diff --git a/doc/source/dev/index.rst b/doc/source/dev/index.rst
index b236236a..21cfebb4 100644
--- a/doc/source/dev/index.rst
+++ b/doc/source/dev/index.rst
@@ -7,4 +7,4 @@ Development
contributing
inspect_slycot
- slicot_slycot
+ inspect_slicot_slycot
diff --git a/doc/source/dev/inspect_slicot_slycot.ipynb b/doc/source/dev/inspect_slicot_slycot.ipynb
new file mode 100644
index 00000000..fd965ad4
--- /dev/null
+++ b/doc/source/dev/inspect_slicot_slycot.ipynb
@@ -0,0 +1,694 @@
+{
+ "cells": [
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Inspect Slycot vs SLICOT"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "This notebook shows how to inspect the slycot module and the slicot libary.\n",
+ "The result gives us a insight which slicot routines are implemented slycot."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'0.1.dev612+g3d12a1d'"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import re\n",
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import matplotlib.pyplot as plt\n",
+ "from matplotlib_venn import venn2\n",
+ "\n",
+ "import slycot\n",
+ "slycot.__version__"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Helper function"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def print_list_chunks(routines_list, n=8):\n",
+ " \"\"\"Print list in chunks of lists.\"\"\"\n",
+ " start = 0\n",
+ " end = len(routines_list)\n",
+ " step = n\n",
+ " for i in range(start, end, step):\n",
+ " x = i\n",
+ " print(routines_list[x:x+step])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_slycot_routines(sly):\n",
+ " all_attributes = dir(sly)\n",
+ " r = re.compile(\"[a-z][a-z][0-9][0-9a-z][a-z][a-z]\")\n",
+ " matched_attributes = list(filter(r.match, all_attributes)) # Read Note below\n",
+ " return matched_attributes"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Inspect function"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "There are currently 49 routines that are found in slycot.\n",
+ "------\n",
+ "['ab01nd', 'ab05md', 'ab05nd', 'ab07nd', 'ab08nd', 'ab08nz', 'ab09ad', 'ab09ax']\n",
+ "['ab09bd', 'ab09md', 'ab09nd', 'ab13bd', 'ab13dd', 'ab13ed', 'ab13fd', 'ab13md']\n",
+ "['mb03rd', 'mb03vd', 'mb03vy', 'mb03wd', 'mb05md', 'mb05nd', 'mc01td', 'sb01bd']\n",
+ "['sb02md', 'sb02mt', 'sb02od', 'sb03md', 'sb03md57', 'sb03od', 'sb04md', 'sb04qd']\n",
+ "['sb10ad', 'sb10dd', 'sb10fd', 'sb10hd', 'sg02ad', 'sg03ad', 'sg03bd', 'tb01id']\n",
+ "['tb01pd', 'tb03ad', 'tb04ad', 'tb05ad', 'tc01od', 'tc04ad', 'td04ad', 'tf01md']\n",
+ "['tf01rd']\n",
+ "None\n",
+ "\n",
+ "\n",
+ "There are currently 607 routines that are found in slicot.\n",
+ "------\n",
+ "['mb01wd', 'tg01gd', 'ab13fd', 'sg03ay', 'mb01oe', 'mb02fd', 'tg01oa', 'dg01ny']\n",
+ "['sg03ax', 'fb01qd', 'ma02az', 'mc01md', 'md03by', 'tf01mx', 'ib01nd', 'mb02rz']\n",
+ "['mb04bp', 'tb01kd', 'ab09gd', 'ma02jz', 'ud01cd', 'ib01rd', 'nf01bx', 'mb02rd']\n",
+ "['ma02es', 'mb04iy', 'tg01id', 'mb01rd', 'mc01xd', 'mb04wr', 'sg03bs', 'mb03kc']\n",
+ "['ma02cd', 'tb04ad', 'md03bx', 'mb03vy', 'ab09cd', 'tf01nd', 'sb09md', 'sb03ot']\n",
+ "['mb04pu', 'mb04yd', 'mb02pd', 'mb04tu', 'mb02ud', 'ib01cd', 'mb04dp', 'tg01fz']\n",
+ "['sb04od', 'nf01ad', 'mb03qd', 'ab09bd', 'mb02jd', 'sb02mw', 'ma02ad', 'mb04dl']\n",
+ "['sb08ed', 'tb01uy', 'md03ba', 'ab05nd', 'mb03pd', 'sb02mx', 'sb04ow', 'ma02mz']\n",
+ "['mb02cy', 'ag08by', 'mb03bb', 'ab09cx', 'mb01kd', 'sb02sd', 'mb01xd', 'sb01md']\n",
+ "['mb02ny', 'sb02ox', 'sb10pd', 'ma01cd', 'tg01hd', 'mb02nd', 'sb02cx', 'sb04px']\n",
+ "['mb03qg', 'tg01hx', 'mb03ag', 'mc01py', 'mb03kb', 'mb04jd', 'tg01bd', 'tb03ay']\n",
+ "['ab13ed', 'sb03rd', 'ma02id', 'ma02md', 'sb03os', 'mb02cv', 'mb05oy', 'sb06nd']\n",
+ "['nf01bp', 'sb02od', 'mb03md', 'fb01vd', 'ma02iz', 'tb01ld', 'mb02sd', 'tb01nd']\n",
+ "['ud01md', 'mb02xd', 'mb02md', 'sg03br', 'mb04az', 'sb02ru', 'sb10qd', 'sg03bu']\n",
+ "['sb04qr', 'mb03lf', 'ma01ad', 'sb04rd', 'ma02gd', 'sb04ry', 'ab13ad', 'ab13md']\n",
+ "['nf01by', 'mb04nd', 'mb03yt', 'sg02cx', 'tg01hu', 'ab09kx', 'mb04hd', 'mb03gd']\n",
+ "['sb08cd', 'mb03od', 'sb04mr', 'mb02kd', 'ab09jx', 'ud01bd', 'fb01sd', 'mb03rd']\n",
+ "['ab07nd', 'mb03fd', 'sb03ou', 'mb03ya', 'mb01rh', 'sb08hd', 'ab08nw', 'ab07md']\n",
+ "['ab05qd', 'mb02qy', 'mb03id', 'ma02bd', 'ma02dd', 'mb04ed', 'sb03td', 'mb04tv']\n",
+ "['td04ad', 'tb01ud', 'tc01od', 'nf01bs', 'ma02oz', 'sg02nd', 'mb04ru', 'mc01rd']\n",
+ "['mb03bd', 'mb04tt', 'sb08ny', 'tg01ad', 'sb04qu', 'nf01bf', 'tg01qd', 'mc01td']\n",
+ "['mb04fp', 'mb03ud', 'mb3lzp', 'sb04nv', 'mb04qb', 'mb04wp', 'mc01sy', 'sb10dd']\n",
+ "['mb02sz', 'mb04kd', 'tb04bw', 'mb01ry', 'sb03mv', 'tb03ad', 'mb03gz', 'mb01ot']\n",
+ "['mb03be', 'tb01zd', 'ab04md', 'mb01os', 'sb03qx', 'mb04pb', 'nf01bu', 'mb04su']\n",
+ "['mc01od', 'sb16bd', 'mb02td', 'sg03ad', 'sb03qy', 'mb03xs', 'md03bb', 'mb04qc']\n",
+ "['mb03jd', 'sb01by', 'ab09nd', 'sb03md', 'mb04oy', 'mb05nd', 'ab08nx', 'mb01rb']\n",
+ "['dg01md', 'mb02wd', 'sb03ud', 'mb03py', 'mc01pd', 'ma02pz', 'ab09iy', 'ma02od']\n",
+ "['sb10td', 'tf01my', 'sb16cy', 'tg01oz', 'ab05pd', 'mb04cd', 'sb16ay', 'sb10hd']\n",
+ "['mb02gd', 'mc03md', 'mb03bc', 'sb04nx', 'mc01qd', 'ab01od', 'ab09jd', 'sb16ad']\n",
+ "['sg03bv', 'nf01bb', 'ab09dd', 'mb03lp', 'md03bf', 'mb03ah', 'mb3jzp', 'sb04mu']\n",
+ "['ab09kd', 'sb03ov', 'sb03pd', 'fd01ad', 'sb03sd', 'td05ad', 'mb02hd', 'mb02cd']\n",
+ "['mb03qx', 'sb04nd', 'mb04tb', 'sb04pd', 'tg01jy', 'tb04cd', 'tg01dd', 'ab09ed']\n",
+ "['mb03wx', 'tg01pd', 'tf01pd', 'sb08fd', 'ab13ax', 'nf01ba', 'sb08md', 'mb04dy']\n",
+ "['sb04my', 'ab09fd', 'mb04vd', 'mb01md', 'ib01oy', 'mb04ld', 'sb01bd', 'sb02mu']\n",
+ "['sg03bx', 'tg01ed', 'mb02qd', 'mb01ss', 'mb01rw', 'sb10ud', 'mb03cz', 'ag8byz']\n",
+ "['sb02ow', 'mb02dd', 'sb08nd', 'mb03my', 'mb03yd', 'tg01od', 'mc01sw', 'ma02bz']\n",
+ "['ib01ad', 'ab09hd', 'ud01mz', 'td03ad', 'sb03my', 'ib03bd', 'mb04dd', 'mb04xd']\n",
+ "['ma02hd', 'ab09ax', 'tg01hy', 'mc01sx', 'tb01ux', 'df01md', 'mb04vx', 'mb04wd']\n",
+ "['ab08md', 'tb01vd', 'nf01ay', 'md03bd', 'mb03rz', 'ab09ix', 'ab13dd', 'tb01iz']\n",
+ "['nf01bw', 'mb04qf', 'ab05sd', 'mb04db', 'mb03ai', 'sb08gd', 'mb02od', 'mb04ty']\n",
+ "['mb02uv', 'ib01px', 'tb01ty', 'sb03oy', 'sb03mu', 'tg01nd', 'ab09hx', 'ab09id']\n",
+ "['mb04id', 'mb03ed', 'mb04di', 'mb04tx', 'sb03od', 'mb04xy', 'mb03hz', 'tc04ad']\n",
+ "['mb01rx', 'sb02ov', 'mb03zd', 'mb03jp', 'mb02yd', 'mb04ox', 'bd01ad', 'mb04fd']\n",
+ "['ab05md', 'tb04bx', 'dg01od', 'sb10zd', 'mb01rt', 'sb02mr', 'ab01nd', 'mb04bz']\n",
+ "['ma01bz', 'ma02ed', 'mb03ld', 'tb01md', 'tb01xz', 'mb04qs', 'ab09md', 'sb10id']\n",
+ "['sb03sx', 'mb02cu', 'ab13bd', 'mb3oyz', 'mb02tz', 'tb01px', 'mb03iz', 'sg03bw']\n",
+ "['mb04dz', 'nf01bv', 'bd02ad', 'tf01md', 'mb03wd', 'mb4dbz', 'mb04tw', 'mb03vd']\n",
+ "['mb01oo', 'fb01rd', 'mb04rb', 'mb03ry', 'mb01xy', 'tb05ad', 'ib03ad', 'mb03xz']\n",
+ "['mb05md', 'mb02ed', 'sb03mw', 'sg03bd', 'mb01ru', 'mb01oc', 'bb02ad', 'ab09jw']\n",
+ "['mb03cd', 'mb04pa', 'sb10yd', 'mb02jx', 'tg01az', 'sg02ad', 'ma02hz', 'mb03dz']\n",
+ "['tg01md', 'sb08my', 'tb04ay', 'sb02nd', 'sb02mt', 'sb04rw', 'mb04wu', 'nf01be']\n",
+ "['de01pd', 'sb02mv', 'sb10ed', 'sb10zp', 'mb03lz', 'sb02oy', 'sb04md', 'mb03bg']\n",
+ "['mb03ad', 'mb01uw', 'sb10kd', 'ma02jd', 'ma02gz', 'tf01qd', 'mb03td', 'mb04gd']\n",
+ "['tb04bv', 'tg01ld', 'mb03ba', 'ue01md', 'mb3pyz', 'mb03xp', 'sb02ou', 'mb01nd']\n",
+ "['sg02cw', 'mb04yw', 'sb04mw', 'mb01uy', 'sg03by', 'ib01py', 'mb02uw', 'tg01ob']\n",
+ "['mb03jz', 'mb04ad', 'tg01fd', 'mb03sd', 'ab13id', 'ab08ny', 'mb03za', 'mb02uu']\n",
+ "['ab08nd', 'mc01wd', 'tg01ly', 'mb01uz', 'mb03xu', 'mb03nd', 'ag07bd', 'sg03bt']\n",
+ "['mb03xd', 'ma02nz', 'ab13dx', 'ab08nz', 'sb04ny', 'mb03ts', 'sb04qy', 'mb03rx']\n",
+ "['mb03af', 'ib01md', 'mb03ke', 'sb02pd', 'sb16cd', 'ab8nxz', 'mb04bd', 'tf01rd']\n",
+ "['mb01ux', 'mb03bz', 'sb03sy', 'mc03ny', 'sb10ld', 'ma02fd', 'td03ay', 'bb04ad']\n",
+ "['mb03ab', 'dk01md', 'ab05od', 'mc03nx', 'mb01td', 'tb01id', 'tg01cd', 'mb04ow']\n",
+ "['sb04nw', 'mb03ae', 'mb03rw', 'mb03qy', 'sb04py', 'nf01bq', 'mb03dd', 'tb01kx']\n",
+ "['mb01ud', 'ma01bd', 'mb03ny', 'ab08mz', 'sb02rd', 'sb04qd', 'tb01wx', 'ag08bz']\n",
+ "['tg01wd', 'tb04bd', 'sb02md', 'bb01ad', 'mc01sd', 'mc01vd', 'sb10ad', 'mb01vd']\n",
+ "['de01od', 'ib01pd', 'mb03bf', 'sb02ms', 'mb04py', 'mc03nd', 'tb01wd', 'mc01nd']\n",
+ "['dg01nd', 'ab09ad', 'mb02id', 'tb01yd', 'sb03mx', 'mb03vw', 'sg02cv', 'ab05rd']\n",
+ "['mb04ds', 'mb01od', 'mb4dpz', 'mb03oy', 'sb03qd', 'sb01bx', 'sb08dd', 'ib01od']\n",
+ "['sb10md', 'mb01ld', 'mb04iz', 'mb05od', 'tb01td', 'mb02vd', 'mb03fz', 'mb05my']\n",
+ "['mb01oh', 'mb04zd', 'sb03oz', 'tg01kz', 'mb02cx', 'tg01jd', 'mb01zd', 'mb01pd']\n",
+ "['sb01dd', 'mb03hd', 'sb02qd', 'mb03qw', 'tb01xd', 'ud01nd', 'sb10rd', 'ib01my']\n",
+ "['tf01od', 'ud01dd', 'tb01vy', 'ab09hy', 'sb04rx', 'ib01qd', 'mb04od', 'mb03qv']\n",
+ "['sg03bz', 'sb03or', 'mb03kd', 'ab13cd', 'tg01kd', 'mb03wa', 'mb04ts', 'mb03ka']\n",
+ "['mb4dlz', 'mb04qu', 'sb10fd', 'ma02pd', 'sb10jd', 'mb01qd', 'ab09jv', 'sb10vd']\n",
+ "['fb01td', 'ma02ez', 'tc05ad', 'sb10wd', 'md03ad', 'nf01bd', 'ma02cz', 'mb04ny']\n",
+ "['sb04rv', 'nf01br', 'tb01pd', 'ab01md', 'ib01bd', 'mb01yd', 'tg01nx', 'sb01fy']\n",
+ "['mb04md', 'sb10sd', 'mb04ud', 'mb01sd', 'ag08bd', 'ab09bx', 'bb03ad']\n",
+ "None\n"
+ ]
+ }
+ ],
+ "source": [
+ "slycot_routines = get_slycot_routines(slycot)\n",
+ "\n",
+ "print(f\"There are currently {len(slycot_routines)} routines that are found in slycot.\")\n",
+ "print(\"------\")\n",
+ "print(print_list_chunks(slycot_routines))\n",
+ "print(\"\\n\")\n",
+ "\n",
+ "with open('slicot_routines.txt') as f:\n",
+ " lines = f.readlines()\n",
+ "\n",
+ "slicot_routines = [x.split(\"\\n\")[0] for x in lines]\n",
+ "\n",
+ "print(f\"There are currently {len(slicot_routines)} routines that are found in slicot.\")\n",
+ "print(\"------\")\n",
+ "print(print_list_chunks(slicot_routines))"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Generate Sets for the Venn-Diagramm"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "There are currently 1 routines that are found in slycot and not in slicot.\n",
+ "------\n",
+ "['sb03md57']\n",
+ "None\n",
+ "\n",
+ "\n",
+ "There are currently 559 routines that are found in slicot and not in slycot.\n",
+ "------\n",
+ "['tb01ux', 'mb03xs', 'fb01qd', 'ma01bz', 'ib01bd', 'ab8nxz', 'mb03xd', 'sb08md']\n",
+ "['ab08md', 'dg01ny', 'nf01be', 'sb10jd', 'mb02qd', 'fb01vd', 'sb04rd', 'tg01qd']\n",
+ "['mb02hd', 'mb03ai', 'nf01bd', 'mb01ru', 'mb04ru', 'mb04bz', 'tb01px', 'sb10rd']\n",
+ "['mb04dy', 'sb10td', 'mb04ad', 'ma02gz', 'sb03ov', 'sb02pd', 'ma02cz', 'mb03bz']\n",
+ "['sb03mv', 'mb03qw', 'mb02td', 'mb01ss', 'sb08cd', 'sb03td', 'mb04tt', 'nf01bb']\n",
+ "['mb03ld', 'tb01xz', 'sb04nx', 'tg01oz', 'mb01od', 'tb03ay', 'mb02ud', 'sb10qd']\n",
+ "['mb03bf', 'mb01ux', 'sb08ny', 'mb04tu', 'mb01pd', 'mb02ed', 'mb03bd', 'mb02cy']\n",
+ "['sg03bx', 'mb04dl', 'mb04az', 'mb03ny', 'mb03td', 'bb03ad', 'ab09kd', 'mb02sz']\n",
+ "['fb01sd', 'mc01nd', 'tg01ld', 'mb05od', 'sb03mu', 'sb16bd', 'sb08fd', 'md03ad']\n",
+ "['sb04ny', 'tb01kd', 'mb03ag', 'bb04ad', 'mc01md', 'mb01wd', 'sb03ou', 'sb03qx']\n",
+ "['ab09hx', 'mc01py', 'nf01bs', 'mb02gd', 'mb03hz', 'mc03md', 'sb04my', 'tg01bd']\n",
+ "['sb10pd', 'tg01ob', 'mc01od', 'mb02wd', 'mb03ya', 'dg01nd', 'sb04od', 'ab09cd']\n",
+ "['sb09md', 'mc01sw', 'mb02uu', 'mb02kd', 'ab09bx', 'mb01uz', 'nf01br', 'ib03ad']\n",
+ "['ma01cd', 'mb04zd', 'bb02ad', 'sb16ay', 'mb03pd', 'ab09hy', 'ab05rd', 'mb03bg']\n",
+ "['sb01dd', 'mb04iy', 'mb02od', 'ma02ad', 'nf01bu', 'sb03sd', 'mc01wd', 'sg03bz']\n",
+ "['mb3oyz', 'mb02cv', 'sb04nw', 'tb04cd', 'sb04mr', 'mb04oy', 'sb06nd', 'mb02cu']\n",
+ "['mb02rz', 'sg03bt', 'mb02vd', 'mb03id', 'dg01od', 'tg01nx', 'mb04pa', 'mb03rz']\n",
+ "['mb01oe', 'tf01my', 'ab05qd', 'mb03wx', 'mb03lz', 'ab09cx', 'mb03kd', 'mb01zd']\n",
+ "['ab09jx', 'mb02xd', 'mb05my', 'mb01vd', 'mb01ot', 'tb01ld', 'mb01rt', 'mb03sd']\n",
+ "['tf01qd', 'ab08mz', 'sb10zd', 'mb03oy', 'mb03xu', 'ab05od', 'ma02ez', 'mb04qs']\n",
+ "['sb03qy', 'tg01id', 'ud01dd', 'tg01kz', 'tg01fd', 'mb04dp', 'sb10yd', 'ab13ax']\n",
+ "['tg01md', 'ab09jd', 'mb03cd', 'sb02mw', 'mb02md', 'sb02mv', 'mb04md', 'ma02dd']\n",
+ "['ma02hz', 'mb04di', 'mb04qc', 'sb03qd', 'ab07md', 'ag8byz', 'mc01qd', 'mb02rd']\n",
+ "['tg01jd', 'mb03ab', 'sb02ov', 'mb03ka', 'ag07bd', 'bd02ad', 'nf01ba', 'tb01ud']\n",
+ "['md03ba', 'mc01xd', 'ab09iy', 'mb02jd', 'mb01ld', 'sb03my', 'mb02uw', 'tb04bx']\n",
+ "['ud01cd', 'mb04nd', 'nf01bw', 'df01md', 'nf01bq', 'ud01nd', 'mb01yd', 'sb03sx']\n",
+ "['tb04ay', 'sb10ld', 'tg01hu', 'tg01od', 'mb04tb', 'tg01az', 'mb03bb', 'sb04rw']\n",
+ "['tg01kd', 'tf01pd', 'sb03os', 'mb04pb', 'tg01pd', 'mb04vx', 'sb02ox', 'ud01bd']\n",
+ "['tb01uy', 'nf01bf', 'mb01xd', 'mb01nd', 'sb03or', 'mb04ow', 'mb03qv', 'mb04su']\n",
+ "['mb04fp', 'ib01rd', 'mb03ah', 'mb04yw', 'mb01uy', 'sb02mx', 'md03bx', 'mb01rw']\n",
+ "['mb04kd', 'mb04od', 'mb04qf', 'ab09dd', 'mb04db', 'ma02pz', 'sb03ot', 'ib01oy']\n",
+ "['mc03nx', 'sb10ed', 'sb04nd', 'sb02mr', 'ma02id', 'mb03xp', 'sg03bs', 'mb03lp']\n",
+ "['mb02cd', 'sg03bw', 'tg01nd', 'mb03hd', 'sg03ay', 'ab09ix', 'mb01ud', 'mb04ty']\n",
+ "['tg01wd', 'mb03fz', 'mb01rd', 'mb03zd', 'mb03dd', 'mb01xy', 'bd01ad', 'mb03ry']\n",
+ "['mb03xz', 'sg02cx', 'sb10sd', 'sb02ou', 'mb04qu', 'mc01sy', 'mb02jx', 'mb4dpz']\n",
+ "['sb08gd', 'tg01oa', 'ab01md', 'mb03vw', 'mb05oy', 'mb01oc', 'ab05sd', 'bb01ad']\n",
+ "['mb04tw', 'de01pd', 'sb02cx', 'mb02yd', 'mb02cx', 'mb01rb', 'ab08ny', 'ib03bd']\n",
+ "['ib01qd', 'mb01os', 'sb04qy', 'mb04bd', 'sb10id', 'ib01md', 'tg01fz', 'ab13id']\n",
+ "['tg01dd', 'mc01vd', 'sb04px', 'mb04hd', 'mb04wr', 'sg03ax', 'ma02oz', 'mb04qb']\n",
+ "['mb03rx', 'mb04ds', 'sb03oz', 'mb02id', 'ma02bd', 'ab09gd', 'ib01px', 'tg01hy']\n",
+ "['ma02iz', 'mb04jd', 'sb03oy', 'ab09jv', 'mb03qx', 'ab13cd', 'mb03kc', 'sb08ed']\n",
+ "['ib01nd', 'ma02ed', 'tf01mx', 'mb01kd', 'ab08nx', 'ib01cd', 'tg01hx', 'mb4dbz']\n",
+ "['mb03gd', 'ab09fd', 'sb04qr', 'mb4dlz', 'mb03jz', 'tb01wx', 'mb04bp', 'mb03bc']\n",
+ "['mb03ba', 'ma02es', 'ma02az', 'sb08hd', 'mb03py', 'mc01pd', 'mb03qy', 'mb04ud']\n",
+ "['mb03kb', 'ma02nz', 'dk01md', 'sb10ud', 'sb04mw', 'sb03pd', 'sb10kd', 'sg03by']\n",
+ "['tg01ad', 'mb04xy', 'ab08nw', 'mc01rd', 'ag08bd', 'ib01ad', 'mb03rw', 'mb04wd']\n",
+ "['md03bb', 'ab09jw', 'tb01vy', 'sb10wd', 'sg03br', 'mb03md', 'sb04rx', 'sb16cy']\n",
+ "['de01od', 'sb03ud', 'ud01mz', 'ma01bd', 'ma02bz', 'mb02pd', 'sb01by', 'mb01td']\n",
+ "['mb02qy', 'mb04tx', 'tb01kx', 'mb03dz', 'mb01sd', 'sb08my', 'mb04iz', 'tf01nd']\n",
+ "['sb04rv', 'mb01rx', 'tb04bv', 'mb02dd', 'mb3pyz', 'mb03be', 'tb01zd', 'tb01td']\n",
+ "['ag08by', 'mb02sd', 'tb01vd', 'fb01td', 'tg01ed', 'sb02rd', 'mb03od', 'md03by']\n",
+ "['nf01ay', 'tf01od', 'sb02ru', 'sb03rd', 'sb01fy', 'tb01iz', 'ma01ad', 'mb3jzp']\n",
+ "['ab01od', 'nf01bx', 'ab09hd', 'sb04ow', 'sg02cv', 'ab04md', 'mb03wa', 'ma02gd']\n",
+ "['ab13ad', 'fd01ad', 'tb01ty', 'ab09id', 'sb02nd', 'ib01pd', 'tg01jy', 'ud01md']\n",
+ "['mb03gz', 'sb01bx', 'sb03sy', 'mb01md', 'sb02ow', 'mb04py', 'sb10vd', 'mb02nd']\n",
+ "['mb01oo', 'sg02nd', 'ma02mz', 'ib01od', 'mb03jd', 'dg01md', 'ab05pd', 'mb03nd']\n",
+ "['mb03my', 'mb04xd', 'mb03ts', 'sb02ms', 'mb01ry', 'tb01md', 'md03bd', 'tg01ly']\n",
+ "['ab09kx', 'td03ad', 'tb04bw', 'mb03lf', 'mb04dd', 'sb04qu', 'mb03ed', 'mb04cd']\n",
+ "['mc03nd', 'sb01md', 'tb01nd', 'mb01uw', 'mb03cz', 'mb03fd', 'ma02hd', 'mc01sx']\n",
+ "['tb01yd', 'mb01qd', 'ma02jz', 'tg01hd', 'sb03mx', 'sb04pd', 'td03ay', 'md03bf']\n",
+ "['ue01md', 'sb02mu', 'ib01py', 'mc01sd', 'mb04ox', 'td05ad', 'mb03yd', 'sb02sd']\n",
+ "['fb01rd', 'mb04wu', 'sb16cd', 'mb01rh', 'sb16ad', 'mb3lzp', 'mb03ad', 'mb04dz']\n",
+ "['sg03bu', 'tc05ad', 'mb04pu', 'sb08nd', 'ma02pd', 'mb04ld', 'sb10md', 'mb02uv']\n",
+ "['ab13dx', 'sb03mw', 'mb03iz', 'nf01bv', 'tb04bd', 'ma02cd', 'sb04ry', 'mb04ts']\n",
+ "['mb03ud', 'mb03za', 'sb04mu', 'ib01my', 'mb04wp', 'ma02md', 'mb04tv', 'sg03bv']\n",
+ "['mb04vd', 'sb04py', 'mb04ny', 'tb01wd', 'nf01by', 'sb02oy', 'mb03ae', 'nf01ad']\n",
+ "['nf01bp', 'sg02cw', 'mb04gd', 'mb03ke', 'mc03ny', 'mb03af', 'tg01cd', 'ag08bz']\n",
+ "['mb02tz', 'mb04ed', 'tg01gd', 'mb04rb', 'mb02ny', 'mb03qd', 'ma02jd', 'mb02fd']\n",
+ "['mb01oh', 'sb10zp', 'ab09ed', 'sb04nv', 'mb03jp', 'ma02fd', 'mb03qg', 'mb03yt']\n",
+ "['ma02od', 'sb08dd', 'mb04yd', 'tb01xd', 'sb02qd', 'mb04fd', 'mb04id']\n",
+ "None\n",
+ "\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "not_in_slicot = list(set(slycot_routines)- set(slicot_routines))\n",
+ "not_in_slicot\n",
+ "\n",
+ "print(f\"There are currently {len(not_in_slicot)} routines that are found in slycot and not in slicot.\")\n",
+ "print(\"------\")\n",
+ "print(print_list_chunks(not_in_slicot))\n",
+ "print(\"\\n\")\n",
+ "\n",
+ "not_in_slycot = list(set(slicot_routines) - set(slycot_routines))\n",
+ "not_in_slycot\n",
+ "\n",
+ "print(f\"There are currently {len(not_in_slycot)} routines that are found in slicot and not in slycot.\")\n",
+ "print(\"------\")\n",
+ "print(print_list_chunks(not_in_slycot))\n",
+ "print(\"\\n\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "There are currently 608 routines that are found in slicot or in slycot. (union)\n",
+ "------\n",
+ "['tb01ux', 'mb03xs', 'fb01qd', 'ma01bz', 'ib01bd', 'ab8nxz', 'mb03xd', 'sb08md']\n",
+ "['ab08md', 'dg01ny', 'nf01be', 'sb10jd', 'mb02qd', 'fb01vd', 'sb04rd', 'tg01qd']\n",
+ "['mb02hd', 'mb03ai', 'nf01bd', 'mb01ru', 'mb04ru', 'mb04bz', 'tb01px', 'sb10rd']\n",
+ "['mb04dy', 'sb10td', 'mb04ad', 'ma02gz', 'sb03ov', 'sb02pd', 'ma02cz', 'mb03bz']\n",
+ "['sb03mv', 'mb03qw', 'mb02td', 'mb01ss', 'sb08cd', 'sb03td', 'mb04tt', 'nf01bb']\n",
+ "['mb03ld', 'mb03wd', 'tb01xz', 'sb04nx', 'tg01oz', 'mb01od', 'tb03ay', 'mb02ud']\n",
+ "['sb10qd', 'ab08nz', 'mb03bf', 'tb01pd', 'mb01ux', 'sb08ny', 'mb04tu', 'mb01pd']\n",
+ "['mb02ed', 'mb03bd', 'mb02cy', 'sg03bx', 'mb04dl', 'mb04az', 'mb03ny', 'mb03td']\n",
+ "['bb03ad', 'ab09kd', 'mb02sz', 'fb01sd', 'ab09md', 'mc01nd', 'tg01ld', 'mb05od']\n",
+ "['sb03mu', 'sb16bd', 'sb08fd', 'md03ad', 'mc01td', 'sb04ny', 'tb01kd', 'mb03ag']\n",
+ "['bb04ad', 'mc01md', 'mb01wd', 'sb03ou', 'sb03qx', 'ab09hx', 'mc01py', 'nf01bs']\n",
+ "['mb02gd', 'mb03hz', 'mc03md', 'sb04my', 'tg01bd', 'sb10pd', 'tg01ob', 'mc01od']\n",
+ "['mb02wd', 'mb03ya', 'dg01nd', 'sb04od', 'ab09cd', 'sb09md', 'mc01sw', 'sb10fd']\n",
+ "['mb03vd', 'mb02uu', 'mb02kd', 'ab09bx', 'mb01uz', 'nf01br', 'ib03ad', 'ma01cd']\n",
+ "['mb04zd', 'bb02ad', 'sb16ay', 'mb03pd', 'ab09hy', 'ab05rd', 'sb02mt', 'mb03bg']\n",
+ "['sb01dd', 'mb04iy', 'mb02od', 'ma02ad', 'nf01bu', 'sb03sd', 'mc01wd', 'sg03bz']\n",
+ "['mb3oyz', 'mb02cv', 'sg02ad', 'sb04nw', 'tb04cd', 'sb04mr', 'sb03md', 'mb04oy']\n",
+ "['sb06nd', 'mb02cu', 'mb02rz', 'sg03bt', 'mb02vd', 'mb03id', 'dg01od', 'tg01nx']\n",
+ "['sb04qd', 'mb04pa', 'mb03rz', 'mb01oe', 'tf01my', 'ab05qd', 'mb03wx', 'mb03lz']\n",
+ "['ab09cx', 'mb03kd', 'sg03ad', 'mb01zd', 'ab09jx', 'mb02xd', 'mb05my', 'mb01vd']\n",
+ "['mb01ot', 'tb01ld', 'mb01rt', 'mb03sd', 'tf01qd', 'ab08mz', 'sb10zd', 'mb03oy']\n",
+ "['mb03xu', 'ab05od', 'ma02ez', 'mb04qs', 'sb03qy', 'tg01id', 'ud01dd', 'tg01kz']\n",
+ "['tg01fd', 'mb04dp', 'sb10yd', 'ab13ax', 'tg01md', 'ab09bd', 'ab09jd', 'mb03cd']\n",
+ "['sb02mw', 'mb02md', 'sb02mv', 'mb04md', 'ma02dd', 'ma02hz', 'tc04ad', 'mb04di']\n",
+ "['tb05ad', 'mb04qc', 'sb03qd', 'ab07md', 'ag8byz', 'mc01qd', 'mb02rd', 'ab13fd']\n",
+ "['tg01jd', 'mb03ab', 'sb02ov', 'mb03ka', 'ag07bd', 'bd02ad', 'nf01ba', 'sb04md']\n",
+ "['tb01ud', 'md03ba', 'mc01xd', 'ab09iy', 'mb02jd', 'mb01ld', 'sb03my', 'mb02uw']\n",
+ "['tb04bx', 'ud01cd', 'mb04nd', 'nf01bw', 'df01md', 'sb10ad', 'nf01bq', 'tf01md']\n",
+ "['ud01nd', 'mb01yd', 'sb03sx', 'tb04ay', 'sb10ld', 'tg01hu', 'tg01od', 'mb04tb']\n",
+ "['tg01az', 'mb03bb', 'sb04rw', 'tg01kd', 'tf01pd', 'sb03os', 'mb04pb', 'tg01pd']\n",
+ "['mb04vx', 'sb02ox', 'ud01bd', 'tb01uy', 'nf01bf', 'mb01xd', 'mb01nd', 'sb03or']\n",
+ "['mb04ow', 'mb03qv', 'mb04su', 'mb04fp', 'ab13ed', 'ib01rd', 'mb03ah', 'mb04yw']\n",
+ "['mb01uy', 'sb02mx', 'md03bx', 'tf01rd', 'td04ad', 'mb01rw', 'ab09ad', 'mb04kd']\n",
+ "['mb04od', 'mb04qf', 'ab09dd', 'mb04db', 'ma02pz', 'sb03ot', 'ib01oy', 'mc03nx']\n",
+ "['sb10ed', 'sb04nd', 'sb02mr', 'ma02id', 'mb03xp', 'sg03bs', 'mb03lp', 'mb02cd']\n",
+ "['sb02md', 'sg03bw', 'tg01nd', 'mb03hd', 'sg03ay', 'ab09ix', 'mb01ud', 'mb04ty']\n",
+ "['ab05nd', 'mb03vy', 'tg01wd', 'mb03fz', 'mb01rd', 'mb03zd', 'mb03dd', 'mb01xy']\n",
+ "['bd01ad', 'mb03ry', 'mb03xz', 'sg02cx', 'sb10sd', 'sb02ou', 'mb04qu', 'mc01sy']\n",
+ "['mb02jx', 'mb4dpz', 'sb08gd', 'tg01oa', 'ab01md', 'mb03vw', 'mb05oy', 'mb01oc']\n",
+ "['ab05sd', 'bb01ad', 'mb04tw', 'de01pd', 'sb02cx', 'mb02yd', 'mb02cx', 'mb01rb']\n",
+ "['ab08ny', 'ib03bd', 'ib01qd', 'mb01os', 'sb04qy', 'mb04bd', 'sb10id', 'ib01md']\n",
+ "['tg01fz', 'ab13id', 'tg01dd', 'mc01vd', 'sb04px', 'mb04hd', 'mb04wr', 'sg03ax']\n",
+ "['ma02oz', 'mb04qb', 'mb03rx', 'tb01id', 'ab09ax', 'mb04ds', 'sb03oz', 'mb02id']\n",
+ "['ma02bd', 'ab09gd', 'ib01px', 'tg01hy', 'ma02iz', 'mb04jd', 'sb03oy', 'ab09jv']\n",
+ "['tb04ad', 'sb03md57', 'mb03qx', 'ab13cd', 'mb03kc', 'sb08ed', 'ab13md', 'ib01nd']\n",
+ "['ma02ed', 'tf01mx', 'mb01kd', 'ab08nx', 'ib01cd', 'tg01hx', 'mb4dbz', 'sg03bd']\n",
+ "['mb03gd', 'sb03od', 'ab09fd', 'sb04qr', 'mb4dlz', 'mb03jz', 'tb01wx', 'mb04bp']\n",
+ "['mb03bc', 'mb03ba', 'ma02es', 'ma02az', 'sb08hd', 'mb03py', 'mc01pd', 'mb03qy']\n",
+ "['mb04ud', 'mb03kb', 'ma02nz', 'dk01md', 'sb01bd', 'sb10ud', 'sb04mw', 'sb03pd']\n",
+ "['sb10kd', 'sg03by', 'tg01ad', 'mb04xy', 'ab08nw', 'mc01rd', 'ag08bd', 'ib01ad']\n",
+ "['mb03rw', 'mb04wd', 'md03bb', 'ab09jw', 'tb01vy', 'sb10wd', 'sg03br', 'mb03md']\n",
+ "['sb04rx', 'sb16cy', 'de01od', 'sb03ud', 'ud01mz', 'sb10dd', 'ma01bd', 'ma02bz']\n",
+ "['mb02pd', 'sb01by', 'ab08nd', 'mb01td', 'mb02qy', 'mb04tx', 'tb01kx', 'mb03dz']\n",
+ "['mb01sd', 'sb08my', 'mb04iz', 'tf01nd', 'sb04rv', 'mb01rx', 'tb04bv', 'ab07nd']\n",
+ "['mb02dd', 'mb3pyz', 'mb03be', 'mb05nd', 'tb01zd', 'tb01td', 'ag08by', 'mb02sd']\n",
+ "['tb01vd', 'fb01td', 'tg01ed', 'sb02rd', 'mb03od', 'md03by', 'ab13dd', 'nf01ay']\n",
+ "['tf01od', 'sb02ru', 'sb03rd', 'tb03ad', 'sb01fy', 'tb01iz', 'ma01ad', 'mb3jzp']\n",
+ "['ab01od', 'nf01bx', 'ab09hd', 'sb04ow', 'sg02cv', 'ab04md', 'mb03wa', 'ma02gd']\n",
+ "['ab01nd', 'ab13ad', 'fd01ad', 'tb01ty', 'ab09id', 'sb02nd', 'ib01pd', 'tg01jy']\n",
+ "['ud01md', 'mb03gz', 'sb01bx', 'sb03sy', 'mb01md', 'sb02ow', 'mb04py', 'sb10vd']\n",
+ "['mb02nd', 'mb01oo', 'sg02nd', 'ma02mz', 'tc01od', 'sb02od', 'ib01od', 'mb03jd']\n",
+ "['dg01md', 'ab05pd', 'mb03nd', 'mb03my', 'mb04xd', 'mb03ts', 'sb02ms', 'mb01ry']\n",
+ "['tb01md', 'md03bd', 'tg01ly', 'ab09kx', 'td03ad', 'tb04bw', 'mb03lf', 'mb04dd']\n",
+ "['sb04qu', 'mb03ed', 'mb04cd', 'mc03nd', 'sb01md', 'tb01nd', 'mb01uw', 'mb03cz']\n",
+ "['mb03fd', 'ma02hd', 'mc01sx', 'tb01yd', 'mb01qd', 'ma02jz', 'tg01hd', 'sb03mx']\n",
+ "['sb04pd', 'td03ay', 'md03bf', 'ue01md', 'sb02mu', 'ib01py', 'mc01sd', 'sb10hd']\n",
+ "['mb04ox', 'td05ad', 'mb03yd', 'sb02sd', 'fb01rd', 'mb04wu', 'sb16cd', 'mb01rh']\n",
+ "['sb16ad', 'ab05md', 'mb3lzp', 'mb03ad', 'mb04dz', 'sg03bu', 'tc05ad', 'mb04pu']\n",
+ "['sb08nd', 'ma02pd', 'mb04ld', 'sb10md', 'mb02uv', 'ab13dx', 'sb03mw', 'mb03iz']\n",
+ "['nf01bv', 'tb04bd', 'ma02cd', 'sb04ry', 'mb04ts', 'mb03ud', 'mb03za', 'sb04mu']\n",
+ "['ib01my', 'ab09nd', 'mb04wp', 'ma02md', 'mb04tv', 'sg03bv', 'mb04vd', 'sb04py']\n",
+ "['mb04ny', 'tb01wd', 'nf01by', 'sb02oy', 'mb03ae', 'mb05md', 'nf01ad', 'nf01bp']\n",
+ "['sg02cw', 'mb04gd', 'mb03ke', 'mc03ny', 'mb03af', 'tg01cd', 'ag08bz', 'mb02tz']\n",
+ "['mb04ed', 'tg01gd', 'mb04rb', 'mb02ny', 'mb03qd', 'ma02jd', 'mb02fd', 'mb01oh']\n",
+ "['sb10zp', 'ab09ed', 'sb04nv', 'mb03jp', 'ma02fd', 'mb03qg', 'mb03yt', 'ma02od']\n",
+ "['sb08dd', 'mb04yd', 'tb01xd', 'sb02qd', 'ab13bd', 'mb04fd', 'mb04id', 'mb03rd']\n",
+ "None\n",
+ "\n",
+ "\n",
+ "There are currently 48 routines that are found in slicot and slycot. (intersection)\n",
+ "------\n",
+ "['mb05md', 'ab13fd', 'sg03ad', 'sb02mt', 'sb01bd', 'ab05md', 'ab09md', 'tb04ad']\n",
+ "['mc01td', 'mb03wd', 'sb04md', 'ab01nd', 'ab13md', 'ab07nd', 'sb02md', 'mb05nd']\n",
+ "['ab13ed', 'ab08nz', 'sg03bd', 'sg02ad', 'sb03od', 'tb01pd', 'sb03md', 'ab05nd']\n",
+ "['mb03vy', 'tf01rd', 'ab09bd', 'td04ad', 'ab09ad', 'sb10ad', 'ab09nd', 'tf01md']\n",
+ "['sb10fd', 'ab13dd', 'tc01od', 'mb03vd', 'sb10dd', 'sb04qd', 'tc04ad', 'tb01id']\n",
+ "['sb02od', 'tb03ad', 'ab09ax', 'tb05ad', 'ab13bd', 'ab08nd', 'sb10hd', 'mb03rd']\n",
+ "None\n"
+ ]
+ }
+ ],
+ "source": [
+ "union = list(set(slicot_routines) | set(slycot_routines))\n",
+ "\n",
+ "print(f\"There are currently {len(union)} routines that are found in slicot or in slycot. (union)\")\n",
+ "print(\"------\")\n",
+ "print(print_list_chunks(union))\n",
+ "print(\"\\n\")\n",
+ "\n",
+ "intersection = list(set(slicot_routines) & set(slycot_routines))\n",
+ "intersection\n",
+ "\n",
+ "print(f\"There are currently {len(intersection)} routines that are found in slicot and slycot. (intersection)\")\n",
+ "print(\"------\")\n",
+ "print(print_list_chunks(intersection))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " chapter name | \n",
+ " slycot routines | \n",
+ " slicot routines | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " a | \n",
+ " Analysis Routines | \n",
+ " 16 | \n",
+ " 60 | \n",
+ "
\n",
+ " \n",
+ " b | \n",
+ " Benchmark | \n",
+ " 0 | \n",
+ " 6 | \n",
+ "
\n",
+ " \n",
+ " c | \n",
+ " Adaptive Control | \n",
+ " 0 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " d | \n",
+ " Data Analysis | \n",
+ " 0 | \n",
+ " 8 | \n",
+ "
\n",
+ " \n",
+ " f | \n",
+ " Filtering | \n",
+ " 0 | \n",
+ " 6 | \n",
+ "
\n",
+ " \n",
+ " i | \n",
+ " Identification | \n",
+ " 0 | \n",
+ " 15 | \n",
+ "
\n",
+ " \n",
+ " m | \n",
+ " Mathematical routines | \n",
+ " 7 | \n",
+ " 281 | \n",
+ "
\n",
+ " \n",
+ " n | \n",
+ " Nonlinear Systems | \n",
+ " 0 | \n",
+ " 16 | \n",
+ "
\n",
+ " \n",
+ " s | \n",
+ " Synthesis Routines | \n",
+ " 16 | \n",
+ " 131 | \n",
+ "
\n",
+ " \n",
+ " t | \n",
+ " Transformation Routines | \n",
+ " 10 | \n",
+ " 77 | \n",
+ "
\n",
+ " \n",
+ " u | \n",
+ " Utility Routines | \n",
+ " 0 | \n",
+ " 7 | \n",
+ "
\n",
+ " \n",
+ " total | \n",
+ " - | \n",
+ " 49 | \n",
+ " 607 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " chapter name slycot routines slicot routines\n",
+ "a Analysis Routines 16 60\n",
+ "b Benchmark 0 6\n",
+ "c Adaptive Control 0 0\n",
+ "d Data Analysis 0 8\n",
+ "f Filtering 0 6\n",
+ "i Identification 0 15\n",
+ "m Mathematical routines 7 281\n",
+ "n Nonlinear Systems 0 16\n",
+ "s Synthesis Routines 16 131\n",
+ "t Transformation Routines 10 77\n",
+ "u Utility Routines 0 7\n",
+ "total - 49 607"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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HU6dOxS+//IK0tDTY2tpi0qRJGDx4MADg8OHDGD9+PM6dOwczMzMEBgZi1qxZ0NHRQVBQEA4fPozDhw9j8eLFAIDk5GQ4ODi82YEoAZciEBEREVUiCoUCCoUC27dvR05OzgvrDxkyBL/88ota3Z9//hk1a9ZE+/btAQABAQFYt24dlixZgoSEBKxcuRIKhQIA8L///Q+dO3dG8+bNce7cOSxfvhyrV6/GrFmzAACLFy9Gy5YtMXToUKhUKqhUKtja2r6BK38xJrZERERElYiOjg4iIyMRFRUFpVIJT09PfPnllzh//nyJ9Xv06AEA2LFjh3QsMjISQUFBkMlkuHLlCjZu3Igff/wR3bt3h5OTEzp06IC+ffsCAL777jvY2tpi2bJlqFevHrp164bp06cjPDwchYWFMDU1hZ6eHgwNDWFlZQUrKytoa2u/+YEoARNbIiIiokqmZ8+euHXrFnbu3AlfX1/ExMTAzc0NkZGRxerq6+tj4MCB+PHHHwEAf/75Jy5evIigoCAAQHx8PLS1taVlDc9KSEhAy5Yt1V437OnpiaysLNy8ebPcr+11MLElIiIiqoT09fXRsWNHTJkyBcePH0dQUBCmTZtWYt0hQ4bgwIEDuHnzJiIiItC+fXvY29sDePI6W03BxJaIiIhIA9SvXx+PHj0qsaxRo0Zwd3fHqlWr8MsvvyA4OFitrLCwEIcPHy7xXFdXV8TFxUEIIR2LjY2FsbExatWqBQDQ09NDQUFBOV7Nq2FiS0RERFSJ3L9/H+3bt8fPP/+M8+fPIzk5GZs2bcL8+fPh7+9f6nlDhgzB3LlzIYRA9+7dpeMODg4IDAxEcHAwtm/fjuTkZMTExGDjxo0AgBEjRuDGjRv49NNPcfnyZezYsQPTpk3DuHHjoKWlJbVx4sQJpKSk4N69eygsLHyzg1AKPu6LiIiI6Bnv8iMbFQoFPDw8sHDhQiQlJSEvLw+2trYYOnQovvzyy1LP69evH8aMGYN+/fpBX19frWz58uX48ssvMWLECNy/fx92dnZSWzVr1sTu3bsxfvx4NGnSBGZmZhg8eDC++uor6fyQkBAEBgaifv36+PfffyvscV8y8fS8MpULBwcHjBkzplzewBEUFIT09HRs3779tdt620JDQ7F9+3bEx8dXdCiSzMxMmJqaImOiMUzkshefQG9eaEZFR0BEVdTjx4+RnJwMR0fHYomeJkpJSUHt2rVx6tQpuLm5VXQ4xTzv+yH9/s7IgImJSaltVLmlCHFxcdDW1kaXLu/uX2JPW7x4cYl3OJZFSkoKZDKZtJmZmaFt27Y4evRo+QaJJ++kfjb5DgkJQXR0dLn3RURERGWXl5eH27dv46uvvsL777//Tia15aXKJbarV6/Gp59+iiNHjuDWrVsVHc4LmZqaQqlUvlYbBw8ehEqlwpEjR2BjYwM/Pz/cuXOnfAJ8DoVCAXNz8zfeDxEREZUuNjYW1tbWOHXqFFasWFHR4bxRVSqxzcrKwoYNGzB8+HB06dKl2ExoTEwMZDIZoqOj4e7uDkNDQ7Rq1QqJiYlSnaSkJPj7+6NGjRpQKBRo3rw5Dh48WGqfwcHB8PPzUzuWl5cHS0tLrF69GgCwefNmNGrUCAYGBjA3N4e3t7d0V2NQUBC6desmnfu8uqUxNzeHlZUVGjZsiC+//BKZmZk4ceKEVH748GG0aNECcrkc1tbWmDhxIvLz86VyBwcHLFq0SK3Npk2bIjQ0VCoHgO7du0Mmk0n7oaGhaNq0qXRO0bUsWLAA1tbWMDc3x8iRI5GXlyfVycnJQUhICGrWrAkjIyN4eHggJiZGKr9+/Tq6du2KatWqwcjICA0aNMDu3btLvfacnBxkZmaqbURERFWJl5cXhBBITExEo0aNKjqcN6pKJbYbN25EvXr14OLigo8//hg//vgjSlpiPHnyZISHh+P06dPQ0dFReyRGVlYWOnfujOjoaJw9exa+vr7o2rUrUlNTS+xzyJAh2Lt3L1QqlXRs165dyM7ORt++faFSqdCvXz8EBwcjISEBMTEx6NGjR4lxvUzdkvz777/46aefADx5LAfw4tfklcWpU6cAABEREVCpVNJ+SQ4dOoSkpCQcOnQIUVFRiIyMVPsDY9SoUYiLi8P69etx/vx59O7dG76+vrh69SoAYOTIkcjJycGRI0dw4cIFzJs3T3rlX0nCwsJgamoqbRX1ij8iIiJ686rUUxFWr16Njz/+GADg6+uLjIwMHD58GF5eXmr1Zs+eLb19Y+LEiejSpQseP34MfX19NGnSBE2aNJHqzpw5E9u2bcPOnTsxatSoYn22atUKLi4uWLNmDSZMmADgSQLYu3dvKBQKXLlyBfn5+ejRo4f0oOTS/ppSqVRlrvtsDFpaWsjOzoYQAu+99x46dOgAQP01eTKZDPXq1cOtW7fwxRdfYOrUqdJjPJ7HwsICAKBUKmFlZfXcutWqVcOyZcugra2NevXqoUuXLoiOjsbQoUORmpqKiIgIpKamwsbGBsCTdbp79+5FREQE5syZg9TUVPTs2VO6bicnp+f2N2nSJIwbN07az8zMZHJLRESkoarMjG1iYiJOnjyJfv36AXjynuW+fftKywGe1rhxY+lra2trAEBaWhqAJzO2ISEhcHV1hVKphEKhQEJCQqkztsCTWduIiAgAwJ07d7Bnzx5pFrhJkybo0KEDGjVqhN69e2PVqlV48OBBie28TN2nbdiwAWfPnsWWLVtQp04dREZGQldXF8Dbf01egwYN1N4fbW1tLY3thQsXUFBQAGdnZygUCmk7fPgwkpKSAACjR4/GrFmz4OnpiWnTppX6XuwicrkcJiYmahsRERFppiqT2K5evRr5+fmwsbGBjo4OdHR0sHz5cmzZsgUZGeqPGypK+gBICV/Rg4ZDQkKwbds2zJkzB0ePHkV8fDwaNWqE3NzcUvsOCAjA33//jbi4OPz8889wdHRE69atAQDa2to4cOAA9uzZg/r162Pp0qVwcXFBcnJysXZepu7TbG1tUbduXXTv3h1z5sxB9+7dkZOTU7aBA6ClpVVsucPT62JfxtNjCzwZ36KxzcrKgra2Ns6cOYP4+HhpS0hIwOLFiwE8+SPh77//xsCBA3HhwgW4u7tj6dKlrxQLERERaZYqsRQhPz8fP/30E8LDw/Gf//xHraxbt25Yt24dhg0bVqa2YmNjERQUJL2xIysrCykpKc89x9zcHN26dUNERATi4uIwaNAgtXKZTAZPT094enpi6tSpsLe3x7Zt29Q+Qn+VuiXp1asXpk6diu+++w5jx46Fq6srtmzZAiGElMQ/+5o8CwsLtTXCmZmZxZJpXV3d136VXrNmzVBQUIC0tDQp8S+Jra0thg0bhmHDhmHSpElYtWoVPv3005frbNJNgLO3REREGqVKzNju2rULDx48wODBg9GwYUO1rWfPniUuRyhN3bp1sXXrVsTHx+PcuXPo379/mV4bN2TIEERFRSEhIQGBgYHS8RMnTmDOnDk4ffo0UlNTsXXrVty9exeurq7F2niZuqWRyWQYPXo05s6di+zs7DK9Jq99+/ZYs2YNjh49igsXLiAwMFBtOQHw5MkI0dHRuH37dpmWR5TE2dkZAwYMQEBAALZu3Yrk5GScPHkSYWFh+O233wAAY8aMwb59+5CcnIw///wThw4deqnrJyIiIs1VJWZsV69eDW9vb5iamhYr69mzJ+bPn//CtZpFvvnmGwQHB6NVq1aoXr06vvjiizI9Qsrb2xvW1tZo0KCBdGMUAJiYmODIkSNYtGgRMjMzYW9vj/DwcHTq1KlYGy9T93kCAwMxefJkLFu2DBMmTHjha/ImTZqE5ORk+Pn5wdTUFDNnziw2YxseHo5x48Zh1apVqFmz5gtnsUsTERGBWbNm4fPPP8f//vc/VK9eHe+//770yLSCggKMHDkSN2/ehImJCXx9fbFw4cJX6ouIiKhUocVzhjfXF9/AWF74St23JCsrCzVr1kRERAR69OhR0eFUWWV9JR8REWm+575S9x1PbO/evYupU6fit99+w507d1CtWjU0adIEU6dOhaenJxwcHDBmzBiMGTOm2LkpKSlwdHTE2bNn1Z43v2XLFixduhRnz55FQUEBnJyc0KtXL4waNQpmZmYAnjw6dO7cuVi3bh2uX78OY2NjtGvXDqGhoWjQoAGAJ5/iXr9+vdTYAwMDS3yrKl+pWwkUFhYiLS0NM2fOhFKpxIcffljRIREREVEl17NnT5w9exZRUVG4cuUKdu7cCS8vL9y/f/+V2ps8eTL69u2L5s2bY8+ePbh48SLCw8Nx7tw5rFmzBsCTlx55e3vjxx9/xKxZs3DlyhXs3r0b+fn58PDwwB9//AHgyfPtVSoVVCoVtmzZAuDJ06mKjhXdEP4mVImlCBUpNTUVjo6OqFWrFiIjI6GjwyEnIiKiV5eeno6jR48iJiZGeu6+vb09WrRo8UrtnTx5EnPmzMGiRYvw2WefSccdHBzQsWNHpKenAwAWLVqEuLg4nD17Vnqmv729PbZs2QIPDw8MHjwYFy9elJ5vD0Ca6bW0tIRSqXyl+F4GZ2zfMAcHBwghcOPGDemlCERERESvqug579u3b3+px3eWZu3atVAoFBgxYkSJ5UUJ6S+//IKOHTuqvagKePJY0LFjx+LSpUs4d+7ca8fzOpjYEhEREVUiOjo6iIyMRFRUFJRKJTw9PfHll1+W+Ub4Z129ehVOTk7FnjX/rCtXrpT6JKKi41euXHmlGMoLE1siIiKiSqZnz564desWdu7cCV9fX8TExMDNza3Em7Je5GWeI/CuP3OAiS0RERFRJaSvr4+OHTtiypQpOH78OIKCgjBt2rSXbsfZ2Rl///33C98q6uzsjISEhBLLio47Ozu/dP/liYktERERkQaoX78+Hj169NLn9e/fH1lZWfjuu+9KLC+6eeyjjz7CwYMHi62jLSwsxMKFC1G/fv1i62/fNt6iT0RERFSJ3L9/H71790ZwcDAaN24MY2NjnD59GvPnz4e/v79U73//+x/i4+PVzrW3ty/WnoeHByZMmCC9HKl79+6wsbHBtWvXsGLFCnzwwQf47LPPMHbsWOzYsQNdu3ZFeHg4PDw8cOfOHcyZMwcJCQk4ePAgZDLZm77852JiS0RERPSsd/htYAqFAh4eHli4cCGSkpKQl5cHW1tbDB06FF9++aVUb8GCBViwYIHauWvWrMEHH3xQrM158+bhvffew7fffosVK1agsLAQtWvXRq9evRAYGAjgydKH33//HXPmzMGXX36p9oKGP/74Aw0bNnyzF14GfPMYVSl88xgRERV57pvH6K3jm8eIiIiIiP4/JrZEREREpBGY2BIRERGRRmBiS0REREQagYktERERVWm8j/7dUB7fBya2REREVCXp6uoCALKzsys4EgL+7/tQ9H15FXyOLREREVVJ2traUCqVSEtLAwAYGhpW+AsGqiIhBLKzs5GWlgalUgltbe1XbouJLREREVVZVlZWACAlt1RxlEql9P14VUxsiYiIqMqSyWSwtraGpaUl8vLyKjqcKktXV/e1ZmqLMLElIiKiKk9bW7tcEiuqWExsqUQxMTFo164dHjx4AKVSWdHhAACCgoKQnp6O7du3v35jYbUA+QvWUb3D7wknIiKi4vhUhHdQUFAQZDKZtJmbm8PX1xfnz5+v6NCIiIiI3llMbN9Rvr6+UKlUUKlUiI6Oho6ODvz8/Co6rApRUFCAwsLCig6DiIiI3nFMbN9RcrkcVlZWsLKyQtOmTTFx4kTcuHEDd+/eBQDcuHEDffr0gVKphJmZGfz9/ZGSkiKdHxQUhG7dumHBggWwtraGubk5Ro4cqbYwPicnB1988QVsbW0hl8tRp04drF69Wi2OM2fOwN3dHYaGhmjVqhUSExOlstDQUDRt2hQ//vgj7OzsoFAoMGLECBQUFGD+/PmwsrKCpaUlZs+erdbmN998g0aNGsHIyAi2trYYMWIEsrKypPLIyEgolUrs3LkT9evXh1wuR2pqarExOnXqFCwsLDBv3rxSxzEnJweZmZlqGxEREWkmJraVQFZWFn7++WfUqVMH5ubmyMvLg4+PD4yNjXH06FHExsZCoVDA19cXubm50nmHDh1CUlISDh06hKioKERGRiIyMlIqDwgIwLp167BkyRIkJCRg5cqVUCgUan1PnjwZ4eHhOH36NHR0dBAcHKxWnpSUhD179mDv3r1Yt24dVq9ejS5duuDmzZs4fPgw5s2bh6+++gonTpyQztHS0sKSJUvw119/ISoqCr///jsmTJig1m52djbmzZuHH374AX/99RcsLS3Vyn///Xd07NgRs2fPxhdffFHq2IWFhcHU1FTabG1tyzzuREREVMkIeucEBgYKbW1tYWRkJIyMjAQAYW1tLc6cOSOEEGLNmjXCxcVFFBYWSufk5OQIAwMDsW/fPqkNe3t7kZ+fL9Xp3bu36Nu3rxBCiMTERAFAHDhwoMQYDh06JACIgwcPSsd+++03AUD8+++/Qgghpk2bJgwNDUVmZqZUx8fHRzg4OIiCggLpmIuLiwgLCyv1ejdt2iTMzc2l/YiICAFAxMfHFxsXf39/sXXrVqFQKMT69etLbbPI48ePRUZGhrTduHFDABAZE42FmGby/I2IiIjeCRkZGU9+f2dkPLcen4rwjmrXrh2WL18OAHjw4AG+++47dOrUCSdPnsS5c+dw7do1GBsbq53z+PFjJCUlSfsNGjRQe3SJtbU1Lly4AACIj4+HtrY22rZt+9w4GjdurHY+8OQh1nZ2dgAABwcHtThq1KgBbW1taGlpqR17+sHXBw8eRFhYGC5fvozMzEzk5+fj8ePHyM7OhqGhIQBAT09Pre8iJ06cwK5du7B582Z069btubEDT5Z0yOXyF9YjIiKiyo+J7TvKyMgIderUkfZ/+OEHmJqaYtWqVcjKysJ7772HtWvXFjvPwsJC+vrZdy3LZDLpJiwDA4MyxfF0G0WvGXz6Rq6S+nhevykpKfDz88Pw4cMxe/ZsmJmZ4dixYxg8eDByc3OlxNbAwKDE1xrWrl0b5ubm+PHHH9GlS5fXep80ERERaRYmtpWETCaDlpYW/v33X7i5uWHDhg2wtLSEiYnJK7XXqFEjFBYW4vDhw/D29i7naEt35swZFBYWIjw8XJrV3bhxY5nPr169OrZu3QovLy/06dMHGzdufLXkdtJN4BXHjoiIiN5NvHnsHZWTk4Pbt2/j9u3bSEhIwKeffoqsrCx07doVAwYMQPXq1eHv74+jR48iOTkZMTExGD16NG7evFmm9h0cHBAYGIjg4GBs375dauNlksxXUadOHeTl5WHp0qX4+++/sWbNGqxYseKl2rC0tMTvv/+Oy5cvo1+/fsjPz39D0RIREVFlwsT2HbV3715YW1vD2toaHh4eOHXqFDZt2gQvLy8YGhriyJEjsLOzQ48ePeDq6orBgwfj8ePHLzWDu3z5cvTq1QsjRoxAvXr1MHToUDx69OgNXhXQpEkTfPPNN5g3bx4aNmyItWvXIiws7KXbsbKywu+//44LFy5gwIABKCgoeAPREhERUWUiE0KIig6C6G3JzMyEqakpMjIyXnkZBxEREb1dZf39zRlbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhPbVxAaGoqmTZu+lb6CgoLQrVu3t9JXZZOSkgKZTIb4+PiKDoWIiIjeAUxsAcTFxUFbWxtdunSpsBhKS9IWL16MyMjIN95/ZmYmJk+ejHr16kFfXx9WVlbw9vbG1q1bIYQot36YqBMREdGbolPRAbwLVq9ejU8//RSrV6/GrVu3YGNjU9EhSUxNTd94H+np6fjggw+QkZGBWbNmoXnz5tDR0cHhw4cxYcIEtG/fHkql8o3H8bS8vDzo6uq+1T6JiIiocqvyM7ZZWVnYsGEDhg8fji5dupQ4Ozp37lzUqFEDxsbGGDx4MB4/fqxWfurUKXTs2BHVq1eHqakp2rZtiz///FOtjkwmw/Lly9GpUycYGBjAyckJmzdvlsodHR0BAM2aNYNMJoOXlxcA9RnO77//HjY2NigsLFRr29/fH8HBwdL+jh074ObmBn19fTg5OWH69OnIz88vdQy+/PJLpKSk4MSJEwgMDET9+vXh7OyMoUOHIj4+HgqFAgDw4MEDBAQEoFq1ajA0NESnTp1w9epVqZ3IyEgolUrs27cPrq6uUCgU8PX1hUqlAvBkCUdUVBR27NgBmUwGmUyGmJgYabZ6w4YNaNu2LfT19bF27VoUFhZixowZqFWrFuRyOZo2bYq9e/eWeh0lycnJQWZmptpGREREGkpUcatXrxbu7u5CCCF+/fVXUbt2bVFYWCiVb9iwQcjlcvHDDz+Iy5cvi8mTJwtjY2PRpEkTqU50dLRYs2aNSEhIEJcuXRKDBw8WNWrUEJmZmVIdAMLc3FysWrVKJCYmiq+++kpoa2uLS5cuCSGEOHnypAAgDh48KFQqlbh//74QQojAwEDh7+8vhBDin3/+EXp6euLgwYNSu/fv31c7duTIEWFiYiIiIyNFUlKS2L9/v3BwcBChoaElXn9BQYGoVq2a+OSTT144Vh9++KFwdXUVR44cEfHx8cLHx0fUqVNH5ObmCiGEiIiIELq6usLb21ucOnVKnDlzRri6uor+/fsLIYR4+PCh6NOnj/D19RUqlUqoVCqRk5MjkpOTBQDh4OAgtmzZIv7++29x69Yt8c033wgTExOxbt06cfnyZTFhwgShq6srrly5IoQQ0nlnz54tNeZp06YJAMW2jIyMF14vERERvRsyMjLK9Pu7yie2rVq1EosWLRJCCJGXlyeqV68uDh06JJW3bNlSjBgxQu0cDw8PtcT2WQUFBcLY2Fj8+uuv0jEAYtiwYcXaGT58uBCi9CTt6cRWCCH8/f1FcHCwtL9y5UphY2MjCgoKhBBCdOjQQcyZM0etjTVr1ghra+sSY71z544AIL755ptSr0cIIa5cuSIAiNjYWOnYvXv3hIGBgdi4caMQ4kliC0Bcu3ZNqvPtt9+KGjVqlHo9T1970fehiI2NjZg9e7basebNm0vfj7Ikto8fPxYZGRnSduPGDSa2RERElUxZE9sqvRQhMTERJ0+eRL9+/QAAOjo66Nu3L1avXi3VSUhIgIeHh9p5LVu2VNu/c+cOhg4dirp168LU1BQmJibIyspCamrqc89r2bIlEhISXirmAQMGYMuWLcjJyQEArF27Fh999BG0tJ58K8+dO4cZM2ZAoVBI29ChQ6FSqZCdnV2sPVHGG8MSEhKgo6OjNhbm5uZwcXFRuwZDQ0PUrl1b2re2tkZaWlqZ+nB3d5e+zszMxK1bt+Dp6alWx9PT86XGTC6Xw8TERG0jIiIizVSlbx5bvXo18vPz1W4WE0JALpdj2bJlZb5xKzAwEPfv38fixYthb28PuVyOli1bIjc3t9xj7tq1K4QQ+O2339C8eXMcPXoUCxculMqzsrIwffp09OjRo9i5+vr6xY5ZWFhAqVTi8uXL5RLfszd8yWSyMifPRkZG5RIDERERVU1VdsY2Pz8fP/30E8LDwxEfHy9t586dg42NDdatWwcAcHV1xYkTJ9TO/eOPP9T2Y2NjMXr0aHTu3BkNGjSAXC7HvXv3ivX57Hl//PEHXF1dAQB6enoAgIKCgufGra+vjx49emDt2rVYt24dXFxc4ObmJpW7ubkhMTERderUKbYVzeo+TUtLCx999BHWrl2LW7duFSvPyspCfn4+XF1dkZ+frzYW9+/fR2JiIurXr//cmJ+mp6f3wmsEABMTE9jY2CA2NlbteGxs7Ev1R0RERFVHlZ2x3bVrFx48eIDBgwcXm5nt2bMnVq9ejWHDhuGzzz5DUFAQ3N3d4enpibVr1+Kvv/6Ck5OTVL9u3bpYs2YN3N3dkZmZifHjx8PAwKBYn5s2bYK7uzs++OADrF27FidPnpSWPVhaWsLAwAB79+5FrVq1oK+vX+qM8YABA+Dn54e//voLH3/8sVrZ1KlT4efnBzs7O/Tq1QtaWlo4d+4cLl68iFmzZpXY3uzZsxETEwMPDw/Mnj0b7u7u0NXVxdGjRxEWFoZTp06hbt268Pf3x9ChQ7Fy5UoYGxtj4sSJqFmzJvz9/cs87g4ODti3bx8SExNhbm7+3Fnx8ePHY9q0aahduzaaNm2KiIgIxMfHY+3atWXuj4iIiKqQt7De953k5+cnOnfuXGLZiRMnBABx7tw5IYQQs2fPFtWrVxcKhUIEBgaKCRMmqN089ueffwp3d3ehr68v6tatKzZt2iTs7e3FwoULpToAxLfffis6duwo5HK5cHBwEBs2bFDrd9WqVcLW1lZoaWmJtm3bCiFKvtmqoKBAWFtbCwAiKSmpWPx79+4VrVq1EgYGBsLExES0aNFCfP/9988dj/T0dDFx4kRRt25doaenJ2rUqCG8vb3Ftm3bpKdE/PPPP2LgwIHC1NRUGBgYCB8fH+kJBUI8uXnM1NRUrd1t27aJp/+ZpaWliY4dOwqFQiEAiEOHDpV6E1hBQYEIDQ0VNWvWFLq6uqJJkyZiz549UnlZbh57VlkXnxMREdG7o6y/v2VClONrpahUMpkM27Zt41u3KlhmZiZMTU2RkZHBG8mIiIgqibL+/q6ya2yJiIiISLMwsSUiIiIijVBlbx5727jig4iIiOjN4owtEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEnYoOgDSTTCbDtm3b0K1bt9duy8vLC02bNsWiRYteuy1JWC1ALit7/dCM8uubiIiI3gjO2L4BQUFBkMlkkMlk0NXVRY0aNdCxY0f8+OOPKCwsfKm2IiMjoVQqyzW+devWQVtbGyNHjizXdt+UrVu3YubMmRUdBhEREb3jmNi+Ib6+vlCpVEhJScGePXvQrl07fPbZZ/Dz80N+fn6FxrZ69WpMmDAB69atw+PHjys0lrIwMzODsbFxRYdBRERE7zgmtm+IXC6HlZUVatasCTc3N3z55ZfYsWMH9uzZg8jISKneN998g0aNGsHIyAi2trYYMWIEsrKyAAAxMTEYNGgQMjIypBng0NBQAMCaNWvg7u4OY2NjWFlZoX///khLS3thXMnJyTh+/DgmTpwIZ2dnbN26Va28aIZ43759cHV1hUKhkJL0IqdOnULHjh1RvXp1mJqaom3btvjzzz9L7bN9+/YYNWqU2rG7d+9CT08P0dHRAIDvvvsOdevWhb6+PmrUqIFevXpJdb28vDBmzBhp/3l1n5WTk4PMzEy1jYiIiDQTE9u3qH379mjSpIlaMqmlpYUlS5bgr7/+QlRUFH7//XdMmDABANCqVSssWrQIJiYmUKlUUKlUCAkJAQDk5eVh5syZOHfuHLZv346UlBQEBQW9MIaIiAh06dIFpqam+Pjjj7F69epidbKzs7FgwQKsWbMGR44cQWpqqtQvADx8+BCBgYE4duwY/vjjD9StWxedO3fGw4cPS+xzyJAh+OWXX5CTkyMd+/nnn1GzZk20b98ep0+fxujRozFjxgwkJiZi7969aNOmTYltvUxdAAgLC4Opqam02dravnCMiIiIqHLizWNvWb169XD+/Hlp/+mZSAcHB8yaNQvDhg3Dd999Bz09PZiamkImk8HKykqtneDgYOlrJycnLFmyBM2bN0dWVhYUCkWJfRcWFiIyMhJLly4FAHz00Uf4/PPPkZycDEdHR6leXl4eVqxYgdq1awMARo0ahRkzZkjl7du3V2v3+++/h1KpxOHDh+Hn51es3x49emDUqFHYsWMH+vTpA+DJzHDRWuTU1FQYGRnBz88PxsbGsLe3R7NmzUq8hpepCwCTJk3CuHHjpP3MzEwmt0RERBqKM7ZvmRACMtn/3Y1/8OBBdOjQATVr1oSxsTEGDhyI+/fvIzs7+7ntnDlzBl27doWdnR2MjY3Rtm1bAE8Sv9IcOHAAjx49QufOnQEA1atXl25qe5qhoaGU1AKAtbW12jKHO3fuYOjQoahbty5MTU1hYmKCrKysUvvW19fHwIEDpX7+/PNPXLx4UZph7tixI+zt7eHk5ISBAwdi7dq1pV7/y9QFniwJMTExUduIiIhIMzGxfcsSEhKk2dGUlBT4+fmhcePG2LJlC86cOYNvv/0WAJCbm1tqG48ePYKPjw9MTEywdu1anDp1Ctu2bXvheatXr8Y///wDAwMD6OjoQEdHB7t370ZUVJTa0xp0dXXVzpPJZBBCSPuBgYGIj4/H4sWLcfz4ccTHx8Pc3Py5fQ8ZMgQHDhzAzZs3ERERgfbt28Pe3h4AYGxsjD///BPr1q2DtbU1pk6diiZNmiA9Pb1YOy9Tl4iIiKoWLkV4i37//XdcuHABY8eOBfBk1rWwsBDh4eHQ0nryN8bGjRvVztHT00NBQYHascuXL+P+/fuYO3eu9LH66dOnn9v3/fv3sWPHDqxfvx4NGjSQjhcUFOCDDz7A/v374evrW6briI2NxXfffSfN/N64cQP37t177jmNGjWCu7s7Vq1ahV9++QXLli1TK9fR0YG3tze8vb0xbdo0KJVK/P777+jRo0extl6mbqkm3QQ4e0tERKRRmNi+ITk5Obh9+zYKCgpw584d7N27F2FhYfDz80NAQAAAoE6dOsjLy8PSpUvRtWtXxMbGYsWKFWrtODg4ICsrC9HR0WjSpAkMDQ1hZ2cHPT09LF26FMOGDcPFixdf+JzXNWvWwNzcHH369FFbCgEAnTt3xurVq8uc2NatW1d6KkNmZibGjx8PAwODF543ZMgQjBo1CkZGRujevbt0fNeuXfj777/Rpk0bVKtWDbt370ZhYSFcXFyKtfEydYmIiKhq4VKEN2Tv3r2wtraGg4MDfH19cejQISxZsgQ7duyAtrY2AKBJkyb45ptvMG/ePDRs2BBr165FWFiYWjutWrXCsGHD0LdvX1hYWGD+/PmwsLBAZGQkNm3ahPr162Pu3LlYsGDBc+P58ccf0b1792JJLQD07NkTO3fufOGsa5HVq1fjwYMHcHNzw8CBAzF69GhYWlq+8Lx+/fpBR0cH/fr1g76+vnRcqVRi69ataN++PVxdXbFixQqsW7dObWb5VeoSERFR1SITTy+eJHqDUlJSULt2bZw6dQpubm4VEkNmZiZMTU2RkZHBG8mIiIgqibL+/uZSBHrj8vLycP/+fXz11Vd4//33KyypJSIiIs3GpQj0xsXGxsLa2hqnTp0qtoaYiIiIqLxwxpbeOC8vL3DFCxEREb1pnLElIiIiIo3AxJaIiIiINAITWyIiIiLSCExsiYiIiEgjMLElIiIiIo3AxJaIiIiINAITWyIiIiLSCExsiYiIiEgjMLElIiIiIo3AxJaIiIiINAITWyIiIiLSCExsiYiIiEgjMLElIiIiIo3AxJaIiIiINAITWyIiIiLSCExsiYiIiEgjMLElIiIiIo2gU9EB0LvBy8sLTZs2xaJFiwAADg4OGDNmDMaMGVPufcXExKBdu3Z48OABlEplubdfJmG1ALns+XVCM95OLERERFQuOGNbxQQFBUEmkxXb5s+fj5kzZ5Z6nkwmw/bt28slhlatWkGlUsHU1LRc2iMiIiICOGNbJfn6+iIiIkLtmIWFBbS1td9433l5edDT04OVldUb74uIiIiqFs7YVkFyuRxWVlZqW4cOHUpdduDg4AAA6N69O2QymbQPADt27ICbmxv09fXh5OSE6dOnIz8/XyqXyWRYvnw5PvzwQxgZGWH27NmIiYmBTCZDeno6ACAyMhJKpRL79u2Dq6srFAoFfH19oVKppHby8/MxevRoKJVKmJub44svvkBgYCC6dev23GvNyclBZmam2kZERESaiYktvdCpU6cAABEREVCpVNL+0aNHERAQgM8++wyXLl3CypUrERkZidmzZ6udHxoaiu7du+PChQsIDg4usY/s7GwsWLAAa9aswZEjR5CamoqQkBCpfN68eVi7di0iIiIQGxuLzMzMMi2NCAsLg6mpqbTZ2tq+4igQERHRu46JbRW0a9cuKBQKaevdu/dz61tYWAAAlEolrKyspP3p06dj4sSJCAwMhJOTEzp27IiZM2di5cqVauf3798fgwYNgpOTE+zs7ErsIy8vDytWrIC7uzvc3NwwatQoREdHS+VLly7FpEmT0L17d9SrVw/Lli0r041nkyZNQkZGhrTduHHjhecQERFR5cQ1tlVQu3btsHz5cmnfyMgI/fr1e+l2zp07h9jYWLUZ2oKCAjx+/BjZ2dkwNDQEALi7u7+wLUNDQ9SuXVvat7a2RlpaGgAgIyMDd+7cQYsWLaRybW1tvPfeeygsLHxuu3K5HHK5/KWui4iIiConJrZVkJGREerUqfPa7WRlZWH69Ono0aNHsTJ9fX21/l5EV1dXbV8mk0EI8doxEhERUdXBxJbKRFdXFwUFBWrH3NzckJiYWC5J8vOYmpqiRo0aOHXqFNq0aQPgyczwn3/+iaZNm75ao5NuAiYm5RckERERVTgmtlQmDg4OiI6OhqenJ+RyOapVq4apU6fCz88PdnZ26NWrF7S0tHDu3DlcvHgRs2bNKtf+P/30U4SFhaFOnTqoV68eli5digcPHkAme8FLFoiIiKjK4M1jVCbh4eE4cOAAbG1t0axZMwCAj48Pdu3ahf3796N58+Z4//33sXDhQtjb25d7/1988QX69euHgIAAtGzZEgqFAj4+PmpLHoiIiKhqkwkuZKRKqLCwEK6urujTp89z35j2rMzMTJiamiIjIwMmXIpARERUKZT19zeXIlClcP36dezfvx9t27ZFTk4Oli1bhuTkZPTv37+iQyMiIqJ3BJciUKWgpaWFyMhING/eHJ6enrhw4QIOHjwIV1fXig6NiIiI3hGcsaVKwdbWFrGxsRUdBhEREb3DOGNLRERERBqBiS0RERERaQQmtkRERESkEZjYEhEREZFGYGJLRERERBqBiS0RERERaQQmtkRERESkEZjYEhEREZFGYGJLRERERBqBiS0RERERaQQmtkRERESkEZjYEhEREZFGYGJLRERERBqBiS0RERERaQQmtkRERESkEZjYEhEREZFGYGJLRERERBpBp6IDIMDLywtNmzbFokWL3mg/KSkpcHR0xNmzZ9G0aVMAQGxsLIYNG4bLly+jS5cuGDNmDNq1a4cHDx5AqVS+sViCgoKQnp6O7du3v7E+niusFiCXvbn2QzPeXNtERERUIia2b0FFJHEl9WlrawuVSoXq1atLx8aNG4emTZtiz549UCgUMDQ0hEqlgqmpabnEUVIyDQCLFy+GEKJc+iAiIiICmNhWKdra2rCyslI7lpSUhGHDhqFWrVrSsWfrvAnllTgTERERFeEa27fs0aNHCAgIgEKhgLW1NcLDw4vVycnJQUhICGrWrAkjIyN4eHggJiZGKo+MjIRSqcS+ffvg6uoKhUIBX19fqFQqAEBoaCiioqKwY8cOyGQyyGQyxMTEICUlBTKZDPHx8dLX9+/fR3BwMGQyGSIjIxETEwOZTIb09HSpv9jYWHh5ecHQ0BDVqlWDj48PHjx4AADYu3cvPvjgAyiVSpibm8PPzw9JSUnSuY6OjgCAZs2aQSaTwcvLC8CTGeVu3bqpXfPo0aNhaWkJfX19fPDBBzh16pRUXhRXdHQ03N3dYWhoiFatWiExMfG5452Tk4PMzEy1jYiIiDQTE9u3bPz48Th8+DB27NiB/fv3IyYmBn/++adanVGjRiEuLg7r16/H+fPn0bt3b/j6+uLq1atSnezsbCxYsABr1qzBkSNHkJqaipCQEABASEgI+vTpIyW7KpUKrVq1UuujaFmCiYkJFi1aBJVKhb59+xaLNz4+Hh06dED9+vURFxeHY8eOoWvXrigoKADwJFEfN24cTp8+jejoaGhpaaF79+4oLCwEAJw8eRIAcPDgQahUKmzdurXEcZkwYQK2bNmCqKgo/Pnnn6hTpw58fHzwzz//qNWbPHkywsPDcfr0aejo6CA4OPi54x0WFgZTU1Nps7W1fW59IiIiqry4FOEtysrKwurVq/Hzzz+jQ4cOAICoqCi1ZQCpqamIiIhAamoqbGxsADxJVPfu3YuIiAjMmTMHAJCXl4cVK1agdu3aAJ4kwzNmzAAAKBQKGBgYICcnp9RlBUXLEmQyGUxNTUutN3/+fLi7u+O7776TjjVo0ED6umfPnmr1f/zxR1hYWODSpUto2LAhLCwsAADm5ual9vHo0SMsX74ckZGR6NSpEwBg1apVOHDgAFavXo3x48dLdWfPno22bdsCACZOnIguXbrg8ePH0NfXL7HtSZMmYdy4cdJ+ZmYmk1siIiINxcT2LUpKSkJubi48PDykY2ZmZnBxcZH2L1y4gIKCAjg7O6udm5OTA3Nzc2nf0NBQSmoBwNraGmlpaeUec3x8PHr37l1q+dWrVzF16lScOHEC9+7dk2ZqU1NT0bBhwzL1kZSUhLy8PHh6ekrHdHV10aJFCyQkJKjVbdy4sfS1tbU1ACAtLQ12dnYlti2XyyGXy8sUBxEREVVuTGzfMVlZWdDW1saZM2egra2tVqZQKKSvdXV11cpkMtkbecqAgYHBc8u7du0Ke3t7rFq1CjY2NigsLETDhg2Rm5tb7rEA6tctkz15XFdRMk1ERERVGxPbt6h27drQ1dXFiRMnpBnGBw8e4MqVK9LH682aNUNBQQHS0tLQunXrV+5LT09PWgf7Oho3bozo6GhMnz69WNn9+/eRmJiIVatWSbEeO3asWBwAnhtL7dq1oaenh9jYWNjb2wN4stTi1KlTGDNmzGtfQ4km3QRMTN5M20RERFQhmNi+RQqFAoMHD8b48eNhbm4OS0tLTJ48GVpa/3cPn7OzMwYMGICAgACEh4ejWbNmuHv3LqKjo9G4cWN06dKlTH05ODhg3759SExMhLm5+Ss/XmvSpElo1KgRRowYgWHDhkFPTw+HDh1C7969YWZmBnNzc3z//fewtrZGamoqJk6cqHa+paUlDAwMsHfvXtSqVQv6+vrFYjEyMsLw4cMxfvx4mJmZwc7ODvPnz0d2djYGDx78SnETERFR1cOnIrxlX3/9NVq3bo2uXbvC29sbH3zwAd577z21OhEREQgICMDnn38OFxcXdOvWDadOnSp1HWlJhg4dChcXF7i7u8PCwgKxsbGvFK+zszP279+Pc+fOoUWLFmjZsiV27NgBHR0daGlpYf369Thz5gwaNmyIsWPH4uuvv1Y7X0dHB0uWLMHKlSthY2MDf3//EvuZO3cuevbsiYEDB8LNzQ3Xrl3Dvn37UK1atVeKm4iIiKoemeDrn6gKyczMhKmpKTIyMmDCpQhERESVQll/f3PGloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijaBT0QEQVYSG0/ZBS274wnopc7u8hWiIiIioPHDGloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCNozHNsg4KCkJ6eju3bt1d0KGXm5eWFpk2bYtGiReXS3rs2BikpKXB0dMTZs2fRtGnTig5HzUX9wTCRy15cMfSNh0JERKQZQjMqOoI3P2MbFBQEmUyGYcOGFSsbOXIkZDIZgoKCytxeSkoKZDIZ4uPjyy/INywmJgYymQzp6elqx7du3YqZM2dWTFDlLCgoCN26dVM7ZmtrC5VKhYYNG1ZMUERERFSlvJWlCLa2tli/fj3+/fdf6djjx4/xyy+/wM7O7m2E8E4yMzODsbFxhfVfUFCAwsLCN9a+trY2rKysoKOjMR8MEBER0TvsrSS2bm5usLW1xdatW6VjW7duhZ2dHZo1a6ZWd+/evfjggw+gVCphbm4OPz8/JCUlSeWOjo4AgGbNmkEmk8HLy0vt/AULFsDa2hrm5uYYOXIk8vLypLKcnByEhISgZs2aMDIygoeHB2JiYqTyyMhIKJVK7Nq1Cy4uLjA0NESvXr2QnZ2NqKgoODg4oFq1ahg9ejQKCgqk89asWQN3d3cYGxvDysoK/fv3R1paGoAnM8zt2rUDAFSrVk1thtrLywtjxoxRi++LL76Ara0t5HI56tSpg9WrVwN4koQOHjwYjo6OMDAwgIuLCxYvXvxS34ei69u5cyfq168PuVyO1NRUPHjwAAEBAahWrRoMDQ3RqVMnXL16VTovNDS02FKCRYsWwcHBQSqPiorCjh07IJPJIJPJEBMTU2x2vWjmOjo6Gu7u7jA0NESrVq2QmJio1vaOHTvg5uYGfX19ODk5Yfr06cjPzwcACCEQGhoKOzs7yOVy2NjYYPTo0aVec05ODjIzM9U2IiIi0kxv7eax4OBgRERESPs//vgjBg0aVKzeo0ePMG7cOJw+fRrR0dHQ0tJC9+7dpZnFkydPAgAOHjwIlUqlliwfOnQISUlJOHToEKKiohAZGYnIyEipfNSoUYiLi8P69etx/vx59O7dG76+vmpJXHZ2NpYsWYL169dj7969iImJQffu3bF7927s3r0ba9aswcqVK7F582bpnLy8PMycORPnzp3D9u3bkZKSIiWvtra22LJlCwAgMTERKpWq1IQ0ICAA69atw5IlS5CQkICVK1dCoVAAAAoLC1GrVi1s2rQJly5dwtSpU/Hll19i48aNL/NtQHZ2NubNm4cffvgBf/31FywtLREUFITTp09j586diIuLgxACnTt3Vvuj4HlCQkLQp08f+Pr6QqVSQaVSoVWrVqXWnzx5MsLDw3H69Gno6OggODhYKjt69CgCAgLw2Wef4dKlS1i5ciUiIyMxe/ZsAMCWLVuwcOFCrFy5ElevXsX27dvRqFGjUvsKCwuDqamptNna2pZxpIiIiKiyeWufEX/88ceYNGkSrl+/DgCIjY3F+vXr1WZMAaBnz55q+z/++CMsLCxw6dIlNGzYEBYWFgAAc3NzWFlZqdWtVq0ali1bBm1tbdSrVw9dunRBdHQ0hg4ditTUVERERCA1NRU2NjYAniRke/fuRUREBObMmQPgSZK6fPly1K5dGwDQq1cvrFmzBnfu3IFCoUD9+vXRrl07HDp0CH379gUAtcTMyckJS5YsQfPmzZGVlQWFQgEzMzMAgKWlJZRKZYnjc+XKFWzcuBEHDhyAt7e31FYRXV1dTJ8+Xdp3dHREXFwcNm7ciD59+rxg9P9PXl4evvvuOzRp0gQAcPXqVezcuROxsbFSMrp27VrY2tpi+/bt6N279wvbVCgUMDAwQE5OTrHvSUlmz56Ntm3bAgAmTpyILl264PHjx9DX18f06dMxceJEBAYGSmMwc+ZMTJgwAdOmTUNqaiqsrKzg7e0NXV1d2NnZoUWLFqX2NWnSJIwbN07az8zMZHJLRESkod5aYmthYYEuXbogMjISQgh06dIF1atXL1bv6tWrmDp1Kk6cOIF79+5JM7WpqakvvAmpQYMG0NbWlvatra1x4cIFAMCFCxdQUFAAZ2dntXNycnJgbm4u7RsaGkpJLQDUqFEDDg4O0sxp0bGipQYAcObMGYSGhuLcuXN48OCBWsz169d/4dgAQHx8PLS1taWEryTffvstfvzxR6SmpuLff/9Fbm7uSz9tQE9PD40bN5b2ExISoKOjAw8PD+mYubk5XFxckJCQ8FJtl9XT/VtbWwMA0tLSYGdnh3PnziE2NlaaoQWeLMN4/PgxsrOz0bt3byxatAhOTk7w9fVF586d0bVr11LX8crlcsjl8jdyHURERPRueat39QQHB2PUqFEAniRpJenatSvs7e2xatUq2NjYoLCwEA0bNkRubu4L29fV1VXbl8lkUpKZlZUFbW1tnDlzRi35BaCWtJbUxvPaffToEXx8fODj44O1a9fCwsICqamp8PHxKVPMRQwMDJ5bvn79eoSEhCA8PBwtW7aEsbExvv76a5w4caLMfRT1I5OV4TFXT9HS0oIQQu1YWZcplOTp8SyK5env0/Tp09GjR49i5+nr68PW1haJiYk4ePAgDhw4gBEjRuDrr7/G4cOHi32fiIiIqGp5q4mtr68vcnNzIZPJ4OPjU6z8/v37SExMxKpVq9C6dWsAwLFjx9Tq6OnpAYDazVtl0axZMxQUFCAtLU1quzxcvnwZ9+/fx9y5c6WPuE+fPq1WpywxN2rUCIWFhTh8+LC0FOFpRUsFRowYIR17+qa6V+Xq6or8/HycOHFCWopQ9H0omm22sLDA7du3IYSQEtFnH7emp6f30t+Tkri5uSExMRF16tQptY6BgQG6du2Krl27YuTIkahXrx4uXLgANze3snc06SZgYvLa8RIREdG7460mttra2tLH28/OmgJP1siam5vj+++/h7W1NVJTUzFx4kS1OpaWljAwMMDevXtRq1Yt6Ovrw9TU9IV9Ozs7Y8CAAQgICEB4eDiaNWuGu3fvIjo6Go0bN0aXLl1e6Zrs7Oygp6eHpUuXYtiwYbh48WKxZ9Pa29tDJpNh165d6Ny5MwwMDNRmiQHAwcEBgYGBCA4OxpIlS9CkSRNcv34daWlp6NOnD+rWrYuffvoJ+/btg6OjI9asWYNTp05JT4l4VXXr1oW/vz+GDh2KlStXwtjYGBMnTkTNmjXh7+8P4MnTG+7evYv58+ejV69e2Lt3L/bs2QOTpxJDBwcH7Nu3D4mJiTA3Ny/T96QkU6dOhZ+fH+zs7NCrVy9oaWnh3LlzuHjxImbNmoXIyEgUFBTAw8MDhoaG+Pnnn2FgYAB7e/vXGgciIiKq/N76K3VNTEzUEqKnaWlpYf369Thz5gwaNmyIsWPH4uuvv1aro6OjgyVLlmDlypWwsbGRkq+yiIiIQEBAAD7//HO4uLigW7duOHXq1Gs9S9fCwgKRkZHYtGkT6tevj7lz52LBggVqdWrWrCndFFWjRg1pOcazli9fjl69emHEiBGoV68ehg4dikePHgEA/vvf/6JHjx7o27cvPDw8cP/+fbXZ29cRERGB9957D35+fmjZsiWEENi9e7f00b6rqyu+++47fPvtt2jSpAlOnjyJkJAQtTaGDh0KFxcXuLu7w8LCArGxsa8Ui4+PD3bt2oX9+/ejefPmeP/997Fw4UIpcVUqlVi1ahU8PT3RuHFjHDx4EL/++qvaOmkiIiKqmmTi2cWTRBosMzMTpqamyMjIKPUPLCIiInq3lPX391ufsSUiIiIiehOY2BIRERGRRmBiS0REREQagYktEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEnYoOoDJKSUmBo6Mjzp49i6ZNmyImJgbt2rXDgwcPoFQqKzo8KouwWoBc9mb7CM14s+0TERGRGo2ZsQ0KCoJMJsPcuXPVjm/fvh0y2ZtNYFq1agWVSgVTU9M32s/rWLVqFZo0aQKFQgGlUolmzZohLCysXNqOiYmBTCZDenp6ubRHRERE9Co0JrEFAH19fcybNw8PHjx4q/3q6enBysrqjSfQL5Kbm1vi8R9//BFjxozB6NGjER8fj9jYWEyYMAFZWVlvOUIiIiKiN0ejEltvb29YWVm9cCZyy5YtaNCgAeRyORwcHBAeHq5W7uDggDlz5iA4OBjGxsaws7PD999/X2p7z85YRkZGQqlUYt++fXB1dYVCoYCvry9UKpXaeT/88ANcXV2hr6+PevXq4bvvvlMr/+KLL+Ds7AxDQ0M4OTlhypQpyMvLk8pDQ0PRtGlT/PDDD3B0dIS+vn6J8e3cuRN9+vTB4MGDUadOHTRo0AD9+vXD7NmzAQBHjhyBrq4ubt++rXbemDFj0Lp1awDA9evX0bVrV1SrVg1GRkZo0KABdu/ejZSUFLRr1w4AUK1aNchkMgQFBQEACgsLERYWBkdHRxgYGKBJkybYvHlzsXHbt28fmjVrBgMDA7Rv3x5paWnYs2cPXF1dYWJigv79+yM7O1s6b/PmzWjUqBEMDAxgbm4Ob29vPHr0qMRrz8nJQWZmptpGREREmkmjElttbW3MmTMHS5cuxc2bN0usc+bMGfTp0wcfffQRLly4gNDQUEyZMgWRkZFq9cLDw+Hu7o6zZ89ixIgRGD58OBITE8scS3Z2NhYsWIA1a9bgyJEjSE1NRUhIiFS+du1aTJ06FbNnz0ZCQgLmzJmDKVOmICoqSqpjbGyMyMhIXLp0CYsXL8aqVauwcOFCtX6uXbuGLVu2YOvWrYiPjy8xFisrK/zxxx+4fv16ieVt2rSBk5MT1qxZIx3Ly8vD2rVrERwcDAAYOXIkcnJycOTIEVy4cAHz5s2DQqGAra0ttmzZAgBITEyESqXC4sWLAQBhYWH46aefsGLFCvz1118YO3YsPv74Yxw+fFit/9DQUCxbtgzHjx/HjRs30KdPHyxatAi//PILfvvtN+zfvx9Lly4FAKhUKvTr1w/BwcFISEhATEwMevToASFEidcWFhYGU1NTabO1tS2xHhEREWkAoSECAwOFv7+/EEKI999/XwQHBwshhNi2bZt4+jL79+8vOnbsqHbu+PHjRf369aV9e3t78fHHH0v7hYWFwtLSUixfvlwIIURycrIAIM6ePSuEEOLQoUMCgHjw4IEQQoiIiAgBQFy7dk1q49tvvxU1atSQ9mvXri1++eUXtThmzpwpWrZsWeo1fv311+K9996T9qdNmyZ0dXVFWlpaqecIIcStW7fE+++/LwAIZ2dnERgYKDZs2CAKCgqkOvPmzROurq7S/pYtW4RCoRBZWVlCCCEaNWokQkNDS2z/2esXQojHjx8LQ0NDcfz4cbW6gwcPFv369VM77+DBg1J5WFiYACCSkpKkY//973+Fj4+PEEKIM2fOCAAiJSXludf8dBwZGRnSduPGDQFAZEw0FmKayZvdiIiIqFxkZGQ8+f2dkfHceho1Y1tk3rx5iIqKQkJCQrGyhIQEeHp6qh3z9PTE1atXUVBQIB1r3Lix9LVMJoOVlRXS0tLKHIOhoSFq164t7VtbW0vnP3r0CElJSRg8eDAUCoW0zZo1C0lJSdI5GzZsgKenJ6ysrKBQKPDVV18hNTVVrR97e3tYWFg8NxZra2vExcXhwoUL+Oyzz5Cfn4/AwED4+vqisLAQwJOb765du4Y//vgDwJPlFH369IGRkREAYPTo0Zg1axY8PT0xbdo0nD9//rl9Xrt2DdnZ2ejYsaPaNf70009q1wioj3WNGjWkpRdPHysauyZNmqBDhw5o1KgRevfujVWrVj13TbVcLoeJiYnaRkRERJpJIxPbNm3awMfHB5MmTXrlNnR1ddX2ZTKZlAS+6vni/39cXnTT1qpVqxAfHy9tFy9elBLLuLg4DBgwAJ07d8auXbtw9uxZTJ48udgNYkWJZ1k0bNgQI0aMwM8//4wDBw7gwIED0rIAS0tLdO3aFREREbhz5w727NkjLUMAgCFDhuDvv//GwIEDceHCBbi7u0vLA0pSdI2//fab2jVeunRJbZ3ts2Mlk8meO/ba2to4cOAA9uzZg/r162Pp0qVwcXFBcnJymceBiIiINJPGPsd27ty5aNq0KVxcXNSOu7q6IjY2Vu1YbGwsnJ2doa2t/VZiq1GjBmxsbPD3339jwIABJdY5fvw47O3tMXnyZOlYaWtkX0X9+vUBQO2mqyFDhqBfv36oVasWateuXWxm29bWFsOGDcOwYcMwadIkrFq1Cp9++in09PQAQG3Gu379+pDL5UhNTUXbtm3LLW7gSaLr6ekJT09PTJ06Ffb29ti2bRvGjRtX9kYm3QQ4e0tERKRRNDaxbdSoEQYMGIAlS5aoHf/888/RvHlzzJw5E3379kVcXByWLVtW7IkEb9r06dMxevRomJqawtfXFzk5OTh9+jQePHiAcePGoW7dukhNTcX69evRvHlz/Pbbb9i2bdsr9TV8+HDY2Nigffv2qFWrFlQqFWbNmgULCwu0bNlSqufj4wMTExPMmjULM2bMUGtjzJgx6NSpE5ydnfHgwQMcOnQIrq6uAJ4sh5DJZNi1axc6d+4MAwMDGBsbIyQkBGPHjkVhYSE++OADZGRkIDY2FiYmJggMDHylazlx4gSio6Pxn//8B5aWljhx4gTu3r0rxUJERERVl0YuRSgyY8aMYssH3NzcsHHjRqxfvx4NGzbE1KlTMWPGDOkRVW/LkCFD8MMPPyAiIgKNGjVC27ZtERkZCUdHRwDAhx9+iLFjx2LUqFFo2rQpjh8/jilTprxSX97e3vjjjz/Qu3dvODs7o2fPntDX10d0dDTMzc2lelpaWggKCkJBQQECAgLU2igoKMDIkSPh6uoKX19fODs7S38M1KxZE9OnT8fEiRNRo0YNjBo1CgAwc+ZMTJkyBWFhYdJ5v/32m3SNr8LExARHjhxB586d4ezsjK+++grh4eHo1KnTK7dJREREmkEmRCnPSaIqafDgwbh79y527txZ0aG8EZmZmTA1NUVGRgZvJCMiIqokyvr7W2OXItDLycjIwIULF/DLL79obFJLREREmo2JLQEA/P39cfLkSQwbNgwdO3as6HCIiIiIXhoTWwLw5PW2RERERJWZRt88RkRERERVBxNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0At88RlVSw2n7oCU3fKN9pMzt8kbbJyIiInWcsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIIfI7tawoNDcX27dsRHx//RtpPSUmBo6Mjzp49i6ZNm76RPt4kmUyGbdu2oVu3bhUdipqL+oNhIpe92U5C32zzRJVCaEZFR0BEVYhGzNjevXsXw4cPh52dHeRyOaysrODj44PY2Nhy7Ucmk2H79u3l2uaL2NraQqVSoWHDhq90flBQEGQyGWQyGXR1deHo6IgJEybg8ePH5RpnaGhoiYm3SqVCp06dyrUvIiIiopJoxIxtz549kZubi6ioKDg5OeHOnTuIjo7G/fv3Kzq016atrQ0rK6vXasPX1xcRERHIy8vDmTNnEBgYCJlMhnnz5pVTlKV73diJiIiIyqrSz9imp6fj6NGjmDdvHtq1awd7e3u0aNECkyZNwocffggACA4Ohp+fn9p5eXl5sLS0xOrVqwEAXl5eGD16NCZMmAAzMzNYWVkhNDRUqu/g4AAA6N69O2QymbRfZM2aNXBwcICpqSk++ugjPHz4UCorLCxEWFgYHB0dYWBggCZNmmDz5s1S+YMHDzBgwABYWFjAwMAAdevWRUREBIAnSxFkMpm01OF5dUtTNItta2uLbt26wdvbGwcOHJDKc3JyMHr0aFhaWkJfXx8ffPABTp06JZVHRkZCqVSqtbl9+3bIZDKpfPr06Th37pw0OxwZGQlAfZa76Fq2bt2Kdu3awdDQEE2aNEFcXJxa28eOHUPr1q1hYGAAW1tbjB49Go8ePZLKv/vuO9StWxf6+vqoUaMGevXqVeq15+TkIDMzU20jIiIizVTpE1uFQgGFQoHt27cjJyenxDpDhgzB3r17oVKppGO7du1CdnY2+vbtKx2LioqCkZERTpw4gfnz52PGjBlSAliU6EVEREClUqklfklJSdi+fTt27dqFXbt24fDhw5g7d65UHhYWhp9++gkrVqzAX3/9hbFjx+Ljjz/G4cOHAQBTpkzBpUuXsGfPHiQkJGD58uWoXr16idfyMnVLcvHiRRw/fhx6enrSsQkTJmDLli2IiorCn3/+iTp16sDHxwf//PNPmdrs27cvPv/8czRo0AAqlQoqlUptXJ81efJkhISEID4+Hs7OzujXrx/y8/MBPBlLX19f9OzZE+fPn8eGDRtw7NgxjBo1CgBw+vRpjB49GjNmzEBiYiL27t2LNm3alNpXWFgYTE1Npc3W1rZM10RERESVT6VfiqCjo4PIyEgMHToUK1asgJubG9q2bYuPPvoIjRs3BgC0atUKLi4uWLNmDSZMmADgSYLau3dvKBQKqa3GjRtj2rRpAIC6deti2bJliI6ORseOHWFhYQEAUCqVxT5eLywsRGRkJIyNjQEAAwcORHR0NGbPno2cnBzMmTMHBw8eRMuWLQEATk5OOHbsGFauXIm2bdsiNTUVzZo1g7u7OwAUmw1+2svULbJr1y4oFArk5+cjJycHWlpaWLZsGQDg0aNHWL58OSIjI6W1sKtWrcKBAwewevVqjB8//oXtGxgYQKFQQEdHp0xLD0JCQtClSxcAwPTp09GgQQNcu3YN9erVQ1hYGAYMGIAxY8YAePJ9WLJkCdq2bYvly5cjNTUVRkZG8PPzg7GxMezt7dGsWbNS+5o0aRLGjRsn7WdmZjK5JSIi0lCVfsYWeLLG9tatW9i5cyd8fX0RExMDNzc36eNw4MmsbdFH9nfu3MGePXsQHBys1k5RIlzE2toaaWlpL+zfwcFBSmqfPe/atWvIzs5Gx44dpdllhUKBn376CUlJSQCA4cOHY/369WjatCkmTJiA48ePl9rXy9Qt0q5dO8THx+PEiRMIDAzEoEGD0LNnTwBPZkjz8vLg6ekp1dfV1UWLFi2QkJDwwrZfxdPjbG1tDQDSeJ07dw6RkZFqY+Xj44PCwkIkJyejY8eOsLe3h5OTEwYOHIi1a9ciOzu71L7kcjlMTEzUNiIiItJMGpHYAoC+vj46duyIKVOm4Pjx4wgKCpJmXwEgICAAf//9N+Li4vDzzz/D0dERrVu3VmtDV1dXbV8mk6GwsPCFfT/vvKysLADAb7/9hvj4eGm7dOmStM62U6dOuH79OsaOHYtbt26hQ4cOCAkJKbGvl6lbxMjICHXq1EGTJk3w448/4sSJE9La4rLQ0tKCEELtWF5eXpnPf9bT41W0Tvfp8frvf/+rNlbnzp3D1atXUbt2bRgbG+PPP//EunXrYG1tjalTp6JJkyZIT09/5XiIiIhIM1T6pQilqV+/vtqjuczNzdGtWzdEREQgLi4OgwYNeuk2dXV1UVBQ8NJxyOVypKamom3btqXWs7CwQGBgIAIDA9G6dWuMHz8eCxYseO26z9LS0sKXX36JcePGoX///qhduzb09PQQGxsLe3t7AE+S1lOnTknLASwsLPDw4UM8evQIRkZGAFDsub16enovPTYlcXNzw6VLl1CnTp1S6+jo6MDb2xve3t6YNm0alEolfv/9d/To0aPsHU26CXD2loiISKNU+sT2/v376N27N4KDg9G4cWMYGxvj9OnTmD9/Pvz9/dXqDhkyBH5+figoKEBgYOBL9+Xg4IDo6Gh4enpCLpejWrVqLzzH2NgYISEhGDt2LAoLC/HBBx8gIyMDsbGxMDExQWBgIKZOnYr33nsPDRo0QE5ODnbt2gVXV9cS23uZuqXp3bs3xo8fj2+//RYhISEYPnw4xo8fDzMzM9jZ2WH+/PnIzs7G4MGDAQAeHh4wNDTEl19+idGjR+PEiRNqyzyKxiY5ORnx8fGoVasWjI2NIZfLXyouAPjiiy/w/vvvY9SoURgyZAiMjIxw6dIlHDhwAMuWLcOuXbvw999/o02bNqhWrRp2796NwsJCuLi4vHRfREREpFkq/VIEhUIBDw8PLFy4EG3atEHDhg0xZcoUDB06VLpBqoi3tzesra3h4+MDGxubl+4rPDwcBw4cgK2t7XNvWHrWzJkzMWXKFISFhcHV1RW+vr747bff4OjoCODJbOekSZPQuHFjtGnTBtra2li/fn2Jbb1M3dLo6Ohg1KhRmD9/Ph49eoS5c+eiZ8+eGDhwINzc3HDt2jXs27dPStzNzMzw888/Y/fu3WjUqBHWrVun9ig04Mk6Z19fX7Rr1w4WFhZYt27dS8VUpHHjxjh8+DCuXLmC1q1bo1mzZpg6dar0/VIqldi6dSvat28PV1dXrFixAuvWrUODBg1eqT8iIiLSHDLx7OJJDZaVlYWaNWsiIiLi5T62Jo2RmZkJU1NTZGRk8EYyIiKiSqKsv78r/VKEsigsLMS9e/cQHh4OpVIpvbiBiIiIiDRHlUhsU1NT4ejoiFq1aiEyMhI6OlXisomIiIiqlCqR4Tk4OBR7XBURERERaZZKf/MYERERERHAxJaIiIiINAQTWyIiIiLSCExsiYiIiEgjMLElIiIiIo3AxJaIiIiINAITWyIiIiLSCExsiYiIiEgjMLElIiIiIo1QJd48RvSshtP2QUtu+ErnpsztUs7REBERUXngjC0RERERaQQmtkRERESkEZjYEhEREZFGYGJLRERERBqBiS0RERERaQQmtkRERESkEZjYEhEREZFGqPTPsb19+zYGDhyI48ePQ1dXF+np6RUdUplERkZizJgxlSbeV5GSkgJHR0ecPXsWTZs2rehw1FzUHwwTuezVTg4t11CoIoRmVHQERET0BpR5xlYmkz13Cw0NfYNhlm7hwoVQqVSIj4/HlStXKiSGF3FwcMCiRYvUjvXt2/etxOvl5SV9j/T19eHs7IywsDAIIcq1n6CgIHTr1k3tmK2tLVQqFRo2bFiufRERERGVpMwztiqVSvp6w4YNmDp1KhITE6VjCoVC+loIgYKCAujovPkJ4aSkJLz33nuoW7fuK7eRm5sLPT29cozqxQwMDGBgYPBW+ho6dChmzJiBnJwc/P777/jkk0+gVCoxfPjwN9qvtrY2rKys3mgfREREREXKPGNrZWUlbaamppDJZNL+5cuXYWxsjD179uC9996DXC7HsWPHkJSUBH9/f9SoUQMKhQLNmzfHwYMH1dp1cHDAnDlzEBwcDGNjY9jZ2eH777+XynNzczFq1ChYW1tDX18f9vb2CAsLk87dsmULfvrpJ8hkMgQFBQEAUlNT4e/vD4VCARMTE/Tp0wd37tyR2gwNDUXTpk3xww8/wNHREfr6+gCezEqvXLkSfn5+MDQ0hKurK+Li4nDt2jV4eXnByMgIrVq1QlJSktTWi67Ry8sL169fx9ixY6WZU+DJUgSlUqk2FsuXL0ft2rWhp6cHFxcXrFmzRq1cJpPhhx9+QPfu3WFoaIi6deti586dL/zeGRoawsrKCvb29hg0aBAaN26MAwcOSOUPHjxAQEAAqlWrBkNDQ3Tq1AlXr14tNl5PW7RoERwcHKTyqKgo7NixQ7rGmJgYpKSkQCaTIT4+HgAQExMDmUyG6OhouLu7w9DQEK1atVL7AwkAduzYATc3N+jr68PJyQnTp09Hfn4+gCd/NIWGhsLOzg5yuRw2NjYYPXp0qdeek5ODzMxMtY2IiIg0U7nePDZx4kTMnTsXCQkJaNy4MbKystC5c2dER0fj7Nmz8PX1RdeuXZGamqp2Xnh4ONzd3XH27FmMGDECw4cPl5KdJUuWYOfOndi4cSMSExOxdu1aKaE6deoUfH190adPH6hUKixevBiFhYXw9/fHP//8g8OHD+PAgQP4+++/0bdvX7U+r127hi1btmDr1q1S4gUAM2fOREBAAOLj41GvXj30798f//3vfzFp0iScPn0aQgiMGjVKqv+ia9y6dStq1aqFGTNmQKVSqc18P23btm347LPP8Pnnn+PixYv473//i0GDBuHQoUNq9aZPn44+ffrg/Pnz6Ny5MwYMGIB//vmnTN8fIQSOHj2Ky5cvq81QBwUF4fTp09i5cyfi4uIghEDnzp2Rl5dXpnZDQkLQp08f+Pr6StfYqlWrUutPnjwZ4eHhOH36NHR0dBAcHCyVHT16FAEBAfjss89w6dIlrFy5EpGRkZg9ezYAYMuWLVi4cCFWrlyJq1evYvv27WjUqFGpfYWFhcHU1FTabG1ty3RNREREVPmU61qBGTNmoGPHjtK+mZkZmjRpIu3PnDkT27Ztw86dO9WSw86dO2PEiBEAgC+++AILFy7EoUOH4OLigtTUVNStWxcffPABZDIZ7O3tpfMsLCwgl8thYGAgfeR94MABXLhwAcnJyVIS89NPP6FBgwY4deoUmjdvDuDJTPBPP/0ECwsLtWsYNGgQ+vTpI8XSsmVLTJkyBT4+PgCAzz77DIMGDZLqN2nS5LnXaGZmBm1tbRgbGz/3Y/kFCxYgKChIGodx48bhjz/+wIIFC9CuXTupXlBQEPr16wcAmDNnDpYsWYKTJ0/C19e31La/++47/PDDD8jNzUVeXh709fWlWc6rV69i586diI2NlZLRtWvXwtbWFtu3b0fv3r1LbbeIQqGAgYEBcnJyyrT0YPbs2Wjbti2AJ38MdenSBY8fP4a+vj6mT5+OiRMnIjAwEADg5OSEmTNnYsKECZg2bRpSU1NhZWUFb29v6Orqws7ODi1atCi1r0mTJmHcuHHSfmZmJpNbIiIiDVWuM7bu7u5q+1lZWQgJCYGrqyuUSiUUCgUSEhKKzdg2btxY+rpoiUNaWhqAJ4lcfHw8XFxcMHr0aOzfv/+5MSQkJMDW1lYtealfvz6USiUSEhKkY/b29sWS2mdjqVGjBgCozQjWqFEDjx8/lj7SLus1vkhCQgI8PT3Vjnl6eqrF/Gx8RkZGMDExkcaqNAMGDEB8fDxiY2PRqVMnTJ48WUpiExISoKOjAw8PD6m+ubk5XFxcivVdXp6+BmtrawCQruHcuXOYMWMGFAqFtA0dOhQqlQrZ2dno3bs3/v33Xzg5OWHo0KHYtm2btEyhJHK5HCYmJmobERERaaZynbE1MjJS2w8JCcGBAwewYMEC1KlTBwYGBujVqxdyc3PV6unq6qrty2QyFBYWAgDc3NyQnJyMPXv24ODBg+jTpw+8vb2xefPmco21pFiK1sOWdKwovrJeY3l53liVxtTUFHXq1AEAbNy4EXXq1MH7778Pb2/vMvWppaVV7CkKZV2mUJLnjWdWVhamT5+OHj16FDtPX18ftra2SExMxMGDB3HgwAGMGDECX3/9NQ4fPlxsbIiIiKhqeaOPLYiNjUVQUBC6d+8O4EnSkpKS8tLtmJiYoG/fvujbty969eoFX19f/PPPPzAzMytW19XVFTdu3MCNGzekWdtLly4hPT0d9evXf63rKUlZrlFPTw8FBQXPbcfV1RWxsbHSR/BFbZd3zAqFAp999hlCQkJw9uxZuLq6Ij8/HydOnJBmce/fv4/ExESpbwsLC9y+fRtCCCkRfXpdMlC2aywLNzc3JCYmSol4SQwMDNC1a1d07doVI0eORL169XDhwgW4ubmVvaNJNwHO3hIREWmUN5rY1q1bF1u3bkXXrl0hk8kwZcqUF84uPuubb76BtbU1mjVrBi0tLWzatAlWVlbFnihQxNvbG40aNcKAAQOwaNEi5OfnY8SIEWjbtm2xpRLloSzX6ODggCNHjuCjjz6CXC5H9erVi7Uzfvx49OnTB82aNYO3tzd+/fVXbN26tdhTJMrDf//7X8ycORNbtmxBr1694O/vj6FDh2LlypUwNjbGxIkTUbNmTfj7+wN48mSHu3fvYv78+ejVqxf27t2LPXv2qH2s7+DggH379iExMRHm5uYwNTV9pdimTp0KPz8/2NnZoVevXtDS0sK5c+dw8eJFzJo1C5GRkSgoKICHhwcMDQ3x888/w8DAQG3tNREREVVNb/SVut988w2qVauGVq1aoWvXrvDx8Xm5WTUAxsbGmD9/Ptzd3dG8eXOkpKRg9+7d0NIqOXSZTIYdO3agWrVqaNOmDby9veHk5IQNGzaUxyUVU5ZrnDFjBlJSUlC7du0S1/UCQLdu3bB48WIsWLAADRo0wMqVKxEREQEvL69yj9nMzAwBAQEIDQ1FYWEhIiIi8N5778HPzw8tW7aEEAK7d++WPtp3dXXFd999h2+//RZNmjTByZMnERISotbm0KFD4eLiAnd3d1hYWCA2NvaVYvPx8cGuXbuwf/9+NG/eHO+//z4WLlwoJa5KpRKrVq2Cp6cnGjdujIMHD+LXX3+Fubn56w0KERERVXoyUd6voCJ6h2VmZsLU1BQZGRm8kYyIiKiSKOvv7zc6Y0tERERE9LYwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIIOhUdQFWRkpICR0dHnD17Fk2bNkVMTAzatWuHBw8eQKlUIjIyEmPGjEF6enpFh1qugoKCkJ6eju3bt1d0KOrCagFy2YvrhWa8+ViIiIioXHDG9iV4eXlhzJgxxY5HRkZCqVRK+0FBQejWrZtaHVtbW6hUKjRs2LDEtvv27YsrV65I+6GhoWjatOlrxxwTEwOZTCZtFhYW6Ny5My5cuPDabT8tJSUFMpkM8fHxascXL16MyMjIcu2LiIiIqCRMbN8SbW1tWFlZQUen5ElyAwMDWFpavrH+ExMToVKpsG/fPuTk5KBLly7Izc19Y/0VMTU1VUv6iYiIiN4UJrblLDQ0FFFRUdixY4c0SxoTE1PqjGaRp2d9IyMjMX36dJw7d05qIzIyEsHBwfDz81M7Ly8vD5aWlli9evVz47K0tISVlRXc3NwwZswY3LhxA5cvX5bKt2zZggYNGkAul8PBwQHh4eFq58tksmLLCYqWUACAo6MjAKBZs2aQyWTw8vICUHz22svLC6NHj8aECRNgZmYGKysrhIaGqrWbnp6OIUOGwMLCAiYmJmjfvj3OnTsnlZ87dw7t2rWDsbExTExM8N577+H06dMlXndOTg4yMzPVNiIiItJMXGNbzkJCQpCQkIDMzExEREQAAMzMzHDr1q0yt9G3b19cvHgRe/fuxcGDBwE8mfl0dnZGmzZtoFKpYG1tDQDYtWsXsrOz0bdv3zK1nZGRgfXr1wMA9PT0AABnzpxBnz59EBoair59++L48eMYMWIEzM3NERQUVKZ2T548iRYtWuDgwYNo0KCB1HZJoqKiMG7cOJw4cQJxcXEICgqCp6cnOnbsCADo3bs3DAwMsGfPHpiammLlypXo0KEDrly5AjMzMwwYMADNmjXD8uXLoa2tjfj4eOjq6pbYV1hYGKZPn16mayAiIqLKjYltOVMoFDAwMEBOTg6srKxeqQ0DAwMoFAro6OiotdGqVSu4uLhgzZo1mDBhAgAgIiICvXv3hkKheG6btWrVAgA8evQIAPDhhx+iXr16AIBvvvkGHTp0wJQpUwAAzs7OuHTpEr7++usyJ7YWFhYAAHNz8xded+PGjTFt2jQAQN26dbFs2TJER0ejY8eOOHbsGE6ePIm0tDTI5XIAwIIFC7B9+3Zs3rwZn3zyCVJTUzF+/Hgp/rp165ba16RJkzBu3DhpPzMzE7a2tmW6JiIiIqpcuBShkhkyZIg0E3znzh3s2bMHwcHBLzzv6NGjOHPmDCIjI+Hs7IwVK1ZIZQkJCfD09FSr7+npiatXr6KgoKB8LwBPEtunWVtbIy0tDcCTZQZZWVkwNzeHQqGQtuTkZCQlJQEAxo0bhyFDhsDb2xtz586VjpdELpfDxMREbSMiIiLNxBnbl2BiYoKMjOKPf0pPT4epqelbiSEgIAATJ05EXFwcjh8/DkdHR7Ru3fqF5zk6OkKpVMLFxQVpaWno27cvjhw5UuZ+ZTIZhBBqx/Ly8l46fgDFlg3IZDIUFhYCALKysmBtbY2YmJhi5xWtQQ4NDUX//v3x22+/Yc+ePZg2bRrWr1+P7t27v1I8REREpBmY2L4EFxcX7N+/v9jxP//8E87OztK+np7ea890ltaGubk5unXrhoiICMTFxWHQoEEv3fbIkSMRFhaGbdu2oXv37nB1dUVsbKxandjYWDg7O0NbWxvAk6UGKpVKKr969Sqys7PV4gXw2tft5uaG27dvQ0dHBw4ODqXWc3Z2hrOzM8aOHYt+/fohIiLi5RLbSTcBzt4SERFpFC5FeAnDhw/HlStXMHr0aJw/fx6JiYn45ptvsG7dOnz++edSPQcHB6n83r17rzSz6eDggOTkZMTHx+PevXvIycmRyoYMGYKoqCgkJCQgMDDwpds2NDTE0KFDMW3aNAgh8PnnnyM6OhozZ87ElStXEBUVhWXLliEkJEQ6p3379li2bBnOnj2L06dPY9iwYWozr5aWljAwMMDevXtx586dEme2y8Lb2xstW7ZEt27dsH//fqSkpOD48eOYPHkyTp8+jX///RejRo1CTEwMrl+/jtjYWJw6dQqurq6v1B8RERFpDia2L8HJyQlHjhzB5cuX4e3tDQ8PD2zcuBGbNm2Cr6+vVG/o0KFwcXGBu7s7LCwsis2GlkXPnj3h6+uLdu3awcLCAuvWrZPKvL29YW1tDR8fH9jY2LzStYwaNQoJCQnYtGkT3NzcsHHjRqxfvx4NGzbE1KlTMWPGDLUbx8LDw2Fra4vWrVujf//+CAkJgaGhoVSuo6ODJUuWYOXKlbCxsYG/v/8rxSWTybB79260adMGgwYNgrOzMz766CNcv34dNWrUgLa2Nu7fv4+AgAA4OzujT58+6NSpE598QERERJCJZxdO0jsvKysLNWvWREREBHr06FHR4VQqmZmZMDU1RUZGBm8kIyIiqiTK+vuba2wrkcLCQty7dw/h4eFQKpX48MMPKzokIiIioncGE9tKJDU1FY6OjqhVqxYiIyNLfT0vERERUVXEzKgScXBwKPbILSIiIiJ6gjePEREREZFGYGJLRERERBqBiS0RERERaQQmtkRERESkEZjYEhEREZFGYGJLRERERBqBiS0RERERaQQmtkRERESkEZjYEhEREZFG4JvHqEopenNbZmZmBUdCREREZVX0e/tFb2BlYktVyv379wEAtra2FRwJERERvayHDx/C1NS01HImtlSlmJmZAQBSU1Of+4NBZZOZmQlbW1vcuHEDJiYmFR1OpcfxLF8cz/LF8SxfHM+XI4TAw4cPYWNj89x6TGypStHSerKs3NTUlP+RlCMTExOOZznieJYvjmf54niWL45n2ZVlQoo3jxERERGRRmBiS0REREQagYktVSlyuRzTpk2DXC6v6FA0AsezfHE8yxfHs3xxPMsXx/PNkIkXPTeBiIiIiKgS4IwtEREREWkEJrZEREREpBGY2BIRERGRRmBiS0REREQagYktEREREWkEJrZUZXz77bdwcHCAvr4+PDw8cPLkyYoOqVIIDQ2FTCZT2+rVqyeVP378GCNHjoS5uTkUCgV69uyJO3fuVGDE75YjR46ga9eusLGxgUwmw/bt29XKhRCYOnUqrK2tYWBgAG9vb1y9elWtzj///IMBAwbAxMQESqUSgwcPRlZW1lu8infHi8YzKCio2L9XX19ftTocz/8TFhaG5s2bw9jYGJaWlujWrRsSExPV6pTlZzw1NRVdunSBoaEhLC0tMX78eOTn57/NS3knlGU8vby8iv0bHTZsmFodjuerY2JLVcKGDRswbtw4TJs2DX/++SeaNGkCHx8fpKWlVXRolUKDBg2gUqmk7dixY1LZ2LFj8euvv2LTpk04fPgwbt26hR49elRgtO+WR48eoUmTJvj2229LLJ8/fz6WLFmCFStW4MSJEzAyMoKPjw8eP34s1RkwYAD++usvHDhwALt27cKRI0fwySefvK1LeKe8aDwBwNfXV+3f67p169TKOZ7/5/Dhwxg5ciT++OMPHDhwAHl5efjPf/6DR48eSXVe9DNeUFCALl26IDc3F8ePH0dUVBQiIyMxderUirikClWW8QSAoUOHqv0bnT9/vlTG8XxNgqgKaNGihRg5cqS0X1BQIGxsbERYWFgFRlU5TJs2TTRp0qTEsvT0dKGrqys2bdokHUtISBAARFxc3FuKsPIAILZt2ybtFxYWCisrK/H1119Lx9LT04VcLhfr1q0TQghx6dIlAUCcOnVKqrNnzx4hk8nE//73v7cW+7vo2fEUQojAwEDh7+9f6jkcz+dLS0sTAMThw4eFEGX7Gd+9e7fQ0tISt2/fluosX75cmJiYiJycnLd7Ae+YZ8dTCCHatm0rPvvss1LP4Xi+Hs7YksbLzc3FmTNn4O3tLR3T0tKCt7c34uLiKjCyyuPq1auwsbGBk5MTBgwYgNTUVADAmTNnkJeXpza29erVg52dHce2DJKTk3H79m218TM1NYWHh4c0fnFxcVAqlXB3d5fqeHt7Q0tLCydOnHjrMVcGMTExsLS0hIuLC4YPH4779+9LZRzP58vIyAAAmJmZASjbz3hcXBwaNWqEGjVqSHV8fHyQmZmJv/766y1G/+55djyLrF27FtWrV0fDhg0xadIkZGdnS2Ucz9ejU9EBEL1p9+7dQ0FBgdp/EgBQo0YNXL58uYKiqjw8PDwQGRkJFxcXqFQqTJ8+Ha1bt8bFixdx+/Zt6OnpQalUqp1To0YN3L59u2ICrkSKxqikf5tFZbdv34alpaVauY6ODszMzDjGJfD19UWPHj3g6OiIpKQkfPnll+jUqRPi4uKgra3N8XyOwsJCjBkzBp6enmjYsCEAlOln/Pbt2yX+Gy4qq6pKGk8A6N+/P+zt7WFjY4Pz58/jiy++QGJiIrZu3QqA4/m6mNgS0XN16tRJ+rpx48bw8PCAvb09Nm7cCAMDgwqMjKi4jz76SPq6UaNGaNy4MWrXro2YmBh06NChAiN7940cORIXL15UW0NPr6608Xx6PXejRo1gbW2NDh06ICkpCbVr137bYWocLkUgjVe9enVoa2sXu4v3zp07sLKyqqCoKi+lUglnZ2dcu3YNVlZWyM3NRXp6ulodjm3ZFI3R8/5tWllZFbvJMT8/H//88w/HuAycnJxQvXp1XLt2DQDHszSjRo3Crl27cOjQIdSqVUs6XpafcSsrqxL/DReVVUWljWdJPDw8AEDt3yjH89UxsSWNp6enh/feew/R0dHSscLCQkRHR6Nly5YVGFnllJWVhaSkJFhbW+O9996Drq6u2tgmJiYiNTWVY1sGjo6OsLKyUhu/zMxMnDhxQhq/li1bIj09HWfOnJHq/P777ygsLJR+IVLpbt68ifv378Pa2hoAx/NZQgiMGjUK27Ztw++//w5HR0e18rL8jLds2RIXLlxQ+4PhwIEDMDExQf369d/OhbwjXjSeJYmPjwcAtX+jHM/XUNF3rxG9DevXrxdyuVxERkaKS5cuiU8++UQolUq1u06pZJ9//rmIiYkRycnJIjY2Vnh7e4vq1auLtLQ0IYQQw4YNE3Z2duL3338Xp0+fFi1bthQtW7as4KjfHQ8fPhRnz54VZ8+eFQDEN998I86ePSuuX78uhBBi7ty5QqlUih07dojz588Lf39/4ejoKP7991+pDV9fX9GsWTNx4sQJcezYMVG3bl3Rr1+/irqkCvW88Xz48KEICQkRcXFxIjk5WRw8eFC4ubmJunXrisePH0ttcDz/z/Dhw4WpqamIiYkRKpVK2rKzs6U6L/oZz8/PFw0bNhT/+c9/RHx8vNi7d6+wsLAQkyZNqohLqlAvGs9r166JGTNmiNOnT4vk5GSxY8cO4eTkJNq0aSO1wfF8PUxsqcpYunSpsLOzE3p6eqJFixbijz/+qOiQKoW+ffsKa2troaenJ2rWrCn69u0rrl27JpX/+++/YsSIEaJatWrC0NBQdO/eXahUqgqM+N1y6NAhAaDYFhgYKIR48sivKVOmiBo1agi5XC46dOggEhMT1dq4f/++6Nevn1AoFMLExEQMGjRIPHz4sAKupuI9bzyzs7PFf/7zH2FhYSF0dXWFvb29GDp0aLE/YDme/6eksQQgIiIipDpl+RlPSUkRnTp1EgYGBqJ69eri888/F3l5eW/5airei8YzNTVVtGnTRpiZmQm5XC7q1Kkjxo8fLzIyMtTa4Xi+OpkQQry9+WEiIiIiojeDa2yJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0AhNbIiIiItIITGyJiIiISCMwsSUiIiIijcDEloiIiIg0wv8DERHlww/fFeYAAAAASUVORK5CYII=",
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