diff --git a/.coveragerc b/.coveragerc
deleted file mode 100644
index 7516597..0000000
--- a/.coveragerc
+++ /dev/null
@@ -1,17 +0,0 @@
-# Configuration for coverage.py
-
-[run]
-branch = True
-source = gnuplot_kernel
-include = gnuplot_kernel/*
-omit =
-    setup.py
-    gnuplot_kernel/__main__.py
-
-[report]
-exclude_lines =
-    pragma: no cover
-    def __repr__
-    if __name__ == .__main__.:
-    def register_ipython_magics
-    def load_ipython_extension
diff --git a/.github/utils/_repo.py b/.github/utils/_repo.py
new file mode 100644
index 0000000..2ef15da
--- /dev/null
+++ b/.github/utils/_repo.py
@@ -0,0 +1,228 @@
+#!/usr/bin/env python
+from __future__ import annotations
+
+import os
+import re
+import shlex
+from subprocess import PIPE, Popen
+from typing import Literal, Sequence, TypeAlias
+
+ReleaseType: TypeAlias = Literal[
+    "alpha",
+    "beta",
+    "candidate",
+    "development",
+    "stable",
+]
+
+pre_release_lookup: dict[str, ReleaseType] = {
+    "a": "alpha",
+    "alpha": "alpha",
+    "b": "beta",
+    "beta": "beta",
+    "rc": "candidate",
+    "dev": "development",
+    ".dev": "development",
+}
+
+# https://docs.github.com/en/actions/learn-github-actions/variables
+# #default-environment-variables
+GITHUB_VARS = [
+    "GITHUB_REF_NAME",  # main, dev, v0.1.0, v0.1.3a1
+    "GITHUB_REF_TYPE",  # "branch" or "tag"
+    "GITHUB_REPOSITORY",  # has2k1/scikit-misc
+    "GITHUB_SERVER_URL",  # https://github.com
+    "GITHUB_SHA",  # commit shasum
+    "GITHUB_WORKSPACE",  # /home/runner/work/scikit-misc/scikit-misc
+    "GITHUB_EVENT_NAME",  # push, schedule, workflow_dispatch, ...
+]
+
+
+count = r"(?:[0-9]|[1-9][0-9]+)"
+DESCRIBE = re.compile(
+    r"^v"
+    rf"(?P<version>{count}\.{count}\.{count})"
+    rf"((?P<pre>a|b|rc|alpha|beta|\.dev){count})?"
+    r"(-(?P<commits>\d+)-g(?P<hash>[a-z0-9]+))?"
+    r"(?P<dirty>-dirty)?"
+    r"$"
+)
+
+# Define a stable release version to be valid according to PEP440
+# and is a semver
+STABLE_TAG = re.compile(r"^v" rf"{count}\.{count}\.{count}" r"$")
+
+# Prerelease version
+PRE_RELEASE_TAG = re.compile(
+    r"^v"
+    rf"{count}\.{count}\.{count}"
+    rf"((?P<pre>a|b|rc|alpha|beta|\.dev){count})?"
+    r"$"
+)
+
+REF_NAME = os.environ.get("GITHUB_REF_NAME", "")
+REF_TYPE = os.environ.get("GITHUB_REF_TYPE", "")
+
+
+def run(cmd: str | Sequence[str]) -> str:
+    if isinstance(cmd, str) and os.name == "posix":
+        cmd = shlex.split(cmd)
+    with Popen(
+        cmd, stdin=PIPE, stderr=PIPE, stdout=PIPE, text=True, encoding="utf-8"
+    ) as p:
+        stdout, _ = p.communicate()
+    return stdout.strip()
+
+
+class Git:
+    @staticmethod
+    def checkout(committish):
+        """
+        Return True if inside a git repo
+        """
+        res = run(f"git checkout {committish}")
+        return res
+
+    @staticmethod
+    def commit_titles(n=1) -> list[str]:
+        """
+        Return a list n of commit titles
+        """
+        output = run(
+            f"git log --oneline --no-merges --pretty='format:%s' -{n}"
+        )
+        return output.split("\n")[:n]
+
+    @staticmethod
+    def commit_messages(n=1) -> list[str]:
+        """
+        Return a list n of commit messages
+        """
+        sep = "______ MESSAGE _____"
+        output = run(
+            f"git log --no-merges --pretty='format:%B{sep}' -{n}"
+        ).strip()
+        if output.endswith(sep):
+            output = output[: -len(sep)]
+        return output.split(sep)[:n]
+
+    @staticmethod
+    def commit_title() -> str:
+        """
+        Commit subject
+        """
+        return Git.commit_titles(1)[0]
+
+    @staticmethod
+    def commit_message() -> str:
+        """
+        Commit title
+        """
+        return Git.commit_messages(1)[0]
+
+    @staticmethod
+    def is_repo():
+        """
+        Return True if inside a git repo
+        """
+        res = run("git rev-parse --is-inside-work-tree")
+        return res == "return"
+
+    @staticmethod
+    def fetch_tags() -> str:
+        """
+        Fetch all tags
+        """
+        return run("git fetch --tags --force")
+
+    @staticmethod
+    def is_shallow() -> bool:
+        """
+        Return True if current repo is shallow
+        """
+        res = run("git rev-parse --is-shallow-repository")
+        return res == "true"
+
+    @staticmethod
+    def deepen(n: int = 1) -> str:
+        """
+        Fetch n commits beyond the shallow limit
+        """
+        return run(f"git fetch --deepen={n}")
+
+    @staticmethod
+    def describe() -> str:
+        """
+        Git describe to determine version
+        """
+        return run("git describe --dirty --tags --long --match '*[0-9]*'")
+
+    @staticmethod
+    def can_describe() -> bool:
+        """
+        Return True if repo can be "described" from a semver tag
+        """
+        return bool(DESCRIBE.match(Git.describe()))
+
+    @staticmethod
+    def get_tag_at_commit(committish: str) -> str:
+        """
+        Get tag of a given commit
+        """
+        return run(f"git describe --exact-match {committish}")
+
+    @staticmethod
+    def tag_message(tag: str) -> str:
+        """
+        Get the message of a tag
+        """
+        return run(f"git tag -l --format='%(subject)' {tag}")
+
+    @staticmethod
+    def is_annotated(tag: str) -> bool:
+        """
+        Return true if tag is annotated tag
+        """
+        # LHS prints to stderr and returns nothing when
+        # tag is an empty string
+        return run(f"git cat-file -t {tag}") == "tag"
+
+    @staticmethod
+    def shallow_checkout(branch: str, url: str, depth: int = 1) -> str:
+        """
+        Shallow clone upto n commits
+        """
+        _branch = f"--branch={branch}"
+        _depth = f"--depth={depth}"
+        return run(f"git clone {_depth} {_branch} {url} .")
+
+    @staticmethod
+    def is_stable_release():
+        """
+        Return True if event is a stable release
+        """
+        return REF_TYPE == "tag" and bool(STABLE_TAG.match(REF_NAME))
+
+    @staticmethod
+    def is_pre_release():
+        """
+        Return True if event is any kind of pre-release
+        """
+        return REF_TYPE == "tag" and bool(PRE_RELEASE_TAG.match(REF_NAME))
+
+    @staticmethod
+    def release_type() -> ReleaseType | None:
+        if Git.is_stable_release():
+            return "stable"
+        elif Git.is_pre_release():
+            match = PRE_RELEASE_TAG.match(REF_NAME)
+            assert match is not None
+            pre = match.group("pre")
+            return pre_release_lookup[pre]
+
+    @staticmethod
+    def branch():
+        """
+        Return event branch
+        """
+        return REF_NAME if REF_TYPE == "branch" else ""
diff --git a/.github/utils/please.py b/.github/utils/please.py
new file mode 100644
index 0000000..5ec3f5f
--- /dev/null
+++ b/.github/utils/please.py
@@ -0,0 +1,84 @@
+import os
+import sys
+from pathlib import Path
+from typing import Callable, TypeAlias
+
+from _repo import Git
+
+Ask: TypeAlias = Callable[[], bool | str]
+Do: TypeAlias = Callable[[], str]
+
+gh_output_file = os.environ.get("GITHUB_OUTPUT")
+
+
+def set_deploy_to():
+    """
+    Write where to deploy to deploy_on in the GITHUB_OUTPUT env
+    """
+    if not gh_output_file:
+        return
+
+    if Git.is_stable_release():
+        deploy_to = "website"
+    elif Git.is_pre_release():
+        deploy_to = "pre-website"
+    elif Git.branch() in {"main", "dev"}:
+        deploy_to = "gh-pages"
+    else:
+        deploy_to = ""
+
+    with Path(gh_output_file).open("a") as f:
+        print(f"deploy_to={deploy_to}", file=f)
+
+
+def set_publish_on():
+    """
+    Write index (pypi or testpypi) to publish_on in the GITHUB_OUTPUT env
+
+    i.e. Where to release
+    """
+    # Probably not on GHA
+    if not gh_output_file:
+        return
+
+    rtype = Git.release_type()
+
+    if rtype in {"stable", "alpha", "beta", "development"}:
+        publish_on = "pypi"
+    elif rtype == "candidate":
+        publish_on = "testpypi"
+    else:
+        publish_on = ""
+
+    with Path(gh_output_file).open("a") as f:
+        print(f"publish_on={publish_on}", file=f)
+
+
+def set_commit_title():
+    """
+    Write the commit title to commit_title in the GITHUB_OUTPUT env
+    """
+    if not gh_output_file:
+        return
+
+    with Path(gh_output_file).open("a") as f:
+        print(f"commit_title={Git.commit_title()}", file=f)
+
+
+def process_request(task_name: str) -> str | None:
+    if task_name in TASKS:
+        return TASKS[task_name]()
+
+
+TASKS: dict[str, Callable[[], str | None]] = {
+    "set_deploy_to": set_deploy_to,
+    "set_publish_on": set_publish_on,
+    "set_commit_title": set_commit_title,
+}
+
+if __name__ == "__main__":
+    if len(sys.argv) == 2:
+        arg = sys.argv[1]
+        output = process_request(arg)
+        if output:
+            print(output)
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
new file mode 100644
index 0000000..14556e1
--- /dev/null
+++ b/.github/workflows/release.yml
@@ -0,0 +1,90 @@
+name: Release
+
+on:
+  push:
+    tags:
+      - 'v[0-9]*'
+
+jobs:
+  run-tests:
+    name: Run all tests
+    uses: ./.github/workflows/testing.yml
+    with:
+      skip_codecov: true
+
+  check-semver-tag:
+    name: Check if the tag is in semantic version format
+    needs: [run-tests]
+    runs-on: ubuntu-latest
+    outputs:
+      publish_on: ${{ steps.variables.outputs.publish_on }}
+
+    strategy:
+      matrix:
+        python-version: ["3.13"]
+
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v4
+
+      - name: Install a specific version of uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Copy build utils
+        run: cp -r .github/utils ../utils
+
+      - name: Decide where to publish and create output variables
+        id: variables
+        run: uv run python ../utils/please.py set_publish_on
+
+      - name: See outputs
+        run: echo "publish_on="${{ steps.variables.outputs.publish_on }}
+
+  # Ref: https://github.com/pypa/gh-action-pypi-publish
+  publish:
+    name: Build and publish Python 🐍 distributions 📦 to TestPyPI or PyPI
+    needs: [check-semver-tag]
+    runs-on: ubuntu-latest
+
+    if: ${{ needs.check-semver-tag.outputs.publish_on != '' }}
+
+    environment:
+      name: release
+      url: https://github.com/has2k1/gnuplot_kernel
+
+    permissions:
+      id-token: write  # IMPORTANT: this permission is mandatory for trusted publishing
+
+    strategy:
+      matrix:
+        python-version: ["3.13"]
+
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v4
+
+      - name: Install a specific version of uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install Packages
+        run: uv run uv pip install build
+
+      - name: Build a wheel and a source tarball
+        run: make dist
+
+      - name: Publish distribution 📦 to Test PyPI
+        if: ${{ needs.check-semver-tag.outputs.publish_on == 'testpypi' }}
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          repository-url: https://test.pypi.org/legacy/
+          skip-existing: true
+
+      - name: Publish distribution 📦 to PyPI
+        if: ${{ needs.check-semver-tag.outputs.publish_on == 'pypi' }}
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          skip-existing: true
diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
new file mode 100644
index 0000000..50e4156
--- /dev/null
+++ b/.github/workflows/testing.yml
@@ -0,0 +1,121 @@
+name: build
+
+on:
+  push:
+    branches:
+      - '*'
+    tags-ignore:
+      - 'v[0-9]*'
+  pull_request:
+  workflow_call:
+
+jobs:
+  # Unittests
+  unittests:
+    runs-on: ubuntu-latest
+
+    # We want to run on external PRs, but not on our own internal PRs as they'll be run
+    # by the push to the branch.
+    if: github.event_name == 'push' || github.event.pull_request.head.repo.full_name != github.repository
+
+    strategy:
+      matrix:
+        include:
+          - python-version: "3.10"
+            resolution: "lowest-direct"
+          - python-version: 3.13
+            resolution: "highest"
+
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v4
+
+      - name: Install a specific version of uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install Packages
+        run: |
+          sudo apt-get install gnuplot
+          # Install as an editable so that the coverage path
+          # is predicable
+          uv run uv pip install --resolution=${{ matrix.resolution }} -e ".[test]"
+
+      - name: Environment Information
+        run: |
+          gnuplot --version
+          uv pip list
+
+      - name: Run Tests
+        run: |
+          make test
+
+      # https://app.codecov.io/github/has2k1/gnuplot-kernel/settings
+      # https://github.com/has2k1/gnuplot-kernel/settings/secrets/actions
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v5
+        with:
+          fail_ci_if_error: true
+          name: "py${{ matrix.python-version }}"
+          token: ${{ secrets.CODECOV_TOKEN }}
+
+  lint-and-format:
+    runs-on: ubuntu-latest
+
+    # We want to run on external PRs, but not on our own internal PRs as they'll be run
+    # by the push to the branch.
+    if: github.event_name == 'push' || github.event.pull_request.head.repo.full_name != github.repository
+
+    strategy:
+      matrix:
+        python-version: [3.13]
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v4
+
+      - name: Install a specific version of uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install Packages
+        run: uv run uv pip install ruff
+
+      - name: Environment Information
+        run: uv pip list
+
+      - name: Check lint with Ruff
+        run: make lint
+
+      - name: Check format with Ruff
+        run: make format
+
+  typecheck:
+    runs-on: ubuntu-latest
+
+    # We want to run on external PRs, but not on our own internal PRs as they'll be run
+    # by the push to the branch.
+    if: github.event_name == 'push' || github.event.pull_request.head.repo.full_name != github.repository
+
+    strategy:
+      matrix:
+        python-version: [3.13]
+
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v4
+
+      - name: Install a specific version of uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install Packages
+        run: uv run uv pip install ".[dev]"
+
+      - name: Environment Information
+        run: uv pip list
+
+      - name: Run Tests
+        run: make typecheck
diff --git a/.gitignore b/.gitignore
index 458a5ac..0fd8f0a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -13,6 +13,16 @@ pip-log.txt
 # Unit test / coverage reports
 .coverage
 .tox
+htmlcov/
+.pytest_cache
+coverage.xml
 
 # other
+.cache
 examples/.ipynb_checkpoints
+
+# Catch all unnamed notebook files
+**/Untitled*.ipynb
+
+# uv
+uv.lock
diff --git a/.travis.yml b/.travis.yml
deleted file mode 100644
index d18cc1a..0000000
--- a/.travis.yml
+++ /dev/null
@@ -1,30 +0,0 @@
-sudo: false
-
-language: python
-
-python:
-   - 2.7
-   - 3.5
-
-addons:
-  apt:
-    packages:
-      - gnuplot
-
-cache: pip
-
-notifications:
-  email: false
-
-install:
-   - pip install nose-cov
-   - pip install coveralls
-   - pip install IPython[notebook]
-   - pip install metakernel
-   - python setup.py install
-
-script:
-   - nosetests --with-cov --cov-config .coveragerc
-
-after_success:
-   - coveralls --rcfile=.coveragerc
diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 0000000..64ad321
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1 @@
+include README.md LICENSE
diff --git a/Makefile b/Makefile
new file mode 100644
index 0000000..cb03adc
--- /dev/null
+++ b/Makefile
@@ -0,0 +1,96 @@
+.PHONY: clean-pyc clean-build docs clean
+BROWSER := python -mwebbrowser
+
+# NOTE: Take care not to use tabs in any programming flow outside the
+# make target
+
+# Use uv (if it is installed) to run all python related commands,
+# and prefere the active environment over .venv in a parent folder
+ifeq ($(OS),Windows_NT)
+  HAS_UV := $(if $(shell where uv 2>NUL),true,false)
+else
+  HAS_UV := $(if $(shell command -v uv 2>/dev/null),true,false)
+endif
+
+ifeq ($(HAS_UV),true)
+  PYTHON ?= uv run --active python
+  PIP ?= uv pip
+  UVRUN ?= uv run --active
+else
+  PYTHON ?= python
+  PIP ?= pip
+  UVRUN ?=
+endif
+
+help:
+	@echo "clean - remove all build, test, coverage and Python artifacts"
+	@echo "clean-build - remove build artifacts"
+	@echo "clean-pyc - remove Python file artifacts"
+	@echo "clean-test - remove test and coverage artifacts"
+	@echo "lint - check style with flake8"
+	@echo "test - run tests quickly with the default Python"
+	@echo "coverage - check code coverage quickly with the default Python"
+	@echo "release - package and upload a release"
+	@echo "dist - package"
+	@echo "install - install the package to the active Python's site-packages"
+	@echo "develop - install the package in development mode"
+
+clean: clean-build clean-pyc clean-test
+
+clean-build:
+	rm -fr build/
+	rm -fr dist/
+	find . -name '*.egg-info' -exec rm -fr {} +
+
+clean-cache:
+	find . -name '__pycache__' -exec rm -fr {} +
+
+clean-test:
+	$(UVRUN) coverage erase
+	rm -f coverage.xml
+	rm -f .coverage
+	rm -fr htmlcov/
+
+format:
+	$(UVRUN) ruff format --check .
+
+format-fix:
+	$(UVRUN) ruff format .
+
+lint:
+	$(UVRUN) ruff check .
+
+lint-fix:
+	$(UVRUN) ruff check --fix .
+
+fix: format-fix lint-fix
+
+typecheck:
+	$(UVRUN) pyright
+
+test: clean-test
+	$(UVRUN) pytest
+
+coverage:
+	$(UVRUN) coverage report -m
+	$(UVRUN) coverage html
+	$(BROWSER) htmlcov/index.html
+
+dist: clean-build
+	$(PYTHON) -m build
+	ls -l dist
+
+release-major:
+	@$(PYTHON) ./tools/release-checklist.py major
+
+release-minor:
+	@$(PYTHON) ./tools/release-checklist.py minor
+
+release-patch:
+	@$(PYTHON) ./tools/release-checklist.py patch
+
+install: clean
+	$(PIP) install .
+
+develop: clean-cache
+	$(PIP) install -e ".[dev]"
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..76b5a78
--- /dev/null
+++ b/README.md
@@ -0,0 +1,69 @@
+# A Jupyter/IPython kernel for Gnuplot
+
+[![Release](https://img.shields.io/pypi/v/gnuplot_kernel.svg)](https://pypi.python.org/pypi/gnuplot_kernel)
+[![License](https://img.shields.io/pypi/l/gnuplot_kernel.svg)](https://pypi.python.org/pypi/gnuplot_kernel)
+[![Build Status](https://github.com/has2k1/gnuplot_kernel/actions/workflows/testing.yml/badge.svg)](https://github.com/has2k1/gnuplot_kernel/actions/workflows/testing.yml)
+[![Coverage](https://codecov.io/github/has2k1/gnuplot_kernel/branch/main/graph/badge.svg)](https://codecov.io/github/has2k1/gnuplot_kernel)
+
+`gnuplot_kernel` has been developed for use specifically with `Jupyter Notebook`.
+It can also be loaded as an `IPython` extension allowing for `gnuplot` code in the same `notebook`
+as `python` code.
+
+## Installation
+
+It is good practice to install `gnuplot_kernel` in a virtual environment.
+We recommend using [uv](https://docs.astral.sh/uv/getting-started/installation/) or
+[python venv](https://docs.python.org/3/library/venv.html).
+
+### Option 1: Using `uv`
+
+```console
+$ uv venv
+```
+
+**Official release**
+
+```console
+$ uv pip install gnuplot_kernel
+$ uv run python -m gnuplot_kernel install --user
+```
+
+The last command installs a kernel spec file for the current python installation. This
+is the file that allows you to choose a jupyter kernel in a notebook.
+
+**Development version**
+
+
+```console
+$ uv pip install git+https://github.com/has2k1/gnuplot_kernel.git@master
+$ uv run python -m gnuplot_kernel install --user
+```
+
+### Option 2: Using `python venv`
+
+```console
+$ python3 -m venv .venv && source .venv/bin/activate
+```
+
+**Official release**
+
+```console
+$ pip install gnuplot_kernel
+$ python -m gnuplot_kernel install --user
+```
+
+**Development version**
+
+```console
+$ pip install git+https://github.com/has2k1/gnuplot_kernel.git@master
+$ python -m gnuplot_kernel install --user
+```
+
+## Requires
+
+- System installation of [Gnuplot](http://www.gnuplot.info/)
+
+## Documentation
+
+1. [Example Notebooks](https://github.com/has2k1/gnuplot_kernel/tree/main/examples) for `gnuplot_kernel`.
+2. [Metakernel magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md), these are available when using `gnuplot_kernel`.
diff --git a/README.rst b/README.rst
deleted file mode 100644
index 39c64bc..0000000
--- a/README.rst
+++ /dev/null
@@ -1,69 +0,0 @@
-####################################
-A Jupyter/IPython kernel for Gnuplot
-####################################
-
-=================    ===============
-Latest Release       |release|_
-License              |license|_
-Build Status         |buildstatus|_
-Coverage             |coverage|_
-=================    ===============
-
-
-`gnuplot_kernel` has been developed for use specifically with
-`Jupyter Notebook`. It can also be loaded as an `IPython`
-extension allowing for `gnuplot` code in the same `notebook`
-as `python` code.
-
-
-Installation
-============
-
-**Official version**
-
-.. code-block:: bash
-
-   pip install gnuplot_kernel
-
-   # or to upgrade
-   pip install --upgrade gnuplot_kernel
-
-**Development version**
-
-.. code-block:: bash
-
-   pip install git+https://github.com/has2k1/gnuplot_kernel.git@master
-
-
-Requires
-========
-
-- System installation of `Gnuplot`_
-- `Notebook`_ (IPython/Jupyter Notebook)
-- `Metakernel`_
-
-
-Documentation
-=============
-
-1. `Example Notebooks`_ for `gnuplot_kernel`.
-2. `Metakernel magics`_, these are available when using `gnuplot_kernel`.
-
-
-.. _`Notebook`: https://github.com/jupyter/notebook
-.. _`Gnuplot`: http://www.gnuplot.info/
-.. _`Example Notebooks`: https://github.com/has2k1/gnuplot_kernel/tree/master/examples
-.. _`Metakernel`: https://github.com/Calysto/metakernel
-.. _`Metakernel magics`: https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md
-
-.. |release| image:: https://img.shields.io/pypi/v/gnuplot_kernel.svg
-.. _release: https://pypi.python.org/pypi/gnuplot_kernel
-
-.. |license| image:: https://img.shields.io/pypi/l/gnuplot_kernel.svg
-.. _license: https://pypi.python.org/pypi/gnuplot_kernel
-
-.. |buildstatus| image:: https://api.travis-ci.org/has2k1/gnuplot_kernel.svg?branch=master
-.. _buildstatus: https://travis-ci.org/has2k1/gnuplot_kernel
-
-.. |coverage| image:: https://coveralls.io/repos/github/has2k1/gnuplot_kernel/badge.svg?branch=master
-.. _coverage: https://coveralls.io/github/has2k1/gnuplot_kernel?branch=master
diff --git a/apt.txt b/apt.txt
new file mode 100644
index 0000000..aff8b8c
--- /dev/null
+++ b/apt.txt
@@ -0,0 +1 @@
+gnuplot
diff --git a/examples/gnuplot-kernel.ipynb b/examples/gnuplot-kernel.ipynb
index 1ca00ca..d610cdd 100644
--- a/examples/gnuplot-kernel.ipynb
+++ b/examples/gnuplot-kernel.ipynb
@@ -23,13 +23,11 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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LWImdDhfmV5LrlrZ1Qsmgo+bRZariZD9dri4+CpEEjDCArJpr6yZtrvYbhhYp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\nBewR4r3ickYGAQAAOP1+Gu/K0HZX6aZzbmPHKL9GcvoDJ3x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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -47,9 +45,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -79,9 +75,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%gnuplot qt size 600,400"
@@ -97,10 +91,19 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "qt5ct: using qt5ct plugin\n"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "plot cos(x)"
    ]
@@ -119,9 +122,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%gnuplot inline"
@@ -130,9 +131,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%gnuplot inline jpeg enhanced background rgb \"#F5DA81\""
@@ -169,12 +168,12 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": false
+    "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/jpeg": 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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -200,24 +199,67 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%gnuplot inline"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can plot the same graph to a file and to the screen with the `plot` and `replot` statements. You can change the terminal(to one of those mentioned above) before the `replot` command to make sure that the image can be shown in the notebook."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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f1hPOhOHSrqUbncRliV0G/7S0ZtycK9pWvre6uN2hP/H13eNvWFDoRLTj7xmpX/HW8pMG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\nS/CEYwAAAABJRU5ErkJggg==\n",
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\n",
+      "text/plain": [
+       "<IPython.core.display.Image object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "set output '/tmp/gnuplot-kernel-example.png'\n",
+    "plot tan(2*x)/2\n",
+    "replot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[0m\u001b[00;38;5;244m\u001b[m\u001b[00;38;5;136m/tmp/gnuplot-kernel-example.png\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%shell\n",
+    "ls /tmp/gnuplot-kernel-example.png"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -235,6 +277,15 @@
     "unset multiplot"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "unset multiplot"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -245,15 +296,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 13,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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QFCPR0T+VAWodpCvFnHD7F46mAOuJHhIGYocpAkkwCJA2I9zlrw4Iis5IdCWo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\nX5oZni/JKGnxnQ6RFl8upSuX7XjQxUT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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -263,7 +313,7 @@
     },
     {
      "data": {
-      "image/png": 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hmAj1mTEeaGTGFty2JR2IAeLG0q46HIaMuz5gDiO66mBJ+KCA+czYj+TTQVy3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\nDdDooV+LRc/eezPVlz67vyvgbdxx3wT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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -273,7 +323,7 @@
     },
     {
      "data": {
-      "image/png": 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FZwyq+MLadN4pdyu8sQzkYt0jLtQQv1bpcC9aCy4bAdEmVpdMqaLDviatbEXPVld9b5O7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\n",
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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -283,7 +333,7 @@
     },
     {
      "data": {
-      "image/png": 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QhRgSDBwOJHBEYzSZi9QD3/DpgE8C0KLXAICMBap+noRaE2bgEG39qp8PBxLhWpsgMVRX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\nBgaXQlBrEEBA+lzVAN2uu5B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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -313,10 +363,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [],
    "source": [
     "%%reset\n",
@@ -327,14 +375,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 15,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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sa7kCedHD2979bsdTFWZtxsKX5Y9t+ev1FtFPRtqO+hkvBlFQpVZ8QDwlNTYKZxQqk1Rl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\noD9H7HEQJgE5SxkIhbr3+XK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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -358,14 +404,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 16,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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JgFC4k64LVZqg7nAgq9NB4uXlTwuftvfq3mn83kzb20FcS0JFmSo0EFzIEBxU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\nNoiFhYVKWBvEwsJCJawNYmFhoRLWBrG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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -391,10 +435,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 17,
+   "metadata": {},
    "outputs": [],
    "source": [
     "%reset"
@@ -429,15 +471,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 18,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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SLOR1ysnJed1VQBDEKnbYiu0wZGCvUVujEQ3JROND7Yomm0g/rWoxlO/gXOWa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\nlf21jDrBSK1pYerZY3Lrtop82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YSuj7NDenc370TrQucWuE8PvyqbOnJImYzGP1O8sRvG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P9+7d27dv38RlFsOY9u2qGNBV8dQ4Mv2Ss2vTDLP6bEHQgoMzN1+u0NnoFru7pasMyk91FS9S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AAAkWicr9SSPwGo6tT8xwTf11niE29yqm8Vgky27iYHdGkMGwsA0K1bt6ioKEtLS9wrq/FY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\nnQAAAGBCbyEGAEBwDo4LvYUoAADgHBzQDADAnHty85ej5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+fn4eHh779+/fv3//nj175s6dS6VS//rrL0x+29v6FINvuidPnuCBy5cvnzNnDoZhDg4OkqPr3bt3VCo1NTVV5plX5i6Tl4HPTTe+RKilpRUeHl5dXf348eNnz54tXLjQyMjo9u3b6enpNTU1b9++zcrKQgiVlZUlJCTw+fyXL1+uWrUKX9bPz8/Pzy8yMpJCoYwYMQIPnDBhwqJFi/BfQqampioqKgghKpWKj+68ePHCyckJD2QymS4uLjJzJRAI2giRXNCRmZq8nCOE+vbti4/btzB48OCEhIScnJwnT548ffp02LBhCxcu3L17N94a3r9/f+TIkZcvX759+zZC6Ouvv160aNHRo0e9vb2nTZvWr18/6aSeP3/OZDJ3796Nf2SxWDExMX5+fgihgQMHSgLxy44IIRUVlfZP3pIU3NfX18zMbP/+/RkZGW/fvhWJRJKfrZLBGPxXF0IoODjYx8fH1NTUx8fH399/5MiRLTKsrq7+559/4h+bmprwNlp6dS3weDzpocf3XqFrnaXWR5HMBWNjYwMCAvD/6XS6t7d3bGwsfhWydZoSqampV65cwf+fNWtW65s2/P39v/zyy9TU1H79+l25ciUhIeH169f4V6tWrXry5Mm2bdsyMzNfvHiBb9WoqChXV1cWi4UQUlJSkhzqbWfjvV68eDF27Fj8f2dnZzx9mUfvByULOkBeCyCzdqSmpuLXu/HADRs24H9dXV3V1dXxwAkTJmzcuBH/v/VBInPXt9C6DUT/6xzg/0s3g61T+9B6TSKRdu/e/dNPP8XExOCj9atXr753756lpWVQUNDQoUPr6uoyMzPLysr8/PyoVGpwcLCNjY27u7uPj8/cuXMlI2242NhYTU3NHTt24B8JBMKrV6/wphJvBvFM4s0gkUhUVlZu0QyeOHGivLwcIWRkZIQPJOPwsR/sv/OoMAyTjAl1oErKOwlKF6qNhl3SADo7O+fk5FRUVOATNiQqKiqSkpKamppu3bo1aNCgV69e4TMl5O2j1qeY3NxcMpksuX/L2dl5+/btfD4/MTHxxIkTeKCNjY2pqWlcXBySdeZls9mtd1kbB8lnpbteIqyvr1+zZk1ZWRk+j2fPnj3v3r3Lysq6evWqUCgkEAj4BBSEkI6OzrZt2/h8vvSoskgkamhooNFo+MwYnFgsxr9CCLUYicVrhXTdaH3tSVVV1czMrPVujo6OlrQL+KEjnaZ0avJy3mJBidevX2/atAkhZGpqGhwcfOrUqcePH+/Zs6ewsJBMJk+bNu3ChQu3b9/W0tLCJ0stWLAgLy9v+fLl2dnZzs7OkotNOKFQKH17y8yZM4cNG9a6sNLXKNtPkv+LFy8OGTKkpKRk+PDhoaGhNBpNsh2ktzke6OjomJubu2/fPhKJNHv27GXLlrWRYRcXF0lzJnNzIYR0dHTOScEv/BMIBOl9IX3Vo3WWWh9FMlck2Yk4sVgsuYjTOk2J2trapP+RDPtLo9PpkydP/vPPP+/cuTNw4EDJbAaE0LJly+bOnUsgECZPnowPtuG5xeRM3W0jG9KkN470iVN6EXzui8yjV16yQCHaaAFk1o4WrVZTU5NAIPjQY7X1rpc2aNCgt2/ftuhzlJSU5OTkSKa9ymsGJQfSB9XrPXv2REVF0el0T0/PH3744fnz54MHD8ZnDg0cONDS0jI8PPz8+fNTp07Fi3P69Om4uDhfX9+IiAhbW1v80r9Ei7Vv3LhRMk2tnc1gamoqXoUzMjKkw1VVVRFC+IUOXENDA5/Px8NRq5POe7VxEmyjRNINu2Tj4/251rcoent7nz59+uLFi8+fP3/79q3kMqK8fSTzFCO9i5uamkgkEolEalFYyVEn88zbepe1cZB8VrprB4vBYPz555+7du2S7Dwul9vc3KyiomJlZaWiojJkyJB169atW7fO1dU1NzeXwWA4Ojrev38fj3z9+nVra2tbW1uRSPTo0SM88ObNm7q6un369JG5RldX15iYmOrqaiS/v7x27dqdO3fGxsZKQv75558TJ05IxjzaTk1ezuVtBDKZvHXr1mvXrklCqqqqyGQyfuQFBQVFRESEh4fPnj0bISQSifAr7nPnzr148eK0adMiIyMRQkQiEd+GTk5OPB5v7dq169atW7t2bVFR0cc/v6C1M2fOfPnll7t27Zo6dWpDQ0NzczPer5VpzZo1ly5dCggIOHr06N69e/FxOAknJ6eampoFCxbgm4vFYrV+SER7KCkpFRcX4/2q+Ph4ydlFptZHEZLahhJDhgyR3NzH4/Hu3bvX4oYAmZydna/8j8w5pwih2bNn//XXX+fOnWvRoPzxxx8HDx5cv379uHHjsrOz8a3q4uLy/Plz/GzH4/GePn363jyg//7UVlJSwmfkIIQkt6e5urrisxURQq9evcIPY5lHb3tWBzqsjRZAZu3o27cvi8XC5+EhhNatWzdv3rwhQ4ZER0dL7va9efNmG8eqzF0vLTAwUFNTc8mSJZLKyOFw5s+fP3DgwBYj0PJS+9B6/fLly3Xr1jU2NuIfhUJhXV2dpCs2e/bsa9eu3bhxA28GU1JSRo0aZWFh8e233z569EhVVfXFixfSB/yQIUO0tbXxVS9cuDAxMVHmKF0b9u3bh1fhn376STrc1NRUQ0Pj/PnzkpBz587R6XTJwFUbZI5+tXESRO1r2PFTAELo1q1blpaWbDZbXgb69+9/7ty5jRs34gebzH0k7xQjEonw6Xf4itzc3Egkkr29vaSFTE1Nzc7OlnfUydxlimr8P7XueomQRCKdOXMmMDAwLCzM3t6+ubn5+fPnI0eOHDduHIlEOnTo0PTp04OCgqhU6smTJzdu3EggEH7++WcvL6+Kigo9Pb1Tp07t37+fzWbv3Llz0qRJ8+fPb2xsPHv2bGhoqLyfJt7e3l5eXu7u7oGBgbdv35YZ7csvvywqKnJ3dx8xYoSJiUlaWlpsbOzu3bv9/f3bkxqDwZCZc3kbwcbGZseOHYGBgf3797ewsCgtLX3x4sXPP/+M33kxePBgbW3t8+fP4z/RSCTSgAED/P39g4KCOBxOeHg4XlUMDAxCQkJ4PN7KlSuvXr06cuTIkSNHPnv2LCsrC/9xrFj4RX0tLa3GxsZz586xWCzpn3QtuLm5zZ49++3btywWKzQ0dOnSpdLfuru7T5kyxcXFZcaMGSUlJfhwXQey5O3tvXTp0vHjx1tbWz98+FBbW7uNyK2PIoSQgYHB+fPn2Wy2ZEhp7dq1rq6u+GOrIiIi9PX1582b14G8tTZixAg+n3/37t0W90u7u7tv2bIlMzMzMzMzIiJCIBA0Njb6+voOGjTIzc1t/Pjx9+7da25ubs8ApJaWFoVCmT59+vbt26dMmeLr68tkMkUi0bt37/AIq1atCgsL8/HxcXJyCgsLwxt0mUevQooM5GmjBZBZO2g02r59+4KCgubNm1dXVxcWFvbkyRNra2svLy9nZ+epU6e+efMmNjZW8puzNZm7XpqSklJERMSkSZMsLS09PDwEAsHjx48NDQ3//vvv1k2ZzNQ+tF7v3bvX29vb0NDQ0dFRRUUlPj5eSUlJcvFo5syZmzZt0tfXx69SmZubc7ncUaNGjRkz5t27d0Kh0NfXl0QiSQ74vXv3jhkzJj8/39zc/OLFixYWFn369FHITwUikXj48OE5c+bcvHnTxMQkNzf3xYsXx44dkzn3owXpKil5aFYbJ0Ek1Si10bCfOnWqsrKSQqGcOXPm8uXLbefB19d32bJlCxcudHFxkbmP5J1iEELLli2bPHlySkpKfHw8/kCi/fv3jxs3Ljc318DA4Pfff//mm29sbGxkPmFE5i7T1NRUSOP/qZE2b97c1XnoIDMzs0WLFuGXbM3NzdesWbN69Wr8/GFvbz9hwoS6ujo6nb5p0yZ8Noyurm5wcHBzczOJRNqyZcuoUaMQQkOHDh07dmxNTY2Ghsa+ffvc3NzwxHV1dR0dHSXrcnNzU1NTCwwMNDQ0rK2t/fLLLz08PKytrVvfiO7p6Tlv3jw6nU6j0YYPH37s2DF8RThra2szMzP8f5mpycw5QkhPT08ywC7Nzc1t1qxZ+G2A+MD4+PHjJd+WlZWJxeJvvvkG/+jj4zNgwICqqipNTc29e/fa29sjhEaNGiUSifr27WthYTF//nw1NbX6+no3N7dDhw5Jnljo7OysoaGB/+/g4CAZM+/fv7+8h7s6OjoaGRm1LviwYcP69+9fVlamra29ffv2AQMGsNlsPBHptRgYGNjb21tZWfn7+1dXVxMIhO+++05yI7eFhYW5uTlCaMKECfb29tXV1YaGhocPH+7fv3/r7SxNX19f+h5PnLKy8qxZs0gkkqqq6s6dOzU0NJycnJhMJp1OHzFihGTYHC+szKPI1dWVRqNpaGjgl+0GDx6spKS0YMECJpPJ5XInTZq0fft2ydB362LK3ICtmZqa2tnZEQgEMzMzLy8vyXVnKysrCwuLwMBAJpNZU1Nja2t76NAhJpNpamqqpqY2bdo0NpstEAiWL1+elZXVt29f/AKBzGxIMu/h4SESiQYMGDB48ODx48c3NDT0799/y5YtSkpK7u7uSkpK+OVIDMO2bt2qq6vr4uLCZDLlHb3g02mjBZBZOxwcHMaOHVtdXW1gYHDkyBG86k2ZMsXa2rqmpsbBweHIkSOS5w60Pkjk7XrpLGlqai5evNjW1pZIJBoaGn7zzTc//fST9ONPXVxc8MESeal9UL1msVhffvmlvb09i8XS09ObPXv2vn37JKtjMpl37tyZOHEiPgGRSCQGBQWxWKy6ujo7O7vDhw+z2WzpA97a2nrOnDkikYjH482ePXvDhg14v1C6NSAQCCNGjJA8FwA/O7RnZ9nZ2c2ZM4fFYjEYDGdn54MHD0rmwyGErKys+vbti//PYDDwDNNotBEjRjCZTEkOJbPlUJsnQUmjNGTIEJkN+4EDBw4ePKivr0+j0fbv3y9zAMnOzk56qq6np6dIJKLRaGZmZjL3UetTTG1t7cGDB58/f15RUWFtbX3kyBH8F6yhoWFwcDCfz8cwbPXq1ZIHorY+87LZ7Na7DMlv/D8rhDamX4Duztvbe+bMmcHBwV2dEdA1YmJiDh069NdffyGEBAKBhYXFvn37oN8Deo+GhgYjI6O4uDhTU9OuzsvnxcTE5MiRIwp5CUQbcnNzTU1NORyOvHmxPVt3vUQI2nbhwoWTJ0/m5ORMnTq1q/MCuoydnV18fLy/v/+gQYMiIyP19fXl3fYIQM8TEhKCX4KE3hXoEjCCBQAAAACgYN31LkIAAAAAgM8WdLAAAAAAABQMOlgAAAAAAAoGHSwAAAAAAAWDDhYAAAAAgIJBBwsAAAAAQMGggwUAAAAAoGDQwQIAAAAAUDDoYAEAAAAAKBh0sAAAAAAAFAw6WAAAAAAACtapL3vGMOzOnTtv3rzR0NCYOHEim83Gw9PS0m7dukWhUKZMmaKjo9OZWQIAgI+XmJj45MkTMpk8evRoS0vLrs4OAKDrdd4IFoZhkydPXr16dX19/e3bty0sLFJTUxFCd+/edXJyysvLi4mJcXR0zMrK6rQsAQDAxztw4ICPj09hYWFqaqqTk9Nff/3V1TkCAHQ9AoZhnbOm2NjYUaNGFRUVqaqqIoSmT5/OZDJPnDhha2v71VdfLVq0CCG0fPnyxsbG33//vXOyBAAAH0koFLLZ7L///nvUqFEIoePHj+/duzc9Pb2r8wUA6GKdN4JlY2Pz4sULvHeFEKJSqRQKpaKi4t27d2PHjsUDx40bd/PmzU7LEgAAfCQCgfD06VMPDw/8I96ydW2WAACfBawrPH78WEVFJSEh4c2bNwghgUCAhyckJCCERCKRzKVIJFJXby0AQMd1YhvTNYqLi42NjY8ePSovAjRiAHQXH98gdOokd9zVq1cXLVr0119/OTg4vH79GiFEIBDwrwgEApEod1AN73h1Ui7bgUBQ/AXWj0nzQ5dtT/z3xmkjwod+9Sm258foDfv3vWqP+zYAACAASURBVNE69q28/fvezHRrycnJ48ePDwoKWrp0qbw4MhuxD9qMnzocMgNbADKDFNRedfZdhJs2bTpz5sydO3cGDRqEENLT00MIlZeX4/+UlZVpa2u30ccCAIDPUHh4+MKFC/ft2zd79uyuzgsA4LNA2rx5c6etbNGiRTExMQ8fPuzXrx8ewmAwLl++rKmpife3Dh06pKenN2nSJJmLb9mypTNz2x4jRoz4rNL80GXbE/+9cdqI8EFfwf5V+LLtjN92tI592y32r6KcO3fum2++iYiI8PX1bTumvI3Q/s3YCeEKSaSN3d35mfmkK1VUSRWSmU8a/qlL+qHhnzRxhbRXnXdRJjw8PCAgICAgQPL4q4EDB3711Vf//PPPjBkz5syZU11dffPmzejoaAsLC9l5/cwuIQHFgv3bs/XU/VtSUmJmZmZvb9+/f388hE6nHzlyRGbknroRWoOS9jy9p6RIQYXtvEuEysrKISEh0iEaGhoIIV9f39jY2Lt37/br12/nzp26urqdliUAAPhIHA5n7dq10iFUKrWrMgMA+Hx0XgfL29vb29tb5lcWFhbyRq1A79Gi/w1At2BhYdFTL31+jN5TnaGkQJ7uNOLXq8YnAehhoP4i2AgAdBMKqapwvx74XMTHx3d1FgAAitF7qjOUFMjTGztYO3bsIPwPjUazsLDYtWvXp/hZWVhYSCAQamtrFZ5ya4mJiWpqau+Ndvz4cQsLCwaDYWtrGxYW1nbkbdu2GRoaqqioDBky5NGjR+3JxsWLF9/7GOvXr18TpEycOBEPd3R0bBHz9OnThP/C7zZFCO3atUtfX19FRWXGjBlcLhchNGfOnBaRv/32W5kZaGNbZWRkeHp6MhiMvn373rhxo3WE/Pz8gIAADQ0NLS2t2bNnV1VVtYjQ2NgYHByspqamqam5devWtjcFAD1V6+rcU0FJgVwdfUJpF1BUbn/++ecBAwYUFBQUFBSkpaWFhoay2ezvvvtOIYlLa2xsvHz5Mp/PV3jK0sRiMV4EGo3Wdsy7d++qq6s/f/5cKBRev36dTqcnJibKi/zHH38YGRllZmaKxeITJ06wWKzm5ua208/NzWWz2SQSqe1oR48e9fDwKPifyspKeTEbGhok0WJiYtTU1MLDwzEM+/PPPw0NDZOTk2tqavz9/WfOnIlhWHV1tSTyqVOntLS0srOzWyTY9rYSCoXW1tYbNmxoamq6ffs2g8FIS0trEcfV1XXhwoUcDqeiosLX13fy5MktIixcuNDb27u6ujo9Pd3c3PzkyZNtb43eo3u1Np8IbAQAugWFVNXuVNsV2MFydHSUDrly5QqJRCouLsYwLCkpycvLS09PT0lJyd3dPTMzE8Ow4ODgpUuXenh4GBsbOzg43L9/38fHx9DQ0MHBAT8Hh4aGurq6Tpkyxd3dfcCAAZcuXcIwrKCgACFUU1OTk5Ojqqq6Y8eOwYMH6+vrBwUF4b2uxsbG+fPnq6qqmpmZ7du3D0m9NQjn5ubWokPcuiO4ZcsWOzu7gwcPvreDde7cud27d0s+Dho06MSJE/IiC4XCuro6DMP4fP6+ffuMjY1b5K11/GHDhq1Zs+a9Hazp06d7enoOGTKkf//+P/zwQ3s6oGKxeNiwYStXrsQ/jh49+ueff8b/z8rKIpPJ1dXVksilpaVsNhvvirXQ9raKiopSUVGR5Gf27NnffvutdITm5uaAgICioiL84/Xr1/X19aUj8Pl8ZWXlmJgY/ONvv/02aNCg95aul4C+BQYbAYBuAjpYHdS6gyUUCikUCt4r6tev348//oh3L3x8fObOnYthWHBwsIaGRk5Ojlgs9vLyUlFRwftV+BO8MAwLDQ1FCOEn9ZSUFBUVlbdv30p3sBBCq1atEovFFRUV+vr658+fxzDsq6++GjJkSElJSXl5ubu7e+sOVm1tbcV/NTQ0tChOUVGRWCx++fLleztY0jIzM+l0elJSUtvRbt68qaysTKFQwsLC2o65ZcuWWbNmJSYmvreDZWJi4u/vn5KS8ujRI3Nz8xUrVuDhcXFx8hb5/fff9fX1JWU3MDC4ceOG5FsajRYdHS35GBQUNHHiRJnptL2tTp48KX1gbN++3dvbu42CLFiwICAgQDokIyMDIcThcPCP0dHRVCq1jRR6FehbYFLzEEJCQro6L59WG9W5h4GS9iTSd0p+fGpd8C7CzxCJRFJXV6+urkYI/fPPP0ZGRkKhsLi4WFtbu6SkBI/j7+9vYmKCEBo8eDCFQsGfKzF06NDw8HA8gp2dnb+/P0LIysrKx8fn0qVLCxculF7LsmXLCASCpqamk5MTfiY+e/bs+fPn8Ud/bd++He9jSVNVVX1v5vX19T+0vAUFBX5+fqtWrRo4cGDbMb29vblcblhY2PTp02NiYiRToFqIiYk5e/ZsfHx8dnb2e9eelpZGIpFIJJKVldW+ffumTJmyd+9eIpEo7wK/SCTaunXr+vXrlZWV8RAul8tgMCQRlJWVGxoa8P8zMzPPnz+PvzW8tba3VYtkGQyGJNnWdu3adfv27aioqBYp4AtKUuDz+UKhkEyGigb+H9Y77iLsPfN1oKQ9yebNm/GnrijkXYS9cZJ7a3w+v7a2VltbGyGUkJDg6OjYp0+fRYsW5eTkSFpDdXV1/B8ikchkMiX/i8Vi/H8DAwNJgpqamqWlpS3Woqmpif9DIpHEYjGXy62trTUyMsID8d5bC76+vmr/tXHjxo8s7NOnT52dnRcuXPjTTz+9NzKZTCYQCIGBgU5OTpKuZAv19fVBQUGhoaEsFqs9GaBSqSQSCf/f0tKyubm59VRxaZGRkeXl5XPnzpWEMBiMxsZGycempibJHjl16pS7u7udnV17ctJCi2QbGxslyUrj8Xjz5s37888/nz17Zmxs3CIFfEFJCnQ6HXpXAADQC0EHCyGEIiIiMAxzd3fPy8ubPn36zp07KyoqHj9+PHz48PYnkpeXJ/k/MzPT0NCw7fgqKirq6ur5+fn4R/x6YguhoaFJ/yXvzrh2OnPmTGBg4G+//fbdd9+1HTMkJGTx4sWSj42NjZIuZguRkZHZ2dnjxo1TU1Nzd3cXiURqamqPHz+WGbmioqJPnz74AB5CKDU1VVVVVdL1lOnq1asTJ06UDF8hhGxsbFJTU/H/s7OzBQKBlZWVJPLMmTPbLpo8NjY2GRkZIpEI/5icnGxra9siTk1NjaenZ319fXR0tKRzLGFiYqKkpCTJm8wUAAAA9Aa9tIMlEAgKCwsLCwvT09NPnDixaNGidevWaWpqcjgcsViMX0hKTEz8/fff+Xx+O9NMSUk5efKkUCi8dOnSs2fPpk2b9t5F5s2b99NPP5WUlFRUVGzYsKF1BF1dXZP/wns5b968efDgQRspFxcXX7lyBR9+k0SOjIxcvHjxH3/8YWtrixcfv6T16tUryVMYHjx48ObNG4SQp6fnmTNnHj58yOfzDx06lJ2dPWXKFITQvXv33r17hxASiURXrlwpLS319fXNysrC+38XL14kkUhJSUlDhw4VCARXrlwpLy9HCJWWll65ckUkEmlpaZmZmX3//fdcLjcnJ+f7779fuXIlgUAQCARnz57FI7coXVRUlKenp3TpgoODDx06lJKSwuFw1qxZExAQgF9LLS8vx5+zIB1ZunQySVbn4uKio6MTEhLC5/Pv37//999/z549W3pjYhg2ceJELS2t/fv319TUFBYWFhcXS5eOQqHMmDFj/fr1+MS7Xbt2zZkzp41VA9BTcTicrs5CJ4GSArk+fhpXp1FUbn/++WdJ8VVUVOzt7Y8dOyb5dtOmTdra2n369HFyctq0aZOurq5QKAwODpbcvrdhw4apU6fi/x8+fHj48OEYhoWGhlpZWU2dOlVVVdXOzu7OnTvYf+8iRFJznydPnoxPcW1oaJg9e7aKioqJicn333+PX3BsTxG+++67FvP0W0zc/vvvv9H/psxLIrfoeSCE8JsKv/nmGzc3N3xBR0dHSUnPnTtnYWHBZDLd3d0l0xsHDhy4YcMGDMPwyiY92RzDMOlJ7jU1NQihyMhIDMPwZ0rhW6CoqGjSpElsNltTU3PNmjVCobBFZOnSicViCoUSFRXVYgvs2rXLyMiIxWJNnjy5pqYGD4yKiqJSqSKRSDqmdOlkbivp1WVkZIwaNYrFYvXt2/fChQstNmbrYTkGg9GidBwOZ968eVpaWlpaWuvXr2/nDu0Nuldr84n0no3Q+hEnPRWUtEdSSFXtTrX9c26bQkNDW/R42iMqKqq2thb//8mTJ1paWgrMkr+/fztj8ni8L774op2Rnzx5snfv3nZG/vHHH+Pj4z9F5Pb7oNLJ0/6NCeT5nOtvp4GNAEC3oJCq2ksvEX4mDh48uGLFiubm5urq6p07d44ZM0ZRKb9582bkyJHtjHzhwoXly5e3M/KdO3faOclJIBCUl5c7ODgoPPIH+aDSyfRBGxMAAABA8LJnRTl9+vSRI0fi4uI+aKnCwsLFixdHRUURiUR/f/8DBw6057kMAHRHn3P97TSwEQDoFhRSVbtTbYe2qWeLj4/vDc9Z6bWg/qLetBF6T3WGkvZI0MECAHQbUH8RbAQAugmFVFWYgwUAAAAAoGDQwQKfheYqESaCX/YAAAB6COhggS4masbuzyk8Y5x2xjq5+Incd/8B0DMQCAQCgYC/76wHS09P7+osdBIoaU+yefNmvIYqJLXuNCEApi/0QBiKnFUoFmIjjutn3qx88V3NF/F9GQaUrs4WUDyov6g3bQQOhyPzVZ49D5S0R4JJ7qDbSz5Z8+5E9aSnZiQ6ASH08sfysudN424Zv3dB0O1A/UWwEQDoJmCSO+jemqtEsRvLPE8Z4L0rhJDjeq2aVF75y6auzRgAAADwkaCDBbrMi5CyflNVNQfSJSFEMmHAV+xXB6u6MFcAAADAx4MOFuganDxBxoW6IRu1JSHx8fEIIet56vm3OY0lwq7LGgDgY+HVuTeAkgJ5utOEAJi+0JM8XFikrEMeulVH5leq5rRBazQ7P1fg04H6i2AjANBNwBws0F1xcvnZ4fX238nuQlkFq6edqenkLAEAAAAKBB0s0AXid1TaLmLT1Ekyv9UbpiwWoIp4mOoOwKcl4mGcfIGwSdzVGQGgB4IOFuhsDUWCrCt1A1e0HL6SvsBvMUM17Vxt5+YLgN4EQwk7Kv4wSgtzzT5tkBa/vUKxr1LoPfN1oKRAnu40IQCmL/QMz1aVIoTc9ui2Eac2jXdtdG5wviVSzAN1QdeD+os+m42AiVHkrAJuvmDU6T6q/aj12fyHXxbT2SSvP/sQKVDlAIA5WKAb4teJUv+oGfC1RtvR1CxpVDVSaUxj5+QKgF4laW8lt0Dgf99UtR8VIcQyo467aSxoFOM/fgAACgEdLNCpXh+pNvFjMo3e/zKcflNYmZfrOiFLAPQqVa+bk/ZWev1pSKL9O1hFohG8zvbJvlpf9AjeBwqAYnRBB6u6unrChAnSIaGhof7+/oGBgY8ePer8/IBOw68Xvz5U5bhBW+a3HA5H+mPfQNWssHrU9ZdTAFCkLn/Z89MVJUNCtFv/yKGpk4Yf03+yrFghk7FaVOceDErakyj2Zc+d3cFKT0/39va+e/euJGT//v1bt26dO3euj4/P5MmToY/Vg70+XGU0RkXNnCrz25KSEumPbBsaRYVY9gLuJQQ9CoZhGIZ1VQcrO7y+uUrU/0t1md+ajGfStchpZxVwf0mL6tyDQUl7ks2bN+M1VCGpdeqMy3Pnzi1btmzixIkXL15sbm7GA3V0dH777bdx48YhhHbu3Pnw4cPbt2/LzuvnMT8UdAyvRvSnZcakZ2byOlitxW4sE/Ew111tTYcH3QXUX/QZbIQw12yH1ZpmASx5EUpjGu/OKJyVYU4kw2x30Ht1v0nuxsbGycnJX331lSQkPz+/vLzcxcUF/+js7BwdHd2ZWQKdJmFHRd/JrPb3rhBCfSerZl2Bq4QAKEZFfFNDscB0ArONOLouykxjSvbV+k7LFQA9Vad2sNzd3Q0MDKRDampqEELq6v8/Xq2mpsbhcIRCue+hI/yXZJhd+vkc6enp0peKpb+S/p/D4aSnp8v8ClJQeArcQkHybzVU/9IPSkHTni4UCfKfV8lcqjtuh96TgmQqgwQCXe3VoSq75RoE0nv2xcAVGq8OwAvXAfhYXTBeHRcXN2zYMPwSYXJycv/+/Xk8HpVKxb9ycXERCAQyF+zy0XXQYffnFKoYUob+JOPNgxLx8fGOjo4tAp99V0pTIw7eKHtePOhGoP6iLt0IAq74D8O0WRkWdE3Zb1CQwETYOfOMMZcNtRyVOrw6mdW5R4KS9kjd7xJha0ZGRkQiMS8vD/+Yl5dnYmLSpTkCileZ1Jx/lztojVbb0WRWXdMJzOxrPf/WFQA+tey/6/U9lN/bu0IIEUgE67lqKaEf9T7Q3nMmhpICebq4g6WiojJy5Mjjx48jhIRC4alTpwICAro2S0Dhnn1X4hSiTWF25GDTG6bMyeNzC2UPagIA2intbK3FLLV2Rraaq55xsU7U3NtHHAH4GF3/oNFjx47duHHDwcHBysqKw+Fs2LChq3MEFCk7vL6pQmSzQPZt4e9FIBFMxrGy/4YptwB0XHOlqPxlk+l4uTcPtqDSh6Jlr5RzA+odAB3XBR0sS0tL6edgmZubv3v37uzZs9euXYuKilJVVe38LIFPhF8vjvqmxP2Q3nvn1SKEpOdWS+s3hZV1GRp6ADouN6Le0EuFRP+AWw3Mp6tmXur4qxTkVeeeB0oK5OmCDhaTyfTw8JAOIZPJtra2/fv37/zMgE8qZl2poY+KwQhGeyLr6enJDO8zWqU6ubmhWO69pQCAtuVc45j6t/V0htbMAlgFkQ2CBnHH1iivOvc8UFIgD7mrMwB6rIJ73LybnGmv+8n8FkNYbEV+THleRTNXR4nppm3iqNlHZkwSlWAynpUVVjfgq/e8IhoA0JqwSVz4gOt5yuD9UaXQ1Ek6Q5XybnH6TenIVQUm88P6c90XlBTI0/VzsECPxKsVPZxf5PmbAVW15V1LfLHoaMozi7Cd86Mu5XCqVSi09LqKmY/PO14/cL8kQ2ZqcJUQ9Bid/y7CokcNmvZKdI333z/YQr9AVXjiKOhVFPsuwu70ZBp4jk438s/kfKYhZdiBlkPKD0oyl0SHmatqbhgw2kXbWBKOIex6fvLy51cXWjhvsvdqsZSIj53WT532qh/DoOUbakF3AfUXddFGiFpZQtckD97wnuektNZULvzTKmNuqRWJCs+JBb1LT3gOFuiRXh+u4uYLXP77DsEmkWBpzNW5Ty/sdRofMXq+dO8KIURAhD4VzXHjV1zPf/fti+stEiRRCab+rMwr8GMagA9WEMk18lbpwIJK2mR1a1rxo4YOLCv9cP+eDUoK5IEOFlCw8pdN8dsqfC4aSv/qTa0rH3L9IFfAexOwapyhjcwFHR0ddZSYkWMWPSrN2vnmYYtv+32hmnmx4/c0AdA7NRQJGoqFWoPoHVvc1J+Vfa0jP2x6z0MpoaRAHuhgAUVqLBXenpI//Fd9ltm/L3W+mvdm+K1j39kOP+MxnUV5T0OvTlWKGD3/aMqzGwXJ0uF9RjLqsvj1OfxPkm8AeqiCew2Go1Xa85wUmcz8mbnXOfDCdQA6ADpYQGGEjeJbE/NsFrDNJv7/8wwxhG17dW9l7LXb3gvnmg9pZzr6yqzLnkELn13O4/77sg4ihdBvCiv9PAxiAfABih419BnVruekyKRmSSNSCdXvmhWYJQB6CehgAcUQ8bF/JuezbeiSubQNQv7Uh+ciClKej/vaQeP9t4hLX+AfqmW0xm7EzMd/iqWmGVrMUEv/s1bhOQegByt+3KA/vOMdLISQoZdKQST3Q5fqPfN1oKRAHuhgAQUQC7HIGQVkJaLnSX1EQAihLE6Va8RhJoX2yHeJnnK7XtDR4gL/yv4eVBL5QPITSYiui7KIh1UkNCk07wD0WNxCgaBBrG5J+5hEDL1UCiI/eJ5775mvAyUF8kAHC3wsTITdCyoUNmLeFwzxqR7X89+53Tyy2Mrlt2Ff0EgdfJgtARF+c/tix+uHWZwqSZDFDNX0P+EqIQDtUvy4wWA4A33cMxb6jGKUPGsQ8WAeFgAfBjpY4KOIBVjkrMLmKpHvVSMSlSDGsM2Jd5c///v6qLlLrFw/MnFTJvs72+ErY69JQixmqmVcqMVE0NaDzlZbW2tpafn8+fPWX71+/ZogZeLEiZ2fPZmKHjfoeyjL+1YoFp/JjJvy8IzHraNfPw9/V1sqMxpNjaRuQy+Nbvxk2QSgZ4IOFug4fr04wi9P2IT5XTMm0QnlzdyxkaeelGW/HP+Nk5bRh6bG4XBaB67s75FeX3GrMAX/qG5FU9ajFD7syIN5AOiwZ8+eDRs2TN7LbqOiojw8PAr+57fffuvk7MlT+qxR1032BKySxvqhEQdPZ8ZNMrbb7OCjraQy6vbxNXERIkzGywf7eDI+tNLJrM49EpQUyAMdLNBB9Tn8MNcsNQuqb5ghiU64W5Q+6Nr+wZqGkT5f6ih15JVVJSUlrQOpRNJ+J/+Vsdf5YhEeYjlbLe0PmOoOOs/jx48nT5787bffMhiyOytRUVEkEmnSpEljxow5fvw4i9WuSYefGq9WxCkQaNjJmIBV3swdduvoZJMBD8Ysnm7mMFKv3w8DR6dMWpNQWTTz8XlxqwdYG3gyPvRxozKrc48EJQXyQAcLdEThg4Yw12zbxWyPI/qNmGBZzNUvoy+f9Zi+ddAYEqGDB5WFhYXMcN8+VuaqmkdSovCPljPVciM4/DpRB7MOwAeys7PLzc2dN2+evAgxMTEsFuvMmTNHjx69ePHimjVrOjN78pTFNmkPViKSW87A4otFk+6fnt3Xcf2AUdLh6lSlW94LSps46+NvtVhEz025IrFJ0CBjcEseedW554GSAnmggwU+EIZe7a+MnFngfd7QbrnG49KsgeF7G4T8V/7feer1k70Ehgo4wqdFzWdTuHvi6zZF13wfVb3lee3BxPrL6Q2J5XyB+D1zqvYOmbDj9cPK5gaEEF2T1Gc0I+MCTHUHnYTNZtPpbT0gNy0tLSwszMrKavjw4fv27fv111/FYrl9EcJ/Sd76LH0PfHp6uvTlGOmvpP/ncDjSVy1bpJD/uFbXRbn1V1/dPsemKYc4eLVO4U1i0tWRwZdyX0UUJEvngaxMVDIXSaZhtT8PH18KSAFS+NQpSF7wLA0pQnd6/Sq8LLbLNRQLHy4oaq4S+lwy4usK1ryMiCxO/8Vlsp+hdevIfBGWVMF/WcZLKuczKARTVYoJi6zHILGoRCqJ0CQU1/DERRxRag0/v17kbkAba6qsrUySt+qvn4eLEXbEOQAhlPcP50VI+ZQXfT9hUYGi9YD6q6Kicu/ePWdn5zbiZGRkWFhYlJeXa2nJeLlyZ26EG765tks0TCf853r925rSUbd/TfT/Vl/+w1OeledOeXgmyf9bbfq/bzCM3VSOiTDnbTqfMMcAfDbgZc+gE2Eo+beaiw6ZOkOVAp6ZXuYn9v97N4tKexewukXvSoyhpAr+0aT6xfcrI/OaLNQoO4apHxih8Y0Dy7+vspMuzYpNMVMl99egDtOnT7VkhDir7/Jg08iENY8rfnvLaRDIPqZDHLwv57xKqS1DCBn5MJsqRPBALPA5qKio6NOnT0ZGBv4xNTVVVVVVU1Oza3OFMFQW26TrrNQieNXLGyEO3m30rhBCbtomM8wc1sXdlA7Ud1cuifqAGwl7z0MpoaRAnu70m7IH/ALupmrTeU+WlfDqRCN/M0jVKV314gZC6BfXyfZsfeloxQ2iRwVNTwqbtZRJbvp0Fz2aKu0DevANAuxCGjeujPeVPctGg9o6woF3T++VpEeMno8Qit9eUZ/L9zzx/gfEg89ED6i/0iNYpaWlUVFRAQEBJBLJw8NDW1v79OnTFRUV48ePnzJlSkhIiMwUOm0j1KTyIvzyZmf9Z9LMk9LsuVEXUyetoRDlDhXjOAKe9dVdYSODh/7vdmABVxyqlzq/0ppEU8zVEwA+ZzCCBT45fr04Zm1pmFu2ka+K1T/K88r/mvn4zyVWLtHjlkt6VzwR9qiwOSSm5seYGoTQJhf1n1zVx5gofVDvCiHEoBDm2zKXDWQdSqy/lSPjt/JSa9f0uor7JRkIIet56llX6mGqO+gqcXFxU6ZMaWpqQghduHABwzBjY2MnJyc/P78ffvihq3OHyl806QxtOXy1JeluiL3Xe3tXCCEmhfbToDHSg1gUFaKaJa0iHoaNAWiv7vSbsgf8Au5GhE3id8drEnZUGPsxmeuwvUWPHpdmrbHzXGrlKnk4e1at4GFhc0wxz5JNGWVIt9emkRTx47aiSbTrZZ01mzKnP5P43wQv5CQdePfk+bivEUJ3pxfouigP+FpDAasEnx7UX9SJG+HJ8mLVfrSBK/6tHW9rSn3unsidsqE9HSyEkAgT24XvPTR04mh9czwkakWJsh550FoZc8sA6GFgBAt8EgKuOGlf5bl+6cWPG7Suon3Tb09M+H2IpmFm4Pcr+3vQSORanvhWTuPqJ9WHkuo16MTdHuw1g1UddT62dyW570NLifSjq3pxg2h/Qp3wvzcYfmEysFkkvJb/DiFkt0zj7S/VqLefsgGQoexFk/aQ/4xgHUx+usTKtZ29K4QQiUAMsfcKSbwjCdEbxmj/NCx5D2XteaCkQB7oYIF/cQsEz9eXnTVLz4uvqz5bvmne36tKr000ss0OXP+d7XAygRJd3LzzZd13j6vzOMJ5tswDIzQC+jHYdMUcRXp6epL/lciEdUNUxRjan1Av/V4cIoGwbZDvhvh/RJhYb5gyiUYouM9VyNoB6DFEPKwmmac16N9HS9QLmq/kvl5k2db9j61NMRlYzWt8WJKJf9RzVy6NaWznTxrp6tyzQUmB1ND3AAAAIABJREFUPNDBAggTo4JI7j+T8y86ZKZgpS/PJS8YdyaakLt10JjkgDVBfZ1eVYgOJ9YvuV/5uLDZRZ92bJTGkgEsazZFsZNdmcz/3E9OJhJWDmIJxdjvb//zfgY/Q2tNOuN0RhzCB7GOVSs0FwB0e5VJzWqWNLLSv837ldzXI/X6aUk9dqE9iATCugEjt726j39U1iFTWaSaNF57lm1RnXswKCmQh9zVGQBdqTadl/FXXeqZ2hojTtrMwvvT0wRINFvLMc51hRZdLamcdziJ86qC11eV4qRLC+6vwqLK7ZGLm0qE9VmihjxRQ4GooUDcWCRqLBJUv0JiAUKIQKSSNQaRWeYkhiGJ2Y+qOZis1h+975nvZCJhxSDVzTE14VmNE/v++87anYP9Ah/+Md3MwXyGasz3pdwCgYohRVHbBIDuriK+ScvxP09GPZMZv7K/RweSmmk2aGPC7VfVxQPZ+gghXVfl0uhGdSsZr98BALTQnaadwiRZRalN52X/XZ95uT4FKysILI0zzS0ncL8wGTjdzKGPkn5COT+hnJdTJ7TRoA7WoTrq0FRb9atEjUXC2mRhzRtBzWthbYqwPo1ApJJZFiQVI5KyIZFhSGIYkJT0yGx7AomOEMKEjYKqeBE3R8TNF9alCqriRE2lNN0RNMPxdONJRKp6G7mt4Yk3RddMsWB4GPx7zpj26Jytuu4PA0dHrSghM4jw/MPPH9Rf1Fkb4eHCIq1BSrZL2PjHXG61041DhVM3Uts9AUva9tf3czjVJ92mIITeHquuSGzyPAmPRwE9nEKqandq8qCB/hgiHlb8uCE3gpP6uPqtdlGeV1m8Xh5dmexv1N9T146BdFKqBW8q+UQCwUGb6qhDs2FTqJJZ62KBoDZZWJcqrHklqEoUVCciDKOo25HVbMjsgWRVa7KaddudpNbEzeW84vvN+Vf5xfdohuMY/b99nSN2dHSUGbmIK9oSU7N6iKq52v+PVOVwqp0iDr6duIpeRAtzyw7KsSArw/XuzxrUX9RZG+HykCz3g3q6rv8/6Lv7zaNMTuVx18COpVbezLUK25kZ+D2bplyZ1Bw5s2D6O/P3LhUfHy+vOvcwUNIeCTpY4D3EQqwivrnwATcvpv5paU6eW3m2dVkWrdJVz9hdy85Eyayep5RWI2gSYP01qdZsip0mVY9BQghhgnphbTLelxJUJwprk0kqJmQ1G4qaLVljEIXtQGL0UVgmedVNGb83pByksAcxHX8mq9nIjJZQzj/1pn6bG1v9f3PqV7280SDk/+Iy+Z+AfEMfFdvFbEVlCXwKUH8RQpJ3nIWEhEjeQqhYYiF2Si1lbpkVhfH/NcU54tBPg8Z46Xf8Tb2zn/w1WLPPNzbumAg7xU4JyrOkqXVkMAyAz9zmzZu3bNmC/w8dLNBSQ5GgPK6pOLohLrMokVtYaFOda15erFw7RMNysKa1Ns2Ax1fJrReqUIiWbIqlOsVSnWLAEIvqUkV1qcLaFEH1K0F1ophXSVa1orDtKWwHsoYDRX0Agcz4pNnGRLzG1KPcNzuVzKYzHX4iUGTMpgzPbHxZxtvsokYhEhBCNfwmq7Cdj3yXqL5RebigeEaK+fvmdIGuBPUXdcpGqHrTfOeLghkp/z/IVNBQO+j6/pKpIWRix6vH49KsJTFXkwNWI4TCPXMc12sZen3YfPlujV8nKolubK4QMU0oOkOV4Vn2vYFCqipMcu/exAKsLotf/ZaX/bo2Kav4Nbe4SKemsm99gSXH2N7QWr2vLcNmAMaq45FJBKRJIpswKJa6PGNiHr0xQ1iXLMxOF9WlltdnkJhmZFUrsqqFktk05uCdZFY/hDq1ESGQaIz+3yr1C+bEra0It1V1O0nT924Rx7+fck694FwKd25/JkJInaq0xs5zQ8I/V0fOoWuQssLq+k1R7cw8g+4iJSVl27ZtFy9e1NPT09fXF4vFxcXFVVVVkyZN2rhxo5WVVVdnUJEqE5s1Hf6drRiW+8bfqP/H9K4QQh66ZhiGPSvPddM20RmqXPa8sZd0sJoqhM83lGVdrtceoqSsQ67N4NVl8m0Xswf/oE2iQzcLvAd0sLqT5ipRbTqvMqUpo6gquawstbaiiFhTadZQbSikW6gZDeijzzAzp6mZiOgDRSQzFawfvcKInGeA8lUF2ZSmPGFFpig7CxM0iFQteKpWJJYl3WgiWc2KrGqNT0X/HwwT12HierG4HhPXYeIGhDVh4noMa8bEXEzMwcQcIf8NwgQt80egkKl2RJImgcgiENUIJA0SWZ9A0iOS2O3pruEX+FXdTvFK7tc9m083nsxy3IGI/94eSEBo0QDWuqfVthq8Ibo0hNAya7dDyU9jK/IHrdN6uaUcOligte3bt1+5cmXOnDm7d++WfpBPQUFBWFhYYGDg1KlTN27c2IU5VKzKV82a9v8+YvRmYfJy62FtxG8UYu8q+VXNYhUqwVKdoqUk49ofARHmWziFZrxw0zbRGaqU8nvNe7PRA+brlMc13fLPM5+mNjvbgqb+/5uFky+IXlV6aUjWuJvGTCMK6hElbafeU1JF6U6D9r3kEoNYiDVXiRqKBMX5nMzCquyq6rK6hqKG+mJaU72BkKdJRgyaBlFDncxWobEoJLKSsM6AUtmXWm5AKFAXFbFExXR+IbExX8yrJCrpkhiGJIYxWdWCpGJKYpqRmaaIgjBxrVhch/eiMHEdJsK7U/jHekxcRyAyCURVApFFJKoSiCqIQCcQVQkEOoGoTCCyCARlEs2WQFBukXMMaxTx3ojFtZi4DhPVisXVYmGRWFSGxE0kqjmJYk6i2pBpAwlEtfdvBH5N3dNgMa9abcRFkvJ/blnKrBXsiqvb5qaOnwl+z3hxJjP+0Zglfw3IdNuja+TTK35Yd0ddVX9PnDixYMECopwhHJFIdPLkycWLF3dOZjphI1z3zh24UsPYl4kQqhc097n4U/HUTSoUGQ9W4Imwi2kNjwqbLNQpWkokrgB7W8k3UyXPtFYxYrb87V3cWG/79+7CqZuwcsJF+8x55T1q2K+1stimmxPyPE8amE6QMV3h1cGqpL2VEx+aqvaV8Vp60AN8FpPcMQwrLCysra3V1NTU0dGR14q1obGxccmSJdeuXSOTyStWrGjjPak9o4PFrxc3VQi5lYLSivrSGm5ZDbeigVve1Fwu5tWQBPVKIh6NIGKSRQyiOpmkh2FMEkWV2MhAXFWsUotUoUMoU8dqVLBKurCGLKwkCqoJVDZZWYfI6kNi6pKUtQhKaojGIFBpBDL6//6TuF4sqsPE9RjGRQgjEjUJJDaByCISWQQii0BUJRDVCCRVAlH1fyEsxT6BFhNzRIIMET9dxH8r5L8hkg0o9GFkuiuJYtL2ctw3OxtTDquPvEbRHCz9RUR2Y2wpb7OLOomARJjY4dr+rYPGWD/r8/aX6oAnpgrMOVCgrq2/ycnJNjb/3j/B5/OjoqJGjhzZydnohI0Qqpv6RXxfhgEFIRSW+/pU+ot/vBe0jlbdLN72otZMlRxkrcL833NYhGLsXn7z1cyGiX2Vx5q2/AU15u7JOeZDppna/2GUFvDIlGXWY/sWdVn8q+7ZI38zwPupMiWfrInfUTH5mZmyLlwI6oG6eA5WSkrKnj17rl27VlVVhYdoa2v7+/uvXLnS2tq6/emsWLGitLQ0JyensrLSz89PV1d3wQIZzcFnSMTHhA1iAVdc19zUUCeqquPWVfNKRM3cRl4dX1jXzK9HgkYxgYuEIoKQSGmgUZvoJC6ZhuhkHo3IV8EI6rQGJV2+LtbYD6tWIjYwCHWqFC4dNSkRuTTEIRDJiK5KoNKJNCaJyiDQ6AQKjUChEUhsRFJFSIyIPAzjYVgDQgQiUYlARBiBi4gYgSgmEAkEAotI0SEQ1fBeFJHIIhBVEKEL2kQCkUmmDSLTBuGbTch7I2h+1li1nkBkUhm+FKVRBKLMVoygYreOomZbfc9PzeMcTd9L8oWfmfK7KsGFVO7/sXfeYVEdXQOfe7f3XZa6FOlFQEUULKjYsWKLJZYktrwppuiriTHWmFhiS2KKib33ggVU7ApKkSa9dxa293LL98f6EVREhIUFX36Pjw9779y5Z2bvzJ575sw5s/2YBAje2nfc10+i0qYtTVgrrLqvFgxuW3/8LjoROI6jKAoAGDVqVElJSf3xrKyssWPH6nQ6i0nWNmiECIbgJu0KAHCtImescyOmJrkBWxcvHdmNNsH9BS2KCEMRrrRgO/L2ZLlQg37oz2q4tD/Ps8/hgqSZbr3sQmjCBO27qmBhRvzm++V9vrNpQrsCAHRfxFNVGq9PL4+85QqbOatFF+8ILdHRtFrtt99+e/369enTp48ZM8bX15fFYkml0uzs7Fu3bh05ciQiImLbtm10+ssvQK9iNBq5XO6tW7f69esHANi/f//vv/+enJzcuKzme/nTapC4xHK5QjtiiAeb/dx4Xlqh2nwz5Ri4pQQqkoHQ+6kr25ah6sbQsMg2BOJQqLyQNKDWQKDoiseCY8PR82RcZwCUVMpICEBkyOjMFPIJ1ahEJoEFZCsW25ZKs6YDgGMyOa7VATqTwGECCEJ1GI7CMAxDRAiCYIiAAwgHEAoBAg5IEKACiAjBTAimQTANgukQxIJgGoDIEMSAYDYE0QBEhGAWBDMhiAHBDAhiAqgzvkLhiD7VoIlGdAlk+mgyc5paQ200FYNB+FB6dxq7z880j7n1B5UG7NuH0kWBrF42ZADAmBt7Rzv6jH4SkH9SPvGGa7u1oYvmYxELVnFxcffu3RtVpEaPHh0TE9PO8rR1J5THqpJ/rJt057kd1/n0D3ciPvFkWzcsY8TwHx7LAq3J73m/9lVEg+CbE2QeXNIH3ZkNDhodT23InfpNxa86TY0xbEdTmemUSmUnzazyZE2tKEU7LqrbGx1HcQxcnVDK8oaG7HRpF9EsTOf9TluAxZYI9+3bR6FQZs+eXR/TpSEYhh05cgRBkAULFryxqoKCAi8vL6VSyWQyAQDx8fHh4eF6fSO5rmRqFY/JAkuj3lba9oROwk5PiQpzqjDoncnUUCZnGCAwcKykuCTVzS2YQAmEADEj/aafnzMEkSGIrlbrhLUqD08fCKKBF10I8/LyHBwc6p/mhqca/q1UKqurq729vVEMl2mNBVnpoX37tKyGV0+1Tw0YKlZJjqH6WB3S2955CUTgv1oDDauU3IxgdP8qRzuo/tTF+MwYjd2WMCsOBU6uKh51e39W5IrrPapHnXCqJGW3cyu6aniphuPHj9eHk6nHIkuEZWVlGo0mPDz87t27piMQBFEoFBcXlxa4NLSStlawUreLVOXGsF0OAIBsmXDMzb0l7616qczhLFWtFl0WzGlaf9Ag+Np46WBHakMr1+x7xwbauUVW93yyRjjlgXsTl+fl5dU/RZ0Icbru0oiSGameDEGz3lp1IvRoQE7EcVenYe++4byTfqcto0P4YLWS1NTUoKAgDMNMulp6enrPnj2NRiOR+MrDjaIQkVjp8mb/6LcFIpKIXj6AQEBysgAMk0P6E93c0Vqh/m4sAIAydBSl30CIQoEYLEAkwBwuRCJDdDpEZ0AkEsRkQWQyxHz+k3O3UDxu7xONATW7kG9uBQS4VJJSjyDY8y+URiJQiTCHRiJAEJdGpBAJdDKBSSZY0clMCoFLI/FoJCaFaEUnWTPIfDrZmkHmM8hE2DK2bhxT6pXHDZoYMiOSwpoFQS/75KLqcsn14TTvhcyAFfUHT+aqy5XI8j4cAMDXCZe0CLIkY2hxlHL81W7tKn0XzcCyPlgoihIIlo+N2dadcOujSoeB9O4LeQCAX7MeZkirTSlu6kmvM+zJUG4ZxGOS3qxcSnTYqkeSxYHsINvnq4FXy7M3pd+6M/jTA4KchVI/mPhuLY3h4ExIYeDnfN8P3uKHpixGde/TqlmZng2za3fR2bGkD5bBYCgoKOjevbtGo/nll1/S0tJ8fX2XLFnC5/Pfqh4GgwEA0Gg09X9QqdRGtCsAgGlyjM+0trYmk8259o8b9EhOFo6ipO4BAMX0cffRqkpy7xDu9j8AjutiLhuznuF6Pa5WAiOCKeS4QY9rtbhajSNGXKnADQZcrYIoFIhK82Mwi6lUmMuD6AyIxYYoFNiKD1GpMM8KZrIgJhtmc2Bra5jNAVQabGUFEdswRbHGgOpRTK41Ihgu1yF6BNUYUKUeFWsMagMi1RhLJFqVARGrDWKNQaQ2iNVGkdrAoRIFHKqATbVjUZw4VCcuzYVLc7WiedswKcQ2nD4gmEXlfExmTtYp9qqEH9G4XxKpoQ0LEBjOVhF3JDFDIYjE8P/adHCaF/27R9L7FbrBTtS1vUb5nd/68eR+0i36msca+35vXqHu4n+HioqKn376KT8/H8Ow+oP1Nq13BnGGrj6lQWxV3hyPFzbVozg4kKlcFMhqjnYFALCiwl/35mxL/nfT7ihH748enqqBFSwXkiRTb92T+sZKOhH5p+QQAfjOe7vXeJcIpl0o7elmUch62zYSrItOSgt9sPr165eenv7xxx8LhcKnT5+GhoY+efKEQqE8e/bsrbQfo9HI4XAePHhgWl/Yv3//n3/+mZiY2LisEGRvby8Wi2EY5nA4fD7f2tra9L+trS2fz+fz+Y6Ojg4ODqbjjStqbQOu0+F6Ha5S4nodJpHgOi2mkAOdDpNKcJ0Ok0owtQpXKjC5DBPVYSolrtFgMglMo8N8a5hn9fyfFR+2tSPYOcBWfJhvTbCxg23ae8SK1AahUl8h19Wq9BUybblMVy7TFks0hSI1j072tKb72DB9bJm9nThBjhwerU0URESfqpVtJ5D9aZxPIZjd8BSqLhdHD2H2+Jbuvdh0pFSBbHwi2ziQZ0cn/JUTf6Yk7bfyGQVn5ROvu7aFbF20GMtasIYOHUqj0UaPHt3QjvX555+3sxht2gk4Bv5hZ31U40tiwgiGWZ9YUzB1pTX136Wr6BJtaq1+ZcjbKRBXijSJQv3afjyTdXvxozO+XNue2zwdBtC7L3q7DKQdGcyIH++eH77HsQWLfepK48leBdOTPFnd2vCduYv2xGIWrKioKIVCkZ+fP3fu3OLi4oyMDBsbG5VKFRgYePHixenTpze/KhKJ9P7773/33XcnT56UyWRbt25dsmRJE+Wrq6sBADqdTiaTicVisVgsEonq6upEIlFFRUVaWlpFRUV1dbVYLJZIJDY2NnZ2dgKBwMnJycnJycHBwc7OzsXFxcXFhccz87wAUakQlQo4XAAAaMoz4QUwmRSTiP/9XyrGhELjszSsrg6TitG6OlwmhXg8gsCJYC8gOAhgKz7B0ZkgcCQ4OBIcnSByI7FtWok1g2zNIPvbv+zJiOF4tUKfL1Ln1qqyhMqozJrUSoU1gxzkyAly5PR24oS4cK0ZrbIs1vvxECm9mLZ79Yr9qtqFNO5SIrVffRkCw5k/+qY4JhwicWhuMwAA3djEyZ7031IU6wfwFvmE/p7zqGhEtWILsfKu2jH83feK6KKZFBYWlpSUtL/TVXuiKDZQbYgkJgwASBSVuzGtGmpXehS/WKD+PvStvSzGudNT6gxXizUmZ6zpbr1WPY0eFRIoTNA0oWB1uqCUecflrG7kFmhXppYGfsZ/slo44rDZkrR2QDrdd2pxWqJgFRUVhYWFeXp6jh49OjU11cbGBgDAZDLDw8MLCgretrZdu3Z9+eWXPj4+AIBFixZ9+umnb7yESqXa29vb29s3UQbDsJqampqamurq6vLy8oqKisePHwuFwtLS0rKyMgzDXFxcnJ2dXVxcfHx83N3dXV1dvb29m7Pz0YzAXB7MbUrVw40GTCJBqyqwmiq0phqTiA1x99GqSrS6Eq2pgm3tiSZ9y7kb0cOb6OlFcO4Gs9hNVNhyUSHIkUN15FDDPZ6vAmM4XijWpFTIn1bKd94vSiiTOnFow72sB7lbDfW0boGy1XDoQhCFyvmESAvTSjaTaClU9qL6nZIElofViGviGyNhMofiGAEAGONGT6sznM9Xv+fN2NJn3H8Tr5zdMD/+m5ppjz3aN99PFx0XgUCg1WpNrgiWxeRv2hbJniXPdPyA5y9dd2sKhzp4NjwbW6b1tSI5vxJB9I1AACwOZK16JA2xp9jRCeH2HiVKib6XTvintomrOtcvMY6Bp5vrhvwhaMG1ppYG/df6qHeeOF3H7/FOLZs2pHN9py2jYbLn1tMSBUuv11MoFAAAlUqlUv99mAgEgsFgeNvamEzmvn37WiBG08AwLBAIBILGB4xCoSgvLzcpW7m5uffu3SsuLs7Pz2exWN7e3iZ9y8fHx9fX18fHx7TD0SJAJDLBzp5g15gqiaJIeSlaWY5WV6ElRbrrV5A/8pCyUohEIrp5EL18iB5eJN8Aom93gn1Tu6lbDAxBXtYML2vG9F4CAACK4alVilv5dUeSKxafSfexYUYG2E30t3/VGNZ8iORApu1fWulWlWgp3WoNTHi+25zIC+QNuyC9NYk37ALZdgAEwH96sr99IOlpQx7r5PdHTtw1z2fOBseiSwr3SW2ibnbR6YiMjBw7duxHH31kbf1vzILx48e3vyRtt0QoydRb+T+fkG9X53/ZfVD9KQTDrxRpvu3bwk1CdnTCRA/6gUzlt325RBie3C3wFi2XW2xnVGEmg1lnp+i8gsIjOA5tuf5NYsK9V9gkbqiNOPs/EbLhXWXdunWmN59GgyS8LZ0xfpIZYLPZ/v7+/v7+Lx0XCoW5ubklJSWFhYVXrlzZvn17bm6unZ1dz549fX19vb29e/ToERgYaF4v+xZCIBBd3YmuL69HYmIRUpiPFOUjBfmqv38z5mQBg57YPYDk7Uv08Sf5B5L8AiAardEqWyUODAU7cYKdOCuGAiOK3S+SRGXWjN+XQICgSYH27/V0CHVpybIsBLPo/A165Sl13ad0qzUEcoDpONmmP3fwEemdKfxRsUReAI8CLwpk7U5VbBlktTMkcuDV3Vd//Dj+a6HrOFZXDMAuAAB79uwBALxkNLKIgtV2iJ/puo1lAQAMGJpQVx5m929Wg8fVeicmsRu75RP+ODf6gwpdslAfbEeZ6hq4+mnM8h7d6pK1giGWNwq2nrRdol7LrN9crkkC/mOVsk0kztDxA99ZI1YXb0VL3LjWrVv3zz//+Pn5lZaWKpXKgIDnv3nZ2dmLFi0yu927Hos4yeI4XlBQkJqampeXl5OTk56enpeX5+TkFBQU1KtXr969ewcHB5sWSTssmExqzExHCvKM2ZnGZ2lIQS7ByYXk34PcK5gcHELqHgjacjdAWpXiQkb1ydQqAgTNCnKc28epG69x9a7pICuILlEj3UzlLCbTR9cf1BafVCZ/Zz3+MUy1BQDsSVdCEFgcyFqVHF2iksz4aaB7JDvgUyuzN6qLFmBZJ/fy8nJnZ2dL3b2eNu2Ekz0Lhh90sgmiPhQWL02ISpjwZf2p1XHSSA96H7tWeW1miAx7nym3D7YCAHc4tf6v1NlufKveKxrXSzpRzKS6p9royWVzCr1bFnWiYUtTfhaJUnUjj72bnlid6DttPRaLgxUbGxsbG9voqREjRowYMaKVMr2ODpKL0Gg0mlSulJSU5OTkp0+fMpnMoKCgoKCgPn36DBw40MqqQ/+i44gRyc81ZqQZUpMNSY/RinJS9wBSjyBK6ABycAhs3Vb7FuNKJCdSqk6lVvZ25Hw12H20j+1LJtg3hgnGkDK1+HsSbSiV/SH4f+8qZcpaQ9VNq4hbEIGmR/Hl9yXzA1jePMj/ws87HCbJpsNz8rzfjVWMzo5lxy+VSvX394+MjIyMjOzZs6elxGi7TsAQ/B9O9gKRL5EGb06/XatT7QiZaDpVokC2Jcl/HcpvfZC7n5PkvlakCe70hY9O2xZzB1/0fd2KWCeK+n17fiXXh9z7mxa+JzdsqVGJHXbPnZ7owXLtAKsc5qYTfaet510INPpWdBAF61WKi4tTUlJSUlISExPj4uJsbGxCQ0MHDBgwaNCgwMDADr5xCVPIjZnpxqdJhsR4Q3IC7CCg9B9EDh1AGTgE5pg/rKsewU6mVP76sFilRz4b6PZhX2c29S3sZzgmU4u/JxCdadxl/+/2jsvuz8YxhDfkJIDgZ2LDH6mKLYOs7gpzlide3hk1k+9KC1nXFZ/G8lh2/KpUqtjY2GvXrl27do1IJJo0rXcp2bMsV39lfOmcfG8AwITY/R969pnq2sN06kCmkkWGp3m9fi0PQ/Q1t42iJFRTCcEkItuL7DCcyGkkiWG1Gl0TJ90xxCquLn/N4+ufLR09r9SnLZrTbhjk6GG3vNm5XjQb8xjy41cKETU26Nc28Xztot2wmIIVFxcXFxfX6KkBAwYMGDCglTK9jg6rYDUEw7D8/PzHjx8/fPjw0aNH1dXV/fv379+/f1hYWEhISEfYxNQUKGrISDUkxBkeP9I/iSN5+VDChpDDwsnBIRDJzC9kj4olux+VxObVLQh1+Xqwux2ruYsXOK7XSjbiuIHOX2dKMYSjesmNkSSbfuw+WwEAx3JUlSp0eR/OlFsHA0gOrlNdZqZ5NTPxRRdtRwcZvxKJ5Jdfftm2bZtGo2l/edquE4ouKrL3S8dFdcMBbntiXXrkMgc6GwCAYPgnt8SmQHGNXIaj6pw/VekbiSwPsm0YgemCowZEnqWvvE5gODN7fk9xHPPSFQcylTAEzfalO57asHTVuC+eBJlLNbEIz/6UVN5Vjz5ltuVjTTVyIiB/ToE3hWf5zAFdtBiLKVhHjx49evQoACAlJQXDsP79+5NIpPj4eBiGf/311ylTprRSptfRQSbot6Kuri4+Pt6kbKWnpwcHB4eHhw8aNGjgwIENN2B2QHCjwZCcoH9wx/DwnrEgj9I/jDp8NHXEGPPGPi2VarffLTz2tGJeH+dvh3k2W83CtLKdqLGYwf/JFIkU00vE1wYw/JbQfT9DcfD9I8lQZ5ptuhz+AAAgAElEQVSvtT44auffObPZZYzhBxzNKHYXLcCy4/fKlSt37ty5c+dOdnZ2nz59hg8fPmzYsMGDB7ezGG3XCcmb6gxyrP9mu2yZcHzs/sJpK03HH1frb5ZpVzcW/grVVMnuzQIQzOm3m8h9cccPjurKLiqffk9gunL67SawPOrPyA3YsnuSnwbyVqWcx06Q1o4f4RJhsX3Wred074L+W+2dR5izCbEfVPADqEHLW+s134UFMc9QxVtKampq3759lUql6aNGowkJCXn06FGLK3wjrZG2I6DRaKKjo7/77rv+/fuzWKzRo0fv2LEjIyPD0nK9GVQq0Vw6J1myoLqHW13kCOXvO40FeWasv1qh++riM87KK2tjchQ6Y/MuwrTyv5XC+SgiMn1GFAU1Jx10FdE4jleqkIU36ipVyI9psZHX9x8QZNcmacwocBctwLLjFwBAo9G++OKLqqoqy4rRRjXfnFOefVCK4/je3Cdz7h2vP/5zkuxuufbV8oiySHjGVZm6HsfQ11aKGlXPttWcsFHn7W94+Eye6rcUeUxFTuDvOxI31jZ6aVJSUssa0p6I0rWHuuU00QHN4dWW1j7VHnLJQY1Yq+rteHSK79RcmGWottw96NatW2PGjKmPEWVKQ/HgwYPWanzvLjQaLSIi4scff4yLiysvL//444/z8vIiIyMFAsG8efOOHDkiEoksLWPjwFwebeIU3q977ZJzWcu/R2uqxLMn1Q4LUfz8gzEnq/X127MoOyP905YPKxJrvDfd3hNfimJvfHWAqOxFJNoItehrDBUBAAgsD97Qs7IHHyCKPAGDMN2bsTtV8VX3ITmqWvVG+f0l1aCTWT+7MCeZmZmbNm0qKiry9/cfMGDA6tWr37FEhJJsPc+PAgB4XFfa3/Z5snO1Ec8UGULsXzYMY9oaccxwZsByZs81AHr9rwBMZPgv44+5p87cpkj4CuDP0ziOc6NniAxeDLcyuiT3WeOzVqcISpl7WOYzh9tEBzSHV1tqE0RluZELzylaVW/Ho1N8px2LFqtmp0+fDg4OVqlUpo9isdjPzy8qKqr1St/raI20HZmCgoK//vpr6tSpHA4nLCzshx9+SE1NtbRQbwLDDGlP5T+trekfKBzRT7l7B1JeapaKUyrkw/6IC/z5bmxeXXPK65QnFTVzUURo+qjO/af2vB+ql2I4vjlBeipXdbe6wPnUD4cHZ5ve77uwFB1k/Op0uu3bt5vS0rf/3dvophiK72FmGhQojuOBF7YliypMx++UabclyV4ujGjqLvdVpm5ofv2oXiqKHiq9OxNHDaYj14o1mxNk068c+WDKBXO0wAJgCHZAkC3N0bVF5UUX5Wf6FbZFzV20D2YZqi1fZTQajePGjUtJSQkJCUFR9PHjxxERESdOnDBL/NNG6Yw+WG+FTqe7f//+9evXo6KiEASJjIycPHlyWFhYw/S0HQ4cNzxN1F48rb16iejmQZ8xhzZuMtRqX/7zGdXLL2f1EnB2TfJ35r4hLKpBdV6vOsew2Q4T7AEAioSvEVmW1YirciP8zQPJ0mDOtqyLRjE++D893s/yonA7cGe+01h2/BYVFd28efPmzZu3b9+2traeMGHCxIkThwwZ0s5itFEnKEsM5wcXf1DmozLq7U+ul87+gQQTAAA/JciGOdP6ObxgwZLHf4Ib5dzBx9/qFjiqk959D4KI3PBTEEw2YvjXdyWB9nW/HY5OXLakM/q5l99QPVktnPbE481F3x4cA8e880YcdbLv167p1ywFhuA18ZqaOI2q3GhQYHQ7Ir8H1TGcwXTurNmvzTJUW24bJZFI169fP3ToUN++ffv373/mzJmTJ0+2nXb1vwCVSh01atT27dvz8/OvXLlibW29bNkye3v7Dz/88Ny5c2q12tICNgYEkYNDOD9ss0/IZn76tS72urB/gGzFF4aUpLetKTk5uf7vKYEOWSuG9nJkB++8/2dcSdPPOZk5hcKaoa5bhqE1AAB2320AghVJyzkUeEEA6/c0xcbe42/p8mQfyJ58L3z7FnbxLuDl5XXkyJGQkJC4uLi8vLzt27e3v3ZlAoIgCILMG5C5fn0wWVzR00pg0q40CJ4nNQbZvrD/V1cepa+6wen/19veAiJQeUPPAYDL7s4AGEKCoenejAqZbbF7XWGS7NXyDYdzxyT3mMzrfTNEomm0pRAMAj61yvxL0vr6Ow6NttSoxhI31B5yyX34dY22FuX5UpxHMGm2xNKrytPBhVGjSspvqtpf1Bazbt060wg1S20t0dFyc3Pd3d1JpNdqpgaDobi42JS/2Yy88xasRqmoqLh8+fKlS5eePHkyduzYSZMmjR07tiOHe8BEtZozxzWnj0FkMn3uQvrk9yBGy3fo5NSqPjqZSibAf03r4WfXVD0GdZReeZJhswMm2GMGmfhKKCPwW7rXR3vSlQiOu1pVfvX40n+XjZ9yydMmqEPv33xXsdT41Wq1NBpNJBI1zEL4aoH2EaaNOiFtp0hZagzb5bAl445QqzSFGH1YpYuv0i/vw6kvhhtVdRf9uYOPkO1auH0SxwzS21NgihV30CEMh/57X5Ked3eoir/qa8toqy0G0WAHnXLfz/ai27WV7U0nQo96580t8n6Hreal15R3P64SDGH0WWVjUvEbgurxgtPyp1vqGA6kwX8IuF6dKfiqxSxYZWVlAwYMOHDggELxshOfSqX6+++/Q0JCSkpKWilZFyacnJw++eSTmJiY/Pz8wYMHHzhwwNHRcdasWZcuXWpBau12ALa2ZX7yle3tBPa6zfqHd4X9A2XffoXk5bSsNl9b5qMlA2f0Egz549Gu+0XY6594MmMihTVDLVqOo2KYzOUNj1I+XWkQPvjQn1koQziwWx8bp8R1uQ+WVHV5u/9PMWLEiGPHjnE4nFdP6fX6gwcPhoeHt7tQZkaaa+D6UAAAiaLyEJvnodWThYZguxd+0lRpP5Dtw1usXQEAIJjMG3oGVRUrklbAEJjmRXexDb6hbeHotiAlV5R2IbS2064AAFRrgstoZt4xedvdwoLgGIhfKbz/efXIo04jjzq9ql0BAAgUyGcud2aaZ7dxrPMDi7L2SdtfTsvSQh2tvLx85cqVly5dCg0N9fX1ZTKZMpksOzs7KSlp4sSJP/30k5ub25treVtZ/yctWK8iFovPnTt3/PjxzMzMKVOmzJw5c8iQIR02XjwmrlMfP6Q5so/o4c38eAllyHDQIutrkVjz4ckUDAeHZwW581/r1qBXHjdqbzOsd0AwW191U/7wQ/74hCrUbsNj2VfBlOE3diw9HjFhkrff/JZknu6iNVhq/Eql0qVLl169enXixImhoaECgQBF0erq6vj4+Ojo6FGjRu3cufN1xi2z00adcCG8OGStreNQRrfTG++M+cSdxUcwfHGsaGc4n0N+PjOg6nJRVJDNpGcwzb6Vt8MMUvG1QXTvhXS/r76IrbtccSFn3nwqoTO5YV2fXu4SwWzreaDitvrR0uoZqZ5tepf2BzXgsXMrNEJkzDkXKr9Z9jlptj7mvTLHocxBu+whQidwJbJ8qpyysrIrV66kpaVJpVI+nx8YGDhx4kQnp7bKc9mlYL1EWVnZqVOnTp48WVNTM3369NmzZ/fp08fSQjUOjhh1V6NUe34FKML8z5e0CVNezTD9xkRXOA5+fVj0U2zB71MDp/V4bSYKnWIvoktmWG+DYIYqY7O+LMoq4k50GfqwSu9rX7wt6c6XX499P81smTG6aCaWHb8FBQX79u27c+dOeXk5DMPOzs7Dhw+fPXu2r28jCWHajjbqhAP2OTNSPDU8vfe5zeLZGyAApdcZzuSrfxjwrwIhf7QApgtYQT+8qTIUQ6owTAYBMkSwggmNZ+hD1eXia2GsPluSyZM2Pyxc2ANM8nshVGlHzluHaLEDDrlzC7yp1mZYvGuqpTg46pU36qSzbZ92WoNuU0wtRfX4tchSEhMeecyZQHkLVcmgwGLeKyMx4FHHnQnUjq5jWV7Bame6FKzXkZube/LkyWPHjlEolHnz5s2cOdPZ2WyZH8yL/v5t1e87kaoK5qLP6O/Nhhr4vjQzVXtiuWzOsaf9Xa1+mxzAojSuJOnkvyOGHIb1VgiiSu/OhAgUzqDDWxJlbmzSobITzk+tp2X0GXn03cx432HpGr+gbTpBL0UPu+UtkvlFV+TszLx/Y/RiAMCBTCWXAk/2fO6siSoLRVf7207Jh8iNLJUCAABuMGjvGrW3UX0GRODDMA8HRgwVAVxHIPkQqf1ItHCYwG94BSLLFMcM4wy7+NEdAUTMPj41ouHZZg5ni1B0QZHxuyQy1tUstTXd0uSf6pRlxvC/BGa5l2XJy8vzdPeKmVpGoMKjjju1wBBlMn3pZei4S906uI5l4V2EXXQcfHx81q5dm5ub+8cff+Tn5/fu3TsiIuLs2bNGo9HSor0MZfAw/qnLvF//0T+8JwzrpfxtG65Smk41czru68xNWTqEQoCDd9xPq2o8lB+V8ymB5K4Rr8JxA3fQQUSeo3629ZOe7DsV2m/9p110Tk0qrii9pjRbq7ro8Hh6eq5fv76wsNDSgpgfaY6e50sGADwVV/TmP08J9bTW0MfuX7cYVcYWuu+nr9GucIP6ikI4x6i9Q6aPYTmcYdkdZtj8wrT5g21/mmV3hMKcihmLVbUL1OJViD6t/jIi15876LDi7ntDasrFsMNL/pEdVrsCABSdV3hMZbfgQj2KSA1auUHX8GDTLfX9kFd4Ro5osBbcrqPh7e39YEk1asBHHm2JdgUAIJChUcedqHxC9LQyDHn3X7c60ztl1xtwM9HpdBcuXPj777+zs7PnzJkzf/787t27W1qoRkCK8pW/bdffu81c/Blj3iKI/nYBY06lVn1x4dmmcb7zQ1waO49rpFtwTMngb0A1NeIroZwBf2dTRuzNUPYUlP6SfHvp6nFzUn3I7K53jHbCsuM3Kirq2LFjly9fDgoKmjt37vTp062srNpfjLbohOwD0qp76uEHnSbfOjjbo/c01x7lSmRLonz3sOcGJ1RTKbrU02ZKHkx5uck4JtdINwFMS+UuIZCadBXCDQbtLb3yJEywpXI+ri+sztolTdy/lHVkWk/edI9GR2LHAjPiBxxyZqY3NwF8hVp+qjg1tio/XVol0qkZRDKK4wiO+nHsBti6jnHyHS7wIsNNLTVenVDqOZ3jM9cMISEsy7M/JM/2SKY+dCexWjVtYggePbmMZkscttcRdFQz1v/WEqFOjNKsibtBhqUF6aKLLlrC5yDQ4rONQqE4f/78mTNn4uLihg4dOm/evHHjxjURccbstIWCFf9NDZlLCF5p43J6470xn7qxrK4Wa6rV6MKA545Byqff40YlO/SXly7EkCq1+FsSbRCVvaDZqxmoQR2tUx4mUftR2QsgmAMAqL36UXJJ0Umv/YdGtUnQTvNScUv1+PvaafHubyyZK69bn3rjRmXuVNce45z8gviOTgwOBCAAgMqofyareVBTHFWemSevm+sZ/LX/YEd648uvRRcU6b+KJ90x/8av9qQuWXt5bOnUR+4cTzNEW0A02MXhJc7DGaEb7VpfW1tg4WTPJmpra2/evJmZmVlRUdHKqt5I66X93wRBkCtXrkRGRvL5/C+//LJjppc25mYXvj+5po+P6vA+3NjMfM84juMqPTL9cFLorgdl0kbSOWOYTln7uVb2F47j6rx9ted99Tr5ivvicwUSu+PrVofer3qgNlsbumiSDjJ+k5KSvvnmGy8vL0dHx759+zo6OkZHR7fb3duiE65OLCm8IBdqlVbHVmM4huP4pgRpfNXzDDAYoqs5aW+U5bx0FWqsVFTP0Ksut+COGKrSynbLq6boVRdwHMOMhuQfev51+qtnIn19mQ6bGPje51XJmxpPUF2PBjGsSLxie3ztprRbCsMbculExd1blhDFP7Z6eeJlmb6RvNqoAdtvly0r0L96qrNgUKFHvfOub35qxjq1dchR77ys/RIz1mlGzDJUW1XFL7/8QqPR6HT6pk2bpk+fPmXKFAxrw/zhHWSC7ryUlpauXr3a2dk5JCRk3759Ol2bJOFqDYZnaaL3JwmHhWivX23+VRiG/3ynwGHdjUbTF2KoQilcoFMcw3FcFvcfye0p1Srjwht1/2Rnuh/86WDPLET/riW975hYdvxmZ2evWbPGy8uLwWDMmTPnxo0bKIriOH7gwAEbG5t2E6MtOuGoV64kWxdTkTMs+k8cxxEM/zCmVqFHTWc1BYfFN0a/dAmGShXV7+tVV1pzX9RYqqz9QlX3NYpUX46ITz9k9ce1o62psD3A8IPOOZLspqa+DEm1//mfZ9w5ItQqm19xtUax8OFpwcn1J4pSXj374Kuqx6uFby1th+H2wopb881vQ5Hm6PbZZtc8buTd2OJYWMFKTk52dHTMysratGnTpk2bRCKRn59fTExM62V6HV0KlllAUTQ6Onrs2LF2dnbfffddWVmZpSV6Gd2dm7WjB9ZNHqVPfNz8q+4UiBzW3fjlftGrpzBEpKiZo1ddxhCd6Ep/Zcq6exXar++KZt05GbnqcKee+DoRlh2/MAwPHz780KFD9fnpTRQWFk6fPr3dxDB7JyA67C9aJmrANqXdWpYQheN4ltjw7QNxfQHRtUHa0hfzMWMGZe0XWvlBc9wf0ylPyaumZO4/tvLP9fmHrbKLO3Si+roU7RHP3CYKnC1Oszm+9mB+Ysvqf1Jb6n/+52m3D9VpX3jM6lK0h1xzMbRltVqY0hjlYbdcg7JNpC+OUhxyydEI32LVon0wy1Btuava/fv3P/jgAz8/P9NHPp8/c+bM9PT0VixXdtEewDAcERFx9erV+/fvq9XqoKCgyMjIq1evYlhH2edCCR9hc+0+Y8586ZKF0s8XoNVVzbkq3IMf/0XY3idln5xLR7AX1s4hAp/B36pXHkGMSbxhFzQFB0OMl32tyEGsUYndS87fyhQmaNumKV10FMrKymJjY+fNm/dSmil3d/dTp05ZSqrWI8/Xs1xJMAlKkVQGWTkCAJ6JDIHWz71kEHkuoiigOo1reIlW8TdM4FLZ88xxf4jCnM602WHb7+5M35rz7Ol43HuYoeMG7C65onQd/9roXLuzH32dEHV91KIPPFsYUDDExiVp4lduLKuel7bHVP4b4N66F5XCgavudch8sk1iVGF3P64M/1tAYrbJfiDXCSyfedybsyvwjvL7Y05a3mVcLre4uLjhkdzcXDu7Duqw1sWreHt779q1q7S0dMqUKevWrevevfs///yj1VpM1cjLy/v3AwzTpsywvZ1A9PCqGztY9ftOXK97/aXP6cajPVoysFyqG/PPE5n2hRAVMNGBzt+ole7ACSLe8Evyx5/Otc+t0+ArA+YdWfTg0seFiPZdHN9d/D+Ojo6WFuE55k32XJ/mOUVcGcR3BABkSQz+/OcKliZ/H91zHoD/9eI36uIRbRyNuxyYb/sWTOwGYzsNSa6TepTW2fUvvz4ZxwwvDOcOQ8llheuExgM0bM2482vWgwdjPwviv92j8lJLqQTi1j7jTwyZ8/Gjs6uSo+ujV/h+wM053EhW7A7Ok9VCp2FM5xFM8EpLzUXIejscB08317VF5W+L5ZM9mxCJRP7+/tOmTVMoFFQq1cbGZt++fZmZmW2XdKIrTEObcv/+/e3bt8fHx3/00UeffPKJq6trOwvwuoDIaFmJ/Mc1SE4mZ8NWypDhb6wHxfBlUVk38movLwjx4L9grkD0yRrpZgb/Z2NloiJphTH84boUCpGRlHevfL1wfNiu10aH76L1dI1f0AadkLSxDtFi3ddxHE/9IJv9A4ZDC2+K/hpuTSNCAEdrz7hYjb5F5DyPVo/jGpVwPo33HZHSw4wyAABwFP+Hmy28ETPf8aGuVm1tcIQDf+lokdw1QuS4b/78Wl+Y9PLP52/ZD3/LenhnzCev2wnYBK+buOp0qhl3j9KJpBND5rBIFG0tcswn/4NynzYyBbUFdSm6K2NKZj3zMoW8b7vo/OpK4+k+hRFnXRwGvl2wnrbDwoFGra2tY2Nji4qKrl69eurUqSdPnly/fr3dUnp1YXYGDx586dKlx48foyjat2/f9957LyEhoT0FeN3QJbi4Wu05zFm/Vb5mhWTRbLSirOl6CDC0a5L/kjC3sN8ePSyWNDxFpATTOJ9oxN+SnQfRPT+kPnlvlheRbuxb560+VpBSdl1ltsZ00UW7IM3W8/woaZLqAK49AYLzpUYXFpFGhAAA+uo7MM2hXrsCAOgUB4iUPmbXrgAAEAHi96A6Sod8mhsuZvXBbIugim1mv0srKb+uchrBeFW7OluS/nPG3diI/7RAuwKvn7hsqMwboxa7MHgDr+4uUUlotkTBYHrh2c6T+xkH9z+v6veTXX1CobbTmBmOpGF7HW/OLtdL0Ta6hUVolSodGBgYHR0tkUgUCsWtW7d69eplLrG6sBTu7u7btm0rLi4eMmTIzJkzBwwYcOrUKRS1/ENPCR9uczOO3KtP3YRhqn9+BwjSdPlPBrgemhU09WDSmbQXXLhItGEU1iy16FtGj69gukNw9UpPLmmq46wz7z05szLHoOhaKHxnwXE8JSXlwoULer1eJBJZWhzzIM3R83woaZKqXnwBACBTbOzOf74gqC06RvOYU18SNRYbNbepnMVtJIlNb5p/ruP92joD+9sY6TyEdldd9j0AHchmWXpN2W3MyypCkqj8s/jzl0fMd2GYPxAoEYb/6D9lsU+/gVd3P6kr8/2Al3Oo06wS5hyW4Sju+2Hb5sOup9s4lvsU9p3Fle1zu/ahJUawuLi4uLi4Rk8NGDBgwIABrZaqcbqWGNoZFEUvX768c+fO8vLyL774YsGCBR3B5o+UFMlXL8dEddyffyMF9Gy6cHq1YvzehK8Guy8d8kJcQZ1iH6JPpXPWia+GUfy+/rFuGoFceSHh+q8ZM0b+3UHTOHZ2LDt+KysrJ0+e/OzZMxzHnz59GhISEhMTM3DgwHYWw8ydgIO/2VkfVvh8+uxcH77zf3z7r38sneTB6GlDxlFd7SmBzeRMmPZ84VstWk6ihZEZkWa7+4tkH5BW3FLvW3h3hMCrUuIzjvfEA11D4vWg2/4IE2zb6KbNB0fx/XY5szK86A7/BnAXapV9L/+yu9/kiS7+TVzbeq6WZ89/eGpP6DRJP+J7Ce4sVzPE6mxTDArsuF/e2Evd2jNNNarHz4YW9viC7ze/nbS6JrDYEmFRUVFsbGxsbOzPP/+8ZcuW+/fvx8fH79ixY9euXTU1Na0UqIuOA4FAmDRp0r17906ePPnkyRN3d/dVq1YJhcI2ul1ycnJzihFd3flHzjEXfy7+YLpi4/e4uqmNOT0c2I+WDDyQUPb1pcyGudKo7PkEootWuYM3/JI2be1XzqkihYO3l/tu9H7p1a4che8gn332WXh4uFwup1Aofn5+W7du/e9//2tpoVqLuspIYsBkDiFNUt3TSmDE8CI54s0jAQD0ldEkfu967QrRP8VQEZkxvu2EsQ2m1SVr33PtcaYk7X1fxp7iHmTW9/qiJyrhYoP6qsVNWTWPtSwXUkPtCsGwGXePzvcKeSvtCsOBWIdVqhD0/xv0OOlpmRKR6LAmfo7HOftdG7Xw88QLzz4v7hSu7onra7uNY72kXTVzim4xBAo08rhz/LdCWa6+TW/UbrRcR0tLS1u0aNHt27eZTCYAQKvVhoeH79y5s8uC9a5SXFy8ffv2EydOTJs2bcWKFR4eFk6LgUnEih9X6xPiedt+J4c29dTJtMbJBxKtGeQjs3tTifUvFahavAomCAi6QOm998v63j1YYnWxat8Hv/f//sJAun2z8pR10XwsO375fH5lZSWVSuVyuTKZDMMwHo8nl7e3Q4x5O6Hyjjphbe2Eu924x74XzlpXoYQOZCo3h1kBAKR3Z1AEI+neC00lVXVLKMwpJNrQ1t8UxXCZ1simEkkEGACAYHiNUm9AMC6ZeNahYGaFR7erGwumrTz0zOjJI41AjqsLtlGDh8AEBo27FCY6tV6AlvHkeyGOg34//rvP/Zukq+mS6qsjF8BNbhnTIni2xJgvNRYrjFUqVKLDmGSIRoCEGtSkYxFhyJ5OUCOYyoDzqLAdneDIJDgxid3YRFc2kdwgKXKxUjL68j/edwVRf82B4Y6ahA8AWb7h/MCiWZmeNBsLTIOZeySZ/0inxbu/6i3Xnlg4F+GOHTvkcvn69evrj6xZs4bBYHzzzTetlOl1dClYHQGRSPTbb7/9+eefw4cPX758ee/evS0rj+7WdfmqpdSRY9nfroUYzNcV0yPYhydTq+S6ywtC2NTnswaOa9R1X5JoQ5EKiTbvnxi3mDQFejR7//ao6e9H+XbYLKSdFMuOXzc3t+vXr3t7e5sUrPz8/NGjRxcVFbWzGObthGd/SeqStXY/EyffOpg79ZtLhRqZHvugOxNH1LWnnWymFpqyOyP6JJ38T6bt3paFZlDqkdv5ooQyWXKFLLNGWaPUsyhEpR4xRZsjwJADi0ImwiK1Qa1F+TQyStW48uh9HATpUvBlX7638qS9+JDVkP/qtefJjEgKayYEUczVA83ndHDhoF8cHMKeb1K7Wp79afy55IlfW1MZjZaX6rH4Kl1Cjb5EgXhyST48khuH6Mgk2tBg4mt0IwTDxTpMqEYrVEiFCi2WGytVqCub6Mcn+fLIvlYkGhGS6DVh2/508+KdnTqXRmi/JJhvRfSUMrt+9N4rmrtlrVqjyJQJCxSiCo28TCUV6pRFSkmJSoJgGACAAMGOdLYTg2tNZVhTGM4Mrhfb2pdr68uxZRAbXyqNmVbG86OE/mDJqE8WVrDOnDmzZcuWe/fumQL3SSSSsLCwLVu2TJgw4Y3XJiQkhISE1H80Go3Pnj0jkUgBAQFNydqlYHUYlErl3r17d+7c6ePj880334wYMcKCwiZeP14AACAASURBVGAKuWLjav2je9yff6MMGPy6YjgOllzISCyXXV0Yas14PrBxVKwSfUVhztCmX0HVVTuoB2qRotR7CXuY04OW2bRXC/4nsOz43bBhw5EjR1auXPnll18eOnRo7dq106ZNW7t2rXnvkpOTIxAI2OzGIy0Bc3fCo2U1NDtizrTyi6XPTg+duyVRFu5MC7Wn6ErOavL3W428ZiqmFi0l08eS6G83SDUG9FRq1YmUyidl0n7deP278YKduD0EbCcOlfAaDePW55W4G5Q4oPJkfvZcl4ExhXKRUqfW6iqlym5UcXdXd3dOoQ+vILDbCD/HIfXvOe2ARogc98ufX+sLEyEAQJ1O1evSjlPhc8PsXk7AjAOQWmu4XqrJlyJ97cmh9tQAaxKppdYmPYoXyIzZEmO2xFgoMzoyiT2syYQH6j3ia+oAZdTw+a9T7yxITbzmxqzy2TneBGpTrc6SCW9XFzwQFj0UFhswtAfPwZNt7czgujC4NlSmG8vKncUnwwQAAIJhlRp5hUYu0qnrdKpytSxPXperqMuR1VpTGT2tBMF8p2Brp2C+k4D+fOBohMipoIKIM5aM2mBhBctoNI4bNy4lJSUkJARF0cePH0dERJw4ceKNEboOHjz4ySef1Ae0LCwsHD16NJPJlMlkXl5e586de9301KVgdTSMRuOJEye2bt1Kp9O///77CRMmtCY+W3JycnBwcIsv19+/LfvmC9rYSNY3ayBy46/IOA6+j845m14Vs7ifm9XzoYsh1WrRV1TOZ4r76xFu39XK/+aqbggOU35dNdYmuP0cPN95LDt+EQTZtm3bvn37ysrKBALB/PnzV65cSSSa8zc+LS1tyJAhMTEx/fr1e10Z83bC1Qmlfgt4e5wesEmU73qMWHCzbucQPocCyx7MI9sOpPt8DABADVkayY8s+8MAEJpZrURj3H638O/Hpf1deR/1dRntY0MnN+tak5972CE7wckN57zG9u0VuvSeZMMAnhUFenp3XVZpaZVgWVadOLumqkDKoBBJvrbc7nZMbxumry3T147pwqVRiG0SIyr3sKz4siLijIvp45TbB304tpuCxzYsg+Egrlp3sUBDhMEYV3p/B0rD1b0maObEheIgV2LMFBvShfqiWiOZqczX5mwJDR3o0LFe5C4MKfb7iNvo5sHE5CSVgHuh9Nnl8iwAwEiB1yB794G2ru4sfgtuhOF4qUqaIqlMFlUkiyuSxRUkmDDQ1jXMzm2gravVE/ajJcIZKR5kTnOfW/NiYQULAIDjeHR0dEJCAgRBAwYMGDlyZNPla2trV6xYce7cOaPRqNM9D8w9atSogICAHTt2GI3G8ePHh4aGbtiwoXFZuxSsDgmO41FRURs2bMBxfPny5dOnTycQLDMkMJlU9s2XaGkxd9vuJjYY/hlX8lNsfvTifgH2zzdFosZitXgFlfmVLGauyOuHX0SjLlfu//jgwO+iBnSiqIAdnHd4/BoMhm3btu3YsUMqlT569KjdFKxjPvljLri8X3F4iV9YD67X9mT5rnA+wBDhaQfriakEuiMAQCP5gUgOIDMnN6dCBMN/e1i86Vb+tB6C/4Z7uPPfzn4gTtddn1H+frbXzLtHRwi8FnqHXi7S5EiMy/twAADK5G/1FdFWo67DNFuDJrZKeDJf7lWoGpovYWULVXl16kq5VsChevAZLjyaC5fWjUdz4dFceDRnLo1MaNUwvPF+ufMIpmlv2tHC5K0ZdxMnfEkh/L+rAAAJNfpTuWoWGZrqyehh0/i6FW6Qo5oKVFmMqstQTRWmF+FGFWaQospiRFkAMOPLF8BEItOdwHSBiAwAk2EyDyIxYYo1TOWn7jHoetgkO5KyVXwK3bmXvU1PG7I/n8QiW3i2KY1Wxi2vmZnmCb2oXKZJqo4UJp8oSnGgsae69oh08e/ONf/6XalK+lBY/Ki25KGwuEwt9RHZ+4kc5n8WFGLjQiW0tzeYhRWsqqqqqqqXk8QJBAKBQPC6S9asWSORSCZOnDhx4kSTgqVSqbhcbkZGhimn4dmzZ1esWPE6x4h3eIJ+B8BxPCYmZtOmTbW1tatWrZo1a5Z5zQPNR3vhtHzjaub8/zA/+RLAjU9Yp1Krvrz47MKHffu7Pn9RMwV5p5IXS2/MSfE5c03hfjbn4B8psyb9ZWFf/ncGS43fbdteG/HSXBsJr1279ueff27evDk0NDQ2NrZ9FCzMiP/Nzlok6+54YUPShK/yJORsifGznmxDzT1F0n+txycCADBUpKpdyLI/DkFvVpWyhMoPTqTyaKTdUwK9bVqydIUh+F5e9kdVvlHiZ3tyH98YvRjB8GX3JQsDWKb0iKr0H7UFB61GxhBYHgBHDJoYvfIERLCmMCNJ1EEoTiyWaArFmjKpplymK5VqyqTaUqm2SqHj08nWDLI1g+zIoQo4VBsG2ZpBppMJVnQyl0bi0ogcKolLIzXqHYVj4IB9zvSnHkwnUo1W2evSjuiRC+vz4RTJkX3PlBiOz/Rh9mygWmF6iVGcbBQ/RWRZiDwbVeTjOEpguBCY3QgMFwLdEaZaQyQWTGbCdAeY5QhBMI4rIZgLE/jPjYWYEVEWoOpKHFEBzIgZpLhRiWlrMYNMVSaR59fa9lJp1NWoXkwCsI7IVwCenmhDpduwmDY8ji2VZgU/V8isIQofptrAZPNH6nqxp8DpPoV9Vtm4T/n/pTrEeKIo5e+8x0Ktcp5nn9nuvX04L9jbVEZMYcCVBsyA4mojbsCe/61F8HIlkiEyGrFmPe0kGPLhkXKlRgCArxXJ14oEQ4gBqTyy+6mkPy4hod5sqx5W9kHWdgE8Ox6FRIIhCgGiEqHmGRlbgoUVrI0bN27cuNH0N4IgKIra2tquXr36888/f90lOI5DEJSUlBQWFmZSsHJycvz8/HQ6HYVCAQAkJSWFhoa+Lqzlq8tPa9euNaX0amikzcvLc3BwqI/Y1PBUw7+VSmV1dbW3t/erp7pqaE0Ne/bsOXPmTHFx8apVq0JDQ11cXNpfhpQb11327cYBztvxZ6Fa22gN13Pr3j+ceOqDviO8bUw1SOsu8Bg3SIaJisfL9rHPFhDo6bfunQyeh/ao6aTfhQVrOH78eMMdMCYsomBFRESYpIqLiwsNDXVzc6usrHz48GFERMS1a9fMcgvTzAYAYDKZb1SwXjrS4klMlm+4NKrI64o+Mv183az1f6UriPLqhYN8FIn/hcnsKtpMBwcHEn4Ox5Q07pI3ft37npStvJa9uDvth+mDTTK27IE53Ct9+C4Pq0FkwckN0b2m+bu452vJR7JUWwdbpac8DQ4O1uT9rUxZW+vwQ+Bg0w5HTCGJ1auiKKRqMn0kiT46NV3yUj8wmMxqhV6kNsSlPGPYuVTItSKVIa+8msbiSpQ6VKXQKNRalQrSakgowiATCnlOHBolSFZCgfFUbrcMOUBezGRvq5N/mnd1TuFtGmpozvfbxf8gjmUyCy8RNiQpKWnx4sU3btyoz5aDIMjjx49Nf7u4uLi4uNSXrFewUlNTg4KCUBSFYRgAkJ6e3rNnTwRBGl1j6rJgdSIePXq0cePGjIyMFStWLF68mEqlvvESMye6wjDVP7tVf//O3byLOnJMo0UeFkumHkzaN6Pn+O7Pzd06xSFEnwBqnTUFp7dxoh6Lk1wP4bt/Gcd26+iBATs+lh2/M2bMmDhx4uzZs00fz549+88//1y/ft28d2mOgmWuTii9pkz/VUzep/85425sxMdL70m+CGK7sol1F/25YYdI1n0AQJU1sxjWP8PEbk3Ug+Ng+ZWsa9nC8x/29bV97T7cZvJwaTXdntR7hfX02IPDnX0+9ukPANiWLHfnEKd4PreK6atiZQ/msHr/RPeaX38hhlQZNNFGTSzAqQRNT1giAEo2LpOjEjEmEWFSKa5WYXIZrpBjahUuk+I6HaZSAgBgJguiUgGFCjOYOJmMGREsLxsAgPgEYDBMzs4AyMtaFESjqSbP2xvykbcH6z3HfFh2G1WmovoSiM6AGTyITMAhAwRTIZgLwRyYYAMTrCCYY/oIwXQIokEwB0AUGOYAiNiyiStuRQ1EgPpvsgMASPSaaXcOk2HCoUEz7WgsAACGg1IFkis1FsqNeVKjRIcJGAQ3DtGFqnakqPgEBY+MEI0y3CjHDDIcNeCIGpFn64pPARwj2YRAMMVQ+xBHzRZNCoVplXYL6gSf861dOWSIRYaZZJhNhptpQNLr9RqNBsdxLpeLYVhlZaVOp3N3d0dRNDU1lUgkBgYGmowsGo3m4cOHZ8+ePXr0aL2jtqXoQAoWAGDp0qUeHh6fffaZ6aNEIql/rVm2bNnKlStNfzdUsMrKyrp16yaRSHg8HgDg3r17kZGRMlnjcdi6FKxOR2pq6vr165OSkr777rsFCxaQyU2pKXl5efUPjLkwpCRJlyykDB7G+X4jRG9klSSxXDZxX8KvkwPe6/l8aVsr246hYiRPpFbWrQZ/3qo5/fHpPivO9SdQusI2tArLjl8ej1dXV1e/bI0gCIfDUTcZpbYFtKeClfaLWF5giF+cU6tVbQga/9lt0f5RNri6RHS1n930KgDBRt0jg/I0w+aXJioxotj8U2mlUs2l+SE8mhmiBuSflBeelUecdfnz8c0zssLbEf8BAIi06LcPpT8M4Dkwnr85I/Jc6Y0pBIMnzWouViNGqyrRqgq0shytLEdFdZAVA7YhAS4O86xgK3sCvxvRxoPAdobYXJjDhegMmGcFUakwkwWa4e4ZPTkl8Asyp698/dNjCz3dBRSjUFFOwWvYJCWEG3G9AQAugexKZPUg0nxggg0EcyGCdfNjSbRs4pLm6C8NL55X6mPa2Iji2IbUm3vznhwd/P5QB8+XChtQvEyJlCqQKjVaoUTqtFidFqUQIB4V5lFgFglmkSEWGaYRoYECKofyr1+EHsUzxYZyJapHcT2KqwyYDsU1RlxuwFQGTGHATZWwyTCpBqnIFVX0qCrV1Exz85ls72xFImiVco1GIxKJtFqtSqUqKioyRY8zGAxKpVKj0ej1etPHvLy8vLw8AICnpycAwHRcr9erVCoAAIVCodPpEATJZDIIghwdHclkcklJCQRBgYGBKIpmZWUZjUYAAJlMDg0NHTdu3Pz5821sbAAAOAaiRpUIBtP7rmkkH4BYr3kmrU6VVGXLarPlwiyZEMGwbkyeC4PryrRyoLNtqUw+lc4kUhhEshWF7sayMu1tBADoUCRXXis1aA0oKjdq1UaDWK+p06nqdOoarfLaqIWtH6pm85JBECQ7O9vHx6f+iJWV1RsTfjk7O9vZ2SUkJIwePRoA8OTJk4bhG7ro7PTq1evChQtJSUlr167dvHnzypUr58+f/zo1y+zaFQCAHNTHNuaBfO03dePDeb8fIPm9HLK5rzP3+sf9xv7zRKY1LurXDQBA436tkawn+bhQnuQuY/wCCb7YPf6g/ze2E3e9POt10YkQCARnz56dOXOm6ePevXt9fX2bvqSDI8/Xc70paZKqMU6++TKjB4cEQ0BTEU1xjAAQDAAwqK82HbodwfBZR58aUOz64n40knk2ptiF0OJW1AAAPuo79PtTDyo1ckc6x5pGmOxGPXM9bSGxBHmWhuRlGwvzsVoJapumZ8VT/EeRPUNIPXoRHJ0Jjs4EaxuT2oRjStSYixryUGM+anxqRGMhgjUMW0EEDgSzIUAHaiKB6E6k9Qc4atTextBaHNcD3IhjKhxT4ZgUxxQYJuu9jkq34xcI8ZE2ZI62riAvy06ZSqE5Em1GUJynkFx6tSw8WD0tm7h4vhS2G7ksRuU6ngUAIEDw+qDRg+zcZ98/vtA7dE3PkcQG/qNkAuTJJXlyX9CAFQZMosNkekxpMP3DS5XIiTtiA/qvWkCCIVeq3hqRQ4hOKxcTUINWLka0algtJylkNIVMo1ZliMWVckl+eRUARroRM6g0qzWaLUwmiUTi8XhUKtXa2ppOp7NYLDqdTqFQOByO6ZRAIKBSqWw2m0wmu7u7d+/eHQCQm5tLJBIpFAqbzaZQKK1flIBgMPKI06ngAsdwhmDwy66BfAp9iL3HEPt/PWUlek2ZWlaqkpaqpFUaeYFCJNar1YhBZTSI9Or66FwAABJM8OXYWlHoZJjAJdNoRBKfQremMrzYNnY0plm8B1r+OrV37969e/ea/sZxvKqqSqVSZWRkODm9IVZvQwsWAGDr1q1//fXXzp07JRLJsmXLTp069brdiF0WrE5NYmLiunXrMjIyVq1aNX/+fBKpXYPsaS+ekW9Yxf5uPX3arFfPForVI/96/MUgt68GuwMAcFyvFq0gEDyUt3ekOvx4TB369NG1s37zfGa2sZPpO41lx29MTMyUKVMCAgIcHR2Li4tLSkquXbtm9rQT7WnBihpd0vMr/jjdnuNDZueK2BgOZvgwpLcmUt1n09xmYGidqvZjlv2J11licBx8dCq1Vqm/OL9vK/fovcR+25yZaZ50B+LnNw6GlYvGCpX/x955xzWRfAF8k5BAIKGFLr1XqQooomJFEbGL7WzYznKenp4VRT275089FQsWLCiKCqKAiggIgoKK0nsnJIH0nuzvDzwOkZqEBGS/f/ghuzNv3qyZ2ZeZN+9xP2fxvuZQFVUFVg4G7i5IW3s5Mws5AyMAgWBXx1DfrUfpjMG6/tVy7LFTQJ5QgBcKmkAhBRRSQZAFgDwBN5/HeQ8AABLtjZAzgcFQAAwFgyvBYBgYQhUGV62MhRWElVrsTcr6GjYCVl+FdMWZzbK0nw1H60iwy6KRH9ZcEUPzfWTY9iKeRVuWeo/IZoR5zbNX61RJBoNBJBKJRCKBQCASiSQSqeUPOp1OJpNJJFJjY2Nzc3NzczMGg9HQ0ECj0S3/4nA4LBarpqamqqqqqIL9RCckUKvQXAXvr46bj41UU1VTVVVtiW3Zr6iKo79eVTsv21xBQ0pH1GXs5J6dnZ2dnd2qChqNnjRpEg7XfTyMwsLCDRs2JCQktF4JDw9/8uQJDAZbuXJly1JWx7pCBtbAJzMzMzg4uKioaPfu3YsWLZKmmcUvKWpaswTlPEzlwHHYDz5h1WTWuAvpKz0Mt401BwAAFFLphE1yMDdqYsgTvXvRzUhYZMXN3bPVrGUQhPrnQObjt6am5tGjR/X19fr6+rNmzdLWlvw5c19f35MnT7b8lO8QCT6EcNOiyfEGRukhzQsPnMqiTzBCu2rC8Hc1tWaXweVxHFq4UEBGq27orPr+hKLn+Y2v13lKau3qG0Lh63FPzS0+KDS8ZZcUfjbUHT11HsrJFengREAp737bvNdD1QD73c4JyKPTvxxmFoYqWqxQstssKdOHR8ri1MQ2pjyWV6pIQ1vXYRZxNaYEORuqyveXwCs8uvCGYeGCPIt2iblAAPzn05t9iQ/HY/XHo7QZZAqRSGw5tt/Y2NhiSAEAoKGhgcPhtLW1cTicxr9gsVgVFZXWj6qqqh3GJqxhUM7lp14tzvTWNt1oNap6NN/n2hC9Uf3OrmrLu114/DvmtHjjlk3VvkbGBta7d++wWKyd3X97LjExMcrKyqNHjxZTp86Q+QQNISnevn27b9++srKy3bt3L168uMUzRsxAoz0BZDLJOzfzC/PVzl+TM2kff6GWwh57Pm25u+GfPuYAAAj59XTiJjneCFr6yTNqMbHEgon3NQ/f9ek6wDFEZ8h2/H748OHHi25ublJWQ1IPQcABL6vmeVarLUi5/XXGH0EviCe81RWbU/4N0ADS8EsU1YMRyI73tR/k1P8Rk/duo5c2VjI/GEAel/s2mRX3lJ3wjANqsIZ48+Za2QYuNIo6+nLyamuVb94zyTXsmDLmX15qP8ZGFzDrGF+OsMpuyw+ZpGixEqUzpmWjs1cIGFXc+tecuhfchiSYnJK84fTkP+w+7x76kY37xRrnZ6bUF0NX5ImLRCI9DPpAx+ARrs2VlZV4PL6hoaG2tra+vl4gEGjr6jDQclRleXcTq1Fmtob6+kOGDNHU1NTU1NTQ0BB5keltY8U/+W8TagsXm7tusPEyxeK+Xmwqf0ydFmfcbV0pTNFdAAqBWP9KFVPUqDO6UmhOZgbWu3fv6HT6zZs3NTU1fX2/nc8CQTA4ONjf3//PP/8UU6fOgAysn4zU1NSQkJCysrLg4OCFCxfCO4lZJXEYt67RTv2lsvcvdMCcdrfqqezxF9/NdtTdP8kKAAABN59B2g2n2NHyH+9HP4qre340Z9y80zbS0fMnQ7bjt/UcKwiCXC4XDodbWFgUFBRIWQ1JPYTmfM6zgCr4c/rjqq+nhy04lEE+54OjZe8GABDrcojP+cSmXMBohXZYNw9PG3M+LX6Vh/MQFfE14RXksR7cZUbdkzM1U5jkh57sV5OjnnOW1PLC3vbhqRwM/lebmOlnPlIV5GCrHDp2zRFyyazScFbxNSEbj9KbKK87FolzRShbwOAdOW6CAgG9kk/J55FzecQsHiENFArkdUaj9CbI64xGYM0a89hHbzaUjBQEDVXwM+py/7HPEAqF1dXVVVVVFRUVVW2orKyUl5fX09BH1Wp4rbA3MjLS1tbW1tbW19fX1tZuOfUFAEA2qTb4Y3w2qWa9jdcqKw+cvIipY0pppNul2XfLPoIAuMZqxHLLYcpIBQAA+EzhLcviqdGGmi4DIGsFlyKIdC9z2a5hs6yDQPOSRWYG1pkzZ/766y86nY5AINDob/8rcDhcX18/IiLC1NRUTJ06AzKwfkqSk5N37txJpVIPHjwoZrKdnsMryGteu1R+5CjlfUdgct9tUxLo3Amh6ROtNI9OtYXBAD77HZN8CqzBkhobQuAX0nKiHuovcljQ0zSoEK30n/FLo9F27dqlq6vberRZakjqIZRH03IvNaXvz1NAyI3RHJWF5/zmokJ86q7sdhSlM4ZFPgWXM5DHtP/9AAAAmy/0+F/Kb96mS4cZiKUBn89KiGVcvySorlScNR89K7B1SZiJ59+1K15BsAFgwNfmhqkvrpTP2QX/d1yz+eCut81TTdE+Bl290fnUYm7dS25jCo/0UUAvh8vjYChVAbUEFHIBOFIOaw7y6UJ2IxytK6diLadqh1R3Qmq6yylbtEpoZAr+imuqZtfrmVSd9ezK2V+CVFVVFRQUFBUVlZeXt/xbXl6Ow+GMjIyMjIwMDQ2NjIwMDAxaPmIwGAAA7jmXjDiuYzC+qwAZX5sbTuclP6z4MtXAZq6x43g9S0W57p0ruELBe2L1y7qimKq8GiZlvonTfFMnd01DWBun/uxjREIWa9I98b4MUqS5gPN4TLlvlKHOiL5NUyjjLcKwsDAtLS0/Pyl9cYH+NEFDSJyYmJh9+/bB4fDDhw9LJ3U0yKA3b14DUihqF67D1b/zHSSzeL6XMxz1lM/PcoDDYDzmCzY1jJdPLOHaHuetwT9/+3jtInX77iN7QbSlX41fKpVqZmZGIBCk3K6kHsKnk0R6De+4X9xS82FkupEmGjFFn9MYaawdSIDB4NSGuRitC3BEB05mv0Z9obL54QucRW4a5HKY9+/QL/4PoauntHQVepIf8EPOhptGhdMTTVTMUAAAuEb/fXzYNJ82oQfqGIJ96c2/u6hYq/fMBRMUClj1IKcJgTWDySmCAraAWgxDKsMVdTte2QKAt3XsG7l05QzCbYP7hQu2t6zWSBYKhVJYWJiXl1dQUFBYWFhQUFBRUaGhoWFtbW1paWlsbGxhYWFubm5sbNxiSHVGbmhT9Qv65AeGXZRpoYnDvFP28VHll/fEakd1PWf1ITaqWoZKahoKSig4QlEOReGyapnUKkZzGY30uak+m1RjpaLlo2s+Rd/aS9sE8cOWK48mvGVRFPDaRM1mILmWVsXTE5fXzEwxVTbtw/CEMjOw2Gw2j8dDIpGtJwFbUVBQ6ElISdHoVxM0hMQpLCz8/Pnznj17hgwZcvjwYXd39z5vUiiknjzEehSp9k8Yyvk7dxwqmz/1SoaNNiZ0tiMMBnDoD3iMp6x3714r/BpKG2rwoOlSqL+sspAOUPrV+E1JSZk7d259fb2U25XUQ0haU6cxVGG6VmjcxKDrXxCLbTDG9KfMwkvqE57z2e84tLsdhr96VUxcevdjzh9jRAt5BfK4zLs36f+cQto7YtZvaTdk2hI3u0rRi+n9mzUAAOfy374jVN7yXtC2QA6R+88n6l4P1SEYCSfUYvHBsFxaKZm31g47/uLJA/4TlwyVgNuQQCAoKCj49OlTbm5uQUFBTk4OHo+3tra2sbHR0NAYOXKktbW1qalp65ZOz+HRhTeNCud/sVDS6+mjoPM4mcTqz011RVRCFZ1M5DC4Aj6Tz1NBKegpKhth1Iwx6g5quu6ahlhkV5bTh4MEciFnfHg3B/9b6YtQhaLx9WLT51PEmW9N0Zp9kpCt8CbZ+hc1CQxVsPcEBwfb2dkFBwf/KC04OFgEgT1ENG0hBgpUKhUEQR6Pd+XKFX19/dmzZxcUFEihXdaL5/XOFox74e2u09g8r7OpQfc/CYUgCIIs8gVaw5qGezonYiMdwiOOLH8LCqWg3c+DbMevextcXFyQSOTWrVulr4akHsKjsWX5cSSlmztYfP7i541svpDybgPty1EQBJlNRzm0hz9WYXD4xgdfxhU0itYiOzUJP3YYcclsbm5Ot4WzDjcmrq9s+ZvEZqjd2t3MYbYr86aGte4VEc/gi6ZPhxQ2cTe+JobmUNl84V9PXtsdPCkUdZQymcz09PRz584tW7Zs2LBhGAzGwsJi7ty5Bw8efPDgQX5+vkAgaCnZMnGJw5tfazOC8WIK6S3sJv4VjbzmIk7Pq4jfUwmSEYyPcCpmN0ny+9PC5zPEG4YFEhmqovycolKpLBYLjUZTqdR2t5SVlZWVlUWw83pCv/oFDNGnsFisM2fOnDx5cvLkyQcOHDAy6irXh/jwS4ubVi9GuXmohByFof77zUfn8KdcybDWwlycr5hmAQAAIABJREFUPRQOA5hN+4UcCi3p9hnliMiG4jP48VN2Qqmge4psx29r0D4AAOBwuKWlpZeXl/TVkNRDuGFQaPwM+Xv5k3ve6y9/oR0dpU54bK/qdR2Jc6I2zMFoXYIjNNtV2fY0r57KEWFzUEhopOzfwf2UpRJ8uLOsU+2oSWRkBuNnpnzzxw1MuuWtY7rWun3UsYRKVnQpc7e7qo6SuIvBbD4YWcx4W8tebo8driNPZDMsw4+eq5+3YG/72MKdIRAIcnNzs7Ky3r59+/79++LiYhsbG1dXV1dXVycnJxsbm757tTXlcaInlC+psIIjpXdC+d1OPIvIH3tJNr7/EiHtj4baJIZ/grG8mmQ2E0AhkLatoeo5ze+ZsbIxSgJDVRzrjMfjZWRkJCUlvf6X8vJy8Y2+zhBTW4gBB4VC2bdvHw6H27p1K4lE6tO2hHR609qlhJmTBMTvfuLT2Lwx/7xdfDubLxAKhWxa40ZaxW819wzXxHy0OXK+5Dm5T7X6mZDt+L1y5Urbj1Qqdd++fdJXo3XiFWexn8cQXETnXi3MXJJ893k58/IXqoCFb7itBgr5PFYmrXH9j1VyG6iae+PwNHbvWhII6LfC6p0tKMdChCxWz+txKIJQTK6A92316GVdkePjkx2WfFXFDHpB+NzYi3WUH8nCs399RfznE4XC+baqFJR6f+pvN2rf0LuuSKVS4+Lidu/ePX78eBUVFSsrq4ULF547d+79+/ccjlgq9ZZHY8uK70lvMmHU867g8mhVXKm12EekbK6751xMr+WJL4rdzH86reJvk1eKgLL41lELov+cIhKJHh4e1dXVbWPhb9u2bdu2baKbe10CrWANTurr6/fv3x8VFbV169YNGzaI4OXQU0CQdvooM/KO+qVwpL1j62UWTzDj2nucEupmoDMcoNMJmwAyEv81ey8qrCEu+8kfgVhjKBV098hk/DY2Nubk5AAAEBgYePfu3dbrxcXFmzdv/tGLtK+RyEMg5bATAquzrhdoKWAUBa72OJSHIJpVdkfN5zGL/Ddcbog8Zm67Kr6XM6bYaG3wMul5K4KGevJvq0EeV+XQKaR1p6FTO+OuXfGEOwYajgoAAIAAaBN1LMxr3ggt4x9LFjTx/veR4mOAnmmh1MPkwa1UUfm3C+h4pmClA9Ye920YvidW+7+4tmPz9F+rhiJQ7SXi8fiUfykuLnZzc/P29nZ3dx82bFhL8juZUB5NyzrUODtDSiviyevrEArwkSdkH85efLIOE75eaPKNMtRyE/3V0JDGfLGoxsQfO+K4Tss6omTmK5FNs6tXr/r7+0vTzBdHW4j+z4cPH7q4W1BQMGvWLH19/WvXrrV6P/QFrOfR9c7mzMeR313kCSaGpi+5ky0QCgV8PLV+Hjl7VkZUwMQH6SuWPuYx+1CfnwaZjF8qlWpra6utrQ2Hw7X/RUdHx8jISFYrWOILKXlAiZ1eOSn+Umx13qbXxCoqj5y+jv71FAgKKfVzBLy6duVj8/C2R1/zBL3wRmInJza4WVHPHAf5Ivq43Jv2+Wvof6vOp76+WfTmTmeFm9mCQxnNO1Kbipp7uqZSTuGdyiKvekF4Xs7kt+mZQCgcHvO/o7eSn/pVtF6k0+kxMTGbN292cnJSU1Pz8/M7duxYWlqaRN5fXU9cPUQoAG9bF3W75CYRyCWcKxp5LGKv/2cl0tO+oPQR5apWftvvW88RcIUZwfgwnfzymO88zCQyVEW30c6ePaugoBAUFCSuiddjoBUsiIyMjC1bttDp9MOHD7cGuZU4/MJ80soFitNnYbfsAv6N38PiCaZczjDXUAqdMxTkVzJIW/klhLckxxDmxLlpuD/OevaRMj8Nsh2/M2fOjIqKklXrrUjkIWQfIbCbBPPcLr+ctP6vd/xrEzVJT+xVR92EY9Es8kmM1pW2hYUg6Pp38v5JVv52PV2uYIRdpIeeUTtzBeUueq7GrxeaCFmssVe+ufg0c1nmDw5/Ddiqq9ixJxMIAMk17Mgihq4SYpIx2llLvsPVLBpX+AHPTa5l4xn8qaaK4w3R7cpdKnwXXpq1/9F0nL2C0Ls6Pj7+xYsX79+/Hz58+IQJE7y9vYcPH45A9Mfzv3mXm8ujqVNj+tbfFACAFwtr1Gzk3XbLbLmuLyAXchICq5X0kWMu6CkN6ekh2drXjNTN9UpDkD5XhijqfncgUcZxsAoKCjZv3hwZGdl1kA8JAhlYEC08fvx4586dOjo6R44cGT58eF80ISQRm1YtQmjrqp48D/t3U5LO4U+7mmmgir423wng5zOIu9g5JVHsX86QdY6RPP22QA7vXSGr8Usmk5WUlBgMxo+3VFWlnb1bIg8hcUWtkjt8guK5dN+9EYXM/a4g4aGZdiCRTbsOADAF5eVtC9/Jrj33tjxtQ888+vl8SshObsZb9at3EfrdR2bqAkIW69Wy2vk5/4W/2vjuMRYpf8i1q99FfCGYXs95VcWqovEt1ZC6SnItqQO5ArCRKaig8UksgYMGaoSegpt2BxYYicO0vX1gs8Dg6eaEIoV0nKb6xIkTJ06cOGbMmH6YwLgdAjZ407RweoJxn8bYI35ix0ypWFRkicT0l5yMkkLABbMPE3LOkezXqA/diOs6gkNdCiPrEIFczPU8rG0+t4OUBjI2sCIiIrZu3UqhUExMTFCob5vfq1atWrVqlZg6dQZkYEG0wufzr1+/vn///tGjRx87dkxPT0/iTYBcDuXP33jFhepX7iC0v/36Z/EE08Pea2JQNwOdhZwUdvMZembmFeBIRDXrvtl0uylQhPdOkdX4hcFgkZGRc+Z0ENZc+vpI5CE8Gl0O28E5yn+xy3YFgSUIxL5kFl1VH/+U3rgSrboFgfovlRNfCNode31x9tCx5t1/M0EWq2nNEhgCoXb2Kkxsc0TIA6+o5y+ttUYpf3uRl9JInk/Pls/ZqSTXvc8ihSMsJvMaGAIqVwgAAAoB00AjDLFyRspyHa5s1dfXR0dHHwi7QMwrHuc+Tit7WHD2YmNjYzF7IWWyjxCaCzjjrvc0MJUIRE+sMA1Qtl+n3ndNyBZaFS/rL0LJfYrBeIzRVKyOBxprjELIw0AhwKjlkb6w65KZFTFUoQBw+h1ns0yts5ObMjawPn369OnTp3YXnZycnJycxNSpMyAD6+dGhEyiDAbj0KFDly5dWrt27fbt2/tiMZURdpF+6az65dtIh29fbA5fOOv6ByV5xO2FLkLWEzY5gp725gTqZvLHqoTAhepWUIT3jpHV+K2pqcHhcCQS6cdb+vp9+CbrEIk8hGt6BfQo0mdBrYPiZGdNlFPdDriirqLNEnrjemXdSKBNIpRrmdW3smpere1+/1pIITctmydnaq565H8/RmYXgaysrKrf1d32aLZNAjP3dfgILePf7EaJL7+Fqqqq+/fvR0VFFRYWuo0dlWWIzt37Dz4cJH5i+1yVUgACCaZA5pAFtyyK5r4366NzM5XPaW9/b5j/xRwuJ0o8CNkme+4V7CZB+RNqdQIdn8li1PBgCJiAI1TURarbyeuOVDTyxWq5oYEun4GMDSzpAxlYEB1SVVW1a9eupKSkffv2LV26VOIOFqxnTyi7t6oePdMaBKhlHUsbK38j0IlLC+NSX1LS0/fK3aa9qLtzZFbrT3aItshq/HZxVLDv0k50hvgPgUcXhmkX5CcWG2JUKwn2f7ipKCQOV/E8DyriBdwCtNr21pICIWh99HXYPKdRpt0sVwhJRNLCAHmvscq7QgDJJQNN396AxCLa+vpkkWpmvLpeMnsHCi7WIG1oaLh3796DBw9azr7MnDnTw9tr+LOzR9ymBhjax/pXWi5UtZgngVTW0iczuJFRz+uL8FQCLnjPsWTEcR1jv44zbf/E8FlChDz8h1xBXSGR+Ur0N0FYWJjX93h7e/v6+m7atKm0tFRMtSAgeo6hoWF4ePjDhw/Dw8NdXFySk5MlKx89Zbp6WARl9xbG1QvfriART5YPq6OwV0XmoLDLkJjhKsPc/+St4fhoH9ieDAol2z6EWKA7R9aqiQKlhKtihsolN1hidckcoS6SwaeVyOFceOxMOYXvsktFfq7TUEJ1b101kYiB/goTpijvPiBB6woAAG0PxYZ0Ztsrrjh9G1Wt8JIs0QTSaLTr169PmDDB1tb28+fPO3furK2tvXjx4sSJE0O+vHLF6QcY2gt5YF0y02CclDyDJY7jb7iyR1RqOVfikj+fIqpYoAahdQUAgBy6d9aVpBC9TU9Pz4aGBi0traVLly5dunTIkCGlpaUTJ04kEokjR45samqSoJYQEN0yfPjwpKSk3bt3L1myxN/fv7CwUILCUU6uGo8SGBE3Kft3AAIBAABoJCJ6xfAiAn115BcFlU1yytbaTmY7wJBX3qzrBz9LsGkIMSnuHFmrJgrkYo6KBSqPjMcgNAyxcnxCKkrTHYCBAk6OnPx3yQGPvi7ZPcGia2kgg960bJ7CuEnYLTslrqqOpyI+gwl8vwoQ7DTx4OeXXKGg53JAEExOTl65cqWRkdGTJ0/WrFlTV1cXFhbm6+vb4v6bii+/W/bxjMcMAAAa0pmqligFjf54TrAnyKshhm7AZe5tlKxYWhXv40niqNO6khUL0TWiG1jFxcX29vZRUVErV65cuXLlvXv33N3dLSwsbt++PWbMmMePH0tQS4jBAI1GE1/InDlzCgsLR48ePWrUqC1btpDJZPFltoDQ09d4GMcvzG8KWggymQAAKKEQz1a6FxLoax58VVDdiVQztLaEbUfcPW1Y9OZGtaTahRAT839hs9nh4eHHjx+PiIiAwWDm5ubdV+5/UIq5CCuQwefSufKmKnJcfApK21vAyUGgzGHw/5ZtXhQRhEJgirV2F6JAPq9pzS9ydkOVt+2VuJ40Gk1RRw6ljGgu5LS9PkLL2EZVK6wosydCCATC8ePHrays1q9fb2Njk5+f/+jRo1mzZrXd22XwuctS713wnIWTVwQAoCqebjhJqstXEpm42uK0WaP6JZ2UI8kouKmb6h03aSibiuXaJfGe/vSIbmAVFhba2X2X5snCwiI3NxcAAGtrawKBIK5qEIOM+vp6iciRl5ffsmXL169f6XS6ra3t9evXJeX6A1dWUb8ZCdfQIs7zExIaAQDAyMs9W+me30hb87AArX4IqT1kpEHhBsynzdSU0hSJ2XYQ4hMZGTlixIjc3FwYDJaUlOTg4JCQkCBrpUSBUsIlmFFtVLQrKQJjZSS3IRmlPYrPeS8nP6xtsWOvS7eONet6x4+yfRMMjVY9cFyyO4MttAxnnRGKDWnMdrcOuvge+PyCxuN0VO8b6enpK1eutLKyys/Pv3nzZk5OzpYtW7S1O7AXt76P8dI28Tf89jKqiqcbTpLqLpikJq5WkFi42y7NtG0NkhJY9pjalM9x/kPcM84S7+nPj8ghSpOSkjQ1NdPS0lo+pqWlaWhoJCYm1tXVOTk5xcTEiCy5M8TRFmJw8v79ew8Pj+HDh6enp0tQLPX00QZPB25+bstHGpvndTZ1deRnPg9PrZuNT7Q//uB/HgdukSukms6snyPb8Tt06NDCwsLWj/fu3XNwcJC+Gq0Tr8i5CB96lR6NTlqReu/3N6TyJmp9uJKQx6A2LOVzi1rLfKql6O9P4PK7SjBAO/93o9/YXmUYFIEv50mvltf8eH1ZSsSfH2J/vM7hcMLDw11dXS0tLY8ePUogELqW/6Tyq0nkIQr3Wy+YeN5ltbzWHIgDFwFPeNumqCKW2n3R7mA38a8NKahLYYgvajAQHBwsvnXUilgiDh48iEQisVgsBoNBo9GHDh0CQdDb23v+/PlCoeS/4pCBBSECQqEwPDxcX19/4cKFNTUdzPWiwXzysN7FkpP5zW6jsXnDTydvf5rH55ZT6gLq48x2P7gx8/eHPAaURecbsh2/3t7ebT9yuVxVVVXpqyH+QwjTzl/3Mur4lzeLnzcy694QYoYL+I2Uupkg+N+Uuzzi018vi7oQwnoV3+Buy69vn1RH4hA+sW5bd6BJHYOicWdvPhn/X0kC4dChQ3p6ehMmTIiNje3JG6ScRtK+uy+98b+UOIW3mp/NrJSI5jKn4hn1lkWh+Gm4EhZWp2zq8//onw+JzFdiOdbv2rWroaEhMjLyyZMn1dXVO3fuBADgxYsXd+/ehfXBmjMEhAjAYLBFixYVFBSYmJg4OTkdPXqUy5XACR20/0y1/4U2rV7Cjn8K/LtXGJuH3/+Ko4Q7jLa3XSMfjPOE7djzGoBCi/QDtLW1nz592vrx6tWrU6ZMkaE+osGlCnl0YTGfoCOvp6uEEBDTUVoj+Oz3cgqureGvmlm8R1/qV7h3GoedX15K3rpe7fx1hE6fuzzj7OUZ9Xw2sb1Lu66i8l6nCWvSHoIAWFlZuXHjRktLy7Kysvj4+ISEhClTpnT7BmEL+LMTb+4Y6uOh+V9umao4aTtg9R1GvlhNF/T7ELGcbYrvUQhZLI/DXbniQfQdYhlYHA6nvLxcVVVVUVGxsLAwNjY2KSmpNao7BESvyMoS8fB2T1BSUjpw4EBGRkZaWpq9vf2zZ8/ElynvNQZ3M5KydxvjxmUAAHBKqMS1Ix5/bdiZACpp7MM42f0pt63YgxN6uA/7BdFDamtrp02bNnToUF9fX1tb27Vr12ZnZ7v9i6y16ymUEo6KOSqPjEeC6iYqcrzGNJTWCD7nPbKNA9bVjCp/ex0tjHyHEkAGo2n1YuVtu1EuwzosIClahjMMAdN2R7cL1tDCOusRlMpa9+m+rq6uioqK+fn5V65csbe376H8dekPzZU1Ntn+F7MUFAJVCXTDydIOQ9B3E5fX/3QLrjfjM1miVaeUclM21k+4pS+HlkyIgj6don9KRA+l1djY6ObmVl9fLxAI5OXl2Wy2srLyxYsXAwMDJatiK1CgUQiJkJCQsH79egcHhxMnTpiYmIgpTVBTRVoyW2HCFOU/gwEYjEDnjruY7mutddCnlkn6u+pd3Ub+/h2g/cQFphJRfuAi2/F7/fr1Lu4uXbpUOmqI+RCK71FyHhOWTb120vFPQ2WEU7qxxrQPDOomrNYVGAIHAAAIAtZHE28EOnsYqXUooXnzGhhKXvXo/0TWobd8OETgUgQjjn2XarqwsPDgwYNxCfHssUPjjvwz0tiqVzL3f0qIrc5/7bu2bdYdQhbr5ZKawNxuIlMMLEofUt/txM/NNkMq9c5I4jGEj0aV2axQd/j1p82K06dIZL4SPSXCo0ePzM3Ni4uLJ0yYcO3aNQaDERAQMHr0aDEVgoDoayZOnJiTk3Pq1Knhw4dv2bJly5YtSGRPs6//CELfUONhXNPKBc2/rVY9+Y8mBvVqjafPhTR5OYNdIxcaut06+P7k7/QN+m9UbEfjJNgLiF4hNROqT6EUc5ttaDaq2uVU/hjVWhgCDSDpcIRWi3UFAEBSKVFeDtGZdcV68pCX81HzaZL0NAYAvVGKadvxrR+rq6t37doVHx+/cePG8+fPx5HKFmRGpmtt1FNU7qHAY19e3y7NTp26vl1Ow8pnNOkvX/U1ZrOUq+JpL5fUTI407HmoTFAAJgRWazijIetKtoi+ctjc3Dxu3Dh5eXk7O7sPHz4MHTp04cKFz58/l6ByEBB9hIKCws6dOz98+JCamurg4BAfHy+ONLiaOu72Y5DJaFqxAGQyNTGoxLUjHubUn8tyl1f3s3VR2I+5teLjK0KJiEv9EOJTVFS0bNkyHx+fMW2QtVK9hlzMaTCg2Krq1NL52qxMlJYnj/1eTuG/Lc4rGVVBHh17Xwka6in7d6iduQyTbgh77eGKTV/ZPIawoaHht99+c3Z2NjIyKi0t3bVrFxaLnWPsuM5m5KSESwQ2vVtRIADu+5hwpSjjte9aLYX2vlblMTSjqT+bgQUAgPc5PTZJ8HZrT0MkgEIgcWWdkAuOuajXp4pBdIvoBpaxsXFLShxLS8vs7GwAAJSUlIhEosRUgxhkFBUVSblFIyOjp0+fnjp16tdff503b15dXZ3IomAKCuoXbiC0dYnz/IQkgiYGFb/a45+3FWFffRXUxw5zoGzQS1x46xmX0osA1hASZP78+TweLyAgYHYbZK1Ur6EUc2tUm00UDdTl4WDTO6SmB5/zoTWAO4XNe5bfuNCl4wzW5O0blX5ZibQbKh1VW4czQgGGGSr8PWibvb09HA7Pzc09cOBA27zs2x3GzjByGPv8YhWjq9BxDD53cfLd57UFqVPXD1Fsn2eQWc+nlnL1RilKvCPd0tcTFwIFm/LIsC6J8W4nvtvCAi74amkNtZzrG2UIR0r4qJn0p+gBj8jnD4lEooaGxr59+/Lz85WVlbds2aKlpRUXFyf+ycbOEEdbiP4PlSqBoC+iwWQy9+zZo6mpeerUKR6PJ44o6qnD+DFu/OpKEATLSAzjgy/Pvy2jN24nZHucvr9v8fanAu6AD9IjGrIdv4aGhjJsvRUxH8IVjbyJMZf+l1N6OptCeOLMaXxDqZ0qFLJb7l5Mq5hz40OHFZkPIxp9vUHxvtu9omU4CwSC0NBQDYy2n+P8roOknM5N1ovY/7Aip8O7L+uKrB4eWZoSweRzOyyQe6kpPrBKfLVFQDoTF4vAvz+s5NWymi4CN9BruFGjy54FVIof3KFDZDhFSx+JzFeir2DhcLiMjIzhw4dbW1uHhobm5+dv2bJl0qRJEjL8IAYdWKzMlvfRaHRISEhqampcXJyrq2taWprIorCb/1Rauoo425eXm2Oirpi41vNoYumNopXyug7z9aMMXKu3QYEbZIGNjc1A//3NaRYIuWABEw8XKptgOHxqEUwJjkBZw2DfDgze+FD9y7AOlq+EJCLl0F7Vo/8D5ER3uu0tWCw2MzPT3d391q1b4ceilqv8NWTIkC7Kb7IdFTFmcfDHeI+nZ8KKM/PI+CYOs4hKuFHyYezzC2vSHh5z87vmNQ+N6NhdsjyGajKtp15ckkU6E5eCBiLgtQmfLbzvUlr9ov12qpAP5oY23XMpNZiAmfzAQFLHBtshwyl6gDKQzuVBpwghpMD9+/e3bNni6+t77NgxVVVV0YSwn0eTd21VD72JGuZR3sQccz4teILhbINgZtHHEMIuu0rbX7e6Slbt/o9sx++rV68CAgK8vb3bviQiIiKkrIY4DwGfyYrfWLnu15vbLLbNUf2gVbpXyesXGFxJHrsIAIASIsPr3NuavRPk4O03hpo3r0HgNJV3HxBX+x7T3Ny8b9++Bw8eHD58ePHixXwmeE2nYDneWk6xmxe/EASjq3Mjyz9/INYQ2HQNBSUn9SEzjR1mGw2Vg3dal88UXtMtWFJhJa82UHM895yyx9R3O/FwJMzIF6tijuIzhaSv7IqnNHVbBa9TOrihCt2LgOgBMjtFeO7cuXPnznV4a/369evXrxdPJQgIWTJ37tzJkyfv3LnTwcHh7NmzAQEBIghR8PVXwyo3rV6idvqiibfPi9WePhfSFKbu9bPYuZN34E/BHuNwlamLB2Sy4QHK77//PmLECEdHR3jn7+l+DqWYQ3GkWatoVdH4mvIfkFoefM4ntOqvLXdvZ9fOdxryo3XFSUvmZqRpvXwnHSWFQuGVK1f27NkTGBiYl5enoqICAABSCabhpFD/lmkwoZsooHAYLMDQPsCwp9GwWqh5xdB0RQ8G6woAANMAZRN/5YY0Zu1rev1bJhID1xiq4LRZQ82m48hnEDJEFAOLRqMVFhY6OzsHBgZqamq2veXk5CQhxSAGHVlZWa6u/WJdR1lZ+dy5c/PmzQsKCgoPDz99+rSBgUFvhch7jVG/fKtp1WKVkKOWUwPiV3lMCH2nMP3AONsdB3MObCIE67/GOo6FIixLCQqF8unTpwGdYYJczCWYUW2UDRF8ANGciTQJ4PEjEUjrlrt3P9aGL3BuX4fPpwRvV9l3BKYoDe/vr1+/BgUFIRCIFy9e8Hi8FuuqhSFjMbVJjG4NLNEoj6aaTJPZ7pX0Jy4YHND1UtT1krZHf/+ZogcKovyY27FjR1pamru7+8mTJ6OiojAYTGBg4NKlS5cuXdq1gQWCYFxc3PHjx8PCwpqamlqvFxYW/v333+fOncPjuz8lAfGz0t+G7qhRoz5//uzo6Oji4nLy5Ek+n99bCSjX4bhbUdSQnYzb1+x0sM9Wuq97XJfSFKJmb35M7fC24kR8KaMvNIf4ESMjo8rKSllrAQAAAIPBYDDYvn37eluRUsyt16Loow2MleV4xEy4mgoCZQvA5AAAyKwigyA4zKD9jjbjVhhCW1dhYp8nBeLz+SEhIT4+PsuXL09JSRk6dGi74azvo1ST2DffdhCofEYz8pONAxbQ/yauvmMw9HTfvn0tI1Qi0sTaZeRyubGxseHh4WlpaQEBAUuWLBkxYkRnhUEQnDVrVnFxcUBAQGFhYWJiYmpqqrW1dUJCwpw5c5YtW0YgEN68efPmzRszM7OOdYV8sCBkQUlJybp168hkclhYWM9TebQiqKogLZqJnrMQu2FLRlWz/9X3V2apjFLdW/qRtr34t5jlM9Hq0nM9liGyHb+//vrrvXv3pk+frqb2XxDOEydOSFkNcR5C5PDSS3+8GmMywQbJHZnvreK7HwZXlscuAABg85NcVTQyeKJl2/JCcnOjj7vGvRg5i97FSe8teXl5v/zyi6am5pUrV/T0Oo69JOCCYVoFi0stFXAS3sjDZ7ASl/9sAdwhZI5E5iux3BFQKNSMGTOioqLy8/NxOJy3t/fhw4c7K5yZmZmQkJCamnrgwIH79+9PmDDh1KlTAAD8/vvvx44dO3369O3btwMCAg4dOiSOShAQEsfc3Dw+Pn716tU+Pj5//fUXj8frVXWEobHGwzh27CPqkf3uhmrRK4atfEh5R9lu5qS00+zGggvPBBzoZ0Ofw2Aw/Pz8BAIBsQ2yVqp3UEq4JSBRwFcyE2ajND343Bw5+aEAAAhBMPJz3Vyla44MAAAgAElEQVTH9pYN7e8jaL+APrWuhELhiRMnxowZs2rVqtjY2M6sKwAAECjYkDFK1QndRxPtLWWPqKYzZbZ8BQHRBeL6e5JIpIsXL/r7+585c2bevHldJKi3tbXNzMxs3ZVHoVBIJJJAIOTm5rbW8vPzi42NFVMliAFKf84kCoPBVqxY8eHDh/T0dGdn53fveucyDNfUwkXEcNKSKbu3uOurRC11++UB/xN9nZMje5nV3dVHX4LCPlIc4hvXv+fMmTPOzj94LPVjWAQ+Fylo5NBIbIQW6yNS21XIq0YgrQAAeFNK0sbK22h/597ELythxURhf9vedyrV1tZOmDAhJiYmMzMzKCio3a7Kj8PZyBdT+ZwmcTXKHlNNZ8jSwOrPE5dkGTw9lRQiGlhMJjMiImLatGn6+vpRUVFBQUH19fW3b992dHTsrAoWi7W1tW35Ozk5OSoqauXKlS1OV7q6ui3XtbW1Gxsbu2gX9j2tfgxt/+OLiopotP+Gcdtbbf+m0Wht4+JAEmQuoXWDv9/2wtDQMCYmZsmSJbNmzfr999+ZTGbPJTAQchp3n/BLips3BSk0Ft1a6Dw/UqmE+8vIobWj7KJ3nEiWWi+kI6HVlaEVoH9QUlKyadMmfX394OBgWevSCyjFXPpwurWyXjNbiKJmItS1EShrAIYEAODep7r5Tu1DTFEPB2PWbISr91X6y3v37rm4uPj4+CQmJhobG/9Y4Ed/HUNfbFU8XbK/JZryOAKWUNNZqsl/2jEYPJNaGDw9lRgiBCe9efMmBoNxdHQ8ceJEXV1dFyUP/EtSUlLrxYcPH2poaMTExIAg+PnzZwAA+Hx+y62PHz/C4fDOpImmLQSExCESiYsXLzY3N09NTe1VRSGbRQpaRFw8S8hgPPhcpxMcn5F7lpA38u/7u/4J/dhH2vYTZD5+X7x44efnB4PBRo8eHR4ezmQypa+DyA8h/1rT9j8SAl893ZVCrL+lzGw6y6beBEGQJxBqB8eXkxhtC3Pev2sYMVTIZklA4x9gMBjLli2zsrLKysrqbd07dkUN7yT52N+H4FM2dfUOgoAQDYnMV6KsYJWWljIYjJKSkuDgYAsLC0wb/vrrr7YlP/1LfX19i7p79uzZvHlzfHy8n58f8O/aVeuqFR6P19LSEsNchICQBjgc7ubNmydOnJg7d+5vv/3GZDJ7WBEmr6B+4TpCW5e0MGCGseLZmQ4BkVaVoN9C6xd4lbj4mLI+VXtwwmQyL126ZG9vv2DBAnt7eywWe+vWrUWLFqGlm/NYTJoLuHgDirbCEHtUCUJRV8AvQqAcAAB4UUQwwykZq393Yp924hD2t+0wecnHnCwsLHR3dxcIBFlZWS4uLr2tbuynXBEryV3Ckkiq2Zz2eQkhIPoJohxfWrJkiZeXV4e3TE1N23588OBB24+rV6/Oycl5//59qxWlqalpa2v77NmzFStWAAAQGxs7btw4EVSC+Amg0WgDKxXD9OnTR40atXHjRhcXlxs3bri7u/eoGgKheuwMJWQnaeGMmbcf8fxtpz8AomfR1pnf35OvovN2luNI6DeGJDE0NHRwcPjzzz/nzJkjLy9/+fJlWWskCuRCTo1dsy5MzUz4HKk5TMgrQ6BsAAC4/6luntN3ruWcd6kCfL3ijLkS1+HRo0dr167dsWPHpk2bui3c4XA2mopJ3VTvHiKZbzi5iMMi8nU8ZZDguS0DbuISmcHTU0khioFlamrazpDqCY8fP758+fKMGTN27tzZcsXR0XHDhg0nTpxYsGDB169fm5qaYmNjxUkDBzGgqa+vH3CjV11d/datWw8ePJgxY8bChQsPHDigoNCDZQMYTCX4MPXgbtJcv3nhD3lTbPwfgtEzKPvNLmwrlD+Mm6NvPcCeQ3/GwMCguro6JyfH3d3dwmKgHuZvLuSUIYgOPLSW8KOcnimAbIbB5HkCYUwe/tAU67Yl6X8fxW78Q7JpB3k83ubNmxMSEuLj47twtG1Lh8NZd4QirZpHr+Fh9DtOKdgrSiKpZrNUYLKOzD8QJy7RGDw9lRTSC8ATEBAAdhRVwtfXt7m5WWpqQPRbLC0tuy/UL5k9e/aYMWPWr1/v4uISHh7eQ1dQ5d0HaWdPEOdMWXjnsWCyzcwnwPPZtMOmf/+eDA9Vnq+mB+UUkwwfP35MT0+/ePGik5OTl5cXk8nsbaANmSPkg6QaVgOfTmTC0NwsuPVMuLwDAABJpSQLDSU95f++KtysTEF9LXraTAm2TiQSZ82apaqq+uHDB2Xlnp7X63A4wxAwo8nYihia/Vp18RUrvkMee7mrBNLSYeBOXL1l8PRUUsja+IeA+CnQ0NCIiIgIDg6eOnXqwYMHexj2Hbthq9IvQcQ5Uxdrcjd5m894spipbXfU7FTQgwccqqCvdR48eHp63rhxo6amZvLkyUZGRo6OjsuXL3/9+rWs9eop1DIu1Z5ho2KsJc8TUgtABEkO5QAAwKMvDTMcdNqWpJ06jFm/RYLLV1+/fvXw8Bg1atTjx497bl11gelM5dKHVPHlELJZPIZQ5vuDEBBdABlYEBASY968eVlZWSkpKSNHjvz69WtPqigtW43d9Adpnt96TeYiF6NZT1YKhlj8ZX1q2aUoIR8KQCpJ1NTUNm/enJ+f/+TJEwaDMXnyZFlr1FPIhVzyULqZkrEjMk9O1VrAK0Kg7EAQiM5tCLDXbS3G+5zNLytGz5gjqXYfP37s4+MTEhJy8OBBSQXaMJyMafzAYhF6nXiqHUW3KVZL1ID+Ev0DAqIDIAMLor/wc0SxGzJkSFxcXFBQkI+Pz+nTpzvcFm+H4txFyvuOkBbP2j6EPcvRYGbMWpiR4Xb70xtPvZSCwoOQsWPH3rt3r7q6Wiati5CLsLmQgzdp1kTpmgk/I3WHwuW0YXDshxqyigLSUlOptRjt/GnMqg0wJEoieh4/fnzjxo3Pnz9fsGCBCNU7G85yaLjhRExFjFhnCYV8sOgu2Wphvzg/+HNMXD1hMPS0H+UilDJQLkKIAUR5efmiRYuUlJSuXbs2ZEj3niLs59Hk3X/gwu7ur1OMzauO8jtdXQq8Kdq157dO83sOLKDxC4j6EF4H1YZ4PHW0mLqBs13LXF9OTQ+tumn38wIQBFo93PllJcTZU7TffoaJHX5CIBBs3LgxLS3t6dOnPfnq9paS+5S8q83+8cYiS6h4Sss6TJj1ttdnrSAgeojscxFCQEB0homJSXJy8ujRo93c3KKjo7str+Drr3r8LGnZ/D1qxLHmegvi1pua851Mz/xz6ZMUtIXozzQXcEpRRDoHpUTLgqP5cih7AACic/HT7LRby9Av/6O0eLn41hWTyZw5c2ZxcXFycnJfWFcAAJj4KxM+sJgNou8S5l9rtlmm1n05CAiZAhlYEBB9BQKB2LVrV1RU1ObNm4OCguj0bjLdKvhMVDsf1rxu+SFMra2O3tKXG11tSGqa5x5HlkpHYYj+Cb6CQYeDKCEdYNUJgCqEvH1lM6uRzhluqNpSQEgisGMfKy1ZIWZDZDJ50qRJKioqsbGxfXcgH6EAM56GLY6giFad2cCvS2KYz+0X+4MQEF0AGVgQ/YW2KfB+Jjw9PT99+iQUCl1dXbOzs7suLO/hhbsWQdm24Sy2QltF95cXv46xK6+Hn0tJqpGOthD9DU6zoEqd5KBs7iL3BaXjBAPgcIR2dG7DVBtt+L+eIozb1xWmTIfjNMVpqL6+fvTo0cOGDbtx4wYSKW6cqq6Hs+VC1cJbZNEkfznfZBGoglLuLy+vn3Xi+pHB01NJ0V++oxAQrTm/fz6wWOzVq1cPHDjg6+vbrec70tEFF/6AunfbZbVqDWXDlYlrAuw+viNeLPoChYsbjDQXcpqd6IaKRhZADkLHrCVDTkwu3s/22/4gyOcxb19T+iVInFbKyspGjRo1b968U6dOScTDt+vhrD8Ow2kSELJYvRUr4IB5l5uGbuirJNYi8BNPXO0YPD2VFJCBBdFf+OljBM+dOzcjI+PevXvTpk1raGjooiTS1gF38wEtePtlTKmCgvHa5NVL7JLCPocSa3r9QoIY6JALuY1mFAxCU4+TDVdGy8nb0zn8jKrm8ZYaLQXYsU/kTC2QNnYiN5GXlzd69Og//vijNc2G+HQ9nGFwwG6V2teLTb0VW3C9WWsYWtVKXgzVJMxPP3G1Mnh6KikgAwsCQnoYGxunpKS4uLg4Ozs/e/asi5JIWwdcRAzj6P7r8vlcmOmmtOWbhz7aF3+FQR5gUcghxIRcxKnRbBLwlTC0bECOgkDZxxcSPI3UsPLfookyroUqLV8jsvzPnz+PHz/+2LFjq1evlpDKPcJmuVrpQyqnuRcBdUEB+PE40WWbWDuhEBBSAzKwICCkipycXEhIyIMHD9asWbNjx44u0rbImVng7jxhnT1xB/mlnm299/Oiva43t0Rc43GE0lQYQraQCznVilQEj4yAs0GQikCaPstvnPrv/iD34wdhc5PCuEmiCc/JyZk8efKZM2cCAwMlp3KPQGvJmUxX/vJPLxaxSiKpirpyul5Q9HaIgQFkYEH0FwZDFLtWRo4cmZ2d/eXLF29v74qKis6KyZmYadyL4Vw++1Dh60eS4/6vgfuGXVp/9Q4oGOwBpaTMtWvXpk+fPnv27KSkpB/v1tTUjGnD7t27Jdh0dSVNAanugviC1B+KQNmAIDyuoNHXWqvlLuNaqNKSlQBclJk8Pz+/xbqaPXu2BBVuoSfD2WWbxpdzJD6zRz8YhHzw/f7GYXu0xFZNwgyeiWvw9FRSQAYWRH+hhzmSfxo0NDRiYmLmz5/v7u7++PHjzoohDIw0IqIFYf88w+ZnEt3+Kpi9x/V/m/7ptDyExPn7778PHjy4bNmySZMmzZo160cb682bN/X19Sv/ZcKECZJqGhSAhVy8pbKZFZiN0NBDoOyyaynKCnLmGkoAAAiJjZw3r9BzF4ogubS0dOLEiQcOHJgzR2KpddrSk+GsZiOv66WYc65Hi1gFN8iKunIGEzFiqyZhBs/ENXh6KikklhMUAgKit8BgsE2bNo0YMWLu3Llv3749fPiwXEdpeltsLGLg9GcLV46vd1dAcDa7Htl7Xjlk3Tjp6zwIOXLkyNWrV/38/AAAaGpqOnLkyJgxY9oWSE1NdXNzy8nJYTKZM2bMGD16tKSaplbwiJZULQVTXWYWTFFPTt7+WT5+is23VRxmxC2FKdPh2F7nYK6qqho/fvzevXtXrBA3dJaYeBzWeTii1PoXVUXtrl5GHLIgM7jRN8pQaopBQIgPtIIFASFjhg0blpWVVVBQMHbs2Lq6ug7LIAyMNO7HgvdvJMDfP63yulE/bp5dyOnrmVJWdRBSVVXV2Njo6enZ8tHDwyMtLa1dmbdv32ZmZpqammpqagYEBISFhUmqdXIBh2hFRYGqGHo2CCMikNbPCxqn2GgDAAAIhYw715UWLu2tzLq6uvHjx7cEv5WUniKjaoGyWaqWtq2rQ7UAAKRvx5v4Y7WHixunHgJCmkAGFkR/YTBv8Kurq0dHR0+ZMsXNzS0uLq7DMgi9IRr3Y2HPH73kvw0vHPOC6jzKYMfNh5+lrOpgo7m5GQAANbVviVlUVVVpNBqf/12al9OnT6ekpKxZsyY4OPjUqVN//vlnFwJh39Oa9bnt97+oqIhGowEA0FzAqdehYFjVcupacLkhZA4qp5bsZaIOAAAn+TWopl6O+s/m6FBCu1sEAmHUqFErVqzYuHEjAAA0Gq1t9MieSGj3d2cSsrKyeijBZoti9RtK2WNqZzqUR9Oq4mmeR3R6q4P4veiJhJZ/ZauDdCSkpKTIXIe+kNCa4LktgCQYSOlXoWSxED89ycnJixcvXrhw4YEDBxAIxI8FhCQiacF0lvuYkQivHcOfOSGKScKz0yZbSF/V3jJAx29eXp6dnR2Hw0GhUAAAfPjwwdPTs4uzn4WFhdbW1gQCQUND48e7vX0Ir1fVLh0VtVsdPkf/hbyRT3TF7DvZtU+WDwMAoGnNLwreYxUXLO25NDqdPnbsWF9f35CQkJ7XkgIN6cznM6sCEk3UbNoHuGrK4zweWz41xghavoKQJlCyZwiInw1vb++srKysrKxJkyYRicQfC8BxGrg7T9AZScn8lMOZvjlCMzS47e1bKJFOX2FoaAiHwysrK1s+VlZWGhsbty1AIpEWLlxIIBBaPhKJRCQSqaqqKpHWKyrJWBTOWvgZoaIkJ+8QX9g4yUoTAABhE4mbnoL2n9VzUTweb86cOS4uLv3NugIAQMdTccQxnZjJFaQcdtvrhCxW9ITyUad1IesKYiACGVgQEP0LDQ2NZ8+eDRs2bNiwYe/fv/+xQIuNhcl8k8xLDXk3tQap1Ujekf+110GxIXoCBoPx8fEJDQ0FAIDP51+5cmXGjBkAAPB4vBYLWF1dPTU19eLFiy0Fjh07Nm/evA4PK4hALr3BWNFIl5stRNLgSPv4AsIka00AAJgP7ypMnALD9DSyNgiCQUFBSCTyn3/+kYhiEsdqsarnEZ0n4yvebmmoe8OoSWSk/lYfM6XS+5yeRSCU1xliQAIZWBD9hbZb44McBAJx+PDhM2fO+Pv7/+9///uxwDcb6/2bZDDtz5RpbEVkWslefA1T+qoOBs6fPx8TE+Ps7GxtbU2j0Xbt2gUAQHx8vKamJp1Oh8Fgd+7cuXjxoru7u5WVFR6PP3XqlETaZZME1ZpNGvJqGFgFHI7JJcgroRBmOCUAAFgPIxTn9CI6Q0hISH5+fkREhKQsv24RYThbBKrMzTKDo2DvduMzg/FySvD5n8xNZ/T6jKSUGTwT1+DpqaSAwjRA9Bfq6+uhXFdtmTZt2rt37+bMmfP+/fvQ0FAlJaW2d+E4DdzdaGDxrGR7jlfijKuT7t1ND1k58QBGBSkrhX9WLCwscnNzCwoKYDCYnd23lH+enp6vX79Go9EAAIwcObKsrCw/Px+JRLYWEJ+mPDbRmjqMXS2nbYZQGPr8Y+Nkay0AAHifs4V0OmqYRw/lRERE3LhxIz09XVFRejHQRRvOGAOk52HtvtCn7xg8E9fg6amkGEhupwPUSRYCQhxYLNavv/6alZUVExNjaNg+DpCQSiEtmtlo6TwWPeq27+2scpvfZ+5FoTvwjpc50PgFevkQckObFoD3f9WmzLNNQ+sHTb6J2zLGdKqNNmXPVriWDnbD1p4ISU5Onjt3bmJioq2trRiKQ0AMLiAndwiInx80Gh0WFrZ8+fKWJZN2d+HKKrhbUVqF2S/oSQueL3AxyjsSeULAh5IV/gyQ8tl0ZZQ17AtMCcYGbD9Uk0eb4kAelxX7RDGgR+HXq6qq5s+ff+vWLci6goCQPpCBBQExANi0adOtW7cWLVp04sSJdrfgyiq4O4+HlH15QUtaFL9gtNm7Q+FngMG+VPQzUFBN0Ebp6YNfALggqQLtbqSGkZfjvIpHWtkiDIy6rc5gMAICAv7444/x48dLQVsICIh2QAYWRH9hMAca7Qljx47NzMyMjIwMDAxkMr/zZ4djldVvPhhSmhNHfTMvfpGPVeLBa9dlpCaExPhKazCSxykqNiNQds8LCC0JnplR99Az53VbFwTBX375xdnZefPmzX2vaQcMnuEM9RSiMyADC6K/AGUS7ZYhQ4YkJSXJycl5e3vX1ta2vQVXUcXdfmRQ/iW66c3cuEUTrO4dD3siKz0hxIdLFVaoEs2BKqSGsZy83fP8xik2WsLmJm56KnqKf7fVQ0JC8Hj8hQsXpKBqhwye4Qz1FKIzIAMLAmIggUajw8PD586d6+HhkZGR0fZWiz+WaU1+VP2LeS8Wj7c+d/p2gqz0hBCT5gIO0Z5jxM1BqqkUkS1hMJi1FoYV80h+7ASYEqbruk+ePAkLC3vw4EFL9HkICAiZABlYEBADj23btl24cMHf3//atWttr8OVVXC3H5k311yvfD3v5ZLRJkcv30+VlZIQHdIuBWFnNOexqfoIS+AzgOIllKq07A+yHt1T7G5/sLi4eNWqVZGRkdraAyzeAQSEzGnNSygRaZCBBdFfaJueE6Jb/Pz83rx5c/To0U2bNrXNPQxTwuCu37dvKj9b+TYwcYmb3v6IJx9kqCdEO0AQBEGwWwOrLo8BV8KaKOTDELrxheRJVpr8ynJ+VaW815guarFYrNmzZ4eEhAwfPlyCOovA4BnOUE9/Jvbt29cyQiUiDTKwIPoLurq6slZhgGFtbZ2RkVFaWjpp0iQymdx6HYbBqoc/dGks+l9F+oI3i8xUdsYlFstQTwgR+Fhba43EyGNhfJTbu8rmMeY41pMHaL8AoMtQ7Bs2bHBwcFi9erXU9OyMwTOcoZ5CdAZkYEH0F6AYwSKgoqISHR3t5OTk5eVVXl7eer1lr9ClsfhkadrK9LkqsI3Z2fUy1BOit+Qx8A5AjZyGfnqtlaOesooCkhUThZ4+u4sqN2/eTEtLa8mKKHMGz3CGegrRGZCBBQExsIHD4SdPnly3bt2IESMSExP/u66sgrsVNYxQfKAg/fes6bSmVQXFJBnqCdFzuFRhhTbZSPAVgUUmVqhOsNTk5eaAbDbK2a2zKoWFhVu3bo2MjMRgunGBh4CAkA5SNbDKyso2bNgwefLkFStWZGdnt16/du3a9OnTZ8+enZSUJE19ICB+GtatW3f37t0FCxZcvny59WKLjeVJKtv46X1I7sSqitXV1VQZKgnRQ5q+sml2cFtkNgwu/6KIMcFSk/UoUjFgDtCJ7y2Px1uyZMmhQ4ckmAkRAgJCTKRnYJHJZE9PTwwGs2fPHgcHh1GjRpWUlAAA8Pfffx88eHDZsmWTJk2aNWsWZGMNWqAodmIyZsyYlJSUEydObN26VSj8li0HrqKKuxU1jli0OOvL/4pGZuesJpFYstUToltIuWyOpvwQTA2J51JNZg3TV2Y9jULP6DQ9zq5du/T09IKCgqSpZNcMnuEM9RSiM6SXfrWpqSk1NdXf3x8AAAqFYmhoGB0dPXr0aG1t7atXr/r5+QEAcPTo0devX8fFxXWsK5QsFgKiO5qbm2fPnq2kpHTnzp3W3SIhiUgMnP5UzSLWx36eXt4U71CMClLKikHjF+jxQ7i/Lf/JsJzTpieecvY8LdK7Y0ajnTik8eRlh4VfvXq1bNmyjx8/4nA4SesLATFIGWDJntXV1f39/TkczuTJk01NTYOCgkaPHl1VVdXY2Ojp6dlSxsPDIy0tTWoqQUD8fKipqcXFxenq6np5eVVXV7dchOM0NO4+8WsunvwyJ7LO+kHiZh5XIFs9IbogG1/nCKuVU1NLLFOdYKnJehyJ7iS7Mx6P/+WXX65fvw5ZVxAQ/Q1pO7mDILhr1679+/eHhoa+ePGiubkZAAA1NbWWu6qqqjQarYvqsO9pjSXTdumyqKiorZC2t9r+TaPR2kb1gCRAEn4aCUgkMjQ0dMmSJW5ubpmZmS23SkhNCpdvT6eUTniZk0Aacilqh1AI9p0OrfH6WgEgekwB0GQN/wRDwl+VciaaYNkvnitMmf5jMRAElyxZsmLFCh8fH+krCQEB0TV9u2jfmsV90aJFS5cubXtr3bp15eXlJ0+etLOz43A4LSkdPnz44OnpyePxOtYV2mL4qcnKyoJyXUmW6OjooKCgy5cvt2zNAwAgJBEb50+7rWZV6mdkjwLWzd8vNWWg8Qv07CHQq3mTbz266nqMojt2QYzvV1cm48YV3J3HP5a8cOHCjRs33r59i0Ag+kZf0Rk8wxnq6U/JANgiDPgXGxubjIyMTZs2td7S0tLi8XiGhoZwOLyysrLlYmVlpbGxcZ+qBNFvGTxDV2r4+/vHxsauXbu2NekvHKehFRG9gJCrE1tbDvLO3z0mWw0hfoSUwwYN4OpY5utat0nWmqyYR+hpM34sVlZWFhwcfP369X5oXQGDaThDPYXojL41sNb/i7u7Ow6Hu3DhQkpKCgAATU1Nt27d8vPzw2AwPj4+oaGhAADw+fwrV67MmNHBVAIBASEabm5uqampZ86c2bFjR8sPMjhOU+tudFD9R8WoxnoE4Z87/8haR4jvKPra5IBshOO0X1WoTzbCct68Upg8rV0ZoVC4fPnyHTt2WFtby0RJCAiIbpGeD5a5ufn58+enT5/u5eVlaWk5bty4DRs2AABw/vz5mJgYZ2dna2trGo22a9cuqakEATEYMDExSU1NTU5OXrRoEYfDAQAAoaOr/fD5amIO4i6hWb7kYsR1Wes4iOg22XNmTZUrvIIvr5BRzR9R9eH/7N13WBTX9zDwu72yBZZepWPBgtgRERVs2GNBQRPbV2OLxhq7sRuNSSxBQxR7iYq9KypgA0EFRZEOInVpy9b7/jG/7LsBFkEXF+R8Hh+f3dmZO2fu7Jw9zNzZpXXwJAsNq8zz+++/q1QqzWsCAIDPp9sfe25KoyJgDMfXrbS0FH6KoeFIJJKJEydmZmaeO3dOJBIhhFR5H3JGDdorbMmbwDVR+AZ907Anj+H4RXXrhNEzz/4waPd7Xqttz0acff4n09ePPWqc5gypqamdO3e+f/++k5NTQwb7WZrP4Qxb+lVqAmOwAKi7nBz4sbwGxGKxjh075u3t3b1793fv3iGEyMYmZsfOTct//uFIpZh+5fj5Wx9tBDQ0RYUqx1JlY5B1O6vdIFsD2f07zH4DNGfAGE+ePHnhwoWNubpCzelwhi0F2kCBBRoLZ2dnfYfwlSORSOvXr583b56Xl9fjx48RQhQzc7OTF+bkPHlzmFKMjp6/+lDfMTZ3eTGVRjZFNIHB9VTjgR+e0Tt1JfMFmjOEhoaWlJTMnTtXXxHWUfM5nGFLgTZQYAHQvEyfPn3v3r2DBg26ePEiImqs4+EL0yOeH6TnK/bcuBun7wCbtVexBR709Dyy6YcyklnUVdag/1y3ff/+/ZIlS/bu3ds47xwEAGiCAguAZmfQoEHqr8hCCFGsbMxPXVyUHvHkb3ZO+cBvTeoAACAASURBVC+RT17rO8DmKyI1tRs34Wa66yA7A3n0A0bf/pqvzp49e/Lkye3bt9dXeACAuoMCCzQW8EuiX1Lnzp0jIiI2b968YsUKjDHF2tbi1IVF6Xcf/G2Q+mFt3IssfQfYTD2jFLXgptzJaDmuMJ7etQfZgKd+6dKlS8+ePVu+fLkew6u75nM4w5YCbaDAAo0FfIvdF+bo6BgZGXn16tVp06apVCqKta3lyQtLU25eDzNJyvgxNbVQ3wE2O/IylcymjM0n3Uk3ah1/mzXw/18flEql8+bN+/XXX5lMph4jrLvmczjDlgJtoMACoPkyNja+detWcnLy+PHjZTIZxcbO4nj4qlcXwo9YPkmYlZtXpu8Am5fcpxWtjd89k7i6sTEp5iHTt5/6pTVr1rRr165///61LA4AaFSgwAKgWeNwOBcvXpRKpf379xeLxVR7J4ujZ9fE/3PuuOXth9OLiir1HWAzEvU0ozfvxfVUl2nlr+g9epG4//edQy9evPjzzz9/+eUX/YYHAKgXKLBAY5GUlKTvEJopJpN58uTJVq1a9ezZMysri+ba0uro2TXPTl06aX4xYnp5Wc0/vg507m5BljMv5Va6U5fX91kDhxATMcbTp0//+eefLS0t9RtevTSfwxm2FGgDBRZoLMzNzfUdQvNFJpN37twZGBjo5eX15s0bWss2VsfCVz/75+oZk1M3p8vkSn0H2Cxk8woqGAaleZibGMv09ScmHjx4sLKycvLkyfqNrb6az+EMWwq0gQILNBbN50cYGq2FCxf+9NNPvXr1io2Npbm1tjp2bvXTk1fPmxy+MAs19x+50Rltv0UoyVO0tE64+r7NXPlrRu++JDYbIVRSUrJ06dLdu3eTyU0sVzefwxm29GsCv0UIAGhAZ86cmT59+okTJ7y9veVxMenjhq/wHtfbV/rd8G3oM9IOHL+o1k6IPZ9byJi58VXf366ftfv+e6bfQITQDz/8UF5evnfv3i8bJgDNHfwWIQBA94YNG3bs2LFvvvkmPDyc1raD9d/HVt89dPsu48+TS/Ud2tfsWmKqJfd96jsGPz2J4dMHIfTy5cvDhw///PPP+g4NAPApoMACjQV8i13j4ePjc+nSpenTpx84cIDu2cV6/5GVNw5FRapCTq3Wd2hfrVco/VG58/fiGNbAISQ6AyE0f/78FStWiEQifYf2KZrP4QxbCrRpSift4RIDAF/S69ev/fz8Zs+e/cMPP1RG3kv/LnDD4ECvToJvRy76hNbg+EXaO0Elx1tPL4wtM1558JT91l/pnbqePXt2+fLlsbGxVCr1y8cJQDMHlwgBAA3IxcXl/v37+/btW7p0KaNrD5tdfy0+fzjyceHBM7v0HdrXJuVRcQ/TV2mxdAN5Jd2zi0wmW7hw4bZt26C6AqDpggILAKCVlZXVvXv3bt68OW3aNFpPH+s/9i0IPxr1JPVIeJi+Q/uqnI99V6BgjMt6xBvxDSKRfvvtN1dX1379+n18SQBAYwUFFmgs4AJ/42RkZHTz5s3U1NTAwECal4/1r3tn/XPsXszzk5dP6Du0r0cmjr2S08ov9QkrYOSHDx82bdq0detWfQf1WZrP4QxbCrRpSqMiYAwHAPoilUpHjRpFIpGOHz8uu3Y5Y/HcveNH9+nULaDP0Dq2AMcv0tIJKgU+fum7U+ettmfctblyd/LkyQKBoKkXWAA0aTAGCwDwhTAYjNOnT3O53P79+5N8+lit3jj10Im7TyKu376u79CavKRHRQy6ZHDyQ6MxgU+ePLl8+fKKFSv0HRQA4HPBCEoAQJ3QaLSwsLCZM2f27dv38uXLFipV8JplhykqDtOgW9cu+o6uCTsdG1vKspqefY85+PCsQYPXr1/P4/H0HRQA4HPBGSzQWJSWluo7BPARZDJ5165dXl5e3t7e0p69LZesGvN3+NUnh2KeJ+g7tCbMSHS54noZ6uJ95NJlhFBQUJC+I9KB5nM4w5YCbeAMFmgscnJymsNvXTV1JBJpy5YtRkZGPXv2vHHjhkWFZPBvv9ygK9m0pa6u1vqOrumRlihZ7IIhb+P4a9f8NG3mkSNHdPU7aPrVfA5n2FKgDZzBAo2Fs7OzvkMAdbV48eI5c+Z4e3sX9fQxnzzN64/bFyLXpaS+13dcTUCVH3s+ffnlqxcGNoqSHZGPevTo0b17d71GpzPN53CGLf2awI89AwAahYMHDy5evPjSpUuGl86lnTgePbtn4IB1FmY1/7QLHL+opk7YffQnyV8vu3d0GrQv9OnTpzY2NvqKDQCgppN8BZcIAQCfKCgoiMPh9O/f/9KlS7YqJWXHieOqZeOHbTE2gjHadYKVWKrMG5j+eBlTPnv2bKiuAPiawCVC0FjAt9g1RSNGjNi9e7e/v39qzz4WI4Z7/HbvSPiCigq5vuNqGq7dSKi8Xh5hZfc4/vn8+fP1HY4uNZ/DGbYUaNOUTtrDJQYAGqdbt26NHTs2LCzM9u7V9Ms3k+Z3mfrNLhrtP3+/wfGLqnXCH8fmu6+7OEOmXLVh44gRI/QYGABAE3zRKACgUejdu/eFCxeCg4MTOvYw79rebsfTkJMzVUqVvuNq1CrLFJJHuSfKSyxa2EN1BcDXBwos0Fio76sCTZGnp+eFCxdmzJiR0NPf0t3ZZvuTP4/NRM39jFVtDl0Mtbzy6Ehh+a5du/Qdi+41n8MZthRo05RO2sMlhq8b7N+vwPPnz/39/TesX9/65sXUpMz3cz1mjP4NkRCC/YsQ0uwEjP5Y8M3B/Ze/Wb7qKxt9RWg+uxu29Kukk41tSv3VrPZuMwT79+vw+vXrvn37LluyxOPupeT04sLZHf83ZjuC/YsQ0uiEv4/9+XLususCw6cvEygUir7j0r3ms7thS79KTXUMllQqbdeu3bp164inFRUVwcHBAoFAJBKpJzYJDXG+9HParO+ydZn/o/PUMsOnvdR4NIf9+9HZPuFVFxeXESNGbP3ll4iO3vbGTM6uuD3HltclkqarvklMJlOk7P1rX3HJ6YuXKBSKtk7Wy3RdNa6NXoJp0JVq06h2R4Pu1iaxm3S1W+sHf3Fz584lk8lr164lnk6ZMqVfv36FhYVJSUlOTk4hISHaFtRLtLVoiHg+p836LluX+T86Ty0z1Pcl2L+6XbaO89c+26e9ihBKT093dnZet2bNQ7/u+3v13XNyTWPbvzpU3yS24fthxlTK6bADmhO1zfyFp0Mw0AMQTC3T6+VLn8G6evXq7du3+/XrRzyVy+WHDx9evXq1UCh0cnJavHjx7t27v3BIAACds7a2vnv37tHjxy96eLchidHeaH1H1FDqm8R+njth197zY0YPGz7+a/hRZwCAVp9fo9Xdhw8f7Ozsnj9/PmTIEOIM1ps3bxBCpaWlxAyRkZF0Ol3b4vruKgDAZ6mQVHyhXPMF1T2JFRUU6HsPAADq6vOTwxf9qZxJkybNmzevdevW6illZWUIIQ6HQzzlcDgymUzb4hhqLACamry8PBaLxSGR0nPyWEyWvsPRvRqTmEKhoFKrZleBoeHM4b5DJs3oO2j4l44SAPDFNWyBpU4xy5YtE4lECoVi1qxZmjMQWamiokL9gMlkNmhIAIAvydjYmHhg68jRbyQNpMYkVr26Ivx++sYXDQ4AoD8NW2A9e/aMeGBiYuLr6/vu3TuhUIgQKi8vv3r16oMHD8LDw1ks1qtXrzw8PBBCCQkJmue3AACgkbOzs4MkBgCo7st9rUV2drb68t/UqVPd3d0XLFhgZmY2efLkjIyMY8eOFRcX9+/ff9asWTNnzvwyIQEAwOeDJAYAqO7LjcGysLBQP2az2QKBwMzMDCG0Y8eOOXPmuLi4IISmTJkyY8aMLxYSAAB8PkhiAIDqmtEXswIAAAAAfBnwY88AAAAAADoGBRYAAAAAgI5BgQUAAAAAoGNQYAEAAAAA6BgUWAAAAAAAOgYFFgAAAACAjjXeAuvSpUstW7ZksVhdu3Ylfk61Rrt37/b39/+SgYGGgzEeM2bMxo0b9R0I0KXi4mIXF5fo6Gj1lM2bN1tYWHC53HHjxhG/5dccVFRUBAcHCwQCkUi0bt06fYfTgDDGRkZGpH8JBAJ9R9QgYmNjq2za1/rGrp6Zhw8fTtKg/tWWJm3v3r3Ozs4cDqd169anT58mJr5588bHx4fD4Tg4OJw/f75+LX7+70U3hJSUFDabff78eYlEsn79ejs7O7lcXmWesrKyxYsXk8lkPz8/vQQJdCstLS0gIAAhtGHDBn3HAnTm/v37rVq1QghFRUURUw4fPmxtbZ2QkFBUVDRkyJDAwED9RvjFTJkypV+/foWFhUlJSU5OTiEhIfqOqKG8fPmSw+EkJydnZGRkZGRkZWXpOyIdU6lUoaGhhoaGDAZDPfFrfWPXmJlNTEzOnj2b8S+ZTKbHCHXi2rVrQqEwOjpaoVCEh4czmczY2FiFQuHm5rZs2TKJRHLlyhUOh/P69eu6t9lIC6x169Zplk3W1tbh4eFV5vHx8Rk8ePDcuXOhwPoKVFRUGBoazp8/v0+fPlBgfTXu3Lljamq6f/9+DoejLrA0d3FycjKVSi0sLNRfjF+ITCZjs9nqTti/f3+HDh30G1LDIc4E+Pn5OTo6TpgwITc3V98R6djq1avbtGnz66+/ahZYX+Ubu8bM/Pr1azqdHhgY6ODg0Ldv36dPn+o3SJ04dOjQli1b1E87dOjw559/3r9/n8vlqsvHCRMm/PDDD3Vvs5FeIkxMTNT8wVQ3N7cXL15UmScsLCw8PNzS0vLLhgYaBJ1OT0hI2Lp1K4PB0HcsQGfatGmTmpr67bffak7UPLrt7e0pFMqrV6/0Ed0XlZaWVlFRod7wGnPaVyMqKgohtGrVqjNnzhQWFg4YMEClUuk7KF2aPHlyXFxct27dNCd+lW/sGjNzVFQUjUYLCAi4cuVKp06dvL29s7Ky9BikTgQGBi5YsIB4nJycnJCQ0KlTp8TERBcXFxqNRkyv72HbSAussrIyDoejfsrhcMrLy6vMA6XV14RCoZiamuo7CqBjhoaGTCazysQqRzebza5+dH99iBE56g3ncDgymUyhUOg1qIayf//++Pj4Ll26tG7dOiwsLC4uTnME3lfAwsKCRCJVmfhVvrFrzMzBwcF5eXnffPONo6PjunXrXFxcDhw4oJfwGkJGRsbAgQMXLFjQtm3bupQitWikBRaHw6moqFA/raioMDAw0GM8AABdqXJ0SySS5nB0E2laveEVFRVMJpNKpeo1qIZCJpPVJzyEQqGJiclXcIbjo5rVG5vFYqkfu7i4fDX79969e126dJkyZcratWvRZ5cijbTAatmypebJ1SpXDAEATZfm0f3u3Tu5XO7q6qrfkL4AOzs7Foul3vCEhISvOKf5+Pj8/fffxOPi4uLc3FxHR0e9RvQlNJ839rJly6ZOnap++vr1669j/x48eHDkyJH79++fP38+MaVly5Zv3rxRKpXE0/oeto20wBozZszt27fDw8PlcvmWLVtUKpWvry9C6Pnz57du3dJ3dACATxccHLxz587ExMTS0tKFCxcOGzaMz+frO6gGR6PRxo0bt3Tp0qKiopSUlM2bN0+cOFHfQTUULy+vDRs2pKWllZaWTp8+vUePHu3bt9d3UA2u+byxe/fuHRYWdufOHblcvn379nfv3n0Fb+br169Pnz79wIEDrVu3zszMzMzMLCsr69q1q6mp6cqVK2Uy2c2bN8+cOTNhwoS6t9lIT1A7ODicPn16wYIFgYGBrVq1unDhAjGS48CBA3fu3Hny5Im+AwQAfKLx48fn5OT4+/sXFxf37ds3JCRE3xF9ITt27JgzZ46LiwtCaMqUKTNmzNB3RA3lp59+kkgkXbt2LS0t9fPzO3HihL4j+hKazxvb19d39+7dU6dOzcrKatOmDfEFB/oO6nNt2LBBIpH0799fPWXLli0LFiy4ePHi9OnTjY2NjY2N9+3b5+7uXvc2SRjjBggVAAAAAKD5aqSXCAEAAAAAmi4osAAAAAAAdAwKLAAAAAAAHYMCCwAAAABAx6DAAgAAAADQMSiwAAAAAAB0DAosAAAAAAAdgwILAAAAAEDHoMACAAAAANAxKLAAAAAAAHQMCiwAAAAAAB2DAgsAAAAAQMegwAIAAAAA0DGqvgMAAADQTN29e9fZ2dnc3Fw95eXLlywWy97evuFWKpFIHj582LNnT7lcHhUV1aNHDyr1Ez8K4+PjhUKhtbW1esr9+/cVCkWV2czMzEgkEoVCcXR0/PS4/6u0tDQrK8vV1fUTls3JyUlMTOzdu3dubq5UKrWxsdFVVEATCWOs7xjAF0Wn06scTgkJCXQ6XV/xfLL9+/enpKSsW7fuo3M+fPhw5cqVV65c+YS1+Pn5bdu2rXXr1p+wLACgdlQqtXXr1g8fPmQwGMSUkSNHOjo6bty4seFW+vbtWycnJ4lEkp+fb21tXVRUJBAIPq0pf3//Pn36LFiwQD2lQ4cOJSUlCKHMzEwul0u0PGLEiIKCAi6Xu2PHDp1sAkIoKCgoKCioT58+n7Ds2LFjHRwc1q1bV1BQMGDAgNu3b7PZbF0FBtTgEmGzY2Nj8/a/6HR6Tk7Oy5cvCwoK4uPjZTIZQqiioiI2NjY7O1tzWaVSGRsbm5SUJJPJ7t27hxCSSCR37txRqVTEDPHx8RkZGeqZExISkpKS1EX8+/fvX7x4oVAoXrx4kZKSotmyWCx+9OhReno68TQiIqKoqEj9amRkZHFxseb8hYWFa9asWbRoUVZWVkxMDDExPz+fiIqIPyIignh87ty5IUOGPHjwoLCwkJjy5MkTdZwJCQnp6emvXr3KzMwsLy+PiYnJz89Xr2j16tVTpkypbycDAOooKSlpyZIl2l59//79kydP1Ie/RCJ58OBBZWVlTExMSUnJq1evsrKyCgoKoqKi8vLyEEKlpaUPHz788OGDZiO5ubnR0dFJSUlVGjcyMjp58iSHw0lLS7vzX+Xl5cQ86enpcXFxRFbUjOrhw4cSiaR6wDExMURebd269YIFC4jHmzZt+t///jdp0iSEUB1jrnG9ajdv3szKyurTp0/taa3GlJuSkpKbm5uWlvbixQsjI6Nhw4atXbtWW/+Dz4JBM+Pg4FB9YkhIiLu7u7m5uZ2d3fPnzw8dOmRoaNijRw9LS8vAwECZTIYxTklJcXV19fT07Nix47BhwzgcDsb4zZs3CCGJREK04+fnt2XLFoxxTEyMg4ND+/btW7du3bFjx/T0dIxxaGho27Ztu3btOm7cODs7uyFDhhBL7dq1SyAQeHl5mZubT5w4UalUenl5rV69mng1KSmJxWKJxWLNgFevXv3dd99hjO/evcvn8xUKBcaYSBMZGRkY46NHj3bu3JmYuVWrVhkZGT4+Plu3bsUYS6VSNptNLI4xdnFxuXz5cnBwsJ+fX6dOnUaPHi0QCLZt26Zel4uLy82bN3XS+QAATRQK5ddff6XRaNevXyemjBgxYtGiRRhjmUwWHBwsEol69uwpFArXrFmDMX7z5g2Px2vfvr2rq+vvv/8eHBzct2/frl27jh49ms1mL1++vHPnziNHjuTxeFeuXMEYl5SUeHt7Ozo6+vr6Ghoa+vv7Y42sRZQjRUVFp06dGvGvVq1aMZnMzMzMgoKCvn372traduvWzcLC4vbt20SEq1atIvJVy5Yt3dzciIxXnYeHx4YNG9RPv/vuuzlz5mCMPxqztvVq8vHxCQsLIx7UktZqTLknT560tbVt3br19u3bMcZZWVl8Pr+oqOhz9yWoBgqsZsfKyuqxhsLCQoxxSEgIhUJ58+YNxvjdu3csFosoKcrLyzt37vzrr79ijIcOHTpx4kSikUmTJtVSYCkUCjc3t5UrVxITZ82aNWzYMIxxaGgojUZLTk7GGOfk5JDJ5BcvXrx584ZGo0VFRWGMCwsLLSwsbt26FRIS4urqSiy+cuXK0aNHV9kKZ2fnCxcuYIwVCoWhoSGxuLe3t7m5+cGDBzHG48ePX79+Pcb47du3Hh4eGOPt27f7+flhjG/fvm1ubm5vb48xTk5ONjAwqKysDA4OdnV1JUrJEydOiEQi9boWLVqkTlsAAB2iUChRUVFr1qyxsLDIz8/HGgXW5s2bHRwcCgoKMMbJyck8Hu/y5ctEwvnrr7+IxYODg11cXIj8ExQUZGlpWVFRgTFetGjRiBEjMMYHDhzo1auXUqnEGOfk5JBIpOfPn1cvsNTxJCcnm5iYHDlyBGM8ZcqUvn37Ejnh1KlTRONPnz5lMBivXr3CGBODKz6hwKo95hrXq9lydnY2hUIpKSnBH0trNaZcjPHo0aOXLVumbrBz585EuQZ0Cy4RNjs5OTlDNURFRRHTbW1tiQGY169fNzY2ZrPZ0dHR8fHxnTt3Pn/+PELo2rVrQUFBxMwzZ86sZRXJycmJiYmenp7R0dHR0dEeHh6XLl0iLiPa29sTw1fNzMwEAkFBQcGNGzdatWrVpUsXhJBQKMzMzPTx8Rk1alRqauqzZ88QQocPH54wYYJm+4WFhUlJSW3btkUIUSiUAQMGXL9+vaKiIj4+fsaMGbdu3VKpVFevXh0yZAj69/ogQiggICAiIkIqld64cWP69Ol5eXlpaWkXL1709/cnxn94e3vTaDSEkKura0FBgXp1bdu2jYyM1EnnAwCqW7p0aYsWLapciyfOKxsaGiKE7O3thw4devnyZeIlzYFHvr6+TCYTIWRtbe3p6clisRBCVlZWxCEcFBR048aNuLi4EydO7Nq1i0KhqK/9VVdcXDxw4MDp06ePHTsWIXThwgUvL6+nT59GR0dbWloWFRXFxMRcu3atW7duLi4uCCE3Nzdvb+9P2N7aY65xvZqLR0VF2dnZGRgYoDqkteopt3o8kOIaCNxF2OzY2dm9ffu2+nRjY2PiQUFBQXl5+apVqzQXwRgrFAoul0tMIbJedUQVVVBQQCKRfvvtN/X0Xr16icVihJC6BYQQiURSqVQSiYTH42lORAjx+fyAgIAjR45IpVKxWOzn56e5ltzcXISQSCQingYEBOzcudPT07NTp05+fn6jRo16/Pgxn89v2bIlQujcuXM7d+5ECNnb27do0eL+/fs3btzYsWPHw4cPb9++fenSpfHjxxPtqGMjkf5z84dIJKoyPAIAoEMUCuXQoUNt27YNCQlRT5RKpXw+X/2Ux+OpBxupkxVCiKhOCOqR8ggh4hCOjY0dOnSoqamph4dHx44dKRQK1nJfl1wuHzFihLu7uzr1FRYWXrx48cGDB8RTLy8vhUJRVlZGVDYEbZmwdrXHXON6NRfPzc1VZ7+6pzX0b8qtHo9IJHr9+vUnbAioHRRYoCpXV1cWi3XhwgXi1uUHDx6UlZWRSKSWLVs+efLE09MTIRQfH0/MTJzyKS0tJf4gS01NRQg5OTmRSKQdO3YQtxCnpaXdunVL2306zs7Or169kslkxJ2M33777cCBA0eMGBEUFDR37lwymTx27NgqN1ETKaO8vJxYqb+//8SJE8+cOePr6+vh4SEWi3fu3EmctSosLMzKyiLOdSGEAgICTp48mZSU1LFjR19f3wsXLty/f//IkSO1d0h5eblmkgIA6Jydnd0ff/wxffp0Jycn4lS6q6vr48eP1TM8fvx44MCB9W123bp1ffr02b9/P0IoLy9v8uTJ2gqs//3vf6WlpRcuXCD+xkMIubi4TJw4cfr06QghhUIREhLSsmXLzMzMsLAwhUJBJKUXL1507Nix/ptbmxrXqzkDl8vVPA/3CWlNvY0ESHENBC4RgqoGDx5sbGw8duzY27dvHzlyZOjQocS9hKtXr165cmVYWNi5c+d++OEHYmYrKytra+uZM2deuXJlypQpxPlnkUg0Y8aM0aNHh4eHX7lyZcSIEXfu3KlySKv5+/tbWFhMnDjxzp07mzZtOn/+fOfOnRFCfn5+JSUloaGhVa4PIoTMzc3ZbDZRzCGEDAwMunfvHhoa2rt3bzKZ3KtXr6NHjwYEBCCELly4oJmUBw8e/Ndff3Xv3p1Kpfr6+v7zzz+enp5CobD2DklNTdXht9cAAGo0fvz4wYMHEwMDEEILFiw4c+bMmjVr7ty5M2vWrHfv3n333Xf1bdPExCQuLo44rzNy5EgSiVTjrX9bt249fvz40qVLHz16RNxF+P79++XLl//000/79++PiIiYOHHi9u3beTze8OHD2Wz2pEmTbt++PWvWrBqvBnymGterOYODg0N6err6XNQnpDUDA4N79+7dunWLeAoproHAGaxmhyhfqjA3N+/QoQPxmEqlRkRE/PLLL9u3b2exWH/++eewYcMQQsQ1u/3799NotGXLls2ePRshRKFQLl26tHPnzt9++23o0KFubm6WlpYIoZ07d/7111+HDh2SSqXjxo37/vvvEUJmZmYeHh7qlXbv3l0gEFAolLt3727ZsmXr1q0WFhb379+3srIiwhg7duzVq1er/4FIpVL79esXERGhbu3bb78lk8nt27dHCI0ZM6aysrJ79+4IoczMzDFjxqgX7NKlS9++fYkBFu7u7v7+/oGBgcRLrq6u6usRHA5Hc2hFRETEoEGDPrW/AQBaeXt7a1YPu3fvFovFxJghNze3J0+e7Ny5c9OmTS4uLk+ePLGwsMjKyvL29iaT/+/UgOZh26JFC/X3+VlaWrZr1w4htHHjxvXr169atUooFM6dO9fT0zMvL8/FxYVohMFgeHt7U6nUnJwcDw8PzS+pWrx48ciRI0Ui0YEDB06fPt2mTZt79+4Rl/Pu3r27YcOGTZs29ezZc+nSpZrfMqrJw8ND8xsHXVxciCuDH41Z23rVOnfuTKPR4uLiiIxXS1qrMeUihObPn7948eLw8PDevXurVKoHDx5ojgkBugJfNAo+RXR0dJ8+fcrKyhp0LZMmTXJxcVm8eHH1l65evbps2bInT540aAAIocLCgmNxSwAAIABJREFUQldX18TERCMjo4ZeFwAA1MWSJUtkMtm2bds+v6lLly6tW7cOBrk3BLhECBqjqKiotWvXhoeHf/vttzXO4Ofnx+fz79y509CR7Nq16/vvv4fqCgDQePz444/nz5/X/DbmT7Z9+/b169d/fjugOiiwwKfg8XheXl4N135hYWF0dPThw4dNTEy0zRMaGnrx4sWGiwEhJJVK09LSavmaaQAA+PIMDQ23b99OfIHO53j58mXPnj179eqli6BAVXCJEAAAAABAx+AMFgAAAACAjkGBBQAAAACgY1BgAQAAAADoGBRYAAAAAAA6BgUWAAAAAICOQYEFAAAAAKBjUGABAAAAAOgYFFgAAAAAADoGBRYAAAAAgI5BgQUAAAAAoGNQYAEAAAAA6BgUWAAAAAAAOgYFFgAAAACAjkGBBQAAAACgY1BgAQAAAADoGBRYAAAAAAA6BgUWAAAAAICOQYEFAAAAAKBjUGABAAAAAOgYFFgAAAAAADoGBRYAAAAAgI5BgQXqp7S09MOHD/qOommDPgTgC8MYp6Sk6DuK2jT+CEF9NaMCSyaTLVmypEWLFnQ63dzcfPLkyV/yQ87f33/r1q3Vpz98+HDw4MFCoZDNZrdv3/63335TqVQfbY3JZD558uQTwoiOjvb19TUwMGCz2Z6enidOnKhvC126dImPj/+EVVcnEAhI1UycOFEnjatFRkZaW1szmczw8PB6Lbhnz57q4VVWVn5+SOo+PHToULt27T6/wer8/f3VMdPp9FatWv3xxx/ES3Z2dhcuXGiIlYIGcuDAgbZt2zKZTIFAMHDgwJiYmC+26o0bNw4aNKj69KysrClTplhaWjIYDHt7+wULFojF4o+2pi0NflR2dvb48eNNTEwYDIazs/OaNWsUCkW9Wvj+++/379//Cauul0GDBs2dO1dzysaNGzt27FjLIo6OjmfPnkXaIySRSHfu3NFpmAghZGVldeXKlU9enMvlqjMMlUq1sLCYO3euUqnUYYRfgWZUYC1fvvzUqVO7d+9OTEw8efLk27dvBw8erN+QwsPDe/Xq5ejoeOPGjVevXv3444+bN28ePXp0A60uLy+vT58+HTt2jIqKio2NnThx4oQJEy5evFivRgoKCnQVT0JCQkZGRkZGhru7+5IlS4jH27dv11X7hKNHj7q7u6empvr7+9d3WTs7u4z/YjKZnx+Sug979uz5aZ83dTFt2jQi5tevXy9evHju3Ln1LTFBY3D58uX//e9/8+bNe/78+d27d21sbHx8fN6/f6/HkFJSUjw8PLKzs48cOfL27duQkJDo6OiOHTsWFRU10BqHDRtWVFR0/vz5hISELVu2hISELF26tF4t6DBx6dbvv//eqVMn1Igj1Obo0aOlpaXE+fg///zzr7/+2rVrl76DamRws9G7d++VK1eqn6alpQ0aNKioqAhj/Pz5c19fX4FA4OTkFBISQswgk8kWLVpkamoqEAgCAgLev3+PMc7IyPjmm2+MjIwsLCxmzJhRWlqKMQ4ODp45c2a/fv0cHR1bt259/fp1ooXLly+3atWKzWaPGjWqe/fuW7Zs0YxHKpWamZlt3rxZc+Lbt2+ZTOY///yDMQ4MDJw4caKNjY2Tk5NMJtuyZYu5ublAIFi1ahWDwXj8+DHGuKCgIDg42NTU1NLSct68eZWVlRjjkJAQX1/fbt26CYXC2NhYdeMRERFUKlUmk6mn/Pzzz3v27MEYOzs77969m5iYn5/PYDDS0tIOHTrk5OTE5/Pbtm177NgxjPGwYcPIZLJIJNq3bx/G+MyZM+7u7jwer1OnTpGRkRjjlJQUQ0PDVatWtWrVysTEZPXq1Tt27GjTpo2xsfGKFSu07RoPD48NGzaon1paWs6ZM8fQ0HDChAlKpXLlypVubm5cLtfc3Hz9+vXEPLa2ths2bOjSpYu1tXWvXr3S0tIwxjExMZ07d+bz+Y6OjkuWLFGpVPPmzeNwOBwOp02bNtp2tObqNKPavXu3g4ND9WgDAwMXLVpEPI6KiuJwOMSG8/l84q9VCwuLoKAgop+rv4s0+zAsLKxt27ZEU6Ghoa6urjwer2PHjsRbSFubdeHn5zd//nzNKV26dFm6dCnRdUuWLGnfvj2LxfLy8iK6rsZ+VqlUCxcuNDc3F4lEvXr1Ur+Xqu930HDWrFnj7e2tOWXs2LH379/HWg5/jPHff//t7OzM5XI9PT2jo6OxlsQVGhrq6+s7ceLENm3a2NnZbd26lVj87du3Pj4+HA6nQ4cOkyZNGjhwYJWQhg0bVmWiVCpt1arV7NmzcbXEVWMaVCgU69ata9GihaGh4dChQzMzM7H2xKVSqSgUyu3bt9VTwsPDZ8yYgTGeMmXK6NGj1dPbt28fFhZWPQ9s3ryZxWIZGBh89913WEsesLW1XbduXbt27UxNTYcOHXrp0iVPT08zM7OAgACJRFLHnTVw4MA5c+ZoTtmwYYOHhwfWfjg7ODicOXOmSoSaEELEtn80wuDg4KCgIB8fn65du3bv3j0+Pp7o1c6dO6tbU392WFpaXr58GWNcPc/jOhzjHA7nzJkzmlNGjBgRFBSEtezcGpNJaGhot27dRo0a5eXl5e7ufuLECaKpBw8e9OjRg8fjOTo6/vrrryqVCmv5nC0sLBwyZIihoaGlpeXo0aMLCwu1BaAXzajAOnTokEAgWLJkyY0bN4j8QhCLxWZmZmvXrpXJZHFxcZaWlhcuXMAYr1ixonXr1u/evZNIJGPHjg0ICFAqle7u7hMmTCgpKXn//n2vXr0CAwMxxsHBwUZGRikpKRjj9evXOzs7Y4wzMjJYLNbhw4flcvnBgwcRQlUKrLt37yKE8vPzq8Q5fPjw8ePHY4wDAwMNDQ3j4+NTU1NPnTolEoliY2MlEsn06dMRQsRB0r9//4CAgKKiog8fPvj4+CxYsABjHBISghA6evRoSkqKUqlUt1xZWdmmTRsfH5+//vrr9evXmitdu3Ztz549ice7du3q1atXaWkpjUZ7+vQpxviff/7h8/kVFRUYY1NTU+KdHR0dzWQyL1++rFAoTp06JRAIcnJyiDEExEf7vXv3EEJTp05VqVSvXr0ik8mpqak17prqBVb37t0zMjKysrIOHTpkY2NDFAHXrl0jkUhEI7a2tj179iwrK1Mqlf379586dSrGuEuXLr/88gvG+O3bt8bGxhERERjjadOmzZw5s5Ydrbk6zajqW2AhhBYsWKBSqfLy8iwsLI4cOVLju0izD9UF1qlTp/h8/p07d+Ry+fHjx5lM5suXL7W1WReaBZZSqbxx4wabzSYSoq2trZOTU1JSUn5+vpeX17fffosxrrGfr1y50qJFi/z8fIVC8cMPP/Tt21fbfq9jVOATJCQkCASCSZMm/fPPP1W6usbD/9atWxwO586dO0qlcufOncbGxhKJpMbEFRoaihAKDw/HGEdGRlIolIyMDIxxmzZtZs6cWVlZ+eTJEyMjoyq1lEwmYzAYp06dqhLnzp07rays8H8Tl7Y0uGnTJkdHx9evX0skkh9//LFTp04qlUpb4sIYT5kyxcnJadu2bY8fP9b8M+PevXtsNrusrIzoKA6HU1ZWVmMeGD169LJly7D2PGBra9utW7fKykqxWGxoaOjh4VFSUlJeXu7g4PD333/XcWfVXmDVeDgTBZZmhFVoFli1RxgcHCwUColPogMHDtja2kql0toLrBrzfF2O8SoFVkREhKGh4a5du7Tt3BqTCfEOPHv2LMY4MTGRy+W+ePEiLS2NzWb//vvvMpksJibGwsKCKIJr/JxdvHjxyJEjpVKpWCz28vJat26dtgDquAd1qxkVWBjjmJiYuXPnuru702i07t27X7t2Df/70aKeZ926dcSnoIODQ1hYGDExPz8/Li7u6dOnZDJZLBarWyOTyRUVFcHBwcHBwcTEZ8+ekUgkjPHOnTs7duyobrZz585VCqzjx4/T6fTqQc6ZM8fX1xdjHBgYOHbsWGLi8OHDieyJMS4tLaVQKI8fP87MzEQIJScnE9Pv37/P4/EwxiEhIebm5jX2QEVFxZ49ewICAgwNDU1MTObOnVtSUoIxTk1NVafXbt267d+/XyqV8vn8adOm3b9/Xy6Xq/OdujiYPHmy5imfPn36/PLLL0QSSU9PxxhLpVKE0KNHj4gZhELh3bt3a4yqeoG1d+9e4rFYLCZay83NvXnzJo1GI/4it7W1DQ0NJebZsWOHj48Pxrh///4+Pj7h4eGlpaXqgNUFlrYdrbk6Tbt37yaRSBwNREKppcAiDn6M8dChQ1evXo1rehfhmgqswYMHa55wCggIWLJkibY268LPz49GoxFhUygUNputfv/Y2tqqPzB27NhBnB2psZ+jo6PZbPbGjRtfvnyp7s8a93sdowKfJisri/gTiMViubi47Ny5E2Os7fD/7rvv1GdBVCrVgwcPoqKiakxcoaGhtra26rUIBIK7d+/Gx8eTSCT1n6CLFi2qUmDl5uYihKqf1Thz5gyVSsX/TVza0qCjo+P+/fuJiTKZjMVixcTE1JK4MMbnzp0LCgqys7Njs9kjR45MSkoiptvb2x8+fBhjvHTpUuKdWWMeUJcv2vKAra3twYMHiYldu3ZVX1sYNmxY3Y+7jxZYNaaIuhdYtUcYHBw8a9Ys9YIikejWrVu1F1g15vm6HOMcDofNZvP5fD6fz2QyLSwsVqxYoVAosJadW2MyCQ0NJa4tEEaMGLFixYpt27YRPUb45ZdfunbtSmxd9c/ZTZs2tWjRIjQ0NDs7W91sjQFU79gvoBmNwaqoqGjXrt327dvj4uLy8/PHjRs3aNCg2NjYtLS07Oxswb82btxIZK73799bW1sTyxoZGbm7u+fm5gqFQh6PR0xs0aKFSqXKyspCCIlEImIihULBGCOEcnJyrKys1Gtv0aJFlXjMzc1lMln1sRSpqalmZmbEY3UAmq1xuVxjY2OEUFpaGkKoQ4cOROQDBgyQSqXEhXz1gpqI4fPTpk07d+5cfn7+1atXHz9+TAwqt7W17dGjx/Hjx1NSUmJjY0eOHEmn0+/cuZOfnz9o0CCRSLRs2bIqo0rT0tJOnjyp7rfIyMj09HTiJaFQiBAik8kIIQMDA2IimUyuy/j9KhuuUCgWL15sZGTk7e1N/LlDdC/6b58TLYeFhbm6un7//feGhoajR4/Oy8urEnCNO1pbdxHTn2no27dvlRnUwWgLqfq7qMYV5ebm2tnZqZ+2aNFC3ZnV21T7559/qP+6detWlTaDgoKIsFNSUsRi8ZYtW9QvGRkZEQ8YDAaxW2vs586dOx88ePDKlSsdOnQgPsZQrfsdNASZTCYSiX766ae7d++KxeLt27dv2LDht99+03b4a77lSCRSt27dioqKPpq40L9vsJycHD6fz+Vy1TNXicfQ0JBOpxNr15Sammpqako8rjFxabaWnp4+Z84cInJjY2OMcWpqKtJ+JJaXlwcEBBw4cCAlJeX169eGhoa9evUi7jiZMGHC0aNHMcZHjhyZMGEC+ow8QCQuhBCZTK4lcc2ZM0d93FUZ1s1kMmUymeYUmUymOXCzlsO5Lj4aoaWlpXpmIyOj6p8vVVJWjXm+jsf49u3bnz17dvXq1bZt23p5eS1dupRCoSAtO7fGZFIlYJFI9P79+zomQ2JD5s+fP3Xq1O3bt1tZWXXt2pW4/0Pbu+vLay4FVlFREZfLVX8I8Xi8GTNmODo6PnnyxNLS0s3NrfhfycnJxD1WVlZW6gMvLS1t2bJlNjY2RUVF6ptl3r17RyaTiVqnOktLS817bol0pqlr167m5ua7d+/WnJicnHzt2rXhw4cTT0kkUvXW1FWUpaUliURKTk4mIs/JyXnx4gXx2aleUNMPP/zQr18/dcvt2rWbM2dOdHQ0MWXChAknT548depUQEAAj8crLi4Wi8WnTp3Kz88/c+bMnj17iFtdNEOaMmWKut9evny5atUqbf1fX+q1LFy48P3796mpqYmJifv27avlLhWVShUXF7d169a0tLS4uLi0tLTVq1drzqBtRyMt3YUQotFojho4HA5CiEwmy+VyYoaPjkut/i6qcXU2Njaa75Z3796pi+xa9OnTR138de7cucqrAoGACNva2ppKpdbeVI39nJaW5uDgcPv27cLCwsWLFwcFBX348KFB9zuorlOnTmvXriUe02i0/v37Dxs2LDo6Wtvhr/mWQwgtXLiQQqHUK3EVFxerh6tXT1xUKjUgIIA46aueKJPJ9u3bV3vi0mzNwsLiwIED6ndRTEzMgAEDkJYj8ezZsyYmJqWlpcRTKyurdevWZWdnZ2RkIIQmTJhw7dq1W7duSaVSX19fbXlAMyRteaCOFi9erD7uiJJCzcrKKikpSXNKQkKCtqqxCm1ZqF7UhW9lZWVmZqa1tbVmviorK6tS/9WY5+t4jJuYmNjZ2XXu3Pnq1asxMTFEdYu07Nwak4lmwAiht2/fWltb1ysZxsfHjxs3Li4uLjs7u02bNkFBQdoC+KTu/FzNpcASCoXjx4//7rvvQkNDnz17Fh0dvXTp0tTUVF9f38GDB+fk5OzYsUMul2dlZfXr12/Hjh0IoQkTJmzevDk9Pb2ysnL58uUJCQktW7b09PScNWsWcd/Ejz/+OGTIED6fX+MaR4wYkZKSsmfPHoVCcfr06fv371eZgUqlhoSEbN68+ccff4yPj09PTz9+/Livr2+/fv2GDRtWZeZJkyaFhoZGRUXJZLKlS5cSB4ytra2Pj8+sWbPEYnFFRcX//ve/wMDAWjph8uTJT58+nTp16vXr1xMSEs6cObNq1Sr1rZSjRo168eJFWFgYcZyUlpb6+fldunSJQqEQf2QQpRuDwXjz5k1ZWdmkSZP+/vvvO3fuYIyjoqLc3d0jIyM/YdfUrri4mPgOi8rKysWLF6tUqioJQo1MJs+YMWP9+vUKhcLCwoJGo6nP0xC07ej6cnJyOnv2LJHft23bVvvM1d9FSKMP1bNNmjRp3759ERERSqXy9OnTV69eHTdu3Ecj4fF4rf9FFH+frMZ+joyMHDRo0Js3b9hstkgkYrFYbDb7y+x3oDZ79uxt27Zt3LgxMjIyPj7+zz//PHTo0ODBg7Ud/uPHjz9+/Pj9+/dVKtXu3bvDwsK8vLzqnrhatWrVqVOnefPmVVRUvHjxghgXVcW2bdsSExMDAgIiIyOzs7Nv377dp0+fioqKlStXVplTWxr89ttvV61alZycTATp6elZUlKirQf8/f0tLS0HDx589uzZhISEW7duTZ48uVWrVvb29gghBweHjh07zp8/PzAwkEwma8sDDAYjPT29oKDg8/OAubm5+rir8tKYMWNu3769cuXKFy9ePHv2bNOmTadPn1ZXHrVTR1ivYKo4fPjwo0ePpFLpkiVLLC0tu3bt6uTk9Pz58/v375eUlCxbtoy4sKBWY56v7zHO5/OPHTt29uzZvXv3Ii07t8ZkghBKTEwMCQlRKBQnTpx48ODBmDFjRowY8fbt2z/++EMul8fFxf3yyy9E2VSjPXv2TJ06tbi42MjIiMvlEvu6Xu+uhqWP65L6UVlZuWLFChcXFwaDweVyfX19o6KiiJdiY2N9fHyEQqGpqens2bOlUinGmChlrKyshELhN998Q4xGz8zMHDVqlEgkMjQ0nDx5cnFxMcY4ODhYPYDm+fPn6l69d+9eu3bt2Gx23759+/fvX2UMFuHhw4dDhgwxMjJisVht27bdsWMHcRkb/3esD8Z479691tbWBgYGs2fPtrCwIK6jf/jwYfz48aampkKhcPDgweqbcTQvuldZXf/+/YVCIZVKtbOzW7p0KbGxhDFjxhgbG8vlcuLpyZMnXV1dORyOtbX1tm3biIkrV65kMBirVq3CGJ84caJNmzYGBgYODg7EX7TEXx7EAA6iCkxMTCQWNDIy0rwPSFP1MVjE7S0Y44SEhE6dOhkZGdnZ2c2ePdvT0/OPP/7AGNva2p4/f56Y57fffiMGEsXFxXl5efF4PGLvEKPy1WOwtO1ozdVp0jbIvaCgYMiQITwez8HBYd++fZpjsNQjV0aMGEHcslrju0jdh1XuInRzc+NwOG3btiXGHWtrsy6q30Woptl1u3fv7t69ey39vHz5cgsLCw6H4+7ufvXqVWKp6vsdNKiwsLBOnTpxOBwGg9G2bVv1ELoaD3+M8eHDh93c3AwMDLp160bcrlVj4goNDdUc7KI+QrOysgYMGMDhcNzc3KZPn179LkKMcXZ29rRp06ysrBgMRosWLebNm0fcwIWrJa4a06BMJlu1apWdnZ2BgUGnTp2Icei1JK6srKxJkyZZWlrSaDRjY+Px48dr3hq2Z88ehBAxwBFryQMXL14UCATEYM0a84DmcdG9e3f1XdX1Ou4wxufOnevSpQsxRMnDw+P48ePEdG2Hs3oMlmaEmpDGGKzaIwwODg4ICOjSpYuBgUHfvn3V4/Pmz59vZmZmZGT0888/u7i4VLmLsMY8/9FjvPpdhOvXr+dwOElJSTXuXFxTMiFunR49ejSfz2/Tpo06w0RGRnbv3p3H49nY2GzcuFF9F2H1z9ni4uLRo0cbGhpyudx+/foRm6wtgC+PhP97RRY0ZwsXLpTJZJ92XgcAAPTi0qVLS5cuffbsmb4D0bOJEyeKRKKG+2o9nfv7779///33T/vS7CbhIyMzQDORk5Pz9u3bAwcOVB8rDQAAjZNYLE5LS1u/fv3UqVP1HQsAVTWXMVigdqdPn/b39585c2arVq30HQsAANTJu3fvunbtKhQKp0yZou9YAKgKLhECAAAAAOgYnMECAAAAANAxKLAAAAAAAHQMCiwAAAAAAB2DAgsAAAAAQMegwAIAAAAA0DEosAAAAAAAdAwKLAAAAAAAHYMCCwAAAABAx6DAAgAAAADQMSiwAAAAAAB0rFEXWDk5OdHR0UVFRfoOBAAAPu7Vq1clJSX6jgIA0Cg03gJr+fLlbdq0mTdvnr29/enTp/UdDgAA1CYuLq5Lly4JCQn6DgQA0Cg00gIrMjJy586dsbGxUVFRZ86c+fbbb8Visb6DAgCAGshksvXr1/v6+paWluo7FgBAY9FIC6xz5875+/tbW1sjhHr16mVtbX3u3Dl9BwUAADW4ceNGVFTU3bt3WSyWvmMBADQWVH0HULO0tDR7e3v1Uzs7u9TU1BrnpFKpSqXyC4UFAPgMGGN9h9Ag+vfvP2DAgLrMCfkKgKbi8/NVIy2wKisraTSa+imdTlcoFDXOqVQqG0/WJpFIOg/mk9us74J1mb/2eWp5tb4vNURPfjKdB/M5DdZr2c/fp7XPoO0lbfu09kiarrpvWo35ql7d2NDTIRjoAQgG6ShfNdICy9DQUHPQVVFRkaGhobaZ/yC9IB7QOGR5uYpERiwTKkNIQQiJ38oQQkJXBoVByo+rJJGRhReH70ynG1CobBKVTXYazeda06TFyqw75QgjmgGZxiFT6CS6gEKmkug8MpVFpjC/2g8GAAAAADSERlpgeXp6Hjx4kHgslUrj4uJ+/vlnbTNzkiQcGp1PY5FlJCGPJaSymaU0sphCx2S+MwMhVPhSqqhQGXdgYhXKulVeliGXlSrl5Vj8VnbY9Y2iQkVhkqx6cyl0krxMJS9XKWVYWqTECiwrVSkqVEoppvMpFAaJxiVTmSQKi0znkRkCCkNIIdNIDAGFwiAxjSg0A/L6USFpF0uZIiqdR6YwSHQehSmifGZXrFy58sssWJf5a5+nllc/7aVGQucRfk6D9Vr28/dp7TNoe6nx79NGpb7d2KDTddW4NnoJpkFXqk2j2h0NulubxG7SS7JqRBdiNBUXF7dq1Wr06NEDBw78448/8vPzIyIiapyTRCIFRxytUMiLZRKZSlkmlxZIK8QySZlCxqLQ2FQam0rn05lGDDabSjdisA1oDAGdJWJyRAwOk0ITMTkiBlvE5LAoNC6NoS0eabFSJcPyMpVCgpWVKqlYJS1SSouVKjmWiZXKSizJVyrKVfIylbxMJclXyMtUSimWFimlRUqaAZkhoDAEFJoBmSWiMI2oNC6ZIaQwjShMEYVlTGWZUOkGZJoBmSWiIjhZhhBqZJcIgU40h33K5XJv3LjRpUsXbTM0h04gwJZ+fZrPliIdbWwjPYMlEAgePXq0cePGbdu2ubu7//XXX7XMbEv147DIBnQSj0bmMcgGNLIBnWRAJyOSnEpRICQvlFYUyyrLFbL8yvIyhbRIKnktzousTJUo5fmV5QXSigJpRYVCpsQqEZNjxOCYsrgiBseIwRExOSImx5jJMWZyRQyOyJxjxGDTyPU7KSUrUUmLlTKxUlaiqsxXEKWYtEhZ/EZWGa2Q5Cok+Up5mUpWoqwsULJEVI4FlWNJY4ooTCMKS0RlmVLZplSuNY0lorDNaaRGet8nAAB5eXnxeDx9RwEAaBSafEFKIpFeZbwppZiUKGilMlwiU5XJVCUyXCpTlchUJTKVXIWEDLKQSebRyQZ0khGTImCQ+Qwyj042YpF5dDKD8n9njYh6K6+yPK+yjCi88qXl+ZXlHyrL1FMKpOV8GtOSzTdn84wYbDMWz4YrMGKwbbmGJkyuOduAR2N+8rZgJa4sUJZlKSqy5ZJ8ZWW+QpKnlOQpKnIVZRnyynxFZYGSaURhm9MMbGkGNjQDO7qBDY1rRePa0NimjbRW/jTN6k+lZgL2KWpOnQBb+vVpPluKvu4zWPUijPLlV+aSaHwy05jCtSUzRBSOJUVkS+HaUDi2SrqohCQorFQRJVeBRJVaoiBqr3yJSixV0SnIiEUxZlEMaCQRiyZiGZmzjFvzKXwGiUur4XxRXmVZVkXJe0lJfmX5e0npu9KCR3np6eXFHyRl2ZISGolswxXacATmbJ45i2fNEdhwBTYcoS1XyKR8pLdJFBLLhMoyoaL2NVdpShmuzFOUZytK0+Vl6bKSd7LsO+WlGfLngZarAAAgAElEQVSydLm8TGVgS+M70vlOdJ4dXeDCELoyDGxoTfSaIwziAaBJaz6HMGwp0KbJF6QkEqmy5CCJbIKUDJKCrCovVkmLlBWZyrJ0ZXm6sixNJc3D8lIKx5rMsaFwbChcWyrPicpzonBsyCwzhFCZXJUvUeVLlKUyXFCpzKtQ5leqCiVKsUwlVyFjFsWYRbbgUk3YFBGTbMSiGLPIBnStF+oKpRXp5cXpZUXZFSW5laVpZUXpZcUZ5cVp5UUiBseZb2zLFdpyhA48IyeeyI5raMYy0Ek/KCpUJaly8RupOFkmTpaJk2RFr6XSQqXAlWHoxhC2ZAhdGIZtmAJHehMtuUBT16z+/NUGOgGAJkEnh2qTP9pJJJJE/JdKmYsV71XKDypVAZnMJ1OtyFQrMsWMTLUiUy1ISKiSFCjL0pXlGcqyVGVJkqL0rbI8A8uKKRwbioE9ledC4dpRBa4Urh2Fa0+i/N9od6kS50mUHypU2WWKPImSqMPyJEoKiWTCppixKeZcigmLYsGlmHOoHNpHKpeM8uKkkrz0suK0sqI3JXlvSwtSSgvlKqWbwMTRQNTCwNBNYOrCM3bhm7CptNqbqiN5qarolbQwQVqUKC16Jc2Pq5QWKkTtWSYeLGMPpokHi+/EaJyDup4+ferh4aHvKIAuQW2BmlMnNJ9DGLb0qwQFFkI19AJWKfNVikyVIkulfK9SZKgU71WKTBKZQ6ZakylmZKo1mWZNodqRqWZYKVeWpytL3ipK3ihL3ylKXivLUpVl6RSOJYXnQhW0pPKJ/13JdKHmSoulqjyJMqdcmVuufF+hzC5TZJcrWRSSGYdiyqHY8WjWXIollypkfrx4KZBWJBbnvistSC4teCX+8FqclyTOs2DzOhhZuQlM3ASmbYXmLnwTso6+pLGyUJn3VJL3VPLhqSTvaaW0WGneg23hxTHrxjbxZFHocHYLNJTmU1vUAjoBgCYBCiyEECKRSM9zSlxNuFRybcWBSpmnUmSolLkqeYZSkaZSpKuU+WSKGYVmR6baUeiOFKodmWqOEBmpFIrSZIX41b//EhXiVyQKiypoSeU504StqYbtqYKWZLqgyioKKlW55YqccmVqiSKrTJlZppApsSWXasej2vKo1gZUOx6VRf14BaPC+LX4Q1xRTmJxbmLxh5iCzNzKMnehuYeRlYfIysPIyk1gQtHReSfJB0X2vYqce+U5DyqKk6QW3hxbfwNrPy7fga6T9gFQg9oCQScA0ERAgYUQQiQSyWXjrfQiib0Ru6WpQTtLXktTA3dznr0R+yNLYrlSkalSpCvlb5XydypFGlYWkqm2FJoDmWZLoTlSaE4kMpeYV1mRpShOVJa8lhfGywufKcSJZIYRTehOFbamGXnQjDpQuHbV11AuxxmlitQSRWaZIlWsSC9VGNDJdjxqCz61BY/qIKAJGHWqk8SyytjCrKf5mU8LMp/mZ2ZLStoZWvQwbeEpsu5ibGvB1s1t4ZWFyswbZelXytKvljIEFPvhPPvhfGMtw+0BqC+oLRB0AgBNBBRYCP3bC1KF6nVe2cv3pc+yShJyS59lictlSg9rgYcV38OK72El+Hi9hRDGUpU8WSlPUSpSVbI3SnkyiSKg0JwpdGcKzYlCc1bXWwhhRclbRfELeWGcvOCpoiAGKytpRh1oRh40USe6SXcyy7SG9hH6UKFMEStSSuQpYsXbYrkBnWzPp9nzqc5CmgOfWvtJOLUSeeXj/Iz7uSlP8jOj89J4NKaXaQsvU/u+ls42nKrn1T4FRrmPJO/+Eb89VUKmkVwC+S5BQgNb3QwLq6NmdbG/mYDaAmn8wNnKlStXrVql11gaVvM5hGFLvyarVq1avXo18RgKLK1ZO7dU+jRT/DSz+GmmOCZTXCpVdLDke1jzPawEXW2FNkJWHdrGKkWGUpaklCcpZUlKeTKJwqfQ3KiMVhSaM4XmjEj//2sXVJJcecFTecFTef5j2YcHJCqXbtKNZtyFZuRBE3mqR83/p3WMMssUKWLFO7E8qViRXaZowae6CukuhjQXIa0uFxMRQhjhV8Uf7uWmROS+u56VxKcze5k59LN06W3uaMj4eE35UbmPJEmHipOOFJt2Yreabmg3yKBxDooHjR8UWAg6AYAmAs5gIVTnXsgrkxHF1tPM4qjUIiqZ1NFa0M3OsHsLoae1gEapS9WAVYpMhSxRKXuplL1SKbLJNHsq3YVCd6cyWpPImqeOsKIkWZ4XKcuLluc/VYgTaIbt6aZedFMvukl3Eq3m72WoVOCkIvnrInlioTxZLDfnUNwM6W2N6W6GNPVXoX4kPoQTinNv5by9kvn6fm5KeyPLwdYtB1i5uglqOJ1WLwqJKvlkyfNdBZUFyvY/ilwnCmE4PKgvqC0QdAIATQQUWAghRCKRxBtW0Tt1pXfsTObx67jUu4KKxxnFkamF994Vvs0v97QWeNkb9nQw6mIjZNPr9Es4GFcoZUlKWYJC9kIpe0EiG1EZ7agMj2rFFsKKctmHSFnuPVnuPXnBU5phO7qZN92sF92kR41nthBCChV+J1YkFMrj8mQpYrmDgNZWRG9rTLfl1fWLYSuVipvZby5mJl7MSGBT6cNt24y1b99aaFbHxbXJeVDx9Oe8gheVHZcZu30rJH/smykAUIPaAkEnANBEQIGFEEIkEqlkxybZoyhZ7BOqtQ39/7F3ngFRHG8Dn73eDzh676D0DlYQG8beNWqs0RjzGhMTU2yJf2M0GnsvUYO9ixUbCoqK0kF6bwd3XO+3t+8HCCJSDjhAZX+fbmdnnp1ZmfHZmacEhhAHhBJCBmqvbAnl6qdFtbEFtbEF3OQKobspfZA9a5iz4UB7FhGn5XmYBlYVqhWJakUSrMzAYM1xRG8c0QdL9IKgd1QoBJYp2bFKdpyy8oGKl04wGUi0GEm0GIFjOLUkWq5GMrjKVI4ypUYpVyN+JkR/E2JfVju2tV5xyi4VpZ4pSGISyDPtfWY6+HbSVIv9UvZyHVuQpxy4w8zmM90ESm2CSCSi07tEMkpPgeoWoPMvAQFljyRyrtp8AJVi9kHn4eg9Uxgd6ScJqmAB0PgtqNXK9BRlwnNF3CPlq5c4W3viwDBicH9CYD+Ioq01kkwFvyzhx+Rzo7Nr0quEAVZ6Q5wMR7gY+1owtQ5EBauVb2BFilrxGlbmYAmuOFIAjhiAxds3qadR8pQV9xXldxUVdwGGSLQYQbQYSTQfCmFbtA9jS+GEKkVitbJAoHI3JPQ3J/kaE7TUtDQI8qy66ExB0vmiFD+W5ZcuwWOs+rY3cXVjSqPFT76pZHkSB+02p5jqeK3PyclxdnbWrUyUngVVsEDnXoKoRHVzTDEGC+g2hIo4Scgfpn0X6bfdrIfoPVMYHeknCapgAdDSW1CrlSmJithHyudPlalJBE8f4qAhxNBwfB93oLWixJep4gprH+Zy7mRXcyWq4S5Gw5yNRroaGdOaP9d7HwSRwYoUlfylWvEKIGocuR+eGIgj+gCoqUeempemKL+rKL+j5CQQzcJJNhOIVqObRDdtjESFvK5WPC2X5/BUboaEgRYkX2MCXjsnRDmsvlSUeijnea6Qs8ApcKlrP7OOBnqA5UjChuo3x3iD95rbT9RNtAiUTxVUwQKdeAlyLnx5QEHfhfre3xsCAPg5iuvDikI2mzpN13arHgUFRXtQBQsALd4CIpEoXjxVPHmoePxQIxKQhkaQhkUQQwZqv60FACjhye5mV0dn1zzI5fQ1pY/qYzzWzdTdtB2bpbCqSC1/rla8gFWFOKIfntwfRwqGoKZ90Ch5itIb8uIrisoHBOMQsv1MkvWEluziAQBSNZJQpYgtlxcJ1YGmxMGWJBd9beMpvOGz92U9O12QNNnW8wf3UEeGofbDaQz7pezezFLbMfR+f5litHN+ROmFoAoW6MRLuPd5GdkIO2CHWUMJN1V+NbxwygsHhj0aFhgFRcegChYA7XwLcGmx7M4NxaN7ypREYnB/4qAhpKEjsRZW2j9OodY8zufezqq+klZJxGEmephN8DALsNLTPpMNouGr5PEqWRysTMcR/fDkQThSSBNTLQAAopYqym7KCk4pqx4TLUaS7KYTLSMgTIsraa1c87RC/rBEhsFAQ63JAy2INLxWBmRchXRXZuyBrPhQM4dfPMO9DMy1HUkjFHz43swyRIOMOGdFYHb82BHlEwZVsEBHX0LJHfGTZRXTUx1xlHcmdeLmmopY6egbNrrrIAoKCgCoglVHx96CRihQxDxQxD6SP7iDNbckjxxDGjUGZ9+ipXmzvC4TXE6tvJJeKZKrp3qbT/U2D7TSb4+mJVLJYlXyWFj5Bk8KwVPCcURfAJpqRRpFrbz4oqzgtJqfQbKdSnGcizcMaFEmAG+4ygel8qRqRYAp8TNbirV2jocStfJQ9vOt6TH9je3+8IvowG4WAiNxK6rKHohH37Sh23b2k7o3RLTrbaAKFujoSzjnkxf0u4ntmKY72RoVctYzb+BOM6vhtGYb9iC9ZwqjI/0kQRUsADr/FmBYkRAvvx0lvxOFMTIhjxpHHj0ea23bLhmZbNHZpIpLqZVipfpzX8vPfS3c2nN6iGj4Kukjpey+Bq4hkAfjKSOweMdmeiopkeVHSnOPYfAMisuXZPuZEL5FsyexSnO/RB5dJDWj4j6zJ/sYE7VR/KRq1c7M2G3pMQudg9Z4D6Pi2q0npezkpuzgjn9oy7BDjy1Q3gFVsECHXkLpPXHcd1UzUh1Bc3M4O5L/5ihv/CM73fQPBQUFAIAqWHXobNXWaBQvnspvXZfduo6ztiGPnUQaOQZr1r7zsvQqUeTrstOJ5YZUwmx/y2ne5uaMduTy06jLVLKHSsltCGtAoI7Gk8Mg6L3miEZR+UCac0hZ8YDs8DnFdRmO6dKSQBgBzyvlUQVSGAETHCjBZiRt7OCrZKIfE27EVOX/HTh2sq2n9v2vI21vbcoOzqSn9mTjD9qNHKWbQRUs0KGXEBVR5DiV2Wde8y4vGjVyyjl32ClL0xAdZG5AQUGpA1WwAOiKVVutVsTFyKIuyx/cxfdxp0yfTRr+GUTWJrVOPRoEeZzPjXxdfjW90tucuTDYeoKHGUnbkFoAAEStSFJKbqgViXjyYAJ1NBbfzNmlRlYpydonzTmCN/Ci9v2WaDECNPuFCwAAILlGeSVPwpNrxjlQQq3I2gR2iGUXfh1/2YLCPNh/cnvjZiX8Xl10QzThsR2OjCbWQakHVbBA+3MRistU57zy5pa7YkktTtrU3Vz2c9mwU5a66iQKSq8FzUX4Dl23aiMqpfzuTdnFM8rEBNLQkZRpswmBIdpHeQAAKNSaqEz2kefFCaX8yZ7mS/rZ+Fi0w6daA3NU0ttKyS0Ia0ikjseTBzfOfljfSVghLzwrydyBaJQ09x/J9jMBpkUvwhye6ly2hK/QTHeh+pu2fWio0sDb0h9vz3iyNXDMbIf2Hb3fn12GIGBYZAcX/V4VcKWXgCpYoP0vIekvDj9HEXbYopU68lo40iFndqEzUe8D8i/pPVMYHeknCbqDBUC3rNoabo3s6kXJmROIQkGZMJUyfTbWvH16Q4VQfjyh9MCzYjsDypJ+NpM8zQhaZT+sA1HJ45XiKxp1CYE2hUAd9X5wBwCAsvKhOPUPtSif5vETxWl+K2pWco3yTJaYgIXm9qU56LUd0yG1tnLG40g/luX+fpO0t8pSyzSXBxT2XaDvvtRAyyaN6VUhg3sJqIIF2v8SznnnDdhhZhFKbb3a3amlluFUt8UdmWtdRO+ZwuhIP0lQBQuA7l21VZlp0nORsmsXCT7+1LlfEgcNadeGllqDXE2vOhhfnF4pXBBkvSjYxka/HSePsCpfITqjVrwmUCKI9CkQphmbDFXNC1HyerUwh+a5muIwG2Cat4JCEPC4XH42W+xrTJzhQqUT2tD2pGrV188vJ9SUXgmf66S1g6EgT3mpX8G4+7Ysz3YYoqF8qqAKFmjnS+BnK66GF31R4gK19TlWfEv0amPNpKdN00WgoKB0DFTBAqAnVm1ELpdFXZb8cxCRiCmz5lGmz8HQ2xfEPKtafDC+OPJ1WagD66dwJz/Ldp0bshXiiyrpfQIlgkif2iSxdB3K6qfipHWwpITu+z+S7ZSWbLOkauRCjuRphXyWK22QZds60KHs52uT7v47aMYwc213id/8w0vbWzv5uT0agBQFVbBAO19C4haOqEg5eF/brjYaFfKPWda0ZEeapbZxhlFQUFoBVbAA6NFVW5n0SnL8kOLRPVLEWOqcBXi39jnciRXqYy9Ltz3Od2BRV4Y6RLgaa78dpoG5CtFplewhgTKcSJsGYZs5GlBWPhS++gHCkhgBf+ONgloSVSRUH0gVMgiYLz3ohuQ2bDji2IVTY/5d7z38S5dgrTqKgOvDi6xH0urye6D0ZlAFC7TzJVweWOD3i5FNxNtDGalaRcE1r0Ld/6LMNIjSsRN5FBSUJuhkvfoUnLymT58eGxvb/c8l+Pjr7zxk/PAFztq2duHn3OljFbGPgNb/JDQi7v8G2uX9PGRRsPUvt974bX9yMbVSo11zDJZF1vuGbnwUACCqXiAXHkY04qbdMxtiODqB4vwlL2YyP26eRl7drChbBm5jf4O+LMLPcbyYUnnrzx1gYhc76uut6THrku5q008AgcEHzBM3cyQVaq3q/8fr16/bVR8F5RNDXgtz0xSWYfURRAtE3EkPTxieXos9/sPc2LNsmahJffsJjPzLwm7vZov0nimMjhSlJT76b0oIgvbs2bNr1y46nf7tt99OmTKFSNQ2GbMuUatl1y+JD+1GNBra/CXkidMgQju6gSDg5hv2pgd5NWLFr0OdZvlZYrXL3AwA0MAcheikSvaMxJhFoI4BoOkuFKISiVJ+l+WdoHuvp7gsAS0YdJSK1LuSheZU7GJPBqXVE70auXj43UPh5k5bA8Zo08MXa9jCQlWHPQpRPg3QHSzQnpeQc5qfd1446qo1ACCNVxkRfWRZn/7f9B2gQZDfk+9dLUm/P2KxDe2tIaZapvnHNGtOscsH5UuIgvKRgh4RAvDfW9BoNLdv3965c2daWtrixYu/+uorExOTHumP4tkTyaE9qjfptC+/ocz4ol0ppQEATwq4a+9kVwjkP4c7zfa3xGmtZsGqQrlgvwauITOX4EjNHAiq+ZmC50sRtYzZ/zBev/nTTJUGiXwjTq5RfufLtGk1xw5PKRt25+BwC+c//Ea12Te1VBPplDPmNmrt3qtBFSzQnpfwcH65sT/ZfamBRK30urrtN58Rnzv4NtzdlRl3IDv+9dhvydi3J4Y3PivuM0/fYXL7TEJRUFDeB1WwAHjvLWRlZe3cufPcuXMTJ05ctWqVk1P70gvqClVmmnjvdkV8HHX2fOqCrzCMdpixAwCeFHDX382pEMr//KzPeHdT7Ruq5S9lgr1YnDWJuQSDez92DiLN/Uf0+mdqn2U0j59b8jF8ViH/J0M8z43Wz7w1fYirkIbe3jfPKeA7t8Ftdiz5bw77hWzEuXbk1Ub5xEAVLNCel3DSLmfMbRt9V+Ky51ckauU/A6Y1qTDryWkDAmVX8PiGkrQ93Jok+ZCjrQXNQkFB0QbUBqsZXF1d9+/fn5eXZ2VlNWDAgPHjx8fHx3d/N/B9PfT3HjO8dBuuKKsO9Rft2KwR8LVvPsie9fCrkF3j3dfdye6/++njfK6WDXGkQLrxUSzBTVzzjUJ0EiBNLJ8gitN8w7GJyupnnFv91IKsZoX0MyetCdI7my05lSVu5Q+MRaTcHrZoV2bc+cKUNjvmvsSg4omE90ah5UDQw36U3owgX6lRavRdiblCzoXClO2BY9+vsyd4wsXi1OTaioYSm8/oxbdF4MNQYnvPFEZHitISH/03ZStqpkwmO3HixJYtW2xsbFatWjVy5Mhu7lsd6qIC8d7t8vu3qfO/os1fAlHbiBnYGA2CnE2qWHMny9WY9teYvn1NtA3ypoE5cv4uWF1G0f8eS3B77z4izT4kSlpD991IcV7UrASxSvP3ayEZB/2fD4PYcm6d1NrKYXcP3hy2wN+wjd2pl+urZdVqbXzOUT5J0B0soPVLyDzMq4iVDD1p+UXsWWeG4a9eQ5uttj/r2bWSjDvD307hU845Iy9ao2fxKCidBN3BagMymbxkyZKcnJxFixatWrXKz8/v0qVLGo2mm7uBs7XX+2u34ZVodV42e7Cv+Mg+RNGGs14DGAia6WvxZlXYcBejsH3x317N4MtUWjXEGlJYv5MYc6W1v8n4uxGkyRMhistiVsQT6Zs9/NjZiFryvgQaHvNrkB4FD218wZeoWvw78zQwO9R/yqSHJ2rkTd0Ym+Cx1CD3rEBeC2vTfxSU3kx5jMQijFokrr1dlvVN3wEtVVvoHFQg4j6uym8osRxKK3vQxkxEQUHpHj5lBasOHA43c+bM5OTk9evXb9261cPD48yZMz2iZunvPMSKvKJ88bQ6NEB64TSAtVU1CFjM8oH2mT+GylSw6+ZH+58VwRqtNGs8eRDN+BhAZOLqRbAys2mXmK6s0c8hDIFzI1AtePN+cywElnoxHPXwvz/niZQtvrFx1m6zHf1nxJxqPcYE2RhnM4qefYKnTc9RUD5VIAiCIKj1TM+VTyVmA6hHcl7OcvBl4FvcjsJjsKs8hmxOe9RQYhFKLY9p5nsJBQVFG9avX183Q3UjDulpVq5caWdnt27duqVLlzKZzGfPniEIAsPwkCFDQkJCfvrpJzs7u1WrVrXUvL1DuH//fr9+/Tw8PK5cuaLRaDrb+w6hePWCM3U0OzxI9uBue9umVghC9z71+/txYhlf+1ZKWZygcrJceBJB1O/fleYerzpjLCs831Lzs1ni7x9zBQq4pQpqDRx2e/+G5Hutd6Pskfi0e642HRYKhdpUQ/mI+BBWmx5Hm5cgLlcdMcxUqWGLs7+n8ypbr6yE1VbnNiRyyuoupWzVYb1MjbpnVrbG9J4pjI70k0Qn61UPL3kajebHH3/Mycmpuxw/fvwPP/yAIMiFCxesra2VSiWCIGVlZWQyuaCgoFkJHXsLUVFR/v7+ffv2PX36NAy3qDd0KbKH0ezwIM6McaqszHY11GiQEwmlJuvu/hiVKVU2ozA1C6zmiDmrRNXLYHX1+3eV3GT2BVtR8u8tNT+XLV75mCtsWccqlwhMz6yPry5qtevISfvs6kRZm73Nzs5usw7KxwWqYCHavYTcc/yb44qvl2QMuLlHG5l/pj5cEHeu4fK0W071a2nHu6gjes8URkf6SaKT9aqHjwghCNq8ebOTk9OpU6fmzp1bXFy8dOlSAMCjR4+GDh2Kx+MBABYWFp6ennfu3NHhc0ePHp2QkLBz585du3b5+/s/fPhQh8K1hBQ2zPhOHGnkGM6McYL1P2l4tVo2hCAwx98ydeXgMoHM/a+Y21nNh2hvAgbLorI24clh4pqv1fKXTe7iDbwMP3suL40SPF0ANM1EXZ/qTPU1Jvzxki9TN38OaE5hHOg3edbj02JVy66CEHCZrafNKaGzs7bpDlFQPjGqnktNg8nnCpNn2vs0FFZI4PslsuhimVjV9LB+rqP/5aI00X/zziKUWv6o508Je88URkeK0hIfig0Wj8djMpkVFRUpKSkAADabbWZm1nDXxMSkqqqqpbbQuzQYNzT2Kc3JyRGJ3iaXqLs1dOjQZ8+eTZ8+/auvvho6dOjz589FIlFOTk6Taq1IeP93+yTgcNQ5C4zvx9dUVVWHB0si/wEwrKUEYxrxO1fkwGTPby6nzzqV+Cj+lRZ9gIor3CHSzzL+TplgL0DUjYUnZZaxRj6C5dW1D8aIeFXvS5jhSnPUw2+IreQJhM0JB5Y18mBjm3VJ0a30wXkGM+tsrUio6zeJSvjAJDSYMjQAULSj6pnUsB/xdlnWOGt3AIBag+xNEf4Wz8vlq7J5quWPah+UyBrXNyHTB5naXyxKrbs0G0itjJP2QL9RUFDepQccp+/evZuQkFD3+9dff2288u7YsWPLli0VFRUTJ050c3PbsGFDXfn48eN9fHzWrVv3vjSd+FKq1erjx49v2LAhICDgzz//dHR07KTADqB6kyFYvwoRCpm/bSYEhmjfUKqEV9/OOp9ScXCK52d9tIpfj2j40to/AISh6K+BMO+GjUBgQfxSVW2SwdBbGFLTDM0aBGxPFBCw0DJvRrP/YXIVUvcrf90cttCX1WK0wzNuuUOOWZoEkbXpKsonAxqmAWjxEmAlcpT1xjwF+vPNg7jPliEI2PJKgMOAb7wZBCwEAKiUwFtfC4JNiVOc387c6yUZ2zIeP45YCgCQlKvOeuctqO4DUJ0WBaWjfKxhGsrKypL/QyQSHTx4UKlU1t0KCAhgs9lKpdLMzKy6+u3JF5vNNjVtR0Dz9oLD4RYuXJidne3v7x8SEvLtt9+2smHWReD7uBmeu0Fb9h1v+SL+yq81fG297SgE7N/j3E7P8v2/K+mLL6RKlW07J0IYParhn1i8g7jmK4269N17WGa/g0Tzody7YRp5TZOGGAj8nw+DI4NPZzXvCs4iUv7wG/V1/GWk5XCH9hMYBVfayEqLRrRD6Z1wkuV6zsTrlemTbD0BAFEFUjmsWeHLJPwXi86Mil0XrBdbLn9W8Tb2ykhL10w+u0wiAABQLfB4Koafq21Q3y6i90xhdKQoLdJ5M67OoFQqaTTahQsX6i7Xrl3r4+ODIMj58+cdHBwUCgWCIBUVFSQSqSXzOp0Pgc1mf/vttywWa/Xq1SKRSLfCtUEjFvPX/1Tl7yK9dqldDYVy1ZzTiS5/PnxeXKtlE4X4pqByskqe3Iy0xDXVV91haTNOTCIlvPwR51Fp87bqGkQTFLXzRG5CSw+tfiWNdMnRsoconww9vtp8CLT5ElJ3c2KWlFuf25AtqC4XqxdF13CkzTiyFAtUC6NruLK3TicL485vS4+p+x09sw54n08AACAASURBVDTzqLaLAAoKyvvoZL3qYRssPB6/c+fOxYsX//DDD3PmzNm/f//BgwcBABMnTrSxsRk0aNCaNWsGDhy4cOHCbjOvMzY23r59e3JycklJiYuLy7Fjx5DuPdeAqFTmuk0Gx8+LD+6qnTsVrijTsiGdiDsxw2djhOv4Ywl/PMhtPSpVHQTqKIr+z9LaDSrpvabSfH4n203n3h4MSyua3KLhMT8G6J1+Iy4UNGMODwFoZ9D4X17flqqbj4lq5EtWCmBhoVK7YaGg9CLYCTJxgAQDYZwZRuezxaPsKSwy9v1q1gzcCFvy0fS31m/T7LzP/Ze0yqw/pfIpaoaFgtLD9LyR+/z582NiYiwsLEJDQ9PT0wMCAgAAWCw2Ojr6hx9+oNPpe/bs2b17dzf3ytLS8sSJE9evXz9y5EhISMizZ8+6uQN4N0/Da/fwfoE1o8Mk/xzUPirpJE+zVysG3cuuGXrgebmg7ZDxOKIvzehvufC4QnS2yS2a569kp3m10cPePys0p2Lnu9O3JwqkzTkVBhlZBxvb7H3ztPlHQsAynFZ2v+cdnVBQPjSqX8qSrctGWLgUC9VZtaoI2xZNFcc7UMrF6nRu/YdKmJlDkai2VMIHAJj2p1Q9QxUsFJSepvObYD1LVw9Bo9GcPHnSyspqzpw55eXlXfqsZlHl53Cmj63+LFSV/Ub7VmpYsyE6x+K36NgCrjb1YTVHxF4g4+9HkKYhCoWJq2uu+2mUgvdbHUsXbn/dfLzTTF6V8el1AmXzx4hvjvPuTClppT+9KuBKL+ETWG06T+svQcFXH6RnjLxz+HJR2r4UwbU8SevS4ivkP8VyG2bs3Nize988RRBEo9YcYmTIuNoGyesKes8URkf6SaKT9arnd7A+cCAImj17dmZmprm5uaen59q1a6XSbv00xNk7sc5co86ax5k+Rnxwl5ZbWVgMtHqY09Fp3pNPvNoWk9/maSEGy6IablcrM2T8XeBd+3S6zwa8URDv4USgaXrkN6sPrVICPyyVgffoo2cy3MJl75vmd/6shtHKHoqRlvMVNQ7SgYLSS6hJkuv5EJ7WFAYa2idUKcKs2sjZHGRGhCAooarenn2sldv1kgwAAISFTAIp7Oc9uYnVe6YwOlKUlkAVLK2g0WibNm1KTk7Ozc11c3O7evVqN3eAMn2O0fUHiof3ODPHwRXlWrYa4WL0YvnAc8kVM08lStryLoQwdKrhZo26SMbbAsA7ug8zaBeEowrilzRpgsdA/+fDOJ0lqZQ0I/xXr/AdGU+ajTtKNcdRTHCc5GY0szrodHrrvUVB+fTgJMmq+/FdmMZJbOBvQqQTMAAAWFIiiP+KE+XPuRkiTvkfonrrwAsBMMGBciWv/rR9uIXz85pioUoOADAJoVTF96SC1XumMDpSlJZAFax2YGlpeebMmePHj69ZsyY8PPzNm2YSJHcdWEtr1plrpMFDa0aHyS6f07KVjT75ybL+JBym/+64wto2FlwIolBYf2pgroz31zv7WBBWb/BpFS9VnLqpSRMLGm6iI+VgqvD9PTJXpnGYmeORnKZR4+swG0BF7XBReiGtJHvmpMhzHCvCzByelMuHWJEBAMqqR5yoAAzRgBmyj+H3h1qYU3PNQ1Wb1NDE35SohEEqRwkAoOII/Yxt75XnAABMQ8hV8S1+wKCgoDSLbpM9owpWuxk8eHBiYmJERMSgQYPWrVunUHRjvBkMhrb0W9apy6IDO3nfLNCI2ogmVQcJh/lnuvfCIOt+u+Ie5HJarwxBRAprgwZmy/g7G+tYEI5qEH5dmn1AXnKlSZMIW4oGAU2iS9fxg0fozsxYuLmzQNMQcs9+YaOg9Ah1xhktKViv6aU+ei5ipcZFH6/ivubFTNcPPU/33Yg3DCSYhukNPMnw/6v2XoSKWx+RCAJgjD3ldmH97Btp4XqnPBsAYBpMqU6QInBvj+yKgtIu1q9f32CD1XlQBasj4PH4lStXJicnp6WleXt7P3jwoFuf3sfd6PpDjJ5BTcQgZcJzLVstG2B3drbfrFOJxxNKW68JQUQK63+wKl8u2N+4HEM20x9yWfBsiZqf8W59sMiDfi5bwlM0VaT8WJYWFMa1kgzwHqb9WnN0QiPaofQ2YCVSUyhLU1Zo1CYh5iQAS/hPPmcG7yGYDm5cjWQ7mRlygPdwokZeH4q5nzkxj6+qkcEAgAhL1zvlWQhAiPpYihmel9VjwVB6zxRGR4rSEqiC1XEsLCwuX768efPmL7/8ctKkScXFxd32aIhEYm74i/nbZt7X84R/bQDqZuJRvc9gB1bM0n7/u5e7+nZW6wo6BFGorE1qRapceLRxOZ7lxwjYyns4EVEKGpdb0XHh1uSTmc2Ed1/uNnBnZuz75XpORLUUkZQ3HyvLz8+vzeGgoHxK8DIVnCB+Hz2T12x1iBlRnPoH3jCQZDvl/Zok6/Fkh9n82C/qLglYaJAl6UGJHADgxDAkYfFptVUAAGN/cvWrHjsl7D1TGB0pSkugClZnGTt2bEZGhq+vr7+//44dO2CtA1Z1HlL4CKPbsaq0FM7n4+FqtjZNXIxpz5cPiMnnzjmTpIJb9uIDAMLQqIab1fJnCvHFxuVkh9lEi+H8uLlNnA0nOlLy+aqUmqZfzBOsPQpFtSm1TaOVAgiYBJOrnqNmIigoAADATZVX+vL89F2kao0dkSPNPkj33dhSZbr3eo28RpZ/su5yiBU5plRWdx440sLlTnkWAMDYj1TzGp1fKCg9Bqpg6QASifTrr7/Gx8dfv369X79+qamp3fZoDMuQdeICKXRozahBiicPtWliSCXcWxwskKvGHksQK1rb+oIwTArrT6X4kkoW07icHrANllVKMrY3LiRgoQXu9GMZIpXmHcULh8EscQ3Z01zQUZNASvVL1AwLBQUAALjp8gJrthnB3s+YKEndRHaah6VatVgbg2P2Pyx89aNGyQMAWNCwhmRsGkcJABhq7ny/IhcAYOTXkztYKCgoqIKlMxwdHR88ePD111+PGDHip59+ksvbjqKuGyCI9tW3+rsO81d+Ldq9FWha25eqg4zHXp4bYK1HDtsfz5W0ZqWBwRpRWBtl/N2wMvPtAzEE/cHnxOlbGixt6/AyIljRcQ32tg0scg66WJQqUDZ9IUa+pJrE5t8SetiP0tuoTVdkUKokSmYASykrOEXt+y0AAEGkClGkhPODhPuTQvQvonl7NI838CFZjxen1O9yDbYkPS6TAwCGmDk+rymWwSojXzI3Ta5pLtdCN9B7pjA6UpSWQBUsXQJB0Jw5c5KSkvLz8729vR8/ftxtjyb2G2QY9UgR+6h2/nSNUNBmfRwGOjjFM9zJMGx/fKWwNV0Qi7en6P8krV2vgd+eQmJpNsyg3fzHMxH1OxlvZveh3SiQipTvKHlGJFq4udOFopQmko38yNWvZaC59R897EfpbeQX1Wpw2CoxZM87RTQfhqVYwKo8MXu+Rl1OpE0mUsdrYI6IPV8lfxu8l+79myz/BCwuAgD0MyclVyukaoSOJ7rrmz6rLsLTMDQrPO9NN7o5N6L3TGF0pCgtgSpYusfU1PTChQubN2+eM2fOvHnzuFxu9zwXa2JqePoa1t6RMzZc9aYZx733+fOzPjN8zAfueVbAbe2oDkcKINCmS7lrEOStKkaynYI3Cha9/qlxTRMKNtiMeDW/qbQvHP1P5L1qUkgxweHIkKgYzfqM8qGTnZ29ffv2PXv2sNnNGDsKBIL1jTh7tmlazzZRCuBsg6ogQy8Xfbwi5wDFdZlGXSzh/kxiLiXrr8KRgnCkYLLeCipro5y/Sym5WdcKQzahuCwVp2wAAFDxkLsh4WWVAgAwrOGU0JeMmmGhoPQUqILVVYwbNy4jI0NfX9/Dw+PMmTPd9FQcjrn2D/p3v3A/nyC7cl6bFj+HO/0Q5hC671l2dTM+gA0QaROxeGcZb0tj23ZG0E55yTVl1aPGNSc6UR+XybnydzaxIixc84ScPGHTKFxGvuSWTglRUD4QoqOjAwMDi4uL4+Pj/fz88vPzm1SIjY3ds2dP2X904JuKm65g+/LNiDaBhDSAqAjGgdLajSTGfDx5UONqWIIr1fBvhejfBrNImtt38tIotSAbANDfnPS0Qg4ACDdzqlewfFo8hUdBQelqUAWrC6HRaH///ffVq1f//PPPcePGVVVVdc9zyWMnGp65JtqxWbhxrTYmWYtDbP4X4Tpkf3xaZWuRS8l6yzVwtUL8Vm/DEPSY/Q7yny5sfFCoR8QMsSJdzn3n6BCHwUyx9TpXmNxEppEvuSapmS9skUjUZrdRULqH7777bsuWLTt27Dh16tT48eM3bmzq3BcXFzdp0qSJEyeOHDly06ZNX3/9dXsfUZshL7PlIhoDJ9EFssNsuegUBmdOoES8XxODM6ew/pDxd8OqQgAARGBS+3wjSd8CAPAxJuTzVQKlJtjYJkdQU6uQtjS/uoHeM4XRkaK0BKpgdTmBgYEJCQmenp5eXl7//POPrkLEtg7OpY/h9QeqjNTaBTO0Cfg+x99y+zi3EYdeZFS1PIUgPMVgnUJ8Sa14qycRLSIIJgNFib82rjjWgfKiSsGRvROxYqqd1/nC98ywWrBzr6ysbLPPKCjdQE1NTUZGxqhRo+ouR48effPmzSZ1nj59eu7cuZMnT+7du9fV1TU+Pr69T6nNUJTqi9RKQKy4QLCJUEquk5jftFQZi7cnM5dIazcARAUAoLh+LS+5qpFVEbGQjxHxZaWCgMH2M7Z9XFVg6E3ipspbyaredfSeKYyOFKUlUAWrOyAQCBs2bIiOjt63b9+wYcMKCgq64aEYph7r5EWsjR1n7FB1cWGb9ad6m28b23fEoee5HElLdTBYI4r+LzLeHxq4pqGQEfC3rPCcquZtTHkaHhNuRYoqeMcSq7+JLV8pe8N/x4TFwI3UrBGus7Nzmx1GQekG6oyuzMzM6i5NTEyqq6s1724MjxgxIioq6uzZs48ePZo/f/7ixYtbEQi9S13OnLwiLp1kOpj0Cku1hkGcWBEskRIamjT23qr7jacMw+JthNwjOTk5GKIByW6aJGvf69evg8yIL6oUAABPPPNOSSZRH0s0wAnyFO9LqEMkEuXk5DR7Kycnp/GORXslODs7d1JC5/vQPRLqFquPfRTaSGiYBR/1KN6X0JB/sDFAJyAfOR/XENRq9datWw0NDXfu3KnRaLrnoeJ/j1UFuCoSE7SpfPxlifWGewVcSSt15KJzoupliEbVUCLNO1lz3RfRqBtK+Ap4QXQNXw43bvjti6u/J0U3LtGoNQcoGSrJO9VQPkk+rqnaQEpKCgBAra7/205KSsJgMDDc4l9sXRg8Pp/f7N2WXsLyIXfHRsUnRv+fKOVXQcU4DSxss2MauFZQMVGtLEQQRMXPqjprqoEVcrVm7p1qoQJO5JS5XtqMIMitCcU5Z5vvDAoKSkvoZL1Cd7C6FSwW+/3338fHx58/fz4sLCw3N7cbHkqdNY+5eVftgpmyqxfarPxFgNWqMMdhB56XC1q0jSXSpkAYhlx0vKGE7DAbwjOlOYcbSpgETH9z4u2id+w/xlu7N8lLCGEhhj2Bn4s6EqJ8oNR9tVdX1yf+Y7PZxsbGGMzblVMoFB4+fFgmq/9Th2EYgiA8Hq/9I5RCTQGLwySYGPNvY0xoePIQCENvsxWE0ScxZsv5OwBAcEwXvL6HvOgiEQt5GBJes5VeBuY1cnGFVGjkS+Yko3buKCg9AKpg9QCOjo6PHz+eMGFC//79d+zYodHCDr2TkMKGGZ69Ltr+p/CPdW2avS/tb7ukn83wg89bjkEKUfR/VEnvqxVJDUXMoF2i5PUa+Vs/wc/sKPdLZNJGcQ4HmNiVSPhF4trGsvRdCbyspqeEaEQ7lA8EIyOjvn373rp1q+7y5s2b4eHhjSuQSKQVK1ZERUXVXZ4/f37AgAEUCkX7R/DeKKr7CpgKNh5I1UgikTZey4YE6lgEkalksQAAiuvX0qx9AIBAM2ICW4GBoAEmdrHsAkMvEie5B+zce88URkeK0hKogtUzYLHY5cuXP3/+/PLly0OGDCksbNtGqpPgnF0Nr91XprzmfbMQUbTxRbsy1GGcu+moIy9ELeTSgTBMsv6PMt5mRFN/no3TdyfbzRAl/txQx5iC9TAkPCp9u7hjIcxoqz5RpZmNRem7EvnvKVhoRDuUD4etW7euXLlyxYoVX3zxxenTp9euXQsAePLkibu7u0wmIxAIW7duXbJkyapVq7744ov9+/fv3LmzXfJ5b+R8K2wgeEh0GoTFWWFw1lo3xZCYi+XCIwBRk6xGw5ISNS/d15iYyVUqYGSAiV0cu5DlReKk9MAOVu+ZwuhIUVoCVbB6Ent7+5iYmLFjxwYFBR06dAjpYgdDjJ4+699LAANxZ03UCPitV94Y4epjwRx/LEGhbn7HC0f0xZMHy/g7GkroPr8pym6ral40lIyxp9wulDVOTjjO2v36u6eEei5EXnbPBJtGQdGGiIiIFy9eODg4BAYGpqen1xk1m5qaTp48GYvFAgCWLFny6NEjMzOzwMDAzMxMHx+fdsmvyBbjaQYemniMARVPDmsoF8rVZ5LK98QVXk6r5MlUzbbFEX0xOEulJApAWLLjXGnuUQoOstfDp3GUA03sY9mFdGs8LEdkNa1lHf3EkFaqE36rjhpZdCW08MmyCvSEFKWngLr6P/WuBoI++iEAAN68efPFF1+wWKx9+/bZ2dl17cMQRLhxrfzJA9a/l7Empq1U1CDIjMhECIDTs3wxzXpVIEpxzVdE+ud48pC6Aln+SWn2QdaoOADq6//6lDfBkeJvQqy7lKiV5md/L5+2hoavL6l+JYv5snxqoqOuxofyYfJpTNVO0uxL+Hvei/tjwWHFaPqgYLrpKQjDAADsii38/V7OADsDCyaphCd7VlS7KNhmzTBnKgHbpDmsKpRyV9FM/tVIKjk3AoynlN4tRQqFqoXuVNbptSVTV8eMqPL71chqKK2bBtmjZB3nPf2hymka02YUHUfGVD6Tpu+vdZjE6LfFFEvUkWsYSi9AJ+sVuoP1QdCnT59nz56FhoYGBgb+/fffXWuVBUGM1RsoE6ZyJkeoi1oLGIGBoJMzfNgixaobb1oQRSDr/ywT7Ec0vLoCsv0sBJbLiy42VImwIzc2dafiCP6GljFVb2Nh67sS+TnKJhkJGzvZoqB82mRK2H0wXLypFZboXqddLTqfEvm67OXygVfnBeyd6BG1IDDth9AKgdxr6+M37KYZF7B4Oyyhj0pyE0uzxRv4yEuu+ZkQkthKLIQNMLR6yi4y9CJxu/2UsEem8KsN1YmbOROf2A/aY24zim4RRvX/1WhGuqO4RHVzTLFa1iXrau9ZrHrPSHUFqmB9KOBwuFWrVr148eLatWthYWFdHSuL9tW39GXfcad+pkxuzW6RiMNcnhdwI5N94FlxsxWweEcCZYSMv6f+GsLQ/beIEn8FmvojiRAzUoVYXSJ6e0IRYel6uyyr4RJPw+BpGEnlO0cYjQOuoKB8wsBKpECP76J+SbSwxZP6AwC2xuQnlQtilvazZ721lDdnkE7O9Fk3wjls/7OE0qbn+0T6bIX4HEBUZMe5srx/jMhYfRImh6caYGL3rLqoR8ywun8Kp++rzT4lGB9jp9+H2LicqIcdedGKbISLnl7aFTFXe89i1XtGqitQBevDwt7e/tGjR+PGjQsODj548GCXHqlQps1m/rmzdv4MRVxMK9X0yfibC4N+v5dzO6u62Qok+hewqkAlf1p3STQLx1CtpPkn6i6xEBhiRb5X/HYTK8LS9U55dmMJDHuCsPAdj0U6vW03dRSUTwBhvlLUF9dHEw/IShwpILlcuDUm/9r8QMp7R4EAgNl+lkemeo09+rJJViss3hGDt1NK75FsJqg4r2BJWYAp8RVb0d/YLq660NCTxE3tbgWrm6cw+4Xs5W/VY27ZUExw79+FsFD4cQsFX5PwW/OLWGfoPYtV7xmprkAVrA8ODAbz3XffPX78+NixYxEREWVlZV33LNKQ4QYHT/L+70v5nahWqtmzKJe+8J97Jrn5RDoQnqz3rZy/G0HqQ7czfDeKk39H4HrT9aE25KcVctl/8Rrc9EwVsLpA9DYhLsOOICxAQ2Gh9EZ42Qq1MdmOmIXBsTSQ8YLzyVtG97VgklqqP7qvyY7x7mOOvmSL3nENIdJmKsRnISyRZDtFlv+vvwnxZZUi2Ng6kVtO64Pn5yo1qk/WAA6WI/dmlYYeNGfYE1qqg8FDIy9YZR6prYqXtlQHBUW3oArWB0qfPn2ePn06YMAAPz+/EydOdN2DCAHBrH8vCtatkvx7rJVqIbb6eya6jzn6slrcjMcfjuiFI/orhP/UXeKNgnH6HrLco3WX+kSMG4vwvPJtw1Azh4eVeQ2XDHt8kx0sFJReQn4ezwWnJBgZ4CkDTieWM4i4Of6WrTeZ5m0+P9B68olXKvjtiReO6AlhmCpZHNlxjiz/X1sGDkaASIF3pLNSJRV0azz/0/XVTdrKMfQi2Y9ntF6NbIwbuMv84YJyWPHJ6pooHxSogvXhgsPhVq9eHR0dvXPnzlGjRpWXl3fRg/BunoYXb0sO7xEf2t1KtSle5jN9LSYdf9Vs4AYS80ulLAZW1p/90X1+F6f+gcD1BxNhVqTGAbHCTB0fNVaw7AjCwne80NGIdii9hLTKSh9MGc7IBEsI2Pww75ehTtq0WjPMWY+M/+VWVuNCIm2qQnyBYBQCEFjFfe1tREiuUfQ3sXtaXcjyIHHTulXB6rYpLK1Up+zg9N+mlXmQwySGnjMxZTun7apa03sWq94zUl2BKlgfOl5eXi9fvgwJCfH19Y2MjOyip2CtbAwv3ZFePCP887dWqm0Y6WpMI351KfX9WxCGQWYslvG3AkQNAMCzfPGG/g3Jc7yMiDUyuFwM110ONXd6UJmH/Oc6+P4RIRrRDuVTpXGOZwBAhpzjBFKxJOR2niGFgB3mbKSdEHBihs+FlIo7jSwj8eT+iEYAK9PJ9jNl+f/6GBOSq5X9jW2fVRezPIjctG41w+q2Kfx6U43rXH26jba5iQb8bZq0jSOp0FlgsN6zWPWGkTYkftaJNFTB+gjA4XBr1qy5c+fOli1bpk2bxue3ESO0Y2CMjA3PXFPE3Bf+sa6lOhAETs70SakQbo3Jf/8unjIUwrIUkqt1lzTvdZL0v+ossbAQGGBBii2vX+JtaPoUHD6LX/9/w/tG7igouiU7O/vHH38MCAgwNTU1NzcPCgpavXp1VlZW2y11TV0W2AYFq5Sp6ktNw2KtDr+o+GZAO2LgGVDwJ2f6LDiXUiNumDsYInW8QnyF7DBLVnjWwwCTy1f5sWzi2IUGHqRuVrC6B3GZKuc03/dHQ+2bMOwJfefrv9qge2t3lE+A9evXNyR77jyogvXR4OPj8/LlS1NTUy8vr+jo6K54BIZlxDp7XREfK/j9l5bqUAnYq/MC/n5c8DCvmW12MvMbheg0AnMBAHgDH5y+h+w/d8LBlqTHZW+jug82dXjCrg9FQbPEyWrUqGEESlfA5XJnz549ePBggUDw1VdfHT9+/MiRI4sWLaqoqAgLC5s9e3ZNTU1P9U3Bg5XmsAFDUqPp/6yodrJn+9zgB9mz5vhbLr6Y0lCCp45UKxIhCgNHdwTsaEc9vFBOxUEYqbOs+x0Ju4GU7VzXL/TJxs14DraCz49GeRcFoiL0ow6la0EVrI8JEom0c+fOo0ePfvnll0uXLhWLm4Yc7DwYPX3WqSvKhOeC334GLWjxVnrkyM99Zp1KqhA2XbIxOAsCZYRcdLzukubxszhtM0BgAIAlDcckYjJr6xe1gSZ2sez6DIwQFqJZ4EXFb9c79LAfRVeMHTt29OjR5eXlBw8enD9//siRI0eNGrVw4cJjx44VFxePGDFizJgxPdU3fq7SllWFMTA5k+Ewxcu82dAMrbN+hEs+Rxr5ut7XGIIoeMpQpeQ62WG2LP9fLyNCSo0y2NgmlVgh58EKPqzrEbRIN0xhpQDOOs7z+pbV3oYkFtZ9icGrP3SjWPeexar3jFRXfBAKVkVFxb59+7Zt25aUlNRQqFarz58//+eff969e7cH+/YBMnTo0JSUFLlc7u3t/fjxY53LxzCYrNNXVcmv+b98B1qIKT/E0XDZANsZ/yaqNU2VMCJjtlr+AlblAAAIJgOwZFN58ZW6WwMtSE/L6y1tB5nYP24Uz51hRxAVvbVz7w2H/Sjdw8OHD6dNm1aXNLAJBAJh1qxZMTEx3d6pevJzue7YCjyNcCEdnuXXhvNgsxBxmH+me6+Mymxw7yVSxyslt4i24xXld330ZMk1yn7GNvE1RQZupNqM7rNz74YpnHmEZx1Bp1lpa33VGK9vDQsuCSXlzWd4bBe9Z7HqPSPVFT2vYL148cLNzS01NbW6unrIkCGnT58GAGg0mhEjRuzYsaNuV/+nn37q6W5+WDCZzGPHju3YsWPWrFnLli2TSCS6lY+hM1iRV+CCPP7KrwHc/FfvT0McqQTsTzebZtGBIAqRPkcuOFh3SXX/UZy+ue53P3NSAluh0iAAAEeGoQZBisX1OXZoVnhxmQ4WOxSUJhCJRADAwoULGxdyudwhQ+oTaJJILQad6mpSS6v8qNklAstKoaqfrX7HhPhaMr/wt/r2an0OdQzOAktwheFEgmkYqzZKgwBXul18dTHLjVib/gmdEiIg4xDPY5lBx1qTWFiXOXrJ27ltV0VB6Sg9r2AtW7Zs7dq1Bw4c2Lx58+HDhxMTEwEAly9fzsvLe/z48aZNm2JjY3ft2lVYWNjTPf3gGD16dHp6ulgs9vb2jouL061wiEo1OHEBrmbzV/1fs/tYGAiK/Nz3SlrlpdTKJrcI1FGIRqCSPwMAkKzHIrBcUXEfAKBPxFjSsGmchlNC+7dmWFZ4cSmqYKHomMLC1lK7UwAAIABJREFUwtWrV69evfr8+fOrG7FixYrG++U9RYZcYE0tvl3sN6avSfP51LVj3XDnFyW8u9n1Z15E2gSl+ArZfrqs4IynIUGjZmUJqsmeWG76pxMKq/yxBEuETIMpbVdtAe/vDbP+4SmFXZn4FaV308MKVk1NzevXr+fMmXPr1q3IyMigoKCtW7cCAB49ejR06FA8Hg8AsLCw8PT0vHPnTs929cOEyWQeP35827Zt06ZNW758uW6tsiASyeDwKXVJEf/nFc3qWAYU/Pk5/ksvpRXWNgmOjCExFssFhwGAAYBo7j+K0zbV3ehnTnpWUb/K9zexjfvPDItqgRM32q4XiZoLGY+C0k5sbGx4PF5eXp5arc77j/z8fAwGU7dZ3rNUESRMuupmge04d9POyKEQsHsneiy9lCpTwQAAHNEfAA3WxE7FSfBl8DO4Kg99s3IHbnc6Enb1FM48zOu7qIN7fnXQLPFWw2hZJ3id7EnvWax6z0h1RQ8rWIWFhSQSadq0aXv27Dl16lTfvn3r/OPYbHbjvJImJiZVVVUtCYHepcH/ubFFXk5OTuM/jsa3Gv8WiUSNE4Z/LBLGjh0bGRkpFAq9vLxiY2N12AeITGb9c56fmsRfvbLO5r2JBMDO+ync8fNTiSpY01iCTOUqV1CUktsAALLddBknQ1WbBAAIMiW+qpLVCoQAgH7Gts+qi+pa1e1gNUiorKz8SP8tUAl1PxrCyTQAegIMBrN3796zZ8/+9ttvZ//jzJkzx48fj4iI6JEuNYauVyqhGCdVYsOd2hFooFlGuhoHWOltelAfv5dAHa+S3SBajnKSXH9Tqwo2sn1jUNWdR4SVlU03tnWIUqgpviVy/lyvk3I8lrHS9taCzrkvd+lIPyh6z0h1BdSl6YSb5e7duwkJCXW/Q0NDBw4cuH///iVLlgAAtm3bdujQoezs7IkTJ7q5uW3YsKGu2vjx4318fNatayY+EwT1wBA+WG7cuLF48eJp06b973//o1A6vnneBEQm486ZhO/rwfxtczN3ETDm6EsPM/qmz/o0LodVOVLuGprJSQgiilM3waJcZv9jAIDfnvNG21H8TIhqjYZ1em3R1F/1CWRumjx6ZtmMNEdd9RnlQ6PHp2pZWVlBQYGm0V5saGhoN/eh8UuQ18I77q2yNRUeeTPv/pKQzguvEMq9tz2OWzbA2YiKIApR1QwCPFmSdnAH86oJs+pB1YsxM4OnJztSzNoX1OAD5M0/vKIoUcRl686LOueT1+8vU6uhtM6LQvmU0Ml61QM7WGVlZcn/YWhoCAAIDw+vuzVs2LDc3FwYhs3MzKqr3waCY7PZpqad2kLvJYwePbrOXcDLy0uHVlkQmWxw7KwyMUH4v9XN3IXA8Rneka/LmkTGwuKdsQQ3peQqAIDivEhefFUjrwEABJmSnlcpAAA4DMbf0PJFTTEAgGaJl6BG7ihdxrZt22xtbceNGze5ET3bJU6uzEuvJKbYsfPbV3WYM0g/DXFafjUdAABBRAJlGKCL1YLMACYHpzF+Vl3Ecu/ueO5dRE4k32VWZ7ev6nD70iDzcGdPCVFQmqUHFKwFCxZc/A9nZ2cLC4uGsJkvX750cnLCYrGhoaEPHjxQKpUAgMrKyuTk5LCwsO7v6scIi8WKjIyss8pauXKlXK6b9RRDZ7BOXVE8ixXt3vr+XUMq4Z/p3nPPJHMl78TuIzHmK0TnEI0YQzIk2UyU5hwBAASZEhPZShgBoP6UsBgAQNTHatSISoQanKJ0Cbt3746NjeXxeJxG9GyXkvMq7ag1ceU24U5apcfRhm8G2JbyZVfTqwAABOo4pfQuyXqsl+xaAR/CY7AKX0VtxkevYEnKVZwUuc1ndJ1Ic57JLL0nltXoLHMOCkoDPWyDhcFgDhw4sGbNmuXLl69YsWLlypXbtm0DAEycONHGxmbQoEFr1qwZOHDgwoULnZ2de7arHxdjx45NSUkpLS318fHR1VYWhsFknbggu3xOfGDn+3eHOhtN9zGfeza58a4qBmeJJwUrxBcBAJQ+30iz9gKNSp+EMadhMzhKUKdgsYvqKlMt3kZqQCPaoegWBoMREqKDY7jO02AqmsypVWM0FWKynyVTV8LxWMzuCe7fXcuQqWAMzhxLcCLYuFPZF2vlmmAj52KXmm4LhdV1Uzj3nMBuHANL1I1VH4GJtR/PyD7Z8fxjvWex6g0j1W0uwvrEWB8vn8AQupTLly9bWFisWLFCKpXqRKC6soI92E90aPf7t5RqOHhn7I4n+Y0LYXWloGKCBuYhCMK5NUBWdAlBkGv5ksNpQgRBuHKJXuRqWKNBEOTa0MKSaJFOOonyAdKzU3Xu3LnXr1/vwQ7U0fglLN129eTdeaMOxej8KdNOvlp3JwtBEKXsmaj666qzJofjk1Y9T1xw5cKF4Pw2m3/gnPfPK72vy4WiPEZ82i1HhwJRPgF0sl51dgcrLS3t33//3b1795kzZzIyMjqt76HomAkTJqSmplZWVvr6+sbHx3deINbUjHU2SnLiiPTcv01u4bGY07N8N97PTasUNhRisKZ4SrhCdBoAQHFZKs3eDwAINCEmVCkQBBgQKfpEcp6IAwCgWqKxRlG6itLS0rFjx9ra2vo3ome7pMd487LGup9d+/IPasPWsW77nhXlciR4UjAC80iOowLUUXjEJBUqr82Qd9JprmcR5CnFZSqLUKoOZZoPoqplSE2iTIcyUVAAAB10J1Gr1UeOHNm6dWtFRYWTkxOdTufxeAUFBVZWVitXrpw3b15dCCuUDwEDA4MzZ85cvHhxypQpY8aM2bJlC53eKfMFrKkZK/Iyd+pnGKYeaeQ7edzsDCibRvWZezY5/v8GELD16juJ/rmIPY9Am0KynSRMWKEW5poynOgETJ5A5aSHDzC0esUpc2YY0SxxqJ07Shcxa9asWbNm9XQv3qGPUd6unKDNQR2MRd4KlkzSL+FOSy+l3VscTKCOVpu9Nnl5uYr2VaawGjJERCUqus3Huj7nXxbaT2RAWJ1G/YCA6xy9rBN8I1+yLsWi9Ho6soOVnZ09aNCgV69eHTp0SCQSpaSkxMXFZWRk8Pn8gwcPPnnypH///jrvKEonmTx5ckZGhlqt9vLyavAq6DA4W3uD4+f5v3yveNo0GeKCIGtLJvm3u2/DJkEYPQJ1lEJ0FsIQyA5zZDlHAAB+JoREthIA4MeyfMUpBQBQzfCSynpT08ZRl1BQOk9cXByLxZo2bdrcRvRgfxR82IbBzuAYBljpxhuuCd8MsONKlGeSygnUCBjKw2i4tiDXU8+ZHyLqHjv3LprChVeF9uMZOhfrPEsv96xAo+7I5l7vWax6z0h1RUcUrJKSksjIyCNHjgwZMqRxClUikRgWFhYZGXnq1Cnd9RBFZzCZzMOHDx84cGDJkiULFy4UCoVtt2kZfF8PgwMneN8sUiY3tXw8PNXz2MuS58VvnZ+JtKkq2UMNXENxXiTNPwk0Kl9j4qtqBQAgwNAqgVMKAKCY4aRV9QpW4zCzKCidx8TEZM2aNUZGRhMmTDh+/HiPuxAWvuFzFFQnFkwjdklUKiwGOjjFc+X1TIGCiiMFE/sMHqyJcqX1LXXndk/CnK6YwrJqNS9LYT5Yl+eDdTAdCAw7fNmDjiR17T2LVe8Zqa7oiII1bNgwe3v7Vio4OTl1tD8oXc7w4cNTUlJwOJyHh0dUVFRnRBECQ/S27qldOFOdm9243JhG3DPRY97Z5LrEHQAACMMkUCKU4vM4hhOO6SIvjXLWwwsUmhoZ7GdomVJbASMaihmuYQerk4eYKChN2LhxY3JycnZ29qhRo65evWpnZzdo0KAe7M/LoqpMkXGITZdsX9URYKU3uq/JurvZROpYiKmwEV0hQ6Z5puzuiefeFVO4MEpkPZyGJXRJVgCnGXq5ZzriS9h7FqveM1Jd0XEj92PHjg14l0GDBkVERCxfvjw/P1+HXUTROXQ6/cCBAydOnPj++++nTZvGZrM7LIo0ZDhz9f+4X0yBq97JojDJ08zbgrnu7lvFi0ifopTeRzR8itMCae5RCAJehoSkaiUDTzIh07MFNVTTtztYKCg6h8/nv379OjMzs7CwEIZhHK4nA5oXCXNSeJYBtnZd+pRNn/W5kFKZWmOBwRuSmRiqOD+TUPPxxhotviGyHdNV/8c7TWMWXhfB8o/ZBaA91GYq4n9mXw0r/NchJ9Ip59rQooTfq3lvPp104B8CHVewQkJCqqqqjI2N66wZLCws8vPzhw8fzuFwUBusj4LQ0NDU1FQHBwdPT88TJ050WA55/BTqvMXcOZM0/HcCIu+e4B75uvxlSf1HIYTRx5PDFOJLJNvJqpoXsKTM14T4mq0AAPiyLJK45RQzvLRK9VG7OKF8sPj7+5ubm2/evJlCofz999+1tbUPHz7swf4YUJOTq439rHQWYrT5p1DwGyNcl1xMxZLH4+1dwpAoEt6oiM3vmLFRzwIrkfIYifWIrlKwKKY4I19y8e1PP5+xqER1d2rptaGFEAb4rzEeG207+patz0pDlUhzdUjhzbHFqJqlKzquYOXm5rq7u1++fHnhwoULFy48d+5cUFCQk5PTqVOnuj/DF0rHIJFIf/zxR3R09K5du0aOHFlUVNQxObRFX5NCh9XOm4ZIpQ2FhlTCjnFu888lK9T18dmJ9OlKyQ0AwSS7abL8E95GhGyeSq5GfAwskmrLsUQIR8Yo+DDoHRHtULoTe3t7Go2mUCjUajUMw40zEvYIRoySchGjr0mXp8CbG2BFI+COJtlDRNhNc8ON0ZftWyvIVbbdsnPofApXxkn1XIkkQ2zbVTuK03Rm7llBe1t9XItVzin+eb88lidpdp5z8EYTyyFUpgNBz4lgPZLW7y/TOUUulkNoV0ILE7dw3v/W/bhG+iHQcQUrOzvbzc2tcYmTk1NdKCxXV9fO9gulG/Hy8nrx4kVYWFhAQMD27dthGO6AEMbP63FOrrWLZyOqt2v3VG9zFyPahnv1vicYrDGOFKiURFGc5ktzjpJxwEEPn85V+rAskrjlAACKab0Zlp+fny5GhoJSz/nz56uqqg4ePKivr79161ZLS8ue/Q6UIJCjngT/XygTGIZv3LgxefJkMplMIpFGjx69ffv258+fd2wyNgaCwN5JHr/fz68BEyhWeq7qmnLv2m44JdT5FC6+JbId1bX6qP1ERmm0WCVpn/L9ES1WL9dXv1xXPSHG3n+1EY7SzP/+WCLk9S1rSoJD0XXhrQklTXKXfUQj/UDouIIVGBh4+PDhhtiV8fHxx44dCwwMrKysvHbtmo66h9JN4HC4VatWxcfH37hxIyQkJCUlpd0iIEhv03aIQuV/9xVotD2wd5LH0RclL0rqTw+JtOkKyRW8gQeGwFBWPfEzJrxm1ytYCECoZqgZFkpXgcFgiEQikUjEYDBqtVpn2TDaj0oKF0uZPub1RmCvXr3y8vLauHHjyJEjKysrq6urZ82alZ+fv2TJElNT03nz5kVHR3dG03I1pn3d3+6bWw54Y70A9fUiG3H3OBLqlpI7IusIrc4H84ScY7kvV726ueTZpTWJd07mvSqRaGW9TjLAmvanFF3/FE8JEfBkWUXxTdGkeHsDN2LrdenW+HEP7SgmuKtDCuuOFFA6RscVrMGDBy9fvnzw4MEMBoNOp4eHh69YsSIsLGz69OnoDtZHiqOj44MHD3744YeRI0cuX75cImmn0zIWq7/rEFxVKfxjXUOZKZ24e6LHF2eS5WoNAACLt8PinZTSaLLDbFn+SR9jYkqNwphEo+AIxWIexQwvrURjjaLonjlz5pibmw8YMODFixezZ88uLi5+9OhRT3UmK4uXJTDpZ28NAIiLi/vss89Wr14dHx+/cOFCPT09BoMxffr0PXv2JCcnJyYm+vj4rF271sLCYvny5QkJCR174s/hjqV8+Hr+0CC9pxI6uTpD2nabDwlxmUpWDbceCFSDIGcKkvyv7xh8e19MZb4+gextYI7HYG+VZQVc3zHo1t6o0sw2H+Q0jZl7rt2nhB8+L9ayq1/Jxj+0Ixtp5duBJUChB83NBlCiRhQ12cdCaQedTLXD5XLv3Lnz4MEDDodTV6JQKDqdwKcddH4IKO9TWVk5ZcoUJyene/futbctzOexh4WIDu9tXDjlxKtfbr6p+61SpAqr/p+98w5o6uoC+H3ZmxAg7L1kCII4UMSFA8VVt7Zq3a27butua6vWRd3V1mpduHCB4lacgAjI3iMkQPZe773vD/zQKipCILHN76/k5Y5zk9z7zjv33HO+hJXVvBMsRKeYd5tfIdXF3Dh8oTwreTH3+dY6FEVTU1MNMhAzpoNxp+r8+fNv3Lih1WqNKAP6/0TokQMmBP58OK2CX15ebmdn15RZVlhYuHHjRi8vr6CgoB07dvB4vE/t+nGZ0H5dQvHLgUvO7dkQmdws8T8Bw07hnD+E18dXfKiAiBd+Jbbr5dhrVXn1uU3fRAfDcaUvguO3hV+JzRRWf6AdjQQ+aJGjEeubLpvpL1Z5R0V/e+er6j5hUK9A0DuzOPF9S/UaBP0cRtpy1q1bZyjtCEXRljZx5cqV77//PjEx8caNG3V1dS0X6FMxK1itx9WrV93d3ceMGcPhcD6por6aw+saoLx4ruEKV6pmr73+vEpc/1ZWO0+rvCdIilYWHz+UJb1crFiVmrA+/frzrXXJi7mGHIMZk8FYU3Xv3r16/XtvLTqdbvfu3W0mTP2XcOj0NvLycwqNfsyYMRs2bGh6dQRBbt++/fXXX1taWo4cOTI+Pv6TVMYFF16OPrDzQdKwMUPP6JTwJ0tvPK6Pq8j9U/i+T+PLX7JPrNuX+whB31at3gRGkEP5T9kn1v2ccetdJayBhBHluUdELRLXlOBnqg7b5AqyVM2rjuiRhOHlt6dXGVYq08cg61WLkj2PGjXq22+/vXjx4osXLy5evNi9e3eVypwv89/DoEGDsrOzfX19O3TosH//fhRt6tFurL0D6884yfoV2icP66/Y0Yk/D24360wmjKAAACJ9rEZ+iuw1SVX0Z7ANIYOvDWY5ZAq5Zh8sMwZHKpWGhoZu3769qqrqzetlZWXbtm1r3769SCR6X91WQgWq2SRl2tNHz549W7p0adMrQhDUu3fvP/74o6ysbNCgQdu2bXN1dV28eHETj3dtGtTuBd+9SG8hjdCI8lr9IKGhQBFQeVPu3K9xD/fDBc/mPD5/td+02e3CIfAhvzoMBE3z6Zw6dGEiJ2/4rT9lusYd0TxHMYrP/kt2CWENemNiVfdf7ViBpOa1AGGhqL+dalNUWbsFhpXtv0DzFazExMSysrKCgoKJEycCAGJjY93d3S9cuGA42cwYHzKZvHHjxrt37x47dqxnz555eXlNrIhv52+5+5BwzlR9SWH9la87uTBIuF0PSgEAeFI3FFHi7Lx0wgw/YlWhSOfHtM8QVlPscGYfLDOGZfny5XFxcRkZGR4eHo6Ojp06dQoNDbWzs/Pz80tLS7tw4cLq1avbWCQZAnswZL/++uv3339PJjcnwTCDwZg6der9+/dv375No9HGjRvn7++/adOm8vLyD9SiELDHvuy+7NGgCPd0Uc5nE26U/0JFYeOojo0kqP6rKPWHjBt3o78Js3ZuYmvOVObNAbMcKBaRCXuqlY2kC3OLYVTfV2il/wbHo6draizbEX0ntShhAJ6KiT7vkvpjHe/xZ+a6Z3Sar2BlZ2fHxMQQia/OI0AQ1L1797eeEc38O/D393/w4MGYMWMiIyPXrFnTRDslsVskY9UGweQxcG0NAACCwP5RQZtuFZYKlQBARNoonfIi2X0sUnbMlYGD9RY8lQy21itr9AAAmezfeJDHjJHw9fX966+/BALB4cOHZ86cOWfOnKNHj/L5/BMnThjlRE6Nmmyt4z969GjChAktbKpdu3YbNmwoLCz8448/qqurO3fuHBkZefDgwfeZ5bq4WM0OFsWXeOfkt242RgNO4apbCsc+jZivrnPyV6YlJA2Y6cWw/qQG8Rjs/m4jx7h3iEjYXSoTvvUpgYFxiKSWXWlqqlaTXaxqnqry/xb33OvQ8qYYHoTevzteH1+hlZgPFX4CzVewPDw8bt682XB4GEXRmzdvenl5GUgwM6YFBoOZO3fuixcvioqKAgMDr1692pRalJHjqOMmCaeMQeUyAICXNXVBD/c557IAAARKf70uj+Q5WFV8rL01Ppuv82falpKE9QoWl8v9SNNmzHwKx44dw2AwAwcOnDFjxrRp0/r370+lGj5ncJNAQZmCKUh7PmnSJAqFYqhWu3btunv37qqqqmXLlt2+fdvNzS0qKmrPnj0cDuetkuuGfckgag5hnhmq60Yx4BSuui136vv2j1UiE0x+cOpM70k+jGZGw18Z1GdJYK8+1/aXy99WRj1HMorPNVXBMs3FCtGht6dWRcY6GCo0q9sQumUP9N63pjhYk6X5CtaQIUPUanVISMjly5dv3LgREREhlUqHDBliQOHMmBoODg4nT548cODAd999N3z48KYYLGlzFhHCughnvgpAuryPV7lIdT6LCyACgTIYxuVDWFII9kUmXxvMcshFarQSBNGhPj4+rT8aM/8hduzYYWtrO2nSpBs3bhg3jDuXIy0Q2xQ+S588ebLBG8fj8TExMadOneLxePPmzUtJSQkODg4PD9+yZUtRUVF9GSyetjzwyTM97n5JK3rVGGoKw1qU90jp2PMfCpYWgcfcObY6OKo7260ljX/brtviwJ59r+1/a6/QbQij6pZCr2rS/8Q0F6uMXQK6O8FzFMOAbQ466FuXrmpGsPv/LM1XsPB4/P379ydOnMhmsykUysCBA5OTk/H4RrbJzfzLiIqKysrK6tixY2ho6I4dO/T6j7ilW6z/BaLRJSsXAQAIWMz+UUHzzr+UqHVE2nCd6g7Zc4R13Zk6FezLcH4p5pJYWDXfbIU2Y2CeP3+ekpLi7Ow8c+ZMZ2fnpUuXZmZmGkWSF/mpxWUqBIbbt2/fer2QyeRhw4YdOXKEy+Vu3LixrKysZ8+ePj4+ixcvvnv3rpQcs69fwoRjKTUyU484WvNUyfQhEi3/YYZZ/TzRhcac62eApLdz/brP8O06MOl3ifa1UxrJCsvuSKpMkre8faOg5Oqfb67rsdPesM3iyJh+x5ySF3IVHLOnbJOAmn40zDSBoM9+CJ8vBQUF8+bNq66u3rt3b48ePT5QElWp+GNjSFED6fOXAgCmx2VQCdhdwwNV4p1AD6Q3f/7bM4dBlR0ru/rtigFRx5ysg5t55sWMyWIiUxVF0du3by9evDgjIyM4OHjmzJkzZsxosydDCIL2ndmx6o/nIx2Jv//+e9t0Wg+KohkZGRcvXkxISMjNy+sShAFe/SRuox+uHtmQsccESdlYq1cg4ZvtGq7c5RV/df/Ei2GLrYgG22Bd8DQ+S8S71n8GAfNKk8vaLahNVfU94mSoLtqSOzM4JCtc+C+2rdF46g+13EfKIQluHzyy+dljkPWqOfNq06ZNtPewadOmFgpk5jPCx8fn+vXr69evnzBhwsyZMwWC9+44QGSy1eGTytN/q86fBgBsifE/k8FNrRQTaaN0umQc3a0r9pFSY/FSxKPY4lQ1enNWUTMGRy6XnzhxYujQoYMGDaJSqfv379+0adOJEydGjRrVlmLUaUSgNG3gwIFt2SkAAIKgDh06rFu37unTp2Wlpa5hXW3kyVk7v7Vxdp87d+7p06ff9dZqCYaawpy7Coder/cHpTr11w9OH+w22oDaFQBgR+dhFnjSrEdnG664D2eUXZUh+o/fYk1tsRJkqcsuyzqu/DTH/6ZQP9LQlTZqAZxzuK2Dm3yONEfBmjRp0s2bN69cucJms9esWXP//v3Hjx//9NNPdnZ29SEbzPynGDlyZHZ2NolECggI2L9///uSpmFs2FZH4iQ/rtE8us+i4H8Z7Df7bCaKccQSfAm+Ee7Ss4UihIjFKZzVylq9OauoGcMybtw4W1vbtWvXduzYMScn5+HDh7NmzRo0aNDevXtv3brVlpIINDpZWXFUVFRbdvoWLBYLCf1m+0LL8twVNuPWcTGWJ0+eDAkJ8fX1rVe2Wu64bZApDKvR2lSVQ8RrBWvN82t9HbyinQx89hMDQcd7Tnwp4m3OepVAieaEZ7gTqu9/PDCBqS1Wj5fXdPzehmBhGN/2N6kfKQYH9Tnk+OT7GlXtvzNmYflV2ZlOxQZpqjkKlpOTU9euXauqqqKjo5cvXx4aGtq+ffsFCxYMHjw4MTHRIGKZ+bxgMBixsbFJSUlxcXFhYWEPHz5stBjO29dy7x+i+TP0JYVfdXSiEnD7H5cTaSMhugBbfRlCVEFMz2pnoarm3zlvzRgRCwuL69evFxUVrV+/3tPTs+G6q6vrgwcP2lKSglI5g8W0sLBoy07fxY3IzuXYE/W3rq3s+9gqctYvB2tqak6fPu3u7n7y5MmgoCBvb+8vv/wyNjY2JSVFqzVOVFLeEyUrgISnv7pPpQs4caUZW8JiWqMvCg4f33fK7tzkixXZ9Vc8RjBKLjT1LKGJwLmjEBdoAmaxWrUXqyBSu8nM5O94rdpL2yMt0V4aUPZwKa/j9808mvoWzd96r62txWD+UV2pVGo0pu4yaab1CAoKun379saNGydOnDhp0qSampp3yxC7RjCWrRVMHoMK6w6ODtqQlM9T+wEIR3Dt2Bd3x43iVWkl+rc+GJkxIgcOHIiIiHj3uoWFRUhISFtKUlwgpDFp69evb8tO3yXax/ku9IW2RuWAO3NuctiUky9SqyQdOnRYvHhxfHx8bW1tfHx83759c3Jypk+fbmlpGRERsWTJkpMnTxYUFLSZLx3nrsKp92vz1YKn8T+GRrMMujn4Jo4Uiwt9psx8eCZDWA0A8BjBKL0oBcb3G/wEHq+q6fKjLZbQ6u5RndezuQ+VlTc+13OcRC66AAAgAElEQVQA75JzWHS2a0ku+uirXD/PEYZ5/mm+G1dhYWHHjh1Xr17du3dvGIYTEhJ+++23rKwsJ6c29Qo0Ec9ZM2+iVCq3bNmyb9++VatWzZkzB4d7O3+7dOsP2icPrU7Eb7hbnsmVnhpdoxGc4WbL9lK3lxXfn3e/r/NKhWkefjbTbMxTFQAAQRA1LOrb6E5bNhrZXRXWI5FxSScw0y0jO9LYsQkFpBlxGddmdg12aORgv1KpfPr06ZMnT9LS0tLS0oRCYWhoaGhoaEhISMeOHb29vd+d4wUFBS2fwvF9SkOX27gMoAEALpS/3PAiKW3oQiz0XrsAioJCsS6Try2V6HkKWKSBFToUAEAnYJhEjB0V60jFejDx/iw8nfDeRuJKM1akXX0Ws8CaRD3hVxh11Ind6UPR9g0yUoNQcU3+cClvXIbX+7+hFvHWSMsTZMkLueOyvLHEz9vdHVajd2ZxBBnq/qecLdu9jp3e8vWqRU3cunVr5cqVaWlpEAR16dJl+/btXbp0aaFAn4p51TZZcnJy5s2bJxQKd+/e3b37Pw9Uo6ho/nQAAHXHweBt97fEePdkzVM+erSR+vA+P/6XE6N7nmbR6XTjyG2mdTBPVQAABEEYe697Z45EdDdAiIEWErH9zELnO/3aK/Bsdwpr/blM7tzzWe/Tsd5EIBCkpaWlp6c/f/78+fPnHA6nPmOpv79/aGion5+fg4ODTCZr4RSGtehh69yvOe3wdIweQQIubN0dPqKfQ+OqTIVMf6tC9ZirYRIxwTYELybegYplEjE0AgagQKZDxGqEp4QrZfpiiT5XoHWg4ULYhE62RFfG26ohAGBVWsLTuorr/Wemrq6DMKDLjx86jtfykRqKs+ElHb6z8hrdWrvP7440cUQFuzO540rDbKgZBSVXnzC83MKL2Pt3BxzltWZqfAWrHhiGIQh6a7uwzTCv2ibOqVOnli1bFhERsXXrVkdHx4brqEYtmDiC0Knr0xHfzj6bmTqrBKo+d6p8+HqxYueuoeNSvI0os5nWwDxVQb2CRSDKREIDxnBvNlPWnKd2tF+rGUHp2ZvC+h5LCDybyZ13PuvytM5hzp+QvU6tVmdmZmZlZb18+fLFixc5OTkajcbX1zcgIKBdu3Z+fn5+fn5ubm7vWrk+DPehMnkhd3SKJwDg94KncaUvbgyY9W6xSpn+RJ6iTKrr60Lu4UiypXzcuRtGQb5Q+7xW+4SroROgvi7kCAcSCffaDIOgaPSN3zuwHL+D+9yeVjX+5WewHFXelCcv5I7L9G4l81WjyMq0cZ2Kx6R50V0+yxCYkiLtxX5lATMsO660eSvqhNEUrEOHDuFwuEmTJjWqVMEwfOTIkWnTprVQsiZiXrVNH6VS+fPPP+/fv3/58uULFixoiDmEiIT8UdHUSdO/hkL92NB37VeXp4GZ+tkjfrBbnt7ZuDKbMThGn6pXr149ePBgVVXV5cuXY2Njf/jhh7YPjAxBEM3eXlZd3cb9Nsr+ramX3KBY8mr7gC4oTUCziQUAupxdMz0u4/jEkCif5pslRCJRbm5ubm5uXl5eTk5OXl4eh8Oxt7f38fHx9/f38PDw8vLy8fFxdnYmEAjvayRtU51aCHf/1U4N673P/Xy+z5RO/8zorNChp/LlT3maL7yofV1IeMwnb1ShKMjga29VqHKFut5OpAFuZGvyK/1MoFGGXdq5rdMQWQ/CsFtuTB/ipzbexsT3LvWfbukzsUV5nZtByoZaYbZmQFxTk22bDqI8zaX+ZZ3Wsf2nWb77qdEULLVavWrVqkuXLo0dOzY6Orpdu3Y0Gk0sFufm5t66devvv/8ePHjwnj17WihZEzH6qm2miRQXFy9YsKCwsDA2NnbAgAH1F2FOJX9Ef926bSFPsfcmp1hX/LVE+Sf5R+mBR4P+3VHs/oMYd6oeOnRo/fr133zzzS+//FJUVNS/f/+oqKht27a1sRgQBLmEBpanZbVxv43y8jx/pPraBgdClGIbqXNHAnU4gdIfAJBcKhz1V+qmQe2mdnYxVF86na6ioiI/Pz83N7esrKywsLCgoKC6utrKysrV1dXFxcXV1dXX19fDw8POzs7Ozo7JZF6OLguczXIfxtid+/BWdeGFvlPebDBHoNuTIQ1lE8b50qj4li4WdSr4WpnqXpU60Ao/xIPiycQDANIEVYOSDm1LGR1gbxuy1PBhpQwI77Hy5ldVE/K8MbgmfRUaWJ8nqc2X1FUpxU/rKi5VZKthPQGDDWe7dWe7udFZLlSmM5XpSbciYj9id9SrkJOBRb0POjj1bSQht8kiyFRfGljW/Vc7nwmNq6RG3iLMz8/ftm3bxYsXa2tr66/Y2toOHTp00aJFfn5+LRSr6ZgVrM+Ly5cvL1iwICAgYM+ePS4uLgAA7fMU4fSJ8Qtjr2hwx/puPvJi4N04h1Wzfbr0Mq3oMmZaiHGnqo+Pz9mzZ4OCgphMplgs5nA4YWFhbZ+mF4KgsME9U67cbeN+G0VcoOkUv7db8Pitip6MiJ+0SByd/QeEoQEACuoUQw4/Hexnu2WIP+7TLUMAgLS0tI8GiEIQhMvllpWVVVRUlJeX5+fnl5SU1NTUcLlcCIJocnZwlI+zh/MpYdH88AHdfAPt7e3t7OzYtrbxRYrrZarZwYwONu81gDUDlR69U6lKKFXZ07BjfaheTPzhgmebn95Zd2j4xHu+LRlpa5MwvMJlAC3wmw9FZ1DButvVRbe4hQ9qSnPEPA+6VTsLtjOV6ce0He0WxCSQFXrtg5qSVH5VmVxYIRdXKsTlcpGvhU2YtXOErXsPW3dRQVmjIy27LHu0nDcuwwvTYk23bRDlaS72Le2xy+EDuRpNwgcLRVEejycSiaysrNhsNgS19fdrVrA+Oxp2DBctWrRo0SIymay6eE6yecPo/hvn9H7gq0xbkDLr0tgvmL6mbpM380kYd6paWlrW1tbi8fh6BUun09na2gqFwjYWA4KgkbMnnN13vI37bRQURvtM/8NzYt+ljHO2qlRicBcAIDJzQf2nIpVu4t/P5Vr90fEhbqy29hgruMW7OCet3VbkRMrd1KK8HiRbDofD4/GquVyRWEJmWLbzdHewY1tbW9vY2Nja2jo5Odna2lpZWVlbW1tbW2Oxr3b6UK0EhZWoXgXhKBgSG6AwrOJCWDKGaAXe46wEo+BOpSq+SGlPw47xoW7Oin9xvubesllUexN1MxLlauL7lH5V4oMjN+a0gyK3qouOlzy/VJEdYuXY38Gnh51HJ2vnhqRAH0AD6zOE1amCquSa0vu8EhwGE+3UboRL+172nm9VvzK43LE3NWSJSdv56pGV6y5ElnT50db3qw9tp5qEgmV0zArWZ0pxcfHy5cvT0tK2bt06atQo2W+/1l29Gt117q0hW6ZmzTviMcIhkvrxVsx8Phh3qvbp06dPnz6rV6+uV7C2bduWkJDQxjHcAQAQBK3b9fP6+SvauN/3MX/ctarxpBgX78F5QVZDn6pkq8ms1ThCYP2nCIruuFey+U7RpkF+0zq7tOXjc/pWvrxKF77D1vf85r8jJ4SzXQEAYg3yS4rYmYQMsdNUVZTX1dXx+fyampq6urrKysra2lp+LZfPrxWIZJZ0PIsGMak6KzrGkoGnUQgWZNiSpGDRMdbWLAZJR8FKrViW1tZsLM0VS3XB0lywdE+cRTuchS+EJQMAYBTcq1KdK1Q6UDHx6Ze74Vi7prdKgNOWc2c6h+5GCFv9ts+cVKc+XPDst9xkGxLtS8/Qce4dbEgt2sXLk9RersiJr3iZK64Z6NRuhGvgICc/Ko4AAJAUac91Kxmb7kl1NFE1tB41Hz4XUdJ+DitontWHS/5LFCwEQfbv35+UlESj0WbNmtWQM7i8vHzz5s0lJSUhISFr164lkxuPRGJWsD5r7t27N3/+fDab/VtsrO2+7Y9L+A++CrAnKvvpVvuNbt1gxGbaGONO1czMzP79+xOJxOrqaj8/Px6Pd+PGjeDgYEO1/+eff8bHx+Px+Llz5/bq1avRMmqNhkwiZeZmt2/nb6h+W8jxGTkreiRE20/ZyvwFAgg58Au19DCdfQBAr7fesnmyKade0AjY2BGB7e0/EsHBUFyJKfefavkwuPBIYcqtgbMBAEI1svGJqIcjaaT3Px69UFit4VzTcK5pOEkorCawu+GsOkoQJ7GWKVQQBWKFQCBQKBRCoVAgENTV1QmFQpFIJJPJ6mprRWIxnUa2oJMsqDgqEWVRtURIwWJSGJZshpUzlelk4xhYARyfCUg1iHBIe/bXoSEMBoNMJpNIppKNXsnVnwwsnFjgQ7J6bVISaJTbX947kP+4v6PvooDItw4HtJxatTy+/OX58qyndRXRTu1GuQVFO7XL+kEkytUMOG263u56JRLfp9S5H63LDx9Pg/0vUbBmz559+/btn3/+WaVSLV269MCBA0OHDpXJZP7+/mPHju3Xr9/evXsVCsXNmzcbrW5WsD539Hr9nj17fvrpp6mTJ03PSz+O2vdYKM9OXjhvfS9ji2bGkBh9qkokkitXrpSXlzs6Og4ZMoTFMpgGv2PHjt27d2/btq2urm7FihXnzp1rVMc6d/3yqIFDTWq9ev5LXTRr70Tfb6Z7Ka3ud7T5okCt2IvB2pIsZr5ZDEbQg0/KNyQVxPjbru3n42L5ocCb9bTEMwmF0cPWeRMLvTsn79zWaWh/R5967aqPM3mo5+vNSm1NsqroiLriAt4qlOg0mOjQD8cM+HDDKCIHAEAYCgCv1BGpVCoWiyUSiVQqravjqFX6uupCaV2RmF+ukPD4tVyVWiPVUAQSvAjglUoY0Wg1apVGo7GwsCASiTQaDQBgaWnJYDAIBEKD+sVgMPB4vIWFBYlEIpPJdDqdQCBYWFhYWVkFBARgsVgej6fRaOh0upWVVUuCHD35vkYrgSN3O9S/les027Pvx+Y8GO0evKJ9H1daI+fjms27v6lQozxTlnG2LPO5gDPEMYD9k82c5WGufdtIC/8kUARcG1lBsMD0/dOpKSeo/g0KlkQisbS0fPr0aadOnQAAhw4d2rdvX1pa2r59+w4fPpyamgoAUKvV9vb2iYmJXbt2fbcFo6/aZgwCj8dbtmzZ7Zs35xIhTfQAfPCwVbOGGVsoM4bkXzxVbW1tDx8+HBMTAwDYvHnznTt3rl279m6xRb8s37lyi0l9CWWXZZPTT0QO6O1GtR8l/Q5DcaQFLZTXziRbfo8jvm3eE6t0W+8UH3hSPrK9/fwe7gF2rRVdsy5NdXNyleV1eEVqQvqwRVItuu7Ra+0KhdWq4mOK3FiAwBSfaST38VjKK/UCoFpYX4HoKxF9DQLXojAfQSQoIkURCYoqAArXu/CjiAIA5N1+IYiMoioAESAMDYJoEESCMGSAEoBOW5fG11nWoHAtQydSwTQMxRODc0YInhqspw7notbAEolEq9XKZLL6lHESiUSn00mlUpVKpVarpVKpVquVSqU8Hi8/Px9BEFtbWxKJJJFIBAJBfe84HI5IJCoUCiwWa2tri6JoTU0NgrySk0QiBQYGZmZmvpUXkgCRpk+ZuWbTSrat7eHCZ+vTr/e29/ohZKA7/R/PDzoEFagQgRoWaRCZFpVpEZkWkWoRhQ6VaBCOXA+joP4wZn3s+zfBQMCSiKERMDgMRMFBeAxEwAIaHkPFQyQcRMNjmESMClY9qC28nJNZKqmZGBo4zrNDZxtnyJSOgj9ayqtNUw255vZWHiEERcvkwmKZoEQmKJTy69SKSoWYq5TmjVze8qn6aZHf3uXq1auPHz+OiIjA4XAdOnSwtv40Hzcul4uiqL//K4O5m5tbeno6giApKSnh4eH1F0kkUocOHR49etSogmXm34Gdnd3Ro0dTUlLmzpihPnJi8Fc1AJgVLDMGoN7G0ChyuQEyqVVUVNTW1jasV127dv3pp58aLVlUVtby7gwLK5DoepRd3augVsaa1HmFMCGcFrCYbLlcJfqZxt4PYf7hBcwk438a1O67nh67H5b1P/DEjUWZ3MlpeKAdm2bg8yjVyUr7COqPWZcXB/bU6MEvz8QRjqShnhQUVinz9spfbsNbd7ToEkuw640iYr02WydNgnWFiK4MRUQYnAMG54rB2mLxLhCpI4SxwGAYEIYBQTQA4RAUrZVrlVqYQsCyaQRMY25lKKoBiBxFFSiqRhEVispRRI6l8OX5/OoIrlxbF86kqtV1GLSMjs+3wOghLAQQFLXGYgAJQGQIS8fgWBg8G8JaAMgGgqgAwkMQGYKIACJgsNZYvDcAGASuARAWg7VpsKXp9XqNRkOlUmEYrqmpgSCIzWY3eOsLhcLs7OywsLA3vWWyDwozLpSmMo+7e3ioVar6i8cBMO4Zip0A7DSqAB+ibY9OtUjBGjVqVEpKCoPBoNFoHA5nzpw5L168eJ+zVKO4u7szGIwzZ85MmTIFAHDu3DkURWUymUgkejOnIZPJFIlE71ZHdCgAYA/0siWjMGNKkCeBvwEA4CDYc9D8s5oxAPXeBfHx8ffv31+7dq27uzuHw9mwYUNkZKRB2q9fmiwtX+3FMJlMmUym1+vfDVz+w4K1Vw7EvXXUet26dfWJn9/cfykoKLC3t29IS/LmR2++lslkXC63IT1cM1qArDQumVZna58Mt+tWoHMmk8IU+ftogcvwlP78qlUky5/pdIu3allRCTFWstVrohLzao8/5yy7nOPLIowKdevpaRXkwMjOSG/5KPiP2IoYeaG0LkRP2/JM4GFBHOVNURX/LXiyhOrQndo7XghUKaXJ2OorIpVWBrtL1bZV4jAseZhcR+IrdDy+kEChS9U6mUZbK62EUSBWv8ofj4EgNo1AIWCVWrhWrkU+wUTBAIABcjyaXP4tUADUAKgBkAJQ0txGAIh/x1XGHwDQG3zTu/ltmmmU7UNb3kbzjfaJiYlr1qx5+PDhjh07AADLly+Pjo6eNGnShAkTPlxx9+7d8fHx9a+TkpJOnz49bdq0zp07S6XS4ODgI0eO6PX68ePHe3l5bdr0Kh9qTExMeHj4999/38gA/r37Dv9ZHt+pvBO3pODcjQQEs3T58gULFnwg3LOZzwWjx8FKTk5ms9n1bwUCQfv27asNEVE9JycnICBAo9HU/0tTU1PDw8N1Ol2jhU1wvTrTtWjGN0f2hy+WanBTnSsF1/uwvyiE8FQFfyUW70qy+PbD1TV65FYhPzGvNrlUkF+r8GVTQxwtfGxotmTIx87SlUWxoRKIuI/4GKEoEKt1IqVOrNLJNPozE0sfTi1ytbDWamyECp0dRlBTWyjUU7VYBl+F1eohFgW2puLoJKolhWZJxtOIOGsqgU7E0Yg4KwqeQsBS8Fg6CUcj4KypBAIOwyThW34E8vLAMv/pLPvh5L7X9vd18P4xdCAAQKFD75SK04SgUgaH2xM72RH9WHg8BgIARdR8WMVFlBxEzUfUfETDR9S1iFaC6hUA0SJaMYC1iEYAq3gAhT/UMQaPo3thqY4Qjg4weATHlMJYCUyu4ZNKVFQZjYFgIAdLWyc6nUVnsJlsGwsWDkeqPwtpWJqYdTH1h9q6dHX0+VdRanPFNYmcvBucwoe1pSFWjgMcffvYe3W0csL/M9CDSo+ScRCCApkW0SMok4TFfvpPpoH1OeKadCEnR1yTLuBkirioHssuoPUIdIsMc/Nn2gZa2uGbEJ8CGGiqNt+ClZ2dHRMTQyS+Tj3dvXv3qqqqj1YMCgpqeA1B0Pjx43v06JGamurm5sblch8+fIjFYt3d3cvLyxuKlZeXjx8/vtmimvm8aOdoUzsCo6uMjlOVb7t7948//vjtt9+ioqKMLZeZz5ja2to3XYnrPWMM0rKLiwsGgykvL/f29gYAlJeXu7m5GaTltsHKn9wBdtJjqp/xbKcG+BEd+itydtCC11JYa+R18zHY8wTaFx+oTsRhBvmxB/mxAQBqPZLFlaZzJMV8ZXJ+rUjPKxMq+QotAIBKwAIAxGrdW/csCgGrg1EdjFiS8UwynknGU1CsxEtZJFQ6E61UWs0o5nUrQr5tsIU1TU+jhdpZhrEYQQAyQiwArzEWhafFnqMYl6Omdr+625HC+KZdNyoe8gF1MV19+Cr4YbXmXKGiQqoPsiH4sQi+lpYuTBu8ZdDHm34/egStVsCFUn2VTM+Rw5UyvVSBuDJwDlTocnZaEavo1049Y1zaGWqMH4bL5TZFwQpZZnMqqKg8QeY6iA4A8GPa+jFtvwvoqYJ193klSZyCbx+fz5fUBjDtQqwcQ60cO7AcfSxsLAlkAAAGAhbEJrn8axG4UiGukIuKZYICaV2euDZXUstRSDwZViEsx0BLu6XtewWS7R8P4HuOYoSONU466ubraOfPn9++ffu9e/e2bt0KAFi+fHmvXr0WLFjwxRcfmo3vEhkZuXLlyujoaI1GM3DgwJ49e65fv/7hw4dDhgx58eKFi4vLgwcPoqOjS0tLbWwa+Y5M8InQTAvRSuB5Z2O9bcrc95b08bFNjhq6YOHCsLCw7du3v7lxbObzwrhTddq0afn5+atWrXJ0dCwtLd2wYUPv3r23b99ukMb79esXHBz866+/6vX6IUOGtG/ffsuWLY2WNMH16sV2/gHVI1I/lIlEDnanhFA4/KtdbIbnYEg2CMxT1C0iMiYTKANb0oVGjyh1MIoCJhn3ltuTQgsTsBAe+/qemn9MvKroqv8gZg/Mo84W9yAijciIwVP7YQk+wKhO02oh/LdnweRKXzwNUyITRCbs3dopZrxHyFvFpFoko06bJ9TliXR1StiJjnOiYR1oOBsyxoaMZZEwVDyG/M+ENio9qtAhMi0q0SJSLcJXwQIVwlPAXIVeqkVtKVgXBs6VjnOgYZ3pODsK9ia3YOrt074PHc9tm2BBMZWAEW9SeUN+d1b1+JdeOErj2pJCr80QVj8XcJ4Lql6KeIVSPowiLlRLWzLNhkSzIJBUet3ZskwVrAMAkLH4UW5BZBxeolXXqeV8tYKvUQg0SgcKw5Vq6UZn+TJs2jHZ/kxbD5oVruE5CgXXx1ZiyVDUX825axj5FKFOpwsPD9dqtXQ6nUQiqdVqpVL57NmzT82fevLkyblz5wYHBxcUFHTt2vXvv/+uDzGyfv362NjYgICA7OzsXbt2ffXVV40PwPQWLDMtp9/y838M/XHMg+/+vH3IMWYwbsbczZs379mzZ968eUuWLKFQ2jqutJmWY9ypqlQqly9ffuLECaFQaGNjM3XqVAMmey4sLIyJiaFQKDKZzM7O7urVqxYWFo2WNMH1qjJJfvKPl3ETnmzuMCuLr10YaiF9tghFtBZd9wAAEH2Vgr+EyJhMoES3hTSo/tlvF8W9T4XSxUAgptp/S3aYYly96k2uDCr3ncz0HmsBAMgW8/pdPxjbZfgot/faqNR6tEqur5TB1Qo9X4XUKWGhBlboULX+H/8BEg6i4iE6HsMgYiwIGCsyxpqEtaNi7alYFgn7ZqYiqU69IjXhamXO3Kd9+lh7d1xpHMNMU7gxsYrmhAvfbNfE8hKtulIh5qlkdWq5TKfRIfAY9+D6yKh1anlcaQYeg6XjiTYkmg2Jak2i2pMZjZ5RaCBlQ23lDfmwW+5YYnP+P8YP06BUKn/77bcnT57o9frOnTt/9913VGpbR982wQXLTMv5atyFL8YnUu21yy4MTrz7A3PlevLQL8rLy1esWPHw4cMtW7aMGzfO2DKa+TRMZKpqtdrWcOnT6/V5eXkQBAUEfCgUk4l8CW+iqNaf6FSwePPxwpGrVz6Q/9bbmoyI6i74WUXfxVn4AQAQPUfBX0agDSXSxraeGLCuRKtM0CnvVJUDijRHje3hG7kdwptW/uDcP0TlibKBZ155F2UIqwcm/b6zy7Cx7h3aoPfrnPwZD88MdPT9wT36cmDllwU+JOsmuRMZBWWN/nRwUUyCq02o4b3BPkpJvDR5AXfUM0+KbTP9oIyvYAEAVCoVmUzOzc1NTU2Njo7+1DANLccEFywzLWfFwCTlTNE6r51LX67yloKvDy5m/f43oWNnAMCjR4/mzJljaWm5e/fuhgAfZkwf407V+iBVb3HlypU2FsM016vDVrknjtxb1CGyoNaxA5vQx5msyP1NU3mJ1f9GfQEE5isFK7F4XxJzHgQ16aR7EwONoqhKp7qrVSSgcB2BMlCZl8nN+fuJy86pfT5yWMooqAXwMc+CKRxfPPXVPlSWiNvv6r4VIf0WBvRovX5FWtWSZ5dvc4sOR4zpY++V+lOdrFTb+5Bj6/XYKJ8aPLbguDh9K3/UM8+3Qk+1NsIcTXzv0pirruyw5ut2BpmqzQ8gq1KpwsPDd+zYweFwunXrtnbt2tDQUKlU2kKBzJgBAASRXZL1RGW1bG3XC7t4RMmabaJvJsOcSgBAt27d0tLSpkyZ0rdv3wULFpj/cmaaQsT/6d69u6+vb3p6ujmuXgOsQFInvdstbmGkE+lelRoAQPX9BlHXqcvi6gtgsNZUm1gUaBV1c2BdUVPa/NidGNGrU5SiTTLeOL36CYk+kULfIn90pKgodSP1/KReJnqkiWSFte1Crkh8HT6tvaV9yojvDhc+XfTsIow2Ery0haAAPVacFnBhKxVHyBy+uI+9F6JDX+4TBs3/SCq91uBTQ/P7TGTSXPCpP9a1kjyNohbCicPLu/9q1xLtylA0X8FKSEggEAjz5s07fvx4cHBwaWlpt27dLly4YEDhzPxnsbOkS7TcVHV/FrZ2bR/KdA6L+s0iwZQxiEQMAMBgMJMmTcrOzgYA+Pv7Hz161AStAmZMihX/Z+XKldu2bbtw4UKjwdb/m1i1J7avdrxdXRTCJtYoYK4CBhicRfgBydOFiJpfXwaCyBTLVUTaeAV/uUq8C4UFzeoKhbW5askeKW+sWnYURwig2x6lsDbo6+r4VzpLLaO20o46V+pwGFNxunoXr9EWRWckb15xpjIfDDFtQfQAACAASURBVJrzUsQbfOOwQKM0YF+ZQm7PhL2xOcmX+n4d23U4HU8EABSfkzK9CVZBpujb/i69DzjmHBTWpqjapjtEh14fXeE+nOH7FfPjpVuf5itYxcXFAwYMoNPpSUlJw4YNAwAEBgZyuVzDyWbmvwvZFmelQJ7ghmorKif5J6l08MXgwaTe/YXTxqOaV6frWSzWrl274uLidu7c2bt374yMDOPKbOYzwt/fPz093dhSmAqsQJJtBrNCIRZq5D0cSXcrVQAAvE0XsscEyZNv3iyJp/Sl2x6BIIKsdrpKtEWvyWg058xboIhYp0pWiWNlvPFK0RYIw6BZ76LZ/EagDgMoUfpskfTJXGKPc7/IZ6YJb0xtZ7AM3K2BxxeMyiS5Tv6PUTMJ5Gv9ZwSzHEIubr/NbZKF78PUqeVzn1zod/3ARM/QpzHzw97I1pz5m8Ao5qvmQbHHRe5xSBpfqZUa3rz3Lve+rcbTMOG/NNWzvrVpvoJlb2+flpZWUlLy4MGD/v37a7Xa69eve3g0O9CtGTOvUUBCVylTTHFW8mFE82LvF47LLucgC7/H2jmIl8wBb9irunXrlpKSMn78+AEDBsyfP18sFhtRbDMmy7U3uHz58uTJk98MyPcfxyqQJM7S9bB1v8Mt7uVMvsdRwygAANBDf4RlJYrc2DcLQxg6yeIbuu0RDN5DLdkn5Y5Win7WyM/r1U9gXQGi58C6AlibU1Z8ViOPUwp/ktVMltVM1ioTMTg7qvVWuu2fRPpXGJwDAEAvyedf6YyouFZD0w9wAiAsz/0uzqNb4wcwTQQSC2vXnVJ2WdZwpaCgAACAhTCbwwYf6j5m8oOTcx6fFzbXlCXQKNc8v+Z3fgsOwuR8sWyWb/ibZ+VqnqmUPL370NbKAvlh6kf6qXiOZDgPoN2dyTG4PG/x/Je6uufqfiecoebrNQam+W5cCoWiV69eqampkydPPnLkSN++fRUKxf3799s46LZpOo2aaSGZh3l/5qfzB1jMQBI6OBcR7HstvNENh4F+G+wtmDCc0LU7Y+mat6qIRKL169efPHny+++/nzdvXksS1JtpDYw7Vd+MoIbBYHx8fH799dcOHdri8NebmOZ6pRHDR13zlY8EOZKaA91GbXwi7u9K7mpPBADAshJ+QjfLXmcJthGN1kXgWr0mDdYWITAXhUUoKq/P+gcjFCLJBYP3xuK9sXi3d0MtqIr+kqYupYduovhMv1KifMhV/1mye9nvg7+7/2mOPm1P/jFx8VnJoIuu9W/fim8u0qpWpyWeKcuc7x8xzy/CgtDUvbwccc2+vEcnStJHuQWtCurrSrN8t0zShErbzpTghcaxYDUxkvu7wGr0bNfi9nOt/Kc3MiiDUHha8ngZb+RjT6pDSzMs12OYqYq2DIFAUP8iJydHp9O1sLVm0PIhmDFBKm7INo951P3SXxtuPK2Nd5VUDxcppU4bkpJLBLCAXxMZqjh9rNGKz58/Dw8PDwsLe/r0aRvLbObDmNpUVSqVbd9pw8K7bt26tu/9AxxxznucVeF5ZhOKoo+r1esfCxs+UlddqzntoJeVGaovWFUrvD2yNj5QJ8xCUbRIpJ2RVPd7Xkb4wd13ZnIM1UvroZHABy1yVAL9B8rkS2on3T/JOr5mRnJcYlWuUq99X8k8ce3O7PtdLu9yPLVxzfNr1QrJ+0rKKrWHWDkaCdwi6Y2EMFd92Ca3Nq1VJl1FkuwP21x+pqrlTa1bt85Q2hGKoi3S0TQazcuXL/V6PYqiCIKIRCIqldqrV6/mq3ufjmk+EZppIYJM9aWvSxcsOj7WduEPygG0Tl0JFgPiC8N+uFHw/LtIqLyEP2aw5a6DxO49362LIMjhw4fXrFkzevTojRs3NmThNWNcjDtV60MWN7ytrKz08/OTy+UfqNIamOx6dXVIebupzAjNzscx85yprLm3+as6M53pr4wBitzdytzfrAY9wJDYLexIw7kueTiN7DGRFrIRwhJlWmRlsmiyP21R2u9RSYHjO3bwnWQS7skf5vrYSqe+1ICZrA8Xq1ZKT5Q8v1yZ81zACWTa+VrY8DWKm9WFKIp2tnHBQZgMYTWDQOrn4DPaLbivgxf2g5tbT76v0cmQHrH2Bh1K21FyXpr8HXfU0+bHpmoUzl3F9TGV0Rdc7LsbMgC1kXMR1tbWhoWFcblcGIaJRKJarWYwGPv372+hQGbMAADItji0ErIiUlwYSB1lNJmXrcGeG9NhyNHUql0PSpf08mLt+VP4zRTrU5dwPm/n4cJgMDNmzBg5cuSaNWv8/Pw2bNgwY8YM847hf5Pi4uIpU6agKFpUVBQR8XqTi8/n29mZiiesKWDdgSTI0PTp7XWrumiaT+f+ruSEUtWsoFf7QVS/uahWJLjW22rATQy5mTd4RF0nTVmirXnA7HGUYN8HAICiIPaFtLsDkUAQVCrErvG2dvM+jyQN3uMtMncJPqpgOVAYSwJ7LQnsJdNpXgiri6V8Eg5/oudEHIR9UlcOAAi0tGOTmhRMFVajOYdEXzxwN4D0RsLjC4YwW50wtHz4XXcc2TALcr12NSDO2bDalaFo/iAvXLjg5eUll8sjIiJevnyZkZFhZWXVs2cjFgUzZj6V3IoMjRgOZNqRibJnxBHq/EQIoujVz3aNCNh8u6hCpCJ06Wax4RfB1HFIXW2jLbBYrD179iQlJR0/frxbt25ZWVltPAQzpoCnp+f8+fO//PJLCoXy5f/56quvVqxYcffuXWNLZ0JYB5P5L9RRDj43qwsAAFEu5Gc8jVT7+uQXLXgN2fMrfkKEXpz9/mZek5aW9voNolPk/lZ3sT2GZGMzPKteuwIAXCpRamF0rC9tf/7jSXadgAay8GpTF95m4xpNF7xUyyp04K2Rvgc6ntjD1n2Kd6dx7h0YeBIFh+9j79XH3quJ2hUAIP+4mN2JzPRpUpTXVqIpI/0wYavZln7E62MqEZ0B7LhVt19pV4692jqFTBNpvoIlEon69u1LJBIDAgJSU1ODgoImTpyYmJhoQOHM/Gfp2KkjkYn1I9pK9JwUiRXOsj1G466Rn/W0os6LcP/mXCYAgDzkC8roCYKvx6LK9x7YCQoKunfv3rRp06KiohYvXmyOSvofZPTo0bNnz758+fLs/zNr1qwpU6aYE4e/iXUHEj9D3d/R5xa3CEFROgHT1Z54vewf4Yto7VfQQzYKrvVWFhwC4CM3yFdBKRG9qvjvunh/TVWC1YBbjE6/QrhX98J8kS6hVDm/A0Op18SVZgysCrTrZopGiEbBEiGv0Rb5x8Tg08NvNgcUZOzgd1hk5OgMBhgpBHr/7ggAuDmpCtG3SMcquSBNGl858KzpalegJQqWm5tbcXExAMDHx+f58+cAACqVyufzDSaamf82ZFucN2KTLyvHQZDacaymOBXRc2Bd4Yq+XmVC1YUsHgCAPn8p3tdPNOdrAMPvaweCoBkzZrx8+VIsFvv7+585c6YNB2HG+CxcuDAjI+Ps2bML38HYopkQDA+CWqC31tLYJFq6kAMAGOpJuV6uUv7zLkj2mGg18I6y4IAgIULDvfUBNQvRihQ5u2ov+CoL/7DodojVLxHHfJ2lUaJFYtOl3wQzrMjYo8Vpfe294ccY09zleR/tpljm/yX6mJ5pGCqS5Bgc5NTXtDIzNg8MHhp4xkUrQ66PrtQrmxUcCwXPt/AfzOcOuebmEGm62hVoiYLVr1+/y5cvb9iwITo6ev/+/UuWLNmxY0fbH3s282+FYotzV1lniqrbWxOyycM01Ul48iCN/AwBi9k/Kmju+SyJWgcgyOKXnahaLflx9Ydbs7GxOXz4cFxc3IYNG4YMGVJSUtI2ozBjdORyuV6vlzeGsUUzISAMsA4iCTLU/Ry9kzgFAABbCjaETbhW9rZ5GMcMsB78lOI7S/psYd15H+nTBery86hOCgBAdXJ15WXZi/XCpH51Zz10/GeWkSesBt4m2P3DdQRBQexzaaQjqYMNAQXobznJCwJ68B4qPiMLFgDAtjMZwkHcR4YM3f4+nm+u67CkrfP8th5YEhR93oXAxJ7rXiIt0X5SXY0IThxVUXxWMuqJh02IqYezb5GffElJSX5+fnR09KlTp44dO9azZ89ly5YZULimYLKncsy0hLS0NME2tvMgahi69WrvNU+5upmyyUTXGD3lKo19AINlTzudQSfidg4PAAAgMqlg9CDy8NG02Qs+2rJWq92xY8evv/66YMGCpUuXEonG9Gn4T2GeqsC0v4R7c6qZPkTuqLrNmXfuRH8DAOAp4NWPRNt7shiExh/FdcIX2uobGt5dLfc2CqshLJFgG4m37kxgh+dwGSGdGs9/fCJPXirVr+zExEDgGifv+7TEJ70X/OmQN43vhyWabpKcd0n/lS/K0VjM4bXqLiHvkfLGV1UT870xOCN/OZ+a7PmjZO0WpPxQ12OXvfe4JkWXLYmXPpjH9RzJCN9s19p/FYNMVQM0AcNwQyMYDKaNj2uZ8oJlpiUkL+LSnPFTvY7t6DTySCZ5j89dVcF+atfRAEAki1lCpS5gy50LX3fq6moJAIBrePwR/RlLV5NHjGlK4xUVFQsWLMjOzt67d29UVFQrD8UMAMabqitWrHjfR7/88ktbSgJMe73K+V3Ee6zsepBtf2pDxZjV9REy/8qRIyj6dYDBQoc/42mO5sh/jrCkEzAAgME3Do9xD+5T1i51Y92I+5/ZETlVrf54u8JJZb4ERive9a4MLncfRv/oicXPlNpU1e2pHKojrusmuw9YpGqeqp6s4ilr9JG7HdrG6cogU7X5fwu9Xv/ll19SqVQcDof/Pxs3bmyhQGbM1ENm41S1cDDLoVDGtaNiK+iD9KIsLNRRq7yGokoWBb9liP+c81l6BAUAYG3trP46I/lxjebxg6Y07uLicuHChZ07d86YMWPKlClCobCVR2PGaFS9H2OLZlpYBZP4GWoKDt/d1i2pOr/+4hdelMfVmkqZ3iBdVEj1h7Jk33W0qNeuimWCVH7lWPcOvIdKu8/KAaseMhvn1IdaeLIV03PxX6j5Gep2k/+1wfzYYeQxaZ5uMYyEoeXnI0oydvB5j5WqWr1GBKtq9VW35E/X1p4KLkqaUOk9njn2hZcpu7S/S/N1tBMnTqxcufLgwYOurq4NF62tra2t23Sr2JSfCM20hLwjIs49ZeaS4hKZoJtlPywEDRStgoiWWBc8luBDpI0GAAw4+CTK22Zpb8/6KponyaI506xPXcJ5+zaxF7lcvnr16ri4uO3bt48bN661BmPGNKaqWq0WiUTW1tZ4PN4oApjCl/A+9ErksE3eDLHfvqJHKfzKIz1eTYfr5aqnXM3ari2N/ylSI2seiSa0o3ZzeGWoWJpyBQtBv4QNvtS/LGieldsQ46TYawmVN+UPF/PGZXi1UvtJ4yrZncgdFv97HLDeB6JHK67Jy6/KatNUsjIdokcxeMjSl2gfQXEdTLfvRnkn2VLrYuRUOVu3bl26dGmzqxuKlgzBjMkilUrLE2WXBpTeqi7scXV3Nl+7KlmoFbyoOeOq1xRKuWNRRIeiaIlAYb3mWhFf3lBRGX+GF95ez63+pO6ePHkSFBQUFRWVl5dn4JGY+T/GnapCoXDs2LH1mVLJZPL06dMVCkXbi2Hi69XxdgX8TFWpTGB7cj2MIPUXYQRddl9wt/LT8pBIpdI33yp0yNL7gotFr79zpV5rc2JdiVSA6JGDjGwV/0OZZ0wXBP27XR7nrvzjJT8dUYHmsE2uVmoquXHe+k3/3RhkqjZ/izAyMvLZs2d6vWFMx2bMvAmXy6XY45Q8fTDLIVPE9WHhuAq9itYeQ2DCwioM3k2rugkAcGdRVvTxmn46o+FJgzxsFHXydOHkUYjsE0JedenSJS0tLSYmpkePHuvWrdNoNK0xKDNGZPbs2XQ6PS0tjcvlJiUl5efnL1q0yNhCmRzWwSR+htqNxrIhUZ/xK+ovYiDwbTDjeK5coP6EQ/VcLrfhtRZGN6eIA6wIQz1f7wOeKE7vYuPiTmfxMzU0JzzJCmuoUbQpELAfh2b+JmiNttM21QXNY+HpppKF4s3f1ExTaM4vl5SUtGTJkri4uNLS0m7dui1cuHDJ/0lKSjK4iGb+g/j4+FDscAqu3opIoeOJlXKRH4vwkq8le05SFR8j0sZqZKfrY/AsjPRQaOHDzyoa6tJmzSeE9xDN+BLVfoKehMPhFixY8OLFi6ysrJCQkOTkZMOPyozxKCws/P333wMDA+3s7CIiIs6dOxcXF2cUSSAIgiBo/fr1Run9w1h3IAky1ACA4S6BF8pfNlx3ZeAGuVNi0yVwk/dMfHx86l9oYXRrqoRNwU7y/0cYp315j+b7RwAAuMkK+4jPybHmLXos9uHcU0hLPy3cwEeRlmrLrkjbzzNycNE3afhN/8WsX7++foYapLXmKFhKpZLP5/P5/N69e/v7+4vFYv7/Ub4/prYZM58E2QanFcOIDg1hOaYLOR1sCOm1WrLHBHX5BSzWF8JQderHAAAsBvprfMjKq7nFAkVDXYu1mzBW1uLvvgXIpwWyc3BwOH/+/I8//jhu3Lhvv/3WHPn9XwOFQlGr1Q1vtVotm93SvMXNo37vwFQVLHJduhoAMMK1/YXyf2SXGuZJoeCgozmyT2pQpUc3p0gYBMw3QYw3b1kPakrlek2UgzcAgPtA6RD5+Xm4N4CnYfynsTJ3GdiIlbKhtv0cKyLz8zTsfbasX7++YYuw5Ziux2UTMWWnUTMt5Ihj3ugUry01txAUXejXb3my6GCUtfj2ELLbaJyDq0Z+jmYTW19y653ia3m1N2eHNzx4oFqNcPIYnKeXxY/bmtG1RCJZu3btuXPndu3aNXLkSEON6L+Mcafq0qVLnzx5smjRIkdHx/Ly8k2bNoWHhw8ePLj+05iYmLYRw8TXK2WN/qR/4TSBHwDA4+ymy1FTA5ivU2IrdOj6J6Jwe+IXXk0yONWp4C2pEj9L/JQAOuafFoGRt/+KcvD+pl03gII/HfJGPfWkuxjn2IFBUHB0p4KKviz2MZQ+JMrVXOhV+mWhT6sGgDDzAYwZpuHevXv9+vWLjo5OSEhooQRmzLxLfVZRij1eydWFWDmmCzlWZCyLhCkU6yjeU5WFf+LJPVBEotdk1pdf3MtDCyMHn5Q3tAARiKxDx7WZL2S//tgMASwsLHbt2nX8+PFVq1aNHTu2pqbGIOMyYyzOnDlTWVn53XffjR07dtmyZWKxODExce7/MbZ0pgLFFoclQbIyLQBgmEvAubJ/GLGoeOj7zsxkjuZ4rvyjt564RzmrH4r6OJOnBr6tXZXJhfdrSiZ5hQEAxAUaLAnzWWtXaWlpVEe8+3BGluE8sZ6srglZYm1q2lXLkz3/12jO78fhcAYMGGBjY+Pk5DRs2LCUlBSDi2XmP059vOB6N6wQlmO6gAMA6MgmPq/RkJxi9JI8vbSESBurkZ+oL4+BoIOjg9dcy6sQvU5PC1FpVkfiVImXFYf3NU+Mnj17ZmRkeHp6BgcHHz16tMXDMmM0yj6IsaUzIWxCX+0SjnXvcLr0xVufMomYjd2YRRL9T8/EAlXjCUBFamRfpvS+2nZRqEW0G/ndAjuzH0z17kzFEQAA1feVjj0/4/1B8P/FquMqm8zdQp28Wcn1/gnvsbLuuTrIlLyv6mmLtNb/LpqjYCUkJISEhJw4ceL3338fPXr0+fPnDS6WGTMAAKo9TsnTu9IstQjMU8k62hJSa7UAgyd7TFQV/UGg9Ed0ZbCusL6wny1tYaTH1NMv3ny2xrCsrI6dlx/ao7rczH8piUTatGlTYmLirl27BgwYUFpa2vJxmTEK5eXl9+/fv/sGxpbIFLEOeaVgdbVx1cD6TOHbB8doeMyaLkx/K/zyZNGBTFlGnVYDozAKBCo4tUYTmy5dfF9gQcBsjWS1YzVilxJpVUeLUuf6da9/W31fYd/jM/Zwb8DCk+DUl9ry44QoApIXcrv+xMaSPqesQWYapTkKFo/H8/Pzq38dGBjI4/EMKpIZM6+o3yIEAARbOrwQcjwt8HItUqOEKT4zlIVHAIoSaWM0shMN5Zf19hKrdH+8caIQAIB1cGT9GSdZv1Jz/3azJQkJCXn69GlUVFTnzp137NiBfKLvvBmjs27dOg8Pj+HDh496A2MLZYrYhJDqnr8yA49yC3rXiAUAwEDgCy/qjp4sBxr2fJFiahL/y8TaNY9E18tUviz8b72tJ7Sjkd+TOO9A3uMhLgHO1FdhS6vvKxx6fN4WrAY6b7B9sZ2vFjRu2GsiuX+IIBzkM76lYV3NmALNUbBgGG5IOEggEHQ6nUFFMmMGFBQUAACodjgFTw8ACLN2SuVXQRDowCak12pxFr44uoeak4inDtZrX8K6svpaOAx0ZHzIyoTcNzcKAQD4dv6sg8dEC2dr01ObLRIOh6t3lL506VLPnj3z8/ObPzwzbc7+/ftzc3OFQiH/DYwtlCliE0rmp7+aPl96djxWnAajjT9O0AmYIR6UDeGWx6NtTg5i7+1r/X0X5gBXMhUPgf9P4bdQwbrY3ORl7XvVv5VV6PRqlOn9eSdcbxgp05vgNcoi7ee6ZjelFsBP19RE7nZo46jlTaTR39TMBzAtHzozZuqxt7cHAFDscEpuvYLlnMqvBACEsonPazUAAIrPdGXB7xBEJNJGaWR/N1QMtKMv6eU55dQL5J9euISOnS237xNOn6jPz22JYJ6enrdu3Ro7dmyPHj22bNkCwy16WjXTZrDZbG9vb2NL8RlAd8UjeqCo1gMAAi3t7CmMG9XNua3WT+G3OFzwrKuNS8PJRO4DhUOPtk6BYnDeHGnnDez8Y2JRbjMjFT9czPUeZ/GBnMfGpdHf1MwHaKaCdfHixbCwsLCwsF27diUmJob9n4MHDxpWPjP/Teh0OgDgf+ydd1wUxxfAZ29vrx/H0buIioKIXSxg710TW0xssUZNjClGk1hiYkuM5hdjjMYWa2LvJSpKEQvVRhPp7eA4rrctvz/OnCcccOjRjvn+4Wd3dnb2ze698THz5j1DMHfw3wwWACDYiZEm0WtwitVyir7kHqHIZnDH4bok4yQWAODz/q1IitoeUdFZitl/kGDNRvHMd4mcLPAW0Gi0JUuWPHz48Nq1a3369ElMNLOGAmlszJ07d9GiRQ8fPkwxoaGFaqS4dGWXxL2cxJrrH/Jn2oM3aMSgwqZoCfzHx+GrggcZSwqjVE06xKgB056yXejdvnGOWFIAar/BP/uKPP+OKmS9qzWFsyqVvymkBt4+207DYgNdgFSFLFt3wPtlckCXo2vylVKKojbcl8QUaCiKkt5bKotfTVGURn5CKV5teuMLsdJ59dVHBdLKbSoO7Svu24UQFb+9eCRJ7t2719XVdfXq1Tqd7u0btG0aVlXXrFnTGEa/JjFe3fu2+P7qlwoi02kcjnxbqLJCErpfnkaO+XevacnR9mmiWNXbt9yoIHHyRMjzxzvFtbpLka/f556cf6dOchpC3gCrqCpcIoQ0XrgedHUxThEUAKCrk5dhlbC7G/NhkRYAwGm7QJ3+JyD1TO5YQpdG6J4Zb2zpwNk0KmDGsQQtXtF9hPv+bPa775VOH0+K39YFB0GQOXPmJCQkxMfHh4SEPHr06C0bhNQdO3fujI6O1mq1ehMaWqhGiks3tij25QwWH2NO8u24N+3+W7apxHWbHt9a32W4sURTSijzcadOjXQ57I1BUGTQAa8Ha0RlzyxdKCS01LXJOR0WO3r0bfLzeRBToIEFaYwYItrR6AjLCf1vldA7VpwHAOjuykwo0eIkRbdvj9q1VWefBgiDyf9AI9tn2sKcHj5tnHifnX9auXH+0s/Yw0aXThtLllkhMKC7u/uFCxeWLl06ZMgQw1TW27cJsTrOzs69e/dmMBh0ExpEksaci9CAS1eW0cACACxs12tP2v2qXN2rokJQyl+eRfZz9evo4GEsKYhQuvXhIGgT98AyF35T2I7Z52e3y+OyNWUW+GhSIHx+PtcD67bKuU7ksx7NIdBow+cifEsSEhLs7V/tQc3JyZkwYYKjo6Ozs/MHH3wgFr/8P+/y5cuBgYFsNrtXr17p6en1LyekATFGtON5YfJcPQCgp7NPjCgLACBg0rx49CdiPQCAG7BElbIDAMDgDieJUlybYNrInsnBV1NKzj4xE0aE/9kq1pAR4g/eIWVSqwg8e/bsxMTEpKSkHj16wKmsRsikSZM+//zz3NxchQkNIolh7aAxG1hcTwxBgTzn5QxfJwcPT47grEnuZ0swDUpZplVtfxppOn0FAMi/o/TsZwsTNmbDb7Z9377VRLtLY7JxVbWGKQUiPymUZegGHfBs/M7+zSHQqHVzEdargUVR1IEDBwYPHmyadXXatGnOzs7Z2dnJyclisXjBggUAgKysrEmTJm3ZskUikYwdO3bo0KE4jtenqJBGAs8bU+bhAIDeLr73S3JwkgQA9HBj3i/UAgBY3mMJRY6+LAEAGstuRoVJLAELO/J+50UnHxXINJVbtvviW0ZI77IZ71JK6/xH6+7ufu7cuWXLlg0ZMmT9+vVwBapR8euvv27dutXHx4dvQkML1Xhx7cERPXg1ifVFh/6bHoe/cWvfJ9141ze4tZ2TaWHBHaWHTRhYVdFrk5uwLfPCyCrnsUg9dXNOfvFD9ehLLegcuJpkg9TrR12/fv3PP/9s6m2q1WpdXV3Xrl3L4/GcnJwWLVoUExMDADhy5EhYWNjo0aNZLNbKlSsJgrhy5Up9igppJPC8MEWeHgBgz2B7c+0fSwoBAL3cmQ+LtQQFAI3OabdI+ex/AACMPQBQWr0m2vT2EB/hktCW7x9JIM39RSL49gesfQfxnKmUWl356psxa9asuLi4Bw8e9OjR4/HjxzXfAKkX4uLiMl8H7iKsBtce7OL7KuPpWO/2Klx3o+BNVhJSpKLDGfHrOg8155THxQAAIABJREFULdSUEbIsvXMXW3PAeg0EDPjT0y2EfaJbRtZFeYWLRTGqEz0ydOXEuBu+DIF1UkRDGhv1amDNnTs3KSmpd+/exhImk3n69GkPj5cL8+fPnw8JCQEAJCcnBwUFGasFBAQ8eVLlBDXyOsa5d9MF47S0NLn81U/c9JLpsVwuN42lBltoqBbi4uIMLXD/M7Di4uL6uPjeFWUBAMS5GU5M8EysAwBw2i5QZZ4m1cUAICy7D8uLfwOANJVh5aDWKA354Ua6GRkQRLD+J7qXT9aUMdR/s6pv34vi4uILFy58/PHHgwcPXrduXXJycm1baFTf4s1aMLoyGAENiq8JLBbrwIEDffv2bViRGjOuIexikxksGoJ803Hwt/FXLW/B+Ev4+N7ZrzsOcmbxTK8W3FG69+bQqoj23rSoxjMJoYFem9367/KI+aroWIfnMSuLn/5Rdv/b4jN9M6+/l9f5c6cRZ3wwbpOZu2oOPlhW5u03ItaWhw8fMpnMyuWbN2/28vLKysqiKGrcuHGrV7/aeD9hwoSvv/7abGsN0gVIvZF2rPzalBzD8b60B+/dPmw4Ppeh3P3o5dbx8uh5soQ1hmNFyada5eUKjRTJNB5rr99KLzH/DBwvWzq39P2JpEZtXeGzs7OHDh3auXPnxMRE67bcFGkMqhobG/vBBx8wGIw2bdr88MMP9S9AY3gJlqAtx//gPyX0pLGEpMjO534+k/24Vu0cSH/Y8exWHYFXKI9YWhC/pQp9tElIKv+O4sG64vAF+ffXFGddlBE6sua7IA2HVVS1Dm1nsVhs3K1jNgiNEa1WO2fOnCNHjkRHR7do0QIAwOVyVapXE9QqlQo6TDRPjEuEAIA+rr7RoqyXx+7MB0VaggIAAF6HFaqUnZReAQBgCT7SyPZTlMq0EVc+888pHWcdTyxRmNvih6LCbbto9vaSRbMovTX3APr4+Fy7du2TTz4ZOnTohg0boB9hQ4Hj+IkTJ0JDQ/v27Xvs2LETJ06kpaWtWrWqoeVqvDAEKM8LK3v6KtAAApCNXUd++fCimrDUuTBPKV0Re2lf6BSMVnEJLO+WwmugLTtgVQQBHn253Ve79N/l0WOtS4tRfBpmC7N3kOqpQwPL3t4+8T8WL15cVTWJRDJgwACZTHb37l0fHx9DYWBgoKmHRIUVQ0jzgeeNKXJfDuj+ds46kshRlgMAHNmoGxd9UqoDAKD8Vgy3/qq0PQAAFGtNZ3bSyk9UaGdEO5f3u3hNOxxHkOa2h6Co/bZdgI5JFsygtGY84t+GmTNnxsXF3b59u0+fPtWsdEPqiM2bN/v5+a1atWrChAn5+fkCgaBLly4NLVQTwDWEU3zvtT9Uhnm27eLo9V3iv5bcTlDk9IgjnwSGdXH0rHBJLcKVBTYYAQsCqUAdGlgoigb9h4uLi9k6FEWNHz/e2dl527ZtEokkLy+voKAAADB16tTw8PDz58/r9foff/yRJMlBgwaZbQFikxjdergedNV/sUYBAH1cfCOLXhiOe7kz7xa+NIZ4Hb5SPtsGSD0AgGU3T6c8RxKiCm1+N7wtgiBrr5tP0ozQMeHOfQiXWzZnGqVSma3zxnh5eV27dm3evHmDBg3auHEjzGBYn3z11VfDhg27f//+Z599ZhogBlI97r05hXcrKsIvIeMOPo+N+E8Hq+GT6NNsFFvRYUDlS/m3lR5hthABy4CpD6Jt03x6ai0a2L0uMjIyIiLi/PnzPj4+3t7e3t7e/v7+AIBWrVqdOnXq66+/dnBwOHXq1MWLF1ks+OdOM6KwsNBwQMMQlhPdkHoWABDm6hdZ/DLJYC8PVmyRTkdQAADMsQtd0E794igAgIY6M7hjNbK9FdpEaciR6Z0PPsy7mlLR9jKA0DHh9t2oh6d45ruUUmndHiEIMnfu3NjY2Fu3boWGhqammrfzIFbnzJkzOTk5np6eH3zwgWGTMsQS3PpwCqMqGliubP7+0CnTI44UqGTV3LsjOfpyXvLx/u/TzG1uyL2h8BzIq1zeRDEOVjZP8+mp1Xh7N66GxQa6AKmeU6EZxhRdCeL8wNNbjJd+uC+Jzn/pma7J/1d0pj1FEhRFkaRGVjhNr31UubXIF2LXNdcyxcoqn0eSkhWflLwznFTIrdgLk+bJ3377zdnZ+ZdffiHJZuTo2rCqmpGR8eWXXzo7OwMAVq1alZmZ2SBiNKXxiqT+dHymLNBXvrLlUXjA6S3FavMKsu1JRIt/vn8hqzIZ318tU8VPNFaTEwKpA6yiqk1mgyik2WLXkiF78dL3PFjoXqiSiTQvQ4P29WRF5L9cJWR6DEboXE3OWQAAgjBZdh9qpL8bQzYYCW3psHJQ64kHYpW6KtbpEMR+4zasbYB4+gRSWm717iAI8tFHH8XExBw7dmzkyJHwj8L6wc/Pb/PmzXl5eUePHo2KivLz8+vXr19DC9W4QYBbLzOrhACALzr0f79Vl+7nt1eIjJWvkk4K/+uvjNjbIxa15DuYbVWaoSO0pEMgs05khkAaE9DAgjR27PwYssyXfu40BAl1bXm7MMNw2t2NmS7By7UvrShex28USesBoAAAGGcggrC1irOVG/wkzK+Ll+CDo/Fmo48CAACCCL7fyugWIp42zir5CivTqlWryMjIkJCQzp07Hz9+vC4eAakMg8GYNm3anTt3nj592qlTp4YWp7Hj3odTGG1+rXxV8KA9fSYvvHuyz6Ud38Rf3fTo1tTbhzue3dpW4BIzaqkvz7x1BQDIu6nwGsRr/GlhIJC3BxpYkMaIaUQ7u5YMWear6AkD3FuHFz03HDNRpIcbMyLv5SQWy3s0QGianPMAAAAQtv2nWvnhyt7uAICd73QoU+m/uVK1IxSC2H3zPWvgkNIpowlR8dv3qDJ0On3t2rUXL15cv379pEmTiovr5CkQswQEBPzyyy8N8ujGn+zZiEdfbsHtKp0Rh3r6p76zYlXwIIxGK9epR3i1ezrhi++7DGeidFB1UMrcfxXeg23HAQs0p/CbzaGn1k32jFBWSmrYUCBIk+8CpHoKIpT3VhVPjPIznCaVFUwOP5T6zgrDaZpEvzNJtq2/o0EhNLkX5PFfO49NBAgNAKCVHyZ0KRzH7ys3W6bS9/wlcvVQ//e7elXzdMVv21T/HHY4eILu62fVbr1Co9GsX79+7969v/zyy5QpU+roKQ0OVFXQ1F4CiVN7nVI+eO7PcrJOLheKoPa5pkx73IbjTrdKgxBIHWEVVYUzWJDGjp3fazNYwQ7uUr0mTyk1nPoLMRRBUsteriGyvMcgKFuTfcpwyuRNJfB8vTqycrMOHOzsnO6fnX8WkyWp5um8xZ/yFn4snjRS/yTJOv2pBIvF+uGHHy5cuLBu3bqpU6eKxXWyKAmB1BYaHXHvzSmIsNqO2sK7Kr4vA1pXkGYCNLAgjR2uB6YpI3D1S0crBCD93PxuFr7yrh3kw7qe/SpvGr/zd/L4bwCJAwAAQmcLP9NId1CkonLLga78A9M6vXMw9oW4usBXnGkzBd9vFc+crIu9b5UemaV79+7x8fFeXl7BwcEXLlyouwdBIJbjOYCbF241AyvnqqLFcJtaH4RAqgEaWJDGiGlqYYQG+D4MedarBB3DPNtezXsV6H+ANzupRFemeWmBMT2H0dhu6heHDad0RhCd1Vsj2232QSPauXw3vO2oP+9L1NUlAGENGyXcvqts/geaq3Vo+rBYrJ9++un48eOffvrpnDlzpFJp3T0LArEEr0Hc/Ftm/jipEVMVNpJzVeEz3NaSnpntqU3SfHpqLaCBBWmMuLu7m54KWr2K1AAAGOHZ7npBGkG9tKjYdKS3B/NmjskkVteN8sS1FPGyhCWYh2ticW282WfNDfEZFeg6cf9DLV4xpoMpzLABjodOStesUB07+GadspCwsLDExEQmk9mxY0c4lQVpWJw6sVXFuDLf0vyDRiqoMABAkatX5OrderGtJFpjoXJPbZXm01NrAQ0sSGOkQm5ve3+GJPVV3ll3jp0XR/CwNNdYMsyXfTNHjf+XZ5Dh0htz6q58ut1wiiActv2nasnWCkmgjWwZHeDEZcw6nlhl4AYAAABY+2DHfy7Jd25X/LbtzfplITwe7/fff9+/f/8XX3wxZcqU0tLSOn0cBFIVCA14DeTl/lvrSawKKgwAeHFW5juabzMZcoxU7qmt0nx6ai2ggQVpAti3ZZan6kxLRnoHXDZZJfTi0b359LuFr4wwfpeNymc/k+qXYTzprO50VjdN+U6z7dMQ5ND0LgVSzbKzT6uXhN6ipdOpq+oLp6RrVoA6Tik4YMCAxMREb2/vjh07nj9/vk6fBYFUhfcQXu6/VnDDyjwrazne7u3bgUCaCtDAgjQBhO2YkhStaclo78ALOa8ZQyNasq9kvpqgotu15vjPlz383FjCEizEdY/0mmizj2DRaec/7B6VWbb2Wg1ZAlEXV6eTV/DnaWWLZlJqdfWV3xKDV9bff/+9fPny2bNnQ68sSP3jPZSXe0MB3m7HulZCiOI03kO4VhIKAmkCQAML0hipENGusoHVy7lFkVqeKS8zlnR2ZmoJ6pn41UQXL/hrneiurijccIogbI5wpbp8O0mYj4MgYGFX54ccS8j/NSqzevEQHt/hwN80Hl88dQxRVOe5bkJDQ5OSkthsdnBw8NWrV+v6cZAKZGRktG7dulOnTr6+vkOGDJHJKuY5joyMZDAYrf9j0aJFDSJnHcFvgTGFaElC7f6WqKDCmeflXgO5dLYN/o/THMJvGmg+PbUWNvhzh9gAXbt2NT3luNNJHaURv1qSoyHIaO/AcyaTWAgCRvtxzmW8msRC6By77lul95YA8qWLLsoIYHLHqyUbQBV/j7vwmNcX9Np6O2Pfg5zqJUQwhv3Wnazho0vHDdIl1vm4w+Vyd+7cuW/fvsWLF8+cObO83PpJEiFVsWjRorFjxyYmJqanp9NotJ9++qlChaioqAkTJiQkJMTExDx//vz3339vEDnrDt9R/KyL8lrdUkGFM05KW71rm+uDFXpqwzSfnloLaGBBmgb2bRnlqa9NYo3zaX8u54lpSZgnK0eOZ8twYwmrxUSU661M/p+xhMl/DwBEKz9c1YNaCNn/Luy15mrq0fj8GmRCEN6iZYIN28rmTKvT8A1GBg0a9PjxYzs7u+Dg4EuXLtXDEyEKheLWrVvz5s0DAGAYNm/evMOHK/54oqKi4uPjAwICfH19w8LCCgoKGkLSOsR3DD/rQu0MLFP0crIgUuU7CrpIQ5oX0MCCNA0qrxIO9vBPKisoUr8a9zEaMqol52zGa1sF7UJ2KB5tJBTGVT+EI1ypU17ENQ+relYbJ+6Nhb2+vPjsn8Sa/6dkDRrmePiUdN1Kxa5fQN1nQeFwOL/++uuhQ4eWLVv23nvviURmMi1CrEheXh5BEH5+LxMl+fr6ZmdnV6hDo9EWLFiQl5dXUlLC4/Hmz59fTYPI6xiTEpquv6Slpcnlr37YppdMj+VyuWloorprwT2UU5amUhbgb9ZC1kW5eyjn8fPEhu0FbAG2YLYFY/5BU4BVoJo4NtAFSGViY2MrlMRtFEV/Xlih8IM7R3c8izIt0eDkvOsl+QrctFCeuF58Y7RpiV77WFrwDoFXbNCUhDyp65prF58VWSIwXpAvGjOwbOmHpEZtSf23R6VSffnll66urocOHaqfJ74lTUhV4+PjIyMjIyMjHz16lJCQAAAgCMJwKSkpCQCA43hV9969e5dGo1V1tQm9hApcm5bz5A+x5fVNVfjimKyUg5I6EKpRUHmwslWaT08pK6kqnMGCNEYqL/Y7dmSVJGgqFE5u2fGfrNdSBDJRZERL9qm013aV8zp8RaoK1C+OGEvojCAW/z2VeC1FvTYrZkonT7vzc3p8+HfSmcdFNQqMuns4nbgEEJp4Sn24vQMA2Gz25s2bL1++/OOPP06YMMH2lqUakI8//nj8+PHjx49fuXKlg4MDAMC4f1MikQgEAhR9lfwYx/H09HSSfBmlVigUGo9tidbvCjJOVPTurwajCmvKiMJIld8E23TAAs3JM6n59NRaQAML0jRw6couiVdX8E0f6tn2qaTImPjZwAhfzhOxztQTC9Dogt67ZQ8/I9WvTCUGbyIN81GXVxcytIeP/dV5PRefflyzPxYACJMl3P4Ha+io0nGDdA9iLOvW29KlS5eHDx926NChU6dOu3fvpup+jbI5EBkZWVpaWlpaevHiRW9vb1dX1wcPHhgu3b9/v0ePHqaVFQpFu3bt7t27Z7y3VatW9S1x3dNiJL8kXq0qxmuu+jrP/5b6jOBhfPh/DaTZAX/0kKYB24VO59BkWa+FG2XQ0Hd8gw9nvLaJj0VHxrbi/PP6JBbm2JXjP6/87rzX2rT/jNRnahUnq3luJ0+7Gwt7rrj47I+Yip43ZkAQ3kfL7H/cIVk8W7Hnt5rrWwMGg/Hdd9/dunVr//79ffv2ffLkSc33QCwGQZDly5cvWrTo3Llz+/fv37Rp0xdffAEAePr06ZIlS3Q6nb29/Ycffjh//vwrV67s379/xYoVGzZsaGiprQ/KQlqM4mecrMUkloGUv8rbTrevC5EgkEYONLAgjRFTP0Qjzl1YJfEVVwlntu62P/0h9frU1rAW7Fw5nlL2WgI1XsdvSWWeKn2fsQRBmBzH9TrFP7jmQTXCBLry7yzu82N4xqZbzy0Rntl3oNO5G+pzJyUfz6WUVgiBbQlBQUHR0dHTp08fOHDg6tWrtdoqlz4hteXLL79ct27doUOHLl++fOzYsSFDhgAAZDLZkydPCIIAAOzcuXPBggV//PHH5cuXDx8+PHny5IYWuU5oM1WQdsTS+CAGFS5N0ijz9T7DeXUpVwNjdrCySZpPT60F0tTXFBCkyXcBUpm0tDR/f/8KhQ/WiiicCvnetUJ5u9ObD4RN7encwrQwMl9zPVv9XW+h6W4QvPyZ+Gp/x5HRdLs2xkJC90wp/pbr9COK+VUjUqFMM3jXvfFBbt+PaGfJFhNKq5Gu+Ur34K7Drr/o/u1qvsFKFBYWLlmy5NmzZ7t37w4LC6u359YIVFXQxF8CRVB/tUwbc8XXoT2zxsoGFb7zUQHHjd59tUs9iNdQmB2sbJLm01NgJVWFM1iQxohZNXbuwq48gwUA+LBNyO8pFX2eQj1YJAUi8l6rT7cP5Hf+rvz2FIp4VY4yAtn2S1Xir0mipBqR3O1Ydxb3Ds8onXU8QU/U7MWMMFn2m7bzl3xWOnWM6uSxGutbC3d391OnTm3YsOG9995btGgRzK4DsRYIirSbYf9sb1nNVQHw9/fXSYnn/0gDPxTWtWANS/OxOZpPT60FNLAgTQaXbmxRbEU/dwDA3LYhF3KeFqtfm75GEDA3iH8sRaHUv3YDp+1CuqCt7P4npoUYuz+DN14lXkmRimoEcOIybi7sJVHrJ+yPVeosyvTMnjjF6fgFxc5t5Ss+oTRmrMM6YsKECU+ePKEoKigo6OzZs/X2XIhtEzBHmHZEiqst2ib55A9JixF8ridW11JBII0TaGBBmgxcDzqdg5Q/11UoFzLY7/gG702v6EfVUkAPcWceSaloMwl679GJokydsQAATN4UOrOrUrySolSgatgYenpWd1c+s+9v0flSiwwmun875wvhlFpVOm6QPrn+PNAFAsGuXbuOHj26atWq4cOHp6Sk1NujIbaKnR/DvTcnZX/NnliElnr0P3HnL5zqQSoIpHECDSxIY6SqrKJuvThFd80YQEsDQn9PuasnK84qTW3LSxBpK3i7IxhPOOC0PG6lvvQ1m4wlWIhirVTib6oJjgUAoNOQvVM6Tunk0fvXqMeFFm2qQrhc4f/2cOcvFU+fqNjzWz0EfDcSFhaWlJQ0YsSIvn37fv3115p6nEWD2CSdv3RK2FpKETX8hq9+k+TcheUYzKofqRqQ5pMCufn01FpAAwvSGKkqop1bL05RjBkDK9jBva2dy4msRxXK2XRkVnv+7sdyPfna/wd0QVtBnz8l4e+SatOgoAjb/hMa3VMl/gZQFefJKvDlgNY/jg4cvOueJWFIDXDemep8/obmynnxzElkSf2luMEw7JNPPnn06FF6enpwcPDVq1fr7dEQ28OtF4fvgyXvq24SSycjRYdZvTZU3I9ikzSf8JvNp6fWAhpYkKaEW2/zBhYAYFn7sO1PIyqXh7gxPXnomecV72J5j+G0XVh2YwyFm0ZSQNj2nyI0O1XZekDVEFNxciePy/NClp17svpqKmnZpBTq5eP0zyVGp66iEWHqy+csucVauLm5/fPPP7t27Vq+fPmYMWOysrLq8+kQW6LPz+73Vxdry6t0Q3ywpth3FN8hyPanryCQaoAGFqQp4dSRJcvU6aRmRvaRXgEqXH89P63ypTlB/Bs56oxyfYVyXvAqzKm75PZkQJk2SOMIVwIEVZatrnEeq6uX4OGysIgX4nH7Hko1Fds3D53OX77S4c+j8h+/L/9iKaWszq3e6gwcODApKWnw4ME9evRYu3YtXDGsfyrkeG6KOHdm+Y23i1pmPiVU3i1lxklZry1u9SwVBPL2GBM/W6U1aGBBGiOmudBNoWGIWwgn/46ZSSwagqzqOGhd4vXKl4RM2pz2/B2JMm0lxxFByP8AoZU9+PS1UoTOcVhNowmU4q+q93kHALjwmP8u6OnnyOm2LTIh39KYCIxOXZ0v3gYoKhoWqr0XZeFdVsGwYvjw4cOkpKSgoKDjx4833chMTRFDFtgmbWABAHr/5FaSoHm8Q1yhvDxV++/7uQP3eeaUZjSIYPVPVYOV7dEcerp27Vpjsue3BxpYkMaIu7t7VZe8hvBy/zU/6zOlZUexVnmjIL3ypZ7uTH8HbN/TSpGIaZhwwCldcYQi6fsKF9jCL2l0T2XpCoqsIX4xhtJ+GR/0w4h2w3bfOxSXV31lIwiXa79pu/33P5UvWyD99gtSXuskJG9DixYtzpw5s2fPnq1bt/br1y8xMbE+nw5p6mBc2ojTPvFbSpO2i42RU4rvq88Pzeq10c17CK8aFbYxYE8hVdGEwwobaNKRkSFvQEmC5vq03OkpbcxePZ6Z+POTO/fHfIyAinO8WoJaGSUZ35rT17OiawipLhZfCeO0W8wN/OT1K5RGuhvXPuA4bqKhzjXK9rRI/s7B2F4thL9OCOIx6Rb2iJSWy7d8p7lxVbB2E2vEWAvvshYkSf75559r164dOXLkxo0bnZ1r7uabAVUV2NxLkGfrr7yTgyDAox9X9kJXdFfV73cPvwl2DS0XBPK2NOFI7sbU9AAAvV5/2wTTVLWFhYX37t2TSCQNISOkkeLciaWVEIpc8w5Pk3076kjiXM7TypeYKPJpF7vDzxR5iore6zS2q8OwG8pn25XJO16/grAECzDOCGXJUkJfcyLC9m78uE/7ojSk2/bIuDxLlwtpAnvBDz8Lf9sv27qhbP77RLGl2xKtAo1Gmz9/fkpKikAgaN++/U8//QTzGEIshN8Cm/ywVfc1LhxXut8Eu/eS20DrCgJ5BVXv7N+/n8ViGU8jIiIwDGv1HwsXLjSUf/PNN46Ojj179rS3tz958mRVrTVIFyANy7VpOU93l1V5NS+19cmNGlxv9mpEnvrj8FK5jqh8CZdnFZ9spXj8Y+VLOlWEtGCiTh1loYR/J+S7rrm29lqqniAtvIWiKFKrkf28sbBza8WhfRRZixutRUpKytixY/38/A4dOoTjuHUbh6pKwZcAgTQRrKKq9artxcXFM2fO5PF4TCbTWLhhw4bJkyfLZDKRSGQsjI6OtrOzy8nJoSgqPDzczs6uvLzcbJtwwLJJYmNjq7madrz8wsisaiqMu7FvY9LNqq4eSZavjSnTmTN9cGWe6FQb+aNNZi7pUmWFUzSyY9U815QCqXrIrpg+v0Y9L1VYeIsBfVpKyYShJe8M1z17UqsbrUV4eHhYWFhgYOClS5es2CxUVao5vYTqVdiWgD21SayiqvW6RLhjxw4ej3fq1CnTwqioqPj4+ICAAF9f37CwsIKCAgDAuXPnhg8f7u3tDQDo37+/t7f3uXP1GjQI0rBUH9HOdxS/MFqlk1WZEO3nHmO3Pr2TpTCflXZaW549E92RKKu8wo5yPB2Gh6ufH5THrwKvZz1EMX+u8296TYRasrn6UO8G3O1Y1+b3fDfYvdf/on6/m2X5aj69TVunk1fYEyaL358o/fYLsry+l8j79+8fERGxZcuWzz//fOjQoTB8M+QNaD5BKWFPIVVRrwbWunXrduzY4eDg8JoENNqCBQvy8vJKSkp4PN78+fMBANnZ2X5+fsY6vr6+1cRFRF7HuP/Z9D+GtLQ0ufzVXjDTS6bHcrncdCcqbKFxtpBZ8Nw5hJF9RV5VC358x+Xt+y2IPGG2BQQBQzlFUjV+8JmZFhKTixxHRmoLw8ujZsulZaYtJCRmcZ22UYBQlix58Tyqxl4gCPiws/OhUZ4HH+YN3hWTIVZa+h4SErjTZ7vcvAcQpHhgyIufNwGCqIs3WU0Lbm5ujx49euedd8aPHz9u3LjLly/XqgVjOBkjAAKBQJoTdbilBcfxe/fuGY59fHx8fHwMx7GxsaGhoWYjHMbExISGhiqVyqlTpwYHB3/33XeG8okTJwYFBRlPTbGxXTkQC3m2V5JzRT78pE9VFfQkEXLxf0sDQme36W62ghqn1sRIergx323DrXyVwlXlEe9RuEo44CSCVfTb1SkvamT72fYfY+x+lkhLkNQvkZkbb6Z/Eub35cBWDLQWf9jok5/I1q0iykoF321h9gy1/EZroVard+7cuWXLlokTJ3777bceHh5v1g5UVQBfAgTSRGjsuwhlMtn4/zhy5IjZOjiOp6enk+TLtR6hUEiSpFqtdnBwkEpfbcKSSCQV5r0gtk2Ny1KtJwnybio1pVUm68Bo6MGwqStiL1W1UMimI1/3sL9boDmfYSaUKELnCAecogvall6prfDIAAAgAElEQVQOJRTZFa4yuKO5Tps1sj/V5b9YslyI0pDl/fziPu37MLe8y88RMVm1WPXDAoIcj5+3W76yfPlHkkWziJwsy++1Cmw2+7PPPktJSbGzswsODl68eDFMswOpkeazsgx7CqmKOjSwHBwcSv9j5cqVZusoFIp27doZJ7oiIyNbtWolFAq7d+9uDOWg1WqTkpJ69OhRd6JCGhs1LvYz7Gg+I3jpf1cXCqGD0H1l8MBpt4/oSfN2mIBJ+yZEeCtXbdbGAghqF/Irx39e6aVe2oIbFS6iWGue8y6KUitECwi9RQGOfYTsc3O6rxnq/+7B2MWnH0vUlqXWAQAAwBo+xuXWA6x9cMm4wdLvVpHiEsvvtQpCoXDz5s3Pnj0zqOeSJUsM7pIQiFmaj78O7CmkKho4kru9vf2HH344f/78K1eu7N+/f8WKFRs2bAAATJs2LScnZ/ny5Tdv3pw2bVpQUFDv3r0bVlRIYyNgljB5fw1TQcvahzmyOKvirlRVwYFFW91TeDtPfTJdabYCN2CpsN8xadQsRdJ3gHrNrR6hcTnCr1h2s5SlK7XyowBUOZ1myqSOHk++7A8ACNgcviMqEyctnYVGWCzekuUu/94FBCEa1FO+bVM95zEEALi4uHz//ffJycksFqtDhw5Lly7NycmpZxmaOjaQixACsVWsm4uwARwCUlNTly5dev36y5xxOI7//vvvN2/exDBs9uzZI0eONJTn5+dv2rQpIyMjODj4q6++sre3N9sa9GlovlDgSLv0QQc83XpxqqlVplV1u7B9S7fR7/oGV1VHqiV/eFDe3pExI5BnVrFIdZHkzjSEhtn3PUJjVYx1ThIlaslPFCVn2y9HsdYWiv+kSP7puaciuXb7+PYDWjtZeJcBIi9HtnWDNiKct3Ap94O5CKtibPp6oLi4eNu2bX/++ee4ceNWrFjh7+9ffX2oqgC+BAikiWAVVW3y2g4HLJtELpfz+fwaqyVtKy1+qB561Lv6agni/OHX91wbNr+TQ5UO2ko9tSW23J5JW9zRjoGas7IoQp6wWv38oCD0ANNjcOXrevUdtXQHxu7PsvsQQSy1eE4+Klxx8VmgK3/jqIAgt5q7bAqenir76Qd9Uhxv8WecKdMRBrNWt1sFiUTy66+//vbbb2FhYStXrqxmEQGqKmhOL8FCFbYBYE9tksbu5A6BvDGFhYWWVAuYI8y9pqgqbY6Rzo6ev/WaOP7m/nxVlT5bXAz5JsQeoyFrYiSlanOLfQjK7/KDIOygNHqO7P7HFF7RbQtj9+O77KaIMoVoPq55YKYFc7wb7P7sywGD2jgN3hXzwdGEbInawhsBAPQ2bR3++MthzxFt+HVRWGflX39Sep3lt1sFoVC4evXqzMzMfv36TZw4ceDAgZcvX24mNgSkGixUYRsA9hRSFU3+z6nm8xchxCwxK4pwNRX2v5rTvG95HH4kI/7OyI/sGexqqt3IUZ9IUy7tZBfkxDBbgdSVy+5/rC+5J+izj+FqJm4Crnmglu6k0T3ZgsU0uqVBDeRa/Oc7L36NypzV3XvFgNbOPPNPrwr900fyrRv0Tx9x5yzkvj8H4fJqdbtV0Ov1J0+e3Lx5M4Igy5Ytmzp1KpP5alINqiqALwECaSLAJUIA4IDV7FGL8KOB6dMet+G402usvPzB+Xsl2deHzudh1a2mPSnV/ZooG+3HGe3HqcrXUZNzTnZvMdN7DL/rRhqjkoMghWsVJ7WKfxicYUz+dIRmqblTJNduuJF+NCF/ZjevFQNbu/Bqt+qnT36q+H27Nuo2d8Zc7oy5NAfHWt1uFSiKun79+vbt25OSkubNm7dw4UJ3d3cAVRUAAF8CBNJEgAYWAHDAggAQs6JIU0YM2ONZY00KUIvunn4iKbw0ZK6AUZ2blFhNbE+QcTFkUUc7AcP8Sjqlk8riV2myz9h13chuPQOAisYYRZRp5Af16mgWfzqDOwYgNZuABgplms23Mg7H533Q1evTvn4+wuqm3CqDZ2cqdv1Pc+ksa+Q43oeL6G3a1up2a5GcnLxjx47jx4+PGjVq2bJlXbt2haoKxysIpEkADSwA4IBlo8TFxVkec0UvJ48EpI847ePao2ZDhALUJ/fORYsyLw2Z68auzmGToMCJNOXtXPWcIH4PtypnkvSlsdJ7ixEaZhfyP8yxi5l29Jka2R8kXsDiz8A4Ay13fCyQaX6JyNz7IGd8kNuKga3bOJmJOF8NpLhUefSA8uAeRpce3DkLGiQKPACgvLx8z549v/32W3Z2NlTV5jNe1UqFmzSwpzYJNLAAaE4DFqQaUv8qf/Sr+N17fojZDYCV+D7pxr70BxcGz2lv71Z9zTSJftcjmQ+fPrs9X8CswjaiSFX6PnnCaqbnUH6XH1COmbk0XJukle0nSQmTP53BGQQAaomcAACJWv+/yMyd0Vm9fIUrBrTu5Su08MaXomk0qhNHlQd3A4rifvAhZ9J0hFs7Q80qkCSJoihUVTheQSBNAmhgAQAHLIgBCpwfluUznNdpuaUBpY6+SPj0/rm9oZNHewdWX1NPUifTlOG5miltuQO92VWFoKP0csXjTarUPzhtPuQGfUFjmZEE1yZp5YdIQsTif4BxBlpuZqn1xMGHeVvCn3vZsz4O8xvX3hWrTUJDAIDuQYzywG5t9B32mAncWQvorWsIW2V1oKoC+BIgkCYCNLAAgAMW5D+kGbpTvV6MD2/p0N5Sx/D7JTnvhh+c6x/ybcchtJpC92bL8L1P5AQFPgzi+wmq9KYiVAWKRz9oMo9z/Odzg76gMc3k0MS1SVr5XyRexOBNYHBHIYilLlY4SZ15XLgzOiu1RDmvp8+8ni28BLULMUoUF6mOHVQe3oe1acd5byZr+GgEq912xTcGqiqALwECaSJAAwsAOGDZKGlpaTVGBq9M8n5J4s/iSff96BxLZ3eK1PL37hxBEeSvsGnuHLvqK1MARORpjqUqOjgxJvtzndlVzj8RylxF0vea7FMc/3nc9p/SWC5m6uhStYoTuDaBwR3F4I6jobXY8ZdcrPgtOvNYQn7/Vk5Lw1r283OsVWoHSq/TXL2oOnpQn/KUNWIsZ/J0Rqc6d62Aqgqa00t4MxVuisCe2iTQwAKgOQ1YzYo3Dhl8c1YeoaNqjO1uCkGR3yfd2JUSs6PnhHeqTqdjRINT51+ormerwzxZ77Th8LAqjTlCmaN4vEWTeYzlO5kb+DFdEFC5DonnaxWn9eqbdGZXBnc0ndmp8m7EqlDqiEOxeb9FZ+oI8oOu3rN6eNd6Qis/V332pOrvQ4DF4oyfzB4/CfWoeTPmmwFVFTSnl9B8on7Dntok0MACoDkNWBBLIDTU6b4v/MbbdV1VMWNg9dwryZ4Veby9vdsvIeO9uIIa60t15Mk0ZUyhtp8Xa3RLjpBVpZlFakSqlN+Vqbswh07cgKVMz+EAqViZolR61b865UWK0jK4oxicYQjNfPJNs9zPkfwVm3c8Ib+Hj3BaZ88JHdz4TEtDQhger4t7oD7zt/rSOUanrqzRE1hDR9Lsan4JtQKqKgDAmER2zZo1MN8zBNLYWLt27bp16wzH0MCCozakIqoi/FSfF92+cQ6YXbsNd1oC3/T41o7k6M+D+n/avi+DVrMHulhDXs5U3c7V9PJgjm7JceNWeQtFaDVZfyuTf6V0Mk67RexWM8y6ZxG6ZzrlJb0mis7sxuCOojM7Wz6hpdIRF54VH0vIv5MhHtHOZXpXz2FtXei0WqwdUhqN5uoF9eXzursRjN5h7HHvsgYMRTjV5dK2HKiqAL4ECKSJAGewAIADFsQc5WnaswOzem1wbTujFvNABjLk4mX3zz2XlW7tMWakl5lFvcrIdeSVLPWNbHUbITaqJTvQsTq3cZ0oWpW6S5t7kek9muM/n+EaaiZCKanUq2/olJcpshxjD8A4Q1CsleVdKFPp/0ksOByf97xU+W6w+8Rg935+jmitLC2FXH31ovr8KX38Q+aAwezRE5h9ByHs2sU7rQBUVQBfAgTSRIAGFgBwwLJR3j6inSRFe35oVtAih64ra7dWaOBSbvKXsRddWLz1XYaHura05BYdQUXkay5nqjEaGOzD7uPJ4tCrtGlIbZk64y9V2p8UoWb7TWf7vUcXtDNTDc/RqW7pVf8iNDbGHoyx+1qe3BAA8EKs+iep4GRSQb5UMzHYfWIH936tHGs1p0VKyzWXzqovndMlxjFD+7OHj2b2HUhztDQWhilQVUFzegnNJygl7KlNAg0sAJrTgAWpLcoC/PK4bIf2zP5/eKLM2uyyAwAAQFDk4Yz475NuuLP5X3YYMMo7ALFgtY4C4HGJ7lau+lGprrsbc7APu409Vk19fVmiOuOwJvM4jeXMbvUB228ajV05cTVF6J7qVDf1miga6oyxB2DsMBpaQ4hUU56XKk89Kjz9uDBDrBod6Dqxg9vgNs4chqVRuAAAZLlEc+Oq5vol3d1Iemt/1tBRzP6DsMAOlrcAVRXAlwCBNBGggQUAHLAg1YKryJuz8uXZumH/+PBbVGfoVAVBkSezHm15HI6T5Bcd+k9u2ckS3ywAgFRH3snVhOeqKQDCPFmhnixXTtU3UqSuOEKdcUiTc5YuDGa1mMDymYByK++FpHBtgl59W6+OpqGOdFYfjN0LxdpY7qeVJ9WcfVx45nHRw9zyPi0dxge5DfF39nOshZcVhet196I1N65qw/+lCII1YAiz/2Bmz9AaA8RDVQXwJUAgTQRoYAEAByxIjVAgcVtp/ObS3lvc2s2stUuWkav5KT8/iXgsKZzVpvtc/5BWfEvDVmWU6yPzNXcLtc5stLsbs48Hs5oAWhSh0RXc0OSc1uReQHktWT7jmV4jMYeOlUwoitA906uj9Jr7FCXHWL3prB50ZmcEsdRUkmvxqymiC0+Lb6SX8hjo8HYuw9u59G/lWKtpLTw1WXP7X+2dW7rEWKxDJ1bfQYyefbCOnRG6GVsWqiqALwECaSJAAwsAOGDZKFZf7C9N0tyancd2off9zUPQ6s1jl6dKS/ak3Tv0PK6jg8fsNt3H+QRxzBkTlSEokCzW3S/S3ivUunDQbq6Mzi5MX7uqgymQuE4Uqck5r827TOplTM/hTM9hTPfBlTPwkHiBXnMX1zwkdM9QRms6sxud2Q1ltLEwqzRFgUeFsqspomupJQ9zy4Pd7Yb4Ow3xdw5pIbTcW4tSq3X372oiburuRRO52YyQ3oyeoczQ/ljbAPBfYAKoqqA5vYTm468De2qTQAMLgOY0YEHeEhKnkraJ47eUBM516PyFE8uhFlM1FdAS+JmcJ4eex90VZY32DpzeqvMg9zaYZUuHBksrXqSLF2lxEnR2YXR0ZrR3ZLCr9ognFJnavKvagmvaott0u7ZMz2FMj6GYU3cEfS0pEEVpCe0jXBuLa+NIQkRndKIzO6HMTijW0sI1RLWeiMmWXEsp+TetJEOs7NlCGNbSsW8rh+7e9mzM0tdFlom1MZG6e1HaiHBSWs7oFsII6c3o3ovZuRtUVTheQSBNAmhgAQAHLEgtUebrH35XknFa2uEjx+BPHN/GzAIAlGgU/2QmHX2RkCoVjfIOHOfTfrBHGzvM0nDqeQo8UaRLKtGllet97egdnRmdnJkt7ehV5r0h9TpRtDb/mrbwBi5NYTj3YrgPZLiGYU7dEdpr03IUKcO18bg2EdfGU5SazghCGR3ozGAU87NwZkui1kdnlkW8EEdllj0qkHXyFPT1cwxt6dDbV2jPttSbjRAV6x7G6B7E6O7fdbkWBVUVjlcQSJMAGlgAwAEL8kbIs3RxG0szTkn9p9t3WOJo3+ZtEx4XqGRnsh9fzE2+K8rq5dJiuGe7oZ7+gfauFt6uI6iUMn1SqS6xRCfREG2FWIADo50D5iegV7VOR+kV2qJwXVG4rjgSl6Zijl0Zrn0Zzj0wx2409mvPJYliQvsE1z0mdI9JXIQyWqOMIJTRjo4FIKiZYKeVUeqIBzmSiBdlkS/ED3LKvexZPXyEoS0dunnZt3fjYahFFhtUVQBfAgTSRIAGFgBwwLJR6ifplbIAf7xDnLxP4tCeGTjfwW+cHcqqdTSHim3iuqt5Kf8WpF/LT9WTRH/3VkM8/Ae4t/bhWupfL9ORKWX65DJ9SpmuQEn42tEDHRhtHTA/Ad2OYd6UofRyneiuThSlL7mvL42lsRwxp+6Yc2+GSy+6sIPp5BZFKgh9Gq59TOhTCF0yQuOjWBsUa4My/FHMH6HV/M5xknpaJH+QI4nKLIvNlWZJVEFu/C5egs6egq5e9h3c+Ywq7C2oqqA5vYTmk7cO9tQmgQYWAM1pwGpW1GfadkJHZZ6VPdsrKYlVtxxn13qywHMgF2W8raUFAMiQi+8UZfybn3an+AWG0MLc/Hq7+HZz9Ork6GlhrAcNTqWV61PL9CkSfaZUz6bT/IWYvxDzE9Bb8Okss25bFIlLk/WlsTpRtL7kPi5Lp9sHYI5dMIcumFNXujAYQVkmVXMJXTqhTyP06YQuHaHZGSwtlNEGxVohtJpzDSl1REK+NCFfGp8njcuTPi9VBrryunrZd/UWBLryO7jzBayX64lQVUFzykVYnyrcsMCe2hIwF+FrwFEbYi1UhXj639LnJ6TlKVqf4fwWo3g+Q/ksp7dy0jKSLiuNKs6MFmXGluZlyMWdHDy6Onp1dfLq6ujVVuCMVkr/XBkKgGIlkSbRp5XrM6V4rhx3YtNa2GFePLSlgO7Foztz0MoGF0Wo8bIkvThBL47Ti+NwaSrK9aQ7dMEcgun2QZhDJ5Tn858LPEXieYQujdCnEfrnhD4TABLF2qBYSxrdB8V8aVhrBKnBvUylI5IKZHF55YkFsqdF8idFcicuo50Lr70bf+vY9lBV4XgFgTQJ4AwWAHDAgtQBqkI884Is56oiP1wpaMPwHsJz78NxD+Uy7CxyNqoRmV4TW5oXV5oXJ86LE+cVqeWdHDw6O3h2cfQMErq1E7jwMGaNjRAUyJfjuQo8R4ZnyvB8BaHSkz52dE8e3YOLevHpLfh0IauSwCSOy9P14ni8/KlenIhLHpG6crqgLV3Qjm4f+PJffmtAwwAAFCkhdM8JPIvEcwh9BqnPQmhCGuaN0lvQ6N40rAVK90FogmqEJCkqq0ydLJI/LZKvGNgGqiocryCQJgE0sACAAxakLiH1VFGMKveGsihaWfxQbd+a4dab49yV7dKVLQxk0qoOrFArynXqBHF+vDg/oSz/WXlxqlTkyuZ3cfRqJ3BpJ3AOsHdtY+dkyc5EuY7MleMFSiJfQeTJ8UwZTlKUMxv15NE9eagnj+7GRZ3ZKBd7TWxKL8elqbg0GZcm4+UpePlTQpmLcr3p9gF0u7YozxcV+NP5rVCOF6DRSLyIxHMJPJvEcwl9NonnAAqn0T1pdG8a3ZtGd0PpXjS6h9m1RaiqAL4ECKSJAA0sAOCAZaM0woh2pJ4SxamLY1SiOE1JnFqRq3fowHLuwnLuzHYIZAoDmEyhdRYTKUClSUuTygqSpcUp5aJUWUm6rJRBQ9sJXALtXf34jq34jv4CZx+uvQOzhrjtCj0pUpF5CrxAQRQo8CIVUaIiMBRxYaPuXNSVi7qwUQc2zYmFOnNQ4/oiReoI2XNcmoLL0ghFFi5NI+QZpKYE5fmiPF+U643yfFB+K7qdP8rzRRgsEs8j9TkEnkcRxQSeQ+JFgNLS6N40uisNdUZQNxrqQkNd6Mx2UFWbz3jVCFW4joA9tUmggQVAcxqwII0KvZwsSVCXxGvEjzRlzzSSFB2dhQgDmcK2TMO/dq0YPG/MKs7yAIBSjTJZKkouL85UlD2XlaZJS3KU5ThFtrFz8rdz9uHZ+3CFLXjCFlyhO4fvxOJWk5daoiVLVESBkhCpiBI1UaomxWpCoiWdWDQnNurAptkzaUIm6symObFRRzaNh9EAABShJeTPCUUWocwllDm4LIOQpRGKbIrSo9wWKK8FyvGgsVxRrhfK9aHxXBEGjULkJCGiiGKSEJF4Md/1D6iqcLyCQJoE0MACAA5YkEaDsgCXJGvKU3Xip5ryVJ3shU5VhPO86PyWDL4PxvfB+C0YPB+M74NxvaxjeMn0mvT/jK0chSRHWZ6tkBSqZeU6tSdH4MO19+U5eHIFriy+J9fOlcV359h5cQVs1EyYUD1JiVREqZoUa4hyLVmuIUvUZKmaEGsILQGETJoTm+bERvkMmiOLZs+k8Rk0IZMmZNF4iIJQ5BDKbEKVT6qLCVU+ocgmlDmEIhtQBMr1orHdaCxXlOstCNkOVRWOVxBIkwAaWADAActGWbt2rQ1sYif1lOyFTpapl+foFDl6eY5enq2X5+hVhXqWI8rzYbCdUH4LjO1C53pgXA86y4nOcUFZTnSM91be9HqSyFNKc5SSbIUkTyUt0ShyldJitbxQJctTSekIzZnF8+IKPDkCJxbXkclxYnGdmFxnFs+ZxTUcM1G6SWuUREOWqolSDSnXkaVqUqYlZTqyXEuWaUg1TvIZNAGT5sRG+RhiOOYzaHYMhE/X8vQFXLyYoRcRyjxe0HKoqs1nvLINFbYE2FObBBpYADSnAatZYduflSIoZSGuyNVrSglZlk5dQqgK9MoCXCXCNSW4upSgSIrjSuf7MFhOKNuZzhSiGBdhOdLZLnS2M8pyorMcUTobYQjexOtLrteKNIp8pbRALSvVKMVaZalGWapRijSKUo2yVKss1SgZKN2JyXVh85yYXCcWl48x7RlsJybXkcVho5jBCHNkcjh0BpfOlOsoqY4sVRNyHSXTkTIdKdeRch0p01FyHSnTkTqCsmPQ/hjibMPf1EJs+4dtCuyp7dF8egqaroFFEMS2bds+//xzY8mTJ09u3ryJoujw4cNbt25tKMRx/PTp0y9evOjcufOwYcOqaq1ZffLmQzP/rLiKVBXjijy9poRQiXCdlNArSE0poRLhmlJCU4prxASuJnE1xXJEmUIU49HYTnSMR2MIaCxHOp2NoGwayxFl2NEYfJTORlhOdDobYdijKAOxZHpMpteUaJQlGkWpRinWqhR6rUSnNphfGgI3GGRirVKF69WEnkdnCBhsByabj7EYNNSRybFjsOwZbHsGW8hg02k0PsZCKOaUVgE2/02PHDnSr18/Ly+vqio0nx827Knt0Xx6CqzVWap+0Wq1c+fOZTKZxpK///7b1dV15cqVn3zyCY/Hu3TpEkVRBEEMHDiwV69eX331VcuWLVesWFFVg/XfhWpYs2ZN42mztjdaUr/6OtVcre0l2/6sb9Og6b24llTk68ueaYruqbIuytL/KX/yhzhuk+j+6uLoLwpvzs7bGnjl/LDM031fHA1M+8svdY/w2R/cpzuQx3udk//ySz3aPu3vrs+3tbx5fljm1Uk5/87IDZ+fH/15YcyqorhNosTtpU/+EKcdLd8weY8oXo1rSVxLlj5Si59qpBlalUivlRJr1qzREniZVvVCJo4tzb1d+PxaXurRjPjRP67a/OjWV7GXFkSf/DDq70m3/hr9795G9U3rgj179tBotJiYmGrqmH0JVf0eGqTcWo1X9bkbRJg6fahVemotYeq0vE57Wtvyun6oVcarejVIY2JiZs2axWAw0tPTNRqNoTAsLGz8+PGfffYZAGDRokVKpfKvv/46efLkZ5999vz5cwzD8vPz27Rp8/Tp05YtW1Zus1HZ1HUhzBu3WdsbLalffZ1qrtb2km1/1rdpsFb3mq1MkUBTiusVJK4iCS0V2m3Av1du6OQErqIILamTkoSO0stJXE0SGkonI04cPzWow2hJihYAIGjNAAAQWkonIwgtpZeTAACUiSAogqtIBEU4rijTgZ76JNWV7gsQ4NCeCQAoe6pFaGCRNqjxfFPrUlhYOHPmzOzs7MzMzIiIiJ49e1ZVs1a/9gYph8LANwCFqaa8VtBrrmI9UlNTf/jhB19f39DQUGOhj4/Ppk2bRCKRRqOJiIg4cOAAACA8PHzw4MEYhgEAPD09g4ODr169umjRovqUFgKxSRAaYLvQ2S4vT9PAfZ/hvGrqDzv+6Z5Hy8w3hSAURRFaisQpjEujCEpVTGjE+KfBQ/OVGYAEpY80AACnYBappxbZWbsnjYbs7Oxhw4Z99NFHzs7ODS0LBAJpLNSrgTVr1iwAQGxsrGnh9u3bx4wZg+O4UqlUqVR6vR4AUFxc3K5dO2MdV1fXoqKiqpo15k9tDNSFMG/cZm1vtKR+9XWquVrbS7b9Wd+mwVrd+/bftPoKVV2iM62TVqhJ0LNnz2pmrSpQq197g5RDYeAbgMJYhTo0sNRq9datWw3HYWFh/fr1q1yHoqh33333u+++Gzp0KADg119/nTFjxvPnz0mSNO0zgiA0mvnx2lYXHSAQSKNl9+7dIpEIAODj4zNjxgzLb4TjFQTSfKhDAwvH8cTERMOxcW9gBdLT0yMiIi5dumQ4HThw4Mcff6xWq93d3Q3jl4Hi4mI3N7e6ExUCgUAsJyUlJScnBwCg1WobWhYIBNJIqUMDi8/nnzx5svo6zs7ONBrt5s2b48aNAwDExMT4+fmx2ez+/fuvXLlSp9MxGIzCwsLExMQBAwbUnagQCARiOT///HNDiwCBQBo79eqDVRmhULhu3bqZM2cuWLBApVIdPXr0yJEjAICJEyfu2rWrb9++Q4YMOXbs2Ny5c/39/RtWVAgEAoFAIBALaYDN8AUFBfv27fvmm2+MJfHx8ZGRkUwmc/jw4b6+voZCgiDOnj2bkZERHBw8fPjwehYSAoFAasuGDRtmzJhRTaBRCATSfGhE0YYgEAgEAoFAbINmtJUaAoFAIBAIpH6ABhYEAoFAIBCIlYEGFgQCgUAgEIiVgQYWBAKBQCAQiJWBBhYEAoFAIBCIlWngOFhvQGpq6uXLlzEMmzRpkqura1XVjhw50q9fP7hfukkDP6LNUOFTSiSSEydOSKXSESNGBAUFNaxs9XrVKmUAABVlSURBVImFw5cN8Msvv0gkEsMxi8X66quvGlaeuoAgiG3btn3++efGEhv+YUdHR1MUFRoaajg9d+5cQkKC8erChQttINuKWq0+c+ZMXl6en5/f+PHj6fSXBtKdO3fu37/v7u4+ZcoUBoNheYNNbAbr+vXrPXr0yM7OjomJ6dq1a0ZGhtlqf/7554wZM/Ly8upZPIgVgR/RZqjwKfPz8zt06HDz5s3CwsK+ffueO3euYcWrNywcvmwAmUy2fPnyFy9e5OXl5eXlFRQUNLRE1ken0y1cuNA0oKMN/7AfPHgwbty4qKgoY8n69evv3r2b9x96vb4BxbMKZWVlQUFBhw4dUigUW7du7dWrl1qtBgCsXbt2xowZEolk9+7dgwcPrl1PqSZF+/btd+3aZThevHjx7NmzK1QoKCgYMmSIv78/hmExMTH1LiDECsCPaDOY/ZSLFy+eOnWq4fjEiROtWrUiCKLhZKw/ahy+bIYrV660b98+Jibm8OHDqampDS2O9bl7966/v39QUBCTyTQW2uQPG8fxJUuWCIVCHx+fjRs3GgoVCgWDwYiKijp06JBhZssG2LRpU2hoqOFYq9X6+PgcOXKkoKAAw7CUlBSKonAc79ix48GDBy1vsynNYJWUlDx9+nTkyJGG09GjRxuzRBvJzs4eNmxYYmJirebxII0K+BFtBrOfMjw83KjFo0aNevHiRWpqagMJWH9YMnzZDNHR0enp6WvXrj1z5kznzp137tzZ0BJZmdTU1B9++GH//v2mhTb5w9bpdCiKPnnypEOHDsbCe/fuEQTx8ccfX716dcKECe+9914DSmgtZs6ceejQIcMxnU5HURTDsKioKG9v77Zt2wIAUBQdPnx4rdS2KflgFRcXAwDc3d0Np66uriKRiCRJGu2VmdizZ8+ePXs2jHwQKwE/os1g9lMWFxcbtZjNZvP5/KKiooCAgHqXrl6xZPiyGQxzdbNnzwYAXLp06Z133hk/fryHh0dDy2U1Zs2aBQCIjY01LbTJHzabzd6+fXuFQjs7u9WrV69cuRLDsIKCgoCAgNOnT0+cOLFBJLQWpj5kmzdvBgCMGDHiwIEDxm8KAHB1dY2JibG8zaZkYJEkCQBAEMRwiiCITY5NEIhtQ5KkUYtBs1HkZjV8TZ061Xg8atQoLpcbGxs7duzYBhSpHmg+P+zu3bt3797dcOzh4TF48OCoqKimbmAZIEny22+/PXbs2PXr13k83lt+06b0+Q2GpEgkMpwWFxe7uLjY6i8YArFV3N3djVqsVqtlMpkN7D+qkWY1fB0/fjw9Pd14SpJkc1jubz4/7IiIiIiICOMpQRC28X1lMtmYMWOio6MfPHjQunVr8Po3BQAUFxfX6ps2JfV2dnYODAy8fPmy4fTSpUuDBg1qWJEgEEht6d+/v1GLr1y54unp6e/v37Ai1QPNavjau3fvtm3bDMfXr18nSTIkJKRhRaoHms8POzIycvHixQRBAABKSkpu3749dOjQhhbqbVEoFAMGDPD09Lxx44aTk5OhMCws7MWLF8+fPwcAEMT/27fzqKaOtgHgAwlCDgIqsihBrOwIKkUkogIhLizK4gKtBNxwo1ZbAbVILQoKKNDieqwielDbQqmVIqgcQbaEKBQqJgSQHZQqS0UNiSz3+2O+9568gNZqcnirz++vuZPJzHMDec5z750MXL9+/R99bf9NjwgRQnFxcatXr75//35XV9e1a9c4HA5CqKCgICgo6O7duzQabbQDBAD8jT179tjb2/v6+hoYGJw+ffrs2bPSN+HfYyOmr/dSTEwMi8USi8WamppnzpyJj48fP378aAcldx/OP/bnn39+8eLFxYsXz5s374cffvD09HR2dh7toN5VeHg4n8+fNWvWli1bcI+Pj8/ixYvDwsKcnZ0DAgKKioooFIq/v/+bz0mJiIiQS7DyYWxsvHz58u7ubjqdfvz4cQMDA4SQRCIZGBhwdHSkUCjSgxcsWKCurj5KkQLZgD/ie4P8U2poaKxdu3ZgYIBCoURFRb0HqfkNjZi+3kuTJ09es2aNSCSiUqkHDx50dXUd7YjkRU1NzcHBAbff+39sKyurKVOmIISUlZUDAwNpNJpIJFq/fn1oaOhohyYDzc3NM2fO1NDQUP8Pc3NzfX19JpNpa2vb2dnp4OAQFxenoqLy5nMqEAQhv4gBAAAAAD5A/6Y9WAAAAAAA/wpQYAEAAAAAyBgUWAAAAAAAMgYFFgAAAACAjEGBBQAAAAAgY1BgAQAAAADIGBRYAAAAAAAyBgUWAAAAAICMQYEFAAAAACBjUGABAAAAAMgYFFgAAAAAADIGBRYAAAAAgIxBgQUAAAB8WPr6+kY7hPcfdbQDAKPmwIEDubm50j0WFhYnT54crXjeRXZ2dkdHh7+//9+OvHXrVmVl5RdffPFPlxAIBFeuXNm7d+9bBQgAGAGLxfLw8NixYwfZ88033+jp6W3atEl+i7a1tfn5+d28efPp06erVq3KzMwcO3bs2021a9cuGxsbX19fsmfp0qXPnz8fMszFxYVCodBotG3btr193P/tzZPecMePH+/q6tq3bx+kNbmCAuvDJRAIFBQUNmzYQPZoaWmNYjxvrbu7OzQ0tLi4+E0GX7x40cPD4y1WsbCwCA4OLiwsXLBgwVu8HQAwXH5+fkFBAYPBsLOzwz18Pl8ikch10d7e3vz8/MHBQSUlJUtLSwqF8tZT3bt3T1tbW7onICDg5cuXCKF9+/bNmTNn6dKlCCFDQ8OGhgZlZeV3jJz0j5LecEVFRUZGRgjSmpxBgfVBMzQ0ZLPZQzpXrVq1cuXK1NRUGxubsLCw5ubm+Pj4+vp6CwuL3bt3T5gwASEkkUiOHDnC4XCMjIwcHBzKysqio6MPHjyopaWFLz0FAkFwcHB2djZCSCQSJSQk3L17V0dHZ/v27ZaWlgihmJgYOp1eX19fWlpqYGAQEhJiYGCA35iYmNjc3GxlZRUaGvry5Us2m52amoqLv/Ly8sjIyF9++UU64ISEBHd3dw0Njbi4OAUFheDgYIRQdHT0w4cPjx07hhBKSUlpamoKDw8fHBzMzc318vLy9/dPSUlBCGVnZ8fHx2dlZY0ZM6aysnL//v0///zzJ598smXLlvT09KamJhsbm127dtFoNIRQcHDw7t27ORyO3P8wAHww7O3t/fz8Kioqht9GqqqqOnr0aEtLi7m5eUhIiI6OTltbW1BQ0MqVK9PS0tavXy8UCvX19e/du1dRUTF9+vSwsLBTp05xOBxzc/OIiAh1dXWEUG5ublpaWkNDw4QJEzZu3MhkMsn5+/r67t+/PzAwkJKSkpSUJL10cnLyRx99VFBQcP78+e7ubicnp23btuFSrKWlJTY2tq6ubtmyZcNPx8fHBze+++67WbNmkQm2qKgIp5GYmJi/jXnEdaWRSY/NZq9bt47FYiGEfH19Fy9ejK+Zg4ODmUwmlUrFtVRmZqaqqmpgYOCCBQuSkpJyc3O5XC5CKCoqCtKa/MAeLDAUl8v9+uuvvb29GQxGW1vbzJkzaTTazp07RSIRg8HAF5dsNvvWrVvh4eFmZmYbN26srKxECFVVVdXX1+NJenp6CgsLEUKDg4NMJpPH4+HSysHBQSAQIISEQuHWrVsNDQ0PHz78+PFjfKO7traWwWBMnjx5z549bW1tLi4uenp6HR0dqampeNpz587p6OhIR9vf33/y5MlPP/0UIaSvr09mybNnz547dw5fSp4/f55OpyOEOBzOjBkz7OzsLl++/OeffyKE0tLScnNzeTweQujXX3/FKb6kpGTr1q0rV66MiIj46aefoqOj8ZxMJrOuru7u3bty/fwB+KBERkaOHTt2+/btQ/rLy8ttbW11dXWDg4NfvHhhbW3d1dXV29ublZV14cIFPz8/ExMToVC4adMma2vrxMTEGzdumJmZ0en0uLg4LpcbFRWFECosLPTy8po7d254ePi0adPc3d27urrIJSQSSX5+fn9/v4uLy/H/UFBQUFRUpNPpGRkZHh4eDAYjKCgoIyNj3bp1CKHnz5/Pnz+/v78/NDS0vLx8yC6L16iurn7w4AFC6G9jHnFdadJJT01NLT09HSHU0tKSlpZ2+fJlfF6nT5+ePn16e3t7XFycQCCIjo62sLBwc3Pr6enx9vbGt9bw80pIa3JEgA+Vr6+vvr6+u5SnT58SBKGnpxcfH4/H7Ny5c8mSJeRbrK2tk5KSWlpaEEINDQ24c/Pmze7u7gRB+Pn57d69G3dyuVxVVVWCIDIyMsaPHy8SiXD/l19+6e/vTxDEmjVrVqxYgTvv3LlDpVLxcl5eXrhTJBIdPHjw2bNnsbGx8+bNIwiir69PW1u7uLhY+iyKi4vHjRuH23/99ZeSklJra2tdXZ2hoaGlpWV+fn5PT4+Kisrjx48JgggJCfn+++8JgrC1tb148SJBEFOmTPH09Ny/fz9BEHZ2dunp6QRBGBgYHDt2DM95+PDhhQsXkst5e3vjwQCAd0ehULhcLp/Pp9FoaWlpBEGsWLECpxE2m41zBcZgMA4dOlRbW4sQKisrw51r1qzx8fHB7dDQUAcHB9xOSEhYtGgRQRB//PHHtWvXcKdIJFJSUuLxeHiS3t5enMq6u7vJVaKiooyNjTs7OwmC+Pjjj6Ojo3F/Z2cnlUp98ODBhQsXDA0NBwcHCYIYGBgwMjI6cuTIiKdmY2NDvp0giA0bNuzYseNNYh5xXemZpZPetWvXjIyMCIJISkry9PSk0WhisTg7O9vKyoogiOTkZC0trYGBATxYVVW1qKiIIAhfX9+9e/eSE0JakxN4RPhBMzAw8PLyIg/JLQLGxsa4IRAIqqurXVxc8GF7ezufz582bZqqqurUqVNxp62tbWtr66uWEAgEAwMD3t7e+LC1tZVcZcqUKbhBo9H6+/sRQtXV1TY2NmRnWFgYQojNZu/du7e5uZnP56upqdnb20vPX1NTQ0aioaHh4OCQk5MjkUicnZ2pVGpeXl5HR8fs2bPxE8bMzMy8vDyEkIeHR05OzuzZs5WVlVevXn3q1KmgoKDKysolS5a8KjbM0NAQZ2cAgKxYWFgcPnx48+bNDAaD7KypqfHz8yMPbW1thUIhbpMJCiGkp6eHG2PGjJk0aRJuKykp4bvXlpaWPB7P09Oztrb25cuXg4ODg4ODrwojNTU1ISGBw+HgjRBVVVVpaWm3b9/Gr1IoFIFAUFNTY2lpqaCggBBSVFS0trZ+i/N9fcwjrmtoaCj9yZBJj8Vitbe3NzY25uTk+Pj41NTUlJSUZGVleXp64gF0Ol1R8f8fVamoqEhnMxKkNTmBAuuDZmpqGhgYOLxfSUkJN9TV1efPn//ZZ5+RL2lra0skkt7eXolEgkulFy9e4JcUFBTI5EV2qqur0+n0iIgIcgYVFRXcIL/2JE1NzWfPnpGHWVlZ9vb2kydPZjKZqamplZWVw38yIxaLyWgRQh4eHjdv3uzv71+xYgWVSsUbOHCuEQqF48aN09XVxcNcXV3nzJnDYrGcnZ3Xrl175coVJpOpqqo6PDaCIKQ/GbFYPPwTAwC8i23btmVlZQUEBIwbNw73aGlpPX36lBzQ3d1NbtKS/soPTyPSoqKiUlJSEhMTbWxstLW1X7PNvKSkJDAw8MqVK6amprhHTU2NzWbPnTuXHGNkZCQQCLq7u8keMtH9I6+PecR1pQdIJz1lZeVFixbduHEjLy/v22+/5XK5ubm5WVlZP/7444hrSWczEqQ1OYE9WOB1XFxciouLTUxMGAyGubn5xo0by8vLTUxMTExMTpw4gRASi8V4tzhCSEtLq6SkBH+ByV1TLBarsbFRUVER/1AoMTGRHD/cwoUL09PTcf4qLS319vYeGBhACAUEBFy9evX69evDt+RPmjSpo6ODPMS3pgoKCphMJpPJvHPnzm+//YYLrKtXr5K/H5wxY4aSktKJEydYLNbEiRONjY0jIyPJa77XePLkCXnFCQCQoeTk5Pv37+NfxiCElixZcuHCBbxlqqGhISMjg7yV/uZ4PJ6rq6ubm5uOjk5qampfXx9OKUM0NjZ6enoeOXIE7xbHXFxcioqKbG1tGQzGmDFjvL29xWKxm5tbSUlJeXk5Qqi+vh7fEZetEdeVHjA86R09enTixIm6urrOzs7JyclisZh8FDAiKpWK75ZhkNbkBAos8Dpr1651c3MzMTFhsVimpqZWVlYeHh4UCuXSpUuJiYkMBsPS0pK8Qtq0aVN1dbWZmZmxsTF5nYRLMVdXV0dHRzMzM6FQuHPnzlctx2azXVxcTE1NmUymq6vrmTNnNDU1EULe3t4VFRVGRkbS98kxOzu75uZmcuPq1KlTdXV1dXR0tLW1J0yYYG5urqmpiR8oZGRkSJdQy5Ytq6qqwj8pYrFYra2tI/4maIiysrIhzygBADKho6Nz7tw5spjYunXr/PnzTU1NnZycbGxstmzZ8iaXQENs3rz5/PnzOP/ExsZOnTp1xP0MO3bsEIlE+Da2k5OTk5PT9evX4+Liurq6jIyMnJ2dWSxWSEgInU63srKKjY1lMpmOjo4LFy40Nzd/19MeZsR1pQcMSXru7u5CoRCXhk5OTm1tbR4eHvgh5qvY2tomJibibfII0pr8jO4WMDCK+Hy+UCgc3s/hcPAeT1JHRwePx2tpaZHulEgk5eXlHR0d0dHReJM77vz999+bmpokEklBQQE5+MWLF2VlZQKBAG8OJQiiqqqK3Ln5/PnzvLw8cnB7e/udO3ekd54SBOHo6Hjq1KkRT8TBweHSpUvkYVVVFZ/Px22BQCAQCHC7sLBQ+l2PHj0i98s/fPiQw+GQL3G53I6ODtxubW0tLy/H7ba2Ng0NDfxTAADAu7t9+/aQLxSPx6urqyMP29vbS0pKnjx5gg9FIlFeXh65a1s6jdTX15NffOmvbWdnZ0lJSXV19eDgIJ/Pf/DgATmJWCzOy8vr6+urqKjI+2+PHj3Cb29sbOTxeF1dXdJBPn78mMvl9vT0CASC5ubmEU+ttLS0qamJPBQKhbW1tW8Y86vWJQ1Jelwut62tDbc5HM7Dhw9x+9GjR6WlpeSwoqIiMq9WVFTgpSGtyY8CMdITWQDeXExMTFFRUWZmpvyWqK2tnTNnTkNDA7k/Q1pOTk5kZGRBQYH8AsAOHDggFosPHTok74UAAOA1ZJj0IK3JDzwiBP/rli9fbmFhsWvXrhGrK4TQokWLJk2adPPmTbmG0dnZefXq1a+++kquqwAAwN+SVdKDtCZXcAcLAAAAAEDG4A4WAAAAAICMQYEFAAAAACBjUGABAAAAAMjY/wHMIdLjdVtNLQAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -579,9 +620,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 19,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -632,9 +672,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 20,
    "metadata": {
-    "collapsed": false
+    "scrolled": true
    },
    "outputs": [],
    "source": [
@@ -644,14 +684,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 21,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -701,5 +739,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/examples/gnuplot-magic.ipynb b/examples/gnuplot-magic.ipynb
index 3f76c39..e24bb1d 100644
--- a/examples/gnuplot-magic.ipynb
+++ b/examples/gnuplot-magic.ipynb
@@ -24,13 +24,11 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
     "\n",
     "# inline plots for matplotlib\n",
     "%matplotlib inline\n",
@@ -50,15 +48,14 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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0dmCv09MRFsnmmgq+WrubgI8+59rF85g5I1s0Ewn9MqaCQENDAzabrV9PxCNN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\n7ruPuLjunbIWi4Wjn37KutHdtwiNjIwkvDqWknPVJI2L6vd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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f527f6fe198>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -72,7 +69,7 @@
     "x = np.random.rand(N)\n",
     "y = np.random.rand(N)\n",
     "colors = np.random.rand(N)\n",
-    "area = np.pi * (15 * np.random.rand(N))**2  # 0 to 15 point radii\n",
+    "area = np.pi * (15 * np.random.rand(N)) ** 2  # 0 to 15 point radii\n",
     "\n",
     "plt.scatter(x, y, s=area, c=colors, alpha=0.5)\n",
     "plt.show()"
@@ -88,13 +85,11 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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By2q/L3VHDABgrlG4zwTDPi77yEUdxCy9e3w5dOggzChVZckcjdAdUEcjvft8KSZ6KOQa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\nT31hZXm+JKukxXc6TFp8ubSuXK7jQec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\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -112,15 +107,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Use the `%gnuplot` line magic for to change the inline plot options"
+    "Use the `%gnuplot` line magic to change the inline plot options"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%gnuplot inline pngcairo size 600,400"
@@ -130,13 +123,12 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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d7zO8gzCZUifLuUrTdyjI0ueD9AwcDVqqcdzMVuOy4lv0VyAQpoVuIAyc2LZXsW7Lpmvz\ntfrZtz7xzHV9r+5qTY6Esb4zlxTL1t9da1Zp8pd99b65voYWSGN/hr0FQkrRjbrejwLQa41XggPx\nQG885yoWG/tDdpSHrnwYKLyRxYc9e4E66iO8HVH2vkKsaAbC+FBja6hkeRn1RGP6iiU5A8c7krOj\neMXtN+mPPP/aeXcsMnhs12td5bevlE4r12mQCbL3H4Fi1mYGCCFNrkJXqBw6DcuEPNK9z194g47B\nzmrjFd2kvwI9t3imZ3+g6Aa28uEIIYShohuhTiodNAMhEfaEMbXh0yMTMLURJ4L+aNL0AzPd8PMX\n/6nzOwssKnXeyp8rHtm2eR5b62GCM3girCtUagsUrH5L0Q06WCbklSsfsDv6QQjlLdV4O2KhoTir\n3wJSFw8SQ6dC+SvYWiCkwCaK9NAMhDKNWU2GvOHhyEeEPBGZzpC8Iy7S9Ozn79t/6+6LnkjY3vBi\n7Y7bVm/rmuzpxJLYbDZ61yYAbOdFKYU36Hr2w7PBIz37/UU3szkzQEimwApWamF5mD/6Dgdz6jVK\nHbuF+sW36K986CfFXiZls9mw0Wh+IM27osieV6e7fLidSoaS3pajg7OWz9F89gOJgQNvtpQ88J0v\nzDGq8Ky61Rtv1598q2GyRXwyiSQCIWsbJ5IV3qDrPxJMRGGZkBfcbREijsyVrOdFim6CLBmPsLeD\nMJmuUKnNVdhPi7ydgs1mI0ej+YF0hyf6xRvXoJ2btx4eCPk79tgeP1K2fm2l6rP/X26tW2hse/m3\n+zr88Zi7Ze+2PYNFy0tZLBIQjliAGDoVYq+WegRulpvm4oPHRf5sCMWV9wMln2d99IMQKr4Z6mV4\n5MqHfnYXCD8FmyjSQHueblj13N5nS1+5Pl9rKN947rbtuzdXKVG06alKvP6FrgRC+pW/fPvZ+e9/\nrdygVFlqHmn+4rY3f1Crmv5zxa/3QCB3MeupEkrRjbCJgi+62dxBmMxap44FoYaQF2I+wtkUyVvK\n+qgXQSBMC0Z/UskUDOPRxWTAoUf7NNmKqx/PycB3db3rO/2c/a4PyzLwXWAKZIL8fW7LVxsq2K6Q\nouxbd6Xwel3tg5YMfBeYQudffGd/5Vj9fmkGvivmJ16a1bK+v1qhlVDjMJrhQ0K/Kb7pO8T8WXST\nmbVKN3giFA+JfQ2d94ZOhbUFisxEQQS7CXmjZ3+giP0FQopSL7PWqQdPwlLIDEAg5EYiQrqaIjn1\nGVotVeplWfPU/R/Ds8GxKx/4i2/OxAIhpegmfff74q8h5L8rH/ozUCkzIu8aDZxNOCMQCLlhPxs2\nV6oymbsouhE2UXCv92BwFgtn0U3GUKLETXJ3KxzOzKWwI+HtiOUu1kz/owzJu0Yz+AkEwhmAQMiN\ngaPBzKycj4Cmo3wweCKUd01G73vuNRooGOZWzz8CBSu1MgWLjYTGyL1GO/AJdJqdAQiE3Bg8Hspd\nkrkRIkIo/1qt/WwYTiTgkK8rJlMg3awMLRBS8pZoBiAQcqr3QICNI+mnYJ6rivmI4AD0FUoVBEJu\nDBzL9IxQoZFZ63A7NB3lzsAnwQxPBxFCOYs1cFo9twaOBfOXZ/a+YygXsqMzAYGQA2FnIjgQt1Rn\nejtlLrwTOTV0IpSTwYUiSu7VGmdDmIhJaGMSrxAx0tkUyV6U6SYieZAdnQkIhBwYPB7KXaxh9fCB\nCeUu1gxBUTV3Bo6H8jKbD0cIKbQyQ6nK0QD1MtxwnA8by1WZ6ZuRLO8azQDMCFMGgZADA8eCuRlP\nkSGEchfDchF3SGQ/Hc65OtOBECGUt0QzeBwmB9wYPBHKZL3oCCo1CjtnUgSBkAMDn4TyruHg2bDU\n4IHeWMQN5yJzwNUaUWfJ1VkcnMWZuwRS4pwZPBHK5WL0o8lR4Ba55wJkAlICgZADg8e5CYSYHMte\nqIZ6GU5kvk54RO5i2EHBmaETnN33vKWQHU0VBMJM83ZE5SpMV6jk5NthcsAVrlJkCKGshWrPhSg0\n2Mu8RJh0tUaz5nNz3A4sE6YOAmGmDRwL5XIxHaTkXg2BkBsczgjlKsxSg9vPQCYg0+xnw5YaXK7O\ndFkcJfca7cAxWBtOCQTCTOMqL0qBHRScIOKk43w4p567+w6ZAC4MHg9ylQZACOVcpXY1RRIR2Dkz\nPQiEmTZwjINd1SPMlXjEmQg7oF4mo5wNEcNspdLA2eMGy4ScGDwZ5qRShqLQyMyVKsgEpAICYUYR\ncdJ+lpsa+mEYyq5Xw27CDBs8HspdwtnoB1EzQgiEGTfIXaUMJW8pbKtPCQTCjHKcjxhKVSojl7/2\nPMiSZRyHlTIUay3u74GdMxkVDxK+zqi1DufwGqDRWoogEGbUwLEghwuElByol8m4weNBbmcGsHMm\n8wZPhqzz1DIlN5UylDyol0kNBMKMGuRoK30yqJfJMKqGPnsBNzX0I6BeJsOGuE4DIIQsNXhwEGoC\npgeBMKMGPsn0oRPjGctU8SAR7IcjWjJk6EyIwxr6EVAvk2GDJ8OcB0JMhnKuUsMAaFoQCDMn5iN8\nnTFu1wwQQgiD7tsZNXSCg17b4+Uu0UKn2UyieutzfRUob6l2EOplpgOBMHMGjoey6zleM6BA9+1M\nGjjOwelL45nnqqKeRGgIMgGZEPUkAr2xzB+1Nh70l0kFBMLMGeRBXpSSczXMCDNnkIvTlyaAodyr\nNUMnoV4mEwZPhnPqOThqbbz8ZdqBY/CwTwMCYeYMfMLxpqIRsKssY2I+wt8ds9RynQ9HCFGn1cN5\nTBkxeCKUs5jj8iiKtkAhU2HejijXF8JrEAgzZ+CTUP5SXgRCfZESyZD/SozrCxG/wZOh7IVqmYL7\nmQFCKG8JpMQzhA8loyMgOzotCIQZEuyPJyKEoZT7NQMKdN/OjKGTPHoh5sDOmUwZPMnNMYQTyl0C\nSyHToB8ICfexrfdWKjEMw3KWbtjeNv73TbiO/OLuuQoMw7CC636wt1eSq/X2s+HshXx5MBC1TAjv\nRPbxJx+OEDKUKBGJAj2QCWBX2JkIOxKmCl7kwxFC2QvUjnOwNjwVuoGQ9OzffNfTjgcP9AV8nTtW\nHHxo9ZaG0WciE/1/vP9LW2WPHR8KOs8/bX3b9vwZKb5/HefCWQv48mAgaLSWKRyevjShnKshO8q6\nweOh3KvVGG/SbVkL1HYIhFOie68CJ7btVazbsunafK1+9q1PPHNd36u7WpMjYaJn938drvrpr79Z\nn62xzPvWWxdObuFNpiiTHOfDWfN4sXhOGc6SwQktbIq4E2FH3DSXRwOg3Ks1Q6fgnciuoZMhLhvr\nj6MvVibCJOycmQLNQBgfamwNlSwvo97wmL5iSc7A8Y7kAWf44oFOc5Xzl6t0VGr0+3t6JHk7HOfC\n2Qt5FAi1eQqFVga1ZKxynAtb5/FoZoAQylqgdp6HQMguvqUBEEJZkB2dEs1nlAh7wpja8Gn3KExt\nxImgP5o0z0j4Bp2X3/kg/9kWb2Dg6A/VL679+mu9k3W+w5LYbDZ618YjRIx0t0V5UkM/ApqOss1x\nPpI1n0ejH4RQ1nwcsmRs4/ywkfFEtkxos9mw0Wh+IM1AKNOY1WTIGx6OfETIE5HpDHjSVWEqLW66\n8Uf/cl2xQZu7dIPtPuOJtxone/uSScQUCN2tEcNspULDp6kBQjn1aji0k1XOhnDWPH6NfkxzVKGB\neMxPcH0hohW2J2J+wsib+nBK1ny1/Vxk+p8TCJvNRo5G8wNpvpoV2fPqdJcPt1ORjfS2HB2ctXxO\n8lgIL72mODE4EBy+UJJACpwfm6oyyH6WX3lRinWe2tEAgZBF9rPhLJ7dd0yOWWpwuO/scTSEs+ar\nEc/ecVkL1A5IiU+O7hxFv3jjGrRz89bDAyF/xx7b40fK1q+tTB4Lqebc982KY499/5UGZ3Dok222\nN8Kfu28+v7IG7HOcj1h5liJDCGXNVzsbxDNI5B0SORv5VSFFgeUiVjnOh608SwMghKzzcFdzhIhD\nddzEaCfrDKue2/ts6SvX52sN5RvP3bZ99+YqJYo2PVWJ17/QlUAIKSu++/YrX+764fwsXe7yXys3\nv/HbO7L5lSJkn+NcmPPj6MYzlqtCQ/GoF7JkrPB2RlUmOW6Rc30hY2XNVzvOwwCILc6GCA9HP0qd\nTF+o8FyA4riJKWh/Amao3/R6y6bXk/9MVftkW+TJkf9VsmbrgTVbaX+TcNnPhbP4FwgxGbJU486m\ncP4yXrQCFxkHL286QihrPn7pbS/XVyFajoZw5ToT11cxAWo3oaWGd7NVPpDa3IwDYWci5icMJUqu\nL2QCkB1lDw9LRinZCzWQGmULiVxNEWsdH+971nzYOTMpCISsc5wNZy/g3eI5xToPd0LdBDsc58NZ\n8/k4+lZny+U4Bi3X2eC7HFPoZGor7/LhCPrLTAkCIevsPGuulixrHtSSscVxno8Lw5Ss+XDfWeFs\n4OnoB0GR1JQgELLOeT7MzxQZGt5dBM8G8xIR0tcVM1XCO1Fa+NZJMZmpXBVxJSLuydqZSBoEQtbx\ns1KGoi1QIBKFBiXZ9Y5Nzsawaa5KruJlQhwKR1njaIhY+RoIEYasdZAJmBgEQnaRCZK3i+cUK2RH\nWcDbShlK1nwcbjobeNhLKFnWArVDRP1lGASBkF2ei1FtvkJl5O/vOWse7oDCUabxtlKGYq1Tey5G\nE1HYXs0kIk66L0T5vD8B1oYnw98XtDjwOS9Ksc5TQ+Eo43i7iZAixzHDbKW7FQZATHK3RfVFSoWW\nvy/VrAU4rA1PiL/3TBwc5yN8fiEiGCSyw8HjCikK3HfGORv42FwtWfYCteN8mIReUuNAIGSX4xzv\nX4jzcGdTBE7oZVDYnkhESH0RH1sojIB6GcY5Gni9MIwQUpnk6iw5nEI6HgRCdvE8RYYQUpnkuFnu\n7YRngzH2syGe33QEOyhY4OTx3okRcN8nBIGQRTEfERqKm+bw62Sy8WBywCyel4xSoHCUcQ7ep0aR\n6E7oZQoEQhbZz4WtdTjG+99xFjRaYxTPS0YpxlJV1JMIO2F7NTPiQSLQEzfN5fuo1wprwxPh/Uta\nyPifF6XACb3McpwXwn3HoGCYSc7GiKVaJeP9oeMwI5wQBEIW8b90kAKpUQaRBHI1R6y1cN+lxdEQ\n5m9PmSTmSlWgNx7zQ+XoKBAIWcTP83jHs9Tg3nbYXs0Mz8WIJpfXLRRGwA4KBjn53FwtCSbHzNW4\nsxEGQKMI4HEVKpLfjQeTUNurPW3wbDBAEJUyFNhezSAHj8+dGAOyo+NBIGSLtzOqMsrUWXw8mWy8\nrPlqaLTGCGEsECKEhm96GLaQMoLP506MAQXD40EgZItQKmUocEIvUxznBDMzwM2whZQZYWciHuR7\nC4URcELveBAI2eJsjAhlhIhguYg5zgbBzAwQbK9miPN8OGsejvheMTosaz5UC48FgZAtzqaItVYY\nMwM0vIMCUqN0xQJEoDduruT7ZrIRUDjKCKHUh1M0uQqEwSmko0AgZIurOWIRTiA0zVGFBuMxHxRV\n0+JsiJircUwukKkBLBcxRChlcSOsNWpnEwyAPgOBkBUkgdxtEUuVYAIhJkOWatzRCO9EWpyNvD6X\ndTxIiTOC5+fxjmepxV3NEAg/A4GQFb6uqNoqVxqE9Ou1zlPD7iKanE0Ra52QZgbmKtzXGSNiUDlK\nA4mcjQKbEVpqIBCOIqQ3tYAIKy9KgY6j9LmaI3w+oHw8uQrTFys97VA4mj5fd0yhxYSyUYpircEh\nNZqMfiAk3Me23lupxDAMy1m6YXtbaLKfG9pzfw5mXvuPAO2v5D9Xc8RSLaQXIoK6CSYI8b5ba3EX\nvBNpcAqkuVoySy3uaoZR72foBkLSs3/zXU87HjzQF/B17lhx8KHVWyYsPkz0v7Fh499UWmFstKFN\nKN0mk1lqcWcTPBvpiweJ4EDcWCawf+PmatwJWTIanE0Ra53ARj/6QmXMT0RccPbIMLqBMHBi217F\nui2brs3X6mff+sQz1/W9uqt13FOV6Pvjhs1Xvv2bdcVCSh/Q4GwSWIoMIaQvVMYDRMQNz0aaXK1R\nc4VKQCWjFCssF9HjbolYawQ26kUYslTjrvGvaqmiGQjjQ42toZLlZdQ/A1bNaeEAACAASURBVExf\nsSRn4HjHmOxooue1B78/8L2djwqqjIAWV4vwAiHCkLkKd7fCclGaXM1h4d10qJugzSm0hWGKpQZS\n4p+hGQiJsCeMqQ3q4UEwpjbiRNA/6hiDxJWd3/yh8193PFKNC2yonK5gX1yuEtjiOcVSAysH6RNc\npQzFUoO7WyMk7CBNl7tVeAvDCAZAo9EMhDKNWU2GvOHhyEeEPBGZzpAU8eKXX17/RPBHOzdVpdJs\nA0tis9noXRtnnE2CnBkgyJLRI9BAqNTLcKvc3x3j+kIEKTgQx2SYOlt4o15rrVq4a8M2mw0bjeYH\n0gyEiux5dbrLh9upZCjpbTk6OGv5HM3I/0+6Dv1+X8/B71aoMAzD5z3dOvDaDfrSx85M8vsnkwg3\nEApx7wQF6ibocDVHrAIMhAgmBzQIdPSDBJ4atdls5Gg0P5BusYx+8cY1aOfmrYcHQv6OPbbHj5St\nX5vUaRHLWXt45FIjDT+pyvvqfn/nLxYJ8l9OqpyCfSHCjDBtRIz0dsRMFcK975AST4cQN8xQjOWq\n4EA8FoCcOEIM7CM0rHpu77Olr1yfrzWUbzx32/bdm6uUKNr0VCVe/0KXNAsQXQIsGaUY56gCPfFE\nGPqMzJinPaovUsiFuQ5uqYFMQJoEWRaHEEIIkyFzhcrdBsVxCCGkoP0JmKF+0+stm15P/jNV7ZNt\nkSfH/qSq7qmWftrfx39C3ERIkSkwY5nSc1Fg/aL4wNUcsQjzpiOELDV4604311chSK7myOzbDFxf\nRZosNbirKZxTL9R/twyCFmsMi7gSiQipLaA/wuAGTA7SI9y1IgRrhDTAfRcHCIQMczYK+MFA8Gyk\nS7iVMgghTY4CyeCAuhmL+YmIO2EoFlgvoRGCLhxlFgRChrmahXQe73iWagiE6RDoruoR1ho13PeZ\ncjVHzFWCOZh+PEEXjjILAiHDnMJsLzICZoTpIJG7NWIWzvGT40FKPA3CLRmlmCtVvsuxRBSK4yAQ\nMk24JaMUSzXuvhAlE/BszIDvcgw3y1VGAT9NMABKg3BLRikyJWYoUXouQuEoBEKmCT01qtDKNDly\n32XoMzIDwm2hMAICYRoEvTBMgewoBQIhk2J+IuxI6EtSaSfHX/BOnClXc1gEL0Q4qXWmhL4wjKjT\nKKGXAgRCZrlaIuYqHBP4LxUC4UyJ4IVoKFZGvYmoR5o9MNJBxEj/5ZhxjuBHvbA2jCAQMkvoC4QU\nKBydKUFvJhuGIXMl7oJDuFLmvhDVlyjlKsHWjCKEYNT7KQiETBLBzADBIHHmxBAIh7NkcN9TJYIF\nQkQVx7VBcRwEQkYJvVKGYq1Vw/p56qh96JocofYSGgGTgxkRx+hHoZVpchXeTqkXx0EgZJJLsCcR\nJlNnyTEF9BlJlXBby44BxzLPiND3ToyATACCQMigRIT0X4mbBL54ToE+I6kTRz4cwSFcMySOGSGC\ngmGEEARCBrnbIsZypUwp7MVzCiwTpk40L0TjHJX/ChzClRoSudsi5kox3HdIiSMIhAxyiqJklGKp\nVsGzkSLRBELqEC73Bbjv0xNBL6ERsJUQQSBkkGjWihBClhq1qwVeiCkR1QAIJgepEc3oB43cdGkn\nAiAQMkaEzwaYTtRLRD0CPohnDEstrA2nRDSVMggh3CxX6GT+HkkXjkIgZIzQW9EnM5QoI65EzEdw\nfSF8R/USEu5BPGNAvUyKxPSwI9gxBYGQKSSBPO1Rc6UYSkYRGukzIulnIxXi2Dk6AoqkUiSy+26u\nUkn8YYdAyAxfZ1STI1doxfP7hOxoKsSUD0cImatUnovQZ2R6zuawWUQzQksV7oZACOgbTpGJCHQc\nTYVL4Ocwj6HQyLR5Cm+HpJeLphV2JMg40uYJvpfQCHMV7pZ2m1kIhMxwt0UtIguEMCNMgas5Avdd\nakRw/OQYliqVxKvEIRAyQ4Qzwhpc4s/GtBJR0tct+IN4xjBXSn25aFriaLedTF+iCjsTMb90i+Mg\nEDLD3RoxV4nrhVih8l2OJaKwXDQpb3vUUCz4g3jGMEt+uWhaTnHlwxFCmAyZ5qjcF6SbHYVAyAx3\nm9hSZDIlpi9Wei5K99mYlrtNbGkANFw3ATd9Ku6WqJj2TlAs1bhbwhkgCIQMiPmIqJfQF4lkV/UI\nc6UKJgdTEF8+HCFkroJtM9NwNovyvqvcbdK97/QDIeE+tvXeSiWGYVjO0g3b20JjfyA+sO+p28vl\nGIZhhqo7nv5wKEH7O3nG1RIxV6hEs6t6BBRVT83dKrYKKYSQbpYiESYiLtE9pQxJhMlgf8xQKrpR\nr7QHQHQDIenZv/mupx0PHugL+Dp3rDj40OotDaN+m4meXfeveR5973Cv339lz329z3zl0QM+ml/K\nN65WEY4Q0fCzAVmySblEtzBMMVXg7ja47xNzX4gYy1QyhdiGvZYqSI3SEDixba9i3ZZN1+Zr9bNv\nfeKZ6/pe3TVqXEEi8+e+8+xzG5cV6HSFqx745+pg8wW3yEabbtEGQklnS6Yl1vsOmYApiDINgKgi\nqbaoZFtv0wyE8aHG1lDJ8jLq0AVMX7EkZ+B4R3J2VFF4509+voGqsYr3vv9mZ9mdK/Pk9L6Vb8T6\nbEh8kDi1sDNBiGtX9QgYAE1BlBVSCCGVUaY0SLf1Ns1ASIQ9YUxtUA/nCTC1ESeC/glL7mO9ex+5\n9d9iP9z1/bpJs0lYEpvNRu/aMkesKTJNroIkUNghsgk8M9ytEYsYbzqS/HLR1FytEfG0FB5NQDtn\nbDYbNhrND6QZCGUas5oMeT891JoIeSIynQEfe1WE68jPbq7/7tDmj/b9aKF28o8jkwglEJIE8rZH\nxXFW9XhQODoZseZFEeygmBLcdz6w2WzkaDQ/kGYgVGTPq9NdPtxOJUNJb8vRwVnL52hG/QzhPvj4\nDat3r/zDide+VasT2xoz8nfHcItcqRfnRhSYHEzG1RoV6wvRVAGttyfluSDOdRAk7TMo6L6+9Ys3\nrkE7N289PBDyd+yxPX6kbP3aUYkDYvDNb9zzp1Vv7PvZ9VkiWxqkiHIz2QjoxjsZd6vYWiiMUOpk\n6my5v1uiy0VTCA3GEULqbFG+yZClWjCpUcbRnscYVj2399nSV67P1xrKN567bfvuzVVKFG16qhKv\nf6ErgZD3yP/sHbr0wvUW2afJ3KxvHAwwcek8Ib7masmggHAyor/vsHNmPHebaNMAiEr/SLU4jn7N\nG2ao3/R6y6bXk/9MVftkW+RJhBBC5rs+FHeKxSXemQGCAsJJkAnS2xEzzRVtIDRXqdytkZIv6Lm+\nEH4R645hirFUGRpMxIOEmM5VTZHk/oMZ5xbvWhFCyFyBey5FibioxzIz5+2MafIUCo1oHx9YG56Q\nW7wlowghTI4ZyyTaXli0T3LGiLiMHiEkV2PaPIWvC5aLRhH3TUeCKiDMJBEvDFMkOwCCQEhLLECE\nHQl9sdgaDyYT0O6ijBFxDT0FbvqERFwqTLFUS3QABIGQFndb1FShwuSi2xSSBOplxnOJtJfQCH2x\nMuKS9Emt4xFx0tcVNYnrHOYxJDsAgkBIi7tF5KkSBK23JyLuklGEECZDRmmf1DqetyOmm6WUq8U8\n6pXsVkIIhLSItblaMigcHU/c1YMUyASMIe5KGYqF2kEhvdo4CIS0iH6tCMELcZyYj4j5CH2hmBeG\n0ac7KLi+Ch4RfaUMQgi3yBVqWbA/zvWFZBoEQlqk8Gzoi5RRLxH1wnLRMFerOM9hHkOyBYSTkUIa\nAEk1OwqBkAYSuS9ETRUiz5YgDJnmqDwXJPdsTEYKaQCEkLlSogWEkxF3W5kR0swAQSBMn78npjTI\ncLM4Gw8mg8lBMleraA8bSWah1oalt1w0GdFvHqVI82GHQJg+lwRKRinQejuZ6EtGKSqTXKmTBXqh\nlwJCCEW9RMxH6GaJfGEYSXUrIQTC9Im7uVoyC9RNJJHCwjAFds6MGC4ZFfvCMKLWCKXXehsCYfok\nkipB1IwQdlBQSOS5GDVVSCQQwgBomEQqZRBCxnJVoDeWCEsrJw6BMH3SeTYsVbi7LQrLRQghX3dM\nZZKpjJJ4cKRZNzEhiVRIIYRkCswwW+Vpl1YmQBLPM0uk82woDTKlQebvgeUiCd10JNW6iQm520Te\nVC+ZBJdCIBCmKR4iggNxw2zxL55TJNuEcAzpLBAiKJJKIoW2MiMkOACCQJgmz4WoqVwlU0hg9Rwh\nJNVasvFEf/5AMmOZMtAnueWiCZDIc1ESe2YolmrJHVUPgTBN0lkgpJgrpdhvYjx3myT2TlBkCsxY\npnJLvpcCtTCsNEjlbWmuxN1t0hr1SuXWMk4ibSZGWKBwFCEkjfNGkknwnTiepBaGEULmSpVHYg87\nBMI0udsiZtE3V0sCy0UIoXiICA0lpLMwjCRZNzGepBaGEUKaXAVJorA9wfWFZA4EwjS52yS0ZoAQ\nMpTCchFyt0WN5Upxn8M8hll6y0Xjudui0qmUoZgrpXX4GgTCNHnaJFRFhqjlolKV56KEno3xpJYi\nQ1RqVPLH80qtIAAhZK6Q1lIIBMJ0hO0JkkCaXAXXF5JR0HBLUpvJKOZKSI1KcwCkktQACAJhOiRV\nOjgClovcEksDIIQ0OQoMQ6EhyZ3UOkJqO4YppkqYEYLpuNsiZml0m0wmwW22Y7jbIpJaGKaYpH0w\noeeitHYMUywSK46DQJgOCS6eI6ikl9J5I8mkVjcxhjRvuqlC5WmPkgTX15EpGQiEhPvY1nsrlRiG\nYTlLN2xvC7H/lWxzt0VM0psZSPwsguBAHJMhdZb4z2EeQ+IDIFerFNMASp0Mt8j93VJpL8x6ICQ9\n+zff9bTjwQN9AV/njhUHH1q9pUHwL1Op7Z2gSHy5yN0muYoJisTPoJBmQQCSWCaA9UAYOLFtr2Ld\nlk3X5mv1s2994pnr+l7dJeyniiSQpz0qqd30I0wVKslODqSZIkMSeyGO55bkjBBJLBPAdiCMDzW2\nhkqWl6kRQghh+oolOQPHOwSdHfV3x9RWuVIvxeVVKZ9BIcGSUYqpQuW5FCXiEu2l4LkguT0zFHOl\nyiOZNrNsv82JsCeMqQ3q4ZIrTG3EiaA/OskzhSWx2WwsX1uaJPtCRBIbJI4hzXw4QkihkWnzFL4u\nqSwXJQsNxkkSqbMltzCMEDJX8rdK3GazYaPR/EC2A6FMY1aTIe+nnbmIkCci0xnwSS6bTMLfQCjV\nVAmS9nKRuzVikeRaERoeAEnxvkutt34ycyV/10FsNhs5Gs0PZDsQKrLn1ekuH26nkqGkt+Xo4Kzl\nczQsfyur3BeiJkkuECKqcFSSL0QyQXo7o6a5Un0nSmxX2QiXhEc/xnJVoFcq7YVZX+jSL964Bu3c\nvPXwQMjfscf2+JGy9WuFnViU5q5qimmuRJeLvB0xbb5SrpbWruoRkq2X8Uj4YZcpMEOJynNJEgMg\n9is+DKue2/ts6SvX52sN5RvP3bZ99+YqYTcrknK2RLLLRVLOiyIJrw27pFoqTJHOACgDbaMxQ/2m\n11s2vc7+N2VAIkIGemPGUmHHcjrMVbi7LWKaI62oIOU0AJJwm1l3m7QHQFVSGQBJcQ8AHZ72qGG2\nSqaUaIoMUZMD6S0XSTkNgBDSl6jCzkTML5mOWwghamG4I2qU2JgvmblCKkfVQyCcGXerdPdOUCyS\nrJdxSfu+YzJkmqPyXJTWAIhaGFZopPuSlE5KXLr3OD0ST5Gh4Rmh5AKhxGeECCFzpYq3u8pYIvGF\nYSSlNUIIhDPjuSDR5mojJHg8byxARFwJfZF0F4YRQuYqXCJZshGS7S47QjdLGQsSEXeC6wthHQTC\nmYGZgb5YGXFJa7nI3RoxzVVh0n5WpJMlG+FqlWgvoc9gyDxX5ZHAUfXSfrhnDlKj1HKRWwLPxgh3\nm0S7TSaTYmpUws0UR1BV4lxfBesgEM5A1JOIBQhdQQb2nPCa1A4mhAopJKVK+hHuVqmnRpFkMgEQ\nCGdgOFUi3a0TwyzSGCSOkGy77WRqq1ymRMEBqZxGGfMTETch8YVhNHzymvgfdgiEMwCpEorUthJC\n0QRFUgXD7raIuULqC8MIZoRgPM8FmBkghJBJMkXVFHdbRLJt1pNZpJQddUOlDEKI2jd8IYLE3l0Y\nAuEMwIyQYqnCXa3ifzYowb64HJeprVI8kW4M6ewqQ1QLBWlvIqSoTHKFRhboE3lKHALhDMBaEQW3\nyBVqWbBf5M8Gxd0GL8RhkkuNwsOOEJJGTQAEwpSRyHMRUmTDpHMwoUvC5zCPIanCUbe0z51IJoVM\nAATCVAV6YwqNDDdDigwhhMyVuER2lbnbopAPp5jmqrydUSImiZy45yKsgwwzVfD3qHqmQCBMFeRF\nk5krxf9sUGAz2Qg5jukKlN5O8Z9GGeiNw6h3hLkSUqPgU1Apk8xcJZXlIhgAJZNILwU35MOTSGEH\nBQTCVLkvRGGBcIRFGoGQiJG+y1GpnUI8BSnUTSAY9Y5mmqvydYk8JQ6BMFWuFkiRfcY4R+Xrjon7\n2UAIeS9F9YVKOS75ZkKfMlWIf3KAhvdOwMM+TI5jullKb4eY7zsEwlS5WyOWang2hslVmL5Q6b0k\n5mcDQV50HKmkRiV/yMwYlirc1SLmhx0CYUoSUdJ/JWYsh2zJZ6RwMCHsqh5DCnUTCNqsj2OuFvkA\nCAJhSjwXo4YSlVwFKbLPSGFyAE31xjAUK6MeIuYT82mUMOodz1KNu1rE/LBDIEyJuyViqYYHYxRz\nJe6+IOZnA8HC8HiY+I8j8LZHDcVKGPUmE31TIQiEKYEX4nhSOIMCFobHs1SJfHIAh42MBzNCgBBU\nkU3EIvbUaMSdiAXhHOaxRL827IJzJ8bR5ivIBAo7ElxfCFsgEKbE3Ra1QCAcTTdLGQsSEbdonw03\nnMM8EUs17hb15MADmwgnYq5SiXhSSD8QEu5jW++tVGIYhuUs3bC9LTT2B+ID+566vVyOYRhmqLrj\n6Q+HBPjmhBTZBDCRZ0ddLXDTJyD6futw3yck7mZSdAMh6dm/+a6nHQ8e6Av4OnesOPjQ6i0No35Z\niZ5d9695Hn3vcK/ff2XPfb3PfOXRAz6aX5phwYE4hiF1NjQeHEvc/WXcrREL7J0Yx1yFuy9ESfHW\njbpaImYIhOOI+2GnGwgDJ7btVazbsunafK1+9q1PPHNd36u7Rv22SGT+3HeefW7jsgKdrnDVA/9c\nHWy+ILBsmrslYqmBB2MC5iqViM+ggIXhCSl1MrVV7u8WZ+vtsCNBJpA2DxaGxxL32jDNQBgfamwN\nlSwvUyOEEML0FUtyBo53JGdHFYV3/uTnG6g4Eu99/83OsjtX5glrbgUvxMmIu5YM8uGTMYu3cNTV\nAi0UJibuh51mICTCnjCmNqiHCwowtREngv7oRB0oY717H7n132I/3PX9OoH9O4MjOicj4mUDMkF6\nL8VMcwX2bzUzRNxLARYIJ2OqEHPr7TQCYaLrhXqMctU2l1FNhrzh4V8OEfJEZDrDuB7FhOvIz26u\n/+7Q5o/2/WihdvKPxpLYbLaZXxsr4NmYjLlS5WmPEnERPhvezpgmT6HQQln1BCxVoj2WGY6fnAyv\n2gvbbDZsNJofmMZzLp/98GmScurhBQvqdJcPt1PJUNLbcnRw1vI5mlE/T7gPPn7D6t0r/3DitW/V\n6qa8YDIJfwIhFE1MRqGRafOVPjGe1OpugZs+KUu1aKuF3a0R2Cg1GTNvsqM2m40cjeYH0h3w6hdv\nXIN2bt56eCDk79hje/xI2fq1o/bgEINvfuOeP616Y9/Prs8S1tIgJREh/T3QeHBSFpHuLoKF4SmI\neo0wCiWjk7GIt16GdubHsOq5vc+WvnJ9vtZQvvHcbdt3b65SomjTU5V4/QtdCYS8R/5n79ClF663\nyD6dw2Z942CAiUvPDM+FiLFUJVPCtuqJWarFuUzoboUWCpPSFyuj7oT4Wm/DOcxTE/HaMP0qYcxQ\nv+n1lk2vJ/+ZqvbJtsiTCCGEzHd9mBDyEpILKmWmZK7Ch06Pa6IgfK7WyNz7TFxfBU9hMmSaq3K3\nRXKu1kz/08LhaY/qi+Ac5klZqvGW7W6ur4IVUAswDaiUmZq5CneL8cROWCOcmlmM9TLwsE/NXCXa\n7noQCKfhhqNZp2SpFuELMeJOxAKEbpaS6wvhL1HWy0DJ6NS0eQqSRGG7sBqipAQC4TSgimxqulmK\nRJgIO0X1bAzvHIUM2eRE2YIZFoanJdY6KQiE03C3wRrhNMS3rR5GP9MSZedJV0vEDOdvT8ki0q6K\nEAinEuyLy5SYWpD7PjJHfO9EF+TDpyPK1tvuNhgATUN8o14KBMKpwAsxFeLrxgtFE9NS6mW4RVSt\nt0NDcTKBNLnQbnsqYu04CoFwKvBCTIX4TmqFoolUWMS1q8wFh8ykwFwlwiIpBIFwavBCTIXIDmMi\nE6S3I2augEzANPjTcIsR0Fs/Faa5Kt/laGLCcxWEDALhVKCKLBXmStzbIZ629N7OmCZHDu22pyWy\n1tvQUjgVchVmKFZ628U2KYSnfSpwVnUq5Dimm6X0dojk2YA0QIpEliWDhz1FouylAIFwUokwGeiL\nGUthV/X0LFW4Syz9ZWBhOEUiWyOEPTMpEl9NAIJAOAX3hYixDNptp8RcLZ53IuTDU6QvUUVciZhf\nDFsoElHS1x0zQrvtFIivShxBIJyCqwVGiKkS01ZC2DOTIkyGjHNU7jYx3HfPxaihRCVXwah3eqI8\ngwIC4aTcrXAyWarE1HgJ1ghTJ5pdZdBSOHWWKtzVLIabngwC4aSgiix1onkhRj2JmJ/QF8LCcEpE\nUy8DC8Op0+QqMBkKDca5vhAmQSCclKsFZgap0uYryAQKOwTfetvVGjVXQrvtVImmXgbSADMivsJR\nCISTcrfBszED4jiOAFJkMyKaTIALKqRmwlIttlNIIRBOLNATU2hlaiu0206VOLrxQopsRsyVImm9\n7W6F+z4DlhqRDIBGQCCcmLMxYq1Tc30VQiKOwlFIkc2I0iDDzTL/FWG33g4OxDEMqbNh1Jsqay3u\nbApzfRVMgkA4MWdTxFoLL8QZEEeWDFJkMyWC7dXuVugpMzOWWtzVJOybPgYEwom5mqEV/cyYqwXf\nXIZMkN5LUXMlrBHOgAiyZNBCYaaMpaqwMxH1Cj8n/ikIhBNzNoatdfBszADVll7Qrbc97VFdgQLa\nbc+IpUYt9F1l0GV0xjBkqRbVbkJ45ifmao5Ya2GNcAbkKkxfpPQIuS29syligXz4DFnrcGejsF+I\nLtgxPHMWcS0TQiCcQLAvjikwWDyfKaEvE0KFVBqsdbizUdgvRKiQSoO1Ti30AVAyCIQTcEBeNC3W\nWmFnSyAfngZNjgKTY8F+ofYZSYTJQG/cNBdmhDNjrRH2wz4GBMIJuKBkNC1CHyQ6G+G+p0PQk0Jn\nc8Q0VyVTQDOhmbHW4U4RFY7SD4SE+9jWeyuVGIZhOUs3bG8LTfZzQ3vuz8HMa/8RoP2VbHM2wQJh\nOgT9QiQTpOdiFFJkabDUCniZENIA6TGUqsL2eMwnksJRuoGQ9OzffNfTjgcP9AV8nTtWHHxo9ZaG\niR6JRP8bGzb+TaUVRDNjFxRNpMVSg7vbomRCkIWjVMmoUgc5khnLqlMLd3IAC8PpwWTIXCnsmoBk\ndB/7wIltexXrtmy6Nl+rn33rE89c1/fqrvH9RRJ9f9yw+cq3f7OuWBD1J87mMKTI0qDQyrT5CoEW\njjobIzAzSI+gMwHOBpgRpslaK57sKM1AGB9qbA2VLC+jRlSYvmJJzsDxjjHZ0UTPaw9+f+B7Ox8V\nxMArOBBHCGlyFVxfiCBlzRNqlgxmBmkT9NqwszGSNQ/uezostbhLLDsoaAZCIuwJY2qDenilGVMb\ncSLojybnxhJXdn7zh85/3fFINT7tejSWxGaz0bu2NLma4IWYPuG+E51NYciHp0edLZcpsWCf8ApH\n40EiOBA3lglixYZ3OJwR2mw2bDSaH5hGIEx0vVA//OVXbXMZ1WTIGx6OfETIE5HpDEkRL3755fVP\nBH+0c1NKG1bJJFwFQmcj5EXTJ9wsGcwI6RBoF2ZnU8RSpcLkUDKaDg5HvTabjRyN5gemEQjlsx8+\nPfzlpx5esKBOd/lwO5UMJb0tRwdnLZ+jGflZ0nXo9/t6Dn63QoVhGD7v6daB127Qlz52hsdzBmcz\n1NCnT6AzQiJOei5GLdWwmSxNAu0v42wIWyEvmi5juSo0GI8FxFA4SrdYRr944xq0c/PWwwMhf8ce\n2+NHytavTWpajOWsPTwSsyMNP6nK++p+f+cvFvE40DgbIxbYO5EuSzXuaRdex1Fve1Q3S6HQQMlo\nmgQ6AIIKKTowGTJVqIR+9giF9pNvWPXc3mdLX7k+X2so33jutu27N1cpUbTpqUq8/oWuBBOXmGGw\nm54OuRrTFyk9FwVWOAp5UZqEmhqF+06PtVbAO2eS0a+NxAz1m15v2fR68p+pap9sizw59idVdU+1\n9NP+PlaF7QkiTmrzoWQ0fVSWTFiHWMHxkzQJdkYIeydosYhlBwXkgkaBB4M+IdbLwH2nSYiFozE/\nEXYkDLNhYTh9VrHsoIBAOAqkSugT4uQA7jt91jrcIagBkKMhbKnFMXgF0iDQIqnx4F/BKE44mJ42\nwc0IiTjpaY+a4UQ6egQ3AILRD32mOapAXzweFHzhKATCUSBFRp+5Cvd2xBIRwRSOQskoI6y1uEtQ\ny0XwsNOHyTHTXJWrVWDFcePBwz+KC86doE2uwgylSs8FwbwTYWbACMFlAmDvBCPEsUwIgfAzYUci\nESF1s6BklC5rHe4QTpYMZgaMgNSoNImj9TYEws9At0mmCOudCHsnGKHOkstxLNArjMLRqCcR9SYM\nxdBllC5hPeyTgUD4GUiVMEVYWTKYGTDFIpxt9Y6GiLVOjaDJKG3iOIMCAuFnXM0RK5SMMkFAg0Qo\nGWWQgO67szGcBaNeJpjmqvw98XhI2IWjEAg/AzMDppgrVf7umCCe+0Lv7gAAHZhJREFUDc/FqL4Q\nSkaZIaBMAKR/mCJTYMZylbtN2IWj8Px/BtYImSKgZwNGPwwS0A4KuO8MyhLOAGgyEAiHRdyJeIDQ\nF8LiOTOE8my4YPTDHCGlRuEAJuZYanBXszDu+2QgEA4bPn0JFs8ZIpTeS5AiY5BQCkdhoxSzBDQA\nmgwEwmFwMD2zrPPUzgYBzAid0EKBUYJYJoSdo8wSyqh3ChAIh9nPhLMXwguRMdZaATwbUDLKOEFM\nDpwNsEDIJHOlKtATi/kFUBw3GQiEw+xnw9mL4NlgjGmuKtAXjwV4/WxAySjjBLGV0AEzQkZhcsxS\ngzvO8/2+TwFeAQghRBLIcT6ctQACIWMwOWauVLlbeD05gNJBxlnrcGcDr286oloKQyBkVPYitf0s\nBEKB87RHNdkK3Czn+kJExVqr5nkTQvvpUBbkwxmVvVDjOB8meZ0IQM7GCJSMMit7odp+BgKhwNnP\nhCAvyjj+L6EPnYF8OMNURpkmR8Hns0dCg3GSILV5UDLKpOxFGpgRCp7jHORFmWedp3bwu3DUcRYq\npJiXXa8e4vHkwAGVMizIWqB2NoTJhGBOIR0DAiFCCA2dhpkB87IX4HzOloSG4jE/YSyFklGG5Szi\ndZbMfjoEox/GqYwybZ7Cc1EAzaQmBIEQIYTsZ8I5EAiZZpitSoSI4ABPt1fbT4ez66GFAvOyF2ns\nZ0JcX8Wkhqj7DpiWtZDXmYCpQSBEYUciHiAMs2FmwDQMZfN4cgALhCzJrlcPneLpTUcI2U+Hcq7S\ncH0VIpS9UO0Q7DIhBEI0RJUOwsyABdn1Gvtpnk4O7GdCOYvghcg8fZGSJMhgHx8zAfEQ4e2MWeC0\nNRZkL9LwdtQ7LQiEyHEW8qJsyalXD53m6bNhhxkha3IWaYZ4mR11nItYqnG5Coa9zMtepLaf5eNN\nTwX9QEi4j229t1KJYRiWs3TD9rbxvwnCdeQXd89VYBiGFVz3g718a8lrPxuGzWQs4e2MMB4k/Jdh\nZsAW3qbEh06FcmCBkB2GEmUiQvK2JmBqdAMh6dm/+a6nHQ8e6Av4OnesOPjQ6i1j+koQ/X+8/0tb\nZY8dHwo6zz9tfdv2PM+GivYz4WxIkbHDUqUK9MWjngTXFzKW/VzYXI3LlDAzYAV/A+HpUHY9POxs\nyVqgdpzj432fFt1AGDixba9i3ZZN1+Zr9bNvfeKZ6/pe3dWaHAkTPbv/63DVT3/9zfpsjWXet966\ncHLLYh79Q0xESM/FqBVmBuzA5Jh1ntrOv2cD6oRZxdtMgP10OOcquO9s4e0AaFo0A2F8qLE1VLK8\njPqnhekrluQMHO9IfgLCFw90mqucv1ylo1Kj39/Tw6eps7MxbKpQydUwM2BLTr3azr9lQlggZBWV\nCYj5+NVpjYiTzqZI1ny472zJXijU/jI0AyER9oQxteHTOIKpjTgR9EeT2gskfIPOy+98kP9sizcw\ncPSH6hfXfv21Xv5kyuD0Jbbl1Gt4WC9jPxOCfDh7MDlmrcX5lglwNUcMJUqlHioE2ZK9UM3nLaRT\nSOPfRKLrhXqMctU2l1FNhrzh4chHhDwRmc6AJ82vMJUWN934o3+5rtigzV26wXaf8cRbjZP9qrAk\nNptt5tc2Y3ZossWy7Ho137JkZIJ0NkagqR6reFhMb4et9Cyz1OLejlgizHqjNZvNho1G8wPTCITy\n2Q+fJimnHl6woE53+XA79aIjvS1HB2ctn5M80sZLrylODA4Eh381JIEUuGKyqyaTZC4QQoqMTVnz\n1e4L0Qw8G6lztUZ1BQqVEWYGLMpexLvJwdDpUA5UyrBJrsLMFSpnI+sDIJvNRo5G8wPpvgv0izeu\nQTs3bz08EPJ37LE9fqRs/drK5B4tqjn3fbPi2GPff6XBGRz6ZJvtjfDn7pvPl3+MJHKcC2cv5Mvl\niJIcx0xzM/FspA7yohmQzb8tpEOnoFKGddmLBNlojfag2LDqub3Plr5yfb7WUL7x3G3bd2+uUqJo\n01OVeP0LXQmEkLLiu2+/8uWuH87P0uUu/7Vy8xu/vSObJ0Nxb2dUqZOps+EYQnbxbVs9VMpkQPYC\ntas5QsR4kwkgqXUQGACxS6CN1ugfyoUZ6je93rLp9eQ/U9U+2RZ5cuR/lazZemDNVtrfxDjIi2ZG\ndr1m6HQIIQvXFzLMfia88HtZXF+FyCm0MkOJ0tXClypNz6UoboJRL+uyF2kuveXj+ipmjCdzM27A\nzCAz+LaDwn4mDGtFGcCrXWX202HYSp8Bw43WeJMISJGkA6EDUiUZkb1I4zjHl0M7/VdiCEPaAjig\nnHW8CoRDp6G5WibgFjlulns7BHYwoaQD4dAZ6DKaCSqjTFugcLfx4tmwnwnDCzEzcoZT4rwwdAqa\nq2VI1kK14LbVSzcQRtyJsCNumgPHEGYCf96Jdug2mSnZVEqcF4kAZD8DJaMZkr1IeP1lpBsIHWfD\nWfPVmHR/ARmVzZtlQqiQyhhNjkKhxXyXY1xfCAr2xYkYqS9Scn0hkpC9kEcp8RRJNw7ACzGT+NNo\nbeg0tNvOnOx6DR+21Q/BqfQZxMNeCtOSdiCEBcJMyblKPXSK+1qyqJcIDcZNFXDYSIbkLOLFFtKh\n07AwnDmmclXETURc/GkpPT0JB8IzUDKaOZpchULDfZbMfjZknQf58MzhScdR6CWUURjKmo/z4b6n\nTqKvhHiQcLdGIDWaSdk8qJeBJlsZxpMs2dDJcM7VcN8zJ2+ptv9okOurmAGJBsLB46GsBWo5DscQ\nZg4fttU7zoZzYGaQQaY5qoibCDu5zJJF3ImQPW6aC/nwzMlfph2AQMh//UeDecvghZhRfNhBMXgi\nBAfxZBSGsheph05yed+hPjzz8pdr+o9ynwlInUT/dfR/HMpfruX6KqSF8x0UUS/h7YxChVSGFVyr\n7TvM5eRg6BSUjGaarlApxzFPOy96aKRCooFw4GgwfxkEwowylqpiASI0FOfqAvo/DuZerZEpIR+e\nUfnXavuPcBoIT8NGKQ7kL9f2fyyY7KgUA6H3UhSTI30x7K7NLAzlLtH0f8xZwqTvcLBgJYx+Mq1g\nhXbgkxCHnWb7P4ZRLwfyl2kEtEwoxUDY/3GwYIWO66uQooIV2v7DAa6+vf9wIP9aeCFmGm6R6woU\njoYIJ98eHIiHHQlLDVTKZFreci2Ho96ZkmQgPBqCShlOFKzU9R7iZpBIJsjBE6G8pRAIOVCwQtvP\n0TJh38FgwQotVMpkXk69xt0aifkJri8kJVL8B9L/cRAqZTiRv0zjOBuOBzl4Nuxnw/pipdoK57Jy\nIP9abR9Hy4R9hwMFK+Bh54Acx6zzOS4YTp3kAmE8RLhbI3AuKycUWpm1Dh88wcGz0XcY8uGcKVjB\nWeFo36FgwUq479zIX64RyrZ6yQXCweMhax0uV0PpIDcKVur6uMiO9h8JwgIhV8yVeDxABHoy3WAv\nFiBczZHcxTDq5Ua+cJYJJRcI+4/CDkIucTU56DsMgZA7GMpbxkHBcP/Hwex6NYx6uZK/TDA7KCQX\nCAc+DuZBLTV3ClZp+w4HM1xMH+iJxUOEeS4cwsyZgmu1fRkvGIa8KLf0xUq5CvN2CGBbveQCYf9R\nqJThkiZHoc1TOBszWkzfeyg4a6UOwcSAO/krONhW3384CJUy3MpbphHEpFBagdDXGcVkyFACW+m5\nVLBSm+FlQlgg5FzuYo2zMZLJgmEiTg58AvedY/nLhLFMKK1ACC1G+SDzy4SwQMg5hUZmnYcPHs/c\nO9F+JqwvUcGGGW7lLxfGMRQSC4RHYYGQewUrtb0fZW65KBYg3C2R3KuhdJBjBSt0mdxN2HcoOAs6\n6nEt52qNqyWjmYD0SCwQwlZ6HjBX4kSczNhp9YOfhLIWQukg9/IzewxF3+FAPiwQck2OY9Y6fJD3\n2+rpB0LCfWzrvZVKDMOwnKUbtreN+y+Odb/9g5uLMQzDMEXFmp8fdHA0OIiHCFdTBA4o54P8a7V9\nhzI0Kew7HCyAvCgPFKzU9h8Jkpl6/PsOw4yQFwSxTEg3EJKe/Zvvetrx4IG+gK9zx4qDD63eMrq7\nbqJn1z+v25H1H42uSLDvH1/veeqeRw/4aH5peoZOhi21uEIjrUkwP2VymbD/SBBmBnygzVPgFrm7\nNRMFw56LUUyGGUphwwz38oSwTEg3KgRObNurWLdl07X5Wv3sW5945rq+V3eN+pce6ztzSbFs/d21\nZpUmf9lX75vra2hxJWh+a1pg4wR/ZK6/DIkGjsEpPHyRsUN6+w4FZq2Cm84L+cs5PpAyFTQDYXyo\nsTVUsryMSjdi+oolOQPHO5KnwXjF7Tfpjzz/2nl3LDJ4bNdrXeW3r8zjpJALjiXjj5yr1L7OaNjJ\n+ojI2RjGrXJtvoLtLwKpyNghvX2wg5A3DCVKTIH5Onm9rZ5mICTCnjCmNnxaiICpjTgR9EeT2oZg\npht+/uI/dX5ngUWlzlv5c8Uj2zbPm/RsMCyJzWajd21jDRwL5S+H0kFekCmw3MWZOLez7wi8EHkk\nYylx6CnDK3lLGW6wZ7PZsNFofmAagTDR9UL98Jdftc1lVJMhb3g48hEhT0SmM+BJVxVpevbz9+2/\ndfdFTyRsb3ixdsdtq7d1xSf5aDIJs4HQ1xklEySsGfBHwUpdBt6JsHOUV6zz1MGBeNjObiYgbE8E\n+uJZ8+EwXr7IX87wOVw2m40cjeYHphEI5bMfPj385aceXrCgTnf5cDsV7Elvy9HBWcvnJE27EgMH\n3mwpeeA7X5hjVOFZdas33q4/+VZD5hPGXe/6i2/RZ/xrwaQKVmSiv0zfITiOjkcwGcpfpmF7N2Hv\noUD+cg0mhw0zfFF8i77rHW5qJFNEt1hGv3jjGrRz89bDAyF/xx7b40fK1q+tTJp2ya11C41tL/92\nX4c/HnO37N22Z7BoeWnmdzB0veubfZsh418LJpW/XDt0KpSIsNh9OzQYD9sTllrYMMMj+ddq+1nu\nvt1/BDbM8Ev2AjURJTNTMJwe2nsJDKue2/ts6SvX52sN5RvP3bZ99+YqJYo2PVWJ17/QlUBIv/KX\nbz87//2vlRuUKkvNI81f3PbmD2oznKCMh4jeA4GSW2FGyCNKg8xcibN6gHXXu/7CG3UY7Jfhk+Kb\n9V3v+ln9it6DwYJVsEDIJxia/SVD51/5OynE6GdXmYJhbF1M1zu+U7+w3/2PMjY+HKTt4CN9ukLl\nVY9ls/T573358uzbDDUPWFj6fJAGMkG+NKv1y8fKWVqwj4eI3+e0rB+sVmhhBMQjnXt9Z39lX/0B\nWy9hmuFDEv9WOv8KeVE+Kr5Zf/ldtgaJiQh55f1A6ZfgvvMLJsdm32bo2MvWfb/yfiB3iQaiIN8U\n3aQbPBGKennadJQ3/1zYnJd2/dUHL0QeKr5Fbz8TZqmGsPdAwFKLa3JhByHvlN1h6GQtEF5621t2\nl5GlDwdpU2hlBSt03X9nJStO/6BvvgTC9j97WfpkZ0MYk2HWOqil5h25Giu+Rd+xh5Vb37HXV3YH\njH74qPjz+v6jQTYmB2SC7NzrK4dAyEuzb9OztEzYc4BuHTJfAiFVyRJhofla5198pbfDC5Gnyu82\nXnqLlUDY+Rdf6Z3wQuQjpV5WsEJ7+W/MvxN7PwoaZisNs+HkbT4qvdPY9Y6Pja7r7X/y0PwEvgRC\npV6GEGIjYdL5V99syIvy1ezb9L0fBWI+hh8O+5kwJkPWWkgD8FTZHUY2HvZLb3nL74bRD08ZSpSa\nHPngCYYLxUkCXdpNdzDNl0BIaf8z3cA+RtiZcJyPFF4HtdQ8pTLJ86/Vdr3H8Duxc6+37E4Y/fBX\n2WpD1zs+Is5oaQCJOnZDIOS10i8ZupjOjvZ+FNAV0M0B8CsQ9hwIRj1MZkcvv+crvF4Hh7LyGRvZ\n0Y69vtI74IXIX7pCpb5Y2f8xky1mBk+G5DhmqYE0AH+xsZuw/Q3PnHvoPuz8CoSzVmk7/8Lkr6nr\nr36oF+W5stXGy+/5E1HGJgfBvrjnQhRO4eG5sjsZzo5eestbfo+JwQ8EjCtYofV1RgM9MaY+kCTQ\npbe85WvEFQjn3GtisHyUTJCX/+4r+SI0lOE1bZ7CWov3fMhY263Ov/hKvqiXKSENwGulTG+igAVC\n/sPkWPEt+q73GNtE0Xc4oMlRWKrppgH4FQjLVhuufOBnqnSi/+OQoVipL4ISMr5jNjvasddbBnlR\n3su9WhP1Ee42ZvpPui9Eo14ibwmcs8Z3sxldJrz0Zy/9vCjiWyDEzfKCFbpOhvqUQ72oUMy5x9ix\n20t/VyyCvrICgqHSLxmYWgq59GdP+V0GBFkA3pt9m+HKhwFmuu2T6NJb3jn3MpAP51cgRAjNudfY\n/gYztaOdf4FAKAyGUpUmT9F/lIG66ivvB3Ku1uAWOf2PAmxjMDsKeVGhUFvl1jq89yMGlkL6Pw4q\nDTJGyqN4FwjL7zZ27wvEAnSzo/7uWGggDqkSoWAqO9qx1wsNZYSi6Cbd0KlQ2EG3UDzQE/NcjM76\nHOySEgamNlG0/5mZ6SDiYSDELfK8pZrLtA9q6fyLr+RWPRzOKRTMBEISdf3VN/t2mBkIg0IjK7xe\nR7/FTMdu3+zbDVAeJRTMbKIgUfufGdg4QeFdIEQIzb3XRD872vSiq+KfoJZaMLIXqhFC9rNhOh8y\neCKkMsrNFRk+7xKkr5SJFjOX3vJCf1EByV6glimxnv20sqODJ0JytSxrPjPHbvMxEJbdZbj8N388\nlH52tPt9fyJKzv4ipMiEpPxuY8fbtCaFF//oKVsNL0QhKf2SofvvtArFI67EwPFQyRegPEo4MFT/\n/ezTz9npfEb7G5659zL2sPMxEGpyFDlXay7T2Gty+jl7/fezoYRMWMrvMra/mX4gDDsTzS+55n3H\nyuAlAbZpCxQlXzSc/40j7U/o3OsrulEHBxAKS+X9Zvu5sON8+hmgi28wtkCI+BkI0XDtaJrvRPvZ\nsKspUvFVyIsKTP61WiJKdu9LcwB07teO8jVGQwlsGxWYxf+ec/ZXjvTq40gCndlqr3nAwvhVAVbJ\ncWzBJuvp/0xzUjh0KoTJUPYiZvKiiLeBsPxu4+W/+QK98TT+7unn7AseyZKrYD4oMJgMLbHlHnti\nII1TmqOexPn/cVz9oxwWrguwy1KDz/qcrvG3zjT+7sU/eeQ4BuesCdG8b1u7/urzd6fTbq3hf5yV\na80MXgxPA6E2T1H7oPXYjwdm+hf93bHL7/nqvgUjREGq+IopESU7Zl49ce6/naW3G43lUCYjSEue\nzD39n/aZlgWQCfL4U4NLf5YHiyBCpDLJax6wnP31jLPijnPhzr/4Fj2axeDF8DQQIoQW/3tO17u+\noZMz22R95pf/v727j2rqvOMAfi8ESAiRl0CCRAkq0Cp0GgVj0Wp9aWt1tS1z68Sew14sXTfctC3t\n1olS0Va7zp4iaofzWCvl2BXbdXhsdcfDRoeKCNYKCqhAcLwlBEISJCG5uftD1qOVlwC5L3C/n3+T\nmAcffvfHfZ7n/n4ds14I8Q3E89TjE0nMf1NZtqV9RN07HT2uK7nGeb8PZWxYwKyQOD/lfP9rh7pG\n9Knaoyax3HvqYzgmM17N3iSv+bDLbhrZg6SlGW0JmQrPXuT5mwh9ZF6JmYrSjDb3P2LvomrzTT/Y\n6Mm/FIBl09bIRFKvET0/c2Vf55TlAUEPoP/OOJa4TVH5Tof7lbdcDro827Bgh5LRUQGjpCqfqB/K\nqj8Ywaq47qTFonPEpXl4zY+/iZAgiLi04F690/1qhFf2dU5/ZpI0QsToqIBp2jcVZZl6N7u2Ujb6\n2/c75v0Bt4PjW5hGLH9IXHPE3ZvCq3/tCor1jUDP7XFu7uthl3OMlM2tYKcp+uzr7QvfDfd48QRe\nJ0LSm0zaHV76apvLMfx/E2Wnr+w3zn4ZF8Rxb+rjAdIIUd3Hbt0UVh0whif5h8R77PwYcCVxq6Ji\np8GdzpSUja542zA/C7eD417wTL8wjaQ23+TOm6vzuiRh3kycjeJ1IiQIQr1aJlP7XD04/N+JNR92\nKRMlIbOwPuYZWVlZHH67dofyQpZ+2GsiZacv/VkQh0W5nQ52KLWSoFi/6wXDXxOrDhgVCRKllstK\nwkKYEXZoMkIvvdsx7LEAh8VVnq1f+KdwJsZA0rTHOoOPEUkOPJiOy7ailY3ra2KG2B3t1TuPJ9Uv\nO6yKeARLJZ4x2HSwpujJxmlPT4r/1VAPyFft72w6ZVn1hZq1UXGF8+lgR0tJT/GG5pRrMUNUCXZY\nXfkxdWtOR3mqvNboCGRG2FGovTnzl8FxaUMF+/k32ntancsPqwZ8dYzTwcodIdVZlvPcDC9Sk6sb\nRZ350NniqNWyircMg73BVGs/nlQfkxKELDiRaLOVFTsNQ2wetJ27XZ6tT9iiYHNUwKiIxVKpyuc/\nLw+1G/LtXqNqqZTbLAieteyQqmKnoXLXoBd5i85Rnde5YAdTwc58InQZTzw/a81XkSuiR79oqc1W\nXj3UNWALq5avez5f0jDvj2Ha7bggTiiKBIlqqfT4ovr2svseoaGJyt2GL5ObluapFOi0NbGsLIw0\nN/R9trjB0tj3vZccVtfZ19ouv2ecn4Vgn1BC4sU/Ojfj+ifd/3qx5f5TcvYuqmRjy0PpcqmKqbpR\nzCdC6ja99ODFzzYlBI7+u/wnix79i+rMz5s/X9KgO2n5rvLI9WPdX629teLoFNRYmpBWHJkyZ7P8\ny2Rd8QvNto7+1YRevbNoVWPjCcuPL8yIQuvBCUcs9179hTrmJ5MKF9Tf3Znrxt+6C2Ze79U711VF\nB8XiKMBEI40QJZdMt95ynFzT9F0R9p5mR+mrbfkxdZJQkSaDwYOQbC1zU80HF8TsT712MV092Ebf\nsIu8NEXf+NRcudtAu4i5r4VamhzVH3SuPqHGIgkT+LMF0md2XdjWXlfQrd2uCIz2PfOz5gdTgxKz\nFF4iARUU4c90sEZf3nvqp7fUq2SzNgSXvtJm63Auzo2YvMif63H1E+CMsMDlpEt+09p+4fYj70+u\n/chU/3fzg6nBszfLA6YMcy841umg2eH8b16CZM7eRufgbxn9zwAAAMI2lgTFxLPnlC43IWrjNwRB\nEJp9uvJfR7pXCmekuZCmaDSgFxaa6DNTqJ8nNHYT5ReESRcWli/vTCRCb3X6JTqdgX/4XsiCgkMS\nyIIChCwoQCxf3vn+QD0AAACjmN/v7Tq+RL625K4vCVxX3FzwKJ74AwAAPsDBJwAAEDQsjQIAgKAh\nEQIAgKAhEQIAgKAhEQIAgKAhEQIAgKBxnQgH6NDkMpXtWRvrQ5IkGaZNO1J3X+sBYJ71n8lS8i7R\nmVV2rsckZAgKnkGA8IHn0geniXCgDk10d/HmZ7YbN/y7tcfS+NHCr196ehd+w9jX1230mpPT4Ph/\nKb4b2fGo988ZBAXvIEA459H0wWkiHKhDU8/FvCLR87s2JoX7B6hXbnlrSevHBbUIepZRVoOVCFDI\nUNqKFxAUfIMA4Z5H0wenidBn6lNpT029p72G01Bd2xv58LQ7jZXIgJjEsPbyBiwEsYyy6q32m3uX\ny0iSJKXRq7aebqeG/xQwA0HBOwgQ7nk0fXC9R/h9Llu3jRTLxP0FV0nxJD/XbWsfqt+wixRHrXj2\niSe2ndf3mHVFqeY9yevzmxHpHEFQ8A4ChJdGHyksJ0JKl6vp312eu79pgF8cL0mQmO412/qH7urt\ntntJZX7oM8G4e6amVZ2675PDmc/Gh/nLIpe98k5KwLlj3/RwPUShQlDwjs90BAgPjT5SWE6E3ur0\nS/27y5UD9ikUhcbHSZtKb965m6XNNef1EQ/PkLA7SkG6e2peUjSfOXjgVIvzzku0w06JJL58Wz0Q\nDAQF39C2JgQID40+Ung3dwEJLyYTRzfvKW3vtTb8I+uNs9N+kRLry/WoBIZ0Nh7b+rtNu0/e6LZb\ndad3ZRRSj6Vq/LkelmAhKHgGAcJTo4+UsbS3H6vOwsX33rQGriu20i5zZc5zD4gIgiCUi377aaOd\nyyEKFWUqz1mvCSEIgiDkmpT3znVSXA9J0BAUPIMA4ZxH0wfaMAEAgKDxbmkUAACATUiEAAAgaEiE\nAAAgaEiEAAAgaEiEAAAgaEiEAAAgaEiEAAAgaEiEAAAgaEiEAAAgaP8DnUMPOHiXk9gAAAAASUVO\nRK5CYII=\n",
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4Ws5qWE3ILl0UrCCMNW1tUhdME7JJzwFXzhoqX32u00C+TMLwBMKDBw+uW7dOKpUihHJycubMmbNnz57YA3JycpxO54033vjLX/7yjjvuePDBBwsKCrCcmgf6jrl1xTJFCoU1sXLXqbsPOCPQCWcHR0fAbw+nVFA4bpmzWn3pkCvkh3lCVvAOheztgfQFSupOkb5Q4ewOuHuD1J2Cx/AEQpPJlJWVFf02IyOjr68v9oDS0tIXX3zR5/MFAgG73R4MBsmdsUZFXMloNGK5SNbq+tRJUb5olDpHqtCLzbDSiB26PnXmrkvCsuPEWBQpYl2x3PSlm8JzgEnrPuDMXqkSSSlsckJMTFuTxO9aa0ajkRgByydjmyOMvSCCIESiKz55375927dvJ3dYPn78+L59+95+++2xPm3YTlG8D4Sd+6idICTlrEmCaUKW6N5P1cKJWLnrYBEFW/QcdFE6QUji/SIKo9E46n6EU4cnEGZlZfX390e/NZlMmZmZsQf84x//qKysJL9WqVSLFy8+f/48llNznXcoZGvyY6+sNlLOalhWzw4R1PO5axqV00UkKDrKHt0HqFpKH+vysnoYDo8fnkC4atWq/fv3+/1+hFBvb29NTc3q1atjD8jIyDh06FAwGEQI+f3+M2fOVFRUYDk113V95sy+Rk3pmAlp2mr1pUPuSAjuEoYNnvPKtGJNvozqE2WvVA+e9frtMDPMMNeloHcwmDKH8qUsmjypTCcePAczIHHDEwhvv/32vLy8q6+++umnn165cuX9999fXFyMELrzzjtfeOEFhNATTzxhMpmqqqqeeeaZFStWFBYWfve738Vyaq7rpnjhRJQyXZKUK+3/Cm4ShnVTVlBmGLGCyKhUXjoEo6MM697vzFmtxrj10jimQ621hOBpHLFYvG/fvieeeEKj0bzyyisvv/wy+fM1a9bMnj0bIZSdnV1XV3fvvfcqlcqf//zne/fuFYth41CEEE2jZKRpa9U9sBMF06gqMToa2ImCDXoOuqatpqnFc9aoez6HV5+4EbgmG3EhCNZdEnU8A8G3ipvuGyqj522xbafj/J+Gbt6bT8fJwGhC/sjf0+q+11ZCzw7yppOeA/f1bDo/k4ZzgbG8MaPx5j15uhI66jq5+4Jvz2q6b7CM0pxkVsESMqDWKJP6T3nSK5X0REGEUM41qr7j7pBPKO8ZLNR/yqMrltMTBRFC6QsUrp6Apx/WljHG3uoP+8P0REGEkCpTIk0S2VphE674QCBkkulLT8ZiCtfYDiNLFhvKYG0Zk0wn3JnLKM8QjiLERMYipemkh7YzgmHoHAknpS9Swj0eLwiETDKddKdX0vdYRLCakGn9pz3pC+l79UEIpS9S9Z+CQMiY7oPOnFU0JQGQMhar+uHVJ04QCJkTQf2nPBmLaH0sZq9QmU7A2yJjTCfpbvGMSqXpJLQ4Y0wnPFkr6Q2EMAYQPwiEjLE2+6UasSqT1u2o0hYq+095YMktI7xDIZ85lFxE62ZY6ZXK/pPQ4szwDoZ8lpBuJuVrRmOlL1QOnfNCKkBcIBAyxvSlm+bOAUJIlSGRqET2dphLZ4DppDt9IX25USRVpkSiFtnboMUZcHkknN4ETolKlDxTNnQeVgzHAQIhY/ppHyUjpS9U9p+GkRMG9J/0pDPR4jBWxpT+0540eqeESemLlKYvocXjAIGQMaYv3RmLac2UIaUtUA5AfRkmmE550iuZeCxWKiFfhhEDX3ko3XppLBmLVDAxHBcIhMwI+SPmi77U+ZSXHxwpfaFy4Ct4LDJg4LQnYxEDrz7plZA4yoz+0570hQzc4xmLlZA4GhcIhMwYrPHqimVSNQO//8tDozCVTi9HRwCJkDqb1twoUkalcqDaEw5Ck9PKbQoG3WFNHq2ZMiTDLIWrN+izjLnnKxgGAiEzTF+605noHCCEFKlimU5sa4HsCVqZTrozmRgJRwhJNaKkXKml1sfI2QWLrBvFSKkzQoTS5isgFWDyIBAyg6lMGVL6QrhJ6NbP0AQhKb1SaYLRUXrRXzwhVgbky8QDAiEzTCc9jGTKkNIXwDQh3fpPMZMySsqAfBnaDXzlSWMiU4aUDvky8YBAyACfNeTuC+hLGZg8IKXBCgp6RcJooNrLSAIhKX2Rqh8ei/Tq/4rRHuFi6BHGAQIhA0xfetIWKAkxYxulZFQqB854IrB1OV0sdT5VhkSuZ2wPztS5CmujP+iBJqeJszuAwigpV8rUBSRNk4okyNERYOoCuAUCIQP6TzKzgjBKlixWpkusjZA9QRPTSQaqCMUSywl9mXywBtaP0oSppfSxMhapYBuKSYJAyAD6Ky+PBPVl6MRspgwpfRFME9JngNFxUVLGYqgoNFkQCBlA/6YTI6VBvgyN2BAIIV+GTv2nmakpEysdeoSTBoGQbvY2PyFG6hzGJg9I0COkTcgXsdT5UucxUGEkVnqlCvoHtBn4yst8j7BSOXjWC4UUJgMCId1MJz0ZS5icICSlL1AO1sBNQofBGq+uRC5RMnyv6cvkbhNUG6GDo90vkhGqLAaqCMWSakSa6VLzBUgFmBgEQroxsvvSSFKNKGma1FoPNwnl+k+5GR8XRdFqIzAeTr3+08x3B0mQLzNJEAjp1s/oUvpYMDpKD6Y2nRjp8ia9gGL9X3nSFzA8Ek5Khx24JgcCIa3CgcjgWW/aVax4LKYtUPbDfkzUY7acXizYj4keAyxYO0HKWAw9wkmBQEgrS51PM10q07Li1w49Qhr47WFnT0BfJmf6QhBCKAMqjtIgggbOMJ8ySkqZLXe0BwIuKKQwAZxP5N7e3hMnTlgslrEOsFqtJ06c6OzsxHhSbhms8abOY8UdghBKu0phPu8NByBfhkL9pz1p85QiCWNVhGJp8mXhQMR1Kcj0hfCZrdUv1YiU6QxnypBEEkJXKod8mQlhC4RPP/307NmzH3300YKCgu3bt4884JVXXikoKHjqqacWLlz44IMP4jovtwye86bMZkXnACEkUYk0+VLzRbhJKNR/0s1gre2R0iuVUIuZUsxuOjFS6hzF0DmYAZkAnkB47NixP/7xj9XV1cePH3///ffvvfdem80We8DZs2e3bt166NChAwcO1NbWbt++/csvv8Ryam4ZOu9NmcOKWXRS+kIlpBFSaqDam3YVm1p8gXLgDDwWKcTsphMjpcxRDEIgnAieQPjhhx+uX78+NzcXIbRq1arc3NwPP/ww9oC3337729/+9qxZs9ra2lQq1eDg4OLFi7GcmluGznpT57LosZi2QDkA04RUGjzrTZ3Lrsci9A8oxbYeIbT4ZOAJhB0dHQUFBdFv8/Pz29vbYw+oq6sTiUSzZ89etmyZXq9/9tlnx/k04kpGoxHLRTLO0x8MByKM15SJlV4J+TIUCnkjzq6Arpix/bZGSpktHzoPj0XKRNBgtZdVPcLLQ6O8yAQwGo3ECFg+Gc+MrtfrlUq/eb7LZLJg8IoJeafTeejQoS+++GLOnDlnzpy5+uqrly5dumrVqlE/LRLhRaONMHiOXeOiCKHUOQpzrS8cjLAkm4NnzBe9uiKZSMqi323yTLnHFAw4wlINK1KXecbW6pclixQGxvbbGkmRKpaoCEdnQJPHolfwxBiNxpH9IiyxEM/NYDAYYicFLRaLwWCIPUCr1V5//fVz5sxBCF111VVr1qw5dOgQllNzyGCNl/GCk8NIVKKkHImtyc/0hfDT4DlvCptGwhFChAjpy6FTSJUh9r3sIoRS5yphdHR8eAJhZWXlyZMnya99Pt/Zs2cXLVoUe8DChQubmpqi3/b19aWkpGA5NYcMnfemzGbdTWKYrYDHIkXY2eKpc6DFqcLOFod8mQnhCYSbNm3q7Oz8yU9+sn///k2bNlVUVCxbtgwh9Pzzz3/wwQcIofvvv7+np+eHP/zhoUOHHn/88a6urk2bNmE5NYcMnWXj22IKBELKDJ3zsfCxCK8+1GFpIJwthx7h+PAEQp1Od/LkyUAg8MILLxQXF+/cuZP8eXNzc29vL0IoIyPj7NmzWq32d7/7ndvtPn78+LCxU94LByPWJr+hnC2LCKNSZiuGzsNSQkoMnfemsu/VJ3WOYugctDglhs6z8dUndS4kjk4AW/mDnJycl19+edgPt23bFv06LS3tueeew3U6zrHU+TR5UomKdRkKKTBQRg13XzASjjC+F89IKXMVg2QaIYuSePgg5I04OwPJRSxKEibpSuWOzkDQHWbh84cl4PdCk6FzbOwcIISSC2We/qDfDtUIMWNtiysMYqmacHQFmL4QvjHXenXFMrGMde8XIgmhK5aZa2EYYEwQCGnCznQyRKYRlsrNtdApxIyFq2WiYJE1Fdg5LkpKmaMYPAstPiYIhDRh9WNxtsIM04S4sTNvggT1J6kwdN5rYHGLm2EGZGwQCGnC2h4hgmoj1DCzOBBC4igVhthUUn8YWEExPgiEdPAOhoLuiCaXpZUd4LGIXTgYsTT4DbPY+licDT1C/Fg9BjBPMQRDo2ODQEiHwbOelDkK1ibpQXY1dtZGf1IuG5OESfoyub09EPLys5YhI7yDoZA3ksSmSsKxlGkSkZRwdkOG1OhYeqPyzNA5dm06MYwyTUJICHcv7NeKDZtHyRBCYhmRXCgz18HEMDaXu4NsfdlFCKXA++7YIBDSYZCVFUZipcyGKQSc2DxKRoLRUbyGznsNLH71QZAhNS4IhHQYYl/x5WEgXwYvNudGkaDF8eLAqw/ky4wNAiHlwsGIpd7H2rwJElQcxYu1q+mjoKIQXpwIhNAjHAsEQspZG/1J06RSNat/1SmzYZkRNn5byGsJafJZV2orFjwWcYogSx3bX3b1ZXJ7G2RIjY7VT2d+GDrnTZnD6jsEIWSYJbfU+8NBuEkwGDznTalQEOy+t5KmScOBiKcfMqQwsLX65XqxXMei/XhHggypcbD7ZuUF9o+SIXKH3mkSWzPs0IuB+byP5ROEJEMFjI7iwf5xUVLKHMXQWQ/TV8FGEAgpx+biarFgWT0uXHksQhohLmyuIhQrZQ7suTY6CISUY+d+vCPBxoS4DLJ7EWEUtDgubC63HSsVSm+PAQIhtbzmkN8e0rI7b4IEC8vwiCDzBc70DyCfHouh89x49UmdqxiEodHRQCCk1uX1ZCyuNxEFC8uwsLf7ZcliuZ7VeRMkQ4XcWu+LhCBDakpCvoijM5BczIFAqMqSECKoITUKCITU4sp0ESJ36DUFA07YoXdKuDJKhhCSqkWqLIm1CTKkpsRc60suZON+vKOCGlKjgkBILUutL6WCG49FQkzoy+RDF+AmmRL215SJBePhU8eVTBlSSoXcArtwjwCBkFrmWp++nANjJqSU2QrzBciemBJOrJaJgvoyUzd0ngMLhaP0ZXJYSjgSBEJqWep8+jLO3CQwTTh1Q+ehRygsHJr+QAjpy+QWCIQjQCCkkHcwFA5GVBkSpi9ksmCF9RSFfBFHR0BXzIEkYVLKbLn5IjwWp2Togs8wi1OBsBZafDgIhBQy13kN3BkXRZcLT0AgTJytyaedIRVJuZE3gRDSFshcvcGgBzKkEuQ1hwLOsGY6S/fjHUmZJkEiBKX1hoFASCFujYsihFQZsEPvlJhrOdbiIgmhLZDZIHE0UZd3YObMmw9CCBnKFDA6OgzOQNjb23vixAmLxTL+YadPn7bZbBjPy1qWOp++lEuPRYRQSgUkjibOUs+xQIgQMpTLzTBWlijzRc6khUfpy6DFh8MWCJ9++unZs2c/+uijBQUF27dvH+uwvXv3Llq06Pz587jOy2bcShkl6cvklnq4SRJk4VqPEEH2xNRY6rxwj/MAnkB47NixP/7xj9XV1cePH3///ffvvffeUft8AwMDDz30kETCmeSRKbLU+QzceyzCsEnizHU+Qzn3+gfQ4gnj3PQHgnyZ0eAJhB9++OH69etzc3MRQqtWrcrNzf3www9HHnbvvfc+9thjKpUKy0lZLuAM+8yhpOmcSSAkwWMxYZFQxNbs51DKKMkACxU5e3sAACAASURBVMumwMzJl11o8eHwBMKOjo6CgoLot/n5+e3t7cOOeeWVV0Kh0I9+9KMJP424ktFoxHKRNLPU+3QlcpbvzjqSAQJhouxtAVWmRKLiWJPriuX2FtiTORE+ayjoCquzOZMyStLkSv32kN8WYvpC4mY0GokRsHwynpvW6/VKpd/8b5DJZMHgFZmHFy9efP7551977bXJfFrkSlwNhBycLkIIqbIkIX/EO8S9m4RxnEsZJYkVhDpHYm+FxNG4Wep9+lKOpYwihBCB9CVySwP3WtxoNEZGwPLJeAKhwWCInRS0WCwGgyH6bTAY3LRp0wMPPNDb21tTUxMKhZqbm/v6+rCcmrXMHJw8IOlK5NYG6BTGzVLn5dwoGQnSCBPDxQlCkr4MKo5eAU8grKysPHnyJPm1z+c7e/bsokWLon/qcDjsdvtf/vKXW2+99dZbb3W5XFu3bn3rrbewnJq1LHU+bq2mj4JJo8Rw97EI4+GJ4W6LQyrAMHgC4aZNmzo7O3/yk5/s379/06ZNFRUVy5YtQwg9//zzH3zwgV6vb4+h1Wrffffdxx57DMupWQtuEqGx1HFvtQwJWjwxljqfvoxjScIkyJcZBk8g1Ol0J0+eDAQCL7zwQnFx8c6dO8mfNzc39/b2Djt4xYoVycnJWM7LWiF/xNkVSC7kWAIhCR6LiYggS4NfX8LNQFgOa2YSwd2XXUM53ONXwLakLycn5+WXXx72w23bto08cteuXbhOylq2Ro7VnIwFM0YJcPYEpGqCExvTj6QvlVvqfSiCuJf3wZyQN+K6FNTO4FjKKElbIHNdCoa8EbECmhwhqDVKEe5myiCEtDNknv5gwAWFmOPA3VEyhJBMK5LrxI6uANMXwiWWBp+2UCaScDKQiCSEdobU2gjvu5dBIKQEd8dMEEKECCXPlFkbuZddzSCOrp2IgvHweHGxblQsmCaMBYGQEpwOhOhyGiFkV8eBB49FyKePC+fvcZgYjgGBkBLmWg4PlCHoH8SPuymjJOgfxIvrgRDu8VgQCPGLhBEXa07GgpskXlx/LMJSwnhxOg8AwT1+JQiE+Nnb/KoMiVTN4d8t3CRx8Q6FwsGIKoPD26roIZ8+HpFQxN7K8ZfdErmtGWrMXsbhhzVrcbTKaCxdsdzeHoCbZJLMtV6OVhGKUqZJEIE8/cGJDwUI2VoDqkyJRMnh56dYQaiyJPY2SBVGCAIhFbg+ZoIQEssJdbbE3gKJo5PCg1cfhJABtqKcNK6PhJNgWX0UBEL8+HGTQPbE5EGLCw13C6zH0kNy+NcgEOJnqeP8QBmC7Il4cHFj+pFgYnjyePPqAy1OgkCIn6Xery+Fm0RA+PNYhNJ6k8ObFodiiiQIhJi5egISJVdrTsbSw4zR5AScYZ85lJTLyZqTsWBodPIsDXx42TWUKy7XmBU8CISYmTm7DeEw+jI53CSTYanz6UrlBPfvJE2u1G8P+W0hpi+E7XjzsivTimQakbMHEkchEOLGjzETRN4kWpGzG26SCZhruV1c7RsE0pfILfWQKjwBHqSFR8HADwkCIWac3oVgGLhJJoM3rz7o8rJ6SCOcAK9aHKYJEUIQCLHj001iKIdJo4lZ6nnU4vBYnARLPV/GAGAp4dcgEGJmqfPpSzhceCmWvhRukolZuF9WJuryxDAYFz/qJ5B0xTJocQSBEC+fNRRwh9XZnE8gJMEKigmFfBFnd1BbwJdXH1hBMQm8mv4olVshEEIgxMva4NcVyxEn96weBQTCCVkbfdoCqUjKkyZPLpS5eoNBT5jpC2EvnzUU9ITVWRwusB5LnS0NesI+q9BThSEQ4mRt8OlLeDJmghBSZUrCwYh3UOg3yTgsdT4erCeLIsSEtkBmbYTE0TFdHhflyZsPQgRKLpJbG4Te4hAIcbI0+PSlPBklI+lLYdJoPNYGn45Hrz4IIV2xzNoILT4mM4/GRUn6Erm1QegtDoEQJ0s93x6LMDo6Pgs5GM4j+hLoH4yHT2nhJF2JzAKBkOkL4BVro59ngdBQLjfDwrKxWRt9nN6ddSQd9A/Gxae1EyQY9UEQCDG6vGl1Eb8ei8VyK5QaGRv/Xn10xdA/GI+lzqfjy/ookq5EDrPCEAixsbcHlGliiYpXv1IYNhmHuzcolhEKA+drTsaCx+I4Qr6I61JAO4NfgbBYZm/xR0KCLiuM7an9ySeflJeXK5XKpUuXNjU1jTxg27ZtxcXFarW6oqJi+/btuM7LHvzLm0AIaQtkrkuBkFfQN8lYrI186xwghBQGsUiK3KYg0xfCRrZmvyZPxpvVMiSJUqRMFzs6BF1VGE8gbG9v37hx43PPPWexWG6++ebrrrsuGLziRvr000+3bt36z3/+0263P/vss5s3b66pqcFyavawNvAqk54kkhCaPJmtBboIo7A0+HiWKUPSFcM04eh4eY8jhHQlQp8mxBMI33rrrZUrV950000KhWLr1q2hUGj37t2xB/T39z/11FOLFy8Wi8UbNmwoLy8/deoUllOzh6XBz6dFhFH6Ehk8FkdlbeDbBCEJEkfHYmngTwHFWLCCAk8grKurq6ioiH5bVlZ24cKF2APuuuuuxx9/nPy6paWltrZ20aJFY30acSWj0YjlIqlmqefhQBki3xaFfZOMxdrIz8eirgSWEo6Ol9Mf6PI9zoFXH6PRSIyA5ZPxBEKn06lWq6PfqtVql8s16pFdXV033njj448/Pnfu3LE+LXIlrgRCHt8kAn9bHIuVv0Oj8OozKgtPxwB0HBn1MRqNkRGwfDKeQKhWq91ud/Rbt9ut0WhGHnb48OElS5b84Ac/+NWvfoXlvOzht4cDznBSDk/KbcfSc+RtkWbhQMTRFeBNue1YOhgaHYOtkVc1FKNgKSGeQFheXl5fXx/9dthIKemNN9644447/va3vz322GNYTsoqlnofn8ptx9KVyKA+/Ui2Fn/SNKlYzsMmT54pc3T6wwFIFb6CZyCIEFKk8mq1DCkpRxpwCrr0Np5AeOeddx48eHDnzp2BQOD5558Ph8Nr165FCB04cOD8+fMIoU8//fSHP/zh66+/XlFR0d3d3d3d7XQ6sZyaJawN/JwgRAgp0ySE6PJTAETxdSQcISSWEUk5UnsrdAqvwL8Cit8gkK5Y0OtH8QTCwsLC7du3/+xnPzMYDNu3b9+1a5dCoUAI/fd///frr7+OEHr22Wc9Hs/111+f+7X//d//xXJqluDZvhPDJBfDWNlwfE0SJnEle4JOfE0SJnFlmpAi2HbVqqqqqqqqGvbD06dPk18cOHAA14nYydLgK7wjmemroIq+RGZp8GWtUDF9ISxia/SlVyqZvgqqfJ04OspMv2BZebp2giTwFRS8qgfGIEs9z/sHQr5JRmXh79AogjX1o+F5iwt7lRQEQgwiYWRv8SfPhLdFAbHyemgU1tSPxO+hUX2p3CLg8voQCDFwtPuVaWJpEm9/mTBjNIzPGgp6w6pMbDMLbKMrkcOa+ljhQMTR6U/m42oZksBLb/P22U0nfo+ZIISSi2SODsin/8bl7iAPl05cps6WBD2Czqcfxt7qT8qRihW8bXKJSqRMEzs6BVp6GwIhBvweM0EIiWWEOltqb4NO4WV8rSkTK3mmoPPph+FrTZlYQi69DYEQA36nk5Fg0iiWhb/LRqMEnk8/DI8XCkcJuaIQBEIMLA0+HR83Z4kFO/TGsjbyfDAcka8+ME34NX4vFCYJeZ8ZCIQYWOr5f5PACopY1gY/74dGdVBFIQbv8wAQQrpS4a6ggEA4VQFHOGAPJ03jYbntWDA0GhUJI1uLX1fE+4EyGAP4Br9Xy5D0MEcIEmap9+mKZTxOICQJfL1tLGenX2Hg82oZkq5Ebmv2R8JMXwcL8H61DClpmjTgCPvtQmxynt/MNBDCmAlCSJ0tCXnDXjPk0wsigRAhJFWL5Hqxs0ug+fSxLs998P1lFxFIVyTQaUIIhFPF410IhtEVy21NMDoqiARCkpCzJ2Lxfn1UlGAHfiAQTpUQJg9IkC9DsjbyfxEhCerLkISwPook2HscAuFUCWHtBEkP2RMIIUG9+hRDaT2EBDP9gQScEweBcEoiYWRr5n8CIUmwb4vDCGE1PQnW1JMENP1RKtDEUQiEUyKQBEKSkCswRQXdYe9gSDOd56tlSLDrCEIoEorYWwNCedktlgkzVVgQT3DqCCSBkKQrltlbA4KtT0+yNvm1hTJCzPsMQoQQ0uTLPAOhoFt4z8UYjo6AMk0sUQniUSlVixQpYmen4EZHBdG61BFOAiFCSKIUdH16krXBpysWSosTIqSdIbU1C+6xGEs4E4QkYe65BoFwSoSTQEgScllekhBqTsYSbD59lHDWTpB0JTIBpgpDIJwSa6NfOP0DBNOEgmxxePURyNoJkjAnhiEQToml3qcXxtoJkl6Qb4uxBDdQVgwtLrQWF+KrDwTCxAU9AkogJMEKClsT//ediCXM/kEs4aydIAnz1QcCYeKsjX5tgVQgCYQkgQ+NuvuChAQpUsRMXwh9hJk6ERVwhP02/u8tE0uTJxVgqjAEwsQJ7VURIaTJlfqs4YBDWDdJlNAyZRBCihSxSILcpiDTF8IMa6MvuUhGCOkxSYgJbYHUKrCqwkJqYdwE+FhEBEqeKbM2CbRTaG0UVgIhScjj4ZYGYaWFkwTY4vQFwk8++aS8vFypVC5durSpqYm281JHaAmEJMFWI0SXH4uCbPFGgba40NZOkATY4jQFwvb29o0bNz733HMWi+Xmm2++7rrrgkHOD7YILZ2MJOSNywU4GI7I7AnBtnijsNZOkATY4jQFwrfeemvlypU33XSTQqHYunVrKBTavXs3PaemjtASCElC3prH2iiUfSdiCXlNvVWwQ6MCu8dpCoR1dXUVFRXRb8vKyi5cuEDPqSniNgkugZAkzGVGCKFwIOLo9GsLhNc/EN5A2WURZG3yJwuj3HYsAaYK0xQInU6nWq2OfqtWq10u11gHE1cyGo10XGKchPmqiKJr6oVXedve6k/KkYrlAlotQ0qeKXN0+MMBwTW5sycgTRLJdYJ72VUYWJoqbDQaiRGwfDJNgVCtVrvd7ui3brdbo9GMdXDkSmwNhEIcJUMIyZLFUrXIdUlwpbcFtdNILLGMUGdL7W3C6iIgoU4Jk9iZOGo0GiMjYPlkmgJheXl5fX199NthI6VcZG0UYgIhSYAjJ4hsceHlTZCEmSos2JddJLzEUZoC4Z133nnw4MGdO3cGAoHnn38+HA6vXbuWnlNTRJgpoyRhblwu2MFwJNRUYUG/7AoscZSmQFhYWLh9+/af/exnBoNh+/btu3btUigU9JyaIsJcYETSFQsuqQwJu38gzBYX9suusFKFJbSdqaqqqqqqirbTUSocjDg6/cnCSyAk6UvkPQfGzHXiK2ujoB+LTe/YmL4Kugn6ZReGRsGELicQKgSXQEgS4ECZ3xYKuMLqLPpeHFlFL7zB8JAv4uoNaPMFVG47ltBShSEQJsLaIMSl9FHaApnrUiDkFcpNgsiU0WI5EuibD1JnS4OesM8aYvpC6GNr9mvzZSKpQJtcaKnCEAgTYWkQbgIhQkgkITR5MluLUG4SdDmTXrgtjgiUPFNuE9KOBFZB1pWNJahUYQiEibA2CjeBkCS0reqtjcLbaeRKumJhjYcLOVOGpBPSPQ6BMBFCnkUnsXO9LXUEPhiOhNjigg+ExQJKHIVAmAhh1qSPpSsW1pp6gQ+GI+GtsBZmgfVYgkochUAYN78tFHCE1dkCTScjCWpNfSSMbM1+XZGwH4sCW2Et5NX0JEG1OATCuF3ej1eg2WSX6YU0UObsCsj1YqlG0DeLrlhubfJHwkxfBy28g6FICCnTBbpahpSUIw04hZIqLOh7OzEwi44QUqZLIhHkHRTETQKdA4SQVCOS60TObkEUW4eRcIQQIpCuSCaQVGEIhHGzNgo9U4akKxZKUpm1QegpoyTh5MtApgxJOIXWIBDGDRYYkYSTVAavPiTh5MtApgxJOPkyEAjjBv0Dkk4w620t8OqDEBJS9oSQdxqJJZwWh0AYpwiytfiThZ1ASBJOvgwMlJGEM1AGc4QkfYlQdh2BQBgfZ3dAphXJtPB7E0rhiaAn7DYFNXmCXi1DEshAWSQUsbf5k2dCICS33xJEqjA80ONjgTGTryXPlNla/eEgz0tv25r8yQUykUTYy2UQQghp86XuvkDQw/Pnor0toMqUSpTwbERSjUiWLHL18D9VGBo7PlBcLUqiFKkyJI4Ont8kkCkTRYgJ7QyZrZnnnUKoGxVLL4zxcAiE8bE1wU3yDX2p3FrP85sECqzH0pfKLbxvcRj1iaEvldsEMB4OgTA+lnqfrhRukst0xfyfS7fUQ97EN8hJI6avgloWGPWJIZAMKQiE8bHU+/QQCL8mhOwJ2IAplhCqKAh978krCWEMAEEgjEvQHfYMhDR5cJNcpiuR8f4msTYKfQOmWPpS/q+ZgcHwWPpSGe+nPxAEwrhYG/3JM2UE/M6+xvuhUbcpSIiQIlXM9IWwha6U51UUAo6wzxpOmgarZS5Lmi7zDoUCTp6nCsNDPQ4wLjqMJlfqt4f9dt7eJNYGn74MWvwbCoNYJCXcpiDTF0IVa6NPVwQvu98gREhbKLPyvfQ2NHgcLPVQYeRKBEoulNmaeNsphFefkfidKgx7y4wkhPFwCIRxgAVGI+lL+ZxUBstGR9KV8nliGJaNjiSEfBkIhHGwQv9gBF0pnxNHoUc4Er9XWFsbfPpSeNm9gq6E/6W3sQXCjo6Ohx9+eP369Vu3bvV4PCMPqKmpeeCBB2644YYtW7a0tLTgOi99IsjaBG+Lw+lLeD1QBoFwBH2p3FoPrz4CAj3CyXI4HCtWrFCpVI8++mhtbe2GDRuGHVBbW7ty5crCwsLHH39cLpcvWrSop6cHy6lp4+gKyHViaRL0oa+g4+9NEvJG3L1BTT4kEF6Bxy0eCSNbE6yWGU5XIrc18bz0tgTLp7z55psZGRl/+MMfEELXXHNNVlbWiRMnlixZEj3go48+2rBhw09/+lOE0Jo1a/bt27dnz5777rsPy9npAeOio9KXyGzN/kgY8S/Rztro0xZIodz2MNp8qdsUDHrC/CtL7ewKyA3wsjucVC2SG8TOrgCP92DB0+SnTp1aunQp+bVCoZg3b96xY8diD/jpT3/6r3/9i/za4XBcunRp+vTpWE5NGyiuNiqJSqRIETs7eThWBqNkoyLEhLZAZuNjPj20+Fh4v/konkBosVj0en30W51OZ7FYRj0yEAjcfffdlZWV69atG+vTiCsZjUYsFzlFlgZIGR2drlRu4eOkkbUBHouj0/M0cRQC4VhYMh5uNBqJEbB8coKB8PDhw+u+Vl1dLZVKg8Fv1tgGAgGFQjHybw0MDFx77bWhUOj9998f5x8QuRJLAqEVFhGOQV/CipsEOyi+PBa+Zk9YYRHhGPQlMjakChuNxsgIWD45wUCYnZ1969fS0tJmzJjR0dER/dOOjo78/Pxhf+XcuXOVlZXLly9///33lUplwlfMFEuDH94WR6Xj6bAJ9A/GoivhZ6E12GlkLDpeV1FACSfLFBYWbtmyJfrtzTffvGHDhs7OzunTpx8+fLitre26665DCNlsNqlUqlKpmpub16xZ89JLL23evBnPhdMr4Aj7bSGoQDgqfamsZbuN6avALYKsjdA/GJ2+VH72xSGmrwI/GAwfi75EbuHjq08UnjnC5cuX//jHP543b97KlStvueWWV199NS0tDSG0du3an//85wihp556ym63G43GmV/729/+huXU9LCQe3VC/uBoeDlQ5uwOyLRimRYSCEehL5FbG30Iz6AUW5BVc5Ny4GV3FEnTpH57iMdVhfEsn0AIGY3GH/3oR21tbUVFRdHEmW3btul0OoTQf//3fz/88MOxxxcWFuI6NQ1glGwc6hxp0BX2WUNyHX92aYAWH4dUI5Ili53dgaRc/oSNyxOE8LI7KgLpiuTWBl96JfdmtSYDWyBECKWlpZEdwagFCxaQXyxcuBDjiegHe3WOj9y4PGMRf24SSz2U2hoPOQzAp0AIrz7jI6sK8zUQwsjPpMBNMj7+7UgACYTj498KCiusjxoXvyuOQiCcFNiFYHw63hVittT79dDiY+NfqjBUzBgfL1MBoiAQTiwSRrYWv64I3hbHpCvhW/8AHovj0/OuioKl3gevPuPQlfCtxWNBIJyYvc2vTJdIVPC7GhPPtu4MOMN+W0jDowkw7HjWP4iEIva2QDK87I5NVyyzt/ojIX7lCn8NHu4Tgy3KJqQrlttbA+EgT24SSz2slplA0jSp38affHp7W0CVKeFfGXGMJEqRMl1ibw8wfSGUgIafGGTKTEgsJ1RZEnsbT24SaPGJEWSqME86hTAuOhn6Ut7my0AgnBhkykwGn0ZHYbXMZPBpdNTa4NPBqM9E+NTiw0AgnBj0DyaDTzcJtPhk8Cmf3tIAPcKJ8bXGLIJAOBlWuEkmgVePxXoosD4xPr36WKHFJ4Gv+8wgCIQT8llDQU9YlYWzBA8v8eaxGAlF7K3+5JkwUDYBPq2ggNUyk8Gn6Y9hIBBOwFIHo2STouPL26K9PaDKgNUyE9MVy+0tfh6kCnvNoXAgosqAl90JqLIkIV/Eaw4xfSH4wd0+AWsDvCpOiipDgsLIO8T5m8QKE4STI1YQqkyJo4PzqcJW6A5Omq5YxptU4VgQCCdgaYBSW5PFj06hpR4SCCeLHzVmITdq8vi6Qy8EwglA/2Dy+FF/EhIIJ0/Hi9LbUG578vi6Qy8EwglY6mEXgsnix44EkEA4efzIkLLAQuFJ05fKLXWcb/GRIBCOJ+SPODqgAuFk8aRHCDNGk6bnxcIyGBqdPH253FLrZfoq8INAOB5rg087QyqWQdHJSeFBPj0kEMZFx/0eYTgQcXYGtIXwsjspyTNlzp5g0MOTGrNREAjHY6716cvhVXGykgtlzq5AyM/hfHpIIIyLKkMSDkY4nSpsa/En5cLL7mSJJERyoYwHwwDDQCAcj6XWZyhXMH0VnCGSEknTpbZmDt8k5lqfoQwCYRz0ZXIzl8fKoK5svAzl3G7xUUEgHI/5otcwCx6LceB67Qlo8XgZyuWWWg63uKUOXn3io+d4i48KAuF4zLU+AwyNxkPP8a3qzRd9hlkwBhAHwyyF+SKHWxxSRuPF9RYfFQTCMYX8EUd7ILkYbpI46Mu4nT0Bs8LxMsySmy9yeKAM1kfFi+stPioIhGOyNfo0+TCLHh99OYffFn3WkN8e0uRKmb4QLuF2/yCCLLUwGB4fXiaOQiAc09BFH9wh8TKUy631vgg375HL46Lw5hMPdbYkHIh4BzmZOOroDMi0YrlOzPSFcIlIQmgLZNZGDufEjYQtEHZ0dDz88MPr16/funWrx+MZ6zCHw7Fhw4bz58/jOi91IGU0AdIkkSJNYm/j5E1ivuhNgVef+HE3cRRyoxKTwrvRUTyB0OFwrFixQqVSPfroo7W1tRs2bBjryC1btuzatctms2E5L6XMtV6YLkqAYZaco2NlZhgDSAh3R0eHLkBuVCL4lziKJxC++eabGRkZf/jDH6qqqv79739/9dVXJ06cGHnYO++809raqtFosJyUauaLPugfJCClQmG+wMm3RUgZTQx3syegR5gYQ7nCDIFwpFOnTi1dupT8WqFQzJs379ixY8OO6ejo+OlPf/rmm2+KRByYmAwHIo72QHIR3CRx43KPEB6LieByi/sMFfDqEzfutvhY8MQki8Wi1+uj3+p0OovFEntAKBS66667fvvb3+bl5U34acSVjEYjlouMi7XBp8mXiuWQOBE3jvYPfJZQ0BNRZ0PKaNwMsxRDHBwDiISRtQFW0yciuUjm7A7QnzhqNBqJEbB8coKB8PDhw+u+Vl1dLZVKg8Fg9E8DgYBCccV71q9//evc3Ny77rprMh8euRIjgRCW0idMXya3NvnDQY5VHB264DXMkkPKaAJUmRKEkGcgOOGRrGJv8ytSJVINBwao2IapxFGj0RgZAcsnJ/ifIDs7+9avpaWlzZgxo6OjI/qnHR0d+fn50W/tdvuvfvWrvr4+8niXy/XUU0/961//muKlU8pcC9NFCZIoRepsib2FY4mjkCkzFYYy7uXLQItPBddL6w2T4HYzhYWFW7ZsiX578803b9iwobOzc/r06YcPH25ra7vuuusQQjabTSqVyuXyv/71r9GD9+3bt3LlyrKysileOqXMF72FdyQzfRVcRaYRcqtgB2TKTAU5aZSzSs30hcTBfMGbAhOEifq69DZPHpJ49l1bvnz5j3/843nz5s2aNevixYuvvvpqWloaQmjt2rWrVq36wx/+8F//9V/Rgx955JHrr79+/vz5WE5NEQsMjU5BSoV86IK34HYt0xcSB/NF74xbuJHPzEJcnBg2X/RNX5/E9FVwlWGWovFfVqavAhtsG5AajcYf/ehHbW1tRUVF0cSZbdu26XS6YUfu2rVr9uzZuM5LhXAgYm8L6KDKaKIMsxStH9iZvor4mC/6UqBHmCjDLEXzu5xrce+8x1KYvgqu4lniKM6duNPS0siOYNSCBQtGHrZixQqMJ6WCtdGvyYOU0cQZZslP/4ZL/QPvYCgciKiyYGP6BHGuRxgJRWzNsO9E4pKLZM6uQMgbESv48JyEjKlRwHqyKdKVyO1tXNqqHlp8ipTpEkJEuE2cSRy1NftVWRKpGh6ACRJJCG2B1NrIk04h/D8YhbnWp4cqo1MglhOa6VJbE2cSRyFTZur05VwaK4PialPH3dJ6I0EgHAVkykwdt8bKhqBHOGXcanHzRW9KBbT4lHydOMoHEAhHAQNlU2eo4NLbIvQIpy6FU/0DaPGpgx4hn0HKKBaGWXIOld2y1MLa6qniXI8QWnyK9OVy3pTehkA4HKSMYsGht0VPfzASiqgyIGV0SjjU4uFAxN4aXT8KBgAAH+9JREFUgJTRKdIVyZydgZCPMzlx44BAOBxsQ4gFeZPQX5Y3AbAFARaKVLFISrh7OZA4Ci+7WIikhLZAam3gxtvP+CAQDgeTB1iIpIS2kIGyvAmAUTJcDLPkQ1wYHR264DVApgwOHBoGGB8EwuEgZRSXFI5MGpkvQovjwZXHIrzs4sKbxFEIhMOZa73wWMSCK0WY4LGIC1fyZWAMABfe5MtAILwCzKJjZKhQmLmQOGqug8ciHvDqIzRcGQOYEATCK1ib/EnTYRYdD048FsmqYMp0SBnF4PJjkd1ZhCFvxNkZ0BXJmL4QPricOOpld5NPAgTCKwzWeFLnwKsiHsmFMndfMOBideIodA4wUhjEEiXhuhRg+kLGY2nwaQtlIim87GIgkhLJRTJOjIePDwLhFYbOelPmwmMRD0JMJBfJrPWs7hTCdBFe7B8rM1+A4mo4pc5TDJ6FQMgvg+e80CPEKKVCMXSB3Y9F2IYQK3JPZqavYjxmSAvHKnUuBELeGazxps6HxyI2+nK5hd3Z1YM1nhR49cHHMJvtj0XzBS/UT8AIAiHfePqD4UAkaZqU6QvhD8MsVvcII6GI+aIPAiFGafMVg9WsfiwOXYC6sjilzlMOnfWyPENqQhAIvzFY44VnIl4pFaxeWGZt9KsyJTIt3AXYGGYpbC1+1qYRBt1hd18wuRBSRrFRpIglapGjgwM1pMYBj4BvDJ71ps6DQIiTJl/ms4R8lhDTFzK6gWpP2nwl01fBK2I5oSuSsXaacPCcV18qJ8SQMooTD/JlIBB+Y7DGmzYPHos4ESKUOlc5wNaxssFqmBLGL3WeYrCGrS1+xpu2AFocs9S57G3xSYJA+I3BGg+sncAudb5i4IyH6asY3UC1F3qE2KXOVw5Us7bFYQwAPx7ky0AgvCzkjdjbA/oymEXHjM3ZE4NnPTAYjl0ai3uEAzAGQAEYGuWPoQteXbFMLIPJA8zSrmJp/8DZFRCJCVUmFFfDLHW+cui8N8K+gkLhQMRa74OFwtglz5R7BoJ+G0tTASYDAuFlg2e9qTAuSgF9udzZGQg4WfdcHKj2pl0Fo2T4ybQiZZrE1sS6ZTPmiz5NnlSigoceZoQIGWYphs6zrsUnD9vrcDAY3LFjR2tr6/z586uqqkY9Zs+ePTU1NTk5ORs3blQo2BV1hiAQUkMkIfRl8qHz3sylKqav5QqD1R4YJaNI2nzFQLWXbbu4DFR74NWHImnzFIM1nqwV7LrHJw/Py1E4HK6qqnrppZdsNttDDz305JNPjjzmO9/5zuOPP+73+19//fUlS5Z4vewaUx6s8aZCyig10q5SDpxhV3Ojyy0OgZASqfOULJwmhCRh6qRwPF8GT49wx44dzc3Nzc3NUql0y5YtRUVFDz744IwZM6IHfPzxx8eOHbt48aJWqw2FQt/5zncaGhrmzp2L5ewYRNDQBW/KbLhJKJE6XzFwmnXThAPVnmXPZzJ9FfyUNl9x9o9DTF/FcANnPAW3aZm+Cn5Knauo+7uF6atIHJ4e4cGDB9etWyeVShFCOTk5c+bM2bNnT+wBn3zyycaNGy0Wy2uvvXbw4MF3332XRVEQIXu7X5okUqSKmb4Qfkqbz7qlhOQyf20BVBihROo81qUKR8Jo8ByMAVAlZY7CUusLB1laUWhCeAKhyWTKysqKfpuRkdHX1xd7QFtb27lz56qqqvbt23fffffdcMMNodCYKUbElYxGI5aLHMdgDUwQUihljtxS7wv5WXSTDFR7U+YoCEiboIY6R0qIkKuHRRsT2pp8yjSJXA8vu5SQqkXqbIm1kdpCa0ajkRgByycnODRaX1//3nvvkV9v3rw5HA7HXhBBECLRFc+YQCBAxkK1Wm2328vKyv7zn/9s2rRp1A+PROh+YkJxNUpJlCLtDKn5oi+NNTM0gzWwsJpaKXMVgzVedQ5bStgPVHvZ89+Pl8jq25RucWU0Gkf2i7DEwgRfia1Wa83XHA5HVlZWf39/9E9NJlNm5hWzL2lpaUuWLFGr1QghrVa7ePHiurq6qVw3XkNnvalz4bFIobSrlINsWk04WA2vPtRi23j4YLUnFV59qMTpfJkEA+GSJUve+9rs2bNXrVq1f/9+v9+PEOrt7a2pqVm9enXs8atXrz527JjT6UQI+f3+mpqasrKyqV89LgM1sDE9tch8eqav4hsDNV54LFIqdZ5isIZFrz4DZ6BHSK3Uuexq8bjgmSS5/fbb8/Lyrr766qeffnrlypX3339/cXExQujOO+984YUXEEJ33313UVHRqlWrnnnmmVWrVuXm5t5xxx1YTj11flvIOwg7s1Ardb6SPRVHQ96IvdUP25RTin2vPrCIkFqcLrSGZ/mEWCzet2/fBx980NLS8sorr6xfv578+Zo1a/Lz8xFCMpls7969u3fvvnDhwiOPPHLrrbeSKaZsMHgW8iYol3aVcui8NxKKsGEHnKHzXl2xTCxn/kp4LLlI7hkI+iwhNuSnODqhnB7lkqZJw8GI2xRUZXDv94ztisVi8be+9a1hP3zggQeiXxMEccMNN9xwww24zogLFFejgUwrUqVLrE1+fSnz/bCBag8UT6AaIUIpFYqhc97sa9RMXwsarPakLYAWp1zqHMXQWa/quiSmLyRu0A+C4mo0SWXNNhSDNTBdRIfU+YoBdtSXGaj2pl0FLU651HlKlrR4vCAQogEorkaLNNZsUzcAKaO0SJvHllThgTOwWoYOqXMVQ9ycJhR6IAwHI5Y6n2EW8+N1vMeSiqORMDJfhDEAOqTOZ8vGhFBllB4pcxWDZ1nx6hMvoQdCa4M/KVcqTRL674EGaVcpBs54ENPlZayNPlW6RJbMfAYH76XMVlgb/SEvw03uHQwFXGFtPqSFU85QLre3BYIe1u25NiGhB4DBGg90DuihTJdIlISjk+GyW9A5oI1YTiTPlJlrGe4UDpzxpM5TIMgRpp5ISuiKZOaL3NuYUOiBEKaL6JR2FfOrCQehihCNUucxPzo6UA0ThPRh1YrhyRN6IOw75mbbhrE8lsqCslsDZzyQQEgbNiyrHzgDKaP0yVyi7DsOgZBTQr7I0HlveiW8LdIkbb6C8TRCWDZKp9R5SsbLbsGe23TKXKbqO+5m+iriJuhAOFDt0RXLpWpB/xLoxHj/wNHuF0kQe7ZE4L20qxSDZ73hAGP5MgFH2NUT0JdCpgxNDLMU7r6gd2jMXfbYSdAxoO+YO3MZjIvSR5MvC/nC7r4gUxdw6Yg7aznzhU6EQ5Ys1s6QMThNOFDtSZmjYENhP4EgRChjkdJ0gmOdQkEHQtMJT+YSGDOhVepcJpfVm064M5dCi9Mqi9GxMsiGo1/mUu6Njgo6EPYec2cthx4hrTKXKvuOMXaT9B51Z0KPkF6ZS1UMtnjfUciGo1vmUlUvcy2eGOEGQkdHIBKMaGCZLb2yVqh7jzBzkwQcYVuzH/oHNMtcrrrEUIsjhHqPurJXQiCkVcYSZf9pTzjIdO2MeAg3EPYdd2dCd5B2mUtV/ac9IT8DN0nfCXfaVUqxDKaLaJVcKIuEIs4uBgop2Fr8iCDgZZdmcp1YkysdOs+lZfXCDoQwZkI7mVakK5IxsuQWcqOYkrlU1XuUgU5h72HoDjIjc5nKxKlpQgEHQlhKz5CsFerewwzcJPDqwxSmsid6j7qzVsCUMAM4ly8j0EAY9IQtdT6oN8GIrBUM9A8iYWT60gMpo4zIXMZMvsylw+6sFfDqwwDO5csINBD2n/IYKuQSpUD/+czKvlrde9gVobdCvfmCV5khUaZJaD0rQAghlL5QaanzBZy0Nrl3MOQxBVMqYIc1BuhL5X5riMEVw/ESaCToOw7TRYxRZUpkOrGlnta59N5j7ixocYaI5UTKHEX/aVonhi8ddmUuU8FSemYQKGOxqo87y+oFGwg9MF3EoOyVqt4jLjrPCBOEzMpaTvd4eO8RWCXMpMylSg7lywg0EJpOwGORSVnL6V5N2HcMVsswif7sid4jrixIGWVO5jIVh7ahEGIgtDX7RTIiaRpUXmZM1koVnYHQ0x/0DoX0pTBdxJjM5aq+Y27aJoaD7rC51pdRCYGQMRmLVANnmFkxnAAhBsK+4zBdxDB9iTzgCju7aVpk3XvUnblURQjxPztbqDIkcr3Y2kDTxHDfCU/qXIVYAROEjJFqRMkzZUNnGd6NcpKE+GzoO+7OgHFRZhEoaxl9k0YwQcgGWcvoS6nvPeyCFYSM49AiCmyBMBgM/uc///nd7363d+/eUQ/w+/3vvPPOc8899/777weDTKbVwlJ6NshcTt/oaB9UV2cBOlcT9h6FFYTMy1zKmfoyeAJhOByuqqp66aWXbDbbQw899OSTTw47wOfzLV++/M033/T7/b///e9XrVoVDtO7juxrAVfY1gKVl5mXvVJNT+JoyBcZPOtNr4Sl9AyjLRCGgxHTl7A+inkc2q0ez/riHTt2NDc3Nzc3S6XSLVu2FBUVPfjggzNmzIgecOTIkcbGxpMnTxIE8YMf/CAzM7O9vb2goADL2eNiOuFOnaeAysuMS7tKYWvx+20hWbKY0hMNfOXRlcilSUKcBWCVlNkKV2/QOxhSpFLb4oM13qTpMoWB2rOACSXPlIV8EWd3gP2ZiXieDgcPHly3bp1UKkUI5eTkzJkzZ8+ePbEH5OTkOJ3OG2+88Ze//OUdd9zx4IMPMhIFEUJ9xz2QKcMGIimRvlBJQ4I1LKVnCXLvchoWWfcecUOtbZbIWKw0neDAIgo8gdBkMmVlZUW/zcjI6Ovriz2gtLT0xRdf9Pl8gUDAbrcHg8FQKDTWpxFXMhqNWC6SBJky7JG1go7RUciUYQ96xsp6j7hggpAl8K4fNRqNxAhYPjnBodH6+vr33nuP/Hrz5s3hcDj2ggiCEImuCLH79u3bvn37F198gRB66qmnSktL33777c2bN4/64ZEIVUtPwoFI33H32tdyKPp8EJfsFarTvxmg+ix9x90r/m/WxMcB6mUtU53+LeUt3nvUvfwFaHFWyFqpPrTlEq5PMxqNI/tFWGJhgoHQarXW1NSQX99yyy1ZWVn9/f3RPzWZTJmZmbHH/+Mf/6isrCS/VqlUixcvPn/+fGKnnopLh1y6ErkyHSovs0LmMtVAtSfki4jlVE3Z2lr8BIE0eWyfohCIjCWqga88IX+Eukl6a5NfJCGgxVkic4nS2R1wdAY001ndIgkOjS5ZsuS9r82ePXvVqlX79+/3+/0Iod7e3pqamtWrV8cen5GRcejQIXLVhN/vP3PmTEVFxdSvPl7tHzvyb0ii/7xgVNIkka5YPvAVhVMIl75wZV8N68nYgtyWuf8khS3eewRanEUIMZG3XtO528H0hUwAzxzh7bffnpeXd/XVVz/99NMrV668//77i4uLEUJ33nnnCy+8gBB64oknTCZTVVXVM888s2LFisLCwu9+97tYTh2Xjl2O/A1a+s8LxpK9QnWJytWEbR/a8zdoqPt8EK/8Ddr2j+zUfX7vEVhByC55N2raPxZGIBSLxfv27XviiSc0Gs0rr7zy8ssvkz9fs2bN7NmzEULZ2dl1dXX33nuvUqn8+c9/vnfvXrGY7uRma6Mv4I6kzoUVhCySfY2654CTog8PesI9X7jzrodAyCIzbta07aTwsdh9wJV9DfQIWWR6VdKlL1xBDzMLxycJ22yZWCz+1re+NeyHDzzwQPRrlUp111134TpdAto/cuTfpEGwgJBNplclHbi3x2cJyfX4X4y6PnWlL1RS8ckgYWlXKQOusLXBpyvBXwN94IxHJEGGcqiuziJyvTh1vrLngCvvRva+krJxlbH5IiWVeTs+ceTdwN6WECaJSpR9jbrjE0q6CO0fwbgo+xAo/yaqOoWtHzgKb4e5D9bJv4mq0dHOPXjGk9gYCJv+bcP+mX57uP+0J3cdjJmwTsFt2tb38U8aRcKofZdjxs0QCFlnxi3atp2UTBO27rAV3J5MxSeDqci/UdO+y4EoWBZX95oFy+ewMRA2/wd/IOzc48haqZao2PjvFbgZt2i6PnMFXJinEEwn3Mp0iXaGDO/HgqnLWa02X/C5TZgr71ub/D5rOGMRFJVlHX2ZXCwnBs9h3pIp6A537uVvjzDkDZsvYP6VtX/syGfxCLWQyXXijEpl16eYU2badjpm3AKjZGwklhG51yZhHw9v3W4ruBWSAFjqcqcQq47dzgxMxfTZGAgLv5Xc/B7OkZNIGHXtdeZdDysIWYqK0dG2nXYYF2Wt/Js17binCVvftxfcBq8+LJV3o6YD9zRhy7u2wo14WpyVgXCjthnrNKHphFuZIdHkwygZS824Vdv+kSPkxzaHYGv2+22h9AUwSsZS+Tdpug+6gm5s4+GunoCt1Q8LJ1gr+xq1udbn6cc2Hh7yRjr3OQtu5W8gzFysCrrD5lpsuaPtHzvyb4LOAXupsyW6EvmlL7AV4G79wD7jZi2MkrGWXCdOu0rRfQBfi79vz79JK5JAk7OUWEbkrlPjSvJECHXsdqRdpcRVL5ONgRARqOB2bcu72DqFHTBByHp4R0fbdzryYVyU3WbcjDN3FMZF2Q9viZnmd22Fd2BrcVYGQoRmbsQ2TejsCji7AxmLYZSM1Qpv17a+b4/gGCrzDoWGznunrYYpYVYruFXTvtOBq8VhcRT75d+o6drnxDIDEvJGOvc4Mb76sDQQZi5VBewhSx2G0dH2XY68GzSEGMZMWC15pkyZJjHh2LW1fZdj2jq1WAEtzmqafJkiTWI6iaHF23bac69LgsVRLKdMl+iKZb04agt37HGkzlOoMrBVRmPrfx0CFdymbXkPw+ho+8cONpf2AVG4Rkfbdtpn3AyjZBxQcAue3FEYF+UKXLmjLe/aZ27EWTmBrYEQocI7kpvfnepjMegJ9x52Ta+CUTIOKLhN27J9qi0e8kV6Drig0DYn5OOYJgw4w5e+cEH1RE7Iv0nT9iGGe7xjtwNXviiJvYEwc5nKOxS0NkxpdLTlPXvmUpVcB2WXOSB1ngIRaGhq5Se6DzhT5igUqdDiHJBRqfRZQrYW/1Q+pHOPM3MZ3OPckDZfGYkg05dT2pCyc68zZY5ClYVzf3X2BkJCNOWV9RFU/fzgvJ+k4rsoQK2C27QtO6b0wti6HdbRcweB8m+a6jAAjItyCYHmPZpy5rmBqXxGy3u2mfjyRUnsDYQIocI7prSIomOPgxCj3GthXJQzpjhN6LoUbP3AXvJ9HcZLApSa9UPDuT8OhbwJZhKG/JGO3VBLj0vK7tX3HnFbGxMc6gv5Iu27HIXfwlxandWBMGuF2t0ftDYlOHJS/dzg/CdSYVU1h2QuVQVd4YRX1lc/N1D6/9u786Cm8jsA4C+JCQmI3CSIsGA5u4JyLrKeLDZMp5aKFHSLGRFn0dXp6iq7qFjRXZmtoDJWppaKM7oix1CKVwd0aookIiKXiKIbIiJHEkggKEeOl/QP3IyzIHK9vCTv+/krefDIN/zmm29+7/2OrTYMh7m8ZgIw5RBAdwikP70wwz0Enl0cYIYy5nD0IMDaPHPykp22jSelMzv91e03dkvm+LooYuCFkERGPP5o9TRvJkkifjAy2K7yiIM9WYwJiYyEHHG8nyaewbnDIvWzHwcC9sOVcCMTctix/q+9M5hehiq0D7+XhKQ7YhEVwI7/bru2EvnMth95mtfvET/3n+oGXQgRBAn8xv7Jednrl6rpnthwonfZ13aw5JLR8frcSiFDZ7C7SkNWn/cWa3MWdA6MjGMIw+bXZs8uDkz3xJZ/yOyW0llh5lhEBbBDt6d4fm7d/LdpdwpF1cOSuhHfxLm/92HohdDCmeq3y+7+oel1EQaFyu67w76JNhhFBbBDopBC0h3vHxJPaxvPUSnaerE/IAW6g0Yp5Ijjw+OSaXUK1SOahsy+T44xsYsKYGfZ13Ytuf2q19NZWEiLVH3Vs/wHJhYrJxh6IUQQJPBb++67Q6J701iPoP5E35IvbanzjeDdgfE8Yq0QjVY4nflGDVl9nvFWFs5U7KIC2GGFmVt7mj3Pn0an8NEZKSvc3H4ZHbuoAHYWuNMWfWbx5Lxs6qc8yx8gkRCvzZgMhTOCUjHPnBya7sjfL5piF2FEom4rkfvtssU4LoAZEhJ6jFlzWDLFhShHZeiTXFlAigPGYQEMhR51rDveq1FPKclVbzRN2dJQuDtozAJTHRpPSad4GQAd1dakicOzWBgNfjSCQoggiM9WG1SpneIMs0dnpJ6brWHooFFz+50lzZI8xW0pm7Klv4q1svwIuoNGjBVubrGI+lPhlFq8IavPlT3fxtcM66gAduyX0m18zKaY4w0n+xxDGAtXYrWuunEUQhIZ+TSTde8bEar4wNcH1ZCm5Z/9S/fY6Scw05aeno7jq3/yneODI+IPdhGUcrTlnCww1cTvDuLbFvoRctjh4TGJFv1AiysG0Md/lwUfxrM7SITm0IOAFPuGzL4PXuobkaibsvvCMljYRULSaudsW/A5QSK9N6Sb6186r7WYfKWYmr9I5M8Vvyl0wSY6YpmkLfSjLOKFd4K177bJBj3VHpO8bldFXHDWW1S4wL0t9KN0hdBvt53npsnGx1enihUD6JpzC/UW1XgEaQ49KAoQLNtn750w2Z2//+3oplqQPz05cSGck7bQd4+wq6vr8uXLMzs3/ASr/oe+USk64U+1GoS/T9RWIl9+AsMvDkCfwr5n1n432Qyz7sqhR2ekgQfg7qCJCD7seP+gWPbkvcuODIvVT87LgtOgxU1ExHnn6m9FzTnvHTUja1EI/z2IdYvrtRCKxeINGzbMuBDa+Jp5xC3g7xepR345iEI9oqmI6+itH9nIX2zpCveKTAQr3NwxiH71sxd9Tb9ciVuLamuPSSo2v1qX72LtScMlPDDnXNnzgw87lK15MeFaM513hq5GvPj4C9v5iyDHTYRDECOGt7g5R8rfJxo/OE7Rj1b9uTvooIOZDbaLquuvEObl5fn6+g4NzXD1rDGh6UxFP/rj4ucPj/eOyt52DUd61WUR7fMY5PUVblj/v4CesYtdvbdYX2e3V33Vo5S/bfGhbvXVde3dlUPxdR6wx5aJ8U202VDp3pQtvf2nTt08s6Eu1a1Nr7jbu8IymGEZMHfQpCxwp23kL+6tH6mI69B1ct68UvH3iS57Prf8iOb3JeZTAPRXCDs6Om7dupWYmDibP0K3p/y2zPUPd9wHhcp8z+e8vT1d3KF/LRe6RFpEXlpEocE6MqaGREY+/sJ2c4snOqrN9/2p9eLAy/+8Lg4WLIqY//vb7nO+5CAwBDa+ZrE1i6mW5OIggbhmpP5EX+EygZWX2eYWD1hf2ySZ2VDWV7jNY5DLItq77w79d2tnUYAAISHxjR4RF5zJVOw/2LX6lZmZyWazJ/kFzN8wAAAAEzL7woTVF+rW1taSkpKxxwkJCW5ublN/S9N6IS2qJVGgI0gUWg2ieqOhLTCOaT9g9hQDKGy6Syi4fKRjVQgHBgYaGxvHHkdHR2P0KgiCQBUkFBIZgSpIKFAFiQaXj3SsCmFYWJiuRwgAAAAYLPhyDQAAgND0PeguPDycxYIJ7wAAAAwFLBQEAACA0ODSKAAAAEKDQggAAIDQoBACAAAgNCiEAAAACA0KIQAAAEIzrDWL+Xy+VqtdsWLF2FO1Wl1aWioUCgMCAthsNr6xAYCvysrKmpoaJyen+Ph4Gg12nsKNXC4/ffq07qmPj8+mTZtwjIewurq6uFxuQkKC7siMc8SAeoQPHjyIjo7m8XhjTzUaDZvNzs7OlsvlO3fuTE1NxTc8Arpx44a9vf32n+Xk5OAdEXGlp6dzOJz+/v7c3NzIyEiVSoV3RMRVVVV19uzZzp9JpVK8IyKi8bvbziZHDKJHiKLonj178vPzLS0tdQdLS0sFAoFAIKBSqbt37/b09ExOTnZ3d8cxTqLh8XgbN26Mjo4eHh5evXq1gwNsC46Pnp6ejIyM5uZmb29vFEWDgoIKCgo4HA7ecREU5AXu8vLyUlJSnJycbG3fblU4yxwxiB6hUqmkUCiPHz/28/PTHeRyuZGRkVQqFUEQZ2dnf3//8vJy/GIkIj6fX1RUdOnSpZycHB8fn+rqarwjIigej+fi4uLt7Y0gCIVCiYqKunnzJt5BERfkBe7G7247yxwxiELIYDCys7MXLlz47kGxWOzk5KR7ymQyRSKR3kMjNDabff369cLCQi6Xu23btuTkZLwjIijIBYMCeYG7o0ePBgcHv3tkljmCz6XRioqK2trasceHDh0ikSbYd0Oj0bx7nEQikckGUbZNWG5urkQiQRDE1dWVw+GkpaXpfsThcLKysvALjdAgFwzK+LyQy+VWVlY4hgRmmSP4FMLOzk7dboVarXbCQujk5DT2oTxGLBbDat1Ya21t7ejoQBBEoVAMDg4WFRUlJCQwGAwEQVAUnbCZgB5ALhiOCfNi7A4OwNEscwSfQpiUlJSUlDT576xZs+bAgQNKpZJGo/X09DQ2Nq5du1Y/4RHWqVOndI+VSuXevXutrKzi4uIQBCkuLtZNawF6tnLlSqFQKBAIPDw8UBQtLy/ftWsX3kERFJ1OH58X5ubmeMdFdLPMEYMYNTqhmJiYc+fOrVq1at26dQUFBdu3b/fy8sI7KAKh0WhZWVk7duyoq6sTiUTXrl27c+cO3kERFIvFOnjwYEREBIfD4fF4FAply5YteAdFUJAXhmmWOWJY2zBduXLF1dVV1/NAUbSsrKytrc3f3z8qKgrf2IipqamJy+VSqdSYmJh370UD/ePxeDU1NUwmMzY2lk6n4x0OoUFeGIJ79+4JhcJ3J9TPOEcMqxACAAAAegZjzwAAABAaFEIAAACEBoUQAAAAoUEhBAAAQGhQCAEAABAaFEIAAACEBoUQAAAAoUEhBAAAQGhQCAEAABAaFEIAAACE9n+qA7jpk09WBAAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -176,9 +168,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/gnuplot_kernel/__init__.py b/gnuplot_kernel/__init__.py
deleted file mode 100644
index ae43d9c..0000000
--- a/gnuplot_kernel/__init__.py
+++ /dev/null
@@ -1,11 +0,0 @@
-from .kernel import GnuplotKernel
-from .magics import register_ipython_magics
-
-__all__ = ['GnuplotKernel']
-
-
-def load_ipython_extension(ipython):
-    """
-    Load the extension in IPython
-    """
-    register_ipython_magics()
diff --git a/gnuplot_kernel/__main__.py b/gnuplot_kernel/__main__.py
deleted file mode 100644
index 65afecc..0000000
--- a/gnuplot_kernel/__main__.py
+++ /dev/null
@@ -1,9 +0,0 @@
-from .kernel import GnuplotKernel
-
-try:
-    from ipykernel.kernelapp import IPKernelApp
-except ImportError:
-    from IPython.kernel.zmq.kernelapp import IPKernelApp
-
-
-IPKernelApp.launch_instance(kernel_class=GnuplotKernel)
diff --git a/gnuplot_kernel/kernel.py b/gnuplot_kernel/kernel.py
deleted file mode 100644
index 497b441..0000000
--- a/gnuplot_kernel/kernel.py
+++ /dev/null
@@ -1,280 +0,0 @@
-from __future__ import print_function
-import re
-import os.path
-import time
-import random
-
-from IPython.display import Image, SVG
-from metakernel import MetaKernel, ProcessMetaKernel, pexpect, u
-from metakernel.process_metakernel import TextOutput
-
-from .replwrap import GnuplotREPLWrapper
-from .exceptions import GnuplotError
-
-# This is the only place that the version is
-# specified
-__version__ = '0.2.2'
-
-try:
-    FileNotFoundError
-except NameError:
-    # Python 2
-    FileNotFoundError = OSError
-
-# name of the command i.e first token
-CMD_RE = re.compile(r'^\s*(\w+)\s?')
-# "set multiplot" and abbreviated variants
-MULTI_RE = re.compile(r'\s*set\s+multip(?:l|lo|lot)?')
-# "unset multiplot" and abbreviated variants
-UNMULTI_RE = re.compile(r'\s*uns(?:e|et)?\s+multip(?:l|lo|lot)?')
-PLOT_CMDS = {
-    'plot', 'plo', 'pl', 'p',
-    'splot', 'splo', 'spl', 'sp',
-    'replot', 'replo', 'repl', 'rep',
-}
-
-
-class GnuplotKernel(ProcessMetaKernel):
-    implementation = 'Gnuplot Kernel'
-    implementation_version = __version__
-    language = 'gnuplot'
-    language_version = '5.0'
-    banner = 'Gnuplot Kernel'
-    language_info = {
-        'mimetype': 'text/x-gnuplot',
-        'name': 'gnuplot',
-        'file_extension': '.gp',
-        'codemirror_mode': 'Octave',
-        'help_links': MetaKernel.help_links,
-    }
-
-    inline_plotting = True
-    reset_code = ''
-    _first = True
-    _image_files = []
-    _error = False
-
-    @staticmethod
-    def is_plot(stmt):
-        """
-        Return True if stmt is a plot statement
-        """
-        m = re.match(CMD_RE, stmt)
-        if m:
-            return m.group(1) in PLOT_CMDS
-        return False
-
-    @staticmethod
-    def is_set_multiplot(stmt):
-        """
-        Return True if stmt is a plot statement
-        """
-        m = re.match(MULTI_RE, stmt)
-        return True if m else False
-
-    @staticmethod
-    def is_unset_multiplot(stmt):
-        """
-        Return True if stmt is a plot statement
-        """
-        m = re.match(UNMULTI_RE, stmt)
-        return True if m else False
-
-    def bad_prompt_warning(self):
-        """
-        Print warning if the prompt is not 'gnuplot>'
-        """
-        if not self.wrapper.prompt.startswith('gnuplot>'):
-            msg = ("Warning: The prompt is currently set "
-                   "to '{}'".format(self.wrapper.prompt))
-            print(msg)
-
-    def do_execute_direct(self, code):
-        """
-        Execute gnuplot code
-        """
-        if self._first:
-            self._first = False
-            self.handle_plot_settings()
-
-        if self.inline_plotting:
-            code = self.add_inline_image_statements(code)
-
-        success = True
-
-        try:
-            result = super(GnuplotKernel,
-                           self).do_execute_direct(code, silent=True)
-        except GnuplotError as e:
-            result = TextOutput(e.message)
-            success = False
-
-        if self.reset_code:
-            super(GnuplotKernel, self).do_execute_direct(
-                self.reset_code, silent=True)
-
-        if self.inline_plotting:
-            if success:
-                self.display_images()
-            self.delete_image_files()
-
-        self.bad_prompt_warning()
-
-        # No empty strings
-        return result if (result and result.output) else None
-
-    def add_inline_image_statements(self, code):
-        """
-        Add 'set output ...' before every plotting statement
-
-        This is what powers inline plotting
-        """
-        # Ensure that there are no stale images
-        self.delete_image_files()
-
-        def append_output_stmt(lines):
-            filename = self.get_image_filename()
-            if filename:
-                lines.append("set output '{}'".format(filename))
-
-        # We automatically create an output file before every
-        # recognisable plot statement is executed or before
-        # a multiplot block. When inside a multiplot block
-        # image files are not created.
-        lines = []
-        inside_multiplot = False
-        for stmt in code.splitlines():
-            if self.is_set_multiplot(stmt):
-                inside_multiplot = True
-                append_output_stmt(lines)
-            elif self.is_unset_multiplot(stmt):
-                inside_multiplot = False
-
-            if self.is_plot(stmt) and not inside_multiplot:
-                append_output_stmt(lines)
-
-            lines.append(stmt)
-
-        # Make gnuplot flush the output
-        if not lines[-1].endswith('\\'):
-            lines.append('unset output')
-        code = '\n'.join(lines)
-        return code
-
-    def get_image_filename(self):
-        """
-        Create file to which gnuplot will write the plot
-
-        Returns the filename.
-        """
-        # we could use tempfile.NamedTemporaryFile but we do not
-        # want to create the file, gnuplot will create it.
-        # Later on when we check if the file exists we know
-        # whodunnit.
-        settings = self.plot_settings
-        filename = '/tmp/gnuplot-inline-{}.{}.{}'.format(
-            time.time(),
-            random.randint(1, 10**12),
-            settings['format'])
-        filename = filename
-        self._image_files.append(filename)
-        return filename
-
-    def display_images(self):
-        """
-        Display images if gnuplot wrote to them
-        """
-        settings = self.plot_settings
-        if self.inline_plotting:
-            if settings['format'] == 'svg':
-                _Image = SVG
-            else:
-                _Image = Image
-
-        for filename in self._image_files:
-            try:
-                size = os.path.getsize(filename)
-            except FileNotFoundError:
-                size = 0
-
-            if not size:
-                msg = ("An unknown error occured. Failed to "
-                       "read and display image file from "
-                       "gnuplot.")
-                print(msg)
-                continue
-
-            im = _Image(filename)
-            self.Display(im)
-
-    def delete_image_files(self):
-        """
-        Delete the image files
-        """
-        # After display_images(), the real images are
-        # no longer required.
-        for filename in self._image_files:
-            try:
-                os.remove(filename)
-            except FileNotFoundError:
-                pass
-
-        self._image_files = []
-
-    def makeWrapper(self):
-        """
-        Start gnuplot and return wrapper around the REPL
-        """
-        if not pexpect.which('gnuplot'):
-            raise Exception("gnuplot not found.")
-
-        # We don't want help commands getting stuck,
-        # use a non interactive PAGER
-        command = 'env PAGER=cat gnuplot'
-        d = dict(cmd_or_spawn=command,
-                 prompt_regex=u('\w*> $'),
-                 prompt_change_cmd=None)
-        wrapper = GnuplotREPLWrapper(**d)
-        # No sleeping before sending commands to gnuplot
-        wrapper.child.delaybeforesend = 0
-        return wrapper
-
-    def do_shutdown(self, restart):
-        """
-        Exit the gnuplot process and any other underlying stuff
-        """
-        self.wrapper.exit()
-        super(GnuplotKernel, self).do_shutdown(restart)
-
-    def get_kernel_help_on(self, info, level=0, none_on_fail=False):
-        obj = info.get('help_obj', '')
-        if not obj or len(obj.split()) > 1:
-            if none_on_fail:
-                return None
-            else:
-                return ''
-        res = self.do_execute_direct('help %s' % obj)
-        text = res.output.strip().rstrip('gnuplot>')
-        self.bad_prompt_warning()
-        return text
-
-    def handle_plot_settings(self):
-        """
-        Handle the current plot settings
-
-        This is used by the gnuplot line magic. The plot magic
-        is innadequate.
-        """
-        settings = self.plot_settings
-        if ('termspec' not in settings or
-                not settings['termspec']):
-            settings['termspec'] = ('pngcairo size 385, 256'
-                                    ' font "Arial,10"')
-        if ('format' not in settings or
-                not settings['format']):
-            settings['format'] = 'png'
-
-        self.inline_plotting = settings['backend'] == 'inline'
-
-        cmd = 'set terminal {}'.format(settings['termspec'])
-        super(GnuplotKernel, self).do_execute_direct(cmd)
diff --git a/gnuplot_kernel/replwrap.py b/gnuplot_kernel/replwrap.py
deleted file mode 100644
index 5a578ba..0000000
--- a/gnuplot_kernel/replwrap.py
+++ /dev/null
@@ -1,121 +0,0 @@
-import re
-import textwrap
-import signal
-
-from metakernel import REPLWrapper
-from metakernel.pexpect import TIMEOUT
-from .exceptions import GnuplotError
-
-CRLF = '\r\n'
-ERROR_REs = [re.compile(r'^\s*\^\s*\n')]
-
-
-class GnuplotREPLWrapper(REPLWrapper):
-    # The prompt after the commands run
-    prompt = ''
-
-    def exit(self):
-        """
-        Exit the gnuplot process
-        """
-        try:
-            self._force_prompt(timeout=.01)
-        except GnuplotError:
-            return self.child.kill(signal.SIGKILL)
-
-        self.sendline('exit')
-
-    def is_error_output(self, text):
-        """
-        Return True if text is recognised as error text
-        """
-        for pattern in ERROR_REs:
-            if pattern.match(text):
-                return True
-        return False
-
-    def validate_input(self, code):
-        """
-        Deal with problematic input
-
-        Raises GnuplotError if it cannot deal with it.
-        """
-        if code.endswith('\\'):
-            raise GnuplotError("Do not execute code that "
-                               "endswith backslash.")
-
-        # Do not get stuck in the gnuplot process
-        code = code.replace('\\\n', ' ')
-        return code
-
-    def send(self, cmd):
-        self.child.send(cmd + '\r')
-
-    def _force_prompt(self, timeout=30, n=4):
-        """
-        Force prompt
-        """
-        quick_timeout = .05
-
-        if timeout < quick_timeout:
-            quick_timeout = timeout
-
-        def quick_prompt():
-            try:
-                self._expect_prompt(timeout=quick_timeout)
-                return True
-            except TIMEOUT:
-                return False
-
-        def patient_prompt():
-            try:
-                self._expect_prompt(timeout=timeout)
-                return True
-            except TIMEOUT:
-                return False
-
-        # Eagerly try to get a prompt quickly,
-        # If that fails wait a while
-        for i in range(n):
-            if quick_prompt():
-                break
-
-            # Probably stuck in help output
-            if self.child.before:
-                self.send(self.child.linesep)
-        else:
-            # Probably long computation going on
-            if not patient_prompt():
-                msg = ("gnuplot prompt failed to return in "
-                       "in {} seconds").format(timeout)
-                raise GnuplotError(msg)
-
-    def run_command(self, code, timeout=-1, stream_handler=None,
-                    stdin_handler=None):
-        """
-        Run code
-
-        This overrides the baseclass method to allow for
-        input validation and error handling.
-        """
-        code = self.validate_input(code)
-
-        # Split up multiline commands and feed them in bit-by-bit
-        stmts = code.splitlines()
-        output = []
-        for line in stmts:
-            self.send(line)
-            self._force_prompt()
-
-            # Removing any crlfs makes subsequent
-            # processing cleaner
-            retval = self.child.before.replace(CRLF, '\n')
-            self.prompt = self.child.after
-            if self.is_error_output(retval):
-                msg = '{}\n{}'.format(
-                    line, textwrap.dedent(retval))
-                raise GnuplotError(msg)
-
-            output.append(retval)
-
-        return ''.join(output)
diff --git a/gnuplot_kernel/tests/utils.py b/gnuplot_kernel/tests/utils.py
deleted file mode 100644
index 9194a55..0000000
--- a/gnuplot_kernel/tests/utils.py
+++ /dev/null
@@ -1,27 +0,0 @@
-import os
-
-try:
-    FileNotFoundError
-except NameError:
-    # Python 2
-    FileNotFoundError = OSError
-
-
-def remove_files(filenames):
-    """
-    Return a function at remove files
-
-    This is meant to be used as a teardown
-    function.
-    """
-    if not isinstance(filenames, (tuple, list)):
-        filenames = (filenames,)
-
-    def _remove_files():
-        for filename in filenames:
-            try:
-                os.remove(filename)
-            except FileNotFoundError:
-                pass
-
-    return _remove_files
diff --git a/how-to-release.rst b/how-to-release.rst
deleted file mode 100644
index d853a02..0000000
--- a/how-to-release.rst
+++ /dev/null
@@ -1,82 +0,0 @@
-##############
-How to release
-##############
-
-Testing
-=======
-
-* `cd` to the root of project and run
-  ::
-
-    nosetests
-
-* Once all the tests pass move on
-
-
-Tagging
-=======
-
-* Check out the master branch, open `gnuplot_kernel/kernel.py`
-  increment the `__version__` string and make a commit.
-
-* Tag with the version number e.g
-  ::
-
-    git tag v0.1.0
-
-  Note the `v` before the version number.
-
-* Push tag upstream
-  ::
-
-    git push upstream v0.1.0
-
-
-Packaging
-=========
-
-* Make sure your `.pypirc` file is setup
-  `correctly <http://docs.python.org/2/distutils/packageindex.html>`_.
-  ::
-
-    cat ~/.pypirc
-
-* Clean up
-  ::
-
-    rm -rf build dist
-
-* Build distribution
-  ::
-
-    python setup.py sdist bdist_wheel
-
-* (optional) Upload to PyPi test repository
-  and then try install and test
-  ::
-
-     twine upload -r pypitest dist/*
-
-     mkvirtualenv test-gnuplot-kernel
-
-     pip install -r pypyitest gnuplot_kernel
-
-     cd cdsitepackages
-
-     cd gnuplot_kernel
-
-     nosetests
-
-     cd ..
-
-     deactivate
-
-     rmvirtualenv test-gnuplot-kernel
-
-
-* Upload to PyPi
-  ::
-
-    twine upload dist/*
-
-* Done.
diff --git a/postBuild b/postBuild
new file mode 100644
index 0000000..f6b94fe
--- /dev/null
+++ b/postBuild
@@ -0,0 +1 @@
+python -m gnuplot_kernel install --user
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..d3bd177
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,179 @@
+[project]
+name = "gnuplot_kernel"
+description = "A gnuplot kernel for Jupyter"
+license = {file = "LICENSE"}
+authors = [
+  {name = "Hassan Kibirige", email = "has2k1@gmail.com"},
+]
+dynamic = ["version"]
+readme = "README.md"
+classifiers = [
+    "Framework :: IPython",
+    "Intended Audience :: End Users/Desktop",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: BSD License",
+    "Programming Language :: Python :: 3",
+    "Topic :: Scientific/Engineering :: Visualization",
+    "Topic :: System :: Shells",
+]
+
+dependencies = [
+    "metakernel>=0.30.0",
+    "jupyter>=1.1.1",
+]
+
+requires-python = ">=3.10"
+
+[project.optional-dependencies]
+
+dev = [
+    "gnuplot_kernel[test]",
+    "ruff",
+    "matplotlib>=3.8.0",
+    "pyright>=1.1.405",
+]
+
+test = [
+    "pytest-cov>=4.0.0",
+]
+
+
+[project.urls]
+homepage = "https://github.com/has2k1/gnuplot_kernel"
+repository = "https://github.com/has2k1/gnuplot_kernel"
+ci = "https://github.com/has2k1/gnuplot_kernel/actions"
+
+########## Build System ##########
+[build-system]
+requires = [
+    "setuptools>=59",
+    "setuptools_scm[toml]>=6.4",
+    "wheel",
+]
+build-backend = "setuptools.build_meta"
+
+########## Tool - Setuptools ##########
+# https://setuptools.pypa.io/en/latest/userguide/pyproject_config.html
+
+[tool.setuptools_scm]
+fallback_version = "999"
+version_scheme = "post-release"
+
+
+########## Tool - Pytest ##########
+[tool.pytest.ini_options]
+testpaths = [
+    "tests"
+]
+addopts = "--pyargs --cov=src/gnuplot_kernel --cov-report=xml --import-mode=importlib"
+
+########## Tool - Coverage ##########
+# Coverage.py
+[tool.coverage.run]
+branch = true
+source = ["src"]
+include = [
+   "src/gnuplot_kernel/*"
+]
+omit = [
+    "src/gnuplot_kernel/__main__.py"
+]
+disable_warnings = ["include-ignored"]
+
+[tool.coverage.report]
+exclude_lines = [
+    "pragma: no cover",
+    "def __repr__",
+    "if __name__ == .__main__.:",
+    "def register_ipython_magics",
+    "def load_ipython_extension"
+]
+precision = 1
+
+########## Tool - Ruff ##########
+[tool.ruff]
+line-length = 79
+
+[tool.ruff.lint]
+select = [
+   "E",
+   "F",
+   "I",
+   "TCH",
+   "Q",
+   "PIE",
+   "PTH",
+   "PD",
+   "PYI",
+   "RSE",
+   "SIM",
+   "B904",
+   "FLY",
+   "NPY",
+   "PERF102"
+]
+ignore = [
+    "E741",  # Ambiguous l
+    "E743",  # Ambiguous I
+    # .reset_index, .rename, .replace
+    # This will remain the correct choice until we enable copy-on-write
+    "PD002",
+    # Use specific rule codes when ignoring type issues and
+    # not # type: ignore
+    "PGH003"
+]
+
+# Allow autofix for all enabled rules (when `--fix`) is provided.
+fixable = ["ALL"]
+unfixable = []
+
+# Exclude a variety of commonly ignored directories.
+exclude = [
+    "**/__pycache__",
+    "**/*.ipynb",
+]
+
+# Allow unused variables when underscore-prefixed.
+dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
+
+########## Tool - Pyright ##########
+[tool.pyright]
+# Paths of directories or files that should be included. If no paths
+# are specified, pyright defaults to the directory that contains the
+# config file. Paths may contain wildcard characters ** (a directory or
+# multiple levels of directories), * (a sequence of zero or more
+# characters), or ? (a single character). If no include paths are
+# specified, the root path for the workspace is assumed.
+include = [
+    "src/gnuplot_kernel/"
+]
+
+# Paths of directories or files whose diagnostic output (errors and
+# warnings) should be suppressed even if they are an included file or
+# within the transitive closure of an included file. Paths may contain
+# wildcard characters ** (a directory or multiple levels of
+# directories), * (a sequence of zero or more characters), or ? (a
+# single character).
+ignore = []
+
+# Set of identifiers that should be assumed to contain a constant
+# value wherever used within this program. For example, { "DEBUG": true
+# } indicates that pyright should assume that the identifier DEBUG will
+# always be equal to True. If this identifier is used within a
+# conditional expression (such as if not DEBUG:) pyright will use the
+# indicated value to determine whether the guarded block is reachable
+# or not. Member expressions that reference one of these constants
+# (e.g. my_module.DEBUG) are also supported.
+defineConstant = { DEBUG = true }
+
+# typeCheckingMode = "strict"
+useLibraryCodeForTypes = true
+reportUnnecessaryTypeIgnoreComment = true
+
+# Specifies a list of execution environments (see below). Execution
+# environments are searched from start to finish by comparing the path
+# of a source file with the root path specified in the execution
+# environment.
+executionEnvironments = []
+
+stubPath = ""
diff --git a/setup.cfg b/setup.cfg
deleted file mode 100644
index 5e40900..0000000
--- a/setup.cfg
+++ /dev/null
@@ -1,2 +0,0 @@
-[wheel]
-universal = 1
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 8a91d4f..0000000
--- a/setup.py
+++ /dev/null
@@ -1,105 +0,0 @@
-import sys
-import os
-import json
-import pkgutil
-
-from distutils import log
-from distutils.command.install import install
-from setuptools import setup
-try:
-    from jupyter_client.kernelspec import install_kernel_spec
-except ImportError:
-    from IPython.kernel.kernelspec import install_kernel_spec
-from IPython.utils.tempdir import TemporaryDirectory
-
-
-kernel_json = {
-    'argv': [sys.executable,
-             '-m', 'gnuplot_kernel',
-             '-f', '{connection_file}'],
-    'display_name': 'gnuplot',
-    'language': 'gnuplot',
-    'name': 'gnuplot',
-}
-
-
-def install_kernel_resources(destination,
-                             resource='gnuplot_kernel',
-                             files=None):
-    """
-    Copy the resource files to the kernelspec folder.
-    """
-    if files is None:
-        files = ['logo-64x64.png', 'logo-32x32.png']
-
-    for filename in files:
-        try:
-            data = pkgutil.get_data(resource,
-                                    os.path.join('images', filename))
-            with open(os.path.join(destination, filename), 'wb') as fp:
-                fp.write(data)
-        except Exception as e:
-            sys.stderr.write(str(e))
-
-
-class install_with_kernelspec(install):
-    def run(self):
-        install.run(self)
-        with TemporaryDirectory() as td:
-            os.chmod(td, 0o755)  # Starts off as 700, not user readable
-            with open(os.path.join(td, 'kernel.json'), 'w') as f:
-                json.dump(kernel_json, f, sort_keys=True)
-            log.info('Installing kernel spec')
-            install_kernel_resources(td, files=['logo-64x64.png'])
-            kernel_name = kernel_json['name']
-            try:
-                install_kernel_spec(td, kernel_name, user=self.user,
-                                    replace=True)
-            except:
-                install_kernel_spec(td, kernel_name, user=not self.user,
-                                    replace=True)
-
-
-svem_flag = '--single-version-externally-managed'
-if svem_flag in sys.argv:
-    # Die, setuptools, die.
-    sys.argv.remove(svem_flag)
-
-
-with open('gnuplot_kernel/kernel.py', 'rb') as fid:
-    for line in fid:
-        line = line.decode('utf-8')
-        if line.startswith('__version__'):
-            version = line.strip().split()[-1][1:-1]
-            break
-
-
-setup(name='gnuplot_kernel',
-      version=version,
-      description='A gnuplot kernel for Jupyter',
-      long_description=open('README.rst', 'r').read(),
-      author='Hassan Kibirige',
-      author_email='has2k1@gmail.com',
-      license='BSD',
-      url="https://github.com/has2k1/gnuplot_kernel",
-      cmdclass={'install': install_with_kernelspec},
-      install_requires=[
-          'metakernel >= 0.10.5',
-          'notebook>=4.0'],
-      packages=['gnuplot_kernel',
-                'gnuplot_kernel.magics',
-                'gnuplot_kernel.tests'],
-      package_data={
-          'gnuplot_kernel': [
-              'images/logo-64x64.png']},
-      classifiers=[
-          'Framework :: IPython',
-          'Intended Audience :: End Users/Desktop',
-          'Intended Audience :: Science/Research',
-          'License :: OSI Approved :: BSD License',
-          'Programming Language :: Python :: 2',
-          'Programming Language :: Python :: 3',
-          'Topic :: Scientific/Engineering :: Visualization',
-          'Topic :: System :: Shells',
-      ]
-      )
diff --git a/src/gnuplot_kernel/__init__.py b/src/gnuplot_kernel/__init__.py
new file mode 100644
index 0000000..2912503
--- /dev/null
+++ b/src/gnuplot_kernel/__init__.py
@@ -0,0 +1,23 @@
+"""
+Gnuplot Kernel Package
+"""
+
+from contextlib import suppress
+from importlib.metadata import PackageNotFoundError
+
+from .kernel import GnuplotKernel
+from .magics import register_ipython_magics
+from .utils import get_version
+
+__all__ = ["GnuplotKernel"]
+
+
+with suppress(PackageNotFoundError):
+    __version__ = get_version("gnuplot_kernel")
+
+
+def load_ipython_extension(ipython):
+    """
+    Load the extension in IPython
+    """
+    register_ipython_magics()
diff --git a/src/gnuplot_kernel/__main__.py b/src/gnuplot_kernel/__main__.py
new file mode 100644
index 0000000..4b17c0f
--- /dev/null
+++ b/src/gnuplot_kernel/__main__.py
@@ -0,0 +1,4 @@
+from .kernel import GnuplotKernel
+
+if __name__ == "__main__":
+    GnuplotKernel.run_as_main()
diff --git a/gnuplot_kernel/exceptions.py b/src/gnuplot_kernel/exceptions.py
similarity index 99%
rename from gnuplot_kernel/exceptions.py
rename to src/gnuplot_kernel/exceptions.py
index 02bebbb..29dd510 100644
--- a/gnuplot_kernel/exceptions.py
+++ b/src/gnuplot_kernel/exceptions.py
@@ -1,5 +1,4 @@
 class GnuplotError(Exception):
-
     def __init__(self, message):
         self.args = (message,)
         self.message = message
diff --git a/src/gnuplot_kernel/images/logo-32x32.png b/src/gnuplot_kernel/images/logo-32x32.png
new file mode 100644
index 0000000..070ab09
Binary files /dev/null and b/src/gnuplot_kernel/images/logo-32x32.png differ
diff --git a/gnuplot_kernel/images/logo-64x64.png b/src/gnuplot_kernel/images/logo-64x64.png
similarity index 100%
rename from gnuplot_kernel/images/logo-64x64.png
rename to src/gnuplot_kernel/images/logo-64x64.png
diff --git a/gnuplot_kernel/images/logo.gp b/src/gnuplot_kernel/images/logo.gp
similarity index 100%
rename from gnuplot_kernel/images/logo.gp
rename to src/gnuplot_kernel/images/logo.gp
diff --git a/src/gnuplot_kernel/kernel.py b/src/gnuplot_kernel/kernel.py
new file mode 100644
index 0000000..5701932
--- /dev/null
+++ b/src/gnuplot_kernel/kernel.py
@@ -0,0 +1,370 @@
+from __future__ import annotations
+
+import contextlib
+import sys
+import uuid
+from itertools import chain
+from pathlib import Path
+from typing import cast
+
+from IPython.display import SVG, Image
+from metakernel import MetaKernel, ProcessMetaKernel, pexpect
+from metakernel.process_metakernel import TextOutput
+
+from .exceptions import GnuplotError
+from .replwrap import PROMPT_RE, PROMPT_REMOVE_RE, GnuplotREPLWrapper
+from .statement import STMT
+from .utils import get_version
+
+IMG_COUNTER = "__gpk_img_index"
+IMG_COUNTER_FMT = "%03d"
+
+
+class GnuplotKernel(ProcessMetaKernel):
+    """
+    GnuplotKernel
+    """
+
+    implementation = "Gnuplot Kernel"
+    implementation_version = get_version("gnuplot_kernel")
+    language = "gnuplot"
+    _banner = "Gnuplot Kernel"
+    language_version = "5.0"  # pyright: ignore[reportAssignmentType,reportIncompatibleMethodOverride]
+    language_info = {
+        "mimetype": "text/x-gnuplot",
+        "name": "gnuplot",
+        "file_extension": ".gp",
+        "codemirror_mode": "Octave",
+        "help_links": MetaKernel.help_links,
+    }
+    kernel_json = {
+        "argv": [
+            sys.executable,
+            "-m",
+            "gnuplot_kernel",
+            "-f",
+            "{connection_file}",
+        ],
+        "display_name": "gnuplot",
+        "language": "gnuplot",
+        "name": "gnuplot",
+    }
+
+    inline_plotting = True
+    reset_code = ""
+    _first = True
+    _image_files: list[Path] = []
+    _error = False
+
+    wrapper: GnuplotREPLWrapper
+    _bad_prompts: set = set()
+
+    def check_prompt(self):
+        """
+        Print warning if the prompt looks bad
+
+        A bad prompt is one that does not contain the string 'gnuplot>'.
+        The warning is printed once per bad prompt.
+        """
+        prompt = cast("str", self.wrapper.prompt)
+        if "gnuplot>" not in prompt and prompt not in self._bad_prompts:
+            print(f"Warning: The prompt is currently set to '{prompt}'")
+            self._bad_prompts.add(prompt)
+
+    def do_execute_direct(self, code, silent=False):
+        # We wrap the real function so that gnuplot_kernel can
+        # give a message when an exception occurs. Without
+        # this, an exception happens silently
+        try:
+            return self._do_execute_direct(code)
+        except Exception as err:
+            print(f"Error: {err}")
+            raise err
+
+    def _do_execute_direct(self, code: str) -> TextOutput | None:
+        """
+        Execute gnuplot code
+        """
+        if self._first:
+            self._first = False
+            self.handle_plot_settings()
+
+        if self.inline_plotting:
+            code = self.add_inline_image_statements(code)
+
+        success = True
+
+        try:
+            result = super().do_execute_direct(code, silent=True)
+        except GnuplotError as e:
+            result = TextOutput(e.message)
+            success = False
+
+        if self.reset_code:
+            super().do_execute_direct(self.reset_code, silent=True)
+
+        if self.inline_plotting:
+            if success:
+                self.display_images()
+            self.delete_image_files()
+
+        self.check_prompt()
+
+        # No empty strings
+        return result if (result and result.output) else None
+
+    def add_inline_image_statements(self, code: str) -> str:
+        """
+        Add 'set output ...' before every plotting statement
+
+        This is what powers inline plotting
+        """
+
+        # "set output sprintf('foobar.%d.png', counter);"
+        # "counter=counter+1"
+        def set_output_inline(lines):
+            tpl = self.get_image_filename()
+            if tpl:
+                cmd = (
+                    f"set output sprintf('{tpl}', {IMG_COUNTER});"
+                    f"{IMG_COUNTER}={IMG_COUNTER}+1"
+                )
+                lines.append(cmd)
+
+        # We automatically create an output file for the following
+        # cases if the user has not created one.
+        #    - before every plot statement that is not in a
+        #      multiplot block
+        #    - before every multiplot block
+
+        lines = []
+        sm = StateMachine()
+        is_joined_stmt = False
+        for line in code.splitlines():
+            stmt = STMT(line)
+            sm.transition(stmt)
+            add_inline_plot = (
+                sm.prev_cur
+                in (("none", "plot"), ("none", "multiplot"), ("plot", "plot"))
+                and not is_joined_stmt
+            )
+            if add_inline_plot:
+                set_output_inline(lines)
+
+            lines.append(stmt)
+            is_joined_stmt = stmt.strip().endswith("\\")
+
+        # Make gnuplot flush the output
+        if not lines[-1].endswith("\\"):
+            lines.append("unset output")
+        code = "\n".join(lines)
+        return code
+
+    def get_image_filename(self):
+        """
+        Create file to which gnuplot will write the plot
+
+        Returns the filename.
+        """
+        # we could use tempfile.NamedTemporaryFile but we do not
+        # want to create the file, gnuplot will create it.
+        # Later on when we check if the file exists we know
+        # whodunnit.
+        fmt = self.plot_settings["format"]
+        filename = Path(
+            f"/tmp/gnuplot-inline-{uuid.uuid1()}.{IMG_COUNTER_FMT}.{fmt}"
+        )
+        self._image_files.append(filename)
+        return filename
+
+    def iter_image_files(self):
+        """
+        Iterate over the image files
+        """
+        it = chain(
+            *[
+                sorted(f.parent.glob(f.name.replace(IMG_COUNTER_FMT, "*")))
+                for f in self._image_files
+            ]
+        )
+        return it
+
+    def display_images(self):
+        """
+        Display images if gnuplot wrote to them
+        """
+        settings = self.plot_settings
+        if self.inline_plotting:
+            _Image = SVG if settings["format"] == "svg" else Image
+        else:
+            return
+
+        for filename in self.iter_image_files():
+            try:
+                size = filename.stat().st_size
+            except FileNotFoundError:
+                size = 0
+
+            if not size:
+                msg = (
+                    "Failed to read and display image file from gnuplot."
+                    "Possibly:\n"
+                    "1. You have plotted to a non interactive terminal.\n"
+                    "2. You have an invalid expression."
+                )
+                print(msg)
+                continue
+
+            im = _Image(str(filename))
+            self.Display(im)
+
+    def delete_image_files(self):
+        """
+        Delete the image files
+        """
+        # After display_images(), the real images are
+        # no longer required.
+        for filename in self.iter_image_files():
+            with contextlib.suppress(FileNotFoundError):
+                filename.unlink()
+
+        self._image_files = []
+
+    def makeWrapper(self):
+        """
+        Start gnuplot and return wrapper around the REPL
+        """
+        if pexpect.which("gnuplot"):
+            program = "gnuplot"
+        elif pexpect.which("gnuplot.exe"):
+            program = "gnuplot.exe"
+        else:
+            raise Exception("gnuplot not found.")
+
+        # We don't want help commands getting stuck,
+        # use a non interactive PAGER
+        if pexpect.which("env") and pexpect.which("cat"):
+            command = "env PAGER=cat {}".format(program)
+        else:
+            command = program
+
+        wrapper = GnuplotREPLWrapper(
+            cmd_or_spawn=command,
+            prompt_regex=PROMPT_RE,
+            prompt_change_cmd=None,
+        )
+        # No sleeping before sending commands to gnuplot
+        wrapper.child.delaybeforesend = 0
+        return wrapper
+
+    def do_shutdown(self, restart):
+        """
+        Exit the gnuplot process and any other underlying stuff
+        """
+        self.wrapper.exit()
+        super().do_shutdown(restart)
+
+    def get_kernel_help_on(self, info, level=0, none_on_fail=False):
+        obj = info.get("help_obj", "")
+        if not obj or len(obj.split()) > 1:
+            return None if none_on_fail else ""
+        res = cast("TextOutput", self.do_execute_direct("help %s" % obj))
+        text = PROMPT_REMOVE_RE.sub("", res.output)
+        self.check_prompt()
+        return text
+
+    def reset_image_counter(self):
+        # Incremented after every plot image, and used in the
+        # plot image filename. Makes plotting in loops do_for
+        # loops work
+        cmd = f"{IMG_COUNTER}=0"
+        self.do_execute_direct(cmd)
+
+    def handle_plot_settings(self):
+        """
+        Handle the current plot settings
+
+        This is used by the gnuplot line magic. The plot magic
+        is innadequate.
+        """
+        settings = self.plot_settings
+        if "termspec" not in settings or not settings["termspec"]:
+            settings["termspec"] = 'pngcairo size 385, 256 font "Arial,10"'
+        if "format" not in settings or not settings["format"]:
+            settings["format"] = "png"
+
+        self.inline_plotting = settings["backend"] == "inline"
+
+        cmd = "set terminal {}".format(settings["termspec"])
+        self.do_execute_direct(cmd)
+        self.reset_image_counter()
+
+
+class StateMachine:
+    """
+    Track context given gnuplot statements
+
+    This is used to help us tell when to inject commands (i.e. set output)
+    that for inline plotting in the notebook.
+    """
+
+    states = ["none", "plot", "output", "multiplot", "output_multiplot"]
+    previous = "none"
+    _current = "none"
+
+    @property
+    def prev_cur(self):
+        return (self.previous, self.current)
+
+    @property
+    def current(self):
+        return self._current
+
+    @current.setter
+    def current(self, value):
+        self.previous = self._current
+        self._current = value
+
+    def transition(self, stmt):
+        lookup = {
+            s: getattr(self, f"transition_from_{s}") for s in self.states
+        }
+        _transition = lookup[self.current]
+        self.previous = self._current
+        return _transition(stmt)
+
+    def transition_from_plot(self, stmt):
+        if self.current == "output":
+            self.current = "none"
+        elif self.current == "plot":
+            if stmt.is_plot():
+                self.current = "plot"
+            elif stmt.is_set_output():
+                self.current = "output"
+            else:
+                self.current = "none"
+
+    def transition_from_none(self, stmt):
+        if stmt.is_plot():
+            self.current = "plot"
+        elif stmt.is_set_output():
+            self.current = "output"
+        elif stmt.is_set_multiplot():
+            self.current = "multiplot"
+
+    def transition_from_output(self, stmt):
+        if stmt.is_plot():
+            self.current = "plot"
+        elif stmt.is_set_multiplot():
+            self.current = "output_multiplot"
+        elif stmt.is_unset_output():
+            self.current = "none"
+
+    def transition_from_multiplot(self, stmt):
+        if stmt.is_unset_multiplot():
+            self.current = "none"
+
+    def transition_from_output_multiplot(self, stmt):
+        if stmt.is_unset_multiplot():
+            self.previous = self.current
+            self.current = "output"
diff --git a/gnuplot_kernel/magics/__init__.py b/src/gnuplot_kernel/magics/__init__.py
similarity index 54%
rename from gnuplot_kernel/magics/__init__.py
rename to src/gnuplot_kernel/magics/__init__.py
index 37ba064..486cb06 100644
--- a/gnuplot_kernel/magics/__init__.py
+++ b/src/gnuplot_kernel/magics/__init__.py
@@ -1 +1,3 @@
 from .gnuplot_magic import GnuplotMagic, register_ipython_magics
+
+__all__ = ["GnuplotMagic", "register_ipython_magics"]
diff --git a/gnuplot_kernel/magics/gnuplot_magic.py b/src/gnuplot_kernel/magics/gnuplot_magic.py
similarity index 72%
rename from gnuplot_kernel/magics/gnuplot_magic.py
rename to src/gnuplot_kernel/magics/gnuplot_magic.py
index c3336a6..b0bb4d2 100644
--- a/gnuplot_kernel/magics/gnuplot_magic.py
+++ b/src/gnuplot_kernel/magics/gnuplot_magic.py
@@ -1,7 +1,4 @@
-from __future__ import print_function
-
-from IPython.core.magic import (register_line_magic,
-                                register_cell_magic)
+from IPython.core.magic import register_cell_magic, register_line_magic
 from metakernel import Magic
 
 
@@ -46,22 +43,25 @@ def line_gnuplot(self, *args):
 
         """
         backend, terminal, termspec = _parse_args(args)
-        terminal = terminal or 'pngcairo'
-        inline_terminals = {'pngcairo': 'png',
-                            'png': 'png',
-                            'jpeg': 'jpg',
-                            'svg': 'svg'}
-        format = inline_terminals.get(terminal, 'png')
-
-        if backend == 'inline':
-            if terminal not in inline_terminals:
-                msg = ("For inline plots, the terminal must be "
-                       "one of pngcairo, jpeg, svg or png")
-                raise ValueError(msg)
-
-        self.kernel.plot_settings['backend'] = backend
-        self.kernel.plot_settings['termspec'] = termspec
-        self.kernel.plot_settings['format'] = format
+        terminal = terminal or "pngcairo"
+        inline_terminals = {
+            "pngcairo": "png",
+            "png": "png",
+            "jpeg": "jpg",
+            "svg": "svg",
+        }
+        format = inline_terminals.get(terminal, "png")
+
+        if backend == "inline" and terminal not in inline_terminals:
+            msg = (
+                "For inline plots, the terminal must be "
+                "one of pngcairo, jpeg, svg or png"
+            )
+            raise ValueError(msg)
+
+        self.kernel.plot_settings["backend"] = backend
+        self.kernel.plot_settings["termspec"] = termspec
+        self.kernel.plot_settings["format"] = format
         self.kernel.handle_plot_settings()
 
     def cell_gnuplot(self):
@@ -108,22 +108,21 @@ def register_ipython_magics():
     # not the main kernel and it may not have access
     # to some functionality. This connects it to the
     # main kernel.
-    from IPython import get_ipython
+    from IPython.core.getipython import get_ipython
+
     ip = get_ipython()
-    kernel.makeSubkernel(ip.parent)
+    kernel.makeSubkernel(ip.parent)  # pyright: ignore[reportOptionalMemberAccess]
 
     # Make magics callable:
-    kernel.line_magics['gnuplot'] = magic
-    kernel.cell_magics['gnuplot'] = magic
+    kernel.line_magics["gnuplot"] = magic
+    kernel.cell_magics["gnuplot"] = magic
 
     @register_line_magic
-    def gnuplot(line):
+    def _(line):
         magic.line_gnuplot(line)
 
-    del gnuplot
-
     @register_cell_magic
-    def gnuplot(line, cell):
+    def _(line, cell):
         magic.code = cell
         magic.cell_gnuplot()
 
@@ -133,13 +132,13 @@ def _parse_args(args):
     Process the gnuplot line magic arguments
     """
     if len(args) > 1:
-        raise TypeError()
+        raise TypeError
 
     sargs = args[0].split()
     backend = sargs[0]
-    if backend == 'inline':
+    if backend == "inline":
         try:
-            termspec = ' '.join(sargs[1:])
+            termspec = " ".join(sargs[1:])
             terminal = sargs[1]
         except IndexError:
             termspec = None
diff --git a/gnuplot_kernel/magics/reset_magic.py b/src/gnuplot_kernel/magics/reset_magic.py
similarity index 89%
rename from gnuplot_kernel/magics/reset_magic.py
rename to src/gnuplot_kernel/magics/reset_magic.py
index f537a87..c936f2d 100644
--- a/gnuplot_kernel/magics/reset_magic.py
+++ b/src/gnuplot_kernel/magics/reset_magic.py
@@ -1,10 +1,7 @@
-from __future__ import print_function
-
 from metakernel import Magic
 
 
 class ResetMagic(Magic):
-
     def line_reset(self, *line):
         """
         %reset - Clear any reset
@@ -12,7 +9,7 @@ def line_reset(self, *line):
         Example:
             %reset
         """
-        self.kernel.reset_code = ''
+        self.kernel.reset_code = ""
 
     def cell_reset(self, line):
         """
diff --git a/gnuplot_kernel/tests/__init__.py b/src/gnuplot_kernel/py.typed
similarity index 100%
rename from gnuplot_kernel/tests/__init__.py
rename to src/gnuplot_kernel/py.typed
diff --git a/src/gnuplot_kernel/replwrap.py b/src/gnuplot_kernel/replwrap.py
new file mode 100644
index 0000000..eba32de
--- /dev/null
+++ b/src/gnuplot_kernel/replwrap.py
@@ -0,0 +1,254 @@
+import re
+import signal
+import textwrap
+from typing import cast
+
+from metakernel import REPLWrapper
+from metakernel.pexpect import TIMEOUT
+
+from .exceptions import GnuplotError
+
+CRLF = "\r\n"
+NO_BLOCK = ""
+
+ERROR_RE = [
+    re.compile(
+        r"^\s*"
+        r"\^"  # Indicates error on above line
+        r"\s*"
+        r"\n"
+    )
+]
+
+PROMPT_RE = re.compile(
+    # most likely "gnuplot> "
+    r"\w*>\s*$"
+)
+
+PROMPT_REMOVE_RE = re.compile(r"\w*>\s*")
+
+# Data block e.g.
+# $DATA << EOD
+# # x y
+# 1 1
+# 2 2
+# 3 3
+# EOD
+START_DATABLOCK_RE = re.compile(
+    # $DATA << EOD
+    r"^\$\w+\s+<<\s*(?P<end>\w+)$"
+)
+END_DATABLOCK_RE = re.compile(
+    # EOD
+    r"^(?P<end>\w+)$"
+)
+
+
+class GnuplotREPLWrapper(REPLWrapper):
+    # The prompt after the commands run
+    prompt = ""
+    _blocks = {
+        "data": {"start_re": START_DATABLOCK_RE, "end_re": END_DATABLOCK_RE}
+    }
+    _current_block = NO_BLOCK
+
+    def exit(self):
+        """
+        Exit the gnuplot process
+        """
+        try:
+            self._force_prompt(timeout=0.01)
+        except GnuplotError:
+            return self.child.kill(signal.SIGKILL)
+
+        self.sendline("exit")
+
+    def is_error_output(self, text):
+        """
+        Return True if text is recognised as error text
+        """
+        return any(pattern.match(text) for pattern in ERROR_RE)
+
+    def validate_input(self, code):
+        """
+        Deal with problematic input
+
+        Raises GnuplotError if it cannot deal with it.
+        """
+        if code.endswith("\\"):
+            raise GnuplotError("Do not execute code that endswith backslash.")
+
+        # Do not get stuck in the gnuplot process
+        code = code.replace("\\\n", " ")
+        return code
+
+    def send(self, cmd):
+        self.child.send(cmd + "\r")
+
+    def _force_prompt(self, timeout: float = 30, n=4):
+        """
+        Force prompt
+        """
+        quick_timeout = 0.05
+
+        if timeout < quick_timeout:
+            quick_timeout = timeout
+
+        def quick_prompt():
+            try:
+                self._expect_prompt(timeout=quick_timeout)
+                return True
+            except TIMEOUT:
+                return False
+
+        def patient_prompt():
+            try:
+                self._expect_prompt(timeout=timeout)
+                return True
+            except TIMEOUT:
+                return False
+
+        # Eagerly try to get a prompt quickly,
+        # If that fails wait a while
+        for _ in range(n):
+            if quick_prompt():
+                break
+
+            # Probably stuck in help output
+            if self.child.before:
+                self.send(self.child.linesep)
+        else:
+            # Probably long computation going on
+            if not patient_prompt():
+                msg = (
+                    "gnuplot prompt failed to return in in {} seconds"
+                ).format(timeout)
+                raise GnuplotError(msg)
+
+    def _end_of_block(self, stmt, end_string):
+        """
+        Detect the end of block statements
+
+        Parameters
+        ----------
+        stmt : str
+            Statement to be executed by gnuplot repl
+
+        Returns
+        -------
+        end_string : str
+            Terminal string for the current block.
+        """
+        pattern = self._blocks[self._current_block]["end_re"]
+        if m := pattern.match(stmt):
+            return m.group("end") == end_string
+        return False
+
+    def _start_of_block(self, stmt):
+        """
+        Detect the start of block statements
+
+        Parameters
+        ----------
+        stmt : str
+            Statement to be executed by gnuplot repl
+        Returns
+        -------
+        block_type : str
+            Name of the block that has been detected.
+            Returns an empty string if none has been detected.
+        end_string : str
+            Terminal string for the block that has been detected.
+            Returns an empty string if none has been detected.
+        """
+        # These are used to detect the end of the block
+        block_type = NO_BLOCK
+        end_string = ""
+        for _type, regexps in self._blocks.items():
+            if m := regexps["start_re"].match(stmt):
+                block_type = _type
+                end_string = m.group("end")
+                break
+        return block_type, end_string
+
+    def _splitlines(self, code):
+        """
+        Split the code into lines that will be run
+        """
+        # Statements in a block are not followed by a prompt, this
+        # confuses the repl processing. We detect a block and concatenate
+        # it into single line so that after executing the line we can
+        # get a prompt.
+        lines = []
+        block_lines = []
+        end_string = ""
+        stmts = code.splitlines()
+        for stmt in stmts:
+            if self._current_block:
+                block_lines.append(stmt)
+                if self._end_of_block(stmt, end_string):
+                    self._current_block = NO_BLOCK
+                    block_lines.append("")
+                    block = "\n".join(block_lines)
+                    lines.append(block)
+                    block_lines = []
+                    end_string = ""
+            else:
+                block_name, end_string = self._start_of_block(stmt)
+                if block_name:
+                    self._current_block = block_name
+                    block_lines.append(stmt)
+                else:
+                    lines.append(stmt)
+
+        if self._current_block:
+            msg = "Error: {} block not terminated correctly.".format(
+                self._current_block
+            )
+            self._current_block = NO_BLOCK
+            raise GnuplotError(msg)
+
+        return lines
+
+    def run_command(  # pyright: ignore[reportIncompatibleMethodOverride]
+        self,
+        command,
+        timeout=-1,
+        stream_handler=None,
+        line_handler=None,
+        stdin_handler=None,
+    ):
+        """
+        Run code
+
+        This overrides the baseclass method to allow for
+        input validation and error handling.
+        """
+        command = self.validate_input(command)
+
+        # Split up multiline commands and feed them in bit-by-bit
+        stmts = self._splitlines(command)
+        output_lines = []
+        for line in stmts:
+            self.send(line)
+            self._force_prompt()
+
+            # Removing any crlfs makes subsequent
+            # processing cleaner
+            retval = cast("str", self.child.before).replace(CRLF, "\n")
+            self.prompt = self.child.after
+            if self.is_error_output(retval):
+                msg = "{}\n{}".format(line, textwrap.dedent(retval))
+                raise GnuplotError(msg)
+
+            # Sometimes block stmts like datablocks make the
+            # the prompt leak into the return value
+            retval = PROMPT_REMOVE_RE.sub("", retval).strip(" ")
+
+            # Some gnuplot installations return the input statements
+            # We do not count those as output
+            if retval.strip() != line.strip():
+                output_lines.append(retval)
+
+        output = "".join(output_lines)
+        return output
diff --git a/src/gnuplot_kernel/statement.py b/src/gnuplot_kernel/statement.py
new file mode 100644
index 0000000..26a98ab
--- /dev/null
+++ b/src/gnuplot_kernel/statement.py
@@ -0,0 +1,98 @@
+"""
+Recognising gnuplot statements
+"""
+
+import re
+
+# name of the command i.e first token
+CMD_RE = re.compile(
+    r"^\s*"
+    r"(?P<cmd>"
+    r"\w+"  # The command
+    r")"
+    r"\s?"
+)
+
+# plot statements
+PLOT_RE = re.compile(
+    r"^\s*"
+    r"(?P<plot_cmd>"
+    r"plot|plo|pl|p|"
+    r"splot|splo|spl|sp|"
+    r"replot|replo|repl|rep"
+    r")"
+    r"\s?"
+)
+
+# "set multiplot" and abbreviated variants
+SET_MULTIPLE_RE = re.compile(
+    r"\s*"
+    r"set"
+    r"\s+"
+    r"multip(?:lot|lo|l)?\b"
+    r"\b"
+)
+
+# "unset multiplot" and abbreviated variants
+UNSET_MULTIPLE_RE = re.compile(
+    r"\s*"
+    r"(?:unset|unse|uns)"
+    r"\s+"
+    r"multip(?:lot|lo|l)?\b"
+    r"\b"
+)
+
+
+# "set output" and abbreviated variants
+SET_OUTPUT_RE = re.compile(
+    r"\s*"
+    r"set"
+    r"\s+"
+    r"(?:output|outpu|outp|out|ou|o)"
+    r"(?:\s+|$)"
+)
+
+# "unset output" and abbreviated variants
+UNSET_OUTPUT_RE = re.compile(
+    r"\s*"
+    r"(?:unset|unse|uns)"
+    r"\s+"
+    r"(?:output|outpu|outp|out|ou|o)"
+    r"(?:\s+|$)"
+)
+
+
+class STMT(str):
+    """
+    A gnuplot statement
+    """
+
+    def is_set_output(self):
+        """
+        Return True if stmt is a 'set output' statement
+        """
+        return bool(SET_OUTPUT_RE.match(self))
+
+    def is_unset_output(self):
+        """
+        Return True if stmt is an 'unset output' statement
+        """
+        return bool(UNSET_OUTPUT_RE.match(self))
+
+    def is_set_multiplot(self):
+        """
+        Return True if stmt is a "set multiplot" statement
+        """
+        return bool(SET_MULTIPLE_RE.match(self))
+
+    def is_unset_multiplot(self):
+        """
+        Return True if stmt is a "unset multiplot" statement
+        """
+        return bool(UNSET_MULTIPLE_RE.match(self))
+
+    def is_plot(self):
+        """
+        Return True if stmt is a plot statement
+        """
+        return bool(PLOT_RE.match(self))
diff --git a/src/gnuplot_kernel/utils.py b/src/gnuplot_kernel/utils.py
new file mode 100644
index 0000000..67ea9c3
--- /dev/null
+++ b/src/gnuplot_kernel/utils.py
@@ -0,0 +1,17 @@
+"""
+Useful functions
+"""
+
+from importlib.metadata import version
+
+
+def get_version(package: str) -> str:
+    """
+    Return the package version
+
+    Raises PackageNotFoundError if package is not installed
+    """
+    # The goal of this function to avoid circular imports if the
+    # version is required in 2 or more spot before the package has
+    # been fully installed
+    return version(package)
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/conftest.py b/tests/conftest.py
new file mode 100644
index 0000000..2dd7f4b
--- /dev/null
+++ b/tests/conftest.py
@@ -0,0 +1,24 @@
+import os
+from contextlib import contextmanager
+from pathlib import Path
+
+os.environ["JUPYTER_PLATFORM_DIRS"] = "1"
+
+
+@contextmanager
+def ensure_deleted(*paths: str):
+    """
+    Ensures the given file paths are deleted when the block exits
+
+    Parameters
+    ----------
+    *paths : pathlib.Path
+        One or more file paths
+    """
+    paths = tuple(Path(path) for path in paths)
+
+    try:
+        yield paths if len(paths) > 1 else paths[0]
+    finally:
+        for path in paths:
+            Path(path).unlink()
diff --git a/gnuplot_kernel/tests/test_kernel.py b/tests/test_kernel.py
similarity index 55%
rename from gnuplot_kernel/tests/test_kernel.py
rename to tests/test_kernel.py
index a0ed260..2704d30 100644
--- a/gnuplot_kernel/tests/test_kernel.py
+++ b/tests/test_kernel.py
@@ -1,14 +1,12 @@
-import os
 import weakref
+from pathlib import Path
+
+from metakernel.tests.utils import clear_log_text, get_kernel, get_log_text
 
-from nose.tools import (assert_equal, assert_true, assert_false,
-                        with_setup)
-from metakernel.tests.utils import (get_kernel, get_log_text,
-                                    clear_log_text)
 from gnuplot_kernel import GnuplotKernel
 from gnuplot_kernel.magics import GnuplotMagic
 
-from .utils import remove_files
+from .conftest import ensure_deleted
 
 # Note: Empty lines after indented triple quoted may
 # lead to empty statements which could obscure the
@@ -25,10 +23,7 @@ def get_kernel(klass=None):
     """
     Create & add to registry of live kernels
     """
-    if klass:
-        kernel = _get_kernel(klass)
-    else:
-        kernel = _get_kernel()
+    kernel = _get_kernel(klass) if klass else _get_kernel()
     KERNELS.add(kernel)
     return kernel
 
@@ -48,17 +43,15 @@ def teardown():
 
 # Normal workflow tests #
 
+
 def test_inline_magic():
     kernel = get_kernel(GnuplotKernel)
 
     # gnuplot line magic changes the plot settings
-    kernel.call_magic('%gnuplot pngcairo size 560, 420')
-    assert_equal(kernel.plot_settings['backend'],
-                 'pngcairo')
-    assert_equal(kernel.plot_settings['format'],
-                 'png')
-    assert_equal(kernel.plot_settings['termspec'],
-                 'pngcairo size 560, 420')
+    kernel.call_magic("%gnuplot pngcairo size 560, 420")
+    assert kernel.plot_settings["backend"] == "pngcairo"
+    assert kernel.plot_settings["format"] == "png"
+    assert kernel.plot_settings["termspec"] == "pngcairo size 560, 420"
 
 
 def test_print():
@@ -66,37 +59,50 @@ def test_print():
     code = "print cos(0)"
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true('1.0' in text)
+    assert "1.0" in text
 
 
-@with_setup(teardown=remove_files(('sine.png',
-                                   'sine-cosine.png')))
 def test_file_plots():
     kernel = get_kernel(GnuplotKernel)
-    kernel.call_magic('%gnuplot pngcairo size 560, 420')
+    kernel.call_magic("%gnuplot pngcairo size 560, 420")
 
     # With a non-inline terminal plot gets created
-    code = """
-    set output 'sine.png'
-    plot sin(x)
-    """
-    kernel.do_execute(code)
-    assert_true(os.path.exists('sine.png'))
+    with ensure_deleted("sine.png") as f1:
+        code = f"""
+        set output '{f1}'
+        plot sin(x)
+        """
+        kernel.do_execute(code)
+        assert f1.exists()
+
     clear_log_text(kernel)
 
     # Multiple line statement
-    code = """
-    set output 'sine-cosine.png'
-    plot sin(x),\
-         cos(x)
-    """
-    kernel.do_execute(code)
-    assert_true(os.path.exists('sine-cosine.png'))
+    with ensure_deleted("sine-cosine.png") as f1:
+        code = f"""
+        set output '{f1}'
+        plot sin(x),\
+             cos(x)
+        """
+        kernel.do_execute(code)
+        assert f1.exists()
+
+    # Multiple line statement
+    with ensure_deleted("tan.png", "tan2.png") as (f1, f2):
+        code = f"""
+        set output '{f1}'
+        plot tan(x)
+        set output '{f2}'
+        replot
+        """
+        kernel.do_execute(code)
+        assert f1.exists()
+        assert f2.exists()
 
 
 def test_inline_plots():
     kernel = get_kernel(GnuplotKernel)
-    kernel.call_magic('%gnuplot inline')
+    kernel.call_magic("%gnuplot inline")
 
     # inline plot creates data
     code = """
@@ -104,7 +110,7 @@ def test_inline_plots():
     """
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true('Display Data' in text)
+    assert "Display Data" in text
     clear_log_text(kernel)
 
     # multiple plot statements data
@@ -114,17 +120,17 @@ def test_inline_plots():
     """
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true(text.count('Display Data') == 2)
+    assert text.count("Display Data") == 2
     clear_log_text(kernel)
 
     # svg
-    kernel.call_magic('%gnuplot inline svg')
+    kernel.call_magic("%gnuplot inline svg")
     code = """
     plot tan(x)
     """
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true('Display Data' in text)
+    assert "Display Data" in text
     clear_log_text(kernel)
 
 
@@ -142,7 +148,7 @@ def test_plot_abbreviations():
     """
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true(text.count('Display Data') == 4)
+    assert text.count("Display Data") == 4
 
 
 def test_multiplot():
@@ -157,7 +163,21 @@ def test_multiplot():
     """
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true(text.count('Display Data') == 1)
+    assert text.count("Display Data") == 1
+
+    # With output
+    with ensure_deleted("multiplot-sin-cos.png") as f1:
+        code = f"""
+        set terminal pncairo
+        set output '{f1}'
+        set multiplot layout 2, 1
+        plot sin(x)
+        plot cos(x)
+        unset multiplot
+        unset output
+        """
+        kernel.do_execute(code)
+        assert f1.exists()
 
 
 def test_help():
@@ -167,17 +187,17 @@ def test_help():
     # stuck in pagers.
 
     # Fancy notebook help
-    code = 'terminal?'
+    code = "terminal?"
     kernel.do_execute(code)
     text = get_log_text(kernel).lower()
-    assert_true('subtopic' in text)
+    assert "subtopic" in text
     clear_log_text(kernel)
 
     # help by gnuplot statement
-    code = 'help print'
+    code = "help print"
     kernel.do_execute(code)
     text = get_log_text(kernel).lower()
-    assert_true('syntax' in text)
+    assert "syntax" in text
     clear_log_text(kernel)
 
 
@@ -185,35 +205,88 @@ def test_badinput():
     kernel = get_kernel(GnuplotKernel)
 
     # No code that endswith a backslash
-    code = 'plot sin(x),\\'
+    code = "plot sin(x),\\"
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true('backslash' in text)
+    assert "backslash" in text
 
 
 def test_gnuplot_error_message():
     kernel = get_kernel(GnuplotKernel)
 
     # The error messages gets to the kernel
-    code = 'plot [1,2][] sin(x)'
+    code = "plot [1,2][] sin(x)"
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true(' ^' in text)
+    assert " ^" in text
 
 
 def test_bad_prompt():
     kernel = get_kernel(GnuplotKernel)
     # Anything other than 'gnuplot> '
     # is a bad prompt
-    code = 'set multiplot'
+    code = "set multiplot"
+    kernel.do_execute(code)
+    text = get_log_text(kernel)
+    assert "warning" in text.lower()
+
+
+def test_data_block():
+    kernel = get_kernel(GnuplotKernel)
+
+    # Good data block
+    code = """
+$DATA << EOD
+# x y
+1 1
+2 2
+3 3
+4 4
+EOD
+plot $DATA
+    """
+    kernel.do_execute(code)
+    text = get_log_text(kernel)
+    assert text.count("Display Data") == 1
+    clear_log_text(kernel)
+
+    # Badly terminated data block
+    bad_code = """
+$DATA << EOD
+# x y
+1 1
+2 2
+3 3
+4 4
+EODX
+plot $DATA
+    """
+    kernel.do_execute(bad_code)
+    text = get_log_text(kernel)
+    assert "Error" in text
+    clear_log_text(kernel)
+
+    # Good code should work after the bad_code
     kernel.do_execute(code)
     text = get_log_text(kernel)
-    assert_true('warning' in text.lower())
+    assert text.count("Display Data") == 1
+
+
+def test_do_for_loop():
+    kernel = get_kernel(GnuplotKernel)
+    code = """
+    do for [t=0:2] {
+      plot x**t t sprintf("x^%d",t)
+    }
+    """
+    kernel.do_execute(code)
+    text = get_log_text(kernel)
+    assert text.count("Display Data") == 3
 
 
 # magics #
 
-@with_setup(teardown=remove_files('cosine.png'))
+
 def test_cell_magic():
     # To simulate '%load_ext gnuplot_kernel';
     # create a main kernel, a gnuplot kernel and
@@ -224,45 +297,47 @@ def test_cell_magic():
     gkernel = GnuplotKernel()
     gmagic = GnuplotMagic(gkernel)
     gkernel.makeSubkernel(kernel)
-    kernel.line_magics['gnuplot'] = gmagic
-    kernel.cell_magics['gnuplot'] = gmagic
+    kernel.line_magics["gnuplot"] = gmagic
+    kernel.cell_magics["gnuplot"] = gmagic
 
     # inline output
     code = """%%gnuplot
     plot cos(x)
     """
     kernel.do_execute(code)
-    assert_true('Display Data' in get_log_text(kernel))
+    assert "Display Data" in get_log_text(kernel)
     clear_log_text(kernel)
 
     # file output
-    kernel.call_magic('%gnuplot pngcairo size 560,420')
-    code = """%%gnuplot
-    set output 'cosine.png'
-    plot cos(x)
-    """
-    kernel.do_execute(code)
-    assert_true(os.path.exists('cosine.png'))
+    kernel.call_magic("%gnuplot pngcairo size 560,420")
+
+    with ensure_deleted("cosine.png") as f1:
+        code = f"""%%gnuplot
+        set output '{f1}'
+        plot cos(x)
+        """
+        kernel.do_execute(code)
+        assert f1.exists()
+
     clear_log_text(kernel)
 
 
-@with_setup(teardown=remove_files('sine+cosine.png'))
 def test_reset_cell_magic():
     kernel = get_kernel(GnuplotKernel)
 
     # Use reset statements that have testable effect
-    code = """%%reset
-    set output 'sine+cosine.png'
-    plot sin(x) + cos(x)
-    """
-    kernel.call_magic(code)
-    assert_false(os.path.exists('sine+cosine.png'))
+    with ensure_deleted("sine+cosine.png") as f1:
+        code = f"""%%reset
+        set output '{f1}'
+        plot sin(x) + cos(x)
+        """
+        kernel.call_magic(code)
 
-    code = """
-    unset key
-    """
-    kernel.do_execute(code)
-    assert_true(os.path.exists('sine+cosine.png'))
+        code = """
+        unset key
+        """
+        kernel.do_execute(code)
+        assert f1.exists()
 
 
 def test_reset_line_magic():
@@ -277,36 +352,14 @@ def test_reset_line_magic():
 
     # Remove the reset, execute some code and
     # make sure there are no effects
-    kernel.call_magic('%reset')
+    kernel.call_magic("%reset")
     code = """
     unset key
     """
     kernel.do_execute(code)
-    assert_false(os.path.exists('sine+sine.png'))
+    assert not Path("sine+sine").exists()
 
     # Bad inline backend
     # metakernel messes this exception!!
     # with assert_raises(ValueError):
     #     kernel.call_magic('%gnuplot inline qt')
-
-
-# utils tests #
-
-def test_remove_files():
-    filename = './antigravity.txt'
-    func = remove_files(filename)
-
-    # Create file
-    # Verify it exists
-    # Remove it
-    # Verify it does not exist
-    # Remove it again, nothing happens
-
-    with open(filename, 'w'):
-        pass
-
-    assert_true(os.path.exists(filename))
-    func()
-
-    assert_false(os.path.exists(filename))
-    func()
diff --git a/tools/release-checklist-tpl.md b/tools/release-checklist-tpl.md
new file mode 100644
index 0000000..90de4d6
--- /dev/null
+++ b/tools/release-checklist-tpl.md
@@ -0,0 +1,98 @@
+# Release Issue Checklist
+
+Copy the template below the line, substitute (`s/<VERSION>/1.2.3/`) the correct
+version and create an [issue](https://github.com/has2k1/gnuplot_kernel/issues/new).
+
+The first line is the title of the issue
+
+------------------------------------------------------------------------------
+Release: gnuplot_kernel-<VERSION>
+
+- [ ] Upgrade key dependencies if necessary
+
+  - [ ] [metakernel](https://github.com/Calysto/metakernel)
+  - [ ] [jupyter](https://github.com/jupyter/jupyter)
+
+
+- [ ] Upgrade code quality checkers
+
+  - [ ] pre-commit
+
+    ```
+    pre-commit autoupdate
+    ```
+
+  - [ ] ruff
+
+    ```
+    pip install --upgrade ruff
+    ```
+
+  - [ ] pyright
+
+    ```sh
+    pip install --upgrade pyright
+    PYRIGHT_VERSION=$(pyright --version | grep -oE '[0-9]+\.[0-9]+\.[0-9]+')
+    python -c "
+    import pathlib, re
+    f = pathlib.Path('pyproject.toml')
+    f.write_text(re.sub(r'pyright==[0-9]+\.[0-9]+\.[0-9]+', 'pyright==$PYRIGHT_VERSION', f.read_text()))
+    "
+    ```
+
+- [ ] Run tests and coverage locally
+
+  ```sh
+  git switch main
+  git pull origin/main
+  make typecheck
+  make test
+  make coverage
+  ```
+  - [ ] The tests pass
+  - [ ] The coverage is acceptable
+
+
+- [ ] Create a release branch
+
+  ```sh
+  git switch -c release-v<VERSION>
+  ```
+
+- [ ] Tag a pre-release version. These are automatically deployed on `testpypi`
+
+  ```sh
+  git tag -as v<VERSION>rc1 -m "Version <VERSION>rc1"  # e.g. <VERSION>a1, <VERSION>b1, <VERSION>rc1
+  git push -u origin release-v<VERSION>
+  ```
+  - [ ] GHA [release job](https://github.com/has2k1/gnuplot_kernel/actions/workflows/release.yml) passes
+  - [ ] gnuplot_kernel test release is on [TestPyPi](https://test.pypi.org/project/gnuplot_kernel/#history)
+
+- [ ] Update changelog
+
+  ```sh
+  nvim doc/changelog.qmd
+  git commit -am "Update changelog for release"
+  git push
+  ```
+  - [ ] Update / confirm the version to be released
+  - [ ] Add a release date
+  - [ ] The [GHA tests](https://github.com/has2k1/gnuplot_kernel/actions/workflows/testing.yml) pass
+
+- [ ] Tag final version and release
+
+  ```sh
+  git tag -as v<VERSION> -m "Version <VERSION>"
+  git push
+  ```
+
+  - [ ] The [GHA Release](https://github.com/has2k1/gnuplot_kernel/actions/workflows/release.yml) job passes
+  - [ ] [PyPi](https://pypi.org/project/gnuplot_kernel) shows the new release
+
+- [ ] Update `main` branch
+
+  ```sh
+  git switch main
+  git merge --ff-only release-v<VERSION>
+  git push
+  ```
diff --git a/tools/release-checklist.py b/tools/release-checklist.py
new file mode 100644
index 0000000..ceee6fc
--- /dev/null
+++ b/tools/release-checklist.py
@@ -0,0 +1,161 @@
+from __future__ import annotations
+
+import os
+import re
+import shlex
+import sys
+from pathlib import Path
+from subprocess import PIPE, Popen
+from typing import Literal, Optional, Sequence, TypeAlias
+
+TPL_FILENAME = "release-checklist-tpl.md"
+THIS_DIR = Path(__file__).parent
+NEW_ISSUE = "https://github.com/has2k1/gnuplot_kernel/issues/new"
+
+VersionPart: TypeAlias = Literal[
+    "major",
+    "minor",
+    "patch",
+]
+
+count = r"(?:[0-9]|[1-9][0-9]+)"
+DESCRIBE_PATTERN = re.compile(
+    r"^v"
+    rf"(?P<version>{count}\.{count}\.{count})"
+    rf"(?P<pre>(a|b|rc){count})?"
+    r"(-(?P<commits>\d+)-g(?P<hash>[a-z0-9]+))?"
+    r"(?P<dirty>-dirty)?"
+    r"$"
+)
+
+
+def run(cmd: str | Sequence[str], input: Optional[str] = None) -> str:
+    """
+    Run command
+    """
+    if isinstance(cmd, str) and os.name == "posix":
+        cmd = shlex.split(cmd)
+    with Popen(
+        cmd, stdin=PIPE, stderr=PIPE, stdout=PIPE, text=True, encoding="utf-8"
+    ) as p:
+        stdout, _ = p.communicate(input=input)
+    return stdout.strip()
+
+
+def copy_to_clipboard(s: str):
+    """
+    Copy s to clipboard
+    """
+    import platform
+
+    plat = platform.system()
+
+    platform_cmds = {"Darwin": "pbcopy", "Linux": "xclip", "Windows": "clip"}
+
+    try:
+        from pandas.io import (  # pyright: ignore[reportMissingImports]
+            clipboard,
+        )
+    except ImportError:
+        try:
+            cmd = platform_cmds[plat]
+        except KeyError as err:
+            msg = f"No clipboard for this system: {plat}"
+            raise RuntimeError(msg) from err
+        run(cmd, input=s)
+    else:
+        clipboard.copy(s)
+
+
+def get_previous_version(s: Optional[str] = None) -> str:
+    """
+    Get previous version
+
+    Either the 2nd commandline arg (v) or obtained from git describe
+    """
+    if s:
+        vtxt = s if s.startswith("v") else f"v{s}"
+    else:
+        cmd = "git describe --dirty --tags --long --match '*[0-9]*'"
+        vtxt = run(cmd)
+
+    m = DESCRIBE_PATTERN.match(vtxt)
+    if not m:
+        raise ValueError(f"Bad version: {vtxt}")
+
+    return m.group("version")
+
+
+def bump_version(version: str, part: VersionPart) -> str:
+    """
+    Bump version
+    """
+    parts = version.split(".")
+    i = ("major", "minor", "patch").index(part)
+    parts[i] = str(int(parts[i]) + 1)
+    # Zero-out the smaller parts
+    for j in range(i + 1, 3):
+        parts[j] = "0"
+    return ".".join(parts)
+
+
+def generate_checklist(version: str) -> str:
+    """
+    Generate checklist for releasing the given version
+    """
+    path = THIS_DIR / TPL_FILENAME
+    pattern = re.compile(
+        # The template is everything below the dashed line
+        r"\n-+\n(?P<tpl>.+)",
+        flags=re.MULTILINE | re.DOTALL,
+    )
+    with Path(path).open("r") as f:
+        contents = f.read()
+
+    m = pattern.search(contents)
+    if not m:
+        raise ValueError(f"Cannot find the relevant content in '{path}'")
+
+    tpl = m.group("tpl")
+    return tpl.replace("<VERSION>", version)
+
+
+def process(part: VersionPart, prev: str | None):
+    """
+    Run the full process
+
+    1. Calculate the next version from the previous version
+    2. Add the next version to the checklist template
+    3. Copy the template to the system clipboard
+    """
+    prev_version = get_previous_version(prev)
+    next_version = bump_version(prev_version, part)
+    cl = generate_checklist(next_version)
+    copy_to_clipboard(cl)
+    verbose(prev_version, next_version)
+
+
+def verbose(prev_version, next_version):
+    """
+    Print version details
+    """
+    from textwrap import dedent
+
+    from term import T0 as T
+
+    s = f"""
+    Previous Version: {T(prev_version, "lightblue", effect="strikethrough")}
+        Next Version: {T(next_version, "lightblue", effect="bold")}
+
+    The release checklist has been copied to the clipboard. Use it to
+    open a new issue at: {T(NEW_ISSUE, "yellow")}\
+    """
+    print(dedent(s))
+
+
+if __name__ == "__main__":
+    if len(sys.argv) >= 2:
+        part = sys.argv[1]
+        prev = sys.argv[2] if len(sys.argv) >= 3 else None
+        assert part in ("major", "minor", "patch")
+        process(part, prev)
diff --git a/tools/term.py b/tools/term.py
new file mode 100644
index 0000000..d064aa4
--- /dev/null
+++ b/tools/term.py
@@ -0,0 +1,107 @@
+from __future__ import annotations
+
+import sys
+from enum import Enum
+from typing import Optional
+
+RESET = "\033[0m"
+
+
+class Fg(Enum):
+    """
+    Foreground color codes
+    """
+
+    black = "\033[30m"
+    red = "\033[31m"
+    green = "\033[32m"
+    orange = "\033[33m"
+    blue = "\033[34m"
+    purple = "\033[35m"
+    cyan = "\033[36m"
+    lightgrey = "\033[37m"
+    darkgrey = "\033[90m"
+    lightred = "\033[91m"
+    lightgreen = "\033[92m"
+    yellow = "\033[93m"
+    lightblue = "\033[94m"
+    pink = "\033[95m"
+    lightcyan = "\033[96m"
+
+
+class Bg(Enum):
+    """
+    Background color codes
+    """
+
+    black = "\033[40m"
+    red = "\033[41m"
+    green = "\033[42m"
+    orange = "\033[43m"
+    blue = "\033[44m"
+    purple = "\033[45m"
+    cyan = "\033[46m"
+    lightgrey = "\033[47m"
+
+
+class Effect(Enum):
+    """
+    Text effect codes
+    """
+
+    bold = "\033[01m"
+    dim = "\033[02m"
+    underline = "\033[04m"
+    blink = "\033[05m"
+    reverse = "\033[07m"  # bg & fg are reversed
+    hide = "\033[08m"
+    strikethrough = "\033[09m"
+
+
+def T(
+    s: str,
+    fg: Optional[str] = None,
+    bg: Optional[str] = None,
+    effect: Optional[str] = None,
+) -> str:
+    """
+    Enclose text string with ANSI codes
+
+    e.g.
+        # Red text
+        T("sample", "red")
+
+        # Red on lightgrey background
+        T("sample", "red", "lightgrey")
+
+        # Red on lightgrey background and underlined
+        T("sample", "red", "lightgrey", "underlined")
+
+        # Red underlined text
+        T("sample", effect="underlined")
+
+        # Red & bold underlined text
+        T("sample", effect="bold, underlined")
+    """
+
+    def get(Ecls, prop_name) -> str:
+        return getattr(Ecls, prop_name).value if prop_name else ""
+
+    _fg = get(Fg, fg)
+    _bg = get(Bg, bg)
+    if effect:
+        _effect = "".join(get(Effect, e.strip()) for e in effect.split(","))
+    else:
+        _effect = ""
+
+    _reset = RESET if any((_fg, _bg, _effect)) else ""
+    return f"{_fg}{_bg}{_effect}{s}{_reset}"
+
+
+def T0(s: str, *args, **kwargs) -> str:
+    """
+    Enclose text string with ANSI codes if output is TTY
+    """
+    if sys.stdout.isatty():
+        return T(s, *args, **kwargs)
+    return s