From c4ef2f981814542a30928363018d866e97d66bfb Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Tue, 29 Jul 2025 17:45:38 +0200
Subject: [PATCH 01/14] Fix bugs

Interesting bugs caused by notebook usage (accidental usage of global
variables).
---
 source-code/ising_model.ipynb | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/source-code/ising_model.ipynb b/source-code/ising_model.ipynb
index 7c2d44a..066b685 100644
--- a/source-code/ising_model.ipynb
+++ b/source-code/ising_model.ipynb
@@ -982,13 +982,15 @@
     "    '''Class that implements a stepper for the Glauber dynamics.\n",
     "    '''\n",
     "\n",
-    "    def __init__(self, temperature):\n",
+    "    def __init__(self, temperature, ising):\n",
     "        '''Initializes the stepper.\n",
     "        \n",
     "        Parameters\n",
     "        ----------\n",
     "        temperature: float\n",
     "          temperature to use in the dynamics\n",
+    "        ising: IsingSystem\n",
+    "           Ising system to update\n",
     "        '''\n",
     "        super().__init__(temperature)\n",
     "        self._row_indices = np.arange(0, ising.nr_rows)\n",
@@ -1331,7 +1333,7 @@
     "                self._compute_measures(step_nr)\n",
     "                if self._is_converged():\n",
     "                    break\n",
-    "            self._stepper.update(ising)\n",
+    "            self._stepper.update(self._ising)\n",
     "        else:\n",
     "            self._compute_measures(step_nr)"
    ]

From 882fd79f8f5362aca93b9eb5c1aa4a631a4f398e Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Wed, 30 Jul 2025 14:08:57 +0200
Subject: [PATCH 02/14] Fix bugs

---
 source-code/ising_model.ipynb | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/source-code/ising_model.ipynb b/source-code/ising_model.ipynb
index 066b685..94cbb79 100644
--- a/source-code/ising_model.ipynb
+++ b/source-code/ising_model.ipynb
@@ -444,6 +444,8 @@
     "        self._name = name\n",
     "        if headers is None:\n",
     "            self._headers = (self._name, )\n",
+    "        else:\n",
+    "            self._headers = tuple(headers)\n",
     "        self._sep = ' '\n",
     "        self._values = []\n",
     "\n",
@@ -936,7 +938,7 @@
     "            ) + ising.h\n",
     "        )\n",
     "\n",
-    "    @abc.abstractclassmethod\n",
+    "    @abc.abstractmethod\n",
     "    def update(self, ising, nr_steps=1):\n",
     "        '''Abstract method that updates the Ising system according to the dynamics\n",
     "        specified by the derived classes.\n",
@@ -1160,7 +1162,7 @@
    "outputs": [],
    "source": [
     "class IsMeasureStable(AbstractIsConverged):\n",
-    "    '''Convergence criterion that will stop the simulation if the meaure is\n",
+    "    '''Convergence criterion that will stop the simulation if the measure is\n",
     "    constant to within an absolute error for a given number of steps.'''\n",
     "\n",
     "    def __init__(self, *, measure, nr_measurement_steps, delta):\n",

From 2b256655e1e6ee9afd6e8e4f700b2c5da96cdd79 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Wed, 30 Jul 2025 14:09:53 +0200
Subject: [PATCH 03/14] Update environment

---
 environment.yml                           | 328 +-----------
 scientific_python_linux64_conda_specs.txt | 593 +++++++++++-----------
 2 files changed, 311 insertions(+), 610 deletions(-)

diff --git a/environment.yml b/environment.yml
index 51cbec4..47e91df 100644
--- a/environment.yml
+++ b/environment.yml
@@ -3,7 +3,6 @@ channels:
   - conda-forge
 dependencies:
   - bokeh
-  - hdf5
   - ipywidgets
   - jupyterlab
   - jupyterlab_widgets
@@ -14,334 +13,11 @@ dependencies:
   - opencv
   - pandas
   - pytables
-  - python
-  - scikit-image
+  - h5py
   - scipy
+  - scikit-image
   - sympy
   - xarray
-  - debugpy
-  - nbclassic
-  - pygments
-  - ipython
-  - libllvm11
-  - openh264
-  - libwebp
-  - cycler
-  - lerc
-  - mock
-  - pyqt
-  - blas
-  - xorg-libxau
-  - notebook-shim
-  - stack_data
-  - backcall
-  - libgcc-ng
-  - entrypoints
-  - jxrlib
-  - argon2-cffi-bindings
-  - appdirs
-  - libtasn1
-  - libsodium
-  - bzip2
-  - fonttools
-  - libbrotlidec
-  - jupyter_core
-  - libunistring
-  - pyqt5-sip
-  - comm
-  - tzdata
-  - mpfr
-  - partd
-  - libtiff
-  - libopencv
-  - libgomp
-  - libbrotlienc
-  - pure_eval
-  - xorg-fixesproto
-  - jsonschema
-  - pyparsing
-  - brotli
-  - libopus
-  - nbformat
-  - send2trash
-  - libblas
-  - glib-tools
-  - python-fastjsonschema
-  - fontconfig
-  - pytz
-  - openssl
-  - dask-core
-  - yaml
-  - dbus
-  - idna
-  - libglu
-  - matplotlib-base
-  - pyrsistent
-  - typing_extensions
-  - libogg
-  - xorg-libxext
-  - gnutls
-  - charset-normalizer
-  - contourpy
-  - pyqt-impl
-  - xorg-xextproto
-  - libglib
-  - notebook
   - networkx
-  - freeglut
-  - tomli
-  - ffmpeg
-  - expat
-  - libopenblas
-  - libzopfli
-  - libgfortran-ng
-  - attrs
-  - traitlets
-  - imagecodecs
-  - sqlite
-  - openjpeg
-  - munkres
-  - libxslt
-  - giflib
-  - wheel
-  - libcurl
-  - markupsafe
-  - python_abi
-  - pooch
-  - gettext
-  - krb5
-  - requests
-  - pywavelets
-  - cairo
-  - cfitsio
-  - pillow
-  - py-opencv
-  - terminado
-  - certifi
-  - xorg-libxfixes
-  - qt
-  - alsa-lib
-  - pickleshare
-  - libcblas
-  - websocket-client
-  - locket
-  - bleach
-  - libaec
-  - nest-asyncio
-  - jasper
-  - kiwisolver
-  - libstdcxx-ng
-  - libdeflate
-  - argon2-cffi
-  - libidn2
-  - xorg-kbproto
-  - pyyaml
-  - _openmp_mutex
-  - prometheus_client
-  - jpeg
-  - widgetsnbextension
-  - asttokens
-  - libxml2
-  - six
-  - packaging
-  - cffi
-  - c-ares
-  - libedit
-  - libevent
-  - python-dateutil
-  - brotli-bin
-  - pyzmq
-  - executing
-  - readline
-  - libssh2
-  - libffi
-  - platformdirs
-  - mysql-common
-  - mpc
-  - ptyprocess
-  - libclang
-  - libpng
-  - _libgcc_mutex
-  - jupyterlab_pygments
-  - mpmath
-  - jupyterlab_server
-  - pexpect
-  - matplotlib-inline
-  - babel
-  - graphite2
-  - glib
-  - zeromq
-  - lame
-  - xorg-libxi
-  - tornado
-  - pysocks
-  - ca-certificates
-  - jinja2
-  - setuptools
-  - icu
-  - libxcb
-  - blosc
-  - x264
-  - lz4-c
-  - pyopenssl
-  - decorator
-  - harfbuzz
-  - libuv
-  - gstreamer
-  - ld_impl_linux-64
-  - soupsieve
-  - ipykernel
-  - nss
-  - libzlib
-  - fsspec
-  - zlib
-  - imageio
-  - pcre
-  - cytoolz
-  - mysql-libs
-  - brotlipy
-  - libprotobuf
-  - cryptography
-  - cloudpickle
-  - gst-plugins-base
-  - xorg-xproto
-  - xyzservices
-  - brunsli
-  - tifffile
-  - jupyter_client
-  - lxml
-  - lcms2
-  - pandocfilters
-  - libuuid
-  - psutil
-  - libxkbcommon
-  - beautifulsoup4
-  - defusedxml
-  - flit-core
-  - libiconv
-  - prompt-toolkit
-  - gmp
-  - jedi
-  - wcwidth
-  - snappy
-  - libbrotlicommon
-  - nettle
-  - charls
-  - pixman
-  - pyqtwebengine
-  - tk
-  - mistune
-  - ipython_genutils
-  - nspr
   - nbconvert
-  - xz
-  - webencodings
-  - zfp
-  - sniffio
-  - anyio
-  - lzo
-  - liblapacke
-  - libgfortran5
-  - pyqtchart
-  - ncurses
-  - liblapack
-  - libwebp-base
-  - parso
-  - bottleneck
-  - libvorbis
-  - pycparser
-  - pip
-  - freetype
-  - gmpy2
-  - json5
-  - zstd
-  - jupyter_server
-  - libpq
-  - nbclient
-  - libnghttp2
-  - libev
-  - toolz
-  - urllib3
-  - tinycss2
-  - numpy-base
-  - xorg-inputproto
-  - xorg-libx11
-  - typing-extensions
-  - jupyter_events
-  - python-tzdata
-  - exceptiongroup
-  - pcre2
-  - rfc3986-validator
-  - nbconvert-core
-  - libexpat
-  - c-blosc2
-  - overrides
-  - backports.functools_lru_cache
-  - prompt_toolkit
-  - zipp
-  - nomkl
-  - libavif
-  - typing_utils
-  - unicodedata2
-  - async-lru
-  - pandoc
-  - rfc3339-validator
-  - lazy_loader
-  - libsqlite
-  - aom
-  - nbconvert-pandoc
-  - importlib-metadata
-  - zlib-ng
-  - importlib_resources
-  - jupyter_server_terminals
-  - backports
-  - jupyter-lsp
-  - importlib_metadata
-  - click
-  - python-json-logger
-  - dav1d
-  - h2
-  - arrow
-  - cached_property
-  - isoduration
-  - rpds-py
-  - httpcore
-  - types-python-dateutil
-  - webcolors
-  - referencing
-  - pkgutil-resolve-name
-  - jsonschema-specifications
-  - hyperframe
-  - libasprintf
-  - jsonschema-with-format-nongpl
-  - libgettextpo
-  - gettext-tools
-  - libasprintf-devel
-  - cached-property
-  - fqdn
-  - jsonpointer
-  - httpx
-  - uri-template
-  - h11
-  - hpack
-  - brotli-python
-  - libgettextpo-devel
-  - h5py
-  - libgfortran
-  - zstandard
-  - pthread-stubs
-  - libdrm
-  - libstdcxx
-  - lazy-loader
-  - xorg-libxxf86vm
-  - libglvnd
-  - libgl
-  - libpciaccess
-  - xorg-libxdamage
-  - xorg-xorgproto
-  - libegl
-  - xorg-libxdmcp
-  - libglx
-  - libgcc
-  - qhull
 prefix: /home/gjb/mambaforge/envs/scientific_python
diff --git a/scientific_python_linux64_conda_specs.txt b/scientific_python_linux64_conda_specs.txt
index 9e9098c..b8605b6 100644
--- a/scientific_python_linux64_conda_specs.txt
+++ b/scientific_python_linux64_conda_specs.txt
@@ -3,344 +3,369 @@
 # platform: linux-64
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
-https://repo.anaconda.com/pkgs/main/linux-64/blas-1.0-openblas.conda
-https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2024.8.30-hbcca054_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.43-h712a8e2_2.conda
+https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.7.14-hbd8a1cb_0.conda
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-h77eed37_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.44-h1423503_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/libglvnd-1.7.0-ha4b6fd6_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.1.0-h767d61c_3.conda
 https://conda.anaconda.org/conda-forge/noarch/nomkl-1.0-h5ca1d4c_0.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/pandoc-3.5-ha770c72_0.conda
-https://conda.anaconda.org/conda-forge/noarch/tzdata-2024b-hc8b5060_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/libegl-1.7.0-ha4b6fd6_2.conda
-https://conda.anaconda.org/conda-forge/linux-64/libgomp-14.2.0-h77fa898_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/pandoc-3.7.0.2-ha770c72_0.conda
+https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda
+https://conda.anaconda.org/conda-forge/noarch/tzdata-2025b-h78e105d_0.conda
+https://conda.anaconda.org/conda-forge/noarch/wayland-protocols-1.45-hd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/libgcc-14.2.0-h77fa898_1.conda
-https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.34.3-hb9d3cd8_1.conda
-https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.6.4-h5888daf_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-14.2.0-h69a702a_1.conda
-https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-14.2.0-hd5240d6_1.conda
-https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-14.2.0-hc0a3c3a_1.conda
+https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-0.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/libegl-1.7.0-ha4b6fd6_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/libopengl-1.7.0-ha4b6fd6_2.conda
+https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.1.0-h767d61c_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.14-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.34.5-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.1.0-hb9d3cd8_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.24-h86f0d12_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.1-hecca717_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.6-h2dba641_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.1.0-h69a702a_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.1.0-hcea5267_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.18-h4ce23a2_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-3.1.0-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.1-hb9d3cd8_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libntlm-1.8-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libogg-1.3.5-hd0c01bc_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/libopus-1.5.2-hd0c01bc_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libpciaccess-0.18-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.1.0-h8f9b012_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/libuv-1.51.0-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libwebp-base-1.6.0-hd42ef1d_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/openssl-3.5.1-h7b32b05_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-hb9d3cd8_1002.conda
-https://conda.anaconda.org/conda-forge/linux-64/xorg-inputproto-2.3.2-hb9d3cd8_1003.conda
-https://conda.anaconda.org/conda-forge/linux-64/xorg-kbproto-1.0.7-hb9d3cd8_1003.conda
-https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.11-hb9d3cd8_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/rav1e-0.7.1-h8fae777_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/xorg-libice-1.1.2-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.12-hb9d3cd8_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.5-hb9d3cd8_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/xorg-xextproto-7.3.0-hb9d3cd8_1004.conda
-https://conda.anaconda.org/conda-forge/linux-64/xorg-xorgproto-2024.1-hb9d3cd8_1.conda
-https://conda.anaconda.org/conda-forge/linux-64/xorg-xproto-7.0.31-hb9d3cd8_1008.conda
-https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.3.2-h166bdaf_0.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h280c20c_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.1-h166bdaf_1.tar.bz2
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 https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/expat-2.6.4-h5888daf_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/gettext-tools-0.22.5-he02047a_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/double-conversion-3.3.1-h5888daf_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.10-h36c2ea0_0.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/gettext-tools-0.25.1-h3f43e3d_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/giflib-5.2.2-hd590300_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/jpeg-9e-h0b41bf4_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/graphite2-1.3.14-h5888daf_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/imath-3.1.12-h7955e40_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/jxrlib-1.1-hd590300_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.1-h166bdaf_0.tar.bz2
 https://conda.anaconda.org/conda-forge/linux-64/lame-3.100-h166bdaf_1003.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.0.9-h166bdaf_9.conda
-https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.14-h166bdaf_0.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/lerc-4.0.0-h0aef613_1.conda
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+https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.16.6-hed9df3c_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/py-opencv-4.12.0-qt6_py313hc0a75a6_601.conda
+https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.6-pyhe01879c_0.conda
+https://conda.anaconda.org/conda-forge/noarch/jupyterlab_server-2.27.3-pyhd8ed1ab_1.conda
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.16.6-hb482800_0.conda
 https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.4-pyhd8ed1ab_1.conda
-https://conda.anaconda.org/conda-forge/noarch/jupyterlab-4.3.2-pyhd8ed1ab_0.conda
-https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.1.0-pyhd8ed1ab_1.conda
-https://conda.anaconda.org/conda-forge/noarch/notebook-7.3.1-pyhd8ed1ab_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/opencv-4.12.0-qt6_py313h6537eeb_601.conda
+https://conda.anaconda.org/conda-forge/noarch/jupyterlab-4.4.5-pyhd8ed1ab_0.conda

From dcc1afe65bf538a22246bf960a3c8ab04fdef9a3 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Wed, 30 Jul 2025 15:57:48 +0200
Subject: [PATCH 04/14] Fix bug

---
 source-code/ising_model.ipynb | 291 ++++++++++++++++++++++++----------
 1 file changed, 207 insertions(+), 84 deletions(-)

diff --git a/source-code/ising_model.ipynb b/source-code/ising_model.ipynb
index 94cbb79..fcee435 100644
--- a/source-code/ising_model.ipynb
+++ b/source-code/ising_model.ipynb
@@ -322,7 +322,7 @@
     {
      "data": {
       "text/plain": [
-       "1"
+       "np.int64(1)"
       ]
      },
      "execution_count": 6,
@@ -371,6 +371,16 @@
     "print(ising)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a59dfea9-4910-4499-99b4-cb8f751815ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "bae6eb9d-858e-47d4-8aff-322e6d8800b8",
@@ -390,25 +400,6 @@
     "  * the energy."
    ]
   },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "50de9177-b032-4727-a9dd-4f9b00c7883f",
-   "metadata": {},
-   "source": [
-    "To test the measures you define, it is a good idea to use a very small Ising system, so that it is easy to check the results by hand."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "5355cecb-a38b-4fc1-b42a-41c7b07784fb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "mini_ising = IsingSystem(nr_rows=4, nr_cols=4, J=0.5, h=2.0, seed=1234)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "0e990376-7c28-4f1e-b6ed-cba7cce33bef",
@@ -629,6 +620,25 @@
     "        return magnetization/ising.N"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "44353a9a-56f2-4653-b6cd-100df9a3fe05",
+   "metadata": {},
+   "source": [
+    "To test the measures you define, it is a good idea to use a very small Ising system, so that it is easy to check the results by hand."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "5355cecb-a38b-4fc1-b42a-41c7b07784fb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mini_ising = IsingSystem(nr_rows=4, nr_cols=4, J=0.5, h=2.0, seed=1234)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "676e6fcb-9eae-4b8d-8637-04c9caa08e23",
@@ -639,7 +649,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 29,
    "id": "e8ef6d91-071a-47ef-b392-f296b6cde930",
    "metadata": {},
    "outputs": [],
@@ -649,7 +659,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 30,
    "id": "3247c2eb-03cc-4d03-949e-f022a30e950c",
    "metadata": {
     "scrolled": true
@@ -658,10 +668,10 @@
     {
      "data": {
       "text/plain": [
-       "0.125"
+       "np.float64(0.125)"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -672,7 +682,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 31,
    "id": "8d88729d-dbd4-48a5-abf0-f1ddc542886e",
    "metadata": {},
    "outputs": [
@@ -699,6 +709,16 @@
     "The system has 9 spins up ($s_i = 1$) and 7 spins down ($s_i = -1$) while $N = 16$, so the magnetization should be $(9 - 7)/16 = 1/8 = 0.125$ as computed."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "ab636c0d-cf08-4c7e-b4ee-22b114194b5e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del mini_ising, M"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "d2114304-d63b-49d5-beb1-b6b58dec632e",
@@ -762,9 +782,28 @@
     "        return energy/ising.N"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "b023beb7-4de2-4de3-83a9-d2165705868e",
+   "metadata": {},
+   "source": [
+    "To test the measures you define, it is a good idea to use a very small Ising system, so that it is easy to check the results by hand."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "9abd4c5b-545e-497d-ae24-9a773f078dbf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mini_ising = IsingSystem(nr_rows=4, nr_cols=4, J=0.5, h=2.0, seed=1234)"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 34,
    "id": "98473b4d-74a2-4808-83b9-bdc67d436c94",
    "metadata": {},
    "outputs": [],
@@ -774,17 +813,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 35,
    "id": "7c3374cd-13f2-4791-bcca-4c89eec59b05",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "-0.125"
+       "np.float64(-0.125)"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -795,7 +834,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 36,
    "id": "37169d46-f5c4-44c6-ac64-df8023310bce",
    "metadata": {
     "scrolled": true
@@ -818,7 +857,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 37,
    "id": "a59b0432-7a6d-4744-b038-c0e9811c6769",
    "metadata": {},
    "outputs": [
@@ -828,7 +867,7 @@
        "\"{\\n    'nr_rows': 4,\\n    'nr_cols': 4,\\n    'J': 0.5,\\n    'h': 2.0,\\n    'seed': 1234,\\n}\""
       ]
      },
-     "execution_count": 19,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -845,6 +884,16 @@
     "Again, this checks out, so the implementation could be correct."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "bbec6169-6ffc-4e29-a0fc-b13124343baf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del mini_ising, E"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "775d8ad5-4828-4b77-b76a-2f53e43c3f68",
@@ -1106,7 +1155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 23,
    "id": "2ee63b6b-567d-4e93-b3a5-490727f539fa",
    "metadata": {},
    "outputs": [],
@@ -1156,7 +1205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 24,
    "id": "e33e760c-e55f-4943-b3e7-a6b186588de9",
    "metadata": {},
    "outputs": [],
@@ -1233,7 +1282,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 25,
    "id": "990696f0-1970-40ac-b917-82af57398c94",
    "metadata": {},
    "outputs": [],
@@ -1390,7 +1439,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 26,
    "id": "c2fd28f7-f2da-456e-bbac-880cd034ee6c",
    "metadata": {},
    "outputs": [],
@@ -1408,12 +1457,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 39,
    "id": "c19a4dcc-32f6-4c89-b03e-6ebf71259bf4",
    "metadata": {},
    "outputs": [],
    "source": [
-    "stepper = GlauberStepper(temperature=2.0)"
+    "stepper = GlauberStepper(temperature=2.0, ising=ising)"
    ]
   },
   {
@@ -1426,7 +1475,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 40,
    "id": "5b951fc1-29fb-43d0-81ac-c2df9ce34667",
    "metadata": {},
    "outputs": [],
@@ -1448,7 +1497,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "id": "e51bb5c2-86b9-435f-9d93-90ee10f0fbb6",
    "metadata": {},
    "outputs": [],
@@ -1471,7 +1520,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 42,
    "id": "44f889be-034c-43d4-a635-5eee0ac95bb6",
    "metadata": {
     "scrolled": true
@@ -1483,27 +1532,57 @@
      "text": [
       "step magnetization energy\n",
       "0 0.0114 -0.0226\n",
-      "10 0.9828 -2.9164\n",
-      "20 0.9802 -2.905\n",
-      "30 0.9844 -2.9252\n",
-      "40 0.9848 -2.9284\n",
-      "50 0.9838 -2.9226\n",
-      "60 0.9854 -2.929\n",
-      "70 0.987 -2.937\n",
-      "80 0.9856 -2.9312\n",
-      "90 0.9834 -2.9206\n",
-      "100 0.983 -2.9194\n",
-      "110 0.986 -2.932\n",
-      "120 0.9854 -2.931\n",
-      "130 0.9842 -2.9262\n",
-      "140 0.9824 -2.9164\n",
-      "150 0.9854 -2.9294\n",
-      "160 0.9812 -2.9088\n",
-      "170 0.9834 -2.9202\n",
-      "180 0.9848 -2.9264\n",
-      "190 0.984 -2.9224\n",
-      "200 0.9846 -2.9246\n",
-      "210 0.9846 -2.9266\n"
+      "10 0.9804 -2.9092\n",
+      "20 0.978 -2.8956\n",
+      "30 0.9836 -2.9212\n",
+      "40 0.9824 -2.9176\n",
+      "50 0.9834 -2.921\n",
+      "60 0.9852 -2.9288\n",
+      "70 0.987 -2.9366\n",
+      "80 0.9854 -2.929\n",
+      "90 0.9844 -2.9248\n",
+      "100 0.9826 -2.919\n",
+      "110 0.9856 -2.9296\n",
+      "120 0.9824 -2.9176\n",
+      "130 0.983 -2.9218\n",
+      "140 0.9818 -2.9134\n",
+      "150 0.9838 -2.923\n",
+      "160 0.9826 -2.9154\n",
+      "170 0.985 -2.9262\n",
+      "180 0.9824 -2.9144\n",
+      "190 0.9832 -2.9192\n",
+      "200 0.9838 -2.9222\n",
+      "210 0.9868 -2.936\n",
+      "220 0.9862 -2.9338\n",
+      "230 0.9814 -2.9106\n",
+      "240 0.982 -2.914\n",
+      "250 0.9822 -2.9142\n",
+      "260 0.9794 -2.9026\n",
+      "270 0.986 -2.9348\n",
+      "280 0.9816 -2.9116\n",
+      "290 0.9834 -2.9214\n",
+      "300 0.9854 -2.929\n",
+      "310 0.9834 -2.9198\n",
+      "320 0.9872 -2.938\n",
+      "330 0.9824 -2.9168\n",
+      "340 0.9844 -2.9256\n",
+      "350 0.9836 -2.9228\n",
+      "360 0.9848 -2.9292\n",
+      "370 0.9852 -2.9284\n",
+      "380 0.983 -2.9178\n",
+      "390 0.9826 -2.9178\n",
+      "400 0.9856 -2.9324\n",
+      "410 0.9846 -2.9266\n",
+      "420 0.9838 -2.923\n",
+      "430 0.9838 -2.9222\n",
+      "440 0.9838 -2.925\n",
+      "450 0.981 -2.9086\n",
+      "460 0.9856 -2.9304\n",
+      "470 0.9858 -2.9314\n",
+      "480 0.9846 -2.9258\n",
+      "490 0.983 -2.9198\n",
+      "500 0.9882 -2.9434\n",
+      "500 0.9858 -2.9302\n"
      ]
     }
    ],
@@ -1519,6 +1598,16 @@
     "Since the temperature $T < T_{\\mathrm{crit.}}$, the system is in the ferromagnetic phase."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "e2ded424-301f-4743-904f-64af37119b25",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising, stepper, is_converged, simulation"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "38958218-7614-45fc-9360-ba746040e2f1",
@@ -1545,7 +1634,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 45,
    "id": "e20922e8-41e8-4a5c-8c7d-5e62f6527f91",
    "metadata": {},
    "outputs": [],
@@ -1563,12 +1652,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 47,
    "id": "98db23eb-3305-4934-9138-955eb29891a7",
    "metadata": {},
    "outputs": [],
    "source": [
-    "stepper = GlauberStepper(temperature=5.0)"
+    "stepper = GlauberStepper(temperature=5.0, ising=ising)"
    ]
   },
   {
@@ -1581,7 +1670,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 110,
+   "execution_count": 48,
    "id": "346f89ef-4f88-4509-a0a9-d7b38b7e0f40",
    "metadata": {},
    "outputs": [],
@@ -1603,7 +1692,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 111,
+   "execution_count": 49,
    "id": "3d67235c-f72c-4789-a273-667a81c90df9",
    "metadata": {},
    "outputs": [],
@@ -1626,7 +1715,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 50,
    "id": "2c1ed2d8-3394-4e02-861a-6f45f6d79a58",
    "metadata": {
     "scrolled": true
@@ -1699,15 +1788,21 @@
   {
    "cell_type": "markdown",
    "id": "be9a1115-ca45-4694-9dea-6b94fffd2b4f",
-   "metadata": {
-    "jupyter": {
-     "source_hidden": true
-    }
-   },
+   "metadata": {},
    "source": [
     "Note that the for this temperature, variations in the magnetization are higher, and don't converge to within $\\delta = 0.001$.  However, it is clear that $M \\approx 0.48 < 1$."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "67de5ce1-de2c-42f7-aea6-502a35298591",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising, stepper, is_converged, simulation"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a7f7f7c8-4c98-471a-9207-ce0b7f05426d",
@@ -1750,7 +1845,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 53,
    "id": "af5d8dac-6735-4b78-ac81-dd723064757b",
    "metadata": {},
    "outputs": [],
@@ -1768,7 +1863,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 114,
+   "execution_count": 54,
    "id": "9428a125-4892-43c3-bd53-c05f4d46980e",
    "metadata": {},
    "outputs": [],
@@ -1786,7 +1881,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 55,
    "id": "fe7b79a1-152d-48e2-8991-072f54b9674f",
    "metadata": {},
    "outputs": [],
@@ -1808,7 +1903,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
+   "execution_count": 56,
    "id": "30d1b553-35cc-4ac3-aa56-f95a8e174296",
    "metadata": {},
    "outputs": [],
@@ -1831,7 +1926,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 117,
+   "execution_count": 57,
    "id": "efaaf211-451d-41fd-8639-0e6a985464f4",
    "metadata": {
     "scrolled": true
@@ -1911,6 +2006,16 @@
     "Although the failure to converge seems to be a drawback at first glance, it will also help to escape local minima, so for large spin systems, the accuracy should be better when compared to analytic results."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "f4484bb4-cef0-4ccb-bbae-873bdf22299d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising, stepper, is_converged, simulation"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "de8c57ba-4efb-4c4f-b247-2b1d1c45616a",
@@ -1937,7 +2042,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 118,
+   "execution_count": 59,
    "id": "f6e66add-ce3c-4fcf-9d3e-ad92a5ea4167",
    "metadata": {},
    "outputs": [],
@@ -1955,7 +2060,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
+   "execution_count": 60,
    "id": "93e0662e-e212-477d-a89a-ab6077f4facf",
    "metadata": {},
    "outputs": [],
@@ -1973,7 +2078,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
+   "execution_count": 61,
    "id": "89e28e3e-13b3-44db-a15e-70e241fa2bd0",
    "metadata": {},
    "outputs": [],
@@ -1995,7 +2100,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 121,
+   "execution_count": 62,
    "id": "f115d837-8a23-48dc-a3e3-7d27a805f3b5",
    "metadata": {},
    "outputs": [],
@@ -2018,7 +2123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 122,
+   "execution_count": 63,
    "id": "e9761af8-0618-4310-98c7-a76d5f8e5e95",
    "metadata": {
     "scrolled": true
@@ -2095,6 +2200,24 @@
    "source": [
     "As for the ferromagnetic phase, the variation is higher for the Metropolis-Hastings dynamics than for the Glauber dynamics."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "0ead386d-faa0-4a22-b40a-21990664eebe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising, stepper, is_converged, simulation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "323782dd-e9d0-48d1-a0b4-8ba778e1e3ad",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -2113,7 +2236,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,

From 29e856862bba1189a7b311dc541c50336da9f84d Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Thu, 31 Jul 2025 17:15:16 +0200
Subject: [PATCH 05/14] Add seaborn package

---
 environment.yml                           | 1 +
 scientific_python_linux64_conda_specs.txt | 4 ++++
 2 files changed, 5 insertions(+)

diff --git a/environment.yml b/environment.yml
index 47e91df..47dc742 100644
--- a/environment.yml
+++ b/environment.yml
@@ -20,4 +20,5 @@ dependencies:
   - xarray
   - networkx
   - nbconvert
+  - seaborn
 prefix: /home/gjb/mambaforge/envs/scientific_python
diff --git a/scientific_python_linux64_conda_specs.txt b/scientific_python_linux64_conda_specs.txt
index b8605b6..decf487 100644
--- a/scientific_python_linux64_conda_specs.txt
+++ b/scientific_python_linux64_conda_specs.txt
@@ -289,6 +289,7 @@ https://conda.anaconda.org/conda-forge/noarch/matplotlib-inline-0.1.7-pyhd8ed1ab
 https://conda.anaconda.org/conda-forge/noarch/mistune-3.1.3-pyh29332c3_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/numexpr-2.10.2-py313h5f97788_100.conda
 https://conda.anaconda.org/conda-forge/noarch/overrides-7.7.0-pyhd8ed1ab_1.conda
+https://conda.anaconda.org/conda-forge/noarch/patsy-1.0.1-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/noarch/pexpect-4.9.0-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/noarch/prompt-toolkit-3.0.51-pyha770c72_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/pulseaudio-client-17.0-hac146a9_1.conda
@@ -346,6 +347,8 @@ https://conda.anaconda.org/conda-forge/linux-64/pango-1.56.4-hadf4263_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/qt6-main-6.9.1-h6ac528c_2.conda
 https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.25.2-py313ha87cce1_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/sdl2-2.32.54-h3f2d84a_0.conda
+https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.2-pyhd8ed1ab_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.5-py313ha014f3b_0.conda
 https://conda.anaconda.org/conda-forge/noarch/urllib3-2.5.0-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/xarray-2025.7.1-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/httpx-0.28.1-pyhd8ed1ab_0.conda
@@ -354,6 +357,7 @@ https://conda.anaconda.org/conda-forge/linux-64/librsvg-2.58.4-he92a37e_3.conda
 https://conda.anaconda.org/conda-forge/noarch/nbformat-5.10.4-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/pyside6-6.9.1-py313h7dabd7a_0.conda
 https://conda.anaconda.org/conda-forge/noarch/requests-2.32.4-pyhd8ed1ab_0.conda
+https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.2-hd8ed1ab_3.conda
 https://conda.anaconda.org/conda-forge/linux-64/ffmpeg-7.1.1-gpl_h0cf71c1_707.conda
 https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.12.0-pyh29332c3_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/matplotlib-3.10.3-py313h78bf25f_0.conda

From 2c1a2db42d76aa210cfde35df2476271ebee5320 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Thu, 31 Jul 2025 17:32:06 +0200
Subject: [PATCH 06/14] Update for newer versions of numpy and Python

Benchmark results depend on the versions of the software tested.
---
 .../numpy/to_numpy_or_not_to_numpy.ipynb      | 89 +++++++++++++++----
 1 file changed, 70 insertions(+), 19 deletions(-)

diff --git a/source-code/numpy/to_numpy_or_not_to_numpy.ipynb b/source-code/numpy/to_numpy_or_not_to_numpy.ipynb
index 90f3d05..d280124 100644
--- a/source-code/numpy/to_numpy_or_not_to_numpy.ipynb
+++ b/source-code/numpy/to_numpy_or_not_to_numpy.ipynb
@@ -12,7 +12,9 @@
    "cell_type": "code",
    "execution_count": 1,
    "id": "25528046-848b-44d4-9df3-eb66af4d6e4a",
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
     "import functools\n",
@@ -165,7 +167,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -261,7 +263,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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ZgxA5r3LFbz8EdjzHzXDe5vjzpnWNGZcljHJgbcsaVjJUSVnD7pfY1j1IWhtCrwM/UqnfjXA57TB7Yzamo1EAjb/4/SSJ03iOq9M+y3P8eWJeY8ZlAaMYUFtiN4wrrAw6KWtQs4GtJDuotGuSom3yPinwMqmZnqnG4qy0A5l5PUktZNh04zmuznvW8LwwrzHj8gC/Nm0/5fhJdxZEZxANYtSbvcO262na7P3sSXmZvbzK9IuPilGe9biM57ganrc5/jwwrzHjGgBGxcxsytARID/1qcxTg+6t2NZhSqOrW2VGGeXG9KhhEJOUl6lwkLHwYlKmfh2VQ4hfXFXPxnNcDU9jjj/rzGvMuDQgEyWbyaUjBjb/xQlts+D8bM6r2jHqiWnTV4NsENsSMNNGvQk3v//91i/DWUjqJq1Ct6eiGovxHDfDR22OP8vMa8y4PEBcBCYp1eS5Y5L+VBvnNqYUWyltlBK9bRq/pi/btvjZO1LhovtPRFVF5G0Jgi2R9QMmrUdVnl8TpVzmeI7bp/mozPFnFcaMSwG6BWaSprwWy6BSJYE84Uz5RrGQ/MIw5oxh9kZGIRUSUfU7hn6ZwrBgkriHgfEct4PxHH92YMy4JHgWB0pn7tGBTdpRl2eT91nsW7/glxiOss0i4TmP/Tqe488GeO3DPgswZlxPEAaVAP1KnoPU48dEM4p6vdKOsqxRluF3EQ+LG5l3nhcYz3H7tOdljj8NGDMuAYY1TXill/cBBjH9nJU0JOLmV5odxBzm1RfDSMuDOFTY7LkMCrZEUjdn/PTFMIxuPMcfTy/j9FGd488aMws9bQSeFaBJNspF4lWPbvPdhIPtgrNZaH72FGzKsPkt42lTt1+8/Own2G6ai+A1RiYnBtt0qv6zmZ9e78dz/Nmc437B7xz32986J45nRfsfMy48viHt5Xkzqvr8vhtVHXIa08SWPc5M/WLzexBcbQiT+G3KMyjhtpFc5fdyXToiqiKAKuI/CuFqPMcfhycxx004+BFMBoFByvQSSp42jBmXAmwJz3kBWyIzigWgW6Am6dWPpuG1sPyUKxKUQCCgzGfaB/FiDCqtxKu/R0XgxnNc/c5v272Ykfjfq/5R1f2k8j9N+MjvcdlO6FFLGfJehFz+oPsNg+QbNK8KiBDrPpRGxsHPONia9wYxA6ree0ngqvbp2u5Vv+1+w6g2/sdzfDjQjYWqX0fJJEYpvIhlDpLvacBHmnF5Sdty2lGbUkymLb91DSq1mRiKCkwOBDbEWlWOSeL3Igp+TFIy8VIxwWGdCVQMTH5n6hvb8bNluiYYz3E1+GVuNmMxqJAyaJ0q8BL6/PTN02ZevhnXt771LfyP/+P/iPn5eTiOg//v//v/+t67ros/+IM/wPz8POLxOH7mZ34G169f70vTbDbxm7/5m5icnEQymcQv/uIvYmNjY6iGjBr8TrRBCJ6unicBgywax3EQCAR4IQYCgb7/RKRMfeE18eUyVMROx4D8SIxe5auIuhfomLGOcOr6cNA5YdJuVDCe42rwI9Da1K+bm2fRL6Mei0HWwZMA34yrWq3i4x//OP74j/9Y+f5f/It/gX/1r/4V/viP/xhvv/02Zmdn8fnPfx4nJyec5q233sKf/dmf4Stf+Qq+853voFKp4Bd+4RfQ7XYHb4lPGGQA/Ej3w9RzFjDMBDRpEXId8nt50dqY8byINzEXHXMw4aYqR1W+iKMtMVBpiiomrOojuR02jEzGz1YTtWmLn3fnYY7bgleZqrk+ak3WBIOM35Msb1TguEPoq47j4M/+7M/wS7/0SwBOB21+fh5vvfUWfu/3fg/AqXY1MzODP/zDP8Sv//qvo1QqYWpqCn/6p3+KX/mVXwEAbG1tYWlpCX/+53+On//5n/est1wuI5vNDoo24y6DaaNVl0eV3ya9Hxv1MBvosiOBbbu9TCtnubEr9qMX0fZqz5PcgNaNv2n8BsFVZ+K0mSPjOX42c8LULzb1DYPfqNujM9d7rcVBoVQqIZPJ+Moz0j2uhw8fYmdnB1/4whf4WTQaxec+9zl897vfBQC8++67aLfbfWnm5+fx6quvchoZms0myuVy32dQMEk/JgncZmL4kbBszTQmpmICP1K4jLdoujLh79c0pUqr0mp02ohuL0mFm6pOVV1eWpXKLKlLoxt/0/jJxMrG5CmPkfhfV6f4/KM8x23L1tWnGxtTv5gIvtgGW+FBVfewzEMuT/4vzlOv9E8CRsq4dnZ2AAAzMzN9z2dmZvjdzs4OIpEI8vm8No0MX/rSl5DNZvmztLQ0SrT7YNSTwG/dNs8GLUuXTv74ZUIqwqMjUCoTH32rTF8iMdfVYWJEJs1NfG7D1OV0fgiNF0OSy/drphT/ix9dno/SHB8VqPrUJMjYljcow5LL8oJRjPnTYFIqOBOvQtXg+lGVZfj93/99lEol/qyvr48ML5t0tvC0iIHf+mXCJktUNhqPqhz5na5esSzdnoAunwknuSzdnoeOSdiCrZlMp0Wq0um0SS+tV0yvGleV84dXuSZ4Xub4WdShmmumeWYLtpr2sOA1X/2Czfw+Kxgp45qdnQWAxzSnvb091sJmZ2fRarVwdHSkTSNDNBpFJpPp+4wCvBiZ38G0Yc7DlE95Bp3gKgKnM2t4mWFMGpX43sRYdGV6aRs6s4yuLSamYfNeV79XGpPJSNYqbZig3JemfpI1WJuxt4FnfY4PAraMxzTXRkE7/DCWYRnNKPI9Te1rpIzr4sWLmJ2dxde//nV+1mq18M1vfhOf/exnAQBvvPEGwuFwX5rt7W18+OGHnOYswKaTTYRGhGEYh1+cVGXYLCzdO5OZSCZ0OgKi045VC1uuz4bYmpiaCRf5t6l9XmNoW5bXM7E+uX/lPCripOsP2cyk60/6tmFioyBET3OOA95r09RPur40lSn2p1zmqJivar2NWujweudnvTwJ8B3yqVKp4N69e/z/4cOH+MEPfoBCoYDl5WW89dZb+OIXv4grV67gypUr+OIXv4hEIoFf/dVfBQBks1n82q/9Gn77t38bExMTKBQK+J3f+R289tpr+Lmf+7nRtUyApyEZ6AjqWddF4LWQVMTThrmpyvZ6pyO8qrplUBERneQr4m3LWHV1eaWV+0pHbE2mVxWYGJUKTP1mwlvG2TRH/QoNZwGqflRpPV7PbIU71XO/DOSs6Y6uz/2MhW1anbVALmOUDNsEvhnXO++8g7/7d/8u//+t3/otAMA/+Af/AF/+8pfxu7/7u6jX6/iN3/gNHB0d4dOf/jS+9rWvIZ1Oc54/+qM/QigUwi//8i+jXq/jZ3/2Z/HlL38ZwWBwBE16HEa9wGzKsl0sOjxNz7zemQi7H/z9TEAVwzD1u0lStf1v034VDn6JjRfRNI2ZSYBQlWOj4drMYZGh6vDQpbfVYp+VOe73mZ96VGV5jYcNvfFDh2xojGmsTXj5mVd+haqzhKHOcT0t8HOO62l06tMCE1H2IkZ++mkQ5q+rx0bj8tsmv3lN+WXcbBe3TR+pJFe5Pi8w9asXnrp8XjiYzJtPGgbps1HWfV7py7Bt8zMvnvo5rmcNnoSq/iyUSQzLS5Owse/LuKjs/n6kWFVdKtzlenT4yHl1xF+uT2yLKr1NflUb5HJVuHm1wy/IOHrh7lWnqjyViVZOI38GwX9Y8Fu3DmxxkvtBN/6jqs9PnlH369PM7wXnmnENAiZiY0OIdWltJ5XfAfcyD8hpdXZ6FbESicIgzMrLnKBK69eM52UC88LVlN/WfKRrp5eJTWY6Xhqzqg5VubbChqnPbftVbq/tPLSBs9bmBhHGdGvHT11iOX7aqBNGzkrrtMHtaWnc55ZxDTqIpgVqO9lUk3nUk8pxvCNcyAxUNGOp3nuVY6MV6fKIz+X6ZHxspFqTpGurWXoxU11+L6HElkh59ZFJC9aNiVifCWedRiiX6UcAo7moOzvmF85aan+SZj4bxq8Drzl5Vu0YVgg5y/49t4yLQEccvPKYwNb+fxagIgY6hqLSBkQtwq+ErPvWpbVl4CotRaWJiOMoa4l+NBITqPpLZ5rTlasaG106lUBk269eGrFKABDfyYxN7muVhG+jnanaNwgT87tmn4b070egsi1DhqdJbwYBG8F2WDiXNyDrTDd+8tuYibzqNoFcvq1ZSoWf6tsP4aF3fvC3yeu3D/0wFtm0ZmqXaj7YtldHqIeRlG3rMZWrGmO5TTaChq5+Lwal6lcdXnJekybohYMMOhProOvXpi4TjmdJM0ad1wTD9J9K+Bw1nDvG5TWBz2JCq+rzqsfPhFcRHlWbVHV7MStbJi9L7OJ/1QSViYkXI1UxYpUGacov42YiaMMQIBEvHQOR61DhYSpbzGNiSLp+042PPI463OQ65Pr85DFBIBB4TBNUtVnX16p5aVOvqg4v8EqnKu8s6c0wwqaqLFtBxKtNqvk6auZ17hiXCF4SkmkAbCU4v+YTXR6bcrwIvZjHRDy9CKsJP129KiZiIqomPHXEUdcvNv/l5zbpTcTST1m288N2Xtj2q65OL0HGNBds14tNO0xtsMHda574FR51eW3Hxc/6HQQGZQh+rDmqZ36EOpv3o4BzzbhG2cGDLljbsnRMRUU45TJ0jGgQpuqFn8ycVJPbD5EZBD8RvKRBU5+IjEklvZr60ISHWJauTlVer3mhyy/jrfqvymvqK502bUPsbdPK5av6Xkwrw1kSUC+hbpCyhyXog66VJ8FInjScK+cM3WJ9nkBmWuK3ClTESCzLLxARtyEaKgKsA1vir/sv4qMzWYp4qfpR99vUzyqp1qTNiDioylCVZyM5y+3yQzxtmJAKJ50wpSpb1k5NZevap3pm017bNS7PnUHAq8+HKf95o1Ui6Pp2lOZMEc4N45IXJf22kfp0/23fDQM6gmE70CYJWq5H1wYd4ZfL1+Es5vXbTya8TMRMlU7G26sdVL/pPb3zEghkhm9qi06zsZ2Pqnaq8NE9MzFomzki59P9lzVPXRu8wKu9tkxyEGaveycLdqMg0GfJFActw0uAJfCyGMi/h4Vzw7hU4FdC8yJeXmUMMrF0hFYFg046r3c2C0YmasMweRWj9MJDp6k4jvrckA5Xv4RZR5CGFTjEfKrfXiAKKdQHqr6U08llyGZSW2GB8utwH3R92GjtqvaKaWyJ7aAWAi8C7aceP2lGQfgHnZ9+GP6T0BzP3R6XTQeLJg0TmNKoFqpN3ap0w+BhAhXxMtUppvOSlsU88jvZfOQHLxUuYj4vQq8yVfkVSOS8shnMtg1eacRybUGsX9X3fmBQQmirperyes09W/Aqx6u8UWhHNu20pUnDgEnAGqWmo6rXtNbOqv5zoXENQ9SHSaMi0DYqtfzfS1pXLQCThmBjvlCZpXQT0KSxmBanaVF7TWgZF1nKtmEWcp0qnGyIv0rQkcuTx1FmWoR/MBjkdgQCAWVeEy42oMLFNBb0rfotppHr0JWle3ZWc9xPe3XljRq8+meYOlXl6NpsO05e7waxUsnvR8nEnnvG5UWIdGBrTrApd1BiQ5NNRWR1hNdUj4pgek04WybiJdHpJExVP4vt9upX3YK0FRBkvP0wXjm/zjRmElpEZhsMBnHx4kWEQiEtE/YaCxuhRG6fiaDrNDfdmOsYuNwPXszvrOa4V3u9BDa/4JcBjYJJDivc2AqMtnkAvaA4SFk28NwzLhlsO8WLUNmkH1Yi1tWnIzAq8MrvxSBkXGQiMIzk7WUuMS0SmfB49YftuNlI9CoYxHQptiEQCCASiSAejyOZTCIcDivbJ37bMCU/UrypL1VzUjV3bOalPH5Pa46r+tK2TlvwK6jKv89C23saYDsvRgXnbo/LLww7kQeV2GzzqDQGL4lLZcaywdfEDGyIqFf5OuIvl6/Tls6ifttyZfxkTVU1LjLhvHz5MqampuC6LgqFAt555x00m83HcFThq+sLG0lY1p5MWpOpDl17/Zh9dTjq6tHlt53junF7WjAovVFZNs4SRr2OZNAJNLZw7jQuE/hRZ+V0g9p45bQ6bcumfNWE0Zk+bJmTDb5i2SrTn6xh6frZRjqXiZeuveK37TjqmIDcrkG0N1WbxN+BQACrq6u4f/8+crkc7t69q2yjjoGbmIkKVIRdJHwmxmBrEvVr/nsW5rg8z2zAxvQ5SjBZNkx4D4LTIHTNa3z81jUIPPeMS7eIVDCItOq1SGxBtWC8pEr5nUpK9kvQTGBjatItIFnKVRE/+ZnKpdmEg0qSVjE7G5BxUZUnvzeZPnX5A4EAYrEYFhYW4LouAoEA6vU6qtVqX3oV8/YqW8bDixmZtEIaCzGvaSx0a8IWP12+JzHHRWFCbLcJN3EOeLVlUNxE/AYBXb5RCN4mAcm2L4aloSI894zLREh14EdCH2Vn6+ofRJoTF5FOQvPD1CmPV3odrjrmJILoTaerS0c8TZK4CQddO2XmasJFfqcjBCqm5TgOpqamEAqFEIvFEI1GUavVkEql8Hf/7t9FOBw23qumGkMTgTK1Rdcesc915+HENsv9bNOXz/Ic96OF2QpZtulM+UYFprb57bdB6x+kThM894xrELAZhFGptSZNS1z4tpKpipCrCIdYju69CWfbRamSRE2mLRNzMTFEG2ndr2TnpR3oNCyTVib/dl0Xe3t7ODw8RDQaxfT0NKLRKK5cuYIHDx7g2rVrmJ6efoxhyPXKY+JHUjbNDRN4EXNTnzxvc1zV9zZljDLd04BBtNdB5qGqzmHg3DKuYTtnFJ1rWlReexO65zpCbpLWxfc6qVenvdjgJpcvEgA5qoWpHX4Jm6oPvBbgMOZQsQxZAzEx6ng8jqmpKQSDQZRKJSwtLSGZTGJ6ehqHh4fodDoIh8NIp9NYXFx8zOOQ6jSNOb1X9a/fuSwTcdsyzsMcF8t6lhnOqMGrrTpmZTvmo4Zzy7hEMNl4nxToJHQbvAZNo5tgqsmm05TkNDoJTUXEVWn9MkRTOlM7dOBXMlflNRF1VfuTySSuXLmCcDiMa9euoVgs4ujoCJ1OBxcuXEC328XLL7+Ma9euodvtIhQKWRFt8bkfDUz3TGbIcvle8+k8zfFhGP+ToDWjrmOYNaH7f5b98JFgXINKTyqGZytFigtAZ++3MeF4MQwxjQlMBGhQ7UZ+r+tnE7MS6/far5A1WC9irgNbHL3yqgiczEgcx8HBwQG++93votFo4O2330axWMT09DR2dnawvb2NeDyOer2OS5cuodPpoN1uW2k6qrFR9aWX4KBrg1yH3D7ZPCzjdh7m+CAMbBjhyJbe+BEAZYbuRwAw1ecFZ6mxnrtzXDYTXE6ny6N6b0MsVVK4qgy5Xhup0AsnGzOICmcdLl7liGGL5DaIIJevaqet9qDqH1XfqZiiSUL0MxYmoiYSeXo+PT2NSCSC/f19hEIh3LhxA8FgEMViEQAQDAbx/e9/H61WS9lHMvFRtUMlDAxLPLzWiApXU77naY7L9diOhRduXm236SNdXq/nfvvMBIPiOQo4d4zLZhKeZUfbTB7dM9OikheRn3pswISLiI/qvR9p1g9R9TNOsiZAfWciTiairJOa5XRyvMFsNoter4dms4lut8vpt7e3EQwGEQwGEQ6HMTs7i16vh2AwiO3tbRwfH+PNN99EqVTSakjDzgEvzcsEun611eZU/5+XOW4aDxtcBqU3o1wfg8CoyvcjaNjCuWBcug7WEUndBB5EehLz6aRDnQagS6eS8LzaZwuDlCXjpiNc9F6Htyypim1VwTAESsewVHjpCJgqr/iMmBCZX4LBIBYXF9FqtbC3t4darcZpu90ulxsMBnF8fIzd3V1mcL1eD9vb23y+y9QuGU/67ZVmVHNFVZZK23te57g8t20Yngm88nul1+F31lqOLZ6DtGdYOBeMy8/iGqYTvUwNg2opusVrYgKD4m1LpEUgrUIEnUYiS6cqadXLBGPSMsRydQtc1U4V7qb8qj4T0wcCAUSjUUxNTaFcLmN6ehrNZhNHR0eo1+vodDoIBAKP9W8wGESz2USpVEK73WaG1uv1cPfuXfR6PWV/2fSJ+E7XJ/J8smEu4nPTnLZ596zNcZ3WJ5ajm5d+GJipn23Ats+fRTgLHD8SzhmAfu9FBJv3VJb4X/5teibjJKYzleFFuHTl+zFnqLQnsX558asWvC6N6plNP+oIjo5Qm4QYr/GS8ZU/ct52u43j42PE43EUCgXk83lEIhG8/PLLfLA4EAggHo8jFoshmUzi1VdfRafTQbfbfawdItP02x+m/td9q+aGV796CQQ6Yv4sz3FdG3R9Kucztc1La/PS1rzS+GEINnUNW47q3Vkw1o8M47JZePJ73QDpJjstDJPUK0v0KmKlyiuWK096XZ2mhSSnMRFsr3K8TDC69vjNYwsmIqMqU9Unpht2xT6j81fkwj47O8tnthzn1CyYyWRw6dIlZDIZFAoFJJNJLkcVaskLfzmfVx4TM5LHUdVH8nPTXFMxzmdtjuvql/PaCp6i1uY1Ljb4+0kzzLoYFPww6LOCc2EqJNCp717PbCQ2XRrTJPUyN8nPbfGn53IZXiYk08I14WhKa0pv02e29XvlMT33wkOnpajSy+NVr9fR7Xaxt7eHaDSK7e1tlMtldDodvjQyEAggFAohlUrh/fffR7PZRDAYRDabxcLCAh4+fIijo6O+cmWmIgpGcj+ZBCwvQnxWYyHW/bTnuB/tzRY3XXkq2jKsmdAEg9KtpwmjwOlcaVy2i8xWIvcjOZlAlhZVEqw4mCrJ0ws/0zOviUKS4qBgK5V7lTFMWpmpyO90eWXtypZIUZs7nQ52d3dxcnKCZrOJ4+Nj1Ot1FAoFvjCy0Whgd3cXvV4P7XYbvV4PoVAIhUIBABAOh9njkJidWKeXZqUj1Kr0JvBihLYaGZUjx6R8WnPcS2DTpVEJEF71ysKQqtwnyUgGrctLE9fV4yftMHCuNK4nATotSrVwvBaYLCGqJEZVel2dfiRDuRxxkepMSiapWE5jK2GapGS/AoVMaHTt9osj5dFpAO12G6VSCdVqFY7jIBqNYnZ2Fq7rolKpoNfrodvtotFowHVdzMzMoNPpoFaroVgsot1uIxgMIhaLIRQK4fDwkMuWcTOZy2wYgWkcTVqWKu0wY/Qk5rgKb9u0YjobxqrSjuW1LeNii7Oqb8T/w2iUNun8Cj9PQst77jUuv5L9sKBiWvSt0zpEwidPCD+mHBVjJEZjIyXLUqAfSVG3AGVGYKN5eeFrM/HFPlWZpGTcTW0X86rq0f2mD2kWrnt6bcnJyQlarRabCCcmJvDCCy/gzTffRKFQQDgcxvz8POelq0+Wl5cxNTWFeDzeF0mftDAV3ip8qB+92iCmkwmi6rdu7qvKM807Fe46/PzOcR3oBCRdGToria4uuX0qYWIQZmBiWnLdtmX5qVOuy09+EwxLt597jUs3sGddp06KNEmuOqIhl6MyUeikaq82iyZAVf0m6VfOo5P4dG3UjYmKeZvaYyvx6hjxsKBro+M4SCQSCIVCHPEiFAphcnIS7XYb+XwerVYLmUwGFy5cwLvvvot2u41AIIDd3V2022127KjVatjb20O73WbTIXkk0kHl4+NjxsGkeenaIBNi1ZwdRtpWaUuqcmQNX07jd46rhEJVO1XtU9WtYz66ukxMRYe/rYCmK+NJ0LpB1pBpLsllD8O8nnuNi8CLKeie+Xkvp9URD5t6ZMJBeeVv3aLzqkOnYdjkU+Hr1R7V/0EXJT2zwVunbQ27sL3KIU0oEokgFAohFAohGAzyPla73UalUkEikcDBwQEODg7wiU98AsvLy8hkMggEAlhaWuJzXY7joNVqodVqodFoIBQKIZvNYnJyEtlslhmeF246zcJETE3zS/z20p7FvCqiJeKma4ufOe6ltcvtVGkQujbJ69Kk+ZiYtEnoGYVmMiqL06jKGVTo8V2P+6RtbSOAcrmMbDYL4Gw6x0tSEL9tJQyvumwkz0Hwe5bBtl0mIiiXMyoNyyT9h0IhxONxZLNZ5PN51Go1TExM4P79+wDAJsJ0Oo3l5WX2OIxGo3CcUxf5TqeDXq+HVquFk5MTdDodJBIJHB0doVwuIxAI4JVXXkEmk8H29jbu3LnDUTZUTEXVZ/RtywyGnb+6MTJpJF5MzgZHk0ZkYjSDtnUYkNf7s05+bawsfvLL7wCgVCohk8n4wuu5NxXqwKvDTJ1vKwmZJFvTYlGlMREWL9OJF7MahAF6wagYoxduKvMW8HhwXxVefoiCqQ9V2lwwGMT09DRrTBRJAwCy2SzK5TIikQgKhQLK5TJCoRASiQQymQw6nQ4qlQqSySQ2NjaQSqVQq9WQyWTgOA4ajQYAoFgsotPpoFqtIplMYmlpCffv30en09GatFTajzzPdH06CEG3WUeqMTKtE9VzuUzTmrARJAcRNged87r17ke71JU7DE5eeVVp/NCQUTB6HZwrjctWmhpUS9IxKnkhDjtgXsRHfCf/til7UMLk1wRoi4MXEfPSroiJmSR7W/AixMS0wuEwMpkM4vE4ut0ums0mQqEQVlZWsLKygu9973twnFMPw0gkgpmZGQDA/Pw8EokEHj16xJ6IrnvqfRiLxeC6LhKJBLa3twGcuso3m00sLCzg0aNHODw8ZAYlt09lAlOl8+qbQTVfv+WJ71Vt8SNA+knjpSUCT3aOPyva16gZjRedHWtc/3/w0jzkdKq0fpge5VcNkGpx2JgwVDiJ5di2UQemsr3aPEidNtqlScuh36r6A4EAkskkGo0Ger3eY9qEbhz8gmq8SWtyXRfdbhfdbpfPdL344otIpVIAgEKhgEqlgqtXr2Jrawv1eh2JRILxCQaDfIi5VCoBAKrVKmq1Gnq9Hscu3NjYQKfTsZZuVZqV2N/ye68ydfPVpk/9rEfTnDAJcCbGII+/Tqt7WnPcJGzZmNpGJbiOWjsaVLi2gXPFuAjOwgQmT2ovgihOSnlReEmAqgmpM43JZYj/den9MtZBGLBXm2XcdPiqiAk9I8ZFe0aO46DX6/F5KbE88TsQCKDX6xkJtxczBU5jFdJ+VDAYBAB0Oh3cvn0bjnNq8iNXdzqAXCwWcXJygnq9zngWCgWk02lsb2+j2Wzyc8LRdV0cHx8zc5bxCQQCrJnJDIrKEUF+r2unShgT+9+LycjvTHNONf/l8ryYgc3aeJbmuCxkiXjo8g/LDEbF5ExpTM9GpdWdS8Zl6phBOs7PwPgpz0RcVXWbyjdNcFW9KgJhqsvPQvVawCo8dQvWq5xAIICrV69ib2+PmQFFp5DbRwwmn89zdHYVUdf1na7/0+k0Go0GHMdBrVbD2toaO2gcHh6ydkbnsyqVCiKRCDNZgm63i3A4jFQqhZOTE9Yk5Yjx9Mnlcjg+PkYkEsH8/DwODg54Py0ajWJiYgLFYpHDSdlK6DoCacso5Hcma4Hut5+5qXr2PM1x1X+dQDEM4febdxCmpcunm0ODwrlxh1ep2Crwmhxeeei/F9NRTVDVIjIRSVUoIp35R5a05bJE/GxCHNmYLHR5de2Vn6mYkIyfXK78vFKpYG9vj/OQ2zgxDtLIaF+K/lNQXJugqLp2xuNx/PRP/zSmpqa4PAB8v1av18PJyQl6vR6uXLmCiYkJdLtd1Ot1tFotdpsPBoPMtOLxOCYnJzE1NcVnxOT+cZxTz8apqSmkUik+BwYAiUQCExMTePHFF9k936ttOqHHdk3Jc1L+PQixksNF2eChgmdhjpv+m3D2MxdtwJTXtk/99P1ZwrnRuHQTTicV6NR/+b840fyoziaJU1enSfr0kvJMC860eGV8VHiZ/qvMTiKuNn3mxTh0eYhRHR0dIRqNwnVddpaga0UuX76Me/fuoVwuI51O4/Lly+j1etjZ2cHh4SHvTZGbuY75q/Btt9vY3NxEu93GzMwMewkCp04YtVoNgUAAKysruH//PqLRKKrVKtdF93EVi0W4roupqSn2GJycnMTBwQFc1+V7vYBT7S4ajeLk5AQHBweIRqO4du0aHjx4gFgshm63i0AggKOjI+zt7aFSqSjnncnc5tf8o+obr/Re5jdd36ueqeadqh6b+nW4iuXLdfk1qamEZ1N5sjBgu5b9MDm5Xhttys9cGTWcG8alAy+JySafSrrSDZbtBFDV4ZVOLtNLOpQ1CpFgyellAim3S1ev6bdu8du0WdUHMmGKRqMIBoNwXReZTAbdbhfJZBLtdhuRSATHx8dYX19njz/XdbG7u4t8Ps/pcrkc9vb2UCqVHttDMuFBh4/p+pKZmRk0Gg02G3a7XaTTacTjcRwcHKBWq6FUKsFxTqNtpNNpAKceVcfHx3BdFzs7O5idnUW1WsXJycljd3ZRPZlMBo8ePUIoFEI4HEapVGJ3+1AohEajgePj4z4tUDVGqucqAutFnPyMoQ4PU5007iYrijy/bBmY7t2o5rgMOkuN1zO/2qsqnRddshUgTUzYz5oeBp57U+GoVFeddKGSsmxMDPJ7nTmF6pAnqCqPqa06phWPx/GzP/uziEQij8W9k9NTO0STlBwyyoSXjJ/cd6qPDaiISjAYRCqVQiKRQCQSwezsLOLxOFzXxcTEBKLRKOLxOB/sJQ2s2+2iWq2iXq9zRAqxv0w4Ud2RSASvvPIKstksZmdn8dJLL+Hw8BBbW1uoVCpot9vY2dnB0dERAoEAms0m2u02Op1OX3mZTAaRSASu67Lmt7OzA8dxMD8/zyZPwi0QCGBnZwfr6+vIZDKIRqNIJpPIZrPIZrOIx+PY39/H9vY2O4CYNCsRTIRRHEdxHMR8pjGTwc8c1817ej7I+peJrVjeoHPci2ibmLyqzfJvP8zAa0zk33770IspPgl47jWuUXaWjdrr9Z7SmCay+NxL8rR5p/ovfm7duoWXXnoJOzs7cF0XsVgMGxsbjy1InaRnktL84jzoeMn5iHmsr68jEolgf38fFy9eRK1Ww9LSEu7cuYNkMolQKIRYLIZisciMe3p6Gjdu3EC5XEYsFkM2m0WtVutjYjocHMdBp9PBvXv3EI/HsbGxgXw+z16F5BrvOA7HH6zVamg2mwBOmVUsFkOpVGJPQ9oTI6ZITiOTk5OoVqsol8twXRfJZBLNZhPNZhOf+9zncOfOHTiOg3Q6jWAwiPX1dXZKITOkTsgymZ/k92Kf+CFyZzVfVCY10xqU26Ran/I60LV/GA1DpwWqypTrFd/7qcsGRkFD/fbBsArHc8+4dDCIBCBPGLGDdeYFeYGI70wLdxjcVM9EfMTntLlPIYgqlQrq9TprH36kMNV7Lw1lWFAxTcc53dv60Y9+BADI5/MIh8NoNBqIRCJYXFzEw4cP0Wq10O12UavVEI1GcXR0xC7p5LTgui6q1epjZkKdQELj2mq1MDc3h1KphImJCXYQEb0Am80mDg4OOH8gEEC5XEYqleqr13V/7LIeDofR7XZx//591rSSySRc18Xi4iI2NjbQ7XbxjW98A8lkEqlUiuMbOo6DeDyOcDiMnZ0dboeqP1WMSEfodWMi/5bLGcUc1733WmOq8lTM2UZwNJU/DIMwCYQm3LyI/iDr7klpTDbzywbOLePyKwHo8usmlCzB6epWSVCmxa7DySRdiuXKaWq1GoLBIA4PDxGLxdBoNDhEkWhuMS1glUnmLCa5TV/R/263i0qlgvn5edTrdb4TKxKJ4Fvf+hZHZyfzHcUGJO2G2tNsNvv+exE0EVfSmG7fvo12u/3YfCCNR7z2xHVPz2TVajX+L57X2tvb68MhEAjwvtbU1BQODg7QbrcRCoWQz+eRTqdRKpWQTqfR6XRQr9eNB5XlvjbNNZPmIacX3+nq9jPHTflNZdiUo2qLV72qNF6E18TAdevZloHpNGlTPlN6v2NhAhsrzbBwbhmXl0TmVyocZpKJv01EQleuTV0mZtZsNpm4EyEFTj3UyuUyLly4gN3dXVQqlb78gUAA6XS6z1FAxcRUMAhhUvWVKU8wGMRP/uRPYn19Haurq2g2m6jVaqxZ0t6SuI8k4yO2x68ETweMO50O9ykJBGIYKrFMivpOHoeURmRe9Ixge3ubzY4TExOIxWLY39/H1tYWM7disYharYZUKoVsNsvMVAUmE5pqHGR8xDL8zAU/c9xL4zeltWGcfkDHELwYhc1ct7HO6OoQ2+2nbr/v/fabimmNmoE9984ZgH5RAWY1X5d/kA4WCY6KEIhSt6pOU5kq3LwmueOcOjBMTk6yp1k2m0UymcTMzAwSiQSmp6eRTCYxPT2NixcvIpvN8pmnhYUFJJNJpNNp/Hf/3X/XV6+J4cttNy0uFcjlq5iZWPZf/dVf4fr166hWq6hUKgiHw8jlcgiFQqhUKpibm0MikcDrr7+OXC7HZjeZAavaJ39M7ZVNfqp2RSIRJBIJPrtFWlMkEuGyRCZG2mG73cbh4SFOTk4QCAQwNzeHdDqNVqvFHpPkVXlycoKNjQ2+KkXE09SnNuOi+q8j4uK3CWRTpYirV9mmsTGtRy98dDjJhFgEHROXy9LNOx0uch3ib685afPMZowGZThegsowcC40Lr/Shim/PDFN2ppKcpUlDJ2k6cVYTRqVXI/o+UdpI5EIR2oIBoPI5XJYXl5mSX96epqjOWxubqLZbKLT6TDj6na7yOfzaDab+NGPfmTsl2EkPzmtjiGrFnG328Xh4SHC4TCmp6cRCARQr9dx584d3rNqt9tIJpPo9XqIRCJ8rknG2WYBq9qkk7SDwSCi0SharRa3K5PJYHp6GrVaDaFQCJFIBJ/61Kfwwx/+EOvr61yeyPxE4tJqtfjaE/JeJLf8tbU1jnkoa5Y2bZTfm+a4qT/E/6OY47r1ZcpnwtmP1m9qg0lLonrkdOJvFRM0aXMm3GwEb9tnunbYplflHzXTAs6JxgX4k/JU+WQwSTS6RWGSiHT1mOrX4eHFCB3n9IxTNptFOp3G7OwsOp0OGo0GcrkcVlZWEI1Gkc/nkc/nUa/X2XU6Foshn8+jUChgYWEB6XQaruv2nQmS6xLdtm3apmqrrp3ywpdxIEK1srKCWCyGdruNRqPBe1rkiHF4eIh6va7UiLwIrCqtrp30O5lMYmJiou/4QaPRwMnJCWq1GpLJJBKJBK5fv45arYZcLveYqVD8kNNHq9VCuVzmILztdptNuaFQCNPT055tUkn9JoKtSqvKM+gcVz1Xla0j1Cq8ZGYwKrpgwl+3/uXnOmHHJAyq2i4z97MAv2Otyq/K53c8ZDg3jMsP8VHlUz2z7Vx5MEyTSScd2S56G+kKOHXKKBaL2N7eRqPRwLVr1+C6Lqanp5HJZPhamEajwebDUCjUt0dD5qZUKoV0Os1MSocPvRcZmq5/dYxI1S45vZwnGAzi7t27KJfL7GxBGufk5CQ7QpTLZbRaLd8mWL9pQqEQLly4wMFvo9EoQqEQnyGbmppCNpvlcE3hcBjLy8vcnzrzUqfTwcHBAY6Pj/sulez1eigUCnwgO5VKYWFhgV30qRy5P1XPdaAjODrNR5VmGOZhqkeFk0rIUjExL0Jqk9ZkmrPVUG3WtYrO0LeXQKUCv4KG+N5rDPwKK37hXJgKTeBHVZUngJ9OVpk26LkKFxu8VBKYLLHppDzXdTluX6VSwa1btzAxMYGZmRk2AZZKJUSjUWYwS0tL2NvbY1Nhr9dDLBbjIK1EGOk6D7kNOjOibqHaSqwysxTTOs6Pwz6Jh3UJl2g0ikwmg1u3bvW5qtsQC525TJVWhG63i7t372JiYgJzc3MoFArY2Njgg9Lb29t45ZVX2AOw0WjgwYMH3O9iX6q+RZwcx0E4HMbMzAwcx0EymUQ8Hsfu7i5fbNlut5UEW6dpDaI56Yj3MITKdq3oNBrV+Oo0N9OcNPWHbq4PKkgPCn7aZFvWoO9VaWQ8TP1qA+eOcak6aNByKL9u8E3SlIow6BaiaQBNBF5H6Ok7FAohl8uh0+nwfguZzYrFIgDwWadwOIzJyUkcHR0hk8lgdnaWCWo2m8Xk5CQODw9xeHjI3ofyYvEiLl4MV8WgaK+IPCJNREQ8i1WtVtFsNhGLxZDL5Yy4mHBWtUvX7yIEAgFkMhkkEgkcHBywS36j0UAoFML6+jpfX1KpVFg7ks2FqnaKbXDdUycO8iBMJpMcQoocOBzHecxEqsJZRUxsiIs8/qb54CWte+GlYhSqtSozKHE9yulVZalw9RLIVG1RCate7VW1wQtMbdLBILRRN36jYHZ+4NwxLpsO8upo3YS10RJ0eUxSoUnKMxFP3Tuxzk6nw1EbKBQRRRPP5XJ8aWG9XucDunQ1CO0PhcNh7O/vI5lMolwuKwmUbsF7CRGOc+rIMDc3xxrR4eEhQqEQxxd87bXXcHR0hEgkgvv37/e5eesWPn1efPFFPHz4UHnNiW4OUGR5+cyXCnexneL/hYUFZDIZjoXYarX4epNYLIZ6vY7Dw0NmqmTGFNugA3lOVSoVrK6uIp/Pc5BfGkNV9AxVWXKfqIirjYYt//ci0qbnqrbq8tnON1M+W0ZhI0jK70y0Q6eNmPpVVY+XRWdYDViHw6iZkg2cO8ZlAyrJSSZCMmPxMnnZLC65Pvm9zaKjdzLBVBEI8kKjqOOimazdbiORSGBzcxOO47A3Wq/XQ6fTwdbWFqetVquYnJzE5ubmY9dkqIiXafHo2lEul7GysoLt7W3EYjHMz88jlUrh4cOH2NnZQavVQqvV4sgStvA3f/M3fPBYxFnXZ8RIX3jhBRSLRZRKpcdiDJraQhdHbm5uskm13W6zZhsKhThkVCAQwLVr15DJZPisnch0TeC6LjvFkGfh/v4+x6SkQL8m06jYbtUzL8nfL5G31d5068APHqo56FW/11o1mQZN+KnKNgkLOlpiW4euvcMwGC96eFaMUgfnknHZdKJJkpM1BpMko2JapvoHGUgZHxXj072nyZvL5VCpVNh9vNlsYm9vD4VCAd1uFwcHB3ylhkw4yeQlx/LzSwjkPhQ/7XYb1WoVH//4x/HgwQPem0un03x4utPp8GFf3XkpqofOOzUaDTQaDdRqNeMYOY7Tp+XRweV8Ps/Xi5jqonbEYjFcvHgRh4eHaLVauH//PqrVKgsOlUoFJycnAE7NoN///vc5XJXY97K5UDUP6ebko6MjpFIpRCIRbGxs9F3TIrbXBkySvpcg5yXx+2ViMtisHR1+ooCnqttLMBX/y+WJ/03l6jRU+bkXvbHBfdSg6gubPGcF58arUAQbqcxLE/BKq5qwuolpA7rJLL6Tib38XHVBJP0OhULsKi46VwQCAXz2s59FLpfjK0LoQ5rK7u4ubt26xbf1ym2X69K907WVInQ0Gg0cHh7izTffxOLiIhYWFuA4DhN9sU/kqOnix3FOrw65ePEiHMdhE5ypHx3HwQsvvIAXXniBQ2O1Wi2cnJz0ubSLn2AwiHQ6zZdTUhSNra0t5HI5XLt2jaNkiJdL0qfdbqNSqeDo6Ijd2+UIGvJ8oO9er4fj42MOyOs4Tl8dlNaP1K0SkEzvbTVD8dsLj0EFO9Xa0/Whnzq8aIlq/avwMz2X+1pkiDrwMsGqhOlBwSavrk+HqdcE51LjksFGIrGRlnSEWHw3jFnFCzeZGZAzA13ZQZqLjA+ZvKgMOohMUv7q6ioymQxKpRK7i6s0LxNxMDEmU38QnnT4ud1uswv73Nwc78nV6/U+pxCxjeTtSI4IADA5OYl2u43XXnsNb7/9NgcU1knPtI9Hd2UtLy9z3EDS9ETGTcIARek4Ojri/qSD0ScnJ9jZ2Xnskkqx70TCriO0MtDzZrOJzc1NdLtdHB8fo1AoPMb45HaatA3duFF5XuOqIr5eRNgkFHqBlxVDtUZl/GyYma2mMey6UNXjRZdMINOuQcFE12xxGDWcW8blR63VTSDVpNNJpTrmZTKt2JYtfgcCAUSjUZaqA4EApqamkE6nMTc3h3fffZevcad8pDlR/uPjY0xOTvJezIcffsh7LyqGRbjpcNcRNrlNYh6ZgdCh3GQyie9973vseReJRLC8vIzV1VVUq9XHmBYxkEwmg0qlglQqxYwmHA7DcRwsLCygXC7j4OCgzwGC6g8Gg/j85z+PmzdvotlsYmFhAfF4HHNzc3z26rXXXsO7777LGhiZA8l0GY1G4TinV5mQOZCYqRwJQ+5PXZ/rgNLRviT9p6C/Ok3LNIY68Et4dOtON8fF9vjVOrzyy/Wp/ov1mNL6md+m+sVn8repfC/GYYOHKZ1XuX7abtNvw4IvU+GXvvQlvPnmm0in05iensYv/dIv4fbt231pXNfFH/zBH2B+fh7xeBw/8zM/g+vXr/elaTab+M3f/E1MTk4imUziF3/xF9kbalQgD9gweVVqua2kp5Lw5edUhy6fWB8FaSVGRbEIy+Uy3nvvPT67JecTiVmlUuGrME5OTlCtVlljEE1yKm1L9V/VF7q8IsOR+7ndbmNvbw/lchlbW1vY399HuVzG9vY2jo+PAeAxk2A4HGYt6bXXXsMLL7zAZsd79+5hd3cXx8fHHKNQdLmncgDgm9/8JhqNBmKxGBzHwcrKCrLZLC5evIhUKsV9S/d7UVxE2rd6+eWX+SwVmexUTEulxfrRtFQfeqdjWqq+9wsqbcIGbIiYTki0xdWEm279ieWb1qhMuP0KFyrcVGtbfK+iE2IZMrNVpdOV43fsBxFqdALEKMEX4/rmN7+Jf/gP/yH+9m//Fl//+tfR6XTwhS98AdVqldP8i3/xL/Cv/tW/wh//8R/j7bffxuzsLD7/+c/zhjQAvPXWW/izP/szfOUrX8F3vvMdVCoV/MIv/IIvbzFbsJ34KkKrG2x5Iusmkw4XnURKH3E/RU5H0v3i4iIuX76MfD7P7u3k/SaXIROAQCCAarWKw8ND476KaWLK7+QoGSLuqr03uc2uexrZotPp8NmzTqfDV3eEw+G+8sRPJBJBoVDgixbp7BeZ0qrVKmKxWB+uIk7BYJCdVOhM1NbWFo6Pj3F8fIxQKIR4PA7HcZDNZnHlyhXk83lMT0+jUCggGAxia2urz1WfGAn9lpmM6pncdzpGJefxej8smOatLq34X15PJrxUTFw3j1X1mAQoOb+4dnXlm9pj0ib8ajW6vGLfqbQvm7GwSTtqxqLDZWTluUNgvL+/j+npaXzzm9/ET//0T8N1XczPz+Ott97C7/3e7wE41a5mZmbwh3/4h/j1X/91lEolTE1N4U//9E/xK7/yKwCAra0tLC0t4c///M/x8z//8571lstlDlk0ig4Rr5fQLQDxva0kqCpHJ3HavguHwygUCuy9VigUsLq6ilKp9JhnoMz8HOc0skIkEuGArGIIJDnCubhIbcxdKqlW1w4ZL2JIZPar1+sATm86TqfT6Ha7KJVKjB/loSj35BIeCARwdHTEGiWZ0hzH4XNNIr6JRAKXLl1CIBDA4eEhAoEA4vE4Wq0WUqkU9vf3OfDw4eEhgsEgMpkMLl26hEKhgHfeeQcHBwc4OTnpEwBUjEqeGyYGYyMMmRiY2Mc6jU7HJEzzX4eLDZgIveq9TfpB6jWVq9KIdVqP1zPVe795VRqrPDfk9yYcvIQGXVleZQ8ChEupVEImk/GVdyivQtrwLxQKAMBnbr7whS9wmmg0is997nP47ne/CwB499130W63+9LMz8/j1Vdf5TQyNJtNlMvlvo8OdItUByotwZRW1BBUWpr4W6VdyBKgrF2p6hP/k2mqWq3i4OAAt2/fZgIt5iHNLJFIIBQKsRaSy+UwNTXF57VM7ZTBJL2qGJH8kTUvlSbW6/VQKpX6zG2hUAjLy8sc6FfU7prNJt9FVa1WcXx8zB59iUSCGZ2ojYqfZrOJhw8fcnSLk5MT1vxoj4qCEycSCWQyGbiuiwcPHqBUKnFsROofmXmIz21Anjsq6Vs3JiqtTQVe2oVfoc1rzanWgwlkLUN8LjNmGyHSD8GVyzQJkyJeXuPk1WcmfOTf8lrT9Zdcj1dfmWihibGqfp81DMy4XNfFb/3Wb+Hv/J2/g1dffRUA+LrwmZmZvrQzMzP8bmdnh8/H6NLI8KUvfQnZbJY/S0tLfXiIYNvhpnaZNAexXHmgdQtU/C+6cdtMIpVZoN1uo1aroVwu8x6OWDcxrTfeeINvz6VAufPz8+zppmuTSlJXMV45j45ZUfBemanG43FEIpE+d3MCsZ5er8f3Tolpxcsbe70eyuUyn/fa399XholSMc1Wq8XnrrrdLprNZl/opGazibt376JSqaBSqSCTyeDk5AT7+/scysmPgCS3T3wmC0Uq7U18Lpd3FpKxDDqhRcesxfemfhLnOaVVCYm6+WkDuj7T4WHKr8PHZl3L69tLExJ/y3ir+kh874d5yelV/8XnOhp41jAw4/pH/+gf4Uc/+hH+/b//94+985JIVGBK8/u///solUr8obuLqK5Rc32dBGUz6CYwLQgxjfwRn4sXUh4dHaHdbvNNvxRFgYj75uYmrl69ivn5eWSzWb6PipjFIHiKDMyGaUWjUUxNTfFZJ4qGvri4iMXFRbzwwgvI5/NaDcBxTvegPv3pT3PA2lgsxm2kKBF0tYfrnl7BsrW1xdHtxfaIzhki8SDzo+js8alPfYqdOsgzs1ar4dGjR1x2JBJh70UqSwe2zE3sY9XcMzGAQbQL27QEOu1LnBdiHpEJiaBjwqa2yExNLkuFl67NXvNc9U5uky3z9GIsclvkclX1qBimPB42ApP8XNdmGXSCrA0NHpZOD8S4fvM3fxP/6T/9J/y3//bfsLi4yM9nZ2cB4DHNaW9vj7Ww2dlZDkWkSyMDRfgWPyKopD8RTItcRywHmZC6soj4yk4BKkKvw4kY0uTkJObm5voioNPFkHSmiBhYMpnEw4cPUa1WOVbe/v4+X7Mh94H4W+UgIkuJYt+qpEBq0/z8PLuYT01NIR6P4+TkBK57esaMItSL/UPf8XgcmUwGDx8+5Ft+VfgQc2m1WohEIko85EPL8ryhg9CO42BnZwcPHz5kJum6bp/zRq/Xw/7+PqamprC8vMxpTKASsrzyqPrVK63uvw4n05oxMRSdgCVrSipmIadVzXkdMzKtW5u2mUC1nk3WERXz1KUz0QebtPStsyKo2iCvVVOdNu1QtUunsXrlGwZ8MS7XdfGP/tE/wv/7//6/+Ku/+itcvHix7/3FixcxOzuLr3/96/ys1Wrhm9/8Jj772c8CAN544w2Ew+G+NNvb2/jwww85zajBppNsO1+WEr0mNHm9ZTIZZipkPqMbik0LLBAIIJFIYHJyEplMBsFgENVqlWPi5fN5pFIp1Ot1JBIJZnAAcHx8jEqlwoyBHB7oHJiK8BC+KpOmatLLBEm1b7WxsYFKpYKJiQlkMhlMTU0hHA7zHpF4JQkx6XQ6jWw2i0wmA8dxsLu7y1qU67rKe78cx8Hk5CQODg768KP3dJSADizLzBI43a8lxr+7u8uHnmXHi2AwiMuXL2NnZwePHj3SmgtN80pFcFTzSGYEo9C25Hxe46rDT5XWCw9bZi0LJoMwZirHBidV+TZz3yRUmAQAXVqvd3K/yKDCUfXbhhnb4DcsExoEfB1A/of/8B/i3/27f4evfvWrSKfTrFlls1l2F37rrbfwxS9+EVeuXMGVK1fwxS9+EYlEAr/6q7/KaX/t134Nv/3bv42JiQkUCgX8zu/8Dl577TX83M/93Ohb6AGiFGLDiGRJUGXnFX87zqnW8NJLL+HmzZvodrtsQnvppZdw584dHB4eas0OjnPqkJFMJtkxYGdnh81us7OzHNGdtFjxxt18Po9arcZOBJVKBeVy+TG8RRPa8vIyTk5OUCwWEQwG0el0+iJyUL/p+ocgHA5jamoKrVYL8Xgc8/PzyOfz2N7eRr1eZwYuXkciMpp0Oo0rV64AOHX8EftUZFqk7YRCISQSCdTrdX5HZYtRLqLRKI6OjrgNsVgMrusilUrxlS+yW7vsVRkIBHD37l3eb/Ra1F6Cjtx3Ok1e1thsylNJxXJ+PwzKFn8TIdeBKp+ttiNrFrr0fsySYnkmPLw0Yi/cTHlV7+T/XvV7zRWb9IPkt7EUDAK+GNef/MmfAAB+5md+pu/5v/23/xb/8//8PwMAfvd3fxf1eh2/8Ru/gaOjI3z605/G1772NaTTaU7/R3/0RwiFQvjlX/5l1Ot1/OzP/iy+/OUvG/ddzgp0TAdQD55pgaiYluOcHki9f/8+Ll26hG63i729Pbiui8PDQ0xMTPD16yY8KpUKut0uXnzxRXYIAIB8Po/Dw0NEIhEm0JQ/Go2i2+1qHQhkZjE/P4/Dw0MA4Jt05+fn8eDBA65Pt4h1fVGv19k0KQa6JQ/HUqmEYrGoJKLhcJiv+8jlclhcXMQHH3yAXq/HjDYSiSCVSnHk9UKhgHa7jWAwiOPj475LMsPhMCYmJrC3t4der8cMLp/Pc4QMOg/n5dpeLpf73PN1BNmP2cUvsZf7W2SOKiFIl19HZPyajORvlbahYqImBmrDDOV84vEWU1ovDUenQaqYvG49iMKtLfMwpfdiyjowCdm2jNwPyH3nl3F6lu/6mZ3PCIjnuAD1ArTpJC9NS0WkvaQIWSNwHAepVAqFQgEvvvgiyuUyisUiWq0WKpUKkskkewiqpOxgMMgMKRwO85X0APiaD9I0Tk5OEAqFMDk5yQT5/v37fGaLCKwYJshxTs8yAaeMIp/PIx6Po1gsslmu1+sxsbeZLqI2RMwkHA4z/sTM8vk8KpUK1tbW+soOBAJIJpNIJBJ8iWQ2m+Wr68WzWTMzM3j99ddxfHzMWiKFdaJoG4RDNpvFzMwMDg8Psb29jVarhcXFRdTrdWxubrJWKh/Itj1ILL8T55H8TCxTR8zFfI7jPKb1yYRHxxBMz3WEUYW/Lejq1ZWlYrK2Gozp3SD1e71TMS0vbdbmnR/NRMfQVc9VeKveD8IGbOit1ztgsHNcz32sQpUEYcvZdel1DEv1W/yvy0ehlFZXV9HpdBCJRFCr1dBut3F4eMhxBOWySVug/RjybKOzWcfHx+xWvri4iEePHrEpMpFIIJVKsRZLTEQ8oEz1TU9PIxqNolaroVAoIJVKIZfL4YMPPuDwULp+NUnTrusik8mwNyNdJU9XjRCTIFOf2AeNRgOdTgfXrl3Do0ePEA6H4bpun/nPcU7PYe3u7qJarXJEd2LUYhDiTCbDcRop0gtdYeK6rjFOoy3oCKZMTPxK1DomINalqlsl9aqeq3DVCWuq9unwN0n5KnxUeOj+24CuH2WG40fzMGlisqAh51HRBxUeMnjl12k3pj5TCT5+wUarGqWWJcK5vNZEBK9BkRekSVpUgRdDo2elUomji9OliKKWIWtpgUAA4XAYsVgM09PT7MKeSqXwyiuvYG5uDpFIBNPT01haWuI9RnIEqdfr+OEPf4hWq4VgMIiVlRW8/vrrfZ6H9Dk4OOD9rGq1ikgkgm63i8uXL2NycrJvIejaKE5iMU21WsX+/j663S7S6TSb5WjPCQAmJiYec5YAwMy+3W5jbW2NGbWY1nVPzailUon3y2S8Op0ONjY2mMF94hOf4DE4ODhgbVA3jiL40ThN73SCka2G4UUIbfA0aQyqdDLuwzIcVXm6jwofE65yHbQXKp8plNunKksW9OT+9cJXHCud9utF4P1oj16ChkmY8KpfVdYgMGg+gude4/ICr0HxO4CqvCrC7jgOhyECgE6ng+PjY2ZAqijl4u9AIIDFxUUUCgXeo2o0Gmg2m3j//fcRj8eRSqVYg5iamkI0GsWFCxfYbJbP5/kSxkgkgkgkgtnZWfaUEycwaSp0/ouinsfjcYRCoce0Li/zCPUFXTVCDiR05oxMpcFgkE2I5BAh5q/Van0ejjMzMzg+Pua9qGazia2tLdbmxCj48XgcjUaDy0qn0+h0Onj77bc5mka1Wn1Mq1QRP6+FJhMnVT+Z3g2ykL20F1vNzmbemxilDMMSJRtcvN7J32R+zufzPL9t6vGjRajG14tJ2NIccQ7aaKp+6/Sa47q5Mgj99KscqODcMy4v0Nlg5QHRTUAd0wqFQrh69SouXryIv/7rv4bjnO4lxeNxdoAQz2KJnnVURi6Xw/LyMl9XQdoEEdnl5eW+yOeRSISZViKRwLVr13Dr1i2+DmRnZwfpdBqXL1/G8fExDg4OEAgEkMvl4Lou77c1m00EAqc3EF+9ehUbGxt9XnY65kWakjzJXdflyBakAdF7xzmNn1goFPhMV6VSYdd9UWIOh8OYmZlhhiX2veu6fCiYzrtls1k2z87OzuLo6AjNZrPvhmDVJZUqhqACXTrdPJHnEJk9VX1K/0UNUqxLlV7HcMXxMBE9HYMz9YO8Dsica8rj9c6EjxeoGBd5ttK6DIVCysgxKtOhqX55HGQtzraPTWXL5kfb8bOtX4W3Hzz91E3gd0xV8JFlXPJi1klXgH5BiwxL1jSAU8J048YNRKNRRKNRXLp0CcfHxyiXy+j1euxoQZEfZDPX3bt3eS+rVCqhUCjAcRxUKhVcu3YNrVYL2WyW4/ldvHgRJycniEajaDQa7F3nOA6KxSJrGBQCqlwu8z1S2WyWb+QNBAJ45ZVXcOvWLbz77rusfRFzlZms3K86qYy8+MQ0vV4PtVoNU1NTKBQK3Deiez7twV27dg2O47DJlZxSpqam2Gz63nvvMTOanZ1lBthsNplp6YixPCeICIvMTccg5Hz0nyT9YDDI0T2AU2/ImZkZPHr0yHgdiUpIkLUfnbYlPxPziulMc9+WiavS6+aIiUHqyrKpU9XWQCCAWq2GVCqFcDiMSqXS5+RC6VR9YquFiL9tNCwTYZfrVjEvVT02+PjVHv3AKJiRHzh3jGsYSUHHxFQDL08SmXnF43Gsra0hlUohHo+zIwYFCCaCOzExgYODA778UYR2u43r16/zoeJut8uHju/evcsaSDabxezsLGZnZ7G7u4vd3V10Oh3cunUL7Xab4/eJXoXkgk7mwWvXrqHRaGBzcxMA8ODBA1QqFSwvL3NMRCqDmJjcD2Jf+AEy9yUSib74g1Qe3ShADi2ZTIZvGybHi09/+tP4xje+wabZQCCAhw8fIhKJoFqtemomIs7BYJDHjBxLyMmFIn6IeeWygB8T4kAgwLE1Dw4OcHR0hFAohKWlJVy7do3Dl6mi75vKtSFGOnOuKq2NtOyHAIrCG50FVGmduvw68JOf9kHD4TCy2Wyf6bxcLj92U8CwoBMCTNqSitHJ6fz0l5eQbXov1z8oPAkmdi4YlzxhvKRIUxk2k0UsmxYm8GPTn+OcumnTgdZQKIR0Oo16vY54PM4LptvtsrZFeVWmR9d1uYx4PI5SqYT/9X/9X/HVr36V93BqtRpefPFFtNtt7OzsIJvNcrDYWCyGhw8f8gFk8k6kCdrtdvHee+/BdV2OedhsNjm6ejQa5egcZOYjJuYFclvkvnYch6N/AKdHHURvP+rrSqWCzc1Nxi8cDqPT6XDoqm984xt8Pi4YDHJQXgqMK+JDzh3iDcK0jxYOh5HL5ZDNZlGtVtFut+E4pxrp5uamVhKn9sXjceRyOezu7vKzZDKJdruNyclJvhm5VquhWCxiZWUFDx8+7HNIcV3Xqm+9+p36Wuxz3Xv5OYHftSTXQVYF6ktVnSrQ1atbl/l8ng+W011sZBmIRqMoFAp8xdLW1hYikQiHQRPro98mLVaV3g9TNwk+qjpN/W5jojP1n2x9UM3tUTH2UcJzf47LJD2YQKUZ6LQtnQYWCASQzWYxOTnJJjY6DJxKpXhBkSZBC5eI0tLSEm7dusVMIRQKYX9/n/eYiMmRlhONRlmjSKfT+OQnP4nNzU2EQiGkUilcuHABa2trODk5QalU4uvrZ2ZmcOfOHZYyqUzZREVtDQaDWFhYYG+7TqfD+2xTU1PodDp48OBBnzOFqn/lb/lDRO3q1atoNpu8d5dIJLC6utoXlzAYDPJlkLFYDAsLC3xrNkXoKBaLmJ6e5gjvtVqNXeOpzfF4nONllstlPp9G4zk5OcnnxwqFAo6OjrC5uYlyucyMW+wzcV6Q1+fk5CRqtRoajQaq1SqfwSMX/XA4jGg0yhHp6TzezMwM9vf30ev1WLPzugdNB+Jc1mleJul6GIZFfRkIBLCwsIDJyUkcHx/j6OioL2KJV902eJDwmM/nceHCBTQaDV5DzWYTwOlhdxLgms0mWy6KxSKbpsW6gcf3nOX3g4BuTHRmXV3dJpqn6yc5jak+3Zzxws0vc6M6nvh9XM8iDCIZyCYML22Lvh3H4TNJruuyNB2LxZDJZNhElEqlsLi4yHH3KpUKDg4O8O6776JWq6Hb7SISiTCDSiQSyGazSKVSfJWH45w6NZAbfb1ex/Xr13nxtdtt3Lp1C5OTkwgGg5idnWXi3W632SRI8Q5l6ZKIJP3e29tjRjI3N4dYLIZwOIxr165xOlXAYApUK15BoorHSIyLvCwXFxeZwScSCRQKBY6ZSPkpuK0YTDcYDHI093A4jJOTE2SzWT4bRhdvRiIR3hNbWFjA4uJi3/1eVEe5XEatVkMwGESv10M0GkUsFmOGJcdwlAP3xmIxzMzM4MqVK3CcU2eAj33sY5icnGST1crKChPVUCjENzhPTExwLEV5vpkIg4kIijiqypLHTzffVetBLpNArI/2R1utFu/1qeJZqtaajIesqcjzjrTtfD7Pa4nGcXl5mT1zyVxIY2BTn9hvXhqQF8hjIgrHXuZdvxqVnzQ2oBM6nrRGdi5MhbbgZd+l/wReizYYDOLKlSvs4p3JZHB8fIxOp4NSqYR0Os3XXkSjUczPz/N5qUajgZ2dHTaD0d1PkUgEExMTHDEiEAjgJ3/yJ/HOO+/whBcP8qbTaUSjUezt7bEJCjjdiyFCv7q6yowxEokgl8uxG7i8WIi4z8/PY319Hc1mE5ubm3wdynvvvcdmMArWKxJ1Ylzk6XhycsLvZWLYbDaRSqXgui7W19f7+o3Mqp1OB47jsEkvGAxiYmICKysrzJAp1mA8HkcwGESxWESj0UAwGMTFixcRCoXw6NEjDjm1vb3N7Y1Go4xfLpdjYlsul9nc2Gg0MDc3h7W1NU8TVrfbxdWrV7G1tYVUKsXHAD71qU/hb//2b7G0tISHDx8ilUphdnaW9xTJ1X9zc/Ox+9VUfSfPUxNR9aM96daHqQwRN/HSUupHMkHT0Qagf0/PRLRNuNEzEjg2NjYQCoUwNTXFxywo1Nza2hpbHOh+N5PFQFWfX81TJUTQc5FZyf2qm1s2mtQg42xjRpbn15NmVDJ8pEyFKknTC+QJJkrXdLB3cXERtVoNs7OzePfddzlqBbml0/4NxcN77bXXUCwW8f777yvdsWnhJxIJRCIRzM3N8X4O2fCTySSOjo6YgbTbbY6oUSqVmHDU63U0m03E43HWZLrdLhNI0hYJyERJrvEicwuFQpiYmMD+/j4cx8Hs7Cza7TY7elBA37m5Od5je/jwIVqtlnJxkGmNtDly+iDmOzk5iYmJCZTLZfa6dByH8xBxarfbmJ+fx8nJCUcloX1H8rgMBoOoVCpoNBqYmJjA5uYmotEoa2nNZhNLS0vsiUm3TFO8xHA43Bf2SmViFffJyHzlOA4zPgC8d3jlyhXcuXMH9+7dw+XLl7G2toZMJoPd3V0+sC1KtyrpX7YUmOa7/Fz1W8yjEuh0/0WtgUKGraysYHV1Fc1mE5FIhCOlkGcngD4PT8dx+taBiiypCD9pcOTARIGnm80mGo0GZmdnUavV+OhHs9l8LAQalSmaB02M1MvMOgh4mU/lulV5vRib7rmuzLNmDcOYCs+dxmUaJD9MzqvcaDSKK1euoFQqYXJyEnfu3MG7777LjCCVSjERpb0N0npu3LiBVquF5eVlPHz4kBeNCL1eDz/xEz+Bzc1NHB4eolqt8jmliYkJ5HI53lxuNpvI5XLodrtss4/H43j55Zfx3nvv8QWIAJDJZNiLkYij+Ol2u+h0OqydiMSl1+thZ2eHiTOdpSIz3KVLl3B0dIRut4udnZ0+ZiP3I31Xq1UO+0QCAZmXiNgAp0zs6OiIiV+v10MsFsPKygp2dnbQbDZRKBR4P4kOKNO+FGk+1EcAsLi4iLW1NSaq6+vreP311zE5OYnbt29zOC46g0bnf8hcqWuXGJE+Go3CdU/PyJGmnEwmcfv2bRwfH6Pb7eKHP/whut0u6vU68vl837UsfuYkoNbEVGl1GpxOovbKT7/J0YgsC5FIBLFYDLOzszg8PGSGks1msb29jU6nw0x9d3eXbyEwAc0JYlT5fJ4ZIlkgaH83Ho9jf38fwWAQ2WwWx8fHfWcETRYWlSao6i8b854Nw1FpOnJ6lfCgG0OvfCb8RsGYTQx1WDhXjEvHiEwd58W8VO+DwSCWlpZ4P+T999+H4zi80U52dCJckUgEpVIJyWQSwOn9Y3Nzc5iYmMDx8TGKxWLfgUhiYvfu3cPS0hLq9TqSySQfJKZ9LdKCkskkkskkaw4Uk/Du3bssXQJgN+CDgwPepJa1B2KiqsgC4kKJx+NIp9PI5XJYX19HNptlxkOHmEXnCnk8xGdk1hO1FgDMhF599VUcHR0x4w+Hw7zJn06nOazVxMQEUqkU9//+/j4CgQBrMLIn4b1799BqtfrMR9///vdx4cIFDjU1MTGByclJAECtVsPR0RHi8TgfD6D2kMRPTIvOb5FmWqvVEIvFMDk5iYcPH3IAYMK33W6jVCoxc6ZyZclY7EN5bFTvTOtB/jZ5MnpJ6OI7ih85MTHBxz7i8Tjm5uaws7ODeDyO27dvIxQKIRaLsdcl9Z/qcLBcl+OcRkKZnZ1lYWF/fx+u6/J5wYWFBdRqNUxPT6NcLrNnYyKRQLVa5Sgrqj5WEW6xv2zNmjLxtjH7in1uU6Yqr59nJro5DPM6C4ZFcK4Yl06yMaUH/EkGpJVsbW2h0+lwVPZAIIBSqcREjAiluCFMRJKuMWm1Wpiensbx8TFvFAPgfayjoyO0220cHx/zfpV4IDYYDGJ6ehqXLl3C1tYWn5ehfaFqtdq3v9Tr9ZDP57G3t9e3MS0zLbGtOgL52muv4caNG+wuTpdV0h6ZqJHJ+xqiaUmuS6yT3OIPDg5weHjI8QhzuRzvod25c4eJH0nvP/zhD3F0dISJiQnuBzJlTk9P42/+5m9YExNNRq7rotFo4NatW4xnqVRCPB7HT/7kT7InJTmNEH6kVUQiERYoALDHZzKZRC6X43NyIhMlzVclRKjGwYuYes1hFbEj4Yo8GWUTpYlhyeMZCARQKBRQr9fhui6uXLmCYrGIT33qU7h79y57/ZHLOjnkvP7666zhqiwQqvoajUbf/WtkhRDNtOl0mr1Faa83nU5jdXWV54UsYNnQA5VwIPabijnJc16Vn9LQupHng2mMBxHCbdo5KPPS0Y9RMLRzt8dlC7pJBDxORMUoDpRXNFeIgxsIBHDhwgVUKhUsLS3hwYMHvM+SyWTQ6XRYqqa9LLqIUJzsZAYhd3Sqk+z55MFG8ffI/EF7YdeuXcP9+/f7LjokIgWcag/imSGRcFIfiN9y+/P5PDPsXC7H+02Oc+otePnyZfzN3/xNXyR3FZEQCZ78Tf1DDi5ElJaXlxEMBlEul/HCCy/g8PAQk5OT7J1J16aQw0e32+UbqOv1OtbW1tBut5lpqZgG4UXmpmg0yo4mExMT2NjY4HvGiHHSniHt1ZGH6crKCrvfp1IpdtMnc2yxWGQiKh9RkImWbkxU81b3Xp7H8/PziEajbLojoUZVt2ouUJnkmDM9PY2TkxPEYjFMTEzws83NTTaDUuzOYDCITCaDWCyG3d1dzM7O8uF33dwTP+SZSvOQ1mWhUEAsFkMsFmMz7P7+PltEyEQtmpDFtsrM2wZ0AscwxFq1Hm3oFmDWrFS/Vd/0XtZER8GQqMyxO7xPMC1GU3qRwNCekPi/UqngpZdeAgA+v0VSOWljdNaIPJ105jrx+g/XdfvutlpcXGQTYb1eR71eZ62sVCrhwoULeOWVVwCA8XSc09ht5DKeSqXYpCVPVNOH9rKIEZMZstVqoVgsYnV1lbWSxcVFzM/PM4NTxTSkA6Siu7Truuw5SAenaf+Oou3fv38f1WoVBwcHfFllvV7H3t4ee/XV63UcHBzg5OSE97fC4TDHjqRDzGLbSeKniCT7+/solUqoVCpYXV1Fr3d6K/XU1BSSySTC4TCSySTS6TRee+01dsGns3jVahX1eh2NRoPNhOQBqWIUpnlpMieJ72WiKzMtYlztdpsj96+srLAwJmtSKhduWQCp1+vY2tpiQerw8BD7+/scLHpycpL3aunYxJUrV1hDOzw8ZG9am/roPjoAfFBeDGP20ksvYXp6Gq57us/4qU99Cul0GoVCAVeuXMHU1JRSiJXrkeeHiqnLaWVtWAYbhqhqt64MVd0yfnIeOb+qPF27ZDy9YJQ60rkyFfoFWXpQSaQm0ElYu7u7KJfLmJiY4CtCisUiDg8P+SCqaRB1khBweqYqn89jf38f7XYb1WqVI0U4zulNv/SODmE6zo8vIazVajg5OUE8HketVsNLL72E9fV1VCoVTqeT+MU+E6Hb7bIZr9vt8nUsdP6JNsYdx+k7GEpAkvorr7zCnpamxXLnzh3WhAharRb29vY4yjzVQUJCt9vlfSjy+svlclhYWAAAfPvb32bvR/GSx2q1ynuHYt84joOjoyOUSiUAp2bN5eVljnoPnO4pHhwcMLMkRkUm40ajwYep792799jelvjbZGqSx8Yrjagh0Z4kCSEbGxt9EWDk/teZ8Khu0mBJsyTB4Bvf+AafY5Nd07/97W/DdV3W2OXx1rWBgimTQEDrK5FIoNvt4uTkhKOt0OWoDx48QCaTwfb2NkKhELLZLHZ2dvrGXMdo5L7Q0Q6v/PJY6jQzuUzxufxeVa48NmI58reKYXlpcH5h2PwifKQZF/C4lGJSg1Udr5ugFMqJNoEpHRFlEy46icZxHGxtbbFpaXZ2Fi+88AKuX7/OG83VahWvv/467ty5g62tLbiu2xf+JhAI4LXXXsPGxgZarRZ2dnbQbrc5egcFsNW1zbSwM5kM3ypM0jK5lpMmRftO8XictTJiQltbW3Achw8Gu+6Pz4ZRgOFGo8F3Z12+fBnNZhPFYhEnJydIpVIcPJjMcBQVXGTi09PTaDab7DL/8OFD9rYUCRjtZcrMjL7FK1MikQiOjo7wqU99Cmtra3zvE5mpgsEg0uk011kulxGPxzE1NcVR801SuU4jMKXTSf+kYYtXyZCmQ/e6ua6LWCyGarWKaDSK6elpZtQm5kXjl8vlkEqlsLu7y+bBRCKBvb095PN5vihUtCZQX4lmO5mwUh1kJicvQgouTeZ14FRQ2N7extLSEnZ2djA/P4/V1VW2Tty/f/+xS0ypLlW9OoahYx4mZqAaS68x1pWjo08qxqdjRjZt8BKK/JgLh9W+zg3jMk0+1X85L2CeXDb1ib9d12WTkEqzI5DfiWYrYjRE6IkYbm5uslS8t7eH4+NjZkx7e3uo1+vs/EGEgdIDp4cxq9UqE9JYLMb7N2SysZEYZaD9nkqlwjH7yNznuqfeXgsLC3Cc08j3AHDhwgXeK6Nza67rsideKBRCu93Gxz/+cbTbbTx69IjPqv3oRz/C1atXmdhRaKFut4tWq8UMGQD29vbYC5Bs6p1OB/fv38fh4WFfkGORQHlpoPSMTKU3b97kc0viTcxzc3NoNpvIZDLsNEPR4ulbpWnZSv+muS0T2StXrrDpjG4gSKVSHLWDnIGWlpZw48YN9Ho9XLlyBTs7O7h37x5CoVDfbQZUrsjE0+k0a6qk7dK9buQBure3pzySIbdN/h0MBpHL5bC0tIRwOMyhvyKRCJLJJC5fvsxX8TQaDWxvb6NUKnEotUKhgFqtxvVTma7r9u052/Sl/Fz3XtWOQUFkKiZaZcLPi1GbyjDhZQI/WqkXnBvG5SWtmDp1UIblZUbzIjwy08rn8wDAzIO8Bl3XxfLyMu7evYudnZ2+IL3Aj803tHck7ruJDhjkdbi7u8s2/osXL+KrX/0qEysVAdH1lfiMzjrNzs7iypUr6HQ6iEQiePToETqdDrukb25u8j4UcMpQGo0GX7FCEbzpUHWj0UCr1cKdO3fgui6y2SzS6TTvGd28eZOl/IcPH7JXpeu6qNVqHCuS4gKS+Y+ODZCWqdIiZGYlMzBx/KjPDw4O4LouM05K22q1MDc3h0ePHvXta1YqFe53kRipQMfUVIKRiaE9fPgQ6XQamUyGtWTas3PdU5Od67ocuT4cDnNMzWvXrqFareL+/fuPBailuur1Oh48eMDzjsaHHD8uXLiAjY0N5HI5DozsNcfkd2TWJLNvq9ViE/nt27c53Bmd7SONu1AoAACbcx3nx/tk0WgUmUyGI3C0Wi32jBX7XTc2NkxJN066MnRjaYOT3Geq+SOXa2KCfhmNHw3ML5wbxjUs2GhkgHlgxXJ0ZgLxmUysut0um3GazSbb63u9Hvb29pBIJNjdmoghleU4Pw5ESw4bVDYR5Ugkwu7HFJKInCzC4TA+/elP42tf+5rxdlhTP6XTaTSbTWxsbOCll17C7u4uQqEQfuInfgI3btzA7u5un8uz67p8yJgk8kQigYmJCezs7KBWq/F+UK1W4xiOGxsbHBaJ8pHpiIgXHX6t1Wp8nks02eZyOXaWESVs8gi0IQZyGiJ2JHiIe1a0j0IhwWi8yetRpW2p6pR/+yU+jnNqTm61Wjg5OcGbb77JRJ8u9NzY2OBIIhsbGxxSizTUlZUVPigtMy0SYsiMSqbeZDKJTCaDWq2GO3fusGYsCwy6dSO3s1QqsfOPmJ4uUiWvWzJX0jza39/nq2oo/8TEBLrdLubm5nBycoJMJoPFxUXcunWrbz/WSyvRgW5svYRrv9qUDVOVmZYO/DBGHfhRHvzCR4JxeUk5gF2nmgZdV46ozqvqFcttt9t4+eWXcfv2bY5vWCwWea+BTF+lUukxMwGFaqLo6BS4dXt7m4lotVoFcOp9VS6X8d577yEWiyGbzeLw8BB/8Rd/YXWdhow7eUweHx9jZmYGjuOwSYzunyJCQm7fouZCUnmn08H09DRHPaCDqYRTt9tls4/ruhzfjw739no91qKoXDJdyqG1RA/MdDrNezckAJBgoDMZyZo1AHbCkOcBSfUUzYPqII1YBJ32NIxZRcSHmEkqlUK328X169c5hBhp7ORAROa2QCCAtbU1drx4+PBh3/6eCmQt9eTkhPc36eYCU/vFcnTrTTxaIVob6NnHP/5x3Lp1C4eHh31jT276JNBUq1VMTk6yhy1wuucnHjBXacI6QVTXF/JY6ECkF360MLkulVChwtWrHaOYf6OGjwTj0kmjftV720mkSyfXLz4nSZ/iDFYqFSwsLPCCS6VSODg4wKVLl3Djxg2cnJxwGcQYKPpCLpfDysoKtre3+w4x9nqn12XQQVOSjkkbMcWKM0n0tD9FJrdGo4GbN28ycf7+978Px3GwuLiIvb09jnAg90MoFOKIChQaiBgXaQoU5Z72/rrdLod9unz5MjOgbreLw8ND1haoDiKWR0dHAE61UGIk1K7Jycm+O8xEpid+ZBCJpvgBwB5wqVQKW1tbeOGFF/iMHzFIk/TsRTy8pHORiIVCIUxOTvJ+Dh1DaDab2N7eZvf4/f19JuDieTcyn3lpAyJQZAvqJ+pPnXVCV67MLMkELo6h45zGs1xYWOALV+msVrVa5b1TOhIiavUU7eP27dt9lgcbbcimP1QCj47ZiW01CTAqjUosV/VftZ7lOSjj+ywxsHPPuGwXmIk5yeWYmJCXpKSrm4LLvvPOO3xYuVgs8jminZ0dlMtlrK+vP7YxfvHiRbTbbbbbx+NxZDIZuO6p5xt5Fco40EQlJxIvwkh4y4som81yJHfa16nVahyk9vj4GJFIBP/9f//f4zvf+c5jpjjqs8nJSfYsJHOO2KfyQXAKM/Xw4UOcnJygWCz23dJMHovktUhmVrHvWq0WMpkM5ubmsLW1xftNvV6PTZO7u7vsvGHTRzLQ3iJF5I9Go7h69SoikQj29/exv7/PV9aQF6Sp7+V3KgInA6UhE2q32+WwVdeuXcPe3h4zMboKp1qt8gWMdJZOx7S9gIQkirCi6i8vIVKl4dF/umm8XC4jEDi9J+/tt99GJBLhQACi9k59PTMzg0KhwDc1UPBp2fFEtXYH7QcvK48Xk9T1gWptetXlJXjbttVEZ71o6yBw7g8g+9GobNOrBlM2jZjqkvMCYE2ACC85GbTbbbzxxhtYWlpCOp3mg7ii5H98fMwLMR6P4+DggIPzyiGNqB76iOec5HJt8HYcB5cuXcL+/j4f8G21WlhdXcXh4SGy2Sx7zv27f/fvsL6+rtReer0e7ty5w44b4h6IKJ0DYLMjBd4l05PoYu26p+7cL730Eq5cuYJcLsf7IWI/kBROzJKifpD7OpktL1y48FhfyP2j6iPXdXHhwgXMz88jHo/zPuP169f7Io3Mz89jYmKi73C2SsPwkvLFeawi9CQgbWxs8NU3N2/exMnJCZLJJH7+53+e978oyvulS5fw6quv8iWmJtzkQ8MUvoxMpQcHB9roKapySAARY1iq1iqN6eTkJB9NyGQyePPNN5FMJjnSjjj2jnN6NICC/xJzVu3xqnBU9a8IJjpgIvK6tDZrUtdHOlxkbctL4/LbHhUuo4Bzr3HpwEZCUD0H+iexjfnGpG6rJkmr1eKDralUCt/61rewu7uL7e3tvlBNlGdvb48JHh3O/fSnP41Hjx6xx5iO8ch4qDQrHZ6Oc7ovJYZ26na7mJmZQaVSQbfbxfr6OhKJBIrForI+qkckKDLxA8BecIeHhwiFQpibm+M6gB8zfgBsHm02m1hdXUWhUMDk5CS7/Iv3MImmUoruUK/X8ZM/+ZMc07FUKuH+/fuPMXSTxkB9R/tD4hmjqakpdkJpNBqYmZnBjRs3ONiwLtisqj6/ZjZKT2VTdA/XdbG7u4v/5//5f9BsNtnJhxg43WGm0hho7kUikcfMa3TQ23F+vLel6zPxWTQa5QgppqC7VEe328XCwgKbk8PhMJsnG40GrxtxLTQaDdy9exeu67KZMZfLseYuH5S3Wbs6MDEEU3/ozIBiWtW8U2k5tr9t6h6l9jQIfGQZF4HMXEzmCDkPvVMNvGpSqOpWlQ+Ag9Tu7OywJ1qv1+vbDxGJEHmm0eJcXV1lM6FOi1K1SceQTZOUNvBd99TBZHV1lcvY2dlRlq/rO2qDHBYqk8ngypUrWFtbQ6VSwcnJCcLhMFZWVgCAzxs5zmkoIYoCLt5KTYd/RQ2OmGQ0GuVzV8ViEbdv38bk5CTK5TLW1tYeY7w6rVRsI31TeC+6NJOcI8jBgUxwU1NTOD4+5j0+irwvCxNi2bZSsGoOk1b60z/907h37x4ePnzI3natVgu1Wo3DN9GZJ52mQY4yR0dHfQSfzLQkmHjhRvfXtdttPnRONwHIfSyOXygUwtLSEu7fv8/7Vdvb2xyqS3XvHc1X8bD8wsICotEo9vf3ldfLyAScnokCmNwuFY2Rx0JMJ4MNvRHxkOuQNSkTfTOtTxuapsN71HCuGJdKylC9F8G0uL3y0nMbfHR16PLTlfTkGu66Lh/qVO1XEdAG+tbW1mMhjHTtUS0s0wLUlUEgRgdRLVY/C4AIPV2T4bqn3mQUl67ZbHKf0AIl5wLaMyuVSnxxpHzAmkIv3bt3D47jsCkPAF8cSZv4jx49YpxUjEuce3SRJu3rUKipTCbDGjKdX2s0GrzvND09jeXlZayvr/N+jZemJYOJEIn/33zzTQCnB9IPDg76zvElk0m+54ocXnSE13F+7DWZyWQQj8f5uAId8aAraXZ2dvpCeontoP23z372s3jnnXfYOYc0UJFpic40ly5dQqPRwIMHDxAIBHivl4SWqampvpBdqjlGc4E8JkXnJ1X/2momYn/p5rqKZqn62nbMTe90a1gnfKtoga3mdZYa2XPPuFQSgS3TEsGrk3XE1m+ZugkpTxqKQUjRrImAeDFKALynZIOPChdVWlW9Ji2T/quYt5xfhZcoUQeDQcTjcYTDYWxtbfH5mwsXLmBtbY0D2VIdZBJcXFzEyclJX/Rv2ZvNcRyWxslslslk+G6sra0tXLx4Ebu7u8o9QBWzd123LwrI1atXsbm5ydqz4zh8h1kymeQrb8iRpFqtYn9/v885xQ/YCm/vv/8+n52jq+wpLwWAptu36TCyimlFIhFks1mOu0gXYrZaLRwcHCCZTHLkipmZGezt7fXdik0fOix8//59RKNRFjTC4TDq9TqbeOmakk6ng3K5jNXVVeTzeQQCAXz44YePudmvra0ZrQ6ue3qwnQ7Ry+Z4Vd/Kz1R9Y1qr8ljoGIRJU/JTrmlOyGXbCKeqtHL6s4TnnnHZdtIgzEyXVkWY/YLXJKVzVxQ5QjYneC0KsWxVnXI7xGcqhiNL66Y22UxmkTHJZkHxUkk6WFytVjmcFXCq1R0eHuLg4IBvghbLbbfb7Mot3vEk9yPVmUwmce3aNdy4cQPXr1+H4zgs8d+6dasvv4oAylIo3Qfmui4zIXIgoQC09AHAxJmONcTj8T7hw5YAqdKL/SLiSVe7iHt+lI7m3sc+9jGsra31HcyW66YjENlslg92V6tVxGIxlEol9lAkU65qLjnOaVzJqakp9Ho9fO5zn8P+/j7no/6nq26uXr2Kk5MTlEolrK2tsUAgHmoW22ra53Vdl8eaPA917vqEq6oc+b2cTleOrlwTzfKr6ehwlgVynWDupVWa6j4L+Mjcx6WaDDpiLDMpk0ZgU69NWbqydXV4DZtpUdhoiXL7vP6Lz+i56L4uvnMch+9hikajrFFSHrr6otfr8S3RshTsOE5fpH3xOZ0rcxyHL4ykNPI+SzQa5Usg8/k8Zmdn8fbbb/NhYTGPyLi8xoEiekSjUbzwwguoVqt8iJc0xEajAdd12dnEcRzeY2o0Gn1XuYhjpyOEpjFVjZXq2hDxXSAQQCaTYW1H1dfAaaiydDqNubk5PgJBkfFJkxPHTnYYIq1teXmZgyjPzMyg0+kgGo3i8PAQjx49Ys3ok5/8JN577z0Eg0Hs7+/3HThXjY9K2ND1nci0TIzOqxwVmMpTMRA5n1/BUV7rNvPGRB8GbbeubCpjkPu4nnuNyw94DahK8/BSm02TSSe9qMqSJephVW6VRmdqj5+6dITQFi/HOd1Mp/uYqtUqMzmS7BcXF3F0dMQmI/EYAIEcRVzU3NLpNBYWFvCjH/1IKfmKbc9kMhyp4+DggDUGAI9J77LGpnpG5VNIp83NTY5J2Ov1HtNwXPd0T4ki1tNFo3Iaeay8mJhKyxLz6/KJbZmamuLzXmJ54nyiIMF09o20pHQ6jVgshv39/ce0GJlRkqYWiUTYqzYQCHB091wu1xeXMJFIcBxME3NSace69orMzwTyXPdKL689sQ/l8lTamu3a8lqTJk3JBn+vMrxo4iBt0sFHgnF5MRAZdB2sm7Ay05EJjSxFiZNYJWGJ5ZsmjR9moWqjjK/cdtt6dAxfNUHF8ilCPd2fRLEX6fLISCTCUd3FfDJucl/G43Ekk0m+ToXSix6WlL5er2N3d5cJMADGw6sfVbjIjKTT6aBUKj1m7hXTU2DYmZmZPtMY0K+1qu5xsxE8VO90gpvYlxRdolgsspOIaO6T65+dnWVzbjQaxdLSElZWVvAf/+N/fMwNXnQ6cRwHtVoNa2trAE5DktH5v1qtxsGT6ZD76uoqO3/YMiedtiALM35Bnpeqea/rf51m5QdUa0xFl1TPTe0RyzYxrUGE32GZFvARYVwm1VdF+MR8JsJuSqvKo9OwZJxknE3M1Q+otC5V/ab3qnpVhM+EI7WdnC7IrFYqlfgYQKfT6Ys/RxG8xYC4qoUUCoXwP/wP/wMePXqEO3fucBSF6elp3L1797FYiQBY42s2m0in07hy5Qp++MMf9mlGcn1e2o74XLzjTPWe8KGjA2J9jnN691Qmk8Hu7m4f81LNLzK9yniZhCN53IBTxtLpdHDv3j0kk0k+U+W6Lps4xbKbzSZfVRMKhTAzM4ODgwN88MEHyjvoZIJH153EYjFOQxoWxYCkS0lJ0JHbqAM/TI3wMeXRMQMxv01eXVpxfFWCpFyvSkjWtcVrHqjK0DGnUWhOg8Jzz7hG2XkmVVan7aiItpcE4kdCEXEhaVd87rftXuq8DqguEyOz0czED8VUvH//PtrtNu9zbGxsIB6Po9fr9ZmI9vb2mPFQW+R9tG63i//23/4bQqEQQqEQIpEIwuHwY7fcihKy4zjct51OhyPmqxa5DcMS61D1gfxb1M4cp3/viSKrx+NxvPTSS7hz5w6bx8SyKEJFMplkhxRd3aq5qltHkUiEo1HQ+SrRSUYsg7wSHcdBIpHA1tYWM1GZ6esINkW5ODk5QT6f5ytWer0eO68kk0nWqMX+U5Un121Kq1vfKqFU1a9yvSrQlSGWo5t3cptU9evKVTEfm/bqytSBrTA+LDz3jMs0EWSwTednUpgmtB8cvLQ1VX6R+JpwVNUlpvfCXfT88wIVgxOfkafg9PQ0arUaXz1CtwDncjlcuHCBJfDd3V3U63WOPi9v6ruuyzfeUh0UqHhycpIdBchdOhQKcYBdmXm5rss3KsvPdYtRJQl7EVJVn8n5Hec0HFE0GuUoGnRVDY0FHaomgr60tIREIsH3SOkYGNUjMzL6L+4VNptNTE5OYmdnhy8npTQ6LaDX6+Hu3buPmTbFeURXwIhjSVovnc2rVCoc9Z+EDjovRuG9hgFxrHSaDYFOU/Fi/LbCi/yeBCnTfPICk6Agt9cPHfGjuct1jYp5PfeMCzgb26qpk2XmYjMgqoE1aWsqPEz40PtBGKiOURIxIQeJSCTCewsiiOXIGhBw6mE3Pz/P7umzs7PI5XJIJpP4xje+wbfkJpNJjj348Y9/HBMTEygWiwiFQnygWj5MTbfp1ut1xONxdiZYXl5Gp9NBMplELBbDvXv3cHh4yB5oqv4DTh01PvnJT+Kv/uqv+t7J2plu8XotapP5R17giUSCnTYoBqTjnDq20PUbZFrrdruoVCoIh8MccaJYLPKemQ5EpkXj5zinHpvEND788ENcu3YNBwcHHF1ER6AIv4WFBTx69OgxBkeepBcuXMCPfvQj9ia9cOECdnd3EY/HUSwW+aYB+cB9vV5/bB9QBfIaVfW3DejWhm7sxN82a1Gl3dBhdNFU7Rd3E0P20vbOCsYalwG8NBrb5yomIDMfnUSkk87l/zrmp5t0KnVelU5+7qU1yDi7rtsX3JQ87hznx/dIqfpLDIRKQGVMTk6i2+3i+PgY6+vrKJVK7FFI5RFTCYVCuHfvHq5fv85xDslkJONN/U8u8MFgEO12myPSU+DhRqOBWCzGhFJFCMhVvVgsYmpqiqV+qiMSiXD0dDGWnYiXjeSt03hlAtZoNLC8vIxyucxaB0UE6fV6HMqI2pdOpzE9PY3bt28DOL0ss1araYUl+qZxTSQSWF5exsOHD7GwsMCefru7u/jggw/6nFZkRkwCC+1XFgoFbG5u9u1VOo6D+fl5xq1QKHDbKGCyHBhaZd6VPT3ltaBiWl4alaksFajoghcd0IEoOESjUczPz+Pg4ID7RsZFV5+Mj+q/id6onquELRtm6MW0B9UiCc4d49INmFcnqgiIieCrtBXVQKvwUv3WvdfVq0trkuh1E1CVhiQ/cmmm+7GISKkWaSaTQT6fZ/dnKufFF1/kyBTLy8t48OABx58TJWdyFSdHAMdx8Oqrr2J9fb0voC7V57qnHnm7u7uYnZ1FIpHg61QI11wuh+3tbTSbTb6M06Tp7O3tcWBZus2YYicWCgXMz88zzt/73vf6cJHLEvvUDxCjJ49LipNId4dVq1W+pXd3d5djKh4eHmJ/fx+tVguBQIDT68Zc1rZmZmb4xmq6441MtVQ/RRmh8iiyyfT0NFqtFlKpFEd7yefzCIVC7K0ZCAQ4LFSxWEQqlUKn02EPQtLmVOexVH1pmr82xNvmHdVjGkO5PhLWYrEYnz9UlU3po9EoC0okKNJ+pbyPJ4+fiUmr/uvoja7dBKr6TWCraQ4K545xieBXNfVicqr3pgWiw8NGUjFpWTbMWFWmagKbFm0qlcLk5CSmpqbYY0zHmEnbqtVqmJ+fR6fTQaVS4fSXLl3CN77xDWxtbfVdqyLj6boum6kODw/x3e9+lyNj6KTqTqfD8f8c59TBgiJSlMtlRKNR5PP5x/bIqCz6UCRz1z29KoauOyEmUCgUsLCwgG9/+9t8KaKIt+6/CUSHG2oPMcqtrS2+BiSbzaLVamFubo5v8KW69vb2AIAvRKQ9MdExQgUyU9vc3MTs7Czy+TxmZmawv7/PWsDU1BTi8TifnRIFk3g8zu7vdCUNRQshxxpicpOTk3BdF+VymeMQuq7Lda6trfkmarp1SSDuhXmV67WW5bEV6xY/kUgEc3NzWFtb62P2cl2O47DjSSwWQygUwsHBAYcpMwmxcv22GpgOdOlshP5h6h0EzjXjsgUV8wH0xF0nragmj1+pRceUTNKjSQpTaYQ6RiqnpX0V2ggXzUEyIyHJe3l5GdPT0xznj+4JEwmefL2EjAsxGDG6vVe/0cFU2hsQy6/VavxObK9YZygUwssvv4zZ2VmOLE5u3/F4HK1WC1tbW/yc+tGWYenmhSw0UJkbGxsIBoPMfNrtNl81Qh6YxWKRGRVFmVAFk7UlHpOTk1heXkYmk0G73cbVq1c5sr3jOGzKpfEWodvt8n1j3W4Xe3t7aLfbfX0VCARw9+5dFgLS6TSOj4/Z6YOu8hFxpgPpqnWmEsQmJiYQDAZRLBZZEyTm4bqn5l7VdSXyf5UAqVs/Mr50kJr27ehoAfDjyBzi+EciEQQCASwsLDDz3traYoclk4VAhYeJBunw9hLAdTTSBGfFtIAx43oMVBqIajKYzIK697bpvPAS/5sWka4+OZ0qL3BKLOl8FTkDZDIZ5HI5vnae8pCbMnnzUYw6kvyPj49ZuhYJvMrUQXEIbRYc/aaDvqpLMalMlZQq4hCNRnF0dMR7b8Cpeex/+p/+J3z961/nuIh0FYbYn16Rx03PdYSI2kKhl1KpFO7cuYNcLsfmVIogPzU1Bdc9jdZx7949LlfuZ/k3pSPN6caNG8hkMnz1CoVxEuMIEjMR+/7k5AQHBwfIZrNYWVnhQ9eO4/B1MlRnMBhEKpXC2toazxExOoeIO2kkquDIlC4UCvGzWq2Ga9eusYmXbnWm6Pwf+9jH8J3vfKdPm7FZ217rU2Rc8Xgc+XwexWIRS0tLCAaD2NjYYPOzqK3T3uzc3ByuXr2KV199FV/96leRyWTgOKchwGid6dauaV7LYNKqTLTB6/9ZalcqOJeMa5BO9JKsbDUgk8Yjv1f9l3HR1a9LJ7+XNQPdBNVN2nA4jHQ6jWg0yiYdsrvLUnepVEKhUMDbb7+NcDiMfD6Pzc1NHBwc8ELU4akywcjjoGoveRU2m02+cl4sT6UFqSTSZrOJ69evIxaLcVTybDaLRqOBv/zLv0Sj0UAmk8HU1BRu3ryJRCKBdDrNe0CiNqcSdEygEpZE3Hq9HorFIk5OTphIN5tNvPzyy3xmrV6v4+joCPV63Vo7kX8/evSIHVxKpRJ7Y4rX4ySTSaWLPQkb+/v7SCaTffuhdAyh2+0inU4jlUrxBY8yYyWzouM4fG6s1+thYWGBgx3L/bO8vIyf+qmfwle/+lW0Wi2Uy2UUCgW+3Zg0yFQqxUxdbr9q/quYuzhmKiDLQ6FQwNTUFEqlEnZ2dvg8YSKR6Lvni9p5cnLCjJwO29M+I/Ud0B+CTEdjxLJV/eWVV15nNtq7jfA9SjiXjGvYzjNpRrr0qvc6ScivNOOFi45IyQtPp+XoCFkgEMCLL76ImZkZFItFOI7DizCTybAJkZgDXX+Ry+Xw2c9+Fn/5l3/J2g95i4n4ivibzGymfnFdt+86DlX5XmVSueL1IoVCgZk0EZxms4nDw0Pk83n+TyZIk3ZuA17Mi/b5QqEQtre3USwW+czTxMQEYrEYe6GZBARdHxA0Gg2+OkaMXNLtdrG6usrHImQnF9d1+SoeGg8i4tlsFteuXcO9e/cwOzuL7e1tjoYhAjEtCk4shn7a39/n9zIhrdfreP/995FMJjm4Ml3HQnud9Xqd7z+jfDZar7iWyGmHYjPqNLJ6vY6dnR04jsNzntrQ7Xb7wpCl02m+ALNSqeDhw4dwHAcTExMolUq4cOECcrkcPvjgA44ao1vjKu3aRCfEtF40wYYp+aVbw8C5ZFx+VHxVHtUzPx0ua1Oq/CpzhM0727p173RMT05Hm8vVahW1Wg3xeLzvZtxer4epqSlEIhGUy2WW9ElC3tjYYFdyeU+Lrlqn+kVipJMCZZxFd/1oNIpMJsNESl6YJuk4Go1yKCHao6MI5ScnJ4jH47xnV6lUUK1W0Ww2cXBwwERaJuA24DXf5PKoTbTn1Ol02GFmY2MDuVyuz3wn9wMApaZEjJvy0H5ZIBDA6urqY31JRyMogj2dsxLrLBQKbB4mnLa2thCNRrG6usrMRWRsJycn7LovBmBeWlpCIBDA97///b62ifjTrcuFQgGvvvoqrl+/jlQqhdnZWbzzzjt8IFt2CPLSRkUgXEnjpHNmdNkmRXQhDTkcDmN1dRWzs7PcPsojC0v37t1Ds9nE7u4ua6skIJCmL2qi4ryQ8TbRDh09Mmle8lwy0RfT+1FrY+eGcenU2WGkABvmJw+oTssyqexeZZrw1TFpXTrde/l5MBhkUx8AvhMrmUyiWCyy+SqfzwMAE/58Po+pqSn88Ic/5HLE9tN/AH1ExKbtBEREiOiR1pVKpXB0dNTXTipTdfYnl8thbm4Oq6urWF5e5rNikUgE8/Pz2NjY6DOT9Xo9TvfOO+88dpuyzMBM4+e1wHVatPiM9r/oMki6EoXSk5dlIpFAr3d6SaKIrxcREjUn6kNi5rTnKQoLuVyOhRfRxEWCAe3X1Gq1Pjd6mlviHijNNbqzLBQK8dxRRZmncaJ9skqlgpOTE+6nXC7Hl4GKfWgD4XAYn//85/Hee+8hGo3iU5/6FKrVKm7fvo1oNIpQ6JSM0rEB1z29gy0UCqHdbvOBat2cqFQqmJubQygUguOcRkyhM3CdTgc3b95EOBz2FDypL3TtshEKxf8mwVsFXkLzKOHcMC5Z3bXtKBvmYCrbaxLI5YppBmGqXv/FBW3SGFVtEJ91Oh3cuXMH3W6XA7ySpA+cMo90Os33opEzxczMDI6PjwEAhUIB0WgU5XIZx8fH7GRARLHVauHw8FCpFZnGkNyq4/E4FhYWsLq6ylfPE6ElIiDvP4njeHR0hEKhgEuXLqFWq+H4+BjlchndbheHh4ccloguUmy323j48CHC4TA+8YlPsHlHdTO1lzBk004ZXNflixTJuSAUCiGfz2N+fp5d6AkX8m5zHIdd+/0CMW263JPKEhkStavb7eKFF15ArVZjASIcDvOeGXnzUVl09czJyQmmp6fhOA729/f5oHc6nea4laTt0IHrw8NDAEA8HmemfXR0hHfeeQfJZBLpdBpHR0dYXFzk/T95HEwajJiu2+3iW9/6FjOp119/HQ8ePEC5XMbR0RFqtVqfCZDKdl0XlUqFmZbolUtMluqo1Wq4fPkyR8gnpxWau2L/e9EiE30ygdgXXgLWIKBjnIPAuWFcgD1D0IFqsHSMQK7TS8LWaWW69zaSk9czm3wyPvSf9m8cx2G3duoHkVjRvhA5MtBiXFpaguu6WFhYwP3799n0Rndttdttvg5ep6moFiL1C0XG2N/f54jodPCWNsczmQwzF1qMIpPsdDrY2tpCp9PBlStXsLS0hL/+679GIBDA8vIynylynNMoFuTWTLflTkxMYHJyEj/84Q+N/e41DrZjR+fJSBMBTr08Jycnsb29zd5zvV4PoVAImUyGHVfori9T8GDVtwjk6p3P59mFu1wus7NOp9NhoYUiuGcyGc5z7949xONxLC4u4tatW3z+rtPp4OLFi303BNDVNrQ3tbCwwJFXaJ8pEongypUrcN3T4wOpVIojsTx8+BCu6/KcpD1Z0bVep1HIAh8xYApT9l//63/lYxczMzNYXV1lLZO8Lkl4IiZFWmsgEEA+n2dPzF6vh+npaVSrVdy8eZP3scR905OTE+UdbiYhXR5jlRArWgr80A4/wpZN/YPAuWJcg4AXEdH9FtOryrMxCek0ItUzcYGZCLvpuReoJpLrurz3QBJ+Op3mKOqNRoPdf+v1Oubm5rC+vo5QKIRyuYwPP/yQTR7AaZSAUqmE3d1djoYhm69k/MVQUoRHp9NBsVjE3NwcIpEIR3Wg96lUis+hyQyLgMIm0X4OnSOq1Wq4ceMGawh0LXw8HmciffPmTWXZXovRS2OWyxD7IxgMYmZmBul0Gnt7e8xMj4+PWUskwSIWiyEWiyEcDuPSpUt8kaWqH1R9rZqD+XwemUwGFy9e5PNs2Wy276xdqVRCMBhELpdj5pbJZLC/v8/X2Liui4997GO4ceMGjo+PmUm5rtsX3kpcR7VaDcFgEOVymSOJzM3NYX9/H657etaO5gWZTOfn5xEKhbC+vo5IJKIdDxsm3m63+YhHIpFAo9HAxMQE5ufnWSN3XZcdeRzndK/vypUruH37Nra3t+G6p165r7zyCh+YT6VSqNfrHEZMPMZBH69LRWXaQKZj6kuZgenK0r0b1Ko0CIOzhY8847KVIkwDrCrPhkDpypKZn4652jBVlbYi16PqAxUjof+zs7OIRqPY2triK+e3trawuLiIRqOBubk5Ji60p9Fut9n8EY/H+eoQmZDKTCsYDLI7s3hthuM4LIG/+uqraDQaCIVCCIfDKJVKWF9fZ0LmxVioHDGAMDEx0i6z2SzH1qOgwHIcPS8wMQzTM2qv67p8JoiInhitnYgzBSMmQnj9+nXk83kOKUR9R4xX1KRnZmY41BO1j0xcpVIJH/vYx7jsarXK149Q9AfXddmxgK5jabVaHD6s3W5ja2uLzWDiWT/qU9GZx3VPvQwpCoUYQolc26PRKCYmJpBMJtHr9dgs2u12sbGxgU6nw/tPOkuFF/Mi79FcLoeZmRlcv34d0WgUH374YZ/DRTQaZS2wWq3i/fffx9TUFGte3W4XDx48QDKZxOzsLKanp3F4eNjnIq+bM7q5Inp5Oo7DZlcKWeZVrlyejvnoaKCq30y/RwEfOcZlYgIm84ENg/NSp3UMyYt5yWCaUCqcxHyDtonKoYO+hUKBtarXX38dd+/eRaPRwMzMDKamptBsNlGv1xEKhTA5OcleU61Wi/dIdJqQ3NZIJALXdTE5OcmXPJJZjMxToVAIP/VTP4VvfetbfKjz6OiITWckueoYmK6fe70elpaW2HkgkUjw4VYRf53QoQMVoVTlFecnmcCi0Simp6c5CkShUGAGkslkcHBwwAeok8kkdnZ2EI1Gsbi4yFppuVzGwcFB31ynw+M0bqIXInmC/vVf/zVfp0IMpN1us7ed6DACnF5fEovFkMvlOJoGzaNUKoXp6WncuHHjsT4R+7bdbuPtt99GPB5/TGBwnFNzNZmDqWwy6QKnjkX1ep332mTvStVYyRo+4VIqlVCpVJgZ5nI5NBoN7m/XdZFOp/vM5iREkSCVSqUQCoWwurqKtbU1JBIJ7TwQcZHBcRw+fB6LxXB0dMRWhgsXLuDSpUu4ffs2u+bbzHlxfcj0Qq7btG7PUtsCPoKMSzdBZaLh1eleKrGX+q3CRSddeUnlNhPES1tULRYVk3fdU48pcgdPpVL4/ve/j0gkgkQigd3dXRwcHLD5iEI+EbHpdDosHYomENWichyHI43v7OwgHo/zRYrNZhO5XA7RaBTFYhGTk5Mc1b1SqWB/fx/xeJwPCYuETcUsdUSi2+2yQwbFkvNiWqpydAvZltERkHbR6XQQiUQ4gnun00EikUAgEOB9R4obSBpSOBxGtVplh5VAIIDFxUWOvi8eqAbUd24Rwaa9RDpoHo1GEY/HOZJHtVrF0tISms0ma11TU1M4ODjA0tISHjx4gGw2yx6GjnNqim23232u66LQQXNKxInm0PHxMUqlUp+WuLKywpo6efiJMSszmQw7ecggjyONEd2W7TgOmw5JKyS8PvjgA0QiEbzwwgvY3NxEMBhkbTiRSLCmSkdHyMRL/R2NRvvic4pzgyLUkIYq77uGw2Fm7rdu3UIymWQhg+qgWJYkDMlzfxRM5yyZFgDY3Q74HICXqcZkKgLs7LZiOlESM5VhImQqE5nOZKHCxQtX1XMZHxvNQCYUjUaDpdmJiQl+n0gk0G63OTYgLRQyIU1NTXFoG9FNXv6IdVerVd5vunTpEnsLkkZHhGRxcRFXrlxhrc9xHI6VRxvecn2m9oofMncSU1ZFL1eVr6vLFhcCcXy63S5qtRqSySTfy5VIJDA1NYVut4vt7e0+wYBMXBS/j2IDiswpm83i6tWr+Dt/5+8gkUjwfhGNn7jvJc8funvLdV02Rc7OzuLKlSuoVCpIp9P45Cc/iWw2y3VubW3BcRzed0skEohEIozHxMQEotGotr/ksaJbBcQ9IgDsFJTL5fDCCy9genqa8S0UCnjttdf6zgOKDhQm64SIh+M4ePnllzm6DJ3tazab7NwTCoUwOzuLpaUlvPbaa2zaE8t2HIfPyE1PTyOXy/HxAjFdMplkR6K5uTmEw2G+uYGsG6FQCA8ePEC1WuXD5HT0oFAoIJvNIhaLIZVKPRb9xmYees3XJwHnRuPyIsR+CLaOyKvyeanMXnjo6lbVI9ZnwzR1ZXvho5LAxLpJeqvVarw4k8kkHjx4gHQ6Ddc93SwXox0cHR1henqamVEsFutzbtDhSXU1Gg384Ac/4BtwaY/m6tWrfIPy3/7t3yIYDPLBXDpDI2tIqrbJfSuPBQC+nkN+bmKCXnNH1+diGgr947ouu4UTrsFgEAsLCzg4OECtVsPU1BQymQx6vR5WV1e57eTAIXqrUagoivRwfHyMRCKBUCjEt1OvrKzg0aNHHGjXcRzWIIgx/s3f/A27vZMDRbfbxfT0NOLxOLa2ttjDLplMYmVlBe+++y46nQ7y+TzS6TRH5s/n8+zpqRsX6i95TEmLIK2iVCrxwXnaRyMBKhwO44MPPlDOcXl8ZCYm4kKhrojxue7pOcDp6WnWmOgm6kQigTt37rADSygUYguE45zuTdEh+LW1NWxsbHB7CMgT89KlS2xJoIj74rrqdrts7o1EInz2znVPHWCI6d2/f79vfZjmq+7Z04Bzw7gIbM0uXul0gziqgVQxH8JLTKN7pkrv1QY/eKl+U330nIKY5nI5JBIJlEolvvxwfX0dsVgM8Xgc9XqdFxzdoizf62QCMolQBIRKpcKeUx9++CFisRiKxSIKhQKOj49Z+qRQVarLI1V1ejEi0zUTcn9RX+n6UXwv1y/2cSAQwAsvvICjoyPeR6lUKkgkEuwoQEFbE4kE1tfX+dZk0cwmO6kAYEeJQCDAfRqNRvn818WLF/Hiiy9icnISP/jBDziiRiwW43vVCHq9HqLRKJvQXPf0tmK6xZk8BymEluM4rCHS+DabTTx69IjLI4JNTJJMXOJBX92Y0Xm3aDTKeff399Fut1nYIq9Mqk/sf9pXlcN50ScSibCbP0VtIS0qFovh8uXLuHfvHhzH4T3BSqXCHrp0LGBvbw/FYpEZTzKZxP7+Pi5dusROOKJJvdfr4ejoCMViEe12G/Pz82i1Wixw9Ho9xGIxZLNZRCIRPn9J2tzly5fxzjvvIJ1O4+7du4/dcSfPv0HgSTC8c8e4AHv7qlc6sbNFJjPKQVHlUzFNVR4VYTRJ9LYSviq9Ccdms8n7BqlUiu3toVCoLywQES4iQF6MQqyr1Wphc3OT01JYKcdx+C6jcrnMl146zmm8NzJX0QFUG9OcXLfcL3K/6bRoFSOS36nyyWUcHR1hZmYGJycnWF5ext27dzExMYErV67gzp07rB05jtPHpInx6cJrkfBBzwqFAl/kSdeM3Lx5kx1U1tfX+WAwHRReXFzEwcEBm57oYDKVTftArVYL6XQaxWIR29vb7CrfaDT4WESxWEQmk0E6nUav18PBwQEzSiLgdF5KPJsn9yntb4XDYZTLZWxsbODw8JC9DSmALTHHqakpFIvFvuMU5BFJe4KySzo5AE1OTrLTDvDjW7xv3LjBXq7ZbJb3oei8o+u6fD1NoVDgvqdYlKKJTwSaS2tra/jkJz+JQqGADz74gIUOAMwgxZvL33zzTWxubvJ+5s2bN/vWoDhndPNQnKumNWSyeI0KziXjOisQmZdMlFQgamkmExSVo/otliW+U5m4TPn9SFGyNqgi2qJUSpvMtI9BzgGNRgMXLlxgiZs8uvwwD7Gv5D50XZfNM81mk0Mb0b5WuVzmQ6eyR6GXSUTXlzpNmdLq+s5GQFE9c5zTvY+VlRV88MEHuHv3LhznNHrFd77zHbiui4sXL2JtbQ2f/exn4bouHj58iGw2i8985jNYWFjAf/pP/4m1IJ3WSSYuAMjlcmxa293dZccDuh+tVqthYmICc3NzrC3ReayVlRUOtkznyYgxkSZHJryrV6/yAXFiGsfHxzg8PGSiOz8/j/X1dY5dSCZp0j7lOQKANTliMLQfSmbng4MDZqykOSUSCWauhPP09DS77ot3eDmOw4xoe3sboVAIzWaTz6zR4f1sNot0Os3zga79oVuhSVMmK4LrunjjjTdw//59vj6o2WyiWCzy4XqKe+g4Dra3t3F0dISFhQU2F+7v77O348bGBlsfPvjgA3S7XRwdHfFND3LINVumJc71pwXnhnH50RD8lAnotRAv1dqUTyRwMqGzkXzE8uXfuny2aWz6iSTFarXKBGVubg43btzoC1NTr9dZKgXAZhFVe7zwlpkX8GOvMnISmZubw+bmJh/Q9VqgtlqfDQPSzQ+v9lFauRzHcZDP5+E4Dp+roqtNHjx4gFQqheXlZTx8+BCVSgXf+973MDk5iXa7zaGGbt269ZgjjIifWOfOzg7m5+f58DJd8Ei3FYuMwXVdPp90fHzMnqN01ormxMTEBLa3t9HpdDAxMcHaOO3B0WWYZJYjBtHpdJDNZtlrMRaL8ZknMkuqzuiRdk77TmI6SiM6Di0sLOC1117D3/7t3yKTyeCll17iaCyrq6u8X6Qa13q9jna7zcwqGAzi0qVLbBkoFApotVqsrQYCAb7dmM4ykvcgmc6//e1vs4MHBXQOBoMcyxAAe1ceHh4iFotxv5G3aavVQjKZZE2vVquh0WiwQ8/6+rryOIqXpcdmLuto21jjUoCuY8TnJkbgRwvR/TaZEk2qs87EZ5LGVRPNy8Sn0zBkLcqLkdJvilZBcexoQVBMP+A0OOnR0RETOJHQeGmpqraotB0qq1KpcCgd0hBUTMu0GL2ECV1/iuWamL+XQKJqN4WyCofDbM4CwP1PN0u7rouDgwNmEq7r4s6dO7zHKEZGl9tJIaLItEvaK7nYu67LTi4A2AWbIlJUq1UmvHR2jtyyKUTT3t4eyuUyO9aQ04Do0UeChsh80uk0ut0uqtUqNjc3+ZZnMVqHOA/EcSAHHl1/U/y/mzdv8kFo0qDIwWJzcxOO4/SdWxPHqdvtolwu85UndCyk0+lgZ2cH2WwWh4eHeOmll/Do0SNkMhkkEgksLCzgvffeY40VQN++ZKVS4XGjvUM6WpBIJHDt2jWsr69zm0ulUt+1JxsbG3Bdlw/LkxZNQoncfyrwSzN1grwXbRoEHPdp6nsDQrlc5uCuo+bkKqCJpSJoMpgIr837QZ7bmqN0jEAuR1W+nI7s95lMBp/4xCdwcHCAaDSKBw8ecAQKknibzSZf/3B0dPTYgvGa0F6SG+FH5qV6va4kbKa+8apbVacpjdxnXnWpBBnSCuibnl+8eBErKyvc191uFxcvXuTLCn/0ox9xeynosS6CApVNxJRuu6bQRRQgWdS4xOj8hC/tRQGnB37JGUE8PzQzM4N4PI6NjQ2Uy2WEQiHE43G+BkQMWEv9FQ6H+4IzVyoVvttNZsbyR+x7FYh7SOFwGPF4nANDU5gvakMmkwEAjsVIfRcMBrmcUCiEixcv8nGR6elp9Ho9vPLKK7h27Rr+8i//EsVika8A+oVf+AV85StfYRM7mfbkM2xiXRMTE5idnUWpVGIv11QqhU6nwxeg0qH0SqWCR48e9QkoAB47xC2CjQYmC886sFnXwGlEFupfWzgXGpcfMA2GVx4vtVfFCOTybRmFqmyxDpXWpMprqs/EVFV1i+/IHNhut7G7u4t4PM62eFp0dJ4FAHZ2drgsG+atwtPU74SLGP9QfGcq16ZuXZ26eaEbd9N8U/WJHLOP4ip+/OMfRyKRYC3s4OAAExMTbNoiwrS1tWVsC41HIBBgDz/SeEgDI1MZ1U+aBuUjpkq3JyeTSbRaLcTjcQ6GOz09jc997nP43ve+x/jRgWAK2ivGLKRPp9PhK+/pPjSRuMpEVEd4VfNAnCfkMJRMJhGJRFCr1VAoFDjixiuvvIJIJILvfOc7fZrX5OQke7sCp1EywuEwhx4jjevu3btIJpN8tczu7i7+7b/9t/yMPG9FfFVtSaVSvAdHJka63md/fx/hcBidTgcPHz7kfpb7R7ZCyHNQN0d1tM1UljwOo4KPHOMSQaeBmIiQX41FZdqykUJUeJgmlTyJvJisrr0qgqBrT7fbRaVS4cjkFKVAlhZlHG0lYhWY+pgIrq6tcn4/faZjtl4arVyubv54CUQERHTef/997OzssFmWhAYy2clecLr5ROWLcQzFILc2wo2oiYXDYbRaLVy8eBE3b95k0+b09DT+6q/+is13hF+5XMbFixe5vmw2i93dXS6bTHSZTAbZbBarq6scGd+rr+i/PN/E9pNnIR0ZoPNsdGj5+vXr6PV6bEKkPUSKWB8IBDhQM8UjTKfTuHjxIjY3N9HtdrG7u4tqtcrX5kQiESwsLCAcDvOll2SeJPf6mzdvKiOF7OzssFmQvBLpsDJpc7S3ePPmTSUDNPWdHyuBbTkmmjoo+Iqc8Sd/8if42Mc+hkwmg0wmg8985jP4L//lv/Qh8wd/8AeYn59HPB7Hz/zMz+D69et9ZTSbTfzmb/4mJicnkUwm8Yu/+IvY2NgYqhFeIGskJonCloCoBkJHjL00KLlMUUq30QjF96qFqpskJk3GlkFSsFdyBiDTj0rKUxEQr4WkeqZajKrnYh4VEaZnOuFAJbnrQFW+iJtJw7J9Tv1IYahIGyJmcHh42HetvIi/3P+6drqu2yd86MZNnDsUDisYDGJrawt7e3scH4/Cc3344YdYX1/H6uoqawsA2Ank3Xff5byELzGVYDDI5kEKayVqgBTtQ+4723kinncLhUJ444030Ol08OjRI8TjcaRSKQDgIx90IWa5XIbjnN5Bl8/nUSgUeHzoEDcdDH/06BHvZ5VKJbRaLWbsxWIRh4eHyGazmJycxMLCAgfqFfu/2+3i5OQEBwcHHLar0+mgXC7j9u3bODk5QbPZxLVr1x47AiH/Vs0tL4uMKo8KbOb6sBqYrz2u//yf/zOCwSAuX74MAPi//+//G//yX/5LvP/++3jllVfwh3/4h/jn//yf48tf/jJefPFF/LN/9s/wrW99C7dv30Y6nQYA/O//+/+O//yf/zO+/OUvY2JiAr/927+Nw8NDvPvuu4+dWdDBk9jj0g2kjpCbJGcbyVrUfqg8W4nchK/8W6ddqf6LecV8IsEPhUKYn5/H8fEx34UkljWsZDUKsGEQYv979b1pLFRlyAKCiZHJY6aTXIlo69qjEoDEfTK5bF1YJ6rHcRy+lgQAE/l8Ps/OMGI4LPE8HYUbOjo6YmcBIu50kJq0EtG8JRNa2u8iRwrqi1wuh16vh729vce85cSPV5+TxriyssKR5snVXTzPJUbVD4VCuHLlCgqFAp9RI0Zer9cxNTXFmuLk5CQHGqaoFnSOrdPp8IHmZDKJo6MjrK2tKWMJiuNBjiCkbROIsQ5pzpmERnHOymtXN9dNJke5XN07YLA9rqGdMwqFAv7lv/yX+F/+l/8F8/PzeOutt/B7v/d7AE61q5mZGfzhH/4hfv3Xfx2lUglTU1P40z/9U/zKr/wKgFMb/NLSEv78z/8cP//zP29V51kwLi+GQ6CK7aXLS2BT7iDvTURWZjT07UWEvYiy+Js+8pXqcvtV+Mvl+Wn/KEDF1AcBVT+b6jNp0bR/JDMOHc66dKo04n8T46LfcvpAIIB4PI6VlRUcHR1xoN2f+7mfww9/+EOOWCLur9H+FxHkarXKt2mTB5zjnEaWoPN3dLaKnCKojwmfyclJAODQUK1WCysrKzg5OeHbBwCwh6KY3zQ2YjsXFhawsLCAWCyGdDqNtbU13mOjM2FUJt09dvnyZRwcHGBra4sdV6amppBMJvlW6mvXrnHg452dHVy6dAmZTAbf//732VRLh+XFYNQynmJQ4mw2C9d1++7HE7Vlar+JacnPTWlFGmLDuEwwDOMaOMhut9vFV77yFVSrVXzmM5/Bw4cPsbOzgy984QucJhqN4nOf+xy++93vAgDeffddtNvtvjTz8/N49dVXOY0Kms0myuVy38cGZInCBLqFb1OmSQvTlauThGyItooh6d4B6JNgTVqZ6r8OqDzaG5AlZS/8verRSc0qSXwQkM0wfso0CSU2aeX225YnzxN5Dqnw9xIS/NRJETAmJyfZHf8HP/gB0uk0ZmZmsLi42HcUQay70+kgl8shlUox0SOzGkX6X15eZo1HDMUkpqVzgORNGQwGcXR0hJOTE9bsxGtCVETY9MxxTg8o379/H47j9F3ZMjExgYmJiT6c6Fqd999/H2tra+zm/4lPfILNoMSAKLbn3t4eWq0Wtre38eGHH7Km2Ww2+fwhmWtV85OYVzQa5fBZdHWMam54td8LVJr40wbfzhkffPABPvOZz6DRaCCVSuHP/uzP8PLLLzPjmZmZ6UtPV1sDpxuLtAEppyGvMxV86Utfwj/5J//EL6pGLWQQEMsRyxff0XMdEVG98yP922hbKpzov/zMT7/I7RYXh4nx22hfpvdepgaxLt1/FajGQqVBeWm0OlxNY2PCdZDx8NK+VfXYgEi0yFRHBD0ajfJBV3IaIIILgLUBChOVTqeRzWaxtbXFkTyIidE+XTQaxcHBAcf/E83PjuPwRaQUkYIcFAD0hRijdps0C9WzQqHAFoQHDx6wZ2GpVGKmKZvvSGij/Tg620UekBRlgw5nkzegeFkpmU/Fw9jyGAPg2wDokHen08Hk5CQymQzu3LnDHodebaXnujXqRTO91r4OhqXBBL4Z19WrV/GDH/wAx8fH+I//8T/iH/yDf4BvfvOb/H6QReiV5vd///fxW7/1W/y/XC5jaWnJusxRSQriQMoDbkM4ZQJjwllVtmqymJiejgCrmJeqfh3oGLdX+kHKtQWZidm2RZXWRrDww5BMTE6cT/Lc0rVTN+ZeTF7W+FQaoPyM9rXICadarWJ9fZ3TnJyc8H1gkUikb/+n2+3yZZH3799n5wQ6skBl0FUolUoFkUiE71gjpiXOe7rrKxgMotlsYnJykmMKktNEMplkJxU/4Lqn3pUXLlzA9vY2AoEAyuUyB3De2trqY6Kq8SUGf/fuXTZbEt4UoT2fz+MHP/gBB6h+6aWXcOfOHWaQ4t4U5Rf7NJlMcrxIKpcYNu1zyVqaag2qBFjT2jYJp7YwKm3NN+OKRCLsnPETP/ETePvtt/F//V//F+9r7ezsYG5ujtPv7e2xFjY7O4tWq4Wjo6M+rWtvbw+f/exntXVSlGc/MGp1Vied2Gp1OulbR7x05XuVp3ovlmXS+vz2mYqxmpisjZZo0mbEukzt1EmDthqPXI4pnVd7xHxiG3RjPSqJVAXEJEjzoXNRIoj3UgGnWkw2m0W73eZDuXRmieLnESMi8x2VQxc70mFkIqri+SlyRb9z5w4SiQQuXrwI13Wxvb3NOMmEmxyB6G62XC4H1/2x+ZAutJSJv/gt9om4HlqtFl/1QTSnWq323XCsEgAcx+GoGcFg8DHnCLo3KxaL8SHmTqeDSqWCvb095PN5ZpQmfE9OThAOh/Hiiy/ypZ/3799HMBjEyy+/jBs3bvQxLVuhUQVe2tbThKEvknTd07AiFy9exOzsLL7+9a/zu1arhW9+85vMlN544w2Ew+G+NGTnNTGupwmyOUb1XsWIZLCVbrwIrVyfmE4u02aCiQtEXiyqxaN7Jj9XaYS6NprwVGkFqve6xWpqly3o8pn6Wkc4TNqbnE4lKMl12+Ao4plIJBAOh3HlyhU2b1Fd5FpeKBQwMzODubk5TExMoFAooFQqcYBd0ax1fHzM0SxEZwLSlBzH4cO1uv1QSheJRLC1tYWbN2+yc4bsku+6bt+FkYeHh7h9+zbW1tbYRXx/f1+peZjWL/2mfbxOp4P9/X2srq6y27nssRgMBrG4uMgu+tFoFIlEghmU6/7Y5EfMf39/n8/fUT8cHBxgfX2db4PW4eu6p2bKYrGId999F8fHxxyHsF6v48aNG30HuG1Bt27k/iEYVMAdJfjSuP7P//P/xN/7e38PS0tLODk5wVe+8hV84xvfwF/8xV/AcRy89dZb+OIXv4grV67gypUr+OIXv4hEIoFf/dVfBXA6eL/2a7+G3/7t3+YF8Tu/8zt47bXX8HM/93MDNWAYCdUmr5dZRqe9qMr3mgAmzUnHGGWm6VWW/E4sS9bIRmEaUOVVMWw/4yjiqCrbpK0NOl9UdcnasghedYj5vIQVm2c28yYUCuHChQtwXRf37t17LHgsOUSkUink83nedy4Wi9xW+WA57U2J/S8yw4mJCQ47JOcn4h+NRjE3N4dMJoOdnR2OJEF7X2KbJicn+XqQUqnEd5OdnJxgfn4eiURCefBW7hfxv9iHhCNpd+JBbLmsYDCIRqMBxzn18CMhnm4Wput8AKBWqyGbzfL9cMQEE4kEGo0GyuUyt1e1TkVcXdflG8gJKACz6uC/3H6xvWK7xTrlek20SYWrCGdhQfDFuHZ3d/H3//7fx/b2NrLZLD72sY/hL/7iL/D5z38eAPC7v/u7qNfr+I3f+A0cHR3h05/+NL72ta/xGS4A+KM/+iOEQiH88i//Mur1On72Z38WX/7yl63PcMlg03FeeQcFE0FU4TMsgVLVZ9t+EyNSTXQvRuA1ieWyvQQA02/5v602Z9tGr7bJ771w8CpH907VVyY8/AgYRIjX1tb4Isjj42M21VHddLbo4sWLAE4tIqT9yAIT/SctgeoR5yY5T4gamMxQ6Nbk1157Dbdv3+6L6i+nbTQamJiY4P0zMhu6rovNzU0OCixrUoSbaUxE/MV+081nCmk2NTWFUqmEUCiEVCqFhYUFviWBNMbj42MOoiuOx/b2tjI2oSyc2TAjU1rd3JLnj81cEhmZTnBTlT1K+EgH2R2U2ItgWgx+ylGlHTSfzX9VXh1zGMUEHITAq9KayhoEp0HLsskrv5cJvI5geJWt0pKAH/el+EzU6uhMVTQa5Rt2Z2dnsb29zftWdAg3k8kgFovxoV4yz8nBbVX1OM6pSXJ2dpbNieQxSAduReIXCARYGywWi9jf3zdG7iDtkbQ9lVblRdZUQpasoaraRc9oLzCZTOLq1at48OABX3KZzWYxMzOD999/n0NyBQIB5HI5ZnaJRAIHBwd9JkixT20Yli6dScuUGaIsSNisR5v+FfHwEhbGQXYtQEWc5ecENoRfNTgqKUYntakmkpxvEObh1RYvnHX9pEvv9c5WM/Ca7IPgYspnqksHNu3TjZmX1igSSJlYy6Ar29TXpBVMTU1x7LxUKoVIJILZ2Vm+DiOfz6NYLPK1KLT/VSqV+vZRVO1wnFPPuomJCRSLRb6sUXSVlw/HUh4dMxe1KNd1eT/NRtvQgdzXqvWmGwPHcfierK2tLVQqFWZSjUYDm5ub7FUo9lEul+P/tVqN9+VMWpL8TMVsqHxVHtO8lNPbMC0ZFxkvE90YFXzkGJcfDct2EOTJbUN0bTQaP0xLlU5HmE0LUs6rMwWoFoDcJjmdzSIx9YOOWdjk0eFq6gcTA7BhemLb5d/ye1MZurbp0ovlix/gx9ePZLNZvPDCC3jw4AG7YB8dHfHFhGJIJrrmvlAoIJ/P4/79+33RIwjo8LHjOKjVarh16xZfOCqe0+p2u313RzmOw/d7UbBZIvrpdJq9E2XmRX2h+vbqRxNDsul3us6EonWIAXHFe+fEcuhG6JWVFY4rSR6I8rktEyMTmb44t3Rak0xHVH1hy8wcRx0x4yyZlAqG9ip8HkEnleiYlm4x+JFWVFKPVz55EXlJk3I6WyZKeUztVL33apMX01cRIK92eTEaE7M25VPhY8LbVJ/pt/hRaWk6nFVlqN7p0gYCAVy6dIldyG/cuIGNjQ3ef261WuxiPjExgXg8josXL/I1GdVqFXt7e32ea2IfuK6LixcvsrMFXUwZDoc5okU2m+VbfeX9HDJDihE4otEo5ufn+7QUeRx0zEz3UY2j2HeyRiGvJcc51bQymQySySRrTXIwXNH8R8+IWd29e5dNinRJpIy3qZ1eOKvmhU0a8bdpnqnqVzFqHXjRMRs49xqXqjNtOteL0NlIcCqtQ5Vf9c6LIJrKsJ08JinM1D5dHbaaiAoX8dsrryqd16KRx0L8bcNERLBtm9i3KkIgj5dXubImJb8Tn4lnsSKRCFZWVjA7O4v9/X2+pdhxHJTLZQ76Wq/XEY/HkcvlkEwmMTk5yWkpQrsqAC7tqbVaLaRSKUxOTuLg4ADNZpM1qGq1isPDw8fuCxNxb7fbODk54UsmKZwTMQqKzq5jVKZx0PWlPJe8hA7a2yoUCmg2mxz9QsRDJuSO47D22m63UavVUC6XUalUEA6HjdqVzHAGWZdye3WCoK58eZ2pyjYJvYPQXy8494xrlCqsTORNg6wjhF4E1i8R0/3X4W7TBhlfFf6mRWRiCCqcVM/9tlFXjokgmZi/CeRxVtUvMy3RYUK8UdurXTLYMD/HOT0TRe7uvV4Pu7u7ODo6QiqV4nNKuVyOrxGJx+P45Cc/iQ8++AAPHjzA0tISm/MajQZisRhef/11fO1rX+vzEAR+HCm+UqmwY0Iul8ODBw9wcnKCer2OSqWCVCrFIY9kbSYQCCCfz2Nubg6O4yCdTnNEjmAwyAeSaU6pmJbNvLEdYzEvRaeIx+PodDoIh8OIRqNwXRepVAqlUqmvL2TcwuEwXn/9dXb139/f78NV7g8V01K1wwS6dopMxlYYtQEvhjlqOHdehX4npinPIGWJOHlpAKMaVB2T8CKMNhKWDohADsKY5Hc2ddrWMYqxVGk0pjJ0mhOVQ6ayw8NDAKd7HeSlZ4uPjJdJ64pGo5iZmeEbhWu1GhzH4Sjt7Xa77woQKicWi7GJb2JiAlNTU1hbW4Pruhw3UIwGIWt45MDx5ptvolarYWtri8NDua7LzJT2g8QyyGkkHo8jGo3iM5/5DHZ2drC8vIxvfetbrMGJOOg0Bpt1oPK8NHljplIpLC8vI5fLYX19Hc1mk/es1tfXuQ6KQyhrXeFwuC8wr4r56hiKjdajS6t6rtJQbdeRbs4Osu4Ih7FXIQbj8CZpYRhGKH7L9dhqJXK5KnxVE07FGGyYhSqPqg5duV59oarbhtnqTBSmOm3feWmZuvp0i12lbUWjUVy+fBnFYhGZTAbb29t8iFTXNlljFM1/KryIeVy8eBFzc3PsOEBaF0W9AKBknBS5gZwsyuUy3/SbTCZxfHysZBT023VdvjTy6tWrKBaLfaY90uBUfUXv6QDvvXv3EA6Hsbu7y/tycuR5lcZgK7zJz8X+Fd/R+1arhVKphI997GPY29uD4zg4PDxkU2Y4HMb09DSOj4+xt7fX127VwWIRDxMTlkHHtMQ5J6dTPdPVoypH7BMdbrq1cVYa13PPuEaluXgR8mHKG5U2YVOOKOXpytQ9UzEW0wRW4Sjj4xf8aGEqZijiqGqHiriZCIQJB1Xd9FxmJnQFPRHgbDbLV9ib+k/8JBIJdiun6AsiHqTxHB8f4/j4GMFgEPPz87h//z5L+XLgWrnNrnvqCk/msKOjIw6Qq2IWYp8C4MPGDx8+ZEaluxjSdfsvtxSZ5vb2NhznNFzU5cuXcXx8jKOjI6OWqtNYxGc6YSwWi+Hy5cs4PDzEwcHBY8yLzqN997vfRSgU4nepVIrPb5GLvuzqr9NwRHxVjMHEjExgomVyXar1IedRlaOrl96b1s0oaPZzz7i8pGAZdJK/iWDaEDFT2TZahzyZVBKpCk8dEfbSBkSwxUnETW633JdyXlO/qEDXB7qxEX+b+trv+NqOvQp/OudDRC+RSKDVamFjY4P3n8RDybpyRMZ15coVJJNJfPe73+V9oXq9jnq9zpcarqysYG1tDaVSiWMMitfTq/pOhKOjI2SzWSSTSY6pp8NNLqPZbKLdbjOT8WIivV4PsVgM4XCY7/iiC2fL5TIODw/xgx/8AHNzcwiHw3zg2MSk5Lp0c1rEIxwOo1Kp8JUoqv6nIwPBYBAvvvgiGo0Gcrkca2PHx8cIhUIIBAKPxTWUcdIxLapT/FbhbWIwqvWnq8umv0SBcBj6qMJ1UHjuGZfcaX60G1umZ0NoVQzEhJtOWpff6/A1MTUdzjr8VRqDXJ6KsarSqAQBlSSmI2iqNuiYlg5MGpWXJOrFKG0gEAggEomwK3gwGEQ2m8XR0VFfgFkVg1XhS59arYbV1VVks1nk83nk83nWrMLhMLuf04WCxWIRd+/efSz6hJdm0m63cXh4iOPj477r4GXc5DZEo1FMT0/j4sWL+Pa3v23sIxGfdruN5eVltFotdhi5desWR+ygKBOZTIbDO+kIsF9BjsZrYWEB1WoVyWSSI9oXCgU2d5LW7Lou33kVDoe5DtIcq9Uq8vk8x1tUMUoV07IRnlRjoGqbqRwvIdAk1HrRxycJzz3jGrbTbLUuem8zeF7ESDdJTczA1E4Zb5mhyWWoGKqXZmezMMSy5fJ1ONuUqXtno4l5MXhZotTVYQuO47Dm0+12+QqRvb09XLhwAZubm317RTq86D89i0QivIEdDAYxMTGBWCyGRqPB5jVyPT84OGDnCFHqVxFRVZ/Jmpmu/WLf0ieZTOLOnTt9z0waB3C6f3Tr1i04jsNalajl7e/vA8BjDFiFv24+mBhCJpNBo9FgN/5YLIZLly7xDcPHx8dYXl7G/v4+R/9oNpvIZrOYn5/na13IhEgMTuwjVR/rmJaKfpgYjQ0DGlTT8gJbBjhqeO4Zl99Okie3LQG1YSCmOsVyTYTAT31ei9OPhmKTT8UATIxZfO6l7Xn91xEjm/zitxdD1rXLjxbmuqcXEiaTSbiuy1oCmZFEgi4TKLnfxN/dbhfZbJbNZtFoFKVSCYuLi9jZ2UGr1eIwS41GQ7l/JjIxWbjxC6rxiMfjcJzTO7sajUbfPVamQL0EotOIDbOVn8uE3ma8ms0mNjY2cHBwwOZdOnd2cnKCdruNcrnMjIzqmJiYQC6XQ61WQyQS4bTi3WMqRiXjrFs7pjSqOSSnNY2pPMdV68Km7/zSrFHBc8+4bIihKv0gzM6mfBNO4juTlOUHF9Uzr0lH71VMx4tp+xEU5IVnIwnr/ttI/TbE12ZuyP/FPDZMi4jW1NQUtre3kcvlmIC32204zo/3tlzX5QjtlF9VT7fbxaVLl7C7u4vd3V2Ew2EEAgFMTExgdXUV9XqdCazrupiYmMDly5dx48aNx8x9VL7MtLz6TzXvROeTubk5bG5usrmN2hkOh5FIJNDr9VAq/f/au7bYuI7z/C25Fy6X1IoUKa4oKZEsuwliykYqJ47VIHYjx0Vg1ShSII3rhwDtS5rYsFAXQZ08SA9FJASo0wZpG9QNEgdBoBfbRYC0qWXEVmoYrlXJaiRZVeVIoq4UJV6WFC+75HL6oJ7T2dFc/plz9sr5gAW558z8889//vlvZ/acYtVuStGwy7IzlZxVbSiGm+87NzcXOt3gVSW9vb3o7OxEpVLB0tISLl++jKGhoXCXZiqVwtzcXPhSyHw+j8HBwfDNx6lUquoxTjp+VetX1kY2V1OGpXKApu+8HHWytHFYcWVjbfnIJ4pxEf+aohMb+rpxVUpEpSlblLqsUTW3QNF0TlZGW/ZdZyhMfKr68bzbGFSKA7ONJHleqKhUKrhy5UoYfZdKJUxOToYZV/BopLVr12JgYCDc8i1eE/776OgolpaWwqi+WCzixo0byOVyoZEtl8thOWt0dPSO18Dz85H9NbWRtUun0+jt7UUicXsDSZDxBW9IzmQy6O3txd133y19Jp+N0+IzN9XmD/Gp8qZ3VAXnZ2dnwyfXB7sjg/PLy8u4fv065ufn0dXVBeD2749mZmYwPj4OADh9+jS6urowPDyMdevWobu7W8q/al66AEyn4yqnZWvXXEBZSxQbYIu2dFwmiFF6vdJbgG4AVQ5FFZGrFj2fKcnoUWmYoFNg0TCpImSxvWjITfzyWRElStQ5RpMz1UGcZ/BG3uDRRUG21N3djTVr1iCdToeZCz9nfj6JRALT09PI5XIYGRkJfxDc3d2N3t7e8EkOwW+Gbt68GWZ5sgBJVZ7ij1FKWMDtezrZbBb9/f1hFhhkWtlsFqlUCgsLC7hw4YL0esoyEtm1Fh2QLGvk5SXrr7pPxtjtTDl4AeTVq1cxMTGB6enpqpdFZrNZTE1NYWpqCqVSCaOjoygWi2G2du3aNczMzIT9dHrPy1m1Tl11XBzXRsdt2pgCX1WbqFiVjgu403nZRNMu0C18U/sA4oLkFdNUytRlZeJ325KgjJZsAcqiSqozsx0zymLRGQORtulaBg9jzeVy4c65wKgXCgVs374dfX19dzgvAHd8Z4xhfHwc//Ef/4GFhYUwkxsbG8Ps7GxVhrG4uKh8XQaFf5vsuKOjA6VSCYlEAnNzc+EOx3w+j3vuuQddXV0olUqYnZ1FJpPBunXrqjYw8LR1eqPjU5d1yOYgC6YYY9i+fTtSqRQmJyerntyeTCaxfv16bNy4EQsLC+jp6QmfPrK4uIjR0dHwWYrB0++D33Xp5Ge6FrY6rgpuTetTB6rT0wXVcdvXtnvkkwq8IaYYeiqtKNBlehQe4+KDOrYpq6I6PFXUL0biqu8yHkVegvYUnkXeTJmmGB3zjoZvE7xkMLivEzwnMIj6gwfZlkqlcKt8sViscjhi1hVsrw9+rLthwwaMj4+HmzHErIJ3ZgCq/vLHebmp5hz8FTPDgJd0Oo1MJgMA4Q9ze3p6wtd3LCwsYMuWLdi0aRNeeeWVqleBiIFd1IDSZo3z67CzsxM9PT3hW595BO8xu3jxYrg1v7OzE8lkEr29vVheXg4fWsz/7MEUtOoCJaqOy+jo1qRJxwNQH0umg86eAG6PfGp7x2UypDqHYOMYXJ2IKmKkQhWByYy/OCcqz5R2umxEJUud49bx4MKPrL+KDoUn3knx/XgnFhi0IPvYtm0bZmZmkMvlwoetBg9tHRkZwfj4OGZnZ3H9+vU7fusV0A+cRnDvKJvNhs/v452R+LDXoH86ncbi4iI6OzsxPz9/h+PSRf3BuHwWGBwLDHgymUQulwu3iQfP6CuXy5iamsLS0hLS6TSuXbumfOagjhcV4grsKDrJBxHB61cKhQIWFxcxPT2N2dnZO540opqPzGFTeTc5RJGuKVuT9XFxXDZ2BfDPKpRCpwgmw2WTlfGG0BTtURSUevF1UaRuTjaZCKUPxQHI5GCah+y8i1xk/W0yMUob2XyDFzEmk0nMzc2Fv+m6detW+JT2SqWCsbExXLp0CR0dHejt7Q03MaTTaSSTyfC3THym09PTg56ennBXHJ8BBe+EAhA6k5WVFWzZsgW/+c1v0NPTg4sXL1bxaor8E4nbPzLu6OgIdyoGr0cJfmQd7JacmppCLpfDZz7zGfznf/4nlpeXUS6XQwfW29uLmZkZ6eYRqtOirDcTHdk14/ur1mbQpqenJ3zcU39/f5htBaVb1Xx0AYJqXFl7VbYqG8cmGBcdnYy2rm+t0Vb3uFQpM0AzrDqaupQ8OKZSdl20o4o4KYZT7EtZHBT6/KLXGTNVGxuFl/FOjbSpxk3FrylK1clVJxt+rtPT0+ETFLLZbOiI8vk8HnnkkfDHrJcuXQo3XFQqFeRyOWzbtg0dHR0ol8thebCjoyO8ZxZExPl8PnQeQfkxk8lU9UkkEhgaGgp/C1YsFpFOp6uMn+kTbLwINlyk02ncd9996O/vRy6XQ6lUQnd3dzju0tISLl68iHK5HL4SJJ1Oo6+vDyMjI1W/iZLJm+p0+DmIOw5NH115VTwvlv6Cx1UFjipw5vzPD6hOSwXd+jM5eN52iTKTOTwTfZsMsNZom4zLFC26ghqp22QMsuOiklGMvclB8nRUfWS0bTMSE30VPZE3XRvZuCINWUQpjm2rCyb9kZ1PJBLhlukgA8rlcpiYmEA+nw+fLXjkyBFkMpnwfVWBHIrFIhYWFrBhwwYkk8nwqe2MMXR2dqKvrw/r16/HzMxM+Ggh/l5L8JLDIOMKypqVSgWFQgG5XA5zc3MYHh4OH61EccTLy8soFovo6+sLnzZx/fr18OWIQVYVZCJr1qzBhQsXwm37g4ODOH36NFKpFN5//32Uy+U7xqAayqjOQJVJBeOq9Jl3qolEApcuXQrbTE9P49Of/jTefvttqeGn2CiTjptomaoA/PGAvyCbptDT8V+PTCtA2zguVZpdT2FGBb9YqBmRqkTC0+P7yNrxx0TjL3NkfBvxmDiWyxxVxkK1KHWGiCJHE2zpJxKJMCvJ5/PIZrNYWFgIDfXc3Fy4W23Lli2YmZnBhQsXQnpBdB88Ib1QKGBsbCx8Zl6pVMLMzEyVbILnFGYyGaysrKC/vx89PT2YmJhAV1cX1q9fj0wmgzNnzqCjowPT09O4fv260WkFYwQZF4DwMUhr165FNpsNH3wb/H5szZo1mJ+fRyaTwezsLFKpFBYXF3Ht2rXwd2j86+3FcagQnYjp2lB0nKcr9lHJBbh9zcvlMn75y19WZXy2c9HpuGxMFS3ZPPlzOtthex0aYWNb3nFFzajqCQqvusyLYohV2RA1K9L9L5uH6NhsnIUsW1JlTFRQeJBBtaD58zL+ZeMyxlCpVNDf34+FhQUUi8VwM0U+n8fVq1fDLeujo6Ph09t5dHZ2YnBwMHwixtDQECYmJpBIJMLsJngxYzabDXcsDgwMYHR0FCsrK8hms6GjyOfzmJiYQKVSQSqVCp0Hb6R0kX3gUGdmZqq2vPf29obZX/BA3M2bN+ODDz7A2NhY+MqP4F5YInH7cVDivS2dsdRlVzIdEq8Tf41M/4t0ed502QyfYVEyI9k4qvPi/yb9VNkOGc+ywNMWjbDBbb+rkAclI9D1tR3LxuiLkC0saolDVFaRno0DlfGl6y8zJCaHoHK4FB4pY5j627RTjRPwm0gkkM/nUSgUkM/nce3aNczOziKZTKK7uxu3bt1CR0cHhoeHce7cufB+CP9eqnQ6jWw2i3Xr1oVZ0/LyMvL5PNLpNKanp9HV1YVcLoeFhQV0dXWFT2o4efJkuOkj2PgRbM1OJBLYsGEDNmzYgHfffTfcVWiT9fDz7OrqCrOrxcXFcC7B77aCLC344XXw2KeJiYmqHY2845RdF935Rui4ajwdbdWcKE5L5qhtoZKTDLY7Cal2VRaUA6t0V6GN0aIawjigc0im8oMYOerai2OZokLKuGIbk7M1GXZZRM+3l/Ftyr5sMz1Rnjw9ajTK95XNMfge7Lo7e/ZsmF2sWbMG2WwW09PTKJfLuH79elXWEZQBgdv3kgLDHpQYGWPhY51SqVS4OSIYb3JyEleuXEFnZyd6e3vDLA9AmFlVKhWMj4/jgw8+kBonPmPQBSaBQwqcY/Bm5YCm+MSOrq6usN/69euxuLiI+fn5KtnLslfxOH9e9b0eOi7yRYn9dTzLaOicKn9ezJQowbIKNg5StoajtLNFW2VccTmeRqS+Oojpf3CM/863dQUlSxSP6ca3oac7R3FQNtl0lKhVXITisUQiUfU7J/54Op2uevq52EcsqQUbLoLnGgZPhQ82a/T09KC7uzv8oW86ncbly5eRyWRw+fJldHV1obu7G1euXAl/WxQ4GNXuO5VcZQj41t3PCTKzYHNJMplEV1cXbt68qX38ks4xNJuOxzGuzlGLDtek6y76rRvf1M92zYvzcMm42mo7vEzJXOkA9Cio1uAXshgpygyprJ/umEhLd1y1iHXOVdVXdk52DSmZAMWYuPCl6qc6FjgD8SGvlUolfEyTbPt1LpfD2rVrq35gnEjcfvpG8CPe69evY3JyMnQG3d3d2Lp1K/r7+5FIJDA4OBiW7NLpNBhj+OhHPxq+TiV4pmA+nw9fgiiTgc6RiX34TEvVZmFhAfPz81hYWMDc3Bzm5ubu+JF00FbmBJtVx6l6oxuXp2WiR81cbByrbeaoG0v2XbZO4kgKWr5UKIJaNqIIzyWyokKWOekiF3ERqDITPnKiLlKKzGR9VcdUc1ItPOrYpshbZeBk8xMDAd15FY+qY7LzplJNZ2cnNm3ahCtXrqCrqyvcgTg4OIj5+XkkEgksLi6Gr8vgr3NXVxempqbwP//zP1heXsbNmzfDB7wuLi6iUCiEJctMJhO+8LBYLIbOQsebbG7Uc8G8g3tswW+eZLKS0WyUjssyEIp8+HF0GZGOpimj4s+Z5mTj5KJAxYdtxYWKtsq4AsRxsWRGMq6LzNNTKanqgqt400Fc6LJI0DZbdXVyIk9iO53DpnwX6aicpU6+wXlKhKuK+MXzusygo6MD/f39GB0dDXfp9fb2olQq4cKFC0gmk1i7dm344+XgDcjlchlXr14N7yndunULmUwGIyMj6O7uRrlcxn/9139hdHQUALBt2zZks1kMDg5i48aN6OrqIhlX/rs4H91HbB9kWTJ6JtRKx3W8m8ZS8aiTqUpGKlo6erJzIk2TfuqOqeag4oNKw2dcsIvWqVEKYB8pqM5FjYhk9IJ+ujRcPKaKUmVZAT8O39/G4escgy4IEOelk6kqu9GNL2sjo6eaj2l+qnYy+QdjLi8v4ze/+Q0ymQw2btyIvr4+pFKp8Ldbk5OTYIyFPypes2YNbt68WbVBAkD4SKWJiYlwi31wLwlAuMtwYWEBk5OTVdvhdQGAKcPRHdf9T1kbOh3X0RXPqfiyhU22oMusdDrOrzedI9bBFBTbOCpXJ1pLtNXmDB7ihW9HyMpQ1DnL2qicu4yuqT9/LODRNngwQXQAKoesO6eDTp6yY7LvOgfN/w3uPwWvOJmZmQlLhMEuwuAeWCqVQl9fH6anp8MfOA8PD+PmzZs4c+ZMuMGju7s7/OFvpVIJf0tWqVQwMzMj/REwPz/+rytc6MiuVy2hC0Z07Uw6xv915ctmvaj03BRY1MsFqGS06jdn8LApN1GOUy6uLj2njkVpq4osbUpbpqhLFrG5ZKmqkpuJR/6vqo1qV5puLJMB4Om5ZsN8FmPSqeD8ysoKUqkUisUiJiYmQsfS1dWFdDodbrYInoxx6dKl8AfBFy9exPHjxzE0NISBgQHMz8+jp6cnfJpGsPNveXkZS0tL4VM7TFviTQ7NdH1MMjDJUtbXJFMVr6o2AahrRuVIgvVCnTfVaah0UTYnVSBlCp5UY/Lf43BuYvUhCtq+VChTNFOZyhRJm8aipvIiXCJ7UQlMEaCqVBZ8p8hJ1tYmgzJlc5TMySay1PEh0uK/6xwYtWTCXx8VzwGKxWJVm+ABu1u2bEEymcTFixfDV4V0dXVhaGgIk5OTSKfTGBkZwblz51AsFrG8vIzp6WkMDQ3h6tWr4e/FVlZWwof46gynKaDRzZH/rssAAhom425TJqMYbpUuqXiTZc2qwE90JnHquGmu/PiqtSm7HqagT8erCaq2tgGhDC3vuCiG3kbYLgYwLkS5yOLi1hljnWLazl8XEaqiRJkhEY2HGN3qxqAsPtVx3aJ00QHdvFU0+awraJNIJMLHQo2Pj2N5eTl8j1aQaV69ehWdnZ2YmprCu+++i3K5HL5QslKpIJ1Ohz9GDuSk+92WbSSscn4qg8+fo0TxKgMexXiqeNM5ORX/wXfxvIpOVB1XOSKZ45XNn+K0TGiEXZSh5R2XCJnhVQk77oigUQ5P5AHQZ4+6TEn33cawm+Sqi0J1zkXGk2ruFB4pgY6MlinbVPUJjunai0ZxcnIy/F1XKpXC5s2bMT8/j6tXryKR+P9HRAX3sZaWllAsFjE6OgrGWPjcw5mZGczOzlY9lV2EyZiJvNnqi8phmjIIU1vVeZEXCi1VhhJA97u1eul40Ec1X/GvSI96DXQw9amlLWzbe1wU6CJj2XdbeiKi0g/6qPrxxkQ1lsn56CJAmRFW8SaLSGWZh4ymKpqV9VUZRltaKp5UPOpkaMo4dNdd5DfInoJP8APm4PmFwWaNjo4ODA0Nhe+HWl5exuTkZPjD5nQ6jZ6eHhQKBSSTyTuic5NeiR/V3HneZX1lkPESHFcFXqoxVedN11DHV/CR/WBaNl9xzLh1XNVOBupcdaCsnXqj7RxXlKzHFAXxY9SSvomGqp+sFCAqrmphB32Cv6romD+vG181nm7BqqJTVXuRF1WmJLanGg/+nMlAiHRUxlvkQdVf5C/4TE9P4+TJk5ienkalUkEmk8HHP/5xzM3Nha8VCZxcKpXCRz7ykfC9XoVCAR0dHchms1JdMY1t0hsX+YjylemWydkH/VVG2jUA1V1Pvl2jdFynQzodMzl2Fc86uNpEV7RlqbAZoDOotRxLNrZsocgWAMW58e2o52SLVJfZiXMTv6siUJnxMhkcl/mY5K2bm8iPrHwl8s8buyDyD579Nzc3h8nJyXA3ImO3H8OUSCSwvLyMsbExjI2NoaenB0tLS+GbenUGLvjOl8R0zsmUUchkJeqa7C9PXxyfbxsck/XV8WsKdGwyjUbquIo3SgBAtU0UHa0n2uJ3XCbFr5UTifuCqaJNncKrFqsMKudlilQptFVGWmckosqOIi/RaYvyMjkal3FUEbWqr8iXaNgTif9/CG/wvbOzE+l0GplMJty4ETi1gE4ymQzvfyUSCWQyGdy4cQNr1qzBjRs3wo0cPF/8X5v56kBxOlTY6g11jaiyK1mbZtZx3ZjitbaxNfz5KPOS6c2qfK0JIE+/VcYjTkcTd5RhiqBU50yRnMzA8MbSdmxKVCs7psr8bMfStdMZDj77lLWn8mWav8l4qQy+yvhkMhls2bIlfEty8LT4QqGAubk5lEqlsB//SKVkMonBwUGk02mcOXMmzMSCl1OKhkyVJZnmxOuRCir9oDhJ/rhNWzEAEM/xfymZSCvoODW4MM1FN/8odi8um9nyjou/mKJhrtfYzUpTt1Ao0SG/4ExZhGocU9AgGmtdVKcymPxiVvEpm4vOien4phok2diyeZjaBJsqLl++jJWVFWzYsAEDAwMAblcfOjo6kEwmq56EwRgLdx52dnZiaWmpykCrXuIoyojnT2WQTXPXyUscS+RHdh1sM1oRvK1QZSGtruPiPCnXSsZzs6LlHZdJaWxhivYo45lKCjq4LhgX8HzKFpKLbG0yXVlbk8ExHbPl01WOpkhfB9VcVTpWKpVw8eJF9PX1YXZ2FhMTE1UOKplMYsOGDWG7oFxYqVTCl1DyY/DGTGXQTHJV9ePlKpuLqr2sjcg31Vnp5K8z5O2m4zwPLqDoci2CdwraZleh68URoboIYsRjohFV2UyIk55ozFTnxTY6OYh9+OMBZFG22CcwgjI6OuMpQnbt+PFM81fxThlHxZdqfHFumUwGn/zkJ5HNZpHNZrFu3TpUKhXce++94Xu5JicncePGjZCG+Dgs1TgyHnVtTLJSZbCqPtSsQHX9ZHRUc9I9IqwddVzXn4I4A+240TaOS2UwVMqlA8UxufaNC7bzMbXXGSRVxKiLDgPDRXHgsqhVLIuIi5s/JvJscioieB2RGUCdUVRBp498G1lAxPOTSqWQTCbxwQcfIJvNYmFhAcPDwygUChgfH8fAwAA+8YlPIJPJ4Hd+53cwMDAgNb46hyTOX1fGks1RbGPSC5GeSp9kBl1WLlNBFhio0G46HtVpRQHF6UdFy5cKA8iiPMAtIohSQnIpN8i+xzGOSia6sSjGSdXHZhwZbCI8cW66+ciMhoxnSsRvA35s1f86+ozdfuVJIpHAf//3f6NcLqO3txfnz5/Hhz70IeRyOXR2duL999/H8vIyzpw5E76bi+qkVOObnJZqnnG3sQlCTBmeSk8paCUd5/l1hav9A9SOOU60jeOiXtRaCFE2nmmcKA5WXESqMcVMwbQAZGPoaMn44M+b5K4y5rIMRMa32F/kTee0VbKzySpUchcjaBXvPK+yeQPA0tISrly5gkQiET4lo7+/H9evX8f69esxMzODtWvXYnJysurNxwEdldPSzVE2H9lx2THbLMxlPYqyU2UlVP5EfmTfW0XHXR2Wynbo9FtHi59LLext25QKZTBFcDYRtqqt6jjlwlLoqGjLFqNsbkFb14hMZuz48VTRoTiGbvFReJddR1EGlOhURkdmHFTGX5y/iqbuOw+Z3Hhe+M/KygquX7+O06dP46677sLZs2dRKpUwPj6OUqmEdevWYXBwUCprfh4yefLtZf1V86AYJV1QqWunWieq4MyUXZnWvsyxtJKOqwITylrXXVsbfZbxbcMHFS3vuGycj+15Slvbi6pqozIWrohz7oA6epfRMzlSEx82vLksUr6tLnoUHQeVD9FJyAxqAMoCF53X0tIS3njjDczNzaG7uxulUgmLi4tYWlrCjRs3wnay/rpxRIepa2uav6mvzAmIbU3GNJgnJYtU0VHRDnhpJR13CaLriTj5aHnHZRJGnF6+FWGbWVHa8Q8b1RksHhSl1S1QVQYkRtym6N5U6hH78P1sXlypygpkjkxnIMV58217enrQ3d0dPgLqypUr0qdhqDIpcRzV3ES5UuYvG8fklHTHRT7FB97aQJyrzuDbVCoapeNioNII6HSnFmh5xwWojafOkIltZd+p56KAGim6jm8yOHw7akQkM6YBDVs+dQ5TFamqyn08byZaKuMrKwupjItsHpTxTc5ShMzRJRIJbNu2DVNTU7j77ruxefNm5RZ4kY6tgaVWFUxrL0rELXPcqjYm3kwlN7E9j2bTcWrAybe3gWld8fxFzSxt0BabM2yjN5VD0wlZZvgox0ygto+66HkjzP819aHwwhtTU1/xvMqgy8a04UlHh/+rMua68VZWVu44b1PqVV0DU1TN/18qlXDkyBFks1kAwPnz56VOSyVrFa+2OszPxURLFuDo5Kwy1CJNyjq3qcxQ9LjROh5HIGvT3jaorXUlrC0cFw+KgCmGG7A33tRIVrdIxUWja+/i9KiK6OIoVYZJRdvGMNgYLJEfFR88r67XjxoIiGPyf01BkGwMxlj4vMHFxUWUy2VlCVc2B9PcVE5Ol0XpDLQ4R1Nb0xzEvtQMT5Rh0E7XV+RDzH7qreMqhy7ybRo/Duiuay3Hb3nH5SoYqoOjjG2TbVCdkMnBRHUsNn1sx5IZHFXkrYJKHirDw5+zjZ5tjsucsmjE4lqsMjmK2R5jDOfOnQvPudCkwDbQMRk0FW+67Io/HtDkqwmydjpHoHJAqnayzFLnlHTnZeeoOi7+Vc1fNb5LJmly0CqogryoaHnHBeiVztQnaqYE0EsBKtQyIrIZxyWrMdHT8aFb3KqMQ8eX7jpQDSBFBiZjpQLVuKgyMNl32ZiqtrJ2rtEyxSnoQOHRlMmY1jBFz/i2KicgG0dlkMXzceq47JrHbW9cA2XbbDEq2sJx8aBeSNuIwyXaqCfiiPKpBtqFnsowqQyvzAjqDKuu7COjKdJT8WIjA9V8485wbUppOlActW49mAy5jG/ROFNgc+1M61RsJ86DGqiYnJmMN92cTDoe1zWvFSgyiyvbAtpkV2EURDXWNheiVkpX6+gmbgTRMv9qDQqvYjtx4VOyKh1tXclFpCcra+l4DubLfxf7RXVaumPimFTdEAMD6jl+fJUMxDaqeaiuq6gLFH7Ea6yioeob9LHJum0DF5EnUYb1gOmaNhpt47iohs+2T9BO1TaOiNwGlHIBpTRiom/TnmrEdf35/3XZj0yGsutqw5NrtkrpI7s2It8q5yr7X5YhyCDLLMRymCpjDb6bypWyObo4SlO2Jru+OidjuybF8VVBBT+2ypZQ17iNjuvWuowHG7jYNapeUMdyQVuVCk0GyDa7iuIATHRta8biMZc6Nb/o4pqTzOi4zo3STja26rqK8ooafOjkbzIo4vlgk4WKF7GPrBwma6PiR6bL1PIYVV9cgxd+PIo+UTIfHY/UtWNafzKHYsuTqr0us6bwLqOl0zcTdHxS7WicaJuMS0QcqS7FCLuAUuuNomQmmjqnEWUMm2hT104sjVDKJLIsRmYEVZGymB2osiK+jY4O/79svqpMbGVl5Y4SKp+JqsZXjR3AVCLTzUWWAYj8imVQmXxsHRt/vVTZia2BtylvirzK+sqcKiXgVTllqr7bQGfHbOXmOn7caFvHpYNt9NgoHnjYGO1a8xInTUq0pjJ4qvmqjJxsPPF4sMjFzFSMxCllKl3EboLMgMmcEZWOjk8VAhm4BBKikRdlRil5UTJmSkatm5uJf553fi66a6kLDHVOLeo6dgHFkYuIK9CNgrYqFQL0cpUJjbogKriUzIDqxe9SWlHRi4OW7bgiDzx4nuKMVE282JRPVOU3iixlpUVd1qXTCbE9JXujXHNZlktpJx43BRkqWjJ5yv7X2QiqMzbJw6QDMlnV02GJoOiJ7LrI5kHR06iIlHHt378fiUQCe/bsCY8xxrBv3z4MDw8jm83ikUcewalTp6r6lUolPPPMMxgYGEAul8MTTzyBy5cvR2GlCqYyRbPAhSdK5sXDxblQFq+r04rrOvClKvH68kbJJlsz8SYaPVN2JfKqmgfF2Ltk6HwZT/UxrQ1KVqvKIsRMxcSvSxuV7GQ2gOpsVFkIpQQo40ukIdMN23URtz2Lq1pTL2fs7LiOHDmCf/zHf8R9991Xdfzb3/42XnjhBXzve9/DkSNHUCgU8LnPfQ6zs7Nhmz179uDVV1/FwYMH8dZbb+HWrVvYvXs3KpWK+0w0cM3AZIK3KU/p6AZ8US4uNTU3zZFaWqplJhUlI1JdC2oJSyz3yGiaQIlMxbFk/UxZRRRjH7Wvim+Vc5ZdU921UJVQdXOn6KVY7qX21TleFT9UiFUAPuiRyYhqb2yyRUoQZQqeXGxCLe2Ik+O6desWnnrqKbz44ovo6+sLjzPG8Dd/8zf45je/iS984QsYGRnBSy+9hPn5efz0pz8FABSLRfzgBz/AX//1X+PRRx/Fxz/+cfzkJz/BiRMn8Prrr8czK5iVzRR9A/KIkVrX1kFWP6e2pyDKQouz1OaSPZiyPd5ZqRYvn22IDk00RirDzI9jOzexbGlbkqIaWtVxMSBSzUW1BnRy5duIslOdt5Er317Fk00kLzpEGS+m7Ei35qlZukhT9VoWio7rxjIdj9PeuK6ROODkuL72ta/h8ccfx6OPPlp1/Pz58xgbG8Njjz0WHstkMnj44Yfx9ttvAwCOHj2KpaWlqjbDw8MYGRkJ24golUqYmZmp+thCXMi1jAbiQC0vOmWxUfuZMpyovKhAzXyC/8XsjBJhRi3fUMaRnTONrcvW+PmJ7XSGTWxDzfJlfOmO6RyHLttT8WsDHS88P+I4VB3XZYqiQ3LhV0a7lqg1/SiwdlwHDx7EsWPHsH///jvOjY2NAQCGhoaqjg8NDYXnxsbGkE6nqzI1sY2I/fv3I5/Ph5/NmzeTeKVEgPx3VwNMvcCULI86po4OJaJy4Vll1CiLV8eL7rupvUhfF0WL2ZcqohbLOmJ/FX3byFbVVxdYqXRI5rBUfSnGVDTYOiOu40nVTja+jHcX4+mSAciycVGmFEfH95Mdo8wnio7HCepatK0oxAErx3Xp0iU8++yz+MlPfoKuri5lO9kFphh/VZvnn38exWIx/Fy6dInMs42zsKHFf6dGU6qyVBTeXJxqVAeq491lMekMHAWmcp9qTL5sI3sJo2ksGU3d2GJGpGqrCyxUc1U5FlUWKBo/SlAiOybORXctZPMKjrlkuOK8ZOPy53QGVjd/lbNWXUOxn6wsWA8dbxTqwZOV4zp69CjGx8exY8cOJJNJJJNJHD58GN/97neRTCbDTEvMnMbHx8NzhUIB5XIZU1NTyjYiMpkM1qxZU/WxBWVxUEs0soWgMwAURImedM6JkhlEhUuWBKh5tJGhTTZHoSXLYnR8qQymLlOjzNeFdxl92yzQ1ihSAydddC47R80qVFmzrq1sbP67bJ2bKgOy663LsBqh43E5FFNAWA9YOa5du3bhxIkTOH78ePh54IEH8NRTT+H48eO46667UCgUcOjQobBPuVzG4cOHsXPnTgDAjh07kEqlqtpcu3YNJ0+eDNvEDV6x41i4lKi71mk8D0pWRDlfL6WjyogiQ2oGZAPR8OgejisrL8l4lAVFspIUhTfZODZ9g/Y2pTORV12wxP+lViNEuqqynQiKHvNr3xRE2QQPMplQfmJg4t+mjY2Ox2WTGmk7Alj9ALm3txcjIyNVx3K5HNatWxce37NnD771rW/hnnvuwT333INvfetb6O7uxh//8R8DAPL5PP70T/8Uzz33HNatW4f+/n78xV/8BbZv337HZo84IS5EXbnD1F8H3cLgyyKu9KmwoWdqGxdvMjou14KKuK5p0FakLYvIbXiPkmmIvNnoZtBep4dipqbiSxYUqrIRlf7r1oSMd3EM07xssjcqbzJ6YiYexd5QEaeOR0U9nVfsT874+te/joWFBXz1q1/F1NQUHnzwQbz22mvo7e0N23znO99BMpnEF7/4RSwsLGDXrl340Y9+hM7OzrjZkcKU9suOR734JsMWt6GyMRL1cqgyGVCvRS3gOpZr6UYn54Cuytjxx8RzLsGAio+oMlGVwFTndVmQih9bPXUNOHXBpuikdPRaVcd1uigbp56OK8HqnePFgJmZGeTzeae+UZWGckFdjb1ugdhmT7aKFzeijGlTNjNFtVGi7SjtXJxCVL2xqRzI5GPSP5PTlbWzdaK1zE5csllZf/F/V1qtruNiH1cUi0XrfQur8iG7UUDJwkyLO/hfVYsXj4nKqltAlKwmLqiiasqYrlmLrJ1sQfNtXB2NaUxxLB78fQ++rey6q+jpjvH0ZPqh4kvUD5We8DT4trpMSpUNmvTClJ2Y5kQxmqoyooqG6rrp+LDhqx10vJFou4fsmlCv7ENVkpP9b+qnoqGjUw9E4SXO7KMRMpEZfh1EJyOLknWGSTS8YrRNib5l46vaqrIi0TmZZC9zCLKMj+8rc5g66LJBldxU8xXPB6+YccFq0fFGOLZVmXFFjdzioG2KiF34qIUC1VImOlBLGnGPW0s6KsMafFQ70nQlIlkGpTPgYoakgi67kGVeqv68sxP55PmQOY4oa03mwE1ZbfC/7Dp4Ha/t+LZYlY4L0N9Qpab4OhqmCClqDZkSJVPomBBHCSLKXKOUW+KKSm3KSzZQBR+yspSqdEcdh6qX/HFZhqXL6GT9+fFlzlD8bqpK6DI03Tn+GM8Lz4OuDOh1/M7vjSwhrrpSIQWu6bsNbEuWptKPK11XvuIqubqWVF3oxtnXxLeJjo2cVd9tSl668XlnJAuQVOU/XRYoa6MLDHVO2bacqCqnBqCW/7yOm3W8UVi1GRdwZ7Rnahsn4lAAl6zLdA9CF+WajKYMNnKLU8ZR5GuK9Kn0o8rIVA42ZWZ8uU7Gm1jO48+JGRP/V6d3spKlzPjJxtY5KxWPqvmJPJsyKq/jdjreyGwLWOWOSwZTqSDumrON0Yoyjgo2Cmwqk1Lpq86bnKqJT/FcXNdCxltUUCJuVQakgqzMqPoEtFRORXZMdBYyY68rJcmckTiGzjnKrg+/Lk3z1dHyOl4bR10r+FKhAGp5xba/LvK15UN2Po6yFE/bVIa0UXKXkgRlDFmpitrXRM8E13npjtmUZmyuKcVwi+PZGnsxexL505USZX11c4nDcHodNyNKKbLW8I4L9AukigJd+satFDpacSl43AtFVqaiQraIo8jUxbm70KOU2aKOH1UOrtBlWPx3WVamy9RqBa/jelCz3kbAO67/g6tCuCpRLSKZekRIUaJLEVGiv7iMDqUvdT61lr8qixFBaRMHL42A1/HG6XizOC3A3+OqArU+Tzlea35kUNXP4+QxymKNwgfVcVBgywdf2tL1l0XHUcdW0ee/63RTd8/G6zhtDJs27arjzeS0AO+4lDDda9DdRObPx8WDbHzTorUpQdXCAKj4aTR9UwlEJgPqvQW+r8xp1EIGKpo2909k372O22M16HgzwDsuAVSltr2pajM+NfJ0uTeioxe1DNNsUZkM1GzJ1F6FKPdBVYhLrrY8eB2/E6tRx5txzt5xSWCzcynudvxirbfC2N6MFc/VMjKnoBZllLgMJgViRlCLLM1lE4TXcX1/E404UW8db0anBXjHpUSUlFzWxuXGp63BqoWS6XiIU0ZxIK5rIaLeu9yoWYYLXy7lIK/j0WjEiVbX8bjgHZcCjYgEZTdEo0SD9ajpx4m4NzOoaNiWRlRyjcpL1LnZZnKmY7WG1/HW0vFmlql3XBrU++LJbpbrShvUexBxRYO29zFs+8sWT5T7TSq6tpsWdOdd74Hxc3Odl8loq/QkLrm6wOt4a+h4s8M7rjrARRl1i6JRSmezc0tmlG23++oWY1RjTzlG3UDgAtuSnSyiNhltlbxsjRwFXsft+8vaN4OON3OmFcA7LgJMES3/v00d3yVad80CXZXUNaNQfaf0j+owbK+F6hjlnk2UrDzKDfS4dwiq4HX8TrSzjreC0wK84yLDpCCUkoVoBFxuClNvvMpq2KYyhQ0fsjFsz6va85EshYZsrpS5RUUgU9fFb3u/xvV+ju19JRWPXsftz6vaN6OOt4rTArzjsgKvZDY3lAO47OgyjaU6T919pKMTVZFVZQ+KfILvFKOiizAp2bLNeUo/V7nW6n6OTq66DMXruBntouOt5LQA77iswRsPnXK6KpNuTNfzrjAteptxeZlQSnCqMVXj2zoDarmGSo96XtYmilxl/W366Ayi1/HVqeOtAO+4LGF7I1ZEPW46uyqrKfKLalCp/V2idhfeXMpYJpq247iMFdXR2fTxOm7HRyvqeCs6N++4HBD1xiqVhitqUfeOsmh05ZlGLZpa3JSm3hSvxTgiqNlQlHl7HW99HW9FpwV4x+WMOGvj9YLJaLneRzBBVteX/R9Fpo28HuI9IYpca20wVHLVXYta8lAveB1XoxbBWqPgHVcEtFoE42K0opZkbHZMxV2Tr9e1EHd4udznsgVF91zk6rLDrZngdby2/ZoF3nFFhG2NO2rExe9sjBu1KHVRFqrrTjTK2AFcd8+ZEKVsHHeZjhL1m3YKxuF0vY7rx220jre60wK846o7oihtsHXWlUaU3WdxGdkoET119xX1vE2GpKPrclM/6rgiqNdHNqbuHk8tdgia+nodN49BPR+HjjcjvOOKAa4RYi0iS12EFcW4murjUQyn2F+3vZcyXr3KJy4GP87I13aHq+12aipd05hex+/s3wgdr2UmW294x9UgRNnJpINsEcYVbUW9yR8lmrRtb5JTHDfpXQy+bfmOMn5Ug1oreB2vRjPoeLvAO64YIUY0JiUWa+OUG+46Za7nTjUTZNFqLYyLDKJsqU7KpXwTB+K4x1JPeB2/jVbR8XbKtAJ4x1UDyCJNSpmGcuPYxhi7ljriQC23XVMzDdv6vi5L0hnfdjEK1Hs9tlu9vY67046q4+2imyK846oTAuMXVZFsjHEtFxYFcRoVakRpM4ZNW53xpRiNOA1IrYy1TrcoY3gdbz4db1d4x1UjyBawrHRCpSX7W0u48Ggq+US5p2O6n+R6U97W0FINlVg2crnuqjHiNNZx65LX8ebQ8XYsD/LwjqvGsNkEoKr/ixGobVnAxTDb3oim3s+g0jbRUEFWuqLch6HyQHUaMuNNNeimfnEYJNuNE9TdbrL2snHFY17H6TDpeDs7rADecTU5bIydKtqzWUQmg6Ez4uIx15KTbgyb0kxcZSNbo833c7kWtZKrbgyVXG0CL1d4HW+8jrcavOOqA2Rpu41BsDV2tdiVZbvRwUTHtY1Lmcw2snahFUfk7cpT1HFk/WXX27X8pxvHdFzVxuv4nX3avTzIwzuuBsEUZdlCVYKRjUsdq9kWQRwLs1alHZf+pvnUK5qmytXWWXgdt8dqcj5R4B1XHaFTyig374P+lGO646Z2jV5QrpswTKUfFz7i6G/ayFAvebvKVaRBaeN1XA+Xa7EanZ13XA2AStF09fIoO9+ignozmxoRx8FLHGW0Wi52Cp8mucru59Rq112c9Gzvj3kdl9Nz2cizWuAdVwNhU56xMb61uHnu2s4lyqaUz3i6NjezZbRqAfG6RblOsns7rrxTSqVRdqiJOwS9jssRh46vVqcFeMfV8rApdcSh6KJRszFMcTsUlcGr906rqA5URq9W2UecmyAo9GtRmvU67uEdV4MRd9Rks1vJhQfRqMWxDbnVQXGg1LkHGUs7yLVWGcFq1/HVnGkF8I6rCeCS9tvUv01tbaPFONCIXV9RaEUtn1H71nMnYa1pRZ2L1/E723mndRvecTUR4t5wELXMY6IfBVHuKdR6TFPfWsi13mgWubrQXY067h1WNbzjajJEVVCbLcM2PFB3XZnoxI1WW9BxXou4ESWrrCe8jnt4x9WEMClqrRVZdjNctetMhBgN16K8IYu4G7W4a72lXpxfcMx1WzxlN5v4v45WrZyd1/Ha/OyhXeAdV5OCamDiHpOy9Zh6c1w0BnGBusvMZFTjMDi1LPOotsGLW87rBdGYihsXeCNeD7m6oJV03DstNbzjamLUWnFF+rY7qEzQ0YrjxrWptGPKIOKerypKbtRvjnTQlcpMmy1MRj1uuUZBq+q4d1p6eMfV5IizHBOHQZX9VqmWO+VMRtLlvoQMUbIEkYdaOZY4+ul4lP3wNQ6oHCIlU3YdK0Cr6bjfOUiDd1wtgjgMtKyvrTGxKanYGKY4ymm2NMV7Fa5lv3qUQ008uMJlK7vtPViKQ4+yU1A2lo6fZtVx77Do8I6rhaCLxuI0/LbGmVKq09Hm28Z5U9p0L8xlY0dcTooaWVOvhczo1mrjBFWuNnQo16JdddxnWfbwjqsFoVt0cdwUp25+cKXP/5Wdj+OGt8wYqIy6rDRGiY6jyIWa4VGvhWmLuKs8KZlDve4ZtaOOe4flBu+4WhQqQ1uL7eFxGj0KPds5uIxjKgdRjEoUg+1aLo3D2NmU5UwOUUc7brSbjnun5Q7vuFoY/NZjcTGbShiyklzcCylqJK7qL/IsMwJxZAE2W6J1JU5qWcqlxOYC13t5lHa13MbeLjruS4PR4R1Xm8G2Tq8qJ9V6YcW1w6wZtl1Ttt2bUG9D1gi5RsmgqWXPZtdx77DigXdcbQLbReFSIooT1J1bVEcQx7bnKKhHFmQL3fzi2rJvszmBirhk0Uw67h1WvPCOq80Q9wKJY5dXlHZxzMf1PoTN9uU4tzrX8hrWctcm5XgUOdTK+Ndax73Tih/ecbUhoiwU6j0Lm51/Udq5RK1x3XexidijRveUDRMmQ66at4zPemQDYhXAdreoze+pbPmi0I1Dx73Tqg2842pT8Bs3qO2B+m0Q0PGgG5OSMegi+7hu1Me5s48Kyk5Im7H4ax7nfHi6cWzJtxmb0q4eOu7vZ9UW3nGtAlC3Wdv2ibsdhQdqpmAqY5mi6VpvXjA5nVref5MZ8KgZGMVB1cqQuzqiWui4d1j1gZXj2rdvXxhFBZ9CoRCeZ4xh3759GB4eRjabxSOPPIJTp05V0SiVSnjmmWcwMDCAXC6HJ554ApcvX45nNh5K2NwvcCmRUA29aeu4rI/qXBTnYXJajd6tGOW3bDZypW7VN41JQb030NRbxz3qB+uM695778W1a9fCz4kTJ8Jz3/72t/HCCy/ge9/7Ho4cOYJCoYDPfe5zmJ2dDdvs2bMHr776Kg4ePIi33noLt27dwu7du1GpVOKZkYcSvNOw+Y0SBdTshXc4rhlPLQ1IMzgtHi7ZhC7jiev+X9A37qxFNoYr6qXjPstqAJgF9u7dy+6//37puZWVFVYoFNiBAwfCY4uLiyyfz7Pvf//7jDHGpqenWSqVYgcPHgzbXLlyhXV0dLBf/OIXZD6KxSID4D8RPolE4o6P6nhcHx394FyjeHOdA//dhXfTvKPKtZ7yi3MOUedULz1q9Dpuh0+xWLRxQ4wxxqwzrrNnz2J4eBhbt27Fl770JZw7dw4AcP78eYyNjeGxxx4L22YyGTz88MN4++23AQBHjx7F0tJSVZvh4WGMjIyEbWQolUqYmZmp+nhEA3OMvsU+Nu1U9BkzvxiRwptp/DiQEMpGiYT51So63k3ztuEpahsgmtzEMWxoiX1d5RHlWog0TG1qpWMeZlg5rgcffBA//vGP8W//9m948cUXMTY2hp07d2JiYgJjY2MAgKGhoao+Q0ND4bmxsTGk02n09fUp28iwf/9+5PP58LN582Ybtj00UC1A1aKkGhQbwxOHMQnOi4YrbuNCod/KBk0XXOi+29CKi74LXco5Hd/eYTUHrBzX5z//efzhH/4htm/fjkcffRQ///nPAQAvvfRS2EYWdZkU2NTm+eefR7FYDD+XLl2yYduDAH4xyq5HvRerbTaoylyiGE/dOPx3lzGjZK5xoV4ZkatcbfuY6ETVce+wmgeRtsPncjls374dZ8+eDXcXipnT+Ph4mIUVCgWUy2VMTU0p28iQyWSwZs2aqo9H/LDNvlTnRQPhApdSkUt0HXVMHXRjumauYmZpGjMOHlyvoaps1ygHwPNB5SlYE95pNRciOa5SqYTTp09jw4YN2Lp1KwqFAg4dOhSeL5fLOHz4MHbu3AkA2LFjB1KpVFWba9eu4eTJk2Ebj+YAv1BlWQUP2X0f8Vw9QOExQFQnR2kbl8EWr4WMdtAurntFMhpxGW8KPZ2DroUTkem4d1ZNDJudHM899xx788032blz59g777zDdu/ezXp7e9mFCxcYY4wdOHCA5fN59sorr7ATJ06wJ598km3YsIHNzMyENL7yla+wTZs2sddff50dO3aMffazn2X3338/W15eJvPhdxXW/1OrXVlx7/CK+7zLfJtZRvWUa3A8Lrm68Gs7TqPX2Wr8uOwqTMICly9fxpNPPombN29icHAQn/rUp/DOO+/gwx/+MADg61//OhYWFvDVr34VU1NTePDBB/Haa6+ht7c3pPGd73wHyWQSX/ziF7GwsIBdu3bhRz/6ETo7O21Y8agz2P9F8wnCUxii0I8CU3+X84mE/RuZXeYhjuEij7iuhQgVPZVOiP1UcnWBTi4yfmzGYT7DahkkWAterZmZGeTz+UazsWoRp2GMw2HVA1H5pDqVKOPwfV0dn62h17Vvpmurk38LmsC2QrFYtN63YJVxNQu8ojUWccu/Va5nHHxSaEQZh+/rQse2j6l9s13bZuPHw+2atORDdvlHSHl4eHh4tC5c7HlLlgpXVlZw5swZfOxjH8OlS5f89ngJZmZmsHnzZi8fBbx89PDy0cPLxwyTjBhjmJ2dxfDwMDo67HKoliwVdnR0YOPGjQDgf9dlgJePHl4+enj56OHlY4ZORq57FVqyVOjh4eHhsXrhHZeHh4eHR0uhZR1XJpPB3r17kclkGs1KU8LLRw8vHz28fPTw8jGjljJqyc0ZHh4eHh6rFy2bcXl4eHh4rE54x+Xh4eHh0VLwjsvDw8PDo6XgHZeHh4eHR0uhJR3X3//932Pr1q3o6urCjh078O///u+NZqku+NWvfoXf//3fx/DwMBKJBP75n/+56jxjDPv27cPw8DCy2SweeeQRnDp1qqpNqVTCM888g4GBAeRyOTzxxBO4fPlyHWdRO+zfvx+f+MQn0Nvbi/Xr1+MP/uAPcObMmao2q1lG//AP/4D77rsv/EHoQw89hH/9138Nz69m2ciwf/9+JBIJ7NmzJzy2mmW0b9++8On7wSd4gTBQZ9lYvwilwTh48CBLpVLsxRdfZO+//z579tlnWS6XY6Ojo41mreb4l3/5F/bNb36TvfzyywwAe/XVV6vOHzhwgPX29rKXX36ZnThxgv3RH/2R9H1oGzduZIcOHWLHjh1jv/u7v2v9PrRmxe/93u+xH/7wh+zkyZPs+PHj7PHHH2cf+tCH2K1bt8I2q1lGP/vZz9jPf/5zdubMGXbmzBn2jW98g6VSKXby5EnG2OqWjYh3332Xbdmyhd13333s2WefDY+vZhnt3buX3XvvvezatWvhZ3x8PDxfT9m0nOP65Cc/yb7yla9UHfvoRz/K/vIv/7JBHDUGouNaWVlhhUKBHThwIDy2uLjI8vk8+/73v88YY2x6epqlUil28ODBsM2VK1dYR0cH+8UvflE33uuF8fFxBoAdPnyYMeZlJENfXx/7p3/6Jy8bDrOzs+yee+5hhw4dYg8//HDouFa7jPbu3cvuv/9+6bl6y6alSoXlchlHjx7FY489VnX8sccew9tvv90grpoD58+fx9jYWJVsMpkMHn744VA2R48exdLSUlWb4eFhjIyMtKX8isUiAKC/vx+AlxGPSqWCgwcPYm5uDg899JCXDYevfe1rePzxx/Hoo49WHfcyAs6ePYvh4WFs3boVX/rSl3Du3DkA9ZdNSz1k9+bNm6hUKhgaGqo6PjQ0hLGxsQZx1RwI5i+TzejoaNgmnU6jr6/vjjbtJj/GGP78z/8cn/70pzEyMgLAywgATpw4gYceegiLi4vo6enBq6++io997GOh4VjNsgGAgwcP4tixYzhy5Mgd51a7/jz44IP48Y9/jN/6rd/C9evX8Vd/9VfYuXMnTp06VXfZtJTjCiB7fXyzvGm10XCRTTvK7+mnn8avf/1rvPXWW3ecW80y+shHPoLjx49jenoaL7/8Mr785S/j8OHD4fnVLJtLly7h2WefxWuvvYauri5lu9Uqo89//vPh/9u3b8dDDz2Ebdu24aWXXsKnPvUpAPWTTUuVCgcGBtDZ2XmHdx4fH7/D0682BLt7dLIpFAool8uYmppStmkHPPPMM/jZz36GN954A5s2bQqPexkB6XQad999Nx544AHs378f999/P/72b//Wywa3S1nj4+PYsWMHkskkkskkDh8+jO9+97tIJpPhHFezjHjkcjls374dZ8+erbv+tJTjSqfT2LFjBw4dOlR1/NChQ9i5c2eDuGoObN26FYVCoUo25XIZhw8fDmWzY8cOpFKpqjbXrl3DyZMn20J+jDE8/fTTeOWVV/DLX/4SW7durTrvZXQnGGMolUpeNgB27dqFEydO4Pjx4+HngQcewFNPPYXjx4/jrrvuWvUy4lEqlXD69Gls2LCh/vpjtZWjCRBsh//BD37A3n//fbZnzx6Wy+XYhQsXGs1azTE7O8vee+899t577zEA7IUXXmDvvfde+FOAAwcOsHw+z1555RV24sQJ9uSTT0q3o27atIm9/vrr7NixY+yzn/1sW2zVZYyxP/uzP2P5fJ69+eabVVt25+fnwzarWUbPP/88+9WvfsXOnz/Pfv3rX7NvfOMbrKOjg7322muMsdUtGxX4XYWMrW4ZPffcc+zNN99k586dY++88w7bvXs36+3tDW1vPWXTco6LMcb+7u/+jn34wx9m6XSa/fZv/3a43bnd8cYbbzAAd3y+/OUvM8Zub0ndu3cvKxQKLJPJsM985jPsxIkTVTQWFhbY008/zfr7+1k2m2W7d+9mFy9ebMBs4odMNgDYD3/4w7DNapbRn/zJn4TrZnBwkO3atSt0WoytbtmoIDqu1Syj4HdZqVSKDQ8Psy984Qvs1KlT4fl6ysa/1sTDw8PDo6XQUve4PDw8PDw8vOPy8PDw8GgpeMfl4eHh4dFS8I7Lw8PDw6Ol4B2Xh4eHh0dLwTsuDw8PD4+WgndcHh4eHh4tBe+4PDw8PDxaCt5xeXh4eHi0FLzj8vDw8PBoKXjH5eHh4eHRUvCOy8PDw8OjpfC/rfkOi9V+1tMAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -314,7 +316,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -373,7 +375,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -406,7 +408,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 27,
    "id": "75e97201-addd-4c53-ad4b-18cb72dc3d6f",
    "metadata": {},
    "outputs": [],
@@ -452,24 +454,37 @@
     "    plt.ylabel('Time (s)')\n",
     "    plt.xlabel('Implementation')\n",
     "    plt.tight_layout()\n",
-    "    plt.show()"
+    "    plt.show()\n",
+    "    print(df.groupby('method').median())"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 28,
    "id": "6bc150f2-b82d-4d0a-9520-16be1077454c",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                                          time\n",
+      "method                                        \n",
+      "iterations = julia_vec(Z)             0.010208\n",
+      "julia_numpy_arrays(iterations, Z, c)  0.007970\n",
+      "julia_numpy_naive(iterations, Z, c)   0.105095\n",
+      "julia_pure_python(iterations, Z, c)   0.012355\n"
+     ]
     }
    ],
    "source": [
@@ -483,7 +498,7 @@
    "source": [
     "From the benchmark above, it is quite clear that simply using numpy arrays as a drop-in replacement for a list-of-lists is detrimental for performance.  The problem is that accessing individual array elements from numpy arrays is quite slow due to type conversion that are handled under the hood.\n",
     "\n",
-    "Using numpy array operations is slightly faster than a list-of-lists implementation, and using `numpy.vectorize()` yields the best performance in this case."
+    "Using `numpy.vectorize()`is slightly faster than a list-of-lists implementation, and using numpy array operations yields the best performance in this case."
    ]
   },
   {
@@ -496,7 +511,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 29,
    "id": "986d1e58-d5a3-44d3-bebf-650753f4e57d",
    "metadata": {
     "scrolled": true
@@ -504,13 +519,25 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                                          time\n",
+      "method                                        \n",
+      "iterations = julia_vec(Z)             0.044188\n",
+      "julia_numpy_arrays(iterations, Z, c)  0.018800\n",
+      "julia_numpy_naive(iterations, Z, c)   0.464113\n",
+      "julia_pure_python(iterations, Z, c)   0.053993\n"
+     ]
     }
    ],
    "source": [
@@ -522,26 +549,38 @@
    "id": "b181599f-9e91-45c8-92da-8a3ac9f0b417",
    "metadata": {},
    "source": [
-    "In this case, the implementation using numpy array functions only has an edge over the `numpy.vectorize()` implementation.\n",
+    "In this case, the implementation using numpy array operations is by far the fastest implementation.\n",
     "\n",
     "However, as illustrated below, results also depend on the size of the data."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 30,
    "id": "92a5c2a5-e81a-4153-b05b-e65de8600aed",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                                          time\n",
+      "method                                        \n",
+      "iterations = julia_vec(Z)             0.039988\n",
+      "julia_numpy_arrays(iterations, Z, c)  0.038036\n",
+      "julia_numpy_naive(iterations, Z, c)   0.424582\n",
+      "julia_pure_python(iterations, Z, c)   0.049861\n"
+     ]
     }
    ],
    "source": [
@@ -550,19 +589,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 31,
    "id": "f3d6e8d8-dd84-49d5-a3f4-db0993329d87",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                                          time\n",
+      "method                                        \n",
+      "iterations = julia_vec(Z)             0.168675\n",
+      "julia_numpy_arrays(iterations, Z, c)  0.076183\n",
+      "julia_numpy_naive(iterations, Z, c)   1.900526\n",
+      "julia_pure_python(iterations, Z, c)   0.224786\n"
+     ]
     }
    ],
    "source": [
@@ -582,7 +633,7 @@
    "id": "0ebc3685-2848-4d17-9bd2-73713c5333f8",
    "metadata": {},
    "source": [
-    "Overall, using `numpy.vectorize()` seems to yield the best performance.  It is interesting to note though that for this particular problem, the difference between the pure Python implementation and the best numpy implemenation is not that large."
+    "Overall, using numpy array operations consistently seems to yield the best performance."
    ]
   }
  ],
@@ -602,7 +653,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,

From 9284039940323f43152625866add5e692200e2a9 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Thu, 31 Jul 2025 17:47:49 +0200
Subject: [PATCH 07/14] Add pure Python version of Ising model experiment

---
 source-code/ising_model_pure_python.ipynb | 2275 +++++++++++++++++++++
 1 file changed, 2275 insertions(+)
 create mode 100644 source-code/ising_model_pure_python.ipynb

diff --git a/source-code/ising_model_pure_python.ipynb b/source-code/ising_model_pure_python.ipynb
new file mode 100644
index 0000000..fa5b470
--- /dev/null
+++ b/source-code/ising_model_pure_python.ipynb
@@ -0,0 +1,2275 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6c7321ac-f110-42a1-9db0-1ada19ea6a58",
+   "metadata": {},
+   "source": [
+    "# Requirements"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "d2854c99-8bdf-48d8-aa37-ebd05709e1d3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import abc\n",
+    "import collections\n",
+    "import copy\n",
+    "import itertools\n",
+    "import math\n",
+    "import random\n",
+    "import statistics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "65063840-c7c9-4bc4-b4b3-ba7a3c7ff1da",
+   "metadata": {},
+   "source": [
+    "# Ising system"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "083aedf6-aeef-4f05-96de-bd753958ce5f",
+   "metadata": {},
+   "source": [
+    "An Ising system is defined as an $N$-dimensional grid of spins.  Each spin interacts with its nearest neighboours, and is subject to an external magnetic field.  Here, you will only consider a 2-dimensional system that is defined as $s_{kl}$ for $0 \\le k \\lt K$ and $0 \\le l \\lt L$, so $K \\cdot L$ spins in total.  Conventially, spins are denoted by $s_i$ for $0 \\le i < N = K \\cdot L$.\n",
+    "\n",
+    "The Hamiltonian of the system is given by\n",
+    "$$\n",
+    "    H = -J \\sum_{\\langle i, j \\rangle} s_i s_j - h \\sum_{j=0}^{N-1} s_j\n",
+    "$$\n",
+    "The sum index $\\langle i, j \\rangle$ denotes the sum over pairs nearest neighbor spins, where each pair is counted only once.  Periodic boundary conditions are applied, so, e.g., the downward neighbor of a spin on the last row will be the corresponding spin on the upper row, and similar for the other edges.\n",
+    "\n",
+    "This Hamiltonian will be used to define the system's dynamics (see later)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "99cd95d7-d7ec-4250-a0c1-792167760962",
+   "metadata": {},
+   "source": [
+    "The implementation of a class to represent Ising systems is straightforward.  Note that this implementation is *not* efficient."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "13c127ad-a665-4c74-8d14-29370e205438",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class IsingSystem:\n",
+    "    '''Class to represent 2-dimensional Ising systems of `nr_rows` by `nr_cols`\n",
+    "    spins.  The interaction between the spins is characterized by `J`, that of\n",
+    "    the spins with an external magnetic field by `h`.\n",
+    "    \n",
+    "    A seed initializes the random number generator for reproducibility.\n",
+    "    '''\n",
+    "\n",
+    "    def __init__(self, *, nr_rows, nr_cols, J, h):\n",
+    "        '''Initializes an Ising spin system.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        nr_rows: int\n",
+    "          number of spin rows\n",
+    "        nr_cols: int\n",
+    "          number of spin columns\n",
+    "        J: float\n",
+    "          strength of the interaction between neighboring spins\n",
+    "        h: float\n",
+    "          strength of the interaction between a spin and an external magnetic field\n",
+    "        seed: int\n",
+    "          seed for the random number generator that initializes the spin values\n",
+    "        '''\n",
+    "        self._nr_rows = nr_rows\n",
+    "        self._nr_cols = nr_cols\n",
+    "        self._spins = [random.choice((-1, 1)) for _ in range(nr_rows*nr_cols)]\n",
+    "        self._J = J\n",
+    "        self._h = h\n",
+    "\n",
+    "    @property\n",
+    "    def nr_rows(self):\n",
+    "        '''Returns the number of spin rows in the system.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        int\n",
+    "          number of spin rows in the system\n",
+    "        '''\n",
+    "        return self._nr_rows\n",
+    "\n",
+    "    @property\n",
+    "    def nr_cols(self):\n",
+    "        '''Returns the number of spin columns in the system.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        int\n",
+    "          number of spin columns in the system\n",
+    "        '''\n",
+    "        return self._nr_cols\n",
+    "\n",
+    "    @property\n",
+    "    def N(self):\n",
+    "        '''Returns the number of spins in the Ising system, i.e., the number of\n",
+    "        rows times the number of columns.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        int\n",
+    "          number of spins in the system\n",
+    "        '''\n",
+    "        return self.nr_rows*self.nr_cols\n",
+    "\n",
+    "    def __getitem__(self, item):\n",
+    "        '''Accessor to get a spin value.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        i: int\n",
+    "          row index of the spin\n",
+    "        j: int\n",
+    "          column index of the spin\n",
+    "          \n",
+    "        Returns\n",
+    "        -------\n",
+    "        int:\n",
+    "          value of the spin at row i, column j\n",
+    "        '''\n",
+    "        return self._spins[(item[0] % self.nr_rows)*self.nr_rows + item[1] % self.nr_cols]\n",
+    "\n",
+    "    def __setitem__(self, item, value):\n",
+    "        '''Accessor to set a spin value.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        i: int\n",
+    "          row index of the spin\n",
+    "        j: int\n",
+    "          column index of the spin\n",
+    "        value: int\n",
+    "          value to set the spin to\n",
+    "        '''\n",
+    "        self._spins[(item[0] % self.nr_rows)*self.nr_rows + item[1] % self.nr_cols] = value\n",
+    "\n",
+    "    @property\n",
+    "    def J(self):\n",
+    "        '''Returns `J`, the strength of the interaction between neighboring spins.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        float\n",
+    "          strength of the interaction between neighboring spins\n",
+    "        '''\n",
+    "        return self._J\n",
+    "\n",
+    "    @property\n",
+    "    def h(self):\n",
+    "        '''Returns `J`, the strength of the interaction between a spin and an\n",
+    "        external magnetic field\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        float\n",
+    "          strength of the interaction between a spin and an external magnetic\n",
+    "          field\n",
+    "        '''\n",
+    "        return self._h\n",
+    "\n",
+    "    def __repr__(self):\n",
+    "        '''Returns a representation of an Ising system that allows to recreate\n",
+    "        its original state for reproducibility.\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        str\n",
+    "          string representation of the initial state of the Ising system\n",
+    "\n",
+    "        Note\n",
+    "        ----\n",
+    "        This representation *can not* be used for checkpointing/serialization.\n",
+    "        '''\n",
+    "        return f\"\"\"{{\n",
+    "    'nr_rows': {self.nr_rows},\n",
+    "    'nr_cols': {self.nr_cols},\n",
+    "    'J': {self.J},\n",
+    "    'h': {self.h},\n",
+    "}}\"\"\"\n",
+    "\n",
+    "    def __str__(self):\n",
+    "        '''Returns a human readable representation of an Ising system for debugging\n",
+    "        purposes.  Note that -1 values are rendered as 0 to improve visual layout.\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        str\n",
+    "          string representation of the initial state of the Ising system\n",
+    "\n",
+    "        Note\n",
+    "        ----\n",
+    "        This representation *should not* be used for checkpointing/serialization as\n",
+    "        -1 values are rendered as 0.\n",
+    "        '''\n",
+    "        return '\\n'.join(\n",
+    "            (''.join('1' if self[i, j] > 0 else '0' for j in range(self.nr_cols))\n",
+    "             for i in range(self.nr_rows))\n",
+    "        )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f7803b10-49a7-4ced-a8ae-9f8b8c071f5c",
+   "metadata": {},
+   "source": [
+    "Note that since the `__init__` method uses the seed provided as an argument to seed the numpy random number generator, and the representation provides that string, an instance of an Ising system can always be reproduced from its representation, without having to contain the individual spins at all.  Incidentally, initializing the system randomly may lead to slow convergence near the critical temperature.\n",
+    "\n",
+    "Also note that to make the string representation visually more pleasing, the $-1$ spins are represented as $0$.\n",
+    "\n",
+    "The `IsingSystem` class is essentially a wrapper for a numpy array.  This allows to later optimize the implementation without having to modify the API."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ebdca70a-4b22-41e1-b977-49cc9f65bf00",
+   "metadata": {},
+   "source": [
+    "You can test the class by\n",
+    "\n",
+    "  * creating an instance,\n",
+    "  * checking its representation,\n",
+    "  * checking its string representation,\n",
+    "  * get the value of a spin,\n",
+    "  * set the value of a sping, and\n",
+    "  * show the string representation again."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "2d0b5964-2299-48b5-95f4-d48c4bab2b40",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ising = IsingSystem(nr_rows=10, nr_cols=10, J=1.0, h=1.0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "14f9f55c-3093-4ee5-8a57-46ecde3bfb77",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{\n",
+       "    'nr_rows': 10,\n",
+       "    'nr_cols': 10,\n",
+       "    'J': 1.0,\n",
+       "    'h': 1.0,\n",
+       "}"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ising"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "cdde4b32-7bb7-4dfb-935f-20c47686f778",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0000010010\n",
+      "1001100010\n",
+      "1010000101\n",
+      "1001010001\n",
+      "1010100101\n",
+      "1110001101\n",
+      "1100001000\n",
+      "1100011100\n",
+      "0101000100\n",
+      "0010110101\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ising)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "0f526f45-a8af-4761-95ce-f2a2097877ed",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ising[1, 4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "fc42bca1-c185-4472-90f3-1d6ae81734f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ising [1, 4] = -1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "57e810b0-fe30-4dbb-81de-43612753c1a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0000010010\n",
+      "1001000010\n",
+      "1010000101\n",
+      "1001010001\n",
+      "1010100101\n",
+      "1110001101\n",
+      "1100001000\n",
+      "1100011100\n",
+      "0101000100\n",
+      "0010110101\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ising)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "a59dfea9-4910-4499-99b4-cb8f751815ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bae6eb9d-858e-47d4-8aff-322e6d8800b8",
+   "metadata": {},
+   "source": [
+    "# Measures"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc53d9ab-ae0d-4e4b-8e37-1a93b875548d",
+   "metadata": {},
+   "source": [
+    "Several measures can be computed to characterize an Ising system, e.g.,\n",
+    "\n",
+    "  * the magnetization,\n",
+    "  * the energy."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0e990376-7c28-4f1e-b6ed-cba7cce33bef",
+   "metadata": {},
+   "source": [
+    "Since many measures share implementation details, it is convenient to define an abstract base class `Measure` that encapsulates the common functionality."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "11cdc23e-a3a7-4312-8eef-9f13c41cb06b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class AbstractMeasure(abc.ABC):\n",
+    "    '''abstract class that represents a measure of the system such as the\n",
+    "    magnetization or the energy.  It is however more general and can be used\n",
+    "    for non-scalar measures as well.\n",
+    "    '''\n",
+    "\n",
+    "    def __init__(self, name, /, *, headers=None):\n",
+    "        '''Base initialization method\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        name: str\n",
+    "          the measure's name\n",
+    "        headers: list[str] | tuple[str] | None\n",
+    "          the headers for the measure, if `None`, the measure is assumed to be scalar\n",
+    "          and the name is the sole header\n",
+    "        '''\n",
+    "        self._name = name\n",
+    "        if headers is None:\n",
+    "            self._headers = (self._name, )\n",
+    "        else:\n",
+    "            self._headers = tuple(headers)\n",
+    "        self._sep = ' '\n",
+    "        self._values = []\n",
+    "\n",
+    "    @property\n",
+    "    def name(self):\n",
+    "        '''Returs the measure's name\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        str\n",
+    "          the measure's name\n",
+    "        '''\n",
+    "        return self._name\n",
+    "\n",
+    "    @property\n",
+    "    def headers(self):\n",
+    "        '''Returns a string representation of the headers for the measure, separated\n",
+    "        by the `sep` value passed on initialization.\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        str\n",
+    "            column headers for this measure\n",
+    "        '''\n",
+    "        return self._sep.join(self._headers)\n",
+    "\n",
+    "    @property\n",
+    "    def sep(self):\n",
+    "        '''Returns the separator for textual output.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        str\n",
+    "          separator for output\n",
+    "        '''\n",
+    "\n",
+    "    @sep.setter\n",
+    "    def sep(self, value):\n",
+    "        '''Sets the separator to use for output.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        sep: str\n",
+    "          separator to use for output\n",
+    "        '''\n",
+    "        self._sep = value\n",
+    "\n",
+    "    @property\n",
+    "    def values(self):\n",
+    "        '''Returns the accumulated values of this measure, i.e., all values measured\n",
+    "        during the lifetime of the measure up to the call of this method.\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        list\n",
+    "          values measured up to now (note: a deep copy is returned)\n",
+    "        '''\n",
+    "        return copy.deepcopy(self._values)\n",
+    "\n",
+    "    def __len__(self):\n",
+    "        '''Returns the number of values measured so far.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        int\n",
+    "          number of values measured so far\n",
+    "        '''\n",
+    "        return len(self._values)\n",
+    "\n",
+    "    @property\n",
+    "    def current_value(self):\n",
+    "        '''Returns a string representation of the most recently measured value, if non-scalar,\n",
+    "        components are separated by the `sep` value passed during initialization.\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        str\n",
+    "          string representation of the most recent value that was measured\n",
+    "        '''\n",
+    "        value = self._values[-1]\n",
+    "        if isinstance(value, collections.abc.Iterable):\n",
+    "            return self._sep.join(str(x) for x in value)\n",
+    "        else:\n",
+    "            return str(value)\n",
+    "\n",
+    "    @abc.abstractmethod\n",
+    "    def compute_value(self, system):\n",
+    "        '''Abstract method that has to be implemented to compute the specific measure\n",
+    "        that is derived from this class.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        system: Any\n",
+    "          system to compute the measure on\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        Any\n",
+    "          the value the measure computes\n",
+    "        '''\n",
+    "        ...\n",
+    "\n",
+    "    def __call__(self, system):\n",
+    "        '''Computes and stores the value of this measure.  This makes the objects\n",
+    "        callable, so a measure `A` on a system `s` can be computed as `A(s)`.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        system: Any\n",
+    "          system to compute the measure on\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        Any\n",
+    "          the value the measure computes\n",
+    "        '''\n",
+    "        value = self.compute_value(system)\n",
+    "        self._values.append(value)\n",
+    "        return value"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ebaaa595-6532-49c7-acb7-6f5e7ff0dd00",
+   "metadata": {},
+   "source": [
+    "## Magnetization"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bd1fea95-e07d-4c47-826d-09697eba57d6",
+   "metadata": {},
+   "source": [
+    "The magnetization of the system is defined by\n",
+    "$$\n",
+    "    M = \\frac{\\sum_{i=0}^{N-1} s_i}{N}\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6ba352a3-0aa9-47a2-8542-4ac156de0d88",
+   "metadata": {},
+   "source": [
+    "The concrete class `Magnetization` now simply has to implement the `compute_value` method."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "eed317ec-5aaf-4e88-8c6c-34a1e6898ada",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class Magnetization(AbstractMeasure):\n",
+    "    '''Computes the magnetization of an Ising system.\n",
+    "    '''\n",
+    "\n",
+    "    def __init__(self):\n",
+    "        '''Initializes the measure.\n",
+    "        '''\n",
+    "        super().__init__('magnetization')\n",
+    "\n",
+    "    def compute_value(self, ising):\n",
+    "        '''Computes the value of the magnetization for the given Ising system.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        ising: IsingSystem\n",
+    "          instance of the `IsingSystem` class\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        float\n",
+    "          magnetization of the given Ising system\n",
+    "        '''\n",
+    "        magnetization = 0.0\n",
+    "        for i, j in itertools.product(range(ising.nr_rows), range(ising.nr_cols)):\n",
+    "            magnetization += ising[i, j]\n",
+    "        return magnetization/ising.N"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "44353a9a-56f2-4653-b6cd-100df9a3fe05",
+   "metadata": {},
+   "source": [
+    "To test the measures you define, it is a good idea to use a very small Ising system, so that it is easy to check the results by hand."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "d03ad0a3-7f06-479b-9d55-d1032c25d123",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "random.seed(1234)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "5355cecb-a38b-4fc1-b42a-41c7b07784fb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mini_ising = IsingSystem(nr_rows=4, nr_cols=4, J=0.5, h=2.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "676e6fcb-9eae-4b8d-8637-04c9caa08e23",
+   "metadata": {},
+   "source": [
+    "The implementation can now be tested using `mini_ising`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "e8ef6d91-071a-47ef-b392-f296b6cde930",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "M = Magnetization()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "3247c2eb-03cc-4d03-949e-f022a30e950c",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-0.375"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "M(mini_ising)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "8d88729d-dbd4-48a5-abf0-f1ddc542886e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1000\n",
+      "0001\n",
+      "0000\n",
+      "1110\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(mini_ising)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63785ebb-8de6-4540-a8bc-967747416720",
+   "metadata": {},
+   "source": [
+    "The system has 5 spins up ($s_i = 1$) and 11 spins down ($s_i = -1$) while $N = 16$, so the magnetization should be $(5 - 11)/16 = -3/8 = -0.375$ as computed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "ab636c0d-cf08-4c7e-b4ee-22b114194b5e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del mini_ising, M"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2114304-d63b-49d5-beb1-b6b58dec632e",
+   "metadata": {},
+   "source": [
+    "## Energy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "37015ddd-e551-47ea-b6c3-d86bce53239e",
+   "metadata": {},
+   "source": [
+    "The energy of the system is defined as\n",
+    "$$\n",
+    "  E = H/N\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "af1644ad-fcf4-4ff5-a90f-6243bb52298c",
+   "metadata": {},
+   "source": [
+    "The implementation of the `Energy` class is very similar."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "fd6dbbce-bc93-491a-8ac3-96a864631368",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class Energy(AbstractMeasure):\n",
+    "    '''Class to compute the energy of an Ising system.\n",
+    "    '''\n",
+    "\n",
+    "    def __init__(self):\n",
+    "        '''Initializes the measure.\n",
+    "        '''\n",
+    "        super().__init__('energy')\n",
+    "\n",
+    "    def compute_value(self, ising):\n",
+    "        '''Computes the value of the energy for the given Ising system.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        ising: IsingSystem\n",
+    "          instance of the `IsingSystem` class\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        float\n",
+    "          energy of the given Ising system\n",
+    "        '''\n",
+    "        J, h = ising.J, ising.h\n",
+    "        energy = 0.0\n",
+    "        for i, j in itertools.product(range(ising.nr_rows), range(ising.nr_cols)):\n",
+    "            energy -= J*ising[i, j]*(ising[i, j + 1] + ising[i + 1, j]) + h*ising[i, j]\n",
+    "        return energy/ising.N"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "b023beb7-4de2-4de3-83a9-d2165705868e",
+   "metadata": {},
+   "source": [
+    "To test the measures you define, it is a good idea to use a very small Ising system, so that it is easy to check the results by hand."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "82830bd4-9b42-4b7a-814b-835fa20b803b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "random.seed(1234)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "9abd4c5b-545e-497d-ae24-9a773f078dbf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mini_ising = IsingSystem(nr_rows=4, nr_cols=4, J=0.5, h=2.0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "98473b4d-74a2-4808-83b9-bdc67d436c94",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "E = Energy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "7c3374cd-13f2-4791-bcca-4c89eec59b05",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.625"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "E(mini_ising)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "37169d46-f5c4-44c6-ac64-df8023310bce",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1000\n",
+      "0001\n",
+      "0000\n",
+      "1110\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(mini_ising)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "a59b0432-7a6d-4744-b038-c0e9811c6769",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "    'nr_rows': 4,\n",
+      "    'nr_cols': 4,\n",
+      "    'J': 0.5,\n",
+      "    'h': 2.0,\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(repr(mini_ising))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7d0bd2aa-dc42-4cc5-a817-7fb24e204d02",
+   "metadata": {},
+   "source": [
+    "Again, this checks out, so the implementation could be correct."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "bbec6169-6ffc-4e29-a0fc-b13124343baf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del mini_ising, E"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "775d8ad5-4828-4b77-b76a-2f53e43c3f68",
+   "metadata": {},
+   "source": [
+    "# Dynamics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "494ab68d-d58d-45e0-9d83-c8b32aaf5e7a",
+   "metadata": {},
+   "source": [
+    "There are several ways to define the dymamics of an Ising system, and you can consider\n",
+    "\n",
+    "  * Glauber dynamics and\n",
+    "  * Metropolis-Hastings dynamics.\n",
+    "\n",
+    "Both are based on the same Hamiltonian, but differ in the selection of spins to update and transition probabilities."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7144767a-5fe9-4710-ba13-380538725239",
+   "metadata": {},
+   "source": [
+    "Since both methods share the same Hamiltonian, the energy difference between the original state and a new state where a single spin $i$ is split can be computed by the same function.\n",
+    "$$\n",
+    "    \\Delta E_{i} = 2 s_i \\left( J \\sum_{\\langle i j \\rangle} s_j + h \\right)\n",
+    "$$\n",
+    "Again, the sum index $\\langle i, j \\rangle$ runs over *all* neirest neighbors.\n",
+    "\n",
+    "The dynamics in both cases is considered at an absolute temperature $T$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "6443bdd7-a8e2-4098-9c33-b2b6115bc2bd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class AbstractStepper(abc.ABC):\n",
+    "    '''Abstract base class for steppers.  Derived classes should\n",
+    "    implement the `update` method.\n",
+    "    '''\n",
+    "\n",
+    "    def __init__(self, temperature):\n",
+    "        '''Initializes the stepper.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        temperature: float\n",
+    "          temperature to use in the dynamics\n",
+    "        '''\n",
+    "        self._temperature = temperature\n",
+    "\n",
+    "    @property\n",
+    "    def T(self):\n",
+    "        '''Returns the temperature for the dynamics\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        float\n",
+    "          temperature of the dynamics\n",
+    "        '''\n",
+    "        return self._temperature\n",
+    "\n",
+    "    @staticmethod\n",
+    "    def _compute_ΔH(ising, i, j):\n",
+    "        '''Computes the energy difference of the Hamiltonian if a spin\n",
+    "        were flipped (without actually flipping it).\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        ising: IsingSystem\n",
+    "          Ising system to compute the difference for\n",
+    "        i: int\n",
+    "          candiate spin's row index\n",
+    "        j: int\n",
+    "          candiate spin's column index\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        float\n",
+    "          difference for the Hamiltonian value if the given spin were flipped\n",
+    "        '''\n",
+    "        return 2*ising[i, j]*(\n",
+    "            ising.J*(\n",
+    "                ising[i - 1, j] + ising[i, j + 1] + ising[i + 1, j] + ising[i, j - 1]\n",
+    "            ) + ising.h\n",
+    "        )\n",
+    "\n",
+    "    @abc.abstractmethod\n",
+    "    def update(self, ising, nr_steps=1):\n",
+    "        '''Abstract method that updates the Ising system according to the dynamics\n",
+    "        specified by the derived classes.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        ising: IsingSystem\n",
+    "          Ising system to update\n",
+    "        nr_steps: int\n",
+    "          number of update steps to take, defaults to 1\n",
+    "        '''\n",
+    "        ..."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8c618d6-d282-440e-8bb7-01dea5c1b201",
+   "metadata": {},
+   "source": [
+    "## Glauber dynamics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "407cf016-4b2a-4f16-b8ec-a5dc9bcc42c9",
+   "metadata": {},
+   "source": [
+    "A step in the Glauber dynamics is defined as follows:\n",
+    "\n",
+    "  1. pick a spin at random,\n",
+    "  2. compute the energy difference $\\Delta E$ when it would be flipped,\n",
+    "  3. with probability $\\frac{1}{1 + e^{\\Delta E/T}}$, flip the spin."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "2befe8e6-8de1-4c9e-bea5-2e69784098cb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class GlauberStepper(AbstractStepper):\n",
+    "    '''Class that implements a stepper for the Glauber dynamics.\n",
+    "    '''\n",
+    "\n",
+    "    def __init__(self, temperature, ising):\n",
+    "        '''Initializes the stepper.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        temperature: float\n",
+    "          temperature to use in the dynamics\n",
+    "        ising: IsingSystem\n",
+    "           Ising system to update\n",
+    "        '''\n",
+    "        super().__init__(temperature)\n",
+    "\n",
+    "    def update(self, ising, nr_steps=None):\n",
+    "        '''Updates the Ising system according to the Glauber dynamics.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        ising: IsingSystem\n",
+    "          Ising system to update\n",
+    "        nr_steps: int\n",
+    "          number of update steps to take, defaults to the number of spins\n",
+    "          in the system\n",
+    "        '''\n",
+    "        if nr_steps is None:\n",
+    "            nr_steps = ising.nr_rows*ising.nr_cols\n",
+    "        for _ in range(nr_steps):\n",
+    "            i = random.randrange(ising.nr_rows)\n",
+    "            j = random.randrange(ising.nr_cols)\n",
+    "            ΔE = self.__class__._compute_ΔH(ising, i, j)\n",
+    "            if random.random() < 1.0/(1.0 + math.exp(ΔE/self._temperature)):\n",
+    "                ising[i, j] = -ising[i, j]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "78ee7902-d235-4c00-8035-ae5fbbbea62c",
+   "metadata": {},
+   "source": [
+    "The process is repeated for as many steps to reach convergence, i.e., thermal equilibrium.  Note that the default number of steps is $N$, the number of spins.  Choosing this default makes it easier to compare the Metropolis-Hastings algorithm that (potentially) updates all spins in a single step."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "801d9588-60c0-4ace-9608-de0cf84ede92",
+   "metadata": {},
+   "source": [
+    "## Metropolis-Hasting dynamics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c4253cae-89f6-4ae2-9d8f-727946110bf3",
+   "metadata": {},
+   "source": [
+    "A step in the Metropolos-Hastings dynamics is defined as follows:\n",
+    "\n",
+    "For each spin (in order):\n",
+    "  1. compute the energy difference $\\Delta E$ when it would be flipped,\n",
+    "  1. with probability $e^{-\\Delta E/T}$, flip the spin."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "97327a74-b10d-4892-add6-43dbfb438f76",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MetropolisHastingsStepper(AbstractStepper):\n",
+    "    '''Class that implements a stepper for the Metropolis-Hastings dynamics.\n",
+    "    '''\n",
+    "\n",
+    "    def __init__(self, temperature):\n",
+    "        '''Initializes the stepper.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        temperature: float\n",
+    "          temperature to use in the dynamics\n",
+    "        '''\n",
+    "        super().__init__(temperature)\n",
+    "\n",
+    "    def update(self, ising, nr_steps=None):\n",
+    "        '''Updates the Ising system according to the Metropolis-Hastings dynamics.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        ising: IsingSystem\n",
+    "          Ising system to update\n",
+    "        nr_steps: int\n",
+    "          number of update steps to take, defaults to the number of spins\n",
+    "          in the system\n",
+    "        '''\n",
+    "        if nr_steps is None:\n",
+    "            nr_steps = 1\n",
+    "        for _ in range(nr_steps):\n",
+    "            for i, j in itertools.product(range(ising.nr_rows), range(ising.nr_cols)):\n",
+    "                ΔE = self.__class__._compute_ΔH(ising, i, j)\n",
+    "                if ΔE <= 0.0 or random.random() < math.exp(-ΔE/self._temperature):\n",
+    "                    ising[i, j] = -ising[i, j]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "39c81c9b-4a90-43e2-b892-95efd7320ca0",
+   "metadata": {},
+   "source": [
+    "# Convergence criterion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bb210695-04df-449f-b4bb-e56af8e3d9fe",
+   "metadata": {},
+   "source": [
+    "Many convergence criterions can be considered, for instance, the magnetization doesn't change for the last $n$ steps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "2ee63b6b-567d-4e93-b3a5-490727f539fa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class AbstractIsConverged(abc.ABC):\n",
+    "\n",
+    "    def __init__(self, measure):\n",
+    "        self._measure = measure\n",
+    "\n",
+    "    @property\n",
+    "    def measure(self):\n",
+    "        '''Returns the measure used in the convergence criterion.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        AbstractMeasure\n",
+    "          measure used in this convergence criterion\n",
+    "          \n",
+    "        Note\n",
+    "        ----\n",
+    "        The measure returned is *not* a copy, it is the actual object.\n",
+    "        '''\n",
+    "        return self._measure\n",
+    "\n",
+    "    @abc.abstractmethod\n",
+    "    def is_converged(self):\n",
+    "        '''Returns `True` if the simulation has converged, `False` otherwise, should\n",
+    "        be implemented by derived classes.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        bool\n",
+    "          `True` if the simulation has converged, `False` otherwise\n",
+    "        '''\n",
+    "        ...\n",
+    "\n",
+    "    def __call__(self):\n",
+    "        '''Returns `True` if the simulation has converged, `False` otherwise.\n",
+    "        \n",
+    "        Returns\n",
+    "        -------\n",
+    "        bool\n",
+    "          `True` if the simulation has converged, `False` otherwise\n",
+    "        '''\n",
+    "        return self.is_converged()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "e33e760c-e55f-4943-b3e7-a6b186588de9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class IsMeasureStable(AbstractIsConverged):\n",
+    "    '''Convergence criterion that will stop the simulation if the measure is\n",
+    "    constant to within an absolute error for a given number of steps.'''\n",
+    "\n",
+    "    def __init__(self, *, measure, nr_measurement_steps, delta):\n",
+    "        '''Initialize the criterion.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        measure: AbstractMeasure\n",
+    "          measure that is used in the simulation\n",
+    "        nr_measurement_steps: int\n",
+    "          number of measurement steps for which the measure should be constant\n",
+    "        delta: float\n",
+    "          absolute error to consider the measure to be constant within\n",
+    "\n",
+    "        Note\n",
+    "        ----\n",
+    "        This class is only designed to work for scalar measures.\n",
+    "        '''\n",
+    "        self._measure = measure\n",
+    "        self._nr_measurement_steps = nr_measurement_steps\n",
+    "        self._delta = delta\n",
+    "\n",
+    "    def is_converged(self):\n",
+    "        '''Returns `True` if the measure remained approximately constant, `False`\n",
+    "        otherwise.\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        bool\n",
+    "          `True` if the measure was approximately constant for the specified number\n",
+    "          of measurement steps, `False` otherwise\n",
+    "        '''\n",
+    "        if len(self._measure) < self._nr_measurement_steps:\n",
+    "            return False\n",
+    "        values = self._measure.values[-self._nr_measurement_steps:]\n",
+    "        mean = statistics.mean(values)\n",
+    "        return max(abs(value - mean) for value in values) < self._delta"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2ba579d4-77c4-4f68-9d94-dcf28c524d03",
+   "metadata": {},
+   "source": [
+    "# Simulation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "254de867-be37-4942-881c-94ca26c0c7c7",
+   "metadata": {},
+   "source": [
+    "A simulation consists of\n",
+    "\n",
+    "  1. initializing an Ising system,\n",
+    "  2. creating a stepper for the desired dynamics and temperature $T$,\n",
+    "  3. updating the system for multiple time steps while printing various measures,\n",
+    "  4. stop when either a convergence criterion is met, or a maximum number of steps is reached."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d5da0e2a-ced6-4440-84bf-34650862ec78",
+   "metadata": {},
+   "source": [
+    "Again, it is convenient to create a class to encapsulate the scaffolding."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "990696f0-1970-40ac-b917-82af57398c94",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class Simulation:\n",
+    "    '''Class to run simulations with a given initial Ising system, dynamics\n",
+    "    and stop criterion.\n",
+    "    '''\n",
+    "\n",
+    "    def __init__(self, *, ising, stepper, is_converged, sep=' '):\n",
+    "        '''Initializes the simulation.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        ising: IsingSystem\n",
+    "          instance of an initialized Ising system\n",
+    "        stepper: AbstractStepper\n",
+    "          stepper implementation to update the Ising system\n",
+    "        is_converged: Callable\n",
+    "          callable that returns `True` when the dynamics has converged, `False`\n",
+    "          ottherwise\n",
+    "        sep: str\n",
+    "          separator to use for output, defaults to ' '\n",
+    "        '''\n",
+    "        self._ising = ising\n",
+    "        self._stepper = stepper\n",
+    "        self._is_converged = is_converged\n",
+    "        self._sep = sep\n",
+    "        self._measures = []\n",
+    "        self._measure_steps = []\n",
+    "        self.add_measures(self._is_converged.measure)\n",
+    "\n",
+    "    def add_measures(self, *measures):\n",
+    "        '''Add measures to the simulation.\n",
+    "        \n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        measures: *AbstractMeasure\n",
+    "          one or more measures to add to the simulation\n",
+    "        '''\n",
+    "        # ensure the separator is propagated to each measure, this only\n",
+    "        # matters for non-scalar measures\n",
+    "        for measure in measures:\n",
+    "            measure.sep = self._sep\n",
+    "        self._measures.extend(measures)\n",
+    "\n",
+    "    def _compute_measures(self, step_nr):\n",
+    "        '''Computes the measures for the simulation.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        step_nr: int\n",
+    "          current step number\n",
+    "        '''\n",
+    "        self._measure_steps.append(step_nr)\n",
+    "        values = [str(step_nr)]\n",
+    "        for measure in self._measures:\n",
+    "            measure(self._ising)\n",
+    "            values.append(measure.current_value)\n",
+    "        print(self._sep.join(value for value in values))\n",
+    "\n",
+    "    @property\n",
+    "    def measures(self):\n",
+    "        '''Returns an iterable over the measures of the simulation.  The\n",
+    "        actual values are deep copies of the original measures.\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        Iterable[AbstractMeasure]\n",
+    "          iterable to deep copies of the measures\n",
+    "        '''\n",
+    "        return (copy.deepcopy(measure) for measure in self._measures)\n",
+    "\n",
+    "    @property\n",
+    "    def measure_steps(self):\n",
+    "        '''Returns the step numbers at which measurements where computed during the run\n",
+    "        of the simulation.\n",
+    "\n",
+    "        Returns\n",
+    "        -------\n",
+    "        list[int]\n",
+    "          deep copy of the list of steps at which measures were computed\n",
+    "        '''\n",
+    "        return copy.deepcopy(self._measure_steps)\n",
+    "\n",
+    "    def run(self, *, max_steps, measure_interval=1):\n",
+    "        ''' Simulates to convergence, or a maximum number of steps.\n",
+    "\n",
+    "        Parameters\n",
+    "        ----------\n",
+    "        max_steps: int\n",
+    "          maximum number of simulation steps to perform\n",
+    "        measure_interval: int\n",
+    "          number of steps between the computation and display of measurements\n",
+    "        '''\n",
+    "        print('step' + self._sep + self._sep.join(measure.headers for measure in self._measures))    \n",
+    "        for step_nr in range(max_steps + 1):\n",
+    "            if step_nr % measure_interval == 0:\n",
+    "                self._compute_measures(step_nr)\n",
+    "                if self._is_converged():\n",
+    "                    break\n",
+    "            self._stepper.update(self._ising)\n",
+    "        if step_nr % measure_interval != 0 and step_nr <= max_steps:\n",
+    "            self._compute_measures(step_nr)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7d74d743-9e96-4f0f-a2fc-1cee6193ea14",
+   "metadata": {},
+   "source": [
+    "Note that the measure used in the convergence criterion is added automatically."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f35ecc3d-1ce5-4e0b-bb63-bfa9bfa2c72e",
+   "metadata": {},
+   "source": [
+    "# Simulation run"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e01d9e02-50e5-4b1f-8762-46b366a894a8",
+   "metadata": {},
+   "source": [
+    "## Glauber dynamics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "28193261-6f84-43fe-80de-671e50164510",
+   "metadata": {},
+   "source": [
+    "### Ferromagnetic phase"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f9805d31-8ec3-4038-8ce4-4e6879d66569",
+   "metadata": {},
+   "source": [
+    "First, you can run for $T < T_c$, i.e., the system should be ferromagnetic.  At equilibrium, the magnetization should be very close to 1 if $h > 0$ or -1 if $h < 0$."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "10c5c8ae-4b7f-451f-bc2a-a4ead231fa19",
+   "metadata": {},
+   "source": [
+    "First you can set up a system of $100 \\times 100$ spins with $J = 1$ and $h = 1$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "4ce070bf-8bbf-49a2-a5fb-a412dbdb5124",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "random.seed(1234)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "c2fd28f7-f2da-456e-bbac-880cd034ee6c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ising = IsingSystem(nr_rows=100, nr_cols=100, J=1.0, h=1.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3fa76c6f-8ddc-4f7c-986e-dba2c09dd6ee",
+   "metadata": {},
+   "source": [
+    "Since you want to use Glauber dynamics, you can create such a stepper with temperature $T = 2$, below the critical temperature $T \\approx 2.27$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "c19a4dcc-32f6-4c89-b03e-6ebf71259bf4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stepper = GlauberStepper(temperature=2.0, ising=ising)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f94eadc2-1751-4a31-a979-336bd8bff5b3",
+   "metadata": {},
+   "source": [
+    "The convergence criterion is that the magnetization remains constant to within $\\delta = 0.001$ for 5 measurement steps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "5b951fc1-29fb-43d0-81ac-c2df9ce34667",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "is_converged = IsMeasureStable(\n",
+    "    measure=Magnetization(),\n",
+    "    nr_measurement_steps=5,\n",
+    "    delta=0.001,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3e2418ec-48cf-4227-b673-49b813338745",
+   "metadata": {},
+   "source": [
+    "Now you can create the simulation based on the Ising system, the dynamics, i.e., the stepper and the convergence criterion.  After that, you can add any additional measures you like."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "e51bb5c2-86b9-435f-9d93-90ee10f0fbb6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "simulation = Simulation(\n",
+    "    ising=ising,\n",
+    "    stepper=stepper,\n",
+    "    is_converged=is_converged\n",
+    ")\n",
+    "simulation.add_measures(Energy())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "141da7b5-4f3c-4f10-809a-51f8795f2490",
+   "metadata": {},
+   "source": [
+    "Now you can run the simulation for at most 500 steps, computing the measures every 10th step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "44f889be-034c-43d4-a635-5eee0ac95bb6",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "step magnetization energy\n",
+      "0 -0.0102 0.005\n",
+      "10 0.979 -2.9022\n",
+      "20 0.9848 -2.9248\n",
+      "30 0.983 -2.9178\n",
+      "40 0.9826 -2.9154\n",
+      "50 0.9842 -2.9258\n",
+      "60 0.9788 -2.8988\n",
+      "70 0.9842 -2.923\n",
+      "80 0.9796 -2.9016\n",
+      "90 0.9828 -2.9216\n",
+      "100 0.9876 -2.9396\n",
+      "110 0.9806 -2.9058\n",
+      "120 0.987 -2.937\n",
+      "130 0.9848 -2.9264\n",
+      "140 0.9832 -2.9208\n",
+      "150 0.9796 -2.9056\n",
+      "160 0.982 -2.9128\n",
+      "170 0.984 -2.9224\n",
+      "180 0.9818 -2.9126\n",
+      "190 0.982 -2.9144\n",
+      "200 0.9846 -2.9266\n",
+      "210 0.9852 -2.9284\n",
+      "220 0.986 -2.9328\n",
+      "230 0.9834 -2.9218\n",
+      "240 0.9828 -2.9172\n",
+      "250 0.9844 -2.9256\n",
+      "260 0.9826 -2.9166\n",
+      "270 0.9874 -2.9394\n",
+      "280 0.981 -2.911\n",
+      "290 0.9872 -2.9372\n",
+      "300 0.983 -2.9166\n",
+      "310 0.9858 -2.9298\n",
+      "320 0.9852 -2.93\n",
+      "330 0.9828 -2.9188\n",
+      "340 0.9842 -2.9254\n",
+      "350 0.9858 -2.9298\n",
+      "360 0.9828 -2.9188\n",
+      "370 0.982 -2.914\n",
+      "380 0.986 -2.9312\n",
+      "390 0.9852 -2.9276\n",
+      "400 0.981 -2.9078\n",
+      "410 0.9818 -2.9146\n",
+      "420 0.9858 -2.931\n",
+      "430 0.9828 -2.9176\n",
+      "440 0.983 -2.919\n",
+      "450 0.9824 -2.9156\n",
+      "460 0.9826 -2.917\n",
+      "470 0.9842 -2.9238\n",
+      "480 0.9876 -2.9408\n",
+      "490 0.9816 -2.9116\n",
+      "500 0.9852 -2.9304\n",
+      "CPU times: user 7.69 s, sys: 23.4 ms, total: 7.72 s\n",
+      "Wall time: 7.7 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "simulation.run(max_steps=500, measure_interval=10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3cc8bedd-26e5-4483-81bb-dacd50b453d9",
+   "metadata": {},
+   "source": [
+    "Since the temperature $T < T_{\\mathrm{crit.}}$, the system is in the ferromagnetic phase."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "e2ded424-301f-4743-904f-64af37119b25",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising, stepper, is_converged, simulation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "38958218-7614-45fc-9360-ba746040e2f1",
+   "metadata": {},
+   "source": [
+    "### Paramagnetic phase"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3f1decb3-32ed-4791-aac1-1f9ccbfc22a3",
+   "metadata": {},
+   "source": [
+    "Next, you can do a run for $T > Tc$, i.e., the system should be paramagnetic.  At equilibrium, the magnetization should be significantly different from 1 or -1.  For $N \\to \\infty$, it should be zero."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "311c888a-7f39-448b-abb7-6ef4283cf976",
+   "metadata": {},
+   "source": [
+    "First you can set up a system of $100 \\times 100$ spins with $J = 1$ and $h = 1$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "e20922e8-41e8-4a5c-8c7d-5e62f6527f91",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ising = IsingSystem(nr_rows=100, nr_cols=100, J=1.0, h=1.0, seed=1234)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b06bb109-facc-4a1a-9054-e99e938ac6d9",
+   "metadata": {},
+   "source": [
+    "Since you want to use Glauber dynamics, you can create such a stepper with temperature $T = 2.5$, above the critical temperature $T_c \\approx 2.27$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "98db23eb-3305-4934-9138-955eb29891a7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stepper = GlauberStepper(temperature=5.0, ising=ising)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0f1f5f32-7a51-4b5c-bb02-e218eb8a7ce3",
+   "metadata": {},
+   "source": [
+    "The convergence criterion is that the magnetization remains constant to within $\\delta = 0.001$ for 5 measurement steps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "346f89ef-4f88-4509-a0a9-d7b38b7e0f40",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "is_converged = IsMeasureStable(\n",
+    "    measure=Magnetization(),\n",
+    "    nr_measurement_steps=5,\n",
+    "    delta=0.001,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "04b65011-73dd-4154-8078-928dbb24a65e",
+   "metadata": {},
+   "source": [
+    "Now you can create the simulation based on the Ising system, the dynamics, i.e., the stepper and the convergence criterion.  After that, you can add any additional measures you like."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "3d67235c-f72c-4789-a273-667a81c90df9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "simulation = Simulation(\n",
+    "    ising=ising,\n",
+    "    stepper=stepper,\n",
+    "    is_converged=is_converged\n",
+    ")\n",
+    "simulation.add_measures(Energy())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "28ac8e9a-2bc9-4a6d-a031-d9dd5a6848fb",
+   "metadata": {},
+   "source": [
+    "Now you can run the simulation for at most 500 steps, computing the measures every 10th step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "2c1ed2d8-3394-4e02-861a-6f45f6d79a58",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "step magnetization energy\n",
+      "0 0.0114 -0.0226\n",
+      "10 0.4522 -1.1514\n",
+      "20 0.4912 -1.2504\n",
+      "30 0.498 -1.2644\n",
+      "40 0.4802 -1.2138\n",
+      "50 0.4652 -1.176\n",
+      "60 0.477 -1.2018\n",
+      "70 0.5068 -1.2776\n",
+      "80 0.4832 -1.2224\n",
+      "90 0.5016 -1.2632\n",
+      "100 0.4974 -1.2606\n",
+      "110 0.461 -1.165\n",
+      "120 0.4896 -1.2476\n",
+      "130 0.47 -1.1792\n",
+      "140 0.4956 -1.2296\n",
+      "150 0.466 -1.1608\n",
+      "160 0.4698 -1.1938\n",
+      "170 0.4928 -1.2372\n",
+      "180 0.455 -1.1758\n",
+      "190 0.4832 -1.2308\n",
+      "200 0.5038 -1.2398\n",
+      "210 0.495 -1.265\n",
+      "220 0.488 -1.2384\n",
+      "230 0.4796 -1.2148\n",
+      "240 0.4776 -1.2092\n",
+      "250 0.4972 -1.2396\n",
+      "260 0.4902 -1.2298\n",
+      "270 0.4844 -1.2164\n",
+      "280 0.4554 -1.1242\n",
+      "290 0.506 -1.2528\n",
+      "300 0.4846 -1.2126\n",
+      "310 0.4818 -1.2338\n",
+      "320 0.486 -1.2384\n",
+      "330 0.4834 -1.2294\n",
+      "340 0.4836 -1.2128\n",
+      "350 0.512 -1.3024\n",
+      "360 0.4952 -1.2532\n",
+      "370 0.5026 -1.2594\n",
+      "380 0.4836 -1.2316\n",
+      "390 0.4728 -1.1828\n",
+      "400 0.4996 -1.2492\n",
+      "410 0.4716 -1.1828\n",
+      "420 0.4908 -1.2176\n",
+      "430 0.4834 -1.2178\n",
+      "440 0.4848 -1.2272\n",
+      "450 0.477 -1.2174\n",
+      "460 0.4902 -1.2054\n",
+      "470 0.4826 -1.203\n",
+      "480 0.4838 -1.195\n",
+      "490 0.4704 -1.1832\n",
+      "500 0.4944 -1.2352\n",
+      "500 0.4884 -1.2204\n"
+     ]
+    }
+   ],
+   "source": [
+    "simulation.run(max_steps=500, measure_interval=10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be9a1115-ca45-4694-9dea-6b94fffd2b4f",
+   "metadata": {},
+   "source": [
+    "Note that the for this temperature, variations in the magnetization are higher, and don't converge to within $\\delta = 0.001$.  However, it is clear that $M \\approx 0.48 < 1$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "67de5ce1-de2c-42f7-aea6-502a35298591",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising, stepper, is_converged, simulation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7f7f7c8-4c98-471a-9207-ce0b7f05426d",
+   "metadata": {},
+   "source": [
+    "## Metropolis-Hastings dynamics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d1fac941-cd0c-4248-af9d-385c025838d8",
+   "metadata": {},
+   "source": [
+    "You can redo the same simulation, but now with the Metropolis-Hastings dynamics."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8a8c2813-540b-4531-be6d-dcc9f16cdea3",
+   "metadata": {},
+   "source": [
+    "### Ferromagnetic phase"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7a01dbd3-56f2-45ce-93a2-2d681190d8ab",
+   "metadata": {},
+   "source": [
+    "First, you can run for $T < T_c$, i.e., the system should be ferromagnetic.  At equilibrium, the magnetization should be very close to 1 if $h > 0$ or -1 if $h < 0$."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b0932eb-b4f0-4769-b652-f8d632528e92",
+   "metadata": {},
+   "source": [
+    "First you can set up a system of $100 \\times 100$ spins with $J = 1$ and $h = 1$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "af5d8dac-6735-4b78-ac81-dd723064757b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ising = IsingSystem(nr_rows=100, nr_cols=100, J=1.0, h=1.0, seed=1234)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "90649c9b-928a-4bac-8be4-ebeebd6eb4c2",
+   "metadata": {},
+   "source": [
+    "Since you want to use Glauber dynamics, you can create such a stepper with temperature $T = 2$, below the critical temperature $T \\approx 2.27$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "9428a125-4892-43c3-bd53-c05f4d46980e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stepper = MetropolisHastingsStepper(temperature=2.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df08b52e-e916-42ae-8597-797ac211e5fd",
+   "metadata": {},
+   "source": [
+    "The convergence criterion is that the magnetization remains constant to within $\\delta = 0.001$ for 5 measurement steps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "fe7b79a1-152d-48e2-8991-072f54b9674f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "is_converged = IsMeasureStable(\n",
+    "    measure=Magnetization(),\n",
+    "    nr_measurement_steps=5,\n",
+    "    delta=0.001,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a353f77d-0f47-4c21-922c-f8c9ba2a9719",
+   "metadata": {},
+   "source": [
+    "Now you can create the simulation based on the Ising system, the dynamics, i.e., the stepper and the convergence criterion.  After that, you can add any additional measures you like."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "30d1b553-35cc-4ac3-aa56-f95a8e174296",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "simulation = Simulation(\n",
+    "    ising=ising,\n",
+    "    stepper=stepper,\n",
+    "    is_converged=is_converged\n",
+    ")\n",
+    "simulation.add_measures(Energy())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "12b60aa1-abca-4ffa-a488-2ccaf4fb6563",
+   "metadata": {},
+   "source": [
+    "Now you can run the simulation for at most 500 steps, computing the measures every 10th step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "efaaf211-451d-41fd-8639-0e6a985464f4",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "step magnetization energy\n",
+      "0 0.0114 -0.0226\n",
+      "10 0.9816 -2.9124\n",
+      "20 0.9832 -2.9196\n",
+      "30 0.9814 -2.9126\n",
+      "40 0.9836 -2.9212\n",
+      "50 0.9828 -2.9172\n",
+      "60 0.9806 -2.9078\n",
+      "70 0.985 -2.9282\n",
+      "80 0.9824 -2.916\n",
+      "90 0.9868 -2.936\n",
+      "100 0.9836 -2.922\n",
+      "110 0.9846 -2.9246\n",
+      "120 0.9844 -2.9256\n",
+      "130 0.9836 -2.9196\n",
+      "140 0.9816 -2.9112\n",
+      "150 0.9844 -2.9264\n",
+      "160 0.9824 -2.9156\n",
+      "170 0.98 -2.9072\n",
+      "180 0.9832 -2.9204\n",
+      "190 0.9854 -2.9274\n",
+      "200 0.9834 -2.9198\n",
+      "210 0.9852 -2.9276\n",
+      "220 0.9864 -2.936\n",
+      "230 0.9856 -2.9292\n",
+      "240 0.9834 -2.9206\n",
+      "250 0.983 -2.9206\n",
+      "260 0.9824 -2.9136\n",
+      "270 0.982 -2.9136\n",
+      "280 0.9858 -2.9306\n",
+      "290 0.9836 -2.922\n",
+      "300 0.9836 -2.9216\n",
+      "310 0.9826 -2.919\n",
+      "320 0.9822 -2.9158\n",
+      "330 0.9802 -2.9042\n",
+      "340 0.9816 -2.9124\n",
+      "350 0.9792 -2.8992\n",
+      "360 0.9798 -2.9042\n",
+      "370 0.9838 -2.9222\n",
+      "380 0.986 -2.9332\n",
+      "390 0.9772 -2.8936\n",
+      "400 0.984 -2.926\n",
+      "410 0.985 -2.931\n",
+      "420 0.9844 -2.9244\n",
+      "430 0.9832 -2.9204\n",
+      "440 0.9828 -2.9176\n",
+      "450 0.9856 -2.932\n",
+      "460 0.9794 -2.9018\n",
+      "470 0.986 -2.934\n",
+      "480 0.9902 -2.951\n",
+      "490 0.9832 -2.9212\n",
+      "500 0.982 -2.9148\n",
+      "500 0.9812 -2.9112\n"
+     ]
+    }
+   ],
+   "source": [
+    "simulation.run(max_steps=500, measure_interval=10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bc98f07e-8594-47dd-a5c3-04380904d2be",
+   "metadata": {},
+   "source": [
+    "The Metropolis-Hastings dynamics shows more variation between measurement steps, and doesn't converge to within $\\delta = 0.001$ withing 500 steps.  It is however also clear that the time taken by an update by the stpper is less than for Glauber dynamics.\n",
+    "\n",
+    "Although the failure to converge seems to be a drawback at first glance, it will also help to escape local minima, so for large spin systems, the accuracy should be better when compared to analytic results."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "f4484bb4-cef0-4ccb-bbae-873bdf22299d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising, stepper, is_converged, simulation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de8c57ba-4efb-4c4f-b247-2b1d1c45616a",
+   "metadata": {},
+   "source": [
+    "### Paramagnetic phase"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "30d34473-1846-4023-b96c-c12427e5c6fc",
+   "metadata": {},
+   "source": [
+    "Next, you can do a run for $T > Tc$, i.e., the system should be paramagnetic.  At equilibrium, the magnetization should be significantly different from 1 or -1.  For $N \\to \\infty$, it should be zero."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba6b7be5-5c6a-4bce-b010-79a3a7641d4d",
+   "metadata": {},
+   "source": [
+    "First you can set up a system of $100 \\times 100$ spins with $J = 1$ and $h = 1$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "f6e66add-ce3c-4fcf-9d3e-ad92a5ea4167",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ising = IsingSystem(nr_rows=100, nr_cols=100, J=1.0, h=1.0, seed=1234)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "64442e72-afab-4812-8cda-8c615dfba853",
+   "metadata": {},
+   "source": [
+    "Since you want to use Glauber dynamics, you can create such a stepper with temperature $T = 2.5$, above the critical temperature $T_c \\approx 2.27$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "93e0662e-e212-477d-a89a-ab6077f4facf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stepper = MetropolisHastingsStepper(temperature=5.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e280806-68d6-4b78-8c31-2c0046a174c8",
+   "metadata": {},
+   "source": [
+    "The convergence criterion is that the magnetization remains constant to within $\\delta = 0.001$ for 5 measurement steps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "89e28e3e-13b3-44db-a15e-70e241fa2bd0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "is_converged = IsMeasureStable(\n",
+    "    measure=Magnetization(),\n",
+    "    nr_measurement_steps=5,\n",
+    "    delta=0.001,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ac897f44-d9fc-48dc-8e74-9254ac31c40c",
+   "metadata": {},
+   "source": [
+    "Now you can create the simulation based on the Ising system, the dynamics, i.e., the stepper and the convergence criterion.  After that, you can add any additional measures you like."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "f115d837-8a23-48dc-a3e3-7d27a805f3b5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "simulation = Simulation(\n",
+    "    ising=ising,\n",
+    "    stepper=stepper,\n",
+    "    is_converged=is_converged\n",
+    ")\n",
+    "simulation.add_measures(Energy())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "84eb9f5e-9514-40ef-adbd-7f14248f711c",
+   "metadata": {},
+   "source": [
+    "Now you can run the simulation for at most 500 steps, computing the measures every 10th step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "e9761af8-0618-4310-98c7-a76d5f8e5e95",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "step magnetization energy\n",
+      "0 0.0114 -0.0226\n",
+      "10 0.4748 -1.2004\n",
+      "20 0.4716 -1.1752\n",
+      "30 0.5022 -1.2562\n",
+      "40 0.4822 -1.2146\n",
+      "50 0.4974 -1.2462\n",
+      "60 0.4876 -1.212\n",
+      "70 0.5278 -1.3098\n",
+      "80 0.4948 -1.244\n",
+      "90 0.4898 -1.2286\n",
+      "100 0.4778 -1.2094\n",
+      "110 0.4696 -1.19\n",
+      "120 0.504 -1.2684\n",
+      "130 0.4806 -1.205\n",
+      "140 0.504 -1.2808\n",
+      "150 0.4584 -1.1508\n",
+      "160 0.4766 -1.1962\n",
+      "170 0.4868 -1.2012\n",
+      "180 0.493 -1.2478\n",
+      "190 0.484 -1.2268\n",
+      "200 0.5026 -1.2538\n",
+      "210 0.4886 -1.2398\n",
+      "220 0.4714 -1.1934\n",
+      "230 0.4968 -1.2484\n",
+      "240 0.4764 -1.196\n",
+      "250 0.4882 -1.2442\n",
+      "260 0.5022 -1.273\n",
+      "270 0.5042 -1.2662\n",
+      "280 0.4776 -1.204\n",
+      "290 0.491 -1.2282\n",
+      "300 0.495 -1.2414\n",
+      "310 0.461 -1.1766\n",
+      "320 0.48 -1.202\n",
+      "330 0.4936 -1.242\n",
+      "340 0.4748 -1.2048\n",
+      "350 0.4814 -1.211\n",
+      "360 0.4996 -1.2456\n",
+      "370 0.4872 -1.2324\n",
+      "380 0.4724 -1.1708\n",
+      "390 0.4836 -1.2388\n",
+      "400 0.4932 -1.2312\n",
+      "410 0.496 -1.232\n",
+      "420 0.5018 -1.2618\n",
+      "430 0.4864 -1.2536\n",
+      "440 0.4672 -1.1836\n",
+      "450 0.482 -1.2232\n",
+      "460 0.479 -1.229\n",
+      "470 0.486 -1.2268\n",
+      "480 0.4764 -1.2048\n",
+      "490 0.4796 -1.2244\n",
+      "500 0.474 -1.194\n",
+      "500 0.4748 -1.2008\n"
+     ]
+    }
+   ],
+   "source": [
+    "simulation.run(max_steps=500, measure_interval=10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4384eda3-dc17-4fce-9c7c-a762a42672ee",
+   "metadata": {},
+   "source": [
+    "As for the ferromagnetic phase, the variation is higher for the Metropolis-Hastings dynamics than for the Glauber dynamics."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "0ead386d-faa0-4a22-b40a-21990664eebe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "del ising, stepper, is_converged, simulation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "323782dd-e9d0-48d1-a0b4-8ba778e1e3ad",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From b66717dface36a7badf6d0503ebb408ced562fef Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Thu, 31 Jul 2025 17:50:35 +0200
Subject: [PATCH 08/14] Add nbdime Python package

---
 environment.yml                           | 1 +
 scientific_python_linux64_conda_specs.txt | 6 ++++++
 2 files changed, 7 insertions(+)

diff --git a/environment.yml b/environment.yml
index 47dc742..272c7d2 100644
--- a/environment.yml
+++ b/environment.yml
@@ -20,5 +20,6 @@ dependencies:
   - xarray
   - networkx
   - nbconvert
+  - nbdime
   - seaborn
 prefix: /home/gjb/mambaforge/envs/scientific_python
diff --git a/scientific_python_linux64_conda_specs.txt b/scientific_python_linux64_conda_specs.txt
index decf487..14c4bc0 100644
--- a/scientific_python_linux64_conda_specs.txt
+++ b/scientific_python_linux64_conda_specs.txt
@@ -188,6 +188,7 @@ https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.1.0-py313h46c70d
 https://conda.anaconda.org/conda-forge/noarch/cached_property-1.5.2-pyha770c72_1.tar.bz2
 https://conda.anaconda.org/conda-forge/noarch/certifi-2025.7.14-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.4.2-pyhd8ed1ab_0.conda
+https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/noarch/comm-0.2.3-pyhe01879c_0.conda
 https://conda.anaconda.org/conda-forge/noarch/cpython-3.13.5-py313hd8ed1ab_102.conda
 https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhd8ed1ab_1.conda
@@ -246,6 +247,7 @@ https://conda.anaconda.org/conda-forge/linux-64/rpds-py-0.26.0-py313h4b2b08d_0.c
 https://conda.anaconda.org/conda-forge/noarch/send2trash-1.8.3-pyh0d859eb_1.conda
 https://conda.anaconda.org/conda-forge/noarch/setuptools-80.9.0-pyhff2d567_0.conda
 https://conda.anaconda.org/conda-forge/noarch/six-1.17.0-pyhe01879c_1.conda
+https://conda.anaconda.org/conda-forge/noarch/smmap-5.0.2-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/sniffio-1.3.1-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/noarch/soupsieve-2.7-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/tbb-2022.2.0-hb60516a_0.conda
@@ -273,6 +275,7 @@ https://conda.anaconda.org/conda-forge/linux-64/cffi-1.17.1-py313hfab6e84_0.cond
 https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.3.3-py313h7037e92_0.conda
 https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.3.0-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/fonttools-4.59.0-py313h3dea7bd_0.conda
+https://conda.anaconda.org/conda-forge/noarch/gitdb-4.0.12-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/h11-0.16.0-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/h2-4.2.0-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/imagecodecs-2025.3.30-py313h8b391ee_2.conda
@@ -310,6 +313,7 @@ https://conda.anaconda.org/conda-forge/noarch/arrow-1.3.0-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/noarch/beautifulsoup4-4.13.4-pyha770c72_0.conda
 https://conda.anaconda.org/conda-forge/noarch/bleach-with-css-6.2.0-h82add2a_4.conda
 https://conda.anaconda.org/conda-forge/noarch/fqdn-1.5.1-pyhd8ed1ab_1.conda
+https://conda.anaconda.org/conda-forge/noarch/gitpython-3.1.45-pyhff2d567_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/h5py-3.14.0-nompi_py313hfaf8fd4_100.conda
 https://conda.anaconda.org/conda-forge/linux-64/harfbuzz-11.3.3-hbb57e21_0.conda
 https://conda.anaconda.org/conda-forge/noarch/ipython-9.4.0-pyhfa0c392_0.conda
@@ -368,8 +372,10 @@ https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.16.0-pyhe01879c_0
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.16.6-hed9df3c_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/py-opencv-4.12.0-qt6_py313hc0a75a6_601.conda
 https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.6-pyhe01879c_0.conda
+https://conda.anaconda.org/conda-forge/noarch/jupyter-server-mathjax-0.2.6-pyhbbac1ac_2.conda
 https://conda.anaconda.org/conda-forge/noarch/jupyterlab_server-2.27.3-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.16.6-hb482800_0.conda
 https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.4-pyhd8ed1ab_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/opencv-4.12.0-qt6_py313h6537eeb_601.conda
 https://conda.anaconda.org/conda-forge/noarch/jupyterlab-4.4.5-pyhd8ed1ab_0.conda
+https://conda.anaconda.org/conda-forge/noarch/nbdime-4.0.2-pyhd8ed1ab_1.conda

From 79071606139864e5ade71574d9d31cd2b6e5a070 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Wed, 15 Oct 2025 08:59:30 +0200
Subject: [PATCH 09/14] Add material requirements

---
 docs/README.md   | 8 ++++++++
 docs/_config.yml | 3 ++-
 2 files changed, 10 insertions(+), 1 deletion(-)

diff --git a/docs/README.md b/docs/README.md
index ee50c5c..9011993 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -56,6 +56,14 @@ from scratch.
 If you plan to do Python programming in a Linux or HPC environment you should
 be familiar with these as well.
 
+For following along hands-on, you need
+* laptop or desktop with internet access.
+* a system set up so you can connect to an HPC system, an account on an HPC
+  system (e.g., VSC, CECI, ...), compute credits if that is required to run
+  jobs on the HPC system if you want to use an HPC system;
+* a Python environment that can run Jupyter Lab if you want to use your own system;
+* access to Google Colaboratory if you prefer not to install software.
+
 
 ## Level
 
diff --git a/docs/_config.yml b/docs/_config.yml
index c741881..2933e3c 100644
--- a/docs/_config.yml
+++ b/docs/_config.yml
@@ -1 +1,2 @@
-theme: jekyll-theme-slate
\ No newline at end of file
+title: "Scientific Python"
+theme: jekyll-theme-slate

From 608dbe43264075f2dcbf8d0a20fb4d5e626ea1e9 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Mon, 3 Nov 2025 20:51:31 +0100
Subject: [PATCH 10/14] Fix VSC logo

---
 scientific_python.pptx | Bin 2457964 -> 2493986 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/scientific_python.pptx b/scientific_python.pptx
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From d90b877c5a9c80408ee227d6431db1c969f90db0 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Mon, 3 Nov 2025 20:55:26 +0100
Subject: [PATCH 11/14] Fix VSC logo

---
 scientific_python.pptx | Bin 2513724 -> 2545106 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/scientific_python.pptx b/scientific_python.pptx
index 6bcf84908b2df1088a5d4243aa34839383e2d793..52a8616bede7495ceabf563f9e4ab797ba5cf176 100644
GIT binary patch
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From c471dd73436a79ca0cd1b73593a57b2fb9ebdfb6 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Tue, 18 Nov 2025 14:50:25 +0100
Subject: [PATCH 12/14] Update VSC logo

---
 scientific_python.pptx | Bin 2513724 -> 2545116 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/scientific_python.pptx b/scientific_python.pptx
index 6bcf84908b2df1088a5d4243aa34839383e2d793..b7b54d5e23610f1e0b137be7aaf312d9dd9d7e64 100644
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From 2068af65ff655b56bb271fd3fd7cf12deb46af53 Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Tue, 18 Nov 2025 15:43:43 +0100
Subject: [PATCH 13/14] Add slide on array memory layout

---
 scientific_python.pptx | Bin 2545116 -> 2602252 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/scientific_python.pptx b/scientific_python.pptx
index b7b54d5e23610f1e0b137be7aaf312d9dd9d7e64..66230d6af6939417764461566af0e306245ee372 100644
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From dbea46108e9e6edf720494f44cb2808626e0e1dd Mon Sep 17 00:00:00 2001
From: Geert Jan Bex <geertjan.bex@uhasselt.be>
Date: Tue, 18 Nov 2025 15:44:30 +0100
Subject: [PATCH 14/14] Fix speedup binary versus text I/O

---
 scientific_python.pptx | Bin 2602252 -> 2602257 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/scientific_python.pptx b/scientific_python.pptx
index 66230d6af6939417764461566af0e306245ee372..a0c9ad3cf0b699f39b365260af0285d3f85bd856 100644
GIT binary patch
delta 6700
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