diff --git a/.github/workflows/python-package.yml b/.github/workflows/python-package.yml index 562ed11..5e78f6b 100644 --- a/.github/workflows/python-package.yml +++ b/.github/workflows/python-package.yml @@ -12,11 +12,11 @@ on: jobs: build: - runs-on: ubuntu-latest + runs-on: ubuntu-20.04 strategy: fail-fast: false matrix: - python-version: [3.6, 3.7, 3.8, 3.9, '3.10'] + python-version: [3.6, 3.7, 3.8, 3.9, '3.10', 3.11] steps: - uses: actions/checkout@v3 diff --git a/.gitignore b/.gitignore index 84a665b..32de0af 100644 --- a/.gitignore +++ b/.gitignore @@ -3,8 +3,12 @@ __pycache__ build dist +statannot.egg-info/ statannot.egg-info/dependency_links.txt statannot.egg-info/PKG-INFO statannot.egg-info/requires.txt statannot.egg-info/SOURCES.txt statannot.egg-info/top_level.txt + +# IDE files +.idea/ diff --git a/CHANGELOG.md b/CHANGELOG.md index 890fdbc..2ddf94f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,25 @@ -## v0.5 -### v0.5.0 +## v0.6 +### v0.6.0 +#### Features +- Add option to skip annotation of non-significant results + (PR [#95](https://github.com/trevismd/statannotations/pull/95) by + [sepro](https://github.com/sepro)) + +#### Fixes +- Fix keeping annotation with reduced ylim ( + PR [#116](https://github.com/trevismd/statannotations/issues/116) by + [amkorb](https://github.com/amkorb)) +- Fix pvalue legend (usually for NS range) + +#### Additional testing and documentation: + - PR [#84](https://github.com/trevismd/statannotations/pull/84) by + [JasonMendoza2008 ](https://github.com/JasonMendoza2008) + - PR [#86](https://github.com/trevismd/statannotations/pull/86) by + [mbhall88](https://github.com/mbhall88) + - PR [#117](https://github.com/trevismd/statannotations/pull/117) by + [tathey1](https://github.com/tathey1) + +## v0.5.0 - Add scipy's Brunner-Munzel test - Fix applying statannotations for non-string group labels (Issue [#65](https://github.com/trevismd/statannotations/issues/65)) diff --git a/README.md b/README.md index c91b2f3..c9a6126 100644 --- a/README.md +++ b/README.md @@ -62,6 +62,7 @@ corresponding branch). - Optionally, custom p-values can be given as input. In this case, no statistical test is performed, but **corrections for multiple testing can be applied.** +- It is also possible to hide non statistically significant annotations - Any text can be used as annotation - And various fixes (see [CHANGELOG.md](https://github.com/trevismd/statannotations/blob/master/CHANGELOG.md)). @@ -69,7 +70,7 @@ corresponding branch). ## Installation From version 0.3.0 on, the package is distributed on PyPi. -The latest stable release (v0.5.0) can be downloaded and installed with: +The latest stable release (v0.6.0) can be downloaded and installed with: ```bash pip install statannotations ``` @@ -90,9 +91,9 @@ pip install -r requirements.txt . ## Important note -**! Seaborn ≥ v0.12 is not officially supported, we know there are at least -some bugs. Issues can still be reported (and upvoted) in order to plan further -development to support these versions. Also see +**! Seaborn ≥ v0.12 and pandas 2 are not officially supported, we know there are +at least some bugs. Issues can still be reported (and upvoted) in order to plan +further development to support these versions. Also see [discussion](https://github.com/trevismd/statannotations/discussions/81)**. ## Usage @@ -142,7 +143,7 @@ annotator.apply_and_annotate() + numpy >= 1.12.1 + seaborn >= 0.9,<0.12 + matplotlib >= 2.2.2 -+ pandas >= 0.23.0 ++ pandas >= 0.23.0,<2.0.0 + scipy >= 1.1.0 + statsmodels (optional, for multiple testing corrections) @@ -171,7 +172,7 @@ Bibtex month = oct, year = 2022, publisher = {Zenodo}, - version = {v0.5}, + version = {v0.6}, doi = {10.5281/zenodo.7213391}, url = {https://doi.org/10.5281/zenodo.7213391} } @@ -181,7 +182,7 @@ Example Florian Charlier, Marc Weber, Dariusz Izak, Emerson Harkin, Marcin Magnus, Joseph Lalli, Louison Fresnais, Matt Chan, Nikolay Markov, Oren Amsalem, Sebastian Proost, Agamemnon Krasoulis, getzze, & Stefan Repplinger. (2022). -Statannotations (v0.5). Zenodo. https://doi.org/10.5281/zenodo.7213391 +Statannotations (v0.6). Zenodo. https://doi.org/10.5281/zenodo.7213391 ``` ## Contributing diff --git a/docs/build/doctrees/modules.doctree b/docs/build/doctrees/modules.doctree index 21c3b1b..0fb6ef9 100644 Binary files a/docs/build/doctrees/modules.doctree and b/docs/build/doctrees/modules.doctree differ diff --git a/docs/build/doctrees/statannotations.doctree b/docs/build/doctrees/statannotations.doctree index cd61983..2fd98df 100644 Binary files a/docs/build/doctrees/statannotations.doctree and b/docs/build/doctrees/statannotations.doctree differ diff --git a/docs/build/doctrees/statannotations.stats.doctree b/docs/build/doctrees/statannotations.stats.doctree index 6a8f43b..556534b 100644 Binary files a/docs/build/doctrees/statannotations.stats.doctree and b/docs/build/doctrees/statannotations.stats.doctree differ diff --git a/docs/build/html/_sources/modules.rst.txt b/docs/build/html/_sources/modules.rst.txt index 56a5960..86a09c7 100644 --- a/docs/build/html/_sources/modules.rst.txt +++ b/docs/build/html/_sources/modules.rst.txt @@ -5,3 +5,4 @@ statannotations :maxdepth: 4 statannotations + custom-test diff --git a/docs/build/html/_sources/statannotations.rst.txt b/docs/build/html/_sources/statannotations.rst.txt index 3a24356..e48438f 100644 --- a/docs/build/html/_sources/statannotations.rst.txt +++ b/docs/build/html/_sources/statannotations.rst.txt @@ -20,6 +20,8 @@ statannotations.Annotation module :undoc-members: :show-inheritance: +.. _Annotator_module: + statannotations.Annotator module -------------------------------- diff --git a/docs/build/html/_sources/statannotations.stats.rst.txt b/docs/build/html/_sources/statannotations.stats.rst.txt index 846d287..b660e9b 100644 --- a/docs/build/html/_sources/statannotations.stats.rst.txt +++ b/docs/build/html/_sources/statannotations.stats.rst.txt @@ -20,6 +20,8 @@ statannotations.stats.StatResult module :undoc-members: :show-inheritance: +.. _StatTest_module: + statannotations.stats.StatTest module ------------------------------------- diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html index 8c420f7..ae59124 100644 --- a/docs/build/html/genindex.html +++ b/docs/build/html/genindex.html @@ -211,6 +211,8 @@

C

diff --git a/docs/build/html/modules.html b/docs/build/html/modules.html index b54367e..b7c41fb 100644 --- a/docs/build/html/modules.html +++ b/docs/build/html/modules.html @@ -91,6 +91,7 @@ @@ -187,6 +188,7 @@

statannotationsModule contents +
  • Extending to other statistical functions
    • diff --git a/docs/build/html/objects.inv b/docs/build/html/objects.inv index ca638c7..947802e 100644 Binary files a/docs/build/html/objects.inv and b/docs/build/html/objects.inv differ diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js index 6c83a1d..ad32996 100644 --- a/docs/build/html/searchindex.js +++ b/docs/build/html/searchindex.js @@ -1 +1 @@ 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to other statistical functions","Welcome to statannotations\u2019s documentation!","statannotations","setup module","statannotations package","statannotations.stats package"],titleterms:{"function":0,annot:4,comparisonscorrect:5,content:[1,4,5],document:1,extend:0,format_annot:4,indic:1,modul:[3,4,5],other:0,packag:[4,5],pvalueformat:4,s:1,setup:3,stat:5,statannot:[1,2,4,5],statist:0,statresult:5,stattest:5,submodul:[4,5],subpackag:4,tabl:1,test:5,util:[4,5],welcom:1}}) \ No newline at end of file diff --git a/docs/build/html/statannotations.html b/docs/build/html/statannotations.html index 65c4e2c..817e274 100644 --- a/docs/build/html/statannotations.html +++ b/docs/build/html/statannotations.html @@ -104,6 +104,7 @@
  • Module contents
    • +
  • Extending to other statistical functions
    • @@ -204,6 +205,11 @@

    Submodulesclass statannotations.Annotation.Annotation(structs, data: Union[str, statannotations.stats.StatResult.StatResult], formatter: Optional[statannotations.PValueFormat.Formatter] = None)

    Bases: object

    Holds data, linked structs and an optional Formatter.

    +
    +
    +check_data_stat_result()
    +
    +
    property formatted_output
    @@ -223,7 +229,7 @@

    Submodules -

    statannotations.Annotator module

    +

    statannotations.Annotator module

    class statannotations.Annotator.Annotator(ax, pairs, plot='boxplot', data=None, x=None, y=None, hue=None, order=None, hue_order=None, engine='seaborn', verbose=True, **plot_params)
    @@ -314,6 +320,11 @@

    Submodules +
    hide_non_significant: hide annotations for non-significant pair

    comparisons

    +
    +

    +

  • line_height: in axes fraction coordinates

  • line_offset

  • line_offset_to_group

    • diff --git a/docs/build/html/statannotations.stats.html b/docs/build/html/statannotations.stats.html index e7370d1..6d403f8 100644 --- a/docs/build/html/statannotations.stats.html +++ b/docs/build/html/statannotations.stats.html @@ -41,6 +41,7 @@ + @@ -103,6 +104,7 @@
  • Module contents
    • +
  • Extending to other statistical functions
    • @@ -241,6 +243,11 @@

    Submodulesproperty formatted_output

    +
    +
    +property is_significant
    +
    +
    property significance_suffix
    @@ -250,7 +257,7 @@

    Submodules -

    statannotations.stats.StatTest module

    +

    statannotations.stats.StatTest module

    class statannotations.stats.StatTest.StatTest(func: Callable, test_long_name: str, test_short_name: str, stat_name: str = 'Stat', alpha: float = 0.05, *args, **kwargs)
    @@ -357,6 +364,7 @@

    Submodules + diff --git a/docs/source/custom-test.rst b/docs/source/custom-test.rst new file mode 100644 index 0000000..6b9f882 --- /dev/null +++ b/docs/source/custom-test.rst @@ -0,0 +1,4 @@ +Extending to other statistical functions +**************************************** + +.. include:: ../../statannotations/stats/README.rst \ No newline at end of file diff --git a/docs/source/modules.rst b/docs/source/modules.rst index 56a5960..86a09c7 100644 --- a/docs/source/modules.rst +++ b/docs/source/modules.rst @@ -5,3 +5,4 @@ statannotations :maxdepth: 4 statannotations + custom-test diff --git a/docs/source/statannotations.rst b/docs/source/statannotations.rst index 3a24356..e48438f 100644 --- a/docs/source/statannotations.rst +++ b/docs/source/statannotations.rst @@ -20,6 +20,8 @@ statannotations.Annotation module :undoc-members: :show-inheritance: +.. _Annotator_module: + statannotations.Annotator module -------------------------------- diff --git a/docs/source/statannotations.stats.rst b/docs/source/statannotations.stats.rst index 846d287..b660e9b 100644 --- a/docs/source/statannotations.stats.rst +++ b/docs/source/statannotations.stats.rst @@ -20,6 +20,8 @@ statannotations.stats.StatResult module :undoc-members: :show-inheritance: +.. _StatTest_module: + statannotations.stats.StatTest module ------------------------------------- diff --git a/requirements.txt b/requirements.txt index b27df50..c7dd725 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,7 +1,7 @@ numpy>=1.12.1 seaborn>=0.9.0,<0.12 matplotlib>=2.2.2 -pandas>=0.23.0 +pandas>=0.23.0,<2.0.0 scipy>=1.1.0 statsmodels -packaging \ No newline at end of file +packaging diff --git a/statannotations/Annotation.py b/statannotations/Annotation.py index 9f79398..f2fbc91 100644 --- a/statannotations/Annotation.py +++ b/statannotations/Annotation.py @@ -1,3 +1,4 @@ +import warnings from typing import Union from statannotations.PValueFormat import Formatter @@ -43,3 +44,10 @@ def print_labels_and_content(self, sep=" vs. "): for struct in self.structs) print(f"{labels_string}: {self.formatted_output}") + + def check_data_stat_result(self): + if not isinstance(self.data, StatResult): + warnings.warn("Annotation data has incorrect class." + + "Should be StatResult. Cannot annotate current pair.") + return False + return True diff --git a/statannotations/Annotator.py b/statannotations/Annotator.py index 6e6d41f..28ff3b2 100644 --- a/statannotations/Annotator.py +++ b/statannotations/Annotator.py @@ -38,6 +38,7 @@ 'text_offset', 'use_fixed_offset', 'verbose', + 'hide_non_significant', ] @@ -56,7 +57,8 @@ "text_offset": 1, "color": '0.2', "line_width": 1.5, - "custom_annotations": None + "custom_annotations": None, + "hide_non_significant": False, } ENGINE_PLOTTERS = {"seaborn": _SeabornPlotter} @@ -130,6 +132,7 @@ def __init__(self, ax, pairs, plot='boxplot', data=None, x=None, self.line_width = 1.5 self.value_offset = None self.custom_annotations = None + self.hide_non_significant = False @staticmethod def get_empty_annotator(): @@ -216,6 +219,9 @@ def annotate(self, line_offset=None, line_offset_to_group=None): self.validate_test_short_name() for annotation in self.annotations: + if self.hide_non_significant and isinstance(annotation.data, StatResult) \ + and not annotation.data.is_significant: + continue self._annotate_pair(annotation, ax_to_data=ax_to_data, ann_list=ann_list, @@ -261,6 +267,8 @@ def configure(self, **parameters): corresponds to "{suffix}" * a custom formatting string using "{star}" for the original pvalue and '{suffix}' for 'ns' + * `hide_non_significant`: hide annotations for non-significant pair + comparisons * `line_height`: in axes fraction coordinates * `line_offset` * `line_offset_to_group` @@ -687,7 +695,7 @@ def has_type0_comparisons_correction(self): def _plot_line(self, line_x, line_y): if self.loc == 'inside': - self.ax.plot(line_x, line_y, lw=self.line_width, c=self.color) + self.ax.plot(line_x, line_y, lw=self.line_width, c=self.color, clip_on=False) else: line = lines.Line2D(line_x, line_y, lw=self.line_width, c=self.color, transform=self.ax.transData) diff --git a/statannotations/PValueFormat.py b/statannotations/PValueFormat.py index 2f35b4d..5c2b8d0 100644 --- a/statannotations/PValueFormat.py +++ b/statannotations/PValueFormat.py @@ -154,8 +154,10 @@ def print_legend_if_used(self): print("p-value annotation legend:") pvalue_thresholds = sort_pvalue_thresholds(self.pvalue_thresholds) + print(f"{pvalue_thresholds[-1][1]}: ".rjust(10) - + f"p <= {pvalue_thresholds[-1][0]:.2e}") + + f"{pvalue_thresholds[-2][0]:.2e} < p " + f"<= {pvalue_thresholds[-1][0]:.2e}") for i in range(len(pvalue_thresholds)-2, 0, -1): print(f"{pvalue_thresholds[i][1]}: ".rjust(10) @@ -163,9 +165,7 @@ def print_legend_if_used(self): f"<= {pvalue_thresholds[i][0]:.2e}") print(f"{pvalue_thresholds[0][1]}: ".rjust(10) + - f"p <= {pvalue_thresholds[0][0]:.2e}") - - print() + f"p <= {pvalue_thresholds[0][0]:.2e}", end="\n\n") def _update_pvalue_thresholds(self): self._pvalue_thresholds = self._get_pvalue_thresholds( diff --git a/statannotations/_version.py b/statannotations/_version.py index 3d18726..906d362 100644 --- a/statannotations/_version.py +++ b/statannotations/_version.py @@ -1 +1 @@ -__version__ = "0.5.0" +__version__ = "0.6.0" diff --git a/statannotations/stats/README.rst b/statannotations/stats/README.rst new file mode 100644 index 0000000..c199c38 --- /dev/null +++ b/statannotations/stats/README.rst @@ -0,0 +1,31 @@ +1. Write your function that takes in two sets of data, and outputs a test statistic and a p-value: + +.. code-block:: python + + import numpy as np + from scipy.stats import ttest_ind + + def log_ttest(group_data1, group_data2, **stats_params): + group_data1_log = np.log(group_data1) + group_data2_log = np.log(group_data2) + + return ttest_ind(group_data1_log, group_data2_log, **stats_params) + +2. Initialize a ``statannotations.stats.StatTest.StatTest`` :ref:`object ` using your function: + +.. code-block:: python + + from statannotations.stats.StatTest import StatTest + + custom_long_name = 'Log t-test' + custom_short_name = 'log-t' + custom_func = log_ttest + custom_test = StatTest(custom_func, custom_long_name, custom_short_name) + +3. When you configure the ``statannotations.Annotator.Annotator`` :ref:`object `, you can pass your ``StatTest``: + +.. code-block:: python + + annot = Annotator(, ) + annot.configure(test=custom_test, comparisons_correction=None, + text_format='star') diff --git a/statannotations/stats/StatResult.py b/statannotations/stats/StatResult.py index a71c0e6..61b327d 100644 --- a/statannotations/stats/StatResult.py +++ b/statannotations/stats/StatResult.py @@ -51,6 +51,12 @@ def formatted_output(self): return stat_summary + @property + def is_significant(self): + if self._corrected_significance is False: + return False + return self.pvalue <= self.alpha + @property def significance_suffix(self): # will add this only if a correction method is specified diff --git a/tests/test_annotation.py b/tests/test_annotation.py index 1b72dfa..b8a70d6 100644 --- a/tests/test_annotation.py +++ b/tests/test_annotation.py @@ -19,3 +19,13 @@ def test_missing_formatter(self): annotation = Annotation(("group1", "group2"), res) print(annotation.text) + + def test_check_data_stat_result(self): + annotation = Annotation(("group1", "group2"), "p=0.05") + + res = StatResult("Custom test", None, pval=0.05, stat=None, + stat_str=None) + annotation_stat_result = Annotation(("group1", "group2"), res) + + self.assertFalse(annotation.check_data_stat_result()) + self.assertTrue(annotation_stat_result.check_data_stat_result()) diff --git a/tests/test_annotator.py b/tests/test_annotator.py index 2c9f4dc..a213d2b 100644 --- a/tests/test_annotator.py +++ b/tests/test_annotator.py @@ -40,6 +40,32 @@ def setUp(self): "hue": "color", "order": ["a", "b"], "hue_order": ['red', 'blue']} + + self.df_x_float = pd.DataFrame( + data={ + "x_axis": [1.01, 1.02, 1.03, 1.01, 1.02, 1.03, 1.01, 1.02, + 1.03, 1.01, 1.02, 1.03, 1.01, 1.02, 1.03, 1.01, + 1.02, 1.03, 1.01, 1.02, 1.03, 1.01, 1.02, 1.03], + "y_axis": [16.99, 10.34, 21.01, 23.68, 24.59, 25.29, 8.77, + 26.88, 15.04, 14.78, 10.27, 35.26, 15.42, 18.43, + 14.83, 21.58, 10.33, 16.29, 16.97, 20.65, 17.92, + 20.29, 15.77, 39.42], + "hue": ["hue_2", "hue_2", "hue_1", "hue_1", "hue_2", "hue_2", + "hue_2", "hue_1", "hue_2", "hue_1", "hue_1", "hue_2", + "hue_1", "hue_1", "hue_0", "hue_0", "hue_2", "hue_1", + "hue_0", "hue_0", "hue_2", "hue_0", "hue_2", "hue_1"] + } + ) + self.params_float = { + "data": self.df_x_float, + "x": "x_axis", + "y": "y_axis", + "hue": "hue", + "hue_order": ["hue_0", "hue_1", "hue_2"], + "order": [1.01, 1.02, 1.03] + } + self.ax_float = sns.boxplot(**self.params_float) + self.params_arrays = { "data": None, "x": self.df['x'], @@ -51,6 +77,16 @@ def setUp(self): def test_init_simple(self): self.annot = Annotator(self.ax, [(0, 1)], data=self.data) + def test_init_float(self): + self.annot_float = Annotator( + self.ax_float, + pairs=[ + ((1.01, "hue_0"), (1.01, "hue_1")), + ((1.02, "hue_0"), (1.02, "hue_1")) + ], + **self.params_float + ) + def test_init_df(self): self.ax = sns.boxplot(**self.params_df) self.annot = Annotator(self.ax, pairs=self.pairs, **self.params_df) @@ -170,6 +206,16 @@ def test_support_int_labels(self): self.annot.configure(test="Mann-Whitney") self.annot.apply_and_annotate() + def test_support_float_labels(self): + self.test_init_float() + self.annot_float.configure(test='Mann-Whitney') + self.annot_float.apply_and_annotate() + + def test_configure_hide_non_significant(self): + self.test_init_simple() + self.annot.configure(test='Mann-Whitney', hide_non_significant=True) + self.annot.apply_and_annotate() + def test_get_annotation_text_in_input_order(self): self.test_init_df() self.annot.configure(test="Mann-Whitney", text_format="simple") diff --git a/tests/test_pvalue_format.py b/tests/test_pvalue_format.py index acf6cc4..c5dbcd7 100644 --- a/tests/test_pvalue_format.py +++ b/tests/test_pvalue_format.py @@ -83,7 +83,7 @@ def test_print_pvalue_default(self): pvalue_format = PValueFormat() self.assert_print_pvalue(pvalue_format, "p-value annotation legend:\n" - " ns: p <= 1.00e+00\n" + " ns: 5.00e-02 < p <= 1.00e+00\n" " *: 1.00e-02 < p <= 5.00e-02\n" " **: 1.00e-03 < p <= 1.00e-02\n" " ***: 1.00e-04 < p <= 1.00e-03\n" @@ -94,7 +94,7 @@ def test_print_pvalue_star(self): pvalue_format.config(text_format="star") self.assert_print_pvalue(pvalue_format, "p-value annotation legend:\n" - " ns: p <= 1.00e+00\n" + " ns: 5.00e-02 < p <= 1.00e+00\n" " *: 1.00e-02 < p <= 5.00e-02\n" " **: 1.00e-03 < p <= 1.00e-02\n" " ***: 1.00e-04 < p <= 1.00e-03\n" @@ -130,6 +130,6 @@ def test_config_pvalue_thresholds(self): ]) self.assert_print_pvalue(pvalue_format, "p-value annotation legend:\n" - " ns: p <= 1.00e+00\n" + " ns: 5.00e-02 < p <= 1.00e+00\n" " <= 0.05: 1.00e-03 < p <= 5.00e-02\n" "<= 0.001: p <= 1.00e-03\n\n") diff --git a/tests/test_stat_result.py b/tests/test_stat_result.py index efe3ffe..484c854 100644 --- a/tests/test_stat_result.py +++ b/tests/test_stat_result.py @@ -9,18 +9,34 @@ class TestStatResult(unittest.TestCase): def setUp(self) -> None: self.benjamini_hochberg = ComparisonsCorrection("Benjamini-Hochberg") - self.stat_result = StatResult("Test X", "X", "Stat", 1, 0.02, - alpha=0.05) + self.stat_result = StatResult("Test X", "X", "Stat", 1, 0.02, alpha=0.05) self.stat_result.correction_method = self.benjamini_hochberg.name + self.stat_result_non_significant = StatResult( + "Test X", "X", "Stat", 1, 0.06, alpha=0.05) + self.stat_result_non_significant.correction_method = ( + self.benjamini_hochberg.name + ) def test_ns_if_ns(self): self.stat_result.corrected_significance = False assert self.stat_result.formatted_output == ( "Test X with Benjamini-Hochberg correction, P_val:2.000e-02 (ns) " - "Stat=1.000e+00") + "Stat=1.000e+00" + ) def test_nothing_if_s(self): self.stat_result.corrected_significance = True assert self.stat_result.formatted_output == ( "Test X with Benjamini-Hochberg correction, P_val:2.000e-02 " - "Stat=1.000e+00") + "Stat=1.000e+00" + ) + + def test_is_significant(self): + assert self.stat_result.is_significant + + def test_is_non_significant(self): + self.assertFalse(self.stat_result_non_significant.is_significant) + + def test_corrected_significance(self): + self.stat_result.corrected_significance = False + self.assertFalse(self.stat_result.is_significant) diff --git a/usage/example.ipynb b/usage/example.ipynb index 07fe9f3..c403646 100644 --- a/usage/example.ipynb +++ b/usage/example.ipynb @@ -56,7 +56,7 @@ "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -149,7 +149,7 @@ "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -184,41 +184,32 @@ }, { "cell_type": "markdown", - "source": [ - "Or another" - ], "metadata": { "collapsed": false, "pycharm": { "name": "#%% md\n" } - } + }, + "source": [ + "Or another" + ] }, { "cell_type": "code", - "source": [ - "x = \"day\"\n", - "y = \"total_bill\"\n", - "order = ['Sun', 'Thur', 'Fri', 'Sat']\n", - "ax = sns.boxplot(data=df, x=x, y=y, order=order)\n", - "annot.new_plot(ax, data=df, x=x, y=y, order=order)\n", - "annot.configure(comparisons_correction=\"BH\")\n", - "annot.apply_and_annotate()" - ], + "execution_count": 6, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, - "execution_count": 6, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -231,7 +222,7 @@ }, { "data": { - "text/plain": "(,\n [,\n ,\n ])" + "text/plain": "(,\n [,\n ,\n ])" }, "execution_count": 6, "metadata": {}, @@ -245,30 +236,45 @@ "metadata": {}, "output_type": "display_data" } + ], + "source": [ + "x = \"day\"\n", + "y = \"total_bill\"\n", + "order = ['Sun', 'Thur', 'Fri', 'Sat']\n", + "ax = sns.boxplot(data=df, x=x, y=y, order=order)\n", + "annot.new_plot(ax, data=df, x=x, y=y, order=order)\n", + "annot.configure(comparisons_correction=\"BH\")\n", + "annot.apply_and_annotate()" ] }, { "cell_type": "markdown", - "source": [ - "To have `\"ns\"` instead of `\"* (ns)\"`, configure with `correction_format=\"replace\"`." - ], "metadata": { "collapsed": false, "pycharm": { "name": "#%% md\n" } - } + }, + "source": [ + "To have `\"ns\"` instead of `\"* (ns)\"`, configure with `correction_format=\"replace\"`." + ] }, { "cell_type": "code", "execution_count": 7, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -281,7 +287,7 @@ }, { "data": { - "text/plain": "(,\n [,\n ,\n ])" + "text/plain": "(,\n [,\n ,\n ])" }, "execution_count": 7, "metadata": {}, @@ -301,13 +307,7 @@ "annot.new_plot(ax, data=df, x=x, y=y, order=order)\n", "annot.configure(comparisons_correction=\"BH\", correction_format=\"replace\")\n", "annot.apply_and_annotate()" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - } + ] }, { "cell_type": "markdown", @@ -333,7 +333,7 @@ "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -409,13 +409,19 @@ { "cell_type": "code", "execution_count": 10, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -465,13 +471,7 @@ "annot.annotate()\n", "plt.legend(loc='upper left', bbox_to_anchor=(1.03, 1))\n", "plt.savefig('example_hue_layout.png', dpi=300, bbox_inches='tight')" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - } + ] }, { "cell_type": "markdown", @@ -535,7 +535,7 @@ "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -596,7 +596,7 @@ "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -705,23 +705,29 @@ }, { "cell_type": "markdown", - "source": [ - "### Use a different test with StatTest" - ], "metadata": { "collapsed": false - } + }, + "source": [ + "### Use a different test with StatTest" + ] }, { "cell_type": "code", "execution_count": 16, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -734,7 +740,7 @@ }, { "data": { - "text/plain": "(,\n [,\n ,\n ])" + "text/plain": "(,\n [,\n ,\n ])" }, "execution_count": 16, "metadata": {}, @@ -773,13 +779,84 @@ "annot.new_plot(ax, pairs, data=df, x=x, y=y)\n", "annot.configure(test=custom_test, comparisons_correction=None,\n", " text_format='star').apply_test().annotate()" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Use a custom test with StatTest" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "p-value annotation legend:\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", + " *: 1.00e-02 < p <= 5.00e-02\n", + " **: 1.00e-03 < p <= 1.00e-02\n", + " ***: 1.00e-04 < p <= 1.00e-03\n", + " ****: p <= 1.00e-04\n", + "\n", + "setosa vs. versicolor: Log t-test, P_val:4.416e-18 Stat=-1.066e+01\n", + "versicolor vs. virginica: Log t-test, P_val:1.979e-07 Stat=-5.598e+00\n", + "setosa vs. virginica: Log t-test, P_val:3.486e-29 Stat=-1.605e+01\n" + ] + }, + { + "data": { + "text/plain": "(,\n [,\n ,\n ])" + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
    ", + "image/png": 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\n" + }, + "metadata": {}, + "output_type": "display_data" } - } + ], + "source": [ + "from statannotations.stats.StatTest import StatTest\n", + "import numpy as np\n", + "from scipy.stats import ttest_ind\n", + "\n", + "# Any function that follows the StatTest API could go here\n", + "def log_ttest(group_data1, group_data2, **stats_params):\n", + " group_data1_log = np.log(group_data1)\n", + " group_data2_log = np.log(group_data2)\n", + "\n", + " return ttest_ind(group_data1_log, group_data2_log, **stats_params)\n", + "\n", + "df = sns.load_dataset(\"iris\")\n", + "x = \"species\"\n", + "y = \"sepal_length\"\n", + "\n", + "pairs = [(\"setosa\", \"versicolor\"), (\"setosa\", \"virginica\"), (\"versicolor\", \"virginica\")]\n", + "\n", + "# Required descriptors for annotate\n", + "custom_long_name = 'Log t-test'\n", + "custom_short_name = 'log-t'\n", + "custom_func = log_ttest\n", + "custom_test = StatTest(custom_func, custom_long_name, custom_short_name)\n", + "\n", + "# Then, same as usual\n", + "ax = sns.boxplot(data=df, x=x, y=y)\n", + "annot = Annotator(ax, pairs, data=df, x=x, y=y)\n", + "annot.configure(test=custom_test, comparisons_correction=None,\n", + " text_format='star').apply_test().annotate()" + ] }, { "cell_type": "markdown", @@ -791,7 +868,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": { "scrolled": true }, @@ -824,7 +901,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": { "scrolled": false }, @@ -834,7 +911,7 @@ "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -867,23 +944,29 @@ }, { "cell_type": "markdown", - "source": [ - "Non-hue violin" - ], "metadata": { "collapsed": false - } + }, + "source": [ + "Non-hue violin" + ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -912,13 +995,7 @@ " .set_pvalues(pvalues=pvalues)\n", " .annotate())\n", "plt.show()" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - } + ] }, { "cell_type": "markdown", @@ -929,12 +1006,12 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": { - "scrolled": false, "pycharm": { "name": "#%%\n" - } + }, + "scrolled": false }, "outputs": [ { @@ -942,7 +1019,7 @@ "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -979,23 +1056,29 @@ }, { "cell_type": "markdown", - "source": [ - "With a log-scale swarm plot\n" - ], "metadata": { "collapsed": false - } + }, + "source": [ + "With a log-scale swarm plot\n" + ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -1009,7 +1092,7 @@ { "data": { "text/plain": "
    ", - "image/png": 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TgODgYNq0aQNA8+bNyc7Opnnz5pw7d44nnniCtWvX8tJLLwEwbtw456qSq1evZvTo0WX2cfjwYTp06EBERAQADz30ELt27XLG2bt3b+fxWVlZzv5XrlxJQUEBu3btYuDAgUBxxbb69evj7e1NYGAgPXr0ACA8PJycnJxyr3UtrVZLVFQU48eP54MPPmDKlCnUq1fvln7uV0iiLYQQQghRzdKyCm9p/43o1auXcwoJgMPhcDvGZrMBYDQanW2KoqCqKoGBgaxZs4ZHHnmEc+fOcf/995OTk0PXrl1JSUlh/fr1REREOJPT0vq49pqqqjqvefU5ilIyXWbIkCFs376ddevW0adPH+cxer3epS+tVuuyXd61VFV1ec0AH330Ea+99hqqqjJ16lR2797t9jO6GZJoCyGEEEJUs5AAr1vaf6OuTCFJSUmhe/furFmzhsLCQmw2G0uWLKF79+5lnrthwwZefPFF+vXrx8yZM/Hx8SExMRFFURgzZgxvvvlmuasrd+zYkUOHDjkrnnz33Xd069btuud4e3vTp08f/vnPf97Q6s3Xu1ZgYCCnT592vi6AjIwMhg0bRosWLXj22WeJjo7m5MmTFb7e9UiiLYQQQghRzUb3uQsvg7bUfV4GLaP7NqvU612ZQmK1WunXrx/9+vVj3LhxDB8+nPDwcB555JEyz+3Tpw9eXl4MHz6cBx54gFGjRtGyZUsAhg8fTkFBAYMGDbru9UNCQnj99deZPn06w4cPZ/fu3cyePbvcuIcPH47JZKJjx44Vfq3Xu9b//d//MWfOHMaNG4efnx8AQUFBPPTQQ4wfP56xY8dSVFTEuHHjKny961HUK+PnNYjFYuHo0aO0a9fO5faFEEIIIURViI2NpXXr1hU+vrSqI1CcZN/dom6lVB2pag6Hg2+//ZZz584xc+bMSu/fbrczb948goODmTJlSqX3fzOufZ/LyzmlvJ8QQgghRDXTaBT+9Og9bDl4iRWbT5fU0e7bjD53N7jtk2yA6dOnk5iYyGeffVYl/Y8bN47AwEA+/vjjKum/OkiiLYQQQgjhARqNQr9OEfTrFOHpUG7KRx99VKX9L1++vEr7rw4yR1sIIYQQQogqIIm2EEIIIYQQVUASbSGEEEIIIaqAJNpCCCGEEEJUAXkYUgghhBCiBlq7di0LFizAZrOhqiqjR49m6tSpng6rVpFEWwghhBDCA1TVQd6xbWTHrMKWm47OL5g63UZiatsLRbm1SQfJycnMnTuXpUuXEhgYiNlsZtKkSTRp0oSBAwdW0isQ5ZFEW9RKBeePYEk8g3ejdhjDK3f1LSGEEKI8quog+Ye/U3DuEKrVAkCROZu0Hz/BHLuTeuNfvKVkOzMzE6vVSmFhIQC+vr789a9/Zf/+/UyYMIFFixYBsHTpUg4dOkTHjh3ZunUr2dnZxMfHEx0dzWuvvQbAJ598wsqVK9FqtURHR/Piiy+SmJjI9OnTad68ObGxsQQHB/Pee+/x008/sWvXLt555x0A3n//fYxGIxaLhcuXL3P+/HkyMjJ45pln2LlzJ4cOHaJVq1bMmzcPRVHKvNbkyZPZuHGjs0+Ap59+mldeeYVTp04BMHHiRB588MGb/plVBZmjLWqdzC2LSfz6NTI2LuTSFzPIObjB0yEJIYSoZfKObXNJsq9QrRYKzh3CfGz7LfXfqlUrBg4cyKBBgxg/fjx///vfcTgcPPTQQ6SmpnLx4kWguFb12LFjAThw4AD/+te/WLlyJb/88gsnT55k8+bNbNy4kSVLlrBs2TIuXLjgTNJPnDjBlClTWL16Nf7+/qxatYphw4axc+dO8vLyAFi9ejWjR48GIC4ujoULF/LGG2/wpz/9iSeffJLVq1dz/Pjxcq9VmgMHDpCdnc3y5cuZP38+e/fuvaWfWVWQRFvUKqrdRtauFS5tWTuWeigaIYQQtVV2zCq3JPsK1WohK2bVLV9j9uzZbNy4kd/85jdcvnyZBx98kJ9++on777+flStXcvnyZdLT0+nYsSMAUVFRmEwmvL29iYyMJDs7m127djF8+HC8vb3R6XSMGzeOnTt3AhAcHEybNm0AaN68OdnZ2fj6+tK3b19++ukn9u7dS2RkJPXq1QMgOjoanU5HeHg4devWpVmzZuh0OurVq1futUrTvHlzzp07xxNPPMHatWt56aWXbvlnVtlk6oiofVTH9beFEEKIKmbLTb/ufntu2i31v2nTJvLz8xk2bBjjxo1j3LhxLF68mB9++IFZs2YxdepUDAaDc7QZwGg0Ov+tKAqqquJwuH9G2my2Mo+H4qXTP/74YyIiIpyj5QB6vd75b53OPQUt61pX932lTafTERgYyJo1a9i+fTubN2/m/vvvZ82aNfj7+1foZ1QdZERb1CqKVod/12EubXW6jfJQNEIIIWornV/wdfdr/UJuqX8vLy/eeecdEhISAFBVldjYWFq3bk2DBg0ICwtj0aJFLol2abp3786aNWsoLCzEZrOxZMkSunfvft1zunTpQlJSEjExMQwaNKjCMZd1LX9/f7KyssjIyKCoqIitW7cCsGHDBl588UX69evHzJkz8fHxITExscLXqw4yoi1qneABk/CKaFX8MGTjdng3aufpkIQQQtQydbqNJO3HT0qdPqLojQR0G3lL/Xfv3p3p06fz9NNPY7VaAejduze/+93vABg2bBjr1693TusoS//+/YmNjWXcuHHYbDZ69erFI488QlJS0nXPu/fee8nKysJgMFQ45rKupdPpmDp1KuPHjycsLIz27dsD0KdPH9avX8/w4cMxGo2MGjWKli1bVvh61UFRrx6LryEsFgtHjx6lXbt2Lrc1hBBCCCGqwpXR4ooqreoIFCfZ3k063nLVkeux2Wy89NJLDBkyhPvuu69S+1ZVFavVypQpU3jllVdo27Ztpfbvade+z+XlnDJ1RAghhBCimimKhnrjX6TusGcwhN2F1rcOhrC7qDvsmSpNslVVpXfv3iiKckPTOioqNTWV6OhoOnbsWOOS7JshU0eEEKIWKiwsxGw2M2vWLN555x1UVWXhwoU0bdrUWRkAYNKkSXzzzTdYrdYbugUshCifomgwteuNqV3varymct1KHrcqNDSUPXv2VFn/dxpJtIUQohZau3Ytq1ev5ty5c/z2t7/FarWSm5uLj48Pu3fv5v777+dvf/sbycnJPPnkk0yZMoXo6GhPhy2EEHcUmToihBC10IgRIzAYDLRt25bRo0fzl7/8heDgYDQaDY8//jitWrWie/futGvXjvDwcEmyhaiAGvjYm7jKzby/MqIthBC1kFar5amnnqJly5acO3eOwMBAZs2aRX5+Pr6+vgB069aNJ598kgMHDng4WiFuf15eXqSnpxMcHIyiKJ4OR1QyVVVJT0/Hy8vrhs6TqiNCCCGEELfIarWSkJBAYWGhp0MRVcTLy4uIiAiXhXfKyzllRFsIIYQQ4hbp9XqaNGni6TDEbUbmaItaS7XbsBfkeToMIYQQQtRQMqItaqW849tJW/cpjvwcvBu3J3TsC2i9/TwdlhBCCCFqEBnRFrWOo9BM6uoPceTnAFBw/giZWxZ7OCohhBBC1DQyoi1qHWtGostytwBFKec9E4yoUZYuXcratWs9HYYAhgwZwtixYz0dhhCilpMRbVHrGEIbofUNcGnzbtLRQ9GImmTt2rXExcV5OoxaLy4uTr7wCCFuCzKiLWodRacn7KFXSN/wJbasFHxb9yCgxxhPhyVqiBYtWrBgwQJPh1GrTZs2zdMhCCEEIIm2qKWM9e8i/JHXPR2GEEIIIWowmToihBBCCCFEFZBEWwghhBBCiCogU0dErWXLSSf9py+wJJ7Bq1E7gu99DK2Xr6fDEkIIIW5KTEwM8+bNIzIyklOnTmGz2Zg9ezaqqvLXv/4Vh8MBwFNPPcXgwYM9HG3tIIm2qLVSls+jMD4WgLzDG8FhI3T0sx6OStzJRo0a5ekQBPI+iNrt8OHDzJo1i9atW/P5558zb948tFotU6ZMYfjw4Zw4cYLvvvtOEu1qIom2qJUcVoszyb4i/+xBD0UjaooRI0Z4OgSBvA+idgsPD6d169YAtGnThmXLlvHwww/z+uuvs3HjRnr27Mnzzz/v4ShrD5mjLWo8W14WBeeP4CgqcLZp9EZ0gWEuxxnqNqzu0IQQQohK5eXl5fy3oiioqsqECRNYuXIl0dHRbNu2jVGjRmGxWK7Ti6gskmiLGi338CYuvv8UiV+/xsX3n6Iw/oRzX+jI36PzDwFAHxJByJAnPRWmEEIIUWUmTJhAbGwsY8eO5Y033iAnJ4fU1FRPh1UryNQRUWOpdhvpP38BDhsAjkIz6RsX0uDROQB4RbYicvrH2M056EwB1+tKCCGEuGP98Y9/5K233uLdd99FURSmT59ORESEp8OqFSTRFjWWaivCUWB2abPnprtsK4pGkmwhhBA1Qrdu3Vi9enWp20uXLvVUWLWaTB0RNZbG6INPs04ubaa2vT0UjRBCCCFqGxnRFjVa6JjnyNqxFEvyeXyadsS/y1BPhySEEOIOsXTpUtauXevpMAQwZMgQxo4d6+kwbpgk2qJG0xi9Cer/sKfDEEIIcQdau3YtcXFxtGjRwtOh1GpxcXEAkmgLIYQQQtQkLVq0YMGCBZ4Oo1abNm2ap0O4aTJHWwghhBBCiCogibYQQgghhBBVQBJtIYQQQgghqoAk2kIIIYQQQlQBeRhSCCGEEKIUo0aN8nQIgjv7fZBE+zaz/2QKp+Oz6NAshFaNgzwdjhBC3LGsGYlk7/kR1VaEf9S9GMObeTokcYcZMWKEp0MQ3NnvgyTat5H//i+W736Oc25Pf6Ajg7s39lxANVjB+SNkbPoWe342fh0HENBzLIqieDosIcRNyD9zgPSf/4M1MxlUB4reC7+7B5F7aANqYR4AeUc20+Dxv2EIbejhaIUQtYnM0b5N2OwOlm8549K2ZONpD0Vz53JYCjCfjMGSdLbMY+z5OSQtfhvLpZPYMpPI3PQNeUc2VV+QQohKY8vLIvn7uVjTEsBuBYcd1WImJ2aFM8kGUO1W8o5t8WCkQojaSEa0b2MqqqdDuKMUpcZzeeGrOApyAfDvMpSQwVPdjiuMP4Fqtbi05Z89iF+H/mX2bcvNQLUWog8Kr9yghRC3pDAhFtVurdCxGh//Ko5GCCFcyYj2bUKn1TCqd1OXtrH9m3somjtT1o6lziQbIGfvWqxZKW7HFd86dp0mYgxtXGa/aes+4+L7TxH/8e+5/PVrOIoKKytkIcQtMtZrwrW/z1foAsKc/9bXbYhfx4HVFJUQQhSTEe3byORhbWjTJJgzCVm0bxZCmybBng7pjmIvyLumRcVRkAcBoS6t+sAwgu97nIzN36JaCvBt1Q3/rsNK7bMw4SQ5e38s2T5/hJwDPxHQbWRlhy9qILtD5dPlR1i/+yImbz2PDm/DgC6Rng6rRtEHhhE8eCoZG75EtRU5273viiJ07B+xJp/DYS3Cu3E7FI3Wg5EKIWojSbRvM11a16NL63qeDuOO5Hf3AArO7HduG8KaYghrUuqxdboOwz/qXlRbERov3zL7tGYmubXZSmkTojTrd51n9fZzAGRY7bz33QHaNg2mXpCPhyOrWep0GYJ/1CDs+Tk4LPno/ILQGIt/xtrI1m7Hq6pK3uFfyD93CGNoY/y7DkOjN1Z32EKIWkASbVFjmFr1QDNhJnnHt6OrU5c6XYddt5KIotOj6PRu7Zbk8xQlncWrYRu8IlujaPUuc0A1vgHkHd+OT7POaAxeVfJaRM1wMC7VZdvhUDkVnymJdhVQtDp0fkHgV3pZVIfVQua2H7CmJaCiUhC3BwDzsW1YEk9Tb9yL1RmuEKKWkERb1Cg+d0Xhc1fUTZ+ftWslGRu+LN5QNOj8gkuSbK0OrSmQrC2LANAFhNLgsb+i9a1zq2GLGiY3v4g5X+zm2Nl0l3atRqFlQ6mPX91sOekk/Ps5HIXmUvebT8TgKDRf9+6WEELcDHkYshJZbXbiLmZiLij7CXi73cH2w5dZs+0s6dkF1RidKI9qt5G5dfFVDQ5sOVeNSNpt2LNLtm1ZKeQe2liNEYo7xQ8bTrkl2SEBXrzwcGfqBnp7KKraK2ff2ozBLzUAACAASURBVDKTbADF6I2iM1RjREKI2kJGtCvJqfhMXv80hqw8C0aDlmcfiqL33Q3cjnv9sxj2nyyuhPHlj7HMnd6LJuEyIno7UB12VFvFyoRdIRVIRGniU3Ld2p77TSc6NKvrgWiEvfDaB6VdBfWbWOo0MiGEuFUyol1JPlt5jKy84trMliI7C5YdwW53uBwTdzHTmWQDFFhsrNpa9sIqonpp9Eb8OvS7/kHaku+misELvw59qzYocUe6p02Yy3Ydk4GWjWTKiKf4dRgASukfd3W6jaROl6HVHJEQoraQEe1KkpKZ77KdlWehsMiOr7eGtKx8lm8+i7mwyO082zXJuPCskKHTMDZoTlHSOfShDUn/3wKX/fqAepja9MJhs+DXcYAsYCNKNbh7I/ILbWzen0BQHS8eGdIKo15Ky3mKV4PmhD/6FukbvsQSH+uy73pTSoQQ4lZJol1JojuEs3xzyRLqLRoGoNdpOHI6jT9/sh3110UeFXCu96jTahgWXXr5OXFz8o5vJztmFSgKAT3G4Nuy2w2dr2i0+N89qKS/gxuwJJa8rxpvPwJ63i+3mWuJS6l5WIrsNG1wY9O7FEVhbP9mjO3frNT9J85nEHMsifohvvTvHIleJzcXKyrnwM/k7F+PxuhNYK/xOCwFpP/8H+x5mZja9yVk8BMoWvffT68GzQl74GXiP3wGh6VkYMS3VffqDF8IUcsoqqrWuHW+LRYLR48epV27dhiN1VMb1WZ3sGTjKTbtT+Byah4OFQJMRkw+ehJSXOcHtmsaTPtmIfTqGE7DMFkSuLIUXjrF5f/8CedXGUVDxNR3fl0J8ubYcjOLqxVcteJknW4jCR702K0FK25rqqryz2/3s2lfAgCtGwcxe1oPvI23Pjax88hl3v5yj/PLd7e2Ycx8/Ma+ENZW+af2kbT4Lee2otWjqio4bM62oAGTCOgxpsw+LElnydq+BHtBHv5RgzC17V2lMYs7V8zRRFZvO4dOp2H8gOa0bSqLyAl35eWcMoxSSXRaDeMGNCc1qwDHrx+gWXkWtyklAHUDvZk4uJUk2ZUs/8x+Su4XAKqD/LMHbq1T1eGSZEPxh72o2Q6fSnMm2QCx5zP4KeZCpfS9aus5rh7eiDmWREqG+98J4c58eq/Ltmq3uiTZAIUJJ67bhzGsKfXGvUj4I7MlyRZlOnEhgzn/2c3BU6nsjU3mL/N3lPp5LkR5JNGuRCfOZ2Apsru0aa5ZMEVRYHSfuyrUX2KamW2HLpGRI5UtKsJQ131pa0NISZs1O4WitJLkKf/MAaxZydftU+vrj8bH9QuRPiTiFiMVt7vSPlBTsyqnHOe100QUBbTashdWEiUMpf3uKa5z370iWqHarFiSz+OwWqopMlHT7DqS6PKFuMjmYG/s9T8vhCiNzNGuRNdOEQGICDVxf7/mrNhyBi+DlseGt+GuiIBy+/rfzvN8vOQQqlo8Wv6nx7q6VTIQrnxbdsOv4wByD28CwL/TfXjfFYWqqqSt+fjXmtcqxvDmFKVcQLUVP5zq07IbYeNfKrVPRaun7rBnSF3zIY6CPPQhEQQPnFxNr0h4Spc29fA2aimwFH9x1igQ3bFyHnwdN6AZR86kYbUVPwh9X7dGBNeR2toV4Rd1LwXnj5Ift7u4iojqALVkcMNQvxnG8GZceH8ajvwcNF4mQu9/Hp+mHT0YtbgT1Q9xX7yofrAsaCRunMzRrkTxybn87u8bXb4Fvzy5C9Ed3etpl2bdrgv8tPsCfj4Gjp9NI99S8gHSuL4/7/+xf2WHXCPZ83NBAa23HwAF54+Q+PVr1z2nwRP/wBhW9oOpDlsR9rxMdHVCr7usu6g5TidkseyX0xQW2RkW3ZjOrepVWt9J6Wb2xSYTXtfE3S3qyv9TN8iak07CgudQLddUDFE06IMbYE2LdzbpAsNo+NsP3fooOHeY/HOHMIY2xrdNTxSNVIURJaw2O2/9Zw97Y5NRFBjUtSG/f/Bu+V0VbsrLOWVEuxJF1vPjud904tt1JykssjG8V5Myk+yzl7LxMmgJr2sCYMfhy3zw/cEy+87Ndy8NKEqn9fFz2bZmln+7z5J42i3RtmWnUnDxGDr/uthy0tAH1UcfUHnJlri9NYsI4MVJXdza45OL5+xH1vNz21dRYcG+DO/V9KbPr+203ibUolKm8qgObJlJLk22rBRUh90lkc7Zv560/813bvtdPEbdYU9XWbzizqPXaZk1tTuJaWZ0Wo2s6CpumiTalax/50j6d47E4VBZvvkML3+4jYhQExMHtyLI34v8Qiuv/XsXseczABjQJZLfP3g3C5YfuW6/93VrVB3h1xhFqfFovE3oTIH4NOuEojeiljVfU9Hge81DUfmn9pH0w9/cHrQyte9H6KjfV1XY4jZmszv465d7iDlWnMh1bVOPVx67B51WHnWpbhq9EVO7PuQd2eS2T7W7ru7q06IrKBps2aloTYGoqoPMbT+4HJN7aCPBAx9FY5RkSrgqbQqJEDdCEu0q8v3GOP77v+Kn34+dTedMQhbznuvH+pgLziQbYOPeeELqeJOe7f7A47gBzcjMsdChWQgDurg/6Cfc2QtySVo0B8vlU6BoCOgxhqD+D1P/4dfI2rkc1VqIX9Rg8g7/QsH5w2i8fAkZ+hRag5dLPxlbvnNLsgHyjmyiKC2e+r951Tk1RdQOOw8nOpNsgD3Hk9l+6DJ9O0UQdzGTzQcSCPLzYnCPxpi8pc56Vas7/GmMYU3IO7aVorQE1CLXv6GG0MZ4NWqLqW1vEuY/izX9UvGDzYoGhznL5VhFowWNfGESQlS+2zbRPnXqFO+//z4+Pj6MHDmS6OhoT4d0Q3YcSnTZPp2QTVK6mdRM99udCSm5bm0dm4fw2PC2VRZfTZW9e3Vxkg2gOsjasRRTuz54NWjh8sCjqdX16xarRWWXcSpKPEP2rpUE9X+4UmIWd4bSKpGkZOZz5HQaM+fvwPFrXc8tBy4x77m+aDQyl7MqKVo9de4ZQZ17RpD0w9/IPxnjsj9k+DN4hTcj8ds3sKZfAsCRn1NqX36dh6DRV9/zPEKIYlm7VpC950c0Oj0BvR7Ar31fT4dU6W7br/D5+fm88sorvPDCC6xevdrT4dywesE+LtveRi11TEZ6dWzA1Z+/XgYtcRczXY7VaRWeHtuhOsKscWylzMe2XjNnsyL8ou677n5rRuJ194s7X8zRRJ59ZxPT3v6Z5ZtP061dmMs0EZ1WQ/d29Vm767wzyQY4ezmbExcySutSVBH/qHuLq5D8yli/Gcb6xWVUry7pWRatl0wPEKK65Z/aR8aGr7DnpGHNSCR15fsUpV70dFiV7rYZ0f7000/Ztm2bc/vzzz/n4sWLvPzyy0yefOeVU5s0tDVnErJIySzAoNPwyJDWeBt1tG4SxEuTuvDznnh8vHQciksl7appI4oCf3miOxGhMi3hZvi26k7esa3ObY23H96N2t1QH9l7fiRrx1LQ6tAHR2Bs0Bzz4U0ucz99WnSttJjF7Scp3czbX+7B/msC/dnKY9QL8uXNp3uyYssZAEb1bkpkPT+8DO5/RktrE1XH564owie9Qd7x7ej8g/HvdJ+zOoTPXZ3IPbD+uufbctOrI0whxFUKLhy9pkWl4MJxDHVvfjXn29Ft82kwdepUpk6d6tw+evQojRs3ZtGiRTz++OMMGzbMg9HduMh6fiz40yC+WX+S1VvP8O8VR9l/MoUAPyOb9iWg1SgM7dGYbLNrNRFVpVKWea6tfFt1p+7I35N7eCNanzoYwpqQ9MNctN5+BPYajyHU/aFSVVXJillFzt4fUS0FOApL6qFbU84T2PN+6nQaTObW77DnZeHXoV+NvL0lShw9k+ZMsq84GJfCM+M6ui3DPKbvXew4fJm8guIvYj071KdpgzrVFmttVnjpFFk7l6FaLfh3GkzI4Cfcjgke9CiKTkfB2UMY6jXGt2U3Ule+f9UXZwVTm17VG7gQwnnXqby2O91tm9FZLBb+/Oc/YzKZ6Nv3zkxqsvIsLNl4yvmBve9EinOf3aGyYutZDDoNRb8uXAHFI9pXP+V8OTUPq81Bo/qyXHtF+XXoh1+HfphPxpD8w9+c7QXnj9Dwdx+7VRbI2bOGzA1fltlf4eVTmNr2IuyBl6ssZnF7adrAfVGpspLnyHp+LHhlEHuOJxPkb6Rj87pVHV6tlX96H3nHd6CrE4KpTS8Sv34N1Vp8R7Dg7CHqT3od74ZtXM7RGLwIuc81ATeENiJr5wocFjP+dw/Cu5E8DyNEdfNtE43/5VPk7l8PWh2B0ePwatDc02FVuipPtPPy8pgwYQKffPIJERHFy+euWrWKjz/+GJvNxqOPPsrDD7s/VNa5c2c6d+5c1eFVqfjkXLdRsWv16RTBpn3x2OwqGgUmD2tDHZMRh0Plna/3seVg8UM8HZuH8OoT3THqZVGFijKf2OWy7SjIpeDCUXyvmvbhKCokK2bVdfvxjmxz3f2i5mnaoA6PDm/D4p9PUmR10L9zJIO6ln0708/HIJWBqljukc2krvxXyfbhTc4ku5iK+cQut0S7NIaQCEJH/q4KohRCVJSiKITcO4XgAZNAUWrsolFVmmgfOnSImTNncv78eWdbcnIy8+bNY+nSpRgMBiZMmEC3bt1o1qxZpV//6NFr5/9UnSyzjd1xeVhtKp2a+VI/0IDF6sCoV7BYS0+2FQVa1rXQ44Fw0rKtBPvr0Wlz2LdvH3GXCthysGTe4KFTafxn6Ta6NDNV10u64/ldjHP7HzzuchqO3H3Obd9DyzHkpLmdqwKq3htLo66cMOtg3z63Y0TN1qQOvDAmDIeqYtA5OHjwwA33kZJlxWyx07CuEa1UIblpSpGZOps+4uqfoL2U39uk3CIuyO+qELc/ayGGxOMoDjtF4W1QDTX3geQKJdp2u51Fixaxbds2tFot/fv3Z9y4ceWet3jxYmbNmsVLL5WUVduxYwfdu3cnIKD41uzgwYNZu3Yt06dPv8mXULbqWoI9r8DKM3M3kJVbvCDKoXMF/PO5vjQK80fvl8TchXuxWIuXU28eWYezl3KwO1RUFc5meDNkQEe3PpMKzwGuD+h4+9Wlc2cZXa0Iy+XTXMpxrTZijGhFVL+hzm1VVTm3fq77yRotdYc8WVzJQIib9P7ig6yPKa54ER7iy9u/60WQv1c5Z4nSZG5fSmYpde1920RjPr4DUDGEN8dXW4g9dgWm1tH4dx5c/YEKIcrlsBSQ8Nkfnau4+sXvocET/0DnF+jhyG7OlSXYy1Kh8n5vvvkma9euZeDAgfTt25clS5Ywb968cs+bM2cOXbq4LmGckpJC3bolcxhDQ0NJTi5/iezb2e5jic4kG6DI5uCXvfEAxF7IcCbZAKfis12mk/xv53le/nAredcssd61TT0MV00T0WgUerYPr6JXUPPYShntMgQ3cNlWFAWdv+uDbWi0+EXdh6ldH4DiVeS2LyXh38+T9N1bFKVcqLKYRc2QkpHPpn3xrI8p+X/lcpqZlb9WKxE3znI5zq3Nu0lH6t3/PJHTP6LBk//EYc7GfGwrhReOkbZ2ATkHfvJApEKI8phP7nIm2QB2cxbZe9a4HGNJPk/mlsXkHv7FbbXXO02FRrS3b9/OmjVr0OuLVzsbNWoUo0aN4rnnnrvhCzocDmfZJSgeVbx6+05k8ja4t/kUt5W24uO1jp3N4NHX1/Hy5K50bRMGQGigD28905Nlm85gtTkY3qsJzSLdH9ASpfNu0gGNtx+OgpLFgHzbuC96FHLfVJKX/7NkVTmHndx9/0NRHYQMnUbO3rVkbvoagKKUCxReisO3bW90pkD8O90rq0PWItsOXWLDnngC/YyMH9ic8BD3aVyfrTzKii1nUEuZLZaRU/7fAuEu/+xB8uP2uLQpXibqjX0BAH2dUAovxWHLTnE5JvfIZuy5maDR4Ndx4B07WiZEbZCzZw3+ne9DXyeUgnOHSVz0JjiKBynzju+g/oQ/ezjCm1ehEe2goCDs9pJRWUVR8Pe/uSoYYWFhpKamOrdTU1MJDQ29qb5uF51bhdKhWYhzu0FdX+7rVlxGrk+U6yiqr1fp322KrA4+WXrYZWS7ZaMgXn60Ky883Ik2jYOqIPKaS2P0IXzSG5ja98W7SUfqjn4Wn6buU3R8mncm8ql/ubWbT8bgKCok/9Rel3ZHQS65e38kc9PXXP5qJqrD7nauqHl2HrnM3K/2sjc2mZ92X+T5d7dw+JTrXZMLiTks31x6kq0o0K9z8cOSp+OzWLfrApfT8twPFG6uTbIBgno/iOaqRWZ0/nVdFqwBsFw+RebW78jc/C2XPn8Re4H7CrxCiOrn27I7Gh/XHFK1FZF3eDNA8ej2VZ+tBWf2V2jhqdtVhUa0W7VqxcSJExk7dixarZYff/yRwMBAvvjiCwCmTJlS4Qv27NmT999/n4yMDLy9vVm/fj1vvPHGzUV/m9BqNbzxVE+OnEnDYrUT1SIUva74j37nVvWYOeUeft5zkTomI2P7N2PH4ct8uSbWrZ+UzAJ+8+r/iGpRl5cmd8XHqOPjpYf5KeYCWo3C6L53MXmYzNGuKH1IBBq9F3kXjlJw4SiWhJMED57qdgdF6xeI1i8Ie27Jan52cxYX3nsCY/2yH9K1piVQeOEY3k1kFc+absuBSy7b5gIrf/5kO2P7NWPKyLZcTs3j9c92lXE2GHRaGoT48sPGU3y55jhQPB1sxqQu9OwgU8KuRx9U363NeE0JMJ1fIEH9HyZj07fgsKHx8XdZbt2el4k5dif+na6/4qsQouppjN4E9ZtI2o+fuLQr2l9TUsV9DFjR3LYLmZerQom2xWKhZcuWHDt2DMBZpi8uzn3eXHnq1avHc889x+TJk7FarYwfP54OHe78REWjUdzq52bkFLJ621lyzEWM7dec1k2KR6XHD2hB4/p1+OD7g6VOLTkQl8p3P52kRWQga3eeB4rrbn+/4RRRLUJpf9XouShbftxucvavc27n7FuLd9O7Xcr7ASiKhrrDniZlxb9cFqtRiwopjI/FEHYXRUlnQKN1+ZYNoBhca3KLmikkoPT3eeXWMzwwsDnzlx0hJbOgzPMtVju//ftGiqwlNfMdDpVv15+URLscflH3kn/mAAVnD4KioU7XYXg1aOF2XECPMfh16I8tN4OCC0fI+Nm1Nr6id5/iJ4TwDFO7PmTv+RHrr0uua/2CMXXoD0BA91EUnDngnJvt26oH+qA79++koqql3ei8s115ArS6qo6Uxmqz88zcjSRn5APFifgfH+5MzNEkLqXl0b1tGKP63MWyTafZczyJ0wnZLudrNQpajeKymA3Ak6PbMapPzVs5qTLZctIouHCMwovHyT34s8s+Y4MWhAx5EmNYU8yn92M+vg1dnbr4R92HxsePxP++huXSSZdz6j30Csa6DbEXmkn8ZrZzpMyneVfCHpRFbGqDzJxC/vzJduKTXad7KAp8+ZfB/GHeJjJyLGWcXbb6wb4seGVQZYVZo1mzklF0RnSm8p9VsefncumLl7BlFc/b1tdtSIMpf0WjL/48UFUVa/oldKZAlykoQojq47BaMJ+MQbVZ8W3VHe1Vv4vWzCTMcXvQ1wnFp0WX27rGdnk5Z4US7ZiYGBYsWEB2tmsy+MMPP1RepJXodki098YmM/tT11vJvl46zIUlJaoeGdKKh+5ticVq5/E31pNzzXLs19Io8K8/9qdRmKwSWZa0DV+Rs2vF9Q/SaDE2aIkl/nhJk28AkU//i4wNX5J7cIPL4brAMCKfehdFq8deaKbg9H40vv54N+5wxz/IKyrO4VD5Zv0Jvvup5E5ekL8XWXkWvI06zAUlT8Y3Dffn7OWc0rpx8cSodozpK1+cq4LDUoA5LgZFo8OnRVdnkm1JOk/S4jnYczNQdAaC750iU0qEEDetvJyzQlNHZs6cyaRJk2jYsOyV0YSrzFIqDFydZAPsOprIQ/e2xKjXMmtqd75YfYxjZ9PdHqbSaBQah/nzwKDmkmRfR/7Zg+Un2QAOu0uSDeAwZ5Eftxtbbqbb4bbMJArOHcanWWe0Xr6Y2vWurJDFHeDAyRTik3OJalmXe9qEUTfAm4tJuZyKzyL2fPG8fnOBFaNBi7+vgWYRAUwd3Y7jZ9P5bOUx8i02iqyuU478fQyEBnlTL8jHEy+pVtAYvfFr38+lrSg1nktfzIBfa3KrtiLS1n+OIewuvMLlC48QovJVKNEODg5m8uTJVR1LjbF882k+W3ms3OMa1C0pDdeiYSBv/7YXMz7YyvFzGS7HtWoUyNzpktyVJ7ucpdTLozF4ozGWPhdXY5SEqDb69/IjrNx61q09ukM4udfUvrcU2Xn7xV7O5Dm0s4+z0simffF8vuoY2XkWFI1CTn4ROflFvP3lbuY8HS3PXVSCorQELEln8Y5sja5O3VKPyY5Z6UyynexWLn/xEt7NOhP2wIzb+ha1EDWZqjpQSnkQ8k5XoVc0YMAAvv76ay5evMjly5ed/wl3DofKop/Kf0g0sp6JR4a2cmufNqY9/r4lD+34+xqYNqZ9pcZYY2kq9L0RRWcAvevtHV1IBD7NOxPQ434wuK7e531XFF6RrSstTHFnyMsvYs32c6Xu2374MqHXjEbXDfQu86HJfp0j+XLWYJ6dEIXdXnLLSlWL63OLW5O950cS5j9L6or3uPjR7zCfiCn1OIe17Hn0Baf3kbP3f1UVohCiDHZzNomL3uTcWw8SP/9ZChNOeDqkSlWhzCQzM5N//vOfeHuXfIgoisL+/furLLA7lQpYr3mA8VpeBi2tGwe5JNRX3BURwFevDeFiUg6qqtKofh20GpkHXBF1Og+m4HRJ3WtFb8TUvh+5B9YXZzQaDT7NuxIy7BnsuemkrvmYosQzgIrisGPLSccY1oRGv/uYvJMx2HPS8YpsjXcT+aJTG9kdKtd7hKVTy1C8DTr2HE8iMsyP347reN3fVUVRqB/svsiNTB+5NarDTuaWRSUNDjsZW77Ft1U3t2P9o+51Ltlemrzj26lzz4gqilQIUZr0jV9RcOYAUFw2N3npOzSc/kmNubtUoUT7l19+Ydu2bYSEyO3N8mg1CsOjm7Bs02lnm16ncUm+C4vsrI+5iN2h8ocJnUrto0l4nWqJtybxadaJ8MlzyIvdjs6/Lr4tuhI//w84J707HGh966Dz8UOj1WFNi+fKB641I5GMzd9Sb8xzaH38qRN1r+deiLgt1DEZ6dc5ko174932eRt19Lm7Afd1a8Te48l4GbXcFVF+NYzWTYIY3L0R62MuoKrQunEQQ3o0roLoaxGHA0eR60i1ozC/1EO9G7cn/LG3yDu2DVtuBvkndrrs1/rK6rtCVDfLJddZAPbcDGy56ejr3NmLGV5R4TnaQUGyMmFFTRnRhuaRAcRdzKT9XSGEBvnww8Y4Nu93vUW8/0TJksHxybkE+hmdS7eLm+MV2QqvyFY4LPmk/m++23zM3IMb0Hr5YerQF/Wa28i2jMTqDFXcAf7voSiiWoZyMSmHQD8jx85mYNBruL9fM1Tgt3/bSFpWcf3stk2DmfN0T7Ta68/Im/7A3TwwsAUFFhuN68vDzTfCHLeHnL0/gkZLQPfReDduj6LT49ehn0spT43eSO6hjfh1HODWh1eDFng1aIHqsHPxw1PYc35d4VPRENBjdHW9FCHEr7wi22BNL5mOrKsTis6/5gzsVijRbtGiBRMnTqR///4YDCWJ4I2sCFmbKIpC77sb0PvukuXXX5jYmdjzmaRklIy0NKrvT0ZOIa/9eyfnLueg12l4bEQbRvWWp99vVcqqD8g/Wco8TYedrB1LsJndq4t4Ne6AJfk8hpCIkhWqRK2m1Sj06xTh3B551e/mt+tOOJNsgGNn09l/MoWubcLK7Vemi9w4y+XTJP/wN1CL7w4WnD9C5FPvoQ8MI2ToNAxhTcnc9A2OwjysGZdJXf0hqs2Kf+fBpfanaLREPPEPcg78hCM/G1O7Phjry99eIapb0MDJOIoKyD+9D0NIJCFDptWohyIrlE0UFhbSpEkTzp8/X8Xh1FyKovCHCVH88+t9pGUX0jDMj6fub893P53k3K/1dq02B1+sOkbvuxsQ6OdVTo+iLJakc+Sf3H3dY/KObHFry969muydy9D4BlD/N69irNfYue/KXF1bTir2vCyM9e+qMfPHxM3Jt9jc2gpKabtWdl7xnZQ6Js/U+L9TmeP2OJNsAOw28k/vw6thW8yxO7Ckxrus7AqQs389fp3uLfNDW+vjR2D02KoMWwhRDq2XL/Xuf97TYVSZCiXab7/9dlXHUWNcSMrh4yWHuZCYQ6dWoTwzriPxSbls2HsRf18Df/+/Pmg1CoH+xYn05TSzy/k2u0pyRr4k2jdBtVtJWjyXgrMHyj/42hJfAL8u9+owZ5Gy4l0ip70LQMaW78iOWYlqt4HdDqjog+pT/+HZ6PyDK/EViNuR3aGy8MfjbNx7Ea1GQ8Mwf/p3jmDQPQ35ccd5Z43suoHebqPZZy9l8/Oei3gZtAzt0ZjFG06xPuYCqCr9u0Ty+wej5GHnCtIHud8pyDm4gfT1n5d5TlHKeRIWPEf9h19DZwqsyvCEEKJUFUq0Dxw4wIIFC8jPz0dVVRwOBwkJCWzatKmKw7uzqKrK2//Zw6XU4lGVLQcukV9oY//JFBwO1dn28YwBmAus7DyS6FYOTFHAZr1+1RJRurzYnaUm2Yq3H9iK3OZko9WB3QaKxnWkjOInn1WHnYJzh8nautitT2tGIlk7lhIy5MlKfQ3i9rN2xzmW/FLycHNadiH7T6bw8JBW/PMPfdiwJx5vg5YhPRrjbSz5k3o+MYfn39vsLOf3445zmAtKvuBt2BNPl9b16NWxZIqZKJupbS/MJ3eTH7cbUPBq1JbCC0fLPc+alkB2zCqCB5asBVGUGk/a2gUUpVzAu0lHQoZOQ+vtd51ehBDi5lRoFDAomwAAIABJREFUEszMmTOJiooiLy+PkSNHYjKZuO8+WbL2Wpm5FmeSfcWxs+nOJBsgOSOfbYcu87u/b+S97w7w8+6LXD2eparw33U1q4ZkdbFlp7m1+bbtQ+Qz72Nq19f9BHtx0mNq2xu0etd9qopqtVB4qeya6LYc9+uJmufQ6dLf53U7z9MozJ/HR7blN4NbOe9SXfHdTyddamZfnWRfEZ+c59YmSqdo9YQ9MIPI331Ew99/gm9L9/J9ZbFmJbtsJy/9B4UXj+MoNGOO3UH6T/+p5GjFnUxV1XLL9ApRURVKtBVFYdq0adxzzz00bdqUd999l+3bt1d1bHecOiYjdQNdR6iD/N2ngBw7m056dskS7ddWdM0oZfn27DwLSelmt3ZRwrdVt+JR6quYj23h4r+eLK6lXYb8M/vdqhN43xWFxuiDd8M2ZZ5natvr1gIWd4RmZZTt8/XWl9quqip7jidx/Fz6dftVFOjSumaUr6pO+oB66PxD8Gneufhu1LV0RpRrVnK9uqKB3ZyNNS3BZX9FRsZFzaGqZdfI330sicff/IlxL6/izc9jyC+0VnN0oqapUKLt6+sLQMOGDTl16hReXl5oNDXnidDKotUovPhwFxrULf55dWgWwgsTOxNSpyTZ7tG+frkPQZkLrFxOyyPuYiYWq52F/8/eeQbGUV1/+5nZvqveJatacu/dxr1g4wY2vYMJvfMnJLyBgFMdegsJAQIJPRSDqcYY4957k2TZ6r237WXeD2uvtNpVcZFlSfN80ty5d3RW2pk5995zfueHdG75w4/c8de1PPHPLfKN3wrq8D7E3fAHDAMneb9oHW3/vZRBEZhPNBVfUkUmEL3kEcCtu6tNGuozJmzOre6VcJkez2XTU5k2sg9Cs60nhShwwyX+q4W++eUh/vjvHVTXt16FMCZcz29vGke/BDlu+ExRhUQTe8PTqMLiQKlG0BjQD5hI4t2voA6P8+prr8jHXu12tkV9IMoQ7wmOJq7febNbpmv55KdMrnnie6598nv+91Om1zmTxc7zH+6hstaMJMGOI6V8vCazlSvJyHSMDsVoDx8+nIcffpiHHnqIu+66i9zcXJRKWf7MH4NSwnjj8TnYHU5USrcqxau/nsmbXx2iosbMkL7hjBkQxbebszFZ3FvJYUFar1XseqONu1b8DIBeq/T0Azh4vJLvtuRw1ez+5/FTdR9O6Whn/+2ajg1QKLFVl4C96e9vryjAXl2CJi4Nl9WM01jrM0wdmXiuTJa5wNGoFDx201geunYUJVVGcorrGZIS7rN7BdBotvPDttx2r3njJYOYPCKu3X4yrSNJEtWbPsNe49a/NwyaROSi+xBEBQpDiwmMICKoT06+XS6Cxi6gbsc3OBuq0CYNIfxiWaq2N7Avs5wPVzeFZn6wOoOBSWGM6B8JQGF5o49yUFaB7/NfRuZ06JC3/Lvf/Y4DBw6QkpLCE088wZYtW3jhhRc627ZuzSknG+Ctrw6xfo97q/JIdhUV01J5+ZEZrNtdgEatICE6kD+/40fzGbyc7FO0jAOX8cXQfzzG9K3td3Q6PLHaXs3GOgDKvnjWZ5tZYQhGmzDwnNgp031QqxQkxQSRFNNGkRlJ8gkFiwzVYbc7qW20AZAcG8TEYbGdZ2gvoeBfD+GoaioC1nhoA9rEwQSNnEPolCsx5x1Gsrl1zoMnLEYZEILLZqb4v09iK88FQB2bSsw1TyCqZKnF3sCxfN/6CZn5NR5HOyk2iEC9mgaTzXN+WGrPKZzSHWhM30bt1pXgchI8YTGBw2e6hQmy9+OymND3G4Oo6V51CDrkaAuCQHi4W8ZMkiSCg4OJjIzsVMN6Ck6niw17vR21X/YUcPtlQ7nhkoFkF9Xx/g/pCPjGarfGxKHyS7o9Ihfeg72q2PNCPR0UAWFok4fiqK/CnHPQ65yoNRB7/XL5xSzjw/GCWt5fnY5Bq/K8qAUBbl04mLGDotl+uASVQsGEoTGoVbIG+9lgry7xcrJPYS0+ASPnoIlLI/H+f2LOPYQqNAZNTF8AGg9v8nom2EpOYMzYRuCwGefJcpmuZEhfXzlWm91Jek41g1LC0KgUPHnbeN5adZiyKhNTRsRx9Rw5rOh8YSvPo/zLFz0qYBXf/B1lSBQ1mz7DknsIAEVAKH2W/a1bVY7skKP91FNPAXDLLbfw5JNPMnXqVH73u9/x2muvdapxPQGTxU7LnAu1yh3fbrE5+P2/tlJvtPkZ2cSkYbE4nC4aTXYuHp8oO9odQNTo6fOrZ6nfu4aaTZ/iMtU3nRQEfP4pJ1EEhBJ361/cjrTTgaBQITmbYrw1cf1QR8lhIzLemK0OnnpzKw2mpu/KxKExXDW7P/0T3WEMs8bK35tzhdPiPzFclzLC87NCF0jAoIu8zrcsaONuk5PMewtDUyO447KhfPHLcZxOFyarg/+tPcb/1h5jwUXJ3HPFCAanhPPSw35UqmQ6HVPOAR+p3fq9P3mcbABnYw31e1YTNvPG823eGdMhR/vw4cN8/vnnvPnmmyxdupRHH32Uyy+Xq2l1hMPZVT4r1WaLgxMFtRzJqWrVyY4K1REZqmdQSihzxycRGxHQ+cb2MARRQfDY+RgGTKR63XtYy3LQJQ9HlzyUuu1f47JZCBw1B3tVEeacg2hi+hI26yaUgWGAe/U6ZOpV1Kz/yH09jZ7QaR2M/ZbpUZgsdo7l1xBoULNy3XGyCmsZnhbBskVDMOhUpOdWeznZ4N4JPOVky5xbNLGpKEOicTST7dP0GUDAoIltjjMMnkLNlpWekBJRa8Aw8KI2x8j0LIb3i0ShENlysJhDzaQ7f9iWy5Wz+vvNvZA5P6ijknzaTr2Pm+Oy+SqzXch0yNGWJAlRFNmyZQt333034C7LLtM2FpuD8GBfeT+jxcHDL29oc+yiKX2JCtPz+mf7+fzn46TGB/PErRPkh0AHsBYfx1KUiabPALRxaSgDQ4m67CGvPob+4zt0rdDJV2AYOBF7ZRHapCEotIbOMFnmAuZIdhV//Pd2n3yJkkojVruTR68fQ3xkAKIAzSTzSYj2XwAlv7Qeg05FeLB8L58pgiDQ57ZnqN3yJdayHAKGTSdo+Ix2x6lCouiz7G/U712DIAgEjZmHMlCeDPUW1u7M59VP9/nd0JQk9ztbpuvQp4wgeOKl1O36HiSJwBGzCZl2NcbMHThqSgG3nn7giNldbOnp0SFHOzExkTvuuIPCwkLGjx/Po48+ysCBcjJYW3y8JpPP12Vhdzjb7dvyBR0TrmfqyD7c/9w6jCdf7icK63jv+6M8esOYzjK5R1C3+weqfnzbcxw+91cEj1vgObZWFuCsq0DXdxTCSb02R30lksuJKiTa61qOhmoEUYE6vA/qcLl6X2/lP98e8ZuUDLAnvRyAqDA9yxYP5f0f0rHZnQxLjWDpjDSvvkaznaff3EbmyYSsPpEB/OWei2SH+wywFGTgshoJm3kdQstiU+2gjognYu5tAEgOO9bSHFRhsYhq30URmZ7FJz9lthY1yNDU8FYnxzLnj/DZtxA69WqQJE/SY59b/kr9vp9wWY0EDpvhd+X7QqZDjvaKFSv46aefGDNmDCqVirFjx7JkyRIAcnNzSU5O7kwbux3H8mv46DSqO6qUChQKwfMyL60y8dGaDI+TfYr80oZzamdPpHbz597HWz73ONrFHzztKUwhqDTE3fYcddu+ovHgL4CEvt84oq94FBAoX/UyxvRtIIgEjZ5L+LzbPY65TO+iuqF1Peyk2KYX85LpqcydkIjJ4iAixNd5/m5LjsfJBrd60B/e3s6rj848twb3YCRJouzTFZiO7wFAGRpDn1v+isIQ3O5Yp7EOW2UBmthURLUOS2EGZZ8/i9NYh6jRE7XkEfRpozv7I8h0ITa798KXUiFy8fhEYiMMXDIpuWuMkvFBVHs/PxWGYEKnXNlF1pw9Hao6o9frueyyy4iPjwfguuuuQ6dz/yEeeeSRzrOuG2J3uFi3u+C0xljtTp8VsyPZVZ7CN6cYI1eRaxfJ5f13lE4WqzFlH/Cq/ibZrZR9/gyNB9dxSu/FlLWLxsObaDy80e1kuy9I/Z7VXskYMr2LmaPjvY7VSvdjs09kAHdfPtzrnF6r8utkA34ru+YU18sFqE4DS95hj5MN4KgppW7P6nbHNRzeSN5rd1LywdPkv3YXloJ0qta845HxdFlNVK5+s9PslrkwWDy1r8/xvVeOYOmMNHQauTbIhYwpez+l//srZV88h6XoWFebc1qc9TertTKmvRGj2c5jr22ioKxjK89tiF8QHxnIbZcO4d1vjlBU0cjYgVEkxQSx5UAx4wZHy/JgrRA8bhE1Gz/xHAtKNfn/fMBv0Rlno6+mqrUkG0HtK91X8cO/UEUluytIOmyg1hJzze/QJw45tx9A5oLj+nkDCQnUsP9YBSlxwSyZnorF5iAsSHtauxwXDY/jp535Pu1bDxYzZ3z32grtCiyFmVT9/J5Pu8vc9vNWcjmp+uldj16+y2Kk+IOnffo56iqRnA4Ehexw9VSumt2fpJggDp2opH9iKFNOs2jU7vQyth4sJjbCwMLJKei1pxe2JHNmWEtOUPrJXzyKJKbje0m457VuI/F31k8UeTu9iV/2FPg42SqliN3h8ts/MkRHeY3Zc3zK8Y4M0bFs8WBiwvQM7htOg9HGuj2FfLUxG4CE6ACef3CafJP7IXTqVRizdmErOQHgdrD9ONkA+rSxGI9u9pITMmXvI2rxA9RtW0VzZXNHTaknGQMAm4XS958m5XefyfdAD0cUBRZN6cu8icl8uzmbVz/dx5CUcBZOTkGhaPrfO50udqeXUWe0MWFIDMEB3hO2sYOiCdKrqG+hTrLzaJnsaLeDo7GGko/+gGRvEcYjKghoRwNbcthwmVo44y7f3Bl9v7Gyk90LGD8khvFDYjrc32Sxk5FXQ1F5I29+1bSzuSejnL/dN4XyGhN//3Q/GXk1DEoO4/6rRsqiBecYY8Z2r/e05LBhPLab4LGXdKFVHUd+qpwjXC6JleuP+7SP6BfJ4ROVWGzeD/bQQA0PXzealz7eS0WNGbVKJCJYR3GlkYpaM//59igGnZJ1uwt9rllQ1siGfUXMl2PKfJCcDmwl2e32MwydRtSlD1JYlu1V+dFRU4qoCyBq6SPU7vgGW3FWW78NS95hdMnDzoHlMhc6b6w8yJodeQBsPVhCSZWRu5Y2hY784e3t7DtWAcC7OhXPPTiV+Cjv5KobFwziH597F0GKi5CVbNrDnH3Ax8lWRcQTueg+tHHupFOXw4aoVHv1sRYfp3rDRwhqrUfSryXKkGj0/cbK0p0yPmTkVbP8zW0++VLgDu8sLG/gn18c5OBJmcC9meW8+r99/OluWTLyXKIM9i2QqArpPkUTOxSjLdM+H6xOp6LG90G+L7OcG+YP8mmfNzGJIIOa6jq3TKLN7qK4simGc8eRUtbv9XWyT2GVZYj8IiiUKNu5AQWlmujLHkIQBJ+kCwBBpSVg8GT63PIXFIaQNq+llNVIejROp4tDxyvJKa7zyb1ofpyRW+1xsgEazXa+3Zzjc735k1JYNDmFU5sgfeOCfdRJZHxRhfkW6QoadTHaPv2xluVS8OYj5D5zHUXvPo795M6Ty26l5JM/u530VpxsgIgFdxEx9zZZulPGh/e+S/frZINbLUyvVXE4u8qr/XB2pd/+MmdOwLDpXgtahiFT0KWO6kKLTg95RfsccSDL/83ldEn8b42vAsmaHfls2l+E09V6jLsoCLj8FGbXqESmjpQdvNaImH835V+9iMvcCH6K22sTmiY+op+Xq608D4UhCFGpJmz2zVR8/arf36NJGYHKj5i+TM+gtsHK469vpqjCXU1Qo1LQXK0zpFloiNXuG4pwIKuCH7fnMmdcIgpF05rGXZcP56o5/alrtJIcGySHHnUAbfwAgsYtpH73DyC50PUdQeCoiwGo+PpV7BXu2HdrcRYV379B3A3LsRYd843fVqigWaXXgOGz0CV7J7TKyJyipqH1eiGXTkslLEjLgMRQ0nOrPe39EmRd9nONqNIQe8NybBX5CAqV34n3hcxZO9qytJ+b4WkRHMv3Ta4DaDT7zoir69su+CMIkBYfTEaeb3yx1e6iosYk6++2gr7vCBIffAtHTSmKwHDMOQep2fwZ9vI8lGGxqMJisRQfRxuXhiauH+bs/V7jy1c+j+R0YBg0iYiF96AIDMPZ0PQgRRDRJg4m4uJl5/mTyZxPvtmc7XGywe1MK0QBp0tCpRRZtrgpEXZoagQpcUHkFNd72grLG/n7ZwfIyK3hoWu9V1/CgrSEBcm6zadDxNzbCLloKZLdiirUHWPrspqxled59bMWZuCymlCFxYEgesV2Bo6cjaO2HFtlAbr4QUTMvU2e6Mi0yswxCbz/Q7rneHi/COZPSiYm3EBavHu388FrRvLiR3vJKqilf2KIz70uc+5QRyZ2tQlnhGL58uXL2+tkNBpZsWIF7777LjNnzuSvf/0r48ePR61Wc8klF14wutPppLy8nKioKJTK87NoPzQ1nJ1HSqltQ3O33Wv0DaPeZMPhdK/AVtZZmDIijrJqk8/Kt8PpYtKw08uY7k0IogKFIRhRqUYdmUDwmHmYi7KwFWdhLTlOw4F1aGJScZrqvWT/gJOJUhL2igIQRURdkDsR0iMdKOGoK8eUtZugcQsQBDkCqyeyYW8h2UV1Xm0PXj2SeROTuG3xUNISmsKKREFg2qh4QgI1HMuvwdYsATq3tJ4l01NRKeXvydkiqnUodAGe4+oNH2MtzPTu5HJhPLaLkAmLURiCsRQcBacDbdJQnA3VWPIOIVlN2CrysJZmo+831ie2W6ZnY7U7Kak0EqBTIYqtT7QGp4QRFqRFIQpMHhHHXUuGkRof4jVJDjJomDcxmWvm9OeSSSkEGeTvUm+jPZ+zQ17on//8Z6KioqiqqkKj0dDY2MhTTz3FCy+8cM4N7q4oFaKPykBH+eOdk4iLDMBksfPgC+u9zh3IqiA8REtxhbcGb1JM0Jma2iuxVxdjyd7X1CC5qNv9PbbK1uPgAeo2f4En9KTF6pijvhJbeR6amL7+B8t0a2aMiWftrnyPBGdYkIYpI/ugVft/bBp0Ki6blsq6XQU0mpscdI1KRKmQV03PFKfFSOOhDUh2K+roJEzZB1BoAwgaPRfTiX1+x9grCzEd30vw2PkEDp+Jy2pG1OjIfe4Gr37m7P3kv3on0Zc/Kher6SXsTi/jhQ/30Gi2ExGi48ll40mN95+LIwgCl0xK7lAxm+bhYTIyzemQo52ens6KFSvYsGEDOp2O559/nkWLFnW2bd2KLQeL2d8sGeoUoggu/+p+KESBa+b0Z9SAKIxmOyv+u9OnT4PJToPJ7qW5HRmiY+HklHNpfs9H9P2qu6zmDsh5NdtJkLz/kYJSjTJYLiLUUxmeFskf7pjE2p35BOhVLJ2R1qqT3Zzr5w1gxX93eXahpo7sg1J+CZ8RLruV4ncfx15d7HOu4dB61NEpnvhsH07ObUS1FlGtRZIklCFROGrLvbpJdgtVa/8jO9q9AJdL4vXP9tNodsfpV9aaefvrw6y4d0oXWybTk+mQoy2K3i8Jp9Pp09bb2eBHIUSjUjBucBT9E8OICtUTEqjh07XHqG2wMm5INJdNSyVQ795mWvHfnZworPO5xikkCa6fO4DkuCDGDoqRt6FPE1VIFAHDZtB4aL2nzVqUiaZPfxw1ZbRMmGwNUReIy9yAoNG7lQqabWPL9DxGDYhi1IDTm0xNGBrLozeM4YUP9+B0SazZ4V4Vf/CaURzLr+HzdVlYrA7mX5Qsh3+1gylrt18nG9xSnKEXXY6jtgxbaTbNE5/VUYk+jrMgCEQuvJfyVa/4FKtyNHgrR8j0TKx2J5V13vlRReWNfvseL6ilzmhleFoEKqVcIK6zcZoaEJRKv0pg3Z0OOdrjxo3jueeew2KxsGnTJj788EPGjx/f2bZ1K8KDfRObrHYnmw+UcDSnmrd+dzEqpcjwtAg27i8it7ie6noLgXo1P+3Ia1W1pDkHjlcwdnC07GSfIZGL78fZWIM554CnzVp0jKgrHsNRV0H1+o/cVR9bRSDu5j+7V8h0gYiqMwsVkun5rN9T6JVXsXZXPgsuSuGJf27xaOrvz6rgL/dMZlhq96hu1iW0s6CjDI0h/lfP4WioRnI5MWXuQFDrCBg8GUHhW9BLlzyMxPvfoOyrlzBlbPe0BwyZes5Nl7nw0GmUjOgX4fW+nTjUV8HipY/3euQ7I0N1PHv/VCJCep4DeCEgOeyUf/0KxvTtCEoVIRddTujUq7rarHNKhzy2X//61+j1egIDA3nppZcYMGAAjz/+eGfb1q24clY/YlspPFFdb+VoThXfbs7hP98dJbuojh1HSnn6zW3YHS5+3JHnM0YhCkSH6b3ajmRX88Q/t2Ky2H36y7SPIAiIGr1PuzIglJAJiwmfdZP/gaICdUxfYq5/GnVEPMqgCNnJ7kWYLHZyiuvalOJsia2F3J8kufMtmheukiTYdqjknNnZEzGkjUUd1axqZjOFEF3fEWgTBwOgDAxDFRxJ8PhFBI2cjahuXdFFUCiJuuwhQqddiy51FKEzridi3q867TPIXFg8duNY5k5IIjU+mMtnpPGry4Z6nT9RWOulkV9RY2bVxhPn28xeQ/2+nzCmbwMkJIeNmo2fYC31LjrnshhpOPgLjUe34GpzMezCpEMr2hs2bOC+++7jvvvu87R99dVXLFmypNMM626EB+v4529mkZlfw9qd+fy00ztusLbBys6jpV5tVXUWThTWEhdhIDPPeytz4tAYJKC82uQV1GC2OjicXcX4wR0vIdubaDiwjsb0raiCowiZfAW26hKq1rzj3n6WfIPlBY0ea3k+lavfwlFfiS51NE5TPbaSpiqf6qhEVCHRyCpgvY8Newv5+2f7sdicRIXqeOr2iR1KRF4wOZn9WU05G8PTIhiY7Ku53nIyLeONoFQRPGkpddu/QlCqCZ1+LZa8I5jzDiOo9ViLs9D26Q+Ay2amau17mE/sRR2VRPjFy1rV2xWV6h63aibTMYIDNDxw9chWz9cZfR252sYzVxOTaRtbRYGftnyPyICjsYaid36L82R4lzo6hT63rkBQ+u5YXai06WivW7cOh8PBs88+iyRJSCez8RwOB6+99prsaLdAoRAZnBKOyWz3cbR3Hi0jPjLAK2FSqRCICTdw+2XD2JNRTv3JGzwyREd5jZmsAl8NbYD4SDku2B/1+9dS+d0/ATADpux9OGoraCv+WrKaqPrhDc+x+cRed1GLZthKc7CV5mDM3EGfZc+giZVVRnoDdoeTN1Ye9KxCl9eY+c+3R3n69ontjm2pEtRosTOkbzjzJiaxZkcekgTDUiOYNyGplSvIAJiO76Fi1cue4/IvXzpZiMp9T5uydpNwz6uogqOo/vl9GvatAdyKQI76CuLveKkrzJbpxgxLDScqTE95tQlwb6LMGdu2frPF6uDrTdnkFNcxekAUc8YnyvrsHUSfOspz3wIIChW6pKYqkA0H1nmcbABbWQ7GrN0EDJqErTwPY9YeVOGxGPqPRxAvzFj6Nh3t9PR0tm/fTlVVFe+9917TIKWSW2+9tbNt67aE+4nl0qoVXH1xfzLza8gqqEWjVrBs0RBCAt0hCB/+cT57MspQqxSkxAZx3e9/8HvtpNgg4mRH2y/GI5u9jluqC3QYZyuhOZKLxqObQRRRhUQjauSYvZ5Mg8nuUSc4RUmlsZXe3mw+UOR1nF1YR0mlkfuvGsnVc/pjtTlJiA48Z7b2VBqPbvE69qn06LTTcGAdYdOuxdQs9wLAVp6Po6EGZaBvpT5HfRWCWovTWIutIh9dwmAUhuBzbr9M90OlVPDs/VNYtTGbukYrs8YkMKJ/ZJtjnv9wDzuOuHesNx8opqbBytVz+p8Pc7s9hgHjCZ93Bw37fkRQ6wmdejXKoHDPeclPqIjksGI6vofST//m2akOGDqNqMseOm92nw5tOtqnwkU+/PBDbrjhhra6ypzE6XThdEqMGxzNrqNlAOg0CqLD9BSUNXDvFSMQBGgw2VArFby16hBBejWXTEpmzMBowC1BFBGio7LW7LmuKMDF4xO57dKhfn+vDCia3ZxufMuvny31+9dSt30VglpL5MJ7CRg8+ZxeX+bCISxI61Ptcdxg9z2aW1LP26sOUVRhZMKQGKLD9HzxSxYOh4vLpqUSGarneDMVIY1aQXCAW2EoKlQOF+koysCW97QvtZs+QxUchToqyV1Y6iSKgFAUBu8wH5fNQtkXz2PO3ueliy8o1cRc+wS6JPn5KuMOBb2tWeVXl0tiT0YZJZVGxg6OJi6iabGr0WTzCQv9eVe+7GifBsFjLyF4rP/ih4HDZ1K363skq3uHQRkUgaH/BEo/f8YrHLTx8CbCZt7o5aRfKHQoRvuqq67ip59+wmh0r+Y4nU7y8/N55JFHOtW47kZBWQNPv7WNihozaqXIZdP6YrO7WL09lw9WZ3j6NdfEPsUvewr4+2OzUCpEjhfWMmZgJD9ubwo/cUmw91gFd8kyQ60SOuUqzCf24zS6Q25EfRAuU+uSiacQtQZclpMrlYKALmWk+0UMCEoNkuNUfJ6AdLKfZLNQufotDAPG+1U3kOn+VNaaqWtR6dVkceB0SfzpnR2ereXvtuR49floTSZ3Lx1GVn4NlXUWlAqBZYuGoNfK35PTJXj8IoxZuz1a2e57ut6nX/UvHxC37G846iqxlZ5AERhG5OL7fbaS63f/4Lm3m7+kJYeNmg2foLv5z533YWS6La9+uo+fd7ljid/99gjLb5/kWeVWqxRo1UrMVoen/5kWr+vN2CoKqPzxLWzl+ehTRxEx73ZErQHVSWWhhoPrEVVqAkfM7na7yR1ytB955BEKCgqoqKhg8ODBHDhwQJb388N/vztKRY17FdpcPAq9AAAgAElEQVTmcLFmRx4KUfBxqlseAxRVGNmTUUZGrltn1x8VNWZ+3pXHJZPkYjX+kJwOnJYmTVR/TnbY3NsRRIGAwZNxmuqRrGbUsalYy3KxFmYQMHQaCq0BW2Uh9ppSLLmHaTyy6aTz7v2Pc5kbcFlM8pZzD+Tg8QqWv7kdu9M7gfZAVgUllY0eJ7s1KussvPXExZworCU6zOAJEZM5PRSGYOLveAFr8XEU+iBsZbmUrXzBJ7HZaTGiDIog/lfP4jTVI2oNIAg4GqpRBIR64mVtVUX+fo37Gi3DUmRkcE+4m6uQOJwSK9cf93K0b1kwiDe/OoRLcoeJ3rRgUFeZ2y2RJImyL57FXuXWzG88vBFBqSZy4T0AqEJjCJt+rdeYkAmLKc09zKn3smHIlAtyNRtOozLkmjVrWL58OcuWLcPlcrF8+fJONq37UV7j/fI1W52Ip5EP8eJHe7DaWikjeZKCVsT1ZcCYuROcjlbPq6OSCBk333Os0DXFyGpjUtDGNE1g1BHx1Gz85KTskH+0CYNkJ7uH8r+fjvk42QB9+wQTGaonQKfyid9uzuCUMJQKkQFJvkojMqeHIIgogyMR1VoMAycSf/sLVK55G0veEU+fwOGzEAS3Wq1CH4Sl6BjlX76Io64CVVgsUZf/Gk10MoZ+Y2k8+Ivf3xM4cvZ5+Twy3QunS/JZHHO0eDYsnNKXsYNjyCutZ3ByGAEnC9HJdAxnY43HyT6FOe9wm2MEpfpk6e2Tkql+VMUuFDrkaEdFRaFUKklOTubYsWPMnz+fhgZ59t+SycPjvOI5+yWEoFaKHMmp7tB4k8XZbp+542WVgtZQBrdd+MNWXYLLau7QtpPLYcPYrKCFz++KSCDq8l+fto0y3QOLzXfClhIXxO2XDkWjUvDI9aN5/bP9VNdbfTIBYiMMjJPlN88JLquZspUvYM7eh6DSEDr9OkImLCb2huU0HFiHJT8dTVwaQaPneo2r+PZ1HHVuhSd7dQmVq9+kzy1/xTBwIhHz76Jh/1oEjR5VeB8kmwV96ki5aI2MX6LD9EwaFuvRvBcFuHSqr/JUdJhelus8QxSGYBRBETjrmwoJaWJT2xxTu/3rJicbMB7dgn3mDahCojvNzjOlQ462Xq/nm2++YeDAgXz66af07dsXk6ntrdPeyFWz+6NWKdh5tJSEqECumzsAg07Fiv/u4kh2FaIoEB9lICRAi9nqYEBSKJ/97D9MpCUKUeDXN4wmKbZ9Dd/eSsCgSTQe3oj5xD7/HRw2HHUVqKPalmoCqFrzrv8YH0A0hBB3w3KUASFnY67MBcz8SSkcy2/6Ho0dFO0l6zd+cAxjfj+PT9dm8tGPmV5j7XbfCfOP2/P47OdjOF0SS6anctm0tl8iMm7qdn7riamW7Faqf34PQ/9xqEJjCBo5h6CRc3zGSC4n9spCrzZbeVO+S9DouT6OuYxMW/zmprFs3FdIcaU7+blfgq+SjcyZI4gKoi57yD1BrilFmziE8Dm3tj3I3/u5lXd2V9MhR/upp57i008/5bHHHuPzzz/npptukhMh/SCKAktnpLF0RppXe1u6u8UVRrYcLPZ7rl9CCGkJIYQHa1lwUQqB8nZUmwgKFbHXPom1LJfiD57yJC42x2n2TaTyR+PhjT5tIVOvQhPbD33aKM82tUzPZM74RMKCtew6Ukp8dCBzJ/hOzhSiQFWdxae95WQ4q6CGv3+233P89qrDJMUEMrJ/1Lk3vIdhq/CuR4Dkwl5ZhCq09R0DQVSgSxmBuZncnz619QIlMjLtoVSIzGpHS1vm7NAlDibx3tdx2a0dqrwcPH6h+x4/GTKiPzkBvxDpkKP9xRdf8Jvf/AaAl19+uZ3evROTxc7HazLJKqhlSN9wIkN0bNpfRGiglmsu7u/RzJUkie+35rLtUDEx4QZuuGQA4cFaDmRVkFfqHY6jUorce8WIrvg43RpNdDLhs2+h8rt/+JyTbB2r8KUMDHNXkzyJIiiSsGnXtjFCpqcxekAUowe4nWGTxc77P2RwLL+GxOhAjBY79Y024iINXmMEAe5aOtyr7Uh2FS3ZeaRUdrQ7gD5tNMb0rZ5jQaNHmzCw3XGRlz5I1dp3sRZloU0c3P7qmIxMMxrNdvZmlBEerGNI3wszwa6n0hEnG9yFbvr86jlMmTtRhkZf0FK7HXK0169fz6OPPtrZtnRrXv5knyeGq+WL9eDxCt5+4mLUKgXfbs7hza8OAXAgq5KjOdW8/thMXBLctWItZc3UDCYMuTBnZ92BoJGzEXUBlH/xvGfGqwyNRpcyvJ2RbsLn3ErZly8g2a0ISjURc2/rTHNlLnBau7/3Z1UwbVQfMnKr0WtV3HjJQGIjvJ1vf9vMO4+WcefSzrW5JxA4fCZOUwMNB39BYQgmbPq1bkWRdlAGhBC9RN51lTl9Csoa+O3fN9NgchdKmTE6nkdvGNPFVsn4QxOdjCY6uavNaJcOOdrx8fHcdtttjB49GoOh6SG3bNmyTjOsO+F0uthxuKTV8zUNVo7mVDGyf5RPxbiCsgbyShtIjg3iD3dO4v0f0imtMnLRsDgWTu7LsfwaosP0si7naSK5nGgiE4m75c9UrX0fW8lxHPXVVG/8hLCZN7ZbHlffbwyJD7yJrTQbdXQKCr1cxa+34nC62N7G/e1wuvj3k63H/A7pG05ooIaaZprcZdUmSquMxIS37zT2dkImXkrIxEvPybWsJdlUfP8G9op8dKmjiFx4r3xvy3jx5frjHicbYP3eQq6c3Y+kGDk/SubM6JCjHRLiTvoqKmpdg7Q3o1CIRIToKK8x+z0vCBB1Mhs5KkzP0WYqJEqFSOhJjd0+kQE8fvM4APJK6rlzxVqq6y2olCJ3Xz6cuRNkxZGOYC0+TukXz+Gsr0TUBuBqpq1dt+0rEBVoIhJQx6QgOWzYKgvRJQ1DEEVMOQdQhcai7dMPhS6gwyvgMj2XRlPrMn4A0WHtO8uDUsLYerDJWddpFITIk+fziiS5KFv5HI7acgBMx3ZSpdUTtfiBLrZM5kLCZPFVHDL7aZM5P0iSRP3u72k8ugVlcCRh065BFRbX1WadFh1ytFesWNHquf/7v//jxRdfPGcGdVfuvnw4z32wB7PVgUGnIkivpqTKiCgKXDW7n6dk6/VzB5KeU01ZtQmlQuCWhYP9rlb/9/ujVNe7E63sDhdvrzrMtFF90Ko79C/r1VT++LZHJqi5k32Kui1f+A4SFQiiiORwO1XBExa3GtfpNNYhqLUdjiWT6d5s3Ffok8x+StIvOTaIy1skP/vj5gWDyS6qo7TKhFql4M4lw9Bq5Hv5XOCyW3Ga6lAYQhAQEJS+FTjtdeVY8tM9TvYpLAUZPn1lejdzJyax7VAxrpP3fEpcEP0Tm8K/nC6JmnoLYUFaxNMplCFzRtTv+ZGqNe8AYC3MxFqYScK9r/tUfb2QOesnfU5OTvudegHjBsfw36fnUVjeQGJMEGqlyPdbc/hlTyEHsyrZElvM5BFxxEYY+NfjszlRVEdkqI7QQK3f67WsPGe2Omgw2mVHuwPY26j+1iouJ1IzTc66nd8RPHGJl4Sf09xI2crnseQeQtDoCZ9zi195MZmehVLpqzBz84JBjB4YTUpcULthSODerXrj8Tnkl9Z7Ct7InD0NB9ZRueYdJNvJ3USlmtBJSwmddrWnT93Ob6la+193roYgeEmAaeMHnG+TZS5wRg+I4q/3TmHjvkLCg3UsuCjZ41Bn5FXz7Pu7qagxExtu4PFbxtG3j1y0rDMxZXrXs3DUVWAtyUbbp18XWXT6yBpl5xCdRkm/hFA0KgWF5Y289dVhMvNqSM+t5pn3d5GZ5w4ZUShE+ieGtupkA0wZ2cfreGBSKJGh7RdakQF9v7FnfxHJhWT3lm6r3foFllx3IqtkNVH5w1s4GmvP/nfJXNBMHxXvleAYG2Fg/kUp9O0T3CEn+xQKUSAlLlh2ss8RTouRytVvNTnZAA4bNZv+hzn/KAAum5nq9R81VY2TJAS1FgQRfdoYWY1Exi9D+oZzzxUjuHpOf68qj6/+bz8VJ0NES6qM/OOLA61dQuYcoQyN9W4QlSiDI3HUV1K28gUK3niAyh/fxmXzlVq9UJCXRzuJPRnlOF1NKyeSBLuOlrVakrmu0YpKKaLXul/CV8/uj1atYNfRMhKiA7n2YnnlpaNEXHInLqsZU9auM76GqAvEWpzlpctpKy/w7uRyYK8ulgvX9HAMOhWv/N8Mth1yyz1OGhaHTg77OO/Ya0qp3fol5txDSDYLqugkJIfNb19bWQ66xMG4rGYku7ekpyokivg7XjofJsv0IFwuicJybwne/NKO1WWQOXNCp1yJpTADe0U+gkJF2KwbUQaEUPTu41iL3QX/7FXFSE4nkQvu6mJr/SO/LTqJ+KgA37ZmWtpGi4MAnQqb3ckLH+1h26ESVAqRK2f357q5AxBFgSXT01gyvf34TxlvRI0Oh6nurK7hMjdQ/tXLSE4HgcNnAqBPG+WpUgcg6oPaLRMr0zPQaZRnXLBCkiQ+XJ3Bj9vzMOhU3LRgEJOHd69knq7GaTFS9J//h8vU5Ng4cw4iKFWevIomBHRJQwG3Hr4ueRjmkztRAAHDZpwHi2V6GqIoMKp/FHszm+L8Rw+M5uDxCr7bkoNSIbJ0ehppCfLCy7lEGRRO/B0vYq8sRBEQgkIXiNPc4HGyT2E6sbeLLGwf2dHuJMYMjGL+pGR+3J6LBEwbGc/UEXEcy6/h+Q/3UFJppG+fYMYNivaoEdgcLj76MYMJQ2LkuK+zwFFfha3oWNudBBFRq8dl9k2WbE7j4Y0eRzto7HxcFiONRzajDAonbMYNckKkTLv8vKuA/611fx9rG6089/5u+v1uDlGh+i62rPtgOr7Hy8k+heSwo+8/HmvxcSSHDdEQTNiUq1BHNSk0RV/xGLU7vsZWUYA+bQxBI2efT9NlehCPXDeaf399mMz8Gob2DWfW2ASefGOrZ/d655FS3nh8NuHBcpjnuUQQBNSRCZ5jUaNHERiGs6FJwU0dkeBv6AXBWTva0gVaW76rEQSBe68cwQ2XDMTlkggNcsdjv/jRXkoq3aXBs4vqqGvwrVSYX1ovO9pngagLAJUG7K1XgQwYMpXweb8i/+VfITlbl29TBDRlmwuCSOjUqwmdenWr/WVkWtKygJXTJZGRWy072qeBQu9fw1gdlUTMVb9tc6yoNRA2/brOMEumlxESqPEqXvPe90e9QkQtNic7jpSy4KKUrjCv1yCICiIX3U/F16/iNNaiiognfO6FW9elw452UVERdXV1Xo71kCFDeOklOdatLZpL91lsDooqvFdQjS30OdVKkeH9Is+LbT0VUaUhYu5tVH7/Bj66bICoDSB02tUotAZCp19L9S8fnkyWOiXa5kYREEbI5CvPn+EyPZK0hGDW7mrZJm8vnw66lOHo08ZgOr7H06YIjiJy0X1daJVMbycyxHflOsJPm8y5R993BIkP/AunsRZFYPhpJaafbzrkaL/yyiu88847hIeHe9oEQeDnn38mJUWeuXUUrVrJwKRQMvJqPG3jBkczNDWcH7bmYtCpuHJWP9buzCc9t5ohfcO5bFoqKj/yYjJtEzRyDoZ+4zAXZKDQGdDEpmE6vhcUCgxpYxAU7q9+yKQlGAZNwl5dijomBUdVEZIggsOGNn6gX01eGZnToeXjXyEKBDZTMpBpH0EQibnmd1gKM3HZzKgjE1EEhGItzKTw37/BUVuGYeBEwufeJodzyZw3Zo5NYMO+Is+u1aRhsYwZGN3FVvUeBIUSZVBEV5vRLh1ytFetWsWaNWuIjpa/QGfLYzeO5V9fHuJ4YQ3D0yK5c+kwAvVqz1bTK5/sY+2ufAB2p5dRXm3i3itHdKXJ3RaFIZiAgRMAsFUVU7frO6xFx9AmDiZy8X2ogqMAENU6BIUSe1UxgiCg7dMPQfCe3DjNjXI5dpkzYuuhUq9jp0ti15FSZo07s+TK3kxz3WuXw0bp5894Yrcb9q9FoQ8ibOYNXmPstWVITifqcDkBVebcolUr+dt9UzheWItKKcpl2mX80iFHOzY2VnayzwFHc6r4aUc+sREG7lo6zFOWvTnr9xa2OC7g3itHIEkSheWNhAZpZR3eM6Di61c9WcqWvMNUfvcGsdc/RePRLVR8/ZpXnLY6OoXYG/+AQuvWTjYd30vZyueR7FYEpZqoyx7GcNKBl+nZ1BttbNpXiCAKTBvZx0tTt6O4XC6ftsq6C1fztbtgryj0SZA8pZ8N7pLrFV+/RuPhjQDoUkcTc+Vv5F0qmXNOWrwcCibTOh1ytCdNmsSzzz7L7Nmz0WqbiqwMGTKk0wzraWTkVfP//rEF18nEiU37C3nj8Tk+erxhwVqvqpBhQTqq6swsf2s7uSX1qJUity0ewsIpfc+r/d0Zp8lXCshSmIkkuaha845PMqStLIeGfT8RMmkJAFVr/+PR4pUcNqp+ekd2tHs4LpfEP744wI/b8zxtX/xynFf+b8ZpT3QnDI3l0AnvhMjkOHnl62xRhcchavS4rE3PS01ckxyq+fg+j5MNYD6xl4ZD61GFRCOotWj79D+v9srIyPROOuRor1y5EoDVq1d72k7FaMt0jF92F3icbIDqeit7M8qZPMJ7O/OOy4by3Pu7sTlcaNQKbr9sKB+vySS3xL1yY3O4ePvrI0wZ2ccr0VLGP9aSbEo+Wu7Trk0YgOR04GxFb9ucf9TjaDuaSQgBOBprkSTpgk6+kDk71u7K93KyAcqrTWzeX8Qlk5JP61rzJiSx5UAx6bnu79HEoTFyHOc5QFRriVryCJWr38JRX4m+31jCmikC2WvLfMZUr//IswquTxtD9NWP+4SJycjIdB9cVhOCWocgCO6flWpPDtaFQoesWbduXWfb0e1Jz6lm5fos7A4Xk4bFciS7ipp6KzPGxDN7XKJfp3jroWK+35pDcICGa+b0Jyk2iIlDY3n3qXnkFNWRGh9MgF7Nl+uPe41zOF2U15hkR7sD1Gz+FJfF6NWmTRhE5IJ7EBRKBKXap3IcgPnEPhz1VSiDwgkcOo36vT96zgUMnSI72T2cjNxqv+1tiZkWlDXwyU+ZVNdbmDE6gXkT3VrOWo2SZx+YSlZBDSqlguTYIMprTHyyJpOSKiMXDYtj0ZQU+Tt1BujTRpN4/z+RnA6fl6u+3xiqf36vacdKELxCTUzH92DOPoA+ddT5NFmmG5JdVEdlrZnhaRFoT+5CZ+RVU1ppZGT/KEIC5Xfx+cZWVUz5ly9iK8tBGRaLMiAUS346os5A+OxbCBwxq6tN9NAhR9tkMvHss8+yceNGHA4HkydP5oknniAgwLf6YW+kvMbEk//ais3uBNzl10+xP6sCpUJkwUUprN2ZT0Wt2XNu474iz88Hsip4+4mLMVnsfL81F6PZjkGnIk2vZsLQGA4er/T0jQrT0zdO1tnuCE5Tg09b5KL7UAZH4qir8OtkAyC5MB3fQ9DouYTPXYYyJApL/lE0ffoTPPHSTrZapqsZ0jecn3bme7WFB2mYOrKP3/42u5Mn39hCdb37+3T4RBVqlcjMMU1FFPoluDXZXS6Jp9/cRmF5o6evhMSlU+Uqo2eKvxUsVUg0sTc8Te22VUguB4JSjSlzh1ef1na0ZGRO8Y8vDvDD1lzAraP9zH1T+HZLDt9sygZAp1Hwp7suYkBSWBda2fuoXP0mtrIcABzVJTiq3YX/XOZGKr5/A13fUSgDQ9u6xHmjQ472ihUrcDqdvP766zidTj766CP+9Kc/8cwzz3S2fd2C3ellHifbH5sPFDF9dDyXTErm/R/S/fapN9r4ZtMJVm/Po6LG7Yz/uD2X5x6YxuIpfXE6JbYcKCYqTM+NlwxEoZC3OztC4IiZWAszPMfahEGowmIBUASGoQgMx9lQ5XesMsS9vS8oVO4wkpOhJDI9n1ljEygoa2D19jwEASYMjuFXlw1Fo1J4JsHNycir9jjZp9h6sNjL0T5FflmDx8k+xZYDxbKj3QloEwYRkzAIcIeRmbL2gMtdu0DUB6FPG9uV5sl0IeU1Jo5mV5EaH0JCtH8lqeKKRo+TDVDbYOXDHzPYvL9pkcxsdfLZz1k8eZuct3M+sZVmt37S5cRWmd+9HO0DBw7w9ddfe47//Oc/s3Dhwk4zqrsR7Uc9xPu8W72iT2TbOwDv/5DhdexwSqzdlU9awnCWzkhj6Yy0VkbKtEbQyDmIWgOmzJ2oQmMJHt/0vRVEBdGX/x8V3/0Te2URKJXgcG8zBwyfgS5leFeZLdPFCILArYuGcOuipoTv1dty+c93RzFZ7EwYEsOj14/xbCNHheoRBO/6SDHhBr/XDgvSolSIOJxNaiTtPUNkzh5NbF/ibvoj9fvWIqo1BI9bgEIn78r2RrYdKuaZ93Z7qjrevXSYX4GBeqPNp62u0YqrRQyZqUXhOZnOR5c8DGPGdr/nBI0ebVy/82xR63TI0XY6nbhcLkTRvYrqcrlQKBSdalh3YvSAKPolhJBVUOtzLikmkCtmuh3kiUNjmDwiji0HigHQa5Xt3qAtV85kTg/J6UAVkUBEykktctH9vXWaGxFEEUVgGPq0MbgSBhE0cg6CWougVKEKicZpbkAQlYgaudJXb6eixsw/Vx70JDRvP1zKVxtPcO3Fbl3nmHAD188byCdrMnG6JFLigrh8pv+JcZBBzbLFg3n3m6M4nC5iI9xjZTofbfwAjxa3JElYCjNBEGQFkl7GB6szvEqnf7A6g0suSkEheudJ9E8MJTEmkPzSphDERVP6Ikl4hXNeMimp842W8SJi/l0gKrDkHUEdm4oqJApT1m4UAWGEzboBUXPhLF50WN7v4Ycf5rrrrgPg448/ZsIEeZvkFIIgkBgT6ONo37JgMFfMSvMkOZ0oqsNkttMnMoAJQ2O4dk5/rn/qBxzOphtep1FgtrrDUCJDdSy4KPm8fY6eRmPGDipWvYTkaCbfp1ChjojHVp4HooggKjxx2g0Hf6HPrStQhcVS/vWrNB7eBKJIyIRLfYpgyPQu8krrvVSDAI63uN+vvXgA8yYmUddoIykmsM3kxkunpjJ9VDyVtWZS4oIRRTkR8nzictgo/eiPWArcoXzapKHEXvckgkJe2OgNmMzekq4Wm8O9gCh6LyCKosBf75nMqo0nqKqzMH1UPKMHRjGyXySrt+dSXGnkomGxjOwfdT7NlwEU+iCil/6fd+O827vGmHbokKP9+OOP849//IMXX3wRp9PJ1KlTuffeezvbtm7FyH6R/LyrwHOsVIjMGpfgedmarQ6e+tdWjCdXsFf+chyXS2LRlL58teGEZ9yo/lHMnZiEze6kb59gThS5k3XCg+VV1dPB5bBR8fUr3k42gNPuSaDA6UJyNttRcDpoPLQBdVQSjYc2ePrUbl2JPm002pOxnjK9j4HJYWhUCqzNcjGyi+twuSQvJzk0UEtooNbfJXwIDtDIykFdhPHIZo+TDe4iVsb07QQMndqFVsmcLy6ZlMwHq5tCNWeNTUSl9L9LHxyg4eYFg73atBolS6bLoZxngyRJ1G5dSeOh9SgMoYTNuB5tQs/c2euQo61UKnnwwQd58MEHO9uebsuMMQmU15j5cUceAToVN80fRFhQ0ws3I7fa42Sf4tvN2Xzyl4XklzawN9OtVLL1UAkGnYpJw2K595l12BwuFKLAQ9eO8ptYJeMfZ0N164oibWDKPoAxa7dPu7UsV3a0ezEBOhUj+kWy82hTOfWKGjOHTlQyol9kF1omcyY4Gn3D/BzGmi6wRKYruObiAcSEGzh0opLU+BDmjk8862uWVhl555sj5JXUM2ZQNLcsHIxGJYfYtkbD/rXUrP8IAHtVMSX/+wtJD/zrggr5OFe06Whfd911fPzxx4waNcrvNujevXs7zbDuyNVz+nP1HP+xfvFRvlnNDqdEQWkDR3K8VS/W7y0kI68Gm8OdLOV0Sbzz9RFmjI6XtXY7iDIkuk1FEf8I2CsL/J6xluacG8Nkui3hIb4r1XLIR/ckYNAkajd/huRwJ7sJKg2GARO72CqZ88n00fFMHx1/zq73l3d3egrLFZ+U/rtzybBzdv2ehunEPq9jyWrCUpjZI3Xt23S0X3nlFQC+/fZbn3OS1FbpBpmWRIbqGJ4W4ZVAYdAqiY8KIDxIS3FlU1GViGAddY3eq7G1jVZOFNWSFn9hyNVc6DjqKoi56rdUfPs6tqoiBIUKQaNDaQhFGz8AS0E6gkJJ8EVLUegCMB7Z4lWUpiXm43vOo/UyFyKLJqewYW+hJ4F5UHIYQ/uGd7FVMmeCKiyWuJv+RN2eHwCR4HHzUYXIcbYyZ0ZVndnjZJ9iT3oZyI52q2iikr117QURdWTP3LVv09GOinI/eJ5++mnefvttr3NXX301n376aedZ1gN58rYJvPzxXnYcKSUqTM/dlw9Hq1Fyx5Jh/O29XVhtTnfZ9SVD2Xmk1KcE9IerM7h5wWBS5GI1reI01VP66QqsRccQVBrCZt1E8Nj57Y6TrJY2HW1FgDzB6e0kxgTx+mOz2HqwmKAADZOHx8o7TN0YTVwaUXEPdLUZMj2A4AANIQEaapstkCXFBnWhRRc+wRMXYynOwnxiL4JaR9jMG1EGRXS1WZ2CILWxNP3ggw+Sk5NDQUEBCQlNMw2Hw4FarWbVqlXnxcjTxWq1cvjwYYYOHYpG0z2SjRrNdnKK6kiJCyJAr+ZEYS0Pv7TBb98hfcNZfvtEj4avTBOVP71L/c5mOzCigsQH/oWyHUdZklyUf/kixvRtAKgi4rHXlILTgaDSEn3Vb9CfkgiUkfGDyyUhgY9EmIyMTM9nd3oZr3yyj9pGK8mxQTyxbHyrWvoyTThNDQhqDaJS3dWmnDHt+Zxtemq/+c1vKCoq4ve//z2///3vPe0KhYK0NDnjtjWsdidfrj9OZl4Ng1PCWDI9DZXSfyVHu8PFVxuOczSnmr6loVMAACAASURBVAFJoQxIcjuEqfEh9E8M4Vi+b9LOkewqft6V71dgv7djryzybnA5cdSUtutoC4JI9OW/xlZZiOR0oIlOxtFYi608D01cGgqt/MCUcbP/WDmrt+Wh0yhZOiOVxJggvtuSw4er07HYnMybkMQdS4bJ8dsyMt2E6noLucV1CKKAWikiCAJ944JPazFr7KBo3n1qLnWNVlkl7DRQ6P1X5exJtPktio+PJz4+ntWrV3uK1ZzCZDJ1qmHdmX98foB1u91JdbvTy6ioNXPvFf5XQ9/66hA/bMv19C2pNPLIdaMB+MOdF/HAc+uorLP4jKuoNXeK7d0ddUQ85uymJAuFIQRNbMcnheqIpuQYZUAIyoCQc2qfTPcmI7eap9/c5qkMt/1wCb//1QTeWHnQ0+fbLTmkxocw5xwoGcjIyHQuP+/K57VP93sVsAF3DtVTt09kcErH8zCUClF2smV88L/M2oJ169Zx6aWXMmfOHGbPns3MmTOZPHlyZ9vWLZEkiY37Cr3aftnjX8kCYEOLvhv3FXoSTRuMNr9OtigKTB4Rdw6s7VlYS05Qt+u7pgZBJHzBPQhK/0Uo7NUlVP38HlU//xd7dfF5slKmO7Nq4wmv8suNZjvrdvne38cKZKk4GZkLHafTxTvfHPFxsgGMFgfvfH2kC6yS6Wl0yNF+9tlnufvuu4mNjeXpp59m6tSpXHvttZ1tW7dEEAR0Wu+NAovVyfMf7PF7M7eM51QqRE+CVaBB7TfkZMn0vvRLkJPzWtJ4ZBNIrqYGyUXFqpdoPLoFp6nBq68p5yCFbz9K3fZV1G3/mqJ3fouj3i0FaCk6hin7gHcxG5lez7rdBWw+4DshG5IaTssokWF9e2ZSz4WGpTAT47FduDqomW8tzcGYuROXVd4RlAG700Wjydbq+Ypaeede5uzpUACSTqdjwYIFpKeno9FoWL58OQsXLuS3v/1tZ9vX7bDandhsLp/2DfsKmTgshikj+ni1Oxzefa12J06XhEIUCNCpmDQ0ho37vV/u32zK4eYFQ+SkqxYo9L5qLJLNQvmXLyKoNMRc/f/QJQ+jcs071Ddf+QZcVhMNRzZhLczAdGwXAKrwOOJu/gsKvZw9LgNfrj/u0zZ5eBwzRsez+2gZG/e78wNEUSBA77uLsju9jLW78gkyqLl8RpqcKHWWlK183pO8rAgMp88tf0EZ3HrxoOb3vagPIu7GP/ZYOTGZjqFVK5k0LI4tB/3vaE4dee50tmXOPS67FQThgk+k7NCKtkajwWazkZiYSHp6OqIoyrJWrVBTb/Eq09ycoopGn7aWCVMqpei1OhZg8P0C2R0uLFZ5tbUlgaMuRtT5T6yQ7FaqN3yMvbac+l3f++3jbKz1ONngrlZVv3dNp9gq0/0RgPIaEyv+u4tth0s87S6XxMdrMr367sss54//3s6WA8X8sDWX3/59c6vPCZn2sRRleZxsAGdDlXfYWAta3vcuUz21W1d2qo0y3YOHrx3F9fMGMig5jOTYIBKjAxiQGMrNCwZx66LB7V9A5rwjSS4qf/w3uS/cTN4Lt1C94eOuNqlNOrSiPWvWLO68806eeeYZrrnmGvbs2UNoqBy64I+Csga/7aIoMH5wjE97y5etyyXxzaZsThTVMaJfJPMnJfP9llyvPpGhOgw6/3HHvRmFLoA+y56h4B/3+j3vMjXgMjcAviE86qgklEG+SS9OY53Xz/X71yLZzAQMm+GVOCnT81k6I42XP9nLKUFUCcgqqCWrwFcZqNFs9zpev7eQ5kKq1fUWDmZVMM7PM0GmfVwW30ULp9n/s7epv/d931Z/md6DVqPkurkDuG7ugK42RaaDGDO2U7/bPXGWgNrNn6NLHo4uaUjXGtYKHXK07777bi699FKio6N5/fXX2b17N4sXL+5s27ol2w6V+LQlRAewbNEQEqMDeWvVIdbvKSQsSMuyxUOIDNFTUtVUFVKlVPDWqsOAOyb0pvmDuGvJMN797gh2h4vYcAN/u3/Kefs83Q1lcASahEFY/3979x0eVZn2D/w7fZJMyqT3HhIgBELoHaRJVVEMIsW+uOruusirq4Jl2bXsz7L4quur6+quZVGpCiiC0kKNQAiEQAghhVRSJpMy9fz+CEwyTMqAmUzK93NdXhfnmXPO3DPmzNzznOd57oIsm8fMZhPqzh2FzDcchop8S7vcPxLeU+9D6TevWh8gEsNs0OPi35YAAiCY9MDVcds1R7ch5L5Xeeu5D5kyLAyh/iocP1eGtIxi5BbVtLnvzFERVtveHrbl29WttJF9XCISIfUKgLG6tKlBJIZ70hQAgKmxDjWHNsNw5TJc+w2D+6BJELupIXHzgqmu+UeR++BbnBE6Ef1K+pKLtm2lF3t2ov3ggw9aKkMOHDgQAwcOZGXINrQ27nLl4mGIDvHExp9zsGVvLgBAU6fHX/51BE8sHIK3/3sCeoMJcpkYjXrrISE/HL6ED5+dhjnjuWa2PSp3/7vVJBsATNWlqN7/FRShCVBGJqExr2lJNn1ZHkr/+2cIJuteSHlwHLQnf2z1XIJBh9qTu+EzdVnnvgDq1vqFq9EvXI0qjc4q0ZaIRVg0PR7l1Q1IjvfH2CTrVYHmTYjGwVPFluFj00aEIzaUS0feLJFUhuCla6E5tg2meg3ckyZBGdYfAFD61StozD8DAKg7exCm+lpo0ne0SLJF8L5lCVT9RzspeiK6nllXD23mPpiNOigCY2CsLoUipJ/lzrGpQYu67EMQSxWWa72ZCC6R3bfcfbuJdsvKkC17sK9VhnQ0k8mE5cuXY9WqVRg0qPu+iS3NGReFY1mlyMqrhFgEzJsQg+iQpkl6p3OvWO2r05vg7irHJ6un40JRDcID3LHi1V2oa2xOtlubVEVtq834qcN9dIVnbdquT7IBwFBq+6u5JZGsZ1Qdpc5399R+yLpYidzLNZBLxVg2ewDmTYhpc3+1uxL/+9RkZOVVwsNNjvBATrD9taTuanhPXmzVZqgusyTZ12jSv4exqqRFi2Bb2IqInMZs0KHo46dhuHL9dSmC7+wVcI0diqKPVsGkrQTQNNTTZ9r90KTvACRSqMfeAbl/hO2Ju4luXRny/fffh7+/v8OfpzO5KmV47fHxKCithatSarV4fVyYFw6fbv7Al0rEiAr2hMpVjsFxTbPl7721Pz7YdAqC0DQx8t6Z1/9yo/ZIXD1gbrAdv3kzRK7uEDRXWn9MpoBH8rROeR7qedQeSrz9x0koLKuFl0oBlWvHHQ8SiRiJMVz2z5HESjeIJDKrH84SN08Yq4pt9iOi7qH+/LFWkmwAEFC150uYtFWWJBsA9GWXIFF5IWzFuq4L8lewqzLk999/7/BVRj788EPs37/fsr1o0SLExcXBbLZdKq+7qtHqsPtYAXQGEyanhNlUiLptUiwKy7TYe6IIXioFHpyXiMzcCnz6XRZq6/WYMSoCS2cNwNB4f+RersHAKB+O47xB3lOWovSb1wFzOys6iMXAdX9XrnHDYNBUwlDaNLRHGZUE71uW4fKHK3H9JCqx0g1B977U6uRJ6ltC/Xt/+eCeRKJ0g3rC3aj86TMAAsQuKvhOfwBV+9dbVhSSqLzhOXyWcwMlIruYDY2t1rRo7S50dyUSBMF2CYbrtDXxcevWrZ0e0DVPPvkkVCoVMjMzERMTg9dff93uY3U6HTIzM5GYmAiFomtu7zfojHj8bz+htLJpgXs3pRRvPTkJLgoptuzLRVlVPcYPCcGIAYEwmsyQiEUor27Aw3/50aqQzeMLh2D6yOZbIHqDCTVaPfzULOtqL6O2Go0FZ2CsKkNjUTbMDbVQhg+AIiQecr9QaNJ3oObQFsv+6vF3Qz1hIQRBgK4wGyKJFIrgWFQf3YbKvf8FGrWAVAapTwjEIgk8R86Be+IEJ75CIrqeYDKi5th26AqzIfMJgSKkH1wiBkAsb/rsbMg/DVO9Bq7RyRDL2YFB1F2YDToU/XMVDBWFNo95jbkd7snTUPThSph1TfmV1NMfoQ+9AbGie+RFHeWcdk2GbDlsxGAw4LvvvkNYmGNXW3jjjTcAAOvWrcOkSZMc+lyd4fDpEkuSDTSVb915JB9Hz5Tg4mUNAODn9EI8vXS4pXx6dl6VTbXI07lXLIn2vuNFePebk9A2GBAT6onn7hsJX6/u8YfVnUlVXnCLG478d38LU+3Vao8FWQi4838g8wqAzy3L4BIxCLrSPLhEJUEZ3DQMSiQSQRmWAADQpO9A5Q8fNZ/UaICxNA8AUL75bUiUbnCNTenS10XOZTSZ8Ut2GUQAkuP9IZXYVYaAukjF9x+h9njzuvcew26FW1zzNeoS3j1XJCDq68QyBUKWvwLtmQMw6xsgkkhhqCiEMjQBbgPHQSQSIeSh/wdtxh6IZHK4J03uNkm2PexKtEeMGGG1PWbMGKSmpmLFihUdHqvVapGamor3338foaFNs0e3bt2K9957D0ajEcuWLcPixYvbPP7xxx+3J0Snk7XypVtRVW9Jsq/ZeeSSJdGOC/eCWAS0zLUTIprWJ2/UGbHuqxNouFqY5kJhDf69PQt/WDTUQa+gd2nIP2NJsq/Rnt4Ht/imv2XX2KFwjW37vdSe3t/mYwCgPZPGRLsPadAZsWrdPuQVN13P0SGe+MujY9GoM8LbQ9nm0LrqWh1kUjHcXGQ4nl2GPccLEeTjhtljo+wa103205762Wq7NuNn+M540DnBUK9yLKsU/96WBU29HtNHhCN1ejyL9nUyscIFHslT23xc5ukP9fi7ujCizmNXon29qqoqlJWVdbjfyZMn8dxzzyEvL8/SVlpaijfffBMbNmyAXC5HamoqRo4c6ZDJlZmZmZ1+zrZITQIC1TKUVDWNGxIB2J1uexukrKIa6enplu15I9X48UQNGg1mJEe7wVd2BenplSivMViS7GuyckusjqW2ibUVuL4g+5UGIwrtfP9cjWK0N+iovN6AAv6/6DPSc7SWJBsAcotqcN+LO9CgN8PbXYq7x/sgwKt5hSCjScCGg5U4k98AiRgIVMtQdKV5TOHXu7Px6KxAeLhKuvR19GYeUiUkRr1l2yhV8vOSfrXaBhPe2lwM09VpPZ//kI06TRmSozmhluxjV6Ldcoy2IAgoLi7G3Xff3eFx69evx5o1a7Bq1SpLW1paGkaNGgUvr6Y1ZGfMmIEdO3bgscceu9HYO9SVY7QBIDnZhIOnivHJd2dQXt3Q6j4lVQb06z8I7ld7s1JSgAfuanpfW/5CNpsFbDi8C8UVzcVsJqZEIyUlwbEvohep0F+G5sh3AATIfIIRPu9hSN3tq2iqjwxC8WcvWHrFRTIlBEMjAEAeEIWIeQ9B4sqJcH3FJc15ANYVIBv0Td+8lbVG7Mky4NXHRlke2552EWfym2bRm8ywSrIBoFEvoKTBE5PHsxpdZ9G6PoSyTW8DZiMgkSL41ocQl8C7TvTrHMi4DJPZetWaGoMbUlL4t0VNro3RbovdY7TLyspQU1OD+Ph4uLu7QyLpuCdm7dq1Nm1lZWXw8/OzbPv7+yMjI8OeMLo9uUyCiUND8cYXv7S5j8Ek4I3P09EvXI0LhTUABOSXaNGgM8DLXYkgXzdMHxmBIF83RAV5oFFvhFgkglIuwfaDF3H8XBkev2swIoKu76+l6/lOuw+ew26Fqa4aiuA4iMT29x7KfYIR/tt3obucA6mnH6QePjBUl8LcoIU8MJq3DfuQ0sp65BVrIBGLbOZUXNOytxsA8ks7Lu/907F8hPqrMH5ISKfE2dep+o+BMrQ/dCUXoAiKhVTFgkD060UHe0IkAlouG3F9samcgmoIEBAXZl9HDvUtdiXau3btwmeffQaVSgWRSGTpfT148OANP6HZbLZKUq7vye0Nhsb741hWaZuPH8sqw7Es26E31Vo98oo1OHiqGG4uMtQ12C5fU6PV48m39+KT1TM4xtMOMnUgZOpAGGrKUJd1CBJXDyhC43Hlh4/QWJAFZUg8fGf9BjIvf5jqaqA9vQ8QiaAaOB4SVw/L5EgAkHkFAF4BTnw11NX0BhOefmcfKmoaLW2jBwWhulaHrLzmdV1TEqz/Lob1D8C3+9sveFR8pR6v/fsYxGKRTSVJujlSdzWk7sOcHQb1IkG+blhxRxI+3ZaFep0RE5NDMGtMFADAYDTjpY8O4cS5cgDAoBhfvPjwKMikHBJGzexKtHfu3Il9+/ZBrf71v9YCAwNx7Ngxy3Z5eXmPK0rTkd/dnYx/bMxA+tkyAAK83JWordND20ri3JbWkuxr9AYzjp0tw6ShoZ0Qbe+nK83D5U+etQz9ECncIOiahuQ0XDyJ8q3rELDgKRR+tBKm2qbkqTptI1wTRkMEAe6Dp0ARGO20+Ml5Mi9csUqyAUAuleCZZcPx4ZZMnM+vRmKMD+6fa72iRUpCAB5fOATr1p/o8Dn2Hi9kok3Ujd06JgrTR0bAaBagkDUn0WkZly1JNgCculCBvceLcMvwcGeESd2UXYl2ZGQkPDw6p2TwmDFjsG7dOlRWVsLFxQU//PADXn755U45d3fh5a7A/ywdbtW2+1gB3mxnSMmN8vXkOrD20hzbbkmyAViS7Gsa87NQm7nXkmQDgElbhdpj2wAAtcd/RMj9r3brEq/kGN6tXGfenkqoPZR46t72e06nj4zAvuNFOHG+vN39fD17zjJVRH2VRCLG9SNmKzWNNvu11kZ9m10LwS5ZsgT33nsv3nrrLbzzzjuW/25GQEAA/vCHP2Dp0qW47bbbMGfOHCQlJd3UuXqS8UOCkRTbXH65teUAr4kO9sTEoc3jNr3crSd0Du8fwFLO7RBMBsvC9vaQB0ZZD8Br5XyajJ9gauh43C31LpFBHrh1dKRlO8jXDfMn2H9343epyRjWPwBuLjJ4qmyHeoX4ueGOyZ2/4hJZM9ZWovFyDoQ2KsaadfUwG3RdHBX1dKMHBUHeoodbJhVjDO9O0XXsqgy5aNEiqFQqhIdb3w5pWcimO3FGZciOZF2sxDtfn0BhaS0GRPtg1b3DUFiuhb/aFfklGlRUNyA+Qg290Yz4cDVEIhEKSmuhrTcgPkKNSk0DjpwpRUKEN6JDOBGyLZrjO1G5+98wN9bDNX4E/Of/DobKYlz+5E8Qrn6RygOiIJhNMJTntzhSBMjkQFtftnIXQN8ARXAcAu74I6Sefq3vR71SQWktqrU6DIj0huRXFKq5eFmD8/mV6BeuRqPehLhwNSTi3jVHpbupOrABVXu+AAQzpOpABC1eA5ln03BFwWxC+XfvQntqL0QSKbzGLoB63J1Ojph6kvMFVdiyLxeCGZg7PgrxEd7ODom6WEc5p12J9m233YZNmzY5JEBH6G6Jtslkxv1/3ml1S2n8kGAkRHhjTFJwm9UeL16ugUgkQmRQ5wzb6e2Mmgrkv7MCEMyWNvXERVCPuxOG6lLUZR2ExNUDbgPGoujjVTCU265z7j5kKsRunqg58E2bz+OWMAoBC55yyGugnqdS04i8Yg36hauhcpHBZBaQU1AFtYcSVVeveX75OoexthL56x6x+kxwHzIVfrObiq1pTvyIiu/eszom5L5XoQjmXQYiR6s5+h20p/ZAolJDPSEVisCoDo8xaqtQufs/0JVcgDJsAERSGXSF2VAEx0I9cREkyq5f37xTSrBHRUXh7NmzSEjgGs43o7Sq3mbc1r4Tl7HvxGX83+ZMLL21P+6a2s/ymMFowksfHraM7RzWPwDP3jeCJZ87oC/Lt/pCBQB9adPKDzKvAHiNvg0AIAjmVpNsAJC4ekDuG9bu8+iulmIn2n0sH+vWn4DRJMBFIcHjC4fgsx3ZKCrXWu2XGOODFx8abXWbmRzPWFtp85lgrGkeM68vvWRzjK4sj4k2kYPVntyNKz/807LdWHQO4Y+9D7Gs/c7Rsk1vovHSaQCAobzA0q67fB7GmgoELnzaMQH/CnZlbsXFxbjzzjsxY8YMzJ071/If2apvNODomRJcbvFFG6B2hU87kxc//+EszC3W5/1u/0WrCVTHskpx8FRxa4dSC4rQeIjk1u+zS9Rgm/1EIjGUEYmtnyOkH7Tnj6KptmfrXFs5J/U9JpMZH205DaOp6dpt0Jnwj42nbJJsoGn1kv0ni7o6xD5PERgFqTrQqs1twBjLv12ir7uWxRK4RA7qitCI+rS6c0etts31GjQWnG33GLO+wZJkt6b+/DEIJmObjzuLXT3aTz75pKPj6BVyCqrx3D/SUNdggEgE3DuzPxZO7QeJRIxnlg3Hu19noKCsFgbjdT0sJgEGkxkKsQQ/HsnHP7+1/UOqaKPSJDWTKN0QuPAZVP70OUx1VXAfNBnuydNa3dd//u9QtvltNOafAQQzRDIl1BPuRvm378Lc0Fx8RKxUwX3wLdBX5ENfXgDXmGR437Kkq14SdWMGkxnaer1VW0Nj2x/ylRpOtutqIrEEQYvXoHr/NzDWlMGt/1h4DJlqedwtbhh8pj8ATfqOps+A8Xc1rZdPZIe9xwuxcc8FiEXAgslxnAh5A+S+Iag/16JBJIbMJ6jdY0QyJaQevjBqKlp9XOrlB5HErrS2S9kV0YgRIxwdR6/w2fdnLetfCwLw5c5szBoTCZWrHPER3nj7j5MAAPe99L3V2rxhASpIJWKcvlCBj7Zk2iyAIZeKMXpQ+3+A1MQlIhEhy//S4X5Sd28E3/uiVVtdTrpVkg0AEEvgM3VpZ4ZIvYRSLsXoQcE4kHHZ0pYc74/Dp0ts9pXLJBiTxGv419KV5sGkuQJlZGKHt5ivkXn6W8Zkt8Zz+Cx4Dp/VWSFSH3Euvwp/+yzd8n396qdH8daTkxAVzMUK7OE5aj4a8rOgKzwLkVQO9cRUyyTltohEIvjOeRTlm9+Gqa4GEpUagskIc0MtxEo3+M58uIuivzHdL/XvwWq01j1WBqMZdY1GmwqOf310LFZ/cBBXNI2ICfHC4wuH4NFXd+FyhfX6zkDTckF/eXQsAn26foB/XyOSyGzbuCIEteP3i5IREeSBC4XVGBznh1ljo7DveCF+/qUQUokYYrEILgop5oyLQrCvytnh9mgV338EzdW17SVuXgha8jLkPuxBJOdIzyq16hQzC8AvZ8uYaNtJ4uKOkGVrYagug0TpBrGdkxhdowYj/PF/wKi5AqmXP2A2QV9RBJl3kN0/vrsaE+1OdMvwcJwvqLZsJ8b4IMDb1Wofk1nAXz89huIrTes8Xyisxpc7s1tNsgFg/oQYrljQRVyjkiDx8IWpxW0pr7F3OTEi6u6UcikWTY+3apuUEoZJKe1PqKUbY6gqsSTZAGCqq0bNwY3wm/NbJ0ZFfVl4K6uBRXCFsBsm87rxyuAiiQyya3MvJGIoAiI7N6hOxkS7E80eGwWViwxHTpcgxF+F+RNibPY5nVuB3KIay7beaMbZvEqb/QbF+GJ8cghmjGQ1wq4U9ug7qN73FfQVhfAcMRsu4QM7PoiIHMpUb1ssylRX08qeRF1jdGIQZoyKwM4j+RABuHV0JFISbjxppN6PiXYn0hlMiI9QY2iCP9xbDBfRGUzQ1uvh4+nS6hJ9of4qlFU1T3ZUuyuwcnEKlAoJxBy60KXEEhm8J93j7DCIqAVFcAxkfuFWRabcB09xYkTU14nFIjx21xAsmz0AIpEIKhfboYdEABPtTrMt7SL+b1MmjKamFUXGJgVj5b0p2Hu8CB9szEBdoxHxEWr8aflwJMX6IiOnaXiCm4sMD84fhHP5Vfhg4ynU64yoqtVh2UvfQyoRYcHkONx7a39nvrReQTAZ0Vh0DlIP35u6VUVEziMSiRG8+AXUHPkWRk0FVAPGwTUuxa5jBUGArvgCxHIl5L6hDo6UervzBVV495sMaLQ6TEgOwdJZTYl2o96IzXsvILeoBkPi/DBjVCQ7yggAE+1OUVHdgH9syECLpbBxIOMy+h/wxqfbsqA3mAAA2Zeq8MUP5/Diw6Nx+HQJNFodRiUGQe2hxM7Dl1Cvs14azGgS8N8fz2HEwED0C1d35UvqVQxVJSj+z5qrSwKJ4DVuAbwnLnJ2WER0AyRunvCevPiGjjE31qH48xehK74AAFANmgj/eU84IjzqA67UNOCpv++D6eqX/de7c1CvM2HFHUl484tfkJbRVO8iLaMYlRodFs9kkT+ys2ANtS+/tNYqyb7m3KUqS5Jt2bdEA6lEjLFJwbh1TBTUHkqYzAIOn267IM2R0yV4/T/H8Nq/j+HMxSudHX6vV33gmxbrbgqoPrABRg3fR6LeTnN8pyXJBgDtqT1oyG+74AVRe/adKLIk2dfsSS9AfaPBpqjc7vQCEAHs0e4UCRFquCikaLiuR3piSijO5FVaFZsZ1t+2GMLn35/F5Yr6Vs8tEYuw8ecc6K8WuTl4qhh//+MkhAW4d+Ir6J0MVSXQnklDY9E56wcEM4zaKkg9fJwTGBF1idYKW/BHNt0sH08XmzY3FxnkMgnclDJor9bRAAC1qnsuNUddjz3ancBVKcNLD49GZJAH5FIxvFQKPLogCSMGBOKFh0Zh+IAAhAW4I3VaPO6YHGdz/J5fCm3aXJRSxIerMXVEuCXJBgCjyWxVIINapy+7hML/+yOqfv4Mhgrr91fmEwxFULSTIiOirqIaMA4QNX/NiZVucI1JdmJE1JONGRRk1cklEgGP3JEEqUSM5XMGWsZkK+USLJ3NuVXUhD3anSQh0hvrVk62aY8I9MDqB0a1e6yvlwtKK5t7tN1dZfj0hZmQSsTYf7II3x+6ZL2/p7Jzgu7FNL/8AMHQaNWmCI6DIjgWXqNvh0jE35hEvZ0yLAGBd/8JmuM7IZa7wGvUfEhceDeQbo5EIsa7q6bg0KliFJZpMW1kODyv9lzPGBWBofH+uFSiQUKE2qZQHfVdTLS7geWzB+DFDw9B22CAVCLGA/MSLcsAjkoMwrD+ATiWVQoASIr1xYRkzpzvkMh2trf3pHvgEpXkhGCIyFlcY5LZamz/LAAAHbBJREFUi02datSgoFbb/dQu8FPbDi+hvo2JdjeQEOmNj5+fjvOF1Qjzd4eXe/PYLqlEjDUPjsLFyzUwmwXEhHo5MdKewyNlJmpP7YGga7pToAjpB2Vk4k2fr+7sYWjSt0MkU8BrzO1QhnI2OREREbWPiXY3oVRIMSjGFwBQVduI9zdk4ExuJeIj1PjNHUmICvZ0coQ9i9w3FGEPv4W6swchdnGHW//RNz1cpLEgC6XfvA6gabZ5w8UMhK14h5MpiYiIqF1MtLuJSyUa/HgkHwq5BNmXqnDiXDkA4PDpEjTojFi7YqyTI+x5pB4+8Bwxp8P96i+eRO3J3ZAoVfAcNQ8yL+uVYeqyD+Nakg0AglGP+gvH4ZE8tbNDJiIiol6EiXY3kF+iwZNv7bVZc/uajJwKXCisRtqpYoxODEJsGIePdJaGS5ko+fxlXEuk67IPI2zFOxDLmyecSr0CbY6Tedu2EV0q0aCssh6DYnyhVPDjlYioM5n1Dag/dwyQSOAaNwxiafefdMpvgm5g97GCNpPsa37/5h4AwPofz2H22Cj85g5O6rOHubEOdeeOQCSVw63fCIikMqvHtaf2omVvtUlbhYaLGXCLH2Fpcx88GfXnj6Ih9wQAEdyTp8Il4ubHe1Pv9M+tp7Hx5xwAgKdKjr+sGIvwQA8nR0VE1DuY6mtR9PEqGKvLAABy/wgEL/8rxLLuvWY5E+1uwEVp+7/B3VWG2npDK3sD29Mu4v65AyGXSRwdWo9m1Fah6J//A1NtU4EKeUAUQpb/1SrZlqhs7w5c3yaWKRC06HkYKoshkso5NptslFc1YPOeHMt2jVaPr3adxx8XpzgxKiKi3qP21E+WJBtoqpdRd/YQ3AdNdGJUHeNiwk5Wo9XBaBTg5tKc/A2I8sbssVFtHmMWAF0HPeAE1J7cbUmyAUBfehF1549Z7eMxbBZk3sGWbVXiBChD+rV6Ppl3EJNsalVtvR7XVWZGjVbnnGCIiHohwaC3bTPatnU37NHuYiazgPU/ZuPn9EK4KGW4Ut2A6qtfyHKpGFEhHogO8cKgGD9881MODC2qQl4T6qeCOxfD71BrF6BgtE5+pCovhD7yFhrzz0Ds4g5FQGQXRUc9TaPeiI0/X0BuUTWGxPnh1jFRlkpwUcEeiA7xRG5RjWX/W4aHW/5d32jA1v25+OVsU2/MkH7+mD8hGq5K66FMRNQ1rtQ0QFOnR2SQB0St1F2g7kc1aAJqDm+BubEOACBRqeGW0H5BwO5AJAiC0PFuPYtOp0NmZiYSExOhUDhv7I4gCDh8ugQ5hdUYHOuHQbG+eG/DSWw7kNfhsX5qFwzv749tadZVIUP9VXjjdxPgwi/oDhmqSlD40VOWtbSlnn4IfehNiBUsKEA37q+fHEFaRrFle+HUflhya3OZ5RqtDlv25aKssh5jBwdjVGJzUYvn30/DifPlVudLivXlakJETvDptjP4Zvd5mAUgOsQTLz082lLhkbo3Q3Upak/uhkgig/vgKZC6ezs7pA5zTvZoO9DH356xTI76785zWLEgCbuOFNh1bHlVAw6fLrFpb9AZmWTbSaYOROgDr6M242eIZXK4D76FSTbdlAadEQdPFVu1/ZReYJVoe6oUVtvXlFXV2yTZQNNqQqWV9Qjwdu38gImoVQWltfhq13nLdm5RDTbtuYBlswc4MSqyl8wrAN4TFzk7jBvCRNtBDEYzvtufa9W26ecLULlKoauxb3y1h5sCV2p017VxyMiNkKkD4T0x1dlhUA8nl4qhcrGeoKx2t68HzFUhhVQihtFkPQxMKhHDrZWJ0ETkOGVV9TZtpZW2bUSdhZMhHUgkth73JRYDD9+WBHtGg00bEY6HbxsEqaR5b4lYhOWzB3ZylGSPxqJzKN/2Pq7s+gTGGtveSerdJBIx7p87EJKr17SLQmL3tahylePuabYTbO+e1g8qzrUg6lIDo33gdd0wkbGDg9vYm+jX4xhtB/psx1l8uTPbsv27u5MxdUQ4qjSN2HU0H65KGf757Wno9NY93PfPHYjbJ8UCaFrN4MDJIpjNwJikYHjZ2YtGnUd3OQdFnzwLmI0AmiZghK1YB7Gcw1D6mis1DbhUXIv4CLXVSkH2KCitRU5hFUQQITbMC6H+7g6KkojaU1Bai//uPIdqbSOmDAvHlGFhzg6JejCO0XaixTMTMCjWBzkFNUiK9bVUdFR7KHHnLU09XKWVddjw8wWr41quj+3uKsfM0W0v9UeOV5u5x5JkA01FbepzfoFqACey9TU+ni7w8by5H1hhAe4IC2ByTeRsYQHuWHkv17inrsGhIw6WFOuHOybHtlk2feqICMilzf8b3JRSjB4U1Oq+5BwSpW1yJHFhwkRERETtY4+2k4UFuOPVx8ZjW9pFSCVizBkXBW8PpbPD6jUa8k6hseg8XML7QxlmuyKEPTxSZqA2cw+MVU2rwLjEDIUyclBnhklERES9EBPtbiA2zAtP3J3s7DB6neq0Daj86TMAQBUAn+n3w3P47Bs+j8TNE2EPv4WGvAyIFa43nbATERFR38KhI9RrVR/cZL2dtqmNPTsmksrgGpvCJJuIiIjsxh5t6rVsFtQRbMvZE7VFEAQcOV2CvGINkuP90S9c7eyQiIioh2GiTb2W16j5qNrzhWXbc/RtToyGepoPNp7CtwcuAgA++/4snrwnBZOGhrZ7jNks4Mej+TidewXxEWrMGBkBiYQ3DomI+iom2tRrqcfdCUVQDHSXz0MZ1h8unMBIdqpvNGD7wTzLtiAAG3/K6TDR/nTbGXzzUw4AYPexAlwq1mDFgsEOjJSIiLozdrU4SKPeaDV0wWA0o1FvREV1vVW70dTUbjILaNQZWzsVAEBbb4DOYF/pdmrmGpMM9fiFTLLphomuL+F63bbBaELDddfsD4cvWW3vPJJvO4SJiIj6DPZod7Lyqga8/p9jyMqrRLCvG36fOhTZ+ZX49/Ys6A1NY4SlEhF+f/dQaBv0+Pf2LNTrjJBKxDAYzRg+IAArF6fAVdlUdS6/RIMXPzyEsqoGAMCgGB88d/9Iy+NE1PlclTLcOiYKW/flAmhKuhdMjrU8/vXu8/jvzmzojWZMTgnF43cNgUQihspFjtp6g2U/lYsMIpuMnYicTdtgwPa0iyivbsD4ISEYFOPr7JCol5K88MILLzg7iM5mMplQVlYGf39/SKVd+1vi7f8ex/Fz5QCA2noD0s+WIS2jGCZzc6+WWQCOnCnB0axS6I1Nybf56uOXy+tgNgtIjvcHALz44SEUlGotx5ZVNVg9TkSOMTTeH3FhXogI8sDy2QMt11xuUQ1e+fQojCYBggBcvKyBr5cLYkO9oPZQ4NCpYggCIBYBj9yehOgQTye/EiJqSRAEPP2/+/FTeiFyCqqx+1gB4sLUCPZTOTs06oE6yjnZo93JcgqrrbYrNY2t7mc0tX07+UJR8zlyi2o6fA4i6nwikQjDBwRi+IBAq/bcItvr79p1Om5wCOLDvXH2UiXiwrwQ6OPWJbESkf1yCquRU9B8HQsCsONgHob1D3BeUNRrcYx2J7v+9lOInwoSse2tYxeFBDJp62//4Di/5vPF2t7OSmqljW6OYDKi7uwhaH75AUYtf8BQxwbF+tlc0y3vMPmpXTB+SAiTbKJuqrWhl65K9juSY3DoSCcbFOuLK9UNqNQ0IiFSjSfvGYpBsX7ILapGXaMRggB4qRRY89AojBwYhILSWgBNYzldlFLMGBWB1OnxEF/9Ih/Szw/nC6pRWdMIiUSMW4aFYemsAa0m73RjBEFA8Rcvo+bgRtTnpKP25C649hsOiauHs0OjbkzlIkNUsAcKy7VQKqS4e2o8po4Id3ZYRGQnDzc5yqrqcfGyBkDTNf3EwmR4uSucHBn1RB3lnCKhF06J1+l0yMzMRGJiIhQKXjjUusaCLFz+9DmrNo+UmfCd+ZCTIiIioq5y5uIVlFc1ICXBHypXubPDoR6qo5yT90qozxJMtsspttZGRES9z4AoHyDK2VFQb8cx2tRnKcMHQB7Q/CkrksjgkTzNiRERERFRb8IebeqzRGIJgpe8hNqMn2Gqr4Fq4HjIfduv/EdERERkLyba1KeJFa7wHD7L2WEQERFRL8ShI12goroBpy5UwGBsLqGuN5hwOvdKm+tsE1HvU99owKY9F/DRlkxkX6p0djhERORg7NF2sA0/5eCTbWdgNgtQuyvw8m/GwGwWsPqDg6iu1UEiFuGh+YmYPS7a2aESkQMJQtN1n32pCgCwZe8FvPjwaAzpxyqvRES9FXu0Hai2Xo//7MiylFevqtXhi++z8Z/tZ1FdqwMAmMwCPv7uDOobDc4MlYgcLKew2pJkA4BZALal5TkvICIicjj2aDuQpk4Pg9Fs1VZR0wCDwbpNpzdBW2+wqlZ15uIVZF64grgwL6uqc0TUMynlth+3SrnECZEQEVFXYaLtQCF+KsSGeSGnoLm098TkUBiMJuRerrG09Y/0hr+3q2X7uwMX8f6GDMv2PdPjsWhGQtcETUQOERbgjglDQrD3RBGAppLPt0+KdXJURETkSEy0HeyFB0fhq13ncblCi1GJQZg+MgKCIECpkOLI6RKE+rvjrlvirI755qfzVtsb9+Tg7mnNZdmJqGdaeW8Kpo0MR0V1I4b1D2DJZyKiXo6JtoN5qhR4cH6iVZtIJMKsMVGYNcb+klRCZwdGRF1OJBJx8iMRUR/CyZDd0ILrbiffNjEWEvZmExEREfUo7NHuhmaPi0ZksCcyL1QgLkyNoQnsASMiIiLqaZhodyKTWcCOtIs4lXsF7q4yNOhM8FIpMG9CNPzVrh2foIWB0T4YGO3joEiJiIiIyNGYaHeif317Gpv2XLBpP3CyCO8/MxUKGZfyIiIiIuorOEa7E+06WtBqe0VNI06eL+/iaIiIiIjImZhodyIvd3nbj6m4jBcRERFRX8JEuxMtnzMQMqntWzoxORT9wtVOiIiIiIiInIVjtDvRiAGB+Pj56cjOr0JEoDuKyuvg4SZHbKiXs0MjIiIioi7GRLuTeaoUGDEgEAAQ4O3m5GiIiIiIyFk4dISIiIjoqrKqetTW650dBvUS7NEmIiKiPq9BZ8Rf/nUEJ86VQyoR4c4p/bB4ZoKzw6Iejj3aTlZWWY9/fXsaH2w6hbxijbPDISIi6pO+O3ARJ841LcVrNAn4cmc2v5fpV2OPthNp6/X449/3orpWBwD4/tAlvPWHiQgLcHdyZERERH1LYVmtTVtRmRaRQR5OiIZ6C/ZoO9GhzBJLkg0AeoMJP6W3XvSGiIiIHGfkwECrbReFBINifZ0UDfUW7NF2IjcXmU2bqpU2IiIicqzRg4Lx2F2D8cPhS1C5yrFoWjw83NouREdkDybaTjR8QAAGRvvgdO4VAECwrxumjYxwclRERER904xRkZgxKtKqzWwWIBaLnBMQ9XhMtJ1IKhFj7YqxyDhfDr3BhKEJ/pBJJc4Oi4iIqM/bcTAP/9mRhYZGI2aMjsSD8xKZcNMNY6LtZBKxCMnx/s4Og4iIiK4qKK3Fu9+chCA0bW/dl4uoIA/edaYbxsmQRERERC2cL6iyJNnXZOdXOScY6tGYaBMRERG10D/SB9ePEkmM9nFOMNSjMdEmIiIiaiHI1w1P3pOCIB83eKrkuHtqP0wcGurssKgH4hhtIiIioutMHBrK5Jp+NfZoExERERE5ABNtIiIiIiIHYKJNREREROQATLSJiIiIiByAiTYRERERkQN021VHcnNzsXLlSkRHRyMxMRHLly93dkhERERERHbrtj3a6enpCAwMhFKpRHJysrPDISIiIiK6Id2mR/vDDz/E/v37LdurV6/GLbfcApVKhRUrVuCjjz5yYnRERERERDem2yTaDz74IB588EHL9qZNmzB69GjI5XJIpd0mTCIiIiIiu3TbDDY6OhqvvPIKVCoVFi5c6OxwiIiIiIhuiMMTba1Wi9TUVLz//vsIDW0qZbp161a89957MBqNWLZsGRYvXmxzXFJSEt58801Hh0dERERE5BAOTbRPnjyJ5557Dnl5eZa20tJSvPnmm9iwYQPkcjlSU1MxcuRIxMbGdvrzZ2Zmdvo5iYiIiIjs4dBEe/369VizZg1WrVplaUtLS8OoUaPg5eUFAJgxYwZ27NiBxx57rNOfPzExEQqFotPPS0RERESk0+na7dh1aKK9du1am7aysjL4+flZtv39/ZGRkeHIMIiIiIiIulyXr6NtNpshEoks24IgWG0TEREREfUGXZ5oBwYGory83LJdXl4Of3//rg6DiIiIiMihujzRHjNmDA4ePIjKyko0NDTghx9+wIQJE7o6DCIiIiIih+rydbQDAgLwhz/8AUuXLoXBYMCdd96JpKSkrg6DiIiIiMihRIIgCM4OorNdmwHaU1cdOZVTgUOZxQjydcO0kRFQyCTODomIiIiIrtNRztltK0P2VftOFOG1fx+zbB/NKsWLD412YkREREREdDO6fIw2tW9b2kWr7V/OlqHkSp2ToiEiIiKim8VEu5tRyq1vMohFgJxDR4iIiIh6HCba3cxdt8RZJdazxkTB20PpxIiIiIiI6GZwjHY3MyDKBx88cwuOZ5chyFeFgdE+zg6JiIiIiG4CE+1uyMfTBVNHRDg7DCIiIiL6FTh0hIiIiIjIAZhoExERERE5ABNtIiIiIiIHYKJNREREROQATLSJiIiIiByAiTYRERERkQMw0SYiIiIicgAm2kREREREDtArC9YIggAA0Ov1To6EiIiIiHqra7nmtdzzer0y0TYYDACAc+fOOTkSIiIiIurtDAYDlEqlTbtIaCsF78HMZjPq6uogk8kgEomcHQ4RERER9UKCIMBgMMDNzQ1ise2I7F6ZaBMRERERORsnQxIREREROQATbSIiIiIiB2CiTURERETkAEy0iYiIiIgcgIk2EREREZEDMNEmIiIiInIAJtpERERERA7ARJusFBYWYsqUKTbt8fHxMJlMWL16NebMmYO5c+di69atlmPi4+Nx4MABq2OmTJmCwsJCAMA777yD2bNnY/bs2Xjttdcc/0KICED71/Q1paWlGDdunNUxHV3TAKDVajFnzhyrNiKyT8trsC1///vfMWnSJHz88cd27d9V1q1bh7Fjx2L+/PmYN28e5s6di0OHDjk7rG6JiTbZbcuWLdBqtfj222/xySef4M9//jO0Wi0AQCaT4fnnn7dst5SWlob9+/dj48aN2LRpE06fPo2dO3d2dfhE1Io9e/Zg6dKlKC8vt2pv75oGgJMnT2LRokXIy8vrgiiJ+qbNmzfj448/xn333efsUGykpqZi8+bN2LJlC1577TU8+eSTzg6pW2KiTXa7/fbbLb3RZWVlkMlkkMlkAAB/f3+MGTMGr776qs1xfn5+ePrppyGXyyGTyRATE4PLly93aexE1Lqvv/4a69ats2lv75oGgPXr12PNmjXw9/d3dIhEvdrhw4dx//3349FHH8WMGTPwxBNPQK/XY/Xq1SgtLcVvf/tbZGVlWfZft26d1TV77U6TyWTCX//6V9x+++2YN28e/vWvf7V7/h07dmD+/PmYP38+5s6di/j4eGRkZODcuXNYsmQJFixYgMmTJ+OLL77o8DXU1tbCx8en09+b3kDq7ACo+ykrK8P8+fNbfUwqleLZZ5/F5s2b8fDDD0OhUFgee/rppzF37lwcOHAAY8eOtbTHxcVZ/p2Xl4ft27fbdeESUedo75puLcm+pq1rGgDWrl3bqTES9WXHjx/H9u3b4e/vj4ULF2L//v146aWXsH//fnzwwQcIDQ3t8Bzr168HAGzcuBF6vR4PPPAAEhMT2zz/zJkzMXPmTADAn//8ZwwbNgxJSUlYu3YtHn30UYwePRoFBQWYN28eFi1aZPN8X375JX788Ufo9XpcunQJL730Uie+I70HE22y4e/vj82bN1u1tRwbtnbtWqxcuRJLlizB0KFDERkZCQBQqVR4+eWX8fzzz2PLli025z1//jweeeQRrFq1ynIMETleR9d0Wzq6pomoc8TFxSEwMBAAEBMTg5qamhs+x8GDB5GVlWUZK11fX4/s7GzExsa2e/6vv/4aZ86cwSeffAKg6Qf2vn378I9//APnzp1DfX19q8+XmpqKxx9/HACQm5uLxYsXIyoqCikpKTcce2/GRJvslpmZCZVKhcjISKjVaowfPx7Z2dlWSfO4ceNavd2cnp6OJ554An/6058we/bsLo6ciG5WW9c0EXWelneHRSIRBEFoc1+RSASz2WzZNhgMAACTyYSnnnoK06dPBwBUVlbCzc0NJ06caPP8v/zyC95//318+eWXlqGgv//97+Hh4YHJkydj1qxZ+PbbbzuMPzo6GkOHDsWJEyeYaF+HY7TJbidPnsTrr78Os9kMrVaL/fv3Y+jQoTb7Pf3009i/fz/KysoAAMXFxfjtb3+Lv/3tb0yyiXqg669pInIetVqNnJwcAEBGRoZlIvOoUaOwfv16GAwG1NXV4Z577sGJEyfaPE9xcTFWrlyJN954A76+vpb2AwcO4IknnsDUqVOxd+9eAE1JfHs0Gg3OnDmDAQMG/NqX1+uwR5vslpqaiuzsbMydOxdisRiLFy9GcnKyzdJe1243P/DAAwCAjz76CDqdDq+88orVuVob80VE3c/11zQROc+sWbPw/fffY9asWRg4cKAluU1NTcWlS5dw++23w2g04o477sDIkSNx+PDhVs/z7rvvoq6uDi+88IIlkX7kkUfw+OOP45577oFCoUBCQgJCQkJQWFiIiIgIq+OvjdEWi8XQ6XS46667MHr0aMe++B5IJLR3f4KIiIiIiG4Kh44QERERETkAE20iIiIiIgdgok1ERERE5ABMtImIiIiIHICJNhERERGRAzDRJiLqI9atW9dmmeSvvvoKn332WRdHRETUuzHRJiIipKeno7Gx0dlhEBH1KixYQ0TUQ9XV1eGZZ57BpUuXIBaLMXDgQMyePRtr1661lE0+fPgwXn75Zcv2hQsXsHjxYtTU1KB///5Ys2YNDh48iN27d+PAgQNQKpX49NNPsXr1aowdOxYA8Oyzz6Jfv37QaDS4dOkSSkpKUF5ejoSEBKxduxYqlQqlpaV46aWXUFxcDIPBgNmzZ+M3v/mN094bIqLugD3aREQ91M6dO1FXV4fNmzfj66+/BgCbSq3Xy8/Px7p167B161YIgoD33nsP06ZNw5QpU7B8+XIsXrwYixYtwvr16wEAWq0Wu3fvxu233w4AOHr0KN566y1s374dUqkU//u//wsAeOqpp7BgwQJs2LABX3/9NdLS0rBt2zYHvnoiou6PiTYRUQ+VkpKCnJwcLFmyBB988AGWLVuG8PDwdo+ZNm0avL29IRKJsGDBAqSlpdnsc8cddyAtLQ2VlZXYsmULJk2aBA8PDwDAzJkz4evrC7FYjDvvvBP79+9HfX09jh49irfffhvz58/HwoULUVxcjLNnzzrkdRMR9RQcOkJE1EOFhYVh586dOHz4MA4dOoT77rsPqampEATBso/BYLA6RiKRWP5tNpshldp+DXh4eGDmzJnYsmULtm7dijVr1rR5vFgshtlshiAI+PLLL+Hi4gIAqKyshEKh6LTXSkTUE7FHm4ioh/r888/xzDPPYNy4cXjqqacwbtw4AMDly5dx5coVCIKA7777zuqY3bt3o6amBiaTCevXr8eECRMANCXQRqPRst/ixYvx6aefQhAEJCUlWdp37dqF2tpamM1mrF+/HpMnT4ZKpcKQIUPw8ccfAwA0Gg0WLVqEXbt2OfotICLq1tijTUTUQ9122204cuQIZs2aBRcXFwQFBWHJkiWoq6vDggUL4Ofnh0mTJuHUqVOWY2JiYvDII49Ao9EgJSUFDz/8MABgwoQJeOWVVwAAjzzyCBISEuDp6YnU1FSr5/T19cVDDz2EqqoqDB8+3DLh8W9/+xtefvllzJ07F3q9HnPmzMG8efO66J0gIuqeRELLe4xERERomjS5ZMkS7NixwzIcZN26daiqqsLq1audHB0RUc/AHm0iIrLy9ttvY/369XjxxRctSTYREd049mgTERERETkAJ0MSERERETkAE20iIiIiIgdgok1ERERE5ABMtImIiIiIHICJNhERERGRAzDRJiIiIiJygP8PjqM5W7RG+hcAAAAASUVORK5CYII=\n" + "image/png": 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\n" }, "metadata": {}, "output_type": "display_data" @@ -1052,33 +1135,27 @@ " **fig_args, plot='stripplot')\n", "annotator.configure(**configuration).apply_test().annotate()\n", "fig.savefig(f'flu_dataset_log_scale_in_axes_strip.svg', format='svg')" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - } + ] }, { "cell_type": "markdown", - "source": [ - "With a horizontal orientation" - ], "metadata": { "collapsed": false - } + }, + "source": [ + "With a horizontal orientation" + ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "p-value annotation legend:\n", - " ns: p <= 1.00e+00\n", + " ns: 5.00e-02 < p <= 1.00e+00\n", " *: 1.00e-02 < p <= 5.00e-02\n", " **: 1.00e-03 < p <= 1.00e-02\n", " ***: 1.00e-04 < p <= 1.00e-03\n", @@ -1091,16 +1168,16 @@ }, { "data": { - "text/plain": "(,\n [,\n ,\n ])" + "text/plain": "(,\n [,\n ,\n ])" }, - "execution_count": 22, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": "
    ", - "image/png": 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\n" + "image/png": 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\n" }, "metadata": {}, "output_type": "display_data" @@ -1128,18 +1205,91 @@ { "cell_type": "markdown", "source": [ - "Back to vertical, with a different format for pvalues" + "#### Hide non significant results" ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "p-value annotation legend:\n", + " *: 1.00e-02 < p <= 5.00e-02\n", + " **: 1.00e-03 < p <= 1.00e-02\n", + " ***: 1.00e-04 < p <= 1.00e-03\n", + " ****: p <= 1.00e-04\n", + "\n", + "H1N1_Nonsynonymous vs. H1N1_Synonymous: Mann-Whitney-Wilcoxon test two-sided, P_val:5.014e-04 U_stat=2.624e+03\n", + "H3N2_Nonsynonymous vs. H3N2_Synonymous: Mann-Whitney-Wilcoxon test two-sided, P_val:1.294e-03 U_stat=1.535e+04\n" + ] + }, + { + "data": { + "text/plain": "(,\n [,\n ,\n ])" + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
    ", + "image/png": 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ob3FEkGtbrVaRMyKBr109iuc6peV0FhPpGwWaOymdA3m1bDpQGjCXpDfBgvyJWfEsmzOUX7yys9vtLDYnj/11i9Lg3X64gqsuG8wdV40kOiKEowV1vLHmOI0tdhZMSeem+cOVScAnSxpYvTUwyAdY/kW+EugDfO+OSeSMSKCkqoUpoxMZN8wXXHettLN4egbPv9cxCjV9bDJuj5cf/HkTucUNxEWG8MitOcq12vkzf7Sgjif/vk1Jp7t6xhCeuG8aq7YW8PLyI37HMYXpCQvRsWBqOgumDAJ8o2tdGXQaoiIM2Owuls7MYE5Oml96YncWzxjC3hNVDEo0ER8dis3uor65lddWH2Pn0Uo8nX4TnG4P727I5eGbxmPp0qBttpzZKKMQA4EE+pcwU5iepx6agdnmJFSvGfBVDCLDDdy8IIt3PskFfMHqbVdcmJxivU7D/96Ww/PvHaDJ7GB4ehT3LBlNtCnEL50gKsLA1TMy+uWYbk/gD2WwH8+zkT001q93Li4qlDFDY6nqktO+cnMBKzcXoNepuXHecO64ciQAKpWKCKOOkE4BWmxkKPdfk93nc/jbfw8qkyINeg3fDJLP3zVnv6sRg2OIiwyhtlMjxRSm58HfbsDrhRhTCL/59sxeR0FOnm5QgnzwlRq8++rRqNUq3G4PGo2aGWOTWTozg7U7ivB48QsuAGZPSPV7PGlkIqnxYcqIT4hew6Jpg0mKNVJY3sTWQ+XoNGrGD4/nt6/twqDTcOdVI8nOjOOZN/ficPp6KD/fW0pKbBi3t733eSX+aVNuj5ePtxb5BbO5xQ0cKagle2ic37qjBsfQVWxkCHNyUpk0MgG3x8vm/aUczq8lKiKEZbOG0tDSyk9f3KYESbddMYI7rxrpt4+CsiZ+9PwWpXHzxb5SXnxsQdAG5YpN+byyoiNQvO7yzKCTtpNijby59jif7Cwm3Kjn7sWjmJbt6x0/cip4+o5KBYvbrj+tRs0P7prEN67LZs/xKv707v5uA/7O1aMA9Dp1wLWWGBfG5FFJpCWEU1odOHfEl9vvVYL8dmt3FLP1UDm/eHA6v3hlu9Lz/PrHx2ky23E43UwZk8RLXSaEd9Z1VEenVfdpJPPKywYTGxnC7mOVDEqMYNFlg3nu7f3kFvs+Q7VNrfzf2/v45xOLAkbu3t940u/6W7u9iFuvGMGyWUPZdqhC+c7T6zT85OtTGZ0R67d9VISB6HANDeaObv24qBAqai14vHA4v47r7C6GpkYydXQiu475jxTMnpBKclwYkWF63lx7ApvdhVqtYsqoRPbn1SjXRzBV9VZarE60GrXfa5g78dzL/4qBZ9WqVaxcufKMt7vqqqu44YYbzsMZ9S8J9AeAYL2aA9WdV41k9oQUymstjM2M61M5t/5yWbavEkqL1eFX3eNXD81g97EqLDYnl2Un9Vh55Uz4evr8f/kdvY2Fn8G+n7x/GofzazFbnUwcmcDH3fQmgq+B8fb6XMYNiyMtIYJf/3MnJ4obMIZo+ca1Y1k4ddAZHb+uycba7UXKY7vDzZodgcdvtfecN67Tqvn1t2fy7id51DXZmDwqkX+u6hiur29u5d1Pcvlel4mdXb213r+Xu6rexoG8at5Yc5xTpU3odWruWzqGb94wjruXjGbFpvyAnvGuo0t6nYZnH5nDht2nsba6mDspTbkPwo/unkKzxcGB3Gqe+XdHJZ7f/Gs337t9YkAQc6JTCtDYobFKlZ7296A91aKzT3eXBAT647PiuWfJaD747CQWmxOP1zeS8+Hn+Wg1alqsTr+/y383nmTE4Gi/ntD3Ps1jycwMv2N+trfEbwSj0Wxn97HKoHnVKzfl+z3+eGshs8anBqz36a4S1rSdS32znadf380rP7mC2MhQ9p4Inj7iy8X2D4ojww0smDKIwUkm/rXal57WOUUsLFTHN68fy6otBThdHhZOGcTqrYUBqXpHTtVyJL82YPThsjFJJMYaUatVrNhUQDAtVic/f3mHEuS3a19/zfbioNu1u3xix/vz7oZcVnxRgEaj4taFWSztVBknmMmjEv3mfOR36UFvbLFT39wakLrVuYoP+NKVHE43KpWKXz44nc0Hysgtrmdfbg0/en4LozNi+MGdk5VGm0ql4uZZsWw4ZKeospmsQVF+c3sO59eyZlsRN8wbxvdun8idP1vrN1o7b1IaU0Yn8dhftygpSB6Pl51H/auRBX3NIxP5bE9JQEdBSvzATW0VF1Zenm+yuAT6QpwHg5JMDEo698muxwvree3jYzQ0tzJvcjq3LszqtY64VqMOKOGn1agZnRGD3enutyAfINiZ9GfVHZVKpQz5AwGTF4MpKGti84EyTrT1CFpbXfztvweZlp2kVCvpC7vTHZDn7HYHdmd2nXxcWWfhsz0lnCxpxBii47q5mQxLi+K7t09Uzq9rT3t9c/Bc7s6C5Xv/c9VRiip8+f4Op4cXPzzMzPEpREWEcPWMDNZuO0Vdsy8AGT88jokjAyfQhhv1XHf5MN/8kvw67A63kgJkCtPz5trjAdvsOlZJqEHjFxRmD+3oLb1qRgaV9VY27ikhMtzAvUtH43D4qvt01nlyK/gqBu08WklaQjjPfGc2D/1uo9/za3cUYbX5N6zcHm9AaoXb46XF6vAL9IOl0LWn3mw/XM6hU7UMT49i7sT0gJ5jjUZNdmasX568Rq0KSLNwub0cK6xn9oRUBieZaGgJzOsHeOrVnfz6WzP9llXUWth9vJKDJ2v9li+cks7dV4/m/c9Ocrqypa286emAIB+gpNrMT17cSteBtj0nqjCG6HpNCzmXtJGj+b7e860Hy3lzTUcD8+8fHiZrUPQZ3RxrWHqUX/UclcqXErgvt4q31p5Aq1Hz9WvGMGV0IofzO96v5LgwJR1Lr9Mwb1I6b6/PVUYBjxXW8/KKw8pEeICUGD1/+v50wFcd6kRRR6MWoKLO9z4fPFUbMFl397EqpoxOorGl9+u3s5wR8SydPZTVWwIbXd2V8hRfbUuXLmXp0qVntM2DDz54ns6m/0mgL76SrK1OfvHKdqXSyr/XniAyTK8M+5+Jf3x0lJWb8nF7vEwelchj90zplzJ7XStrAJyuMhMTZDJpf4iN6rkRoVLBuOHxAQGlw+WhotZCxKC+B/opceEkRIdS3dCR5jBjXDKFFc1+6QtJMR09cOt2FPHX9w76jXHsPFrBi48tUHKLM1JMhIXq/HJzu6YUBKPXabB2qboTLD3j092nuXG+726o31qciDo8jRC9luzM2G4biZsPlPHsm3uUhs03rs3mmjmZANQFaYQUljfx6N1TeOG9gzSZ7UwdnURNg41H/7KZ8cPjuWVhFvdfk+2XJmV3ugPmkIzoVLZz5aZ8Xm5Ll9l5NPjkV6fTg1ajxu3x78nVadW0durdHTEo2q+EbGF5Exark+gIg1LnfuKIBHKyEnh/40leW31MWTfvdCO3XpHFc+90pNHcNH84C6cOoqreyrqdxYSH6vja4lHUN7ey9VDHyIVKhVJR7MHrx/Lk37dQ2xQYPB86VUtpdYtSMWr1lgL+vjx4WkxUhIFf/2uXksoCUFwZWEmmXZBsOlxub7/lfht0GuxBUlJKqs188NkpXv/4WMBzxwrrzyjQT+xyAzqv11eN56NOk4B/+OfNTOhSdae63kpji11p4LVYHQGpfscL61mxKZ/jhfWMHBJNirHjTc/Jig9owM5om6jctcIYgCnc930yb3K6X+Oma5qVChicbOKeq0eRlhihNEbmTU5nxaYCpaGfHBfGjAtYjlmILwsJ9MVX0onihoByintPVJ9xoJ93usGvZN+e41Ws21HENbMzz/kcUxPCKa7o6JVVq3xl886XkYOj+XxvadDnDDoN37llAkOSTUweleDX0xcbGXLGN7RpaG6lpsE/l/nQqbqAYMzl9gUFbo/XV0Gjy35aHW52Ha1U/m7VDbaACXh7T1Qpcwu6E6xhptWoleO3i430TQTcfKCMU/kW7lgWHTRtprN/rz3hN3rx1vpclswaikatIiJUT53TP9hPignjk53Fys2ath2uUBp9x4vqsbY6+UaXqk4GnYYf3T2Zv/33EJV1FiLDDeQWN7BxTwnzJ6fz2T7/v2t+aVPAxPaU+HAuy07mrXX+KUnLZmeSlhDO9sMVJMUauX7uMOW5fSeq+cWrO5RRlBGDovn6sjHK57Tr5NJ1O4q5/5psMlIiOZxfy/C0aEZl+OYN3LV4FHd1qvHucnsoKGti454SjCE67r56lHKn1vTECH73P3O4/9cbAt5vlQoMOt9Pm9Pl4Y01x7vNfa+otfoF+RfKhKx4DnfpxdaoVfzm2zP5/Rt7AgLosZlx/Gv10aCv40zLKcfFBFZXOnjKf6TD68WvbC0EjuREGPUBnyFrq1OZf7H1UDmThoUxdYrvuchwA796aCb/2ZCHze7iqsuGKJOAxwyNZfrYZLYf9tWsTY4LY8lM3zV9y4IsosIN7MutZkiSiWHpUfz3s1OYrQ6uvGwIy2YHT12KjgjhLz+Yx+YDZWg1KmZPSD3nYhVlNWYqai2MGRobdAK5EF9G8kkVX0mDgtzU6mxuphKs17csyLKzMWFYvF+gHxluCMg/7k89pe5MHpXI5W0T2a69fBitDjdbDpaTGGPkniWjA9IxemO1uwKCdpfbQ4RR71dqb0Tb5FG32xPQ494urlMPZX5Z4M28KoKkYXQVbGJfzoh4th/uGL3QatRMHJnI9/+0SUmL2Z77GX/87uV+59BV1/r0Dqe77WZMKm6/cgTPv3fQ7/nLJ6byf50qynQd2dl2qDwg0AeYkJXA778zmwd+vZ6GFjsNLXZyixswhemJ6ZJuptequfbyTN779CTg67W/b+kYxmfFMzYzlpWbC3C5PcwYm8KCKemoVKqAycYAKzfn+6VK5Z5uINrU0fAJ6ZJ6ZdCpUatVZKRE9lrFSKtR88itOXzrxvGo1aqAtIuEmDAmDI/jQJd0nEXTBit54i63J6DEZGdWe/ASmpNGJrQ1qvy3TU8IpyTI9a3XqnudON7ZuGFxTM9O5m8fHFKWfeO6sWQNiualxxdSUt3Cii/yyTvdwOihsYzNjO22rOWHn58iO7PvHQDzJqbx6e7TSgNnQlY8Wq3KryxtMF1Hchwud0C6Tdf34GCh/7WXNSian943Lej+f3zvVPJON2C2Ohk7LE658aNKpeLKy4Zw5WVDlHWn9LFEpilMrzQYztVb607w9vpcZb+/emhGr59hIb4MJNAXX0nB8rZ7quLQnZysePQ6jd+27ZVBztXhLvcM6M86+sGE9dDb5cW/5/GOK0f22kvek9T4cLIzYzmS3/EaF8/IICpczwvvH6Ky3sKUUUnKXTz1Og1zclL5rMuIw4xxyUzqlBs/MkhVmbSE3t+vqE5pJ+2umZ1JemIEG3eXEhcdwgPXZHMwr8Yv973RbOeTXad7vKPs1TMy/MppLpo2WGkYXXnZEEprzHy8pRCNxve+hob0/LWc1MO9Mg6erKHV4R9s7ThSwZ1XjST3dD1NZgdqla/3/Pq5w5g9IZXiimbGDY9XGrrZmXFkZ8YF232AYOlK6k7L7lg0kmf/3ZG2dNuikWecJ93Tnb6femgme45Xsj+3hhhTCCMGR/ude6hBy6wJqWzaXxZ0+yunDeFYYb3fxNPrLs/k/muy2XWskqde9S+lec2cTDZ0CpIBNGp49pE5FFc28/flh7utv98uJyuepbOGEmrwpXydKG5g5OBoZd6RWq1icJKJR27NUbax2JwYQ7RBG7u7jlVSUWtRRjt6E2LQ8sx3ZnO8qB6tRk3WoGjKa8zsP7Ex6E2tpoxKZEiKyW8kByBEr2XiiAT25XZ0EBgNWqydGlZhhjNLYTyTFKQLqbHFzn825CmPmy0O3vkkl8fvmdrDVkJ8OUigL76Sut6YCbrWt+mbaFMIv3xwOv/ZkIe11cniGRl+d7E8F4MSI/wmQhpDtP06GberG+cPY8+JqoDUFyDo/QLO1RP3TePjbUVU1FqYPjZZqQzy0o8XKiUtO/vOLTkMTY0iv7SRpFgjs8anMDjZv0ctxhTCdZcPZfkXvol4oQYt375pQq/ncusVI3j6td3K4+S4MEZnxJKdGcfXFo9WllfWBaY2eVdD4sIAACAASURBVHsp0n7LwixSE8I5fKqWYWlRzJvsX4nm/mXZ3L+sI9/+RHF9110oeckxJoPful21V/XpumxoaiSv/OQKcosaSI4PUyqs9KVnvSc3zB3GgbwapeLOnAmpfvXzZ+ekkpkWyeH8OoanR51xildfTB6VxORR3ffw/r/bchieHkV+WRMhOg3Hi+rxeL1cf/kwZo5PITHGyIq2kYlls4YqN+maPDKRWeM7bkw1blgc8yanMzQ1kqde3Umj2Y5Br+G7t00kIzWSjNRIHC4Pz793IGiKjUoFL/xwHmmJHYUE+lpYICxUxy8fnM6ba0+QW9wQMEpxpo0nlUrlN3clJT6cfzyxiKde3cmp0o5RsUFJETz5wGXd7ucHd03i32tPcKq0kXHD4shINvF/b+/H5fbN91g0cWD0eLdYHQGNoCaz1OQXlwaVt7dfKXHG7HY7R44cITs7G4Oh5/zdL6u9e/cyaVLPJQkvZR6Pl+//6QtOlfoCaa1GzW8fnhm0R/hiqW6w8tSrOymqaCYsRMu3bxrPnJzzWwfabHWw82glr6w44jex84n7p11Sd5Q8XdlMZb2VsZlxfc6l3XW0ki/2lxIfFcq1l2cGVFcCXxrO//u/z5Xa+BFGPc999/KAu+ieC4/Hy8PPbPRLC/v+nZNITwhnUJKpxx5ugH9+dJTlm3yB64Th8fz461PPaz5xea2ZXUerSIo1MmV00oCrbFJa3YLL7WVIckdA7nS5KSxvJjU+PKDEb3FFM8eK6klPCOfdDXkcyKvBFKbnO7dM4LJ+GO07nF/Lz17arnRWzJ+crlSdOlcut4d3Psll19FK0hMiuHvJaBLP8LPd0NLKqZJGhqVFUXDy6ID5HfnBnzb53en6O7dMuCB3ZRdfTu1Vd1566aVz3te5xlu9xZwS6J8HEuhfGqytTj7dXUJDSytzctL8fsi/TKrqrURFGPqlkk9flVa38N6nJ2m2OFgwJT1onfOvKovNyef7SikoLOaOZdMC7qDbH5rMdlZsyqe20cacnDS/Ouh90dhip9Xh6vHutOLCaLW70Os0ATe9OheVdRZ2H6siOS6MiSMS+nXf/Wkg/Y60WB0s/yLfNwKZnczsHPlO/Cq7lAJ9Sd0RX1nGEF23FRu+TM60R60/pCVE9Fsv4UATFqpjycwM9obUn5cgH3wTr+++enTvK3bDVxnl0uxkGGhCzsNoSlJs2CXx3TWQRBj1ypwhIS4lZ1YqQwghhBBCCHFJkEBfCCGEEEKIAUgCfSGEEEIIIQYgCfSFEEIIIYQYgCTQF0IIIYQQYgCSQF8IIYQQQogBSAJ9IYQQQgghBiAJ9IUQQgghhBiAJNAXQgghhBBiAJJAXwghhBBCiAFIAn0hhBBCCCEGoAER6JeWljJ//vyA5SNGjMDtdvPkk0+ydOlSli1bxkcffaRsM2LECLZu3eq3zfz58yktLQXg+eefZ8mSJSxZsoTf//735/+FCCGEEEKIAcHtdrN8+XLsdvtFO4cBEej3ZOXKlZjNZlatWsVrr73Gr371K8xmMwA6nY4nnnhCedzZtm3b2LJlCx9++CHLly/n6NGjfPLJJxf69IUQQgghxCXm0KFDPPLII6xevRqLxXLRzmPAB/rXX3+90htfXV2NTqdDp9MBkJCQwIwZM/jd734XsF18fDyPPfYYer0enU5HZmYm5eXlF/TchRBCCCHEpWfkyJFotVqKior42c9+dtHOQ3vRjtzPqqurufbaa4M+p9Vq+clPfsKKFSt48MEHMRgMynOPPfYYy5YtY+vWrcycOVNZPnz4cOXfRUVFrFmzhrfffvv8vQAhhBBCCDEgFBQUcMUVV2A2m/nDH/5w0c5jwPToJyQksGLFCr//Ovv1r3/N5s2bWb9+PVu2bFGWh4eH89RTT3WbwnPy5Enuu+8+Hn30UYYMGXK+X4YQQgghhLjEJSQkMGrUKFwuF16v96Kdx4AJ9Ltz5MgRioqKAIiOjmb27Nnk5ub6rTNr1qygKTx79+7l3nvv5fvf/z7XX3/9hTplIYQQQghxCbNarTz99NO0tLTwxhtvXLTzGPCB/sGDB3nmmWfweDyYzWa2bNnCxIkTA9Z77LHH2LJlC9XV1QBUVFTw8MMP8+yzz7JkyZILfdpCCCGEEOISZbPZsNvtGI1Ghg4detHOY8AH+rfddhuxsbEsW7aM22+/nTvvvJOcnJyA9dpTeJxOJwCvvvoqdrudp59+mmuvvZZrr71WcvSFEEIIIUSvUlNT+cMf/sDYsWP95oBeaCrvxUwcGqDsdjtHjhwhOzvbb+LvpWTv3r1MmjTpYp+GEF9aco0I0TO5RsRA9eCDDwLw0ksvnfO+zvU66S3mHPA9+kIIIYQQQnwVSaAvhBBCCCHEACSBvhBCCCGEEAOQBPpCCCGEEEIMQBLoCyGEEEIIMQBJoC+EEEIIIcQAJIG+EEIIIYQQA5AE+kIIIYQQQgxAEugLIYQQQggxAEmgL4S45HndLlrL8nC1NFzsUxHnkdvWgqfVcrFP44LwOO1YT+7FXlHge2y34rHbLvJZnTmXuQGPy3GxT0OIryztxT4BIUT/cttaMB/+Aq/bRfiY2WhNsRf7lHrlaqmn9uMXaS09gSE1i/jF30QbGd+nbZ315VT8+xe4mmtBrSFm/l1ETbvmPJ9x37ktTaiNEahU/v0qruZamnatxtNqwThsEi5zPdrwaIxZU1CpNed0TPOxrVjzdqOLSSFy6hLUIWG9btNamov11D70CYMIG3nZOZ9DO6/bhSVvF25LE2EjpqGNiDnzfXjc1Kx+EfPhz0GlJnLKYmIX3tsv53euHDUlmI9tQWOMJGLcPNSGULweN60lJ9CERaKPSzvjfTobKil//Qnc5nrfArUWPG5QqzFN9r12Z00JTXvXoFJrMU268qyOcz65rc1EbHqR02vrQaMjdsE9RE5ZfLFPS4ivHAn0hRhAPHYbZf94FFdjNQCN25eT9sCzaE1xF/nMelaz6gVsBfsBsOXvp/qjv5By1y/7tG39pnd9QT6Ax039Z/8mYuw8NMYI3yKHjZYDn+Jx2jFNWIgmLBJXUw11n76Go7qY0IwJxMy/C7XO0K+vyVFbStUHf8BZcxo0vq/asOFTiFvyLVQaLWX/+jHuljoAWg5+qmwXmplD8m0/PevjNu9bT+2av3c8PvAJqfc+3WODz3xkM9UrnlMeR4yfT/zSh8/42I66cpq2L8fdasY0YQHGYZOofOdX2IoOA1D/+VukfO2XGBIzzmi/lmPbMB/a6Hvg9dC08yOMmRMJzRjX43aeVgu208fQxaaij03p8/GshQep//xtXA1V6KLiib78doyZOQHrtZafouL1n+J1OwFoOfQZiTf/iIo3f4aroRKAiImLiF/8zV6P6XU7aTn8Bc76Chx1ZR1BPoDH1fZ/N827VqExRtLwxVvg9fqOe3Aj6Q/9+awb9bbyUzR+/hbamCTiFt2vNPK8Xg+OykI0ETFow6PPaJ9VH/wBrbXtNbid1K1/lfDsWWhCI87qHC8Gd6sFtVaPSqu7oMdt2rWKpp0fgVpD1MwbME1Y6Pe8teAArSXHCUkbGfRzKURnEugLMYBYcncoQT6Ax9ZCy6HPiZ5100U8q961nj7q/7j4WJ+3dTXV+i9wu3BbGtAYI3A77ZT85SE8rWYAGje/R9o3/0T1h3/AXpEPgLOuHFvhQXTRSYSPm0f4qOnn9FpsRYdp2Ppf7BWn8LanWrh9gZrlxHbUoeEYM3OUID9g+/z92CsKMCQPPavjtxzc6PfY3VJP2Ws/ZtDDL3TbS9+48yP/fRz6nJgFd59RUOax2yh//Sd4rM0AWHN3EbvoPiXIB/DarZS98kM0EdHELbqfsJGX9WnfjprTQZf1FOjbSk5Q8e+fKe995MwbiZ17R7fre71ebAUHsJ7aS/OeNcpyu62Zyv/8lvRv/QVdVKLfNi371ilBPoCjsoD6Da8pQb5vnfVETroKfcLgHl9j1Yd/xJq7s8d12jXtWK4E+QBeZyuWE9uJnLoUj92G29qELjqpb/vat5669oZh4UHMBz8j40dv42qupeKtX+CsKwe1hug5txE98wbA14ByNlShTxiEShM8jLBXFnRZ4sVacJCIMbP6dF4Xk8fRSvXKP2PN3YXKEErsvDsxTbrqghzbWniQuk/+qTyuXf03DIkZGJIzAWjc9iH1n72pPB99+e1f+u93cXFJjr4QA0mQQE6l/vJf5u0/Yt097kn46Jl+j/UJg9DFpQPQtOU9JcgHX69p7fpXlCC/nbOuDOupvVR/8CyWk3t6PJ7b1kLDlvcxHl2DrUsDxdVUQ+U7v6a16HBHkN9Fa8lxXJbGHo9R+d5vadr9cY/rtGs+8ClV/32G+i/exmO3Bk3TcTfXYi872e0+Aj4jKhWozuxzYy04oAT5Pl4sJ7YHWdOLu6WequXP4ba29GnfoV17LVVqQodO8O2tU6DdWfWK55QgH6Bp6we4e8jvr1v3CpXv/MovyFd43NgKDgYuDxLkBptD4DL3PHfE1Vzb5yAfVEFz9dWhETTvXUfxn+6n5IWHKX310V6PC1C/8Q2/x16Xg4bty2nY8l9fkA/gcdPwxdu4muswH91M8Z+/Qdk/fsjp57+FvapI2dZaeJCGzf/BWnAQXZDUu9D0kQHLWg5upPTl71L6yg9oOfgZrWUnA3L6vV5vt3/n86Fp9+q2v4cXr91K7bpXcTZV97pdf2gtPhqwrPP3TOPOlX7PNXV53Bceh42a1X+j+M/foOLtp3DUlp75iYpLhvToCzGAhI2YRmNcGs62L25NeAzh4+Zd5LPqXdySb1Oz4jnsFfnoEzOIX/Y/fd42csrVqDRaLLk70EUlETXrJlQqFQDO5vqA9T2tVjTh0bi7CYIsx7YSNnxy0Oe8Xg8Vb/4cR3URBqDijQMk3fYTZfjcWnCw14AkJDULbXjPKRbulnrq1r+KLiZZ2bfX66W1+AjOunJCM3PQRSXQuGMl9Z++pmxnL8vD0ym47UwTHtXt8SLGz8defgrw9RKbJl2Js7aEppN70cWmED5mdrc9t+08NnPgMocdbWQCrmBBktuJ5fg2NBExhA4Zi1of0u2+VRodUbNvxnpyLyq1hqgZN+BqrqXynV/jaqrBOGwi8dc8giY0vGP3zV1HTHwNDE2whpCtheZ963t8ffr49IBlIWmjaOm8nVaPafJibIUdjQKNKY7QQWN63Ddqja9h5fX0vJ5KTfy1j9C4fQXOqkL/pwxGala/oDRuHJX5NG55n7irvtHt7iwn9+B1BDYa3C11gX8zrwdnYxW1617B67T71jPXU//p6yTf8WRAT7NpytXY68pRtV0PocMmYTmxg9DMHPSxqYCv0Vuz6q/KNjWrnve9HUYTSbc8TkhqFtZTe6n5+EXcLfUYs6aQsOw7fZpzcra8HjetpbkBr91RfRpdZMJ5O247Q/KwIMs6Oj66zvU50wY5QP3GN2k5sAEAW0s9Ve//nrRv/kn53hQDiwT6Qgwgap2B1K8/jeX4drxuF2Gjpl8SObH62BRS7/s9XpfzrPJhTRMXYZq4KGB5xJhZWI584bcsfOxcdJFxVK94Lmhw2tN8BnvZSRzVRZ2WeGk5sEEJxvVxqT2eZ2hmDjHz76a1pG+pSbbCQ8q+69a+TPO+dYAv8E26/aeYD38WsH6wUZ2wsXO7TeWwlRyndt0rtAf5mohYDCnDKX/tp8oy66l9JN7w/R7PVRcTuH+V3oCrMj/I2j61a1/yHTMsipS7f4UuJtnvea/LScU7v6K1+AgAIYPHkHTLj/F6vZQ835GSZT21l4Yv3u4xqAVfr3c7t6WJxh0rcDXVoE/O7DHINg6fQkj6qIDlzfu7NA5cDrweF/rEITiqikCtQR0SRsnf/5fQIWOJXXgPaoMxYD/a8Ggichb6NxqC8XoIGz6Zln3r6dqcbN650m8EA8BeXdztruwVBVS99zu/FKB20XNux3JiO7aCAx3nGJWILiY54JpxNlYB0Lhjhd9y85FNNM7/f4yKD6Vl/wYsx7dhO7UXPn2dpFsex5iZg7XT/jvzWJup2/Avkm9/ksr3n4G2xoI1bze1G98k4WrfnAev10vD52/RvHctKp2B6Dm3YcpZGHSffWErOkz1ij/7z48AVLoQQtICRyPOh7ARU4mcfh3Nuz/25ehPv86voRg18wbq1v+j4/GMG874GLbCQ36PnXVluFvqLshcLldzLbbCQ+ji0ghJzTrvxxMS6AtxUbmtLbQc2ojHbiNi7OUBgc7ZUOtDiRg/vx/O7sLr70lvzvrygGXeVjPGiVcQf80jVL37G//jG4xETl3a7f6C9SSqtHrl3yHpo4ictsyXduNxB6yrTxiMSm/oc4+kPsk3adVlbqB5/ycdr8HtpHHbh6jDooCO/HWVVo83SI9+RPacbo9Rs+I5v3N1t9TRsPk/tAf5AJbj23C1fL3HijleT2DA6Gys6Xb9ztyWRhp3rCD+6of8lpuPb1OCfPClNRT93z2g0oDL7rdua1kezoZKtFGJvp7JIAGsu9WMNjwKr9dLxVs/x1F9Wnl9PXF0EzC76isCljXtWuML8gE8bpxt27YcqMLrdpFwzXeC7ivuqgdpLT6Ks66s2/MIHToer8uFOixwYmznuTmKHhovlpO7A59XqYleeA+aECOmCQvA68VybAsaUzzRs29CGx5NyKDRtJ7uaKgqc1oCeoNV6OoKaS4uxpq3u2Oxx03jjhUYM3PQ9tBD7mqsprXkuBLkt7Od3A34An3L8W00bvvA94TdSu3HLxKSloU+flC3++2O1+uhZtVf/YJ8lVaPPimDmLl3+I0WnW+x879GTNt8kq7zaiKnLMGQPKxtMu6IoA3Q3ugTh/h9N2rCotCEdT/i11+shQepeve3yqhn1IzriZl313k/7ledBPpCXCQep52yfz2mTNxr2vURqff9XhnWHqhcTTVY8najjYjFmDW538o4BhVkWNtt9+VQhw7ODkjhiV/yMJqwyG53Fyy9pLXMf5g/duG9RM24keI/3huwbtP25XiddmIX3Y8hZTj28m7y5lUaTDkLCW+buOh1OwOCMq/LgT4pk9ZOvXMqfQhaYyTO2pJO+1IREiQ3GnxpCgGTmQFPkNx5S+4uIid3PyHRf6Sjbf9B0kK647EFHjNoj6/bBQQ2Zhw1JZS88DC6uDSSbnmczg2Vdu2xqKOyUAny+8JlCZ7m5bZbA5bZq7pOQu1gzd/X/TEaqwKCfG1UIqFDxuKoOY0+cQieVgvFz93ne1KtBk/HZ0KpPNWJty3X3dlUjauxhpDULKUxHbRTweuhYcO/CB00hpCkDEw5CwN6yBNv+AENm//jq1g1dAJRM65vS/vyZxw2Cc++9wl8h1BGHlwtgal17cJGzQg+56hTdazW0hNdXwCtpbk9Bvq24mNYT+4idPhUjINHd2zpaMXV5N8wVYeEkXrPb3yjP9s+xOt2+kYEo85/Ck9P34shaSMISRtx1vuOXXgvruY67GW5aExxxC/9dq+pef2hccv7fqmNjTs+InL69UHT6S6kVatWsXLlmc11yMvLIyvr0hiRkEBfiIvEemqvX3UOr6OVloMbiZ3/tYt4VueXvSKf8jeeUHJ8jcMntwVl50ewEYL2iYxqnYHku35J47YPcJsbiRh3OeGjeq4C4wjS2+pqqMJ2+qjf8LqvtKeKYMGmJXcnMXPvxNnpbw++3nt9bBqR065BF5fqV+5TF5mAMWtKp55RFabJVwdMHPVYm4lb8m3q1rzk65nU6Ii78oFuS4eq1Bq00Ul+n0OVzuALIruoW/cy2ohowkZMC7ovfWJgVRmtKR5na2B6VJAzIWKc/yiUx2HD0ucJqig9v87aUuo2vB50lfa/vSbM1Pf9AhqDLxDxej3Ub3gd85FNvjkPrsD5GCqvJ8hf3aenyjua0AhfS6TTSIQ6NIL4Jd8CoOXw59Ss/EvHBl7Qxg/CFaQiUbvQwdk0bP1AKcWpCY8m+c6fo49LI3zUDKy5uwInTHu91Kz8M+kP/tFvscfRiq3gIGpjRECKVPVHf/GbiK1PyuzhxmYqZdSsu4agxhRH5OTFaEyxqEPC/SbUR05dovw7JG2kL8Wlk64BsMdpR6VSo9LqqFn7Mi171wLQtPMjTJMWE3fVAwCoDUYMaSOwd8rPN2bm4LFbKf3Ho7jbGlJNu1aRev+zFyTYP1+0plhS7/2Nr3yoITQw7/888TjsXRa48Qa5hi4FWVlZXHXVhanEdK4k0BfiIlFpAoPQC9Grcq7cliZUWh1qgxGv10vLvnVY8/ejjx9E1PTrekxLadq1SgnyAawn9+CoLu619ODZCpaX3rlEokqF78fG7Qz8EQoiJDUrIBgD3+TZQMHDPV1MMraiwwE92Pr4wd2mdQAkXv/9tjrr5YRlTSUkfSTWU/ugc+UfjZbQ1CwG/+/LOJuq0YRFoe6UWhRMwrX/S+X7z+BpS1nQRiXitjQFXdd8dHO3gX6wyc0aY0RALnngSjqSbn0cY8Z4v8Wuxhpw9v43Caa7ORDOhhpCUobjaQ3azwyASmto6wnv+Pu52/5WdZ++QfMuXylStzX4e6SNS8dZEdjDrYtLI+7KB7o9rsvaHPC56tzD7Kgp6boJKrqfPKnSh2DMmkrFm08q+3WbG6jb8BrJt/0ElUZL4o0/oHbDv2juUl7V2XYsj8PWls+tonbdy8rn3DhiGkk3Pepbx2lXJv93nHc1hqTAeyWYJi8mPPtyQlKHAxAxbi7Ne9YoIw/t3M211H3yT5Ju/TGmSVfSuPUDwIvaYCRk8FhlPUP6KFS6ELzOVgA04dFo265vr9dD3dpXaD7wKSqNhqjp1wfMgWjet04J9MF3jdVt+Cf2ykJCh4wjdsHdWHJ3KEE++KoqmQ99TvScW7p97y8VF7on3TTpSmpXv6A8Dhs5DW0PRQIulKVLl7J0afcpm5e6L39UIcQAZczMwZA8DHtbUKAJi8KUEzih9Hzwul20luWiNcUF1AbvdhuXk+qVf8JyfAdofJPEVBodDV+8DfiCdntlPjGX30FTW09z5OTFGFI6qkgEyx/3ugNz2fuNLrTb43ndTsrf/LlSz761+AgqjZaIcXO73Z2ruS4w91utITRzYp9OR2OKI3bh1/EGyZ1W9XLDLpVWF5BGET3nZuylJ3z5thotsfO/htpoonnvWix5u9DFpBI188Yef0xDUrMwZk7A3FZ/31lzuttz0UR0Xy3IVy3EfxSjL6k78Uu+FRDkA+jiUtGa4vxSUkKHTsBRW4rX6cBjaw7Yxk+QBln7DaU8Qc5Ln5RJ1LRlaCJifMFxJ+0TMS1HNvV8yFATusj4gEA/bun/YBrfc/UrV5cRHgBvp3kIxmETadq+vONJtYaQQaNw1gSfP+B1tNK4/cOA98De5dyi59waEOiDF2d9BeWv/xR3kFKw1tydtJblEZKahVpnwJCahb0sT3k+dMhYomZcT9PxHajtvt5405QlxC26z28/+vhBpH79aZr3raN577ou55mPx26ladcq2j9THruVxk3vkHjjDwEwH9yoBPnga8hY83YRPmY2lqNblcnrXo+Lhk3vBHmT/K9DrSmWxBt+4LcsaIfMBb6B1kBhmrAAbUSM7w7ccWmX7FyyS40E+kJcJCqNlpS7f4Xl5G48dhthI6ZdkAlfzsYq3507m2oAFVEzbyRm7u29btdy8FMsx9uG+d0uGre8j6ZLrWxbwUHKTx9Xeugsx7eR9uAflZ510+TFWHJ3KXf6DBk05qxvDNXO6/VVvrGe3IsuLpWo6dcr72NL16oo+G5aFT3zelrL8gJuWmU5sb3HQL9zTnS7kEGj+twz1n7TKmthkJrsnuBlMXuii0wg7aE/4agqRmuKRWM00bhzJfUbfCU3bQUHaS3NJe3+3/e4H3vJcb/HXqcddVgknk49+9roJKKmXdPtPvRxaYSNmY3l6GbAiy4uDU1sKnSdh6DWknDD93DVVxA6ZFy3f3+VWkPSrT+m7tPXcNZXEDZiGjHz7qRu/T+VAK47oUPG4qguwVnXea6CmtB0X1qHIXU4+sQMHO0lKlVqYubfiTFjPLVrXgrYX/tcCZU+BLovxY9KBaGDRmPtnA6j0WLMnNDj+YKv4a/SGfxGvEKHdtw/IHTQGOKv+Q5Nuz5GpdESNfMGDIlDsBzf1uX+BR2Cpc8EjLgFmUQN0LhjZdAgv135az8mdMg44pf9DwnXfZfatS/jqMwnZHA2cVc+gMZoomnOtxkVq0driu02b16fMNg3Ebk0r+PvAYQMycZtafJ7P6DLBO8gDWZv28TywBt2ETCvAXwjEj3dFds4Yir6hMHKhGyNKU4C1HNgzMyRu/leYBLoC3ERqbQ6wkfNuKDHbNzy304pAV4at32AaeIVvZZWC5o60DUtRKPzG4b3uhxYTuwgavp1gC8ISrv/GczHt6E1xRLeQzWYvmrauZL6T9tysk/uxl52kpSv/RIAQ3w6XTPEtW25tdrI+IDa5dpe8m71CYMIzRjXUZ5OrSF6xo19Plevx93tJLuA97KPVCq1X5qE5Zh/BRlHZT7O+nJ0MSnd7sOQmoWzUwUZjSmO9If+rPT+qlRqDKlZPU4QdNSWYDna0ePtrC1FG2TCp8YUS3g36T9d6RMGk3x7R++6q6Xer/qQ/4614HahT8okdsHdlPz9//k/7/XgMjegDY9GpVKTfOfPadm/HldLPeFjZim99mpjYDlaXVvZ1Jj5d1P93+4bTR5rM5qIaExTrqbl4GdowiKJnf81tOGBVXKCSf3676he+WdcLXUYMycSv/Rhv+cjxs4lYuxcv2VpD/wf5mObUWl01H3yL78GoyY8Gl3cIJy1HXn80V3KMTbtWE5XKkMYntZebmbm9WIrPEjt2pdIuvkxkm/7SeA6Gm2fg7rEG75H7ZqXsFf50mbiFj2AxhiBPmkojk5Be/joju/LiHHzaNq9Win5yI81SwAAIABJREFUqY1KVFLLQjPG+d9MSqVGExGHu/P9AfpQCECt1ZNy72+x5u3G63IQNmLaea3jL0R/k0BfiK+YgEoXXg+uloZeA33jsIk0t01kA5RUkZqPnvdNllNrCB89E/Phz/2263qjJn3CIGISzrz8XXfMh/3TKVpPH8XVXIfWFItp8lU07V6tNGxU+lDiFt0P+HrDo+fc6isl6XGjix9E1PTea1In3vI45iObKDlxiGHzfL2qwWjCovx6RFWGUCVfPnRwtl/alkofimlS/0zs0ppi/ar5qLR61MbuKwkBxC64B7elCVvBQXRxqcQv+RZqnaH3Gz110rx/Q8AyZ2VhwLLwkT1PeO6J1+UI2ourDgkj6bYn0EbGdQTV3sCUMI+jI81DExoetAa5adJizEe3KKk0xqypyvsQPnIauvt+T/0X72DrroKOx0vcovuVz9mZ0Menk3b/M2e0jTYimqhp1+BsqKRu3St+z7kaq0m56+c07lyJq6GKsFHTA+4kHazn2+uwETF+gS9Nry1tRhsZj2FwNpZD/vduCLi51FnSxaSQfOfPA5Yn3fJjGrb8B2ddOWFZUzBNuVp5ThsZ72voHNnk6zQZezlqvS9dz5iZQ+yi+2navRq1Tk/UzJvwOFr9csRNkxf32JvfTq0zKKM6QlxqJNAX4ismPHs2toL9ymNdbAqGlMwetvAxDptE3NUP0bx3HWp9CFGzbsY4dDyh33kRe9lJdLGpaIwmXM21fjc4Ch81s5c9nxtNRDR0Ku2o0hmUmxKpNDrSv/UXrCf34XG2EpY1FbWhI28/etZNRExYgNvS5Ktx34c7Q6q1ekwTFtLqju42yAdIvuNJKt5+Cre5AXVoBIk3P9ZxjmoNyV/7JZZjW3HbzISPmu4bYegH0Zff3paWVA9qDTHz7+o1tUgTFkny7U/0OOLQG0PK8IBl2tgUjCOm0rx7DeBFF59O1GXXntX+wTe5OjRzYqcgW0Xk9GuJnnljwI2ojCMua0sj8tGY4tH34T4V2vAo0r/5HLaiI6hDwgJu6mNIziTppkcp+9fjfqkm4GtwhLXXlb/ANMZIv4mpALqoBGVUoTuhGeOw5e/3W6ZPGIwxM4fkO3+G+chmNBHRRE6+Gk1YJKWV+X6lSc+lzGNfaCOiiV/8ze6fN8USNeP6oM9FTrmayE4NA/Dd1M5WcAh94hCMWVP69VyF+DJSeb1B7ioizondbufIkSNkZ2djMPTeW/BltHfvXiZNmnSxT0OcJ+ajmzEf3Yo2Mo6o6dcrkxT7S2uZr0e5vbrG+WSvKKDi7V/6qtio1MRecS+RU5b0vuE56us14vV6Llj5OuWYbif2iny0UYl9ThvpD6X/eBRHhe9OuCp9CGnf+CO6qAScDZW4rc0YUoad83vhcTkwH9yIs6ESY9aUbkcdvF4PDV+8iyV3R1se+Df69S7RHqcdy4kd2IqP4qgpQR+TQswV96A1nlnpzv7UvP8T6ta9itftRBsZT9JtP0Ufl9bjNl6Pm5rVf8N8ZBN43GhMcSTd8ni3jVhHzWlqVv8Ne0UBoUOyiV/6cLc3UpPfESF6d67XSW8xpwT654EE+kJcWB6nHXtZHrqYlH5vtHRHrpHgWstP4TY3YMycELRiiTi/3NYWXE3V6BOHnPHojNva0nYPiP4h14gQvTvfgb6k7gghLnlqnYHQIWN7X1GcdyGdyqmKC09jjDjrYL0/g3whxJfDhR1PFkIIIYQQQlwQEugLIYQQQggxAEmgL4QQQgghxAAkgb4QQgghhBADkAT6QgghhBBCDEAS6AshhBBCCDEASaAvhBBCCCHEACSBvhBCCCGEEAOQBPpCCCGEEEIMQBLoCyGEEEIIMQBJoC+EEEIIIcQAJIG+EEIIIYQQA5AE+kIIIYQQQgxAEugLIYQQQggxAEmgL4QQQgjx/9m708CoqrsN4M+dNZlM9n0nIZAQCGtkR3aIClVxQVyrrVu1rV2se6tWX1u31qq1arVuRQXrgiAgiCCETQgkkJAEspF932Yy+8z7Ycglk5kkk43A8Pw+ce/ce+fMJMBzzv2fc4k8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiDyQb6QYQEZ2vOvQmZBXUIdDXC+MTg0e6OQNmMFlw7FQDAn2VGB0TMNLNAQDUNGrR3GbA2PhASCXCOX9/o8mCrfvLUF7bjvTUcExPjTjnbehNcWUrPttxEh16E5bPHIVZaZHia4Wnm/HmFzmorNNgxoRI3LNqIryVQ//fudlixfeHylFep8El48KRlhQy5O9BRMOLQZ+IyIWqBg0eenUPWjQGAMClk6Px4C3pI9yq3rVpjfjvlhMormzFpLGhWL1kLBpb9XjotT1oatMDAJbPjMf9100e0PWLKlrw3635aG7TY2F6LH4yb/SArvPexlx8vvMUbDYgKsQHz947B98fLse3B8qgVilwS8Y4TE0JG9C1u2ppN+CVT48gq6AO8RG++OX1kzEmNhAA8OJ/D2PfsWoAwOZ9pbjv2knImDXK5XV0BjPKqtsQF+ELlZccgP33o6CsGcnxgYgKUQ+6rV21aY145J970KE3AwCyCurw7D1zkJYUArPFiiff3of2DhMAYMehcviqFPj5lRP69R6aDiNUXnJIeulkvbw2C7uPVgIAvth5Cr+9cSoWTosd4KcaWhaLFZ99fxI/5tYiJlyNmzPGISTAe8DXK61ug0wqICbMdwhbSTTyGPSJyOM0t+lR3ajFmNgAyGXSAV3jy11FYsgHgB+OVuLaxWOQEOU/VM0cci98eAhHT9YDAPLLmqHTm2GyWMWQDwBb95fhyktHIzbcFzWNWpyuaUdqQhDUKkWv19YbzHjizX1o7zACAE5VtMLHS47Fl8T1q41VDRr87/tTXba1eOXTLBwtbLDvaOzAn989gHefWIpAX69+Xbu7dzYcx6ETtQCAkqo2PP/hIbz58BK0ag1iyO+0ZX+py6B/pKAOf/ngR3TozfBWyvDQrelo1RjwyidHYLUBEgH49Q1TsCi9f99Db7IK6sSQDwA2G7AnuxJpSSH4aleRGPI7HS9ucPvadc0deP6DQyg43YzQQG88cMMUTEwKdTquuV2PPdmVDvs27ik+b4L+J9sK8cm2AgBAwelmlFS14ZXfLuj3dQwmC57+937knLJ/h3MmReHBm9NH5C4T0XBg0Ccij7JpTzHe/uo4LFYbAn2VePru2RgV6efWua0aA5QKKbwUMmh1JqfXNS72DZeSqlY0tuqRlhQCpbzvzkqH3iSG/E57c6qQHB/kdGyrxoCjhfX491fHYLUB3kop/vizmZgwuufSjBOlTWLI73Qgt6bfQb+xVe+0r6SqzWHbbLHiaEE9Fqa7Fyor6zXYdqAMMqkEy2eOQmigt9jmrmoaO9CiMUApl0ImlcBssYqvqZRyl9d++6tjYujWGcx464tjMJgssNrsr1ttwAffnOgz6OsMZuw/Xo36Zh0mjw3F2LjAHo8ND1Q57wuy79ufW+30Wmw/RqHf2XAcBaebAQD1zTq8vDYL7zy2FFKp45Q9mVQCiSDAYrOJ+6QSAY2tOgT7nx051+hMqKhtx6hIP3gNQ/lQT/Yfd/weiitbUdvUIX5PrtQ0arH94GkIgoBlM+IRGuiNnYfLxZAPAJnZVViUXnvelXIRDRSDPhF5jA69Ce9uzIPlTAprbjfgo80n8PgdM3o9T2cw44WPDuHHvFp4K6W4+bJxWDYjHnuOVoqBLjbcF6kJQ1env+9YFd79OheNrXrMmxyNX1w7SQz0//o8B5sySwAAQX5KPHff3D7LQ5QKGQJ9lWhuP3sXIiLEB4sviUVmTpW4LzrUB4kxAXj6nf3iZ9MZLPhoSz7+ct/cHq8fFaqGRIB4DgDEhPW/ZGXcqCCEBXqjrlkn7vPxkqNV49iJ6DA4d6qMJgsOHK+B0WzBzAmR8PGWo6ZRi1+++D1MZnto37yvFG88tBh+PgqkJgShtqlDPD8yxAeBvkoIgoBrFiXh022FAACFTIIblo112d6u7ezclsscR3u7jr678sXOU3hvUx6sZ768DzefwAM3TOmxkzQuIQjLZ8Zj6/4yAEBKfCAWnen0yCTOa2j01HZXiitbHbYbW/Vo1RoR5Od498RXpcDEpBAcKTzbeSw83YKfPv0t0seF46Fb03GkoB4vrT0Mg9ECtbccj98x45zNZYkM8UFp9dkOospLBn91z3elGlp0+M3fdomd9c37SvDa7xc5/XwBoL7L7wzRhU765JNPPjnSjfA0FosFdXV1CAsLg0x2YfalqqurERUVNdLNIBe2HyzDXz44hC9/KIJEEJAc3/PI4MWmsVWPL3cVOexTKqS4rIfa606ff38SW/bZQ5XZYsPRgjrcsCwZsydGQS6TYPr4CNzbbcLjQP+OmMxWvPzfw/hoSz40OhOsVhtKqtogkwhISwpBVb0GL3+cJR6vM1hgNFkxY3zvI4wSQUBEsA8OnaiF2WJFkJ8XHlgzFWmjQ5ASHwRBAKalhOG+aydDECCG3E4KmRQr5ib2eH21txxKuQx5xY2wWG1ITQjCPVdPhMKNuw0O7ZQImDkhEkazvY03LU+B2keOvBLH0ffVS5Idaq6NJgse/MdubMwswf7jNdiZVYH5U6Pxr//loLxWIx5nMFkQEaTCmNhApCYEo7Jeg7rmDiRG++O3a6Yi6Mxo9MSkUEwfH4HUhGDcedUElyVZBWVNOHSi1iHIXzo1GhMSQ5Bf1izuWzkvEQq5FB9vLcDxokbEhKvh422/Q1DdoMXT7xxAl4FxAEBlvRbTUyOQlV8HpULqVDo1fXwEFqXHIjHKH1kFdfjgmxPILW6EzebY+ZBJBdxyeSpkUvcW0csrbkJ5bbvDvvlTYhDkfzbom8xWHMqrxbrvHH9HOj9DVYMWucWN2JlVDs2ZMiKj2YrS6laH8qfh/H8kMdofh0/UQaMzwUshxT2rJonzL1zZsq8UB/NqxW2D0YKwQG9MSwnHtwfKxM+mVEhx19Vp4s+PaLgN9u9JX5nzwkyhROeZVo0Bh07UIsjPC5PGhPY6wW0wTlW04JVPj4rbb315DHHhvpg01rnGdjgdK2rA7qOVCPH3xuVzEqA+T/5TjAj2QUKUn0MpyPwp0X2e13VkELCPWpfXtuOS1AiEB6lQUtUKQRj8z/SbvSX4aPMJpxpr4GyZSZvW6PRaa5e5Ar2ZlRaJyWOXo6ZRi9hwXzH8TU0Jc5rcOmN8BA7k1ojbiy/pu0xm1cIkLJ8ZD43O1GuJRF/Cg1S479pJ4nZaUgj25dSgst4e2OdPiUHKqCDklzahpKoVaUkhKKlqQ3HV2dHohhYdth88jYp6jdP1W7X278tfrez1bk5STACSeliFqKFFh8f+tRcGo0Xct2R6LO6+eiIUMiniI/yQX9aElPggRIb44NE3MsUR+z3ZlfjXw4vhpZChoq7d5fV1ehPu/L9tsFhtkAjAL6+fgiXTHUf4QwO88dGWE2K5U86pBqcAarbY0NSqR1To2bsrtU0dOFHahDGxAYgOdbzrMirKz+EODwDsO16NpFj797A3pwqvf5bt8vewq7ySJnT/G+FqdLw3zW16HCmsQ2SwGuMSgpBb3AidwYxJY0L6nFsTHarGvx5ejPK6doQGeIuTpHviqvzNSyFFYrQ/nr5zFr7eUwy5TIKrFyQhzEXpFNGFikGfaJBO17ThD6/tEWu6Z0+MxCO3TR+W9zpe5DzpLqeoYViCfklVKzr0ZowbFeTQcfkxrwZ/fvfsCOW+Y1V4+YH5QxKEB8tssToFFHeWHexetgAAUkHA9oNleHV9NqxWG5QKKR796XRMTR7YajC5xY144385Pb7e3G7A59+fwuWzRyE23Ndh1LU/dfDeSplbE4Z/f9M0bNhdjNLqNkxNDnMKmT3x8ZYP+WhngK8Srz+4ELkljfBVKZAQ5Y+Pvy3A2q35AOx3ARa46LAZTVakxAehql7rsH/BEEwY/TGvxiHkA0CA2gteCvvv05LpceJ39vpn2WLIB+x3lo4U1GNWWiRSE4Kh8pI5lfeYLFaxxMxqA97/Js/pZ9DcbnCa09D9b5lcJkFjq04M+pnZVXj+o0OwWm0QBOAX1ziuJpTo4nfjYG4NbrlsHPQGM/7x6RFo+yhF6hTk7+XQvnmT++5Ud8ovbcLjb57tSHUt54oM9sHzv5yHAF9lr9eQSATER7g3/2bBtFh8vadE7EzGR/hi7iR7eyeNDT3ngyVDZePGjdiwYUO/z8vIyMCqVauGoUV0vmHQJxqkL3cVOUzc3JtTjZKq1mFZncXV6GNPI5IDZbPZ8NcPDyEz2z7qNyrSD8/9Yo5YWrB1f5lDGcKpilacqmjp9bb5uXKqvMUpGO05WonLZif0ep6rEfN/bziOFo1RDHAGowXvb8obcNDvOuHPldLqNvxnYy5Oljfj/+6dg7e+zEF+aTOiQn0QHeozoPfsjZdShuuXONZ2Z5+sx2c7TsJssWLl3ETMnmi/nfzN3hJkZlchPEiFG5YlD8uIp1QqEVd/MZos+GzHSfE1q9WGHYcrHI5XKaUI9vfC1ORQFJxuRmWdBhIJcEvGOEQE9f59HStqwIYf7CVeP7l0NNJcTEIOc3HHwtU+APD3ca4N9zuzz8dbjqfumoWPvjmB6jN3WtYsS8ZT/97vcLz2TBlX1051sL8XokJ8UNVwtiMzKy0S1Y1aHC9qBGAvs3n2Pwfxnz8uh7dShg83n50LYLPZ5wMsnxkvdsQvSQ2Hn4/CoUNcWt2GL3edwtjYQJchXwAweWyoQ70+AKycm4j2DiNOlrcgLSkE1ywc4/L7ceXT7YUOHamudwOqG7X4Zm8Jblye4vb1+uLjLccrv1uAg7k1kAgCLkkN73fZmacoLLSXZDHoXxwY9IkGqfuoHwDoDc77BmLbgTLsPVaNyBAfXLdoDCaMDsFNGSn4/PuTsFiBFXMSMHPC0K4OcayoQQz5gD0EbN5XiusW20Ohq9Hcvm6bnytB/s4jgC19lCAAcDly2NKuh6Zb6CmtasVr64/iZz/p35rlADAm1rlDFhGsgsFocZhAuzenCktnxCEzuwpWG1DfosNDr+3BW48ugW8fS2AORk2jFk++vV9ciSa3qBHP/2oeispb8K8vjonH5ZU04Z9/WORUnrb/eDWOFTVgTGwgLp0c3e/yNU2HEfuPV8NLKcPEpBBYuqyI05VEImB2WiQO5tXg9c+yIRGAu65KQ2piMIL8vOCvPvuzbGzVISu/DlGhanGSaHltO/745l6YLfYwfOhEHf7xuwWIDXdcuWbK2DDMnxKDXUfsHYxJY0LECbHdXTEnAbuOVKCm0T6Jc1ZapMOk1JT4IDxz7xyHc5bNiHdYZnTp9Din70wQBDz60+l44/McnK5pw7Rx4fjZTybg+Q8PORyn1ZtRVNGCCaNDnIK6zmCG1WqDVCqI10yKCUBWQZ3Dce9syIW3UoYgPy+H5VgBwAagtKYNv7tpGt7flIc2rRGLL4nFVfNHO63W05sjBXV4/5s8tGqM6OsGYLsbf2/7SymX9uuuw4VgxYoVWLFiRb/Oueuuu4apNXQ+YtAnGqSMWaOwJ6dKHEUbHeM/JBNkv9lb4lDqcbyoAf/43ULcsDQZ1y0aAxvg9gS8/mhocV7+8GR5i/jnVQuTcDC3Rly9YsklcU51wCPFbLY57etaUtGTaxaOwZZ9ZTCYznbQ4qP8xVFT8Vo2+x0NqUTA9FH9a1v6uHBct3gMNuwuhgDgqvlJuCkjBb97ZZdD0PdSyrD/eI3D6jYanQmHT9QOSUlKTw6fmcTbyQbg7x9nIaDbWvaV9RqUVrchMfrsHavPdpzE+5vyxO2T5c2488o0t9+7oUWH3/797PcwNi4Ai9Jjse3gaadjrVYbTte2w2iyt9VqAz7YfALP3z/P4e9DbnEj/vjWPhjP/ExXzEnA3asmYv/xajHkA/Zyr/3Hq52CvkQi4Pc3T8ONGckwma29logE+nnhn39YjJxT9VB7y5EUGwiL1YaDeTXILWpA2ugQTB8f4VDeduvlqYgOVeN4cSOS4wOxfEa8y2vHR/qJqyHtya7Ee5vynEKyQiZB3Jn2ZcwcJa4vD9hLjLqH8TXLk3GitAk6g3OnIDUhCInR/sjKr4O1y6275jYDAn2V+M8Ty3r8HnrTqjHgmf8cFH8e3XVd7lQqEbDIjTkjze16fLbjJKobtJidFokl011/h0QXMwZ9okFKSwrBC7+ch91HKxHk54VlM+KHZDLurizHUoWSqjacrmlDXIQfpFIJWtoN2He8Gv4+CkwfHzFkoV/t7fzPQtdAEB/hh7cfXYKsgjqEBHgP6ZKTgxUWpHJaYtKd5f7sQW0R/vLBj9B0GDB3cgxOdencdHeksB7TR/W/M3fr5aliOULnz+uWy8bhz+/aA5AgADdnjHPocHQKHsRTP13R6ExYt70QJVWtmDI2VAyKXVXWa8USlE4yqYBgf8fwv3FPscP2lr2luGPFeLdHe7fsL3X4mRWebsF1i8ZiwugQbDtY5tDhCvH3grHbXbQOvRn3v/g9FDIJbl85HivmJmL9d4UOofKbvSW4fslYl5OIe5tY3NOypifLmyGTSsQSPblMgrhwP7y09jByixvhrZRCd+bO3lc/FGNsXACev3+e+J1IJAKWzojH0h4CfnfrvyvEB9+cELfDAr3R0KKDv1qJO69KE39ONy5PRmSID44XNWBsXKDL66fEB+Hdx5di+8HTeOfrXIfXpBIJnvjZDNzypy0OD4wDAJN54Hcq80ubnEL+hNHBGBXhh8gQH0xJCcO2A6fRoTdhyfQ4t0oBn3x7v7hc6I95tTCarbi8jzI9oosNgz7REBgbF9jrA3AGIsTfMdjJpIJYllBR144H/7FbHFWfmBSCZ+6ZPSQTYi0uRsA71yjvpFYpcOmUmEG/11CTSSV46NZL8Nr6o6iq1yB9XARuuyK1z/OKKlrw4Ku7xc95srwFMaFqp5rkTq4mNPanjV1NHhuGdx9fitziRoyK8kNUiBoanQl7sitRVGEPMQumxrisIx+MFz46hKx8e/nG0cJ6XLMoCeNGBTk9ZCo+wg8tGiOqG7SQSQXcdkWqQ3kM4LyiiVwu7dfvosnkXKZjtlqxKD0WC6bG4LMdJ7EnuxJhgSrccvk47D9ejY825zudYzRb8c6G45gzKQr6bp0Bq82+9ObsiVGYMb5SXHFoemqEOBfBHQaTBX96ax9yi+2dj0tSw/HYT6dDKpXgjc+zxf26buV7hadbcDCvFrPSIt1+r6627Ct12G5q0+Ojpy+Dj5fcYWBBEAQsSo/tscyok1qlwFULkrD3WLX4M5cIwGWzRwGwr8LUtbRIIsDtia+uJET7Oz2HIT0lHNcsOlvXf8fK8W5fr7y23emZADsPVzDoE3XjdtDfsmULTpw4gXvuuQffffddv2vCiKh/bliWjNySRjS26iGRCLg5Y5wYsDbuKXF4SmvOqQbklTQNycNqDC5CV28PojnfjE8MxhsPLYbNZnM7bP79kyMOnZmjhfVYOS8RW/aXOpR5APaykjt+Mh7lxSe6X2bA/NVKh7Cp9pbjbw/MR+HpZngrZS5H2wdDozOJIb/T7qNVePae2bjnL9+JnT1BABalx+GeayahpLIVIQHeLuczrFmWjJc/zhInad+wNLlfd7WWTI/D5n0lYjiOCFYhfVw4APvI9/VLxjpMHI4L90WwnxeOFNTjZHkLqhvPTlY1W2yoa+rAFXMSxNAN2J8hEBFsn6T7+B0zxFWNupfs9GXn4XKH6/6YV4uDeTWYlRaFwtPNvZzp/jKprnRfPUopl0KllA367uFTd83CtwfKUNfcgbkTozEuwf4k5TXLUrBxT7H474HVBry/6QR+f/O0Ab1PWKAKv7h2Mt7flAutzoS5k6Kxcl7Pz23oi5+PAjKp4PD3M2SI73oReQK3gv5bb72FzMxM1NTU4Kc//Slee+01lJWV4b777hvu9hFdtGLDffH2o0tReLoZ4UEqh//EzC4mKg7mtnpXqQlBkEoEh5H9WRMGNgo5kvozotx98iEA1DRonUK+n48CL/16PgCgfHDN65MgCEiODxqWa3sppPBVKdDecXbCY2iANyKCffDUnbOwfkchTGYrVs5LFINfkovJxJ0WTIvF6JgAHC9uxJiYgF6PdSU23Bd//+0C7DhUDpVShiXT48VlLF0RBAFLpsdjyfR4bNxTjDe7TBYOCfDG6JgAJMcHIUCtxP7j1YgK8cGSbiUs/Q34nbqv6gScndcyPjEYe3OqXZ7nrZBi5iD+Ht2UkYK/fnBI/Hu5ZnlKvybC9sRbKcOVl4522t+iMTh1+rs+x2Agls+Mx5JLYmGyWHv9+brDX63ETRnj8OE3ebDa7EvkrlmWPKhrEnkit/6mbdq0CevXr8f111+PwMBArFu3DqtXr2bQJxpmcpnE5Sh9xqxR2HGoXByFTojyQ1rS0KwDHRaowkO3puPDzfnQ6kzImBmP+VPPvzKdoTQ1ORQ7syrFbYkALJ0Rj33Hqx3qw6enDu0KRyNFJpXgrqsm4B/rjsJktsJXpcDtK+yDS0DMAAAgAElEQVQlTgNdUzw23HfA4Rmw18LfnDGu3+ddMScBZosVPxyxl/bclJEilkelJYUgLWloS57mTIrC+u8KxU6gUiHFjDMrX927ahIsFhtyTtUjPtIfsWFqnKpoQUyYL25cntznuvC9mZUWhTcfWYLc4gaMjg5AfOTQ3uXpLizQ22lpz8lDsNa8VCoZkg4KAFy7aAzmT4lBbZMWyfGBfT5ki+hi5FbQl8lkUCjO3rr38/Nz+ZhdIjo3kmIC8MpvF2DXkQr4+Siw5JI4SIfwabyz0qIwK214Hl1/Pvr1DVNhMFmRlV8HtUqO+6+bDG+lDH+4OR3vbsxFUUULJiaFulXvf6FYMC0WU1PCUVHXjtExAS6fHHohEAQBV81PwlXzk87J+8VH+OGZe+ZgU2YJpFIBV84bLT5XIMC39yfxDlZ4kArhQe4/PG0wBEHAY7dPx9tfHUdFbTvSUyNw6+X974gNt9BAb4QGsmSHqCdupfXIyEjs3LkTgiDAaDTinXfeQXS0Z61FS3ShiQ33HdAIKDmTSSV49KfOTzMO9PPC724cWE3yhcDPR3FerZp0oRifGDwk82HOd3ERfvjz3bNHuhlENAhuBf0nnngCf/jDH1BQUIBJkyZh8uTJeOmll4a7bURERERENEBuBf3w8HC8//770Ol0sFgsUKvPj4fjEBERERGRa24Ffa1Wi9dffx179uyBVCrFokWLcPfddzvU7RMRERER0fnDranvjz/+OGpra/HII4/gwQcfRFFREZ555pnhbhsREREREQ2QWyP6eXl52Lp1q7g9c+ZMXHHFFcPWKCIiIiIiGhy3RvTDwsLQ1HT2segdHR0IDAwctkYREREREdHguDWiHxERgWuuuQYZGRmQSqX47rvvEBISIpbvPP7448PaSCIiIiIi6h+3gn58fDzi488+PpxlO0RERERE5ze3gr6/vz+uvvpqLqtJRERERHSBcKtGv6CgAMuXL8djjz2GY8eODXebiIiIiGgEWSwWfPnllzAYDCPdFBoEt0b0n3nmGWg0GmzYsAFPPfUUbDYb1qxZg5UrV0KpVA53G4mIiIjoHMnJycGbb74Jo9GISy+9lFnvAubWiD4AqNVqXHbZZVixYgVaWlqwdu1aZGRkYMeOHcPZPrdUVFRg0aJFTvuTk5PFP9fW1mLu3LkO5yQnJyMzM9PhnEWLFqGiokLc1mg0WLFihcM+IiIiIk+VkpICmUyG0tJS/OlPfxrp5tAguBX09+3bhwceeAAZGRkoLi7G66+/js8//xzvv/8+/vjHPw53Gwdt165duPXWW1FfX++wXy6X44knnoBGo3F5XnZ2NtasWYPS0tJz0EoiIiKikVdcXIylS5ciLi4OL7300kg3hwbBraD/1FNPYerUqdi+fTuefvpppKSkAADi4uJw/fXXD2sDh8Jnn32GV1991Wl/WFgYZs+ejb/+9a8uz1u3bh3+9Kc/ISwsbLibSERERHReCAsLw7hx42A2m2Gz2Ua6OTQIbtXo33LLLbjpppsc9r311lu466678Ktf/WpYGtZfdXV1uPLKK12+5irkd3r44YexcuVKZGZmYs6cOQ6vPfvss0PaRiIiIqLzXUdHB/7yl7+gvb0dH374IX7+85+PdJNogHoN+h9//DH0ej3ee+89GI1Gcb/JZMInn3yCu+66a9gb6K6wsDB89dVXDvu61uj3RK1W489//jOeeOIJbNiwYbiaR0RERHRB0Ol0MBgMUKlUSExMHOnm0CD0GvRlMhkKCwuh1+tRWFgo7pdKpXj44YeHvXHnyty5c3st4SEiIiK6WERHR+Oll17Cu+++61TtQBeWXoP+ddddh+uuuw7bt2/HkiVLzlWbRkRnCU/3CbtEREREFxOVSgWVSoUrr7wSMplbVd50nnJrMu6sWbPw0ksvYdWqVVi9ejVef/11h1IeT9BZwmMymUa6KUREREQjJicnB2+99RZeeOEFTsa9wLkV9J9++mnU1NTgwQcfxK9//WucPHkSzzzzzHC3zW0xMTEu1/MvKCjocdvVOXPnzkVBQQFiYmIc9u/YscNpHxEREZEnmjhxIvLy8lBaWopbb711pJtDg+DW/Zi8vDx8/fXX4vaMGTN6XOGGiIiIiC5cR48eRUBAABITE/H222+PdHNoENwK+v7+/mhpaUFAQAAA+7JLvr6+w9owIiIiIjr3Jk+ejMmTJ2Pfvn0wGo1QKBQj3SQaoF6Dfmd5jkwmw6pVq7Bs2TJIJBLs2LEDSUlJ56SBRERERHTuzZo1a6SbQIPUa9DvHMFPT09Henq6uH/FihXD2yoiIiIiIhqUXoP+/ffff67aQUREREREQ8itGv2VK1e63N91gi4REREREZ0/3Ar6TzzxhPhnk8mETZs2ITY2dtgaRUREREREg+NW0J8+fbrD9uzZs3HDDTfg3nvvHZZGERERERHR4Lj1wKzumpubUVdXN9RtISIiIiKiITKgGv2qqiqsXr16WBpERER0sbGaDNCX50MeGA55YMRIN+ecMjXXwNxSB2VsCiQyrtdONJTcCvqPPfYYysvLER8fj4MHD0IQBD4SmYguCLrTuWjc9h4sHW3wnbwYQfOuH+kmnfcsOg0at70LXekxKCNGI3j5HZD7h410s9xis1qgKz4Kq0EHr9hxMNQUQR4cBUVwzDlrg0XXjo7CHyHx9oUqaSoEibTX4w21pahe+xSsHW0ABAQuWIPAOdf0eo7VqIe28CAECFAlT4dErux3O202GwyVhYAgwCt6bL/PHwpNP3yKlt3rAdggVQci8qYnoQg5dz8rIk/nVtDftGkTBEHAlClT8Mknn2DevHl49NFH8eqrrw53+4iIBszc3ozq/z4FWC0AgJYfPoXNbETwwptHuGXnt4atb0ObuwcA0NHeBEtHK6J/+lyf5+lKj6Fl31eAzQK/S66Az5h0WI16NO/+FPrTJ6CMSUbQpashUaqGpd02mxXVa5+CvizX6TWvUWmIuunJAV9bX1GAlr1fwGY2wG9qBnxSZrg8ztRcg8r3HjkT2gHvUWmIuPFPEAShx2s3714nHg/Y0LzrE6hGT4MyYpTL4616LSr/8xBMTdUAAHlwNKJv/ysgAG1Z38LUXAOf5JlQJU7q8T2tJgOq1z4NQ0X+2Xbe8BgEqbyPb8LFtcxGNG75NzR5eyDzC0bw0jugGj2lz/PM7c1o2fMZABsAwKJpRu3/XkTwstuhSui57UTkPrdq9HNzc/Hkk09i+/btuPrqq/Hcc8+hsrJyuNtGRDQoHacOiSG/U/uR7YO6prm9GU27PoH3ie0w1JYO+Do2iwmavEy0/vgNzO1Ng2rTUDC11KLt6Hboq05BV5Lj8JqhshBWo77385uqUP3xM9AVH4GuJAe16/8KQ3UxGra8hdb9G2CoOom2gxtRv/Gfw/YZdMXZLkM+AOhLj0Fb+OOArmtub0L12qfQcfJH+2f73/No+uFT2Cxmp2NbD23uEtrtnR99eV6v17doWhx32Kyoev+RHn+/NLm7xZAPAKbGSmjyMlGz7jk0ffcB2rO+Rc3HT0OTl9nje2pyd4shv7Od2oKDvbazJ637vkJ79newmQwwNVah9vMXYTV09HmepaMVsFkd9pkaylGz9mm0/vgNAMBmMaN59zpUvv8o6je/CYu2dUBtJLpYuRX0bTYbJBIJMjMzMXPmTACAXt/7P/pERCNNHhjpvLOPMoreWI06VL73MFr2rIdX2UFUvddzGOtk69bRAOz/plavfRp1X7yMxm/fQfmbv4axoWLA7Ros7clDKH/jl2jY9Aaq/vMQJApvh9flQZGQKLx6vUbHqSzA2iX42qzQFh6E5sydAfG98vfDZrOP4NpsVpdheSD0VafQdvS73o+pKHC539zWiNZDm6E5sQ82ixnG+tNo2vUJ2rK+hdVkQEdRFmwmg8M5LbvXoWbdX5yuZTMZ3drXlW/afOdzzEa0nQm73Zla6533NVU5dXLasr7t8T2dOhewj6gPhL7ihMO2zaiHobakz/MUYfFQhI1y+VrrAftzepp2fYzmHz6FoaIA7VnfovbzFwfURqKLlVulO3FxcbjzzjtRUVGB6dOn43e/+x1SUlKGu21ERIPiPWoCFOEJMHYJHYGDqNHvOJUFS1uDuG0zG6HJ+R7Kpbc7HWuoLUX9hldhrCuFV9x4hF35K8j8QgAA+vIT0J8+O8prM3Sg7dBmhGTcOeC2DUbL7vUOdz7M7U1QhMXDWFcGWUA4Qn/yqz6vIXMxgdTUUut0R0Wi9IYgCGjL+hZNO/8Lq0EP34kLEHLZXX3Wsvek+Yd1aN79aZ/H+aTMdNpnrDuNyvcfhc2oAwAoIkfDWFsmdlo0x39A4PwbXF5PV3wEhppiKCMSxX1+U5ZAk/M9bBYTAEAeEgPvUWm9tsu7hxIbW7fRbnG/i46DWdMKCBKHEXKJ0tvpuE4+42ajJfN/sJnt1xLkXvBJdl2O1Bev6BToirPFbUHuZQ/w9fk9nwRAEARE3vhHNO/93N6p6dJ2QWr/XdCe2Odwjv50HiwdbZCq/AbU1k4dpw6jaefHsOo18J20GAFzr+2xvMpmtUBXehwSuRJescw+dGFxK+g/99xz2LZtG6ZNmwa5XI709HRcddVVw902IqJBi/7Z82jP3gljbQnUqbPhFTtuwNfqPtINAEIP9eZ1X/4NpjOj9PrTuWjY/BYiVj9qf9HVKP8QjWwPhNXU7Q6t1YLIW/4M2KyQeKl7rS/vpEqaCkHhBVuXEp/uJUAAoAgbBVNTFRo2v4XO2uz2o9uhjEiA37SM/rfdqEfznvVO+32nLIO5rQH6smOAVI7A+WvgFZXkdFzL/q/EkA8Axuoih9f15ScgyL3gO2Up2o9sc27AmbsTAGDRtkJfeRIB866HVdcOqToAvpMWQ5D2/l+tROkDSGSOd0QEAf49fB+CxPlmvKm+DH7pl6Htx032YxTeCJhzrdNnaT/+A6Q+AfCfloHIW/6MtkObAUEC/0suh8w/tNd2dmezWmDVd8B/1pUwtdZCk7sHMr8QhCy9A1IvH7euIfXxR8jS2yH1UqP5h086PyECZq8CAMgDI2BuqRWPl6j8Bj3Hw9zejNrPXhA7Y80/fAKZfyh8Jy5wOtai06Dqw8dhqi8HAHgnTkbE6kcH3CklOtfcCvoqlQpXXnmluL1mzZphaxARUW80+fvQssc+Eul/yeV9hkNBkMBv8qIheW/vxEnwih8vlkjI/ELgN3WZ03FWg04M+Z30VSfFP3vFpUIRMRrGGnuoFGQK+E1bPiRtHAi/aZehcevb4rZ6wjy3g1onQZAAVscRaKteC1lgBMzNNeI+/5k/gaG6GJ0hv5O+qgh+0/rfdmNdmVOdNwD4pM5B/Zd/g81sAiwWl50rANBXui7n6crUWIXQy++BavQU1H7xMnCmU+YVPx6avExUf/xnSJQqWDpaxY6OROUH74RJUEaWwTt+fK/Xl6p8ETj3WjHoCjI5wq56AEoXHRP7Z5uL1oMbHa/hG4iQZXdAPX4ezM018E6c5DDqrSs9huq1T4vflTYvEzF3/Q1hP/lln58fAIwNFdDm74fMLxjq1LnQl59A3devwdLeCGVkEsKv+T3CVrp3ra5aD22BJud7SFR+CL78HtiMenjHjxfvkgQtvhU1nz4LS3sTBLkXQpb/3KHj1HZkO9oOfQNBrkTg3GuhSur9l8hmsznccemkKz3mMui3H90uhnwA0BUfhbbwINQps/r9WYlGgltBn4houNksJpha6iAPCO9xBNTYWIm6z18Ww0rDlrchC4zsdXWRoSRIpIi86UnoirNxKj8XE5Zd53JZQ4nS26lkyDsu1eE6YVf/Bo1b/w2LthX+069wKP841/zTMyAPCEVH8VEowuLhm7ZgQNdRT7gU7UfPTnb2TZuPwHnXo/XABpg1zfCdMB+qMdNgbmuwz5XoEr69R/UehgF7KZAmZxcEuQK+kxZBqvKDIjQWgkwhlqAA9rsGbYe+gUV7pg7dZkXzzrX2c7p1YGxmx8DnSuv+r+Cbdil8kmcg5ucv2QOvbxCsRj0av30HAGDVtTucY+1ogzZ3N7R5mYi69Rl4xST3+h6B866DT+psmJqq4R2X6nLU2lBdhMbv3oe5pQ4SvxBYO8vIBAkCZl0NAPCKHgNEj3E6tz17h0OHyNRYCf3pvD7LigD7nYCq/z4pdnDaj+2CqaFCrOk3VJ9C4/b3EH7Ng31eq5PNbELj9x+hrUuHxVBZgLj7/+Xw2ZXhoxB33xsw1p+GPDDC4bWOoiNo+OYNcbtm/fOIveeVHp9DYDXoUL32KRi6dLrF94lIcHmOq7kG2vz9503Q37hxIzZs2NCvcwoLCzF27Mgsp0rnHoM+EY04ffkJ1P7vRVi0LZD6BCD8mgdd1sLqSo45jd7qSo6es6AP2EeuVaOnwNRi7XXt8rCrf4P6Da/CUFsKr5gUhGTcJb5ms5hR++mz4sop9V+/Dqlv0JAtKagtOGBfCtJihv+MFW4Fd1XStD5HQ/sSkvFzyAMjoK/Ih1dMMvynr4QgkyO42xwGmV8Iwq/+HZp2rYVVr4XvlKVQT3CekNrJ0tGGtqxvHWrK27K2IubOv0GiVCFoya1o3PrOmTIaAeqJC6HN3e1wDZvZaC+n6Rb0vePHQ3Nsl7gtUQfBqmsTQy1w5q7BGYqQGCjm2kti6r78e99fis0KzfEf+gz6AKAIjoYiONr1Zcwm1Hz6f2c7L10IEilkvkG9XttVx0Hipe6zTQDQ+uMmh+9DX3rM6ZjOSek2mw26oiwY605Dqnf98Cv7pPZHYao/7bhfr4XudB58xqQ77BekMpcd4Y7io90ubEZHcTb8p50N+ua2RghSGaQ+/mg98q1zyBcEqMfP6/GOmqvv1WrQuTjywjF27FhkZPS/TI4uTAz6RDTi7Mvm2QOMRduChi1vIebOl52OU4aPctrX06odI83UWGUfDbSYoS87Dm3+fjFM6MtPOCyPCNigyf5+SIK+sb4ctf97UewQ1W94FfKAiHMyiVCQyhEw+2qHfVaj3r7SjsUMn3GzxKDtkzKjx7Xou+q+Ln0nc0sdOgp/hHrCPPtEULFW3obmXR8jYO61MFSfEo9XRo1xOdIbvPg2WLQt0BXnQB4chdArfoHmvZ9Dd+qweIzXqAku26aMHgNNtw6FK1KfgD6P6YnV0IGmnWvRUXzUZcgH7HfDtCf2OX33XfnPWAlN7h5Y9RoAgCp5Ro+j2E4E5zkBssBwmJvP1s53/u42bn9PHKX3BdBgqoF6wjyHB3JpcjOdQv6ZN4IiOMq9NgGQB4Y77TOeua7NbELtFy+jo/AgIEjgl34Z9GXHnY4PybjLZfldJ1c/O0Nt6Zm7jyP/ELkVK1ZgxYoVI90MOo8x6BPRiDM1VnfbrnJ5nFdsCgLmXofW/V/BZrXAd+JCqMfPPRdN7LfmXWu7jILa0LRzLXynLIEgkULi7et0vKt9A6EryXa669FRlDUiq4VYjXr7g53OzFdo3r0OMT97AVIff7ev0Za11Snki2T2/8LMrQ0Ou20mPdSpcyD1VqOj8EfIgyLFyZ3dSX38Ebnmj/ZlUK1WWM1GSGTdRqJtNpfn+k1dDkNtGTTHdkKi9EHA7KthMxuhzd8H45kRbnlITJ/zL2w2K1r3b4C28EcogqMReOlqyPyCAdg7wdpuS5S6YulWOtSdqbESVr1W3O44dRg1X7yMkKV3QKbuvSPiP30FOgp/FO+mSLzUsGjbIFUHAYL9blDQ4ltgNejQdmiLeJ4AoO3QN2g79A38pmWIq0rZuk/+BgBBgsBLV0Me5Bz0LSY9LJoWKLp11OQu7n50Ttxtz/neHvIBwGa1T1Lu3mERhD5XGlJGjnbaZ21vRM265xB71996PZfofMCgT0QjzmdsOrT5+8Vt1dhLejw2aP4N9pFLq7XX5QNHmkWnddi2GnWwWS0QJFIow0dBnTZfLBmR+gbBf8bKIXlfeUis0z5FaNygrmlua0TLgQ2waJrhmzbf7RIfbcF+h0nJlvZGtOd8j4BZ7q/aZjO7Xo1IEZ4AnyR7iYfPuNkO8yGUUWMgDwiDfMpS+E1Z6tb7tB/9Dk07PrSXZXRb1UZfliv+7LoytTVAm78XsFpg1bVBV3YMkasfQ+Dca2GoLoLV0AGvuNQ+V2hp2fsFmneuBQAYKvJhqClGzM/t68V3FB5yq/2GulKY2xrQenATLDoN/CYvclhhqi1rGxwmQFvM6MjLRL2+AyHL74CuJAfy0DiHuSSdvKLHIuauv9lLwvZvgLXz7ptRB98pSxF6+T0AcOYhWa47RW2HtyJg1lWQ+YfCZ9wcNO9ZD6vOfndBUKgQfduzUITZf08NtaX2CbpePjC3N515yJ0NEi8fRN3+FyjOdAaU4YlO8zOUUfb5CaZGFw/1lEgAy9lOsCwgvM9Op3f8BPhOXYb2bs8kMNWfhqm5psf5AETnCwZ9IhpxoVf8AlKfAOgrCuAVk4yghTf1enxvtfHnC7/JSxzWdldPuNRhpDjsJ7+CX/rlsGhb4D0qbcg+kypxEvynr0DroS2AzQrfiQvhM27gEwdtFjOqPnxCHCnV5mUi4vpHoRrTd9i3WVwsI9rD6jc98ZuyVHzqKgBI1YEIWnQLfMbNgiCTAwACZl8FiVyBjpOHIA+JcVpWsi/mtgY0bHn77J2Qbm2UBYa7DOv1G16FrUu9tu5UFnSn8+Adl+pyJLgn3deKN9aWiCFSHhwFY02x+Jo8OAqhV/0WVe/83vEiNqDyvUdhaW8EAGiO7UTULX8W7+T01CnWFR9B+ZsPiJ85YPbVCFp4s9Nx8sAIqFPnoOm7Dxz2d31Il0Spgt+UpWg7vKX76QBssJ5ZxlTmG4joO16wT9y22eA7ebEYmA01xah87xGHOQGdrHotaj97QRxJl6p8EfqTX6Fx27uwaFrgM26W2IlUjb3EYWUiQSqH37QMtB78+swOCYLmu7eCYOhld8Pc1gTdqbOdLolSBak60K3ziUYSgz4RjTiJl8+IPSxquATMuw6ywDDoSo9BGTHaZR2wq3Xdh0Lw0tsROO962Gw2SL3dm3DZE335CYd1zAGg/dhOt4K+OmUmWnavs6+yA3t5Un9X9FGExSHm5y+i/fhuSL18oJ640GlCrSBI4D99BfynD6xW2Vh32nmJTpkCMBsh9fFH6BX3ujzP3FLntE9ffsLlqHhv5IERDnckBLkXpCr7SHNIxp2o/ewFWDRN9jXnL78HXhEJ8EmZBW3+mQ6CRAqvmGToS84+tAo2K9qP7RSDfsCsq9Bx6rBD+Q4ApxHxlgNfI2D2KpeTd6XqQEh9g2BpbxL3dV8CNHj5z+GdMBGa3ExoT2SePS4mxeHOkjwgDEELbnR6j/bsHS5Dfidzt6cCq8fNsj8IzWpxWK3LO34Cwq56AK2HNkMiVyJg9ip4j0qDT8pMGGqK7Q/T68edrpBlt6OmpQamhgoIShVCLrv7ghhwIGLQJyIaBoIgwDdtwYCXqhwsST/Xwe+Jq8mI0j5quru2IfqO59F+bBdsFjN80+aLtef9IQ+KQtClq/t9nruUMckQFN4OD84KXvJTqBLSIPMPhSCVuzzPe/QUaLK/c9jnO3Fhv98/cMGNMNQUwdxSB0GmQPCy28UReK/osYj75b/sI/wBYWJbwq7+DbQFs2FuroFqzCWw6jVo2b3O4brSLvM+FGHxiP3F62jL2oa2w1tgaW+ELCAckEhhbuoyJ8Zq7fGuiyCRIuyq36Bh0z/ty4COSkPQ4tscjzlT9+6TPAPZW+MQZW2EPCC81wmvXbl6KF1Xru6UCIIAuFiSVz1+HtTj5zns84pNGdB8FXlgBGLu+jvMzdWQqoMgUXj1+xpEI4FBn4iIeqQIjXWoUZb5hyJgxk/cPl/q44+Ame4fPxKkXj6IWP0Imr5fC4u2Bb5p8+E3dVmfTwQOveJeWHXt0BUdgaDwQtDi2/pc5tIVRXAUYu99Dcb6csj8QpzuwggSqdOym4JECvW42Q77fFJminNdZAHh8LvkcsfP6e2LwDmrEDD7ali0rZD6+KE9+3s0bPqneIx6wjyHDkJ33nGpiL33Ndgsph47QJ3MIQkInda/Miq/aRloP7ZTvGsgD4mFpb0JVqMOivAEhF//cL+uN5QEQXA5WZjofMagT0REvQq97G74T7sMZm0zvONS+wx4FyLvuPGIvu3Zfp0jCAIirntoSN6/c5L2YIRf8yD0lYWw6jTwTkjr8eckCIK40o7f5MWQB4ShoygLitA4qCdc6l57h+l3QOYXjNi7/4GOoixIlCp4J06yP3WZiAaEQZ+IiPqkCIuDAoNbvYeGX9f16t3lPSrNrSfknisSpTfUqXNGuhlEHoHdZCIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnIiIiIvJADPpERERERB6IQZ+IiIiIyAMx6BMREREReSAGfSIiIiIiD8SgT0RERETkgRj0iYiIiIg8EIM+EREREZEHYtAnItYiqVoAACAASURBVCIiIvJAspFuABER0YWm8HQzPt95CgajBVfMSUD6uPAhu7bFakNWfi3atEZMHx8BX5ViyK5NRBcXBn0iovNM4elm1LfoMGVsKFRe8pFuDnXT2KrDY29kQm+0AACy8mvx11/OQ0p8kFvnN7fr8fr6bGSfrEdSbADuu3YSYsJ8AQA2mw1Pvr0PRwvrAQD+agVe/NWliAj2GZ4PQ0QejUGfzgs2mw1f/VCMvTlVCA9W4ablKRf9f2wFZU3Yd6wa4cE+WJQeC6VcOtJNGlYmsxXbDpahtKoNU1PCMHNC5Eg3aUS8/lk2tuwrBQD4qhT4y31zEBfhN6JtIkeHTtSJIR8ArDZgb06120H/jf/l4EBuDQDgeFEjXvjoMF757QIAQG5xoxjyAaBVY8TXe4px55VpQ/cBiOiiwaBP54WvdxfjnQ3HAQAnSptQWNaMNx5aDIlEGOGWjYwf82rwzLsHYLXZt/flVOHpu2ePbKOG2SufHMGuIxUAgM37SnHXVWlYOS9xZBt1jlU3aMWQDwDtHUb87/tT+M2aqUP6PjabDd8eKEPOyQaMjvHHirmJUAxjR7K9wwidwYywQNWwvce5FBbo7bQv3MW+nuQWNzpsF1e2Qmcww1spg8FkcTr+wPFqjI0NxPypMf1vLBFd1DgZl84Le49VO2xXNWhRVtM2Qq0ZeRszS8SQDwBHCutRXts+cg0aZhqdCbuPVjjs27yvdETaMpI0OqPzvg5Tr+dYrTbknKrHsaIG2Gy2Xo/t9N+t+XhtfTZ+OFqJ/2zMwyufHhlQe93x8dZ83PrkVvzsmW144l970aHv/fMMRH2zDlrd0F+3J5PHhmLhtLOhO210CBZPj3P7/OT4QIftuAhfeCvt426TxoQiNlzt8Hptkw4v/vcwth0oG0SriehixBF9Oi9EBKscRrnkMgmC/d0fIfM0CplzH3w4R1y7s1isMJmt8FKem38iZFIBEokEVotV3CcVLr67OUkxAYgOVaOyXiPuWzSt51FcvcGMR97IxKnyFgBAakIQnrlnNuSy3n9Xvjt42mF7T3YVfrXaMuTlYWU1bVj7bYG4ffRkPTZlluC6xWOH5PpanQn/995B5JxqgEImwY3LU7BqYRL2H6/GyfIWTEwKweSxYUPyXl0JgoDfrJmKNctSYDRZEB/Zv9Kqe1dNgs5wGMeLGpEY5Y8H1kwRX5NJJfjr/fOwbnshvtxV5HDejsPlWDojfkg+AxFdHBj06bxw47IUFJQ1o6JOA7lMgp+tHA8/n4t3pYlrFo5BVkE9jGdu4y9Kj0V40Lkpe9h+sAzvfp0Hrc6IWWlReGDNFHgphvefCrlUAplUgLlL1YJEevEFfavVBp3BcWS6qKoVcyZHuzx+15EKMeQDQF5JEzJzqrGgjxIPP7USDa16cdvHSwbZMJTJVdZpnPZVuNg3UF/uKkLOqQYAgNFsxfvf5KGyQSuOfK//7uSQl4BpdCa88kkWDubWIDJEjfuum9Tva4QGeuO5X8yFxWqD1MX37qtSYNXCJHy9uxiWLrf2gny9BtV2Irr4MOjTeSEsSIV//mERTte0I8jf66JfTi5lVBDefHgxfjxRi/AgFaaMDT0n79vYqsNr67PFcJGZU4WEKD+sXpo8rO/bYTA7TG4EAE2HcxnLcMkva8KOQ+Xw81HgijkJCByhQFVep0FTm8FhX/bJ+h6Otk/U7K5NY3DaZ7PZcCC3BmU1bZiaHIbbLk/Fs/85AKPZCokA3HbFeEilQ1/JOTEpBN5KGXQGs7hv+viIIbt+RZ1jOZvNBnz/o+Pdii9/KHIr6JdUtWLjnhIAwBVzEpAY7e/yuA++ycP+4/aJtJX1Gjz/wSG8+vuFCPBV9njtuqYOvLb+KPLLmpGaEIT7r5uMkABvlyG/U6CvF65fMhafbCuAzQYE+CqxeunQ3AkhoosHgz6dNwRB6PctcE8WEuCNy2aNOqfvWVrd5jCCCABFla3D/r6+KgUC1Eq0dAmpncsNDre8kkY88s9MWM987h+OVOL1BxdB7qJ8arhFBKvg4yWDVn82GCdGB/R4/LzJ0Vj3XSEMZzpJKi8ZZk+Mcjrujc9zsHlvKQDgv1vy8eBN6Xj3iWU4UdqExCh/hA3T3SK1SoGn756Fj78tQLvWiKUz4jHHRfsG6pLUCOzJrhK3fbzlsFgsMBvP/g67c6eitqkDf3h1t9jZ3HWkAq/9fqHLlb8KSpsdtls0Btzy5BaMivTDH25JR2y48+/t3z7JwvEie2ni4fw6/OPTI25Nrr9xeQoWTItBbWMHUhODPX7lLSIaegz6dEGra+pAflkTxsYFXvTLcQ6F5LhAeCmkDqPrk5JChv1927RGtHYbiW7VOo9MD4ftB0+LIR+wr3yTc6oe01KG7gFI7vJSyPDbG6fhlU+PoE1rxPjEINyckdLj8ZEhPnjhl/OwKbMEEomAFXMSEBLgOLdFozNh6/6zkzhtNuDznScxb0r0OVnCNCU+CE/dOWtYrr0oPRZanQnfHTqNALUSN2WkICu/Dh9tyQcACAJw/RLHUfA92ZVYt70QZosVV146GstnjkJmdpXD77zBaEFmdhWuWTTG6T1TE4NQXOXc+S2tbsOr647i+V/Oc3qt+yo7x7tt9yYqRI2oEHXfBxIRucCgTxes3Ucq8eLaw7BabZAIwK9WT8HiS9xf+YKcqVUKPH7HDLy/KQ/N7QYsSo/FZbMThv19JQIgkQgOdxNkw1BK4oqPt/MDqVztO1cKy5vRprWX5BRXtqK6QQt/dc9lIQlR/rj/usm9XrP7mLYNwMY9xSg83YzxiSFYOj1uUEvZGkwW7M2xh+U5E6MGNL+mvcMIq9XW62d1ZeW8RIfSnDGxgZgwOgQny1uQNjoYo2PO3hEpq27DCx8eEle0em19NiJDfBDg69zentpxy2Xj0K41Yf/xKhhMVofXXHUAAGBsbCAKTp+9EzA2LtDlceQ+rc6EnFP1iAj2QUKU6zIrImLQpwvY+9/kiSOxVhvw/qY8Bv0hMGlMKF5+YP45fU+1SoGMWaOwKdNeIy0RgGsWJvV5Xm5xI9768hhqG7WYPTEKd6+a2O/yhpXzEvHDkUo0tdknp85Ki3T54CODaehXpemuvcOI/+04KW7rDBZ8vK1gUCPiam+5w3crCICPlxxvfnEMAPD94QrUNGpx2xWpA7q+yWzBg//4ASVV9uVw127Nx99/M9/tVbNsNhve+vIYNu8thc32/+3deUCU5frw8e8w7AzIooCKmibuS+YuoiiWiiIgZrhLeiqXOmkHD5pZLpWVqWW5tNivOhnyigoumaaZSrimmLkbIrgAbgjDNszM+wc5iWwqgzPi9fmLZ7vvax688XqeuRc9vTrU45Wh7crtv16Rlo3caNnIrcT+xDMZ3NUzjcOnMhj2bFN+2pvM8aTrADR/wpUe7UofAG1va8V/RrYH2vPGsnjDYGCAto1LH0vz77B2LFx1iLOpmTSt78KrQ8t/MBPlS7qUyYyl8WT/PaVqiF9jXghsaeKohDBPkuiLR9bd82ar8wrR6/UoHsNpGauDl0Ja06G5Bxeu3OLpZh48UcF4jXyNlne+3k/W34N2t+2/gIuTLaP6N7+vet1d7FkR6c/vp9JxcrCm1ZPFuyqdS73Jwh9+58KVLJrUd+Y/IzpQu2bVdBPLzS+kUFs8EzXGoOSXQlrzdFN3kq/coq13Lf776Z5ix7ftT37gRH//8TRDkg9wMyufrXuTGda37C5Hdzp8KsMwCBZg+4EUnm7qTo92xl8cqrQ3v43q1MDaSsn8Sd05cf46en3RNKX38ndk6vCnWb72KKeSb9CikRsvh7Qp9bx6Ho4smuKHVqurkkHPj5vVP582JPkAsb+eJahHo8d6SmYhyiKJvnhk9e3SgJhfzhq2n+1cX5L8R5hCoaBDcw86NL+3vvEXrtwyJPm3HTt3tYyzy2drU/ogVoBFfyf5AKcv3GRpTCJzq2iVYneXohmWDp/+Z6adZzs/UelyFQoFnVp60qmlJ3q9HpWdVbGBz5WZ5Uqr1ZXYV3j3a/NyXChlIbjb99vYWjeuydA+TVi/8yw6vZ5nOjXAp23R712hUNCiYclvAcrjVsOON8I73/P5kuQbx90Pvzp90VgUSfSFKEkSffHIGh3QAi93FX/+dZ2mDVxkIZnHjJe7I/a2luTcMUONsfs+F2i0JN+VdN45b31VmDG2E5vik0hNz6ZzK0+jD5hVKBSMGdCCJdGH0emLFisbHXB/34LcqVNLT2rXdODyVTVQNCf/M/exSuzTTWvxtYXC0A1PoeCeH/YexKj+zXnO3xu9HsNqtOLR0qdTAxLP/PNQ37SBCw08ZcY2IUojf+XEI8vCQkGfTg3o00kS/MeRnY0lESM7sGztUa7eyKFL69oMe9a48/1bWylp2sCFU8n/DKRsXcWzENnaWJY624sx9elUn9aNa3I25SbNnnCp1JtQW2tLPvp3D3YcTCGvoJBeT9e7r+k663s6MWNMR2J+OUuhVkdwzydp9kTJMRLGVNULwImq5fe0F/a2lsQnXsLTzcGoC6IJUd3IXzshxCOrQ3MPvnrjmTJXGDWG/4xoz7KYo5xJuUHrxjWZMPj+V0I1Rx6u9kZbbdnR3pqgHk8+8PWdW9Wm80OY6lNUH51aeNKphfEWXxOiupJEXwjxyKuqJB/A082B2S9WzTzwQgghRFWSkUFCCCGEEEJUQ5LoCyGEEEIIUQ1Joi+EEEIIIUQ1JH30HyKdTsfVq1e5efMmWq3W1OGUy9LSkhMnTpg6jEeOra0tXl5eWFlZmToUIYQQQjzmJNF/iFJTU1EoFDzxxBNYWVmZ9eJOarUaB4eqWf2zutLr9Vy7do3U1FQaNmxo6nCEEEII8ZiTrjsPkVqtpm7dulhbW5t1ki8ejEKhwM3Njby8PFOHIoQQQgghif7DZmEht7w6kwc4IYQQQpgLyTofIUeOHGHUqFEEBgYycOBAxo8fz5kzZ0wdFgCRkZH069ePnJycYvvbtWtHamqqiaISQgghhHh8SaL/iCgoKOCll14iMjKSDRs2sHHjRgIDA/nXv/5lNgN7L168yDvvvGPqMIQQQgghBDIY95GRm5tLVlZWsTfmgwYNQqVSMXPmTNzd3ZkyZQoAsbGxbN26ldGjR7No0SLq1avHmTNnKCwsZPbs2bRv356srCxmz57NyZMnUSgU+Pr6MnXqVCwtLWndujVjx47lwIEDpKenM378eIYPH15hjKNHjyY2NpaffvqJvn37ljj+888/8+mnn6LT6XBwcGD69Om0adOGJUuWcPHiRTIyMrh48SIeHh58+OGHuLu7s2rVKqKiorCyssLGxoY5c+aQmZnJ66+/zo4dO7CwsCA3N5fevXuzadMmhgwZQkhICAkJCVy+fJmgoCBee+01AFavXs13332HhYUFNWvW5M0336Rhw4ZERkaiUqk4deoUV65coWnTprz//vsyGFkIIYQQjzR5o/+IqFGjBhEREYwfPx5/f38iIiKIiYmhW7dujB49mpiYGAoLCwGIjo4mLCwMgKNHj/LCCy+wfv16Bg8ezKJFiwCYN28ezs7ObNiwgZiYGE6dOsXKlSuBom8PnJ2diYqK4pNPPuG9994jPz+/whhdXV2ZP38+s2bN4vLly8WOnTt3jrfeeoslS5YQFxfHq6++ysSJE8nOzgbg4MGDfPzxx2zZsgU7OzuioqLQarW8++67fPnll8TExDB06FAOHTpE+/btqVGjBrt37wZg06ZNdO3aFVdXVwBycnIMDwgrV64kJSWFhIQEvvzyS7799lvi4uIYOHAgkyZNQq/XA3Ds2DG++uorNm/ezMWLF9myZUtlf2VCCCGEECZVZYl+06ZNKzznk08+wc/Pj6+//vqezn9YlixZgo+PD0FBQQwaNIjAwED27t1r6rAIDw8nPj6emTNnUqtWLb744guCg4Px8vLCy8uLnTt3cu7cOdLT0+nevTsAderUoXnz5gC0aNGCzMxMAHbt2sXIkSNRKBRYW1sTFhbGrl27DHX5+fkB0LJlSwoKCkr0vS9L9+7dCQkJISIiAp1OZ9i/d+9eunTpQr169QAMifmxY8cA6NSpEyqVqlicSqWSfv36ERYWxpw5c3BycmLIkCEAjBgxgujoaKDoTf2wYcMMdfn7+wPg4eGBm5sbmZmZ7N69m4CAAMPDwODBg0lLSzOMH/D19cXa2horKyuaNGliuE9CCCGEEI8qk77Rj42N5euvvyY8PNyUYZQqLCyM2NhY4uLi+OCDD5g6dapJ4zl06BBffvklKpWKXr16MW3aNDZt2oRCoSA+Pp4RI0YQExPDmjVrGDp0qGH2F1tbW0MZCoXC8AZbp9MVmyFGp9MZvhEAsLGxMVwDGK67F1OnTkWtVrN8+fJi5d89I41erzfUWVacCxYsYPny5dSvX5/PP//c8HsIDAzk0KFD7N27l5ycHDp27Fgi9jvLuvOh437qF0IIIYR4VFV5or9v3z5eeOEFJk6cSN++fXn11VcpKChg1qxZpKWlMWnSpGIrsC5ZsoQlS5YYtnv37k1qaiparZb33nuPkJAQBg0axP/93/+VW/6WLVsICgoiKCiIwMBAmjZtytGjRzl9+jSjRo0iNDSUXr168cMPP1T4GbKysnBzczP6vbkfrq6uLFu2jIMHDxr2ZWRkkJ2dTZMmTejbty8nTpzgp59+IjQ0tMLyunfvzv/+9z/0ej0FBQVER0fTrVs3o8RqbW3NRx99xMqVKw1zynft2pU9e/aQkpICYOhD37Zt2zLLuX79Oj179sTZ2ZmxY8fy2muv8ccffwBgZ2fHoEGDmDFjhqGbUnl8fX3ZvHkz169fByAmJgZnZ2caNGhQ2Y8rhBBCCGGWHspg3MOHD/Pjjz/i7u7O0KFD2bNnD3PmzGHPnj18/vnneHl5VVjG7W4a69ato6CggHHjxtGqVasyy+/Xrx/9+vUDivqjd+jQgTZt2vDOO+8wceJEunbtSkpKCoMGDSrW7eO2qKgofv75ZwoKCkhOTmbOnDlGvCP3r2HDhnz22WcsWrSIK1euYGNjg6OjI++++y6NGjUCoG/fvly9etXQPaU8M2fOZN68eQQGBqLRaPD19eXll182WryNGjXiv//9LzNnzgSgcePGvPXWW0yePBmtVoutrS3Lly/H0dGxzDJcXV2ZMGECY8eOxdbWFqVSybx58wzHBw8eTHR0NMHBwRXG4+Pjw9ixYxkzZgw6nQ5XV1dWrFgh6xoIIYQQotp6KIm+t7c3np6eADz55JMP1P85ISGBEydOGPrK5+TkcOrUKRo3blxu+WvWrOH48eN88803QNF877t372bFihWcPn26zL7nYWFhvPLKKwD89ddfjBgxgoYNG9K+ffv7jt1YunTpQpcuXUo9lpOTw4EDB5g1a5ZhX+fOndm4cWOp2y4uLnz00UellnXq1CnUanWx7YrMnz+/xL7nnnuO5557zrDdv39/+vfvX+K82/e5tO2wsLBS39jr9Xp27dpFUFBQsYeFHTt2FDvvzu0RI0YwYsSICmMv7bMIIYQQQjxqHkqiX1qf6bIoFIpi/ak1Gg0AWq2WiIgInn32WaCoW4eDgwNHjhwps/zff/+d5cuXG6ZnBHjttddwcnKiV69eBAQEFEuEy9KoUSOefvppjhw5YtJEvyy7d+/m9ddfZ9iwYTz11FNVUsfevXt57733Sj3WuXNnZsyYUSX1lsXf3x93d3eWLl36UOsVQgghhHhUmN08+i4uLuzbtw8omhoyIyMDKHqbHR0dTa9evSgoKGD48OHMnj27zHIuX77Mf/7zHxYvXkzNmjUN++Pj4/nxxx/x8PDg+++/B4oeIpRKZZll3bp1i+PHjzNy5EhjfESj8/X1Zf/+/VVaR5cuXYiNja3SOu7H3W/uhRBCCCFEcWaX6AcEBPDTTz8REBBAy5YtadGiBVDUhSM5OZmQkBAKCwsZPHgwnTt3NjwU3G3p0qWo1Wrefvttw8qxL730Eq+88grDhw/HxsaGZs2aUbduXVJTU0sMyrzdR9/CwoL8/Hyee+45unbtWrUfXgghhBBCCCNR6GUeQaPLz8/n2LFjtGrVqli3ohMnThjmtDd3arVaVoZ9QI/S71k8uNuLtwkhSidtRIiKVbadlJVz3iZTjgghhBBCCFENSaIvhBBCCCFENSSJvhBCCCGEENWQJPqPsdTUVJo2bUp8fHyx/b179+bSpUsmikoIIYQQQhiD2c26I4rT6fTsOpxK7K5zXL2ZR01nW4J6PEmPdl5YWCgqXb6VlRVvvvkmcXFxqFQqI0QshBBCCCHMgbzRN2M6nZ73vtnPZ2sSOZuayc3sfM6mZvLZmkTe+2Y/Ol3lJ0xyd3enW7duvP/++yWOLV++nICAAAIDA5k/fz5arZbU1FSCg4OJiIhg4MCBjBkzhps3b6LRaIiIiCA4OJjg4GCio6PJzs6mc+fOZGdnA0XfIAQEBJRZBsAvv/xCUFAQgYGBTJw4katXrwJF3zIsXryYIUOGMGDAAI4dO0ZycjJ+fn6GBdb27dvH+PHj2bdvH+Hh4bz44osEBASwYMECli5dyuDBgxk8eLChzPLqSk1NNZQ5atQoAL7++msGDRpEcHBwsRWIhRBCCCHMkST6ZmzX4VSOnM4gr0BbbH9egZYjpzPYdeSiUeqJjIxkz549xbrwxMfHs2PHDmJiYli3bh3JyclERUUBcPLkScLDw9m4cSNOTk5s2LCBw4cPk5mZyfr161mxYgUHDx5EpVLh5+fHli1bAFi/fj3BwcFllnHt2jVmzZrFZ599xoYNG3j66aeZM2eOISZnZ2fWrFlDWFgYK1asoEGDBnh5eRnWUli/fj2DBw8GIDExkdmzZxMTE8P333+Pq6sra9eupWnTpmzatKnCuu6m1WpZsWIFMTExrF27Fo1GQ1pamlHuvxBCCCFEVZBE34zF7jpXIsm/La9AS+yvZ41Sj0qlYu7cubz55puGt+/79+9nwIAB2NnZYWlpSWhoKAkJCQC4ubkZFjLz9vYmMzMTb29vkpKSGDduHFu2bGHatGkAhIaGGlbU3bhxI0FBQWWWcfToUdq0aYOXlxcAzz//PHv37jXE6evrazj/9jcAoaGhxMXFkZuby969e/H39wegSZMm1K5dGzs7O1xcXAyLndWpU4dbt25VWNfdlEol7dq1Y8iQIXz66aeEh4fj4eFRqfsuhBBCCFGVJNE3Y1dv5lXq+P3o3r17sS48t7vD3KmwsBCg2IIMCoUCvV6Pi4sLmzZtYuTIkSQlJRESEsKtW7fo2LEj6enpbN26FS8vL0NyXFoZd9ep1+sNdd55jULxz9iEfv36ER8fz08//USPHj0M51hZWRUrS6lUFtuuqK7b68jduW/p0qW8/fbb6PV6xo8fz/79+0vcIyGEEEIIcyGJvhmr6WxbqeP363YXnvT0dDp27MimTZvIy8ujsLCQmJgYunTpUua127dvJyIiAj8/P2bOnIm9vT2XL19GoVAQHBzMvHnzDN1qytK2bVsSExMN/eNXr15N586dy73Gzs6OHj16sHDhwgrLv9e6XFxcOHv2rOFzAVy/fp2AgACaNGnCv//9b3x8fDh16tQ91yeEEEII8bDJrDtmLKjHk3y2JrHU7ju21kqCejY2an23u/CMGzeOHj16kJ+fT2hoKIWFhXTv3p2RI0dy5cqVUq/t0aMHW7duZcCAAdjY2DBo0CCaNm0KwIABA1i5ciV9+vQpt/6aNWsyZ84cJk+ejEajoU6dOrzzzjsVxj1gwAB+//132rZte8+ftby6Xn31VebOncunn35K9+7dAXB1deX5559nyJAh2NnZ0bBhQ0JDQ++5vupGm6dGfeI3FBZKHJp3xcLaztQhiQdUkHEBvU6HjccTpg6lQnq9jsx9G8g5fQArt7q49HgeS0dXU4clhBBmS6G/3UdBGE1+fj7Hjh2jVatWxbqonDhxgubNm99zObdn3bl7QK6ttZKnmtRi+phORpliszRqtRoHB4dKl6PT6fjhhx9ISkpi5syZRoisOK1Wy6JFi3BzcyM8PNzo5T+I+/09P2q06kxSV05De6toliIrtzrUfeGDxy7ZP3ToEO3btzd1GA9Mr9OStuZDcs4cAMD2idZ4Pj8DC0trE0dWthvxMdzYucqwbe3ZCK9xH5owosdPYfYNck4fQOlQA3vvDigslGWe+6i3ESEehsq2k7Jyztvkjb4Zs7BQMH1MJ3YduUjsr2f/mUe/Z2N6PFW3ypJ8Y5o8eTKXL1/mq6++qpLyQ0NDcXFxYdmyZVVSvigp649fDUk+gObaJdQnEnBs29uEUYn7pT6935DkA+Sd/4PsY7txesrfhFGVT30iodh2wZW/0Ny4gpWLp4kierwUZKRw6ZsZ6PJzALBr1Jbaw2SqYSHMmST6Zs7CQoHf0174Pe1l6lAeyNKlS6u0/PXr11dp+aIUupJdyfSlDN5+XGUfj+fGrtXoNfk4deiPc9dgU4dUKu2ta/e0z5xYOrtTkJZk2FZY26J0qGHCiB4vmQc2GZJ8gNy/Esm7eBrbuk3uu6zCzAw01y9j49UUC6uSbyGFEMYhg3GFEPdF1bonFvZOhm2lU00cmnc1YUTmo+DaJdLXL0Zz7SKFt65yfcd3qE8fqPhCE7Bv0gnFnd10LCxxaFb2gHtz4Oo3HMsatQBQWFrj1iccvU6H/o6HT71Wg/rkXrKP7UZXkFuijNzkY1zb8R1Zf+wsdp2omFadWWJfYdYNMvdvJCtxBzpN/j2Vc3NfHBc+m8jlVbO58OnL5F9JqvgiIcQDkTf6Qoj7Yunoitf4j8j+41dQKnFs1ROlbeXHc1QHeRf+BH3xbzdyzx/FoUlHE0VUNitnd2qPnEPm/g2g0+LUMQBr9/qmDqtc1jW9qDfxMwrSklHY2HFtyxdc3bwMC3snavYdj0OTTlz85g0KrpwDl3nvmAAAF41JREFUwLKGO3VfeB/l3w+mWYk7yNj4maG83PN/4B74ikk+y6OotAej9LgloCl6oMo8+CN1w+eX229fl6fmxs4fDO1El3OLG7tW4zk0smqCFuIxJ4m+EOK+WTq64twtxNRhlEtz4wr5l85i69XU8Ba4qtl4PllyX+2S+8yFbV1vbEOmGr1cbZ6a69u/JS/lODZ1m+DWe7TRutgoLJTY1G7E1a0ryU1KBIqSxYyNn6F7Ns+Q5AMUZqaTlbjD0H0q88DmYmVl/7ELtz5jUdo5GiW26q7UBF7zz7cmBVf+IvfcEey9yx5YqM1Toy8sKLavMOu60WIUQhQnib4Qotq5deRnrm76e4C2wgL3kKmoHkL3IpvajXD1H82NPWvQFxbg9FQfVK16VHm95ubq5uWoT/wGFA3W1qozqR1m3Fm3CtLOF9vWa/IpzEwvcZ6uIA/NjSvoCvJQKO/6L8/Coty3z6I4p6f6kHP6AFA0WZ+FvRO6nFvFztHryx+vY+Xsjo1XM/JTTxr2ObZ+/NqIEA+LJPqPuS1btvD5559TWFiIXq8nKCiI8ePHmzosIR6YXq/n2s/f3LFDx7VtKx9Kog/g3CWIGp0Ggk6HwtKqxHH1qX3kJv+JTZ3GqFp2R6Ew3VApvU5L7l9Fb8XtGrU1WtKbc+73Ytu5546g1+uM+lntGrYp6ir1N6WDM07t+5OVuAPt32+IFdZ2FFxNIWXpJACs3OoCCm4nqjU6DsDCxt5oMVWGNicLCxu7kg8jRqIryEN9ci/odTg06/JAn9veuz21R7xF9vF4LB3dsGv0FJd/mIP+7wG61u71sX+yXYXleD4Xyc2969FcvYh9k45mPdOTEI86SfTNnF6vI/vPPWTu20Bh1jUsHd2o0TnQKAlCWloa77//PmvXrsXFxQW1Ws2oUaNo2LBhuavgCmHe9IbE4zZt1o2HGoHCQgmlJM03f1vH9V/+Z9jOv3SGms+OM0qd6pN7ubF7NbqCfJza98O5y6Byz9dp8rn07UwKrvwFgLVHQ+qMnoeFdeVX3LauWY/8S2cM21Y16xr9gca5azC6fDXq479h6eyBm/9oLFXO1A3/gKwjP6MvLMCqVj0yYj82XKO5dpEaXUOwdHTF2r0+dg1aGS2e7D93k5X4C0p7J5x9BmNd697GO2jVmaTFfEheygks7J2o1f8low+K1uXncvHraWiuXQLgxu7/R91xHzxQlyW7J1pj90Rrw3a9fy0k+3g8Fjb2qFr63tODitLeEbfeo+67biHE/ZNE34zp9TrS1nxIblIi+r9nMyhQZ/79tXgCHkMiKvWf540bN9BoNOTl5QHg4ODA/Pnz+f333wkPDyc6OhqAtWvXkpiYSNu2bdm9ezeZmZmkpKTg4+PD22+/DcDy5cuJi4tDqVTi4+NDREQEly9fZvLkyXh7e3PixAnc3Nz4+OOP2bZtG3v37uWjjz4CYMmSJdjY2JCfn8+lS5c4f/48169fZ8KECSQkJJCYmEizZs1YtGgRCoWizLpGjx7Njh07DGUCvPzyy8yYMYMzZ4qSjuHDhzN06NAHvmfiEVDqGoAPb13A9NiPyT4eDwoFNToF4tZ7pOFY5sHifcSzft+Gm/+YSr/F1Vy/TNrajwwDHK9v/wYrFw8cmnYu8xr18XhDkg9QkJZE9p97cGpX/grW96JmvxdJi/mQwsx0lI5u1BowwXBMm5tFXvJxrGrWxbrmg08brFBa4uY/Bjf/McX2Wzq64OL7HABZR3eWuE5fmE+NjgEPXG9p1KcPkL5+sWE7JymR+pOW3tMicldiPiQ/5QRQNNYgfcOnNGjU1qgL0GWf+M2Q5EPR2IXsY7uo0XFApcu2rFHLbKeQFULI9JpmLfvPPcWS/Nv0mnxykxJR/xlfqfKbNWuGv78/ffr0YciQIXz44YfodDqef/55rl69yoULF4CiueoHDx4MwOHDh/nkk0+Ii4vjl19+4dSpU/z666/s2LGDmJgY1q1bR3JyMlFRUQCcPHmS8PBwNm7ciJOTExs2bCAgIICEhASys7MB2LhxI0FBQQCcPn2a7777jrlz5zJ9+nT+9a9/sXHjRo4fP15hXaU5fPgwmZmZrF+/nhUrVnDw4MFK3TNh/nR56hL7FA9pnu4b8WvJPraraK0BbSGZCevISTpqOH73fOEKSytQVH7hu9xSZ/v5o9xrtKXcJ11+yX0PwqZ2I+pN+ox6k5dRf/IybL2aAZB38TQXPp1AWswHpK74Nzf2rDFKfWWxf7IdimIJswJV825Gr+f2eITbdDm3yD1/rMLrMg9sNiT5t+kLcim8WXKsQaVoC0vs0hdqjFuHEMIsSaJvxjL3bSiR5N+m1+Rzc9+GStcxe/ZsduzYwbBhw7h06RJDhw5l27ZtDBw4kLi4OC5dusS1a9do27YtAO3atUOlUmFnZ0e9evXIzMxk7969DBgwADs7OywtLQkNDSUhoWgFSzc3N1q0aAGAt7c3mZmZODg40LNnT7Zt28bBgwepV68eHh4eAPj4+GBpaUmdOnWoVasWjRs3xtLSEg8PjwrrKo23tzdJSUmMGzeOLVu2MG3atErfM2HelPZO2NRuXGyfqrXfQ6n77oQPKJqG9G8uvs/DHd/COfsONUq/eBuPRiX2WXs0LPcaVfNuxfppK2zsUbXwqXQshvIUFljVcC/2+W7sikJ/x9z2N/esKfXBzFiUDjWoM2oODi18sG/cHs+h07Gt19zo9VjWcC+xz8rZo8Lrsv/cXWKfhYMLVpX4pqM0Ds27oVS5/lOHvROqVj2NWocQwjxJ1x0zVphV/iqV2qyrlSp/586d5OTkEBAQQGhoKKGhoURHR7NmzRoiIiJ49dVXsba2NrxtB7Cx+eeNpEKhQK/XoytlVdTCwsIyzwcIDQ1l2bJleHl5Gb4tALCy+mfwoqVlyX+eZdV1Z9m391laWuLi4sKmTZuIj4/n119/JSQkhE2bNuHk5FSiHFF9eDz3X67/8j8K0s5j16gtLj2HPZR6rWvVK7ZyK1AssVS18sXasyF5F45jU7sxNrVLJugPwqZ2I1x7j/p7th8Njm38cGzjV+41lk5u1Al/n6zDW9Hr9Tg9/SyWTjWNEk9ZtDnZxbb1Wg26gjwsqnAdBhvPRnhUwRSid6rRaSA5534v6gqlsKBGp4H3tCaBpaMbxV7lKBR4DJ5q9JmAlPaO1B33AdlHd6LX63Bs7Yelo4tR6xBCmCdJ9M2YpaMbBaWsRHib0rFy/ynb2toyd+5c2rRpg5eXF3q9nhMnTtC8eXPq1KmDp6cnUVFR/PDDD+WW06VLF5YtW8bzzz+PpaUlMTExFQ7m7dChA1euXOHixYu88cYb9xxzWXU5OTlx8+ZNrl+/jkqlYvfu3fTq1Yvt27cTFxfH4sWL8fX1JSEhgcuXL0uiX81ZOrriPujVh16v2zMvkJt0FK36JgA2dbxL9Hm3rulVqb7pZXHuGkyNTgPQ63QlugiVxdqtDm59xho9lrI4tu3NtTvmubdr1BZLJ7eHVn9VUdo74jXuQ/LTzqO0c7znz+TS43nyUk+izb4BCgtce4/Crn6LKonRUuVi9mtfCCGMTxJ9M1ajcyBXNy8vtfuOwsoG586BlSq/S5cuTJ48mZdffhmNpqi/pq+vL5MmTUKj0RAQEMDWrVsN3WrK0qtXL06cOEFoaCiFhYV0796dkSNHcuXKlXKve+aZZ7h58ybW1tb3HHNZdVlaWjJ+/HiGDBmCp6cnrVsXzQrRo0cPtm7dyoABA7CxsWHQoEE0bdr0nusT4n4o7R2p/+8vyL94GgtbVZUk9OVRKK1QmPG08DU69ENp70jOmYNY1fQy+qBYU7PxeOK+zreuVY/6k5aRd+k0Vs6e1eKhRwhhXhR6falTVIhKyM/P59ixY7Rq1apY15Xbb8vvVWmz7kBRkm/XsG2lZ90pT2ZmJrNnz6Zfv348++yzRi1br9ej0WgIDw9nxowZtGzZ0qjlm9r9/p7Fo+nQoUO0b1/2CqBCPO6kjQhRscq2k7JyzttkMK4ZUygs8BgSQa2ACVh7PonSoQbWnk9SK2BClSb5er2evn37olAo6NOn8lPt3S0jIwMfHx/atm1b7ZJ8IYQQQghzIV13zJxCYYGqlS+qVr4PsU4F27dvx8GhagbIubu7c+DAgSopWwghhBBCFJE3+kIIIYQQQlRDkug/ZKVNDymqDxnyIoQQQghzIYn+Q+Tg4MDFixcpKCiQhLAa0uv1XLt2DVtbW1OHIoQQQgghffQfJi8vL65evUpycrJhQSlzVVBQcF/TXooitra2eHk93CkVhRBCCCFKI4n+Q2RhYYG7uzvu7iWXSzc3hw4dom3btqYOQwghhBBCPCDpuiOEEEIIIUQ1JIm+EEIIIYQQ1ZAk+kIIIYQQQlRD0ke/CtyeUaegoMDEkVROfn6+qUMQwqxJGxGifNJGhKhYZdrJ7VyzrNkcFXqZ59HosrKyOH36tKnDEEIIIYQQj4EmTZrg6OhYYr8k+lVAp9OhVquxsrJCoVCYOhwhhBBCCFEN6fV6NBoNDg4OWFiU7JEvib4QQgghhBDVkAzGFUIIIYQQohqSRF8IIYQQQohqSBJ9IYQQQgghqiFJ9IUQQgghhKiGJNEXQgghhBCiGpJEXwghhBBCiGpIEn0hhBBCCCGqIUn0hRBCCCGEqIaUb7/99tumDkI8Gv766y/GjRvHgQMHuHTpEk899ZSpQxLC7Gi1WsaMGYO3tzceHh6mDkcIs3PmzBlmz57Nr7/+ip2dHfXr1zd1SEKYlQMHDvDxxx+zdetWMjMzadmy5QOXZWnEuEQ1d+jQITw9PbG1taVdu3amDkcIs7R8+XLc3d1NHYYQZisnJ4cZM2agVCpZuHAhPj4+pg5JCLNy69Yt5syZg7W1NRMnTuS555574LIk0Rdl+vLLL9mzZ49he9asWfj7+6NSqZgwYQJfffWVCaMTwvTubiPDhg3D29sbnU5nwqiEMC93t5OVK1dy4cIFIiMjGT16tAkjE8I8lNZG9Ho9CxYsqHQbUej1en1lAxSPh/Xr19O1a1c8PDx46aWXWLFihalDEsKsTJ06FZVKxbFjx3jyySf58MMPTR2SEGbn2LFjPPHEE6hUKl544QVWrlxp6pCEMCu3bt3ivffeY/jw4bRu3bpSZUmiL+7Z0aNH+frrr1GpVPj5+eHv72/qkIQwS0uWLMHPz6/Sf6CFqI4OHTrEt99+i0qlokmTJowZM8bUIQlhVqZNm8aVK1dwd3endu3avP766w9cliT6j6Hs7GzCwsJYvnw5Xl5eAGzYsIFly5ZRWFjImDFjGDFihImjFMJ0pI0IUTFpJ0KUzxzaiEyv+ZhJTExk2LBhnD9/3rAvLS2NRYsWsWrVKtavX8/q1as5e/as6YIUwoSkjQhRMWknQpTPXNqIJPqPmejoaN56661is4L89ttvdOnSBWdnZ+zt7enbty9btmwxYZRCmI60ESEqJu1EiPKZSxuRWXceM++8806Jfenp6dSqVcuw7e7uztGjRx9mWEKYDWkjQlRM2okQ5TOXNiJv9AU6nQ6FQmHY1uv1xbaFeNxJGxGiYtJOhCifKdqIJPoCT09PMjIyDNsZGRmy4I8Qd5A2IkTFpJ0IUT5TtBFJ9AXdunUjISGB69evk5uby9atW+nRo4epwxLCbEgbEaJi0k6EKJ8p2oj00Rd4eHgwZcoURo8ejUajYciQIbRp08bUYQlhNqSNCFExaSdClM8UbUTm0RdCCCGEEKIakq47QgghhBBCVEOS6AshhBBCCFENSaIvhBBCCCFENSSJvhBCCCGEENWQJPpCCCGEEEJUQ5LoCyGEEEIIUQ1Joi+EEI+hlJQUXnnllfs6Ly0tjbCwsKoOrUKffvopP//8s6nDEEIIsyeJvhBCPIYuXbpEUlLSfZ3n4eFBVFRUVYdWoX379lFYWGjqMIQQwuzJgllCCPEI2rdvHwsXLqR27dokJSVhZ2fHiy++yHfffUdSUhLPPvss/v7+zJ07l40bNxqumTt3LrGxsfTr14+0tDQ6duzIV199xfLly9m+fTt5eXnk5uby3//+l969exc7b/bs2QQGBnL48GE0Gg3z588nISEBpVJJmzZtmD59OiqVit69exMSEkJCQgKXL18mKCiI1157rdzPExkZyc2bN0lJScHPz48hQ4YwZ84c1Go1GRkZNGvWjMWLF7NmzRoWLFiAi4sL06dPp2fPnixYsIADBw6g1Wpp0aIFM2fORKVSlVmXWq1m+vTpJCcnY2FhQcuWLZkzZw4A7777LomJiajVavR6PfPmzaN9+/ZERkZia2vL6dOnuXbtGr1798bZ2ZlffvmFjIwM5s2bR9euXYmMjMTGxoaTJ09y7do1fHx8mDlzJlZWVsb75QshxD2SN/pCCPGI+uOPP3jxxReJjY1FpVLx+eefs2LFCtauXcuqVatIT08v9TqlUsm8efOoX78+X331FRcvXuS3337ju+++Y8OGDUyZMoVPPvmkxHl3WrZsGenp6cTGxhIbG4tOp+ODDz4wHM/JyWHVqlVERUWxcuVKUlJSKvw8eXl5bNq0iYiICKKjowkODiY6OpqtW7eSmprKzp07GTFiBK1atWLatGk888wzfP755yiVStauXUtcXBzu7u4sWLCg3Hq2bduGWq0mNjaWNWvWAEVdlBITE0lPT2f16tVs3ryZkJAQvvjiC8N1x48f55tvvuF///sfK1euxN7enqioKEaPHl3svKNHj7Jy5Uo2b97MuXPnWL16dYWfXQghqoKlqQMQQgjxYLy8vGjRogUA9evXx9HREWtra1xdXXFwcCAzM/Oeyqlbty4ffPABGzZsIDk52fBGuzy7du1iypQphjfVo0aNYtKkSYbj/v7+QFF3Hzc3NzIzM6lXr165ZbZv397wc0REBPHx8XzxxRecP3+e9PR0cnJySlyzc+dOsrKy+O233wDQaDS4ublVWM+iRYsYNWoU3bp1Y8yYMTRo0IAGDRpQo0YNoqKiSElJYd++fTg4OBiu69WrF1ZWVtSqVQt7e3t8fX2Bont/8+ZNw3khISGG64KCgti+fTsjR44sNyYhhKgKkugLIcQjytrauti2pWXxP+lNmjThzt6ZGo2m1HL+/PNPJk6cyNixY/Hx8TF00ymPTqdDoVAU276zfBsbG8PPCoWCe+klam9vb/h56tSpaLVa+vfvj5+fH5cvXy61DJ1Ox4wZM+jZsydQ1C0nPz+/3Hrq1avHtm3b2LdvH3v37iU8PJw5c+ZgYWHBO++8Q3h4OP7+/jRq1Ii4uDjDdRXd79uUSqXhZ71ej4WFfHkuhDAN+esjhBDVlJOTE5cuXeLatWvo9Xo2bdpkOKZUKg2J+YEDB2jVqhXh4eF06tSJ7du3o9VqS5x3J19fX3744Qc0Gg06nY7vv/8eHx8fo8W+Z88eJk2aREBAAACJiYnFYro9GLd79+58//33FBQUoNPpePPNN1m4cGG5Za9atYrp06fTvXt3IiIi6N69O8ePHyc+Pp5evXoxfPhwWrVqxc8//2yo8378+OOPFBQUkJ+fz7p16+jVq9d9lyGEEMYgib4QQlRTFhYWhIWFERoaytChQ/Hy8jIca9y4MTY2NgwZMoSBAwdy48YN+vfvT0BAAPb29mRmZpKdnV3svDvfqE+YMIGaNWsSHBxM//79KSws5I033jBa7FOmTGHSpEkEBgYya9YsOnbsyIULFwDo3bs3CxcuZN26dUycOJG6desSEhJCQEAAer2eyMjIcssODg5Gq9USEBDA4MGDycrKYtSoUYSFhbF//34CAwMJCQmhXr16pKamotPp7it2W1tbhg8fTmBgIB06dCA0NPSB74MQQlSGzLojhBBCGElkZCTe3t6MGzfO1KEIIYT00RdCCFH1/vrrL6ZMmVLqsYYNG7J48WKj1vfaa6+VuU7AokWLaNSokVHrE0IIcyRv9IUQQgghhKiGpI++EEIIIYQQ1ZAk+kIIIYQQQlRDkugLIYQQQghRDUmiL4QQQgghRDUkib4QQgghhBDVkCT6QgghhBBCVEP/H8gM3aR1G/1HAAAAAElFTkSuQmCC\n" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(1,1, figsize=(12,6))\n", + "fig_args_horiz = {\n", + " **fig_args,\n", + " 'y': 'subtype',\n", + " 'x': 'mutation_rate_samp'\n", + "}\n", + "ax.set_xscale('log')\n", + "sns.stripplot(ax=ax, orient='h', **fig_args_horiz)\n", + "annotator.new_plot(ax, plot='swarmplot', orient='h', **fig_args_horiz)\n", + "annotator.configure(\n", + " hide_non_significant=True,\n", + " pvalue_thresholds=[[1e-4, \"****\"], [1e-3, \"***\"], [1e-2, \"**\"], [0.05, \"*\"]], # removing ns as won't be shown\n", + ")\n", + "annotator.apply_and_annotate()" + ] + }, + { + "cell_type": "markdown", "metadata": { "collapsed": false, "pycharm": { "name": "#%% md\n" } - } + }, + "source": [ + "Back to vertical, with a different format for pvalues" + ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 25, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", @@ -1165,32 +1315,33 @@ "\n", "sns.swarmplot(ax=ax, **fig_args)\n", "annotator.new_plot(ax, plot='swarmplot', **fig_args)\n", + "annotator.reset_configuration() # undo hide_non_signif and pvalues\n", "annotator.configure(**{**configuration, \"text_format\":\"simple\", \"text_offset\":6})\\\n", " .apply_test().annotate()\n", "fig.savefig(f'flu_dataset_log_scale_in_axes.svg', format='svg')\n" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - } + ] }, { "cell_type": "markdown", - "source": [ - "As a violin plot" - ], "metadata": { "collapsed": false, "pycharm": { "name": "#%% md\n" } - } + }, + "source": [ + "As a violin plot" + ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 26, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", @@ -1221,25 +1372,7 @@ "y_lims = ax.get_ylim()\n", "ax.set_ylim(y_lims[0], 1.25 * y_lims[1])\n", "fig.savefig(f'flu_dataset_log_scale_in_axes_violin.png', format='png')" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - } - }, - { - "cell_type": "code", - "execution_count": 24, - "outputs": [], - "source": [], - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%%\n" - } - } + ] } ], "metadata": { @@ -1258,7 +1391,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.8.10" }, "toc": { "base_numbering": 1, diff --git a/usage/example_tuning_y_offsets.svg b/usage/example_tuning_y_offsets.svg index 42a7655..e90c1c5 100644 --- a/usage/example_tuning_y_offsets.svg +++ b/usage/example_tuning_y_offsets.svg @@ -347,7 +347,7 @@ z - @@ -399,7 +399,7 @@ z - @@ -439,7 +439,7 @@ z - @@ -488,7 +488,7 @@ z - @@ -521,7 +521,7 @@ z - @@ -562,7 +562,7 @@ z - @@ -611,7 +611,7 @@ z - @@ -640,7 +640,7 @@ z - @@ -772,7 +772,7 @@ z - - - - - - - - - - - - - - @@ -886,244 +886,244 @@ L 2.12132 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