{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Example of DOV search methods for groundwater screens (grondwaterfilters)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/DOV-Vlaanderen/pydov/master?filepath=docs%2Fnotebooks%2Fsearch_grondwaterfilters.ipynb)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Use cases:\n", "* Get groundwater screens in a bounding box\n", "* Get groundwater screens with specific properties\n", "* Get the coordinates of all groundwater screens in Ghent\n", "* Get the 'meetnet' and 'meetnet_code' for groundwater screens in Boortmeerbeek\n", "* Get all details of groundwaterscreens of 'meetnet 9' within the given bounding box\n", "* Get groundwater screens based on a combination of specific properties\n", "* Get groundwater screens within a groundwater body\n", "* List yearly average water head levels (GxG)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import inspect, sys" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# check pydov path\n", "import pydov" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Get information about the datatype 'GrondwaterFilter'" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "from pydov.search.grondwaterfilter import GrondwaterFilterSearch\n", "gwfilter = GrondwaterFilterSearch()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A description is provided for the 'GrondwaterFilter' datatype:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "In de Databank Ondergrond Vlaanderen zijn verschillende grondwatermeetnetten opgenomen. Deze meetnetten staan in functie van uitgebreide monitoringprogramma’s met de bedoeling een goed beeld te krijgen van de beschikbare grondwaterkwantiteit en grondwaterkwaliteit van de watervoerende lagen in Vlaanderen.\n" ] } ], "source": [ "print(gwfilter.get_description())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The different fields that are available for objects of the 'GrondwaterFilter' datatype can be requested with the get_fields() method:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "gw_id\n", "pkey_grondwaterlocatie\n", "filternummer\n", "pkey_filter\n", "namen\n", "filtergrafiek\n", "putgrafiek\n", "Aquifer_HCOVv1\n", "Aquifer_HCOVv2\n", "diepte_onderkant_filter\n", "lengte_filter\n", "putsoort\n", "filtertype\n", "meetnet\n", "x\n", "y\n", "start_grondwaterlocatie_mtaw\n", "gemeente\n", "grondwaterlichaam\n", "afgesloten_volgens_gwdecreet\n", "datum_in_filter\n", "datum_uit_filter\n", "stijghoogterapport\n", "analyserapport\n", "boornummer\n", "boringfiche\n", "peilmetingen_van\n", "peilmetingen_tot\n", "kwaliteitsmetingen_van\n", "kwaliteitsmetingen_tot\n", "recentste_exploitant\n", "beheerder\n", "aantal_dagen_sinds_laatste_meting\n", "eerste_invoer\n", "recentste_installatie\n", "geom\n", "meetnet_code\n", "aquifer_code\n", "grondwaterlichaam_code\n", "regime\n", "datum\n", "tijdstip\n", "peil_mtaw\n", "betrouwbaarheid\n", "methode\n", "filterstatus\n", "filtertoestand\n", "mv_mtaw\n" ] } ], "source": [ "fields = gwfilter.get_fields()\n", "\n", "# print available fields\n", "for f in fields.values():\n", " print(f['name'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, you can list all the fields and their details by inspecting the `get_fields()` output or the search instance itself in a notebook:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", "
\n", " \n", "
\n", " pydov.search.grondwaterfilter.GrondwaterFilterSearch\n", "
\n", "

In de Databank Ondergrond Vlaanderen zijn verschillende grondwatermeetnetten opgenomen. Deze meetnetten staan in functie van uitgebreide monitoringprogramma’s met de bedoeling een goed beeld te krijgen van de beschikbare grondwaterkwantiteit en grondwaterkwaliteit van de watervoerende lagen in Vlaanderen.

\n", " \n", "
\n", "

gw_id - Identificatie van de grondwaterlocatie. Dit veld was vroeger bekend als 'putnummer'.

  • type: string
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

pkey_grondwaterlocatie - URL die verwijst naar de gegevens van de grondwaterlocatie op de website. Voeg '.xml' toe om een XML voorstelling van deze gegevens te verkrijgen

  • type: string
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

filternummer - Het filternummer van de filter.

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

pkey_filter - URL die verwijst naar de gegevens van de filter op de website. Voeg '.xml' toe om een XML voorstelling van deze gegevens te verkrijgen. Wanneer dit veld leeg is betreft dit record een put zonder filters.

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

namen - Andere namen voor deze grondwaterlocatie

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

filtergrafiek - URL die verwijst naar een interactieve grafiek van de filter op de website. Wanneer dit veld leeg is betreft dit record een grondwaterlocatie zonder filters

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

putgrafiek - URL die verwijst naar een interactieve grafiek van alle filters van de grondwaterlocatie op de website.

  • type: string
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

Aquifer_HCOVv1 - None

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

Aquifer_HCOVv2 - None

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

diepte_onderkant_filter - De diepte van de onderkant van de filter (in meter, positief onder aanvangspeil put gegeven in attribuut Z_mTAW)

  • type: float
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

lengte_filter - De lengte van de filter (in meter).

  • type: float
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

putsoort - de soort grondwaterlocatie

  • type: string
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.FeatureCatalogueValues\n", "
    \n", " \n", " \n", "
    \n", "

    Installatie - Installatie

    \n", "
    \n", " \n", " \n", "
    \n", "

    batterijput - batterijput

    \n", "
    \n", " \n", " \n", "
    \n", "

    bodemlus - bodemlus

    \n", "
    \n", " \n", " \n", "
    \n", "

    bron, natuurlijke holte - bron, natuurlijke holte

    \n", "
    \n", " \n", " \n", "
    \n", "

    bronbemaling - bronbemaling

    \n", "
    \n", " \n", " \n", "
    \n", "

    draineringsinrichting - draineringsinrichting

    \n", "
    \n", " \n", " \n", "
    \n", "

    galerij - galerij

    \n", "
    \n", " \n", " \n", "
    \n", "

    graverij, mijn, groeve - graverij, mijn, groeve

    \n", "
    \n", " \n", " \n", "
    \n", "

    niet-verbuisde boorput - niet-verbuisde boorput

    \n", "
    \n", " \n", " \n", "
    \n", "

    onbekend - onbekend

    \n", "
    \n", " \n", " \n", "
    \n", "

    ring- of steenput - ring- of steenput

    \n", "
    \n", " \n", " \n", "
    \n", "

    verbuisde boorput - verbuisde boorput

    \n", "
    \n", " \n", " \n", "
    \n", "

    vijver - vijver

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

filtertype - Het type van de filter. Wanneer dit veld leeg is betreft dit record een put zonder filters.

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.FeatureCatalogueValues\n", "
    \n", " \n", " \n", "
    \n", "

    infiltratiefilter - infiltratiefilter

    \n", "
    \n", " \n", " \n", "
    \n", "

    natuurlijke filter - natuurlijke filter

    \n", "
    \n", " \n", " \n", "
    \n", "

    omkeerbare filter - omkeerbare filter

    \n", "
    \n", " \n", " \n", "
    \n", "

    peilfilter - peilfilter

    \n", "
    \n", " \n", " \n", "
    \n", "

    pompfilter - pompfilter

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

meetnet - Het meetnet waartoe de filter behoort.

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.FeatureCatalogueValues\n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 1 - primair meetnet - afdeling Water - meetnet 1 - primair meetnet - afdeling Water

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 10 - rubriek 55 (verticale boringen) - meetnet 10 - rubriek 55 (verticale boringen)

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 11 - rubriek 53.6 (koude-warmtepompen) - meetnet 11 - rubriek 53.6 (koude-warmtepompen)

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 3 - tijdelijk meetnet - afdeling Water - meetnet 3 - tijdelijk meetnet - afdeling Water

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 4 - externe instanties - meetnet 4 - externe instanties

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 5 - peilputten drinkwatermaatschappijen - meetnet 5 - peilputten drinkwatermaatschappijen

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 6 - peilputten individuele bedrijven - meetnet 6 - peilputten individuele bedrijven

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 7 - winningsputten - meetnet 7 - winningsputten

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 8 - freatisch meetnet - afdeling water - meetnet 8 - freatisch meetnet - afdeling water

    \n", "
    \n", " \n", " \n", "
    \n", "

    meetnet 9 - peilputten INBO en natuurorganisaties - meetnet 9 - peilputten INBO en natuurorganisaties

    \n", "
    \n", " \n", " \n", "
    \n", "

    onbekend - onbekend

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

x - De x-coördinaat van de put in het Lambert72 coördinaatsysteem (in meter, EPSG:31370).

  • type: float
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

y - De y-coördinaat van de put in het Lambert72 coördinaatsysteem (in meter, EPSG:31370).

  • type: float
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

start_grondwaterlocatie_mtaw - De hoogte van het aanvangspeil van de put in het TAW stelsel (in meter).

  • type: float
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

gemeente - De gemeente waarin de put gelegen is

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

grondwaterlichaam - Het grondwaterlichaam waarin de filter hangt. Als tekst, opgebouwd uit de afkorting en de naam gescheiden door \" - \"

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

afgesloten_volgens_gwdecreet - None

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

datum_in_filter - De datum wanneer de filter in gebruik genomen is

  • type: date
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

datum_uit_filter - De datum wanneer de filter uit gebruik genomen is

  • type: date
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

stijghoogterapport - URL die verwijst naar het stijghoogterapport van de grondwaterlocatie in PDF formaat.

  • type: string
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

analyserapport - URL die verwijst naar het analyserapport van de grondwaterlocatie in PDF formaat.

  • type: string
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

boornummer - Het boornummer (ook gekend als proefnummer) van de boring.

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

boringfiche - Permanente URL die verwijst naar de gegevens van de boring op de website. Voeg '.xml' toe om een XML voorstelling van deze gegevens te verkrijgen.

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

peilmetingen_van - Datum waarop de eerste peilmeting werd uitgevoerd.

  • type: date
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

peilmetingen_tot - Datum waarop de laatste peilmeting werd uitgevoerd.

  • type: date
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

kwaliteitsmetingen_van - Datum waarop het eerste grondwaterstaal op deze filter werd genomen

  • type: date
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

kwaliteitsmetingen_tot - Datum waarop het laatste grondwaterstaal op deze filter werd genomen.

  • type: date
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

recentste_exploitant - De recentste exploitant van een grondwaterlocatie (installatieput)

  • type: string
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

beheerder - De huidige beheerder van een grondwaterlocatie (meetnetput)

  • type: string
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

aantal_dagen_sinds_laatste_meting - None

  • type: integer
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

eerste_invoer - Het tijdstip waarop deze filter voor het eerst in DOV ingevoerd werd. In het geval van een grondwaterlocatie zonder filter: het tijdstip waarop deze grondwaterlocatie voor het eerst in DOV ingevoerd werd.

  • type: datetime
  • notnull: True
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

recentste_installatie - De unieke identificatie van de meest recente installatie waaraan deze grondwaterlocatie gekoppeld is.

  • type: string
  • notnull: False
  • query: True
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

geom - None

  • type: geometry
  • notnull: False
  • query: False
  • cost: 1
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

meetnet_code - Tot welk meetnet behoort deze filter.

  • type: string
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.XsdType\n", "
    \n", " \n", " \n", "
    \n", "

    0 - 0 - onbekend

    \n", "
    \n", " \n", " \n", "
    \n", "

    1 - 1 - meetnet 1 - primair meetnet - afdeling Water

    \n", "
    \n", " \n", " \n", "
    \n", "

    10 - 10 - meetnet10 - rubriek 55 (verticale boringen)

    \n", "
    \n", " \n", " \n", "
    \n", "

    100 - 100 - meetnet 100 - Geotechniek

    \n", "
    \n", " \n", " \n", "
    \n", "

    11 - 11 - meetnet 11 - rubriek 53.6 (koude-warmtepompen)

    \n", "
    \n", " \n", " \n", "
    \n", "

    12 - 12 - meetnet 12 - lokale besturen

    \n", "
    \n", " \n", " \n", "
    \n", "

    2 - 2 - meetnet 2 - onzekere kwaliteit - afdeling Water

    \n", "
    \n", " \n", " \n", "
    \n", "

    3 - 3 - meetnet 3 - tijdelijk meetnet - afdeling Water

    \n", "
    \n", " \n", " \n", "
    \n", "

    4 - 4 - meetnet 4 - externe instanties

    \n", "
    \n", " \n", " \n", "
    \n", "

    5 - 5 - meetnet 5 - peilputten drinkwatermaatschappijen

    \n", "
    \n", " \n", " \n", "
    \n", "

    6 - 6 - meetnet 6 - peilputten individuele bedrijven

    \n", "
    \n", " \n", " \n", "
    \n", "

    7 - 7 - meetnet 7 - winningsputten

    \n", "
    \n", " \n", " \n", "
    \n", "

    8 - 8 - meetnet 8 - freatisch meetnet - afdeling water

    \n", "
    \n", " \n", " \n", "
    \n", "

    9 - 9 - meetnet 9 - peilputten INBO en natuurorganisaties

    \n", "
    \n", " \n", " \n", "
    \n", "

    edov - edov - meetnet 20 – eDOV erkende boorbedrijven

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

aquifer_code - De aquifer (watervoerende laag) waarin de filter hangt (code) (HCOVv2)

  • type: string
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.XsdType\n", "
    \n", " \n", " \n", "
    \n", "

    A0000 - A0000 - Onbepaald

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0100 - A0100 - Quartaire Aquifersystemen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0110 - A0110 - Ophogingen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0120 - A0120 - Duinen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0130 - A0130 - Polderafzettingen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0131 - A0131 - Kleiige polderafzettingen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0132 - A0132 - Zandige Kreekruggen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0133 - A0133 - Veen-kleiige poelgronden

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0134 - A0134 - Strandafzettingen***

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0140 - A0140 - Alluviale deklagen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0150 - A0150 - Eolische deklagen buiten de Roerdalslenk

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0151 - A0151 - Zandige deklagen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0152 - A0152 - Zand-lemige deklagen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0153 - A0153 - Lemige deklagen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0160 - A0160 - Fluvio-eolische deklagen binnen de Roerdalslenk

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0161 - A0161 - Boxtel zand 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0162 - A0162 - Boxtel klei 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0163 - A0163 - Boxtel zand 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0164 - A0164 - Boxtel klei 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0165 - A0165 - Boxtel zand 3

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0170 - A0170 - Pleistocene afzettingen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0180 - A0180 - Maas- en Rijnafzettingen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0181 - A0181 - Beegden zand 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0182 - A0182 - Beegden klei 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0183 - A0183 - Beegden zand 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0184 - A0184 - Beegden klei 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0185 - A0185 - Beegden zand 3

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0186 - A0186 - Beegden ongedifferentieerd

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0187 - A0187 - Sterksel zand 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0188 - A0188 - Sterksel klei 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0189 - A0189 - Sterksel zand 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0200 - A0200 - Kempens Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0210 - A0210 - Klei-zand complex van de Kempen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0220 - A0220 - Pleistoceen en Plioceen Aquifersysteem - west

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0221 - A0221 - Kleiig zand van Malle

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0222 - A0222 - Zand van Merksplas

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0223 - A0223 - Zanden van Zandvliet en Merksem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0224 - A0224 - Kleiig zand van Kruisschans

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0225 - A0225 - Zanden van Oorderen en Luchtbal

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0226 - A0226 - Ongedifferentieerde zanden van Lillo en Poederlee

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0230 - A0230 - Pleistoceen en Plioceen Aquifersysteem - oost

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0231 - A0231 - Zand van Mol

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0232 - A0232 - Kiezeloöliet zand 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0233 - A0233 - Kiezeloöliet klei 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0234 - A0234 - Kiezeloöliet zand 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0235 - A0235 - Kiezeloöliet klei 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0236 - A0236 - Kiezeloöliet zand 3

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0237 - A0237 - Kiezeloöliet klei 3

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0238 - A0238 - Kiezeloöliet zand 4

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0240 - A0240 - Kleiige zanden van Kattendijk en Kasterlee

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0250 - A0250 - Mioceen Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0251 - A0251 - Zand van Diest buiten de Roerdalslenk

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0252 - A0252 - Zanden van Diest en Bolderberg binnen de Roerdalslenk

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0253 - A0253 - Zand van Bolderberg buiten de Roerdalslenk

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0254 - A0254 - Zanden van Berchem en Voort buiten de Roerdalslenk

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0255 - A0255 - Voort zand 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0256 - A0256 - Voort klei 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0257 - A0257 - Voort zand 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0258 - A0258 - Zandig deel van Eigenbilzen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0300 - A0300 - Boom Aquitard

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0301 - A0301 - Kleiig deel van Eigenbilzen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0302 - A0302 - Klei-silt van Boeretang

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0303 - A0303 - Klei van Putte

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0304 - A0304 - Klei van Terhagen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0305 - A0305 - Silt van Belsele-Waas

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0400 - A0400 - Oligoceen Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0410 - A0410 - Zand van Kerniel

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0420 - A0420 - Klei van Kleine-Spouwen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0430 - A0430 - Ruisbroek-Berg Aquifer

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0431 - A0431 - Zand van Berg

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0432 - A0432 - Zand van Ruisbroek

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0433 - A0433 - Zand van Kerkom

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0434 - A0434 - Kleiig zand van Alden Biesen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0440 - A0440 - Tongeren Aquitard

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0441 - A0441 - Klei van Henis

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0442 - A0442 - Zandige klei van Watervliet

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0450 - A0450 - Onder-Oligoceen Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0451 - A0451 - Zand van Neerrepen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0452 - A0452 - Kleiig zand van Grimmertingen

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0453 - A0453 - Kleiig zand van Bassevelde

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0500 - A0500 - Bartoon Aquitardsysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0501 - A0501 - Bartoon klei 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0502 - A0502 - Bartoon zand 1

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0503 - A0503 - Bartoon klei 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0504 - A0504 - Bartoon zand 2

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0505 - A0505 - Bartoon klei 3

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0600 - A0600 - Ledo Paniseliaan Brusseliaan Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0610 - A0610 - Wemmel-Lede Aquifer

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0611 - A0611 - Zand van Wemmel

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0612 - A0612 - Zand van Lede

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0620 - A0620 - Zand van Brussel

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0630 - A0630 - Afzettingen van het Paniseliaan

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0631 - A0631 - Zand van Oedelem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0632 - A0632 - Zandige klei van Beernem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0633 - A0633 - Zanden van Aalterbrugge en Vlierzele

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0700 - A0700 - Paniseliaan Aquitardsysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0701 - A0701 - Kleiig zand van Pittem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0702 - A0702 - Klei van Merelbeke

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0800 - A0800 - Ieperiaan Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0801 - A0801 - Zand van Egem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0802 - A0802 - Klei van Egemkapel

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0803 - A0803 - Silt van Kortemark en zand van Mont-Panisel

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0900 - A0900 - Ieperiaan Aquitardsysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0901 - A0901 - Klei van Aalbeke

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0902 - A0902 - Zandige klei van Roubaix

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0903 - A0903 - Kleiig zand van Mons-en-Pévèle

    \n", "
    \n", " \n", " \n", "
    \n", "

    A0904 - A0904 - Kleien van Orchies, Mont-Héribu en Het Zoute

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1000 - A1000 - Paleoceen Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1010 - A1010 - Landeniaan Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1011 - A1011 - Zand van Knokke

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1012 - A1012 - Zandige afzettingen van Loksbergen en Dormaal

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1013 - A1013 - Zand van Grandglise

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1020 - A1020 - Landeniaan en Heersiaan Aquitard

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1021 - A1021 - Siltige afzettingen van Halen en Tufsteen van Lincent

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1022 - A1022 - Kleien van Waterschei en Beselare

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1030 - A1030 - Heersiaan en Opglabbeek Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1031 - A1031 - Kleiige mergels van Maaseik

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1032 - A1032 - Mergels van Gelinden

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1033 - A1033 - Zand van Orp

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1034 - A1034 - Zand van Eisden

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1035 - A1035 - Klei van Opoeteren

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1100 - A1100 - Krijt Aquifersysteem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1101 - A1101 - Kalkareniet van Houthem

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1102 - A1102 - Kalkarenieten van Maastricht en Kunrade

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1103 - A1103 - Krijtafzettingen van Gulpen en Nevele, zanden en mergels van Vaals en Dorne en de Turoonmergels

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1104 - A1104 - Zand van Aken

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1200 - A1200 - Jura - Trias - Perm

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1210 - A1210 - Jura (incl. Sleen)

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1220 - A1220 - Trias (excl. Sleen) en Perm

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1300 - A1300 - Sokkel

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1310 - A1310 - Boven-Carboon (steenkoolterrein en -lagen)

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1320 - A1320 - Kolenkalk (incl. Wealdiaan)

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1330 - A1330 - Devoon

    \n", "
    \n", " \n", " \n", "
    \n", "

    A1340 - A1340 - Cambro-Siluur Massief van Brabant

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

grondwaterlichaam_code -

  • type: string
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.XsdType\n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0160_GWL_1M - BLKS_0160_GWL_1M - Quartaire Maas- en Rijnafzettingen, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0160_GWL_1S - BLKS_0160_GWL_1S - Pleistoceen Rivierafzettingen, lokaal gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0400_GWL_1M - BLKS_0400_GWL_1M - Oligoceen Aquifersysteem, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0400_GWL_1S - BLKS_0400_GWL_1S - Oligoceen Aquifersysteem, lokaal freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0400_GWL_2M - BLKS_0400_GWL_2M - Oligoceen Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0400_GWL_2S - BLKS_0400_GWL_2S - Oligoceen Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0600_GWL_1 - BLKS_0600_GWL_1 - Brusseliaan Aquifer, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0600_GWL_2 - BLKS_0600_GWL_2 - Brusseliaan Aquifer, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_0600_GWL_3 - BLKS_0600_GWL_3 - Brusseliaan venster: contact met Diestiaan, lokaal gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_1000_GWL_1S - BLKS_1000_GWL_1S - Landeniaan Aquifersysteem, lokaal gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_1000_GWL_2S - BLKS_1000_GWL_2S - Landeniaan Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_1100_GWL_1M - BLKS_1100_GWL_1M - Krijt Aquifersysteem, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_1100_GWL_1S - BLKS_1100_GWL_1S - Krijt Aquifersysteem, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_1100_GWL_2M - BLKS_1100_GWL_2M - Krijt Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    BLKS_1100_GWL_2S - BLKS_1100_GWL_2S - Krijt Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    CKS_0200_GWL_1 - CKS_0200_GWL_1 - Centrale zanden van de Kempen, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CKS_0200_GWL_2 - CKS_0200_GWL_2 - Noordelijke Zanden van de Kempen, freatisch, plaatselijk semi-freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CKS_0220_GWL_1 - CKS_0220_GWL_1 - Complex van de Kempen, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CKS_0250_GWL_1 - CKS_0250_GWL_1 - Diestiaangeul: contact Brusseliaan, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CVS_0100_GWL_1 - CVS_0100_GWL_1 - Dun Quartair dek boven op Paleogeen klei, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CVS_0160_GWL_1 - CVS_0160_GWL_1 - Pleistoceen afzettingen, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CVS_0400_GWL_1 - CVS_0400_GWL_1 - Oligoceen Aquifersysteem, lokaal freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CVS_0600_GWL_1 - CVS_0600_GWL_1 - Ledo-Paniseliaan Aquifersysteem, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CVS_0600_GWL_2 - CVS_0600_GWL_2 - Ledo-Paniseliaan Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    CVS_0800_GWL_1 - CVS_0800_GWL_1 - Ieperiaan Aquifer, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    CVS_0800_GWL_2 - CVS_0800_GWL_2 - Ieperiaan Aquifer, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    CVS_0800_GWL_3 - CVS_0800_GWL_3 - Ieperiaan Aquifer Heuvelstreken, lokaal gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    KPS_0120_GWL_1 - KPS_0120_GWL_1 - Duin- en kreekgebieden in het kustgebied, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    KPS_0120_GWL_2 - KPS_0120_GWL_2 - Duin- en kreekgebieden in de Oost-Vlaamse Polders, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    KPS_0160_GWL_1 - KPS_0160_GWL_1 - verzilt Quartair en Eoceen van het kustgebied, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    KPS_0160_GWL_2 - KPS_0160_GWL_2 - verzilt Quartair en Oligoceen van Oost-Vlaamse Polders, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    KPS_0160_GWL_3 - KPS_0160_GWL_3 - verzilt Quartair, Plioceen en Mioceen van Scheldepolders, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    MS_0100_GWL_1 - MS_0100_GWL_1 - Quartair Aquifersysteem, freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    MS_0200_GWL_1 - MS_0200_GWL_1 - Kempens Aquifersysteem, freatisch, plaatselijk semi-freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    MS_0200_GWL_2 - MS_0200_GWL_2 - Kempens Aquifersysteem in de Centrale Slenk, freatisch, plaatselijk semi-freatisch

    \n", "
    \n", " \n", " \n", "
    \n", "

    SS_1000_GWL_1 - SS_1000_GWL_1 - Landeniaan Aquifersysteem, depressietrechter, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    SS_1000_GWL_2 - SS_1000_GWL_2 - Landeniaan Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    SS_1300_GWL_1 - SS_1300_GWL_1 - Kolenkalk, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    SS_1300_GWL_2 - SS_1300_GWL_2 - Sokkel + Krijt Aquifersysteem, lokaal freatisch, voedingsgebied

    \n", "
    \n", " \n", " \n", "
    \n", "

    SS_1300_GWL_3 - SS_1300_GWL_3 - Sokkel + Krijt Aquifersysteem, depressietrechter, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    SS_1300_GWL_4 - SS_1300_GWL_4 - Sokkel + Krijt Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    SS_1300_GWL_5 - SS_1300_GWL_5 - Sokkel + Krijt Aquifersysteem, depressietrechter, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    X_BLKS_0400_GWL_2 - X_BLKS_0400_GWL_2 - Ten noorden van de grens van het BLKS, in het Oligoceen Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    X_BLKS_0600_GWL_2 - X_BLKS_0600_GWL_2 - Ten N van de grens van het BLKS, in de Brusseliaan Aquifer, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    X_BLKS_1000_GWL_2 - X_BLKS_1000_GWL_2 - Ten N van de grens van het BLKS, in het Landeniaan Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    X_BLKS_1100_GWL_2 - X_BLKS_1100_GWL_2 - Ten N van de grens van het BLKS, in het Krijt Aquifersysteem, gespannen

    \n", "
    \n", " \n", " \n", "
    \n", "

    meerdere GWL - meerdere GWL - Bevat filters in meerder grondwaterlichamen

    \n", "
    \n", " \n", " \n", "
    \n", "

    onbekend - onbekend - onbekend

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

regime -

  • type: string
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

datum - Datum waarop de peilmeting uitgevoerd werd.

  • type: date
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

tijdstip - Tijdstip waarop de peilmeting uitgevoerd werd (optioneel).

  • type: string
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

peil_mtaw - Diepte van de peilmeting, uitgedrukt in mTAW.

  • type: float
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

betrouwbaarheid - Betrouwbaarheid van de peilmeting (goed, onbekend of twijfelachtig).

  • type: string
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
\n", "
\n", " \n", " \n", "
\n", "

methode - Methode waarop de peilmeting uitgevoerd werd.

  • type: string
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.XsdType\n", "
    \n", " \n", " \n", "
    \n", "

    Dieptelood - Dieptelood

    \n", "
    \n", " \n", " \n", "
    \n", "

    Onbekend - Onbekend

    \n", "
    \n", " \n", " \n", "
    \n", "

    andere methode - andere methode

    \n", "
    \n", " \n", " \n", "
    \n", "

    automatische sonde - automatische sonde

    \n", "
    \n", " \n", " \n", "
    \n", "

    borrelbuis - borrelbuis

    \n", "
    \n", " \n", " \n", "
    \n", "

    gemiddelde van loggermetingen - gemiddelde van loggermetingen

    \n", "
    \n", " \n", " \n", "
    \n", "

    manometer - manometer

    \n", "
    \n", " \n", " \n", "
    \n", "

    peillint - peillint

    \n", "
    \n", " \n", " \n", "
    \n", "

    peilmeting onmogelijk - peilmeting onmogelijk

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

filterstatus - Status van de filter tijdens de peilmeting (in rust - werking).

  • type: string
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.XsdType\n", "
    \n", " \n", " \n", "
    \n", "

    in rust - in rust

    \n", "
    \n", " \n", " \n", "
    \n", "

    onbekend - onbekend

    \n", "
    \n", " \n", " \n", "
    \n", "

    werking - werking

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

filtertoestand - Filtertoestand bij de peilmeting. Standaardwaarde is '1' = Normaal.

  • type: integer
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
  • codelist:
    • \n", " \n", "
    \n", " \n", "
    \n", " pydov.util.codelists.XsdType\n", "
    \n", " \n", " \n", "
    \n", "

    -999 - -999 - Vertrouwelijk (SCK-meting)

    \n", "
    \n", " \n", " \n", "
    \n", "

    -998 - -998 - Past niet in de stijghoogtereeks

    \n", "
    \n", " \n", " \n", "
    \n", "

    -990 - -990 - Verdwenen

    \n", "
    \n", " \n", " \n", "
    \n", "

    -985 - -985 - Infiltratie

    \n", "
    \n", " \n", " \n", "
    \n", "

    -981 - -981 - Buiten bereik Diver (VMW-980)

    \n", "
    \n", " \n", " \n", "
    \n", "

    -980 - -980 - Afpomping

    \n", "
    \n", " \n", " \n", "
    \n", "

    -971 - -971 - \"Meting onder filter (VMW-970)\"

    \n", "
    \n", " \n", " \n", "
    \n", "

    -970 - -970 - Onder water

    \n", "
    \n", " \n", " \n", "
    \n", "

    -960 - -960 - Loopt over

    \n", "
    \n", " \n", " \n", "
    \n", "

    -950 - -950 - Vervallen

    \n", "
    \n", " \n", " \n", "
    \n", "

    -940 - -940 - Verstopt

    \n", "
    \n", " \n", " \n", "
    \n", "

    -930 - -930 - Beschadigd/defekt

    \n", "
    \n", " \n", " \n", "
    \n", "

    -920 - -920 - Bevroren

    \n", "
    \n", " \n", " \n", "
    \n", "

    -910 - -910 - droog

    \n", "
    \n", " \n", " \n", "
    \n", "

    -905 - -905 - \"Geen meting (onbereikbaar)

    \n", "
    \n", " \n", " \n", "
    \n", "

    -903 - -903 - Afgesloten van het net (VMW)

    \n", "
    \n", " \n", " \n", "
    \n", "

    -902 - -902 - Vee in de weide (VMW)

    \n", "
    \n", " \n", " \n", "
    \n", "

    -901 - -901 - Werken aan de put (VMW)

    \n", "
    \n", " \n", " \n", "
    \n", "

    -900 - -900 - Geen waarneming

    \n", "
    \n", " \n", " \n", "
    \n", "

    1 - 1 - normaal

    \n", "
    \n", " \n", "
    \n", "
\n", "
\n", " \n", " \n", "
\n", "

mv_mtaw - Maaiveldhoogte in mTAW op dag dat de put/boring uitgevoerd werd

  • type: float
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
\n", "
\n", "

\n", "
\n", " " ], "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gwfilter" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Example use cases" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get groundwater screens in a bounding box" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Get data for all the groundwater screens that are geographically located within the bounds of the specified box.\n", "\n", "The coordinates are in the Belgian Lambert72 (EPSG:31370) coordinate system and are given in the order of lower left x, lower left y, upper right x, upper right y." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n", "[000/026] ..........................\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filterpkey_grondwaterlocatiegw_idfilternummerfiltertypexystart_grondwaterlocatie_mtawmv_mtawgemeente...regimediepte_onderkant_filterlengte_filterdatumtijdstippeil_mtawbetrouwbaarheidmethodefilterstatusfiltertoestand
0https://www.dov.vlaanderen.be/data/filter/1999...https://www.dov.vlaanderen.be/data/put/2018-00...SWPP0201peilfilter93913.0169219.09.749.74Wortegem-Petegem...onbekendNaNNaN1999-04-13NaN9.49onbekendpeillintonbekend1.0
1https://www.dov.vlaanderen.be/data/filter/1999...https://www.dov.vlaanderen.be/data/put/2018-00...SWPP0201peilfilter93913.0169219.09.749.74Wortegem-Petegem...onbekendNaNNaN1999-04-14NaN9.74onbekendpeillintonbekend1.0
2https://www.dov.vlaanderen.be/data/filter/1999...https://www.dov.vlaanderen.be/data/put/2018-00...SWPP0201peilfilter93913.0169219.09.749.74Wortegem-Petegem...onbekendNaNNaN1999-04-22NaN9.74onbekendpeillintonbekend1.0
3https://www.dov.vlaanderen.be/data/filter/1999...https://www.dov.vlaanderen.be/data/put/2018-00...SWPP0201peilfilter93913.0169219.09.749.74Wortegem-Petegem...onbekendNaNNaN1999-05-06NaN9.74onbekendpeillintonbekend1.0
4https://www.dov.vlaanderen.be/data/filter/1999...https://www.dov.vlaanderen.be/data/put/2018-00...SWPP0201peilfilter93913.0169219.09.749.74Wortegem-Petegem...onbekendNaNNaN1999-05-18NaN9.70onbekendpeillintonbekend1.0
\n", "

5 rows × 23 columns

\n", "
" ], "text/plain": [ " pkey_filter \\\n", "0 https://www.dov.vlaanderen.be/data/filter/1999... \n", "1 https://www.dov.vlaanderen.be/data/filter/1999... \n", "2 https://www.dov.vlaanderen.be/data/filter/1999... \n", "3 https://www.dov.vlaanderen.be/data/filter/1999... \n", "4 https://www.dov.vlaanderen.be/data/filter/1999... \n", "\n", " pkey_grondwaterlocatie gw_id filternummer \\\n", "0 https://www.dov.vlaanderen.be/data/put/2018-00... SWPP020 1 \n", "1 https://www.dov.vlaanderen.be/data/put/2018-00... SWPP020 1 \n", "2 https://www.dov.vlaanderen.be/data/put/2018-00... SWPP020 1 \n", "3 https://www.dov.vlaanderen.be/data/put/2018-00... SWPP020 1 \n", "4 https://www.dov.vlaanderen.be/data/put/2018-00... SWPP020 1 \n", "\n", " filtertype x y start_grondwaterlocatie_mtaw mv_mtaw \\\n", "0 peilfilter 93913.0 169219.0 9.74 9.74 \n", "1 peilfilter 93913.0 169219.0 9.74 9.74 \n", "2 peilfilter 93913.0 169219.0 9.74 9.74 \n", "3 peilfilter 93913.0 169219.0 9.74 9.74 \n", "4 peilfilter 93913.0 169219.0 9.74 9.74 \n", "\n", " gemeente ... regime diepte_onderkant_filter lengte_filter \\\n", "0 Wortegem-Petegem ... onbekend NaN NaN \n", "1 Wortegem-Petegem ... onbekend NaN NaN \n", "2 Wortegem-Petegem ... onbekend NaN NaN \n", "3 Wortegem-Petegem ... onbekend NaN NaN \n", "4 Wortegem-Petegem ... onbekend NaN NaN \n", "\n", " datum tijdstip peil_mtaw betrouwbaarheid methode filterstatus \\\n", "0 1999-04-13 NaN 9.49 onbekend peillint onbekend \n", "1 1999-04-14 NaN 9.74 onbekend peillint onbekend \n", "2 1999-04-22 NaN 9.74 onbekend peillint onbekend \n", "3 1999-05-06 NaN 9.74 onbekend peillint onbekend \n", "4 1999-05-18 NaN 9.70 onbekend peillint onbekend \n", "\n", " filtertoestand \n", "0 1.0 \n", "1 1.0 \n", "2 1.0 \n", "3 1.0 \n", "4 1.0 \n", "\n", "[5 rows x 23 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from pydov.util.location import Within, Box\n", "\n", "df = gwfilter.search(location=Within(Box(93378, 168009, 94246, 169873, epsg=31370)))\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using the *pkey* attributes one can request the details of the corresponding *put* or *filter* in a webbrowser:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "https://www.dov.vlaanderen.be/data/put/2018-007290\n", "https://www.dov.vlaanderen.be/data/put/2018-007287\n", "https://www.dov.vlaanderen.be/data/put/2018-007300\n", "https://www.dov.vlaanderen.be/data/put/2019-019725\n", "https://www.dov.vlaanderen.be/data/put/2018-007293\n", "https://www.dov.vlaanderen.be/data/put/2018-007295\n", "https://www.dov.vlaanderen.be/data/put/2018-007305\n", "https://www.dov.vlaanderen.be/data/put/2019-020544\n", "https://www.dov.vlaanderen.be/data/put/2018-007289\n", "https://www.dov.vlaanderen.be/data/put/2018-007313\n", "https://www.dov.vlaanderen.be/data/put/2018-007292\n", "https://www.dov.vlaanderen.be/data/put/2018-007311\n", "https://www.dov.vlaanderen.be/data/put/2017-002867\n", "https://www.dov.vlaanderen.be/data/put/2018-007299\n", "https://www.dov.vlaanderen.be/data/put/2018-007291\n", "https://www.dov.vlaanderen.be/data/put/2018-007304\n", "https://www.dov.vlaanderen.be/data/put/2017-002866\n", "https://www.dov.vlaanderen.be/data/put/2018-007288\n", "https://www.dov.vlaanderen.be/data/put/2017-002868\n", "https://www.dov.vlaanderen.be/data/put/2018-007307\n", "https://www.dov.vlaanderen.be/data/put/2018-007286\n", "https://www.dov.vlaanderen.be/data/put/2018-007285\n", "https://www.dov.vlaanderen.be/data/put/2018-007310\n", "https://www.dov.vlaanderen.be/data/put/2018-007294\n", "https://www.dov.vlaanderen.be/data/put/2018-007296\n", "https://www.dov.vlaanderen.be/data/put/2018-007312\n", "https://www.dov.vlaanderen.be/data/filter/1999-011029\n", "https://www.dov.vlaanderen.be/data/filter/1999-011004\n", "https://www.dov.vlaanderen.be/data/filter/1999-011011\n", "https://www.dov.vlaanderen.be/data/filter/1999-011014\n", "https://www.dov.vlaanderen.be/data/filter/1999-011013\n", "https://www.dov.vlaanderen.be/data/filter/2007-011018\n", "https://www.dov.vlaanderen.be/data/filter/1999-000607\n", "https://www.dov.vlaanderen.be/data/filter/1999-000606\n", "https://www.dov.vlaanderen.be/data/filter/1995-061303\n", "https://www.dov.vlaanderen.be/data/filter/1999-011008\n", "https://www.dov.vlaanderen.be/data/filter/2007-011024\n", "https://www.dov.vlaanderen.be/data/filter/1999-011007\n", "https://www.dov.vlaanderen.be/data/filter/1999-011010\n", "https://www.dov.vlaanderen.be/data/filter/1999-011005\n", "https://www.dov.vlaanderen.be/data/filter/1999-000605\n", "https://www.dov.vlaanderen.be/data/filter/1999-011006\n", "https://www.dov.vlaanderen.be/data/filter/2007-011019\n", "https://www.dov.vlaanderen.be/data/filter/1999-011032\n", "https://www.dov.vlaanderen.be/data/filter/1999-011015\n", "https://www.dov.vlaanderen.be/data/filter/1999-011031\n", "https://www.dov.vlaanderen.be/data/filter/2009-011026\n", "https://www.dov.vlaanderen.be/data/filter/1991-062098\n", "https://www.dov.vlaanderen.be/data/filter/1999-011030\n", "https://www.dov.vlaanderen.be/data/filter/1999-011009\n", "https://www.dov.vlaanderen.be/data/filter/1999-011012\n", "https://www.dov.vlaanderen.be/data/filter/2007-011023\n" ] } ], "source": [ "for pkey_grondwaterlocatie in set(df.pkey_grondwaterlocatie):\n", " print(pkey_grondwaterlocatie)\n", "\n", "for pkey_filter in set(df.pkey_filter):\n", " print(pkey_filter)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get groundwater screens with specific properties" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next to querying groundwater screens based on their geographic location within a bounding box, we can also search for groundwater screens matching a specific set of properties. For this we can build a query using a combination of the 'GrondwaterFilter' fields and operators provided by the WFS protocol.\n", "\n", "A list of possible operators can be found below:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['PropertyIsBetween',\n", " 'PropertyIsEqualTo',\n", " 'PropertyIsGreaterThan',\n", " 'PropertyIsGreaterThanOrEqualTo',\n", " 'PropertyIsLessThan',\n", " 'PropertyIsLessThanOrEqualTo',\n", " 'PropertyIsLike',\n", " 'PropertyIsNotEqualTo',\n", " 'PropertyIsNull',\n", " 'SortProperty']" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[i for i,j in inspect.getmembers(sys.modules['owslib.fes2'], inspect.isclass) if 'Property' in i]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this example we build a query using the *PropertyIsEqualTo* operator to find all groundwater screens that are within the community (gemeente) of 'Hamme':" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n", "[000/002] ..\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filterpkey_grondwaterlocatiegw_idfilternummerfiltertypexystart_grondwaterlocatie_mtawmv_mtawgemeente...regimediepte_onderkant_filterlengte_filterdatumtijdstippeil_mtawbetrouwbaarheidmethodefilterstatusfiltertoestand
0https://www.dov.vlaanderen.be/data/filter/1993...https://www.dov.vlaanderen.be/data/put/2019-02...7-0010161pompfilter224798.0157819.0130.80130.80Herstappe...freatisch45.05.0NaNNaNNaNNaNNaNNaNNaN
1https://www.dov.vlaanderen.be/data/filter/1900...https://www.dov.vlaanderen.be/data/put/2019-05...7-970271pompfilter224843.0157842.0132.09132.09Herstappe...onbekendNaNNaNNaNNaNNaNNaNNaNNaNNaN
\n", "

2 rows × 23 columns

\n", "
" ], "text/plain": [ " pkey_filter \\\n", "0 https://www.dov.vlaanderen.be/data/filter/1993... \n", "1 https://www.dov.vlaanderen.be/data/filter/1900... \n", "\n", " pkey_grondwaterlocatie gw_id filternummer \\\n", "0 https://www.dov.vlaanderen.be/data/put/2019-02... 7-001016 1 \n", "1 https://www.dov.vlaanderen.be/data/put/2019-05... 7-97027 1 \n", "\n", " filtertype x y start_grondwaterlocatie_mtaw mv_mtaw \\\n", "0 pompfilter 224798.0 157819.0 130.80 130.80 \n", "1 pompfilter 224843.0 157842.0 132.09 132.09 \n", "\n", " gemeente ... regime diepte_onderkant_filter lengte_filter datum \\\n", "0 Herstappe ... freatisch 45.0 5.0 NaN \n", "1 Herstappe ... onbekend NaN NaN NaN \n", "\n", " tijdstip peil_mtaw betrouwbaarheid methode filterstatus filtertoestand \n", "0 NaN NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN NaN \n", "\n", "[2 rows x 23 columns]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from owslib.fes2 import PropertyIsEqualTo\n", "\n", "query = PropertyIsEqualTo(\n", " propertyname='gemeente',\n", " literal='Herstappe')\n", "\n", "df = gwfilter.search(query=query)\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once again we can use the *pkey_filter* as a permanent link to the information of the groundwater screens:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "https://www.dov.vlaanderen.be/data/filter/1900-050992\n", "https://www.dov.vlaanderen.be/data/filter/1993-065801\n" ] } ], "source": [ "for pkey_filter in set(df.pkey_filter):\n", " print(pkey_filter)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get the coordinates of all groundwater screens in Ghent" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filterxymeetnet
0https://www.dov.vlaanderen.be/data/filter/1997...106124.00199042.00meetnet 7 - winningsputten
1https://www.dov.vlaanderen.be/data/filter/2025...101458.94190074.92meetnet 100 - Geotechniek
2https://www.dov.vlaanderen.be/data/filter/1999...109236.00192894.00meetnet 9 - peilputten INBO en natuurorganisaties
3https://www.dov.vlaanderen.be/data/filter/1998...109642.00208006.00meetnet 7 - winningsputten
4https://www.dov.vlaanderen.be/data/filter/1999...109264.00192359.00meetnet 9 - peilputten INBO en natuurorganisaties
\n", "
" ], "text/plain": [ " pkey_filter x y \\\n", "0 https://www.dov.vlaanderen.be/data/filter/1997... 106124.00 199042.00 \n", "1 https://www.dov.vlaanderen.be/data/filter/2025... 101458.94 190074.92 \n", "2 https://www.dov.vlaanderen.be/data/filter/1999... 109236.00 192894.00 \n", "3 https://www.dov.vlaanderen.be/data/filter/1998... 109642.00 208006.00 \n", "4 https://www.dov.vlaanderen.be/data/filter/1999... 109264.00 192359.00 \n", "\n", " meetnet \n", "0 meetnet 7 - winningsputten \n", "1 meetnet 100 - Geotechniek \n", "2 meetnet 9 - peilputten INBO en natuurorganisaties \n", "3 meetnet 7 - winningsputten \n", "4 meetnet 9 - peilputten INBO en natuurorganisaties " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = PropertyIsEqualTo(propertyname='gemeente',\n", " literal='Gent')\n", "\n", "df = gwfilter.search(query=query,\n", " return_fields=('pkey_filter', 'x', 'y', 'meetnet'))\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get the 'meetnet' and 'meetnet_code' for groundwater screens in Boortmeerbeek" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n", "[000/062] ..................................................\n", "[050/062] ............\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filtermeetnetmeetnet_code
0https://www.dov.vlaanderen.be/data/filter/1969...meetnet 7 - winningsputten7
1https://www.dov.vlaanderen.be/data/filter/2006...meetnet 9 - peilputten INBO en natuurorganisaties9
2https://www.dov.vlaanderen.be/data/filter/1900...meetnet 3 - tijdelijk meetnet - afdeling Water3
3https://www.dov.vlaanderen.be/data/filter/1979...meetnet 7 - winningsputten7
4https://www.dov.vlaanderen.be/data/filter/2004...meetnet 7 - winningsputten7
\n", "
" ], "text/plain": [ " pkey_filter \\\n", "0 https://www.dov.vlaanderen.be/data/filter/1969... \n", "1 https://www.dov.vlaanderen.be/data/filter/2006... \n", "2 https://www.dov.vlaanderen.be/data/filter/1900... \n", "3 https://www.dov.vlaanderen.be/data/filter/1979... \n", "4 https://www.dov.vlaanderen.be/data/filter/2004... \n", "\n", " meetnet meetnet_code \n", "0 meetnet 7 - winningsputten 7 \n", "1 meetnet 9 - peilputten INBO en natuurorganisaties 9 \n", "2 meetnet 3 - tijdelijk meetnet - afdeling Water 3 \n", "3 meetnet 7 - winningsputten 7 \n", "4 meetnet 7 - winningsputten 7 " ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = PropertyIsEqualTo(propertyname='gemeente',\n", " literal='Boortmeerbeek')\n", "\n", "df = gwfilter.search(query=query,\n", " return_fields=('pkey_filter', 'meetnet', 'meetnet_code'))\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get all details of groundwaterscreens of 'meetnet 9' within the given bounding box" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n", "[000/017] .................\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filterpkey_grondwaterlocatiegw_idfilternummerfiltertypexystart_grondwaterlocatie_mtawmv_mtawgemeente...regimediepte_onderkant_filterlengte_filterdatumtijdstippeil_mtawbetrouwbaarheidmethodefilterstatusfiltertoestand
0https://www.dov.vlaanderen.be/data/filter/2002...https://www.dov.vlaanderen.be/data/put/2019-09...WVSP0281peilfilter89779.0165983.011.4111.41Avelgem...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1https://www.dov.vlaanderen.be/data/filter/2000...https://www.dov.vlaanderen.be/data/put/2019-09...PBRP0031peilfilter90313.0164385.014.3414.34Kluisbergen...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2https://www.dov.vlaanderen.be/data/filter/2000...https://www.dov.vlaanderen.be/data/put/2019-09...PBRP0071peilfilter90234.0164282.014.3814.38Kluisbergen...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3https://www.dov.vlaanderen.be/data/filter/2000...https://www.dov.vlaanderen.be/data/put/2019-09...PBRP0051peilfilter90234.0164282.014.3814.38Kluisbergen...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4https://www.dov.vlaanderen.be/data/filter/2000...https://www.dov.vlaanderen.be/data/put/2019-09...PBRP0021peilfilter90313.0164385.014.3414.34Kluisbergen...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
\n", "

5 rows × 23 columns

\n", "
" ], "text/plain": [ " pkey_filter \\\n", "0 https://www.dov.vlaanderen.be/data/filter/2002... \n", "1 https://www.dov.vlaanderen.be/data/filter/2000... \n", "2 https://www.dov.vlaanderen.be/data/filter/2000... \n", "3 https://www.dov.vlaanderen.be/data/filter/2000... \n", "4 https://www.dov.vlaanderen.be/data/filter/2000... \n", "\n", " pkey_grondwaterlocatie gw_id filternummer \\\n", "0 https://www.dov.vlaanderen.be/data/put/2019-09... WVSP028 1 \n", "1 https://www.dov.vlaanderen.be/data/put/2019-09... PBRP003 1 \n", "2 https://www.dov.vlaanderen.be/data/put/2019-09... PBRP007 1 \n", "3 https://www.dov.vlaanderen.be/data/put/2019-09... PBRP005 1 \n", "4 https://www.dov.vlaanderen.be/data/put/2019-09... PBRP002 1 \n", "\n", " filtertype x y start_grondwaterlocatie_mtaw mv_mtaw \\\n", "0 peilfilter 89779.0 165983.0 11.41 11.41 \n", "1 peilfilter 90313.0 164385.0 14.34 14.34 \n", "2 peilfilter 90234.0 164282.0 14.38 14.38 \n", "3 peilfilter 90234.0 164282.0 14.38 14.38 \n", "4 peilfilter 90313.0 164385.0 14.34 14.34 \n", "\n", " gemeente ... regime diepte_onderkant_filter lengte_filter datum \\\n", "0 Avelgem ... NaN NaN NaN NaN \n", "1 Kluisbergen ... NaN NaN NaN NaN \n", "2 Kluisbergen ... NaN NaN NaN NaN \n", "3 Kluisbergen ... NaN NaN NaN NaN \n", "4 Kluisbergen ... NaN NaN NaN NaN \n", "\n", " tijdstip peil_mtaw betrouwbaarheid methode filterstatus filtertoestand \n", "0 NaN NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN NaN NaN \n", "\n", "[5 rows x 23 columns]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from owslib.fes2 import PropertyIsLike\n", "\n", "query = PropertyIsLike(propertyname='meetnet',\n", " literal='meetnet 9 %')\n", "df = gwfilter.search(query=query,\n", " location=Within(Box(87676, 163442, 91194, 168043, epsg=31370)))\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get groundwater screens based on a combination of specific properties" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Get all groundwater screens in Hamme that have a value for length_filter and either belong to the primary meetnet of VMM or that have a depth bottom screen less than 3 meter." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filterxygw_idfilternummerdiepte_onderkant_filter
0https://www.dov.vlaanderen.be/data/filter/2006...137459.00000193510.000000GWZP01011.93
1https://www.dov.vlaanderen.be/data/filter/2006...137181.00000193667.000000GWZP00711.89
2https://www.dov.vlaanderen.be/data/filter/2006...136895.00000192591.000000GWZP00412.55
3https://www.dov.vlaanderen.be/data/filter/2003...131837.65625197054.203125810/21/112.50
4https://www.dov.vlaanderen.be/data/filter/2004...128749.00000199574.000000DURP01612.38
\n", "
" ], "text/plain": [ " pkey_filter x \\\n", "0 https://www.dov.vlaanderen.be/data/filter/2006... 137459.00000 \n", "1 https://www.dov.vlaanderen.be/data/filter/2006... 137181.00000 \n", "2 https://www.dov.vlaanderen.be/data/filter/2006... 136895.00000 \n", "3 https://www.dov.vlaanderen.be/data/filter/2003... 131837.65625 \n", "4 https://www.dov.vlaanderen.be/data/filter/2004... 128749.00000 \n", "\n", " y gw_id filternummer diepte_onderkant_filter \n", "0 193510.000000 GWZP010 1 1.93 \n", "1 193667.000000 GWZP007 1 1.89 \n", "2 192591.000000 GWZP004 1 2.55 \n", "3 197054.203125 810/21/1 1 2.50 \n", "4 199574.000000 DURP016 1 2.38 " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from owslib.fes2 import Or, Not, PropertyIsNull, PropertyIsLessThanOrEqualTo, And\n", "\n", "query = And([PropertyIsEqualTo(propertyname='gemeente',\n", " literal='Hamme'),\n", " Not([PropertyIsNull(propertyname='lengte_filter')]),\n", " Or([PropertyIsLike(propertyname='meetnet',\n", " literal='meetnet 1%'),\n", " PropertyIsLessThanOrEqualTo(\n", " propertyname='diepte_onderkant_filter',\n", " literal='3')])])\n", "df_hamme = gwfilter.search(query=query,\n", " return_fields=('pkey_filter', 'x', 'y', 'gw_id', 'filternummer', 'diepte_onderkant_filter'))\n", "df_hamme.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Combine `datum` and `tijdstip` in a datetime object" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Get some data and keep only the relevant waterlevel measurements:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n", "[000/001] .\n" ] } ], "source": [ "query = PropertyIsEqualTo(\n", " propertyname='pkey_filter',\n", " literal='https://www.dov.vlaanderen.be/data/filter/1997-000494')\n", "\n", "df = gwfilter.search(query=query)\n", "df = df[df.filterstatus == \"in rust\"]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If the `tijdstip` field contains data, it can be combined with the `datum` field to create a date.datetime object. Make sure to fill the empty `tijdstip` fields with a default timestamp." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 1998-07-31 01:05:00\n", "1 1999-01-16 15:01:00\n", "2 1999-08-14 01:05:00\n", "3 1999-11-14 02:40:00\n", "4 1999-12-27 00:01:00\n", "Name: tijd, dtype: datetime64[ns]" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "df.reset_index(inplace=True)\n", "df['tijdstip'] = df.tijdstip.fillna('00:00:00')\n", "df['tijd'] = pd.to_datetime(df.datum.astype(str)+' '+df.tijdstip.astype(str))\n", "df.tijd.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Working with water head time series " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For further analysis and visualisation of the time series data, we can use the data analysis library [pandas](https://pandas.pydata.org/) and visualisation library [matplotlib](https://matplotlib.org/). " ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Query the data of a specific filter using its `pkey`:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n", "[000/001] .\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filterpkey_grondwaterlocatiegw_idfilternummerfiltertypexystart_grondwaterlocatie_mtawmv_mtawgemeente...regimediepte_onderkant_filterlengte_filterdatumtijdstippeil_mtawbetrouwbaarheidmethodefilterstatusfiltertoestand
0https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...onbekend0.720.32003-10-18NaN58.26onbekendpeillintonbekend1
1https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...onbekend0.720.32003-11-01NaN58.30onbekendpeillintonbekend1
2https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...onbekend0.720.32003-11-17NaN58.31onbekendpeillintonbekend1
3https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...onbekend0.720.32003-11-23NaN58.31onbekendpeillintonbekend1
4https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...onbekend0.720.32003-12-14NaN58.30onbekendpeillintonbekend1
\n", "

5 rows × 23 columns

\n", "
" ], "text/plain": [ " pkey_filter \\\n", "0 https://www.dov.vlaanderen.be/data/filter/2003... \n", "1 https://www.dov.vlaanderen.be/data/filter/2003... \n", "2 https://www.dov.vlaanderen.be/data/filter/2003... \n", "3 https://www.dov.vlaanderen.be/data/filter/2003... \n", "4 https://www.dov.vlaanderen.be/data/filter/2003... \n", "\n", " pkey_grondwaterlocatie gw_id filternummer \\\n", "0 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 1 \n", "1 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 1 \n", "2 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 1 \n", "3 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 1 \n", "4 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 1 \n", "\n", " filtertype x y start_grondwaterlocatie_mtaw mv_mtaw \\\n", "0 peilfilter 218953.0 198767.0 58.48 58.48 \n", "1 peilfilter 218953.0 198767.0 58.48 58.48 \n", "2 peilfilter 218953.0 198767.0 58.48 58.48 \n", "3 peilfilter 218953.0 198767.0 58.48 58.48 \n", "4 peilfilter 218953.0 198767.0 58.48 58.48 \n", "\n", " gemeente ... regime diepte_onderkant_filter lengte_filter \\\n", "0 Houthalen-Helchteren ... onbekend 0.72 0.3 \n", "1 Houthalen-Helchteren ... onbekend 0.72 0.3 \n", "2 Houthalen-Helchteren ... onbekend 0.72 0.3 \n", "3 Houthalen-Helchteren ... onbekend 0.72 0.3 \n", "4 Houthalen-Helchteren ... onbekend 0.72 0.3 \n", "\n", " datum tijdstip peil_mtaw betrouwbaarheid methode filterstatus \\\n", "0 2003-10-18 NaN 58.26 onbekend peillint onbekend \n", "1 2003-11-01 NaN 58.30 onbekend peillint onbekend \n", "2 2003-11-17 NaN 58.31 onbekend peillint onbekend \n", "3 2003-11-23 NaN 58.31 onbekend peillint onbekend \n", "4 2003-12-14 NaN 58.30 onbekend peillint onbekend \n", "\n", " filtertoestand \n", "0 1 \n", "1 1 \n", "2 1 \n", "3 1 \n", "4 1 \n", "\n", "[5 rows x 23 columns]" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = PropertyIsEqualTo(\n", " propertyname='pkey_filter',\n", " literal='https://www.dov.vlaanderen.be/data/filter/2003-009883')\n", "\n", "df = gwfilter.search(query=query)\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The date is still stored as a string type. Transforming to a data type using the available pandas function [`to_datetime`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html) and using these dates as row index:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "df['datum'] = pd.to_datetime(df['datum'])\n", "df = df.set_index('datum')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plotting" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The default plotting functionality of Pandas can be used:" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filterpkey_grondwaterlocatiegw_idfilternummerfiltertypexystart_grondwaterlocatie_mtawmv_mtawgemeente...grondwaterlichaam_coderegimediepte_onderkant_filterlengte_filtertijdstippeil_mtawbetrouwbaarheidmethodefilterstatusfiltertoestand
datum
2003-10-18https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...NaNonbekend0.720.3NaN58.26onbekendpeillintonbekend1
2003-11-01https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...NaNonbekend0.720.3NaN58.30onbekendpeillintonbekend1
2003-11-17https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...NaNonbekend0.720.3NaN58.31onbekendpeillintonbekend1
2003-11-23https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...NaNonbekend0.720.3NaN58.31onbekendpeillintonbekend1
2003-12-14https://www.dov.vlaanderen.be/data/filter/2003...https://www.dov.vlaanderen.be/data/put/2018-00...ZWAP2051peilfilter218953.0198767.058.4858.48Houthalen-Helchteren...NaNonbekend0.720.3NaN58.30onbekendpeillintonbekend1
\n", "

5 rows × 22 columns

\n", "
" ], "text/plain": [ " pkey_filter \\\n", "datum \n", "2003-10-18 https://www.dov.vlaanderen.be/data/filter/2003... \n", "2003-11-01 https://www.dov.vlaanderen.be/data/filter/2003... \n", "2003-11-17 https://www.dov.vlaanderen.be/data/filter/2003... \n", "2003-11-23 https://www.dov.vlaanderen.be/data/filter/2003... \n", "2003-12-14 https://www.dov.vlaanderen.be/data/filter/2003... \n", "\n", " pkey_grondwaterlocatie gw_id \\\n", "datum \n", "2003-10-18 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 \n", "2003-11-01 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 \n", "2003-11-17 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 \n", "2003-11-23 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 \n", "2003-12-14 https://www.dov.vlaanderen.be/data/put/2018-00... ZWAP205 \n", "\n", " filternummer filtertype x y \\\n", "datum \n", "2003-10-18 1 peilfilter 218953.0 198767.0 \n", "2003-11-01 1 peilfilter 218953.0 198767.0 \n", "2003-11-17 1 peilfilter 218953.0 198767.0 \n", "2003-11-23 1 peilfilter 218953.0 198767.0 \n", "2003-12-14 1 peilfilter 218953.0 198767.0 \n", "\n", " start_grondwaterlocatie_mtaw mv_mtaw gemeente ... \\\n", "datum ... \n", "2003-10-18 58.48 58.48 Houthalen-Helchteren ... \n", "2003-11-01 58.48 58.48 Houthalen-Helchteren ... \n", "2003-11-17 58.48 58.48 Houthalen-Helchteren ... \n", "2003-11-23 58.48 58.48 Houthalen-Helchteren ... \n", "2003-12-14 58.48 58.48 Houthalen-Helchteren ... \n", "\n", " grondwaterlichaam_code regime diepte_onderkant_filter \\\n", "datum \n", "2003-10-18 NaN onbekend 0.72 \n", "2003-11-01 NaN onbekend 0.72 \n", "2003-11-17 NaN onbekend 0.72 \n", "2003-11-23 NaN onbekend 0.72 \n", "2003-12-14 NaN onbekend 0.72 \n", "\n", " lengte_filter tijdstip peil_mtaw betrouwbaarheid methode \\\n", "datum \n", "2003-10-18 0.3 NaN 58.26 onbekend peillint \n", "2003-11-01 0.3 NaN 58.30 onbekend peillint \n", "2003-11-17 0.3 NaN 58.31 onbekend peillint \n", "2003-11-23 0.3 NaN 58.31 onbekend peillint \n", "2003-12-14 0.3 NaN 58.30 onbekend peillint \n", "\n", " filterstatus filtertoestand \n", "datum \n", "2003-10-18 onbekend 1 \n", "2003-11-01 onbekend 1 \n", "2003-11-17 onbekend 1 \n", "2003-11-23 onbekend 1 \n", "2003-12-14 onbekend 1 \n", "\n", "[5 rows x 22 columns]" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = df['peil_mtaw'].plot(style='-', figsize=(12, 5))\n", "ax.set_title('Water heads `Put ZWAP205` in Houthalen-Helchteren');\n", "ax.set_ylabel('head (m TAW)');\n", "ax.set_xlabel('');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Or a combination with matplotlib to have full customization options:" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_11791/3156484461.py:5: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", " ground_surface = df[\"mv_mtaw\"][0]\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAABKUAAAJOCAYAAABm7rQwAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjYsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvq6yFwwAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzsnXd4FFUXxt8tyW56b5AGhNB7D12qICoiKNJRREXs+AH2hmDBhqBYAEVAkSIqKEVCCb13CCmkQHrvW+b7YzOTmdmZ3dnNbnYT7u95eMhOvdNuOfec98goiqJAIBAIBAKBQCAQCAQCgUAgNCByRxeAQCAQCAQCgUAgEAgEAoFw90GMUgQCgUAgEAgEAoFAIBAIhAaHGKUIBAKBQCAQCAQCgUAgEAgNDjFKEQgEAoFAIBAIBAKBQCAQGhxilCIQCAQCgUAgEAgEAoFAIDQ4xChFIBAIBAKBQCAQCAQCgUBocIhRikAgEAgEAoFAIBAIBAKB0OAQoxSBQCAQCAQCgUAgEAgEAqHBIUYpAoFAIBAIhEbGv//+i/fffx81NTWOLgrBDuj1enz88cfYunWro4tCIBAIBIJdIUYpAoFAIBAITRKZTIZnn33W0cVgSE1NhUwmw9q1a+t9rK5du2LlypV4//33618wgtMhl8sREhKCxx57DFevXnV0cQgEAoFAsBvEKEUgEAgEwl3Kb7/9BplMhm3bthmt69KlC2QyGfbv32+0LjIyEnFxcRada+XKlTYxxhAMhISEYOPGjfj4449x4cIFo/W0AYz+p1AoEBkZifHjx+PcuXNWndOSZzhz5kzO+YX+RUdHAwCeeeYZyOVyFBQUcI5RUFAAuVwOlUqFqqoqzrrk5GTIZDIsXryYs7yoqAhqtRoymUzUmMMvm7e3N7p06YJPP/0U1dXVzHb79u3D7NmzERsbC3d3d7Rs2RJPPPEE7ty5I3jcI0eOYMCAAXB3d0doaCiee+45lJWVcbaJj48XvR/Hjh3jbDt9+nRMnToVjz/+OPR6vfjNJhAIBAKhEaN0dAEIBAKBQCA4hgEDBgAADh8+jPHjxzPLS0pKcOnSJSiVSiQkJGDo0KHMuvT0dKSnp+PRRx+16FwrV65EYGAgZs6caZOyE4DBgwfjzTffxOzZs3H8+HEoFAqjbSZPnowxY8ZAp9Ph6tWrWLVqFXbt2oVjx46ha9euFp3Pkmc4d+5cDB8+XHDdvn37sHbtWvTt2xeA4T1ctWoVEhISMG7cOGa7I0eOQC6XQ6PR4NSpU8z7CgAJCQnMvmw2b94MmUyG0NBQ/PLLL6KeZCqVCt9//z0AgyFry5YteOWVV3Dy5Els2rQJAPC///0PBQUFmDhxIlq3bo3k5GSsWLECf/31F86dO4fQ0FDmeOfOncOwYcPQrl07LF++HBkZGfjkk0+QmJiIXbt2GZ3/ueeeQ69evTjLYmJijLZbsWIF+vbtiy+//BIvvPCC4LUQCAQCgdCYIUYpAoFAIBDuUpo1a4YWLVrg8OHDnOVHjx4FRVGYOHGi0Tr6N98Y4Ai0Wi30ej1cXV0dXRSHsWjRIixatEh0fffu3TF16lTmd//+/XH//fdj1apV+Pbbb+1Wrn79+qFfv35Gy+/cuYOXXnoJUVFRWLVqFQCucZRtlEpISEDnzp1RWVmJw4cPc965w4cPQy6XG3nsrV+/HmPGjEFUVBQ2bNggapRSKpWc+/LMM8+gT58++PXXX7F8+XI0a9YMy5cvx4ABAyCX1wUWjB49GoMHD8aKFSs4x168eDH8/PwQHx8Pb29vAEB0dDTmzJmD3bt3Y+TIkZzzDxw4EA8//LDpmwhArVZb7dlGIBAIBEJjgITvEQgEAoFwFzNgwACcPXsWlZWVzLKEhAR06NAB9957L44dO8YJHUpISIBMJkP//v0BAGvWrME999yD4OBgqFQqtG/fnjE20ERHR+Py5cs4cOAAE6o0ZMgQZn1RURFeeOEFREREQKVSISYmBsuWLeOclw5H++STT/D555+jVatWUKlUuHLlitlr3L59Ozp27AiVSoUOHTrgn3/+MdomMzMTs2fPRkhICLPdjz/+yNmmpqYGb775Jnr06AEfHx94eHhg4MCBgiGORUVFmDlzJnx8fODr64sZM2agqKjIaLusrCzMmjUL4eHhUKlUCAsLwwMPPIDU1FSz12UN99xzDwAgJSUFAPD2229DJpMZbbd27VrIZDKmHOaeoRT0ej2mTJmCwsJCbNiwAX5+fgAM4aARERGM9xNNQkIC+vfvj7i4OMF1HTp0gK+vL7MsLS0Nhw4dwqOPPopHH30UKSkpOHLkiKSyyeVy5nroax40aBDHIEUv8/f354QGlpSUYM+ePZg6dSpjkAIM4Xeenp747bffBM9ZWloKrVYrqXwEAoFAIDRViKcUgUAgEAh3MQMGDMDPP/+M48ePM4PyhIQExMXFIS4uDsXFxbh06RI6d+7MrGvbti0CAgIAAKtWrUKHDh1w//33Q6lU4s8//8QzzzwDvV6PefPmAQA+//xzzJ8/H56ennjttdcAGDSRAKCiogKDBw9GZmYm5s6di8jISBw5cgSLFi3CnTt38Pnnn3PKu2bNGlRVVeHJJ5+ESqWCv7+/yes7fPgwtm7dimeeeQZeXl748ssvMWHCBKSlpTHXkJ2djb59+zLC6EFBQdi1axcef/xxlJSUMGFTJSUl+P777zF58mTMmTMHpaWl+OGHHzBq1CicOHGCCYejKAoPPPAADh8+jKeeegrt2rXDtm3bMGPGDKPyTZgwAZcvX8b8+fMRHR2NnJwc7NmzB2lpaYzmki1JSkoCAObapWLqGUrlvffew/79+/HBBx8YeTgNGDAAW7duRXV1NVQqFWpqanDy5Ek8/fTTqKiowKuvvgqKoiCTyVBYWIgrV67gqaee4hxj48aN8PDwwH333Qc3Nze0atUKv/zyi2T9Myn3pqysDGVlZQgMDGSWXbx4EVqtFj179uRs6+rqiq5du+Ls2bNGx5k1axbKysqgUCgwcOBAfPzxx0b7EwgEAoFwV0ARCAQCgUC4a7l8+TIFgHrvvfcoiqIojUZDeXh4UOvWraMoiqJCQkKor7/+mqIoiiopKaEUCgU1Z84cZv+KigqjY44aNYpq2bIlZ1mHDh2owYMHG2373nvvUR4eHtSNGzc4yxcuXEgpFAoqLS2NoiiKSklJoQBQ3t7eVE5OjqRrA0C5urpSN2/eZJadP3+eAkB99dVXzLLHH3+cCgsLo/Ly8jj7P/roo5SPjw9zjVqtlqquruZsU1hYSIWEhFCzZ89mlm3fvp0CQH300UfMMq1WSw0cOJACQK1Zs4bZFwD18ccfS7oeS6Dv1zvvvEPl5uZSWVlZVHx8PNWtWzcKALVlyxaKoijqrbfeooS6g2vWrKEAUCkpKcwysWcohfj4eEqhUFDDhg2jdDqd0fqvv/6aAkAdOnSIoiiKOnr0KAWAunXrFnXlyhUKAHX58mWKoijqr7/+ogBQv/zyC+cYnTp1oqZMmcL8Xrx4MRUYGEhpNBrOdjNmzKA8PDyo3NxcKjc3l7p58ya1ZMkSSiaTUZ07dzZ5He+99x4FgNq3bx+zbPPmzRQA6uDBg0bbT5w4kQoNDWV+JyQkUBMmTKB++OEH6o8//qA+/PBDKiAggFKr1dSZM2dMnptAIBAIhKYICd8jEAgEAuEupl27dggICGC0os6fP4/y8nLGu4QdOnX06FHodDqOto+bmxvzd3FxMfLy8jB48GAkJyejuLjY7Pk3b96MgQMHws/PD3l5ecy/4cOHQ6fT4eDBg5ztJ0yYgKCgIMnXN3z4cLRq1Yr53blzZ3h7eyM5ORmAwatpy5YtGDduHCiK4pRh1KhRKC4uxpkzZwAACoWC0a/S6/UoKChgPGTobQBg586dUCqVePrpp5llCoUC8+fP55TNzc0Nrq6uiI+PR2FhoeRrsoS33noLQUFBCA0NxZAhQ5CUlIRly5bhoYcessv5hMjLy8Njjz2GgIAArF+/3igkDuDqSgEGj7zmzZsjMjISbdu2hb+/P/MeComcX7hwARcvXsTkyZOZZZMnT0ZeXh7+/fdfo/OVl5cjKCgIQUFBiImJweLFi9GvXz/BTJQ0Bw8exDvvvINJkyYxYZAAmNBXlUpltI9areaExsbFxeH333/H7Nmzcf/992PhwoU4duwYZDKZSW0wAoFAIBCaKiR8j0AgEAiEuxiZTIa4uDgcPHgQer0eCQkJCA4OZjKBxcXFYcWKFQCEjQEJCQl46623cPToUVRUVHCOXVxcDB8fH5PnT0xMxIULF0QNTTk5OZzfLVq0sOj6IiMjjZb5+fkxRqDc3FwUFRVh9erVWL16tdkyrFu3Dp9++imuXbsGjUYjWK5bt24hLCwMnp6enOO0adOG81ulUmHZsmV4+eWXERISgr59++K+++7D9OnTOZnd6sOTTz6JiRMnQi6Xw9fXFx06dBA0ntgLiqIwffp03LlzB7t27RK9ro4dO8LX15djeKJ1y2QyGfr164eEhATMmTMHCQkJiIiI4Dzb9evXw8PDAy1btsTNmzcBGAxC0dHR+OWXXzB27FjO+dRqNf78808AhufQokULhIeHi17HtWvXMH78eHTs2JHJ2kdDG2arq6uN9quqquIYboWIiYnBAw88gK1bt0Kn0wlmUSQQCAQCoalCjFIEAoFAINzlDBgwAH/++ScuXrzI6EnRxMXFYcGCBcjMzMThw4fRrFkztGzZEoBBg2fYsGFo27Ytli9fjoiICLi6umLnzp347LPPOELlYuj1eowYMQKvvvqq4PrY2FjOb3MDfD5iA3yKopjzA8DUqVMFNZ8AMHpa69evx8yZM/Hggw9iwYIFCA4OhkKhwIcffsjoEVnKCy+8gHHjxmH79u34999/8cYbb+DDDz/Ef//9h27dull1TDatW7fG8OHDRdcLiZwDgE6nq/e5AeCTTz7Brl27sGDBAowaNUp0O7lcjn79+uHIkSOgKAoJCQlYvHgxsz4uLg4//vgjozX14IMPMusoisLGjRtRXl6O9u3bGx07JycHZWVlHCOhQqEweV/YpKenY+TIkfDx8cHOnTvh5eXFWR8WFgbAkFmQz507d9CsWTOz54iIiEBNTQ3Ky8s5YukEAoFAIDR1iFGKQCAQCIS7HHboVEJCAiPsDQA9evSASqVCfHw8jh8/jjFjxjDr/vzzT1RXV2PHjh0crxWhbHRixo9WrVqhrKxMsoHA1gQFBcHLyws6nc5sGX7//Xe0bNkSW7du5VzPW2+9xdkuKioK+/btMzKEXL9+XfC4rVq1wssvv4yXX34ZiYmJ6Nq1Kz799FOsX7++HlcmDToDXlFRESeT3a1bt4y2FXuGYhw/fhyvvfYa+vTpgw8++MDs9gMGDMCuXbuwY8cO5OTkMJ5SgMEo9dprr2Hnzp2orKzkeOsdOHAAGRkZePfdd9GuXTvOMQsLC/Hkk09i+/btmDp1qkXlB4D8/HyMHDkS1dXV2LdvH2OAYtOxY0colUqcOnUKkyZNYpbX1NTg3LlznGViJCcnQ61WG3nXEQgEAoHQ1CGaUgQCgUAg3OX07NkTarUav/zyCzIzMzmeUiqVCt27d8fXX3+N8vJyjjGA9kKivY4AQ8jemjVrjM7h4eGBoqIio+WTJk3C0aNHBXV/ioqKoNVq63NpZlEoFJgwYQK2bNmCS5cuGa3Pzc3lbAtwr/f48eM4evQoZ58xY8ZAq9Vi1apVzDKdToevvvqKs11FRQWqqqo4y1q1agUvLy/BUDB7QOttsbW7ysvLsW7dOqNtxZ6hEEVFRXj00Ufh7u6OjRs3wsXFxew+9Lu1bNkyuLu7M9kMAaB3795QKpX46KOPONsCdaF7CxYswMMPP8z5N2fOHLRu3Rq//PKLpHKzKS8vx5gxY5CZmYmdO3eidevWgtv5+Phg+PDhWL9+PUpLS5nlP//8M8rKyjBx4kRmGft9ojl//jx27NiBkSNHCuptEQgEAoHQlCGeUgQCgUAg3OW4urqiV69eOHToEFQqFXr06MFZHxcXh08//RQA1xgwcuRIuLq6Yty4cZg7dy7Kysrw3XffITg42CiUqUePHli1ahXef/99xMTEIDg4GPfccw8WLFiAHTt24L777sPMmTPRo0cPlJeX4+LFi/j999+RmpqKwMBAu17/0qVLsX//fvTp0wdz5sxB+/btUVBQgDNnzmDv3r0oKCgAANx3333YunUrxo8fj7FjxyIlJQXffPMN2rdvj7KyMuZ448aNQ//+/bFw4UKkpqaiffv22Lp1q5Hw+40bNzBs2DBMmjQJ7du3h1KpxLZt25CdnY1HH33UrtdMM3LkSERGRuLxxx/HggULoFAo8OOPPyIoKAhpaWmcbcWeoRBPPfUUUlNT8cgjjyAhIYHRiuLD9l7q3bs3XF1dcfToUQwZMgRKZV031d3dHV26dMHRo0fh6+uLjh07AjDoOG3ZsgUjRoyAWq0WPMf999+PL774Ajk5OQgODpZ8b6ZMmYITJ05g9uzZuHr1Kq5evcqs8/T05IQQfvDBB4iLi8PgwYPx5JNPIiMjA59++ilGjhyJ0aNHM9s98sgjcHNzQ1xcHIKDg3HlyhWsXr0a7u7uWLp0qeSyEQgEAoHQZHBc4j8CgUAgEAjOwqJFiygAVFxcnNG6rVu3UgAoLy8vSqvVctbt2LGD6ty5M6VWq6no6Ghq2bJl1I8//kgBoFJSUpjtsrKyqLFjx1JeXl4UAGrw4MHMutLSUmrRokVUTEwM5erqSgUGBlJxcXHUJ598QtXU1FAURVEpKSkUAOrjjz+WfE0AqHnz5hktj4qKombMmMFZlp2dTc2bN4+KiIigXFxcqNDQUGrYsGHU6tWrmW30ej21ZMkSKioqilKpVFS3bt2ov/76i5oxYwYVFRXFOV5+fj41bdo0ytvbm/Lx8aGmTZtGnT17lgJArVmzhqIoisrLy6PmzZtHtW3blvLw8KB8fHyoPn36UL/99pvkaxTDkvt1+vRpqk+fPpSrqysVGRlJLV++nFqzZo1Fz5BPVFQUBcDsPz79+vWjAFCLFy82Wvfcc89RAKh7772XWbZlyxYKAPXDDz+IliU+Pp4CQH3xxRcURVHUjBkzKA8PD7P3xdQ18J83RVHUoUOHqLi4OEqtVlNBQUHUvHnzqJKSEs42X3zxBdW7d2/K39+fUiqVVFhYGDV16lQqMTHRbHkIBAKBQGiKyCiK5YNOIBAIBAKBQCAQCAQCgUAgNAAkcJ1AIBAIBAKBQCAQCAQCgdDgEKMUgUAgEAgEAoFAIBAIBAKhwSFGKQKBQCAQCAQCgUAgEAgEQoNDjFIEAoFAIBAIBAKBQCAQCIQGhxilCAQCgUAgEAgEAoFAIBAIDY5DjVJvv/02ZDIZ51/btm2Z9VlZWZg2bRpCQ0Ph4eGB7t27Y8uWLWaPm5mZialTpyIgIABubm7o1KkTTp06Zc9LIRAIBAKBQCAQCAQCgUAgWIDS0QXo0KED9u7dy/xWKuuKNH36dBQVFWHHjh0IDAzEhg0bMGnSJJw6dQrdunUTPF5hYSH69++PoUOHYteuXQgKCkJiYiL8/Pwkl4miKJSWlsLLywsymcz6iyMQCAQCgUAgEAgEAoFAIAjicKOUUqlEaGio4LojR45g1apV6N27NwDg9ddfx2effYbTp0+LGqWWLVuGiIgIrFmzhlnWokULi8pUWloKHx8fFBcXw9vb26J9CQQCgUAgEAgEAoFAIBAI5nG4plRiYiKaNWuGli1bYsqUKUhLS2PWxcXF4ddff0VBQQH0ej02bdqEqqoqDBkyRPR4O3bsQM+ePTFx4kQEBwejW7du+O677xrgSggEAoFAIBAIBAKBQCAQCFKRURRFOerku3btQllZGdq0aYM7d+7gnXfeQWZmJi5dugQvLy8UFRXhkUcewe7du6FUKuHu7o7Nmzdj5MiRosdUq9UAgJdeegkTJ07EyZMn8fzzz+Obb77BjBkzBPeprq5GdXU187ukpAQRERHEU4pAIBAIBAKBQCAQCAQCwU441CjFp6ioCFFRUVi+fDkef/xxzJ8/HydOnMCSJUsQGBiI7du347PPPsOhQ4fQqVMnwWO4urqiZ8+eOHLkCLPsueeew8mTJ3H06FHBfd5++2288847RsuJUYpAIBAIBAKBQCAQCAQCwT44PHyPja+vL2JjY3Hz5k0kJSVhxYoV+PHHHzFs2DB06dIFb731Fnr27Imvv/5a9BhhYWFo3749Z1m7du04YYF8Fi1ahOLiYuZfenq6za6JQCAQCAQCgUAgEAgEAoFgjFMZpcrKypCUlISwsDBUVFQAAORybhEVCgX0er3oMfr374/r169zlt24cQNRUVGi+6hUKnh7e3P+EQgEAoFAIBAIBAKBQCAQ7IdDjVKvvPIKDhw4gNTUVBw5cgTjx4+HQqHA5MmT0bZtW8TExGDu3Lk4ceIEkpKS8Omnn2LPnj148MEHmWMMGzYMK1asYH6/+OKLOHbsGJYsWYKbN29iw4YNWL16NebNm+eAKyQQCAQCgUAgEAgEAoFAIAihdOTJMzIyMHnyZOTn5yMoKAgDBgzAsWPHEBQUBADYuXMnFi5ciHHjxqGsrAwxMTFYt24dxowZwxwjKSkJeXl5zO9evXph27ZtWLRoEd599120aNECn3/+OaZMmdLg10cgEAgEAoFAIBAIBAKBQBDGqYTOnYWSkhL4+PgQoXMCgUAgEAh3LTklVTh9qxAj2odAqbDeuT45twxpBRUY0ibYhqVzDDVaPfZcyUa/VgHw93C1aN+SKg321u57+lYhBrYOgo+bi51KSiAQCARC48ChnlIEAoFAIBAIBOdk1OcHUVihwZv3tcfsAS2sPs49nx4AAGx7Jg7dIv1sVTyH8NV/ifjqv5toGeSB/14eYtG+n/57HeuO3mJ+92nhj1/n9rNxCQkEAoFAaFw4ldA5gUAgEAgEAsE5KKzQAAD2Xcu2yfEu3y6xyXEcyc6LdwAAybnlFu/LNkgBwPGUApuUiUAgEAiExgwxShEIBIKTQlEUdHoSYU0gEByLiaTHFiGT2eY4jkQpJ11nAoFAIBBsCWlZCQQCwUl5btM59FmyFyVVGkcXhUAg3MXobCQ/uuK/mzY5jiNhG9bKq7UW7auQNwGrHIFAIBAINoYYpQgEAsFJ+fP8beSV1WDnhTuOLgqBQLiLsVVOnDvFVTY5jiOp1ta5jd3ILrVoX0VTcBUjEAgEAsHGEKMUgUAgODkkgI9AIDgSEkZcRw3LKOViYUZC4ilFIBAIBIIxxChFIBAITs7X+xt/yAuBQHB+dHoK7/91BXuucIXNdTa0Sb2+/SLOpRfZ7oA25FZ+ORZtvYhb+eIi5hpdnVHKUgcypYBRqriShGezuXK7BIu3XUROaeP3qmvqrIpPwvpjt8xvSCDcJey6eAcf7rwKvZ5i2tN/L2c5uliNAmKUIhAIBCcno7ASN3PKHF0MAoHQxNl2NhPfH07BnJ9OcZbbKnwPANYfS8ODXyfY7Hi25LHvjmPjiTTMWnNSdJsOzbyZv/UW3he5gFFq2T/XLDpGU2fMl4ew4XgaFm+96OiiEEyQWVSJZf9cw+vbL0FPPCkJBADA07+cwbcHk7H7Shb+unAb3x9OwdyfTzu6WI0CYpQiEAiERkApETsnEAh2JrtE2DulPuF7tjRo2ZvMokoAQHKeuKdUrxb+zN+WGqWEPKWu3imx6Bh3C0m54s+A4HjKqupE/mt0NkrPSSA0EXJKq5uEhmJDonR0AQgEAoFgnsYzrCMQCI0VMR3u+jhCNDU9KrYd6sqdEijlckQGuMPHzcXsvkKeUpU1OlsWr8ng5qJwdBEIJiivqTNKaXR6qMnzIhAY9HoKaQUVji5Go4IYpQgEAoFAIBAIkItYpeoTnqNtYkYpNq9tuwQACPVW49jiYWa3F/KUqtQQo5QQ7q7EyOHMTFh1hPmbLf5PIBAMEzkbjqc5uhiNChK+RyAQCAQCgUCAWHI4XT1C8Bqjp5SYxxggHI6YJRL2yEco+56GDOgFcSNGKaeG/RmQ8D0CgYtWz/0mGlMYu6MgRikCgUBoBJD2jEAg2BtRT6l6VECN0VPK1OXWpy4WMko1xvvTEBBPqcaDRkveYQKBjYaXspb/m2AMMUoRCASCHfj9dAYGLPsPJ1IKHF0UAoHQSDl9qwD3fBKP+Os5DX7uid/UhefUJ3yvMXpK0ej0FB777hj+9/sFAMC+q9n4dM8NwW2vZZkXLBcySuWUVmNl/M36FdQK3t5xGQ+vOgKNk3q5uLvWT2Hku4PJGPXZQeSXVduoRASa9/66wvldo7v7QlB1egqPrj6KRSRLZJOHoig8+dMpRC/8G4u2XuCs+/P8bdzzaTyuZ5Vylt/I5v521nrWmSBGKQKBQLADr2w+j4zCSrzz52WbHM9UOAmBQGiaTPn+OJLzyjFzzckGOZ+MVdGcTC1k/q6PXYkfxtCYOJdehCNJ+fj1VDoA4PF1p0S3fX7jObPHU4hU5B/9c92q8tWHtUdScepWIQ7eyG3wc4vBNn7W11Pqg51XcT27FCv2N7zBr6nzw+EUzu+au9BT6vStQhxLLsDGE0Q3qKlTUqXF7ivZAICNJ9I56+ZvPIvk3HK88Os5zvI/zt3m/NYSTymzEKMUgUAg2JHbtSnG6wsJ3yMQ7j6qNA1r0BHVlLpLPaW0FsxuSxEsF/KUcjTO9HzYGd08VLbJxUQ8FOzP3agp5UzfDcG+8OcShPShKll1lxB34zdiKST7HoFAIJigSqPDmoRUDGsXjNgQL4v3J92Wu4vrWaXYdekOZsZFw9fd1Wj9xYxiHE3Ow+MDWjrlAJVwd2OJplRplQY/Hb2FmGBPvL79EtqGeuHVUW3RKdwHqXmGmeOuEb4mO+ObTqQhzNcNg2ODABiM+FvPZOCxPlHw9zB8P0eT8nEztwzT+kbZ4Aotw5JxJyWhtr/GC/Eg1HH6VgF2X85mfgtlKrQGGUg9a2+KKzWOLkKDQ7zXmyb5ZdXYeCINE3qEI8zHDQCMapCk3DL8eznbIvFyYhw3DzFKEQgEggm+3JeIlfFJWPbPNaQuHWvx/vXRYiE0Pp7dcAaJOWUoqtDg7fs7GK0ft+IwAEDtosD0ftENXDoCwTSWeEot2XmNE7qSW1qNQ4mHkbp0LMZ9dRil1VqcSy8SPdeV2yVYWKvHQtetU74/jpS8cpy+VYg1s3oDACZ/dwwA0DrYE31bBlhzWVbDHnSYq8urG9irrakxYdVRzm9btZzEeGB/buaUMYbluxG9noKcTDI1CV749RwOJeZh29lM7Ht5CADjyYl7vzhksXA5Cd8zDwnfIxAIBBOYGlRJwXbNEGnQGgOJOWUAgMM380xudz69uCGKQyBYhsgIvlprbHA5lSqexKG02nQoAwDcKTYObU7JKwcg/P2kFVSYPaat0bGNUmZmxaskhO85IzIntdrUJ+MjG+e8uqbF3WiPYXuV6oi+QpPhUKKh7UnKLWeW8T2ihAxS5t4AEr5nHmKUIhAIBDtC+ip3J+bcuqu0jXMA2xjJLKpERmHDGzScCa1Oj5zSKtH1FTVaFFdoRAeX1bz3taiiBpkienkHJApnsz+RCp4eh1Ju3D21JFTCVrBnyM0NPIUMdw0FRVHIKhZ/vqbIL6tGlUZn8v2wJ1qdHtklxufW6Sgk5ZYhr6waGp0euaXVyC6pstj72FmNbjTFFRqj998ZKSivETW8StFTa2qwX6uG1JfKKakielZ2QizETsrtLq7UICm3zOJjE+og4XsEAoFgRxwxkCI4HnNPvfou7MQ7gqt3SnDvF4cAAH/M648uEb6OLZCDeOz74ziRUiB6D7q8sxsaHYXXxrQT3J8tuF5apUHXd/eInmvGjycklSmntJr5u/2b/3LCo5UKY0OCI6pSPSd8z/S2jjRKfbY3EV/uS8RrY9phzqCWFu27cOtFJozy7+cGoEMzH3sUUZSJ3x7F2bQio+XfH07B97VZ3pr7ujFG0Ps6h2HFY90bsoh2o6xaiy7v7oZCLkPSkjGOLo4oeWXV6Pn+XgR4uOL0GyOM1lfW3N3tWUMZiY4n5+OR1ccwtE0QE95MsB2TVx8TXC7Fa7OoQoNhnx4QXU/C98xDPKUIBALBjtiqr0JsW00LS/UICNax72qdcPKvp9JNbNm0OZFiCLXbdFI4fTn9Ppqa6aW5kW0bse6rd0o4v9kDOyHfFkc4B7AnFZw5ROfLfYkAgA92Xq3XcX4/nWGL4liEkEGKD9sr768Ldyw6vjM7St2sDfd2ds8Xuv7IL68RXK918vLbA/Zr1VDXv+5oKgBg/3Vp3qgEyzh1q1BwuS1CiUn4nnmIUYpAIBDsiJSMTIQmiJnHbiu9FIJp2KE7xGvR/OBXygBeIRBaZw38upEdIihUSkfUpWzvKHsYDhaMagMAcFU6R3e8KX4izpx9j10yZ66fxLJy0tyNCV0cEb7nonCOeuJugX6utvg0SfieeUj4HoFAcCqW776O28VV+Pjhzk6nBUFRlMVlslU/08luhc1YvucGMgsr8clE53ve9UHosbPTZhNX7obHXPiVs2NN/cPHXL84p6RadJ1eT2HF/pv47lByvcpAs/4Y12uLHQJUWmWsseOIcS/beJwjoHvEZ+uZDLz023mj5a+PbYcnBoqH1WmdZMDCNowUltdg2PIDKCivwV/zB6Bjc9uG9f15/jbmbzxr9f4nUgrwxb4beOf+DmgV5InF2y7Cx80VC+9ty9nOmZsVdtkoynnLak7I/G6bZFm09SISWR6jWjs0Ll/tS0RSbhk+e6QrU++ztfYqarRwdyXD+PpQVFGD5zadw8M9wnF/l2ZG6zU6PRRyBfos2Vfvc5E+n3mIyZVAIDgVX/53E7+fzsDl2yXmN25grmVZHrZiq2aoqfb5vtyXiC1nMnAxs+lno/uqNsQGcP5wjaYCe5DX2AdOtnhlzN2DfddyRNedTC3A8j03BA1GtoAvlswXVXa00Pl7f5sOjevb0l/QIAUA74vsO7B1IHMeZ/A2YZdg+Z4bKKgN1xLTWqkP9TFIAcCkb48i4WY+nvzpNJLzyrHxRDq+OZBk9J44qZ0HANeLy5nDQxVmrFJOYlNtEG7ll2PjiTROqJc9Jjw+3XMD28/dxvGUuiynrsq657D2SKrtT3qX8dmeGzh4IxfPidRF1Vo90vJtkySFeEqZhxilCASCU8LP9uQMWCNk68wu+c5EjQNFgu2B0HMvrGB5SjV2t51GAjvsxAnG/PXCFnWJkDFU6nFtoYO249n+WPpQJ8F1fCMU34DmiKqU/Z2a85TqHuln9nguPAH36EAP5m9NA9YJYs+cvbiApR9UWu282eFuF1dy2g/+K+6s3keA4zK4WQq7HhUqZ2M3+FuCUD1oz/acXS+yw/fyy4T1vQjSEdNIo9Ho9DZ7tkRTyjzEKEUgEJwSZ+zjSB28sTttGh0lmkbZkRRXaLD1TAbKnGSwYc3jLqqowdYzGU6ZTtvc9TjzAKQpIeeExzTue26L0h++mWd8XIkHzpYQvmaOzuG+aN/MW3Dd8OUHOb//uZSF/SzPLXs/P6F6mh1yYW7gvTI+yeT6jMIKowGtCyscp6zWA+1Ycj5e+u0c8svEQyktobRKg1lrTuDIzTwcTszDa9suIkvkWVKgkFNahe1nM/GfCa85a6mo0WLrmQwUVdh2QH2bJYR+Lr0If5zLZH47c1g4ux1wBsPO4m0X0eO9Pfj2QBKKKmpwMrUAx5Lzkct6F4UmDP84l+kUnn58Em7m4WxaIU7fKsQLm87ibJqwkLUlCDmNSW3PNTo9/jiXyXlf+VzKLMYT604JrmMbpZwl5LepIJRB8p9LWbjOi5DwUlsXMnkrvxx/nMuETk8hvaACv51KFx0bpOSV4+8Ldxp9n8VSSDAqgUAgSERq87Dh+C3O76fWn8baeqbvtXXT9NT60zianI+xnXPwdSNNrz1r7UmcTStCws18fDqpi6OLw0GoL8EWar4bsxU5AnZ4jDMM+uqDLcpfUF6DwvIa+Hm4MsukHvXlzcKhaWw6h/vgQobpUFw/d1eT62n4oXD2fnrL/rnG+V1SpeGEXNT3m73nE+N04UqW59QHf1/F8ke64tHaULkD13Nx+o0R9TonAAz8aD+KKjScjF07zt8W3JaigPu/ShA1WtWXN/+4jN9PZ6B7pG+9jpNbWmckkUGGx1mD+AmrjnC2dV6TFLCOFYLl6ImKs2mF2HDcoPP24a5r2HMlWzAb2WPfHTdaVlihwY7zt/Fgt+Z2L6dUckqrMOV7blm3n7uN1KVj63VcIdF3qc/up6O38N5fV+DhqsDld0cLbnPfV4dF92cbpWqIRlG9YRusfz6WarT+9e2XjJa5Wik2v2SnoX2pqNFh86l0nEkrQm5pNeYNjTHadugn8QCAb6b2wOiOoVadrzFCPKUIBILTwJ4VcJbmlj0OlDomTLiZz/kd74Tpe48mG8r4t4XptZ0JOpU4e1bcWTCXKczRA5C7Ba6mlOPKYQtsZVPjhyyYMnZ9P72npGOO6hCC6AB3fDe9Jz5/pKvgNv++MAgAEOHvLq2gPOz9/HZdzOL8Lq7QcAxROj2FqADryg4Ih28oWW4X285lctpAc6ElQsQEexotK2KFDdOI6YLJZLCbQQqoq6vP1Nbd1pLH8txpzBluDybW9Q0cXT9dvcP1CBEySAEGTzQhjqfkCy53FGzDJZv6enQJ6WtJbc8P3jA873IBrxwpuLKM2NVO6IHfmLkiUce2vplSjyTlM/Xfv5ezTG57xgaefY0JYpQiEAgOg68jpLfCAGRvzHV4tTq90XVYmjG9qekpNTRO8qpYRGPxlKIoyuT7qdXpndrAxp4JdWYhYcB8PWC74kvTagr0dMXw9iFmj/bB+I74dlpPxC8YihBvNR7s1hypS8caeSS0CfVi/p5/j/HssDlqtHqLwxn499TUPXZRcgebOj3F0VWqrNHBzUVh0fnNwX4/Kcq4XrC0beCHlli6v73bIlvokgGWZbJy5vA9th+XvcPfarR6TuidTk8hr6walTU6aHR6FFoRUjl3cF1GSaHwJ0ci5NEE2EfbR0p7Xl6t5Xo6aev6jjo9ZTYcT6PTc97lcp5sQVPrRzbE9bDD50okJvBwsdJTiobdhpmrx3JKqpBbWn3XiKQToxSBQHAIybllaPfmP3j3zyvMMvaM/RPrTjqiWEZw+xrcBkSnpzD6i0MY8vF+TuNmSSd40dYLaPPGLtzKLze5nZOPpx2KM8bdCxaJtcwZ9TeEeGLdKXR7dzeKBbwttDo9Rnx2EA9+neCUzwDghu7onDjc4eejqYh9fRcO3BD3qrSVR0hyLreuETuu2KDOFlgTArHsn2uY+/NpydsfuZmH2Nd3YfVBg9bTNweS0OaNXTiZWiC4vYJ3vUM+icfH/15nfueUVluVgVUqCrnMaJDS8e1/UVJl/O2JcZblgVRQXoPY13dZVIbfTmWIrquv8VnMw8Yaxq2oC3Gq0pgesG07K35NzoQ9jebFlRrEvr4LbV7/B6/+fh4URaHV4p3o+f5etHvzH7R+bRfnXZfK7aI6r7rt527jp6OpNix1/RCrvs6IeIBJRegxmfs2Xth0Fh3e+hd7r2Yzy2Jf34XY13fh43+vYdxXhzHy84Oixymr1qLfh/vwBSuDL/u93389B7Gv78L6Y7eEdm90XMgoQuzru7B8t+XvpFT2X8vBnit1z0Oqhl5aQf2y8f3Fik4w995sP3cbvT7Yi/M2rDudGWKUIhAIDuGr/25Cp6fwY0IKs4xtlJI6a2F32IYEXvtRVFGDmzlluF1cxRGutGQwt/FEOigK+P5QivmNCYI4o33H3PiisXhK7buWg/IanaCbeWp+BVLyynExs9iqzJQNAftTdOZ7/sYflwFANDU1YDvDdCUv7EPsuObSwEvhhxk9EeajxoY5fTjLJ/QIt+p4u1mDCHMs+P0CgDotj6W7roGigMVbLwpub8+wNT5eKqVRFsLx3ZobZeCr0eqx14JrZrP1jG2NMSWV0o1jQqxzUAr77BLbCMbbB5bQuR3rp92s+vu3Uxk2q6//5GmTvVlbjzkDYv2wt3bUr4xC4c5SjAtifL0/CVfulCA5txx3ioUF0A9cz0UeL9te53Af5u95v5wBIKyB1Bh5/++rAIAv/7tpt3Ms33PD4n0m9bS83fJUict3S824aou2uDFAhM5tjLaifhZUAuFuQVNRARetoZGlvxuNVscsYy93JHJNFVMmfVUlp0yaihpmnaaiEtoKg51fydqHRuxamO1qKo22YR+DqjZeXx+c5T6L3VtL9gWc410B6sqk1MiNyiSrqXsvZNXG650R5vkIvH+6yrpvuLykHEo35+tSyGuqmTJSVrxjDQVdRl2lhlNG9jteU1EBlc66e8w9Dq8e0+iM6isAcNUa3tEXB0Zixf66wcH/RrfBjH5RaP/WbsOC6irR+zo4yguHnu8HgPuNBrtC8JxSkPoMXXXVnDaG/lulqxE8hqu2BjorButX3hkJmUyGlfFJ+EriIOrka4OhVBju76yeoVh/LA2hKgpVZRVG90VeI35/aYTqQqWm2up7LERZSRm8ZGqr99dXVdq0PJbgrN+9QlMNF63B2FdTUQGt0j7GfX0Vt09SVV5ut2fhLPdaXyn8vlnT12DD7rvS1FRUQFshnsBB6r3WVhiXWV9VCX211mg5uz1T62ugqQ3NdJb7Xx8UGm7dbQ/Y/Rcp+LorsWRMa2w7lswse6xPBDYcTze535hOgdh2VtgoKatWCF6fcRtQ3eifq9LdvB6jjHJWn3sHUlJSAh8fHxQXF8PbWzh1sRgbOnSwU6kIBAKBQCAQCAQCgUAgEBoHj10276FIwvcIBAKBQCAQCAQCgUAgEAgNjvP52jdyJp10DnFmAsHZmfPzaRxOzAMAxL8yBEM+iTfa5vQbw+Du4thq6pHVx3AhoxgA8NPsXugV7c+syyqpwtBPDgAAtj4dh3ZhhuxSi7ZeNNIQuPruKMHjt3vzXwDAo73D8dZ9HQTXAcDPj/dGzyi/el6N8LEf6BKGP87f4ZTziZ9OIeFmvsmy1xednkLHtw0hQOuf6I0ekZZdH/sa7FVGS6HLFOKtQvwrQwTXAYCfuxJHFg5ryKJZBV3mdx7ogEk8HaAv9ibim4MGV3b2++9M/HoqHW/vMCRT6Bbpiw1P9DGzh2MQe5fZy48uuge+bi6c5aE+Kux/eYjR9p9N6oLRHUONjgEYwu9mxkUzv0urtej9wT6jMrVv5oUtT8VxvlMAGNg6EKun9ah7N+7vYJXWBr3/5N4ReHpIKwz+ON4i3Sxz3/yYLw4hJd9+IQ9qFxn+fHYgwv3cAABrj6Ri2T8GYd4/5vVHoJcKKXllmPr9Cc5+i+5ti+n9opjfIz47gIxCg57Vsgmd8L8tXM2rb6Z2x+DYIM6yh785issSU5jbGkvr2mX/XMPaI84jwGzvtmLnxTt4efMFzrm+O5RipGFz9d1R6LNkL0qqDGFX/zw/EFEB5kNcrIFdD/KZ2LM5gjzV8FApUFyhQXN/d/iolcgqqcblzCK4qZQI8lShsKIG5dVanE8vhodKiTWzesHdRYHvDiVj7ZFUFFcadEDXzuqFP85lMiFLDdE28+s4KfDL1f6tf5n6x1SZb2SX4YGvEzjLfpjRE4+vO8VZduh/QxHo4Wp1+cwxsWc43r2/g9HxhcpOr48OcMeu5wfavCz1gS5bjyhfrH/c0D5P+/EETqUaBOlt9f6MX3lEUqKKCD83rJvdG/d8esBo3dV3R6GkWos+te3lN1O7I8DTFRO/OSZ6vMcHROOHw6lmzxv/yhCEeKsAGL8vfz83AC0DPcweo7FDjFI2RkrMJIFAAPQuKmiUhgbbxd2N+ZuNTOUGpdqloYvGQcsqJ1RunG9cViNj1snUamYdpVIbXY9Y3UBvR7mqjbZhH0OmMl5fH9jHplR1958+h95VbbTM5uj0zDnkajeLz8O+Bmepe+kyaZSuJp9npVzpNGU2BVNmVzXO51Yh0t8DN3PK0DXCF7fK655fjcD1SuF2USUKK2rQoZlBtPVQYi7OpRWhW6Qf+rT0r3f6ZRnr3a5WWFdGNhU1hkFZ7xb+NhUfZb8b+Vo5ckqq0Snch7M8rVyPxKJKyGR126eXU5xropcr3AzfU3Glxqgu0ihVnH3kMuNtAMDL2wtKd3coAWhdXJkBG33sunrRurqJ3j+ufTjCgv3QpVUITqZKz4xl6pxanR43irWAwHXZivbhvohuHsD8plh1ZvMQP/i4uyA40Mfo3nZtHcopu2E/g5bQnSoYPwuB+1ujcBV8Zg2Bpc/ahf2uOAFaFxXULgq7HZ99vXXtqUqwT5CvVQDK2rKouc+5pEqD/ddyEBPsydSP1tY/7PacjdpFjiWP9rbo+vg8e28nDOsahXu/OAQA0LmobN5/SM4tAwWgVZAns+x8ehECvVTYcjrDqvfr5J1KVGq0yCmpxiO9IqB3UTHJMEyVWabWGp1P6Plqla64Va6HDALftA1IK9Mz5TTXF6LXp5TqGqzfkZpXDq1ej5hg05NVdNkqZS513wur322r8upcVNAozSc96NgyBBFh/ggP9UNKHjdTrdLdHf7u7H6eCl1jQtGhRbBodlG1p4ek51+tcBF8ngCg8nBvFP3F+kKMUgQCwSGw+1MykSwp8ddzMa5LswYqkQgmpu7Z2XLYGVkaW6IModuvaIBrYN/ZpqZuaO566ptevaE5eCMXi7fVeXAMaROEhJt5zO8qXkY3qcQt/c9w/AVDUVatxbQf6rxKHh/QAm/c197KEhugWG+ZVld/EeG5P5/GocQ8LBjVBvOGxtT7eEL0WWKYhd394iDO8odWHhHcvqiiBr7u3E4s/U0v2HzeaHsN/z6IvIrse9c53JdJS82vGnzc6jdx4Otu2L++Bkg2n+9NNL9RPYnmebUUVNSJ07oqxa9FwatwO4f7IrXWo+tsmrFRTqMzfkAql8ajvuHuaj8DkDW8+Os5rJraw27HVwq8x0LyvZlF3Exr/Ox7479OQFKuYVCcsPAeNPd1s7r+sbd8sIdr3XByyc6rjBHNFtRo9YzXyrX3RkPtosDl28VG3kqWMvm7Ou8WN1cF5HKZpFS+UrPvFVVocN9Xh+tVRlMcZrW/UmmoDLR6PcVEP1x8eyS8JEwu1wjUc7ZELrHKpJ+lq4T2iM6sZ6rP7ybRAH4tqxQtWUZXNndL9r3G06oRCIQmBdsQJVbf7rtqXSpsW8Juwyne6I3dN2FvJ5aK2BSONMoI3X9rrsFSmpohyhIam1Fq3zXutxh/PRfBXnWZuCprrDNK0VzMLDZKh/3D4ZR6HRPgvmNaG3R6D9WGHK8/Zv9wpBMpBZK2owe33IGn4fvdfcW4DuUb54QGWXzWzepltP2S8Z3waK8IjGgfIqmcfJZN6IQ5A1ugTwt/o3XPsgbc7z/Y0eJjrzuaalWZpPJwj3C8yTOYllZpmL/dWIYY/uCGP8BYMKoN83eqQLihViBteNcIX4vK60j8PVQm1381uVsDlcTArktZdj2+kvV86W9NqLq/docbfsnfhjZIAcCN2rAjuv5ZeyTVojKJfeIj24dadBwxIlkGWikhUpZQpa1rWwprDb9Hk/Jteo6NJ9I4z80UQvdSqD3PKxP2ygnzkZbBMsDDebwLLYVt/MotNe+dBNjfcCozmk4Rhq5vTRn+P364M2b3b4H+MQZPWVP9OTeJRnmjySIWSqkWtUbO3XGVBALB6ZDS/jvDsJ1viGLDHsyxGyUxz6/6lcN+CBmg5A0wM2Pq3jZ2zF1ZYzBKsWfuhfqL7E5UpZWeUjRavV7QI6S+sDu6GoHBvTNj6TvCNYyLb8efkZZyFrYnFn2ex/pEYumEzia9gkzxSK9IvDa2vWB9+cqoNkhdOhapS8diat8ogb1NY8/wLAD4ZGIXBHhyjS1iYyp64ELDN0pF+LujW6QvAEM4Kx8hY2pDGfQ7Na+/x4spo+eMflEY16WZkWZWY4b9fOk6TcrzMvm98z4RUwNYIcQG/LP6R1t0HEfA7p/Qt8jWHj+VGr2RB6MYUo1SNVrjZ/TN1O44umgYUpeONVo3vltzzu9Trw+Hl8p0QJM1hpyG6Huwv3mp/WHuPjYvkuRjSvGUmtgzAm+Oq2u72O9j6tKxCGS1DVLbInpiT8ij+y6xSZHwPQKB4CjqWgixJtIZPGk441gK+PdyFub+fBoA0Ldl3Qz/76czEOHvJigYDADRC/8GYGgYtzwdh+4WinpLLy+FKd8fh6+7C+QyGfLLq7Hhib4mjUybTqYbLdsj4GFB89PRVHx3KBm/PN6XM0NqKbZ8vuXVWjy08ggGxQbitbH1C/myBeaurSHc6CmKwqy1JxF/PRfNfd0Yj5rV03pgZAfTM+S7L2fhydr3HBAuL3vZ6VuFRqG2R5LysGDzBTw/rDVWxt/EI70i8fSQVgCAW/nlmLy6LnwiMbsM+eXSZlQBYN2RVHx/2Pw7yC51cq3nwf7rOZi1hpuUJMxHjRdHxOLV3w0CxefeHIEn1p2CTAZserIfLmVyw0XuFFchLb8CkQHuWL7nBv46fxtbno6DnxWz25cyiwWXv7XDfAplABj7pSFEZOszccwyUwMB/oBWbGAjNrMsxbOqITiSlIfnN53Di8Nj8VifSM46lZWGsvogdlf44VxCoRh0iEeFgMch+3lVa3UYsfwg0grsJ+DORmhgzWbeL2fw98U7aO5rEAeOCa4LP8kpqcJDq44go9DY0ManMRjppfDj4RS8+1edoHhyXhnzffLhf0bfHkzC2bQi/Dq3L8J83DjrZq05yfGoK6rQ4PStQvSQmPxE7PaqlPYx3m45k8H8Xa3V1es87PqGnihZuuua9YUT4Hx6kWAYMkVRaLFoJ/P7uWGt8eU+49BgofZR6Fs2FaKm5nnmyGQyqF0VKK3Wiu7DLhtTFp1eMISUpkqjg4cZY5e1lFVr8dDKBPRpwdLak9heWFsF7L+Wg9e3X8InE7ugX6sA0e0snSz2UnPvkanJF357w/4t1Sj15b5ErD9+C5cyjRNYEE8pAoFAsCPs9kFskOMMgx92CfQUGIMUABxLrguv2XgiDd/EJ5s/HgV8XJuhSew8hu24S6Q2p8l5ZTianI9dl7Lw98U7OJZcgKTcMol7S+PNPy4jvaCS0/l2NFvPZuJ6dim+O1T/kC/b4Ph3t7BCg/jruQC4+iVsY5MYUrZhh+y5CIiQPfbdcWQWVeLVLReQml+BZf/UDSR+OZ6G28VVzG8KFDaeMDaOivHWDvodNG244eu0ADAySAEGIxNtkAIMhtpTtwpxMrUQ2SVVeGq98f34YKfh/f9yXyKS88otDqmhmfL9cav243PwRi7zN2338FYbDz74RimxwcD/Rrfl/H5yUEsAwCsj2wht3uDMWnMSuaXVHK0zGil6IJbw4UOdmL87NvcW3EasuVp4L/c+Cnmmmmrq2APe/ddyrDZIDW9nWZjlB+M74j1e6CRbR0ur0+Pvi4asrZlFlfjflgucbc+mF0kySAHcd619WN39XTmlu0VldjT8NlHMICXEH+duI62gAst33xBc//G/3H7DjB9PCG4nhNDAONhLhehA24kni2UH5otFWwrFqq7sZby8t2OooLG4pJJrEBIySAHCxlshoxR7IvPJQS05/eCnBxtrhLHf/4GtAw3b1U7siHG7qMrkemv1H6Xw28l03Mguw89WhLdbG743a+1JZBZVcjTChDDXh3ZVyqGQyzClj8Ez95mhMZx+zQoTYcbPDWsNpVyGeUMNz4ZtlPJUSTNK3S6uEjRIAXePphTxlCIQCA6BU8WKCe06flxvUUMp1YiWXWq602A4L++35DIIHEvivpZSra1f58aWz9fcjH5D4wzvrtRwBGtha31UaSy7/+W82V9r9Z7KTMwiA8bvvpCRSgh2+bQ6SnCAUa2V5nFkjhKWFlF9YD8D2vARG+KFU7e44tlGnlICNUTvaH90CueGbi0e0w4vj4y1m3eFpfDvP5voQA8kCwyGP5rQGa/yjCdfTe4GCsBzG89yll95dxQ0WgoyOeCtdsGirQbjl9Dg0YDw828V5IlwPzfGQCM0vpjVPxpHk4V1crQcTynja27u64bdLw6CSilHcaUG3m4u0Oj0aM9LK/7d9B7YcyWbMThfemcU3FwUaLW4ztvi2nuj4aqQo0KjY0R8r78/Gj8fvYX3/76KNqF1mbSqeGUpq+J+i/zPIdzPDX/PHwiZHOj89m7Ouk7hPrj+/mgABu+dsmot3F0M4tNbno7DhFXCIv+NmSqR9tPUe83GXN3HRidQNx3631Cbfsubn+on6LlT37aZI5MgcB3D24VgL0t/1FUpx/FFwyCTGQy6KqUcKqUCq+KT8NleYYOfSikXNBbXSAyTFHqWfONPx+beHB3GxWPa4YXhreGqkEOjo+DmqsDs/i3wY0LdxFqvaH9cemcUNFo9/DxcGa+z+ffEoKRSi74fGnvmC4WpD2kTxExQSb0ma7A0rJSNvftMYt2h6++Phk5Pwc3FUO/Qouy9ov1x/q2RTH1kKqHHkDbBuPD2SLjXCv6zvaoi/Opv+JWqd9bYIUYpAoHgENgNhBOM3zks2XkV/1zKwp6XBnEayvIa053A+Os5ko4vZQDO36KyRofP997AqA6haMeaSc4prcKX+xJRWaNHVG0oEZ+HVh7Bm+PaI72gAvOGxuCUBWnXTaGnKBSW12BNQgom9AhHVICHRftL0ZS6kFGE/ddy8fSQVthw/BYiA9xxT1vjGX8dryN2u6gSG0+kYVrfKAR7SxMWtQSKovDdoWS0D/PBgNoZTM56C493+lYhjtzMw9NDWpl0vbcIE/2Y9IIKVNToMOrzg1g1pTvaN/PGhhNpmNonChH+0jpR7G/jv2s5eE/SPhR+OJyCP87d5iz/9qB5L0MhjiUXoKC8BvM3nkHCzXy8PCIWId5qeKiUoEDhnT+5ngtP/HRK0nG/+u8m8/egj/dL2sdSHbY/z99GpUZns844exBEf1tCh954Ih1zBrZkMv0InV8sVMFZDFLmEJtZFhKd9XV3EQyPcHdVAgLRmELC4+Zg30+hMBJTM+EXWeGdQp4ivu4uTDgOrXMllMlQJpNxyuEpEMJDe9Sw16mUCub4/17ORk5JFYK91UbJDehJipySKizcetFIjNpL7QIfd/GBHfvdYp+fH0bjLOy5ko2skipMs0LzDABe/s04M6a9ENKpsfW3LBYeVR9DBWAcvsefWIjktVfNfNSCYdQuSvFvbDuvPaqo0eLbA8mSDYSXbxt7uPANVULfG23EoB+FUNPvqVICtRJF9DNzd1Uy+/I5nVqIVrwsbuxbptFa3+BodHp8E5+EAa0D0U2iBIX0CVUKV26XYPeVLIsnuaQglryH/R3wswTS91hKhln281CxPBNt0Z8jnlIEAoFgR9h6JWKDsqh66BVZS41Wj9W1A+RPd9/gGE7MpRkXypwkRGF5jfmNeHy29wYuZBTj872JHJHM5zae5YQRClFWrWVCk2KCPfH8pnMWn1+IW/kVWLztInZdysK6o7dw/q2RFu0vZTB+/wqDjs+1rBIma5KQSCi/3ztzzQncyC7DseR8bH4qzmj7+nIwMQ9Ldl4TLY8Urxl6cAeA8QTw93Rl3Mfri6kyTFh1BDm1WXGe/uUMBrYOxKHEPNzIKsWaWb0tPleuSKYhPok5ZXj/76uSj6vR6QUH2Gx6f7CXCXH6VMAoy+a/a9IMx1JhezkJDTrE0Oj0mF/rmdPMR80JZbQWtpGA/h7E3oGxXx7G1fdG125jvN4aw0t9GRQbhCNJ+YIptHtG+Rl5fJlCzEswNsTLaJkMMos6/fwBH02vaH/RENRhbYORnCseWsw//8M9wvH7aYMuz2+nMvDRw10ACBulLMl+yB/AS4VdvDk/ncIfzw4w8gShB/Bz15/G2bQio2PUCHiTdJegiRTkaTp7n6OYU2vg7hXth7ahwiGdppBq8LAF/IkwqVpUtqC+18n2jtLoKOw4zzUgBXmpoFLKmfOItReWZBT+Ym+iRRMlG46nGS3jG1bMtWOAbbIev7rlAib1iuAsY7cDNTrrPdzXH7uFT/fcwKd7bgj3ewT2keqdTAEY8+Uhq8tmjoa064zqEILz6UXoEuFrEy8n4ilFIBAIdkSKplRLkc6/PWHPbp2+VciZYbp6RzjeGwBCvdXIKpE2sDQlXEnDH0xeyBAWQzZnkOJjjUFMjKziKqYjWFxpeQiSJfN1+814ofHfoRvZBh2tkzbyCuOTUWjaACl0bX7uLiisqLtPpdVaBPO2Scy2nf6Xqb5gDi9NM51qfP/1XKHNzSI1VJAftmeOSo3ObGe+IUTjhZDLZKhmDTy8Jcym0rAH9L1b+HNm6kd1CMG/l8UTDYjBzoBIGy/E7gx7W6H61x6ZEM3x+IAWCPFWcURyab6b3hN7r2Zjwe8XBPY0RiGgcbZmVi+0CfXCT7N7Qy6TYeoPBi0vChTHQ+HN+9qjdwt/o/13PjcQGYUV6CiSke7Brs2hkMvQNcLXaN2zQ1szendChkK2UUopl+GN+9ozRilTzOofjWeGiIUT1nFwwVAAhjb1x5k9OdmhpMD2gjlf2xbx3xv6nREySAHcsKH4V4bgfEYR7uclRxDCz8MVvzzRB8m5ZQj2VqNVkCeW7rqG18e2w5BP4i26DnuQXVKNtqbzRliEPaKu6ZCusZ3DMCQ2yGJ9Man8+mRfPLKaq+1T37qE/Zpp9XojjcypfSPRPdKXOe9rY9sJHmdQ6yDJAunnM4qsKiubap7RVsjYzsdSHVW1i9xir6KaenhKXbtTanK9YGZCyULn9m1zhBJ3/Py45RNwUpjdvwX83V0R1yoQSoG2yFLuFk8pInROIBAcQnYJW+RYGKkzLKZIy6+w6DhVNdyBXZpE7ychg9RTg00LUrJd6s+lFTG/88qqJRu4LKW40rRRYPflLGw9wx0M3covx6XMYtzKL+e44tN6DUJUaXTIMuP9wR+caXV6JNzMg1anx6XMYhxJymPWsXUpqjQ6o9Tp59OLmL/56+jzpBdU4MrtElzMKEZFjRYHb+RaJfqZll/BMfhUaXS4mVOKHNYzK6rQIKu4CkeT8hmDHT8kqrhSA03tNdOUVGlwIqUAGp0eJVUaZBZVIjm3zKx+V1FFDed+3y6qtNgARGNJuEXLIEPIZqVGh9O3ClFcYdo4+deFOxaVpUpAy8maemFC93CL9zFHZY2O05GuMKdvRVG4lV8OiqI4RqF9V7kG12+n9cR9ncMEjzFnYAvR4yfn1Q3W6HJJuVVCgwGhcB9746KQY3y3cDTzdTNa5+fhiok9IwT2EkbISDq0jcEEPCg2CD2juZ4ibA+FsZ3DBA1P7Zt5m8xaKZfL8EDX5oJhzGpX091tdnn9PFwlhYsAwMQeESazQgGAu6uCk6HynrYh6BzuK+n4NFLE2fkh1HzYdXh0oAce6Npcckas/jGBmNYvGqM6hCIm2BPfz+iJ6EDLwsXtBV0f2UqE+yyrL2AN5dVaTlsE1HlKeatdMLFnhFVZQqXQp2UAOvO06GypKbX7cjbyyrgTa15qF44HpJjXmp+H9EkDazUO2VzL4hpwhEKHjc5r4TvUt6V4tjk2eo6nlPTnkVtajbT8Chy8kYsard6orcgorOA8XyFJhuySahRVcJ+ZVqfH+fQiznuaXiAtKYI5arR6TmIXGiFv7lA7SDsAhjDoR3tH1is7NRtLMwc2VoinFIFAaHCSc8twhjWbKhZiInWGRYzNp9Kx4PcLeKhbcyx/pKukfdiDxXMsQ4c1+JvpBL3xxyXm7yt3SvD69kt4/b726Pn+XknH33fVcm8KMaFPGqGsa4M/jmf+7h3N9SAQM0rd80k8bhdXYf8rQ9BCZPDAf7oxr+0SLRe7rzbyM+OU6Luv1N2LuKX/cdb9cDgFE7qHY+BHxtpAEf5uOPTqPaLn5fPHuUyj8Eeh8gDgiJCmfDjGqKP70Epj8d6tZzKx9UwmQrxVcHNRMCGhozqE4NtpPQXLpNNTGPHZQRSW1+DoomHIL6/G6M+td4Mf+dlByduyP1E6BDHlwzGinagfDouHMAmRnFdupAn26R7j7JXm8DWhZWMtR5PzOZ30t/+8gpn9xY1GK/67iU/33MCzQ2MwuE0Qs1zIczJAZNBoyljBztzDDG4k1KFCtoSGDC2yB+Zmp9nhEC4KOWcm2h6z0myjk5DnH3swmlsqHgrLf5pCWS/5hPpIG3iFeIt7T+UJDOj4A1RzA/lQH2NjY1OANkbxs+NZS1pBhcm20BxxS/9DcaUGxxYNY549beSS8r7UF36mv6W7rloUYsqH3fav2H+Ts46uD9nNjVifxN1F+pD3jg3CqQ/c4HodX88y7WUEGIyGlhDiJfxt6/QUpx5jf6pSjYQVNVoM+mg/0yeODfHkGOtP3yrAhFVH0SXCF3/M6y96HDpL5M0P7mX0ld7ccVkw5LG+aHV6TPr2KM6lF2HrM3HoXqt7lVlUKZgFsiE8kO4WLydbYLWnlEajQXp6Oq5fv46CAsvCRwgEwt0N3zNAbNxU35nHL/8zaEBtPZspeZ9KG6XLHRATiKk8AdRAT8NAk07ty9cf2XQyHSm50tMn0yFXDcmJ1Lr6/r7OYYICwQAYjRxThjPKynGvpSnR1x+7xRELZmPp7NzXvE6x1PJodBQKK6SHTmaXVHM0ykyFc1VrdcgtrYZWTyEptww7LfRG4iPUeQv1VmNq30ij5UIZoGxp0CgRCAv9en+Sxcd5woSHEQDMHdQSAOBlgS4UYFkdRetdrdh/U9Sj7IXhrWv/j0X/GMMs+CsjY7H0oU4YHBuEWf1bYPW0HgCAST3DOSnG2egFwvdmxkULbytQAdsr9Xp9WXhvW0nb8cPTvp/ONegqFXI8MaAFhrcLMdLXsYd+h1Ihx5yBLfBorwjBRAJCRh8h+F6MMcHiIe4b5/RFv5YBzPsixu9P9UPflv5YN1s8lCVdoI7jvyJCWb/YvDZGOKyqPjzUrbngcvp7bghog+I3ByyvlwBg5ZTutiwO45l7jJXNUVNbRrH22pbww9SScsvr5fVuat/fn+oHAPB1d8X0flGYGRct6gXm4+6CKX0iOXVDqyAPdGhm7Fllq4yobPhhh0I8MbAFBsUG4aMJnSUdc3FtqKKXSonXWWGL/HaZXcdL9YTOK63h9IdvZJdx+uq/njT0X9le6qbmQEpZ2TktMUhZktW2QqNjJpN/ZfWvEwT6yn1b+iPawuQ81hDspcaUPpGY1T/aov2WTegEAGgjoIPYVLGo91VaWor169dj06ZNOHHiBGpqakBRFGQyGcLDwzFy5Eg8+eST6NWrl73KSyAQ7iKsTbFOY41WLz+jkBjfT++J4bWzfw+vOsKI8A5tEyQqFP38sNZ444/LJmPnpcSf0/WuqbANWoTyTnEl+n34n+h29UEhl1mccYwN29W7vs/aFLYcX1vbqa/U6GxaDjZsA0K1Vm+77H21KOUyHFs8DACw/hi3MzmodRC28MI9qzQ6o9lya7GFkbhtqBfCTHhptArywKIx7bBIZNA86dujOJFiMMZO6ROJX1gdamtfW6HrYgvHGnR0+nLWP9rbYBQc2SHUSGQ29rVdnLAMRlOqtnw/zuyJjs18sPZIqtF5G5NR6qnBrXA4MQ+Hb5o2yLPrk+Htgpm6ms3r97UX3NdeM9uvjRU+HyBd4Jjt5fDRhM4mwzr6tQpAv1bmw3t6Rvtj05P9TG4jZGjm19mm3pmHujUX1OmqLy+NjBWcdHpiYEssGtMO0Qv/tvk5+Qh9P4kf3GvkEZecW4Z7Pj1gtO2YTmFIXToWX+1LNJuowRLYId8N6yll3P4cTc5H/xjjLLVSMFXHtmYN2N99oKPZY30wvhM+GN+Js2zb2Qy8+Cs3E6Itwvf4qCVkO/RSu+AnE8ZhPj5uLkxbQFEUPtx1DTo9hSqNjuNVa42nlJCRmf2NW9pEWJuFsVqrt6o/wZE8EHjtf5zZq179V0ug37k1CakADKLr5u5fuJ+7oJh8U0Zyz3X58uWIjo7GmjVrMHz4cGzfvh3nzp3DjRs3cPToUbz11lvQarUYOXIkRo8ejcRE01mqCAQCgUbMSGPNwOjfy1l4YMVhXMgo4sSVP7DiMB5edQS/nRLOjgQYRMDHC4RUCcE2HrHHBaYGCbQQclGFBpN5YqA0cySkrG+xaCfu/eIQkyWQD9t9XUpHyFq0OsqsV4GpDiV7nb00tACDJ9P0Whdya5n4zRFEL/wbV0yI3Zuiyzu763V+AHh+01lB4x37M/nr/G0st+HABjBo0lhC13f34J9L9fPWoqm2QWpoc4Zec3oNptZKraP4GjH1DQ3mw9cJeXnzeUz9/jjKawyz0zIYG7GjF/6NxOxSwc6xOa8XRyJmjK/W6jBzzQmsPpjEuSZLdVoawpuEj7kyPr3+NPR6ijOwa6gBFWA8kH3x13PGnlI6StDLEpCWecwaxIx55mx8l0Q8Z61Bp6dw+hY3YkToeu11D8RgP7MjSQavKVuILptDSNBbimi/GGIyDrZ6/YW+d1t5zLOx9/cqk8mYe99nyT58f6iuf8i+gx/svIrohX9j21nTz+S/q8bJZdiZD9mPJXrh36jS6EyGsPZess8qfTFLkuisqzX6AIY28Yu9iXjyp1OC3nb27BubQ0qTdLdk3GMjuYY8efIkDh48iBMnTuCNN97AqFGj0KlTJ8TExKB3796YPXs21qxZg6ysLDz44IM4dMh+aR0JBELTQjR8z4rJquc2nsX5jGImjp3mfEYxTt0qxKsmsjdZ0nFidzDZArwPdBXPJuTuanBOvXy7BEdZrvVsMgqlhZOZygT46ui6EBcvtRLBXvZJqV2j05vtaJnyCmOveefPKzYqleWY89Kq1urslsXPEv44d1vQKMbucG2uR+dfjAWs94kOPaVnwx/rYxzSBwBPrT9jk3NXmRF4l8KTgwwJB8Z0qhOp9nN3wfja0B86ZE6Mp4ZwExY8zfrNn/0VE5ffK9DBtzeHb+YhuTYcWCYTHhTP/fm0iNC5c3pKAeLeHn+ev4P467lYsvMap02RYjhkb+8IDRA6VJPNUJbu2K5LWTieUsAZ1NHfYkMwhfedbzubKdgGffC3cD0+WaSeqC+iRqna//83Wjjcc8r3x21WBp2ewoRVR81uF2xCswswCOzbErZ3W0BtyFqRmUQUtkAoG9yuS3dQamVInFgfYs5A24Ro0sk67M3iMdJCj+sDO2zv/b+vMn+z+zg3cwxhhHzvMD4f7Lxqcj1f1Py1bZdEtqzjFM94KwUxQ7cQbE/DGq0en+29gd1XsnEwkavv1SLQo0GN+kIMjg0yud7FTAKLpojk8L2NGzdK2k6lUuGpp56yukAEAuHuw5bZ9+iOWKEVnS9LdATYsxgTe4SjU3MfyGUytAkVj/82lyXJWjo198GiMW3hpXKBh0rBERZXKuTY89JgXMosNtsR/2Zqd8hkMqTmleNDCamTq7V6mJt4NfUI2R2lgnLpektSeaBrM/xx7rbZ7TQ6Cq5K8QtxJqcRofDS+qZS/mZqD5xKLcD3LBHyh3uE45WRbVCl0SGKlUHm+xk9kVtajVBvNfLKahDqo8bWZ+IERdtlMsNgf8Vj3TAwJggp+eUorKjBrDUnmW2m9IlEqyBPvPuX8GDW0nTiP83ujWa+aijlclAwDBhp3Z2vJnfHtL4FiAxwh4erAt5qFywY1UYw2xsbOmsbzfx7YrAq3qAfwx+AiRlz+J5M/KyPZ94YYfba6oNYuG9mUaXg+1PfjFn2xFVkhpvtjca+JklGKdbfjpihFgovfXJQK+y/XjeY0uj0qKl9v8Z0CkWInTJHCdFHIMuXkJFBaFKldbAnukb42qNYHI+olVO645lfztQuN6x4ekgrDGwdCLWLHMOX1yVwsMT7QgjKxPv10cPCekAqpQLn3xqJkkqNYNKNlkGeOLF4GMZ8eZjRGBvZPoSTxMMSuOG8hr/tEULJ56HuzfHP5SwABl2c1QeTkZRbjp0X7+CRXpYbJ8UmjebYSDesQ7M68e7H+kRapHe08N62WCrQV3qoe3NsPWMIKx3bKQwvjog1qf9mK+bfE4Ov/jPWvbSHOgL/mPnl5nXxtDrKYqkGazUq2fux9awA4K/5A6w6pi1ZPb0Hpn1/gqPTysbFAR67jsaiK16zZg1u3bplr7IQCAQbUV6txaYTaWbFUytrdJjx4wn8d826To9UKIrCtrMZSMwuRXZJldEMjK2y7wmJsZqirFqLF389h5d+O4d/LmUJppEVg63bI5PJ0C7M26RBCgBc7eS+3zncB3GtAtEp3ActgzyNwpF83FwQ4Wc+Ne3ojmEY1SFUsvZDtUbHy/Bi0DLYdIKluSNqchQ3RtqKzuG+kjqCprQOdHoKG09I76QCQHMzRo76IGSkoQcA1jK8XTDGd+cKBvdtGYBQHzWiAz0475NKqUC4nzuUCjmT2UlMHJz+fAfGBMHH3QVdI3wxtE0w7mlbZ+QJ8lLBk7U/33BiSWp0tYscg2KDEBPshehAD7QI9OA8f4Vchn6tAtDc1w2+7q6Qy2VmDVJCsD2OzqVzPejE6ixXnvU2/jp35tbTQoF1S5FB2NhSo9M3uux7Yp5SYrojlobvOXoGnYYfapVVXIUv9xmkMUK9HZ/JTijE6ZpAhjGp2f+sgX2H2N86e3nH5j6ICbatWDD7M998misJ4K0W/5Z93FwQ4e+OIBHv5WBvNdqzhLfNeVeZgh36TLcbDRGaSnuEAwZdnId7GDzJrQ3hoz/fAA9XTlZSewza1UqFRUZpsSyp3SLrkidE+Ls3iEEKMAi+89lx/rZJz3pr4der/DZNiOk/nsC8DcJe1OzJLzZ5JrKRmoLdhvEnizzs3N5KQaVUoFWwuJeeRJnBJoVFT+WZZ55BTU0NoqKiMHToUOZf8+bC2S8IBIJjeOfPy/jtVAbaJKTi3xcHiW435ftjOJNWhAM3cu0qqLf7SjbjKiw0YBcbM1iqKTXoY+PZR1OsPpCEbbUiqfSsllSsCYnzdrNPQyilE2Xu3OwOga+7tLTEVVo9PFV1A8GdF7Nw+lYhfkyo87iRqillD1oEuqNNqBfjri5GjVYPD5HH+c+lLFEvHiF6RfvhdpH99LG0euNwMSlu82LIZQYDK1sUFQDyJWYDA2C0Lx8VT/iWLYSrkMk4Xi0KXk/MEoPCgBjT7vD1wc1FgUqNDm1CvaCUyxgvsDf+uMzZjv98aPiDQb4B3N4CxDKZsHYWRQl72jmzp5SQN1rCzTx4sYwBFzKKmL/bmZksAMQHlw1Jjyg/nL5ViJ612QD5YYSvbqkLPbdWNNiWCIVpNTgywT8FUchlNhPwZ38zx5K5ng6eKvPtZ1yrAPxx7jb8Bd479iRdfbKDsT2laON+Q2hKsfsP7q4KjO/WHB//ew0nUwuRmleO6EDLrom+1zKZjDPRym9XbEHbUC+LJ0OFYE/UNGRdWsbzCNpx/jae23jWLueSmhSIz86LwpNokf7uuJVvPLFsrUHNmdswmo7NfQAI69xK7Yc3JSz6oouKirB3715Mnz4dN2/exJw5cxAZGYk2bdrgqaeewq+//orsbPt6XBAIBPP8c8lQ6V/PNp61ZHMmragBSgNcZomKCnkjiYUfWRq+Z2lf4t/L4vUVO4X4JxO7cNZ9/HBnwbTeQrDHFe3DjFMP2wIpM/v8GbQ3eZmnfnmiD/N3uJ873n+wI959oINJketqjY7TaT6eko+9V7n31NQzNOVFBRhS3kthZlw0ZsZFY8Vj3QAYBvhPDmqJoW2CsZCnKSLmLSLG9SzpHSJvtRIrp5hOvz4zLhp/zR+Ayb2NwxjcXBRGqez58AfktJC1tdCeSeF+7ph/Twyz3JJQ1mBvNZY+1AmDRDQS+B4sbI9BuVyGVqxZZP7jMTf4fmZIKxx6dSheGhGLj0XCZmzButm98dKIWEzqGWEIhRPxehQb9JoaDK6e1sOs2Hp9kZkYstP1L9swZuqbcDRCEwJX75TAS13XiWeHZ80fZlozDDB4M3z0cGd8x6r3G5qPHu6MuYNbYlnte8w30LKJ8He8p5RUA099w4tNwX6vzZ1l/eN9zGwhHbFLD/BwRd+W5kPk3n2gI14eEYttz8QZrRvdsU77rle0P8Z0CrVK1JvtKUUb9xsi+16HZt54fWw7LLy3LbqE+yLUR42BrQ1tAz9TqxTo94x/D2yV4RUAtj0Th4X3tsWEHuFG9cvfz4mHerGz/wHA1L6R+GZqD463eaiPfTQ9hajQcPsDR5OEtUulYC7Us8JM3yPS3x27nh9ochu6z/D62Hb44MFOmNY3ymgbU7IXpkIB+SHyzgB/ouHRXpFYeC+3j7p6Wg98/HBnhEuIbmhqWDRtr1KpGO+ot99+G1VVVTh69Cj279+P+Ph4rFu3DhqNBlpt/TrJBALBeooqaoyMFJU1OrixjAt6PdUggw6tTg89Zd5oIqbDUlSpgVYnnOJer6dQWqWFT+1sgqVx6oDpzvLw9iEc77FXNhs8vRRyGUfY3BwKuQx6Xd1M39hOYfj7om0ykzHnsHBA2zPKD7MHtGA8gL6Z2t2oAZxa2zmY3i8aAARTa9do9VCx9F2EZs5MPhWRlb880Yfp1MW1CsQLv55j1tHPhC5PqLcab9/fgVl/X2eu0DzbePjs0Bi8MqoNZvx4Agdu1Lmam5pRU0gMEZjYIxwf84yX7PLy+fChTvjwoU6C6+776hAuZQobw/jfrTV6V88Pa40vasOA2KFoL49sw+hRWKrl9GjvSDzaO1JSCnb2ORVyGfxYM4L8uoJfN/A7mi+OiIWLQo7nJBge6kPvFv6cTrqrQi4Y4iY2UBe7m2M7hWFkh1CRtZbTLsxbcGbZVBVBFznEWy050YIjaSUSCsNuA+hren5Ya7OGXppJFtTr9qBVkCcW3duO+W3qC5QSjm1vTLWfniolI7psaV1iCez3ml0cofe9XytjXSxrEZtQeX54a8H+Ch8fNxdRYyl78spFIWcmOoTqVp2eYga6pVUaThhwja6urmzI8D2ZTIYneCLkE3uG48CNXGw5nYEXh8daFCJLP1d7JiDoFunHhNwNbROMTScN3isuChlHc4oP30v4kZ6R6BTuw5lM8Rdzw7YHvNfSkvB3Pv4CoYBsykU8pVoGeuC/V4Ywv1OXjkW1Voc2r/9jtO3amb0478J7D3bErYIKHGT1z9hhwvTYhTZImgozZ0/YFVbUaZbaa3JYCmqlnHPfFHIZnhrcCqdSC5kJXVv2Bxob9aqd5HI55HI5ZDIZZDIZKIpCZKR0Ebu3336b2Zf+17ZtncUwKysL06ZNQ2hoKDw8PNC9e3ds2bJF8vGXLl0KmUyGF154wZLLIhAaLV/uS0TXd/dwMqy8+ccltHvzH1zMqPNWmvTtUXR461/OvjdzTHtVWcPw5QfQ64O9Zj2exAZyPxxOQcxruwTXtVy8E13e3c3oYS3edtHi8oll7jGFpe7//A65Pdzns0osCxdz43k/STW88OF3CGp0eqTxdL1MDVyKRMRm2c+Ffb+8BLQ6PFTSZ0vpGTd+ympTBlqpz8uWji6mUhXzjTK0sVQqchn3+YulKbfVAEBoZp6dVUYhk3FmvPnf5H/X6rLW5ZdVo/2b3I5tQ6dZpxGbvRWrH8QM7z42dtH3EQnTNfU06W/UmvrQEagFwnYUchlnPEZnbLp82/ZaKg2FqYkWtQkP1obCVN3O/qbtGWroqHdW7NJtkbWSXT+bS45C39vvDiaj8zu7sflUnScSx1OqAcP3hBjeLgTeaiVuF1fhiIXeOw1dP7HvuY+bacMMvy9B3192u9QQ3mk0Kl556pON15wn+/n0IsHlQu+YkGexXCY8Yc03pLH7PI+sPop2b/6Doloj065L4hO86QV1EyxsrTt7hH1KRUjzC7CftEdjw6InU1NTg4MHD+Ldd9/FkCFD4OPjg7lz5+LOnTuYM2cOEhMTkZycbFEBOnTogDt37jD/Dh8+zKybPn06rl+/jh07duDixYt46KGHMGnSJJw9az4+9uTJk/j222/RubP93PkJBGdjOSsdKs1PRw3JCWjPCAA4davQaPC0QiBjR33Q6ymk5leguFKDW2YEyKvNpH03ZdSavfYUAGDjCeG4bFOIudmLZc+xBUIzlfyODR+2MLQQqfnSUuYum9AJLQI98E6tZ9H0flHoGuFrNjUtAPwwwzispVqr4wxMOof7Gm1jyoYnlgGJ3Wlgl23trF7M3yse64aoAHd88Wg3U8UGALwwvDViQzwxo9brq6iSm+nPtKeUtA5lSaXtPIQ/fMjwnN4e195oXTVPx+XwzTyzx5sZF421s3ohKsAdm57sx/H44Q8YXx3dBq2DPa1Otz0zLhohLHFefugrwO2gymSm3/9mvnUiyX9duMN5n4a0sZ+GlDnEjGFiGlhiM9bP28jD65khrdA+zJvxcDRCJn4+vUh4jLMSG2KsEdU62EvQUMAPJ25MmBoSmmszGgJTtqZHetWFXtvTKOXn7oKR7UMwon0I/DzqDLz21isUM8hJyUBmDvazVUk0Sn2w8yooCnhte93kHEdTignfc8yAXO2iwP1dDV7Mv5+2rK9GV6kyGfDZI4b2xJ51/8j2dZ4q7D6HEMFeKvSONrSnHZt7o2VQnZzBxB7haB3siSFtTPffbMns/tGIDbGNqLq18msqgUk1mUxmpNv3YDdhPWr2BDrA9cA/mVoIiqoTVf/kX+MxjzmWTXCcXeDbaT0QFeCOlVO6c5bPjItGqLcaT9ooo2RjxSLTnI+PD4KDgzFu3DjMmzcPmzZtQmho/dzMlEql6DGOHDmCVatWoXfv3gCA119/HZ999hlOnz6Nbt3EByJlZWWYMmUKvvvuO7z//vv1Kh+BcLdQYaVooRhssUhzA3tz567S6jgZXSzVmuJDURRkMpnobPO9HY3rpAh/N87Mi7UIzZqtnNIdOaVV+N8WYW+vH2f2khQWZY5HekVyUjK/+0BHyfsOa2cIZ+z27m4U1nriVWn0nNl8wYG3idGBmFcJu1PupXYRDIG7r3Mzo1A9MV4YHosXhscyvwe2DuKI05oaNEnNxONiZvBgCa1DvLD/lSEortTg7T+5IutCGa/MQYc3Hlhg6Bxzwpx4z+CZITF4ZkgMrOXt+ztwwimFYH8DCrmM4xnAfxZVnAxS3HVfPGLeIGkvLPWU0ogstyZhghCvjm6LV0e3xeFEYSMlrb3z4ohYzgQFUDf4cJasc+Zo5mOsp0SZnddvfJjylHKEUWpk+xDsvlJn5DNVPrbYty28h8SQyWRYXasDlmtlli5rELt0U9ptUmE/WyEj0rS+Ufj5mGGykX9v2Z7Z7MkWuu60JLOcrXm4RwTWH0vDP5ezUFKlgbdampco21NqfLdwjO8mTWvSWga0DpSc+Ecul+G3p/oJrhMK57c3vu6u2P3iYJv0F62RxADE66bTb4yQtH9cTABH71Woz0O3s6UWaF8Chr690KRGQ9GxuQ8OLBhqtLxzuC+OLR7mgBI5Fxb1ort06YKsrCwcPHgQhw4dQkJCAvLzrRdRA4DExEQ0a9YMLVu2xJQpU5CWVpd6Oy4uDr/++isKCgqg1+uxadMmVFVVYciQISaPOW/ePIwdOxbDhw+XVIbq6mqUlJRw/hEITY29V7MRvfBvHEkSHrSwNXaE2H8tBy/9eo7RiTAHe3BmLrPd9B9PmFy/fDd3NoQfNnbDjKA7H7rjJmbcEhLQtJUWg5Brs0xWP9FOe88Ks2HPglVpdJzZNKHOgyn7odhssy0FTKUc/7Vtl0Q7YFI78dZ24EwhFK1gjVHK+Lh1BxbThbAnfE0pdrgi32uN7QmWzvO4dFE6boBlefiesOHT1gLnYuUy9RqvjL9Zu03jMEoJFVNPwbzSdSPDVJXCD8FuCPjFMRXKzralOLNovrWIefnaAiFPEzauSjnzPZuaUGH3k7QNqCklRpdwH8QEe6JKo8fOC9J1NRubJ2dTwdoujbmQU3Pw39FKgSyf9KS3pWWUOn4hOAaL3pxjx44hPz8fH330Edzc3PDRRx8hLCwMHTt2xLPPPovNmzcjJyfH/IFq6dOnD9auXYt//vkHq1atQkpKCgYOHIjSUsMA87fffoNGo0FAQABUKhXmzp2Lbdu2ISZGfBZ306ZNOHPmDD788EPJ5fjwww/h4+PD/IuIcKzYJYFgTx777rjgclOCgQAwa+1JbD2bia94s+xi2Cr1MgB8fziFM1jlD8zFrkmM5LwyAOIGE6HZyen9DGEx/WPqJ5ZaWGHcmZXLZGY7oqZC+B7rI13Lz5Zo9RSnUyxslBJ/D8REugM97Zuend+Rv5hZLJqlxkMlzaG4oQyD1qZhdibY35dcJuN46Gj1FNqGcmcyc2o10/jvl6NCUQBhjQzAck0pWyPmlcrOesqvS+hQiNzSasytDR94SCS0wlnR64U9pdo5UNS2vrQI9BBdZysPO0vgexDrTFR6bANnQ737bM1BdzNag/U1cNBC2HyGtq1/WBm77Gwhbf/a8KeR7UMYMXVTBj9226vVO1ZTCjAY4B/uYfBy+t0CrSNn9eQc2ynM0UWwK3qBaIceUX5m96uv4Yf/jlYJ9HnodraPhEyXbA6JeBITnAOLlbU8PT0xevRojB49GgBQWlqKQ4cOYc+ePZgzZw7KysokZ9+79957mb87d+6MPn36ICoqCr/99hsef/xxvPHGGygqKsLevXsRGBiI7du3Y9KkSTh06BA6dTLOWpSeno7nn38ee/bsgVqtNlovxqJFi/DSSy8xv0tKSohhitDosIenhhBSszOZ6rBag0anZ2Zg+IPTvDLL3Pbpgb0lhrMZ/aLROdwH7cPEM7EI0SvaDydTC5nffVr442/eLKHBKMUd5KqUcvw5fwDTKV05pTsu3y6GngImfnOUs+3kXg1nlHp1dBu89FuduDbb00ajNb6flnpK7X1pECe1uz1oE2rsvi028y006zeifQh6R/vjkd4R6Pz2bgDmRUFthTOmObYUfvgeny1Px+Hr/TexMj4JQJ3BnG+EcmQoCt9TxVUhR41OL6oppakdFA5vF2JXnSMxIzB70uGd+ztwBORpdHoKC0a1wYj2IegUblk952j0FCVoGJ5/j/WhqI4mwFOFvS8NxvDlB4zWiQnm2hO+No6pMHr2d21PTSk2ahcFDtaGxohN8nzxaFc8v+kc2oTWz1iZW8pNLvJIzwhM7BmOHlGWDZKFcFHIcejVodDpKU4989/Lg5FeUIlO4T6G+karN2nwY9932ju8IUW3hRjfrTk++ucaTt0qREpeuUnDK40zJmLwUinx6aSGD8+TyvZ5/fHg1wn1Ogb9eU/uHYG3xnXAxcxitAryxLxfzuBosmES75WRsRjXpRk0Ooqpp+o7SWrsKSVulIoN8cLeq9KdYQjOjdVy73q9HidPnkR8fDz279+PhIQElJeXIypKRGRTAr6+voiNjcXNmzeRlJSEFStW4NKlS+jQwaBP0aVLFxw6dAhff/01vvnmG6P9T58+jZycHHTvXicgptPpcPDgQaxYsQLV1dVQKIwbKpVKBZWq4WedCHVs6NABHZ95Bp3nzXN0UQAAmvJynFm2DJnx8ajKz0ebqVPRY9EiRxfLJOY8nWyFVEPOP5eybHpedueLH8ZjKUt3XcNrY9uJhjIKIZfLrOpw8jvHQjoKcpmx8cNTpeTEvqtdFKLnb8gZxCDeDH0Fa1aMnYKaprC8xmgZjdAAOibY/vH+Qp1bS0xKSrkMc3iClA3mKdUkjFJsTynj9R4qJZOeG6gbXPGfm61D3yyBr5uhUhqMUjo9hdO3CnE2rRAz46KhVMhxLDkfd4oMg1hXO4ccig1S2WcV03KRywClQo6e0fUfWNsTId0enV5YVcqeaeQbgphgT3irlSipcnzYCd+DwVRXgP2tNlTfBAAiA9xNrm/ma9Aju3qnhNGWtAb+ezWpV4QkLxKpRPgbX4evuytjjKSNS3V1o/HzSLiZj5d/O482oZ5MMhlHhu8BQIi3GoNigxB/PRdbTmfglVFtRLdNL6hATmk1yyjVUKU0T89oP7vLDNSHZj7SHTPEoGUxekb5Q+2iQK/adiGYlcjkmSExRv1PD9f6ZZLjG04vZhYbbUO/EzYMyCA4ARa9OSdOnEB8fDzi4+Nx+PBhlJWVITw8HEOGDMGXX36JoUOHIjo62urClJWVISkpCdOmTUNFhWHQKedVoAqFAnqRmI9hw4bh4kWuUPCsWbPQtm1b/O9//xM0SDUmyjIycHXtWmQdOYKKbMNMq0ezZgjp3RsxkybBr4145U6wjMvffYfk7dvR8amn4BkRAZ+Wzp8RwdZC5WKIeQKwSckrx6u/X7DpeTWs7/7R1cfqdazjKQW4f0X9ZpGkwu/zCrrPywAXB3cWpRLoyTVKldfUDZaEPKV+PZWOZSLZDE2F9jU0YkURWi7kLUinoLclQn3wphi+J4Q/K5MWbYirr1aFLeEPSFQucpRWAxU1Wkz7waCRV1ShQVxMACe82N6DQnYIExv2bVY42FvCHugp4W+1KVypsxjW+CGrJsP3WGUuMDEx0dCwv48LGcXoEuFr5XG4ht2GFp7nh++plArBCYstZzJ4+zn+XXq4R7jBKHUmAy+OiBV9vwd+tB8A8FZtFlpn8pRy5ISIFNwlyg5czyoV9BzX6PS4U2yYSKniZcf2Y3lpCk2IsrNgWkO0gPdcQXkNE74K1E2OO1MfklB/LDJK9e3bF6GhoRg6dCiWL1+OoUOHolWrVlaf/JVXXsG4ceMQFRWF27dv46233oJCocDkyZPh6+uLmJgYzJ07F5988gkCAgKwfft27NmzB3/99RdzjGHDhmH8+PF49tln4eXlhY4dudmkPDw8EBAQYLS8sZEZH4/Dr7wCuUKB6LFj4du2LWQyGUpSUpC+dy8Sf/0VD+zeDY9m0rJREUyTffw4Ajt3RqdnnnF0USRT346f1DZWJyYExOLanfolC3h6SCusqg3dobG3LsXUvpFYfywN7z5gOnOYpfA7Ui0DjdP1uijkRqFJpq72y8ndsGzXNWQWVeK3ucKZX+xFuzBvvDg8Fp/tNYjPs40klgraSniV7IJQqKtY+J3QcrYhru6Y9S+XFGzlKbVudm/M+PEEfpjR0ybHswR2pkKxAUl3lqcUHbIoVd+rIRAK3wOAMpZHy48JKUaddnsPXjs290GfFv44m14EHzcXwYxkYmGPjaZ/Lyh0TgkOUJxpIGstCpYhs02IF966v71DysE3xJoM33PS+96G5X18p7jSaqNUCMtjeO7glmgX1rAZvej6hhEwV8gACdrrjtThoxneLgTeaiXuFFfhaFI+BrQONLn92bQiAM5lCHISO7EongJtZedwH1zI4HodnU8vEjRKsb0b+d7ujw9ogYLyGiN91c8f6Yrr2aXo17J+uquz+kfjdlElhrYNxqw1JwEY9A4FjVK1/w9tE4T914WTNbEzZx9YMKReZSPYF4t6eFevXkUbEW8ciqLwzz//4IcffsDvv/8u6XgZGRmYPHky8vPzERQUhAEDBuDYsWMICjIIBe7cuRMLFy7EuHHjUFZWhpiYGKxbtw5jxoxhjpGUlIS8vKYtXFaaloaEV16BR1gYhv34I9yCuEKKXV96CYmbNpm1KmgrKqB0N+3afDdD6fXQazRQqFSoKiiATz0Mro7AUl0lPmHeaknu7Fo9JbgdvYyiKGYWz1L+eWEg2oZ6Y21CitG6Gq2+Xu72pnh5RCzmD2uN9x801qqrL/ziCs0iKeUyi7Qe7u/SDPd3cZwB+vnhrbH5dDoyCis5Hnr8zGnm4M+0h3g7LozaEjdwIY0Ue+um0OnYbaUpNTg2SHLaa1vjakZTCjAMQNqEeOF6dikqawz31tQguKFxc+FpwAkYm/QUZaQV1xBZ036tNVS/++cV/Fhbl7JfT7F7bmsdwIZETwmblZ1oHGs17Ob0vQc7oncL5wivNOU17QS2D0FkMhkGtg7EocS8ehn46Wt/oGszLLq3na2KJxl++J5UfT1H6vDRqF0UuL9rM6w/lobfT6ejf0yAyX4dbWx25Dslk/GN9o6/j+ZoEejB8eD+4MFOGLfiMGcbsck4toFfw5sQjvB3x5eTuxnt86CNkmOolAq8+4DBkaS5rxsyiyqNvlXaKEW3WS2DPAWNUmE+ahx69R6blItgfywySgkZpFJSUvDjjz9i7dq1yM3NxfDhwyUfb9OmTSbXt27dGlu2bDG5TWpqqsn18fHxksvjrFz98UdoKyvR94MPjAxSACBXKtFm6lTOsqOLFyN9927cu3UrTi1ZgtzTpxHaty8GffUVtBUVuLBiBdL+/RdV+fnwaN4cMQ8/jLYzZzINQ1lmJnaMHIm+77+PluPHc47N13+68PXXuLRyJcbt3IlL336LjP/+AygKEcOHo+frr0Pp5sbsq6upwbnly5H611/QVVcjpHdv9HrjDcn34vovv+Dmr7+iLDMTcldXeEVEoO306Yi+7z7munNOnsQDe/Zw9qPL+Njly5zraD15MgK7dsWV1atRcusWBixfjkPPPQcAKM/IwIZaPbP7d++GW1AQLn/7LTIPHkRZWhr0Oh3827VD52efRUifPpzzUXo9rv/yC5K2bEHprVtw8fCAf/v26Pzccwhgee2l/Pknrv30E0qSkqBQqRDavz+6vfwyPMIsz+qRX1Y/T6nbxVVosWgnekf747enxL1vDiXmYcCy/fjj2f5MKNe7f17BvmvZmBUXjRX7k5hMdZZCexEIDZoGfbwfncN9sPXpOKuObQp7ajLxZ+qFPCVcFHKjwauzU1rrEZKYU8Ys+/uicJrnQ4m5GNjauO7ieyw5o1eD0DhdKEzR3mnPaWPG3qs5jHH2/b+u2PWcDYmQJoq69prpDqkzueoLaUoBXMOOXg+j77ohdUjY4Y5sD1exgaktM6baE6Fq4vLtEnx3MNlouTPWKZbiaB0gMfaZEOx3ok/VCPobpI3d1kAbpRz1bOiJv8ScMvSM9pcc4mnthKGtebhHBNYfS8P2c7ex61IWvpnaA0NZWUH3Xql7t+h3yZHfspoXHukEtj2z8NsaS0I32RNAjmwX6H7PryfT0ZXl1Ui3s2sSUgEAWSVV/F0BSJMbITgPVtVO1dXV+OWXX3DPPfegTZs2WLJkCV566SXk5ORwQusItiHzwAF4RkYisLOwLosYep0O+598Emp/f3RbsAARI0aAoigcePZZXPvpJ4T174/ur74K7+honP3kE5xZtqxe5Tz88svQlpej6wsvIHLUKCRv346LK1dytjn+5pu4/vPPCI2LQ9cXX4RcqUT8009LOv7NzZtxeskSeLdqhR7/+x86z5sHv7ZtkcfTEbOE7OPHcWbZMkSOHo0eCxfCLSgI/ZYuhcrPD35t26Lf0qXot3Qp1H5+0JSXI2nLFoT06oWuL72ETs88g+rCQux/8kkUXr3Kvc433sCZpUvhHhqKri+9hPZPPAGFSoW883VZyy59+y2OLloEr6godH/1VbSZNg3Zx45h74wZqCmxPPytvp5SNCdSC8xuk1lUyRkA/JiQglv5FXj7zyvIK6vG8j03zB5DKJ1uaK0444j2oUbrAIMGBB3nTuPnXv9MbfbU7Fh4b1uolHI8V5sFSmhQKpfJ4MrTvFshMBPlTIhlqxOC1tjhw7fjrHisYa65b8sANPd14ywTewMEjVKsgr/7QAeoXeRYPqlr3bFs9DqxZ49jgurCPmnX+u8PG3sUNgYyi+q+YVrAWWiwpKJ1U2qv15k8ecp52l60AYgdZqynKCMPKheFrME0gth17P1d6maxxbwSnOj2WoxKKRcegDSCwaM52F4J7ZvVL2ucLTFlJDiTVugUXjlC0N9qtdZ6Tym6TnKUzl1abbIXbW1bJLVOcXT2PZou4T6ICTa0adVaPWatPclZ/8RPp5i/6ckIR4bvfTedG+beGGzd7AyRD3VvLvjsQ7yFBdHZdanGUToLqPvOCsq54xu+1zQ/ozVNY5loIRiwyFPq9OnT+OGHH7Bx40bExMRg2rRp2LhxI8LDwzFq1Ch4eztPY9lU0JSVoTInB+HDhhmtqykpgZ6V7Urp5galuq6C0dfUIHLUKHR98UVmWcZ//yH7+HF0fu45dJw7FwAQ+9hjOPTii7i+fj1iH3sMXpHWpfP0a9cOfd97j/ldXVyM5K1b0e3llwEAhdeuIfXPP9H60UcZ76jYxx5DwquvouiGeSPG7YMH4RMTg4GffWZV+YQoTU3FmG3b4BNTlzY6sHNnXPjyS7iFhKDFuHHMcrlKhft374bCtS6uOebhh/HXfffh+oYNzLVnHz+O5O3bETt1KnqyMva1mzmT8Qwpv30bF7/+Gl2eew4dnnyS2SZixAjsevhhJG7axFkuBVsZpaRS3xmIzx/tiit3SjjuxXSmulBW5pBRHUKw9KHOGPJJPIorNajW6hDo6Yq8Ws8wX3dXFFbUGUiOLx6GbWczsXTXNcllsWfnOTbEC5ffGcUMuoU8orR6PVxYWbnCfNSIizGts+CsKOQyyR0BurPZp4U/1j/Rp8H0LtQuChxYMATbzmZiQa0gv5gXjtBStlfU9H7ReKx3pN1noNm6D1UanZFx01Uht7u3lq1gdyjpt15Ig4ae2dXWdoqdyWjSr2UAfj9dJyJM1yHselFPUVDzvneZTIYHujTD1rOZdi9jp3AfXHtvNJRymaT305mMfqYQqq2rNMLvfiMYO5qlR5QfEj+4F4BzaALR8EOW6bA4wNAOKOQyp/RUcKG/1XroVNJeM+4NEI4rxH2dwrD1bCbz3kv12HIWrzuZTIaHe4RL6qfR75AjbZwDWgfim6k98NT607Vlcf6aZXLvSHz1300AwCM9IwSfvViVz+7DVYvUrQ3B88Na4+XN51HJK4PUro62kfSJCAYsqp369OkDlUqFY8eO4eTJk3juuecQEhJir7IRYDBKARDUgto7cya2DhjA/EvcuNFom9aPPML5ffvgQcgUCqNwv3YzZwIUhduHDlld1taTJnF+B3fvjuqiIuYa6GPzz9122jRJx3fx8kJFdjby6+EZxSe4Z0+OQcoUcoWCMUhRej2qi4oMIXwdO6LwSl0YTdqePYBMhk4CHmD0TE/6nj2g9HpEjhqFqsJC5p86MBBekZHIPiHsWWKKvHqG77EREoK2NQqZTFLImkqpgJ+HKxMuM3z5QSZ0DDDOeqZSyi0WE7Z3R589IBSa7dPoKE5mo8bQ4RHDEgNfdq3LtVIha/DBFn+QztdNMAV/MNYQIRFs1/uk3HJc5SUTaEzhn0IDVaHXhr6vlzKLsXTXNRRVOE8WL742FN3hZ3eC9ZSxJ0VDf9lqF4Xk99OZwiMt5fJt47ThQOOuS9kIJcNwNPw6k55UAgzfg7N6StHfw18i4eZSoBN8NHTWPRp+aLNUW5MzPZOHJGoQnar13nf0t8yu8xtbtaJUyATD97JFwt44RikLtUJtCX3P+VqaUidQSqqMk9IQnBeLPKWGDRuGH374ATk5OZg2bRpGjRrlVNkQmiJKD0NqTG1FhdG63m+/DW15OSrz83H0f/8zWi9TKuEeyg2DKr99G25BQXDx4Kbc9G7ZEgBQccf6Rtqdp4PkWus5V1NSAhdPT5Tfvg2ZXA7PiAjuuVu0kHT89o8/jqxjx/Dvo4/CMzISYXFxiB47FkHdu1tdZo/wcIu2T96+HdfWrUNJcjL02rrKjn2csvR0uAUHQ+XrK3qc0lu3AIrCnyzRfjZypeVZpmzpKVWt1ZvVPqnvly+XyzC2UxiuZZUCALx42UJoj5sBtR5D7JhxU42km6sCahfLOu+OTpMc5qPmDF7tLZptCwbHBuHADWNhSaVcBqlvIp0ZrL56aNbSLqzOu1fsngsZaMfbSNDTWiZ/d8xIVN5VKQf7xnu4KlBeo0OPKD84Gz1ZZerY3AeAsK4b7dHw3SHnC1PkvxZ0+Az7PWob6mVkLJTJgP4xgQ3iKWUpjcUmJdTvpD10jLe1d2nuLnpH+zMh/vw6k20zUzZgmKql0Ab98+lFVh+DHiQ3ROICIWhjGG2U8la7AKg0u5899TMtJVgkdAwwtGd0G0d7wju66OzwN1kj8MHceqaujXFRyOHtZix1cbtI+J1hG6X6ODCxAv2e841S/PC9Zj5q5JfXONSARqg/Fo18//33X6Snp2PNmjV4+umnUVlZiUdqPXGIcco+uHp5wS0oCEWJiUbraI2pskzhzq3CxQUyK111xZ4nO1zQaB+FcONsK68bn1atMO6vv5B54ADuHD6M9D17kLhpEzo+/TQ6P/usoQxiWhki5VaopGf7SvnzTxx77TWEDxuGdrNmQeXvD7lCgcvffYey9HSLroWiKEAmw5BvvoFc4L5ZkyUxv9Yo9fiAFkjKLUO8SHpUPt9N74l5G85wBrkanXmjlDVPdUT7EOxhCVg+NaQVIgPcUVypwagOXAPqoVeH4lx6EUbXLle7yEVDNGjeuK89VEoFJ4W2FFwc6NL+2SNd0MzXjdPBbwwN6ycTu6DXB3uNllsym0kb4qICHJMVtGNzH8Z4I2qU4v3+cnI3jGjXMB7CYndSSpbD/QuG4FhyAQYLCMw7mmHtgvHq6DbwcFUy4qVC742YsTg2xBM/zOhlzyJaTJ1Rqu6NGSiQ6lwuk2F8t+Zwd1Wgs5Xp6AnScbR3RVNj7exeaP/mvwCMPR7ZRigXhdxpRLX5FJTXfxKENgY5ykOVMUrVemz5ubua2txpWfFYNzy74SxaBnInyid0b46NJ7j9akd/y+xn3RiqlUyWwcnNRVFruOQiNmZif9uOzPSsqp1grqwR9pSKCnDHrfwKvH5fe7i5KIy0yQiNC4tr04iICLz55ptISUnBzz//jNzcXCiVSjzwwANYvHgxzpw5Y49y3tU0GzQIZWlpyLtwod7H8mjWDJW5udCUc0OeSlIMM9G0txPj5VRaytmu4vZtAIZMPvywKSnnpvR6IwMOfW4pKN3dEXXvvej7wQd4YO9eNBs8GJdXr4au2mCQcfH2NiozAJRlGspdHwNZ+u7d8IyIwMAvvkCL++9HswEDENqvH3NuGs+ICFTm5KC6qEj0WJ4REQBFwTM8HKH9+hn9C+zSxeLy0eF793YMxdpZvTG5d4SZPQx0au5jpHsiZdBrKXMGtsDwdsGcZS4KOR7o2hzT+0UbCS4283XDmE5hzMxe62AvmIP2wBCbURPzcHGkp9T4bgYvO3ZoBn9WyBkJ8lIJ62lIuJUVNVpcyCjC8RTDjHtzX8cYpQCDoRQw8c7zqoz7uzQzOzvuiA4rP/TKw1WJ+7s0g48NEgHYGplMhmeGxGBGXDSzTMirQmxQe2/HMET4O+6dEYIuP19PjR+pKIPBW+HeTmFGYvsEaVjyeTWCsWOjwt1ViWUTOgmuYw9waU0pZ8QWxg3a28pRnlK0NzjdV6CsmiZ0PGG1+qH8cCyhd8fRRil2MprG4IjBjhgQm2QW62vS7Zivu4tDveto4yvfo+tO7W8vtcG3xs1VgWieYZPQ+LDIKDV79myUsgb8I0aMwIYNG3D79m3Mnz8fu3btQq9ezjV72RRo9/jjULi54fgbb6AyT8BF3QJDS7NBg0DpdLixYQNn+bWffgJkMjQbOBAA4OLpCZWfH3JOn+Zsd2PTJgDA0aR8DP0kXjTjgeC5BwwAAFxfv5577p9/lrQ/38ijcHWFT8uWAEUxoXReERHQlJai8Pp1ZrvK3Fyk7NkDANh1KUtyefkwXmes+5134QInox4ARI4YAVAULq5aZXQM2igWMXw4ZAoFLq5caWQooyjKpEFLDNpTKsDT4P0V4CHNC0ypkMFVyW2w7CGYHOipqldDHu5nfgBHd1rEOsNBXsL3xNk6z43BUwoQ1tMolRDDP/fn07h/RQJO1BqltA7M7kIbA6VoSvl7OO9sdKgP9/twdAfeUqIFvOXErsEZrs1TzXU0p7Va2JmKdHrj5tkJin53Qe63zRHzRHZhe0rJZZLa7MZIal45bmQbtFIdJXSu5oXviQ0DnF1rkGl/eX0eIX18R2u0s5PROFmXURC2IUrsPa00Y5RytAYZbfTle7NvP3cbpVUaRvBcIZPBQ+AanSXbJEEaFoXvrVu3DkuXLoWXF9djwc/PD/Pnz8f8+fOJp5Qd8I6KQv+PPkLCggX46777ED12LPzatAEFoDwjA6l//w2ZXA43CaLzzYcMQUjv3jj/xRcoz8yEb5s2yDpyBBn//Yc206ZxMu+1mjABV77/HsfffBP+HTog59QpgxYSgKziKkANfHcoGe9KvA6/du0QNWYMEjdtgqasDIFduyL72DGUpqVJ2v+/OXPgFhiIoG7doA4IQHFyMm5s2IBmgwYxGllRY8bg3PLlOPT884idMgW6qiokbtqEEu9g+Oam4VRqIcZ0CjNzJmGaDRmC9L17cfC559B80CCUZWYi8bff4NOqFUfzK6RPH0Tffz9urF+P0lu30GzAAFB6PXJPn0Zw795oM2UKvCIj0Xn+fJz//HOUZ2YifNgwuHh4oCwjAxn79iFm4kS0mzVLctkqa3RMivJAT8PAee7gllix/6bZfdUuCiM9Ko3WdrNuHz3cGXuvZGNGXDT+PH/b6uN8+FAns0ZFesAnZvya3b8Frt4pgbfaBX+zRE6DvcS1DQjimAvxFIOv/+IoTSkAcFHSRimx8L26b+Gn2b0bpEw0lhgw1j/eGz3erwundHQH3lLeuK89Ptx5DdPjophlbUO98Od5422dISpoIC87Jj2bzM7opdPrjTzYnGWG/d0HOuDNPy47uhhWYcktdAYDZlNDaKA6sUe4kbfzl492wxt/XMKTg1o2VNEkUV9JidT8uiiBQQ4Kj6aNOXR9I5akoEuELzP544zQIfz8iVChy3H0t6xmTd42hlolyt8dRRWGBBD0ZDUfMU8peqLQ0fe8VZAn8zd/wvNWfgWjLaWQyziTzo/0jEBGUQVm9ItukHISbINFXTspFXn3eohOE8QJv+cejNm2DdFjxuDOkSM4vXQpzixbhoz9+9Fs8GCM3rwZ0SKi2WxkcjkGrViBNtOmIfPAAZxZuhTFSUno9sor6M4TS+/49NNoNWEC0nbvxtlPPwWl12PIN98AAMqqDZXDufQi5IhkbxCi7/vvI3bqVNw5fBjnPv0Ueq0WQwQ8ioRoPXEitBUVuLZuHU6+/z4y9u1DmylTELdsGbONytcXA7/8Egq1Guc+/RQpf/yBLi++iMSwDgCA5LwyyWXl0/LBB9HlhRdQdP06Tn34Ie4kJCBu6VL4d+ggeJ3dXnkF5ZmZOPvJJ7j83XfQVlcjqFs3ZpsOc+Zg4OefQyaX49LKlTj78cfIjI9HaFwcmg8dalHZaKOSSimHZ61guJdA/DgA7Ht5MOe3WinH0DbcjlWNCe0wGqlN1aSeEVg9vSfULop6NXC+7q54ZWSsyW0YTymR84T6qPHz430wrV8UZzntQu5onH1Wk4+tQhccGT7pqjBjlKpt9oa1DWZEuZ2NHc/2R4CnCt4s7x1HdyYtpVukH357qh/u61ynX9E/xliTCXAOw45cLsNzw1ozv+mBOluLQ0dRTpvRbnq/aHw0obOji2F3HP+mND34nsX9YwLw8cQuHO8RCkCEvzvWzuqNuFbC37GjaN+sfvU4PZDvGeUnOti3NwqmvjG0W2LVTI1Wj0GxzqcrSEMb1/jh80LjTUfX+9zse85fs0hpeSpFdFqdxVPKRSFnDJd8r65qrZ4J+5TLZJxnEhngjl+e6IuRPK1agnNjcYqv0tJSqNWmB3De3t4m1xOswysyEr3efFPStv2WLEG/JUsE17l4eKDH//6HHgIZ+9go1Wr0efdd9HmX6ws1+dIlvPvmP0BtZfZf25FYcvllo/1bjh+PluPHc5YpVCr0XLQIPRct4ix/7LL5GduYSZMQM2mS2e3C4uIwdvt25rdWp8eOI3JsixqKiFyDUWr/tRx8M2MFqrU6xHx/DD/M6MXx+oj84Te8teMyvG4VolNzHzy/6SxaBnlgwZw56DBnDud8zQdzjTwAIFco0G7WLLPeThEjRiBixAiz12QO2iglJUSOb/hQsip9mhoJnlI/HbuF1+9rb1E56+u9Yc4zhz6+uXaUH3bmKF0IPmoXRaMJ3QMsS4e9ZOdVLB7TTnAdX4enIaE7XQk38/DyyDa4lFmMxdsuYuHotohjGUUs6YM2dGYe2gDF1mASM8w2JsQ6xM5ocGMGiTrT4XvOVHa1k9R7lmLJ9+VM2caaCnyj1MmUQsMfTvRum4LdB8otrRYN6xejrNqxmfcAtoad4bdYC1qt1Tu1YZaeFOJ7SgkZ8x0dicXuf1ZrnV/3U9jbjBsa+ef52/hqcjej7eg+mcLRNx2GfmaNVm8kdl6j1XM8pdhoJcgxEJwPi4eIsbGx8PPzE/zn6+sLPz/nSz9NsC0llVpOFrQ/zmYynlPOSFZJFVPBZhRWokqjw/pjt5BWUIHskmok3MxHwk1uONHqg8m4kFGM1QeTcDK1ALsuZWFVfJJRpegs0CLndOgezYTuBhHtjx82zIhH+LtxXOwDa2f5XHjxMFI0paSIoUfyxIgHxAQJLpcKuxOokMvwYFduVhB6sGJuIMLO9qZ2kTd45po3ao15C+9ty1nOFqZsDFhilFp9MFl0nSONUrRLOP0OzPnpFC5kFOOx748DYHf2Hd85E4P2NGN3zBrJ+NAk/HqJxhnC9wAw9U/XCF9mcMU2KguH7zVc+czBT3DRFHGi291kKK7UcH7T/QV2s/tAV+GkIs7AY33qZCo++fe6iS2N0ej0WJNgSM4THeA4YWV60oGuX8QiWaq1Ojw9pBUAx2ZRE8OVCZ/na6sab+togz4dhQAAybmWJXpyBC8MN3jyTuoZziwTalOF3p06TynHtxF0P5MfaqjRsT2lDMu6RfoCAMZ1sU6mheBYLPaU+v333+Hv72+PshAaCdmlhnA9HzcXBHi6Ijm3HNvPZmJq3ygzezqGzMK6rA0UZdADuHTbEGfdNtQL17JKcSgxD8Nq07zr9BSOJOUDAI7czEebEIOGmp4CrmWVoFuk8xle81meUmw+ergzXhkVizAfN4xsHwo3VwVcFHJcfmcUSqo0zEDc2FPKMm8dlVIu6OFzYMEQzu8gLxXOvTkC7q4WVz0AuEYQpVyGJwa2xPZzdTpVdMPE7ry0C/PG1491QzNWpitfd1ecfWMESqu08PNwMbp+e/P4gBa4v0szoxlaazWaHIWqkRnRhOjXKgC/nkpn3l++bgHdX3NEf1iqRwg9QGFv3RjCC8whFtbp6MEJTcsgT5x5YwS81Uq8ucPg7VvBmrgQFDpvyAKawVk8RC3FIq9FZ7rhTQSxkFT2gDcm2FNwG2egbWidLm5BhWV6ht8eSMLl2yXwdXfB/GExti6aZOSMpxRtlBLerlqjR9+WATj1+nD4N/DkmxRoY75OT0Gnp5iJFaF5Kke3aexJH3tkqLY1w9qF4ORrwzmT1UJtZ7VWb9T3pMPQncHRlG6nKgQ8pej3n/4eNs/th5IqrVMnpSGIY/HIsH///ggODja/IaHJklVsMEqF+agxsWcE3vvrCn45noYpfSId3mjQnEkrRGF5DYa1C0FGITeV6ImUAmSXVEMmA+YMbImXN5/HocRcZv3FzGJmJrC0WosNJ9KZdZdu1xml9HoKW89moku4D1qHcMX/G5o8JvMetyJWyGUIq83KxU4N76FSwoM16+PKmz0R09cRw1UhbJQSeh9869Ex4hul+A0pfT6OtgVFoWWQcQfZz8MVfg5suIRCBtTKxjVItMRTCjCENimdxc2lFn4WI5VSDrbuf2NItU13yJzFWGMrXERmaZ3pOunOL/3tnk0rZNbpBTSlnKjoFn+/jRFn6ZM0JcQMII7Wn5EKu/6wxLhwI7sUX+4zJI95a1x7hyZIUbKMUr+fzsCFjGLB7egwM/6EpbPgwpoQ1Oj0UMgNdZKQ944zvV6WGjMdBb+fKXQPqzQ6o7603ok8pfh9NJr4GzlMXaRgSRgQg1TjxfFvG6HRkV0rbB7srcaE7s2hUspx9U4JDvIyajkKvZ7C42tP4omfTiElrxyZRVyj1I5az5oWgR4Y3j4EchmQlFuOO8WG7Q7dyOVsz85Md+V2XcP/87FbeGXzeby+/ZK9LkUydeF71nU8+J5C/Hh5cx23hhq2q3nhe77uXDF3IU+pga2dS2TVFI3N88hSTwu+iz5N1whfG5TGOuhroENzxbzVnKg/bIRSbmyMbQp4qoXnzZzxOg/WTmxcyypllun0lFNrSond36aEM93vpk5sqGMn56TCfiekTsDp9BQW/H4BNTo97mkbjAcdHJ5IT0QcvpmHVzafF5VccDaReT7sCdFqliyIUE/Bmb7logqN+Y2cECFpC76xB6jzlOJrNTkCt9p+cWUN14t9/bG0Ou0rJygnof5YNAKKioqCQtH0Z9YIpskpNRhpQrxU8HV3ZcL2lu66xljXHUlaQQUKKzSgKOBUagEyCisAAF61nkGnbhlmsjs284GPmws6h/sCqEtTf6hWX6pjc2PB/su3SwAYsg9+uS8RAHCnWHr2QXuRJxK+JxV+nHkVLyMHu+PmpTIeyDRUhim2J5FSITe6XrrTwm54nx3aGo2FxuwpxdcJe6xPJKOdRSNk3IwKcMes/i3sU0AJ8PUK+IZBR4bv8Yl/ZQg6CWQAFBI6bwqIzXg6Ywf0Zo5xZled3nmz7wGO1cSxFXwvXz6NLaNpY4D/Ro/tbNBvGRIbhPce7IgtT/dr+EJZgIz1Skj9Pn88nILz6UXwUinxwfiODvfAM5fIYkBMIBbe2xbvPdixgUpkHS4KGVOfV7EmQwWFzp2w3m9sCN1DIVFwZzL20BOF/PA9gK1n5/hyEuqPRa11SkoKAgIC7FUWQiOBDt8L9TG4Lj87NAZeKiWu3inBjvO3Te3aIFy9U8L8fTa9iAnfi4vhvrsdmhmMTrQnzeHEPJRXa5nwi4Wj6zKFtQg0dN6v3SmFRqfH6oPJyC83eCcVOYEbr1j4nlT4nlJ8QUF2mvPpcQYjJDv9fEMNvNieObR3CDteXsZ4StXt48PzpnJmGpunFNuryMeNe5+fGtQKg3mpqIVmc798tFuDa3qxoY1SubXfEN8w6EiTAr+fFR3ogW3PxBltR3ccxTSYGjNCYa6OHhAK4S7gNWgwSnGXOVPZzRl0nBX2LXQx8843lpCyRgWvvY+pDY+XyWSY1jcKPaKcW3eWPYCVMo+akleOT3YbBNFfG9uOkURwJOaMBaE+ajw1uJVRu+xsyGQypg2u5OjxGT8YJ6o6Gy3sd9+rtg9fUF43htHpKZRXa53MU0rcKFVdO1ZxgihDgg2w6jHm5+dj3rx5aN++PQIDA+Hv78/5R2jasMP3AIM2z1O12T0+2X3dYj0iW3OVFT5xNq2ICd8bHMvVQuvQzOBxMLC1YeB8+GYe4q/nQqOjEOHvhgGtA5ksbQ92bQ4vlRI1Oj0OJ+bh+0N1mcRKqrQOzR4GAPm14XtBNvKU4lf+7DTndIx5SZWWWd5QzgBCGigqlhGBbnAb62CrsQmds42E/FA+mcz4OQgZpXQO9iRxczWUsbRKi5zSKtEMiJakofcQ8Ca0FUKdRHrg7evkAxBrEPrmnaGjzCdYwHimoygjTTJnKrm5LKWNAXMG7aZwjc4G/5474/doCnZxzXn36/UU/vf7BVRr9egfE4BHekXYuXTSMHfPndlDk4+QJ8xfF+4YbUe8YeoPu49A9/sf+DoB8ddzAADjVyagw1v/Iqc2oZUzGPVp2Y6/Lhg7PdBatuY8BwmNA6tGbtOmTcOePXswY8YMfPLJJ/jss884/whNG9ooFcLqhM/u3wKBnq7IKKzE3wKNSUNyjeUpdT2rhMm+1z8mgNOQ055S3SJ94eGqQEF5Dd7aYdCHuq+zIXXuvKEx6NDMGxN6NEf72u1f+u0cKmp0TOpRACipdGx8ORO+JzAwkgJ/IM4Ps2J7SrHDtGhBeLr/46VS4ukhrRAb4okfZvS0qiymoD3WAKC82hBfzjaG0O1Sz2h/DGwdiGlOmhFSjMYmPMwur7HoPOCi5HYU6PeK3dFxdBYbdrl3X842NgzWvtyW9Hm+eLQr2oR4YdWU7rYoIgchTxt64D3/ntYI9VbjuXsclxXK1ggZCZ2gn2zERw93MVom7CnVQAVqwrANxEIpzmmGtQ1Gy8DGH6LobDzA01NqfEapuvKa+x7XH7+FE6kFcHdVYOlDnZ3G09GsmHPjsUkxIbZiulg0jew1c0q+ntIdsSGe+HZaD853+/7fVwGAEczfeyUbgHN823RGZFo+hY2Wl32P0Lixajr30KFDOHz4MLp0Me6EEZo+2SUGAwgdvgcYDAMz46Lxye4b+OZAEh7o2sxhjTdbaFZPGWaMlHIZmvu6IdLfHSl55Wju68ZkXnNRyNG3ZQD2XctBXlkNfNxc8NQgg+fXpJ4RmNTTMDPWoZkPjqcUoLBCA4VchiXjO2HSN0dRWq1FUaXGYZncNDo9CmtFFwOsLAPfGMLvHLC93xRyGVRKQ7Y9WiCRnpXb/dIghPm44X+j21pVDnO4cjK1UEZlpzubCrkMPz/exy5lsCdiXjrOCvveu/HKLpPJjAaM9HukkMuYzoSjjVLsa6AoysgoZU3fPjbEC/++OKieJROnU3MfXMysS7pAzxIObRuMY4uH2e28jkDIUOuMM+ZtBESeDULn3DfIGcvemDFllPphZq8GLMndg9pFgcGxQThQmxTGGQaulsD+BE2VPb2gAkt3XQMA/G90W0TwdBMdSTNf05n/GpFNijFKmYuyIHVn/WkX5o3dLw4GALyz4zKzXGwi2hm+7QExATh4I9fkS008pZoGVhml2rZti8rKSvMbEpocOj3FaK+EeHMbxWl9o7EyPgnXskpx31eHjTqLLgoZ5t/TGoNig5BwMw9rj6Ti3Qc62DQ+v7RKg7QCg7B5v5YBOJqcDwAI81VDqZCjVZAHUvLKGS8pmgGtA7HvmsF9dd7QVoI6RGzh88cHtEC7MG/4uLsYjFIVNQBsPyP737VsrNyfxPFU4kOHDsplgJ+7bYxSGl4D9f2hFM753FwVqNbqGe0punQN2WmgDWdCRqnGSmML32NnQ+S/QzIYDxhzS6sRG+LFCS2odiJPqaTcciNhZGcSOqfh6+gomqCWFA2dWZSNM37nQsazAzdycSu/nLPMCYve6GDfQ0fq0d3NsL1dnSHExxLYnnbHkgtEt3t9+yVU1OjQO9rf6byuzXlV843hzgzdTzA3QUW8YWwLOzFKWkEFSqvqIj7YE4iOhn7XS6u1ots4QzkJ9ceq1nzlypV47bXXcODAAeTn56OkpITzj9B0yS+rhk5PQS4z9srxcXfBtH6Ghvvy7RKcSy/i/DuZWohFWy8ip7QK8zeexZ4r2Vh35JZNy3cj2+AlFeKtwrB2dRpSzX0Nhq8+LQxi5wN5AszD2obAVSFHpL87pveLFjx2r2h/uChkiPB3w/PDDBndfGuNV0V2CN8rqdJgweYLOHWr0Ohesv/RHhOxIV5WN9p8YwjfU2rtkVTm7+5RfixhSj0oimIMY44YcKkFwvcaK3TYaDMf07OgzkJU7cyxq0LOaMzRyGUyePB0puhMlWwbK99A3NDwQxDVPM8pGks0pezNmbQizu/GFvZpCbQmIBtnFHR3UcgE65/U/ArOb+creR0P9wh3dBEsprHX+Y0VdtbhxjYglGJEq9LoGE+wJQ91dDqDiKcZ3cKxtX2JxgBtWDZrlHKCRzB3cEsAwOTekQ4uSf3ht61f7E1k/qYz8jmrwZmvV0ragaaBVZ5Svr6+KCkpwT333MNZTlEUZDIZdDpjhXxC04AO3QvyUgmmH39lZBsMiAlElYbbuFAUhde2X0JmUSUmfnOUyfZw+GYuANuFel29YzBKtQ31RrdIP2Z5uJ9h8DyrfzT6tQpA+zDuQDgywB3/vDAQPm4uot4qEf7u+OeFQfB3d2WEjH3dDIa54grbG6W+3JuI/PIatArywMJ725ndnq1xZSn82WZTnYMWgR51RimNjiPy7tIAKTA8VUqUsWZM2GFjjb1h6t3CH/+8MJAxojo7A1sHYuszcQj0UOGvi1wRSpkMRnUELYxPvzObn+qHZg6+VrlchoGtA3EoMQ+uChknhLJGp68zTDnpu7VkfCeTIUxNEWf0KJTJZHCRy83qojhzJfXhQ50cXQRJyET+JjQcA1oH4kqtfmdjM4rL5TLc1zmMEdPW6Skjwxo7E1yLQM8GLZ8UlAo5WgZ6IDmP64m5ckp3NPd1Q+dwHweVzHJoz1923emtVqKkSou4VgE4kmSIeHAGD9lXR7XF2E5hRmOIxsiDXZtjy5kM5jfb0KxxovC9TuG+RsvcXBWoqax7X5zh3SDUH6uMUlOmTIGLiws2bNiAkJAQpxH+I9geiqKw+0o2Kmq0GN0hDFm0yLm3sCeHi0LOZLPjk1FYiXf/uoJbrJnjy7dLkF9WjQArs8bRlFZp8O/lbOy6ZOhktA3zQodm3nBRyKDRUcwgX6mQo2Nz4ca6ZZD5jkcr3jZ0mJ8hfK+O7JIqXLlTgiGxQVZ9H0m5ZYx30pvjOmBwrPA9tRX8WYdbvNl9PvSgsKRSwwktbAgPhiAvFc8o1XTC9wCDQbWxIJPJ0L3W+CsUvsenUqPjZDvif0+Oon2YNw4l5qFSo+Nkc6yq0eNGTpkDSyYMrekGAM39GocB05Y46yBYqZBBIGs1Byfo4wvSNtSrURo3+XW+l0ppMsyDYBt8WFm8+JlXGwN0ZmXAEKqkkHOvoaJWmsBVKXeKgbkQLYOMjVLeahd0ifB1TIGshJ4UTWFdC33PvdR1w1RnGGsq5DJ0FjCSNEYCPLnRLmxNr8oaQx3qDO++O69+CfZSIb+cO+ZydNZ3gm2wyih16dIlnD17Fm3atLF1eQhOxubTGXj19wsAgI3R6bi3UygAINjL8vCix/pE4psDScgprcaknuG4kFGMa1mlSEjKx/1d6udq/MXeRHx/uE73qH2YN9QuCnRo5oNz6UWcjHG2hE6vyg/fW7T1Iv67loPf5vZD7xb+Fh93bUIqtHoK97QNtrtBCgBceJ5S/1zOMrk97RB1IaMIfVrWXV9DDGr4ejpsI0JTMEo1Vvj3XqgDWanRQccKiXMWcUo1y/NPzXqfKjU6bDieBsAQutzQiN0eF0WdUcoJ+owNjrMOgqWEOjhTGChgGBDWaPVoHWIs1O6ssOsW9qAVqG3LGv5TvetQ88KeGxvRAXUaoBqd3ugarmcZvMCcpY0SQui+N8b24Fx6EQBg6a5reGqwIckQHT6m5kw6NnjRmjT89ood9XAju6x2G8dPVBhNeMq4ZQWItmBTwaqn2LNnT6Snp9u6LAQno6C8Bh/uvMr8PpFagM9rY45DfSz3bFK7KPDl5G6Y1T8ar9/XHgNbBwIADifm1rusZ2sbtR5RfpjeLwqjOhiMZ6+NbYeZcdEY3TG03ucQgtGU4oXvZRYaYrVvC+ihSIEWa7dXufnwPaXYCAlm0otclXKm8wA0TPw53/ClYoVbkU6L42DPPAPCBhWtjuJ0JpygvwOgzshRWaPnJHjR6utm3zIKnSe5B9sjsTEOCC3h6SGtjJbxxeidBSlGeWcb466Z2QsTe4RjwcjGOckYxgv/5U9aEOwD+z47q+eiKcZ3a878rdEZ93HoNPT8wa8zIXjfG+Hrz5f7AABNbdvbt2UAs8wZvHaaEnx5BQ1bikNRl8na0Ujp49gyYRbBcVjlKTV//nw8//zzWLBgATp16gQXF26mss6dO9ukcATHsnTXVRRWaNA21AsvjYjF3PWnUVzrERRihacUYGhg6EZmQOsgfHcoBYcT8xg9MiHY6yiKYjwEFHJDynm9nsL1LIOW1IcPdUIsa8a3V7Q/ekVb7qkkFUZTiucpRYeX8cMITF0nm+zaMMlgr/qFNUrF1CyDUJ+sV7Q/Lt8uQaVGx3QegIZpwIyMUqyyO5sXwt0E33tS6ElodHpO5j1n8WyjO/dVGh0oqq49Yw9I9E40OGEbf9meXU2RloHGWU2d5b3hIyV82dlK3j8mEP1jAh1dDIswdQ8bYwhiY4T9DTqr56IplApDWJ5OTwmG/tB9OnbCHGdD6L43hT4QRVGMobAFq/531nq/seLC669Xa+piz+n77wxGKf573hTecYIwVhmlHnnkEQDA7NmzmWUymYwInTchLmYU47dTBgG8D8Z3Qo8oP7wysg0+/vc6AHFNKUvoHe0PV4Uct4urkJRbhphg4/CBBZvP40hSPna9MBDeahfMXnsS+68bPKtUSjnWzOqFCD93lFVr4Vor/NiQiGlK0alVy6rqjFKZRZW4/6vDmNw7Eq+MMj0rnVtqiD+wxX2WgilPKba3CA3dSOy5ko0pfQwZFw3Zp+zfWPANaOzwPRkZjzgMfsdBqAOZVVyFXu/vZX47Q4cHAEe4n2L5SrH10pzIJgU/d1fklRnqHLYwe1NE34hSm0sJddA604vUBODXIKbaMoLt4BilGqGnFGDos+j0lGBiF9r7na2d5WwI3XcnaVKtprC8Bt3e28P8Zofnmk0iQbAIBW8S5XhKgfE2TvBCqXl9fmKbbLpY1XqnpKQY/UtOTmb+JzR+jqcYsl0MaxuMHlEGIeNnhrTC5N4R8HV34bjUWoubqwL9YwzH2Xw6Q3Cb/67lILOoEpczS6DR6RmDFABUa/X45VgakwGmdYinYEZAeyKkKUVRFMpr1W7LquuWn0wpQH55DfZezTZ5zBqtnhHxcwZPKSH3dTqLWrCXmlnfULHn7z/YET5uLlg8xpC10Rk9b+5G+BkD6UfxwfiOzLLNpzOYbwNwnuelZsL3dGDbQNihqToHGEfEZgTffaDunkbYSS/PWejXMhA+bi7o08Ifg2KD0DbUC21DnVP/SIqnVE4pETyqL+xqQyaT4f0H676Hhki2QTAY8GnCG2myBdqrzpSnFD3x6IwIhTU5gxh4fdh4Mo3zmx2WlelEIfRNAZ1A2CqfhpDkMFsG3rjO8SUi2AurPKWioqJsXQ6Ck5Feq2kUy+r8y2QyfPhQZ3zwYCfIbVRRTe4dif3Xc7H5VAZeGhHL8XoB6sLfcsuqmZkrmQz4bW4/TPzmKP67lsMMyhyRtczXvTZ8j6UpVaXRM4YatqdUXq1QMj/Ujw+9nYtCBj93V5Pb2gohoxTj+ShglOoR5Y/vDqUYwvdqO3QNNRiIDfHC2TdGMO8gOxOKE7Sfdy2uSjknKxxtUJnSJwqZhZVYGZ9ktI8zzMIBXE8pNuzBijOF7/VrFYDED+6FQiazWV3srEQGuOPU68OZzjFFwWmvWZrQOcGWyGDQXnx9+yUAzmPobuqwvYuc2ZvIFK6MUcq4bmeMUk58bcJGKQcUxIbw537YfdNqLYnCsSVimcjZOEtbO6xtMPZdywFgGIv2buGPEwKeXYTGjWTXhmPHjkk+aEVFBS5fvmxVgQjOwa1ao5RQ1jpbVlL3tA1GqLcaBeU1+OcSN+Pb/9m777CmzjYM4HcGhA2yUQHFLe6BintUW612WFedtVWrdm+77G6t3V8dtdbRuuqutVbrHuDeeyKgMkT2Dsn7/RFySCBMIQl4/67LSzg5nLwHcpJznvM8z5ubp5VOfO6m5SAlS5c95GJngw6BtVC3ln3+7FiRAIBmfua/ey41OjcINKXlGH5tGJTSjb9wU/TC9P2kvJxUZvtAMNUcVh9cMBWU0pcMHY9MkspRzNnLw/D3YthTihcklmVYwmdYSlnca8NKzncK9ZQqeL2/ve6M9HVatnVNM2+jkFvNCWNVs1HIIZPpyoOteZ/L8h5oPaHN6sswG0QjhFGgr7pnilQXhkGp6vo7L1OmlBUHpexNlG5b8dtjmRSeWMcw0G+qzJIqriwz1llDphRQdKyc0KJmKvNV5NixYzFgwACsWbMGGRkZJte5cOEC3n33XTRo0ADHjx+vtEGS+elnfwus4tIQpUKOER39AQDLDxun7WYYBHTuphVkSrk52EAmk2FgSz8AQGr+xaJFMqXsC3pK6TMpMnIK7uYYZkrpp5TPUmuQrS7+jo++vMPLTP2kANMfTln5ZVameqAY3qG7Fq+fOtYyHxJGjc75OWVRhk23Df8Uhadtl9axkj+Yva3uNaTrKVXg/J1U6Wv2s6DSsHTM/P45EwNHVcH7S3HvNVS5cmtA71gbpe54NRmU0p9v2psnW70iDF/3Barfe9CIDv7S10UypRRyNPfTndt3q2YTMli7stxEsZZsdttC5/l9m/pYcDRUVcoclLpw4QIGDRqE999/H25ubggODsZDDz2EwYMHo1u3bvD09ES7du0QERGB//77D+PGjavKcVMV0mgFbiXqarfN0a9kZIg/5DLgSEQirsalScvTCwWlkqSglO4k4ZEWvkbbaWqBTCmX/KCUVgDpubrxGgai0nOKlu8BQGoJJXz6oJSPmfpJAaYbZupLmUyVLRkGoPT9ryw165HK4G4hZ+WwLMOm24YBpyfb1bXEcMpMH2Qt3FPK0qwkZkdlZK6+emTMzkaBv1/ohk0vdIVjNZwJrjoyVfJW3dhU8/K9Ho29iiyrjp8ZHz8WLH1d+HRTLpfh1/Ed8MOINpjaq6GZR1azlSVTSmElL6jCE1gMauVnoZFQVSrzGZSNjQ1eeuklXL58GQcPHsSkSZPQokUL1KlTB7169cIvv/yCO3fuYOXKlWjZsmVVjpmqWGxqNnI1WtgoZKjtVvUNLP1c7dG3mS7qbZgtZRSUSs+RZrjTZye18XdDbVddNpGnkwqeTuYL4ujZ2SikgI7+zpph+Z7hPuiDN4BxuR8ARN7LQFL+4/H55XveLubbH1O9CfRBqdJmiwq/lgDAclkChn3IrOSmzgPL8HVk+Lew5hN7oCAoG5+WYzT7HlF5sKTAclrWdUWrum4s4TaTmlBKZVvNy/ecTGRKVcfXv52NQgqQmJpQpI6bPR5vW6fIDL90f8ryeVV4hj5LsSmUKVUdX+dUugrlOXfo0AEdOnSo7LGQlYi6pyvdq1vLwWypm6M7BWD7hThsOHkbMwc3h0wmK5IppT9JqJXfx0kmk+HhFn5YFBZhkX5Sem4ONshK0SA5Uw1/9+LL9xIMZl0y7Ct14U4qHp8ThqZ+ztj0QjfEp+ozpcxXvmcqy0lfvmfYU0o/G6DhycG/+b3A1BY6SXWxKzhptJZysAeVUSmlQdaaQi6DrVJutRcyhmUQhsevIX0AnKg4zJSyPH4GmIe5JmGpSvrzHlOl2cn5PUytOShlstG5BcZRGWwVuvODE5FJlh7KA0NVnXpKKYzPLQtnTlHNwOJ7KiIqUdczzJxTjYc28IRcprs7dTc9B97OdibK9/IzpQxOhqb0DEJsahbGd6lntrEW5mpvg5iUbOkkJt1Eo3MhBBIMM6UyC77+YccV5Gq0OHMrBZm5eYhLM3+mlCn6DCnDoNQPI9oAgFTjb+hOSrZZxlVYgIcDJnWvD0eV0mrq3x9UKoOT5MLXhvqTTmvkbVAqG59m+nU8e1hrcw2Hqin2lLI8fgSYx3Pd6+NKXBoeaelb+spWSp8pUviGWk6eBtlq3TJXB+sNSinkMrz2UGPsvBSP09HJAKpn+R6QX0qWAziqmA1lLraK0n/XCiu50VK4d6yrgw36N/fBfxfi8PvEEAuOjCoTg1JUhLmanBuyVcrh62KHOynZiE7M0gWlDLKMEjNykJhR9M6Vj4sd5o5ub7ZxmiLNwJef/WTUUyr/67ScPKMLcn353rnbKfjvQpy0/Hp8hpQp5W3GTClTNFrdePXBKVd7G4TmN5o0dTe6Y71a5htcIe8Nam6x56YCJTWdLxwwHBBsPY0qZTIZPJ1USEjPQWau6UypDhZ4fVfT64sHVuGMU05bbX4s6zAPR5USc0a3s/Qw7ktxPaX0WfkyGeBsspm49XipbyOM7RyItp9uB1C0UXh1oQ8Q5ljpjauaSN/ovyTW0lPKxihTSmfBOFZs1TTWEQIlqxKZX74XYMagFADUzX++W0m65zfMlNIK4PpdXQZXLSu7c6WfnUUfaEo3KP/JUmuQp9HiXnqu0c/o+0/9vOua0fKr8WlSpoalM6X0Ge36TKnSspBYNkEqo9n3jF8PKSU097cG0gx8xQSl2ESfSlP4PbIs5RFUuazkxj5VA/o+RoV7SuknonGxs4G8GqTeGWZomurJVB3o/xY5am2RZVQ1ylICZy3Zv8az71nHmKjy8YinIvSZUgEe5g1K+dfSPV90/vNnGASlAEgz87lZWS8DfaZUSmbR8j1A16PGcOY9oKBfwfEoXf18izq6criLMalSQ3RzZ0p1qu8OoGAGNX0wKi8/Y6rwBVfhc7UhrWtX8QjJ2hnPvlfyutY2k44+oKZv8F9YNbg2IQsr3Dh2Uvcg6Wt3R93n1tB2dcw6pgcNM6WorPQX5dmF3vOTpZmeresGaHEML9ittUS+NKY+f6vrvlQXKhM9yQqzlpYYvMHzYLDuvFSyCKl8z9xBKXfdTH/RiVkAgLRs46BUUv6JgrXV+LuWUL4H6Gbju1c4KJWphhBCypjq2tAT526nIvz6PQih+yDwcDRv8G3lpM5Iz83DsHkHcTkuDdr8O275MakiDQ+VhXoEjekcaLaxknUynn2v+JOZZ7rWQxt/NzOMqOz0FyjFnQjzYpdKY9jo/M0BTdCjsReOvd8PNnI5nO2USM/NM5qYgSofj1MqK7v8CVsKB6Wqw8x7hgwzXqprIEc/A65hprK1nSPUNHZlCPRYS/me4eRK1jEiqgplDkr99NNPZd7oSy+9VKHBkOWlZKml4Io+c8lcpEypJNOZUnrWNutL4fK9tELjTs/JQ0Kh8r3kLDWy1Vpp1peOge74BTdwISYVAODlpDJ72rhcLjNKV88rJVPKRi6Dfq9c7BjfpsKz7xXP08mypamm6O82xxTTsN8S52ZMU69eTJU6GL7WGZCqejxkqKz0gRB9awhANynN3D3XAVSfoJTh50ThAFt1of9bZKoLzp9Zvle1lGUo37OWTCmjmSatY0hUBcp8Jfn9998bfX/37l1kZmbCzc0NAJCcnAwHBwd4e3szKFWN6UvnPJ1URtOkm4N+tr9oEz2lDLlZ2YmC/sRFH8wrHExLz86TyvfsbRTIUmuQkqmWSviUchla+bsCKGhSacl+UvqMKG2h2feKNqr2xfqTtwEAQ9qwdI+AugaB7JIuDguXOVmD0vorMEBEpck06CfIl4tlMFOKykqfVRSTkiUt23Y+DscjdW0VXKzsXLMsarvZW3oIFaLPWjN8D+3awNNSw6F81tJTyvB93TpGRFWhzFGHiIgI6esVK1Zg7ty5+O2339CkSRMAwOXLlzFp0iRMmTKl8kdJZlPL0Rav9mtskRNqffleTHI28jRaKeNIH8iRxmhtmVL6nlJZ+p5Shcv38qRG5w28HXHudiqSs3KNUsS9nFRwc7CRAluWnHlPnymlKSUo9fFjwajlaAshgBf7WFd/ILKMMZ0DICDQso5rkSDOS30b4aedVwEUnaXMGvCuLN2vurUKLgjZGN8yGJSisqqX36LC8PPo/J0U6WtruwFaknVTuyAqMRMt6rhaeigVYp/fj1I/+62jrQJTezWw5JAeCKundEFMShbO3krBwgMRRR63lkypxj5O0te8QVhzVSgV5oMPPsDatWulgBQANGnSBN9//z2eeuopjB49utIGSOZVx80eL/drZJHn9nG2g61CjlyNFrGp2VLGUT1PR1zML2uTyQBnKysVc7MvuaeUYaZUAy8nXVAqUy31k3K1t4FMJkMjbyccvam7Q2cNmVL6WVz0QanCPaWc7WzwwaPNzTs4smrOdjaYVkwD8x6NPBmUohrNKCjF82aLsJJrKKoG9Nn5Rs21DWbiqy7lewDQPtAd7QPdLT2MCpN6SuX/LcaH1uNnshmE5E9w5OWsMh2UspIPMgf2lHogVOiIj4mJQV5e0dIqjUaDuLi4+x4UPZjkchnq5J/UR93LlII79T0LSoJc7a1vil6p0Xl+5pM+U0ofPEs3yJRq6KWL9uvK94wbtzf0dpa26WPJTKn8X+/p6GQABb2leAea7odhTwBr7HthjSWF1jciKonhZOz821mGk5XdtCLrpW+ebNhc27BReHUKSlV3ho2sAZ5vmpt9MTPxWcu5mq2i9JkCqfqrUFCqb9++mDJlCk6cOCEtO378OKZOnYp+/fpV2uDowdPMTxeYORmdLAV36ns6So9bW+keALjljyklf0Y9/bj9XHWBJaNMKW9dUCotJw+JGbpAlf7Ep5F3QXqqJTOlYlN1jZ71PcWkTCkrvGin6qOJb0HQNbaYZuKWZKs0fdLTv7kPJoTWM+9gqFoybJIvSliPqs5LfRqhbYAbPnu8haWHQlZOfyFueOHNoJRl2BUKijAmZV6Fg4J6hSdpshQbpUFPKb42aqwKBaUWLVoEX19fdOjQASqVCiqVCiEhIfDx8cHChQsre4z0AAmpp0slPXTjnhTcqedREJSyxpMEfflerkaLLLVGyvDyddVlfaXlFASlgrwK9iUqv6m8FJQyqJn2sWBQqldjbwBATv7JWUFPKaZSU8UZluzps++sSXGNzheM64CPhgSbeTRUHRlm22ms8DX+IKjlaIsN07piTOdASw+FrFxBUKogEGUYlNL3C6WqVzhTh32DzMvw99/a3036WljJ7ZXSJqKhmqFCec5eXl7YsmULrly5gkuXLgEAmjZtisaNG1fq4OjB0ynIAwBwPDJJarBnGMixxpMEB1sFbBQyqDUCiRm5yMhPBfdz0WVKJWbkIDU/UOXjbAdnOyXSsvMQeU83DbE+qNXYpyCTxJKNzvXBg592XsXgVn5SAKFwTymiirLGC3ZbJV/fdH+UBoF7rRW+xomogCr/QvxyXBr2X72L7o28oDboKVUdZ9+rrgoHpXi6aV6Gv3/Doghr+RizMegvlqexkkFRpbuv0GPjxo0xZMgQDBkyhAEpqhRNfJzham+DzFwN0rL1ZXD2UsNDayzfk8lkcLXXjetOckH5hk9++V7kPV1GlFIug6u9jRRY0y/XZ0p5O6sQ4O4AB1sFAjwK+miZm2Fzyc/+uViQKcU7V3Sf9CWqg1vXtvBIitKX0xqys7Hs3TkectWL4XunfqIIIrJOhhfi05fr2pEYZvFaY2Z+TaU/X9bj7KXmZWdQvmcY87GWjzHDTCnDyQioZqlwR8hbt25h06ZNiIqKQm6u8cn8d999d98DoweTXC5Dx3ru2HGxoGG+k50SXk4q3E7OstqTBDcHGySk5+BWUkEAytNJF6i6mZ8R5e5oC7lcBjd7W0QjC1H5QSn93TiZTIYN00KRpdbAxc5y+2l4YXUhJhV5Wt0HgLVMDUvV16YXuuFOShYaeDmVvrKZdWvoiW3nC953nu1W32IzkVL1ZFi+x0wpIutm2EdHn81uWDbmZoU3QWuqR1v54a21Z6TvebppXnYGPTXVBiWs1li+p2ZQqsaqUFBq586dGDJkCIKCgnDp0iW0aNECN2/ehBAC7dq1q+wx0gOmc5BxUMrRVglvF11QyhozpYCCErzbSVkAdIE0/ex7+mWeTro+UfpMqbT8nlmGJz4eTpbrJaVna3BhlafRQivY6Jwqh72twioDUkBBY3+9QA8HiwaHqfox7LvHTCki62ZqxrHcvIKm59Z6E7QmUhWaaMTaZtmu6QxvqBhmIlnLx5jh6yEuNceCI6GqVKHahBkzZuCNN97A2bNnYWdnh3Xr1iE6Oho9e/bEsGHDKnuM9IAJqe8ufe1gq4BCLpNmsvN0ttKgVH6gSd+83NFWCSeVbpn+hrlHfuZU4RMdazvxsS1Uu62v32amFNVkhS9Q/PInKiAqq7q1Cl4zvJlrHt7Olr+RQ9WTk13R+/KGs7A6FjMjGVU+hVzGc0wLMswQNMxECrRgKxF68FQoU+rixYtYuXKlbgNKJbKysuDk5IRPPvkEjz32GKZOnVqpg6QHS3M/FziplEjPyYNTfvbCi30aoW4tBzza0vp60QAFWVD6PlHOdkpp7HpehTKl9KwuKGWQJitQ0JSajc6pJrMrdAHSu4mXhUZSgDMQVS/9m/tIX2ut5RZzDffeoGaWHgJVU4XP0YCCwLKXs4rvv2Zmo5BJ55ty/u4tRisEVkzqhPBr9zCig7+lh0MPkAoFpRwdHaU+Un5+frh+/TqCg3VTZickJFTe6OiBpFTI0T6wFvZeuSudNDTzc0EzPxcLj6x4+qBURH7/KCdVQfmenj5Tys3eONvL2oJShrNcaIWQGn/yLhbVZEVn/+HrncrH8CLWGmeYrIk4QxpVJn0s+TErnIyjprNVyJGt1mXp8HTTcoQAQht4IrSBp6WHQg+YCgWlOnfujAMHDqBZs2YYOHAgXn/9dZw9exbr169H586dK3uM9ADqFOSuC0qZSK+2Rl75JQR303S1zo6qoplShXtK6RX+3tIMM6W0QhhkSll2JjKiqlQ4KMWYFN0PBqXMg4cpVRaNVkDkR6X4/m9++mbzAKykvfaDiUm+ZCkVusr87rvv0KlTJwDAxx9/jL59++LPP/9EvXr18Ntvv1XqAOnB9GjL2vB0UqFPU29LD6VMvAr1tXCyUxYJqOmbmFt7TymVwcW5i50NM6XogWBvWzgoxdc7VRzL98yDxyndj471aklf307KkoIhfF1Z1r10NrO2FL70yVIqlIYSFBQkfe3o6Ij58+dX2oCIACDAwwFH3+tbbU4MCgelnE1mSuWX7xnMtmerlMPOxAwwlmRnUL7nZKeERqtLp2ZPKarJTM3ERFRRzJQyD34q0f14uW9jjPntMABAQECrZaaUNeDnseUYVksQmVOFX3nJyclYuHAhZsyYgcTERADAiRMncPv27TJv46OPPoJMJjP617RpU+nx2NhYjB07Fr6+vnB0dES7du2wbt26Erf55ZdfomPHjnB2doa3tzcef/xxXL58uWI7SRZVXQJSQEFpnp6jSgmVUm40zaqp8j03K8uSAgAbww8kAWZK0QPB2oLDVL0xU4rI+qm1BTON5eZpCzKlGO60qMITj5D5KBV87ZNlVCgodebMGTRu3BizZs3CN998g+TkZADA+vXrMWPGjHJtKzg4GDExMdK/AwcOSI+NGzcOly9fxqZNm3D27Fk8+eSTGD58OE6ePFns9vbu3Yvp06fj0KFD2L59O9RqNfr374+MjIyK7CpRmRQp31MpIZPJjLKlpKCUQSDK2kr3AOMPJK0Q0GhEkeVENU3hiQmI7gczpcyjgbeTpYdA1VhDr4LXT7ZaK/XT4T04y2K2jvm1D9SVsj4c7GvhkZhmq+Rroqar0Fn4a6+9hgkTJuDrr7+Gs7OztHzgwIF4+umnyzcApRK+vqYPgPDwcMybNw8hISEAgPfffx/ff/89jh8/jrZt25r8ma1btxp9v2TJEnh7e+P48ePo0aNHucZGVFaOtgrY2yiQpdYAKLjAdbJTIilTDQBwd9SV7bk6WHlQSm7Y6JyZUvRgsLNRwMPRFvcyci09FKoBNNrS16GK2/1GLyRn5qKOm72lh0LVmL+7g/R1llojZThWo0T9GsmGQSmzmze6HY5FJlltL9/TH/bHt/9dxvjQepYeClWRCh31R48exZQpU4osr1OnDmJjY8u1ratXr6J27doICgrC6NGjERUVJT0WGhqKP//8E4mJidBqtVi1ahWys7PRq1evMm8/JSUFAODu7l6ucRGVh0wmM8qW0mdIOdrq/ne1t5Gi/IaBKGubeQ+AUckhZ9+jB0nbADdLD4FqCJbvVa36no5oG1Cr9BWJStHczwUApJuKAMv3LI03Qc3P28UOA1v6WW0rA3tbBd5/tLlRIJlqlgpdZapUKqSmphZZfuXKFXh5eZV5O506dcKSJUuwdetWzJs3DxEREejevTvS0tIAAKtXr4ZarYaHhwdUKhWmTJmCDRs2oGHDhmXavlarxSuvvIKuXbuiRYsWxa6Xk5OD1NRUo39E5WUYlHLMD0rpM6Y8nAqam6uUCjjk18u7WGGmlGHQLE8jmClFDwy+xqmy+LnaWXoIRFQG+plXs3ILMqX4UWBZngbnzET0YKhQUGrIkCH45JNPoFbrypJkMhmioqLw9ttvY+jQoWXeziOPPIJhw4ahVatWGDBgALZs2YLk5GSsXr0aAPDBBx8gOTkZO3bswLFjx/Daa69h+PDhOHv2bJm2P336dJw7dw6rVq0qcb0vv/wSrq6u0j9/f/8y7wORnuGHqJO+fC8/OFW4Ebq+r5Q1lu818nFG3/z03ey8gpM0zr5HNZ1KaZ13CKn6+PnpthjY0hcTu9W39FCIqAz02eFqTUFPKdbvmd+qyZ2lr/s3t86+RkRUdSoUlPr222+Rnp4Ob29vZGVloWfPnmjYsCGcnZ3x+eefV3gwbm5uaNy4Ma5du4br16/j559/xqJFi9C3b1+0bt0aM2fORIcOHTBnzpxSt/XCCy9g8+bN2L17N+rWrVviujNmzEBKSor0Lzo6usL7QA8uw0wpZ5W+p5Qu6FT4ro+rQ35/KSsMSgHAR0OCAQDZag3yNMyUogdDs/wyDqKKerRVbcwd3b7IjQgisk76/kV5Wi0EmCllKZ2DPHDzq0G4+dUgyPkHIHrgVKjRuaurK7Zv344DBw7gzJkzSE9PR7t27dCvX7/7Gkx6ejquX7+OsWPHIjMzEwAgL9THRqFQQKstvoOoEAIvvvgiNmzYgD179qB+/dLvVqpUKqhUPIGk++PlVFCuoS/fKy1Tys1Kg1L6dPZstRZ7r8QDYKYU1Xx2NuybRkT0IDl4/R4A4NU/T+PpTgEA2FOKiMjc7msO7G7duqFbt24V/vk33ngDgwcPRmBgIO7cuYOZM2dCoVBg1KhRcHNzQ8OGDTFlyhR888038PDwwMaNG7F9+3Zs3rxZ2kbfvn3xxBNP4IUXXgCgK9lbsWIF/vrrLzg7O0uN111dXWFvz1laqOqYanTeLsANq45GoUM940b7HevVwtGbiWjt72bOIZaZYaNDD0cVrt/NQGp2ngVHRFT1rLXBJxERVQ1930wAUvkeq/eIiMyrwkGpnTt3YufOnYiPjy+SubRo0aIybePWrVsYNWoU7t27By8vL3Tr1g2HDh2SmqVv2bIF77zzDgYPHoz09HQ0bNgQS5cuxcCBA6VtXL9+HQkJCdL38+bNA4AiM/QtXrwYEyZMqMCeEpWNYYmevsH5sA7+GNjST8qc0nutfxNM6dmgyHJrYTgDX3aebkYazkxGNR0zpYiIHlyCjc6JiCyiQlfEH3/8MT755BN06NABfn5+kFXwlkJpDcgbNWqEdevWlbjOzZs3jb4XnIaZLMTU7HuFvzZkrQEpALAxKJvNzp8mWc5bh1TDsdE5EdGDKyv/fKei1zVERFQxFboqnj9/PpYsWYKxY8dW9niIqq06tewhl+mal+sbZ1ZXcrkMSrkMeVqBbLUuE5I9paima+jtZOkhEBGRhfx16g4Alu8REZlbhYJSubm5CA0NreyxEFVr3s52mD+mPWo52pa+cjWgVOiDUvmZUgxKUQ3X2McZ88e0g7eLXekrExFRtbflpe4Y+NN+o2VsdE5EZF4VSud47rnnsGLFisoeC1G11z/YFx0LNTWvrvTZXkmZuQAABW8d0gPg4RZ+aBdQy9LDICIiM2jg7VhkGU93iIjMq8yZUq+99pr0tVarxYIFC7Bjxw60atUKNjbG09p/9913lTdCIrII2/yglFqj69Om77VAREREVBPYmmi3wMRwIiLzKnNQ6uTJk0bft2nTBgBw7tw5o+VsDkhUMxTui3U1Ls1CIyEiIiKqfKauW1i+R0RkXmUOSu3evbsqx0FEVsZGaXxSptZyZksiIiKqWT58tDk+2XxB+p7314mIzKt6TxFGRFWmcKaUhkEpIiIiqmGUCuMoFKs+iIjMi0EpIjKpcJ+Ffs18LDQSIiIioqqhKNREiiEpIiLzYlCKiEwqnCnV2MfJQiMhIiIiqhryQplRbHRORGReDEoRkUk2TGcnIiKiBwzPd4iIzItBKSIyqXCmFM/RiIiIqKap42Zv9D0zpYiIzItBKSIyyVZp/PZQOL2diIiIqLrr3sjTeAHPd4iIzIpBKSIyqXCmFO8cEhERUU1TuFyPpztERObFoBQRmVS4pxQzpYiIiKimE5YeABHRA4ZBKSIyKTEj1+h7xqSIiIiopotLybb0EIiIHigMShGRST0bexl9z0wpIiIiIiIiqkwMShGRSXY2CqPvGZQiIiKimi5Xo7X0EIiIHigMShGRSfa2hYNSFhoIERERkZnk5jEoRURkTgxKEZFJ9oUypQrPTkNERERU02gFW50TEZkTg1JEZFLhoBQRERFRTcegFBGReTEoRUQm2dkyKEVEREQPFi1jUkREZsWgFBGZxEwpIiIiehDMebqd9LVgphQRkVkxKEVEJhWefY+IiIioJhrUyk/6Wss+50REZsWgFBGZxEwpIiIietCwpxQRkXkxKEVEJjEoRURERA8ahqSIiMyLQSkiMsnOlm8PRERE9GDRstM5EZFZ8aqTiExiphQRERE9aFi+R0RkXgxKEZFJhkEpL2eVBUdCREREZB6dgjwsPQQiogeK0tIDICLrpFTIseSZjlgcdhNfPtnS0sMhIiIiqjL73+qN45FJGNy6tqWHQkT0QGFQioiK1auJN3o18bb0MIiIiIiqlL+7A/zdHSw9DCKiBw7L94iIiIiIiIiIyOwYlCIiIiIiIiIiIrNjUIqIiIiIiIiIiMyOQSkiIiIiIiIiIjI7BqWIiIiIiIiIiMjsGJQiIiIiIiIiIiKzY1CKiIiIiIiIiIjMjkEpIiIiIiIiIiIyOwaliIiIiIiIiIjI7BiUIiIiIiIiIiIis2NQioiIiIiIiIiIzI5BKSIiIiIiIiIiMjsGpYiIiIiIiIiIyOwYlCIiIiIiIiIiIrNjUIqIiIiIiIiIiMyOQSkiIiIiIiIiIjI7BqWIiIiIiIiIiMjsGJQiIiIiIiIiIiKzY1CKiIiIiIiIiIjMjkEpIiIiIiIiIiIyOwaliIiIiIiIiIjI7BiUIiIislI9GnvBy1mFLkGelh4KEREREVGlkwkhhKUHYW1SU1Ph6uqKlJQUuLi4WHo4RET0gBJCQKMVUCp4D4mIiIiIah6lpQdAREREpslkMigVMksPg4iIiIioSvDWKxERERERERERmR2DUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdZ9+rREIIpKWlWXoYREREREREREQW5+zsDJms+NmkGZSqRGlpaXB1dbX0MIiIiIiIiIiILC4lJQUuLi7FPi4TQggzjqda0Gc8lRbRK+7nyPqlpqbC398f0dHRJR4gRGQ9eNwSVT88bomqHx63RNWPNR+3zJSqAJlMVqE/ZEV/jizHxcWFfzOiaobHLVH1w+OWqPrhcUtU/VTH45aNzomIiIiIiIiIyOwYlCIiIiIiIiIiIrNjUIoeSCqVCjNnzoRKpbL0UIiojHjcElU/PG6Jqh8et0TVT3U+btnonIiIiIiIiIiIzI6ZUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdg1JUbX355Zfo2LEjnJ2d4e3tjccffxyXL182Wic7OxvTp0+Hh4cHnJycMHToUMTFxRmtExUVhUGDBsHBwQHe3t548803kZeXJz2+Z88eyGSyIv9iY2PNsp9ENUllHbcvvfQS2rdvD5VKhTZt2ph8rjNnzqB79+6ws7ODv78/vv7666raLaIay1zH7M2bN01+1h46dKgqd4+oRqqM4/b06dMYNWoU/P39YW9vj2bNmuHHH38s8lx79uxBu3btoFKp0LBhQyxZsqSqd4+oRjLXcWuN17YMSlG1tXfvXkyfPh2HDh3C9u3boVar0b9/f2RkZEjrvPrqq/j777+xZs0a7N27F3fu3MGTTz4pPa7RaDBo0CDk5uYiPDwcS5cuxZIlS/Dhhx8Web7Lly8jJiZG+uft7W2W/SSqSSrjuNWbOHEiRowYYfJ5UlNT0b9/fwQGBuL48eOYPXs2PvroIyxYsKDK9o2oJjLXMau3Y8cOo8/a9u3bV/o+EdV0lXHcHj9+HN7e3li2bBnOnz+P9957DzNmzMDPP/8srRMREYFBgwahd+/eOHXqFF555RU899xz2LZtm1n3l6gmMNdxq2dV17aCqIaIj48XAMTevXuFEEIkJycLGxsbsWbNGmmdixcvCgDi4MGDQgghtmzZIuRyuYiNjZXWmTdvnnBxcRE5OTlCCCF2794tAIikpCTz7QzRA6Iix62hmTNnitatWxdZPnfuXFGrVi3pOBZCiLfffls0adKk8neC6AFSVcdsRESEACBOnjxZVUMnemDd73GrN23aNNG7d2/p+7feeksEBwcbrTNixAgxYMCASt4DogdPVR231nhty0wpqjFSUlIAAO7u7gB0kWK1Wo1+/fpJ6zRt2hQBAQE4ePAgAODgwYNo2bIlfHx8pHUGDBiA1NRUnD9/3mj7bdq0gZ+fHx566CGEhYVV9e4QPRAqctyWxcGDB9GjRw/Y2tpKywYMGIDLly8jKSmpkkZP9OCpqmNWb8iQIfD29ka3bt2wadOmyhk00QOuso7blJQUaRuA7rPWcBuA7rO2Isc+ERmrquNWz5qubRmUohpBq9XilVdeQdeuXdGiRQsAQGxsLGxtbeHm5ma0ro+Pj1QzGxsbaxSQ0j+ufwwA/Pz8MH/+fKxbtw7r1q2Dv78/evXqhRMnTlTxXhHVbBU9bsuiLMc2EZVPVR6zTk5O+Pbbb7FmzRr8888/6NatGx5//HEGpojuU2Udt+Hh4fjzzz8xefJkaVlxn7WpqanIysqq3B0heoBU5XFrjde2Sos9M1Elmj59Os6dO4cDBw5U+rabNGmCJk2aSN+Hhobi+vXr+P777/HHH39U+vMRPSiq8rglospXlcesp6cnXnvtNen7jh074s6dO5g9ezaGDBlS6c9H9KCojOP23LlzeOyxxzBz5kz079+/EkdHRKZU5XFrjde2zJSiau+FF17A5s2bsXv3btStW1da7uvri9zcXCQnJxutHxcXB19fX2mdwjME6b/Xr2NKSEgIrl27Vkl7QPTguZ/jtiwqemwTkWlVfcya0qlTJ37WEt2HyjhuL1y4gL59+2Ly5Ml4//33jR4r7rPWxcUF9vb2lbszRA+Iqj5uTbH0tS2DUlRtCSHwwgsvYMOGDdi1axfq169v9Hj79u1hY2ODnTt3SssuX76MqKgodOnSBQDQpUsXnD17FvHx8dI627dvh4uLC5o3b17sc586dQp+fn6VvEdENV9lHLdl0aVLF+zbtw9qtVpatn37djRp0gS1atW6/x0hekCY65g1hZ+1RBVTWcft+fPn0bt3b4wfPx6ff/55kefp0qWL0TYA3Wft/R77RA8icx23plj889aibdaJ7sPUqVOFq6ur2LNnj4iJiZH+ZWZmSus8//zzIiAgQOzatUscO3ZMdOnSRXTp0kV6PC8vT7Ro0UL0799fnDp1SmzdulV4eXmJGTNmSOt8//33YuPGjeLq1avi7Nmz4uWXXxZyuVzs2LHDrPtLVBNUxnErhBBXr14VJ0+eFFOmTBGNGzcWJ0+eFCdPnpRm20tOThY+Pj5i7Nix4ty5c2LVqlXCwcFB/PLLL2bdX6LqzlzH7JIlS8SKFSvExYsXxcWLF8Xnn38u5HK5WLRokVn3l6gmqIzj9uzZs8LLy0uMGTPGaBvx8fHSOjdu3BAODg7izTffFBcvXhRz5swRCoVCbN261az7S1QTmOu4tcZrWwalqNoCYPLf4sWLpXWysrLEtGnTRK1atYSDg4N44oknRExMjNF2bt68KR555BFhb28vPD09xeuvvy7UarX0+KxZs0SDBg2EnZ2dcHd3F7169RK7du0y124S1SiVddz27NnT5HYiIiKkdU6fPi26desmVCqVqFOnjvjqq6/MtJdENYe5jtklS5aIZs2aCQcHB+Hi4iJCQkKMpr0morKrjON25syZJrcRGBho9Fy7d+8Wbdq0Eba2tiIoKMjoOYio7Mx13Frjta1MCCEqO/uKiIiIiIiIiIioJOwpRUREREREREREZsegFBERERERERERmR2DUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdg1JERERERERERGR2DEoREREREREREZHZMShFRERERERERERmx6AUERERERERERGZHYNSRERERERERERkdgxKERERERERERGR2TEoRUREREREREREZsegFBERERERERERmR2DUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdg1JERERERERERGR2DEoREREREREREZHZMShFRERERERERERmx6AUERERERERERGZHYNSRERERERERERkdgxKERERERERERGR2TEoRUREREREREREZsegFBERERERERERmR2DUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdg1JERERERERERGR2DEoREREREREREZHZMShFRERERERERERmx6AUERERERERERGZHYNSRERERERERERkdgxKERERERERERGR2TEoRUREREREREREZsegFBERERERERERmR2DUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdg1JERERERERERGR2DEoREREREREREZHZMShFRERERERERERmx6AUERERERERERGZHYNSRERERERERERkdgxKERERERERERGR2TEoRUREREREREREZsegFBERERERERERmR2DUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdg1JERERERERERGR2DEoREREREREREZHZMShFRERERERERERmx6AUERERERERERGZHYNSRERERERERERkdgxKERERERERERGR2TEoRUREREREREREZsegFBERERERERERmR2DUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdg1JERERERERERGR2DEoREREREREREZHZMShFRERERERERERmx6AUERERERERERGZHYNSRERERERERERkdgxKERER0QNt27Zt+Oyzz5Cbm2vpoVAV0Gq1mD17NtavX2/poRAREVEhDEoRERFRqWQyGV544QVLD0Ny8+ZNyGQyLFmy5L631aZNG8ydOxefffbZ/Q+MrI5cLoePjw+efvppXLx40dLDISIiIgMMShEREVWC1atXQyaTYcOGDUUea926NWQyGXbv3l3ksYCAAISGhpbruebOnVspwRjS8fHxwcqVKzF79mycOXOmyOP6AJj+n0KhQEBAAJ544gmcOnWqQs9Znr/hhAkTjJ7f1L969eoBAKZNmwa5XI7ExESjbSQmJkIul0OlUiE7O9vosRs3bkAmk+Hdd981Wp6cnAw7OzvIZLJigzmFx+bi4oLWrVvj22+/RU5OjrTezp07MXHiRDRu3BgODg4ICgrCc889h5iYGJPbDQ8PR7du3eDg4ABfX1+89NJLSE9PN1pnz549xf4+Dh06ZLTuuHHjMGbMGDz77LPQarXF/7KroczMTMyZMwf9+/eHn58fnJ2d0bZtW8ybNw8ajabI+lqtFl9//TXq168POzs7tGrVCitXriyy3pEjRzBt2jS0b98eNjY2kMlkxY5h3rx5GDZsGAICAiCTyTBhwoTK3EUiIqrBlJYeABERUU3QrVs3AMCBAwfwxBNPSMtTU1Nx7tw5KJVKhIWFoXfv3tJj0dHRiI6OxsiRI8v1XHPnzoWnpycv/CpRz5498eGHH2LixIk4fPgwFApFkXVGjRqFgQMHQqPR4OLFi5g3bx7+/fdfHDp0CG3atCnX85XnbzhlyhT069fP5GM7d+7EkiVL0LlzZwC61+G8efMQFhaGwYMHS+uFh4dDLpdDrVbj2LFj0usVAMLCwqSfNbRmzRrIZDL4+vpi+fLlxWaSqVQqLFy4EIAukLVu3Tq88cYbOHr0KFatWgUAePvtt5GYmIhhw4ahUaNGuHHjBn7++Wds3rwZp06dgq+vr7S9U6dOoW/fvmjWrBm+++473Lp1C9988w2uXr2Kf//9t8jzv/TSS+jYsaPRsoYNGxZZ7+eff0bnzp3x008/4ZVXXjG5L9XRjRs38OKLL6Jv37547bXX4OLigm3btmHatGk4dOgQli5darT+e++9h6+++gqTJk1Cx44d8ddff+Hpp5+GTCYzei/asmULFi5ciFatWiEoKAhXrlwpdgyzZs1CWloaQkJCig00EhERmSSIiIioUtSvX1+EhIQYLdu6dauQyWRi1KhRYsCAAUaPrVixQgAQf/31V7meJzg4WPTs2fN+h2tErVaLnJycYh8HIKZPn16pz3k/IiIiBACxePFisz3X7NmzjZZv2rRJABCTJ08u9zYr4294584d4eXlJQIDA0ViYqIQQojIyEgBQLz11ltG677zzjuibdu2omnTpuLLL780emzy5MlCLpeLpKQko+U9evQQTz75pHj11VdF/fr1TY5h/PjxwtHR0WiZRqMRHTp0EADE7du3hRBC7N27V2g0GqP19u7dKwCI9957z2j5I488Ivz8/ERKSoq07NdffxUAxLZt26Rlu3fvFgDEmjVrivsV1RglHZ93794V586dK7L8mWeeEQDE1atXpWW3bt0SNjY2RseyVqsV3bt3F3Xr1hV5eXnS8tjYWJGZmSmEEGL69OmipMuGmzdvCq1WK4QQwtHRUYwfP75c+0dERA8ulu8RERFVkm7duuHkyZPIysqSloWFhSE4OBiPPPIIDh06ZFQ6FBYWBplMhq5duwIAFi9ejD59+sDb2xsqlQrNmzfHvHnzjJ6jXr16OH/+PPbu3SuVKvXq1Ut6PDk5Ga+88gr8/f2hUqnQsGFDzJo1y+h59eVo33zzDX744Qc0aNAAKpUKFy5cKHUfN27ciBYtWkClUiE4OBhbt24tss7t27cxceJE+Pj4SOstWrTIaJ3c3Fx8+OGHaN++PVxdXeHo6Iju3bubLHFMTk7GhAkT4OrqCjc3N4wfPx7JyclF1ouNjcUzzzyDunXrQqVSwc/PD4899hhu3rxZ6n5VRJ8+fQAAERERAICPPvrIZInTkiVLIJPJpHGU9jcsC61Wi9GjRyMpKQkrVqxArVq1AOjKQf39/aXsJ72wsDB07doVoaGhJh8LDg6Gm5ubtCwqKgr79+/HyJEjMXLkSERERCA8PLxMY5PL5dL+6Pe5R48ekMuNTzt79OgBd3d3o9LA1NRUbN++HWPGjIGLi4u0fNy4cXBycsLq1atNPmdaWhry8vLKNL6y0Jc0fv/990UeCw8Ph0wmMyp5q8zXfHmPT09PTwQHBxdZrs/YNPz9/vXXX1Cr1Zg2bZq0TCaTYerUqbh16xYOHjwoLffx8YG9vX1JvyZJYGBgieV9RERExWH5HhERUSXp1q0b/vjjDxw+fFi6KA8LC0NoaChCQ0ORkpKCc+fOoVWrVtJjTZs2hYeHBwBdX5bg4GAMGTIESqUSf//9N6ZNmwatVovp06cDAH744Qe8+OKLcHJywnvvvQdAd/EI6HrL9OzZE7dv38aUKVMQEBCA8PBwzJgxAzExMfjhhx+Mxrt48WJkZ2dj8uTJUKlUcHd3L3H/Dhw4gPXr12PatGlwdnbGTz/9hKFDhyIqKkrah7i4OHTu3FlqjO7l5YV///0Xzz77LFJTU6WyqdTUVCxcuBCjRo3CpEmTkJaWht9++w0DBgzAkSNHpHI4IQQee+wxHDhwAM8//zyaNWuGDRs2YPz48UXGN3ToUJw/fx4vvvgi6tWrh/j4eGzfvh1RUVFSz6XKdP36dQCQ9r2sSvobltWnn36K3bt34/PPPy/Sk6xbt25Yv349cnJyoFKpkJubi6NHj2Lq1KnIzMzEW2+9BSEEZDIZkpKScOHCBTz//PNG21i5ciUcHR3x6KOPwt7eHg0aNMDy5cvL3P+sLL+b9PR0pKenw9PTU1p29uxZ5OXloUOHDkbr2traok2bNjh58mSR7TzzzDNIT0+HQqFA9+7dMXv27CI/X15BQUHo2rUrli9fjldffdXoseXLl8PZ2RmPPfYYgMp/zeuV9/gsLDY2FgCMfr8nT56Eo6MjmjVrZrRuSEiI9HjhMk4iIqIqZelULSIiopri/PnzAoD49NNPhRC6khtHR0exdOlSIYQQPj4+Ys6cOUIIIVJTU4VCoRCTJk2Sfl5fKmNowIABIigoyGhZcaVfn376qXB0dBRXrlwxWv7OO+8IhUIhoqKihBAF5WguLi4iPj6+TPsGQNja2opr165Jy06fPi0AiP/973/SsmeffVb4+fmJhIQEo58fOXKkcHV1lfYxLy+vSDlSUlKS8PHxERMnTpSWbdy4UQAQX3/9tbQsLy9PdO/e3ah8LykpyWSJXWXQ/74+/vhjcffuXREbGyv27Nkj2rZtKwCIdevWCSGEmDlzpskSp8WLFwsAIiIiQlp2P+V7e/bsEQqFQvTt27dISZwQQsyZM0cAEPv37xdCCHHw4EEBQERGRooLFy4IAOL8+fNCCCE2b94sAIjly5cbbaNly5Zi9OjR0vfvvvuu8PT0FGq12mg9ffne3bt3xd27d8W1a9fEF198IWQymWjVqlWJ+/Hpp58KAGLnzp3SsjVr1ggAYt++fUXWHzZsmPD19ZW+DwsLE0OHDhW//fab+Ouvv8SXX34pPDw8hJ2dnThx4kSJz10Wv/zyiwAgLl68KC3Lzc0Vnp6eRuVplf2ar8jxWVhOTo5o3ry5qF+/vtHfbNCgQUXeT4QQIiMjQwAQ77zzjsntlVa+Z4jle0REVB4s3yMiIqokzZo1g4eHBw4cOAAAOH36NDIyMqTsEsPSqYMHD0Kj0RhlJRiWyqSkpCAhIQE9e/bEjRs3kJKSUurzr1mzBt27d0etWrWQkJAg/evXrx80Gg327dtntP7QoUPh5eVV5v3r168fGjRoIH3fqlUruLi44MaNGwB0WU3r1q3D4MGDIYQwGsOAAQOQkpKCEydOAAAUCgVsbW0B6ErREhMTpQwZ/TqArtmyUqnE1KlTpWUKhQIvvvii0djs7e1ha2uLPXv2ICkpqcz7VB4zZ86El5cXfH190atXL1y/fh2zZs3Ck08+WSXPZ0pCQgKefvppeHh4YNmyZUVK4gDjpvuALiOvTp06CAgIQNOmTeHu7i69Dk01OT9z5gzOnj2LUaNGSctGjRqFhIQEbNu2rcjzZWRkwMvLC15eXmjYsCHeffdddOnSxeRMlHr79u3Dxx9/jOHDh0tlkACk0leVSlXkZ+zs7IxKY0NDQ7F27VpMnDgRQ4YMwTvvvINDhw5BJpNhxowZxT53WQ0fPhx2dnZYvny5tGzbtm1ISEjAmDFjAFTNa16vvMenoRdeeAEXLlzAzz//DKWyoDAiKyur2N+t/nEiIiJzYvkeERFRJZHJZAgNDcW+ffug1WoRFhYGb29vaSaw0NBQ/PzzzwBMBwPCwsIwc+ZMHDx4EJmZmUbbTklJgaura4nPf/XqVZw5c6bYC9n4+Hij7+vXr1+u/QsICCiyrFatWlIQ6O7du0hOTsaCBQuwYMGCUsewdOlSfPvtt7h06RLUarXJcUVGRsLPzw9OTk5G22nSpInR9yqVCrNmzcLrr78OHx8fdO7cGY8++ijGjRtnNLPb/Zg8eTKGDRsGuVwONzc3BAcHm7zArypCCIwbNw4xMTH4999/i92vFi1awM3NzSjwpO9bJpPJ0KVLF4SFhWHSpEkICwuDv7+/0d922bJlcHR0RFBQEK5duwZAF7SoV68eli9fjkGDBhk9n52dHf7++28Aur9D/fr1Ubdu3WL349KlS3jiiSfQokULadY+PX1gNicnp8jPZWdnl9rjqGHDhnjsscewfv16aDQak7MolpWbmxsGDx6MFStW4NNPPwWgK92rU6eOFEiritd8ScvKYvbs2fj111/x6aefYuDAgUaP2dvbF/u71T9ORERkTgxKERERVaJu3brh77//xtmzZ6V+UnqhoaF48803cfv2bRw4cAC1a9dGUFAQAF0Pnr59+6Jp06b47rvv4O/vD1tbW2zZsgXff/+9UaPy4mi1Wjz00EN46623TD7euHFjo+/LewFa3AW+EEJ6fgAYM2aMyZ5PAKR+WsuWLcOECRPw+OOP480334S3tzcUCgW+/PJLqR9Reb3yyisYPHgwNm7ciG3btuGDDz7Al19+iV27dqFt27YV2qahRo0aoV+/fsU+XlyjZ41Gc9/PDQDffPMN/v33X7z55psYMGBAsevJ5XJ06dIF4eHhEEIgLCwM7777rvR4aGgoFi1aJPWaevzxx6XHhBBYuXIlMjIy0Lx58yLbjo+PR3p6ulGQUKFQlPh7MRQdHY3+/fvD1dUVW7ZsgbOzs9Hjfn5+AICYmJgiPxsTE4PatWuX+hz+/v7Izc1FRkaGUbP0ihg3bhzWrFmD8PBwtGzZEps2bcK0adOkDLWqfM1XJEC0ZMkSvP3223j++efx/vvvF3ncz88Pu3fvlnqK6el/32X5/RIREVUmBqWIiIgqkWHpVFhYmNTkGADat28PlUqFPXv24PDhw0ZZDH///TdycnKwadMmo6wVU7PRFRf8aNCgAdLT08scIKhsXl5ecHZ2hkajKXUMa9euRVBQENavX2+0PzNnzjRaLzAwEDt37iwSCLl8+bLJ7TZo0ACvv/46Xn/9dVy9ehVt2rTBt99+i2XLlt3HnpWNfga85ORko5nsIiMji6xb3pnKDh8+jPfeew+dOnXC559/Xur63bp1w7///otNmzYhPj5eypQCdEGp9957D1u2bEFWVpZRtt7evXtx69YtfPLJJ0WaYSclJWHy5MnYuHGjVL5WHvfu3UP//v2Rk5ODnTt3SgEoQy1atIBSqcSxY8cwfPhwaXlubi5OnTpltKw4N27cgJ2dXZHsuop4+OGH4eXlheXLl6NTp07IzMzE2LFjpcer4jVfUX/99Reee+45PPnkk5gzZ47Jddq0aYOFCxfi4sWLRkHHw4cPS48TERGZE3tKERERVaIOHTpIfWhu375tlCmlUqnQrl07zJkzBxkZGUbBAH0Wkj7rCNCV7C1evLjIczg6OiI5ObnI8uHDh+PgwYMm+/4kJycjLy/vfnatVAqFAkOHDsW6detw7ty5Io/fvXvXaF3AeH8PHz5sNCU9AAwcOBB5eXmYN2+etEyj0eB///uf0XqZmZlSCZJegwYN4OzsbLJcqSro+20Z9u7KyMjA0qVLi6xb3N/QlOTkZIwcORIODg5YuXIlbGxsSv0Z/Wtr1qxZcHBwMAo2hISEQKlU4uuvvzZaFygo3XvzzTfx1FNPGf2bNGkSGjVqZNRjqawyMjIwcOBA3L59G1u2bEGjRo1Mrufq6op+/fph2bJlSEtLk5b/8ccfSE9Px7Bhw6Rlhq8nvdOnT2PTpk3o37+/yX5b5aVUKjFq1CisXr0aS5YsQcuWLaXMJ6BqXvMVsW/fPowcORI9evTA8uXLi933xx57DDY2Npg7d660TAiB+fPno06dOmWeXZGIiKiyMFOKiIioEtna2qJjx47Yv38/VCoV2rdvb/R4aGgovv32WwDGwYD+/fvD1tYWgwcPxpQpU5Ceno5ff/0V3t7eRUqZ2rdvj3nz5uGzzz5Dw4YN4e3tjT59+uDNN9/Epk2b8Oijj2LChAlo3749MjIycPbsWaxduxY3b940mh6+Knz11VfYvXs3OnXqhEmTJqF58+ZITEzEiRMnsGPHDiQmJgIAHn30Uaxfvx5PPPEEBg0ahIiICMyfPx/NmzdHenq6tL3Bgweja9eueOedd3Dz5k00b94c69evL9L4/cqVK+jbty+GDx+O5s2bQ6lUYsOGDYiLi8PIkSOrdJ/1+vfvj4CAADz77LN48803oVAosGjRInh5eSEqKspo3eL+hqY8//zzuHnzJkaMGIGwsDCpV1RhhtlLISEhsLW1xcGDB9GrVy+jZtcODg5o3bo1Dh48CDc3N7Ro0QKAro/TunXr8NBDD0mNrwsbMmQIfvzxR8THx8Pb27vMv5vRo0fjyJEjmDhxIi5evIiLFy9Kjzk5ORmVEH7++ecIDQ1Fz549MXnyZNy6dQvffvst+vfvj4cfflhab8SIEbC3t0doaCi8vb1x4cIFLFiwAA4ODvjqq6/KPLbSjBs3Dj/99BN2796NWbNmFXm8sl/z5RUZGYkhQ4ZAJpPhqaeewpo1a4web9WqlRRIq1u3Ll555RXMnj0barUaHTt2xMaNG7F//34sX77cqEQ3MjISf/zxBwDg2LFjAIDPPvsMgC6D0TBj7O+//8bp06cBAGq1GmfOnJHWHTJkiFEgj4iIyIhF5vwjIiKqwWbMmCEAiNDQ0CKPrV+/XgAQzs7OIi8vz+ixTZs2iVatWgk7OztRr149MWvWLLFo0SIBQEREREjrxcbGikGDBglnZ2cBQPTs2VN6LC0tTcyYMUM0bNhQ2NraCk9PTxEaGiq++eYbkZubK4QomHJ+9uzZZd4nAGL69OlFlgcGBhaZ/j0uLk5Mnz5d+Pv7CxsbG+Hr6yv69u0rFixYIK2j1WrFF198IQIDA4VKpRJt27YVmzdvFuPHjxeBgYFG27t3754YO3ascHFxEa6urmLs2LHi5MmTAoBYvHixEEKIhIQEMX36dNG0aVPh6OgoXF1dRadOncTq1avLvI/FKc/v6/jx46JTp07C1tZWBAQEiO+++04sXry4XH/DwgIDAwWAUv8V1qVLFwFAvPvuu0Uee+mllwQA8cgjj0jL1q1bJwCI3377rdix7NmzRwAQP/74oxBCiPHjxwtHR8dSfy8l7UPhv7cQQuzfv1+EhoYKOzs74eXlJaZPny5SU1ON1vnxxx9FSEiIcHd3F0qlUvj5+YkxY8aIq1evljqe8goODhZyuVzcunXL5OOV+Zov7/G5e/fuEl8XM2fONFpfo9FI47C1tRXBwcFi2bJl5dpu4dfr+PHji11Xf4wSERGZIhPCIIeYiIiIiIiMtG3bFu7u7ti5c6elh0JERFSjsKcUEREREVExjh07hlOnTmHcuHGWHgoREVGNw0wpIiIiIqJCzp07h+PHj+Pbb79FQkKCNKsfERERVR5mShERERERFbJ27Vo888wzUKvVWLlyJQNSREREVYCZUkREREREREREZHbMlCIiIiIiIiIiIrOzaFDqo48+gkwmM/rXtGlT6fHY2FiMHTsWvr6+cHR0RLt27bBu3bpSt3v79m2MGTMGHh4esLe3R8uWLXHs2LGq3BUiIiIiIiIiIioHpaUHEBwcjB07dkjfK5UFQxo3bhySk5OxadMmeHp6YsWKFRg+fDiOHTuGtm3bmtxeUlISunbtit69e+Pff/+Fl5cXrl69ilq1apV5TEIIpKWlwdnZGTKZrOI7R0REREREREREJlk8KKVUKuHr62vysfDwcMybNw8hISEAgPfffx/ff/89jh8/XmxQatasWfD398fixYulZfXr1y/XmNLS0uDq6oqUlBS4uLiU62eJiIiIiIiIiKh0Fu8pdfXqVdSuXRtBQUEYPXo0oqKipMdCQ0Px559/IjExEVqtFqtWrUJ2djZ69epV7PY2bdqEDh06YNiwYfD29kbbtm3x66+/mmFPiIiIiIiIiIiorCw6+96///6L9PR0NGnSBDExMfj4449x+/ZtnDt3Ds7OzkhOTsaIESPw33//QalUwsHBAWvWrEH//v2L3aZ+ut7XXnsNw4YNw9GjR/Hyyy9j/vz5GD9+vMmfycnJQU5OjvR9amoq/P39mSlFRERERERERFRFLBqUKiw5ORmBgYH47rvv8Oyzz+LFF1/EkSNH8MUXX8DT0xMbN27E999/j/3796Nly5Ymt2Fra4sOHTogPDxcWvbSSy/h6NGjOHjwoMmf+eijj/Dxxx8XWc6gFBERERERERFR1bB4+Z4hNzc3NG7cGNeuXcP169fx888/Y9GiRejbty9at26NmTNnokOHDpgzZ06x2/Dz80Pz5s2NljVr1syoLLCwGTNmICUlRfoXHR1daftERERERERERERFWVVQKj09HdevX4efnx8yMzMBAHK58RAVCgW0Wm2x2+jatSsuX75stOzKlSsIDAws9mdUKhVcXFyM/hERERERERERUdWxaFDqjTfewN69e3Hz5k2Eh4fjiSeegEKhwKhRo9C0aVM0bNgQU6ZMwZEjR3D9+nV8++232L59Ox5//HFpG3379sXPP/8sff/qq6/i0KFD+OKLL3Dt2jWsWLECCxYswPTp0y2wh0REREREREREZIrSkk9+69YtjBo1Cvfu3YOXlxe6deuGQ4cOwcvLCwCwZcsWvPPOOxg8eDDS09PRsGFDLF26FAMHDpS2cf36dSQkJEjfd+zYERs2bMCMGTPwySefoH79+vjhhx8wevRos+8fERERERERERGZZlWNzq1FamoqXF1d2eiciIiIiIiIiKiKWFVPKSIiIiIiIiIiejAwKEVERERERERERGbHoBQREREREREREZkdg1JERERERERERGR2DEoREREREREREZHZMShFRERERERERERmx6AUERERERERERGZHYNSRERERERERERkdgxKERERERERERGR2TEoRUREREREREREZsegFBERERERERERmR2DUkREREREREREZHYMShERERERERERkdkxKEVERERERERERGbHoBQREREREREREZkdg1JERERERERERGR2DErVYOHXEvDL3utQa7SWHgoRERERERERkRGlpQdAVWfGhrOIvJeJK3Hp+GZYK8hkMksPiYiIiIiIiIgIADOlaiytVuBOchYAYN2JW/jmv8sWHhERERERERERUQEGpWqopMxcqDVC+n7O7uv44+BNyw2IiIiIiIiIiMgAg1I1VHxaDgDAw9EWr/ZrDAD4cNN5XLiTaslhEREREREREREBYFCqxopLzQYAeLvY4aW+DdG/uQ+EABYeuGHhkRERERERERERMShVY+kzpbydVZDJZHihT0MAwN+n70gBKyIiIiIiIiIiS2FQqhr5YccVPLf0KNQabanrxucHnnxcVACAVnXdEFLPHWqNwNLwm1U5TCIiIiIiIiKiUjEoVU1otAJz91zHjovxOF+GvlAFmVJ20rJnu9cHACw/HIXM3LyqGSgRERERERERURkwKFVN3EnOQm6eLkMqJjmr1PXjU/ODUvmZUgDQr5kP6nk4ICVLjbXHb1XNQImIiIiIiIiIyoBBqWoiIiFD+vpOSuk9oeLS8hudG2RKKeQyTOymy5ZadCACGq2o5FESEREREREREZUNg1LVhGFQKjalYplSAPBU+7pwtbfBzXuZOHj9XuUOkoiIiIiIiIiojBiUqibKkyklhMBdg9n3DDnYKjEg2AcAsPNSXCWPkoiIiIiIiIiobBiUqiZuGGVKlRyUSs5UIzd/hj6vQkEpAOjbLD8odTEeQrCEj4iIiIiIiMhaqTVaaGto+x0GpaqJiIR06evSGp3rZ96r5WADlVJR5PFuDT1hq5AjKjET1+9mFHmciIiIiIiIiCwvPjUbnb7Yicl/HLf0UKoEg1LVQE6eBreSCgJRcWk5JTYpj0vVZVL5uNiZfNxRpUTnBh4AgJ0XWcJHREREREREZI22nI1BYkYudlyMk671axKlpQdQ0+RlZlb6Nm/Ep0OpzoWTSoEstRaaPIHY+GT4uBQtzQOAuIQU2OTlwteu+PH0re+CgxduY8/ZaDzb0a/Sx0xERERERERE92fP2WjY5OUCAHaejsLw9nUtPKKyUzo4lLqOTLCpUBGpqalwdXVFSkoKXFxcyvWzK4KDq2hURERERERERETVw9Pnz5e6Dsv3iIiIiIiIiIjI7Fi+V8mGHz16Xz9/PCoJYxYeAQBMCA3E2w83xfsbz2LdiTuY3rsBrt9Nx9ZzcXj74SaYEFrP5DZe+fMUtp2Pw3sDm2JM58Bin+u77Vfw6/4IPNrKF7Ofan1f4yYiIiIiIiKiyqOPBYztEoD/zschLjUH88e2Q89GXpYeWqVhUKqSlaVmsiSn4mKgVtoCAHbeSMV7Dg64nqqBWmmL+nU8kAEl1MokxGYX/1wx2YBaaQtvL7cSx9OndQDmHryNXRFpgMoOSgUT54iIiIiIiIgsTasV2HEjDWqlLfq2DkS23BYrDkdhd0Qq+rYuPvmkumEUwsqciEqSvr6RkIEbd9MRkZABAGjg5QRfV3sAQExK8V3349P0s++ZboSu1zagFmo52CAlS40D1xLud+hEREREREREVAnO3E5BQnoOnFVKdKznjn7NvAEAuy7Goya1BmdQyooIIXAiKhkA4O6oy5baePI2EtJ1nfbreTqitqsdAOBOSlax24hLzQEAeDvblfh8CrkMj7etAwBYFHbzfodPRERERERERJVg18U4AECPxl6wVcoR2sATdjZy3EnJxqXYNAuPrvIwKGVFbiVl4W5aDpRyGSZ1DwIALDscBQDwdlbBSaWEn5suUyq2mEyp1Kw85OZpAQBeziVnSgHAM6H1IZcB+67cxeUa9MImIiIiIvMQQkCrLfhXndWkfSGi8rGG7CPD96Cdl+IBAH2a6jKk7GwU6NrAEwCwK/+xkrZT3ue1FAalrIi+dC+4jisGtvQFACRm6LKk6ns6AgD88jOl4lKzkafRFtmGvnTP1d4GdjaKUp8zwMMBA4J1z/XbgRv3uQdEREREZGm7L8Wjw2c7sOtSXJU/19GbiWj50X8IencLgt7dgqYfbsWc3deq/HnvR+S9DHSbtQtf/nvRaHl0YiZCvtgp7UvQu1vwwcZzFholEZlT+PUEdP1qFz7dfKFMAZqbCRno+tUuzNp6qdLGcDk2Db2+2SO9/5y/kwqZDOjVpKCpeZ/8Er7/LhT//h55LwP9v9+H55YeQ7ZaU+rz3knOwqCfDmDsb4eRkZN3/ztSTgxKWZETkbqgVLsANwR6OKKht5P0WJCXLijl6aSCUi6DVgB303OKbKOgdK/0LCm95/KzsjaevIO7aUW3SURERETVx/qTt5GQnoMvtlyq8rvff526jXSDi5jcPC1mb7uMPw5FVunz3o/5e6/jVlIWFu6PwO3kgpYYv+6/UeRceNnhSNzM7+9KRDXThTupmPL7cdxJycZvByLw/fYrpf7M3D3XcDs5C7/uu4GYYlrrlMed5CyMX3QEkfcyjZY/0sIXHk4F1/YPNfOBUi7D6ehknL2VUmQ7Cek5GL/oCK7Gp2PHxTi8tPIkNCVkfaZkqjFh8RFciEnF/qsJmLr8BNQmkl+qEoNSVkTfT6pdQC0AQN/8ND2gIFNKIZfBxyW/r1Ry0RK+gibnJfeTMtQ+sBbaBrghV6O16hMIIiIiIirdpZhUAMC1+HTsuXK3Sp/reGQyAOCbYa1x8oOH8HLfRgCAD/86h63nYqv0uSsiIT0H607cBgBotAJLw28CAJIzc7Hm2C0AwG/jO+DkBw+hZ2MvCAEsCouw1HCJqIrdSsrEhMVHkJaTh0AP3cz1P+26huWHi78uvpuWg40n7wAA8rQCS8Pv7xo6JVON8YuOIDY1Gw29nXDg7d44+cFDOPXhQ5jzdDujdb1d7PBoKz8ARSudMnLy8OySo7h5LxO+LnawVcjx34U4zNx0zuQNimy1BpP+OIYrcenwclbB3kaBfVfu4u11ZyrlhkZZS6CV9/1MVCmycjW4mH8C0S4wPyjVzAe/7NO90Op7FmRN+bna4XZyVn5EtpbRdiqSKQUAz3ULwvQVJ7DsUCSe7xkEB9uCl0bYtQQcvZmIyT2Ml1PNkJSRi98ORKBvM2+0DahV+g8QERGR1cpWa3DDILPnt/0R6N3Eu4SfMBaflo0Fe29gZIg/Gno7l7huek4eLsfqzl+7N/JELUdbvNKvEeLTsrHySDReWnUSKyd1RvvAgvOLlCw1/rfzKoa0qY1Wdd3Kt3OVYNmhSOTmaeHmYIPkTDVWHo7Ci30aYvnhKGSpNWju54I+Tb0hk8kwuUcQ9l65izXHbuG1hxrDzcG20sYhhMD8vTfg726PR1vVrrTtVkf/nInBzXsZmNIjCEpFQc7E1nMx2Ha+oESpobcTJvcIgo2i5udVnL2VgqUHb0oZLh6Otni+VwN4OpXvGo9KlpyZiwmLjyI+LQeNfZywZkoofguLwE87r+KDjefg5aRC//xWN4b+OHgTuZqC95EVhyPxYp+GcFQpkZmbh7m7ryO0gQdCG3qWOoZstQaTfj+Gq/Hp8HWxw9KJIaiT30e6OM92C8LGU3ew+UwM3n6kKfxc7aHWaDF9xQmcvpWCWg42WD6pEy7HpuVf40fhVlIWahV6D4tIyMCp6GQ4q5T4fWIIYlKyMOn341h/4jbupuWYfL2FNvDAsA7+pe6XEALv/3UOXzzRstR1a/4RXU2cuZWMPK2Aj4tKmmGvXYAbvJxVUMhlaOpbcFJQUrNzfaaUl0v53rAGBPugbi17JGbk4uVVp6Q3wP1X72L8oiP4YcdVTF9+wmQfK6q+snI1mLj0KH7efQ2jFx7GmVvJlh4SERER3Ydr8enQaAUcbBWQy4AD1xKkG59lMWfXNSw8EIFRvx5GdGJmieueiU6GVgB13OylLH2ZTIZPH2uBfs28kZunxcd/nze64/7TzqtYeCACoxcexqXYso+rMmSrNfjjoC6j4eMhwQjyckRaTh6WH46SMqae614fMpkMgO7iq6mvM7LUGqw4ElWpYzkckYhZWy/hhRUnseHkrUrddnUSm5KNl1edxOxtl/HhpoLXyoaTt/D8shPYcPK29G/2tsuYsf6sVTSjrkpCCLy+5hTWHr8l7fvCAxGYsPiIUaks3Z9stQbPLT2Ga/Hp8HPVBYNcHWzwar9GGNnRH1oBvLjyJI5HJhb5OX110aePtUB9T0ekZudhzbFoqDVaTFt+Aj/vvoYXV54stZ+TRivw6p+ncORmIpxVSiyZ2LHUgBQAtKzrik713ZGnFVgSfhNCCLy34Sz2XL4LOxs5fpvQEQ28nDCwpR9mPtocALDn8l2j42nDyds4FZ0MG4UMv4xrj2Z+LujT1AdfPNECALD/akKR9TecvI03157Bwv2l96L+edc1rDhctvdNpr1YCcPSPf0HoVIhx4rnOiExIxf+7g7Suvpm56bL93SZUj7OZS/f0z/Xd8PbYMxvh7E9P8VvZMcAPP/HceTlB6h2X76L9zacw1dDW0pjpOorT6PFiytP4GT+ay8zV4OJS45i3dRQBHo4WnZwREREVCH62ZRb1XWFh5MK/5yJwW8HIvDNsNal/qwQBbM93U3LwfjFR7Du+VDUcjSdIaSfpKdtgJvRcqVCjllDW6HLV7tw5lYKjkUmoWM9d6Rmq/Hn0WgAQFp2HiYsOor100JRuwwXYZVh48nbuJeRizpu9hjU0g8ZORq8u+Esvtl2Wbo5bJi1JJPpZsR+fc1pLA2/iee6BcFWWTn39HdeLMgAenPNGXg6qdC9kVcJP1Ez/X7wpnStsTnJTcMAAG6nSURBVOJwFGq72qG1vxveXHMGAPBYm9poUdsVqdlqzNl9DWuP34Kvix3eGNDEksOuUvuvJuBKXDocbRV4uV8jCAEs2HcD526nYuqy4/htfMdKex0+qDRagZdWnsSxyCS42CmxdGII/Fx170MymQyfPd4C8Wk52HUpHs8uPYa1z4dK/Z7Xn7iNpEw16tayxyMtfJGcpcYHG89hUdhNnL+Tij2XdSXT9zJysfHkbYwMCTA5BiEEPvn7PP49FwtbhRwLxnVAU1+XMu/DpO5BOByRiBWHo6DVCqw+dgtyGfC/Ue2kdkAAMKFrfTTwdsKlmDST2+na0BPNaxc874iOAQhwd8S520X7Vd1IyMDKI1H47J+L8HGxw+DWprM8Vx+Nxrdl6Mulx6CUlTguNTk3Lp9q5FM0bVoflIpN1TVUy8jJw6noZAgBXI9PBwB4lzNTCgBC6rvjxxFtMC0/xW/t8VvIVmsR2sADYzoH4oUVJ/DnsWj4uNrhtYcal3v7ao0WxyOTkKfRffD4uKhM7l91JoTA9bsZaODlaBS4K255Vbkal4ZAD8diP7CEEPjgr3PYcTEeKqUcv4xtj9nbLuP8nVSMW3QEHw8JhlIuh1IhQ/vAWlaTJh2dmCk1/5PJdCfBZS0pjU7MhJNKWeyJdXWVkqU2anLY0NsJvq7lC0pXpmy1Bicik6AvIfd3t2eQk6gSxaZk41r+Zz0ANPNzNmqAShWXmZuHO8lZpZasmUtunhYno5Kg1hTNCnFQKdCmrhvk8qLnFPrso6a+LnisTW38cyYGf526jbcGNIF3KT1Hr8Sl41ZSFmyVcng62uLG3QxMXHoUrz3UGDLIYKOQoW1ALen8onA/VEMeTioMbVcHK49EY+H+G+hYzx1/HolGek4egrwcoZDJcDU+HeMXHcEHjzaHXKbbfvvAWkYlXJVFCIGFB3S9oSaE1oNSIceT7epg9rZLSMpUAwDGh9Yrcu40uHVtzNp6CXGpOZi35zraB9aCXAa0DagFe9vSZ7oujj74F+TpiBsJGXj+j+OY9VQruNmXfJ7Syt8VLnY2FX5eS0rJUiNbrZGy6jJzdVlqAPBwsC+2no/FN/9dgUopR55WYHDr2vh+eBvpdV7HzR7vrD+Ln3dfg52NHG38da+7QA8Hoxv4JclWa3A3LafM6xvKydMgNiW7yHlNbp4WMSlZJZ7vqDVa3ErKkvoEl+TX/CyU4R39MblHAwBApyAPjFpwCPuvJuCNNacxPL98yslOidZ1XYu9vtBqBSLuZSDI0zzXIFXh/J0UJGWoS1zHVilH+8BaUBR6T7xxNx0B7g5G7ylCCMzcdA7/XYiDrVKOX8d1QONC16RKhRw/P90Wo349jNPRyRi/6Ag+e6IFbORyLMzv4/RM1/pQKuQY2q4Ovv3vMqISMxGVmAm5DOjT1Ac7LsZh4YEIjOjob/J3P3/vDSzNz9z8bkRrdGngUa7fS5+m3qjv6YiIhAz8ul/33vbZ4y3xUHOfIut2b+RVrqB3lwYeJscjhICtQoalByPx+urTyFZrpGCeXnRSJt7Pn7V0Wq8GZXo+BqWsQG6eVkoLbBfoVur6hplSd5KzMHReOGIKlfKVp9G5oUda+uGjwcGYuek8stVaNPV1xvyx7eFiZ4NPH2+B9zacw087r6JzkDtCG5ReI6uXnpOHUQsO4WyhiOs7jzTF8z3L9mK1dlqtwOtrTmPDydsY0ro2fhih+xAVQuCttWew5vgtDGzpi/+NalfkDbMybTx5G6/8eQojOvhj1lOtTK7z085rWHkkGnIZ8OPItujVxBvNa7vgybnhiLyXiQmLj0rrtqzjipWTO8NJZdm3i81n7uCllSdh2C+vjps91k0NLTUIE5GQgQE/7IOrvQ3WTw2t0ImINboWn45h88Olk2kAsFXIsfiZjuhahhr2ynY3LQfD5ofjpsGsITIZMPup1niqfV2zj4eopsnK1eCRH/cZHfOOtgqsmtwFLeu6WnBkNcPLq05h+4U4vDuwqXQhaElf/XupxAbbnz4WjLFd6hVZfik/U6qprzPaBtRC+8BaOB6ZhE//uYgfR7QxGcjS23lJl73TtYEH3h3YDEPnheNkVDLG/nZEWmdi1/r4cHBzCCFwMj9Tql2g6Z6Uz3arj5VHovHfhThci0/H4vz9mdw9CN0be2Ho3HBcjU/HuEUF2+8QWAvLnusEO5uKB3xM2XvlLq7Fp8NJpcSIEN0FvZ2NAmM7B+KnXddgb6PA0yYyGmyVcowPrYfZ2y7j+x0Fd/4D3B2wbmoovMrZxxXQnZfcuJsBpVyGNc93wQsrTuLgjXt4YcXJUn/W3dEWa5/vgiAvp1LXtSY37qbjqfkHkZ6dJ52nrD1+CylZagR6OGDO6Hb45r/LmLfnOnLytOgS5IFvhrUyer2ODAlAbGo2fthxFd/8V/C3kMuAOU+3wyMt/UocQ0J6Dp6aF47IxEx8O6w1nmxX9nOTlEw1hv9yEJfj0oyOvdRsNUb8cggXY1Ixc3BzPNO1fpGfzcjJw9O/HsLpWyl4++GmmFrChfrl2DTsv5oAuQx4JrRgW2383TB3dDs89/sxbDp9B5tO35EemzW0JUZ0LPraVWu0mPz7Mey+fBcTQuth5uDm1S4w9dnmC1IwuTSd6rtj6cQQ6b3jhx1X8MOOq0XeU+buuY5lh6IgkwE/jGiDTkGmg0EOtkosGt8BT80/iIiEDDxjcH3krFJieIe60nqjOwVgzu7rAIDPn2iJQa38EPrlLmmyicJ9/dafuIVZWy8BAD54tHmF+srJ5TJM7FYfH+QHgF7q2whPdzKdlVVZZDIZPhwcjPi0HPx7LhZvrj1T7LpPtquDN8uY0Vjh2xBqtRrR0dG4fPkyEhMTS/8BKtam03eQlKmGj4uqTA0f9dHIqETdTAExKdlwd7RFU19nNPV1xiMtfNHGv/TtFGd8/pvWw8G+WDoxRLobM7pTIEblf4gv2Fd6Halebp4WU5cdx9nbKXBSKdHU11lKf/zq30tYf6Jm1NHP2noJG07qZnPZdPoOvthyEQDw7X9XsOa4bh+3nI3FJ4V6K1QmIQR+3n0NALDuxC3cSS46PemqI1HSSdXHj7XAwy10zfu8ne3w+8QQ9GzsJb2WnFRKnL2dgmkWmBrUUPj1BLz252lohe5uWFNfZ9RysMHt5CxMWHwEKVkl3z357cAN5OZpdaUIi44gMSPXTCOvOnGp2Ri/6AiSMtXwdFKhqa8z6rjZI1ejxZQ/juP8naIpt1UpIycPE/Nn+3C1t0FTX2fU93SEEMA7685gz+V4s46HqCY6cysZSZlqqJRyNPV1hq+LHTJyNXhmyRFE3uOU9ffjcmwatl/QBWS+2HIJG/M/zy0lKSMXK47o7qA39HaSPpf17/UA8PeZGJM/ezG/RKOpn64c480BTaCUy/D36Tv4Kv8iqDi7Lureq/s080EjH2csmRiCkPruRuduK45EIjkzFxEJGdLrsbmf6ZKTht7O6N1EN4Pd5D+O4U5KNjwcbfF42zqo42aPpRND0K2hp7RvDrYKHItMKnUK84pYmJ9JMKKjv1Gm0bPdgvBwsC8+GtK82EbmY7sEoneTgvMjNwcbRCVm4pklFevxoy/d6xTkDg8nFX4Z1x6Ptalt9Hc29c/TSYXEjFyMX3xE6iNbHcSnZWNc/vmX/jzl3O0ULMoPNjzbrT4UchneGtAEL/VthMfb1MYv49pDpSwamHy5byO8/lBj6XcS4O4ArQBe/vMUjkQUf01qeJ4iBPDW2jPYV8aZKfUzlF2O0x1bH246j63nYpGTp8GU349LPds+2XwBm8/cMfpZfY+h0/lZ7bO2lnzto59NbUCwLwI8jG+i9m7qjZ9HtUXruq5o6usMf3fde8H8vTeKzHImhMCM9WexO7+UbEn4TczfW/brN2vw674bUkCqiU/Jx4a9jQKHIxLx+urT0GoFVhyOwg87rgKA0XvKmmPRmL3tMgBg5qPNMbCUQKaHkwpLnwkxOv6b+bngg0ebw9ngfeS5bkHo09QbHw1ujlEhAXCxs8GIjrrr5t/2GwfV9l65i7fygzmTewTh2W5FA5llNax9XTzayg8v9mmIV/s1qvB2ykMhl+H7EW0wKsS/2L/H+C6BmDW0VZmDoDJRjqvjtLQ0LFu2DKtWrcKRI0eQm5sLIQRkMhnq1q2L/v37Y/LkyejYsWOFd9IapKamwtXVFSkpKXBxKXtdZ0UIIfDIj/txKTat1Mi5XnxaNkI+3yl97+OiwvppXcvUFO1+Rd7LQK9v9kAIYPurPUotvxNC4PXVp7H+5G3Y2yiwanJntM4PmH3+zwX8uj8CSrkMi5/pWK3r6BcdiMAnmy8AAJ5qXxdr84NQfZt6S+nZQ9vVxbr8D6G3Hm6Cab0aVvo49lyON8pymtIzCDMeaSZ9v/NiHCb/cRwarcD03g3w5oCmJW7vVHQyRi04hCy1Bk+2q4Nvh7U2+x2WS7GpGDbvINJy8vBIC1/8/LQu0yw6MRNPzgvH3bQcdA7S3RkxdfKSlJGLLl/tRLZaC1d7G6RkqdE2wA0rnut8X2n3lpSWrcbw/Lty9T0dsfb5LvBwUiEnT4Pxi47g0I1EeDmrzJYVptZo8ezSY9h35S7cHW2xbmoo6ns6QqsVeG31KWw8dQcOtgr8yWwOovsyb891zNp6CY+08MW8Me2N3gvqeeiyNljKVzFvrz2DP49FS58TNgoZFk8IQbdG5s86BYA5u69h9rbLCK7tgs0vdjP67I1OzET3r3dDIZfh+Pv9jAIpCek56PDZDshkwPmPB0gl7uuO38Lra04D0N2VN3URlJiRiw6fbYdWAOHv9CnS50kIgUE/HcCFmFS8OaAJvJ1VeHPtGXQIrIW1U0OL3ZewawkYvfCw9P0r/RrhlX6m20AcvnEPYxcdQW6eFmM6B+DTx1pUynnHxZhUPPLjfshlwN43e9/3Z2NEQgaGzgtHYkYuujfyxKIJHcvV6uDpXw8h/Pq9Yv8WxbmbloOh88IRlZiJFnVcsGpyF4tnspcmPScPI345iPN3UhHo4QAfFzsciUiEvY0CWWoNXO1tcHBGnwrP8K3RCjy/7Di2X4iDi50Sa6eGFinFUmu0eG7pMezNP09pF+CGHRfj4WirwJ9TuqBFneLPTTRagRdXnsCWs7FwVinRrZEn/j0XC5VSjg71aiHs2j042irQs4kXtpzV9Qb6/dkQdA7ygBACb6w5g3UnbsHORo5+zXyw+UwMlHIZFk3oiB6Nja997qbloOtXu5Cr0WLd1FCjWSuL+912+XIn0rLzsHBcB/QzKNv6Zttl/Lz7GhRyGR5rUxvrT+gC7d8NL1+GmKX8deo2Xl51CgDKlL0afi0B4xcfgVoj0KuJF/ZduQut0PUk+/dcLHLztOjZ2AsHriXoXjM9G+CdR0q+Drpf0YmZ6Dl7N7QC+Pfl7mjm54Kzt1IwYsFBZOZq8Fgb4/LUB1mZg1LfffcdPv/8czRo0ACDBw9GSEgIateuDXt7eyQmJuLcuXPYv38/Nm7ciE6dOuF///sfGjUyT7Sust1PUKrTFztKXadFbVd8N7wNXB1scOBqAsb8dhj2NgocmtEXrg6l14hrtQJNPvgXao2As0qJNVO7lKsp2v2a8scxbDsfh5Ed/fHVUF152Jzduu76eVrjbBqNViAhPRcKuQwLx3cwSl3UagVe+fMUNp2+A1uFHLUci+67l7MKnz/eUgpkAbomiGuOR+ODR5sb9TBYfTQaP+++hpy8orMc1HKwxUdDgtG5mPTMTafv4LcDEXizfxOjE9AtZ2Pwy74beLVfI/QyGPu287GYtfUSMvLvjsWn5UAI3d3I6b0bYv7e6/jq34K7kfoTsN8ORODT/ODVt8NaY2gxJU3h1xLw8d8XkJyly+ixs1Hg5b6NjD5Ejt5MxOf/XMTTnQKkuvIxCw/jwLUEtKjjgnO3U+Fsp8TBGX3hpFLiZFQSRv16CNlqLYa2q4tvhpUter3rUhwm/a4LZHk62UIhl0Epl2Ncl0BMMSi9vBafjrfWnsZtE9lZCpkMIzoG4KW+DU0+Z3RiJl5fc9rknX5d/wEtQuq54/dnQ4zS+c/fScGIXw4hPScPg1r54X8j2xZ5Y/95ly7FO7i2C34Y0QZPzT+IlCw1XO1tYGdT8glkr8beuvrx/BPN1Gw1Xll1Cl5OqjI1/M/IycNba89AIZdh1tBWUhAsK1eDt9adwZGIeyX+fHGycjVIzc6Dp5Mt1k/tanQnLSVLjRG/HMSl2DQ42irgZFf0JK+Jrwu+H97a5MWrVivw6T8XcC0+vUgjzTm7r+GPg5EQMP7YyM3TIilTDXsbBVZM6oS2Bsdlbp4WE5ccxYFrCVAp5XDLf4/zr+WA2cNal6m3QnktDovA5jMx+HhIcIknmkTVzXNLj2HHxTi8N7AZJvUIAgDEp2bjibnhuJ2chdZ1deXWFb24s6T5e68j/Po9/G9k2zKdC5XFkrAILNh3A5r8U93abvaY/VSrIj2j7qbloOusXcjN02LN812wJPwm/jkTAyeVEn+/2K1K3qcMbT0Xg//tuoYPHm2OzkEeyMnToNus3bibloPvR7TGE22LnisM+H4fLsel4ceRbfBYmzrScn0AqJ6HA/a82dvoZ+buuYavt+oyBHzye486qpR4a0BTPNzCFxtO3sKrf55GMz8X/Ptyd5NjXX/iFl5bfRpezir0bOyFtcdvYXKPILw7sJnJ9QHjG7C2SjnC3+lT4rT2W87GYPqKExAC8HRSoXCsRyGTYXqfhhjdKbDYbRT2xprTWHv8Fga19MOc0e3K/HMlMbxxV8vBBrZKOWTQBQDefripdD4Sl5qN11efRmMfZ7w/qBnSc/PQ7pPtyNMK7HmjF+qV8/VlGBBzsVNK5xY9Gnnh8ydaWlUD7Nw8LZ5dehT7rybAw9EW66eFws3BVjpPAYCpvRrg7YfvLziQrdZg9MLDOB6ZBHsbBVzsjd8DC5+nNK/tgmcWH0X49XtG5yam5GkE7mXkwlYhx5KJHRFSzx3PLzuBHfnZbvqb66ENPDF9+QlsPR8rXdcYXgctGNsevZt449XVp/DXqTuwUcjgXqjPabZaK9083TCta5n2/cstF/HLvhvoHOSOVZO7AAD+OBQplXR99WRLjAwJMEoGKBwQ++dMDBbsv4HXH2pcJFBWHodu3MM7684gq5QZ58oiIT0XGq3AM13r4cNHy1Z2uOm0rtWH3vAOdTFraCtsPReLafnvKQDwRFvdjXZzBIOmLz+Bf87GwFmlhINKgeRMNXLytOja0AOLJ4RY1fFqSWUOSo0aNQrvv/8+goODS1wvJycHixcvhq2tLSZOnFgpgzS3+wlK1XvnnzKtF1LfHb9PDMHzy45jz+W7GN8lEB8/1qLMzzP8l4M4cysZiyZ0LFdvp8pw9GYihs0/KJ1YbDx5G5/9c7HY9RVyGb58sqUUODGUk6ebinP/1YRif97d0Rbrp4ainqej1C8JANwcbKSZEDafuYMXV55ESa9mZ5USf07pYjS7AADsvhSP534/Jk2fvGpyZ7Sq64Z9V+5i4pKjyNMK2NnIsWJSZ7QLqIXw6wmYsOgocguVsxm+aQoh8Pk/F7HwQESRO31fbLmIBftuQCmX4bcJHdGz0Jv/udspGPHLQWTkGr+hy2XAvDHtMSDYF5dj0/DU/HCkZedBll9HX9/T0egu4PhFR3AjIQMzBzdHz8ZeGDpP13uoZ2MvLBzfoVx39FYfjcaMDWeLpNJ/NLg5JnStj7jUbDyZf1FUEn3QzlBiRi6emheOGwnFl5409XXGn5O7mLxQCbuWgAn5d0Ymdq2PDx5tJv2uTZ3YH7uZiPGLjhT5/RZHnyGWq9FKWUgA8OfkzsXWoAO6u3KTfj8mzcDxUHMfzMs/ETY8makoFzsllj/X2WTmUWxKNob9Eo7oxOL/HqYuXoUQ+PjvC1iSPy325he7GQV1un61q9i/sa1Sjnmj26Fvs6LNFdOy1Ri98DDO3DIuKbyffhzFWXkkCjPWnwWgu5hZPzW0SPo7UXUkhECHz3bgXkYu1k3tgvaB7tJj1++mY+i8cCRnqtG7iRd+HdehShpFV6U2n/yH5Ew13ujfGC/0qZybmp2/2InYVOMSp9qudlg/ratRL8Lvtl/BTzuvoo2/GzZMC0WuRosxCw/j6M0kDO9QF18/VfqsdRWVp9Gi5+w9uJ2cJZ2nXIhJxRtrTsPXxQ773upt8qLl662XMHfPdQxpXRs/jWorLV+4/wY+++ciHg72xfyx7Y1+RgiBTzdfLNKnykYhw9JnQrDiSBQ2n4nBC70bFjuzWW6eFt2/3oW41Bwo5DJotALzx7SXWgEUZ+u5GDy/7ASe61Yf7+dPT16SpeE38fHf51FcBZ+znRKHZvSFYxmyhOJTs9F11i6oNQIbpoUa3Ti5X7svxWPKsuPIzTM+J9Rnqhv2GwJ0/bjaBbrhhRUnEeTliF2v96rQ856KTsbYhYeRVqh08PE2tfGdlWReGFZLGJ5fA7rzlKfmhyM1S43tr/WscC9cQ0kZuRi54JBUYldY4fOUtGw1nv71cJF+t6Yo88uV9DONZeXqMtNPRCVh9rBWUuA4W63BhMUF54qA7jro88dbSDOw5eZp8dzvx0osHfxtfAeT51OmxKRkofus3cjTCmx+sRtuJWVh6vLjEAJ4tV9jvJxf0qXVCikgZpghtudyPJ5begx5WgF7GwVWTu5coTYwQgg8MTccp6KTy/2zxalIJtFvByLw2T8X0LepD+aNaSdd7/x+8CY+2nQePRp7YcHYDmYLBp29lYLH54YZXUO1rOOKFZM6GZX/PejKVb73oLifoJSpqRMN3cvIxQvLTyAtJw+dg9xx6EYiZDJgzxu9yjVDVW6eFpm5ecXWvlclIQQenxuO09HJ0j4AumygfibeQL2dVSXO9iKEwJW49CI9i7RC4L0N53D2dgoC3B3wev/GeGPNaag1Am4ONkjOVKOOmz3efqQp3lh9GrkaLZ7uFGCySeUnmy/gSEQivJ1VWD8tFHVr6S5SDe9y6bfp6WSLTx5rgTfXnEZGbsHyWg42+PyJlnh77RmplEwfYHG2U5r8+91LzymSjWL4oVC4pCnqnq4kLSE9B12CPPDeIN2dx98P3sTqY7egUsrx7fDW+GzzRcSmZktjs1XI0aKOC05EJWNQKz/Mebodlh2KxPsbz6GOmz3kciA6MQst67hi1eTOZTqJKywuNRt303IAAP+dj8VPu65BJgNmPdkKi8IicCk2DfU9HfHd8NZFAl57r9yV6re/GVbQ9DorV4OnFx7Cyahk1HGzx48j2xRpbCqXydDYx6nEC6ziUnzXHIvGm2vPFDmxT8lSIzoxs7jNAQCuxqfhjTVnpBTfW0mZ2GzQv+Oh5j74dVwHkz8rhMCba89g7XFdurZW6I5ZffPBFYejYKuU46eRbaTXYnkFejiU+GGWk6fB1bj0IstTstSYvuKEdPG6YFxBgPKXvdfxpUGG3/ppoUbZiB0/34G7aTn436i2RTIH/FztSiwb0mgFLsemQSsEcvK0eOXPk/f9mixs58U4TPr9GLQC0rFhWN5IVJ1F3stAz9l7YKuQ48xH/Yu8Vx6PTMLohbpsWP3d4erS0DYpIxdtP90OQJchfeDt3ibLscvjTnIWQr/aBYVchnVTQ6UL5BsJGWjq64zVz3eBi50NstUahH61C4kZuZjzdDsMaqXrL3I8MhFD5x2ErUKOsHf6VGrw3NDmM3eMmlt7O6vgZKfEjbsZJbZ10I/PxU6JEx88JH1G6jOCSiqRi7yXgbRsXTBj7p5r2HI2Fk4qJYQQyMjVFHnvL8ww4woAjrzXF97OpQcV4lOz4emkKvMFZmxKNhLSc4osf3HlSUQkZEg3xkqjL2NqH1gL60ooM6yoxIxcqYfn8cgkzNx0HoDufGTP5bsIv34PLnZKpOb/zn1d7BCbml1qhllpUrPViMqfWOT63XS8vvo08rSiSOsGS5m19RLm7blusloC0M28l5unrdRrmTyNFpfj0kzepDZ1nmJ4blISHxe7Iu8BWq1Acpa6SLaTVitwJT5Nmm3cy1lVJOhW3LUPALja25S7vPTlVSfx16k7aBvghgt3UpGTp8WoEH988YRxVn9unhbPLDmCsGv3pOudN9acRqbB9U5FG+lL75lKOZY/1wn29zlRgZ2NosKzlt9Lz4G7o22Rny1ueVUzfC+Ty2Ro4utcpZNeVUflCkotXrwYffr0QWBg2dNlq6Oq7ilVONNmQLAPfhlr+uLWWv19WpeZpFdVMzrcTcvBk/PCjDI+Hm3lh4+GBGNY/kwIeg8H+2LOaNMz26VkqjHsl3BciUtHkKcjHm7hCwHgz6PRSMzIRY/GXvhpZBuMXngY5++kSj/XtaEH5j7dHuMWHZYaFAIFmW4VnRmm8IfCsA7+kEGXsn7zXqbRCTOg+5Cd/Mdx7LpU0Cy6obcTVk/pgnfWncF/FwqybvR3AbNyNQj9aqc0S1OghwPWPl85WSlCCHz413n8cShSWubppMKGacX3MDLMEBvXpR7sbOQ4HpmEwxGJcLW3wbqpXe5rGu4F+67jiy26gMqYzroGg/+cjUHkvcwy92srbPWxaKkRIaC7m/zBo83x4V/nIZMBu17vJQVntl+Ik2YhikrUBbDkMuDXcR2g1mgxdXlB2rBMBswb3Q4Ptyi5uWJVMbx47d3EC838XJCarcayQ7ppmfV3vwtng7X95D8kZaqx47Ue9z1lumH5QYfAWgip715kndpu9hjewb9Md7NORSdj5IKDyFZrMax9XbwxoImUvdfa3w0rJ3WqliVNVP38deo2LseavlNvqFsjzyKZzv+djzW6y9yxnjt6N9VdyOlLq0oq69h+IQ5T/tAFZl/q2wivPWQ6KGFtjkcmYei8cOn72U+1wjAT2dUX7qRiy9kY6QIywN0BT7Wva/KmhT7Y06KOCza/qCtFM+xF2MbfDaENPKT36zpu9tj7Zi+jbT0xNwwno5KNfpcRCRnYczkeozsF3veddsObfM90rYewawm4kn8zobS2DhqtQIfPtiMpU230Xj34fwdw9nYK5o8p22dMtlqX8XE4v0G0h6MtjrzXr8QLpuTMXHT5chey1BrUrWWPA2/3Ke+u3xd9aVKAuwN2v9ELCrkMOXkarD4aXWQ2agBYcSQKyZlqzBtd+uxslUHfD0xPn5Vy8Po9fL6loLJg1eTOxbaVqIi1x2/hjfy+YcXNAmcuvx+8iQ//0gXnijueqfKcuZWMIT+HSd/3a+aN+WPam3xvNOxFqNetoSd+frotxv52BGdvp8Df3R6DS5kNzslOiREd/KVA39Rlx/HvudgSZ/8mKk65ztCnTZuG3NxcBAYGonfv3tK/OnXqlP7DJAlt4Ilvh7eWgjrPdQ+y8IjK75EWvqjjZo/byVkY2NIXH5Sx1re8vJxV+H1iJ+nitXOQO74d3hoqpQJLnwnBk/PCkJCei471auGHkW2KPYlydbDB0okheHKurkxs7p7r0mMt6rhg7uh2cFIpsfiZjnhybjhuJWWhmZ8L5o9pD2c7G/w2oSOGzgtH5L1MNPZxwq9jO9zXVMW2Sjnmj2kvfSjMMxiPfjYaw5lhlAo5fn66LUb9ehino5Ph46LC0okhcHe0xU+j2kp19O0Da0lp6fa2CozpHIj/7boGD0dbLH0mpNLu9MpkMnw0JBhxqdn470IcHG0VWPJMxxLv7LzzcFPEpWbjr1N3jEoHVEo5fhvf4b6DHJO6ByE2JQeLwiKk4AoAONianuK5LIZ38EdcSja+3a6brXD2U63xeNs62HP5LnZdiseiAxH49PEWWBp+U7ozaujzJ1pK6dcfDQ6W1vl4SLDFAlIA0D6wFv43qh2m/KGbJlg/MwugmwEn7FoCLsWmQa0xvmeh/748pZ/Fqe/piEUTOmLUgkM4FpmEY5FJJtc7ejOxTKnbn/9zAdlqLXo18cIXT7aEjUKOpRND8NR83QXfiytO4pexpk/QiCrLpdhUKWuzNPP2XsdcgynMl4RF4KO/Lxito5DfwL63eqOOmz2O5x8jJWWwPNTcB5893hLvbjiLn3ZehY+Lqlx9dyxFf4NJJgOE0JVfPNW+rtF5hWFms6FT0cn48smiPf5ORCYDMP59+bs7YPGEjhjxy0Gcik42CgA+07VekfeH57oFYfqKE1h2KBLTejVAXGo2hs0PR0J6LrLUmvuesOREVBJORyfDVinHtF4NMblHEJ6cG46YlGwM71C3xN5aCrkMvZt4Y/3J29h1KR6dgjyQp9HiSn7pUll7jdrZKLBgXAcMm6+7cde7qXepd/DdHGwxrENd/H4wEiH1it5QqGpD29XBt/9dRlRiJrZfiMVDzX3x6p+nsOVsbLE/4+9uj/7BJZcYVpZpvRogNiUbfxyKhFIuw7wx7dGijiuCa7sgJiUbi8Ii4OZgU2oT6/J6qn1dxKVmY/a2y/hk8wV4O9tJmX/mFJ+ajc8264Jvbw5owoCUGbSq64aQ+u44EpGINv5u+N+odsWe7zjb2WBJ/vXO7eQsNPdzwbwx7eBsZ4NF+dc7UYmZRtdKxdl06g7+nNIFKZlqbDuvO/6e7W65YChVX+XKlMrJyUF4eDj27t2L3bt3SzPwNWzYUApQ9erVCz4+ZauBtVbmmn1vx4U4JGeppVKm6ubsrRQcjriHMZ0D7ytAUxbX76Zj96V4jOjob1SyFJGQgZ0X4zCsgz9c7Uuvy41OzMTKI1HSSa2bvS3Gdgk0Sr29k5yFf87E4Ml2dYzSfGNSsvD36Tt4om3dSgvu3EvPwR+HIpGSpctmcrBVYFRIQLElXcmZuVh7/Bb6N/ct0tx6+eFIDGzhZ9QwMytXg0VhERgQ7HPfQR9TstUarDwShZD67giuXXpD6dw8LZYfjkRUfumcXCbD4Na1K1S7bopWK7DqaDSuxhdkKfRt6nNfsycJIbDx1G242dtKGQvh1xLw9MLDsLOR46PBwZix4SyEAAa29JVStDsHeWBAoRPgf8/qyv/Mcae2LMKvJWC7QW+rRt7OGNnRH4/NCcPZ2ylYPKGjtM8A0Pj9f5Gbp0XYO30qbbbPs7dS8Nep21IjYj21RotVR6J1pQg9gjCjhBKHxIxctP9sO4SJGaOORybi6V8PIydPi5Ed/U1evBJVFv3ECo28nUp839Fl29yFrVKOZc92QkJ6jtTYeVBLP3i7qHDgagKuxqdLJT4Df9yPCzGpRiVmxdH3SJLLgF/GdsBDza37vGz2tkuYs/s6BreujZ0X45CZq8GyZztJv0PDzMq2AW5o4++GbLUWfx6NglaYns3tsTlhOB2djB9GtMHjbY1vnl64k4oNJ28hL7/Hh4ejLSb3aFAk88mw39PrDzXGuhO3cDO/XMrHRYX9b/W5r2wpU5kFUfcy8dep2xjftZ7RzSlT/jmjawjewMsRO1/vhWvx6ej33V7Y2yhw/uMB5erDcjctB2uOR+OpdnVLbLmgl5GTh2WHIvFYmzpG/bnMRf+aaR9YCy3ruGJJ+E3YKGQY2TEASoXxfstlMjzRto5ZJ77QaAVWHY1CI29no0xgrVZgxZEoNPR2qtQsKT0hBGZuOo/fD0YazQJnToblkmuf78LPXDOJupeJv8/cwehOAWUqibydnIUtxVzvLD8UhYzcvBJ+Gth8JkaaATvIywkrDkehR2Mv/D4x5L73hR4899VTKjs7GwcPHsTu3buxZ88eHD16FGq1Gnl5Jb+IrZ25glJEVD0ZTout93SnAHz+eOVMXW1pT84Nw4moZCwY297oznLQjH+gFWXvH3K/9LM8AcCHjzbHxGKmzdav19zPBVtMzBj13/lYPL/sOLQCeLlvI7xaTUqayDpk5ubBViEvctc5PUe33DAooS/3+uKJllIPOVMMpzB3tlMiJ0+L3DwtxnYOxCePBUMmk2HXpThMXHIMzioldr7eE52/3AmtAA7O6AM/15KDwkIIvLPuLP48Fg07GzmWP9e50rMyKtO05cex5WwsPni0OaITM7Ek/Ca6NfTEJ48FI0utwdRlJxCVmImWdXQTNDjl96DT904EgC+fbIlR+Vmx2WoNWn60DWqNwL43e9/XZAeGs+YCQN1a9sjJ05Y4M15xhBC4lZQFtUaLexm5GPHLQWgF8N+rPYpMYV8WqdlqaRa3lZM640pcGmZuOo/W/m74a3rZZu6qrgybl+v9NKothrQuueToQaDRCmkWOGc7JRaM7SDNtlicurUcKqXxc2ZuHkK/2oXkTHWZS0ipejKcAVvvj2dD0L1RxWfvowfXfb37yOVyyOVyyGQyacaxgICyl8l89NFH0s/q/zVtWjAlaGxsLMaOHQtfX184OjqiXbt2WLduXZm3/9VXX0Emk+GVV14pz24REZVIJpPhOYP05Iea+xjNsFjd6S++DU/2NVohzYJka6YSuCfb1cVbD+tmgPr0nwvYfOaOyfV2XtT1WuvbzNvk4/2DffHp47rZTX/ceRUrj0SZXI+osHvpOej0xU4M/jkMyZm50vKTUUno8sVODJsfDm3+gZGQniOVg/Vpavq1qKeQy/C/UW3RPrAW0rJ1zX4HBPvgoyHB0vtIr8beCPJyRFpOHt7beA5aoZs5rrSAFKB7j/r8iRbo09Qb2WrdTKBp2eoK/haq3o27uvK9IE9HPNO1HmQy4MC1BPT5di8G/XQAUYmZCHB3wKIJHaWAFACM6RyIF/voSuje23BWmmzm3O0UqDUCnk628He/v6zO4R3qwjn/OWvltwKYEFoPAPDrvgiU597urK2X0f3r3ejz7V4Mm68LSPVs7FWhgBQAuNjZSFk4o349JJWIN/Ot/Mxoa+PtYochrQsy4N4f1IwBqXwKuQw/jGyDjvV07y+jfj2EPt/uLfFf72/2SE3T78e6E7eRnKlGgLsDHmpunnJJsozg2q74ZWx72ORnJjbxcUa3huadEZ5qjnJdWeTm5mLfvn345JNP0KtXL7i6umLKlCmIiYnBpEmTcPXqVdy4caNcAwgODkZMTIz078CBA9Jj48aNw+XLl7Fp0yacPXsWTz75JIYPH46TJ0+WsEWdo0eP4pdffkGrVmy0RkSV79FWtdGjsRf6NfPBTyPb1qhZNGyloFTBrDCGX5uzL9PUng0wvksghABe+/M0Dl6/Z/R4bp5Wmla5pEDA6E6BeMng4nWHweQARMU5FpmEtOw8XIxJxXNLjyFbrcGNu+mYuOQo0nLycPpWCvZc0QVF91y+CyGA4NouZSpnsrNR4LfxHdC9kScGtfLDj4XeR+RyGZ7Nzw7cnv96bVuObCd9L8IgT0ckZuTiz6PR5dl1s9FqBW7e0wWl6ns6ItDDEZO7B8HV3gYudkq42CnRqq4rlk403RfxtYcaY0CwD7QC+GWf7hz0RFRB/637vVngbGeDNx9ugkbeTvhtQkc08HLC6E4BsLdR4EJMKg7euFf6RqArv18afjN/m7r9qu1qd9/N6J/tVh/ezirpd+Xnaocn2j4YvV5f7NMQDb2d8Gq/xtWyP2tVsrNRYOG4jujR2Et6bRT3T6WU43ZyFsYvPoLEjNzSN14MrVZg0QFdz9CJXevVqPMiMq1rQ0/8MKIt6nk4YMbApjXm5iyZX7kanbu6usLb2xuDBw/G9OnTsWrVKvj63l8UXKlUFruN8PBwzJs3DyEhutrU999/H99//z2OHz+Otm3bFrvN9PR0jB49Gr/++is+++yz+xofEZEptkp5ja2b19/1MgxE5Rp8baMw30mHTCbDh4ODEZ+Wg3/PxWLyH8ew5vkuUhPfYzcTkZaTB08nW7Su61bitl59qDFiU7Ox+tgtvLDyBFZM6lxi02iiSzEF/emORSZh+vITuBKfhqRMNWwVcuRqtFi4PwJ9mvpgZ35/Nv3kBmXh5mCLP57tVOzjQ9vVxTfbLkuzqJb39epgq8TkHkF4Z/1ZLA67iQmhRZt5W1psajay1Voo5TLUraXLapoxsFmJfeQMyWQyvNinEbadj8OWszF455GmBU3OK6lkcVyXehjXpZ70vZuDLZ5qXxd/HIrEb/sjisyiaMryw7p+ls38XLDlpW6VdvHWt5kPjrxn3T3Dqko9T0fseK2npYdhtVwdbMp0nhKXmo0n54YjIiEDE5ccxYoKzla761I8IhIy4GKnZHPzB8igVn4WaahPNUu5zkxat26N2NhY7Nu3D/v370dYWBju3SvbHaLiXL16FbVr10ZQUBBGjx6NqKiCsorQ0FD8+eefSExMhFarxapVq5CdnY1evXqVuM3p06dj0KBB6NevX5nGkJOTg9TUVKN/REQPKhsT5Xt5Bl/byM17UauQy/D9iDYIqeeOtOw8jF90BLeTswAAOy/pslR6N/EutamvrqSpJXo38UK2WotnlxzF9bvpVT5+qr4ux+nOBx4O9oWtQo6dl+IRnZiFQA8HrJ3aBQq5DOHX7+FUdLKUsde3lNK98rCzUWBs54LZ8yrSF+rxtnXg4WiL28lZ2Hq++NnJLEVfuhfg4VDhgFmLOq7oEuQBjVZgSViEUaZUVdGXGe68FI/H54ThiblhmLD4CGJTsousm5unlbKknutWn9kEZFV8XOywdGII3BxscCo6GY/8uB9PzNW9pj//54LRDSqNVmD2tkv45O8LyM0rWK7VCszfq5ut7elOgXBUlT+oRUQPrnJ9+h86dAj37t3D119/DXt7e3z99dfw8/NDixYt8MILL2DNmjWIj48v8/Y6deqEJUuWYOvWrZg3bx4iIiLQvXt3pKXp7kyuXr0aarUaHh4eUKlUmDJlCjZs2ICGDYufgnfVqlU4ceIEvvzyyzKP48svv4Srq6v0z9+f0X0ienDZlFC+p5TLyjWjU2Wxs1Hg13Ed0MjbCXGpORi/6AiSM3MNslPKFgiwUcgxZ3Q7tK7riqRMNcYvOoL41KIXkURAQabU6M4B+GFkG8hkupnalj4TglZ13TAwfybN1/48hYxcDTydVGhZyTN8je1SD852Sng5q9Dcr/yTr9jZKDAmP7D16/7y9UAyh4gEXWA4yGDm2IrQ9/n7/WAk4tNyoJTL0Kpu1c22FuTlhIfzJ4I4FZ2Mk1HJ2HP5LpYfjiyy7uYzdxCflgNvZxUGs+8RWaGG3k74bXwH2NnIEXkvEyejdK/pX/dH4N31ZyGEgBACH206jzm7r2NRWATeXncGWq1u+Wf/XMSxyCTYKuQYHxpY+hMSERkodxjbyckJDz/8MB5++GEAQFpaGvbv34/t27dj0qRJSE9PL/Pse4888oj0datWrdCpUycEBgZi9erVePbZZ/HBBx8gOTkZO3bsgKenJzZu3Ijhw4dj//79aNmyZZHtRUdH4+WXX8b27dthZ1f2maFmzJiB1157Tfo+NTWVgSkiemCZLN/LvyNaeKptc3LNbzL85NxwXItPx4hfDuHmvUzYKGToVo7ZXhxslVg0oSOGzgvHzXuZmLD4KP6c0hnOpUy/Tg+WrFwNIvJ7HTXxdYa3sx12v94LtRxs4eqge608260+/j59BzcSdOv1aepV6UFbL2cVtr7SAwqZrMKzY43pHIh5e6/jdHQyjkcmoUM999J/yEz0v7v69xmU6t1E1xhen3nVvLYL7GwU9z2+knwzrDWGd/BHnlbgRFQS5u25jh0X4/F6/ybSOkIILNyv67MzPrRepcxwRlQV2ge6Y88bvXE2f8KAO8lZ+Pjv81hz/Bb8XO2gslHgj0ORkMkAuUyGDSdvw8fl/+3dd3iUZdbH8d+UNEJISCEhlFACCdJ7VRRQXlEQRVFkUQRdVIqKuquuytpxV7Gi6EqzIIgIq+iqFEVQaqihCSEQSCChJSG9zLx/JBkyZAjJMKl8P9c11zLPPHPmnsR9MveZ+5zbUwHe7prze8F/4/++o0OZNmMAgOKcXltpsVi0efNm/frrr/rll1/0+++/Kz09XWFhzmfH/fz81Lp1ax08eFAxMTF6//33FR0drbZt20oqKB9cu3atZs6cqVmzZpV4flRUlJKSktSlSxfbsfz8fP322296//33lZ2dLZOp5AcUDw8PeXiUvlUqKtaCtm3V7uGH1WHixKoeiiQpNz1dW19/XfG//qqs06cV8Ze/qOvTT1f1sIBK4bB8r3CHMbcq7kcT6uel+eN66PZZf2h/YsEqll4tAux25CqLgLoemj+uh0Z8+If2HE/VQ59v1Zyx3ZkwXsF+P3hKjfy81KwwOXIg6Zys1oKVUUF1Cz4jNLsgcdKpiZ+6N6uvzYcLysUGRFZMb59Gfpc3yQvy8dCtnRpp0Zaj+teP+zWsU8FqnTYNfdQ1rHITVHGnM5R4LkvdCxNjsYVJqRZBdS8rblFj+H8sjZZUsaV7Rbw9zLqusFyza1h9fbQmRnuPpyohOVOhhb+z9TGnted4qrzcTBrds+w7VANVIcTX026jBg+zUU99s0vvrj5oO/b8zVeprodZT36901ayJ0nPDInULZ2ujCb7AFyrXJ++N23apH/9618aMmSI/Pz81Lt3b82cOVMNGjTQu+++q0OHDik2NtbpwaSlpSkmJkYNGzZURkbBtqTGC3qXmEwmWSwWR0/XwIEDtWvXLm3fvt1269atm0aPHq3t27c7TEjVJGnHjmnzyy/ruyFDtKhrVy3q2lXLhw7V5pde0tn9+6t6eLXK7v/8R4eWLVOru+5S7+nT1XzYsKoeElBpzKWU77lXgybJESE++s893WxjKW3XvdKEBXhrztjuquNu0rqDp/S3r3fIYqlepU2oHJ+sPaTRn2zUvXM32crbikr3Ihv6lNoDqGjXL3eTUVe3qr7bYY8vLG/bdPiMnl0WrWeXReuujzcosZLLV8fN36w7Zq3X5sNnJJ1PSl3uSilJuq1zY9UvXMXmqibnZeXv7W5LhK3ed76VxSeFu5Hd0a2x/Oq4V+qYgMt1V4+menRQK9v9Cf1b6L6+zXVHtyZ6cvD5FYHj+jbXA+yACMBJ5fpquVevXgoJCdF1112nGTNm6LrrrlPLli2dfvEnnnhCQ4cOVVhYmBISEjRt2jSZTCaNGjVKfn5+Cg8P14QJE/TGG28oICBAy5Yt04oVK7R8+XJbjIEDB+rWW2/VpEmT5OPjo3bt2tm9hre3twICAkocr2nif/1V6554QkaTSc1uukl+kQXbbqbGxuroypU6sGiRbvn5Z3mH0qvAFRI3blRghw5q//DDVT0UoNK5V9PyveJ6tQjQnLHdtWLPCd3Z3fly6w6N/fTB6C66f/4WLdueoGBfTz19Y9l2/ULt8O2OBL38/V5J0pHTGdp34pzaNKynvScKmpwX7fR4Mde3CdaTgyPUxL9OtW7u2zrYRy/e0lZ/HCzYoGZr3FklncvW6n1JGtWjclbwnEjJ0sGkgh5SH/92SB0b++nomYIvIS+3p5Qkebmb9N6oLlp78KRubHd5u0M7Y0CbBtpy5KxW7U3UX3qF6WBSmlbvS5LBIN3Xt3mljwdwhUcGtlL9Ou7KybNofL/z/x0/fG1L1fNyU3p2nv56dQsa+ANwWrk+Pe3du1cREREOH7Narfrxxx81e/Zsff3112WKd+zYMY0aNUqnT59WUFCQ+vXrpw0bNigoqKA3yA8//KCnnnpKQ4cOVVpamsLDwzV//nwNGTLEFiMmJkanTp0qz9uocc7Fxen3J56Qd8OGGjhnjryC7HundJo6VQcWLpQu8ccgLyND5jp1KnKoNZrVYpElN1cmDw9lnTkj38tIuAI1maPyvaIEVVWX7xXXr1Wg+rlgZcq1EQ00fUQHPbF4hz5ac0gNfDwdltmYjQandweDa1mt1nJNgC52/h8HT+nxr7ZLkuq4m5SRk6/V+5LUpmE97T9RsFIqIsSn1NhGo0ETr7v4BizVyT29m+me3s0kSe+vPqA3fv5Tq/YmVlpSqmhXPElauTdRv/15Uhar5O1uUpCPa9oouOq64IyBkcH614/79XvMaWXk5Gl24SqpQW2CXbISDKgKBoNB9/Zp5vB48d1BAcBZ5UpKOUpIxcbGas6cOZo3b55OnjypQYMGlTnewoULS328VatWWrJkSannHD58uNTHf/311zKPp7raO2eO8jIz1euVV0okpCTJaDYr4i9/sTu2/plndPTnn3XjN99oy6uv6mRUlEJ69dI1772nvIwM7Xz/fcX99JOyTp+Wd6NGCr/9dkWOHWv70J4WH69vb7hBvV5+WS1uvdUu9oX9n3bOnKnoDz7Q0B9+UPRHH+nY6tWS1aomgwap27PPyux1vhdGfk6Ots+YocPLlys/O1vBPXqo+3PPlflnsf+LL3Rw0SKlxcfL6O4unyZNFHnPPWp288229520ebNuWbHC7nlFY7x7926799Fq1CgFduqkPR9/rNQjR9RvxgytnTJFkpR+7JgWFPYzG/bzz/IKCtLujz5S/G+/KS0uTpb8fPm3aaMOkyYpuGdPu9ezWiza/8UXilmyROeOHJGbt7f8r7pKHaZMUUCxVXux332nfZ9+qtSYGJk8PBTSt686P/64vBs2LPPPBHA1N3PJ8r2inlLVoXyvItzetbESU7P075/266Xle/TS8j0lzvHxMOuV29prGLtnVanDp9I14sM/1Dc8UDNGdrxkojA6PkX3zdus/q2D9MYdHW3HT6RkacJnUcrNt+qm9g3Vu2WAnl0WrVV7E/XwtS2193jBSqk2l1gpVVMNiAzWGz//qXUHTykrN7/Cm4JL0tYj55NSVqv00vcF/z9rHuRdK1ZZtA6uq0Z+XopPztTyHcf1zdZjkkRZEwAApXBqdpGdna0vvvhCAwYMUEREhF599VVNnTpVSUlJdqV1cI34NWtUt2lTBXboUK7nWfLz9ctf/ypPf391fvJJNbn+elmtVq2ZNEn7Pv1UDfv2VZe//U31mjXTtjfe0NbXX7+sca57/HHlpaer06OPqungwTq0bJl2ffCB3Tkbn39e+z/7TCF9+qjTY4/JaDbr14ceKlP8g4sXK+rVV1WvZUt1/fvf1WHiRNWPjNSpXbucHnPixo3a+vrravp//6euTz0lr6Ag9Z4+XR7166t+ZKR6T5+u3tOny7N+feWmpytmyRIFd++uTlOnqv3DDyv77Fn98te/6uzevfbv87nntHX6dNUJCVGnqVN11f33y+ThoVM7dtjOif7oI61/+mn5hIWpy9/+pogxY5S4YYNW3nuvclJTnX5PwOVyM5Ys38vNq34rpVzt4Wtb6sH+LWW6yO5p57Lz9PhX27XuQO1enVvdzVoTo9PpOfp2R4Ke++9uWw8oR+JOZ2js3E06eS5bX0cd05+FzfElae7vsTqXnacOjX315siOGtSmoEn5tqPJ2nv8nM5m5MpokFoFX14D7uqqTUMfhfp6KivXovUxpyvlNYtWSt3RtbGkgnJJSWoeWDt+xgaDQQPbFPS4e+G73crOs6hDY191b1a5/a0AAKhJyrVSKioqSrNnz9aXX36p8PBwjRkzRl9++aUaN26swYMHq1692vltYlXKTUtTZlKSGg8cWOKxnNRUWfLzbffNXl4ye57fMcOSk6Omgwer02OP2Y4dW71aiRs3qsOUKWo3YYIkqfXdd2vtY49p/+efq/Xdd8unqXPL+Ou3aaNeL71ku5+dkqJD33yjzo8/Lkk6u2+fDn/3nVrddZdtdVTru+/W73/7m5L//POS8RN++02+4eG6+q23nBqfI+cOH9aQpUvlG36+9CKwQwftfPddeQUHq/nQobbjRg8PDfv5Z5nczzcqDb/9di2/+WbtX7DA9t4TN27UoWXL1Povf1G3Yjv2tRk71jZ5Sk9I0K6ZM9VxyhS1/etfbec0uf56/e/223Vg4UK740BlcnPQ6Dwnv3r1lKoIBoNBT90YqUcHtVL+BQ3PrZKeWrJTy3ce14OfR2nRhF5qG+pbNQO9gp1Ky9Y32+Jt97/cFKeGvp6aMrBViXNPp2Xr3rmbdCotx3Zs9tpYvX57B6Vl52nBpjhJBf1SPN1MCvE1qW1oPe1OSLXtKNU80LtSVhBVBYPBoAFtGujzDXFatS/RtotcRcnOy1d0fMEXLhOvC9fuhFTtKVyNVptK2wa2Cdan648oPafg89n4fs1rxSowAAAqSrm+8u7Zs6c8PDy0YcMGbd68WVOmTFFwcMVsf4wCuWkFDUEd9YJaOXasvunXz3Y78OWXJc5pdeeddvcTfvtNBpOpRLlfm7FjJatVCWvXOj3WViNH2t1v0KWLspOTbe+hKPaFrx05ZkyZ4rv5+CgjMVGnL2Nl1IUadOtml5AqjdFksiWkrBaLspOTC0r42rXT2T3nS33iVqyQDAa1d7ACrOiD6dEVK2S1WNR08GBlnT1ru3kGBsqnaVMlbtrkgncHOOd8+V7xnlIF/67NK6WKeLqZ5O1htrvV9TDrzZEd1auFv9Ky8zR27mYlJGdeNMbBpDRN+2+0rYnzlSojJ08vfrdHGw65ZiXO5xuOKCfPoo5N/PTS8IJS6Bkr/tSizXElXnfc/C2KPZWuRn5e+nB0F0nS0u3xOnkuW19tPqpzWXlqEeit6yLOJ2MGFiZmlu9MkHTpJuc13cDIgs9wq/cm2b40+WLjEX3w68FSV6A5Y3dCqnLyLfL3dldYQB3df/X5hsmuaHJeXfRs7q867gWJzFBfTw1pTzk+AAClKddKqYEDB2r27NlKSkrSmDFjNHjwYL79qWBm74IPankZJSc2Pf75T+Wlpyvz9Gmt//vfSzxuMJtVJ8R+95n0hAR5BQXJzdv+A2C9FgX9DjKOH3d6rHUu6IPkXrhyLic1VW516yo9IUEGo1F1m9jvlFWvedl2pLlq/Hid2LBBP911l+o2baqGffqo2U03KahLF6fH7N24cbnOP7RsmfbNn6/UQ4dkyctzGCft6FF5NWggDz+/i8Y5d+SIZLXqu2JN+4szmqvvDk6o/cwOyvfyCv9dW3tKlYWH2aSP7+mmkbPWa9+Jc3p31QFNH+G4rPrfP+3TT7sT9cv+k1ryUB+XNXGuaZbvPK45v8fqi41HtOCBnuoa5u90rKzcfH22/ogk6f5+zTW0Y6hOpGRq5i8xemZptIJ8PDQgMlh5+RZNWrBNO44my6+Omz4d30MtAr3VqYmfth9N1qfrD2tp4Wqrcf2ay1isXHNAm2C9u/qgihbKRV6iyXlN17tlgDzdjEpIydLe4+e0/tBpWz+19o18dXWrkn0snVXUT6pLUz8ZDAbd3CFUb/78pxJSMtWuUe1J/nm6mTQgsoGW7zyucf2aXxGJfAAALke5Zr4//fSTjh49qrlz5+qhhx5SZmam7ixciUNyqmK4+/jIKyhIyQcOlHisqMdUWnx8icckyeTmJoPRuQ9DF/t9Fi8XLPEck+MSB1d92+rbsqWGLl+u+DVrdHzdOh1dsUIHFi5Uu4ceUodJkwrGcJFxWy8ybpNH2SeKsd99pw3/+IcaDxyoNvfdJw9/fxlNJu3+z3+UdvRoud6L1WqVDAZdO2uWjA5+buySiKrk7qDR+ZVQvlcW9Tzd9PLwdrp91np9sy1ej98QUSLhlJWbr7WFfafizmRo3LzNWvjXXvL2uPKSzTFJBStls/MsGj9/i75+sI/CGzjXP2jZtnidTs9RIz8v3diu4AuXJ26I0ImUbC3ZekwPf7FVCx7opYWb4rR6X5I8zEbNvre7WgYVvN4DV7fQxAVb9cGvMcq3WFW/jptGdLH/YqJDI18F1vXQqbRsSVJkw9qTLHHE082kfuGBWrk3SS98t1ubDp+xPfaftbEuTUpti0uWJHVuWtBfyd1s1MK/9lJ8cqbCG9Su5N9Lt7TTLZ0a2VbeAQCAiyt3xqJJkyZ6/vnnFRsbq88++0wnT56U2WzWLbfcomeeeUZbt26tiHFe0UKvuUZpcXE6tXPnZcfyDg1V5smTyk1PtzueGluwbXHRaifbKqdz5+zOy0hIuKzXtlosJRI4Ra9dFuY6dRR2443q9corumXlSoX276/dH3+s/OyCCYRbvXolxixJ6ZexAqzI0Z9/Vt0mTXT1O++o+bBhCu3XTyG9e9teu0jdJk2UmZSk7OTki8aq26SJZLWqbuPGCundu8QtsGPHiz4XqGjne0pdmeV7l9I1rL46NfFTTp5Fn284UuLxjbFnlJGTrwBvd/l7u2tXfIoe/DxKq/clavW+RG05fMapZL3FYtXmw2dscTYcOl2i91V1c+hUwd8aD7NRyRm5unfOJiWmZpU7jtVq1SfrCv5W3Ne3mW3HPYPBoOkj2qt/6yBl5Vp010cb9NWWYzIapPfv7qKuYecbTA9uG6xGfl62n9lfeoXJy93+SwGj0aABkecTMbV9pZRU0ANJKvjv1mqVbu7QUEaD9NufJ7X/RMm/p86Ksq2UOv87aeJfR71aBLjsNaqL+t7uuv6qYLtVeAAAwLFyzS7GjRunc8Um/Ndff70WLFighIQETZ48Wf/73//UvXt3lw/yStdm/HiZvLy08bnnlHnKwa5P5ZjchF5zjaz5+fpzwQK74/s+/VQyGBR69dWSJLe6deVRv76SoqLszvtz4cLyv4Gi1+7XT5K0//PP7V/7s8/K9PwLkzwmd3f5tmghWa22UjqfJk2Ue+6czu7fbzsv8+RJHVu50ulxF7GtOiv28z61c6fdjnqS1PT66yWrVbs+/LBEjKKJaJNBg2QwmbTrgw9KTE6tVmupCS2gojlqdF5UvkdSqiARUtQP5/MNR5SVa78Sc/XeREnSDW2DNWdsd3m5mbT2wCmNm7dF4+Zt0e2z1mvqVztkKUdCyWKx6pFF23XHrPW2OHd9vEETPouy/W6qo9jCpNS/bu+g5oHeik/O1L1zNik1K7dccTbGntHBpDTV9TBrZHf7EnA3k1EfjO6iDo19bSv6Xh7eXtdfZd/z0mwyaly/gt+bu8moMb3DHL7WgMI+S3U9zGpc36tc46yJivfUurFdiN65q7MGty1YiTZnXdm/NCpNQnKmTqRmyWQ0qGMTNggAAADnlauWYP78+Zo+fbp8fOy/Oaxfv74mT56syZMns1KqAtQLC1Pff/1Lvz/5pJbffLOa3XST6kdEyCop/dgxHf7+exmMRnmVoel8o2uvVXCPHtrxzjtKj4+XX0SETvzxh46tXq2IMWPsdt5rOWKE9nzyiTY+/7z827ZV0pYtBb2QnFS/TRuFDRmiAwsXKjctTYGdOilxwwadi4u79JMlrX7gAXkFBiqoc2d5BgQo5dAh/blggUKvucbWIytsyBBtnzFDax95RK1Hj1Z+VpYOLFwon2bN7JqROyP02mt1dOVK/TZlihpdc43S4uN14Kuv5NuypV3Pr+CePdVs2DD9+fnnOnfkiEL79ZPVYtHJqCg16NFDEaNHy6dpU3WYPFk73n5b6fHxajxwoNy8vZV27JiOrVql8DvuUJv77rus8QLOcjOV7ClV9G93M9/8S9L/tQ1RIz8vxSdnaum2eI3qUXDttFqtWrUvSVJBcqNTEz/NHttN7606qIycguT57oRULd0Wr+B6nnrqxsgyvd6rP+zVdzsSZDYa1Da0YCXr3hPntHJvop77b7RevbV9tSujz8u36MjpgqRU17D6+nRcD936wR/ad+KcHvwsSnPv6y4Pc9l2ttt4qKCsbEBkA9XzdCvxuLeHWXPGdtdLy/eoR3N/3d3T8S6yd/doqt0JKeoaVl8NfDwdnjMgsoHu7tlUHRr5VrufaUUI8fXU1Otb63hKpqYNbSuTsSDp+r/oE1q6LV5PDC5ZolpeW+MKVklFhviojvuVV8YKAAAurlyfDMpSbtDlMppO4+IaDxigIUuXat+8eTr+xx86tHSpZDDIOzRUof37q9XIkaofeenJjcFo1DXvv6+d77+vuB9/1KGlS+XdqJE6P/GEIseOtTu33UMPKfvsWcX9/LOO/PijQq++WtfOmqVvCldTOaPXyy/Lw99fR5Yv17FVqxTcs6eu/fBDLRs48JLPbXXHHTr8/ffaN3++cjMyVCc4WBGjR6vdgw/azvHw89PV776rrf/6l7a/+abqNm6sjo89pnNHjlx2UqrF8OHKOnVKB7/6Ssd//12+LVuqz/TpivvpJyVt3lzifdZv3Vox33yjbW+8ITcfH/m3baugzp1t57R94AHVa9ZM+z79VNEffCCpoHwypE8fNbruussaK3A5bCul8s5f83MKy/fMTvapq23MJqPu69tML3+/V7PXxerObk1kNBp0IClNx85mysNsVL/wQElSn5aB6tMy0Pbcr6OO6YnFOzRrTYxC6nlobN/SN3v4ZO0hW+naG3d01PDOjSRJP+0+oYc+j9KXm44qpJ6XHhnUqoLerXPikzOVm2+Vu9moUF8vGY0Gzbuvu+78aL3+iDmtJxfv1Nt3dipTiVNRUqNLU7+LnhNY10Pv3NX5oo9Lkpe7STNGdir1HHezUa/e2v6SY6pNpgy0/2+na5i/Ojf107a4ZH224YimXt/6suJvPZJcGLd+6ScCAIArjsFajsYWRqNRBw4cUFBQ6Y0v69Wr2Y1BU1NT5evrq5SUlBr/XgCgvFbsSdQDn25R56Z+WvpwX0nSrDUxmv6/fRrRpbHeHEnPM0k6l5Wr3q+tVlp2nt6/u7Nu7hCqD3+N0es/7tN1EUGae1+Piz535i8H9e+f9stgkGbe3cVu2/gfdh3Xa//bq7SsgpVVZzMKSt2evjFSE/q3tIvz2YYjem5ZtCTp9RHtdWf38yuEftmfpJeX79GTgyP0f+0qf1v6X/Yn6b65mxUR7KOfHrvGdnztgZO6b+5m5VmsemRgKz12iYSHxWJVpxd/VmpWnr6b1E/tG1P+VRm+33lcExdslb+3u1Y8do0C6jq/WuqWmb9rx9FkvX1nJ1tSFQAAQHKi0Xnr1q1Vv359hzc/Pz/Vr8+3YABQkzkq38ujfK8EH0833VPYl+jJxTu142iyVhX2kxrQpvRy6oevbakxvcJktUqPLtqujYdOS5LWHTilRxZu09EzmTqbkWtLSP31mhb66zUtSsQZ0ytMk64LlyQ9szRaq/cVvP62uLN66PMoxZxM16s/7KuShuixJwtK95oHetsdv7pVkF67rWAl0n/WHlJKRun9pQ6dSlNqVp483YyKbFj7G49XF4PbBqtFoLfOpOdo3PwttvLT8voz8Zx2HE2W0SD1bOHv4lECAICartyF/V9//bX8/flQAQC1FeV7ZffooNbaFZ+itQdO6b55m5WckSOpoC9RaQwGg/45rK2SzmXpp92Juv/TLXrplnZ6dlm0cvOturlDQz1aWI5Xx92sUL+LN9x+/IbWOpGapa+jjunhL7Zq+m0d9OLyPcrKLUgkxp3J0Io9Jyp9tVRRk/PmQd4lHru9a2PNXherfSfO6cvNcXrwghVgxRWVfnVo7Eej/UpkNhn18T3ddPusP7TjaLImLdimj8d0te18WFaz1xaUng5uG6KGvrW/cTwAACifciel+vbtqwYNSv+wDQCouWxJKUvJRuckBey5m4368C9dddfH6xUdnyqpoJlzo1KSSEVMRoPeuauz/vLJRm05claPLtouSerdIkBvjuxY5ibgBoNBr93WXqfSsvXr/pO2OB0a+6prWH3N/f2wPlkbW3VJqcCSSSmDwaDx/Zrrya93at7vhzW+X/OL/rd1vp8UK7ErW3iDupp9bzfd/Z+NWr0vSf9YGq3pI8reVP/kuWwt3R4vSbYdKwEAAIpjdgEAsONw9728wqQU5Xsl1C3c+a2Jf0Ei6vqrLr0TahFPN5M+ubebwhvUlVSQ0Pronq5lTkgVcTMZNfPuLupQ2G8pLKCO5oztrof6t5SbyaAtR85qW2Fyp7IUJaVaOlgpJUnDOoUqyMdDJ1Kz9P3O4xeNE3Xk0k3OUXG6hvnrvVGdZTRIi7Yc1dsrD5T5uZ9vOKKcPIs6NfEjqQgAABwqV1IqLCxMJlP5PigDAGoWR+V7eYU9idxZKeVQAx9PfTWht569qU2JZuSX4lfHXV8+0EsvDGurL+7vqXqebk6NwdvDrE/H9dALw9rqqwm9FVjXQw3qeWpYx4LG0kU7+FWGrNx8xSdnSpKaB9Z1eI6H2aR7C3tyfbLukMMdflMyc3UgKU2S1IWd26rMDW1D9NLwdpKkd1Yd0IKNcZd8TlZuvj7bcESS9MDVLcq8ugoAAFxZylW+FxtbeR9oAQBVw5aUKrZSKqfw3/SUuriGvl66/+qSzcjLIsjHQ/f2aXbZY/Cr414izv1XN9eSrcf0v13HtT7mtPzquMnTzeSwrM5VDp8uWCXl6+Wm+nUunmS7u2eY3v/loKLjU7Ux9ox6tQiwe3z70WRJUlP/Ogq8jN3fcPlG9wxTYkqW3l19UM8u2yUPs1FXhV58h+LV+5J0Jj1Hjfy8NLht2VcPAgCAK0u5e0pJ0unTp/X888/rl19+UVJSkizF+o5I0pkzZ1wyOABA5aN8r3Zp07Ce+oUHat3BUxr1nw2247d2bqQ37+goo9H1v9PiO++VtkLG39tdI7o01hcb4/T6j/v05QO95Ol2fkX21sLSva6skqoWHru+oKn+V1uO6fHFO8r0nPv6Nit3c3QAAHDlcCopNWbMGB08eFDjx49XcHAwS7IBoBY5v1KK8r3a4onBETp6NkPp2fmSpDPp2Vq6LV4B3u569uarXP56hwr7SbUow2qsCde01LfbE7QtLlmPLtyumaO7yFSYKDvf5NzP5WNE+RkMBr1ya3uZjEat2JN4yfObB9bRXT2aVsLIAABATeVUUmrt2rVat26dOnbs6OrxAACqWOnle3wJURN1auKnNU9eZ7u/dNsxPbZohz5ZF6sQX0+nyw4v5tDJi++8d6GmAXX00T1dNXbOZv24+4Re+G63XhjWVlartD0uWZLUmSbZ1YabyajXbmuv125rX9VDAQAAtYBTSanIyEhlZma6eiwAgGqgqHwvz2KV1WqVwWAoVr7HSqna4NbOjZWYmq3p/9unl7/fqyVb42VQwe/+0etb67qIBg6fF5+cqeeWRWtMrzBdF+n4HEmKPVXQnLz5RXbeu1CfloF6c2RHTf5ymz5df0TrY07LaDDoXHae6ribFBniU+73CAAAgOrPqdnFBx98oH/84x9as2aNTp8+rdTUVLsbAKDmKp54KirhK1o15Ub5Xq0x4ZoWuq9vM0nS3uOp2nM8VTuOpeif3+5WvqXkTniSNOPnP7V6X5L+sXSX3Uq6C8WeKvtKqSJDO4bqucJSwgNJadqfeE6S1Dc8kJ5EAAAAtZRTK6X8/PyUmpqqAQMG2B0v+kY9Pz/fJYMDAFQ+N2PxpJRF7mYjPaVqIYPBoOdvvkq3dW6sMxk5slitenThdh05naGVexM1uG2I3flJqVn6dke8JCkhJUv/iz6hYR1DS8Q9m56jsxm5ksqXlJKk8f2a65pWgUpIyZIkmQwGdaafFAAAQK3lVFJq9OjRcnNz04IFC2h0DgC1TFH5nnR+hVROYfme2cT1vjYxGAxq39jXdn90z6b64NcYzV4bWyIp9en6I8rNt8psNCjPYtUnaw9paIeGJT4DxJ4uWCXV0NdTddzL/zGjVbCPWgVTrgcAAHAlcCopFR0drW3btikiIsLV4wEAVDGT0SCDQbJaKd+70tzbp5n+s/aQNh0+ox1Hk9WxiZ8kKTMnX59vPCJJeuGWtnrxuz3aeSxFmw+fVY/m/rbnW61Wfba+4LwWZewnBQAAgCuXU7OLbt266ejRo64eCwCgGjAYDCV24KN878oQXM9TQwtL8mavi7UdX7L1mJIzctXE30t3dW+q27o0liR9svaQ3fP//dN+Ld0WL5PRoAf7t6y8gQMAAKBGcmp2MXnyZD3yyCOaN2+eoqKitHPnTrsbAKBmczMWlGRRvnflGd+vuSTp+13HdTDpnFIycjWnMEE1rm9zmYwGje/XTJK0Ym+i9iSkKiUzV3N/j9UHv8ZIkl67rb2ubhVUJeMHAABAzeFU+d6dd94pSRo3bpztmMFgoNE5ANQSbmajlJNP+d4VqG2or/q0DNAfMac1aMZvtuM+nmbd0a2JJCm8gY+uiwjSL/tPasi7a+2e//j1rTWy8DwAAACgNE4lpWJjYy99EgCgxrqwfK8oOUVS6srw2PWttS1ukzJzC75kMhqkyQPCVdfj/MeGRwa11qbYM0rPKTjHbDRofL/mmjQgvErGDAAAgJrHqaRUWFiYq8cBAKhGLizfyyv8X3pKXRm6N/NX9AuDZbEWJCMNkswX/O47NfHTrn8OVn4p5wAAAAClKfOnxw0bNpQ5aEZGhnbv3u3UgAAAVc/NbL9SKqdwpRQ9pa4cJmNBw3s3k/GiySZjGc4BAAAALqbMnyDHjBmjwYMHa/HixUpPT3d4zp49e/TMM8+oZcuWioqKctkgAQCV63z5Hj2lAAAAAFSMMpfv7dmzRx9++KGeffZZ3X333WrdurVCQ0Pl6emps2fPat++fUpLS9Ott96qn3/+We3bt6/IcQMAKlDJnlKU7wEAAABwrTInpdzc3DRlyhRNmTJFW7Zs0bp163TkyBFlZmaqY8eOeuyxx3TdddfJ39+/IscLAKgEbqYLe0pRvgcAAADAtZxqdN6tWzd169bN1WMBAFQTxcv3rFarcijfAwAAAOBizC4AACUUXymVZ7HajlO+BwAAAMBVmF0AAEoo3lOqqHRPktzMlO8BAAAAcA2SUgCAEmxJqbzzpXuSZDbyZwMAAACAazC7AACUYCvfs1hszc6LHwcAAACAy0VSCgBQwvmVUueTUm4mgwwGklIAAAAAXKPMu++9++67ZQ46ZcoUpwYDAKgeiu++V9RTitI9AAAAAK5U5qTUW2+9ZXf/5MmTysjIkJ+fnyQpOTlZderUUYMGDUhKAUANV7x8L6fYSikAAAAAcJUyf+0dGxtru73yyivq1KmT9u7dqzNnzujMmTPau3evunTpopdeeqkixwsAqATFG50Xle+5m1kpBQAAAMB1nJphPPfcc3rvvfcUERFhOxYREaG33npLzz77rMsGBwCoGufL9yzKzbPaHQMAAAAAV3BqhnH8+HHl5eWVOJ6fn6/ExMTLHhQAoGrZyvfyLcq1FKyUMlO+BwAAAMCFnEpKDRw4UBMmTNDWrVttx6KiovTQQw9p0KBBLhscAKBqFG90nptnsTsGAAAAAK7g1Axjzpw5CgkJUbdu3eTh4SEPDw/16NFDwcHB+uSTT1w9RgBAJbMr3yvcfc+dpBQAAAAAFyrz7nvFBQUF6YcfftCff/6pffv2SZIiIyPVunVrlw4OAFA1HJXvsVIKAAAAgCs5lZQq0rp1axJRAFALOSrfo6cUAAAAAFdyOil17Ngxffvtt4qLi1NOTo7dYzNmzLjsgQEAqo6j8j1WSgEAAABwJaeSUqtWrdKwYcPUokUL7du3T+3atdPhw4dltVrVpUsXV48RAFDJ3MzFk1IFK6XoKQUAAADAlZyaYTz99NN64okntGvXLnl6emrJkiU6evSo+vfvrzvuuMPVYwQAVDI3Y7GeUvmU7wEAAABwPaeSUnv37tU999wjSTKbzcrMzFTdunX14osv6vXXX3fpAAEAlc+upxTlewAAAAAqgFMzDG9vb1sfqYYNGyomJsb22KlTp1wzMgBAlaF8DwAAAEBFc6qnVK9evbRu3Tq1adNGQ4YM0eOPP65du3bpm2++Ua9evVw9RgBAJXNUvudG+R4AAAAAF3IqKTVjxgylpaVJkl544QWlpaVp0aJFatWqFTvvAUAt4Kh8z8xKKQAAAAAu5FRSqkWLFrZ/e3t7a9asWS4bEACg6jkq36OnFAAAAABXcnqGkZycrE8++URPP/20zpw5I0naunWr4uPjyxzjn//8pwwGg90tMjLS9viJEyc0ZswYhYSEyNvbW126dNGSJUtKjfnaa6+pe/fu8vHxUYMGDTR8+HDt37/fuTcJAFeoolI9+55SlO8BAAAAcB2nVkrt3LlTgwYNkq+vrw4fPqwHHnhA/v7++uabbxQXF6dPP/20zLHatm2rlStXnh+Q+fyQ7rnnHiUnJ+vbb79VYGCgFixYoJEjR2rLli3q3Lmzw3hr1qzRxIkT1b17d+Xl5emZZ57RDTfcoD179sjb29uZtwsAVxzK9wAAAABUNKdmGFOnTtXYsWN14MABeXp62o4PGTJEv/32W7limc1mhYSE2G6BgYG2x/744w9NnjxZPXr0UIsWLfTss8/Kz89PUVFRF433448/auzYsWrbtq06duyoefPmKS4urtTnAADsnU9KUb4HAAAAoGI4NcPYvHmzJkyYUOJ4o0aNdOLEiXLFOnDggEJDQ9WiRQuNHj1acXFxtsf69OmjRYsW6cyZM7JYLFq4cKGysrJ07bXXljl+SkqKJMnf379c4wKAKxnlewAAAAAqmlPlex4eHkpNTS1x/M8//1RQUFCZ4/Ts2VPz5s1TRESEjh8/rhdeeEFXX321oqOj5ePjo6+++kp33nmnAgICZDabVadOHS1dulTh4eFlim+xWPToo4+qb9++ateu3UXPy87OVnZ2tu2+o/cGAFcS+/I9VkoBAAAAcD2nZhjDhg3Tiy++qNzcXEmSwWBQXFyc/v73v2vEiBFljnPjjTfqjjvuUIcOHTR48GD98MMPSk5O1ldffSVJeu6555ScnKyVK1dqy5Ytmjp1qkaOHKldu3aVKf7EiRMVHR2thQsXlnrea6+9Jl9fX9utSZMmZX4PAFAb2Zfv0VMKAAAAgOs5NcN48803lZaWpgYNGigzM1P9+/dXeHi4fHx89Morrzg9GD8/P7Vu3VoHDx5UTEyM3n//fc2ZM0cDBw5Ux44dNW3aNHXr1k0zZ868ZKxJkyZp+fLl+uWXX9S4ceNSz3366aeVkpJiux09etTp9wAAtYGj8j03yvcAAAAAuJBT5Xu+vr5asWKF1q1bp507dyotLU1dunTRoEGDLmswaWlpiomJ0ZgxY5SRkSFJMhrt82Ymk0kWi+WiMaxWqyZPnqylS5fq119/VfPmzS/5uh4eHvLw8LissQNAbeLuoHzP3cxKKQAAAACu41RSqki/fv3Ur18/p5//xBNPaOjQoQoLC1NCQoKmTZsmk8mkUaNGyc/PT+Hh4ZowYYLeeOMNBQQEaNmyZVqxYoWWL19uizFw4EDdeuutmjRpkqSCkr0FCxbov//9r3x8fGyN1319feXl5XU5bxcArhhFpXr5Fqty8gqSUmYjSSkAAAAAruN0UmrVqlVatWqVkpKSSqxcmjNnTpliHDt2TKNGjdLp06cVFBSkfv36acOGDbZm6T/88IOeeuopDR06VGlpaQoPD9f8+fM1ZMgQW4yYmBidOnXKdv/DDz+UpBI79M2dO1djx4514p0CwJWneKleRk5+iWMAAAAAcLmcSkq98MILevHFF9WtWzc1bNhQBoNzE5VLNSBv1aqVlixZUuo5hw8ftrtvtVqdGgsA4LziO+2lFyalKN8DAAAA4EpOJaVmzZqlefPmacyYMa4eDwCgGiielMrMyStxDAAAAAAul1MzjJycHPXp08fVYwEAVBMmo0HGwkWwReV7ZiPlewAAAABcx6mk1P33368FCxa4eiwAgGqkaGWUracU5XsAAAAAXKjM5XtTp061/dtisejjjz/WypUr1aFDB7m5udmdO2PGDNeNEABQJdxNRmXnWZSenWe7DwAAAACuUuak1LZt2+zud+rUSZIUHR1td9zZpucAgOrFXLjbXnZewQ6rlO8BAAAAcKUyJ6V++eWXihwHAKCaubCxOeV7AAAAAFyJGQYAwKELk1KU7wEAAABwJWYYAACH3EyGC+7zJwMAAACA6zDDAAA4dGESymyipxQAAAAA1yEpBQBwiPI9AAAAABWJGQYAwKELG5tTvgcAAADAlZhhAAAccjPal+tRvgcAAADAlUhKAQAcunBlFCulAAAAALgSMwwAgEMXlu/RUwoAAACAKzHDAAA4dGH5nhvlewAAAABciKQUAMChC8v1TEaSUgAAAABch6QUAMCh4uV77iajDAaSUgAAAABch6QUAMCh4uV6lO4BAAAAcDWSUgAAh9yM5/9EmGlyDgAAAMDFmGUAABxyMxdfKcWfCwAAAACuxSwDAOBQ8USUO+V7AAAAAFyMpBQAwCH3Ykmp4k3PAQAAAMAVmGUAABwyF1sdZTayUgoAAACAa5GUAgA4VLx8j55SAAAAAFyNWQYAwCG7nlKU7wEAAABwMWYZAACH3CjfAwAAAFCBSEoBAByifA8AAABARWKWAQBwiPI9AAAAABWJWQYAwCF3VkoBAAAAqEDMMgAADpnpKQUAAACgApGUAgA4ZNdTivI9AAAAAC7GLAMA4JBdTynK9wAAAAC4GLMMAIBDbpTvAQAAAKhAJKUAAA5RvgcAAACgIjHLAAA4RPkeAAAAgIrELAMA4JC7+XzJXvFSPgAAAABwBZJSAACHzMbzfyLMrJQCAAAA4GLMMgAADtn1lCIpBQAAAMDFmGUAABwqXr7nTvkeAAAAABcjKQUAcIjyPQAAAAAViVkGAMAhNzPlewAAAAAqDrMMAIBDxXfco3wPAAAAgKuRlAIAOOROo3MAAAAAFYhZBgDAoeJ9pOgpBQAAAMDVmGUAABwqXr7nRvkeAAAAABcjKQUAcMit2O577qyUAgAAAOBizDIAAA4ZjQaZjAUrpCjfAwAAAOBqzDIAABdVVLZH+R4AAAAAVyMpBQC4qKJd9yjfAwAAAOBqzDIAABdVlIxyM/PnAgAAAIBrMcsAAFyUubBsz2ykfA8AAACAa5GUAgBcVP/WQQr19VR4g7pVPRQAAAAAtYzBarVaq3oQ1U1qaqp8fX2VkpKievXqVfVwAKBKWSxWGVkpBQAAAMDFWCkFACgVCSkAAAAAFYGkFAAAAAAAACodSSkAAAAAAABUOpJSAAAAAAAAqHQkpQAAAAAAAFDpSEoBAAAAAACg0pmregC1idVq1blz56p6GAAAAAAAAFXOx8dHBsPFd/MmKeVCp06dUoMGDap6GAAAAAAAAFUuJSVF9erVu+jjJKUc8PHxUUpKinx8fMr1PHd3d0nS0aNHS/zQu3fvrs2bN7tsjMSsGTErKi4xa1fM1NRUNWnSxOG1w9mYZUXM6h+zouISs3bF5DpSNTErQk167zVlrMQsf8zSrinVaZzErNkxKyouMatXzEvlVUhKOWAwGEr9QFfa8ySpXr16JZ5vMpmcilkaYlb/mBUVl5i1M6aja8flxrwUYlb/mBUVl5i1MybXkcqNWRFq0nuvKWMlpvMxmdcQsyJjVlRcYlb/mMXR6LySTJw4kZhXYMyKiktMYhLzyolZUXGJSUxiVk816b3XlLESk5jErJ4xKyouMat/zOIMVqvVWqGvcAVJTU2Vr6/vJWsmAaA4rh0ALhfXEQCuxDUFQGVhpZQLeXh4aNq0afLw8KjqoQCoQbh2ALhcXEcAuBLXFACVhZVSAAAAAAAAqHSslAIAAAAAAEClIykFAAAAAACASkdSCgAAAAAAAJWOpBQAAAAAAAAqXa1PSr322mvq3r27fHx81KBBAw0fPlz79++3OycrK0sTJ05UQECA6tatqxEjRigxMdHunClTpqhr167y8PBQp06dSrxOVlaWxo4dq/bt28tsNmv48OFlHuPixYsVGRkpT09PtW/fXj/88IPd4998841uuOEGBQQEyGAwaPv27WWODcA5teHaUdyDDz4og8Ggt99+u8zxAVye2nAdMRgMDm///ve/y/waAFyjul9Tdu/erREjRqhZs2alfuaYOXOmmjVrJk9PT/Xs2VObNm0qU3wAtVOtT0qtWbNGEydO1IYNG7RixQrl5ubqhhtuUHp6uu2cxx57TN99950WL16sNWvWKCEhQbfddluJWOPGjdOdd97p8HXy8/Pl5eWlKVOmaNCgQWUe3x9//KFRo0Zp/Pjx2rZtm4YPH67hw4crOjradk56err69eun119/vRzvHMDlqA3XjiJLly7Vhg0bFBoaWub4AC5fbbiOHD9+3O42Z84cGQwGjRgxohw/CQCuUN2vKRkZGWrRooWmT5+ukJAQh+csWrRIU6dO1bRp07R161Z17NhRgwcPVlJSUplfB0AtY73CJCUlWSVZ16xZY7Vardbk5GSrm5ubdfHixbZz9u7da5VkXb9+fYnnT5s2zdqxY8dSX+Pee++13nLLLWUaz8iRI6033XST3bGePXtaJ0yYUOLc2NhYqyTrtm3byhQbgOvU1GvHsWPHrI0aNbJGR0dbw8LCrG+99VaZ4gNwvZp6HSnulltusQ4YMKBM8QFUrOp2TSnuYp85evToYZ04caLtfn5+vjU0NNT62muvlfs1ANQOtX6l1IVSUlIkSf7+/pKkqKgo5ebm2n0LEBkZqaZNm2r9+vUVPp7169eX+AZi8ODBlfLaAMquJl47LBaLxowZoyeffFJt27at8DEBKF1NvI4Ul5iYqO+//17jx4+v8LEBuLTqdk25lJycHEVFRdmNz2g0atCgQdVifACqxhWVlLJYLHr00UfVt29ftWvXTpJ04sQJubu7y8/Pz+7c4OBgnThxosLHdOLECQUHB1fJawMom5p67Xj99ddlNps1ZcqUCh8PgNLV1OtIcfPnz5ePj4/DUiAAlas6XlMu5dSpU8rPz2fuA8DOFZWUmjhxoqKjo7Vw4cJKf+24uDjVrVvXdnv11VcrfQwAnFMTrx1RUVF65513NG/ePBkMhgoeJYBLqYnXkQvNmTNHo0ePlqenp4tHCKC8asM1BQAkyVzVA6gskyZN0vLly/Xbb7+pcePGtuMhISHKyclRcnKy3bcKiYmJF23Q54zQ0FC7XfOKltmGhISU2BHD1a8NwHk19dqxdu1aJSUlqWnTprbH8/Pz9fjjj+vtt9/W4cOHXTZGAKWrqdeR4tauXav9+/dr0aJFLhsXAOdU12vKpQQGBspkMjH3AWCn1q+UslqtmjRpkpYuXarVq1erefPmdo937dpVbm5uWrVqle3Y/v37FRcXp969e7tsHGazWeHh4bZb0cW7d+/edq8tSStWrHDpawMov5p+7RgzZox27typ7du3226hoaF68skn9dNPP7lsfAAurqZfR4qbPXu2unbtqo4dO7psXADKp7pfUy7F3d1dXbt2tRufxWLRqlWrmPsAV7Bav1Jq4sSJWrBggf773//Kx8fHVq/s6+srLy8v+fr6avz48Zo6dar8/f1Vr149TZ48Wb1791avXr1scQ4ePKi0tDSdOHFCmZmZtm8HrrrqKrm7u0uS9uzZo5ycHJ05c0bnzp2zndOpU6eLju+RRx5R//799eabb+qmm27SwoULtWXLFn388ce2c86cOaO4uDglJCRIKvjjIhV8G8K3CkDFqOnXjoCAAAUEBNg9x83NTSEhIYqIiHDRTwlAaWr6daRIamqqFi9erDfffNN1PxwA5Vbdryk5OTnas2eP7d/x8fHavn276tatq/DwcEnS1KlTde+996pbt27q0aOH3n77baWnp+u+++5z8U8LQI1RtZv/VTxJDm9z5861nZOZmWl9+OGHrfXr17fWqVPHeuutt1qPHz9uF6d///4O48TGxtrOCQsLc3jOpXz11VfW1q1bW93d3a1t27a1fv/993aPz50712HcadOmXc6PBkApasO140IX254ZQMWoLdeRjz76yOrl5WVNTk52+mcB4PJV92tKbGysw+f079/f7rz33nvP2rRpU6u7u7u1R48e1g0bNlzujwZADWawWq1WZxNaAAAAAAAAgDNqfU8pAAAAAAAAVD8kpQAAAAAAAFDpSEoBAAAAAACg0pGUAgAAAAAAQKUjKQUAAAAAAIBKR1IKAAAAAAAAlY6kFAAAAAAAACodSSkAAAAAAABUOpJSAAAAAAAAqHQkpQAAAAAAAFDpSEoBAAAAAACg0pGUAgAAAAAAQKX7f0/1A0b0R/G3AAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from matplotlib.dates import MonthLocator, YearLocator, DateFormatter\n", "from matplotlib.ticker import MaxNLocator, MultipleLocator\n", "\n", "# Get height of ground surface\n", "ground_surface = df[\"mv_mtaw\"][0]\n", "\n", "# create a plot with 2 subplots\n", "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 6), \n", " sharex=False, sharey=True)\n", "\n", "# Plot entire time series in the upper plot\n", "df['peil_mtaw'].plot(ax=ax1, title='Water heads `Put ZWAP205`')\n", "ax1.xaxis.set_major_locator(YearLocator(5))\n", "ax1.xaxis.set_major_formatter(DateFormatter('%Y'))\n", "\n", "# Plot the data for 2011 in the lower plot\n", "df['peil_mtaw'][\"2011\"].plot(ax=ax2, title='Water heads `Put ZWAP205` year 2011')\n", "ax2.xaxis.set_major_locator(MonthLocator(interval=3))\n", "ax2.xaxis.set_major_formatter(DateFormatter('%Y-%m'))\n", "\n", "# Adjust configuration of plot\n", "for ax in (ax1, ax2):\n", " ax.set_xlabel('')\n", " ax.set_ylabel('head (mTAW)')\n", " for tick in ax.get_xticklabels():\n", " tick.set_rotation(0)\n", " tick.set_horizontalalignment('center')\n", "\n", " # Only draw spine between the y-ticks\n", " ax.spines['left'].set_position(('outward', 10))\n", " # Hide the right and top spines\n", " ax.spines['right'].set_visible(False)\n", " ax.spines['top'].set_visible(False)\n", " ax.yaxis.set_major_locator(MultipleLocator(0.2))\n", " \n", " # Add the ground surface (provided in the data) on the subplots\n", " ax.axhline(ground_surface, color = 'brown')\n", " ax.annotate('Ground surface', \n", " xy=(0.05, 0.68),\n", " xycoords='axes fraction',\n", " xytext=(-25, -15), textcoords='offset points', \n", " fontsize=12, color='brown') \n", " \n", "fig.tight_layout(h_pad=5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Pandas package provides a the functionality to further analyze and process [time series](https://pandas.pydata.org/pandas-docs/stable/timeseries.html) data. Particularly, the [`resample`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.resample.html) function can be useful." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For example, calculate the yearly minima and maxima of the time series:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_11791/3158431998.py:1: FutureWarning: 'A' is deprecated and will be removed in a future version, please use 'YE' instead.\n", " df[\"peil_mtaw\"].resample(\"A\").agg(['min', 'max'])\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
minmax
datum
2003-12-3158.2658.36
2004-12-3158.2258.36
2005-12-3158.1858.35
2006-12-3158.1058.42
2007-12-3158.2858.53
2008-12-3158.3258.57
2009-12-3158.2458.51
2010-12-3158.1858.53
2011-12-3158.0358.53
2012-12-3158.3058.52
2013-12-3158.2058.54
2014-12-3158.3158.58
2015-12-3158.2158.58
2016-12-3158.3858.58
2017-12-3158.2858.56
2018-12-3158.1058.54
2019-12-3158.2658.52
2020-12-3158.2058.56
2021-12-3158.3258.54
2022-12-3158.2158.52
2023-12-3158.2158.52
2024-12-3158.4158.56
\n", "
" ], "text/plain": [ " min max\n", "datum \n", "2003-12-31 58.26 58.36\n", "2004-12-31 58.22 58.36\n", "2005-12-31 58.18 58.35\n", "2006-12-31 58.10 58.42\n", "2007-12-31 58.28 58.53\n", "2008-12-31 58.32 58.57\n", "2009-12-31 58.24 58.51\n", "2010-12-31 58.18 58.53\n", "2011-12-31 58.03 58.53\n", "2012-12-31 58.30 58.52\n", "2013-12-31 58.20 58.54\n", "2014-12-31 58.31 58.58\n", "2015-12-31 58.21 58.58\n", "2016-12-31 58.38 58.58\n", "2017-12-31 58.28 58.56\n", "2018-12-31 58.10 58.54\n", "2019-12-31 58.26 58.52\n", "2020-12-31 58.20 58.56\n", "2021-12-31 58.32 58.54\n", "2022-12-31 58.21 58.52\n", "2023-12-31 58.21 58.52\n", "2024-12-31 58.41 58.56" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[\"peil_mtaw\"].resample(\"A\").agg(['min', 'max'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "or the monthly minima and maxima:" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_11791/1348260655.py:1: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n", " ax = df[\"peil_mtaw\"].resample(\"M\").agg(['min', 'max']).plot()\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = df[\"peil_mtaw\"].resample(\"M\").agg(['min', 'max']).plot()\n", "ax.set_title('Monthly minimum and maximum water heads `Put ZWAP205`');\n", "ax.set_ylabel('head (m TAW)');\n", "ax.set_xlabel('');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Calculate 10 and 90 percentiles of the time series with the `quantile` function:" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(12, 4)) \n", "ax.plot(df[\"peil_mtaw\"], label='head (mTAW)', linewidth=0.75)\n", "\n", "ax.axhline(df[\"peil_mtaw\"].quantile(0.1), color = 'brown', label='p10', linewidth=3)\n", "ax.axhline(df[\"peil_mtaw\"].quantile(0.9), color = 'darkblue', label='p90', linewidth=3)\n", "handles, labels = ax.get_legend_handles_labels()\n", "\n", "ax.set_title('Water heads `Put ZWAP205` with 10% and 90% quantile');\n", "ax.set_ylabel('head (m TAW)');\n", "ax.set_xlabel('');\n", "\n", "fig.legend(handles, labels)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A duration exceedance curve provides the percentage of time that the water head is above a given value:" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sorted_heads = np.sort(df[\"peil_mtaw\"])[::-1]\n", "exceedence = np.arange(1.,len(sorted_heads)+1) / len(sorted_heads)\n", "\n", "fig, ax = plt.subplots()\n", "ax.plot(exceedence*100, sorted_heads)\n", "ax.set_xlabel(\"Exceedence [%]\");\n", "ax.set_ylabel(\"Water head (mTAW)\");\n", "ax.set_title(\"Duration exceedance curve `Put ZWAP205`\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualize locations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using Folium, we can display the results of our search on a map." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "# import the necessary modules (not included in the requirements of pydov!)\n", "import folium\n", "from folium.plugins import MarkerCluster\n", "from pyproj import Transformer" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "# convert the coordinates to lat/lon for folium\n", "def convert_latlon(x1, y1):\n", " transformer = Transformer.from_crs(\"epsg:31370\", \"epsg:4326\", always_xy=True)\n", " x2,y2 = transformer.transform(x1, y1)\n", " return x2, y2\n", "\n", "df_hamme['lon'], df_hamme['lat'] = zip(*map(convert_latlon, df_hamme['x'], df_hamme['y'])) \n", "# convert to list\n", "loclist = df_hamme[['lat', 'lon']].values.tolist()" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Make this Notebook Trusted to load map: File -> Trust Notebook
" ], "text/plain": [ "" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# initialize the Folium map on the centre of the selected locations, play with the zoom until ok\n", "fmap = folium.Map(location=[df_hamme['lat'].mean(), df_hamme['lon'].mean()], zoom_start=12)\n", "marker_cluster = MarkerCluster().add_to(fmap)\n", "for loc in range(0, len(loclist)):\n", " folium.Marker(loclist[loc], popup=df_hamme['gw_id'][loc]).add_to(marker_cluster)\n", "fmap\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get groundwater screens within a \"grondwaterlichaam\"" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "gwfilter = GrondwaterFilterSearch()" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n", "[000/010] ..........\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filtergw_idfilternummerxygrondwaterlichaam_code
0https://www.dov.vlaanderen.be/data/filter/2003...620/76/173199254.58162047.33BLKS_1000_GWL_1S
1https://www.dov.vlaanderen.be/data/filter/2011...2-936131194226.00169852.00BLKS_1000_GWL_1S
2https://www.dov.vlaanderen.be/data/filter/1995...2-0001221189724.90170211.80BLKS_1000_GWL_2S
3https://www.dov.vlaanderen.be/data/filter/2015...7-1011242229414.00174604.00BLKS_1000_GWL_2S
4https://www.dov.vlaanderen.be/data/filter/1900...2-1064361199712.00166782.00BLKS_1000_GWL_1S
5https://www.dov.vlaanderen.be/data/filter/1900...2-1002361201770.00162472.00BLKS_1000_GWL_1S
6https://www.dov.vlaanderen.be/data/filter/1900...7-1043361207815.00165898.00BLKS_1000_GWL_1S
7https://www.dov.vlaanderen.be/data/filter/1900...7-1029961220481.00165697.00BLKS_1000_GWL_2S
8https://www.dov.vlaanderen.be/data/filter/2003...620/72/103202242.33164202.26BLKS_1000_GWL_1S
9https://www.dov.vlaanderen.be/data/filter/1900...2-1002351198412.00162379.00BLKS_1000_GWL_1S
\n", "
" ], "text/plain": [ " pkey_filter gw_id filternummer \\\n", "0 https://www.dov.vlaanderen.be/data/filter/2003... 620/76/17 3 \n", "1 https://www.dov.vlaanderen.be/data/filter/2011... 2-93613 1 \n", "2 https://www.dov.vlaanderen.be/data/filter/1995... 2-000122 1 \n", "3 https://www.dov.vlaanderen.be/data/filter/2015... 7-101124 2 \n", "4 https://www.dov.vlaanderen.be/data/filter/1900... 2-106436 1 \n", "5 https://www.dov.vlaanderen.be/data/filter/1900... 2-100236 1 \n", "6 https://www.dov.vlaanderen.be/data/filter/1900... 7-104336 1 \n", "7 https://www.dov.vlaanderen.be/data/filter/1900... 7-102996 1 \n", "8 https://www.dov.vlaanderen.be/data/filter/2003... 620/72/10 3 \n", "9 https://www.dov.vlaanderen.be/data/filter/1900... 2-100235 1 \n", "\n", " x y grondwaterlichaam_code \n", "0 199254.58 162047.33 BLKS_1000_GWL_1S \n", "1 194226.00 169852.00 BLKS_1000_GWL_1S \n", "2 189724.90 170211.80 BLKS_1000_GWL_2S \n", "3 229414.00 174604.00 BLKS_1000_GWL_2S \n", "4 199712.00 166782.00 BLKS_1000_GWL_1S \n", "5 201770.00 162472.00 BLKS_1000_GWL_1S \n", "6 207815.00 165898.00 BLKS_1000_GWL_1S \n", "7 220481.00 165697.00 BLKS_1000_GWL_2S \n", "8 202242.33 164202.26 BLKS_1000_GWL_1S \n", "9 198412.00 162379.00 BLKS_1000_GWL_1S " ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = PropertyIsLike(\n", " propertyname='grondwaterlichaam',\n", " literal='BLKS_1000%')\n", "df = gwfilter.search(max_features=10, \n", " query=query, \n", " return_fields=(\"pkey_filter\", \"gw_id\", \"filternummer\", \"x\", \"y\", \"grondwaterlichaam_code\"))\n", "df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## List yearly average water head levels (GxG)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For some of our Grondwaterfilters precalculated groundwaterlevel statistics (GxG) are available next to the individual measurements (peilmetingen) themselves. These statistics give information about the average high, low and medium groundwater levels at that location, per calendar year.\n", "\n", "This data is available in a separate subtype `Gxg`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To check the available subtypes for a the `GrondwaterFilter` type, you can use:" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'Gxg': {'name': 'Gxg',\n", " 'class': pydov.types.grondwaterfilter.Gxg,\n", " 'definition': 'Subtype listing the GxG values or precalculated groundwaterlevel\\nstatistics. It has the following fields: gxg_jaar, gxg_hg3, gxg_lg3, gxg_vg3.'},\n", " 'Peilmeting': {'name': 'Peilmeting',\n", " 'class': pydov.types.grondwaterfilter.Peilmeting,\n", " 'definition': 'Subtype listing the water head level measurements. It has the following fields: datum, tijdstip, peil_mtaw, betrouwbaarheid, methode, filterstatus, filtertoestand.'}}" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from pydov.types.grondwaterfilter import GrondwaterFilter\n", "\n", "GrondwaterFilter.get_subtypes()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To retrieve the GxG values, we can instantiate the search class with the `Gxg` subtype:" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "from pydov.search.grondwaterfilter import GrondwaterFilterSearch\n", "from pydov.types.grondwaterfilter import Gxg\n", "\n", "grondwaterfilter_search = GrondwaterFilterSearch(\n", " objecttype=GrondwaterFilter.with_subtype(Gxg)\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The extra fields are now available, and should be included in the output of `get_fields()`. E.g. to get more details about the `gxg_vg3` field:" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", "
\n", "

gxg_vg3 - gemiddelde van de grondwaterstanden op 14 maart, 28 maart en 14 april in een bepaald kalenderjaar

  • type: float
  • notnull: False
  • query: False
  • cost: 10
  • multivalue: False
\n", "
\n", " " ], "text/plain": [ "{'name': 'gxg_vg3', 'type': 'float', 'multivalue': False, 'definition': 'gemiddelde van de grondwaterstanden op 14 maart, 28 maart en 14 april in een bepaald kalenderjaar', 'notnull': False, 'query': False, 'cost': 10}" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grondwaterfilter_search.get_fields()['gxg_vg3']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And this data is returned when querying:" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[000/001] .\n", "[000/001] c\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pkey_filterpkey_grondwaterlocatiegw_idfilternummerfiltertypexystart_grondwaterlocatie_mtawmv_mtawgemeentemeetnet_codeaquifer_codegrondwaterlichaam_coderegimediepte_onderkant_filterlengte_filtergxg_jaargxg_hg3gxg_lg3gxg_vg3
0https://www.dov.vlaanderen.be/data/filter/1996...https://www.dov.vlaanderen.be/data/put/2018-00...SNOP0391peilfilter182987.0169274.057.8757.87Boutersem9A0000NaNonbekendNaNNaNNaNNaNNaNNaN
\n", "
" ], "text/plain": [ " pkey_filter \\\n", "0 https://www.dov.vlaanderen.be/data/filter/1996... \n", "\n", " pkey_grondwaterlocatie gw_id filternummer \\\n", "0 https://www.dov.vlaanderen.be/data/put/2018-00... SNOP039 1 \n", "\n", " filtertype x y start_grondwaterlocatie_mtaw mv_mtaw \\\n", "0 peilfilter 182987.0 169274.0 57.87 57.87 \n", "\n", " gemeente meetnet_code aquifer_code grondwaterlichaam_code regime \\\n", "0 Boutersem 9 A0000 NaN onbekend \n", "\n", " diepte_onderkant_filter lengte_filter gxg_jaar gxg_hg3 gxg_lg3 gxg_vg3 \n", "0 NaN NaN NaN NaN NaN NaN " ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grondwaterfilter_search.search(query=PropertyIsEqualTo('pkey_filter', 'https://www.dov.vlaanderen.be/data/filter/1996-011637'))" ] } ], "metadata": { "kernelspec": { "display_name": ".venv (3.13.5)", "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": 4 }