diff --git a/.gitignore b/.gitignore index 8c0da0f9..10fe2e4a 100644 --- a/.gitignore +++ b/.gitignore @@ -44,4 +44,6 @@ next-env.d.ts *.db *prisma/migrations -martin \ No newline at end of file +martin +.obsidian +.idea \ No newline at end of file diff --git a/.idea/.gitignore b/.idea/.gitignore deleted file mode 100644 index 13566b81..00000000 --- a/.idea/.gitignore +++ /dev/null @@ -1,8 +0,0 @@ -# Default ignored files -/shelf/ -/workspace.xml -# Editor-based HTTP Client requests -/httpRequests/ -# Datasource local storage ignored files -/dataSources/ -/dataSources.local.xml diff --git a/.idea/codeStyles/codeStyleConfig.xml b/.idea/codeStyles/codeStyleConfig.xml deleted file mode 100644 index a55e7a17..00000000 --- a/.idea/codeStyles/codeStyleConfig.xml +++ /dev/null @@ -1,5 +0,0 @@ - - - - \ No newline at end of file diff --git a/.idea/dataSources.xml b/.idea/dataSources.xml deleted file mode 100644 index 7ae40895..00000000 --- a/.idea/dataSources.xml +++ /dev/null @@ -1,12 +0,0 @@ - - - - - sqlite.xerial - true - org.sqlite.JDBC - jdbc:sqlite:$PROJECT_DIR$/prisma/dev.db - $ProjectFileDir$ - - - \ No newline at end of file diff --git a/.idea/inspectionProfiles/Project_Default.xml b/.idea/inspectionProfiles/Project_Default.xml deleted file mode 100644 index 708ddf95..00000000 --- a/.idea/inspectionProfiles/Project_Default.xml +++ /dev/null @@ -1,6 +0,0 @@ - - - - \ No newline at end of file diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml deleted file mode 100644 index 105ce2da..00000000 --- a/.idea/inspectionProfiles/profiles_settings.xml +++ /dev/null @@ -1,6 +0,0 @@ - - - - \ No newline at end of file diff --git a/.idea/meeting-intellectuals.iml b/.idea/meeting-intellectuals.iml deleted file mode 100644 index 02f253ce..00000000 --- a/.idea/meeting-intellectuals.iml +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml deleted file mode 100644 index 5264df9f..00000000 --- a/.idea/misc.xml +++ /dev/null @@ -1,6 +0,0 @@ - - - - - \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml deleted file mode 100644 index c87131d9..00000000 --- a/.idea/modules.xml +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - \ No newline at end of file diff --git a/.idea/vcs.xml b/.idea/vcs.xml deleted file mode 100644 index 94a25f7f..00000000 --- a/.idea/vcs.xml +++ /dev/null @@ -1,6 +0,0 @@ - - - - - - \ No newline at end of file diff --git a/.obsidian/app.json b/.obsidian/app.json deleted file mode 100644 index 9e26dfee..00000000 --- a/.obsidian/app.json +++ /dev/null @@ -1 +0,0 @@ -{} \ No newline at end of file diff --git a/.obsidian/appearance.json b/.obsidian/appearance.json deleted file mode 100644 index 9e26dfee..00000000 --- a/.obsidian/appearance.json +++ /dev/null @@ -1 +0,0 @@ -{} \ No newline at end of file diff --git a/.obsidian/core-plugins.json b/.obsidian/core-plugins.json deleted file mode 100644 index b977c255..00000000 --- a/.obsidian/core-plugins.json +++ /dev/null @@ -1,31 +0,0 @@ -{ - "file-explorer": true, - "global-search": true, - "switcher": true, - "graph": true, - "backlink": true, - "canvas": true, - "outgoing-link": true, - "tag-pane": true, - "properties": false, - "page-preview": true, - "daily-notes": true, - "templates": true, - "note-composer": true, - "command-palette": true, - "slash-command": false, - "editor-status": true, - "bookmarks": true, - "markdown-importer": false, - "zk-prefixer": false, - "random-note": false, - "outline": true, - "word-count": true, - "slides": false, - "audio-recorder": false, - "workspaces": false, - "file-recovery": true, - "publish": false, - "sync": true, - "webviewer": false -} \ No newline at end of file diff --git a/.obsidian/hotkeys.json b/.obsidian/hotkeys.json deleted file mode 100644 index d9076a84..00000000 --- a/.obsidian/hotkeys.json +++ /dev/null @@ -1,148 +0,0 @@ -{ - "insert-template": [ - { - "modifiers": [ - "Alt" - ], - "key": "T" - } - ], - "editor:delete-paragraph": [ - { - "modifiers": [ - "Mod" - ], - "key": "Y" - } - ], - "obsidian-languagetool-plugin:ltcheck-text": [ - { - "modifiers": [ - "Alt", - "Mod" - ], - "key": "C" - } - ], - "obsidian-languagetool-plugin:ltaccept-suggestion-1": [ - { - "modifiers": [ - "Mod", - "Shift" - ], - "key": "C" - } - ], - "editor:set-heading-1": [ - { - "modifiers": [ - "Alt", - "Mod" - ], - "key": "1" - } - ], - "editor:set-heading-2": [ - { - "modifiers": [ - "Alt", - "Mod" - ], - "key": "2" - } - ], - "editor:set-heading-3": [ - { - "modifiers": [ - "Alt", - "Mod" - ], - "key": "3" - } - ], - "editor:set-heading-4": [ - { - "modifiers": [ - "Alt", - "Mod" - ], - "key": "4" - } - ], - "editor:set-heading-5": [ - { - "modifiers": [ - "Alt", - "Mod" - ], - "key": "5" - } - ], - "editor:set-heading-6": [ - { - "modifiers": [ - "Alt", - "Mod" - ], - "key": "6" - } - ], - "app:go-back": [ - { - "modifiers": [ - "Mod", - "Alt" - ], - "key": "ArrowLeft" - }, - { - "modifiers": [ - "Alt", - "Shift" - ], - "key": "ArrowLeft" - } - ], - "app:go-forward": [ - { - "modifiers": [ - "Mod", - "Alt" - ], - "key": "ArrowRight" - }, - { - "modifiers": [ - "Alt", - "Shift" - ], - "key": "ArrowRight" - } - ], - "editor:context-menu": [ - { - "modifiers": [ - "Alt" - ], - "key": "Enter" - } - ], - "editor:follow-link": [ - { - "modifiers": [ - "Alt", - "Shift" - ], - "key": "Enter" - } - ], - "editor:cycle-list-checklist": [ - { - "modifiers": [ - "Alt", - "Mod" - ], - "key": "B" - } - ] -} \ No newline at end of file diff --git a/.obsidian/workspace.json b/.obsidian/workspace.json deleted file mode 100644 index 7a380fcf..00000000 --- a/.obsidian/workspace.json +++ /dev/null @@ -1,168 +0,0 @@ -{ - "main": { - "id": "1bfbade88fcfec55", - "type": "split", - "children": [ - { - "id": "7facf39ed5015822", - "type": "tabs", - "children": [ - { - "id": "c408eff3df45f809", - "type": "leaf", - "state": { - "type": "empty", - "state": {}, - "icon": "lucide-file", - "title": "New tab" - } - } - ] - } - ], - "direction": "vertical" - }, - "left": { - "id": "be7671ba7092d719", - "type": "split", - "children": [ - { - "id": "d35c2a0a402ecd5d", - "type": "tabs", - "children": [ - { - "id": "4f11d12d34891ea7", - "type": "leaf", - "state": { - "type": "file-explorer", - "state": { - "sortOrder": "alphabetical", - "autoReveal": false - }, - "icon": "lucide-folder-closed", - "title": "Files" - } - }, - { - "id": "eaaec87adeac134e", - "type": "leaf", - "state": { - "type": "search", - "state": { - "query": "", - "matchingCase": false, - "explainSearch": false, - "collapseAll": false, - "extraContext": false, - "sortOrder": "alphabetical" - }, - "icon": "lucide-search", - "title": "Search" - } - }, - { - "id": "15a237b845d3e20b", - "type": "leaf", - "state": { - "type": "bookmarks", - "state": {}, - "icon": "lucide-bookmark", - "title": "Bookmarks" - } - } - ] - } - ], - "direction": "horizontal", - "width": 300 - }, - "right": { - "id": "50eec151107f9ed7", - "type": "split", - "children": [ - { - "id": "5b09bb3294264e7f", - "type": "tabs", - "children": [ - { - "id": "b2fe533e95f324e8", - "type": "leaf", - "state": { - "type": "backlink", - "state": { - "collapseAll": false, - "extraContext": false, - "sortOrder": "alphabetical", - "showSearch": false, - "searchQuery": "", - "backlinkCollapsed": false, - "unlinkedCollapsed": true - }, - "icon": "links-coming-in", - "title": "Backlinks" - } - }, - { - "id": "985abb1f14124830", - "type": "leaf", - "state": { - "type": "outgoing-link", - "state": { - "linksCollapsed": false, - "unlinkedCollapsed": true - }, - "icon": "links-going-out", - "title": "Outgoing links" - } - }, - { - "id": "6a75acc48fb81d4f", - "type": "leaf", - "state": { - "type": "tag", - "state": { - "sortOrder": "frequency", - "useHierarchy": true, - "showSearch": false, - "searchQuery": "" - }, - "icon": "lucide-tags", - "title": "Tags" - } - }, - { - "id": "55ebdc78da69d9f1", - "type": "leaf", - "state": { - "type": "outline", - "state": { - "followCursor": false, - "showSearch": false, - "searchQuery": "" - }, - "icon": "lucide-list", - "title": "Outline" - } - } - ] - } - ], - "direction": "horizontal", - "width": 300, - "collapsed": true - }, - "left-ribbon": { - "hiddenItems": { - "switcher:Open quick switcher": false, - "graph:Open graph view": false, - "canvas:Create new canvas": false, - "daily-notes:Open today's daily note": false, - "templates:Insert template": false, - "command-palette:Open command palette": false - } - }, - "active": "c408eff3df45f809", - "lastOpenFiles": [ - "README.md" - ] -} \ No newline at end of file diff --git a/README.md b/README.md index a235b6ec..8f85ed1a 100644 --- a/README.md +++ b/README.md @@ -62,33 +62,6 @@ Run the following commands to set up your database and Prisma schema: ```bash npx prisma migrate dev --name init -``` - - -### 4. Seed the database - -Add initial data to your database: - -```bash -npx prisma db seed -``` - -
- -Expand for yarn, pnpm or bun - -```bash -# Using yarn -yarn prisma db seed - -# Using pnpm -pnpm prisma db seed - -# Using bun -bun prisma db seed -``` - -
### 5. Run the app @@ -98,28 +71,5 @@ Start the development server: npm run dev ``` -
-Expand for yarn, pnpm or bun - -```bash -# Using yarn -yarn dev - -# Using pnpm -pnpm run dev - -# Using bun -bun run dev -``` - -
- -Once the server is running, visit `http://localhost:3000` to start using the app. - -## Next steps - -- [Prisma ORM documentation](https://www.prisma.io/docs/orm) -- [Prisma Client API reference](https://www.prisma.io/docs/orm/prisma-client) -- [Join our Discord community](https://discord.com/invite/prisma) -- [Follow us on Twitter](https://twitter.com/prisma) +Once the server is running, visit http://localhost:3000 to start using the app. \ No newline at end of file diff --git a/martin/Date Me Directory.html b/martin/Date Me Directory.html deleted file mode 100644 index 3aa0d7bf..00000000 --- a/martin/Date Me Directory.html +++ /dev/null @@ -1,2 +0,0 @@ - -Date Me Directory
Date Me Directory
BrowseFAQJoin
You are any gender looking for any gender between the ages of 0 and 100 in the world. There are 513 profiles for you.
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NameAgeGenderInterestedInStyleLocationLocationFlexibilityContactLastUpdated
Kyp
34
M
F
mono
Southern US
Some
kypsta@gmail.com
2025-07-20
Calum
27
M
F
mono
San Francisco Bay AreaNorth AmericaFlexibleWestern USBerkeleySouth Bay
Flexible
see the doc!
2025-07-14
Rj
40
F
FMNB
Any
UK
Flexible
See in doc
2025-07-14
Alex Hedtke
31
M
F
mono
North AmericaFlexible
Some
alex.hedtke@gmail.com
2025-07-10
Flora Scarabello
27
F
FMNB
Any
UKFlexible
Flexible
flora.minerva@hotmail.co.uk / (+44)7496049168
2025-07-04
Erik Lönnroth
39
M
F
mono
LondonSweden
Flexible
see doc
2025-07-02
Cuong Tran
33
M
F
mono
Asia
None
hey@cuongtran.net
2025-06-29
jean
23
NB
F
mono
Flexible
Flexible
https://www.notion.so/Jean-s-Date-Me-Doc-21595d49d32380fda385c25fa7504e51
2025-06-17
Panagiotis
24
M
F
mono
Central EuropeNorway
Flexible
skyrimborn229@gmail.com
2025-06-16
Dan Elton
37
M
FNB
Any
DC
Flexible
in the document
2025-06-07
Yash Mittal
27
M
F
mono
San Francisco Bay Area
Some
At the bottom of the doc
2025-06-07
Matthew Goodman
30
M
F
mono
UK
Some
mattgoodman95@gmail.com
2025-06-06
KW
24
M
F
mono
Flexible
Flexible
kvnwkw@gmail.com
2025-06-05
Quinn Dougherty
32
M
F
poly
San Francisco Bay AreaNYCNorth AmericaFlexiblePhiladelphia
Flexible
quinn.dougherty92 at gmail dot com
2025-06-04
Emmet
34
M
F
Any
LondonCentral EuropeFlexibleSpain
Flexible
You'll see!
2025-05-29
Mr. Gillion
47
M
F
mono
Berlin
None
saihtame13@freenet.de
2025-05-29
Jarrett
35
M
FMNB
poly
San Francisco Bay Area
None
https://forms.gle/nTe1wMVuyRwbVShb7
2025-05-26
Pavitthra Pandurangan
26
F
M
mono
NYC
Some
pavitthra.n.p@gmail.com
2025-05-25
Max Carpendale
34
M
FNB
Any
LondonVancouverVancouver Island
Flexible
Maxcarpendale@gmail.com
2025-05-24
Michelle Savage
57
F
M
mono
Western US
Some
Michelledenmaar@gmail.com
2025-05-21
Terrence Chan
44
M
F
mono
Canada
Some
terrencechan00@gmail.com
2025-05-14
Joe Parrish
33
M
F
mono
North AmericaNorth Carolina
Flexible
josephparrishnc@gmail.com
2025-05-13
MP
31
F
M
mono
UK
Some
See doc
2025-05-07
Cynthia
27
F
FMNB
poly
Philadelphia
Some
@cyndipaula on discord
2025-05-06
Baram
29
M
F
mono
San Francisco Bay AreaBerkeley
Some
See doc
2025-05-05
Rhys Lindmark
34
M
F
mono
San Francisco Bay Area
Some
rhyslindmark@gmail.com
2025-05-04
David McKibbin
29
M
F
mono
Miami
Flexible
Phone: 561-818-6008, Email: dmckibbin95@gmail.com, Instagram: @davidmck95.
2025-05-04
Maria Marshakova
42
F
M
mono
DubaiGeorgiaNorwayIsraelSpain
Flexible
icbsmma@gmail.com
2025-04-28
Toku McCree
44
M
F
mono
Flexible
Flexible
dateme@tokumccree.com
2025-04-24
Dillon Paul
42
M
F
mono
Flexible
Flexible
dwpaulDE@gmail.com
2025-04-22
Isaac K.
25
M
F
mono
DC
Some
ikarachunsky@gmail.com or ikarachunsky on insta
2025-04-21
Jack Malde
32
M
F
mono
NYCDCNYPhiladelphia
Some
jack.malde@gmail.com
2025-04-20
Stefan
49
M
F
Any
San Francisco Bay Area
Flexible
lingua2015@gmail.com
2025-04-17
Heather K
27
F
M
mono
DC
None
hath0r on discord (or see doc)
2025-04-17
Elsie
44
F
FM
mono
BerlinMiami
Some
elsie_kk@icloud.com
2025-04-16
Voyteck
37
M
F
mono
Spain
Some
see the link
2025-04-12
Benjamin
28
M
F
mono
DC
Some
https://docs.google.com/forms/d/e/1FAIpQLSfoRgz4CBz_hI-G3BUc4-4Jmq2SrDvUztQyL5sVJ7RyI6qFoA/viewform
2025-04-12
Dmitry Vaintrob
36
M
F
mono
San Francisco Bay Area
Flexible
mvaintrob@gmail.com
2025-04-12
Alice
22
F
M
Any
London
Some
aliceolafferty@gmail.com
2025-04-08
William Thacker
35
NB
NB
mono
Spain
Flexible
katana
2025-04-05
Laura
30
F
M
Any
London
Flexible
through the form
2025-04-04
Hanna
29
F
M
mono
London
Some
In the doc
2025-04-03
Kendra
37
F
M
mono
Paris, France
Some
kendrasdatingemail@gmail.com
2025-03-30
Daniil
35
M
F
mono
Central Europe
Flexible
dweidmann.mailbox@gmail.com
2025-03-29
Serena
49
FNB
MNB
Any
Seattle
Some
See doc, thanks
2025-03-27
Andreas C.
27
M
F
Any
Central EuropeFlexible
Flexible
higher.ton1e@icloud.com
2025-03-20
David S
38
M
F
mono
LondonUK
Some
dwsaxton@gmail.com
2025-03-19
Kiran Kaja
43
M
F
Any
San Francisco Bay AreaNorth AmericaFlexibleWestern USSeattleBerkeley
Flexible
kirankaja12@gmail.com
2025-03-18
Abe K.
29
M
FNB
Any
San Francisco Bay Area
None
abe.karplus@gmail.com or (831) 419-9368
2025-03-14
Gabin
25
M
FNB
poly
Central EuropeSouth of France
Some
GabinDatingDoc@proton.me
2025-03-07
Malvin G.
34
M
F
mono
San Francisco Bay AreaNYCCentral EuropeDCLos AngelesNorth AmericaFlexibleBostonNYWestern USSeattleChicagoNJPhiladelphiaColoradoTorontoAustinPACanadaSouthern USVancouverTXPortlandMADenverBrazilAmsterdamSouth of FranceCambridgeBerkeleyWAOxfordOregonNorth CarolinaSacramentoOhioIndianapolisGeorgiaAshevilleSydney AustraliaSwedenNew HavenNebraskaMontereyLubbockCollingswoodCTRhode IslandMiamiNorwayIsraelSpain
Flexible
https://docs.google.com/forms/d/1-opeZgl3qdr4ppvmzsc214knLDHcUyr7zHD3nWyVM1g/edit
2025-03-07
Callum
40
M
F
mono
UK
Flexible
callumcallum109@outlook.com
2025-03-04
Ari Zerner
27
M
FNB
poly
San Francisco Bay AreaPhiladelphia
Some
ari@zerner.com
2025-02-24
Aeneas
29
M
F
mono
Flexible
Flexible
aokook@gmail.com
2025-02-20
Mike
31
M
F
mono
North AmericaFlexiblePhiladelphiaPA
Flexible
please see doc :)
2025-02-20
Alicia C
33
F
FMNB
poly
San Francisco Bay Area
Some
alicia.combs.92@gmail.com
2025-02-18
Brad Levin
41
M
F
poly
San Francisco Bay Area
None
🤙 See doc!
2025-02-13
Julie M
39
F
M
mono
Sacramento
Flexible
jlmccollo@gmail.com
2025-02-05
Ja
37
M
F
mono
LondonUK
Some
jyue87@gmail.com
2025-02-05
Mairead
37
F
FMNB
poly
North America
Some
firstdate.mairead@gmail.com
2025-02-03
Aaron
43
M
F
mono
Philadelphia
Some
https://docs.google.com/forms/d/e/1FAIpQLSdh9M8tkGJi-o9bPIlueShS8Alzrff203tPTSXhmBfp6D05pg/viewform
2025-02-03
Oscar
23
M
F
mono
UKOxford
Some
in the doc!
2025-02-01
Jessica H Halasz
32
F
M
mono
Colorado
Some
jess.halasz@gmail.com
2025-02-01
Tanner Godarzi
32
M
F
mono
San Francisco Bay Area
None
Tanner.godarzi@gmail.com
2025-01-28
Henry Roark
34
M
M
mono
San Francisco Bay Area
Some
henryrrk@gmail.com
2025-01-27
Ethan
20
M
F
mono
North America
Some
See document
2025-01-26
Tom Keith
27
M
F
mono
LondonUKOxford
Some
tom.arrow42@gmail.com
2025-01-25
Aaron
25
M
F
Any
UKOxford
Some
m_aaron@hotmail.de
2025-01-21
malcolm handley
45
M
F
mono
San Francisco Bay Area
Some
m@redheron.com
2025-01-20
Emily
24
F
M
mono
DCNorth AmericaFlexible
Flexible
See doc :)
2025-01-20
Grant Eckett
30
M
F
mono
LondonUK
Flexible
grant.eckett@gmail.com
2025-01-19
Arpan Bhattacharya
24
M
F
mono
San Francisco Bay AreaNYC
Flexible
9453452930
2025-01-18
George
34
M
FNB
Any
Flexible
Flexible
đź’Ś georgesdatemedoc@gmail.com
2025-01-12
Michael Creger
55
M
F
mono
North AmericaFlexible
Flexible
mike.creger@gmail.com
2025-01-10
Sam B
37
FNB
MNB
Any
FlexibleWestern USSeattle
Some
samantha.bernecker@gmail.com
2025-01-09
James Norris
41
M
F
Any
Indonesia
Flexible
http://www.jamesnorris.org/contact
2025-01-05
Libby
22
F
M
Any
Central EuropeUKOxford
Flexible
burnerfahrenheit@gmail.com
2025-01-04
JW
38
M
M
mono
Spain
Some
https://t.me/hombreafricano
2025-01-03
Dave K
38
M
FNB
Any
DC
Flexible
See in the doc
2025-01-02
swyx
38
M
F
mono
San Francisco Bay AreaNYCLos AngelesFlexibleAsia
Flexible
x.com/swyx
2025-01-02
Jen Ba
27
F
M
mono
San Francisco Bay AreaNYC
Some
jenniferb4869@gmail.com
2025-01-01
Aaron Boddy
31
M
F
poly
LondonUK
Flexible
dr.aaronboddy@gmail.com
2024-12-27
david talavera
35
M
F
mono
Flexible
Flexible
talaveradf@gmail.com
2024-12-26
Jose Luis Ricon
32
M
F
poly
San Francisco Bay Area
None
See in the doc
2024-12-26
Anne
60
F
M
mono
NYCNY
Some
osbornmessenger@gmail.com
2024-12-21
Jayme Halbritter
53
M
F
mono
North AmericaFlexible
Flexible
thisisnot.thisisnow@gmail.com
2024-12-16
Kelechi Nwankwoala
25
M
F
Any
NYC
Flexible
knwankwoala2@gmail.com
2024-12-16
Crystal Richard
28
F
M
mono
North America
Flexible
c13219438@gmail.com
2024-12-15
Chris Pang
22
M
F
mono
LondonUK
Some
See doc :D
2024-12-12
Marie
23
F
M
mono
Berlin
Flexible
marysp.609@gmail.com
2024-12-12
Siris Hill
35
M
F
mono
Oxford
Flexible
sirishill@hotmail.com
2024-12-11
Inzy - TJ
29
M
F
Any
NYCNorth America
Flexible
injamulhudatalukder@gmail.com
2024-12-08
Daniel Filan
30
M
F
Any
San Francisco Bay Area
Some
df@danielfilan.com
2024-12-05
Hussein E
38
M
FM
mono
LondonBoston
Some
hello@hussein.love
2024-12-01
Tara
34
F
FM
mono
Spain
Some
See Doc
2024-12-01
Dominik
45
M
F
poly
Berlin
Some
dominik100101@proton.me
2024-11-29
Sonia Albrecht
37
F
MNB
mono
San Francisco Bay Area
None
salbrecht314@gmail.com
2024-11-27
Zachary Robert
29
M
F
mono
Toronto
None
zack.robert@live.ca
2024-11-22
Seth Ariel Green
36
M
F
Any
NYC
Some
setgree@gmail.com
2024-11-21
Swathi Challa
43
F
M
mono
Austin
Flexible
Challa.swathi@gmail.com
2024-11-20
Alex Turner
30
M
F
poly
San Francisco Bay Area
Some
alex@turntrout.com
2024-11-18
Matthew Poon
22
M
F
mono
San Francisco Bay Area
None
matthewpoon00@gmail.com
2024-11-15
Robert Kingett
36
M
M
Any
North AmericaFlexibleChicagoColoradoTX
Flexible
https://datekingett.bearblog.dev/contact/
2024-11-15
Arun
30
M
F
mono
Asia
Some
Check the Doc
2024-11-14
Amaryllis
27
FMNB
FMNB
poly
SeattlePortland
Some
am8ryllis@gmail.com
2024-11-13
Chase Denecke
32
M
F
mono
San Francisco Bay Area
Some
chasedenecke@gmail.com
2024-11-04
Rosie
40
F
M
mono
London
Some
morningtonglory2019@gmail.com
2024-11-03
Saurav Saha
29
M
F
mono
San Francisco Bay AreaNYCLos AngelesFlexibleSeattleChicagoAsiaDubai
Flexible
sauravsaha.in@gmail.com
2024-11-02
Asher
47
M
F
mono
Flexible
Flexible
asher.dateme.directory.brilliant164@simplelogin.com
2024-11-01
Collin
37
M
F
mono
Central EuropeUKNorth AmericaFlexibleSouthern USWIAsheville
Some
collingowcnc@gmail.com
2024-10-27
Wiggles!
37
F
M
Any
San Francisco Bay Area
None
Form in the doc
2024-10-24
Katie Barlow
32
F
M
mono
Philadelphia
Flexible
kbarlow257@gmail.com
2024-10-22
Blake Boles
42
M
F
Any
Flexible
Flexible
blakeboles@gmail.com
2024-10-22
Charlie Rogers-Smith
26
M
M
Any
San Francisco Bay Area
Some
charlierogerssmith@gmail.com
2024-10-19
Nate A-M
28
M
F
mono
BostonRhode Island
Some
1nate146 [at] gmail [dot] com
2024-10-15
Swante
31
M
F
Any
Central Europe
Flexible
It's in the doc
2024-10-14
Dan M
38
M
F
mono
North AmericaGeorgia
Flexible
DansBurner07@gmail.com
2024-10-12
C
31
F
M
mono
UKFlexibleBrazil
Flexible
on the doc!
2024-10-08
Kaden Sieracki
21
M
F
mono
North America
Flexible
kaden_sieracki1@baylor.edu
2024-10-06
Krzysztof
55
M
F
mono
UK
Some
Please contact me by email on the address krispawlowski@ymail.com
2024-10-06
Will
33
M
F
Any
TorontoCanadaON
Some
willdatemedoc@gmail.com
2024-10-06
Kaushik Donthi
27
M
F
mono
San Francisco Bay Area
Flexible
kaushikdr@gmail.com
2024-10-05
Tim
35
M
F
mono
Western USSeattleVancouverPortlandWAOregon
Flexible
sirtofu@gmail.com
2024-10-04
Voy
37
M
F
mono
LondonCentral EuropeFlexible
Flexible
See the link
2024-10-04
Monica Rodriguez
39
F
M
Any
North AmericaWestern USSeattleWA
None
Monicarodriguez69691984@gmail.com
2024-10-02
AAA
25
F
M
mono
San Francisco Bay AreaNYCCentral EuropeUKFlexible
Flexible
arabella.a.anca@gmail.com
2024-09-29
Elliot
40
M
F
mono
London
Some
Deets in the doc
2024-09-29
Carson McNeil
34
M
F
mono
San Francisco Bay Area
Some
carson.mcneil@gmail.com
2024-09-28
Richard Ngo
29
M
F
Any
San Francisco Bay Area
Some
richardcngo@gmail.com
2024-09-27
Lazar Ilic
26
M
F
mono
Austin
Some
lazar_ilic@yahoo.com
2024-09-27
Robi Rahman
30
M
F
mono
NYCDC
Some
robirahman94@gmail.com
2024-09-27
Dario Marino
24
M
FNB
mono
Chicago
None
dariomarino@uchicago.edu
2024-09-27
Joshua Oreman
33
M
FNB
poly
FlexibleColorado
Flexible
oremanj@gmail.com or +1 626 318 1577
2024-09-26
Alex
35
M
F
mono
ColoradoDenver
Flexible
alex.mcclary@gmail.com
2024-09-23
Elana Ramos
19
F
M
mono
TX
Flexible
elanaramos16@gmail.com
2024-09-20
Rich
41
M
F
mono
Los Angeles
Some
xyphratl@gmail.com
2024-09-17
Luisa S.
25
F
F
Any
Berlin
Flexible
+49 1741878956
2024-09-16
Pip Moss
34
M
F
Any
London
None
MDUMoss@gmail.com
2024-09-16
Vanessa Kosoy
41
F
FMNB
poly
Israel
Some
highpriestessofelua@gmail.com
2024-09-13
e
27
M
F
mono
TX
Flexible
check doc
2024-09-11
Ying
33
F
M
mono
LondonUK
Some
Dengying1107@gmail.com
2024-09-10
Maya
45
F
M
mono
London
Some
https://docs.google.com/document/d/18wrUMScMym7xlWHGYZUNLC4WSsnZO2SsPQxE1ITXWNg/edit#heading=h.dad961ycjsll
2024-09-05
Ally Berke
36
F
M
mono
San Francisco Bay Area
Flexible
allyberke@gmail.com
2024-09-04
Xavier Richards
33
M
F
mono
FlexibleChicago
Flexible
xavierjayrichards@aol.com
2024-09-03
Jenn C
28
F
FNB
mono
CanadaON
Some
hi@jenn.site
2024-08-28
Carter Allen
23
M
FMNB
Any
San Francisco Bay AreaBerkeley
None
atcarterallen@gmail.com
2024-08-26
Hannah E
30
F
M
mono
London
Flexible
https://docs.google.com/forms/d/e/1FAIpQLSfpEgN-k4s7OSbcrAm8Wo_BWrM5sGsImhrYdiHCkoQwxO-jOQ/viewform
2024-08-25
Lugli
34
M
FNB
mono
North AmericaFlexible
Flexible
workefficient777@gmail.com
2024-08-24
Dave
64
M
F
mono
Los AngelesWestern US
None
davidabarak@gmail.com
2024-08-17
John Wentworth
32
M
F
Any
San Francisco Bay Area
Some
See doc
2024-08-17
Chi
37
M
F
mono
NYC
Flexible
chitangchitang@gmail.com
2024-08-17
Maura Kate Costello
37
F
M
mono
NYCFlexibleNY
Some
maura.kate.costello@gmail.com
2024-08-16
Ben Schwab
40
M
FMNB
Any
DC
None
schwabbenjamin@gmail.com
2024-08-15
Liziane P.
34
F
F
mono
Some
5551993987733
2024-08-13
Grace
23
F
M
mono
Philadelphia
Some
See the doc!
2024-08-12
Destiny
29
F
M
mono
North America
Flexible
serendipitousfox37@gmail.com
2024-08-12
S Lou
36
F
M
mono
London
Some
datemelou@yahoo.com
2024-08-12
Mal Gordon
46
M
F
mono
None
malgordonperth@gmail.com
2024-08-08
Stephen
25
M
F
mono
North America
Flexible
It's in the doc
2024-08-06
Tenley Schwartz
28
F
M
mono
None
tenleyschwartz@gmail.com
2024-08-05
Aron 'æX' M
32
M
F
Any
Central EuropeBerlin
Some
see doc
2024-08-05
Croelan Grandez
48
M
F
mono
North AmericaOhioMiami
Flexible
croelanjr@gmail.com
2024-08-05
Jake Owen
32
M
FNB
Any
Southern US
None
See doc
2024-08-04
Stephen
25
M
F
mono
North America
Some
Read the doc first.
2024-08-01
Yash
34
M
F
mono
San Francisco Bay AreaNYC
Some
avjscfhr@duck.com
2024-08-01
Paul
23
M
F
mono
Berlin
Some
@paule03
2024-07-30
Brian Hodges
57
M
FNB
mono
Flexible
industrial9999@aol.com
2024-07-29
Steven Elleman
29
M
F
mono
San Francisco Bay Area
Flexible
steven.elleman@gmail.com
2024-07-28
Daryna
27
F
M
mono
Berlin
Some
@silxxdar on Telegram or Instagram
2024-07-26
Chiaki Mizuta
35
F
FMNB
mono
LondonUK
Flexible
chiakimizuta61@gmail.com
2024-07-21
Beat
24
M
F
mono
Central Europe
Some
In the doc :)
2024-07-20
Joann C
44
F
M
mono
San Francisco Bay Area
Some
https://forms.gle/7F3X29KF7dXoSmzV9
2024-07-18
IM
44
M
F
mono
Asia
Flexible
Please refer to the doc
2024-07-14
Campbell Hutcheson
33
M
F
mono
San Francisco Bay AreaNYC
Flexible
nchutcheson@gmail.com
2024-07-09
Shray J-S.
27
M
F
mono
LondonUKFlexible
Flexible
shray.jain-surana@hotmail.com | +447552150653 | Calendly: https://calendly.com/shray_js/30-mins-with-shray
2024-07-07
(Kir)Sten
35
FNB
FMNB
Any
San Francisco Bay Area
Some
6kpqjfea@duck.com
2024-06-27
Sisi
31
F
M
mono
San Francisco Bay Area
Some
https://forms.gle/Ywsjv9518mas9sHq9
2024-06-24
Francesca
32
FNB
FMNB
poly
San Francisco Bay AreaBerkeley
Some
🤙See doc!
2024-06-20
Allan J.
35
M
F
mono
DC
None
Discord: Cellie Twitter: @CellieALC
2024-06-03
Aleksandar
35
M
F
mono
San Francisco Bay AreaCentral Europe
Flexible
See the doc
2024-06-01
Jaiden
18
NB
FMNB
mono
North America
Some
My discord is "jaiden115", and my snap is "JaidenTheRadiant"
2024-06-01
TJ
39
M
F
mono
Western USLos Angeles
Flexible
See doc
2024-05-31
T.
27
F
M
mono
Boston
Flexible
See doc
2024-05-31
Akshay
27
M
F
mono
NYC
None
akshay.balwally96@gmail.com
2024-05-27
Nadia
28
F
M
Any
LondonBerlinCentral Europe
Flexible
see in doc
2024-05-25
Phoenix
35
F
M
mono
UKCentral EuropeAsia
Flexible
ashesphoenix235@gmail.com
2024-05-24
Harry Altman
37
M
FNB
poly
NYC
Some
see end of doc
2024-05-22
Matt Reardon
33
M
F
mono
NYCDCChicagoLondon
Flexible
mjreard90@gmail.com
2024-05-22
Nick Graham
47
M
F
mono
LondonUK
Flexible
https://www.linkedin.com/in/nickgraham77/
2024-05-18
Luca
44
M
F
mono
NYCLondonUKBerlinVancouverNYCentral EuropeBrazilDubaiSouth of FranceNorth AmericaAsiaVancouver IslandRibeirĂŁo Bonito
Flexible
peteray77@gmail.com
2024-05-17
Rishi Mohnot
34
M
F
mono
San Francisco Bay Area
Flexible
rsmohnot@gmail.com
2024-05-16
Marcus Doshi
49
M
F
mono
Colorado
None
marcus@marcusdoshi.com
2024-05-09
Joao
48
M
F
mono
LondonUKCambridge
Flexible
djeidot@gmail.com
2024-05-05
Ricardo F.
42
M
F
mono
Miami
Flexible
786-419-6488
2024-05-02
Greg Rosenthal
28
M
F
mono
UKCambridge
Some
See doc.
2024-04-29
Domo Hazzard
33
FNB
FMNB
poly
DC
Some
https://docs.google.com/forms/d/e/1FAIpQLSccVxbjnBme5IVjfvsgaCVBQCJyUyfERRD11sCvl3twOTJrpw/viewform
2024-04-29
Sai Prasanna
29
M
F
mono
San Francisco Bay AreaNYCBostonPortlandLos AngelesLondonUKTorontoBerlinCanadaCentral EuropeAmsterdam
Some
sai.r.prasanna@gmail.com
2024-04-23
Bilqis R
35
F
M
mono
LondonUK
Some
Instagram @hej.bilqis
2024-04-21
Devin Maureen
34
F
M
mono
San Francisco Bay Area
Some
devinmnadi@gmail.com
2024-04-20
Sean Langhi
30
MNB
FMNB
Any
San Francisco Bay Area
Some
See doc
2024-04-20
Lane Huitt
28
M
FNB
mono
Chicago
Some
lane@lanehuitt.com
2024-04-15
Kerry M
32
M
F
mono
Colorado
Some
see doc
2024-04-15
Meaningful Existence
38
M
FNB
Any
Flexible
meaningfulexistence@yandex.com
2024-04-15
Dan Kendall
30
M
F
mono
UK
Some
https://www.cognitoforms.com/DanKendall/DanKendallDateMeContactFormAllOptional
2024-04-14
Y
28
M
FM
monopoly
Western US
Some
E-mail in doc
2024-04-13
Kiya
32
F
M
mono
NYC
Flexible
see doc
2024-04-12
Omar
31
M
F
mono
Central Europe
None
Telegram: @Jerid616 (use hashtag #JustReadYourDateMeDoc)
2024-04-12
Lilith
32
F
MNB
mono
NYCNY
Some
hihellolilith@gmail.com
2024-04-11
Jonathan B
38
M
F
mono
NYC
Flexible
datejonb@gmail.com
2024-04-09
Matt
38
M
M
mono
Chicago
Flexible
boarded-prices0g@icloud.com
2024-04-06
Katie
36
F
M
mono
LondonUK
Flexible
See end of doc :)
2024-04-02
Ben Rachbach
34
M
FNB
monopoly
San Francisco Bay Area
Some
datebenrachbach@gmail.com
2024-03-30
Benedict Ide
30
M
F
poly
Rhode Island
Flexible
benedictide@gmail.com
2024-03-26
Anya
35
F
MNB
mono
Asia
Some
rosesoutofthesnow@gmail.com
2025-01-11
neutraluce
45
NB
NBFM
poly
Some
lucemelove@gmail.com
2024-03-23
Kayla Pio
31
F
FMNB
mono
San Francisco Bay AreaSacramentoMonterey
Some
see doc
2024-03-22
Diego
41
M
F
monopoly
San Francisco Bay Area
Flexible
VT7684@gmail.com
2024-03-19
Monano Pierre-Paul
29
M
F
mono
NYCNJ
Flexible
MonanoPierrePaul@gmail.com
2024-03-18
Karthik
38
M
F
monopoly
NYC
Flexible
609 613 2710
2024-03-18
Jamie
37
M
F
mono
Los Angeles
None
datemedoc.magnetize042@passinbox.com
2024-03-16
Shyrome
47
M
F
mono
Flexible
Flexible
ripe_ostrich0g@icloud.com
2024-03-16
Ava
38
F
M
mono
Flexible
Flexible
apommerenk@gmail.com
2024-03-14
Divya
37
F
M
mono
Chicago
Flexible
divs.joy@gmail.com
2024-03-13
Kyron
23
M
F
mono
Chicago
Some
Discord: kyron54
2024-03-13
Julie D
34
F
MF
mono
DC
None
See doc
2024-03-11
Holden Lee
32
M
F
mono
DCPhiladelphia
Some
oldheneel@gmail.com
2024-03-11
Sebastian Schmidt
31
M
F
mono
LondonOxfordSan Francisco Bay AreaAmsterdamBerlin
Some
sebastian@sebastianschmidt.world
2024-03-09
Eleanor Huntington
35
F
M
mono
Los AngelesChicago
Some
https://forms.gle/pyhFob135nVSTd719
2024-03-07
Lily
32
F
M
mono
San Francisco Bay Area
None
See doc
2024-03-07
Roberto
32
M
F
mono
Central EuropeBerlin
Flexible
lazy.romantic.nerd@gmail.com
2024-03-05
Neissa
26
F
M
mono
San Francisco Bay Area
Some
neissa@dorsinville.com
2024-03-02
Sophie
31
F
M
mono
LondonFlexibleAsia
Some
shsph6@gmail.com
2024-03-02
Blake
28
M
F
mono
Los Angeles
blakeraya.fractoid@gmail.com
2024-02-27
Victoria
25
F
M
mono
FlexibleUK
Flexible
victoriadorheim@gmail.com
2024-02-25
Ryan
33
M
F
monopoly
LondonSan Francisco Bay Area
Some
see doc
2024-02-20
Bee
49
M
F
San Francisco Bay Area
brendanbradley1974@gmail.com
2024-02-20
Kim Korte
31
M
F
mono
Berlin
Some
@akimbow on Telegram or psaniko@gmail.com
2024-02-19
Jacob
35
M
F
monopoly
BrightonLondonUK
Some
See doc
2024-02-19
Allan J
35
M
F
mono
DC
None
https://twitter.com/CellieALC
2024-02-18
Micole Rondinone
35
F
M
mono
NYCNYNorth America
Flexible
micole.rondinone@gmail.com
2024-02-18
Jennie Rose
35
F
M
mono
NYCNY
Some
jrh325@gmail.com
2024-02-17
Joe Walz
45
M
F
mono
North America
Some
joejoewalz@gmail.com
2024-02-16
Taren Stinebrickner-Kauffman
42
F
M
monopoly
San Francisco Bay Area
None
datetaren@gmail.com
2024-02-16
Stevie
20
M
F
mono
San Francisco Bay AreaNYCDC
Some
steviebmiller2@gmail.com
2024-02-16
Ariel Vargas
41
M
F
mono
Flexible
ariel.arielv@gmail.com
2024-02-16
Ian
33
M
M
mono
North America
Flexible
datethetulsaguy@gmail.com
2024-02-15
Dan!
26
M
F
poly
Boston
Flexible
datemedansubmissions@gmail.com
2024-02-14
Carly
36
F
M
mono
Boston
None
carlyhodes@gmail.com
2024-02-14
Cole
31
M
F
mono
NY
thecole777@gmail.com
2024-02-12
Abeer Agrawal
33
M
F
mono
San Francisco Bay Area
Some
abeer.ag@gmail.com
2024-02-08
Debbie
51
F
M
mono
UK
Some
chickenlegs70@yahoo.co.uk
2024-02-07
Mitchell Reynolds
32
M
F
mono
San Francisco Bay Area
Some
https://forms.gle/TzLYUCcAMY5ox9B56
2024-02-05
George
22
M
FNB
mono
UK
Some
dmdgeorge24@gmail.com
2024-02-05
Helga
36
F
M
mono
Central Europe
Flexible
https://t.me/OlyaRiv
2024-02-02
Samantha
38
F
M
mono
DCPhiladelphia
None
See doc
2024-01-30
Oz Chen
34
M
F
mono
Los Angeles
Some
It's in my Date Me Doc :)
2024-01-29
Avi
23
M
F
mono
NYC
see doc :)
2024-01-26
Richard Nicholson
30
M
F
mono
San Francisco Bay Area
Flexible
elathrain@gmail.com
2024-01-25
Kyle West
31
M
F
mono
None
kyle.west@wheehaa.com
2024-01-25
William Wolf
28
M
FM
mono
NYC
None
hi@willium.com
2024-01-24
Angie
23
F
M
mono
Central Europe
Some
shirona4444@gmail.com
2024-01-24
DH
31
F
M
mono
Seoul
Flexible
My Username at Telegram @delightfulhours
2024-01-24
Lisetts
40
F
M
mono
Flexible
Shoplarimar@gmail.com
2024-01-24
Ana Zenobia
26
F
NB
Some
anitalantigua30@gmail.com
2024-01-24
Ruth Celina Martinez Castillo
28
F
M
mono
Some
8095193356
2024-01-23
K
40
F
M
mono
London
Some
seno.radsky@gmail.com
2024-01-23
Tanner
40
M
F
mono
Amsterdam
Flexible
See in doc.
2024-01-21
Victor Gorleku
33
M
F
mono
Some
graygv7@gmail.com
2024-01-21
Mary
44
F
M
mono
Los Angeles
None
In doc
2024-01-18
Stephanie
36
F
MF
mono
San Francisco Bay Area
Some
datingstephanief@gmail.com
2024-01-15
Liza
24
F
M
mono
FlexibleAsiaCentral EuropeNorth America
Flexible
lizakopy@outlook.com
2024-01-14
Irina
44
F
M
mono
jinakiss@gmail.com
2024-01-13
Alice
24
F
M
mono
Asia
Some
1066429751@qq.com
2024-01-13
Nurdaulet
20
M
F
poly
Asia
None
https://t.me/NurdauletShk
2024-01-12
Dan
36
M
F
mono
London
Some
dansherid@gmail.com
2024-01-12
Travis
40
M
F
mono
Canada
Flexible
see doc
2024-01-12
Irina
44
F
M
mono
Flexible
Irinasolnca (telegram)
2024-01-11
Paulin
29
M
F
South of France
Some
pppauling@outlook.com
2024-01-10
Sheena
41
F
MF
mono
SeattleWAFlexible
Flexible
sheeniebeenie@gmail.com
2024-01-10
River
38
NBM
FNB
monopoly
NYCSan Francisco Bay AreaDC
Flexible
river.f.bellamy@gmail.com
2024-01-10
Mars
32
M
F
polymono
San Francisco Bay Area
Some
x.com/marknadal
2024-01-10
Lexi
25
F
M
mono
WI
Flexible
hello.lexii101@gmail.com
2024-01-09
Kavindu Bimsara Fernando
28
M
F
mono
Asia
Some
94710119042
2024-01-09
Nita Jain
31
F
M
mono
North AmericaFlexible
Flexible
nitajain8@gmail.com
2024-01-09
Yuliya
32
F
M
mono
see in doc
2024-01-08
Ksenia
32
F
M
mono
Kseniyavogue@gmail.com
2024-01-08
Bee
49
M
F
mono
San Francisco Bay Area
Some
brendanbradley1974@gmail.com
2024-01-08
Talu Velludo
34
F
M
monopoly
BostonMA
Some
talu@c3-english.com
2024-01-08
Judith
23
F
M
mono
San Francisco Bay AreaNYCNYWestern USSouthern US
Flexible
flowersjudit.h9.3@gmail.com
2024-01-08
Connor
25
M
F
mono
DenverColoradoLos AngelesWestern US
Some
See contact info in doc.
2024-01-07
Yulia
46
F
M
mono
Central EuropeLondonAmsterdamSouth of France
Some
yulyru@gmail.com
2024-01-07
Eric
43
M
F
mono
North AmericaBoston
None
Langevinvt@gmail.com
2024-01-07
Jacob
39
M
F
mono
San Francisco Bay Area
Some
6266795421
2024-01-07
Xing Ye
27
M
F
London
Flexible
07440685729
2024-01-06
Rebecca
28
F
M
mono
Central Europe
Flexible
beccamullier@hotmail.com
2024-01-06
jocy.wu
48
F
M
mono
Asia
Flexible
281056154@qq.com
2024-01-06
Edwin
33
M
F
mono
Some
ronyargueta123@gmail.com
2024-01-06
S
28
F
M
polymono
San Francisco Bay Area
Some
https://forms.gle/fJZBHGULUC7y3bmq6
2024-01-06
Padma
40
F
M
mono
Toronto
None
+1 9057829528
2024-01-05
Lilith
17
F
FMNB
monopoly
Some
lilit.hananushyan@yandex.ru
2024-01-05
Matthew
21
M
F
mono
UK
None
07443 561341
2024-01-05
Karryl
41
F
M
mono
NYCNYLondonBrightonSeattleSouthern USTXNJSwedenLos AngelesSydney AustraliaONNorth CarolinaBostonNorth AmericaTorontoCanadaFlexiblePhiladelphiaUK
Flexible
silk0622@gmail.com
2024-01-05
Milka
41
F
M
mono
Central Europe
Flexible
lifelongpartnerformilka@gmail.com
2024-01-05
Anish Shah
37
M
F
mono
NYC
Flexible
anischster@gmail.com
2024-01-05
G. Scott Graham-Stephens
60
M
M
mono
gscottgrahamstephens@gmail.com
2024-01-04
Simon
30
M
F
mono
Central Europe
Some
meetsimon@pm.me
2024-01-04
Sandy
40
F
M
mono
Los Angeles
Some
sandylaca19@gmail.com
2024-01-04
Arina
18
F
M
mono
None
telegram @rinshmel
2024-01-03
Kay Day
40
F
M
mono
UK
Flexible
keday82@icloud.com
2024-01-03
Ben Dylan
39
M
F
poly
NYCLos AngelesFlexible
Flexible
bendylanxxx@gmail.com
2024-01-03
Scott
32
M
F
monopoly
San Francisco Bay Area
None
wampiter at gmail dot com
2024-01-02
Nosa
33
M
F
mono
ColoradoFlexible
Flexible
nosavalue@gmail.com
2023-12-29
Anna (Zane) Shive
29
F
FMNB
mono
San Francisco Bay Area
Some
annakshive@gmail.com
2023-12-29
Harrison
23
M
F
mono
Madison
Some
paekharrison@gmail.com
2023-12-28
Brett
25
M
F
mono
PA
Some
see bottom of page
2023-12-27
Tim
31
M
F
mono
San Francisco Bay Area
None
See doc
2023-12-27
Nadine
20
F
M
mono
San Francisco Bay Area
Flexible
nadinefrench26@gmail.com
2023-12-27
Yash Sharma
33
M
F
mono
NYC
Some
in the doc
2023-12-26
Benjamin
35
M
F
mono
DC
None
gamerguy@gmail.com
2023-12-26
Rocco
34
M
F
mono
ChicagoWI
Flexible
raber60@hotmail.com
2023-12-26
Puja Gandhi
37
F
M
mono
San Francisco Bay AreaSeattleBostonWestern US
Flexible
gandhi.pj@gmail.com
2023-12-25
Ridhi
32
F
M
mono
Boston
None
ridhi.chandarana@hotmail.com
2023-12-25
Aaron Bergman
23
M
F
mono
DC
Flexible
aaronb50@gmail.com
2023-12-23
SwirlsOfSouns
39
NB
F
2023-12-22
Tejas Subramaniam
22
M
FMNB
San Francisco Bay Area
Flexible
tejassubramaniam@gmail.com
2023-12-22
Nonie
49
F
M
mono
PortlandSan Francisco Bay AreaSeattleLos Angeles
Some
https://www.instagram.com/ultra_violet_lemon
2023-12-20
Sindhu
35
F
MF
mono
LondonUK
Some
In the doc
2023-12-18
Michael Greger
51
M
F
mono
DC
Flexible
mhg1@cornell.edu
2023-12-17
Dragos
27
M
F
monopoly
TorontoBerlinCanadaVancouver
Flexible
dragos@rotaru.co
2023-12-17
Alice
38
F
M
mono
Austin
Flexible
hecila@gmail.com
2023-12-14
Michael
33
M
F
mono
NYC
None
hello.there.msh@gmail.com
2023-12-12
Manan Ghelani
32
M
F
mono
France
Flexible
mghelani05@gmail.com
2023-12-11
Josiah
30
M
F
mono
DC
Some
1sensible.email.address@gmail.com
2023-12-11
Jon Lee
40
M
F
mono
San Francisco Bay AreaSouth Bay
None
hello@wronkyn.ca
2023-12-05
Luka
19
M
FM
mono
See bottom of doc
2023-12-03
Jackie Mc
44
F
M
mono
Brighton
Flexible
missjacquelinemccullough@googlemail.com
2023-12-02
Max Alexander
22
M
F
mono
NJ
Some
absurdlymax@gmail.com
2023-11-29
Courtney
33
F
M
mono
Some
melchione@gmail.com
2023-11-28
Thais
34
F
M
mono
Brazil
Flexible
cinema.thais@gmail.com
2023-11-27
Stephen W
51
M
F
mono
NYCPANJ
Some
See doc!
2023-11-19
Ujwal Velagapudi
32
M
F
mono
Southern USTX
Flexible
at the bottom of the doc
2023-11-17
Lawrence Chan
27
M
F
San Francisco Bay Area
Some
lawrencechan96 at gmail.com
2023-11-17
Cristian Trout
27
M
FNB
mono
NYCPortlandLondonSeattleVancouverSomervilleCentral EuropeBostonCambridgeDCMA
Some
ctroutcsi@gmail.com
2023-11-16
Andrew H
36
M
F
mono
SeattleWA
None
Google form in doc
2023-11-13
Louis Tse
34
M
F
mono
Los Angeles
Flexible
louistse1@gmail.com
2023-11-09
Anya
23
F
M
mono
NYC
Some
https://forms.gle/WSF4B1BapMTZUrxU9
2023-11-07
Nancy R
64
F
M
mono
PA
Flexible
Nancyjaneross@gmail.com
2023-11-06
Furqan
24
M
F
mono
Los AngelesDubai
Flexible
see notion link!
2023-11-06
Violet
38
F
MF
mono
Los AngelesNYC
Some
nerdygymkitten@gmail.com
2023-11-05
Ha
23
F
M
mono
NYC
None
see doc :)
2023-11-03
Abeer Agrawal
32
M
F
mono
San Francisco Bay AreaNYCNYWestern USBerkeley
Flexible
https://twitter.com/abeerag
2023-11-02
Anna Crow
22
F
FMNB
monopoly
UK
Flexible
Discord: aclockworkmagpie, email: annacrow@proton.me
2023-11-01
Alex Wilson
32
M
F
mono
San Francisco Bay Area
Some
https://twitter.com/awlego DM
2023-10-31
Nelson
31
M
F
mono
Berlin
Flexible
yewcb0yk@duck.com
2023-10-30
Alexandros Steven Martinez
29
M
NBMF
mono
South BayLos Angeles
None
310-818-1972 (cell); SouthBayNative1994 (Instagram); alclark815@gmail.com (email); @AlexandrosMart8 (Twitter)
2023-10-28
AP
32
M
F
mono
NYCNY
Flexible
dapurv5@gmail.com
2023-10-26
Alena
34
F
M
mono
Central EuropeBerlin
Some
2023-10-21
Kamil
24
M
M
mono
Central Europe
Some
postreduxx gmail
2023-10-19
Zak Kallenborn
33
M
F
mono
DC
Some
zkallenborn@gmail.com
2023-10-18
Frazer Kirkman
44
M
F
poly
San Francisco Bay Area
Some
Frazerkirkman@gmail.com
2023-10-16
Marta
35
F
M
poly
Central Europe
Flexible
SoYouWantToDateMarta[at]gmail[dot]com
2023-10-11
Vasco Grilo
25
M
F
mono
Central Europe
Some
+351918368684
2023-10-10
David
34
M
FMNB
monopoly
London
Some
see doc
2023-10-10
Jacques
31
M
F
mono
London
Some
https://x.com/jacquesthibs or thibo.jacques@gmail.com
2023-10-10
Niranjan Chavan
26
M
F
mono
Central Europe
Flexible
niranjanchavan1065@gmail.com
2023-10-07
Jay Geis
31
M
F
monopoly
DC
Flexible
https://docs.google.com/document/d/1uU_iDs-dut3kl2Dqm4oUDvU0CksCIMUU_JK2-vC1O4g/edit?usp=sharing
2023-10-06
Tara Schuster
36
F
M
mono
San Francisco Bay AreaLos Angeles
Flexible
Tara.Schuster@gmail.com
2023-10-06
Antonia
27
F
M
monopoly
BerlinCentral Europe
Some
@antoniabr on Telegram, other see doc
2023-10-04
Omair
27
M
F
mono
SeattleWAWestern USNorth America
None
see doc
2023-10-01
Kaushik Donthi
26
M
F
mono
San Francisco Bay AreaNYC
Some
5107714914
2023-09-30
Watson Ladd
32
M
MFNB
poly
San Francisco Bay Area
Some
watsonbladd@gmail.com
2023-09-30
Gina Stuessy
37
F
MNB
poly
San Francisco Bay Area
Some
See doc
2023-09-28
quinn
31
M
F
poly
San Francisco Bay AreaBerkeley
Some
quinnd@riseup.net
2023-09-28
Jess
36
F
M
mono
NYC
None
https://forms.gle/ku4Scg7pdr6QxUs76
2023-09-25
Dima
24
F
M
mono
NYC
None
see doc
2023-09-21
Paul
43
M
F
mono
NYC
Some
https://docs.google.com/forms/d/e/1FAIpQLSePxg2WeEGpIm2aIZ8enBf9xdhmDRsSWpX5eogour3NHykRvg/viewform
2023-09-19
Jessica
32
F
M
mono
Western US
Some
harumageddonhime@gmail.com
2023-09-19
Jessica
32
F
M
mono
Western US
Some
harumageddonhime@gmail.com
2023-09-19
Chris M
25
M
F
mono
Seattle
Some
christopher.morris55@gmail.com
2023-09-19
Ross
30
M
F
mono
Seattle
Some
See doc!
2023-09-17
Ben Weinstein-Raun
31
M
F
poly
San Francisco Bay Area
Some
b@w-r.me
2023-09-17
Kevin
24
M
F
mono
Flexible
Flexible
Insta @kevcampbell14
2023-09-14
Taylor
31
M
F
mono
Nebraska
Flexible
In doc
2023-09-14
Ryan McGuine
27
M
F
mono
Brighton
Some
2023-09-14
Mahir Jayswal
24
M
F
mono
Oregon
Flexible
Instagram : Mahir14_
2023-09-14
Isabel Hasse
24
F
FMNB
monopoly
Oregon
Flexible
Facebook
2023-09-14
Marcos Abraao
40
M
F
mono
Some
See doc
2023-09-14
Christina
42
F
M
mono
Ladysmith BC
2023-09-14
Nancy
31
F
M
mono
NYCFlexible
Flexible
@nanseaful
2023-09-14
Enishi
25
M
F
mono
Asia
Some
https://twitter.com/eni_naka
2023-09-12
Sohit
25
M
F
mono
NYC
Some
sohitmiglani@gmail.com
2023-09-12
Alex
36
M
F
mono
LondonUK
Email in doc
2023-09-10
John
29
M
FNB
monopoly
UK
None
johnrwoolley0@gmail.com
2023-09-09
Laurence
31
M
F
mono
NYCNJ
None
lrnc.lau@gmail.com
2023-09-08
Cher Hu
24
F
M
mono
San Francisco Bay AreaNYC
Some
yunfei.cherhu@gmail.com
2023-09-05
Jake Gloudemans
25
M
F
mono
DCPhiladelphia
Some
jake.gloudemans@gmail.com
2023-09-05
Malvin
32
M
F
mono
NJ
Flexible
https://forms.gle/oxZGCRJj1VCv5J4dA
2023-09-05
Ryan
42
M
F
mono
Seattle
None
(360) 995 - 3421
2023-09-05
Tauno
30
M
F
monopoly
Central Europe
Flexible
cooldrylichen@protonmail.com
2023-09-03
Guy
33
M
F
mono
BrightonLondon
Some
guy.aziz@protonmail.com
2023-09-03
Lauren
32
F
FM
mono
London
Some
lagilbert@gmail.com
2023-08-31
Ben Orenstein
39
M
F
polymono
BostonMA
Some
ben@benorenstein.com
2023-08-30
Jacob (Jisk) Kopczynski
32
M
F
poly
San Francisco Bay Area
Some
ja.kopczynski@gmail.com, Discord @_jisk
2023-08-30
Jeff Chang
37
M
F
NYCSan Francisco Bay Area
Some
jeffchang@gmail.com
2023-08-29
Brian
44
M
F
monopoly
Austin
Some
See my doc ;)
2023-08-28
Jeremy S
38
M
F
mono
Southern US
Flexible
See email in doc
2023-08-28
Charles
24
M
F
mono
PhiladelphiaFlexible
Flexible
Listed in the doc :)
2023-08-27
Rico
28
M
F
mono
WIFlexibleNorth CarolinaNorth AmericaChicagoTX
Flexible
ricojrobbins@gmail.com
2023-08-26
Amy
28
F
MFNB
mono
Los Angeles
None
@amyleeskates
2023-08-26
Anton
40
M
F
mono
Boston
Flexible
tonicave@aol.com
2023-08-26
Kemal Abuhan
56
M
F
mono
San Francisco Bay Area
Flexible
kabuhan@hotmail.com
2023-08-25
Jessica
32
F
M
mono
Western US
Some
harumageddonhime@gmail.com
2023-08-25
Vipra
26
F
M
mono
Asia
Flexible
viprapathak96@gmail.com
2023-08-25
Lars Hansen
31
M
F
mono
Central Europe
Some
See Doc!
2023-08-24
Kevin
39
M
F
mono
Austin
Flexible
kevin@myplaceonline.com
2023-08-24
Julia Silbergeld
39
F
M
mono
San Francisco Bay Area
None
juliaheartsthebay@gmail.com
2023-08-23
Cory Hinkle
26
M
F
mono
OxfordOhioIndianapolis
Some
DM @coryclauz on Twitter or caboose2233 on IG
2023-08-23
Alexandros Steven Martinez
29
M
FMNB
mono
Los AngelesSouth Bay
Flexible
3108181972
2023-08-22
Taylor
29
F
M
mono
NYC
Flexible
646-701-5901
2023-08-22
Semin
42
F
M
monopoly
SeoulAsiaFlexible
Flexible
semin.shim@gmail.com
2023-08-21
Varun
32
M
F
monopoly
Sacramento
Some
varunarora.mct+dmd@gmail.com
2023-08-21
J
35
NB
FMNB
mono
Toronto
Flexible
mightbeyourmatch@gmail.com
2023-08-21
Lune
30
F
M
mono
Berlin
Flexible
https://www.okcupid.com/profile/17018999571702682544
2023-08-21
Anastasia
50
F
M
mono
Central Europe
Some
See form in doc
2023-08-21
Mike
70
M
F
mono
Colorado
Some
m888653.denver@gmail.com
2023-08-21
Colleen
59
F
M
mono
Chicago
Flexible
colleenmahon@gmail.com
2023-08-21
Gustavo Cunha
36
M
F
mono
Brazil
None
+5562981214448
2023-08-21
Bennett Gebken
34
M
NBF
polymono
DCNorth America
Some
email in doc or IG @bennettgebken
2023-08-21
Felipe
28
M
F
mono
Brazil
Flexible
See doc
2023-08-21
Niki Paulk
39
F
M
mono
San Francisco Bay Area
None
Twitter (@Nicole_Paulk) or email (nikipaulk@gmail.com)
2023-08-21
Lucas
26
M
F
mono
Brazil
lucasps26@mail.com
2023-08-21
Ilya S
39
M
mono
Boston
Some
617-932-9115 / ilyasitnikov03@gmail.com
2023-08-21
Dan L
27
M
F
mono
San Francisco Bay Area
None
847-691-1042
2023-08-21
Weiwen
35
M
MNB
monopoly
North America
Flexible
see doc
2023-08-21
Yolande
26
F
M
mono
Boston
Some
lonearchivistboston@gmail.com
2023-08-21
Tamera
28
F
M
San Francisco Bay Area
Text me at the number in my dating doc!
2023-08-21
Robert Nusbaum
62
M
F
mono
Central Europe
Flexible
maiwenn.kafka@gmail.com
2023-08-21
Kadi
39
F
M
mono
NYC
datekadi@gmail.com
2023-08-21
Neall
28
M
F
mono
NYCDCSan Francisco Bay Area
Flexible
@neallseth
2023-08-21
marie
36
F
M
mono
Los Angeles
Some
https://forms.gle/7tYAV1MvAWWdhJgn7
2023-08-21
Svitlana
24
F
FM
monopoly
San Francisco Bay Area
Some
s.midianko@gmail.com
2023-08-21
Priya P
34
F
M
mono
San Francisco Bay Area
Some
https://docs.google.com/forms/d/e/1FAIpQLSetdiMRUyCtKSXuAZ581Q-DOJkS9GPoVeagAD8iBNN7ldVLcA/viewform?usp=sf_link
2023-08-21
Xavier
33
NBM
FNB
poly
NYC
Some
https://docs.google.com/forms/d/e/1FAIpQLScBUdUuOf8I9Ak52jq4RFvPtYyCuoNN1hih6EFhe2ksR-xabw/viewform?usp=send_form
2023-08-21
Patricia Monthe
39
F
M
mono
Amsterdam
Flexible
Patricia.monthe@icloud.com
2023-08-21
Ryan
46
M
F
mono
DC
Flexible
ryan@speakerblast.com
2023-08-21
Jeff
35
M
F
mono
CTNew Haven
None
jtcoutts@gmail.com
2023-08-21
Connie
33
F
M
mono
San Francisco Bay Area
Some
https://twitter.com/lishiyori/
2023-08-21
Josh
34
M
F
mono
Los Angeles
Some
Form on dating doc
2023-08-21
Eduardo
26
M
F
mono
PA
Some
elihumunguia7@gmail.com
2023-08-17
Swami
28
M
F
mono
PA
Flexible
Form and contact info in dating doc
2023-08-14
HERIK
31
M
F
mono
Flexible
9033711517
2023-08-13
Kyleigh
30
F
mono
Los Angeles
Some
Look in doc 🙂
2023-08-08
Omar
33
M
F
mono
NYCNJ
None
ig: yankeesten1
2023-08-07
Prasad
25
M
F
mono
San Francisco Bay Area
Flexible
See doc :)
2023-08-07
Mahir Jayswal
24
M
F
mono
NYC
Flexible
Instagram : Mahir14_
2023-08-07
Ravi Roshan
27
M
F
Flexible
roshanraviraj@gmail.com
2023-08-07
Sakshi
38
F
M
mono
ChicagoLondonSan Francisco Bay Area
Flexible
sakschadha@gmail.com
2023-08-04
Claire
20
F
FMNB
mono
NYCIndianapolis
Some
please see doc!
2023-08-03
Rita
24
F
M
mono
DC
Flexible
ritasabri00@gmail.com
2023-08-03
Surya Kasturi
31
M
F
mono
Boston
Flexible
2023-08-03
Victoria
30
F
M
mono
Boston
Some
2023-08-03
Shanni
30
F
M
mono
Vancouver
Some
https://www.instagram.com/shanni_daily_drawing/
2023-08-03
Johnson
30
M
F
polymono
Flexible
johnsonhsieh310@gmail.com
2023-08-03
Kara
35
F
M
mono
NYCBoston
Some
kjancourtz@gmail.com
2023-08-03
Nate Strum
22
M
F
monopoly
Flexible
natestrum@rocketmail.com
2023-08-03
Aella
31
F
M
poly
San Francisco Bay AreaAustin
Flexible
aellasinbox@gmail.com
2023-08-03
Lulie Tanett
34
F
M
mono
Oxford
Some
DM @reasonisfun on Twitter
2023-08-03
Joseph
29
M
F
mono
London
Some
2023-08-03
Tyler Johnston
23
M
FNB
mono
Flexible
tylerthomasjohnston@gmail.com
2023-08-03
Nicole Kelner
29
F
M
mono
NYNYC
Some
nicolek13@gmail.com
2023-08-03
Ansh Radhakrishnan
23
M
F
mono
San Francisco Bay Area
Some
See doc!
2023-08-03
Mark
34
M
F
mono
Berlin
Some
date.mark.1co4i@simplelogin.com
2023-08-03
Tyler Alterman
33
M
F
NYC
Some
https://docs.google.com/forms/d/e/1FAIpQLSfz0F9mEMVEr-PATsw3FPA0XpB6qAxcM85f4r_tMV7n-Txs3A/viewform
2023-08-03
Eli Tyre
29
M
F
monopoly
San Francisco Bay Area
Some
elityre@gmail.com
2023-08-03
Emanuel Rylke
30
M
F
mono
Berlin
Some
ema@mailbox.org
2023-08-03
Armand Cognetta
35
M
F
mono
San Francisco Bay Area
Some
https://twitter.com/armandcognetta
2023-08-03
Aron Mill
30
M
F
mono
Berlin
None
aronmill1992@gmail.com
2023-08-03
Eneasz Brodski
42
M
F
poly
Denver
Flexible
embrodski@gmail.com
2023-08-03
Bill
36
M
F
DC
Some
IG: billbeaver_
2023-08-03
Gavriel Kleinwaks
26
F
M
mono
DCNorth AmericaColoradoDenverFlexible
Flexible
gavriel.kleinwaks@gmail.com
2023-08-03
Julian WIse
29
NBM
FNB
monopoly
NYCNYSan Francisco Bay AreaAustinNorth America
Flexible
pitter.patter.precisely@gmail.com
2023-08-03
Carissa Cassiel
38
F
MF
poly
Georgia
Flexible
fluffypeanuts@gmail.com, Facebook Messenger: Carissa Lorraine Cassiel
2023-08-03
Tyrone-Jay Barugh
29
M
F
mono
Flexible
Flexible
tyronebarugh+dating@gmail.com or @barughtyrone on twitter
2023-08-03
Juma Al-JouJou
37
M
F
poly
Berlin
None
Email or FB
2023-08-03
Nathan Young
29
M
F
monopoly
London
Flexible
@nathanpmyoung
2023-08-03
Kevin Wheeler
32
M
F
polymono
Lubbock
Flexible
kevinwheeler90@gmail.com facebook.com/kevin.wheeler
2023-08-03
Quinn Dougherty
29
M
FNB
poly
PhiladelphiaPA
Some
quinnd@riseup.net
2023-08-03
Gustavo
43
M
FNB
monopoly
San Francisco Bay AreaBerlinAshevilleVancouver Island
Flexible
2023-08-03
Dan
38
M
F
poly
Chicago
Some
2023-08-03
Agnieszka
34
F
M
mono
LondonBrighton
Some
facebook
2023-08-03
Liav Koren
42
M
F
monopoly
TorontoCanada
2023-08-03
Meredith
32
F
M
mono
San Francisco Bay Area
2023-08-03
Graham Bessellieu
33
M
F
mono
EwingNJ
Flexible
2023-08-03
Robert Mushkatblat
29
M
F
mono
BerkeleySan Francisco Bay Area
2023-08-03
Daystar Eld
35
M
F
polymono
Flexible
2023-08-03
Mati Roy
31
M
FM
poly
North America
Flexible
2023-08-03
Catherio
32
F
mono
San Francisco Bay Area
2023-08-03
David
30
M
FMNB
poly
London
2023-08-03
Quinn
29
M
F
poly
PAPhiladelphia
2023-08-03
Wiskerz
32
M
F
mono
South of France
2023-08-03
Shaked
30
M
F
NYC
2023-08-03
Kathy Garcia
29
NB
FM
poly
CambridgeMA
Flexible
2023-08-03
Neil Thawani
34
M
F
mono
DenverColorado
2023-08-03
David
34
M
F
mono
Western US
2023-08-03
Rachel Clifton
24
F
M
polymono
London
Flexible
twitter.com/rachelclif
2023-01-23
Dony
27
M
FMNB
San Francisco Bay Area
https://calendly.com/donychristie/30min
2022-10-16
gruffyddgozali
20
M
F
London
2022-10-16
Dan
34
M
F
monopoly
SomervilleMA
2022-10-16
BlaĂŻse (bless)
38
NB
M
mono
Ladysmith BC
None
Academia_nut@shaw.ca
2022-10-14
Brian Tomasik
35
M
FNB
mono
NY
Flexible
2022-10-01
Wes
39
M
F
poly
CollingswoodNJ
2022-09-29
Mercer
22
M
NYC
2022-09-29
Bhargab Acharya
27
M
2022-09-29
\ No newline at end of file diff --git a/nextjs-auth-starter.png b/nextjs-auth-starter.png deleted file mode 100644 index c40063cd..00000000 Binary files a/nextjs-auth-starter.png and /dev/null differ diff --git a/notebooks/meeting_rational.ipynb b/notebooks/meeting_rational.ipynb deleted file mode 100644 index 631259bb..00000000 --- a/notebooks/meeting_rational.ipynb +++ /dev/null @@ -1,468 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "id": "f0fca831fd4bce0b", - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-11T17:45:28.758995Z", - "start_time": "2025-07-11T17:45:28.753825Z" - } - }, - "source": [ - "from numpy.linalg import norm\n", - "import numpy as np\n", - "\n", - "# value openness\n", - "value_openness = .4\n", - "\n", - "n_connections_per_person = 4\n", - "\n", - "# value alignment for each person\n", - "values = np.random.random((100, 2))\n", - "values" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0.50541276, 0.96489386],\n", - " [0.69923343, 0.51486219],\n", - " [0.51818961, 0.55622392],\n", - " [0.82471679, 0.85683328],\n", - " [0.03003602, 0.40893862],\n", - " [0.72340702, 0.45851414],\n", - " [0.96031095, 0.91176534],\n", - " [0.77762674, 0.93060203],\n", - " [0.73366894, 0.62942441],\n", - " [0.16556218, 0.52102087],\n", - " [0.28297315, 0.949682 ],\n", - " [0.84873053, 0.03402777],\n", - " [0.67030246, 0.43412316],\n", - " [0.10195847, 0.58346601],\n", - " [0.73732509, 0.89413267],\n", - " [0.93932095, 0.08508319],\n", - " [0.66873754, 0.02710137],\n", - " [0.93756584, 0.15149255],\n", - " [0.45837504, 0.28230035],\n", - " [0.80052405, 0.13128764],\n", - " [0.49238007, 0.70684337],\n", - " [0.37129101, 0.90424873],\n", - " [0.38671108, 0.6224561 ],\n", - " [0.32006823, 0.93773524],\n", - " [0.21180011, 0.90088257],\n", - " [0.62984921, 0.64543132],\n", - " [0.78963413, 0.89228071],\n", - " [0.54353751, 0.34561676],\n", - " [0.04952843, 0.59392552],\n", - " [0.62928888, 0.32419132],\n", - " [0.69862464, 0.07755117],\n", - " [0.90439098, 0.67790266],\n", - " [0.06802643, 0.27465137],\n", - " [0.48588699, 0.81436865],\n", - " [0.93242716, 0.89261304],\n", - " [0.417973 , 0.46572186],\n", - " [0.2035363 , 0.97260404],\n", - " [0.41922857, 0.78336934],\n", - " [0.35223713, 0.58269557],\n", - " [0.55471428, 0.80081503],\n", - " [0.23442792, 0.23371869],\n", - " [0.05500204, 0.15545015],\n", - " [0.01122013, 0.17282004],\n", - " [0.72287723, 0.01213723],\n", - " [0.45460454, 0.58002577],\n", - " [0.01925273, 0.5971478 ],\n", - " [0.29925279, 0.30300129],\n", - " [0.24913729, 0.9677658 ],\n", - " [0.99415867, 0.53593297],\n", - " [0.94808735, 0.40614115],\n", - " [0.87990825, 0.64789485],\n", - " [0.13135803, 0.5403963 ],\n", - " [0.76824445, 0.32741741],\n", - " [0.45964502, 0.41040048],\n", - " [0.6865855 , 0.87705836],\n", - " [0.58758102, 0.66641753],\n", - " [0.14212951, 0.13627496],\n", - " [0.43423354, 0.18794528],\n", - " [0.86829682, 0.02995288],\n", - " [0.74781507, 0.32179226],\n", - " [0.84406153, 0.91962371],\n", - " [0.90573452, 0.30864335],\n", - " [0.44533079, 0.42186724],\n", - " [0.85909674, 0.47823898],\n", - " [0.12259992, 0.32190149],\n", - " [0.2057768 , 0.58800185],\n", - " [0.71858991, 0.99843546],\n", - " [0.55181692, 0.07687816],\n", - " [0.21165845, 0.82401785],\n", - " [0.36802147, 0.81062941],\n", - " [0.53343057, 0.73265878],\n", - " [0.24023319, 0.96739781],\n", - " [0.14427525, 0.4187982 ],\n", - " [0.28866763, 0.47114135],\n", - " [0.26618516, 0.7699329 ],\n", - " [0.6862106 , 0.83642333],\n", - " [0.7933839 , 0.99236947],\n", - " [0.14210864, 0.85743911],\n", - " [0.84807708, 0.48759296],\n", - " [0.45757035, 0.44831668],\n", - " [0.14748315, 0.63414228],\n", - " [0.48878589, 0.2863741 ],\n", - " [0.97285364, 0.43449953],\n", - " [0.67896612, 0.57878626],\n", - " [0.59473293, 0.61627698],\n", - " [0.02981777, 0.24087601],\n", - " [0.5993968 , 0.2581582 ],\n", - " [0.15193835, 0.62771533],\n", - " [0.34012668, 0.27448646],\n", - " [0.95317559, 0.85321408],\n", - " [0.8838663 , 0.64294991],\n", - " [0.3181282 , 0.47967143],\n", - " [0.38438976, 0.65332643],\n", - " [0.27296308, 0.57872169],\n", - " [0.03069519, 0.4041206 ],\n", - " [0.75799873, 0.87257359],\n", - " [0.54387531, 0.71991869],\n", - " [0.23263987, 0.08577908],\n", - " [0.73810136, 0.417901 ],\n", - " [0.82483447, 0.4766117 ]])" - ] - }, - "execution_count": 159, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 159 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-11T17:45:28.796624Z", - "start_time": "2025-07-11T17:45:28.794027Z" - } - }, - "cell_type": "code", - "source": [ - "accepted = norm(values, axis=1) < value_openness\n", - "user_values = values[accepted]\n", - "n_users = len(user_values)\n", - "user_values" - ], - "id": "45ec688cb3e8840a", - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0.06802643, 0.27465137],\n", - " [0.23442792, 0.23371869],\n", - " [0.05500204, 0.15545015],\n", - " [0.01122013, 0.17282004],\n", - " [0.14212951, 0.13627496],\n", - " [0.12259992, 0.32190149],\n", - " [0.02981777, 0.24087601],\n", - " [0.23263987, 0.08577908]])" - ] - }, - "execution_count": 160, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 160 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-11T17:45:28.898550Z", - "start_time": "2025-07-11T17:45:28.896274Z" - } - }, - "cell_type": "code", - "source": [ - "# user_values[0] = [0, 0]\n", - "# user_values[3] = [0, 0]\n", - "# user_values[2] = [openness] * 2\n", - "user_values" - ], - "id": "fb3c05d6dc9dadf3", - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0.06802643, 0.27465137],\n", - " [0.23442792, 0.23371869],\n", - " [0.05500204, 0.15545015],\n", - " [0.01122013, 0.17282004],\n", - " [0.14212951, 0.13627496],\n", - " [0.12259992, 0.32190149],\n", - " [0.02981777, 0.24087601],\n", - " [0.23263987, 0.08577908]])" - ] - }, - "execution_count": 161, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 161 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-11T17:45:29.000756Z", - "start_time": "2025-07-11T17:45:28.995783Z" - } - }, - "cell_type": "code", - "source": [ - "import numpy as np\n", - "import random\n", - "from collections import defaultdict\n", - "\n", - "\n", - "def make_connections(n, n_connections_per_person):\n", - " \"\"\"\n", - " Generate a symmetric undirected graph where each person has exactly\n", - " `n_connections_per_person` mutual connections.\n", - "\n", - " Assumes:\n", - " - n_connections_per_person < n\n", - " - (n * n_connections_per_person) must be even (required for undirected graph)\n", - "\n", - " Returns:\n", - " A dict mapping each person to a set of their connected people.\n", - " \"\"\"\n", - " if n_connections_per_person >= n:\n", - " raise ValueError(\"Each person must have fewer connections than total people.\")\n", - "\n", - " if (n * n_connections_per_person) % 2 != 0:\n", - " raise ValueError(\"Total number of connections must be even for mutual pairs.\")\n", - "\n", - " connections = defaultdict(set)\n", - " attempts = 0\n", - " max_attempts = 10000 # to prevent infinite loops\n", - "\n", - " while True:\n", - " # Clear previous attempts\n", - " for k in connections:\n", - " connections[k].clear()\n", - "\n", - " people = list(range(n))\n", - " success = True\n", - "\n", - " for i in people:\n", - " while len(connections[i]) < n_connections_per_person:\n", - " possible = list(set(people) - connections[i] - {i})\n", - " possible = [p for p in possible if len(connections[p]) < n_connections_per_person]\n", - " if not possible:\n", - " success = False\n", - " break\n", - " j = random.choice(possible)\n", - " connections[i].add(j)\n", - " connections[j].add(i)\n", - "\n", - " if not success:\n", - " break\n", - "\n", - " if success:\n", - " break\n", - "\n", - " attempts += 1\n", - " if attempts > max_attempts:\n", - " raise RuntimeError(\"Failed to generate a valid connection graph after many attempts.\")\n", - "\n", - " return dict(connections)\n", - "\n", - "\n", - "connections = make_connections(len(user_values), n_connections_per_person=n_connections_per_person)\n", - "connections" - ], - "id": "287ea5b687a0e603", - "outputs": [ - { - "data": { - "text/plain": [ - "{0: {2, 4, 6, 7},\n", - " 1: {2, 4, 5, 6},\n", - " 2: {0, 1, 4, 5},\n", - " 3: {4, 5, 6, 7},\n", - " 4: {0, 1, 2, 3},\n", - " 5: {1, 2, 3, 7},\n", - " 6: {0, 1, 3, 7},\n", - " 7: {0, 3, 5, 6}}" - ] - }, - "execution_count": 162, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 162 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-11T19:38:53.640720Z", - "start_time": "2025-07-11T19:38:53.542753Z" - } - }, - "cell_type": "code", - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "\n", - "def plot_connections(connections):\n", - " # n = len(connections)\n", - " # angles = np.linspace(0, 2 * np.pi, n, endpoint=False)\n", - " # positions = {i: (np.cos(a), np.sin(a)) for i, a in enumerate(angles)}\n", - " positions = {i: a for i, a in enumerate(user_values)}\n", - "\n", - " fig, ax = plt.subplots(figsize=(12, 12))\n", - " # openness = 1\n", - " ax.set_xlim(0, openness)\n", - " ax.set_ylim(0, openness)\n", - " # ax.set_aspect('equal')\n", - " # ax.axis('off')\n", - "\n", - " # Draw nodes\n", - " for i, (x, y) in positions.items():\n", - " ax.plot(x, y, 'o', color='black')\n", - " ax.text(x * 1.05, y * 1.05, str(i), ha='center', va='center')\n", - "\n", - " # Draw edges\n", - " drawn = set()\n", - " for i, neighbors in connections.items():\n", - " for j in neighbors:\n", - " if str((j, i)) not in drawn:\n", - " x0, y0 = positions[i]\n", - " x1, y1 = positions[j]\n", - " ax.plot([x0, x1], [y0, y1], color='gray')\n", - " drawn.add(str((i, j)))\n", - "\n", - " plt.title(\"Connections on Unit Circle\")\n", - " plt.show()\n", - "\n", - "\n", - "plot_connections(connections)" - ], - "id": "ea836b54e9db2be3", - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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AgMrPYhiG4eoiAAAAAAB40bEGHAAAAAAAExDAAQAAAAAwAQEcAAAAAAATlCmAf/rpp4qIiJC3t7eio6O1Z8+epx67c+dOWSyWJz6etWcpAAAAAAAvmlIH8CVLluj999/XL37xC8XFxalnz54aNGiQbty48czzLly4oISEBMdH06ZNy1w0AAAAAABVTam7oHfu3FkdOnRw7J0qSS1bttTw4cP18ccfP3H8zp071adPHz148EDVq1cvd8EAAAAAAFRFpdoHPDc3V8eOHdPPf/7zIq8PGDBA+/fvf+a5UVFRys7OVqtWrfTLX/5Sffr0eeqxOTk5ysnJcXxut9uVkpKiWrVqyWKxlKZkAAAAAABKzTAMpaenq27dunJzc077tFIF8Hv37slmsykkJKTI6yEhIUpMTCz2nNDQUMXGxio6Olo5OTn66quv1K9fP+3cuVOvvPJKsed8/PHH+u1vf1ua0gAAAAAAcLqbN28qLCzMKdcqVQAv9P1RaMMwnjoy3bx5czVv3tzxedeuXXXz5k396U9/emoA/+ijj/Thhx86Pk9NTVX9+vV18+ZNBQQElKVkAAAAAABKLC0tTeHh4fL393faNUsVwIOCguTu7v7EaPfdu3efGBV/li5dumjBggVP/bqXl5e8vLyeeD0gIIAADgAAAAAwjTOXQZdqIrunp6eio6O1ZcuWIq9v2bJF3bp1K/F14uLiFBoaWppbAwAAAABQpZV6CvqHH36ot99+Wx07dlTXrl0VGxurGzdu6Ac/+IGkgunjt2/f1vz58yVJn3zyiRo2bKjWrVsrNzdXCxYs0IoVK7RixQrnvhMAAAAAACqxUgfwt956S/fv39fvfvc7JSQkKDIyUt98840aNGggSUpISCiyJ3hubq7+4R/+Qbdv35aPj49at26tDRs2aPDgwc57FwAAAAAAVHKl3gfcFdLS0hQYGKjU1FTWgAMAAAAAKlxF5FDnbGYGAAAAAACeiQAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACcoUwD/99FNFRETI29tb0dHR2rNnT4nO27dvn6xWq9q3b1+W2wIAAAAAUGWVOoAvWbJE77//vn7xi18oLi5OPXv21KBBg3Tjxo1nnpeamqpJkyapX79+ZS4WAAAAAICqymIYhlGaEzp37qwOHTros88+c7zWsmVLDR8+XB9//PFTzxs7dqyaNm0qd3d3rV69WvHx8SW+Z1pamgIDA5WamqqAgIDSlAsAAAAAQKlVRA4t1Qh4bm6ujh07pgEDBhR5fcCAAdq/f/9Tz5s7d64uX76sX//61yW6T05OjtLS0op8AAAAAABQlZUqgN+7d082m00hISFFXg8JCVFiYmKx51y6dEk///nPtXDhQlmt1hLd5+OPP1ZgYKDjIzw8vDRlAgAAAABQ6ZSpCZvFYinyuWEYT7wmSTabTePHj9dvf/tbNWvWrMTX/+ijj5Samur4uHnzZlnKBAAAAACg0ijZkPT/ExQUJHd39ydGu+/evfvEqLgkpaen6+jRo4qLi9OPf/xjSZLdbpdhGLJarfr222/Vt2/fJ87z8vKSl5dXaUoDAAAAAKBSK9UIuKenp6Kjo7Vly5Yir2/ZskXdunV74viAgACdOnVK8fHxjo8f/OAHat68ueLj49W5c+fyVQ8AAAAAQBVRqhFwSfrwww/19ttvq2PHjuratatiY2N148YN/eAHP5BUMH389u3bmj9/vtzc3BQZGVnk/Nq1a8vb2/uJ1wEAAAAAeJGVOoC/9dZbun//vn73u98pISFBkZGR+uabb9SgQQNJUkJCwnP3BAcAAAAA4GVT6n3AXYF9wAEAAAAAZnL5PuAAAAAAAKBsCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOAAAAAIAJCOAAAAAAAJiAAA4AAAAAgAkI4AAAAAAAmIAADgAAAACACQjgAAAAAACYgAAOwOl+85vfyGKxFPmoU6eOq8sCAAAAXMrq6gIAvJhat26trVu3Oj53d3d3YTUAAACA6xHAAVQIq9XKqDcAAADwGKagA6gQly5dUt26dRUREaGxY8fqypUrri4JAAAAcCkCOACn69y5s+bPn6/Nmzdr1qxZSkxMVLdu3XT//n1XlwYAAAC4jMUwDMPVRTxPWlqaAgMDlZqaqoCAAFeXA6CUMjIy1LhxY/3TP/2TPvzwQ1eXAwAAADxXReRQRsABVDg/Pz+1adNGly5dcnUpAAAAgMsQwAFUuJycHJ07d06hoaGuLgUAAABwGQI4AKf7h3/4B+3atUtXr17VoUOHNGrUKKWlpWny5MmuLg0AAABwGbYhA+B0t27d0rhx43Tv3j0FBwerS5cuOnjwoBo0aODq0gAAAACXIYADcLqvv/7a1SUAAAAAlQ5T0AEAAAAAMAEBHAAAAAAAExDAAQAAAAAwAQEcAAAAAAATEMABAAAAADABARwAAAAAABMQwAEAAAAAMAEBHAAAAAAAExDAAQAAAAAwAQEcAAAAAAATEMABAAAAADABARwAAAAAABMQwAEAAAAAMAEBHAAAAAAAExDAAQAAAAAwAQEcAAAAAAATEMABAAAAADABARwAAAAAABMQwAEAAAAAMIHV1QUAqDpsNpv27NmjhIQEhYaGqmfPnnJ3d3d1WQAAAECVQAAHUCIrV67UT3/6U926dcvxWlhYmP7yl79o5MiRLqwMAAAAqBqYgg7guVauXKlRo0YVCd+SdPv2bY0aNUorV650UWUAAABA1UEAB/BMNptNP/3pT2UYxhNfK3zt/fffl81mM7s0AAAAoEohgAN4pj179jhGvgMDA/WrX/1K//RP/yRPT09JBSH85s2b2rNnjyvLBAAAACo9AjiAZ0pISHD8edy4cXJzc5Ovr6/eeustRwj//nEAAAAAnkQAB/BMoaGhkqSIiAiFhIQ4Xm/cuLGmTZumWrVqFTkOAAAAQPEsRnELOyuZtLQ0BQYGKjU1VQEBAa4uB3ip2Gw2tWzZUsOHD5efn5/jdcMwZLFYlJ2drT179mjXrl1sSQYAAIAXRkXkUEbAATyTxWLRjBkzHOH72rVrSkxMlMVi0cOHD+Xt7a3+/ftr586dstvtLq4WAAAAqLwI4ACeadeuXcrIyHB8fvjwYe3du1eS5OXlpZo1a0qS9u7dq4ULFyozM9MldQIAAACVHVPQATzV5cuXtWDBAsfnfn5+6tChgxITE3Xz5k1lZ2dr0KBB8vHx0bp165SXl6fAwECNGTNGdevWdWHlAAAAQPkwBR2AadLT07Vy5UpJkr+/vySpQ4cO6tu3r8aPH6++fftKkvbv369WrVpp6tSpqlmzplJTU/XFF1/o+PHjLqsdAAAAqIwI4ACeYLfbtWLFCmVmZqpWrVpKT0+XxWJRdHS045j27dvLz89PqampOnPmjEJCQjR9+nQ1b95cNptN69at09q1a5Wfn+/CdwIAAABUHgRwAE/YuXOnrl+/Lk9PT4WFhUmSmjZtqsDAQMcxHh4e6ty5s6SC9d+GYcjb21tvvfWW+vTpI0mKi4vT3LlzlZqaav6bAAAAACoZAjiAIi5fvqw9e/ZIkgYNGqQLFy5Ikjp27PjEsZ06dZKnp6eSk5N16dIlSQVd01955RVNnDhRPj4+unPnjj7//HNduXLFvDcBAAAAVEIEcAAOaWlpjnXfhdPNs7OzFRgYqMaNGz9xvLe3tyOYF3ZGL9S4cWPNmDFDoaGhysrK0oIFCxwj5QAAAMDLiAAOQFLRdd8hISEaOHCgjh49KqkgjLu5Ff+fiy5dusjd3V03b97UjRs3inytevXqmjJlitq3by/DMLRt2zYtXbpUOTk5Ff5+AAAAgMqGAA5AkrRjxw7duHFDnp6eGj16tJKTk3X79m25ubkpKirqqef5+/urXbt2kp4cBZckq9WqN954Q0OGDJG7u7vOnz+vWbNm6e7duxX2XgAAAIDKiAAOQN99950jPA8dOlS1atVyjH63bNlS1apVe+b53bt3l8Vi0aVLl5SUlPTE1ws7qL/77rsKCAjQ/fv3NXv2bJ0+fdr5bwYAAACopAjgwEsuLS1Nq1atklTQaC0yMlI5OTk6deqU47XnqVmzplq1aiVJ2rdv31OPq1evnmbMmKGIiAjl5eVpxYoV2rx5s2w2mxPeCQAAAFC5EcCBl9jj677r1Kmj1157TZJ08uRJ5eXlKSgoSA0aNCjRtbp37y5JOn36tB48ePDU4/z8/DRx4kTH8QcPHtRXX32lR48elfPdAAAAAJUbARx4iW3fvr3Ium+r1SrDMBzTzzt27CiLxVKia4WGhqpx48YyDEP79+9/5rFubm569dVXNWbMGHl6eur69euKjY3VzZs3y/2eAAAAgMqKAA68pC5duuSYLv7GG2+oZs2akqSbN2/q7t278vDwcDRXK6kePXpIkuLj40s0ot2yZUtNnz5dQUFBSk9P17x583T48GG2KgMAAMALiQAOvIRSU1Md6747deqk1q1bO75WOPodGRkpb2/vUl23QYMGqlevnvLz83Xo0KESnRMUFKTp06erVatWstvt2rhxo1avXq28vLxS3RsAAACo7AjgwEvGZrNpxYoVysrKUmhoqAYMGOD4WkZGhs6ePSupZM3Xvs9isThGwY8cOVLi/b49PT01atQo9e/fXxaLRSdPntScOXOUkpJS6hoAAACAyooADrxktm/frps3b8rLy0ujRo2S1Wp1fC0+Pl42m01169ZV3bp1y3T95s2bKygoSDk5OY7R9JKwWCzq1q2bJk2aJD8/PyUlJWnWrFm6ePFimeoAAAAAKhsCOPASuXjxoqNB2uPrviXJMAwdO3ZMkhQdHV3me1gsliIdzvPz80t1fsOGDTVjxgyFhYUpOztbixcv1s6dO1kXDgAAgCqPAA68JFJTU7V69WpJUkxMjGPf7kKXL1/WgwcP5OXlpcjIyHLdq02bNgoICNCjR4904sSJUp8fEBCgd955R506dZIk7dq1S4sWLVJWVla56gIAAABciQAOvARsNpuWL1+urKws1a1bV/3793/imMLp4u3atZOnp2e57ufu7q6uXbtKkvbv3y+73V6mawwePFjDhw+X1WrVd999p9jYWCUmJparNgAAAMBVCODAS2Dbtm26detWseu+JSktLc2x1roszdeK06FDB/n4+CglJUXnzp0r83XatWunqVOnqnr16nr48KHmzJlTplF1AAAAwNUI4MAL7sKFCzpw4IAkadiwYapRo8YTxxw7dkyGYahBgwYKDg52yn09PT0VExMjSdq3b1+51nDXqVNHM2bMUNOmTZWfn6/Vq1drw4YNstlsTqkVAAAAMAMBHHiBPXz40LHuu3PnzmrZsuUTx9hsNh0/flyS80a/C8XExMjDw0MJCQm6cuVKua7l4+OjcePGqVevXpIKpszPmzdPaWlpzigVAAAAqHAEcOAFVbjuOzs7+6nrvqWCzuiPHj2Sn59fsQG9PHx9fdWhQwdJBaPg5WWxWNS7d2+NHz9e3t7eunXrlmJjY3Xt2rVyXxsAAACoaARw4AW1detW3b59W97e3ho9erTc3d2LPa6w+VpUVNRTjymPrl27ys3NTVevXtXt27edcs2mTZtq+vTpCgkJUUZGhubPn6/9+/ezVRkAAAAqNQI48AI6f/68Dh48KKlg3Xf16tWLPe7+/fuOqeHl2fv7WQIDA9W2bVtJ0t69e5123Zo1a2rq1Klq27atDMPQli1btHz5cuXk5DjtHgAAAIAzEcCBF8zDhw+1Zs0aSVKXLl3UokWLpx577NgxSQUjyk8L6c7QrVs3SQUPBpKTk512XQ8PDw0fPlyDBw+Wm5ubzp49q9mzZ+vevXtOuwcAAADgLARw4AXy+LrvevXq6dVXX33qsXl5eYqPj5fk/OZr3xccHOx4ELB//36nXttisahTp05655135O/vr3v37mnWrFnl2voMAAAAqAgEcOAFsmXLFse671GjRj1zTffZs2eVlZWlwMBANWnSpMJr6969uyTp5MmTSk1Ndfr1w8PDNWPGDDVo0EC5ublaunSptm7dKrvd7vR7AQAAAGVBAAdeEOfOndOhQ4ckScOHD3/ulPLC5msdOnSQm1vF/6cgLCxMDRs2lN1ud6xPd7Zq1arp7bffVpcuXSQVdF5fsGCBMjIyKuR+AAAAQGkQwIEXwIMHDxzrvrt27armzZs/8/jExETdunVLbm5ujm3CzFA4Cn7s2DFlZmZWyD3c3d312muvadSoUfLw8NDVq1cVGxvrtA7sAAAAQFkRwIEqLj8/39H9OywsTP369XvuOYWj3y1atFC1atUqukSHxo0bq06dOsrLy9ORI0cq9F6tW7fWtGnTVKtWLaWlpWnu3Lk6duwYW5UBAADAZcoUwD/99FNFRETI29tb0dHR2rNnz1OP3bt3r7p3765atWrJx8dHLVq00J///OcyFwygqC1btujOnTvy8fF57rpvScrJydGpU6ckVXzzte+zWCyOUfBDhw4pNze3Qu9Xu3ZtTZs2TS1atJDNZtP69eu1du1a5eXlVeh9AQAAgOKUOoAvWbJE77//vn7xi18oLi5OPXv21KBBg3Tjxo1ij/fz89OPf/xj7d69W+fOndMvf/lL/fKXv1RsbGy5iwdedmfPntXhw4clFaz7DgwMfO45J0+eVG5urmrVqqWGDRtWcIVPatWqlWrUqKGsrCzFxcVV+P28vb01ZswY9evXTxaLRfHx8Zo7d64ePnxY4fcGAAAAHmcxSjkfs3PnzurQoYM+++wzx2stW7bU8OHD9fHHH5foGiNHjpSfn5+++uqrEh2flpamwMBApaamKiAgoDTlAi+sBw8e6PPPP1dOTo66deum/v37P/ccwzD097//XXfv3tVrr73maFZmtqNHj2rDhg0KCAjQT37yk+eO2jvLlStXtGLFCmVmZsrHx0cjR440pQM8AAAAqp6KyKGlGgHPzc3VsWPHNGDAgCKvDxgwoMR7+8bFxWn//v3q1atXaW4N4DH5+flatmyZcnJyFB4err59+5bovFu3bunu3buyWq1q165dBVf5dO3bt5efn5/S0tJ0+vRp0+7bqFEjzZgxQ3Xr1lVWVpYWLlyo3bt3sy4cAAAApihVAL93755sNptCQkKKvB4SEqLExMRnnhsWFiYvLy917NhRP/rRjzRt2rSnHpuTk6O0tLQiHwD+f99++60SEhLk4+OjN998s8QjyIXN1yIjI+Xj41ORJT6T1WotslWYmQE4MDBQ7777rqP7+44dO7RkyRJlZ2ebVgMAAABeTmVqwmaxWIp8bhjGE6993549e3T06FH9/e9/1yeffKLFixc/9diPP/5YgYGBjo/w8PCylAm8kM6cOePoID5ixIgSrfuWpMzMTJ05c0aS+c3XitOxY0d5eXkpOTlZFy5cMPXeVqtVQ4cO1dChQ+Xu7q4LFy5o1qxZSkpKMrUOAAAAvFxKFcCDgoLk7u7+xGj33bt3nxgV/76IiAi1adNG06dP1wcffKDf/OY3Tz32o48+UmpqquPj5s2bpSkTeGGlpKRo7dq1kgr21G7atGmJz42Pj5fNZlNoaKjq1q1bUSWWmLe3tzp16iSpYLcEV0wD79Chg6ZMmaLAwEClpKRozpw5jg7xAAAAgLOVKoB7enoqOjpaW7ZsKfL6li1b1K1btxJfxzAM5eTkPPXrXl5eCggIKPIBvOwK133n5uaWat23VPBv7tixY5IKRp6fN2PFLJ07d5a7u7tu376t69evu6SGunXrasaMGWrUqJHy8vK0cuVKbdy4UTabzSX1AAAA4MVV6inoH374oWbPnq0vvvhC586d0wcffKAbN27oBz/4gaSC0etJkyY5jv/b3/6mdevW6dKlS7p06ZLmzp2rP/3pT5o4caLz3gXwEti8ebMSExPl6+urUaNGyc2t5P98r1y5opSUFHl5eSkyMrICqyydatWqKSoqSlLBWnBX8fX11YQJE9SjRw9J0uHDhzV//nylp6e7rCYAAAC8eKylPeGtt97S/fv39bvf/U4JCQmKjIzUN998owYNGkiSEhISiuwJbrfb9dFHH+nq1auyWq1q3Lix/vCHP2jmzJnOexfAC+706dOOBmojRowo9ayQwnPbtm0rT09Pp9dXHt26ddOxY8f03XffKTExUXXq1HFJHW5uburXr5/q1aun1atX68aNG4qNjdXo0aNVv359l9QEAACAF0up9wF3BfYBx8vs/v37io2NVW5urnr06KF+/fqV6vy0tDR98sknMgxD7733nmrXrl1BlZbdihUrdPr0aUVGRurNN990dTm6f/++lixZouTkZLm5uWnAgAGKiYmpNFP3AQAAUPFcvg84AHPl5+dr+fLlys3NVf369dWnT59SX+P48eMyDEP169evlOFbKmgoJxV0eE9JSXFxNVKtWrU0bdo0RUZGym63a9OmTVq1apVyc3NdXRoAAACqMAI4UIlt2rTJse77zTffLNW6b6lgCcjx48clVY6tx56mTp06atKkiQzD0P79+11djqSCppMjR47Ua6+9JovFolOnTmnOnDmV4gEBAAAAqiYCOFBJnTp1ytG5fOTIkWWa9nLx4kWlp6fL19dXLVu2dHaJTlXYAC0+Pl6PHj1ycTUFLBaLunTposmTJ8vPz093795VbGys6fuWAwAA4MVAAAcqofv372v9+vWSpJ49e6px48Zluk5h87WoqChZraXuuWiq+vXrKywsTDabTQcPHnR1OUU0aNBAM2fOVHh4uHJycvT1119r+/btstvtri4NAAAAVQgBHKhk8vLyHPt9N2jQQL179y7TdVJSUnT58mVJUnR0tBMrrBgWi8UxCn706FFlZ2e7uKKi/P39NXnyZMXExEiS9uzZo0WLFikzM9PFlQEAAKCqIIADlcymTZuUlJRU5nXfhQqnrzdp0kQ1atRwZokVplmzZgoODlZOTo5j9L4ycXd316BBgzRixAhZrVZdvnxZs2bNUkJCgqtLAwAAQBVAAAcqkVOnTjmapo0cOVL+/v5luk5+fr7i4uIkVe7ma99nsVgcHdEPHjyo/Px8F1dUvLZt22ratGmqUaOGHj58qDlz5ji+3wAAAMDTEMCBSuLevXtat26dJOmVV14p87pvSTp79qyysrIUEBCgpk2bOqtEU0RGRiowMFAZGRmKj493dTlPFRISohkzZqhZs2ay2Wxau3at1q1bV2kfGgAAAMD1COBAJVC47jsvL08NGzZUr169ynW9wunbHTp0KPMUdldxd3dX165dJUn79++v1I3OvL29NXbsWMf+7MePH9e8efOUmprq4soAAABQGVWt38wBSZ9++qkiIiLk7e2t6Oho7dmzx9UlldvGjRt19+5d+fn5aeTIkeUKzUlJSbp586YsFos6dOjgxCrN06FDB/n6+urBgwc6e/asq8t5JovFoldeeUUTJkyQt7e3bt++rdjYWF29etXVpQEAAKCSIYCjSlmyZInef/99/eIXv1BcXJx69uypQYMG6caNG64urcxOnjzpWD9cnnXfhQpHv1u0aFHua7mKh4eHo9v43r17ZRiGiyt6viZNmmjGjBmqU6eOMjMz9dVXX2nfvn1VonYAAACYgwCOKuW///u/NXXqVE2bNk0tW7bUJ598ovDwcH322WeuLq1MkpOTHft99+rVS40aNSrX9XJzc3Xy5ElJVav5WnFiYmLk4eGhpKQkx3ZqlV2NGjU0ZcoUtW/fXoZhaOvWrVq2bJlycnJcXRoAAAAqAQI4qozc3FwdO3ZMAwYMKPL6gAEDtH//fhdVVXZ5eXlavny58vLyFBERoVdeeaXc1zx58qRyc3NVq1YtRUREOKFK1/Hx8XHsX753714XV1NyHh4eeuONN/T666/Lzc1N586d0+zZs5WcnOzq0gAAAOBiBHBUGffu3ZPNZlNISEiR10NCQpSYmOiiqsrum2++cdq6b0kyDMMx/Tw6OloWi8UZZbpU165d5ebmpuvXr+vmzZuuLqfELBaLOnbsqHfffVf+/v66d++eZs+erTNnzri6NAAAALgQARxVzveDpWEYVS5snjhxQvHx8bJYLHrzzTdVrVq1cl/z9u3bSkpKktVqVfv27ctfZCUQEBCgtm3bSpL27dvn4mpKLywsTDNnzlTDhg2Vm5ur5cuX69tvv63Und0BAABQcQjgqDKCgoLk7u7+xGj33bt3nxgVr8ySk5O1YcMGSQXrvp01Vbxw9Lt169by8fFxyjUrg+7du0uSLly4UCWncfv5+entt99Wt27dJEkHDhzQV199pYyMDBdXBgAAALMRwFFleHp6Kjo6Wlu2bCny+pYtWxzhprLLzc117PfdqFEj9ezZ0ynXzcrK0unTpyVV/eZr3xcUFKSWLVtKqpqj4JLk5uam/v37a/To0fL09NS1a9f0+eef69atW64uDQAAACYigKNK+fDDDzV79mx98cUXOnfunD744APduHFDP/jBD1xdWols3LhRycnJqlatmkaMGFHudd+F4uPjZbPZVKdOHdWrV88p16xMCkfBT506pdTUVBdXU3atWrXStGnTFBQUpPT0dM2dO1dHjhxhqzIAAICXBAEcVcpbb72lTz75RL/73e/Uvn177d69W998840aNGjg6tKeKz4+3unrvqWizdc6duxY5dbDl0S9evUUEREhu92uAwcOuLqccgkODnZso2e32/XNN99ozZo1ysvLc3VpAAAAqGAEcFQ5P/zhD3Xt2jXl5OTo2LFjTtm+q6LdvXvXse67d+/eatiwodOuffXqVaWkpMjT01Nt2rRx2nUrm8JR8OPHjyszM9PF1ZSPl5eXRo8erf79+8tisejEiRP64osv9ODBA1eXBgAAgApEAAcqWOG67/z8fKeu+y5UOPrdtm1beXp6OvXalUmjRo0UGhqqvLw8HTp0yNXllJvFYlG3bt309ttvy9fXV4mJiYqNjdWlS5dcXRoAAAAqCAEcqECGYWjDhg26d++e/P39NXLkSKdOEU9PT9f58+clvXjN177PYrGoR48ekqTDhw8rNzfXxRU5R0REhGbOnKl69eopOztbixYt0q5du1gXDgAA8AIigAMVKD4+XidPnnSs+/bz83Pq9Y8fPy7DMBQeHl6ltmIrqxYtWqhmzZrKzs7WsWPHXF2O0wQEBOidd95RdHS0JGnnzp1avHixsrKyXFwZAAAAnIkADlSQpKQkffPNN5KkPn36OL1RnN1u1/HjxyW9+KPfhdzc3BxrwQ8cOCCbzebiipzHarVqyJAhGjZsmKxWqy5duqRZs2YpKSnJ1aUBAADASQjgQAXIzc3V8uXLlZ+fr8aNGzumTjvTpUuXlJaWJh8fH7Vq1crp16+s2rZtq2rVqik9PV0nT550dTlO1759e02ZMkXVq1fXgwcPNHv27BfyfQIAALyMCOCAk31/3feIESMqZGuwwuZrUVFRslqtTr9+ZWW1WtW1a1dJ0r59+17ItdKhoaGaMWOGmjRpovz8fK1atUrffPPNCzXiDwAA8DIigANOFhcX51j3PWrUKKev+5akBw8e6LvvvpMkx7rhl0l0dLS8vb11//59RxO6F42Pj4/GjRvn2GbvyJEj+vLLL5Wenu7iygAAAFBWBHDAiZKSkrRx40ZJUt++fVW/fv0KuU9hA7LGjRurZs2aFXKPyszLy0udOnWS9OKOgksFa9779OmjcePGycvLSzdv3tTnn3+u69evu7o0AAAAlAEBHHCSnJwcx37fTZo0cTQLc7b8/HzFxcVJenmarxWnc+fOslqtun37tq5du+bqcipUs2bNNGPGDIWEhCgjI0NffvmlDhw48MI+eAAAAHhREcABJzAMQ+vXr9f9+/cVEBBQYeu+JencuXPKzMyUv7+/mjVrViH3qAr8/PwUFRUlqWAU/EVXs2ZNTZ06VW3atJFhGPr222+1YsWKF2Y/dAAAgJcBARxwguPHj+v06dOO/b59fX0r7F6Fzdc6dOggN7eX+59w165dZbFYdPnyZSUkJLi6nArn4eGhESNGaODAgXJzc9OZM2c0e/Zs3b9/39WlAQAAoARe7t/eASdITEx0rPvu169fha37lqS7d+/qxo0bslgs6tChQ4Xdp6qoUaOGIiMjJb0co+CSZLFY1LlzZ02ePFnVqlVTcnKyYmNjX9hmdAAAAC8SAjhQDoXrvm02m5o2bapu3bpV6P0KR79btGihgICACr1XVVG41v7s2bMv1Uhw/fr1NXPmTNWvX1+5ublasmSJtm3bJrvd7urSAAAA8BQEcKCMDMPQunXrlJKSooCAAA0fPrzC1n1LUm5urk6ePCnp5dx67GlCQkLUrFkzGYah/fv3u7ocU1WrVk2TJk1S586dJUl79+7VwoULlZmZ6eLKAAAAUBwCOFBGx44d05kzZ+Tm5qZRo0ZV6LpvSTp16pRycnJUs2ZNNWrUqELvVdUUjoKfOHHipdsn293dXQMHDtSbb74pDw8PXblyRbGxsbp9+7arSwMAAMD3EMCBMkhISNCmTZskFaz7Dg8Pr9D7GYbhmH4eHR1doSPtVVH9+vVVv3592Ww2HTx40NXluERkZKSmTZummjVrKjU1VXPnztXx48ddXRYAAAAeQwBHpWSz2bRz504tXrxYO3fulM1mc3VJDjk5OVq+fLlsNpuaNWumrl27Vvg979y5o8TERLm7u6t9+/YVfr+qqHAU/OjRo8rKynJxNa5Ru3ZtTZ8+Xc2bN5fNZtO6deu0du1a5efnu7o0AAAAiACOSmjlypVq2LCh+vTpo/Hjx6tPnz5q2LChVq5c6erSiqz7DgwMrPB134UKR79bt25d4VPdq6qmTZuqdu3ays3NdXy/Xkbe3t5666231LdvX0lSXFyc5s6dq4cPH7q2MAAAABDAUbmsXLlSo0aN0q1bt4q8fvv2bY0aNcrlIfzo0aNF1n37+PhU+D2zsrJ0+vRpSVLHjh0r/H5VlcVicYyCHzx4UHl5eS6uyHUsFot69uypiRMnysfHR3fu3FFsbKwuX77s6tIAAABeagRwVBo2m00//elPZRiGJKlt27b62c9+pqCgIMdr77//vsumoyckJGjz5s2SpFdffVVhYWGm3PfEiRPKz89XSEiIafesqiIjI1W9enVlZmYqPj7e1eW4XOPGjTVjxgyFhoYqKytLCxcu1J49exz/ngAAAGAuAjgqjT179jhGvqtXr64RI0bI399fU6dOlVQw/fvmzZvas2eP6bVlZ2c79vtu3ry5unTpYsp9H2++1rFjR5qvPYebm5tjTf7+/fvZE1sF/5amTJmiqKgoGYah7du3a+nSpcrOznZ1aQAAAC8dAjgqjYSEBElSnTp1NHXqVEfY9PHxUY8ePZ44ziyF674fPHigwMBADRs2zLQgfO3aNd2/f1+enp5q06aNKfes6qKiouTr66uHDx/qzJkzri6nUrBarXrjjTc0ZMgQubu76/z585o9e7bu3r3r6tIAAABeKgRwVBqhoaFq3Lix3n33Xfn7+xfp3NyvXz+1atXKcZyZjhw5orNnz8rNzU2jR482Zd13ocLR7zZt2sjLy8u0+1ZlHh4e6ty5syRp7969TLd+THR0tN59910FBATo/v37mj17tqO/AAAAACoeARyVRrVq1TRhwgR5eXnpypUrRUaZLRaLRo4cqejoaPXs2dO0mu7cuaNvv/1WktS/f3/Vq1fPtHs/evRI58+fl0TztdLq1KmTPD09dffuXX333XeuLqdSqVevnmbMmKGIiAjl5eVpxYoV2rx5c6Xa6g8AAOBFRQCHyxmGoR07dmjDhg1yc3NTfHy8Vq9eLXd3d8e6b6lgGu3w4cP14MEDU+p6fN13ixYtHKOqZjl+/LjsdrvCwsJUp04dU+9d1fn4+Cg6OlpSwSg4ivLz89PEiRMdSzsOHjyor776So8ePXJxZQAAAC82Ajhcymazac2aNdq9e7ckObZOioiIkFQwCrxly5Yixy9cuLDCg4JhGFq7dq0ePnyo6tWr64033jC1AZrdbtfx48clMfpdVl27dpW7u7tu3LihGzduuLqcSsfNzU39+vXTmDFj5OnpqevXrys2NtbxwAsAAADORwCHy+Tk5GjRokU6ceKELBaLhgwZor59++rNN9/UokWLJElBQUH68ssv1bRpU0kF63sfPnyoxYsXKzc3t8JqO3z4sM6dO2fqft+P++6775SamiofHx+1bt3a1Hu/KPz9/dWuXTtJ0r59+1xcTeXVsmVLTZ8+XcHBwUpPT9e8efN0+PBh1s4DAABUAAI4XCItLU1z587VlStX5OHhoXHjxjmmDEtyjHBHRESod+/eevXVV2WxWJSXlycvLy/duXNHK1asqJBtpm7fvu1Y9z1gwABT130XKmy+1r59e1mtVtPv/6Lo1q2bJOnixYtKSkpycTWVV1BQkKZNm6bWrVvLbrdr48aNWr16tfLy8lxdGgAAwAuFAA7TJSUlac6cOUpKSlK1atX07rvvOka4C6WlpUmSAgICJEm1a9d2jGbWqFFDVqtVFy9e1MaNG506UpeVlaXly5fLbrerZcuWiomJcdq1S+rBgwe6dOmSJBV5KIHSq1WrlqN7/v79+11cTeXm6empN998UwMGDJDFYtHJkyc1Z84cpaSkuLo0AACAFwYBHKa6evWq5s6dq7S0NAUFBWnq1KnFbiv2/QAuSb1795a7u7sSExPVtWtXSQUjxc4KVq5e912ocO13o0aNVKtWLdPv/6Lp3r27JOnUqVN6+PCha4up5CwWi7p27apJkybJz89PSUlJio2N1cWLF11dGgAAwAuBAA7TnDhxQgsWLFBOTo4aNGigKVOmqHr16sUeW1wADwwMdHQiv3DhggYMGCBJ2rp1q1P2Mj506JDOnz8vd3d3jR49Wt7e3uW+ZmnZbDbFxcVJovmas9StW1eNGjWSYRiMgpdQw4YNNWPGDIWFhSknJ0eLFy/Wjh07KmTJBwAAwMuEAI4KZxiGdu/erdWrV8tut6t169aaOHHiMxubFRfAJalHjx7y9vbW3bt35evr6wjkq1ev1rVr18pc4+3btx3d1gcMGKC6deuW+Vrlce7cOWVkZMjf31/NmjVzSQ0vosLttuLi4pSRkeHiaqqGgIAAvfPOO+rUqZMkaffu3Vq8eLGysrJcXBkAAEDVRQBHhbLb7Vq/fr127NghqaAp1ptvvvnMxmKGYTw1gPv4+DjC1I4dO9SvXz+1bNlSNptNS5YsUXJycqlrzMrK0rJly2S329WqVStH4HCFwuZrUVFRcnd3d1kdL5qGDRuqbt26ys/P16FDh1xdTpXh7u6uwYMHa/jw4bJarfruu+8UGxurhIQEV5cGAABQJRHAUWFyc3P19ddf6/jx47JYLBo0aJD69+//3HXVmZmZstlskgq2kvq+mJgY+fv7KzU1VUePHtWIESMUHh6u7OxsLVy4UOnp6SWu0TAMrVmzRqmpqapRo4aGDh3qknXfkpScnKzr16/LYrHQfM3JLBaL48HNkSNHlJOT4+KKqpZ27dpp6tSpqlGjhh4+fKgvvvhC8fHxri4LAACgyiGAo0I8evRI8+bN06VLl2S1WjVmzJgSdxQvHP328/MrdqTcw8NDffr0kSTt2bNHNptNY8eOVc2aNZWamlqqPcIPHjyoCxcuuHTdd6HC0e/mzZs/MfKP8mvRooVq1aql7OxsHTt2zNXlVDl16tTR9OnT1bRpU+Xn52vNmjXasGGD8vPzXV0aAABAlUEAh9MlJydr9uzZSkhIkK+vryZPnqwWLVqU+PynTT9/XLt27RQcHKysrCzt27dPvr6+mjBhgnx9fZWQkOCYUv4st27d0tatWyVJr732WrHd2M2Sm5urEydOSGLrsYpisVgcHdEPHjxIcCwDHx8fjRs3Tr169ZJU8NBo3rx5jn+zAAAAeDYCOJzq+vXr+uKLL5SamqqaNWtq6tSpCgsLK9U1ShLA3dzc1K9fP0kFYSotLU01a9bU+PHjHWtVN2zY8NQ9wh/f77t169Yu7zh++vRp5eTkqEaNGmrcuLFLa3mRtW3bVv7+/kpPT9fJkyddXU6VZLFY1Lt3b40fP17e3t66ffu2YmNjy9UEEQAA4GVBAIfTnD59Wl999ZWys7MVFhamqVOnqmbNmqW+TkkCuCQ1a9ZM4eHhys/P165duyRJ9erV06hRo2SxWHT8+HHt3bv3ifMMw9Dq1asdDwlcue67UOGU6OjoaJfX8iJzd3d37CG/f/9+ttUqh6ZNm2rGjBkKCQlRRkaG5s+fr/379z/1oRcAAAAI4HCCwv2VV6xYIZvNphYtWmjSpEny9fUt0/UKm6g9L4BbLBa9+uqrkgq2l7p3756kgjXUAwcOlCRt3779iZHOAwcO6OLFi451315eXmWq01nu3LmjO3fuyN3dXe3bt3dpLS+D6OhoeXt76/79+zp//ryry6nSatSooalTp6pt27YyDENbtmzR8uXLaXIHAADwFARwlIvdbtfGjRsde2h37txZo0ePloeHR5mvmZqaKun5AVyS6tevr+bNm8swDG3bts3xekxMjLp16yZJWrNmja5evSpJunnzpmPd98CBA1WnTp0y1+ksR44ckSS1atVKfn5+Lq7mxefp6eloCLh3715GbMvJw8NDw4cP1+DBg+Xm5qazZ89q9uzZjgdiAAAA+P8RwFFmeXl5Wrp0qSNADhgwQAMHDpSbW/l+rEo6Bb1Qv379ZLFYdP78ed28edPx+quvvqrWrVvLbrdryZIlunHjhpYvXy7DMBQZGVkpmp1lZ2fr9OnTkuTydegvk86dO8tqtSohIcHxcAZlZ7FY1KlTJ73zzjvy9/fXvXv3NGvWLJ07d87VpQEAAFQqBHCUSUZGhr788kvHFl6jRo1yrK0tD8MwSh3Ag4ODHVO3t27d6hjRtFgsGj58uBo0aKCcnBx99dVXjmZtQ4YMqRRrrU+cOKH8/HzVrl1b4eHhri7npeHr66sOHTpIUrF9AlA24eHhmjFjhho0aKDc3FwtXbpUW7ZsYa09AADA/0MAR6ndv39fc+bM0e3bt+Xj46NJkyapdevWTrl2dna2Y3sof3//Ep/Xu3dvWa1W3bhxQ5cuXXK8brVa9dZbb8nX19dx3WHDhrl83bdU8LChcO/vjh07VooHAi+Trl27ys3NTVevXtXt27ddXc4Lo1q1apo0aVKRZncLFixQRkaGiysDAABwPQI4SuXmzZv64osv9ODBA1WvXl1TpkxR/fr1nXb9wtFvX1/fUq0jDwgIUOfOnSUVjII/PuKWnJysrKwsx+e7du2SzWZzUsVld/36dd27d08eHh5q27atq8t56VSvXl1t2rSRJO3bt8/F1bxY3NzcNGDAAI0aNUoeHh66evWqYmNjedABAABeegRwlNi5c+c0f/58ZWZmqm7dupo6daqCgoKceo/STj9/XPfu3eXt7a3k5GRH5/PMzEzHuu/GjRvLarXqypUrWr9+vcubbxWOfrdp06ZSjMi/jAob9Z07d46mYRWgdevWmj59umrVqqW0tDTNnTtXx44dc/m/PQAAAFchgKNEDh06pKVLlyo/P1/NmjXT5MmTVa1aNaffpzwB3MfHRz179pQk7dixQ7m5uVq1apXS09NVq1YtjRkzRqNHj5bFYlF8fLxj73BXePTokaNBFc3XXKd27dpq3ry5pIKp0nC+4OBgTZ8+XS1atJDNZtP69eu1du1a5eXlubo0AAAA0xHA8UyGYWjz5s3atGmTpII9lN966y15enpWyP0KtyArzfrvx8XExCggIEBpaWlatmyZvvvuO1mtVo0ePVqenp5q1qyZXn/9dUkFU9Hj4+OdVXqpxMXFyW63q169egoNDXVJDSjQvXt3SQUN8QofAMG5vLy8NGbMGMeOBfHx8Zo7d64ePnzo6tIAAABMRQDHU+Xn52v58uU6ePCgpILtvl5//fVybzP2LOnp6ZLKNgIuFTRd69OnjyTpu+++kyQNGjRIISEhjmOio6PVo0cPSdK6det0+fLl8pRcana7XceOHZPE6HdlEB4ergYNGshutzt+1uF8FotFPXr00MSJE+Xr66uEhATFxsY6/p0CAAC8DAjgKFZWVpa++uornT17Vm5ubho5cqR69OhR4Z26yzMFvVDjxo0dDwmCg4MVFRX1xDF9+/ZVmzZtZLfbtXTpUiUmJpb5fqV1+fJlpaamytvb22nd41E+haPgx44dK9KwD87XqFEjzZgxQ3Xr1lVWVpYWLlyo3bt3sy4cAAC8FAjgeMKDBw80Z84c3bhxQ15eXpo4caKjW3RFKwzggYGBZTrfMAytWbPG0QU9JSXFMar+OIvFomHDhqlhw4bKzc3VokWLHNPfK1ph87X27duXqtM7Kk6TJk0UEhKi3NxcHTlyxNXlvPACAwP17rvvOvZi37Fjh77++mtlZ2e7uDIAAICKRQBHEXfu3NGcOXN0//59BQQEaMqUKYqIiDDl3oZhOEJwWUfA9+7dq8uXL8tqtapOnTqy2WzauXNnsce6u7vrrbfeUnBwsNLT07Vo0aIKDwAPHz7UxYsXJRVMhUflUDg9WipoOEiDsIpntVo1dOhQvfHGG3J3d9fFixc1a9YsJSUlubo0AACACkMAh8PFixc1b948ZWRkqE6dOpo2bZpq165t2v1zcnIcwacsTdiuX7+uHTt2SJIGDx6swYMHS5Li4+OVnJxc7Dne3t6aMGGCqlWrprt372rp0qUVukf48ePHJUkRERFO38IN5dOqVSvVqFFDmZmZjr8nVLyoqChNmTJFgYGBSklJ0ezZs3Xq1ClXlwUAAFAhCOCQVDAt+uuvv1ZeXp4aN26sd955p8ydyMuqcPq5t7d3qbusZ2RkOPb7bteundq3b6/w8HC1aNFChmFo27ZtTz03MDBQEyZMkKenp65evaq1a9dWyHpUm83mCHY0X6t83NzcHPuCHzhwoEIfxKCounXrasaMGWrcuLHy8/O1cuVKbdy4kb8DAADwwiGAv+QKw+mGDRtkGIbat2+vcePGycvLy/RaytqAzTAMrVy5Uo8ePVJQUJAGDx7saBbXt29fWSwWXbhwQTdu3HjqNerUqePYI/zkyZOOkXRnOn/+vDIyMlStWjXH3tOoXNq3by8/Pz+lpqbq9OnTri7npeLr66vx48erZ8+ekqTDhw/ryy+/LLaHAwAAQFVFAH+J2Ww2rVq1Snv37pUk9erVy7Ee0xXKGsD37NmjK1euyMPDw7Hfd6Hg4GC1b99ekrR169Znjmw3adJEQ4cOdVyzcKswZylsvhYVFeWy7zGezWq1qkuXLpKkffv20ZnbZG5uburbt6/Gjh0rLy8v3bx5U7Gxsbp+/bqrSwMAAHAKAnglcfv2bU2cOFG1atWSr6+v2rdv7/QA+Ljs7GwtWLBAp06dkpubm4YNG6bevXtX+DZjz1KWAH7t2jVHk7XBgwcXu2a9d+/eslqtunnzpqMB2tNERUXplVdekSRt2LBBly5dKnEtz3Lv3j1du3ZNFouF5muVXMeOHeXl5aXk5OTn/rygYjRv3lzTp09X7dq19ejRI82fP18HDx7kgQgAAKjyCOCVwIMHD9S9e3d5eHho48aNOnv2rP7rv/5L1atXr5D7paam6osvvtC1a9fk6emp8ePHO0aJXam0AfzRo0dasWKFY+r8095DQECAOnfuLEnatm2bY4uyp+ndu7fatWsnwzC0bNkyJSQklPxNPEXh6HezZs3KvMUazOHt7e1Yo793715Cn4vUqlVLU6dOVWRkpOx2uzZv3qxVq1YpNzfX1aUBAACUGQG8EviP//gPhYeHa+7cuYqJiVHDhg3Vr18/NW7c2On3SkxM1Jw5c5ScnCx/f3+9++67FXKfsihNALfb7Vq1apUePXqk4OBgR8fzp+nRo4e8vb2VnJysEydOPPNYi8WioUOHqlGjRsrLy9OiRYv08OHDEr+P78vLy3Pck9HvqqFz585yd3fXrVu3ntk7ABXL09NTI0eO1MCBA+Xm5qZTp045tkkEAACoigjglcDatWvVsWNHjR49WrVr11ZUVJRmzZrl9PtcvnxZc+fOVXp6uoKDgzV16lTVqVPH6fcpq9IE8O+v+/bw8Hjm8d7e3o7mTjt27HjuPs/u7u4aM2aMQkJC9OjRIy1cuFBZWVklfCdFnT59WtnZ2apevbqaNGlSpmvAXP7+/o4ZFfv27XNtMS85i8Wizp07a/LkyY7tAmfNmqULFy64ujQAAIBSI4BXAleuXNFnn32mpk2bavPmzfrBD36gn/zkJ5o/f77T7hEXF6dFixYpNzdXDRs2dOy7W5mUNIBfvXrVse779ddfV3BwcImuHxMTo4CAAKWnp+vw4cPPPd7Ly0vjx4+Xv7+/7t27pyVLlig/P79E93pc4fTz6Ohol66xR+l069ZNFotFly5dUlJSkqvLeenVr19fM2bMUHh4uHJycvT1119r+/btz11SAgAAUJkQwCsBu92uDh066Pe//72ioqI0c+ZMTZ8+XZ999lm5r20Yhnbu3Km1a9fKbrerTZs2mjhxory9vZ1QufPk5OQoJydH0rMDeOG6b6lgy6h27dqV+B5Wq1V9+vSRVLC2tyQj2gEBAZowYYK8vLx0/fp1rVmzplRrgu/cuaM7d+7Izc1NUVFRJT4PrlezZk21atVKEqPglYW/v78mT56smJgYSQUzYRYtWqTMzEwXVwYAAFAyBPBKIDQ01PGLfqGWLVuWe+2pzWbT2rVrtWvXLkkF66BHjBhRKbfAKhz99vLyeuoe5Ha7XStXrlRGRoZq16793HXfxWnbtq1q166t7Oxsx/ZrzxMSEqIxY8bIzc1Np0+f1rZt20p8v8LR71atWsnPz6/U9cK1unfvLqlgGcGDBw9cXA2kguUhgwYN0siRI+Xh4aHLly8rNjZWd+7ccXVpAAAAz0UArwS6d+/+xHrGixcvqkGDBmW+Zk5OjhYvXqz4+HhZLBa9/vrr6tevX6WdAl2S6ee7d+/W1atXS7zuuzhubm7q16+fJOnQoUNKTU0t0XmNGjXSG2+8IalgNPTIkSPPPSc7O1unT5+WJEdXbVQtoaGhatKkiQzD0P79+11dDh7Tpk0bTZ06VTVq1HDs7BAXF+fqsgAAAJ6JAF4JfPDBBzp48KB+//vf67vvvtOiRYsUGxurH/3oR2W6Xnp6uubOnavLly/Lw8NDY8eOrfQB8HkB/MqVK46R/CFDhigoKKjM92ratKkaNGggm83mWEteEu3atXNMYd+4ceNzm0CdPHlSeXl5Cg4OVv369ctcL1yrcBQ8Pj5ejx49cnE1eFxISIhmzJihZs2aOWb8rFu3rky9GgAAAMxAAK8EOnXqpFWrVmnx4sWKjIzUv/3bv+mTTz7RhAkTSn2tu3fvavbs2UpKSpKfn5/eeecdNWvWrAKqdq5nBfD09HStXLlSkhQVFaW2bduW614Wi0WvvvqqJOnEiRO6e/duic/t2bOnoqKiZBiGVqxYodu3bxd7nGEYjunnHTt2rLQzD/B8DRo0UFhYmPLz83Xo0CFXl4Pv8fb21tixYx0Px44fP665c+eWeHYLAACAmQjglcSQIUN06tQpZWdn69y5c5o+fXqpr3H16lV98cUXSktLU61atTR16lTVrVu3Aqp1vqcF8O+v+x40aJBT7hcWFqaWLVvKMIxSrekunM7fpEkT5eXlafHixcWuDb5x44aSk5Pl4eFR7gcGcC2LxeIYBT9y5Iiys7NdXBG+z2Kx6JVXXtGECRPk4+OjO3fuKDY2VleuXHF1aQAAAEUQwF8QJ0+e1IIFC5STk6P69etrypQpqlGjhqvLKrGnBfBdu3bp2rVr8vT0LPO676fp27evLBaLLl68qOvXr5f4PHd3d40aNUp16tRRRkaGFi5c+EQX5sLR78jIyErXcR6l17x5cwUFBSknJ0fHjh1zdTl4iiZNmmjGjBmqU6eOMjMztWDBAu3du7dUOxcAAABUJAJ4FWcYhvbs2aNVq1bJbrerVatWevvtt+Xr6+vq0kqluAB++fJl7d69W1L5130XJygoyLE12NatW0v1S3rhHuGBgYG6f/++vv76a8e604yMDJ09e1YSzddeFI+Pgh88eJA1xpVY9erVNWXKFLVv394xw2Xp0qWObQ4BAABciQBehdntdm3YsEHbt2+XJHXt2lWjRo2S1Wp1cWWl9/0A/vi67w4dOqhNmzYVct/evXvLarXq1q1bz22q9n3+/v4aP368vLy8dPPmTa1atUqGYSguLk52u11169atMksA8Hxt2rRRQECAHj16pBMnTri6HDyDh4eH3njjDQ0ZMkTu7u46f/68Zs2apeTkZFeXBgAAXnIE8CoqNzdXX3/9tWM67MCBAzVgwIAq2ewrNzfXsa42ICBAdrtdK1asUGZmpkJCQjRw4MAKu7e/v7+6dOkiSdq2bZvsdnupzq9du7bGjh0rd3d3nT17Vt9++63j74TR7xeLu7u7unbtKqlgK7rS/qzAXBaLRdHR0Xr33XcVEBCg+/fva9asWTpz5oyrS3Oq3bt3a+jQoapbt64sFotWr17t6pIAAMAzEMCroEePHmnevHm6dOmSrFarxowZo86dO7u6rDJLT0+XJHl6esrLy0s7d+7U9evXK2Tdd3G6d+8uHx8f3bt3T/Hx8aU+v2HDhho2bJikgunJDx8+lLe3tyIjI51cKVytQ4cO8vHx0YMHD3Tu3DlXl4MSqFevnmbMmKGIiAjl5eVp+fLl+vbbb1+YBygZGRlq166d/vd//9fVpQAAgBIggFcx9+7d05w5c5SQkCAfHx9NmjRJLVu2dHVZ5fL49PPLly9rz549kqShQ4eqVq1aFX5/b29v9ezZU5K0c+dO5eXllfoabdq0Ub9+/Ryfh4eHV/iDA5jP09NTMTExkkRzryrEz89PEydOVLdu3SRJBw4c0Pz581+Ifd0HDRqk//t//69Gjhzp6lIAAEAJEMCrkBs3bmjOnDl6+PChatSooalTpyo8PNzVZZVb4X69vr6+WrVqlSQpOjra1BHkTp06KTAwUOnp6WXe6/nxeq9cuaJbt245qzxUIjExMfLw8FBiYiLbXFUhbm5u6t+/v0aPHi1PT09dv35dsbGx/DsFAACmIoBXEWfOnNH8+fOVnZ2tevXqaerUqaaMDpuhcAT8/v37yszMVJ06dSp03XdxrFar+vTpI6lgZPP724qVxPHjxyVJPj4+stlsWrx4sVJSUpxaJ1zP19dXHTp0kFTws4KqpVWrVpo+fbqCgoKUnp6uuXPn6siRI8xmAAAApiCAV3KGYejAgQNavny5bDabmjdvrsmTJ8vPz8/VpTlNYQDPyMhwrPt2RSf3Nm3aKCQkRDk5OaUOVjabTXFxcZKk1157TaGhocrMzNTChQuVkZFREeXChbp27So3Nzddu3aNEdQqKCgoSNOmTVOrVq1kt9v1zTffaM2aNWVafgIAAFAaBPBKzG63a9OmTfr2228lFUyTHjNmzAu3tjgxMdHx5zfeeEM1a9Z0SR1ubm6OddyHDx92TI0viQsXLujRo0fy8/NTZGSkxo8fr+rVqyslJUVff/01v9i/YAIDA9W2bVtJBR3RUfV4eXlp1KhR6t+/vywWi06cOKE5c+bowYMHri4NAAC8wAjglVReXp6WLVumw4cPS5L69++vQYMGyc3txforS0tL0507dyRJTZs2VevWrV1aT5MmTdSwYUPZbDbt3LmzxOcdPXpUkhQVFSV3d3dVq1ZNEyZMkLe3t27duqWVK1e+MF2XUaCwodf58+fZX7qKslgs6tatm95++235+voqKSlJsbGxunTpkqtLAwAAL6gXK829IDIyMjR//nydP39e7u7uevPNN9WtW7cqucf3s9jtdi1fvtyx9rJXr14urqjgF/JXX31VkhQfH6+kpKTnnnP//n1dvXpVUkHzuEJBQUEaN26c3N3ddf78eW3evJl1pi+Q4OBgtWjRQpK0f/9+F1eD8oiIiNDMmTMVFham7OxsLVq0SDt37qwS/14fPXqk+Ph4xxaKV69eVXx8vG7cuOHawgAAQLEI4C5UOMq6ePFi7dy5UzabTSkpKfriiy9069YteXt76+23335h95Pevn27bt686fjcVVPPv69evXpq1aqVpIIan6dw9LtZs2aqXr16ka/Vr19fI0aMkFQwrf3gwYPOLRYu1b17d0nSyZMnS7VkAZVPQECAJk+erI4dO0qSdu3apcWLFysrK8vFlT3b0aNHFRUVpaioKEnShx9+qKioKP3qV79ycWUAAKA4BHAXWblypRo2bKg+ffpo/Pjx6tOnjzp16qRPP/1UKSkpCgwM1JQpU9SgQQNXl1ohLl26VGTtrNVqlbe3twsrKqpv376yWCy6ePGirl+//tTj8vLyHCNPj49+P65169bq37+/JOnbb7/VmTNnnF4vXCMsLEwNGzaU3W7XgQMHXF0Oyslqter111/XsGHDZLVadenSJc2aNatIn4rKpnfv3jIM44mPefPmubo0AABQDAK4C6xcuVKjRo0q0j25efPmGjx4sGw2m7y9vTVt2jQFBwe7sMqKk5qa6tjvu3AKb0BAQKWaYl+rVi3HVlNbt2596lTUM2fOKDs7W4GBgWrSpMlTr9e1a1d16tRJkrRq1Sqmh75AevToIalgG7qybF+Hyqd9+/aaMmWKqlevrgcPHmjOnDk6efKkq8sCAAAvAAK4yWw2m3760586Ap2np6d69OihsWPHysPDQxcvXtTnn38uHx8fF1daMWw2m1asWKGsrCyFhoaqWbNmkgoCeGXTq1cveXh46NatWzp//nyxxxROP4+Ojn5mgzyLxaKBAweqefPmstls+vrrr3Xv3r0KqRvmatSokerUqaO8vDxH00RUfaGhoZoxY4aaNGmi/Px8rVq1St98841sNpurSwMAAFWY+Zstv+T27NnjGPm2WCz6x3/8R8e2YllZWapWrZp69+6tv/3tb6pdu7asVqs8PDxktVqf+uen/e/3X3N3d3f5KHPhum8vLy+NHj3aMR07MDDQpXUVx9/fX126dNGePXu0bds2NW/evEjITkhI0O3bt+Xm5uZYf/ksbm5uevPNN/Xll1/q9u3bWrhwoaZOnapq1apV5NtABbNYLOrRo4eWL1+uw4cPq1u3bvL09HR1WXACHx8fjR8/Xjt37tTu3bt15MgRJSQkaPTo0ZXyoSEAAKj8COAmS0hIcPy5MBwX8vHxcYx8P3jwoEL2oy1JUC/Na887xs3NzRH6L1686OgWPWzYMNWoUUNpaWmSCsJuZdS9e3cdPXpU9+/fV1xcXJF13oWj3y1btixxiPbw8NC4ceMc+w0vXrxYkydPJrBVcS1btlSNGjX04MEDHT9+XF26dHF1SXASi8WiPn36qF69elq1apVu3bql2NhYjRo1Sg0bNnR1eQAAoIohgJssNDTU8Wd/f39ZLBYZhuEIqQkJCTp8+LD++Z//WU2aNFFeXp7y8/OVn5/v+HNxrxX39cL/fXz9cuGxZrFYLLJarXJ3d1dOTo6kggcN+/bt0+HDhx37J1+5ckUZGRlOC/3O4uXlpVdeeUWbN2/Wzp071bZtW3l4eCgnJ0enTp2SJEfX5JLy8/PThAkTNGfOHN25c0crVqzQW2+99cLt8f4ycXNzU/fu3bV+/XodOHBAnTp1kru7u6vLghM1a9ZM06dP19KlS5WUlKT58+erf//+6tKli8tnFgEAgKrDYlSBjU7T0tIUGBio1NTUKj/tz2azqWHDhrp9+7Y6deqkwYMH68qVK4qPj9eQIUPk6empjIwM/eAHP1CjRo3KfT/DMGS320sU1J8V8Esb+l3Jzc2tTKP6Twv5FotF69evV0ZGhmJiYhQTE6MzZ85ox44dqlWrln74wx+WKTzfvHlT8+fPV35+vjp27KjBgwfzi3wVlp+fr7/85S969OiRhg0bpvbt27u6JFSAvLw8rV+/3tGUrXXr1nrjjTeYxQIAwAuoInIoAdwFCrugjx07Vs2bN9eWLVu0b98+BQcHa/To0apdu7YsFov69u2r7t27V7lQZhiGbDabI4zv2LFDcXFx8vT01NChQ+Xj4+P42rp165Sbm6suXbrIx8enVA8AHv9fVzdGcnd3L/HI/eN/fvDggWMdfMuWLdWyZcsSnWe1Wqvcz8XLYN++fdq6dauCgoL0wx/+kL+jF5RhGDpy5Ig2b94su92u4OBgjRkzRkFBQa4uDQAAOFFF5FCmoLvAyJEjtXTpUsXFxUmSLl++LEny9vZWnz595O7urpMnT2rbtm26efOmhg8fXqW6ohdOO7darbpw4YLjfY4YMcKx7ZhUMGK4YsUKSQVbOfn5+ZX5noZhlHh0vrQBv/DPKSkpstvtcnNzk91uL3J/m80mm83mmGZfFufOndO5c+dKfHxpGvOVd1p/4TICAuWzdezYUXv27NG9e/d04cKFIj/veHFYLBbFxMQoNDRUS5cuVXJysmbNmqXhw4erZcuWri4PAABUYgRwF+nYsaPOnDkjDw8P/dd//Zfq1q2rnj17yt3dXYZhqH79+tq4caNjW7LRo0erXr16ri67VB4+fKjVq1dLkjp37vxEGElPT5dUMHrs6+tbrntZLBZ5eHg4OspXhO+++04LFy50rKlv3769Bg0a5JTQf+vWLaWkpEiSgoOD5e7uXuw1ilvPn52dXWHv+ftKs0bfWaG/KvHy8lKnTp20d+9e7d27V82bN+ehxQssPDxcM2fO1PLly3X9+nUtXbpU3bt3V9++fenpAAAAikUAd5HCUe+WLVtqxIgRRb5msVgUHR2tevXqaenSpXrw4IG++OILDRgwQDExMVXiF3qbzably5crOztb9erVU//+/Z84prADekBAQJV4T40bN1b9+vV148YNSVKnTp3k6enplLWfhmFo2bJlOnfunNLT0zVlyhQFBwc/cZzNZqvwkf7v/+/j8vLylJeXp6ysrHK/55IofLBiZugvb3Dq3LmzDh48qNu3b+v69et0yn7BVatWTW+//ba2bt2qgwcPat++fUpISNDIkSPLNasHAAC8mAjgLlIYwJ/VaK1OnTqaMWOG1q5dq3PnzmnTpk26ceOG3njjDXl5eZlVapls3bpVt2/flre3t0aNGlXsSObjAbwqsFgsqlOnjiOAO3N01mKxaMSIEXr06JFu3rzp2CP8+9uzubu7y93d3bS//8L1/GaG/seb+BmGodzcXOXm5pryfqWCJn7lDf1hYWG6du2aNm/erH79+j33WlXhARSezt3dXa+99prq1auntWvX6sqVK4qNjdWYMWOq3MwlAABQsQjgLpCRkeHYD7xx48bPPNbb21ujR4/WoUOHtGXLFp09e1aJiYkaPXq06tSpY0a5pXb+/HkdPHhQkjR8+HBVr1692OOqWgA3DEOXLl1yfL5t2zaNHz/eadf38PDQ2LFjNWfOHKWkpGjx4sV65513XNpd+fH1/N7e3qbcs3A9v7O79j/rtceb+NntduXk5JRrPX+hxMRELVy48LnHubu7mzrSz3r+ihEZGanatWtryZIlSklJ0dy5czV48GB16NBBUsEMlj179ighIUGhoaGOZUcAAODlQQB3gStXrkiSQkJCVK1ateceb7FY1KVLF4WFhWnZsmVKSUnRnDlzNGjQIEVFRVWqX6QfPHigNWvWSJK6dOmi5s2bP/XYqhbAL1++rAcPHsjT01N5eXm6dOmSrl275tQpxr6+vo49whMSErRs2TKNGzfupVpPasZ6/u+z2+1OD/137txRRkaGvL29Va1atSeOe7yRX2ETPzOVZau+8oR+Nze3SvXfqopSu3ZtTZ8+XWvWrNH58+e1bt063bp1S7m5ufrggw9069Ytx7FhYWH6y1/+opEjR7qwYgAAYCYCuAsUBvDnjX5/X1hYmGbOnKlVq1bpu+++07p163Tjxg0NHjy4UuxB+/i677CwML366qvPPL6qBfBjx45JKmi+ZrfbdfToUW3dulVTp051arCoWbOmxo8fr3nz5um7777T+vXrNXTo0JcivLiKm5ub09bzF0pKStLf//535eTkaPr06apZs2aRr9vt9lJN6y/pqP6zzi2uiZ9ZCmdTlDbglyTsPyv0u4K3t7fGjBmjffv2afv27YqLi9OdO3ccjScL3b59W6NGjdLy5csJ4QAAvCQI4CYzDMOx/ru0AVwqGCEdP3689u7dqx07dujEiRO6c+eORo8eXWzTLjNt2bJFd+7ckbe3t958883nTq2sSgE8LS1NFy5ckFTQwd7Hx0cnTpzQ7du3de7cObVq1cqp96tXr55GjRqlJUuWKC4uTtWrV9crr7zi1HugYoWEhKhp06a6dOmS9u/fryFDhhT5upubm7y8vExdz++K0P/4/Qub+JnFzc3N9NBf+KDMYrGoR48eCgkJ0RdffKG6detq5syZWrFiheP/AwzDkMVi0fvvv69hw4YxHR0AgJcAAdxkycnJSk9Pl9VqVf369ct0DYvFop49eyo8PFwrVqxw7EE7dOhQtWnTxskVl8y5c+d06NAhSc9e9/24qhTAjx07JsMw1KBBA8eDjq5du2r37t3avn27mjdv7vRfnps3b66BAwdq48aN2rFjh6pXr662bds69R6oWN27d9elS5cUHx+vXr16PdFUz0wWi8XRxM8shU38zOza//31/GY38XN3dy8SynNzc5WamiqLxSJfX19NnDhReXl5+vjjj2UYhgzD0M2bN7Vnzx717t3btDoBAIBrEMBN9t1330mSGjZsKKu1fN/+hg0bOkZUrl27ppUrV+r69esaOHBgua9dGo+v++7atesz130XstlsevTokaTKH8BtNpuOHz8uqWD0u1C3bt109OhR3b9/X3FxcUW+5iwxMTFKTU3V/v37tWbNGvn7+ysiIsLp90HFqF+/vsLDw3Xz5k0dOnToucsyXjSPN/EzS2ETPzNDf3Hr+R9v4hcSElLke+Lh4aEmTZoUaepY2JgTAAC82AjgJivr+u+nKdyDdufOndqzZ4+OHTvmmJJeo0YNp9zjWfLz87V8+XLl5OQoLCxM/fr1K9F5heHbzc2t0u+Ve/HiRT169Ei+vr5q2bKl43UvLy+98sor2rRpk3bt2qW2bdtWyFr8V199VampqTpz5oyWLFmiKVOmqHbt2k6/D5zPYrGoe/fu+vrrr3X06FH16NHDtG7yLytXNvF7PKhnZGTozJkziouLKzLt3m636+bNm0XCtySFhoaaVi8AAHCdl6e1ciWQl5en69evS3JeAJcKQmzfvn01YcIE+fj4KCEhQZ9//rnOnTvntHs8TeG6bx8fn6fu912c1NRUSQWj35W9udjRo0clSVFRUU+8v44dO6p69ep69OiRY+s1Z7NYLBo+fLgaNGignJwcLVy40DF9H5Vfs2bNFBwcrJycHMfPEl4shU38/Pz8lJ+fr0OHDmnhwoU6fPhwkbXwdrtdS5Ys0dy5cx3nWiwWhYeHq2fPnq4qHwAAmIgAbqIbN24oPz9fAQEBCgoKcvr1mzRpopkzZyosLEw5OTlaunSpNm/eXGHbG509e1aHDx+WVLDuOzAwsMTnVpX13/fv33fMWihuirm7u7v69u0rSdq3b58yMzMrpA6r1aq33npLQUFBSktL06JFi5yyTzUqXuEouCQdPHjQ1CZkMEdhc81Fixbpf//3f3XkyBHl5uYqKChIjRo1ktVqlWEYWrlypaOZoyTHw8dPPvmEBmwAALwkCOAmKux826hRowob9Q0MDNQ777yjLl26SCr4hX/evHmOEWdnSUlJ0dq1ayUVrIVu1qxZqc6vKgG8cOuxpk2bPrWxXGRkpOrUqaPc3Fzt3r27wmrx8fHRhAkT5Ofnp6SkJC1dutT0vaNRNpGRkQoMDFRGRoZOnDjh6nLgJLm5uTp69Kg+/fRTLViwwDGtvFmzZnr77bfVqlUrxwO8sLAwPXz4sMj5YWFhbEEGAMBLhgBuovJsP1Ya7u7ueu211zRmzBh5eXnp1q1b+vzzzx0N4Mrr8XXf4eHhjhHg0qgKATw/P1/x8fGSpOjo6KceZ7FYHM21jhw5ogcPHlRYTdWrV9f48ePl4eGhK1euaP369UX2dkbl5O7urm7dukkqmCnxeNMuVD0PHz7Uli1b9Oc//1kbNmzQvXv35OnpqZiYGP2f//N/NG7cOCUkJDgeyA0cOFDTpk3TtWvXtGPHDi1atEg7duzQ1atXCd8AALxkaMJmkvT0dN29e1dSwQi4GVq2bKmQkBAtW7ZMiYmJWrhwoXr27KnevXvLza3sz16+/fZbJSQklHrd9+PS09MlVe4AfubMGWVlZSkwMFBNmzZ95rGNGzdWo0aNdOXKFe3cuVMjRoyosLrq1q2r0aNHa/HixYqPj1dgYCDbF1UBUVFR2rVrlx4+fKgzZ864bMtAlI1hGLpx44YOHTqk8+fPOx581ahRQzExMYqKinLs6X7kyBFt3bpVktS3b1917txZUsGDGP6tAgDwcmME3CSFo99169aVr6+vafetWbOmpk6d6hjB3bNnj7766itHF/LSOnPmjI4cOSJJGjFiRJkDdFUYAS9smNWhQ4cSPbAo7AB/8uRJJSYmVmhtTZs21euvvy5J2rVrl+Li4ir0fig/Dw8PRxDbt28fMxeqiMKZMLGxsZo3b57OnTsnwzAUERGhsWPH6sc//rG6dOniCN/x8fH65ptvJEk9evSguRoAACiCAG4Ss6afF8dqtWrIkCEaOXKkPDw8dO3aNX3++ee6du1aqa7z+Lrv7t27P3dU+Fke74JeGSUmJurWrVtyc3NThw4dSnRO3bp1FRkZKUnatm1bRZYnqWBafI8ePSRJ69evd/yMofLq1KmTPD09lZSU5LQlIagY6enp2rFjhz755BOtWbNGiYmJslqt6tChg9577z1NmjRJzZs3L/Jw7uzZs47/RsbExJRpeQ4AAHixEcBNYBiG0/f/Los2bdpo+vTpCg4O1qNHjzR//nzt2bOnRCNx+fn5WrZsmXJzc1W/fv1y/WJpt9sdI/CVNYAXjn63aNFC1apVK/F5ffr0kZubm7777jtdvXq1ospz6Nu3r9q0aSO73a6lS5dW+Mg7ysfHx8cxG2Xfvn0urgbFuX37tlauXKlPPvlEu3fvVkZGhgICAtSvXz998MEHGjp0qGrXrv3EeRcvXtSKFStkGIaioqI0cODASr/FIgAAMB8B3AQJCQnKzMyUp6enwsLCXFpLcHCwpk2bpnbt2skwDG3fvl2LFy9+7vZZmzdvVmJionx9ffXmm2+Waw35o0ePZBiGLBaL/Pz8ynydipKTk6NTp05JKn7rsWepWbOmI2Bt3bq1wqcZWywWDRs2TA0bNlRubq4WLVrk9I73cK4uXbrIzc1N169f182bN11dDiTZbDadPn1ac+bM0ezZs3Xq1CnZ7XaFh4dr1KhR+ulPf6oePXo8dfnQ1atXtXTpUtntdkVGRmrIkCGEbwAAUCwCuAkKpwZHRERUir1ePT09NWzYMA0dOlRWq1WXLl1SbGysbt26Vezxp0+fdowIl2fdd6HC9d/+/v7lCvIV5dSpU8rNzVWtWrXUsGHDUp/fq1cveXp66s6dOzp79qzzC/wed3d3vfXWWwoODlZ6eroWLVqk7OzsCr8vyiYgIEDt2rWTxCi4q2VmZmrPnj36n//5H61YscKx7KRt27aaPn26pkyZotatWz/zv1M3b97U4sWLZbPZ1Lx5cw0fPrxS/ncNAABUDvyWYAJXrv9+GovFog4dOmjq1KmqWbOmUlNTNXfuXB08eLDIqO39+/e1bt06SQUNhZo0aVLuexcG8MDAwHJfy9kMw3A8bOjYsWOZRrH8/PzUtWtXSdL27dtN2avb29tbEyZMkL+/v+7evaslS5awR3glVrgl2YULFxy7I8A8d+/e1dq1a/XnP/9Z27dvV1pamvz8/NSrVy998MEHGjFihOrWrfvc6yQkJGjhwoXKy8tTo0aNyrwrBAAAeHkQwCtYTk6OY5ppZQrgherUqaMZM2aoVatWstvt2rx5s5YtW6bs7Owi674bNGigPn36OOWelbkD+q1bt5SUlCSr1eoYpSyLrl27ys/PTykpKTp+/LgTK3y6wMBAjR8/Xp6enrp27ZrWrl1Lp+1KKigoSC1btpQk7d+/38XVvBzsdrsuXLig+fPn67PPPlNcXJzy8/MVGhqq4cOH6/3331fv3r1L3PMhOTlZCxYsUE5OjurXr6+33npLVis7ewIAgGfjt4UKdv36ddntdtWoUUM1a9Z0dTnF8vLy0qhRo3T48GF9++23OnfunJKSkhQSEqKkpCSnrPt+3ONT0CubwtHvyMhI+fj4lPk6Xl5eeuWVV7Rx40bt2rVL7dq1k6enp7PKfKo6depo9OjRWrRokU6ePKnAwEA6MVdS3bt317lz53Tq1Cn17t1b1atXd3VJL6Ts7GzFx8fr8OHDevDggaSCGUAtW7ZU586dFR4eXuqZLikpKZo/f74yMzNVt25djRs3zpR/3wAAoOojgFewwq2GKuPo9+MsFos6d+6sevXqafny5UpJSVFKSoqkgnXfzgzLlXUEPDMzU2fOnJFU+uZrxYmOjtbBgwf14MEDHThwQL169Sr3NUuiSZMmGjp0qNauXas9e/YoMDDQ0RgOlUe9evUUERGhq1ev6sCBAxo0aJCrS3qh3L9/X4cPH1Z8fLxyc3MlFSzV6NChg2JiYsq8BCY1NVXz58/Xo0ePVLt2bU2YMEHe3t7OLB0AALzAmIJewSrD9mOlERYWplGjRhUZESpsSuYslTWAx8fHy2azqU6dOiVa//k87u7ujtHn/fv3KyMjo9zXLKmoqCi98sorkqQNGzbo0qVLpt0bJVe4j/vx48efuxMBns8wDF2+fFmLFi3S//7v/+rw4cPKzc1VcHCwXn/9dX3wwQfq379/mcN34faNqampqlmzpt5+++2ndkYHAAAoDgG8Aj18+FD379+XxWIpUzdtV8jLy9P69etlGIaqV68ui8WikydPavbs2UpOTnbKPSpjADcMQ8eOHZNU9uZrxWndurVCQ0OVm5ur3bt3O+WaJdW7d2+1b99ehmFo2bJlSkhIMPX+eL6IiAjVrVtX+fn5OnTokKvLqbJyc3N19OhRffrpp1qwYIHjgVPTpk01ceJEvffee+rYsWO5polnZmbqq6++UkpKigIDAzVp0qQSrxcHAAAoRACvQIXdz8PDw6vMFMVNmzYpKSlJfn5+mjJliuOXzOTkZM2aNUsnT54s1/XtdrvS09MlVa4u6FeuXFFKSoq8vLzUpk0bp13XYrHo1VdflVSwvrxwDaoZLBaLhgwZokaNGikvL0+LFi3Sw4cPTbs/ns9isah79+6SpMOHDysnJ8fFFVUtqamp2rJli/785z9rw4YNunfvnjw9PRUTE6Mf//jHGj9+vBo3blzuB2o5OTlauHCh7t69q2rVqmnSpEmV6r9fAACg6iCAV6DCAN6oUSMXV1IyJ0+edHTsHjlypPz9/dWwYUPNnDlTERERysvL06pVq7Ru3Trl5+eX6R4ZGRmy2+2yWCyVavSocPS7bdu2Tm+m1KhRIzVu3Fh2u107duxw6rWfx93dXWPGjFFISIgePXqkhQsXKisry9Qa8GwtWrRQrVq1lJ2dbVrH/KrMMAxdv35dS5cu1V/+8hft379f2dnZqlGjhl577TV9+OGHGjRokGrVquWU++Xm5mrRokW6c+eOfH19NWnSpErbUBMAAFR+BPAKYrfbHeu/nbF3dkW7d++e1q9fL0l65ZVXijw0qFatmiZOnOhYU3z8+HHNmTPH0aStNAqnn1erVs1pXdXLKy0tTefPn5fknOZrxenXr5+kgvX0Zk8F9/Ly0vjx4xUQEKB79+5pyZIlZX6AAudzc3Nz7At+4MAB/m6eIj8/X/Hx8YqNjdW8efN07tw5GYahiIgIjR07Vj/+8Y/VpUsXeXl5OfWeS5Ys0Y0bN+Tl5aWJEycqODjYadcHAAAvn8qRgF5At2/fVk5Ojry9vRUaGurqcp4pLy9Py5YtU15enho2bFhst243Nzf16dNHEyZMkK+vrxITExUbG6tz586V6l6Vcf338ePHZRiG6tevr9q1a1fIPUJDQxUZGSlJ2rZtW4Xc41kCAgI0fvx4eXl56fr161qzZg17hFcibdu2lb+/v9LT03Xq1ClXl1OpPHr0SDt27NAnn3yiNWvWKDExUVarVR06dNB7772nSZMmqXnz5k5/oGez2bR8+XJduXJFHh4emjBhQqX/bzkAAKj8COAV5PHp55VlpPdpNm7cqLt378rPz++5+303adJEM2fOVHh4uHJycrR06VJt2rRJNputRPeqbAHcbrc7pv1W1Oh3ob59+8rNzU2XL192zI4wU0hIiMaMGSM3NzedPn3aJQ8CUDyr1aouXbpIkvbt2ye73e7iilzvzp07WrVqlf785z9r9+7dysjIUEBAgPr166cPPvhAQ4cOrbAHZna7XatXr9aFCxdktVo1btw4hYeHV8i9AADAy6VyJ8MqrDCAV/btx06cOKG4uDhJ0ptvvlmiddkBAQGaPHmyunbtKkk6dOiQ5s2bp9TU1OeeW9kC+MWLF5Weni5fX1+1bNmyQu9Vo0YNR8jfunWrS0agGzVqpDfeeENSQdA7cuT/Y+++g6M8t33Pf7uVs4QEykgIASIJtUASGLDJGDBgMiZjbPB2AlxTc2b2rZq6dWvu3Km6dW0ctr0xBmySjBHBgAk2OYvQLQQiCkUUUM6xu9/5Q6M+yCQBLbXC+lS5zjkt6X2XUDj6vc/zrHWl1WsQTzd48GDs7e0pLCzk7t27li7HIgwGA0lJSWzatMnU9NFoNBIYGMjs2bP5/PPPGTFiRIuO/lIUhQMHDnDz5k3UajVz586lR48eLXY/IYQQQnQu1pYuoCOqrq4mKysLaNsBPD8/nz/++AOAt95666X+yLSysmLChAl0796dffv28fDhQ9avX8+MGTPo1avXMz+urQXwq1evAg1zs62tW/7H4c033yQhIYGcnBySkpJM29Jb06BBgygtLeXkyZMcPnwYV1dX+vTp0+p1iKbs7OyIiori7NmznDt3jrCwMLONw2vrqqqq0Gq1XLlyxfQ7Qq1WM2DAAGJiYvDz82uVOhRF4ciRIyQkJKBSqZg1a9Zzf58JIYQQQrwsWQFvAampqSiKgpeXV5sdVfP4ue8ePXqYGqy9rLCwMFatWoWvry/V1dXs2LGDEydOPHMLbVsK4EVFRaadCoMHD26Vezo5OZkabp04caLZW/fNbeTIkWg0GhRFYffu3aYHRsKyYmJisLa2Jjs7m7S0NEuX0+Ly8vI4cOAAX331FcePH6esrAwnJyfefPNN1qxZw4wZM1otfEPDz+Tly5cBmD59Ov369Wu1ewshhBCic5AA3gLaw/bzQ4cOkZ+fj7OzMzNnznytc+oeHh68//77pu3VZ8+eZevWrVRUVDzxvm0pgDeOHgsNDcXDw6PV7jts2DCcnJwoLi421dDaVCoVU6ZMITQ0lPr6emJjY1t1Rrl4OicnJzQaDQDnzp2zcDUtw2g0cvfuXbZs2cIPP/yAVqtFr9fj4+PD9OnTWbNmDaNHj8bFxaVV62rceQAwefJkBg0a1Kr3F0IIIUTnIAHczBRFafMBPCEhwbTFcubMmWaZx21tbc2UKVOYOXMmNjY2pKWl8e9//7vJKp6iKJSXlwOWD+B6vd509r21Vr8b2dramjrNnzlzhtra2la9fyMrKytmz56Nj48PlZWVbN++naqqKovUIv7TG2+8gUqlIiUlhezsbEuXYza1tbVcunSJ7777jl9//ZXU1FRUKhX9+vVj2bJlrFy5koiIiFY5CvJ38fHxnDhxAoDx48cTFRXV6jUIIYQQonOQAG5mRUVFlJaWYmVlRVBQkKXLeUJ+fj6HDh0CXv7cd3MMHDiQlStX0q1bNyorK9myZQtnz55FURQqKytNW65be3Xr727dukV1dTWurq707t271e8fGRlJly5dqKys5OLFi61+/0aNM8Ld3NwoLCzk119/pb6+3mL1CHB3d2fgwIFAQ6O89q6wsJDDhw/z5ZdfcvToUYqLi7G3t+eNN95g9erVzJkzh6CgIIudd9dqtRw5cgRo+J3YeERECCGEEKIlSAA3s+TkZAC6d++Ora2thatpqq6uznTuOyQkhJEjR7bIfby8vPjggw8YNGgQiqJw4sQJduzYQV5eHgDOzs5YWVm1yL2bq7H5WmRkpEXGxFlZWTFmzBgALl68+NTt+q3FxcWFhQsXYmdnR2ZmJvv27ZMZ4RY2fPhwoOFBUWFhoYWreXmNO4F27NjBd999x+XLl6mrq8PLy4spU6awdu1axo8fb/EeGTdu3ODAgQNAw9GQxp0pQgghhBAtRQK4mTXOd26L28/Nee77RWxsbHj33XeZNm0a1tbWJCcns3v3bsDy288fPXpEZmYmKpWKyMhIi9XRr18//Pz8qKur48yZMxarA6Br167Mnz8fKysrbt26xZ9//mnRejq7bt26mXZmXLhwwcLVNF99fT1Xr17lhx9+YNu2bdy/fx+AXr16sWjRIj7++GOGDBnSJh5O3rlzh7179wINx1DGjx/fabrOCyGEEMJyJICbkcFgIDU1FWh7ATwhIYHr16+bRus4OTm1yn01Gg0ffPABXbp0MZ0v1uv1Fl1hbVz9DgsLs+hWeJVKxbhx44CGhnBFRUUWqwUgODiY6dOnA3Dp0iXi4+MtWk9nN2LECACuX79u6p3QVpWWlvLXX3/x5Zdf8scff5Cfn4+trS3R0dF8+umnLFiwgJ49e7aZgPvgwQPi4uJQFIXw8HCmTJnSZmoTQgghRMcmAdyMMjMzqa+vx8nJCW9vb0uXY5KXl2ea9z1q1CiCg4Nb9f7e3t6sXLkST09PUz27du2ipqamVeuAhm34iYmJAKau7ZbUo0cPevbsidFo5OTJk5Yuh4EDBzJ27FgAjhw5wu3bty1cUecVGBhI9+7dMRgMFu0T8CyKopCRkcGuXbv4+uuvuXDhAjU1NXh4eDBx4kTWrl3LpEmTTD/3bUV6ejq//vorBoOBvn37Mn36dAnfQgghhGg1EsDN6PHu523lD7rGc996vZ6ePXu22LnvF7GzszPN81WpVNy+fZsff/yRnJycVq3jxo0b1NXV0aVLF7M3oHtVjavgN2/ebBNdr4cPH256OLFnzx4yMzMtXFHn1bgKfu3aNaqrqy1cTQO9Xs/169fZsGEDmzdv5tatWyiKQo8ePZg/fz6ffvopQ4cOxd7e3tKlPiE7O5sdO3ag1+sJDQ1l1qxZFukBIYQQQojOS/7yMKPGAB4SEmLhShooisIff/xBQUEBLi4uzJgxw6IPBhpngL/11lu4ublRXFzMxo0buXr1aqtsSVcUxbT9fMiQIW3mIYmPj4+p6/Xx48ctXE3DA5JJkybRu3dv9Ho9sbGx7bIRWEcQGhpKt27dqKur48qVKxatpaKiglOnTrFu3Tr27dtHTk4O1tbWaDQaPvroI5YsWUKfPn3abKB99OgR27Zto66ujuDgYObOnWvxZpBCCCGE6Hza5l9K7VBlZaVpNbetnP9OSEggMTGx1c99P0tjAA8ODmbVqlX07t0bg8HAH3/8wd69e6mrq2vR+2dlZZGbm4uVlRUREREteq+XNXr0aNRqNSkpKaYHOZakVquZNWsWfn5+VFdXs337diorKy1dVqejUqlMq+Dx8fEWGRGXnZ3N3r17+eqrrzh9+jSVlZW4uroyduxY1q5dy7Rp09rUkZunKSwsZOvWrVRXVxMQEMD8+fOxsbGxdFlCCCGE6IQkgJtJY/dzb29vnJ2dLVxNw2pP47zv0aNHW3wmuaIopgDu6uqKg4MD8+fPZ9y4cahUKm7cuMGGDRvIz89vsRoaV78HDBiAg4NDi93nVXh4eBAVFQXAsWPH2sQYMFtbW9577z3c3d0pLi4mNjZWZoRbQP/+/XF3d6eqqgqdTtcq9zQajSQlJbFp0yY2bNhAYmIiRqORwMBAZs+ezeeff86IESNwdHRslXpeR0lJCVu2bKGyshIfHx8WLFiAnZ2dpcsSQgghRCclAdxMHj//bWmPn/sODQ01raBZUnV1NQaDAcDUeVylUjF8+HCWLl2Ks7MzBQUFbNiwgevXr7fI/ZOSkoC20XztaUaOHImtrS25ubncvHnT0uUADTPbFy5ciL29PVlZWezZswej0WjpsjoVtVrNG2+8ATSMJGv8OWoJVVVVnDt3jq+//pq4uDgyMzNRq9WEh4fzwQcf8P7779O/f/92s3W7vLycLVu2UFZWhpeXF4sWLWpzD9+EEEII0blIADcDRVHaTABXFIWDBw9SWFjYJs59N2pc/XZycsLa2rrJ24KCgvjoo4/o0aMH9fX17Nu3jwMHDph1tTUhIQG9Xo+3tzf+/v5mu645OTk5MXz4cABOnDjRokHrZXh5efHee+9hZWXFnTt3OHr0aJtYoe9MIiIicHR0pLS01PQgyZzy8vI4cOAAX331FcePH6esrAwnJyfefPNN1qxZw4wZM9rsz82zVFZWsmXLFoqLi/Hw8GDx4sUWP4YjhBBCCCEB3Azy8vKoqKjA2tqa7t27W7QWnU7HjRs3UKlUzJ49u81sEX18+/nTODk5sWjRIt566y0AtFotmzZtMsts7LbafO1phg4dipOTEyUlJaaa24Lu3bszY8YMAC5fvsylS5csXFHnYmNjw9ChQwE4f/68WR6AKIrC3bt32bJlCz/88ANarRa9Xo+Pjw/Tp09nzZo1jB492rRjpT2pqalh27ZtFBQU4OrqypIlS575u0cIIYQQojVJADeDxtXv4ODgJ1Z3W9OjR484fPgwAGPGjLH4w4DHvSiAQ8NW21GjRrFo0SIcHR3Jzc1l/fr13Lp167XunZqaSlFREba2tqZu422Vra0to0aNAuDMmTPU1tZatqDH9O/fn/HjxwPw559/tshKrHi2qKgobG1tycvL4/79+698ndraWi5dusS3337Lr7/+SmpqKiqVir59+7Js2TJWrlxJRESERX+XvY66ujq2b99Obm4uTk5OLF68GHd3d0uXJYQQQggBSAA3i7aw/by2ttZ07rtXr16mrcxtRWlpKUCzVtN69uzJqlWrCAwMNJ1nP3LkyCtvyb527RoA4eHh7aL5kkajoUuXLlRVVXHhwgVLl9PEsGHDiI6OBmDv3r1kZGRYuKLOw97e3tS/4Pz58y/98UVFRRw+fJgvv/ySo0ePUlxcjL29PW+88Qaff/45c+fOJSgoqE3vEHmR+vp6YmNjefjwIfb29ixevBgvLy9LlyWEEEIIYSIB/DXV19eTnp4OWC6AP37u29XVlXfffbfN/RFdXl4OPH8F/HGurq4sXbrU1HwqPj6ezZs3m4L8y9z3zp07QNttvvZ3VlZWjB07FoCLFy9SUVFh4Yr+k0qlYuLEiYSFhWEwGPj1118pKCiwdFmdxtChQ7GysiIjI6NZDz8a+1PExsby7bffcvnyZerq6vDy8mLKlCmsXbuW8ePHd4gVYoPBwK5du0hLS8PW1pZFixa1+fFoQgghhOh8JIC/poyMDAwGA66urhZbadFqtdy8ebPNnft+XHO2oP+dlZUV48ePZ/78+aYu3OvXr3+p7bdardY0Pqk9/THet29f/P39qa+v5/Tp05Yupwm1Ws3MmTPx9/c3zQhvSw8JOjIXFxcGDRoEPH8VvL6+nmvXrvHDDz+wbds27t27B0CvXr1YtGgRH3/8MUOGDMHW1rZV6m5pRqORPXv2cP/+faytrVmwYEG7axonhBBCiM5BAvhrSk5OBiAkJMQiq865ubmmc99jx44lMDCw1WtojlcJ4I369OnDypUr8fPzo7q6mh07dnD8+PEXjsMyGo1otVqg/ax+N1KpVIwbNw5oeIhgjmZ05mRjY8N7772Hh4cHJSUlxMbGUldXZ+myOoXhw4ejUqm4d+8ejx49avK20tJS/vrrL7788ksOHjxIfn4+tra2REdH8+mnn7JgwQJ69uzZ5nbIvA5FUdi/fz+3bt3CysqKefPmERQUZOmyhBBCCCGeSgL4a0pJSQEgNDS01e/deO7bYDDQu3dv03bttkZRFFMAd3Nze6VreHh4sHz5cqKiogA4d+4cW7ZsMW1tf5r79+9TVlaGg4MD/fr1e6X7WlJwcDChoaEYjUZOnDhh6XKe4OTkxMKFC3FwcCA7O5vdu3fLjPBW0KVLF9P3c2NH9IyMDHbt2sXXX3/NhQsXqKmpwcPDg4kTJ7J27VomTZqEp6enhSs3P0VROHToENevXzftALLE72IhhBBCiOaSAP4aysrKyMvLA6BHjx6tem9FUThw4ABFRUW4uroyffr0NruqVVNTY5rp/TojjaytrZk8eTKzZs3C1taW9PR01q9fT2pq6lPfv3GMl0ajabcdnRvPgiclJZGdnW3hap7k6enJe++9h7W1Nffu3ePw4cMyI7wVNDZZvHnzJj/88AObN2/m1q1bKIpCjx49mD9/Pp9++ilDhw7F3t7ewtW2DEVR+Ouvv0w/5zNmzCAsLMzCVQkhhBBCPJ8E8NfQuPrt7+/f6ueur127RlJSEmq1us2e+27UuPrt4OCAjY3Na19vwIABfPjhh3Tr1o3Kykq2bt3KmTNnmgS/4uJi0/GAwYMHv/Y9LcXHx4fw8HAAjh071ibDbWBgIDNnzgQaHnq8Sodu0XwVFRXcvXsXKysrFEUhPz8fa2trNBoNH330EUuWLKFPnz6o1R371/uZM2e4ePEiAFOnTm3zIwaFEEIIIUAC+GtpHD8WEhLSqvfNycnhyJEjQNs+993odc5/P4uXlxcffPABERERKIrCyZMn2b59O1VVVcB/jh7r2bMnXbp0Mdt9LWH06NFYWVmRmppqeujT1vTt25e3334bgOPHj3Pjxg0LV9TxZGdns3fvXr766itOnz5tGsunVqtZuXIl06ZNa1eNBl/HhQsXOHXqFAATJ04kMjLSsgUJIYQQQjSTBPBXpCiKRc5///3c97Bhw1rt3q+qJQI4NDQCmz59OtOmTcPa2poHDx6wfv160tLS0Ol0QPtrvvY07u7uprPvbXUVHCAmJoahQ4cC8Pvvv5OWlmbZgjoAo9FIUlISmzZtYsOGDSQmJmI0GgkICGDmzJn4+flhNBo71QOPq1ev8tdffwEND6cav+eEEEIIIdqD9nkwtg3IycmhqqoKW1vbVht309jtt7i4GDc3tzY57/tpWiqAN9JoNPj5+bFr1y4KCwvZsmULiqLg7OxM7969W+SerW3kyJHodDpyc3O5efNmm91uO2HCBEpLS7l9+zY7d+7k/fffp2vXrpYuq92prq7m2rVrXLlyxfTzo1ar6d+/PzExMabfOdbW1vz2229cuXKF4cOHY2dnZ8myW9z169f5448/gIZz8CNHjrRwRUIIIYQQL0dWwF9R4/bzHj16YGVl1Sr3vHr1Krdu3TKd+3ZwcGiV+76ulg7gAN7e3nz44Yf079/ftEJsZ2fXYUZjOTo6mhpvnThxAr1eb+GKnk6lUjFjxgwCAwOpqalh+/btz+1UL5rKy8vjwIEDfPnllxw/fpyysjIcHR158803WbNmjWn+eqOwsDA8PT2pqakxHbvoqG7dusXvv/8OQHR0NGPHjm0XDyCFEEIIIR4nAfwVNQbwnj17tsr9srOzOXr0KADjxo0jICCgVe5rDq0RwKEhcD++IlZYWMj69evbZPfwVxETE4OzszMlJSVtOmzZ2Ngwf/58unTpQmlpKTt27OgwD0JagqIo3Lt3jy1btvDDDz+g1WrR6/X4+Pgwffp01q5dy+jRo586QUClUpkezFy8eLHNPph5Xffv32f37t0oikJERARvv/22hG8hhBBCtEsSwF9BbW0tmZmZQOsE8JqaGuLi4jAYDPTp06fdnXlsrQAO/9l8LSgoCHd3d0pKSti0aRNXr15ts2enm8vW1pZRo0YBDR2ga2trLVvQczg6OrJw4UIcHR3Jzc1l165dMiP8b2pra7l06RLffvstsbGxpKamolKp6Nu3L8uWLWPlypVERES8cIReeHg4rq6uVFRUkJiY2ErVt57U1FR+++03jEYj/fv3Z+rUqRK+hRBCCNFuSQB/BWlpaRiNRjw8PFq8w/bj577d3d3b9Lzvp1EUpdUCeF1dnSmAjBw5kpUrV9KnTx8MBgN//PEHe/fubfcrsRqNBk9PT6qqqrhw4YKly3muLl26sGDBAqytrUlOTubgwYPt/iGIORQVFXH48GG+/PJLjh49SnFxMfb29rzxxht8/vnnzJ07l6CgoGb/nFtZWZmaMZ4/f75DPejIzMwkNjYWvV5P7969mTFjRocfryaEEEKIjk3+knkFrbn9/MqVK9y+fbvdnftuVFtbawq9LR3Ab968SW1tLR4eHoSEhODg4MC8efMYP348KpWKGzdusGHDBvLy8lq0jpakVqsZO3Ys0LDluKKiwsIVPZ+/vz+zZ89GpVKh0+k4e/aspUuyiMapCbGxsXz77bdcvnyZuro6vLy8mDJlCmvXrmX8+PG4u7u/0vUjIyNxcHCgqKiIO3fumLd4C8nJyWH79u3U19cTEhLCnDlzWq3fhhBCCCFES5EA/gpaK4A/fu57/PjxrdZt3ZwaV7/t7e2xtbVtsfsoisLVq1eBhtFjjauHKpWKN954g2XLluHi4kJBQQEbNmzg+vXrLVZLSwsLC8Pf35/6+npOnz5t6XJeqE+fPkyaNAmAkydPtut/+5dVX1/PtWvX+OGHH9i6dSv37t0DoFevXixatIiPP/6YIUOGvPbPhq2tLdHR0QCcO3eu3e80yM/PZ9u2bdTW1hIYGMi8efNeuBVfCCGEEKI9kAD+koqLiykqKkKlUtGjR48Wu09NTY3p3GxYWBgxMTEtdq+W1Frbz7Ozs8nJycHKyoqIiIgn3t69e3dWrVpFSEgIer2effv2sX//furr61u0rpagUqkYN24c0HDmvbCw0MIVvVhUVBRvvPEGAPv37yclJcXCFbWs0tJSjh07xldffcXBgwfJz8/HxsaGqKgoPv30UxYsWEDPnj3NepwkOjoaGxsbcnJy2vW/b1FREVu2bKGqqgpfX18WLFjQog/vhBBCCCFa0ysF8O+//54ePXpgb2/P4MGDn7utdM+ePYwfP56uXbvi6urKsGHDTKu67VHj6ndgYGCLzdxVFIXff/+dkpKSdnnu+3GtFcAbV7/79++Po6PjU9/HycmJhQsX8tZbbwGg0+nYuHFjuwiwfxccHEyvXr1QFIUTJ05YupxmGTduHAMGDMBoNPLbb7/x6NEjS5dkVoqikJGRwa5du/j66685f/481dXVuLu7M2HCBL744gsmT56Mp6dni9zf0dGRyMhIoOEseHtUWlrKli1bqKiooFu3bixatAh7e3tLlyWEEEIIYTYvHcB37tzJmjVr+C//5b+g0+kYOXIkkyZNIiMj46nvf+bMGcaPH8+hQ4e4du0ao0ePZurUqeh0utcu3hIaV5Zacvv55cuXuXPnDmq1mjlz5rTrP0BbI4BXV1dz8+ZNoGH7+fOo1WpGjRrF4sWLcXR05NGjR/z4448kJSW1WH0tpfEs+K1bt8jKyrJwNS+mUqmYPn06QUFB1NbWsmPHDtP3R3um1+u5fv06GzZsYPPmzdy6dQtFUQgODmbevHl89tlnDBs2rFV+jocNG4ZarSY1NbVdfE88rqKigq1bt1JaWkqXLl1MP6NCCCGEEB3JSwfwL7/8khUrVvDBBx/Qt29f1q1bR2BgID/88MNT33/dunX87//7/05UVBS9evXi//l//h969erFgQMHXrv41mY0Gls8gGdlZfHnn38CMGHCBPz8/FrkPq2lNQL49evX0ev1eHt7N3s+ekhICKtWraJ79+7U1dURFxfH4cOHMRgMLVanuXl7ezNo0CAAjh071i7O/VpbWzNv3jy8vLwoKytjx44dbXqc2vNUVFRw6tQp1q1bx759+8jJycHa2hqNRsNHH33E0qVLCQsLa9Wu3W5ubgwcOBBoX6vg1dXVbN26lcLCQtzc3FiyZAnOzs6WLksIIYQQwuxe6i/Duro6rl27xoQJE5q8PmHChGaPRDIajZSXl7f4+K6WkJWVRW1tLQ4ODvj6+pr9+tXV1cTFxWE0Gunbt6+pqVJ71tIB/PHma4MHD36prfqurq4sXbqU4cOHAw07DzZv3kxJSUlLlNoiRo8ejZWVFWlpaabjEW2dg4MDCxcuxNnZmUePHvHbb7+1qwcf2dnZ7N27l3Xr1nH69GkqKytxcXFhzJgxrF27lmnTpuHt7W2x+hq/n2/fvk1BQYHF6miu2tpatm3bRl5eHs7OzixZsgQ3NzdLlyWEEEII0SJeKoAXFBRgMBie+OPS29ub3NzcZl3jf/2v/0VlZSVz58595vvU1tZSVlbW5L+2oDHghISEmH1V6/Fz3x4eHkybNq3dnvt+XEsH8LS0NAoLC7G1tSU8PPylP16tVjNu3Djmz5+Pvb09WVlZrF+/3tStuq1zc3MzPahpL6vgAO7u7rz33nvY2NiQkpLS5meEG41GkpKS2Lx5Mxs2bCAxMRGDwUBAQACzZs1i9erVjBw5sk1sme7atSt9+vQB2v4qeH19PTt27CA7OxsHBwcWL17cLh/OCiGEEEI01yulyL8HQ0VRmhUWY2Nj+a//9b+yc+dOunXr9sz3+x//43/g5uZm+i8wMPBVyjS7xwO4ucXHx3P37l2srKyYPXt2uz73/biWDuCNq98DBw58raZ4ffr0YdWqVfj5+VFTU0NsbCzHjh3DaDSaq9QWM2LECOzs7Hj06BE3btywdDnN5ufnx5w5c1CpVCQkJLTJkWrV1dWcO3eOr7/+mri4ODIyMlCr1QwcOJAPPviAFStWMGDAgDY3n3rEiBEAJCYmtpkHmH+n1+vZuXMnGRkZ2NnZsXjx4uf+/wUhhBBCiI7gpQK4l5cXVlZWT6x25+XlvXDL5c6dO1mxYgW//fabaYTSs/yf/+f/SWlpqem/zMzMlymzRVRXV5uaGpn7/PfDhw/566+/gI5x7rtRbW2t6XxvSwTwiooK7ty5A7y4+VpzuLu7s3z5ctOK8vnz59myZQvl5eWvfe2W5OjoaApcJ06cQK/XW7ii5uvVqxdTpkwB4PTp022mOWNeXh4HDhzgyy+/5Pjx45SVleHo6Mibb77JmjVrmDlzJv7+/pYu85kCAgIICgrCaDRy8eJFS5fzBIPBQFxcHA8ePMDGxoaFCxe2yLEeIYQQQoi25qUCuK2tLYMHDzaFxUZ//fWXacbv08TGxrJs2TJ27Nhh+mP7eezs7HB1dW3yn6WlpqaiKApeXl5mPZ/4+Lnvfv36ERUVZbZrW1pjcLWzs2uRkW1arRaj0UhAQAA+Pj5muaa1tTWTJk1i9uzZ2Nrakp6ezvr169v8XOWYmBhcXFwoLS017QpoLwYPHmx6gHDw4EGLnWVXFIV79+6xdetWfvjhB7RaLXq9Hh8fH6ZPn87atWsZPXo0Li4uFqnvZTX+m167do3q6moLV/OfjEYjv//+u2nHz/z589vMLichhBBCiJb20lvQv/jiC3766Sc2bdrE7du3Wbt2LRkZGXz00UdAw+r1kiVLTO8fGxvLkiVL+F//638xdOhQcnNzyc3NpbS01HyfRStoDAXmXP1uPPddWlqKh4cHU6dO7RDnvhu15PZzo9GIVqsFzLP6/Xf9+/dn5cqVeHt7U1lZydatWzl9+nSbPadsY2PDqFGjgIbRfzU1NZYt6CWNGTOG8PBw04zw5vaUMIfa2lri4+P57rvviI2NJSUlBZVKRd++fVm2bBkrV64kIiICa2vrVqvJHHr27ImPjw/19fVcvnzZ0uUADb/zDh48yI0bN1Cr1cydO7dFjvQIIYQQQrRVLx3A582bx7p16/hv/+2/ERERwZkzZzh06BBBQUEA5OTkNJkJvn79evR6PZ988gm+vr6m/1avXm2+z6KFKYrSIgH80qVLplWg9j7v+2kaH7K0RABPTk6mtLQUBwcH+vfvb/brA3h6erJixQo0Gg0Ap06dYvv27VRWVrbI/V5XREQEXl5eVFdXN3sqQVuhUqmYNm0awcHB1NXVsWPHjhZ/SFdUVMSRI0f48ssvOXLkCEVFRdjb2zNs2DA+//xz5s6dS1BQULt9KKZSqUwd0ePj46mrq7NoPYqicPToUXQ6HSqVipkzZ9K7d2+L1iSEEEII0dpeaUnn448/5uOPP37q237++ecm//epU6de5RZtSmFhIaWlpVhZWZkeNLyuhw8fcuzYMQAmTpzYIc8/Nq6At8SW3cZt1i29MmljY8O0adPo3r07f/zxBw8ePGD9+vXMnj2b7t27t9h9X4VarWbs2LHs3LmTixcvEhUV1W62SwNYWVkxb948Nm3aRH5+Ptu3b+f9998364MpRVFITU0lPj6+Sad7Ly8voqOjGTRoELa2tma7n6X169ePEydOUFxcjE6nIyYmxmK1nDx5kvj4eACmTZvWYg/OhBBCCCHaMvPO0uqgGle/u3fvbpY/zqurq9m1axdGo5H+/fu3yBbqtqCltqCXlJRw//59oOH8cGuIiIjgww8/xNPTk/Lycn7++WcuXLjQ5rak9+nTh4CAAPR6fZvsKv4i9vb2LFy4EBcXF/Lz89m5c6dZZoTX19dz7do1/v3vf7N161ZT+O7VqxcLFy7k448/JioqqkOFb2h4KNPYn+PixYsWm7d+7tw5zp49C8DkyZOJiIiwSB1CCCGEEJYmAbwZzLn9XFEU9u3bR1lZGV26dOlw574f19iEzdwB/Nq1a0DDODhPT0+zXvt5unXrxocffsiAAQNQFIW//vqLnTt3tqkGVyqVyjRlQKvVUlBQYOGKXp6bmxsLFizA1taWtLQ09u/f/8oPOkpLSzl27BhfffUVBw8eJC8vDxsbG6Kiovj0009ZsGABoaGhHfZnEBoeHjk5OVFaWsrNmzdb/f7x8fEcP34cgHHjxnWoRpNCCCGEEC9LAvgL6PV60tLSAPME8IsXL3Lv3j3Tue+W6A7eVjSugJuza7zBYDCNqrLEzgE7OztmzpzJ5MmTsbKy4u7du/z4449kZ2e3ei3PEhQURO/evVEUhRMnTli6nFfi4+PD3LlzUalUJCYmcvLkyWZ/rKIoZGRksGvXLr7++mvOnz9PdXU17u7uTJgwgS+++ILJkye36sMbS7K2tmbo0KFAw2i91ty1odPpOHLkCABvvvmm6Uy6EEIIIURn1b7a+lrAw4cPqa+vx8nJ6YWzzl8kMzPTdO777bffNtvorLaqJbag3759m8rKSpydnS3WwEmlUhEVFYW/vz+7du2ipKSETZs2MXHiRIYMGdImVlPHjh3L/fv3uX37Ng8fPiQgIMDSJb20nj17MnXqVPbv38/Zs2dxc3N77pEDvV5PUlIS8fHx5OTkmF4PDg4mJiaG3r17o1Z3zmeOQ4YM4dy5c+Tn53Pv3j369OnT4ve8efMm+/fvB2Do0KGmLv1CCCGEEJ1Z5/xr9CUkJycDDWHgdYJVVVUVcXFxKIrCgAEDWu3ssqXU19ebtmabM4A3Nl+LjIzEysrKbNd9FX5+fqxcuZI+ffpgMBg4dOgQe/bsoba21qJ1QcN2+UGDBgFw7NixNndWvbk0Gg1vvfUWAH/88Yfp7P/jKioqOHXqFOvWrWPfvn3k5ORgZWWFRqPho48+YunSpYSFhXXa8A0NZ+sbd4ycO3euxb8f7t69y969e4GGPg0TJkxoEw+mhBBCCCEsrfP+RdpMKSkpwOttP3/83LenpyfvvPNOh/9jtHH128bGxmzb7PPz80lPT0elUhEZGWmWa74uBwcH5s2bx4QJE1Cr1dy8eZMNGzbw6NEjS5fGqFGjsLKyIj093fQgqT166623iIiIQFEUdu3aZdrun5OTw759+1i3bh2nT5+msrISFxcXxowZwxdffMG0adNee9dKRzJ06FCsrKx4+PBhk1GR5paSkmJqMhkeHs6UKVM6/O87IYQQQojmki3oz1FZWWnayhoSEvLK17lw4QL379/H2tq6w5/7bvT49nNz/fHduPrdu3dvs54rf10qlYphw4bh7+9PXFwchYWF/PTTT0yZMsWi3Z7d3NyIiYnhwoULHDt2jJ49e7bLVWCVSsU777xDWVkZKSkpbN26lS5dujQ5dx8QEEBMTAx9+/a1+M6ItsrZ2ZmIiAiuXbvGuXPnzDZS8XEZGRn8+uuvGAwGwsLCmD59uoRvIYQQQojHtL+/xltR4+q3j48Pzs7Or3SNjIwMUwfgt99+u9OsyJn7/HddXR3Xr18HLNN8rTm6d+/OqlWr6NmzJ3q9nt9//53ff/+d+vp6i9U0YsQI7O3tycvL48aNGxar43XV1dXRvXt31Go1NTU1ZGdno1arGThwIB988AErVqxgwIABEr5f4I033kClUpGcnExubq5Zr52dnc2OHTuor68nNDSUWbNmtcsHPkIIIYQQLUn+OnqOxvFjr7r6/fi574EDB7aZbdOtwdwd0G/evEltbS0eHh5m6UbfUpycnFi4cCGjR49GpVKRkJDATz/9RGFhoUXqcXBwYMSIEQCcPHkSvV5vkTpeVX5+PgcPHuTLL7/k1KlTGI1G04qqr68v06ZNw9/f38JVth9dunShf//+QENHdHPJy8tj27Zt1NbWEhQUxNy5c7G2lg1WQgghhBB/JwH8GRRFea3534qisHfvXsrLyzvNue/HNQZwFxcXs1yvcfb34MGD2/y/o0ql4s0332Tx4sU4OTmRl5fHjz/+SFJSkkXqiY6OxsXFhdLSUq5cuWKRGl6Goijcu3ePrVu38v3333Pt2jX0ej3e3t5MmzaNFStWYGdnR1ZWFr///nu7bTBnKY2jwJKSkiguLn7t6xUWFrJlyxaqq6vx9/fnvffew8bG5rWvK4QQQgjREUkAf4a8vDwqKiqwtrame/fuL/3x58+fJzk52XTu29bWtgWqbLvMuQU9Ozub7OxsrKysLHqm+mX16NGDVatWERQURF1dHXFxcRw6dKjVV6FtbGwYPXo0AGfPnqWmpqZV799ctbW1xMfH89133xEbG0tKSgoqlYqwsDCWLVvGqlWr0Gg0+Pv7M3fuXFPTu8bRfqJ5fHx8CA0NRVEULly48FrXKikpYcuWLVRWVuLt7c3ChQs7RY8LIYQQQohXJQH8GRpXv4ODg196K2V6ejonTpwAYNKkSZ3m3PfjzBnAG5uv9evXDycnp9e+XmtycXFhyZIlplXHK1eusHnzZkpKSlq1jkGDBtG1a1eqq6vNuvXYHIqKijhy5AhffvklR44coaioCHt7e4YNG8bnn3/OvHnzCAoKarLzISQkhGnTpgENTQ7bw8p+W9J4LEGn01FRUfFK1ygvL2fLli2m6Q6LFy/GwcHBnGUKIYQQQnQ4EsCf4VW3n1dWVrJ7924URSE8PByNRtMS5bV55grgNTU1puZhbbX52ouo1WrGjRvHe++9h729PdnZ2axfv5579+61ag1jx44F4NKlS6avj6UoikJKSgqxsbF8++23xMfHU1dXh5eXF5MnT2bt2rVMmDABd3f3Z15j0KBBppX9w4cPc/fu3Vaqvv3r3r07AQEBGAwG4uPjX/rjq6qq2Lp1K8XFxbi7u7NkyZJ293BMCCGEEMISJIA/RX19Penp6cDLBfDHz317eXl12vm3er2eqqoq4PUD+PXr19Hr9XTr1o3AwEBzlGcxvXv3ZtWqVfj7+1NTU0NsbCx//fUXRqOx1e4fGBiIXq/n9OnTrXLPv6uvr+fatWv8+9//ZuvWraaHEKGhoSxcuJCPP/6YqKioZh/ZGDlyJBqNBkVRiIuLIysrqyXL7zBUKpVpFfzKlSsvdSyhpqaGrVu3kp+fb9rhYa5pB0IIIYQQHZ0E8KdIT0/HYDDg6uqKl5dXsz/u3LlzPHjwoNOe+27UuLpqbW39WltSFUUxbT9vD83XmsPd3Z3ly5cTHR0NNGyf/uWXX1plRVqlUjFu3DigYetxQUFBi9+zUVlZGceOHeOrr77i4MGD5OXlYWNjQ1RUFJ988gkLFy4kNDT0pb/GjTPCQ0ND0ev1xMbGmqWxWGfQu3dvunbtSm1trenn7EXq6urYsWMHubm5ODo6smTJEjw8PFq4UiGEEEKIjkMC+FM8vv28uYEgLS2NkydPAjB58mS6devWYvW1dY9vP3+d0Jyenk5BQQE2NjYMGjTIXOVZnJWVFZMmTTI9pMnIyGD9+vWmufMtqXv37vTp0wdFUUzz6VuKoihkZmYSFxfHunXrOH/+PNXV1bi7uzNhwgS++OILJk+e/FIPuZ5GrVYze/ZsfHx8qKysZPv27aYdGOLZVCqVqTfBpUuXXtgcUK/X8+uvv5KZmYm9vT1Llix57a+dEEIIIURnIwH8KV72/Pfj574HDRrUac99NzLX+e/GVbmBAwd2yM7K/fr1Y+XKlXh7e5vO1DbOum5JY8aMQaVScefOHTIzM81+fYPBQGJiIj/99BObNm0iKSkJRVEIDg5m3rx5fPbZZwwbNgx7e3uz3dPOzo4FCxbg5uZGYWEhv/76K/X19Wa7fkc1YMAAXF1dqaysJCEh4ZnvZzAY+O2330hNTcXW1pZFixZ1yuaSQgghhBCvSwL435SVlZGfnw80dFp+EaPRyJ49e6ioqKBr165Mnjy5pUts88wRwCsqKrh9+zbQfpuvNYenpycrVqwwPbQ5ffo027dvp7KyssXu2a1bN9OOgmPHjpltjnZFRQWnT59m3bp17N27t8nouFWrVrF06VLCwsJQq1vm146LiwsLFy7E3t6ezMxM9u3bJzPCX8DKyoo33ngDaDgO8bSHP42/4+7fv4+1tTULFizA39+/tUsVQgghhOgQJID/TePqt7+/f7POL587d46UlBRsbGw69bnvx5kjgOt0OoxGI/7+/vj6+pqrtDbJxsaGadOm8e6772JjY0NKSgrr168nIyOjxe45atQorK2tycjI4P79+691rZycHPbt28e6des4deoUFRUVuLi4MHr0aNauXcv06dPx8fExU+XP17VrV+bNm4eVlRW3bt3izz//bJX7tmcajQYHBweKi4u5detWk7cpisL+/fu5desWarXaNBJOCCGEEEK8Ggngf9N4Drc5289TU1M5deoU0HDuu2vXri1ZWrvxugHcaDRy7do1oGOvfv/doEGD+OCDD/Dy8qK8vJyff/6Z8+fPt8gqrpubm6kR3LFjx15627vRaOTWrVts3ryZH3/8kevXr2MwGPD392fWrFmsXr2aN9980yKjqYKDg5k+fTrQcLb5VcZsdSa2trbExMQANPl+UxSFQ4cOcf36dVQqFbNnzyY0NNSSpQohhBBCtHvWli6gLVEUpdnnvysqKtizZw+KohAREUFEREQrVNg+vG4Af/DgAaWlpdjb29O/f39zltbmdevWjQ8//JCDBw9y48YNjh07RkZGBu++++5rdZR/mhEjRqDVasnPzycxMbFZ38PV1dVotVquXLlCaWkp0NAErX///kRHRxMQEGDWGl/VwIEDKS0t5fjx4xw5cgRXV1f69u1r6bLarKioKM6fP09ubi4PHjygZ8+eHDt2zNSH4d1335V/PyGEEEIIM5AV8Mfk5ORQXV2Nra3tc884yrnv53vdAN74R39ERAQ2NjZmq6u9sLW1ZcaMGUyZMgUrKyvu3bvHjz/+aPYZ1w4ODqZZ0CdPnnxu07L8/HwOHjzIV199xbFjxygtLcXR0ZGRI0eyZs0aZs6c2WbCd6Phw4ebdlDs2bOnRRrOdRSOjo4MHjwYaFgFP3PmDBcuXADgnXfeITw83JLlCSGEEEJ0GJ0ugP/www+Eh4fj6uqKq6srw4YN4/Dhw8B/nv8OCQnBysrqmdc4e/YsqamppnPfnTEkPovBYDA1EHuVAF5SUsK9e/cATIGgM1KpVAwZMoQVK1bg4eFBSUkJmzdv5vLly2bdkh4dHY2rqytlZWVcuXKlydsUReHevXts3bqV77//nmvXrlFfX4+3tzfTpk1j7dq1jBkzBhcXF7PVY04qlYpJkybRu3dv04zwwsJCS5fVZg0bNgy1Wk1aWprpaM3EiRM79c+hEEIIIYS5dboAHhAQwP/7//6/XL16latXrzJmzBimT59OUlJSkwD+LI+f+54yZYqc+/6b8vJyoKG7sqOj40t/vFarBaBHjx4yYxjw9fVl5cqVhIWFYTAYOHz4MLt376a2ttYs17exsWHUqFFAw4Ol6upqamtriY+P57vvviM2NpaUlBRUKhVhYWEsXbqUVatWodFosLZu+ydY1Go1s2bNws/Pj+rq6hbvMN+eubq6Ntn5M3r0aIYOHWrBioQQQgghOp62/xe0mU2dOrXJ//3f//t/54cffuDs2bOm8WPPajRUUVHB7t27gYbOwY2jnMR/ajwX7OrqikqleqmPNRgMpgDemZqvvYi9vT1z587l0qVLHDt2jKSkJHJzc5kzZ45ZZjEPGjSIixcvkp+fz9atWykqKjIFfDs7OyIjI4mOjsbd3f2172UJtra2vPfee2zcuJHi4mJiY2NZunSp7Fz5m8TExCbb9MPCwixYjRBCCCFEx9TpVsAfZzAY+PXXX6msrCQwMBCj0YiHhwceHh5PvK/RaGT37t1UVlbSrVs3Jk2aZIGK277XOf99584dKisrcXZ2pk+fPuYurV1TqVQMGzaMZcuW4erqSmFhIT/99BM6ne61rqsoCunp6abxeTk5OdTW1uLp6cnkyZP54osvmDBhQrsN342cnZ1ZuHAhDg4OZGVlsWfPnpfu/N6R3b59m3379gGYfv9dvHjRghUJIYQQQnRMnTKA37hxA2dnZ+zs7Pjoo4/Yu3evabX2Wd3Pz5w5Q1pampz7foHXCeCNzdc0Gs1zz+B3ZoGBgaxatYrQ0FD0ej379+/n999/f24Dtaepr69Hq9Xy73//my1btjRp8NazZ08++eQToqKiOtRcey8vL+bPn4+VlRV37tzh6NGjLTLirb1JTk4mLi7ONNFh5syZQMOKeOOOFiGEEEIIYR6dMoD36dOHhIQELl26xD/+8Q+WLl3KuXPngKcH8JSUFE6fPg00dASWs8nP1hjAX7YxV0FBAWlpaahUKmn69AKOjo4sWLCA0aNHo1KpSEhI4KeffqKgoOCFH1tWVsbx48f56quvOHDgAHl5edjY2DBkyBBT8EpJSWnWtdqj7t27M2PGDAAuX77MpUuXLFyRZaWlpbFz506MRiP9+/dn6tSpBAQE0KNHD4xGo6yCCyGEEEKYWac7Aw4NZ0Ibz3kPGTKEixcv8ueffzJ9+nR69OjR5H3Ly8vZs2cPAJGRkTKO5wUam7C5ubm91Mc1rn736tXrpT+2M1KpVLz55psEBgaye/du8vLy2LBhA1OnTmXAgAFN3ldRFB4+fEh8fDy3bt0yrfq6u7sTHR2NRqPB3t4egFu3bnHnzh2OHz/O/PnzW/3zag39+/entLSUv/76iz///BNXV9dON28e4OHDh8TGxqLX6+nduzczZsxArW54Jjt8+HBSU1PRarW8+eabr9RQUQghhBBCPKlTBvC/q6ysRK/XExAQgJ2dnen1xnnflZWVeHt78/bbb1uwyvbhVbag19fXc/36dUCar72sHj16sGrVKnbv3k16errpf06cOBGVSkVSUhLx8fFkZ2ebPiY4OJiYmBh69+5tClyNxowZw927d7l79y4ZGRl07969tT+lVjFs2DBKS0u5fPkye/fuxcXFpcN+rk+Tm5vL9u3bqauro0ePHsyZM6fJsY+QkBB8fX3Jycnh8uXLpk75QgghhBDi9XS6Lej//Oc/OXv2LGlpady4cYP/8l/+C9euXSM8PPyJ7eenT58mLS0NW1tbOffdTI93QW+umzdvUlNTg7u7+zPP4Itnc3FxYcmSJYwYMQJo2E3wzTff8OWXX7J3716ys7OxsrIiIiKCVatWsXTpUsLCwp4I3wBdu3YlIiICgGPHjnXYM9IqlYqJEyeaxrvFxsZ22G33f1dQUMDWrVupqakhMDCQ+fPnPzFSTqVSMXz4cKBhq35dXZ0lShVCCCGE6HA6XQB/9OgRixcvpk+fPowdO5b4+HiWL19Oz549m4S/Bw8ecObMGaDh3Lenp6elSm43DAYDFRUVwMsF8GvXrgEwePDgp4ZC8WJqtZp+/fqZjlCUl5dTVVWFg4MDo0ePZu3atUyfPh0fH58XXmvUqFFYW1uTmZnJvXv3Wrp0i1Gr1cycOZOAgABqamrYvn276fu3oyouLmbLli1UVVXh6+vLggULntlor2/fvnTp0oXq6mrTeEAhhBBCCPF6Ol3a2bhxI2lpadTW1pKXl8fmzZvp3r07Dg4O+Pr6Ak3PfQ8ePJiBAwdasuR2ozG8qNVqnJycmvUxOTk5ZGVloVar0Wg0LVleh2Q0Grl16xabN2/mxx9/JDU1FcC0W6O6upra2lrTGe/mcHV1JSYmBoDjx4936HFdNjY2zJ8/Hw8PD0pKSoiNje2wq71lZWVs2bKF8vJyunbtyqJFi577faFWq3njjTeAhpFkBoOhtUoVQgghhOiwOl0A/7vk5GSg4cyjWq02zfuuqqqSc98v6fEO6I1j3V7kypUrAPTr16/ZoV00BOvz58/zzTffsGvXLjIyMlCr1QwYMIAVK1bwH//xH6YQfeHCBbZs2WL6+jTHiBEjsLe3Jz8/33Q+v6NycnJi4cKFODo6kp2dze7duzvcQ4eKigq2bNlCSUkJXbp0YfHixc1qrDZo0CCcnZ0pKyvjxo0brVCpEEIIIUTH1ukDeEpKCvCf48dOnTpFenq66dz3389GimdrDHjN7WJeU1PDzZs3AWm+1lz5+fkcPHiQr776imPHjlFaWoqjoyMjR45k9erVzJo1i4CAAKysrHj77beZM2cOdnZ2ZGRksH79eh48eNCs+9jb2zNy5EgATp48+dJzxtsbT09P01noe/fucfjw4Q5z/r26uppt27ZRWFiIm5sbS5YsafaYQGtra4YOHQrA+fPnO8y/iRBCCCGEpXTqAF5dXU1WVhbQEMCTk5M5e/YsAFOnTpVz3y/pZTugJyYmUl9fT9euXTtVB+qXpSgK9+7dY9u2bXz//fdcu3aN+vp6vL29mTZtGmvXrmXMmDFP/Xfv168fK1euxMfHh6qqKrZt28apU6eatcIbHR2Nq6sr5eXlXL58uSU+tTYlMDDQNAv96tWrnD9/3sIVvb7a2lq2b9/Oo0ePcHZ2ZvHixS895m/IkCHY29tTUFDA3bt3W6hSIYQQQojOoVMH8NTUVBRFoWvXrgDs3bsXaPiD8++zlMWLPb4F/UUURTHN/h48eHCzt6x3JrW1tcTHx/Pdd98RGxvLgwcPUKlUhIWFsXTpUlatWoVGo3nhLo0uXbrw/vvvExkZCTR099++fTuVlZXP/Thra2tGjx4NwLlz56iurjbPJ9aG9e3b13Ts5Pjx4+1623V9fT2xsbFkZWXh4ODA4sWLX+mhop2dHVFRUUDD94GsggshhBBCvLpOHcAbt+OGhISYzn37+PgwceJEC1fWPr3MCnhGRgb5+fnY2NgwaNCgli6tXSkuLubIkSN89dVXHDlyhKKiIuzs7Bg2bBifffYZ8+bNIzg4+KUeWtjY2DB16lRmzJiBjY0NKSkp/Pvf/yY9Pf25HxceHk63bt2oqanh3Llzr/uptQsxMTGmbde///47aWlpli3oFej1enbu3El6ejp2dnYsWrSIbt26vfL1YmJisLa2Jisr64XfM0IIIYQQ4tk6bQBXFMUUwMvLy8nIyJBz36/pZQJ44+r3gAEDXqpDd0elKAqpqan8+uuvfPPNN8THx1NbW4unpyeTJ0/miy++YMKECXh4eLzWfcLDw/nwww/x8vKioqKCX3755blne9VqNWPHjgUgPj7eNOe9o5swYQL9+vXDYDCwc+dO8vPzLV1SsxkMBnbv3s2DBw+wsbFhwYIF+Pn5vdY1nZycTFMKOsuDGCGEEEKIltApA7jBYODw4cOUlpaiUqm4desWANOmTaNLly4Wrq79am4Ar6ysNP2bd/bma/X19Wi1Wv7973+zZcsW0xnb0NBQFi5cyCeffEJUVNQzZzW/iq5du/Lhhx8ycOBAFEXh2LFj/Prrr8/cYt6rVy+CgoIwGAycOnXKbHW0ZSqVihkzZhAYGGiaEV5eXm7psl7IaDTy+++/c+fOHaysrJg/f77Z+isMGzYMlUrFgwcPyMnJMcs1hRBCCCE6m04XwPfs2UNwcDD/7b/9N6BhqyY0nJPt37+/JUtr14xGoymgvCiA63Q6jEYjfn5+r70y116VlZVx/PhxvvrqKw4cOEBeXh42NjYMGTKETz75hIULFxIaGtpiZ+NtbW2ZMWMG77zzDlZWVty7d4/169ebmhI+TqVSMW7cOACuX79OXl5ei9TU1lhbWzN//nw8PT0pLS1lx44d1NbWWrqsZ1IUhT/++IMbN26gVquZM2cOISEhZru+h4eHqTdGR2hQJ4QQQghhCZ0qgO/Zs4fZs2fz8OFD09gxKysrsrOz+eKLL9izZ4+FK2y/KioqUBQFlUqFs7PzM99PURSuXbsGdL7Vb0VRyMzMJC4ujnXr1pkam7m7uzN+/Hi++OILpkyZgpeXV6vUo1KpGDx4MCtWrMDDw4PS0lI2bdpEfHz8E1vSAwIC6Nu3L4qicOLEiVapry1wdHQ0zQjPzc0lLi6uTc4IVxSFo0ePotVqTav3ffr0Mft9hg8fDsCtW7coLCw0+/WFEEIIITq6ThPADQYDq1evRlEUbG1tCQ0NBRo6Te/atQuDwcCaNWswGAwWrrR9erwDulr97G+rBw8eUFJSgr29fafpNG8wGEhMTOSnn35i06ZNJCUloSgKQUFBzJ07l88++4w33njDYmfhfX19WblyJX379sVoNHLkyBHi4uKeWO0dM2YMKpWKu3fvkpGRYZFaLcHDw4MFCxZgbW1NcnIyBw8ebHOdwE+dOkV8fDzQMEKxpX62vL296dWrF4qicOHChRa5hxBCCCFER9ZpAvjZs2d5+PAhALNmzTKFxNraWgYOHIibmxuZmZmmOeDi5TT3/Hdj87VBgwZhY2PT4nVZUmVlJadPn2bdunXs3buX7OxsrKysiIiIYNWqVSxbtoy+ffs+94FFa7G3t2fOnDlMnDgRtVrNrVu3+PHHH8nNzTW9j5eXl6kR17Fjx9pcCG1J/v7+zJ49G5VKhU6na1O/J86dO8eZM2cAmDRpkulr1FJGjBgBNBxHaA/n4oUQQggh2pJO0+778aZBzs7Opu3Srq6ujBkzhjFjxlBeXk5CQgJ+fn4EBwebtfFVR9ecAF5aWsq9e/eAhtnfHVVOTg6XL1/mxo0bph0Vzs7OREVFMXjwYJycnCxc4dOpVCqGDh1KQEAAu3btoqioiI0bN5pCnUqlYtSoUSQmJpKZmcndu3cJCwuzdNmtpk+fPkyaNIlDhw5x8uRJ3NzcLD5C7/Llyxw/fhyAsWPHEh0d3eL37N69O4GBgWRmZnLp0iXGjx/f4vcUQgghhOgoOk0A9/X1Nf3vGzZswMPDg0GDBjFw4EC6dOmCSqXCxcWF0tJSYmNjUalUBAUF0bNnT0JDQ/H29m6xhlgdQXMCuFarRVEUgoOD6dq1a2uV1iqMRiN37twhPj6+yfZsf39/YmJi6NevH1ZWVhassPkCAgJYtWoVe/fuJTk5mQMHDpCRkcHkyZNxcXFh6NChnDt3juPHj9O7d+82sYLfWqKioigpKeHChQvs378fFxcXszY6exkJCQkcPnwYgJEjR5pWplvDiBEjiI2N5erVq4wcOVJGCQohhBBCNFOnCeAjR44kICCArKwsFEWhuLiYU6dOcerUKdzc3IiKimLIkCGmPyQVRSEtLY20tDSOHz+Ok5MTPXv2NP3XVlcxLeVFAdxgMKDVaoGO1XyturoarVbLlStXTDOy1Wo1/fr1IyYmhoCAAAtX+GocHR1ZsGAB586d4+TJk1y/fp3s7Gzmzp3L8OHDuXbtGgUFBSQkJBAZGWnpclvVuHHjKCsr4+bNm/z2228sX74cb2/vVq0hKSmJ/fv3AxATE8Po0aNb9f69evWiW7du5OXlceXKFUaOHNmq9xdCCCGEaK9USjs4yFlWVoabmxulpaUvPGP8PI1d0IEm51cbV7Z37drFoEGD0Gq13L1797ndjn19fU1hPDAwsN2sbraUTZs2kZmZyezZs586zu3WrVvs2rULJycn1q5d2+7/vfLz84mPjycxMZH6+nqgIbQOHjyYIUOGvNb3aVuTlpbG7t27qaiowMbGhqlTp1JRUcGff/6Ji4sLn332WYc/z/93er2ebdu2kZ6ejqurKytWrGi1r/m9e/fYuXMnRqORyMhI3nnnHYvszklMTGTv3r04OTmxevXqTvc9IIQQQoiOz1w59HGdKoBDQwhfvXq1qSEbQGBgIOvWrWPmzJmm1yorK7l+/TparbbJuB0rK6snOqXb2trSo0cPUyDv0qXLa9XYHq1bt47S0lLef/99AgMDn3j7li1bSE1NZcSIEYwdO9YCFb4+RVFITk4mPj6eBw8emF739vYmJiaGAQMGdNgQUlFRwe7du0lLSwMgMjKS5ORkysrKGDt2bKtuf24rqqur2bRpEwUFBXh7e7N8+XLs7Oxa9J4pKSns2LEDg8HAwIEDeffddy12BMBoNPLtt99SUlLC5MmTiYqKskgdQgghhBAtRQK4mT5xg8HA2bNnycnJwdfXl5EjRz5zRbZxdrNWqyUpKQm9Xg80bDN2cXGhpqbmiXFNHh4eprPjwcHBLf5HuaUpisL//X//3xiNRtasWYObm1uTtxcWFvLdd98BsHr1atzd3S1Q5aurra3l+vXrXL58ucnDmLCwMGJiYggKCuoU/QGMRiOnTp0ydQB3d3enpKQEOzs7Vq9ejYODg4UrbH0lJSVs3LiRiooKQkJCWLBgQYvt7sjIyGDbtm3U19cTFhbGnDlzLH7+/vLlyxw+fBh3d3c+++wzi9cjhBBCCGFOLRHAO80Z8MdZWVkxatSoZr2vSqWie/fudO/enbfffpubN2+i1WrJyckxnfl1dnama9eu1NXVkZOTQ3FxMVevXuXq1auo1WoCAwNNgdzHx6fDhbWKigqMRiMqlQpnZ+cn3t44eqxXr17tKnwXFxdz+fJldDqd6SGLnZ0dGo2G6OhoPDw8LFxh61Kr1YwZM4bAwED27t1LSUkJKpWK2tpazp49y4QJEyxdYqtzd3dnwYIFbN68mZSUFA4ePMi0adPM/jOenZ3Njh07qK+vp2fPnk1GKVqSRqPh9OnTlJSUkJSUxMCBAy1dkhBCCCFEm9YpA/irsre3Z8iQIQwZMoScnBx0Oh2JiYlUVFRQUVGBSqUiJCQEHx8fqqurSU1Npbi4mPT0dNLT0zlx4gROTk6EhISYtqs/LbC2N40N2JydnZ9Y/auvrychIQFoH83XGpvvxcfHc/fuXdPrnp6eREdHExER0enH0/Xq1YtVq1YRFxdnOspx6dIlhgwZ0imPX/j6+jJnzhxiY2NJSEjAzc2t2Q/4miMvL49t27ZRW1tLUFAQ8+bNw9q6bfzqtrGxISYmhpMnT3L+/HkGDBjQ4R4wCiGEEEKYU9v4K64d8vX1xdfXl/Hjx3P79m20Wi3p6ek8ePCABw8e4OTkREREBCEhIRQUFPDgwQNSU1OprKzkxo0b3LhxAwAfHx9TGO/evXu7bE72vA7oSUlJ1NTU4ObmRmhoaGuX1mz19fXcuHGDy5cv8+jRI9PrPXv2JCYmhtDQUAkWj3Fzc2PZsmX89ddfxMfHoygKmzZtYuXKlR2qAV1z9erViylTpnDw4EFOnz6Nm5sbGo3mta9bWFjI1q1bqa6uxt/fn/fee6/N9RmIiori/PnzPHr0iOTkZHr16mXpkoQQQggh2iwJ4K/JxsaG8PBwwsPDKSwsRKfTkZCQQGVlJefPn+f8+fMEBQURGRnJjBkzyM3NJTk5mQcPHpCbm2v67/z589jY2DzRzK09hL7nBfBr164BMHjw4DaxZfbvysrKuHLlCteuXaO6uhpo+JoOGjSImJgYvLy8LFxh22VlZcXbb7+Ni4sLx44do7Kykh9++IHZs2fTs2dPS5fX6gYPHkxpaSlnz57lwIEDuLi4vNZDp5KSErZs2UJFRQXe3t4sXLiwTfaTcHBwYPDgwVy8eJFz585JABdCCCGEeA4J4Gbk6enJuHHjGD16NPfv30er1ZKcnGzagm5nZ0d4eDiRkZGMGzeOiooKUlJSTKvmlZWV3Lt3j3v37gEN50sbz4736NGjTf7xDc8O4Lm5uTx8+BC1Wm2W1UBzevjwIZcuXeL27dumcXNubm5ER0ej0Wg6ZUOxVzV8+HDS0tJITk6mpqaGbdu28eabb/LWW2+1yYcuLWn06NGUlpaSmJjIrl27WL58OT4+Pi99nfLycrZu3UpZWRmenp4sWrSoTX9PDhs2jMuXL5ORkUFGRgbdu3e3dElCCCGEEG2SBPAWYGVlRVhYGGFhYZSVlZGQkIBOp6OkpIQrV65w5coVfH19iYyMZMCAAYSHh6MoCrm5uaYwnpGRQUlJCdeuXePatWuo1WoCAgJMgdzX17fNrI6Xl5cDTwbwK1euANC3b982cdbdYDCQlJTE5cuXycrKMr0eFBRETEwMffr06XSB0VzefvttU6d7gDNnzpCZmcnMmTPbxNe+tahUKqZNm0ZZWRlpaWls376dDz744InJAM9TVVXF1q1bKSoqwt3dnSVLlrT5f0MXFxfCw8PR6XScP39eArgQQgghxDN0yjFklqAoCqmpqWi1Wu7cuWOaJW5tbU3//v2JjIwkMDDQFKrr6upITU01BfKioqIm13N0dGzSzM3FxaXVP6dGmzdvZvv27eTm5pKeno6DgwNDhw6lZ8+euLu7s3TpUoKDgy1WX2VlpakrfUVFBdDwkGTgwIHExMS80gqleNLBgwe5du0aXbp0oby8nPr6epydnZk9ezZBQUGWLq9V1dTUsGnTJvLz8+natSvvv/8+9vb2zfq4LVu2kJOTg4uLC8uXL2833fYfHzf4j3/8g27dulm4IiGEEEKI1yNzwNtxAH9cVVUViYmJaLVa8vPzTa97enoSGRnJoEGDcHJyavIxxcXFprPjqamp1NXVNXm7t7d3k2Zurdkl+euvv+bbb7/lH//4B2+//TZ6vZ5PPvmEmzdv8n/9X/8Xa9eutchqfW5uLvHx8dy4ccP0wMPZ2ZmoqCgGDx78xL+xeD3l5eV8++231NfX8/bbb3Pt2jXy8/NRqVSMGTOG4cOHt5ldG62htLSUjRs3Ul5eTnBwMIsWLXpuk8W6ujq2bdtGZmYmjo6OLF++vN31INi1axe3bt0iPDycGTNmWLocIYQQQojXIgG8gwTwRoqikJWVhVar5ebNm9TX1wMN85b79OlDZGQkISEhT2yLNhgMPHz40BTIc3JymrzdxsaG4OBgUyD39PRsseCjKAr//b//dwwGA6tXr8bd3R1FUfif//N/8h//8R98//33/OMf/2iRez+N0Wjk7t27xMfHk56ebnrd39+fmJgY+vXr1y47zbcXJ06c4OzZs3h6evLBBx9w+PBhEhMTgYZO4e+++y6Ojo4WrrL15ObmsnnzZurq6ggPD+fdd9996s+iXq9nx44dpKamYm9vz9KlS9vlzozs7Gw2bNiASqXi888/x93d3dIlCSGEEEK8spbIoXIG3IJUKhUBAQEEBAQwceJEkpKS0Ol0PHz4kNu3b3P79m1cXV2JiIhAo9GY/pi1srIiKCiIoKAgxo4dS2VlZZNmbhUVFdy/f5/79+8DDc3FHm/m1pytsM1VVVVlWl1u3AafmZlpmg8dHR1ttns9T3V1NTqdjsuXL1NaWgo0PMjo168fMTExBAQEtEodnd3w4cO5evUqhYWFJCUl8e677xIUFMShQ4e4f/8+P/74I7Nnz+40Xw8fHx/mzp3Ljh07SExMxNXVlbFjxzZ5H4PBwK5du0hNTcXW1paFCxe2y/AN4OfnR0hICCkpKVy8eJFJkyZZuiQhhBBCiDZFVsDboLy8PLRaLYmJiabRWNAwk1qj0RAWFvbMVVxFUXj06FGTZm6NARn+M/Q/3sztdRqP5eTk8OOPP+Lk5MT/9r/9bwDs3r2bf/7zn1hZWXHr1q1XvnZzFBQUEB8fz/Xr1007CBrHIkVFRXWK75e25tKlSxw9ehRnZ2c+//xzbGxsyM3NZdeuXRQVFaFWq5kwYQLR0dGdZku6Tqdj//79ALzzzjsMHjwYaNixsWfPHpKSkrC2tmbhwoUW7ZdgDqmpqWzZsgVra2vWrFkjRz2EEEII0W7JFvROEsAb6fV67ty5g06nIyUlxfS6o6OjaZxZ165dn3uNuro60tLSTIG8sLCwydsdHBxMzdxCQ0Nfupnb3bt3+fXXX/Hz8+PDDz+kqqqK0aNHc/fuXf766y+ioqJe6nrNoSgKycnJxMfH8+DBA9Pr3bp1IyYmhoEDB2JjY2P2+4rm0ev1/Otf/6KkpIQxY8YwcuRIoKHB2P79+7l9+zYA/fr1Y+rUqWbdkdGWnTp1itOnT6NSqXjvvfcIDQ1l//79JCQkoFarmT9/foeYoa0oCj/99BPZ2dm8+eabjB492tIlCSGEEEK8EgngnSyAP664uBidTkdCQoJp7BdAYGAgGo2G/v37Y2tr+8LrlJSUNGnmVltb2+Tt3bp1M50dDwoKemEztytXrnDo0CHCwsKYN28es2fP5q+//uI//uM/+Oc///lqn+wz1NXVkZCQwOXLl5s8SAgLCyMmJoagoKBOs6La1iUmJrJ3717s7Oz4/PPPTee+FUXh8uXL/PnnnxiNRrp06cKcOXPa7Zbrl6EoiilwW1tb07t3b27duoVKpWLOnDn07dvX0iWaze3bt/ntt9+wt7dnzZo12NnZWbokIYQQQoiXJgG8EwfwRkajkeTkZHQ6HXfv3qXxy2dra8uAAQOIjIzEz8+vWUHUYDCQlZVlCuTZ2dlN3m5tbd2kmZuXl9cT1z127Bjnz59nyJAhHDp0iO3bt7NkyRKWLVtGZGSkWT7n4uJiLl++jE6nMz0wsLOzQ6PREB0d3W7GNHUmiqKwfv16Hj16xNChQ5k4cWKTtz98+JC4uDhKS0uxsrJi8uTJaDSaDv8AxWAwsH37dlJTU02vzZgxg/DwcAtWZX6KovCvf/2LwsJCJkyYwLBhwyxdkhBCCCHES5MALgG8ifLycq5fv45Op2syJ9zb2xuNRkN4eDgODg7Nvl5VVZWpmVtycrJpZnYjNzc3QkJCCA0NJSQkBHt7e/bu3UtiYiIJCQkcP36cWbNm4efnx6pVq7C1tcXNze2lamikKAppaWnEx8dz9+5d0+uenp5ER0cTERHRrBV/YTnJycls374dKysrPv300yc6YldVVbFv3z5Ts8Dw8HCmTJnS4b+uJ0+e5MyZM0DDWLyPP/74lX5G2rrGc+8uLi58/vnnrToaUQghhBDCHCSASwB/KkVRSE9PR6fTcevWLfR6PdDQLb1fv35oNBqCg4NfanVRURTy8vJMZ8fT09OfaObm7+9PRUUFJSUl/Nf/+l+fep3NmzezbNmyZt+3vr6eGzducPnyZR49emR6vWfPnsTExBAaGtrhV0k7CkVR2Lp1K6mpqQwaNIh33333qe9z/vx5Tpw4gaIodO3alTlz5rywt0F71digDhp2cdTW1hIUFMSiRYs6XEDV6/V88803lJeXM3XqVLPtiBFCCCGEaC0SwCWAv1B1dTU3btxAq9U2CbAeHh5oNBoiIiJeutEaNATjx5u5FRQUNHm7jY2NqQv54sWLCQkJeanrl5WVceXKFa5du2bq/G5jY8OgQYOIjo7usIGso8vKyuKnn34C4KOPPsLb2/up75eWlsbu3bupqKjAxsaGqVOnMnDgwNYstcVdu3aNgwcPAjBq1CjCwsLYvHkztbW19O/fn1mzZnW4h0sXL17kzz//xNPTk48//vi1Ji4IIYQQQrQ2CeASwJtNURRycnLQarXcuHGDuro6oGHlunfv3mg0Gnr16vXKfxCXlpaSnJzMH3/8wdO+hbp27dqkmduzupI/fPiQ+Ph4bt26hdFoBBq2ukdHR6PRaDrk1tzOJi4ujqSkJHr16sWCBQue+X4VFRXs2bPHdD568ODBvP322x1iZbixKR3AG2+8wbhx41CpVKSmprJt2zaMRiNvvPEG48ePt3Cl5lVbW8u6deuoqalhzpw59OvXz9IlCSGEEEI0mwRwCeCvpK6ujlu3bqHT6cjIyDC97uzsTEREBBqNhi5durz0dauqqvif//N/Ag3jzKqrq+nSpQvFxcVNQrm1tTVBQUGmQN6lSxdu375NfHw8WVlZpvcLCgoiJiaGPn36yEpZB1JYWMj333+P0Whk6dKlz51zbTQaOX36tOmMtK+vL3PmzGnXjfZu377Nrl27UBSFIUOGMHny5CYr3devX2ffvn0ATJo0iejoaAtV2jIaz7z7+fnxwQcfdLhVfiGEEEJ0XBLAJYC/toKCArRaLdevX6eqqsr0eo8ePdBoNPTt27fZK465ubmsX78eW1tb6urqcHR0ZO3atdTX15OSkmLqrv742DRoWIVv/LZTq9WEh4cTExPTKUZRdVZ//PEHV69exd/fnxUrVrwwhCUnJ7Nnzx6qq6uxs7Nj+vTp7XJMV3JyMrGxsRiNRgYNGsT06dOf+rmfOXOGkydPolKpmDdvHn369LFAtS2jsrKSdevWodfrX+l4ihBCCCGEpUgAlwBuNgaDgbt376LT6UhOTja9bm9vT3h4OJGRkc88r9vo3r17xMbGmgL48OHDGTduXJP3URSF27dvc/78+SfGnEFDGPfz86Nnz56Ehobi7+8vq98dUEVFBd988w319fXN3opcWlrK7t27yczMBGDo0KGMGzcOKyurli7XLNLS0ti+fTt6vZ5+/foxa9asZ35vK4rCgQMH0Ol0WFtbs2zZMvz9/Vu54pZz+PBhLl++TEhICIsXL7Z0OUIIIYQQzSIBXAJ4iygtLUWn05GQkEBpaanpdX9/fzQaDQMGDMDOzq7JxxgMBnbu3GkaIQXw+eefm7YKG41G7t69S3x8POnp6ab38fPzo0ePHuj1elJSUsjPz29yXXt7e3r06GEK5G5ubi3xKQsLaNyK7OnpyT/+8Y9mBWmDwcDx48e5ePEiAAEBAcyePbvNf19kZWWxZcsW6urq6NWrF/PmzXvh52s0GomNjSU5ORlHR0c++OCDdr31/nElJSV88803KIrChx9+iJ+fn6VLEkIIIYR4IQngEsBblNFoJCUlBZ1Ox507d0xN0WxsbOjfvz+RkZEEBASwd+9eVq9eTe/evXnzzTcByMzMZPLkyUyaNAmdTsfly5dNYV6lUtG/f39iYmIICAhocs/S0lJTZ/WUlBRqamqavN3Ly8t0djw4OPiZzdxE21dbW8s333xDVVUVU6ZMYciQIc3+2Dt37rBv3z5qa2txcHBg5syZhIaGtmC1ry43N5dffvmFmpoaevTowXvvvdfs79va2lp+/vlncnNz8fT05P3338fR0bGFK24de/fuJTExkX79+jFnzhxLlyOEEEII8UISwCWAt5rKykquX7+OTqdrMnLMzs6O/fv3c/36dSZOnMigQYMAOHjwIN7e3kRHR5vOdzs4ODB48GCioqKa9XUzGo1kZ2ebzo5nZWU1aeZmZWXVpJlbt27dpKFTOxMfH8+RI0dwdnbms88+w9bWttkfW1xczK5du8jJyQFg5MiRjBo1qk0dWSgoKGDz5s1UVVUREBDA4sWLX+pzBCgvL2fjxo2UlpYSGBjI4sWLO8SDp7y8PH744QcAPv30Uzw9PS1ckRBCCCHE80kAlwDe6hRFITMzE51Ox82bN9Hr9UDD1mC9Xo+dnR0Gg6HJ9tpu3boRExPDwIEDXys4VFdXk5qaagrkZWVlTd7u4uJiCuMhISEdZqWwIzMYDHz33XeUlJQwevRo0w6K5tLr9Rw9epSrV68CEBwczKxZs3B2dm6Jcl9KcXExmzdvpry8HB8fH5YuXYq9vf0rXSs/P59NmzZRU1ND3759mTNnTod42PTrr79y9+5dNBoN06ZNs3Q5QgghhBDPJQFcArhFHTt2jP/j//g/iIyMfKJBlKIo5ObmcvbsWb777jtGjx5t1nsrikJBQYFpu3paWprpYUCjx5u5BQQEtKmVUfGfbty4wZ49e7C1tWX16tWv9ODkxo0bHDhwgPr6epydnZk1a9Zzx5u1tLKyMjZv3kxJSQldu3Zl2bJlr/1AKC0tjW3btmEwGBg6dCgTJ040U7WWk5mZyaZNm1Cr1axevVp+nwshhBCiTZMALgHcomJjY1mwYAHQsPK4dOnSp67KqdVqevfuTWBgIAEBAfj6+pp9C61eryc9Pd0UyPPy8pq83c7OrkkzN3d3d7PeX7w6RVH48ccfyc3NJSYmhrfffvuVrlNQUMBvv/1Gfn4+KpWK0aNHM2LEiFZfKa6srOTnn3+moKAADw8Pli9fjouLi1mu3fiwAmDixIkMHTrULNe1pJ9//pn09HSGDRvGhAkTLF2OEEIIIcQzSQCXAG5Rp06darKy7enpSXBwML6+vvTu3fuZXxu1Wo23tzf+/v4EBAQQEBBAly5dzBqUysrKmjRzq66ubvJ2T09PUxgPCgp66XO5wrwePHjAtm3bUKvVfPrpp6/c7buuro5Dhw5x/fp1AEJDQ5kxY0arHUeorq7ml19+4dGjR7i6urJ8+XKzP+w5d+4cx48fB2Du3Lntch764+7fv8+OHTuwtbVlzZo1ODg4WLokIYQQQoinkgAuAdyiDAYDwcHBTzRHa+Tp6cmoUaOIjo5+IgD/nYODAwEBAaZQ7u/v/8rnZf/OaDSSk5NjOjv+8OHDJ5q5de/e3RTIpZmbZWzdupWUlBTCw8OZMWPGK19HURQSEhI4dOgQer0eV1dX5syZ80THfXOrra1l69atZGVl4eTkxPLly1uksZiiKBw6dIirV69ibW3NkiVLCAwMNPt9WouiKKxfv55Hjx69Uh8AIYQQQojWIgFcArjF7dmzh9mzZwM0CbWNATYuLo7p06dz//59dDod9+/fN72flZUVDg4OVFVVmUacPa5r165NVsm7du1qlnPcNTU1TZq5PT7rHMDZ2dnUzK1nz57SzK2VZGdns2HDBgBWrVqFj4/Pa10vNzeXXbt2UVRUhFqtZvz48cTExLTIw5X6+nq2b99Oeno6Dg4OLF26FG9vb7Pfp5HRaGTnzp3cu3cPBwcHVqxY0a67iDdurXd0dGTNmjUdosu7EEIIIToeCeASwNuEPXv2sHr1ah4+fGh6LTAwkHXr1jFz5swm71tWVkZCQgI6nY6SkhLT656enqbAkpOTQ3Fx8RP3sbW1xd/fv0kod3Jyeq3aFUWhsLCwSTO3+vr6Ju/T2MytZ8+eBAQENOnwLswrLi6OpKQkQkNDWbhw4Wtfr7a2lv3793Pr1i0A+vbty7Rp08y2uwIa+g/s3LmT5ORk7OzsWLJkCX5+fma7/rPU1dXxyy+/kJ2djYeHBytWrHjtnwdLMRqNfPvtt5SUlDBp0iSio6MtXZIQQgghxBMkgEsAbzMMBgNnz54lJycHX19fRo4c+dygqigKqamp6HQ6bt++jcFgAMDa2pr+/fvTt29fFEUhKyvL9F9dXd0T1/Hw8Giydd3Hx+e1ArJerycjI8MUyB89etTk7ba2toSEhJgC+aueVRZPV1RUxL/+9S+MRiNLliyhR48er31NRVG4cuUKR48exWg04uHhwZw5c/D19X3taxuNRuLi4rh9+zY2NjYsWrSI7t27v/Z1m6uiooKNGzdSUlKCv78/S5cubberx1euXOHQoUO4ubnx2WefyYMuIYQQQrQ5EsAlgHcIVVVVJCYmotPpmnQv9/T0RKPRMGjQIBwdHcnPz+fhw4c8fPiQrKws8vPzn7iWlZUVfn5+TVbJXV1dX3nbcXl5eZNmblVVVU3e3qVLF9PZ8eDgYGnmZgaHDh3iypUr+Pn58cEHH5hty3hWVha7du2itLQUKysrJk2aRGRk5CtfX1EU9u3bR2JiIlZWVixYsICQkBCz1PoyCgoK2LRpE9XV1fTp04e5c+e2y5F79fX1fP3111RWVjJjxgzCw8MtXZIQQgghRBMSwCWAdyiNK946nY6bN2+aVrzVajV9+vRBo9HQs2dPU7ioqakhKyvLFMgfPnz41GZvLi4uTVbJ/fz8XmmVUFGUJ5q5PX52Xa1WN2nm5u3tLc3cXkFFRQXffPMN9fX1zJ49m/79+5vt2tXV1ezbt4979+4BEB4ezpQpU176wYmiKPzxxx9cu3YNtVrN3Llz6dOnj9nqfFkZGRls2bIFg8FAVFQUkyZNapffe2fPnuXEiRN07dqVf/zjH+3ycxBCCCFExyUBXAJ4h1VXV0dSUhJarbbJ2XJXV1ciIiLQaDRPjHdSFIWioqImq+S5ublPdGhXqVT4+Pi89hi02traJs3cHj/TDuDk5NSkmVt7PZ9rCadOneL06dN06dKFjz/+2KzbkRVF4cKFCxw/fhxFUfDy8mLu3Ll07dq12R//559/cunSJQBmzZrFgAEDzFbfq0pKSiIuLg6A8ePH88Ybb1i4opdXU1PDV199RV1dHe+99x69e/e2dElCCCGEECYSwCWAdwp5eXnodDquX7/eZIW7Z8+eaDQa+vTpg7W19VM/tr6+nuzsbFMgz8zMpKKi4on3e90xaI3hv3G7empq6hPN3Hx9fU1hPDAwUM64PkdtbS3ffPMNVVVVTJ48maioKLPfIz09nbi4OCoqKrCxseGdd95p1rbnkydPcubMGQCmTZuGRqMxe22v6uLFi/z5558AZt890Fr++usvLly4QGBgIO+//76lyxFCCCGEMJEALgG8U9Hr9dy9exetVktKSorpdUdHR8LDw4mMjHzhKqaiKJSVlTVZJc/OzjY1gXvc64xB0+v1ZGZmmgJ5bm5uk7fb2trSo0cPUyDv0qVLs67bmVy+fJnDhw/j5OTE559/3iLn6ysrK9m9ezepqakAREZGMmnSpGc+0Dl//jzHjh0D4O233yYmJsbsNb0ORVE4cuQIly9fxsrKiiVLlrRqUzhzKC8v5+uvv8ZgMLB8+fJ2V78QQgghOi4J4BLAO63i4mLTOLPy8nLT6wEBAURGRtK/f/9mBzaDwUBubm6Ts+TmHoNWUVFhCuMPHjx4opmbh4dHk2ZudnZ2zbpuR2YwGPjXv/5FcXExo0aN4q233mqR+xiNRs6cOcPp06cB8PHxYc6cOU88FGns0g0wduxYRowY0SL1vC6j0ciuXbu4c+cO9vb2rFixAi8vL0uX9VIOHjzItWvX6NWrFwsWLLB0OUIIIYQQgARwCeACo9HIgwcP0Gq13Lt3z9QUzdbWlgEDBhAZGYmfn99Ln++urKxsskr+rDFo7u7upjDe3DFoiqKQm5trOjuemZn5RDO3wMBAUyD38fHptM2obt68ye7du7G1teXzzz9v0XP0Dx48YM+ePVRVVWFnZ8f06dPp27cvAAkJCfz+++8AjBw5kjFjxrRYHeZQX1/Pli1bePjwIe7u7qxYsQJnZ2dLl9VsRUVFfPfddyiKwkcffYS3t7elSxJCCCGEkAAuAVw8rqKiguvXr6PVaikqKjK93q1bNyIjIwkPD8fBweGVrm00Gk1j0BpXyZ81Bs3X17dJKH/RGLTa2lrS0tJMgfzvq++Ojo5Nmrm1pyD1uhRFYcOGDeTk5BAdHc2kSZNa9H5lZWXExcWRmZkJQExMDP7+/uzduxdFUYiJiWHixInt4oFIZWUlmzZtoqioCD8/P5YuXdquxuTFxcWRlJTEwIEDmTlzpqXLEUIIIYSQAC4BXDyNoihkZGSg1Wq5desWer0eaAjHffv2JTIykuDg4NcOUTU1NaYGb43/PW0MmrOzc5NA7uvr+9wg9Pdmbn9feffx8TGF8e7du3f4Zm4pKSls3boVtVrNp59+ioeHR4vez2AwcPz4cS5evNjkdY1Gw9SpU9tF+G5UVFTExo0bqaqqonfv3sybN6/dzAjPycnhxx9/RKVS8dlnn7X4110IIYQQ4kUkgEsAFy9QU1PDjRs30Gq1TRqheXh4oNFoiIiIwMXFxSz3UhSF4uLiJoH8WWPQvL29m4TyZ41BMxgMTZq55eTkNHm7jY3NE83c2lNAbK6tW7eSkpLSqquhp0+f5tSpU0DDw5u5c+e2y7FYDx8+5JdffkGv1zN48GCmTJnSbr5Htm3bxoMHDxgyZAhTpkyxdDlCCCGE6OQkgEsAFy8hJycHrVbLjRs3qK2tBRrCcK9evYiMjKRXr15mXx2sr68nJyenSSh/vGlcIwcHhybN3Z41Bq2ysrJJM7fKysomb3d3dzedHe/Ro0eHaebWuBoKsHLlSnx9fVv0fpmZmWzdupX6+nrs7OxM3y8jRoxg9OjR7WYVudHt27f57bffgLbdQO7v0tLS+OWXX7C2tmb16tWd6viFEEIIIdoeCeASwMUrqK+v59atW2i1WjIyMkyvOzs7ExERgUajadGxYI+PQXv48CE5OTmmbfKP8/LyarJK/vcxaIqi8OjRI9PZ8YyMjCeauQUEBJgCua+vb7tZ+Xya3bt3c/PmTXr27MmiRYta5B7/43/8D/75z3/yxhtvMGHCBHr27Mns2bM5fvw4V69eBSA4OJiZM2eabedEa4mPj+fIkSMAzJw5k4EDB1q4ohdTFIWNGzeSlZXFiBEjGDt2rKVLEkIIIUQnJgFcArh4TQUFBeh0OhISEpqMBgsODiYyMpK+ffs+cya0uRgMBh49etQklD9rDJqfn1+TVfLHVwTr6uqaNHN7vBEdNDRzCwkJMW1Xb28Bsri4mO+++w6j0cjixYsJCQkx6/WvXLnCrFmz0Ov1dO/enVWrVrFo0SJsbGyAho7sBw4coK6uDicnJ2bNmkWPHj3MWkNLO3r0KJcuXcLKyopFixYRHBxs6ZJe6M6dO+zcuRM7OzvWrl3bYXZ1CCGEEKL9kQAuAVyYicFg4N69e2i1WpKTk02v29vbEx4eTmRkZKuOQqqsrDR1W2/svP6yY9CKi4tNW9VTUlKe+Hhvb+8mzdxa+kGDORw+fJjLly/j6+vLhx9+aLYV/YqKCiIiIhg7dixHjx4lNDSUP/7444mwV1BQwK5du8jLy0OlUjFq1ChGjhzZbnYWKIpCXFwct27dwt7envfff5+uXbtauqznUhSF77//noKCAsaNG8fw4cMtXZIQQgghOikJ4BLARQsoLS0lISEBnU5HaWmp6XU/Pz8iIyMZMGBAq6/CGY1GCgoKmqySv8wYNKPRyMOHD02BPDs7u8nH2djYEBwcbArknp6ebTJUVlZW8s0331BXV8esWbMYMGCAWa773nvvkZ2dzZgxY9i+fTsTJkzgu+++e+r71tfXc+jQIRISEgAIDQ1lxowZODo6mqWWlqbX69myZQuZmZm4ubmxYsWKNr8bonEOu7OzM6tXr24XD4uEEEII0fFIAJcALlqQ0WgkNTUVrVbLnTt3TOerbWxs6N+/P5GRkQQEBFgsqL7OGLT6+npSUlJMgbyioqLJx7i5uTVp5va0hnCW0tid3MPDg08++eS1x7D9/PPP/POf/+T999/Hx8eHnTt3MnjwYNatW/fcj9PpdBw6dAi9Xo+rqyuzZ88mMDDwtWppLVVVVWzatInCwkJ8fHxYtmxZm97abTAY+OabbygrK+Odd95h8ODBli5JCCGEEJ2QBHAJ4KKVVFZWkpiYiFarpaCgwPS6l5cXkZGRhIeH4+TkZMEKnz4G7dGjR00as0HTMWj+/v74+/tjMBhMYTwjIwODwdDk/f/ezM2SXcDr6ur45ptvqKysZNKkSURHR7/yte7du8eQIUNYuHAhYWFhLF++nGnTphEREfHCAA7w6NEjdu3aRWFhIWq1mnHjxjF06NA2uXvg74qLi9m4cSOVlZWEhoYyf/78Nj1T/tKlSxw9epQuXbrwySeftLtO9EIIIYRo/ySASwAXrUxRFB4+fIhWqyUpKYn6+nqgoeN4WFgYkZGRhISEtJkA1twxaPb29qZA7uPjg16vN80fLywsbPK+Dg4OTZq5WeJn8MqVKxw6dAgnJyc+++yzV1q9ramp4YsvvuCHH35ArVabvmYGgwGVSoVaraa2tvaFobS2tpYDBw6QlJQEQFhYGNOnT29TuwaeJSsri59//hm9Xo9Go2Hq1Klt5nv37+rq6li3bh3V1dXMnj2b/v37W7okIYQQQnQyEsAlgAsLqq2t5ebNm2i12iZnqt3c3NBoNERERODm5mbBCp/u8TFoWVlZZGdnP3cMmoeHB3q9nvz8fFJTU00zsRt17drVtDoeFBTUKudzDQYD33//PUVFRbz11luMGjXqpT6+rq6Obdu2kZycTG1tLdOnTzeNnlu+fDlhYWH8x3/8R7PPmCuKwpUrVzh69ChGoxEPDw/mzJnT4vPKzeHu3bvs3LkTRVEYPXo0b775pqVLeqZTp05x+vRpszfhE0IIIYRoDgngEsBFG5Gbm4tOpyMxMZGamhrT66GhoURGRtK7d+82u7338TFojZ3X/z7CDBrOvvv5+eHq6orBYKCoqIjc3Nwm72Ntbd2kmZuXl1eLhaSkpCTi4uKwtbXls88+azKS7Xn0ej2xsbGkpKRgb2/P0qVL8fHxMb191KhRzd6C/ndZWVnExcVRUlKClZUVb7/9NoMHD27zQbFxRwHAu+++y6BBgyxc0dNVVVWxbt066uvrWbRoET179rR0SUIIIYToRCSASwAXbUx9fT137txBq9WSlpZmet3JyYlBgwah0Wjw8vKyXIHN9PgYtMb/+bQxaK6urri5uWE0GikuLm4yS73x7Y83c3NwcDBbjYqi8NNPP5GdnU1UVBSTJ09+4ccYDAZ+++037t27h42NDUuWLCEgIKDJ+7xOAAeorq5m37593Lt3D4CBAwfyzjvvYGtr+0rXay3Hjh3j/PnzqNVqFi5caPY56+Zy5MgR4uPjCQ4OZunSpZYuRwghhBCdiARwCeCiDSsqKkKn05GQkNCky3j37t2JjIykX79+2NjYWLDC5vv7GLSsrCzy8vKeeD+1Wo2LiwuKolBRUdGkAZxKpcLf398UyP38/F67kVZqaipbtmxBrVbzySefmLaRP+tz2LNnD0lJSVhbW7Nw4UKCg4Nf6/7PoigKFy5c4Pjx4yiKgpeXF3PmzKFbt24tcj9zUBSFPXv2cPPmTezs7Fi+fDne3t6WLusJpaWlfPPNNxiNRlasWPHEAxQhhBBCiJYiAVwCuGgHjEYj9+/fR6vVcv/+fRp/xOzs7Bg4cCCRkZHt4qzw39XW1j6xSv73FXBo2LquUqmeWEG3t7c3NXMLDQ195Z/lbdu28eDBAwYMGMCsWbOe+j6KorB//34SEhJQq9XMnz+fXr16vdL9XkZGRgZxcXGUl5djY2PDlClT2uz2bmjYnr9t2zbS09NxcXHhgw8+aJO/Y3///XcSEhIICwtj3rx5li5HCCGEEJ2EBHAJ4KKdKSsr4/r16+h0OoqLi02v+/j4EBkZycCBA9tF9+yn+fsYtKysLHJzc58YgwYNq+F//1XT2MytZ8+eBAUFNXt3QG5uLuvXrwdg5cqVTzzMUBSFI0eOcPnyZVQqFbNnz6Zfv36v+Fm+vMrKSvbs2UNKSgoAGo2GSZMmtdndD9XV1WzatImCggK8vb1Zvnx5m5sRnp+fz/fffw/Axx9/TNeuXS1ckRBCCCE6AwngEsBFO6UoCmlpaWi1Wm7fvm2au21tbU2/fv2IjIyke/fubb5514s8PgatcZW8rKzshR9nbW1NUFCQKZB37dr1uf8We/bs4caNG/To0YPu3buTk5ODr68vI0eO5NSpU5w7dw6wXIMxo9HImTNnOH36NNDwwGXOnDnP3TJvSSUlJWzcuJGKigpCQkJYsGBBm2siuHPnTu7cuUNERATTp0+3dDlCCCGE6AQkgEsAFx1AVVUVN27cQKvVNjlX3aVLFyIjIxk0aFCzO3y3B80dg/Y4JycnevXqRWhoKCEhIU80cysuLubbb79FURS2bNliWm2eMmUKUVFRpv99yJAhLfNJNVNKSgq7d++mqqoKW1tbpk+f3qqr8S8jJyeHzZs3U19fz6BBg5g+fXqbeiD08OFDNm7ciFqt5vPPP2+TI/+EEEII0bFIAJcALjoQRVHIzs5Gq9Vy8+ZN05lptVpN7969iYyMpGfPnq/duKyt+fsYtMzMzCbb85+mS5cu9O7dm379+uHv78++ffvYsGEDQ4cOJTs7mw0bNhAdHc2kSZOAhhXnVatWtcan80JlZWXs3r2bjIwMAGJiYhg/fnybW2EGuH//PrGxsSiK8krz1lvaL7/8QlpaGkOHDmXixImWLkcIIYQQHZwEcAngooOqq6sjKSkJrVbLw4cPTa+7uLig0WjQaDS4u7tbrsAWVlVVZVolz8zM5OHDh89cJVer1eTn53Pv3j0iIyOxs7Pj6tWrptXuU6dO8eDBA1JTU9tMyDUajZw4cYLz588D4O/vz5w5c9rkKu61a9c4ePAgANOmTUOj0Vi4ov+UnJzM9u3bsbGxYc2aNTg6Olq6JCGEEEJ0YBLAJYCLTiAvLw+dTsf169eprq42vR4SEkJkZCR9+vTB2traghW2vMfHoKWkpJCRkUF5efkz319RFFQqFefPn+evv/4C4OTJk21uBffu3bvs27ePmpoaHBwcePfdd+ndu7ely3rCiRMnOHv2LCqVigULFhAaGmrpkoCGr/OPP/5Ibm4uo0aN4q233rJ0SUIIIYTowCSASwAXnYher+fu3btotVrTGWcABwcHBg0ahEajadNzps2ttraWhw8fsn//flJSUvDw8Giywl1UVMQ333xj+r937NjBe++9Z4lSn6ukpIRdu3aRnZ0NwIgRIxg9enSbOmqgKAr79u0jMTERW1tbli9fjo+Pj6XLAiApKYm4uDgcHBxYs2YNtra2li5JCCGEEB2UBHAJ4KKTKi4uJiEhgYSEhCZdxQMCAoiMjKR///6dJoicOnWK0aNHA+Dt7c3UqVPp1q0b//rXvygtLTW9X1tcAW+k1+v5888/uXLlCgBBQUHMmjULFxcXC1f2nwwGA9u3byc1NRVnZ2c++OCDNrFl3mg08t1331FcXMzbb79NTEyMpUsSQgghRAclAVwCuOjkjEYjDx48QKfTcffuXdPMbVtbW/r378/gwYPx8/NrU92rzc1gMBAcHExWVtYTs8WhYeZ4QEBAmzoD/iw3b97kwIED1NXV4eTkxKxZs+jRo4elyzKpqalh8+bN5OXl0bVrV95///02Mbe+8Zy6q6srn3/+eZv/OgshhBCifZIALgFcCJOKigquX7+OTqejsLDQ9Hq3bt3QaDSEh4d32CZVe/bsYfbs2QBNQnjjg4e4uDhmzpxpkdpeVmFhIb/99ht5eXmoVCreeust3nzzzTbzEKW0tJSNGzdSXl5OcHAwCxcutHgPAr1ez9dff01FRYXFZr0LIYQQouOTAC4BXIgnKIpCRkYGOp2OpKQkU/dwKysr+vbti0ajoUePHm0m0JnLnj17WL16dZOu8YGBgaxbt67dhO9G9fX1HDp0iISEBAB69uzJjBkzcHJysmxh/7/c3Fw2b95MXV0dAwcOZMaMGRb/fjp//jzHjh3Dy8uLjz/+2OL1CCGEEKLjkQAuAVyI56qpqeHGjRvodDpycnJMr7u7u6PRaIiIiOhQP0MGg4GzZ8+Sk5ODr68vI0eObNfbkRMSEvjjjz/Q6/W4uLgwZ84cAgMDLV0WAA8ePGDHjh0YjUZGjBjB2LFjLVpPbW0tX331FbW1tcybN4+wsDCL1iOEEEKIjkcCuARwIZotJycHrVbLjRs3qK2tBRq2aPfq1QuNRkOvXr3adVjtqB49esSuXbsoLCxErVYzduxYhg0b1iZWeBMSEvj9998BeOeddxg8eLBF6zl+/Djnzp3D39+fFStWtIl/IyGEEEJ0HBLAJYAL8dLq6+u5desWOp2O9PR00+vOzs4MGjSIyMhIunTpYsEKxd/V1tZy8OBBbt68CUCfPn14991320QDtFOnTnH69GlUKhXvvfcevXr1slgtFRUVrFu3DoPBwNKlSwkODrZYLUIIIYToeCSASwAX4rUUFBSg0+m4fv06lZWVpteDg4PRaDT07dsXGxsbC1YoGimKwtWrVzl69CgGgwF3d3fmzJmDn5+fxevav38/CQkJ2NjYsGzZMovW9Mcff3D16lVCQ0NZuHChxeoQQgghRMcjAVwCuBBmYTAYuHfvHjqdjuTkZFMncXt7ewYOHEhkZCQ+Pj4WrlIAZGdns2vXLkpKSrCysmLixIkMGTLEotutDQYDO3bsICUlBScnJz744APc3d0tUktxcTHffvstiqKwatUq+b4VQgghhNlIAJcALoTZlZaWkpCQgE6no7S01PS6n58fGo2GgQMHYmdnZ8EKRXV1Nb///jt3794FYMCAAbzzzjsW/brU1tayefNmHj16hJeXF++//z4ODg4WqWX37t3cvHmTAQMGMGvWLIvUIIQQQoiORwK4BHAhWoyiKKSkpKDT6bh9+zZGoxEAGxsb+vfvj0ajITAwUBpdWYiiKFy8eJFjx46hKAqenp7MnTuXbt26WaymsrIyNm7cSFlZGUFBQSxatMgiM8Jzc3NZv349KpWKTz/9VHoaCCGEEMIsJIBLABeiVVRWVpKYmIhOpyM/P9/0upeXFxqNhkGDBrWZGdWdTUZGBnFxcZSXl2Ntbc2UKVOIiIiwWD2PHj1i8+bN1NbW0r9/f2bNmmWRhzQ7duzg/v37DB48mHfeeafV7y+EEEKIjkcCuARwIVqVoig8fPgQrVZLUlIS9fX1AKjVasLCwtBoNISEhKBWqy1caedSWVnJ3r17efDgAQAajYZJkyZZrIFeamoq27Ztw2g08sYbbzB+/PhWryE9PZ2ff/4ZKysr1qxZg7Ozc6vXIIQQQoiORQK4BHAhLKa2tpabN2+i0+nIysoyve7m5kZERAQajQY3NzcLVti5GI1Gzp49y6lTpwDw9vZmzpw5eHp6WqSexMRE9u7dC8CkSZOIjo5u1fsrisLmzZvJzMxk+PDhjBs3rlXvL4QQQoiORwK4BHAh2oRHjx6h1WpJTEykpqbG9HpoaCgajYY+ffpgZWVlwQo7j5SUFPbs2UNlZSW2trZMmzaN/v37W6SWM2fOcPLkSVQqFfPmzaNPnz6tev+7d+/y66+/Ymdnx5o1a9rE3HQhhBBCtF8SwCWAC9Gm6PV6bt++jU6nIzU11fS6o6MjgwYNIjIyEi8vLwtW2DmUl5eze/du0tPTAYiOjmbChAmt/hBEURQOHjyIVqvF2tqaZcuW4e/v36r3/+GHH8jPz2fs2LGMGDGi1e4thBBCiI5HArgEcCHarKKiInQ6HQkJCVRUVJhe7969OxqNhn79+mFra2vBCjs2o9HIiRMnOH/+PAD+/v7Mnj271edzG41GYmNjSU5OxtHRkRUrVrRqV/Lr16+zb98+nJycWL16tcXOxQshhBCi/ZMALgFciDbPaDRy//59dDod9+7do/FXjJ2dHQMGDCAyMhJfX18ZZ9ZC7t27x969e6mpqcHe3p4ZM2bQu3fvVq2hrq6On3/+mZycHLp06cKKFStwdHRslXsbDAa+/fZbSktLmTJlCkOGDGmV+wohhBCi45EALgFciHalvLychIQEdDodxcXFptd9fHzQaDQMHDgQBwcHC1bYMZWUlBAXF2dqljd8+HDGjBnTqt3qy8vL2bhxI6WlpQQGBrJ48eJWW42Oj4/nyJEjeHh48Omnn0qXfiGEEEK8EgngEsCFaJcURSEtLQ2dTsetW7cwGAwAWFtb069fPzQaDUFBQbIqbkYGg4E///yTy5cvAw1HAWbPno2Li0ur1ZCfn8+mTZuoqamhb9++zJkzp1W+xvX19axbt46qqipmzZrFgAEDWvyeQgghhOh4JIBLABei3auuriYxMRGtVkteXp7p9S5duqDRaIiIiJAZzmaUlJTE/v37qaurw9HRkVmzZhESEtJq909PT2fr1q0YDAaGDh3KxIkTW+W+p0+f5tSpU3h7e7Nq1Sp5uCOEEEKIlyYBXAK4EB2GoihkZ2ej1Wq5efMmdXV1AKhUKvr06YNGoyE0NFS2D5tBYWEhu3bt4tGjRwCMGjWKkSNHttq/7c2bN9m9ezcAEydOZOjQoS1+z+rqar766ivq6+tZuHAhoaGhLX5PIYQQQnQsEsAlgAvRIdXV1ZGUlIROpyMzM9P0uouLCxEREWg0Gjw8PCxYYftXX1/P4cOH0el0APTs2ZMZM2bg5OTUKvc/f/48x44dA2Du3Ln07du3xe959OhRLl26RFBQEMuWLWvx+wkhhBCiY5EALgFciA4vPz8frVZLYmIiVVVVptdDQkLQaDSEhYVhbW1twQrbt4SEBP744w/0ej0uLi7Mnj2b7t27t/h9FUXh0KFDXL16FWtra5YsWUJgYGCL3rOsrIyvv/4ao9HI+++/3+L3E0IIIUTHIgFcArgQnYZer+fu3bvodDoePHhget3BwYHw8HAiIyPp1q2bBStsv/Ly8ti1axcFBQWoVCrGjRvHsGHDWvyctNFoZOfOndy7dw8HBwdWrFiBp6dni95z//796HQ6+vTpw/z581v0XkIIIYToWCSASwAXolMqKSlBp9ORkJBAWVmZ6fWAgAA0Gg0DBgzA1tbWghW2P3V1dRw4cICbN28C0KdPH6ZPn97iY+Hq6ur45ZdfyM7OxsPDgxUrVrToNviCggL+9a9/AfDxxx/TtWvXFruXEEIIIToWCeASwIXo1IxGIw8ePECn03H37l2MRiMAtra29O/fn8jISPz9/aXjdTMpisK1a9c4cuQIBoMBd3d35syZg5+fX4vet6Kigo0bN1JSUoK/vz9Lly5t0Rnhv/32G7dv32bQoEG8++67LXYfIYQQQnQsEsAlgAsh/n8VFRWmcWaFhYWm17t27UpkZCTh4eE4OjpasML2Iycnh99++42SkhKsrKyYOHEiQ4YMadEHGQUFBWzatInq6mr69OnD3LlzW6wre1ZWFj/99BNqtZrPP/8cNze3FrmPEEIIIToWCeASwIUQf6MoCpmZmWi1WpKSktDr9QBYWVkRFhZGZGQkPXr0kFXxF6ipqeH333/nzp07AAwYMIB33nkHOzu7FrtnRkYGW7ZswWAwEBUVxaRJk1rs67RlyxZSU1OJjo5m0qRJLXIPIYQQQnQsEsAlgAshnqOmpoabN2+i1WrJyckxve7u7o5GoyEiIkJ+hzyHoihcunSJY8eOYTQa8fT0ZM6cOXh7e7fYPW/dusWuXbsAGD9+PG+88UaL3CclJYWtW7dibW3N2rVrZXeEEEIIIV5IArgEcCFEM+Xk5KDT6UhMTKS2thYAlUpFaGgokZGR9OrVCysrKwtX2TZlZmYSFxdHWVkZ1tbWTJkyhYiIiBa738WLF/nzzz8BmD17Nv379zf7PRRFYcOGDeTk5PDmm28yevRos99DCCGEEB2LBHAJ4EKIl1RfX8/t27fRarWkp6ebXndyciIiIgKNRglKKrUAACqYSURBVNPio7Dao6qqKvbs2WMaARcREcHkyZNbpFmaoigcOXKEy5cvY2VlxeLFiwkKCjL7fRpX2+3t7Vm7dq10zhdCCCHEc0kAlwAuhHgNhYWFpnFmlZWVpteDgoKIjIykb9++LdqNu71RFIWzZ89y6tQpFEWhW7duzJ07t0UeWBiNRnbt2sWdO3ewt7dnxYoVeHl5mf0e//rXvygqKmLChAkMGzbMrNcXQgghRMciAVwCuBDCDAwGA/fv30er1ZKcnEzjr0F7e3sGDhxIZGQkPj4+Fq6y7UhNTWX37t1UVlZia2vLtGnTWmSbeH19PVu2bOHhw4e4u7uzYsUKnJ2dzXoPrVbLgQMHcHFxYfXq1XIMQQghhBDPJAFcArgQwszKyspISEhAp9NRUlJiet3X15fIyEgGDBiAvb295QpsI8rLy9m9e7dpG39UVBQTJkzA2trarPeprKxk06ZNFBUV4efnx9KlS826VVyv1/P1119TUVHBtGnT0Gg0Zru2EEIIIToWCeASwIUQLURRFFJTU9Fqtdy5cweDwQCAtbU1/fv3JzIyksDAwE49zsxoNHLy5EnOnTsHgJ+fH3PmzMHd3d2s9ykqKmLjxo3/X3t3HhXVmed//FPsbuCGiqAIKrghVJGMSweX2ErHjGkbo0YzGo1Otz1Jp4nTczqJfSbp/sc+fSZHk47GpINm6XbDLWqMEVtNMC6dWAWIoGJERcUFBVxQtrq/P/KzphmNUlBcEN6vc+qPerz3ud+rjwWfuvc+j8rKytS3b18988wzHl0jfN++fUpLS1OnTp30wgsvtOh/UwAA8MMI4ARwACYoKytTVlaW7Ha7Ll++7Grv1KmTbDabYmNj1aZNm0assHHl5eVp48aNunXrlgICAjRx4kRFR0d79Bhnz57VRx99pKqqKsXHx+vJJ5/0WFAuLy/X4sWLdfv2bU2ZMkX9+/f3SL8AAKB5IYATwAGYyDAMnTt3Tna7XdnZ2aqsrJQkeXl5KTo6WjabTZGRkR69OvuwKC0tVWpqqs6dOydJGj58uB5//HGPPlOdm5urtWvXSpLGjBmjxx57zGN979q1S+np6QoNDdWcOXO4Cg4AAO5CACeAA2gk5eXlOnLkiOx2uyt0SlJgYKCsVqvi4uI8fit2U1ddXa20tDQdPHhQktSzZ09NmjTJo5/TBw8e1Pbt2yVJSUlJiomJ8Ui/N2/e1OLFi1VVVaWZM2cqIiLCI/0CAIDmgwBOAAfQBFy8eFEOh0NZWVm6deuWq713796y2WyKjo5uUbNr5+TkaPPmzSovL1fr1q2VlJSk3r17e6z/L774QgcOHJCXl5dmzJihXr16eaTfbdu26ZtvvlHv3r31b//2bx7pEwAANB8EcAI4gCakqqpKR48eld1uV35+vqu9devWio2NldVqVXBwcCNWaJ6rV69q7dq1unjxoiRp5MiRGjFihEduzzcMQ+vWrVNOTo78/f31/PPPq0uXLvXut6SkRG+//bYMw9DPf/5zhYSE1LtPAADQfBDACeAAmqji4mI5HA5lZGTo+vXrrvYePXrIZrNpwIABHl1OqymqrKzU9u3bZbfbJUmRkZFKSkryyIR1VVVV+vjjj1VQUKCgoCDNmTNH7dq1q3e/GzduVFZWlgYMGKDJkyfXuz8AANB8EMAJ4ACaOKfTqRMnTshut+v48eO68xHr5+enmJgY2Ww2hYSENOtJvzIzM/XZZ5+psrJS7dq106RJkxQeHl7vfsvKyrR8+XJduXJF3bp106xZs+Tv71+vPi9evKhly5ZJkl588UV16tSp3nUCAIDmgQBOAAfwELl+/boyMzNlt9tVXFzsau/atatsNptiYmLUqlWrRqyw4Vy6dEmpqakqKiqSxWLRmDFjNHz48Hp/8VBcXKyUlBTdvHlTvXv31rRp0+r9vP2qVat0/Phx2Ww2TZgwoV59AQCA5oMATgAH8BAyDEOnT5+W3W5XTk6OqqurJUne3t4aMGCAbDabwsPDm91V8YqKCm3dulWHDx+WJEVFRWnixIn1/tLh3Llz+uijj1RZWSmr1aoJEybU6+/uzJkzWrFihby9vfXrX//aI7e2AwCAhx8BnAAO4CF369YtHT58WHa73TVhmSR17NhRVqtVsbGxzSoAGoYhu92uzz//XNXV1QoKCtLkyZMVGhpar36PHTumNWvWyDAMjR49WiNGjKhXfytWrNCZM2c0fPhwjR07tl59AQCA5oEATgAH0EwYhqHCwkLZ7XYdPnxYFRUVkiSLxaKoqCjZbDb16dPHI7OINwWFhYVKTU1VcXGxvLy8lJiYqEcffbReV66/+eYbbdu2TZI0ceJExcbG1rmv48ePa9WqVfLz81NycnKzfTQAAADUHgGcAA6gGaqoqFBOTo7sdrsKCgpc7e3atVNcXJysVqs6dOjQiBV6xu3bt/Xpp5/q6NGjkqSBAwdqwoQJ9ZpIbefOnfr666/l5eWlZ599VpGRkXXqxzAMLVu2TJcuXdLjjz+uhISEOtcEAACaBwI4ARxAM3f58mU5HA5lZmaqrKzM1R4RESGbzaZ+/frJx8enESusH8MwdPDgQaWlpcnpdKpjx46aMmWKunbtWuf+NmzYoOzsbPn7+2v27Nl17isrK0sbN25U69atlZycLF9f3zr1AwAAmgcCOAEcQAtRXV2tY8eOyW6367vvvnO1t2rVSoMHD5bVaq1z0GwKCgoKtG7dOl27dk0+Pj4aP368rFZrnfqqqqrSX//6V50+fVrt2rXT3Llz6/Szwul06s9//rNKSko0fvx4Pfroo3WqBwAANA8EcAI4gBaopKREGRkZcjgcunbtmqs9NDRUNptNAwcOrPd62I2hrKxMGzdu1IkTJyRJcXFxGj9+fJ2uPN+6dUvLly9XUVGRunTpotmzZysgIMDtfu48V96+fXv96le/ajbP4AMAAPcRwAngAFowp9OpkydPyuFw6OjRo3I6nZIkX19fDRo0SDabTaGhoQ/VcmaGYWjv3r3avXu3DMNQly5dNHnyZHXu3NntvkpKSpSSkqIbN24oMjJS06dPd3uN8MrKSi1evFhlZWVKSkpSTEyM23UAAIDmgQBOAAcASdLNmzeVmZkph8OhoqIiV3twcLBrObPWrVs3YoXuyc/P1/r163Xz5k35+flpwoQJGjRokNv9FBYWasWKFaqsrFRsbKx++tOfuv2FRHp6unbt2qUuXbpo3rx5D9UXGgAAwHMI4ARwAKjBMAwVFBTI4XAoOztbVVVVkiRvb2/169dPVqtVkZGRD0WIvHHjhtavX69Tp05Jkh555BElJia6PelcXl6eVq1aJcMwNGLECI0ePdqt/W/fvq1FixapoqJC06dPV9++fd3aHwAANA8EcAI4APyg27dvKzs7Ww6HQ+fPn3e1t2/fXlarVXFxcU3+M9TpdGrPnj1KT0+XJIWEhGjy5MluL8N26NAhbd26VZL01FNPuT3BW1pamvbt26eePXtq9uzZbu0LAACaBwI4ARwAauXChQuy2+06fPiwbt++LUmyWCzq06ePrFaroqKi3H4+2kx5eXnauHGjbt26pYCAAE2cOFHR0dFu9bFr1y6lp6fLYrFo+vTp6tOnT633vX79ut566y1VV1dr9uzZ6tmzp7unAAAAHnIEcAI4ALilsrJSubm5cjgcrlu7JalNmzaKjY2VzWZTp06dGq/A+ygtLdW6det09uxZSdKwYcM0ZsyYWn9xYBiGNm3apKysLPn5+Wn27Nnq1q1brY+/ZcsW2e12RUVFadq0aXU6BwAA8PAigBPAAaDOrly5IofDoYyMDN28edPVHh4eLqvVqgEDBtRpCbCGVF1drZ07d+rAgQOSpB49eujpp5+u9c+C6upq/e1vf1N+fr7atm2ruXPnKigoqFb7XrlyRe+8844kad68eQ/1uusAAMB9BHACOADUW3V1tfLy8uRwOJSXl6c7Pwb8/f0VExMjm82mkJCQRq6yptzcXH366acqLy9X69atlZSUpN69e9dq39u3b2vFihW6dOmSgoOD9fzzz9d6jfDU1FTl5ORo8ODB+tnPflafUwAAAA8ZAjgBHAA86tq1a8rIyJDD4VBJSYmrPSQkRFarVTExMbUOqw3t6tWrSk1N1YULFyRJI0aM0MiRI+Xl5fXAfUtLS5WSkqLr16+rV69eevbZZ2s1u/r58+f1l7/8RRaLRS+99JLat29f39MAAAAPCQI4ARwAGoRhGMrPz5fD4VBubq6qq6slST4+Pho4cKCsVqt69uzZ6MuZVVVVafv27Tp06JAkKSIiQklJSWrbtu0D971w4YJWrFihiooKxcTE6Gc/+1mtzueTTz7RyZMn9eijj2r8+PH1PgcAAPBwIIATwAGgwZWVlSkrK0t2u12XL192tXfq1ElWq1WxsbG1CrwNKSsrS1u3blVlZaXatm2rp59+WuHh4Q/c77vvvtPKlSvldDr12GOPacyYMQ/cJz8/Xx9//LF8fHyUnJysNm3aeOIUAABAE9cQOfTB9+3dw9KlSxUREaGAgADFx8e71mu9l8LCQk2fPl3R0dHy8vJScnJyXWsFAJigdevWGjp0qH75y19qzpw5slqt8vX11ZUrV7Rz504tWrRIa9euVV5enpxOZ6PUOHjwYP37v/+7goODdePGDX300Ufau3evHvSdcu/evTVhwgRJ0t69e11X0u+nV69eCg0NVVVVlQ4ePOiR+gEAQMvkdgBfs2aNkpOTtWDBAjkcDiUkJOiJJ57QmTNn7rl9eXm5goODtWDBAsXGxta7YACAOSwWi8LCwvTUU0/pP//zPzVhwgSFhYXJ6XQqNzdXK1eu1FtvvaXdu3fXeH7cLMHBwZo7d64GDx4swzD097//XatXr9atW7fuu19cXJxGjhwpSfrss8+Ul5d33+0tFot+9KMfSZK++eYblZeXe+YEAABAi+P2LehDhgyRzWbTu+++62rr37+/Jk6cqIULF95331GjRikuLk6LFy92q0huQQeApuPSpUuy2+3KysqqEXZ79+4tq9Wq6OjoWk1w5imGYchut+vzzz9XdXW1goKCNHnyZIWGht53n82bNysjI0O+vr6aNWuWunfvft/tlyxZoitXrmjs2LEaPnx4Q5wKAABoQhr9FvSKigodOnRI48aNq9E+btw47du3zyMFSd9fNb927VqNFwCgaejSpYt+8pOfaP78+Zo0aZIiIyMlff989bp167Ro0SJ98cUXNZ4fb0gWi0Xx8fGaO3euOnTooNLSUi1fvlwHDx78wVvSLRaL/vVf/1W9e/dWZWWlVq5cqeLi4vse485V8AMHDqiqqqpBzgUAADRvbgXwoqIiVVdXq2vXrjXau3bt6loWxhMWLlyooKAg16tHjx4e6xsA4Bk+Pj4aNGiQZsyYoZdeekkJCQlq166dysrKdODAAS1dulTLly+Xw+FQRUVFg9fTrVs3/fznP1f//v3ldDq1fft2rVu37gdvGff29tbkyZPVtWtX3bx5UytXrrzv7euDBw9Wu3btdP36dWVlZTXUaQAAgGasTpOw/d9lWwzD8OjSNK+++qpKS0tdr4KCAo/1DQDwvA4dOujxxx9XcnKypk2bpn79+slisaigoECbN2/Wm2++qS1btujcuXMPnCitPgICAjR58mQlJibKy8tLOTk5ev/993/wS2J/f39Nnz5dgYGBKioq0urVq3/w6ra3t7eGDRsmSfr6668bbQI6AADw8HIrgHfu3Fne3t53/SJz6dKlu66K14e/v78CAwNrvAAATZ+Xl5eioqI0depUzZ8/X2PGjFHHjh1VUVEhu92uDz74QO+9954OHjz4wMnS6spisWjo0KGaPXu2AgMDdfXqVaWkpMhut98z/AcGBurZZ5+Vv7+/zpw5o02bNv3glwTx8fEKCAjQ1atXdfTo0QapHwAANF9uBXA/Pz/Fx8crLS2tRntaWhoT0gAAamjbtq0ee+wxvfjii3ruuec0ePBg+fj46OLFi9q+fbvefPNNbdiwQfn5+Q1yVTwsLEy/+MUv1LdvX1VVVWnLli369NNP73k7fJcuXTR16lR5eXnpyJEj2rlz5z379PPz07/8y79IUq2WPQMAAPhnbs+CvmbNGs2YMUPLli3TsGHD9P777+svf/mLjhw5ovDwcL366qs6d+6cPv74Y9c+GRkZkqS5c+cqOjpa//Vf/yU/Pz8NGDCgVsdkFnQAaB5u3bqlw4cPy2636+LFi672Dh06yGq1Ki4uTu3atfPoMQ3D0N69e7V7924ZhqHg4GBNmTJFnTt3vmvbrKwsbdy4UZL0xBNPuML2PysrK9OiRYtUVVWlGTNmuCahAwAAzUtD5FC3A7gkLV26VH/6059UWFioQYMGadGiRRoxYoQkadasWTp16pT27Nnzvwe5x/Ph4eHhOnXqVK2ORwAHgObFMAwVFhbKbrcrOzvbNVGaxWJRVFSUrFar+vbtKy+vOk1Vck+nTp3S+vXrdePGDfn6+mrChAmKiYm5a7v09HTt2rVLFotFU6dOVXR09F3bfP755/rHP/6hiIgIzZw502M1AgCApqPJBHCzEcABoPmqqKhQTk6OHA6Hzpw542pv27at4uLiZLVa1bFjR48c68aNG67b3iXpkUceUWJiYo11yw3D0NatW2W32+Xj46PnnntOYWFhNfopKSnRn//8ZzmdTs2dO/e+a44DAICHEwGcAA4AzVpRUZHsdrsyMzNVVlbmao+IiJDValX//v1rhOW6cDqd+vLLL/XVV19JkkJCQjR58mR16NChxjarV69WXl6eWrdurTlz5tz1JcCmTZuUmZmp/v37a8qUKfWqCQAAND0EcAI4ALQI1dXVOnbsmBwOh06cOOFqDwgI0ODBg2Wz2eq9+saJEye0YcMG3bp1S/7+/po4caL69evn+vOKigp9+OGHKiwsVMeOHTVnzhy1bt3a9eeXL1/W0qVLJUkvvPDCPZ8pBwAADy8COAEcAFqc0tJSORwOZWRkqLS01NUeGhoqq9WqQYMGyd/fv859r1+/XgUFBZKkoUOH6sc//rG8vb0lfX/L+gcffKDS0lL16NFDM2bMkK+vr2v/1atX69ixY7JarXrqqafqcZYAAKCpIYATwAGgxXI6nTp58qQcDoeOHj0qp9MpSfL19dXAgQNls9kUFhZ2z4k/76e6ulp///vftX//fknfL1/29NNPKygoSNL3V7qXL1+u27dvq3///nr66addk8OdPXtWKSkp8vLy0q9//Wt+RgEA0IwQwAngAABJN2/eVFZWlux2u4qKilztwcHBslqtio2NrXG7eG0cPXpUmzZtUnl5uVq1aqWkpCT16dNHknT69Gl98sknqq6u1tChQ5WYmOja78MPP9Tp06c1bNgwjRs3zjMnCAAAGh0BnAAOAPgnhmHo7NmzstvtOnLkiCorKyVJXl5e6t+/v6xWqyIjI2t9Vby4uFipqakqLCyUJCUkJGjUqFHy8vJSdna21q9fL0lKTEzU0KFDJX3/LPnf/vY3+fn5KTk5Wa1atWqAMwUAAGYjgBPAAQA/oLy8XNnZ2bLb7Tp//ryrPSgoSFarVXFxca7byu+nqqpK27dv16FDhyRJvXr10qRJk9S2bVt9/fXX2rlzpyRp8uTJGjBggAzD0HvvvaeLFy9q1KhRGjlyZMOc4P+v5fTp03e1/8d//IeWLFnSYMcFAKAlIoATwAEAtXDhwgU5HA5lZWXp9u3bkiSLxaI+ffrIarUqKirKNdHaDzl8+LC2bNmiyspKtW3bVpMmTVJ4eLi2bdumb7/9Vj4+Ppo5c6Z69OjhujreqlUrJScny8/Pr0HO6/Lly6qurna9z87O1tixY7V7926NGjWqQY4JAEBLRQAngAMA3FBZWamjR4/Kbrfr1KlTrvY2bdooNjZWVqv1vsuHXb58Wampqbp8+bIsFotGjx6t4cOHa+3atTp+/LhatWqlOXPmqEOHDnrnnXdUXFysn/zkJxoyZIgJZyclJydr69atysvLc3vyOQAAcH8EcAI4AKCOrl696lrO7MaNG672nj17ymazacCAATWWGLujoqJC27ZtU2ZmpiSpb9++Gj9+vFJTU3X+/Hl16NBBc+bMUW5urj777DMFBQXpV7/61QOvsNdXRUWFunfvrvnz5+u1115r0GMBANASEcAJ4ACAeqqurtaJEydkt9uVl5enOz8G/f39FRMTI5vNppCQkBr7GIYhh8Ohzz//XFVVVQoKCtKTTz6pbdu2qaSkRKGhoXr22We1ZMkS3bx5UxMnTlRsbGyDnsfatWs1ffp0nTlzRt27d2/QYwEA0BIRwAngAAAPunbtmjIzM2W321VSUuJq79atm2w2m2JiYhQQEOBqv3DhglJTU3X16lV5eXlp+PDh+vbbb3X79m1FR0crNDRUu3btUnBwsH75y1826G3hiYmJ8vPz05YtWxrsGAAAtGQEcAI4AKABGIahU6dOyW63Kzc31zXRmY+PjwYMGCCbzaaePXvKYrGovLxcmzdvVk5OjiQpPDxcBQUFcjqdslqtysnJUXl5uZ555hlFR0c3SL2nT59WZGSkNmzYoJ/+9KcNcgwAAFo6AjgBHADQwMrKynT48GHZ7XZdunTJ1d6pUydZrVbFxsaqTZs2+sc//qEdO3bI6XSqbdu2rufKe/XqpVOnTiksLEzPP/98g1wFf+ONN/Tee++poKBAPj4+Hu8fAAAQwAngAADTGIah8+fPy263Kzs7WxUVFZIkLy8vRUVFyWazKSAgQOvXr1dpaam8vLzkdDpd2zidTs2aNUvh4eEercvpdCoiIkLTpk3TH//4R4/2DQAA/hcBnAAOAGgEFRUVOnLkiOx2u86ePetqDwwM1MCBA1VYWFhjmbM7+vTpo9DQUBUWFiokJEQJCQn1nh19x44dSkxM1LFjxxQVFVWvvgAAwA8jgBPAAQCN7NKlS3I4HMrMzNStW7dc7R07dlRxcbH+74/Vd999VxcvXpQkhYWF6a233lJSUpKpNQMAAPcRwAngAIAmoqqqSseOHZPdbtfJkyd/cLucnBytXbtWklzPg69bt44QDgBAE0cAJ4ADAJqg4uJiZWRkyOFw6Pr16zX+zDAMpaSkuG5dt1gsCgsLU35+fr1vRwcAAA2nIXKol0d6AQCgBevQoYNGjx6t5ORkDRo0SLm5ua4J2SwWi55//nnXtoZhqKCgQOnp6Y1VLgAAaCSsXQIAgId4eXmpoqJCa9asUdu2bTVlyhT16NFDRUVFd21bWFjYCBUCAIDGRAAHAMCDQkJCJEk3btzQ8uXL1b59e127du0HtwMAAC0Ht6ADAOBBCQkJCgsLc024VlJS4rodXfr+lvQePXooISGhsUoEAACNhAAOAIAHeXt766233pL0v7Oe33Hn/eLFi5mADQCAFogADgCAhyUlJWndunUKDQ2t0R4WFsYSZAAAtGAsQwYAQAOprq5Wenq6CgsLFRISooSEBK58AwDwkGiIHMokbAAANBBvb2+NGjWqscsAAABNBLegAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGCCOgXwpUuXKiIiQgEBAYqPj1d6evp9t//yyy8VHx+vgIAARUZGatmyZXUqFgAAAACAh5XbAXzNmjVKTk7WggUL5HA4lJCQoCeeeEJnzpy55/b5+fkaP368EhIS5HA49Nprr+mll17S+vXr6108AAAAAAAPC4thGIY7OwwZMkQ2m03vvvuuq61///6aOHGiFi5ceNf2v/3tb7V582bl5ua62ubNm6fMzEzt37+/Vse8du2agoKCVFpaqsDAQHfKBQAAAADAbQ2RQ33c2biiokKHDh3SK6+8UqN93Lhx2rdv3z332b9/v8aNG1ejLTExUSkpKaqsrJSvr+9d+5SXl6u8vNz1vrS0VNL3fwEAAAAAADS0O/nTzWvW9+VWAC8qKlJ1dbW6du1ao71r1666cOHCPfe5cOHCPbevqqpSUVGRQkJC7tpn4cKF+v3vf39Xe48ePdwpFwAAAACAerly5YqCgoI80pdbAfwOi8VS471hGHe1PWj7e7Xf8eqrr2r+/Pmu9yUlJQoPD9eZM2c8duJAU3Pt2jX16NFDBQUFPGqBZotxjpaAcY6WgHGOlqC0tFQ9e/ZUx44dPdanWwG8c+fO8vb2vutq96VLl+66yn1Ht27d7rm9j4+POnXqdM99/P395e/vf1d7UFAQ/8HR7AUGBjLO0ewxztESMM7REjDO0RJ4eXlu9W63evLz81N8fLzS0tJqtKelpWn48OH33GfYsGF3bb9jxw498sgj93z+GwAAAACA5sjtKD9//nx98MEHWr58uXJzc/Xyyy/rzJkzmjdvnqTvbx+fOXOma/t58+bp9OnTmj9/vnJzc7V8+XKlpKToN7/5jefOAgAAAACAJs7tZ8CnTp2qK1eu6A9/+IMKCws1aNAgbdu2TeHh4ZKkwsLCGmuCR0REaNu2bXr55Ze1ZMkSde/eXW+//bYmTZpU62P6+/vr9ddfv+dt6UBzwThHS8A4R0vAOEdLwDhHS9AQ49ztdcABAAAAAID7PPc0OQAAAAAA+EEEcAAAAAAATEAABwAAAADABARwAAAAAABM0GQC+NKlSxUREaGAgADFx8crPT39vtt/+eWXio+PV0BAgCIjI7Vs2TKTKgXqzp1xXlhYqOnTpys6OlpeXl5KTk42r1CgHtwZ5xs2bNDYsWMVHByswMBADRs2TF988YWJ1QJ1484437t3r370ox+pU6dOatWqlfr166dFixaZWC1QN+7+fn7H119/LR8fH8XFxTVsgYAHuDPO9+zZI4vFctfr6NGjtT5ekwjga9asUXJyshYsWCCHw6GEhAQ98cQTNZYz+2f5+fkaP368EhIS5HA49Nprr+mll17S+vXrTa4cqD13x3l5ebmCg4O1YMECxcbGmlwtUDfujvOvvvpKY8eO1bZt23To0CGNHj1aEyZMkMPhMLlyoPbcHedt2rTRiy++qK+++kq5ubn63e9+p9/97nd6//33Ta4cqD13x/kdpaWlmjlzpsaMGWNSpUDd1XWcHzt2TIWFha5X3759a33MJrEM2ZAhQ2Sz2fTuu++62vr376+JEydq4cKFd23/29/+Vps3b1Zubq6rbd68ecrMzNT+/ftNqRlwl7vj/J+NGjVKcXFxWrx4cQNXCdRPfcb5HQMHDtTUqVP13//93w1VJlAvnhjnSUlJatOmjT755JOGKhOol7qO82eeeUZ9+/aVt7e3Nm3apIyMDBOqBerG3XG+Z88ejR49WsXFxWrfvn2djtnoV8ArKip06NAhjRs3rkb7uHHjtG/fvnvus3///ru2T0xM1LfffqvKysoGqxWoq7qMc+Bh44lx7nQ6df36dXXs2LEhSgTqzRPj3OFwaN++fRo5cmRDlAjUW13H+YoVK/Tdd9/p9ddfb+gSgXqrz+e51WpVSEiIxowZo927d7t1XB+3K/WwoqIiVVdXq2vXrjXau3btqgsXLtxznwsXLtxz+6qqKhUVFSkkJKTB6gXqoi7jHHjYeGKcv/nmm7p586amTJnSECUC9VafcR4WFqbLly+rqqpKb7zxhubOnduQpQJ1VpdxnpeXp1deeUXp6eny8Wn0iAE8UF3GeUhIiN5//33Fx8ervLxcn3zyicaMGaM9e/ZoxIgRtTpuk/nfYbFYarw3DOOutgdtf692oClxd5wDD6O6jvNVq1bpjTfe0KeffqouXbo0VHmAR9RlnKenp+vGjRs6cOCAXnnlFfXp00fTpk1ryDKBeqntOK+urtb06dP1+9//XlFRUWaVB3iEO5/n0dHRio6Odr0fNmyYCgoK9D//8z8PTwDv3LmzvL297/qW4dKlS3d9G3FHt27d7rm9j4+POnXq1GC1AnVVl3EOPGzqM87XrFmjOXPmKDU1VT/+8Y8bskygXuozziMiIiRJMTExunjxot544w0COJokd8f59evX9e2338rhcOjFF1+U9P0jRYZhyMfHRzt27NDjjz9uSu1AbXnq9/OhQ4fqr3/9a623b/RnwP38/BQfH6+0tLQa7WlpaRo+fPg99xk2bNhd2+/YsUOPPPKIfH19G6xWoK7qMs6Bh01dx/mqVas0a9YsrVy5Uk8++WRDlwnUi6c+zw3DUHl5uafLAzzC3XEeGBiow4cPKyMjw/WaN2+eoqOjlZGRoSFDhphVOlBrnvo8dzgc7j0CbTQBq1evNnx9fY2UlBQjJyfHSE5ONtq0aWOcOnXKMAzDeOWVV4wZM2a4tj958qTRunVr4+WXXzZycnKMlJQUw9fX11i3bl1jnQLwQO6Oc8MwDIfDYTgcDiM+Pt6YPn264XA4jCNHjjRG+UCtuDvOV65cafj4+BhLliwxCgsLXa+SkpLGOgXggdwd5++8846xefNm4/jx48bx48eN5cuXG4GBgcaCBQsa6xSAB6rL7y3/7PXXXzdiY2NNqhaoG3fH+aJFi4yNGzcax48fN7Kzs41XXnnFkGSsX7++1sds9FvQJWnq1Km6cuWK/vCHP6iwsFCDBg3Stm3bFB4eLkkqLCyssRZbRESEtm3bppdffllLlixR9+7d9fbbb2vSpEmNdQrAA7k7zqXvZ1i849ChQ1q5cqXCw8N16tQpM0sHas3dcf7ee++pqqpKL7zwgl544QVX+3PPPacPP/zQ7PKBWnF3nDudTr366qvKz8+Xj4+PevfurT/+8Y/6xS9+0VinADxQXX5vAR427o7ziooK/eY3v9G5c+fUqlUrDRw4UJ999pnGjx9f62M2iXXAAQAAAABo7hr9GXAAAAAAAFoCAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAmIIADAAAAAGACAjgAAAAAACYggAMAAAAAYAICOAAAAAAAJiCAAwAAAABgAgI4AAAAAAAm+H/9vHO5n/+S5gAAAABJRU5ErkJggg==" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 175 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-11T19:38:23.029966Z", - "start_time": "2025-07-11T19:38:23.024656Z" - } - }, - "cell_type": "code", - "source": [ - "q = []\n", - "d = len(user_values[0])\n", - "for i in range(n_users):\n", - " other_values = user_values[list(connections[i])]\n", - " user_value = user_values[i]\n", - " user_q = 1 - (norm(other_values - user_values[i], axis=1) / np.sqrt(d)) ** .2 # user_q = np.exp(-10 * norm(other_values - user_value, axis=1))\n", - " # We are utilitarian but still give more importance to like-minded people\n", - " # (whose values are closer to the target (0, 0))\n", - " user_q /= norm(user_value) ** 2\n", - " q.append(user_q)\n", - "\n", - "print(connections)\n", - "q = np.array(q)\n", - "q" - ], - "id": "initial_id", - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{0: {2, 4, 6, 7}, 1: {2, 4, 5, 6}, 2: {0, 1, 4, 5}, 3: {4, 5, 6, 7}, 4: {0, 1, 2, 3}, 5: {1, 2, 3, 7}, 6: {0, 1, 3, 7}, 7: {0, 3, 5, 6}}\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[11.43141733, 11.10411335, 12.04007139, 10.27768479],\n", - " [ 7.86251292, 8.25959871, 8.20670746, 7.80455785],\n", - " [33.65984787, 31.68745496, 34.45818697, 32.10615569],\n", - " [30.13716994, 28.95415839, 31.67817728, 27.73244701],\n", - " [22.92927319, 23.34421467, 24.16499761, 23.31325723],\n", - " [ 7.57933639, 7.35740309, 7.31902691, 6.87557107],\n", - " [16.36282563, 14.51748755, 16.12811129, 13.91023066],\n", - " [13.38402715, 13.52925221, 13.26942118, 13.32897048]])" - ] - }, - "execution_count": 173, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 173 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-11T17:45:29.368669Z", - "start_time": "2025-07-11T17:45:29.366702Z" - } - }, - "cell_type": "code", - "source": [ - "Q = float(q.sum().sum())\n", - "print(n_users, 'users')\n", - "print('Mean Q:', Q / n_users)\n", - "print('Q:', Q)" - ], - "id": "5ea44a6fcee34c82", - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "8 users\n", - "Mean Q: 1.428071218800166\n", - "Q: 11.424569750401329\n" - ] - } - ], - "execution_count": 165 - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/notebooks/meeting_rational_all.ipynb b/notebooks/meeting_rational_all.ipynb deleted file mode 100644 index 51e403a9..00000000 --- a/notebooks/meeting_rational_all.ipynb +++ /dev/null @@ -1,435 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "id": "f0fca831fd4bce0b", - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-23T19:04:00.406284Z", - "start_time": "2025-07-23T19:01:57.060729Z" - } - }, - "source": [ - "import pandas as pd\n", - "from numpy.linalg import norm\n", - "import numpy as np\n", - "\n", - "import random\n", - "from collections import defaultdict\n", - "\n", - "n_connections_per_person = 10\n", - "n_people = 50_000\n", - "\n", - "# value alignment for each person\n", - "d = 2\n", - "values = np.random.random((n_people, d))\n", - "\n", - "results = {}\n", - "\n", - "# value openness\n", - "tries = np.linspace(0.02, .3, 10)\n", - "for selectivity in tries:\n", - " accepted = norm(values, axis=1) / np.sqrt(d) < selectivity\n", - " user_values = values[accepted]\n", - " n_users = len(user_values)\n", - "\n", - " def make_connections(n, n_connections_per_person):\n", - " \"\"\"\n", - " Generate a symmetric undirected graph where each person has exactly\n", - " `n_connections_per_person` mutual connections.\n", - "\n", - " Assumes:\n", - " - n_connections_per_person < n\n", - " - (n * n_connections_per_person) must be even (required for undirected graph)\n", - "\n", - " Returns:\n", - " A dict mapping each person to a set of their connected people.\n", - " \"\"\"\n", - " if n_connections_per_person >= n:\n", - " raise ValueError(\"Each person must have fewer connections than total people.\")\n", - "\n", - " if (n * n_connections_per_person) % 2 != 0:\n", - " raise ValueError(\"Total number of connections must be even for mutual pairs.\")\n", - "\n", - " attempts = 0\n", - " max_attempts = 10000 # to prevent infinite loops\n", - "\n", - " while True:\n", - " # Clear previous attempts\n", - " connections = defaultdict(set)\n", - "\n", - " people = list(range(n))\n", - " success = True\n", - "\n", - " for i in people:\n", - " while len(connections[i]) < n_connections_per_person:\n", - " possible = list(set(people) - connections[i] - {i})\n", - " possible = [p for p in possible if len(connections[p]) < n_connections_per_person]\n", - " if not possible:\n", - " success = False\n", - " break\n", - " j = random.choice(possible)\n", - " connections[i].add(j)\n", - " connections[j].add(i)\n", - "\n", - " # if not success:\n", - " # break\n", - "\n", - " if success:\n", - " break\n", - "\n", - " attempts += 1\n", - " # print(attempts)\n", - " if attempts > max_attempts:\n", - " raise RuntimeError(\"Failed to generate a valid connection graph after many attempts.\")\n", - "\n", - " lens = [len(x) for x in connections.values() if len(x) != n_connections_per_person]\n", - " print(lens)\n", - " # print(lens)\n", - " # plt.figure(figsize=(5, 5))\n", - " # plt.hist(lens, bins=100)\n", - " # plt.show()\n", - "\n", - " return dict(connections)\n", - "\n", - " connections = make_connections(len(user_values), n_connections_per_person=n_connections_per_person)\n", - "\n", - " import numpy as np\n", - " import matplotlib.pyplot as plt\n", - "\n", - " def plot_connections(connections):\n", - " # n = len(connections)\n", - " # angles = np.linspace(0, 2 * np.pi, n, endpoint=False)\n", - " # positions = {i: (np.cos(a), np.sin(a)) for i, a in enumerate(angles)}\n", - " positions = {i: a for i, a in enumerate(user_values)}\n", - "\n", - " fig, ax = plt.subplots(figsize=(12, 12))\n", - " ax.set_xlim(0, selectivity)\n", - " ax.set_ylim(0, selectivity)\n", - " # ax.set_aspect('equal')\n", - " # ax.axis('off')\n", - "\n", - " # Draw nodes\n", - " for i, (x, y) in positions.items():\n", - " ax.plot(x, y, 'o', color='black')\n", - " ax.text(x * 1.05, y * 1.05, str(i), ha='center', va='center')\n", - "\n", - " # Draw edges\n", - " drawn = set()\n", - " for i, neighbors in connections.items():\n", - " for j in neighbors:\n", - " if str((j, i)) not in drawn:\n", - " x0, y0 = positions[i]\n", - " x1, y1 = positions[j]\n", - " ax.plot([x0, x1], [y0, y1], color='gray')\n", - " drawn.add(str((i, j)))\n", - "\n", - " plt.title(\"Connections on Unit Circle\")\n", - " plt.show()\n", - "\n", - " # plot_connections(connections)\n", - "\n", - " q = []\n", - " for i in range(n_users):\n", - " other_values = user_values[list(connections[i])]\n", - " user_value = user_values[i]\n", - " user_q = 1 - (norm(other_values - user_values[i], axis=1) / np.sqrt(d)) ** .2\n", - " # user_q = np.exp(-10 * norm(other_values - user_value, axis=1))\n", - " # We are utilitarian but still give more importance to like-minded people\n", - " # (whose values are closer to the target (0, 0))\n", - " # user_q /= norm(user_value) ** 2\n", - " # print(user_q)\n", - " user_q = np.clip(user_q / 10000, 0, 1)\n", - " q.append(user_q)\n", - "\n", - " # print(connections)\n", - " q = np.array(q)\n", - " Q = float(q.sum().sum())\n", - " print(n_users, 'users')\n", - " print('Mean Q:', Q / n_users)\n", - " print('Q:', Q)\n", - " results[selectivity] = (Q, n_users, Q / n_users)\n", - "\n", - "results" - ], - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[]\n", - "32 users\n", - "Mean Q: 0.0006084262563549525\n", - "Q: 0.01946964020335848\n", - "[]\n", - "209 users\n", - "Mean Q: 0.0005338180983010117\n", - "Q: 0.11156798254491143\n", - "[]\n", - "528 users\n", - "Mean Q: 0.0004895787094351725\n", - "Q: 0.25849755858177104\n", - "[]\n", - "999 users\n", - "Mean Q: 0.00045690902684389974\n", - "Q: 0.45645211781705586\n", - "[]\n", - "1625 users\n", - "Mean Q: 0.00042897726875680336\n", - "Q: 0.6970880617298054\n", - "[]\n", - "2433 users\n", - "Mean Q: 0.00040737235242289407\n", - "Q: 0.9911369334449013\n", - "[]\n", - "3381 users\n", - "Mean Q: 0.00038626885877638686\n", - "Q: 1.305975011522964\n", - "[]\n", - "4508 users\n", - "Mean Q: 0.00036957625446330247\n", - "Q: 1.6660497551205675\n", - "[]\n", - "5833 users\n", - "Mean Q: 0.0003531213285522714\n", - "Q: 2.059756709445399\n", - "[]\n", - "7195 users\n", - "Mean Q: 0.0003393996132746142\n", - "Q: 2.441980217510849\n" - ] - }, - { - "data": { - "text/plain": [ - 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" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 3 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-23T19:04:00.685092Z", - "start_time": "2025-07-23T19:04:00.493140Z" - } - }, - "cell_type": "code", - "source": [ - "fig, (ax, ax2) = plt.subplots(2, 1, sharex=True)\n", - "Q = df.iloc[:, 0]\n", - "Q.plot(ax=ax, marker='o')\n", - "ax.set_ylabel('User Benefit')\n", - "ax.set_ylim(0, Q.max() * 1.1)\n", - "\n", - "x = df.iloc[:, 1] / n_people * 100\n", - "x.plot(ax=ax2, marker='o')\n", - "ax2.set_ylabel('User ratio (in %)')\n", - "# ax2.set_ylim(0, 100)\n", - "plt.show()" - ], - "id": "c8fe7e7ca2a21678", - "outputs": [ - { - "data": { - "text/plain": [ - "
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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 4 - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/notebooks/meeting_rational_qualitative.ipynb b/notebooks/meeting_rational_qualitative.ipynb deleted file mode 100644 index 30e1c8db..00000000 --- a/notebooks/meeting_rational_qualitative.ipynb +++ /dev/null @@ -1,75 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "id": "f0fca831fd4bce0b", - "metadata": { - "ExecuteTime": { - "end_time": "2025-07-23T19:08:52.269336Z", - "start_time": "2025-07-23T19:08:51.671185Z" - } - }, - "source": [ - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pandas as pd\n", - "from numpy.linalg import norm\n", - "\n", - "results = {}\n", - "\n", - "selectivity = np.linspace(0.01, 1, 100)\n", - "\n", - "quality = selectivity\n", - "quantity = 100 * (1 - selectivity)\n", - "utility = quality * quantity\n", - "\n", - "\n", - "fig, ax = plt.subplots(3, 1, sharex=True)\n", - "ax[0].set_title(\"Qualitative explanation\")\n", - "ax[0].plot(selectivity, quality)\n", - "ax[0].set_ylabel(\"Quality\")\n", - "ax[1].plot(selectivity, quantity)\n", - "ax[1].set_ylabel(\"Quantity\")\n", - "ax[2].plot(selectivity, utility)\n", - "ax[2].set_ylabel(\"App Benefit\")\n", - "ax[2].set_xlabel(\"Selectivity\")\n", - "plt.savefig(\"rational_qualitative.png\")\n", - "plt.show()" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
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" 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