From 7a6d456f58ef29cbe814185a0722f54262226ca1 Mon Sep 17 00:00:00 2001
From: "samuel.m" <s1876jpam6y@outlook.com>
Date: Thu, 9 Jan 2025 19:22:53 +0000
Subject: [PATCH] Finished dashboard
---
dashboard_code/dashboard.py | 118 +++-
data_code/querys.py | 12 +-
data_storage/UK/Crime/combined_crime_uk.db | Bin 475136 -> 475136 bytes
.../data/uk_expenditure.db | Bin 94208 -> 94208 bytes
...hest_qualifications_time_series_rounded.db | Bin 110592 -> 110592 bytes
.../data/uk_neet.db | Bin 405504 -> 405504 bytes
...k_post_compulsory_education_fe_students.db | Bin 86016 -> 86016 bytes
...k_post_compulsory_education_he_students.db | Bin 520192 -> 520192 bytes
..._post_compulsory_education_institutions.db | Bin 16384 -> 16384 bytes
.../data/uk_pupil_teacher_ratios.db | Bin 65536 -> 65536 bytes
.../data/uk_pupils_suppressed.db | Bin 323584 -> 323584 bytes
.../data/uk_schools.db | Bin 86016 -> 86016 bytes
.../data/uk_teachers_suppressed.db | Bin 253952 -> 253952 bytes
.../data/cfr_income_la_regional_national.db | Bin 46010368 -> 46010368 bytes
.../data/cfr_income_national_summary.db | Bin 229376 -> 229376 bytes
...venue_reserve_la_regional_national_data.db | Bin 1605632 -> 1605632 bytes
..._revenue_reserves_national_rounded_data.db | Bin 24576 -> 24576 bytes
.../data/headline_key_figures.db | Bin 8192 -> 8192 bytes
...g_peoples_services_la_regional_national.db | Bin 13447168 -> 13447168 bytes
...ildrens_young_peoples_services_national.db | Bin 77824 -> 77824 bytes
.../data/20240125_fig2.db | Bin 8192 -> 8192 bytes
.../data/20240125_school_level_data_csv.db | Bin 6488064 -> 6488064 bytes
.../data/20240125_tab1.db | Bin 8192 -> 8192 bytes
..._Intentional homicides and other crimes.db | Bin 864256 -> 864256 bytes
data_storage/UN/Crime/UN_Crime_Continents.csv | 253 +++++++
data_storage/UN/Crime/UN_Crime_Continents.db | Bin 0 -> 65536 bytes
.../UN/Economy/GDP_per_capita_continents.csv | 504 ++++++++++++++
.../UN/Economy/GDP_per_capita_continents.db | Bin 0 -> 126976 bytes
...penditure_by_function_at_current_prices.db | Bin 6340608 -> 6340608 bytes
.../SYB67_128_202411_Consumer Price Index.db | Bin 471040 -> 471040 bytes
...SYB67_230_202411_GDP and GDP Per Capita.db | Bin 1589248 -> 1589248 bytes
...re on education and access to computers.db | Bin 675840 -> 675840 bytes
.../Education/SYB67_309_202411_Education.db | Bin 2174976 -> 2174976 bytes
..._323_202411_Teaching Staff in education.db | Bin 958464 -> 958464 bytes
...411_Ratio of girls to boys in education.db | Bin 905216 -> 905216 bytes
.../SYB67_154_202411_Health Personnel.db | Bin 1339392 -> 1339392 bytes
.../SYB67_325_202411_Expenditure on health.db | Bin 622592 -> 622592 bytes
.../SYB67_314_202411_Internet Usage.db | Bin 323584 -> 323584 bytes
.../UN/Labour/SYB67_200_202411_Employment.db | Bin 2117632 -> 2117632 bytes
...29_202411_Labour Force and Unemployment.db | Bin 1318912 -> 1318912 bytes
data_storage/UN/Land/SYB67_145_202411_Land.db | Bin 1359872 -> 1359872 bytes
graphs/graphs_display.html | Bin 69230445 -> 129219500 bytes
main.py | 639 +++++++++---------
43 files changed, 1185 insertions(+), 341 deletions(-)
create mode 100644 data_storage/UN/Crime/UN_Crime_Continents.csv
create mode 100644 data_storage/UN/Crime/UN_Crime_Continents.db
create mode 100644 data_storage/UN/Economy/GDP_per_capita_continents.csv
create mode 100644 data_storage/UN/Economy/GDP_per_capita_continents.db
diff --git a/dashboard_code/dashboard.py b/dashboard_code/dashboard.py
index 1014dec..9c9550d 100644
--- a/dashboard_code/dashboard.py
+++ b/dashboard_code/dashboard.py
@@ -2,15 +2,24 @@ import plotly.graph_objects as go
import plotly.io as pio
import plotly.express as px
-
class Dashboard:
def __init__(self):
- self.graph_groups = {} # {group_name: [(title, html), ...], ...}
+ self.graph_groups = {} # {group_name: {category_name: [(title, html), ...], ...}, ...}
+ self.home_graphs = [] # Store the graphs that should also appear on the home page
- def add_graph(self, group_name, fig, title):
- import plotly.io as pio
+ def add_graph(self, group_name, category_name, fig, title):
graph_html = pio.to_html(fig, full_html=False)
- self.graph_groups.setdefault(group_name, []).append((title, graph_html))
+ # Always add to group pages
+ if group_name not in self.graph_groups:
+ self.graph_groups[group_name] = {}
+ if category_name not in self.graph_groups[group_name]:
+ self.graph_groups[group_name][category_name] = []
+ self.graph_groups[group_name][category_name].append((title, graph_html))
+
+ # Add to home page if it’s one of these choropleths
+ if title in ["Combined Choropleth", "Total Recorded Crime 2015-2024"]:
+ graph_home_html = pio.to_html(fig, full_html=False)
+ self.home_graphs.append((title, graph_home_html))
def generate_html(self, output_path="dashboard_code/graphs_display.html"):
html_template = """
@@ -29,7 +38,7 @@ class Dashboard:
<style>
body {{
background-color: #343a40; /* Dark background */
- color: #f8f9fa; /* Light text */
+ color: #f8f9fa; /* Light text */
font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;
}}
.graph-container {{
@@ -39,8 +48,6 @@ class Dashboard:
border-radius: 5px;
box-shadow: 0 2px 5px rgba(0,0,0,0.1);
margin-bottom: 30px;
- height: 100%;
- width: 100%;
}}
.nav-tabs .nav-link {{
color: #f8f9fa;
@@ -61,8 +68,11 @@ class Dashboard:
margin-top: 20px;
}}
iframe {{
- height: 1000px; /* Increase the height for better legibility */
width: 100%;
+ height: 1000px;
+ }}
+ .plotly-graph {{
+ font-size: 16px;
}}
</style>
</head>
@@ -100,10 +110,52 @@ class Dashboard:
tabs = ""
tab_contents = ""
first = True
- for i, (group_name, graphs_list) in enumerate(self.graph_groups.items(), 1):
- # Tab header
- active_class = "active" if first else ""
- selected_aria = "true" if first else "false"
+
+ # Add Home tab
+ tabs += f"""
+ <li class="nav-item" role="presentation">
+ <button class="nav-link active" id="home-tab"
+ data-bs-toggle="tab" data-bs-target="#home" type="button"
+ role="tab" aria-controls="home"
+ aria-selected="true">
+ Home
+ </button>
+ </li>
+ """
+
+ # Home tab content: two choropleths side by side in a single row
+ home_html = '<div class="row">'
+ for title, graph_html in self.home_graphs:
+ home_html += f"""
+ <div class="col-md-6">
+ <div class="graph-container">
+ <h4>{title}</h4>
+ {graph_html}
+ </div>
+ </div>
+ """
+ home_html += "</div>"
+
+ # Optionally include text below
+ home_html += f"""
+ <div class="description-container">
+ <textarea class="form-control" rows="4" style="resize: none; background: #343a40; color: #f8f9fa; border: 1px solid #495057;" readonly>
+You can add any home page description here if needed.
+ </textarea>
+ </div>
+ """
+
+ tab_contents += f"""
+ <div class="tab-pane fade show active" id="home" role="tabpanel"
+ aria-labelledby="home-tab">
+ {home_html}
+ </div>
+ """
+
+ # Add other tabs
+ for i, (group_name, categories) in enumerate(self.graph_groups.items(), 1):
+ active_class = "" if first else ""
+ selected_aria = "false"
tabs += f"""
<li class="nav-item" role="presentation">
<button class="nav-link {active_class}" id="{group_name}-tab"
@@ -114,36 +166,30 @@ class Dashboard:
</button>
</li>
"""
-
- # Tab content
- show_class = "show active" if first else ""
+ show_class = "" if first else ""
first = False
-
-
# Build graphs HTML for this group
graphs_html = ""
- for title, graph_html in graphs_list:
-
-
- description_html = f"""
+ for category_name, graphs_list in categories.items():
+ graphs_html += f"<h3>{category_name}</h3>"
+ for title, graph_html in graphs_list:
+ # The text box description for each graph
+ description_html = f"""
<textarea class="form-control" rows="4" style="resize: none; background: #343a40; color: #f8f9fa; border: 1px solid #495057;" readonly>
- This is a fixed description for {title}. You can style this text as needed.
+This is a fixed description for {title}. You can style it as needed.
</textarea>
- """
-
-
- graphs_html += f"""
- <div class="graph-container">
- <h4>{title}</h4>
- {graph_html}
- {description_html}
- </div>
- """
-
+ """
+ graphs_html += f"""
+ <div class="graph-container">
+ <h4>{title}</h4>
+ {graph_html}
+ {description_html}
+ </div>
+ """
tab_contents += f"""
- <div class="tab-pane fade {show_class}" id="{group_name}" role="tabpanel"
+ <div class="tab-pane fade {show_class}" id="{group_name}" role="tabpanel"
aria-labelledby="{group_name}-tab">
{graphs_html}
</div>
@@ -151,4 +197,4 @@ class Dashboard:
final_html = html_template.format(tabs=tabs, tab_contents=tab_contents)
with open(output_path, "w") as f:
- f.write(final_html)
+ f.write(final_html)
\ No newline at end of file
diff --git a/data_code/querys.py b/data_code/querys.py
index 0d936ce..d87412f 100644
--- a/data_code/querys.py
+++ b/data_code/querys.py
@@ -48,8 +48,8 @@ def sexual_violence_rate():
def overall_homicide_rate():
homicide_rate = """
- SELECT Region_Country_Area, Year, Value FROM data
- WHERE Row_Descriptor = 'Intentional homicide rates per 100,000';
+ SELECT "Index",Region_Country_Area,Year,Row_Descriptor,Value,Footnotes,Source
+ FROM data;
"""
return homicide_rate
@@ -91,6 +91,14 @@ def Government_education_spending():
return Government_education_spending
+def gdp_per_cap():
+ gdp_per_cap = """
+ SELECT "Index",Region_Country_Area,Year,Row_Descriptor,Value,Footnotes,Source
+ FROM data
+ WHERE Row_Descriptor = 'GDP per capita (US dollars)';
+ """
+ return gdp_per_cap
+
#### UK QUERYS
# FORMAT
diff --git a/data_storage/UK/Crime/combined_crime_uk.db b/data_storage/UK/Crime/combined_crime_uk.db
index 1fa931e47c5be68062228d24ea0bb16fa9906c24..f4fe0dad3334ee04f9e956e19a143bc5ce6ce414 100644
GIT binary patch
delta 200
zcmZo@kZov?oggi^oPmL%gn@y9g@J(~ih+S4f1-{t<MNFOtN9rVH}eR*<!3C|{7YU?
zfH872k3ljcYa{~$L*e8S!*DQ*X)7c9fBUTh>>ubr6zaDvVBNNWjU`|^O9Sg4{$(H7
F902Y3Lrnkx
delta 128
zcmZo@kZov?oggik&A`A=!oa}5!oa`~#lXPeK2gV*F?(aeYJSFo%{&5c`57ZO|B@FJ
zU@Y9sW01_qTFAh_P%yc~FdWQcYQAXLe$kMz{h}dL`$a?M_KSur+b<fj8u(3Hz{<9r
f?E~8{{>2v!1=<#{Zd<^{60ntp{g3_P2ZjOwrxzy@
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_expenditure.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_expenditure.db
index 401c2b9032375f9b3bcdeee5e7d1a26ae4705cf4..499fed3e92df38ecfe3cbfdf61642bea9272e467 100644
GIT binary patch
delta 38
mcmZp8z}oPDb%L~DECU0BI0GCoPM)Y^%oy94ur+~kK|TPf&<NuI
delta 38
mcmZp8z}oPDb%L~@A_D`1I0GCoW>3^HW>joU*qXq&ARhpq90)@I
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_highest_qualifications_time_series_rounded.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_highest_qualifications_time_series_rounded.db
index c3fd6a9aeb651b4d8cfe4b9126377138f5ad3c3b..486415ac74ef4f42328e8be9446395825d7b6805 100644
GIT binary patch
delta 38
mcmZp8z}E19ZGyC5ECU0BGy@zkPM)Y^%oy94ur+~k!Fm9yxd|x%
delta 38
mcmZp8z}E19ZGyC*A_D`1Gy@zkW>3^HW>joU*qXq&U_Ah!1qg`%
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_neet.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_neet.db
index 7f616ede93ab26edd2635b957fa0677edfca5a5c..8f5bfba6751eb8c7a94d4a1e56bd372399097a49 100644
GIT binary patch
delta 53
zcmZp8AkpwZVuG|_ECT~WG6NhiPM)Y^%oy94(3-&5n!wbWz}%X^(we}!HGyq`J^)``
B4Wa-5
delta 53
zcmZp8AkpwZVuG}wA_D_MG6NhiW>3^HW>joUXiZ>jO<-zGU~WxdX-#0=n!vU|9{@{9
B4FUiF
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_post_compulsory_education_fe_students.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_post_compulsory_education_fe_students.db
index 4be305e4cf25173865811f5d3d082666ef23e183..a4d7acd575ae724d5e3828d79f07a6d02828543a 100644
GIT binary patch
delta 38
mcmZozz}m2Yb%L~DECU0BC<7cYPM)Y^%oy94ur+~kfj<D3z6e18
delta 38
mcmZozz}m2Yb%L~@A_D`1C<7cYW>3^HW>joU*qXq&z#jmO3J0M8
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_post_compulsory_education_he_students.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_post_compulsory_education_he_students.db
index da2f3f18a6e2d38b8c6df98fe50cb6057456a554..0c7526a43921a57533e6d3db76729e28e6ce03d7 100644
GIT binary patch
delta 56
zcmZp8Am8vneuA`MECT~WJp&vtPM)Y^%oy94(3-&5n!wbWz}%X^(we~9n!vU-fqlVy
E0FlQJcmMzZ
delta 56
zcmZp8Am8vneuA{1A_D_MJp&vtW>3^HW>joUXiZ>jO<-zGU~WxdX-!~lO<>!az`o!;
E0DIF8*Z=?k
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_post_compulsory_education_institutions.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_post_compulsory_education_institutions.db
index 99816aaac3e7cd7c9754e0786e91eaee0416167d..8fdfadc31590fdaf0163ef0d1e28ee348eded41e 100644
GIT binary patch
delta 35
jcmZo@U~Fh$oFFY2%fP_E!T<-1lPBsJGsbRASYQtTb{q!s
delta 35
jcmZo@U~Fh$oFFZz$iTqB!T<-1*%Nh)85K7sEU*UvZAb=E
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_pupil_teacher_ratios.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_pupil_teacher_ratios.db
index 20a1e7fffbdd98c07469fbb8d57e3fcbc4e7ee04..8b996d251e935af8e521f7845cae052f285b8cbf 100644
GIT binary patch
delta 35
jcmZo@U}<PznIJ6~%fP@OzyJq~lPBsJGsbRASnwYJc%cWx
delta 35
jcmZo@U}<PznIJ8w$iToLzyJq~*%Nh)85K7sEcg!qZ_NiJ
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_pupils_suppressed.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_pupils_suppressed.db
index 6c8a6c544737a3043a8a9e2e2cca11a636829751..46bd9147db3a8dce8c8549b3b305c4438a3ebe86 100644
GIT binary patch
delta 47
vcmZp8Al&dkc!IQGECU0BKLZ>vPM)Y^%oy94(3-&5n!wbWz`QkqWx;y@58VuJ
delta 47
vcmZp8Al&dkc!IQ`A_D`1KLZ>vW>3^HW>joUXiZ>jO<-zGVBVU*vfw=c|9T70
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_schools.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_schools.db
index 6bef7ae78dc80444a04dd1dedf1a808ce465d285..c91f104d49cadac005382cfb633fa57e7f873ed4 100644
GIT binary patch
delta 38
mcmZozz}m2Yb%L~DECU0BC<7cYPM)Y^%oy94ur+~kfj<D3z6e18
delta 38
mcmZozz}m2Yb%L~@A_D`1C<7cYW>3^HW>joU*qXq&z#jmO3J0M8
diff --git a/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_teachers_suppressed.db b/data_storage/UK/Education/education-and-training-statistics-for-the-uk_2024/data/uk_teachers_suppressed.db
index 83ebb2ce70d2f061e0271da1fb40d5538d2ee77e..2539c9c8b0cbf69b636dd817183ac9c1e36fee37 100644
GIT binary patch
delta 44
scmZoTz~69ye}c4NECU0B9RnONPM)Y^%oy94(3-&5n!vO*fqB7w0N{}e9RL6T
delta 44
scmZoTz~69ye}c52A_D`19RnONW>3^HW>joUXiZ>jO<>xZz`Wo-0MZ=_eE<Le
diff --git a/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/cfr_income_la_regional_national.db b/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/cfr_income_la_regional_national.db
index ba706a9a89788bfd3d386f684f73cd1d84fa8fa2..308694d2c982ddc726c77e60bc23f6c4d7010f36 100644
GIT binary patch
delta 59428
zcmZoz@Iw@YCrArEWnj>L$N&e7&J%Tv8J})UcrI73(DzP=fk8vQZwn^_gN9u1n_vb8
z4cXphd<+a4GChyv7#P%_^~?@sU{K%KeL0(ff#-Mk1a$@m^$lGovltlE^Sc@&85sC=
zJNG&<FsSEse79y`5M17|-jRVp<XHQwcm@U))%GQ63=Co+ZFg)L7{o5MO%GsTkSuDw
zSi`^|&8XGdX~e)FGpXfpAOnM(eDl931_t@1&07l?7*x2L-q$fODB3rz)@NW)y0rO&
zyokVZmIOwD#VijR7PDLsSk6+wcwsZk0VaXPYz_^J*$f1hvpFycY-e+j`NzMUB|%1D
zIZFeGSO6jpfQSb&0!vwB1-7#&$buAJVEV`3&eFi#&eFir&eFiz&eFiv&eFi%&eFiq
z&eFiy&eFiu&eFiWoTY(h!g7`XriSG#0SW@kSqwmg0I$Gy76DHtfp#_n-gY(vzIHYP
z{&qG45MQvJ%|NJ~%|N)F%|N7`%|NuB%|NW3%|N`J%|N1^%|No9%|L29n}PH{{iQ52
z4$D~rWCXUe6v%*FH397W4IuYk0EvD8iweksJY^s&u$(18R-m1wK(?KwKyEopf&78x
zEDj1FKiPqF3z+}oU&<07u$)D~TwpniK!Ct@76WsTj6wj&1P73)0Z2Xo#Bu<!5<si~
z5UT*hN&vAMK&%1~YXXSX0AeM8Y+nH4I)I#zpwP~epxDlmpw!Nipxn-qpt77LL3P7&
zmJiY(>(vC7vpfK?E=UV(XE`9vB(R)qgS5bMwgu7x+u0^agIv=9k}m)e2_Qm1O`x5{
zK&_p{K)s#CK%<?-K(n32K&zd_K)apAK&PF>K)0R6K(C#}K);>kf<ZgW1;cih3r6iM
z7mV9kE||2lTrl0va>0zrp`C4mc{|$%i*~jRmhEgCtlHT&Shurnu-VSG!S-MNb`}G0
zSZ%NexnY65z;>1i_MjkY01Fg=1QNgk0bl_Kdr+K%hzX$JRImqm#lh~tb~XcpfBf57
z1Rw$i6SlJ1gZKyRnGBY*eK;eqobACGf$eM;&VcMWa7JJ`%LWh;un&}y>p@XjFR-0u
zLl4OA1B*b3@q_(xmJbdOma`Nv3oK{3;JBcjrNOD4rNOzKrNO10rNOnGrNOP8rNMnU
zOM}ORc9spE?JOI-+F3Sux3g^UX=mBs+s?AVZ#&Bdf2M$Twgn&@*v_^fsGV&=a68+A
zkao5Oq3vu7!nU(52>++QoJE0GU^&YIPl4qu6F@|RCny<ug8Y}@DX^R^z!Q|8JVDMk
z0Ld$Why-SV?JN(%L5_Bq{g1zuC8Cujaw$vHgyk#^nIPk$1eUTSfegw7sY%ELg-HOI
z?T`sJ3ZzOQ6O?^2nFN-yWeO~3`;Z~9oNYpsKs(!ksCKpk(d}#pV%pgb#I~~?h-+s%
z5Z}&rAYnV(fy96I?JNtD+F2GPx3errX=hoG+Rm~dt(|2-`gWED86Zzj$ZThukk!sM
zA-kPzLQXr|gxq$v33=^o6Y{sSO(+0)dP5Y*zaSSjB!RqIkR-63Eg=cyw16am<tz>$
zDT5@C;}yW70wB>3lR+_307}|h1ln0X6tuH^C|u6+p=iQ(mH=juITMNnwzGYx0(sYg
z8Km2Q8DypcC@KY*1(vda7$2BG`2s`~I0<ZLxe(4Mu${G`_&<L;%ZB21mJKECEE`JO
zSvHilvur4DXW3BE&a$C$Im?DBhjx|;)$J@3YT8*Q)GlY4P<LQCi^5rjc9w$rc9w#M
z<tzn_1>0F3tN~g4p%Ijr7Bsc9ENE_LS<uqXvY@q{WkFjz%YycHmIWQ#Sr&9MDQsnH
z`Zs?$%YjaT<tzt|3beC4=xk?s(6yZ9LHC61ED5tgero6erQ*q;v@ly>JDb2+kdF*z
zgF*pB2+S7P$}$^l<t&iDAIt)=FU$g|D(C?v1`zQfT%euhKu<f%f!=nO1AXl*2m0Gt
z4oqlgIWV!E<-nxnEC(hlw6io!X=iDe+RoB2t(~P|dOJ(QjCPiWnaf!kW(Bmf6wGdC
zDVWpFQZTojrC?q=OTqkhmVyQCECmafvlJ{+Sk7{w0F;fvS*c(O$ohmS0^3;vrhwez
zFa_i`129_w%odo!B(RkY%zSVZq~yX;ke&^T1eUU#6=-L<u&ABo!s6vD7nXoxcMB*a
z3YLPh@*0py4qHH447Px^ECm&_TLiYUfCWEn1_?gc3`#2?;sA(90I8X<RAD>Ig91=}
zabRgX+ks{6YzLONvmIE`&URpBJKKR(?Q92DZ)ZEO1{8G#Yui~0*0r+~tZ!#2*wD^W
zu(6$`VAFDzg3ST#ED2lMSrWFkvm|V5XGz%J&XTaBoh4ysJ4?c@?JNnqnG}|@J!llz
z&epIL<dlT9pkP=Fa<Ic%kbuEjP~?FKfwcl#S->(Mz}~uW52WhAJ&*$y>~3dSuxB~T
zg1sBIvpAduNhIt8`F+DaCWGy41^fQlFK2nM&tN^v0#8PP{VWqa8JPsuvo(M?Yz3Z-
z|M>T_B!I-$vRN|<EN5%@C$OEZ;NL&~^(+aTi~{Rf3gj6D+F1nlFJ}=r@L)O1hVKH)
zSw0+C(9W{pU^~l#L+vaJ4!5%`II^5&!BJ2>bF7^u;dnbs!ijd4gp=(o38&gw5>78?
zNjMYG&Ju98oh9Jhc9wwiUf=3{y8iJoFtB)c{Viu;VDaku8_&SN;@S1roq>VHqwB8$
z0|SeD*Ix++1{Sxjzl;nFEUsODav2y{T)O^*F)*+=cm1(rU|@0T`lHUkz~b2Tho6Cg
z#i8pr$T0h^-w6y1EOuSLy%`u-Y`cD&GBB{%bp4iRU|_NC`pwC}z+zS3^{a@1fyJ`x
zS2P0yi$&KjR|W<a^R8cd3=Ax0UB5u~ns)tSVPIe}>G}z>*SPB^$X=tapY{w4EQVb_
zLG~JS{RG*o-}R${fq_M@>qjC31B-6g50Je&T|dki7+AEset_)N>iWUXz`&x}^*x_~
zfknNm{(A%i1B+VMcV`9$7S*orx(o~~DqY{j7#LWTyS~*kFt8|feam2AU{UP)7RbQB
zqR{otih+SezU!L`0|Sd(*EazM1{T?_uayi8EHYhRLH0^_ef45sV3F$jYQ(_6BH8s-
zih+SeqU$RY0|SeA*OzPt1{SfdFCb5dc73ULU|?Vo>H4C{z`!Eh^+k|@fkmk6GsrZ-
zuFpvf3@id&pFzIh@A?c1J-)8b3JeS^yj`EU7#LW1x;_;%FtBiUeTrdVVBzZe1PVOP
zu1}!A<LLS%&cMLJ-t~!rfq{js>m$fs)~=5rds(_Zf~;lk`lto+Ayd~!VFm^k#;y-F
z3=Av`T_4gI7`Sx1KKL^*aGdG-V9CJ1{;lhSDgy)i_pT583=G`Qy53hXFz}q|dY{O^
zz;m|iy(a?$&$+Jmh71fm=eyoZF);94=z7n@z`%2{>m8^We5vbQ7y|>(<*s)Q3=BM1
zy54CqFz{UMdMC<I&%kr7>uo&)1JCuYw^<AfJU6=DhBGkm-0XVm$iTpJtLrUD>Fut!
zA`A>Xce>uxFfj1k?Rt~Kz`%2_>x~}+1JC`gH<k<xJP*3ws4y__JnVYI%fP_%sOxnp
z0|U?FuGg^)3_MS|Ub`_c@I38$t<S)~^Q`N&Bm)D_^RCyd3=H)=FS=gkF);AF?0N-q
z;;XJ#_6!U>ue)BUGcfSH>3YS_z`*mi>m|s)@48+lGcfSH?|SLWz`*mN>!mpZ1JB2<
zmr4u_JfFH=@-Q&)eC~Qt&cML)rRxRAg<rc~fL!>k>jg;V_pTQT3=BL!x?XTFF!22B
zdS1Z5z`Omp=LKEH<l|irI2agsPjuY}37+h_AIZSLd#dZc3j+i1>8|^F3=F(yy6%fJ
zFz}x3y3fGCz<aLiUIqgL@A<BK0SpYh7rO3QGBEI7?7FAOz`%Q{>mC;a1MlUoyJZXv
zyjQyJ#xpSRUfmw<ePJqN{k5*Uh71h6*SqdYF);An=(@|yz`%R6>rNg61MjV_JK+or
zytljV*fTKj-s!rd!N9<Kx9g4o0|W29uG<w147~TdZYMA>@IL6e?a9Ev`>^Y_2?GP~
zqpsU>3=F)FyKb{HFz`O<x&`vY)2>?}Pdw|o1@gr6u3Nec47@MuyKadxFz~+Yx>?7-
z!27D}W*P$n@9VCcehdt}Z@O-pF);AH?Yb$?z`*;i>n6w-@4If4Ffj0b=(+*&#mBB2
zUJMMppSo^<?ETzz17z=)t{b4h``UHAn1O+}yz6=b0|WQ2uIpY54BR`rt{XEj@Llb?
zF3Z5cccrWTIvWE6-{r1r`3wwvm%6S+Ffj04?7HU6z`%E*>zW<|1K;_sYZ43$eCN8Z
zF)}dlo$b1s#lXOKrt4}j0|VdbuB$c-41A}$uBtLH@SW_s%E!RKccSY`B?ANB@vbY$
z3=Dk7x~}*#Fz_Aix?;}2z;~qUiUI=z-{Gz+oD2+nhq^A;7c(&M9qhUs!@$6k(LF(g
zfr0Np*JU>b2EP4WmyH-0`1W;OmSJGv+uL=Sm4Sh8PuC@oLw9#w3TI&8+tqc+o`HdH
zXV)c71_r(zU6+Iy82Gk#fjWnL+qy1hFfj0K?YbDqz`(bq>!K9{1K;MZiz*BZe4Dy1
z@-Q&)ZS1;GQqRD^x1sAoECU1I`mPHgd)IYcFkoQdTibO(nt_3DP1gk$1_r*>UFUNc
z82DCooeyPT;9J>s-j0ERZ$;O6H3kO0<z46b85sDMb)BnbVBlNYbuN{Gfp1CIIe!KQ
zzQtYVK=v-`ItQ|MVb?j3$^~6#s~8yg=69V<WvFN1o7Z(Vh=GA`Zr53B1_r)4U1vc`
zXLp?ih2^ZSGvy2nd^5Yw#4|AP&FDJg!N9;bz3Yr20|Vc*t}~#Jnc8)Roq>UGO4sQk
z1_r*#U8iFh82Bc2opxtn;G5WW8We^Tx=w>s_II5IsqE`IRl>l)*V}a}o`FG}uczx2
z$k6VtQy@dTx=u+lFz|J@|MkDn{@4Fv`(OV{?SK6*Z~yCmh23B|%Y;P=+gUDjg6i{t
zW1!}M!!c0j<`}30c?={fa17Le1POjP3ThXA2Q{m%FbV8u`ykE;Y8h;}($2Es>UNe5
z*O(@3XES&PG9=(SsBd!*WXLm6TS?%Vz*e?rpytAdryxTgJO!z`@D$V$1Pg2c3oLjF
zYHeQ!b!V@)vlQHDXDPVZ&Qfrzou%M*J4?Zxc9w#>%UKHUIkd9`+;3+Ic+k!g@UWdF
z;88nEz~gq7fG68o0-l1}{0`6B*&Lp?vpKwIXLESj&gSr{oz3BOJDbCs?Q9NjL3TIn
zR@lyxa2@0rhx;G_gZrRn5Qq@CFR+y5zQA^t58(FCgL|Mx$^ijTt7d}$Bgp3q1Q<bD
z8r}-5XSrYiYPT$S+s?A!-Ex)%?<Xv0QTQ*goy7svuxDHF9n?tv|Brtw%YTqvAO3+f
zKKKV}4uXgS|3DqSe;}y^V5tcpQG*Wx?JNl&wzDLB3_Mo<q;qvP1B1Zh&efp|3<8fj
zS35E=2t4dut;xV3@St<GAOnNI{mxZY3=9JII#(q!FbLf3T;;*QAaJL1l>q~T!0pae
z5)2Fiw>nobF)#?+>|6;l>_+Fx5C#T;>zylY85jhvb*@xpU=X<4xssQGLEuW~ic$s!
zfy<pM;u#nOF4cFg@MK^RxY)VEh=D=iLgxx;1_puiohz6b7zECBF3(|L5IEbp9Aw&=
z&gFIt3<9S+muoOE2%PF%4szPb&SjMh3<4)Qmw}viymJ}Iuw$LeK!zRdTqec9AaJB}
z8OX51olEl=7z7S=E)8d35IESm)PaFP;6P{nQjkaYcP<5)wy$#u$h5tkOOhBE1om_;
z@n&EU*xk9rlz~BDSLYH%1_ptholCeF7zB27E-qqV5ZK<iIGTY$U|Z*6X9fm=t(}Xt
z85jh%bS@TQU=Y~cxu}+bL10toq6`KGfsLJuf*2SCHgqnsW?&Fl-?>PIfk9wh=c0NZ
z1_pt(oeN7C7zEaIE{tVh5Ln&0(4B!nU{&WrkS|ttE|g(l5LnT<kd=W!V0q_)d<F)A
zWt|Hm7#IYWb}j(L){@QzAbS^gE)Zp45Lnc?fPsNQU}5KcP*g1FoDT}T`JMAYQ8BM`
zz8V9Az}(LH{0s~Nb2{f$)H5&$%<i0*z`!6dt8*SG^k#O>Ghtv5n9(^8R6BTg&SPg_
z5SZ3Ew}62`U~=c&2nGhh%FekC3=D!*opZGq7zC?3=ZZ2g2-bAYWnf?stnHkW$-p33
z*EuJMfkCjoa}H>fuAy^|3Il^+W9J-R1_r^V&e`P*41&#_vy&O>83bE8XZtWP2)1_4
zHf3NCZ0npY$G{-i-Z`6%fkCjNb5<S$gJ5UptZ)Vf!LH6(AbYzzXMybP>6`_!x3_a<
z9Rq`4U+2s;1_r_Y&Y6A;41yCnXId~Y2u|#rsmQ<}IH_|cHv@y<<jxr&d#7~HNMK+P
zoZ30VlYyaLa9ZaKV+IDn>76rV7#IX+bk1O9U=W<yIUQv0tj_5mduMk}cVu7?oYOg7
zhk-$GZs&9{1_r@-ozv<W7zF2cP6PROLFY7(e;0O61NnDR=QLFY2EoOh)A$(}1ebJ9
ztzuvhT-rG`m4QKUS?5%c3%_?xHDh29+<s2;lNw`kNoQ{<1A|a$XKx$>gHTy#uR8;S
zP<dysJ_CbLMQ5)#1A|ayXD=fIgHTmxPc8$4P<3Zd7z2Y)O=pii1A|a)XOAWWgHT;(
zj}QZcP<>~2H3NfCLuYpi1A|awXSY8CgHY4<aP3c18S9%nyOkLjgjzbgc^DXkT06VS
z7#M`wI=hk>7=+q8ySy0~ggQFAj2Re&Iy<{$7#M`QI=fgH7=*ezJ98KqgnBwVLl_u@
zdOJI985o56Iy==F7=-#eI|UgSgeG)$R536JP3-JQW?&GS)Y$<tY;tD@$gnA$9U#M|
z)^~P*Oq<r(4)VqH&h|(K2B8_9?M@5~LNhztwHX+MW_7lUFfa(s?rf`JU=W(q*#`2(
z+|D*%1_q&dooyBj3_|le+msj>gcfwRaWgOoE$nP9VPFti)Y%%tz#yd3+3L!`ARyS;
zs>i?}Akf(gDxdf}TbURbgd02STe2A#gc~|rLKql?>pNR)85o4?I$Km37=&v(Tlg3l
zgljsR%NQ7ht2>+H85o4CI-9*27=$Z3n@t!Pgey9mWf>TR%R8Id7#M`hI-Bws7=%kZ
zo5C3wgiAV`oEaE|i#wZi7#M_$I-5io7=#Nu8*3RDgbO+wQyCb9^E(^seHj>p^Ew+r
zaWC4rSC@f7IJdJ=o`FF)r?Zihfk8OCv!R%QK{%_kA%=lLIJ2|Cg@Hjhqq6~|GQG1w
zf`LIet+RoVfk8O6<9{XtgK$d6{~!hi;pC40RtyZnNge-{7#M^TJN|PsFbF4f{3~H#
z5RUKo7stRL9M|#Bvz~!LIJV;-$TKk=|Ku1LgrhtDaWF6lM|J!yVqg%C?Dz|^H=+a7
zg%u9(_zO}Q*6|mlGPL6_I|GAoNXMT-1_t5ajz3Wh48lPje?Z<2?Dzxnc0k7;F$M-<
z|BgQ(7y5Pl28Fh7$8S(*`*i%aWvFKm_U`zt#=s!#)$yC3fkD`_<5vX(gRn=(uS5n0
zVfT(-J`4=PZXLhO85o3JJANrLFbKPJ`~rE#x#K6uGfo{pV;LBP9Xo!yGcX7{bo?}6
zU=X(N_$kG}AZ*w16BIGF9X~)WwCVT(a-ns{50DG3I)3OdFo+9VcKi@!U=X(G_+H1r
zAZ*_8J&l1u*sT4p{-^f8`k&kX>VIkftN*qAul~2~fAzm}7PPZD{Ag!$_}R|p@T;B8
z;deWm!=H9Ghrip|9RB^&-_LTvlaWcGoz39?ZZ-qPf9sdC1iUp^&*A_cc2E!m4L%46
zG79Wv5d;red;rz-Y!5(H{C<`TkP3f;CL^d3us{=}cmkLdU}O~NXF0&g*w1o+2}Cf1
z2o}cmEC*N_H>_t-U}Rjdo~3{d)NDvlVq_BNXPdyr*v~eBopC?g1P;c3{p(o-BtYgF
zfE_YHfKgyA3s~TQCrJ2#IEcIeCJ%tg4dNif7Knq}AQM2Xul+0y5S{`j*nt6@i~`$P
z7F+?@R=~;F&sM+%BDg^W4~XCe5quzmpK(81fdJz_`F<7yLB@U-10fJ03?f88geZs*
zV_eT-AkG-j&!Ql~*w3OM$+(|IL5k7qS-oAy+&~5f9@~z&pw6jH$6Q4Q1|I8<xm*kk
zJXRfZK%G;|jyZ7*3_KPcb3mO_^Nu;7&Z$|)90>*n9@CCFpzgCt$Lw4N1|H*%*`PkL
zQO9gh_t~&xHmFZ*&@o$>fq_TAV-~1Stk*Fsje&tjw_{cS0|Spvea9?o1_mDOj#;2?
ztX9V?K?VjM&5oH>3=BLP9Wz0lQ}vFSpl+;M$4oN@1|HRpnV`<8O2<r)3za)&fLy55
zF$2`WSL~SK#lXO$&@sb^fq_T9V}>*X1CLzC40Z+v9@&oR1q=*4G9A++85nq^JEl7`
zFz`rr)KAxDVBnGHm=1EHc*nF_1_mCnj%gVT3_PM8pn8T!q+^;50|Sq6$22tt1|Fdf
zP(8yV*fAB<(H7{Kn#91s!{0I0n}LCcuVbny0|O6l$5c=l@^nn)W?<mq?wC@-z`(=R
zF$L7Y=j@o`%D}+G(J@7rfq{p;V@kak0|O6R$K*N&1|HUq$sl`KIwprOFz_&UOtxiU
z;9=^R46>K8V=}0N&(JZcf`Nhif5)UG1_thb9h3YR7`Xp-OfqL+;QrGwNr8cZ`*+7A
zE(QkfUmX*R7#O&Jc1(<7VBr4IG0~ZUf%|*ML>&eO?r$9v#TXd4zjjPytY={0{?aia
zn}LD*bH{`b1_tg=9TV&r7zBTGfF=Y5rguybU|`^X(a~SUz`*~qqd$d#L3m?Fzdr+m
z$n=hWD+UIU86Ew~3=ASOJNkJT7(`}u^p!F&h|KQji(_CAnbXnd$-p2ox1-OPfk9+m
zN1rqUgUI}jJ{ATBkp&&SISlm-A`3fuLm3!E7IpMGFffQL?&#HIU=Uf-(JREjAhNWh
zr-p$+WLZZ~3Il`4@{S%~1_qH89X;j@3?eH#dK4HKL{@e5a4|55tnTP8V_*<j)6t#C
zz#y`=qZ_1hT}QVi1B1x=j&2nO29XUN-2w~@A{#rpKxS_0=*nPVs2ADX(G|wPAhM;S
z3pBgAwWCXmfk9+jN0%@IgUI%d&MF25ksTeKNem1kJ3BhP85l%%b#$6CFo^8#=#*z*
z5ZTkw$-%%NvbUq7kbyyDUq?qI1B1x^jt-Dv2Rb@Hh8^ta0Qu!mM|(8`gUI2I_A~|t
zks}@L{tOJF`;T)<GwL!XPip^P$G{*ux&40{1B2+4_WvNssqO#G85l&Twf|ROU=W?&
z4ytHGXSDw-Wnd7U+5Rt{fkAXu`#(<x2GQB=|BM(IMCY{slVM;Go!kD8je$XQUi;sC
z1_sgj?SCT~7(^HB59gL<oXS|gupKm5D!QosFG%g;c2G?tx}^P25d(wh()K^G3=E>n
z+W&YkFo-U1|6{_yAiARck30i|=*sp#+zbq&tJ;58GBAj)ZvUOaz#zJ&{dWKZgXr4!
z-!=>kqU+j!t1~c&u5bS>#K0iBq5W4a1B2+s_FtI{45FLbe}ywJh;FWL|K-fUAiAaf
zmp%i7=+^dM(hLlu+uDDzGcbs5Z~qDM+m801i3|*)JKKNyGBAklYX51;z#zK2{iiAe
zgXo_2pMnewqI=ta)G#oJ?rZ-6GJAjfk5C2%(F5&292poyo!WosGcX9Zw*Qb}U=VI;
z{{gD(o7=yaGB5}?wby?KnJw7<9b~pZ`*$k_22uX@?-~pYqI~V&g&7z`dE38%+|ASe
z4HOsL?cYFg!PWi^<O<IAZy;B2w14AgU=U?*2aTtSvbBE&g#~N-SCE-3?O#E$#@zl@
ziGe|ssr@T21A{1I`<E&P22qCgFZIa`3?l#AzxXgPh!}UQ2PO7@?O)6o7)1WIe^F#$
z5c$*og`0sv<ahh$5(Wm5U+te`85l%<wtseIU=aDy{#loSLF9Y;XE6o_k#Fsv85kHu
zzP5kLW?&Hc(*6mQkUzJ70_CGm?Vmtt?_>KX5e5d45A7f87#Kv}w|~s6XJ8O{*A5z9
z6?xkZ8eSE7)BX{p^mRLEbXDY4`v*`mecApYm4QLzMf-<91_qJm?H{Ze7(|}6gGN_H
zp0<NVS4Ez*gGN_H9=C%=S4AGRzX#=xhwbl87#Ktzw7-{QU=X?A{vMP$@3p@J6$*FT
z-z9=_{GIl9Am86^e`mqKAabkyohk!^$j$b5{0s~tH`?D;FffQ*Z+{EQ$Jg55dNMGG
zTy1}A$iN_SrTwiG1B1xr_P5Lo3?i4>-{debh+J%c6VAXOa-sbV$lK@J-+)5&T>BeP
zmOI=28swKV?XN+_$LaRhz6=cFBB$D4gM#~H`)g2epJ;y#Dz}dJ|K*ov?ElLz10rNW
zgdF4kzx?uy>;d~(8rT?_1lF=SGlGUooWND|11E5`4kizP$qis~0hpWsCL6$Hf;>p&
z22W5sqd}grpQS;8aXm|eBIAU;EQa7VfPxYuXkMj36U_Ty0I|RTq%9!=)K)lP0G8PR
zlG)F)0K%I9;;m<C0IMr70I3rIHBk1mIVdsyli$uV;VroRpag0rD1!(U5TObp)Ifwf
zh|pkM&sLzxDA3QQpvBnFrl1WXbU=hIh|mKO`i$$@6bu*x`q=~w8T;7;j6j4jh%f;W
zrXa$MaX*`YIpe?ot63f}8ti8=fH*}!i}4@-UKTA#lMK}2Vtb$o3dReNrq}_H5X*vS
zkn1NzgMHZ$4fcOQG$_CVEExM)0xTKVvjkW%ZrIQA0W|ltpH09TtR}&haX~+ef;Fg3
zW5c+fMZuQQVJ(Xt$o_<5V8a5AffYI&0|ll5m{b6h0$_5(c98glS`cZ_3~ITxfowIf
z12vfJ86T`?Nhkry2{?c(I^e*#pXGofBh!X{HUVdluU$ZdD~NCd5$+(u0~8XTjQ{+5
zS-co~S-ctdviLB1eybPAY`+=Jz#ydFeiKvzPH4ZW&A=eq-+ohsfkCvd{RXH4=xx6N
zD$sh`Zv-(gh<3N%02NPN?KhMe7(_eUZ-5Hmj`r&%3=E>}?bks?bzA#&P*L65e%+9P
zLA0g)x+DXGXmk5@CI$x4ruJ)D3=E=;?bkqt)i<<Xvu0ort#7}k!oVO}*M1FDgw?iR
z1r_Ht?N^f+7(}bvuX-^sh*q^<1yv`N?N_B37(^@DuQD?*h?cis$z@;=Eo;95D#uIP
zuQ)I;h?cZp0hOG^?N>mha#8zbP$^f~ei>v~LHlKI1_sgm_RD4r45E4U?UzB-NN)RO
zQ00`<ekqTEK{UG^G+->6)qV+7a%Z+*0tHD%`z272q_<xLmBVT67gHG+L{r-@`Y|ww
zrnFxKm9EL{7eR(4wO{05U=U4gzW@r7g!T(D3=E?2?H61a7)0aRFX%Ebh{m>G02vn3
zUVpxtfk8C7{d_V5gJ@Lyd63&8+s~UaFo;I9p9h&1-hLirT3GwJ0tN=r(Dri?3=E<n
z?dL!q4Q@XN@@P=|IZ)LW*nSpN{RFh11v$;X{Vb^9_iH~3GR(LAtQ-S_s89P@kUzcK
z&wwgnul6(bpjz0o{S3&X9_?o|85l&}+s}Z4&8_`3C=OiPPlJNZrTsK04xHOh8#6G7
zI<%jbV_*<dYX=Pxi>bGtDqvs`(`Y{x$-p3{*?!8Afk8~G{gfsHgP3;vDIo?1F`f34
z)eH<`y6q=Z85qR$+D`^DFo@~5pR}rHU=TBCKdHpPAZFNplAD1+%&7fDF$05`ar=pA
z1_m*c_7lzw3}UA3Cv+GX#LU`Hh%+#VnYW){WMB}pXg{9Cz#wMXemt0gLCmWCxHSWV
zn05PcWd;T@oA%>83=Cqn?Z?U(7{u(_k0mlNh}pLv^JZWWb7((i!oVQr*nUiop`Jm^
zsr?u`1A~}z`%#cDT-uLDF))a^wjXt2U=VX_KdR5bAm-kFREmK?%%lA%GXsN|XZw*H
z1_m*&_9Gz-3}W8xM{F4w#C+P1s4*~z`L-Y7V_*>TYd>7hz#!(|emI$dK`fyCunz-+
zSYZ2MQw9dHp!UO{zzc3a%*Md5|JY9-Mm@%4#rEAw3=HB*?Ynsx7{ry^cU3Sjh^w^k
zN@QRVS8d<r$-p44*1pS#fk9loeU}sigSbZfE+z&Ban1IfSqu!~TJ1Z785qR1+jrVA
zFo^54@6=>q5Z7(rDZ;=YuGhY!j)6g3e}DLIAI7PS^#<)bKxz%!ci1y9h#R%<&}Lu|
zH*VhnQftz_y_SJN+_Zgr8Uus4S^IW>1_p8S_U#r74B{5;+d)pWY~Rkuz#wkbzO9^r
zLEO51TLJ@vxJ~;u4+aKt+xBgS3=HCS?b{?77{u+{w}G7K(7rX7fkE7{eQOv4gSb<D
z`&N*>&h1+@7#PG|+P4ZYFo?UhZvlDOt$ho~!|v@{d>9zSJ=(XJGcbsIwr>I1>(#ym
z6g1xLo68s&#C_T~gH-yqZ}w(j5cg}}Y{tMK?%%!{6!#a~H}f(ui14&;Dq~;}6=~lD
zYLg1LZ*pf~5EW{#-=xpLpzPJYNrHhv*}Z)eGXsP2iS~_o3=GQW+Bb$XFeqPW-{`==
zpnR!)qb37`@|E_D!VC<`*V;GKFfb_JXy1^=z@U7qeM1lfgYv!h4b}_{$`9H%C^Il9
zKW^W^!@!{Yq<wuk1B3F@_Vo!249d^i*LyNBC_issZ^Xc${Gxq*y%Yn3^2_%1ptA5#
z`zsFy2IW`n>#`XblwY^63ua(Ye$&3rhJiu(ZTmWP1_tGK?dt>>7?eM@udQTYQ2x}u
zHi>~j`E&bPF9rtXFYRkVhJI~dE6u>5{H=X03j>4l_x3gU3=GOY+Sf!eFev|QU*pWc
zp!}<SjSd5Y^6&OFBJ~Um%75BdgFN%MeRV1WgYv)j)&2|&%KzI}TQM-GFto2$W?)cZ
zY+udIz@Wm^zN&<QL4~<}RV)L83QPMcR|W><NA0Wh7#LJo+gC|4FsN{}gU0@qrQ1Pc
z|0?Y5ps{}y?)H^73=Aqf?JHFn7*u%ML1X_aeC;dB80r~R_}f<`FfgbHw6E}DU{Dck
zUt!F^pd!@1LWY4sMYw$h3j>3SNc-|!1_l+;_T>=_3@T#n%N-dQRK(ktYcVjWNVG2(
zW?)c}Y+qKzz@Q@4zATA>K}EWKnKuK2icI@5kYTdz%Rq+7wJ&35U{H~7Uz*RrprX(Y
z8v7SlQEUed{;MdpFV$vXP*HAQD#E~^qSF8OzYk;o-~YZK!Vg6FGw%QUKY)>4U_Fa~
z1*5}y7J(2@t@|MwL_PqM7r^8JFu4ItP5{@;4PdgM1k`|V2n07XHcSCEXA%M#``HqL
z7}v8U1T#)p&-NgRQD84y2)H?r0B&zwNMZ!d0v$*Kx4t%jc<b2~B!OBd6Ch#@5U~QV
zSOQ3FJxf3m$Wb4HLG1*E5Kzk_6hwr9h;Y!jN(3X5!+y2`P&2Wgr67W_pQRv@aXm{x
z6yt|pmKerfmRQDKmN>><mUzZqmITILmPE$2EJ>ijnGZ>f{VX4n8TYe%NMQ_oR=>XO
zlsyB3#JaXqS_}*lYuio<GcZW3X#*AT606%zrZ6x_tZF;y!@wZ1vhAb^1B1khwv)09
z3=+%RPI53XNGxkRQOLj`v9#?(Bm;xQlC~303=9&B+fHaQFi0$FJ0ZxxAhEFRcohSK
z#DcctNem1U^V^PlGcZWZYddbnz#uWVzU{aI1B1kzw&R=(3=*^3jukU7NX%+G7Q?_G
zF|+NMD+7bXjJ9KX3=9&}+m1;vFi1>mJI2hwAThP=Xg&jj#FREr`7SZJ4OG5MOlkv_
z?-CQ+j!H5xNK9x0mG2V$ZAbDL7$o}IjzlmpNc6THab{qU=xIA*z`!8U-By1@ih)6*
ztL+F21A|0o+hLH>j<&<$3=9(OZHFBg7$n--4ue9bwe7Gd1A|0M+o5^}28rgjLm3PV
z5>0J~0vH%18ru$;GcZUrv>lRXV34S9I|K@uy0(Kw3=9&rZ3jVqscAb1@=JBwL6Bdn
z+75~{Fi2Fk9js?yV34S2JCM!5AW`0SAe4bYqO9!zC`L-#4uAr&r0swZ1A|0y+x}_>
z28p7!{izHL5`}I1{TLV|3flHtFfd5ux9wM9V35db+t1IyAd%a)uabd5BByO%G6RD|
zcH2Hs+-0@xGi6|q$ZXpOa$!c>K9CF3+x8ZLJd@V8H;#cpBDHO=2LppdO50vT1_p`b
zw!NT`Now26!oVOZ*0u)}+;MGtA{ZDXUE20IGB8NGw(ZeoV32fc+atojAnD$=yM}>5
z(xYv68Uur*XWQ-|1_nv5w%s-i43ge$yVV#NBz@X;3otN9`nK(=WMGi=YulB?P|qOg
z-?qz#fk85$ZI>wngJfXaE_nt9$)L7f+zbqo!EHNB7#Ji&+IGe=Fi3{B?Q~~gkPK_v
zsn5V58Q!*2oPj|yqHQMw1A}B_+m1{I2Fa*4P<1F7-3F=-C1culXfQBH#<uMM*&Elk
z9b|8O+x8>|2FZlB?LG_)^^%Eg+szpmB$L{<D=;ufCbw<pU|^6;Y1>xFz#y60wk?u@
zK{Bmvn-c?rWO~~+Ed~b3jJ9pU3=EQ)ZCmRY7$mdWwq`IeNM^Tf1^G9pZ7ayXxoulj
z85kt<+P3mBFi7UNfvQ8vf;LcfC|TIH#hZaa@=zP7I+Wah?q({Z8e_73+nP!S1}TTO
zHHi!iQjTqFycigyoZ8lyGB8Lvx2=(5V32ZYTf@%4Am!S&x{!fE%B^j6Bm;w#d)sO!
z1_mjQw$(Ze3{swLt3??Yq`cZz)iW?idAF^~W?+!=X<HS-z#!$jKm2wosKwydwo09W
zLCU{vl>h^SR6yHGki~&*E0Y))q=MR3dNVLc1-GpPSsc=~Qh|X%Dzt4S7XyP-SlfzX
z1_r6{wiU4q3{nwoE8G|uq$1l^=rb@#MYXMvU|^7nZd<{`z#tXV1}g5QV%tE)y;NM=
za%Tnxsra_#x(p0b3H5EuK}r+bmNPRjNF}u`%Vl7YN^V;g!N4Gu(zeW%fk7&@ZJ7ZB
zgH&4EGD!vosr0sGAVV|SmV$hf*|rqqo2<5_whRnX*=<Wfe#vQDD$KwjmD{!ilmy?m
zEddo<%xz1285ks(+CVeD5{zw2K*bhATm2GN1_tr}ZHx057{vdzEskVh5dYf-n(`I@
z)3#WbfkFIt+hTDB2Jv5Qiy0Ug#DBIe%4A>=|IxMx)Xw_ew#bHoLHt|WA~gmE@vm)*
zgcumazqBm`wX;6AEd;6j)V45$fkFIZ+d@#w=tJ8=Ed~bh_iYPB85qRhwJoe?WMB|~
z+qNKwfkEOy+Z|N~2Jts-pb22{*KG^j7#PG~wJiX(3}3b_kYivFf6=ypi-AG>dE5L_
z1_tqGZSz45w5M(JK@FuRZSz4*s>f~fL8d%vn=i<~ApWpz9>_5d+U9{AbH8m~C<BA|
zy|#JI3=HCT+vXY6GcbtXX`3g*z#x9RZ5{^$gZRz1xg`t?;y2png3P|&HW$=fyVf?>
zl7T_|YTI0p*;m@;g3P|$HV35rQrnyy1_tqqZF4|@ccE>LD+7c0`L;PAXP;}E19JA+
zwmIAk4B}_nW>+#Wh@Wnoox;E%eyVM@A45HZ_{p}}Aa|c=o2|gWAbz}UHpqv^+Gc^8
zf=AnCftrFx+Gc@#c(`qrDFcJ}p|)8dLl3si0=f4<+sq;c2J!uEGh-PT#P_w$^kQHT
z-`h6Rn1MljPuon8&vv)XWMg0u-_<rFpMgPqXWI;rLwB^z06A2Ad)o{>1_tqMZ8Jd8
zytQox0|SHD`ToE6QyKgJ-cJJ&=^!G5asS`@nT(tP``JFUg6s4Py`Uz*fnIQ(zM&T^
zwxAbOS5E-TG(cnuATkMHnE)_pkOfw?7F44LWP!#TvO(hwIgAt5vs|bK$$iKHnH^BV
z_=kVrfojH3wtBm^Hc<MvZEIs=V34wDYX#+d>o(B5sFYP(D=7O}wzYzCibY$i6a#~l
zd0Q(B1A~-VTT31TgOq7o3#f!JX=?%HDdV;lLk0#ZqqY_q1_mj^wib|?25rqCGxgh=
zqZt^a^xB$1Ds|hML1yaIw>5(d)oyEMWnhrfYHKQDV35*mYXaqdjkYFt1_mkhwk9J6
z1}U|+CXk`3ZA~CURoWUshAOu;f(%t^YXmt|v8~aVfk8^4tr1j|$+tCfGB8NVwSi_w
zrDWS0KxWFcHFz*ENJ+Ofm@qI%Nww8CfC?YUwgzqn1}TZw|D_BJQsS-u6Brnz#9IIR
zFfd4ow*EI`V2~1N{V&hJASK-TpM!xxN~rZ;0Rw}SVCz3ni6YSY&w+tKiof-r76XG6
zU+X^+1_mkK*1xq33{pI;f72Kkq_|uE`Y|v_akc&h8OGWA7i1Vm>)(2i6WLq;lrS(z
zv9*E*t)*C7|A0b>rS*><1A`QED`<LDimCNCsI+Bl{hh(UAjQ!7JD7n%@_#F6v|93C
z>u(hX2Fbszzj+xLB>%MjDrI1h{N4HsRGa;3{pH5MAo;TuG)gV`qxF{*1B2xER?q@p
z$#1PcbL$xxB)_))3}s-D{L=c<mVrU?b1P_kTJlrtPf)LPX)9=jujGf;AIS_1l5bmo
zfP&<5>km-qU1|Lx%fKLYwe<%mMy|Df2PKH>t>42L7^H5reg{<<H(S4JGcZWqYW*(6
zz#w(I^;;DKgVdeYZ^;Y{Qg>Uw`7+cqNZo7wX3oGMb-(o+C@LPbegg%`!`82$_<hv+
zHHv{j>T&B=Q0e}p^()A<r>$Q>0sO4>D+2?A)brLanG6h4FIv9@GB8NJZ2e-%z##Ri
z^$W<b*R5Ybwb`52&-n}tQg2&7gPiuR^|K=bgVg)h&)N(O^->>NKZA<(kFB4o85pEK
zwSEG*?Q`oVP!;v1^%E#TeQo^&^60nLPaxC2w|)f0{g2j<pt%3p3L1Ns`qlbTlYv3%
zck4$%1_r4=tsg)h{o4u}dzSjw`oWihLF#|&2U7+HX@=GhvJ4E;fvq1{85pGZpF3F%
zs+!NWzA$EBkUrn~LYjd=`a<gq76u0Ci>=S|85pE5wLXtvV34kBeeTG>Al=aV9MnMg
z*!o<EfkC>l^;s1IgLG5tvt$Ma>E_mFehduKEv?Ti7#O5mTc0U1Fi5wxKI39wkZ#`}
ze!3b|HFvZ=jb>nw?reSP!oVQi)%sMAfkC>v^{EsCgLF^pQ)UJR>E6~S*$fQQeXUPI
z7#O7cTc6l4Fi1~meWJp^AU(152@eB<^rY6ur3?(xlUpArFfd3@X?^U)z#u)f^)bj7
z(^?<PFfd3@Z+#5%#f;WRISdTaGg}{pGB8Nbs&9Q{%fKK#yY-Pe1B3LO)<?n&4AOI3
zAA&aA&1-#_%D^B!zxAO%1B3K})`uW(ENp!U^2VaphujPd(u-RklrS(zFKK-c$G{-H
zwDkeV-es*1Oc)rXm$yCu1?`H~2kZ<C(koj*YkQ?vwSw06O0RCc@65m;y{5JPzAgiU
z^x9U?;$G=>t@lCxUEg{S<iriF_dx#L*m@7-!cDFBR2dkgH@Dv7Wnhrr(s~!<->t28
zLH2HIz3a)qAicfyF37(-TJOp+Fi7ugz01MCAib;gP7wox^zPO>F$@gSds^>!Ffd5(
zZM_3hxv%w3Jt%1Qx84DjclmA8Eg2Z3547ISV_=Xz*m^shfkFCE>um=H2I<4Cx3w4;
zq>r@T7Gq$LKH7S#o`FI7SnI8H1_tTlt+zk{bfWbZD1c73-cn#-kUrIVi<5yt`gH3}
zPyn52y&22EAbqy=rYi%3=)~5Wpjf`#dQ%LP<7c&k25BW{w%$l*V33^A3L2!9oZfl^
z)U2G=dIQvqp4xf?)SR8tdcBH)L2`2I^;8B1$w{r({TUb}C$?U<VqlP*(0W~+fkCpr
z^*TspU+Xnc!?(Bf8mQsh(|XN|fkCpn^_md_gJf6hHE9M0$<Eem?4ZVYN9)xB1_sIY
z)~ld~Z(HkCX9fnz*4C>!3=EPjtye`E7$lopuYel9O|4fz4erL)E1>eOq4f&Lh4rmh
zKn>rz)+?ZfZ*A-4as~#;npV(Qtz>oUWl%f6s`WCconP5{S&o50vZ56<R4ZBD3L2`F
zk}PWljnzt)wt^P-N|v-<0yW=@TQ3Q(+fdCYux~*%Ba6U#mI>ervjI#NfXM_f82~07
zz~qA*P*p3C%h=B%kOw02K|}$FC<GBjAflLYJ&QmIqeDN-hZ0b?xD-T`frxStQ2`<<
zL0#o4My7y%wg=UW``I4UF#cP=o@GHTXwAliV<1}`>KNCvIMg$K*w6A{9=L6AU>Ue=
zuwfafPG7JLEH(im*02mz+ZTYz1h9MnNPaz=1Bk<B(7^bQzn|qn17knSgGR>nEDxF(
z9rm+0G%zwP*w3cW3^um`Vr?^HKZ`>P$nI9g3Hw<NOaa^T0Mb@*0Jl2|z*7(lrhx36
z045v2WC55=m;!QN07Rd|6z~{@0fct}WXgV)0MKwpKbt@sXx5<}M09|NP7u)rBDz6D
z4`@1~m+_x|Kg)w&ki+{xL_dg_03s%Wh)E#NOa_fXT$sYx&vIcZ<9?P4(-_$wFizah
zvtc@;6I;Du>j72<1`&hS{kaSbBKocSL9>l|t^4g67({ei_iHdPi0HKL2Thx6x9+QD
zU=Y!2-3OZK)@<DeS}mZ_x(_tlr{1~`H0!3;x(_rlsM@+0G|8#bx;LJIK}5NAuNMP@
zh*Ilb&=jI#>t4_VyF%+;kV^Ub);%Dla;<wnN@ZL3cr!4F$h7VOEd`Kn-2++*Al15u
zlYv1*vUPV61A~Y}>+Wa<1`+Yr-7X9aB4Vw(br={#L|b=@GBAjUwC-kPU=R^*-36LC
z6>8lD@{3^WF3_yKK<h4T1_lxS)?J`ER=(C<pgC6F*7}_wrQEGMBN!M&xLS8QF))a5
zw(bNe<!A+s{)(`-?f@+;U~Aox!oVQH+PcG+fkA|&bq8p&k-2pT$TLi>J3yXcY~5bW
zz#ziVx;>hKLHK{`cF@YRf34d=>$?87ZU-%z`qR1%v}o#g>$Y?T2H{_=+v<ZD7=(Ye
zZnI%v5dP7+O_hN`_<QR%&@#Gjty@9M=)SgY1uZ@M(z+G2TI+M`R?sB)r`D|!3=F~_
zTemVZFbIEW-IB||ApE{{3uqbLyVfnB)mm>`w`edh2)}9F0$Td@x^;5_1B39Z*3BUd
z48kv4H(N3=2)}6EEDu`F_Plj7XwlcR)=i+*cu!k5g)uM)KWW`$&A=d$*t$uMfkDEg
z6*SB%eyepOsKBjh-RQ-@Ad}R(QICN^Cb<<fzAKZ`x}k!BK_<0zLmUHxOj_#(7X}8I
z^wtg93=A?Ets8_H7-TYA*H<wx$Yiyy2Pw&JUGKzD&mfc2x?Y2UK_<6#JtqT$OkOK!
zC|4%Gb)7#0gG@o|I%5U~nZnj};tUKjMXhUV7#L)VTR~&EG9|5RJsB8eN?X^0Tv67#
zR)B#)ro44c2?K*nMeCYy1_qhR)-_fP3^G-%px(Spb?X{t1_qg$*3}sd3^KK?tNj=l
z>SgL$SDP>}$key4mS$j(X=q)|#K0ia*t#l{fkCFJb(JpzgG_VlDnkYanU>a7Vhjv2
zt*t9T9&Kw~8O6XL)84w$o`FH8qjjY+1A|Ow>q-s=2AQtb75NMdGTp5!!WbB2dRkZ5
zGBC*WwyscNV36r+T>(<k-?}`Dfk9^f@txB_D@9^k=UX!{$i}tKS7Bg~jc*05FP2Sc
zomauYAe-1aFOh*kHmP-<Hv@xgaw}+gv202!s6Q#2+B%Pwfk8H{b#5L5gKT;$XnC=0
zM(bP`1_s&8*15V246<3RpykD~+55wHPY1Pla$4u4F)+yHw$AZmV35sgony|xAe-Mh
zM~Q(!wxAW%hm<XBon6AfAY0TrJC=b#wzze+8v}!EN$YGq1_s&E*4g3=46<ddvzZwf
zWXoG;<uEYFR<zCvV_=Z2Yz3_^maS@?rNO`;Tips;_a$4?I<uOALAJJaCdk^l`qr6&
z3=FdMtusL$ZfKpU%D^Do*gBJ+fkC#Zbw(uvgKTr_j3fpI*_PHBJ`4=9t*tZ67#L*R
zT4yLSFvzyI&fsNWknL!lUe3TE+u1rjfq_A`t97~;1A}aL>vR(a23g+L>7Z6cK<jii
z1_o*W)@h&yh+pe8Py@ubwSJl_1B0|r>ok1^25IlsX%Y+!(q6687#SF(JzJ-O8hReB
zQ^Ob-q}^Mmf?Akvty4iQ57*YIpr)Bi>l9Ga%(-<6sA=ZZItA3ibZnghYI!)cP60Iu
z?OUhtF)&EmwN9>JV34+LoeXM=+O$sgVPKH9Zk=2YYW7;SPL^k2keSeWF@=Fa+Ol;r
zsI6krItkQPF>jre$iN_N);h_XfkE1|brPsCXVN+e)TlCUodjyk8MRI<U|^6oYy~X?
zlQw9b2=bDC>qG+v25G(4iINNq(z>k^L0-~nosh}EAg$dxA&`MVTB~&eXu?ohvvq<J
z1B0|i>jY3EQoXgmjDbN~t+hX%fk9fewI9?(Q)%rtWMGh1ZtVw|rqtTc#K0h}*xHxN
zz#y&A+6QWa%eVG{8j*6XeR>QG(z306prDj#?E|TlZtVrBlxpn-HR2>&dz}~<q$OH=
z^%?3Jq{Ul%L57O8_JWj(w)TLUn<A|}pysA<YmY4hgS1d<52!&b*xDn&z#uKq+6`*g
z^S5@VF)&E;wRQ(EFi7*Zc3UwpNb|IIgBqsXt=*td=W6W&g*s<z7bw&@TDw4@&feN(
z&cGne*4m}Qz#uNo+S&zD%F^0d&cGne+}a5WZl?af`=>MZ|J^?WM9c&cvl#dP-9MX=
zJzzbH!W?j|eHlCv;c%HzU_G0`WzdX*!ewylK;SZ?z*-iNILn7ipo;$in7jZc1?GT6
z4qO7YTMXua7H-Z3twWdxYCvpQ3pVn?Jdj}qpytYcmIWZO{cH>NfQ@cg3({QxCKJ|z
zodJ<|SPPan0Lv(VWez}^LLcUVWgN0VHVVuKHM<soh=m|x5r|j}B9?%NrHuPo1eP%}
zDfF{lSjO1Tc40Y)SOFqdf{0ZhVm0G_whL<*|M~Z`99RolNV^WSVq!gLrRkiO?+FYH
zl5<<WdoVCa&TIK@$iN^uzva6O1B2v(mhY?#43Z05zU4A7NG@vm7RJCJxwz#UsAIjP
z1+;}#a%syqP&a*9%U4i0eR<2*I0gpE6)j&q85ks2wt%*<O0H@FZDEyM-SU;0fkARj
z3up_g<l2@mpf>Qj`j#)&3=ER%TfTrg{To`o@G~$-ZfyBn!N4H7spT`sX`5R<gG}4f
z^4WlaL2_%$X9)%d$!#s485tNPx3_!(wWxQrd;$$6?`-)5a@wwzPoS3k?v_uWmi(TU
zkDxaH-j<J`KL5U!kDwOy{+5qs3=EP7TIxT7hOiH|d;|@hA8z>oDwNDxK7h(=)0PjQ
zLdm4%1E^3kZUJ?4WsO=surV;m8n(PIU|^6nXn7ySz#yyN^4^t!K~}Hjy%7V0tZvJD
zX$A&aotF2Y0#>`_9jJiSYIzsJz#yyH^3H~VK~|&X9jKa6Z+TbG%fKM3)&g2xC9B%<
z7F2Aiw7dn?6Ur@bjTsnZm0I3{OjB%m%fi4QtI+Z$pMgPEzU55>1B0ww3utwftZWNt
zb(O44%Ns!k23hHr*Pt?3s^vAvFv*tJAj2eDUV}U#-tt<Wfk9TR<uxY*gRE%FE6`+y
ztVqkN7zPGe;g(k*UkJ6l0#y@&Ew4b;gh0zHMg|61{+5>@U+}fO3};}F<!*WD#K0i?
zvE`)>1B2|RmX~4-46>hFUNSH+$bM;gk;T9u`?ci-$iLrOUf3}($bN5mp~=7?`=jNB
zC<BA+&z9%)3=FcrTApVx)HBHbZh0QWz##jl<vFNA`P=dw6g2-@p7Sv<$o_8u4G73F
zw15T#<QQ9?`7kiZF||B1WnhqFZh0odz#zxc@{EOnL5{WMX)XhU99zrN2nGf@_LirP
z3=DD{El;%=800uxo(eNC$Z@qisb*l1<8FD9!oVQM)AGchfuUZGx8;c?1A`o2%M)b=
z208wgC%g;{asn-n%NQ8s1X~`*Gcd>rwLJD@V2~4Td2GbMAScoS8V`^YZF$VWz#u2q
z@~DV`K~B8oQ49lvoJ7kbHwFed$(Bd@3=DEoEsrD^804f|9x*X6$jP)k%w}MalWlnz
z%D^Be*YXhL!u`irZUD6(-n85V+4Q#MCdj6DEjK|ny>Gb*^5KV;o2(2Bavxi6<S{VF
zeQLP@^5N%}8%_)ia$j0*=rAzIeQmh`vgupP4MqkAx$iC4GZ`4<ezaT<W?+!}*>c^6
zfkE!q{_xcsK<$U$E!PDZ807x6fO@!ce_O64GBC*fYq<up_<swihbzy}a!r<jL7uVY
z8ao4nJX6cnLIwtT=9a6V1A|yvKpk9p))r6)SDvlqsu%-<JbTNPdIko0juub{SDv%w
zN+<(^JXgyVdj<x1?iSEuBzc||&|)Nc-ujly)eH>sd@YyL85rdGTQ2)EFvttEfL0^P
z3$}oIxbi|RpdPNgaLc6v1_pVNmP?Tg4DzBamz)?F<i%P*i;?8TTP_JPFvv@^T&!YX
zke6(^n9RT+FV%9<mw`cUPRm75b@8|5B4{AtU&}>MyYzm`g+c}fnR_ku7a|!LWbU?H
zaAIJPxzln%i-AGrcFP4&`}S7L`8oy$nVT)=(-|0KZnT^aU|^8B-f|w)2EEpDUWtK0
z=4#7%ZUzRKD=p_r85m?Px10mDgfF$6^I%|*x!7_J)DpeWa!!tcLFRnRId%pHnR6{?
z3mF(>&bFKdwKmVRoUI4hd%ESUHUoofZ)>Lv1B1+|ma`%Z3^FHM&VZ~x(Q*dVc0Jy5
zCYXUi=2*)a8wLiMqb+CD7#L)Zw4C8*V30Z7avIcxJ=AhKk%2+xV9RN51_qe}EvL;u
zEz*|LiVO@g`&v%(FfhpMZ8=rOz#y}y<rGNe?v_(N^$ZL$yIM|xl<sUf1yZ`B<rE(S
zgUt4pla&k%GTT~CCNVI`Y;8FSGIUD|Xa-wmbIVCt1_qf;EhpI+7-TlKoG4&mklE03
zB8GuMW_`;ER|W=|buA}!85m^NwwwSpve&d62l-`n%keY@2ANeY$Nd->WLCBuHwX0?
zR<s-kh2`=V&=Mt?Wi6m3N-|4ZjwLWK$Si3&2I>_oZaD@zt7=ipF;D<4Y&pitz#y}r
z1vG;#Gr#3%Gy{Xoyq2SG3=A@JTaJQM&S^Oca^dWjqoCILtd=9i3=A?eTaJL@XGY5r
zP=9B7%MsAbh|IK>BOq^2Z2_%Rl9|$S8078A{eRbQVC?_9ej|w31R^#w?*F@f3nOR1
zdbR@>K=u2A8;qcRDidxn3an>o0Fwn^GT{ceUcUiu3pju{Yz7du3O5)9dRewI_Ofha
zT+6Z@v~^{{F_7W|+rc9b4Uk5{1IU8MJs^WO>|rce&vF4Q@?krpz*?61ATxF__Ok3`
z>}A=-*vqn;aV^Up#)kDQ3VT6jEnr~+od)8t7u2p1aAp$N%jV1kTDtndiHS*IKidN*
zFz*70x1Q~Q6G$u|87#Kp57-$G{(}cHHZU=P)}{vRW!%peu#fTI`TZ;cAHi*l2m2ZO
z*&ZAK5eGrUArNsGL>vJP@EipXWNbLb*w3=zIEXmGxSwUiNyb37`qwR+f*2U&UbTSw
zqjE1>HmNc&$h~OUB*4HR_q=6e6$69ZvzCpZ68UM%Mn47yxhE|f%^4Wv9=B{%U|^7Y
z)UuI_fkEzJ%Z6eG2Dt|<8)6w4<nFg@0F_qvS~i$4Fv#6)*&xTjAa|!_1E@g0-Lf83
zAm3_P4=Rvv*0-z&mB=?*)`Lpq>n-ag85rcQwX6q~s8?Io6)-T!U1?bt$-p3Yxn&)w
zM7`9q4pe7cY*{D7z#w;_Wi6=AIN!21nSnv>T+3Qe1$4G$Ey#suTGlEuFvy*5S<B79
zAa|-|4XDaE*|H{qfkEy>3uro8?s!W*Xg*r*Sj!rD1_rsKEo(rYInuJaoPj~^aLei>
z1_rr9EvrF>9&A}{#=szVpk+14+xuHqgH-NoSp_n5ZwqMWvD}`PRUnnSTULQo?rK>D
zQn|Bb6-ecdmX#$84079BR>m<f$Zcy`2@0UCEi3CmA+)6hG%GE)xn(8DrJGtnJCNlz
zwtyBP$!%x>Ekcr8-?9Rva$U;`kVDtDtN^K8)3O}o(A6!=K@MHjvK(an%9iCI->+y{
z4)Xo-mgOLo%UYI!9J;gxv=3QsNy{>j%Ec|qEbAE<<QBCoQ(<6`Ti60R=}vNX%hE~)
z2Dt?-OF=<8zhx<?%%0b>)PjLQZf?s`B?bn$SuIO>85ranT9$xH_r{hbsSFJAO)X0T
z7#QT6Tb5WcFvz#GEKy-#kZ)~S!pFcM-`29Yf`LK4y=8F{1A}}=%VJ*!2KmmG#g+{9
z4Dwwqi&YsI<hxrI3otOq_p~em8QR;jD20JRzOQ8wsQ&41Sp+h4Ldzm`1_t?wEucAS
z`AIDcYZw^hC$}sF)l^ej76vmg$WLtn%~8uwYgq_VIlW~eKLdmOjFtuE3=Hx!TNcDK
zFv!npS>VpVAV0fhfdK<Uz5JY(1yT$Q@^f1jFf%a7&ual~OO~JCG9P5xf)>!Qf&9W2
z(6E90qL%p}Z!c~E4I9WWX#ouzXg+G0=gGjJq24mjkbyx%t!17h1A~TY%RD9q1`U;#
zx!DX18p<tm!x$Jelv?K6Gcaf<w#-#$V9<QnGFO0sL1F*7ohLz4GSw}hZm>d43#c2c
zP}>6P1}oIHOi5v2P^fR2;={n8(9kl)gn>b!v1N)J1A{_S%M=a<28HI9$%PCI3N0;@
zBN-SJT3aSNGB7B#wM^DzU{GjpnJmb_pwQ7WshWX7p>u!u?vtPfMpw%uUj_z+?v_cW
z3=9fAEt6y!7!-P2Cb2RwDD<^V%wu3s=x>=A#=xL3p=F{y1B1fEmWf&n3<{H4CJHk!
zC`@jdP{Y8WFr{TeDg%SU)RqY#!=|-N02wyDWdg`;Gg>CFGcYL3Z0QHNZB|Qv3<HD0
z?3R941_p&W^)3Cn3=9f$Tl&Qq7!>BU^wlviD9mr^OJ`tESkThv&%mItu%*v}fk9zW
zOP?|WgTmsLJ{|@Jg(WSZEyxN>TR>Zo6_&O1x-l>)EN|)6V_;BN(E{3ntgy1Bmyv-%
zLA#|Vn}I<tucZgnlFM!Bv1eeA%W3J+U|^8TZmI79HLtQ-KzoqoGFw1<kmWL3x<N%-
zdJCw_E0@*++W91x+R_bbYo@e-wjj$Tw{(GWZc<AZsJu#S=>nBk2`ydX3=DGdEnN%@
z403TTpe@L9u`Qh-dt+KU?HCy3qFX>)kmaIUI{6tG<RV)->OomHqNO8|fk9rT<uIu2
z7v9nV%4A_J9iW0Ew50=-$3t2=K;>m{OFO6#3~FfyH7f&K+Ck0IfR=Vpv(mq%U5tT2
z&ab5nl#P8`+A<gz<a}D%0vH(Nyjws!k>$Kv+CasCXG<F=1B0ALODm{LA?M!G3M!}F
zT0m3oa;`0{AkVn8fVLvbIk&WeJmb{T0y539r3G{vr9(@L6$68ueM<|dq_Asg;b&k_
zv}<XuU|^85X=w&EQLS5=y%-qetXi6l85ra&Tbe;_V~ZBhRJ)vc3uq^@oLNg#Btt!e
zoM}sw3j>3kNlTL+1B0A#OB1MZY}C>OY8)H3G-fd{$QiUWhA=S5>9;i6GBC*LwKS?T
zFv#h)Gzv2?$mz5+)G;u~X}2__Gcd?$wKRbItJ%^3Dxox5Ky&PJ>Mac*|Ee|rFJxel
zQ*Hhq#lRq^()=H^T0%~_`9H|NO3nYJ7#QRfoBx9<8-@PA`%i*~B~F2e(;(suXn^7@
zBfG(VmJ9pA_3(lH;1<S)m!O8ggpVMy;UlPuFZc+SPxuI~rvpH|^=u9xDK-O;*m{-^
zXF;kH1epZ-Sp?33h6c`qh6XM$GELaeHsL<R+zTKz0^l}F!+o&1_aWv&<OA-5<Q>2=
z1`rtqkj#D-0T6F38%Tz2!3FSq%Y_S!>sc;bWc;w6#b7^ZQAWT&(0E0{WyXG%gexH8
zDu}qoxSu8AI(T!&h8v9iY#VNZh+81yHi)<bBJMKoXWMWOJV3GFK4U-2f(MNISr$BG
z4188!)%?btfkC0N`HemUgF;2~8wmymh4SV%3=9kkWzDZM85k5wn_q`8FesEXzqVyy
zP$+JGt;)clP}KaImw`c{u=!OP1A{_A^Q!~~28I0QSKbT^3VF@1KqXyn^D7w!28EpF
zS1b$+3faw|KCVJm^UF{M28GP#mmtG3>YHDxF)%2kH@^fGb!p8nKt)|@^NTbF28ER7
z7l8~63dzkctQZ&+lA2$rFfb@2HoxF!U{FYCeqP1Epb+2u98~VaH9rTbjBS1nQW?_>
z>f<UzH$MltFsk_($c2&3&p<AWXnqEAVR$pBkE;;YT>ng-fkFC8^D|Ik9Mb%>fPq0F
zxcMolFb-;d>cqgH5ZDar<SGO-KNVqMQ1EYl3JMv&<|kPU3<|!@pgC^^pXMia3=9h1
z%}>-B7!<skpMYux&*sM<7kV^5PG(?GaBqGLDreoAA6qgoD7ZF1R$^dKaA|&A&&|M~
z;N1MEgn>c9sTtJCRd8&6<ifz9;L!XCRL<HrKLVArcFm7K_S!asI=Koq%@08_V%_}E
zhJiuBs`()(Ml72jg8XaI`~c)%^X3Qf3=9fp%?~^n7!*vK9~d(*D3~;Z=DZb*n;)<-
zFen%`-_NgSU{Ek@z8}uOpkUB^-+_TaLBIJvsPfTkz7MJ`ber#iIvNj~?}1W+X7jyZ
z1_nj`=6iMw42lBH_cR$86a|~_2{SM#3N_ya9dRq%d^d}MK~bdnZYTqTqG<D7kV>)U
zyXp)KisH?81sE6<C7SP4GB7AgHs1lQwp5gAzT?HfpeWr8n)FtbX}%-Rz@RAGe20^P
zK~b*xb_oN6qI~o1cm@VVg=WyXR*H(vpmVJhm6}24S}7_w-v+5vX}(p)z@Vtwd<&#f
zt@)M*1B0S^^DRRL21SkLTapY6iki*07#SE8wVH2&T&UfAGnj#)UQws{rY!@5qHgm|
z4F(29z2=*O3=E3;%{QtT7!(bfZzMA?C>l23@Md68G-?K&Yo%!1d_$IjLD8i71{(u|
zqG|K>LIws!v*zp33=E3q&DUKR7!)m<uj?`}C|WjO7iC~jv}(Rq%fO&$-Fz*LfkDxx
z`I;XCgQ9KoHFE|A#r@|xAA#BrT+L@~85oqfo6jmSFevdfpJiuYP~vSqlgq%M#Mcb!
zsw(j}pRr<KP!ec9qsYLZB-nh0gMmRwsQGjb1A~%q^XUKv1|^Z^)20jzN}|oD#Tgis
z#F|f4GB7BKH=l}QU{I3SAKv{4)P9g`KBdmUpd{6NikE>wNxJ!D2?K+YO!LWT1_mYB
z=95kg3`%m%C)F4jl;oRFaxyR|DKwwRV_;BHY(5dfz@Vhmd;;VQ<>nJ0m#Q?M;9_7<
zQf)q7#K54W)_gpQfk8>V`M5I!gOWz`aa{%mCC%pJAlGO$A7^A>P|~h%K9<SAprq4$
z4CG?n=3^EN3`%;<#}pVCl=PdAfz%i@A5CIlP%>;j>d3&LWYl~VWRr38Q6>fkC6neO
zX$%ZXrp-ru85oqznva+<FesTf9|38%Xg<Qhz@WIR`7mf;<7@L_(7?u*=EI<YjnB=8
zbr=}rKQ-4MmSA9z|JZz(iGe}>L-V0*1_t@}&4)lED({*Pfksr`HXqVpV32>)d<ZlK
z^1At89Rq{>tLB3l3=B$VnhyptFeqJYJ_rhg3(W^XPCMUxkc)vq{%P}pVg?5JC(Q?<
z85rarHy?0eV32>*d_bRpLH=R$0g$y1nh$_hTgu;W-k;6Dps>36AE+sNuX%q61B3kC
z=KZz|4DxrH_k-HLx10Ba+S9k1_kr5eH=9Az%JMgwLDS0e*PHj5Gcd?sYu=~8z#xCM
z8MJs>{z~&+khd>4?*)1LQuAJr^%t8#XMo6GXx<ANM>^lUryewrbgp?%1_Oiq+2%c<
zCjaT?J(dg%@~4{jfZFjVoA-d)+$WlMS28fjA8+0b8u~fbyxWI?LH=m-Zc_#Z`6JD{
zK`os8=G~kO4DyGXca<_Q$RBLp70<w+bgp@q2Lprr{$|i-BKdvIyQCQy<o7o3VqsvA
z-_yJ^57cAW-3*#fmfzL9)0u%merNMe0|o~99nCu>85rcZH}3>R%(mtoISdT)Tbp-;
zF)+w)Y2IPSz#zZ5c?T$DHZ|`MW?+!t*bLfBB)_3~JE;G#zIl5f1B3j!=Ix-K#@goX
z$_xzhYnr!%TKub<x0Nw4$ggS!?<JC7*}M(pnHA03K%QCNyiJaQL4H~P-~LC8`~UVo
z1~(WAM40~Y@4N7rk!8YqmIIGLHE+Qa(58l`jQd#%o-r~NtY=#Q?)^7#F@Z)c3b>dA
z_Om2#fyDwqV*6PfK)m&A1|TUm1(4W!76C3Mfwe4LOrXQJ{(zeUT1*1HEYBHxSza)%
zWqApj^=SA3ZZ#};$@q_dEep7rQt$)RoJasktY-`O0UC*L0Fwq_QUN5*Ch!Bi?G&VF
zKih}z;I_<!m*CSo4!mUSXFKo;M7#zOZ$QLb5b+K~yl33ccHjf!Kl^@`1s_2Tgij#i
zGl=*CBEEu%Z=goQcksHC2|qxGf&2s=2J(y1FRWgPvw4X;1A`Jr^Ab?0#NNEPfPq1Y
ztr@hIS&6lIF{n^sX<n?wz@Wt3yjYllL5Zn(Q9T2L5@R#y_$noa=0yPv42u7o7g;he
zDE@0+q{zUa__uixsAT`sys(IYLGgDp==3VZU(E~M7#I|PHZRm;U{L(gyilBhL9zaO
z^8!%i^R0OSsEGaAyZ}_heraA{#=xNXxp@JoM)}kXTDGkCv3WkIM)}Y@KbC<(@qP1r
zcLoN<cg^z+7#I}aHqQsu6K|U5GczzKzHXkE%fO)cs(D@n1B2qr=6Rr!{YCRUeFg@_
z=gpvgqT;jWc`OVJicjmC=jJmoC_ZVP8^yq&__%p4$k0d4b3v8Q!{)hC3=E17n&*O)
z-fx}*GW1^aoNxvP#k<XOoEaDt?=;T=RTsCL=YTwOt9cHnn!4FMJDY()@kaCPFa`$2
z>&>%4Dz7!q2C2N-JX?%`LGeoSta=6p#mmk0v(gzD6fZT;@@HUByx2U;f`LKtLh~$8
zAf9iY#m&H=c&>S7IRk^@+2)y`>hVnTOppstH_rrl`&9Ex2?hqmlg%@k7#I{!G|$Lk
zU{E~XJOfmLA8VcgsvVCu&roGxP(0EMnq5{r+&mpr*B)w~9>>6-c(8eTJ;<~J&C`uQ
zHCpp@X$A(xea+KBfw;GMS`Gt)TtV|RP{Uz&^E4|42E`rC(?G@Myyj`3x?_IxR8S4H
zpm{2&np)UA)t!MsX;Jf30|o}A#m!SC7#Nh6G*4w<U{G4xJOxyBENh+uDub6dPXU#|
zE1IXMf>P4TX3)H{(yHdkWef~TtD7f-N~1N+lR>7fZJw;hz@W6Qd9oM-gVOruNp%bi
zN*kIdflBm^&69!{7?d_OPqJZPP}<x)2~_iKX`Up&z@W6Xc_OF=-PSxYnSnuRd-Fse
z1_q@a%@aX&&d%nEAW!USp2*8k&!Dusc|th@gVLVn35g60N_(3pcr!34?Q5O@s*m?K
zPXJ|(1I-ga)#<_J{$d6Or9;jAApah2?)PM1P&(4wZ^Xc$bhNo&ih)7tSTkroS?PFl
zUls#{(uwB2U<L-Ilg)kB3=B%An)_537?e&o_wh3@D4lKYtzcl-fA-}sMs>#Inayp+
z3=GP%n%krq7?fu>x3MrVD9>qb&1Yaxp4;3S!N8zAuesHcfkAnGbE_5ugYtsrR?z0d
zh0QIX{d$X<ThbXAlovOH`i#m;np;4d50^HBPOnm4)(kqmN_qMI@YlaUt%w!PpkAZ$
z%4SfnQF&D}==>_>)y>Tc3=GO^nwz;87?jsGHx)B5D6eY<Eznk8-`wQJz@WULxe2sC
za$|FoBm;x;rsgJQ1_tHL&5gMX49Z)Y8zUJQl(#lFIx#RPZ)<J@IdOY4sMDytqZ!m`
zRNmPP>NG0vs&5AM8kKi9H&`(+DDP=*P-0+E-rEdXnXSC9>3<0WgYy2S|M3hA$_JYM
zgZ45WZ2E7)z@U7n>Ax%kgYw~~|7;8l%14_1fr7@f=^w~m@1}oF3=E2Un*M?IGWs<A
z1MT4SZTbgtp<mPA90mqu|E9m83=GNvP4$0m85ooUoBpaYFenE#{pDj|P!4YTQ^vrc
z9Mbd$WN&EGA8!T*<*+8uaU#m$O@Bc4Ml}5a*&EsP8)R=(({E6eL^u5gMM+H4Z;-vQ
zO~1t$7?k6het~vU#y9=SU|>*AX!;evz@VJi^vi;QK{=`ESG^(wgK~1yFHnNAYTgQR
zeoE8NA_fNK)TW=Y3=GO?O+Vck7?jhSei||`C}%YN1f__~rk|h`k=67A6x`WOKS0}2
zbDDmDwxi}Y{Qw1bUegbd_4!TTLDm;EeFs@z*z_H=9kr+lbSH*#anpBDj#Dma`Yy=8
zpj_JY4YYN%tm#`K1A}sT(>G9XS2TSCrNqjnZy;}1HGSh?U{J1Z`U-MkP1DzC1_tHY
zrmvvQo^?%M^%xkG>zlrcGcYJOG=bJ>D>pWQ)@ds@HGK(TU{G#u`eM((pxn~*MT3Ds
zxwYwwAVWQaa$D2qY6b@7_NLFEMBCBy8MMi?v+1)r1A}r`6X+yn<?g1>AbWe7J{2-B
zDEBsf0@>Tw^vQ*RLAk%_6DYVRG=a_vQJ&cJ5tIWaHGNEBU{Idi^wF1rL3v8kM^JE2
zZThIlz@R*>=_4ltgYxvI51_ps$}^fifF`G7nm&LM>(QnUS_}-TuloPK|HU}}@B813
zocq}(=rVzhf%wD7q_Cgu!834uZ19JXDPcd`hu`24g9YFwzyUC65CCdHJov-N)Ucn;
z!5Q4DNcam{!nr^f)EEiSWnwW{&obd3W5RkCh5ev2zXHImjSHaJh4m~GBtVS{ga3>Q
z>scm9gUl*W22WfhC^HG{XA4jUo9F=Iuo!@3_OmH~#P+iYfOvb^K%Dg~ACy4GYycZ}
z0ZdNt1sT@h3$`r47c#LC%>>%-X#jF&Kg);zjNL3BnAWp=U}T!Go~1w#WW)rJdX^8I
zAc{=^q;Ne;09eKWOd5bm1u!Wf$OJmV46O8n0N9}q1VDx~FoBv&=RobR158ZoSq?BW
zJ=o9E;15>0frSZl5ShVVkaPemQ$I@p8;D>B5gbhGSpqnj7WA`B;9}}$nZOMqct8X%
zh~NVe{7mavCI~PE^s_VwGWD}G2r=zvX%J>&`mmoZ;R)j}{&^36F>>waY7k-aW~*0k
znyJIUpsLn1Q;dN@Rkdj*BLjn~O4E#N1_o8-rWs)j45~^^Gn^S1R27?MfK)0p%@AQ=
zP?c|*UdzCsD%UhUm4QK3wrRRA1B0qe({wWi236^%=}HU?s!~nUxfvK#C7Y&|Ffgb}
zG);?RU{Dorn&!^Hpeoih&47VHRkXfonj`~*sz}o`76t}Y;ijp13=FD5O;f`e7*qwD
zraCY%s0uVq)nH&y<!_n_>Ny;4no`NYpvv1cC7FRim8WTn9|ME@^QI~03=FDVO;h9<
z7*si%rm!<GsB$z-&SzjyWpA1s!N8!()-)Mp7;6(~5L%U`X)<WsBebc0637=!O_S0X
z7*rXXCiycks4_Hx4&hSy-!w^{fkEY8(<BZC29>`}6AKv_RQ@zgjAmd^`Q0?poq<8+
zR}*OUmCDbii4qJ9DnFV)tFKhPH-T1PseEe!t-ezE+BCt6fkEX<(*#up29?iE6ZjYy
zR6aHJmoqS^d~E8k2W{#8&;+V2Ro*v&R$r;SYXa4lDsP+mSs55q-Zb^)F)*mSZt4qX
zU{HD0)Cckfb5kFvFZZIU4-_OXn|eW=nr}_Lpm~h%O}*X>4Dvskdd(OZ<bO8x$}=#?
z|7z+5P0Ign>H&48{xtPOFfhpfZR&9V^_%`R^?*h^x|(`K7#I|Lnz}*#`o5;_R0al>
zTTP%bXqB5y-DV67D%YC2<ro-L_cV30F)*m^ZR!FA@V=(5NCpPg{Y_n<RC1uH3zSL@
zHg$ng$)Tps8U_Z{!%dx_RC1)LGk}3X^=MP4B?E)%v8GNXhI$6o<4v8QWOAaZqnLp~
z^<+~=Gy{X`siqDW1_ssBO&uW9&NOw1GBBu~ZR%iPU{F2R)Skt_pnATkJ%oWl^+Hp-
zJp+U4#in*m1_sqjP3^)A462u#+Ugh>RIfC(fmB{?Y6GR?YfWt+mDiivK<Vj5Q=1?I
zL%r(Frq*f(2Gv_lttku)s<)e3{TLWj?=-bqF)*m!ZE96!U{Jl+)XKxapnAWlrHp|=
z^+8h$C?P*=YH?#=P<_<YqR+sf`nah@f`LKxNmC0G1B2?*re;t&e%90sN_x+mnjIM!
zR9`eTYcnvYzHDk1VPH_RYHF%wU{KqCu2Y0bjWKz9<8KQF2DKfHzm*sm)OI%h=3`(`
z+tv81l7T^OcjK>Q1_re~jlcXD7}WMQ{<36XP}|q|OBtlU@fS$tfySRz3=C=q8-J!T
zFsL1B{OQlYpmw<Nr#S<I+L6Ye3JeTtNB4(!i!e=PtUuQHqmY3??RevlNCpPA6OBKd
z7#P$}HvZ6MU{E{N_(Pn5LG5(o4+aJXwKI+1GZ`4v&NhAzWMEJ`*Z3V|@%hH@Ad4?F
ze&=CeP`lXpt&D*|?NZ~nBnAex%Z=Z>85q>AG=4K-U{Jf-2&yL4t~GvRWnfUd-uN|_
zfkEv?edE_K1_rg8jbH5<7}Rbxe$`}PP`lj-+RvnRr}0Z21B2S##xEHR3~KipLG`5C
z{l+gKZ#-!HBE`U<_OS7DJp+T<qsGsmFnQeg*@J;W?MdTjJq8A~r;VRQ85q>k8$W?+
zz4wiuK(*e<#!nz6S&g5x85oo$8|y!Ts&|RTk0lHY%HoY5L5&5m#*d)GBSafNf*N`v
zjUQPV7?gz@KY-4c5NiAYY9$CZegL(}1R6hp+GMvIKd>_}DBo>-4^nc!@ja*=^RV$f
zs4>Rh_#V{O;A?ybYC!NdzKdaCQ08d_T|=PE-T1B^)VAVke8<JWpc>J%8g#A&XX9H?
zP0rEy7SwQJZ+r`K3|r${IR*x0*2cF?3=GOFjc-7QPB1sV0Udq8)c8i1fkBzE5p*<`
zGDG8QP$T_+Bk1A*rGJgDT^JaY{x-hWW?)eI)A$<HFa6#4s)B(*=~v^c7*Ma`XX7i-
z7}Sr(SE>vQO5Yn_fx5Tf8ee8JFerU(eCf}?p!B8jr7;78(&xsPk_-$=pBi6)^nGl6
z0UD<I(D(v0O!dC;g$V<L3R~j~&`8+3#^==x3`%bspM#1t&c^3%3=B$d8lUShFetrl
zd@jPkp!BNoSv9Cv@uCs5GE3=sBWPuo(z8a;sI}75M$n+O(v!w#pw{2x#;2g}#G}Ti
zprN;ijZZ=DebD$+lYv3$e&bV6C*fY>6Hs^jZsU^x1_q@&jZgF$7?f@|J^{(yYJ3cm
zyV>|Slz~C%M&n~U1_q_;jgQqqr^Q@rd@RVopmeqI5vUt<rSTD{Z*#f-Z@&oB{=faA
zOq>e)*#Z*4)%6BZrV0Hl0b-!4SDa}-OMnEpfv^G8Tv*R?0Nju;NM=%4&r$$xP6UL4
z+a?a7ptgxYDA){zP*9aG01{&P5Dl*47f3LH#z0~~5+6c9q(BU43g&?XQ$NcCNv8EI
z52Qd%jsz``T!S=-d;o621b{^jSc60iz-$FAP&-CIiwU%XLkrxD`Jf55<$)%ccLBmH
zkOsSE0obq)&p?ff1JX?WEC*yjge-`V0}=8dLIFf5GVNzMpu_}PCEB3O)X&zS0wPpF
zgc^uY2N4=f``H>anLw*V3$&Q}Sqik7*0U7oFg;k$qVOLyy3?Qw4w4CfK#O5M{A2v3
zzi)#s(=nF%ZH*V)7#P&HHeS$YU{KrAcmY)MY;L>&DtR_Fp3i1rP}|seK7@fmZA0UE
z8wLio^^NCM85q>oHJ%3*d21Wbfl8h=jpyPS7}Qobp7Ua0P+QdqT1}<4vhkce1B2R%
z#&cW@3~I|8&z3MSs4Z(e8^^$)wzToACj*1plKRH8#taN<iyP0%F)*ktYCH>4y0GyK
z$j}9ipt}In<~M@w0#KXR2)YYEZEoWkPysZj@eDHqgWBvy&=9rStj5!!3=C>B8&5kh
zFsRLFJgv>Zpf<hnv={?}+O)>gAiqp)Je9@3pf;uP6v!`=8&BCWFsMyxtUsl}z@Rp<
z@stn)gW80~lc0jHzwsof!0l^18N|S#*4uc}nt?&Br}3l;1A|(3<4Ily2DPrn6Cf9M
zHl9deU{LF5JmJH@pw`}a!jyqQt*!9{$S<vpCpZ`w)LI&kgUb2lM$qWBT2muv^jfX4
z@wg5HgIYu5@p_OG>l=?VF)*mrH6F`hU{I@VJO=ViP2(|8(Olhl4CKP9#$$pE3~H5)
zN2?ha)G8W}rZX_8l{X#@U|>)yYdi|7wMrY0Dl#yrl{6mZWMEJ$Zaf0Ax2W+*6a#}=
zVdD{31_rf)#v`Cu&Tj;r1EQAKc!UL1isv?h4gyijX*>)n_+%PEW7^8Hji51YwamuD
zAQxsdf`+u!QX3EDGBBunHy#ROU{LpI1Py7c`!<4xwAK9@4+%0bsQWh_tYTnL4`@7?
z#K52)*m%&Jfk8c}@t`>agL-h|K?Mc|^^nGc91INVp^XO$8R{9-!x|4nFfgcxHy&_c
zU{H@}1RVsT9@%(6gn>als&RiU1A}^WBj_Ly^_WJ`K_Kd}jr&a*7}Vn$_scLasK+<%
zXJueePiWi+a#~{JK9JLr8uvLeFsLUt?$c&qP)}*x2Qn<Rac><1gL+!y-gE{A_4LNQ
z0SpZF>KToDtr!^8GaL7+FfgcRHSXnSU{KF)+*8fKpq|sX2h<{c-3S`XR?ltRW5d9p
z5!ARxje$WUuyKz71A|6D<L+t(1`Yql-RTSr8h(wtK^H^%Hi8ZU(eP>9t;)cl;oZ0!
zbWNmJ<E{z@1`W@~UC9g#8Xk?i{1_NC>fIZ6SuikYxHaxlVqnm4ZQRAfz@XvMxU-yr
zLBqLmXA%R0hEwBCkW$CSo#qS-8V-#+<rx?>>>GD-FfeG?HSQ>2V9>B_+!4vZpkdRv
z!;yhO!@6;Y76XHZRpSm(1_lkw#_e?s3>p@VpmVV_%o{=HVriH)g3bZaFs*L{9R#9b
z(zu<QfkDH#aa#!kgL+@%wipHm4a3H5t_%zs294Wv85lJ58@GW>(`y7B1frqaxE17I
zoyM(!3=A6Dja#i57&NpRw<<F*sK033%FV!_ZPmD?n1MmtvT;ik1B13j;}&NI25s}k
zEm{l=+GdSggc%sLO&c{g*D)|?n>21tXJF7aZrmKez@Tl^2-+j1ZP>V3k%2+mpm8%N
z1B15y{Is3AOi}g0jT_t<7&Jl}HyAQ7XbClf&d$&hX<R1Fz@R18xQvy7K}(_$bYzm2
zRO8YJ1_mve#-)x73|exHpc9j{6dIR`GB9W<H7;djV9-)-T$07Wprz8dB#41QOSN%{
zH3Nf|TH_LB1_mwl#wFYg3|bnEi%S?7v@{zR$1^Z!Y1KC__F!Pp(r#P~vR<cgu@nP?
zmTu!>W(Ec=y~ahk3=Ephjf)}}7}TsA7dbI7sH|>W1ZwddZ(JnGz@S;*xUi0aL9?zA
zv@S`rwsBz~1A}Hw<3ei&2F>cmg{lk;npKSp1sNDLD;pP7GcagYG%iSCV9+dY1dTdt
zmNnKdFlS)UENxt%z`&qc(g+%M)+}xW4LfTVHO`M?V9+dVobScJpjps3-<W|xGrw`Z
zGy{WXUgLZg1_sUC#(DV+44OHOpkZgt?8bSH3=EoCjq|h_7&J2*=Ls_~Xl69d1=*Y4
zI5(AnK{Ks!ZU6&=W@_VHkPA~9=L&<InA|v*pMgO$sc}vP1A}Jb{(#-OpeAi-;|3`P
z292=B4a^J-8sUxWa~T*kA{y6&7C1#Vu6JNy(1>bWufxEg5#6|6jDbNTrg1$31A|6v
zBWT~5MqJ~%5C#T~_{Md%3=A3xji4jMG!h%v2{JHfBsGGzpJ^mFuFYg%&`4=q8^pk%
zk=nQxl<LwN*QziuXr$LSt_9_tj7HElG>y#0HL(l~8d;5N+!z=%vK!avGcai6G_C=;
zFt>3HXbDzc<LWF1295m2)gaRf8drl%D{Ne?%)p>g)VLaCSaIVjP)00iToup2p#HUS
zl{*82=99)%`V0)3&l*>WGcahrXk1y(z@Yi6v3_Mb1B2$9#+9HDd)K%U6k;D5L1&0*
zerjCF$H1WZrEvu)z`iwtR_|&4Xk6jRz@Yi75p;x@=ATB;5n`JE8dtC}FlaF}E-zwW
z&|+#_9>c((#nQOkoq<7%t#P>#1A`Vv<8n}9=W1LIO6)w1%L*76wD=mAaYr&RXbChf
zb75d$oNgFk8$RFR0z2c*=>Z$K%J+ZSugk=9VBZ8iCN_ipYz+=fzxekZ&|_i)HL@JQ
z4U`9ZOn>xwSQ!`?53sf{FfeG^@8@aIW2$DgwYy}+z@TY+Nr{0$)8-Nn1B0gZ#Zm?a
zO{<Hs3=Eo<7u^^bG%YUbGB9YGUld_r&@{VH!@!_vdI6MhP4*vY)niI#txs8Q!@!`O
zx?F{UK|5_ZF9U;i`mzcJ2JH;cszdEe(B&uES<4I=7__rNSD$F-EMs9{(9Q*2e4?EP
zI{QpJf2lnKgLVPv2psLgrTh#G+C@u1CKNA8U|`TLS>nmSpk2Degn>c3Y>6BLgLXM+
zx=6cXF{lu#tX~|%z@S~V*o}cfyBd^twQCm3FfeG>E(R4Yb&HA^7_{pbMKdsHH!N~t
zV9;({q|3md-2}?C+RY2=85p!%7G^UrXtyp5VPMd1TWHI`pxwSuje$YCV<8^{gLdbF
zG6n|iF3=)E?d}C03=G;mpmS}sdqKzAX!k9sXJ=s0?w?=4z@R;0KBzpLI3H9TPMWX7
zz@R;Oz8C|8_LO-bYo>w@veBLfI>$zP`aC-Z2JIR1K-SEh2lDZ(x#bKD+Oy|^d^~3^
z$eOvJi6HHHb3vY&KbMVxL3_cRd<F*Xg>xbp7_=A7abRH3UOYzwWb~3bf(#7WOF?JU
zXfK<c#K54ve6}wGgZ7HqW(*A4D?xXcXs?<La_H(=AcwA*1u|moEJp?g?RB$24qZPB
z<j@VX7#J9|H_ilw$EKN~3=G<vXM(KRGE<v@L3=A`2upk0OlAfKZIKx{3=G<$GeQ{Z
z88jPbfC5b%G})sq0h;U4mYfa>G^y#J>yPhE2c4&Pf4V6HgUW;H3JeS?52tf6FsMA5
zR?5Jj@^~7kJM&~3NX^q}AT`fG(>yBAr|~i{sJxh3#=xNRaw@0^stKCnQPY?TYUikf
zCV14;K=V8GYO0|59W|9Hpyr?Q6k7%cHKi$P3=C?DQ}`Je)D$L{Gcc&hgC=&=<R*i<
zs<M*}85q=LCQCCgs7X&|V_;B|nv~DLpe8vfoPj}2ViKrvCO%1>fk90SG@qj;I<bO*
zK}}?0A_Ie(FlaJIO=u#hIVd<0)CjH@n8?k*pvFG|)F|TvoeQtVI|0;c<C!4Cz@WxG
z0n|q2>IaP*aQ6E!FsO3(gWARH{n88!+FpJ23=FD#eMt-qYAk*33=C?_eV`UDQy-`a
z&e&VTz@Wwe+U=+Mzt@I=LG@oRXyET}F9!pI>YpCa=+N)_9?)3cuO3?l2GyTEiVO^@
zKYCah7*xM^gNA0lb$c@~sDAC%WnfVK0y@)O^>Y_!80b?MXyoK$7f9EKF3=#%`z}zA
z`CTW-(6^m|3=FDoI!zfEw6}LkFfeG_bW}4iXxnzgGcah|frgH>?K?CX7_=Qa>Ora3
zvAvXmLEEVvlog%ZLFwNGG+d<Z+RnqkpzYQMN_6gRpbX~GX3oH%?b#;9z@T!s71TuV
zZUrS+pH_DU25sL~Q0DY&6=7h|_HO}M8PEcf4FsM2qaD<u!N8y$+yW|NLYhIjKeRa#
zBpn7C0MZU`21!RW3otNfM>bV5Fla|Lfn=kbd>9zCW12vDA+||@fk8X236vM&8}k?#
zv=bV`7#Oq@8?6}_w38Y^k&;}^z@Ty)l$EVPLyP6o`vmmCg=>I56X@=U27M;bQPNBW
zYgz0-{lo{hAo2j1TmU9N7%(NQXPJ-&5^t~pkq^Ks6Tl)4c_0ykJW#(<ArIV@6vzX2
zSiwRcazW$v6AYPBSnK2Ofim{pyOj(KnsIj%85p$hfldX{j0Iizr+xpf6a#~1%w14<
z`rr<zg%W)SlxZJ=E*jU20-edFEp!J|KSkaKl`dkplNcB@BW{Bl?w@ai8WG{Qr5PC1
zKi+0$V9*S^mCeAQzVB8D1A}JhEzqK6qxxGK3=Enfw?H8(eG}w};F};v$lL_gZ$URf
zg}UrbkRt*?yP>q@K%1d718#sqRQ`rN1B0eN=%f#Ag&QD8_+1A%Lh*Vc1B0gTb#Dd+
zZKdlb3=En+pnLqZm9MihFlc&T%Vl8DR=F0+z@X`MtsYb_s9w`#V9@lu1_}was~|^s
zTm_Yq>Q_A&7&P6l8Za<uYk*E))^xiH3JFcn*~^-)S3r)?0&RBEbh)C=z@V*tMSy`p
z)A=%}X3@C}a)cA;AP;Tb%OFQMg0AS(*1HU9OgUTvE#NM1oU{MoG()D<O!c=LyFf+a
zt;Q};@ZN0f0u`J$8oNNH;`PQZQ3eL>YmJ?tlK5(4X9fd<_LW9Z4${8d*a=Ejml``k
zmE*<6PEdt%p%HW;k@oq<j#LH)?Q@MCpqBC3#tx9mGmRap3=G<*8#_QjeyS044TAQ`
z`o{J&1_tdDjqSk<4BE#V+d;+cvBq{#?QyiR9i;R~V;d;JA8u>|rT9aQZJ^*i*w_Y2
z^9LH+K#6{TBWN|S_P)keP?fm1u@#iU_cXRTF)(QFZfphlWmjV>sPVqD5j3%@y`vE{
zv8(>Fu^u$DtNyAHG_$Mzy0Jx-fkFLEBWPw<{cU4&IRk_GyGGEwuKN2%(7dkthepu6
zu4Y3cXkJ(SQ)4qX1A}H$V^bLegJw%3C{JoBHi9yxmV9HAIRk^1Y-1CsVJ_X+#K*v(
zCE3_m$-tl`-q@JNz@R1C*jOLTz@R1E*l5qdpe5J{n%~vpZ)_A}V9?@iYy`FTxf>gD
z7#OrT8yi6V0`^AG^+Z~%jSZldJac1%ECYiUV`Bpc1B2#&&?K+s-~XWK{|&l1Li6W;
zP;>74f6(&$um3@<oX`J2&AyNSvKbgO-~S6|V5rx8`_GwyLG$%LQ0wsJKN$uF&FBBP
z7#K94{ssBz@n2An_{(2^1_q6re?e`{TYuFV7&LDG6=q=2xbvr;fkET$pBx4TjeCDU
zow@seKpmY2e+(HIG#>r|wOb$k0X3{2{|2df@*C8we)`*qfkERLXmVGh{yAuJSL4NR
zMg|6rm%l(w+gHCpz0uddKn?0Qzcd*bG~WIaVPMdB_p_FPLE}AWm|EilXp~yx<4;g8
z^wUp81_q7KKS6!LFF!yn->*Ls7#K9Z{qSI5(D?oX<dh#jK)V=z{s7tX>pRGn-`_z_
z`BVQL)WZM!9n|&w_Z`$%{QnKq*<k?PqN~aHEtr8plj)ls1A`{>H!TJRO_pz<{s!w;
zP-BtpYZ?QCCi_=^1_n)zuNDjpnw(!j%}uVapdx|$3#i%5^958c@q+Go(B%7K%D|w>
z|3!|0K~vxhD9Qvs*B3G{XbOFfW?;}1{tRlTi+na>V9*r(EX%;4DF&LX)fE3!%)p>2
z@hO3UK~wS*sGB7936!m+KY_YaGM_jZ7&K)+g3OWo7{$P#DgV)lfk9INben^wBIq&)
zO(oDxxthu!K+aVG-Q=LD3L25tRQsUp!@!`a{sGiH)_4zU9&5e_b;q>cgPfxM-hhEY
zQwOxWSX1{sD+7b3-aAlFO#fX31B0f)J5WE&5Og=LrqMf4;xgWUVXh&QIumCCXf>?%
zoqL-5F4!}HP6PT-!lcm8a>0<PpXGuP(|VQ*#-Jg}4JDvKz5)|)HL<`NGR6o#$9ID@
zr~<iQ&BRo&pRK_J+|*wHQMUm!7TM3T!Gx)wWrHb*Far_hAi@GfSTgNr*<i)Q^kF@l
zgAJ3ydbWZ^pb^yrCE)qx3%N`J+gUDrXL4B2cA<n3be-c5&}y{@C5!^gSrmQ<tYygs
zu?&6)tY_Ka0AdDw5LnM*5C~#UI4H25MFGrgxB@z*I1uE6219VIW&`$Wfgz{{oL~YX
z6Ts{QFgpOuUSJOrF96q@7r^8PFew18TMfWu0GKQQlM}$?1u*#mOe)whDXeEXkP9+r
zfek2_9PF5w7VKrSXZkmPJ<A4&1^OWA2VnLAd$1yXup1qiuCqF%G(AjbU{FbJdKk>W
zppw+|(1C$LC9&xt=y2wQribDT3@Y(W51APlRN|T*fX;D_ZF&Hjxr}K7EuB`0o-aPl
zfyul+y6L_I1A}Z-(|yp1B9Tq^iWwMWBbx4kjsOX7x(7M}B&_M4J_CbnXwyAO1_s%X
zrhA|r>cLHSL3_%Bn(jt2Fvtcr-F0SQkPT?M3)%(l-*gwW3*4{iE@*GJZ_}M@1_oK5
zraPcr;NDGlKq|eO?tpfId)7DI0d4N~Xu4g;z#!}1bUU4aLDsG5HfV3RYtwDews)7N
z+n~cjoSSZg_I5ip-6~^XkacXj7019J>(F$|oq<8tz6rD-TGp=VmJ9=ftZmaRb_NDn
zo2HwE3=Fc?O*cXN)UBFsg8X9HbQ9zkizZN`K-Rpe{w5m(gZ#6m8-)xE(tnz6fKG+`
z-E;$VD%`K88=zCtem30z9X|G>=>`J>gY@^N>sbs8(%+h{gANP%+H@UsOxc&F>zWJ<
z(x02IgANP%)N~DWSjfkwYoNnIJ~Uke9aHwc=^E&ivv*C`lo=SL-!@(2XJC+i({#1I
zih)7;b<<Ul(pODaK_^_iYy#c)EB&JBss;mt^z){xf(#7O&zeB@{YpP=x{}1eApNB2
ziWdWe^y8*0paaz&HC+K6nD?;h3h1c02Thmr85pGRH(dsu)^V@tGUzyyyG@t185pGR
zG+hR{@OINBkPB}$T}rEGV35AqbP43d8%>u$PQ2c9NtJ;?`dZT^eg*~wou-SREpq>x
zE`p|(&oo^GP4AgCT?Ebh=r&!HV_;CxYq|(JEnL6p0%(5Rpb2!(uZm&Q1<?GsQPTxO
z1_l-5rVG*x3@Ro~pnHB*Oq<Sw4k<TlIv)-?*4(`5Jm{2ii>C8B3=ArkP3J*V=~hkW
z85tN<teehdGBBvvG@T1#U{JAbItOa++BKb1Vqj3QZ#oA$YTcm;G`O$g*aRBfS8-|r
z4eqNrH=PB!(52}t$c3&=XF)UgZcS&37#LLCo6f{AFsOJmopEPis8{i9I%CAZpyJhZ
zMwWp=#k=VYsO#s`bQ*MiyKmF!I0gn4zoyfk3=As%O`wZ@RRWq$gFF-1bQ&~0AJlXT
z<n7?5Qy@b_nofbd9ohuC=T{}H=@dw1c+)A6%7~_uplle~bTX2GK_#l`qzh>J_V`Q(
zCSAs4jiy7Oj+187AzlUsRjsCj<qQm}+D)L5Y*n46gP<vC-6qiDY*oD`(Bf=W{U*@j
zY*mA%14RrBs)kJmq8J!djhYTPF)*kaHyr>?G@CRX08N^kHth#Zg`4dUpY6cJ$;hG6
z^b$18q&YuhjssImy?GO8WLwpuX+LP?hGo-!&<YBxrv0EEoORPaP+!cZX<rNjgQ{)Q
zKG2lBUDH0$l)QZtXk=T}p=mE@0fl4JUeIv0Q`25h$IQ72G_bAe(zF-kDc7dGp!t2b
zrad6T+?)1*=J!3C_J9oYtZ&)_>iT&#?Ey`ndpGR?O`rQT?FKDB@ofSPX{-7*?Y3rM
zQ1x%x4eAC4G=c7VPz`L_1)7TwYTA{+z@Qr31iI@%HKb{mAp?VIXcOqJ2i35qU7+Ic
zMic0?FE!JqogoYiY9>uP?HL#pdz*HuGcc&!X{z4|+B4SKv;(w`w4-SUXdP*L(+<$e
z&$gx=1`G^}txY>XD?eMBc7Rs8HaBetts`w}+74Pr+Ss%mw2ri)X**~gX?+vujt9lM
zCeR%ZinUGKk{B2iYnnjIvK6bFwwW+6C{{IXlVM;`tZdo_T1HyYw6#8qfkCmn33RBn
z%F3qq84L`HWldW_%SlU{KttM!B~4p-85k6co3@lPFenx^ZHZ-IP%LcP;>y6FSkSaZ
zkAXokziA6--E3adX3)CX+@{SSGjp0Y2Qe@xW;bmH8J5+wS&4x`F|%niXxVH=)23nu
z2F3KIO`zFe#k3~SB@c?JO`tm-6jPcuf!6CLH*I2IU{FkI+6Zz}V$(*@O6G*7ji5!i
z@lBvz){1dW8$qVUHf;boEv5-{2ACRK6KIrNF}i63Xhm^U(*}@Xkxd&whD9{32N@RL
zv_6o5K{2dpy$wS>gJNjYdQj+vG_B`jU{DNhS_g`Xpr&=8s0eIY2a1Y-rgfmG@NZfN
zTFLC!v<?({zD;ZM7#I|Nn%06A9eX#e1x2h^(^_=~21U=NwV-(QXj)Ujz@X^f1Ul_o
z(XDBX4+DduYttIg0&15g(C%s}Mdzk9p!L{JO{<F-7!)0wR)coDI5e$x-S@$si7j9~
zn}8jt>EQqxt6a}g-~g(W7l7LV2@XsG{VWR{nD(<QaAXQ(t5;~BRL{U5F5eDXf-5f9
z4qAdMF55l{bi0U5J7~m4T)KS{KLdlfR6A(QMqILeBIqb+iS~)0dqBk7CxY$)5o@0a
zx~fF9eIg6!imUbspaZmp+b2XYFo+AaPXL`SE!aK*bStMo`vj0-{O$dqwR?Q^?fu~l
z4C1`){h*_>dD{CG85qR5+xyuW7{s~SLCc85Iota}85qPl+WTx77{uAz`#?(A+Ci82
ziL<u%f-Xg2Y3~JHt;O8lYrw!D&eYy3%D^Db*xpmcz#z`h-V@KjAojn#$BltO>|cA2
zE(3$u-}W9+1_r@z?e(CALt=m0yOS6g#D2GTgVg+L@788u5c}B<I;ctPM|&6OwwUkj
zU7)*XzO{FmF))aIZSMkI6Z54V)Ik;d+}@eOz##Uiz0-?<LF{9Dry&D_*oXE`Q3eLF
z_w60!3=CrL+CfW%#NM`d*fB7Oy=m`IWMB|`-QH2p#=s!<svWdANbF@h=uSSd7wzq!
z%VVCmx63dvh&^j>XJKFvd)nRxx{2mVdmHFJoyYBMASI95L5Dz#J#25SWnd6{(B7KB
zz#w+Ny%lty&As+k4F(3WyX~!@+i~u+w-hljh}~{)iC|z5yVc%e&%hvdv%N(fbSuw|
zcF^dL*!A{ikVmhzH-|7Vh+S=Owq#%syV4HoZ;D-R2i=1!!O{-eeJUZ?-W0~bAR*M=
zWXHfDA>7`i&cGlc(%vM%z#t*o-dM%JAR*S?n8LsyA>Q8T&%hud(cWmzz#t*n4m#mk
zLaM!yje$Wzy1gNrp`JlPro91l4S{TXgDwMugj{<AF9U;weB1wA1_lX*w*P(%3=)cM
z|BV?KB$V3z%P=rVD7S(3nM$a%ftCzQsJ4N+lM-re|3Eh*sJH#oU|^8YX!|F~z#yU7
z_7`+Bf>s;oFlPzvw!feo8FbqIS~4(5=(hb;W?-n7&};h(vQWPbv}9PqpzTir1A~NN
z+aHjdjN1Nyu0~*O11%YrU~2;{8J1vg`whAYf};)8r<CAq`wg;}s||GZpagf@Z;-t_
zZNEVF^0xf~1p;5&FVJE0{B6HL*IEd){Q}*yVBGc#bkD;6b1NM|YpFK0eez^rkl5Jv
z$%uhLVpH2EkViMSeF6p4mbQ<e3l_GveFWX3v90YR=(dRMZ6Ea+7$kPIeFWWSv9s+X
z=;n)EZJ^~p61&?zgfK8j>}mS|il4o0A3#B}Z-4k|N6^I6{<imZ3=9$n+TN!#Fi0G1
zdmqTaAaSVeJ?Iq0!)@<D*F_v@d(X$fAaS(qT?GS!#Id$_pz9)zx4i?!<%za;px`^%
z_D+d`LE==~J01oGiPLRwOBom>&a}M+-4=1S?JelGh;wakL6?G@Z+i<mUH?McTaafi
z*0;R@`Q}m^=-xbu%WZE!!FQ$Y4akjG+unfE(6u(u$xag2+d%i`N!)0A4GO-SZLdLb
zajWe$$h6ySuR*5WX?s<`z#wtA?Nu}bgT%eIS8fap5(#au3>X;17Pq~UW?&Fo)b@&%
zfkA9x+sk|g2C)Tg^)ErUKFx1?>B_($Hm~g^Na@_Rm$D2DVsqMFg6@Z!-Sz^M5oWc$
z0I8hW_QIKgL2O3b3s9jjz3qhv1B2MKw&$QMH?<A4=~Zk>+w&j>2C>O)&q4P?O=^3t
z&cGlxu?=+6v)F{TXEh8AV*PE;K=)zwwLPo%XJ8QPZF>efK|ip4i5~-lSWnwC6$S>e
z?zU%w3=CpjZBMHh7{of;o`P<a>S%lF%fKMk-u4t!?zFW%m1kfOYi)bV$-p4i()Og3
zfkCXf?Fp!aYifJq!N4Ha*!Bce{4}&Zkz`;Ht8aV4#K0g{*Y+4xeAKo*4h7}-nzqNF
z0-(C>G00C<ZI3}ERb|^FkX%LEqf7<{vGTS@pz^M)4Rq|YSZUiMO$G+BlD0>nJHCqB
z9#%6jh!wRx1i7%V?IGx{t%A0Ppu4v6+a7{knAi3Y<igyx2cRpya@s)0K8t0yJ#c5J
zXAsM3djN7`X4?Z$1ZA{607X!G8|d6;v9z}Pu?!4iscrY&85qP;+U|qmC%NrD$TLZ8
z_d&OTCANXKz=|cb-2;VseA_+HZD4V2_f#1e#A4e(qq|};ZJ^;@vFJ9?_^wz~8)$%6
zEV2zW!Yd^f(RLSPT6o)CP|$?6fkt`7Lfh_y?h9~YVkzinNpNQBXGw5j+Ru{U%Ea_w
zKbr&ST$%MO22P-gQ~^v1IDytlLk^nx;K&3ze8v$xkZ{2fr04*c+~5eRZ5`a0`dJ*@
zL4*g0@MPN0;^4)^6tJIdgAG_u!XhStr7YC~{VWH(K&zO%LF=o1KtmM{;PqAszF;#$
zKpkp>81S%#LJU~v0$<Ro>`;*Ohs_|;U^kP&dKQC?ObTmRW`G0|HZnQvXSv|Z1X}vO
z;XimVVgY!S(}e%v&20@JvHdIs5MBa=7XaZk`~xqQFZc&msSp6RbAlh!hy5%EKq}U=
zP4EW|l?Wt)Wds61Haf6^$Oj1^(jkB;VLwX(ME`~WrhoG5Srq<&7IHlZVCrXi5C|fI
zK#RwMnI81BB!q%OJ`6;JgNO(a5eXuqnAWo-M1vNH2gHC@w#9;oIHvV10r5;9*0Wpy
z+dN?l$j$_?%?rRH4GAFo9TLD{<{$>15l93nDo6lDjY1;RdKQHwrh@e>4Srx@Fqz;7
z3h4kph%P_yFpvR+rvTvzfOu=!K<d~&fL7M+XPJ=11UiQKK?pb~E`TE|z!_{rLNe1o
z`~55di<p=M`q?%lGxf7=NMYK~wjq`2U;lm<gHo`nfHbhq4d5Xbg;J1n1i<72ut-5A
z$WaeUz)RCElz<LGI#2>icpFN<4qO0|+0W(xF{L04JX`~A^ldN%`E^4YXp|})L}Y-7
zOc0R;BC<h54k$qLKtw)>C;$<KAfgCF6oW##1Qh%ZrJyui21>)_Oo3+g#T`%F85o3$
zI-ck;FbEZPJP~1F5Gv>Z9V;i4-|;w-fk7y*<FO3`gHUeAV|fM!p`4D#%nS@d*&UBE
z7#M`IIv)8lFbHLKJThir5X$IyB+0-al->c_V=t7}0U9q7O6_>)&%hv*((w?aB)J1L
zP$ZPp@t}r*K`61l1GKwdD52wlBLjm_e8&Sd1_q(Hjt5)}3_`IT_wyMTgkn1GhcYk-
zMR(i>xgx6LzA^)YP-Mq_ZUzRSh>m+8CE*?S0vQ;D!aDAmF)#>)cHEO;U=RxFxW~l6
zAQapI+D9)G)Nwb6fk7y+<E|A0gHS-nU63jM9rbs47#M{7I_{J)FbMf}+(}?y5c25&
z?V}g+?f~th7xL=3BgMcV<k@kDk%2+TqvLiK1A~xz$88@51|heO+qw)4LarURc^Mdl
zTsm&$GB5}^ciaL6iBrcd0|o{m$BtX#3=BdJ9k)P^vG2GEQexL}Gn|1z$hPAq=#(`f
zn-0)9@j})eH>DXEgseJ1BSb=$9XARX7=$c3KqEv#<{dZO7#M`iI&OdrHSM?oQfbn0
zgPnmv$hhNr5d(veQ3q(}ypUlBXy?3;K?i8(ypVp!buk78A-#@k^$ZL`x*gX*k*3pe
z4HR739oK9@qFNo-)EO9rG&?}^NkSSOSF0Hq_-=JvO<`aVQtP<t$G{+@+Huu_fk8;A
z<Ejz^gD^+ORnW=NoE=xn85o4QI<CYsFbH#ZT=8IF5a#K)V!*&4%-eAVbaFIb#}x(!
z24Vh=%b5%e!U7$aLl_u@1v@U=F)#=VbzD|wsAmus?zk+#z#uHrajAlVL0GioQX&I`
zuvo_>Zw3Zo@s3Nz3=F~&9hYPo7=$G|E`cs%mg=}z#K0gd-ElFRfk9ZN<09z%YuS#A
zp!2WgIzX#3gylOf)G{y#D|B4QU|<kd?6?3r{#vQyf;9t!uyV%*6$S=jm5vL%3=H+c
zsvYM+=U=OJoCo<rz2m$m1B0+e$9WS524T&P^KuLf!de~Y*%=swwL8ugGB611bexM~
zU=Y^rIOoj3AgtGMPM3i}Sij?(Bm;x6LB}~J1_oinj<eYe48leoXG0kngpE7Sg8XaJ
zaaNsyLD;n8EXccU9cQW;7=-tqt1JgKAg^{DwPj!szSeORbTs$%j-#LezR_`{l7T_^
zX2+3a1_t3<9Y_2a7=&+k9047weW&AyG6RF~-Hs!?3=G2eIu3&Z?|#Q&kje)ghe0Yg
zcO152U=ZHYaTsLp*8Snt<)8-SwvIy}Q@3{<0;%26ama^(L3n4!AyWnh;awevKpx)R
zaR}t$JsqHX&V=`N9E@dP5Z>2u5EQ}tI}RE#FbE&$I4HxwAbhanAm~i*LmdYS7#M^P
zcYp?kgpYK9cI*ou?EvlA7e3Z;K$?L;_;|+w76u046ZIXS6X1nUcI*e8B7Ul4zXJn<
z@ac~InhXrWXF5P9zzd)4*atc<{9MOAP^vlKu@4k`7drNVV(((dK2Ypk>evVJ_vMbg
zpvb$@u{V){fycgMFUT(sJNB9}FbIC_*sH+6Ao!&NbOOBK=Z-xk3=D#wI_g0uzzcrt
z*yGK>Ao!tUj|l^V;QNj}G7JoY?>hFdFfa(d?bw~mz##ahV|N4tgW&6q-A)V)g0DJ2
zC%_B7?AR^Fz##adV>bf>gW&UyU0Dnag3mg3g)lG(KJD0L$G{-?q+^!`1B2k>j$I-Q
z41$k3KqtTpKJ3_;$-p4^pkpWKBzD339XqWV7=)H|d{<#$5WLs16GYwZ*vZSlAb6)^
zM=1k?;O&kbaSRNCw>oxsGB60<?AT$%z#w>|V}}$2gW&a!9n1_2g4a5>gRH;Wu|0@^
zLGVh)c54O(!OI=n)fgBAFLi9^XJ8P#*s-mGfkE&>$F@WU2Ep?k+dS$S7zEFCY%^eB
z5Ioxfy8ct-Xva221_r@19a}-Bo$lBg%D^CassnWUr{Kwst(puBf+sq*3NtVW9`D#v
z!@wYTtYb?m1B2kvjxGKS41z~GwpcPS2p;a(qRhY`c&K9w$lik;o2wWY1P^p<2C3ZN
zu{n@|L2zHkW^0Ce2En}@n^hSY1ow1o7Gz)$+}*LMmVrTVSH~uh^*cK@1v4-R?&#QL
z!@wZ8y<-!|Gut{gfmCko*jUZLAh@MtV;Td4;O35vAa8H#*l5eZAh@w(BS__jj*TGe
z*LQ#pi5Fbgu>s`mwH+J07#IZCbZh`!V<ot{V}mpUgW#%;4eSgIf-5`L7cejguGs&#
zzMRRKt=_TogBb$@k3;7N1qKH0J)Ix87#R3NJKq;GFz|<TzK>yG;1BM6@5aEuAJq9?
zpMiltu=Bkn0|S3R=X+KL27dp}cX<p9{C=J9!WkI&eLF#WF!+5s-)S%~@OyW@6JTKA
z_v(CG$-uzx*$FyEm*1oFtq%hOzkBCfGX@5JxBAYv@(c|8uAOf=7#R3nI^PsBFz`Ef
zzKLRB;CJeL<I2Fm@7M`CVu;_N6LiE7zkTN$Mg|6cyH3y%L;SX#uLBtv_-#60TQM;3
zTX()zVqoC6>U_=3z`$?W`Kp|Of#0I@RU!iezj-I<h#`Kn&R3=k4E&~@ujCjQ_)R+N
zU$HYV@Edo&1leoU3F>X}8+N{QVPN1l=mhn)`1Lzqg8Zx3`I3o&K|rYUMGgalfJEnu
zPzDA8$<7z{3=9HNouJ;9fOO{zVFm^PnNH9)4FTEC=P3*f0&<<teHj=8<U606GcX7!
zbUs&NU=UF3e9ptbAfVLwtiF_iK|s0lSsVj{fJ)~xcLoLl)y`)I3=9HlozEm07zETi
zpMmVv=medkE1=m4I$}sbtMjQV1A~Be=TneMozAB+3=9Igoln^r7zFe>pA<1L2<Ue{
z0hwvg`NW%nLBOyRbegV!QRfqo^~Rk~xEL4&OgbNfP6ZP%?R*@?z#w4O`PhkpLBPBd
z)XfsG=zJ{3z#w4R3F>AESam*1XJ8Pp?tB!$z#w4L`N)ESLBO{2kpcsQfL-S!4h9AR
z`_6}j3=9GeoeyIe7z7+UAG$Fx2sm{<1i8?;^C8GDE}aiSesS%501895&Ih3k^$Y^;
zoew~P=+XH=n}I>Vv-5!{1A~B9=lwbc1_AHR`xy)j0zRGh0~r_ud^_)3GB61Eb%NSN
z0{)%%c^DW30y^)NF)#=OcHT>5U=RrEya)1caOXV}1_ptU&U<nU3<9B@_dp>N)_J#p
zfk7a=6EveH5YY*mQL7h->;z4z2}E^*meL4Bciv@XU=WDuypzwsAQ0Pm2NW`Kop(UN
z9p8CJpMgOjp%c_X5=iX412QzJ^L8-<gFtfUZIHK9I&Xtirgq-eV_*<S>%1+&z#x#`
zd7F`eK|r_@w7f<@r1Mrd1A~BQ=Pd^Y1_2JS&Rd!c3<Bc&4|bL_88aq7?Yzvuz##Cf
z^AaeGo_Ah~U|<k<(Rm4E?8{D2^FZKL=OuXt27%X|m$(@i1m1LlCXfW)c7o2l7kJls
z5foDIJ1>I5^g}18l_2o3^CBoNKXqQHXJ8Qcyg$6V98@!Y=>)YC1ip4&uw`Hn_||zr
zgMmTdd*=lq1_ps2o#(3=7zBQHo(Co3U!CXu85jh9cY@B`75LM6UX6i4;BV)70R{$v
zf1T$l85jiqcb-dTU=U>JJO?Ty89UE`3Q49;&_t3Tb0=sbNsy)UY%v3aAZzE@Xa)vB
zw))PqE({EU?44)z85jgPI?sZNdd|+XtPBi-T%Dkczy-NG&qOjX2=a8Eab{o;<n278
z%fKMW*Lg;QfkBYJ^9)F(K<DXv1_nXF&eI^3LY=2UwU=-wXqSk<)XvkQ3=DiXI!`k)
zFz{XPJeAGBz;~_l6e#QRb=HHfixuGQJO%PLPv<E?1_lA{PSAC+0$iP->tY2sJ5Tz7
z;;8ea6$66+d*?}21_lAP&XXXOteq!n7#IXtI!}NSD0AltkfBVSCqTi@*m(kECPOFa
z)>!`koyS4t-@ne|pmOMM=W#Cv2L3;t$Loz582Ep89+zcc;BV_{1Qj{IIzgAm^8f5S
zR>Z)-|D*F*Gy?<w_s(OWV(?oh=<-<pubs!l85sD#bRJ`1VBr7Uc{GcGf&WwI(GUg(
z{*RqU?HL&OKXe||WMJTb-+5Gsfr0;B=aCu)2L895M^YIW_}_GbT2=h7JCB&xGcfSK
z>I5Bt#Lv=s1XN<OcOEWdVBqKIJe<J5z|Yxv801o}&ch}Q4E)@khd~83Pv>D!LCxEF
z2;@S(&O`AG4E+3^hddb=_ysx-88I;M3w9ooW?<kK>O92Ez`!ruc`%!SfnTKaAjpNH
zod-cK6ze>w#Zb?{FWz}jl!1X?qVoXAF_N7JG8q{7r8*A;GcfQ=cOI~1VBnYOJfP0N
zz%Sbgx;&O&t`juX#xLIqItGbfp>uyI0|UQeC+J!oex=U+S_};Q%ANZ~7#R3fIzf#p
ze$~!>ISdT^YMr31BmC-}`y3b;_%%8~TSvtCH9Pl#tk>$?3$k9jb1x_?b^8DImov@(
z+h4)NzMf@41*jW4p#t2E-B1BqD6t?7)Qx>m!Sv66J&QvnsN-t@?(7Csf=4Y1nwUWM
z9yL@l?PqDIV)~Q6Z-N(i&BF)q3cwBE^$87NG676FfJp^g(AWr=`2f6N;eZWjEy9N?
zrck!}V_jQ~85nqvc5M}5VBkH{wWWlCf%kCNmPiH$-a}nm92ppR4|Z+QVPN1r(6vRJ
zfq{2_*A_+w2Ht&Ln{yZ#c=vW~2C3ZBwb_M%fp>S;W_<<*-d$arr5G4^cXn-NWnkdl
z(Y2|7fq{2>*QO{22HtI5n_L+fc(-<KGGbuh-BRDRNrr)ecXQV!kkU<E8}k_$csF)|
zZYAg4(6!N?fq{2@*G5eS2HtgD8-*Acc-MA;ZYAek)3qUkfq{2*7wA@U-c?;2Y#11L
zS9WbsV_@K2(Y1k}fq{2<*ZN8Z2Hs^|>ysH6c$apq_hVq-UDCDQl7WGDao2h!1_s_m
zUG?j^7#MgLcC9O7VBlTQwGQOO`CaRr85nryb*<B8VBnqGwGI?AbGp{nGcfSZ?ph17
zcUIThKn4chnO&g01iUl4)+#eF@J{anZ6)BH)&)8jn0IQ|ns^2V-YH#cJQ)~xCwGC4
z1?HX91-jUVcVgEXb_NFC30<q}K|#~swK{@<fw!+~wF3hKZ*SLXkbir+R)g&A?pjsL
zz`)zpwJME)fw!}3RR9A6Z%5ZEkT2T1R)Kuc*0qY8fq}QRYh@V&18+;$%0vbR-sUdQ
zEw#K&T`Nr(7<e1IR?0Fk@HTX<WMg39t?vTecEelOwIUMar`oO+peU*70$o$fTivxn
zl7WG@s%r%(Mk>3OgJPtj3v^8_Z)w+ZCk6(-=&t433=DiRUCTun82Dnlmen#a@Wpj4
z%V1#Oi|<+%#K6Fp(6!8lfq^fvYnd7Y17A|tGJXaIzT~c@l?)7gDP2pG7#R3cyO#Pe
z)HCp<buG1EVBkydTB^vvz?adrl#79ZFSBb&2?GOPR@ahP1_r+Dt|e{^4176VOAHto
z_;S0J$S^SQ<#jD#XJFvV?^;~Qz`$3~wK$rAfv>P@u`2@uUs2a$eFg@;;;zM#3=DiF
zU5l9*82C!N7UeK7@RfCecG~cjcP(;eV5sM-=mIU;=d0{mB+kIVSJkzMfq{Xqx(jqo
zEniI+=m=oG+Ah$_eZIP`g_;ZueDz%mg%}w48oCx#F);8ob}dL|VBl-&THwvVz}MWh
zz?gx7ucd2&Gy?-)Yu5r61_r*iuK9Tk41Dcf^CK7-_&U1gJ2Eiv-RzpL#lXO~|J=_i
zP`5R#YkCy}1Alne^kfDG{)n#Wehdu!kzJts_4uQ@rYkcr@JDw|=Vf5vkLj8QYJA3a
zO#>DBab43ujo$dKX%-9&{0Uvt6d4%!6T7ByGBEHbbxj4eJ(Ihpg4(<(`@?@%fhy<J
zF3>?n{ApcNr5G6a)4Qg!Ffj0EbWH)Zwllk?L@+S$XLU_+VqoCU?wX>*z`&o=HARep
zfj_rv3KIhZe_q#Qkjnh7$)I+5K^N#~2L8e>(9sP1MO~9Y6+>|s=zL)QlCDW93=I6G
zU7*u}`OCT{ft*-g-!%!;l&<KS1gaP+yC#DA165rUL2j(>nh3JDrfZ@$0|S3;*F;bu
zTGurJREXAhO~_zi;BV-f5Wv8|-`E9O2hZQsH9>)afxo#6bdC{!OILpZ0|P%>SAQe}
z1CLZ!Kd4Od?CJ-d=5ng5A9Q%m>8|>I(4OowU45Y4-)Fn}LKqm7&v*6NF)%1!?CMiz
zU{Jo?)d$*UezmK&mVrU}dRH&#z?qv}y}=9&%6GbYK`K9V^=dFMsI2Ph6=GmeU*FYJ
z$H1VzuB#`DfkAz37iiVI`kJmD&}PEbT|HV14C<@8KnFCauk7ju9e1a`q6@Twp7(nf
zXtSvL@~-Ys1_t$IUELrZOS?cT>eZKYb&D}Ds4wp7s%KzOU)0r=!N8!tu&XPOfkAyi
zSC<t7gZlg~(CT{id0kyR3=HaXyFl0DsL$yFU5}$ay9+c4t3Io%)0lxleP&muGy{YB
zjIK@=kZIGqI`SD9)TecIfc8*M?dky8JEf}w<kHDq9UwnV>S_n=$eh^Kp3K0YKB24K
zkAXqGzpEXzoj<#)9ke5}x2v6#fkC~e3$z4Zy{oG&oPj~TyQ>YfA+xiqO@o0!y`u|s
zP=k7VS8ELegL+$6Ybt2(W@}fgF9U;mOINEI1A}^VSF1b&gL+d}D?0;&dSh2h0Rw}2
zLsv@-1A}^f7ie+5dR<qGE(3#lZC48@NNT#8LBU<!)ttt_pkCG0402j!S2M`4iZ0MR
zt$KME=)5QOvaTl3&cxELrZ@%$^^z{og}mbG#a&GX3=HZ;T}@I94C;klP0S1o>IM7%
z{;y(+V5?uzeTb8Rfopj;Xvl_ZS@*$c1_rLB-Jq-Kxt4SvG+<!hTHJk5ih+S^QTIV+
z1_rK$-3M|R7`PU69|&V$;F{kJx|yD9UiSeF1_rLV-3J627`Wzi@2_EC;F{gNKZAjR
zYgYIE5C#UWncbkq1=o!3{n`u+T+_Svi!m^8O{?$T&&a^QHMJYGF_mjd_r53w2Cm87
z`#cyJxF&V)Gh|@kn%KQhl7WG1Liau<1_rMFZcyWbtFL=+5Ca2OZ}(nn1_rL4?!9UZ
z3|!sapna)aUEO=i85p=ayZ0n8FmQEr?*SRs-n|Fpm$vRbAj4X_L92JTTDt3Z=P)pE
zHFxg@d8Vm*w*vzMS7Y~XO$G+8hVI=$3=CZL-Mc`Zsq5aA%D})?+r7)5fq|>0dl$&w
z>h4{t3=CXV-Mjc07`Q6CcUCYka8-2gOk`l-D(~Lu$-ux>*1gl1fq|>Ed#4No16N7+
zPBsPxuHx<;MGOpFMcq5<V;C5?3cGi>GB9uzbnnn-VBpH{-XX!jz?Ij%0~9j3-P^Mn
z7`Sq}L92MUvb(q2Gca&vb#Dg+VrKVtP#|V>Z)ad&;7ae_22z>Uy$$4-)b4GL3=CW;
z-P?2+7`T$Vw}H$|>fXl6z`&K*y)}=4fh(bVYj`~a16O?aR*=%T?yVq0W4l2^HthV}
zTWT2?xT3qaWHK;tMRjih1$TJ&7Hb9uZrkoHDhv$VcHLWe7#O(iyEm6GFmO9`Z;oYP
z;CAfZ?8d;r?bN;5fPsPAxqGuT0|U29H>hdE?b;2x!H?Umds74h1GjtkCeZzQ+#cPV
zv>6z<J-auFGB9v^b#JU^VBq%d-k8O}!0pq$F^qwM+qZk8BLf4sU-w2G1_o~b?u`-*
z4BP?T8<`mxxC6U4<S{UC2X$|VVqoA7?%v?az`z~S4cht29oh}LIe|N@djmHE19y1$
z`f>&a?uhR7Nem3!k=>vcQayK6H>iok9o@Yi<foYK^#TkG+_By3Y8e=~<GMkcF1h2o
z*M&1Ma3^$w8cN)W-Rtxj7`T(V*U2z2a3^=K<6>aoPU&7-#=yXx+6}t;k2|e<tv>?;
zcX~Idy~Lf-4O-~Ko!Pxsn1O*it9uQ|gS)%eWHT^u??1;`4XO}dcZ2rfa=+;Y?Zf4M
z+YQ=>%l)o<sTczT_lxeOj0_CiFT0n3biC?b62id1;@iE%j)8&uefJV|1_mCd?j-^Y
z3_Q-=i>nwIcwD*{r!X+^xOOl0XJFuQ>t1Zlz`*0aKb*T7R3UnFFBW28;PLEURLj7?
z<JG+=i-Cd1yL(X>0|Spw_ab`+1|Hw;MH&nYJbvAaK&JY4FRWx>;0fqnn8d)q6WG1b
zi-CbBsC%I?0|QTR_d<CF2A+`ag`5lwJfYnSiWnGp!nzm4Ffj0hcQ0^ZVBm@9UZBgs
zz!TZMK%9YrC#t@C0RsaAPjvTuki9Y8^Fj8;cF%WUVBm@C2DK7+;=AXIFfi~Wbc3#~
z=Sl3Im&U-rlhi#gfPsN0xqF@^0|QS=_dI0=2A<Sz(2hTzwC=f;3=ACey5}Y{FmP#i
z&-G(q;L_@zYr(+4>(M<|iGhLVSNB{V1_oaD?)o|93=F((-E%<AWY_LFJ`4=JF5PoL
z%|_?$IiO~vQ}-M;1_oZo?%8<^47?8Av%?t}c<sAqJ25cu+I7zcbq;L1LFYg6+H}tb
zbq=h%XJs=m@LF}x3T0s6wd@96GRSMuJxhy$f!DlymM8-QuUYpjCI$vx)9#t|xeN@v
zCfzf`85p>3c3%eRFz%iSGTW#dbiNg@VfRc>$HSl-v^$Vjzk3GA6?)yE`|5dhyJvvf
z>N?$^>*{&6yJvvfu3FtQm>C#&HM^&SRBCijk7i)tRqvke#=yX<);-;jfq_@G8+7F$
zuS)lHc2E;oxf^unAg@w4=$tEF#qMd|3=F&q-P6n%7<lEorztQn@XB>h1GTbcyQh{i
zF!0KBPX)E^rMstkF);8-bx#Eamt^-;c?JeviSDVOkQMKq0t#5M?kPzO47{S<Q+yd1
zctyHFr(N+1cTZ7dVBi(%p2EXW&%i6#4LTx{SD<?`sOiq%JsH$h;p?7k#lXPJ+dWy8
zfq|E&dorj~!`(dz)T!a>o&<_5&TdfCikG7sbm$c?dpD?M#mm+`iI;(am$e&oQY0@+
z_rw$i243dwi6AqXx+j8?0Au$=P=|$~dm<m`j`#oF6RH^)c>Z-y0Hv$H-Jrv-c>Z)x
zu-Uhvnu$eVKg$L$CMJRHYzvD2@h@j-s214HQcw*NNT~kDznvuj%ys~?4Zv)LYLG&K
zYJv4E3#vig*bRHZo!x5i{BA=vcz#!*1|(Jh5j#-B^zZz77J(X&>JMN&55VLBFey+C
z+Vr*oEV}@#Z$b^ktQxRc1z@oRh*$tb%mJ+004%ei7OZ+gEz>XgeF1f#j;~}7=;8xT
ziJo>{1_n;?o_28t22Qb_b_NCpPSKvWOa=x{ksi=0Gfv^2HcJKuPNAMQB?bmg!JalQ
z1_n-np4MUp22TE-);I<RPQD({7DG<no>l_}22P%yRw)JsPVSyoW(EdMuAY``1_n;f
zo|X^>22PHi7Fz}ePWJkq7Ig*&PPU#FAqECc)}H2S1_n-+p5|l*22SRlW^V=tPNp8v
z#Rr^>J)nyZI2n3COV2p|_cRqUFmU|qX^LWC;P~6q<ix<h@u#Orn}LDjcTbZj0|Upe
zp2k`R29BRSjp+;w96x#*gBch&zV|fRGB9v_>jB++!11-GzEO~Yf#XY0Llpx9$LF4g
zWCjL~PdyF33=A9}dm1bl7&t!kG$=DLaJ=sUEkxsZ*ZseYfq~;~H|PjUjyK)^JsB7{
zUU&aDVqoBS)eTyY#__WIKL-N?$BXWNMGOoa&%6J{FfedD>;C7)z`*ge8??WP<4HH@
z2uqH~-T&&D7#KJnb^py}VBmPz{WpSvf#X5<Uyx_+cmD->=3e(-5e5d1yWM|4p1ITg
zCyjxD<97F-00st*Tit(b7#KKicK=ahVBomX{YQX-f#Z7j?`j4Hj%(e&Qy3UHu6F<S
zV_@L8(*4_#fq~<4H|T6Gj!WIYc^DWtE_VN_tY={0xX=wcoQvapH)vfN$GPrb<_ruR
zXS;tXFfgz-bpPUHVBk32{j->Xf#XE?Pf#?k>;CD*z`(h_`=>Dj1LuZr&=HoL8@oYA
zSaNRa{*lALz`42mM<@dW=a%jtplIIO{X>m`fpc5;4?zY7&h6dbs~8wKcXWSGW~gW2
z+}Zuzhk=1}SNC@l1_sXE-QQ&y7&!NIf9GUi;N08&4V1k0b$<idyTALJCj$fLfo{+d
zmYfH>L1%Mu9_j`iVaa*88+3#v=aKHOu?!5HN4vj*TzIVes~H0W=ke~Z3JeUKC%V6a
z%skosrHFxn^HlejXa<IQ&ePprTo@QQ&vbtQWq`BYU&I&~IL~!|VPat5Jm38}mw|!v
zLigtg1_sWH-JhKp7&tF=f7W4O;Jn=Z8Km+`_h(R6x!V0Hi-CdjTK6YV>b~Cn$$^1^
z^F}x5z%I_4-Je7m7&vcrf2?I-;Jn@aF^z$NOQ-u|00RTp{&SIaOlpkDE4yEbGca(i
z>V64od9Ch#32Gs)>3$i^z`(V(`=t#71J}ClmnsYlT<g1E@-i@RZRmbc%D}+2vHJz6
zrMRj4g$n}%*XHgQpjO?M?iZl;-`4IIp!VOk?&nzy3|!myhey|e>iHerpmk|nJG(*a
z(zteYKL<6<cXxv>9OT;5{VaunfopH~Gmzu<bw2}HyubUIIs*gOf$nFZcJIONr=SMl
zq3)+3Cm!y83Tglz>3(X<z`%918+0WD*Rk%Wq6`dN$Ge|^JaeKObR`4V$?hki3=CYS
z>bswS8q=q{pMYAGXS$z&{C&3j3COAEx*vmDmFK%3gABdU{n(0uf$L)TV`T;gu1npI
zxfvL^E_Z{jWZ=5e{V1M+f$M7bBT!@dTK6L(1_rL{-H)Uh7`P(4A2Bm9aL9K*%wb^Q
z-qHOK)JWUj4ccDBy{)_cp(X<Z_tx%*LJSPtTe=@qF)(m%?tTDj`fcid;LX6my|Md&
z83P0NhVBRQ3=G`syB}~cFmSKyzF)||z`eHnKB$elrW<r61NZ7~(3K3_tGe$CGB9wj
z?7jywY(@9IR0am_<=yxE7#O&hb%WNBa4+q?2Qq9)_q}?MX^Xo-GbNl}J+ndW=0)A0
z2@~#x-FHE4)CJw3`4aB=-FHEaym{SsK+VFr-FMO%7`W$j-vKosXLsK*XJFu-)eX9m
zfqQ269Zm)Y?it;ni4yMV-M2yQ?P=Y&-5D6Tr*_{qWMJT)(tR7$-k#ij8`SaTp45E{
z)Ha^jeGAk!p3r^Eg@J*)zx$RR0|R$o_bpH>y0;s&z=XS}`z9z5ySs0K+S^^-H$m;~
z&hDGK3=G^I-8VrlZ128N$H2hd)_o(5fq}cV`v%C{E!{UjE^O|;0rGZJ_YIJ*8@sO;
zGt@J1H*{Z*VPN2{@4gQ5Z(a9wkiE6t*FmP$bc0rwa94L<1GV$3x~~N@FmP9PUjv0x
zMfWvOTfDsc8ZQF_cUkw<QU(U@((bEq3=G^Q-B&#s7`ThOuNpBha2Iu71vSD8yRWh_
zFmM-iU&&`+;Lh*962ZVA#hurE#fgD|JGc7^sDF{ueFfCN$nL(vxbHwMxSlVl16Pv*
zGr*Oq!3@ySKG0gN{cH~wg4b3ZSO`|I0K{9*(y$OzTPG|8)#D5Hf(Nn{KpeISd%*?>
z^nv6Tw1LQgdZq*GSuWHv1*~NOSIGu-On>C}Dbz8s3G8P}r~{8|3p6n8XAx**(q`rG
z@40Twz`)|S-(0kjNsh6;tLJ<<0|SRb4`_7>hi}h$4+aJfzn=4;`p3Tqw7P^Npa-<N
zgd?!$Tmb_EM^F!FbqPms&pA+~64G-{i-Cb7wC5bCQVHuh3o8G^d(LJuFmOcloDE`N
z;E3!wYt6vG5!G`RRP9CgoaJU<;E3rtQ^LT&5nJB_+Ihqg*K@{|fq^5w2Xv|!M?w$i
zR56ak9?+>`97#Q(Q^h!vdqAg(aisK|2GzHzJ*PocR9eqzAqEDH^qx~S3=A9@J*PmG
zS!T~EP-T|Ya|%@5X7`*@WMJUP={W_mH@63L2?j@A&&fCj29Erm`jcJ^3>*bLCrua_
zI0}1C$}uo-6!n}0)wjhxCqONNlAaTw7C~vx2^R(ij<O!m<%}HVJtxE&7&t0=PJjxA
z%AVsn3=AAqJ;y^C7&xkXj@vOXaMbi12f47e=Qtk&14muYF;Fnq_Z*97VBl!z0o~2W
z(b#hgbgLXkQ_nGZ1_qAio@1b@v8CrIC}>)Hj)I)n)^ilpB53b9YR168(b01hq_VRI
zbU7nOSI-epi=ev)bgCFfPtOrhjP&*#(P3cV=<7Km!N9=L-*beKfq`Q}&*3Zv29Ak6
zhe0tisRy*~hGTNiVI@#>P3bud3Yw`shd?cnX+4J$7#KLF_kd=IIA-*KW{5au_8gL8
zVBnb5a|qPDnB4=KA>x?Ra}eZT#h!x>3=AAfJqJN4LAmE3C?%-$fF_7IRC_=ZL>y{8
z2SOMaIMjO%I5IGBX!INasnqN_Ak0wDz@gOx8pPqy?%5A&U+DDg_hDe*(Cq>3z2ea8
z*{{UFz@gu>ALK%Vo_(N@G3?m~3K^rGeeMhl9L7ES3>X+VOnN|rHyoxt`&bwlILvzX
z<})yGnD^`jHGnL7_JZuS?AZ%y09p0y1;w3p&t3)whI$U09?%UL9JW1s0vQ-M?0P^q
zWN_H`>;WYjhn_v47;)^`4GL$cp5369mvhf<P|M4uXSY5B1BYwRZcsS8_3Q?PvwP1j
zP|Ek{*#!z`&z@aY3=AAzJ-a|D-@9iQKLZ1YPY-DDhGT9IXz+$(|2fG<P<1WUvx$R&
zfm6C?V<7_rr%cbrNCpN@*&fhn1gBijMlA*gPWc|tL=C4x&jwJFR<UP88Uq8TQqP6}
z1_n;$o()zE44f)G8&nw>I8}Q<6E&P_J)nsiPW7JkDGUsp8vDbg8$s2zX3u&X1_n;8
z9?%vePVFAh79&obo^=%r44k?>>yj84IQ4qgff~yCJ?l&v7&r}j)+sVDa2ock<7Qys
zH0oJf!oa|3+_M(cf->n@>&C#qY1*?^pMinXtY@tx0|Tdd&stDp$D(HqsO4tavj)`I
zvFcd^YV26o_pAZ6c5HgqfLc4YJ*(>(7&z^ER%b9UaN75P4u9fw=vi&ez`*I)vl`?Z
zr=HcIMxJxeDo`WOrDqkWDeu~|%9nwG)2(L}$c64bt3Yi$kDgU*3=ABndRFE$FtGFX
ztc+w};L_|_32Mn`^sLlnVBk{ksb2|d%Bc0M05v64dsd_~FmS2#tN=AnlzUcKGB9u{
z^{h~0VBk{hSpjMnDfED@Zsd~hSq>WHlj~UyY9Gk<fDV7+lIZ~*{=_BSvzflI1q
z8ECXivS%5{UWp#i*-u>JJ<IeM7`ViGmVt%?MSGUjgOrN&fR0jP-`(?woq>T%xMwLy
zhfvQ_(CD0C&r;9;qCn45kPiNyrJ&JBz8=t+3>R+?XiSESr)LSMb;RAX1T-qh)w6`3
zfq{#&XK^(H0~bfnV$k>@d(UE!m)LqhV=`Q<J&QpqS$Y-=fV|Dzv#5%Jfs3hU5lAUx
z&mvIkh@oc@C|&&TSp*98e?5!%7#KMJ_AD%8VBq}Ivk(;9zk3$CGca)e>RAZtj{WRe
z2<ndg=vm0dz`*&vXF)y#1LwD%1)$je+Oq%@+h2MXfRgU#o&})Z*r%TPptDXnKlaQA
zrN|FG^ZgkZIN$fo2c_M2J@b_r7&zbd%;#ZX;C$0F50uJY_sol7VBmb!GtZTQf%9e0
zJW!MRMbA7?(s|x950uKD^~?pOvZp<us~b6=^vng>`?zPWCIbWKqaM&$4Clk1IRy+1
zoDX{DfHrz@-tU<MvhZHd98e?vZVzY>hV#z;zw(Wsaq8c_Q%o5cSbz0`&dp~1*$cY7
zk@ZLK<U$4p*6+Qb%Ntq0^-gwVU|{{)J6Vf?f%Qu-XmW=2b1!IehV@e~=-6!5kG-H{
zvspj%f+lBJ-}iz>5Ln;!g63ve-}X){VPIf=(>pPifr0gPFKDA1>#N?0#taOsFY9|J
z$}%vpzUZCE#=yY(ymvxA0|V=`-U$&546ILkCxGmI(mMfU@8jMHA`A?yk9t9;6|p|-
z?ayXlV13ZrAIiYMdcU{do`He&UT?n!0|V>b-hM#_2G%>hebo#MthamnQWzLmZ}s;1
zF)*;+?CrB+U|_w`+o#IFz<Ry69&~&*>$ToqkkYHYy=e>#tXFz_0~r`tFZcFZGcd4T
z>g`oyU|_x2+bhh#z<Qy#r<Q?%^?Yv+NaeZSo&W|0*0a4mmJAH6XL@^-7#LVj_x5lz
zFtDEL?Ji|tU_IH}oxs4rdZM@6lYxQtcyG560|V=^-fn3I2G*m!-Sx~246H|byK)#9
zSP%Dhg)lI%9_j@hdBl3Kw+rN%1HD~B3=FLMdqJmYv+nEd1lhZ{x6_}2fpt%Brv(E8
z>+ar8kiENlL5FCw?(FRV*}J2+BawlDb$f4z4+8`1w%!hq%B{T}$_xywTY5YA7#LVL
z_qJEoGcd4j>TL&w(8gZSemT|+z3m`xukUSFXJBAm*V``2z`(k;x1EuJfpt}HTP_0w
z+l1b>NCpPBiM?$u3=C|OdfN;b7}zHFw#hOuuubU&jcc$??QJb%U|^fp+nUJ0z&5=X
zG*iPiqZf3fHrvcz&|W&WS-q_y4D}3bvwK1JI<n2_Z2_4*w->ahj%{9V3&`yGy)A|e
z3~UQ}TR>(n>}}y>U|?I++YB;$ac^@90|VQV-sS)X2DYWW%{B}SY|DC^H5nM#miIP`
zGBB{M=xt_VU|?I>+f=~7z_zLvbYBPC>R!<N4cnUDCIbeBdbYK_p!plNb-hh&3=C}R
zdmBMYH}p0}F)*-g>;<iQVcXQ(sL#N_wz;=ahJk@?OK&490|VRE-iAB|2DWXzpaWgl
zw)ZwTGcd62=mqV%W82x=AjZJJwyWoVJp%*V?w<eY3=C|0dj9(}FtF|I`ES9%z|Pn6
zUx|T%eg8R4aD~|2^SzjXfxV~adn^M3dvDKocLoObzMk(!3=Hi3J>O**7}zKDd}n1~
zV4v9Y4OHAu>iHJIz`#Da=bIw~1N)SoZ(0lt>{ENbi7+s*PwV+w&%nSwz2|Ed0|Wbv
zp06Pc4D2)ahiii?#92LGH5eG!XZL&+VqjpO)AOa8fq{K)&zDpN2KIS9UxFAI*ys0r
zv0-3fU(oYKm4ShMVb2#n1_t&;J)g@M7}yv0e2!yaU|-S$I_89ZY0qbn6PNXX4mx39
z-UB-6gndQNry>Rh_LV)KVi*|MSM_{yV_;xk-Sf$Sfq{KZea|N;1_t)EJ)c0nS=R$P
z@q~SS&qt7<8+tx^Ffg!h?D+^XbW_hqSq297%{?F485r2N^nk9XVBgyFA)bMOeOu25
zPX-3|?L8li85r1i^n8$GU|`?b^MQkbf!(_2J!qHznx6Nu3=Hafdft05FsSeDc@H|b
zbyrXQd(fog&Yt&N3=HZ!dft^XFsN_ud6&SzpuVl=9q8Pttv&B77#P&I^t=NdD7v}l
z9UlXO`lcSxB2o3dJ#Rr1nfrU*f~Fo1^t=VBJk;}6iGe}=X3tw*1_t#TJ#Q)*7}T%#
zfR5`{zt;06fPq2%YR?<cRO^+VH}xtE4C<GA-taLnu<7(JEoWd*ztr=(f`LK(V$W-k
z*%x|VgJvSn_q?`bU{F8T^IDC8LH%scYXJrZ^)o%Msu&p5Pxrh^WnfT0)$_`qfkFLb
z&nuA16Fsj$Mj!8a1#<7Po|hn39PN1tn%z9o^Aa@Sd${MNHE81YR?kb&0ZF%eUV_e>
zz0>moWa!<V7oekQ@AbS0Vqj3e-}AzjfkFL2&kJ=12K9$MFF>=ok9wYiv>)tw4w^-N
z((@eTwWmGLLDoO+d9KL7p#Hq)IVS^y22;<oA_fKx=ALJugD_coo`DX+WbJvT&rr{x
z!PfIkf`LJUz2_O|1Wt|~&`5{|XU|j6X|7y7Pi+_&G`M@7sxdHV@brMr`PSg=c>+4U
zmapdt=s+O;o+qFafdqO$JM%OId!9%$FlY$%JYi#C&=Br<oX^0ZA=2|WoPj|@wC6GC
zSRk>U#~KU_8sa^V1sNE`H6(gKr+#Zl_B;X|a4XdV+A*Ucz5lO%BWMTrn%<km3=9lw
zdqIbWFs$pn>B_*su)Y_xBZOf?FX+$^hK;>9nHd-uHuc`fVPIg`+<POGfq`L5?+sf9
z28OM@H&huI7`F9-&J$zU-g~{0fq`L1@AYH`28Nxz*L@fm7<TnuH)UX8*xh?wj)8$;
zPw#aO1_p+`z1IpE7#Q}|_g;%;U|`tad(EAJf#E>!HA4mlhJ(G=q!<_&4)tDRVPIf5
z+<P^bfq~&j@6|8{28N@(R~;A_7>@N`)nQ;@INp0zjDdmSMDJAw1_p+cy;m|B7#L3V
zUI}7gU^v}-#fE`_;Y{xpkPFZDUg2k8U^v%%xtf82;e7AqR0aly3%&K1{TLV+F7{rw
z038b0ds&HrfkD0ZGB+rudM}lN&gSd|?FeDe>b>L*I*PIP638<;y`UwZ47$CS*clj@
z*m^G(FfcH&^j?f&U|>Aj3)&IFc)a(b0Rsc$$=-`n3=E8?doQvuFfg9&y^zPiz<9p*
zLIeW?<Hg<!^^Ob-jF)>aXfrS{UhTag%D}*Qy%%&KIOEM;(4irWw|mcrGcYjT?LF_n
zz`%IF_q-MZ1LMQq^TG@ajE{TI)i5wHKJ7i1#=yY%yccw42;<A%b2bbNjIVposWLDy
zzU@87$H2h&zV~by0|Vp7-m~!x42++9&w4R1Fn;YlYf{g^!1%rQtULn)<Ii5uf#8h4
zdqI77#=pI1;ushh|M#BpWME)o>^)<`z`(@Z3%awC`El<VP?gWv3pz7|m8lnWW(X^D
z?`d}i23D5d)A|eytgOAKB^el4*?LbiF)*;Q_nrdP_#C~bKn)$v-cwEt46Izer*s(V
z8Cbb{Pl+=yu=4bt0@b;^y(d8}9lqX^VGInc{Jkd~7#LUudQWOIFt7^to|Ir<U=`{;
z2{Kf;_XJ3#NH6F*OIFd|6SfQttYW<<K=rtI?+H-zMWXk34FdzKWbg4*1_oBC-s7M)
zk#z5Ia|Q-hncm|H3=H+Gvb~@+o~&}c$3V?C`QBr33=FIay~jKl7+4j1kAd1RO1;Nq
z7#LWUdyj!yZ7RJ-ix?PKReO(u8hC2GN8K10Sk-%v>M<~|YV;lzV_;y_>^%Z%X=wEx
z$zot&)$Tn4YUt?n9<gI!VAbtCqRGI(s@Ho2+|W60*$6rg<xelDXUh7w7j)h=>%U&m
zdDpD}dv{kcFt9Q7?oMN1U}Nmv4XXK>dO?SSurc@UR%c*fW9i*3$iTqH+Pe#+lC2kX
z-ZdM0?=Ei!1~!h~UB(OyY@EHjK&=U`{o&T&3X!{aC#WXp>D>vc^LcxBf@*TU-ksVE
z3~c<pJ4F~6*aUia)G#ox3HI(tWnf?v>fHgdSh#nGB?AMSNbe3s1_n0K-W^;F3~XY(
z+lv_(*u;CcM>8<6N%U?9HDe@uw}ToGQoY+H7#P^3dqL|8*kpRQWil|Z$=3I71DPh*
zyUl`ufla=5n*sv^n?mn44h9A`#onzT)0BF*#xO9jDfe!5Wnf@a>D{Wwz`&;3yH$*V
zflaM<3#gHy-n%7(fq_k<7qp;&O|y3ks5PY3y9LzDUDLaTmw|zur+0HH0|PsEFK9sl
zJ6A7gK><5wZ~bOn1_pMH-pyhR4D9T^n;97x*x7nFWiv3av-WNZWnf@u>D^?{z`)Mj
zyGfIQft{&$lQ07VJ7e$0S_TGohTe@Jd;j-t3}Ikk``5eCj)8&gZ|_D>T>R<X2#Sl}
zy`Z(0Y`=OpfCBGl?*>pa=tnPTttH#{-VOC?3=C}FdO>}7mbty4YLe}1@A?V`2DUG~
z>k}9l*gp5J_h4XP`_#K0)E4~MyIzukf$c-@dQj8ueeXI@tMOg$x-bR?wzs|OK-RzM
zT?aDrb?-V*CHty(Ey%E!y`UuoY%hA(dNDAtJ?~v>#K6Gztaq&xDD<B8u4QImV0+RF
z>cX=<?p+hgz`*vXcZ~xB1KY#iHChY|Y!7<Z2s1FS-S1sp%fP^PuXi;l3Eu5p4f4#L
z-qoPEyWP85iGhLbR_|(F1_rj9y{ka>-slDO;MuPCf_m_5*LqihR9@{}rOd#<cBOX}
z=#D+M%e^Z>N-y=U1hr@{_O1jOdZBkED0!XlT?tZpu6HF50|VRH-W8<`3~Xn5SHv?g
zu$}G&o#M=Ps&|Dc0|VR1-W75T3~VQQK}#;#j`uDHh0L+u<)Dx`+PfU&mm|HPC6{c6
zdqGPs*$(wCt6^XeXFJ%t3=}g5dYAbzFtF|KT?Vpu-~PY$;2vU2-y#kM2Bzk|g@p_Z
zOig_YqZt^O8v8(9W2T0_g@z0aO!a-Bt}#<x-$E7!2BzA+1-T3iOf`KA!WbBss{0l=
zFfcGx^?|y^OqG2LL>U;ED*6^MGB7Ze_s!2@U|=fin;*o$z*O1?>KQYY^vzddU|=fl
zo6pU_z*JP<H?Nq1fvK<$)HP-*=$q%xz`&H>HxFcQUf(<!1_q|wzImWpC#P>N$c5Q`
zb7L47n6mmnM-($<_RR$q)ERwqWf>Tl()&QC6f>pufsQF=O6>!kQ_PgoH^-5IfhnnP
z4ye-E-Zw{_fq`*H-y8-82F9Iz^|Lb=7#Mf;%?@B-VBFm|+meBSaZlfDMFs}Oy?wK}
z7#JA$_00m+CHwnkf$EY2eX~3m7#I)s%`#+QU_8_}OOk<s@o?WPMg|7PBYiWo7#J9j
z^??p9W<1e1)1HBW@l@YTO$G+WGkr5bRoJ<{8MO=yj2HT5fULdLH={m;fr0T#-wcq_
zYke~`7#J9D^vw`tU|_t}2U_gOc&BfA5(5L{y}s$*3=E79`lg#QFfcyqn+|f}lRnTn
z#*EMUrWG?VFuv%U7R$iE_^J<d{}$t$zG?al42<vkK-X_Ee(0M9I)3|8AL#lm#xH$S
zL6z*czNw(=p%{PkO$F7mzxt+v>f=9sQ|cHP82|N6Nn>DOV(6RV$H2hE)HlV9fq{v&
z4>XRzT+|1;e~Y=eZ*l<x19M5=<Y)#4=F+~&E({FJWqp%%85o$$`zDJsFfdp2O{!;L
zV6N<&l+M7wT-7%zfPsOzx^I#t0|RqS-y~&*dIsj&KG2Cd%yoUB6LXmB`#{GWGdJ{2
z^kQIOZtR<A#K6GZ)CW2-hq<|LA~OR6b4wp+9D%vD4>XRz+|~ygM__L61C1jvcl1pV
zVqjqI?CY;$U|{a*>rZB2VD9eg_hDdQ?&<3{Wnf_L?dw-yU|{a+>*r)(kYn!e>nmhn
zV4l#|7sbH9Jh89OiGhK6QXl9PWai29b3GfGqUz`Mb!Rd#FwgDl4q{+np3~QD&A`As
zyRTb?fq{8eUpGGk1M|$jt_lVQ<{5om2@DL()BCzS85o$S^>vvrFfdQ;>yl+)V4l*~
z#m2zEu(}U)#4+>VzRqw429|)nPJ0FhmcYJF4F(35puSE)1_qYkKG12$EFpazX$%Z3
zq4j+ofeZ{RVSOFe3=AyceI05H3@j0S9RdstERlVnC73KxeeJ0X3@p)o?I4vgeeE_3
z3@ovIpc7hI;`-Y885mgN``RiP7+4beKqs`aB=)s=Gcd3u^??q@VM*?5Q)FOZN$CT1
z?^#m&K+6_b()wCs85mg7`|4ZW7#LVG`dalF7+5m<S|u15ShD(B85tN@vim^m7Fcrn
zT0ox3?Q3ylU|`AXYtdq0V9D=m5n*6pDd=miWnf?_>;tXDWGU(cb?8}&`<ks77+6aB
znpGJXSW5evLEbLwYpP;kU@7lwN@ieSsptcp(8}J~*CcGpz`#=3*CfZlz*5x*Iy#x9
zdVjb#xO%VYYm8=KV5#kE1i7)U57d`usqbq9xv`-SbT}(ZV_!oS0|QG_Uqdhh150yX
z11J<*`WjRi7+6~S8bG1g*89Jbfq|vH_kR)t14~Eme^A(T_Wn0vU|{L$1>L>L(%lQX
zdy}Q7_g^6c150l&XyF1&Uwtp=Dr}bi-hYM+3@j6RK}WN)Ozi!~&cMJjsrN5P>EzzO
zF$@eWQ+oe;GBB`A?fnZfbXxCUSq27{>Aip17#LV)^!~|bU|^Zq`zL~dfn`?jA14L|
zmf5|3v=|r|F8BTcjf~ay{$XHXV6Ex>4QgXm_x=Wrj8*m4{{}S}D|>%~2GJ^de}jf|
z%6ma~aI%*5f(~kBE$#gk&cMK0()$afvbYy?Rx4{!?=Mhutgsh!s~BrR@6RL#2G;!E
zpWX}%ta-gZO&Azhb9;ZvF)*;^^#0^zU|`Me{Q+tPX7&DvW?*2=?ET@wz`&Z(`=ef$
zfq^x>_lFn*sI>s<m9VDueh0M%Q+vN>Ffg#D^nMR!U|>z|{SIocCiQ*?4Ywuse&=Uk
zU`^=#R?fh{8sGaZo`HciuJ;?L5gOb3&47V{HKz9)s6`#!`;C=>fi<f4D`@C2viEBw
z0|RSB?^jm_2G;Q2uUa6R!g{~*GBB`)_JUR}u!i)00X3zAd%u7Nx`KMYC^9gx2KIho
zXJB9r=>43>z`*L?`x&IfulKVJ0|TpXFX+-uR-fL_Ae+2<KV>p7uzK}=0*$PB_JW2r
zSUq|{YZO@Bdp}k&FtEDyegqBrx%Pf^12yPfdOv~!!MXP%DDa(nKY)f19eY232Iw4m
zKY(0n-}?d7pttM&0CK2p?|YCdY<k}ZF)*-N_r5n{U|_ZC1)bo^YT5f96wMaB??5Ag
z=DqJgt}yF;2O3T_?R_W4z`$zK3mU6nHST>I%fO(<YSjA{6tRZAZ$X292ECx2tgQOI
zZ*p0=qZmV2L7hRSP5XHQ8kuBR>o@kjtz%$d+R*nFR5P#ddkd<=*Y&*x)sSoZ-s&(g
zFs<o(E5X3Pw7TytsJ36#_oj$}foWym8&IvgqVJ6h0|V3YzBjrI3{1=V-iU%ued~K&
z%fP_2wC{Bq=(giN(3V)HC4HbRu?)(6pe?aXi~B%ZVi{EG`(A-+`$c`A6Nngi`(A-e
zTiEwX7v$%@S7HndObhy6F)}bPu=TwJxp00TXpIL0d*4f21_q{ieJ|A+K+}OQ1sE8Z
z=JtUGHW)bjKv$MA&FOm)z`(%3)%U`Rfq`ju-wPE6&~*I^UIqrHS$)sTL8~YG>OohR
zG0p6I?!~~sz|!{|RHx18d#(W5&Cv%M*<hO9_Y5>Xz~A=_<lkw1&p_h?0)5Z)85o$R
z_JOv<G6?oP1BJ|#zNZBY3=BejPeCoF$$g+Lu?)g}pe?aXllq=YGcYiS^gU%|U|^cq
z2fD|MLA37)Xx%c?gg(#!2ZLB2Xn=#Mzwe0@0|SG2-xFpA2ByBg$Dq!?MBigj#Ps%o
z1~?cb`yPWLrl${d@(_bm-y={IcK3m{#4<?tJ@RK@VCw37WX{0AAkzoh63f)t_lT2$
zfkC$KAt<yv`X0tHFfhpVJ@imuU|?$Rdk7kIkneja&A`Ca*7uN=fq_Ax??D~|15@jM
zm+(fWW~TbheHTL*7?`&7T?B>u*1n5s3=B-$`YwXPeS6=9Y6b?T9eo#485o#$_FVuq
z5O(!lFlS(3+TC{nWXGPq3!DrLOndvzgA&iazVo2K+~0Q|)VMp)cOKNZJJ@#~WdEVQ
z^PnI)+;<LS|B=3P;S3B+N9+5}fl}nLKG1wT)A2sgd_2>MzH<x=3`{5cK&L%0o$3Rf
z_P}(y@2ouo1JjwlvziPHOlSMf3NtV;o$EUTN|ERL&ZILiFkR?76U@NCbg}P@4Fdzy
zrM@$&3=B+{`_Aw&Ffd)|J6+Dez;w0mbUXtC)3v_S9t;dj*Zb;E8#6F4-RL_FYE|Cs
zI}K_f-|9OB3eDSnr(zixnC|p}4gzJm+jq){fr05>-ziW_^?u(eP)qee-${_lhkYkO
zhCb>$2^vy(+;<XW=99jYATyu#foA2Ip7ososeImd0;KXq-w7`U2Bw#NCnQ0Q+E;xi
z<QW*4UiX~<h2@*R<Df>~bVGrFIHcQG>Y3j59gkyRV0zaF+StkTzVA3FQGe(=uE@Z^
z^s(<aHv<FHr@mul3=B-4`;H|tFfe`TJLbc{!1T56m?Z-P)3?53$_xxl-}{b%a>|ds
zqZJGcOh5aMCNVHD{pvdkQu({@C@60K^noq`WBS{7l!t+V>0ck{v<#;D|9wYN7#Nrt
z`i}TBFfcRr9kF6yU}ow&0%{sD_Z{J5U|?qHJ6y@Yz|7ir7}OYJ>jNE^!OY$Vnzm==
z=sT>&z`)GecUX{tftjoCP&ESsGk4#iR0alSp1wmMGkN<CftrgS`wl5HFff1aI|MTG
zOW#3|nP2Ps4yG|MFn{Yi2x?h=?*kp7%KW46AjtZkeFs4;vtNA&KyAU_eFs2o&_8_#
zKyA1ueFtnA7?>aRfp%apKkPdo%)r3>pzi<!0|WE@zWt!q-o3v4feZ}Hcl-8(ymY5;
zKgjyqefzl>7?^MMfeub(zS&m~n!RVf(FdBnXTILIPoIH-`C8vT2?hq{t9|=Grd{dV
zo58@qe7SEg$h1p+du<pPm@oG2Rb^mczR<T9<eBq*psg3o=lb@<GcYip?c3wdz`%T_
zZ;t^31M}&=J<<#e%%}SHure?(pX}S6$H2gRqHlLN0|WE%zTKb;3Yd@efd)sIkM`{r
zU|?WA(zgrL5<T3vE0KYL`B2|3P}}!l-!4$w_dp+LaD;h(-!3)=2IhTzprH}wy?r~w
z7#NuM^np%JW!~MlQ;UItc~{>~P>}5G+X0G^9eq1MvAn%+hc5#I^R~VnAj7uy?T`bt
z?zi;q;ACK6-rTpnh=GB5Q{Q$_LwaN1c2GllL*I6gY3uv8gG^i3x2=wWfq8A;Hc(Wo
z=>rXoFt6_01`6O+ecO~67?@Y~Z36}HiayZL2=nqj(9j6;vc9cu3=GUm`?eY~FfcFa
z+bYSxz`VF`D<gvh1M{Lj&}Iwfg?(E<0lc6ObUp_2{Qkf3jZFLh#y2ss3+!h(09tso
zpRJ(@eDm^!3eXWx3e8OYED9|kq7`(oRU1=7KZ`><=)k595YY)Dx<EuXi0A<w;?&E;
z<j~Ki(8tuzrqB-}CV+^EAYu}Tm<%GOfQYFeVj9zaHihZnMav1`6T}yIftEQfNCqv2
zQkVf=CUs#EWYN?jFmD5dw*bPM0OGA@X#ky#&f)-BR`p;P_*^dVsw#&?Ambh^0C~q@
z2FR5&LBuQ&F&jk80Xcdulg5_%rhd>(Zw$@-pqt(pTKac_D!tZz&`oa)ZT+B|-Wb~Z
zK{vfIbo7I6dSmG92i^3>(AB>K)VAyH-vMge_4I@G)iCt-ZwC!d_w{cF4Nmv>gZ9-h
zOy~!Ve=$t#-wql+pVYrCkAZ<<a{snS1_p*H_5Isi7#J9)_HWZ?U|^Wm4>}5kVS4{I
z(1`bp{;i<F@tOTwL1W{y`nQ5q&h7^dgE7qM2MvQU%<bP&$H2fauOBoF#xTDh6x9q1
z`a%0@7#8+#0ksMi^=}bmU|?9>zZo>*y`&#>6bi%A{>`8P?`8e<n?d#C@_x|0ZwxE?
zH}fzsFs$s~1Zozn>fe;Wz`&r_zX>!u)zQBRG?CTbze$3DfxWGN6KKG!wSQwK0|R?Y
zKj;h;_U8VLwhRpHP5q!VP}m#$L1&<_H}r3)WME*g?+2ZM!d}-8Is=8hwts^O0|R?a
z|Au<dTvv5J=nNG0s{Zw$*}%&F^`Hr~ivIO33=Hh${p&#kb!GkQMHv{_OZ!1PY1m8p
z*QGHquow5Q3uItmFX~@s#lXN`*uPGhfq}iCe;p441ABh|TF|gxUO#9B3wv(=TF}&D
zPCsb;i#@x4Eof>ntA8yUXvQ$Je@y`c1A9jQnn(r)_Vj+x5*GHfe$WaQ_SAmR3KsU1
z{xwVt4D8AMt3d;VN&TxqbBl@ntL+#V*c19!gJu@v`&SDvFtEq<gI2Jx$M%D^9J9yt
zgSH&ANB6G+xiG4Kl?np`du0DA(7<Fw|H^WPdIt9Je$bv{_OO1?o@4gV{*~qo4D2EO
zD-{?R*n|65axyTm2lcN2g-l@o3Q))d^n<n>v-|ghwj8tj^{<d-U|{#{2aSKR`}Bjh
z9J71(FOOniVE5`@?##fz?%BT_6owxC%RzDH-oG3acW(X5vKbia*<JgWg)=a)yYw$}
zVqjo*?q8<Ez`*X*zf6pQf!(oxDJXy(`j=)fFtFSAF9l7L+Vw95O_SR8F9mtqrhlm*
z0|UEd|B^}u2G+X%C7_O?M*kAfEQx;q63{G(LH`m^rZVgY-R{R=)V~-spJLp<7?ir|
zP5Kvu8l9&7i%l397|i+?%QG-AnD;LRB}9w<MHLJT43_<i5*Zj6toj#$R9g2hGG<_4
zu<2hU%fP^3+rJ1jc3{`P5Y*_j?_U_hz`)?pztD|=fx)pKw1S1fsed7;(dpd35Y(b`
z=?AS~VQ}qV5XHd2;8x!c+Ev8h-oF5p|2+B^$S^Q4c=j&<8R`YTJdDA+e?BOy`t;9t
zVqjqK?Vk^taq{b*FTudT;NL$V)G80?pO?kJz!2C!FPMRWA*g>IXvQhHe;%ll5z;@8
zkAZ<9v>&voh#{<hZVCefLwG-EQxQW%e?4ed5kq7@Xjc(KR6l4X3qy22Xj2hGO#hrD
z1_p-M{yCtqjO(8R@^*ax9FS)c`saX3h{XQc`3wvUN&T}yE==y94Jsj0`e*AgFfgR{
z&jz_Lt$#KX0|P^P|18j~T}J;bPyv<M58713kkvn{9^{$q{#hWUIsKsFI)>c-nIO;P
z_0I%(Ccl3s$TJ1~GeMpy?4JqpOi}*~Pzh1oKLg~#lKvSW7nb(V0J*TNe+DQF%ll`5
zTv*XR9n^5I?4KUNz`#(|KOIysR`*ZWU|?XV>7OnLN*J~M(?HXOb^V|l#~AASr+F|i
zFf{Z}Ghkp~XxxAB=UgUNwY_Y8;8n33!0TZ@^n%Lw17P+8F#7_SeF4mV0A?Qmvp;~@
z8+t*9IJAQ_EdUD(fY}qkYy~j80n9c4vkmH*6#7{d=7Flf`JgIr0ciQ{hXo-00^kb9
z089pe$pX--U6u)uT4)1kaqoVX3n1QlwhtgFHi1P<|MdG=9xMVKQ@I#KECCTqLBui;
zu^dFK01+!e#3~T68bquC5o<xjIuNm*X+6t>4NM06SqdQaw!%hmpd8r6q_Cf*0V4Kc
z7x<XS3wxRV*zXhA2wou^08yt<4+@5QkT)(=gQ{AAX7E{(3pO(Kvn|-fw4ZIkW+u?_
z86Ofr3b%mH4n5!tszeuTVd`gDuoXmX0}<On#10U#lW9H6f?c3vA`^Cl3>E+z|6w|a
y{h<zI$pg^3==E$DKpeIMptZ{DSvJ&x<QIU+31G6J4rEWkZl?V#1$&tO{09JSrWB?C
delta 59396
zcmZoz@Iw@YCrAsfWMI&K$N&e7(i3%z8CPyhcrI5j*7r_`fk8vGZwn^_gN8`&n_vb8
z4dLEpd<+a4LOqY<7#P%_^~?@sU{K%KeL0(fftR&=f;t0(`i8EPSqu#7m0gXI3=I6r
zoqL@a7}P5|zFRXe2yX0H@5sO)a-scIJOhJ@bo-Jt1_rUXwmY^A4B~s+rUx)ENY=Do
ztYKh~=GJQMG-6<onbUGOkbyx?v-w{X1B3kf=B)(`3@Thr@9P*C6g`_(>oYJY-P!y>
zUPNF!ivbgpz;d<?j19}#7BC8IW;^hYe=&<g!(tW#fyFErE^KFUU}6&3&Q`$luYNhp
z1tx*zECMA0OIb<;ma}{)7Ff>m07P5>5eJF|wzF&~1{v2-EU=yJLij)a<tznG0_`jh
znA%w$Ft@WjU}<N0z}n98fUTY70ed^k1CDl<2b}FJ54e`IJm8+NoJD|FU^$CHxIjCL
z0dG5t0be_d0e?G-0f;Zy&SD_c&SD_k&SD_a&SD_i&SD_e&SD_m&SD_Z&SD_h&SD_7
zoW(%eU^&YMHG$<U3qZsK5YeC}u$`qq4dk)}HG$=90crx<*&NhB&NBeX3xJ3OX@})3
z0U!@9kQP|ZlE4J=jWpQrOdyp9K%xyG`3oS{1Q6>1h_wKu@&j1q2Bv@fOIc(DwzC`n
zhnj#4NN0e8z;YG^8IaEuKt7RaXEBgn&SD^UU?~g8zaQj4fypD#&XS<e&XS<m&XS<i
z&XS<q&XS<AoFzeZ!*Z4bAQvjA3AD3ZP-|zopx(}ML8G1Jf@V9*1+8|L3)<~07j)WL
zF6g$iT+nN0xuCz4#a>`Li-JAVgm$(I2JLJY4BOc*7`3xqFm7kNVA9TZ!E`y>1v7{3
zYy$Ei7aGV5Y-b6O2YVJQFhO2mIm-qRaREep01*NpZ#aN_AYk6kB4E+ZB4F9hB4E|d
zB4FLlB4D$eMZmUTD~miRm>X;bma{q79oWvc!Tulrb`}A9kf?#3z;-qPJ5U(efxK)h
zu$|?BEy&gjwjgI5010dW3oHN&OaKWSuxB!8XPe-#oo#~Szx&Hs8k`m^XHh5-XlGGy
zZf8+&X=hPzZD&z%YiCh#Z)Z{PSk9v0Ibl1C0x!tm1K>osAsmz*!UeXoOb7=#q#;~j
zIa@)vz;?C-uzUbW-T{>CHh8wPZ18Gl+2GyIvcadFWrJ@!%Lc#gEF1ip0=Ba$fCI+?
z6dDO2q5(uK01*d3!~=POr7WOOQUDWn0<A0ott^49EJ3X-!L2MItt_FfEMZGo!VR{w
z7?dyyY-fEC&M2^*Eui-we=AEwD@){3mZ%BaSpuR#PG1lO3KN9_P`Ze2XGw@@XGw@{
zXGw@_XGw@}XGutCXGut0&XSPiu$*N>6ezw5K)x&h`LY0HKtln@fC7+c0!TEV0OWUv
z0)g#p1_l54+gTPQwX-ZpZf9AL($2CVwVh=_T06^v^zAGQGMECEvpGZyEN3$S5em_u
zc#8(bTQn%%qCoK$1+wBo6exBNfY}qGKxTf(XlMD5+0ODItDWUTc00?5oOYHEx$P_;
z@|LrF$TwKd@?oLCa+V8V_bg))XlMIS(9ZUua68+FqJRC%SsY40&M#&X*w1EA%>*(q
zproB8ptPMOpsbxGpuC+WprV~6pt7AMplUfwK()himIcKE>sdB<F@eZx5V@e5Nnk(A
zglZ;`DGeY~_Olc~cnJ_*0EFiN;<d9(sBUMOP}9ybp>{dTgt`OESrQxsma_yn2(+^l
z)VH$~G%RN+Xe`*y@?aOp%O4s+p{mfipp~Vmm8H3rrKOdnwUwo<m8HFvrDH2gCzHZ<
zwga92__wlL0r~GiXFJ=2uI+3Ox<URk=oQ$`($K>su#{~Ps1WJ}g<pXKNMS;6J6l3u
zJ6l43J6pnpcD96x?Q98?+Sw8&Z)Z!G@=ty{%Y+_~0}g<rwP6vcOj`sJNLU0iBmm5I
z0J9CiY=uQ2mkKNrXlH4d($3N_wVkD5T02X_^mdkp8SN|$Gncb8%nDe}q5yJ}KrfTP
zRyMG6K7g%x&;!zap+{gj%K;Ga0hE0f^nj93L61N?+l5)}Y!_y?vt5|e&URsLJKKeM
z?Q9q3x3gVXu$}F~!hiD1Ssq+gSkAIxk-&1622faDSk%sPVexX73ri*}XHi%Na{f|~
z^FQnYS!A#bq<ASPu`g?9Nm$;_lCYwkC1GVdOTwylmW0*qED39tvm~qqnYI*^{u)7g
z3wDFNp0FFl4%iJc$6+_9oCOgIy9Kth2<!%VYd0t%6|8M%DOlIeQn0?ArC>ulOTor=
zmV!;oSqe4>EN2l|Ca{!c87Oft1yyPw8!mudcVH>V)CZtUv;ZVJVJRpC5|#?IvmMyn
z&URo+JKKS+?Q93OwX+@A-p+PlM?2eroy*w{>{8gyw&Be``F55CyW3e7>{-sTVDE<I
zEDoTgm9P(#QTI7)XDQgnWU!s>!M=a`?JOJiFK5|s;K6d11qT<bXGySS5@=^}IMmMK
zaJZet;Yd4+!_nm|4#yOhvs~x|X$Qss1aLeTTmd;T;R-0xUJ=;N;&25N90p)f1(2w~
z6;QAqYiCI~-p-P6qMaq-WIId3sdkox)5}>B&IBxHF#tJB0YnHm2yA6>0QvEQy})+1
z1K>2Y0h9m&>J_%L1ndJP)eUFb**2Wr&bHy4$G3W?u77+C3@naaf6EydSRA_k#xpRm
z*mwPPXJBBl>-uZJz`$bL^;d#{fyJilFCzm3i*?tZTm}XftFAv`3=AxmU4QHt7+5U2
z{-`rBu$XuK;b&lAG3)vbGR(B=cLD<gi%HjSZw3Yy<F4PP3=AwrUBBfS7+4IueseM~
zuo%>L{VHN$VA1dT70tlFqSy7ym4Sgpx9gW40|Sdr*DsL0+Fid`7#LWzx_*M})$IBS
zvRA$9r#%A$i(1!DkiDv1KSB1Ybp5DcU|>=1`jN=Mz@pUk17xpa*AFuW1{Q^`A0T_>
zyMC}UFtEsVea~lLV3F;r{~p1>z#`N2-I;-bMY`*|E&~ILRM&Sg1_l<%u5a}W3@j2|
z-!d2&Sj4-&1u`(Oh;@ClVqjnq?fRy|z`!EX^-X|*fkn9MYb65%i%{2BkiCLkU%eO@
zSOmJh8Zj`i@OOQcVqjq5>-x&Xz`(-W^(C8ufrY2*3&<1PU0>=Q7#LW%y1r;KFtBiT
zeGz0}VBzTc3^I+q>vIwV0}ET%XOJ&gyFP<LkEQFg0s{jJbJu4s1_l<Uu201b3@nUY
zpJEsoSQxrKxiT<t>2`h6V_@Jo)AdQ5fr0&7*Cz%B2KMh=AF~-4xSw@>3}ay6In(vg
zfq{YNY}ZGvdIkobb6p>W85nrZcYUZ~VBopX^&yRcf#+h^2Y&_zo=aUHEEyPhE_Z!U
zWnkdB()EF#fr000*ZT?v2A*qO?-Lmqc&>N7_hew;xzY9Bkb!~cX4iWu1_qv6UGJF~
z7<g`Xy~}1`;JMTF4rK4$u6H1N?{&S?VqoC8-}O$Ep`L-~LDyT5D;{>e&0=8SdDQhb
zoPmMoao1Z%1_qudU2j23pLV?!VPN2S*7XMD!slIYQWzL`UUa?jV_@KU+4TnG!dG2y
zR2Ud|UU$9WWnkcW)AhQPfr003*XvjY2A+3auiY3Jc;0ut)@NYg`Ox)Rl7WHeW7lg|
z28Mc`PhGF_7#MgycfA5R@k`e$dj<xcuU)Uy85nrJb-e=l_j}h%kbi%4y-a3c;Q870
z(wBjO=U3NDa|Q;U-(4@27#Mi|biL$ZVBq=N^`e}Cf#+Y>3y=%{cfIgqVBlrwdSTAM
zz{}Y6LV<ySm#OOo2Ll5ybJz0%1_s{k$5)=$WlY}N^#CNeuj@WYaDUhRNCpPp16}uB
z7#MgDcHP%wVBkH}bzhu;f%kCNeFg>w-XmT2G8h<mk9OS)U|`@q)^*R4fr0mU*F8lB
z2Hq20_qZ4scu#iSEn{HdJ=JwLo`He)^!D)8=ch8(pXs`5$iTpRw(G7G0|W25uDi?(
z47}&N?&L8r@LuS;6VAZEd$H?|Jp%*prLH>~3=F)NyY2`uFz{aKx?RD*z<agpb^-$f
z@3pSmo(v4U*Sl_;Ffj1m=(;V(z`%R6>oz+B1MjV_TOd!|?z#o?#GS5NAWz)wx~0p&
zz<aO0>y{`31MmH=n{^Bfybro=rZF(^KJ2;)3a3Y1H_aFrcprD&lxJYzebRLk<cp_W
zH%b^7c%OCM0Qus1*9|WQ2HqE4H$e8j?79K6_f^*oP~g4px?aq{!271_I>?1@yRL&&
zzU#Vf%)r3=zU#Uy0|W1euKMe23=F&<yRPLkFz|lrx)#B}!27xDnll3f@0YG?pm6@$
zbxneSfw#Qt8Y2S(_pYw1Squ!^JG-t1GcfR7?Ye5iz`%E<>#8aP1K;JYt9%R$e3!be
zR5CE|UF^D&%)r2Rq3en-0|Vdrt}EsY41DLht|%}t@SW|t!pXqEcc$xdeK7+A-|4Q)
zF$@em8Ql{^7#R3YbzOF2VBkC1b=io4f$v1uWf=wrzT;h&Ss57kj&)tiXJFtv+I1<M
zfr0Nx*Cl%f2EM~xmoym|_zrbl5@KNBJJ<#4Jn|jrx|qShz_-8aVju$p-@dMkRtyY$
zd%G^GFfj1#>AJ|nz`(b=>q1FA0|Vc#t_!gY417DgE`aRa(RIOqfq`#(*9B<?2EJ`w
z7g!h=__lVP&tYKT+tPJDl!1Y7bJux01_r)OUFX#p82C1Jo#$s@;M>r3u9|^?Z++Lf
zR0amVbzSHD85sE1cAW#+yQb?L$lldm=Rhh~b)BtZVBlNXbvBiuo`G*g*V!Nj2EOH8
zXRR3+_?C5@1u0$HbruwsOS;aKGcfQi?m83Cz`(bt>x>5j1K+}~GlmQdd<(kHfI?<|
z*BN#O2EKV+r;8XE_~v$<j$vTno6~jLoq>UGcGqc87|!ZC4N^I?>oiE^jIL893=DkJ
zyH3S3Fo^R_>pBH8bZXZrkfBq$PDwH_@J(+2yZ(Ip-}M*T|E|B-{&)SQ?SI!_W;a;R
z(g5nuuuQnZB(Ro^i&3DRZNrszwhdR8vu(IGVJq7WP}Lo9U0^%Qg*Tv@Rp3TDo50O>
zHi291Yy!92*#z#ivkBa7XA`)$olW5WKl|k@3D*UdvrGWBZ5qJM9*4J}CXm5fP@S*v
z7G#{jTY;r4Z$WLDH=wr68-aF~fcxz%0T0?)0v@)r1UzbI33%Mj67Xa@OTbf5x8}oj
zkhTY4S6l~~a{w%`0VJ>hEHL3Z$dZQZpmssQbx_0gI;cst;AuO{f@ke43!b;LEO^n*
zvfyPq%Ys+!EDK&QXIbz@U^R;aqrq~PhPMKHS(F(;-dpgtoo&Ip?Q9F)gBrshK7d*)
zA3)7?2U{jkAL!#&mQR7l>Th+f&Sqc`xY@Znlz~CuM(1ir1_puaovSq&7zD0$t`=lq
z5V+d8s)~U@;7aGJL<R<d%blw{7#IXDb*?gCU=X<2xk`e8LEu8?DkcU7f%Ba!L57{{
zTp7Z^AaJ&Gr7Z)4z?sgKstgPQr#n~jGB607>ReIEz#wq4b45G@gTRUU&J~^v3<AeH
zR~Ruc2psENA<e)baI|v;GXsObk<R5g3=9H?JC}n@JJh+{j)6hoVCQlT1_prxoy$Q^
z+uymYl7T^BU*|HA)An{Q0~xlba~a66-JQ#%7#IY0buI%LwzG3-9s`5Gj?Sgw3=9I>
zJC`~zFbHhxtX~T9=+@4qAk(&VE&-XgxpPSp1B1Y(&L!Rq3<4WFmzXjz2yEzFqR7A?
zu)cE%7XyR9y3WN#3=9HmI~PYYFbJ&aT<pxiAh5b~u{HyPz^cy0A`A=yD?1m}GB60N
z=v<V+z#y=^b5RfjgTS)RMb-=q0!up=sW31IEa_ZS&%?kVu()$!2?K+`qRxe}3=9Gb
zI~Te$FbFK@TnO^T{LY0k3=9JEIv27sFbK@;T#(PeATXzMK?DPX!0gTipxBz#xd3GE
z%+3X(3=9G@Iv0TI9PiHgps1MEIUf{wlRM|zGB5~McFtF0U=Xb8oX^j|AXwcwucDrT
zL9nKCUIGJyU~T6-PX-3Ty3Tnf3=D$xo%7@v7z7(S=dm*|2sU=kEnr{}Z0ejF!N4Hc
z+&R~QfkCjPbFLNxgJ5gtTu}xF!M4u13=9l{?VWQn85jgRI_Cs2FbH;b&H)Xpb#=~B
zVPFvK?wrHRz#!PuIlG*JL9n-Tb}~afgJ56hY##;&!T!$KrVI>%6FO&u?48&-n~i}%
za8l>2JO&2A$(^&p85jhobj||VJGFBb$lht4vq1Jv@0?l3z#urIb7mR?gW$~0nSKlm
zg0nhjS}-sO&hDJ4$iN^tr*kGZ1B2k)&KV$k=XK5id3S#23{M7zdcg&qGmIG+1Q&MB
zkYQjDT+}&(m4QKUap!c9y-PZ$gX~?}Io*+gL2y~;bR7l;!R4LP#TXa_S9DGT1>VZe
zX(0cu>YN7h@9NHJApfrEoTkdaAh@=38YrCCbxy5fU=Up2IW?7mL2yIoRFDh5cTP29
zU=ZAX?&K#m#^kKd-ckkzq3q7yI0goxoX%c%1_q(r&R%^62BEypUU3Enq5RHXMg|6<
zg3g{?1_q(R&Ymy^2BD(P9(x7`q2kUSO$G*`lFl9>1_q(h&hBak2BEUf?i2<Fq4Lgd
ze+CAjitXX2KTTz<uk7qrW?&Gi>g?uWU=XVA>?&hm5UT0yN@8FTs_pFZW?&Gi>+CXS
zU=XVB?2=(%5Nhb`VqstqYV7RHVPFty>g)_*U=V8V?6hTI5Nhe{RA*oiYVGV4WMB|#
z>+GmvU=V8W>_}!{5bEgc02$WV*#R=FtFr@SSa*GA2gtOZ&UTP5dOO=A85o56I@_HX
z7=-#e+qD@OgeG*hi!d+<P3&x|VPFuN)Y%5|#pKR5Uj_!DDV=Q=3=Be3JKK~P7=)&E
zwsA8s2u<&7En#2~n$g)B!@wXkv$NHefk9|iXR96qgV5~GRtW|Mp*fwcObiS{b35x>
zvKbhJ=5@A!d@;YX1>}nboh_;i3_=S#Tlg3lgcfx+gMvh*vl&!C33fJv3IT!6W)lVm
z0shWrSq28-#?EFo1_t4V&ZayD2I2b7rf>!Z;kwQyX9fo0+Ri2&1_t4p&L$BC2I1<?
z###mj;i}HYR0am&%Ff1mUj_!@iq1w*+>3VZ)n#B1F7IrVXJ8O6>uls?U=S|tY$#@6
z5H9I#h+$w5F79k_VPFt0>TCe1EbMHMU|<j~=xktQU=Ysl_@BwZAe`6nKZt=rIJe`!
z6$68CPRD;G1_t5mj{n>Y48mC*|4JAbgflz-#W64lXLS7YtY=^lPVe|<!oVP$*6~k{
zfk8O6;~xhDgK$d6-y#ME;pC3LAbXQKKz&N##E!opl?fexK`P@r{<1SL2*-8&DP&*}
zj_vpp#lRpO)A0x7?dXm_Aa6%?{1Ibd5RUBl19D+R$M0+g2I26I-ysYP!eJf1Z5iqr
zghM-it1&PLhjjerXJ8Nx?)X)~z#tsd@hg#mK{&AEmk$Gja6rc|a|Q-s|BhdZ3=G14
z9lt=H@$L8t@{CW%&sYWqVegKg?hFjVUL8LT7#M^-JAO(rFbI2e`~*ded&duu3*9<?
zfL!R>@dM;SmyRDg3=HDJ&K*BQ85o3}I=<I2FbF$#d{1Lw5O!$)d;U}V-}9f_|DONS
z{`dUX_P^)9ZU1}zJ7>Xiwtx=;+u0@@1XbJ(S3tvEHcU(o``I4YF#Y3S%VG-}2UCCy
zA^d1(aroKJ;_$1T#o>25i^HFG7KgvfSsea>s^<Ly+gS?sgX;VTA3$bZ09DBcK7a%^
zfCUzO05vy2L<2~w04$XNmNNJt(9Sa9-*T1-|2M2>DKKX=SkEHB$SAO$<pL|?f_@eS
zM#g>?1tt)|3?f(<*Rv?FGJ@2yF$(NwIUvW#B+$<`fsL`BZ2~*vezpl5jQ{%AvpnDg
znPI@mD6pEP0L1*j$p~`9et~`#0WQXV76EP$!2=?AK?EO&;0F-`jO$qh1Q`|9vp9hD
z6ucGK&XNFb8wI@m$G@B90wa^aZnguAAod1ECV|zUS&!Xp6Bz&TuV!gr6zFF$5M=CU
zF%SX~!XQEfM2Lb2F~;>Q2I7nX`&lk<GJ+Z{2RIr3@$YBZ0O2hF@z%3U0K2{cOcsD0
zvEYipdX@mNfC4ATiUx7UewGFa#{Db}l8j!@>P<T41~M@47<bGC^+Sz1<|;BU@ECT?
z<zisqG3b~B>WAug%!y-Q;L+=t1L}wBcFY0wLv=dlNH8$)Xm`v3^^~<bX6G_6@Mw0-
z26cZmI%b1<%IY1nLET@qj@h6Nx@yNPQ1@4*V-~1`uG}#zfPsNWslH>DH3I{WV#h2{
zk5!>#mLLNIk9^0>Dh37~xsI8jeyD86Oi+(iremfV0|SqA$4mtV1|G?dnIIQRbj$#`
zP`qOXs4p+pF~f_2fk(7sh7kh;k4VQ1X$A%!;f@*X3=BL%9n%XK7<dFbrbjX`@CbBF
zcV=MV;qR!QuFb%}!`Cq#<V4<%X|)UtJUkuKG8h<mxH~{K7!Oy+G#ds69?p(wY77iK
z937w<jEB8rDyUD*)-g4Sfq{p$W2!d;0}o5bR8s~99_EgzpfF_Wn99w-z{A)vrG$Zj
zhoNIiECU1g|BflH3=G`=I;Q9{FmV6vm{Kpsz`*^dV{#n>1NZNa$r%g`+`l>|hcGa3
z|LmA-%fP_>qhqof0|WQ>j>-HC4BX#3CRH#naDVNXl*GWm{iS1)9|HsT=Z;C{3=G_#
zIwmPFFbMwWm;`E&P4Adk#K6G+qGMtd0|Wodj)|Zwzp-PY4g-V8^p1&Q3=ASOIwmsK
zGcbtE?3j?vz#uZKV?qc6gUIZT33dz&B6B)GbAuvtJ0=J)Fo?|S=&xd65Sic6pTfW(
zvY?~ipMgPSVMo6e1B1w-j(%kZ29d=b{X7f|B1<~@N*NeLmUi^TF))ZM>*(`jU=Uf}
z(PzxSAhM#PPnv;2WMxMm3j>45s*c_qhI$5()g8T|3=AS`I(i)#7(~`~^lCCNh^*`A
z6=GlzS>Mr9!@wZ2p`!<6@5YWEUj_z|O&vYv3=AThJ9-ot7(}*o^l&jSh-~fXE@NO2
z+1AmW$iN`7y`vkXaz{tEB?E)V&W>&s1_qH`9o-<m?C$6SnYpK<D}#ZdUSw}aR~Q3>
z$i9v)&_w6{jxH?*29X0DUBV0uA_qG<LEb*p(V4`+Aab~))0=@o<VZ)SDFcJZ(T+}e
z1_qI19i1Eu3?j!nItm#WL{4;cL^3dlob2cT8Fs3p17z6gjt-Dt&UCa_Gcbsp?PyP9
zU=TUi(eBT{AiDo}rWB(tV{%9P|2hT+(a!e&X$%aaUG4utlHKk9%^4U(d)ogiFffSr
zwu7oL(Z2S7r3?(B{q6ta85l$-wEy#DU=W?y{?CYkL3C34KN$uF(aG)q*ccc@r?mgg
zXJ8PW+Wt3^fkAZI{_t!m#;J_;)7wGgqM|d}|AN%cYzNh0qO;on6frP}&Tjt`%fKKy
zr~Quy1B2+?_CF>J45IVe|Hv~ih|X{S!_B}Tx}g1cB?E)#!uH=O3=E=++J6TyFo-U0
z|82v-AiAXew>krZ=+gGzLJSO|%i4d{GBAiPZ~v9az#zJ!{Z}{xgXqfo_Fv8n45F*r
zf9W$Yh^}t`CC$Jfx~BaXI|GC0+V-CyzpZQknaIE(y1xCVF9U<<hW4M93=E<h+kdJu
zFo<qy|0&48AiBBzM-2mm=$7^$AhWl&{|IGZ5Z%`P!;yhObbI>`kkLEZe}Fu=v;7Ar
z1B2+U_U|C0cemGn2bsO6{X59)z3tzv7#KwNwSU(DMMnE~VFm`#1MS~H?sjVb2C4~L
z+rRlUFbKD_f3sv@5N>Y&rpmw|+|>S!pMgPCupKmXDk{+a6%-cy?O#D=^0j{j#Tsw>
zS0x4pQJ(g%ybKJY-0feg7#Kvk+P~B%Gcbs9wtw+qU=T6xSg*;zAj;AH#f*VLl)e3n
zA_IdcTl*JKIJ35YE@5C0WoiEmiV^1a&#nv%qD<|dbr~2$8QVXLF))ZSw0~w`U=aD=
z{t1+S|FwStCFH;DpFsKOPx~iO+WX!9NrZtx<X8L0ItB)jpY0zrK{@_M`$v${@9m(G
zRFQA(A3;jLwu1&zMZUCu043AU?H^JZ7(_m`e+Xn?5c$~t!J2_V<U>1XAXVgjJ7^$P
z<Xt;xAXVgTJ7^$P<W2i~Q0{o${@#RvLF85YdpQOMk(cf7L7DSK`#Vsf@Vxz9A}Gf{
zYkvpw{nPe$77Pp`Pukz9GBAidZhyzmz##Id{cQyUgUG}7x1fCdp#7~U1B1x@_P2%%
z3?ld1-%2qsh}>;|%gn$aa;N=G4g-V8?e;g}3=AT-+TVb@eY5=ysQ9?i{sxrguD8Di
z`Q=*sYf$lVwf(g(1B1B8mG;+W3=ATd+g~d(Fo;}ge+??PF82S;mtySyn=cI_WI%*0
z<Nm+-a*XT&>sb=yL9KuVpjJSGJg5RyU|i4ApvX93Kg$IraDA+x1g?)4n1gu_lo<cX
z?`LUX1Gh2+lo|Wk1XMtTDu_@65$Yg914L*tu4fa_ViZ`<W}w6<u$PSy+#vV>YJxmq
z6j;k*0d9wwgPJW5K*q0UyI>AdeE=lHw!xh7AAdiKf)=QmqYWZ-K!h%c&;t?rjQd#>
z3>cXL_Ol%TIdVPA1|^V*3zR@6PJlSS0VK1Zr2xd+&NkugKmPSB0bpegU}XXziGH>M
z1IB)~0z(jC1R{(<gb9c+W!%qJV8;0G|9X~!07i#?mH-RJewF}B#`P=#R*W0Avn1>X
zHCqI%!LB`E&DhU!z=m->%K=+PhxIH9){G0*ve+>i^s`*BV_eU2!JhHKdX@tYj0@JY
z7}zoi^s^*5GVW(daAIWIu$L{85$rs9kS`p-qyd;z0Fwgppg;pNKgfZUJdgu<^nx5D
zE}TI@?gAoQL4+HKa0d|{jQiOHJQ@G_Z)XVrw@MxM|Ks1zVz3`H@T9OGG!4BUWN!i3
z=mbtiQ1kU4lfqgyYes>7wggYcezpWJ#{Fyw-i+?w>V?$XZ$>jPh_<)i1eJGf?Kia<
z7(`p!Z;CK5h_<xf02TMm?KeQhS5y0qAO;4}#`YVa!l<GBhB5<#Xnp$)P%%)~ejQW{
z)V5y-6$3Tx*Fgnyb^CQg1_sfp_Un=i45F3o*O?d?L@U~_Wic>_mbYI68CGA`e$ASJ
zLA12}nhFDhXi57uP=Qt4eic-B7qwqaVqg$0Y`^Noz#v-Ceic-C<hNgyVqg%>Yro3O
zz#y92ekGTIK{TiR3aHf1ZolHdz#y8{eg#xcX0~4emBAV9mqBG(di!ONVQKA`y%`up
zQ`;|t%CeOD_RFA3Bf0%Ds47Zozm&(oAez_?8VMFnXukw1r{mi%fr2Ei{SqihV%sl*
zO5K?Di>V9@qS5Ua{TLWTquMWm%F@X8iy*@y+Anf2Fo=e?UjPM3So?(-1_sg4_6sfy
z45A_J7eFOraQg+2VL|Qn=c^eQL<8H;gNoaL_VXaO`L~}pWnd8XYd;S%&A0tL$TXk!
za|H|xqTcQ2A{ZD%z1q)#JnGqg4&+gf_H&?$%)R|AsIqZuKMQi2Yx`MHG4IlT7G#)n
z`&l^#22qFhvuq3uVruPY@);P!)Z5S0M=~&oX|$hlWMB}}Y(JyPz#yj8enyaiK}@^-
zbR`3Wm`?lYBnAdC-S*R73=Cp=?Wc_y7{v73Ps=edh#9nl#(u>N+fNlRFo+qop8^?X
z+<ppVm`VF7kYT3nr-T?7#LU`HRx>b&nYW)zWnd7qXg?Xqz#wMXe$uL*fkDiw{iG5D
zgP3*uNp1!PF`M=i#S9E$w(TdP85qRu+D|w$Fo@Z=pU`1o5OZihA<n=c=GcCMk%2+X
zsr`5s1A~}z`|)4~1~HfR<JJreVy^ASl^Gbs+}e-xFffR@w;wBGU=Z_YKbFYAAm-VA
z%$tEh%&YyF2?K+ecl$9phI$4upY~(y3=Cqv?MFer@M}LB#lRru-+t7Efk7;w{ir?z
zgIHkuQ7Hxnv7q*&%nS@-!R<$K7#PGt+K+@VFo=b=AF*X%5DRNRqQ<}=7T$h@kAXof
zqWy3=1A|y(`{85;2C=C2!#)fQV$tn~O&J)(V%iUb0x!1xFdGBI{$r6ojCzd8;_bVY
z7#PGQ+IRCXFo;XG@2X&65SMD-mB_##F5SM%lYv28rhS(Y1B1A1`z|R4264IeT}%uN
z;_~e~vltk}720<OGcbrNw(qoKU=UYo->J#KAg<iLQ-py*T%~<S9Rq{7>i+O(A5g<e
zt$hbbt$O<odj<w^jrJYd3=HC$?K?nfwc5AWGBAj1w{K5lU=Y`7-|o-AAg<fK-GYHZ
zT(5mQ$cg&x+xZw6#0}cFl`}Ai8@6vtU|<k8YTxF;z#wkizRi$<LENN$n<N8+xM}+~
zkQ2??x8^c1h?}=>4P#&sx2SL53bNO-eX9logSb`uRsjYEaqIRiAP?KLZvlDOwtb5a
z1B19-`xbKs266lLEg*Xx+P8p$#<6{K83Tj3Q~PF+O6T^?-V6-lF72Dm7#PG|+czsS
zFo?UgZ{}rS5O;6i1XAhIz6mrX;n}{)oq<8ztG#}cJ_Ccecl#y@1_p7T_D#$T4C21+
z8}k?##QoYghBGjT`?qg&U|<lt*uD`|NAt9A1huwA+BbkQmvH+AP|H`SeM1lfgR)oq
z25SZeW%u?C$_xz3C)zjgFfb^eYhPc^z@U7geSHE0gYu>J^_~n2%2(Rg8!<2_Uu$1q
zFU7#1e4~9ms4P6x{>p=aLHSnux@-mp<$LYxf*BZ;AGEKtVPH^x+`dkofkF96`#J#z
z2IZ&iYbzNTl%KV)O=4hBe%`*;i-AG;Mf+Nip)cFlN;5DhziMC0!oZ;Xx_wPP1B3FL
z_BBxq49aiY*ElmUD8Fl8qr<?U{IPwFNIe6C@~8IIH4F^OpW9cbGB7BAX<zNnz@YrK
zeYF(>gYvib)gaG&Z(q&Lz@Yr2eN_nqgYwVzRj~{V%D>uIxiT;)|88HU$H1Wcr+t+q
z1B3G4cF-Jx^1pV_9D?%ycF-Jx3Pbx!8wLgy#`cve3=Aqv?VvdX73TI8WeoKUDlF|Q
zKtc1UeT5eTg9>Z=3S$Na6^`~5G7JpL((Nl)7#LL8+n47uFsN|1FOOhgP~mA`?#RHP
z!rQ)Fi-AFfuYI{N1A_{G`?4wq1{Hz!Wl0PSDuV6Hycrl&gxZ&Z3=?i&Cd0s>BGSH$
zoq<6`w0&tl1A~fKJ7^9;Tt&PcG>M=h(Y{ohfk8#GeW?fogNjuD-*_L!{=f0QAi@ts
z_%rVR8y~>PF0h_u0(i8j089qhg4Rws1Tr!StY=%$2Ch^CL6vF{<9fD)V8#ji**1hQ
zf`*tvK-Kz&0MK~Gfe=tjA{0b~frxO%{VWF}7(wGv37|GjKZ`&lXmlnDG&&Q__+dSZ
z09dyJxK(9f0csj3Sb!UC0v2Gy13`v=2mp}}z~lumc_4sMpqC|vv6m&5v6m%|v6m&D
zv6m%*v6m&0aV<*{W59Zr1z?jWgn-O!2myPe0K{QS06BX<O8`X70W4+!5mSJOeFz45
zHz0|zpDiGnaX(u?3ZwtC`lW5B>=_s&mb9JHVqlP1+;&Qsfk9$X8>q;aSlD(lg@Hk0
zLEA|m1_p`wZ6{3_7$oMkos?x@keJ(cl7oRkVouwMLIwtj*=;8x85ksHwViNcV33&E
zc0!YZL1ISR2|)%1iRo>}s~8w0rnMbUVqlP%+IHNVfk9$Q+i^1n28qe_ZO0WD7$hdO
z9p_|VkeJwZteAm8VnW-o7zPH3{<dST3=9%|ZO8N&7$kbzj!7^uNc6NFV`gBG=x#fj
z&%hwj)dni@B|6(cCB8&Q8>qyWXm2|z$-p4d)&?r^C0g5#<S{Tvw6q<GU|^7FZad=4
zz#!4ocEo^zL87s({)iL<gG58y5f%mpiTbv~Af<I}hr<~dBx>6ZJ1{Uv)U+K2g-mtZ
zVNnJKiK@0k^$ZLWm2HPI7#Jif+71OUFi4cQ9WrNNkSJ?AB+tMgQQCG06fz}k2a6aO
zB#PS(g8Wj{b`a#3!nT7TzZA3`6lY+N$ZtDX&%nSSk=J%0n}I<hx9vbE1A|0P+W}CF
zWVamv1!7j)0U-tkiOjbB)eH<08EyMh85kte+xGi0Fi51e?YCfHkVtLYufo6}k<zxG
zpMgOlxoux11A|0T+dfdUM67KeDDL9g_L(v;NV>G`lV@O%bZy(m!N4Ht*0#5(o`FHq
zy=`wC1B0YT+g=X_21(Dhy@m`7l3s0lr5G3_z1#M(Ffd5^wC%}fV371}+Y`aSAnDh(
z$B}_S(!XtwHUooXK-(S>1_sH%w%s)h43a@@yVDpLB!k;_2Qe^6hP3UrVPKF9ZQHHJ
zz#tjcwp)OKK{C8;S0w|3WJKGpB!+qh$;h@{J`4<!QEj_GPK<8b1#)6c+b(Vf2FcjA
zoh1wml5uT2V;LAE<J)$+GcZUdwC&VqV315~+bPb#Aeq#*lYxOjGP!L>CIf?HN*kzx
zluT^{RgjWtZ96m=7$no%c7W{7Xxk35H?wVf5(9%|R@-(T28Mdc?6&RZ3=EPvZQB(X
z7$kGswu6EuuWef)1A}CK+qOss2FZf9ZB7gfl7(&Cv=|s9i`upcGcZUNw{5LsV2~_n
z+nT|^AX(bB73ANtwyhxlmbYzHWnhr3Xxqxiz#v)K2C5(>tJ**nq-1s57H<Xy$wO_R
z3Q}_aIm=W=HO6Gqwl$Ru3{qxoYZ4h4q|Dpacrh?YS+uP&Wnhr9Y+ED8z#wJSwuYU7
zLCU&qbs+<Tlug^}NCpNe+qTtC3=C3sZL4({7^LjmR*Nz)NIA5vs%K!3a%@|b&A=e#
z)V3;wfkDc7f4Frj<5b3am$p^v3=C4PZL0(r7^K|VR)Q>cZ(Etfz#!$(w$ht{LCUjj
zCCFm0wv`GD3{u{0E4dgLq<q>|6f-bL`L?ZyWnhr<Yg^&Qz#!${wnCqQK`Nkag#-hG
zRAAc*CI$wnpf*qiAQjvOssN-y+Lk*rFi3^AE!SmWkP54BTMkkh-nN{Xfk7&wZCNe@
zgH&YOvIqtSsi?MPt_%!P(QV5N7#O5t+LlQ&Fi6F=Edv=E*R~YooA|b+Am1dkEwyD}
zkV<S@3i3-*+frc$2C3w>B{d8TQYmdqQWzMdQrnjJGB8M`wSnf6rPAA$$TBcUWwg~V
zVP#;D%4}Pl$G{+!)wUQEirH<T$z-XVw#6VP=C&;cC9L;ti$R%_xouG<1A_!p+oE6w
z1_{QtMK%l!5)5sN)EF4V|F<m?Vqg&e*R~MU^7`AhFq45n{7>7$5C#VE-)##)ZKYpr
z3$+*+#DBIe6lGu#|IxOvo{@n;{CnGi90mr72W@v$85qRBwSlIV#lN;KaARN)|I)Sq
z)K>i5wm^=7LHtwO0xkvy@sDluOBoo%KeWvUHQC;`%?CA|-nGpKHL~8e%?FwCrft3;
z1B3YMws|1OylR^Va?H!Nd7%sp;xF3fIWsVbKX037P|v_1{;X}D3<HDs)3$jW3=HB=
z+UAxpFo-{Hn+r1gQQKTl1MXqlTuTN9@ds^lL1y1?n+r1gUfUdy_PcF!au^uI@3hT{
zWMB}#-8RRSfkFIc+Z>RyZ?w$;Is1Cs9Bu{%@oR0fD;XHXueQxjVPFuy(l*<Vp`Jnf
za@%Z>yDzoPR$yQdzt}b#<iiVXvp`M0^KG+0jl*+ovp_yP+cwLTfkFIC+bocwr`u+M
z+<U5RW)TB}_{p}Ju?!62C)#FuF))Z9Z<}e%z#x9CZ6?TPN84tyF))Z9X`7MHz#x9O
zZ3f7phuUU<94daWZH68LgZP2A8R85K;``fXFfcHP@9Y0-pUT+(*FFtIq=SeI#{GZo
zGZ{Gp_OlsefyV<D%m=jx0<u8E4%wh#haAQU>sc1$f-3S4IUrI1Jd&^>m$9E^Lmr68
z2N4Azq7XzBfrw(p^(-4o7#;Sq<TC!@-?zbmkwsuVivhS*pa3QXz~lrI&^%WHm@KdX
zwOlUPfLDEg08NASvwSFF>}UB<3L?rtL^+7401=gp`&m9zfd^zJ<bs{v0Cr>nm`nhZ
z0btSrOd8~Z8Waj(=LqC7hO*V0w6%dUpK)6o8v}!sQClmh&@pTSP4`L}w6%irzJ6OP
zD4XiFwMsECNa?n<vM?}6>9n<gGM08*3n*i0wY7jUv}Rk2Ap?VyMq7&v1A~-$TMNic
zwYFxEnW}Bg(F_byDs9ammC9|+ATyQf+nPa!Dz-I)a;rjHQxOA$lzdwgsOXVvYjS5`
zkdkd{GGbtml4)xK87ke@1Ts{rtr29XWLqQ1P>HrikVD1W8jTqkq{P}9LFK4u8)(v3
zN~8@m=_@7N)&Me7sI9?+fk8^Jt-*wWK}w*lz5!J7@wYW_GcZW;wf-+<V36W%{hz?V
zAjQ-A--m%gio5l{83Th9SL=Uy1_mk4*8dy~3{o7e{|Xowq}W^kfr>M>)_)ER3{tGE
z|Fjqwq*z-2i7+roF}MD$WnhqEYW<tWz#zrg`qz(vL5iXEuNeb_<p0*cpvv!G>)(1#
z1_sH$t$#qZ-=9{{h`HqN)<3Qc43fWE|L8F=Nd9aE&H76IX#EYU!oRov2Gv5}T7L&K
zFi3uF1r3!;erf%!!oVQ;x%D?M1B2wJ)?cLz3}Q=Le}Ssf53Rr47#Jkqwt|Mpr7pMr
z0)_UKR?tFXsjIC&b3ygTwbq}Z3=C4&TYrLz+8eE)!EvdZtv~q~7^H5sf>shs-ERGn
z%)lUZr}YOYNba`&0EOPY)*qmv_I~RRP>eii{SHbH4_m*7GcZU!YW)tXuO7F4*Jfal
zdeZt`h=D=sY3sKt1_r5Tt=~X~J#YQy%TUiC^`iBgIRk^#%hqq8sCd=-jgx^v>UHZ^
zQ2f4W{Tju<AoaHOE2wID*ZLJ?+WXe8paA~R`jvr!LF!}cmrMo*sZXt60vQ;jKDU0c
zWMGi`()tBt*w@xCpsMs+>*st12C46@pFvLh(fZkufkEnL>t}5ShI*-At)D@4%J0@s
z)eH<$e_B6*-1fKi6R3Xt*ZK*Rp#Hahl4W3!W@!Dy&cGne*!r=6fkB$7^<xABgEVt1
zXy99#rS+pG1A{bc>qkKb25Gj|4^<2d((J9Efp2M!)(^f64APvfA50k-q`6u@fD8+4
z{lLn=Aie*bWG<*(aHRExF$072(bgBz3=Go8T3@g*Fi0P7eV)(2Abq0sImo7yt<N19
z7^F|NKG$MkkUrh|T!?`|`b_IHkWFV>pCvOeNS|wc=EuMweZKXX1p|Zhh1O?^3=Gm2
zTc2?;Fi2n8A1<8>Y8TYCK8<EzkZx#w>cYSv`LXq>9s`4PW9w5X1_tS-)~C!24ARZ5
zPqG;pq+42_gfK8jx3)g9VPKGMYki`^z#!e;`h<spLAs;$aVZ0XbZ6`11O^7_uGYt1
z3=GoUt&c&z=xKc{!@wZj+xi&fi@w%JISdTa{jHBe85pD|)VDseWnhq=*!oDFfkApw
z>my+X2I<MI4?!FMrnEjxWnhq=+WOF+fkAp&>qC$?rnf!>d1FTFLv98J>6xt$N*EZV
zXSF_vV_=Y;-TDAz@0`{LCJYSHb6X#Pf_7f(15iB8Zw0L(mR`^bT0<<ou=Tz(1B3LU
z*82Op3=GnXTS1G6rI)nc2l;nt>phSYm$lvl`FDBiJ&+4mwBA!?V31zfdXJZZL3&l|
zU66lQx84QWyQcN7Cj*1@+Sa=u|E_DjE62bfy}tD>2LprjhSobp3=Gm6Tkpg$Fi3A|
zz2m{aAicTu4oKye);sl}pxN4b2UOnWw@tTXV36L{dOMGSL3(@Z?QjML=^d@N9T*s-
zcedUJ#q+M#+hPn1(z{!4)iW?i?`gf2&cGnOxAhh%fcCZC0tL|i)>{e;4AKW$Z*ej(
zNFQvy2@0S?tv6#C7^Dxk-gISP5YcG835w;*tvAI$#mJIY(3r90;?^7K3=EQsT0vvR
zk_%gJfZDVRT5o{b@bg=5fZEdYTCZ0zFi6gAy`IXzAUUV?x<3Ph<m}e#RtyZ1vs$mK
zGcZWbY`qRrIivL&sMS5a^%|(vJ+1Yc7XyRj)YfZ83=EP}TCYhnFi1{ry~Yme2~29e
zTEM^{IkELBsMS58^{O)igJgf}RUHNf$-dUBq6`d@y{%V3t?r)IE1=eXck2~UdDqo?
z1?0lc)+?Y^cSq|LP^-JW^>R4_gJfGPXy{n7we>QnlhM+88Pv&WZoMqWz#!Sw3K}_<
zY-|OM97{<yw1S3?CF@%+*)uRm*0o*&^&M(kFA48^ki*C#(9hyf&A6V$p$4?XV}Tv0
zw*OEAS_rbBmT^7Hf;v#g-=G0hk2W+hGA-z5b7)}fXLD#|+|TCF#Q4vCJ&Qs!NYe&8
zP$R;jnX#Y6p#@}ME2t4Mp$#PWpcO<;$OMrG!0I-%fm#ghAff|Abb^R35YY`HdO%Hy
zUeMB%4`8hdSs<+fS&RZ}S+YQG`H%@7czBQrZUtO`n4Afc*#MDQ0FvovdC<$)&+?!T
zMD&A*2_Rx3h?vB<p5?)0(7KR@Hn3R*ZQyyR1PCtx#9Pne0Cv9tm{b6h0&O5$0w7~8
z7g|As4+c{h``HYpGVW(Hn8wKZfN}PI9)anMPHgq+tp`{c7(~=s_vbP&h^V&i2hAO-
zwC=ZOU=UGm-LJvGAfnW|A2eUC*t)Nlfk8x}bsuPoTfTK4XqkXq>psvlpKR+s&~%$j
z>pswopmgir5(Wklsn)&m3=ATYt$V!~7(^sm_k!jQ#as7+X4b`8_kvW4*0=5fDHUnm
z15zs7x(77PDAc+Kv<5)1bq{C_fI#aWP6h@M{?^?^3=ATCt-GTc7({qmce^k!h;X;=
z2CaGEYTYf$z#ziex|@-KL4>1q7ih|qy>%DJFKn&5K-2ZCt-G`t7(`fFcY#(%Ft_dk
zO|CMv*6#!<Wo+FU!N4HG(7Mx!fkF6x>rQP32H}6Lpn+iFzpXoJ7#M{AwC+e@U=aS@
zx&ySP?N{p#GX@6XpRGGUi`jm(?%-lz5dPk}9kiJ3TkG~{1_t4;t=mD1*}k-H2Q3x*
z+`1jK4(n6vHqbh(kFDF%85o2=v~H^pVqg${-@46)fkF6P>o!#e2I04@+xQq5gx|Do
zEn{F1e%-niw3_Wz>sHVLu$Qe{^%)q1U$kzOU|<k_-nx~UfkF6L>y}&w2H~fzTR<!G
zp0sWOjk6@SZqZ<1kT7Z80_qLiYTXQ~A!}MUhcGb6B(-j~WMGg<Zrv<j&%hv)(z=<A
zfk7s<byFS#gG^fMrZ5Hune^68)(i|X8LgY-7#L(STR|hfGFhz~(-|0KvRgNLF)+yF
zv~JX6V35ge1r7De<h5?7U|^8RZ`}~bz#vo5y1|8kL8h>EgEj+$Oi}9wVFm`7;@0(5
z3=A?Qt?NNbN?X@EG1N22l(nwcU|^6bZ(YyHz#vo63L4dwscc>6&%hv4)w<4@fkCFa
zb)7f^gG^29+8PE1nc7y+aIQ>U>sn6+2ATTSwIEkCw5}CkV328ST~orqAk);kCY*sm
zrnz;E6$67zODm`wFVot(hM9purmb~#1_Ogkd+TaH28Mc>j@H#C3=A@zt*fOO7-YIy
zS2Hm%$aJ@^%4A@W>1kc%%fKMh+q%k-fkCFPb(I(cgG_(xN{~k<w62U|V33*Ey3(G3
zL1t3xN@WHHnaQmyIT#pZrnIieXJC+-+PVT1l+#*Q*fKE4OmAJG!oVOiqjd#H$;{T}
zSquy^`;SXbXVhg(4sM-q&A=cV(mG#-fk8I36|`hoHmr4C1p|X@c<a1G1_s%P)_L9x
z46>1}pcTuqQLUhkq-=ESJXQt<*_hV3c?=A)v8|vL%d&B;b6pr1WaC@s>M}6MCbWW9
zEXyYD50{<}YHcL7&PiinkWFr#<Hx`to6<VRoPj|$wRMgX1A}Z@E2#4*o8CIRgn>ae
zqjh#H1A}a4>ufg$2HC9E*?J5Nve~V(#Tgi6b6RIJGcd^Jw$937V35sgofXEwAe-L`
zTCyx#&^k+lfkC#g6|~?>wy1SxH3NfeaVu!avTR9x>&!p~2HDcqnII3Bwa!#!V2~|u
zoypI@AY0KoqmqF^wz73b5(9&5RqG5N1_s&c)){6D46-$?GZYyZWNTYz@G>yS*0oMA
zXJC-6Z=IgNz#!YuI^BzbLAJ4Vx(Ne=Y*XuW83qQ~=GN(K3=Fa@t<#Da7-U;pr^PTZ
z$hNiCPjh8pkZo_Brq942+tE5rf`LJ{vvnFH1A}Z=>(p!p2HEb`sUXkrwoV1L?gCn;
zf@*#L)~TRokzeZ+P_xLlbqc6i<kLC@)VlL-odT-$y;`S$nq!`=Q}`Gdq&-?ES1>S0
zySGjTwFBK+C;KokNV~R9t_L+aU0Ns0Gcd@^YQ31kz##41IvLbXaB7_dY9~0hPD*58
zkalRD<jue!ZQnWx)R3}kodjyo*tSjrHKc4>CxWuGbt`E7m$X&uL{|m|Y0K7$1`G_+
z7OfK{85pF^TPHFyFi4xVPRL|nkTz|d5XitFZPGdcG<PU%+&V#tfkE1+bpogXXV}_b
z#=szL(Apo*z#y&P+7D_T>9zJ7GB8N%w)TTe(`oHzVqlQgZtcruV35{o?E^J`HCy{Y
z4LFU~K0O8oY4z4V2?hpfwbnk6O4Zh0kV=)-UQh!{xwY4cfk9fSwO5~^o<Ul%wHIWl
zLTfKbseEe>sHrE{+5>9p$+q^`GB8NXwDy1+qtdNC0t^h&Qmx&fHnn7HcNznOv_xxn
z00V=xcx$&61B0|!Yd5G-DB9W$3U!gzE>Nfow|0R-U8uDS6zYPlUFHl7(gLkrDxir$
z{?;y#Qoh#Cas~!z-qub~aP##4m7mVo|5ttnh?of?W-;#nD?b~&L_}Z?sB$lu4Qf9a
z%mJ<0oC{jBIS;f(q+vdIGT_2I(6WsQ^^5}h*(S^f*ZC86fYfi84{9zf01*p8#3B%}
z7(^@q5lb2Ovus$#$fU5J?ZG^7^{&tWHc+4ev|gkEY|@8%ko^z9<OPrwEC=erErJd8
zVEG00Ae$~MW9(<SupC6J01+!e#3~T68no<U4QLvpU_QvC1TYyeAJk580J(oZn*qel
z3Sb!lFzEnk$IJse=fFHrJ3?VCV?Ue1I>!BM3hNm?p4BgF`JTYQAi2EdJ7@%ZMay^4
z2=>aB?=lPwlB-(2vobJ9u5S63%fKMHrsZ201B2w+mT$HU43g_wK)X~W*SCBF^^iBT
zd@W^Qklfhv6*L^aspYFD1B2w|mam|e>XsJJE>+2`Enk@#7$mo~e92~Dklfz#1=Rf9
zQQz{#nt?%bXUi8*e|uNU7k&l?$=xlVD;O9g_q2QlIc;ytXOL<8T0R>vFi7ri`7FV}
zAbFtWGb00o<iVCtpvLUsmQO(p46<e|pKKWzWKCN>sWULhnzVcpU|^6nZuwZnz#wbX
z@-dl#LDsP4BdAC+X!!^#lJr~ZKPoUV$m+Fx<Yr)y)ou9zDwA|tK7fjA?UoOqGD)lD
z1E@^WYytH#Wi?tpfXXEGmiGk=46<r1@1qzPWK~<<gNh`TmiI;s46@2C@1+?SWR+Up
zgUVOMmUp1?RiWiw2m^zxe9Jo<1_oKVmUp09Lbl~yJud@;tV|1NRh6uC%Ue*XDb?~8
zR82^>yftQEkd<h83o=c-<t+;XgREG~n|uZaS<#j^5ey8nA}yd*RkFe@pjB0}LM?9u
z85m>*TV8{TV1bs`Aj9}uUV{wdYk3Xw1b548c?JgAk1ek`85m?gwY&mNV#t1Oc?Bw2
zzqGsp`QmHKD^M-*t>qP{miXTC3RJNEXn6_p#m|<P;S3D2zgk{8F)+yfZh5K0z##jl
z<)s({gY4gymkbOHvj19MWHB(v{%?5^!oVQM(DK5LfkBS3<%K2#gB(-K3sD9JIp&t<
z^$ZMhEG^G780s11SX-V4F)+xnwLG_GV31>Pd9K31Aji@2oR5J)j<W^S7nkE|0rkb@
zxLcn2FfhpRv^+CqV36Z&c_zcaAjjA8jD>+gj=$w;E(3#{K+Dqz1_n97mZy#k401v(
zPqi2r<b+$E3NtXsiL^YaW?+yLZF!Qyz#u2q^2DEkp<YhB<%uN&gPcUm6J-VlImwnM
zybKI-QZ0|m7#QTFTOP+VFv!WYJoaQ@kdtkBY{bAIC)Wb%ip$BjJmz3vkW*-RRK&m_
zr`Yl+hJis&spXLy1B0A$%OiaT204|MM-mJSa;hzlm>3x3)LI^9Gcd@hw>%7GV35;j
zc?fdh{^Oh*K+T6oEjK|nJ#M)Pvgt|7O^{7bTW*4U_^jn7D+7bv^OhTV3=DEFT5f=R
z__F1O69a?XtCkx&3=DFwTW)}Cded@)k%2+(ZOipc1_rrzE!Tq?806l!T(@Chko&Md
zoO=VP`S7vjx*!9C+@}^$=Th!-%e6!X2DvXS*FYA3Z2@&I<-WCClVxC#``&Vmoq<8_
zN6Xbh1_rsGEmxx$803Dnfclnlzgs|kOSwNSSH&0@<o>o?0Y&M*7Es?(?tjabPzDBh
zhL$V#3=Hy&Eudvd@=PtDWl8eP^(~jH85rbQS}vzEFvzpET=r*RkY{TFtxJ+;Zvk~K
z<vChFolAMnmP-W;4Dwtpmm(P$<hffeIWaKE^R$4LCCT%)ToPhnkmqZ;SjE5~&);$}
znSnuGpyi@31B1L^%SCer26>^DiwX=3^1>|_IT;w_MOrQtGBC)Cw$xt$nI_h90c4tZ
z%LOe426>5=3&IQx@{%p*>lhg1rCQFXGcd@_X*mz7rT(^@2h~#lTFxsmFv#3*InT|&
zAak$fTqy&C%-xoApoZ|BmUA8q3^KP{&Vd@Dw_47DTHH5V&apEv$lPc-Tgbp5bG_v(
zsIhsi<!rqZ1B1-fmb2On46?ngoiYpzGFMv8iZC$9Ty8m2$G{+SspSl)>3Xr{OfUn3
z%!QUSHVh0h=UdLGF)+xSYdOQuz#wzB<us@Td#2@dA_IfW>6X*p3=A@-T27lWFvy&2
zIjzXRAakPSG!FxV%<+~}Wef~5$68K-R32?P<pb(49BDZPQhK=M6iDfzmQ#ET3^E5>
zPF6B7$Q)=nnFMOrwwweRx~~N^b1k#C1vGOlv!~@GsH3sF<wOAkgUqg$6EO@7GCNyN
zxH2%v>}WZm%fKMBz2yX`jlHeqILI$sTaKqOFvx6aIqt{6AhWsUxH+i9u&L!ZC@eR&
zfEFvsY-j;3R+3rYax8&?L1tacF;J&qZObtu1_qfmEyq9sw7TUOD+7bfsus}9wam(v
zqtOfuGAmk+x-l@wEN?jqQn{?<s4N46%+i*lpvL)<mLtUs3^I#bj)3B4QOglfcV}VC
z5zvf?%z~C9AaBoa0j*h*nb&d{<n6irfB82s_W$MI2qHFth|P@q|MG8P<P7L#+sfF>
zwvBNw+jho(>({ePume@Q2eyMN@PZwTpmm22wlfN>XK4U87#8ec>}Of96GZF+5xYTy
z9D5iW*0WpytNO5=QD800d=RmNv0y!m!d{Tx2dtoJ3WvSmg^(ZiGVW*lu#fTI`SmOT
z|3K0SmqBA431>l82b={fda$3dpY6c`5OEMh90C!CLBtWp{cI18GXB$F&(Z)MZYcnh
z31Bh+Ogex)VPMC|B(RqaG7w<^9%PwN3$kv*c2I*v;23Ci#&HmFf^k2Kz)8kHw)%%H
zn?MEjgBDN+Q|^AtCRGLoxqB^}1Q;0P?zU{KVqlQF)3Om%#@=q(=*PeycdKQiIRk^-
z&6bS{3=DENS~hYqFvwkR*-*^DAa|{0Lo5S>+|`y1pz`NR%LWq$2D!^E8{`-m<Sw;r
z02Q$pTh@b$*b6P|K}GEO`j+*eGWJ}{dQcgAwq?B}1B2X|mi3@A@^s6(0tN=TQ!VQv
z85rbFwyXn{ktbT#fog%{E$f6B803z%tOeBqM_bk=Gcd><X;}-ZQVzGQ1-bB0%UVSS
z2DyVRYq=R1<PNl~0aXI~Th=5nFv#s|0ZlB+?QN+C%`D69X;~xBz#zA~WevzPyINM4
zGcd^QY+0Sez#zAyWi`mq?JcX#7#QTXwX6ntduz*TkjgDBt3ZZsZUOC1mfO^_3Z!yl
z%PNq{4K1rcD%ZEH0;ycrva*DML2hl!$~XoFxiu{-K>@V7Wo11mgjThH=9lGGwyXrX
zbVUnjm$KaQ7SIACxn(V&1x9j9TULNnE@@c-a_Hig6(E(1T9$(xy0B$A$e{~bmV>OH
z-?AL!`*|(PLB5~cvK*vxR?D(71_t?t7SLX0`No!IJ`4=<O)bkT>lqm2n_HHtFfhos
zw1AGUlU&-ew32~AzO`j3s1$B%SqdtJ+gp}eFfhn>v@BI(V36-@S<1`6Am7!p1XNyk
zw=79zV36-=SrWj&Am7`v#EOAIzOQ8o$jtthC43AF@)KGXS1>ThPi$G7#K0gwsbw+9
z%*ic_Eg9+=<fpVOR%Kw2pW3omfPq1NTFWAkq0?Iyr7$qa&uCc$s!?XPECLxit7VZo
z1B3kR7SL?7{G67BH4F^$b6XaI>YjNm3xgRL<mb15W}D>~v@8UvT-dUZpMgPsQOkmI
z1_t@XEeqlq8043<EO2LFkYC!ez<`0FUVd520x1Rt`Q<GOm>C%4SG0h(F3YcMnGZ5;
zRSRewKz?-#XdFO(P0M_cx7W6S#sTElwSdL}G#|Ch^JHMqkZqY~$iSc>(=tzzfk8vM
zWgZg)gN9Vg+-wF04at_dVGIl!5-oG>85lIgTjr`WFlat(nJd7+ps@d(<Vn!{Mqvx6
zU#n2m0_xW)6t{r-wF)IIQ&Jch6iQpB_%JXil(kGTVPH@wZ<!*;z@SjkGKGVIL7}o`
zav=kQLRHJ;NCpOl>Xyll3=9f2Et54F7!+z-CJQn!DAct~s%BtNsNWwheG=4UXlR+_
z%fO(}*fPnKfkC0EWs)odgF<u5Bvu9ng_f3yc?=8+tt}J77#I}VS|-{vFetRQOw?jv
zQ0QoxD9pg1(AhGfhJit$t7Sqe1A{_$%LI^NJuMSJhV`~g0J*KNWdb_`gF=5xKgewp
zTKZ!c7!)S9^t&=JC`_tv>DOgoP?+4(FUG*2Fr}rhj)6g8YD-@_1B1e}mOg(528HP@
zeHIK13Nu>zlo=QlX14V4Ffb_0Y5{FiR+!xa+NP{9r={18fk9zzORpXSgTlNP&^Bd-
z`7NMr$_fiwda@Z96c)DhgfcKFENbZid17%(j|KyS!jhKy9#EhxZ2|35R#?^o+NZ3r
zyrtWZfk9zK3#bpPu(AcThe<)Zr5n_G%xeK{Q<lqZ=>p~4oR%(7d6nJL1uCzyTDrs;
z800crx)>N3<T6@7+mz+fTRK5)!nBr7P-{801+-0BE~TZDpMgOxxuv5Xlx34zIuaQe
z<Yih8gIaTmEgilL3~~uA9iW0EzNG_{$KzT$K;>m@OFO6#jA>~HH58*;+CdG?sFrq6
zLou?Y9n@ZnXlVnr*TP%cG8h=-!dlt_7#QS2TR^*&<w9E8K*d0COB*KxgIrKcE2xto
z7ueDYDyIWlK=apf{w=K_&-k@~wkyl|wzPsg<I~atGR?cC1$4xuS4)c(1B0ArOADwy
z@6pl%@{D^+a|Hu~oLfsXsL|=#((J{+Am`H3Y|OwQ=iJf^YVA6;G=oZV#}?3TWjTkI
zrbtjH!M>%*g@HlNuBAzjfkDxur3uvBwP|SrHFvFB8nYM}<g8j6L0t~ZmPT6!204qC
zMs)@TIrElAP}AS6rJ;_2LC&<L0o1ZHX=woY*SMv@f`LKKs0B1(Eoa!$0P?Rv^M6od
zSHJl`sIjZp{2#RLK~A^%Kghp2&Htqs8055@|AU;U)&E!iBxC<y`BNa`G>A9@8gV$w
z$ZoKn<-=J}H5$MS+8!Zr4pf7l2i2e#7?~#QXG^#UZZvGT0IJOswt#E%f{UO{8kZRV
zy<g9wFbC8)0FPOGm<=-L0hqi1CJ%tg4YNUd7t99t?I(bQ*cxUt3iPsFVeDnQ%Gk?x
zjj@;QI^$Zl8;l$FvmLkqw(!Fiuwh$3S}%aCUC(v^#9`a81uVY+EI$EEHh{^3EueP5
zh8v)fj+-Fj7KpeFBJO~QyP#Q=d!Q+ffQw+KI9vn`pcsHWxSvG<B(|ST0K{9%auH<t
z2e6+XfVSK2XS)D#)`AP5)tmPjds!YZ?qzw%82GHdp!tnE1A{_-^Ba8z28F!lHxdjC
z3c1a17#J87a++UfGB7A)H@^;HU{J_ver?OZppe=8T9tu8A*1;<F9U-@dh@F?1_p(+
z=2r;}3<{~uue=!;6jGXBfr`WA=2tQd3<^ojuUHru6cU?3U0a2O=9i$XAK&~EWLR8%
z^Gh`b28Gz>m!Pa4)BFNd9!596NMm47h-!Wj$iScw+5Ezafk7dn`GpDtgF<-o3w{O$
zg|O!5pn<L{&CfxFQ%Li3kjmiZ=OC3q&7iKWLSXZAkP8EvpMhNH-~0^ZLciu`AQ$>J
zgSxf~KF#&d<QW(gyqlkaN^Gy@rv(fQ3ZBhRK_#|F^HV1V1_k$KP~TR;t@)`41A~HV
z^HWgBxHLb>Vqj2kZU)UVD>yYjv14FRaBO~}&cLAH(EJ2ceb_fYu3}(Nuxoyt%)p>v
z+x!?*7~3>Iwq#&Xux@^=#K53n)%>`gn}I>WviVU71A~G^GpKK?VBY-5g@HlAtoaeB
zFg9&|1S*V8njeAeHEss=Z551~AA(}Uu=$}41A~G=^FvUK=r=zE`B$&`0m#3)%@5)k
z7-SwcKk#5+P|$3CV9dav$lnZ_WmXhue!#}SpeWdUKfj)VK~bpremDbzqHyzl2L=X3
zk>>lF3=E2*&G&^F7!<{t?}3i26>q+m$-tl}(R?qMfk9ES`JNpEgQ8UPJ&;Q2=6fKO
zGR=2EDrKARW-%}*$~E5&WnfU0Z@vpssnC2^oq<77vH7k51B0Sc^PNft21VuOJD|mt
ziYm=_ycif1RhvQ6%!+EwcjOru6xEyWa569`YBb+2VPH_yY`z`Oz@Vtr3_7t&QM(y*
zVwIv!Gw8%BMcwAxAeDN}x5^k86!n{Lfm9ka-|}E!P&915WyrvwXw-a5l7T_dxcL?%
z1B0ST^G%QoO`C59GceREnl<0FWnfS=Z@#I)z@TW+d{dBtLD91LMim2tqE+*aWCjLB
z>*gEY3=E1k%{NRK7!+-rZ^$w*DB3mO00p9b^Yuao21SSF>(LAhijK|KT^JY?otm%f
zGB7AQH(wWJU{G{vzE;b?py=9sEscRe(XIKK9|MD;d-FAO1_s6b=UzSpH8L2Q&)PCD
zC^0slRbpUJVro9i&cL9=+<YdNfkBC-8Pr2nVr@QS#lWD%)_g{hfkBDA`3wgGgAzyc
z=^O?ICC=v40SpXET+OFV85oqfn@@`~FevdfpQ>bFP~vSq701A!#J4~E^+Ql2gTMKd
zIs=1}K=UbH1_mX;=94813`#=HC!-k{l!Tj4Ix#RPi8P;7V_;AcZ9d7#z@Q}7d?Js5
zK}o#%L<j?el0@?fkTWEkPk>x1)qH}Bfk8>S`FIfngOW`1@hAocCE4cV&I}Ana?Qte
z85or0n~#HBqtJYuk%2);vA+3OCIf?#Qu8s8i<O&?SuijtsWcx`U|>*EZ9WE4qt<*h
ziGe{$z4@pk1A~%A^HGpZn$1U<7#NhanvbM0Feqs^AMs^iP||5WV#dIrq}zN1q+PH1
z2q;YSn-3Q-Fen)`AC6>TP%>;j4Dymu^I;tZ1|{R>`oj_o3`!==he4*9HXq7nU{Eq^
zJ`~Eppk&^B$ew{g$)foXC@Jh}J_H*2_}Y9BG+6Pa`CtYEgZ$^_gMkbT@}HUyf?B;F
zn-78--5;6{axpN-zi&QJ%)lW3uK7ST1B3kA<^wJa4DxT959l*6$iHqrAi=;O|El=_
zXmO>|jpqHJcF^kPf9?znO4pnBgF^ON^L|hoxZS)T)IfgPydTu)e$u=T)aZWP44O=q
zf7A?`OqPGxybm<;@}PMiXyoO7^F9s+2Kjr<dqKlEcboTu243zo?*&<ZyBTzti2SYQ
zy<!Xu@;96J)PuSeH=6f=JafHy52#;ot$B|n1B3k4<~^Xs{*~rEpoaP7=G~ya#---n
zpuWb%=G~xf$%W?KrVI@7=bLxSGcd@XYu*hS@j2VPtCWF3{&e#$P!s-C^DYkt2KkfC
zpxs3BCz^LjGcd>>Z{Eeiz#xCDd1oG|TXD1*G>a^Mq<N<^1A|<C^G*W>2KhtHJ0%$y
z<PSFQ1VzlP<{dc<4D$P%cZ4x8$nR_3VaLEAzqfe@C}j3D?*NS=?QRBbCX(OPydBiZ
z*x9@t6frxRw}T>Pd-HZ>1_t?U&D(hy805D$Zv%C)wlr@8tsa%%+`J9snN7{xK%Uvy
zyiJaQL4HI3-}et0_y2wW2;8bT@EBBw8axKgTU-!k`oll1fuF6P?ZRWmezprw7}v91
zc*<C?pRM6HxH=DzVG`(NdCu6&@`7<K%S(`^fLGvAiv=&i3JT7GYWIX!jQuPLuR+8c
z5b+j7yaN&MLBt2f^(+Y=K^s9gyaY8I4(x|acAN!Ic3c3BMXYB#02-KJ+W-+;0215J
zHUY$2&(Z+4WWh(!P{=0`@fk#X0TEw8#5czMEDOGaS6n*00-I?7aiju-CjjEDWqSph
zp84<+L_PqM7eKCII{@;@ewGO@!HuX7-x>SaKKx+Z&-URbqhDCP;{WC)pmO_P^AZjQ
z2F1V4iwhVS6#q1X)-EglZeHxfz@Yf6d9fA)gW}KT#i07)NAn_3<@3E6bP$%}x8_9w
z3=E22n-^I!FerX$UZlvtp!m6Y5vXYY)V#2WfkE+OGw2*F#ShI3-53}Y-#0G=wNT$R
zFBE5BP^^F3yZ}`DylGwlDq~+aF94OXubLN_F)%2;Y+e9z+KXn;GG)c*&GSnb7!;p1
z&yQtbP<+}v-<^R$@k#T10|o}g$IbIW6~&|G`OFLqiVvIT<uWiRK4_j7!N8z+zj+?0
zXusDyPoIH7@oqDyH>r51c^(S`gW~P_=DGO{42rj!=SDFwDBf(I3o`UZ^ISs)2F2^m
zbEOy<6t6YU1u4DSJO^axmF791I`?w(9A^dw#Y@d|K=sAN<~bnGTxgyHs;AC3&(3CG
zP(0T>JB)!r@oe*KkjgX7vq36PH_sMhU{E~OJPQ<tC!6bMr86)no@k!s&%mH~ym^)d
z1B2qR=2@UXJlZ^qn}I>`Nb}5c1_s5$%`-vu<Dur6AQv8No(b~yf##VKpt`7eCKCgL
z;=bk?ISdSndz)u~`bq`OGeFhj?&cY)3=E1pnn9DwO7ohhmoYFX&2OF#s#z8^Pp=0R
zV+)(78!<2_Eoz=F&A_0vxOqA=1B23%=4qe`YH9PdU<L-IWzEw-mB;etX`mu~Me{UJ
z<*~APDyRxt)jSns+Un-1Aj8%)Pc>j*P+HqO6;xcWYo5x$z@W6gc?ziR*w8#BkbyyI
zWAhY{VVjz#sMa$uC~a;AO(!dDX`T#n+t%jE@eB+~+nOhXOxxZ(S&xB1X-D&9F$M;u
zoz0W#7#NgxHBZW5U{KoKJSm8QL1|C(BpU_>rM=CQKvmzq=1Bq!3`+Z(CxWWb1I-hY
z85oofHc#|nU{E^LJP}ms9B!Tn^2CwmiM$N;3`$3vCzLZVC>?8_kjTKGbi8?jHv@yx
ziRKBQ3i)L71bGGqrBlrlK=tYA=Kf*^2BkC2{UHCIZSMDEU{E^O+z$%8^UeKI3=B#a
znnBaZN*9~^vKSbYE;aXo0`GEjpEU!6(v{{u6$S>StId7<3=B#)n|mu581|p_{Kcrw
znB3poX3W5#JfXP_v}JE%a~lf-gYu;2R?wEc$<3`13=GOsnp+(i7?h_rw`wskC{Jr{
z6=q;ip5EL7+OapIxh0)}L3w5~sAs7>tGNZV{cv`3iz)+y@|<SSIatbb_lJA`0yQJ%
zHG}$=%JZ8+eM{v9&7hO8lovKPD=;u9FKTY)Vqj2S+}u>mz@WUO8MG!^d1-T#8v}##
zvgRgz1_tHj%}t=)eJh%qm>C$9S2j21GB7BwYHo~VU{GG&+~~x>puDEJ5#+?R&7iKO
z^15bF*HU?XGpK8+yrI4s)VEaL*xUfxRk*3SL5YDud2=&pF|_iQrvD`j49Z)Z{>L*g
zC~s@}58BPRz3IOR1B3F8rvI`G49Yv3{<ASKDDP_e2MU_qP5(gl?rHi5vUhLOKOF`J
z<$X>6Bp4W!_c#3mx$r>K-y8-8<%3OsLm3#94>i^QwPj#XKHT&d6gEei{_-&}D0?>j
zDPv$z_HOzE%42(){&+JmDEl;ljt^1xZTbVU*RSah$X@@Z-ynMfntp?#B(Ui>C`y8w
zeuL}{Zu%|8z@Qw`^b53?GPLPe1_Og~Sktcn1_tHure78e49XErzv>kk7?dNMet{B{
zRr6Mm^P`%67BMg=M>qWhZKjNA0-c1V9NYBMkbyxtuIVQzMZ`D#1f__CrXQf-PHg%S
z&cL9Y)bzuFfk8RB=?5sdQ<{E&tWRzF4zfP2={v~!^rr8i4XGJT-$5xNv*|l1$0=tu
zeHUb4P|j}p2HHHD)ATKofk8R9=^H4x^P0YaQeuA7H;}grn!a%`Fen!`eFeF&sOf7o
z1A}sL(^t@T&yuFEpzWTeO<%<s7?jJJzA`W{D3>>ZmPRXAG<^wSU{J1X`eM((pj_4T
zMT3Dsxw`3#AVWQaa!u3cY6b@7+NRH-L|fPN8MMu`zUi|$1A}ry6X=j-<;JGZAbXpd
zJ{2-BC^t8K0@>Tr^vQ*RLAkZ*6DYXbnm&mzFetY-eFWuzj;4<(3=GPhO&@(37?iu3
zK7xX~yXm7M1A}r;(??DQ2IbzS51_pr%6&~Aq8J!tgPJ~o63x-34_XWis$cs5`u}2_
z|JVOFBj<j$51{73ewKva;EKE;kO_2H)r8-SObP4RF6e+J1pa{Q;RB$_i2ZB=Al`bG
z2hTvYzri0yriT4&2mXKuDn48Wi8%x^fp&!o_=B|iGlAwqKKx}&*w6Anhv|?0ya!5*
zZ2Q?Z=zt|A{9{zu&+@?!yc^?zAK2;(5Z(a@Zv%w40K{9*GQkftEus(rR$uTB+-$k9
z7u0O|@Sm}p<pa}tmJf_f6V|ghFoU*yOaQ54ad-wEi+BK1$Ckj%w4W`3h3Vh@{VWC$
z9|f>7fzA^<5C9sT`M}E5&+>r{M6iPh4v>+YObhn2EMNke#&+Qu*wzEjKy9xL;80iq
zv0ws-!`1+j-_KG265G#~0OGA@33vu_;{-0IewGQ`Ac6-(@PY_F5W&y1o@IgnQ^0x_
z1F*vtm_hy&U}ge^Au~9rK7c}%<pG$y0470~hpc5e2XaRP6Uglk1ep3+9tbk+XL%sR
z#Pnf5o5EwpU;O(X2s4GU)yp=`)L~#ym1&wO#=xK|-87Stfk9QOX+|~!gQ{fHj4%cU
zRf(n<&I}By;!QI^D#e;+h%hjyiZ)HJWnfShX_}tOz@RGJG~JhhK~<<}x)}q5s$kP}
zB?bmnfu`x)3=FFLP18yk7~~H(O^ah-P~~l!=FY&N%F{Fr)Np=Y-!x5<fkBn4X&MUy
zgDPj!)I0_TRgR{q;S3C_>`hZ07#LL9nx<+nFsQONO%-5ZP-SVFQpv!e5ZW{)nSnu-
zscDKI1A{7K(-d<C233ZpDe?>qD*v0NfVMXOYnlw&+Wfa^GH9RlpQgzU3=As2n?PgO
zD!-a0gLXFmY^tAB%fO)WqiIqa1B1%<rb+$`3@YE6K&Nr3d~KQpGVM##Bn}1!mCsER
z3mF(xJ~d5@W?)eH*fi0dfkEX%6KFM-%KN5?5)2F~@0viXu~gnRfmUOwylDch#!`9R
zG{K62LFHA`1XTtGRpzD%poxnYP5q#mgO^SH^$83N^52?3)u{aUCeUgu`5#T7YE=Gb
zQ$H&MgZ!_izB~p7`QJ@_;S3D&f13In7#QULHuY&RFv$OF>I02QbT##Y#w2>0dXpF!
z6#JTbLA$+gHT9Y?FsR&Y>IHe?T2n7O1B2?Grk(-@2GzYyJrN8Hs{5LH9O@YuRQET5
zj@nc`(9{Ep*n>^opol%x)D4Q*!%d(eY}F%8-Jpm)+SDz_z@U1pshf>~LG^f3S3U!S
z>WQYVNCpPglTBTqRC21R3zSMuH+6vwJJZxz!@!_=wy6_j*tw?800sut^G%(W3=FCl
znmUyj>KRloHg$rM$)%=_Vg?4)%S|283=FDQnmSw<7*ww|b%0E}*3==&z@U1)se^%m
zLG?ycdlmzO>dmJ15C#U-TTSiu3=FEbo7y!Q7*y{xwF@&asNQXAt7BkLz1P$RQhC3r
z4U~=_G_`?LK5S|OrKd+tZGsF8^{S7XTB{itRG&1prZ6z5K5c3RC8%djtyT;Ss?VER
zl^GaRUo^GyFfgdTY-%ZEU{HP4)B;M#ubW!j7#LLFG_~k6FsQz5YLQ@IP<_|b!o<L!
z`o5_dl#V|%HG{(WV^gyu1B2?Pre<vh2G!3^%_0m8YF156wG0eu`_H`;W>RBJUfcNF
zf`LJ8UE^;h1_rhDjlcOA7}Pd2{;FhPP}|t}E17{oZByefKL!T1&5ge-85q>IH2zX%
zU{KrI_zR?RTjS3v1_rh5jX%>E7}Rz&{`6;HP}|w~)0}}pZCB$@1qKGS-TT8|3o}h+
ztl!fJI!aP)Z{v?h1_rf#jX#_~?r8j>%fO&^pz((|1B2SZ#vcp}3~GlOzh^Qqs2y(n
z9>~C;cBJt;$l{}o-$521Yy8f`z@T=#@mm=KgW8G4Z%GUcY9|}Nc{4Dmoof7M!oZ+*
zx)D@=s-0>4#>&8;cDC_rE(3$wx%$ShVGImv=NrG;Gcc%KX#A?lz@T=q5wy2R?NZ~H
zItB){%Z*<$7#P&9G=eHnwX2O^K;F34_(h6=LG60u=XwSPwHu9}L1A*U@v{d5gW9de
z&w30DYPTCdi!v~%-D&((!@!_+xA9X71B2SV#!nz6_ZvTHGcc$<XsrJv$iSfXu<>IF
z1B2S5#*g6)3~G-XKiV)bs6A=?2nwmEjUPb{PH+4GI(p)L;|Eal;bh|nD+UI&ti}(Z
z#+qc~2X+PqWr@c3ASL3B??DY5vBvkHR+?zzdr%`pr12f7Wg*=7E{1_YS*Q_o^?<Tq
z<GXrLqf4Oi9Tx+GYDCj&(2*Cn8{dMe_`8j7K`pBLjc;uj7?dA2zLjHOQ08xZ%f!H-
z%-8q^bRGq7;~UVa7(9({bQu_wxf?-eWGQnsz6PDD!PyA9Y(SZ#@inN0z~1;;n}I=@
zt?@Oejm+Bks)B(*nWgbn45($q-1rLAXk%)81#%2y<10`@gQ4+dHUopw|Hha83=B&D
z8ebYSFev?Pd@0Gmp!BEl1*n_yyYWRD1B249#uuOgte=f9Oc)rHel)%SjgftCd|u7K
zp!BWrc>)82($~i4ZVU`cUmBn5Ffb^6ZhS7nz@YT0@mV#fyYaCRv{Xy!LnCOZmeTu1
z(0H~ATO(*VTj^cnGf=beZR68o1_l+*#;2e`xi^iVrCLg_8=q=2Fetrhd<yD4yl8v^
z8Y+9<_#}XVLFrlJ6VSzEPaB_r<eoG>2FX2cd<+^Jd(`;Yj)6hxVdG<U&=D{X8XpTX
zFeu$`d<5zr-D`XV>h#?0|NCB;Y5(8%B21hL``Hvk!IghN0;mGrAj;IwvO$b#Kg$Mj
z@HwdskS4|g2~cYy;6G>{2Fy(O530`}NHF!YJdk8s&+<SD)aWpf0V!*c29X>7f$C)k
zu!w^x$nXRirhb+LSr8!yBIH4Y0*Fuq5lT$^SrU|)Kr2TlNP}y9hyNfW4E}=}RSN&X
zBQ*m58UOL`Wr1)$KpgkrA4tK4f8a*Wfq$TNoej!N{cH^?AVL*HsDTJ|5TU`epRGZY
z>7W0876ln_dqzNp31lRM^8sY@ewGK)V5tir-g=e;U=Mu&H+U9+*#*)d4_(k?>Swv2
z#k8K~f;JQA46wh92K!kK=z#SG{027~H~a<d%oWgOI>u7JrV(@xfZFQD3;GNUYO5MA
zfJ&g1jTb;A(2B<M*$fP7%Nx&!FfgbsYdjCirb`>ot1>XCEonRtD*6^To&%LYiyF_x
zGcc$vY&_@1z@WCE5wy%oZGPi9c?Jfxd5!0|7#P&%Hl79L`8kbe;}{s!W;dSoWMEL6
zRo{5ln1MlUW+UhnD76`lXF*D*H=Y3*I;|0O4}jX##xtNIWJ)9G9ssq;jb}gw(WJ&R
z%nS@_6B|K;*lH6RPlqxvsP#9Vc3@yo>uWr%&A_16+jv@xfkCaO@ifRU-HoTR7#P&L
z8c%`z(%E>*j)6g~qp|*!1_Ogyd*dk~1_rgZ#*?4|u(k0dsNijBJQ>8mpw`@Y(wc!m
zt*P;(3Il^$W8+C)1_rf;#uFeH);FF=U|>+IYdqn@z@S#!c*2x{L9M3ogd78dT6N<I
z4h9Cbs>b7m3=C?OjiB*uwTed2__kVk<8d7Z2DP%r<Dm0P)k+(WGchozl{6m9VPH@z
zZafC^Oi|-8P!V0&cnsvig2rQ@f-}GIXf*?aT3+MPbOr{s+{U8;3=C>HjYmO!4VlKH
zpuUD|<55lq2DQw_BOrS-8jnOVFsP+A9&u%0Q1@;;qR+sf?$Zc57)0H-@d!&j1B1F>
zBj{uhb^pf05ey9K0ga$hZ}q@N(5Sb1P~%}S1_t%uM$n+QdPw7;Tm}a9(8fby3=HaF
zji5nq_3%c}ptpKN;~_x?2KC6sgH;R+>QRjclNcD(qZ<!;Gcc&fG#)f(U{H^3JgC6H
zpdQzFkb{9iJ-+ckAwxZbdP3s?kiChG2OJm})RP)PCxfUbHy#jSU{FtK++WMUpq|<Y
zIvGSgtr2uGh<bYCep3bp^^C^-G7JprnT`8d85q>F8ux*mmfg4y<g}c|eU1za>bZ^k
zv>6!G^BVVo49joaTgSklUeLHVoq<8UuyJny14F%fQR7}K1_t%w#=R;G4C*C~d-)j{
z)Jq%pR5LKBmo@H5V_;DI+6Wr$RxfYdW5d9p;nBE9je$YKy>X8K1A~TJ<L+t(1`XH7
z-RTSr8ZM2yL6=54H-b(E(Qs<qt;)cl;n=tvbcLitBk1fb4g1Dj$qWn{c8$CI7#K9_
zZ5wx4FfeG?H11MjV9>B`+{MGdpkdXxvz&oJ!?JN_5(9&VMdMD8QuD^0<_ruPW{o@L
z85lH78+URrFld-G?kHej&@gV?5y`-y-q*Opk%2+OuyKbL1A~S^;|@^<1`Ykj?R5+c
z8hVYOqq8)08$m~BY3MY94hGTCu5SdL45FdcxSgAUK|`}~TL}Y$hDPJI7zPFn^~P<k
z3=A4-joWk?7&KHHw}DJkX#|}NqM_Wl735!~#;t)23>u1!Tdf%wG!z=QDl;&szi8ab
z&A^~-(72_Tfk9ipaZ3~fgSKAd7H0+qZQaH#S_}-@I*nU|85p#+8#OoAF)(OrHEvF4
zV9?fV+#JBbpsmpe+B>DK-ndzjfk9iXaWf|agSP7YG)Y~isCv)F4eksK8eWYX3>g?S
z|22XR)6imQTqe!HpvBa<jFo{wi=`2Cs*)C4<I)HQ1}%=prH%{?T3n5wLzT368kdSP
zFlg~LE@fn3&=P1|lEuKFCDgbih=D;%q;ZKg1A~@W;}T^C1}%xkCEN@QT2hUROBfim
zWEvO8Gcah$)i*BoU|`TvXk2W_z@VknxLAsTK})%DF*5^$mP+HITm}X$)y732d(|2j
zIWaJ3sW&dtW?<0LXj}xcSF>?p9Rq`wRwHP6la_Yl!axQFEuF@NAbWKi7pgKaXz4XB
z6l7q~Y;Ift%IVgP3sM*uR8}{FhNYE{H`XsOXJF8*Z(N|jz@S;z2pX5xtZf91OKa9N
z&W~eY(5!Bp@5R8NS=Bh-n1MmFvT?pN1A}Ho<9rqd2F>!udHD<snq`fkacRxc#(9nm
z44Ng4^RyWlG>aSO2{SNg7B$YTW?;}PY@D0Qz@S;sI5&WSK{LN`t~CRLW?ti5VO0hO
z&D_Sh{0t15IgN8F7#K9O_XkMpf||D8jT@vG7&LquH!w3WX!tg+&t+iH@M~NTS|{b-
zxZZ(*K_j4Xy$%C|MquN5F$M;WpvLtK3=A5<jiCK#8X=AALKqk{LL1lFGB9X_HG)nV
z(+F=|C&<8{5zz?RmZlNexHgl4K_jYhZ4d*4Ms(v^P^yb*T&u#spb=Z&xE7Rm;u=BQ
z(=_56*Tga~Xe2bQabsZ6NNilA&%mIO)VK!Z!sNy^pp{%HjjOX57&KBFSA$GTYg`R7
zExmEIG6RD~M&oLbVVRAqKp8QsaaBA6gGP4aDp1<XX<P*|EVpr$I0J)5UgOGo1_q7%
z#`=|@98u7?GJt_Wqp)!$$h4wH&@p2g#f>XLB|u5ziV6k>^{<VfMSz-58bLReXg+HM
zoie8Rq7ih;nC7d-6>JO)nr|AH7cnqszH3|_!@!{Vp>er81B2$L#^pu~44PjWmxH48
zTjO$81_sR^jmruc7&L!1F5`}5V9@;2xXgutfpNOw2AlBd4hJe1PIq{~)xZCXye<>Z
z0UlNc2F3%dEes3{nx6Z48uXZ|S#3QoSurqZx?fUaV9<2C#KXX#>3Xr0fkD&dVk`rL
zrt?KN1_n*1i@FR9nvNGm7#K7iF4QnEXxd*$VPMd-+kd20k13h8K5DrQ1A}(-auo&!
z?U?1f3=G<_%PJTcwBtZa6Sd<(x2R|*EHh+a&`t#1p`x9%jD>+gI~jC?igpU<@H6ey
zrS=RA+G(H@Z?w~w@-r}KXDk7kkhvs*fk8WKi6;YtcJ>kz1_te%C2|Z5+PR?FBJI4z
zpdu!}esK%~gLc7UHwFgnLQu}sE?O+Zz@S~c7*uqWEGlAP&@NpR&A^~tw#bEnLA!jB
zE(3#h1t?2uS1zn)V9>5wn9abTUA-`bfkC@wp)CW0cI`qn1_tfAg?tPQ+Vu;{7#Or0
zKr0Qk8y9#mFlaY{j<L~h2AyJ~-Ljyboq<8Sb$$T@gLd0|P-)jbA5_?N%-3OH(C(Zs
z#=xN6H4kJ>H|X3N?H<svHQK%N>=+od`{seH>7NJk@r1eM3=G;6K_}H{Pnrv|W-@3V
zNPEg$kY}dOWn*B_o;D|+fkAuvoCpR6?HO|%7#Or?&d~rFJ!_621B3Q#(2+FSb7m(o
zFlf)6?aRQRJ#V%d1B3Q_&?P9^3uc2Hx^NcAp^IjLj95I&k%2*b$t;jVm(Bt?blEHh
z1_tfrGeP08VrD1<gZ9dqAZu35)MjANUJV+k(q1!@nSnuj?Tj1-2JLk-LKx~9wAX_s
zd$c!z=6bX@f~I=3H-Tn)v^P(WXJF9Y0@^&Ny>+@N1B3Rq=?V-C+9K1r7#Orgr-71M
z<1|nli%;`nV9=JB22vvln&r`!n#Rk(pmJ|&83TjL{i*Q`3@Q&mGdwB}r|L5>s5}DA
z@2ETmP4CpJJeiWoz@YMUN(cjk%Cjl93=AsIr>HS7sJxiM&%mJaa&kEXgPJC2UPn!1
zGN?7FKG~3gK}~J4Gy{X0>SQ(s1~rvQ`3wwd%9B7nQl&|trkCO*bp{4C1<-Vkn*78H
z1_m{`iHQshYO<iY95tDVpvIo`L{JmAUTPvY1B0661W=Pp0(1<#n)n3Jh=SMz83qP5
z(Fvdys7QYr1B04yKd7lF)DLR)3igAn7w7|Zsrmbo7#P&}`rH{9)Oh<q?N^>YPy?I0
zw}^p3jSIBLPmQzJhJitqyB9P_!QRWkz@Y8b0~!P3tM381ngz72PmQ@pk%2*tsRz`F
zX6y#Fc^SIB85mUmck41RsQv>T;ja3(3pCjCrwcSb^1I8HfkE|G7ig&EXBVhn{G$_O
z==aV*1_sq{ouKI0-YLPrpl#Gq&A^~-+yRPE6VL#WwrPhZ1B13%M?EO@nzxrSFlbw}
zgR-J!J1G5Ifd+-Nt=oAR7_@ELK#9(_4V1y`+RPakwC&rZ7#Or2T0so}$5v2+b!v5I
zV9<7M1!Yc`RuKjUZPyl%m2NE{S$EKBJK7#C8Vn5Do-Lr1akm+i`@NeZLDD{;VIFPY
zW{|XBvj78wwtrJ41A}%z6G%3&$%lbKJE#ei7lNBW2{5Dylovu9^B5Sk!y3aF7_`G1
ztr-}!BO0X{7_=j+85mS<gR-(AXaKQXdfx+GCN_ihYzlgy&R~EZ(=Yvf6ZDwa4ED1%
zI57R<-*-TdiA7;OOMnBDKtIa^Jy8EspQ&Iy%LD_agtaVopzh}b@G*@CY(c}w3v8MG
z@b8;o$dtlbpLq|IbuZtoWMI(DxSPnppnc`8Cj*0KI_R=K?W>@>`ZUw-f=bM5cXAmR
zG*j<@vgLKqCE}VXphLE_Z`|QyV9-py4Jtow-cDj*&`i4R&A_02>o%wnka!#9rQ5fe
z85lGZZh<oPom(Lc44Uz`KxOXT`db<d44QGbKw)<8Cdd)7H$jfLe-q@0n46$t`@u~q
z1_sS&&^9OShoD_fno&1EVJ39Lo`FF#@&>376T1O&M8x%S1_t%d*Ap2SG{dihTK^xf
zn=mkFhJo(jQ{Q(TRB44?12qkdu7xr%Xog&?2f0G}nkEB-X7DvoNXUQ=S=J1?3Mv(3
zuX->rXa-(2U|`Ue10Are8E_R867rzql{NjZfE=L!+Qp>lcSW6nL0j>P00V=j?`2Tk
zp>!GK2p`bl7~0C0L5}bSU9YFDav9VZ^11|C$6ekyXaB=#hD@uO>Mu5Sfx_lOV;3lR
z&o_2~ipFz|UD^x`+GiWPL>U;g&op*|%G%S7of!-a+NT;pc|`kUV<#x#oM`L>Re#4D
zJ3&>(u}09{McPLjJ5m`Kw2w4)fLgYP8#_QM4>fkEGB9W#Z0rC9`GH2zy$0I*>l@qC
z7#OtoHMR#cFlg^>YzNgsdm7t8LA$%L9i((uV;d+*?`&)XrRg1wZJ^+N+1O^rz@YxB
zu?^I@dff<G6s-QHv9*YSLH%uGYZL>6`n$$fCk6)f_l>Qf?$C$ER!~c?p%FB5tNy7G
zG;^!j)L7pV$iSf4(g>Qm)lzH(P2FnAH-e^awPYKc%NZE7q#HpKw_1{opov>8@kY?Z
zt(IsbXyR5&xUm`3To!C>Dq~>K;%@}yIxXHtP`1<JZfr7VV9?@hYyvf`*&Cbq7#Orz
z8yhPb7_^uh8`BsVv=|#3>w_5>H2*g?f)do<M$iPV=I_QvF$M<BpN)--3=Epz8yj*M
z7&N~&HbgKmXnt-4-DITsv9STv5qRI&Aj`m@`L?lvgMmTwHE0%B^W}d~^gsXa&%mJh
z^gpNp`}n^)1B3dP{~`<w8aMydGcah}`j^eXpmF<OI0Hky#+`r83=A4~|AAU}_x{N+
zFlgNW$Hl;)@!)S61B1rHzo5?8qrd(P3>uIBf?9V^{;D%DXgvKZ%)p@W><`Ge=YMh-
z7&Kn|iDY2Vc=-p^SbX&dw1wdHA5gpV%^y(1`0a0yns>iJ&EogJofsH2K7eL#HR?Zt
zW^Xk<{bpof(D?id)HMC_3)GwZ`U}(`{`O0gfkET@FOb`R{H$eQ(D(@&Zr1n(8g172
z{S(xS{PR<hfkET%Pf%a(-w#mB_5Y6q1_n)rAD~Rc_yZJDOg|(U7&MuGfI^hzdlmzO
zChPYw1_n*G`tJ@544UlUwHO#QIlhZBFlcgqt7Bl$<O1D*tI7Qh6g@oO>=+m{dB1_w
z@O=ZNBL1(S=AgjWGzJDu!LOj87W!(zz@RA%y1hYD<SVF15d8w`Cy0Fkl}qAZd>9xs
zCBB$4Flb7Ckz-)cl==dSGU?Ctg$xXuGM}Rv7&K)+gW9`tpFz!C`Olz;RRGP#YAS+m
zywz0t1oD&eCocvDO_fieY_0kU)E!d$#L2**ss0gUj>g9*1_n*dk4_8>np&Xi88o#)
zw=-z!fNr_f)CFB~tEmUNnn6<^G_tH|@Ie{mF2fI?2C&h4P^-lFJ*Ycn@*d<A)At4p
z44P)3ZNr-8?^zibG%enNdQz6}KuOW+9jG5=4Z7D>)8-whk!-vF!dycpbtcX%(0W(x
zOZPPQDL68L4#IOt2h{`y>7ZKTf+1+E&ImMCXUsHVJ<A7h%}`(h9;;I@1&=pg0E-!z
zg60z00!*3u*#gW!ggJ<?01=iT!is4<TYxoada=O-tZxDMV7(2}pt@#*2@_MndNv0e
zaMd*(EU#e4B(Rpn5agH*;A-guxQd$K1=8@K3RF26*nwSqp$eqP0W5t0%nksvH-Om*
zVD<tqy8z6d0A@FU*$rU!1PI#zWKIECqyWrb02WUGvp0a*0R|xJKRAFx;D8;|Kl!~Z
z_DoC*_Ol5Xf}NcJ*1o`=X~B9H0k9Sa2e7eVask*s2@W7b7C1051?**W1Z#8911U0a
z1d#%cAZY<TkQXO7FkNSLkZF3D&cL7|+w?G)fk8#C=^<#YQoiXS=oDs!ribDT3@VCE
z51APlRFs+?fMzw7n;wAXAyt|{OQcm)=ZjBsU^1@{Y`PCR=^~)%KIps<|E7Dz3=Fb<
zP4_?teE2rq10C?;({vAXCWd#@JxK-zS+AyhpbhArO?N?C#yy(uMlvwSx;Nc*W?+zY
zYq|^C<n7vY7qrRSrRgqc>$Y>#9nk3+PEB_}o4g&H?toM}G~EGh^0u#Ux+BWKAZyoj
zyN-cD*0$+(Is=2OP19}AzI*GY+n`<TR!z4-M}b&2-R5IpkhN&KRmQ*|Yu<D#j)6h`
zS<@|d1_tRrO`wI((!ZN-fsX9@)pQGV7{<@0n}rMv(m$GRf=>7P-gMKAfkFCP(@lK_
z2I;R&pr(QJm!|rgYzz$2pPO!glzwWu0XlE(W77>61_tR5O*cU2kG*fY0Xo*}UDFK)
z1_tT3P1my+7^L4cT@Pbmkbd2C9drQLtETIqBjsK;T?ZWn@}lV)=qQlqP1it2fjn!v
z208%jY11{(`C(6*t|>DxNI!16#?QbY{ix|`J!o0~!=|esr4O2}f_4VqZvx%eD}Ar&
zss;mt^xdYbpmXZ(G=XmHmA>6{C5eGS`c~5w&|zvfo34P4D!b8i1#}eM^`<MJL)@-4
zUCw7<P|#_*9KpaK|G(+7BLjo{nWoF2*11{JWnl&e72T#wH4F?YdQF$o>KPbR^qVgE
zGcc$aG+nY}U{En^x}?g$pkmZ?3DgNOZn{{(z@TE%bTNs6LB+J`B50!6tm&c&1A~fr
z(?vN31{I5@i|h;xDwa(bK(pOeO&4Mr7*wpAE`VmcZJI6^GBBvvHi2&HRk3RV-PEgM
z-*g^y8o5K$`Ebzr<&I6~LC29hHJ#UCU{G;xIuDu{cWFA$$iSfD+H?-oMRIF87sSAz
z;@$+hs#nFM>6{V+gNkR<Ic^396|W}H5WR|b6KIHD#it20M6cr8bQa`7zb4QKy^4R+
zS<rlZK+~Bb1_qVDrZX`N3@SlQXWSVW>Q#c9&KNN;sDw0~k!4^|32i#V#lWBv)^xgr
zfk7p_>2w?egGxlxX-@_QmB=R0RlO=vO{b+97*wL0PO~yFsKhj#0(m>O=@iJ&xTaGe
zZ^t)*Zt7J@XgUQ_nb>p+q%x`LBq$puH=T@RU{FbEI_UzML_I#!fk~G!S+402X#InH
z(;;34233WogXIhis)|jZ@n}`0rh}jfX5}W(B5YNaCeR{mRn;cYB5YN)rUOL`465o)
z2cj4lR5h9oI59A&YBn7JO&e=99RN*%Yd7r&O>FDz51;M8#L37Z*YpxJSR_9`V~zt;
zOTBK>evs*UP5VL9_4-Zw<rx@M4Vw0IFfgbZHthrTxs00j#V|0a8aM3&O|Y9Z?E_7)
zn>K;Qr&Z0G_SP~msG2wJ1r0h|H0=d-z$}|U!_%r(O?yF}vToW7nyt5K+5<AowrLM&
zw%)F356Ce4`ldagE}lcv9?)dCW78hcWVln)ZqQ;9=O)m=w5m(fZfgbxRoAB7$_xyu
zZcU&|9aP<$c7bNrJ(_kUFfgckHi0g6Q1xosWyrvw>fHpo)Irs!X%{mCgQ{;6=qxW)
zzowm_xqttro%Re2ssT+q)fpI61Doo1@-r}~1~u&f1$c1Nj(7$J)sUtgpamzPO*;%2
z7*xZWc7S5>M$--!1_m|LrtP5l4wI(spba0rP1`};_B&16LCZxun?RR2D0Vb~E^|<9
zZ`uZ0T+!A9T7IqA+O!R{o1&#@n+yYkVsq0r(30Dxrmgi^3=E2mO`x-?RaQ2=&tPCs
zY-rkQ1zP0W1R9uDtZUlJ%fO&m+q9*WfkCmRX-g~vgJN~l7FPxa#j2()pjE+@O<O?A
zV=J0AgO<mZH*E%)S=O{Uh=D<|v}rTQu#%?DN(>B&#Z8+*t7D6rHWf24C>Azt0?q9z
z7Bqowb5P800$t{ynAfxkv@AEbX%hnjgJMq8Mv$Abn>K<LEN3-s1g*8rYyxe$R?KMH
z2r@0bX#>b<X-%LLz7$iNKx5sCDNP$d3x|`NHh>IEYT5uYEU{@l$gqT_^??iwit$bB
zZ5Zkq6yuuKgF-L1X+0kUgJMk6I?%WWThltws>0}|b)c2IQBCU%7#I{Io7RCAEJrl0
z1BG6A)7m@+2F0+ZwV<`dp-pS;85k5pn%08$-UK(T<!4|}3~E|a!N8yx*aSMnTQQ(%
zjSmBZqJPsG&^l?qrZu2*VikRx)_|5>`!uaCVqj48Zdwi6+2Yl-+O^NYk!hcU6KKhk
zSo@@U1_p7_cF+=9aglb=5?XQL_DP`oL4?{tLoVWi?UVQ!7{mqIL4z*h{OuD#i|_f`
zCwee2i1W5j1l{Dp(>@V&*$8+0L>2}Hajy0WpldQX+b2XYFo<)sPXL_<&E7r%bU!Cs
z`vj0-tnK}vwRbG_?fsyuG??4_Z5SBDncDjm85qPF+xyuW7{nRcL92bl{<rsqGBAk!
zYwrWypYpf8PmzH^>`y!B(mk=??Y*F@U4FIq`Z6$x{cP_wU|<mY(cUY{z##U$y{C$S
zLF`+5Pdo#I*w^+RHwFf=FYP_L3=CqQ+j~IA=V`XrgVy(meQNIpU0(CCy&I(FLwmP2
z1B2N6cF_4sV(;3!K=-}8ZSMlz9`mNX%Z!0R>~(t==%SZb?V$dr*vt0L6b1&d7ww&(
zyKkPicN#J<h&^lX1i9jAdk5%-mnZF@l{{jP+dJ$S7{ng6cYr+cu)U)mbj{9#cF-Cg
zvHR_yJM_fvwYP(=f4SS<F2leecBj3ag@Hlrc6%G>E}2{HZJ--*Znn39l-y_sotrFn
zy}h-TfkEtAdusv%gV@#fRu={au`BJZ8Vn3#m)k+Bb;K^Uw-hljh@Ee50maDH_7>1_
z;oI6<)Io8-y&W`sBfg`(xqyK|d}n(z=t%Kh?aiPwxp%jNx|8C2+CewsO0cwp_LxdY
zw>O0`Fi6O>H`y^TNXWJ~sWUK0$h9{KFfd5Sw>N@rU{GjpOkrS<P;77XXJC*}YHu`W
zV31I52OWwmq0-*S#=sz<+TM`OP|qNt*52U5z#yUC-k{6CAfeITz{|iOq1pC7mw`b-
ztL;DN@&WC(|Hcdq5;|@FWf&MFblX6?NhS2!Kudll^xHtaMG1qpf1sNT4BP%`Ffd3M
zwfzHK2f^C*7j%;WTN~*7V+r=Qzn~iwINJVNGB8MRw*6IRV5pbiYWoYakh=}E<X3{H
z?N0&&g9LBeACQ~)+Wwd_Fi7yXftLJA2(*Eg{7MM6{mx@xkPvDEbr~gu+kS)W6>0ko
z3Ix%%-ynO%+J1rT6>s|m3IvI^U%m_s5|VAdK-W-6wfzF!++f`H3v_eC{&SvApe0Ys
z+CF(QFi0$K`((txAhDwD6Ud`0+dhE;YE|1u(ESsu+dhKsy;#%s5p=u5+P07S3=9(M
z+CGBrpIG1a5p+|<hBnYD9f^%?A3_)yBsR5u0L9Pdwhy2n*|I;}+X*x;w6*Ph9Rq{J
zwzl`_3=9(6+ujE<Fi7lZdvDFaAhEOUJ?MIeU2X6A7#JjWx4o-iV363;_AZ%$L1J&)
zJ5XHiYkLO@zWr_Qlo%K!4z#`FVPKFr*!H%RfkEO>+uJw>28qLMZ#@_oB#yMb1zqBC
zwCyeE5|3kTZ$X|pUf%{fkxAl28|a=piIZ(_K*4va?G4C{r`z6u($JYU(1}bEXWKyc
z+)12kdkqS{^KGv|adDyTHORD!ZLdM5U21z(z`!7Jx$RXn1B1kswpVTp3=&t{UV$#$
zxYqVcnt?&$dfO{j1_p^6Z7)HAc(bkkWfTL0#I3fMpisQs_7bG@PTNb6p?BL}vNJG9
z+-rLQGBly>1?YyS#ceN~85qPCwY>lp3Jcp_h%hjSEogfV%5wADK)Y7O=CwT!Vqg%P
z+x8q(Ld|J=uFk+9HoFaUII`HRwr4dA3}Q3eo`G((n$h;G-k*U%Y<k->Q0@wBU*gBW
zAU3V-nF<4g*wnUXpbNF8v^@otTa(+Kg6@Qx)b<oqv`uV#3MzLdv^|w)U=ZtXd&<ec
zAlBFR1a!=HZ`%`43D?v1#DjrBth?<AsQBq>dm_oeAlBLTgo%MctfTEQsQ74admIY7
zNvo~xu{{HWSZmv3ke^!G9)n7%=C(&5xu&*9nG6hKjct!W<y}J?=%i$^`nE@!3=Cp*
zZI3{=bk(*!1l`hA)AkVL!s@n%pxd&l+8%;#%c^X92y$UX+e45G%iA7+F6k<3dl1LK
zAXeJ;z#VjxR!Q3fkQ0mB9!N7Vh!wRxU}azsD{KQDl`K}!c0ZPZK`g)RzB>bhSYF$G
zP>G(~b|2)KoVNR*`@FK-KzmrlvfA!}LOrwX9_T)=j5g3o$zthkput<Qv^LP_typRs
zX!uqvrR}aK1A|y{8)yJmN-U}EF37aRw!5I9NoWHN;)=z$-3i@i;0EquE4YC>rf#4v
zxf`f=`oR^nn3(N>E0e%}whOM{KI{QkkfIG>asikOaAGRh&$0ltV0t~<guS3$-3@!e
zD|`w-V*A+=AiMwwZvzw9oCn|)OdI}y7AOTIgU1yPI5G9J9dKq^&vw9t=|Ml6gBw#n
zn}a)u@Bk5>OzYVkyg)Y~22_E~NSF?Cr9w4Cw--paH`9K$13ut&TNA)GB=~~dYajtq
z*#KD_Rq!9YOnU)X=7Ts`ek(}6zz@8}sv!xy*t{SK?E8cyknaN^Vh$j&{cHvho&tm?
z0OGA>Ndg)4ArV9x_%nUj&*H!eHozbNH0+T8T8hQCApq=f1%Hq#g+Gh}>scNIFeR*K
zxeyN$2?%6TSkJN`9yBb|5XjWe(hvk9f|=H{G=zZGQ5AsQ?2rsnYyc(?fES%@0E;((
z*#%%S0qo-d39u6!B$z;V8-_CVvn7Oqh;R@Q0U{znL=@A0wuET#(ys;o8JQf`vrPbL
zXWJkFcJ2kRi4%N5VbtIY9u*1jWdhw-xgnaVpJhV~h=^rc&$1y7?C%7y5&==L<^y1#
z6(oS1{2(6e*8mWE!WIyj02W^m0QPYL$e)Rz)HERpGTb7;^iO_0%LeedM+wPH4(nM8
zrh}AjNCsJ%0<todX~J3-@NiZ@8puQi@aT&`Iw&MRfCq96D!>UOARRPBl>s6$K|~ga
z$OaKPO#9gaa+yH4UM7IecmN*LX|MsAHz5t|Z9~vNO@Sdeqa+xDgaQn~-gJNr2^koI
z+!c_=)Xx%-4<ZUcL?MVM0ujYb>sbOym;&~*d`JW9dyocBWfwra^=t<~_OfjN*~PZO
z5bWy)kPu4&NQlJ&q^h57K?zeo+k#T2{cH=$nEcJ^GdrHRGcX8cbUe{xU=T|0cp}2U
zAe7btI+IQ)wc~Ll1A|aX$734?2BGAR$MOseLP;HunHd;_5<4DcFfa%ubUgB9U=WJ$
zcx24LAQac}NRoj;D7FK%Q(q{i12h^X6x{(j4_+v$;~_{%WCv&%N+_b^K@9_gP<VX@
zXpg>7SjPiL1_q(fjt6QC3_>9t54ac@gn~Qn=QA(}1$EpHWnd5r?6?ndML@@WWd;Tz
z|Bn0I3=Bek9rr*=d^_$1GB61FblfvzU=Z@|xF^HFAmr6?kBNan$g=~q8(+wy<8BZG
zgOGd2T`L9#A-9gZAX8jB>hJO}FbKJH+$m#V5OVIglfb|r<kSJ$jW6WbaR=mJhmJc^
z3=Bf{9d{TR7=-LPZf7wt2-$Yr_F-TUvgx?3%fKLH-Eo_jfkDWs<5n&MgOFv%El`kH
zblfsvU=T9zxFycOAY|5Y3*;Enj+-DQCLK4!85o3&J8puGXcIE(0G;nHWY}?2nt?&c
zpaV4iB&6SQqkw@yNUsAl{v@Q^al?&)K}e_L2FOtDjvFAAS{*mo85o2#JFXWoFbHXM
zfcD?>-Rc1CzZX*L0PVjQQth}d#=sz?)N!qzfkBv~<5~s-gD_{uwLk_2VXlsAwjfdN
zj%(@+48lAepgAjH-j1u)3=G129alkTSo3#W^<!WV7U;NY!N4Fa*l|^ffk9ZP<0|OX
zY2l75<qQnMA{|%a85o2`JFa*zFbIovTrpr^5Ek#a0y=eCqT>n!1B0++$K^~024Sg=
z%OMO5!qOd=?HCw@WjZdaGt@H(%XVBAU|<lI>$p_Gz#uH&aVe33L0F;Vk~af`uwut0
zV+ICcrH)Io3=G1`9hW#67=%?iE*3E`2&;BnjAmdER_nM3Iy+mv<09znY>f`k+74mO
zjtjL648mF+7eM~i?zjLtI$NjXf;9t!ux`f%6$S=jy^agK3=H+c`W@%X7#M^NI?jW9
zVc2orlYv3lsN=i|1B0+}$9Xvh24Rzq^Xv=^!loVP3K<xL%{tCSF)#?5cbs!(U=X(G
zIH$|NAZ*!jPLhE^*s9|k69a>=b;sFk1_oi9j<cZ*48pb@XF>k8>o^MvX8Vq_An&$y
zoB;*%{&P3WK&{x*9Y<{$7=+Js90eWgeYWE$D1gs(9I0er5I)~=B$<Ih_(I1KP*hy(
zI0CwV`clUcWd;V}%N<8}85o4GbQ}f+-qjA!ZJ5H>Iu3(WUhg<;#lRqZqvJ5h-kbZw
zZ<m2uv9~%7flR&KaR_AUosL633=G0|I}VvLFbLo4I0W+W{f<K*4?pMtU5+Nax#M6g
z1B39Ej)R~G-r8}{h=D<PTgO2e1_t5n9S7MM7=(9p94KI55Z>7V8gdfe)dAY~FTA@0
zwC`VdPsagi1_t519S2w#7=-uLcYsch7vA5oA9MowfsXwS3=F~tJN9cbFbE&&0G%E$
ze7IvDC|w@u*au2AM?3a`V((bTK2Yo(@7M>5y%Qb#K>j}2u@@A1r#ki~GBEI%cI*ZD
z<zdHO(6!E59eY7X!fSVcPmkB>03RN&+fffbJzlQ^e0sco#~#o@^9CJzWEdDk3_JF)
zFfa&YcI?h&U=aM)u{(l+LGWwGZYKr?!7m-4)8hp{ckC8pU=aM&v73Q`LGWY8t}F%y
z!4Dm~LKqkX-*@b?V_*<`*Re~3fkE(X$1V{D2EjKSyFe;mckIk$U=V!Ov9msifkE(P
z$4+Yo2B9S#-&GhG1YdOQ1X0gBcJeYX2tMoBQOdv|__Sk390P;kla3vp3=D#gJ9Zc`
zFbF>C*dfKhAo#Fj2QveM;De6sAnWgUYzLWnuVcG41B2k*j_qm;41#w$w(~PE2;T14
zR>8m^c&lSuA_Ifq&5msz^$ZMxH#)W%Ffa&S?*QE*DssMK8zTdQ;I)peAk(gPYz<{#
z5WLa>x<pj)a>rIp1_r@P9b1JN7z8hNY^h;j5WLW_C6$3e@O;M>e+CA@a~)eO85ji5
zc5G2*U=Tdhu?1xB>5k1+3=D#&IyQq;p6u8h$iN_YqGPi)Lp_7w@s7=^3=D$DIyMV3
zFbE#)*i_5FAb6x>6Uh3*9h-s~7z7V>Y_efs5Ioqi3FMgr9h*QZ_jhcpW?&H9*Re5;
zfkAL@$3~F1_jGKuWnd88-LVm*a#zPjko7w|KnKhV?&#P6^7i(Q4PFckg4;Sa7%?!2
z3vTV$AkDxaxTRwQI|GB@=8p9R3=D#s_W!+K#^lUaZ{GRAjDdm2tn-5c0|WP-&JSD+
z4E)}m?~552_`N#c$1pJPdv?BeV_@L-=zOowz`*a``CgKNf#0nYG@Zup+W9Vzfq~zp
z^IbRt1HW_UI|l{^ey7fN8Vn5lj-BrW7#R2+I^R|@F!0-Vg3jROx9fcC!@$6A+xgav
zfq~zqzVod-0|UQx=UWa227ar~H-!ug{Fa?>q8J$XEjr)0GBEI)cY+Qo;y3FA9aO|`
z+WCf&fq~zo6Le4!zj5d5Kn4bWqt4e>3=I5+ov)P`82Al3Uvo1s@auQJDraEe*Xw+h
z$iTp_+X*_Th+n7kl_>)Qzjo&<IR*xPt<L&a><kS2nw>8}_G)y3x_tcVoiAM&82HsX
zL0vw6)lSe}4t|x+mrM){0z#cHau^r{lsaF8GB5}zcfPP^U=UF01a<iYR6Ab?GcX9K
zb%M5Z2&i{HPhnsX(CB>b%fKL@+4<a@fk8m4^SKfOgMfDDa~=i;0iDig^`#690=k{g
z;ushN^g5rpGcX9~cRn*<U=T3qd?v}jAYj<}3}mlSC+HAf0pm{4K}7;4oljjE7z9i^
zpMq4Hbv~70U=T3xe9F$iAYjq?q=<n*z_RlR$V{uwC*BMU0@j_Nqj&{uI-h{7x9xnw
z#lRq7*ZCN90GWV&=i?{_1_6i8$4(3k0*;-JwHX)$oH`$iF)#=?cY^wQ0xq48(is>8
zTst2HFfa(Xbw09SU=VQce5Am@AmGvYh=YMaz_asVAp?VeSLeeR1_lA|&WCOc3<5r#
z4?!;U?R*IGi(ltMkYD^eAArIzpz}c}Lp_5)VCMr+AO>|l0NESd`9PF`K_H~_ejNjY
zKxpUv3<d^)u+IB|3=9I{o%byn7z83ZL2V*|$j<wqK#c0VSH{2~5Z!q%k%2)Vrt==i
zzp<V7Oc)ph;yUliF)#?kcisbqOhV_~0tN<w#7@wBoj_72XuhsqAh{DXVJDE%c~^>o
zK_IpBE-M3rKw9UWd<F)A^v*k=kP+^@0}5`D&O7=H3<9E^pcayVSmzy(q2isliy0UM
zBsy<{ye-*z8>CXI^R^xXgMf7BZ3zYj0h!L*j0_9{vYntMJOXl^x56111mrt!IWRB?
za42-%(qv!|P~3m;Wf_w(WAg3J%M1(*0(Uwufx_r+=cNb+27!B>mq5ne?*ugu1Riu=
zl4oELc-VP~n}I>#Q7346O5kxP=)8P^C!H5TA@#KLA}CCsb%I(60?#`yg5vT;=Y@I(
z27#CR!(W4I##f!7c7nj`&I`5-3<7UDFK93@2)ymQAjH5R@U9bdkGR15&hwx|{Gs!_
zKLdln$4=0Jy#k*)&#N&o2z>55FTlVc@TK!yB?E)N*Uodv3=9I_I?sVre(yX7im4x+
zplK?BpPis-DuG{}XF);ryYp-`1B1Yy`p&a13=9H)JI{hb^<U>%Q277vJj=?!Ajr@O
zx=&n?vGYtM1A`z_=NV@P20`Y|Gr9~6f-Ie9Bp4V3Sv${wRI+uR&Szi{WbZr;QpwSI
z8dQ66c7k@22y%6v7G+=%<nBBTD)4zaPh~SO2=aEG0u}gto%NtQW(D~>Pl2j0fzDH)
zB3G~zbjPfqP$%e)SwZ2>lYR^g0#iFrS}`#2-RL~2%D}*Pz4N3X0|Vc+&J#5Z3<7+e
zCqN05xAO$3JmBd(0Sb2R&J&=Z<mv=nH7mf`c^ni#9G%BO36#C_xEBM109)trdSeC#
z0oKmrvJ4FTZC#C^uwdx~-8d`2+<6R?g_$~!fdY!L^B5@d89G5X&hr27JSNV-!2hrF
z7y|<X|KHA|Squ#Pe>#tbFfj1{?mTMGz`*~j^Qa~R1OLy?qe2V}{69L6)G#pcfA2h!
z%D}+?trOI$;{V!t#Jrw?f&WV<=olsb&z(m=CFZBj!(|K%{2x0HConMZf9O2y#lXP-
zzVomN0|WoN&cmRB`fcZ7P(l5s^H3231OMyJL-7m@{I5C>c``8YvveLZVqoBB?>r>U
zz`)PZd5D>TfuFPUU^W8-KUe2LkPEpx4}x6C(|J&fp`L-CxAUMV0|P%_=K+vo_&X0|
zGBEH9bRGz1VBi<*JYdVfz%SH!K%IesU$_%=<1D{OCuky%U$hf+m=eEO=l)Oz27d8Q
z(3L#=5}o_C7#R2^JNJt)Fz`!tf*Mu)(w+Nq7#R3vIzih@_+>lyf$Ar@PSExeaen#E
zeIV-<I`@LCSM1yi3QMK_zwgVK=Kp<P&cwc#1=JDV&-S4l-18Ku0FQQTXa;xF9V$Ru
z%okLEySx>k{_O^c`~pxvwV&ld1!(VhCDWh$eIKeoGbnqywi+`q@b2!~D#F0PyQ^zU
z2?GP~&aN$y3=F(Gy0$nnFz{~g+M>h2z`Lz$i#P)V@7As@j0_CCTe>#qFfj0L?%E7e
zxv6Wj3j+i1#;(o!3=F&*x;9HOFz~ML+RVzpz`L$%Qvm}5@7k_SQ49>cYq~bMGBEJ2
z?%HI;z`(nzzH5^V0|W2Mu1z4NE4nu3GcfQj?*iRW&bzE@qdfxy@6s;N4duK`x;6?i
zFz_z!0^Lx~yQphJ1_J}{!Y<Ga<-7~JHrOyQ@XqhrpvJ(!JFja4KLZ2r+^+SN3=F(;
zy4EK%F!0XqTJOiez&opJy(I$!@64|CN(>CVGrH>6b1^XRPVZV*#K6Eit!o{~iBr4Q
zIWsWuPU%{w&A`ArxoaILWF~d3t!H51o!GS&WbcHowSf!_y!~CEO#{4rU2ByY7<hZT
zKzjywd%8g92=jJ#t%+w~;O**K<H^9l+t~#=Mwqvw3v{y$Z+jQ$f?D3TuGRIRplR(|
z9l^lB+tRh#fq{Xyxofp10|ReU*J_Zxja{p185npQx>ltzF!0uQtqNdZ;H~Rg1@c90
z*D8=NYPwc&GcfR0cdaaAVBoFlTA9eez+2e`x}TP}qHCoI0|Req*GgFi2EOR7m23<Q
zd@)_1>u&gByH-TjGcfSQb**q^VBm}I0$otcm(aCBl7WFQv1<h@0|Q@D*YbP@2EODj
z&;_-8DP7B*7#R3cyOwJ+Fz}^yEf-;6;7jjXR?EP^m(jH>gMooBvujxp0|Q@H*D@Oh
z2EOdBWoirzd^ugq_!$`Za=VsRGBEJvbuCR|VBpK|TI$14&%jsE1v)vHudr*WA_D_o
zQP)x~1_r+3t|cW5416VBOJW%q_)5E$xG^yBm31vKU|`@Y?^+_mz`$40wS=94fv>V_
zaUlZ(Usc!QXa)wp>aN8gztnUs)@NYgtL<70@=IOUVkQO#zWT03ISdSZ4PBruHGGX-
zi<}u4>iL?wK<oGUn!6T>GcfSAbS+|FVBl-*0$otc*VY9(GMKNu3$%!zucK?BCIbUs
zXV*d@1_r*at_4*L41C>P3z8Wa_<Fh)cr!5Y^>!^VW?<m!>slbqz`)nvwSa|zfp0?B
z{5%E*zKLD)BN!O?CUwnsWMJUC*)?B_fq`%Txt~>_zNb&u^eP4he&4R?$qWqqeqGc3
z7#R5dyFi!Q@dtEGS7u<~5A2%G%fP@N)HMy%f(-7O25LcubWH=bTtmC2Suim0hjmR;
zWMJSA@0!NRz`!5TH5Jr=jO>~UYPd%25C2^S>U&0afsQodkLj8!#lXNH+clMifq_4+
zYYM2z9N#r1f`NfQp=*j00|S3z*AyKF2L7b3DPjx^{K;KYm>3xNQ@SRDRHk-K1~snJ
zx<F?!@TYfy&SK!t=$Z^F-7~vD=Lz#?bxlfPVBpX00-YwzpVKu7<iy<iu1TQwa9-CW
zQ0boEH4)UPFX#f@jKg2pH4$WQQP)Im1_u7(u8E+Mu%v4Os3a`ynvlW3z+cuiA%KB_
zzq|{yB%Z&bYk~p;1Ak@L1dxZTy7~(k82GEZ`Xd<__-nfQK`rLmu6{iR2L8IPehCH!
z{`#(Z(2+*`4PAYp8lbVO4^#s*b@kaXFz`2b^?{1@maaZQ1_pk%uHIS(1|F%dUQmwr
z?CK3>U{F5Q)oaJVpnSTkSA&5;`Ak=@5Cenq*{+^C1_tHxT|HS049XX~Knv)VFL(8T
zHfCS#>H!^RbG-|6B7^eHu5QrDcglCVK#S>lzjuLlg(`pO>JDXKP+8U04cce8z6-Rt
zUVU9xH)ylu+O96pw#qeKT^S4v>Z`lD0vQ<8S9Nt+F)*mF>;f&cS6|W9#lyg$zPt-`
zKaTpcF3|lr>Px#o)4A$Px;l*+7}OVcbxJcZs4wd31aHz@*wvBGz@WaMs{^!Ia(-6_
z$liHf9a;<w>T|m~gcumq=XAA$wqDNeYENchP@mP+?#IBOKC`PGwDodES378R@bs>B
zP6h_`X<eYz`07);+QJza)TeZ{fp%U_?rPIuU{Igb1v;5QePUN@4FiMvgs#?9&?e3P
zu2x?L2DR+2R?u4G-mX@81_t$>u2yyi2KBD4mI4L__3o~g7zPIQ&Mwe8ef5s67F`Ag
z_4ck7P>{5BHG{TZwstkAF)*mNbTxyV*4)($GOVc!G~=t@*abTINxh+~sf2++y}qj{
zj)6hFt_yS<uDE(_SCat)gL+L@lN1AkdUaP5GXsNq)&9T#tC%9#>gRPI;$&dpn%fN;
zcj21TeK4AVfopa*=u&#FS=|Q>7#O%_b{~{tVBnh3eUO=ffoppAfm{X#u4&x|!WbC1
zrgnqwr01H_eL#bOfopR20YL@^u1VedYZw@~CU)=7U|`^y&<#3gk*mKO)I#9u>)x-;
zz`)hpy<d!hfvcy!dp{!s16Ox9Xa_1+SNFas1_rLq?tLB%3|t-E`wSTvxZ1n-Nir~S
zwRP`fVqoBE?FO|FxLUgR1~D*jHFxi|W?<lI>fWoyz`)hm4cdUp)zH1CoPmL>zI#ss
z0|QrG_a2a8wcUF_eyQo+12U|-8??ZOtE#(xcMbysS7rBZkY_5ocRMgJaFuuO)?{Gd
zD(l`Y#K6E++Pw?pnUd~ZsSFHU#ofF785p>Vx_5!>E$rT<%D})?(7lU~fq^T(duIg$
z16N-6&O`<VuH5dOo(v3JIo&&r85p>-yLZYkFmPpc?_^_O;L7aYQN+N&mC?PUK8AsT
zE4_P%D+2>pTK5ip1_rLw?i~^g3|uMQJ3t|m+`T=Ufq^Tj8??}eE3tdKJp%(*Licu1
zAjWrZ2L)nW_jU#b2CmrdZP^SA?EKx^Kz@nt-sZ@_z!lZKO^1PjE4+J~1Oo%NZTB`-
z1_o}s?yY$Y4BYnJTf^%a7`Pp}w>mN~a65Ky)n;JecIpO=yKp;qZ>eQq;CAWWlF7ip
z?b^L1h=GCIt$T|#0|U2v_ZAff25yh;Ej$bi+@9T=OBfiqy}CEYGB9v^cW-uMVBq%Y
z-fY0Y!0p?;S(<@?+pincG~)K}23_ID9nifgf`NfMuzM5ef<5k_?oA+jgS$70GB9w5
zbZ-Q?DYScI76Su!Sog*-1_ti%?u{T9Ms#n~VPN2n?A{3SOjP$qW(EfC=<W?5&%|_Z
zh+<&ij_uyy%D})K*A3d@${pXmL5_ieJE406Hv<EAV)y!T1_th=?)6Cw4BW}xpcYa+
zcS<*?iNu}Sy&mMJwC?o+3=G`q-RnTU&*)y4&A`B&*}X2Dfq^@#8`MzZ&hB2P&%nT)
z)4fiHfq^@>dmR@819x8c+A;<P?)>hxAhQd)*ZMOsa2Ixi+DqI;-JrEV+{N8%g&7#Q
zOS;#9Jh;1i4an&I=QyiD72=C-(1u&?m))QZx7@F~K^tzlUw1DRV_@KZ(+%2i%l)={
z2}sAg?j<1%3@pywOY9gJxZig#QD<P_vFKhRz`(#`*}b@mfq}=WdvOW_1CMq0Vt)n(
z9-HpP)(i|hw)?}mt3ef_UH4)k1_mDc?nR*T-l2O@76Sv1WA~yk1_mCd?nU+t3_Q-=
zi!>M*cwD*{flPJnURcS%z~k1vFo}VI$Gv-@7Xt&2NB2Tw1_mC_?uGIU3_M=l3pp7W
zc)Yt86frRH_;fFbVPN3#?Ox!*z`*0zy+D_Nfycjlfj9#LPe6V50tN;Kp1|(;AbW$l
z=Y#AG?w;?!z`zsI4QeIugm%vtVPN11>jqs|&lBD~FO7kLC!%{^00RS0WcNHv1_qv}
z?s>`#3_Q`@pv`|gG2L@PE{yG-o6Nw#6W2Z0kAZ<FzI(0(0|QS&_gqk`k)?Ys4+8^F
zVt4(Vas~#Tr0zK&rODlMd>9ybQo84uFfj0>cF&PzVBksXp2Nn#z%j3Tb{+!*mv;B;
za0Ui0t?t=Q3=F&;-LpZR1NUywNszp5-LpZR1J~|Z*$fQ4F5R<285nq-yFs@M@;Y_T
z(qdrXb?lxc%D}+u&^?QZfq~b)duDwu0|T#J_e_wXH@h!`bl7&!1etBq4LZ<@*SdQq
zsN-SP4caKkYuP;`kAZ>Lq8oHmJ+FE93{YF$tQ&MuJ+Eo^3`qtCUX$(_%nS^?#@*9F
zDvi3QM>8<+8g@^2V_@Jl=$>xKz`(2D4Z3rXSFd|IJE&Q&+YP#OkXNUBS{wrduXgt|
zZw3Zlt?p@N3=F)Q-P05p7<e_hr-548>fKXI85nrgx<OkAc~!fodNDBYs&r2UwX&7F
zr^+)h@G5mr<zZmpRqUQp&cMK{&^;xIfq_@Pdx|du1Fu{+=y)q$+3qQd3=F(7-BWlN
z>KS;YyFrIV@=A421~uI!yC;LXDiYn3tr!@1#k(h~GBEIpbx#I$YDBvyfjTuJ-IG9_
z8sTnG(~4K9dy+W=1Fv8=sAa_~&^?Klfq|F58+2wQFJJe>6b1%f-tLJYGkLlvS}-v1
za(7Pzby&E%C-N~cNbz!ZPpD>K;N|F^kjB8k%iaw-?TVMJdxFhAgIXq*g#9c6HQ>3<
z57pov=L678{eHFsAl`Zwfof1+Q=t}2ZUT`4wV<U3V1a}Nkidr;kU$NHDNqMu)`6HG
zYC+x82en|MFVup&uLr<l8z5o}AYv21CMnb~UD(fJP{;H~exE`e6Pv((wuCyc9)SkX
zbnFDs0crc$3L2Px$?prO19ffrdq7tqaPsxE>oPEK^7gcgGca)S^t3ZDFmQ7Bv}H0d
zaB}s4R-|!q_Ow|tFmQ78v?(z#aI*KbaWOD(vh}nUGca(n_O!+^FmST;w7N4ea5DF_
z8Za<$GWE1dF)(m4_OvoHFmN*Tv}7|daQyFS31ML1_}9~7%fP_#x4x%Eoq>VlPfv>w
z0|UqJp5|%>2994n&B+W596x)Sy%`ude)NE@Lg4t`1G)-<<694CnHtB}o~A+u297U1
zO;HRC9G`odoER85KJ_$dGca&`>}e8ZVBq-B(^$*E!12DPF`a>d<6Tc<Fara}+aAzO
z2pn&EKsO<9yzZ%Q6l7rFc-7NT#lXPvvZn!L?~9%WUj_z_=RKgS5ICOoG$=DLa6Ih+
zEn4Gv(*3`Tfq~<3H|V%Zjz``9JsB7{9(MmXVqoBS&<$F<#&N&<KL-N?$Gz@<MGOoa
zcf0?^Ffef3>Hg=&z`$|48?@Dl<5oB5xJr(j-T&&D7#KKibpOp|VBomk{WpSvf#X{D
zUyx_6cK-!==1TWp5e5d1%iVuKp1IWhCyjxD<6`%p00st*3*CQg7#KLtcmGjiVBk2{
z{YQX-f#YoV?`j4H)`sriDGUr8r@MdqF)(nP=>83gyLH{5<F+{0cmL*LVBp-){j0K`
zfq`>l_pf9I2F^|0pfzlqo4bFRGca&&>Hej_z`(h+`xhqz1LwBxpP*>o-u)94%{#h(
zdND9??(F_)%)r38s~dD&CFkyL&~cTVd%Az*FfefL?fwzUz`(h$`-d$91LywkA8HH?
zoCmsp2r@8m9_;>J#lXOMsQY^|Lp=lM;qLD~3=Et{y1$z+FmN92{w~YFz<I3uJILPS
z-QPg=p6LDtviD^7H%|rz&Qsl><0?5%cYgz^Jkt$2u9EX?H|V%Z&U4*gV;LAY&v$<X
zx$r{wS2G3%&Wqh&L4LW^{S{>9<?b&<3=EuCy1zs-Fw}Ei?f&Azz`%K}`wJ)oT<`uO
z#=yXNqx%aJ0|V#H?$5al44k*RKSwYyaNh3z?8Lypd8hlc4g&+{-R{pImG`<ogR;u~
z?oU|^44e<TKZP(ba6at*<iNnd`KTLo1{de!?oXl&44hB8Kh`oZa6aw+n8v`srPKW}
zfPsN)|GCIIP)$C+8+5fG*Mjbs^$ZML3%g%}+Q5stUj{QUa4qhBX~V$4wWRx{3IhYz
z((aeM3=CY$x?hwsFmNsJegSF=uIPT@!oa|_vik+7-L|Ux1*nC$y88vFg}0{rc@_f$
z*V_Hz(RHAjd|fwa4I9_`ZqOPwt_|JKL5=T?-Os8R7`QfdKTBa?;M&~%4CJ^i-OoT4
zZ|#1j&cML6t@|0MWxKumX)OZ-*N*O|ASdqZehO+)@9KVP%fP_3yBl=>0@t4Ir=koD
zTzk8pfIPFW8+88y*Z%G&p$rUM2kN_@fSSt(yPtp>qldbmh%+#79qxVta_W)p$C(Ta
zTt~YfgA6^^{n(0uf$MnpV`T;gt`pslxfvL^PIiOtU*I~`{V1M+f$MblBT#esO!p%r
z1_rLP-H)Uh7`V=LKLT|*&UZfqwbCziKLk~p7rQ}wjJPg!*FOX`(=T^F1bOC4_XCi(
zuXaC3VqoC9*8RYnfr0CK_X9Hq2Cm5N2l5OI9P-@{I2ahXcXZz`WMJUl-hCg`3f<NX
zx_^OtYd7fr1@0}~_XQakxHos-t72f_-qd|Bm4ShKWA{Bj1_tg8-Jqo&-0QpV$ulr;
zuj{^74>E0SH)ukG)2nATsAasS8#J%My}J7@s1>@Z8#JxKy|Vi*s2R7S`wpn#x4ipK
zIs*guvhF*eCgRfWJLU`w+)KJa_b+fS?grhzz`dv&G@rq}u=_TsMZKW=wmSm@_x$eL
zh71hc^SVJBlDX%0-v)JUx#x7>0=0f;ci#fFerI*xa$#WLp4oj%kAZ=EM)xgHJ9&CH
zXdMXmwC<ZZ3=G^;yKjP8)Kj`|f?Cv*yKm|;FmO-mz6o;S#O@n)3=G^8x^JX0FmU&G
z-vD{Lulokbg}vQ3K;G`@z5()eclY&ThI$6>uI}qG3=G_z-Pb|>?dZM^vbVkaI>@xP
zZqNb{?$+*Wpq6|~_qAXK2JYtWYoKsy>b?eQZ8vsb<7HsrZs@*R%D})~-+eWXfq}cO
z`>H1c19xrrRU-xl?wanapk{V;_f<9q2JWivEBOoz+?Cx|A{ZE?xGTD^I59AAmv>(Q
z^&rZ+uYh_GrQKH;_bq5(ViDNSQcwpzaC8s2=KQc5R1ZG@lNZ3`f!&}wdBbk-a<c^>
z4%>v?V6_6^s=Z)0sQLyo9p*EEcBt1g9q4D-&;UA6t&vHamBY2?x-kO-i_3oVt&L1_
zjP(sY=gS!wI23w7OFKBid(L|>FmOcloCnn^kv*WL9UM_Tprsug(LLu17#KKWdO%A%
zIAVLwfvSqQo^x6Z3>@)2=Rj3OLeJTH1_qAAp0k+@3>-;4XM-3RIFftLS~D<kr1YEx
zRc5I@XSo>|IMRB~lrS)Gq}TU=HWhJX^qg^JVBpB?0Ui6rk<|k__KPFC2XyQgM@|pu
z*e{OU9?-F09C<ybLA7^&&uLJ_Q_yo7RCyQnoT_19;3(=j1*)QodrpC>sFI#j77Pp=
zr9Gfq6*<a!PJ!$#?*ZLo!BNq3GLC_Pqq3*|q!$ANM^(>B69xv3>YkHw3=AAKJtsl6
zXl>64P(5GQa{^S)*Y})oVPN2B=sBUwz`)Vib3&YffupJC1TzBzM|02d90mrCmY(CG
z3=ABtJ;&`B7&zK`j)Pp--gBIffq|o==NKrMJA01BGca&;^&A6L-rYUNK)1(n^z<A9
zW%u5mW1I{O9DO}UK|#~sa}?yn2|Y(aN+<RlHDh4lnACF=q;hf(=vqaNDLqF(_59Qx
z(6L_}(|V48Vq|*H5gi5wju|~iBp4VtX7(ImWMJT!)pIzDfq`Ro&tXuE%;^Cwdf`y)
zIjjVVE~TEsprBFiIRt87sPr64U|`@-?KuRpSFHy$J;R~ib4ZGTfkUI`5UA0h*#nxM
z;n3<i2=cFX&p`(U1`eH`gP@e4+j9_<67+gNvojp}J)qec4uhTppq7_m&jCjU1`ea1
z10a>gJqLst>KQmpdO(9O9Hu?{L9GU}p8Y-y3>@Y?plwwg7Crlw7#KJ#d-j7|Xw|b1
z6f)L5`#>RM)3eW=fq}!eXP*HB1BYD?XwZejzGoi`0|SRc&)$3n1`fxby`W}|Q_o(I
zz0N&*LCqSMp1q*BbM4v7z`#(?;noAX<buP!XHOsl1BXWs=#mQ#&z?Ps3=AAzJ$pbg
z;@z_w6wW?9yFu+K-=5u|_LN`GZhZy@4*#Crpl}Z8*$oQkz@A;8lpoZy3lz@5J-e(J
z7&t<Dc7alUXwNQw1_q9>9?+l*$J`#!pbN+Tb2}SBm9Rk1CJqJ$PQjjyg$xXwLOmNJ
z85lT)dqATIoFY9NwHO#UMSDOKESzFJ8>$%?IK_K5q%kmXO7v_9U|`^s?Ac(&z`!Zh
zvq6=Cfm6B%G{M3t(*v4d;gs!JpTfYvDYrj-cO$40mhV|_!@$6)&;!~%#HrW=+C9Xn
z)U&RFfq_%GXI&Bl1E)&QI&TIBPSu`urVI?6YCY=|85lU#d)9F?FmP)0tSw<+;MD9{
z3u+f>^{jPcVBpm5S*y>$z^T)-R+52%Q@3X=s0pLjvj)^2)9+aWYQh-wtN}G)4C{N=
zfZ8xdJ!?R17~`JR^$ZN0COxY&7#KKBdqAf%ahmmjPG{mY?^zA<jYZFDP}9w_XBDXF
zX4SI_)MB*mS>?;Xz-iO73gklDo>idsm|f2*HU<Vx`<|8g3=EtOJu5+h=-9Io)W~w`
zSqW-nIrr4B1ljA-vjSwVYtM>w1_n;Io)w@_bnjUKYN~qltN<mtQ#~tq85r1kdq7t-
za%uJ~2Mx|?^ehL}`szKP)0w!`dO)W$ajEt!XJKIAQt4R+>VGTuEQ@4d;8N-V9nQq1
z*t1NJfq_e*XBlW1PrheaJxHls59l-`_T4>?*clkOWP6r^bjb891&yjn_bdes{7LmJ
z1?iCNSqd6Ol;{DCrErP&fW}g|#Cn#1+B~8?OF*M}B0Wp^85p>PdlpwSFmMU=EC!AH
z3HB@owW9=jKw~Lf{5_x>8oBs-77KvdMZ7(WKy446o<$&~+&zmxZ62<kMW7}ZXU`&#
zp&UJnKtqJ=Jqybi7`WJa7RE6!aIy9*bZ21TV(D23av^iiLeMZPQ_n&+1_mz1o(1^~
z3|tI73qY~`zh?m`w*U1k043eOJqv^w7&!m*%m*Dx%K5uzJ}5>0>Y4A)z`*&lXFe$H
z{^*&n%)r3;y=OkCgYd0q9w?Q4?U@(Dz`*&XXPzqq1Lx<Sd7wD_)H4qhg&%uBS2S{d
z=$Q*jW$$}HS2S|I>zNC(_ifKyO$G+eH$9*+6wcQ@a|#$3IA8V531wgq=X}{S2V~)k
zo;jeV`STvo;0fom{eSm2g2tCW_D(TnU|{{w3p(JM^?fhsl1A2dy`W1PS>N`8E@@<a
z(>vLbfr0gP?_@0o2G&=-ph*?hm%X4#71kHMp!2O+pZ9{!w`P6T3z}46ecB7^`LjOh
z1<k3jKJJ}Z!oa}#sCQy40|V>B-iaOz46F}&CmJ&_u->olohZw|z<RHDA{zq(>)qZ7
z`3wxKcX}s8Ffg#*?wtU#_g3!&ki9p1Cx|dGu-@ne9XP~#y|+J`fr0f}Z+|EQ1MAh^
zetQN6)+@dJ8Vn4qmwWpK85meE_4a|fXBT_>QWzLmFZA~LF)*;6@9nc<U|>Dh+o#IF
zz<Rc~zE6OGf%QypFG%U>-rh6@2G&!(y@3o2tS5VWtr-|tPxSVxF)*+m@9h<4U|>Dg
z+f&QHz<RW|2c+^yZ%+UN1MA`59!mxW)<eBLN(>CF2YY+C85md(^mdmrFtG0L?M`4|
zVBOc-?a9Evy0^F6h=GB1Pj9z00|V>s-tKy41_st$y<IsB46HkQyFwTkSa<Y-PAy{H
z-rEK8%(mVxAqEE4t-YY*u35MAc7p8P+}r8Tz`(kxx6^`wfpueVC&=Cny`3O?*Y|dS
z>|NIjy0DRTZEuGU0|V=--VO@}2DS;k9m)(0Y!iDs_!t=2CiS+1dZlcWd)reO7}%!t
zf_BWYP3>*BW?*2O*4wVmz`!=Ww_TKhfo(=_J0k-F+sxj!Tm}ZVS-owM3=C|ud)r(X
z7})0Ywiz%mu+8mllVxCFo7W2(tzetq+girJz_y^bHIadVZDB8HhJ|fWFX-%Rw#B`m
z-E?eAdRs*p>KWLU_JZzjWLwtT0y2AfFKAaC+lt;6kl8DHTMQW(*jDwnfXrUq+rr7f
zz_zBh8D#d_-e!=q*Y!3BFfg#K?`^hWU|`$O+pNjJz_zis8RYCuz0FJv3~ZZwn+g~h
z*tYb7Zroto+6$U@VcXUVns%vY+ujSBcVXMn+r-Aez_zou5u|iiZ(|e#1KaLi(2^6j
zJ-v<k3=C|0dmCjK7})mpHnK7>u<h?{$YWq&JJ1U{v4!nmZ-X-f1KXiq(7rpi!@Uh+
z3=C{Xdj8ilFt8o%`Jc|fz;>($bXp7B@t*${3=HgiJ^z&$7})opI|;538+*PNGcd3>
z^?Z+IU|?_V`R>lZz~0jH-H3sKy|w4N3<CpuThDh^1_t)_o^SaK4D1~}-y#?o*gJc^
zIWjP?clCgdEn)BO`6j}^z~0mIwVr{2y|?FU76Su&U(eSN1_t*2{o$v<72<@RuNn*t
z>=S#w3NbLSPwM$n&A`Aux#vqN0|Wb%o-aWR4D3^TzSuA@uutpxqRPO)KE3A)9|HsX
zjGoVB3=Hfudp^f8FtE?+0i9#QKD!5WkO}*o9?(f9>~niSN13qC>-ki~z`#Dg=Ti&=
z1N(xWPi_nh><fE7889%gFRJhPB*nnMzPRTT$Tv%RKu4OeFYWmVGIUwbM-K)D_T@bv
zLH=IR^HG+8fqiAqM|K7V_EkNg3ntiC_k4(FU|?U<^TCsWfqiYy2V({X_H{iU<QN#(
z*Y|wjU|?Y1(DNQ-{l=d6ps?K3^B!d8=AQSa3=HgBdg|XRFfg!h?Rn3|z`(w(=UpiS
z1N-)#cL@v(>^pkic{4Du@9cR8iXrQscghS5Dr<V)@i8!{@96=p&{W^u^A<D#xvS@`
zF9U=6&Yrgx3=HZ!dfqBAFsN_udCSYdpuVl=O(g?^`qm!Mx!USmdfo&uFsN_tc>|gv
z-PH4@9&{Az-kvw09H`T~w48xKeSgnu(AkLxdR~LfKGgFXG=q4v=d~pRgZho0*J=z5
z>eqW-3otOKU+Z~Q#lWC`wdYkT1B3dNo>%@14C<GAUV&6z>Ujk+`eM&3kb5umyac)8
ze9ueJtmL_#m!OH-vpp}Z>lql-&-A=hWnfT0-SZN3And807a&7V_PhX{9ebkZMGymn
z`thC@whRpF$9i6XjukrE^8z#rd!*+%Nc-WQ=b+i&TRqP~Uc24%9Ay2Sp67}T4C;4#
zo`Ys#@AW(bozZl^=UFTRgZhJ>XKoA(>JNLK>4PR*AN4$wU|>)`*z=5mfkFLA4`_Tt
z{b|orkP{#GJhfq9P=DU@6m$?RQxE7sZVl$1Clw3~8Z13e5*QdXSbLs$FfeGa^?>%~
zX|VS^k!E1f;OKe6#=xM#+4DG`fkA_-=W#d#g9dlcW6;T*JUx#!7#K8odmaliFo<jL
z^?;7&*5L1X1UmFcpa-;FMMH4^-}8-3fo%2LdT$mpFfeTI1)T@Nu%q{;D+2?=&R)=V
z42E63H>DUD7<TvGWM*Js*wcF>hk=1%Z|{vz1_p+Gy*F$b7#Q~V-cV&=U^vhVIxvjk
zVDI%x1_p*hz1Nc&7#I%sUiV>OU^voy-IRfW;b`x5IR*xXW4+fo7#J9i_g*VxU|={=
z-+L{Zfq~&<?=^P@28L6;*9;jL7*6+I1KE3~_ZkZW1H;+gtGNse4Ci{UhA}WOobSEr
zz`($8q4%l|0|Udw-m7Au1NnNdGJwLi_ev({6w=-+L7;Ond#~6qFfeHKUIDpKyY~t|
z0|SFj@8xO+1_s^U%c%?uOl-aNm;D$Rm{@u*TQD#%9__uX#K6FKy!SFU0|Vp9-b<wn
z42-9HLEAAH&-Q}0V=$iYy=2P3z<9A2wBC~Oa_=Q}1_s8fy%!4@7#OejUW{U3V7%E2
z+K$0^yZ5320|VpT-iuNU42<`CFS0N&Fh1<PkjKEl__+5%1Oo%()7}g9jtmTp&wDRu
zGcYi|?7bk$z`*#r7j$Ab<J(@)c_57Md(Ve6Ffe}XJ@3H4!1%fMycPok<JaEv!VC<I
z-+Ry1FfcIw>^+ypz`*#s_goMI1LNP`b2bbNjQ@MjsWLDyG4`J0V_;xn?mb(^z`*>t
z_iQ`^11n?iSuX|#R;J#wCiM&qtjxV<<rx@QS$fZMF)*;Q_JaEEtZcn!;usiM*?Z4`
zDsqnAGbRiStem}|YbRN`de4BWUhZDdaUiTby`bYjSb2L-yE8Db^7Wq9XJBCE?>#Na
zz`!cddzy)XfmN{g6sX1*>OBQ&=m__oa$;a$73n>t!%)w_D%yKWoPmK=toIZn0|Tpg
z?@3TgN22#+7y|>VWba7_1_oBC-jmu446M?<CnXpdSY>)of((`IJpocF*LwogjF9g=
zVave4s?d8voq>T>vG)Y1`J&W&yoP~+Rk`<gDgy(nO7C${n@F|yxH$s@t6J}I1qOzC
zR`p)c0!vnn-eaI<n`ZAZkhisZkAa$P+P%j>?H8TiV=@d3th&9&K&>{t-lIhf46ORS
zM?nodgWjWV3=FJ>y+`#J7+8&ZkBTucup0Ls0R^l{?~yD923FJFBOn)=^&YWfU|==x
zJ)+6Lz-rNZ1k}*kfBa@6=%kZRy`Y{c>*rq3fz+&DdO-(LvwrQ}UB$q_`mJ|2s1@|R
zcQ>f@^`mz;sGat+cQ?qRzj}9r8h^igcY##?=>;7~&HA@@mp20g>%ZPzphoBa-d&*9
z1jGLD+u#b3v3Dn^CTHs1399p%dv}6ra+cnm+6)YAti3x$7#P^tdUw<?FtD-r?nq@|
zVB_fB0cvt^_U^D`U|{3w-J!_9z{cIXgNuQIji+~eF#`h|Z}0YK1_n01-tC}f41e!-
zPy<4sce?}w1DjwkXgvU%Q17-(1_n0a`rd6I(?oi=ftqNdz1tKR7}&&mw{b8qu!;9>
z1(_z%yETS^flab^t1ANon^f;sJq89g>E5kk3=C{Cy<0$y4B6f-84L_;a=oC10BrKT
zTR^QLh2AZy3=C|Fy<2!07}%70H<vOnuqpR~76P!T^nw-wu&MUeZ`NgCU{mYe3^Gl<
zcQdG=r_sA9n}LB%vv*S{0|T2@?<P?5dQI;pO$G*bp59Hu3=Hhty&G#87}&XbK?i@Z
zbM|foH8MDQH`*~Uu(S7WRA*pdXY1W4$iTqP+6!7E$<ETd0o24`?%m+ez`)Mb3tA(|
z&e*%5UX6i)ouL=hhi94F3#umB{`ao0U|?YT*SkJ}fr0IB?|Kgg2DU%F>p^Y7-@WT4
z85r1p^{xjs?SA&I1GO4|^sWnIU|{>+yUvb*f$dxGIyD9cwy(YGK$Yy5-nAgZKKFvA
z{@FhDuJvMIVEfp+)`)?D?L+TcDNyLW?_JBxz`*vd7u1Dkd)vDP<n1@TYaAFD*k1Rp
z(PCg=d)2!}n1O-qW$)@*1_rhly{pq07}%couJ&hOV0+fP8WeX=dsizlFt9!8T@4EE
z$GxjS_CD$b_2Aha_JVrwY!7-@fmGh_U8T&xz;>^973h{cw!6J6K}zrRt^~DcZ}+YQ
z8G5UCB`A5_>|F^`dZTwG4+8_+_1+brIK0-oBA$VP?P@RRm}Ryry(>%^7}zfNu8?D3
zV7t@{S}MtQv3EHrWG?hB2ZhY}-sK>_oa+TGm1H~H3tB44cBXe(4FiKX+v(nApk#fj
zcbOjp1KY{oWgvS`?EiZo+(WGDTg1V@z*O0{u#ka)siJRTGy?-uc^{~2%v9F5(2#+F
zsk9H&HD)U5Tgbw|z*O9~AeVuGsi<#37y|=SVc!A=1_q{rK2X<~DZg)lC<6miUf%*n
z1_q|wzWG@U3`{wF^Me=|n6mpoJ!7V<zWGWF3{07Q^SK!qm@?}7<`pwAFs1i_y2eat
zee>KI7?@J~=7H=@>6<6Rz`&H$HxE?nZ10;}$iTq3qi=2u0|VpEKF}${jJx{gnlLah
z?(Ul_%fP_6rw??{Fyr1n&`HCL`}#mf4KwcVn**wJ4)o0dRXPXzK-Wz&9_pLJz`($G
zxUYV81_J}*k-pgh3=E9N`es`)Ffg9zo2|&ez<8=}HWvc}<C(r$Weg0A=lW*FGcYh-
z=$qxiz`%H^Z<Zkg1LKvxS&|G4jMw^RF)}bP-sqc|#lXOLt8Zo~0|VoozM1w642<{s
zW@<7pFh1y;397;#_06bdU|@XGHv?qtv%VSiAq)(RFZyPHl)mblp~1kw_@-}$AOi#A
zyFSn&O~wy>(~}q&7(ew*_hw*V{L(iaR3Crqn+|f}k3P^*#EifCrWG?VF#hSA7R$iE
z_^%IiQ5F+J-!y#&1}3IH&^=j9tbNm185o$0`at(&F&Fnu4QF6rF6o;Jy2pvRv~Q{w
z0|Rqe-&9cs2Ilg<DRm4C%oTl8(ij++EBinfWieOvO)+C&V6N^1jUzDE^notQVy^9*
zT)@D<T-P@_nt_42zHhP%0|RqI-(+0|2Ij`T$>IzQ%uRiuBXgLW`zEC`Ffh0DO$uOO
zU~cW3WXZt5+}1ZqnW3J6xxEi`W)5>lALz^+=FUFQNyW@veG|PH7?`{JCK@p?F!%I<
z&dg!%?VHHVz`)$s2O39U?(YMQBQQ_s1C1jvPwWGYBQQ_un;^u%z&yFHzlwo@c}ib@
zG6Mti)IQMB#mv+C`b`-an5XykD=;uH&*<ytWMGhEp4rz|$iTontFJGLfq{8;U!M~L
z1M{3d&_Tw`bLZ#2Y-Eb6U(wf{$-uz8ystZmfq{8hU$->_1M||pZWRUw<|TdI{0t1t
zi~G7N7#Nrr^>rmMFfcFd>+)n^U|!JIWx~L~Jio6?mVtqJUSAg*0|Ud>zRr9G2Ijwg
zo#6}&EN*?B_6!Ux?tPsa3=AwDeVu{~3@n~~paY9py!txQ7#LW*>-#za85mf6`Z}x`
z7+8G!I@A~#Sp51r1Q-}t{QE#lCs_je+EW=ASOWXnK`Mj#+HDvZSc3aNN3gPl^tJOd
zFtCL7wN)@Mu!Qx2j$ma8?*kpd$`a8BIv$55vad~%fq^Be57fP9iS7d}Mqr8QYmH@K
zV2SOkZ*^l}V2SH%)n{N}iSKKbU|?WL=xb$UU|>n?1Fc42N$P6>c_z89#gT!5C8e)L
zi-Cb9wXa2lfq^Bhuep|ifhD~Uw1Sc)qYu=fXUXhqwqjsl$?9uXWnf^*?rR2lJEyOy
zih+S8x34Lgfq^Bj4|D`8dwpM%uqgurOMYLI90LPOK_BS!W0u1G;jh8fdr@CwGy?-m
zabF|IjU|1czC255Un9tkWqqL2S6RyY8nPG|SStD&f*BZCD*GBhp;*<|pu)hwQr*`8
z3dNe<|CJ03EVaG=lNcCS>U#fsGcd5!_x?9wU|?zJ1>K&>(%1{SJ(H!W_g^6c150x+
zXgLB)OMNfsHfxsF-hYM+3@mNEptDz5+I#=8Gcd4p^!^1Y?d<&<!@$7O)%(|zfq|vF
z_b<rMp5DK*3=Ay2y?@yl7+Csx|Ku|;u=Mx-iC|!0nb7;kiGhJ-V(%YNC{F7A0}92-
zy?+=O7+9wC{s#GFYVYq*1_qXCz4gBx7#LWl_x=VcozeSSl!1X|W-sU#O_o``pp#fx
zX7~OIXJBBs-1`gEw5;s~9mdL9)B6k59INgHUH`>e)%!Dvfq}KM_a~?wRnhws)c7s$
z{VB)5z*^S(laqmgwY2vKs1;b!`y-lxfwj2zhYJG(Yf<lydR+zv*1}%U^_dLppiT(`
zYe6sQ7ERXt-tQR<46J#*--8(#SaW;7gW9V(z28B@ZP~rw`572kvwFXkGcd4b_I?93
z(=&R%ff}Ldz26KN7+BMKzkyoRslDG=85meodcT5(4wHMoMlvw4CiQ-GWnf@U?ER_*
zYIi2|e&uCgV2$tn0&-$p?-x*0I=1%<sNERT`$ds~fi=4K3p)b?YgF&&JO&2V$llK&
zB@w-!Z5S9>!+Sy3X0nF$eg@eT+WRS!fq^xo_Y-JjEw~pntic-83tD-=8rb_0)a(rC
z{RkTL^Y8uW25Qjz^?n2ef^Y9fQ3eK9pWY9kAw=)q4~Yy6tX{nzKrZ#{{Qzpvd-Q$)
zIn=%PJ;)Vqz3+n<7+76<-<vTou)6euj%a0d?tRa|z`*L%`wr9wcI<rza)m?hJ5bBk
zzV{udwQbi68mnNn?R^`|z@Wxz)B6?_vDUqBl^GaVt$IP*NLej=-{i7#M=^%5f;xjt
zEB5nzXk?OMtzX{vwvK^;X<6S}P|duw?=7efU()y1k%56}ao<}V1_q`@eQzZg7?>9J
zy#>|w3;Ny^F)%RA?|T!&z`!)G?~Mxs1Jm3-&^2OAbNb$hf>s;!y{=_oV4B_cI*oyW
zfx8d1AC+lVA80=+15Y1lKPuDAKG1$t2A2B1SD@N{M&Bz?FPN|I709&deXn#uJGuH^
zi7_xRP3wEb2-^PF_Y&m7sePc88w`SdFKrnZn5Oi-RA*pd5bAp=z`(#Xxeqk3!64iR
zx?7BCQs0XJ1_lO^z86*u3``UIUZ^lIFo^cO;ALQ7n$Y*WoB?zQQ2p}+1_q}7zUN*H
z3=HCZ&&?PZnELvjD=;uHNc4e5Hkf+*o`J>(B>SF${M*y_3^YC<)%Ofkmv;Ao_M<XL
z_dNrJOjqC20tN;KnZBo>7E@;*Xg?~0Y#(SpDpN<_Q)vbU2D!ectPBiH?R}sN#~9@M
zo`BXHGqv@B1~?cL`alC5Os#!Sq(G<Q^*v!`U|?$LdkpIQEA>4FMND%aXn=!3x$iM3
zVw(CuXAd!`^gRMaVPoH;bOr_n-o8iv3=B*SeUHpR>81~~AC;-T?-3^h0|Q&%Lr`ef
z^*xMZ0F4wr^iW`6V5;qV2pV+Y=zA#5z`#_~_mCB|?xycS9s>hY^?sM{jZDo<^(*@>
zhA=QNt?Ii73is807u6UTnAY@N1cm$Bz6;e13{30#E`Y`q*7sci4JmBsyI{`1z_hXN
z0?3X{eHS<x7??Kqod+eJEq&)ffw{HsJg9NEt?xXjakstiJjnhXedj?zw6pIV$o^e@
z=fW8nn0D9qodc!FJ$<10c&5F5p!s;FeSPN`7#NuL_koUDU^>tTI%<LGVBcAL1_q`>
zeP=Zp7?=+CofT$aU^>!w29zR?_MJ&*U|>4dcP5yDf$4bP85;%$rW1W<R2dkUPWGJv
z4HTT}J6+Dez;wFrbUXtC)0w{09t;djXZz|;8#6F4o$EU-%fP^NzV9@sg?yp!6eu(=
z_MM7lU|_n`2Rh@E>2lvGBL)VhD}ARxE!C@ir`Q=7n6CAm1gX5<cM@dijlPqf3=B*+
z`%Z$)yw!ISWajNY(5yVuoxT$wm3RA2fK=Y=JK@E^z;wUwgro@r1Ji@P6Y>lUOb`1`
zfWq=o-*HeQZ@Qs_d>rC>lzOJeeaGV%7?_^)fi_h#J?%RVO4HB!jw>=SFg@=(4r*k-
z=sQ-%z`*pf?^q%O1JkR%V?GQFOt1TnSu!v%z3Drq%)r3(w(l4yqrB@oTEW1;^uF(C
z5(5L%hrXjAl^^?#f}-|QALx=Urq6vxc^DX&zVv}ks$i=B+IJ*{fr05;-w{wU{N8s2
zl>2`49Z_LmVEWm21Qf=<`VLnzFfje@107Yt^rsJWR0Y%DKG3W^)4#sMpp^B$@30^P
z12aS4p=t&OX2!llsSFIvOnry^85o$E`woFxi!6PIlo=S9S^Ez0F)%Q*^&PBaU|?pi
z?>h);rE>Hg1T`!<`#^`IGIRAE1U1aK`woH{W;}fdKutm3z5}2p=*PYTpeEesz5})l
z49s8pKpQ8RzxEvvW?*3c)^~t`fr0sZ-+oYI??>PMKn4cppMCqS7#Ns;_3Z~)|GRHL
z7Xt(HpFYr$sLW6L>OqtD%#Zr^xic^@KkVD5&%nU^pl_c90|WE@zI`Cm?)B}>U|?Xr
z+qV~F+MT|=HVh2RxBK?0GB7aT>e~zQ%*{T~jtS-)eV~IXn6LNk0U36!Z;t^31M}6s
zJ<<#e%vbvMure?(U+&wT$H2gRsc$!^{eH1;H|PQa<_mqGu@UC;eY*u17?{uX?E*DK
z&-U#~WME)E)3?iqfr0sS-!4$o_f#KfY=rq_-!3)=2Idoeppg;g<9$2B7#Nt3^?}Yr
zWj@-s6Vw?v(zg>7B!~NUfMVoO-;NXp2Ihl(JA4@!m=E;r02#KwZ--nx0|WEEz8#zl
z49t7`wihulFz@Nx4r)j5?%NJ(NAK#}4l-?L-*%8`JNmYPx)$5}wt=EzTOVj-gn4V<
zHc$X>>D#8nz`(q@ZyP9pH}!!=MwmDDfksA{H}q|FV_;xj-?!C}fq{8l-&RQm2IjSW
zTNxQ77?{`ef%Zr+ukPCd3gA_JptC8MSN8w?-^jH8@Bbzyc7gRQ7r<Lo6`GkQ>}N69
z1U}j6Kr`s*uNDx|%Cw*DKpWG)`t>Xh^`J#c2J=8<0GKQQlM}$?1~7R6Onv~90`oyC
z4d#Q+adK#9>SuB201=%aq6<WHgNPoc{VWc>OiT{@*%an8{o`ND0@n5bY{UUDxd2Qy
zfXM_f=>R4bz@$Mv$byDm(7|4PAfg{cOaKuRLBu2wF&RWm0TEL{XJSoby0D(50ld&k
z!4KrhhC0x4tA^>|CD0Q<%bELG9A<#rHxoq60ui%8#2k=w=Q3$*sqg6r-QUL0+Yh?G
zjiIl9C#a_E?+4xA#xS8DbblMe#D38IZ48t8cQ`UIFih?T-QUJArGE!#oO){i4p5VD
zT0dwL4a4;Q?O_ZI3^V$-gGRJx_JcOjFwE))4Vp2`?%xg?bDz_{EsueLVQ&AnNCpOm
zdG-C<To@P_=J#*YXJBAh&<{GigkfR-HqbEnqW-O*5%tCWTR}~UCH-4LDwp<y#?Ba)
z^@GOF7?$^MsbgSZSkVs}J7ZYc4@w{mtNKBkXc$)aZvizW*7R=?WME)e+rJq!Ounuk
zba)BF`u@#+3=9k#`s+7?D%Fksn-v)t7&i59=3!u9*xbJf)Rx%NzbS!%fkCf-6KMLW
zu749~_N%sklLP|;drki)Mg|7<>i&(H3=Hg5{h(7z*em-t+A=V(SM-BUEnzS3-^kCv
zz+TqBp^|}ty|f>6Y6*KuKj_pF_Tv5xCJYShMg1G<K@((!{h(7z*bDmCgQgJk``3eJ
z-SYa^yD%`Y=k~AHWnf^>>0d9(z`&l}585`vp4GoDje&tZvwvM60|R?T|2iuM2KMy+
zb;=A3>}mb$co-PiQ~TF~CdN|wLCap)ll#|#<|C8(L4#)OiT!Iq^N|VtYuP~4jPd<z
z3K$sJ<NDV`GBB{m_Jh{Fu*dX+mc6h?_k)(but)W;VParlkL+I!+5r{OzZx`F7~a1c
zG*%eazZx_h8QQ;EfPsNMq#v~Gg*~_*w7-}=s2{Yym_4w67087F{i{?M7})*$SAiC)
z`1P+WXQ*dj_w5I5FlP7Z2W>EB_wHY5&cML#)xQ!n%jem@l9Pdf-J^d6C}iCGSAass
ztsk_%nBBD>w7;0$rGJGq0|UErKWNa5-Kih6znI;ze|Z!G1G_{2a%TnxcKiP2pfI%S
zUk-{p+y3RCxU=bBmd(IW&u-bjES!OXwXS~|s7I#JzYH`Bqu;*_l)4T2m)0{dFc|hP
z&0t_)FzR0lnuRg$UkaLqG3j5b!N9;^+P@T(yv+KSfaZzJ`<Em!Ffds3FY#tzV6g08
z0-7hX>R$rNRM!1VxEUB2Z2A|MGB7aM_Adsdu6n!v#h{j|eg9$;1_lO){>AbP3=EF_
zi$Mv|see%g0|SF||Dr?&1_qb@MIe=~{fmql7#Q687s)a(Fu3<G0u4BL^e+UpR6Y9_
z#xO82c=a!IV_;zL?guS<Vesi+2x_VN_AdlA1O56z%U&4#`xitpFfatv_k*?&F$DH6
z0Oh}+{sl4&3=F~j3qXd3^n)%9V+ie^56Y@x{qvm|7#PC)LHC9+MD)*>U|?W~?4J*6
z%18Cj%VJ<)i0+>k%)r19(?1UsK(YPvKs}SV{&{>13=Hx8pdCaE3H@_Z7#J85`$0R1
z7?S$yL0gCzlKVkhh!|4(LCaqlQu{$Wh#1oP=YYa8y?+iUEHnD&fV`dAKL_NQto}Km
z5+b{Qc0L0GLr(u}kPCDBXM;+Jy#CpG3=9nU{j)(XEa;!j#K6E%*gp$2)mPL%3sgWA
z_k(s2F_iSrst3h(Y5y#c(z1Tg7#~A<|4fi)D*9)FJX6^}6Xcny{+S@pRQJyWd8Vd+
z2B?In?Vka1VO{?WkPGYkXMkMT&_4qdhK>C*KrU?RpAKs6H}_AEU|?Wq>7NcN7+d?N
zgOW~L|8zl6!f5ZG21+{}{h*u17&`l>c`z_AboEa&U|?YA-hc4tTqakwezt`9pd%R<
zfR1Eb$n<ajdKQBjpdw#k5r`B3vkex3ihqH6aPjZ32)w!G1Eewt0P)tdd;ss1NdW74
z0In<w7J*e?096+2SsK758~`oqUC%ZF#9`Y2lG)F)0Hkg`+X9d#whfDz{^_r0QJ4X;
zZ$UEHgauw;`x0!xya$krJT8Eb;yeIx!v>JpewGCg-UJY@pXI?K(2dB8LBtXeu@pos
z0};zX#0n6x5=5*55vxJO8W6D-M63f5>zUTGJlMcwu%G3@MzGxq8^IN@A80-ChmD}%
zG4Nw@=x1@*1giQrGp%QF*aAA$;(#wmZowAN?Is(*hif`)1*zBuBDRBw9Ux*Sh}Z?v
zwHsuj!A2&9wJhN9PS^-Kdh&uVlfinHgx#R}TVM~<einhfOn?6G6WGYaCa|6@U?b?9
dP=$K%mC2Bpxd7Vew4X(w8SL5x8<~FD0|5Ix1DgN<
diff --git a/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/cfr_income_national_summary.db b/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/cfr_income_national_summary.db
index 6addce62c01f6d2559a9a2cda2e6d20c54447b59..a4d38f1a4f33f6dcc6d2d570bf8621d859f4a3ca 100644
GIT binary patch
delta 44
scmZo@;A?2$n;<Rtl!1Z4f&mT~ohRxTGd^uhXiZ>jO<>xZz`URy0N#EI^#A|>
delta 44
scmZo@;A?2$n;<Q?l7WH2f&mT~r6=kbGp=k*XiZ>jO<>xZz`URy0MH5wRR910
diff --git a/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/cfr_revenue_reserve_la_regional_national_data.db b/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/cfr_revenue_reserve_la_regional_national_data.db
index 86e4bb347fccf46b0a9270eb565bc62f7947bbfb..39d740c95d30c6d9d88eb256f58e9e1aec9089aa 100644
GIT binary patch
delta 107
zcmZo@NNQ+EnjkIsl!1Y<g8>d0ohRxTGd^uhXiZ>jO<-zGU~WxdX-!~lO<-$HU~f&}
zXiea3P2g%x;BHOeX-(j5P2g)y;BQS3XiX4oO%Q5L5N=HnX-yDqO%Q8M5Z{_0v7jCR
DM%W+S
delta 107
zcmZo@NNQ+EnjkH>l7WG-g8>d0r6=kbGp=k*XiZ>jO<-zGU~WxdX-!~lO<-$HU~f&}
zXiea3P2g%x;BHOeX-(j5P2g)y;BQS3XiX4oO%Q5L5N=HnX-yDqO%Q8M5Z{_0v7jCR
D5d<GS
diff --git a/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/cfr_revenue_reserves_national_rounded_data.db b/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/cfr_revenue_reserves_national_rounded_data.db
index 8ff5b8304650dc242439b59bcaa85752ee838684..73f2007b73816be40adf8329dd699572732e7414 100644
GIT binary patch
delta 35
jcmZoTz}Rqrae}nqQw9bGHU>Cgbe^bV%=mO;!h(1JlmG}+
delta 35
jcmZoTz}Rqrae}nqN(Kf7HU>Cgl%A+#%(!x6!h(1Ji!2AU
diff --git a/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/headline_key_figures.db b/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/headline_key_figures.db
index 320ad3e621648f7d1280c7bcfc36f738b1deebc3..6b5300aa7ce23ef4ed0eb8ceaae166d9e301946a 100644
GIT binary patch
delta 33
hcmZp0XmFSyE%=myfq{tu4j7#$>KHRV-I%aI9sqD>2Mz!L
delta 33
hcmZp0XmFSyEx3|_fq{tu4j82;>KHSw+?cRH9sp;P25tZV
diff --git a/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/s251_childrens_young_peoples_services_la_regional_national.db b/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/s251_childrens_young_peoples_services_la_regional_national.db
index 9237dd9f835178017225ef0c5c6a82e87151fa38..ab0438d99f99d727c0a96bdb886d0e43933de663 100644
GIT binary patch
delta 18039
zcmZp8u!RkTCrArEWnkdB%m4?B&J%Tv8J})USjEr8`g}8wzzKe>4NX7e7#JAVHk}D#
zU|{HMn!&=rz_6zAF&_g1!^*~WdJGH<tA0c?Ffgp%{7;@uU^~kPP9}k7wg>HO4;b6o
z9x%1DJz#EUd%)7p_JFmW?Ezam+XMFPY!5j8@h@h%08-AuB(R+=z~LAFHU-W=R!)vv
zP5s&o3>>$&N2zl5G1eP5wP!IfupMq{k78h8HEnA5Vqjo3YihS*U|=<GYS&_5U_0K_
zF3G^aYT4Az$-uyB)zntWz`$zV)RxJ>z-rUf7RkWCYTMN2$-uyB*VJaoz`$zX)TY6}
z!0OP{Cc(hK>e$rA!N9=k)YMwRz`%B?sWpRvf$efrYd8Y~t80Bzs~ZCY+tsF469xvh
zYfY`n3=FIuO|60q46L3_tqcqdtX@qm`3wwfx0+hw7#LW6np%7r7+8IqT5K2?SpAw>
zv=|sz{hL}O85r2^H?@Fl3T$dFV_;wnYHChpU|<byY7S;#V0+xu?8v~t8rsxsz`(#7
z*3>M|z`*vbslJ(yfq^xmsi}s6f$e!yQx*dQYh+Us$WKvCO&$yktkF$PW(*9hF-=V>
z3=FKXO-(`!46JcYO(3VmH#O!lFt8>zHO4Y9uqHJ%`Y<rCCO0)&Gcd5GG&O>pmfF+^
z3WT(#Ms@}U*7T-^as~$0jHZTk1_sv5riS`Z1_suwrUn-V2G;DR24e;W)|{pWMFs}e
z+@=Nr1_su=#{YE;3~YZJ|K~C=u;w@Zk6~b7Eol7j&A`C+zwtjPnhG2LYcepf7B&7C
zXJBAwZ2Zs0z`$DE_^*_Kft{)GUkU>QYf0n3U<L-((#C&I3=FJgjsFZ87+A|2|0&cn
zFtAoM{^Mt0V6ANYTg$+}TGjYBhk=1Lq494t0|RSK<6ln(26pbozZMJ(thJ4Q)fgDq
z1sng0GBB`8H~wW|U|^ML{8P-pz$)ALCy9Z9Rj%<*AOi!deB&Q`1_oAz#y@%t46KTc
ze`FXKSd|+8a5FHlDmVVFVqjoZY5bkZ5XZo(+W0$yfq_-6@wYnz1FL%DZ%}Y+H2zj)
zU|`j3{4K)3z^c{wn~8yeRlD(5Ap--ePUEix1_oB$#$Wyn46J&Mzw8(oSoIr!=`t{|
z8Z`a_*<{%Gi;IDQ)oA-cP0kqRda=fj><kQS;*B557#P?j8b72mFtABBegGv5sm2dZ
z3=C}2jUNmd7}#VQKPWITu*o)l;Adc9lWTkr3Viv-_qhxVYzmF<V;C6N6dT|BFfgzw
zHNLlIU|>^jd=JVaDvj@@7#P@88{cy=FtDjLzN=zjU{h~=m&w4urcvMcE`ou9O|$Wx
zI|BooR^vN!1_n0m#&_xr3~V}$@5C4w*mN7;u`)2Q={3GBVPIfA*7!Dwfq`A1@ogXj
z13Q1?TL%UPcD}~91`G`Byp3-a7#LWX8{Y~rFfe5{zNu$mU}A54lgGfo#MJmEj)8%l
zqw$R|0|Vo~#y2($4D4);^>4Hp7#M#yzL8{LU}tH3!@<D7_^t7E1p@=?)yCHu3=E9#
z8(&8-FfhJud<}|&8;!3`85kI!HogWW`CE;zMHm<u?>D|?W?*2w)A*{0fr0U6<Euml
z29||Q(?M~6ukn>X0|Vo=##gos42)MAU+FL~us&>jCC$LVc)syfJt!_7H@>W7U|>Ac
z_!4B{sm7O}NPpJ&(w%{U@p$7)GX@5>ca1MWk^Zvrr6>af<H5$4ptA5)<BK8&28J7r
zFA^CT7_K+I@MmCPd)fHHj)8&UTH^~)q<?69A;ZAHaH;VHHv<F1<;Lfr<n_7nc_sq`
z!@0)i;h;qRweh(t0|V=~#^<0s_Pz1B5(5LnsmAAm3=9kx8lN*TFtFWie3s9^z;Lqh
z8K|K7)A-Dnfq~&@<1<ih{@3^nl$-xIK9gWzU}I=}#>T+FcBS!YDFXxJ;l`&a3=E9>
z8=nR<FfbfyeCou&z;L+nsSyJM8(ZU3MTS%cHulD+f(#67=Nq4bYJ>faPe4T)SL2gd
z1_n0n#wXqk3=G>FpI9<5u$^jrqQStxu&wclI0FM4f8!H21_p*rjgLzi7}x|GAEz)d
zun9Fj2Blo##>XI=)-^shU|?X_z5TB~C%eI776XCpECrlQ0n6DYXbEg*JHYu*e>+P8
zCzHTZHm-o}YzbVy_HPT|4q>gI)Hq+9fq`RU<9s#-2961h^GX>QIQkpsr7$pX^fb;3
zW?<mxZk*@Dz`$YAIM0xQfupl=o&o~{M_1!Keg+0Em&Unu3=EtCjdODu7&v+x=f*NH
zaP&3K^<iM(@@SlE&A`Cr**I5=fq~1bajql-1DAK>Tn+{XE}zCZ<qQm5zV(fB(ij-H
z{2J$kGB9xYH_mZkVBiX9oMX(uz!lgyM~Q)fE2wdfAOi!JapN2Y1_qAVjkEI^7`Q?k
zXM=2-+c+C!Q+VTSD+UIxh{o9(3=A9#8fSyNw6JkDD+2>pbmOcN1_rK}##u=W3|z5|
zvjP|xIF>ffvS(o6Sk_oSOOJtpE1_|gECT~qV&g0x1_q9mjWeql7&uln&dg+B;7Vzn
z8NtB7mD@Peje&t<ZR1Q+1_rM5#+k|t3|twFGeJ(vY@Er!z`&K&I0NLg?8X^!3=AAE
z8)x`2FmSwRoMFqr!126sh7JP*$Fs&6(hLk7Pa9`&F)(lyHBPUuWMJSHZk(RMz`!lo
zI6a(!ft$Z^x*G!nH*e!~Qw9cZ?#AgV3=G_yjnjo07`WLRr!z4yaI-c}D_~&YW^SAo
z&%nUV*f`Cffr0CP<1{-42Cl!2({vdaxPCWIlVM=s`q?;*hk=3Xd*jp^1_rLLjZ<?N
z7`Q$+PK{<@;QH7&)vKO?f$M$aR7(a1uD6X-H5eGUUN=q^V_@KV**Fyxde0lD6f-bz
zJ#Cx<3cbgTQvw(mxE?l6v1MT3y5Bejq~UJk6mbRyuG@`MKpJi~P6lbX-Z(jdfr0C4
z<77Vu2CmDElR<%C**IC3fq}!Sak4xE1BZ3vWIl#^1`eCXNi_@%9JY;<G8q^+>>4M9
zGca)2H%@Y4VBm0QoCHd9j*XKP85lU68Yc-bFmO0GP6DL_m&S<&3=ABujS~|X7&zP-
zC;BolaJV;4v|(W2@MxR}YTtM^PLyI`;P7gk$jQLK;oUf)f`Ng<r*T3$0|SR|<Ag8<
zhI$Ua#tE(r3>^NA6HFKwI070cC^Il{1U60(VqoA1YMcPFDY&sepMilRq_H0qv7wFq
zAe+J(`$0B^H-cMI5sm#In<5+gxfmEYq8j@u85lUC8~ZXC7&u}Y`#@fbZR~SrVBm;r
z>@#Cv;D~SRQ)OV_s849@6JcQBNNnt5W?<k*YV0j$VBkn@>`i81;7Dog4Ps#6NNwzO
zWMJS(YwR^(VBkn^?3H6+;K*p~1*O%@#vV{w&1&q)VqoCNZtRI-VBpAU?D1k?;K*(4
zv1DN2$ZPBY<%;~q9tj2pj)KM>b_NEH!p8101_q9z`o`{51_qAe#_kXX29A=(Zf6Dt
zj?%_%BL)VJvc_&usFyc(gF?Ncv8$eefupjq3zXBV8oOc`7&xjMySy0~IBFWZtQZ(L
zY8$&W85lU~8oNL?)i-v5ij;=NPEe83*w_j3Qd47RAOizOb7Q9i0|Q4(V|}MS0|Q5E
zV<*T@ZH=9L3=ACYjUBZN3>+Pe9XSjPJPeH;(F_bcjEx;$eDw@03=AAU8XG{~``OrF
z!N9=rtFb|yfq~<9V}lq21IM4n237_Jj=%p)7#KMI{Rdh3|9>C@11H0Odj<wh#{YT@
z44h2=Wf&MZng4S$Fw}Fh{HtVO;AH)m!N9=D_Ai`)fs_588v_F;$3IgB22Rd@Dhv#q
zT>pd_7&y8AF)=W3^877gVBqBao5aAt$@e#qfq^USuLA=ESL$DV1_n;Szj6!=T*-fV
z85p>d{?srqaEkoNW?<kH{R7Hz@qfG-7`Wp8STitiO8n7gVBoBm1T~5{rT&0&Y1Ho;
z1_rLk-#H8noU*@T7#KL^e)}>oaE1N0V_@J^_zfzmLVklvs^H%|3=Evgzp5D+xa@vq
zF)(nd{)%K^;8gqN!N9<&{>z+!fm7p`8Uq8T<}XnO22QPCtPBjC+CNJe7&vu)CNnT_
z>i!I3VBm6>`{~HQz{&s9fPsP2;HLru1E=9n0R{$6p`Q#444lH-)1tZS896RCE*EBC
z;L4l+Hip}--lVY|<Q~(;c3lPrPP4{#X$A&P^F~m|fYYL}t%8Ap)3UKGje&vFs<ADU
zfq~PyvCV~nfzzh3&6t6K)3&iqiGhLBuCYy!fq~P$v9+FofzzR}HJ5>b)3LENnt_4S
zsj=0Qfq~Pxu@&SIm&R6*Ph1;YL0)mIZ){~@VBmCbY$;}7;Phy00mX!8V+$yjy&78_
z7#KLc8(Tn;;nUb6%fP_t+t|X*z`*I(*bItk|HfueR0lLRgW@`{u^ANEL5<C(3=AAk
z8k<!Z7?}SyHVZQ_Fn?`qW@KRCy4BbOD%S5bHpMY8Fn?(bZUSZhSB*`e?Ekv42~^O$
zX>0;z|F?}z91IK`?;0CHnd^OHBPefuXlw-4q8}R@LAB_o#zs(y_PMbUREvITYy{=4
zuiI<lxGNdCzcn_1GS~OUhL~*z+<mO|tgnwUF)(mB94TU8V1080<WsRDponuj;>5tf
zDSpI|fr0td5d{VYF54sg3=B*Y4%aa-aM>IN74y!AqZk;ttPguIFfboKY{tOADSa5!
zmV0|xh=GAq<}f1z1Jl$)Air500(tGoAy8dve#nY}foa+y4N&ToKP1M$!20eG3j+g}
z>A@lf1}@8ki3|*!iU$K27+Aj?1f>I|gE|ZhTvi9A7#O&W4stLsFz-81#=yX-asbrn
z_;DbZfq~25fFlC~)4T)v3=CZQ2V@x-n0FrlrFgyl)eH<w^Y>>lFmUPa2Q>zN?RRHj
z;L_P|#=yX3Qomo7fq_eVzX$^Zm(qSvNNDXVWME*b-WSinz@@nllsOFd*)TA0Y3$Qt
zU|?FdPm+OwQ*R#!0|V3Yz2yuHocepy7#Nu9_kvm%s(V3=3+26_wuQ=GP}4$fFDR`W
z?Wtp6U|PKglmLzQfVx(H_joffaEAWa&TY=UlBu3y*Go1A2Bys~N*NfqoL(d|Ft9#-
z0m}KVFB}*cnAX40XJBA`^g@n-f%U-)UIqr{wa=>=7+CLv+MZnY&q00MyU*Pi7+5bq
zH)UX8s(TKKg^SOH85kHJKL`2B>{%fL1LMPI2@DKO&CmQ87#N>FvteLhS^#QqGS<I)
zCdt6S_~{v_$$tB3IRgXJoTq6F42-{?hB7d)Fg$f-U|>G*6x3S(`&5O2fob|vVFm^!
zwx>)C3{2@yKt{iM63@WEH2DcAz;d40Ffgz%KG9-eU}1V9!N9;(@B~zI7d{5HDP$gl
zniSHHeHj?Ir5;-|FmOxOKh|Ji;FfqS#=yWW{+NY<fm`fR2?GPS=%Z8y25yl@p$rV%
zLXVso7`O!<889$#^F5MdVBqF?#KXYA&Git}z~Ok9#=yYM_Ar=%ft%%_3j+f;(?b&m
z25yFjDhv!<{~m%GQGXtQ+9JOm<S{UC{df?|z`*tG0Vq9wc~B2(MSgk!YD9i`0BS?N
zdjM)ezPS%-LB6^VYCpcX4~pPt_njFSxSrfMVqoBUbYGEyf$PD20R{%Hd-v)Y7?}Uv
z%Vl6-{&O#efr0DBJy1b>?H;Jrc;z0b(t31Hf`Nha_&s(82F??ALFxD8-Bbn!&Qo_o
zK;_fvyUq*@oM-NW3b3<xl^GZ~&)o&(qVsnd85lS(+$msS;JkPzj)8&m(j8w02F}ZO
zKxO=uJ6a43oLBFFQsuQf91IMc*KdPT<&E2*((&ePP~mv%HmGd8eH&!*o!g+2@$PL<
zs=Rj#Wbgf3c?|UooDXirGB9vHyye5d!1?Hw6$1n3<6D{x44hAHfn5Fc7Rc4lZh~C>
z{3giNFKz}iFmS%S2`b!Q-2@fxuW!mRFmS%P$;-gN`SwN)0|V!~8=#8m{S8oo`{9Nc
z0|V#B8<q?VoS$x}Gca&|z9GiI!1?6{8>o)_dcBl^f%DsSP{r~6dJqEx=a1{4a`xwS
zP<8t2x(ovY=kM!W3=Euqu7S$fzt_?k7&!l31Nra&HBh85Tr*@~;9|Tc&%nUNbd8UJ
zfs6TSEdv7=%T-WG#d;M~JF;E%VqoB6ziPq2z{PPDl=C^Sf~uW*uB)KtHTM-zQN?p5
zj)8%T_X;Q_^IZXDef}%j3=CWXS3u>D;1y82TIg~m0|S@v<qQS}E|JS&3=CYNmqA%y
z>@q0pi(dw1eTmDUL?;OvnB$VV1TtCr63AqkOCXbFFM-mW+$Bv01}=G?OQ1}maEYCP
zflG1w4qI+}Ceas1L54UU6=G#zU_8Lu4(d8GZs&2}u4UEXQs1M&z`(qE52)|Pvxk*|
zfobFJ5(Wn56}yud7??Kg4rE|p<K6ARz`*!&`&L)(S1cS{`SY0>7`Wd}U+%@7T^}^Z
znt_2Qc#akW15d~t2?hq9&^hc33_M}8%NQ7V!e^&3Fz`go4r5^8iJa}mz`zqV+l+yM
zCwjIT0|QUYY%vA~p4i!J3=BMRvq0+OXMxlw%nD~<;7Oe2!N9<iG|Pg4fhT#EIs*ew
z$}Euj)L9_)X){Y17<kg_XQnVP@MO#kW?<mSoaw~Cz>_u8kb!|Gd!{@C15eIOJ_ZJ!
z+!?hD3_N)=KrOWV8K4GQ!3-}32A;whmJAF$MKd%R7<h_jNHQ?+l+55@VBjg84suG_
z^kfDGp7QB|3=BLK(;XNXcq*ssGcfQ}O_yb0;HjR@!@$5(Gp)Xwfq|!XS{4HXPu;XA
z1_qw`X`T!WJPp%8u5O$L@@3OBQ3eK{=4q@93_LAUL9T9{3UYMY)DQ*+p7yCO3=BLS
zQ%x8ccsi#lGcfRUO%-Nf;OU;q%)r3YGo^@ufu|SLq2cM962!p3(?12|$q7@87#Mga
zPEo37VBncFMTmicXYv##1_quflM5Lbc&36nG(6KL`!g``Ob2ymcxFu2W?<l%Ia!K<
zfoIlakS}LX0{L>zB#=|)P68P{ZxYCt^C#&sFz_sx1oGv=Ng!V?nh5gb;)$6I3_MFF
zf}&>WL{|m|o@En_8R{8$mQPe-VBlFXQILUwXXONtgH}z*Wnkc0JpmNdYbJogW9<ZU
z1_qvW6I2-(c-Bu4VPN3dFahM;jr|1-3_P1aeHEU~psotf7En)xXKOzwJ#Fg;rKj!v
zp!Bq(59HjPeW?r#JiGcpA-B8FnSr66XHOp}DE9U#Ffj1!>jTC2{$5agALs?e_rYF}
zBM$X~;`?wfD87&MYA`VH9PJfnVBk5{3rb4Idq9zLq6ZWbCwo94ajFLt5~q7W@qMO8
zj)8&aY!5F31JAi`P)MBb21WOU?nqE{U+i{gVBopb4NBFQyHyw%c$m9E@yF5)@*is#
z$bW2I@eB++>|K5g3_KiNwhRnBoLxE$3_M(2(hLkd++AD@3_LuYl?)6#yq)O`3_N_D
zp$rT>{GFhbA<${ez`!He2?}GOPEZ&NcQP<A@Q8HeGcfRo)_24)Fz|?V_%JZ=h<8{q
zFz`rpfcz)f0m>>;9V`qCJksr;L?qLmz`(#G+YWMsTsz1S^6el;D1e&8Jc{igM<{_t
z%6XLAG8h<mRN6o>t=b04v}$dp3=BN#Z6NPyw1K>**#`2SR%<;dxoNk8jMixdB{$tx
zkkNXrpya0C3QBGUt(*)DJccb53=BL*Eg=6Hw}6Z`X#s_tX$vUi%vwMx!@LEQGAvp^
zDc`ag<Y=qrL<R;P>t>M2HqCYn3_P~YAV=FZgG{z>W(OrVhbE9C9GgInaB2ei&l%L-
z<#A~O<!sj`P)xfufwG@_BPgal8bOZmYy>&Ns}Yovy&FMk$OqKS<?(F<r6E61MEir(
z1%Tor(3OFKO#n2;@m`gIfhhxAl=iZ!GHmBa;C{eXf2i>?2Ll6}XyYZ&c<qtKOQ2D&
zqm7q>7#P@&HC}RLU|`tTc*%f)f$c=&B{>ELwv&yQco`Vj_!=)(Gcd57ZoCMZ(>T+3
zF_M9S?QG*k4+aLdbBz~4!>*i-7eT|W9E}%685r0uG+tz3U|_r0c%hhqfsM8CLNWsb
z8%urT1&~e5jTaml7}%H^FMw>i-gp5tWpJbM0v`hd+s(%FH4F?4M;gy(Gcd5-ZafdN
z=}zN$(2T+F#`7SX?lqoQV_;zY*?1mg(}TwIAe$aGo&(wRsPSA90|Ud^#&aNxo;03w
zU|?W-+ISAsn*7vQe-6~1{MdL7<fj*nXKNT3Sl>6E1=;kf@oW?W1KaDyvz`nLY;PLR
zS}-uMy=^=TvguXhSrG;Xw)c%^nHd<^J~W;wVqjqV*mx$9fr0H)<Cy>k2DZ<QXY3gm
z*uFHL(PLm>``UO$mVtroTjLoX1_rk8ji*6@_oMN2J!sVWXX9zmp!KiD)1V2O-;Jk1
z6EuGsPlG0CZa1C=jb{F9JPn!!x!HIspMim$q45-G-1K_mDbNJXwZ>DR!Dr^iQ=oCv
zD~+c>W6!LOr$DnHml{uk<|f!1PlCD$7aC6nF)*-mHlB23U|{EJJZS(LuRYs%Ql5c<
z^-SYQ(A>o7#uIf646LUbPvkH#u=6yY0L@LDXgmR$tUBI!!jgf3^+@9h4F(3bRgEV=
zb?@rN6Ko6&Y-<{igT_tQHXaA1pmmMMLF1<D8;^rV{5Lcn2aWh|Y&;Gc@!!;V95mv;
zx$#&%LmUI!md0aw3=C{r8;^lTXty;U0}c6aZ#-thz`(Yn@t6(+1KZBVV=@d3Y`Yqd
zaWgQm?QT2@8uH)McoY<PdmE2}0&idAQP7D0{>G!A;q3#BM^zXY*bZ(#n8_W(T)(t&
zk0ApC`?AJ83JeVF%NzIbGcd5PXxv@Lz`(w;ad$2Q1N*AR-LVV|?5i7h`!X=FuW8&3
z3evTWyR{h@*w;1gmSSLFU*EW!lYxPKL*uRr1_t(xjl0qr7}z&8?h0dIVBg%h%Y}h~
zeM{pmBL)Wct&O`B85r2NHSQ8%U|`=~-?+1$fq{KT<IX$=2KJqeJ3%(>YTOC3X?NpJ
zTLuR9J&ikc7#P_1Htv*WU|<hz+{w+rz#i7Pqnd$%J-l&8CIbU|MB|PK1_t)X#vSeq
z4D7LuJ4_iE*rOYFs4y_F$29H`W?*2CYuv%az`&l+xV?~pfjz!)djbOkds1Wlc0UFN
z_Qb~RAV1|aZr5U9U{7w`F2TUSp3=CToq>TpwQ*Y+0|R?n<F+&g2KMyEZJ`Vd>=}*Q
zTp1YHGaI)VGcd4cHEsj>DZ6nSDDd(cx7IQ+uo*Nys%2nc&u!eA&A`B(-?%l3fq}iS
zaVuydtDteK1p@<napTr{4F(4GqQ<SDIkS?+tso1_8n=KfEN$G9%D}*0-nb>0fq}iM
zaSJG2Ry1zWXJBBjY}_Kpz`$PJxP_O2fxV`2a}5Indu`)pkWI~vn?W|!HEsskRNuJS
zoPmM8p>eY+0|R?w<7N>C2KJ`L&CCo8?Cp)4ia>$i(zq#+fq}iXaZ>;T1AANJCOZZO
z_Rhvlx(p2L9gUl07#P@l8aIJLy{mC!6$1l%cjHD-s849z2nzMy#*H2f4D5Z48$o{R
zZ`=r)oSWUaQIvs!ePZKAkWG^sHxw~2uupE>0J3OG;|7pLQyVwfGo&)GPix$u$H2fo
zy>SD`rWuVJxEL7NXEv^{WME*Q)wn)`fq{Ka<N9z02KM=l>p`JDw{g7*0|WcK#`Ve!
z4D5>=*9$Q)urFv_&&a^QzOZp!0Rsd3qQ-Uc3=C`{jq5<syJY*{eC`u$^^2SKN-!`m
zEo#~e>YsNt?Wtg3U_9BhCzFAJsiSF66axcOdlRVV&3LY952*Xw+O$WTfq|)|X%A=)
z>2lK^ZUzRXrl#Fh3=E7nns$TqH8kyxU|?Wg-?SSvg><)Rw;2NiQ*G03RR#v;4Nbd6
z7#JA#H0@?#U|`---?XcQfq|*AX;(4>1LK#bT|o>COyy0xoER9G%9=pAgNdbSml6X5
zQ%Tb<AqEDf;-+1o9&}OD&U^+2rotvr=3pvl+Ud=}z?9##6EsYc*0fWTfr0sR(@qHn
z29`%nJJ}f+n6jI8lrb<c<uvU`Wnf@_*R&&qfr0&JQ~eH5KK#+N!<d1Aad*=WB?bn@
zJxx1=7#JA$Htk?!U|`(Ww7r0Vf%!rcD0eV*Hf;}JU|_!3wB3P$f%#I?cF+XRi>B=g
z3=B+dP1^++7?`g#Z3FdeuQqMVXJBBy-n1>Afr0r((>8ww2ByZQZT1Wd%r~31=`%1e
z-)h=cFVDche5VPNNto|8Z3WF3)--JeX}s68HI9LSsj6wK9|HsP{idz93=B*aO<Q#s
z7?>Y4ZIxnRV1C%Nm6L&iskCWJIRgXpqoyrs3=GVVo3?~9FfhJp+TzT>!2G0XixC3@
z<A<g#iVO_QPn))YT==YMGsuO{n>OdwGcYjzXxbdZz`*>nX|p#21M{n<%~lKy%&(g^
zYcen}F*I$KU|?W=)3lk5fq{v&X%nc+)Yh~qnSp`1y=hYr0|RqM(<V?@bT)0$V_;zJ
zY64{r=I$m?=3wq=+E~fJz}(xkF@u4DxvyzsI0FN7f73=c1_tH{O&d)a>KT|PHf>a9
zU|^oqv{8tGfq8P%Mn(n(<|$1ZK%qXhX#;2wY+BO>Uj_!|=}jA~85o#nG;PpgU|^ov
zv;pL_Sxp<*7#NsmH?1#aU|^opv_6G_fq8Dz`d|hI=6Ox)ofsIH=Qphf4aqHNTCc#s
zz`U?&JwF2j^P;A8pb;kK#nTT~a+}wmZ(0i)m%h-nHjsgV#lLB-Jp%(vK+{@X1_qYE
zrnNE*3@kxSYq=R1Sc03@R538Hgfy+mU|?VgZCVq~z`zpLw8o8rfhD|YjVS{IOGMKe
z6$S>D$fh;I3=Aw$O>3AK7+9j4Ru?ibu*5X2j%Q$CiEUc#$H2f6*R<M}fq^ByzG<}%
z0|QG!(`qRO2A0I8)tn3rEJ;nPDi|18lABhgF)*;CG_3-SETuNBa$#U#No!hV%)r2s
z-n2@Ifq^BXX_Wv2150Mp%6bL{maL|gxeN>}*-a~>85me{npS!-FtFq{t+ZrdV99G*
zslmX&lHasaoPmL*plKx=0|QH8Q{swJ1_qX*rWGj+3@pV>D}osqSW22!I59A=ls2s}
zWME(^Ygz%C-7arh!Oy_JQqi=$j)8%tvS~TUrmCjpF$@eW)lJL285me<nwDEJFtF4%
zE!SjVV5w_bF3G^aQolXCntLi^eM8f-as~#L#-?Q;KQ%Qi3u9nlX>M8u3cZ%5Wo8Tv
zEUit;R2djp+M1S$Ffg#RH!WjkU|{KJT3W=wz|z^YG=YJErK@SFKLZ0xchgc(==C%$
z)n;H|>1|pHvZ=3WDacR#O-n$*J)vm{NW;XYC7|G*RNu4&G|)D=X$i<}Q<|25LSbst
z5_Sd#mT66kK~9_Av^bN2fn`S1;s^!?mYGe9K~9_1wAh4!fn|2nVo-3;X<7^l?zv5i
zY8e<<<~1z>1;YHMMWA8Irlv){3=Av}n-+nV!8A54(qUj=t!`QbTBuXsRKEzc4yLYY
zA!r>;c+*1AI+&2Ag`l-20Zj`*YfZeH7J}x%-J2FFF)*;YH7yimU|@A=S_o>-IX5lH
zXJBBpXj%YT)nd}Lz=wf>g}-TmH3I{SK+^)y;GtmC0#G0bH7(#^U|<n$nh)}lNYi{!
zXp1(@2d!#h5o?<7!T@R)f@Zu~#GB@Wye82!Uzve{MY3r=D9uVW%?G7f>85$0K$K~k
z2MR>lrg;Gj3@ma@^Bfo$Smc}L889%gC^Uhlo>>%|KvT~wN=<V?L89C=H=BWhMWtzO
z6axc`YSUa#1_l<jrn#1&<f+~?7Zms!O>;rzvu4v=P~dAd%>lVoyJ=230|Sdr(;QH`
z&~2LI%D}*)*E9#@Lj9&Wpujh10!=-$7&d{Xo>`2VKvT~w#!a(9xyqzzHYl1+n`VR3
zg;~>VP^L0(nk~)1z+%xfn~R~IfyJ_ERwV-ii&fJskWJQ2vp~7ZrfC)^SJ^hrGGbt0
zv1^*8$iTp2-!uyp%??d7LC$t;nwihQz~a<26J(Qf(@c;}E=@B*Hn}#<1Qir+O*3T~
z7+Bn!X7VyHuy{1hs9|7W@obs_3Jb5M8IcSOQY_w0Gdvg=SbUmhm@_c2_%_W@V_;zM
zYnmatZ9)Q@z;?C;+`ssFSh=GZLs(To@w0C`PXo6!YdzDprk{Qc3`|>^e%dfFFl=f1
z395$kntn<$Ffgxd`U$GOH#GeyV_;xB+Vmrpfq`jV(~l4a28OPtAI=O6OlzBd7%?y~
zbT|C~)m3Yne(*CeF!VHiuVr9h+S>Fzn}LC$x9NKn0|Udsrte-13=Dlu-z^y!m{vA@
z2d#Rj?{E4p&cML5qUk$m*~5gUZzT*2EIdu$K)t1jP2WHXgS+XQJp%*7q^56rpaHn1
zZ?X&w43nF_@h~v3a5a6cW?*2L()2Zpfr0UB)7MA_28O9kUp*KYn3gnswP0XinAY@F
zje&t_VbfPo3xTESE2yGh+VrK6fq`L0ebX0E669$5;?KaqFth249RmaNo~AFl3=9mj
zn!d;|Ffh$+`ohh?z%aY%b0q@<!<DAb84L^zbDBPfGcYjCZu;!Tz`(Ss>9ZLF1LMV}
z&!DiK+w>VUCO@m`GZO;?!@Q<XMGOo~Gnzhumb1)n`V_#xz%;Yz6Ua*on(9A+YPao8
zpX3-A7#22t;$vW7KHBuLmVtp`QPam91_q`nO&>w40T(xY1QoZeO&={87#Nl`eFRmb
zlbSwCGB7YKZTbkRuqQTs0J(5k(+5zkc&6z?I0FO2@}>_U7xp)OFlAt1Skd$WG-=S+
z^g)Dyfq6;O2UcbV28Ng0HQKr7Gu3ZzdJJml>}Uc_0x<1tdJKx0T}_Wcb@c8g&^!Rs
zo~B2jam~F=k3ino*YwDafq`j%(<2=Q2Brf|kE9tGm<~2Q;$mQ6I@AQ34q!Um^e}^g
zf$2!o!!QO0rlU;{T^Sgdjx{|5O^zIIdI)mOiKd63CfLdPriY+us#8r53K$rePB%RO
z&10NtdH_nEXPX|_FfcHkYkB}mp68n$NHH)lU1)j$^7qB2`xOifOqZJOr!z1xU2eJ$
zvgu0GeUMF8o9>%1Ffd(fy06T@z;wOoKFFpUP4__--E6uCvglURJ&;AWo9gd@Y`W8Q
z57Z>O+jI})r+ZEJKz_R4bPwdG2TgY?85o!zHr)l;^r-1>C<6o2<EFbHo1Qe?1=;kp
z=`N^Q`K;-#AOi!_^QJqXw%3cMJD}BCFPrYfGB7Z`YP#dYz`*pn2{doO^ri_kalrJp
z>5h~n0|V2$CeYjg)B7gS<N?!%rrW6u42=EL4Grv{O?L?3SzgcdvFUaQ0|V2irrV&_
z?B}N2h71f$Uz%=%^555{+x!d+Oy8Prff^y-n{MSYFfjdSx)sB~!1S}}7N|A*tLYXf
z|NU;drOv>>^rz{TC<6o2-=<s43=B;Fnr?#9>i?#jNem3k3{5u!85o!un{I*{VoXgp
zL5<6L<|feW0y9e!XnKK}wFxx8z|7VJnqXjNZ@Ll1z`)GW1e#)C=4=AZF)(vA-2e@d
zb2r@(XJBCFX#!0%F!MHnrWu&|ny!P|Rs2oYLl_vC1)8qAFfcF+HeCmG^@5wOgQ}{Q
zrt5+X49p*!u7etIAL^T~6*4d|zi+w*%C{^{*FfnotLd6O0|OIB(=|N?1}5gFYqAUs
zOpHy}xEUB2|2JK&Vqjo?(R4MFfr0T))75YW2F9OFS6vtw7{51N)n{N}{M>X^mVtrs
zW7Ab01_s8rO;<pjju%Z=(is>SpEX?pwR;~mU2$SyV0_S2e+AT}zteO@nSp`vR?`(x
z1_tKaO;=bL7#OcNT?Va`yV`U)fq{YXQqyJ7<lcp*%b>>PwWiCO3=E8Cn=VT+Ffg8O
zy3EPIz<jys5@?0oiKa^+ryXm$1nS=GXu9Oaz`%H<=@KZzzHYh%nx#J5bO}^=-E6v4
z59;5XZn{{)z`$^;=_07Xe6r~xsKI=q>7pY81M|VAiv|n~%*UE8$}=!9oNu}aT3CFs
z=|UX?1M}gg3!r(iLroWA7#J8%H(dZNL%Z5^!IFW2d4JOdP=S1==>jO4_BLGrmB+`L
z&X+PUFq~*Q4~nK;P3ME_85o#%Hk}8xf44QA2XzAOHJw*vU|>AdbRHB>Tbs^<s+Z$U
z=Rm!U%}wV(4ed=$=Rm!UjZNo3i}(&SodXqmOPkJtCWqHGo#SC(VA#=g78Ffun$Ch2
z@$GCn3kr)>O=sO17#KD;oi%4*VA$GpR*gZLfq8k;Sx~4iYdQ;BF1Wtw3@9x2Hl0b{
z_92H&U^!brg1~k*1?zwO+gTd4m;{!y30Q*&9+0RENc4g%Xo<9g^*{dQEDsh7EN5Ae
zAh480U0^xO1uKE=EE}{y(huT6N+(!@*bZ7C_JLdwyMYJ9Hpm0972-ig1lWKy@qlc4
z0J21Y7bMz{2Qt`3U^z<xh&YfZu#`ncU^$C{jKFr50A7&l1$+X_*%D*~ma|>R1G!LB
zU_09cUXbw<WI*x?aRS@f9?1OX-_9Cf%LuB(Wk4n`;JvV%<$$fgaux+yfu$^Q0^3;x
zWSIoo**5UCvu)sSXWIZ`3%0Xu5Nc=JAl%NjL8P5+gJ?V32C;Uw4dU%=8zkD<Hb`z~
z+aUGt{c;uqTZQE;3APH`Sw8T9Jhea*<N^ao81aHEpTP5<e>;nVEXYkCq(Sbm1-YX^
zR$)8K11pf82eSX<x3f%$1*s5_6Ijmn!Af8|TR|*HS%I9ua+VFCFghRyQrn;o5`7>i
zu$4s~#CM1V*{1+zC#Zwi1_dB<8stF{rU_EKL0(`xi-9_$z;@OJJfMIGC;$l;*a<9W
z`Cu)uo#lZ%NXG<_jtenhsRDteED8eKSrRlsb|@%-{INg_<d24pAdv(GkWC-JwiYOW
zv?QnrEN5u|5e^Ch%ULF<32bMX0Cur~14wOv8c5#+u!9a12rOrL0J6Tp0^|lefu$@C
zAR&;o_5w>;mJ2Lr35WqjQK`UkmID?7TUiW2+7BdwtomR8N*f>x9$0`x7i<JsuptS=
zeqivAzn!H)p`E2cv7Mzsshy=kxt*m!WjRZODk$EiL2lb9u$`p<?4AWlAgvb+K>lyg
z5ZKCQ3*sLD%N2l=?FMO(u?wU@78lejEN8i32THGC6%BSEQ2{@YL+wH7(hg+K12s?#
z$_Z>|GXN*>4RQk8Srj0_FZ-W=Im-o2koQ0t=7TLLX279%Kpte4fi)<$xj}@w!g7`a
zvY<c(rPUAW0^3;@XfPRUXEV_FC%>G<0F-bOG?)~&vlVOvX`P?}imy1ZYvVw^*Z_{H
z3mPEF20l>mY6xs)(F8eh!!m*GYz__}nFAnm3~WH60SW@!*&4txQ~<JAKm(NhG(pB%
zgXAw*gHk2LPoQK|-~bX0-~#14u&9BSz;YG`P->gt0CI<d9LOCDz{(P|KpB-Aw8A#_
zAOBVs9wvdUY+7I!a0|4v9MEcKIiTInazLk@<$!KG%K^RZEC=+NHng(|7`C$s7`3wr
z7`L+tn6$GAn6|SCn6<MBm@j7&uyAN+`(Ux0?Stim?Q9C%zxcN`ShIk(ad3my?}FU>
z0GwYofRa}NkHA)z#h`2;AOngA2XI+p4H7U=00{_y;-r8F6qDfc=m5xo4{9JsJ^*=G
zzy_pN0h|vKz&TvO2ILoTapa&Wu$;|6Q(!Bb4M>B+5>V8E^6iIZAYB16i~`Hq8hAkg
z09H^CC$OAF02E>cphy=0sV@K(aSEVBaRHpb4#<ECh7U5Jz`S7dPkt+l28cNUoJu#?
zg4i2mL1BCW%$@-DYXB&{Jpc<7sDqqm2eRKm9pu9Vd61=c4$D~*K*_iOlJV^fwzCCT
z{L^2~Vh{n!wiZkV%h@hifSd|R;UE`nFaTM%zyMSfOfUc$CICwF7r^=B!W57z7EA#r
z2>XQXY#Zi)0%5`wP^z5+(m0_JBp?8ahk%WsWCF^B6To@)fB{IV0TdezjUcrL8kq&Q
zb2`}k=HJeu&;&{-vLF=(yaL-<4uDIf4NV~XJ~aK|-<A-{1`7C4f$eM`LO{wEgn&|P
z2-qnhASn=`5F*gdcEF*X?SNxD+X1I`wgb-XYzJK0*$%k2vmJ12XFK4&ob7<egm$(M
zp6zTOyxQ45c(=2C@Y&Ax!53s`f+r|d*?{T^1;2JS1^;$7g@EO33V{vnYz{%&*&KrZ
z^)F|+5Dv;_!3N7&9)MT^xeCi!96-)-$OUKA5KtIT$OUC@km!PNkl!LeUU?7#V)}us
z5&*@4KqyFqLLOMo6BH-`p&)huxaKSXvlGDV3!dN@31u|c&UOIIz7YCfemTnqkc$Pv
zKw1sL{^f6H`49+VF9`c*zntYjKFFbApc*J2WO4XE`K2tNQdt4)?gCJ;6b@1z5DqGA
z8p0K}vup@wQrOB?2y)_rz<}i}4W0r^S%N@iTM$U)0#A_41hB1~fB3f*c!E040bo&u
z2vBA)5NKy{h-hbVh-_zZh}zEL5Y6;qIh#VZz;ZT+7!Z*Js>ZVgwz6ga<KN5zE<zq;
zfqZ=-3uMCqFndE5i@<h{3ypvHx3V;WBH18DU_09eaJ5?y15zg-4-SzSP#RTm0F~A;
zpuiLW*I5k(ASD;TrELPp#|uDN;sPko1b}lxf}FroHc%zJ07L{V29=a@Ag>*064=gi
zK^>%hL+mg9EzSHa^(=hNn?dWf&6_ua7B`wTZw8GhJ!u9F%(Cz{Zvrh*Hf`RN#K6E|
z(hM4y<uGpE1X|o^)Vv9_aM-YUlM(|1he7iuK?Vj6{pL-eMbvuD8$pYxb(=SW7E$Xo
zZv?HP)NbAgT1BbVyb-iH<w^5K&??G$&E}1uF-gwm4do0B92(6VK+7oAn>T=l7&@9a
zI5RM?o^Rd&vPrFZ189k|YV!urGD?-^4WOZ`bIt1u7#LXCo7cxPFmNb0uLrHeS885w
z%fP_=zj-}qoQAD=J!l=iV)J@#1_lm==5?TX72)P}pheX3_08)d85lU^n%8+SFmT8=
zuQO+0;E-uv2U=z<-MkL8w?L|S9UB7!hh+0w(As8+=CvRfiZ`zfWnkbCYhDXlx-Qzh
z)|i2TL!@~vC@h4V*MeLq)V!vifq_G?c}*Sz1BXEK8c<m9H?IM?kgs_SC@grJ>(_un
zou_#X$cfy|Yd}uqYF-Um=grx?8nj5Bqj_}%0|N(p^J>tZ1h(eYpv9}K&8t-y7&us(
zR|_*Ra4<KoW@2FAU}|1f$iTqC*t`lf;r6Y06=>=ws(BS?w^T#(D$vH6lg+DS85r2V
zH?QJlVBlbAURe*C&idcH5;UFluX!bCI_q!qO3-xHpXQaINv7Y;D?yV?znWKyGB7Z-
zHLnD<xmlZ66oXblHLm~-)37(M2mr-;^9s<I250jM(BKJI^9pGO1_tit6<na@7R}2+
zLleBs%Rz%De9g;2LlgYX%iZc37#IYamxH=Gg3ZfS7#J9YnwJYPFfa%=F9-D_M4Fd@
zw&;j9F9U6w6l-1v+M*-gyv&AyfkC2qnKlChgJknEDFy}xspe%Mo1~kURxvOz$TTm_
zVqjp9ZC)C|z`!8aywr_>fkD1`sR;uEgF^FCWd;TY#pb0#4D}2QO3h0d85kIpo0k+Y
zFfgbzFNtShU{Gxa4eT<gH7~JcU|>*hUIMa7qj?F)Ce7w0oD2*MTFr|q7#J9|n-_!p
zq|>|@<R{(c#jXqt40_F=aa{)e=EWc{88j~zW?*12Y+ei+5Hf0B1R8oWZeEnYz);U%
z(!2;1dZx{bK%r;Wya*I}=FN*_7#J8VniqkFo-CUeg8XFFyb$Ck>*j@^;WV4(g`nXy
z+vbJV3=9l*%?m*;v~OMra-l=>LXZm`n-_pw=+wL*oq>VDxp_et0|SFg^8!#<xHc~U
z1$w<(^8%0)-J2JHoaoWK0OUl^=J_BedNt1njahj&&j-2Cr+Gfeg}%-6L3>pFn&*RD
z=-)ga<iddFc_0@CHqQg~-h!IvfkHjFd7cLY14BsjJkT&)X!AT!|1zw39%#raym=ld
zwj%1A=Yq!XBAY=2y9`myb3tQW(aoSeMGP^`b3uV0+dLO!VO;ZEP=_|Yc`m3!o6tO`
zj)8$8v3X7|0|P@+^BhozHo19@4+8^3N;7Cp9Ybm}Xi*(QTJs!`h3U<pWpxZ0&7gI4
z44KWKg>?*B&GoZG85kI{n`eVYu5+4agVINC^K4L%<TcL*^||w#XM>V_K{IG;5kq0~
ztYiiThN5QB)*^=D=2@T)ZAtSi9R>!5(&ky9BwyA%3*@!(=9!=*U(q}hlsqb%XM&PP
zRWoR35kqzJOfv=shMMM?E@})647JTOL7A(rc_zrF`sNv+4sAp8j1&e2hQ{U@!3+!x
zP0cf$85kIvn`am^Ffg<<&j6+1*5(<YNNb;dg0s1d<6JXn!w<*V?QUGn`&gH=JctD~
z1Hp~Ff_zZ%uK;Rae~1OQrIvuImJOhmvqC<o3JQo5Sjv_UYJuc|ls155CfI;#iV1w6
zx~PB`)a^<DcTN+)ZS4o3&S`+=KmMgG@u2PlsA*%c7^LF@xQFZz&!n)NtpU`F_>c=S
zq9GpCe!P$i>OaPV>SPBVP<I$aG=LfuA3(+!<boUx?zK+<HMI>AK+aJBwP+8-gA7kd
z0Gah52V~X*kcx&%kctC20_`jt61KB!NMxGO&h{Xwo$Wz#JKKYlcD4tp?Q9Ry+SwkY
zx3fLSSkCq!b3;3uLH2ewgB);+Cm2*I=77v@0GnNq016v{5P_vEAjdc)fWqg2w7_yU
zg#=Lb4jNrZ$OU=e0?5S+Kux3rAqv}B62K08kPB+DhB69lWzAz$*v@tU5*nc(3mm|$
zA%S?1i621WR{$1h2nEH-guMUy+gT1k*l{2?JOGUugn`;8VIUm>`2x$?HpqawW%-~c
z&;?KgH{>%pEN5E~E3lpI0yvf%K%yVOk(v+-8Vvyv3I(8MBuJ41xaTYYQsfX0GW7$f
z@lg;CYNSj6w=6z{f&z2_xMczA!CnBdHh_o^pjK5v3`p07Bv79z3)Hw505_gKWPx-w
zB!N1nNg(eeB!RpTkOYe3AW)mV5Y%UE6liBLC~RjjC~9XhDBjLuP{Q<KJ6i#`{cKPQ
zYP3}|1#D-VP!D!bH8=@XgIY(`Ambgto#|>&>$nsYo&lvGWeueu`woCewgsgiCtWB7
zx$#4(z;d<+r2^a81j;~hQU($%0Pz*dK&EXd1G%jXl;FTp4rKz%*$T=8wzDOG<r_fq
z3qbM{!15Q$6t=RJgLEDM34Q<zDwKoF2a5)jgL(z!AlH?HteQ{`G7ltgP!4kEf^tx=
zqyZ#)0VJwW0W#}Dxx#Xm2OzBp6(ILiC~RjDr~vt{p#qfD3o1Z4Zv$BE1d!whu;hV?
zfBH*V5<p>EA+VLD5~M+)^1u9cR)I>8hJZ>?OWmPTpq*tx<#v_{Rg4STSua$#vtFoa
zXT4Cno%KT9|N7-D3+e?nvjl)#8=wJlEuX+*wgUp2**1XMuM3z2HnU9tu^K?Eg8%%R
zSwUHZWkWq<z;@Pzdhl=xxW)P*9OTvsr67@jdPad()`qRDjsN|Zvm`VsEN58&A|5n?
z%85cyH>43{;{$t8c4`8RfjNK@b<=<S?W_-C7zMVnae_i7p-EvmO9QC++t37xVFNi(
zikbity#OK#ng!Zf6k6I@6k6L^6x!NZ6x!Qa6gsxEY*+$HHwn$4)DI#)EKyj_<^W<D
zfCvQ;A<zsOUF!T-zn#UQ3lw-8Ize`RSPB{i>{Qs!G65`VunZ(B&}FclrC=G@)Gkn|
z)&~kJ5V4?3VLO{cA85$tLf3MZ3*8^KvwYYO^4)@7P!8z@Mf`ytaO=JIU;S2=10cBv
z`#?FlH(@*5hdCex3Vk3KG)w{6rLX~%ia<mHh-d&23qZt!DGu9N4EjL&4}e0>0Ypq#
z3(6d8L53LEgZg$8`nI!8=>NBVJB!04P@p|n0!j@D6F^26Oal390?089OTYr4F8hTE
zphUC`WGjd;0Er1q1m##T7sUFo7&OMV6y(T+i6FZUECxBFVIrt3UknnM0G4c63Q7eB
zCjOV-&Jq9?`2bdKu#{0?Ijh1_f$gjclR#a&4~sx{P67=OEdq6K7J;2UX*=75$^YKB
zvnWh$XHl5e&Z02Aokd|rJBz~1b{2(M?JNqjx3ehBVRC3?o7>7Zua#|nE8BurwuMXC
z7H!zh)&O?M0`P$Cg+-uZ-~o83Xn{H?nSpvi0+T?s)g*!KEDm7zKLEKuVKFGvY?ug2
zTMIy*od6mU-T?CPfu$f{UH}!;0TV&t^}$|XE6Wm4Ferfe0idw@02*Za01Cth6F_+%
zEI$D({{b{kHerdvb`}Nj(5M5*s0&L#t^gIl0&!sT!A=8*oWf#I{#nooia3X*AQv6z
z1R1#$l=41wDlBJPuvB3=Tfszu<!l$03T$T!=mI&*VWPlN7Eok0bb)f%GJ&lu6G4tV
z08YFIK!OP%=>s4~ZU8xQ!ZL6ofTRkLKtdlVh5{xCY-e?t0J2yBG=izHQD7?zco6Qv
z22d;?*Z^{H!bXtIeIT13^e8N6G1v$if!+w}g>L|51cl}8ED9^ySrk^bvnZ@;XHi()
z&Z4kpIg3CGC>6~CscQjgzAy(=6f}cf3Lb2E&<q+^m;%ayAl3oU*vo-tkd+hWfRcGL
zNLK?$*8;Gv0<f+LAhii|K>c$NOP~)_VXkE=*v_`W9^~i+Ye6Plum=sFtZipIux>ls
zf%TyJQvj5!3_wHxh$sLN6F|fU5OHAx$aNb)3G=|lcD4hX+Sv|lZf85NrJe1-)^@f7
z+uGR<Y;R{fu%n&rz|MBI1H0PU4(x7cJFusn?ZDpcYzOv%V!0ROmt_L&EFbo5XSuKs
z<d6rTkxPLCAeT)z^Jo6F0w%V0HiZN2Yzhb4*%S`7vnd>IXHz)R&Zcm*olW6bJDbAs
bb~c3*?Q9As+u0OOwX-Rl-p;0Q=2t!dP2=u0
delta 18026
zcmZp8u!RkTCrAsfWMJUA%m4?B(i3%z8CPyhSjEr8VYrz`-~_+c&ZeJn3=9lAn$83<
zFfdGRn!&=rz_7jXF&_g1!?wnCdJGH<TYf|{FfeT0{7;@uU^&YH4uS0~4KYjt%h?j@
z1-7$&sQ<^mo#jD2qri673m}s109a&0J(Iw8wgq7J1TZ^*;~#%Bi$gn$17kaj15-PT
z19Llz14}!L18X~r16w<b1N(9o2axdz93Z_Hnm{Ih2>-*st$`zum6M0Dsb8Ccf&2aT
zs8)_X#(LYP_ACYlR=cM5C<X>r`=)j;1_oA#rgkd^23E(Wb}a@5R;Q+RNd^YCOHJ*Z
z3=C|So7yTF7+77K+A<j!*seCUMKUn3U2AIdWME+RXlk=$U|{uZYSUm~VD)NhlVD(A
zyVcaj!N9=k)6`nQz`*L;)SAJ-!0Ol38qUDL>R;c~>c+spcE73Bgn@xIu&Gs<fq^xs
zsa24Hfi<|Pm4ShQ?Qv5}J_7@5Xj4lZ0|RSVQ;RPH1KYEv78?cz)`+GSEd~a*=S?k=
z3=FK1O)VgsqMDk^7#LWio0?M@7+7PPnu8e_SYw--9T^x{<C>Zc7#LXNo0{br7+4dV
z>YMo(7+8~<nravrSd*KYKw**6)D+3Uz?$0B<iWten%2~0#=yXu-qfVRz`&Z()Fi~f
zz?#|A#K6G7n$^^p$H2gv-P9P%z`&Z*)ab*&z?$3CXwAUDn%C3_a@yafMhON6*8HYM
zb_NF4f~JOY1_rkOO%3S`46KDs4fUZ646H>>4K54}?2Jtf#taOs#Z3*03=Hf{O$`DJ
z46G%M|LYhSSW6rK=Q1#`mNov5VPIe_Z~X7gz`$D3_#YHam5u*385mfr8vlzkFt8>x
z{%2!gV6AEVSIWS^&fWMgg@J*!w((yu0|UEY<3A?`23G0De})VUtTK)N6zUlmSY;dk
z@iQ>6$~FG2Wnf^HZ~U9Xz`&}|_&1t?fmN~bFDPP_8vj}_Ft92&{#9dOU{z`SE6TvY
zs@nLMg@J)pt?^GW0|Tpi<DVo323C#6KY<JkteTB~>=_tXwHp8EF)*-dH~x`fU|`j0
z{KL(_z^dE$yNZE<Rj=`PCPN$ptA69}2nGgLgT~+P3=FJ>jlV&`ZPfT%m4SiPxbe3L
z0|To`<8LMg23FI?Uxf?|tY(eB5*Qd*%^QFDGcd4PH2$(<U|_Xu{H4plz-ra_3uKdZ
z<1a1-23DKx2Rk`pnCp2OKe970u<<s2C}Ut?<7@no%D}+J-}oVzfq_k+@q-fs1Djyu
z2SWx1HlfB33JeTv!i^vJ85r0^8sFD3FtCX>zRzV~U=wS6AH%@FCf@kohk=1jqVc^o
z0|T36<9kpvOEtciVqjpCZhX(hz`!Qc_^yh9flapY9Vm~;)i=J2U|?XAZ+z#@z`&-^
z_|BYxflaaTojL;pn^NODF$M-U<;Hic3=C{4jc-dB7}!)B-zG6Iu&Fh^4P;<oQ*V6h
zz`($!(fHPYfq_l4@h!-OT8(c77#P^J8{gD3FtF(~zR6=?VAE}U6UV^7rq}q!mw|!x
zSmPTT1_pM4#`-tf3=Hi2jc+6w7})t5-*7N6u=6&)u3%tbVQze#!N9<j+4wqwfq{v=
z@wGbx0~1r@Yf}aWc8<o^Dhv#a{~BM5Ffg#QHNIwMU|{^+_^OD3ft{uCRU!ie%fhDV
z#S9FL-x^<mqT*`fD_aHz#`le{bQl;IUpKyzW?*2w(fF#Ki-CdhY2!;!xpAxUWd;KS
z<Nd~$ph&;d_|lz$f$?VJOHicWYkaB7z`%H|@uesO1LKv(m!RbJu<=C^0|Vpv#uteU
z46KhEU-&aHFrI0AVaLG0c&hOQDAJ!bzK~&HU_9RVf}4SX?Oo$@Q1W`&_&k$=f$?DD
z^YD5G28LIS&s`Z97;ZE^H)dd9xZe0&iGhLbW#e-}1_p*}jn6^3`9tHgd<F)FOO4M!
zh56;iXP`j*-1y9zfq~&%<1<iE__gsFC^vs=d<M#6-y5HnGB7ZlYJ8f)z`$^!@hK=h
z-EDm8#K6FCvhk@A0|V=y#;1x5sSFH98=r!Tw116HK{owwe3H+=z{b${B$k1J?MmYl
zZw3a&!;McY85kJ%H$Kr|U|=}Z_(Yt6f#GoD6E+40Hnzscr3?&g?2V687#P^jH$Dz#
zU|`ta_!yLOxf&mX(gpYSzx^ES2HRN@I6>9Q1&)C2YzCbF^f$8@fcOQR0n6DYXbEg*
zJHYvC|1twBfo&7G`dI6knvXIuFmQPtDPmw?eQ+d+fq~2ONDu=9>!Tx13=CWzM+_Ml
znDUM&Ffeer9|08;PY%~HFmUo81{D%d4@WUDa0(puU|`^KI&8+kz~ypSg@J*~^{@~F
z1E<hoMg|7f=ZEqc7&wIwfeP;zhkO_qxEv3GO0Cz2G#D7T>KzV=F)*;cImE)iz$tdH
zh=GC2?O-AU1E=`G00su;QwQxB7`SW?>M$@cO*kmUz`$j5kb{AN%lSYV0|S@!ffNP?
z=Hmx~85lUF4}gmIw+HkY7&v7P$TBc6O+CQFz`$j(znX!8`N;k(1_mzk{h&lXZNEDM
z1E>6cP>Oq3zh9Msfy;Ei2m=F`<$fjx22RC&pfcvmzIX-(PNjXm3=CXW`)n8(xQzB`
zF)%Ri+b7Auz^SqiRL}g_Th741Ww1Amfq`k>-cSYxF8#eO3=GV>_Zl-WaOv$;VqjpJ
zzgK{PflGG}s0{zLCzpYNOJ`3E0|S@I9&ZK)&d?v*xu<ijWUA+~e+f!ZcVCn;FtA>J
zk<7rrRQCc@j$VA>z`(%x_=P?L1DDwgIR*yChc9>;7#NQ}uV!Fid=5(DObeceGcYi|
zd+x@-!1(F8DFXxJ?dK{C3`}#L3o|e<{(8>Dz`(-rtdN0$`M|RT1_s8z&-@q|n5I9o
zVPIfl10`#w`t)a#3=E8~o^dcRFin06@>b5%GzJD1#;2hS3@l7fT^Sg-3Z9xWFmM$<
zRbgP@mU$}7z`!m2l!<|XTk1(60|U3@lXwOOZiy$p3=G`jPiz<%xW%4mF)(n8K9OKx
z;1+qp%D})a^tgb5fm`4)NG0E6kV>A%)(i~XT=kDN7#O%Y9*Z$BaI-yTVPN29c~ru{
zz|Hh1m4Shq;Snfo|2=YMVBq@m$bf-?>(?VW1_rJlk3bRp?O`PY1J{>_X$%ZppB@G?
zFmQc%=)%Cj_3ohw0|VEahoJQM>Y*S51J{cO^$ZML&mQD4FmOG25X->8_2>a8JwA9)
zZ_U8Kb?*Tvg8w~`WME+a^8l2}Zrlfj#I^e%qp#c#WnkcVbl;hQf%Eu%BL)V}6ZaJv
z7&uSf7hquEJaw<0fr0b%y<7$c&NKI77#KLu-UCJOxqDU&44mihX)-WyUbrX0z`%L&
z9y<dA=cT)43=Eu?@1`;^a9+6^0@8f-F39L>ca0esIIrJTW?<mFaTk<}Zr){NVBoxU
zr+|Th^Y)!M1_sVMcYGNbIPc!EW?<mFcSnnXf%E<yP^x@zhl7EE^Wp7s1_sVYx6>FH
zI3M2*WnkcZa@&Q0f%EBYkjc+(D={!|KEDle^ov^{dtctlW2k4~e03|9fr0b&EguF3
z&NsI}u6}z9<mz{~K(2m&3*_n#H$krccoXF6Pd7oi?(<DY1_sVAHw_pVIKSSMV_@L?
zc9WNZf%E%~8U_Z=A2+fY7&w34h-P5m{B^^Nfr0b)4NC?F&ObNQ85lVK-VkG8;QV)k
zje((_^Z)fy1_myM>&XlZT#VO)7#O&it~)R=a4}!kV_@K7xh})Nz{Pr<i-CcQ?HVY)
z*{`KDFmQ2P1EmbkYoL_Db<L20fs6Z^JOcw4&ow><1}@&KwG0egd{=WA7`XVaMl&#Q
z30(DJVBiwGYQez3C3F>(^M$VpgGwQhs|*YbT%uR<85p?4uEa4gaEV_5WqpY&psX)>
zMVo<vOX>=!{E@x_a)iufkRxO-XD~2u$z2X(VBnI!3`%qgmqA%y@v;&F1DDceP@+=?
zbse}=E`dx|y#z8@?Gngj^-G{Mr*TP>fq_et=aK{i1DDn%b_ND6?d?0}a@jM9-aiU5
z#QUfaD+2@L0oHZ~1_s8L+j$mn)w1d^Rqp{6o`!qG85o$B?O|nLU|PPrgn@ynes>ZB
z1H-=EfeZ``yLLM;Ffgs&zI7?rD;5rp3-g&77&tCYU%rYfyWV4tH3I{W=Nv5t1|F|D
z5)2GH-gDR)7<hbUmoYH#_|8saVBqna9mc@G<3HPtfq^GrwiyEhPvC4d1_qv>*<uU~
zJi)Ws7#Mg$W`Wd)&H||qn-$K$z!N^pgMoo3VwMF115e~Ebp{5Ws97NO(X&A6V`i2z
zF!03I&rD%p;E9_V%)r1CKhueUfhS?6Ap-+X;!Jr42A-sud<+ac$unvh7<f`<<S;Ps
zq|S(DVBkrc;l;qflRm?efq^Guh9(08Pv#6s1_qw285|4@JlWGhPRW^`%)r2tJ3Wwr
zfhTXe0|Nt3{&al?2A+cHvJ4D7h0}Q$7<h`N)mJkx@DxwWVqoAYnHI&sz*9QSlYxP!
zY#PYb<<mgEte7Usz`#>Ejg^6cr)nz5)zwo$j;@&+!oa{&JJp4Ofv0Y&2?GO9{ZwTJ
z2A+ng!VC;NjZ>K!7<ihd6frRHG*3xlVBl$)62!p3(>ev@$+js*3=BN&Q<Ul%7<f9S
z2r)45bWUMnVBqPRT*$z{(>*zXfq|!IvOfa@Pw!+~1_qwK$=VDIJpGfU7#MgaOa}RK
z;v|qSCrtu5W%4AD(NiXYd^vTJ9s>i<v`HXePM-ww<&23SPtKf}$-uxfYa%FWW>0iw
zVBncE(U_s0foJYSB?bnbc@qU07<lGS06A#Egj@y&o`n-YLA_`KC_ENVFlS)kSu#PD
zfq`e~1Q7-Xo@En2&RyPLz`($>qCbv-foEmEF9QS5s(u>=2A<XZp!Bq+AC#Wf_Jh*X
zx;~I|*Y~9|Fz{^X1BKkiK4%7odY(;vprF{?r@+9#v!xFd-&=b@@x84V6yMu>L5|qb
z3ySZZy`cEs)vLk4z_YtooPmL7PcIt-1JB+bP^9eZ0fof=9#BXe=mCYq!5&b2AL@}~
zVBk62!^^<HbEF#-5=Xm1(S58t5)@^}yWJTWcusVKQuWDh6$S>LQ{ABWJKYWP-<d9u
z|IT*BGcfR+>+)k@;5pv~ijE6iIt&av7rUex7<evqaWOFPT<)x7VBlfyOlM%=Vd)HI
zVBlfx1f>kNPGbfJ9`;U97;|)j!kDv@fq{XCt0SL*frq=k0~B;T9X<>UJiHxN3=BMc
z9U%YlcYv~rKnDv01CL-kC=m&@gVKa>JIE0t?I1^pwu2lY)(&!ncss}u5}*z_k7Qd0
z0|Sp#8z`ow+d!FCrp=Urfk(Ct<UP4IkoV-<K;Bbmtp_DH#a58fO0A&errZiLTBQ|~
z+*DgZ$xW@5lYxOpy`_SIfk&eS<Uh?8kkMK#ppesU0fn4S3n*piwt!NGUJEGY>o<cO
zZP1*^z`$eJ3^LiM*^YsM$G92fXp?4;$)?ThpyX!O1agFV6UY%3O(6eSHh~h6RTC&@
zTQ`AX+NKGV{cIaSF>Tifa)f;&$Po^Wpp@*`2uedvji5B-+z3iTE})2Z1*vlb#f7^o
z0|V<{P^%?Rm4SgNLx`30JL6>LLk!zF8n}E|>x~-ci!(5A7&p#mV_@JgX`ENez`$YJ
zI4^~Pfy1nEUN8d#hk4^XCk6%%i^h4N+Qp}F9;hMg+c=M(fq~1fac&(01DAi}+*}3*
zu7Jk5pe99N<6KaiBB*gLsC+kWoU6saz%jdVt|S8kS7_s04h9B}xs7u`?TYaF#yOyt
zMMUEqP}5>T;~W<T29AY|b3j!{bmJUQ@gLJT2ULl~HqK#SVBlEVI6I$#fn!<YY>-U}
zjk7^EB{t5sVqoA{**IH+fq`RH<7{yT2CkIG*{lo<T)B<2N*EY8);7)pwd>OxX9X}Y
zaAh>kvS(o6%51Ek1*%)K8fVEeFmPoz&f;NU;CR_Mvx<R%<3;1lOa=yy=Z!NX7#KL7
zHO_QnVBmP#I1?0>MU69+85p>Q8)phKFmMYt&SYR<;O1|fk<Y-u&D%I5j)8%jyK#me
z0|Pf_;|yB{25$Do89EFM+^mf=q!}2vnHy(tF)(m5Hcqbx)uI0zr-Lfdzm3zw85p>J
zH%@nBVBq@MI2~lu_r~d<*4x*{>7YvbbK`VSPvv9dv;qbOuJ?`8;u#pY-ZoD2XJFuZ
z-8c=@QFz%nO_zaz>v`ieP<!EN<1|nM@p0qS8U_ZghmBJ~4T1ZOQ$a0(yNy%5K&`>s
zjZ-Zd7`SdWP6bt{*BhsbF)(mlZJY`Uy~~YLiWwL<EE_=uIfqr_lmG?>4(rA#whRm$
zHjPt2!EM_(1(bs98mF)_FmTv6P6lakXap7H9FC2X{TLWHoEkwzIfrxOWL*XZ4wuHs
z@(c_du8ouV80r}~+!`m<FfeeqH%<Ztw@2foa0Uhr&&Elhl;G7k$&i78!@F^kA_D`5
zPvay31_ln_#z~-*;MX{@fPsO-zj0y$0|Q4u<3wKu29ChSi8c%j96^l}wHX*Vf*U7F
zF)(n1G*0AXVBiRCoKV5Qz!BCsA)SGNBfN1!7z0B+M?~WUR|W=-$i@jK3=AAmjT4j^
z7&xLECkQbxaKtoD0NE7V*bho`agCtTo+G{yRNQkUG=j=|j>JaLP$EZCV?W5I<i>t3
z1_q9l#=c4h29DImz6=Hij<m);keAXM``j5AI5Hah%orFrG8_9;85lU~vl{zE7#KLR
z8~Z>_lbpt0Q0V10_9inhaO5@i1~D*j<Tv&@GB9uyH1--WFmMz$_R29Za1=H6g3@Yn
zV-F~;mNfQcF)(nHHugj@FmRML_INQcaFjRpSTZnhR5bR0qN%d6M}mQYqpGoooq>U)
zy0N>Afq|o@zOg%%fq|p8u{(r;fupXm+Zp7j#%?1929ActZcwN<Hg<zTy{WOQo`Hd*
zxv?vkfq|o?u`7mwfupst%bS6Lqph(El>gcryEGXXI64};KsI$Yc7ckNuEtJKk<#7R
z3Gz};V`m@(14nOTrvn26M_*%or#=G%M}K1{$WId*JNXzGI3_lB)G{z|Ols`NVPN2X
z*Vq9{toe-{UVQZoEDQ`B?;0CG-h1EJV8Ot^@u9Inoq>VlV`GCD0|UpW#s*L-{QMu3
z=fC_1S^4!p$i{E~?HL$2zW>)_VBq-iUxtB!<L7^FQ2hV;2a2lS|3ESI=N~Ad{{92y
z^nd?M85lVJ|5IUL;AHqG%)r3O_z%=KX8K#iz`)7;H;I9PljUz90|O`PUk3&TPPV_G
zZa4d1PzQkHFQ@~+`3KYi;Q9mV0C4{SbpUw&fI39He?Yw!zCWM_b$uFWRFEt64-W$a
zr{Hf;CQbeg%A-lYK|Lsu-=J=e=x<QQj{glRs^WgjGB9vT{06C){8i1sz$x`Bi-CbF
z>Q^KK16SlP4+aKK*<a=i44iVm)EF4J!hVS|FmNjT0%hiqpCt?oT){t+85lT~e}Xy~
zc5**Kofp-gpw5fhPXz`BPW7Llev!sc1_lOB&FyL3T=k3`=Ngv_Gca(RpZ>Oo%dTFl
zvE7b=fm6G&U6+A@Q>PJB4Rh)?f=0$U^%~nM7#KM98{0sAFN4N5Q0L3Au?^JwGHPrC
zb-#=o+d%y<lg2hd1_n;k##T@d%&f5$)NeFzYz2jrMPsWc0|TdJV=KrbR*kJ{3=Evs
zjjbTB*wi<+f(A-#8(WGQ7&z@3TR<^k-`E0*3WvrPP+T}RwtynTsj&qVSk8?t+zbqy
zE{)BV3=EvEjm;Sh44iI_&EX6TobHXyZVU{Z9*xbW3=Eu}jm@Cw_G)Yf#kY53GpO6?
z)7S(Wz42{q0(Ct78iSiaapK<ys;M~x8k@8k7&rqPo1_>RID;CSK$Y8*#>O%R2Ijww
zjj0R_%wHQDK|S(Yjg6qeq&tm`h71hMUm8JGHpi>RMo`{*y}hQ7tCErXO=ANnbG>bB
zh}pJ*>jhi=na0Z;3=C{%8!v$dZO=7c0u6m}HeL#1U|{2DyyVEhz;>bW5@_h_V&f$_
z1_n0P#!I{m3~Vfo7poZ<*q9qHW-&0ZF*RNUO;B8Kyy(Hez;>hYB53UOX5&S51_p*B
zjTc237}#z%USwflV7t?J0W^;NyYWIY0|VQ=`o;^OVX&W#7eF>WXuJTj>0#pqc?Jfy
zM~xRiQ#)rH&(|<8usvx!pUuF)_O$UlXxiXY<9X1u!N<n)Ae&w^o(GMXzi&JbvguXh
zd5}%78_yLpFtEL8JO>)(ecN~rWYMd}bD&Y)_l@WD85r0;G}fO3`RQZhIgp<|HJ%08
z^ttgY$fhriXQLPx*uFNN^<-dR`__2Yf`NhUd*fL(1_rhtjb}v|7}$O`o@HiWVEfg0
zrig)o?RVpuL<R=7KaFPs7#LV@H=eO)U|{>#cm^~!f3xw7ECT~OL*p491_svaji;*_
z7+9}0p03YiU|?r%JPjJAz0!Evje&ukwed7)mgZ99X=MfmcJ{{8pdrl*ji(tH7}z-*
zPvtW(uyZw@0uA(?Z9D}UJU!ER3N%Y|y73ff@bpyUDbN5kPva@jRLF_Olc2$_<Bcal
z6BI`pPlDogRpUueXs>QOX#g75UekCI6x?eYPl86{*EOC1jmEEUJdwk|z_y|BL^J~f
z+s4KdUJMLun;K78GBB`hZaksEz`(Yp@q{=71KZZd6Ko6&Y}*=-g9cBxHy#J2pdF3J
zLBq5=8;^qqPj@vQ2Mzo0ZafYeRNvEh9Awen#$)viaSUwx8jpcS)%Q0Z0}az2XgmfQ
z_dnQp%!Yx1?NH+}9R>!r!;Qye7#P@&G#&#DJs)j63L5u6)_4>&?ti@TC}`OKMB`D=
zu>Z-%qh<^YY^NHJsxUCHo!)+MCszz}{p`j)h71hsa~k(3Ffg#sZQR4pz`#DQad#a9
z1N;2O-MI`5><b!q$1*UmFKpcH%fP_CsBt%FP=9gbZqS(ilE&Rq3=Hf`8+UUuFt9Ic
z+*QHAz`ne3S2_a&`-;Y0VGIoHD;sx#CYM$<?lNLvU|-$1OOb(reNE#o0R{&4we^iV
z>lql>*ER0UV_;xk-?$TG(}u>KAe%Ne?zClKVBgfZQ-^_peRJbZX$A)NEsZ<585r2N
zHtwiqU|`?YxC4|*wm0sGU|?Y1(YV8%fq{Kz;||d5!LG&~Dhv$lyBl{1Gcd64Y23lY
zz`(w@aeE;H1AA!W_5=n7_OQnK?S2dl?BR{uL4Jy8+^)sIz#iGSU4nsuJ+^T>I|BoI
zbmO)%1_t(+#%*Z~4D4}@+d>%_*b^GJxiT=Y$2V>>W?*1XYTO3$Q)1&bP~hb>Zmnft
zU^8fZRLj7?p4_-Kn}LBnrEzN%0|R?%<5o`w2KKbZtriRn?CFhL>oph{*fScpiZd{<
zXEtsHS(w$h1!Q4%<Catg2KKzhEue|B+{P`A3=Hh~ja&2?7}yINx5zOtuopCL;bmZ8
zFK*mi!@$5^)VLXBQ%U1ykWFQcn?W{}Hf}a&U|=tA+^ovLz+Tn388nkp(YTqJfq}iU
zaZ?c}@T(g)B{DFu*EDVlU|?XcZQNwXz`)+zxJj3RfxWJAlMDj`dwt_3P^dRFZmeQp
zU~g>P2nzM4#*Ls*Z*Sb_!N9=Y(zp@ir`E=eY77kQZH*g685r0*8#jV%>S){mnzQL?
z+yJtut8oL!qVC2G_6(^E>=PO{=rJ&`_cm?-+0@s#fs28Gy}xmNB?AK+W8?Y^1_t(t
zjqAf17}zH@t_Ows<i_<T3=Hg38rOqLfvJt_g%}vvr!}r;WME*Q-ng!Sfq{KS<GOeT
z2KJea>p;;vYy02*TqoG-o0|4YFfcIQXxa-JW^QQOQ^CN%yuN7<Xqx73)1D{>2BzAk
zJ>Coq%p02a*f20K>}lGg&A`CCrD=~e0|QfK(;jXH2F5Q<yQ>%&n97@WXEHD_l{M`K
zjp?&A?FLO;l{D=(V_;w^ZrTm%?-e!e7GYpuDs0-#!oa{(P~Wr*G(?u)v<o!6p4PN0
zh=GCmbJH#-1_qW#O`zPtl-;xoG-#jGv`dJAf%#q2E>N2N*|ZZ>vi)cRWe&#OO*=u8
zHG7(NS}`y%?rqws$-uz4uW6?Q0|WDgrk(5z3{0I(J3v+7#ikvgD)3U%jt~Y0h8Ios
zJ6sqTnA)0l7&9<1UuoK*#K6FOwP^>)rt3{R7#SFtZ!~Q$U|?WsYy#yD=9^91K~o^N
znzlPIFfiX~+HSzWz<jr9y8;6PQ%%!$0R{%<drjNw85o$VnzrRLFfiY5+7{2iz*Nz+
z&7XmR`9ae*dj<yPhfUk`85o#Ko3_=<GcYheY64{v=EqH2>lqjr-!yFnX?)VOHI9LS
z@k7&AKL!Tor%hXJ85o$KHEq>lU|@dUv{j0Mf$>MvR!#;6=9f)d${84#Uo~w>V_;x@
z-Lxf?fq{vkX^S%h1M{1vEk+CsOsq{?6d4$p+nTn3T-e^Uxt@W6xua=w9*FL2+8o2c
zz}(fe85GUkO`EM47?^vSHfu64F!wfX1_feY(`GgX2Il^zO(hHr%oCb6B{MKEPi)!*
zimgdan?PYPxoMLg0|WDvCQ#;Jp4tS;9L&?2HdZn)Fi&sVn8ConJfmr2I0FOo%%+WQ
z3=GV(nl_p;)H5*8ZrZ5Kz`#7GX(K4q=QeEwh5Edv4FwDg%=4Qz#4#{1FKF7}%fP_A
zuxW!e0|WD-rVXG;fyGT5Ku%lIv;pL_rA_Ng85o$CHLV9tKP_)sAI!kOyrOBn69WVD
z%BJ<8CeEs+^$H9O%&VK$^D{6ouW4FW$H2hEymtD*lU(NYx0=?1+U94Q)&?>#u(&p@
zwP#>pacf$u%fP_m-n3SRfq})NX)QMc1B++Vnkohc7O$o?84L_8-c4)585mf6n%1~6
zFtGSGtubX_VDW2Oqr$+z;@`AJn1O*MplJ<gwkNP@bs+--OHkA5cm@WR;HK4n3=AwG
zO{;Ag7+6B<n^x;EFtCI*t(Ib7U<q$p&B?&P64A5@G#wn-v<fus6V<c|H18ALw918n
zfhDGCl`#VYOKj6BB?bnTxTaMC3=AysO)Kje7+4aTR^~D=up~CEjAme9Norc@#lXOl
z+_ch?fq^BZX{81O150YtN^u4Tmb9joYzz!6=}n0%N*NefGMZMTFfg!WHmwL|U|`8=
zS^>(2*-a}985me{npP+<FtFq{t>9;1V99G*UdO<|lHar(WK%)Y@)!mNmcpjx-V6*Z
zMNP}C7#LWJo0e-bFtC&~Eth0qU@6@mewu44V|`iEvT_Cnmhz@$AU{<!Eem5{V5w|c
z1`55Zre$Uf3@p`6%TyT{SZbP<i7+s*)HW?+W?*2cYg$^wz`#=9v^0T%fu*5osXqe)
zOJmbgQ0O%^E!AdVU}<hz3bLuCX(`B0txZcn!QIxh1f-$8X$dH}JL;R3*f21#bT%yk
zxvi^d2`Ci0o0hOMFtGGAEe1KQw`p-E0|QH6)8YsQ2A2M&#UQ6mXj*K-z`!!GX)!3c
zCp9ew1^48pMYRkJEK`~mfdXM_(;`qHOlw-?%fP@gy=f81q8Uw#K=C@WX%Wb2vzqD`
zaWF8j%x+p(#=yWbr)gm-0|U$4riGx0o!7Jw6tVN07J?R>G&L;*+4Qh!p&$bTYh%+w
z&=hrb(*n?{oBE~&prtK!O$$IvTf&<bfR?s|G%WzN=K`7*NHQ?6dN(Zq&4#)+%`azQ
zV0CMnpT@wz>e4hHytKu+X}$}nc?e!U#lqV(ALKQ@ruoVY3@rRj^Fe7=plLoR%?dWn
z0|lZ`(>zch3OCIQU|?VoX`1K2z`!EfG|zy6fkmtdH2lUQ-UJ$cW07c@3knj+rn%V+
z3@lPjbE6m-SfrcgdNMGu$TZEh1SL<|rn#WNmus3U!N9;G-!vB#_zF#+@i!L5ra9>h
z3@l1bb3o}rxoM6o0|Sdn(;ScsRh#C3f<&zeH2lV*-UJ$cW6@{=4ZpEyHq8d*Dy^p3
zplH@^nhi=9I!&`dfv?*%TbhA^MXzZ#7ehS*i+<CrN(KfNgQi&^n+%&~fdb#CX%;B(
zjhki}F)*;0G|f_EU|=zAngxnxv!<CKXPY<8%x7R=v1pnJvdOY(CdekMrkNm{tea+n
z3JRO1nX(KFEVfNEc^Md3?3!lOFfg##H_ZTrg+tSfNCpNq7RRO;9t;dDPE9k+85mfc
zn`WpnFtE5Z%@Aefj$#a9Rb^mcU|O@C=L45CYdyo>rk{Qc3=9XGeuCzOS2q3BW?*1i
z(ex9Pn0T6gg3=Oq(~mOHWK`1+P+H<@`T?rgrZoL<W?*3a+VsPSfq`La(+^Pnw4~_=
zKLZ29w5IR13=B*Qo4#i=Ffgz*eFxR?OPjuXF)%R9X!;H+BsiMBgO)qg&uscG&cMLD
zr|CNz0|UdXrf;CSdT!G<(0tbHrf&fZ3=CJAzS%P{FwANCrpLg*G`r~=XqJCf(>ERl
z2F8m`U#l4y80I#8&0=6+n$`3*l7WF?Uei|(1_q`XO<ye-7#QX^eN|&%V4B(VRfK_o
zVL{VZCI$xP?M+__85kHA);E1gU|?WA+VsVrfq`LB(-%7i2Bs-ZUvwE57#25u0hP(D
zO<%Yf7#Nl`eXe9+V4BqQIfH?LVQJIna0UjZiA|r~7#J9qHGMW?U|>Ge^cfVk%bPw6
zGcYjqH+^PeU|?9$^r?t}fvK<QQz8Qc!^);lATPaa`ULXQs;2r+AU`c``XtA|z_7aM
z6CVQu)1s!2wG0dlYnndhFfcH6HGKrFAY9w@(TjnB@nq9SO9lppbxj{N85o#4nm$T0
zFfgod`pC(^z|`LKp^|}tVMEgg&`O(gO&`J;7#KD-eQ;x7U}|mpV9LP2u&L<-XoWya
z(+5ykY;O9%3R>H9dAr7UuK7&$YnvWhF)%Q#YXVKnGp%oW44P)#(Day%fq`jb6KH0h
zX;agqBnAei%}tL27#NtgG(7@^*Vd*-It&a<+nOGM+H2dJ9&s@+FzsjpP0%y#Y<dV<
zXtb;8VHg7g)9$8+t_%!Jdzv1aGB7ahZF&fD&Az6GLJSN{`|Fz?GBPkQ9cX$0Y7HH1
zdH`zG9BO(1TD5Sv=>aHt9%*_2N}flX9!N1TFdb`p0P^?oru!8P3`{4Q?x!;_Fr93=
z53=c0(|wRlr<?AZFfcHkX}Yh>z`%62=|0G&b4~X_7M*Xp2eRlw(>;(y7n|zufo!_e
zbkCN7f$4J7J&>QSG~EOF>1xwGke{wK-36tA>rHn-Hr;5t3u*@4Y`P1w=~mNSkWIIn
z?t+?<cbe`BGB7aRZMp+$sNHM2lgGfobie6NECU16gQhz^3=B*Un?N)9OplsCQ~6Af
zo9;+SGB7YbX#&mWGd*nrP3JQ`Yr37vz`)o)-Ecww*Xa%hY%}Vao;TeNVPIf-(RAC1
zfr05|({0d7omWk_LHX}>(`|kR2BtSnw?GY#w@tTl85o$}HQkC~U|@RRbjzE8f$2lj
zElUOlrjJdx)EO9<J~iDEWnf_X+;oeXfr05u(@juX{n~UB6v^M3ZU!<iFnw>j37Sy;
z(R35kpsfGd1e)(>`qc!Q@Mrqn1e)<@`qKoO@@M+nbOV&r|22Uo{h9tZfoA=g8Jccr
zFfcGPHr)Vabf%^optclq6KLX}nWgDEs4d0XbUlQDftju8I%pjYd((ALQ<<abI;g44
z*>qiyfq|K;={l&<#$DfZ4YZ<#r|B9f-|{wH1GSa;ny!J`y!=hqK<z_;rfaec49tQ}
z*Fc@8;HImfWnnE%S2GzHm_IgM1+@=9G+hPR^uFn;J_7>_OVd?Qk&@MPm4|_WiKFQX
zsH4H$bOjX2j7?WU85kJ<H(dcW^IkO7UomE2VEof`MVWzt@n_Q&(2BM1O;=bL7#Ke{
zT?VaK``C0DwA$uv(`7#f2F4dnm#rBX7@sv=26Y%7HC+a^svk66=44=Cywh~4l7WHo
zR?{Vr({49iieO-1yxw#Pw4mo|(<RV~o=Z)aKx^?XG+h#5U|_!1bg3R>)7hqrB@7IV
zr<*Q<8p)TNE(S3$FrH|-=*Ympc&zCnsKc<M>7qOX1LKjVi=Yv!*G(7d7#Nt(HeJYN
zU|_h}bOF>FKizb}n}LDhR?`Jb1_tJnO&37XbfW13D4Gs7T>wSXv8MB&m2T&o&VyFE
zU2HlZT+hJ3e7Na6C@>B+oi}1&U^v}$UXg);;cC-)P(1B#IuEMz&orF_^)U7}odd0@
zJJxg#RL7iXI%mhgz`U#J94MN0Hk|`S)3&B_po08f)7dHp2F628XF*}HwdrgG0|UeH
zrnBx049uIG&YCkYFmGx)tHvPBz`U{PtSAEm!-1x=pyk%Po6dkb4C|WCByT&Az$UPr
z?E%*>{%sB#ECS0}0<;CTvj}K|7Q!hc3M^*}uo76#W}ppXaf4JQ{NrEFQjj39oFyRv
zq|zF+bb5l-KmMgG)&k2}6nH>{jKFr53$h?H5_kl*vo+*`G+l@n*v?YG0}_28EwG$z
zf;C8r2PCy2USK)P0tb+JGN6UsA9xrAwzDO~gBD~5#DjDQ*a&QAbKnIjUch@{J4-`7
z$leA`kP3%*MuDxYyo>_vY#aF6**5UEvuyye1>4y+2(`0q5N>DNAkxmZLA0H1gIGJ;
z2Jv>b4HE5a8zi^0ZIJr+emTnrHG%Cc57a;=2B?8dRImrxIUz@2Ih%uwz;?C^5La4(
ze9bMeoaF(?mj|o_wzAlO6bkSPY-cO50XfbA<cR=YkWmwOK}I#?f!GUd{>g7=Dc}Wp
z?tl%*a}yjuvJ3b?vJHIy__wmifQ&Mb5m?UF5GSyltpF4}0$LzL6J!*Yvs_RIg{-Z>
za+U%OP(X5nbWV@~nfoCYr1b#Er4PUw6q-S5<3Q1A3-VelNbLt1kSz%yr2_H-OWEQC
zwzF+e2f0E(79@Wl7G#%!tiX1b3F;tK4zdE<*%V^`^KWNOkYyBD&L*G%S`?`T(sBW8
z<N{lek#-=(6J!OJvnj}d%mkaWK^Ei$4T0q>6JkN}DhE=u0VE$F2ePLCBw8Q`3Xlg@
z|M{1*e2^2^&hkMM<dOwo6$j)5+F2SD+F2SD+gTcv+F2Tu+gTb^ma{adUf9lJAP-V`
zK@Q}Y0&vtlkOL(`d4c6D1_}b(Sq#8_IG_efX*QrhRTtRKW?&7ndjlvAKUfKDXE~tG
zD6pLMfULlF)(N&?SAasf0Oa-pP*5v?SPr%V+gTD8f$R&=0EM?h9Ee?D1u|;_C^A0S
zfCLo4VZQ(r>=!f?wzCw}GYKqZ(^Oc_wm=PJH#o5_&|osy&Q_oa)~g8$p2Y&&Sr%x5
zg2w=qjuyy*ytKg@B(MOK1}1>BL4q8}3Ii>WAGHLQvp9e}`axP?DGMkdH#mS~AAn;s
z0PNBSi$OLxXoHm6fYL1}cW%%USjxg9u$^T?0?29Fprj2>@CMu<>l8RaIT9SC7r2=O
z+SwAc+u0Iy+Sw9x+u0KI+SwBHm$M}pY}n4GPzo~LAVOd%i#;gX?7;B|BH0YU33~!K
zN(vM}$`lj?wz4RI%o8wdXA>}LXA>}PXA>}KXA>}OXA>}MXA>}A&L&{tu$|4p?w|g0
zmI8T!?JNy;pn&=y4-O4*5_3=xXlDzsSk4w;`CvQS0d9~?131@Q0OgtlP)X$gDx?&+
zLDm|85?=#1s3@`mInO~0l<xu{*%TD{A0VDy1j@YNM6Cc0^Z?M(Uk7VYK+AzPpjZoR
zX9=(dnb2VUAGG%boJI>AKz0Ox0<$0<6!;s!WyAxJY6Gyq0v?bNpai4<ihv6?3fox(
z{J=`pKzc9O2`p!607)&7R@lzc04_8RNdJ>x&eEVEu#^Rq{sKTHsemm=Qvn~yzXrCT
zh)S>(*vh5>;y2iW9Jayszx{TW0(FqO54Iq~KY;9YPzU8aa5x^Y1BohtQg;F<<urhZ
z4Io0m9+WyjDi!)cW`F1dmG$-s+u1Ix1KIGP4=lP)U^!btlfZVi0C2*Z0Mhyaq}3r7
zl+i)l1Dc?6i37BMril%d<Fo{}vNeOuxS$0#0~D|gR{!|hSrQ!ESrVMuSrVMvSrS~@
zSrS~^SrXjZSrXjaSrR<9vm|&jP1w#R5CIB7KY^_*5g?x}2nYG$LAbzjmJ1*vArzF&
zLqR$CLx{k3)&(J;D&T`>JKG1ZcD4`R?Q9=>wzGZk1?dV10TqVo0_`jce(fv@{_QLZ
z0oz#=0+|}Nvjv3z^WV<$ArxfChH#L37ZiZpdmvn3D_bGRxeEf9vn&Xju$)C92b7<J
z4VJSc<baZeBS@Wtqri5y1;HSV24DdNkidmtP*N6f6j;t80J2;lS7AGgLkN?=RyIeF
z(tuo0%oT(%DlBLF-~cM6azTY>2uSV$I6Gf}uyaARTPUN!b~c4PP+9B{`d@x2O999~
zd7uCf1-T(150rI7|K%@b33FJ^5)h`aoTULoYzPBofH07n1Noo|JPee;9^?xwWeHc<
z&Y}<kl2Hg(*v@7U3<{`%V33&&Ah#KWfJ(#!kmD61K=qEDKs$>=L_3Q^WIKyP)OHq!
zXr>R#**?U8s>v8oSpv?i3E;pJhy^8>22i;Nt`8InK;ae31hNQR!W?J<*?a-yCWj>;
zn>XZxQtJ|s=md~x0JtD5$Oj1|fCL`MfRs6alx+ZKdj*haK-@3>Z3^0;w#$V)kSpUr
z<y#!c0~7c_`85D+WCEyc{Q%B03SfZ`pi0(36XZZ}k)Qx-gBXBJ2mlq!7r@0hC`B7A
z2DzXiUSK)f0Z<ez0GG!bazV+(0i5X<fO5}+cqWDAYz80|36Rnx0i<F9xKeOPP}t7$
z0W9z!2jq(fpekqrs2Me(66D?-kR1zhK!KP5N&yXE0Re7-t!#;)NDs&XdBq_I<gE)_
zpn_}xHz;KWByML3NMf3>oGkzp10M>&hJ(WTLIFtafdY^|1#o(502lQM3Ls|*D1dA!
zC;*kp50cv19wfK3JxFP1dyv}B_8_gD?Lm4w+k=edY!5OwY-ejI0M&X2Vps&Wb8LwD
z!@r$nK@7-{2{9nsHh_|1K@6yl1aH$bh!JRKn~=4gZ9?|H{^cwViJ)8x@lK+^QZ`Tl
zT>uV)hG2!|EDJ!b$PK}uba5aDlr$R>1eUUZ(%gp}P=N_<FB&9(T7S79CkrHiyp@p4
zsIZ-F0yu*h@POR104#d|oSYwofWi^n=$rs*seQ;bSk7_)R8%W~3t5Lekh=xq1-7z)
z8<z!n0?XMRfZ9V7^8VQ`XPE#>LJ#toKowFLNT~rR%@u$%Q2;2-EdYxi0A;NPaQbWj
zHI)|RgVa6%mAnf;g`xwfMbiLon|%Q35&%bz11PuxK;@+Yh_wL33IMSjKxLXhA*g_9
z5@=^JC~RjjC~9XhDBjLuP{Q<KJKF<!kog9spav+25GWJa%2EbOI2+19EwwUGLTP9K
zWm<<ah3zZ`V7Y`cP*Dsb3P8jHkkScdAd?Q1flLA!QVufY14u@p9305ypdd8>vjf0v
zhjNgP3m_d6%0W?G4od9{%0Z<LSn2>sbOTteLIp_egK|(g4HEqTHeR3tR3KCcEM)^R
z3@QwkvlUc;N<6UY2^F9WQUS8I0W5H#0+cu^K^1TXs9dN76`YkI9~xBtmtW4J0Fp|m
zG}z7(PziGVhDuNzR)QL+mH*|pvno`9!r?=u!EzRZL{M;6ZD%p4W?ZnH)uEIzU^&}?
zQi0`c3rZEXvt0nUWj>S&w6k2OZfChr)6R0Cb~($1x`yp66Tk&wK*N9jr7Y?S%ULFX
z!abl~U@J=lV?aCWf`;v^3mX6XFK1Bz#oLEQh3zZ>;Jo(09ux)wO$yst5*%0swsT&H
z`OUwa#h?jP3W7_%2cTlJpa~Q?4g%ZRCN%xm-_H7=>A(DT7J+6^8aHSL`SXASs6h)V
zi~^b!wzFJt_`|;~A&#G=p2MJdGiZICe)DF~A~wC|&5{fZ9J<Y$LCdLhnm2(~h-o)(
zN@8H(&}s(F2{Art-UM2qsoA^<G@Q!Wyh(|HfkUHtlOO{FhkElSP$zU^^G48E_W9<G
zaSRL`YRwx#tL0RiH-c8nsWflYW?*1F*Srxl8&c2Syb-iqPPutQIRgWSQu7AT6yE>l
z4IvB+ENsmioEaE66q`4IR){GyZvf3Y3pZ~7tzwaH-T+!HC)d0lv@TD!d3`(s1BXoW
zdOrpR4(aCgATLQZuh(H<;E-%yFU`QfA<?{^n}LBtym=jH4Vzf=x-13;4$=DNb&(7V
z93su@JQx@_gqzoyGca%nHLnA$@)B%b2U=?=(7X;57W~a?K}*Z{n%9EXu<<sp1+5|F
zX<iFjImq3-)|i2TgR6NhC@eUe*MeNg(Yyw<hK;>>O&$XS2V3(RP*|`wuK~G`rFjh~
zESQ_?*MLHusd){^iHyx_Km#Y=npcBnouispXEHFbHZ-pWtq3{Uyc)D3<a_gK&`L3e
z=GCCN{{PLZL3928npcD7P5(Bp0?qaRX<h}I>;K)n3N-8dt9g|j0|UdP=2f7PRo3QJ
zvY;)#&8v7plLXBx>uW%v*t`-nT+G?LG77XSqj{w#XoYF>O3)xKPxDGO1_lP+=9QqX
zKVS1oP}iToc||b;1A{>G3eae=VDk#l(5g`L3eeE1aPta~O(M-Jq!}0(M4MM|F)%QQ
zH7^H^kcu}i2aVxMG%p8@kV-Z$cLVJdlxkiM8X}c$UarExz#!AST!?{zLAH50C?&}?
zF9U56ly6=J8qQE?Ugpcdz@XT?%!Yx1L8*C}HUk5La`Q4N1_lO|=4Bw8RGXJpF)%Qw
zH80I#U|>*hUJ4q{&}d!?8ZFjrUTVU?z@XK<RGEQ+LA!aW5JNo!gHH2OMg|53-R30)
z3=9l<%}e4L7#Q@ML32tB2F*)s85kH0o0ouWGHPA|vdOr42`2*sgGuw^3I+xS)8@q>
zKbbWz2KmXnc`<0$qeU}lN{PX;c`?XKR?Ulr85kI>n-_z|rEQuQfkwb>n-?W8Fw`^H
zH7^2%o_+HoQ0O@{F9L<0WAh>z1_lPF=0%_paOdWQAV0Y@F9i9?wRs^Zn%tTff=2b-
zn-_w%OL{af1i8?&c_GM!Ud;<ZF7$3*0CJ&E^MZ5+1_s~e1z`*f41UcEKw;tEyZ{vF
z^#RQbKu!#7UI21pQ1b$i6N8)QgPa)BJRdZ49@;z~<ifD#`5+gDH_r!cua9V+4{~8-
z^L&sCqnhV|To~OvFOz|RA*OjADAZ${=Xo$NFvK;_10|&R=6RrbhlJ*Nppo;$=6Rsl
zN~&+33z|kqZU)UMF{Cul1r52UHiMRQGo&@o1qFV3^IVXH8O?L$85kHco9BYY)v}uB
z)G;tHWH-+NjjQD}&xv7RV90Hr<HNwfkk<^_Y{QV>4BBnOP|!RFWMN@5Xul0ZQ8Q@6
z4MTA=XvYmhNpt<|PzDBu(&pKqNwc!%*`V}M-aH!=Bo)oGL1Xom&9gyCzN#6tvYVm0
zc~&w514B(SXk|A;ZSyQU1_p+@=2<!n3=H+nvp`9{p?Ma_YmLn_K}o);c_t`%G&j!#
zC6AV7(86wp*5;XJ3=9ly%`;s<nXA2dCMa`tG|vRt)Y&|vgn@yft9b@!=&!qZ259SP
zPxB0C1_p-S<{6;fw0+GpKq<Jtc?KxbCQLt(8CS+}yBW0JnulS#TUOjY*6l0;ouJNn
zr@(Ty4;=!_*&cw14IpAc2dJys460ci)`5Cm>jbv4tOM1V57vUJ?E`B;>;-E<3L4ge
zYH6^516V*|tw1|VLvuSzLrXhLLu)%rLt8sbL;G?Tg-%dKw**w>Z0H14nj4mYYVJ;j
z?JN(LfZAmOUH|mAvn=QY8SbzYWKlvFNW1{d{?G}keiw8pY-iiB6x1ZW(6yZ9LidO5
zEFXG6sxB-8wdyYH1NDP?8<w*?=mB*|dO(^s^d@X)3jp^r6~MjB3w@yay9?z01Is|o
z#$_N^P3Qs*J~ea+w6huXZ)Y=@@NfNcmH?2v!!l6cXd=kb3d=wifCLRDf~<Y86lBVU
zrJx?cM1kcj8y16x7(rt#6PAKJvSA`fz5pb80VE#)Qt7Z*U@6Naf$b~`OF`~am;`D^
zg8RE47J=GIAR=Ls!giJo;4zj7lR#!n0Esq$hyx(02NOVU{xAttc?(QbXlF5)yqv{g
z%7^7F27RE`3~0Q>!5-v<3E+6yuohIogL={v`W)I>6sESbC`@Z-QJCJ&qA;VKMPX(;
zi^8mS7KPc{Srq1gnxqEnK(-2i62J#gBwttya_a?qP+JPz>L>u27yyzo0LQ;TA1GQ9
z=CrdU%xz~$nAgsdFu$E8VZnBmgoR8Sma{2L7TC@vFd1a3!6Jp_EDt~-umC(}Qm_cr
z)o54(iu42Ew(^2S0?XM1KyBp%i$LuxfkmLU5hxf9CV^rA6v6_NKrTvH0&3QPhhiQ~
z1SQ7BAWtWNJ6jh(qfrY$;eG(rv}pk8IslOe$4dZ6>ce8tut*0eHVwco_%H!v?tu=4
z?Q8{0{_`(q-7raDIqQN+puYbSP(P;uZ1I653ftKNCV|?D4wD!Kma;8XSk9)fSYSDu
z!BSABng~i{ognWffFk_>$gYN^0!vxC1eUW*0P{e^fu#c5Ssc1R?c5I_6E=YQiVMKW
z>cKvNtt<yX-uVC;5@J0d4@!aw%Rs{m%iCELR<yGytZZjdSk=y=u)3W^Va;}ygmp{>
zOWFEC`FR~ExcmR{x3a8nW!bQlWuwD#7J=mg%UK*Yf(TG52>`JIK&%81D*?nR0I>={
ztOgLP0mPcH5j1$X4CImp8$mvr0LlRyHiE*bVVS^Ew&kD_V;M;112}^?2rOj*4N-3Z
z>rns?NlpL{Ehc~mr2;@hrwN*%ZsCEA?Q91&wX+@A+|G7jOFP?vt?g_Fwzabz*xt@|
zU`IRKft~Ga2X?iy9oXH@c3@9C+kw5?*$(UjrIZi*LG~}`6=-Msux~lrfgaH4MlZ<M
z2S6$Dz=3v_0|(n#4jgJ{IdHh0<-n14mIFuISq>a)XE|`Zo#nuZc9sJt+gT2rYG*lc
QdOOR3Gk@}zDI8b;0HrnDl>h($
diff --git a/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/s251_childrens_young_peoples_services_national.db b/data_storage/UK/Education/la-and-school-expenditure_2023-24/data/s251_childrens_young_peoples_services_national.db
index 319f300bd8e4ec72d9898bf8e1f1ea180c5f7422..8362488a56db588197253dba96ef8a793bba5e47 100644
GIT binary patch
delta 38
mcmZp8z|!!5WrDQeQw9bGVFoy0be^bV%=ol1VQT{80(}6ue+gXx
delta 38
mcmZp8z|!!5WrDQeN(Kf7VFoy0l%A+#%(${KVQT{80(}6j%Lu&y
diff --git a/data_storage/UK/Education/school-funding-statistics_2023-24/data/20240125_fig2.db b/data_storage/UK/Education/school-funding-statistics_2023-24/data/20240125_fig2.db
index 5b6509a28e58b2dba3efe95b1878a2e26ba2cf06..89352128af67f75f8d35e901461751f9545fff1b 100644
GIT binary patch
delta 33
hcmZp0XmFSyE%=Cmfq{tu4j3IL>KHRV+L*9F9sqCl2L=ED
delta 33
hcmZp0XmFSyEx3$<fq{tu4j3gT>KHRF+nBIG9sp+|24(;N
diff --git a/data_storage/UK/Education/school-funding-statistics_2023-24/data/20240125_school_level_data_csv.db b/data_storage/UK/Education/school-funding-statistics_2023-24/data/20240125_school_level_data_csv.db
index 2ca3897c68d908e382e129c5e26230e39a4d22db..536539a01540176fa101955fa75ed1a66328dee4 100644
GIT binary patch
delta 6364
zcmZo@=wSxo3DSa(7#P?L7~p`>aiWef<D-oU)8*N>-pplSV4Sk~pFEpFGs}Z^mIsXO
zEDxBrvpisC+OV0;;oto2EE8Cm1h%s+kow2p&a#1}on-@SJIe;Pc9sq7?JOHO+F3Sm
zwzF*DYG>KN-OjRsr=4X3Z#&BdzIK)kAoT+6EE@#3vuqGzGH7RO5N>B{5NT&?5N&5`
z5Nl^^5N~H|kl4=FAjulQSiGI*f@A}0ebJgS1_s8$HJJ<yj0J0A7#JAy*Z4CqFy^gs
zVqjp*U1Q3?z?ic}gMooDdyO;$17p@2J_ZKH%r%S*42&78OBfg!(^sc6FfgXAj$&Y7
zOkM5Ez`&TY+L3{QF?qEK0|R5yYIOz%#>CZ93=E73t9cn17~@wnFfcI2ttw_<V2rI_
zmBzrp7_%ypfq^l4l@9|0W7H~p1_s8+RYnX9j1j9;85kJDS4l81Fovz-W?*0pU0Kh-
zz!<W!h=GAIcqK@0&`OZrz?C4q0V_dz{a1qY`mF@%^<4?l>$4K1*Ly`B0|TSiib4hk
zM$Z+g3=E7OE9xT{7#Q7GfHb?U0BLqzVa&k5=(0kMfq~I^1<2J-D?qMxTmf>m!*Y<1
z?U#dmY_}ZbW838*AKNT<U|?XhUJkO@YB|Va%jF=8EtZ2UHeUv^*lZcdV$)?Q3=E7W
z%fcBL7>$>CfqY}M%$9+H(Qugo0|TSMGGzt^M*U@C3=B;A%QzVrm<*TJFfcF~EiGVR
zU@~5s%)r28vNVi=fys2KCj$eM*-{$@1}5{R`V0(AmP?fw7?`Y<iZU=TSuf>aU|_OY
z0@7={B%gtS$!-Zqul<s61_maFCEg4SOpZ(J80s0AoR%0eFfchUQDI<Ua#<qIz`*3X
zgo}ZJ$!#%6v-@I@W{<^53=B-3i$fV0n7kH)EcRXuve;)a$YS5ciVO@)ev3sI7?}JQ
zvokO-1uUv$U|<Sdl+D1v6tpOgfq^M_Q6K{YQ^+D01_q|kMdl0)Oks;O85ruB!WYRf
zFfc_d;%8uBid@9Rz`zu>u#|y;DSBZB0|Qgc!YBp?rr3qP3=B+h3mq63nBo^2GcYhE
zEL3A)U`kvl$-uyrw2+5^fhl=GJp%(%%7S7B2By>n=?n}^X$wGl(-(mBW-PF0U|`Bz
z0P<?q0+3g;7l6E4pR)iI$hq^Y85o%I=I1dmFy+rrWME(_m><Hxz*IQjoq>U=Xuc%_
z15@#Q9R>!blKFBB3{0i-1sNEa%H}gOFff(RD`Q|_s+gC_z`#^FFPedYscIg`%IbL_
zD{JN%F)%RI&I38OZk`ka15^DxUIqphrFo$Aq_>^*rerv4y?wg?0|SFyI|~B?gKb*{
z0|SFiTMh#QgLPX10|SFqTQCCygJqi=0|SFan-v2CgL#`C0|SFun-T*9gK3)>0|SFe
z8y5ougK=ve0|SFmYY_tjgJEkL0|SFWYa{~$gMO<I0|SFzt33k)gKn!a0|SFjs~Q6X
zgLbPV0|SFreJc+G1A}HOsL;}ADPdq>P;bd#U|>*diD6)1P;K#NU|>*babjR#P;N0}
zU|>*c(PUs?P;8N9U|>*a0Xbd1g_(hYL9V%sfq_A`Ig5dTL8dvDfq_A~Igo*YL8{q>
zfq_A?*_?raL84iUfq_B18KhUN8KhUVxgMlhqzR;1xG9r?fkCJ#nt_2qu*r{sfkB`N
zWHEme$YQ=GkY?T{IR*v>o+cp%1_tgXHU<U;uEt6R1_sVXP?&Kv#xpQ5ur~%VFfgz+
zx-u{@ur^vSFfe#FYBMk}cr=3ax;F|kFfh0^g2LOij6sos!3E@B=O_jS1}9KZIf6pU
z!H9u@MOlr3f%WC~U-u<>6t=T1VEM<tokc*3X~J?g16hG~whdC-*)~Z3HmyH@B$I)G
z`NEM{1_tJfM*<iam@gf1W?*2xe8h}_f%(c2O$G+$t4CxQ7?`ge;b&lAzJ7$6fr0tP
z;W7pW=9`B>dT$*D>Aih8kb!~u&S6&u2IjkmEg2Y??;X}<U|_y~Sb>3o`N3gf1_tJb
zhuIhym>(UgWME)^d?<&3f%!@Op?C%c=BI~(7#NtJ9Rg{7e#nA>f%(NDZ3YJBmxtsS
z7?@uj5@cXtetn3Afr0tW!Ey!$=C=p47#Nt}9RykY{vgQF9}a>X{qZ2k(Vq^29R2wq
z$kAU8f*k$zAQJ-v^S1*aM}I#6a`cY_F$@gMKM&OVGcYj!I^e{>!2J7wDFXxZp97i<
z3@mI1WEmJ(6b}e6Ft8{bU}j)ok>6j&z`!E6Ka+uhMRtD-0|Sf9et!lA7U}&?3=Aw%
z`%M`bSS0srFfg!4?3ZR>U=iQX$H2fMwx5xKfkkv*2?GO*$i8$21{UFcQ49<$Li>Cf
z7+3`NIn*;Sun6okW?*39->1gFz{0mrl7WGRcOMS}0}IbykSzD!LIwsFuDz)Y3@n^`
zBN!N1IQDuoFtD)iwPRplVcKiRz`(+|SA~Irg<-Ea0|WE_z1$28%>VX)iWP%Bpkigi
zo-_sqruBOw85o$>?eSq?U|PEel*iZXF#;8&tM{lfFfgs!Bf-GHv~mwO0|V2F-E|BM
zOv`r{GB7YL+nvI|z_fHXsQg{B+lzsLY4L7b1_q`@yA2o^m=^9<W?*1iup3nF&)*Fy
zlIHCK6~A+Lfr{TbyFkV7>|LPZch)Ws1_q{?yQ~=)m}czKV_;yKzDp5QkWSkLDu1W$
z0u}sIc7n>Y$vZ*i*`%Ey%@cQmG*8$G(%iojq`7Y=NOSK_P}$wH6Qs9$C#dZ1+EK;8
zz|^@TkAZ>p)eex}jvXMq?K?nv+jfBTw(ihnU|?$5p}@ev)VxEOfq{v)X$Knv15@L6
zP{H3Yo#UnSZ^kX#SzbxEveZxBtj)l{xOuZ20|Vov&4LUJjGH#IFfcGq+*HoMz_@W!
z76Sw0giWyw42&B#1u!r$_HS}#U|?Lo$&7)4v2T+W0|Vo_O(4C!n?QQkZUX7;*$C3R
zW+O;%_ePN3)f+*2yEcOKuG$FF+qn^>cV+!Xkmin!Ak8Z_f;6{p0BK&n0i?NY14#3-
z4Is^}8$g<uZUAX+*`Ue5z_?_C3<CpW^9Ftf2FAr3m>3uso7R^yFfcA!pTWSu*ti~4
zOnI;OV_;xxSPyFSELacHTfZKpcm8^i-n#YmAkFjEgEZH!18JVS4y3teT{Hs&<D7LM
z&DHBbnrE*AwYI9(fm&O$)`41EmFqxyXRc#rU|_6R3v%>~wb={|jOA<N7#J9*uMJ{g
zU@Tkf%D})lZLI|Z17qo0kdLRXm1SUHELkhS%fP_E%dnj7gS5g{HmQI7%UKj;6qd6D
z$OtTFDUcD^&N4v;)Y#l011i)mfY~3wYynv&f#qxtvI^~N1+wjI1#;Wj3gkhpQvn%9
zf$gjU3cuyIIVi9SEN69)5!lY^VDX=SIZFb_*Z>QG<tz;#vlA>B1(vfekP%qUT3{it
zo%MjsfBx+(4Hh7iAIJ!7XPaR0kAEu**ro**0?XMHWCgafZLs(!znvvP_76V~E0;K9
zJqxIwV3{$U?}2p9_6`Gu8O-(5{)6)W)c>ITKjl9t|4;t!z`(#V=|8Bvp7<Y>g(v(M
zV_;zE|If+5z|!}xhJk^l_g_8(153}pBnAeS?tftn3@ly$JQ)~RI{(=)FtBv|Ghkp~
zY5%9pz`)Y>52UyC9~T1yOUvIn1_qYqzo4R{>2C@H150E5-*5&7mWIDx3=Aywe{C5U
zSnB?Q%8uH<stgP)HGd@-7+9+Rg36t$KcI4_@=p;1153ppP`Ok72UPBq{qbR7U@84$
z&%nS^@&{CA75@R1Sw(+9Wme%IklupdAia6NL3(q3gY;(o2I<ZCT@Na>(td+9r~C%_
zIO#XY;)LHIi{pNCGcd5k`~tZ;>KDk>5x+p1!+u3FFtCLD0)<x4FHmR&{4!x+VDbB<
z&cMLp^Gk|>fyL_=sA1yqi-CcG#qDP)0|Sf8Pf#iC^b=G{JNyKd(sn<cK<={nX~w|7
zV)avtfq}*1C#Z-w`w1%IO@4xkc%vVnBHrK!NVEPAkY>XlAkD@<Kt;Ui4^R=$`~y@y
zu>1h&W&I(*z`)A-gPDPWmF0UG0|P7b_e=%`R;KSU3=FJ{-~AaFSQ);9^#1>D%23b1
z^6xvSe)#(xR6qRr4yqr1e+ShMzrKO$ho9d->Ep*YQ2O}(&5wbB<=Zz$1_qX|-#|Y8
z@(twU&)+~k{`3u`_v1H^-Va|vdf$Hq>3#PVr1$MtP-wmR3JR^)UqR9I>Z=+9Lp{sO
zub_B(@f8$L&%c1e<JlKbJU#sa3hF0cK=JhW3n-c%eE~(&!!IDs559mbzW)W}=zCv4
z7T^5>viQztkj1w@gDk%F8D#Oz&mfC$d<I#3{WD1Kwa=jRarHCE-uf$_K^9;B1hV+j
zCy>P#KY=X1@Cjt``A?w4b?y^L^Vv@z&1XJ=G@t$i(tPR@NbkvyAiXC(g7hB$2-17(
zBS`Pjk03`M`3R~I4}SzD>O&tvx#{3XP=&beBPd54sQ*yQz`(rz11NFr|B%YSz`WrD
zC~@uk;KRVcyzv9b$9q2*F)%Q1`T(+c&j(2c2IkElKo;-*z`(%3yyZQ}$GhIAGcYi3
zeGl^S&iB3y49wf!gB-o%y)gp=^Y-_k(Axf9ih+T7$9qu1-1Z)%cjvo$P|Do;4%GPA
z^$wJ{w!8y1Tz0>6W?*31{0`J`+4ByRxHi25HC*<-<7Z%C+4v6BaM|}3q<6#H3<d_~
z{cocg7+BW7^<!XQKJXTlKGwYjwObCp1?gS;R+fQ*`OsTXqF(bB)L=UNrh<WiW%Zk!
zdIkpOBX8mv7+6-l0kyV{zHwz>U|IPF)Kok6MwfwsWyKp%Q|<U0VFm`4<!{&-7?@AI
zu3}(dS@t@Yfr0tt>jVY{mZh(Q85o#Py>??@U|I4Sr1$h|klw|w6&V<q&%738U|?DF
znuCFX`RuD|1_qXeuksien9sdRWMF1sSukDFQsFDl%xCTl3@o#rS%De>iUG1Gwi^gA
z+cHi!5MX{>&ocWN$h<kv6d4#;<~{?NH}4s!IGq0!6n|@<f;yBIPg58enAbdwU|?Wg
z{nVR*fqB(aI|c^kl}|x&u;QsI0|WE&rxFYd%*&qgFfcGLeFF0Rk|#wB49tt4fZ~49
z6Oi78Pe6JXJOSyQ|HP1ifw_L(6BPyq=DANmDQC_TE(QkX*^fb*XFV=qU|^p47!(IH
z9!E1UFi(FBYCBGQ3~D=0eGH0&DUUT67?>wNmS$jJp7fZHfq{AAV@3uB<_V8Ldix)N
z5>DSEklx-$p!n-~<jBCl-2KRefq}W}kvandb7%b{P|E3e#LK|I-2MoZa@rmiGcYi>
zJ_NPlSRaDga7+(D{WQjhpuYS6hoFA{--n=n|L=#A3=E7vAA<V*-yecTI=(&t)!UyR
zfa>j!4?v?N?;n5~3~wK}FfcH_eqheP!1(e3sFm~lfjk2P<I@NA!VC<Ij~}oxFfcy6
zU&X+{c>g|V?C0+NL<R=N+xJ5m7#MHf_h4XPynf$?fr0VreNgZJ@_iKs2F8o`#TghF
z&)?@_U|>9Zua<#<@$@~=(80-jpfQW%_dw$vNAH20&U_E#^h5VRJz|D?AgBMk2XgwK
zd%U25g<tnTeas(sL1Px*?t<L@<u0hr@#!vTgy+Lu&<M}FyPyWko4cR}%d5Mf2Fr`P
zpf<;|yP)>UlRF@PKe_|b```{p@4Y*q_R5_*p!UkGJD~Q;jXR+B%C$S7_R5tzAibCF
zFfr6KFkZL~(tPeVNb{N7AkC+4gEXJG4bpt<HfVV0$Ze43!?!`27v2U9EgifK3h)EB
zK#tyj3pCKO?-ppFW$!JJ-aWTKEwtUYK#iSUw{#d77<b-MU|?X}aZ7}OfpPmSb_NE<
zZ8t%gjb-}(l5H0(*aX_y0u<WW0u;Bi1t|UN-_BAX3~GTSXbCK5OAr>=&K4jHYW+BX
zMGb^O?GO+lAS|$z4J<Pu4y68rkid4f2ST7W)B`1ftt`rn1?{X2%I&NTD($Qds_m=|
zYVE8I>g}uz8rxYLH2>dkWzlYB(P?GTZDrAGWzlbCF=%BmY-KTOWif7LF==HnZDlcQ
zWiemMV&Txv^1z~<<$+~8%LA)+mIv1DEDvnjSsvJKXL(@v=l-?;2R4DNY)&9oesBb}
z*B&^6*cZU;1CIasx3g|=WCRTwI)a=x!BJp4OM~Md{%r^BAG6o9er=rV&A`C=rE#u3
z0|V>l#<@le46L6T=c+O=uzqZuE5X3P`k`?y4+8`1`^LGT-txP~ImHYNtZy6Vq%$zE
zzG<8j4I0sGoa4{Hz^30g$C-hFO|Nl|83O~GZsQzH1_m~r#yK(!3~btsa|9R|*t8nw
zFf%Z)X*SL-V_;yb*Jzxb#lXO(-Z(p!fq_k}adrR$1Dk5&Y>+W3jk7_<C^yaq8KcxV
zTb6-=O|fyd5Ca37LgQ>U1_n0y##xmN3~X|ZvvL_2*kl`LB{DFu$u!OiVPIgBZk*-L
zz`!QeILnHGflab;mM#MWn?&O*1qKE-@y1!g3=C{y^^LPY#)vk~tYTnb6KR|YGDf&@
zWPn^5D-U<L*@!N!?x3=C`njWaD77})q5XX-F8u<<p{1R2BII8%gyfsLneCOZQI
z8+YT3Y6b>2uErU83=C|XjWa-w;b@!zatwRp43J~k8fSnU!`e7QkAZ=Wr7>}a5(5Jp
zbK?wA1_m~!#u*$83~Y>z(?P~CG)@QgvHmwsPh?<V{nt1>gn@zeZ{u`#1_stYjnl0d
z7+8NdPS<5%VExrNU4emt^=IRBVFm`)AC1%57#LW;H%_Z$U|{{W{oqM^XSU@m1zG{i
zSuXesEN403FR-0ugFho8Y;0WC&{?W`Y^Kn?H<_DlioYzYp_*%BNDma_>sU0BX0
z5TLM>EkIy7n*oUU;4iS9%^?7k#vb^C(!PTOD6cq!<Uy<k5KF-Ul;E5}iX5CliVipn
zY-dvd3p{XU64=V-{EvSri;KW=mIqD(%UKjatPf5C+gTi3z+DJuP>M}(0i{?2XHbfD
z0htm2GJAoGz;d<%5bFSlH37tW0Ag)$7TC(>3bONpGst%eVD<+v+X2iLZ~=)YfY}CM
ziyB-(z77Dh7q~KlOa>Wsz!lU3aRHh2z!jutgA1rP;s#<~aA6kM&Z*$`mw!9k2NzKO
za&Q9~A^=vH;0DrU;0p3ZgBz&h6W}Vaon?U=NT2|0+X1jK6Tq%`;0E&729R|ZTtUA5
z08%XgR$%}(Dgewb0JA4RRJ#c*XS?7g(9ZV3t)1<Idpp|)k9M{Xp6zTOyxQ45c(=2C
z@M&lJ;JcjdgWrL6wt#?kwt&EPwt%2^wt(Pvwt$d!wt&!fwt%p9wt(<<wt$Fswt&cX
zwt%R1wt(n%wt$#+wt(2>Yyoiw+t~_~K^|;~19@aYoWORLgrq<7+cw0tZHRB%kg#k+
G;syX5vDL)@
delta 6355
zcmZo@=wSxo3DSbg7#P?L7~p_Wa-xng<Fbtj)8*Os-^^uTV4S!4pFEqwa+VLw3z}IR
z+F2YJ+gTi#wzD`eGi_MTHi1Q8J6nR}KmK->4J_>}8(7;}Hn6p`Y+!F^*}&1xvVpUm
zWdm0`%LeXtmJK}ZEE{;+SvK&svupsV7ieeMAh?}ngAkL!cD4!1|M<7FG$=EH%mcFn
zl$ivUvpFaWEN3$S5emuz+t~z^|M72S0n0p45@=_8Ak@zGK)9Xlfk->s1JQQ22V(7P
z55%{#J&<4xV65HFV<6eUT3@rKjDdl%dQBz+17p>i7zPH$$~FEB42%_PoER7w%h#AP
zFff*_(O_U;EL|hbz`$6thL3@Pv3Lz50|R5x>JkP9#=_O<3=E6~tD_hg81q;AGB7aa
zt#)K!V9Z@@!oa|ovs#^jfiZiv6axce)@oh`2FA?Q3=9m68LNsJ7#P#*SEVs9Fs7}F
zWME)SUFE~Tz?ibio`Hced6f|Z17p%ERR#ve#8nau42%h@xEUB2<5$)*FfhigEMj0_
zj9m%R8?zFmH+m&VZ`4YV-pG|8y%8%xdc#+O^oFej=?z^`$H2fCvZ9cIfiZYRDgy&!
z(2Dv91_s8!6(G$4D?pn4R~R!eF#4@fV_;zPT>)~n&kB&My;p!-?X?`_W6$LvAA2kZ
z`Ph9q$j5HW9T*rGU6+F_c3BRx*m*g~VyERGiyfDNEOuB1ve<rE3IhY9-Lh~721eUu
zULfDtEVE@`V6<Llz`($0wM?0TfzfiA7y|>N#WGF?21fIxH4F@lW=jhg7#K~LCNnTF
znk)@tU|=*}>dC;sXtdOZfq~I*sXhY(qrp-o1_nm`rJ@WBO!`YX7#Nrgm((yYFc~e$
zXJBA5UXskfz+|!{oPmMKbcr_u1C!YjJBE4&Ci5kR3=B+`OH>#bn5>qFGcYh&FX3Wf
zV6s^Z(rmjJq}gt95(5L1{o+st1}2Bao(v33j*D#=7?_+E>oYJgIWJaZU|@1tEW*IR
z<hq!hfq}_wQ6&Qdll!7<1_maNMR5!aOrDDZ85o$n7P&AmFnKRBXJBCRS)|FpP|xJM
zNQQxd$!`%q0|S%)A|?g~rhtW|3=B+x3o{rPn1U8YF)%O%FZ5+#U<z62z`(#1y3m+`
zfhlaE8Uq7U_(Dkr2BwIGJPZs>kqhb>7?`3K6f-a|MK4HaU|@<_0MZ+~0Hil=fjt8Q
zQ~UyuR}&V1yqdTG<kkA51)K~FOv&@B85o#S=I1dmFs05<WME)Qn;*i!z?44Uoq>TV
zW4<K=15@UF9R>!btod>b3{2Vc1sNEaa^^ELFfirLD`Q|_%A1$Tz`&G0FPedYsbC(+
z%EEadD~skCF)%O{&jUHPWS$fQ15@cdUIqphrFo$Aq_>^bQZk&i-m_hRfq}uJorQsc
z!M&}5fq}uTEr)@D!L==cfq}uLEtr9U!MV+ifq}uP&5D76!Ldz`fq}uHO^Jbl!M;t5
zfq}uUjf;VS!M3%Ifq}uMwTOX%!MZh#fq}uQHIjjW!Lrqdfq}uI)t-TY!MxR&fq}uS
zRgHmx!L(J9fq}uKzLkf8fx);HRMZ)@lrS(b7`9|EFfbUj#4s>0=(qSYFfiz~I599V
z=(d<KFfiz}XfiM`Xt&5RFfeGffSj(`!py+HpwV2$z`&s1oW;Pvpw=AAz`&r|9LT`H
zpwjHZz`&r~Y|g;Ipwz6zz`&r`4AQI64ALv#To2ML*96im+my+`z#!8U&A`AQ-Q>r>
zz#!EGvRJYSWU)jONV9m890LP`Sd$O~1A}N28v_G_NMj`f1A}lQD9nT!;~5wj1RH}G
z7#IW^T^Se{_!})47#R2(wHX)~cpE`_c^U;77#O%4LE+6+#-PZ+zzOm%M-&4C13M_F
z*gzr0YQ(_6q6~^Ti|xPcC3zIKvlU2#isAxErU~2G7O;Sdb^)pFECSMhP3vzS$z)()
zzI7y)fr0t<kpKn;<~v8685o%F9x-EJV7_-mlYxQx{t+1l2IdDx_!$_OA0A<5U|@c9
zxQu~;`SD?p-Y17adY>K+WME)^cG#7Hf%*AiO9lq!7l(Bj7?@ukR$yRYesx%wfr0t;
zVKxQ^<~N5b85o$~9?D^0V18GBD4v0V`Te0F1_tI2hd`P?9<pFyVE%MSn}LD(^C39~
z2Ien^1Q{5ZzaC;?U|{}su$+N``TM~v1_tII2SFD9JP301uY({*|2_zE^q+&83=Ax6
z2W1!-SQHQPGcd3y9Asi(V39vi#=yWLcOa92fkpN}3<Cp;%z=7;1_l=C15OMKEK&zd
z85me34}dgF9FS#TU=cqcz`(#Fc7U0IfkkvbNVCX(kY?fiAk9MiL3#!EgY*jQ2kGVC
zuff2;!na?Vfq{j0KOX}F3(tN=1_l=HeI*PGEL{8285meN_eC)<uyE}2Wnf@o-{(-z
zz`(+^&zOOMg>j!60|N`gK1l`!=KuS67#NuU?FE$$273z`7??KfO=VzUTE91ffq`k=
zUQju>cCQ@+1Jjzlpt520UQpSvYA>j4Sh<&*fq`ko9+2MUdqCyNvOQ@G3`|S+L^3ci
zE!pG4z`(S44=9r_+G7MNNf+)>Wnf@hut$P{foc98kmh;2>lhfA=I#brJZE<b0|V3S
z-Jk+^)^0Bb2Bw+2Z5bGtX6!a#U|^cQTbY4@Y1(cv1_q|7yFq2rlwF|mck(V!`8#PB
zsQjI{3snA2*yX{%z|_CXnt_3-Z<ihe15@uVMNmoFvkO!Jckcp~{9QXi1zP7$P=VI5
z6QsF)CrESKPLSr-ogmFEJ3*S8cY+G<rkx<YjXObwcf*b<1_q}39eE54tS@(f^w#YF
z>8;%X(p$3wq_=v9E&~Ho)eZ#)2Byj#!VC;dycIjx7#Nt!w}VRlvgsV2(!Uw^ZD;Y4
zZe^*TyIGrofpPC<IR*yCIhzF;7#R0#W?^7poV}@>fq`-NrYr^q##x(U85kIMZ3<vu
zV4S(hnSp_E=O!}-2F4kiv=|r|cWeUboxTaAcl#!g-f0^_dbe!^>7BX}q<8B^klra9
zL3+1r1nHf;5u|r>{YH@HNgF|$H*ExIp11*|dE*9<<_Q}>nm23!Y3|<u(!72HNORu?
zO$G+WbsJ<D7#Mpu@G~$luHC@Iz`)qEzLbH1an1S+1_s9N_0bFrjH}oCF)%Q8tp~Mw
zR;>r=?OYGiyK+59Z^!z2kmeQZL7Lmwfiy2)2h!ZO4y1Y6I*{hpbs)`4*MXW_E$cwd
zttIO~&8_BjAiay%F*7hQHmwCYdePc!1_s8)wQ&p#4Bl&l7#J8E*19q<FfLeY!N9;+
zzZT@<`D<kv7#Qo;3h;tTJci|L0n!TF*)GWa=ikoSApKu{JBxrkqri671=9cdm$Mki
z3oK{ZAT6+*B|u(aJIeuSP&>0g9;EmJSiuC4@B?X3lXHW-z;?C|;6m_%Jd?muHW`8C
zY#-zWma<6+EN2stQP|F=pzw>o%|NEjKz5sf9Ls|3EDz-V$n&sri8I!-fC_z<zUh1p
z(ly&V3>0QC*Z2Gf<>l`GpuF7mAC#9n|2r@+uyp(f6~68NRTvmp+Ww0%FtD`#=VV}D
zY57;fz`)Y{FQ0*drRiT10|QIrzc2;{mWF?x3=Ayw|7;i-SnB>6Ffg#x{!?aPV5#{B
z(p&wHi-Ccq>Tewb154%KLIwtwioYog3@qjKf5RCVSjzr-F)*-{{<URbU@7@)$iTo-
z{8yEMfu-oL1Oo$0;a?sG29|<9pb{qUPZ0wHOU|EE1_qX_KM@QJEE#`%7#LX6{@61x
zu%!F}l|M;;K;=)uA4vuVmbgD4y)nN*dZT`W^hW#!=?(i0(i`%--kX7eCFnOubHHzq
zkNtjwEcW>gve@f4Hv<EU$1jkp-F|^w?eYtx+38m#0|Sf0FHmUN{Q`xS%`X!M1{SMd
z>I@7l7Qdtz7+B1Hfm#_RzZe)8Sd4y_GBB_h`~;P_`aeM>uHjEmiEI4R3FI!*pJogU
zEX+T(7#LVseu9c?)}I0l46Lj_nHd;ZS$>o;Ft9TJ$Yfw(W%?1rz`)A*!=HhHmEi}d
zxc>hGR9yf20V?YM{s8Iy^8-}W|Na3g>VJI)74<*AgDn2>9c1zM?;wl6eFy3N`rVYF
zo`L1dcTidX`8%kr|MVSH)_?pCD(gRd1C{mfzk$-nyKkWM@%Eb^0|U#OZ;lKMEU&+T
zeEjMg$j2|gfqeYp8%Xc-Zy>$TzJl~V{R-0i<SR(;<FBC5dh`_(S`WX1qUpg`H3o)y
zmiu2p@pSJiD4y<q0fon%FQ9n3{RI@%x4wYl>E;(uG~M_Dil*ydK$@?80a<+Y3&_z|
zzJM&g`~_t3rOzOXFMbADeBm?5;`5(D7N7eJviR(0klr(&LFwc4XOO-1r#^!$KKTh`
z@rh3$i;sT-S$ymh$l{})K#A+fCy?gDpFo-qeFAAd_z9%>z$cL2{U1Sk_k9HE-TM)w
zch5(V-rXNTj^6drj)8$?=SNVY-tiHXo3?)xXJBC7@e!0Gw$*>AWnf_5`2m!;wth%u
zU|`<$0hGA5eDGmlVBY-!<m1gBj2IZ0_j~|Zyy*j|R^9snWbwui3=9m+``&|myy1O1
z0|WE^_aGmyfA7n{z<l66$kFTG8#6F4AAAoAt+nr^7#Nrjy$2=CHSa-s55KDirOegu
zK&_u6??4G;)jLol<mfwR1_qXu??8=^WA8wTYsEWI%jx(#P$OjdJ0=DO<`Zv0dY8S;
zU|?WA`8Jw?fo17iKL!ToQ*S}(W64`n1_tKSZ$Ww&zm;WRU_SE}lrR^)1vP%ozNuhf
zU|IMkr=Ed<`P`d$1_qV|Z$K@l^KV=k7+B`N0X4fWywPP~V43#@)a<(WMwo$tW$qhx
z1_tI!ud5gsSmwOWWnf^w{5pYwfo1mVU<L-}E3e%c7+7Y#2I;-}8l-pTYefbI=4-D-
z85me*yyjqFV7~sUnt_33`l~z!2Id>D5*e5oSf)*vv{d-Y)Bnt!fq`YhGb>PIKv6;F
z#C8KK1qG&hmWj_mMooIA$iTod`5DNlDbGM9;nb&~sN4RufPsPa)zcIP2Ig%~BN!N%
zw?6e|U|`<z)Q*9HdGk|H@Nasm%D}+9@u>s@1M`Nbpa#+UCm@fnds4)}z`XVeDB9ON
z0qI@+1f+M>6Oi7OPYf9tnCn+OQDI<UUj77>XqG+UVqjoi`WU2n$>S0R2Ij?&LBYT1
zaWn%1^TNme3=GT*9y>8GFwcJs3jTSIH5eF}=RTHZU|^o}n2&*hdG=#Q1_tI?k3f27
zJ_4ng8IM4Er#}Kk-LyxJ3=GUuADJ*PFi&};&cMJtx&9F-(M)>8%fP@q@ewG|On6w#
zz`)%9FpYtMx$j{l0|RsKLr{Y2dFa5vz})>1<m0Y~Y77j_oex2Ywc{a3Z~H@##cdBt
z85o#bAAq`+tPf%s7?_wI1TZi#F+Ol%U|{_Jz?^}B@$UmrW99b)c?Jf?pAYJV85kJ9
zKVV~EVElT&ih+Ug^L^0B&&T_T3=E9#?}sulFuuL-!N9=y`aY;9{_?&70|Vpp`zj0!
zj8E^2GcYhdzR$(L!1(Z9EdvAN{d=GxfV=lVV-L6QfyOOv-UAIET)zhzKDc@hH1u%!
zo*DxK<HdWD3=E9t@9}~L2+rOE^%YOw1&uwNybEeN9KQ={Ivl<0&%nUMd>1rQbLg%a
z0|OJoT~NE@-(66<<Ii1C)8W@$P_yI59Z<95+Z~YJFLywCKivT}J3ib2H9Owj0W~|`
z+yON^UflsTJ6_xY>3w#GiJ_i>@yTtF=0~?dnjhQ-X})(Gr1{Qmkmg&rLBl*ZZi6&m
zyA9HO<u+)D=+bS_5YdHOAV;6O1sX6pa|<+Ja_SaH?}=NWhSsrLpf<~qTRIF3jE8S2
zFfcGKyd}cGz<BT$I|Bpbft#Rw#?t%0WQ#njKs#%ILOW}K;&#>mrT_iQSr#Y@EN5BZ
zAh4ZfgEC{ma@K}8fp%5}m3CGI)pk||wRTno^>$VTjdoTA&F!oTTL15FXZfH6YS~<{
z|L4D*CBcEwp_Ns;l~t#eRkxK@ua#B5mDQk?)v%S-sFl^YmDQw`)wGq>td-S#E33tS
z`{gVOpk|T-s40{n&nU2*wLu=#f&#Up*bc~pdW8?<nFO}7Dg2Y)&f=iJB+$<0VA0Oz
zVA;;*VAam%VBOB<VAIa#V7r~o!S2`nZ3pZhv)8j3G|u&AU|`d4oNLd(z^2zY*NB0E
zO}BBbDgy(XPUBn&1_n0m#<@HU3~XABa~T*I*fbmG6f-ceX*AABXJBAcZ=4g&z`&-~
zILDuXflak>jxz%Tn@ZyxGX@4W<;FRh3=C{ajdNre7}yjW=Lj$`uqiaoVP;@plW&||
z#=yW<FV{Fbi-CbnwsCeW0|T2(<Lm$i1~%!&*&t)28fSxyk!+j|GDf0twk!h!n|R}F
zAqECEvBueK3=C|djk78l7}!J_XXP?5un9NLN@QSQ6Kb3l!oa{L*f`6bfq_k+ah4SW
z0~>$iEL{c$HonGL3JeTvyp6Mj85r1j>KkW)jNxvaS;fG>#??3zWDIBH%mfAoHjc)b
z!3+#+?2R+s7#P^t8fRKEFtD*U&eUOGU}I^V2{MMcai$0Z0~=H0Om+qaHpa#o)eH=5
z42?5D9hd)&GZGmXSpPN72w`Ag{o6Rhoq>V%PvZ<L1_svOjWhHZ7+8NbCeBb|U|{{(
zI75_yf%Qk@3=Rec*6)qes~H$rzco$=8S}MqI>?wWjnhHKd~Tc$GUij`bdWJ08>j0s
zFtC1ToUXvY!1}&%x-bI+>$}G3Yzz#nZyTpoGBB{d*?#b(y))Z(mJJR}0n6DYI14Oi
zD*zDzAVR@jpq0&WDVvkPcD4WqP!if;|A&9u0(%yL<t!8I1-7#^*n?7Rfjy`#o?y=i
zQfCiR=KvNr0J8<0m@aH*6L9$lYRbC^ENA)PEU=v=zy+l9f-^|8zy*{`oI&mP2`&Q5
z*%CmOZve3xK&%Tc0^8XZID^dn-~v)~03<5lDzKdG0f=SbDzKH!1tcBd3Nlmy%r0;R
zWda8mf#s|dTm`nXCb<0P-_EkZ6=XmI$ixe-AT0~P?)U&^9{{rj+?WNnb3SnS%fFq?
z!0kW(R#sP#&Hy*C*<ghQZlK<YgDa?aGQmw?IZJ{osEYz(HGo(b+yu6>EC5^e!A)Q}
z+X0XZ-9gqp0J~7Y9W)Z|26BpmyTEcb1vi21YzFS2uy6orb#MpSmEZ;v2yhoz&e8x9
zO#q87aQn}{owdN75o9jN@CJ|x58MRW*(SKRvrX`5XPe;J&NjiToo#}5JKF@GcD4z=
z?Q9eLma|RpKd_w5!2x8K1ITCvQ0e3V4tE7-fu(Gqz<l7Ou$)c68KlM;G<*~g(9RMN
z*v=9V)XowR+|CjZ(#{eP+RhRX*3J?T-p&#b(asVO+0GIW)y@(S-Odsa)6NnQyPYK<
n4m>ju2l8|QcxGTh9N4`0c9wvIc9wv|?JNOFf7UPC5VrsT$;iC?
diff --git a/data_storage/UK/Education/school-funding-statistics_2023-24/data/20240125_tab1.db b/data_storage/UK/Education/school-funding-statistics_2023-24/data/20240125_tab1.db
index 98ab82ed834f8c36b3e69833c28639e96e8ba6b8..3cd965d0078c2d084196514b4c1b2bad96d274dc 100644
GIT binary patch
delta 33
hcmZp0XmFSyE%=Cmfq{tu4j3IL>KHRV+L*9F9sqCl2L=ED
delta 33
hcmZp0XmFSyEx3$<fq{tu4j3gT>KHRF+nBIG9sp+|24(;N
diff --git a/data_storage/UN/Crime/SYB67_328_202411_Intentional homicides and other crimes.db b/data_storage/UN/Crime/SYB67_328_202411_Intentional homicides and other crimes.db
index 62acbcaa03cdc4369423e94b4ad0333bc0ffe18c..12b1f7e9555a16f3a9df01b0282a2fe1b2d936b0 100644
GIT binary patch
delta 234
zcmZp8VAAlwWP-Hd6b1%{%M1(*%n;1XJ5k4&amvPo)%=WXn|TD@^2@WUF)%Q&2s1zc
z6I4AblxEv3p`g#q3NnIex?up<zUdADT<fV#Om-*;Uu2-LDS=I3JDURUFaD;2wgSes
p0;aYC=C%TswgT3+0=BjS_O=3!wgS$!0<N|K?qvl$8x}bT005dDM1lYS
delta 361
zcmZp8VAAlwWP-F{1Oo%ZWd;TYW(a0_I#I`%F=AuFYJNuc%{&5c`Q<OGF)%Q&2s1zc
z69WSS8v_FaE0kv6ETN#!%nA}>nr;}twQssZ0M~kI6O$bh!WS7RP}^7{%$w|x;Jzt<
zO`w^rpq;INv7N1eshzEWxt*<mrJb#SwVkbit(~oay`8Oqqn)jQvz@JgtDUWYdplbJ
K&#(215(EH~lW$W1
diff --git a/data_storage/UN/Crime/UN_Crime_Continents.csv b/data_storage/UN/Crime/UN_Crime_Continents.csv
new file mode 100644
index 0000000..2b9b3a2
--- /dev/null
+++ b/data_storage/UN/Crime/UN_Crime_Continents.csv
@@ -0,0 +1,253 @@
+Index,Region_Country_Area,Year,Row_Descriptor,Value,Footnotes,Source
+1,"Total, all countries or areas",2005,"Percentage of male and female intentional homicide victims, Male",10.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2005,"Percentage of male and female intentional homicide victims, Female",2.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2010,"Intentional homicide rates per 100,000",6.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2010,"Percentage of male and female intentional homicide victims, Male",9.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2010,"Percentage of male and female intentional homicide victims, Female",2.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2015,"Intentional homicide rates per 100,000",5.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2015,"Percentage of male and female intentional homicide victims, Male",9.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2015,"Percentage of male and female intentional homicide victims, Female",2.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2022,"Intentional homicide rates per 100,000",5.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2022,"Percentage of male and female intentional homicide victims, Male",9.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+1,"Total, all countries or areas",2022,"Percentage of male and female intentional homicide victims, Female",2.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2005,"Intentional homicide rates per 100,000",12.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2005,"Percentage of male and female intentional homicide victims, Male",20.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2005,"Percentage of male and female intentional homicide victims, Female",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2010,"Intentional homicide rates per 100,000",12.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2010,"Percentage of male and female intentional homicide victims, Male",19.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2010,"Percentage of male and female intentional homicide victims, Female",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2015,"Intentional homicide rates per 100,000",12.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2015,"Percentage of male and female intentional homicide victims, Male",20.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2015,"Percentage of male and female intentional homicide victims, Female",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2022,"Intentional homicide rates per 100,000",12.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2022,"Percentage of male and female intentional homicide victims, Male",21.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+2,Africa,2022,"Percentage of male and female intentional homicide victims, Female",4.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2005,"Intentional homicide rates per 100,000",5.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2005,"Percentage of male and female intentional homicide victims, Male",8.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2005,"Percentage of male and female intentional homicide victims, Female",1.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2010,"Intentional homicide rates per 100,000",5.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2010,"Percentage of male and female intentional homicide victims, Male",9.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2010,"Percentage of male and female intentional homicide victims, Female",2.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2015,"Intentional homicide rates per 100,000",5.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2015,"Percentage of male and female intentional homicide victims, Male",9.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2015,"Percentage of male and female intentional homicide victims, Female",2.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2022,"Intentional homicide rates per 100,000",6.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2022,"Percentage of male and female intentional homicide victims, Male",10.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+15,Northern Africa,2022,"Percentage of male and female intentional homicide victims, Female",2.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2005,"Intentional homicide rates per 100,000",14.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2005,"Percentage of male and female intentional homicide victims, Male",24.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2005,"Percentage of male and female intentional homicide victims, Female",5.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2010,"Intentional homicide rates per 100,000",13.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2010,"Percentage of male and female intentional homicide victims, Male",22.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2010,"Percentage of male and female intentional homicide victims, Female",5.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2015,"Intentional homicide rates per 100,000",13.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2015,"Percentage of male and female intentional homicide victims, Male",22.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2015,"Percentage of male and female intentional homicide victims, Female",5.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2022,"Intentional homicide rates per 100,000",14.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2022,"Percentage of male and female intentional homicide victims, Male",23.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+202,Sub-Saharan Africa,2022,"Percentage of male and female intentional homicide victims, Female",5.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2005,"Intentional homicide rates per 100,000",14.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2005,"Percentage of male and female intentional homicide victims, Male",26.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2005,"Percentage of male and female intentional homicide victims, Female",3.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2010,"Intentional homicide rates per 100,000",16.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2010,"Percentage of male and female intentional homicide victims, Male",30.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2010,"Percentage of male and female intentional homicide victims, Female",3.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2015,"Intentional homicide rates per 100,000",16.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2015,"Percentage of male and female intentional homicide victims, Male",29.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2015,"Percentage of male and female intentional homicide victims, Female",3.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2022,"Intentional homicide rates per 100,000",14.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2022,"Percentage of male and female intentional homicide victims, Male",26.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+19,Americas,2022,"Percentage of male and female intentional homicide victims, Female",3.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2005,"Intentional homicide rates per 100,000",5.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2005,"Percentage of male and female intentional homicide victims, Male",8.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2005,"Percentage of male and female intentional homicide victims, Female",2.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2010,"Intentional homicide rates per 100,000",4.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2010,"Percentage of male and female intentional homicide victims, Male",7.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2010,"Percentage of male and female intentional homicide victims, Female",2.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2015,"Intentional homicide rates per 100,000",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2015,"Percentage of male and female intentional homicide victims, Male",7.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2015,"Percentage of male and female intentional homicide victims, Female",1.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2022,"Intentional homicide rates per 100,000",6.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2022,"Percentage of male and female intentional homicide victims, Male",9.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+21,Northern America,2022,"Percentage of male and female intentional homicide victims, Female",2.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2005,"Intentional homicide rates per 100,000",20.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2005,"Percentage of male and female intentional homicide victims, Male",37.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2005,"Percentage of male and female intentional homicide victims, Female",3.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2010,"Intentional homicide rates per 100,000",23.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2010,"Percentage of male and female intentional homicide victims, Male",43.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2010,"Percentage of male and female intentional homicide victims, Female",4.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2015,"Intentional homicide rates per 100,000",22.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2015,"Percentage of male and female intentional homicide victims, Male",41.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2015,"Percentage of male and female intentional homicide victims, Female",4.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2022,"Intentional homicide rates per 100,000",19.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2022,"Percentage of male and female intentional homicide victims, Male",35.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+419,Latin America & the Caribbean,2022,"Percentage of male and female intentional homicide victims, Female",3.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2005,"Intentional homicide rates per 100,000",3.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2005,"Percentage of male and female intentional homicide victims, Male",4.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2005,"Percentage of male and female intentional homicide victims, Female",1.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2010,"Intentional homicide rates per 100,000",2.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2010,"Percentage of male and female intentional homicide victims, Male",3.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2010,"Percentage of male and female intentional homicide victims, Female",1.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2015,"Intentional homicide rates per 100,000",2.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2015,"Percentage of male and female intentional homicide victims, Male",3.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2015,"Percentage of male and female intentional homicide victims, Female",1.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2022,"Intentional homicide rates per 100,000",2.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2022,"Percentage of male and female intentional homicide victims, Male",2.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+142,Asia,2022,"Percentage of male and female intentional homicide victims, Female",1.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2005,"Intentional homicide rates per 100,000",6.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2005,"Percentage of male and female intentional homicide victims, Male",10.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2005,"Percentage of male and female intentional homicide victims, Female",3.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2010,"Intentional homicide rates per 100,000",5.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2010,"Percentage of male and female intentional homicide victims, Male",7.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2010,"Percentage of male and female intentional homicide victims, Female",2.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2015,"Intentional homicide rates per 100,000",2.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2015,"Percentage of male and female intentional homicide victims, Male",3.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2015,"Percentage of male and female intentional homicide victims, Female",1.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2022,"Intentional homicide rates per 100,000",1.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2022,"Percentage of male and female intentional homicide victims, Male",2.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+143,Central Asia,2022,"Percentage of male and female intentional homicide victims, Female",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+30,Eastern Asia,2005,"Intentional homicide rates per 100,000",1.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+30,Eastern Asia,2010,"Intentional homicide rates per 100,000",1.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+30,Eastern Asia,2015,"Intentional homicide rates per 100,000",0.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+30,Eastern Asia,2022,"Intentional homicide rates per 100,000",0.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2005,"Intentional homicide rates per 100,000",2.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2005,"Percentage of male and female intentional homicide victims, Male",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2005,"Percentage of male and female intentional homicide victims, Female",1.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2010,"Intentional homicide rates per 100,000",2.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2010,"Percentage of male and female intentional homicide victims, Male",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2010,"Percentage of male and female intentional homicide victims, Female",1.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2015,"Intentional homicide rates per 100,000",2.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2015,"Percentage of male and female intentional homicide victims, Male",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2015,"Percentage of male and female intentional homicide victims, Female",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2021,"Intentional homicide rates per 100,000",3.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2021,"Percentage of male and female intentional homicide victims, Male",6.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2021,"Percentage of male and female intentional homicide victims, Female",1.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+35,South-eastern Asia,2022,"Intentional homicide rates per 100,000",1.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2005,"Intentional homicide rates per 100,000",3.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2005,"Percentage of male and female intentional homicide victims, Male",5.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2005,"Percentage of male and female intentional homicide victims, Female",2.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2010,"Intentional homicide rates per 100,000",3.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2010,"Percentage of male and female intentional homicide victims, Male",5.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2010,"Percentage of male and female intentional homicide victims, Female",2.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2015,"Intentional homicide rates per 100,000",3.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2015,"Percentage of male and female intentional homicide victims, Male",4.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2015,"Percentage of male and female intentional homicide victims, Female",2.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2022,"Intentional homicide rates per 100,000",3.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2022,"Percentage of male and female intentional homicide victims, Male",3.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+34,Southern Asia,2022,"Percentage of male and female intentional homicide victims, Female",2.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2005,"Intentional homicide rates per 100,000",5.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2005,"Percentage of male and female intentional homicide victims, Male",7.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2005,"Percentage of male and female intentional homicide victims, Female",2.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2010,"Intentional homicide rates per 100,000",3.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2010,"Percentage of male and female intentional homicide victims, Male",5.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2010,"Percentage of male and female intentional homicide victims, Female",1.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2015,"Intentional homicide rates per 100,000",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2015,"Percentage of male and female intentional homicide victims, Male",7.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2015,"Percentage of male and female intentional homicide victims, Female",2.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2022,"Intentional homicide rates per 100,000",4.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2022,"Percentage of male and female intentional homicide victims, Male",7.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+145,Western Asia,2022,"Percentage of male and female intentional homicide victims, Female",1.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2005,"Intentional homicide rates per 100,000",6.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2005,"Percentage of male and female intentional homicide victims, Male",9.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2005,"Percentage of male and female intentional homicide victims, Female",3.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2010,"Intentional homicide rates per 100,000",3.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2010,"Percentage of male and female intentional homicide victims, Male",5.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2010,"Percentage of male and female intentional homicide victims, Female",1.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2015,"Intentional homicide rates per 100,000",3.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2015,"Percentage of male and female intentional homicide victims, Male",5.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2015,"Percentage of male and female intentional homicide victims, Female",1.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2022,"Intentional homicide rates per 100,000",2.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2022,"Percentage of male and female intentional homicide victims, Male",3.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+150,Europe,2022,"Percentage of male and female intentional homicide victims, Female",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2005,"Intentional homicide rates per 100,000",13.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2005,"Percentage of male and female intentional homicide victims, Male",21.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2005,"Percentage of male and female intentional homicide victims, Female",6.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2010,"Intentional homicide rates per 100,000",7.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2010,"Percentage of male and female intentional homicide victims, Male",10.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2010,"Percentage of male and female intentional homicide victims, Female",3.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2015,"Intentional homicide rates per 100,000",7.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2015,"Percentage of male and female intentional homicide victims, Male",11.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2015,"Percentage of male and female intentional homicide victims, Female",3.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2021,"Intentional homicide rates per 100,000",4.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2021,"Percentage of male and female intentional homicide victims, Male",6.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+151,Eastern Europe,2021,"Percentage of male and female intentional homicide victims, Female",2.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2005,"Intentional homicide rates per 100,000",1.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2005,"Percentage of male and female intentional homicide victims, Male",2.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2005,"Percentage of male and female intentional homicide victims, Female",1.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2010,"Intentional homicide rates per 100,000",1.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2010,"Percentage of male and female intentional homicide victims, Male",2.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2010,"Percentage of male and female intentional homicide victims, Female",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2015,"Intentional homicide rates per 100,000",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2015,"Percentage of male and female intentional homicide victims, Male",1.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2015,"Percentage of male and female intentional homicide victims, Female",0.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2021,"Intentional homicide rates per 100,000",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2021,"Percentage of male and female intentional homicide victims, Male",1.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+154,Northern Europe,2021,"Percentage of male and female intentional homicide victims, Female",0.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2005,"Intentional homicide rates per 100,000",1.4,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2005,"Percentage of male and female intentional homicide victims, Male",2.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2005,"Percentage of male and female intentional homicide victims, Female",0.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2010,"Intentional homicide rates per 100,000",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2010,"Percentage of male and female intentional homicide victims, Male",1.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2010,"Percentage of male and female intentional homicide victims, Female",0.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2015,"Intentional homicide rates per 100,000",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2015,"Percentage of male and female intentional homicide victims, Male",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2015,"Percentage of male and female intentional homicide victims, Female",0.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2021,"Intentional homicide rates per 100,000",0.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2021,"Percentage of male and female intentional homicide victims, Male",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+39,Southern Europe,2021,"Percentage of male and female intentional homicide victims, Female",0.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2005,"Intentional homicide rates per 100,000",1.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2005,"Percentage of male and female intentional homicide victims, Male",1.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2005,"Percentage of male and female intentional homicide victims, Female",1.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2010,"Intentional homicide rates per 100,000",1.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2010,"Percentage of male and female intentional homicide victims, Male",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2010,"Percentage of male and female intentional homicide victims, Female",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2015,"Intentional homicide rates per 100,000",1.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2015,"Percentage of male and female intentional homicide victims, Male",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2015,"Percentage of male and female intentional homicide victims, Female",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2021,"Intentional homicide rates per 100,000",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2021,"Percentage of male and female intentional homicide victims, Male",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+155,Western Europe,2021,"Percentage of male and female intentional homicide victims, Female",0.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2005,"Intentional homicide rates per 100,000",3.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2005,"Percentage of male and female intentional homicide victims, Male",3.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2005,"Percentage of male and female intentional homicide victims, Female",2.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2010,"Intentional homicide rates per 100,000",2.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2010,"Percentage of male and female intentional homicide victims, Male",3.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2010,"Percentage of male and female intentional homicide victims, Female",2.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2015,"Intentional homicide rates per 100,000",2.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2015,"Percentage of male and female intentional homicide victims, Male",3.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2015,"Percentage of male and female intentional homicide victims, Female",2.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2022,"Intentional homicide rates per 100,000",2.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2022,"Percentage of male and female intentional homicide victims, Male",4.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+9,Oceania,2022,"Percentage of male and female intentional homicide victims, Female",1.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2005,"Intentional homicide rates per 100,000",1.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2005,"Percentage of male and female intentional homicide victims, Male",1.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2005,"Percentage of male and female intentional homicide victims, Female",1.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2010,"Intentional homicide rates per 100,000",1.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2010,"Percentage of male and female intentional homicide victims, Male",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2010,"Percentage of male and female intentional homicide victims, Female",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2015,"Intentional homicide rates per 100,000",1.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2015,"Percentage of male and female intentional homicide victims, Male",1.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2015,"Percentage of male and female intentional homicide victims, Female",0.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2022,"Intentional homicide rates per 100,000",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2022,"Percentage of male and female intentional homicide victims, Male",1.2,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+53,Australia and New Zealand,2022,"Percentage of male and female intentional homicide victims, Female",0.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+54,Melanesia,2005,"Intentional homicide rates per 100,000",8.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+54,Melanesia,2010,"Intentional homicide rates per 100,000",8.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+54,Melanesia,2015,"Intentional homicide rates per 100,000",7.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+54,Melanesia,2021,"Intentional homicide rates per 100,000",8.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+57,Micronesia,2005,"Intentional homicide rates per 100,000",4.0,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+57,Micronesia,2010,"Intentional homicide rates per 100,000",2.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+57,Micronesia,2015,"Intentional homicide rates per 100,000",3.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+57,Micronesia,2021,"Intentional homicide rates per 100,000",3.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2005,"Intentional homicide rates per 100,000",4.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2005,"Percentage of male and female intentional homicide victims, Male",7.6,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2005,"Percentage of male and female intentional homicide victims, Female",1.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2010,"Intentional homicide rates per 100,000",3.7,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2010,"Percentage of male and female intentional homicide victims, Male",6.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2010,"Percentage of male and female intentional homicide victims, Female",0.9,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2015,"Intentional homicide rates per 100,000",2.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2015,"Percentage of male and female intentional homicide victims, Male",3.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2015,"Percentage of male and female intentional homicide victims, Female",1.8,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2021,"Intentional homicide rates per 100,000",3.3,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2021,"Percentage of male and female intentional homicide victims, Male",5.5,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
+61,Polynesia,2021,"Percentage of male and female intentional homicide victims, Female",1.1,Estimate.,"United Nations Office on Drugs and Crime (UNODC), Vienna, UNODC Statistics database, last accessed May 2024."
\ No newline at end of file
diff --git a/data_storage/UN/Crime/UN_Crime_Continents.db b/data_storage/UN/Crime/UN_Crime_Continents.db
new file mode 100644
index 0000000000000000000000000000000000000000..5c65a9542fd1de60b8ca859f9fd3fd584cd5d6fd
GIT binary patch
literal 65536
zcmWFz^vNtqRY=P(%1ta$FlG>7U}R))P*7lCU=U|uU=UzH0DcAr1{MUDff0#~iz&{a
zS5?5vz`(%B@65pOj7!<5_-F`>hQMeDjE2By2#kinXb6mkz-S1JhQMeDjE2By2n_lV
zXtZKv7Z(*}Yzi+)Ov*`3Ni0bOVJ7DwSH}=ng%C$4A6Eq>kdTss2A7g&UP@|(l7gpS
zh^xD6kPerEf>KawdS-rJymNkOUP)19ykk*nqLM<0YeWcGHZnD_2u*!{dAv(%adJ^+
zK}miQlG3omoYGV!g&<c)AFx)p{QQ!<{F2mSBsIbLrA5i95CJYtRt5$JUj7}RKxXFu
z&Hs)6BmW!z=lqZO@9<yazrcTr{|Ns+h%`vaC>{-g(GVC7fzc2c4S~@R7!85Z5Eu=C
z(GVC7fzc2c4S~@RpmPYYHkL6kFt9ZyF)%Q&H~KR$FmN>5FfcH1Hfk|2FmN@3=I^;1
zK{NI|g`i%390LObpEm;o1HT1mW?vOFoi7BMn`h(JVBmM*%jKQIbAyMGTZ7L27`1LR
z1V%$(Gz3ONU^E0qLtr!nMnhmU1O{CQG=?_Ta52g=H43uJH>TPK<mXi8r50x<vOf(-
zElN(!D@jaGRme|M$W6>iRY=TBQAkS#Gc)r_Qu9hO^YapO6f*L2Gm|q@QWeTFlS?vl
zi**#-z>4fY&IEy3uEiypxrrsIdZBrlC8;S2eu*HB#R~puX_?8X3i){oE=8s3#bD!|
zi!yUl6*NNq{9T+ibrixfQ}gl?brisSh2WCJlFZ_g%;aJP(6nPxVsWaDLQZ0Fi9%v>
za%ypLYKnqyVx@wSfsu(`V{l_N*kioZ^q6mAPO5_#Bo+t8TNaH~oQ(2Jk?6ki#1<h%
zi6yDU3I(Y}3Wf#-ItB&?4qRzqFfeWpZL9=G33^()PldGh=L`s(9T<-VH&%c>hMv|a
z@)$U+@qwc&ZD71*(O8Zxt=%Uwt+5TD+d=(*A%?3A{Nj8%ym36G++AFII4^U&;E-as
zVDn|2%5sSLEwd?85@RpJRY-Oo0%W795GSJ~B=0jhrWIu-C$bY885*GMab|$>N01;F
zqa?JBfjRsZ<(b|=XaG}KV}JnIQ{X&L6;FXPyzw)zp9UtwoAP6%uUkZBb`7wz2dJP5
z;sZwoxL$!p#nmC7zIef&LP=i~c?z7qOa?T4@nEE{t3;+R&4El`8Qff)?$GipB)=pv
zM@JzsCr2R}ys#}ZwOAp)NFlK(HL;le85L3;BdFCpbAX!7@myf9@-oUdrqa->ptQ(2
zFom2qCnu*nq!K0IK_Zi;*nlQY4sd*di$46`p{Owm>Crhb4Ww7o*uh=}7l<_UDky0>
zC_|cq1C&D9h)kixHvYs1vP8*X1xFhZDU=#bLS|zy7?_AlV*z`Wh!jeZS0O2MAhV)3
zGm$Bj*yf|eK>8+w2^?)iq)>|5U(hm?WgvTEX^dd65|KhF@+vrms(^E%@qlDSQ2$?q
z!GM9^hA)&ihi3uzPOb}F(wu1=tJuG?+p{&X9%bcV@nJ4yn#1^jk(0roF|@G^JcI*I
z1W4nc6lGLMjN88%$QTc9ECqWE9OcyV7&v|<2QYpcEgDO(jZG0--tZ1&jTqWk42}}?
zv_?^ugQm3s9&;}Odkj6TQRFdjT9X^d`oW^H5L;R!w(BZ1kZnoJ#sW@8MM!tY(l;}?
zC?7h%LuBV>KnI{L8}qR`p4fKpfaY?`#yqT!C$@+h$l>!wqsCmY<3Ym!$jOGtG|w_1
zm42gPV-7f@f?RFpo0^kIQd;L27)M()W`i9Kn$bgYG_h%1ejsZy!^SMI+tC7?$Rs{M
z0dClsiOtbOChY-obZTP;7o$CN4ARuGw78@wF()$-JZbKiTCNb4nwXQAmqLvJNc#r^
zSz#qNrh`2SZbQ(@qo6j0{pW#fzj`#LaWdLN>ScVsB(9ns*e*tDV=6ex!0lN)o}t1B
zq&;N%Vu0qEk{eUN9wn4EDe@>dZGIWZE~7(ZGB|B=$~UIsi%#Ow=77|yp#HxwLk0uC
zB40Z1B%a+ojNCe0p`5chj<LUIH)Ts_oxpO0`7YBRCJV+uh73q~M-JJT+L#1R5`@zJ
zkRL}#ZcGGwlu+8I$fMx2KcMBZLt_FlX`jdz&VZ!-#@NPqa8wBr$iNhJ%OT?p1LMKu
z#yGGC38h7fJP1yUzX!IB5DQL=pq>Gqa+t`5tNno1DZz~~T#VAt_A94<a%y5;W+GKu
zs{^|7&#N&S>@DzoId!}RN_PX)e>Q83;$)PDG)fVkA+DNtU?0e=65JRGjt6ix40k$3
z?J!6I=fE(KEwRAH2(Y)n1s!#~1xj8H13EBf))<bN%7`8A7~oVE296HYR7O#Y2b#(T
zbYVqcV<^~LsHu!1Z-G-852QssFl_|0#t_U@Mr5;Xpv$sgaCD%iGK$(V&{Q^{E6V~K
zgTUTGO=T2$3!KXM2eRHVYYfCpWkfc}95@EDYKd+P;9}B*Hpm!eho=^oq!#5VxRw^>
z7o<{U`_DiQ)j<0H_6+>Wd@j6AJWIKcakFr#b9!*Jv9Dyi#3sRN%@V^ri)k<8Jw_P@
zdq_EjL^eh?`h!CUoLH$FI-o>5uw##QjeeX=nviB5rr(Hb?hWjSV|1f0IC{WEB!(BL
z(Ciyn??pEHfW3!3^-<)#!I1jAai=~an}GwnwJ^HT3miSzQy)d`CP+m+(5cT8>^<zM
zk0S34eCji6^Z=(m(9jr0!9is6a9|p=!Hw?VXaSGvVK|+lb`&Jl4UD%U8{NR(!k*eF
z@)kI?{T#^oal1xWaB2gM;9*7?ku~jrj@v~yx^OXSLz{`}!TF^n8B}g24(M!iWTP|K
zd*IYZUGITY-+(Utv}<(YWYmVV^DzBJWa=BpR(xZ0qa!$az%?y~7bt27LCU;=UF#6p
z=m7Q}_S8p__rR%dKxfkI8trkXK4RN>1Db!L8|}c+gFW?8)DVKEz5&f#k&U)s?_p1U
z6nPJv`UZ0D4AlP@Vq^#P|GjxTcvf+r;%4X4<n-idV_(5`f{m3`oyDEGm1zazNk(?0
ze*bV|Hrh4X;Le0ZHg^Yhup+wA8k|b8XF`hFhl3*%T7kWXJrh#oJy0eb*y$^~MoZkO
zkH}F{`)>oe^gpK2f{O{({AHNsmtREn_V0k!0a1<SVE=)WAC>(FN`LkPSqU`SH=1!W
zK^wqWJV#^;ctBfGF^#6+2m%*>n0}zBjW`&}zo<qNu>Wu*K#Ke~7!sf{o&-p2BY1!l
zpb<ENa3nyAnu*W^IG~OEs76Du|8OKgiu?ykfCF0t+cz5ENr1#Q0DnN*#RD@y7}KZ^
zjvyQfkfJ6MGyx9i2wPO69@u|45+FtX11G=%-EeN-sEa27659s+H;`?>kVYNw2(=(+
zmlMNu*F<X1lrs%X#)@pz2Kx(=@Tlr9aJrKoz>#-Q|6iD4CIi14Um@=-o(DYK+$LOA
zoJ%>*aqzI~vjwnDW!b@elUba}iZPmDCZu?y3)yJbsD+pkzzB5Wnxqbb1G(lUx=|CH
zZXg9Rx)&&Fu|djXhXGwU7TKr)_8#_ZL6P^s*+Ojqvqhs_qdM-?M`U}{L1tjrEvbQ{
z2Yc$HsJRA9eFN#e$VOGL_pqlvio6F-eX0YQ`pg?uz^RW>zA+V}A|<jh%04iaWptx5
zI9{+PJBk`<&}1h)kY##gqY~JA*pnSa-UBB)Q^+XSz{H(hqarxjfoI{->nkFgpbpvt
zSt<lKDsVBuPS9nT23@2{g~KKXc5FYeQ6B6qNUEcXx4@~5YaqJ|W{q;3Owd!B5m7~C
z!)`!VXa_gSf};ac#=)Y4q81ONY_lKGJz9Z{GGK3^rZS4W1x{rm16d-NHA-WqGGZHW
z1KPe0Zj=H?2Wl##sAU69Wdk}&5ZEXQ_7-X?qsUu>A(csBrZOTMY6IGfgY^HaK=c1u
zy!||zxIb}=b6Ig#am;5w#LmQ~#~Q&hgLyC0112@bK!z%6_WT=z8^ys10X2P7)P#bh
zZwKyyY#|0Vih;d_n!YLW7C3z?4{RwaikZHNZ4pXAlFh)hX(Jm&xR_L->oOT8!nW@?
zg6{62M!Rr8=WW9qg~6VKq%|sf4xHi!boj!iQHYaC6|yE1J=%zDBM#`T7eS4J;HZHN
zhNDIeMNKM588<*f;Q@^TU|)f^@uNixMZN+hxB(imuxaGSmC}f9Ck|*zi)`cr#|fk!
zMNMfGHLD;gZD3cXgg5enJ%_D?qsVih1m_?+kb`_SjXb#09nmevfou~*Hgbcb23xwL
zsJR14cLRHeLU<z=*mKy@9Yvl4r#tz9Y@pgSa^gyN#J1=Lv_~J=$ic;^4sFpX!FSqF
zt3~H9pf@9gH?o602Tpg?^c*<d4d{4=X(JmaqdHS0Xi@{+XT-JWm<Os0!3vHOa6yOW
za*7%~(1MO-0Q*Of{(l?;zdBzsZwt?A?&sVbT<V<394+jN+3vF`u)48iF|T5}#`u%b
zk|7S_P~yqP@J1GJ&|yo?6a^hPIS=UUzD*-DI5~qROVASqamjf=2YwnO8=1gSgDq84
z)Utx6>H$4~D4>xM>^X2h1ub?c@*F7Lu?|czWYfriE5Q-lUL4RPU?S_mQGzYKQPiS>
zrndoIy%$~w_8Ychjv~K-lAFVTwzh0)aV0up8;b*)=p1V}84V$$NXp=*qHZd5St6vp
zNL)!hu=8?p)m)5*(Dp7iPYn4h$YZL&9t7tes(TQeg$DEr9>+?&Y49m=X>efAB8;m5
zM-jO2#uh~sHRd2C_`n|K5>pQLAkH*Mkq5zPa6ktM9n0{hL1G6wSqE~!EUXk9Mc{K?
zu%$tY8g`I0I4~`{m=dtZaHc(qJT?f@UNPRZM{MJDK=1hpD*{Im&a_8SD{lbP9;E+&
zhJjy)FPC>R&vx$r+^SrjoLw9n*srjQvRSjnvn*tO&8*9m&$yc54Dmhxfl%2PQwWYE
zocV~NNE!tBr~q$1BDOs~p!vu;pOX<ft1AcFAVgA2d_Ye@vd+WddLrx3fxVT*I2Y`C
z(1~uSVNYZUJTR4`bq?6opkX#tR}-1u?FaN=v&d}lG!nSo%+T+gng_a$N&%AM15%5U
zQ}ap^(^D1l(-d+Ob5g;#RHdbYnVESdsd*)t`FV*s3K{vinaP<csS0J8$t9VU*
zDq~=q%;8yJzk!QeYWfXa(lQQYOVcJ3F++wHX~cEb1~}1WfFlN5qNAuA15I=TdeBIC
zI@oX65*<Z;11GuxJ?`Ho4OgNgvUYJ8$cd!J$W(B|U`uoq^<N-~ZeaZuo&xq8wnRsf
z-@u7ZZXg$Nm?nc09cWG#tq3QwQ7}N0A(2Vo7{Qj>C~D<HQ`>-Uj0sN!`wd%aqsVXI
z)TT0!TYhX3z^M(?mP1QzL^kFeqy{px1jchQi9!eB8TzQ!h#ScI6w?29W8fF%)8LKZ
z$>na~+Q4~~;|7NYdl*|2>uHvsEUL_TOmi4dFiJ4E;p){l`p1Do29ji{5HjGTI-oOp
zy0M&0qL9TZu&5@k={G<ta|2_*F#stLAu&Kvdk9hx+7IZ7HvZ9IKOv_oiu?plRh$Fa
zu`r1Orz&s(2#qA-Qq{n&N(+nxM+9=>qNv>iO<V)Icfvmc>?h>JMUkJtiHm0-t0$9i
z^u$GE8_r=sr*#6uz!8C*xF~AoKoi%1Zl(1P1^Wp(aZ%(aaN-ge$flca2sm+pI|`7J
zi^wM104>_g3g%*Rhql!i7yBfZWacS2=B5^9CMPPWDU@WSDmW(=WhN!1CgxG&c1;Jq
zfsCAtAh2h_$&IF-1*bzt$T^DxGaT$2$jRgmS<pk!r$kn*#sk?R$O-^Q9k}!(<ROY0
zKagV4VL%I!41cg^iAtvwc@~^bT@HZzD+82H{fJJd#18M74QM*`1xFoG>6D^&6fB(%
zWJ@Z;2kcp*(kVrr1*cQjo1loDH6ZB}(*L)Io&R@(`!}}?R}^Op#~Sum?7VDxti>$T
zn71=MXZ*v+kL~_HUvHw5IkAmV^MQ={EH7}(6P3&<YSBTH`GC$iWO#x-OH?wa$g|*N
z?z9=a>uo@id84lf(dm@PcCCZSK(_c|+_@Naq0L)S_-Xsl1};?^v;#W&7Uc%^9yn!E
z*?Zu$s5FpejD;&Fqb_7<5sTl5YqYWrOg4&f0mlotc*Jx&MNKwHfoMOVXA?y^gT03%
z*-_*@aI%vHmw?6t6L<Db;A96Hd&ClT#3eh20bRr#>IjY=@R1srUZAKU21$JbG<F~C
z0QMJnvl^BC1xj`UbgqWIJ)ZPNY-3Om)HI$sFm2<;7&~yh;3(}VY7s%w+rXZ25M>MY
z9*)wEBJY8cor5B{`^_*wrJW6))JJR+Z$Qrn39;s4l!Z3&grP0FVyZOl26S~pkQLZl
z;8aH?Z-G;r)j-y*=9Zj{vXD_pBtH>Zr|J%%%OU;$R0e)IzDV9mp6T3|xIS?SaC&oO
zvv;zcXZ^*h%#z7Gg=sGn7o!bBDkMXbOg4sCfa4rokRrl|qV^QD03Fbz>}?MA7P#J~
zlD9xfS$1GbOan7;8V1eqAbEzkG%PSMP7W~zM*v#7qC!J(V2_XtG68!Ft%#(^TcC91
zU^jpTO{2LnIC+7(ABf~dY%|bcAe(_9M&Rf`OJx+bkD#U3fUZReG6Z`IEtOH^EpRHc
z8pv@za|0}?jM(O$?m(upczrG=*e-vDQ^BQ4y1|JViA9Nd3XW-@S!=4a{6q(`1c=oG
z`w*PqsP98?+A|->F<B>FPA2GC6WF~+TwUs*GoZ;(2OLS@!Var1sL^U0&=XB!wZT5b
zoeU}RAvhVD4dn2$lNSDDNbGd;fL`PguL+JM+{uul))2J%9oS^30rny8WJr+@A<3`-
z+*KQxwz-o!{$xmO(@%RqOG7nqB;ihm6g8Ki$#5VmWk~<Ol!0HDFM@Xg&lT?f+;&_^
zoGl!O*`Kouu=%qVvrJ{a!t{eliZPU-6r7wWCmLf_!NH0<?Nb!2;IwZc2}(BuG;r*s
zf<NsO-5?#v=32Be7bEOOcYeeaGxZvyOas|ii&O&p4x9w3>pO7rQ-$P`fhl_J6ge58
zx4C0_jmSnQIQtCL#7ndSIC8+nE`|>%YMw!hT!w*cphe1qeTO~iQRF*t(o-JLq$h_v
z=@HxT6d%Y^FGLm`Ip8^FjHE|VlMIsd255>oQU>fT>}if7Z-LX?fUc*plg6Fqh;3zx
z4P=23Ed`Do?8O~LO(95{8`woPk&<BFVNZG#`3{`)6bG`ju#>=@^oVWb4P^7bF-V+?
z5q4iD6BP#<g$FWLJjKAC0?*4)#Z#b!COR-}Ia5(iM(8D(aIX;Agwq_zGA&3190%Ys
i4d!r)+BT4)Y+x6l1qg#Z1un{{;wezVaxfXdyaE6<0G4$C
literal 0
HcmV?d00001
diff --git a/data_storage/UN/Economy/GDP_per_capita_continents.csv b/data_storage/UN/Economy/GDP_per_capita_continents.csv
new file mode 100644
index 0000000..1f3455e
--- /dev/null
+++ b/data_storage/UN/Economy/GDP_per_capita_continents.csv
@@ -0,0 +1,504 @@
+Index,Region_Country_Area,Year,Row_Descriptor,Value,Footnotes,Source
+1,"Total, all countries or areas",2005,GDP in current prices (millions of US dollars),"47,816,593",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2010,GDP in current prices (millions of US dollars),"66,633,612",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2015,GDP in current prices (millions of US dollars),"75,440,153",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2020,GDP in current prices (millions of US dollars),"85,483,570",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2021,GDP in current prices (millions of US dollars),"97,329,051",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2022,GDP in current prices (millions of US dollars),"100,834,796",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",1995,GDP per capita (US dollars),"5,450",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2005,GDP per capita (US dollars),"7,293",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2010,GDP per capita (US dollars),"9,541",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2015,GDP per capita (US dollars),"10,161",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2020,GDP per capita (US dollars),"10,905",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2021,GDP per capita (US dollars),"12,309",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2022,GDP per capita (US dollars),"12,647",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",1995,GDP in constant 2015 prices (millions of US dollars),"40,338,168",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2005,GDP in constant 2015 prices (millions of US dollars),"56,485,238",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2010,GDP in constant 2015 prices (millions of US dollars),"64,936,404",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2015,GDP in constant 2015 prices (millions of US dollars),"75,440,153",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2020,GDP in constant 2015 prices (millions of US dollars),"82,306,867",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2021,GDP in constant 2015 prices (millions of US dollars),"87,439,828",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2022,GDP in constant 2015 prices (millions of US dollars),"90,126,325",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",1995,GDP real rates of growth (percent),3.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2005,GDP real rates of growth (percent),4.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2010,GDP real rates of growth (percent),4.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2015,GDP real rates of growth (percent),3.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2020,GDP real rates of growth (percent),-2.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2021,GDP real rates of growth (percent),6.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+1,"Total, all countries or areas",2022,GDP real rates of growth (percent),3.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,1995,GDP in current prices (millions of US dollars),"604,665",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2005,GDP in current prices (millions of US dollars),"1,171,085",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2010,GDP in current prices (millions of US dollars),"2,033,221",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2015,GDP in current prices (millions of US dollars),"2,409,648",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2020,GDP in current prices (millions of US dollars),"2,447,535",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2021,GDP in current prices (millions of US dollars),"2,734,236",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2022,GDP in current prices (millions of US dollars),"2,870,757",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,1995,GDP per capita (US dollars),836,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2005,GDP per capita (US dollars),"1,264",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2010,GDP per capita (US dollars),"1,930",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2015,GDP per capita (US dollars),"2,009",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2020,GDP per capita (US dollars),"1,801",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2021,GDP per capita (US dollars),"1,964",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2022,GDP per capita (US dollars),"2,015",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,1995,GDP in constant 2015 prices (millions of US dollars),"984,617",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2005,GDP in constant 2015 prices (millions of US dollars),"1,534,059",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2010,GDP in constant 2015 prices (millions of US dollars),"1,995,795",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2015,GDP in constant 2015 prices (millions of US dollars),"2,409,648",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2020,GDP in constant 2015 prices (millions of US dollars),"2,635,713",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2021,GDP in constant 2015 prices (millions of US dollars),"2,777,729",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2022,GDP in constant 2015 prices (millions of US dollars),"2,875,884",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,1995,GDP real rates of growth (percent),2.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2005,GDP real rates of growth (percent),6.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2010,GDP real rates of growth (percent),5.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2015,GDP real rates of growth (percent),3.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2020,GDP real rates of growth (percent),-2.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2021,GDP real rates of growth (percent),5.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+2,Africa,2022,GDP real rates of growth (percent),3.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,1995,GDP in current prices (millions of US dollars),"207,392",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2005,GDP in current prices (millions of US dollars),"376,507",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2010,GDP in current prices (millions of US dollars),"646,437",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2015,GDP in current prices (millions of US dollars),"772,568",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2020,GDP in current prices (millions of US dollars),"762,299",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2021,GDP in current prices (millions of US dollars),"852,083",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2022,GDP in current prices (millions of US dollars),"855,580",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,1995,GDP per capita (US dollars),"1,281",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2005,GDP per capita (US dollars),"1,922",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2010,GDP per capita (US dollars),"3,127",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2015,GDP per capita (US dollars),"3,390",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2020,GDP per capita (US dollars),"3,039",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2021,GDP per capita (US dollars),"3,339",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2022,GDP per capita (US dollars),"3,298",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,1995,GDP in constant 2015 prices (millions of US dollars),"354,910",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2005,GDP in constant 2015 prices (millions of US dollars),"557,673",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2010,GDP in constant 2015 prices (millions of US dollars),"700,055",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2015,GDP in constant 2015 prices (millions of US dollars),"772,568",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2020,GDP in constant 2015 prices (millions of US dollars),"869,168",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2021,GDP in constant 2015 prices (millions of US dollars),"932,388",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2022,GDP in constant 2015 prices (millions of US dollars),"959,918",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,1995,GDP real rates of growth (percent),2.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2005,GDP real rates of growth (percent),6.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2010,GDP real rates of growth (percent),5.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2015,GDP real rates of growth (percent),3.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2020,GDP real rates of growth (percent),-3.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2021,GDP real rates of growth (percent),7.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+15,Northern Africa,2022,GDP real rates of growth (percent),3.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,1995,GDP in current prices (millions of US dollars),"397,273",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2005,GDP in current prices (millions of US dollars),"794,578",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2010,GDP in current prices (millions of US dollars),"1,386,785",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2015,GDP in current prices (millions of US dollars),"1,637,080",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2020,GDP in current prices (millions of US dollars),"1,685,236",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2021,GDP in current prices (millions of US dollars),"1,882,153",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2022,GDP in current prices (millions of US dollars),"2,015,177",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,1995,GDP per capita (US dollars),708,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2005,GDP per capita (US dollars),"1,088",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2010,GDP per capita (US dollars),"1,637",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2015,GDP per capita (US dollars),"1,685",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2020,GDP per capita (US dollars),"1,521",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2021,GDP per capita (US dollars),"1,656",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2022,GDP per capita (US dollars),"1,729",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,1995,GDP in constant 2015 prices (millions of US dollars),"629,707",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2005,GDP in constant 2015 prices (millions of US dollars),"976,386",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2010,GDP in constant 2015 prices (millions of US dollars),"1,295,740",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2015,GDP in constant 2015 prices (millions of US dollars),"1,637,080",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2020,GDP in constant 2015 prices (millions of US dollars),"1,766,545",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2021,GDP in constant 2015 prices (millions of US dollars),"1,845,341",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2022,GDP in constant 2015 prices (millions of US dollars),"1,915,966",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,1995,GDP real rates of growth (percent),3.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2005,GDP real rates of growth (percent),6.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2010,GDP real rates of growth (percent),6.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2015,GDP real rates of growth (percent),3.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2020,GDP real rates of growth (percent),-1.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2021,GDP real rates of growth (percent),4.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+202,Sub-Saharan Africa,2022,GDP real rates of growth (percent),3.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,1995,GDP in current prices (millions of US dollars),"71,188",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2005,GDP in current prices (millions of US dollars),"117,409",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2010,GDP in current prices (millions of US dollars),"235,948",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2015,GDP in current prices (millions of US dollars),"330,690",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2020,GDP in current prices (millions of US dollars),"425,948",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2021,GDP in current prices (millions of US dollars),"460,290",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2022,GDP in current prices (millions of US dollars),"512,915",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,1995,GDP per capita (US dollars),326,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2005,GDP per capita (US dollars),407,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2010,GDP per capita (US dollars),691,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2015,GDP per capita (US dollars),843,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2020,GDP per capita (US dollars),951,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2021,GDP per capita (US dollars),"1,001",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2022,GDP per capita (US dollars),"1,087",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,1995,GDP in constant 2015 prices (millions of US dollars),"110,361",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2005,GDP in constant 2015 prices (millions of US dollars),"165,872",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2010,GDP in constant 2015 prices (millions of US dollars),"244,330",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2015,GDP in constant 2015 prices (millions of US dollars),"330,690",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2020,GDP in constant 2015 prices (millions of US dollars),"410,573",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2021,GDP in constant 2015 prices (millions of US dollars),"433,454",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2022,GDP in constant 2015 prices (millions of US dollars),"455,154",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,1995,GDP real rates of growth (percent),4.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2005,GDP real rates of growth (percent),6.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2010,GDP real rates of growth (percent),9.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2015,GDP real rates of growth (percent),6.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2020,GDP real rates of growth (percent),0.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2021,GDP real rates of growth (percent),5.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+14,Eastern Africa,2022,GDP real rates of growth (percent),5.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,1995,GDP in current prices (millions of US dollars),"37,554",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2005,GDP in current prices (millions of US dollars),"101,403",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2010,GDP in current prices (millions of US dollars),"191,153",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2015,GDP in current prices (millions of US dollars),"242,684",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2020,GDP in current prices (millions of US dollars),"195,536",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2021,GDP in current prices (millions of US dollars),"234,765",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2022,GDP in current prices (millions of US dollars),"287,184",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,1995,GDP per capita (US dollars),441,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2005,GDP per capita (US dollars),892,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2010,GDP per capita (US dollars),"1,431",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2015,GDP per capita (US dollars),"1,542",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2020,GDP per capita (US dollars),"1,059",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2021,GDP per capita (US dollars),"1,234",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2022,GDP per capita (US dollars),"1,465",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,1995,GDP in constant 2015 prices (millions of US dollars),"85,635",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2005,GDP in constant 2015 prices (millions of US dollars),"140,505",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2010,GDP in constant 2015 prices (millions of US dollars),"192,186",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2015,GDP in constant 2015 prices (millions of US dollars),"242,684",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2020,GDP in constant 2015 prices (millions of US dollars),"239,188",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2021,GDP in constant 2015 prices (millions of US dollars),"244,752",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2022,GDP in constant 2015 prices (millions of US dollars),"254,834",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,1995,GDP real rates of growth (percent),6.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2005,GDP real rates of growth (percent),9.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2010,GDP real rates of growth (percent),4.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2015,GDP real rates of growth (percent),2.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2020,GDP real rates of growth (percent),-2.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2021,GDP real rates of growth (percent),2.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+17,Middle Africa,2022,GDP real rates of growth (percent),4.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,1995,GDP in current prices (millions of US dollars),"183,240",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2005,GDP in current prices (millions of US dollars),"310,532",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2010,GDP in current prices (millions of US dollars),"448,120",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2015,GDP in current prices (millions of US dollars),"377,771",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2020,GDP in current prices (millions of US dollars),"369,839",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2021,GDP in current prices (millions of US dollars),"458,451",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2022,GDP in current prices (millions of US dollars),"444,845",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,1995,GDP per capita (US dollars),"3,663",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2005,GDP per capita (US dollars),"5,553",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2010,GDP per capita (US dollars),"7,583",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2015,GDP per capita (US dollars),"5,929",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2020,GDP per capita (US dollars),"5,498",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2021,GDP per capita (US dollars),"6,743",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2022,GDP per capita (US dollars),"6,485",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,1995,GDP in constant 2015 prices (millions of US dollars),"207,820",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2005,GDP in constant 2015 prices (millions of US dollars),"289,208",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2010,GDP in constant 2015 prices (millions of US dollars),"337,096",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2015,GDP in constant 2015 prices (millions of US dollars),"377,771",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2020,GDP in constant 2015 prices (millions of US dollars),"369,421",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2021,GDP in constant 2015 prices (millions of US dollars),"387,810",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2022,GDP in constant 2015 prices (millions of US dollars),"395,964",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,1995,GDP real rates of growth (percent),3.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2005,GDP real rates of growth (percent),5.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2010,GDP real rates of growth (percent),3.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2015,GDP real rates of growth (percent),1.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2020,GDP real rates of growth (percent),-6.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2021,GDP real rates of growth (percent),5.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+18,Southern Africa,2022,GDP real rates of growth (percent),2.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,1995,GDP in current prices (millions of US dollars),"105,290",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2005,GDP in current prices (millions of US dollars),"265,234",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2010,GDP in current prices (millions of US dollars),"511,565",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2015,GDP in current prices (millions of US dollars),"685,936",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2020,GDP in current prices (millions of US dollars),"693,913",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2021,GDP in current prices (millions of US dollars),"728,646",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2022,GDP in current prices (millions of US dollars),"770,232",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,1995,GDP per capita (US dollars),506,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2005,GDP per capita (US dollars),974,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2010,GDP per capita (US dollars),"1,636",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2015,GDP per capita (US dollars),"1,915",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2020,GDP per capita (US dollars),"1,700",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2021,GDP per capita (US dollars),"1,741",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2022,GDP per capita (US dollars),"1,795",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,1995,GDP in constant 2015 prices (millions of US dollars),"225,893",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2005,GDP in constant 2015 prices (millions of US dollars),"380,802",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2010,GDP in constant 2015 prices (millions of US dollars),"522,128",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2015,GDP in constant 2015 prices (millions of US dollars),"685,936",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2020,GDP in constant 2015 prices (millions of US dollars),"747,364",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2021,GDP in constant 2015 prices (millions of US dollars),"779,325",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2022,GDP in constant 2015 prices (millions of US dollars),"810,013",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,1995,GDP real rates of growth (percent),1.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2005,GDP real rates of growth (percent),6.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2010,GDP real rates of growth (percent),7.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2015,GDP real rates of growth (percent),3.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2020,GDP real rates of growth (percent),-0.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2021,GDP real rates of growth (percent),4.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+11,Western Africa,2022,GDP real rates of growth (percent),3.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,1995,GDP in current prices (millions of US dollars),"10,242,888",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2005,GDP in current prices (millions of US dollars),"17,124,347",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2010,GDP in current prices (millions of US dollars),"22,077,292",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2015,GDP in current prices (millions of US dollars),"25,414,810",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2020,GDP in current prices (millions of US dollars),"27,666,347",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2021,GDP in current prices (millions of US dollars),"31,004,182",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2022,GDP in current prices (millions of US dollars),"34,020,481",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,1995,GDP per capita (US dollars),"13,176",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2005,GDP per capita (US dollars),"19,328",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2010,GDP per capita (US dollars),"23,622",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2015,GDP per capita (US dollars),"25,872",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2020,GDP per capita (US dollars),"27,003",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2021,GDP per capita (US dollars),"30,097",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2022,GDP per capita (US dollars),"32,842",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,1995,GDP in constant 2015 prices (millions of US dollars),"15,249,801",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2005,GDP in constant 2015 prices (millions of US dollars),"21,080,187",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2010,GDP in constant 2015 prices (millions of US dollars),"22,747,677",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2015,GDP in constant 2015 prices (millions of US dollars),"25,414,810",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2020,GDP in constant 2015 prices (millions of US dollars),"26,454,540",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2021,GDP in constant 2015 prices (millions of US dollars),"28,033,939",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2022,GDP in constant 2015 prices (millions of US dollars),"28,714,113",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,1995,GDP real rates of growth (percent),2.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2005,GDP real rates of growth (percent),3.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2010,GDP real rates of growth (percent),3.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2015,GDP real rates of growth (percent),2.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2020,GDP real rates of growth (percent),-3.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2021,GDP real rates of growth (percent),6.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+19,Americas,2022,GDP real rates of growth (percent),2.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,1995,GDP in current prices (millions of US dollars),"8,249,570",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2005,GDP in current prices (millions of US dollars),"14,219,073",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2010,GDP in current prices (millions of US dollars),"16,675,376",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2015,GDP in current prices (millions of US dollars),"19,860,284",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2020,GDP in current prices (millions of US dollars),"22,980,568",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2021,GDP in current prices (millions of US dollars),"25,606,009",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2022,GDP in current prices (millions of US dollars),"27,892,511",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,1995,GDP per capita (US dollars),"27,958",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2005,GDP per capita (US dollars),"43,196",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2010,GDP per capita (US dollars),"48,297",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2015,GDP per capita (US dollars),"55,097",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2020,GDP per capita (US dollars),"61,453",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2021,GDP per capita (US dollars),"68,233",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2022,GDP per capita (US dollars),"74,012",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,1995,GDP in constant 2015 prices (millions of US dollars),"12,070,353",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2005,GDP in constant 2015 prices (millions of US dollars),"16,891,978",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2010,GDP in constant 2015 prices (millions of US dollars),"17,751,958",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2015,GDP in constant 2015 prices (millions of US dollars),"19,860,284",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2020,GDP in constant 2015 prices (millions of US dollars),"21,309,921",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2021,GDP in constant 2015 prices (millions of US dollars),"22,533,082",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2022,GDP in constant 2015 prices (millions of US dollars),"22,994,457",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,1995,GDP real rates of growth (percent),2.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2005,GDP real rates of growth (percent),3.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2010,GDP real rates of growth (percent),2.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2015,GDP real rates of growth (percent),2.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2020,GDP real rates of growth (percent),-2.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2021,GDP real rates of growth (percent),5.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+21,Northern America,2022,GDP real rates of growth (percent),2.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,1995,GDP in current prices (millions of US dollars),"1,993,319",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2005,GDP in current prices (millions of US dollars),"2,905,274",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2010,GDP in current prices (millions of US dollars),"5,401,916",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2015,GDP in current prices (millions of US dollars),"5,554,527",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2020,GDP in current prices (millions of US dollars),"4,685,778",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2021,GDP in current prices (millions of US dollars),"5,398,173",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2022,GDP in current prices (millions of US dollars),"6,127,970",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,1995,GDP per capita (US dollars),"4,133",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2005,GDP per capita (US dollars),"5,218",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2010,GDP per capita (US dollars),"9,166",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2015,GDP per capita (US dollars),"8,932",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2020,GDP per capita (US dollars),"7,202",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2021,GDP per capita (US dollars),"8,243",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2022,GDP per capita (US dollars),"9,298",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,1995,GDP in constant 2015 prices (millions of US dollars),"3,179,449",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2005,GDP in constant 2015 prices (millions of US dollars),"4,188,209",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2010,GDP in constant 2015 prices (millions of US dollars),"4,995,719",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2015,GDP in constant 2015 prices (millions of US dollars),"5,554,527",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2020,GDP in constant 2015 prices (millions of US dollars),"5,144,619",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2021,GDP in constant 2015 prices (millions of US dollars),"5,500,857",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2022,GDP in constant 2015 prices (millions of US dollars),"5,719,657",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,1995,GDP real rates of growth (percent),1.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2005,GDP real rates of growth (percent),4.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2010,GDP real rates of growth (percent),5.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2015,GDP real rates of growth (percent),0.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2020,GDP real rates of growth (percent),-7.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2021,GDP real rates of growth (percent),6.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+419,Latin America & the Caribbean,2022,GDP real rates of growth (percent),4.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,1995,GDP in current prices (millions of US dollars),"121,859",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2005,GDP in current prices (millions of US dollars),"226,610",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2010,GDP in current prices (millions of US dollars),"297,212",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2015,GDP in current prices (millions of US dollars),"354,748",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2020,GDP in current prices (millions of US dollars),"375,791",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2021,GDP in current prices (millions of US dollars),"424,831",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2022,GDP in current prices (millions of US dollars),"483,941",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,1995,GDP per capita (US dollars),"3,442",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2005,GDP per capita (US dollars),"5,817",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2010,GDP per capita (US dollars),"7,350",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2015,GDP per capita (US dollars),"8,486",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2020,GDP per capita (US dollars),"8,734",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2021,GDP per capita (US dollars),"9,823",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2022,GDP per capita (US dollars),"11,135",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,1995,GDP in constant 2015 prices (millions of US dollars),"202,807",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2005,GDP in constant 2015 prices (millions of US dollars),"294,658",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2010,GDP in constant 2015 prices (millions of US dollars),"325,063",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2015,GDP in constant 2015 prices (millions of US dollars),"354,748",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2020,GDP in constant 2015 prices (millions of US dollars),"339,192",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2021,GDP in constant 2015 prices (millions of US dollars),"354,039",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2022,GDP in constant 2015 prices (millions of US dollars),"367,262",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,1995,GDP real rates of growth (percent),4.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2005,GDP real rates of growth (percent),3.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2010,GDP real rates of growth (percent),1.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2015,GDP real rates of growth (percent),2.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2020,GDP real rates of growth (percent),-8.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2021,GDP real rates of growth (percent),4.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+29,Caribbean,2022,GDP real rates of growth (percent),3.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,1995,GDP in current prices (millions of US dollars),"432,357",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2005,GDP in current prices (millions of US dollars),"1,012,333",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2010,GDP in current prices (millions of US dollars),"1,258,279",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2015,GDP in current prices (millions of US dollars),"1,446,809",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2020,GDP in current prices (millions of US dollars),"1,381,514",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2021,GDP in current prices (millions of US dollars),"1,605,656",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2022,GDP in current prices (millions of US dollars),"1,785,939",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,1995,GDP per capita (US dollars),"3,512",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2005,GDP per capita (US dollars),"6,956",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2010,GDP per capita (US dollars),"8,063",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2015,GDP per capita (US dollars),"8,654",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2020,GDP per capita (US dollars),"7,834",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2021,GDP per capita (US dollars),"9,038",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2022,GDP per capita (US dollars),"9,974",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,1995,GDP in constant 2015 prices (millions of US dollars),"828,947",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2005,GDP in constant 2015 prices (millions of US dollars),"1,154,309",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2010,GDP in constant 2015 prices (millions of US dollars),"1,252,684",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2015,GDP in constant 2015 prices (millions of US dollars),"1,446,809",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2020,GDP in constant 2015 prices (millions of US dollars),"1,415,834",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2021,GDP in constant 2015 prices (millions of US dollars),"1,509,084",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2022,GDP in constant 2015 prices (millions of US dollars),"1,573,131",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,1995,GDP real rates of growth (percent),-4.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2005,GDP real rates of growth (percent),2.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2010,GDP real rates of growth (percent),4.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2015,GDP real rates of growth (percent),3.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2020,GDP real rates of growth (percent),-8.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2021,GDP real rates of growth (percent),6.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+13,Central America,2022,GDP real rates of growth (percent),4.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,1995,GDP in current prices (millions of US dollars),"1,439,103",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2005,GDP in current prices (millions of US dollars),"1,666,331",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2010,GDP in current prices (millions of US dollars),"3,846,426",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2015,GDP in current prices (millions of US dollars),"3,752,970",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2020,GDP in current prices (millions of US dollars),"2,928,474",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2021,GDP in current prices (millions of US dollars),"3,367,686",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2022,GDP in current prices (millions of US dollars),"3,858,090",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,1995,GDP per capita (US dollars),"4,444",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2005,GDP per capita (US dollars),"4,476",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2010,GDP per capita (US dollars),"9,791",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2015,GDP per capita (US dollars),"9,090",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2020,GDP per capita (US dollars),"6,791",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2021,GDP per capita (US dollars),"7,760",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2022,GDP per capita (US dollars),"8,839",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,1995,GDP in constant 2015 prices (millions of US dollars),"2,147,695",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2005,GDP in constant 2015 prices (millions of US dollars),"2,739,242",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2010,GDP in constant 2015 prices (millions of US dollars),"3,417,973",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2015,GDP in constant 2015 prices (millions of US dollars),"3,752,970",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2020,GDP in constant 2015 prices (millions of US dollars),"3,389,594",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2021,GDP in constant 2015 prices (millions of US dollars),"3,637,734",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2022,GDP in constant 2015 prices (millions of US dollars),"3,779,263",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,1995,GDP real rates of growth (percent),3.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2005,GDP real rates of growth (percent),5.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2010,GDP real rates of growth (percent),6.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2015,GDP real rates of growth (percent),-1.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2020,GDP real rates of growth (percent),-6.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2021,GDP real rates of growth (percent),7.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+5,South America,2022,GDP real rates of growth (percent),3.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,1995,GDP in current prices (millions of US dollars),"9,324,655",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2005,GDP in current prices (millions of US dollars),"12,487,279",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2010,GDP in current prices (millions of US dollars),"21,143,028",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2015,GDP in current prices (millions of US dollars),"26,966,511",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2020,GDP in current prices (millions of US dollars),"32,632,452",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2021,GDP in current prices (millions of US dollars),"37,500,174",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2022,GDP in current prices (millions of US dollars),"38,004,625",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,1995,GDP per capita (US dollars),"2,677",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2005,GDP per capita (US dollars),"3,138",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2010,GDP per capita (US dollars),"5,010",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2015,GDP per capita (US dollars),"6,048",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2020,GDP per capita (US dollars),"6,997",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2021,GDP per capita (US dollars),"7,989",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2022,GDP per capita (US dollars),"8,049",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,1995,GDP in constant 2015 prices (millions of US dollars),"10,036,707",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2005,GDP in constant 2015 prices (millions of US dollars),"15,697,678",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2010,GDP in constant 2015 prices (millions of US dollars),"20,870,686",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2015,GDP in constant 2015 prices (millions of US dollars),"26,966,511",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2020,GDP in constant 2015 prices (millions of US dollars),"32,005,321",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2021,GDP in constant 2015 prices (millions of US dollars),"34,117,438",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2022,GDP in constant 2015 prices (millions of US dollars),"35,357,380",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,1995,GDP real rates of growth (percent),5.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2005,GDP real rates of growth (percent),6.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2010,GDP real rates of growth (percent),7.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2015,GDP real rates of growth (percent),5.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2020,GDP real rates of growth (percent),-0.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2021,GDP real rates of growth (percent),6.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+142,Asia,2022,GDP real rates of growth (percent),3.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,1995,GDP in current prices (millions of US dollars),"41,632",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2005,GDP in current prices (millions of US dollars),"93,155",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2010,GDP in current prices (millions of US dollars),"231,077",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2015,GDP in current prices (millions of US dollars),"321,586",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2020,GDP in current prices (millions of US dollars),"293,363",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2021,GDP in current prices (millions of US dollars),"340,224",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2022,GDP in current prices (millions of US dollars),"394,320",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,1995,GDP per capita (US dollars),768,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2005,GDP per capita (US dollars),"1,573",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2010,GDP per capita (US dollars),"3,632",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2015,GDP per capita (US dollars),"4,661",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2020,GDP per capita (US dollars),"3,926",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2021,GDP per capita (US dollars),"4,483",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2022,GDP per capita (US dollars),"5,118",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,1995,GDP in constant 2015 prices (millions of US dollars),"97,467",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2005,GDP in constant 2015 prices (millions of US dollars),"169,983",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2010,GDP in constant 2015 prices (millions of US dollars),"245,266",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2015,GDP in constant 2015 prices (millions of US dollars),"321,586",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2020,GDP in constant 2015 prices (millions of US dollars),"374,436",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2021,GDP in constant 2015 prices (millions of US dollars),"394,728",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2022,GDP in constant 2015 prices (millions of US dollars),"410,564",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,1995,GDP real rates of growth (percent),-6.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2005,GDP real rates of growth (percent),9.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2010,GDP real rates of growth (percent),8.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2015,GDP real rates of growth (percent),3.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2020,GDP real rates of growth (percent),-1.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2021,GDP real rates of growth (percent),5.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+143,Central Asia,2022,GDP real rates of growth (percent),4.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,1995,GDP in current prices (millions of US dollars),"7,283,959",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2005,GDP in current prices (millions of US dollars),"8,636,076",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2010,GDP in current prices (millions of US dollars),"13,712,623",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2015,GDP in current prices (millions of US dollars),"17,889,125",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2020,GDP in current prices (millions of US dollars),"22,453,469",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2021,GDP in current prices (millions of US dollars),"25,852,085",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2022,GDP in current prices (millions of US dollars),"25,047,265",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,1995,GDP per capita (US dollars),"5,054",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2005,GDP per capita (US dollars),"5,618",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2010,GDP per capita (US dollars),"8,663",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2015,GDP per capita (US dollars),"10,966",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2020,GDP per capita (US dollars),"13,503",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2021,GDP per capita (US dollars),"15,542",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2022,GDP per capita (US dollars),"15,063",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,1995,GDP in constant 2015 prices (millions of US dollars),"6,641,899",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2005,GDP in constant 2015 prices (millions of US dollars),"10,311,021",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2010,GDP in constant 2015 prices (millions of US dollars),"13,827,799",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2015,GDP in constant 2015 prices (millions of US dollars),"17,889,125",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2020,GDP in constant 2015 prices (millions of US dollars),"21,591,473",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2021,GDP in constant 2015 prices (millions of US dollars),"23,055,637",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2022,GDP in constant 2015 prices (millions of US dollars),"23,619,905",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,1995,GDP real rates of growth (percent),5.5,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2005,GDP real rates of growth (percent),6.2,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2010,GDP real rates of growth (percent),8.1,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2015,GDP real rates of growth (percent),4.9,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2020,GDP real rates of growth (percent),0.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2021,GDP real rates of growth (percent),6.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+30,Eastern Asia,2022,GDP real rates of growth (percent),2.4,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,1995,GDP in current prices (millions of US dollars),"706,465",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2005,GDP in current prices (millions of US dollars),"962,280",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2010,GDP in current prices (millions of US dollars),"2,021,184",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2015,GDP in current prices (millions of US dollars),"2,526,717",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2020,GDP in current prices (millions of US dollars),"3,092,737",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2021,GDP in current prices (millions of US dollars),"3,384,423",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2022,GDP in current prices (millions of US dollars),"3,630,588",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,1995,GDP per capita (US dollars),"1,459",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2005,GDP per capita (US dollars),"1,711",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2010,GDP per capita (US dollars),"3,370",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2015,GDP per capita (US dollars),"3,969",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2020,GDP per capita (US dollars),"4,615",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2021,GDP per capita (US dollars),"5,008",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2022,GDP per capita (US dollars),"5,330",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,1995,GDP in constant 2015 prices (millions of US dollars),"1,018,089",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2005,GDP in constant 2015 prices (millions of US dollars),"1,489,036",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2010,GDP in constant 2015 prices (millions of US dollars),"1,971,902",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2015,GDP in constant 2015 prices (millions of US dollars),"2,526,717",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2020,GDP in constant 2015 prices (millions of US dollars),"2,955,288",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2021,GDP in constant 2015 prices (millions of US dollars),"3,072,093",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2022,GDP in constant 2015 prices (millions of US dollars),"3,243,635",,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,1995,GDP real rates of growth (percent),7.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2005,GDP real rates of growth (percent),5.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2010,GDP real rates of growth (percent),8.3,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2015,GDP real rates of growth (percent),4.8,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2020,GDP real rates of growth (percent),-3.7,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2021,GDP real rates of growth (percent),4.0,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
+35,South-eastern Asia,2022,GDP real rates of growth (percent),5.6,,"United Nations Statistics Division, New York, National Accounts Statistics: Analysis of Main Aggregates (AMA) database, last accessed April 2024."
\ No newline at end of file
diff --git a/data_storage/UN/Economy/GDP_per_capita_continents.db b/data_storage/UN/Economy/GDP_per_capita_continents.db
new file mode 100644
index 0000000000000000000000000000000000000000..9a19dcc96c53abf75d214d6bc873e814217f25c4
GIT binary patch
literal 126976
zcmWFz^vNtqRY=P(%1ta$FlG>7U}R))P*7lCU=U<rV321(0B!~b1{MUDff0#~iz&#U
zS5?5vz`(%B@65pOj7!<5_-F`>hQMeDjE2By2#kinXb6mkz-S1JhQMeDjE2By2n_lV
zXtZKv7Z(*}Yzi+)Ov*`3Ni0bOVJ7DwSH}=ng%C$4A6Eq>kdTss2A7g&UP@|(l7gpS
zh^xD6kPerEf>KawdS-rJymNkOUP)19ykk*nqLM<0YeWcGHZnD_2u*!{dAv(%adJ^+
zK}miQlG3omoYGVzzFU5NNnU<QYO#_+kgKB)*tp>Q(xPOjA}&o<1_lNh{&-LzGxPuE
z|Hl83{|*0h{zv?G`LFX|<Uh@Slz%_}PX5jOYx$S+FXW%iKb60qzmvb2zm~t8zmPwh
zKNX@GWWXpM4S~@R7!85Z5Eu=C(GVC7fzc2c4S~@R7!85Z5Eu=CksAW6%_R&B3~bFw
z3=9nH%>fJy3>?jN3=9mM%{mMW3|!4p3=9n1%^VC23_ML`3=9msO(_fv417&N3=9nX
zO%4nU3<6Dhpy~J~Sq26Mp(Y*%1_t5ADh37yk;V)L1_sf_Fa`z&u|^jL1_tp)BL)Tr
ziAK=$y<{UF0|SFp4Fdy%bQY+WAHl%DAnVS+z#wM|n%P$ZP3H@O=H{7s%Nh99`TTjy
zM{X>Q`g}A5MnhmU1V%$(Gz3ONU^E0qLtr!nMnhmU1ZWfjjUmnDoQ#G{fx-+;`pUui
zr6n1<sfooUsYQ7Tj>VaY?9bd?0u+i;6LS=b5=&Bx74p**(u?xTOEMHR3Q~)bQ}aqR
zP4&z|^D;|PQxyCXOEUBGiWP!O5=%0ROEQy-6<jjQGK(|w^K=yaQp*)0^NX@|pvn?+
z6daS2K~v4h8mtr?^Ad9^i!;Gi`6g!ODLAI57p10yZP#%0b<|V<O<^Y`7N_bc<RliC
zC?qB)rxq8drYJZT6lLZp7#SFu=rx8km*Mr-Q^Ni-(K8r){t9g_1^Y`BM|?dY>@Qto
zJ@Y~5F;M?skRhCbpNCI^SB1xb+lI@XGn=EIeKXrN)}O30EcVQ<Ox}!v4B;f@gvN3~
zPEL2GQbmR){gC{U#2g)k#GD)jaI!1P1f}O9g~X!N#A5dQpn%KFQ%KIwD=taQD^V~q
zFf>&tD9TJuEmqLT&CJOGC++++h0tJyl>D5W#G+zNb5k7?69XMXQ{zDwppE4MMEd*|
zIX*Wt(Xli((=jnH8H7IPC(`Fv$?>_VnU0Btsg9Ac#US)KACW#kO^(k^40Mc*Ep!ac
z2BFWRctJjQmL!<Z!4+CTYLP;6VnJp}qJjoeb~ZH9F*6x_Wn*I$50Rb&*J`*uXKY|O
z_|j|?H<6wLS8cdFXP{$gU^)mr$3>*)z|{|K&l#E-4nEICa)Lc4PB71bYZx4!v(zy)
z8H|48AkuH(Is}K`%yo<`2Vu(~lATDufolmIelyiEF&%{M<03YY-!hd6rb%!;0BY}*
z78RxDl@My_85$VqSQwk=m|G6Q&Q2jK*wcg?x#0SNcu!lJ>lhnZ>KK>~!VFr-LZqL;
z)dul?wlLK(u`t##H6MhDyO5bkKZ9!%;{80ByD^1KMEV(A$q?^nGcz4CV`CjNL!-f0
zu@*8C>1S}|L%g3&%yldb&2&r$VWkA>{|hmAGw|#3Me(-tY~g;$&BtZU>CF+%p3PRx
z+RZYXc{S5z#@~#}4BiAr02)J@OTc3!xW=@=xdZ>0mWkdV?Bj$q7vuF8I0xYOmxbOS
zY>$LA7vc36IF;k~m+2rJ(rOH8F2w6EaPtbkzsv_?I?QP<0Qsv_9>*9YylF+sP@1uh
zk%_U6neia(#N{;S<Ml7RRYjVA4a|*n3<hCQ+?dmxhu6RG78NP}HPW#(HPtb)7=-0&
zPIE3^|AOlaP%TTEe@%_dbj%G0;c!w;a}Hkrg6k1d{cEUWX>O=vX)p+zQ#sAqc>N2m
zUr6__iG`((f$<>h4(2px;q@=L-XYz;28I?o1{Q;G1kt}a6XaiK&_EQ<IZT|x7{<nf
zu&3wWoPpO%;3@~FmkbOBVJYk1oQ~H^;93QTmrQib3<qJuz`r>Sub03T2M#Y8>sXo%
z%Dj|{*Gu5K0jHOY2ji%Te{%|6FM*4H99}ZiF*h89gJ1s5$#}g4F5z){$;5Q<B|J#~
z--Ll*luwJ-o+pI6iE9JrJx(4DEA|YwX{_s5jxpb1`ozS+D92y|>;E^VH79|BA(LQ7
zgt#$YQ1`<?$8<0@QPY|e@%j{8AAqWKVts0CVWMMVGzbR+(wY<S`V?GEkm6GVOCud~
z<3ZRAPiv0H>r-&;LA+0mbOvpQBds|OuTR013MoD{Ff!CJv>1d-Pg0s=!9JD7F*E|M
zYl!!$rJ0eAk;NcvpQbd&;PofC0wUg@<_2auCT4@Mh3D5C&B>?=Ssp3pO5(yuBfUYG
zLj9VfaQFyZhu|NMG#iY=k$%mQID7=IEAacsU~tA!1P&j8>jeBhGSM4+t-D6Q=5QQ7
z0+;>xePp3G2%F%3&0#ov1TN$8`^Zdh5Dt_1HHYHx5x6wR?;}&aL0EdHH-~_H1YZ4%
zrSt~XPb3ZLf~Jct2j@bw^yXk3UIiEHWO&uU)Ktf8Ft(f1n}cw86<pqv>{UY@Q%ge~
z6Z1jX8A@*s#NkzNML?=o4b62dEG%^ljRs#{h4lY>LG%Bfys115+_Sm1abDzj!y(Te
z#Ma8Xo#iEqG_x;LGGhfpFRcGhGrBRoIRHnvgR3i&!`)cN!pL05+;R}s%<0YkIJ^q3
z$4K_7fsV1Ep^kykAgr>}n*G3D1q~OWRtMk;j#RIj>6n=q>R1fMNcC#=1^E=b93IuD
z;JJBRBZH<o24;h>6!dEL!QmTl-G<vYrY3{1ndQ~&jl(zK>I;`|jCD*624&oM;qVQ(
zhQj3=1074VK{#{j+3X4S4QM72HQ#{CeH^~A&@mf~*~YWk1BYk8B|8q!nCh4r4#L?(
z&t`WVo&lHLI6Y%vIta&L5}VyXp2-9)*hWoe;Nlrn5fL|zZ)B=tU}COgG#H1@5}RFd
zcoJM{ljKPYQzIP%i^11wZA@%-!Qn}8VNQZ4jdV;*jde^0<D76}voj7)g3EZ~JvoT`
zAB~C4PB=UXF8WFEq_K`UXd~fZoLoz2b_9D8vjq&U5{UPtg^roAnT~<^Agsd^njLWX
z5nNLc??-bTBMW04%Rx9<-ss<K&&dRxmSE_2PR%PR0v)G7<be%?@n8c;|9=GozY$*w
z?=+qh+`qVmxHLH(IKtWU*jicVu$*B2%B;lX&sfc{f@b}GA`EWyZ??k~^x%4p&@kyB
zY>osp+k(9WI#U8IHGyj}{9e*E9E^k6{>?UEKY{jup!o@0Y2o*i@nD>B@Nc%p<t1<x
zh2KjSgK>w1f3p=XFM%s0{9dvgj0dy?G+Tnbge5b9>mU4H(lr~5^C+p!79c;Bf>t%4
zWhQusg_MaD6GH<XQ?o%>5~enr<MJrDa0fLWNb#t#rHPKY(ID(jr#746@+i2-C)uOs
zCORgAaV>mmvnei*g6jd2J!)jAV`?!7o4u*cCb&Ebt{q7AsF8`Oj?rKoqf2cz#^q6P
zok6Nc4b3cdEG-7%&}vGv5!j=kGi}gHU2si8sz)u&bxh0#;W|jKW<!ua!P_^`{0XjI
zaE|R64#t5>uVw>Wz5!PuIDBIQI(1<1?L_x#*2m==a6N&;H^w@aMuV`7^lH|_<r{Ei
zfWtQ?I%b3M_#LliU0l8am-sk*16t)i_@>1m{r|fR{4#tNytzD!xUX~ba5-?6a;#!M
z!S;-enN@+smN|;4oN+b7T_U>agG))HSF;YTr~=nnIHJl>$8<2RO7Upc2Kxp}-x^#o
z;qZ<5U_3W2zF7<8mrQ(J8{+0-Ky7_vqd~Y<JHA;Hmlwe`5~v+Pq!&#Lbc~D!VZSZD
zSp%0B!POM;UNo{a)-fK8v$^rj>bSfJuDgi$qVZtu!o)YL;qoH5LL=UbM#hFZ2IhmX
ztsB>@3icwFHa)l^Al{3X#yW<kgK$PPu2}__55biK@jf&$)G;$2d@Yqm_hw~ICQ-<q
z5QaWtPsuhOjHhI~H!Gog1zaWIAEY!Jj9&3*Rs?$mJnjmK6>!my-z&NXgK@Wnd$R)A
zFW?3i#4q479=~5q2jg(Kd$T;cSHNXCey<G5V~^aM<<PwXF0=7_#cVL1xaHm~i|!S0
z;f&uagL02YLbD9WE8smI$fYr;o*`+d-c-lf)Lh4SFz&WYXqHCzBe<9**^eeVhKA-k
zCWG+ka!CLG9Rt4-p9^mqPY3rZt}|S0oDLjS>|5C0v1za-vD7ioV%o-diQ(Pg>fDp#
zn#P1?DfAcx*H$FQsF99=fvJx1U|epW&@74WM{q4hsvnKaK#PTSOb6pZ90|=5=zauO
zZzTKCK*z$|K*ww_&MYM~i=+DyT<?+UM?+H`GfQ(FGxI?>ADYlChVDmjg-Eg=4M0bN
z>6jY~!oH_dvna@qka-qJs}kS*iiM7W$spXX<kT#J?h9~Th-=VM$8s<pS?1I%jP46?
z`H#aFW;&LZgEB=4q5A?{!sGOXfyp4u`%cY*=)M4#;W&I@s$*a{2uFFHng!5(0WPI+
z_`+Dna1gcv8=ac@(R~3fhjIAANXKk2j`Bq{^MQN;-rs@VCn0jA-9pE}z(mJv5bo4%
zjB4gZ_Z_$d2Gx~B`p#U()WAT;(0mY1B}6szp!*J7GLzstBha{|j*00Y9J`Ea=0^7&
zxWp#jcZ0b#9@Wf+?mKWvPJ-_Ybqr06bqogMn!TuIPITXaOL*daXK18jVqvahWIp)X
zb&&plD{TG$YVHGES2<sC{O1s1*JKN0ZD!fPe21BX$&@jPp_QB-H&J>TBbzzEK@8d-
z11-40)erGOY^h^xWTIm>7-weuo7p)T)gkj1tl+CY6&!O@i!zfFiMi#|crXr>`!}=U
z@)Ed8!atsAJ{X5)1DaXEUINWypv4ln9>VV>-9b4w6VS|p%TM6ihk&092V*?>H#39%
z1e&8kizjfMgWpesGMfCGnQ(atT+!h7lIdVPNzK2R5to<11v`E(84t#tP3g@HATNP$
z-#|-v;NculT}9HwhmN_qrH;{HT=SCNRFBK6;NqQhubLT~>zEr4!fr=;Qyng^f{T69
zy=rV>sbgw6D7{*X%d6npfOM~#n;Pj@4#uO$)0=8=c@<nqknU9zLvtO=!MG?iy{Q_P
zSHYDBsa^#g+H9#~G#F3tNpGsc<yCN{Lb_KCP0V%7EC=CgF0ZCakXONT2G}Ya9OH5p
zIu^!*uaDX2)l`AYH{kjNhi}Yv%*_Vjh_6>uIWFITs|*~zG1D=(9DIkfLHhq282GjL
zLU|i_R&!tFX5iB1bmK^5uVI_cx{2j1^9yDvCLhK+h7CmZ<!P*_(W|KpSLlOlF&v?9
zsbgR{DAQ6YF5iGFDxAI<jA^OStEmK+Z@_gC4&RvQm<+}PO}v_larp*Z-Qf0($sla~
zB{mg-d;`9-16z#(syvCDMbNP@wHTb)DY2;#mnXp$4Jn>9HZvcb>p~Kn3UGN6T>lX7
zNh2LgBMTjq!8je1*p!dUli*^WcuyMZ4BBo=VpAS2Pl8K-Qaov4Vy0s<7&m_=Hs#{-
zB)C!_-jjwpW@ctO#>RuM71fy7l!MEY;JShoPnsB8>KG2jGe-lPvN;*GArl$A@WZc&
zpUN;9jKg|?O<A}-1+Fykk5vxJ5#^w!Ot7awlNlH>1+FCUdrH@0Fdl~!*pvbG6=>)m
z!&l&10l%+|2jfPKz@~KEo&whb_&qf!uN?_&O2h3baH)^qQ-ksbpP;5xu&1zQDsU-}
z-&49KgYYOYNdMoOfnSo(h}WAZg?kFu5za51DjXr~Eo@s@PqN%$e$ULrB+974V2#$b
zZ_I2;0R;$nMg${2k~Jp+-gvKLI2ddA%%)`Ao(0zvpgNwE2_QoqQv*vKgTZ*6T4qxc
zZqI`257IqrVrZ&kF&L+SGMf@{dlp=+kl|SqGaU<qK{ynf*_43Wv*7B6bk7=@8tIq~
z&SV^q+q2+mh;+{ynwsbs55|~HZ;AtZ7IdNpMrjPLo=Ekqg^`7hrO6;%|L)Ti3-T&>
zb_Bz#;ED&w*qo(~<zO7_@M(&{?H_R6g3~_+gK;&vPg68*|A4Cx9R4vMoHc|`QxtCh
zfNKaG{;|+88;tiL_%uc0_7Auc!0Desc~Ol|Qv`1RfXjIt{xQ?BG#!NJrTH|4<Mt1@
zD97O+V;xh&LAd%oxhV|fAMo4*_VOB3H4!)aV5nnmVX9*}7^k_Dn?iAW6I_gw;!QIH
zQysIxm^zc2LU4N%T)LCuO=Al~9aF<WIANCD6pY)O;6k4iZ<-9!4gsY9Kb3*slrMlc
zo2QL?A=e(x>l~jrl-WbrT3NTTJYx}O_Fzh8tYMgn*8is+w=uaX2zS_nD=1RJ-pJHq
zQ0~2GOl}Iq?M-mKMT$2K42^V*jR)a@x`|BzU~l5@nGjd}n;08`&I=iQC$@Sw`ExSL
zLncRLofC^Plaf*s^N8EwF$lX@-c5ekyaTSq@DFpE494~7K25%0?|{Z`kzxm2TjBSP
zuEk*Vk9U&~*gv4D5G4PAt0nyYF&d1UI=q{_v3Unv(&P7z;UFASZ}e{R!sZ=tiH_ep
zgYvXG?<P-d-T`++@Ox)a&iE!ad4RkFzEuM$?|{dRK=mytWB8y&LPlnTu*;R$<c`gg
z;PRVfPnw$O7!1Y^S7MVJHcx^}b&@>^T6JMLC}YwUn<v3VJ;|OlHPJC2jAwx)Ho0K)
zB)9?~*^{8#IS1pms>CK|Y@P&H3#59|$P%>Mc@UoJlGx;g&6D8Df@Dt`80lCH#v`5F
zn;b!&1mE+GUWMQonlm)iF*F{0J53<{|80=-|ATq*xx2a6aGvFO$HC8Tz!u0_#Il0<
z9<vCO7h?m%HrjRgNj16At;qo#0iX+`ks<(Gz2S%eOC5{Bcr~b7lRY+{fa@?EKCu{_
zTPfX|?6CO+Tv6fliOFC*dC#rM7MoANwGj@VnClpu4#NE<ZcR4Wd;+d=aQMVj$HH(B
z4oJ8)S!44FxL(2G6Js5d!MKevy2%RU6Y$j+NM#qi|3TzH80d~%lR>x?I=aacoA<y)
zGpGSTr1y+WbSwtrI<V*_3vAv4m)FF5&)D2_P;LiojBYZ=<~?vBPJ;IaYd<5p$qbwK
zz$H8J-ZQc^*D)H56Rpurrr5j(F78S2o{^c3*<d_tF}leFoA<zV0P)^4G&0n&7>u`z
zCo~yzGPy&h5EvKxB$j06!A^=&P*W($NL3(dUSTj^H{O`gWJI(d!BqzS0Y<aIcsf>M
zlOfoTpveY8@d&Or@cU8Md@$~tNoX<vdlEDQLCBNf+5^8Q4F==hjD#kAqWuW2Lh$?1
zRB!N&*MR!}f()(<{9Jt6ygod++<jc@IWKU0WdF+cll3nvBMU1tClfEDCW9-UK6+z9
zlOE9l1+I+n2h^aPLQH7VCEAbR8VSE24F}^@_Z3Y#AU}e4bP&qa@cs%Z^ChM_=7yF!
zW~PI%gIUp}O|;*^H4~`CL7Lw|hwoYpPQPmr?RRjEMY`V&O-yvm3<u$kh>9jnqWuo8
z$Vm6Qsi}#MsnMWJ^BP3^9bCbY>UR?zOG|K`AAAdTDw@=Z_B*)FBHizX78W{2gK@7&
zMUxuQeh1fOr25@h$I#qT$7C>GWD(t@3i3O6^9WIO9FEaNOC2N2!PlN^jBZjP+I!$?
z42SnDbc{>};abAzCS{_%2d=4bc+XtN$Y2mo_D44<5$!#2WrV|f7CM%L@e0rACPkvX
z2d-~$c+XPD&}<Oy+lX#bAliH2Dg}r4Om&P52W8PBPqg>IwFVCFndle}#%0PyO>!Xb
zfp@78RWX1nMdD^N%ybNmK<9@Jz8OMD|9>e1zaXCyuQ87ccOKUa&O;n;I7Hd)*)my+
zS!$WvnI<yMW>|`+|4(bF#-b)!qN4^}sSzJFraH!!7CMH5@o3kgCK;lA4X*2m_qB<R
znT4s2`Cz;fuBb_xXkUY?K;nIEsxxSNVnt0-MEe?CGm_$K69YpXOT$4}VHPz>676en
zg-N`xjdUyxOm&O~<96?&CJCZ_4X#It_qCyprKPcs@n9Th32GAOWYmSsZi)Kk7nNkB
z7QyGYh}kD&G#IA{f||te_zGMX;U5P!9gG_of}2Faz5>l)Va64>uEFms-9dVSlL**b
zpgAi{Z-FZl{N6GegflpeK~2JVd<Cv72>EId4owC%3E}Y-xH7=+E91d<gk4aRARb?V
z3w!*&G8&A<MRt<_$XDRI;4$+RSrbJ@Mmm<3CORgAakeD8i64)5!DT+E#wKNM$jC^?
z)Yw?Zz+w=NNo6<j;qflGG9cNzhM+T)bS#Yq;rhkwCSE+=1y>TJde_iW$HL4&$7m3q
zkp=4i3o&?t?*H@RP2{QI?&n&@xtHS#2NSyiTO4Z-%P!^@%wkOHj1~-@c)R(H*-bon
z!VO#vksNO3I_9Q^I+mt`a4;;pi5ri1!Sxf#-Zj&)ur$=M9E`p4>?STe-UU}&BzxCL
z$H3e`$JlfbPBZv5ae}-H-r$3yM#C|<X>OupFc_DH`ZaOj@e#Pv!r>z`3mv1uI9}`5
z#E!>D;Ccy{j|_E824|{c!{Z}x)q}%FrlvXugYl+%za~~ZJ_1(?IDBMcp<^^SeZ+#t
zN8oZFmye8f3@r!YAe>(lGaes-i*_770?la*#=1GRi3#K*@ICN2N^ekQMcmwtk-3hA
zrIC)Q;UH|QrZzF+@hG@ZC&8npI%WoDItGJr!Afcq10Iip%X$(#YNTUnVW4AbHVB)Q
zsg3n`JPNJ?i1+9q?sqh%HrC<sD7a=I!J}q6X6B|k#)I)1sno_=JRSvC7$kVqM90X`
zQpaF0PFJQh)_^?<y2Kr`)CJcg#CsI9{K!(rbTD2n>eX1y$tVk%$Pk9!<X%kN1jgVy
z<`B~Vf5E_S#+Sppi01|mAGbP}17{>h5qme=64t#e?^zU?gPB?xw=ulH+y5Wrl8s)C
zRajyTTt(s^aWxx^(@x%vm0;h1CTI|85L^%9_l>UcU_8#utFZ#?9ni!K!aLyF4!?Jd
z2IDRYuf}pLz5!Qh_<b`-<E9LYZ@~2yA>Rzb&W=}ODHh*=D<}NEF&d2L<|Q|lfP4d<
zctPYF@+Mp?bj%G+bPNp#;b>fPV=)$Qg3E4Di-M$y77HB%W8*=3esp6I7H@(Jb&|bl
zregxybYe32Rvb1aHx^>?Cb+OC*_)<1CWa<D7K3rKdU9g{7H@)U0g}CGq+<@csoZ=J
z&eJD1=40_DxOyPjn}#|D76v+o7K758d04y&t~W^arlF~hk%^^_g~1>kP;zU`1$h%Z
z?}1jK;1~lmHqx;ejHm3lHRfRP3AoO{<r9O!Ifm}mn2p6J;A#PfPmIiU3<l!`qHc{@
zSbPF5`EmKgRL8=65Uz=EYs|#r6L8^<%O}P<W=4b0Cy@UC5(a)TJ{{f&o)+#6Tz9zG
zIgL5u+3VQmvhHEI&HRg5lF5QGk73C`b@3bB8Z)qjHn@(#5!!~9I>ttWaCq0PF&&Ff
zz|{yYpMbVf4#JL9Y-1Y8C*V02w3-4`Ard#YVr-&gU}T_UVlfD-!q~=CEFJ_`AS8Iu
zP{+W)M8|M2uIq|zOu^zoaJ@pj2aU`jmvRrrYvN)Xld*UZT-}i1!9m=`h;2;5;z4jN
zM1luF%W%wfj0WS`*RhR>SUd<W_=)$Rp}CHsk%^A+;7p<kSUd=>4@mH!fsT=hk&cDM
zAgu5L8sj+`H6fEF+~KLkCE!gTX+@dIiNs8q7!Stty#gBJaQX>cKj0rpG#QK|iGhu=
zU_XH-6wu=dTqWT5ldgf@AZ()qG{%5E1)5es_Y}Aq!0)L+xq~2}F&d|zz$HI^Kba5C
zc#6X5Cvahp-%o>bhAyBn5~rWQ<vV^q84kwXD`|}pAU}a`PC?I4WKB9)7#ipp48|FU
zw8n6pJ_Q%?pxT*~c?WZIP>*!5p8sD6IsZR|r+~YMYX#?RPCgEM_5!wrte04sStObD
znOqs8849V=|8God48s|;;F^ZypfxeqF*X}~ODh`F8bfjV6kPp~>Qm63eM{p(Skb06
zhT!xmxKbk3r=~_mI);OB04J?67^hFcRTZf|HMTI&u^5a;5v4T-;q)oE0wdL@Mn<MO
z7M6o>dfB@%5ad(viC|c(HC#h;I_8#xuS9S3ZVbTb9dO-++dG5tJ^}AWf1KU{*B7|G
zV=xG3zr7p%aC!$^Dd6;urQx7VY`!?X11|Y-ddF-qR%D)yK49-)>oJ0hcO2fa9E|6T
zcs6?D^bEKJ$Ke@MgF)EDNNDr|c?NuI3f4jzR2>mF>tJqfpkp)`kH<@B^u*~$aLG-A
zAB`+@%uEJlJbK{tBe*yx-j8OM#yXaRvG<tJ=#JBm;4+>BKU$dT49X^dLZcf_KY|N>
z;{9l9XsBaqHV7-Xghp4KegxMB#QV|6%v8t7c<^;nA@l#)4EzRs3A__{mU8dnI?wrp
z<0l6nyE2;}YbDDP=JQNHnN%448L}zt|2HNyy5I~>aD7C4a2kTn_Ocv=&AY%xXV6{u
zfuIJ2P;h=J^pq>2Cp-q_g7&~hC)}O_S4{W^GffBM7K)%oN3f?rGaeW*1+IzkdrH@A
zFz!7FY;*wo3TyfU*FE@sWjGk`nh9*Q$L%R_WrN>SgK}R*V51#wPl0O}{GKu$oH1pK
z+f(2&9>1rI2jkpmdZP`<Q{ZV2jFN(^c@JYtQyt5}IAopPXpP&e;F2CxN0Tz~VQgVO
zIM?T=H(KHLD!BY7*{f!jIwphhNUQWlOWa-sR|+J1)!bai+<XwO+DmV=!0lCVRY9^>
zjm>oo2IILM>5b;Ny$Y^CNcF0bg{6*>!5~~kl-_8D+pFMeg=DW9nCn;=4Z;qDPopWw
ztKi89?3E3UQ9Cmo6N^FEhxTbS!R;S#je^rZ=7aG95}!t6-2MSq8#w%9s$((;?~8%-
z|F<*n>+(hMw)1S^e!$JkWyKlFQNZ5Kwv6>4%N^$L%<4?xjO`5DDeV7KQ+uONqY>_C
z09R=^qruW>5Z*%O(`bm>Kj3-`hkwj<Of3fCoT^Ww0dD_*D<>TOG1W00j7PKiH0tB_
z54Z-x;U8liGqXV$KZ%WcApd};Q?OSvpc<99`4kfq6CDeaL0I=BHtOQ`B)IM&!IP#I
zIwq!ru*I9$sDs;+;0lR&Pa2z9>R1>L!s0QpQ5&}>!NolZo*b-wm&8Ub+@1v20mOUK
z#Kc0!a4@!S6B{*gdlFnR5bsH2LjxVt!8nnd*r<Wqli=EdcuyKy80#1f#&aC}8`U`(
z)gfCu1bs78QgTui9EqOjFd2-a=l+dqxV!|eF7OXt4$3290vc7pUII;Xpv4lna=`B;
zU8BLc0mr{l1?(r#BnO(Gz;ywBKN$_ifph;xWn5kYm;Cs>WHK1<CGl@m!sR7!Igj5<
zmV+~v6mfY8T&m;ulGz}<y93hyuVCPp<+I`q=PBV{!F7j=kJEvph<yp$HP&~mtSmCj
z#!Oy}i3}A~?ZBrtDu99#JgI_~hsl~!F)}sLu^5C4EE-cA<#BlwT&I9q0;Ei+7@3&p
zn41p1lO!5b8|83$6kOAg>``M&9mB!6r!}=v7MDlC)ep%YH8IjL8-#a*G^RGn;PNQA
zQX<u(hL%P;h8BZxQDSPNG%k;Vt16N`YGR;cYA^^#L{b{1z#f%kXwpY3b-@)FsUEd3
z)iE<3g#Pqulmz(`Jd1+nPjKymW3bLp$7C?BL-cBtz~vio6@t?@gK@=SqgSIiF5iIb
z37oz$Fdc*=Q(lc?xO@Yy3~>6!bTFQp=G7>Q%QxT>AE$3jj0fS+s7Ip+*f&`EiQr-#
zhi@zf<54Icjl#J60xr36_{C%}Zt03|6ax7LJo$jFbOzNz#7#XIS(xh>4#uWae4`*P
zFM^9~61-?^qGLW7Yo+)`0bE`Lm*d2H(a_RV$8<1m2a9jy$K^$E;ZD34K?n2<#x_2r
z{~raq|Id>*fv1eShieh%4vur|zu48-f>`TVRxw{=W@1ucv}K4Qt^eN`-^hn6@W6Em
z@quS(X{cj37-xm!8+mbg5nREL;6(#N9h1R$W@lU@57>+NdJM#s)yC#Jrlx~$2TWr?
zBR6PU3V6!~pKBtiM^p{U%?$yKTsZv%u7B{4RGJRXQ-U~g`Uza&;P;ckV7&MuppgTo
zpTIQ?em|KF#zFFcMs}Qj0vG)F{bV^f<B1KYpTH$Oem|KFPCv2Y^b@#Cf!|LigV9fE
zjVvHPfoB!4mgS%tnUv9X6H`+i!@*c<r8P3+^eMQ6C)uaQ#-KYRLh~|9Qd1QC5=%1k
z^NJOMOA<>mi%T+-ixpfl%QA~I^Ye5R{8GymBJ+!~b)d=;a}*qtlk-dSN{}^JDLCdO
z=2RAE7AxeZDflL4<|#O)rx&HBCzhlZD`+_SI%+DUB$gy5B^IaZDC8s-mnbAAC#Mz{
zr=}=478GUXC>R+Sndmj9H8SD!DY)Dx*{7goBZKh<wX{Y?oIVBD2BiAb*w{eFY%p$<
zO>1Pp=~HkWL8?zdvtq`^gK#~6T0KsWf-4SEJ!)t+NRPx%tHbG0aBV`eM-2^hjLin&
zsG@f*$fMw?1*}yJj*&Rf<tBsgViQRJ|0Dyy244VgInR9V<6KX<m^kG*Y}g~&%2+3}
z9B2N`tk0CpIGy1nY5jjXt8VnJ!5J;!`Ve=t491ICJgdRJ0gYUvCo*uIhr>6PgK>qj
zXBAGrfNM1zez6#g+kZSOary;ZZ{hHZndKlX$UG}>`UPAy;qZ%z!Qd;#8a>N#`UPD3
z;P8vF(I8xnkWdEl3wU+}J@11juR%2_aYJsVhDJJr^4Pe9Qk-4{7uLjk(ZtL^$7nD%
zaT7{#dJ$ZLli)=oQyoi_LAWh9p%|wZ!38_<UL3R?m4qUkUIdr-#Cy@mc(BG|Ax<xX
zs{!J@XlQ7zV`4A}7iq*7fV~Ks!$2=l!L<YNUNkoxoNE$8^EsIeA$u_xP6d}H=>{ie
zBo-y+k+37fcrY#^56#2xFK}%^XrOWsE>H{01^WxMD+6nMfvX7o{?auZjC(UebHE-0
zbzHD|3|ukb_t>C31Sm8czrVn>0e*iC##sPJ|6dn!|6epu2lrO4M_l}zHXNDk)oi`2
zb6M6h?`1m6c$bltL6@O1Gz)(qfa?oFfiMVnLx*PK_ZPU5!0)d?nP_t}K>jL~XK2#L
zni=8U2~ws+3_)EA9ZR!8*mKHF$M0WoZ2_w6N%OCTiK&k9U|dL-n}*-N;97)q|C*bb
z>6i}24gI;P`27p6TuAq?8R&>7i$OSfkeh<vzu-!TbpIMzn(CMj#x2F!$zcCV<0`Mf
z^$V%~wKO-=F&>P&PO_8m`xad5km_4ABTF6g!8k$}kO=ZEc-jPaU4&zp&QQmEFdo_y
zkbvJy;OYjam&{BDVGSA(kKaq+8U?49Ob6rXhXHZ;y#%f_aC*sXFdnKF5R2bS;CcbK
zmy8GD0DeFWelLNGew<!17>xTw{i4BM!r2uDm+v^dWIia5VT=NKD3fq^g1FfUBOL=n
zQyoL|L6{oTBk}tbT(X0zX5xHmsAFMaG$@y_gZlr1jKYxqzY|XccOKU)&SM;(IONzp
z*-BX#vg~BO$n>1?FQYJ>=ko{7y2kVf{E-i?14)T|(7k;|gK>XLdN_Wcf~!W7d^%Wr
zQt4s%eG0BIN%5(%g_(}|U~C(thJt-cxDQ2K(PeIFqGM`42qzy?L-6|(T)Pq<qsErz
zI!1$WQD|T==qNGp?i7B%{322>6fqu*cW(p+;r0`_YQ;a+YCafm2?z=V`w29ogAq^Q
z8Uw$dbO+@Ca$o@1Q=ld+hNr-l1Ab2#55g0V8Uy`t`w3hP;P=y@-0v0Whucr!o)dmQ
z4aytT1ATG(30%12_mk0JEcnuWKz;&mPr=AfWKG6cnp)~u8V<thIo%t#Pr*ezsA?u<
z8phJtNXK|EcJtG{aQhTo@RRCO3o}a{L$kpcr=GZd3a$-E^{KhJk&fx0^r;7KpMvWM
zl6`7mpkrV<_!gpo`u{=<8yWab`LcN1couQ*<GRK9jZ=t2k3F7k0_#DRPb|vJAxy1|
zvl%uHT$dcl=Eih)+))Fr>PU?mQ&V#tv%%Q%Pj|!ZQ*Z@Hs!xqgO>`^`2jM)Yk1NQh
z;JG2})gq2jQez#XL3pP|qmK)2?||z*oZc}WjEArLIOFyXxPrs!9fLvX9q?tA*b^JL
z7Q^Ws<H5Mj+y{J(C3f$Ct16t{F*F*4Bkw-o`zx_~2VA`4@Q$I5rO_Zf6x9cOb0v1~
zfXi^4-Z8Qmgj<FZ!FN`Ix29k(s6kZ{aRZAMrlvZkgK^PKBKQhR?0y87-lX`^NXK9>
zUeA*VzR?o9AHhXB@qRQnGtx1#9E6Mh6Tw$mV)rAsoF~DLgSDTM2)@G-yC1=YKk<Gv
zGcnUK8H_6f62X^OV)rAsMj+mg#^z=^rh{>DR3iA+O6-0FR};kh(a6AD$9PblU}?_D
zC<)o3!bJQ%A;x-xuhZP<VTR!qaLs^!MACE+o|psb{|htZGVt5*mGN%idBvl`9mh3;
zb34Zs_K)m*Y}%|IEUC=1n9eh?Fj_L?BK5<`VK#c2g2N3oM*>R%;MxX%xak@V!hmb^
zFai4oG&KVA3%FLn@0US&6}g8ohF8Fq2Y#=Z4#w?A9!3~m0oM`uy)r1zQS&gw@Cvvp
z!0#2K!MKYr!2skH@IDk+ULk9?!$`-%+*HS6Fdq1uppW52aFqb6xJjAjFw!vx-A^|d
zmpdouVR#W-dXw%&Gh<U7bHhQn5iCI$!;9cTopdjn7+C6<4a!aXIv8FA7xtuj(NM<{
zw2j1a5H`;ev@yI0t^`Q;qN%Zo&Y-+@AWjSHMbIiQScwX*97y$|rG<%(nc*ND2Xxj1
zc@R8s2J;}e%D^#R23|`%_|7hL*1+%uxK_a73qu`Cvq5-5va>pdFTe#qPG49I#v`?y
z)i8VkF57YV!brzpFdk*$tcu|aaPf`97lt~PgYi^EXB7-zfJ<nczAze$`NB~d><i>B
zAh;05;R}mFxC9*3{}*I<$iUCW$HObcW5^xAmCxD7v4;IL+bcGHRwI^B<_f0SjQbcK
zlGEWI1bP~ylt7UL-n4>Jk$`GS;$|v9y$%B%bJIasOGYVTcn(~@km5OWV-uZ0xjP|B
z0mF0PYKIihnV6XCm=4Ap%A({kJO{3gNb=lZ?PEmAVR#N)Ns;0?17l+yqrteJG)fl3
zbKts*c+VN?7@C8QgB^rjrwAFa=dkuGh$}743`}&)2IGB2anhWe?vVM1ko=Ow936$k
zoE!!4vE@aXsl^KUMGA>Usfoqx;C=@FQ8wejczb!A6p<bTR}uI<I4DO%<0Zi!1Wg~{
zk3n!Xf!~9J^Jeon39t`AElT`81lJY#eK<JNs5p@x1lJe%J!mo*rv~H1i1Z-1&LHH$
zLAX{kPLxOwg1bWaJvb;gr<IF<JXos8(4>z)4}$9nP_0kO_`aoqj-ip6j<L}oto+M`
uiS#+R0wLAs7Unu8#+Eu3MuTu?L%9%<J_pw<B>UV*$JoG3$HHvz^&kNTEDx9f
literal 0
HcmV?d00001
diff --git a/data_storage/UN/Economy/Government_final_consumption_expenditure_by_function_at_current_prices.db b/data_storage/UN/Economy/Government_final_consumption_expenditure_by_function_at_current_prices.db
index f2d38ae15b2ea0522cf6d2fae5403c243c77f2b5..3fb2e7c2a2cde9596a991c6ba4f84d9fa9f9b3be 100644
GIT binary patch
delta 7285
zcmZo@Xl4fC3DSZe7#P@i7~p{M>qH%6#t$14dgTR}SemZ+F)%Q`Z2Y3dz`)qB`L8^?
z!eW*O2FqC{FbXVZ*#IIYFexl&S->o?o#g;ClfZVi4b1=em$PgDiC$n9Sk7{RDPcLw
z0}#sqM0@}d4$J~eSy%*?vm`JnY-Vv_TCkn1feEBdfJI?DO8_&I!FIL@U~?K+CM;($
z04Wt<71++=z``W3oGpPxU^!a=i@<ia0v3?21B?rnvna4SEN3YIxhO$RU^z<wh;RTA
z1|UK}Ltr_Jf||fm77#CiRbV;G0#$+KEDu-(ma?#c<k%9HvrMoMSk7W#Be0yM0Hn-8
zLts0Lfd<G|3K}4b9=Hl@WdZXA)IfX(6@l$60_-3+8L$g%XA58li3)Ile8vtk-5wMG
zAmW2MhzlYvfQSPiVgra+03s%Uhz1a`z!l^ckO2xHXB@B>*v=B54swBmI>>ATb%E_H
z3Sa>N^?&?JSwQ>`Y9Iv<z)oradDK8wpq(Xvqn#yyvz;Y?tDPl)yPYL~r=2B$x1A+`
zubm};znvujq(-ovB|xa1B|x~HB|xN|B|vmJOMsX`JBxz&b`}MRzxmt@42=6(n-~}v
zm=<p5IUrWSTF<nov9XkafoWG`qdx-!)9%Jb4F(3LJ&lb_3=B+r8yjL77?}1oHkdFl
zFwJai;AUW8vHYLRz`$bl-<pAe#rnT60|SfAzbpm@7TbT03=AxG|HK&>SnU7iGBB_>
z{B>YpU~&8_#K6Gf^e2^pfyMccIRgWW%O5TV1{T-fu?!6LEN;II7#LXGe={>Muz36m
zWnf_O{H4jjz|{G(j)8%x>t`?n15@`;bp{5eo*&f=3{1U0f*2T>`hI9LFfjH1U}0cj
zn(!Uu$cf)g85o!*edlFhU}*W4%D}+1^qVaM1JmShq6`d7)4qZn<n`5+fq`kpS6K!I
z7Vj_R3=AywK41J87+8G2s4y_F_<gQoU|{k89L&JL67boGfq^CPGsvYupOP3DSb{%+
z+#d1?Bog{Dj)8$C?4uzA155ZvkRz6Th+tq~TK)m#tQGG;PG9*xkb!||)q52N2By{T
z${84#*1Yp#U|?GNPKJSjY2DjA1_q|}^>6JN7??J^6<}as+Vm!gfq`lB8)F6rrY&z+
z85o$hz7A(#U}1W#$-ux8@v4S_foc0Ie+CAY$X9v{3`{#;@h~v3M7_*rU|@-U8Nk56
z67v!ima#7d85mgNUgR+_u*ARcWME**cmeWW!t*)?2A0I<kqithEYCsSV|y+ODl96V
zr7<wDa6JRX7SA&&1_l<sr=<)G45{1a9v6#ct!H0q!N9=4wp56Lfq`{N4g&*&#u7IM
z1_t#diVO@4YKzMm7#LI+`!X;vs4P}yU|>*QRLQ`=ptQ)3fq_ABkpcq)gTlgM1_lQC
zh5if-3~~!~85kI37jiQ&FnBD;W?*1&U*N;Qz~Ht3B<{L^kAZ=~Wqv*b1B3JY00ssI
zr~3IO3=9m8^Tik#7#!wRFfcIK&x>MUV6dA961SPh#lXN|J2!!Wfx&vN83O}@<y>I~
z1_tdpMGOoKT5|#!7#L*c7%(s}NX_AAU|^7#4f25CY)=LT2EN&93=9msvzZwf7<gvI
zGcd4l%(7-+VBnr5&cMLHH524$&YATfS98qNVqjqKoyp3;z~D0@o`HeEdxj+g1B2HL
zkY%3Ja~T*Itfsp&Ffdq52Zf6Hv}y(h2D53Q3=9mW(?HgnOauAYcxpNW1B202Ck6%v
z!>Mu%3=9TSK%u2SC5(ZAL2rr?0|SHZ6i_18nG8}XJ=w9Ifq_ACvNQt&gZLy+w1`at
zIY@MpCIbV5$Rs8P1_t4Yu?!3hLKBS{7#IX5axyS5@J|5wCTW5x0|QI)1a1ZfmXv-_
zl1=RgrI56KUIqr1^u7WH29}IIPzK2C(_vs>$?D@|U|`AaO=n<W$?0`vU|`AZRbr@T
zV9D!cWME*)?*SQ6&|}NMz*5))N+(6#RSXO)#oeGJRnl$2z`#=44a)yzU1bamEahDx
z3=Aw4U7%c2*~QPmz*5x-O03nL?hFhpHJ!=~3@o)B^$ZLwbseCDUf-e1z`)Yb!OXzG
z(%2rwz`)YfZUibLn%hA|NK0E00|QHI8_3YMHZukWmi9IY1_qXn)(Qp&md;j?5nZhy
z@$Obp1_qX%mSP45mfjYS|N2_A7#LXkTi6&FSSB=syfLvE<g7`}EDQ`Rlbb+#r!;}e
z9pT1W1_tJXje!gd%m*4(7#Nrt_iz7tUW`AWo#lhXa+VL00ZUnA1eUV|NKIJIA^<9z
zKS(WS`5-N@oW(&3M1aeC8HMF60U%`sAYuZD*Z?9ffQSzu;sIE(tU^0WfowZVf!uPI
z0(phyECMnD+gT>a|C8U&G(ln^OFctU;|WkEO>R7%!N9<f(s<mNfq@~Y@whw#14CNl
zF;Fr~Z#)J{JsFM1K)IT+@faTi0}Dgr(JTfACf~-RZVU`et&K<J7#NsZ8jpZV`{u?Y
zJ`4;@O^ruDUT$nW!q33Kl+<`Qmw|!Fwec{hm`Z3o3@W+m-5L*pO0(F;LlF!N44I9G
zj2IZ0yc!RIl4w@r!E^=&CiljJjtmS8*^LJ!85kIH8xIsRFfimb9sp&r{Kf;I0-&IA
zKPclCHtzRkU|=X}+z(3m#f|$wMMp{FK9JF+jr%|us;qGz$dvNNz10j1%>U~f_r@_W
zF#l`Z>&U>s)X=zBm4Sh&zHu)H0|QfC<DP5=2BzA^J$?)fOf`*rKu)V}+yg4`s~UG#
zFfcGxHtvpQU|_0f+zl#c%NutqF)%R2HSPwLt{#oMG8h<`Vj6dW!ost0mp%gnQ)J^V
zP%)R&xU-CbfuXXoekZ7?scPJ5$H2f)-MCYUfq|i>aVI+i14C`&jw}WShPuWbpn|Tx
zaR(^xHZ<-KWnf@vY}^jY)lH4tK{>Ozak~Qp1M}g=?V$AZw{bf=0|Qf8<2I1%OB=U=
ztS@QYrpv&<RNT0Ymw|z)sBtT(dMIq%S`YGCLE~0XfuG;F6%<c-jav#B7?^S!w}2{`
zoW?C6Z)Z1d5n*6p%4*yUir>t}&0!1-Oi_)S%^4V&A{sYKFfcHMH*TtAU|<Ss+!V#Y
zz!ciJ$%=u2DWq|e7y|=SaO1`z1_q{}#*HBR0vk7iD%^m^4fXX53{3uw8$gwtU*iTt
z1_mad#tmEy3{2jQ>r)sQn2$EDcV}Q=F>73}!N9;`(zqT}f*3Wf1GNYY8rS(SFtF$~
zt^?(3oyK*bQb((CZ4Ltii$>#GZw3YywZ^rejH%MN7Nk$9aZLsT1B*iA8fOLu7P-bX
zatyi*EHaI&K^a`CaW$x7mS|iJGEJ;;H9G?Xi%8?DL<R;Hp~h99=7_-dQ`05BF&eY5
zH%^siU|?ZwoC2!knH#5o+6?;}r+|WZN#hhy@OLy$2I=H%oNU9uz{0)#^Gt~xmiqd}
zNremyEWC}Aycrl6>l!DiF)*<3H%?+;U|_6moEX8tz#`Z<QJ;Z<v8Hh%s4x+3oDjpn
zz*yZl!I*)8MYM4OI|Bn_RbxM>^b&9E*JEH{tZeKDIaRW;FN1-Bv7)ihlYxOny0K52
zfq}8Su@6)($~N|vFfcHd)i?Hn>T&tTUQiRgw6T|!fq_M_u_u9nfw82q2joZP#vU;S
z2FBvXZcyp1+Sm<pXi;M~$f4?u-5`e+Hg<um*KF)EVPIe^XzT*D6SNyUQy3T+^BX%s
zrsy_y3NtV;<~4SJB1*rp!;XQ0F}Jb4Lx6#S#jvp*<kFnRc2LwBH?}J=Ffe8}w$(5&
zu$VTsg)=ZPW;M2f{A=FW#>>FKnAzA0sxmAZTOAn~7+V`#r5G5P<}|jHGB7Z<G`4^m
zmUA0hG#D5dn;To085o%6HG;}u#-_$*GX@5x`Hju|3=E8ojZLhe;$*?}hw~+rm$Nv4
zO34KhpyoG-wE@Ix0I?2$SPMX`3n1135bFVm^#H_5FcnzJA`5Eun}S;3AXbB^!giJf
zSx~!rfhnlreLx;mfSZGw<E9`{2h)H2+gS|2Yy~h|!1ND44=d*-#t`PYp!PEJcAgFL
zlbP$8n3}GE+IWmj*Fd>|q3LQS0|Vp#rmG$d42)l!uBtIGFn({k%F4jN__OH>D8zp?
zU2$e$VEof`MTvodIjHFh0|NtdaMR^@1_tJkrptB=49uZTmt`3kn8TVbRWUFyhc{h{
zWME*9Xu4#<z`z{YbV;0nfjO$_Vi^MibA5Ev#SjJt=9s37#taP1u}v3+7#Nu2nl9uq
zFfhkAUGQOGU`}Ydpw7U+oY-`Mg@J)Nsp)(I0|Rq%(|KzK2IiEe^AZdU%&AT1N*EZJ
z)0)otGcYixH=WaAU|`N@I>*7lz?|81Hi?0OIjiX`NJDnhSx|EO*L0?Ufq^-<zUhn?
z0|Rqj(-}}nmfv)`j)8%>py_l30|Rqm(`h3H2Iius)4U7}%*9Qo(ij++OPWrBioVjO
zQ&J2J%w<g{LH3q6odi{{6-_4%7#Nr<n@;jEFfdm&oycNfV6JXD;m*LoT+?(ynSp`1
zw&{310|Rqi)A1;f@0;q6n=vpjH#8jwdAqUc7|7dAO~*iPYHm8F#=yYb(sYcGfq}WT
z>1YfC19Mx`QILlArlSH349p!(N3t0hm^+(}xH2#>=QJIWXJBCNZaNGK^`54~pn&ad
zI;_XQz}(k#n4N)vxxeX9A_D{Sgr-B53=GT@n-0|rGB7YtYC4$7z`#7Y2~_PdPiZ;`
z^4ioUP_@TAt?2;B?CDJhK;b;2X@5Qg1M|$L{UE_vP5Y%87?@`_?JHzpV4l;o&x3)1
zd2Z7_kSpdj?FGf}{HDFW3=GT*n)ZUicVW{WP_60Lw8xu)fq7BW9%WEl(7$O9$cKxY
zb|)|}Fa$L1c4S~+UeW}r+86?xc7q~)Y16J01_p-Urd=)!49v@#cBwEhFoZPiVrF1q
zUf#4biGhJ3v}q?u--@Q4iVO_QT}?Yd$#P}Wj%Wr3<|9ozOc@xMS2gVbwLHR_wu92@
z>Za{R4D}35=}p_Y85o$?G;K>|U|>pX+Gfwdz`V9;8z|4GHf^n7U|?R?v=vnSq%>^>
z8MD4=t1trtQ*zT5kheE9Z3$ptU`lM-qR+s<ys>Eus38&Fv^j@?fq7HYW^V=true4K
znhXrgo0~RsFfcGgG;IP^G+UZBIWREPGetLT0tMpMrj4MsaAecQ00su;ZA}}s85kI%
znl`dAFfea#+K|Y=z!2TE0hEGwG;ILY$T3apK`D4=(|S+~B(`ZiD6#BnTF=P9z!2B8
z4wP7SH?1>gU|@)ES_g{dJxy!#7#J85n%06c)!wGHARG7-n?N-c^S-7v=?o04J=2$M
zm-kUw-n24-fq}KVX{8kd1IyB;m7renvZfWFKIh`56`)dd$#$_F@;ewApKm|EQ(l(2
z{%O-RE(Qk1$4yfc85kHJHcho<U|_u8G*y;?f$?tBlv)M`#@kI(Vi_11Z#GRaXJBBw
z-UR9uFkWo}Ra=agn<kqwFfd+hnhY}KeAA>j1_s8nO_Pin7#L4CP2yl+U_99b>J=~^
zZ<=Vtz`%I4X(Fg*`rQPst`5~VO)y|!VEoZEfscWK@mo`W5d#C`m!|$O1_s7YP5qV(
z42&O|`awDWT~l8%0|VomroI3M2F6!SeYy+`j4zt{K=wXs>IGF4Pnvo`rQf5bUQiML
zps5#R{k^6hkldZ79+2FvrXG;ojiw%u+_k3qZjj`arf!hrrKWC><b|egkmR|hE>N*~
zrl|`QB&V9XK(08^)CqFMv8GPY5Y~~VPE7^|#=}jWpmtbmQ%5QT1LM-B4p2FJps7O<
zG|bV|UeCb5xUZ=l6oz}7+Cd?+r>UKdfq`*%Q(Ju`0|Vo(rZyc02F9IDtstd4npy)H
z7#O!VwJI|(Fm7uC*IrwjT0kz`($pf&z`(e<sX3Q{fpJq)vpoX?<Hn|D0R{%f4NXm;
zC|uvv1PbSMO-;-U42)}=8bN|<ni?G#7#LSKHG<r<s;QBYfq`*lQ$r%i!WB&opz3mY
zQ-cBn1LLyB|8)!uj0YS4M=&rjE@}J^il4=e|3Nj$qQ-ww3=E758~=e?9t#@(u`n<&
z&Tsq+^2EHxzo16O+{V8kd*?L%0aeel8~=cOHmmUuC`4yA{?2D$V4TtT8x(lc8-Hsv
z)H5(nYy1t8oZ9#c6naw{e>pKQFivj#CBwkLIH~bxIRgXZ#KxaN3=E7D8h?UJ>u>xC
zN<w{&Kav<27<(Ikfa0g8@rMKh17mmNcToIvHGcPHU|{TQ{0^!II~u=%ywu+K4V0|f
z8oz-Y`nmBN8v}zB<HyFYAV0lt{0b6%+xV4<fr0UL<Cm~)4hk#}ma{DI5NKyHP;6&0
zP-<r}P+rbr02-dVzy_+WKd^x+aR+vR?JO7A!2;|c0R@mifD=fdzzHO905m8#!AW2_
z%LWi}0YrQN5dzMjp+OK403sYfqjL*X6qd7GP!U+l0_wm$P!U+pA^;joe84WSlm#^Y
zcK}3u01Y-i0Eu4!u@10-hDupMR&HPgS-AitIsrs9fQSOn2;c{m3Cmd~fZWoc=CGY*
z1K7z6*g;K>31D^u*!dekrZ#|;fh^wuVikZ`7eK59AlU>EcLInt0mNzm*&d+5q_Cas
zfjr3e56%m=vn&9QX&Pw$lV8rV0W^S^pa~kd1hFoFSQ9iAma`;)f}sIKEC3M)K*R$l
zfu$^<@K68~S^~>iK7blZ6Tn(s7A$88&=Oe6q77=1X*n!s2>`JUfRq)0SPwuf2awhT
zXNBb~8#EP`vM30&vwYBQXZfJh&hkOGo#lgGJIe?Cc9stY?JOS*+gUyswX=LMUe5Bt
zM4_E!gXwaX3m^**m`&KuVqnQ6(9V`%zMU<>;-CI<mJMbC+gTP^FiqIb_CWO?e>;nV
zWjl+5)piyK>p$nWDJX)5l{Z9yhJryvf)}WT2O=CmgaL@S-~oy(4{&68{NmpxVB^bH
z&&Jujn}dOYjiY&25(5Jpd-E<!1_m~^=3Rme3~a2;J2M#=*jSoDbtM~f^G-<y1~#VV
z9VHA5Y>dr20vH(B7@BveGcd6JZ{A+Vz`**id3y*01MA=B?V1b>tbdxffdqdyZwq2z
zVExs+4W#mC^VS*$2G$?VTLT#wSnIzxgZg%?-<r4bFfg!wZQhc_z`**Yd5b3l1MBDJ
zE!qqWte={<a5FHler(>H&A`C=p&3+3vc7NLti!;-`mT91KLZ2n+vZJ03=FJqnm2(A
zecimtfPsPaRr4lh1_sub%^M>b7+7C4Zv+WGZ{Enuz`**fc>~Czr}fPnJQx^QpEPe!
zV_;x?+`Iv#<5BbaL<R=dht2El7#LU|G_RLoU|_x9ysnCYf%RVVx^M;t*1OH?Oc@wh
z?=-IyW?*2w-MqGdfr0f_^IAU!2G*O+Ye7!C(Y%(6fr0gUGpJL?daZelD+2@T)#f!y
z3=FJSnpf8|FtA>3u3sI)z`%N`d9@`21M9`+)#3~ctQVSBl`=4}o^M_i%)r2Uu6Y&6
z-DjIuaWF8jo@oYGwWpgwRW0kO=9Tgc46G-cS28j%u%2jMk;1^hdb}A_<FX!WUIB`O
zqs=Qofp?^Nc@6^u>*40*-V6+^hnkmbF)*+mY+hc^$-uyRpm|va0|V>+=4I{-46OT_
zmx01!Z}T!xSnO$D3aZ<8H!rniU|`+Vyi|&Tfpur|l5z$H)*a1DK(W2Od5Iwd1M9Zt
zC43AFtXrEGgQ96m^J0);o0}IaGBB`iYF<>$z`(k(c~KYx1M7z7MIbM&Z(hU=3Wase
z3sV^wSl2c$1X;1Bd7%gc1MBMM1)vC8)w}={2P>NwfWmo2^L$XVV|nv@8wLi}WzF*i
z7#LWWHqQfTU(!6!ih+T3aq~QoD;71+O=e(VUD!MqB)Fh?F38#Qo9BS+o7X%CBsaHt
zjvGTg1M8gTIT{QMth1ZvfC6e(^XxnZ2G*I)vq33oM)PcA1_svY&9lWA7+9w@&#GWx
zV4d1LE1H3UbxQLrkSiuP&yr?fV4c)F6O=qAHqQhlwh7HM^%xjf`<rKiQgvVRj2zI!
zRPziU1_n0n<{3H+3~XG@Gk6#nwjYzUv141#asf0&QvfP54V*wz88+=K0k-Wd0d~t-
z0_+Qxvm5})C#Zu))j%cR2XK)HDsTi81eUWjfXW{Q5NiUcz%>A|8bEVX1)!p9gR8)H
zmJMQm__rN!1(gyD#6aaCNZ|w!>j6k}1Bi71WVC@6sLZl&XZhf;oaKX~!*Uh}aN(%w
zu$*OrcEEC$22df|;0$sU$n*yq4$D~#Ky`)#$UO=m*#HnR!3ER_)dZDVE}%KE4O*Zg
z`T|JN2M{5k4VvQuRVoQ!7l0hJ05s**03s4VL;#3z01*ZtLV;0WJBt7#s9gNu+RpaD
zZ9Cfs_kZh`vp9G@SkCgmBcPq7z^k35z`LELz^9$1z_*>Hz^|R9z`vcP03;XK&QcK6
z&QcKE&QcK4&QcKC&QcK8&QcJ*oTVVbU^$C{C#c5^Dk={|fM%u={>*Q?5Ycuavh6}t
V+lA=13o&gMV%sjnExQmO006cw_|O0V
delta 7277
zcmZo@Xl4fC3DSaF7#P@i7~p{M>_i=7#w{BYdgTQe|1@3mV_;zHYW$+bz`&Th`L8^?
z!giJij7$qQvpM|J-_FwD#w4(vt-$Rc|8kZDH-Y6W0U*KwL>PdG11ti|Srps^7PAxx
zEN2k_F&YGxvpis4u$<)pqr!5Q1}1^UEE5zKvpi5(&LY5=u$-lVQD8aC0!D%DEE|}Z
z47RfsIDia)08+O>U@^-Dfz2!jm;|=6F@l5(K#C`Thz%fO0u#tcW`XT23z(S%ma`pT
z7Ff=<fmvWX+XZHj@()ZCma|M?7Ff>Gz~Zo+#er2|Ig5dfz;c!ZHIUmugae2$P!rhB
zqM!z{Mh&Dd0i^JOs=#uV0uXBfh}FQFu$;v~1LQvqfu$@U#sYPaCqa50R6ybKK^3Gq
zKt*6V%K=q^?JNy!Akhgb|M<7FOaQYJR6r^guz^&7hzG6$%ULF<gVd^n)E20N)Fy!0
z7gRy)0<g&&z$Q0<Ol|-<W&=ob13M^aT|lms7HDS);Am$F;B03J;A&?H;BIFL;Av+G
z;B99K;A>|I;BRLM0I3mdX9*B$X9*B)X9*B#X9*Bp&JrMIu$09SWRwHQSq`Akboj&1
z!^*(GxSzF&fq{X=a68Wj@e0;@7URaoQU(SV)5b=B1_l=M#zqYW1{RCPMkWRZra6rb
zu?!4Ma~m5>7#Nu5H8yZFFfh&kpUl9(wBWxr0|V2-|H2FmOpE?yF)%Rg`sc{Nz_k0H
zI0FOIp1-*a3`~3fIxsLW?fWalz`!)~Pbvcgi{&441_l<ZKU@q9EY`nc85rtWY<?Rs
zFtFJEW@cbuvHKOuz`$bvOOt_t#o=ci0|SfW&tL`y7N?);3=AyJKdKoRSX_PtF)*;W
z{?KM%U~&7w!oa}d{ymm~fyLvyDFXwG=XYKP2Byw$sSFHEUEgdO7?`@hi83%S^?U_6
zsQ0TY0|QgvS6K!Irv5MG3=B;56TbK{FfdL0qQbzyH0g5{0|P_L=U@f~rlp^a7#Nr)
zf97IfV4C(RiGhK|>ytSH1JjI8Ah&yejALM6@%d=Tz`)}B5#$KJ4-pIuEdC!r&I))B
za(dwVKn4bup!X^a3@pL#${83~Lf&~XFtCKalVM<B345Ezz`zn-|JI&?foa)W0R{%9
z<!_Q07?@VPF=k+3TKR^Rfq`k&>u?4Jrq!=C85o$>ysBYfU|RdipMimC-77r?2B!6|
zco-O%HoVMcU|`zxGJt`BY4b}11_q`rF9jJGn6|#iV_;yYc;U&wz!LES<h||BLC%VN
z9?8JKwDY+U0|QIcb6Fk+2A1e&X$%Z3G0z+r7+7MTNii_6#61P2iTLevzl+DR)(bAR
zU|?VnSSrN8z`(yGhk=2CZ;2ZN0|W08MFs{2p2g)13=G_heHj=SxE3ojFfec~s$^hb
z;8^6xz`(%1NP&TYfo)+i0|Nu=LVpGZ291Tf3=9nF3%MB>7}OSIGcYiyF7RPsU{F~A
z5?5Zp$H2g#G(Vq#fkAP800RSqLj8Ob1_lQC`C<$V407`-7#J92=S49vFnG)ZiM!9^
zVqjo!o14JEz~DO9jDdl{Wv(y-1B3INA_fKqr#XQP3=EEQ3>X*~9Om#dFfiE926@14
zwkHDvgUxI;1_lP(*~|<K4A!&a85kHWXIV2aFlf&bXJBB^nhA2W%*=X_tEFaYF)%Pl
z%w%O?U<jK5QW`qLl7WFCWCqBx;OV&x3=Bcj-5D4d0;hvQC16@L0|SHqv`_{H2ES<_
z>wTwzeC#tdoq>VDd#V!y1B2I8IR*v>&nckLvYHacz`$TJ#fX7{!F&oY0|SHEWRObJ
z$&U353=Afdr5P9)j3<>cFfbTR0y)TVk|qNKgTW*w1_lQGiLnd}40;od85kIJCvq|{
zFz8GGIZ=9oDFXw8<OGn#;{9<93=CrZAg74-gDeo~D_~$?5bgs-lTe=y0|QG!A14C?
zOJZ+20|QG^uPXxsOLDIgLp=jaN-rY=150WTDAlL+*fKD%r1yZ*Nk(@S0|QHDcO(M?
zOIEi90|QHTw>Sd>OHNlA0|QHLR|o?GOI{Z!m*jWxGcd3ebY?R!uoQN>Gcd3ebt*G3
zuoQRHGcd4}bc8c7u#|S_GBB`|bucq9u#~q)F)*-Hv>SoSh{|>$1_qX@wju@wmg+W;
zp*3x03=Ax_Z4wL&EOo6F3=Aywtso;BT0!ECt)dJJEKM!N3=AyIEq)9PEG;cs3=Ax-
zEo=-7EN#soZ?rdqoYm0`%DkOTAiZ5ppmL|Xv6g{>rKb^;d3zf{nU}F|``7>C`~mGO
z4Px6_8pQwRZ)a?fTf|b&)Y^Cglm%NFk7qD2Ff}(GcV=K<YHB<#&%nUc*m$g(fq^Nh
z@mLrG1CwjxF;IDu(0GiGfq}`b@hGUojBPv$%0`)uN97n8n7kT~fMPeR@rVxt1Cx8>
z5m5YQHy!~c+T6y&pahoJc-V`9fg!)~unGeMLw!Nxp*jWzhQh`}5ey6rMU96*iKn>n
z5GZm>8V`b!Pif;pM+OFlvc`jw3=9nAjRy)D7?}Sz9`IyfVE)&5K!JgQsiARy1*jx!
z-0#i6z*N_`ALN+Y#(kjTv8Hif1Oo$8b>luu1_q|8#(k0u3`~`cdqF;{sBhdG$H2f;
z-nbW3@W(aoRb^mc@@U-4!N9;2)3^szEO|EW0Tr*2je9^&%W2#r%D})-*|-~&iK`lS
zM>8-mR5$LnXJBBcY22;Ez`#)3xEqwi>Kb=tfPC1v3sf>RH15)8U|?u$+yyFuni_YO
zF)%PRH`ecrVqjoC+_=+@fr0sN<4z?82Bxyco$L$@Or?!GKmlCRxC3N;apMk9;1@OS
z096HrjoT|37?=tgw}a}o{KoB|N-D2$JE(}vZQKshp3}Gu<ofK!Z9WVPOj(WFbQu_!
zG8?yn>XxX+t$7R#Oc9M+>p^CRH*N)$#bJ$G`573PLL0XfFfcHMG;RrGU|<Sv+yb&U
zsBw!30|QfF<K|KZ2Bv_<&7cI~-?$l6o%l6wmSA9D@@d=za+7!CCXknoHg2+FU|=z8
z+$6@pz+%$45tQzY8aILxvO(iUP+h3kxS<}Dada9tfa)Es#top<tkJjuR6D6Pu1{fL
zU{PsY56Wjsjq5>Gx<cc6Q0A6vT$jbbz#`MQ&WC}4MXGTfD9cGSuH$83U=eFvo5R4s
zBGS0ln}LBvsBtYQ&j>WG1?l5!T$91Tz{1nG#+iYEg{yIm9D^<c3rFK>P~Kx}Tn(zG
zSsGV^Ok-+X&CbBU!qB)Xk%589w{aDyrLcedsdl+<jK)kXjZ>u=7?_wFr+^X|Q{$8%
z1_ma^#wnm6W@wzk&cML<zi~21XGh~?8wLi(ob8`G<#Jf+I~ykzGB7Y^H%{_qU|{TM
zoTSFUz?juIiGhKEvAuC(1Oo$OX5&PC1_s8q#))hU3`|QJC&Vx?Ft#>MFlJz2VQicL
zGP|X*A5^d~H}>l>FfcYZ_Jf?t+Sr%Dz`)ql*axaD*&F+`85kHF8~Z>-7H4B`2?GOT
zLw#d!00RRHcVjQ8Azk0t%gVsO!rR!Bz`(#**Vtptz`(-a*dxZkz*yVZUBJM=BG}js
za%fFsw;BTji*RE%$f4DZT_Ed48@o&x7#OP>yFm4?cw=V@0|R4aV<*TI$;M7$1_s88
z#tu+KNjG-bF)%QeH`aFuFfg#lHnxLYTGrSOidy-`b|nS|#?r>N8U_Xy#m2U91_s8G
z#x{_Dl^ff585kIg8(Tr8xoTspBLf3tQDZBp*j8_BDP>?_ENpB6wfQs~TQnFL7z-L(
zKn1UMBdB;}%x`Q4m880j&HM}ujCqYstRQ3br$6kMQ(n%pKn~Qd1Q8G91eUVMgPPFt
zpvI`ga+UzefaNR+(gMp_Hb_ob$|3_2mRimd01{as32LN+^fgE;EN7VjVl4nkYyhz~
zfLIqmtOFp{2N3H5h$R5B-~otb0AhUru>wFW2Psff8O-7UHQZ$swzDjdXA)><GmvR#
zGmzcRW+3-ZemhHo+&_7)ON=4Ra~T*In1i<S7${6;u4fKzx~9#*z#P(ajf;VSIkf3&
zCIbU=SkqMx1_tKvrmJcU49pQtS6LYtm?N96q%bfrM>Sn>W?*2BZn~nxz`z{SbOmHw
zY}4g<1_tK1rpus$D8A{kECT~`Ler%x1_tKDrc03w49rPQmn;|<n3J0>i8C-Tr!-wG
zV_;yePi?vw!oa|s)^yRBfq^-_>7oz=19L{xg**lZ=FFxGJ`4=ZSxpzz85o$en=Y_0
zFfjgWI-kJ6z?|E3-kO1dIj`xw1Oo$ee$%-U1_tJWrgQ!b49ta1=X4ktn2VauaWF72
z7dM?vVqjn{X*vtiP}+1>jDdl<tm#Yv0|Rq;ebX5)1_tJerZXxG49t~Hr|TFPn5&vj
zM=&rjS2vwDVqjpdX*$izz`$JFbSjO3fw`{flmp1!O{b(77?>NHPJ--hY&sdpz`)$p
zbkcx<fw{TqBp(9<b4$~SECvSV)}|Bg3=GU|O(&EY7?|6ej@L6VFn2T^2NiOiP4&mk
z7#NsynvR3K-Q9Ey<n5lOV<0#6HXQ>6eqYluMg|7v{-&cb3=GT@nvQ}rOl&$Tz`(#f
zsp&{I0|WEqrX#Kl49ruSj>t1GFi&kd3<~vWO@~1NJH6?!9s>jOjHbiv3=GUOn+_#1
zFfh+*I%LVfz&yL@P`w}n1M{4wgP=&C+XSj7nddbf1bJ<K6S$sS&~yM~_QIwEpm1K)
zv_GGLfq8M$evsgjrv1_k49rWL_JL~DWlj4)X=ZuTK9DO`H0=e&@5-jVz6=b^tD5$L
z!gqDk9#A!#-n7S?fq{8V(;nq|1_q|Irad4Zu5H?#z`($i+O*q|fq{8l6R0j^N@?27
z!oa}1zG+tq0|QfX(=HbV2IdV-yFe9HV$&{W1_tJhO*@kq7#PBvc7pV6YTBvDz`zvW
zv=fvpH#hA7)vpmvJ4_iEn71_T05w&jo3?|}>ei<1Mhx`~43SOSxfvLkw>51`Wnf^4
zYT9Pcz`(q{X`2)S14DGv)(Qp&<{eF2K`qmmrmY}jb~bGVwRdBiwt&37t7!|Ug&x<m
zMW2Czd3VzmP|G8}X>$$(1M{Ay&E5<Q3<*t}H5nL~_cm?jU|?WKY}y3MM*EsJIWREP
zGbA-_0tMp!rj4MMPjb`700su;15F#X85kH+nl`dAFfbo%+K|Y=z>wOs0aS|!H*Em5
zAkv!F7cele_B5>rS&`nfUX6i)wYzCOBLf3NM$@_&1_qYpP3z1V7?``7)(J8&uq<m@
z3rbx_n%079y`@cSwHX+g_%oWoRojxLHK4L>@$_Zp3O*{6n^q<;FtAK%S_!IyCpN7V
zW?*2M)U+a(fq|vJX$7d*ov>ZZLSY9Z<FD=KEfr*$>wh*)<6>Z7{N6M*k%58nYtvL)
z1_s8@O;cqV7#Ke`O{ryIV0_;+C6<AK@om!-a|Q;+*G-@nKI6+KP(8=^ylJv20|VpJ
zrpX{v9yd*jV_;x>*fhzQfr0UU(<BZC2FANhpcX#k?WT!F3=E7nn<j#)vg=LY`t53c
z(*y$s2FA-x6ZjYy7%w*U7cnp}o^R?8V_;xB+thE#z`%IAsUK7`oownWW?*1E-qaVs
zz`%I4sZW=If$?`!AIRQAO}(I+<wsMm2Ll7+x29fDo$#fp7i9gXrXG;oho&Bo+`Fb8
zkldT59+2FtruuG><cp?mkmR$bZjj`Yrf!hrqoyuU&Gw+F3lt>xnz}%)xYN`La>cEt
zPSD8Ijiydb1_s7!O`RY=U1{n_Wnf^u)YRe3z`%H+sY8*0f$>~Zdp!dK<C&&*P#B(S
zY6pePiKcco1_s7sO>Om&3=E7%n%Z<27#I&XwSu}!txc_g3=E7*n_86_7#I&Ufvday
zO)Vf7?rUn1W?*34+ti%Pz`(etso9=^fpK?Jvj77F<F2MAP!#TLY66Axj;1DN1_s9M
zO^qPIZB3013=E80n;JoG+S1g>$iTq3xv3!$<hD&s4WRmUV^f0y0|VoR#{YE;42<g=
z|ASg3>l*)q;%9B+f6(~Ln#O-o3=E8`8~=ftDytg*feQAOjekL&Skd?w)GArt_!ngF
zvc^B4`ut$yACS+MH2wjF=;FrT`3ww<iyD7}0&ijCZ*7Kp2F3-Azd@4o8-Ia9Z(ids
zCk6(_xsAVM7#JAmH2y4SU|^ix_%n!sfpJ#jPmpOd8-Id=dq(4rBnAe?>5V@?@iVRQ
zhXexy<J89Qp!k{6_}!O*fpK!<cThuXQsXy}mnJrT10|~ojo&~H?Qi_X#=s!O*w^?K
z<fq=ouOQK$#;;5a42<24U&6K>kOvJP3YdYaY0&tZffi^~N*mN(01Zt!fQSST;h^wf
zIZJ`HKs$?pVmph0Qag)*@^Tgf(C}CRXk_ezJ*a*M8Swx#M0Ws07=X9|s-R&<&|p^q
zXc%n*h-grou$*NBNQnT52mp=vT>!BTfXw><Vok6RSjqyj*Z?G%0J1`XRbVL#i1z{H
z<_93+0*k;>7O<SU!*Z4bAU7z01{)PP1h%sXaDYY^IY7gIAJ_%9vpir2jrUz(2MHVi
z32cA}*#DDX&XNEc*$V&>4j{q+L@0m=0d|3<EFi`QHi7Ld0pKx30alP11|R_ihyWXC
z;4nagNntx%19&vm0My=b&;ku|YJ#i{&;)6j03JHj1P#BsI4orW4MiGgg2D&HN&tx)
zfLH<`WfMRW2ed)Mtssd8XNTo13ZUpw00rg;kdhA|u7I|~auxwlP!)jmCV(QZ0mNzm
zu_m|*EM);P7PvYrX9)nYK7b?(Kr920t^>{i%UM1+2(+_&&~9h>pwrIsLARadgI+t!
z2mN-I4+iZl9}L@BJ{YyLd@x?l^1(!5JBxzCAO39u3M>L!SrkB?`ydbU{sVas+d&@W
z(F9PNuR&g6Im-r6yHmh)Im-ugf#oa;W)qgPTmT6jFk8-Yz}#Rt%L7({tt=Ky6PB}W
zFcWBJTVT=7w!m^b+XAa!=eG&i__Ecr{%_vR!N9=!uX$Gz0|V>d=3SNy46J{ecL_2u
zu>Nk|naRMw`l}gK!?ONt-YLnz!1|+kM+pN1>-Xjz0SpYR-<o%*Gcd4zZQfqTz`**Y
zd3y*01MBDJ?V1b>te={<fdoG`Zwq2zVExd%4W#mY^VS*$2G)1YTLT#wSnJ<5gSwEc
zZ<@FAFfg#bZr+l`z`**dd5b3l1MAD?E!qqWtS_3ka5FHlK5yQf&A`C=tQl0bvOaCz
zti!;-`lNX?KLZ2n<K|683=FJ~nm2(Aeb~IofPsPaLGvbN1_svq%^M>b7+CK$Zv+Y6
zZQjVsz`%N^c>~Cz+x5*GJQx^QZ#8cK)uK0>H-L29XkMSlz`%OFdA%J21M9Ws^)d_$
ztXG@YRWUHIUTIzz&cMKWxp|!_0|V=&=5@jh46GNM*Mh3#3(af&7#LX3H?IXb?OgL(
zE(QkHv(2EsBkP&wHLeT{tf!mTC^0awo@!oQ&%nTXvblbB3<Cq}iRRUyP(R+hTAYD_
z^;q+&QU(Urqs^;=85mfPG_L}=`*8CrP&6HC2363k2b)0^H0y!pmGTS>toxf+GBPl*
z?rUC=!oa|~w;5DVv+ikL0g8j&%_~5Gx2t)14g&-0&gSLb3=FJ0nwM)aFtBcKUS7}1
zz`(k#d07Sn1MAl2W$p|NtXrCwfx=>Q^D<CaY-(Pbz`($|v3aR20|V=Z=A}{$46N&$
zmy|Owu&!%f0*dXm%}Wd!7+BXdFX3ZgU|rq37!*ybniqo%TiLu=k%57AMf0L+1_svU
z&5Obq7+9AzF9LaKY4aj(P$(>EUYN?jz`D43A;^kF%?m|9qovIYKoPW{c>yR6<~J_@
zh4Z}T`RNP{taF>^+b}S&&S{=6z`(#dyLlc+`>f`9RtyZRGn?muTrs10ZZZP{>-6Ti
zAi-(Pb3x9Y+B^qj-<0M#Ai2rSbKDr}8CWMZ&(UCDV4c`J2NX~fnrG)RFtGMF&jzKW
zzUJA+p!ucd*<uU~Y~0PWDi|2pxSD50Gcd4mHqWwQU|{2Do+Zt|z{cJ@vx<R%jjefR
zBm)B*Yx7J!1_m~k=9xSU3~bEJGjbRh*qEAU_%JZAF*eW8VPIfmXr95tz_9(8q>UZh
za+V3;LJ(B`I;evBj5h5o0k-Wd0d~t-0_+Qxvn&9~KL8cR7uZ16gkw94fzxsp15ml;
z04kIVoI&#(kjWKrX}AGY+8+QFZWlnT3n1155bFVm^#R2CpeeAFMO9!aix#MQ0o5G>
zAeI7%H33|NfmjPbrKEyO!E%-cjRnhD6kG+ivpBedrnUmK{>@*`QlKWVlm#?d762;n
z3P28>0Ag(b5f?y&1IWn}+}c?txG!g!;IUyji-MxSRu-E-{M$ZQvk7cxdtePJ))c$~
zma{B~5LnLQ;Q3%V%LWkZg0;YMmIEMS1Bh4vsv`@$+F1&`+gS>H+F1&G+gS?y+F1(x
z+gS<%+F1$$+gS>N+F1&M+gS=i+F1%h+gS?2+F1(1m$MW^7%XR*05YZlL>!0^XlE&i
nY-cHmYG)~kZf7ZoX=f>jZD%QnYiB8l-_BBy@W+4Ig@^?JeRAxC
diff --git a/data_storage/UN/Economy/SYB67_128_202411_Consumer Price Index.db b/data_storage/UN/Economy/SYB67_128_202411_Consumer Price Index.db
index 9dede1162fbcf535175e3830c9477428cfa22c6b..379e2be685362170a3cf37fa532e0f84ec1dd2d8 100644
GIT binary patch
delta 56
zcmZp8Ak*+bW`eZf6b1%{Vg?2VW(EcZMg|6E-ibQKj8hsDS`!#s6PQ{Pm|GKAS`%1X
M6WF#UurJUD0FD(7lmGw#
delta 56
zcmZp8Ak*+bW`eX}1Oo#@F#`hwGXnzyBLf4|(}_C9j1i3qtqF{+2~4dC%&iG5tqH8H
M32a*v*ca#n0G9y{^8f$<
diff --git a/data_storage/UN/Economy/SYB67_230_202411_GDP and GDP Per Capita.db b/data_storage/UN/Economy/SYB67_230_202411_GDP and GDP Per Capita.db
index b5881ceecc6fa1f395d3b30543c2b6e3522a3920..6bbe1a7ceaa6afd011a9ccc4b728e3a761134446 100644
GIT binary patch
delta 242
zcmZo@NNi|GoFFYYg@J*wg@J*AnSp_Um4ShoccP9l<CKjFtN581*f#SByyaJKR$^da
zU=d`102T%Y#wLhj26l*MFrRI+g2F3SHZYrMyP^VnAmere1$HMQNMXiB1`3l5Shlk$
zNc@p+DrhTUY%5@DD`0LbU}-C0Z7X1FD`0Oc;Aku0Y%AbuE8uP`;At!1Z7bkwE8uS{
s5NIn9Y%36ID-dog5NRtAZ7UF4Rv^A$k%Pb_1GepK0usOY7dZ$3096h;S^xk5
delta 208
zcmZo@NNi|GoFFY2!N9=S!oa}5%)r3F%D}+%bfS(iW5mXURs2kh&6{}y-twzADKRiG
zun00h01E>H0~<s!13OeR8v_Gl^JWEwSFCJcIi}5m0UtOQ87OR42oU6l5%(CI3fc-7
z+X|T43YgmpSlS9$+X~p)3fS8UINAz0+X}ea3b@+}c-jhh+Y0#F3i#U!1lkG&+X{r*
m3WVDVMA`~O+X}>%6^JjG=D^6dolQaF7yqONmdz{yf8+sQ!ZjWM
diff --git a/data_storage/UN/Education/SYB67_245_202411_Public expenditure on education and access to computers.db b/data_storage/UN/Education/SYB67_245_202411_Public expenditure on education and access to computers.db
index cf517ea1e4f6a97222db59608d2b032380d9d1ca..8d5bc504d54f2acd7d165c8713e09bba0a1eb697 100644
GIT binary patch
delta 65
zcmZozpxLlMbAq(s6b1%{r3?%VEDQ_`j0_CSyc2bd8K*QRv?egNCNQ-oFt;YKv?j2&
VCa|?8u(u{~v?g$FP2gJK4*(9#5la97
delta 65
zcmZozpxLlMbAq&B1Oo%ZQU(SF76t|eMg|6^rxSII86z4KS`!#s6PQ{Pm|GKAS`%1X
V6WCf4*jp1gS`#?8CU7nA2LKxn5vl+H
diff --git a/data_storage/UN/Education/SYB67_309_202411_Education.db b/data_storage/UN/Education/SYB67_309_202411_Education.db
index ecdd1175f9badca82aae2e93a69759943bc93695..5288480a79911942ddd75c594690e00b5aaf8884 100644
GIT binary patch
delta 3825
zcmZp8(83796Ql*FFfcF)GcYhPGcYi4F)%RmPSi1GoU$=tt~|f{yaWaa;ACK6;+o8(
zpe)M8z`(@Kz`(@Fz`z6+Wnf_9*qozqiaCkl1Oo%ZNd^XnQw$6Yrx_R+&M+`AoMm8O
zILE-iaGrsI;Q|8#!$k%LMm`1x#<vU%jPDp27~eB6Fn(ZQVDw;MVDw~QVDw^OVDx5S
zVDw>NVDx2RVDw{PVDx8TU<_bjU<};sp>m8_jER+jfr*EKfr*KMfk}XYfeGYBrmc($
zTi7=lum~(?*&ryeoy9<aNnktM0>OX$+gTjI><NPZ`M0wM2rvq4XKMhn69oSAFJ~zb
z6j;tuARw@uB>}{00I>o<MobW36j;vcASke%bpcqH0a(`tur39V+5-Xti&-2dY-V}D
zB(Rl@5oDJFBgkF{#((_FSrQlpma{Z43T$Ut02V#K2y(###{c|VS(q3vEN2a1R#?s|
zASkevRS@K=4<M6S9|#C+XKj%CZ{N;Rz}(JKz|ziAz}n7Iz}C)Ez~0VMz|qc9z}e1H
zz}3!Dz}?PLz|+oBz}wDJz_*>HfS*ZWJKF;OfBnl@3={;mvs@5h6xhnj3^tqzY&jE%
zeSzs8e>=+o!FHAdLhUREgtxOC5Mg&<^w`QH`k%Aja~>$Pz2-TB;$of=C^qIPgW_YJ
zFepamF@xe{ZV4z>=B9$;Wo{?~17px!R|W>g;JKy@42&UjRT&r<L+6SyFffMAWoKYu
z44+fMz`z(WCzFAJF>+260|R5!98g?G&#_@(V2qig$H2fCJ4c>@fibRrjsOD#WBeRO
z1_s82*@X-YjES?87#J9nW(PAcFecA-VPIfPnGLcgbvDSFwArEz42<csSs54@GiH@C
zFfeA$0y!&d7RXuIvp~+unFUgxJ4=m$fiZ6u$XWTb*cccX3ucxxFfbO*%wS+(ESed?
zz`$5MvmTTdOJ-U!Fff+R)MQ{_ESo9Gz`$5Olaqmgv0_FQ0|R5_j4TEQ#;O@0e^k!^
zrPrDnAb-@(&}Cp?teYXnz`$5P1C-7irq?qtFg8xlXJBA#njX)<z}P$;l%89r+cPjQ
zwoW%-U|?*UuE@Z^*gjo|fq}7OIx|Q^=d@x52F9*w$qWpP-P1t+?wJPickeV41_s8y
zX(|j1jQ!I@7#J8QOau9Q;?yz*2F6KK(-{~TCr=G$U|^gw)t!NXaq3hH1_s7yQ$gOC
zK2?f=fpNxEZUzR%nNzA67#L?w$!1_+oINF)fq`+(6i}9%JH>{fo`G@R6p%mWPXYO3
z!4!T52F8VxLC#t<8RU<}lM@&i7?(^2rIMwSL8)ZfWKb$uJ{gosR!jytYvp8+vsO(4
zIcxPKkh9iI0tN5dNuXT5Zju!P1LOKh+6)Yg8z#vxFfeYM#KXYAxM^Yy14BLI=83rs
z42)YQ#xXE3Zk-4Uu5A+?7#JA0Pc&p;VB9fLiGhJ}=R{Cq+%=Jffq`-N1W>H+nE;CQ
zy%RvOzHb63*7r{U#rlB>pj2{j0w~rGO#mgv!~LMdc%&bc7?1XYBJo&1$oI$l?LZNC
zqF<kZf$?NNC^eqy2PMYS{h-8nrmu*Bf$?k~C{oV#fg<I6pECmk<Apv@q+IL+S#zmR
zoPmMyavui+1LKw6N(KhTtG%GKa;+B>$k%&8*4*d?rInk#It&bqw|YUozugP+{hgi~
z1_s8v^*tcp-|GSS{(cY0_YZnNiREDr$XSni6c`v7ANL3{FfcypVParleA*34E6=)9
z7#J9zcY}QYqT7vuf$?LvIRgXZr)~`f2FB0bpd|dIn~Q;g@oN_-?!R?`;{JOV$XP$S
zK+gKvWy`?8_^YcPWX<m`P@4SH1q$T9U7#HQuM=d=|ITCv1_p)BU<L*TxlU&W1_qf<
zV+IBWsZM1E1_p^vP*oz<393v)I!YKA7=$`f85kG@Izky382CC|85kINI!r-TO@|r-
z0|Q5gI0FL%TL&n#c-ujt#nYY%N@(2ekqiusT<xI5!r2bWiX82rG|b)(O2cgJpft?d
z1_~~gwp<1VCYCl(Xfd~eLW`*l6k3dJAa5|V$ulr8{BPrDU|{&y2C69jwiYrlF#Ksv
zVqjqS-3s!?uT~cZ28N%lAZPt(Rb{AWVEEoD%D}+zt(BF5f#GXQDFXw;mzFdJ28Pcq
zVGIlmpIY1)7#Kdbm@zOgd}smr<9&-50|Udm7B&V3hPTb-3=9l!nll&}7+yC=GB7Z_
zYW8MeV0hVV%fP_!qFJATf#G?x0s{lXvt~gC28O52pbG3sQxO9L!{er828McuM@=CN
z3=9vOK*9B(31rRvCUph|hI>sC3=9l+n>ZO5816JyF)%RPZp>z2V7S#7!@$6Bv(cA<
zf#F7@9RmZy^+u32*BTWW7#OZLf+FQgBMSoq!)1_PE~POrFtLV%YEchRHEIc}N3}rh
z02u}b2A1~!{G#pu`Ni7*^NY9t=a*>z&o9~jpI@r|KfiSQe}0+v|NOGs|MSbS7Hnma
zXIikGO@R5I{c@HAat_;B7RdkcpXR{Gww>(*<A46;tQQyswzF;kF<B;nD#HR$Wf;K7
zB(R*#08|kPF#hA;%<_RrU^Cl=U;NWP$a6DtZ|C_S|CF<yac?lFjj`7S)WX;c%E)ee
zLB+T0UQkAM*$c|Z&U?xk7#N-QfXWxgJ)mOGVGpR-v)=<s`gVKN85kIC_kePw%^px1
zv)&C#V^+ICN#AmJECU0h#cogw!+bX=<D2aU)k3DbLHXXKem5xN8}9~Xe4|~UjBmIL
zl<^IAfpVDsE>I5B+Xb>lcNZv!>FfgKFzsES9HzAsl*2T4<}ffYYU~7AqrMYljoMC-
zHL5#7)~M_R6|TxVL6wBk4p5p`+)=>5z^Jezk%56xen))}0|TSn4p8|by8~3d$m{@>
zFVZ_em7UZMQ0XeU9aOqXYzO&Xd^@Og726J~yF|Bx3Vo67AZH102PGNS?HmjY4D8z~
z7#J8hw`DRgFmP{+Vqjq4-3CgT{M&387#IY%=`t`d2yc^PU|<m4#$V6Cz#zU2lw%~f
zf^v-XR#1+S-3rPv@>@YUMsX`B$0%(DWdP-^pp2}tm7RfsL3Inr8nrE;44}Rxf`NfS
zV~ZyP1B2!kD+UGztu5LN3=G;^KuJw!3oio$gYM=!1_lPb&G`%r4EmcvO-_T&fuLMy
zxY>z;fx&1qsC+Trtir&+V6qvMFHJXt@|oEtP(Cx?1gg4)Hi3!@!A+nRg}^3j1_nm{
zO`y{C<tAAM2F6#LK!N;vBPfvHY%E}4V6fPj$iTp0xiN@=fx&7cs1&o_Xu`n2V6#z`
zfq}txqZlX`+HC~+#(o3HHx3&>f#$dY6lhKxK!N7G0TgI18$f~Px&ahuZX5U*7#Q5w
zgM8z$9^@O(^&o4!)`P6^UJtUyXFbRo-}NAC{ML&xFfjP92iX#^4&<4@b)YZ{S_djL
z>VwyLF)%QMtg~idU<h5O!@$50woaCTfgyYys4$CI2a1}=wV<epS__Jr=(V7ziCGJZ
zn%K3VsEJz(ikkSfpr}b$3rYcrYbqHS7?RdxF)%PBuZd=0U`Scx!@$6hx&~A>rLECp
zU|>jJ11d5z>eqm*$y^Oe2U)8@zR6x4&%nTtvpRr*fgyLbBLf3N-fBYz28R6Api-t_
zHK;HvT+PV9z)-Xb<gDUVAm5j)0{Oml70CBxt3bXlUj_1g#VU~RD_4PhU$qhx#?>o9
zVO+Bk6vnkH>p{M+TM0@s^((a)7#JE>N;5DpG_K@kU|?ukQNzH%(7Ymtfq|iA1*q_A
zT>&cm+E#!HzxEZN!mncm$XT5$K!sn|3Q*zKy&P2f^(+U~NWIHJHB#SlP!Zd|928m;
zmV=x%aXBc3O<K+h^7rIrAPrNNfr|dA%fcBL7^W@rU|?XFzRZ$=fnmlnO$G*rnaiXY
z7#L<P<6>Z7n7y=`fq`MpQjoLeE{$biV3@bmkAZ<<{!);$7Ayq?@4}^^w6bU^D6K4B
z0<vYv5>S#{x&#zj%a(vbYxxpqQ2Jl71Qc8=mw?>0Y6&Q~Rxbes*P6wk;99#F6kO{T
zgMw@QVo;LYuo#piH!cRHl}(F58Eo@n9tH-6EsH>*wRI85S=$zYoV9%s$XPoUft<B-
z5h%2FEds^*?nR(T-?NATl>YZF1jXXMg`mW>e<3Jw9asoTTn86|g6q&iP~tkg5R|x%
zECeO4qYFTZ>(~O2vyLwSrQs6`K>7aU0#In3S^x^I(+fbMb!Gu563@;DIqTf~Tu}FL
zejKQSINu-CMVt?6>rH?9UtW6K1O+yM?Q9B)zxcN)D6j}@XPLkc?p`VUv)|6LK;aKe
kxIqCV{6XQD{#F5n5B!rI8U!X8ux)4Cpzuq7nSg=-0DUirrT_o{
delta 3827
zcmZp8(83796Ql(r7#Ns@85kIt85kJ27#NtIPSi1GjM$hkSDrs`UIGIIa56A3F;3=D
zP_|`cU|<6AKuWnmq6`d791IMMfeZ|c0SpX`{tOI^ehdtZz6=bEJ`4<u-V6+kUJMM3
zo(v3(9-CbhPB9BH@-Z+lzGYxwe8<4R_@04*@x$f<m1E3y3>O&~7%ng{Fq~&#U^vIX
zz;Kp<f#D1T1H)+s28L4%3=Ah37#L14Ffg$)Ffa)~oXy0;z`z7@Bhz-q2?|@-HyN-9
zEN5w8oUoncf&3r-X$M%@ma_>k2`p#3ATO|;O@Zkj|8kZC@&emg446Qo8$hBCO#k?|
zvn-Hj64=fb09G+UUSK&(0u#t6klF$!kW_&@NLd3Dqrh_31bKn&tP`02^KWMfkOv7Y
zV7joKRY34R|5g@3km3&l|M|DGJ`i9O*v{4<_s@PiO93;ZLOZJfOFOFoYdfm|TRW=&
zdpoNDM?0$kXFIC^S39c!cRQ;9PdlpsZ#%01UpuP+|8`aZ0Y-)8Yz7Jf+t~~R{`GHW
z31AXf%vK<<m~Dc<X0{Fg_!qNW5LnFeL0~(J03)Noc2)xr$riu}@@N60z;>1k0wDJt
zU=~=;x`A0>JL>{wkeenjgWQ+E2=ajgBS?h;qrg^H#{c|_Ssn;1W;r0RnPmZ^z+%=0
zfz7N5AW;W_b`}M}b`}Mpb`}NU?JNo+><)}U+j$a1{&Us`&jUq%$UH{|2FB2NMhpy$
zVe^z37#PFn2{SM-M$BVoU|@`#Tf)G=7&SMQfq^l4ZYTo-W6WGv1_s91xuy&ZjB#^S
z85kJj=ZY~fFec1pXJBAVoKwNTz?d{AlYxOTc}^4q17pe@P*O^rW5d9}m^Md`fq^l7
zjywYcV@CZP0R{%f%sGq<42)T`3mF&~vu7tUFfiuK4rX9r%$@DRz`&R{8)QxXY>+ht
zvqc#g7z<~!GB7X}%_?PJU@V>ma#qPKkh4l>ft*z~3#7h$mKp;CW5q0xvnpq?F)%Pz
z%`9hNV62{*!N9;+Gc$sLfw6XGy$1sWW8F+k1_s9ZnVJj?j14m-85kHFXL2$yFgDGo
zVqjowo{`1Cz}PYa<d4=Fpls1L1LTkP8M+J%j2$!N7#J8kXMnOs*YtV@2FC8``3ww<
zJ=5bE7#Mq}gR)iMbbAH{#{TIB3=E7DrYkZqFixB<#K6EfX*x4V!{lkj3=E7@rX@2l
zFixEY^7pi9Ab(GvX2QV0IAfX$0|VpCX(9{^jI*YJ{5^YW83P03oT=#y42*N9hBGiQ
z&YSAaz`!_vss#fB<ASLmZ!DZD#lXP0Xeu`Y1LNW;)eH=bOQvKqFfcBi63xKCxNHh2
zhcBOE!%)w_xMB*(A1kMT{IO~ZKLZ2f>d7Eyt(gq+$J)sW3=E9xCWBJR`pKYFvSBhP
zm28|0N+p{ngPgT_GRRq5CV`x_brQ%~+a`g6cl#tz;jv?q6$1m~&Pmz~42-)b$uKZ5
z?w-WMz`(d?VhsaBJ>%YqxeN@9`zFRQFfi_)2nwzP6CD^B7!OV~WME)CG*O9xf${J}
zP+~kXk%fVQ@#q9ltRI^IiuL0YK(T&e0w~r`P5{OFsR^J|a(V(N*3V1;CC0P;pu~8t
zACwr+_k$wwLO;m&7yIo%k$$OPpMin#az7|FUg-xV#;g6H#CWZ*h=GCedLJlKZuEg7
z<z}BV0|Vo&K2W6G?gLqKr%#-Lf$?r1s2IK1Tgkw{c)u5vRvz?%0{LMt$eKsJptSP1
zSBHUt@kuYp_fLC4zJJzJ!@$7!yuJtI`xiYR-+$}@`TkQ6D6xF*0XgeSj{*Y&<JTTR
z1_s7&JxmM?jNiLKY2`<E3IhY<&u)<Ke|5VtFfjh^HfLa9{L`($z`*#o8<d3qb#pN=
zF#hkVW?*1Y=*nhbV36yIW?*2D>GEM<V36vvWnf^C=&ILeU|<mIQe<FY5a|NdCPH1H
z`b40!n1O+TuQQo}fq|zp7*xY_Ix{dZaC90oFfg!ng5sXH6BH>touCqey8~20aCLwp
zg|h?XERGIPq_B5@B89C3loeS!K%vFb!NI`5#L^B5E#~%2P(ovBk7QtAWNZf|7KV09
z1_p-z?V1b>4FB4t7#JA-wsSKuF#Kt&VPIhR-ImM1!0@Xrj)8&UXPZ9*1H+Ftdj<xE
z?`<G&d~1_uU|{&##?QdO@TCn@w|s6bWME+U)SAS=!0@pZ<c$xlE({C|?^{h77#QBQ
zsxs6wFuZLQWnf@<)5^-g!0@`Il!1ZaRZAKJ1H;RfFa`#O7cFiK3=Gd(%orFLp0%hk
zFfcrA5o2Irc+$egz`*dhxtxK4;Zbu20|Udu=12wxh6l~w3=9nSn?b>QuNma5yUhv=
z3=DUg1sNC^Za0JKyjx903=9l6o01tA>KSe{g)lHMTyJt^U|_h`1hVF8lR5(f!<8lp
z1_p-9O`Hr243`?K7#J8XHiBaDLSqc5rfu{E)wPXwpxU+(WX+jIP$Zsi1V!ShMix-5
z3-Zf}G*G=84yt%PKsB!=0|OI}76StllMDj`155k=e3AD5`J(Or^Tpc#=Zm-h&zETb
zpD)?|KVPc-f4+44|9qM4|MO*83zoB7V0Ku}azM^uJIe!ErUhHs<bU~3`ykKF$hn>8
zgZxv@dak{}3=B-%dtE>+i@l(T57-Nec>lei+~~I#lpB5bfXZN>J)lCudk?7W^4bF`
zyFB-R(yzxJbp{4T_dTG5;<g8rtz3755{k=iP}$|YJC=cg(P=lRmEyP?lzSa^gQ^ny
z-Jr~CSHBySdu?}va<9!UQ0}$f1<JivyFlsDau+C@SnL8>W4;TNP0V(IvWe*~P&P5y
z2`VCucjhoKFdFRyS!1{pWR1a2kTv={LDuN)1eK7wJ3%GA&JIw*)!tFSz`&@rBawlD
zQFBLq5Ca3F#tu*+p}qrDNT}@q6%wjDKsA=i4p0%Pyd6|TDs2b(UU569h*a1Ps(|FT
zgGz3>?I35#ZkJ$SV3gSo^1bvnP}wE54ODhXZUdEF65Bu(koY!Gp(3^oRB(%K1361%
z8$ZZJ!rMT}o^>lI*|Tp2C40`Tpk&Xz6_o6Gw}O&A|5i{c7ThY%z`!89m7RfsL3B$6
z0|SHj7Emgd+!DdSz#zTFlYxOjc8e7Q1B3h)Z3YGg#Vw%pqO^sVfq_AJa~%T%gUaT7
z1_lPz&7h{H+U7t|R#M;W#K6Fyu^CiIXl_<vU|`VN49Z;En?adHXA>y1=xzd8qqhl^
zS@bt~F)%O~Y_euxU@+XI!@$5`v`LnMfx&na9|Hq}$;NsH1_slO1q=)fW*ZY37#Peq
zg2Gs6BPfgoH-f@gU?V7u`8SGzs*;x*K}qb@22h~A-T(@;HyffD7#J)zfbyi}1{($j
z2CEIa3=9m`8{`-m7;H9xtg&4W@{QekkZ<hQgRF5_AH=}G;J6-C;yJB1VPIfzUa!i)
zz~HhTl=EHJgTl;h9mq58>p-6ISO@Y<z2`cRZ@kuleB-?i<Qt!LAm8||1C>aA>p)TC
zzZMiV0c$}~6Sx)>H9>1ZQ4_ot6g44hK~WRB78EsMYdIJg7{b?7GB7YitjS_vV2E4;
zD!-%FfXeUaHJ}0}W{n;L14HZ@P`MXZzXoJY{Ay63C9DSdCUJE<0|P_S>Hr1?hUC?b
z3=9k@s|^_#7*bb*ii)(=pb{y4H6sH9L&hqQvocqKe4n)n<ooPZAm8V#0{K3770CB_
zt3bZbUj_1g!AekyDO{P!z`#(n5){V8E9*hNFIfpnGNmiE7#JAJR!TE4FqE$ZmERRB
zK;?JkiW~+8hN=~y60CX!s06E70V=_2SAa^ex)mU2)vo}RU=1rkC0OHfP!ZO&Je7fg
zp?P^I0|P_La!@(hx*QZ*ZOcK<YF`dYVI9j^LH_Ps2GY>A3{-x1FAHa2VCY%q!N9=K
zy9`vV^eqEbEB(tr)yjlrTnr2h6PJRj$4N^;&YHY5mVtp`%2GcD28O9iLC%`C6coJE
zmx9vDjHRHoGII&YmRU<cNpkiQP-x9r0t&6UOPoRJf8G*MaLr!=a@T?-px|1#1QcA0
z7K4Io@nTSLEm;f-uBD4XNpjg@P?B7}7?f64ECyw;m5X^87#LP90)^J<MIdLbSp;&{
z+C?B|ty=_g*7`-D(AuyF6zdxofg*j=A_h=ZvUwpW7Pl+}C9bUtL5XYILQvw`z7P~#
zI~IZx*Up8Y#I<W7C~@sx07_hY7J!_!cL693?^^)M_xl%sLhHZ+P-q=o01B-`3qX;0
zcs|HkN9Kbn;iL0GmGH6opi21od{BdJ`qTgN(xA@VfBx<N<rNtPwkarp`g8{b1eUWn
zC^&3qS)jlqu#^qdBWh6i#XrqKhHX3B2Zdky+XW^leBht#P#`ePK!I&L+XjVS`Vf|Y
H!Y_URb^nH2
diff --git a/data_storage/UN/Education/SYB67_323_202411_Teaching Staff in education.db b/data_storage/UN/Education/SYB67_323_202411_Teaching Staff in education.db
index 5dad2fc5f996cc85137162892b124e05dbd51912..aa82fa2d50121eebb0eb2adf81d67a0aa81999b6 100644
GIT binary patch
delta 223
zcmZoTVAXKIYJ#-j6b1%{R}2gc%n;1XJ5k4&amvPo)%=XCn|TD@^2@)HV_;xl;b(vV
zCI$wEmkbOHY*3nYvxGu7Gb>1lX}jSCZZ5{@4i~t8lTJ)_*wDJjKwz2zBinYi34Fi!
z7dZ$tCA1|lwk0sNB`~)ou(Tzxwk5E&C9t<8aI__Gwk2@2C2+ST@U$iHE=%B3SmYou
N$$)J;TLa%OegL24NKXI&
delta 298
zcmZoTVAXKIYJ#+21Oo%ZD+UGzW(a0_I#I`%F=AuFYJSF7n|TD@^2@)JV_;xl;b(vV
zCI$uuRt5$JHYojSvxGu7Gb>1lX}e(nGZW)<hXCf!<PlF783-&25Fk%8ZaXJCJh;%5
z(3Zg1mcZ1Oz}%L=(w4y5mcZ7Qz}}X?(U!p3mcZ4Pz}=R>)0V)yEP+p9(gL>aY!mo?
J@h@@^006o(V$=Wt
diff --git a/data_storage/UN/Gender/SYB67_319_202411_Ratio of girls to boys in education.db b/data_storage/UN/Gender/SYB67_319_202411_Ratio of girls to boys in education.db
index dedea0417b55292f91c8992b5d30f4465f5b0de3..62b18ca2b71782155d9ab4ac03216174690e3d04 100644
GIT binary patch
delta 143
zcmZozVBWC6e1f##6b1%{y9^8rEDQ_`ObiUnyc2bd8K-PaSk2FPdoz!~TYkn{n}5j*
z3UJ<JU|;~@+nYrUqL~?QHWwJT7Z@|P7Z@|O7Z@|Q7Z|g&7Z|g)7Z|g(7Z|g*7Z`K2
v7Z`K47Z`K37Z`K57Z~$wFEHkv;InN3FPp%2wg%o`@{<DCwzF;E{Ur|ok4P(g
delta 143
zcmZozVBWC6e1f!K1Oo%ZT?PgQ76t|eCI$wkrxSII86!3(tmbFDwV6lYEkEPU&A;RY
z1vqarFff4dt<53^(aemun+uHF3yc}t3yhiC3yhiD3yfLX3yfLY3yj&?3yj&@3yeA1
v3yeA23yiti3yitj3ygWT7Z~$S@R=0Aww-MP?=Sgn4ZLgu+u1ho{*ng(x{fQ(
diff --git a/data_storage/UN/Health/SYB67_154_202411_Health Personnel.db b/data_storage/UN/Health/SYB67_154_202411_Health Personnel.db
index ffdfbcabbb0e282d6d42903dc4533dd16a9675ea..e2ebd6b85c0052ce91c5f06ae7d1534d498cdcfc 100644
GIT binary patch
delta 195
zcmZp85ZLe_aDuep6b1%HcLoLqW(EcZb_ND!-ibQKj8irytm0>4VBgFm@RncSRg-~%
zfklJ?0@xTB7+n|`7+4t?7}yvX7&ssXFuFm-**9w_yklVlt6|#A=<tMVk%7Ua2Da^N
z4kEwgn;P007~2|{+8UVK8d%yISlb%d+8Wr~8aUb-INKVy+8Vgq8hF|oc-tEI+8X%V
d8U)%J1lt;fmNf`(SmYo8Hpf8Z7ylv$1pxZ3FP;DZ
delta 202
zcmZp85ZLe_aDud81Oo%3I|Bm)GXnzyI|BpL(}_C9j1e0XR`D}2x^CtXc+0QvqRGI(
zz#_r`0c;S346F<c3?McK!~jM&h&ZF`W(|dRENmdd7??IQIy~W8WMHsaz~O`ZWB~_(
zriQi##<m8gwg%?529~x4*0u(=wg&dL29CA{&b9`wwg&FD2A;MC-nIt5wg&#T27$H)
j!L|mWWevg`CQV@5&gLNUi+`E|7w2Zqgzxf;1sntbYiKd8
diff --git a/data_storage/UN/Health/SYB67_325_202411_Expenditure on health.db b/data_storage/UN/Health/SYB67_325_202411_Expenditure on health.db
index b0623d80acf8e2c2971df9dcb0ccdae94fed0fab..662e11de1bcba4202179dad040ec8411c8e77d82 100644
GIT binary patch
delta 62
zcmZo@P-|#Vn;<PXg@J)#1_K;0^G?(;W}MQP(3-&5n!wbWz}%X^(we~9n!whYz}}j`
Ku{D8nK|KJ;W)L(0
delta 62
zcmZo@P-|#Vn;<P1!N9;Ug8>eho=(&;W{hY|XiZ>jO<-zGU~WxdX-!~lO<-$HU~f&}
K*qXq(pdJ9!j1ZFm
diff --git a/data_storage/UN/Internet/SYB67_314_202411_Internet Usage.db b/data_storage/UN/Internet/SYB67_314_202411_Internet Usage.db
index 6d4fd3d6e6f951dc1eb4ed759a94f75558a495ab..91f27d6ff01fc372ce590123a1381fbce12a639e 100644
GIT binary patch
delta 47
zcmZp8Al&dkc!IRx6b1$ce+C8y76t|eMg|6E-ibQKj8hsDS`!#s6PQ{Pn71adEO-w9
D5b6wG
delta 47
zcmZp8Al&dkc!IQG1Oo$uKLY~;3j+fKBLf4|(}_C9j1i3qtqF{+2~4dC%v%#!7Q6=l
D7Jm%A
diff --git a/data_storage/UN/Labour/SYB67_200_202411_Employment.db b/data_storage/UN/Labour/SYB67_200_202411_Employment.db
index a62a431708dcf8ecdc7454587d79cddae14b8316..6321e4b08359d963cd6134f7d56442bb12bff922 100644
GIT binary patch
delta 226
zcmZoz(8vhF6Ql*FFfcH&GB7Z(FfcGMGcYjoPSi1GoU$=tH9sTcW*&jJ{EV!df5{69
z@G>wkFflVQFo9^s%@PLR*%=v{1uWVHEEwAbESTB_ESTE`ELhqFELhtGEZEuwEZExx
zEI8T)EI8W*EV$YQEV$bREO^=lEO^@mEcn_5Ecn|6ECkvGECkyHEQHzxEQH$yEJWG`
zEJWJ{EX3LcEX3OdEF{_mEF{|nETq~6ETr27EM(dREM(gSEabKeSjd0azD0pWU^|P0
X!XN%g0c_jZ1Qh=3Z)g1=|C=8G_uVvI
delta 227
zcmZoz(8vhF6Ql(r7#NsX85kH?7#J9s85o$JPSi1GjM$j4nxBz%GmpSqeny7PzvKl4
zco`WOm_Q0ZH0x#wgYWE&jLiZT?E)5z?E)4|?E)6e?E)4o?E)68?E)5T?E)6;?E)4Y
z?E)5@?E)5D?E)6u?E)4&?E)6O?E)5j?E)73?E)48?E)5p?E)4;?E)6U?E)4e?E)5}
z?E)5J?E)6!?E)4O?E)5(?E)53?E)6k?E)4u?E)6E?E)5Z+XXD-KWv|NfQ@ZCn}fnH
W{%s%RSp>GT2q-WbY-LsW%?|*77&JWq
diff --git a/data_storage/UN/Labour/SYB67_329_202411_Labour Force and Unemployment.db b/data_storage/UN/Labour/SYB67_329_202411_Labour Force and Unemployment.db
index 28fe87461d33adddf9757e9d6afc4fc39d23bae3..7cb1132d5793b24df45b0bba39f091b86971e702 100644
GIT binary patch
delta 216
zcmZoT5YTWSV1l&Z6b1%HCk6%v76t|eCI$v(-ibQKj8irytmbF5-^?TMmY>ma^DlWp
z0Zu1~LPq<|A_nhSSV4N2rW<Zx{50KR1LI@TiOCKQu1yYY4vcLMOl=O#Z4NAL4y<hs
zY;6wgZ4Ml54xDWcTx|~AZ4Nwb4!ms+d~FW=Z4Lr$4uWkCLdzV47fcFZS;`_Ju$<+C
Ru)uZ}0g*ra%N_^|004QBMW+A&
delta 216
zcmZoT5YTWSV1l$@1Oo%369WSS3j+fK69WU&(}_C9j1e0XR`WADZsrkq%g^Yv`Io$)
z0H-|z10x7KZWb|k&%$aCQa{~r1LLRZ4jULBlTJ)_aByvMXmem}b6{$7U~Y3@X>(w0
zb6{(8U~hBaXmj9fbKq)o;BIr^X>;IhbKq-p;BRvfXmb#3a}ZkQAiQ9ifQY~(2bSe5
SAA|*#vpf(M*vcaEhaUjC)<yCF
diff --git a/data_storage/UN/Land/SYB67_145_202411_Land.db b/data_storage/UN/Land/SYB67_145_202411_Land.db
index 72782573fe79abc40bf536b632d103d63b0fd2c5..668c296034d6c3cfd2afca580b8bb7a12d01b34f 100644
GIT binary patch
delta 185
zcmZo@2ySQyo**qag@J+5hk=2CnSp_Um4ShoccP9l<CKjFtN581*f;YCyy4ei^igAA
zU|<nqfB+T-1_lm@Y6eaQ1_m}LpMA4}0yirwNQ!AQqr(NRMFs|w3|P0bZV>s+znIZM
zp=m<f1je=rOl=dG+a|EIO<--Cz}7Z_y=?+V+XT+G30!RxxZ5W1v`ye`o50sLfxm5n
ZK-&btwh2OQ6NI--5Mfc+%u?`&9{}9BEVlpv
delta 188
zcmZo@2ySQyo**q4!N9=i!@$76%)r3F%D}+%bfS(iW5mXURs2khKAU+2-tcQMaHugb
zFt7+QKmZE^0|PrmH3KID0|Og`&*-yRL4li<6(q&9nbF|_*CGRh#R3ijlMGn4vuqIg
z!@tNuplL$e1je=rOl=dG+a|EIO<--Cz}7Z_y=?+V+XT+G30!RxxZ5W1v`ye`o50sL
dfxm5nK-&btwh2OQ6NI--5Mfc+%#!ej9{{U!E;;}J
diff --git a/graphs/graphs_display.html b/graphs/graphs_display.html
index 534b003b085422104ea35cd598b56daa0b7fc06f..c62d6f5d527c3ae368d0046d45acd4e0f363832a 100644
GIT binary patch
delta 74770
zcmaF6uTgQ$_j9%zW;1P`$uysFGB306=027-rpa+EveO^Tb7h%q!@@oJ0-HLoUO`TN
zNlvA1dQoCQ#^ePo;*$?Bv2qk=R;5}g7@AGK$fmS;GP@+x<PDr=lV5SFuw>-trcM^%
z5}Vw|tp?$2<5rk_i(85fB%{PN`46}J<n3JItRDHfsa%uoc;wh@^m8)pxTbG3>=m0V
z%^fkBpKHZrX&%|lm$`hICST_fm~6r;Ee6)DP?VpOYO7R|m{gFMmztx*HC^7QSB@Jb
zr(2Skq-4i6S&>76tth`7!jxjm(alZKHJj|nEize;gL{5l?JZ`l=^F&xIGf+|w!i0P
zY=6(o)c&5Ax&1vaOZ$6X*7o<jZ0+xP+1uaqa<sqa<!pb?%hmp#m%IHvFHie>UXUKX
z_V>K}?eBR7+TZgEw!h~UYJblw-2R?dr2RdwX#0C!vG(`8;_dHwCEDNfO18h}m1=*_
zE8YH{SEl_vuWb8!Ub*)7yz=euc@^5<^D4H#=T&Nd&#T=2o>!&)J+Er}dtSBn_q^)u
z?|C)a-}7p=zvtCzf6uGk{+?H-{XMU4`+Hu!_V>K{?eBRF+TZgUw!h~!YJbmb-2R@|
zr2RdwY5RL#v-bDA=I!r!E!yAnTDHIEwQ7IQYu)~y*QWhFuWkE#Uc2`9y!P$yc^%r{
z^E$S_=XGj-&+FX&p4VmjdtO(s2`b5kDV7Fl7M8ju21aJOCWZ!Px`~O&Cc1`Z$rfpb
z#z{$r=El<%7k2+5O6B~G)21*x5~XzdgZZvXib;t@N><fMC7C5TsbEHGMTwG?l4DtV
zSYl3Ts#5LrhZkMNre8X8>F)HYAG-zkV@eGSjFXeVRH|zAbk_y0Y6gzQ#fhakB??7}
zC8-JpsYMEg1_n9?1_lZR`30ppi6xo&c?yYTsYQwDsa6WA)m8H^&Y8ljJAKt!SMBLS
zYg`p19Mg(2lM|J6l>G9GN-|Q5@)RH<(|cCCN=Q5Arh=r4QRE?F(^oHZRaSB=&ID<8
zPR%PRO3YD!a$OUPOTb1IXC_Y9S?#J}5uS<=QPNRzEiK9~NCh#VD&YcfXFx=z2d;J%
z6@%%9h$-nP`6s6)=1rf!&{fgEH#H|QFBRep-^}Eqd>AJnKc^DLc1%mpNX*MDE=kOr
z&a==}bGpMq*P!Wpe|3vZKfTcP>-6)BTwSNTE_N-R{(7;i<n$>UT#cvi+uqGR-FS(s
z!t~-LuAb8uZFIHU&a>3DjB$F)&Tir9`!~C0PxmwJVV|D2+|_`kA~QLE`tIefpQeXx
z>gJ#RcZF-j^k4tGxu$2YbamhcMOvz5X<lZ2-qf5PCAOgQ#JrTm?N3*_dNWSHwz*qm
zdi82oG3J!Syy**9yQVPbr6*3;U*oC*)|i%Dl$}|bI^BPbtJ(A^Yh073=P~v0O@Fn<
zRerk4T33(hJ!@U1f^?L8d|aGCG3Ddp46-lLTuDbM*wZCgDON`*FEKY2l)4Bf7bP8~
z5^z$Co-Vk?RdF<d43h*>k3WHwWfo^9fl8vZ#GK+(9i=KIt7s*^{5()5r3zI~Rnt%n
zGu1QKu{6;$GcpC0V<0yh8Jg*t86$&wm=sj2sh+8hvAMaPnU0yBp%F~d$kJ5L!~h8x
z>zEkpS(xe==^2~oSQuOCnIQumV<Qti6J!w+9RocR9aBRiJtG}MLp?(a9aD2-Ju^$o
zdP_LaF)}sRGk|j~EiKJ;Ow9BQ!0xdy(y=tuGcz~UF*ndNH8HX<H8+HkIz~o%W;*5;
zmU@<^I>rV@dY0yJ4;vaA>6x4Am>B9=fG9m9Qynu)Lp?+Y)EgU{z<g<Fsb`98y`_bY
zp}B#cA>1@*7+IR=nIn779A<!}fu5xavI#ndh6Z{j2-}Q}jdYBRjrELSIt<;+48Wmb
zpl6_CWT*!>3Tl<1v7V`ssg9wc1<2{<kjOMN0>!Mck)8?2PsSjb=>dOSMe5DX!QO=G
zHPf>+M|KP-bWDx(3}JRdl^L2@>X{fJIom?V#K>6Bz!1rc=pkULXKsX)8Vn3|j7$yn
z>MfCj&qBx0)D&Txkr^m@pmv%Vn(Dz57gWs5P|py>xn?@XdWJfNMkacuI)<hedS;-M
zW2OTRDFZ!Y9YbSNP@q}pS?Cy<=ouLs*CPeAiH-#*;-O|kDI)`O<ir6=j>gD7*D*9O
z)iW?M)v++rGe&WXj*+pRnURj6Ia<0l*8#c9*c5D6J)}f1HPbUULk=BN9V1gcQ&Sxi
zJrj%wvCuO$(=jwL)-y+Pys?pviLsHM0W7AB3@r34k>kTm$3o9g2PAB4WD2*c-oQx5
z&`8f1A!1-)0FQ1%Gd*)13vhBaw$w916bjJ50m;MT+0fWP&lsV^#KKe$*?w~!b7PRh
zLD?MUNJHa#13eQXkT;EW%=Az~z`y`hs+fS>49fJ#L2IsKXl|%y0Z$F4pdd!JOUKB_
zTo2(eP|RECSsIz@m>PhKHX}1VXsE)<5_26x6FpPp@H9qbI74$iBczmV1~=IVRIccl
z80lH+7=qHBrJjY3xuu@D38)OU)G@TwGe*iJmX@GYX8}rfaEt1VjX<f+3>G3rW_re^
zpp;__N}#4Fy5Sk!*w`E#Y8Ivjh|B_w5))8ytz!u)Xbto%;r4(TraBlx^`<&T=AbO0
zXJV=YD)`KiQv%#s#ztm(Mj%tc=D-LOP>BvMUqPAH2%P+k4Glp?L0w~LY@ugns$*%a
zXMmjf4Z(#ps1U6O*Nf($bY^610rI=Ck)8#p_%heCgr`yv!$`*roQ)0j43VSS3?3>_
zD^1MxEMTE&XkiMAXh{08&@lvOJ4mim^2@IWRdFU}s0FUEj=7!%ayWp}qB%;u85<kx
zSQwk>Ss>?m9Z<1jWM%@69H?^)P4p~~(~g<BjtR({P-$aBkf)#=q}VjIFhV3?s5FF%
z)tSEWjH|F#txmO4a(+&J5mmZB#-4d4sd=DIPGXKiMt*K)a%M^@xGz+U(is}<0Vxgt
z9#AO$1}?M*L|lp)?F0?aUNW(rppv3eXdlQFqaZXi0yS|=^(;V@uOX<#re~@Hu1XB`
z%yf*v%~)el6VL!e7@;(g>J1DGjC73kOhN5gPzMBDzk`}M;QGf<&%jj2P|v^|)ZefK
zGfj0MEjfrD2x+EgXl|-wtY>5nQUYp&Sb!@@lv>ch5L9G?s%cooXAEgL>R6&S>dnk`
zO!dr6bc|3MK4xZSpaza1s1ie9kbR(Lqk*2ej**@bv|j@0qZotgWD^Te{|BY2GXp6#
z1GU!-jp{*Wni+xY0@d5_CY!mQ0jS$zsAq}VnljQcL35S4j-j5Zg^r;yYPSnyiHRP(
zrv!G9DacMs9RocxcxxTnaMCf<vj9aIS`}xmXNY3GAt*L=OdvHoG^RjZE(1_ih=^hX
zJy7VIAhl0H0cN6OY^Y~|VxEysy)meXZ=h$2Vl$%V2X(<r^$Z~`2@_EB%m`#Qs1XQC
zO(1jO*btQdjLmcmEijX)nI1^9g#}X78ylPInAIDCTm6P6dS>8i-_RHo^PrZ!k)AQ!
zWH7@R97u*}Z9z**9YZrcV-)9`gQ6T1Oy*#>qI91P3_)!dcqo9<KO_ej=@{xEH?F`L
z!_Y_%)UF11pv*zJ%ovi=4G@hZBT#<`+~fjvIKiP~pkrdGX8=kUMmh$d2DY)DF{;mv
zL5V=eNYA`p2ci;^hRt*g^+4&vLdVoZ<H)WND@Y>K5o2>Y1Uos0?+?Fj`b5;0}bT
z9!6d<(lfUJhb4?Kst36e)Pe*zAWifvK)D#yW6(1P^#M`s0%b`vNDB}~n(LV9nSwJR
zN(>;HlUSqC9PTwp`nLd$X29G8p+O;JX{KWgYG)dPTh=Ij2XGl-0ZMAnqzLkdsg8x7
zF=|%VF$P5hxDRNkXQE>QPRd4lCa@j>#C}V29Ya%4Ti-~}6ji?&ECNBv2F+}99YX^>
zb5Oc9feauR>Y2e47T6bt;Al3~GcwaLg%pk^dIm77!9iGW3F=y#8=2}@V)Py%rkm-3
zN?Zd_lN;m)a8YciXM~cdLCMS*wX87#jr*9JgDL_8)U*c*Yfy}VOTc;)Q0WgzeFi$l
zrf5YdsQYY)GB#ii8uPK#0S}58S?Hk}ZKMOLg+NVl@X!b--XN`Q9YgSliJ^g>1t<}L
z-3!WZpz;@#LqMglDN1591UbeG#ZRE(1r(y7g4q}}CV@I+Woc;%>#$gW`i_v2#X!&8
z93{jpLH-AoXW$aI9@PWJpcH~qMuCbgGgDB}X^x^4lsmw69%ziuSkDliqQTK>4(ha8
z=zzw7OhKu{0wrA-f{J>GX`E2YOmya7+&YC>xE^_g3?ipv2Fe4bpww%M)`d6ILF-bR
zf$Do>P^o9EV{D;kiIUqvUO^cV1NFW@BO|6dX0SmQJ+SjFEiFNb&J0YTh8`%7fkrSu
zB_nP6Q1;%LDS3$n1(|v23W+5OB^jv-dEj}Y#2kg3)UwnZ9dL(gv_GYzG_q!t5{c?h
zk)C=+`&J{nZ#5Jrm<-SxeW3OdVnh{G1uH=Z#i2DYcs2$!G-jx00&m}AX`LB>dVAp3
z3yc8OxdxE#38*~-s$I~A^*|MxfsO&Fonr~^mKf=on(5So8ug$qr~zm`3)GcFsm?)-
z07H~IAJh;BxzGSS+XQtt$Sa0=rXX9v4NbJsW%%f|5oo*=G{FV0uOMwZSepQ99B9BB
zKJW}O+d$6{QqLktP@4~>=0ptT8-S*Kphg*BOr(HDuMyz~>02OA1el_Yjf2`~#-K{v
z03{qi0gla4M#wWJmY{KPxJwL-Ak74*0GO&*0?*i(AcrPcLJ8E5L$T2S6oZD~t}-mV
z4D>+lEU0==KtY*M%23Y)wWSQ|bQvMS5Yo2?waQV%j6tyuYQusiB|)Ydp!MC%K<2=^
z;l_HPAOf{Fpw>buBT&B-$~Fae$qXP3Og(Tig!JR4b9VP|gF2Wx29WfFWR4-I*JcD7
zR0nnCKpkdK2Oc!aVTzJEz+)e<i~yoR^9&$6;4?%}SAZra!NCpXLn)(rJ=BzB0G|&r
z&@)Hvp~HP`gf?bx015=uo;zrE$pCF6!psal(E#e}KwMA{c9fAGC|E&5G@y9~h>Q+s
zZpQ$<lV||XP>>ihgLe+GS%*684w^58nhnavMtTNjI`sy62B36>+Is^z)mYC25>KFD
z1!0gcLA_saUdL2#sAmk18bk2>6L``Kq!W%oMxd4{^`Jrp>L?RXh=clwurv-8Hv$!T
zXkw7G2~Mq`f(>pnR0~8J6sYi6vqa1-gJ#MM^~^!tT4`fY&kf!)folg%&dgu9+K*Yd
z-Uu|vW}s()+JgpX1Y{qZqK>A);|V-V3z~<Anhm84(NhP=u^1`NLeID!ZO{z8O99en
z0O}vZ!@vM-C4(`j@<9!Dq)<1|gZmylPK9tEB*+E9Yq>xZND!G=n#|1j2c#Ayr{<L;
zrl%_8rzzwn=A<el=A|g4rGlB6*ye4@GLuU(bBlEp+#rfZXKhBntPOz?dFZSS<*5nL
z>re{GFG<YNQAo_mQAp08F2BZAcyy85$X(=Sq-PACj4^{ZWWi%HptcF9;baPGfr8dC
zffjUu$NWJ}Y$Nb6I-~#vP1xvwDg;A4%X-u%BdA6K8Db1xi~}l}4fM=F&0X*W52)P<
z8Zv|$1EmbXD^@@aCIiqAsR5{+4XOU%Z6FZW1k{)U4NvPBAT1VP2fN)8Ho9d18p?t+
z?+x`#K%=7OAnP$3yHLB0^+3aQhNv|kXd(b(nARM<{)AL6N}#C#cm-DvUb+TaWnzHZ
zDg_NnT7tS57T_T-&?q2k>sH4?58V3z)pQ{JkkLDYAv#7l+j*eXM4*vS13d%yl0V4U
zB-E3j5QPL2j5Gr^InbH|puj>|{Q+7{0W|@X6rfCyO`wHHpeZzvhd|R8kfywWo_W0q
zXyg&x3<M2~gIYJH;Dt*_EjJ@QQ+SgPYNnAMT5y4y1kiDJL=b>jpy@Gq=h6_pnP3WP
zjDlKt@OCOBDL}0OPetj$<;?YrpsS0Z!2*j>sB$yNh&uY}9C-WMLeCuDE(9?QbqwqE
zj3F&V(9{dckSubu7c}c&017)q>&rmT0u(1E;K5uo5EDGeik1pMsR%Rxi#A0A4^G2+
zJ<vKa#9||3v;{N9Ad@ZN?JTHAL2DDC^B|yUR;VZ{1zP3;%F2j_Kd9>kTc-)0eKaxB
zfh~E3OoKp80A*fKc><cfKuL4vph-<sFM>i3eFz!uTmwA|)V>aAZVH|nKx@2^(?7Vx
zL4+{eF&3y957c)6O-_TF)KE203Z>N!T3iWE_OPA-Vu}@#dO#x=pxFl0>2L5PpMjnU
zsxQHb1T^Rm>cAL+CP?)RbW9P=Sf~Rap=bu`UW3vX6vO)ipm4PWPkTc8i^%yOY62u<
znjppzKqDofln0(Z2Xzsk3M~<<m<+&k^@iYiNdxpOVhLZy1)3m%C<V>AK-~r%kw9`H
z>a>L=Xd+Axo?bySygFv6YtBHW4rr1Rl+d81IlLM$0aZ;#sOu@geFNB-4Sbm>sEz>D
zMJQ8CAlr@fj4eQu8lb`ifkCwyf(K@SW{*H21)6??_b;HK1*JeUvqqpL4^Y0b9<xa-
zO*$98lr#r@!CjHjEiuD?L0CRf6Bv}HB}B(!bid4S+E7KHV~TCRj3v0P04=Z90o5Qz
z#(G9NMi$_%f(2;M3AB5}2-F+|^*BtCib~L0e3b5osg6m#9%!D}0<@yQ610#Bv}gg+
z?SM}1>luTVYe1HO!5an8vKO>20M0Z+Y0rZeHGvwGpanB1?GH1=DiY8VA9&>fF8_@{
z%YH0Dt0q8}f`#A&Xx%Z2NuV`apf&a2Ay*wEJxdeN5_WKt4z;xb8kdAR)5s9KRs=G7
zZlq^|vd6*LSjW@?u}i?vNY4OiTZ|ESdk)4*8FR3K;8qIM4ij@dBV-4FR^)@W>3~=3
zgQ|ZEqzQxRDQ{ebA%OsE37hE|gE}5Yrl9pFDEoIT;q5Ln@PrK1LQo?N)VF{K6@;N<
zYOZI7(%6RCU}&y~Fv?KRxZViVL9zfZh(NaxGPMHgfPlsxK@0CeGYH1UdT1*rj6fr$
zkcESWh9-K@wh4rSH%%-->%gF{hEkv|Z9Qlt+Yr5pVFFr|0@rGx2a0b<Hy17lYD7cL
zF$51o8X6<kaG4ro+GY%H-57zosYq$59^Sw*G%!S6<_5CV9JGoIl$ns)bRec7Xuk}&
za}0HZ5hz#<L7M?Un`l5wyFmSWl#N?vpdButHS~yGP$qiyrl{Q(kS>h1Cr~?#(MNzm
zIo%R<H4MDB1=nK++MfVgAB3<LDhHzKQ<Xs5)4)RvCWw}zv7QmMj{(gFu=HbW0v=lj
zwS__05Zt6hUn*&4tOMFg0!fQdQpX5kI%tgwq!ka_v}Oug`2{ay3_(*2AlIcT=|D>)
z3vgb8ia{wOJyX<nKB)Z&?OVXjf~hqGkHSECpgmv^cR}(WXy=+Ccv8s_vc1hv&kSWj
z7I>8*Xx|Yi`GAHXkaIbxTm$vhEI<>n;Du5~;3+IaOHjcCwGv8MKz81lK!Q=p53<n%
z6qF|Bs0&WbK?})1J$guQ1F9cNf#=IW^#C*&Ar!of08RB6g4YRyhj^fxOu=IwP>!J<
zcz_?;g8*e#&~jeTxPc*Pt{0{Xb0sOL|6~A~3xO&zLd`Xxz_3IPYtVu{Q&UjS%N(?C
zQ4cgA1uio|YedcJk@6zabQdVgTk3(wuRu;iV9=5|&=3dujvdf6o*ByYlcA1<IqEuO
z@S;Gpkq>*&3S3aSG0?Fv1y4djy@g5{f_x2HB8AuwX=JEpOq<?^Ye+_FS_#o>rA9a6
zkE~@==|uH9$W23|y^YbuQ_!6$s6`-!JlIerg~njjZfF8(c^MjmW*4w3fbD36N}5@M
z>J~#Y&_F$`VFQ(dQpTW`xCv<gEO?tcXiW)dUB9UbWO0hAg*l}9gjP)OR;dwacQ2%6
z0U=?=Th^Oe=o#yngBp(}MtZ0lCv=QVO!Ytm`%v4>jV)0|!QlgV#)f8~AvsfHOYn{W
zb3Jn%GYiy3+i<lOhI;1kH3hJS2FwBrLy$R89%yeYX#cyhnGxzLG*ca8Qxn86sR?Kk
z1KfOLOVH5<P$Qs}C8!T&YKGFzFfal6+pHekCa|;sw@N@8Tahb%P|b|g`ZO~KZCHYu
zNjzn21ZqcNRc~rhZ;W(Q0jRwPRcB!W>VZHxP|DB@v`F6&w8`4kT+c|y)W{g6B?0d<
zfb0XEK>*sSZ2{U~YiS5N^})yt^@s=1BmtWJAQu>#g3=V!PE^Xm$QX4CKP(*?fflKm
z7=ec7bqq~RLE9CKEx-#-KspfH%uS69!Bc|9pl!E0Mh2$!ptBLoKx@d60^VH5!~)bl
zGcpG4=YcxG)WA&7LdVR~R1djd4^QHtmM&DKp)oi)LV0FppiRxt9D%$_4lG}<q+@Pw
zin7}UZX_tYL0cBU3gN3qjEqe{vx|mC;QeV>%mp2{0P0j5fl`<$$bV1+urx{07Ei(y
z8W|zw14BsL9kgiz-hBYsZf2@uYKGo8hniqw3|i6#<5-%2W>k&L%=9dgN5ai?Ow8-`
z5SwH`t#wl!6AL4xiB-rFeG5zQvNux;Xm{GcK+h5>zCb(XOh8>vV^dSa>Lg<$$lh=>
zP_GnH>_A9Zq5(M%)X}pvv(Piqu`oo6LXZ@$6Iejo_M!5Ipa!{-i8&}jU_$1gIV#W&
zc+iOiX5cM3Feyv4?c{l>O7%L%=E$QTpuGxa5MP=ZgL(&`=r#hUM~ptK8EPPaQZ4E#
zLvtN7Q`BP;;Asoyq<V9td=A=EZw}f6Vgiq7m^uSc$*yB!YzA79XlQ7J+$X@Cvx4d(
zf>MF1u>cKyq1y_PqfKwZ3%nXdAvm?7G%-gZEHghRH7_}p=-$QX8mSSmMk<H6E(K^=
z6S)a#v|lmWuNZ3m3KP&U9-`r4U<g`b4XIk8qzQZp2Izzu<eD0>&Kgp<>sT1;nS=Hb
zqZ~eC0$R2MAGR|z0JZKwZ8Y$HMo^Ey!U%E<0O|$}c<p9pSPxzUZHB&Z0Cct&>h@O9
z*)m8&|0aguc?3hy!fq4LkROuc!Dq368Yu`2+UgD(atEE4g%Gv0v_uS`L;Y!~2O8nC
z)UyO__=Hz<;60C6N7z8^W+b~2b3~v<H)x9}N`M&~=@^3tYN56n)|(jXnSpjWn}Sxi
zfUJhfKq)iOyqF=Rdj)Q2Als#5XlRPk(=s;EF@wy0nW1fDFb6G_0S}oXB?u!ObI=A)
zWFz5?7h?lG19)c%>KG_xY6c$7Ha9|BsDj*H1CPs_o9UPu=~<x6<bdYu;Fg%^)gzV{
z8G>7lNU;M?SWtUSz|B*nR*VTKy+I{GeHqZ1N6?fFp+KiQfF=OJZEz%$Ep<SB1VcRw
zv{^J`G%tV-NrR^W@ZnUT{idMKrYTw**%CAvX=tGXnm#c_TSjF98VU!^_d%Ts+L#Y<
zALPIZaAyiMx(t;EP4$5$QqWyvWRBWwGy@w9n)fs{(=$MsNCB-GLxij)Xm_%aDY!=k
zIv@=(3JmL47(-GR)B(m8pw=UlV+iU(gXYCRyQx8W8Y*rH&bgqKS_ZJ)y6_MNH*w+7
zXKb!#jFtwVW*8dOTcFMgfe-qFcTho_v~*0tv&LrTp!s0XF$A!n1Jj@r3XoDXa=*<S
zG;55AJ<uTzpm7RN$QpoW4MFK1F@SFlI-d)?=Nz8wO$^XhQJR2ec@5#o7gS0Zf>$4z
zBGw6l@+9bh3QJJY1obDBGBgF93j*apD9{o_&`dK38-wx&Jk$(9iQC8$bhrkR2aQ47
zw^903X5d54K+7ME!K;fbk?b%sLhpKj(jI7cy8$#{>XkqTaDh(f1C8$(8zW8dg2ESc
z$^$6CK<Nn-W*CcrA->Qt1s^&B<$%&JC~V;v?kA`MC}jegzy+<P0*ycDq3^dhGBD9I
zf~P3(_A&!dVF=X>rHsuGArBQorNGDBp$Z}MxM2NtXzykF+f%OU(!RwR`Q>Rv;4@*N
z+c7~R$@z)JB{`XSsl`fGVBuOFrQF1#^vpca0mV5=Rt7psMPRZ-$;#9~M=43k%Ai(f
zdcreTNq^!FR#Hf+RB+BO%_}LYRI1fcDlJG!EJ@8x%_}WdvWl)&N=z=vEK60gGSr#g
zpwX*3z3qFC`1HQ}J?zu_@At6Q$AXRzgPxeI<Oo^Ar9jLP$jG+F>L}$TCZ*;OeH?CX
zYDq?ZijtMmblC?z)*zR#fe0MVAtM}+Ttu91B^{;Q)RO7q4|=qwe|^v+i^n;n@6Sew
zA|$5~GD!&Ypn&Ou4|)uyvpwt)n?C=3k6=A|)KRkb3c5)MN6cb1S(l{!M-az1-|tbv
zp6;+(L8J}fMTkT@U61&!Qy_!k4i^HY3jyq|CwBr0SL(oRo*cFlBoMQrsICR)EG`^Q
zrlf<5)7{t%)gX5K1>|@U#@P9W5(+GG(-%DI5uKjL=QeBdd=An1I<>c$1*h}yyYWue
z<>145LVx>Qqu%zpMt$vbjr!Z?8ck@QYc#QauF<6Sxki)Q=Ne6EpKCO=eXh~8_PIvW
z+vgh1XrF5|vwg17toFG^v)kty&1s)&G`D@O(Y*G#M)TX}8ZBs_YqYR^uF<0QxkiiI
z=Nc_(pKG+VeXh~6_PIvO+vggsXrF7evVE@6s`j}?tJ~)qt!bZYw6=Y&(Yp4zM(f+>
z8f|EwYqYU_uF<CUxkj7Y=NfHkpKG+WeXh~A_PIve+vghXXrF7evwg17uJ*Y`yW8g)
z?P;HDw6}e((Z2S%M*G|68Xah#Yjm)EuF;|PxkiWE=NcVppKElqeXh~5_PIvK+vggc
zXrF6zvVE@6srI=>r`zWmooSzIbhdr2(Yf}yM(5k-8eM3gYjkn@T%${I6I9F$(hO59
zEG=~tO-xO7O_I|rb(7MJOmr>GQ!UL*Qw&Uuj0_>C^An>IdOANbO2Mb|PglF(%GZAB
z$ffp6M=rNtI&!7`(vhp}myTR(zjWk!`=ui{+Akfs*?#HBt@cYtZns}La;N>$k-P1e
zj@)a%bmV^fr6Uj8FCBT<e(A`g_De?|w_iH)r2W#7r|p-HJZryn<azt0BQM%79eLS)
z>By`0OGjR}Upn%p{nC-Q?U#<cYrk~lefy;&AKEV+`PhEx$fx#8M?SY-I`XCc(vh$2
zmyUdEzjWk#`=uj4+AkgX*?#HBul7qvez#vb@~8dMk-zPij{IxCbmV{cr6Y{}myR%k
z2qqB03?f)S1S^PO0}<>Xf&)Zwf(R}U!3`pKKm;#{-~$o-AVL5{2!aS95FrdAL_mZn
zh!6u2;vhl-L`Z@NDG(tIB4j{>EQpW;5%M5H0YoT*2qh4q3?fuOger(o0}<*VLIXr-
zf(R`Tp$#H*K!h%c&;t?rAi@Ad7=j2R5Mc}=OhAMwh%f^Y<{-iXL|B3dD-dA~B5Xi}
zEr_rK5%wU$0Yo^02qzHX3?f`Wge!<}0}<{Z!UIHjf(S1V;SC~uK!h)d@B<P4AR+)n
z1cHbl5D^R_LO?_)hzJ7_;UFRcL_~s!C=d}1B4R*9EQp8$5%C}*0YoH%h$Ik^3?foM
zL@J0#0}<&UA_GKZf`}{-kqshpKtwKx$O94iAff<76oQB%5K#;wN<c&@h$sUQ<shO0
zL{x%^DiBc(B5FWHEr_TC5%nOV0Yo%{h$axx3?f=UL@S7B0}<^Yq60*9f`~2<(G4Pc
zKtwNy=mQb`AYuZDm<S>!fr!Z<VhV_u3L>U~i0L3=28fsmB4&Yz*&t#Lh?ol^=7EU$
zAYuWCSO_8(fr!N*VhM;?3L=()h~*$+1&CM)B36Nj)gWRGh*%3E)`5uiAYucE*a#vv
zfr!l@Vhf1a3L>_Fi0vR^2Z-1SB6fj@-5_EQh}a7v_JN4~AmRXsI0zyRfr!H(0-UFh
zf>_5u#BmUD0z{ky5vM@JX%KM+M4SZ?=Rm}H5OD!STm%u9K*VJbaRo$N1rgUk#B~sH
z14P^e5w}3ZZ4hw>MBD`t_dvvb5b*#+JOmMsK*VDZ@dQLX1rg6c#B&hw0z|w75wAeR
zYY_1UM7#wN??A+R5b*&-d;}4nK*VPd@dZSD1rgss#CH(!14R4;5x+phZxHbZMEnI2
z|3Jil#_mf;m_WrJh+qN{%pigVM6iMgHW0xMA~-+<Cy3wz5!@hx2So6K2tE+O4<ZCW
zgdm6z0ujO>LIgyJf(S7XAr2xWK!hZSkOC3XAVLO2$btwt5FrmD6hMR`h)@C%${<1o
zM5uxYH4vc=A~ZmRCWz1i5!xU^2Sn(C2t5#?4<ZaegdvD90uja_!URN^f(SDZVGbfJ
zK!hcTumTa*Ai@Sj*n$W<5Md7@96*F4h;RZC&LF}CM7V+oHxS_tB0NBZCy4L@5#Aue
z2SoUS2tN?v4<Z6UL?DO=0ujL=A_PQ)f`~8>5e_0EKtv>nhyoGOAR-1t#Da)85D^a|
z5<o;Eh)4nv$si&HM5Ka<G!T&vA~HZkCWy!a5!oOj2Snt8h&&LH4<ZUcL?MVM0ujX^
zq69>gf`~E@Q4S(1Ktv^or~(nyAfg6D)PjgQ5K#{z8bCxNh-d;4%^;!$M6`m4HW1Mc
zB04}sCy3|*5#1o72SoIOh&~X}4<aUjh>0L#5{Q@#BBp?dsUTt+h?ou{W`Ky9AYvAX
zm<=N4fQY#uVjhT?4<Z(Th=m|x5r|j}B9?%Nr66J%h*%CHR)C0=AYv7WSPdf9fQYpq
zVjYNB4<a^zh>aj(6NuOhBDR2ttsr6>h}aGyc7TYTAYvDY*bO4~fQY>yVjqau4<ZhL
zh=U;F5QsPoBEWh2D2R0oL>vbZCqTqW5OE4boCXnRK*U)PaSlYB2N4%Q#6=Ks2}E25
z5m!LORS<CvL|g|EH$cQq5OE7c+y)VMK*U`TaSue?2N4fI#6uAA2t+&v5l=wGQxNeC
zL_7x(FF?dg5b+8`yao|(K*U=R@eV}12N54Y#77YE2}FDb5nn*WR}k?HM0^JkKS0D!
z5b+B{{00$!K*V1V@ef4&XX?Imgc(%)fe0oL!3-i;Km;p@U;`2CAc6x#aDoUf5Wx*1
zct8X%h~NVe{2)RAL<oWiArK)9B1AxhD2NaP5#k_10z^oH2q_RD4I*Sfge-`V0}=8d
zLIFf5f(RuLp$sBaK!hrYPy-R_AVLE~Xo3hW5TOksbU=hIh|mKO`XIspL>PhyBM@N>
zB1}MpDTpuw5#}Jm0z_DX2rCd_4I*qnge{1$0}=Kh!U04$f(R!N;S3^NK!huZa03zU
zAi@Jgc!CHo5aA6Xd_aUR^ZrXm{Fo=%A^L&ywQ6rM^YhrGWR@u;=Oh*v+bT`Iz$!ZV
zG%x@BT4sOd4&BK7QibHiJcY!R6otgRO3-oksR{+4^HWk%i<65o3qZ%*D`cb=r7C2m
z&3{mHi&=F3-<n&@BJ+2$_%rh}a?Rh!;?FET{ib2Bo{*ms`W151rHp!2Cb#oS@Y-Y;
z+c_6y=BC={XBbaEDBvbFy-vVQZ+=7VEoKhzopF=j^QwTkto{3HZ!!1ptGx{(?tqB9
zAmSc~xDO&8fQW}6;t_~=3?iO@h^HXp8HjieB3^)qmmuO5h<FVm-hha=AmSZ}cn=~z
zfQXME;uDDY3?jaOh_4{x8;JN0B7T5~pCIBFi1-a6{(y+TAmSg0_|M$Eua>2MUo9hu
zU;+`$Ac6%%u!0CS5Wx;2I6wp^h~NSd+#rGnMDT(LJ`lkVA_PE$AcznG5yBus1Vo5}
z2r&>L4k9E#gd~WN0uj<6LIy<0f(SX5{rhU=SyU&eSSFjB8ycCK>KY}bSm>IVm>K9M
zStO?Fnj0ILnwc6To29~fxx}c1_Hv0)3hw2O-a%IYT3iLYtqy*>+~^&2qj%7O?j{_)
zq>##&6q2#07I`uYHkXAqi%q-|TCQ>j-BdPu2OVey>gXMGmf+>W#-QaDXlWI+D0=h`
zI#Bpnj^05BOB<ti&>4ajvya|E2RiEwTAPjDK{t8_U2@{+E!;!v7VgnI=%Dw!!~4>s
zH?^bR)J|+CX!H)c(L3ls=gx!n@r~X=2ktV!2+%U+(L3ls3z(r;XY>v__-bs>o*nS{
z`JhvkM(>~lr4Y~^Y@pB>y@O82RB!YSI`Ag;(L3mh!Q;tAB^jwjc?yoXsYRK|iPKjv
zb5&MyEY3_+(ou3w%_}KN%u#@HVe>>F?sT2it{N8M(AF+UWOTxSEvP(^$`b~ochG_7
zpr!||b`=$arMA(&)$}QAT$88gG4+t!w*v2O(ow2XvWkX|w^4_p<pk5{9dw|kjIpsX
z{Me+?JLo{uZOAEi^bWewJLr@kdu~DJ>3}ZUGX|X#1)FIay@L*#TTpJZfQo^(*n>7D
zLuu#^VsIl7bX^)m7<6<t{Co${$;xoepnGyg@1O%;Y!ABW2oWyufCSyw2^Jo`gKo5!
zG2PF!hkbh9a#sVEip=Ev>ARP^ewrS(shfZL-xaPA(|`T%=9-?p($#@GrqsY7)v`1%
zGe2)?PLC1|dKm;p<VWwIE6OiO9qoe{7^Ec^WoK5VPWNBqYDUdI$mkt(#_+>nK&Qll
z4`@d^6~q8kw~pRHX8^hl3S5DL4&H}%gADZyAOpOh^E*MO-y4BWOb1;CF?t8x=pA&>
z^a8m(4axyEWkDw!jov{A9Z~=tQDp$SQ4@UDDfl*l(L3l61u$st2y_i6=#VvYP~kFq
z2i@o$bfW{(L^K9R@1O(iuo~S^Mc#%g0v*$`%;L<XoK)yxZIJ1V(L3lM3qe5FgMrSZ
z9KC}Mbip*1xuelL=rGOz9=(GOK2!_sD1a!?)dXgGpqsr6bdYWV8NGvU^bR`Ev<T>8
zK1h)ZB`rW#p+jz*1|=WxC4m-DIVfcgx=0jpN-yY+lhHfq(!&ySN>i0;r$4;tDmMMn
zkxO@{PyN^}zz-V#Hcn0gQ>m)e(_I(1s*T=3m!~kg3<l>A^ynRQ;5B`a6f!z-LA!|y
zXaP?hik6F~M(?15k8~Qt&wn4igAUYyfhOM3JLpF5paU;nfu;v2Wi)yRogbE9frbuf
z+dh;zdIue-FhRP#1sX2IQ=@m#fm>~(J26^zb_-A6zu7f=5Ur6Ky@O6^bQXhdvlzq|
znnb9iWxrzd4m#MLY|GI*=s?ROM(?15C5X{G=%5YfdI&vw2c6mI9dyPzqj%7a-a%K3
zbgdc@*VjR=dmFuj&Pr+Y4!RQ1dLQ`Rhog7UA!nu0JLnL1(9N6vV4f?>{0l7p%z}`!
z{O8v(`!l!CpAf6SqA*?Gu$OcCBYrn2#?1M5YHl&xVkn=yfJ1100<%A}++;lt?)h=G
zx0uzy260TEYt$>wZeXNqWME`8U!T>VSqdyMdRqXEZwoLnGfD*A3!rOaVP>prVw#w$
zo0MW^q-&IHnV4#5W?^ZWnhLoSj~JEE+X9GD3c4*oc6z~_9`WhIYh2~);R_ETXVg_F
zSw$Ox_NEva7#ipp85o-CfRaY6j#8zPRkWF&G3fGW1L)chD5YbnX94ReKxokIz-EXw
z=OC78td3GiWkITvl~QqXVo6DAkrL<zSddG^>K)TS2ev5bD8XF=J=Fofa}162%n@^8
zAeN4yk)9EVfxsXkV~De0BuEI^#S)g5mROxPJ%3J*cs+cuh)idi>KQ>p3PPFdfDRZp
zMZ2)sPzQdD56qpAFcUxzG_b3t_pf#pMZ_L);bo!+aRHnJ-Q;e82rFaI<_SY%)SH+g
zw>G0FGB$w(7e88bf?ZY*9rXpB$wOj%g75D(LyJ`KP1XjmFagsRpxf%rLCFe^4IwT{
zRkGqiPGArhAz~16G!V%t%@qCKaL~onCh%YcG0b&L^vrb3^bFt*fxCmbR;L>5km>7|
zxhiCl7AQubo&QG0dX{jnf*3|RM(By(M90ul&m80wIG#Syw?`bB#USS(k!UwYN-#oC
zL7*$QQP1xKbqz5>fen)1!J$x(b{G?BZbDBU#yX~Y=mnAy+TGybJ%{j6kp{EOG2;mq
zO^L|ILy??T3_(}e>luKS&FL8ELGm#6EUZs_7B)mKhK=-4?x?r4G||B>gqmq}jP=aG
z*#}OT>lljbS>O(c`r!Oh=$TsNBp>udYha>dtY?YpDA0B7Cg?)2yWr)(F=b|Eh9|P>
zVP`2pPwpZuHJR!eg0d3=o9Y<rnZm4v(4d0{O;MewV*-y@KGYfwlENX&l}JuHW_swg
zCdf5tRvYVq@*G+%2Q84H<uM1WeucUwvA6_uFdB)j0u`yCTHnw_&k&wuKnx2Vb3H>8
zSDEOT>!Ao38-vcV1Sz((l!H)~mU!|4qLL-ok?08voac26^^8CmYZ6z=%})UZSWaeM
z>h$V4J=}=oPPQXV5Ge`70xh*R(lO9OTQqA1DjY!a2n-5rA<PC6Bm!YcoNQ--0>c0`
zf=qM_(aTNHfhcI%(+CuDf*9>Kh_k>4LW7UjBQ4W`c4k7d7L){)UzR#XdSHwQ6A%kE
zVZ+ijIO?XC%;^!D-nh<HCX+P#4bjsouHeCpIYf;b=bM_7n3qaQxd@75P=>P5GtdEH
zb3IEC4GLoHAsp|UnOu}lo+T#Wt>hLu#(L&D#&`?)fc%_Fa_vBCS%XSXGt_iutYd`M
z(ls#FG1fB%MJ^b#gGuAq`2w5$m_@cH9PW{oRx8N_kB(F;m84dbC|N0iZ@E(lN-RlL
z@Gna(QV7Y+O|?>({(gt6980Z^QpNPTdp#1Yk*SGAO4BRv^=L6E)y|(Fp}?Xx-R?(^
z;PkfdJ>t{*?)R`y@4w#zzL=hh1gml^s4D|?GCrqrBMos(7hL12I9-&zSAF{X2R&@l
zr{3=oqn#72iEtvcdxPXgC9u$R!=F9cAV(_GB=mfVa2lck59ui)yAf3m?pU7bJP&&W
zrq93M!$aj@WpyON#lfXXy1|JViA9Nd3gA#oR6=s}^uE=uV$)53_JAXwXL{%T9wq9z
zlGUCF2f}-4NX}A%3QiYf?*+#=*kwGRXqTai^H}|fa2X;(p}jR^7otfbMRzACreWEe
zV&@W<sn;!Yl|#wYYnQnyP8WI5qdUF%evc3+;1C53C2nFhBO>6yEnwupax9)+DATJ0
z%Dae|L^ue{BGXl@ZbUc;rK5-JFoXnQ2a@SZq8y0Q(L;71LV`#KlI}|4iV;u;Og9zU
zfJcwu>3X1Iq)Y}<hv1B2u-gy>u`$l-K|~az_7IVS5J`rVFeJ&HL`5>J^^6{RN(c$^
z90+zQ{?KH#AtDT+&3fd(g9uF*e9&Wnr6d7cjGw^iELI<4Tm(&U5N9CQTuQK<0g<A>
zg<$t%b0(`F5iW$+0}ywhI1x>bQa56AC{b>N=Kw5jM3bY68_^s}R7}J202U{rN>R^+
z2xqcc5fRg{UM6z(@J~*io-fm@hqq<}+e12`C`X_r-?+|I3Z>F-Sm!E>tI{Xkel#6o
z4n%|zqA!XZN>EV>3O6*j;N%K85#vZiXBNekP+>Ya6YPF2VgeM=Cq{NER21Y=vFYc&
z_vp^|Ve)5|n7-gqkLdI~J~#X`wew9ux4KI}XIu3YVAsSKmsIAYDv&;TD+uWnC+4Ln
zxF+Z4<>yw8&fwP4?Y?(Y15;B|Q-d^JLsQFCT@zC?6Wt`^WHVg@OM?_66N|J|!_*Y;
z46ZT}D(7#QHig+qg$R`?;0fG%=s~8AWvNAp>8T3tE&&P!sYMFTi3OP@p!+WJ)6$Al
zOVW$-OAC~&lnj-0lt5Fdkp4VK9@^0Z&C!9IMR;$>P|{KINi4~P->jjaHhu3hSHbD4
zR=BE8*9SF0C#-fAnJ%=(RjwX7Q*3BvVWDSYWMOJ<2qBGij7&_;jPwv9COW3(28Mc2
zd9W%SV-r(DJ-8kdBMTE9LjyA-OJr@vI_4&(W}wk6b8`b^2_thIQzH`tV^d@^O?8aT
zjLlJ;Vy0tgVr-;mpkrxnYN2N^KXLICX1PqX5QXF|(14SYjuL8U8c`OS;Co5%hMf`G
z41_7@4kR-Jl!;m$&|PB2dY0xUu+eo84H{UsG}SRO)H63imaqU#Ia?Y+hg(4uXcF2G
zS-{N96*K~CXliU>Vg@6PKohM--~l=qVW?xOXK7-J1kFHko>-AttYoEBX|#XInkmeB
z($j12^+<|gPoL8_-s{oi15dov>L^u$v>Hv1eda2ogB0quI!gIvsYN-7m6>_zAd{7J
zl!`OK1NKFk=@}(T^Gi=mVOAG4s?||SN-Tno<wH`u&h&(5u98TmDS!$|)J&p~RH+b@
znx2`Tr&J3YK;(c4K*kQ)tHHS@8a!H~4jsh-oxcvdXa+JEg_?Ij*U3n*fHD;%qJ`GD
zD(Jx)%^+bV9oR4nDEGnJs?Z#%6stqIef6Z+2Z}u<tLSKGrofhSF*6#LjEa=c>cP3$
z&<slshvr>K*29*$u@n;+c{)}n+R#J~JzW~Y^G!V{g@dmgG}SXlOZHgujFFxtEWtw(
zzY#chVa-KoNngi6542mtR1YP4>KcP)rO~oiY%Fq9A~?UO1e65bT>?NYYXwPA`5X=J
zUBMDcab_YoL2)BSOfskMSmCO`3QmsG`PR6quz{J73uZZ>$*35V_!Pxsb*OD*eJnh^
zU>3|+3UtiE7faGH#fV`YBg`}hPBZleI#^ODH0@%h9Y}JE)rkhj6R6C@64_XigsC1{
z?7<39Skf{x1C^lYsR5A$;VBSXLPbk1#>QAmZ0yO!nYk!4cY5Bp9(R(Op3q4NP$>v)
zDw5p%<Pf#VFt!WMPtMFw1-CXclWp`fjHe$IaFd!|C*Y<BUO331h*rvKga*54f)cuO
zeqKptUTR*+Xd{(=jZ`DcRMWH+(=^?bWD|2;6N{8I-6V^|MBP*i(?l~f%Vd)jvm|gM
zRfQOp&}D|iC<V7tIdc+|Qge!xtfIk_T@sLT3VaI(N(~CW8ap0dXTfS!-^`ShoK)EC
ziH;I{$OLW<Y=i<X04x1a?10Q7fC@zAdgsKV%%r5$#609X;UEf>pf<qnj|0`ykl9_N
zvKQ2LhC37@3w9Rj5N)iEQW@w3D3I69^ejNj|4faI4NT4I4J-{oC-54Wm>ZfKSy&jG
z8ylOOn1h7O3`|VTElmxKOw7#9j0`{<&@3#>EKCdxEsaeK42=!ULDTal1{TI9=Eg<_
zW|jsf#ztl!F;i0`V@oq5BO^mI14|3=Y849$BXa{YGea{YBMYz^Gh<^5LsP?gGcyx&
z0}~@NL(sjerUoWPCT7Nlh6a|VrbebZ#-@4(Mh1pvW)>!9Mh2#!W5-SP49(3fEscy!
zEi8@AjVw(;%Q_4VO-#&;Obsl}4b06z_8D7R8X8#`S{hhdni(5{8k?qOW~QbFrj|w~
z=9b2mplM-aQ)43oXLCyfGZO<-P^Ap2I?W6%EzJx~3@t59%#1B8KuaKv4a|(q49qMo
zOiV0|Ku14X7@3=z7#W&?R2rIDn$8asR$%dBF|@QaonIiTz~aShXlXhBqp$*t3X=gu
z$Y*+vb}!%jf5HkZ5{w35Rlf5L#1vRm<}VUfU@6}JP*j1%n{mF7gaS*FF<Ob0Sgeq!
zfVvvLBqLQJB)=pvM<Ff0NWsw3a(|zM0?R5H4Pvr_x{gBhe8va`7Ew?SNntb>jOGGr
z<bsFc3M`V4T;T7cz#=iC6PJ;hiJ`fXv9YO{LA`;cff=YkHLx%>voHg#lr%RoH8cUO
z12Z!<urM<+HZwIeu`n>V1eLLtpysHl5onRSrKtg^|7>hxX=-6&WNu+-YHDr(E<Mdb
zMX9NQsiB3rrLnQOnU0B`xtXPzv8kbvnYp<+sL(agvoJO@wKO-XH#0RfvoNzXwg45e
zW(J1F78V9ZmX@ZLCT2Ru=6Z$(M#hGwX6DA`CMHIp!qddU5LC9BnVT6{7?^@YK&7aq
zk%^_5F_;8(xXn$>4UG*A%}vb>K!vxlo`s2tshNeLv4N3=k%^(HxsH*ZnI))*wKp{d
z73wCSrDw*bprYLpR010t8k<?@fG;06F*7wawlp_2G%^J(0y8nQG&8a=GBq_eF)}qV
z1Sc$MP)RzPtPIVKEey;IjZKV=>rD(zjX}xE$i%_|6j$a3mXPfcdIm<uCPpU4rl3(1
za}zUAn1X6Pb0aeg10zEtBNHP~Eo}mdL1Pmm3nOC-GZSNQZEk5~YH4n4VQOw^U|?Zp
zZm46TXK7$&VPs%rVqk7)Vr&jNfYZR#!pz9D-qg|pRHGW3g9d|)EKH5fj154Qu91<U
zxsI`+o{_1Mp@Ff1p{a?1fvE|&b7E|02uieuhL$F#hM)zR=B8!_rUpia#-_$*mL{Nj
z+Q`t{#L&{j7&NwIXb7o*O-;?sOie7!%?wN}bd2?kOhC!r$q<x@Oie9~L5uZ_O$|W1
zL@Z5>4NVP=EOkH~8dFfa!PwN;)Xdbx2((1i(89pX%oMbA)WpKb*w_S;vKS5L`}rua
zNRH_8%D}+b)WX2j$k^Dt-oU~VlvfQc%nb}IOe_sdOe`!dj6nftU|?ivW@cbwVrXb&
zYGeSqt-;dL)D+aGH8(S{urRRzCoD?~18{TC)WpQx(!>(ft}-+<urM|QWo#o0Gh<Nm
z%hbTw(8$Ql(8AEv#Mltjt}-+>G%>R@s5i6(H8BlMEFcNX4Af8qjo+9Wffni+>6w}u
zTNoM|nOK+_nu0d=7@3=!7#o_Hn}If9fJOri42>-fO-u|842>*Jz)B1ajSbDsOiWA+
z&5bS1K<Uib+`!zz)WFot*w`H88_>FDb5OoAvNtj{GXSS8&?0tIV@qQLQ%g&bNyY{y
zI%aw%=9Wf=hK2^lhGyobMxc=yV-r&YGgDJj6JrBIGgC;anr~{Uz#=uG)0B~kg`u&z
zg}J$rWxa{H0l4TeHncP_GBLF@G%>e;w5H8X42_J;EzK;=Oie8<O+abN!rair+}Om(
z%)s2t)Y8}(v}?h{#KOYV+|<y_(7*t+fZ5Ez%-qb>)X31(z{1kR611e$&=gd+nVFiI
z8X20HfIBRf<|YQl#wLdKrUvGqWC|X*HZeCeGcz<cH8(P{G&2HqGK>rj49$!{>yeF&
zLG_)Xk(r4ZC=FSHs#8-F(2foR6C+Ts!obkf(%i(*6m(oQ!bPC|0%%dIrGcfnIk*%w
zG%+v%m2d_ImIel94wfdM6l`Q+0m?>3CYB~9CLmv18kw4#nCY17nS(NifuW(Lg_*I5
zff=asGy(N7Kvk)si3uc8$&40MdPe5PW(Fq4=9Y%W_2!_m-%!uMz|g?J#K6qR(9qJ@
z*c4PJnj08e7+6@C7+9DXn;3%9i-n1afe}cXnFXlr1!`%T8X6c{m|B=ySQ;7{8kt+@
z80eW9Sy+N1&cx8f$j}1ZO*An!GdD3aGd8g>GqNx@1gB36b7K=Tqk1z7&@ip31*n`d
zHnube^^}b)4NZ+e$<aj5+}zCE*v#125;T|yYU&sn7#f)wSQ=Yc8kw3JfJ-U^P{n3!
zY-wa*VqpMEFJ=a2CZ@)wMg|7v7G{><{VArV1{R=gg$9P^pzUxbdIsi(76!(K_7=t_
z#^$DGpd!c!RQ6h!7@C=z7+RQsc0X7e85&!FI;tj?CPt>9MbDsi7^op>Y-na|Zf0x_
zE~sSY8wZT|%Foc;(9*=*z}U>N-pI_r5L98AT9{dyn}TaaBglA&shOprk+C^=aKqHt
z5Y#faFfuYTGBGx=G&M3dvor%~G&M9gG&eS~G&Zp`F#|Pw4D`$_LCMj`!UWWaGBUN)
zG1fD%Ff}nYwXiTVGBh#<n`CNYU}S1xSZ``!VqyXsc`!89Gcz(ZHMg`dH8(ahG%z-U
zlvKthrWO|Frk0?F9H`xIVgzmyf|3uY7Su7-GqN<dFf=g-<p>LqJ5BV=O-xOUjm<30
z&5Vpd<0_!33R4p!BTEw#P$SL|G}NMJVPt7)>SShOWNB#(8UWET(laqOH83$TurM?*
zH3n7W=6awBItv3s6LV0Ou>{TR>6sdvT7p6VRD2tonLv{jn~_p&tfuv3LuOIP_HV`*
z1r`TgBF884N^^3MHMhqou*5*j!LjSy2yM^=bC{Rp0cO$pTD7;Bg{SlIyYWue<=~lY
zz{@wys8@2jlu@q@FKF-?JUeKEWzZS4jokt~{ye&IoyHs2&5X<q4J}PfbWKytOmt0B
zj4gE&jSWq7(~?t-l9Egf3@wr@AtTDfsDzFv6QdL~qO3Gs?Sd;``=uk7+Akfs+<xiE
zmG(<VuC`w~a;^Q+k?ZZ3j@)R!bmV6Hr6af6FCDqve(A`a_De_ZwqH7Oul>@I`|X#G
zJZQgk<YD`zBahlI9eLb->By7zOGlozUpn%v{nC-=?U#<cXuoviW&5Qgui7sidEI{L
z$eZ>{N8YwyI`Xdl(vkP=myUdBzjWkd`=ukF+AkgX+<xiEm-b6XzP4XF@~!>Sk?-x7
zj{Io9bmV9Ir6a%EFCF>ae(A`c_De_pwqH8(ul>@I|J|34F!o<M!U!UmKm;?0U;z=V
zAc74<u!9H=5Wxu|xIhFqh~NPcydZ)PMDT+M0T3YwB7{JMFo+NV5uzYM3`B^72ni4&
z2_mFGgfxhd0THqwLJma8g9rr>p$H<BK!h@gPyrFDAVLj9sDlU%5TOYov_OP5h|mEM
zx*$RiMCgME0}x>dB8)(UF^Dh$5vCx*3`CfN2n!Hl2_mdOgf)n;0TH$!!VW~(g9rx@
z;Rqs}K!h`hZ~+mnAi@nqxPu4}5a9_Tyg-CEi0}asz97O6MEHY<01y!fB7#6fFo*~N
z5uqR=3`B&3hzJl72_m9EL^Ozq0THnvA`V2vgNOtWkq9D^KtwW#NC6S4AR-M!q=SeI
z5RnNYvOq*Oh{ypExga7BMC5~r0uWIMB8osnF^DJu5v3ra3`CTJhzbx<2_mXML^X)0
z0THzzq7FpVgNOzY(Fh`%KtwZ$XaNzeAfgRKw1bEa5YY)Dx<EuXi0A<ky&$3wMD&A*
z2_Rx3h?oQ-CWDA6AYv+rm<A%IgNPX*VkU@~1tMmHh&do)E{K>1BIbjL1t4M}h*$(7
z7K4Z-AYv(qSOy}NgNPL%VkL-J1tM01h&3Q$Er?hLBG!Y54IpA8h}Z-oHiL*QAYv<s
z*ajlDgNPj<Vkd~$1tNBXh&>=;FNoL&BKCub10doch&Tiy4uc4Ao<0g<9Rm@^LBt6V
zaS}wF0uiS{#2FBA7DSu_5$8d~1rTu&L|g(9mqEl85OEbmTmuo;LBtIZaT7$`0ui@C
z#2pZE7ew3x5%)pF0}$~LL_7i!k3qx}5b+d5JOdHWLBtCX@e)M50uir4#2XOt7DT)Q
z5${372N3ZQM0^4fpFzYI5b+g6d;<~RLBtOb@e@S+0ujGK#2*mx7exF65&s#xFCAe5
z6@MUt2}Cf12o?~*3L@A*1Urb}01=!Zf(t}&g9siF!3!ezKm<RC5C9Q^AVLU42!jX_
z5FrX8#6W~Nh>!pgk|06~L`Z`O84w{0BIH1XJcv*L5sDx}2}CG^2o(^a3L?}%ggS`O
z01=uXLJLG_g9sfEp$j7PK!iSsFaQyTAi@Yl7=s8C5Mc@;%s_-Wh_C<=mLS3kL|B6e
z8xUa&BJ4nfJ&14s5so0j2}C%92p16H3L@M<ggc1v01=)b!V5%rg9slG;R_=CK!iVt
z2mld*AR-7v1cQhW5D^L@!azhgh=>3Yksu-pL_~v#7!VN)BH}<qJcvjD5s4ro2}C4=
zh!hZ!3L?@#L^_Db01=rWA`3)hgNPgukqaX7Ktw)>C;$<KAfgCF6oZHo5K#&u%0NUp
zh^PP&l^~)DL{x)_8W2$nBI-ayJ&0%k5se_C2}Cr5h!zmh3L@G-L_3J+01=%aq6<WH
zgNPmw(F-E_Ktw-?m;fRsf`~~VVls%B0wSh@h-n~VI*6D7B4&b!Ss-FIh?oN+=7NZM
zAYwj<SO6jxf`~;RVljwV0wR`zh-DyRIfz&RB36QkRUl$Dh*$$6)`Ez2AYwg;*Z?9n
zf{0BZVl#-?0wT78h;1NZJBZi;B6fm^T_9pNh}Z)n_JW9gAYwm=H~=CJf`~&P;xLE+
z=jo#$)-e!q97LP|5hp>!DG+fQM4SN;XF<d{5OE$vTmTUlLBu5xaT!Eh0TEY0#5E9c
z9Yov!5jR1^Ef8@VMBD)pcR|EG5OE(wJOB|7LBt~v@fbur0TE9@#4`}_97MbT5idc+
zD-iJ-M7#kJZ$ZR65b+*Fd;k$2LBuBz@fk#X0TEw8#5WM}9Yp*95kEo1FA(t?MEn5}
ze?i1Q5b>X>`_d6+Q1J&Mm_P(Gh+qK`tRR97M6iPh4iLc!BDg>VH;CW?5xgLR4@B^T
z2mufw2qJ_)gfNH@0TH4gLJUNRg9r%_AqgU+K!h}ikO2|0AVLmA$b$$45TOVnlt6?s
zh)@9$svtrQM5u!Z4G^ITBD6q+Hi*yx5xO8k4@BsL2m=sd2qKI?gfWOP0THGk!VE;1
zg9r-{VF@CvK!i1jumKUaAi@qr*n<cM5a9?SoIr##h;RWBt{}n<M7V<p4-nxABD_F^
zH;C{75x&g(FCFn?o@R%)YYSecuSdpVYV*@iPhr*>?S}HO^zW;saW~Wmw3f-jGDX+W
zILS!Y#L&b{*CN%@P&X~r%*@otJju`?)fCbVB}OH*8%m7Q{Ry$Rm|NxWr=U$Wx0sbk
zPeHb$X@?$ZC)p^;+{nx<QP(WVEJfGE(9l%Z(#R-LH^nH`!Xhcrz%tnwx+snqmC&?9
zj8f1LhV1_3{0b}+RW*pw09rb<AGCDnDbs#e3k8-x%DO~qBY8y6n{aX^as}voaaMn3
zVaCk)+N}P}a-&I_9!WaI(%9I@G}%};)!fWf*TmAmTsJY<%vd+YEXmR^(Jax@($ox8
z9R5}&LLoFo6J_Ru`L442ji*mx?l!_-BzB*g!YnM7SyEb*O3BEu;N<xnqVxOW6j<&9
E04P}dAOHXW
delta 104201
zcmZ4U{haOFeT|A6W;1P`%QTm9@&`74M%BrRY+{oyv&l~8XBOV<%hJYVpOKoGo>5|@
zU}#`qP*7p5ps%IinU`FYnpm8wP?C|V0FhTn%P&$$N-Zf#EmFuyP0viq%*iaNRM66&
zoX8>yHIQ#}CA%ck<Of_~lOJ&MFopU}{=g|V`2j1-<h?xVlk2(DCiioRgZP^ndHg`?
zSm(d*RbY{voXICRzr2HkS$O`zPr2;ElN-2L=UenCu<*`b*TKOoG5>*(2D{+=hCT%r
zqxk~tQ<+)kt8{WO>-29pbc?xv!=c+C;tq(o3nK1;i2ESo0f=}AA|8Q=#~|Vfh<FMj
zo`HzxAmRmxcnKn2fr!^2;thy+3nJcui1#4k1BmztB0hnL&miIpi1-R3zJZAEAmRsz
z_z5C@fr#HA;tz=U3nKo3i2uyp8xFDbZ#cvVBA7q~Gl*aT5v(AB4Mebm2o4az2_m>a
z1UHD_0TH|)f)7OSg9rf-AqXObK!h-e5CIXQAVLg8h=T|T5FrU7q(Fo;h>!shvLHf^
zW&egl@+@i-RE(2N5>3)f(sV5?6HRnYQZ3VTlgy3Hbxn*+%q$H|49zW#66Z6vZf5^Q
zoYIS*)Y%=0Q>rNK$E+lqSdm$*WTljxpOaq%X6q=Wr{*hJfywEPM_m<JGxEz)i>4bC
zx~WZHzQ~nNBq%jKGe0lhIlnZoq^L69u_!gscK*jS4rVFQvecr)^i&0p{M^js%#>7x
zpv00?+xZ8Q{FwC>!N!!NR+K1NMJqX`rDr7OWfqqt<|*kYIi?k5CMV7hJnhG<$)1}E
z;uOy}Ec9azV=B&^e{r%Ov*>hhYd7)rlM4Nq89B2v^AZ)@5{vWaUp(W-?5&%cS5lOi
zqX01_Pa!C^pfo8bGg(PT$r&b9oS6vXW+bLeHw<<wpPy3f$80p+^qQ-bwo7WR9!QU#
zLVg-JH#+C%rROW@D7mEO<t7$ogIHOaN%^HEnbQN`x~gy|7MG+J<taE8XC_WpeB~-K
zz2vQ{7n^HoQGP+{d`3M#W=H14+@$>zr};70FlxFu$CMfvB$_MfDEaufI2VKH#C(N-
z)ck^+RP|y7xb@Qut=yESU;FJ^FO#XHqvV^IQv!0cZ(>n#Mq*Bmf@g6~VqQw|^uTSd
zrtCS1d8r`#8@IWN%`Y_YWBxRK#wAz&`R8ZeViumicJD1_&gpYExN-{k<rkGFRx0Tz
z`6s6)=4B?%-+0lFIfXr^5~4rQ$<2Sd=xtZ^>8!V1`B{QJU4pkWesc9@oPV@VfkkM(
zgO(q&(DXkqT{-8^Dez<FoF1~)ReSoiudc$=x7=|}<OBy)NPb@W{EvHXF{{ikx#GvH
zIQ^-Mn-Nb4$lqznMcJ8^snZwka!s4hUkx(MHQG&j`qeM49xUOh#U;}jU%3j;|1-&t
znR7l%z8|v`W9<Bmul<<yL`IXyXcEDmMCxO8l=2dDQ<bcglysD;l&qo+^o$KGjG@55
zz`(%BM8{0e3@&73X=!PxqidvRYH4T&0p>coCVHk2wwalkxsHLJC0xC+fq{Xcj-{R%
z)JS7vkcbgTi-o0OJye&uj;<k+5oRDuEOd<YETHmcW+440<~qiD79cqY21)AZ8t54r
zfmmP+meA2P)-wmW9fCnNgUmMvs{j)qWgu1c#wIXdfb9f(#R63f>{Pfaa~)k%Jvh${
ztP5n4nUS%Dfu*UDv4x?Lg{hgjj*+3BnIXt(Fb3%|F@?Ctz`y_`2GUiJa5>l{Qynus
zBU5<bfn0550(LPdU_shVK-$oJVya_gre_2)6M{jprju8ilcQs(XJiDAPLOsBkakN0
zn345hTg^cBpaz(c8OYm4i0}u6n5mAro+*d{!5}B;7+UCAn3$UxS{i^zQ*%Qz9dkXf
z|KM&h1bN;FZYS7Ekm&|yX0Z5&h=HA~Yk(GaMrI&ySVD}0Bp*X?C>X<hVFpe<2B^^n
zR$_@NW}#!OX9y1uW1YNuP$20V>cP`8Btk7Ap{HxAX9|yMupMaXOhDd169ah`#bu^?
zCU94n>lm5p86x~r4@wK5+=S2p4hl0J6Fo2k9@3^DtIXl90ZW3?zB$}%u#lOKp`o5B
zJglI()kF`W44lMa;SvkVuHaw?6S^koApr>p3q2Ern{^D0^dQaxlV)aS79h8w2ZNEG
z(KHV?iF&9LjFHO(P{iq&n(7%MlDdI`ftiklo;lp<#-K!r5iI6<=5Qq-lg)LE(DlIl
zW(JPSdP{JUM-)%sU@``|7?C2uVS<Qiuo4|Z13eS455a_)nVAVFYT>yNY&tBV80c9d
z{0~wO&OVk#@DvWV!4PhvIVjFSp#a4oE#Sli<%1}Yn2wpADM}a_>KN)F5-_MJH2`G~
zMEML7GBgAm4|WkGhk?wp&@nR6Lqwx7Bx-eyG0R;;BRvy%83YPt3mp>-cj%fTmCoim
zCdPV*(hj5t6vD<P@Ei^<Hw_S>2XYa}l?aQ#acv9=V??274l1q?i5?s=CZJ4=NG70C
z4IFeB#kQ#)BK$!`gt49_C|n^JWIx1B5I(ptGqKP!fhRApQ%uoaY@%m`a1Y239RoeE
z%OS=X8ylN|OA1qHzN|Mh1DCAE;LHk91R}v&b&d55P>Wb_!Zbz%07#h`B&Lk?j1fse
z$57849z~!yH?V-HGBicb4+aMH21cNa1W$R8WNQHmdNWjynCTcB>LJVo8EOnthF0hp
zp+*U)wnt5UAPY_OEI{#M0J0xi+d&E#EU8V`M9&b_!yp?lGAu;Di5{ZzGKctB*GSJ0
z-6y&xu*3;U|KL<)26Ygq#5FcHG6ls4TBw+t=@_BZ4~E8i2JkQkC2DZE8G$nvC=#LR
z5man~xnKemW#GgQb`;2dP-{TX1W}lP)0!@F>&6_^LPCT+xXq+%qK8O)V4FY@i73cH
zLKa}JL6aKDc97*JI+lpSw%*tn6r9HBZ4XmDESV9bT>)y?q3JZyvp^Ig;FgB2A-Y42
zbPP?QNvR&3Q$gW@(E>2gLk)im3ky)BpgF=4q!-PH7=?rpdc6fM5zG)R40DjlNKIBy
zVldRP&@)5?x{j%y1w67rsozM)7^xhDh@kjh#{jKaYhVIusvyciaQcVT+@Qz-V{p-r
zEeV;UCM!@78p8`CP~x)$dD{fs#ssxAO$<$pz(NLS8bK{6xVP#-g_9|``axteb8x)^
zju~TPW2o6idT1pmIBlWTil7E6qIm%d6L9MeQHYuA7+LBW!yAMa_2z~qI);{dMhIOx
zhA1sW9V0zsxN|`!8kp!986lU|AcunD4>h@1nwx<F1lej`BR%v&tsazokk!D-5o36$
znd_M7S;9jaoL#^%1tB0g3e*&Y@FAJkM9&PKCLz@boD0gAmY}R^3@QM?`5#>9T3CXD
z#sb_<2DO$=ElkaIERfsnpp1%WBY@2@0hPemQi}!1aIlNOaf@hvK++dj21Gzw_!w!>
zLeB^u=8*U|(zAev0Yn5;h@$(-R1YJy8SBC7I#6R$*90k7o9pP-8zA=vKrS*h1qBY=
zE@N;4h1OoWnANMUv7WK9k%@_^iLrsXp^1fgs;;3Cs2L59KXBjB6ckWq2r*E!flBLo
zJ#%=vH`g&VMs5Lti&;aI5?|Ly&j{7epr*JbqQnEGL!|l+<RNe-Gy;_<5DZDKCXi-0
zr2GT<(acoGK+gg-)J=7aEujS^NEayF%|JGw75qlVI)-}2ATL2M$W}v8YQe~zXzA40
zxL(f?r91)`j3yw<AQ)s6C_cb01aZJ=)e_u(MK6(bL5_f>J5a@s$kQN~TUw&DN+3eh
z1&_Fj?N8wGXI7IoNXgGl%*<1=s#dB14>cHoTC=e_N|i{wS{<e2)Vz|^A|<Qp`5*HY
zSY)Ta_jMDRpRnT=GaC=`c<A(roNkir$|fcThNdRd4=#6;Vzn@`Ft?cR_<RbpB%5)n
ziKT_*^oi5lBw39O%`7aYe_ZA!#b#t?VPugyU2wUZB%5KHWvYec^u!r%l5EDNN#^F3
z^B-OZ=`~ADPBpcdesQ*&q-2t5N~%$kQmjt2p`L+`l5$!~s=1M=Qf%z}V*(oN2E6V$
z`ALa63L!<Qc`3#7^`jM7)a$FkV<~hVOo7B6sHIy!AcHB0u@p$511^}*>J)Hk3`;^F
zr&4h+1)k5%AohdmDtZp4fD3H!SV}#($qz3L=rouDjej#s%X&*h#}vaUhI&Sb;tW&-
zf=5aa`5)YUA!jfJF_r?Y^dLnE%qcV<OaZm*LA8J}yweGB0H_29#|^yjgj9#{WC)f7
z6}za7YfBObQ$W=pxOI^i3=WFX!4z<c1cmzOU<#zR1=We8gDH@aIdI2rbTGvjX*L1W
zrb235f+`RraE%FKfjg6<gDInfDWDWFI+y~kTOgfX)LtLBhlAdAF*Ma19ZUfS8K@!x
zwRJ`ZQ^3tWaB3MHOhIHJ&_w&_V2Y)sr73815it#6t~2n1DFU&vwK~;^C1&yS1?~Kp
zg)NmFu`L%<s;!OHQOZe7O3hKS!mecgK}~;Vh4~8tIG9=M4fH@GR7e9^pw6KIcoZ0E
z><QGIH`OuJGt|*F1nB^+zkoJRAe5njIcT&BRK}P<L|~+`8F(ZZ#s$;HIwpFCATvRo
zRxk}(UIOZ)LOBr10yNDA)&M7rz~c+x!9)X)W#Abd6CDFRR38|Cd|;plS}+RNYG7bs
zsbgrS2bmfJX*Pn)RKZmkf?Mf2y5@R_=?{=3cxKfAG+>5mprHw5G72<x3L54EnP~~q
zfWRgoT?U}a8{G0mTE_zNqK<C8r5<W{8G#G|_r{@y8z7GXf;54q8jbY8N|4rNfMmb}
z&}d?2ItI|72CD!O=HOX&h(keZ5g@LGS_fL_0`V1SMgcVI3i5#=$W;a)%}5wLaRZ79
zb8s3m&@t767zHE2y1)(vm%0e8;CWH7L+jy!=3v)@`buyiOVBhvXl)YAKnM+WDY(~d
zpoi%yumosM5274Gf>w_hqO1@CC3Ky7U2vkd)I*vn1WQ2U6jj&&H1A;s^{uXjo&_ju
z40H_iz%dN=6<VeNdkWo&puhyrc^DWVLd--**AmS$p!9D5jSLG=x;2<Tzrl}LwB8b8
zC5GogGlPakXnDa<N7qab>`0`5wY0PZEp5Os0VHT-pa-3O)-}=t&qbhm%EAylMq&tY
zggJWp1o;kW{0S8NhVvIT_%RFDgF^$V&j2mR4M5_s31pBa1861&XCZL5K+8RrAe&4<
z!G@aoA@Kl~MD;P)egi$wh&3ejL#;6YO+JAl(^wBf9JE9Y5(VIL&k!w&EMXyKpl6O^
znYj_DCIJr&g2Nu<oO;ya15_RvVPsAnT?;+X>JCGgt&oBeVK~@KaOOdXffwh&b(li5
zf|fYJeF$Q(8GuSk14v{<LJ|=u?HZaPufBqes9}_-hLF^#YYeIcEFt9&TDAr?%nkL7
zA?AYv8@?g{WIfnmBRy~xi<&?{)e4q?z?Stv?$yO86T$vRElBGjo`ob*Lp^Zq1$70K
z0#$ry;Rv3G0Z$vF=UH%Jhnmg|48i#yOrYivP&1<56nQZhD5@}PGf>wb%_2|+v;^gK
zLp@Bl8G{n3Aw(9<E#M3S9^!-=C<3z55?X{pt4ZDI2Oqf#*XtU9&9MNN3TRmlTsMFT
zR0}}46I$aMnxK_1#^Cj5Q2QX11*oPq1x@;bt6PX5l&rV3gqsF+EK~+sCZPo;Y%JLT
zc^N2J2Wa3I6pN@aZ(s;60l?)3*vViPBE>=KJR==*j8qRzTwt>i1UTxkl|A5u0&X^A
z1|l}c8t8$mH$<IhVF?atgwwz&(+F2{25cYL2o%Q|LJDbc9HZ4&u#&(C6ycx(%+OHJ
zxL(HyvlIj6YlNvFmbs3Z8Cr-#G7~o4pjk3qaH|Acrqwk-ZsmZ(9~4I@>v};}n(7#W
z)>?p=a13f#frAB3nCpO+Q^FO17@&jzEoO~O&`V<U7EmOp@&lE}7=Z<HC#cB-G7^D7
z#Tr^bfHJs=o-y{8xvi3OMq*xiszPQS>Q)ZawmA+(D6MltJ!m@t=6UGyCr~L0Zsvee
zESQ0<Oaw`SFor3{I>vgSlm{sRpiK;vCAc8_jCAV3Mq`O@kVdc^*mw{DTG^yyg5DM|
z1+DXdq#9FnIj}HTtC=3ONeAW`ArwM$3OHqB1O!;IsUE0-YoMbGigu8r;TYsUL$ss-
ztMbsQR8VkW6t*Dm)q~o1&}vl|v!xDF0$L7)NGc!}bd9AcsG>7A&@<LCM_y72QUOZR
zp!A24?~T!_jCyeSU<4^PKsq59R=pd5GCnw0V<r=G3{6Jp4K7fXh*qpY%L`Zu56-FJ
z5QPQ;*vH^}4rYNCd_kN9BXx95z?F+JxNb3k_w!)#(B={-?o9N+tr3W4z{cqspw)Tx
zCeXkHmn>#_&}swJ76xko83Sg330+XC)HOp33q#NfShThoIO&1)fC-Q>#^~)2(4x$G
zs4qYY3^Ch=V9lWQ5#S(#6VN<rjNbSG_k=JTn4n7C6dD$~hA4FsDEvXS0W^n#?E|?5
zJ)KxWg9)ra*BC7X44@7IWiv}e=7K~CsFjMA9l)WZYp!RA)H??$)-eIK`poq}jV%ih
z(-7T<#^Am)C~2b=t>ASl20G?w4F^Ne&;YvUz@7jTy7i!H1<V8!#vr>b^q^@`*U&-_
znqIMa+0YPq!8*7hgsn}hi{S}yG(n03X!!%KFTgGU6IeP}=IBEWP=|pc3#<o0VCk5G
zB|&Slb#x6;>O`>pkPM=0rUz{Yfx^TPWtlqIbLiC`xOaq6XhN*Q77!q(>Vg*OfukQX
zb^=O&&}40B0&Zbqw%0J);-K*fbjLtbAlP;=VQ7LDJ7zkd0uw9;CP2=C?9>3WKy&M0
zanQnHPy)m3N`dzOfYuO#2Wmi#0n`R8xV4U@Dg&E}(P%LOH_huIVGmXUCP2$`LDSl(
zB{#VHg3&GmYXB3vMtYz{Pe^IP2)R833Ssaz1GMgxj&8j<tS1gO2NV(z{~M#069xvx
zpf(-EwV>Xdj;^7Ro*8Jd7+OXIcfL@?Kw}zu$Pt8SE~J2*2J45T>M{VeyFtSqX0RIA
z7|l;c5a+;M4jP02aj-X<xDbt|`R{jbW)~C3(OQDYf?G)<^AGI5#jML@Xg>cylmd&`
z^jllp)`NC$&o|h)nSHK+0vebf|2dakVZNz>KeIANNk(R|LP=`H{D58s7F*~B?gwq4
zE#4ar++t>diXd(2=FZPe%FIhmQ3y#bo<H%>EoSM_?cJd5*tFZ;onm2Wl9XzZq-&g#
zoTO`FVr-^sk!G5zYmsP_nv`sqW{_lI0N&pHTbUS@klo!x84B9nEmvP!T#}!gl30?c
zWECB4WMF6-s}pTxU}OZQ3=JR@M9=^#2<1U2s0ITl4@Cp2b|XWuVW=wWvD<{zG^ij7
z1=WsfsG%{~CaBYlAZ{`+0Slt3tcRF}CW=)MVhq$!tX@MEL^TtY2Q|gOv>xmzd>YYw
z2z46Ps6cfgR3(IhS_riW5f$~I*oKPYa3UTTVhvJ=g+v-wA8lk{U;(iLq7lu%sD47_
zK{UW@g7Bbzfl@FzZ2G`T>fuQq%r!E=rvtkj#B8i`P`^NphQ<Mk%6eFiLlK1u!Zbp{
z8Jm8%N{H`a5sOCyszvqq3`JE6RS9zw#6m-qxWlRet02sjdPt#Qh~i+FBt#JAC#Z#x
z;D$N|nzx}mC<WDkDu+EPjG*}sVm8dBs5}%4VNQc6f!YMq2T_ULCWr=9?S`hYko*Ug
zgiuiZsD_eIq(MwU(~ecpAXW#I|DeH!>Ncp?Pz6y9Mdd+FAwm$@gNXcxy>@{FDb#Ez
z1+xO;C#Vad?uE%g^r7<5w1bsk<UdH7BdigY@vy5z$rZ@{H8Oy@7wVXLR4!B$W+;je
zp(<f=VCTbJ0hNPlhw`wigqR7FtH)*xOcF&7>I<mZP@Ax-#3~5W2MJ%ec4+=Xu?Z>(
zi%~Qkkh%h*0jo{K3mO`r=0B8JBgq(WElN&NrjFF+g7^vQdng4B1f%(ldXLydGL@i5
z>R2hLR)Y@8sRf;&Vw{{*1g29XQxl6oQpxaEU9>?gnwqf0oYGW~qRLt&9i`m-6wo0V
zpi^v8i$EvOKu^t>|6%85c2Q#m4OLAg9VL)e;4^u0l0YZKfX?GVu<}y!i;6(!&^Urw
z(-SwkYD{Odag${!EiNgV?)chOM%S?_wJ0euGYfK-4>HFou_!4qB_Cupj5+_HwjZ<f
z{2PUS%p!d0nWec(I!aEdIUv^jkJ^6Brqid|xXCCKC01qTfTVCRreCyiQ*$cKNlz>S
zAMJz0bWTjlR|rcjN=XGB`IDHJm;!RYGbSS=GbeTW!>g`((=~s(%FE_}x<_E8`NbuP
z3PG94U`|nfVo7G={DfjZW-*Z@uux?|Q7Onz&S1v;29OlHb5&|`MrPvlkJ4@u_3)#E
zT$4)^Q}T<Hbd+3k6oM0T%CPf_OY-x;{&0n}+%oe(2mUDOC}Cr{rxxWV=7A3OaW6_u
zO$K=t!6>y%EJ@8x%mF#py%d>UnV1I=gfcuz^U@QGK*m5>(+ln0B-oNuK~_(Hc->WO
zzIdr0vz!Z9KuJf*vj_{TxF|6d6j`2_jFQA0km;TvdV1k+S8>+dM9^7J38j9_VqA#@
z;56fvSTOyetef!k=dy01tfl3NnI+R59Nfg`KP~lRmJ!M<$tZ=UOdkk)`b0T5DP!0H
zNu@=ZC7Iv|@lCDBOa`6ZgoTlxmzbPCe`1y&v&#HwS$@p&U{X#hGdZy+F})NNEbzmU
zAdKk;!`(#Zf1ByYEXbD+3J@h7r2sHvzThlBW(lGEqLR||M3Bz|pv-v{e#}zySt|UP
z#UP|WelFDMK@iq-!P~A%^Os!mW7e5&wZ@fix|g$?#Pp?+Zc;3X*_ny+{VV;Lr4)1W
z%Tgf;A{dET0NRJ9qZC|_m^uApq?;s1QKo`VVqSLQ{D+tQm{s}8Q&Unw=V=9l8S^hx
z`Y}sKm1mYzr55ER=A|g<C<UYNLNXFFp%OTlppplAhLe(xQfPW&9yl{W81ola`7s+!
zz3nCl!_&Q^-9$l$J1M9*BFYd13tWbPLVC0`87)l)rZfqGlpx^37FwEs*@*MjMvIj}
zTdc@|j{XAe!UavD7=o608R|jSZ5o4CMS*7SjP<|^BfxV#CVH0OQF+j8vyq+==(q|U
z6FmdaaaEur4?qLqmO3VS;4`~Ghjf7!0P293+JICU8tZ{hZ86gU&D)vl8G*Fb>wqjW
z)-wl9ih}eTg68sdjP=0V^>jeXip=#ut1wMK2M(F*n1D<JEr&5O(lZ9_|2EPw(zDb7
z&18Y54-G-C1uy6V*<}ct88OiV9Xw_ZF&i{rWD1^vHPiul!n9t`0^|(PF$)Gd7J4S2
zW2?aK1FhvV1Nj6TASQaophW{Z#-L?GCVJpAieN4Vos4Fz1DbjQjeLV9EkGdvS`-K}
z4>T_ZnyCT#8N>&<9prbA8dE)kdL2tW6X={c==cvq(B^bw5Mcn80a*xIO=%8_7SP-_
zXch|;6rfPF&;d;cKo=%jLVRcl3OYlOHqg2(NZ=akfWpuaG-nFY4q6~$2qx+cKn5G?
z8H3C;1{nbgOjFRb2`GLnbu7W51&KG%#3abwpy^g{Vgb1f<WWOVLNNtLqLGd<ND0(f
z&~j-#GaZnp!Hx$d8bedi<OgW#!a~oy9(4ABj-{Rj$Z886P}~@T!q*UFuMvm~@(Lti
zK{G<2xCEWpVFpqUI-0{+2Q-ZUvKut_3<@}KN-@(h0?mViCV;^n1x<c{QVb|MK;8hY
zV+1Al`hiOL&~#rvPzfKJ?(4y^0ZN$W;Cu`UTTqU$0G(WC4qAOfql6Dm-9~!#Amb@X
z_=X00;5=gnih5JfS{-P};z{(-#0g6C^`MjwDlkCF*a(z7L75el_{^b&6)3fUQZyA4
zJyMznl|P_VPR~RSJ!%28;>WmN53-y9lpPI0Yg53v#SpXx8dNBNLJES-bU;NbsH_E*
zn}(qE35KB3#~8Hc#8eMd?1N5W1Fi1?70J*d45Sv6KS2uxOw9F+bxc6Tohc|Mnu5$S
zsW$|bv7j~hkfO>Ml;lA9+CT@CML`%;a)R<Q#2p4YW+r+@I;J4Eg4ZR3i!pE+4=S)g
zXG4OPv4GqFnqmbVnE{&mwE%BM02yHdDvS(`K+ZNYFagKExgMz20r?QT@CR%&C`}lG
z*WDWFn1dFt7=tPjV^C@X9c`lnayLjG<U`18t`S%aRJeg0Xru?KVZaBqfon5RXoHd$
zxH<tPI#9ATumFX>IjF9&1eHt>Z-Q3A7=e;AsNw}BV~{DJ00x-|DkIH6%P37jB_ODh
z0C^L%J{Y9U5}f$K6TT*(KsE+NBsgwC6&HB9j5%oe3uvwuG@)%)uLBAQaA1Nw39cR>
z&IBD|1d0TN@t|B`2@YwHLqN?0P(^PFI{eW@#}t%-Oh5r_WTt1VV+=|ypaK@;3PVs^
z0_0!t>KTx|pcU7kC@}=t5AqVo;h+ex1f9JFX-nvVTmZ5K6n`L1pkl%lUeTI>d<04x
zMj+RNLJkropx6iL1Xbl0pwtAi2eMQd5*Uy*L!dx0)-$XJM;a&sK~4ub7*v&k!UUB3
zA!!R##hB`V>o0I!4LTnT6xkrRfzlVmaFAY5T?MLTK}iMVK5()Jmm?r|gFFo>?m&qK
z;+T4nASj4Io&?1Th&I*%WiOBcu&4kz4irBiKFDzf;A{(0577@wtspfZ$Aha+kSh#9
zjRtV52ozM{GzT&rv_1~xWDqt5wLd^7WPp;H3AkK>_!*LaK!F6qAQM4;gjf&q2gvV`
zL<bQEIR}Kn6)>nGF#;Xsr~`@`m?lsr2N?vajzKxWs2<e(04EF3ZV^)*kaIx|7l<a1
z=Rhto(E(*CkY<Q$K&b)b4Nz$Vq7i&hS^$ME$O1@!faGBq<YiDR0_1W~+BVmz2YD9~
zdXT0qB<esbO3gt{B9IPH_5;N?DB*xo7bp-xi3&u6Oa|Ew5(i~MkQiuDAt-!6;vjjL
zIEW8RGawg$%+)o}0X2R>aRv$_P=giX8i+<v!UQeVg(McU`HttNFpG)hWag!Uj?YO+
zEY47}QUX)8I`bDEnZhj220nqt3bH7o9y%g9P%Zp=aN8ObZy-;CYE*D_ZK`JoE)zk%
zrfCbmUJsOSLG2mvS#)%7;n#yZK%goQR1AXBBdGi|1l0wgLj}QYAW)eBYDa@It0B0M
z0T-8`1Ptnbfa+MXTln>$G8AMjXq7i8In%j?4{F_mPd6K&7JfabU>d*{em$sK8^9KR
zJ*Z(dfGzxbYIJSEMFxr8T4<WD2Q~3Q6(6Wf1vOCU+`_LPpl&U+g>PQ3XJ}?>Ze(m=
zVQy++Ze|8*P#PGSnp>D!TACP}m|K`xf)4XGGPX1`GB7bSvM@9?2DJoCP0Wl<4J|DU
z4J|D#EJ4EzCI$u;hUO*)CPu~vriP#;>;{G=rj~{VMrIZk7G@Tp^S({M+jPt=4UCP=
z%}hbZgx4EdSQr`_8yFdx8kiXvfh;pNH8U_aH#Igfwlp>enQUxgVqs!rYG!6>Y+`B&
zGRN4^(8$!>%*@2p)ZD-XBw}K2X=q_&Xl`a=Vq$Iy&QO-7mgXjAM&@S5#-`?Ae_0rs
zn;BRb8=9FIn}gkBY*}w=WN2w=WMFDwU}*$WWMpn+U~Xz;ZUH)n)d18)G&MD}G_f=>
zGqE(XG_e4=(7?dL($d(}#Msc((!dg=#@N)r#KgeB)WFQl#LxodXcN#u@0R99rbeb_
z24Is-49rXnO)M<TEzJxJ4M3hZHnyxcGBGu<Fa|pSBxGuAYG`V1U}$V^0y@P|$4t+{
z*wn<_(A31-)Wp!-6x4&UFtao;H3PZN(9+ld6dNWWk6Bunnwl6|8iAc?WNvO|Ze(s|
zWN2<_0uD1HLo-7I0}~TNLsMf*3s4AwyjqXySIkH>F*GtTG%_|fG_$ZY0|%^;fr+Jo
zsfoF<nWc$^ficL{2Bya5=Ef$5MwXVQ7Dgbmjg5`XOw2)v2;^>1YQS`(v6-P+y|Jl*
zp@pH5u`wiy%*_nVKu0568k!hdnt;qUv@kL?G&ME0FgFLqn~u4jvAL0jktN8x7DlF~
zCZNWtrGbT!v4w@PnSqg+iHR|&PB*dy83l@70}}&dkP8eAObks8%+1V9&5R69L2Y(p
z^Lhgd3j<?Ib4v?TGZO=lQAP$9rl!WmW|kI4<|Y>4&^0wPw=^;`F*G$YGXWW7WCqq{
zXkck+U~UA7N=!FdSQr?Y8k!iI8=G60Sb)4@YGz?>VrXe-W@u<(WCj`)w5Z33OVG(Z
zmSzT~mL^7)rUoGEj4dq9jEqc-&CJaW!5%Td3?<AMFf=!_G_)`<H8n6XvjB&rv5}F9
zsgaqnk%6I^5y)U8Bg1+#OLI#j6AKGtQ*%(##>_`XmL?`<rbdRw#%2~q=AiHZr5ogA
zW2R>gPGshW21X{P7T^?NXkuY$Y+z<=W^4({{UF~P8JQbdnwl6`m>C)yLJcynM@yxK
zMrNia2IdBaCKd*!;QVN8VPa`uY;I;?Ze(l<3NsS}kb{g342;c;4MAg(7KRpP=9UJQ
zX2zyQmgb<;XJ%+@YGep1#7s><+ZoOEOpJ_;49ty<EkQXD)ZDW$Fto5RGpjc-H8e9Z
z0_P$_V<SUj3quQ2BSQm2L$Kvok~%157+9JaS{Rrcm>PjSW@ct$4hjNuBLib_$!7>Y
zI1`j!%q)#8!D>t_%`8A=nyIm&sWGU4fRthN$b}eYDPm-5YGh$#VPtM(W@rd59kB!~
z7IzyPS%3-xBV!X#835Wufl(en45~+oBJ><$u7_D_U^>#+*b=Q2GXVM8)Z7wO`dgZT
z0{|R}=7uK5mIlU_;A{nwH?B7WCp~i$6Hu5K8d#c}SQwca7+D&cn}8zQ!ra8n)YuYK
znpjv^f<-J1O-#&;Elezo&CS5I6E@pWqZ_m_#nRZo+|t6*5|oxfaSN$<>Jc@MnVvbQ
zz5+$81?cQgkY$#p#s-EK<_4w~X2yo*pyQA&4UH|p3C|o<O@X5pEro(CGd4E_RR%`J
zprS^{OwZED)WF!#$im#n(A3Bf<W*={P!BH*%=OUou$i8Pskw!jp^1f&iJ5_+AvoEZ
z8Jn0|Sels`T3CYfkco+@sinD*xru?9xseGd@nb2&G1R~d)p}^DYNm%#gqrDL@x6ti
zfq|K!k%_6Hp&=wYTA~Y?>lqk<GMA~LftjI&k-0gjRJF7)GczzYGq5l+F)%j*`2<uv
z7+KVtn;Te~m{=Hs3Kq<I6+Qi%fsTweF*mocFf=zbH8KW8q!C79HvrWQ#-NO2Y-9><
z(qO5xAoWo_a;1r-hQ_GZ4b2P;K~=i3g{g%BD7Z0OONN%{X${>Q=6bNU5h(pb8%Lmx
zH)cj=mgWYQ<`!n)@)@nlHq|pTHv~0Cj1A2#%*?=zBXBN4%0y;*mS!eKhQ?;*#>PfQ
z#%2bfy3ibyW<fPJs0{(u2FvO7u*%R}&)C4!%*?>h!T?n9nSvwD*v!bt%*fQl%-qDp
z0MzsVm2#G5$OXNDsim>GfrX`+xsj;}C^|4pBg`N(H!w9bwE#7h>P^hRbsQ`_5N$=Y
z+R981T4KWsY%@JmV+#vV32g~Fk=hdEJ|hDoOH)$|3o}p{T0jaO^rFBBxhSrOl*MRX
zH`l{#zo3^*=6Z&pMvtkPnT4gXr8&5%XkcPtXl`n01iH|}$Qax%H3o&8v4NSHfrWt?
zsHtdVVQgd$swgcDEDbE`L1h7Y%$w<%8=IILnpv0_m>5_Z8W@6_foKf{Gd=W@$V?BU
z$Jo@+z!cQJumt5OLvuq=+tM6V;~If$Pqge>4|0-;xv{B*iJ7GlC{G!HoeipTQA%sf
zXvNGeCKe{<=9ZvDWNu;%ZibqI+ESpFi?IPDgwT5%^`O#%e%%d7p^qr@&Fl5(+T8#(
zM^Snk_4Ms-pw-i+#`W~=ZXh=s%|V;L>e2d)H12L-^fv10+uZ>78<2Y&_4Ms-pcNwK
zdiC_}Zea8_>e0LHwC!$S^fv10+ueXyUZC0o)Z3`1Z+8Quw^5HWXo1;If%FnkI|-QG
zB#agq=I{eHgA7az>ybO;wC`>pHIzX6uPx2%>D%2v)I8AMMm?Rn8@T!wApg^>b3sJk
zq8_<xh2E1e(?e^mfEp_#bS{YKTht?UuBqO+Afj)9n*T6c${0hjq;xKj8q=U_^RV?T
z>fz&oH0WFq(YL6lW#@v3zC}HFD2zs(3nKa!^(K%3Bea1JQ1xJLZcJh4f{4CFJuN#I
zpzKPZZ{Z0Z3Zh2m0y6VmkJzfCG!PrGLE}ltJF1}Dj<9Zig36&%&~0I88i?M2P0IdL
z)csK?Jm@wl*d{a7J#G+{XfA{*sfW<`G@|(sqJdhw6;bxTVRs_LLhLSt?2RK`A0$X%
z`%edO12*RVQ>>nWraA0#5YJ$hgT@{9zys+++JA~IoM9Rv;f&W65be-}2t8~7s|FN@
zV(dQ!ISRff9YraQy`Ge9TC6uDXV)T;n-)?0f;}qgu^waq2}>e;4-0OH254+yw+TfF
zG-3>4=Py7dArw?Un)O5%X;8D#v_p(W6GYp8iW*+fh(QrV)sM;}-d-dRBIQ476=}%T
z2|*WP=08YQBd8I79wE9!t4G_9jTVTISc9f3D23H&P&ue}C=a_zh?!71^!?wE*oI0%
zje!~pjWtw3tSYez!t_DH7iy*f*7^@B3CmolIv~!6nugUT;sp&2p!FZrP|C_Oa*8qy
z@Xl?B^{59%paueT19m;#HeiS5rREmo<X7gV=9MS}C6=Uu7e4CgjPAuA-HWZHqcpk~
zTSp191zQQm7~P8<GP)Og^kj$Ob+W_gUTpBz^PzdfgB*9P4){i7LvuZ&`4?rp*+p!0
zK+FF@XJmr+B!hOjLbhOowoHLGvOtf@1@9^Vt$9XLY6&p{bhbNWTO?Qxyloe>-4o0M
zZCVC1zyxHWHE0KoA!y$TX!ikV(<5kOC}`^!Xb&`GFNy`|cz@959_ZoChM<jb;EQxX
z`as)nK)awpd$J8pK_@1Ic3p!u|AF>>fNcV8M}{(tz#GWH9MEEQkkddIv}XdeJp}9~
zBhaQg&^`&UGRWpc&}J{tK59eI?FS&If;LQmLJPFh9JH4Xtkwjy!PF46lgbjb2Mx5R
z3*={0=$>|vP2eqWV8x(qcwh!dJ;<$~J>;g~-RGcfX`n4XraB;VVAffHmX?G30t$c7
z9%VD|{&>*9C}<xdD1waZL1&;t4n76#k_7n#qza@9veyZ;=LvdRGswfBy&+&nSn7e6
zYJirYf%iIFfVOXdA`%+qF#m&M2jm{m&JnOaFkuAR2xe%hXR1>V+R$VO+LC7ovd<8-
ze;(viP<&YGf%Xp?fzDjE1nu}X1n=Dk`5s~jXvZ07YYOQ85zyuxuqbFREC_?PR)7V-
zgdu208ffb|m<J|6ip=#CK}i+rKhQ>3ka=KfFfp3cO~9LgKrug*k~(Ow97-|=rE=)u
z$ODqhL8-ic0FyZ=mDl4+=FsgJpsWqq77N-XXaL&33%)4D1XP@YHUq*o4T3fbf;Pi~
zwmyPN9#hcq6egfezh*jk_FIFBT2SGOcf&QP+%N)_w2)nS)ZA}f58B5H+Smy49;md0
z_y={vHKfR-$$o24RR;=2(3VP2@PUrN2JPE~?YT76F*E>IXrO|g2K%i+d&voIxTfKL
zYtUY5(B5QF6o7WlLc#*nEC6kP0!2Jz8!0HQf;Ogs!U&YSK<Yr@1llzX3M)|bfs!Dp
z`>pFil^W>27Vw^G&`w>5eV~1_ATvSn0<sIVYaGM}*#X+-3ff}}vK!=X2o2h*1**^t
zN!o8+52{Mdp<9S?ZMX&n3@Dv~901y^45F#D-@2Zd4c9uLN*T0m9aN!$QX|NZpf(Js
z=>!Th7zS;V2Gy~kZNZ>683=>ag5nY)4st#S!}eQ)&JqB%d?0(LK|8ZS#~FZP7<4iN
zXcsbwhQ%=T_gjO{l7To46s;f(idt|pNC&jD8RR8|7eI9gD8@jo4yx?84umBrkXJ$R
z3gUyj3rbiZ3`%^UL<mYFAlHEs8%P~!!#0Qy$~>TL;h?e$lxT_BZ(R@BZ>@lR1QOAp
z2e;%w@s6z#4{ARef-)*Z0Vv8qO+8S71wLyCv@;)k-UC<!yr~g%=#qtwg<d^qRW_&@
z2f9KNRN{dgkJLcN*EZJ!UBCg_7X-=xpasRCB?XWMIjDvJwT?j;ds`gZ3<n)xg0~$G
z>NXJ30tc1Jpq3}8?QYN(bI@5xpwxuXBGJLu76G-nKvgpChBm0k1o;iQjg4qogPI(M
zW}rf!l$Ny-dZQZDOa@_4#(}q@K?0!C6x3n{VNk0X)K<n!MWFBp6_ucl1qI27>{J9f
zKnS^q2XZ$k)Ic3EqLYyxB<bPo&EZT%^`KkZz$bTsJ96YEBhW4$@TnW1ZTO&m3@Fq=
zmJ&)q^^_+eP?Ly+z8Pu?0&VdJr4|q-l!Tz|P*XiiLvsUD&`u*uV`I=h7c)I0GgDIo
zb3-!|OG6_|WAN@tLrY6jBMWm&&}LoG?h9jM6BBdLen$fn6C*>=ZYg6kW7B#AOVF}c
zBU8{OA2U5;V*?8l(2WS7y-<c0pnWFB#ukR44IqZbW@eU#puB2qY6&ve*xc9vv`-Fn
zNQ5D1JCTX0fq}V^33zLmp{bFjg_(hofu(_^ktx_V3<nvR8yVJvb~l5zA%ZsxnwT1x
z85x;cni`uMn1c6=m>5}Dn3xzFfc85ZTY}6nG&M6bG&MIiH8M7|GzGcG$k@!p%+kcv
zz}VQ(*ch~Z3AF3T*wWnC%)r3H%owx{(a_ukv_sVZwA<1IyiwQC%-qz#q~5~Z0(7qo
zc*m)s0cgVxczcJ5p&7_BBTExg6B7&24ocAOOpsSiKs#J5%q=X<&CHF#YAno+EKET=
zg+ZYYw%)+l!obMD$k4>d+`t69TgTV}6dC5m=B8#w1_mHkn}8f>TyJ7(WMW`s0@_Xs
z+9P6SU~FJ&X=(=A%?vW!&=|Cp&IGi*+0@(&wAaMQ$kNErz`)4R%)%7B=gttcvC+cR
z(#XKT#L^5@7g(Aa8=D%M8yg#%8JJswyl-M=VQy|{Xl7<<VPaqbaw9aT>yg6R7_=SM
z(9p~jw3`?b(*~9XX2#~mX66>A#ztVHEzK+qEQ}4nfekVlv;oP`!obK7v{B3$v@H*`
zsoT=b*Z{N-%mADeP0fr<4GfHoEG-O73_)qp$kf8f#N6E2%&6WBls-Y>YGGht1lo*k
zWMFJ=1Txv!(#+7@%)-I|w9U@|yp!12(9GD#*wD<>#Mr>x2pk$%;vOS47#J9WcF~&~
z8i01q>wuP$niyMxg3q+x(%8}fWE*+{G1W6OHnuc2vjA<>Ha0Q?hnb;?v5~2Xsga?H
zF(?WRjV(;f%ni+q%?vF}zygM#*aPia0L39F_ZVS#3pGaT!JfcKWhN$OmX<~q7KR2U
z=AcU@vF32h@G&wnHMKA>HZV6fGd6<kn8r+a28N~vpbd^@W+rB4^%h`vTNoJ_8JioM
znphfGn1Xj&8yXuL8G!bUTbdgiKoXv@kp(EtA~Kb+sgaqHfw6&wnJH-ZGuXdoh8E`L
zCZ-0amIg-Pf(SEr8XADMPn&=?or3HKIl#!s&=RD_*uca9v{MZfMHU7|7RCk^piAuy
zK%o!Xu8EqAObpE}O-&8K9s%uc2gNLw0?f?V6t$FtWIb@stA}Sj3o}bYOLJojQ%iGG
z3s5>X#0(V7;s8rTnHU&YS{j;}fHp4}gF0&#mZqRQVPI@&X>JBd|M2p%9#&w2wz3+S
z7#mm^8e3W#frHZ0z|zpv(9G1(9JC`HBxG!23fiV=VF23oZwL}G!U%5@LjyBQQ_#M4
zP~i(oUdARCmX-#lmL|ra9X24ZAreJBtT-|TmBuKAF_vN;(?y7!49m#I7KUb~76wMf
zM#i9>mY}me(XtJ~b~B@TNMUGf4$F|R{AgliXlh|%VF4;eK)b}v^b9SHEJ3?;EkHG&
z2`EJvnOPcwa;PO}E3Yv$JkTpbLlaA5Q!`@&(4Iz9a7|=jVQyw>XlQ0^XkbupW)2D>
z6JsM2a}!V=Ff})@1f@t5bM&GZGb@9(45O9&7&#fe`ZU!8?H{!;u`o9=HZ%hrv7lqB
zX8}3|!_d$Sv^mh+2xPsnr4i_42{SVz19MPDHr2B<u{1XV@7*=F06E#f5VSQFbjF35
zr7^gsHZ(G}G_e3}>^A}*76Q6C(a-`dQJI?=BNxu~dPasOW|oGaV>c{K4NXAhHONY1
zLvv$Oa}!I@MsHI+3qwl-QzK&oV<RI2OCt-&u2oAzOAAvA3qvDAQ*hyDY-Vm~Y-wm_
zYH4C&3UZ;bIcgR*)iXCRGc`6eG_^D`G&cfQx%JrM5WR*o0+qpLrk2L0rWVE^7h+n4
zZnvqSrKyEExQ;ipFb5?TLvuqz&=Dm@rbb5QV7pBW4b1A%vI@F6SkgCUZo&}3@D$EA
zTRl0AHq_G07)y~ybepZ7oJJc;F#&BzAhjb%X|vUn(`ch&o2}l0j7A%{=73im7zG7t
z4G+o*xZ7;?<TTol!kW@HTfK<|>5Vp6QIA<7lH6vihc(zqX|%!W2r9JM>do{(Cmfkt
zlG11cM=3^0kEJPq*(*bDvw@EIBDv8<#Wq_#_C^H$Mw^8hsEVRWn+<F~wh|0qqYa+*
zC~vdXLtED*HQHcpHY3dT5UDM+dQ0#gAAC(TnzqpDjSWEEOcOj!G@7>1>Os}HA>Jk$
zO<QQ7@katpH1L5{v}&Q%V`=xJHPL9=LaQg-M8jyznCW5EXJog~>IpZ|Xxc(!hxQ%j
z8y=m)EIztH4YD|#m__Z7#rx2O<IolIP#$zGJ*pt8nW#LdKI{whQI$eB2EYWN?!~&X
z2Gxa7l@JPQA=HIX_o7`;3bO*m7`%dzy#sia;5Q6>K_b!HIjFUp0~#b)FG$4d8EEKX
zmxK5as~j}$prMY%6wD1W5YwPaVHzRf3>Cy`6I2csv3N9~Xdm662HDR9NfEH1LFHkM
z5r`64a6@>|*diF|@Xbx58`MTOs6i7AH2*>=)Px9A0!fH4IS3D`0j2~cA!1hvQ3914
z-JpiFLyXefj-gvRQOaIe#6Scw%8Nm}LCrI-B(*3nwL~GbI58cvJ55KaL_4*jWb~%c
z(VIfScZQDM6k0jDI}LGvXiTYr!RSq)qxTLEpL>T#cc%^I-D$9!LQO&2mn=ZLtt>!m
zdM!Xp|G;~B%s`hd8i8)EvH&fuGzD?ZK|8H1KwAw=K)VvmK`SXOKrB=6Mg`DfPjk>3
zL1WNTOEb`(Bva6aD|66BE(?&XC1{V8G3b8CdSlQcNORC~J0p<ACZP4QV2e#bYAir|
zyTDu{&<bi3kf|o11;^%~d!{TvtEVkN62_pl*5;ta)}|o0fo(DduQvy+^s@lzFa_<8
zG6UHOx}3-mByMb^S8t(X3SPSjGS3*aJkSiZ*w7rbo)@gm0<`wp45S5gS(OoJQx@1g
z7N9k>=AgB$7T}-*?TfPjdC&;FLK39T5VU056trgxWSS9ZkC`!ObCwxsRi`;<)18Gm
zXm^JtXh)hQXw^9AVmz?vCZN4{W*{9FpdE5XAWxZrLkhIO+!$nlDd_SgQ_wXy5FMaP
z#K3`T26B%%$T&;TN_}IHQRX057=l8;2;^~d&~14pAOq?xz`+L!S2NJ%cIKd!++YLE
zz`+8FRU=SLfY+&l_d%F~oB(z+IH_2IV$2d0e1;&SEI^R}mbC<hfhB0&s39oSO+ZWB
zjX{BH2D&y0oUV+)8wpK8v2O<2j%EZ3XNc{ffHDGYYcmFg0wn!_uIV!aEr$gwF$E<o
zkVnix2?rAIpnwKPz6r>3bC83~K^KpifYP%WI1z&46Rh756x;P+rm2~pxsC;Bu_ZV)
zS%Q{anuBZuCvpo=z#GBi2BHHLc%YS}V4k4?*d`ER0g4+-a3FxpGY4fFGZ0}83Vkz>
z7UaAJihsIgHY|A!wz~@y#Wc@sSn?WZp)=hw8)#!BT3)Nq$pPIyY^Fnx%!Vbe)$7nF
zpXnKZ$~j{l^lVm7r+fy^CRnmry$;Rt8FXDVsBpo(KM!<MBxFMys2Bs~dyrbtC8nUN
zjA|F6f+|9+`}07%+d$W8ftKHaHm87g{(v^PQ29bs&|-9~_o3E<Hc-?4LR8SsY*5jU
zu|KaKe785qX&?-`BM-Cz15`JHwm%qxN?vfa0!pT!iVRdefh!V_yFsNkaTlWE+@Dtu
z*)0SruVKc6cEy7#84w0F9Kdl0x@!|u<CA$Ist&0B1=YNuO$eZd6R55QwOPP7Re~!|
z@O7D>s3&!U9=L`D)iof8f~p`;tq-caKx_~ORe&HlkSAfO9ONF*9<+K;0}B+WAR63Y
z0w)Ggk_7FW0&O6K?X?2!`U35%0&Oq^UC{~JZw1=r1={TeVuNlICwYG!Xd^wyFpx!{
zy=|Z!_MpvLp!<tKd=L%F6OavlpqPjF0Cai08EEsoIcNhd#ClL`0ptx(a{!c+A$|lo
z8??b6w4w#H8w#}R3St{L{2_q?@)rbyVjQ9wWId>80PQgYv0?kkK+XYS*akg4(3uIK
zh=T}%+N6*e2JOoOZCV4-pg@FJ06Ihgv@Zk{D+YS?AWb08fp!Jc?m|>h3_}7Bw4(|X
zW1yHb*D(d()C$UOpacU75J=(yU3?01E@;~shz9MWgLn~=OF&|v@BoDmNE{>&@+wFi
z#0Pm76mB4lcYmIU4k)lekpOZ8#Bx$L=wTg!1zn7a+{n^1&;hrxz-><I^kwS7txRxx
z8_}7;(!SC`bYrO6gQ+(M?H;$(F$M)2$vqg#J1?Min+2%f2WjeqdK;hyGD-aw6Y{z&
z;8s+<F>05E-mR#5Ju@9}Z^aB$GvVy0P|!yKcTcdim>><NdbFMixHkyuT#(-tAt{%D
z`z@f(A?aOys^pS-9Y}`{)Z-?qqmQNU0ot7i>M-K!=i|#I^#(d-pe`mceSC~=2NiNj
zJ?OG!P+5$#XAjOMG|MIRpyOpMbg*~oF*_Sn&n2Mp#~jp^$Dd88l1rc+3D8X!Mg~R}
z78VwU7WD?kX5f0=1hkL9(gL)v5p)Bnj<Fu-vIBE7BU8{8Bx5rRP!$N;OK4~bx?sc7
z(%irlv}4Z5!qC{n(A3-vw6)0)d=8MACFr6yV@p#r0~63ylSX>RmL>)U=Ej!hrl6}<
z%|Z8z85kLuSz4Ob8-gzMG%_&*9kgU*X<%S%VP*i@r)X%XW26VVAjr(f#MIabbc>vs
zj-{TVfw`rTCFn9u6C+C_(Cy@grj~}5CdP)Kt(9gVO@^ihpuHp(W(F1}2H>l)EI}K+
z%#1AzjVuf-Oh9{<%q>jKO-+r>E$TsAJVD1zSeTj`m{}N@nHidcE(!!4dSYsBZeeI{
zY-nO`Y+zvwIt0MPz}Udj40IiznV|vXUQN*bo~9N?W`-uFrY07kW}lg%p{c34CFqt?
z17mY@(0LM|8>oyeO$`i8Eet_-!0H(285kNGSeP5s8-W~UY++$x3cmf?(8A0ZWC!T-
zN&{2yu6oe@e-@xyPE0{Jpn*2P8-w<sfcD3jm>3xu8tNDt>zSB>whmfYSeP4_n45t0
z85mibTUeNzfUYw&G6F4w1ziIP+P`LI4%)i}YOY$=o0(gJHkp|ln;MuHnVW*lGBY+X
zGPN|bFfz3?1YH<tsb>HR1w#u9BXiKT3ZQr}voN$YG&eK@ZBR0@0PXHKGX~v5X=n_(
zY|qrpLdRGSbd9R9At->2%`6QJKy4`#$X&9A2ByZKt9Olb>Om&}fG*FqFt-Fnp}7&r
zgP^OsKwCKtKzHAQ@3}NJFgFM7Uo$tiFgG>_U(k*o%%CF*%nXbTK^r(t%uFDc8-O;v
znVFbb7#WzES%7*2pvBD=rY4{be3r&$Cg3~Bj6k<=TACS|8JmDMcIueufqidoXku<)
zVggzY4(dRIuCui;HnlV}GPJO;)G;*CGd3|cwgg=aYieX_ZfXWfGbRSc78Zu4Mh2j5
zy=I{Eu`DbNz?ZO^fbJazwN_CAs@@EI2{UNhsfm$+v6-O}D23>l>KU3Cfp&zM7+4w`
z8iTqdmLPdkOEY6bLlZM|P~@R`1=IsHvj8P3GZQ0I(2gchcf!)b)Xdbt9CUlEv8kbv
z4(Jpj&;`S$ppD3&J7_FHy$=%;a}!H5BMTGI4pbdOJ#%C5MamWi=B8#Qpv(SD^g!3w
znp#*If^vn438*x%v^2H^Z$~q=Fauq9s$-;QU;(<y7?jS8EKLkSF0uga>M}4eG_^1@
zH8U{>7Z9Mklnp_yGBBw(H8uk0EK36eGZWAzVgnN+3lmVI&<J!-t))5WzDLmAuNHbn
zpdHzuovs!Z=AbQDhM>(2peues7Z;m>avErpy@7?1C1^LVp`odvF*qZDHno~tf_8PA
zSQr_D4)?JzFb3TTWNL0!Zwb0h8C3e1fYOYmxtXc4g{g@ND6xV#W`-t~MuwnW=Acmx
zQ06o@GBGqXHZn0ZFb4Gy42&#HEDX#H49v_d4UA1p&5c1pY-S1CA#Mh`0oK?MbcmLP
zxv>%GHc=BZ6JrwtP=2vA1#RB0H#Gz2DML^pY-$0z{MX#v0JH<r0@5usGBpQn3^Osd
zFf=s<b$UQWv4N$Dxsj!XvAL-+=p+s^6VT0^pi40g%t6b^4Gr}Sj0}y8jLgkVK=EJ%
zK6=8;!VGjLD=4lE!1wKfuHUK$-Ju97;Y}?qK)p-Qj%3glSqsoUHbbmsm#LnKxse&@
z>P$;xLsK(jP?-nXoo@+>USmrO6H8Fy0A(g46LVv8BQqoLj!#fVH#9OcFah1l0on%&
z%IN0xmL{Mpoj^C!S{Q>gn&=rB8Jd}ZFT*u3H8KK+0;qBU-E?YUW(K;`TgMo5N1~A#
zc)L63j%Z6zkz@+GV-<Ayq=^OSB1upIWNBh(2)cgL1Qbi4<Y=I0VQ2)pme<J8%-F!#
z)C{~p9+b+BKo>@v8<-n_d*l|D;Phf<VPs|s-kob`YG_~tI+ei0+{nTLRPk6?fNuIU
z0&Ui?FgJ#DqAko!Esabqjg5_sO)QN-MTDWDxsf?&d#Z`Kv9XB}sE7bnd*(*Qpsn+U
z#`R{Pdpr$6)gowHE$FgqW2`9+Ykh2NY-9;G9CY;~=%@rkJ<zq_X2wQlpmM{|z}yU!
zlZ?&4`*Msxb(EzEXgtKi#LURVz{Je3-pt6-!V;8_v7~Jyb3@QA(}qTdh6V<fpzF^K
z^b9O53`|WxH>VjHgQ{jojbR44=^0cTm>L>_jv)lqb|ANaDl$;$80dj7$Tl-K1vLUp
z!Mi|>%#G^JL3i028d@5I%4<_SjOGNkq-<eqVQ6V?ZUU;SLD%q_>VYntwg7ERHV0)Y
zQ&2Elf_57lfzpDdkqM}!VhG-9YHk7A&<WaaZ)mJ%Y*r7-T$YxG=4OVb29}^h&p?-r
z8=D)0ZhZ$eX>>qW1sWS8SMer#mY|ad%s@vCm|IvHfsPO|umo*dHZlO!kf4Jc%s~aX
ziK&UHxq+DxsK^ALl4c6pn`>rdYG!I?YG?#1b?VJcElrI<_l<-0G=eX)$E@nmi+*E0
zj5dY^sLC?8FaTYQX>4q60vdv`G&Tn9v$wD?0);xL>M^!7F*36>0PTggG&L{-9nfPA
z+RknW+NNk~VP<5aW2$FnW@2Cf+6!xHX<%*&%H7~2Gb~IkK<UTG6x2{L(K9hIH#ap0
z-2-ZB4!K*@#LU9b%)kV+JKGGD#*9rZjX?YEEzChTR2zW`1&r$75OfEofw3jHv@ihO
z42~JNn9V>#Jqrs<(0*A<Q_#h)mLL}y>w#KQpleahjm$u0B<SQ7v?32w_nCpNC<Pr2
zU|?ZkVysiIYoKRj0lKWo0(3d5nVF#(r~p6@IwL(}BNG#2&^6AW>sHM{rM#Y@ftiH`
zc)zWgsi7HY0L;wL(!$ILbU(a>v4M#ZsF*hd-R24^){QMJ%`HJy9q7mfBV!{_HZU=*
zH!=m4;N}*lCYHwLCKe$3O+i(ZrICrHfr){kv567r5_Qlu+J^8}JM|jv^(F?Uq_^4)
zsn%$(2i@{Za;qKGrld}zy`HRAJ1D7v8hVsB+Ut#tK#hMATkX_qwAYi>Y6sQj)M>QW
zlhtYmwP&c)Xs;)$)lR)eJ9yrP<W{>0)f(;fppFE|t#;})+Ur3*0z>cx@FcX_sn=+)
zC#%&?y+(UIS*>>JHQMXRYPD0Z(GI$U)zX60Ry*h<9O^XM>y7jbNpH1NuhCvlR;!(Q
zjrMvo3lq{??bK_u*OS$1r(UDI-oOylNCkEKEx|o86C)y8?bK_u*PB_8(Q2n&qrIN2
zR=b|DDU}-S;PFqATkX13YqZCJ=50xCwG-KBAH5b7wBKs<T2N3ZK(~fLcj7^L(EWUP
z1tELM@G3#s9EhQEbk{ZPwoQznL5dhdNI2t*5vUw&TOS?`C>D+Gx*pwi4NHNj`5u~*
zPz6!ajsYqUngWRsgl<a*sT|#PjT*pcfe6_l4O0RsN<qN}x)&G1gKB^&LD7I+B}55S
zZgkf*xR`~6$>^?YB^{-_#N1RRD<!|u+@#bZh5R&y@ci7=JO%H}oSf7YTLq1R)FK5#
z0|Olc0|QN^(OW`YM{fyL8oebn5x)Hz&KSKVbo7=`rO{hLM{f!BO|8gG&R5b=!otYU
zOH9t6KQYUXS!MpTEI(#>FexXMnVeXZm_AypAkK8iKrqQY-a!tw58FV`z{0`+8Gu%`
zfR<x|cJhEQcqg3!XlbE^j)9(`DQN43fuV(=B{BdlOffJrF+~;wuU0WIHv(w`?b85Z
zV@os84jTiLdP~q27bDP(7D#$P#uyry86yc<g0+KIryvW0Ch<Yj?HCR>0j(uP5(T>!
zbY}!;B`0WgBUG*)M1!4Ti0XX<upr2%P?sBmR#|{lLorz1z!X&!6ljJ9W~lxL8Dd~;
z3c0q^Ko7Lo6>5foLA`+iNRP3F1za9<AqsfGshI(?S1n=tTnvm&!FF4MHo_Q~fwsaJ
z7=l6!6!0L8AZ!3SNE>d8fq?-iq(Dnqk;Fh2*PEFdfuu~#K<juBk|6VpOw2%$V_<5I
z8WG^IGz94~Ff<2q49vi>V_*b!n2|Zc91siaLQ{yGg(XM?jtxP#%t8GCTAYdOVX)ms
z<{%?Mmw<qLWnp1~tO6VW$RTG4Qfy*kVG6gv0JM(PKo7Ja5tL|+z=nb@Vu7jv$G-tc
z)X>Bb;ulM>&&<uBDj*antjrCK&5*4JZLR~|&0wf!ZUI`2hLF=S&@(bHK?yZ*fPzdh
z1z85l17HmHzp<$y#1<$Cy$BbSRE;5Sf{@ta)X)OtXG3#vGBPlSWGh2ss7X)?WG`p|
zGn5OVz=HLl>sMe|+tLEX$)MmhG`0kpZ(v}C5~dK_3?S*l0PILpLko}}4Gcl6At5$^
zNw9X%>NPMAN`S+_$imXV4=Mnrz)CH^%bCD@5CIkgt=0l@U>NLl(B4Y4Ty8SIu-=bZ
zwBA6^(8vUq-wcdE%8fzyU%>PmfDREh&@(UrnQm-p2)c3yE(eN!BMVEE;s6x>#+JsQ
z5CKP<ktvvI1W7XB+y}a82x<l-QGt`afu%VjSy+N@jxf+OFtEf-T#y_JT6n8tsAp^p
z&XfiQ<|wX!s<AXNK`|4QGfa@(3$h;?!r**q2)c|1>NXGs^0k2xT0DWBi?t9mG)2vI
z=J1fUGz6Ounp{G55hPKA1J}UF0F){WO~JX!$k-euI1mZl6fMbuBEb-}E*s=tC<a9%
zq_{LNMNK3Ip!fmZ`~nIJ15>d5MyO#7DbK+^2S=KrficMKh89L3_ZeU*FQK^tRMSD3
z28QM!#h_(%$le8;V+2}L40R|d{K1X|IR|us3bJZ&!ZEM_$B!Ynz`_z0U<<(ns1QIc
z9Uytn7_E>+u0Fv2H$knLAZ47TDN4xziE|T(TOc6>jx|F|(Csitt_D?M7LYV=1}>5D
zwiZB}v|x@mhXgZ~nhV6W7C?){L6KrW_2vR7f+1-LEn|WOL7@a{E!2Y|4K4V=3Mg(a
zK$1V9)&j`?v}rC7*IEGE4@*53;Jitt<^m`~L0UZcS_}1NkmN@F<^m}GAvp<OYoQ*T
zMQPDo0QsMAYoQ(-<XDO{13e0x3&gb+K({E-rnvwPe<%UYQCM3G8mNs-aBP68ZS+n7
zYIDH=v<X88wC)|XQ4bDGaIr}JmIBx-_26Q7Kw1h0pdKEmxH7T;7nt;JDS*>+JveX&
zq@@6|->81zS_%fB0v#0oAcqV<O95o9Nj+Ls1!@i$Qm3T=-NHJ07LJhtc#}Nnuo=(+
zGmroQt>rb*F&I4y2YR13=q7d0C<kZ*o-t_iFc^bQMu8k7W2$2~dKQizs3sdd3kP(@
zA?P3>L(qvvpkqKloAP0Tqi5mhfQ~DI97+V*$VJn$aInvdV@!*KPRAiU%uK=vGg3DL
z)Gfy~#7tbD5jHkMLYEP(-UPQ3u?#VT+IZl$D%QajSf7!ME+dlvL8gF)n9)X;L9Gh|
zJ#cpsG};AeXBkp!Tp2XX0U46QGO$csPZ8Eh1kogS6d~<q90SXsmJQ*aB7u$~C{jRC
zhkZ!79yG>dXo@kW42p2VokVc2grYuTJt)<K2RBj2ltEs{>?DHx0v@P^j(t+zJ%q$R
z*tg(zENEmC(v6_cKyoz5YEWa<05p;e;=nK{&J3`24M%&1;F%x;f@8=u?-_!&rehyI
z2B%+eSyfM{Q)r-PK-H0Bkkv>7$B+~bPEBBf$dO~vOcS^^AacAImU}?9qjUnnB|J!!
z(0DN@a}zg846X-2MiMhV3@Kp^sXjmqZo?W79vZGEWh$8l^*m%C9c_{c9JBPP=j(Az
zCDW;%hopZ<sS28rp?5tGwI4h_HW2kZq=q#guzDVx|1H4_C<dgS2aQaD&Juy700;>R
z3<J<OFsJ~h@q}?A#7Yo3TF-+*0n(s{G`guXS3FwJ8-Q2g7#Kk2KS%3%Lr6e?8(;(`
zf}z8^rh1l^mgdGL1_l<!pkwGjhuN5$8k&KQ`7<^%0-f`uW1?qfX=G$(Y+-6>X=Y|<
z3Ocm~E>aH_GSvf}fM;rIVP<J!X<}q<0XjIsz|a76=8379iKV%r3Fr)A(9v(8bH+et
zIf0ILG1W6LH8(diG_*7XAHxPdG0@!D!qURX)WpETz|7E+IQv1TYMNVEm>L>@NDE^l
z9aB9MBQqmo0|Qf#_bknIEc7f)Of1dJL2HOCOhD_O%s>a785)`x8XH=gTY?T3G6LNo
z4mvZ>z{uFx0^}NF3($HZBU8}A4ii(*sXd@W$;^#RjLj`A%#G^}4NO62$eDwV(y}nJ
zv@kL^wlD;H)x_8sbo8MS=wu>@h^eKyfq^CXoG=4WNW()B8i?k4pwj?NEkQ>bnwXgx
zgN`k-G%zqSH!v{+odE>WV{Q%#J4<s@(DFSaW6-HuM&@P)ptI*pLC5-l)}NT^f&2~9
z20juCa=w{?xuuD@fsrxj95G8v@BvJqbJ$GGO-u|xXD@<prv_ag4mvK&7<6=(F({@j
zL8mernwS}YP872+2OZ*RYGP?&ZfOKQps?Q97!)Q(hNecQhL(mVrbcF#mY_@B4b6-V
z&CJ0E6<U}Yg2Kqm$im3d7!)N&X67cKc(pV!u`n?<1~r^P2TkdKQiGY1xv7bfr5Pwi
zg3c{N4<i#jbI@Ul#)d|Q#zy95^+uMU<Gc+_%q>jKEQ~BI%|OQng3bdowlK3WHMcad
zG&Z+1F@l^2W@=(;Vq{`$VgWj45tJf~O^ppf7gt+aSQ;4^fm~^7VrpP%U<o?i&A`YM
zbd-~&p(*I(NDE^_b3+4gl$aWuo0?l#fX<n#H#G;H{bz1zY-DL_W^86|ZfRfw7BMmb
z9sFcqYGH0>1UhEO0Cez{C1?}4v5BPxIDML#TNoP}o12-Mf=<5EG1D_JG%>X_G&3?b
z2OatdjuG@wGu1OTHaD;^F*Y->G_*9RHvpYfXJBb&YzaQq%+TE2(8Nr~T+h(d$jrjT
z(#!;OB%=lBa&!YjV?zVb(Njhy2Bs#UQz{J%%ni+qKxavrn;KXc>zL?Sm>Zayni?6K
zSsEJ{m|KF6_cAs$wKOm>HZ!rbG%`1_(6P`nH?%M_H#ak~G%%~TFfaq1lWqw*Y0JdK
z#1N#-43u$<jLZ#<Ees66v0wzct-#z8bf%o4rHQGDfeAQqSr{9e7#bRa1|3W-jX*xJ
zFfud&=Ub2xV?)rHYDSi3pmRdajm#`f!4YY$XJP_6r_R#I*r49j2y{9s=r$iyL(qAZ
zW~L@arl3xjxt_TZ==3lX6C+bY3nTEE0~Urx#%9I_78Vx9CSczg>6sgv8k?ILnwuJ%
z7@3)3PjQ%O5H5l!|BOH}X$Crs(8AOV9G0N7JIqatz{jS7^Rl^xp^1T|sfme+iG?A!
zWJ5{IMwU9}dd8M!p!8vCZe(g?Yyc85G6ZP>l}ARF=HL>@!pOwL(8SQh%*3MJ9JB`0
zM9;#))Wp!p!qmvv#Mm5EPFR?lnpuL9o~fak3CLR(M#i8OerD!o2B37RW2R>a3MykG
z0}C^A&|#iBW_qBrWlfAN4b4qW%*{+e#+ZY`%EH(bbd;MVIMafT1vLeodTC~8Y-&*t
z@~OFrsX6GBHFFbFQ)AFckf3vDEi4TzEWsw5f%3YAsgXJ8tUOSLH?uGYWi>NHP~J2!
z1s&ZAI_u0-&k$USf{y1h0_9sBQ$0&_Q%f^L3(z5cW}wsFO!Pp9rCJynTN;>ISQ=Q?
zTbg32APhn0mVr(NG&eLdG&ctwscWuh2|B6I(#XWf(%jJ45}ayHjZMr9EI=o5ni&`v
zg3_M>=xkPF(5V}y#-QbghM)zBpj2ZDI*iiX)B;pX7=v;RXho^9alIvI6)ULrF#sJ5
zYhYk#4mzI>luInZ3;WD1Ei6n-EI^0v80eXrfR6YyH8VCbFtaoO6)y0E1g!#0^$g6-
z4a`BA+YoeKEXX=g#s#HV6H5b-cR+`x!VAuNOK{0)p=WGlY+_~#I&9U<#2j2qSs0sJ
zm|2)u7#kQF7#M-datl!LZf0p}X=!Y3WN8WtIdd~JQ&Z6Krv}C*CZ?c>0@c)}21cL~
z!OYCWLdVEN&jfT@FsOtvGqW%Tr3woJ3qw<5BU2;8dP^g719MOb04jqFEKCh7Oie*&
zxq|9nV<SUzV*^V|Q!_IYaA5{IK@xPPuc?K(rKvf{|CZ+FpoMK_=9Zu`4Rm;*fq|j1
zfsqmDpjXi7Ajr4q^`@nf1!x^5=wQcsV`EcL*<xU72J(f8nWc$=p&7VzH31#_Yi4F)
zVQ69oK8w`IzyNeCpQWWC_^3FL$(EKDhGr&~h9H}az=tK9fyxt8Ljw~N6H8OjxqU{U
zmWYYDCFoR1Qxi~pn3#fs3Up$og;~9&5y<nP!)VP64Nc5J=hA`vWo`gUdM0M(pk{(0
zs5}IvC(sFXhDM+|3gkjVP(5m4Vqj(tO3UCT0(x|Sl7oe*nISm$7#bTHf#S^4!qUXh
z%+Soh$k?*p*bJ1pEkP&YnVMNzm|B>a8|i==0MH}?I@%807z5d3YG7z#VE{US8l(xc
z@WIkxGc`2=mHj5>7NBZW$4t+{)YQ}%RQVfPni`nbTk4qUfmY{O8X1`zSeSyEJXkWM
ziJm1|JI2D$+`tTUM5Kv{fhA}H#6-`+)WXcn(hwB5pgI@S9Kc8mXvLaoy`GVYAt;4`
z&R{h(wE&eX#-Lpc7M8{ahGynQ;N}^+h`F9A=tNyJLlYw-Q)5d|vbQuaGcq(b1+AJk
zvM>WDa?nYzpz_=hbYvj734@gJ!TH`?uin(i(9qNvbnv4QsO|(EVhL)$n3$TH8=IMe
z7MYvsnOPc`fzIeQH#ajeGy<DMVY3@vTGS6rvm0u^p+UVKs3k=AW;eXmU2kY+G62nP
zP!0pPy6eqAr<ogpdIumeV@N8ed9xed>aHJ{W;eXmT|Y3*Zg{J^eqfs22H>`WrI~U4
zz%;wzt!~hQ*#T&F!&}{;^fv&_ZfN;qs#iZS&2D(ByMADr-Nrg5df--fy&<SGP4{Lu
zywzQgJT64PW;eL@1+}{C2d3E#Z*|uXOtTx_>aHJ{W;eXmT|Y3*Zg{J^-eN$S-SAd-
zJ?Pd4`Zv4bt?v4PX?DX~-5~o1pxF&?b!(Xu-Rz!kcytQ0$bR{+>g@8;^Pg<L#Vk3$
z`t1~EUS5<1Z}T5)-^{KhV5*~3l$e*Es$>;ypkrzfJD-2&EoK=ZrCMZhLj!}@`4`pw
znS~)H2`iKpD}*H$W#*R_E4U>lm*f`}&)1JuU{RmH;q4S=<@pb^{F$W%D-tU*i<PXZ
zl}a*8azN+P%>S@+GrOpgf`%&S6dHuRAoFW$V|A2r5|dJMl&q8>3Ryr3=O5JcXEvB_
zzurw8Y^*?RY^_eU5{B8Kd8xStIr){jsd*&|L5U@)Ak9k1zA!b2MX>~{4zP8;V4Jw+
zD=<%GW(~%$3hUK+czlDY9&C%*{0+aSFtdT}5}SWt%b%Hb+7>s~dJOxBT)v3M1w@*V
zn_7~QKmVkrKQqt#1N(0=>oOUd&p!~Qz#=yN))qHWMxFVN(F!c0_0>w1N><U)kTv4q
z`6$qO4bWW&#-NK5Oh5!^K__Th9JB-sgh2~}L036if^J~~jdz-W2DHs|j6rK;K^K6U
z=z(u6(E;6k2f7E_5OmEp=&o7NWojTv6VSERCYE|8^*W{?1*V|OXidNiuR&Mdfv%PW
zxyTT79XUiV=z1Q|s0nCB7_>S7<PIv_A6u_yq+@6VayPz3^PqcJ!B>VF>6n9@V+^{#
z)fjY}q!H*MRgk+u*OY;L2)gAFa>XQQ1jRrH<O9&EVGsu0*$KHD)fgN!hI;0Zt9e0J
zLK+%?78aXhy+D?B_s7;7fo^vPt=|P*Q3(nM&~j!YkS9U+<v^VYx~m6tVJY?3%!3xa
zSn5Cm5EQkbK(o|=1QIBDfs!8VB2&<{JD~OGps1(T{jnhXL1r3&ZiE550~CRX@BnR8
z0{I@at{Fm8_x{*=NJarA0MON?pcDeakhSF?hk?cyK|?#B?HiDQ067j6KcLJ7i7-&M
z1?34)K!WsucKw0^2{eETz9I+r{jnhbgZv1>peuerBZHV1$U?#dWHbbWc1a+o7f_l(
z+`bB0vjlPu2t%&E(E%lGtZU{$SF;*{vlb{IU@>f<gL;81$Rv>GK!pw{FhE!AfIJCu
z4alPq8$srP0tezUkRDJr0|gvN9;Ob&24Rqo&2;KbLAOThff6^!a?rvLkinq7GHBcq
zJT9sOx<AnnbO$LY$3rqVD6LZC{@8j@!UADXLI)*6&_o=_d7#7w@*c=FAU^2Q6p$-H
zm(_wSH-prjmFV@ddrp2*Vvd4Ger{%RW=blw`b0Z44pF_Rpx30>^n<H7h57-lD0EEg
z2ehKlGpZlZib4l;8;%aBoEVsj!pNjv50s@~*$9+VjCJT&QNVVt!O}n7Dhlw~0w7}k
zZ5eNNuK5pSyxCbt$<YuP4S|ss0%<tvT;If;RHAEK^a>YKGo-p@1y{H86Q4%12#>UY
z9`)~N2#kgRatMIN2|&$$5C(M%KwSk;mjQGMD~JzkmVtUTpsoX`O97#&(_gIzb-y5E
zK%h|$P&<^a{Z)|vLH-1Fg+P7;VS4sg>-CIvK%-Kio-e4MX$T(S0(BWduA+T^wcbDv
z<YmxW9#GVRdV(O!L9K9550U2mRq*B%kc}YQK^T<yK#7pj{;FGQE-|&I4$`<b%E&J^
z{oo2z1Ul?#jBVHxJhm-pUs6<>s)Lt^MIOoy&d4uU2q{X<OHuI2%u6i>+oQ#cV!-?h
z@24=!$)f1<0CmLC^}*a{irak&C?;cdDfR($$DAAm=ls&VlA_GiVkMODLXm=aAcC+p
z;6TD<S5jhLW+J*RAi?<yKTcuRrqKAjl>DM1bmPH-5aVqqasB+jLO*6v9^?=L3yIHP
z`f&=gdJH9ID>)XWr{<Mp=Ak<tDhzRc2!&RZCSe#~nglVLLf4lTmlP%DV8kp`7-9v5
zaSJjFs|A@5<6|icoT}8Kq{Pgu#5}ab2^F8e;mZ_eooI^ea7rvnN=(T|%VaQ7NdAhX
z%!bsQ#G+Dk3m}42GCw`DG#539oKkZ@f)Mj5i)5$NqTJFHv_uLKghX;EWx<nCT7n+I
zP8p>okjSO5a5&?~EQ3}!obh9pn}0;ppIJSeGItjxR%Pa(g*sRa66ln<{9~#gvjnQk
zK|)dxmq$_N^3t62#3J-;>jV*nL}@%l79btkk6bV#9p(=SqA&_=$xB2}md=TJi75~-
zP?jp4Gct2hQ6m>D1aUZpajWCUEQS`hI)2O&)QDT>jLf`59R=US<ivc1V8<X7FHBe5
z>?%SPTk>=AbCb|hkTXOS68x0aUC#N%C5Z|_naOCy4pe;p{Et(Zbtx;>oQv`kOEA0u
z7KHd9h_cj)QLj70s&&fB9p}mdjM@Yu21%O~hDudxat21IfCV9;LRnqtlA4#BSd@*D
zDwUvu5a&~7zH4%6VoH7ys`*esi1~>W#j0zLLU3YE85TPb5)gYRiw4)?l6;IdIYf{e
z(cqSumy?*6f*MRvL5TAyiw5`9qTIy1N>uZqf)Mj5%LDF3sj10m#WO?<Vmf7ok9%oi
z38+(xR`$SzArU}X-Q`|dnTX!40E<Bkr!4e6O7qeai_k(JDhLT5%FOpnPQ^?;P(g_K
zl=X=`^HR`DAdnCwXeg?Br!(GgMQsm)M4-(<3InAGTcAJ$A%Q|!lJ_hwN=!v-ZbHN$
zrc>73@hnNqK}#@TA&A+OrFE~w+(e9u93%*-#e*p-ki8NM&^r%ai3O0p17)30@5HLa
z?2KZJz6nemVh3d@-8(g}60MX02|-diW$DGcv^+7h1hoW)h*2X>eG*H`(DNu*4B~Xk
zDnFmpq{O^@v_3yXaQ?<GQ<$|=C`vLunW@PcC8>GEC8?R{mLN$%tfH(Y@yRU7D8(FH
zg9$?di?Z<x-^84h%rf*rLYOEdt|?2TzKJ;{Xo(ag1aUlNdCWJlv?#MA6Mb+5E(~!#
zWf=i_X&6dJ6e30y)4>;zp=L8*uo%R2%Bm~Dzpip99mVN_e_a(IJvhozrXT!*G?ajW
z2}2^6vVix?FDg$&t5hIjke~^qC>Q(ZqL=&rxsW26viuYPxi=2Y-7ryz%PFg}0#b`g
zQ4<VE1Y$B}As&#A*)D^KK}@GGWb%tjO4Ae3+8_Z?QHTu`CHMJ(voOc<XZbNh$MPww
zRD$wzF$-ddASAI<=5)gfKV}h>tU4bgBsTx2hCj19MP^Sg+~F#YVl+rZ5>g5fF~fvs
z>L)lcGp|I!r!*P8E=NdEA#kP_enM|`7k+Yuwz?^+K!P*#(i02vi_rRlaA8QQq-?k}
zI48d>F&iU<Afk}qq1=L0jNU%T+SEMgJPKtscyK`?dP@f+M2!|sa8ag$Phws+S_1(l
z3<(~}lD~nA8*0v)Zs6i321)*u^-O}xQ&UpWnt)(2NXSq&R1{pESyGi+gjpgZNkEb(
zWyNv`>|#%piX0{iu_2kFsutxMVpLm@ZW4vqL|KG{rYGj159x!&sF98squo$P-KR4~
zyFmxt(<us|(7eo&)D#8p%)IoJe6)!;R5?f>QI;Pr-gT8itqv~Ub(NVv^YavDb;`yt
zLW@e%OVOKbP(g^xDJ!i*tCCW)Gcmi=FmXuxjWR!kCFYeTmY_ATpn_mOz?N;8<6gEw
zL`wtLQi>df$kfClw8>u3k`1sh*a2G36eTtz14C1#+WC7|=CaGoKdb4_EJs;$)X2cd
z2(>v15}}ey4U}r<uZU1!p^{4tFkEV21aT>)VPIg29tH-c5R)m5Eh9sv+WCx8R0{(`
zV|14q8dJ%opxEk*q?$_&Owe6wU;=R|rLkp*VX`5WOg6B<aI*!K+>BweA+=04M0c~H
zA=u5ZqRtYjs9Qhz0V~UVgPoh%=L#sGf%);DbJ-PCok4TEd8sK1A*sbBdJ2*Gr3%T3
zc?!iPl{u*jB^jB;3MHu(^8<PnSZwD%5Yk{5od2MWgIRd~h6A^lS->K^^Uw7vumsOP
z_$ilNcya?5>wJqo1r}AXoZ$S1J_Qz|`2y@ynOWxV>Qi8`=-+VY7IXiGL$^W19T0IB
zMBD=r_d&!15b+R1JOUAqLBtaf@f1Wn0};<b#0wDd5=6WL5wAhS8xZjpM7#qL??J=|
z5b+U2d;$@lLBtmj@fAdT0}<ar#19bh6GZ$15x+si9}w{uMEnC0|Czft9AfF;aEK8^
zFo6hW5WxZ>SV06Eh+qd193X-dL~wx!ZV<r(B6vXrABf-w5dt7W5JU)p2w@N*0wP2~
zgcyhr2N4n=LJ~wsfe2|3Ap;_0L4+L3{tbuZS=1(|q!}0_C0iIK>KY^^n(LaRnk4Ba
z8l<M^rlp!&nk1T8m?v8%&Sz}h%>Iiwr58V`vpW)}R8iWGS*hK@qo>`$qqp6`qp#h;
zqrct3V?w)w$HaCAk4fzg9+TT0Jf^fecuZ|~@R-)_;4!`3!DB|dgU8Hv2aj3p4j!}H
z9X#f=J9x}(ckr0k?%*-M-N9o)yMxEVb_b6|?G7G`+Z{ZXv^#h#ZFlfk*6!f3yxqZL
zMZ1H?%612jRqYNQtJ@ts*0ei#tZjGjSl900vA*5GV?(=x$HsOCk4^0k9-G@8Jhrqu
zcx-KV@YvSw;IX~k!DC0egU8Nx2ajFt4j#MP9X$55J9zAEcktNP?%=V%-NEBPyMxEU
zb_b6`?G7G?+Z{ZPv^#hlZFlfE*6!eOyxqa$M7x8>$#w^iQ|%5Or`sJo&a^vtoNagT
zIM?pralYNb<3hWG$HjIBk4x<i9+%r4Jg&4mcwB9F@VM6Q;Bmd(!Q)1|gU8Kw2aj9r
z4j#AL9X#%|J9yk}cksB^?%;91-NEBQyMxEWb_b6~?G7G~+Z{Zfv^#h_ZFlf^*6!f(
zyxqa$MZ1H?%XSBkSM3fSuiG6w-n2V-ylr>zc-QXW@xI-`<3qcH$H#UDk5BCm9-rGC
zJifF$czkVl@c7p5;PJiP!Q)4}gU8Qy2ajLv4j#YT9X$TDJ9zwUckuYv?%?si+rfje
z-@$_sL@<E}W)Q&wB3MBL8;D>B5gZ_b6GU)<2yPI;10r}q1Rsdt2N41wLJ&j<fe2v`
zAp#;qL4+8H5C;(wAVLyENP!4x5FrC1WI==+h>!;n3LrueL@0p>We}kPB2+<y8i-H_
z5gH&u6GUi%2yGCd10r-mgdT{{2N4D!!Vp9lfe2#|VFDsdL4+BIFb5G9Ai@$vSb+#@
z5Mcu%Y(az_h_D9{4j{r2L^y#6XAt26B3wa)8;EcR5#Vt41hKq8gg1!r0TI3+!Vg6F
zgNOhS5eOoJKtwQz2mukHAR-JzgoB6(5D^I?qCiA6h=>6Zu^=K2M8t!L1Q3x3B9cHv
zGKfe45vd>|4Me1ahzt;s2_mvUL^g=X0TH<%A`e95gNOnUQ3xW6KtwT!C;<_rAfgOJ
zl!J&05K##tsz5|Fh^PS(wIHGnMAU<b1`yE*BAP%%Gl*yb5v?Gi4Menqhz=0Z2_m{c
zL^p`&0TI0*q7Ov$gNO+rVj_r`1R^Gbh$$dqDu|c{BBq0g86aXNh?oT;W`l@1AYv|v
zm<J-}gNOwnVj+lF1R@rLh$SFmDTr7GB9?=Q6(C|Ih*$+8R)dH&AYv_uSO+53gNO|v
zVk3yy1R^$rh%F#uD~Q+zBDRBw9Ux*Sh}Z=pc7upLAYw0w*asr^gNOql;vk4P1R@TD
zh$A54D2O-)B94QI6CmOwh&TlzPJ@UuAmS{DI0qumgNO?t;v$H+1R^ejh$|rCDu}oS
zBCdmo8zAB)h`0qJZi9$BAmT2FxCbKcgNO$p;vtB51R@@Th$kT8DTsImBA$bY7a-y#
zh<F7eUW14?AmS~Ecn2chgNP3x;v<Oo1R_3zh%X@GD~R|8BEEx&A0Xl<i1-B}euIcV
zAmT5G_y;2XGj=<8FoB9c5Wxf@m_Y;!h+qW~Y#@RiL~wuzP7uKbBDg^W4~XCe5quzm
zA4CX%2tg1b1R{h%gb0Wb1rcH(LL5X$fCxztAq66&L4*v5kOdKPAVMBQD1Zn>5TOJj
zltF|Fh)@L)Y9K-#L}-8rO%S04BD6t-4v5eN5qcm(A4C{{2tyEI1R{(<gb9c+1rcT-
z!W=|cfCx(vVFe<rL4*y6umurzAi^F*IDiO85a9$OoI!*Oh;RiFZXm)PM1aHD6U6cY
z5#Aue2SoUS2tN?v4<Z6UL?DO=0ujL=A_PQ)f`~8>5e_0EKtv>nhyoGOAR-1t#Da)8
z5D^a|5<o;Eh)4nv$si&HM5Ka<G!T&vA~HZkCWy!a5!oOj2Snt8h&&LH4<ZUcL?MVM
z0ujX^q69>gf`~E@Q4S(1Ktv^or~(nyAfg6D)PjgQ5K#{z8bCxNh-d;4%^;!$M6`m4
zHW1McB04}sCy3|*5#1o72SoIOh&~X}4<aUjh>0L#5{Q@#BBp?dsUTt+h?ou{W`Ky9
zAYvAXm<=N4fQY#uVjhT?4<Z(Th=m|x5r|j}B9?%Nr66J%h*%CHR)C0=AYv7WSPdf9
zfQYpqVjYNB4<a^zh>aj(6NuOhBDR2ttsr6>h}aGyc7TYTAYvDY*bO4~fQY>yVjqau
z4<ZhLh=U;F5QsPoB94HFqaflKh&T=+PJoD$AmS8=I1M7sfQYjo;v9%L4<asrh>IZN
z5{S4ABCddlt03YUh`0_SZh(lJAmSE?xD6uifQY*w;vR^&4<a6bh=(BJ5r}vUBA$SV
zry$}Ph<FYnUVw;~AmSB>cnu=nfQYvs;vI;14<bH*h>sxR6NvZ>BEEo#uOQ+Zi1-d7
zet?LdAmSH@_zfcdfQY{!;vb0k&(!VU!3-+?Km-$rU<MH^Ac7S{uz?76=KT&H9Lx*s
z2zEE;dnG(#)8injUy0gxZ2XeTF3g!&Qd*R1qn}|iU-8f_W~u(%#7AuXxrvWK#1jzl
z6hu4&5zj%y3lQ-VM7#nKuR+8c5b+j7yaN&MLBt0T@exFP0ui4<#1|0p6-0ak5#K??
z4-oMaMEn8~zd^(w5b+m8`~wmH*}8KR+52-789@XSh+qa0EFgjvM6iJfb`Ze<A~-<=
z7l_~n5j-G*7ew%Z2!0SD03rlIgb;`j1`#44LKH-Zfe3LBAps&JL4*{DkOmPlAVL;I
z$bkrX5TO7f6hVX%h)@O*Dj-4?M5wXv&rMWkSDK)bWMYtNkz#7BYhY+<s%v6lXsT;r
zX_%;+0y?YP(A?bA(kKPmmn2Flq%TR7Qczz~cK+j;o7t`R-)Y;-9$<ub9Ap05otxQ(
z858F-?%K>QLQVp+Onk(qGdef{8cd+w;DoW6aZ<9GnSpMKg>kB`iCLntuBBmenyyi5
zN=lkxqFJhGGHh^yD5a1DMU+x-g4!SaS)DyY4u4Xr5z=5+A}0yO3u~~OjwT`6CZR;*
z)KrUPb8}r&bE7m}69dykT?>muW8IXrR0Biv)T9&>Ls$|bN+~1>5v3HIgyzo*QDEWP
z-?KEAy<Js<7=7wG3eo#NUdm;E%CukMTrT?`Wffwy&3E{e%U*{ssd^KaNFf8X3X|9I
XvQ3}2)lG0dXuOtv{-s@;*>3>=s!PnN
diff --git a/main.py b/main.py
index 040d1ba..196136d 100644
--- a/main.py
+++ b/main.py
@@ -31,341 +31,328 @@ table_list_UK = sql_t_UK.list_db(verbose=False)
-def combined_graph():
-
-
- male_homicide_rate_query = querys.male_homicide_rate()
- male_homicide_rate = sql_t_UN.query_db(male_homicide_rate_query, table_name="SYB67_328_202411_Intentional homicides and other crimes.db")
+def un_crime_line_chart():
+ # Query the crime data
+ crime_rate_query = querys.overall_homicide_rate()
+ df = sql_t_UN.query_db(
+ crime_rate_query,
+ table_name="UN_Crime_Continents.db"
+ )
+ # Ensure 'Value' is numeric
+ df["Value"] = pd.to_numeric(df["Value"], errors="coerce")
+
+ # Get a list of unique regions
+ regions = df["Region_Country_Area"].unique().tolist() # Convert to list
+
+ # Create a line chart for each region
+ traces = []
+ for region in regions:
+ region_data = df[df["Region_Country_Area"] == region]
+ grouped = region_data.groupby("Year", as_index=False)["Value"].mean()
+ trace = go.Scatter(
+ x=grouped["Year"],
+ y=grouped["Value"],
+ mode="lines",
+ name=region,
+ visible=(region == "Total, all countries or areas") # Default visible
+ )
+ traces.append(trace)
- education_rate_query = querys.education_rate()
- education_rate = sql_t_UN.query_db(education_rate_query, table_name="SYB67_245_202411_Public expenditure on education and access to computers.db")
+ # Create the figure
+ fig = go.Figure(data=traces)
+ # Create the dropdown menu
+ buttons = []
+ for region in regions:
+ visibility_array = [False] * len(regions)
+ visibility_array[regions.index(region)] = True
+ buttons.append(dict(
+ label=region,
+ method="update",
+ args=[{"visible": visibility_array},
+ {"title": f"Crime Rate Over Time: {region}"}]
+ ))
- merged_df_male = pd.merge(male_homicide_rate, education_rate, on=['Region_Country_Area', 'Year'], suffixes=('_Male_Homicide', '_Education'))
- merged_df_male['Gender'] = 'Male'
+ # Update the layout with the dropdown menu
+ fig.update_layout(
+ title="Crime Rate Over Time: Total, all countries or areas",
+ xaxis_title="Year",
+ yaxis_title="Homicide Rate",
+ updatemenus=[dict(
+ buttons=buttons,
+ direction="down",
+ showactive=True,
+ x=0.02,
+ xanchor="left",
+ y=1.15,
+ yanchor="top"
+ )]
+ )
- fem_homicide_rate_query = querys.female_homicide_rate()
- fem_homicide_rate = sql_t_UN.query_db(fem_homicide_rate_query, table_name="SYB67_328_202411_Intentional homicides and other crimes.db")
+ return fig
+
+
+
+def gdp_per_continent():
+ # Query the GDP data
+ gdp_per_cap_query = querys.gdp_per_cap()
+ df = sql_t_UN.query_db(
+ gdp_per_cap_query,
+ table_name="GDP_per_capita_continents.db"
+ )
- merged_df_female = pd.merge(fem_homicide_rate, education_rate, on=['Region_Country_Area', 'Year'], suffixes=('_Fem_Homicide', '_Education'))
- merged_df_female['Gender'] = 'Female'
+ # Ensure 'Value' is numeric and remove commas
+ df["Value"] = df["Value"].str.replace(",", "").astype(float)
- unemployment_rate_query = querys.unemployment_rate()
- unemployment_rate = sql_t_UN.query_db(unemployment_rate_query, table_name="SYB67_329_202411_Labour Force and Unemployment.db")
+ # Filter the data to include only GDP per capita
+ gdp_per_capita_df = df[df["Row_Descriptor"] == "GDP per capita (US dollars)"]
- homicide_rate_query = querys.overall_homicide_rate()
- homicide_rate = sql_t_UN.query_db(homicide_rate_query, table_name="SYB67_328_202411_Intentional homicides and other crimes.db")
+ # Calculate the total GDP per capita for each year
+ total_gdp_per_capita_per_year = gdp_per_capita_df.groupby("Year")["Value"].sum().reset_index()
+ total_gdp_per_capita_per_year.rename(columns={"Value": "Total_GDP_Per_Capita"}, inplace=True)
-
+ # Merge the total GDP per capita back into the original DataFrame
+ gdp_per_capita_df = gdp_per_capita_df.merge(total_gdp_per_capita_per_year, on="Year")
- combined_df = pd.concat([merged_df_male[['Region_Country_Area', 'Year', 'Value_Male_Homicide', 'Value_Education', 'Gender']],
- merged_df_female[['Region_Country_Area', 'Year', 'Value_Fem_Homicide', 'Value_Education', 'Gender']]])
- combined_df['Homicide_Rate'] = combined_df.apply(lambda row: row['Value_Male_Homicide'] if row['Gender'] == 'Male' else row['Value_Fem_Homicide'], axis=1)
-
-
-
- merged_df_unemployment = pd.merge(unemployment_rate, homicide_rate, on=['Region_Country_Area', 'Year'], suffixes=('_Unemployment', '_Homicide'))
-
-
- fem_homicide_rate['Value'] = pd.to_numeric(fem_homicide_rate['Value'], errors='coerce')
- homicide_rate['Value'] = pd.to_numeric(homicide_rate['Value'], errors='coerce')
-
- fem_homicide_rate['Num_fem_homicide'] = (fem_homicide_rate['Value'] / 100) * homicide_rate['Value']
- internet_usage = querys.internet_usage()
- internet_usage = sql_t_UN.query_db(internet_usage, table_name="SYB67_314_202411_Internet Usage.db")
- merged_df_internet = pd.merge(fem_homicide_rate, internet_usage, on=['Region_Country_Area', 'Year'], suffixes=('_Fem_Homicide', '_Internet'))
-
- # Combine all data into one DataFrame
- combined_df = combined_df.rename(columns={'Value_Education': 'Education Expenditure (%)'})
- merged_df_unemployment = merged_df_unemployment.rename(columns={'Value_Unemployment': 'Unemployment Rate (%)'})
- merged_df_internet = merged_df_internet.rename(columns={'Value_Internet': 'Internet Usage (%)', 'Num_fem_homicide': 'Number of Women Killed (per 100,000)'})
-
- combined_df = combined_df.merge(merged_df_unemployment[['Region_Country_Area', 'Year', 'Unemployment Rate (%)']], on=['Region_Country_Area', 'Year'], how='left')
- combined_df = combined_df.merge(merged_df_internet[['Region_Country_Area', 'Year', 'Internet Usage (%)', 'Number of Women Killed (per 100,000)']], on=['Region_Country_Area', 'Year'], how='left')
-
- # Ensure all colunms aside from Region_Country_Area are numeric
- for col in combined_df.columns:
- if col != "Region_Country_Area":
- combined_df[col] = pd.to_numeric(combined_df[col], errors='coerce')
+ # Calculate the percentage of the total GDP per capita for each region for each year
+ gdp_per_capita_df["Percentage"] = (gdp_per_capita_df["Value"] / gdp_per_capita_df["Total_GDP_Per_Capita"]) * 100
-
- #print(combined_df.head())
-
- # Create Plotly figure with dropdown menu
- fig = go.Figure()
-
-
- # Function to add trend line
- def add_trend_line(fig, x, y, name):
- # Ensure the data is numeric and drop NaNs
- x = pd.to_numeric(x, errors='coerce')
- y = pd.to_numeric(y, errors='coerce')
- df = pd.DataFrame({'x': x, 'y': y}).dropna()
- X = sm.add_constant(df['x'])
- model = sm.OLS(df['y'], X).fit()
- trendline = model.predict(X)
- fig.add_trace(go.Scatter(x=df['x'], y=trendline, mode='lines', name=f'Trend: {name}', line=dict(dash='dash')))
-
-
- # Create Plotly figure with dropdown menu
- fig = go.Figure()
-
- # Add traces for each variable
- fig.add_trace(go.Scatter(x=combined_df['Education Expenditure (%)'], y=combined_df['Homicide_Rate'], mode='markers', name='Education Expenditure (%)', hovertemplate='Country: %{text}<br>Year: %{customdata[0]}<br>Value: %{y}', text=combined_df['Region_Country_Area'], customdata=combined_df[['Year']]))
- add_trend_line(fig, combined_df['Education Expenditure (%)'], combined_df['Homicide_Rate'], 'Education Expenditure (%)')
-
- fig.add_trace(go.Scatter(x=combined_df['Unemployment Rate (%)'], y=combined_df['Homicide_Rate'], mode='markers', name='Unemployment Rate (%)', hovertemplate='Country: %{text}<br>Year: %{customdata[0]}<br>Value: %{y}', text=combined_df['Region_Country_Area'], customdata=combined_df[['Year']]))
- add_trend_line(fig, combined_df['Unemployment Rate (%)'], combined_df['Homicide_Rate'], 'Unemployment Rate (%)')
-
- fig.add_trace(go.Scatter(x=combined_df['Internet Usage (%)'], y=combined_df['Homicide_Rate'], mode='markers', name='Internet Usage (%)', hovertemplate='Country: %{text}<br>Year: %{customdata[0]}<br>Value: %{y}', text=combined_df['Region_Country_Area'], customdata=combined_df[['Year']]))
- add_trend_line(fig, combined_df['Internet Usage (%)'], combined_df['Homicide_Rate'], 'Internet Usage (%)')
+ # Create frames for the animation
+ frames = []
+ for year in gdp_per_capita_df["Year"].unique():
+ year_data = gdp_per_capita_df[gdp_per_capita_df["Year"] == year]
+ frames.append(go.Frame(
+ data=[go.Pie(labels=year_data["Region_Country_Area"], values=year_data["Percentage"])],
+ name=str(year)
+ ))
+
+ # Create the initial pie chart
+ initial_year = gdp_per_capita_df["Year"].min()
+ initial_data = gdp_per_capita_df[gdp_per_capita_df["Year"] == initial_year]
+
+ fig = go.Figure(
+ data=[go.Pie(labels=initial_data["Region_Country_Area"], values=initial_data["Percentage"])],
+ layout=go.Layout(
+ title=f"GDP per Capita as a Percentage of the Total for {initial_year}",
+ updatemenus=[dict(
+ type="buttons",
+ showactive=False,
+ buttons=[dict(label="Play",
+ method="animate",
+ args=[None, {"frame": {"duration": 1000, "redraw": True}, "fromcurrent": True}]),
+ dict(label="Pause",
+ method="animate",
+ args=[[None], {"frame": {"duration": 0, "redraw": False}, "mode": "immediate"}])]
+ )],
+ sliders=[{
+ "steps": [
+ {"args": [[str(year)], {"frame": {"duration": 1000, "redraw": True}, "mode": "immediate"}],
+ "label": str(year),
+ "method": "animate"} for year in gdp_per_capita_df["Year"].unique()
+ ],
+ "transition": {"duration": 300},
+ "x": 0.1,
+ "xanchor": "left",
+ "y": 0,
+ "yanchor": "top"
+ }]
+ ),
+ frames=frames
+ )
+
+ return fig
- fig.add_trace(go.Scatter(x=combined_df['Number of Women Killed (per 100,000)'], y=combined_df['Homicide_Rate'], mode='markers', name='Number of Women Killed (per 100,000)', hovertemplate='Country: %{text}<br>Year: %{customdata[0]}<br>Value: %{y}', text=combined_df['Region_Country_Area'], customdata=combined_df[['Year']]))
- add_trend_line(fig, combined_df['Number of Women Killed (per 100,000)'], combined_df['Homicide_Rate'], 'Number of Women Killed (per 100,000)')
+def large_grouped_bar_chart():
+ # Get crime dataset
+ crime_rate_query = querys.overall_homicide_rate()
+ df = sql_t_UN.query_db(
+ crime_rate_query,
+ table_name="UN_Crime_Continents.db"
+ )
+ # Get economic dataset
+ gdp_per_cap_query = querys.gdp_per_cap()
+ df_gdp = sql_t_UN.query_db(
+ gdp_per_cap_query,
+ table_name="GDP_per_capita_continents.db"
+ )
- # Get unique countries and years for dropdowns
- countries = combined_df['Region_Country_Area'].unique()
- years = combined_df['Year'].unique()
+ # Ensure 'Value' is numeric
+ df["Value"] = pd.to_numeric(df["Value"], errors="coerce")
+ df_gdp["Value"] = df_gdp["Value"].str.replace(",", "").astype(float)
+
+ # Group by Region_Country_Area and calculate the average Value for each region
+ crime_avg = df.groupby("Region_Country_Area", as_index=False)["Value"].mean()
+ crime_avg.rename(columns={"Value": "Avg_Crime_Rate"}, inplace=True)
+
+ gdp_avg = df_gdp[df_gdp["Row_Descriptor"] == "GDP per capita (US dollars)"]
+ gdp_avg = gdp_avg.groupby("Region_Country_Area", as_index=False)["Value"].mean()
+ gdp_avg.rename(columns={"Value": "Avg_GDP_Per_Capita"}, inplace=True)
+ # Merge the two datasets on Region_Country_Area
+ merged_df = pd.merge(crime_avg, gdp_avg, on="Region_Country_Area", how="inner")
- # Add "All Countries" and "All Years" options
- countries = ['All Countries'] + list(countries)
- years = ['All Years'] + list(years)
+ # Create the grouped bar chart with secondary y-axis
+ fig = go.Figure()
+
+ # Add GDP per Capita bar
+ fig.add_trace(go.Bar(
+ name='Average GDP per Capita',
+ x=merged_df["Region_Country_Area"],
+ y=merged_df["Avg_GDP_Per_Capita"],
+ yaxis='y1',
+ offsetgroup=1
+ ))
+
+ # Add Crime Rate bar
+ fig.add_trace(go.Bar(
+ name='Average Crime Rate',
+ x=merged_df["Region_Country_Area"],
+ y=merged_df["Avg_Crime_Rate"],
+ yaxis='y2',
+ offsetgroup=2
+ ))
+
+ # Create dropdown menu for sorting
+ buttons = [
+ dict(
+ label="Sort by GDP",
+ method="update",
+ args=[{
+ "x": [merged_df.sort_values("Avg_GDP_Per_Capita")["Region_Country_Area"]] * 2,
+ "y": [merged_df.sort_values("Avg_GDP_Per_Capita")["Avg_GDP_Per_Capita"],
+ merged_df.sort_values("Avg_GDP_Per_Capita")["Avg_Crime_Rate"]]
+ }]
+ ),
+ dict(
+ label="Sort by Crime Rate",
+ method="update",
+ args=[{
+ "x": [merged_df.sort_values("Avg_Crime_Rate")["Region_Country_Area"]] * 2,
+ "y": [merged_df.sort_values("Avg_Crime_Rate")["Avg_GDP_Per_Capita"],
+ merged_df.sort_values("Avg_Crime_Rate")["Avg_Crime_Rate"]]
+ }]
+ )
+ ]
+ # Update the layout for secondary y-axis and dropdown menu
fig.update_layout(
- title='Homicide Rate vs Various Factors',
- xaxis_title='',
- yaxis_title='Homicide Rate (per 100,000)',
+ barmode='group',
+ title="Average Crime Rate and GDP per Capita by Region",
+ xaxis_title="Region",
yaxis=dict(
+ title="Average GDP per Capita",
tickmode='linear',
tick0=0,
- dtick=5, # Set the interval for y-axis ticks
- range=[0, 50] # Set the fixed range for y-axis
+ dtick=10000 # Set the interval for y-axis ticks
),
- xaxis=dict(
- range=[0, 100] # Set a default range for x-axis
+ yaxis2=dict(
+ title="Average Crime Rate",
+ overlaying='y',
+ side='right',
+ tickmode='linear',
+ tick0=0,
+ dtick=2 # Set the interval for y-axis ticks
),
- updatemenus=[
- {
- 'buttons': [
- {'label': 'Education Expenditure (%)', 'method': 'update', 'args': [{'visible': [True, False, False, False, True, False, False, False]}, {'xaxis': {'title': 'Education Expenditure (%)', 'range': [0, 100]}}]},
- {'label': 'Unemployment Rate (%)', 'method': 'update', 'args': [{'visible': [False, True, False, False, False, True, False, False]}, {'xaxis': {'title': 'Unemployment Rate (%)', 'range': [0, 50]}}]},
- {'label': 'Internet Usage (%)', 'method': 'update', 'args': [{'visible': [False, False, True, False, False, False, True, False]}, {'xaxis': {'title': 'Internet Usage (%)', 'range': [0, 100]}}]},
- {'label': 'Number of Women Killed (per 100,000)', 'method': 'update', 'args': [{'visible': [False, False, False, True, False, False, False, True]}, {'xaxis': {'title': 'Number of Women Killed (per 100,000)', 'range': [0, 100]}}]},
- ],
- 'direction': 'down',
- 'showactive': True,
- 'x': 0.17,
- 'xanchor': 'left',
- 'y': 1.15,
- 'yanchor': 'top'
- },
- {
- 'buttons': [
- {'label': 'Global Homicide Rate', 'method': 'update', 'args': [{'y': [combined_df['Homicide_Rate']]}, {'yaxis': {'title': 'Global Homicide Rate (per 100,000)', 'range': [0, 50]}}]},
- {'label': 'Male Homicide Rate', 'method': 'update', 'args': [{'y': [combined_df['Value_Male_Homicide']]}, {'yaxis': {'title': 'Male Homicide Rate (per 100,000)', 'range': [0, 50]}}]},
- {'label': 'Female Homicide Rate', 'method': 'update', 'args': [{'y': [combined_df['Value_Fem_Homicide']]}, {'yaxis': {'title': 'Female Homicide Rate (per 100,000)', 'range': [0, 50]}}]},
- ],
- 'direction': 'down',
- 'showactive': True,
- 'x': 0.37,
- 'xanchor': 'left',
- 'y': 1.15,
- 'yanchor': 'top'
- },
- {
- 'buttons': [
- {'label': 'Show Trend Lines', 'method': 'update', 'args': [{'visible': [True, True, True, True, True, True, True, True]}]},
- {'label': 'Hide Trend Lines', 'method': 'update', 'args': [{'visible': [True, True, True, True, False, False, False, False]}]},
- ],
- 'direction': 'down',
- 'showactive': True,
- 'x': 0.57,
- 'xanchor': 'left',
- 'y': 1.15,
- 'yanchor': 'top'
- },
- {
- 'buttons': [{'label': country, 'method': 'update', 'args': [{'visible': [True, True, True, True, True, True, True, True]}, {'xaxis': {'title': country}}]} for country in countries],
- 'direction': 'down',
- 'showactive': True,
- 'x': 0.77,
- 'xanchor': 'left',
- 'y': 1.15,
- 'yanchor': 'top'
- },
- {
- 'buttons': [{'label': str(year), 'method': 'update', 'args': [{'visible': [True, True, True, True, True, True, True, True]}, {'xaxis': {'title': str(year)}}]} for year in years],
- 'direction': 'down',
- 'showactive': True,
- 'x': 0.97,
- 'xanchor': 'left',
- 'y': 1.15,
- 'yanchor': 'top'
- }
- ]
+ updatemenus=[dict(
+ buttons=buttons,
+ direction="down",
+ showactive=True,
+ x=0.02,
+ xanchor="left",
+ y=1.15,
+ yanchor="top"
+ )]
)
-
-
-
+
return fig
+
+
def combined_choropleth():
- import plotly.express as px
- import pandas as pd
-
- # GRAPH 1 DATA
+ # 1) Load your data
general_homicide_rate_query = querys.overall_homicide_rate()
- general_homicide_rate = sql_t_UN.query_db(general_homicide_rate_query, table_name="SYB67_328_202411_Intentional homicides and other crimes.db")
-
- GLOBAL_AVERAGE = 5.86666666667
-
- # Ensure that the 'Year' column is integer and 'Value' is float
- general_homicide_rate['Year'] = pd.to_numeric(general_homicide_rate['Year'], errors='coerce') # Convert to int
- general_homicide_rate['Value'] = pd.to_numeric(general_homicide_rate['Value'], errors='coerce') # Convert to float
+ df = sql_t_UN.query_db(
+ general_homicide_rate_query,
+ table_name="SYB67_328_202411_Intentional homicides and other crimes.db"
+ )
- def calculate_average(group):
- return pd.Series({"Average_Homicide_Rate": group["Value"].mean() - GLOBAL_AVERAGE})
-
- # Apply the function to each group (each region/country)
- average_df = general_homicide_rate.groupby("Region_Country_Area").apply(calculate_average).reset_index()
+ # 2) Ensure 'Value' is numeric
+ df["Value"] = pd.to_numeric(df["Value"], errors="coerce")
- # GRAPH 2 DATA
- def calculate_change(group):
- min_year = group["Year"].min()
- max_year = group["Year"].max()
-
- # Get the values for the earliest and latest year
- min_value = group[group["Year"] == min_year]["Value"].values[0]
- max_value = group[group["Year"] == max_year]["Value"].values[0]
-
- # Calculate the change
- change = max_value - min_value
- return pd.Series({"Change_Homicide_Rate": change})
-
- # Apply the function to each group (each region/country)
- change_df = general_homicide_rate.groupby("Region_Country_Area").apply(calculate_change).reset_index()
+ # 3) Group by Region_Country_Area AND Row_Descriptor, average the Value
+ grouped = df.groupby(["Region_Country_Area", "Row_Descriptor"], as_index=False)["Value"].mean()
+ grouped.rename(columns={"Value": "AvgValue"}, inplace=True)
- # GRAPH 3 DATA
- education_expenditure_query = querys.education_rate()
- education_expenditure = sql_t_UN.query_db(education_expenditure_query, table_name="SYB67_245_202411_Public expenditure on education and access to computers.db")
-
- # Ensure that the 'Year' column is integer and 'Value' is float
- education_expenditure['Year'] = pd.to_numeric(education_expenditure['Year'], errors='coerce') # Convert to int
- education_expenditure['Value'] = pd.to_numeric(education_expenditure['Value'], errors='coerce') # Convert to float
+ # 4) Get a sorted list of crime types
+ crime_types = sorted(grouped["Row_Descriptor"].unique())
- def calculate_education_change(group):
- min_year = group["Year"].min()
- max_year = group["Year"].max()
+ # 5) Create one choropleth trace per crime type
+ traces = []
+ all_countries = df["Region_Country_Area"].unique()
+ for crime_type in crime_types:
+ subset = grouped[grouped["Row_Descriptor"] == crime_type]
- # Get the values for the earliest and latest year
- min_value = group[group["Year"] == min_year]["Value"].values[0]
- max_value = group[group["Year"] == max_year]["Value"].values[0]
+ # Ensure all countries are included, even if they don't have data for this crime type
+ subset = subset.set_index("Region_Country_Area").reindex(all_countries).reset_index()
+ subset["AvgValue"] = subset["AvgValue"].fillna("None") # Set default value as None
- # Calculate the change
- change = max_value - min_value
- return pd.Series({"Change_Education_Expenditure": change})
-
- # Apply the function to each group (each region/country)
- education_change_df = education_expenditure.groupby("Region_Country_Area").apply(calculate_education_change).reset_index()
-
- # Combine all data into one DataFrame
- combined_df = average_df.merge(change_df, on="Region_Country_Area", how="outer")
- combined_df = combined_df.merge(education_change_df, on="Region_Country_Area", how="outer")
-
- # Ensure all colunms aside from Region_Country_Area are numeric
- for col in combined_df.columns:
- if col != "Region_Country_Area":
- combined_df[col] = pd.to_numeric(combined_df[col], errors='coerce')
-
-
-
- # Create Plotly figure with dropdown menu
- fig = px.choropleth(
- combined_df,
- locations="Region_Country_Area", # Column with region/country names
- locationmode="country names", # Use country names
- color="Average_Homicide_Rate", # Default column for color intensity
- hover_name="Region_Country_Area", # Region names appear when hovering
- color_continuous_scale="Viridis", # Color scale
- title="Global Trends", # Title of the map
- labels={"Average_Homicide_Rate": "Average Homicide Rate"} # Label for the color scale
- )
+ trace = go.Choropleth(
+ locations=subset["Region_Country_Area"],
+ locationmode="country names",
+ z=subset["AvgValue"],
+ text=subset["Region_Country_Area"],
+ hovertemplate=(
+ "<b>%{text}</b><br>"
+ f"{crime_type} average: " + "%{z}<extra></extra>"
+ ),
+ colorscale="Reds",
+ colorbar_title="AvgValue",
+ visible=(crime_type == "Intentional homicide rates per 100,000"), # default visible
+ name=crime_type
+ )
+ traces.append(trace)
+
+ # 6) Build the update menus (one button per crime type)
+ buttons = []
+ for i, crime_type in enumerate(crime_types):
+ # For each button, set the corresponding trace to be visible,
+ # and all others to be hidden.
+ visibility_array = [False] * len(crime_types)
+ visibility_array[i] = True # Show the current crime type
+ buttons.append(dict(
+ label=crime_type,
+ method="update",
+ args=[
+ {"visible": visibility_array}, # which traces are visible
+ {"title": f"Average {crime_type} by Country"} # update the figure title
+ ]
+ ))
+
+ # 7) Create the figure
+ fig = go.Figure(data=traces)
- # Update layout with dropdown menu
fig.update_layout(
- updatemenus=[
- {
- 'buttons': [
- {'label': 'Average Homicide Rate', 'method': 'update', 'args': [{'z': [combined_df['Average_Homicide_Rate']]}, {'coloraxis_colorbar': {'title': 'Average Homicide Rate'}}]},
- {'label': 'Change in Homicide Rate', 'method': 'update', 'args': [{'z': [combined_df['Change_Homicide_Rate']]}, {'coloraxis_colorbar': {'title': 'Change in Homicide Rate'}}]},
- {'label': 'Change in Education Expenditure', 'method': 'update', 'args': [{'z': [combined_df['Change_Education_Expenditure']]}, {'coloraxis_colorbar': {'title': 'Change in Education Expenditure'}}]},
- ],
- 'direction': 'down',
- 'showactive': True,
- 'x': 0.17,
- 'xanchor': 'left',
- 'y': 1.15,
- 'yanchor': 'top'
- }
- ]
+ title="Average Intentional homicide rates per 100,000 by Country", # default
+ geo=dict(showframe=False, showcoastlines=False),
+ margin=dict(l=0, r=0, t=50, b=0),
+ updatemenus=[dict(
+ x=0.1, # position of the dropdown horizontally
+ y=1.15, # position of the dropdown vertically
+ xanchor="left",
+ yanchor="top",
+ active=crime_types.index("Intentional homicide rates per 100,000"),
+ buttons=buttons
+ )]
)
return fig
-
## UK GRAPHS CASE STUDY
-def graph8():
- # Query the education expenditure data
- education_expenditure_query = querys.uk_education_expenditure()
- education_expenditure = sql_t_UK.query_db(education_expenditure_query, table_name="uk_expenditure.db")
-
- # Convert time_period to a standard year format
- education_expenditure["time_period"] = education_expenditure["time_period"].astype(str).str[:4]
- education_expenditure["time_period"] = pd.to_numeric(education_expenditure["time_period"], errors="coerce")
-
- # Filter only 'Total' expenditure type to avoid double-counting
- education_expenditure = education_expenditure[education_expenditure["expenditure_type"] == "Total"]
-
- # Ensure the data is sorted by time_period
- education_expenditure = education_expenditure.sort_values(by="time_period")
-
- # Remove non-numeric or missing values in t_expenditure_millions
- education_expenditure["t_expenditure_millions"] = pd.to_numeric(education_expenditure["t_expenditure_millions"], errors="coerce")
- education_expenditure = education_expenditure.dropna(subset=["t_expenditure_millions"])
-
- # Group by time_period and education_function to get the total expenditure
- grouped_df = education_expenditure.groupby(["time_period", "education_function"], as_index=False)["t_expenditure_millions"].sum()
-
- # Create a stacked bar chart by year
- fig = px.bar(
- grouped_df,
- x="time_period",
- y="t_expenditure_millions",
- color="education_function",
- barmode="stack",
- labels={"time_period": "Year", "t_expenditure_millions": "Expenditure (Millions)"},
- title="UK Education Spending"
- )
-
-
- # Update the y-axis to have regular intervals
- fig.update_layout(
- yaxis=dict(
- tickmode='linear',
- tick0=0,
- dtick=100000 # Set the interval for y-axis ticks
- ),
- xaxis_title="Financial Year",
- yaxis_title="Total Expenditure (Millions)"
- )
-
- return fig
def graph9(): # CRIME MAP
@@ -586,6 +573,53 @@ def graph11():
)
return fig
+
+def graph8():
+ # Query the education expenditure data
+ education_expenditure_query = querys.uk_education_expenditure()
+ education_expenditure = sql_t_UK.query_db(education_expenditure_query, table_name="uk_expenditure.db")
+
+ # Convert time_period to a standard year format
+ education_expenditure["time_period"] = education_expenditure["time_period"].astype(str).str[:4]
+ education_expenditure["time_period"] = pd.to_numeric(education_expenditure["time_period"], errors="coerce")
+
+ # Filter only 'Total' expenditure type to avoid double-counting
+ education_expenditure = education_expenditure[education_expenditure["expenditure_type"] == "Total"]
+
+ # Ensure the data is sorted by time_period
+ education_expenditure = education_expenditure.sort_values(by="time_period")
+
+ # Remove non-numeric or missing values in t_expenditure_millions
+ education_expenditure["t_expenditure_millions"] = pd.to_numeric(education_expenditure["t_expenditure_millions"], errors="coerce")
+ education_expenditure = education_expenditure.dropna(subset=["t_expenditure_millions"])
+
+ # Group by time_period and education_function to get the total expenditure
+ grouped_df = education_expenditure.groupby(["time_period", "education_function"], as_index=False)["t_expenditure_millions"].sum()
+
+ # Create a stacked bar chart by year
+ fig = px.bar(
+ grouped_df,
+ x="time_period",
+ y="t_expenditure_millions",
+ color="education_function",
+ barmode="stack",
+ labels={"time_period": "Year", "t_expenditure_millions": "Expenditure (Millions)"},
+ title="UK Education Spending"
+ )
+
+
+ # Update the y-axis to have regular intervals
+ fig.update_layout(
+ yaxis=dict(
+ tickmode='linear',
+ tick0=0,
+ dtick=100000 # Set the interval for y-axis ticks
+ ),
+ xaxis_title="Financial Year",
+ yaxis_title="Total Expenditure (Millions)"
+ )
+
+ return fig
@@ -604,21 +638,22 @@ def graph11():
if __name__ == "__main__":
- pass
-
graphs = [
- ("Combined Choropleth", combined_choropleth, "UN"),
- ("Combined Test", combined_graph, "UN"),
- ("Total Recorded Crime 2015-2024", graph9, "UK"),
- ("UK Education Expendature", graph8, "UK"),
- ("UK Crime Bar Chart", graph10, "UK"),
- ("Distribution of Crime Types", graph11, "UK")
+ ("Combined Choropleth", combined_choropleth, "UN", "Crime"),
+ ("Total Recorded Crime 2002-2022", un_crime_line_chart, "UN", "Crime"),
+ ("GDP per Capita (USD) by Continent", gdp_per_continent, "UN", "Socioeconomic"),
+ ("Crime and Economy", large_grouped_bar_chart, "UN", "Crime"),
+ ("Total Recorded Crime 2015-2024", graph9, "UK", "Crime"),
+ ("UK Education Expenditure", graph8, "UK", "Socioeconomic"),
+ ("UK Crime Bar Chart", graph10, "UK", "Crime"),
+ ("Distribution of Crime Types", graph11, "UK", "Crime")
]
# Add each graph to the dashboard with a progress bar
- for title, graph_function, group_name in tqdm(graphs, desc="Generating graphs"):
+ for title, graph_function, group_name, category_name in tqdm(graphs, desc="Generating graphs"):
fig = graph_function()
- d_board.add_graph(fig=fig, title=title, group_name=group_name)
+ d_board.add_graph(group_name=group_name, category_name=category_name, fig=fig, title=title)
+
# Finally, generate the HTML
d_board.generate_html(output_path="graphs/graphs_display.html")
@@ -626,5 +661,3 @@ if __name__ == "__main__":
# Open the HTML file in the default web browser
webbrowser.open(os.getcwd() + "/graphs/graphs_display.html")
-
-
--
GitLab