6mztRsj57jsnnJOjI+I9Ee4w49Q03U1T4VVJS5vyfOcD/C5iYmOCZp59mYHAQ0TCYv2UrlZEIOXf9Atfxx/9X96XrMcKRFsKhPYTCzZPkaO8hOUwJAx4YsdISl7CLAj+snMeszAVJr5GrCpst/1M9zx/HSCjO157YxpaOcQRM5svdzHNMcNFFF1JZWfnpG/gUmKbJCy+8wK5du/B4PNxwww0HFe41DA1N86OqflRtnFi0l8TAVqSuLVgH9uIeGcWaOJgg6gIEPDLjXgsT3hT6RB/+kJtYwIrZFSY2KqJIWZx3251kleyXhY9Ge2hs+p8pJdT09BVUV9+F1fLfIXwAzWPN/HTDT6kbqQOgxruAMq7jpc1+ovpkXqUkEph8b9FVrrENcXZwL5bN69HHxhi0p/JcxYm8U7QIdVJMaHaOEwyTnYPJsPnvpv6NyoVNKFEni+a8gi2v+IjHZJomvS07sb52Exn+ZFHPD/Q5fE+9jiGSpKk0w8kJFRksKU/nmLK0KSn2sXCC9c81sWP3ME2Czm6bwNhhiNH/BhT5HFxxTCFfmF9AqjM5H9HGYwz9tRYjqGItSyH9mhmYokFb++/o7LwPgBTPXGaU/Bjh6duY6L0M1SwhRALjihlMm/nZQ2EThoHlP/B4fU6CjhK/bOun2mnjtPSUQwqj7kN402YGfvxjEh0dALhOOonsO26fClc6Eib821i16ts0NR5LIuFAURTOOeccZs48fEKnf8LPmlc/YGzcz0BgEEnsQHIYGIZEVHeQUJ2kJoKoyMQEK7opT5GBfxedvixWVc1LKnLoOse17mJaf8dh649LkkRhYSH5cjqpTZCuuej0DfNE9VusH09aBBySjatzl/Ol1DnYYgH+POHkLltSTemk3VupHDywKF1SGiDf6Cc1nEl/eBmyNYA7dycTnceDISPLQZZ77qPKsv7ggyk5AZZ9j2BaBu0dDzMy8iqmmZwsm7pEdDAdo8+HNSLiIIqdGHZiKGYCzTTxmCJP53+PeyuTdUTO6hvnD3tuwyns4UhQIyKRISuRIQuRYSuJ4AHJvbINOXc+SuGxyOn7Bz1TjWAX1+C2v4ug72Xn9BQC2RJGTGLwwxp2hGbTaM+nTc4kLnzc0mtSLYS4DphlZmBnP0FKoNEtjtAlDTMojSEIOmFDxxBEWvU01qrJvJW5cjenyjvJZ4AU+xCP6Ct4P7AYqxTjh4v/yM7U03hSOx0A1+hDnOmT+Om8W3A89gWUsWYCopeHjIsIkMw/EUWV6dO78KZuBjQEQaGz+Qw6+70gGLgiZaxctpSqaV6suS7EyUFA04J8tP4ENC3A9P4sUpvbies26orSCGTY6YiW8KLtInZ5C0AQkhOmsSGu1B2Ye/sYbG0DJHKH25jRmox9X7P4VJRpZ5Eqp6IlDDTVQEvoB703dBOBBJqUYMy00aKYtCg6Ax+LFfTpAuWqSI3kp8jbiTOtC4evE2tqO5JycEhIzIDNAQdrQgoj5uRAZgoUBWdQM3QC6f5KVN1E32eZS/489d5hQoqR7GucKRbmnelGTHucwcGXABNBtLFx8DQeqTuerHicv274G/LoMIjiQUmxcnY2wsrz6EhZSMueBPqkxKwnw87clQVUHZvDRHA7P/zn03T3zGCx0oVpwgdqOSFbJjeXCiz8ww8hGCT7zjtJveTiI977R8LnJOjI+LxtkkgkErz44os0NSVDfyp3NzN7507SLr+czFu/c8T8hf8WVHWCUGgP4fA+crSHseBu/jKg0haXsAsmX8+MUWBJ9gmS5MDprMDlrMLpqsQ1lW/0yZP8hGZwx0v1PLs1Ka9fLg1zrNzJKStPYsmSI4ewHgjTNNC0IKo6jqr5UdVxNDX5GolM8NprEwSDkJUVYd78PehakvRo2pFzdCY3jCMmkBlx4/PruEfHkKMHRxiYkhW/p5K6gIe2WDqjXSFIJJCtVs761m2UzV98wOZ0urr/QWvrvf95gdUjQDd0Hq57jt+9X0d4dAEYSQNrgc3C3FGoQWb2VVU8sbefN+sH2DeTXVKayjeyYhQ3byX4/vv0D07wfMVy3iw+lsSkodKViHBr6+MU3tSEKRnMmPFnsjJPP+QYJiIJ1reOsnbvMGv2jNA7EUVC5yvSG9wiP4dV0IiILupm/oCC5deQl3rkkGJTNxl5tIH4nnEEt4J+VTWNgSjhuI4gJA1zAsKU0VIQkpJEB36/7/PkGsnv1AjCyF6EkebkMroXQYuz38cDgighpJUhZFYjZNYgZNSAIwUBAUMz2PFuF71NYygITM/zsOD0YkpnZyCIAkZEZei+nWhDUeQsB5lfm32QGuvw8Hs0Nt2KpgVRFB8zKn6J8/W/M9FyGqpZSpQ44YunMWde7n90P3xWfE6C/ssw4nFG77+fkQcfAlVFdDjIuPlmUi+/bKqQ4+EwMPAyO2p/wO7dS/BPJEnTokWLOOWUU6aUWz6OQKCO+oZvE412YhowuCOdkb3V9C2/Gru2jTvafoGEwdPZp3Nr+a2IpklBWGX2uMosDaZbZWwpTXRpj2IYAmm+07B4T+WF3hHq/UGs8R7c4V1khdx4VS8Rxcrq6XPpTEmqJVWFhjhvsAdrIobFYqG4uJjS0lLy0nMIvdJOtH6UQWWUJ8ve5j3hI0xMZFHm4sqLubzkcsb7xmltbaW1tZVIJMKmkmnsKKxENAzO27GGxTu3kz3Qj1ZWwpbs5INxyQnVeOJWVq+2MT6h4CleT3y8iLg/GUZU7F7LCvsD2CwaRtlJjFTNoMesZ9y/eardHI4S8vOuJCfnQrq7R3jzzTenZEG9Xi+lpaXouk7r4AR/tZQQKfECcGlHhFuadQR0+m2b6DW3k1D6OdFoJNNQmRBFmhSF7JhARsLAJmrIioGhCmgxkXjQwnBvBtuiZfQoXtIkK5XeYnKzahCt+2NijXA//uGtvLdgnNVCGQ2jVajGfmKTEg+xaLCJ+WPtpMTC9NrcjNpSMG0pnGjPoNTqps+u0WYP0aP40Q8oKGuayc7RGouSqo/S6M7jlUiyJtNPrP/gauE9HtDO5C7tCkQMHnDfx0nV2YjlJ/NTeRZ/HUqAaeAZ+QO+cDNLBqfz/dh7pDHBCKm8X/gd8qtFDOMpEomkZTXNdwKVlT/Caivmx7/7F3KwHkwB7+gcvM40HCnWA0iJjqf0OVKrXic6WkLn+9/nkCQyoNen8v4cK50ZyWujaCrzOrs4tlHHFUlDQKC09SVyBjcRs3pprL6aqPPIVqZ96nYmBpoSRJPDGKJKHBjCSqtoo1lUpsImABwGlKsS5apEkQYO9zC21A7C6Y3UOfeyWQ8TN5PHbhNMFjs1lro1PDEfsbESYmMlRMeKiY0XYeqHl5SNCibUWDnvjG109zw4FXvvST2Ln69dxs4+K6kOhYevWcR0KULnl65G7e5GysjAMX8+fbVddKQdz3D6LJg8dp8twtxTCqk8bSaiKGCaJlu3XczrW70Y/XmIAmxR82kT87nvqnksq8wk0dmJ/5VXSb/pxn8rpOXzif6R8Xnb7IdhGKxevXpKXS+nr49jNmzElZ9P7q/vxn4Ew+D/KZimyViolRtX3ULDeDsuSeE7hRn49K4j1jFSFN9BIgwuZxVOZwWy7Dxouw9/1MHPX2/EMCFDCHGiZS+zK9M4YVkOAqGDCI6q+lHVCTRtAlWdQFX9HCmkDyAUSqV2x+mYpkRJyTbyCxoP+l2W3ShyKhZr5mSeTgkOZxlORyk2W/7+kErThNFW6FgLHeuSr6GDveCqKdEX99ITdNId9lJ63o0sPPeSg/qJQwus/nfqVo2G4jywto3HN3QSSSTDqkVrH5b09ynJCXJ55/8Q2Gtgdytc9N0FDBk6961u5aUdvWiTMWlzCrzcuLyMJUqQ8Acf0Ll6Pc/E0xl0pPJ1+xC2qwOMxtfi9S5m3twnEQSBhGawo2uctXtHWNsyQl3PBAfOkBVJYEGRjyUV6ZycPkbFhtsQ+nYkf6w8Hc7+fbLe3xFgxDSG/roTbSiCkuci4/pZiJbPINlvmjDRBd2boGtjchlq5JCwbpsXCo+BgsXJ19y5h4hk7EN/qJ9tg9tpWjWIbUc+op6cl0o+jdxjLczutCH1qIgeC5lfn4PsPXRMi0a72LXrJoKhBkCgtOgmcra04t85D9UsJ06MkXOrWXzsoWHhn3q+/2ao5eck6CjROhyiOM05ldj8aYjv3Uv/j35MdEfyxrfNmpWsBFxVdeR9tP6W9o6/0dk5l+6u6QDk5eVx8cUXk3JAbLSq+unte4a2tnsxTQ2rNYfCrO/z9u9fIDA8iN3t4bzbfoQnuBPnazcgmAZvZp7BV6r+B/1jbsOcqMGMWC/F3leooYFZY6eS7/giTS74ZTjANiWGLfg6ZYObmTc8B6tuo3uGg3d8J6IJChmyyZ+nl7PMl+zM4l0Bxp7azVhwlGcz3ua11NWoaEiGxGkppzFfns9Q9xDDw8MHHYfFYqGwuJhX8qtYo0u4JJFHO+tJ//29GOEw2+fNZW9lJYos85XrriM9LYOd73ez5fV2JGcLdl8HE23LwRSxKuNU5P4Ls2YXumdShtOEdKGY/Pwr8ZVdhXBADR1d19myZQurVq2aKmI4a+5cPiidwfMjScuZ3OynuD/CH1zjZI0mH1C/HGGVVE9C6OF6nsBJgsc9bn6dlgomFIQLmDZaztJADyuFj3A6kyFNalhicJeHD6JzyJ0/zgr3TuLGDEa0M4kbx2KdzB8yMNmCzpskaLQOMVuoY/mqBqYPdiAdjWdPEBCsVky7Hb/dw15nKg2WbIZ9XqqX7GRu/k4EAV5qOYNX205DwOTSqiGeac7ERODHlqe4RnwNHYFO8mmknLtrLmFvZg0YCVKG78YS28MJwlx+PbARZ3SQiCeFLdMlNEXEZs2lsvIO0tNPnhoQVU3n9nsfxB4ZQNDspI3OQzAP7twla4CyM7+HKKt0rfoOkZFqZEVEUOMIiRCmQwOrgYDBoNNJW0oqhiHjjJu4oxppoQQOVQT9P1deMjHRlCCq4idumWDcNkpU8TAYT2VIszJh2gmaVuyKyPSSAVTnGtpi+5Xc8jQfp2iFLEwRELJ7iRudHC6/yCKXYVOmYZOnY5WnIYvFrNk7xrvdz3Nu5auk2ZN1MlI8c7Gm3cJ1T0cZCMTITbHx2JcXU56ZTAhV+/ro+NLV9Ee8dJefyYR9/2CSPt5AQcc7eP0tCIC1uhrPGWewe6aX36zqZkY8hCIY9MnZ1Evl9PnjKJLAj8+ezhWLC/+jeP7PJ/pHxudtcyjq6+t56aWX0DQNTzjM0lWrcEVjpN9wA+k3XP+J+W7/JxBKhLj+3eupG6kj1ZrKgyc/QL5NOSCcLplzFI12cejznYTNVoDDUYyuR6cIzY7+LO7beRURzYFDiLNCaaHQ3cO06R9is326ApgkOVHkFBQlFVlJQVG8yUX20toqs379OKIo8IWLj6ewoBRFSUGWU45aevwQmCaMthxAitYdSooMkVEpj4ylVyCVLYO8+SBbkwVW2/5AZ9cDgInNlse0mt/8WwVWh4NxHpwkP/uEJ6bnevjWigokVwN3bb6LocgQsm7hi3vvwDLuITXHyYW3zcdql+kZj/Dgmjae2dI9pdpWleXma8vLOGtWDubICEYkTCR1hO3bLwVEcsqeZlNPGuv2jrChbXSKdO1DRaaLpRUZLK1IZ3GpD4flgDbWNfjo98k8LENNko8zfgMzv3DEybs2Gk2GloU17NPT8F1Rc+R6V7oGg/VJstO9Ebo2QbDv0PVSS5Jkp/AYKDgG0iuTkQMf35yh0zLRwo6hHWwf2s6OoR0MhPeHi9pUJzP7lzFjYClW3cF8h0S+RSSGyh1lfyOaoZLtyibbkU22M5scZ87Ua7rNS2frL6ck1dN8J1DVnU9gfTGqWYlKlN4zyllywqerqzLWDhv/lrwHL37009c/DD4nQUcBVTeY97N3kUWBE6szObkmi6WVGVNxnEeCaRhMPPssQ7+9FyMUAlkm7dprSf/61xAPowhjmga76r/B8PBb+P3VNO8+nng8hs8XZenSPKzWXvyBWiKRtqn/ZGacTnX1L1CUFMIT47x4950MtrUgW6yc+c3/odzeC//6CpgGidmXs2bJXXw0FGTDeIhdiQT6x56pVHOUuf4ox/amM29MIzdm0uYU2ZIywmrHv8gfsZIXycU9s4UnUy+lT0hOsr6Sl86X+3T0d1t4yfsBz6W9i0WzkhnNpMKowBF0HFRRG5IEr7S0lLKyMvLz85FlmbhhcNnONtZPhMi2KLxS7EP+858Yf+kl1iw7gcHsbNySxPXf+AYur5fgWIx1z+2lY1cXqVVvE+w6hkRw0sIiGDjT91Do3MhsdR1p+mTleLsPyk6EshVQdhJ4kp63UCjEe++9x9a6Ot6rWUhHeg4iJj8pyuHl1/bS0BcgxS5zV+F7TG9bjqx6QASh2kOo7SWquBeAuzKm87Rrf9hBbjiX2aPTucwbYXb4XcRYUv/fUDwIiQCCAFuNSq5O3IaOgxNROB2FuQfUwtGlCMGcTUS8e0hrOBl5XEIQI0jeBKItRiI6TktTB9H+AdKifryJTx5AE6JMe3YuGSfkUnbW6fy5u4onNu0PQbx8UT5frBTYvWM9zZ0DRPeJ5iHwrzlVjKZUIxhhvIM/R1Z7qLA6ubuzlYpoAr9bYfSsWykq/xaSdKhVaSIY4p7f/xlZjzGsZZKXvZBMl5UMWce752Xk0CgjqR4CsgNBL0ShimgwQTSkYuiftRsykdUw1kQAQQsz4lTp941jzXNx+rSTyc3IYndLPVtrNyFZ4fKLr2K8J05n4zAjHRESYfNjWzPR5DCqxY9qmSBiHaXN00aLp5WoJbBvJVzBEhZst3Jhn0zlkpswwgaiQybl8nzivm4CgToCwZ0EAnWHraciijYslgxisWTIzGg0lQn5q8yrvJAvP7YNf1SlPNPF419eRE5Kso111aB58wA73mxjYiRppRZMncp5acw7uwpvCgQ/WEXg9dcJrVtHzBR5snolb1Ucx2nWZlxCAosng1tu+iqqAbc9XzdVW+PCefn84vwZ2JTPXkAUPp/ofxI+b5vDo7e3l2eeeYZgMIjVMDn2ww/JGhrCNnMmuXffjbX0/64CXiAR4KvvfJWG0QZ8Nh8Pn/rwITL4uh4hHG7ZH1YXaiYUbiaRGD7CVmEgnMGfaq9nIJyJhM4SpZ0q+yjHL9HJyz2A2CheZHnf+1QUxYMoHrkoqWmaPP/88zQ0NJCSksL1119/UH7QfwWTpMhsX0Nw15tInetwfrzWn2yHgkVQvBSKlzDhgobm70/2bQKFhV+mtOSWTy2wCjAUjPHA6jae2NRJbDKsd1Z+Ct88qYIVNZlThpqwGuZPO/7EU01P4Yh7uLD+VhwJD/k1qZx102ykyZSG4WCchz9q5/ENnVMS54U+B9cvK+WkqnR27bwQSd/L5sETuH/nRQcdS5rTwpKKdJaUp7O0IoPslKNQ+RtsgJe+Bv07k5+rz4Kzfgeuw+dZxjv8DD+4C3QTS5EHJduB5LUhu0wktRXZvx1xcDVC71ZQPzbmizLkzE6SnX3eHvfhoyGiWpT6kfop0rNzaCch9eAwSEmQqPHVMCdzDpWplYzHx+kfG2L2unLmBLIwTJONYZ0uguzKWU199loS8uFVA302H2kWK3a1D6+kkWF1c058DnlbF6OaVehEaFtZyIkraw7fjt2bYf2fMJteoyM2n6Cezqzv/gzSK47c9kfA5yToKLB3MMiFf1tPILZf7ckiiRxTlsbJNZmsqMki13vkeGV1cJDBn/+C4LvvAqAUFpJz509wHnvsIetGIp3sqP3SZAfhwDASiOKh9Qfs9mKKi24gJ+eigyy0iViU135/N+07tu4vapYXnyJCzLkSzvkTiCJhTWdLIMz68RDrx0PUBkNoHxMhSIsbzBvTmT+uM3dMo1/YzsvudVQEi5k5ew0vO8/jPeE0ACRDJ32inor+BirGJKzGwZ1aSkoKZWVllJWVUVJScsQO2a9qnLOjheZwjCqnjVfmlmNpaqTjV7/i9ZwcQm43mX4/l595FikrTkIQBDrrR1nzzG5M+2os7mFCPQuJBw50N5tke4Yok96nVP4Qj3TAoJQ5LUmGylcQyF3MJbXt7IhpSIbOysatLJZ0lq44lZ98MMi2znEciskt0x7i+MFluAeSNSTkDDvu2H041ecwTCf1i37Hw46NvN/1PiYmoiFS5a9iibiAWRkSatMbnCxuBeAV/VhuVW9ARaLIp8BImDLRxflYmIU0VYB16ho7BrHVpJF58rHI3v0dr2EkWNe0kR+8PMLAhERqLEhaLEBa1E9WYpQZchvVYhjL3gDOiYmDtmlkZnHrtEtp8hYgYHKmfS/ppn/qd4fDQVVZMTUpMdJDO1hsPYagrQqbNkba0E9JaKNYMLlt1M+Z4xKx9GOJnnQv0ahANKgSCSaSRCaoEg0mGA0O0C9tBQHsoQKcoUIEjm6CrVhFlMg4cnQUIT0AuQFkaxDJrtPlO53XtVSGrSJhm4g7PsHSnr0s++hDKhoaGXVYqC3MZCAtzq7pES6ccQ19q/swTZPzzz+f2bOTClBhNcxdm+7ig8a15ATKmJlYTHFoGpGx5LPotw1Tn72W5oxNJOSkh0/RLRQHSygNFuPSXCRMiXHTjpGAXHsWM+MuZuAh78IZOOfvH4xi8QGCgTr8gbrJ153oenIAkiQHY8KlfPetaaiGBVkU0AyTuYVe/vGlhaQ6LcTCKg1re6n7oIdIIEl+LFaRvIGPyG16FVd2CkWPPYqSvf95eHtLKz9+tZHhhMnplt2kixHsoRCnvfse3nlzSTnzTFwrV/KPulF+9eZuDBOm5Xi478r5FKZ9LpH938TnbXNkBAIBnnnmGfr6+hAFgfl1uyhtaECw2ci89dZkmPl/qdbO0cAf93PdO9fRNNZEuj2df5z6D0pSPp2MJRJjhMN7iEZ7kGTnlLdmH7kJJWS++fQOVu9JjkuzpV7mWQY4/fTTWLhw4b/thY3FYjzwwAOMjY1RVVXFpZde+n+0dpSuaax7/F4Sm/5JgX2cfGcAl/yxsEHZjlY4n70F0GfuBvYVWL0Xt/vwk96hQIz7Vrfx5KbOKc/N7AIv315RwfKqw9d8Atg1vIs7N9zJaHeYcxu+iWJYKVzs5qyrFxz0H39U5YmNnfx9XTtj4eTxLs1bz9XTnyGi2vn+uttJmCksLE5l6aSgwbQcD+K/oUaGrsK638Pqu5NeIbsv6RWaceFhvULh7YOM//PIOcigIgnDyOIYkltAzvAg5RUglVQiZ6QgpVgQPpbHPhYbY8fQDnYM7mDH0A4axxrRjIPnmQ7ZweyM2czNmsu8zHnMTJ+JQzm47w9t7GPipdbkcc7KYGPDKKHRZDSNYDExa8YZLt9Nn9lFf7ifwcggUe3IcuqnBU2+0/stNLMagzB/rngZocKT9CI5ssge7yan8U2y+3YSjZWxPvgl+tXpSDJcceexuNM+e97g5yToKKHqBls7xnmvaZD3mgbpHD242vG0HA8rp2WxsiaTGbkph304gu+9x8DPfo42mHQfuy84G/vXzyRstOIP7CDgryUWP9SFaZo2JiZSCQbScTpncsop1+P1Hlmm1tB13vv7X9n1/tsALDz3IpbOdCG8cN0hROhAhDWdFxv+xEejwzQJ02kTakiYB5+HJ2EwbzSCxf8qOdEhTpy+kQZlOs+qV9Fl2V/kLGdihHkDnZzkdVBRVkZpaSlpaWlH3QH3xhKcuW0vAwmV470unppdigVoe/ZZnm5oQJNlyva2sMxuJ+sH38daWoqW0Nn+difb3+5E15K3q8UuYbHLhMYOVtPLTA1Rat9EWeIFvHKyzYcUH5fNuocGVxluNH7CAD2b6onGkpPcymkzeWk0i82dfiySxo2zH2ClbQGpO0/DCGsgamTav49FbyJuVBGe9g/GVlr41dbf8VHLMFpwBkaomu8LL/EV+U0AHtZOYb0xgxXibuZ5cnEMLcSUcg5SHWpFpxmdDFllnqEgTeYHmZgopXa0sh62sYlX9khs6J1NRDu0AO8p1VZ+et6xZHudmKZJ984m3n74JWw7NjNrpBWLoaEKEj895hq2ZlXj0GLcNPohlcfOouD45aR5s4iH9SkSU9/fzF0emWFHCr5ImNzu3zNoTw5oJaOzWNZ2KbbDHMeBCLs6iLgma+ToFoRQIQE1g7AgEBFNZuRsoyyzkdZIJs93rES0S+RnuyjLdlOe7iBj/Xuk/vMRPNnjBK+WSWRMkhH3YlY7v8vfBw1ikwSycHSA41p2sah2O8rEMF0pNgxJJlBegyRaKasp46pLrgKgfqSe29bcRnewG1EQuWHWDVw36zokQWJVyxoeq3uc7aHNmJNhLynRTGb2n0Dl8EIshg1TiROTx1EtE6iKH0M++N4zTAWv00vltGKys7PIzMwkMzNzql6IaRpEIh1EIq14PHOwWjO4+dkdvLgjeZ8W+hy8+a0lGGGdne9307iuD3WySp0r1crsFQVMOz4XYXyIzi9+CbWnB6WwkKLHHmXIlsJPXmng3cZBwORU225yCGGRDM5sbsOydX8oH4qCa+lSdh9/Bt9rVRiNqPz2C7M/l8j+L+PztvlkqKrKK6+8wq5dSaWtmmCQGW+8iWiaOI87jpxf3vUfFVj9rJiITfDld77MnvE9ZNozefi0hyn0HEGK+jNAN0x++UYTD61rB6BIHGOJ0s6iebM588wzj5gb/Gno7+/noYceQtd1Tj31VI49jPH1v42Ohl28/JufoUXDeO0qOXkKczJVsuOtiJGRqfWGfRaaKt2oFgEBEae9GFF2IYpWRNFKwpBoH1VpG1GJazKqIeNzuphXnEVxeiqSaJlaVzzo/f7PhiDxattbvL9+C8fsuQR0K8KCCa694gtY5IMNtdGEzjNbunj0o3q+Net2PJYQHYmvUF76FRYV+7B/lrycT8NAPbx0Awwk72tqzoEz7wXXAcrAWgLW3kNi9fOoWimamYluZqGZGehCLrqRCnyKEUAA0y0RsscYkIdpMTvYY7QzqIwypIwxpIyhihqZ9kzmZs1lbmaS9FSkViB/QthktHGU0ccbwQTPyUV4VhRi6AYt24bY/nYno71Jz5Qki1Qfl8PckwvxpNsIJAL0h/sZCA/QH+6nL9hFc//bDIYHGNcFqoMSd3bfiG5MwyTMr/L/yBp399R+PdF0FnefRdlosnaXIWpEp/Xx1S9egPff6D8/J0H/BkzTpHU4xLuNQ7zfNMi2rvGDkuKyPFZW1CQJ0XFl6dgUCdM0icW6GR/axODaRwkmdqPmm3DIPSbiclZgtxcyMroK09TIy/sisei5vPbaa8kYaY+Hiy++mPz8I09GTNNk0wvP8tE/nwCg+vhlnLasCOml6z+RCJmmTn3DtxkaegNdTEEo/zt1ag4bJkJsC4SJHiBwLyd6uaj/Ec4q2J4M6fIfz5vCF9jjyceYJDtFNgtfyc/g0hwfbvmzdSANoSjnbt9LSDe4MCuVP9UUIgoCTTt38uyLLwIwf+tWyjs68V1xBek3fh3J4yHsj1O/ppeGNb1TdVUki0hmoQdd1RnqCh4Utp2WpuHI6uRnFSV029LJSIzydN1tzAi3YLhz6bZUsGnURTuFxJUUttvnUTukIQsa189+mCsWXYN1QyXRXSNIwiBZ1m/x/7F31uFxnWfa/51zhkkjjZjZkmVLZoaAHTuJk4adtE0baMqw7X7tdre07ZYZUkjTNEnThtOQHTtgx2zHbJFFFvNIGmkYDnx/jCxZ5qTJbsH3dc2l0cyhec8573nv97mf+xHxMybfwK/M9/BEJEQgqmAgxo/0D/A+Ke5gd0CYia3g49hbIhCdao8q2WWsS4pRShJ4oWOYx/Z10OoO4BBifDnjKPNCWVg8ZRPL+9HYSoxNxOgzB7hupoHr51Ty3FEvf3kr7vZlN+r4t1UlXFucQGNtEy0NbTR2B2kLp5IT8JId9JEkx+hIzEeTLFhVDYsGCGc/b16zwCNXOhizSmQOx6hqeJnDWS+higrWqJ3rW9cwPeDELI5iFsew2I2Y0zMx507DXDgDU2ICne3H2Prai4yp8RmcvMxUpi1Zy0DMQNdgLRX6T6FqAl/b8xX6A2eXDFjkCNm+frLsg6SUD5Bu6ybL5ian8GZe4Gb+0u9FAdA0Sge6WHiilqKgF3csimJ1IERCdGsHmXfDTeisJu4/cj+yJpNhzeD7y79PWVIZL514iccbHqdtrG1iv8uzlnNL/m3k+srpb/bS2zLKUJeP03tKlRBBnY+Q2YdoGEHVhc7m9YDD4ZggRCkpKaSmppKens4jezv5nw2Tic0pisCdziR0PSG08fvRlWVl9upciuenTUg9AGI9PXR8+C5CPb28NO96/py3gpCsohMF7sg4gTQ8jCCofOhDd1JQUEK0qwvvxlfwbtxIpLl5YjtDzjT2L7uBT961GvOMirOeh/Ph0kD/3LjUNheGpmns3LmTrVu3ApBjNjP/2efQ+3yIDgfpX/86Ceuu/V87npHwCPe+ei8toy2kWdJ4eO3DZ63x9U7wzMEuvvJ8LVFFJVEIcqWhmbKcVNavX4/d/s6MBPbv388rr7yCKIrcc8895x07vFvwDg3y7He/gaenC00QCWcVILnSuGpuPrMSfEide6B9F9HYMA0lNtzJF5bDvesQdEiiaQppkkQjshIkHO7CYili4YKN713tLSUGO38CO34EqgwWF1z7E6i4MS6Ze+GT8VwfgPSZkLd0Mp/HkYGmaCjeCIongjwaRvFEiHqC+AY9xDwhDH4RnXYR4y6rhD7Jgi7RGJfbJRqREk3onEakROOEe+tJRLt8uH9fjRZTsc5Px3lT8ZQJbk3T6KgZ5tDmDvpb44oSQYDieWnMXZuHK2tqUVNN0+jseogTJ36IoiqYwnkU7bkdVSkHguxP/D47zSOYh64n3b0cSdOhodKYcoADORsJm/wc+uAhJPHtk9RLJOhdwLA/wpuNbt6oH2BHs3tKwpxJp1KVPsCMpP1UJO4nwTjVolL0gqFNwKoVkLnuMyQVXoFOF79ABgY3UVv7aQCmTfsf9LoreeqppxgZGUEURd73vvdNyHfOhbrtW3jtgV+iKgo502dyw7oZGDZ8+rxESFUjHDv2UUY8u9DpEpg75wlstmlEVZWj3iDbPX6e7h+mKxwDTePawIPcankDvaAQFZOwF/2I7dFSHusdZlQen6GWRN6f4eLe7GTyzBff2W0f8fGB6hPIGnwmN5WvFMVd4nbu3MmWLVsQNI3L3nyT1EE3UlISKZ//N5w33YQgScgxhab9Axzb0sVI77heVoCcsiSSMq0M9/rpaRylzyHy+Ao7AbOIK6jw7Z4OlsmbSB56EUGdnMVXEegljWYtnxeFlbwcnoEmwEerXuDfb/4JseMyoy+2YAjtItnwbQDujf47W9S5FBij/N7yU0pC1WgaBMnAE/kNMF4zCBVdrBGbeRdmaQ86QwAWfxptyacJKIMMD+1g2/EGXqpP4vDgdK7I3c0Hc3aS2L8Ya/dlmCOTRdsklwnr3DRMs1IIRFUOHR3g1Z2dCGMx0mQR01mNzc8PXSyITvQhuryIVh86ow+LxcJmSWFj8eXIOjNLLGa+nB7ifw5/jXZvOwB3jXr5TFjCEBqeukFRF69MHhgiOtzGbv1l7FKrUBQVURRZsGABl112GQ2Nn2Z4+E3S0tcjJX6Z5kE/LQM+mgf9NA/6aR8KTLj8nA6DGCHTPkJ2bja9GVnUC/FrUVIVVtftJ38kHg0xdZ9A7xslqlOpz/fSlRpi7syV3Fv5ETa0beCF5hfwxeL3rVVv5YbiG7h92u3kJ+Sfsc9ISKavZZTe5vjL3eFDPe34ZEnDLYXw6n2ohlHM+hGs4jlqQUgGTkTtdMpO1hSV4eyOofWHJ77OmpbInKtyyZmedM4o694DjfznY/tot8Ste+dl2bh7hsaB7dsAuPzyTFau/OgZ64WbmvC+8greja8Q64rPxOU88DtsK1ee/VjPg0sD/XPjUttcPI4fP85f//pXYrEYiXYHKw8fxngoHr10XHM16V//OpLT+b9yLEOhIe559R7axtrIsGbw8NqHybJlvSvbPtQxwsceO8SQP4pJkLlc30xxgsD69evfEYHRNI1nnnmG+vp6nE4nH/vYxzC/x5bjAJFgkA2/+AHtR+PnKJyaTSwpDWdiIqtXr2Z6eTnCUBNa2w78DX+iz9PLRnUh+4RyBFFFJ8oUJ+u5rNRJXpIOVYuiqpHx19nen/739PdxS+iLxayqh3G5VrxHrXMK+o6h/vVjiO64e17IlovJ342ASki0stV0DULFjaxZuxbpNJdhf9RPtbt6wsCgZqhmQnImaAJO2U6WksZcUxXTdaXkqVkkRR0IYwrKaBjttLpQZ4No0SE5J4lR8KgbNRDDWJpI8oennyG3OwlN0+hrGeXQ5g4660YmPs+f6WLO2nwyiqYWQ/aMHqBt70fJaOshZQA8sW8QUStRtRj7gjLuWJyMZU93UrTGTsAxQn+gH2/Uy53T77z49j4Fl0jQuwBNUwkEWvB6j+IeOca+1mH2diZyzF2B55TBqYBKSZKbZQUyq6anU5VdQfCJ1xj+ze/QolEEk4mUz3yGpA9/CGE89N3W/mtaW3+KIEjMqnoYi2UuL7744kQthZtuuonKysrzHl979RFe/ul3iYZCuLJzue2W+Vhe+8J5iZAsBzhy9MN4vUcwGFKZN/dpzOapM137x/x8ur6TznCUHK2DT/EzcogPlpostzGn9Es0hhQe7HbTHBzXiQJrkxO4LzuFxU7rRcnjnuwb5t8a4tv9QWk2H85KRtM0nnvuOWprazHr9aw5cABjQyMApunTSbzzTsxVlRjy80EQ6G7wcGxrFx01k4NxV7YNeWkK38BLAI20UZk7tvuwh+OXusNlpLAgTJHlAGkjLyAMHZ9yXH7NzE51BjvVmRTMcnDfrd9E8UfZ80Q93R3f5w7dJkY1K9ujX+dq/a8xiHHpV0zNYjD6c2QMVFuaqU04gqE9wFVHOin91n3oG36POG6nGdVLtOWaOJKQzc6+RezpXTBxTU1LbOYTVX/Erg+iDcxCaPsIxQEb0vigW9M03LJGV1SlL6ZxqpdNDI2AqBEUIChohESNoDD+/8R7jaCoYdZF+M+yX5OQ3Q6ANAyOZ3WYjglgt/HM3Ax+f/NXUHQmbkx18uPSVH568Cc83RR3fymLRPlB6koKi9dC23Zo3Qae9slrzZyC9uGX8BnSefXVV2lsjJ9Hq9XK0qXFBEP/D1E0sHTJdozGqdGgqKzSMRygqd9L9SvbOF7fTqctlW5HKrIwdfZKteuQ820kEmJRYw2yJtFndmIOhYnJIAfDmKJ+HKYaPDkddCX5OKkGzXPkcUfZHbyv6H3YDFNnsc6HaFhmoM1L5/422l8/iteSjXrarGJE0OjSyYzowgQNfgTdGDmWGBbFj6TEMIZTMAdy0Mvx/WpoNOtj7DWqfOiaEj59xdmTQUcCUb6/6ThPH4wbXiTEgtxb8xJzEsJsnVGBqkFhURcf/MAD53WL0jSNcE0NvtdeI+Vzn3tHzlyXBvrnxqW2eXvo7+/niSeeYGxsDKPRyFVGE5aHHgJFQZeaSsZ3voNt+bL/lWNxB93c8+o9tHvbybJl8cjaR0i3ntv6+O2gZzTEfY8epL7Pi4jGIl075UYP1113HbNmzXrb2wuHwzzwwAN4PB7KyspYv379e5ofdBKqorD14Qc49vor8Q9SMvG50kEQycnJYc2aNWiWJH67rYVnDnQSG+90F4oNfG6+mcXXfQRBd2Zx8HcCTdNQ5Cgv/24/Ay0jhAwjvD7999gcIvfOuIsFqbPRtDhxMhhcOBznH1tdLFRVJRAIMDY2xtjYGKOjo2e8j4UDXMNW5lA7MU3ZRQZPcj0B4rk4RUVFXLbuMupG6yZIT5OnCVWbSmQcBgezU8elbWlzmO6ajvEsxhOapqEGZRRPGGU0guwJj0eVThYVj6CFz8xJB9BnWuPW3RcwCDsJd6ePw6920HJ4cIKHZpY4mbM2j9zyRIQTW2DPr+JjBEDVRI5oq9EFP4pLZ0TWNA7IARbeu4Dc6a7z7Ont4RIJegeIRkfweo9N5PGcmsh8KozGLIaU5RxzV/JWVyL1/VNne3OTLFxZnsrKRI2c3/+Y6P54IVHj9HIyvvU/mGdUoGka9fX/Tv/Ai+h0DubNfQ6zOZ+NGzdy6NAhBEHg5ptvZsaMGec95sH2Vp7//n/j94xgS0zi9vWLSdjxX+clQrHYKIcO30Eg0ITZnMvcOU9jNKZMWSaiqvy8fYBfdgwgahE+yJ9YxWYA2ihkr+O/uC1vNjpB4A89Q7w5MhkJm2kzc19OCu9LdWK8QHLrT9r6+VF7PyLwyMwCrkpOIBaL8cc//pG+vj5SU1K40WzG+5vfxp34xiHabJhmzsA8sxJzVSXhjFLqjwVp2NtHXbLEXxfbkHUC0xWJRyryCXcFOHHETWftMHJssmOxOo0UTjdTlNREincjnNiCQZnqxjJiyuK11Pv4ekspmirzouGbTBdPTG1TNQ139GfEXDqeKvgqzwZDhMYrZM4SEvlggQO93EiyO0RhWxBbOE5dOtRUfiLfxsvqIhJNRm4qSmVegpXB9gFCvW0ovhQ0xYAEZOoFcgwiKfpTZFGaSgejeDJUCq9ewCF3lO9srEfR4u466Q4TA94wfWNh3L4IGqAXI4iCRkQxUexs5TOzH2Bf6wJGdmcyu+8EcwYbscfiM077yyv5r099EUXScW3bCT7mtNOYFeSBpu8wpoYxqiofo4oK57fweYL0t3YSHfMhaRp+8zBeh5ec3GwKCgrQ6/UcOHCAkZH4zFFiYpD8/DepqLiFgsIv4QvHGA3GGA3F8ASjjAVjjAajjIZiDLV307f3IGOKyIglgVFXIn5FJKoamKpB00CMIOpHEXRjiPoxBN0oOkctknFwYqmEkWRmtpmZQwb5M2aTVzmLnIpKzPa334eEautou+teRqUUgrOvwl+4iP42H6cb3kVRMQoNFOn3E9TK6IvNR0NCExRC5n5Clh5UXRgtEEMbjTLLZmJJhh1BA1QFRVbZEEvk/mgW3nG97fX087FAPcEj+3l9+TKiRiOZox1cEQhg1KeAoqCpKqgqmqqAcvK9Gv9O00BRSP/61zBfIPp8Nlwa6J8bl9rm7cPv9/PUU0/R1dWFIAhcMXMmGQ/+gVhbXK6a+P73k/rF//eeF1gFGAgMcPerd9Pl6yLHnsPDax4m7Tw1yd4OglGZLz5TzcaaPgDKpQHm6zpZsngRq1evPiMqcCH09PTw0EMPoaoqV199NQsXvn176ncCTdM4/MpLbHvsD6Bp2LPzcCekMiwbqFYyaFWTUcfJz+JcK58Tn2ZR/1/iK6fNhPf9Kl7D5m9ALBYjFAoRDAYZ8/jZ+1gPgRGFkMlDdfbL6DSRdH06mcZMYuEYer2e+fPnM2fOHPQXmPiRZRmv1zuF3JxOdhRFOeu6KiqaEGEl+7lcO4KERhSRFoNEp17PkKuC7owl7Go7jNvgJqgPnrGNLFsWc1LnTJgYFCQUIArvjmGIGpbjBGlknCiNR48cV+Yi2d8+OR0dCHL4tQ4a9/VPuL0mm3qYY3ycItM+BEGgM/3j7OhYgNfjQAQW21SSdUYEIrSkHmLZ5744Rfb9t+ASCboIxGJj9A+8OE54jhIKdZyxjCRZsNtnkpAwmwTHrImE5lPRNxZiy/F4HtHuE8NE5clBtt2kY6klwqydLzK3/TA2JUrShz5Eymc+jWbSceTIBxjzHsFszmf+vOeQJAcvv/wyR44cQRAEbrnlFioqzq/V9w4N8tfv/TfD3Z0YzGbW37aI1APfAU05JxGKRAY4eGg94XAXNlsZc2Y/gV5/ZvvV+IL8W0Mndf4wc7QDfJxfY8VHGCN/4h56Ldfwsdw0qmxmHusb5pn+kYn8ohSDjrsyk/lQlosUw9k7G03T+PfGLh7vG8Esivx1djGzHRbGxsZ48MEH8fv9lJWVcfOqVXj+9BjBQ4cI19WhhcNnbEuXns6ma2/l+3MXowoCpT1RbtrrxygIlC5Ip+qKHBJSzHTWDXPiiJv2miFi4ckOzGzXU1iVTIqzi1DTw1hG68mjl28qH+Zp5XIAVkuH+Un2HuyDBxHGi+qphhTGch4i0CjRVfkjgsm1BIN2nvfHOBCJt7tV0FgoZTA2diWH+0pZp+zhTg6hyCkMxoroVysYi2WgqmfO4Im6EMbETkZ0UbZ5ixF0IleJUS7XLDiZdJHTMq3c6RmiPRTj2soMfnX77ClGHlFZobVrIx1t36PfJ/GDA58jKFsw66JkOBIIRlXcgSiaqlDq6WLuYD0LRnfQnrOA790Tl2/e9/wT3LhlM7tyC9i6pocTifHzUOBzYW77NElRBzZNwKIKxASNoBRlzOzGrwsRRUIWDWQaIqQrA0ioaECrmsiBWB5h7UKRCA3E0DixGZvyV9SPIurGEPReEM9e7FBTDMTG5hL1LEGLxu/h1Mgg+cEOCoLtpMSGSS8oJm9mFXmVs8ksLUdnuLiHgW/nTro/+SmIxTDNnImxai59h4cYki34rQ5SUruZZt1JmmEyHyeoJNA/kMNom0ybPYuerCxGXFNnwmxeH1k9PaieKH/Ju4J6V9yxKn+sl88ce47pIx1EDAbeWLUKv8NO0tAwl7/5JrpzPJjPhZwHH3xHs+yXBvrnxqW2eWeQZZkNGzZw9OhRAGZXVjKvtg7v448DYMjPjxdYvYBS4t1Af6CfuzbfRY+/hzxHHg+veZgUS8qFV7wIaJrGL7e08LM34g5hmeIYK/UnKCvM5dZbb33bttf79u1j8+bNiKLIvffeS1bWuyPhuxi0HHyLjb/8IYOqmWMZy6mTstDGJ6cyJS8rXUEK7So6SaIkfIT5Q89hVANoCLSmXUNr3u2IxriCRNO0eGRHUVAUBVmWkWWZWCxGNBolEokQiUQIh8OEw2FisamT0KJiJHF4NqJqIGIcxuusO2uuptVqZf78+eQX5DMaGGXQM8jQ2BDDvmFG/COM+kfxRXwoooIsyMiiPOXvqZ9reg1VUlFEhRgxokQpDQf5tnuYkvHje9Vq4buuREbOQXAFDVxqMiuLV7I4dzGzU2eTajl7vuzfLQLD+Hf8iaPbBqnzLkfW4uMTmymE3uHAMxhvC71JI6lsA868Vyk98EnEYBUQode5ldn//s0LktOLwSUSdBGIRNzs2r1oymcWS1Gc7CTMIsExG6u15G0VIAtEZHY2D7Hl+ABbGwYZDkwOyCRNZcZQKwv761imDjHnP/8N/aLpHDxwI+FIL4nORcya9Qgg8eKLL3Ls2DFEUeTWW2+lvPwcvurjCAf8vPTj79BVX4MoSdxywxxyjv/ivEQoGOzg0OH1RKNuEhLmMnvWo2et/xJVVX7VMcjPOvqxqSN8RvgVZVo1APtYzEN8HLPByd1ZydyQ6mTT0Bh/7BmiLxK/4A2CwE1pidyXk0KF7cztx1SND9W08uaIj2S9jo1zS8gzG+nq6uKRRx5BURRWrFjBFVdcAYAmy0RaWghVVxOqriZcXUOkpYUnr7yGB276AABr9m7nQ68dpK9wLWOGjIl9ZZUmMGtVHnkzXCiKStdxD62HB2mrHiISnAwPG606DGkaTw6O0ijpUAWVT+o28O/SU4jC5C2jmZPw3fZT3GorfR3PEmEy2gBwzJPMU+1LMLjnkxJJIk0WSVNEXKp4Vu8Xoy5MSo6NlJJMUnLtJOfY8IafpOXE9wGVLm8OvzjyETyRRATgfS47H7LbSe0JQkylF5UH00S+/8G5qGGFkDduYe3zteJTf4Gqj2u4lUgyLx/7MC97cifsO4tiApeF9Bg0Eb+o4RM1em1tdOf8CgtXUVse1+Z+6U+/4+q921GBHeuiPDjDTEwQMMd0eLvvIBy+cIK9hShz9V0USfGoUESTOKym0GM0YLH6MZl96A1eBJ0XRfQQZYSgOoKsRS6w5ThsIZA0G57EQiJ6F7I+l+yhTKrauunRnHQrCQxpU+VvVtlPfrCT/FAHOaFuzHqJrLLp5M2cRW5pOQmSHrmvj1hPD7GeHqI9PcR6eon19KAMn5YbhYYlLYqzMIg9K8TJLkTVRIajRTj1PejFyZm/mJZMSJvOsFhGm2CjOhRj1CAREySOyZnUKWloiBhQWG8d5qNJIcyShCIKvDQ8TE8kgln1c+Xrr2P1RJGSkki69x50TieIUlzbLYgIkogmCKAJhOqO43tjG4p7hOxf/xTb4vkX1ban4tJA/9y41DbvHJqmsXfvXl577TUA8vLyuDY/n7H//mbchVWScN5yC/Yrr8CyYMFZ6/O9W+j193L35rvpDfRSkFDAH9f8kWRz8ru2/U01fXzh6WOEYgoOIcwV+mbyk0zccccdpL0NdzxN03jqqadoaGhAEAT0ej2SJE28RFGc8v+FPn8763R6Ff5yyM1b/fLE86QySaPKMIg02nnGsVoJspZtzCQukR4hgZdYTTt/mwmFIAjx3y47sLsrEDSJsLOPI9mbGJAGiIgR0qPpFIwWYFbiY5GoGKXF0UKLo4WYdI4czrcBvabxcc8Y94zF4/UjoshP07PYl5iORW/BorNgURUs7ibMYR/5MZnZ4QgVERmvlsKAPpeilXeQOHM1JLz3RhfvCoZaYN+v4egTMJ63FLaWckD/RWqbU6bUAcwscXLlXeXoLW5qaj+Nf6yRwn2fQOefC0QZtT1P7ie+Tuuhg/iG3Sy/48Pv6JAukaCLRF39/8NszhuP8lSi1ydceKWLhKJqHO3y8MbxQd6oH6B5cKq0LtfbzwprmKtuqUIOfQpN9ZOZuZ6yad9B0zSef/55ampqEEWR9evXM23atPPuT47FePW3P6dhd1x7ef1V0yjufhhBU2DWB8aJ0NRZCJ+/gcOH70CWvbhcK6mc+TtE8eyz3/X+EP92vJMaX4BreYn1PI6IgodkfsXnaBSmYxIFbk1P4p7MZBqDYR7ocnPENznYW+q08dGcFFa5HEin6Jb9ssKNR1qo8YcoMht5eW4JSXodR48e5YUXXgBgQVkJs+bMJbO0bMpxaZrGNxs6+F3/KAB3Ntdw35MPo/TGpQZjjgK6si/HnTILbdwRzaYLU14mUnF1OZbCXFRVo6fRw4kjbtqOuifc5wAiaJzQKzTpFQrMNXy2qJFCpQ4h0E99iZlR8yTRVaJmQn3F9I/cQl9PClJYIlEVEM4yFWWy6UjNSyAlQyJl7DVSOh7ELvTGnyEzboErvgpJBSiKwq5dDxIK/xK9PkIkamZr/6d5oSl3wjwgF5EfYSELkbCqsT+g4FE0BCmCq/wVkqa9hijJqIqOkcY1DB+/Gk0x0qCX2WCJTeTIiMCVdjs3ZrlIcpow2w08HXyYl0aeQXXdxbD1SiTgPw7vZOZLz5My2EdwqZ/vLbTQMh41WXjcSXL3YnrTpzFgzyLi19ATQKcfw5IYQJ/oIaj24Y8NYidG8VgR9qgTgFHDKEddRxk2nU4qJpFoTCRFdOBo7scypjCSXoJJtTIz30yG/XUSJJXkXRbsT8r4LVae/u5PecwY7xtcYxGyD9VTKAxjF8L0KE66VCe9qgP5lHpGejVGmaeN+QPHWdxbT7b/3MdzEqLNhiHFgM3ajrMghN46GY2JKTkE1KtQim7EcnMBRksS4oltcOwJaNoMyvg1JIjxYr9Vt/P5I2m8VO9BGT+uXNHDQn0nViGKTtKRn5ZDKBKmZ7gPnaRSOWsjmYE87D8fRh0dRErKwHHrNxAMCWgRGS2iokZktIgMp1nkW6pCJN1x1QV/4+m4NNA/Ny61zd+OpqYmnn32WaLRKE6nk/XXXYf6m9/i3bhxYhnBaMSyaCG25SuwrVyBIefdcXM7FV2+Lu7efDcDwQGKncU8tOYhkkxJ79r263u93Peng/SMhjAICit0LRSYQtx4441Mnz79orcTCoV45JFHGBgv1/FeY0i1cEzOpEudzJHOFT1U6npJFs+Ud52OUlpZxxYcxMdGh5jB6ywnJlknyNbp7mQno0Sqqp5RqP1UGMLJJIzG285nb+Z4+h5qEmuISTEETSDHn0PZWBn2WNyZLybE6HR00pPYg86kw6K3YDPasBltE+TFrDNPEpmzfJY00kHu1u9jGG4BQJ3+PsRrfwrWs5DmWBgO/jGeK9N9AIJnecbYMyFnftxsKHtBvEiq/r0j/G8LmgYdu2Hvr6FxExMJQRmzCM/5LIc7ZlK9rRdlXBkl6UWU8VQEo1VH5eU5VKxIobP3u/R1P0f+gY9jGJsHxPCJD7K53Qvo+OhvHsHqTDzrIZwPl0jQ3yE6hgNxQlTby/52D8opA2OnFKMi7RCzUmu4akY5ZSVfQKdL4vnnn6e2thZJkrj99tspKTl/5VxNVdn55J848OKzAKxakknl6LPnJUKjowc5cvTDqGqYtNR1VFTEDRvOhpiq8ZvOQX7S3k+22sxn+Dmp9KEhstewnt9Gb0QdX3e1y8HHc1IwCgIP9gyxwT06kSeRbx632E5PwjZusT0QiXHNoSZ6IjHmO6w8VVXISEsDLz//PAMRGVQFc3crZdOns+IDd5GYkYWsanyhsZOn+z0AfK0ok0/lxkPIsttNqKaWUPUxwtU1eBo66XTOozdzKbIuLjXQxYJkjRykOGUUV2UJxpkzeMjr5PntvZREJaarEib5FEkZGm5DCKe9kcySXZgFEdWXS7g3E1+4AC14jgejCFYpyrHEgzQl1TJk7UKn0/jPRf/FuvJ18WU87bD1O1Dz9Pg6eoIVd/DsYAGtA16MJh+VM/dgMg+iqRJdR9eztWspx4wqXlEjRRN4QLWSKokomkZTQiva7N8gGeOdqxidj5VPY7MXYrEbMDsMmO16trQP84Vnjk3x1km2GfnSmmncMjebqBrh1pdvpc3bjiX9K3QaypAUhXXVu6lSIqxITCSj62EedPXwl4T4AyVjWCPRD8MJAiN2gZh07m5G0AQKfAVUeCowjNdKchvd9Fv6cRgc5CfnMy1zGpUFlRSmFmLSxR8CoZERfveznzEmSWT09LJW03B840M09/8Yn7eWhD9LWPfGr63Ni1fykw/ehyxKFAT8rH7qZdKGetA7JEJpTtyJSQyodrpUJ12KkwBTk00LxnqZP1DPzOFmskL9hA06SHbhKCsnbfZMctODGFs3QMeuiXWUqEDMtQTT7f9D0J3NyDNNoEDY3kEot54k+3Is+hKE4Cj6odcwjG5EH6mdWN+nmXlFWcg2ZTmXaVUUiEHaRTed0hB+Yaoc1GLxkJbWSmXnzbgGEwju+glaaBjBmopl2b8jms/1EFEQrUaSbi/DVPLePWj+FXGpbd4dDA4O8sQTT+DxeDAYDNx8881kDQ3he/U1/Dt3Ivf1TVneUFCAbcVyrCtWYJk/H/EiJa0XQqe3k7s3381gaJDSxFIeuuohnCbnu7JtgCF/hE/8+RAH2j0IaMzTdTFdGmDlyhVcdtlliBdZPFZVVbxe74ScTFXVifenvs71+cWsc2JM4/VeiUZvPMQtoFFui7DE6cUlhRgbHCQSDoMgYLBacTgTsVgsmM1mLBbLlJdNr5Je+ztsx58CQLOlIVzzY5h+/UX91pNyuVNlcyffN+0epmnHKAhQvtaGkBagK9xFkiOJlIQUXA4XQ91DHN53mMGBuIpDkiTmzJnD0qVLcV6sI6EciRdJ3fXzuPrGkjxuiX3Dxa2vaTDSSrRtDye2P4nT10QabsTTHe9EPWRUxglR9jzIWQAJOWctxvqeQYlB/Yuw934YN3oCoPRqlAWfoqYtl4ObOiaUNVmlTpbcXIwr00bjW/0cfrWDMXc8WqQzSpQvTkW0vUBY/yfyj96HyTMfiKHofsfArDVUXXMHxrcpDYVLJOjvHmPBGK9vOczGTW+x35xJQD8pE8uw9vOB6Ru4Zs4V5GTfzfPPv0J9fT2SJHHHHXdQXFx8we0feXUDbz78ezRNZVmlnQXyq+clQsPD2zlW/TE0LUZW1geYVvrN8zrMNARC/NvxLo57h/kQf+Qy4nUeRGsVzxn/nec81onbt9Jm5uO5qcyxW3isb5g/9w4zNm6xbZdE3p/p4p6suMV2YyDM9YeaGFNUZva3cdWLf0TQNEI5JSi28SidoqAL+cnMy+OV+avYFZKRBPjJtBxuzzi3u4imqkQ7OvAdrqZxv5umkSSCknP8SwVz7BgvuExUS/G8i5XZu7h92vMonhx83XNwdyxGilz4GhsVVTwGyChIYOm8DCpnpmI2SwSPufHt6eVJ/waeSN04kQg5W1/J9675PlnO+Aym3HkEedPXMfXtACCCnj3qAmq8tyDF0smc/yiO3IMAhAYuxxT7DAN2IwVZDqal24i+ehzlRBQNlcFpTxCeVk9pyVdJTl59znP62L4OvvZCfACeZNEzEoxHwmZmJfC1deV09G3lW03fQhNEJPs3GUjMx4bGi3NLKbebOTpwGMNLn8XjOcHXkl0Mn6V2lNOv4fJBol/EFnZgUVPJza8gbw4Egk+QqMvD3Xc3zc0t52zb5ORkCgoKKCgooK6ujrq6Omw6HatfehmD14uUkkzG977LUNPLBH73MpJ3ct3q4ml87WP/jtdmJ3l0hG//9sdM64wnXActZjryC+ktzMdttTGqmelSE+hWnLg124S+HcBKlFx/K1fIB1htOkq5fRCjFL+eNQQiafOJBAvoe2gHmiqQ/N9fxF15HE9DNVlHPosudvZrSEbjVaEdWdrK9eIuckT35HdaKkHlcrzalQjmPGrFDvZGj591O0lmJ0X2ZBI3PIWztQVdchr6/EqiLU1ochhBVEm46X247v0w+pS/Tdbzj9r//m/gUtu8ewgGgzz99NO0t7cDsHr1apYsWQJApLmZwI4d+HfsJHj4MMiTsmbBbMa6aBG2lSuwLV+O/m/Mk2kfa+fuV+9mKDREWVIZf7jqDyQY3z31SFRW+doLtTx1MO6aWiy5WazrYHpZKTfeeONE4eX/K+xrHeZXW5vZ3TI+sSbA+2Zl8anLiyhOnax1pKoK2/70B45sehmAzNJyqlZfTcmipegN5yil0bEHXvoMjEdRKL8ervkx2N+5GYWmabz55waO7+5DZ5S4+YtzSM4+syaTpmk0Nzezc+dOusbLBoiiSGVlJcuWLSM5+Tz9ZM/heN2fcRtsKm6Ca3509ujPRSAWi/H888/TXH+MTAa4stROrjAA3fsh4D5zBVv6JCHKXgCZs0D/HhiHhL1w+FF46wEYGy9yqjNB1R1oCz9Jc4eDfS+04huOT9AlZlhZclMReTNcU8Ydqqpx4vAg+19qZnQwroDQNBlBqCF76cuU96/DMrwQiKE3/Brjfd/GmXP+dJCz4RIJ+geBJssMPPIntj2+kb2uYrZlz2HMGM9VmJtylA/O3Mm86Xexe5dGQ0MjOp2O97///RQWFl5w2y0H9rHxlz9CjkZYUCyyzLDrvERoYGADtXX/Bmjk53+KosIvnHf7sqrx265Bftzez2xlJ/fyABaCSJKNxIKv83hoAU+fYpSQadTzkewUbkpLZPPQGH/odtMybrEdl2EZWdpazYnDB3l81XoUScf82n18xhCl/LKrONzQyPHj9YTDESKSnk0zF9KfkIykKHwkOMhNeZkUFhaet/BcvLhtNz5fHV5vLR21HroO59I6XMSLlihjkoYOjVvT93DljGfRuRX03SKaCcLTVY42XUVN4w0UR+MyN4+o0S+pDEoaA5KMXj9Knt5NtjiG2WQgJSWFlJQUkpOTJ95bfBIt26r5wchvOOqsRRM0dKqOVb7rmTWymuHhUbz2RnIMdaxmJ5njeUYhLZG2pHuJlN+BlLwB9+j9gIbDMZvKmb9Gp7PT3v4bOtofJuX4rSR2XwmAdWkazmtLEMTzzxb9akszP3k9nqR7XVUG2xrc+CLxAUWBOIw17SU6nI049CnYS+7nqD+KlTAZwz9iLNCEpGn8ZHCI2eEIr1ot/MlhI9VUyhdtN+Fs6EGuridcX48WOTOvR3YJxPJlkha9D6Xiara2tNDT2wuA2WzGbDZPuMqdjoqKCqanpCD97GdojU1Tz3eKCTUaQhoT0ASNPlca//WJL9KRmY1JUfivoIcT9R42DoJfbybZbuILl2WTL45QX19Pd3c3YU1Hj5pAl+pE0VSuE3Zzs7SDInFyBnpAdlA7ms4JTwI+2YTeYGROIIqrvgVNgJGPxIjM1ki33Epy+01E/IP4o3XIwhiqLkyDksED7um0jRsTzk+z8aMqL7nuVxBOvIQQnZTS1lmX8nxoIbKqUVmVg9H4C0ZG8pFj6+jq6p8iETGFQmT19JDV3UOqx0Pybbfhuu8j6FNT0TSNnt43cbsPUV72aUymt//g/Efvf99LXGqbdxeKovDKK69waLx+UGVlJdddd92UJGrF5yOwZy/+nTsIbN+B7J46aDQUF2FbsRLbiuVY5sxBeAdRotbRVu5+9W5GwiNMd03nwasexGF4986vpmk8vLudb2+sR9UgVfRzmb6Z3BQnd9xxBy7XuSf63gtomsauliF+taWF/e3xPlgnCtw8J5tPXFZEfrL1nOse3vQyrz3xAEJMRaeKmKw2pq+8ksor1+LKPotsMRaGHT+cjKiYEuCq78DsD77jaIeiqGz41TG6GzzYEo3c8h/zsDrPTsQ0TaO9vZ2dO3fS2to68fn06dNZvnw5GRmT+cXIEdj2fdg9nnttTYlHf6a/7x0d56lQVZVNmzZx4MABAJYtW8aVV1yBMNYJXQfihKj7APTXxIuxngpRFy/AelJClzMfnHnvPFo02gVv/Q4OPQrRcRdgSzIs+CjMv5eebok9f21hsCP+nSXBwMLrCylblI54mtObHIvR/NZujr2+iZ6GOkRdPjrTAkR9PPdJEMBV2MVMxYdjtAqQ4f05ZFdeeOL/dFwiQf9giHZ30//f32TgrYP8uewqXi5YiipKGLQo1zle57qlHbS3r6W9fRidTscHPvABCgoKLrjd3qYGXvjhtwj5vMzOjnK54+B5iVB3z+M0Nn4NgJLir5Cbe88F99EUCPP5hk46xtr5FD+ndDzZMT39RlLyv8pfBsP8sWcIdzR+s9okkQ9kuLgnO5lmf4hfNbTx1imSs7TBHvK8Q+wvjlv2fqs4k4/mxCVuqqpS29PL3Q099OiMGGJRrq57i4yxST1tamoqhYWFFBYWkJKiEYk04fPV4vPV4fPXI8unhAeA3T0LeKx+PTFNT4IK7wsYSVNEzPoo+XIjaXUbEIa6cP+HjJyj0bC7gl+M3YMs6VEFSDO7meusZ3leFUJYwu12MzIywrluLUnSYdE7EKNmfKEwdckH6ExoJqAL4IgkUTUyg5RIMpKgZ0bePJal9eFq/DniaDxqQVIRXPl1htOc1NZ/Hln2YjCkIAp6wpE4cXAlrSRn8HOEtsZ/q3lmMkm3TUPQn1tSoWka/7PhOH/c3YYowLXJHhpGZJqVZEDAIEVxTvslIW0IvS6JgeQvohiykWK9ZA//jCuz57M6eyUrdvwaqW07fTo9t2SmMivvcn5++c/Ri3q0WIxwYxOh6moGt75F8Fg1Zl/fmcei09GzcAGHc3IIjX9WUlxM6bRpdHZ2UlNTM2V5cyBIVfUx8jriSbiqIKDLzKTgjw/ht/TS1/YE7rGtmF+PwJs2vvPhz7G/YhYAn08VmSem8u2NDbQNxVlIVY6Tb15fQb4djtceJXD4WfJGdlKkdUwYY4Q0AxuURTyjrGS/VgYIpOsi5PpOkD3aREaoj6ruQXJGfKgC9F6zjMzrbyd3ZhX2pGRk2U9t81/48RuD7OqZA4DdEOLzl1u4a+UaxJP3ZiyE1rCRE288ROJoLQ8Lt+PHSjEdrE3bSY8rjHnmRygt/29CoRB1W7ZQu2MH3Xo98ikDRJ0sk+hyYbDZiMVieL39zKx8HpMpSLLrE1RV/b9zXhvnwj9L//te4FLbvPvQNI39+/ezefNmNE0jPT2d9evXk5h4ppRT0zQijY34t+/Av2MHoaNH4RTXRNFiwbJkMbYVK7CtWIE+/eLrALV4Wrjn1XvwRDzMTJ7JA6sfwG449+TbO8GOJjeffvww3rCMTYxxua6JLIvKLbfcclFqkL8VmqbxZuMgv9zSwtGuUQAMksht87P5+MoishPPLlEKxoIc6D/A3r697OndQ9tY/LmlU0SMEQFTVMIUFUkyu8jLnkZhfgXJ1hScRieJpkSSTEkkjvZi2/RFhL64ARMFK+G6X0DShcc8Z0MkGOO5Hx7C0x8kOcfGqrum48o6f1247u5udu7cOVHfDqCkpIQVK1aQIw6OR38a4l/MuBmu/hFY3z2CqmkaO3fuZOvWuMpm1qxZXHfddVPt06NB6DsaJ0Rd48TIf5Z8MGtqnBSdzC/KnA2Gc5NXIB7h2ns/1L0QJ3kAydNg8aegcj3Dbpm9z5+YqNGoN0rMWZNL1ZW56I1Tx5We/l6q39hM3bY3CPniYxJBFCmau5CqVWsxWAs5/FrnKfUeFeYljaKYh6n6whqs1rd/3i+RoH9AaJpG6PBhvK9s4tiuQ9yfczk1yUUApAeH+HD0BRKcCTQbctEZjXzwgx8kLy/vgtv19Pfy1+9+g9GBPmak+Lgqpea8RKi9/TecaP0JACUlXyXRuRBJspzyMp+RM6RoGr/vcvOj1m7Wqs9wI88iomI251JR8XOM1pn8ddDDA11uGgNhDNEwlY1HWNpwAMPwIEOJqRyauZjj0+YQG7/JbZKIX4nPav+hIp91qU7aghHWHztBZzhKqkHHf4cH6H7xKfyqgGx1oJosU2Y8BEHB4XDjTOwj0dmHzT6CKOqw2Uoxmmfw8NF5vFAbnxW6bFoK372mgu4Dg9Ru754wR9AZREorE8hyHaDL8QMQYOiRMg4Gy6m8rYcM134y0m+gouInE/uVZZnu9n5aGzvp6epneHgIf3gMWQzGvTDPAgUFv96P1+DFqOpZqyxj5qwqspaVYLCI8VD0tu9DcCi+QtZcgis/SbXnDwQCcetlkylrivQteGSQkWebQNEw5DtI/tB0RMu57Sc7Ojv57J8PcMxrQkJljbmZpGkWXutwMOhJQDK3Yc57AEEAgyGT0fRvEMDCLLuJ52aXYJUkCI/BAyvB08Z2q5VPpyRxdeE1fG/Z95BOu9aUmErN5kZann+NrMTfYexS0bfY0AXjUsGoXk9dRQXNpSVoooikqqSPjqKEwlhnzqBq8WK8j/4J57ZtSLKMBrQVFlAzcyZRg4Hk0VGK58whf+lS9HqIRg8SaNuE+shhHi75IM9dcTUAl48e5CszFbZ3LOA32wcIRBUqhHb+M+MgS4JvIoY9E8fcbyjgrWgxdZTiVu10q4kMGdLoCBlQTzm1ZiFEodrFsuPVXNl2DLMSZn9hJqNWE/aUVFrTF7AhnI1/fALgspz93Fj8V2z6IDZbOYUFnyM5edWElCAcDvPDn9+PGvaToI3xCeHPmBiXE5id+JKX01Kr0dYRxGd34LU78CU60VQVSZaJnFZbZVrZTlJT2wkHrOTqv8XMtTec87o4F/6Z+t93G5fa5r1Da2srzz77LMFgELPZzC233EJRUdF511HGxgjs2RMnRbt2oQwNTfneWFqKbeUKrMuXY5k9+4LFgxtHGrn3tXsZi4xRlVLFl+Z/ifKkcvTS327vexKtbj8f+dNBWt0BdILGMt0JCnSjrFq1iiVLlrwnRVFVVeO1+gHuf7OZ2p74gNWoE7ljQS4fX1lEesJUSZ6iKjSMNLCndw97evdw1H0U+fToxDuAXtSTKOhJDI2RqMgkqgJJWfNIzFtBotkVJ0umxDhxMibhMDrOW0NnzB3iuR8enHiuF81JYd41BSRnn58MDQwMsHPnTurq6pC0GCvZx1IOIqKhWVMQrv3pReUvvVMcPnyYl19+GU3TKCkp4dZbb8VwrgimpsWlal37oftgPGLUVw3qaa53ggRpFZMSuux5kFQYX79pc5z8dOyeXL5gBSz+DBSvIuCNsf/lVo7v6UPTQBQFKpZnMu/aAiyOyeNSZJkTh96i+o3NdFRP5g7ZXMlUXrGGGVesxp40VTLYfWKI117aRtdII4gxNE3g7js/Sl5JBm8Xl0jQPzg0RSFw8CDPb9zPL3zJDI27W83vP849TRtQEq30FRZw1Rf+nbyLiAgFvWM8/4Nv0t/SRHniCFdnHEfQ1LMSIU3TaGn5Hp1dD51ze6JomkKKJMmKJJkJY+KoXyMQ81NOHWZCgEiy6zKSk1fjd0fY8WYTI4fq0MXiA7iI3oi7cj7Lr17H8tJpPN43wsM9Q/RHJ29cEfhSQTp/6B5iKCaTa4RfZjSTEDnK6HAtbXvdDBxxImsGFIsdKd1MzJxANDZ1tsNo1FNQUEhyZh4PHA1woDeCIAh87soSPntFyURdHTmm0HxgkGNbuhjumZQiFa96Hl3SK5hMOeSm301T+7eQJAtzqjYx1mdhoN3LYLuXwQ4fgdEzZV+iDhxZIqZkBcESJqL56R3oxufznbHsSQiagNNoJyUjlcxMJ+WeN0hpeQpRjhMFueQKWqZnoXcUkJ//yTNszsMtoww/Vo8WUdClmEm+ewa6pKkPsv7+frZu3UpTUxMxFF5X8xmMpiOIYcx5v0c09iL7ZhIbXIcuaQeGpN3o1ES+svQxvjbgxSMrXJ5k508zC9GLAvQehYdWgxLlx0lJPJpg47bS2/jqoq+e9cEdDsTYt+0rKObnCA4WM/DqfZSljpFnHURpqmOgs4tDFdMZHLeMtQQCzD5yhKzePoRx+ZeuuJjABz9Aq8FAW0sLvuC53YkkKUqpt4YT0Xx+fd2HUSQdZX1NfEn7DmlBAVdfmHx1MkI1JiXhzbsKX8E6cBURjUbp6emhvb0d97jkJqJJ9Kp2BiQTnbEUgspkG4uayvThNua7GwlZo2xPXUifKd6xuyJDXD68g2kOFVuagGBtxOwYw2qJ4DQUkmm/EbOaxwu1dXQE/Eiqhq53lMLyNooiA5RFO7Ex+VvdJHGMcmooY4x4v5HkHmJGXS3ulFS6s7MwlQxTVrYbTRM4dnQNSzOWsej9d5yzvc6Ff9b+993ApbZ5bzE6OspTTz1FX18fgiC8LWKgqSrh+uP4d2wnsGMnoWPH4gPAcYg2G9alS+MGC8uXo089e72W48PHufe1e/GNy4QMooGK5ApmpcyiKrWKqpSqv9lOeywU47NPHGF7U7yfqZJ6mKXrpbJyJtdff/27UlMF4m62r9T0cf/WFhoHxqVNBok7F+Vx7/ICUu2T/Vl/oJ89vXvY27uXfX37GI2MTtlWli2LJZlLWJK5hPnp89GJOkbCI3jCHjxhD73DnTTUH6Ctox6v6idiUAkbFGJWibBBIaKdvdbb+SAJEgnGhElyZEycjCyNkyWL34lnp57uY2MT6xXOSmHetfmk5Jw/kjdWtxXh5U/jCPcAUMM0jqS/nwWXrWXatGnvCSE9icbGRp555hlkWSYrK4v3v//9WK0XiOScRCwMfcfihOhktOgs6gssrnh06KSluaiLR7gWfwoyqoiGZY681snR1zsnCs4Xzk5h8Q1FONMmo4LeoUFqtrxKzdbXCIyOTx4KAgVVc6hcfQ2Fs+chnlYraWxsjH379nHo0CGi0fi5N+ospJtL+MBnrj036TsPLpGgfyL4gxF+/sRuHmkOICOiU2RubtnG7U1bQSdgXXU5WbfdgWXeXITzVJqORcJs/OWPOHHwLUodQ6zLakRAhar3w/vuP4MItbb+lIHBjShKEEUJoSgBON2t5G0gOGSkbVMOsWC80xadKidmlLOh5EbC43lQafRxrfAGK6WjHBXm8rKykhZ1ajJrHm18Sfs2TkanfK6GHbiP5tNXHQMNBEmi7PKrcJZX0tndQ1tbG5HT8lECGCkuKmLZnAoKCgrOKFCnaRo9TaMc29JFe80QohSiYO3X0VtG4zbDgoav9TZ6Dq4+4/cKQjw5MC3fQWq+g7R8B0mZViRdfLbK7Xbzwgsv0NMT71Tz8vJIS0tj17FdDIlDGFUjjqgD/VmKiFoJsIJ95Cc10p9uYNhlQBMEjPpkrPZybLYybNZp2GxlWK2FKIMyQw/XooxFEW16ku+qwJBtZ2hoiG3btnG07ij95n56bD0MWgeJqCqhrntQgoVIugC3XN7JLRUrmZ5YxQM7Gvlj+2cQDMPERhewKPczbEsSCKsat6Ql8svyXERBgP0Pwiv/D1WQuDM9hWqTgY/M/Aifm/O5s14fkcgAu/esRNNidGz5D0LDxUg6kaorc5i9KouW7W+wY8MGRhMTiRrj0bu0/n7mHD6MwztOIkURY0kJpspKlLxc2o4fp3lkBL/djqzTIRsMyEYjsfEHliTL6Pw+Wufn8T7Pm6wZ3oNei89iKoLANir5U2QtO9WZ2IQIC3RdZEtjZz3+KdeiBm7NRp/goltxMiSf2Ykb1Ri3De5n9YkdSIEABkVBp6jIRiN+mx2f3Y7fbsNntzOUnEzsHA8CEZUCOpmt1DJNbEUvjJs0aOALJROOFCLrp6NJZvxbthA1+Bj8qgImFc/AIuqaSvn0Rz+KK+O9m237V8SltnnvEYvF2Lhx40Rh1YqKCq6//nqMxnMk358DssdDYPeeOCnauQvF45nyvXF6+YQFt7myEkE3WTuwcaSR+4/ez9HBo2eQAYBsWzazUmdNEKMSZ8kZEfELQVE1vvfKcf6wKy4tyxM9LNO3kpuZxu23305Cwjs3Z5AVlZeO9fLrN1s44Y7Lge1GHR9eks89ywpIshoIxoIcHDg4Ee05KXE7CaveysL0hSzJXMLizMXk2HMuihSoqkL70cMce2MTbYcPomnjdsoJNnKXLSRjwWwUuw5PaISRE68z0rwZDzIeSceIMwuPwYwnMoo/5r/AniZhlIz8aOYvie530HJ4cGJIU1CVzPxrC0jJPY0MxcKw7Xuw55egqaiWFI5k3smmdgl53IQjNTWV5cuXU1FRcdEufm8XXV1dPP7444RCIVwuF3feeefFu9edjrHucQndeH5R37HJMg3GBJh3Fyz4GCRkoSgq9Tt7ObCxbSKKll7oYMnNJWQUxa+7ifP4+iu0HTk0cR4tCU5mXnEVM69YQ0LqmQYXbreb3bt3U11dPZHLmpqayrJlyyba8p2Sy0sk6J8QrW4/33ypju3N8TC+KzTKx2peYllvNQIguVw41qzBcfVazHPmnJUQqarC1j8+wLHXX6HU7mZddtM5idDp0DQNVY2gKIEJUjT1bzD+UkMocoD+kRH27GzBGWgnZ14vkl5DDkuMNmWQkGnEmhlAVYMMKSZe1VaxhasICPEOyKb5uJJXWc0mesniF3yRgGBH0BRu5Blu0W0j0VGG3V4Rf9kqMJtzEAQRd2c7O/7yMO1H4wm0RquVRTfdzsxVV/O7146ydX8NGaKXVNF/hgVlRkYGRUVFFBYWkpOTM2WWbXQgSPWb3XS2bSRj4f0ARP0ptG3+Jpqqx5FsIjXfQWqeg7R8O8k5dgymMwvtqqrK3r172bp1K4qiYDQaWbNmDbNnz0YQBHw+H399/q+8PvQ6dc469JqehKiDRd7ZlPoLCZsGMWZWk5zehNF44VoMgqDDYinALlTh2H4lwrAZ9FBfNMxTQy/TbelmwDyAIk7q5dOt6azIXMObe2fS5o6Sk2Dikbvn4DLrUBSF7W0H+OmhbyNqIvLAOuSEMrpmZqMKAjcZNe4zC0ybVoplwyeg/gUCVhdXuUx4JYnPz/0898w4e67Z8eP/SW/f09gtK+jZ/Rl6m0cB0Nll3Pb9yKpM6fEGdKpCQ1kZqiQhAhWhEOUHDyGME8opv99oREpIQPX7UcejQxogJYu4FlhxOnvRqZORuBpLMd5uM7q8XrxVInv6FvBs8/X4ovFrs8QaYqV9EEO0j2gshiLr0bTzD2p8qoFuJQGPV0evPomZwye4rWsHBiMTRMdnt+O32VB0Z14zE79FUbCEg5izRjA7xrDXhkjd70OfmU/VZz6GuawQsWsrQvVT0L5zckWdGcqvI5p5Ofsb/odIXhRjt4kFa15HtjvfdnX6k/hX6n/fLi61zf8ONE3jwIEDbN68GVVVSU1NZf369e/YQEBTFMJ1dRO5ROHa2qlRooQEbEuXYF0Rd5zTje9H0zQ6vB0ccx/jqPsoRwePcmL0BNppzxiLzsLMlJlxUpRSRWVK5UU7zD1zsIuvPF9LVFFxSWEu1zWSZtNz2223XZQ0/lREZZXnj3Tzm20n6BiO94sJZj33LC3gQ0ty6Q22xKM9fXs5MnhkisRNFERmJM+YiPbMSJ6BXvzbIlLeITe1b75OzZuv4R+elCrmTJ9J5aq1FC9Ygi48DK/8Pzged50juRSu+yXR7LnxKFPEMyXiNBIewRPxTEagAr30B/pJMiXx7HXPIo1aOLipneaDAxNkKH+mi/nrCkjNc8QlZS98EobG84Jm3gpX/xAsSfj9fvbu3cuBAwcmohdJSUksW7aMyspKdOfpx98p3G43jz32GF6vF5vNxgc/+EHS30Yu2zkhR+KyOV8fFF0ORnt8Ivyom73Pn2BsMJ6Zm5BqZvGNRRTOSkEQBPyeEWrffJ3qLZvxDU2akOTOqKRy1TUUz1+IpDvzuujq6mLXrl1T8q3y8vJYtmwZxcXF70pU7RIJ+ieFpmm8Xj/AtzbU0+2JX5il/m4+c/gZikcmB4C6lBTsJwnR7NkIp8xOaJrGgZeeY+fjj1Bqd3NtdmOcDFwEEboYDLS2cGTzBhr2bEeJxWcOtFSRrKsGSLXGO7eMzDuYVvKVCemWqkbxRgM81TfCQ31+OiPxy1IvaFyTEGSd3cMvBxOpicRDwEVmI98tzWZl0rlD2O3HDrP9z39kqLOdiGBge/bVNOoyAbh1bjZfu6aU/p4uWltbaW1tZXBwcMr6Op2OvLy8cZOFQtLS0hBFkXAgxoG9nyQibMMS/R+yclaTmm/HbLtwyNbtdvPiiy/S3d0NQHFxMdddd90ZM3knE4Bf2vIShxMO02ftYoYJlpp15OhUNE1CUXSoETuKr4xYwE6a5yhGQ5CgQU/QYidkTSKshlFkGVWVUFUJTdFjHCmDqA1FUPCa+/BJfmKqBJoBo2TFgAnUuBuTLMvnNHg4HU2pOWwtnwvAohO1LHR3sWzRPBYe+zKG0RY6MipYZ/SCIPD1xV/n1tJbz9hGMNjG3n2rAY0F819hqDWJvc/U0RPeQsAm4Roa4ootW3Fefz36e+/ljYMHaGqKO8LZbDYuX7CA4nCYSE0toepqwjU1E8QHQJ/mxDldh83Sisk+OXsoh0WGfdl8e8EneSZ3MYKq8rHnH+f2sVrGbpMZNPTxcusatnRehqJJSILM6rxtrCt8lcLsdeTlfRZBSCIajRKJRIhGowwNDdHa2kpnZydjYxeOHp1y8gHQ6fXoJYnQePTS6BtA19NNxiw3GQvcRMb0NDxdhKYKjOoTyCouYd7cStIKi0ktKMYYHYLqp+DYk5O2s0DYIDLgMhJ5zookTSP30UfOKfe5EP7V+t+3g0tt87+Lzs5Onn76afx+P0ajkZtvvpnS0tK/ebvy8DCBXbvipGj3btTT7mXTjBlYly3FkJePPj0NXVoautQ0JJsVX9RHjbtmghRVD1UTiAXO2EdRQhGzUuOkqCq1inxH/jnzWw51jPCxxw4x5I9iERVW6prI0AW55pprmDdv3gV/T0RWePpgN7/bdoKe0fgYIslq4PaFKeRktXF4aM9FSdzeTWvwU6EqCm1HD1L9xuYpUQWz3UHFZauovHINiZ6D8MoXJ00A5n8ErvwGmM5/n4XkEB945QM0e5qZlzaPB696EJ2ow9Mf4OAr7TQfGJjgu3npw8yP/ZA0fVPcWGDdz+BkTb9TtxkKsX//fvbt20coFG9Ph8PB0qVLmTNnzrsmVzyJsbEx/vznP+N2uzEajdxxxx3k5+e/q/voOzHGnuda6G+NX+tmu5751xYwfXkmogCdtdVUv7GJloP7UMfNRkxWW/z8rFpLUmb2Gds8aUO+a9cuOjs7Jz4vKytj2bJlZGefuc7fgksk6J8c4ZjCA9tb+c22FiKyioDG/EgLHx/6M+l1IYTgpE2uLi0Nx9o12NeuxVxVNUGIju/axubf/JxiSx/XZjXGXa/eIRFS5BhNe3dx5NUN9DVPsvu0wmJmr70O86wF/MeJbrJHH2QdLwKgNxcye8YvsdunesArmsbmoTF+1+nmgHfygXFZoo1Zdgt/6R+ZcJpbl5LAN4uzyDKdnYCoqsIrG97gazs9eCQ7oqbwPl0z/+9DV5M1bWolbp/PN0GITpw4gd8/NcRusVgmCFFhYT4Wi4bBMDkLeLJQWzQaJRaLTXkfjUapr6+nvr4eTdOQJImCggISExPPWPbU9+FwkGg0jKoKwHunOb5YqAgYDXr0Oh2SJOGOuIloEUx6O4FQArUZudSPF/St7G5hbnsjLoPIivBrzNGOsnv6aj4dOo6AwA9X/JC1BWvP2EdNzacZdG8iPe0GcrquYtMzz3A8Jxt9NMqSXfV0ZV+PdVYVS24uJqMogebmZjZt2jRhoZ2Tk8PVV19NZmYmmqIQaW4m9MKvkE68jC3Ni6iLd3maJhARC/H2uRje1QuyiixK/HL9Xby8YhUAV+9+ky889xiJH7yG/iWNNAz18GTDjdQOx6+dBKOXj8zv4/bF83ElLkYUzz77Nzw8TF1dHfX19fT398fXTUjA6XRiNpsRBAFZlgkEAng8nomH6enQSSEWLHwBSSfTcWwanvYUFE8QMRpGOK0rT8zIIq2wmLSCInKdMRwDG5AaXkYvTy4XHtHj92WT8I0n0Oe/d7UY/hVxqW3+9+H1ennmmWcmar1cdtllrFix4l2TKGmyTKi6ZsKCO1xff85lRZsNXVoa+rRxYpSehpiaQneiRr1piBqli5qx43T4Os9YN8GYQGVy5YSMbkbyDCz6yWhtz2iI+x49SH2fF0nQWCi1U6obYt68eaxdu/asUYhQVOGJ/Z08sOMEA974xEqCRWB6US8+0yt0+JunLG/VW1mQvmCC+FysxO3dhHdokJqtr1P75mv4RyYdYHNnVDJr5XKKhl9GPPaX+IeOrDhRKV1z3m22jbVx+4bbCcpB7pt5H5+d89mJ70YHghx89iBNNVE04tdMrquP+R9YQfr0s1h6n4JIJMKhQ4fYs2fPxNjBarWyePFi5s2b967WeAqFQjzxxBN0dnYiSRI333wz06dPv/CK50F/fz9H99cTarXR2xA/fp1eZNbqXGavzkWOBajbvoXqNzYx2j+ZU3ShGlCKolBbW8vu3bsnJppFUaSqqoqlS5eevwbT34BLJOhfBF0jQb71Ui2vN8RDkWYhys0FL3NVcCeu41lIh3xo/smZcF1GxoRkzlRZSVddDS/95DvkSe3viAj5RoaofmMz1W9sJjg2CoAo6Zi2eBmz1qwjo2QyYVDVNB7rHeaZ5k3cpf6CRDyo6Ckt/g9yc+46awd7aCzAb7sGecU9xklad21yAg6dxFP9I6iAWRT5Qn4aH8tJwXDaw+7Foz18+bkaQjEFl17lqt4NJPvjEbPSRctY/v67cKadGU7WNA232z1BiNrb24nFpjqs2O12VFWdIC7/W7eSKijEBBlVULEarSRpDgjEkFQBVSfhEcZwaYNk4MZAFAmFZoPEfrOOgAgmTJS5SlkYLsXUqkdCREnvZyx/E7I6iCgqky9BRRAVBsIZ/OjQJ/FHzczNjnD/rS6SnOUcG2nn3tfuBeCXl/2Wgw3J/Kp3iGh+PMfLHIsyt/0403vbceHhcuEt9s+fzS/cO9EJOn5xxS9Ykb1iyu/zeqs5cPDGeDTql7nsmbMSgGty89Fcyzn6RtdEYmbR7BQWXZuGTXKz96397KjpJKZogMZc+xBX6g5h8bWDPEkqohErnuMSY+1mlLCEsbychBtvQLTZCO7Zi2/HDp6Zu4Tf3nInqihS2XScb/3+Z9jwMnajjLiqmHrPYh44UMhgMAmAwoQ2PjTjDRaXziItbR0JCXMQzjGTe3Km+nwzhAMDA/zp0UcJBIOYQiFsPh/ehASyymvIzj6O35fEkSPXMEmMNWRFRYkoJMgB8HkQI6EJciToVKbd3IbZESGpO5G8UQfOsWqE8fynQMZdWD/2i7dzGY6fq3/t/vd8uNQ2/zeQZZnNmzdz8GC8oPS0adPes0KjstuNf+cuggcPIvf3ExsYQB4YQPVfXI6KoNcTyEmmpcRCU7ZAQ0KQBsMIUWGqu5okSJQmllKVUjURMUo0pPGlZ2vYWBMfkJZL/czXdZGfl8ttt92GzRbvgwMRmT/v6+D3O1sZ9o8nnRuDiIlbkBLeQhDj+3ovJG7vFlRFofXIQarf2ETb0UMT0XKzI4FlC3Kp8L2M5B0v4DnjFrj6B+ctVrqpbRNf2vElAH676rcsy1oWz/158zuw935GY6kcitxJo38xmhbvY3PKE5l/bQEZxc7zHmssFuPo0aPs2rVrQgFgMplYsGABixYtesfS47Pt57nnnqOhIW7Tfe211zJ//vy3vZ2gN8quTUep29uJPuxEQAQ0UstMrHp/JYGRTqpf30TTvl0o4zlQBrOZ6SuuoHLV1aTk5p91u9FolMOHD7N3796JdjAYDMybN49Fixa9533iJRL0L4bXa3v4j6cOMBKLd1oF9k7urHiSfEs/mYMrsB61EnxzF2pgMrKiz8zEfvVaYnNms/HZP5MZO35RREjTNHqO13Hk1Q0079+DNp7QZktMomr1Ncy8cg1W55l1G06iKxzlq/U1VIz+kLnEH1SmhOXMn/ljDIazd1wdoQi/6hjkL33DaMSJz/qMRGp9IQ564ySvyGzkO6VZXJbkICqrfPeV4zyypx2A5SXJ/OL22RgiPnY//Rdqt70OmoYo6Zi9dh2Lbrodk+3cVpmyLNPT08OJEydobW2lp6fnPHWAJPR6PQaDAVmWCY7LsQRBIC0tjdTU1Inv9Xr9xHtVHcbnO4DPvw9N8yJJMpKk4kqaTVbW9USjRWzYsIneQDfHkg7Tb4vPjDlCehbWJOL06elMD+FO01EcmkW2rHElO6gkPsMXFHT0lH+A4pt+hKCLz9j49/cx+kILqGAsceK4LYug3II/0EjA34jf34A/0ISiBGgdy+XHBz9DRDEyN+0IH698BKPByV9HbWwZGSbVlMCfV/2YiFLM+zc00ZaiR7PFr0dXyM+i5mpyPIOkiaP0l0n8NfgaRp2RB1Y/wNy0uIxOHhrC/Ytf0JL+BL5CE9VvXYOZKAtKMlg8Iw/Guom5Oxk70QJj3dikIUzi5DU9ho3XWU4tZQCYCXEFe5hr6ECceSPMvhOy5hKqrcPzxBN4N26cKN4q2u04b7oR5623Ig+P8OK+1/nqtCsIGs1kugf47m9+SF5/L4LVSsJ112G65hoeHvLx+z1+wnL8PlmWtZebijeQ5rCTmnYt6WnXYbNNf1szqOG+Ph7+/e8Z0DRsPh+rXn+DxNmzsX9qPUcDn0fTYhiN/4F70EFPTz2jozLyWYwXIE6RDALk5+8iNaeNaNBA/YvT0LwK+ZYRrss6jlGn4J79JVLe95WLPsaTuNT/nhuX2ub/FocPH2bjxo0oioLL5WL9+vWkvkPZ59uF4g8gD8YJUax//O9AP/LAYJwsDQ6iDA9PyTU6CVmE9jRoyhJoyhJozBIYTjiz/0gSbMw0l+DzXsn25vhzM1vnY7nUjMtuZsnKK9k+rPHnvb0EIvH1Bf0IBtc29AmHEESFLFsWizMXsyRzCQvSF7xnErd3E173IDVvvkbt1tfwe8aLtwoKa8tDlGrH4jnO5iRY+32ovO2cRUK/ve/bPNX4FE6jk2fmfpX0V78KQ+PFtivXw9rvMxYwcWhzB417+1HH6x9kTUtkwbp8MkvOPcaBeASkpqaGnTt3Mjw8XktHr2fevHksWbLkvEXdLxaqqrJx48aJAsIrVqzg8ssvP+/zRtM0RvoCtFcP0XZsiIG2MU5VmUSNI/htrSj6IKKmIo0MYvC4EWMRUguKqFp9DWVLV2A4R3HtQCDA/v372b9//4SiwWq1smjRIubNm4fZfPb13m1cIkH/ghjzB/jcr19gl8eOjISAxsrs3dxYvIEEs0hexkdIai/G/+oWfG++iXZKroScm82BzCRSdOeOCMXCYY7v3sbRzRtwd7ZPrJtdPoNZa9ZRPH8R0kUmA2qaxuO9w7zZ/AduVh/BQAxZSmL29B+RmnLZOder9gX5WnMPb43FB77ZRj1rkhN4aXAUdyw+S7HKamHswCA1XfHZh09fXsznV5ciiZM3urujje1//uOEf73JamPRzXcwa801Z03kOx2hUIjh4Xjh2lPJjF6vR5IkhoaGePHFFydkGUVFRVx33XVnuLkoSpCBgY309D6F1zvppW8yZpKReRuZGTcjkURvUwPdDXV01VXT29yAqsh0pAfZP91D0KRwOvSKnmW9i0iSU8mlh6vl18nQxR2PQoYUhqZ/HNOsm0jMzCbW6mfkL8fRYir6DCvJd1UgJUyGtTVNJRzuwe9vZHtDO1/elIasiizP2suHpz9BVIMf9JsYUUSWWmPcmiRjMhfwUtst/MUzDbnYDob4NZQ33Mei1joSg35ke5gG8w6cxgDfKLubpP2HiBzZgU4fRkpSwCZh1cIXPBcAEdWCX0tB58rFXlBEJxm8ckJjcFz2kZSURFlZGcXFxeTm5k7IRWSPh7G/Po/nySeJjZ8rAHmGBe/SMVpmZvETvsqglII1HOLrv/85C45XTywnJiYSXnkVD6bPZ0Nc5YZZF+a6wk1cmbsDnahgsRSSlrqOtLR1WK3nrmUiezwMPfggrzQ20Tku/1vX00vxJz6BddFC6ur/H/39z5OYuJjZsx6beNAFg50cb/gN7W17CATsBINOBscyEGJOFFkmKambihlvAlBTvYrR0QxmUcc6bQs6QcGtOBi94meUXH7LRbX1qbjU/54bl9rm/x49PT089dRTeL1eDAYDN9xww98sG3q3oEWjyG43sYFB5IGTUaST7+NkSR4cRIvFGLYzQYiasgXa0kCRJp9nMe8Mwr23gWbAIQTJE8doVFKIEu/nBIMbo2sbCclNLMyY938qcXu3oCoKJw7vp+aNzbQdOwyaRprJx9rsVpL14wXRi1fDup+CM/eM9SNKhDs3foDjnkZmhSP8sW8AvS0N1v0cyq6Zsqx3KMShzR007OmbJEOlTuZfW0DWtPOTIVVVOX78ODt37pyQQkuSxOzZs1m6dOlZC/2+HWiaxvbt29m2bRsAc+bM4dprr51SVFVRVPpaxmg/NkRbtRvv0NTnakznI63Ewqx56bQc3UJdYwMReyKafnIckJ2RztIVKyktLZ1asHUco6Oj7NmzhyNHjkyoZhITE1m6dClVVVXvem7UhXCJBP2LIhgMcv9Df2ZTn4k2NZ6vYjOEubHoBVZk78VsSqOo8AukOtcS2Lkb3+bN+N7chhYKERMFDuen48oMcG1WA6IA2vT3EShYx5G6AY7t2EVkPJKkMxgpX34Zs9esIyXvnVVxBugJR/lu3Q7mj32HHOLaaGvah1hQ/mVEMX4DxmIxjhw5wqFDhxBFEWdiIo1J6TytszM0Hqpe4LCQYzbyYkM/0tERhKiKwSDx8/VVXFNxbuvftqOH2P7YQwx3x/ftTMtg+QfuomTBOytEp6oq+/btY+vWrciyjMFgYM2aNcyZM2fK9rzeGnp7n6J/4GUUJS6dEAQdyclXkpx4PYG+BHoa6ulpqGOgtWUi2nYSeouViN5EwGKgNn+ApsR2AFJjyWS4E8kZcuD0CWB3ErQ7ENCYE9rPFfoDWHXxDqrd72TbYDFqUhHZadOZFpiFJEtgk3DdVY45++yd8+baPj75l8OoGtyz2MF9CwbZ27Odb9TFB9qfTAlTalTQySJdnpt5rd5Jb2EOx3OnowgikqZwe+8rfLn9D6TIoxduU1GH6MyDhCxIyIlrvxOywJENCdl091vY/XI/Q13xdrQlGln0vkKK56Vy8NBB3nzzTcLhyU5fr9dTUFBAcXExJSUlJCYmoqkq7tefYPDR+xGPeBDGrytSbZhvu5P/qljMVvSIaHzujZe5/rknzjjO4ylFPLDgdhr18XbLcvhZX/IkFa5J0mSzTSctbR02awk6fQJ6nRMxCGN/eYGxPz1OdWEBdTNmIGgat86dR/l16+IuPP5G3tp/LaAxf97zOByVZ+w/GGynte1++vtfRBBUNA3CLMMiHkPTfESjK+ntWkhV35PMUw8DsNM2l49WfJ0Hs5NZNnPGBc/F6bjU/54bl9rm7wN+v59nn32W9vZ2AJYtW8YVV1zxnlkZv5vQVBXF4xmPJA1M/A0M9NIQbKNW6uO4zUtTmsKIlEmo60No8mS/7RRCzNT1Up4f5LIrVjA/b/7fjcTt3cTY4AA1W1+j9s3XCI0OM9/VzaLkTnSihiqZYNU3EBd+HE4951376XrxE9xmDeMXRe7SZ/LvNzwBlqRz7sc7HOLw5g6O7+lDVeJD58wSJ/OvzSdrWuIFIzDNzc3s3LlzYnJUEATy8/PJyMiYeCUlJb2ja/PgwYNs3LgRTdOYNm0a1197A71NXtqrh+ioHSYSPMXdTwLZOEZAN4hsHCZF8BLraiMSnFRVJGXnkj5vMe6oSmvbpCW63W5n7ty5zJkzB4fDQX9/P7t376a2tnZCHZORkcHSpUuZPn36/9l9dokE/QsjEAjw6KOPUt0f4oCSz/B40cb8hH7umPY4xc52bLZyiou/jCtpGWoohH/7drybNuPdvp3qFAfWvPAEEYJ41H4oYmEw6ED12jCPJSDKlnhBLVGMmy1I0jn/IgoIogSSeMZfRIm2aIje0mO4SuNkRPM6KWi5HG9XjJ6+PiIxGU0QQABtPHSriCL9CS56ncnIokgz6dSKOWgIqDYdsVkusnVR/nOoi5WxEAjxTiceHh//KwioaLR0tXH4+DFCkfhgOdWVwoLK+aQlp4IgTix76jakxCSsS5dMGE2cHv0pLCzk+uuvn4j+yLKP/v4X6e19Gp+/buJ8GQ3ZGJRFeFuT6alrZ6ir44xzak9OIbt8BtllFWSVVZCUlY3X6+WFF16gra2NsBg/bpNqwmw2s6h0DvlHTEhRaLINsEutR1VVkk0ia8S3KAzsQRJUVA2OejLZ685FEpNZkXYrDoOLqBrmaHQ7QqaB5OxcXOOvpKxs9EYTTx3o5D+eqwHgP68u42Mri/j23v+h89ij3BFSWBHwIslTde2t5iy+VfgJNicvByAh5uPzHY9yU+8bhDQzg6JITkIRuuKFvH6gAS82UorqceV6Wbp0JzrdueWKmqrRuL+ft15sxe+JR3+Sc2wsubmY5DwzJ06coLm5mZaWFgKBqe5MSUkJuFxDGIw7SUjox+gRSD1ajri1H3V03AlKr6dp8TJ+sfAy6gtKeH/Mz0e+/RWE8UKpgsWCFgyiIvB67jwemX4No6a43GFJeoA75+7EKL+Gpp27krq7O5+G1njbVFX1U1QsoNc50ekdDA1tJRhsxeGYRWHh59HrEtDrE9DpnOh0tin5Rz7/Cf6641tkGndN3L+SZGfutF9h2vgd9F17Afhh3t38LO9DaILIt3KT+WjR23fnudT/nhuX2ubvB4qi8MYbb7B3b/zaLyoq4uabb37X8jP+ryH7/HR0HmNH60EePGom7JO5bGAvMzIy6DTFf6PRaGTlypUsWLDgPbFv/nuAIsu0Ht5P9Rub8Tbs5qr0JrIs8aiQ15SPcMOvsRfNha3fhr2/BjReT8rgCwlxYvjLy3/J5bmXX3A/vpEwh1/toH53L+q40UxGcQLzrykgu/zCZKi9vZ2dO3fS2tp6xvd6vZ709PQpxCglJeWs0ZfTcfitGt746z70oSQMMWe8luE4JJ2MTjeAP3qC0SQNdAJCLIq5uwUpHFcFSXo9pQuXUrk6bhx18nd4PB4OHjzIkSNHpsj7LRbLlOdpYWEhS5cupbCw8P88wniJBP2Lw+/38+ijjzIw6KZDn8uhWCb+SFw2tSzrEDcV/5UEo4+kpOUUF38Zuy2eQ6EGAvi2bWPPs0/go52KhAGyLF6chjNlSXJYJDRkIDhkIDSkJzxiQFP/tgs/PENl9E4Z1Q5CFBzPSFh2iwjncUYL6oz8bPZt7MqqAuDyrkPM0PXy0I3rGUmIz4otP/IWn3rmMdI8w+fcjiwKtKY4aU11oo4TmwyPj2n9I1iiZx+8WpcvJ/373+NQUxNbtmw5I/oDMDZ2iN7epxgYfAVVPdmOOtSxAgaqLQzURzjd+S0pM5vs8hlklVeQXVaBI+XsWvaTkactW7YgSRJLlixh0aJFmEwmYgMBhv5UjzIcZsDgZYu5lmAkhMVi4YPXLCWj9tcIDRvjv11no9l6OfWeXIoDs3DpM1A0mf3uV+gMHJ/coSCQkJKKKzuXfcYynuq3kSMM8JvyeiqGXkH0Tq3TE9ULhI0SAXMur/aX0KO6GM6r4nBGJg22uETB5fMwv6ORvOF+QEOv1yPHZGbNmkVa+q8JBlspKf4vcnPvPee5mziHUYVjW7s4vLmDaDh+vedWuFhycxGuTBuqqjIwMEBLSwvNzQ10dfVMkeWLokZeXhalpTMpys1F/9Z+Rp94gnBNzcQyzTn5vLBiNeErVvHfOzej/OlRUFUEsxnrggXIPh/DtQ08XnolLxYuQxEl9KrMbfoe7lg+SMzVSsjdQjTgRjWraCYY86VQU70aTZPIzq6loPDI6T/tPBDR6Rzo9Y5x0pSATpdAY3c9iYZWNCDgTWZZfS+uqBevZOVT5V9ld8pSbkxL5M7MZKrs5nf00LrU/54bl9rm7w/V1dW89NJLyLKM0+nk9ttvf3fqrPydwb9jB92f+SxaJIJ/5QqOzJ5N77gUy+VysXbtWkrGXTz/WTE22E/Nls1o+//AQls9BklBVgUighWrEFcNDKcsZ3T2Z3nUv5Xn+zZiN9h55rpnyLJlXWDrcfg9YQ6/2kn9rl4UOa7WSC90MP/aAnKmJ12wTx0cHKSrq4v+/n76+vro7++fKMB6KiRJIjU1dQoxSktLQyfpcHf5aDnYx4mjA3jdU9dVlRHU2AmU6AlUpY9YUiqR1GwQBAxyhFKHhfTcfFw5uSTn5JGYkYXuPLK1aDTK1q1bOXz48ERtJIgbHsydO5cVK1b8r+X8XAiXSNAl4PP5eOSRRxgeHsZgdzGYsYgXquMWhRa9wvuKXuay7G3oRI2MjJspLPw8JuPkA+H4m28wUF9LWeVsEkwgDlUjDtcgDtcijjUhqFPd0jRBh2orQraVothKkC3FaJIdTVFBVeKSLkVFUxU4+dnEdxqxcJiuzg66hk5gvawVfW68o5K70yjvXYVBNoKqAlo87KpptCsmvhwrpgMzkqZypb+OacF2BEAU4MCMWbxZNR9VlDDEoly3eytr9+/AoMgTxdFEAQz6eF6PQa9H1Um0EaVbHU+YB4qNNsqNNgyI8bCYqhI8fBgtHCZit7Nz4QKGk5Mnoj9Wq0Zf3/P09D5FMDhZoyUyZmaozsFIkwMlMq7XFkRSCwrJKqsguzwe6bE43l6Cqt/vR6/Xn1EpXQ3GGH68gUjLKH7CbHEdxx0YQRRF1q1bxxynFzb/JwyOW72mlKNe+V3ce13EGuMzaIOuPpoDhxnu7iTki3+mExRK7EPkJIeYaZzMpQmj5wW7kRftVv7tqt+TLjTScuKH8d9pvpbPbrgCv6Kn3NvKbdP285OyuxkyxOUHqd5eVjY14ArE97FkyRJKSkZobfsKRkMaS5a8OSGRvBBCvigHNrZTt6MHVdUQJYEVt5dSsTwLRQnT3f0o7R2/IxwOMTqaTiAwC89IBj7fVGtqp9MZzyPS63Fs205440a08c7fZ7ayb8UVrL72Ksx/fIjQeNV6Y0kxKZ//PIrXS+22A/zMn8Kh5PiAIyk0xj31G5k70IRejWEryMV8z1082dREKBSmuDiTtWvLkJUx5JiXaMxDT89fiEYHMZmyMJmykGNjxOQxYrExVPXsVtoQv7wFYKC/nJub92HUYjRZcvmv6Z+gxFLLEnZgExV0ugSmT/8xrqRlF9W2p+JS/3tuXGqbv0/09/fz5JNPMjo6ik6n4/rrr6ey8kx56T86Am/tp/sTn0ANBjHNmcPIpz/F1t27J2buS0pKWLt27TsuKvuPAkWW6dj1Mubt/02G1g6AL2bgjf5iWv3x364IGpsW9zPkjJLqt/Ch7kUkJKVgS3JhS0yK/z3lvdFinUJwAqMRDr/WQd3OXpRx59K0Agfzrsknb4broieYFEVheHh4ghD19fXR19dHZNy8BwBNwBB1Ygi7MEZciOrU/F1N7kWJnUCNtaKpHjCayCgqxWtPpH+85EhVVSXXXXf9RUcEZVmmurqaPXv2MDQUr/UoiiIul4vR0dGJHCCdTseMGTOYP38+WVkXRyTfK1wiQZcAxNvnkUceYWRkhMTEROasvpkfbW2nujsu88lz+rit+GHKkloQRRO5OfeQl/dRdLoLOJfEwtB3DLremnwF3Gcu58yD3EWQswByFkLq9DMc53w+30Tl5YmEumQXWkk35frn0aHgFVzklv6IuVkrJ9Z7paaPLz5zjEBUIc1h5DcfmENVTiJ/6h3ih239jMrjkS+HhdFolNpwfJYkTY2xbriL1L4uxsbGUE/LtzkJMRzEONiFLuCL/28wkjV/KSXLVpKckkrv3n0IP/oRdp8PVRCIfuD9ZH10Oe0nHsEX3A1CfP9qTMDT6mD4uJPggBlJbyC9qHRc3jadjNJyjH+DLENVZYLBE8RiJ4v4nXpLa2iqRvRNFfmgSgyFHYl1tIXi52rWrFyWLSnEXP8a5n2PIYbjBCSSvxCP/vPINXEJmjQL9FeoaO3HkKo34+g9iG6cJKoa7FJn8oyyAmPvIG1FdTTl+kkOmXlk9XdRxOO0tf4CBA25zsJX276I2+BiuamD+/U/4P7sW/l97vuJICJoGtP62lnQ3oAlFsFkMpGdU01q6kFmVHybzMzb3lbbjA4E2fVsMx018Qhg3uwwjvIfEJPjxWqt1lKKi76Ey3UZEC9m29LSQktLCx0dHSjKpOmEKIrkZGaS5fNh2/omzubmifhdbMFCUkuLGduwEXV0FADH9deR9sUvIjocvLJhL987OEKPNpXEGZC5xnAcpxjGg5V9UiU6vR6jTsSgEyl3HmVd7i+QVQMv9/0cRUie+M6okzBIGjoxhk6MohMiiEKYfiHKDOlnZGjtuE6YqOqLR+d2OivZlV9ApngCgyijE2X0YgydKLNo7kMkuxa/rbaFS/3v+XCpbf5+EQwGee655zhx4gQAixYtYvXq1RclOfpHQujoUTo/+jFUrxdTRQUpv76f3ceO8dZbb6GqKqIosmjRIlasWPGeWIj/XUHTCOx9lEDTbjptSxnzhvGPDBPwjODzDDMQGuDFJb1EDSrlbXYWHj93bpDOaMSe5MKamIQt8SRBcqE3JdF7wkB7TRAlFn8Op+bZmX9tAXkzL54MxaIRRrq7GO7uxN3ZTk97H8ODOpRYOjotA4FJ8qIJClHDCBHTMFHjCEYDJCcm4EpOobWrC58/gCAIaJqGIAisWbOGhQsXXtSxnKx9tHfvXny++DjIaDQyf/58Fi5ciN1uJxKJUF1dzcGDBxkYGJhYNzMzk3nz5jFjxgwMhgsXkn+3cYkEXcIExsbGeOSRR/B4PCQlJfGhD3+YTY1j/HBzA55gnHQsyWnjxoKHSTKNotcnUVjwOTIz1yNebBKlpoGnDbr2j5Oi/TBQx9QBOWCwQ/ZcyFlEwDWD3e0R9lc3TISA09PTWbFiBWVlZQiCwMsdewm0/gep9KIi4NGVYpTsbG5cxKameDXwynQ/X1s1QKrdhCRZkSQLIUw86w7z8lCMECZUwczspAz2+zTcsfjA9tqUBL5RkI49GmZkZASPxzPxOvl/JBxGCngxDnQhReNSNlVvJJKajWx3ootGmN1Vg5DbjTg3jD5xMhwddBsZbkgk0J1GesGMuLytbDrpRaXo3mGnoKoygWALPm8tPl8tXl8tfn89qhq54LqOnmWk1X8YQdNxwHKMajVODBITeygr34lJi1DQGSS7N4yogSpAt/UWpKF1WKVtmI0bMKpDk7/PJNKXZqI31cTP6u/j8HAVBiHCHeY/szGzhYheY+lxJ7c1+3BKITz3yqAHZVTHdxs+S7s3n7v1m/iG9Bjt5gw+kv9talOLARCVMLN7jjO7vQudpmIwBCkobGHRwqvRG6xIohlJMiNKpsn3omn8MzOSaEIUTYiiDlVV2f38Nqpfj8dGTEmtFFz2V8pn3kt6+g0IwtkHPtFolPb29nHpXDMej2fK9xaDAePgENPqasno78cQi6FLT0eXmkK4Oi6fE202Uj73ORLvuJ2IJvDQrlb+sKMVT0hGQGWVvpksyUtA07MhMp0Qk9eFgMo3l3yfLFs/G1tX89eW6855bjWdgJJpQcm2cpvtKW6JPkd5fYBkbwQVgZ8pt3B/7H0TBQBPx4/WBbh12dsjmHCp/z0fLrXN3zdUVeXNN99k586dAOTl5XHrrbdO1Nf5Z0H4+HE677kXxePBWFJC7h8fYlQQ2Lx5My0tcZWCzWbjyiuvpKqq6h/CMOK9gKoqvNa4iS/u/08APuv8IOWhTPyeYfwjwxOEKRy4iBpQggWdaR46YxUI8TGU0RwisyREVqkNuytOmqzORIJjowx1dzLc1cFQVyfD3R2MDvQjCE5EfRGSvhBBlzkl71MUw9hcIayZoHNp+KJhBt3uiXo850JeXh6LFy8mIyMDh8NxTiLk9/t56623OHDgwISpkN1uZ9GiRcydO/eshFnTNLq6ujhw4AD19fUTE4gmk4mqqirmzZtHSkrKhdvuXcIlEnQJUzA6OsojjzzC6OgoLpeLu+66C0Uy8tPXm/jzvg5UDUw6uKFkJ5dlPY9elLFYCsnL+xgWcz5GYyoGQwqS9Db0nuEx6D44SYy6D0LUN2URDRgkmRFrCc7KtaTPux4hqWCKt39/aJSXjnyFovBmxiJ2Hqi+i0ZPXF60Jm8LN5e8jCSePZpzOoKYeY7beU24GhUJA1FuM+zkFtNRzHozkmQZf1mRRAuqpicSFggGZfoaT+CuayQWjKFGRfSJAq5iNwm5Pk6Oo5WoyFizA0NkPtnlV5NdXkFKXgHiO5hhfDuER5JsGI0pTOYWndq5jdeIEAQMw1m43roFKWLjhL6LHfpGFFXAYg0xb24zVmsYUyBEXn0rzqFRYFJWBaBiYCQjGXduCj5XwsR5iikS39+9lhp3NnZDmNXFf+Z1rQVjROSWbZlUdo3gvMJDaIUCAiiawG+O3stR90x+rf8F10r7GcXOj3PuYFP+QnrEOBmyxEa4rK2WnL4RBMBk8pKff5TklI5zlX+YAkHQI4pGFMVPoH86vfs+hhK1YLLpWXvfjAvam56K4eHhiShRW1vbFO22pmkkejxkd/eQ0ddHos+HZLWijj+UjOXlpH/9a+irZtESDJNt0LNl0yscPXIYnV7Pdbe+H3tiChFZJSqrRGSV0OiLyJ5vowl2/I4niaiWie8iskpYVuhQZI6JMi06DUWAMq2OH4z9F1XHvZiiKgHBwo9t/49dwjy6R0OEouMPJr2IrKiMy9h5+EMFXP4OrIMv9b/nxqW2+cfA8ePHef7554lGozgcDtavX/9/LuV5txE5cYLOu+5Gdrsx5OWR+/Af0Wdm0tTUxObNmxkZidfbycrK4uqrryY7++2bpPyz4KcHf8rDdQ9j09t4et3T5Dhypnwfi4Txe0bixOjk35Ov8f8DnuF4YVHBjM40D8lYhSDEJ7hUeRA5vA811nLangUEXSaSvghRX4goTY1EJaToKJiVQun8bJJzbGclMMFgcEJKV19fT09PzxnLnITZbJ6SY5Seno4gCOzdu5cjR45MkBiXy8XSpUuprKy8aPlcIBDgyJEjHDx4kNFxZQRAfn4+8+fPp6ys7D2Pul4iQZdwBjweD4888ghjY2MkJydz1113YbPZqOsd4xsv1nGwIz7TnZ2gcHvpE5Qn7j9jG/HBdpwQTfw1pGAwpsb/jn+u0yWccZMO9vdRs+Upws07yKaHHPpI4iwzF9YUyFmIlr0AJXsBkZSZRDHw1/rD/PyVIXwhAUlSmFbRSW56P0ZCmAljIkyKLkqyFMMpRrAIEUQ1iKIEiMoBBG2SPHSRwyPcR4NQAUC61suHeIgqjr6jtlWDaVhD8zA+XIO5tR/RaCT9a18l4eabLyrs/HYJj91egcM+A7t9Bg7HTMzmvCkzReeDMhZh6LF6Yt1+hiQfW+x1+MIBjEYjH1g1i9zhHVD9FAQnTSRUzYxX+TAB+QpEVxLJd89AnzyVELf7Qnz4D/vpGPBjEGXSXD9nNHmIilYH8xsSmb7iChauX07t8U8Si41gNGbyfPtnebUGNhi+Qr44QDBnNiNrP8Wve/w8OpaPqouTlMJYL/Pqa0gajefAJCREmFY2gMs1hKqGUZUQihpGUUJnzZMRRQPZ2R8myXoPrz/UznC3H0EUWHJTEVVXvv1aGbFYjM7OzglS5HZPlYIaw2HS+/tJ6+snKkjUFpRwqGwmx6ZXEtTpMaGR199JaX8XX7h6FeVlZVPPkRJh774riUT6KC7+Mnm5901855UVnhvw8FjPEPWBScOSSovMT9vuZHpjL6IGJE+D2x+H5DihjMoqn3r8MK/XD2DUifzxrvksLnQx6mvHYctDJ739GeBL/e+5calt/nHgdrt58sknGR4eRpIkrr322gljm38WRDs76bzrbmK9vegyM8h7+GEMeXnIssxbb73F9u3bJ5Ldq6qqWLVq1btS0PMfDTE1xr2v3suRwSOUJ5Xz2DWPYZQuLhf1JDRNI+TzjhOjYTx9w7QdizLYZUZTxwf/2jDRwB70RiNGewVyLA1VmSQZoiSQNS2Rgspk8iuTsSddnFzxdCfEkpIS5s+fz44dO+jujsvAT8rjzoesrCyWLVvGtGnT3nF0UFVVTpw4wYEDB2hubp7Yp81mY86cOcydO5eEhPemQO8lEnQJZ8XIyAiPPPIIXq+XlJQU7rrrLqxWK5qm8cLRHr77SgNuX3zgvSTPz/XFb6IpQ4QiXmKKiqzqiKk65PHXud7LmgFNcKAKNsIRGyNjZnwBEQUBBRGDyYjF5iBJDFESraMsepzpSgPTtBMYmOpwEtF01GoFHFJL2aeWM+iaz88+uBTZqmP/WIADYwH2jwXoDEfP+L0ZRj3zE6wsSLBSaTOwc8jNY91dCGoQE2FK7U4OhZ0MyfGOaaV1lM85m0kVPShKnEDJ43/jryCKHCQm+9EUjWTXavIL78JmmwaAMjpK7398Gf/27QAk3HAD6d/4OuIpjin/n737Do+qSh84/p0+k8kkmfQeEkISCCX03pEmIjaw4qprwbJr1921r64/67qu3VXBLhZEQEDpvZeQQAihpfc2k+lz7++PCYEAgYQi7XyeJ08gc+/MmQM5d957znnf4wc8u47IHHfY6QY8LZHdXmp+ysO2tRwHVZSYfqC9ez3RlB8+yD/SV3FbqYKNn+K2+1Ppfh6vHInCoKRmcgfWmxRsrrexua6Bgw4XuLxoN1SibPCA3oMx7mU0agdXLo8ioEFFZPsOjL5/KrkHHsLhKEChCOLzdddQUR/IT9pn0Ck8eC97EdXAB5iz/3ce3L6KBtN4aEyI0N26jYycCnSNm3vbtWvHyJEjiYs7fLdOlmUkyYnUFBQ50GiC0Wh8g63b5WXZlznkbvCtX+7QO4Lht6Sh0Z76nana2lp+3JrJquxdBDRYKA8wUxQURqE5DJuuebCo9njwHHFHLVar5rqoEK6LDCbJz/c+D+b/j7y8l9HpoujfbzFKpZatFhtfFFfxc1kt9sZ9bHqlgivCg7g1IoDEeWMJ2ZsDgJQ6FuVVH4O++Zjo8kjc+9VmFu0qR6/xBUID2oee8vsW42/LRN9cWBwOB7NmzWL37t0A9OzZk3Hjxl1U6aTdJSXk33Y7rgMHUIeFEf/Zp+iSfTdJLBYLixcvZltjghetVsuQIUPo16/fRdUHrVHaUMrkOZOpcdYwOWUyT/d/+ow8r8PqZtvifDKXFuJ2HFvkXOenJqFLCIldw4jvFIzW0LZ+t9vt/PDDD0173YYMGcKwYcNQKpXIsszSpUtZsWIFAB07dqR9+/ZNCRjKysrweDwkJyczaNAgEhISzmia69raWjZv3syWLVuaknMoFApSUlLo3bs3SUlJZ3QppgiChBZVVVUxffp0LBYLERER3HrrrU31EiwON28v3sNnqw/gkf74/xo6XHRW7KenMpeeyj30VOYSqqhvdoys1KCI7wftR/i+IruCUkmZ090UFK2vs5JlteM96i34qZSk++upd3vZbfMFewEqJV1MfqyrteIFDEoFf0mIYFpcOPpTuDsuSxJV//uEirfeAklC3T4e/dOTsJnLzkrAI8syhU43HkkmVKvGX6U8+eAleZH3LcPz28eoyxahUPj2hnlRspsk6pKupPf1j6PW+u4+ldaUsWnd1+wsqWVg0WASGnQ4lPCPbnqWhx/eN5ZQXEj7g/lsdLbD7ZRRGKoxxv2HfsHpdJ/jwmG14BcYxLi/3k1h7T9xOvfi8WjYWfswVdt38qLmMzyocE+dhyGpP7P2zOIf6/9NQ9BknEZf9jIdbsZ7nIRtWIHS7Qt8U1NTGTlyJOHhx08lfrw+y1xayOof8pAlmZAYf8bd04XAsLan96z3eFlba2VFtYXfquopOCoYV3m9RNVVEltTQWxtBcHWOsoCginxCyI7PpkGw+GkGN0a6rlS7yZB9Qx6uZS4Dq+yVjmUL4qryLIenuHq4KdjanQo10aaMTuqcH01AW1pLjLgHHA7+lFvNC8MeASnx8u0L7ewJMcXCE2/rQ/9kk4tQ5QYf1sm+ubCI0kSK1euZOlSX+Hn2NhYJk+efFH9+3kqK8m/7Xace/agMpuJ/+R/6I9YCltYWMj8+fObllIFBwczZswYUlJSznntlz/SqqJV3LvoXmRkXhn8CuOTxp+x53Y0uNm+pIDsFUVo9WradQslsWsoUe0DUZ7CZw7wzWZ+8803VFdXo9FomDRpEunp6ccct2HDBn799VcA0tLSuOaaa9BoNHi9Xlwu11lPce3xeMjJyWHjxo0cPHi4JqLZbKZXr1507979jNTvEkGQcEKVlZVMnz4dq9VKZGQkU6dObfYfL6/cwovzdrH5YA1alS8blVatPO6fdUf93dFgoay0iIZ6CyokVAqZULOC6EgHfvp6FHINSLUg1aBRuFApvWgas1X5MlYd/rNa4SbQ5STEYifEKhNc40J/1IdMj06PLbId9pgUXLGdISAKtcqIU+HPTlcA2216ttpUbLXKWI6Oio4QqlFj1qjY0xgcJRq0vNghlpEhrft/dShLW339DiyWLBrWr0f7zgFU9SDpZGpv8uLo5buDfzozPOVON9ssNrbW29hmsbHdYqPaffiukl6pIESjJlSrJkyrIbTpz2oSbEV0zJtFdM4PaCyH1wu7ScTqHsVWXRpLKaHCPwBXfBJyckcybU6KnIfToRs8Mi9vtzOo0ouEzFrDLpzbFtPxwF6iR44g/PHH2CMbuPK91bidXpSG/fjFf8pbfV+k+LNfqcg/gEKtgYxutEteSGBgOUqlDrfpBTyzP2a8ch3lyjCU96wiNDySz7M/57VNr+HWJqEPu5FSlW/WLVKjYlx9GbqNqzlU7Kdbt24MGzYMs9mM3SuRbbWz3WIjVKvmirAglEddxIv31LDgoyzsFjc6PzWX3ZFOQvqJAwKXJLG53saKagsrayxstdiaBduKxn8DuySjBl6KC6ZrfSU5a9eyv6wMl1JJZEkJg1esxGM0siqtC7/1HczGTt2a6lOpZA/B3irqCMal9gWZWmSuCAlganwEfQIbU7QWbkL+9kYU1jI8KgUVw24iavC7J/0/5HB7ufuLzSzPrcCgUTH9tt70PYVASIy/LRN9c+HKzc3lp59+wuFwYDQamTx5MgkJCee6WWeMp6aGgjvvwpGVhdJkIu6jD/Hr3r3pcUmSyMzMZNGiRVitvkQAycnJjBkz5g/d3H6uvb3lbT7e8TEGtYFvJ3xLUmDSuW7SceXm5vLjjz/idDoJDAzk+uuvJyoqqsXjs7Oz+emnn/B6vcTHx3PDDTeck/o+5eXlbNq0ie3btzelAVepVKSnp9O7d29iY2NPOfAWQZBwUuXl5cyYMYOGhgaioqKYOnXqKf8iyLJMXl4eK1asoKDAVzdGqVTSrVs3Bg0adNxaBLLsxeWqxuWqwOkqx+Vs/O6qwOmswOUqb/retDdGljE4JEJqXARXuzHXuVEfFdhYqTbRiQAAeaZJREFUjCqqzVqqzRpqAzRIKt8vkYSCQuLIJY1cRTq5pFHBsUuBVHhRAm4OLZGr5/GIOuL9dL6ECWp/1CojkuTGYsk+4ZI2ZR0Ef6ZDm+tro+6qAYQ//jjGoA6tCnjqPV62NwY7h4KeYqf7mOM0CgUapQKb99gEEX5eO5dXLOeG0vkMqNvW9PMatYmfwkcxN+Zy9ptSke1e7MhYNQqkowYeJZBq1NM70EgPkx/dsucStmQfDnkUAAZpDobhnfAb96emc7YV1nLth2vxuCVUxhwS0lYy7/Iv+f3Dd8jML8ITGIJeLTFqXD51dStRKFT4Bz1K1Ow3iKOUVareRN09i/bhJt7Z+g4fZn6IDPQJ78Fmvz9TJvnWq3cxaBhRlIdzh6/AqKxUUhyfzJLo9jRoDq/lHhTkz1sd44nVN8/MZ61xsOCjLMr214MC+k5MoufYw0sBZFkmp8HB8moLK2osrKtrOKafkww6Bpv9GRJsYkCQP1qlggd25vNrpW/P21/iw3kyKQpkmZKtW5G++Rbrr7821r0CfbduVPXpxxtx7VgVGoVbcbjdSq+Xznt386e5P5CRl4M2Pg59ahqBCfX4W39BIXto8FOxr09f0ofMQals3RIKh9vLnZ9vYuOBaj65tTcDk9u+LO5CGH/btWvX7I4jwMsvv8yTTz7Z4jkOh4NHHnmEb7/9FqfTyZgxY3jvvfeIiIho9eteCH0jtKyqqorvvvuO8vJylEolY8eOpXfv3hfNbIjXaqXg7nuwb96Mws+PuPfew9ivb7NjnE4nK1asYN26dXi9XpRKJX379mXo0KEXf0ptwCN5uOv3u9hYupHkoGS+vvxrDOrzoxgo+K5Nq1atYvHixQDEx8czefLkVmU43L9/f9P4Fh4ezs0333zOximn00lWVhYbN26ktLGoL/iyBU+ZMgWzufUJjA4RQZDQKmVlZcyYMQObzUZMTAy33HJLmwY3SZLYvXs3K1asoKSkBPBF8j169GDgwIEEBQWddhtlWcbrteJ0luPxWBr36VjxehrwuOpQl+agL8hCX7wHfXVZs7xoklJJndlIdbCOykAFVoPULPNcDWZySSObLmykL/UEcry0YwpZoiPZjGc2aezCwLHL2XzvvfkMj8nUGYM2lsp33qPqww8B0HfpQuxb/0ZzVAYiu1ciy2pnW2Ows63exl77sYkRFEAHPz0ZAQYyTH50DzDSyV+PTqmkweul0uWhyunGXbCekKxvids3D53btwZXQsH6kD58FTmeOcH9cbZQfFQhS0TXVhJTU0GItY6dUYkcDIsixO3kjnk/Mfr3uajxYho4GjnkOgAMyuV4Ou/HMuIfhIXEE6hRs25fFTd+sh7JK6MO2MYVI6K4RZvBL7/84gtoD+4mLj6a9Ks9VFbPAyBWfwOJv72PFg+vK6Yy7Nbn6Zlg5v82/B9f53yNEplbQmVyYr5gQa0ST+MIpnO7GLgnk5QK3+ZPt1LFnoQUNOldWdPgxi5JBKiVvNwhlqsjzM0+zHjdEitm5rJzZTEAgb1C4bIo1jT4Znwq3c33qYVo1Awx+zM42MRgs4k4/bEpzyVZ5pX9pfznoG/v0fjQQP7bKR5jY1Yc5779VH34AbVz5qJoDIbWd+rG9MuvYU9SIgkqDZUeL/VHBMtJhfmM2bCc6+3zSY31zeSVh2jZlehP9LyemKIz0KWlok9LQ9ehA8qT/C473F5yyyx0jQ064XEtuRDG33bt2nHHHXdw552Hk0uYTCaMRmOL50ybNo158+Yxffp0AgMDuf/++1EqlaxevbrVr3sh9I1wYi6Xi9mzZ5OdnQ34ZponTJiARtPK0hHnOclmo/D+B2hYswaFTkfs2//Bf+jQY46rqqpi4cKF5ObmAmA0Ghk5ciQZGRkXfUrtClsF1825jipHFVclX8ULA184100CfP83f/nlF7KysoBT28NWWlrKl19+idVqJTAwkJtvvvmczvTJskxRUREbN24kKysLg8HAQw89dEqZ5EQQJLRaaWkpM2bMwG63Exsbyy233IJOd+JsKJIkkZ2dzcqVKykv922m12g09OrVi/79+5+7f4uGKti3FPYuhb1LwFLc7GHZFImcOBhPQh9ccV3x6rR4PA1NgdUOq8S/yqPZ7Tp0J+XIBNE+CiQSKKCDYi9xOgUJfoEkBkTTISiZ+MBEVMrj/8Jaly+n+PEn8NbVoQwIwP38C2zt1rMp6MlpcByzhwkgXq8lI8CPDJPvq6vJgL+6hUGhvgQyv4WtX0HVnqYfV/rH8UvMBN4zj6BQ13zfjEoB7fQ6YvVaQjUqNMU2Gkqt1Ks8RJZtw1zn+/et0BqZPHsW4XW+LIIrMvrw7nW3MMKi4uEcBUpUaBU78NO/zgcJE+nYdTyXJ3dmSaGCO77YjCwrUJs3kR4WR/f8fLp3TKNg4SycDQ0YzWb63h5BtXUWAGkNPYjZ/BtuWcWN3udIHTMOb7iOpTmv0VC7DDUyfcI6M9vQ/G6+Auip9NJ/1ybcpb6g3GAwkNKjJ9/IelarDHiVKiaGB/FKSixmje+CUef2sLrWyuydZayqs1Jlat6/BqWSfkFGhphNDAk20dGoP2ZpXUu+L63mkZwCXLJMF38DM7okEqhWMau8li+KK6ncu4+b5//MZRtWoWoMhhR9OhP/4N/RZGSwtLqe70trWFhZh6txuFbKXobWbGKYZynxodsI/0LCb91R/yeUSrTt2qFPS0WXmoYuNQV9WhrqiIgzdjf7Qhh/27Vrx4MPPsiDDz7YquPr6uoICwvj66+/5tprrwUgJyeHjh07snbtWvr169eq57kQ+kY4OVmWWbNmDYsWLUKWZaKiopgyZcoZucF3PpCcTooeehjrkiWg0RDz+usEjBl93GPz8vKYP38+VVW+zKFRUVGMGzeO+Pj4P7LJf7j1Jeu56/e7kGSJFwe+yJXJV57T9tTV1fHtt99SUlKCUqlk3Lhx9O7d+5Seq6amhi+//JI8Sx6VAZVMTp1Mv6792jTrfTbYbDYqKytP+f+WCIKENikpKWHGjBk4HA7i4+O56aabjhsIeb1eMjMzWblyZVNtAa1WS9++fenXr98J767+4WQZKnJ8wdDeJXBgNXiOTJ+sgKhuvuQKySMhtg+otciyzILKOp7NK27KOBeiUWHxSE0fQluiAWL0GmIbg4pYvZZonRqVQkG120tVfj69X36B+L2+AOWrMRP59IrJSI13OsK0arqb/JqCnm4mP0K0LdzZcdSDpdQX6NUW4Nn5C6q9i1DIvg/SNpWBX0KH8k3keNYHdm2a4YrUaugZ6EfPACO9AvzoYvLDcNRmTNu2cqp/2IPk8bBBm02W0hcIxeXn06uwiJoHHiS/R28q3R4qXR5MB61MXlaOzqtArThIqPY51IrGtNFKNbM0Y3mo7gZAgSL6IBMj1LzZNQ6rV8/cz76itLAUlVpNl1uTQD0bZJm43UZSyvMplEMZ7/wXVakxeBMMRFX+C489F51CZnj6CwyOG4FBqeD9gnLW1PpmvMK1am7Vy2jWLqe68nCBV5RKSv2DKAoMpTo8ik7xsRS6ZbZbbBy5wE0hy0RXeUmu8jC5ZywTekajO407nhtqrdyWdYAqt4dgjQqXJGNtXFKnUSi4PCyQEfkfkDTzJ/zWq1A0Nsavfz/C7rsPv169qD24iV+WfcbMwP5sCuzc9Nx+CidX6P2YWFlEenYmrt05OHJ24238/TyaKjAQXVpaU3CkT0tFm5yM8hQK+F4I42+7du1wOBy43W7i4+O58cYbeeihh1q8Y7pkyRJGjhxJTU1Nsw+6CQkJPPjggzz00EPHPc/pdDatawdf38TFxZ3XfSO03r59+/j++++x2+34+flx7bXXkpR0fu4RaSvZ7ab4iSeo/3U+KJVEv/wvAq88/gd9r9fLhg0bWLZsWdP/9y5dunDZZZdd1P/PP9j+Ae9uexe9Ss/Xl39NB3OHc9KO/Px8vvvuOxoaGvDz82Py5Mm0a9fulJ9PkiX+t+1/vLv9XSSFhJ/bj4FlA2kf1J709HQ6d+5MaOipZxA9Vy6IIOhU1mof7UK4CF8oioqK+Pzzz3E6nSQkJHDTTTehbfxg5Ha72bZtG6tWrWqqSmwwGOjXrx99+vQ5J5vq2sztgPy1jUHRUijb0fxxjRESB0P7kdB+BI6gRD4srOQ/+WVNe0DSjHr22I4/Y9NqsoxKklB5vSiQkRUKZI0WlVKBSqFAK3kIc1cR6awk0llJhLOScGdF4/dKIpwVhDsrMHqPrYcDsC6gC99FjuOXsOG4NUa6mgz0DDTSM8BIzwA/Yo6zdOt4HHkVFP/tNZzZ89nXLo7NvXohKZVERkRww403HpPf31VspXJ6NlK9C0lpQWF4hyhpHWrZl7ThBeUYPrXdCoA3WcHt2pU8t+89FIBD1mJ1qqn36NjfPgQ5pRa1V6L7ZhuBTgeLvd25w/0oQ7pH88S4JJ7/bSy7GhrwV2v5Yvx3JJuTm4LX5/cWc8DuC17TjXqmKhxo9+1mS0U1e/QmisxhlASG4FE1/xAcp4QhwSZGRYbQXaVj7We7KN5TC0DPsQn0mZiEUnnqMyj5didTd+wnp7G2T6JBy83RoUyJDEbr2MnGTVcBCnrGfIr9y9+pnfUzNBZkDR8ZQXBEFgrJDWFpLOs9im+tsEoxgkoO77dL0Gu5LjKY6yLNxFjrceTsxtkYFDl35+Dctx+8x6ZmjX7tNQKvmNDm93QhjL9vvvkmPXr0IDg4mDVr1vC3v/2N2267jTfffPO4x3/99dfcdtttzQIagD59+jB8+HBeeeWV45733HPP8fzzzx/z8/O5b4S2qa2t5bvvvqOkpASFQsGoUaMYMGDARbFPSPZ6KXnmGep+/AmAyOeexXz99S0eb7VaWbJkCVu2bAF8K0EGDx5M//79L5rlgkfySl6mLZrG2pK1JAYm8u3l3+KnOf0sZm2xZcsW5s6diyRJREREcP3115/SfplDahw1PLX6KVYU+tJm65V6HJIDjVdD//L+hDl8S+MiIyNJT08nPT2d4ODgEz3leeOCCYLaulb7aBfCRfhCUlhYyBdffIHT6SQxMZFrr72WzMxMVq9e3ZQlxmg0MmDAAHr16nXSZXPnNUsp7FsGeYt9S+gamhe8JDAekkdQEz+Ef8kpfFHj+/Dop1QQodOw335sXaITkmWCPBYinRVEuqqIclYQ6fIFOoe+RzkrCXXXoKR1v5b1KiOlulBKtKFsM6WxImEiYVFp9Ao00iPAj3R/wynNYFiWLKXspZdwN6ZJVUV0prbHFSwNLcbu9mVMuv7665vV5wHw1Dqp/CwLT5lvZuWrBDV7O3m4132Qfavm8ZY+ksJaXzIFd3oQV6tX8tbuV1A1m4eBihAtWR1N+Nm89N5ai1KGetlAnhyDHBBDUqI/35WtYhcaHMZQnh37MdHhXUChwClJfFpYyb8PllLv8T1vgFrZ9OdDDG4nsdXlxDSmrvZ3+oJKk8lEfHw8cXFx1OQq2LvGigIF8enBXHZ7OnrjqV/gLR4vX5dUke5vYECQP8rGonVbt91CTc1aIiOvIr3T6wC4Couo+vgD9Ps/xZzk+92zWSOpGzGNnbr/ggK6dptBrrIb35fWMKeiloYjEjb0CzRyXWQwV4QHEdC4fFJyOnHm5eHM2Y1jdw7O3bk4c3JI+PILdB3afmfzXI2/Tz75ZIvByCG7du0i7agitACffvopd999N1ar9bjj16kGQWIm6NLgdruZO3cu27dvByA9PZ0rr7yy6YbhhUyWJMr+9TI1X34JQPgTTxBy259OeE5xcTHz589vSohkNpsZPXo0aWlpF0VweKQqexWT50ym3F7O5UmX8/Kgl/+Q9+j1elm4cCEbNvgK2Hfq1IlJkyad1v+5zWWbeXzF45TbytEqtTzR5wlGJYzigSUPkFmRiVqhZhzj0B/QI0mHryvR0dF07tyZ9PT0s1bo9Ey4YIKgtqzVPh4RBJ15BQUFfPHFF7hcrmaVhQMCAhg4cCA9evS4+O70SBKUZcHexb6Zovx14D0iyFEosUZ2Z5Z/d741dmdbQBp6lYaGxlpKOslJhLOaSFcF0c5Kusi1pEo1JLirCHNWYrSVobaWovAcP6HC0dwKFWXaUEp0oU3fS7WhlOpCqdCF4vKPRGGKIsAvkDCthnCtmji9hsDGPS5HDsuKI/52aLxuadhWFxcT9J83MaxeBYAnIoL6+x8k0JlMUFYNFuwsCMimzlWHQqkiZcQoojodrkWgQIHS6SVoUSHmbN/eoXwDbJC3UEsNa+NC2FdViLt6CDIy7owQEuP9eTTQTne5Cv3u9eSvnI0fDeiivRR1h8gyO2l5DcfZndWcrNahCIyDwFgIjKUyIInXtRl87gpGQoGfSsmAIH9fQgOziTSjnt+Lyvj3xkx0VeVE1VURYa0DuXmwpFZrUNn8UTkDCPIL44o7BhDV7szdDauqWsm27X9CodDSv98iDIbGhBmWUpg5FQrWIwOVWUFUZhkABc72EoY/XUbKtf9tugg3eL0sqKhjZmkNK2osTWG0XqlgbGggkyODGWI2oT5qNuvQ7/epXMzP1fhbUVHRtC+hJUlJScf9kJCdnU3nzp3JyckhNTX1mMdPdTnc0cS16eIlyzIbN25kwYIFSJJEeHg41157bavrlJ3PZFmm4s1/U/XxxwCEPnA/offee8LxQZZlduzYwe+//47FYgF8v39jx469KPrkSJvLNnPHwjvwyl6e7f8s16Zce1Zfz2az8f3337N//34Ahg8fzpAhQ045+JJkiU92fMK7297FK3tpF9CO14e+Tmqwbyx0eBz8fdXf+f3g7wDc0/ke+sp9yc7O5sCBAxwZMsTFxTXNEJlMptN8p2fWBRMEtWWt9vGIC83ZcfDgQb788kvcbjdBQUEMHjyYbt26XTqVo10Nvj1Eh/YTVe5u9nC92p9M/w6Y3fXEuCoJcte1/rkNwRAQDaZIMEUhG8KoW7EFy5pM3DYVni79KHzyJQr0RoocLgqdbgodLoocLkqc7qPmTM4MjdvN5EVzuWX+LHRuNx6lipmjLueL8Vfh0OlBlpmS7+ah3U5k2cMcwy6qZd8+oW2xyaxPSkc+alAeVO7hH9kOwlwyEjIbjOWsm9ST8vIZrN0o467tg6wAd88QRqeG82F6O3RKJVVFBcx+7UVqSorwj/CQcmUJnXKKiahw4dIF8YFzLAZPPcnaStL1maicbkKOs8TrkHxdJJVaM531KrTJw6DDZRDfH9S+WYAat4cncwuZXV6L2uthgMfODWoX1pJiCgoKcLmOmvGTFYSYw0jp2J74+Hji4+NPeS+cLEts3DgJizWbuLjbSOnwlO+Bgo0w8xawlIAuEK75GJepK7n/dyPKxSUoPL6+NnTvTui992IcNLDZRbHY4eLHshpmllY31b0CiNCquTrCzOTIYDr6n/4S1gtx/P3qq6+YOnUqlZWVx11KcigxwjfffMM111wDwO7du0lLSxOJEYRmDh48yPfff4/VakWlUjF48GAGDRp0UVwnKz/4gIq3/gNA8B23E/7ooyf94O10Olm1ahVr1qzB6/WiUCjo06cPw4YNuzCWzLfSJzs+4a0tb6FVavnq8q9ICz52xvlMKCsr45tvvqG2thatVstVV11Fx44dT/n5Ku2V/H3l31lbshaAy5Mu5+l+T2PUNL9+SbLEvzf/m+nZ0wG4Kvkqnu7/NE6bk507d5KVlUV+fn6zcxISEujcuTOdOnU6L/aGXxBBUFvXaoNYcvBHqqiooLq6muTk5FNKUXhRqS1ozDrXuJ/IUXvsMWo9mKJ8XwFRR/052vfdPxI0x09bXPvjj5S+8E9kpxN1VBSxb/0bQ7duzY5xSzIlThdFjYHRoa8ihxtb45T1kb/R8hHL6uSjvh86NmXHNq6e8SHhpb5Mens6deGHW++iLCau+aI8GTqWu5i2vg6jS2K1fj85+O5OVYdFkdO9P16N7867CgWp/no6bN9Kl0wXHSRf4TZvqB7T1bFcsX4yZfvG47F0RVYpcPUKZUhiCJ92aYdRpcJpa+DX/77Ovi0b0Qa46HJVOX0yD+LnkKiP68+48scoqnMQoG3g1q4fMN9pRWO3MNAYz2MpN6BrqIC6Qt9XbYEvU96RMzwaIyQN9SXESL4MzAnMKqvhidwC6j0SBqWSZ5OjuSXSTHl5Ofn5+RzYf5C83ftwy8fO5oWEhDQFRPHx8QQHB7fqTl1p2Ryysx9EpfJnQP+laLXBsHkG/PqobyYyLA2u/xpC2lNY9DW7dz+Nuk5L0vYJNPz0G3JjgKbv1pWw++7DOHhws9eVZZntFjszS6v5ubymWVHdLv4GJkcGMykiiDDtqc3snu8f9NeuXcv69esZPnw4JpOJtWvX8tBDDzFu3DhmzJgB+PZCjhw5ks8//5w+ffoAvhTZv/76K9OnTycgIIAHHngAgDVr1rT6tc/3vhHOjPr6eubOnduUPjosLIyJEyces1T4QlQ9YwZlL/8fAOYbbyDiqadQtGJ5dXV1Nb/99hs5OTkA+Pn5MWLECHr06HFRpNSWZIkHljzAisIVxJvi+W7Cd/hrT16bpy127drFTz/91HQj+oYbbjitjG3rS9bz5MonqbRXolfp+XvfvzMpedIJr1Pf5nzLyxteRpIl+kf1541hb2DS+mZ86uvryc7OJjs7m8LCwqZzFAoFiYmJdO7cmbS0NPz8/th9U4ecsyDobK7VBrH5VDgPSF4o3gaVueAf5gtwTJFgMB+3xlBbOHJyKPrrg7gOHgSNhojHHsN8y81nZd2xu6yMsv/7PyzzFwCgCgsl4vEnCJhw+Qlfz1Nlp/LznXjKbOxTl7NCuwuP5CE0NJQbbrihqTDu7t27+eabbwAwJg/jslw1oS4ZlJDfuZ777M9iL70VhyUJNEqcvUPpHRvEl12TCFCrkCWJNd9/xbqfvkPt56b32EL65RSilKGq75+5JXcSO0vq0Sqd3NRtNr9Le6lz1dE3qi/vjnwXneqIMcRW7Qti9yyCvEXQUN78TYWmQPIoKhOG8RdbLEvqfQVpRwSb+HdaPBE6X5Dg9Uos/2EHW9fuxK2tB38rDslyTB8ZjcZmQVFkZOQxNxIkycW69WOw2/NJSnyIxLi7YMETsOlT3wEdr4BJ74POREPDXjZsnIgkOejQ4Sni427DXV5O9SefUPPtd8iNN4b0XbsSeu80/IcOPebf0CVJLK7ypdv+vaoed+PQr1bAW2nxXBvZ9iV+5/sH/S1btnDvvfeSk5PTtM/xlltu4eGHH266xhw4cIDExESWLl3KsGHDgMPFUr/55ptmxVIjIyNb/drne98IZ44sy2RnZ/Prr79is9kA6Nu3LyNGjLiw980CNTNnUvrscyDLBE6aRNSL/0TRipkut9vNvHnzyMzMbNpT4ufnR9euXenQoQPBwcEEBgZesEFRraOW6+ZeR2lDKaMTRvP60NfPyHVakiRWrFjBsmXLAEhMTOS666475WDCK3n5IPMDPtz+ITIy7QPb8/rQ10k2J7fq/OUFy3lsxWPYPXY6mDvw3sj3iDQ2Hwdra2vJzs4mKyurqV4kgFKppH17X5a5tLS0P7TA7jkLgs7mWm0QM0HCxc9rtVLyj6ewLFwIgGnsWKJe/CeqVlSBbg3Z7ab6iy+pfOcdJJsNlErMN99E2AMPoGrlul7J6aH6u1wcO6uoVNSzyD8bq9uGXq/nuuuuIzQ0lA8++AC73e5Lnz7qMq5Zk8ONWy2MLfVlPCs2VPCv8OmUWG6hrNoPdEqcfcLoEmHim67tm1KD71m/hvnvvokkNzByYC5dSiuRFFBx5b94dHMPVu6pRoHELf2qWdjwHjaPjRFxI3hj2Buolce5WEuSLzPgnt99STEK1oN8eIZE1vhRENmX/+m7stDcF0tAPK+mxDEhPKjpmH1bK1g0YyduhxeDWUnn8UHUOyvJz8+nqKgI71HL8zQaDbGxsU1BUUJCAqWl37I791m02lAGdP4W1Y93+9qCAkY8BYMfAYUCSXKxafO1WCzZBJsHkZHxGYojCqh6Kiqo+uRTar79Ftnhm6XSp6cTet+9+A8fftwLc5XLw+zyGr4vrWGrxcbavh1J9Gv7hzXxQb9lom8uPTabjYULFzYlTQgMDGTChAl0OIWkI+eTujlzKH7yb+D1Yho7lphXX0HRwqZ8WZbJyspi0aJFTZlkW6JSqTCbzYSEhBAcHNzsu8lkOu8DpO0V2/nT/D/hkT38ve/fuSHthtN6PqfTyc8//8yuXbsAXyA9evToU16JU24r58mVT7KxdCMAV3e4mif7PIlB3balidlV2dy/+H4q7ZWEGcJ4d+S7dAw5/rK8qqqqphmisrKypp+rVCqSk5Pp3LkzKSkpZ/3mwAWxHO5oJ1urfTziQiNcjGRZpuaLLyl77TVwu9EmJBDz9n/Qt3BzoLVsmzZR+vwLOPf46hQZMjKIfPYZ9KewzliWZOoX52NZnI8NJ4sDdlLmqkahUGA2m6muriYqKoo77rgDtVpNpsXGxC17GFDs4oXdbvQOL168zAxZym+KweypdKLwU2PvE0qK2cj3Ge2bZmAq8w8w+/WXqKsqZHK37cTaGnDolFRNfouXVur5NccXIF7ZS89K2xO4ZScT20/knwP/iVJxkgupvbYxS2DjLJGlpNnDew2xLA3ug7v9SG7qP4kAg++1akob+PX9HdSW2VCqFQy9IZVOA6Nxu92UlJSQn5/f9OVwNF9CFxAQQHT0KkJCM+lmnkr40q/AWtq4/+d/kHK4WGHe3tc5ePB91Oogeveeg0JjxuV14fQ6cXqduLwu398ry1F8/Qua2YtQNNa3ciRFUzp5MBW9EnHJ7qbzjjy/yqPhkW43nVLdCzH+tkz0zaUrLy+PuXPnUltbC0DXrl0ZM2bMebFX4lTV//47RQ8/Am43/sOGEfOft1Ae9UG2sLCQhQsXNmWKCwgIYOTIkZhMJoqLi8nMzGwqrn4yarWa4ODgY4Kj4OBgTCbTeZN57vPsz3lt02uolWq+HPcl6aHpJz/pOGpqavj2228pKytDqVQyYcIEevToccrtWl20mr+v+jvVjmoMagPP9H+GCUltL4NwSIm1hHsX30tebR4GtYHXh77OkNghJzynoqKiaYao8oh6fWq1mpSUFNLT00lJSTkribbO+yCoNWu1W0NcaISLmX37dgoffAhPSQkKnY7IZ54mqHGzdlt4Kispf+116mbPBkAVFET4Y48SeNVVrVrjfSK2HRXUzMzF7Xazxn8PuR5fWm2tVss999zTrK7AtyVVPJhTgNkl8WOxmoDdvjuFpcY63lYbWVFnQ2nSYOsVSrtAPTO7tSfe4LvQOqxW5r39KsXZ67ktbRP+Xg8VwVosE57l7SV7+TnPl3q7XwcVu9T/QMLFTR1v4oneT7T+ginLUJYNeb5ZIjl/LQrJ0/SwQ6nFHtcfc8dxkHwZLr8EFs3Yxf7tvgG+46AIul8Vg01uwOqyYnFZqHfWU1lZSWVxJZZyC44yB7KrcSmaysI471oy2EmZwcRbKX3I12iaApVwRS03BZSiUMD0KgPbbCd/HyabzBXrJcZultH7VvVxIBx+HKhkQ6rimAQWAB+M+oCBMQNb10dHEONvy0TfXNpcLhdLlixh/fr1yLKMn58fY8eOpUuXLufNB/i2sq5cSeH9DyA7nfj170fcO++gNBqpq6tj8eLFZGZmAr6Z70GDBtG/f/9jVv0cnVLb39+flJQU1Go1NTU1VFdXU1NT0ywt89E0Gs1xg6Pg4GD8/f3/0P6VZZkHlz7IkoIlxPjH8N2E7wjUtS119IEDB5g5cyY2mw2j0ciUKVOIj48/pfa4JTfvbn2XT7I+ASDVnMrrQ1+nXWC7U3q+I1lcFh5a9hDrS9ajVCj5R99/MDl18knPk2WZsrKypoCopqam6TGtVktqairp6ekkJyefsaQi530Q1Jq12q0hLjTCxc5TU0PxE0/QsGIlAIFXXUXkM0+jbEW2Hdnrpea776j491tIFgsoFARddx1hDz2I+jSKrB3NVWyl6vOdeGodZOkK2RNQzujLxx5379/juwv4vLiKILWKb2QJ3cJiArz+SAqYqfHwvsuGwqzD2iOYaKOOmRntSfbzrSWWJC+rvv2Cgws+48ak7aiQyU0yUtepH7/u0vH5zhvxyko6RMmUmJ5HoXIwrds07s249+R9JcvYPXasbl/wYnFZsDeUozu4FtWB9YQX7yDKVd/snHKdH5tNZpar9axUKajXnrx2lFJSklyfREZtB7yyb523XlHL+uDd5JkKm/KAGxQyj0U6CFbLrLOq+Lam+bioVCjRqXToVDq0Kq3vu1Lb9Ocgu5Ley8votqIQrcO3PK8uNoi8Sd2p6peCVqNrOn9Y3DBi/GNO2vajifG3ZaJvBPDNjvzyyy9NMyAdOnTg8ssvb5Z+/ULSsGEDhfdMQ7LZUPfoQcGtU1mzcSOexsLO3bp1Y+TIkSf8P3+ylNper5e6ujqqqqqorq5u9r22tpYTfWzVarXHDZBCQkLw8/M7KwFSvaueyXMmU2QtYnjccP4z/D+tfp2NGzcyf/58JEkiKiqK66+//pTr75Q2lPLY8sfYVrENgCmpU3is92PN98eeJrfXzfNrn2f2Xt8N1dvSb+PBng+efMVFI1mWKSkpISsri+zs7GZLJnU6HWlpaXTu3JmkpKTTSsh13gdBZ4q40AiXAlmSqProIyre/i9IErqUFGL+8xa6xMQWz7FnZlL6/As4srMB0HfqRORzz2Lo2vWstNFrdVH1VQ6u/XWggICR8ZhGxKM4qi6NU5KYtCWPrRYbnf0NjLPNI2aVmkGW7gDkKST+KdsoDNdR181MqE7DzIz2dDoipXPO6uUUf/04I8JykBSwuVsg9QE6sio78GHW/dhcMhFBXqyhr6LU1HF96vWY9eam4ObIQOfQ360uKx7ZQ4tkmfZuNwPtDgbb7PR0ODlyEt8FbNbrWeWnZ43eRJUxmEC/QExaE/4af/y1/gRoA9BVb+L6neuIsclsIIMVqgG4vL7B3hBoIKlHErEdYvGUfIirbiVqbRTt0j9Bpw1sFvQcd7/T8f5damupmjGDmi++RGoseKxNbk/otGkEjB2L4g+40FyKRN8Ih3g8HtasWcPy5cvxer1otVpGjhxJ7969z/t9L8dj27aNFc89z/aUDtgbN+zHx8czZswYYmJafzPleCm1+/bty9ChQ1tMqe3xeKitrT0mOKqurm5aftgSnU5HQkICkyZNOuNZy7Irs7ll/i24JTeP9XqMqelTT3h8XV0dy5cvZ8uWLQB07tyZK6+88pSXhi0rWMZTq5+izlmHv8af5wY8x5h2Y07puU5GlmU+zPyQd7e9C8DohNG8NOgl9Oq2JT6QZZnCwsKmPUSHAmIAg8FAx44dGTFiBP6nsB9aBEGCcBFqWLeeokcfxVtZidLPj6iXXiRg3Lhmx3hrayl/89/Ufv89yDJKk4mwB/+K+frrT+sDb2vIXonaOftoWOfbV6NLMRM8JRWVsfnAXuRwMXpTLlVuD1eFasjKuoduFe15pOpPaJwq3Mh8hpNZ0RoqOgcSqFHzTdckegQeXlNfvn8vlo8m0l5XiF2nZEOPIDwaJXWKK/i/NRMotzjxN3iRIt9BpW++z+dEVAoV/lp//DW+oMVf649JY/J915oo92j5rdqN5IEBDSXc4S6gR1U2uqP2EtV7w3DFDiNkyCQU7QbhLFqFc8d0dLsWo3NJSDojymtn4IwfwoYNG1i9enXT3qHgYD0RkQsIDS2mV8/vCAzsfqr/JE28dXVUf/4F1Z9/7psVBLRJSdhuu520SVei0bR9GYIYf1sm+kY4WkVFBXPmzGmqsRIbG8vEiRMvqIKi+fn5LFiwgOJiX0kFo9VKr7IyBr3xBppTfB/V1dUsXLiQ3bt99fj8/PwYOXIk3bt3b1OQ6PF4qKmpOe4MUn394Vn8jh07Mnny5DM+K/Rtzre8tP4l1Ao1n439jIzwjGaPe71ecnNz2bJlC3l5eU0zWqNGjWLgwIGn1B63182/t/ybL3Z+AUB6SDqvDX2NONPZT9E+Z+8cnlnzDB7JQ0ZYBm+PeBuz/tRWmEiSREFBAVlZWezcuZOGhgY0Gg2PPfbYcROpnYwIggThIuUuL6f44UewbdoEgPnmm4l4/DFQq6mbNYvy19/A27jmNvDKKwl/7FHUoaF/aBsbNpdR+3MesltCFagj+KY0dPHNfz9X1ViYvG0vEnC9YROLd/+HeGUMn3hfwZPju2Dl4OW/MSrWp/tjVKv4vEsiA82HM9jZKgrxvjsAE3VUmLVkdjYhoyC2w1c88IOTPeVWdBqZ/t2zSI72NM3KmLSmFv9sUBtOejGqdHl4dHc+Cyp97ewX4Me7ES5iClYg5f6GvH81Kg4vjZNpWuUGgN1kwvCn5RDSvulnDoeD9evXs2bNapxO37nmYBVjRl9HamrqGblgN3i8bCkqo+qLL4if9T2GhgYAPI88Spc772jz84nxt2Wib4TjkSSJzZs38/vvv+NyuS6YIqu1tbX8/vvvZDeuLNBqtQxITyfy328hl5aiSYgn4bPP0ERHn/Jr5OXlsWDBgqZN9FFRUYwbN67N+2Mkmw3nnj04cnbj3J2DI2c3DXv2UO7nx4qhQ5CVSkZHRdH3pptR+Z+5ZBWyLPP4isdZcGABkcZIvp/wPUH6IKqqqti6dSvbtm3D2jgbD74Co0OGDKF9+/YneNaWFVoKeWz5Y2RVZQFwc8ebebjnw2hUZz7RQEs2lm7kr0v/isVlId4Uz3uj3iMhIOG0ntPr9XLw4EFqamro2bPnKT2HCIIE4SImezxU/Odtqj7+GPDVh1GoVNi3bgVA1yGZyGeewa9373PWRndpA1Vf7sJTaQeVgqDxiRgHRDf7MP/OwTJe3FeCBon0mucpsuzj5rSbuV97GxWz9qB2SbiQ+T5Mydvd/NBoVPyvcyKjQg7/rkuFW+GTUShlD7vj/Slsp0elDKBzxq/c990B1u+vRqVU8MyETkztn3DG7v7Jssw3pdU8vaeIBq+EUang7ZB6hhX/gCL3NwyVxbT0SnJUNxTD/wEdRjerLSXLXtatv5WdO22UFKfj8fhm7qKjoxk2bBgdOnRoU/vLnG7W1zWwsc7K+roGsq12vI0jvtFu46qlCxi/bgWuz79kbGJsm/tAjL8tE30jnEhdXR3z5s0774usHr1kDaBHjx5Ny5RcBQXk/+k23EVFqKOjSPjsM7QJp/4h2Ov1smHDBpYtW9ZUDqVLly5cdtllx/weybKMp7QUR04Ozt27fUFPTo6vzt5xPtoqNBqyU1PZ0TkdjcvF2OUriB4xgqApUzB0PrWsbkezuqxcP+96CmoLGKEfQTdnNw4cOND0uNFoJCMjg+7duxN6GjcnfzvwG8+teQ6L20KANoAXB77I8PjhZ+AdtN2+2n3cu/heiqxFBOmCeHvE23QPP/3VC6dDBEGCcAmwLF1K8ZN/Q2rcXKj08yP0/vsJvuVmFGch7WRbSQ4PNT/uwb7Dd2fP0C0M89XJKHW+O56yLPPn7APMq6gjwrMLqfhfqBVqfrzyRxIUMWR/toPgEjsAew0KnuhhoMik5r1OCVxxRN0eNn4C8x7GKyvY0DEIW7gKjTqSbt2/4rlfa5m11Zex7tqesbw4qTN6zRlaFuh2ULJrLvs2fUKnsm2YnbZmD1v91JToYim1pKO2m8mIK8RQsRa8jbXOorvD0CcgZSwoFBw4+CF7976KSmWkS+fv2bq1gPXr1+N2+9K8xcbGMnz4cJKSko4JhiRZJs/mZENdA+vrrGyobeCg49hEDbF6DX0D/ekTaKRPoJEUg/aUN6CK8bdlom+Ekzmfi6xKksS2bdtYsmRJ0+xFu3btGDNmDFFRUc2OdZeWkv+n23AdOIAqLJSETz9Fd5q1kaxWK0uWLGnaM6PRaBiQlkYXScazJxdnzm6cu3fjbaEWkSo0FH1qKrq0VPRpaehSU9ElJuKur+fTjz6i1OkkvKyMYUuXocBXWy1oymQCL78c5WmkMi8rK2Px2sVkZWahlQ4v40pOTqZHjx6kpqae1oZ/p9fJaxtf47vd3wHQLawbrw15jSj/qJOceXZV2it5YPEDZFVloVVqeWnQS4xNHHvO2iOCIEG4RLgKiyj75z9RBQUR9tCDaNpQ1f6PIMsy1tXF1P26HyQZdZiBkJs7oonwXWgsHi/jN+eyx+akXc3bNFg2MiR2CO+OfBdZlpn/bRaJ22swocCtgPc66PimnYY3OiYwJSr40IvAD7dD9k9YJC3ruppRBntRKYLo2esrvt2q5eX5u5Bk6BYbyAe39CQqsG0F45rUF+PKnol31/doi3ahOqIwqlcBFUF+bA3tiLHLzQxMvxFbHSz4cAflBy0oFDBwfCBddT+j2Pg/cDcGTZFdqR9wI5uq/oMsu+mY9grR0dcC0NDQwOrVq9mwYUNTBqb4+HgGDR1KXWgk62utbKhrYGNdAzWe5kValUAnf0NTwNMn0Ei0vu3rq1vsCjH+tkj0jdBa51uR1f3797Nw4UJKS0sBCA4OZvTo0SdcluuprCT/9jtw5uaiCgoi7pP/YUg/tdkVT2Vl01K2gtxcVnu9VDRujve3WMjYuo3o4saZdpUKXVIiutQ09GmpTd/VYWEtPn9VVRUffPABbrebfg4n7ebNQ2680aT08yPgiiswT5mMvlOnVrXX6XSSnZ3Nli1bKCwsbPq5TWUj35TPfZffx+AOg0+pL450sP4gjy5/lJzqHABu73w793e/H43y3N/wBLB77Dyx4gmWFiwF4MEeD3J759vPSUp4EQQJgnBecR6sp/qrXXjrXSg0SszXdMAvw7eRNrfBwbjNuTgcRYSU/h1Z9jSrXfPenJ2ErS6lf2M+tsxAJc93MXB3Rhy3xzZe7Bz18NFQqN7HQW8AO7r4Ywh1gaQno/uHZFel8Jdvt1FrcxPqr+P9m3vQu13wcdvajCQhF23GlfUF7PkNXXXzBAgOrZK6iFC87YdRnnQjfy2JYLfNNwNzS3QIz7WPRifDym9z2bnad67WoCYiwkVX3c/EWX4A7GzoEYTNT02Yritd+v1wTBKLoppa5i5bTsmOTJB8wU5RYCgb26VRGuRbVmFQKugR4At2+gYZ6RlgxKRu+a5jg9PDst0VXN711O4iivG3ZaJvhLY610VWq6ur+e2338jJ8X3I1ul0DB06lD59+rRqv5K3tpb8O+/CsWMHSpOJuA8/xK9Hy8uiZLcb5/79jUvZcnDm7MaxezfeIwprgm9P5cGEBDK7Z2DX+zKQxfv7c9nAgcT06HFM0dbW2LRpE3PnzkWlUvHnG25Au2IltTNn4jpi6Zq+SxfMUyYTMH48yqOyycmyTHFxMVu2bGHHjh24XL4xX6lUkpqaSvfu3fms9DPm7p9LmCGM76/4nhBDSJvbeci8ffN4Ye0L2Dw2zDoz/xr8LwbFDDrl5ztbvJKX1ze9zpe7vgTgupTr+Hvfv7c6m+mZIoIgQRDOO16ri+pvd+PMqwXA2C+KoAlJKNRKfimv5a7sAxhrvsbPMp+kwCR+nPgjaqUaWZZ5dnYWVetKeAA9/ihwKOH9DjraDYvngcTG2a+S7cj/uwyF18kmZThF7XX4R/mW02k0wWgN3Zi3O4w1+TEUWeN46ooMbu53nPXrjjqkvN9wZX2Nev9a1E5700MyUG9SY41JQpE6gaCUW/AzJh0+1Svx8v4SPiqoQAbaGbS80zGBXoFGslcWseqHPDzOwzM2ekU9KX3ewJVQjM7ppe/mWuwksT/6TjJjR5FjgLUqNzsbkyX4Oe10z8+lU8lBVLKvoKA2OpY+Q4YwNKUDGmXr7rptOlDNwzO3k19t4+s/92VActvXp4vxt2Wib4RT4XQ6Wbp06R9aZNXhcLBixQrWr1/flKq6V69eDBs2rM0BmNdqpeCee7Bv2ozCz4+4997F2K8f3traZokKHLtzcO3Ja5qBaUahQJuQgC7t0OyOb0mb12xm1apVrF27Fq/Xi1KppE+fPgwbNgy9vu3pmb/++mv27NlDZGQkf/7zn1GpVNjWb6B25nfU/74IDs0O+fsTOPEKgqZMQY6PJzMzky1btlBWVtb0fMHBwfTo0YNu3bphMvmS99jcNm6YdwP76vbRL6ofH4z6AJWybUvh7B47/7fh//hpz08A9IzoySuDXyHCGNGm5/mjfbXrK17Z8AoyMgNjBvLG0Dcwav6YYB5EECQIwnlKlmTqFx3EssRXMVwT60/IjR1RB+t5Pq+IDw4eIKT4URSSlb/1+Rs3drwRAEmSeWjmNtZuK+HvCgO9ZN+dpW1BKvaPjub+7o1JDxr3B0kKWBbcjmqtmsDEOpTq5kOd26tmf308GkMGl/ccQ6gcjDJvCZ6dP6AtyUFxxNDoUSmoDjbgSOiGrtMUzLFXotWeeBZpVY2Fv+7Kp8jpRgn8JSGCh9tFoPJCbYWNmhIbNaUN1NQtRxX5TwD8NnSjh20tOqVvmVyVO45NDZPJc/SnxqjBHqTBL1xPdIyJ5HA1VUU7yNyxvam6enJyMsOHDz9hrQ6nx8u/f9/Dhyv2IssQE2Tg31My6JPYilmxo4jxt2Wib4TT8UcUWfV6vWzZsoWlS5c27Ulq3749Y8aMOa203ZLdTuH9D9CwejUKrRZVSAiekuOXKVAajY1BzuGlbLoOHY6ZeTlSVVUVCxcubEoqYTQaGTlyJBkZGW1KqW2xWHjvvfew2+0MHjyYkSNHNj3mqaqibtYsamZ+jys/n4qwMPa1T6IwPh5v42uoVCo6depEjx49aNeu3XGD1LyaPG789UbsHjv3ZtzLtG7TWt2+vbV7eXT5o+TV5qFAwd3d7uburnf/4bMqp2pJ/hKeWPEEDq+DVHMq74589w8L3kQQJAjCec2+u5qa73Yj2TwoDGqCp6SiSTEzeftethT8jKlmBgHaQH69eh6BOl8FbbdX4u4vNrMkp5zr1DqmoUfrkXEoYVPvYK6b2BGVUoH8w20osmfh0CnZ1eN+Vn23E7WxlqjORhL6hGOxbsfjrCKozk1otYvQKhd+DqlZ+xoMKqrDApHaD8GYdjPm0CGo2lh5u87t4R97ivihzJeyvKu/gXc6JRCj17C13saW6kIS82/GT65lPpczx3YriTW1/Kn0RyY2/IwfvhTW1Z5YNlknk+cYgEzzO4lqkwdHYCE1ngJ881SQlJjMqFEjiI5pnq52V0k9D323jZxSX52ga3vG8swVnQjQn9qacjH+tkz0jXC6PB4Pq1evZsWKFWe8yOrevXtZuHBhU5AVGhrK6NGj25yBsiWSy0XRQw9jXby46WeamBjf7M4RCQs0sbEoTvG97NmzhwULFlBVVQX4smiOGzeuTRn2du7cycyZM1EoFNx2223N0nFbrVa2bdvG5jVrqLEdTnoTWFtLclERXbp0JfL6KehTUk74GrPzZvPU6qdQoOCj0R/RL6rfCY+XZZnZe2fzr/X/wu6xE6IP4f+G/N9JzzsfZVVmcf/i+6lyVBHuF857I98jNTj1rL+uCIIEQTjveWocVH21C3ehL/uQaXgczqHRjN6cg/PgE6jdhdyYdiN/6/u3pnMcbi9TP93Ahv3VpBm0vBgYRGSpr8hoQYSOHrd0RufvwfNeT9T15VSF+uO4bCE/v/IiSkc1XROU9EhVoC3chMpzOHuapICaQA1VIVoqg7XYDSq02lACA3sSFNiLwKCemPw7oTyFTahzymt5fHcBNR4vGoUCCRmvJPMIL9ODzeQTz6uq18gIMtM30EifQH8ytG78Nn4E694Fhy8DktMviQPm28i1D6Sm1Iml2tH0Gl6VnQb/fJz6sqaiRCZFBEnh3YiOj+T3WgvTs4vwSDIhRi3/uroLY9JPL4mGGH9bJvpGOFMqKir45ZdfKCjwzZ6fTpHVyspKfvvtt6ZZFIPBwLBhw+jVq9dpZS07HtnjwbJ0KWqzGV1qKiqT6eQntZHH42lKqX1oX07Xrl0ZNWpUq3/vfvrpJzIzMzGbzdx1110UFRWxefNmdu/e3TTLrtFoSO/QgQ7lFWh//hnPEQkQDN27EzRlMgFjx6JsYVnes2ue5ac9PxGsD+aHK34gzO/4iRtsbhsvrnuROfvmANAvqh8vD36ZUMMfW+vvTCqyFnHvonvZV7cPo8bIG0PfaNrve7aIIEgQhAuC7JGonbePhrW+5RK65CD2T4hjytZ5+Jf/HwqFkp8nziIp6PC+m3qHmxs+Wkd2cT0xgQaeTo8maX0Ffl5wqRQEj0/ElFCM4tPLUEoytsTuKGtr0NccaPbaTo2CwoBAPqm7jkXOLsQFl/KnXnVE+e2hvj4LWW6eYlqp1BMQ0I2gwJ4EBvUkMKAHGk3rxp0yp5sHc/JZWu2bhblatYhrPO8jKzSEpn9Hl7CuqI53B9ZRB+s/grXvgKPW97OQZBjyGO6Uq6itcPmW1ZXaqClpoLSkglJHDg5deVMwVOoOZq0UTZ1sINmt4lo/E3FRJoKj/AiKMBLXMRh/c9s3F4vxt2Wib4QzSZIkNm3axKJFi06pyKrdbmf58uVs2LABSZJQKpX07t2boUOH4neCpWcXCqvVyuLFi9naWCtPq9UyZMgQ+vXrd9L+cTgcvPPOO1itVrRabVMwBRATE0OPHj3o3LlzU9pyWZJoWLOW2u++w7JkCTRmCFUGBhJ45UTMkyejS05u/hoeBzf+eiN7avbQK6IXH4/++Jhlbburd/Po8kc5UH8ApULJfRn38ecuf0apOL1Zv/NBnbOOh5Y9xMbSjagUKp7u9zTXpFxz1l5PBEGCIFxQbNvKqflpD7JLQhmg5dcJ0bya8xQ6+xbSw/vz7biPmh1faXUy+YO17KtsoH2YkQdGd0Ax/yA9q30XJHViAOrIzwjd+lmz88pcRvbWhVBIKBl3TSWx0ySckolHZm5jYbZvo+st/RL4x/j2OGzZ1NZtpq5uM7W1m/F4ao9qtQJ/YwqBQY2zRYE90etjWlxOIssy2VY7fp4CDm6/Gkly0CH5H8TH337yDnLUw4bGYMjuW15HcBIMfhS6TgHV4Quq5JXYt7uAmQt+x1Vf2Pja4PSEEVkbj8bbfIPquHu6kJTRckrZlojxt2Wib4Szoa6ujrlz57Jnzx7g5EVWvV4vmzZtYtmyZdjtvgQvKSkpjB49+rSKdZ6vioqKmD9/flOq6uDgYMaMGUNKSsox47LX6yU3N5ctW7aQl5fHoY/DGo2G7t2706NHDyJPUnLCXV5O3U8/UTvze9zFxU0/N/TsiXnKZExjxjRlr9tft5/r516PzWPjzi538pcefwF814Xvc7/nlQ2v4JJchPuF8+qQV+kZ0fOM9cv5wO118+yaZ5tmue7scif3d7//rAR5IggSBOGC4y5roOqrXXjK7chKBU8Pd7Gp+GEUeHlxyNtcmdi8InZRrZ3r3l9DcZ2DLjGB3HN1RxYv3se03Q4MXkCjRAr5DK36FyxhIZA6Do1xGIvfmUNtaQnGIDPX/uOfhMa3Q5Jk3l2axxu/+5aJ9GkXzLs39SDM1Hj3T5aw2fb5gqLaTdTWbcZuP3jMe9BpIxqDop4EBvbE378jyiPu+EmSi02br8NiySLYPJCMjOko2nIRcFpg4/9gzX/B5lsLj7mdLxjqdj2oNJTXO3jix0yW7q7ArLAxIrACk8O39l+hUJCckEZieBfcdSpqShsYfnMagWFtvxssxt+Wib4RzhZZlsnKymL+/PknLLK6Z88eFi5cSGVjyunw8HDGjBlD+/btz0m7/yiSJJGZmcmiRYuaCr0mJyczduxYQkNDqaqqYuvWrWzbtq3pcQCTyYTFYsHPz4/77ruvTZnxZK+XhjVrqPnuO6xLlzXNDqkCAwmcNImgKZPRJSUxf/98Hl/xOADvj3qfjLAMnl/7PAsOLABgcMxgXhr0Ema9+Yz0hSzLyHY7nuoavDXVeKurfX+ursZbc+Sfa5BcLvQpKei7dsHQtSv61FQU2jNXV+5Qe97f/j7vb38fgHGJ43hx4ItoVWf2dUQQJAjCBUlyeqn5aQ/27RU4lHBD97k4bL+i1sWw6trZGNXNl23trbBy3QdrqW5w0TcxmHuv7sTTm/bxaKadHjWNF6IEDcFXdEIX6xsjGmpr+PGlp6nIP4De38Q1f3+ByPa+woSLdpbx4HfbsDo9RAXq+eDmnnSLCzpuW52uSupqG2eK6jZjsWQhy55mx6hUfgQEZDQFRdU1q8jP/x9qdRD9+v6KTneK2XKcVtj0Cax+G2yNdTWC4slM/DO3b0um0g5atZLHx6Ry+8BEyspKWbp0adNeAIVCQUZGBkOGDMFsPrULrhh/Wyb6RjjbWiqyGhgYyMKFC9m7dy8Afn5+jBgxgu7du5/xfT/nM6fTyYoVK1i7dm3TEsCoqCiKioqajjEajWRkZNC9e3cCAwP56KOPqKiooGPHjkyePPmUkkS4y8qo/fFHar//oVlWPL/evQmaMoW3zZuYmfcDQbogTFoTBZYC1Ao1f+3xV6amTz3hzIgsy0j19XgaAxdvdTWemhq81Yf+XH3En33fZaezze8BQKHRoOvUEUOXrhgaAyNNQsIZSZwxO282z615Do/soUd4D/4z/D8E6YNO+3kPEUGQIAgXLFmWaVhXQu3cfeTqbfyl3XMoJAud2t3Dd0PvO+b4rKI6rv9oHVanh1Edw7l7Ykem7tjHmH0OHtjjRNdYlsfQJZSAyxLQhPtht1qY9fJzlOTtRmswcNXjzxLbqTMAeeVW7vpiE/sqGtCqlbx8VReu6Rl70nZ7vXbq6zMbg6JN1NVtweOxHPfYLp3fJTx87Kl30iGuBtj0KdKq/6C0VQBQKIcyyziFMTc/Qkp08wJ9RUVFLF26lLy8PMBX3O/KK6+kW7dubX5pMf62TPSN8Ec5usiqQqFAlmWUSiX9+vVjyJAhba6jczGprKxk4cKFTUsIwTcz1KNHD1JTU5sFhiUlJXz88cdIksRVV111SuPiIbLXi3XlSmq/m4l1+XJoTLLgDQ3i6T9pydNUAxBliOBfyQ/S0R3eODtzOJDx1tY0zdZ4aqrx1tSCx3OCVz0+hVaLKjgYVbAZtTkYVXAw6mAzKnMwKrMZVbAZhUqFI3sn9sxMHJmZeOvqjnkeZWAghs6dMXTrir6LLzBSh5xaEdh1Jet4eOnDWNwW2gW0472R7xEX0PrMficigiBBEC54rgILVV/t4t/+S5hv+gpJaeSxod/yp/h2xxy7bl8Vt366AadH4uruMdwxPoXrM/ehqXXxyH43QwpdvjwBCvDrGUHAqHgkncTPr71IQXYmao2WiY/+g8QM3zrseoebh77dxuIc3zKy2wa24+/jO6JRtX7pmixLNDTsaVxC5wuMHI5CYmJuIi31hTPQQz4r91Tw1MyNjLT9yj3qOYQran0PBMTC4Ieg+y1w1AzawX0HWTLvNwqqirlv2n2ERIhiqWeS6Bvhj3SoyOq6desASEtL47LLLiPkFD+gXoz27t1LVVUVKSkpJ6y3tGLFCpYsWYJOp2PatGlnpDaTu7SU2h9+pPaHH/CUllIaBG9epSK2Sub23yT8HSd9imaURuMxQY3KHIQ6ONgX2ASbfX8ODkZtNqPw82vTDI4sy7gLCrBvz8S+IxNH5g4cO3ciu1zHHKuJjkbfrWvTjJE+PR2lwdCq18mryePexfdS0lCCWWfm7RFvkxGe0ep2tkQEQYIgXBS8DW4qZ+7kap6gXlmE0/8yfhjxT7qaj12vvXhXGXd/sRmPJPOnAe24ZWR7Jm/fS5HTTXuLl2cPSnQqarzaqBT494/GMDCcXz96g31bNqJUqbn8r4+R0teXvlOSZN5alMvbS3yzJv2TQnjnxu6E+Lc9k9ohHo8Vlcp4RpYU2F1eXp6/i8/X+vYmJYYa+ffVqWSUz4ZV/wZrqe9AUzQMegh6TEVyq7CuLcG6pgipwUOdwkbCFV3wHxB9glc6PjH+tkz0jXAulJeX43a7T1gwWTgxr9fLZ599RmFhIe3atWPq1KmnXZfpENnjwbpiJbXffYd1xQpfxhqFAlVg4BFBjbl5INPsz2ZUZnNTsoU/kuxy4cjdg2NHJvbMHdgzM3Ht2+d7D0dSqdB16IChS5fG/UXd0CW3R9HCUswKWwX3Lb6PXdW70Kl0vDz4ZS5LuOy02iqCIEEQLhqyJLN4/i88VPkUMkq0oS+xsNcwwiL8jzl29rYiHvxuG7IMfx3ZgduHJfHmgTI+KarAI0P3Wi8v5EtElfiCIYVWhXFgJKuzfyJn/TIUCiVjpv2V9KGHq4cvyCrlkZnbaHB5iQky8OEtPekcE/iHvf/j2ZpfwyMzt7Ov0ldQ9db+CTw5riMGbeOFxu2ALZ/7giFLMR45BKvyZhpcI5C9vmNUwXpMQ2Iw9oxAoWn7XgEx/rZM9I0gXLiqqqr44IMPcLvdjBkzhv79+5/x1/DW1iJ7vagCA1G0Is35+chrseDIzj48Y7Q9E09FxTHHKfz8MHTqhL5rVwxdfTNG6qioppuBNreNx1c8zvLC5ShQ8EivR5jaaeop3ywUQZAgCBedu3+5hzU1q3Hpu5Kufpgv0hIwph+7jOvztQd4ZnY2AM9M6MTtgxLJbXDwbF6Rr06PLDO2Dp7c78G/3BcMKf3UFOsOsHLrt0iylxG330P3MROanjO3zMJdn2/iQJUNvUbJK9d05cqMP/5uq8sj8d8le3h3aR6SDJEBel69titDUo6f4tpdXItl9ipsB42A70KrUeVjygDDhEkoDK3PgHQ0Mf62TPSNIFzYNm3axNy5c1GpVNx9992nVJz2UuQuK8O+fTuOHTuwZ+7AsWMHUmMWwyOpQkObAiJ9ly5oO3fitV3v8e3ubwGYkjqFJ/s8eUw9pdYQQZAgCBedg/UHufLnSXhlD3Vhj3JrURqPxIYTOLodClXzO0b/XbynKd3169d149qesciyzO9V9TybV8R+uwuFLHN7vYo7cx2oq30ZdNxqN1tLFnHAuoOB199C36smNz1nnc3NX77dyvJc352uu4Yk8fiYVNRt2Cd0OvaUWXho5jayiuoBuDIjmhcmdibQT3PMsc78eizLCnHsrGr6mS7Mhsn9CTr7QhQKwBgOA/8CvW4HbduDITH+tkz0jSBc2GRZ5uuvv2bPnj1ERkby5z//uVWFaYXmZK8X1759viV0OzKxZ2bi3J3blEb8SJrEdiwYZuKjyF1oFBq+HvcVqWEd2/yaIggSBOGi9MamN5iePR2POpqaqJf491YXI/2NhNzQEVXA4VoDsizz4rxdfLJqP0oFvHx1F6b0jgfAKUn8r7CSfx8oxeqVUEkyz1q1jM+2Qr1v42e9q4odNSuJHtWFQTfe2jQt75VkXv9tN+8v86WfHdwhlP/e0J0gvzNb5+BIkiTz6er9vLpwNy6PRJCfhhcndWZC1+b7eGRZxpFbg2VZIa79hzP76NNDMA2NRRcfAB4XbP8aVr4Btfm+A8a9Bn3vanO7xPjbMtE3gnDhs1gsvPfee9jtdgYPHszIkSNPfpJwUpLDgWPnLt/+ou2Z2HfswF1Q0PT4+hQFsgJumb4a9SmUcBBBkCAIFyWLy8KEWROodlRjNd+MWj+aL9Y2EK9SE3JjGrqkoKZjJUnmqdlZfL3e92H/ibFp3DM0qSmgKXe6+de+Er4t9aUqDULBG/U6MrbXINt8aUirnaU0JDnoe++NKI/Y2Dk3s5jHvs/E7vYSF2zgo1t60THqzI9BBdU2Hv1+O+v3+9o4PDWMV67pSnjA4ZS3slfGvqMCy/JC3CW+PUKoFPhlhGMaGosm/DiFUL1u5G3fIG+YgfKOOaAVxVLPJNE3gnBx2LlzJzNnzkShUHDbbbcRHx9/rpt0UfLU1ODIzGyaMfLW1JL4/cxTei4RBAmCcNH6Pvd7Xlj7AkqVP+WRr9LB5c+nq6zoZQgY0w7TkFgUSl+gI8syry3czXuNMzd3Dk7k7+M7NttwubXextN7CtlU71u3nKpS82aNhrANZSi9vuOsunra/Wkg+sSgpvN2ldRz1xebKKi2Y9CoeP26blzeNeqMvEdZlvl+cyEvzNmJ1enBT6viqcs7cUOfuKa2y24vDZvKsKwswlt9KNGDEmOfKPwHx6AObDmDkOTyUv3VLpz76gi9s4tvlqiNxPjbMtE3gnDxmDVrFtu3b8dsNnPPPfegOwfZ2YTWE0GQIAgXLa/kZfLcyeTW5CIHjKYy6BaucKh4ZnktCkDfMZjg61JQHrFX5n8r9/HivF0AXNMjlleu6dJsL48sy/xYVsOLe0sodbkBGGsw8NdtZQTv96JS+NaC69LMBI1NRBPp20NT0+DigW+2siqvEoB7h7XnkdGpqJSnngK70urkbz/t4PedZQD0SjDzxuRuJIT4XlOyubGuK8G6uhipwddWpVGN/4AY/PtHNXvfxyPZ3FROz8aVb0GhURJySyf0KWdvycGlSPSNIFw8HA4H77//PnV1dfTs2ZMrrrjiXDdJOAERBAmCcFHbULKBO367A6VCRU3ki7g0sTyrNXHF/BLwyKiC9YTc1BFtzOE02j9uLuTxHzPxSjKjOkbwzo3d0R+VGrrB4+Xt/HI+KCjHKcmoFDDV7WLM3G0k6VNRKpS+gqsZ4QSMikcdYsDjlXhlQQ4fr9wPwLDUMP4zpftxExaczMLsUv7+0w6qGlxoVAoeviyVu4YkoVIq8NY5sawqomF9KbLLt6lUFaTDNCQWv14RKLUnT3PtrXNS8WkWnjIbCoOa0D+lo0s4tbFTjL8tE30jCBeX/fv3M2PGDABuvPFGUlJSznGLhJaIIEgQhIveX5f8lSUFS4gz92KL/19QKxXMjIkhcdYB3/IwtYKgie0x9o5sWkK2aGcZ9329BadHok9iMP+7tRcB+mODlYN2Jy/sLWZehS/BQIBC5oqVy7im3ES8MdV3kEqBsU8kASPiUZm0zN5WxOM/ZOL0SLQL8eOjqb1IiTC16r3UO9w8/8tOftxSCEBapIk3J2fQKToAd4UNy/JCbFvLwesbsjWRfpiGxmHoGoqildnp3BU2Kj/JwlvrRBmgJeyOzmgiRIrss0H0jSBcfBYsWMC6deswGo3ce++9GI2nPn4KZ48IggRBuOjl1+dz5ewr8Uge0pKfZaUrmUithgXpiahn78exy5dMwK9HOOarkpsKgq7fV8WfZ2zC4vTQKSqAGbf3Icx0/DXeK6stPJ1XRE6Db89NeHU5169exQRtV4KJAEChUeI/MAbT0Fh2Vjdw9xebKaq1Y9SqeGNyBmM7R57wfazZW8lj32dSVGtHoYC7h7Tnocs6oCixYVlWgH1nFTSO1Np2AZiGxaFPNbepkJyr0ELlZ9lIDW7UoQZCb++MOlh/8hNPQIy/LRN9IwgXH7fbzUcffURFRQUdO3Zk8uTJp1zQUzh7RBAkCMIl4c1Nb/JZ9mckBLSjLupl9tg99As0MrNrexyriqhfeABk0MT4E3JzR9Rm3wf/7OI6bv10I5VWJwkhfnx5R1/igo+fIc0jyXxeXMmr+0up9fiWoaXszeLOfcWMihyBt9gOgEKvxjQsFle3EO7/fjvr9vmCsL+M7MCDIzugPGqfkMPt5bWFu/lklW8ZXXywH29c15UubiWWZQU49x2R5rpjMKZhcae0dM2xt5aqz3ciO71oYvwJvS0dlf/pp/QW42/LRN8IwsWppKSEjz/+GEmSmDRpEhkZGee6ScJRRBAkCMIl4ciU2bdnPMy7dT2xeiXujgvj+eQYHHtrqf56F1KDB6WfmuAbO6JPDgLgYFUDN3+ynoJqO+EmHZ/f0Ye0yJbHkWq3h9f2lzKjqBIJUHncDN6zjTe7DUO5oR5PmS+7nNKkwTg8jrcravhk7UEARnUM580pGU1L73YU1vHQzG3klVsBuLF3HI+2C8e9uhh3cWOaa6UCv4wwX5rrU1y2Zs+qpOqbHPDK6NoHEnJLJ5T6M1PwT4y/LRN9IwgXrxUrVrBkyRJ0Oh3Tpk0jKCjoXDdJOIIIggRBuGT8kPsDz699HpPWxENDvuaB3FoAPuiUwKQIM55aB1Vf7MJdZAUFBI5LxH9wDAqFgvJ6B1M/3UBOqYUAvZpP/9SbXu2CT/h6u6x2nty5n/UNvsKqATYLTyVGco09gPpFB/HWOAFQBevJSfbnns0HcHolksKMfHBzTxZklfL24j14JJlofx3vdI4nKrfucJprjRJjn0hfmuugU1+yZt1QQu2sPJDBkB5C8PVpKDSt2z/UGmL8bZnoG0G4eHm9XqZPn05BQQHt2rVj6tSpKJVnbmwVTo8IggRBuGR4JS9T5k5hd81urk+9HsJu47/55fiplPzaswNpRgOy20vNrDxsW8oBMHQLw3xNB5RaFXU2N3fM2MimgzXoNUrev6knw9PCT/iasizz4/5Cnt61nxo/39iToVPxSqdE2u+sp35JPpLVl77aE6LnNZuFeXZ70/n+wBMRIQy3AofSXPup8R8QjbF/NCpj2zPLHdk2y7JC31JAwNgnkqBJyU21k84UMf62TPSNIFzcqquref/993G73YwePZoBAwac6yYJjVo7/oqwVRCEC55KqeLx3o8DvkKq15obGGz2x+aVuGPHAeo9XhQaFebrUgi6sj0oFdi3V1Dx3nY8VXYC/TR8cUdfhqeG4XBL3Pn5Jn7eWnTC11QoFFybFMeagV0Ym7sZjdvFNqeXsVvzeCbYg/rBDALGJKDQq1BXOfibXcMXugAGoOavKgPz1IEML3NDgxtVoI7AK5KIfLIPAaMSTi8AkmTq5u1vCoBMw+MIuqrlAKjB6+UCvxcmCILwhwsODmbMmDEALF68mLKysnPcIqGtRBAkCMJFoU9UH0bGj8Qre3lj02u81zGBGJ2GvXYnt+3Yz9zyWqrcXvz7RxN2ZxeU/hrcpQ2UvbMNR24NBq2Kj6b24qruMXgkmQe/28Znq/ef9HXNQWY+vOV6/r5hHh1ztyEDX5dUM2BLLl+21xPyaE9MQ2NRaJQkOuFV/LjOq0HlkVFH+GG+LoXIx3thGhjTqjo/JyJ7JWq+z8W6yhfABU5IInBMu2bZi+xeiVU1Fl7ZV8LELXtIW5nFPrvztF5XEAThUtSzZ086dOiA1+vlp59+wuPxnOsmCW0glsMJgnDRKKgv4MrZV+KW3Lwz4h0CAntz5ZY9uI4Y5lKNevoH+dNXqyNtQRGmAxZQQMDodpiGxSLL8M95O/ls9QEA/jIimYcuSzlpGlS3w8HsN15iTVklSwZdQWlYNABJBh3PJ0czQqunfkkBtq3laCKNmIbGok8LPmNL1CSXl+qvc3DkVIMSzNemYOwRgUuS2FJvY3WNldW1VjbXN+CUmg/7b6XFcX1USJtfU4y/LRN9IwiXBovFwnvvvYfdbmfQoEGMGjXqXDfpkif2BAmCcEl6c/ObfJb1Ge0C2vHTxJ/Y0eDi+9Ia1tRa2d1Y6+dISV4FGcVOelZ7GRgeQMo1qSi0Kt5dmsfrv+UCcFPfeF64sjOqkwQsHrebef95hT0b15PdsSfrhk6kpnHCfUSwiRc6xJDsd3q1eY5HsrmpnLET18F6vFolRdcmsSlQyeoaKxvqrNiPCnoitGoGmU0MDPJnoNmfeL32lGpdnO/j77Jlyxg+fPhxH9uwYQO9e/c+7mPDhg1j+fLlzX52991388EHH7T6tc/3vhEE4czZuXMnM2fORKFQcNtttxEfH3+um3RJE0GQIAiXJKvLyuWzLqfaUc1jvR5javrUpscqXR7W11lZW2tlTY2VnccJiuIdMgOjghgUGUjpnhpe/zUHWYbLu0Tx5pRu6NQnXrLm9XhY+P5b7Fq1DKdWT/FtDzFb6Y9bllEr4I7YMO6ODSNaf/p1egBcdQ5Wf5vNOtnNplAN20PVWI8a1kM0agaa/ZuCnvYG3Rkp8He+j78ul4vq6upmP3v66adZvHgxe/fubbEPhg0bRkpKCi+88ELTz/z8/Nr0Hs/3vhEE4cyaNWsW27dvx2w2c88996DTHb8At3D2iSBIEIRL1o+5P/Lc2ucwaUzMu3oeZr35uMfVuD2sr21gTa2V1eV17HQ6kY/6YBxR5aZ+SwWyJNM7KZjpt/bGqDtxnR1Zklj86fts/30+AB1uvYeZsZ1YVFXfdEwHPx1Dg00MaZyRMZ4kuDpEkmVyGhysrrGyqryONdUWLOrmbQ5SqxgQ5M+AxsAnzag/K1XNL7Tx1+12ExMTwwMPPMDTTz/d4nHDhg0jIyODt95665Rf60LrG0EQTo/D4eD999+nrq6OHj16MHHixHPdpEuWCIIEQbhkHZkye0rqFJ7q91SrzquusbN47m7Wu11sCVaRE6BCUoCy0oFmWzUKr4w6SMvIMUkMiwxiQFDLS8lkWWbFV5+xac5PAAy47iYaho3nrYNlbKm3IR1xrEahoGeAH8OCTQwJNtHN5Ieq8TllWWaPzcnqWiurayysqbVS7fY2ey1/j0y/YH8GhQUy0OxPur8B5VkIeo52oY2/P/74I5MnT+bgwYPExsa2eNywYcPIzs5GlmUiIyO54oorePrpp/Hz82vxHKfTidN5OMFEfX09cXFxF0zfCIJw+vbv38+MGTMAuOGGG0hNTT3HLbo0iSBIEIRL2sbSjdy+8HaUCiU/XPEDHcwdWnWe7JGonbePhrUlWFWws2sQWRlmluZXs29FEQq3hGRU4+oZAgY1MToN/YP86R/kz4Agf9oZDgdFsiyzftZMVn/3BQA9J1zF0Jtvp87jZVWNlRU1FpZVW8h3uJq1waRSkmjQoVRAgcNF1VFBj59CQbcqDz0rPfRTahg8JR1dwB+/9OJCG3/Hjx8PwK+//nrC4z766CMSEhKIjo4mMzOTJ554gj59+vDTTz+1eM5zzz3H888/f8zPL5S+EQThzFi4cCFr167FaDRy7733YjQaz3WTLjkiCBIE4ZL30NKHWJS/iD6RfXhv1HvoVK0PFBo2lVHz8x7wyKhDDYRM7cROj5s/fbaBGosLjUGNvWcwnqNq+kRqNfQPMvqCosb9N1vn/8LSGR8D0HXkWEb+eRpK5eHlb2trrXxVXMXaWivFTjdHD8oKfMkM+gf5c6VTReqsg2jcMtrEQEJv7YRSf+LleWfLuRp/n3zySV555ZUTHrNr1y7S0tKa/l5YWEhCQgIzZ87kmmuuadPrLVmyhJEjR5KXl0f79u2Pe4yYCRIEAXzLbj/66CMqKipIS0tjypQpZ2U5stAyEQQJgnDJK7AUcOXPvpTZiYGJvDDgBTLCM1p9vqvQQtUXu/DWOVFoVQRPTqE61sgtn6xnX0UDQX4aHrymM2UGBWtrrWyptzVLxw0Q1hi89Ni9hYaZ00GWCGmfgmrkBLZGt2d1bQMHj5oJUgFROg0yUOJ0N1s6p5Jk0uskBio1jB2cSE+zP+ozlGa7rc7V+FtRUUFVVdUJj0lKSkKrPZx84p///Cf//e9/KSoqQqNpWzHahoYG/P39WbBgQVNxxJMR1yZBuHSVlJTw8ccfI0kSkyZNIiMj41w36ZIigiBBEARgReEKnln9DFWOKhQouLnTzTzQ/QEMakOrzvdaXVR/nYNzXx0ApuFxuPtHcvvnm8gsrMPYWGR1YHIodq/E5voGX/a5xqDoyJo8qXk7GL/0R9ReX0G9spAo1vUYyr6kTnQL9CUxGGQ20SvQiJ/Kl1rb4vGyptbKoh0lLG+wkW9sXuPapFIy0OzP0OAAhppNJBpOLd31qbhQxl9Zlmnfvj1XX301r7/+epvPX716NYMGDWL79u107dq1VedcKH0jCMLZsXLlShYvXoxWq2XatGmYzcdP0COceSIIEgRBaFTnrOPVja/yy95fAIgzxfH8gOfpHXn8OjFHk70ydfP3Y11VBIA+1Yx2Unum/bid1XlVaFVK3ro+g/Fdopqd5/BKbLXYmlJyb65vQGmtp9f21fTYuQG12zcDFBQVQ7+rJpM2cCgqdfOlbbIkU7dgP9YVvteuHxrNlq6BrKi1srLaQo2n+X6hWL2GYeYAhgSbGGz2x6w5e0vlLpTxd/HixYwaNeqYJXIARUVFjBw5ks8//5w+ffqwd+9evv76a8aPH09ISAiZmZk89NBDxMbGHlM76EQulL4RBOHskCSJzz77jIKCAhISErj11ltRKpUnP1E4bSIIEgRBOMrKwpU8v/Z5ymxlAExJncJDPR/CqGndxlXbtnJqftyD7JZQhegx3ZDGY8tymZ9VikIBL03qwo19Wy6S55IkchscxOm1aB02tsyfw9YFv+BsaAAgICyCPldeQ/rQUai1WmSvRM2Pe7BtKQcgcHwipiGHs5p5ZZkdFntTgoWNdQ24jxjSFUA3kx9Dg00MNZvoFeiH9gxehC+U8ffGG2/k4MGDrF69+pjHDhw4QGJiIkuXLmXYsGEUFBRw8803k5WVRUNDA3FxcVx11VU89dRTok6QIAhtUl1dzfvvv4/b7Wb06NEMGDDgXDfpkiCCIEEQhOOwuqy8uflNvs/9HoAoYxTP9n+WgTEDW3W+q9hK1Rc78dY4UWiUBFzTgX/tK+ObDfkAPDYmlXuHtW/1kjSnzcb2339l87yfsdXVAmA0B9Nr3CRiKhLx5llBCeZrUjD2jDjhczV4vayrbWB5tYXlNRZ2H1UM1k+lZECQP0PNvlTcKX6nVzRVjL8tE30jCALA5s2bmTNnDiqVirvuuouIiBOP48LpE0GQIAjCCawvWc+za56lyOpbZjYpeRKP9nqUQF3gSc/1Nrip/iYHZ14tAMbBMfxP5eLdZXsBuGNQIv8Y3xFlGxIWuJ0Odiz5nY1zfsRaVQmAVmkgxdybvn++nqAeLc8wtaTE6WJFtS8V9/JqC5VuT7PHo3QahphN3B4bSjdTyzVwWiLG35aJvhEEAXx7Er/55htyc3OJiIjgzjvvRK0+Nxk9LxUiCBIEQTgJm9vGf7f+l692fYWMTJghjKf7Pc3w+OEnPVeWZOoXHsCyvBAAXXIQs5MMvPjbbgCu7h7DK9d2RaNq2/IzV3UDG177muz85Vg9tQBoDX5kjLmcnpdPwi/g5EHa8UiyzK4Gh2+WqNrC+jorjsakDV93TWJESNvHTzH+tkz0jSAIh1gsFt577z3sdjuDBg1i1KhR57pJFzURBAmCILTS1vKtPLP6GQ7UHwBgXOI4nuzzJMH64JOea8usoOaHXGSXhMqsY2WvEP62eDdeSWZkWjjv3NgDg1Z10ucB8FTZqfgkC2+1A/xV1HSrZ/OyX6gq9C21U2t1dB01ll5XXIUpOPSU3y+A3Suxsa6BZdUWHk2MbMpG1xZi/G2Z6BtBEI60c+dOZs6ciUKh4LbbbiM+vu2z+0LriCBIEAShDRweB+9vf5/p2dORZAmzzszf+/6dMe3GnHTfjLu0gcovduKtcoBayfb+YTy8di9Oj0Tvdmb+d2tvAg0nrk3jKrZS+WkWktWNKlhP2B2dUYcYkCWJvM3rWf/TTMr27QFApVaTPnQUva+8lqCIyDPWB20lxt+Wib4RBOFos2bNYvv27ZjNZu655x50utYX8BZaTwRBgiAIpyCrMounVz9NXm0eACPjR/KPvv8gzC/shOdJNjfV3+3GsbsGgD1dgvjLnmIsDg9pkSY+v6MP4Sb9cc917qujckY2stOLJspI6O2dUZm0zY6RZZmDmVtZP2smhbuyAFAolaQNHErfSdcREvvH31UU42/LRN8IgnA0h8PB+++/T11dHT169GDixInnukkXJREECYIgnCK3183HOz7m48yP8cgeArQBPNHnCa5IuuKEs0KyJFO/6CCWJQUAHIwx8GBdDRVWF/HBfnxxRx8SQpqn47bvrKLq6xzwSGjbBRB6azpKw4k3zRbuymL9rJkc2L7F9wOFgg69+9P3qslEJCUfc7zHK9Hg8mJzeWhwemhwen3fXb7vA5NDCTO1/Y6kGH9bJvpGEITjOXDgANOnTwdgypQpdOzY8dw26CIkgiBBEITTtLt6N0+vfppd1bsAGBgzkGf7PUuUf9QJz7NnV1I9MxfZ6aXEX8XDSjsF9Q5C/XV8fnsfOkX7xqqGTWXU/JQLEug7BhNyYxqolTjcElanB5vL0/jd6/veFLz4flZWWs7+3blUVFThVmpwKzQoTWZUAcG4FOqmYMfpkU7Y3i/v6MugDm3fYyTG35aJvhEEoSULFy5k7dq1KBQKBgwYwLBhw9BoTrxkWmg9EQQJgiCcAR7Jw/Ts6by/7X1ckgujxsjDPR/m2pRrUSpaTibgLrdR9cVOPBV2KlUyj/t7yK2zY9KrGZYaTn2xlfqKBmzIOHUq7FolNpeXBpcH6SyNymqlAqNOjb9OjZ9WhVGnxqhT8cjoVHrEm9v8fGL8bZnoG0EQWuJ2u5k9ezZZWb6lzSEhIUycOJGEhIRz3LKLgwiCBEEQzqB9tft4Zs0zbK/YDkCfyD48N+A54kxxLZ4jOTxUz8zFsbMKCzJ/N3nYarG3+jWNWhV+Rwcth36mVeOnUzU+psZfpwK7leLt6ynZsQWNx4FGchMdH0v/8RNI79MbvfbM3mkU42/LRN8IgnAyOTk5zJ07F6vVCkCfPn0YOXKkSJhwmkQQJAiCcIZ5JS9f53zN21vexuF1YFAb+Ev3v3BD2g2olMdPgy1LMpalBdQvOohTllmkk2hwevBDQUhGOKEZEUfMyviCHKNOjUGjalOx1SPVV1awae5P7Fj8Gx6XE4DQuAT6XjWZlP6DULbQ1ja/jhh/WyT6RhCE1rDb7fz2229s3boVgMDAQK644gqSk4/d3ym0jgiCBEEQzpKC+gKeXfssG0s3ApARlsHzA58nKTCpxXPsOdVUf5uD7PCCAszXdMDY6+ymt7bV1bJ53s9s+20eLrtvBsocFU3vK6+l0+DhqNSnNzMkxt+Wib4RBKEt9u7dy5w5c6itrQUgIyODMWPGYDAYzm3DLkAiCBIEQTiLJFnih9wfeHPzmzS4G9AqtdybcS+3pt+KWnn87G7uSjvW5YUYOoegTz15IdYzxWG1snXBHLbM/wWH1QKAKSSM3hOvpvOI0Wi0p7b0Qoy/LRN9IwhCWzmdTpYsWcL69esB8Pf3Z/z48XTq1Okct+zCIoIgQRCEP0CJtYTn1z7P6uLVAHQK6cQ/B/6TFHPKOW7ZsVwOO9t/n8/mubNoqPXVM/ILDOKyux4guVffNj+fGH9bJvpGEIRTlZ+fzy+//EJlZSUAHTt2ZPz48ZhMpnPcsguDCIIEQRD+ILIs88veX3hl4ytYXBbUSjV3dbmLP3f5MxrV+Zf21ONykbX0dzb88gOWygpu/r//EJHYvs3PI8bflom+EQThdLjdblasWMGqVauQZRm9Xs/YsWPp1q3bCevVCSIIEgRB+MNV2Cr457p/srRgKQAdzB3458B/kh6Sfo5bdnxej4eCrO20y+h5SueL8bdlom8EQTgTSkpKmD17NqWlpQAkJyczYcIEgoKCzm3DzmMiCBIEQTgHZFlm4YGF/Gv9v6hx1qBSqLg1/VbuzbgXneriSnsqxt+Wib4RBOFM8Xq9rFmzhmXLluH1etFqtYwaNYpevXqhVLZcr+5S1drxV/ScIAjCGaRQKBibOJafJ/3MuHbj8MpePs36lGt/uZZt5dvOdfMEQRCEC4xKpWLw4MHcc889xMXF4XK5+PXXX5kxYwZVVVXnunkXLDETJAiCcBYtzl/Mi+tepNJeiQIFN3W8iXu63UOgLvBcN+20ifG3ZaJvBEE4GyRJYuPGjSxatAi3241arWb48OH069cPlerM1IC70InlcIIgCOeJOmcdr218jdl7ZwOgVqjpGdGT4fHDGR43nGj/6HPcwlMjxt+Wib4RBOFsqqmpYc6cOezbtw+A6OhoJk6cSGTk2a0/d7bZ7Xb27dtHXV0dAwYMOKXnEEGQIAjCeWZV0Sr+vfnf5NbkNvt5qjmV4fHDGRE3grTgtAsm848Yf1sm+kYQhLNNlmW2bdvGwoULcTgcKJVKBg8ezODBg1Grj1+v7nwjyzKlpaXs2bOHvLw8CgoKkGUZlUrFE088gVarbfNziiBIEAThPFVQX8CSgiUsLVjK1vKtSLLU9FiUMYphccMYHjecXpG90CjPvxTbh4jxt2WibwRB+KNYLBbmzZtHTk4OAGFhYVx55ZXExsae45Ydn91uZ+/eveTl5ZGXl4fVam32eGhoKB06dGDQoEEYjcY2P78IggRBEC4ANY4aVhSuYGnBUtYUr8HusTc9ZtKYGBQ7iBFxIxgUMwh/rf85bOmxxPjbMtE3giD8kWRZZufOnfz66680NDSgUCjo168fw4cPP6XZlDNJkiRKS0vJy8tjz549FBYWcmT4odFoSEpKIjk5meTkZMxm82m9ngiCBEEQLjAOj4P1JetZWrCUpQVLqXZUNz2mVqrpE9mH4XHDGRY3jEjjuV/3Lcbflom+EQThXLDZbCxYsIDMzEwAzGYzEydOJDEx8Q9tx6HZnkPL3BoaGpo9fmi2Jzk5mYSEhDO6fO+cB0EvvfQS8+bNY9u2bWi1Wmpra485Jj8/n2nTprF06VL8/f259dZbefnll9vUEeJCIwjCxcgredlRucO3bC5/KQfqDzR7PD0kneFxwxkeP5wOQR3OyT4iMf62TPSNIAjnUm5uLnPnzqW+vh6Anj17ctlll6HX68/K6/3Rsz0ncs6DoGeffZagoCAKCwv55JNPjgmCvF4vGRkZREZG8tprr1FSUsLUqVO58847+de//tXq1xEXGkEQLgX76/b7Zojyl7K9Yjsyh4fuGP8YhscNZ0T8CLqHd0et/GM2xIrxt2WibwRBONccDgeLFi1i06ZNAJhMJiZMmEBqauoZeX6bzca+fftanO0JCwsjOTmZDh06EB8f/4clazjnQdAh06dP58EHHzwmCJo/fz4TJkyguLiYiIgIAD744AOeeOIJKioqWr1+UVxoBEG41FTaK1lRuIIl+UtYV7IOp9fZ9FigLpAhMUMYHj+cgdED8dP4nbV2iPG3ZaJvBEE4X+zfv59ffvmFmpoaALp06cLYsWPbnHTg0GzPoaDnRLM9HTp0ICgo6Ey+jVZr7fh7zvLnrV27li5dujQFQABjxoxh2rRpZGdn071793PVNEEQhPNaqCGUqztczdUdrsbmtrG2eC1LCpawonAFtc5a5uybw5x9c9AqtfSL7te0jyjUEHqumy4IgiD8wRITE5k2bRrLli1j7dq17Nixg7179zJu3Dg6d+58wuXUNputWSa382W250w4Zy0tLS1tFgABTX8vLS1t8Tyn04nTefiu56G1joIgCJciP40fIxNGMjJhJB7Jw7bybU2JFQosBawoXMGKwhW8sPYFuoR18S2bixtBYmDiBVOPSBAEQTg9Wq2W0aNH06lTJ3755RfKy8v58ccfycrK4vLLL2+aMZEkiZKSkqa9PUVFRc1me7RaLYmJiU1JDc7VbM+Z0KYg6Mknn+SVV1454TG7du0iLS3ttBp1Ii+//DLPP//8WXt+QRCEC5VaqaZXZC96Rfbi0V6Pkleb17SPKKsqi8yKTDIrMvnPlv+QEJDgS6wQN5xuYd1QKVXnuvmCIAjCWRYbG8tdd93FypUrWblyJbt37+bAgQMMGDCAqqoq9u7de9zZnkNBz4U223MibdoTVFFRQVVV1QmPSUpKarafp6U9Qc888wy//PIL27Zta/rZ/v37SUpKYsuWLS0uhzveTFBcXJxYdy0IgnACZQ1lLC9czpKCJWwo2YBbcjc99mz/Z7k25do2P6fY99Iy0TeCIJzvysrKmD17NsXFxc1+rtVqm2Vyu9Bme87KnqCwsDDCwsJOu3EA/fv356WXXqK8vJzw8HAAfv/9dwICAujUqVOL5+l0OnQ63RlpgyAIwqUiwhjB5NTJTE6djNVlZVXxKpbmL2VV0SoGxww+180TBEEQ/mARERHccccdrF+/nj179hAVFXXRzfacyFl7h/n5+VRXV5Ofn4/X622a8UlOTsbf379pXeItt9zCq6++SmlpKU899RT33XefCHIEQRDOIn+tP2PbjWVsu7F4JM8fllJbEARBOL+oVCoGDBjAgAEDznVT/nBn7cr3zDPPMGPGjKa/H1retnTpUoYNG4ZKpWLu3LlMmzaN/v37YzQaufXWW3nhhRfOVpMEQRCEo4gASBAEQbgUnfU6QWebWHctCIJwbojxt2WibwRBEM6N1o6/yj+wTYIgCIIgCIIgCOecCIIEQRAEQRAEQbikiCBIEARBEARBEIRLigiCBEEQBEEQBEG4pIggSBAEQbggvfTSSwwYMAA/P78Wi/nl5+dz+eWX4+fnR3h4OI899hgej+eEz1tdXc1NN91EQEAAQUFB3HHHHVit1rPwDgRBEIRzRQRBgiAIwgXJ5XJx3XXXMW3atOM+7vV6ufzyy3G5XKxZs4YZM2Ywffp0nnnmmRM+70033UR2dja///47c+fOZcWKFdx1111n4y0IgiAI54hIkS0IgiCckvNl/J0+fToPPvggtbW1zX4+f/58JkyYQHFxMREREQB88MEHPPHEE1RUVKDVao95rl27dtGpUyc2btxIr169AFiwYAHjx4+nsLCQ6OjoVrXpfOkbQRCES41IkS0IgiBc0tauXUuXLl2aAiCAMWPGUF9fT3Z2dovnBAUFNQVAAKNGjUKpVLJ+/foWX8vpdFJfX9/sSxAEQTh/iSBIEARBuCiVlpY2C4CApr+Xlpa2eE54eHizn6nVaoKDg1s8B+Dll18mMDCw6SsuLu40Wy8IgiCcTSIIEgRBEM4bTz75JAqF4oRfOTk557qZx/jb3/5GXV1d01dBQcG5bpIgCIJwAupz3QBBEARBOOSRRx7hT3/60wmPSUpKatVzRUZGsmHDhmY/Kysra3qspXPKy8ub/czj8VBdXd3iOQA6nQ6dTteqdgmCIAjnngiCBEEQhPNGWFgYYWFhZ+S5+vfvz0svvUR5eXnTErfff/+dgIAAOnXq1OI5tbW1bN68mZ49ewKwZMkSJEmib9++Z6RdgiAIwrl3wQdBh5LbiU2ogiAIf6xD4+65SjKan59PdXU1+fn5eL1etm3bBkBycjL+/v6MHj2aTp06ccstt/Dqq69SWlrKU089xX333dc0a7NhwwamTp3K4sWLiYmJoWPHjowdO5Y777yTDz74ALfbzf3338/111/f6sxwIK5NgiAI50qrr03yBa6goEAGxJf4El/iS3ydo6+CgoJzMv7feuutx23P0qVLm445cOCAPG7cONlgMMihoaHyI488Irvd7qbHly5dKgPy/v37m35WVVUl33DDDbK/v78cEBAg33bbbbLFYmlT28S1SXyJL/Elvs7t18muTRd8nSBJkiguLsZkMqFQKNp8fn19PXFxcRQUFIhaDkcRfdMy0TctE31zYhdT/8iyjMViITo6GqVS5Nk5krg2nT2ib1om+qZlom9adrH1TWuvTRf8cjilUklsbOxpP09AQMBF8Q9/Noi+aZnom5aJvjmxi6V/AgMDz3UTzkvi2nT2ib5pmeiblom+adnF1DetuTaJW3eCIAiCIAiCIFxSRBAkCIIgCIIgCMIl5ZIPgnQ6Hc8++6yo73Acom9aJvqmZaJvTkz0j9Aa4v9Jy0TftEz0TctE37TsUu2bCz4xgiAIgiAIgiAIQltc8jNBgiAIwv+3d38hTf59GMev3K/lCIkyXEVZ1omlVtpUclAHSREVBFEEBlKns2ZCMIrooNQMCsGVZUQnJRVE9Ac6EAPNSFzaIumPB0FEkBZEkoHFdj9nPow2H5/fyfeG7/sFO7mPLkR880E3AQCwC0cQAAAAAKtwBAEAAACwCkcQAAAAAKtYfQRdvHhRK1asUHZ2tiorKzUwMGB6kis0NzervLxcOTk5ysvL0+7du/X+/XvTs1zp7NmzmjVrlurr601PcYXPnz/rwIEDys3Nlc/nU0lJiV68eGF6lnGJREInT55UQUGBfD6fVq1apdOnT4vPpUE6tCk92jQzdOlvtCk929tk7RF0+/ZtNTQ06NSpUxoaGtK6deu0bds2jY2NmZ5mXE9Pj0KhkPr7+9XV1aU/f/5o69atmpiYMD3NVWKxmK5cuaK1a9eanuIK379/VzAY1OzZs/X48WO9efNG58+f1/z5801PM66lpUXt7e2KRqN6+/atWlpadO7cObW1tZmeBpehTZnRpv+NLv2NNmVme5us/YjsyspKlZeXKxqNSpKSyaSWLVumw4cPKxKJGF7nLl+/flVeXp56enq0adMm03Nc4efPnyorK9OlS5d05swZrV+/Xq2traZnGRWJRPTs2TM9ffrU9BTX2blzp/x+v65duzb1bM+ePfL5fLpx44bBZXAb2jRztCkVXUqPNmVme5us/E3Q79+/NTg4qOrq6qlnWVlZqq6u1vPnzw0uc6cfP35IkhYsWGB4iXuEQiHt2LEj5XvIdg8ePFAgENDevXuVl5en0tJSXb161fQsV6iqqlJ3d7dGRkYkSa9evVJfX5+2b99ueBnchDb9f2hTKrqUHm3KzPY2/WN6gAnfvn1TIpGQ3+9Pee73+/Xu3TtDq9wpmUyqvr5ewWBQxcXFpue4wq1btzQ0NKRYLGZ6iqt8+PBB7e3tamho0PHjxxWLxXTkyBF5vV7V1taanmdUJBLR+Pi4CgsL5fF4lEgk1NjYqJqaGtPT4CK0aeZoUyq6lBltysz2Nll5BGHmQqGQhoeH1dfXZ3qKK3z69EnhcFhdXV3Kzs42PcdVksmkAoGAmpqaJEmlpaUaHh7W5cuXrQ/NnTt3dPPmTXV2dqqoqEjxeFz19fVasmSJ9V8b4N+gTf9Fl6ZHmzKzvU1WHkELFy6Ux+PR6OhoyvPR0VEtWrTI0Cr3qaur06NHj9Tb26ulS5eanuMKg4ODGhsbU1lZ2dSzRCKh3t5eRaNRTU5OyuPxGFxozuLFi7VmzZqUZ6tXr9bdu3cNLXKPY8eOKRKJaP/+/ZKkkpISffz4Uc3NzVaEBjNDm2aGNqWiS9OjTZnZ3iYr3xPk9Xq1YcMGdXd3Tz1LJpPq7u7Wxo0bDS5zB8dxVFdXp3v37unJkycqKCgwPck1tmzZotevXysej0+9AoGAampqFI/HrQ5NMBj86+NqR0ZGtHz5ckOL3OPXr1/Kykr9cevxeJRMJg0tghvRpunRpvTo0vRoU2a2t8nK3wRJUkNDg2praxUIBFRRUaHW1lZNTEzo4MGDpqcZFwqF1NnZqfv37ysnJ0dfvnyRJM2bN08+n8/wOrNycnL++vvzuXPnKjc31/q/Sz969KiqqqrU1NSkffv2aWBgQB0dHero6DA9zbhdu3apsbFR+fn5Kioq0suXL3XhwgUdOnTI9DS4DG3KjDalR5emR5sys75NjsXa2tqc/Px8x+v1OhUVFU5/f7/pSa4gKe3r+vXrpqe50ubNm51wOGx6his8fPjQKS4udubMmeMUFhY6HR0dpie5wvj4uBMOh538/HwnOzvbWblypXPixAlncnLS9DS4EG1KjzbNHF1KRZvSs71N1v6fIAAAAAB2svI9QQAAAADsxREEAAAAwCocQQAAAACswhEEAAAAwCocQQAAAACswhEEAAAAwCocQQAAAACswhEEAAAAwCocQQAAAACswhEEAAAAwCocQQAAAACswhEEAAAAwCr/AdB0WLM707fTAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Validate the two simulators\n", + "ts = jnp.arange(0, 10, 1.)\n", + "# ts = random.uniform(key, (100,), minval=0, maxval=10).sort()\n", + "thermox_samples = simulate_thermox(key, ts)\n", + "diffrax_samples = simulate_diffrax(key, ts)\n", + "fig, axes = plt.subplots(1, 2, figsize=(10, 5))\n", + "axes[0].plot(ts, thermox_samples)\n", + "axes[0].set_title(\"Thermox\")\n", + "axes[1].plot(ts, diffrax_samples)\n", + "axes[1].set_title(\"Diffrax\");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that we don't get the same trajectories because `thermox` and `diffrax` handle seeds differently, though we see that the mean and variance of the distribution evolve similarly." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running for T=10.0\n", + "Running for T=31.62277603149414\n", + "Running for T=100.0\n", + "Running for T=316.2277526855469\n", + "Running for T=1000.0\n", + "Running for T=3162.277587890625\n", + "Running for T=10000.0\n" + ] + } + ], + "source": [ + "# Time the two simulators\n", + "# T_range = [10, 100, 1000, 10000]\n", + "T_range = 10 ** jnp.arange(1, 4.1, 0.5)\n", + "\n", + "# Init run for compilation\n", + "simulate_thermox(key, jnp.arange(2.)).block_until_ready()\n", + "simulate_diffrax(key, jnp.arange(2.)).block_until_ready()\n", + "\n", + "thermox_times = []\n", + "diffrax_times = []\n", + "\n", + "for T in T_range:\n", + " print(f\"Running for T={T}\")\n", + " ts = jnp.arange(0, T, 1.)\n", + "\n", + " # Thermox\n", + " start = time()\n", + " vals_t = simulate_thermox(key, ts).block_until_ready()\n", + " end = time()\n", + " thermox_times.append(end - start)\n", + " \n", + " # Diffrax\n", + " start = time()\n", + " vals_d = simulate_diffrax(key, ts).block_until_ready()\n", + " end = time()\n", + " diffrax_times.append(end - start)\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's visualise the runtimes" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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WrVtF9ebNmweJRILXXntN6xyl+8aPH2/Ap0hEZH4XL14UDbuws7NDYGCgGSPSj8W2MMXHxyM4OBj+/v6YN28epk2bVm7d8looJk2aBAB45ZVXdO6PiIiwiNYNQa1GYU6OucPQm329epDU4JMMJ06cwPz589GlSxeMGzcOp0+fxubNm3Hu3Dn89ddfcHBw0NQ9duwYoqOjkZ+fjz59+iA4OBgZGRn46aef8Ntvv+HIkSNa/eR3797FM888Aw8PDwwbNgwPHz6Em5sblEql5pyffvopoqOjMW7cOCQmJuLbb7+FUqlE3759ERcXh/79++OZZ57Btm3b8Nlnn8HFxQUzZszQXEMQBAwePBi//PILQkJC8PrrryM/Px/r1q1Dv379sHDhQrz55psAgHfffRe7d+/G999/j+eeew4DBgwAABw/fhwzZsxAixYtsHDhQhN/6kREplG2Oy44OBh2dnZmikZ/EqEWjK4tTZjK65LT5eHDh2jUqBHy8/Nx7do1eHl5afaVdsnFxsZi+fLlRolRqVRCLpdDoVDAzc2tSseq7t7FrnbtjBJHTeh5/Dhk9etX+zwBAQHIzMwsd4B3UlISunTpAgBYu3Ythg4dqtk3atQorFq1CmvWrMGwYcMAAEVFRQgJCcHdu3exb98+tG7dWlP/4MGDiIqKQq9evUQtOqXduaNHj8aPP/4o6kN//PqbN29G//79Nddp27Ytzp07h/r162P79u2IjIwEAOTm5iIoKAjFxcXIzs7W/COwcuVKxMbGonPnzti1axfs7e0BPOoqfuqpp3D//n0kJydrkrnr16+jVatWEAQBf/75J9zc3NC6dWtcu3YNx48fR8uWLQ392ImIzKagoAALFiyAWq3WlA0aNAhPPvmkGaPSj8V2yVXXpk2bkJOTg379+omSpcdlZWXh66+/xieffIIlS5YgLS1N7/OrVCoolUrRi0yjU6dOomQJAF5++WUAj1qfSv3666/IyMjAO++8I0qWAKBjx47o378/tm/frvVd2dvbY/78+eUOOOzSpYsmWQIeNR8PHjwYgiCgb9++mmQJAFxdXdGnTx/cu3dP9MjsihUrAADz58/XJEsA4OfnhzfffBPFxcX46aefNOWNGzfGkiVLcO/ePYwcORITJkxAWloa5s+fz2SJiGqtlJQUUbJkY2OD4OBgM0akP4vtkquuJUuWAADGjBlTbp3du3dj9+7dmm2JRIKXXnoJ3333HZydnSs8/9y5c/Hhhx8aJ1iq0FNPPaVV1qRJEwDA/fv3NWVHjx4FACQnJ+vsas3OzoZarUZKSgratm2rKW/atCk8PT3LvX5ERIRWWem4uor2ZWVlaR4uOH36NJycnNBOR0tiaSvWmTNnROX9+/fHa6+9hu+++w4A0Lt3b0yePLncOImILF3Z7rigoCDIZDIzRVM1VpkwpaenIzExEX5+fujRo4fWficnJ3zwwQcYMGAAAgMDoVarcerUKfznP/9BQkICHjx4gI0bN1Z4jWnTpmHKlCmabaVSabErLNd2uro4bW0f3bolJSWasnv37gGAqKVGl/z8fNF2gwYNDL5+RfuKioo0ZRXdH6UJlq5WyoEDB2oSpokTJ1YYJxGRJVOpVLh06ZKorDY8HVfKKhOmpUuXQhAEjB49Wuc0697e3pg9e7aorFu3bnjmmWfQpk0bbNq0CadOnUKbNm3KvYZMJjNaVmxfrx56Hj9ulHPVBPt69cwdgk6lycvWrVvRp08fvY+riZWx3dzccOvWLZ37srOzNXUed//+fYwdOxbOzs4oKSnBpEmTcPr0abi6upo8XiIiY0tNTRX9J1cqlSIkJMSMEVWN1SVMarUay5cvh1Qq1Yxz0ZeTkxNiYmIwffp0HDp0qMKEyZgkUqlRBlHXde3btwcAHDlypEoJU01o3bo1fv/9dxw/flyrWy4pKQmAdvfeq6++iitXriA+Ph4FBQWYNGkSXn/9daxcubKGoiYiMp6y3XFNmzaFo6OjmaKpOqsb9L1jxw5cu3YNPXr0gJ+fX5WPLx3LUrbbhixf//794efnh4ULF2L//v1a+4uKinDw4EEzRAbExsYCeNSV+3hX3dWrV7Fw4ULY2tpq5g0DHo3B+/nnn/Hiiy/ilVdewcSJE9GnTx+sWrUKq1evrvH4iYiqo6ioCKmpqaKy2tQdB1hhC5M+g70rcuzYMQCPHnmn2kUmk2HDhg3o1asXOnfujK5duyI8PBwSiQSZmZk4cOAA6tevr7WGUU2IiYnBpk2b8Msvv6Bly5bo06ePZh6me/fu4fPPP9dMKZCSkoI33ngDvr6++OGHHzTnWLp0KVq2bInx48fjmWeeqXC2eiIiS5KWlib6z6JEIkFYWJgZI6o6q2phun37NrZu3QovLy/069ev3HqnT5/WOffPpk2bsGLFCtSrVw+9evUyZahkIpGRkTh79izeeOMNXL16Fd999x2WLl2KixcvYsCAAfjmm2/MEpdEIsGGDRuwYMEC2NnZYfHixUhISEB4eDh++eUXzQMEhYWFGD58OAoKCpCQkAB3d3fNOby8vLBy5Urk5uZixIgROmcTJyKyRGW74/z9/St9Gt3SWOzElfHx8Zruk3PnzuHUqVPo0KEDgoKCADyaV6dsK9Lnn3+Ot99+G1OmTMHnn39e7rmjoqKQlpaGZ555Bk2aNEFJSQlOnTqFgwcPQiaTYf369RUmXLpUZ+JKIiIia1VSUoLPPvsMKpVKU9arVy+d06xYMovtkjt48KBmsr9Shw4dwqFDhzTbZRMmfbvjRo4ciY0bN+Lo0aO4c+cO1Go1GjdujDFjxuCtt96qdc2ERERElury5cuiZAlArfw9a7EtTLUNW5iIiIi0bdmyBadPn9ZsN2nSpNw1Xi2ZVY1hIiIiIsuhVqu1HrRp0aKFmaKpHiZMREREZBKZmZkoKCgQldW26QRKMWEiIiIikzh//rxo28fHR/T0b23ChImIiIiMThAEre642tq6BDBhIiIiIhO4evUq8vLyRGW1dfwSwISJiIiITKBsd5y3tzfq1+J1U5kwERERkVFZW3ccwISJiIiIjCwrKwsKhUJUxoSJiIiI6DFl147z8PCAt7e3maIxDiZMREREZDSCIGglTM2bN4dEIjFTRMbBhImIiIiM5tatW7h3756orDY/HVeKCRMREREZTdmn4+RyOXx8fMwUjfEwYSIiIiKjscbuOIAJExERERnJnTt3cPv2bVFZbX86rhQTJiIiIjKKsq1LLi4u8PX1NVM0xsWEiYiIiIyibMIUFhZmFd1xABMmIiIiMoKcnBzcuHFDVGYNT8eVYsJERERE1Va2dcnR0RH+/v5misb4mDARERFRtenqjpNKrSfNsJ53QkRERGahVCpx7do1UZm1PB1XigkTERERVcvFixdF2zKZDM2aNTNTNKbBhImIiIiqpWx3XGhoKGxsbMwUjWkwYSIiIiKD5efnIzMzU1Rmbd1xABMmIiIiqoaLFy9CEATNtp2dHQIDA80YkWkwYSIiIiKDle2OCw4Ohp2dnZmiMR0mTERERGSQgoICpKeni8qssTsOYMJEREREBkpJSYFardZs29jYIDg42IwRmY7FJkwJCQkYN24c2rZtC5lMBolEguXLl+usO2vWLEgkknJfGRkZOo/buXMnOnfuDFdXV7i5uaFLly7Yu3ev6d4UERGRFSnbHRcUFASZTGamaEzL1twBlGf69OnIzMyEp6cnfHx8tEbg6xIbG4uAgACtcnd3d62yhIQExMTEwMvLC3FxcQCAdevWoUePHli/fj0GDx5czXdARERkvVQqFS5duiQqs9buOMCCE6b4+HgEBwfD398f8+bNw7Rp0yo9Ji4uDlFRUZXWy8nJwaRJk+Dp6YlTp06hSZMmAICpU6eidevWGD9+PKKjo+Hq6lrdt0FERGSVUlNTUVJSotmWSqUIDQ01Y0SmZbFdct27dzfZon0///wz7t+/j0mTJmmSJQBo0qQJJk6ciDt37uB///ufSa5NRERkDcp2xzVr1gwODg5misb0LDZhMsT+/fvx6aef4rPPPsPmzZuRl5ens15SUhIAoGfPnlr7oqOjAQD79u0zWZxERES1WVFREVJTU0Vl1twdB1hwl5whZs6cKdp2d3fHokWLMGrUKFF56ZesayR/aVnZG6EslUoFlUql2VYqlQbFTEREVNtcunQJRUVFmm2JRGLV3XGAlbQwtWrVCkuXLsXly5c1c0IsXrwYEokEcXFx2LJli6i+QqEAAMjlcq1zubm5ieqUZ+7cuZDL5ZqXr6+vkd4NERGRZSvbHefv7w9nZ2czRVMzrCJhGjhwIEaPHo2mTZvCwcEBAQEBmDhxIn7++WcAj564M7Zp06ZBoVBoXlevXjX6NYiIiCxNcXExUlJSRGXW3h0HWFmXXFndunVDYGAgzp07B6VSqWk9Km1ZUigUqF+/vuiY0q41Xa1Pj5PJZFY71wQREVF50tPTRUNSgLqRMFlFC1NFPD09AQAPHjzQlFU0Tqmi8U1ERER13fnz50Xbvr6+dWIaHqtOmPLz8/H333/D2dlZkzgBQOfOnQEAu3bt0jpm586dojpERET0iFqtRnJysqisLrQuAVaQMOXm5mr1pQKPFgQcO3YscnNzMWTIENja/tP7OGTIEMjlcixevBjXrl3TlF+7dg1fffUVPD09MXDgwBqJn4iIqLbIyMhAQUGBqKyuJEwWO4YpPj4eBw8eBACcO3dOU1Y6h1LHjh0xZswY3L17F2FhYYiMjETz5s3RsGFD3Lx5E3v27MG1a9cQHh6Ozz77THTuevXq4auvvkJMTAzatGmDoUOHAni0NMrdu3exbt26OtG8SEREVBVln47z8fHRufyYNbLYhOngwYNYsWKFqOzQoUM4dOiQZnvMmDHw8PDAhAkTcPz4cWzfvh05OTlwdHRE8+bNMXnyZEycOBGOjo5a5x85ciQ8PT3xySefYNmyZZBIJHjqqacwffp0dO/e3eTvj4iIqDYRBAEXL14UldWV1iUAkAiCIJg7CGugVCohl8uhUCg0T+MRERFZiytXrmDZsmWisokTJ2o9bW6tav0YJiIiIjK9sk/HeXt715lkCWDCRERERJWo691xABMmIiIiqkRWVpbWkmFMmIiIiIgeU/bpOA8PD3h7e5spGvNgwkRERETlEgRBK2Fq3rw5JBKJmSIyDyZMREREVK5bt27h3r17orIWLVqYKRrzYcJERERE5Sr7dJxcLoePj4+ZojEfJkxERERULnbHPcKEiYiIiHS6c+cObt++LSqra0/HlWLCRERERDqVbV1ycXGBr6+vmaIxLyZMREREpFPZhCksLKxOdscBTJiIiIhIh5ycHNy4cUNUVhefjivFhImIiIi0lG1dcnR0hL+/v5miMT8mTERERKRFV3ecVFp304a6+86JiIhIJ6VSiWvXronK6nJ3HMCEiYiIiMoo27okk8nQtGlTM0VjGZgwERERkUjZhCk0NBQ2NjZmisYy2Bpy0P3797Fz507s3bsXp06dws2bN5GTk4N69eqhQYMGeOqpp9C1a1dER0fD3d3dyCETERGRqeTn5+PKlSuisro6WeXjqpQwnTt3DosWLcKaNWvw8OFDCIIg2v/gwQNcv34dp06dQnx8PBwcHDBixAhMmjQJLVu2NGrgREREZHwXL14U/X63s7NDYGCgGSOyDHolTLdu3cK0adOwYsUKqNVqeHp64vnnn8e//vUvPPHEE6hfvz7c3NygUChw9+5d/PXXXzh8+DD279+PJUuWYNmyZYiLi8Mnn3wCb29vU78nIiIiMlDZ7riQkBDY2dmZKRrLIRHKNhPpIJfLkZubiz59+uCVV17B888/D1vbynOt4uJibN26FUuXLsW2bdsgl8uRk5NjlMAtjVKphFwuh0KhgJubm7nDISIiqrKCggIsWLAAarVaUzZ48GA88cQTZozKMug16Ltdu3Y4ceIEtmzZgv79++uVLAGAra0tBg4ciK1bt+LYsWNo27ZttYIlIiIi00lOThYlS7a2tggODjZjRJZDr8xn9+7d1b5QZGSkUc5DREREplG2Oy4wMBD29vZmisaycFoBIiIigkqlQlpamqiMT8f9wyQJk0Kh0HqCjoiIiCxXamoqSkpKNNtSqRShoaFmjMiyGJQw/fXXX/jvf/+LlJQUUXliYiKaNm0KDw8PeHt7Y/ny5caIkYiIiEysbHdcs2bN4ODgYKZoLI9BCdN///tfTJkyBY6Ojpqyu3fvYsCAAcjMzIQgCLh79y7GjBmD06dPGy1YIiIiMr6ioiKkpqaKytgdJ2ZQwnTo0CE88cQT8PX11ZStWrUKubm5GDduHO7fv4+VK1dCrVZj8eLFRguWiIiIjO/SpUsoKirSbEskEnbHlWFQwnTz5k34+fmJynbv3g0bGxt89NFHcHNzw8iRI9G6dWscOXLEoMASEhIwbtw4tG3bFjKZDBKJRGcXX1FRETZu3IjY2Fg0b94cLi4ucHV1Rfv27fHtt9+K+mNLZWRkQCKRlPuaNWuWQTETERHVRmW74/z9/eHs7GymaCyTQWvJlU7S+Lhjx44hIiIC9evX15QFBwdj+/btBgU2ffp0ZGZmwtPTEz4+PsjMzNRZLy0tDYMHD4aLiwu6deuGfv36QaFQYOvWrZgwYQK2b9+OLVu2QCKRaB3bqlUrDBgwQKs8KirKoJiJiIhqm+LiYq0xyeyO02ZQwuTm5obr169rti9cuIB79+7hpZde0qqrK1HRR3x8PIKDg+Hv74958+Zh2rRpOuu5urri66+/RmxsrCgb/vzzzxEVFYVff/0VGzZswIsvvqh1bEREBFuTiIioTktPT4dKpRKVMWHSZlCXXEREBA4fPoxLly4BAJYsWQKJRILOnTuL6qWnp8PHx8egwLp37w5/f/9K6zVu3BgTJkzQajp0dnbGlClTAAD79u0zKAYiIiJrd/78edG2r68vXF1dzRSN5TKohWncuHH4/fff8dRTT6FZs2b4888/4e3tjeeff15TJzc3F2fOnEHfvn2NFmxVlS4WWN5SLllZWfj666+hUCjQoEEDREVFcUVmIiKqM9RqNZKTk0VlbF3SzaCE6cUXX8SFCxfw6aef4uzZswgICMDKlSshk8k0ddavX4+ioiKtVqeatHTpUgBAz549de7fvXu3aLkWiUSCl156Cd99912lg91UKpWoCVOpVBohYiIiopqTkZGBgoICURkTJt0Mnul7xowZyMnJwa1bt3D58mV07NhRtL9Hjx44ffo0Ro8eXe0gDfHDDz/gt99+Q9euXdG7d2/RPicnJ3zwwQc4efIk7t+/j3v37mHPnj1o164dEhISMGrUqErPP3fuXMjlcs3r8SkWiIiIaoOyT8f5+PjA3d3dPMFYuGotjWJvbw9PT0+d+/z8/NCqVSu4uLhU5xIG+fXXXzFx4kT4+/sjISFBa7+3tzdmz56NNm3aQC6Xo169eujWrRt+//13hIaGYtOmTTh16lSF15g2bRoUCoXmdfXqVVO9HSIiIqMTBAEXL14UlbF1qXxWt/ju9u3bMXjwYDRo0AC///57lQadOzk5ISYmBsCjyTkrIpPJ4ObmJnoRERHVFlevXkVeXp6orEWLFmaKxvLplTC98cYbuHv3brUudPv2bUyePLla56jMtm3b8MILL8DT0xOJiYlo1qxZlc9R2mKWn59v7PCIiIgsRtmn47y9vUVzKZKYXgnT119/jaZNm2LatGlaa81UJjk5Ge+88w4CAwPx7bffGhSkPrZt24ZBgwbBw8MDiYmJCAoKMug8x44dAwAEBAQYMToiIiLLIQiC1vgldsdVTK+E6cSJE2jZsiU+/fRThIWFoWPHjpg5cyZ27NiBzMxMTZNeXl4eMjMz8dtvv2HGjBl45pln0KJFC3z++edo1aoVTpw4YZI38dtvv2HQoEGoV68eEhMTERwcXGH906dPQxAErfJNmzZhxYoVqFevHnr16mWSWImIiMwtKytL6+luJkwVkwi6ModybNiwAV988QWOHDlS6Qzepaf917/+hTfffBODBg2qUmDx8fE4ePAgAODcuXM4deoUOnTooGk56tixI8aMGYOLFy8iIiICKpUKw4YN07lYYEBAAOLi4jTbUVFRSEtLwzPPPIMmTZqgpKQEp06dwsGDByGTybB+/Xr069evSvGWLhejUCg4nomIiCza7t27cfjwYc22h4cHJk6caPDqHHVBleZhGjx4MAYPHowzZ85g8+bN+P3333H69GnReB9nZ2e0adMGXbp0wYABAxAREWFQYAcPHsSKFStEZYcOHRINxh4zZgyys7M18yGtXbtW57k6d+4sSphGjhyJjRs34ujRo7hz5w7UajUaN26MMWPG4K233kJYWJhBMRMREVm68rrjmCxVrEotTOV58OABFAoF3N3d4ejoaIy4ah22MBERUW2QnZ2N77//XlQ2duxYNGrUyEwR1Q4GzfRdlpOTE5ycnIxxKiIiIjKhsq1Lcrnc4HVf6xKrm4eJiIiIysfuOMMwYSIiIqoj7ty5g9u3b4vKOFmlfpgwERER1RFlJ6t0dXVFkyZNzBRN7cKEiYiIqI4o2x0XFhbG7jg9MWEiIiKqA3JycpCdnS0q42SV+mPCREREVAeUbV1ycnKCv7+/maKpfZgwERER1QFlE6bQ0FBIpUwD9MVPioiIyMoplUpcu3ZNVMan46qmWhNXKpVKJCQk4PDhw7h9+za6deuGd999FwCQkpKCjIwMdOrUCQ4ODkYJloiIiKqubOuSTCZD06ZNzRRN7WRwwrRr1y6MGDECOTk5EAQBEokEjRs31uxPTk7GgAEDsGbNGgwZMsQowRIREVHV6eqOs7GxMVM0tZNBXXIXLlzAwIEDoVAoMH78eKxbtw5ll6SLjo6Gk5MTfvnlF6MESkRERFWXn5+PK1euiMr4dFzVGdTC9Mknn+Dhw4f4+eef8cILLwAAhg4dKqpjb2+PiIgInD17tvpREhERkUEuXrwoatSws7NDYGCgGSOqnQxqYUpMTESrVq00yVJ5mjRpghs3bhgUGBEREVVf2e64kJAQ2NnZmSma2sughOn27dsICQmptF5xcTHy8/MNuQQRERFVU0FBAdLT00Vl7I4zjEEJk1wux/Xr1yutd/nyZXh7extyCSIiIqqm5ORkqNVqzbatrS2Cg4PNGFHtZVDC1KZNG5w8eVJrENnj/vrrL5w9exbt27c3ODgiIiIyXNnuuMDAQNjb25spmtrNoIRpzJgxePjwIYYPH661Lg0A3LlzB2PGjIEgCBgzZky1gyQiIqKqUalUSEtLE5WxO85wBiVMgwcPxosvvogjR44gMDAQPXv2BAAcOnQI/fr1Q7NmzXD8+HGMGDEC0dHRRg2YiIiIKpeamoqSkhLNtlQqRWhoqBkjqt0MXhpl9erVmDZtGgBgz549AB59Ob/++isKCwvx1ltvYfny5UYJkoiIiKqmbHdcs2bNuPJGNRg807eNjQ0+/vhjvP3220hMTMTly5ehVqvh6+uLbt26cbA3ERGRmRQVFSE1NVVUxu646qnWWnIAUK9evUrnYyIiIqKac+nSJRQVFWm2JRIJu+OqyeAuOSIiIrJMZbvj/P394ezsbKZorEO1WpgePnyIP/74A1lZWXj48GG59UaNGlWdyxAREZGeiouLkZKSIipjd1z1GZwwffbZZ/jkk0+gVCorrcuEiYiIqGZcvnwZKpVKVMaEqfoMSpi++uorTJ06FQAQHh6O4OBguLq6GjUwIiIiqrqy3XG+vr78HW0EBidMtra22LhxI/r27WvsmIiIiMgAJSUlSE5OFpWxdck4DBr0nZGRgU6dOpk0WUpISMC4cePQtm1byGQySCSSCud1UiqVmDJlCvz9/SGTyRAQEIB33nkHeXl5Ouur1WosXrwY4eHhcHR0hJeXF4YPH47Lly+b6B0RERGZVmZmJgoKCkRlTJiMw6CEydvbG15eXsaORWT69On44YcfkJmZCR8fnwrr5ufno3Pnzvjiiy8QFhaGN998E6GhoViwYAG6du2qc0D6uHHjMHnyZAiCgMmTJ+O5557Dpk2bEBkZqTV3BRERUW1w/vx50XajRo3g7u5unmCsjEEJU69evXDkyBHRCsjGFh8fj4yMDNy+fRuvvfZahXXnz5+PM2fOYOrUqdi5cyfmzZuHnTt3YurUqThx4gS++OILUf3ExETEx8ejU6dOOHXqFD799FOsWrUKmzdvxr179zBx4kSTvS8iIiJTUKvVuHjxoqiMrUvGY1DCNHPmTBQWFmLy5MkoLCw0dkwAgO7du8Pf37/SeoIgID4+Hi4uLvjggw9E+z744AO4uLggPj5eVP7jjz8CAObMmSNatblXr16IiorCrl27cOXKFSO8CyIioppx9epV5Ofni8qYMBmPQYO+GzVqhIMHD6Jfv34IDQ1Fly5d4OfnB6lUO/+SSCRaiYwxpaamIisrC9HR0VqTcjk7O6NDhw7YuXMnrl69Cl9fXwBAUlKSZl9Z0dHRSEpKwr59+xATE2OyuImIiIyp7NNx3t7eqF+/vpmisT4GJUyCIGDRokW4ePEi1Gq1zsHYEokEgiDUSMIEAMHBwTr3BwcHY+fOnUhNTYWvry/y8/Nx48YNPPnkk7CxsdFZ//HzlkelUonmudBnPioiIiJTEARBK2Fi65JxGZQwffbZZ1i8eDFsbW3Rp08fBAcHw8XFxdix6UWhUAAA5HK5zv1ubm6ielWtX565c+fiww8/rHrARERERpaVlaX1H/cWLVqYKRrrZFDCFB8fDycnJxw4cACtW7c2dky1wrRp0zBlyhTNtlKp1HT5ERER1aSyT8fVr1/f5E+z1zUGJUxXr15FVFSURSRLpS1F5bUIlWbcpfWqWr88MpkMMpms6gETEREZUXndcRKJxEwRWSeDnpJr2LChxUyzXtmYo7JjnJydneHj44P09HSUlJRUWp+IiMiS3bx5Ezk5OaIyjl8yPoMSpoEDB+LAgQM6J4SsacHBwWjUqBEOHTqk9Thlfn4+Dh06hKZNm4q6yzp37qzZV9bOnTsBAJ06dTJt4EREREZQtnXJ3d290gmfqeoMSphmzZoFDw8PDB8+HHfu3DF2TFUikUgwZswY5OXlYc6cOaJ9c+bMQV5eHsaOHSsqf/XVVwE8mqfp8XmkfvvtNyQlJaFnz556zQFFRERkbmUTprCwMHbHmYBEEAShqge9/PLLuH//PjZv3gxXV1c89dRTFc7DtGTJkioHFh8fj4MHDwIAzp07h1OnTqFDhw4ICgoCAHTs2BFjxowB8KglqUOHDjh79ix69uyJNm3a4NSpU9i1axciIyOxb98+ODo6is4/duxYxMfH44knnsDzzz+PGzduYN26dXBxccGRI0cQEhJSpXiVSiXkcjkUCoXmSTsiIiJTunPnDr7++mtR2csvv8yHkEzAoIRJKpVq5lmq9AISic6xQpWJi4vDihUryt0fGxsrmv9JoVBg1qxZ2LhxI7Kzs+Hj44MXX3wRM2fO1DneSq1W46uvvsIPP/yAS5cuwcXFBd27d8fHH3+MwMDAKsfLhImIiGra/v37kZiYqNl2dXXFm2++yRYmEzAoYaookdElNja2qpeodZgwERFRTfv++++RnZ2t2Y6MjETv3r3NGJH1MmhagbqQABEREVmynJwcUbIE8Ok4UzJo0DcRERGZV9nB3k5OTnxgyYSYMBEREdVCZROm0NBQnQ9fkXHo1SU3e/ZsAMDEiRPh4eGh2daHqRffJSIiqmuUSiWuXbsmKuPacaal16Dv0qfiLly4gJCQEL2ekivdb+hTcrUNB30TEVFNOXbsGHbs2KHZlslkeOedd2BjY2PGqKybXi1MM2bMgEQigaenp2ibiIiIap6u7jgmS6Zl0LQCpI0tTEREVBPy8vLw+eefi8qGDh2KsLAwM0VUN3B0GBERUS1y8eJF0badnZ1BEy5T1RiUMDVr1gxTp06ttN60adP4JRIRERlR2e64kJAQ2NnZmSmausOghCkjIwO3b9+utN6dO3eQkZFhyCWIiIiojIKCAq3fq5yssmaYtEvu4cOHsLU1aDJxIiIiKiM5ORlqtVqzbWtri+DgYDNGVHeYLGEqKSnBH3/8AS8vL1NdgoiIqE4p2x0XGBgIe3t7M0VTt+jd/NO1a1fR9o4dO7TKShUXFyM1NRW3bt3CiBEjqhchERERQaVSIS0tTVTG7riao3fClJSUpPm7RCJBdna21qJ/ZbVt2xZz5841ODgiIiJ6JCUlRTQRtFQqRWhoqBkjqlv0TpgSExMBAIIgoGvXrnjuuefKfVLO3t4eTZo0ga+vr3GiJCIiquPKdsc1a9YMDg4OZoqm7tE7YercubPo71FRUaIyIiIiMo2ioiJcunRJVMbuuJpl0CNspa1NREREZHqXLl1CUVGRZlsikXBm7xrGmb6JiIgsXNnuuICAADg5OZkpmrrJ4EmSSkpKsGHDBuzZswfXr1/Hw4cPddaTSCTYu3evwQESERHVZcXFxUhJSRGVsTuu5hmUMCkUCkRHR+PEiROobO1eiURiUGBEREQEXL58GSqVSlTG7riaZ1DC9MEHH+D48eNo3LgxJk2ahObNm8PNzc3YsREREdV5ZbvjfH194erqaqZo6i6DEqbNmzfD3d0dR48eRePGjY0dExEREeHR8Jfk5GRRGbvjzMOgQd83b95Ehw4dmCwRERGZUGZmJgoKCkRlTJjMw6CEqUGDBpwsi4iIyMTOnz8v2m7UqBHc3d3NE0wdZ1DC1LdvXxw6dEg0JwQREREZj1qtxsWLF0VlbF0yH4MSpg8//BC2trYYP358udMJEBERkeGuXr2K/Px8URkTJvMxaND3N998g549e2LZsmXYvXs3unXrBj8/P0il2vmXRCLBBx98UO1AiYiI6pKyT8d5e3ujfv36ZoqGJEJlEynpIJVKIZFIKpyDqXS/RCIRra5srZRKJeRyORQKBadYICKiahEEAV9++SWUSqWmrHQdVzIPg1qYZs6caew4qm358uUYPXp0hXW6du2qmXV81qxZ+PDDD8utm56ejoCAAGOGSEREpJesrCxRsgQALVq0MFM0BFhRwhQREVFuXBs2bMDff/+N6OhorX2xsbE6EyM+hUBEROZS9um4+vXrw8vLy0zREFCNteQsTUREBCIiIrTKCwsL8dVXX8HW1haxsbFa++Pi4tjESUREFkMQBK3xS82bN+dSY2Zm0FNytcnmzZtx9+5d9OnTBw0aNDB3OERERBW6efMmcnJyRGV8Os78DGphmj17tt51zf2UXHx8PABgzJgxOvfv378fx44dg1QqRXBwMLp37w4XF5eaDJGIiEijbHecu7s7fHx8zBQNlTIoYZo1a1a5T8k93mRY+pScuRKmzMxM7N27F02aNMFzzz2ns07ZcU/u7u5YtGgRRo0aVeG5VSqVaPXosoPziIiIDFG2Oy4sLIzdcRbAqIO+1Wo1MjMzkZiYiKtXr+KVV15BkyZNqhVgdSxbtgxqtRpxcXGwsbER7WvVqhWWLl2KqKgo+Pj4IDs7G7/++itmzJiBuLg4uLu7o1+/fuWee+7cuRU+ZUdERFRVt2/fxp07d0RlfDrOMhg0D1NlCgoKMHbsWOzfvx+nTp2Cp6ensS9RKbVajaZNm+Lq1atIS0tD06ZN9Tpu79696NGjB5588kn8+eef5dbT1cLk6+vLeZiIiMhg+/fvR2Jiombb1dUVb775JluYLIBJBn07Ojrihx9+gEqlwowZM0xxiUrt2bMHV65cQdeuXfVOlgCgW7duCAwMxLlz5yrsZpPJZHBzcxO9iIiIqoPdcZbLZE/JOTk5oW3btvj1119NdYkKVTbYuyKlLWIPHjwwakxERETlycnJQXZ2tqiMT8dZDpNOKyCVSnHr1i1TXkKnu3fv4pdffoGHhwcGDhxYpWPz8/Px999/w9nZ2SxdiUREVDeVfTrOyckJ/v7+ZoqGyjJZwpSVlYWDBw+aZe6jVatWobCwECNHjoRMJtPan5ubi5SUFK3y0rFXubm5GDJkCGxtrWZeTyIisnBlu+NCQ0N1LmpP5mFQRrB///5y9+Xm5uLChQv4+uuvoVQqK3083xSWLFkCoPzuuLt37yIsLAyRkZFo3rw5GjZsiJs3b2LPnj24du0awsPD8dlnn9VkyEREVIcplUpcv35dVMan4yyLQQlTVFRUpYPQBEFA27ZtMWfOHIMCM9Tx48fx119/oV27dggPD9dZx8PDAxMmTMDx48exfft25OTkwNHREc2bN8fkyZMxceJEODo61mjcRERUd5VtXZLJZFV6YIlMz6CEqVOnTuUmTPb29mjcuDG6d+9ulm6tdu3a6ZxQ83Fubm746quvaigiIiKiiunqjis7fyCZl0HZTFJSkpHDICIiqpvy8vKQmZkpKmN3nOUx6Wiy+/fv4z//+Y8pL0FERFSrXbx4UbRtb2+PwMBAM0VD5TFJwqRUKjFz5kwEBARg3rx5prgEERGRVSjbHRccHMyntC1Qlb6RkydPYuvWrbh58yYaNGiAfv36oU2bNpr9Dx8+xMKFC7FgwQIoFAoIgsBmRSIionIUFBQgIyNDVMbJKi2T3gnT22+/jS+++EJUNmfOHHzwwQeYNWsWTpw4gaFDhyIzMxOCIMDPzw+zZs0yy7QCREREtUFycjLUarVm29bWFsHBwWaMiMqjV8K0bds2LFy4EMCjJ8yCg4OhVCpx+fJlzJkzB6GhoRg/fjyUSiU8PDwwffp0TJgwAfb29iYNnoiIqDYr2x0XFBTE350WSq+E6ccffwQATJo0CfPnz9fMnn3hwgUMGjQIsbGxKC4uRpcuXbBu3TouKUJERFQJlUqFtLQ0URm74yyXXoO+T548iYCAAHzxxReipUaaN2+OL7/8EsXFxXBzc8PmzZuZLBEREekhJSUFJSUlmm2pVIqQkBAzRkQV0Sthun37Nlq3bq1zTZunn34aAPDss8/C1dXVuNERERFZqbLdcc2aNYODg4OZoqHK6JUwFRYWQi6X69zn5uYGAPDy8jJeVERERFasqKgIly5dEpWxO86ycRlkIiKiGnbp0iUUFRVptiUSCcLCwswYEVVG72kFLl26hJUrVxq0n1MLEBER/aNsd1xAQACcnJzMFA3pQyJUtlItHg1EK2+x3UovIJGguLjYoGNrE6VSCblcDoVCoemmJCIiKkupVOKbb76BSqXSlPXu3RuRkZFmjIoqo1cLk5+fn8EJExERET1y7949rFq1SpQsAWB3XC2gV8JUdtp2IiIiqprs7GwkJCQgPz9fVB4SEsKnzGsBru5HRERkYleuXMHq1au1Wpbq16+P559/3kxRUVUwYSIiIjKh1NRUrF+/Xms8b8OGDTFy5Eg4OzubKTKqCiZMREREJnLu3Dls3rxZtMAuAPj7+2PYsGGcqLIWYcJERERkAidOnMD27du1ykNCQjB48GDY2dmZISoyFBMmIiIiIxIEAQcOHEBiYqLWvpYtW6Jfv36wsbExQ2RUHUyYiIiIjEQQBOzcuRPHjh3T2teuXTs899xznKanlmLCREREZARqtRpbtmzB2bNntfZFRUWhU6dOTJZqMSZMRERE1VRcXIwNGzYgOTlZa1+vXr3Qrl07M0RFxsSEiYiIqBpUKhXWrl2rNcmzVCrFgAEDEB4ebp7AyKiYMBERERkoPz8fP/30E27cuCEqt7W1xYsvvoiQkBAzRUbGxoSJiIjIAAqFAqtWrcLdu3dF5TKZDMOHD4e/v7+ZIiNTYMJERERURXfu3MGqVaugVCpF5c7Ozhg5ciQaNmxopsjIVKTmDsCYAgICIJFIdL6ioqK06qtUKsyePRvBwcFwcHBAo0aN8Oqrr+LWrVs1HzwREdUKWVlZWLZsmVayJJfLMXr0aCZLVsrqWpjkcjn+/e9/a5UHBASIttVqNfr374+dO3fi6aefxqBBg5Camor4+Hjs3bsXR48ehZeXV80ETUREtUJGRgbWrFmDwsJCUbmXlxdGjhwJNzc3M0VGpiYRBEEwdxDGUpoUlX1SQZdly5bh5ZdfxvDhw/HTTz9p5sb47rvvMH78eLz66qv4/vvv9b62UqmEXC6HQqHgDwwRkRW6ePEiNmzYgJKSElF548aNMWLECDg5OZkpMqoJdTZh+te//oUjR44gIyNDNDBPEAQEBQXh5s2buH37NhwdHfW6NhMmIiLrdebMGWzZsgVlf2U2bdoUw4YNg729vZkio5pidV1yKpUKy5cvR1ZWFtzc3BAZGYn27duL6jx8+BDHjh1DaGio1lMMEokEPXr0wPfff48//vgDzz77bE2GT0REFubo0aPYuXOnVnnz5s3xwgsvwNbW6n6Vkg5W9y1nZ2dj9OjRorLIyEisWbMGgYGBAIC0tDSo1WoEBwfrPEdpeWpqarkJk0qlgkql0myXHfxHRES1myAISExMxIEDB7T2tW7dGn369IFUalXPTlEFrOqbHj16NPbu3YubN28iPz8fp0+fRkxMDE6cOIFu3bohNzcXwKO5M4BHA8R1Ke1SK62ny9y5cyGXyzUvX19fI78bIiIyF0EQsH37dp3J0r/+9S/07duXyVIdY1Xf9syZM9G1a1d4e3vDyckJERERWLlyJWJiYpCZmYkff/zRaNeaNm0aFAqF5nX16lWjnZuIiMynpKQEmzZtwh9//KG1r1u3bujRowcX0a2DrCphKs+4ceMAAIcOHQLwT8tSeS1Ipd1r5bVAAY9mcnVzcxO9iIiodisqKsLatWvx119/ae3r06cPOnbsaIaoyBJY3RgmXTw9PQE8WvMHAJo1awapVIrU1FSd9UvLyxvjRERE1ufhw4dYvXq1Vo+BVCrFCy+8gCeeeMJMkZElqBMtTMeOHQPwz7QDjo6OaNeuHZKTk5GZmSmqKwgCdu/eDWdnZ7Rt27amQyUiIjPIy8vD8uXLtZIlOzs7jBgxgskSWU/CdPHiRTx48EBn+dSpUwEAI0aM0JS/+uqrAB6NRXp8Xo3vv/8ely9fxksvvaT3HExERFR75eTkYOnSpbh586ao3MHBAaNGjdI8YU11m9V0ya1duxYLFy5Ep06d4O/vD2dnZ6SkpGD79u0oKirCtGnT0KlTJ0392NhYrFu3DmvWrEF6ejo6d+6MS5cuYdOmTWjatCk++ugjM74bIiKqCbdu3cKqVauQl5cnKndxcUFMTAy8vb3NFBlZGquZ6Xvfvn345ptvcPr0ady8eRMPHjyAp6cn2rdvjwkTJqBnz55ax6hUKsybNw+rVq3C1atX4eHhgT59+uCjjz5CgwYNqnR9zvRNRFS7XLt2DT/99BMePnwoKq9Xrx5iYmJQr149M0VGlshqEiZzY8JERFR7pKWlYd26dSgqKhKVN2jQACNHjoSLi4uZIiNLZTVdckRERPo4f/48Nm7cCLVaLSr39fXFiBEj4ODgYKbIyJIxYSIiojrj5MmT2LZtm9YiukFBQRgyZAjs7OzMFBlZOiZMRERUJxw8eBB79+7VKn/yyScxYMAA2NjYmCEqqi2YMBERkVUTBAF79uzB4cOHtfa1bdsWvXr14rpwVCkmTEREZLXUajV+/fVXnD59Wmvfs88+iy5dunBdONILEyYiIrJKxcXF2LRpEy5cuKC1Lzo6Gk8//bQZoqLaigkTERFZncLCQqxbtw6XL18WlUskEvTr1w8RERHmCYxqLSZMRERkVR48eIDVq1fj+vXronIbGxsMHjwYYWFhZoqMajMmTEREZDWUSiUSEhJw+/ZtUbm9vT2GDx+uWYSdqKqYMBERkVW4e/cuVq1aBYVCISp3cnLCSy+9hEaNGpkpMrIGTJiIiKjWy87ORkJCAvLz80Xlbm5uiImJgaenp5kiI2vBhImIiGq1zMxMrFmzBiqVSlRev359xMTEQC6XmykysiZMmIiIqNZKSUnBzz//jOLiYlG5j48PXnrpJTg7O5spMrI2TJiIiKhWOnfuHDZv3qy1iK6/vz+GDx8OmUxmpsjIGjFhIiKiWuf48eP47bfftMpDQ0MxePBg2Nry1xsZF+8oIiKqNQRBwP79+5GUlKS1r1WrVujXrx/XhSOTYMJERES1giAI2LFjB44fP661r3379oiOjua6cGQyTJiIiMjilZSUYMuWLfjzzz+19nXp0gXPPvsskyUyKSZMRERk0YqKirBhwwakpKRo7evduzciIyPNEBXVNUyYiIjIYj18+BBr165FZmamqFwqlWLAgAEIDw83U2RU1zBhIiIii5Sfn4+EhARkZ2eLym1tbTFkyBAEBwebKTKqi5gwERGRxVEoFFi1ahXu3r0rKpfJZBgxYgT8/PzMFBnVVUyYiIjIoty5cwerVq2CUqkUlTs7O2PkyJFo2LChmSKjuowJExERWYysrCwkJCSgoKBAVO7u7o6YmBh4eHiYKTKq65gwERGRRUhPT8fatWtRWFgoKvfy8sLIkSPh5uZmpsiImDAREZEFuHjxIjZs2ICSkhJReePGjfHSSy/B0dHRTJERPcKEiYiIzOrMmTPYsmULBEEQlTdr1gxDhw6Fvb29mSIj+gcTJiIiMpsjR45g165dWuUtWrTAwIEDuYguWQyrWKHw+vXr+PLLL9GzZ0/4+fnB3t4eDRs2xKBBg3Ds2DGt+rNmzYJEIin3lZGRUfNvgoioDhEEAb///rvOZKl169YYNGgQkyWyKFZxNy5evBiffvopAgMD0bNnT3h5eSE1NRWbN2/G5s2bsXr1agwdOlTruNjYWAQEBGiVu7u7mz5oIqI6Sq1WY/v27Th58qTWvg4dOqBbt25cF44sjlUkTO3atUNSUhI6d+4sKj9w4AC6deuG8ePHY8CAAZDJZKL9cXFxiIqKqsFIiYjqtpKSEvzvf//D33//rbWve/fu6NChgxmiIqqcVXTJvfDCC1rJEgA8++yz6NKlC3JycnDu3DkzREZERKUKCwuxdu1arWRJIpGgb9++TJbIollFC1NF7OzsAEBnX/j+/ftx7NgxSKVSBAcHo3v37nBxcanpEImIrF5BQQHWrFmDq1evisptbGzwwgsvoEWLFmaKjEg/Vp0wXblyBXv27IGPj4/OFa1nzpwp2nZ3d8eiRYswatSoSs+tUqmgUqk022Wn8Cciokdyc3ORkJCAW7duicrt7OwwbNgwNGvWzEyREenPKrrkdCkqKkJMTAxUKhU+/fRT2NjYaPa1atUKS5cuxeXLl1FQUID09HQsXrwYEokEcXFx2LJlS6Xnnzt3LuRyuebl6+tryrdDRFQr5eTkYNmyZVrJkqOjI0aNGsVkiWoNiVB2pjAroFarERMTg9WrV2Ps2LH44Ycf9Dpu79696NGjB5588kn8+eefFdbV1cLk6+sLhULB6fuJiADcvHkTCQkJyMvLE5W7urpi5MiR8Pb2NlNkRFVndQmTWq3Gyy+/jBUrVmDkyJFYsWIFpFL9G9KCg4Nx6dKlKic+SqUScrmcCRMREYCrV69i9erVePjwoajcw8MDMTExnL6Fah2r6pJTq9UYPXo0VqxYgeHDh2P58uVVSpYAwNPTEwDw4MEDU4RIRGT10tLSsGrVKq1kqUGDBhg9ejSTJaqVrGbQd2mytHLlSgwdOhSrVq0SjVvSR35+Pv7++284OztrEiciItLf33//jU2bNkGtVovK/fz8MHz4cDg4OJgpMqLqsYqEqbQbbuXKlXjxxReRkJBQbrKUm5uLGzduICQkRFReUFCAsWPHIjc3F6NHj+aU/EREehIEAXfu3MG5c+dw4MABrf3BwcF48cUXNdO8ENVGVpEVzJ49GytWrICLiwtCQkLw0UcfadUZMGAAIiIicPfuXYSFhSEyMhLNmzdHw4YNcfPmTezZswfXrl1DeHg4PvvsMzO8CyKi2kOtVuPq1atITk5GcnIy7t27p7NeeHg4+vfvX+UWfyJLYxUJU+liuXl5efj444911gkICEBERAQ8PDwwYcIEHD9+HNu3b0dOTg4cHR3RvHlzTJ48GRMnToSjo2MNRk9EVDuoVCqkpaUhOTkZqampKCgoqLB+ZGQkevXqxXXhyCpY3VNy5sKn5IjIGimVSiQnJyMlJQXp6ekoKSnR67hOnTohKiqKyRJZDatoYSIiIuMQBAE3b97ExYsXkZKSghs3buh9rKurK0JDQ9GqVSs0adLEhFES1TwmTEREdVxJSQkyMjI045GqstRTw4YNERISgtDQUPj4+LBFiawWEyYiojqooKAAqampSE5OxqVLl1BYWKjXcVKpFE2bNtUkSXK53MSRElkGJkxERHXEvXv3NOORMjMzoe8QVgcHBwQHByM0NBSBgYGcS4nqJCZMRERWShAEXL9+XdPVdvv2bb2PdXd3R2hoKMLCwuDr68tpAajOY8JERGRFioqKcPnyZU1LUn5+vt7HNmnSRNPV5uXlxfFIRI9hwkREVMvl5eUhJSUFKSkpSEtLQ3FxsV7H2draolmzZggNDUVISAhcXFxMHClR7cWEiYiolildiqS0q+3atWt6H+vs7KxpRWrWrBmXKyHSExMmIqJaQK1W48qVK5okKScnR+9jvby8NElS48aNIZVKTRgpkXViwkREZKFUKhUuXbqk6W57+PChXsdJJBL4+fkhNDQUoaGh8PDwMHGkRNaPCRMRkQVRKBSipUjUarVex9nb2yMoKAihoaEICgqCk5OTiSMlqluYMBERmZEgCMjOztZ0tWVnZ+t9rJubm6arLSAgALa2/CedyFT400VEVMOKi4s1S5GkpKRUeSmS0q62hg0b8tF/ohrChImIqAY8ePAAqampSElJMWgpktJH/7kUCZF5MGEiIjKR0qVIkpOTceXKlSotRRISEoKQkBAEBQVBJpOZOFIiqgwTJiIiI1Gr1aKlSO7cuaP3sfXq1dN0tfn5+fHRfyILw4SJiKgaCgsLNUuRpKamVnkpktIkydPTk+ORiCwYEyYioioqXYokOTkZly9frtJSJIGBgZruNi5FQlR7MGEiIqqEIAi4ffu2pqvt+vXreh/LpUiIrAMTJiKq80pKSpCfn4/c3Fzk5eUhLy9P9PebN2/i/v37ep/Py8tL09XWuHFjdrURWQEmTERktQoLC7WSH11/f/DgQbWuI5FI4O/vr3n0n0uREFkfJkxEVKsIgoCCggK9EiF95zoyhL29PYKDgxESEoLg4GA4Ojqa7FpEZH5MmIjIIpR2iz2e8DyeBD2+re/6asbm5uam6WoLCAiAjY2NWeIgoprHhImITKq0W6xsIvT4mKHc3Nxqd4sZg1QqhYuLi+jl6uoKFxcXNG7cmEuRENVhTJiIqMoe7xarrEXIlN1i+rKzs9MkPmUTocf/7uTkxISIiHRiwkREGmq1usIxQY+/SkpKzB0uHB0dNcmOq6srnJ2dRdulCRGXFiGi6mLCRFTLqNVqlJSUoLi4WO8/dZUVFhZqPUpflVmqTUUqlYoSn/Jag1xcXDiGiIhqTJ1PmE6cOIGZM2fi8OHDKCoqQnh4OKZMmYIhQ4aYOzSyAIIg6ExQqpKsVPSnIefVdwFXS8NuMSKqzep0wpSYmIjo6Gg4ODhg2LBhcHV1xcaNGzF06FBcvXoVb731lrlDtHqCIGgSh5KSEk1yYuh2RUmIoYkNVezxbrGKEiF2ixFRbSYRaut/V6upuLgYYWFhuHbtGo4ePYqIiAgAgEKhQLt27ZCRkYGUlBT4+/vrdT6lUgm5XA6FQgE3NzcTRq5NEAStxMMYyUdF2+X9varnqqO3n8XT1S32ePLDbjEiqmvqbAvT77//jrS0NIwePVqTLAGAXC7H+++/j7i4OKxYsQIzZswwS3yFhYVY9eOPjxKL4mKoS0oe/alWQ/3/rR/q0u2SEkAQIAGA/09AJKWJiCCI/15aR1c9PfeVd52KrmsDwEaPmB4/t77XLRuDTtXo4hH0PbYmrlHJdSUSCWykUkikUkhtbCCVSiGVSP75u1T6qM7/b9vb20Mmk8FeJoPM3h4yBwfI7O1hZ28PzVnz8h69HvPw/193DI/aquiV+FfzPwdGuUYl+2viGjqvo+uYMmU6Y9PjPJW+JxNd2xT/GSy3q1pXeTl1dZ6jKucthzHOq+85gsaNg42Dg96xGUudTZiSkpIAAD179tTaFx0dDQDYt29fTYYkVlwM74ULzXd9qhPUAAr+/0VEVBs0Gz2aCVNNSk1NBQAEBwdr7WvYsCFcXFw0dXRRqVRQqVSabaVSadT4pLZ19qshIiKyOFJzB2AuCoUCwKMuOF3c3Nw0dXSZO3cu5HK55uXr62vU+GyYMBEREVkM/lY20LRp0zBlyhTNtlKpNG7SZIrHqiUSQCKBRCp99GfZbemj/Ll0G/8/3qWiOmXPpTlGKn00Buax7dJ6Zc8lOqb0emWO0YrhsTqi6+n63HSNa9D1+egzTgF6jmeoyrGWHgs9+vwq+ZnUayqEyupYwDX0UWkceoxF0TqHPsfocy0d56n0Wia6dpXG9TyunJ/Ncn9mq1he7k++sc5v4jglZmpQqLMJU2nLUnmtSEqlEvXq1Sv3eJlMZtLHpCUSCbofOKAzmahKAiORSv85loiIiAxSZxOm0rFLqampeOqpp0T7srOzkZeXh3bt2pkjNA3HRo3Men0iIiJ6pM6OYercuTMAYNeuXVr7du7cKapDREREdVudnrgyNDQU169fL3fiyuTkZAQEBOh1PnNOXElERESmVWe75GxtbREfH4/o6Gh06tRJtDRKZmYmFixYoHeyRERERNatzrYwlTp+/LjOxXeHDh1apfOwhYmIiMh61fmEyViYMBEREVmvOjvom4iIiEhfTJiIiIiIKsGEiYiIiKgSTJiIiIiIKsGEiYiIiKgSTJiIiIiIKsGEiYiIiKgSdXamb2Mrnc5KqVSaORIiIiKqKldXV0gkknL3M2EyktzcXACAr6+vmSMhIiKiqqps4mnO9G0karUaWVlZFWaokZGROHHiRJX2KZVK+Pr64urVq7VqBvGK3qslX8vQc1X1OH3r61OvLt1XQM3dW7yvKq5jbfdWXbqvDDnWWPeWJd9XbGGqIVKpFE2aNKmwjo2NTblfdEX7AMDNza1W/eNT2fux1GsZeq6qHqdvfX3q1aX7Cqi5e4v3VcV1rO3eqkv3lSHHGuveqs33FQd916DXX3/doH21UU2+H2Ney9BzVfU4fevrU68u3VdAzb0n3lcV17G2e6su3VeGHGuse6s231fskrNwXNSXTIH3FZkK7y0yBUu4r9jCZOFkMhlmzpwJmUxm7lDIivC+IlPhvUWmYAn3FVuYiIiIiCrBFiYiIiKiSjBhIiIiIqoEEyYiIiKiSjBhsiKbNm1Cjx494OHhAYlEgoyMDHOHRFZg7ty5aNu2LVxdXdGgQQMMGTKE9xZV2xdffIEnnngCLi4ucHd3R9euXXHs2DFzh0VWZvz48ZBIJPjqq6+qfS4mTFYkPz8fnTp1wuzZs80dClmRffv2YdKkSTh27Bh27NiBe/fuoVevXiguLjZ3aFSL+fv7Y+HChTh79iwOHz6MoKAgREdH4+7du+YOjazEr7/+iiNHjqBRo0ZGOR+fkrNCf/31F8LDw5Geno6AgABzh0NWJj09Hc2aNcPZs2fRsmVLc4dDVqJ0np2kpCR07tzZ3OFQLXfz5k20bdsW27dvR9++ffH2229j4sSJ1TonW5hqUEJCAsaNG4e2bdtCJpNBIpFg+fLlFR5z4sQJ9O7dG+7u7nB2dsbTTz+N9evX10zAVCvU9H2lUCgAAB4eHtUNnSxYTd5XhYWF+OGHH1CvXj2Eh4cb6R2QpaqJe2v06NGYPHmyUe8nriVXg6ZPn47MzEx4enrCx8cHmZmZFdZPTExEdHQ0HBwcMGzYMLi6umLjxo0YOnQorl69irfeequGIidLVpP3VUlJCd5++2307t270rUTqXarifvqwIED6NWrFwoKCtCwYUPs3r2biXgdYOp766uvvkJ+fr7xf0cKVGN2794tZGRkCIIgCHPnzhUACMuWLdNZt6ioSAgMDBRkMplw+vRpTfn9+/eFkJAQwd7eXnOuss6dOycAENLT0438DsgS1dR9pVarhTFjxgjBwcHCrVu3jP02yMLUxH314MEDITU1VTh69KjwyiuvCM2aNRNu375tirdDFsSU99aFCxcEb29v0e8/f39/YfHixdWOm11yNah79+7w9/fXq+7vv/+OtLQ0jBgxAhEREZpyuVyO999/H4WFhVixYoWJIqXapCbuK0EQMGHCBOzZswd79+6Fl5eXscInC1UT95WjoyOCgoLQvn17xMfHQyqVYtmyZcZ6C2ShTHlvHT16FLdv30ZQUBBsbW1ha2uLzMxMvPHGG6LjDcEuOQuVlJQEAOjZs6fWvujoaACPnl4iqgpD7itBEPD6669j27Zt2LdvH3x9fU0eJ9Uuxvr3ShAEqFQqo8ZGtVtV760BAwagbdu2WvXi4uIwevToasXChMlCpaamAgCCg4O19jVs2BAuLi6aOqXu3buHK1euIC0tDQBw/vx53L9/H35+fhwXQAAMu69ef/11rFmzBlu3boWjoyOys7MBPBr0bW9vb/qgyeIZcl9NnToV/fr1Q5MmTXDv3j188803uHbtGgYNGlQjMVPtUNV7y93dHe7u7qJ6dnZ28PHxQVBQULViYcJkoUqfRJLL5Tr3u7m5aeqU2rJliyiDfv755wEAy5YtQ1xcnGkCpVrFkPvq22+/BQA8++yzovLExERERUUZP0iqdQy5r7KysjBs2DDcunULHh4eiIyMxIEDB9C8eXOTx0u1hyH3lqkwYbIicXFxTIzI6ARO1UYmsGrVKnOHQHWEsVYm4KBvC1WaTZeXOZdO8kZUFbyvyBR4X5GpWNK9xYTJQpX215bt9weA7Oxs5OXl6ezTJaoI7ysyBd5XZCqWdG8xYbJQpUsD7Nq1S2vfzp07RXWI9MX7ikyB9xWZiiXdW0yYLFS3bt3QrFkzrF69GmfOnNGUKxQKfPLJJ7C3t8eoUaPMFyDVSryvyBR4X5GpWNK9xcV3a1B8fDwOHjwIADh37hxOnTqFDh06aB517NixI8aMGaOpX9508JmZmViwYAGXRiEAvK/INHhfkanU2nur2nOFk95iY2MFAOW+YmNjtY45duyY8Nxzzwlubm6Co6Oj0K5dO2Ht2rU1HzxZLN5XZAq8r8hUauu9xRYmIiIiokpwDBMRERFRJZgwEREREVWCCRMRERFRJZgwEREREVWCCRMRERFRJZgwEREREVWCCRMRERFRJZgwEREREVWCCRMRERFRJZgwEREREVWCCRORgQICAiCRSCCRSLBhw4Zy63Xv3h0SiQTLly+vueAMEBUVBYlEgqSkJHOHYnJbt27Fs88+Czc3N813aIz3nZGRAYlEgoCAgGqfq66oS/cd1W5MmIiM4D//+Q+Ki4vNHQbp4cyZMxg0aBCOHDmCp59+GqNGjUJsbCwaNmxY6bGlSXJGRobpAyWDLF++HBKJBHFxceYOhayMrbkDIKrtnJyckJKSgvj4eLz22mvmDocqsXnzZhQVFeH999/Hxx9/bNRzN27cGBcuXICdnZ1Rz2vNVq5ciQcPHsDPz8/coRBViC1MRNX0xhtvAABmz56NBw8emDkaqsyVK1cAAMHBwUY/t52dHcLCwhAYGGj0c1srPz8/hIWFwcnJydyhEFWICRNRNfXu3RudO3fGjRs38MUXX+h9XFxcXIVjm8rrWni8XKFQYMqUKQgICICDgwOCg4Px6aefQq1WAwCuX7+OcePGwdfXFzKZDKGhoVi8eHGlse3btw89e/aEh4cHnJyc0K5dO6xatarCY/bu3YsXXngBPj4+sLe3h7e3NwYOHIgjR47orF86dggAli1bhmeeeQZyubxKXV7FxcX47rvv8K9//QtyuVzzGUyePBnXr18X1Z01axYkEgmWLVsGABg9erQmhqioqAqvU/qZZ2ZmAgCaNm2qOfbx8TcVjWF6/P0mJCSgXbt2cHFxgZeXF4YPH65J5ARBwFdffYWIiAg4OzvD09MTcXFxuHXrVrnxpaSkYNy4cQgMDISDgwPkcjk6deqEhIQEfT5Gkcfvy7Nnz+KFF16Al5cXHB0d0bJlSyxatAglJSXlHr927Vp069YNHh4ekMlk8Pf3x8svv4yUlBSd9csbw/R4HOnp6YiJiUHDhg0hk8kQGBiI6dOnQ6VSiY4JCAjA6NGjAQArVqwQfUePf8cKhQLTp09HeHg4nJ2dIZPJ0KhRI3To0AEzZsxAUVFRlT83qgMEIjKIv7+/AEA4cOCAcPToUQGA4ObmJty5c0dUr1u3bgIAYdmyZaLy2NhYneWlli1bJgAQYmNjdZb3799faN68ueDt7S0MGjRI6Nmzp+Do6CgAECZOnChcunRJaNiwoeDr6ysMGTJE6NKli2BjYyMAEObNm6d1vc6dOwsAhMmTJwtSqVRo0aKFMGzYMKFTp06CVCoVAAhTpkzRGetbb70lABCkUqnQrl074cUXXxTat28vSCQSwcbGRli6dKnWMQA0sUqlUqFjx47C8OHDhfbt2wsZGRnlf/D/7+HDh0L37t0FAIKDg4PQq1cvYejQoYKvr68AQPD09BROnjypqf+///1PiI2NFQIDAwUAQocOHYTY2FghNjZWmDt3boXXOnDggBAbGys4OzsLAIRBgwZpjo2NjRUuXLggCIIgpKenCwAEf3//ct/ve++9J9ja2gpdu3YVBg8eLPj5+QkABF9fX+HevXvCkCFDBAcHB+G5554TBg4cKHh7ewsAhJYtWwoqlUrrvOvXrxccHBwEAEJYWJgwcOBAoWvXrppYR48eXeln+bjS+3L8+PGCg4ODEBAQIAwdOlTo2bOnYG9vLwAQBg8eLKjVatFxarVaGDVqlABA8/6GDRsmhISECAAEJycn4bffftO6Xul9l5iYqDOON954Q3BzcxP8/f2FIUOGCN27d9fc5wMGDBAd89ZbbwkdOnQQAAiBgYGi76j0O87PzxeefPJJAYDg5eUl9O3bVxg2bJgQFRUlNGzYUAAg5OTkVOkzo7qBCRORgR5PmARBEF544QUBgPDmm2+K6pkqYQIg9O3bV8jPz9fsO3nypGBra6tJeF577TWhqKhIs3/z5s2axO7x4wThn19cAIRPPvlEtC8pKUnzS2rHjh2ifT/88IMAQAgKChLOnj0r2rdv3z7B1dVVsLe3F1JSUkT7Sq/l5uYmHDlyROdnUJGpU6dqfjGmp6drygsLC4VXXnlFACA0bdpUK8mo7HOvSOl3/vj1HqdPwlS/fn3hzJkzmvIHDx4IHTt2FAAI4eHhQmBgoChhvH37thAUFCQAEBISEkTn/PPPPwWZTCY4ODgIGzduFO3LyMgQwsPDBQDCihUr9H6PpZ8PAGHChAmi++evv/4SvLy8BADCd999Jzru22+/1SSqp0+f1pSr1Wph5syZAgDB3d1duHXrlui4yhImAMJ//vMfobi4WLPv3LlzmoTw8OHDouPK+7kptWLFCgGA0KtXL6GwsFC0r6SkREhKStKZmBKxS47ISD755BPY2trim2++0XTdmJKLiwvi4+NFYz/atGmD3r17Q61WIy8vD1988QVsbf95tqN///4IDw+HUqnEH3/8ofO8rVu3xrRp00RlnTt3xoQJEwAAn3/+uaZcrVZj1qxZAB51xbRs2VJ0XKdOnfDBBx+gsLAQ33//vc7rvf3223j66af1f+MAHj58iK+//hoA8MUXX4i6wOzs7PDf//4XDRo0QHp6eoVTPpjD7Nmz0apVK822o6MjpkyZAgA4d+4c/vvf/8Lf31+z39PTE+PHjwfwqNvzcR9//DFUKhU++ugjvPDCC6J9/v7+WLJkCQDgv//9b5Xj9PHxweeffy66f5544gnMmDEDgPg+AIAFCxYAAGbMmIGIiAhNuUQiwcyZM9GyZUvcv38fP/74Y5XieOqppzBnzhzY2Nhoyp588knExMQAAPbs2VOl8928eRMA0KNHD63B+VKpFJ07d4a9vX2Vzkl1AxMmIiMJDQ3Fyy+/DJVKhQ8++MDk13vqqafg7e2tVV46mLlLly5wcHAod39WVpbO844aNUpneWxsLADg4MGDmjEsp0+fRlZWFgIDA/HUU0/pPK507Mjhw4d17h88eLDO8or88ccfyMvLg4eHB/r27au138nJCcOGDQMAJCYmVvn8ptS7d2+tstLvxNbWFj179ix3/+PfmVqtxm+//QYAGDp0qM5rtW3bFi4uLjh9+jQePnxYpTiHDBmi8/4pvQ9SU1M18Vy7dg1paWmi/Y+TSCSasUVV/T769OmjGfv1uObNmwOA1li1ykRGRgIA5s+fj5UrV+LevXtVOp7qLiZMREY0a9YsODk54aeffsKff/5p0muV9xi2i4tLhftdXV0BoNxfoE2bNq2wvKCgAHfv3gUAXL58GQCQlpYmGmD7+Ktdu3YAgNu3b+s8ryGTPJb+kiwvVgCaJ9Wq+gvV1HR9L6XfmY+Pj6hFp5Su7+zu3btQKpUAAF9fX52fvVQqRV5eHtRqteY701d5n62rqyvq168P4FGiBPzzGdevXx9ubm46jzP0+yjvPi69TlUTwaioKEydOhW3bt1CbGwsPD09Nf/Z+eWXXzQPTBCVxXmYiIzIx8cHb7zxBubOnYtp06Zh27ZtBp+rsn+4pdKK/79T2f7qEAQBwD8xNmzYENHR0RUe4+npqbPc0dHRuMFZuIq+l6p8Z4/fH7padcqSyWR6n1tfpfeBKZniPp43bx5ee+01bN26FQcPHsShQ4ewbNkyLFu2DJGRkUhMTISzs7PRr0u1GxMmIiObOnUqfvjhB2zfvh379+8vt17pOInc3Fyd+2tiHJQu6enpOstLH/V3cHDQtDD4+voCeNSyUJNLvzRu3BhA+bEC/7R+lda1Np6ennB0dERBQQEWLFhQbkJqqPI+29zcXE1rVZMmTQD88xmXtnrpamWytO8jICAAkyZNwqRJkwAAJ06cwMiRI3HixAnMnz8fH374oZkjJEvDLjkiI5PL5Xj//fcBAO+++2659Up/cVy4cEFrnyAImvEpNa28uXtWrlwJAOjYsaOm2ygyMhKenp44f/48/v777xqLsXRszr1797Blyxat/QUFBVi7di2AR2O5jKU0ybWEZXBsbGzQo0cPAMD69euNfv6ff/5Za54jAJr5uIKCgjT3cJMmTTRdbroSZ0EQNOXG/D50MfQ7ioyM1DzYcObMGWOHRVaACRORCbz++uvw8/PDsWPHyp24sXv37gAe/QI6f/68pryoqAhTp07FiRMnaiTWsk6ePIn58+eLyg4ePKh5Ku3NN9/UlNvZ2WHmzJkQBAEDBw7EwYMHtc5XUlKC33//HUePHjVajA4ODnj99dcBAG+99ZaoNa6oqAhvvPEGsrOz0bRpU4MGlZentEWlJpPDisycORP29vZ45513sGLFCp3duH/99Rc2bdpU5XNnZWXh7bffFk1SeeHCBcyePRuA+D4AHj3tCABz5szB2bNnNeWCIOCjjz7CmTNn4O7ujrFjx1Y5lqoo/Y4e/5l63P/+9z/s379f67MqKirCjh07AED0lCJRKXbJEZmATCbD7NmzERcXV+5yKR06dED//v3xyy+/oG3btujYsSMcHR1x6tQpKJVKvPHGG1i0aFENRw5MnjwZ06ZNw8qVK9GyZUtkZWXhwIEDUKvVeOONN7Se8po4cSKuXLmCzz77DM8++yyeeOIJBAUFwdHREdnZ2Thz5gzu37+Pb7/9tsrTB1Tkww8/xB9//IG9e/eiefPm6NKlC1xdXXHkyBFcuXIF9evXx88//2zUR8QHDRqExMREjBw5Ej179kS9evUAAO+88w5CQ0ONdh19tWnTBgkJCYiLi0NcXBymT5+OFi1awMvLC/fu3cO5c+dw7do1DB06VGvagcq89tpriI+Px7Zt29C+fXvk5OQgMTERhYWFGDhwoGaqg1Ljxo3D4cOHsWrVKrRt2xadO3eGt7c3Tp06heTkZDg6OmL16tXw8vIy5keg5emnn0ajRo1w+vRptGnTBuHh4bCzs0NoaCjeeecd7Nu3D4s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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "linewidth = 3\n", + "plt.plot(T_range, diffrax_times, label=\"Diffrax\", color=\"grey\", linewidth=linewidth)\n", + "plt.plot(T_range, thermox_times, label=\"Thermox\", color=\"firebrick\", linewidth=linewidth)\n", + "\n", + "fontsize = 16\n", + "plt.xlabel(\"Number of time points\", fontsize=fontsize)\n", + "plt.ylabel(\"Runtime (s)\", fontsize=fontsize)\n", + "\n", + "legend_fontsize = 14\n", + "plt.legend(frameon=False, fontsize=legend_fontsize)\n", + "plt.xscale(\"log\")\n", + "# plt.yscale(\"log\")\n", + "\n", + "ticks_fontsize = 14\n", + "plt.xticks(fontsize=ticks_fontsize)\n", + "plt.yticks(fontsize=ticks_fontsize)\n", + "\n", + "# Remove top and right spines\n", + "plt.gca().spines[\"top\"].set_visible(False)\n", + "plt.gca().spines[\"right\"].set_visible(False)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And there you have it! `thermox` is roughly constant with respect to the number of time points, because the computation is dominated by the diagonalisation that is performed at initialisation. For a small number of time points, performance is comparable, but `thermox` really starts to shine for $\\sim 10000$ time steps, where we get $\\sim 800\\times$ speedup with respect to `diffrax`, as well as being exact!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "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": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/thermodynamic_linear_algebra.ipynb b/examples/thermodynamic_linear_algebra.ipynb new file mode 100644 index 0000000..e368116 --- /dev/null +++ b/examples/thermodynamic_linear_algebra.ipynb @@ -0,0 +1,236 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import thermox\n", + "import jax\n", + "import jax.numpy as jnp\n", + "from jax.scipy.linalg import solve, inv, expm" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this notebook we show how to run three basic thermodynamic algorithms, using functions from `thermox.linalg`:\n", + "\n", + "1. Thermodynamic linear solver: find $x$ such that $Ax = b$,\n", + "2. Thermodynamic matrix inverse: find $A^{-1}$,\n", + "3. Thermodynamic matrix exponential: find $\\exp{(A)}$.\n", + "\n", + "These algorithms are all based on extracting statistical information from the multivariate Ornstein-Uhlenbeck process, defined as\n", + "$$ dx = - A(x - b) dt + \\mathcal{N}(0, 2D) $$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us start with solving a linear system $Ax = b$. In this case, $D = \\mathbb{I}$." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "key = jax.random.PRNGKey(42) # random PRNG key\n", + "dimension = 50 # problem size\n", + "mean = jnp.zeros(dimension) # mean vector\n", + "n = 2 * dimension # number of degrees of freedom\n", + "A = jax.random.normal(key, shape=(dimension, 2*dimension,))\n", + "A = (A @ A.T) / n # random positive-semi definite matrix from the Wishart distribution\n", + "b = jax.random.normal(key, shape=(dimension,))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "x_s = thermox.linalg.solve(A, b)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We know look at the absolute error $||x_s - x^*||$, using `scipy`'s `solve` function to get the exact solution $x^*$:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "||x_s - x*|| = 0.14343248\n" + ] + } + ], + "source": [ + "print(r\"||x_s - x*|| = \", jnp.linalg.norm(x_s - solve(A,b)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Thermodynamic matrix inverse\n", + "\n", + "This time, no need to define the vector $b$. The matrix is simply defined as the continuous-time correlation matrix\n", + " $$A^{-1} \\approx C(t,t') = \\langle x(t) x(t')\\rangle$$" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "thermo_inv = thermox.linalg.inv(A)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "||A^{-1} - C(t,t')|| = 1.7223996\n" + ] + } + ], + "source": [ + "print(\"||A^{-1} - C(t,t')|| =\", jnp.linalg.norm(inv(A) - thermo_inv))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's increase the number of samples to get a better inverse and look at the error again." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "||A^{-1} - C(t,t)|| = 0.5807177\n" + ] + } + ], + "source": [ + "thermo_inv = thermox.linalg.inv(A, num_samples=100000)\n", + "print(\"||A^{-1} - C(t,t)|| =\", jnp.linalg.norm(inv(A) - thermo_inv))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It went down! And gathering 10 times more samples only took about twice the time." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Thermodynamic matrix exponential\n", + "\n", + "Let us now consider matrix exponentials. Due to the way we obtain the matrix exponentials, the negative exponential $\\exp{(-A)}$ is more easily gathered. This is because the autocovariance function is equal to $\\exp{(-A)}$, when we have $A$ as the drift term of the SDE.\n", + "\n", + "$$ C(t+\\tau, t) = \\frac{1}{T} \\int_{t_0}^{t_0+T} dt x(t+\\tau) x^\\intercal(t) = \\exp{(-A \\tau)} $$" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "thermo_negexp = thermox.linalg.expnegm(A)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "||exp(-A) - C(t+tau,t)||= 0.6535645\n" + ] + } + ], + "source": [ + "print(r\"||exp(-A) - C(t+tau,t)||=\", jnp.linalg.norm(expm(-A) - thermo_negexp))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We once again increase the number of samples, which brings the error down." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "||exp(-A) - C(t+tau,t)||= 0.21104243\n" + ] + } + ], + "source": [ + "thermo_negexp = thermox.linalg.expnegm(A, num_samples=100000, dt=1)\n", + "print(r\"||exp(-A) - C(t+tau,t)||=\", jnp.linalg.norm(expm(-A)- thermo_negexp))" + ] + } + ], + "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": "3.10.13" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..21ebe00 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,28 @@ +[project] +name = "thermox" +version = "0.0.1" +description = "OU Processes and Linear Algebra with JAX" +readme = "README.md" +requires-python =">=3.9" +license = {text = "Apache-2.0"} +authors = [ + {name = "Sam Duffield", email = "sam@normalcomputing.ai"}, + {name = "Kaelan Donatella", email = "kaelan@normalcomputing.ai"}, +] +keywords = ["jax", "linear algebra", "ou process", "stochastic process"] +classifiers = [ + "Programming Language :: Python :: 3", + "Topic :: Scientific/Engineering :: Mathematics", + "License :: OSI Approved :: Apache Software License", +] +dependencies = ["jax>=0.4.0", "jaxlib>=0.4.0", "fmmax>=0.8.0"] + +[project.optional-dependencies] +test = ["pre-commit", "pytest-cov", "ruff", "optax", "mypy"] + +[tool.setuptools] +packages = ["thermox"] + +[tool.ruff] +[tool.ruff.lint.per-file-ignores] +"__init__.py" = ["F401", "F821"] \ No newline at end of file diff --git a/tests/test_linalg.py b/tests/test_linalg.py new file mode 100644 index 0000000..ad44be7 --- /dev/null +++ b/tests/test_linalg.py @@ -0,0 +1,37 @@ +import jax +from jax import numpy as jnp + +import thermox + + +def test_linear_system(): + A = jnp.array([[3, 2], [2, 4.0]]) + b = jnp.array([1, 2.0]) + + x = thermox.linalg.solve(A, b, num_samples=10000, dt=0.1, burnin=0) + + assert jnp.allclose(A @ x, b, atol=1e-1) + + +def test_inv(): + A = jnp.array([[3, 2], [2, 4.0]]) + + A_inv = thermox.linalg.inv(A, num_samples=10000, dt=0.1, burnin=0) + + assert jnp.allclose(A @ A_inv, jnp.eye(2), atol=1e-1) + + +def test_expnegm(): + A = jnp.array([[3, 2], [2, 4.0]]) + + expnegA = thermox.linalg.expnegm(A, num_samples=10000, dt=0.1, burnin=0) + + assert jnp.allclose(expnegA, jax.scipy.linalg.expm(-A), atol=1e-1) + + +def test_expm(): + A = jnp.array([[-0.4, 0.1], [0.5, -0.3]]) + + expA = thermox.linalg.expm(A, num_samples=100000, dt=0.1, burnin=0, alpha=1.0) + + assert jnp.allclose(expA, jax.scipy.linalg.expm(A), atol=1e-1) diff --git a/tests/test_log_prob.py b/tests/test_log_prob.py new file mode 100644 index 0000000..f8508d8 --- /dev/null +++ b/tests/test_log_prob.py @@ -0,0 +1,158 @@ +import jax +from jax import numpy as jnp +import optax + +import thermox + + +def test_log_prob_numeric_identity_diffusion(): + A_true = jnp.array([[3, 2, 1], [2, 4.0, 2], [1, 2, 5.0]]) + b_true = jnp.array([1, 2.0, 3]) + D_true = jnp.eye(3) + + nts = 1000 + ts = jnp.sort(jax.random.uniform(jax.random.PRNGKey(0), (nts,)) * 1000.0) + x0 = jax.random.normal(jax.random.PRNGKey(0), b_true.shape) + + rk = jax.random.PRNGKey(0) + samps = thermox.sample(rk, ts, x0, A_true, b_true, D_true) + + def transition_mean(x0, dt): + return b_true + jax.scipy.linalg.expm(-A_true * dt) @ (x0 - b_true) + + @jax.jit + def transition_cov_integrand(s, t): + exp_A_st = jax.scipy.linalg.expm(A_true * (s - t)) + exp_A_T_st = jax.scipy.linalg.expm(A_true.T * (s - t)) + return exp_A_st @ D_true @ exp_A_T_st + + def transition_cov_numeric(dt): + s_linsp = jnp.linspace(0, dt, 1000) + evals = jax.vmap(lambda s: transition_cov_integrand(s, dt))(s_linsp) + return jax.scipy.integrate.trapezoid(evals, s_linsp, axis=0) + + def transition_log_prob_numeric(xt, x0, t): + mean = transition_mean(x0, t) + cov = transition_cov_numeric(t) + return jax.scipy.stats.multivariate_normal.logpdf(xt, mean, cov) + + log_probs_numeric = jax.vmap( + lambda xtp1, xt, dt: transition_log_prob_numeric(xtp1, xt, dt) + )(samps[1:], samps[:-1], ts[1:] - ts[:-1]) + + log_prob = thermox.log_prob(ts, samps, A_true, b_true, D_true) + + assert jnp.isclose(log_prob, log_probs_numeric.sum(), rtol=1e-2) + + +def test_log_prob_numeric(): + A_true = jnp.array([[3, 2, 1], [2, 4.0, 2], [1, 2, 5.0]]) + b_true = jnp.array([1, 2.0, 3]) + D_true = jnp.array([[1, 0.3, -0.1], [0.3, 1, 0.2], [-0.1, 0.2, 1.0]]) + + nts = 1000 + ts = jnp.sort(jax.random.uniform(jax.random.PRNGKey(0), (nts,)) * 1000.0) + x0 = jax.random.normal(jax.random.PRNGKey(0), b_true.shape) + + rk = jax.random.PRNGKey(0) + samps = thermox.sample(rk, ts, x0, A_true, b_true, D_true) + + def transition_mean(x0, dt): + return b_true + jax.scipy.linalg.expm(-A_true * dt) @ (x0 - b_true) + + @jax.jit + def transition_cov_integrand(s, t): + exp_A_st = jax.scipy.linalg.expm(A_true * (s - t)) + exp_A_T_st = jax.scipy.linalg.expm(A_true.T * (s - t)) + return exp_A_st @ D_true @ exp_A_T_st + + def transition_cov_numeric(dt): + s_linsp = jnp.linspace(0, dt, 1000) + evals = jax.vmap(lambda s: transition_cov_integrand(s, dt))(s_linsp) + return jax.scipy.integrate.trapezoid(evals, s_linsp, axis=0) + + def transition_log_prob_numeric(xt, x0, t): + mean = transition_mean(x0, t) + cov = transition_cov_numeric(t) + return jax.scipy.stats.multivariate_normal.logpdf(xt, mean, cov) + + log_probs_numeric = jax.vmap( + lambda xtp1, xt, dt: transition_log_prob_numeric(xtp1, xt, dt) + )(samps[1:], samps[:-1], ts[1:] - ts[:-1]) + + log_prob = thermox.log_prob(ts, samps, A_true, b_true, D_true) + + assert jnp.isclose(log_prob, log_probs_numeric.sum(), rtol=1e-2) + + +def test_MLE(): + A_true = jnp.array([[3, 2, 1], [2, 4.0, 2], [1, 2, 5.0]]) + b_true = jnp.array([1, 2.0, 3]) + D_true = jnp.array([[1, 0.3, -0.1], [0.3, 1, 0.2], [-0.1, 0.2, 1.0]]) + + nts = 300 + ts = jnp.linspace(0, 10, nts) + x0 = jnp.zeros_like(b_true) + + n_trajecs = 3 + rks = jax.random.split(jax.random.PRNGKey(0), n_trajecs) + + samps = jax.vmap(lambda key: thermox.sample(key, ts, x0, A_true, b_true, D_true))( + rks + ) + + A_sqrt_init = jnp.tril(jnp.eye(3) + jax.random.normal(rks[0], (3, 3)) * 1e-1) + b_init = jnp.zeros(3) + D_sqrt_init = jnp.eye(3) + + log_prob_true = thermox.log_prob(ts, samps[0], A_true, b_true, D_true) + log_prob_init = thermox.log_prob( + ts, samps[0], A_sqrt_init @ A_sqrt_init.T, b_init, D_sqrt_init @ D_sqrt_init.T + ) + + assert log_prob_true > log_prob_init + + # Gradient descent + def loss(params): + A_sqrt, b, D_sqrt = params + A_sqrt = jnp.tril(A_sqrt) + D_sqrt = jnp.tril(D_sqrt) + A = A_sqrt @ A_sqrt.T + D = D_sqrt @ D_sqrt.T + return -jax.vmap(lambda s: thermox.log_prob(ts, s, A, b, D))( + samps + ).mean() / len(ts) + + val_and_g = jax.jit(jax.value_and_grad(loss)) + + ps = (A_sqrt_init, b_init, D_sqrt_init) + ps_true = (jnp.linalg.cholesky(A_true), b_true, jnp.linalg.cholesky(D_true)) + + v, g = val_and_g(ps) + v_true, g_true = val_and_g(ps_true) + + assert v_true < v + for i in range(len(ps)): + assert jnp.all(jnp.abs(g_true[i]) <= jnp.abs(g[i]) * 1.5) + + n_steps = 20000 + neg_log_probs = jnp.zeros(n_steps) + + optimizer = optax.adam(1e-2) + opt_state = optimizer.init(ps) + + for i in range(n_steps): + neg_log_prob, grad = val_and_g(ps) + if jnp.isnan(neg_log_prob) or any([jnp.isnan(g).any() for g in grad]): + break + updates, opt_state = optimizer.update(grad, opt_state) + ps = optax.apply_updates(ps, updates) + neg_log_probs = neg_log_probs.at[i].set(neg_log_prob) + + A_recover = ps[0] @ ps[0].T + b_recover = ps[1] + D_recover = ps[2] @ ps[2].T + + assert jnp.allclose(A_recover, A_true, atol=1e0) + assert jnp.allclose(b_recover, b_true, atol=1e0) + assert jnp.allclose(D_recover, D_true, atol=1e0) diff --git a/tests/test_sampler.py b/tests/test_sampler.py new file mode 100644 index 0000000..14fb46f --- /dev/null +++ b/tests/test_sampler.py @@ -0,0 +1,22 @@ +import jax +from jax import numpy as jnp + +import thermox + + +def test_sample_array_input(): + key = jax.random.PRNGKey(0) + dim = 2 + dt = 0.1 + ts = jnp.arange(0, 10_000, dt) + + A = jnp.array([[3, 2], [2, 4.0]]) + b, x0 = jnp.zeros(dim), jnp.zeros(dim) + D = 2 * jnp.eye(dim) + + samples = thermox.sample(key, ts, x0, A, b, D) + + samp_cov = jnp.cov(samples.T) + samp_mean = jnp.mean(samples.T, axis=1) + assert jnp.allclose(A @ samp_cov, jnp.eye(2), atol=1e-1) + assert jnp.allclose(samp_mean, b, atol=1e-1) diff --git a/tests/test_utils.py b/tests/test_utils.py new file mode 100644 index 0000000..25f4673 --- /dev/null +++ b/tests/test_utils.py @@ -0,0 +1,60 @@ +from jax import numpy as jnp + +from thermox.utils import ( + handle_matrix_inputs, + ProcessedDriftMatrix, + ProcessedDiffusionMatrix, + preprocess, +) + + +def test_handle_matrix_inputs_arrays(): + A = jnp.array([[1, 3], [1, 4]]) + D = jnp.array([[9, 4], [4, 20]]) + + a, d = preprocess(A, D) + + A_star, D_star = preprocess(A, D) + + assert isinstance(A_star, ProcessedDriftMatrix) + assert isinstance(D_star, ProcessedDiffusionMatrix) + assert jnp.all(a.val == A_star.val) + + +def test_handle_matrix_inputs_processed(): + A = jnp.array([[1, 3], [1, 4]]) + D = jnp.array([[9, 4], [4, 20]]) + + a, d = preprocess(A, D) + + A_star, D_star = handle_matrix_inputs(a, d) + + assert isinstance(A_star, ProcessedDriftMatrix) + assert isinstance(D_star, ProcessedDiffusionMatrix) + assert jnp.all(a.val == A_star.val) + + +def test_handle_matrix_inputs_array_drift_processed_diffusion(): + A = jnp.array([[1, 3], [1, 4]]) + D = jnp.array([[9, 4], [4, 20]]) + + a, d = preprocess(A, D) + + A_star, D_star = handle_matrix_inputs(A, d) + + assert isinstance(A_star, ProcessedDriftMatrix) + assert isinstance(D_star, ProcessedDiffusionMatrix) + assert jnp.all(a.val == A_star.val) + + +def test_handle_matrix_inputs_array_diffusion_processed_drift(): + A = jnp.array([[1, 3], [1, 4]]) + D = jnp.array([[9, 4], [4, 20]]) + + a, d = preprocess(A, D) + + A_star, D_star = handle_matrix_inputs(a, D) + + assert isinstance(A_star, ProcessedDriftMatrix) + assert isinstance(D_star, ProcessedDiffusionMatrix) + assert not jnp.all(a.val == A_star.val) diff --git a/thermox/__init__.py b/thermox/__init__.py new file mode 100644 index 0000000..64a3b84 --- /dev/null +++ b/thermox/__init__.py @@ -0,0 +1,6 @@ +from thermox import linalg +from thermox.sampler import sample +from thermox.prob import log_prob +from thermox.utils import preprocess +from thermox.utils import ProcessedDriftMatrix +from thermox.utils import ProcessedDiffusionMatrix diff --git a/thermox/linalg.py b/thermox/linalg.py new file mode 100644 index 0000000..6d7a87a --- /dev/null +++ b/thermox/linalg.py @@ -0,0 +1,159 @@ +import jax +import jax.numpy as jnp +from thermox.sampler import sample, sample_identity_diffusion +from jax.lax import fori_loop +from jax import Array + + +def solve( + A, + b, + num_samples: int = 10000, + dt: float = 1.0, + burnin: int = 0, + key: Array = None, +) -> Array: + """ + Obtain the solution of the linear system + + Ax = b + + by collecting samples from an Ornstein-Uhlenbeck + process and calculating the mean over the samples. + + Args: + A: Linear system matrix. + b: Linear system vector. + num_samples: Number of samples to be collected. + dt: Time step. + burnin: Time-step index corresponding to the end of the burn-in period. + Samples before this step are not collected. + key: JAX random key + + Returns: + Approximate solution, x, of the linear system. + """ + if key is None: + key = jax.random.PRNGKey(0) + ts = jnp.arange(burnin, burnin + num_samples) * dt + x0 = jnp.zeros_like(b) + samples = sample_identity_diffusion(key, ts, x0, A, jnp.linalg.solve(A, b)) + return jnp.mean(samples, axis=0) + + +def inv( + A, + num_samples: int = 10000, + dt: float = 1.0, + burnin: int = 0, + key: Array = None, +) -> Array: + """ + Obtain the inverse of a matrix A by + collecting samples from an Ornstein-Uhlenbeck + process and calculating the covariance of the samples. + + Args: + A: Matrix to invert (must be symmetric positive definite). + num_samples: Number of samples to be collected. + dt: Time step. + burnin: Time-step index corresponding to the end of the burn-in period. + Samples before this step are not collected. + key: JAX random key + + Returns: + Approximate inverse of A. + """ + if key is None: + key = jax.random.PRNGKey(0) + ts = jnp.arange(burnin, burnin + num_samples) * dt + b = jnp.zeros(A.shape[0]) + x0 = jnp.zeros_like(b) + samples = sample(key, ts, x0, A, b, 2 * jnp.eye(A.shape[0])) + return jnp.cov(samples.T) + + +def expnegm( + A, + num_samples: int = 10000, + dt: float = 1.0, + burnin: int = 0, + key: Array = None, + alpha: float = 0.0, +) -> Array: + """ + Obtain the negative exponential of a matrix A by + collecting samples from an Ornstein-Uhlenbeck + process and calculating the covariance of the samples. + + Args: + A: Matrix to exponentiate. + num_samples: Number of samples to be collected. + dt: Time step. + burnin: Time-step index corresponding to the end of the burn-in period. + Samples before this step are not collected. + key: JAX random key + alpha: Regularization parameter to ensure diffusion matrix + is symmetric positive definite. + + Returns: + Approximate negative matrix exponential, exp(-A). + """ + if key is None: + key = jax.random.PRNGKey(0) + + A_shifted = (A + alpha * jnp.eye(A.shape[0])) / dt + B = A_shifted + A_shifted.T + + ts = jnp.arange(burnin, burnin + num_samples) * dt + b = jnp.zeros(A.shape[0]) + x0 = jnp.zeros_like(b) + samples = sample(key, ts, x0, A_shifted, b, B) + return autocovariance(samples) * jnp.exp(alpha) + + +def expm( + A, + num_samples: int = 10000, + dt: float = 1.0, + burnin: int = 0, + key: Array = None, + alpha: float = 1.0, +) -> Array: + """ + Obtain the exponential of a matrix A by + collecting samples from an Ornstein-Uhlenbeck + process and calculating the covariance of the samples. + + Args: + A: Matrix to exponentiate. + num_samples: Number of samples to be collected. + dt: Time step. + burnin: Time-step index corresponding to the end of the burn-in period. + Samples before this step are not collected. + key: JAX random key + alpha: Regularization parameter to ensure diffusion matrix + is symmetric positive definite. + + Returns: + Approximate matrix exponential, exp(A). + """ + return expnegm(-A, num_samples, dt, burnin, key, alpha) + + +def autocovariance(samples: Array) -> Array: + """ + Calculate the autocovariance of a set of samples. + + Args: + samples: Samples from a stochastic process, as an array of shape (num_samples, dimension). + + Returns: + Autocovariance of the samples. + """ + return fori_loop( + 0, + len(samples) - 1, + lambda i, x: x + jnp.outer(samples[i + 1], samples[i]) / (len(samples) - 1), + jnp.zeros((samples.shape[1], samples.shape[1])), + ) diff --git a/thermox/prob.py b/thermox/prob.py new file mode 100644 index 0000000..9f28418 --- /dev/null +++ b/thermox/prob.py @@ -0,0 +1,124 @@ +import jax.numpy as jnp +from jax.lax import fori_loop +from jax import Array, vmap + +from thermox.utils import ( + handle_matrix_inputs, + preprocess_drift_matrix, + ProcessedDriftMatrix, + ProcessedDiffusionMatrix, +) + + +def log_prob_identity_diffusion( + ts: Array, + xs: Array, + A: Array | ProcessedDriftMatrix, + b: Array, +) -> float: + """Calculates log probability of samples from the Ornstein-Uhlenbeck process, + defined as: + + dx = - A * (x - b) dt + dW + + by using exact diagonalization. + + Assumes x(t_0) is given deterministically. + + Preprocessing (diagonalisation) costs O(d^3) and evaluation then costs O(T * d^2). + + Args: + ts: Times at which samples are collected. Includes time for x0. + xs: Initial state of the process. + A: Drift matrix (Array or thermox.ProcessedDriftMatrix). + b: Drift displacement vector. + Returns: + Scalar log probability of given xs. + """ + if isinstance(A, Array): + A = preprocess_drift_matrix(A) + + def expm_vp(v, dt): + out = A.eigvecs_inv @ v + out = jnp.exp(-A.eigvals * dt) * out + out = A.eigvecs @ out + return out.real + + def transition_mean(y, dt): + return b + expm_vp(y - b, dt) + + def transition_cov_sqrt_inv_vp(v, dt): + diag = ((1 - jnp.exp(-2 * A.sym_eigvals * dt)) / (2 * A.sym_eigvals)) ** 0.5 + diag = jnp.where(diag < 1e-20, 1e-20, diag) + out = A.sym_eigvecs.T @ v + out = out / diag + return out.real + + def transition_cov_log_det(dt): + diag = (1 - jnp.exp(-2 * A.sym_eigvals * dt)) / (2 * A.sym_eigvals) + diag = jnp.where(diag < 1e-20, 1e-20, diag) + return jnp.sum(jnp.log(diag)) + + def logpt(yt, y0, dt): + mean = transition_mean(y0, dt) + diff_val = transition_cov_sqrt_inv_vp(yt - mean, dt) + return ( + -jnp.dot(diff_val, diff_val) / 2 + - transition_cov_log_det(dt) / 2 + - jnp.log(2 * jnp.pi) * (yt.shape[0] / 2) + ) + + log_prob_val = fori_loop( + 1, + len(ts), + lambda i, val: val + logpt(xs[i], xs[i - 1], ts[i] - ts[i - 1]), + 0.0, + ) + + return log_prob_val.real + + +def log_prob( + ts: Array, + xs: Array, + A: Array | ProcessedDriftMatrix, + b: Array, + D: Array | ProcessedDiffusionMatrix, +) -> Array: + """Calculates log probability of samples from the Ornstein-Uhlenbeck process, + defined as: + + dx = - A * (x - b) dt + sqrt(D) dW + + by using exact diagonalization. + + Assumes x(t_0) is given deterministically. + + Preprocessing (diagonalisation) costs O(d^3) and evaluation then costs O(T * d^2), + where T=len(ts). + + By default, this function does the preprocessing on A and D before the evaluation. + However, the preprocessing can be done externally using thermox.preprocess + the output of which can be used as A and D here, this will skip the preprocessing. + + Args: + ts: Times at which samples are collected. Includes time for x0. + xs: Initial state of the process. + A: Drift matrix (Array or thermox.ProcessedDriftMatrix). + Note : If a thermox.ProcessedDriftMatrix instance is used as input, + must be the transformed drift matrix, A_y, given by thermox.preprocess, + not thermox.utils.preprocess_drift_matrix. + b: Drift displacement vector. + D: Diffusion matrix (Array or thermox.ProcessedDiffusionMatrix). + + Returns: + Scalar log probability of given xs. + """ + A_y, D = handle_matrix_inputs(A, D) + + ys = vmap(jnp.matmul, in_axes=(None, 0))(D.sqrt_inv, xs) + b_y = D.sqrt_inv @ b + log_prob_ys = log_prob_identity_diffusion(ts, ys, A_y, b_y) + + D_sqrt_inv_log_det = jnp.log(jnp.linalg.det(D.sqrt_inv)) + return log_prob_ys + D_sqrt_inv_log_det * (len(ts) - 1) diff --git a/thermox/sampler.py b/thermox/sampler.py new file mode 100644 index 0000000..c4faa96 --- /dev/null +++ b/thermox/sampler.py @@ -0,0 +1,118 @@ +import jax +import jax.numpy as jnp +from jax.lax import scan +from jax import Array + +from thermox.utils import ( + handle_matrix_inputs, + preprocess_drift_matrix, + ProcessedDriftMatrix, + ProcessedDiffusionMatrix, +) + + +def sample_identity_diffusion( + key: Array, + ts: Array, + x0: Array, + A: Array | ProcessedDriftMatrix, + b: Array, +) -> Array: + """Collects samples from the Ornstein-Uhlenbeck process, defined as: + + dx = - A * (x - b) dt + dW + + by using exact diagonalization. + + Preprocessing (diagonalisation) costs O(d^3) and sampling costs O(T * d^2) + where T=len(ts). + + Args: + key: Jax PRNGKey. + ts: Times at which samples are collected. Includes time for x0. + x0: Initial state of the process. + A: Drift matrix (Array or thermox.ProcessedDriftMatrix). + b: Drift displacement vector. + + Returns: + Array-like, desired samples. + shape: (len(ts), ) + x0.shape + """ + + if isinstance(A, Array): + A = preprocess_drift_matrix(A) + + def expm_vp(v, dt): + out = A.eigvecs_inv @ v + out = jnp.exp(-A.eigvals * dt) * out + out = A.eigvecs @ out + return out.real + + def transition_mean(x, dt): + return b + expm_vp(x - b, dt) + + def transition_cov_sqrt_vp(v, dt): + diag = ((1 - jnp.exp(-2 * A.sym_eigvals * dt)) / (2 * A.sym_eigvals)) ** 0.5 + out = diag * v + out = A.sym_eigvecs @ out + return out.real + + def next_x(x, dt, tkey): + randv = jax.random.normal(tkey, shape=x.shape) + return transition_mean(x, dt) + transition_cov_sqrt_vp(randv, dt) + + def scan_body(x_and_key, dt): + x, rk = x_and_key + rk, rk_use = jax.random.split(rk) + x = next_x(x, dt, rk_use) + return (x, rk), x + + dts = jnp.diff(ts) + + xs = scan(scan_body, (x0, key), dts)[1] + xs = jnp.concatenate([jnp.expand_dims(x0, axis=0), xs], axis=0) + return xs + + +def sample( + key: Array, + ts: Array, + x0: Array, + A: Array | ProcessedDriftMatrix, + b: Array, + D: Array | ProcessedDiffusionMatrix, +) -> Array: + """Collects samples from the Ornstein-Uhlenbeck process, defined as: + + dx = - A * (x - b) dt + sqrt(D) dW + + by using exact diagonalization. + + Preprocessing (diagonalisation) costs O(d^3) and sampling costs O(T * d^2), + where T=len(ts). + + By default, this function does the preprocessing on A and D before the evaluation. + However, the preprocessing can be done externally using thermox.preprocess + the output of which can be used as A and D here, this will skip the preprocessing. + + Args: + key: Jax PRNGKey. + ts: Times at which samples are collected. Includes time for x0. + x0: Initial state of the process. + A: Drift matrix (Array or thermox.ProcessedDriftMatrix). + Note : If a thermox.ProcessedDriftMatrix instance is used as input, + must be the transformed drift matrix, A_y, given by thermox.preprocess, + not thermox.utils.preprocess_drift_matrix. + b: Drift displacement vector. + D: Diffusion matrix (Array or thermox.ProcessedDiffusionMatrix). + + Returns: + Array-like, desired samples. + shape: (len(ts), ) + x0.shape + """ + A_y, D = handle_matrix_inputs(A, D) + + y0 = D.sqrt_inv @ x0 + b_y = D.sqrt_inv @ b + ys = sample_identity_diffusion(key, ts, y0, A_y, b_y) + return jax.vmap(jnp.matmul, in_axes=(None, 0))(D.sqrt, ys) diff --git a/thermox/utils.py b/thermox/utils.py new file mode 100644 index 0000000..ffb4c08 --- /dev/null +++ b/thermox/utils.py @@ -0,0 +1,116 @@ +from typing import NamedTuple, Tuple +from jax import numpy as jnp +from jax import Array +from fmmax.utils import ( + eig, +) # differentiable and jit-able eigendecomposition, not yet available in jax, see https://github.com/google/jax/issues/2748 + + +class ProcessedDriftMatrix(NamedTuple): + """Stores eigendecompositions of A, (A+A^T)/2""" + + val: Array + eigvals: Array + eigvecs: Array + eigvecs_inv: Array + sym_eigvals: Array + sym_eigvecs: Array + + +def preprocess_drift_matrix(A: Array) -> ProcessedDriftMatrix: + """Preprocesses matrix A (calculates eigendecompositions of A and (A+A^T)/2) + + Args: + A: Drift matrix. + + Returns: + ProcessedDriftMatrix containing eigendeomcomposition of A and (A+A^T)/2. + """ + + A_eigvals, A_eigvecs = eig(A + 0.0j) + + A_eigvals = A_eigvals.real + A_eigvecs = A_eigvecs.real + + A_eigvecs_inv = jnp.linalg.inv(A_eigvecs) + + symA = 0.5 * (A + A.T) + symA_eigvals, symA_eigvecs = jnp.linalg.eigh(symA) + + return ProcessedDriftMatrix( + A, + A_eigvals.real, + A_eigvecs, + A_eigvecs_inv, + symA_eigvals, + symA_eigvecs, + ) + + +class ProcessedDiffusionMatrix(NamedTuple): + """Stores preprocessed diffusion matrix D^0.5 and D^-0.5 via Cholesky""" + + val: Array + sqrt: Array + sqrt_inv: Array + + +def preprocess_diffusion_matrix(D: Array) -> ProcessedDiffusionMatrix: + """Preprocesses diffusion matrix D (calculates D^0.5 and D^-0.5 via Cholesky) + + Args: + D: Diffusion matrix. + + Returns: + ProcessedDiffusionMatrix containing D^0.5 and D^-0.5. + """ + D_sqrt = jnp.linalg.cholesky(D) + D_sqrt_inv = jnp.linalg.inv(D_sqrt) + return ProcessedDiffusionMatrix(D, D_sqrt, D_sqrt_inv) + + +def preprocess( + A: Array, D: Array +) -> Tuple[ProcessedDriftMatrix, ProcessedDiffusionMatrix]: + """Transforms the drift matrix A to A_y = D^-0.5 @ A @ D^0.5 for diffusion matrix D + and preprocesses (calculates eigendecompositions (A_y+A_y^T)/2 as well as + D^0.5 and D^-0.5) + + Args: + A: Drift matrix. + D: Diffusion matrix. + + Returns: + ProcessedDriftMatrix containing eigendecomposition of A_y and (A_y+A_y^T)/2. + where A_y = D^-0.5 @ A @ D^0.5 + ProcessedDiffusionMatrix containing D^0.5 and D^-0.5. + """ + PD = preprocess_diffusion_matrix(D) + A_y = PD.sqrt_inv @ A @ PD.sqrt + PA_y = preprocess_drift_matrix(A_y) + return PA_y, PD + + +def handle_matrix_inputs( + A: Array | ProcessedDriftMatrix, D: Array | ProcessedDiffusionMatrix +) -> Tuple[ProcessedDriftMatrix, ProcessedDiffusionMatrix]: + """Checks the type of the input drift matrix, A, and diffusion matrix, D, + and ensures that they are processed in the correct way. + Helper function for sample and log_prob functions. + + Args: + A: Drift matrix (Array or thermox.ProcessedDriftMatrix). + D: Diffusion matrix (Array or thermox.ProcessedDiffusionMatrix). + + Returns: + ProcessedDriftMatrix containing eigendecomposition of A_y and (A_y+A_y^T)/2. + where A_y = D^-0.5 @ A @ D^0.5 + ProcessedDiffusionMatrix containing D^0.5 and D^-0.5. + """ + if isinstance(A, Array) or isinstance(D, Array): + if isinstance(A, ProcessedDriftMatrix): + A = A.val + if isinstance(D, ProcessedDiffusionMatrix): + D = D.val + A, D = preprocess(A, D) + return A, D