\n",
"\n",
"# Bicycling Statistics\n",
"\n",
- "During a pandemic, bicycling is a great way to (1) spend some time, (2) get some exercise, (3) stay outside and be safe, and (4) track how you are progressing against your goals. My data comes from [Strava](https://www.strava.com/athletes/575579). At various times I've had various goals:\n",
+ "During a pandemic, bicycling is a great way to (1) spend some time, (2) get some exercise, (3) stay outside and be safe. In this notebook I track [my cycling performance](https://www.strava.com/athletes/575579) against various goals:\n",
"- **Distance**: I do about 6,000 miles a year.\n",
"- **Climbing**: In 2022, I climbed to *space* (100 km of total elevation gain).\n",
"- **Explorer Tiles**: In 2022, I started tracking the 1-mile-square [explorer tiles](https://rideeverytile.com/) I have visited.\n",
"- **Wandering**: In 2020, I started using [Wandrer.earth](https://wandrer.earth/athletes/3534/) to track what new roads I have ridden.\n",
- "- **Eddington Number**: I've done 67 miles or more on 67 different days. So 67 is my Eddington Number.\n",
+ "- **Eddington Number**: I've done 68 miles or more on 68 different days. So 68 is my Eddington Number.\n",
"- **Speed**: I'm not going particularly fast, but I am interested in understanding how my speed varies with the steepness of the hill.\n",
"\n",
"This notebook is mostly for my own benefit, but if you're a cyclist you're welcome to adapt it to your own data, and if you're a data scientist, you might find it an interesting example of exploratory data analysis. The companion notebook [**BikeCode.ipynb**](BikeCode.ipynb) has the implementation details."
@@ -25,12 +25,12 @@
"source": [
"# Yearly Totals\n",
"\n",
- "Here are my overall stats for each year since I started keeping track in mid-2014. I have done 6,000 miles per year since 2016, except for 2020 when an injury kept me sidelined for two months. The columns keep track of speed/distance (**mph** is the speed, computed as the quotient of **miles* and **hours**; **kms** is the metric conversion of **miles**) and climbing (**feet** is the total height climbed (or **km_up** in metric), **vam** is vertical meters ascended per hour, **fpm** is average feet ascended per mile and **pct** is average grade of climbing (**fpm** × 100 / 5280).\n"
+ "Here are my overall stats for each year since I started keeping track in mid-2014. I have done 6,000 miles per year since 2016, except for 2020 when an injury kept me sidelined for two months. The columns keep track of the total **hours** on the bike, distance traveled in **miles**, and total **feet** climbed. Then there are some columns that are dervided from these: **mph** is **miles / hour**; **vam** is vertical meters ascended per hour (or **feet × 0.3048 / hours**); **fpmi** is **feet / miles**; **pct** is the grade in percent (or **feet × 100 / miles / 5280**), and finally **kms** and **meters** are the metric equivalents of **miles** and **feet**.\n"
]
},
{
"cell_type": "code",
- "execution_count": 92,
+ "execution_count": 85,
"metadata": {},
"outputs": [
{
@@ -60,15 +60,28 @@
"
\n",
" \n",
"\n",
""
],
"text/plain": [
- " year hours miles feet mph vam fpm pct kms km_up\n",
- " 2022 1.5 17.2 1035.2 11.31 207.0 60.0 1.14 27.7 0.315\n",
- " 2021 1.4 17.3 561.8 12.36 122.0 32.0 0.61 27.9 0.171\n",
- " 2020 1.3 15.3 270.8 12.17 66.0 18.0 0.34 24.6 0.083\n",
- " 2019 1.4 17.2 428.0 12.63 96.0 25.0 0.47 27.7 0.131\n",
- " 2018 1.4 17.4 453.3 12.82 102.0 26.0 0.49 28.0 0.138\n",
- " 2017 1.6 21.0 577.4 12.97 109.0 27.0 0.52 33.8 0.176\n",
- " 2016 1.4 18.1 575.6 13.03 126.0 32.0 0.60 29.1 0.175\n",
- " 2015 1.2 15.6 599.6 12.98 152.0 38.0 0.73 25.1 0.183\n",
- " 2014 0.5 7.1 338.5 12.92 189.0 48.0 0.91 11.4 0.103"
+ " year hours miles feet mph vam fpmi pct kms meters\n",
+ " 2023 1.7 20.2 779.2 11.66 137.0 38.0 0.73 32.6 237.5\n",
+ " 2022 1.7 19.3 1161.3 11.31 207.0 60.0 1.14 31.1 354.0\n",
+ " 2021 1.6 19.4 630.2 12.36 122.0 32.0 0.61 31.3 192.1\n",
+ " 2020 1.4 17.1 303.8 12.17 66.0 18.0 0.34 27.5 92.6\n",
+ " 2019 1.5 19.3 480.1 12.63 96.0 25.0 0.47 31.0 146.3\n",
+ " 2018 1.5 19.6 508.5 12.82 102.0 26.0 0.49 31.5 155.0\n",
+ " 2017 1.8 23.6 647.7 12.97 109.0 27.0 0.52 37.9 197.4\n",
+ " 2016 1.6 20.3 645.7 13.03 126.0 32.0 0.60 32.7 196.8\n",
+ " 2015 1.3 17.5 672.6 12.98 152.0 38.0 0.73 28.1 205.0\n",
+ " 2014 0.6 7.9 379.7 12.92 189.0 48.0 0.91 12.7 115.7"
]
},
- "execution_count": 93,
+ "execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
@@ -407,7 +435,7 @@
"source": [
"# Climbing \n",
"\n",
- "In 2022 my friend [A. J. Jacobs](https://ajjacobs.com/) set a goal of **walking to space**: climbing a total elevation equal to the distance from the Earth's surface to the top of the atmoshere. [A group](https://www.facebook.com/groups/260966686136038) of about 40 of us joined the quest. The boundary of \"space\" is vague, but could is often reckoned as either 100 km (the [Kármán line](https://en.wikipedia.org/wiki/K%C3%A1rm%C3%A1n_line)) or [50 miles](https://science.nasa.gov/edge-space); in 2022 I surpassed 100 kilometers of climbing (over 1,000 feet per day), but most years I'm closer to 60 kilometers (about 600 feet per day)."
+ "In 2022 my friend [A. J. Jacobs](https://ajjacobs.com/) set a goal of **walking to space**: climbing a total elevation equal to the distance from the Earth's surface to the top of the atmoshere. [A group](https://www.facebook.com/groups/260966686136038) of about 40 of us joined the quest. The boundary of \"space\" is vague, but the [Kármán line](https://en.wikipedia.org/wiki/K%C3%A1rm%C3%A1n_line)) is 100 kilometers; in 2022 I surpassed 100 kilometers of climbing (over 1,100 feet per day), but most years I'm closer to 60 kilometers (about 600 feet per day)."
]
},
{
@@ -419,18 +447,18 @@
"# Explorer Tiles\n",
"\n",
"\n",
- "The [OpenStreetMap](https://www.openstreetmap.org/) world map is divided into **[explorer tiles](https://www.statshunters.com/faq-10-what-are-explorer-tiles)** of approximately 1 mile square. Sites like [Veloviewer](https://veloviewer.com) and [Statshunter](https://www.statshunters.com/) challenge bicyclist/hikers to record which tiles they have passed through. The process is gamified to highlight the following statistics:\n",
+ "The [OpenStreetMap](https://www.openstreetmap.org/) world map is divided into **[explorer tiles](https://www.statshunters.com/faq-10-what-are-explorer-tiles)** of approximately 1 mile square. Sites like [Veloviewer](https://veloviewer.com) and [Statshunter](https://www.statshunters.com/ and [RideEveryTile](https://rideeverytile.com/) and [SquadRats](https://squadrats.com/map) challenge bicyclist/hikers to record which tiles they have passed through. The process is gamified to highlight the following statistics:\n",
"- The largest **square** (an *n* × *n* array of visited ties). \n",
"- The maximum **cluster** (a set of contiguous interior visited tiles, where \"interior\" means surrounded by visited tiles).\n",
"- The **total** number of visited tiles.\n",
" \n",
"\n",
- "Since I live on a penninsula, it is not easy for me to form a large square, and I sometimes have to work hard to connect different parts of my map (such as connecting San Francisco and Marin). I have a [separrate page]() documenting my explorations, but here are a few key points along the way:"
+ "Since I live on a penninsula, it is not easy for me to form a large square, and I sometimes have to work hard to connect different parts of my map into my main cluster (such as connecting San Francisco and Marin). I have a [separate page](???) documenting my explorations, but here are a few key points along the way:"
]
},
{
"cell_type": "code",
- "execution_count": 94,
+ "execution_count": 87,
"metadata": {},
"outputs": [
{
@@ -438,74 +466,98 @@
"text/html": [
"\n",
- "
\n"
],
"text/plain": [
- ""
+ ""
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- "execution_count": 94,
+ "execution_count": 87,
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}
@@ -522,164 +574,1674 @@
"\n",
"The website [**Wandrer.earth**](https://wandrer.earth) tracks the distinct roads a user has biked on. It provides a fun incentive to get out and explore new roads. The site is gamified in a way that there is a reward for first reaching 25% of the road-miles in each city, and further rewards for higher percentages. (You get no credit for repeating a road you've already been on.) \n",
"\n",
- "The wandrer.earth site does a good job of showing my current status, but it requires clicking around a bit, so I summarize it all in one place here. Each line gives the county (e.g. SMC for San Mateo County); city preceeded by the percentage of roads I've rode there; miles rode/total miles in city; and miles to go to the next big reward level."
+ "The wandrer.earth site does a good job of showing my current status, but it requires clicking around a bit, so I summarize it all in one place here. Each line gives the percent of roads/trails that I have traveled on for each place (specified by **county** and city **name**), as well as the **total** miles of road in the place, the miles I have **done**, and the amount I need to hit the **next badge**. "
]
},
{
"cell_type": "code",
- "execution_count": 95,
+ "execution_count": 88,
"metadata": {},
"outputs": [
{
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "SMC 100.0% Los Trancos OSP 0.3/0.3 mi \n",
- "SMC 99.9% Los Trancos Woods 5.3/5.3 mi \n",
- "SMC 99.9% Menlo Oaks 3.5/3.5 mi \n",
- "SMC 99.9% Kensington Square 0.6/0.6 mi \n",
- "SMC 99.9% Ladera 8.1/8.1 mi \n",
- "SMC 99.9% Palomar Park 4.0/4.0 mi \n",
- "SMC 99.8% North Fair Oaks 27/27 mi \n",
- "SMC 99.8% Emerald Lake Hills 25/25 mi \n",
- "SMC 99.8% West Menlo Park 11/11 mi \n",
- "SMC 99.8% Atherton 56/56 mi \n",
- "SMC 99.7% Sequoia Tract 11/11 mi \n",
- "SCC 99.6% Los Altos 138/138 mi \n",
- "SCC 99.6% Loyola 18/18 mi \n",
- "SMC 99.6% East Palo Alto 48/48 mi \n",
- "SMC 99.5% Menlo Park 139/140 mi \n",
- "SMC 99.5% Woodside 75/75 mi \n",
- "SMC 99.5% Portola Valley 48/48 mi \n",
- "SMC 99.4% Sky Londa 12/12 mi \n",
- "SCC 99.4% Los Altos Hills 91/91 mi \n",
- "SMC 99.3% Redwood City 239/240 mi \n",
- "SCC 99.2% Mountain View 206/208 mi \n",
- "SMC 99.1% Windy Hill Preserve 4.1/4.1 mi \n",
- "SMC 99.0% San Carlos 98/99 mi \n",
- "SCC 99.0% Palo Alto 294/297 mi \n",
- "SMC 91.6% Burleigh Murray Park 1.9/2.1 mi 0.2 mi for 99%\n",
- "SCC 86.8% Foothills Preserve 1.0/1.1 mi 0.0 mi for 90%\n",
- "SMC 80.7% Foster City 121/150 mi 14 mi for 90%\n",
- "SMC 77.9% San Mateo Highlands 14/18 mi 2.2 mi for 90%\n",
- "SMC 74.9% Skyline Ridge OSP 0.6/0.8 mi 0.1 mi for 90%\n",
- "SMC 71.4% Burlingame Hills 4.3/6.0 mi 1.1 mi for 90%\n",
- "SMC 66.7% Coal Creek Preserve 2.6/3.9 mi 0.9 mi for 90%\n",
- "SCC 62.7% San Francisco Bay Trail 164/261 mi 71 mi for 90%\n",
- "--- 61.6% San Mateo County 1,732/2,814 mi 800 mi for 90%\n",
- "SMC 54.3% Burlingame 48/88 mi 32 mi for 90%\n",
- "SMC 54.2% Belmont 53/98 mi 35 mi for 90%\n",
- "SCC 52.4% Sunnyvale 187/357 mi 134 mi for 90%\n",
- "SMC 52.3% Hillsborough 45/85 mi 32 mi for 90%\n",
- "SMC 51.8% San Mateo 133/256 mi 98 mi for 90%\n",
- "SMC 51.5% Half Moon Bay State Beach 2.3/4.4 mi 1.7 mi for 90%\n",
- "SMC 51.2% Russian Ridge Preserve 6.2/12 mi 4.7 mi for 90%\n",
- "SMC 51.2% Long Ridge Preserve 5.6/11 mi 4.3 mi for 90%\n",
- "SCC 51.2% Castle Rock State Park 5.7/11 mi 4.3 mi for 90%\n",
- "NSW 47.3% Barangaroo 0.8/1.7 mi 0.0 mi for 50%\n",
- "SCC 47.2% Gardner 11/23 mi 0.7 mi for 50%\n",
- "SCC 47.0% Edenvale 14/30 mi 0.9 mi for 50%\n",
- "SMC 46.7% Brisbane 19/41 mi 1.3 mi for 50%\n",
- "ALA 45.9% Newark 67/147 mi 6.0 mi for 50%\n",
- "SCC 44.7% Monte Sereno 9.1/20 mi 1.1 mi for 50%\n",
- "SMC 44.3% Moss Beach 8.7/20 mi 1.1 mi for 50%\n",
- "SFC 43.9% Presidio Terrace 1.2/2.8 mi 0.2 mi for 50%\n",
- "ALA 43.3% Hayward Acres 1.5/3.5 mi 0.2 mi for 50%\n",
- "ALA 40.8% San Lorenzo 23/56 mi 5.1 mi for 50%\n",
- "SMC 40.8% Millbrae 27/65 mi 6.0 mi for 50%\n",
- "SFC 39.6% Lincoln Park 1.8/4.5 mi 0.5 mi for 50%\n",
- "SCC 39.5% Communications Hill 11/28 mi 2.9 mi for 50%\n",
- "SMC 38.7% Purisima Creek Preserve 6.4/16 mi 1.9 mi for 50%\n",
- "MAR 38.7% Mt Tamalpais State Park 12/32 mi 3.6 mi for 50%\n",
- "SMC 38.4% El Granada 19/49 mi 5.7 mi for 50%\n",
- "SMC 38.3% Colma 5.2/14 mi 1.6 mi for 50%\n",
- "SMC 38.2% Broadmoor 3.4/8.8 mi 1.0 mi for 50%\n",
- "SFC 37.4% South Beach 1.8/4.8 mi 0.6 mi for 50%\n",
- "SCC 37.3% Milpitas 84/224 mi 28 mi for 50%\n",
- "MAR 37.1% Muir Beach 1.7/4.6 mi 0.6 mi for 50%\n",
- "SFC 36.8% Lake Street 1.4/3.9 mi 0.5 mi for 50%\n",
- "SCC 35.7% Spartan Keyes 23/64 mi 9.2 mi for 50%\n",
- "ALA 35.7% Ashland 13/35 mi 5.0 mi for 50%\n",
- "SCC 34.9% Willow Glen 28/82 mi 12 mi for 50%\n",
- "MAS 34.7% MIT 3.3/9.6 mi 1.5 mi for 50%\n",
- "NSW 34.3% Millers Point 1.1/3.2 mi 0.5 mi for 50%\n",
- "SCC 34.0% Santa Clara 118/348 mi 56 mi for 50%\n",
- "SCC 33.6% Seven Trees 14/41 mi 6.7 mi for 50%\n",
- "SCC 33.4% Parkview 14/42 mi 7.1 mi for 50%\n",
- "SCC 33.2% Cupertino 57/172 mi 29 mi for 50%\n",
- "SCC 33.2% Los Gatos 49/148 mi 25 mi for 50%\n",
- "MAR 32.9% Stinson Beach 3.7/11 mi 1.9 mi for 50%\n",
- "--- 32.8% Santa Clara County 2,483/7,569 mi 1,302 mi for 50%\n",
- "SMC 32.7% Montara 9.1/28 mi 4.8 mi for 50%\n",
- "SMC 32.7% Pacifica 49/151 mi 26 mi for 50%\n",
- "SCC 32.7% Branham 14/44 mi 7.6 mi for 50%\n",
- "SMC 32.2% Half Moon Bay 22/68 mi 12 mi for 50%\n",
- "ALA 32.2% Fremont 251/780 mi 139 mi for 50%\n",
- "MAR 31.9% Marin Headlands GGNRA 21/66 mi 12 mi for 50%\n",
- "SCC 31.1% San Martin 11/35 mi 6.7 mi for 50%\n",
- "SCC 30.7% Forest of Nisene Marks SP 14/44 mi 8.5 mi for 50%\n",
- "ALA 30.7% Union City 64/209 mi 40 mi for 50%\n",
- "SCC 30.5% Willow Glen South 19/63 mi 12 mi for 50%\n",
- "ALA 30.0% Hayward 133/444 mi 89 mi for 50%\n",
- "SCC 29.7% Saratoga 53/180 mi 37 mi for 50%\n",
- "SMC 29.5% San Bruno 34/114 mi 23 mi for 50%\n",
- "SFC 29.4% Golden Gate Park 12/41 mi 8.4 mi for 50%\n",
- "SFC 29.3% Seacliff 1.2/4.1 mi 0.8 mi for 50%\n",
- "CCC 29.3% Rosie Riveter Park 1.6/5.5 mi 1.1 mi for 50%\n",
- "NSW 29.2% Dawes Point 0.5/1.8 mi 0.4 mi for 50%\n",
- "SCC 28.8% Campbell 34/119 mi 25 mi for 50%\n",
- "SCC 27.7% San Jose 725/2,619 mi 584 mi for 50%\n",
- "ALA 27.5% San Leandro 63/231 mi 52 mi for 50%\n",
- "SMC 27.2% South San Francisco 50/185 mi 42 mi for 50%\n",
- "SMC 27.2% Daly City 40/148 mi 34 mi for 50%\n",
- "ALA 27.1% Cherryland 5.7/21 mi 4.8 mi for 50%\n",
- "CAL 26.8% Mokelumne Hill 3.9/15 mi 3.4 mi for 50%\n",
- "SFC 26.7% Presidio National Park 12/44 mi 10 mi for 50%\n",
- "SON 23.6% Guerneville 5.4/23 mi 0.3 mi for 25%\n",
- "SFC 21.6% Presidio Heights 1.4/6.5 mi 0.2 mi for 25%\n",
- "SMC 21.4% Bay Area Ridge Trail 85/396 mi 14 mi for 25%\n",
- "SFC 20.6% Panhandle 1.5/7.3 mi 0.3 mi for 25%\n",
- "SFC 18.2% Polk Gulch 0.7/4.0 mi 0.3 mi for 25%\n",
- "SFC 18.2% Balboa Terrace 0.6/3.4 mi 0.2 mi for 25%\n",
- "SFC 18.0% Cole Valley 0.3/1.7 mi 0.1 mi for 25%\n",
- "SON 17.8% Healdsburg 9.6/54 mi 3.9 mi for 25%\n",
- "SON 17.0% Bodega Bay 4.9/29 mi 2.3 mi for 25%\n",
- "SFC 15.9% Forest Hill 1.0/6.1 mi 0.6 mi for 25%\n",
- "SFC 15.5% Northern Waterfront 0.9/5.6 mi 0.5 mi for 25%\n",
- "SFC 15.4% Aquatic Park Fort Mason 1.0/6.4 mi 0.6 mi for 25%\n",
- "--- 15.4% Alameda County 895/5,818 mi 560 mi for 25%\n",
- "SFC 15.2% Little Hollywood 0.6/3.7 mi 0.4 mi for 25%\n",
- "SFC 14.2% Clarendon Heights 0.9/6.0 mi 0.6 mi for 25%\n",
- "SFC 13.8% Fisherman's Wharf 0.9/6.2 mi 0.7 mi for 25%\n",
- "SFC 13.2% Sutro Heights 0.9/7.1 mi 0.8 mi for 25%\n",
- "SFC 13.0% Ashbury Heights 0.5/3.7 mi 0.4 mi for 25%\n",
- "MAR 12.9% Corte Madera 6.6/51 mi 6.2 mi for 25%\n",
- "MAR 12.9% Sausalito 4.2/33 mi 4.0 mi for 25%\n",
- "SFC 12.3% Dogpatch 0.6/5.1 mi 0.6 mi for 25%\n",
- "ALA 12.2% Alameda 25/207 mi 26 mi for 25%\n",
- "SCC 12.1% Gilroy 23/189 mi 24 mi for 25%\n",
- "SFC 11.9% Cow Hollow 1.4/12 mi 1.6 mi for 25%\n",
- "--- 10.8% Marin County 251/2,333 mi 332 mi for 25%\n",
- "SFC 10.7% Golden Gate Heights 1.9/18 mi 2.5 mi for 25%\n",
- "SFC 10.7% Pacific Heights 1.9/18 mi 2.6 mi for 25%\n",
- "SFC 10.2% Financial District 1.0/9.4 mi 1.4 mi for 25%\n",
- "MAR 9.1% Mill Valley 8.4/92 mi 15 mi for 25%\n",
- "SFC 8.6% Mission Bay 1.2/14 mi 2.3 mi for 25%\n",
- "ALA 8.0% Emeryville 2.2/28 mi 4.8 mi for 25%\n",
- "ALA 7.4% Berkeley 19/260 mi 46 mi for 25%\n",
- "--- 7.2% San Francisco County 88/1,217 mi 217 mi for 25%\n",
- "--- 7.1% Santa Cruz County 194/2,718 mi 486 mi for 25%\n",
- "ALA 6.8% Albany 2.9/43 mi 7.8 mi for 25%\n",
- "MAS 6.2% Cambridge 11/181 mi 34 mi for 25%\n",
- "SFC 6.0% Central Waterfront 0.6/10 mi 1.9 mi for 25%\n",
- "--- 5.1% Sonoma County 251/4,895 mi 973 mi for 25%\n",
- "--- 4.8% Napa County 78/1,609 mi 324 mi for 25%\n",
- "MAR 3.7% San Rafael 9.6/260 mi 55 mi for 25%\n",
- "--- 2.0% Contra Costa County 122/5,945 mi 1,364 mi for 25%\n",
- "--- 1.7% California 6,450/0.38M mi 1,090 mi for 2%\n",
- "--- 0.1% USA 6,840/6.4M mi 5,973 mi for 0.2%\n",
- "--- 0.017% Earth 7,202/42M mi 1,192 mi for 0.02%\n"
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18
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\n",
+ "
SMC
\n",
+ "
Palomar Park
\n",
+ "
4.0
\n",
+ "
4.0
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.9%
\n",
+ "
SMC
\n",
+ "
Emerald Lake Hills
\n",
+ "
24.6
\n",
+ "
25
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.8%
\n",
+ "
SMC
\n",
+ "
Atherton
\n",
+ "
56.3
\n",
+ "
56
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.8%
\n",
+ "
SMC
\n",
+ "
Windy Hill Preserve
\n",
+ "
4.1
\n",
+ "
4.1
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.7%
\n",
+ "
SMC
\n",
+ "
Menlo Park
\n",
+ "
139.5
\n",
+ "
139
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.7%
\n",
+ "
SMC
\n",
+ "
East Palo Alto
\n",
+ "
48.3
\n",
+ "
48
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.6%
\n",
+ "
SMC
\n",
+ "
Sky Londa
\n",
+ "
11.8
\n",
+ "
12
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.6%
\n",
+ "
SCC
\n",
+ "
Los Altos
\n",
+ "
138.2
\n",
+ "
138
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.5%
\n",
+ "
SMC
\n",
+ "
Portola Valley
\n",
+ "
48.2
\n",
+ "
48
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.4%
\n",
+ "
SMC
\n",
+ "
Woodside
\n",
+ "
75.2
\n",
+ "
75
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.3%
\n",
+ "
SMC
\n",
+ "
Redwood City
\n",
+ "
240.5
\n",
+ "
239
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.3%
\n",
+ "
SCC
\n",
+ "
Mountain View
\n",
+ "
208.1
\n",
+ "
207
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.2%
\n",
+ "
SCC
\n",
+ "
Los Altos Hills
\n",
+ "
91.3
\n",
+ "
91
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.0%
\n",
+ "
SCC
\n",
+ "
Palo Alto
\n",
+ "
297.2
\n",
+ "
294
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
99.0%
\n",
+ "
SMC
\n",
+ "
San Carlos
\n",
+ "
99.0
\n",
+ "
98
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
90.9%
\n",
+ "
SMC
\n",
+ "
Burleigh Murray Park
\n",
+ "
2.1
\n",
+ "
1.9
\n",
+ "
0.2 mi to 99%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
90.4%
\n",
+ "
SMC
\n",
+ "
Foster City
\n",
+ "
150.0
\n",
+ "
136
\n",
+ "
13 mi to 99%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
86.8%
\n",
+ "
SCC
\n",
+ "
Foothills Preserve
\n",
+ "
1.1
\n",
+ "
1.0
\n",
+ "
0.0 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
77.9%
\n",
+ "
SMC
\n",
+ "
San Mateo Highlands
\n",
+ "
18.0
\n",
+ "
14
\n",
+ "
2.2 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
74.5%
\n",
+ "
SMC
\n",
+ "
Skyline Ridge OSP
\n",
+ "
0.8
\n",
+ "
0.6
\n",
+ "
0.1 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
74.1%
\n",
+ "
SCC
\n",
+ "
San Francisco Bay Trail
\n",
+ "
260.8
\n",
+ "
193
\n",
+ "
41 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
73.2%
\n",
+ "
CCC
\n",
+ "
Rosie Riveter Park
\n",
+ "
5.5
\n",
+ "
4.0
\n",
+ "
0.9 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
71.5%
\n",
+ "
SMC
\n",
+ "
Burlingame Hills
\n",
+ "
6.0
\n",
+ "
4.3
\n",
+ "
1.1 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
66.7%
\n",
+ "
SMC
\n",
+ "
Coal Creek Preserve
\n",
+ "
3.9
\n",
+ "
2.6
\n",
+ "
0.9 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
63.5%
\n",
+ "
---
\n",
+ "
San Mateo County
\n",
+ "
2814.0
\n",
+ "
1,787
\n",
+ "
746 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
59.5%
\n",
+ "
SMC
\n",
+ "
Russian Ridge Preserve
\n",
+ "
12.2
\n",
+ "
7.3
\n",
+ "
3.7 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
59.3%
\n",
+ "
SMC
\n",
+ "
Montara
\n",
+ "
27.8
\n",
+ "
16
\n",
+ "
8.5 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
56.2%
\n",
+ "
SMC
\n",
+ "
Burlingame
\n",
+ "
88.4
\n",
+ "
50
\n",
+ "
30 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
54.7%
\n",
+ "
SMC
\n",
+ "
Belmont
\n",
+ "
98.1
\n",
+ "
54
\n",
+ "
35 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
53.3%
\n",
+ "
SCC
\n",
+ "
Sunnyvale
\n",
+ "
357.0
\n",
+ "
190
\n",
+ "
131 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
52.3%
\n",
+ "
SMC
\n",
+ "
Hillsborough
\n",
+ "
85.3
\n",
+ "
45
\n",
+ "
32 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
51.8%
\n",
+ "
SMC
\n",
+ "
San Mateo
\n",
+ "
256.0
\n",
+ "
133
\n",
+ "
98 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
51.5%
\n",
+ "
SMC
\n",
+ "
Half Moon Bay State Beach
\n",
+ "
4.4
\n",
+ "
2.3
\n",
+ "
1.7 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
51.2%
\n",
+ "
SMC
\n",
+ "
Long Ridge Preserve
\n",
+ "
11.0
\n",
+ "
5.6
\n",
+ "
4.3 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
51.2%
\n",
+ "
SCC
\n",
+ "
Castle Rock State Park
\n",
+ "
11.2
\n",
+ "
5.7
\n",
+ "
4.3 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
51.0%
\n",
+ "
ALA
\n",
+ "
Newark
\n",
+ "
147.0
\n",
+ "
75
\n",
+ "
57 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
50.2%
\n",
+ "
SMC
\n",
+ "
Brisbane
\n",
+ "
40.9
\n",
+ "
21
\n",
+ "
16 mi to 90%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
47.7%
\n",
+ "
SCC
\n",
+ "
Edenvale
\n",
+ "
30.0
\n",
+ "
14
\n",
+ "
0.7 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
47.3%
\n",
+ "
NSW
\n",
+ "
Barangaroo
\n",
+ "
1.7
\n",
+ "
0.8
\n",
+ "
0.0 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
47.2%
\n",
+ "
SCC
\n",
+ "
Gardner
\n",
+ "
23.4
\n",
+ "
11
\n",
+ "
0.7 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
45.1%
\n",
+ "
SCC
\n",
+ "
Monte Sereno
\n",
+ "
20.4
\n",
+ "
9.2
\n",
+ "
1.0 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
43.9%
\n",
+ "
SFC
\n",
+ "
Presidio Terrace
\n",
+ "
2.8
\n",
+ "
1.2
\n",
+ "
0.2 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
43.6%
\n",
+ "
SMC
\n",
+ "
El Granada
\n",
+ "
49.2
\n",
+ "
21
\n",
+ "
3.1 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
43.6%
\n",
+ "
SMC
\n",
+ "
Moss Beach
\n",
+ "
19.7
\n",
+ "
8.6
\n",
+ "
1.3 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
43.3%
\n",
+ "
ALA
\n",
+ "
Hayward Acres
\n",
+ "
3.5
\n",
+ "
1.5
\n",
+ "
0.2 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
42.6%
\n",
+ "
SMC
\n",
+ "
Millbrae
\n",
+ "
65.0
\n",
+ "
28
\n",
+ "
4.8 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
40.8%
\n",
+ "
ALA
\n",
+ "
San Lorenzo
\n",
+ "
55.5
\n",
+ "
23
\n",
+ "
5.1 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
39.6%
\n",
+ "
SFC
\n",
+ "
Lincoln Park
\n",
+ "
4.5
\n",
+ "
1.8
\n",
+ "
0.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
39.5%
\n",
+ "
SCC
\n",
+ "
Communications Hill
\n",
+ "
27.8
\n",
+ "
11
\n",
+ "
2.9 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
39.0%
\n",
+ "
SMC
\n",
+ "
Purisima Creek Preserve
\n",
+ "
16.5
\n",
+ "
6.4
\n",
+ "
1.8 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
38.9%
\n",
+ "
SMC
\n",
+ "
Colma
\n",
+ "
13.7
\n",
+ "
5.3
\n",
+ "
1.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
38.7%
\n",
+ "
MAR
\n",
+ "
Mt Tamalpais State Park
\n",
+ "
31.7
\n",
+ "
12
\n",
+ "
3.6 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
38.2%
\n",
+ "
SMC
\n",
+ "
Broadmoor
\n",
+ "
8.8
\n",
+ "
3.4
\n",
+ "
1.0 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
37.4%
\n",
+ "
SFC
\n",
+ "
South Beach
\n",
+ "
4.8
\n",
+ "
1.8
\n",
+ "
0.6 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
37.1%
\n",
+ "
MAR
\n",
+ "
Muir Beach
\n",
+ "
4.6
\n",
+ "
1.7
\n",
+ "
0.6 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
36.8%
\n",
+ "
SFC
\n",
+ "
Lake Street
\n",
+ "
3.9
\n",
+ "
1.4
\n",
+ "
0.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
36.8%
\n",
+ "
SCC
\n",
+ "
Spartan Keyes
\n",
+ "
64.3
\n",
+ "
24
\n",
+ "
8.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
36.7%
\n",
+ "
SCC
\n",
+ "
Milpitas
\n",
+ "
224.0
\n",
+ "
82
\n",
+ "
30 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
36.1%
\n",
+ "
ALA
\n",
+ "
Ashland
\n",
+ "
35.1
\n",
+ "
13
\n",
+ "
4.9 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
36.0%
\n",
+ "
SCC
\n",
+ "
Willow Glen
\n",
+ "
81.6
\n",
+ "
29
\n",
+ "
11 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
34.8%
\n",
+ "
SCC
\n",
+ "
Santa Clara
\n",
+ "
348.0
\n",
+ "
121
\n",
+ "
53 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
34.7%
\n",
+ "
MAS
\n",
+ "
MIT
\n",
+ "
9.6
\n",
+ "
3.3
\n",
+ "
1.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
34.3%
\n",
+ "
NSW
\n",
+ "
Millers Point
\n",
+ "
3.2
\n",
+ "
1.1
\n",
+ "
0.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
33.7%
\n",
+ "
SCC
\n",
+ "
Parkview
\n",
+ "
42.5
\n",
+ "
14
\n",
+ "
6.9 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
33.6%
\n",
+ "
SMC
\n",
+ "
Half Moon Bay
\n",
+ "
68.0
\n",
+ "
23
\n",
+ "
11 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
33.6%
\n",
+ "
SCC
\n",
+ "
Los Gatos
\n",
+ "
148.0
\n",
+ "
50
\n",
+ "
24 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
33.6%
\n",
+ "
SCC
\n",
+ "
Cupertino
\n",
+ "
172.0
\n",
+ "
58
\n",
+ "
28 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
33.2%
\n",
+ "
SMC
\n",
+ "
Pacifica
\n",
+ "
150.9
\n",
+ "
50
\n",
+ "
25 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
33.0%
\n",
+ "
---
\n",
+ "
Santa Clara County
\n",
+ "
7569.0
\n",
+ "
2,498
\n",
+ "
1,287 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
33.0%
\n",
+ "
SCC
\n",
+ "
Seven Trees
\n",
+ "
40.9
\n",
+ "
13
\n",
+ "
7.0 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
32.9%
\n",
+ "
ALA
\n",
+ "
Union City
\n",
+ "
208.8
\n",
+ "
69
\n",
+ "
36 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
32.9%
\n",
+ "
MAR
\n",
+ "
Stinson Beach
\n",
+ "
11.2
\n",
+ "
3.7
\n",
+ "
1.9 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
32.9%
\n",
+ "
ALA
\n",
+ "
Fremont
\n",
+ "
780.2
\n",
+ "
257
\n",
+ "
133 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
32.7%
\n",
+ "
SCC
\n",
+ "
Branham
\n",
+ "
44.0
\n",
+ "
14
\n",
+ "
7.6 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
32.7%
\n",
+ "
ALA
\n",
+ "
Hayward
\n",
+ "
444.5
\n",
+ "
145
\n",
+ "
77 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
31.9%
\n",
+ "
MAR
\n",
+ "
Marin Headlands GGNRA
\n",
+ "
65.7
\n",
+ "
21
\n",
+ "
12 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
31.5%
\n",
+ "
SCC
\n",
+ "
San Martin
\n",
+ "
35.3
\n",
+ "
11
\n",
+ "
6.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
31.0%
\n",
+ "
SMC
\n",
+ "
San Bruno
\n",
+ "
114.0
\n",
+ "
35
\n",
+ "
22 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
30.9%
\n",
+ "
SCC
\n",
+ "
Willow Glen South
\n",
+ "
63.3
\n",
+ "
20
\n",
+ "
12 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
30.7%
\n",
+ "
SCC
\n",
+ "
Forest of Nisene Marks SP
\n",
+ "
44.0
\n",
+ "
14
\n",
+ "
8.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
30.0%
\n",
+ "
SCC
\n",
+ "
Saratoga
\n",
+ "
180.0
\n",
+ "
54
\n",
+ "
36 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
29.6%
\n",
+ "
SMC
\n",
+ "
South San Francisco
\n",
+ "
185.3
\n",
+ "
55
\n",
+ "
38 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
29.4%
\n",
+ "
SFC
\n",
+ "
Golden Gate Park
\n",
+ "
40.8
\n",
+ "
12
\n",
+ "
8.4 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
29.3%
\n",
+ "
SCC
\n",
+ "
Campbell
\n",
+ "
119.0
\n",
+ "
35
\n",
+ "
25 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
29.3%
\n",
+ "
SFC
\n",
+ "
Seacliff
\n",
+ "
4.1
\n",
+ "
1.2
\n",
+ "
0.8 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
29.2%
\n",
+ "
NSW
\n",
+ "
Dawes Point
\n",
+ "
1.8
\n",
+ "
0.5
\n",
+ "
0.4 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
28.2%
\n",
+ "
ALA
\n",
+ "
Fairview
\n",
+ "
34.4
\n",
+ "
9.7
\n",
+ "
7.5 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
28.0%
\n",
+ "
SCC
\n",
+ "
San Jose
\n",
+ "
2618.7
\n",
+ "
733
\n",
+ "
576 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
27.8%
\n",
+ "
ALA
\n",
+ "
Cherryland
\n",
+ "
20.9
\n",
+ "
5.8
\n",
+ "
4.6 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
27.7%
\n",
+ "
ALA
\n",
+ "
San Leandro
\n",
+ "
230.6
\n",
+ "
64
\n",
+ "
51 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
27.4%
\n",
+ "
SMC
\n",
+ "
Daly City
\n",
+ "
148.1
\n",
+ "
41
\n",
+ "
33 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
26.8%
\n",
+ "
CAL
\n",
+ "
Mokelumne Hill
\n",
+ "
14.7
\n",
+ "
3.9
\n",
+ "
3.4 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
26.7%
\n",
+ "
SFC
\n",
+ "
Presidio National Park
\n",
+ "
43.5
\n",
+ "
12
\n",
+ "
10 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
26.1%
\n",
+ "
ALA
\n",
+ "
Castro Valley
\n",
+ "
192.5
\n",
+ "
50
\n",
+ "
46 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
25.6%
\n",
+ "
SMC
\n",
+ "
Bay Area Ridge Trail
\n",
+ "
395.6
\n",
+ "
101
\n",
+ "
97 mi to 50%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
23.6%
\n",
+ "
SON
\n",
+ "
Guerneville
\n",
+ "
22.7
\n",
+ "
5.4
\n",
+ "
0.3 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
21.6%
\n",
+ "
SFC
\n",
+ "
Presidio Heights
\n",
+ "
6.5
\n",
+ "
1.4
\n",
+ "
0.2 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
20.6%
\n",
+ "
SFC
\n",
+ "
Panhandle
\n",
+ "
7.3
\n",
+ "
1.5
\n",
+ "
0.3 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
18.2%
\n",
+ "
SFC
\n",
+ "
Balboa Terrace
\n",
+ "
3.4
\n",
+ "
0.6
\n",
+ "
0.2 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
18.2%
\n",
+ "
SFC
\n",
+ "
Polk Gulch
\n",
+ "
4.0
\n",
+ "
0.7
\n",
+ "
0.3 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
18.0%
\n",
+ "
SFC
\n",
+ "
Cole Valley
\n",
+ "
1.7
\n",
+ "
0.3
\n",
+ "
0.1 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
17.8%
\n",
+ "
SON
\n",
+ "
Healdsburg
\n",
+ "
53.7
\n",
+ "
9.6
\n",
+ "
3.9 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
17.0%
\n",
+ "
SON
\n",
+ "
Bodega Bay
\n",
+ "
28.9
\n",
+ "
4.9
\n",
+ "
2.3 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
16.6%
\n",
+ "
---
\n",
+ "
Alameda County
\n",
+ "
5818.0
\n",
+ "
965
\n",
+ "
490 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
15.9%
\n",
+ "
SFC
\n",
+ "
Forest Hill
\n",
+ "
6.1
\n",
+ "
1.0
\n",
+ "
0.6 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
15.5%
\n",
+ "
SFC
\n",
+ "
Northern Waterfront
\n",
+ "
5.6
\n",
+ "
0.9
\n",
+ "
0.5 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
15.4%
\n",
+ "
SFC
\n",
+ "
Aquatic Park Fort Mason
\n",
+ "
6.4
\n",
+ "
1.0
\n",
+ "
0.6 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
15.2%
\n",
+ "
SFC
\n",
+ "
Little Hollywood
\n",
+ "
3.7
\n",
+ "
0.6
\n",
+ "
0.4 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
14.2%
\n",
+ "
SFC
\n",
+ "
Clarendon Heights
\n",
+ "
6.0
\n",
+ "
0.9
\n",
+ "
0.6 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
13.8%
\n",
+ "
SFC
\n",
+ "
Fisherman's Wharf
\n",
+ "
6.2
\n",
+ "
0.9
\n",
+ "
0.7 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
13.2%
\n",
+ "
SFC
\n",
+ "
Sutro Heights
\n",
+ "
7.1
\n",
+ "
0.9
\n",
+ "
0.8 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
13.0%
\n",
+ "
SFC
\n",
+ "
Ashbury Heights
\n",
+ "
3.7
\n",
+ "
0.5
\n",
+ "
0.4 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
12.9%
\n",
+ "
MAR
\n",
+ "
Corte Madera
\n",
+ "
51.0
\n",
+ "
6.6
\n",
+ "
6.2 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
12.9%
\n",
+ "
MAR
\n",
+ "
Sausalito
\n",
+ "
32.7
\n",
+ "
4.2
\n",
+ "
4.0 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
12.3%
\n",
+ "
SFC
\n",
+ "
Dogpatch
\n",
+ "
5.1
\n",
+ "
0.6
\n",
+ "
0.6 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
12.2%
\n",
+ "
ALA
\n",
+ "
Alameda
\n",
+ "
206.7
\n",
+ "
25
\n",
+ "
26 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
12.1%
\n",
+ "
SCC
\n",
+ "
Gilroy
\n",
+ "
188.9
\n",
+ "
23
\n",
+ "
24 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
11.9%
\n",
+ "
SFC
\n",
+ "
Cow Hollow
\n",
+ "
12.0
\n",
+ "
1.4
\n",
+ "
1.6 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
10.9%
\n",
+ "
---
\n",
+ "
Marin County
\n",
+ "
2333.0
\n",
+ "
255
\n",
+ "
328 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
10.7%
\n",
+ "
SFC
\n",
+ "
Pacific Heights
\n",
+ "
18.0
\n",
+ "
1.9
\n",
+ "
2.6 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
10.7%
\n",
+ "
SFC
\n",
+ "
Golden Gate Heights
\n",
+ "
17.8
\n",
+ "
1.9
\n",
+ "
2.5 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
10.2%
\n",
+ "
SFC
\n",
+ "
Financial District
\n",
+ "
9.4
\n",
+ "
1.0
\n",
+ "
1.4 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
9.3%
\n",
+ "
---
\n",
+ "
San Francisco County
\n",
+ "
1217.0
\n",
+ "
113
\n",
+ "
192 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
9.1%
\n",
+ "
MAR
\n",
+ "
Mill Valley
\n",
+ "
92.2
\n",
+ "
8.4
\n",
+ "
15 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
8.9%
\n",
+ "
---
\n",
+ "
Napa County
\n",
+ "
1609.0
\n",
+ "
143
\n",
+ "
259 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
8.6%
\n",
+ "
SFC
\n",
+ "
Mission Bay
\n",
+ "
13.8
\n",
+ "
1.2
\n",
+ "
2.3 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
7.7%
\n",
+ "
ALA
\n",
+ "
Emeryville
\n",
+ "
28.1
\n",
+ "
2.2
\n",
+ "
4.9 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
7.6%
\n",
+ "
ALA
\n",
+ "
Berkeley
\n",
+ "
260.3
\n",
+ "
20
\n",
+ "
45 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
7.1%
\n",
+ "
---
\n",
+ "
Santa Cruz County
\n",
+ "
2718.0
\n",
+ "
194
\n",
+ "
486 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
6.8%
\n",
+ "
ALA
\n",
+ "
Albany
\n",
+ "
42.7
\n",
+ "
2.9
\n",
+ "
7.8 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
6.2%
\n",
+ "
MAS
\n",
+ "
Cambridge
\n",
+ "
180.8
\n",
+ "
11
\n",
+ "
34 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
6.0%
\n",
+ "
SFC
\n",
+ "
Central Waterfront
\n",
+ "
10.2
\n",
+ "
0.6
\n",
+ "
1.9 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
5.1%
\n",
+ "
---
\n",
+ "
Sonoma County
\n",
+ "
4895.0
\n",
+ "
251
\n",
+ "
973 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
3.8%
\n",
+ "
---
\n",
+ "
Contra Costa County
\n",
+ "
5945.0
\n",
+ "
226
\n",
+ "
1,260 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
3.7%
\n",
+ "
MAR
\n",
+ "
San Rafael
\n",
+ "
260.0
\n",
+ "
9.6
\n",
+ "
55 mi to 25%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
1.8%
\n",
+ "
---
\n",
+ "
California
\n",
+ "
377037.0
\n",
+ "
6,719
\n",
+ "
822 mi to 2%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
0.113%
\n",
+ "
---
\n",
+ "
USA
\n",
+ "
6406754.0
\n",
+ "
7,267
\n",
+ "
5,546 mi to 0.2%
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
0.017%
\n",
+ "
---
\n",
+ "
Earth
\n",
+ "
41974536.0
\n",
+ "
7,159
\n",
+ "
1,236 mi to 0.02%
\n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " pct county name total done \\\n",
+ " 100.0% SMC Los Trancos Woods 5.3 5.3 \n",
+ " 100.0% SMC Menlo Oaks 3.5 3.5 \n",
+ " 100.0% SMC Los Trancos OSP 0.3 0.3 \n",
+ " 100.0% SMC Ladera 8.1 8.1 \n",
+ " 100.0% SMC Kensington Square 0.6 0.6 \n",
+ " 100.0% SMC North Fair Oaks 26.7 27 \n",
+ " 100.0% SMC West Menlo Park 11.2 11 \n",
+ " 100.0% SMC Sequoia Tract 11.0 11 \n",
+ " 99.9% SCC Loyola 18.3 18 \n",
+ " 99.9% SMC Palomar Park 4.0 4.0 \n",
+ " 99.9% SMC Emerald Lake Hills 24.6 25 \n",
+ " 99.8% SMC Atherton 56.3 56 \n",
+ " 99.8% SMC Windy Hill Preserve 4.1 4.1 \n",
+ " 99.7% SMC Menlo Park 139.5 139 \n",
+ " 99.7% SMC East Palo Alto 48.3 48 \n",
+ " 99.6% SMC Sky Londa 11.8 12 \n",
+ " 99.6% SCC Los Altos 138.2 138 \n",
+ " 99.5% SMC Portola Valley 48.2 48 \n",
+ " 99.4% SMC Woodside 75.2 75 \n",
+ " 99.3% SMC Redwood City 240.5 239 \n",
+ " 99.3% SCC Mountain View 208.1 207 \n",
+ " 99.2% SCC Los Altos Hills 91.3 91 \n",
+ " 99.0% SCC Palo Alto 297.2 294 \n",
+ " 99.0% SMC San Carlos 99.0 98 \n",
+ " 90.9% SMC Burleigh Murray Park 2.1 1.9 \n",
+ " 90.4% SMC Foster City 150.0 136 \n",
+ " 86.8% SCC Foothills Preserve 1.1 1.0 \n",
+ " 77.9% SMC San Mateo Highlands 18.0 14 \n",
+ " 74.5% SMC Skyline Ridge OSP 0.8 0.6 \n",
+ " 74.1% SCC San Francisco Bay Trail 260.8 193 \n",
+ " 73.2% CCC Rosie Riveter Park 5.5 4.0 \n",
+ " 71.5% SMC Burlingame Hills 6.0 4.3 \n",
+ " 66.7% SMC Coal Creek Preserve 3.9 2.6 \n",
+ " 63.5% --- San Mateo County 2814.0 1,787 \n",
+ " 59.5% SMC Russian Ridge Preserve 12.2 7.3 \n",
+ " 59.3% SMC Montara 27.8 16 \n",
+ " 56.2% SMC Burlingame 88.4 50 \n",
+ " 54.7% SMC Belmont 98.1 54 \n",
+ " 53.3% SCC Sunnyvale 357.0 190 \n",
+ " 52.3% SMC Hillsborough 85.3 45 \n",
+ " 51.8% SMC San Mateo 256.0 133 \n",
+ " 51.5% SMC Half Moon Bay State Beach 4.4 2.3 \n",
+ " 51.2% SMC Long Ridge Preserve 11.0 5.6 \n",
+ " 51.2% SCC Castle Rock State Park 11.2 5.7 \n",
+ " 51.0% ALA Newark 147.0 75 \n",
+ " 50.2% SMC Brisbane 40.9 21 \n",
+ " 47.7% SCC Edenvale 30.0 14 \n",
+ " 47.3% NSW Barangaroo 1.7 0.8 \n",
+ " 47.2% SCC Gardner 23.4 11 \n",
+ " 45.1% SCC Monte Sereno 20.4 9.2 \n",
+ " 43.9% SFC Presidio Terrace 2.8 1.2 \n",
+ " 43.6% SMC El Granada 49.2 21 \n",
+ " 43.6% SMC Moss Beach 19.7 8.6 \n",
+ " 43.3% ALA Hayward Acres 3.5 1.5 \n",
+ " 42.6% SMC Millbrae 65.0 28 \n",
+ " 40.8% ALA San Lorenzo 55.5 23 \n",
+ " 39.6% SFC Lincoln Park 4.5 1.8 \n",
+ " 39.5% SCC Communications Hill 27.8 11 \n",
+ " 39.0% SMC Purisima Creek Preserve 16.5 6.4 \n",
+ " 38.9% SMC Colma 13.7 5.3 \n",
+ " 38.7% MAR Mt Tamalpais State Park 31.7 12 \n",
+ " 38.2% SMC Broadmoor 8.8 3.4 \n",
+ " 37.4% SFC South Beach 4.8 1.8 \n",
+ " 37.1% MAR Muir Beach 4.6 1.7 \n",
+ " 36.8% SFC Lake Street 3.9 1.4 \n",
+ " 36.8% SCC Spartan Keyes 64.3 24 \n",
+ " 36.7% SCC Milpitas 224.0 82 \n",
+ " 36.1% ALA Ashland 35.1 13 \n",
+ " 36.0% SCC Willow Glen 81.6 29 \n",
+ " 34.8% SCC Santa Clara 348.0 121 \n",
+ " 34.7% MAS MIT 9.6 3.3 \n",
+ " 34.3% NSW Millers Point 3.2 1.1 \n",
+ " 33.7% SCC Parkview 42.5 14 \n",
+ " 33.6% SMC Half Moon Bay 68.0 23 \n",
+ " 33.6% SCC Los Gatos 148.0 50 \n",
+ " 33.6% SCC Cupertino 172.0 58 \n",
+ " 33.2% SMC Pacifica 150.9 50 \n",
+ " 33.0% --- Santa Clara County 7569.0 2,498 \n",
+ " 33.0% SCC Seven Trees 40.9 13 \n",
+ " 32.9% ALA Union City 208.8 69 \n",
+ " 32.9% MAR Stinson Beach 11.2 3.7 \n",
+ " 32.9% ALA Fremont 780.2 257 \n",
+ " 32.7% SCC Branham 44.0 14 \n",
+ " 32.7% ALA Hayward 444.5 145 \n",
+ " 31.9% MAR Marin Headlands GGNRA 65.7 21 \n",
+ " 31.5% SCC San Martin 35.3 11 \n",
+ " 31.0% SMC San Bruno 114.0 35 \n",
+ " 30.9% SCC Willow Glen South 63.3 20 \n",
+ " 30.7% SCC Forest of Nisene Marks SP 44.0 14 \n",
+ " 30.0% SCC Saratoga 180.0 54 \n",
+ " 29.6% SMC South San Francisco 185.3 55 \n",
+ " 29.4% SFC Golden Gate Park 40.8 12 \n",
+ " 29.3% SCC Campbell 119.0 35 \n",
+ " 29.3% SFC Seacliff 4.1 1.2 \n",
+ " 29.2% NSW Dawes Point 1.8 0.5 \n",
+ " 28.2% ALA Fairview 34.4 9.7 \n",
+ " 28.0% SCC San Jose 2618.7 733 \n",
+ " 27.8% ALA Cherryland 20.9 5.8 \n",
+ " 27.7% ALA San Leandro 230.6 64 \n",
+ " 27.4% SMC Daly City 148.1 41 \n",
+ " 26.8% CAL Mokelumne Hill 14.7 3.9 \n",
+ " 26.7% SFC Presidio National Park 43.5 12 \n",
+ " 26.1% ALA Castro Valley 192.5 50 \n",
+ " 25.6% SMC Bay Area Ridge Trail 395.6 101 \n",
+ " 23.6% SON Guerneville 22.7 5.4 \n",
+ " 21.6% SFC Presidio Heights 6.5 1.4 \n",
+ " 20.6% SFC Panhandle 7.3 1.5 \n",
+ " 18.2% SFC Balboa Terrace 3.4 0.6 \n",
+ " 18.2% SFC Polk Gulch 4.0 0.7 \n",
+ " 18.0% SFC Cole Valley 1.7 0.3 \n",
+ " 17.8% SON Healdsburg 53.7 9.6 \n",
+ " 17.0% SON Bodega Bay 28.9 4.9 \n",
+ " 16.6% --- Alameda County 5818.0 965 \n",
+ " 15.9% SFC Forest Hill 6.1 1.0 \n",
+ " 15.5% SFC Northern Waterfront 5.6 0.9 \n",
+ " 15.4% SFC Aquatic Park Fort Mason 6.4 1.0 \n",
+ " 15.2% SFC Little Hollywood 3.7 0.6 \n",
+ " 14.2% SFC Clarendon Heights 6.0 0.9 \n",
+ " 13.8% SFC Fisherman's Wharf 6.2 0.9 \n",
+ " 13.2% SFC Sutro Heights 7.1 0.9 \n",
+ " 13.0% SFC Ashbury Heights 3.7 0.5 \n",
+ " 12.9% MAR Corte Madera 51.0 6.6 \n",
+ " 12.9% MAR Sausalito 32.7 4.2 \n",
+ " 12.3% SFC Dogpatch 5.1 0.6 \n",
+ " 12.2% ALA Alameda 206.7 25 \n",
+ " 12.1% SCC Gilroy 188.9 23 \n",
+ " 11.9% SFC Cow Hollow 12.0 1.4 \n",
+ " 10.9% --- Marin County 2333.0 255 \n",
+ " 10.7% SFC Pacific Heights 18.0 1.9 \n",
+ " 10.7% SFC Golden Gate Heights 17.8 1.9 \n",
+ " 10.2% SFC Financial District 9.4 1.0 \n",
+ " 9.3% --- San Francisco County 1217.0 113 \n",
+ " 9.1% MAR Mill Valley 92.2 8.4 \n",
+ " 8.9% --- Napa County 1609.0 143 \n",
+ " 8.6% SFC Mission Bay 13.8 1.2 \n",
+ " 7.7% ALA Emeryville 28.1 2.2 \n",
+ " 7.6% ALA Berkeley 260.3 20 \n",
+ " 7.1% --- Santa Cruz County 2718.0 194 \n",
+ " 6.8% ALA Albany 42.7 2.9 \n",
+ " 6.2% MAS Cambridge 180.8 11 \n",
+ " 6.0% SFC Central Waterfront 10.2 0.6 \n",
+ " 5.1% --- Sonoma County 4895.0 251 \n",
+ " 3.8% --- Contra Costa County 5945.0 226 \n",
+ " 3.7% MAR San Rafael 260.0 9.6 \n",
+ " 1.8% --- California 377037.0 6,719 \n",
+ " 0.113% --- USA 6406754.0 7,267 \n",
+ " 0.017% --- Earth 41974536.0 7,159 \n",
+ "\n",
+ " to next badge \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " 0.2 mi to 99% \n",
+ " 13 mi to 99% \n",
+ " 0.0 mi to 90% \n",
+ " 2.2 mi to 90% \n",
+ " 0.1 mi to 90% \n",
+ " 41 mi to 90% \n",
+ " 0.9 mi to 90% \n",
+ " 1.1 mi to 90% \n",
+ " 0.9 mi to 90% \n",
+ " 746 mi to 90% \n",
+ " 3.7 mi to 90% \n",
+ " 8.5 mi to 90% \n",
+ " 30 mi to 90% \n",
+ " 35 mi to 90% \n",
+ " 131 mi to 90% \n",
+ " 32 mi to 90% \n",
+ " 98 mi to 90% \n",
+ " 1.7 mi to 90% \n",
+ " 4.3 mi to 90% \n",
+ " 4.3 mi to 90% \n",
+ " 57 mi to 90% \n",
+ " 16 mi to 90% \n",
+ " 0.7 mi to 50% \n",
+ " 0.0 mi to 50% \n",
+ " 0.7 mi to 50% \n",
+ " 1.0 mi to 50% \n",
+ " 0.2 mi to 50% \n",
+ " 3.1 mi to 50% \n",
+ " 1.3 mi to 50% \n",
+ " 0.2 mi to 50% \n",
+ " 4.8 mi to 50% \n",
+ " 5.1 mi to 50% \n",
+ " 0.5 mi to 50% \n",
+ " 2.9 mi to 50% \n",
+ " 1.8 mi to 50% \n",
+ " 1.5 mi to 50% \n",
+ " 3.6 mi to 50% \n",
+ " 1.0 mi to 50% \n",
+ " 0.6 mi to 50% \n",
+ " 0.6 mi to 50% \n",
+ " 0.5 mi to 50% \n",
+ " 8.5 mi to 50% \n",
+ " 30 mi to 50% \n",
+ " 4.9 mi to 50% \n",
+ " 11 mi to 50% \n",
+ " 53 mi to 50% \n",
+ " 1.5 mi to 50% \n",
+ " 0.5 mi to 50% \n",
+ " 6.9 mi to 50% \n",
+ " 11 mi to 50% \n",
+ " 24 mi to 50% \n",
+ " 28 mi to 50% \n",
+ " 25 mi to 50% \n",
+ " 1,287 mi to 50% \n",
+ " 7.0 mi to 50% \n",
+ " 36 mi to 50% \n",
+ " 1.9 mi to 50% \n",
+ " 133 mi to 50% \n",
+ " 7.6 mi to 50% \n",
+ " 77 mi to 50% \n",
+ " 12 mi to 50% \n",
+ " 6.5 mi to 50% \n",
+ " 22 mi to 50% \n",
+ " 12 mi to 50% \n",
+ " 8.5 mi to 50% \n",
+ " 36 mi to 50% \n",
+ " 38 mi to 50% \n",
+ " 8.4 mi to 50% \n",
+ " 25 mi to 50% \n",
+ " 0.8 mi to 50% \n",
+ " 0.4 mi to 50% \n",
+ " 7.5 mi to 50% \n",
+ " 576 mi to 50% \n",
+ " 4.6 mi to 50% \n",
+ " 51 mi to 50% \n",
+ " 33 mi to 50% \n",
+ " 3.4 mi to 50% \n",
+ " 10 mi to 50% \n",
+ " 46 mi to 50% \n",
+ " 97 mi to 50% \n",
+ " 0.3 mi to 25% \n",
+ " 0.2 mi to 25% \n",
+ " 0.3 mi to 25% \n",
+ " 0.2 mi to 25% \n",
+ " 0.3 mi to 25% \n",
+ " 0.1 mi to 25% \n",
+ " 3.9 mi to 25% \n",
+ " 2.3 mi to 25% \n",
+ " 490 mi to 25% \n",
+ " 0.6 mi to 25% \n",
+ " 0.5 mi to 25% \n",
+ " 0.6 mi to 25% \n",
+ " 0.4 mi to 25% \n",
+ " 0.6 mi to 25% \n",
+ " 0.7 mi to 25% \n",
+ " 0.8 mi to 25% \n",
+ " 0.4 mi to 25% \n",
+ " 6.2 mi to 25% \n",
+ " 4.0 mi to 25% \n",
+ " 0.6 mi to 25% \n",
+ " 26 mi to 25% \n",
+ " 24 mi to 25% \n",
+ " 1.6 mi to 25% \n",
+ " 328 mi to 25% \n",
+ " 2.6 mi to 25% \n",
+ " 2.5 mi to 25% \n",
+ " 1.4 mi to 25% \n",
+ " 192 mi to 25% \n",
+ " 15 mi to 25% \n",
+ " 259 mi to 25% \n",
+ " 2.3 mi to 25% \n",
+ " 4.9 mi to 25% \n",
+ " 45 mi to 25% \n",
+ " 486 mi to 25% \n",
+ " 7.8 mi to 25% \n",
+ " 34 mi to 25% \n",
+ " 1.9 mi to 25% \n",
+ " 973 mi to 25% \n",
+ " 1,260 mi to 25% \n",
+ " 55 mi to 25% \n",
+ " 822 mi to 2% \n",
+ " 5,546 mi to 0.2% \n",
+ " 1,236 mi to 0.02% "
+ ]
+ },
+ "execution_count": 88,
+ "metadata": {},
+ "output_type": "execute_result"
}
],
"source": [
@@ -692,12 +2254,12 @@
"source": [
"As part of my wandering, in April 2022 I was able to get to 25% of every city that rings the San Francisco Bay and is below San Francisco or Oakland (see map [with](ring2.jpeg) or [without](ring1.jpeg) roads traveled; as soon as you get 25% of a city, it lights up with a color).\n",
"\n",
- "I live at the border of Santa Clara County (SCC) and San Mateo County (SMC), so I ride in both. Wandrer.earth says that Jason Molenda is a whopping 1,700 miles ahead of me in SMC and Megan Gardner is 1,000 miles ahead of me in SCC. Barry Mann is the leader in both total miles in the two counties and average percent. Kudos to all of them! However, I do occupy a small section of the [Pareto front](https://en.wikipedia.org/wiki/Pareto_front) for the two counties together: no single rider on wandrer.earth has done more than me in *both* counties. Here are the leaders (as of September 2023), where the dotted line indicates the five riders on the Pareto front."
+ "I live at the border of Santa Clara County (SCC) and San Mateo County (SMC), so I ride in both. Wandrer.earth says that Jason Molenda is a whopping 1,700 miles ahead of me in SCC and Megan Gardner is 1,000 miles ahead of me in SMC. Barry Mann is the leader in total miles in the two counties, and Megan leads in average percent. Kudos to all of them! However, I do occupy a small section of the [Pareto front](https://en.wikipedia.org/wiki/Pareto_front) for the two counties together: no single rider on wandrer.earth has done more than me in *both* counties. Here are the leaders (as of December 2023), where the dotted line indicates the Pareto front."
]
},
{
"cell_type": "code",
- "execution_count": 96,
+ "execution_count": 89,
"metadata": {},
"outputs": [
{
@@ -734,91 +2296,58 @@
" \n",
"
"
]
@@ -873,16 +2396,14 @@
"source": [
"# Eddington Number\n",
"\n",
- "The British physicist [Sir Arthur Eddington](https://en.wikipedia.org/wiki/Arthur_Eddington), a contemporary of Einstein, was a pre-Strava bicyclist who favored this metric:\n",
- "\n",
- "> Your [**Eddington Number**](https://www.triathlete.com/2011/04/training/measuring-bike-miles-eddington-number_301789) is the largest integer **e** such that you have cycled at least **e** miles on at least **e** days.\n",
+ "The physicist/bicyclist [Sir Arthur Eddington](https://en.wikipedia.org/wiki/Arthur_Eddington), a contemporary of Einstein defined the [**Eddington Number**](https://www.triathlete.com/2011/04/training/measuring-bike-miles-eddington-number_301789) as the largest integer **E** such that you have cycled at least **E** miles on at least **E** days.\n",
"\n",
"My Eddington number progress over the years, in both kilometers and miles:"
]
},
{
"cell_type": "code",
- "execution_count": 97,
+ "execution_count": 90,
"metadata": {},
"outputs": [
{
@@ -914,6 +2435,12 @@
" \n",
"
\n",
"
\n",
+ "
2024
\n",
+ "
102
\n",
+ "
68
\n",
+ "
\n",
+ "
\n",
+ "
\n",
"
2023
\n",
"
101
\n",
"
67
\n",
@@ -978,6 +2505,7 @@
],
"text/plain": [
" year Ed_km Ed_mi\n",
+ " 2024 102 68\n",
" 2023 101 67\n",
" 2022 96 66\n",
" 2021 93 65\n",
@@ -990,7 +2518,7 @@
" 2014 46 35"
]
},
- "execution_count": 97,
+ "execution_count": 90,
"metadata": {},
"output_type": "execute_result"
}
@@ -1003,7 +2531,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "My current Eddington Number is **101** in kilometers and **67** in miles: I've ridden at least 67 miles on at least 67 days (but not 68 miles on 68 days). My number is above [the median for Strava](https://swinny.net/Cycling/-4687-Calculate-your-Eddington-Number), but not nearly as good as Eddington himself: his number was **84** in miles when he died at age 62, and his roads, bicycles, and navigation aids were not nearly as nice as mine, so bravo zulu to him. "
+ "My current Eddington Number is **102** in kilometers and **68** in miles (I've ridden at least 68 miles on at least 68 days, but not 69 miles on 69 days). My number is above [the median for Strava](https://swinny.net/Cycling/-4687-Calculate-your-Eddington-Number), but not nearly as good as Eddington himself: his number was **84** (in miles) when he died at age 62, and his roads, weather, bicycles, and navigation aids were not nearly as nice as mine, so bravo zulu to him. "
]
},
{
@@ -1015,7 +2543,7 @@
},
{
"cell_type": "code",
- "execution_count": 98,
+ "execution_count": 91,
"metadata": {},
"outputs": [
{
@@ -1040,111 +2568,73 @@
"
\n",
"
\n",
"
kms
\n",
- "
km rides
\n",
"
kms gap
\n",
"
miles
\n",
- "
miles rides
\n",
"
miles gap
\n",
"
\n",
" \n",
" \n",
"
\n",
"
\n",
- "
100
\n",
- "
107
\n",
- "
-7
\n",
- "
67
\n",
- "
74
\n",
- "
-7
\n",
- "
\n",
- "
\n",
- "
\n",
- "
101
\n",
- "
105
\n",
- "
-4
\n",
- "
68
\n",
- "
67
\n",
- "
1
\n",
- "
\n",
- "
\n",
- "
\n",
- "
102
\n",
- "
99
\n",
- "
3
\n",
- "
69
\n",
- "
54
\n",
- "
15
\n",
- "
\n",
- "
\n",
- "
\n",
"
103
\n",
- "
97
\n",
- "
6
\n",
- "
70
\n",
- "
44
\n",
- "
26
\n",
+ "
4
\n",
+ "
69
\n",
+ "
13
\n",
"
\n",
"
\n",
"
\n",
"
104
\n",
- "
91
\n",
- "
13
\n",
- "
71
\n",
- "
37
\n",
- "
34
\n",
+ "
11
\n",
+ "
70
\n",
+ "
24
\n",
"
\n",
"
\n",
"
\n",
"
105
\n",
- "
86
\n",
- "
19
\n",
- "
72
\n",
- "
35
\n",
- "
37
\n",
+ "
17
\n",
+ "
71
\n",
+ "
34
\n",
"
\n",
"
\n",
"
\n",
"
106
\n",
- "
83
\n",
- "
23
\n",
- "
73
\n",
- "
32
\n",
- "
41
\n",
+ "
21
\n",
+ "
72
\n",
+ "
37
\n",
"
\n",
"
\n",
"
\n",
"
107
\n",
- "
76
\n",
- "
31
\n",
- "
74
\n",
- "
31
\n",
- "
43
\n",
+ "
29
\n",
+ "
73
\n",
+ "
41
\n",
"
\n",
"
\n",
"
\n",
"
108
\n",
- "
73
\n",
- "
35
\n",
- "
75
\n",
- "
24
\n",
- "
51
\n",
+ "
33
\n",
+ "
74
\n",
+ "
43
\n",
"
\n",
"
\n",
"
\n",
"
109
\n",
- "
68
\n",
- "
41
\n",
- "
76
\n",
- "
23
\n",
- "
53
\n",
+ "
39
\n",
+ "
75
\n",
+ "
51
\n",
"
\n",
"
\n",
"
\n",
"
110
\n",
- "
61
\n",
- "
49
\n",
+ "
47
\n",
+ "
76
\n",
+ "
53
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
111
\n",
+ "
55
\n",
"
77
\n",
- "
21
\n",
"
56
\n",
"
\n",
" \n",
@@ -1152,21 +2642,19 @@
""
],
"text/plain": [
- " kms km rides kms gap miles miles rides miles gap\n",
- " 100 107 -7 67 74 -7\n",
- " 101 105 -4 68 67 1\n",
- " 102 99 3 69 54 15\n",
- " 103 97 6 70 44 26\n",
- " 104 91 13 71 37 34\n",
- " 105 86 19 72 35 37\n",
- " 106 83 23 73 32 41\n",
- " 107 76 31 74 31 43\n",
- " 108 73 35 75 24 51\n",
- " 109 68 41 76 23 53\n",
- " 110 61 49 77 21 56"
+ " kms kms gap miles miles gap\n",
+ " 103 4 69 13\n",
+ " 104 11 70 24\n",
+ " 105 17 71 34\n",
+ " 106 21 72 37\n",
+ " 107 29 73 41\n",
+ " 108 33 74 43\n",
+ " 109 39 75 51\n",
+ " 110 47 76 53\n",
+ " 111 55 77 56"
]
},
- "execution_count": 98,
+ "execution_count": 91,
"metadata": {},
"output_type": "execute_result"
}
@@ -1179,7 +2667,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "I need three 102-km rides to improve from 101 to 102; In miles, I need one 68-mile ride to improve from 67 to 68.\n",
+ "I need four 103-km or thirteen 69-mile rides to increase my Eddington numbers.\n",
"\n",
"Here are some properties of Eddington numbers:\n",
"- Your Eddington number is monotonic: it can never decrease over time. \n",
@@ -1215,7 +2703,7 @@
},
{
"cell_type": "code",
- "execution_count": 99,
+ "execution_count": 92,
"metadata": {},
"outputs": [
{
@@ -1255,12 +2743,12 @@
},
{
"cell_type": "code",
- "execution_count": 100,
+ "execution_count": 93,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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jowMpJd3d3YTDYfr6+ohEIgwMDODz+fD7/fT39xMKhejp6SEajdLZ2TkmhvFvV1cXkUiE3t5ehoaG8Hq9DA4OMjg4iN/vZ2hoiN7eXiKRCF1dXQljdHZ2Eo1G6enpIRQK0d/fn1BTNBrNSlMgEEipqa+vL2tNXq9XqaZ07eRyubLSlK6dfD6fUk2hUMhy34vXFAwGLfc9sybjvarayYhppe+ZNbndbuV9T0ppue+ZNe3fv99y3zNrCgaDyven/fv3W+57Zk1SSst9z6ypp6dH6THC7XZb7nvxmgClx71gMKjk/GRoGhoaUnZ+MjT5fD6lx3KXy6Xk/GRo8vv9lvueWZPb7VZ2fjI0GedTVccIv9+v9JwbCoWUnZ8MTV6vV8n5ydBkPg+oOEYYxxuVx4hAIEAkEiFX8uIx5StXrpSbNm2yHKe1tZXly5dbT8hEf38/1dXVkyae46EaVPuou2bHQz1jOh5aR3cP7YjpeKhfPOfcrAbDRyHEZinlymw/r/VIdT5QWlo6qeLZge6aHQ/1i2cH+aBZdx8dD62TD5odD/WLZwe6a9bRQ6eotsjAwMCkimcHumt2PNQvnh3kg2bdfXQ8tE4+aHY81C+eHeiuWUcPnaLaIlOnTp1U8exAd83meC0tLbS0tCiNr4J88lBX8kGz7j46HlonHzQ7HuoXzw5016yjh05RbZHu7u5JFc8OdNfseKhfPDvIB826++h4aJ180Ox4qF88O9Bds44eFkx0AvlOQ0PDpIpnB7prbmhoGB2dbmtrAxj9ubm5Wem2ciUfPNSdfNCsu4+Oh9bJB82Oh/rFswPdNevooTNSbRFjGZbJEs8OdNfseKhfPDvIB826++h4aJ180Ox4qF88O9Bds44eOiPVFmlsbJxU8exAd82NjY2jI9K6jVAb5IOHupMPmnX30fHQOvmg2fFQv3h2oLtmHT10RqotovuVl45XcvHortnxUL94dpAPmnX30fHQOvmg2fFQv3h2oLtmHT10RqotovuVl45XcvHortkcT7cRaoN88lBX8kGz7j46HlonHzQ7HuoXzw5016yjh85ItUWMx4lOlnh2oLtmx0P94tlBPmjW3UfHQ+vkg2bHQ/3i2YHumnX00CmqLVJTUzOp4tmB7podD/WLZwf5oFl3Hx0PrZMPmh0P9YtnB7pr1tFDp6i2iNfrnVTx7EB3zY6H+sWzg3zQrLuPjofWyQfNjof6xbMD3TXr6KFTVFukrKxsUsWzA901Ox7qF88O8kGz7j46HlonHzQ7HuoXzw5016yjh1oX1UKIi4QQN/X19eH3+/H5fAwMDBAIBOjr6yMcDtPd3Y2Uko6ODuDA3aAdHR1IKenu7iYcDtPX10ckEmFgYACfz4ff76e/v59QKERPTw/RaJTOzs4xMYx/u7q6iEQi9Pb2MjQ0hNfrZXBwkMHBQXp6ehgaGqK3t5dIJDI6xyc+RmdnJ9FolJ6eHkKhEP39/Qk1DQ4OZqUpEAik1LRnz56sNXm9XqWa0rXT0NBQVprStVN3d7dSTV6v13Lfi9cUDAYt9z2zJr/fr7Sddu/ebbnvmTUFg0HlfU9KabnvmTXt3bvXct8za+rv71e+P+3du9dy3zNrklJa7ntmTfH9xuoxIhgMWu578Zr8fr/S414wGFRyfjI07du3T9n5ydDU3d2t9Fg+NDSk5PxkaPL7/Zb7nllTMBhUdn4yNA0ODio5Pxmaenp6lJ5zQ6GQsvOTocnYnqpjhPk8oOIYYRxvVB4jAoEAkUiEXBFSypw/PF6sXLlSbtq0yXKc1tZWli9fbj0hE4ODg0qvlnSP53ioBtU+6q7Z8VDPmI6H1tHdQztiOh7qF885N6vB8FEIsVlKuTLbz2s9Uu3g4ODg4ODg4OCQDzhFtUWsfE2Qj/HsQHfNjof6xbODfNCsu4+Oh9bJB82Oh/rFswPdNevooVNUW6SoqGhSxbMD3TU7HuoXzw7yQbPuPjoeWicfNDse6hfPDnTXrKOHTlFtkcHBwUkVzw501+x4qF88O8gHzbr76HhonXzQ7HioXzw70F2zjh46RbVFqqqqJlU8O9Bds+OhfvHsIB806+6j46F18kGz46F+8exAd806eugU1Rbp7e2dVPHswJxjS0sLLS0tyuKpIN88nAzx7CAfNOvuo+OhdfJBs+OhfvHsQHfNOnroFNUWmTZt2qSKZwe6a3Y81C+eHeSDZt19dDy0Tj5odjzUL54d6K5ZRw+dotoixoLhkyWeHbS3t4+OULe1tdHW1mZpxHqyejiZ4tlBPmjW3UfHQ+vkg2bHQ/3i2YHumnX00CmqLdLY2Dip4tmB7ponm4ctLS08/PDDyuLB5PPQjnh2xVSJ46F18kGz46F+8exAd806eugU1RbR/cpLxyu5eNrb22lubqa5uZmmpiaamppGf841nur8xpNcRulV5+jxeJTGy5d+qHM8u2KqxPHQOvmg2fFQv3h2oLtmHT0ssCuwEOJm4EKgW0q5zPT7fwb+CYgAf5NSfsWuHMYD3a+8dLySi0d3zZPFQ6OQb2trG/Nzrhc3ZiaLh3bGsyumShwPrZMPmh0P9YtnB7pr1tFDO0eqW4DzzL8QQpwBXAIcKaU8HPiBjdsfFzo7OydVPDsw52hlhDpRPBWMl4dW5pWrzrGyslJpvHzrhzrGsyumShwPrZMPmh0P9YtnB7pr1tFD20aqpZRPCSHmxP36c8B6KWVw5D3ddm1/vKivr59U8exAd82TxUPjYkblCLXBZPHQznh2xVSJ46F18kGz46F+8exAd806ejjec6oXAacIIV4UQjwphFg1zttXTl9f36SKZwe6ax4vD63MK1edY0GB2uttpx/qG1MljofWyQfNjof6xbMD3TXr6KGQUtoXPDZSfZ8xp1oI8SbwGPAFYBVwJzBPJkhCCPFp4NMA06dPP+b++++3nE9vby81NTWW45iJRqO4XOquTcYz3tatWwFYtGhRxvEcD9WQysdc2iWbHDOJn+8e5kI+aFYd0/HQOrp7aEdMx0P94jnnZjUYPq5YsWKzlHJltp+3bfpHEnYDfxwpol8SQkSBWmBv/BullDcBNwGsXLlSLl++3PLGW1tbURHHTH9/P9XV1XkZr7W1FSArTxwP1ZDKx1z8zSbHTNo93z3MhXzQrDqm46F1dPfQjpiOh/rFc87NarDq43gX1X8GzgSeEEIsAgqBnnHOQSmFhYV5F8/OVR5yIR891I1Mcsym3R0P9YtnV0yVOB5aJx80Ox7qF88OdNeso4e2zakWQtwOPA8sFkLsFkJ8ArgZmDcyDeQOYF2iqR/5xPDw8KSKp5qWlhbuvvtupTEnm4egv2bHQ31jqsTx0Dr5oNnxUL94dqC7Zh09tHP1j6uT/Olau7Y5Eai+JhiPeHau8qADureJVRK1WyY5ZtPuh7qHicgHzbr76HhonXzQ7HioXzw70F2zjh6O9/SPQw7VT57TPZ4qzFMRPB6P0gJ/snhoRnfNjof6xlSJ46F18kGz46F+8exAd806eugU1RYJBAKUlJTkZTxdRqhV7xi6t0mupJoTbc4x3QVKJu1+qHqYinzQrLuPjofWyQfNjof6xbMD3TXr6KFTVFukoqJiUsVThZ1TUCbSw4maUqN7v9G1H5rJB826++h4aJ180Ox4qF88O9Bds44ejvfDXw459u3bN6ni2YHqB42k0pzNo78ziTeepHo4zL59+yw95jyeydgP80Gz7j46HlonHzQ7HuoXzw5016yjh85ItUXq6uomVTzVNDc3K7/ZIBvNmYwsZxJvopcp1L3f6N4PIT806+6j46F18kGz46F+8exAd806eugU1Rbp7Oxk+vTpkyaeHdipOX6kNr7ozTaeDiQq1Ds7O5VOqXH6oX7x7IqpEsdD6+SDZsdD/eLZge6adfTQKaotorpBdY9nBxOhubOzE4BgMAikLkQziTfRyxTq3m+cfqhvTJU4HlonHzQ7HuoXzw5016yjh86caou0t7dPqnjZksm8Xjs0x88vNjDmIzc0NNDQ0JBxPN0x52iea60ingryzUMd49kVUyWOh9bJB82Oh/rFswPdNevooTNSbZHGxsZJFc8OJkJzNiPL2eSXSTHb0tJCaWkpy5cvzzhuOnTvN04/1DemShwPrZMPmh0P9YtnB7pr1tFDZ6TaIh0dHZMqXqZksxKFHZqTrZSRyyjuRHmYDdnkmMm3B4dKP8yGfNCsu4+Oh9bJB82Oh/rFswPdNevoodZFtRDiIiHETX19ffj9fnw+HwMDAwQCAfr6+giHw3R3dyOlHDXX+Dqgo6MDKSXd3d2Ew2H6+vqIRCIMDAzg8/nw+/309/cTCoXo6ekhGo2OzrM1Yhj/dnV1EYlE6O3tZWhoCK/Xy+DgIIODg5SUlDA0NERvby+RSISurq6EMTo7O4lGo/T09BAKhejv70+oqaamJitNgUAgpSaDbDR5vV7LmlwuF0IISktLcblco8vmJdI0bdq0rDSlayePxzOqyeVy4XK5kmo655xzaG5uTqmpsrJytJ02bNjArbfemnXfCwQC3HLLLdxyyy20t7fj9/vZsGEDt912W859z6yptrY243Zyu924XK6U+5OxIouVvmfW1NDQoLzvSSnT7k/ZtFNRUZHlvmfWVFFRoWx/MjQVFRXl1PeSaZJSWu57Zk3GMSfb414yTQ0NDZb7Xrym2tpapce9YDCo5PxkaCovL1d2fjI0eTweJecnQ9O0adOUnJ8MTX6/33LfM2tqaGiw3PfiNdXU1Cg5PxmaSkpKlJ5zQ6GQ5b4Xr6mgoEDJ+cnQZD4PqDhGGMcblceIQCBAJBIhV4SOz06PZ+XKlXLTpk2W47S2tir9yh2gu7ub+vr6SRMvWw8zmV6hu2ZzPCs3IpqX3Zs5cyZutzvnWKlyzGT7EJtfnmz7urcJqN+f80HzRO/P6XA8tE4+aHY81C+eU9+owfBRCLFZSrky2887c6otMmXKlEkVzw501zxlyhQl61Cb53GXlpayevVqpTmqRPd4dpAPmnX30fHQOvmg2fFQv3h2oLtmHT3UevpHPuDz+SZVvGzJZA6z7pon2sNMyCTHVE9kzCWe6vwmmnzQrLuPjofWyQfNjof6xbMD3TXr6KEzUm2RkpKSSRXPDsw5qljn2Q4PVa5D3dzcTGtrq+W8zOjeb/KtH+oYz66YKnE8tE4+aHY81C+eHeiuWUcPnZFqi4TD4UkVzw5013yoeZjJtweOh/rFsyumShwPrZMPmh0P9YtnB7pr1tFDZ6TaIkKISRXPDoQQSuYsG59zuVysXbtWaX4G4/2kxEzRvd/kSz/UOZ5dMVXieGidfNDseKhfPDvQXbOOHjoj1RYxVnCYLPHsQPccdc8P9O83h7qHidb+tkOz7j7mQ7+ZbB7aEdPxUL94dqC7Zh09dEaqLRIKhSgtLZ008ewgFApZnrNsHukuKSlRMvfZnF8yD+O3o3K72aB7v8mXfqi7Zt19dDy0Tj5odjzUL54d6K5ZRw+dotoiqhtU93iqaWlpQQjBunXrlMUMhULKYoF6D+MfU66iENe93+jeDyG3HFNNW7JDs+4+5kO/mWwe2hHT8VC/eHagu2YdPXSKaosMDAxQW1s7aeLZgfkrnFwLS/NIcUFBAddee62CzGIk8jC+mFq/fj0AwWBwzN/Ha8R6PPtNLtryoR/mw76nu4+Oh9bJB82Oh/rFswPdNevooVNUW2Tq1KmTKp4qzEWp+UZFFUWolUeMJkKVh/FPVFRZiOveb3Tth2ZyyTHVtB87NOvuYz70m8nmoR0xHQ/1i2cHumvW0UPnRkWLdHd3T6p4dlBRUaEsVnNzM+edd56yeJDYw/gHqdxwww3ccMMNGT1YxQ7Go98YN+O1tbXR1taW8OY8u/LLZlu5kg/7nu77s+OhdfJBs+OhfvHsQHfNOnrojFRbpKGhYVLFU0WyET4VI9a6ehj/mPJPfOIToz/H/93883jmmC/x7MBKjonayg7NuvuYD/1msnloR0zHQ/3i2YHumnX00Bmptkh7e/ukimcHHo9Habzx9DB+RHq8R6gNzDmqGNVNpDmbx5xnEi8TrIyOZ0s+7Hu678+Oh9bJB82Oh/rFswPdNevoodZFtRDiIiHETX19ffj9fnw+HwMDAwQCAfr6+giHw3R3dyOlpKOjAzhgckdHB1JKuru7CYfD9PX1EYlEGBgYwOfz4ff76e/vJxQK0dPTQzQapbOzc0wM49+uri5aWlq49dZbGRoawuv1Mjg4yODgIGVlZQwNDdHb20skEqGrqythjM7OTqLRKD09PYRCIfr7+xNqqqury0pTIBBIqcnlciXVFIlE6O3tPUiT1+tVqilVO5177rlcc8013HbbbbS0tLB3717a29u55ZZbuOWWWw7S1NLSwsaNG1NqKioqUqqpurract8zt9Pq1atpamoa1bR27VrOO++8UW1tbW309/fT0tLCbbfdllE71dfXj2oyLlKstJOxqH4iTRC7uTRd3zPvT42NjTn1vYKC2JdpVVVVY7R1dnYipbTU9+Lbqbi4OCtN6fanqqoq5ftTcXGxpb4Xr0lKmZWmdPuTgapjRGNjY07HvVSa6uvrlR73gsGgkvOToamiosJy34vXVFRUpPRYPn36dCXnJ0OT3++33PfMmhobG5Wcn8ya6urqLPc9s6aysjKl59xQKKTk/GTWVFhYaLnvmTWZzwMqjhEGKo8RgUDA0n1ZQkqZ84fHi5UrV8pNmzZZjtPa2jq6jFm2JPtK3tiBVaF7PCseJqO9vZ2HH34YOLCaRlNTE3Cw35lMjdDJw2T5JvIxfkWRZB4kyzFTDzNBJw8hsY+q+6JumscjpuOhdXT30I6Yjof6xbPr3KyzZjva2fBRCLFZSrky2887c6rTkO7x2aobVKd447UsXGNjY9r5xJk+xtyOnFW3STKszKnWqd+MRzw7yAfNuvvoeGidfNDseKhfPDvQXbOOHmo9/SMfiP/a81CPZweqczSmDKgil/zGcy4wxHK0Muc5UTzV+VlhPOaq66Z5vGKqxPHQOvmg2fFQv3h2oLtmHT10RqrTkG70sKamRun2dIiX6aiwKsw5JttGNiPZLpdLac6q2yQdueSsQ78Zz3h2kA+adffR8dA6+aDZ8VC/eHagu2YdPXRGqi3i9XonVTw7UJ1jSUmJ0njZ5GeMSKscNc42RxXbcvqhfvHsiqkSx0Pr5INmx0P94tmB7pp19NAZqc6QZEVKWVmZ0u3oEE/lmtGZkE2OmYxkCyFYt26dgsxiqG4TO8gmx0zaVYd+ON7kg2bdfXQ8tE4+aHY81C+eHeiuWUcPnaLaIsFgkOLi4kkTzw5U52gsI6iKTPJLNmVmvNC930zGfmiHZt19dDy0Tj5odjzUL54d6K5ZRw+dotoiqm+K0ymeHSPUiUZJVWpubm5mcHBQWTxQ3ybZksnIciY5ZjNXXqd+OF7kg2bdfXQ8tE4+aHY81C+eHeiuWUcP9cvI4ZDC6hSS8ZqCYpX4KTMGdtzsmS+eODg4ODg4TCacotoiVp68k4/xciXVKGmqHI2nHmWDnR6OZ0GbzLNEnmSiOZu58odqP0xFPmjW3UfHQ+vkg2bHQ/3i2YHumnX00CmqLVJUVDSp4mVKfEGYKo9EfzM+HwwGx/ycSTGrUnO2Nz7m8jCaTLUZxXQiT3TvNxPVD7MhHzTr7qPjoXXyQbPjoX7x7EB3zTp66BTVFhkcHFQ6UV73eLnS0NAw5mdzAZkox/jR2GxGrM3xVIwsm9e9Hq+1u82xk41Qm3/Opp0zyflQ7YepyAfNuvvoeGidfNDseKhfPDvQXbOOHjpFtUWqqqomVbxMSTbVINGqGDpqjn+YjMfjySlOJiPUyVYMMT5rFM/GhYnxfvOFio4e2hnPDvJBs+4+Oh5aJx80Ox7qF88OdNeso4dOUW2R3t5epk2bNmniWSVRkZkox1QFZDp6e3t54IEHxnw+WcGaCWVlZYRCoYzea8cItqHdiPmNb3zjoG2YPVSRw6HeDxORD5p199Hx0Dr5oNnxUL94dqC7Zh09dIpqi6huUHM8FcWRnR0uk/wymWOcKEfj7+vXr0+7jXhUaDZvPxQKHVTkZ0oqj+I1GhjbMH5vzKGOf5859mTuh6qw00OdY6rE8dA6+aDZ8VC/eHagu2YdPdT6MeVCiIuEEDf19fXh9/vx+XwMDAwQCATo6+sjHA7T3d2NlJKOjg4A2tvbAejo6EBKSXd3N+FwmL6+PiKRCAMDA/h8Pvx+P/39/YRCIXp6eohGo6NfsxsxjH+7urqIRCL09vYyNDSE1+tlcHCQwcFBtm3bxtDQEL29vUQiEbq6uhLG6OzsJBqN0tPTQygUor+/P6GmnTt3jmoyphyk0hQIBFJqevvtt7PW5PV6M9Jk5JdOk7mdEmnas2dPUk2NjY3MmDEjq3basmULV111FZdddhlz585l7ty5uN1uhBD09PSwa9cubrvtNlpaWtK2U3FxMdXV1VxxxRVcfvnlzJkzh3nz5rFmzRouuOCC0b7X0tLCxo0baWtro7+/n5aWFm677TYA3G73Qe0UDAbZsGEDt912G6FQiKKiIjo7O0fX2Da+1iorK8PlclFWVkY0GsXlclFYWEhhYSH79u1j79699Pb2jtHU399PW1sbGzdupKWlJeO+Z26nt95666C2zrbvmdvJeKnqe52dnUgps9KU7hixdevWrDSl25/ef//9rDWla6etW7dmfdxLpUlKmdNxL5mmN998M6fjXjJN7e3tOR33UmnatWuX5b5n1hQMBpWcnwxN27dvV3Z+MjRt2bJFyfnJ0LRnzx7Lfc+sye/3W+57Zk3t7e2W+168pp07d1rue2ZN27Zts9z3zJpCoZDlvhev6d1337Xc98yazOcBFccI43ij8hgRCAQsrSoipJQ5f3i8WLlypdy0aZPlOK2trSxfvtx6QjYTP9e2qakJyG1lCdV5lZaWjh4A0+UX/9lsP6OCZOtGp9t+snwNkrVF/Gonxihz/PZaW1tpbW3NaBvxNyoaMY1t3HDDDSlzzrXf5Npm49Uv82V/1hnHQ+s4HlrH8dA6jodqMHwUQmyWUq7M9vPO9A+LtLe309jYmNF7Myk2jKulTMhkRYxs8rODTB7XrTpHczwVFyLmmyGSfS7dw1/icygtLU16M2f8NA+DVPPM29vbs1qHOh3Z9MNM401kP8wEO/uhzjFV4nhonXzQ7HioXzw70F2zjh46RbVFVDdoY2Nj2uIomzWcVeRnHrGcOXMmbrcbODBSmknxlkqTHR5axWqBmurznZ2dKW+8TLX8IBw8zzzXked0/UZlfN0OfInQsR+OR0yVOB5aJx80Ox7qF88OdNeso4dOUW2RdAUSZFfMpIqXyXrFueRnB+mWizOjOsdU8XIZvc1mOb1MpsAEg0GGh4eTLjeYrp8k0mbOUcW0i/FsE13IB826++h4aJ180Ox4qF88O9Bds44eOnOqLWLcPJaKbOampoqXbn6wgTluJvllSjZzqlVpTpRDsjiJ4mU70pzo/ao8NK/mMXPmTPbu3QscXCTnMo9bCMHs2bMTvi+ebD3MFjs9NKN6f1adox2aVcd0PLSO7h7aEdPxUL94E1XfHErxwJlTPeH09fVRW1ub8j3ZfI2eKF6ym+BU5WcHVjVbYTzjZVO0p1t7O5lnmcxLLysrS/uebNC9TewgHzTr7qPjoXXyQbPjoX7x7EB3zTp66BTVFqmsrLQtXibFFBy8KoS5KFOZX3Nz85ir4VzmGyf6TCY5ZjOFprKyMqv3p4oPIIRg3bp1aXNMh/lGRGNeerJtpsrJiGMuurPJMZP2stJvkrWJ7ti5L+scUyWOh9bJB82Oh/rFswPdNevooVNUW8Tv91NYWJjRezMpZhLFy2ZlCSv52UGumq1gTE9RRaKvl7It2s00NDSMmUYTTzYj1KlytIIdbTKR/TAT8kGz7j46HlonHzQ7HuoXzw5016yjh05RbZFUDZrLSG5hYWFWN/nBgWkEO3fuPGh7VvJL9/dcRqgTFaGZ7BTZTCfJZSdLdeHi8XhyXgUk2bYyGfHPRrPqeyNUH6jsPvCpaJ980KzbCSQex0Pr5INmx0P94tmB7pp19NApqi0yPDw8bvGS3ahmYBRW5gLDHE9lYaiS8fQwFxKNAme73Fy+oXub2EE+aNbdR8dD6+SDZsdD/eLZge6adfTQKaotkmiEMNOpAYl+L6UcM/c20efiSbXEXi755Tq1IdX7UhWh2YyyZlK8mj3MtuhN1EYul4u1a9dmnKNq0l1MtbW1UVxcrLTAVz3ybdcqQ1am4cSTD5p1X63J8dA6+aDZ8VC/eHagu2YdPbStqBZC3AxcCHRLKZfF/e1fge8DdVLKHrtyGA+yWcM403hGYZDu4S7JimDzqhLmeLmsHjIe2OGhSuzecdM9GTOTQlH1FbvubWIH+aBZdx8dD62TD5odD/WLZwe6a9bRQztHqluAG4FbzL8UQswCPgTstHHbyklW2AQCAUpKSsb8Lt0oaao50+ZVITIl1ch2IBA46P3pntiXLdmMFib6ndlDQ8MNN9yQcz7meFa1NTc309fXZylGMjK9eIp/f/w61k1NTbjdbq677jpluSXq1zrFM1A5DScfNNvloyocD62TD5odD/WLZwe6a9bRQ9uKainlU0KIOQn+9GPgK8Bf7Nr2eFJRUaE03vDwcMaFQnwBGl8sJ5vWkW51iWye2KgC1R6qjJfthVEmRV3LyEN00vmczTcMqkeqdW4Tu8gHzbr76HhonXzQ7HioXzw70F2zjh7a+kTFkaL6PmP6hxDiYuAsKeUXhBA7gJXJpn8IIT4NfBpg+vTpx9x///2W8+nt7aWmpiarz2zduhUAn88HHGjERYsWAdaulIzYBj6fD4/HQ3Fx8ZjfG9sy3m/83NraCpD0KUqtra0UFBSwbNmyhJ9Pl1cizak8zDR+PIFAgC1btgAHikNjxD6XJ0SpvHrdunUrQggWLlw4+rOZZP0iFa2trZSWlqaNkawdDMzb0n0EwI4RhVz251Tkg2bVMR0PraO7h3bEdDzUL55qD0F/zXaeV1asWKH3ExWFEKXAV4FzMnm/lPIm4CaIPaZcxeM3c3mMp1G47t69GzjwlbsRR0qJECLnfMzEbyN+1NN4/4MPPggcmDZgjHAaI9bxI5yRSCRhvGQY2oyR8E984hNjckhVxJs/nylSSp588knggCZjVDaXdrfSJgbxHg4ODo75e/xo/+rVq7OKOXPmzNELB+Nx5WafgYOW3DO2Yfxs9iYbzZku0WfVQzvjgfrH8uaDZtUxHQ+to7uHdsR0PNQvnh2PKddds47nlfFc/WM+MBd4bcSEmcArQohjpZT2zi+wQLqpGJ2dnUyfPt1SbIOWlhY8Hg9r1qw56PdwoMBL1omM95mnEVRVVY3+nO2800TTSUpLS5Our5zrfNbOzs7RCwIVc6qttEkizB7Gz3/ONq9EP8f7nO5ziXxWrVn3eHaQD5p199Hx0Dr5oNnxUL94dqC7Zh09HLeiWkr5BlBv/Jxu+ke+oLpBw+Fw2vfMnj0bSD5CbRRpbW1teL3e0ZHvbMm2SM71ZjHVHqqIZ775c2hoaIynid6XCfExjJ/TxUhXdENmmrOZB27Fw0RxdTvwJULHfjgeMVXieGidfNDseKhfPDvQXbOOHtq5pN7twOlArRBiN/B1KeVv7dqeauJHTJMVPu3t7TQ2NirZZnNzM+3t7Ql/DwcXK0aOyVaFgNgoq0Eu62bHx585c+bodq2M2poxexg/Qp1Loa6iTcwrc5g9TDY1JxOMz3zjG9/IKEY2RbBZs4qVMFT26/h4KtfTVomdmnWOqRLHQ+vkg2bHQ/3i2YHumnX00M7VP65O8/c5dm17PFHdoNnEix+hjkcIwcDAANXV1QoyS06yqRGJiqZ0K5KoQHWbeL1epR4KIZTPA8tEczae5+JhqosA3Q58iZjIfXkiY6rE8dA6+aDZ8VC/eHagu2YdPXSeqBhH/Chsqjm+yeZAW6GjoyPpVxrJiqD4YskocqWUVFVVsXNn4iXB44vxROtmx8cvLS0dvaHO8CbZ1IhMMS/gni6nTIrvVB5milmzqjY2/JJSIqVMO388myK4o6ODhx56CFDzdEEVHsbHU5mfHdihWfXXk3bEVInjoXXyQbPjoX7x7EB3zTp66BTVFslkDrRBJkVEJvNns8Hr9SofFY1/aImBsWJHqhFqo6BSPYXEjBUPE7VRNm08UWSjOdNpJ9kWu6kuAtLlp0OBrXrfUx3PrpgqcTy0Tj5odjzUL54d6K5ZRw+dojoOY9Twm9/85pifzZgLxPLy8qQju7mwd+9e6uvr078xAfHbXb9+PaWlpXz+858Hko8Cxz9UJNV0jtbW1oOWAjQIhUI55V1eXn7QNs1PCzS2nSlWPEy00kZ3d3dOseIxr3DidruTjlDnsqrK3r17lU6pKShQe2hQnZ8dWOk34xHPrpgqcTy0Tj5odjzUL54d6K5ZRw+dojoO44RvPBQnXQHg9/vTLriezQ1nU6ZMSRsn02IkFAqNrlGtkvgbJQ1SeZbqZsvh4eGMp5Ck8yDXgi1+9N0cJ1Wb6IKKHM391OVyWR6xNpMsv2z2DbtR3c529Bvd+6LjoXXyQbPjoX7x7EB3zTp66BTVOWAuEN1u9+hTALMtDBK9z+fzMXXqVCV5zp49e/QBI/F5pyL+K5V0Oqw+1rywsHB0G8Y3BFaKKrPmTEmlQWWbQMxf8xMVDTItMBPNxTbnqKIgjX+qZ6I8M92OsZ9cd911WX1uvFHdzqrj2RVTJY6H1skHzY6H+sWzA9016+ihU1THke1X1NFoNOOYRjGUbKQXSPjIzWxH88zv93g8OY/+pbvBMX5ONVJSRJDyYD+l+GHLAxD0QXAAhgYg6KO5zgdBHx9873e4ZYQrh3x4gsPs/c5vccsIn40GEUi48V6Q0ZGXxOsbJCpcnBceJoqL7u/+GImLaTNmg6eM93d3EBFFHLZ/iIiriM0/eZCQq4QTzjgPiquguDr2b8kUKJ0KrrGFd7I1pCFxm+hES0sLQgjWrVtnKY6576uIZybZfqLTlBDV7WxHv9G9LzoeWicfNDse6hfPDnTXrKOHTlGdJVJKIlHJcFRy5dXX0u8doKy8nOGo5PY77kAiOP/y1UgJHd4AUsJdf/gDAL0BCUj+8zs/ACAUiiKAG3+zAQGsueZq9u8PUO3y4BYCt0tQ4Ep+k2EmhUgmo7bJRqbHFP1BH3h3U9H1Egt9mykd7udIuZsK9lPBIKUEKMOPmyjIkc/cfsfYDQk3FFdCYQVTwkGGRQF+okSFB2/IRYQSopQhgZ4+NxI3S5ceDkLQ+/52XHKYofB+XEQpE0W4GIaQHwZ7qA12UiBDzGaIwmgYV/9IEvf8IYFiESusy+pGXrU019dDRQP37tmKj0quuXANVMbuKg6Hw0l33mymo5gvdmbOnJl07nS6Eer4lWkaGhqU34yaKJ6Vi7vi4mItCudUpGpnHeLZFVMljofWyQfNjof6xbMD3TXr6KFTVCeh7uhz+fpf3+TH33iYyHCUSPRAMZ2cWgB++J1H435fM/bfuAFetsX++f43H0kYVYg6ClwCGa3FLSRlu4rxuAXBgB+3kNz+46fwFAiKCtwUFbgoKlhKUYGbbREPhQFYOeUoij1u1n3/LjwuSYEoweOSDESmUiCGGR70UOiSlDNIw3AHf/yfa6mjjwuGe5mCl8H//ill+IHYs+bnx7JiP6X4RAUNC1dCWQ3PvrqFQVHKOZdcDWW1UDI1NjpcVBF7eUpgpFirHtF2b0sLLpdr9KE3RsFYVBi7eXLpR2JTHOaNvD9ZYVZp+rvL5WLt1VfGRseH+mHIe+Dl7wN/DwzuHXn1QuebsL8bgl4uMgLe+PvYv8VVlFXMhJq5UD0bqpti/05pgilzE7bXeGHcGNrW1kZRUZGyorW5uRmfz2cxu7EY8+1TbXOiGY8LEx1jqsTx0Dr5oNnxUL94dqC7Zh09dIrqJEyvLuacwxvwuAQFbhcF7tiocYHLRYFL4HYL3EIwHAlTXFSE2yVwCePBHiCI/esa+T/AM88+i7m06O3tRQJTp9YQBY499jiGgiEKCjxEopLHn3iCKIITTzyJSFTS+vobDEuIyiDDErzRQaIIXIPDBCVUT59BMDLMjj2dRKRgKFLMcMTFBy99QCQqCMsyAMrxc5jYySLXbhaIPSzs3M1C1x6mif7R3IaloIMadkXreZFF7JG1RGsWsDdaSUfAg99dxeDgfgoZpqGrihK3JOA+jCIxzPwZF1FV4qGqxIPH7crI71TTL3LCUwKeElrueQDIsGgLDcJAB/jaYcD06v0AerfB9scg7B/zkcsop5cpbPnBnXg99Rx73lVQu4gNf30SKVwJR3VbRtb7Xr16dcI04nM1PmtePQTGepZqGlJ8sZ3rNxzZTtUwv9/lcrF27dqU759ocpmLP57x7IqpCjvaebJ5CPmh2fFQv3h2oLtmHT3UuqgWQlwEXDR37lz8fj/Dw8NIKfF4PAQCASoqKti3bx91dXV0dnYyffr00cdWdnR00NDQwN69e5kyZQo+n49IJMLAwABCCNxuN6FQiNLSUgYGBpg6dSrd3d00NDTQ3t7O0bMbaSgI0NjYSFdXFzU1NXi9XsrKyggGg6NLju3bt4/a2loGBwepqqqit7eXadOmjeZh/NvZ2Ym/eoiCggKGh4dxuVzs8ntxuVw01lQgpeSiw6qIRqM8+OCDRCIRTqz24fV6mbZ3E+FwmB9edy4NDQ1s3LiRSCTC3r17CYfDzJw5c8SxLYgiQXRuFLfbzfvvv8+MKcWUDWxjdmE/lYMf0OjqZWq0d9TjoCgiNGUR/WWn8EbZPHqK59DhnkGPp5GnX34NfyTK7HmLiIgCegcG6R8M0h8aYmhYMDRcThQBXUa02Hjxn3745Gj8skI3U0o9lBe6qK0spdg1zPSplXiiQZoaanDNWUV9VSlvbHqBIsIUlZQSjYRxuWLFuN/vH9NOa9euHV3iLt7jrq4urr32Wvbs2cPQ0BDBYHA0jtfrpaio6KB22rhxI+FwmHPOOSfWTpFy6ptOpq+vj8rDKvH7/QwNDVFWVoaMRvGEvYS6t9H62J+pivYi+rZT7/bR6G+lOOqH2/8MwBrhYcAzjT1U0F8wjbB/AG9RI76BWJsLIQiFQgn7XrwmiB08DE3Gw3Iuu+wyioqK+NWvfgXA+eefz7Rp0/j5z3+Oz+dj7dq1NDY24vF4CIfD9PT0UFlZSX9/P5FIBJ/Pl3R/am9vZ8GCBbS3t/Pwww/j8Xi45ppr2Lt372g+gUCAcDicdn/yeDxEo9ExmpLtT5FIJGE7JdqfpJSjmvx+P4WFhZaOET09PdTV1WWkKVE7xWvy+/2x6WJZaKqvr4/1vSSaenp6mD59elbHvZKSkqSapJR0dnZmrClVO8GBBzlloylVO5WWluL1erPSlK6dCgoKCAQClvqeWZPR1lbPT4am/fv3A1jqe/Ga9u7dy4wZMyz1PbMmj8eD1+u11PfMmvx+/5h+Y/UYYWzDSt+L1+RyuRgaGrLU98ya+vr6Rr/BU3GMCIVCBAIBS30vXlN3dzezZ8+21PfMmoqKiujv77fU98ya9uzZw8KFCy31vXhNgUDA0qppIt3XsjqwcuVKuWnTJstxWltbWb58ufWETIRCIQoLC7P6TPzcVPNazKFQiB/96EeAaSrEyDrS8esax68C8f+++x3qZTcfO/tw2PUSA+88RmWkZ/T9+6ikg3qGqhfRVziTvsJG/O5qmj/2sYR5GitxfO1rXxv9ndnD3/2uhYiES668ioFAmN/f/ReGoi6OPek0vIEw/f4w/YEQXn+Yff4Q/SO/2+cP0e9P/kCVIhFhRm0VtWVF1JQXUlNeSF15MXUVRWNeteWF3H7braPeGd4KIUYPVok8TuVhIlK18ZjP+/tiI9o9W6H7Hdi7hf0fbKJ8eN+BDxSWQ/1SegoaqF12Bkw7AqYthcKyg2In6ycG5hVT3G43X/3qV8fkFD/6b/Sj+LXAE404mzWrmFaSy36SDtX7s+oc7dCcTcxM2k2Fh+Z+6na7Ry/yVUzpmWgPM0H3fmhHTMdD/eLpUt/kczw44KMQYrOUcmW2n9d6pDofGBgYoLa2NqvPpPoafWBgIO3njc9FhgaZSQfP/M8FzI7u4ouynUIicD/43ZXsK5rDtqqTOfrDH4eGI/jLXX9NuP1kzJ49O+XfhQCPgPvvid2QKPe2UQT0vxab6/uFFCfVyHCU/kCY7/30F8jCMs487yJ6B0P85cFH8UcLmNMwi579Qd7r3s/z7weTFuElrhrKC6I8+tsXqa8opmtvGdWFUOoKU1kQxS89FHPwZ1OtSx1PojZO9nmD5uZvA3B3SwsF0SGuPWcVdL0Ze3W+yZTdj8KOWHsgXFC7GBpXQOPy2L/TliX1zljuz9imlJLi4uLRiyDjgiJ+9Zb4h/OkWvpwYGCA++67D1CzhnQu+8l4ozpHOzTr7qPqm4Ymo4f5oNnxUL94dqC7Zh09dIrqJGRaQKhcI9HYZtL5xZEQ7H6Zo/ofpGHoPer4gAKGiQ4LOqnnVZaxm0a6C5vwiipu+Mq/MysaBZcr4XaSFUuZrvKQaXGeiNtuvQWAssgAYtjHa3/bAMAyEQQ3NIWjUETsNRWuuXYtvYNB9vqC9OwP8ucHH8cXcdGxbxB/xMOW90O8Gi1gUBYjMeudgkDS0FHCtMpi7vz2H6kqGEYEwpS7whRFyygTITo6Okl2z4OVNh7j2cxjRv/7xquvsnzO1FiR3fE6tL8K2/4Or8VukIzionnaUpi5kmd8QfYWzcEroyBco4W8uWgeHBw86GZA4wo+fn56JvPWVa/9qdtaoonIB82pYsbvh+P1QB07l0Ucbw91IB80Ox7qF88OdNeso4dOUW0RY15OLiQ6+Xg8HtasWQPEvsavlF6al0Xhvb/D974Kof2sQEDDEbzpP4XO4oW84S0nKIoPTBdxxb7mb2lpGRPPShGcK8mmV5hHSSsqKtKuNlFY4GJ6VQnTq2IjYTtfGAKgbTBWWBpTG4aGghSUT8FdPpWBiIvdvfsZjHqYt+BougaG2B10s21/IWE59uErriFJlSfKaze9wIwpJcyoLmHmlBJmTCmhODLIkQtmUeA++CmDORcyQoysINIESz4c+52U4Ovg0dt+SG1wJ0eVR+CtP3HykDemjSLaXY3sktPYyQx200hYFI56aDxdyii2Dc/jc4lfLz0R3d3dSoslK/vJeKE6Rzs06+6jMadaFZPRw3zQ7HioXzw70F2zjh46RXUc2a7Fq6JBzdsUMsqDv/wqMwNv8tnhd6gOd8F9QNVsOHI1zD8L5pwEJVPYNPK5KSP1YaIRyHD44KkP6YqlZH83Vq1QMW/LPBo/MDBw0Hxfo+jOZHqGOd4BDdeO+RyDr7LMDQvcbUgX1M+aw0DYxY69A+yPelh27Kns6Q+wZ5+fp9/bS7cviHng1+16i8bqYgqGqqj2DLP/sfeYNbWU3YECpniGKXXLpCPdmdKyITZa37a3EljGq1OaYNpFVIX3UhfcMfJqY070RVxIotJFn2cGHwxPY7d/FqGKowkUVKZ8XHwirxKh+kCl24EvEfmgOVHMZHPvU82ZtwM7tjNeHupEPmh2PNQvnh3orllHD52i2iLGHaNWcEdDzAi8y3L5PIvFB5R0BRimAPf8U2HBv8CCs6F2IfFVW/xJ7Bvf+MaYn9va2qiqqkpaXMXPqc11RDJREb5+/XrWr19/0INKjNFT86hpRUUFZWVlozlnQrLHihurTcQXGkbRDjEbS92SUvcwDbNi220+f8mYeMHIMB39Q+zpD/DG++08+9q77AsH6ApE6PQX8erDW0feGRsdrigqYHZNKbKgkqmeYZYcfhxzasroHhiirqJozHqaWV2cCBfewml4C6dx8j//EoAfffcbNEb3cNUJTdTufJ7qthdYNbwJdv8Jb0E978kGdjCT4Ug1gYKD2z+T9jX3axXFkor9xG5U52iHZt19dDy0Tj5odjzUL54d6K5ZRw+dotoiOTdo0Afv3g/v/JXr2h+FSIAAxWwTCzhi9Q2455+ZcEWIbPF6vVRXVwMHF83prvISzbFO9CRAg1Q3vhkkyyF+akL8vPJMSTYtI9lTI5NRVOBmTm0Zc2rLOGlBLcXtr4zJZ/qsJvaF3ewLudkXdjNt/uG09fp5Y6+bd32FPHPPG6OxSgvdNNWUMbe2lLm1ZezxFjFTuvD6w1SVHvwY+XRTSqZOb2KIJjgz9v6CSAg6X4e2Z6na8SxHbnuClfJ12H0/1C7i3WAdHcULwX9x7EmSGaD6QKXbgS8R+aA5m5jjNUJt5lDzcCLIB82Oh/rFswPdNevooVNUWySrK6XwELz3MLx5N2x9CCJDUDmDd0pWsrP0CF7q8lBROZXNL/bCi3/I+KRorPpgYMypbWpqGjOn2ijK4kdx4x9/rWIObfyDSuLn9xo0NzfT3t5+0Goa6Qr0VA+LaW9vTzmFJVvM8Qw9hS6YVjTMUOf7lABN+wLMc8GG/2kmMhylvX+ID3oHaesd5IOeQXb0DPLCu7t5IOxGUgkdcOM3H6bUHaW2sJrawgjhp95nfn0ZfSEX1Z4oyZ5Qf1C7FBTS7mqk8aQvwElf4Pbf/ZapoT00DG2jYfA95gZeZonvWeT3NtBbOIPaVVfAvNNh9gmxh+Qk0XyojyjEkw+adffR8dA6+aDZ8VC/eHagu2YdPXSK6jiyvTkrVYO2tLQgZJR1p86B1/8A794HwQEoq4MV18ERH4GZx/LiLbGVMKKibczIsgrC4XDKqRCZYC4o3W73QZ5ksjxdqrnqiTxMN7Js/GxcUJj/nqpNcrlQaGxszKroL3C7mF1TyuyaUqBu9PctLS0MS3hrRyeeqTPZuW+I/mgRfUEPbweKeeX+d0beWUNhgYt5tWUsqC9nf1kpdYURTjr/IppqEn97Yda87mOfGN3eW1VnsnPHB8ygkxXVAzQGtsDzv4BnfwruImg6gZf3VbGn5DAu/dQNo1OMJsOIQjz5oDlRTDtX38iWfPVQJ/JBs+OhfvHsQHfNOnroFNUW6erqYtq0aQf/oXc7K/b9jQX7X4Jb+6GoCg67GI64AuacCu7E1ldUVGS8beMkaqwnbRSsxs/Nzc10dXXxwAMPjPmcUbDGr2NsEL8OcrqTdLL5zeZtpaKrqyvpyhTpRpbjF35vaWmhoKCAa6+9Nu12M8GIF0+200nM74nNqS7ksKoIMExb2/sA1M2cQ0/QzZJVp7F9737e697P67u97OwrBQR/+PFTFLgETTWlLG6oYNG0A6+S4f3MmJ44p5iHcznayDG4H3Y+D9sfh+2PsWrfE6za9xf48a0w/0xYcDbdFYdTP3uh6fPWirWk+4lGqM7RDs3mmDoU0fHkm4c6kg+aHQ/1i2cHumvW0UOnqE5CpieqmpqaAz8E98Pbf6bzwR/RENzOEQi208TuukvZXbKM4X4PPL2T5vnJbR8cHFS69uKY/EYwil5jlYj4h4LEYx6lHR4eTjovOtX6x6lG0xLlGP+5VDmZfwbGPGI0k3ne6YhEIjkX/YkwHgt9sCfrEr4/EBpm+979bOvez3vdPrZ27eft9gEeeLNzdIUSj1uwoL6CJQ0VLG6I/XvY9ErqK4oOviH19rtH/rcIyhaxb++bzGcHR0b20th6N4Wv3kqdcMemhyw6h6pQAK/nwIErl2IuVRvnGlM16XKc6HjpYupQXOe7hzqQD5odD/WLZwe6a9bRQ6eotojX66Um0gkv/xZevxNC+ykpqGNz9YU82T8dn6igqawpZQxzceV2u7nuuutSvj+b6Rxer/eg38UX0cZor/H7ZI+3zobOzk5aWloOmu6RLMd7770XyH1et3kJvrKyMsvzxM0el5WVJc0/l0KmoaGB0tLS9G8coaTQzbIZVSybUTXm94HQMNu697Oly8frO7pp80Z4fnsvf3p1z+h7qks9VLOYaUUR7tq0i6XTK4lEocD0fJwBUcGrHEFffRNCDrPurMMJvP4Xhl77C1PbvsZlxB5x/84P72F3yeG4ShYSFdkdOrxer5YHQDOqc7RDs3lfGa+Hu2RDvnioc1/MB82Oh/rFswPdNevooVNU50okBO/8lSkv/hp2vxCbn7rscjimmapZx3GMELzR0oJ5zDmTk2A0GlWWojEH+vrrrx+z3fg1oI1i2hi5jh/ZNI88l5aWsnr16oTxDDo7O5OOfifSbCynlw2pVsowRtTjc8qVYDCY9brZich0FZVMKSl0c8TMKo6YWcWFh9dSXFwMQL8/xLudPjb8+RG6ggXsGhhms7+EF+9+HQBBLVUiwKwKFw1FEabXLmB6cWTMSLmrfjl/7VlMaWQfpbufYSHvs8D3PIf5niaIh23M4akbX2Z3yVKu+cQ/ps01WRunmms/3uTSD8cznl0xVeJ4aJ180Ox4qF88O9Bds44eOkV1tgx0wMu/gVc2wOBeZNVs+ND/wIprM16uLBnNzc0JR5YTvQ+Sr2xhvonPKLRg7FrOcKCQMUaqjYLR+Lvx/lymOhQWFtLc3JxRkRQMBi3fbBU/2m8U1Zk8kjuXeLoRDAZH27q6tJDj59Xw7tSRp06G2ohKCHoq6BkuoTvkoS9awg5/BW8MHOgft61/jMMbK1k2o4o5VQVccPlV1FcWs359kDdZxYz6qUwfeo8p3c+ziPc5vOc2orig5QFYfD4suTD2hMg0+emK6hzt0KxiX7GTfPFQ576YD5odD/WLZwe6a9bRQ6eozpSO1+H5n8Ob90A0AovOg1WfZGj6cZSVJ765MNkqGalOguab4nI9aRpTH6SUDA8PH7T2c/zKGcmWu0s0Ktva2pp2+km2BWyiGwEzJZE3Usq0c6Cz8dQcT4dCJlEOiTxMffEVprn5Ynr3B3mrfWDk5eXt9gEeeadrZK7229RXFFESaKLWHWDl8R/miJlVPPDHO3hDRmn+0FG4ttwPW+6Hh/4j9mo4Eg67KPaqWzK6mkiyNk7WThOBlX44HvFaWlpwuVysXbtWadxU24Ps2kTF8StZPFXYEVMl+aDZ8VC/eHagu2YdPXSlf8vEIYS4SAhxU19fH36/H5/Px8DAAIFAgL6+PsLhMN3d3Ugp6ejoAGLrFgJ0dHQgpaS7u5twOExfXx+RSISBgQF8Ph9+v5/+/n5CoRA9PT1Eo9HRkVkjRvue3bD1YYK/Phd+dQrynb8SWbGOgY89xeAlv2Ww8QR8+wcZGhqit7eXSCRCV1fX2Bgj/xqxCwoKCIVC9Pf3J9QUiURGNe3fv5/Ozs6kmi6++GI++tGPjmpavXo1l156KcPDw3g8HoQQlJeXj17NtbW10d/fz/r16/nZz36GEILS0lI2bNjArbfeisvlwuVy4Xa7EUJQVlaGy+Ua7bgbN25k69ateDweACorKxFCMHPmTKZPn05VVRVlZWVcccUVXH755QQCAS6++GLWrFmTcTvFa0rXTi0tLWzcuBGI3Ql87bXXctZZZzE0NITX66WxsZHGxka8Xi9DQ0O43e7R9yZrp2g0Sk9PD6FQiEsvvZQLLrhgtJ2EELjd7qz7XiAQGPXX4/GMelxQUJC4743829XVRSQSobe3d1STEcfQ1Nvby/DwcFJNRnsZmtxuNy6XC5/PhycaZNWscj565BR+fOUR3LF2Ka9//Rx+enET59bvp9Hto3/Yw+ZgPZ+8ZRPHfedRfrhtKne0T+FHb5XwQM1a/q/4H/jjrK8ROOU/iLqL4PFvwy+OJ/KT5fDI19n72sMgZUJNRt+TUiKl5NZbb2XDhg0Z7U9SylFNyfanbNrJ6/USCASyO0akaCe/38/g4OCYdkqnydz34jXF971169Zx7rnnZtT3kmmSUibVZOz3Zk2Dg4MpNXV3dx/U91JpyvVYbqWdhoeHs9KUrp2CwaBSTYODg5b7Xrym/v5+S33P7nby+/1Za7K6P2WrKRKJWO57Zk0+n0+pplAopLyd+vr6LPc9O9vJON6oPEYEAoExix1kizDm0erMypUr5aZNmyzHaW1tzezR0BBbbuyBf4OeLVDRCMd9Bo5ZByVTxrzN6/VSVVWVJEh2JJtq0NQ09iv1dKOm5pv0SkpKGBqKTQMw2toYWTZGoo348XETbd88pzrZg12yHZmy4mGiUdhEN3sm05RJrqnyi/cg05wTzU1Pl0sqDSr7IcQ0/+lPfxrdXli68NTPpWPIQ3HjIl7f7eX9nsHR90/xDHPK0lkcNauaVTVBDvM+jWfrffDB0yCHiVbOwrXsUlh6Gcw4enQE20q7ZLU/Z6hZtYcq4pk9Kikpob6+HlAzqp/IQ6v7irnfZPv5RPFUtokdMXXvh3bEdDzUL55qD0F/zXa0s+GjEGKzlHJltp/Xb+xcFzwlUFAIl90Eh18W+38CclkZIxXmKyiD+LnQ8b+PxzxnOhwOJ50zbZDuZGe+Sc98g108uZw0W1paEEKwbl3i5eRSfQ4OvsEN1N7sCerb2A5U5mi0ycEXb2PX/v7lbzfQMVTAWx376Rku44m3dvHX10ZGOV0zOGz69Zxw+Fc4t2Azi3sfpeyFXyKe+xlUzYKll8Dhl9O8bh0IMe7TahJtT3U729FvwuGw8pgqyQcPdd+f80Gz46F+8exAd806eugU1cmYdRx85unREbVkDA4OWp4oH798WzJyeax4UVFR1l9lxM9zjb+xMZuVMDIpllwu67OQ4pfUi99upnOiE/09URvHt0E2I9bJ5qanyy2VBhX90EwmbVLilswrC+P2xLxvampiIOxi8Ynn8Nquflp39fP7N7zcFJwPzGd2yTrW1r7DWdHnaXrxJlzP3wjVTXD4ZUwNeugrnKEs/3QkuiBV7aGqeOm+hVGNlfsHBgcHld5/oLpN7IqpknzQ7HioXzw70F2zjh46RXUy0hTTBqq/eggEAqNzYJMRv1xdqicamuNl+jWscTI0CkaDpqYmSktLR+clW1kJw1xQulyurE/AyVYkaWtrIxAI5JxXIlS3sR2onmaQSZukusnw3MNjF2LDUcm27v1s2tHLa7u93Lmzhm91L6eStZzr3sRH929ixbM/42KGCVfPQz62B3HElVC32LKeRMT3bbNG1e1sR7+JXypSN/LBQ93353zQ7HioXzw70F2zjh46RbVFent7LT8m01wgFhQUjI4sp1sOLtnfzSPLZWVlSp/QGJ+v+Wcz2YzCmkfnE69Ukb7Yjvcw2WPK041QJ8o3URsbI9K5zKmOzyXblS8SvU9FPzSTyfqfqQpUA7dLsLihgmrhZ83xcwDwBsK07urnlbbl/HTnFXywcyenRJ7nwt4XOP6pH+J+6vv0li8mtPRy6o6/hoKps5XpSnUBqtpD1fGam5tHb/YZD3IZYTZrVjGVR7WHdsVUST5odjzUL54d6K5ZRw+dotoiqhvU/EjsdAVmsmLM/PdQKJT1yS1V/NbW1qxipdtGMk3ZxjFj5c7dROi20yZCRY4qv7aPx5xfVYmH0xbVcdqiOgCGo8eypfNcNu/cx4Pb3qOm7X5OG3iSFS99F176Lu8WLmPPzAspO/ojHLloLqWFuR+24qcymS9IVbez6njjPe88F3T30K6YKskHzY6H+sWzA9016+ihU1RbpL29ncbGRiWxmpubR5d1Sfb3bGhoaEg7lSQRmYxApssnmwLN4/EctE0rjxlPpTmdlkR/T9XGuYxQx+di5SmNBir7IaT20CCbNk6Vn9slWNpYydLGSji+CTibDm+AR998Dd68h4VdD3DW++sJb/8+T8rlbK4+F7HoXKpFgLmLwlSVZt7HU10wqvZQdTzIrF0mknzw0I6YKskHzY6H+sWzA9016+ihU1RbRHWDmuOlK64yechKNqsFJFvVw06SjVAne8x5JqheIWGid9pMilaVOcZvR8UIabb5Ta8qYfpJx8NJx4P8HoM7X6X3+ds4bvtfOXvgOwy8/BPuHz6Wzzx7Ct66lRw3v47j503l2Lk1TC1LvFKPmUT7jp37shWyvaF1ItHVQ7tjqiQfNDse6hfPDnTXrKOHTlFtgZaWFjweD2vWrFEWM5Mrr2xOsrmMbKmcBpDJZ9vb2w/6Wn727LHzaDO9ubKtrY2qqqqkU2fSeZZoO3ZdDav0eSJHADJt45zzE4KypqMpazoaot+HD56i7LU7ueLNP3NV9Al69tfzh00n8f+eP5kP5HQWT6vg+HlTOX5eDcfNS1xkj0c729FvdLwxx0w+eKjj6JaZfNDseKhfPDvQXbOOHjpFtUV0HBXNdmQr2fvHi8bGxqRfy+eSi9frpbq6Wk1yjP/VcKIVTcy/T9SOdowAZNqP7BhJTxrT5Yb5Z+CefwZvzm7mqKLd1L52O5/d/hc+5/oTnRVH8KDrdP5v03I2PF8CwJKGCk6cX8sJ82s4du5UqkoSX2jqNoqS6027E4luHo5XTJXkg2bHQ/3i2YHumnX00Cmqc8BcbFRWVio92XV2dqad1pHNSbaystJyTnZj1pztg2ni37d+/XrKy8uzmjOdTX52MF79Jtt4KrHDQ1lQDEd8BI74CGKgA974Aw2v3U5z989YV1jIvnln8mz5edy5r5qNL7Zx87Mf4BKwbEYVJ86v5aQFNayaM5Vij9uWHO3QnM03TxNRhOeDh3bvz1bJB82Oh/rFswPdNevooVNUW8Tn8zFlypT0b8wQ4xHEVsi2gEz2/vEasVah2XzTXygUUlpQqMgvE+JHho11xY2nRqXSojrH+vr6tP0om29EMs0v5/nDldPhpM/Dif8Mna/zzu//i3m7nuai6INcVD6NyMmrebP+Ih7rncLz23v4zdPv839PbqfQ7eKYpimctKCGE+ZNpXY4SoHb+sOIIPc2SeVBqqeF6jCSbUc/VM147c+5kg+aHQ/1i2cHumvW0UOnqM4Bc7GRak3kXOjr66O2tjarPFJRUJB9E4/3jVHZaM6EVGss56JBdX52oDpH3eMlRQiYfhQv1VzOpqkXs/b4BmjdSMGLv2C5/BnLZxwDx6xh8OpLealzmOe29fDMtl5+8PBWACqKCzhxfg0nL6zjlAW1NNWUIjJ8EFQ8dmjOJOZE3tiYD/1G9/05HzQ7HuoXzw5016yjh05RbZFUTzjL5WSmcrpGc3NzVqtojPcItYF5Ck2uhYB5+kc0GlVaQIzXFJpk/mey5J7qHM3xVHiZaX5W5w8f1I9EAXAuzV/+Kbx+F7RuhL99ibKH/oMzll7CGSuuhfNPptcf5qktXby4o5+n3+vhobdiD1mZUV3CKQtrOWVhHScvqM1q+b5c2ySVB4lixms2vtmYCOzsh5lwKEyJsyO/iW6X8cbxUA26a9bRQzXfc9qEEOIiIcRNfX19+P1+fD4fAwMDBAIB+vr6CIfDdHd3I6Wko6MDYHSd546ODqSUdHd3Ew6H6evrIxKJMDAwgM/nw+/309/fTygUoqenh2g0OjqP1Ihh/NvV1UUkEqG3t5ehoSG8Xi+Dg4NceeWVnHXWWQwNDdHb20skEhl94pnxWWMOZGdnJ9FolJ6eHkKhEP39/Qk1DQwMZKUpEAik1LRr166sNA0ODuJ2uxFCUFZWhsvlGh3tjo+RqaZ07TQ4ODi6jdLSUjweDy6XC5fLlbadWlpa2Lhx46gmIQTl5eUHafJ6vSnbKZWmvr4+y30vvp2MaSrJ+p7RbwoKCnC5XJSVlSGEwO12J9Tk8/my0pSunXbu3JlWkxACl8tFUVERHo9ntN/Ea9q4cSN33nlnRn3P0OR2u0ffm0yTlPIgTUa/8Xg8lJaWjnooy+romHsFfO459l56Fyy/hui7f4MNFzH8kyOpfvnHHFvaydcvWMj9nzuG+z63iv86fxGL60v42xsd/OPvX2HF/zzMhT95gh8/spWHNm8lMhxNqam3t9dS33O73bhcrjHt1NnZmbDvGf3FWB2ktLQUl8tFaWnpaDslOkZIKbM+7qXSZBT2qo4Rfr8/q+OecRxJpcnn82WlKV07BYNBJecnQ1NPT4+S85NZU0dHR9bHvVSaBgcHlZyfDE1+v99y3zNr8vv9ys5PhqaBgYGsNKVrJ8NHq+cnQ1MoFFJ2fjI0tbe3W+57Zk1+v19pHWEcb6z0vfh8AoGApQfICSllzh8eL1auXCk3bdpkOU5rayvLly+3npAJv98/evI2SDY31iDVKEqieKrzS0ey/Jubm233MNsRykQrZXg8ntG7glWMsqpuE8iuL2biyUT2m29+85sAfO1rX0v495aWFlwuF2vXrlWWH6T2MKN+FPLDO/fCq7fCjqeRwoVYcDYcvRYWnQfuWKEaGY7y2u5+ntzaw1Nb9/L67n6iEiqLCzh5Ye3I0yHraagqHhPejn6TKmayVWPM+288qvfnieqHqY5Zdueou4d2xHQ81C/eeNU3h3I8OOCjEGKzlHJltp93pn9YJNX0j3gyWVHBHE/FXMhs8jMY7yW8cskx1VfeLpfaL2ByyW+8UZ1jJvGMNjAuzJPd6NrW1kZRUVFW/WlclpMrLIWjPhp79X1A6MWbKXr7D3DntVBWD8uvhqPXUVAzn2OapnJM01S+9KFF9PtDPLutlye3dvPU1h7ufyO2Xy9pqOC0xbHHr69smqp8X4bM2mUil+CbiH6oQ0yV5INmx0P94tmB7pp19NApqi2SaKTfytxYld8cxI8Q6rA6QCLMmnPNzbysjupR0Yn+NicTT6zkmKhfZBIv/iIx1UVjrjf7ZUq8hqz70dS5BE+6nqJzvg7bH4VXboHnboRnfwpNJ8ExzXDYxeApprq0kA8fOZ0PHzkdKSVbunw8sWUvT27Zy83PfMCvnnyfQleUBWVh1p2zkjMWW1sFJNN20WG/TpVfLsefTPt1NhcSE70/p8OO/FTHdDzUL54d6K5ZRw+dojoJmZ4AMlk3Npviw+PxJL1pz8COk1IixuMk3dLSghCCdevWKYupekfL5amU443qHDOJF/8UzGRrjGfTxvF933gYUCYXpFbxeDzgLoBF58Zevk5o/X2swP7jp6D4ejjqajhmHdQfBsQuFpY0VLKkoZLPnjaf/cEIz27r4aZ7n+G9/YX82z1vADBVlDLT7WXXL29jRnGEj38s+/yz3VcmosieiH6oQ0yV5INmx0P94tmB7pp19NApqi0SCAQoKSlJ+LdEX4PDwcVHfDyrmLdXWlo6roVJLqicrtHc3ExfX5+yeJC6jXXBnGOm7ZtqxZVMNJtXXEm3PdVTcgxULR/X0tKC2+3muuuuO/DLigY45Utw0r/Ajqdhcwu8/Bt48Zcw67jY6PXSS2PTSEa4+/bbADgy2MZxlaXsDXvYGa5gR6iMNyLTeb1NUOqO8uZdrZx92DROWVhLRfHYE0Oqi2qzj7rtx5B4X7HSRtnue3bEHG/syE91TMdD/eLZge6adfTQKarjyPYEUFFRkTZmNsVHRUVF0ukjuZyUhoaGtLyaM/vscrmyLhBSfd2bSZtkg+p4djCRmjN5Amg4HM4oVrJ2HY8CMun8PJcL5p0Wew32jIxeb4A/fw4evGFk9PpjUL9kzMeCwSEOn1XH4QAMERgOMmPlh3jsnS4efaebP76yhwKX4Lh5UzlzyTQ+dNg0ZtccfNON8c1WMBgcs6/oSD7se7rvz/mg2fFQv3h2oLtmHT10imqL7Nu3L+On+sQXH0aRfcMNN+QULxnmQsT8cJp0hclEjXypvntXhYd2xrNKonbat28f999/P6DmoR/ZaM4kvm4eGpgv7srLy9N7VlZ74MmNO56Bzb+Dl38LL/4fzD6B5mM+BksvoWXjHQfteyVuycVHNXLxUY1EhqO8uqufR9/p5tF3uvif+97mf+57m0XTyjn7sOM5e+k0oo/+BZdpKrrxzZO5yDZr0GHEOlE7W7kwsqPfpIqpg5fjrVmHeKpxPFSD7pp19NApquPI9gRQV1eXdexM48W/P5cDvpX1Fu1E1Qhkos9l0ybp0PVCJB6VmnWIF+9nLtM5sv3c/v37qampyezNQsDcU2KvwZ7YQ2U2t8CfPg0P/hurPEexpeKk0bfH51HgdrFqzlRWzZnKDecvoa13kL+/083f3+7iV0+9zy+e2E6Zu4ZF5UH+8ZJTOHlhLXdsvHVMDOPiSScmut9MVEyV5INmx0P94tmB7pp19DDjoloIcSIwx/wZKeUtNuSUV3R2djJ9+vSsPhM/x9k8Yp1LvFSYp36kKwxVzEuN/1y6WJ2dnZSXl2e1nXTY6eFEkmqurcfjUTpVQrWHquMZpJsukoxE7/d4PKxZsyb7JMpq4aQvwAn/DDuegk2/4/B37+PwgSdgw9Ow8uOw+MNQUJh0+001ZXzi5Ll84uS5eP1hntjazd/f6eaJd7v55C2bKPG4aSqqZFl1hK9+7FKmlBVm3c7jcQGYqp1z2a4d/SZRTFXHQBWMl2ad4qnG8VANumvW0cOMimohxK3AfKAVMCYeSuCQLaozPZiqbtBU8XI5wGc6l3WiSDcfN55MTnYq2iTdSVankzCob+fx7NcqsdIulj10uWDe6bGXryv2UJnNG+APzbF1r49eG1s5pHp2yjBVpR4uWT6DS5bPIBSJ8sL7vTz8diePvN3F3buD/Onbf2fVnClU7y/hsIqgtZwVkw/9RreTcDz5oNnxUL94dqC7Zh09zHSkeiWwVOq4KOAE097ePvr0vkwx5lAnmlOdS7x4zIVFVVVV2sLC6ghnokKms7OThoaGjIrSTHLMBhUemjEe/awb5rm1uXiYqt1Ve6g6XktLC6WlpaNPEMt2hDpRvzQeU5vp9s3bPYiKabQvuIbGk78I2x6FTb+Fp3+IfPqH7C5ZiiewkO3MSRunsMDFqYvqOHVRHd+8eBmPvbaNV7uHeeitLl7oLufB7nIeu/EZzjm8gfOWNTC/7uBvfXK90Mhln9S93ySLOZ43xKZjvDTrFE81jodq0F2zjh5mWlS/CTQAHZkGFkLcDFwIdEspl4387vvARUAI2A58TErZn03CuqG6QVXH83q9VFdXK42pmkxyzKYwUOFhupOsTidhsNbOidZN171fGxdt8VhpF9s0Lzon9urfyeu/+zKLfM+zhrfYRxXbvafyXvnxGcVzuQRnr1jI2cD15y5h+979PPRWJw+92cn3H9rC9x/awoL6cs5fFiuwl06vtP2hO/Ho3m/siqmSfNDseKhfPDvQXbOOHqYsqoUQ9xKb5lEBvC2EeAkY/b5RSnlxio+3ADcydorII8C/SykjQoj/B/w78G+5pa4HHR0dOX8FYR6hVhHPINd5olZvFsxmTrWSuaxJUOGhGV3mVKeaP2zFw0TFqWoPVcUztAeDQYaHhw8amTY8SfaApVR9NZMcs7m4Oyhe9WyO+uIfIBLiiV/9K0sGnmXlvntZOfAQ3PMarPokzDo2dhNkEswx59eV8w+nL+AfTl9Ae3+Ah9/q5MG3Ovn549v42WPbaKop5bxlDZx/1qUcNbOKDRs2JM01V41pNVvAjmMDpM5xoi+OQf2+Z0dMO3JUieOhGnTXrKOH6Uaqf5BrYCnlU0KIOXG/e9j04wvAR3KNrwvZzgke73jZzBNNNkXD7hNNJjlmk5NKD5ubm7V/NDTkNh84VfE03v06076W7Omk8fFzyX/cNBcUsqPsaHaUHU3zBcfBppvhtTvgjbtg2hGw6hNwxJVQdPBUjmQxG6tLaD5pLs0nzaVnf5BH3u7igTc7+e3Tscemz6guYZYo4/DKINGoxOWyZwR7Io9fmaI6R9XYkZ/u5ynVOB6qQXfNOnooMp0mLYRoAI4lNnL9spQy+bO2D3xmDnCfMf0j7m/3AndKKW9L8tlPA58GmD59+jHGGrxW6O3tzXzJrAyx8wlBW7duBWDRokVK4qUjfnuJtq/aw61btyKEYOHChTnlmIh8eGqTah9zydHw0ufzAQcW0l+0aJGlfpNLfpn2dXPOZWVlDA0NAQce3OJ2u8f8bNaUjvHWbOb9d19ntvclDh98jpKB7QwXlNE3+1x65l5CsGJOTjEBfMEoL7cHeG7XEK2dQ0SiUFPi5sRZxZw0u4QafNTV1ibUlqhfpEPFvmLevsfjobi4OOPtZ4Lq/Vnlvpzt8TBTdD8m6nA8HO+YunsI+mu289y8YsWKzVLKldl+PtPVPz4JfA14DBDAz4QQ35RS3pztBkfifRWIABuTvUdKeRNwE8DKlSulcUOSFVpbW1ERx0w4HFY6PcAcr7W1FcBSzpnkFz9i+f777wMHlvzz+/1AbBRRtYfZaszk/Xa2iSpU+5hLjsb2jfZfvXp1TvGstEl83zP3tVQ5r1+/frSABti9ezcARUVFwIG+29TUlDa3dDkmQnU/bG1t5c2ilaz89M9g10u4X/4NdW//mbr3/whzT41NDVn8YcJRmXU7nwJ8Cfi/325gy/5CfNULeGhrD/duHaSmxM0lRxdy4VHTWTGrGiHEqDbDU7s8TIZ5+y6Xi1mzZmW8/UxQvT+r3JdVHPMTofsxUYfj4XjH1N1D0F+zjufmTG9UvB5YIaXsBRBC1ADPAVkX1UKIdcRuYDzrUFhNxOfzMXXqVKXx/vrXvwJqlmtTnZ9V4ufAGk+JUznVxI420cnDREyE5kzn3ra0tOB2u7nuuuuU5dfQ0EBpaenohYCKqUvZeJhJ3Jw8HJ33/Gs49zvw6i2w6Xdw11qoaCS89KN4Tv4sVGT/tWexW3JUVZDmdasYGArz6Dtd3P7MFm57oY2bn/2AGdUlXHjkdD589qUcMSPzOdjZak6HuQ1V9xvQc3829wPVx0OYfMdEO/KbbB6C/pp19DDTono34DP97AN2ZbsxIcR5xG5MPE1K6c/28zqi+quHiYiX6gY48892kcm8yWxuntK9TezASo7j4WE0Gk257VyWAzRG9VShXb8pr4NTvgwn/QtsfQhe/jWlL/4YXv4ZHHYRHPtpmH1CyhsbIfW+M1f0MHfx4Tzydhf3vd7Ob5/5gF899T5NNaXMoowjKoaySnm8+o0VdN+f7ZhHrl3fthk78ptsHoL+mnX0MNOieg/wohDiLyM/Xwy8JIT4EoCU8kfxHxBC3A6cDtQKIXYDXye22kcR8MjIUk8vSCk/a0nBBBMOh5U2bDgcVlrUqs4vV+JP7MZXyk1NTbhcLtauXatsW3a0iQ4epmIiNKfrp+Y2Ly4utvUiLdnqMtmgo4cAuNyw5AJYcgH721opf+cuaL0N3voT1B8Ox34Sjlid8MbGTKgq8fCRY2bykWNm0u8P8dBbndz3egfPbivlmd5SHv3xk1x0ZCMXL2+kqaYsZSyVHjY3NzMwMKAklhkd92dzP1B9PITJd0y0I7/J5iHor1lHDzMtqrePvIzpGn/hwFJ7CZFSXp3g17/NKrs8QPU6sBMZT0VhYhfZXGjo3iZ2oLvmdDO9su1rLXEPf1HBRHqYbAnAeOTU+XDed+DMr8Ibd8PLv4b7vgiP/DcsvyY297p2wZjPZLPvVJcW8tFVs/noqtnc+JsNvO0rort4Cj98ZCs/fGQrR82s4qKjGrnoqEamVRYf9Hnd+6FdMXUnH9pFJfnQb3T3EPTXrKOHmRbV9wP/AcwxfUZKKY+0I6l8wnyzlOp4Kopa1fnlSqoTu3FzmirsbJN4dHn4ixXNiTRkEy+ZdrtH31Qznv0mnkyXhhqNWVgWe+T50Wth14vw0q/h5d/Ai7+E+WfCqk/BonNjo9w5Ul4gOXbKEM3NJ7KnP8B9r7Vz7+vtfOtv7/Dt+9/hxPk1XHLUDM47ooHKYs/Y/BRhx/FLl2NiIpqbm5UfDyE/2kUl+dBvdPcQ9Neso4eZFtW3Af9K7MmK6ie55TGhUIjS0lIlsey4MUdlfnaRTY6ZFK+qNR9qHqqOp+Lbg0wvTsxTSmbOnKn0omYiPMz2QSsHxRQCZh8fe/m+A6/cElv3+o6roWo2rPo4rFgLZTUZe5Qsp880N/OZ0+azrXs/f23dw19ea+cr97zOf/7lTc5cXE9l/xYOqxzmY+v0Pn7pvj+r3veyjZkJh5KHExVTdw9Bf806ephpUb1XSnmvrZnkKaobVPWNObp1uEQHf9U5jkc8K0+ds4NcNKfSoNLD5uZmQqGQsnh2oXs/bGlpQQjBunXrEr+hYhqcdj2c/EXY8rfY6PXf/xse/y4suxyO/RTMOMZyHgvqy/nSOYv54ocW0bqrn7+0tnPf6+307K+iuCPK1j++zmUrZrKyaYrlh8zYcfzS7ZgYTz5odjzUL54d6K5ZRw8zLaq/LoT4DfAoYx9T/kdbssojBgYGqI17eEK2mIub8vJypQWaivzsRnWOusezg4nQnM2FRbJ42V6cmKeUpFpSLxcmwsNsb0rO6OtOdwEsvST26n4nNi3ktTvgtdtjRfWqT8Hhl4Hn4DnR2eQkhGDF7Cm89thf+NwMePGDfbSJadz98k5uf2kXM6pLuHRFI5etmMGC+qS336TEjn3PHHOiL4YToXrfyzRmNuh+TLS73+gYzw5016yjh5kW1R8DlgAeDkz/kMCkL6pVr5E4ODio9KlIuq3hmAjVOY5HvPFedjAduWhOpUH3NrEDOzVb6SfmAkoIkV2s+sPgwz+Es74eK6xf/jX8+bPw8Ffh6HV4So/POo9E23ULmOEeYKbwcfnC2WzxFdFTUccvn9jOzx/fzpEzq7h8xQwuOqqRmvKijLdpR7/RvS/mg2bHQ/3i2YHumnX0MNOi+igp5RG2ZpKndHd3W37+vLm48Xg8rFmzRkFmMVTkZzfmHFUUqao155uH6cjE40ziZXNhkSxerhcnzSPrVKuchmOlnRNtN5t4meZrPDI8a4or4bhPx6aAfPBkbGrIsz9hqQR2XhBbNWTe6WPWvM6mLSDx8avbN8RfW9v506t7+O973+Zbf3uHM5bUc8XRMzhjST1FBalH3u3Y97q7u3nwwQcBfaZvmVG972UaMxt0Pyba1W8mk4egv2YdPcy0qH5BCLFUSvm2rdnkIaobVPXC/7p1uESoznE84+lwEgZrmhNp0L1N7CCbHDMpZhoaGpQU/Uq/FREiVjzPO50//OZHLAu8xGE7n4d374PaRbGpIUddFSvCR8hGg/n4Zbzvk83NfPKUebzbOcAfX9nDn17dwyNvd1FV4uHioxr5yDEzOXJmVcKbWe3oN7r3xXzQ7HioXzw70F2zjh5mWlSfDKwTQnxAbE61wFlSD4D29nYaGxuVxGpubqa9vV1JLAOV+dlFe3s7Dz/8MKBm5Ei15nzxMF2O2RRH2WjOpI3Sxcu1UFRZcObSzqk8Vb0vA3g8HmWxBgum8sa0yznsshZ4+8/w0k3wwPXw6DfgyI/GRrXrD8s4XjrNSxoq+Y8LKvnKuYt5dnsv92zezV2bdnHrC20sqC/nI8fM5LIVM8asf23Hvtfe3q7d9C0zqve9bGNORDzV2NVvJpOHoL9mHT3MtKg+z9Ys8hjVDap7PDvQXbPjoTV0LFwSkYnm+CK6qCj5/ODGxkalxZtV/4wcDEaXJdx4Ryz+px6DPZvhpd/Aq7fBpt/CnFNoPvZTsPjDtNx6W9o8Ghsb0168FbhdnLaojtMW1TEwFOZvr3dw9+bdrH/gXb734LucuqiOjxwzkw8tnWbLvqfT/pyoX+SDZp08TITjoRp016yjhxkV1VLKNrsTyVd0v/LS8UouHtUjR5PVw3Q5ZuOxas0qR1gToaJgN2vOtB/Gf/1ofr9uo2XGUxtTfmU64xi47Bg451vw6i3w8s1w11qoaORI93LeKz8hbX7ZUFns4epjZ3P1sbN5f+9+7nllN398ZQ//9PtXqS71cPbCaj522mIOb6zKKm66HA0PdbzQ063fjEc81TgeqkF3zTp66JroBFIhhLhICHFTX18ffr8fn8/HwMAAgUCAvr4+wuEw3d3dSCnp6OgADhzUOzo6kFLS3d1NOBymr6+PSCTCwMAAPp8Pv99Pf38/oVCInp4eotHo6EnHiGH829XVRSQSobe3l6GhIbxeL4ODgwwODlJWVsbQ0BC9vb1EIhG6uroSxujs7CQajdLT00MoFKK/vz+hprq6uqw0BQKBlJpcLlfWmrxer1JN6dpp+vTpo5rcbjdCCEvtVFRUpFRTdXW15b4X307BYNBy3zNrqq+vz1iT2+3G5XKl1GTMb7XS9zZu3EhLSwv9/f1s27Zt9GdVfU9KabnvmTUVFxePanK5XLhcroM0nXfeeTQ3N7NgwQKampo455xzaG5upqAgNj5h1lRVVTWq6aqrruKiiy6yvD8VFxdn3fc2bNjALbfcAsTWwTf2sfnz51NRUTGqaUw+ZTV0LbyGyD9uYuDCXzNcu4ij++9ndfs3idy5jv1v/52hQOCgdoJYoXrOOefQ1NTEggULWLt2LRdeeGHadiqXfv71nMX8Ye1hbPj4sRwzo4y/vtnLh//3GT78v09z40NvsNfrz6jvJdufbrvtNh5++GGlx71gMJh13zP2hd7eXnbt2sWtt97Khg0bGBgYoKKiQtn5ydBUVFSk9Fg+ffp0JecnQ5PxFElV56fGxkZl5ydDU11dnaW+F6+prKxM6Tk3FAopOz8ZmgoLC5WcnwxNjY2NSusIAyt9Lz6fQCBAJBIhV4SUMucPjxcrV66UmzZtshyntbWV5cuXW0/IRFdXF9OmTZs08RwP1aDaRx01m6cBVFRUHLT8kdVRQjs8fOCBB4ADUxeampqAg3PNZCTbjn6TS8z169cDEAzGHjFgTFlpaGgYs9Z3Ov746++xZOAZloZaIeiFaUfAsZ+EI66MPTY9Lj8V3zptbdvD83vC/GHzLt7cM0BhgYtzD2/gqlWzOGFeTdYPl2lpaaGgoIBrr70255ziyaUfxk+RMfczXfqNQaJ21P28opuH4xHPOTerwfBRCLFZSrky289nOqfaIQkq15TOh3h2oLtmx8PcSDbdJH5ury5kozmTQjGbeJkWoLm0izHdwyjgjJ+NZQkzZcBTz0s1l7P0mtvhjT/E5l7f+wV4+Guw/BpY9UlqauaMvl/F1Ip5M6axqKmAdSfO4a12L3/YtJs/vbqHe19rZ9bUElYfM4uPrJzJ9KqSlHHMRazL5Zrwef6ppmLZcbzR8fhgJ46HatBds44eOkW1Rbxer9KG1T2eHeiu2fHQOm63O+UNbBNd5EBMs8q5/Xb0m1xiGhqMEWuzxtLS0rSjWwe12+//EIvz2adh14uxNa9f/g28+Euis06GEz8Hi86LPdnRIma9hzdWcfjFVdxw/hIeequTuzbt4oePbOXHf9/KaYvquOrY2Zy5pB6PO/WsxpKS1AX4RKNLv0m1v+p+TNTFw/GMZwe6a9bRQ6eotkhZWdmkimcHumvOdw+TjRSnKhhVam5ubmZoaIg77rhDWUw7sKI5kaeZxMt2HWsrOSpf01UImH187LX/u/DKBjwv3wx3roHKmbCyGY5eB+X1OW8ikd5ij5tLls/gkuUz2Nnr5w+bd3HXpl185tbN1FUUsXrlTD66cjaza0pHP2Pu+0II1q1bl3NOKknUznYcbybbMdHxUA26a9bRQ6eotkgwGKS4uDj9Gw+ReKnIdXRPd83j6WGu6K45GAwmLOpbWlpoaWnR4sl2Zs0qtm9Hv7ESM97/0SX1knie1cVYeT2cej0DR3ycqs7nYyPXj30Lnvh/sPTi2BMbZ58w5omNmZBO7+yaUr58zmK+cNZCntiyl9tf2jn6aPSTF9Ry1bGzOGdpA4UFB0avjZu3dUWXfpOq3XU/Juri4XjGswPdNevooVNUW8S463+yxLMD3TXnq4fxo6DxN6ylKpIcDzMj1UhzJvGynW6iu48FhcVw2IWxV8+22FrXr26EN++BusNg1SdiD5YxPbExZbwM9Ra4XZy9dBpnL51GhzfAHzbt5s6Xd/FPv3+V2vJCPnLMLK45djbNzc0MDg5akWg7drTxZNufHQ/VoLtmHT3ULyOHvCPbr7Dt2LaO6806JMbcVsnm+zpMHMr259oFcN534cz/jBXVL/8W7v9X+Pt/w5GrYeUnoGGZsrwNpleV8PmzFvKPZyzgqff28vsXd/Lrp9/n/57czikLa7niqGl8eEVJ2rnXDjESfYPhcrlYu3btxCTk4KAxTlFtESvrGeZjPDvQXXO+ephu9Y1URVIqzbkUWcniGbEyGT23m1zaOZWn2cTLVK/ufTFhfoVlcPTa2GvP5lhx3fp72HQzzDoeVn4cll4CnoO/xrWi1+0SnLG4njMW19PpHeLOl3dx58s7+Ze7e/jOQ9u4atUsrjp2No3Vet24aEcbq44pspzGM97kg4e678ugv2YdPXSKaoukekzxoRgvEVZXTMglx1SjafnooVV01zzZPLTrhrhscky2P8av/hG/TrWV/TltfjOOib3O+daBwvpPn4YHb4AVa+CYj0HN/KTxcj3GNFQV84WzF/JPZy7g4Tf28IdXO/jZ49u48fFtnLlkGtceP5tTF9Zlve61Hdixr6iIaT7mFhQUaP0toa4e2hnPDnTXrKOHTlFtkcHBQaUT5XWPZwe6a853D5MVVdnGszItIFl+Kpews4qVdk6Utx03xOneFzPOr3QqnPhPcPw/wAdPxorr538Bz/0M5p8ZG71edJ5yvW6X4NiZJZx/1Cp29fm5/aWd3LVpF39/p4vZU0u55rjZrF45i6llhcq2mS12tLHqmDoWM2bywUPd92XQX7OOHjpFtUWqqqomVbxU5FoQ5ZJjqmIsnz3MFd01TxYP7X7ISCY5Znrx05zm4S/pclay77lcMP8MmH8Gd/7mpyza/zwr9r4Od16Lj3LeLTiKk/7pV7T8+VFAzX0bRo6zppbylfOW8C9nL+LBtzq57YU21j/wLj96ZCsXHjmd645vYvms6nGf6mDHvqIipk4XwOnQ1UM749mB7pp19NC5U8Mivb29kyqeHeiu2fEwRnNzM83NzTQ1NdHU1DT6s4r8sollF+YcjaX+kv2cCXasoap7X7SSX6Cgiteqz4MvvA5X3U4ndZwYeRZ+eiRndd3ETP+bCBlVnmNhgYuLj2rkrs+cwMNfPJWrVs3ioTc7uewXz3Hxjc9y18u7CISGLW831/x0jKnjqgtm8sFD3fdl0F+zjh7qvWfkAaqfO697PDuwkmOiQszx8NCPZwcqcrR7NC+THO3OIdVIeC4exsf75re/A4AUl1ElvaxyvcNRgdc4O/AWx7urea/iBFZc9kmompFT/qlyXDStgm9esoyvnLeEP72ym1tfaOMr97zOt+9/h9UrZ3Ld8XPGPFTGDuzYV1TGnOiL30zQ3UM74tmB7pp19NAZqbZIe3v7pIpnB7prdjwcSy6jyvnioflhNG1tbaxfv57169eP/pzNiLXH47ElR51RkZ+UEill7Ifq2TwqT+An4lOw+ha8ngZW9D8AP1kGv78KtjwI0exGkTPJsbyogOtOmMND/3Iqd3z6eE5eUMvNz+7gtB88zidaXuaprXuJRmUu8pTkN9ExJ0M/tDum7h6C/pp19FDroloIcZEQ4qa+vj78fj8+n4+BgQECgQB9fX2Ew2G6u7uRUtLR0QEcMLmjowMpJd3d3YTDYfr6+ohEIgwMDODz+fD7/fT39xMKhejp6SEajdLZ2TkmhvFvV1cXkUiE3t5ehoaG8Hq9DA4OMjg4SFlZGUNDQ/T29hKJROjq6koYo7Ozk2g0Sk9PD6FQiP7+/oSa6urqstIUCARSajJulspGk9frVaopXTtNnz49K03p2qmoqEippurqast9L15TMBi03PfMmurr65W2kzGP1ErfM2tqbGxU3veklJb7nllTcXExQghcLhdFRUV4PB6Ki4txu92Ul5cjhBgtlNO102WXXcall16qfH8qLi7OWNOaNWu4+OKLU7aTlDLrvnfllVdy2WWXUVpaSnV1Nddeey3nn38+ZrLRdPHFF7NmzRrmz59PU1MTCxYsoKmpiaqqKrxeL/Pnz2dm01y6a0+g/svP0L/uScLH/zPRPZvh9o8S/fEyhh74OqG972e0P9XX12fc94QQzC4O8vM1R/PH5qX80xkLeGVnH2tvfokzfvAYv3lqG/v2B5Scn4x2qqioUHZ+MjQVFRUpPZZPnz5dyfnJ0OT3+7PWlGp/amxsVHZ+MjTV1dUpOT8ZmsrKypSec0OhkLLzk6GpsLBQyfnJ0GQ+D6ioIwysnp/M/wYCAUtL9YnREQGNWblypdy0aZPlOK2trSxfvtx6QiaMHXiyxHM8VINqH3XXnG8e5rK2d6p46cg0vg77c/x0jaamJiCWu5X84r8BaGtro6qqiurq6tH4YxgOw5YHYPPvYPvjsd8tOAuOXgeLzwd34m8KrHoYjAxz/xsdbHiujdZd/ZQUCD56bBPrTpzD3NrU8+gzaWc79hXd92fdj4d2xNTdQ9Bfs53nFSHEZinlymw/78yptojqBtU9nh3ortnxUL94djCemjMprhK9R3cfs8kvXl/8BQyA1+sdLaoPwu2BpRfHXvva4NXbYq+7roOyOlh+TazANq17nW2OiSgqcHPZiplctmImr+3q50f3vcLGF9toeW4HZyyu42MnzeWUhbU5rxpiRxtPtv3Z8VANumvW0UOnqLZIZ2cnDQ0NkyaeHVjJMVHh4Xh46MezA3OOuaztbaalpQWPx8OaNWvSvg8yXypuIn3MZPReRX7m+Jl4CMCUJjjzq3Dav8G2v8Mrt8BzN8KzP4Wmk2DFdbGnNhaWKvXwqFnVfPGEqXx//hJ+/+JObnthJ2tvfon5dWU0nzSXK46eQWlhQVbtrLqNs/IxQ3Tfn+3Ib7IfEydDPBU4RbVF6uvrJ1U8O9Bds+NhdiQqGA41DzMZaQ6Hw0k/ZxRXiR6i0dnZOXqzZPy2JtJHYw5iKjLJL5sCM5GHKXEXwOLzYq+BDnjt97HR6z9/Fh74Ciy7gvrl14KcBgrXn66vKOZfzl7E506fz/1vdPC7Z3fwX39+k+8/+C5XHzebkrCLak9mywHa0cZZ+5iG8eyHuUy9siM/nY6x44XumnX00CmqLdLX10dtbe2kiWcHqXJMdkBNdWJ2PDz049lBNjkmKzDN/bK8vDxtQRA/ytLc3JxydZGJ8NHIJxgMjvk5kSaV+TU3N9PT05N7gMrpcMqX4eQvQduz8Mqt8NoduDb/DqYtg+Vr4MjVUKbOT2NqyKXLZ/DKzn3c/MwOfv3U+whRy3nLGmioL2BmcSRlgajKw2z7Yjbovj/bkZ9zTDz046nAKaotUllZOani2YHumh0PMyPVhc6h4mE2BWYgEDjod8mmTpgL6VTTK8bTR2P78RcQqUasM8kvm5s/legVAuacHHtd8D0irXdS8Prv4aF/h0e+BovOjU0PWXB2bKRbAUIIjmmayjFNU9m9z88tz7dx+0s78Q1NYUZxmNrX2jl/WQMF7oMX4LKjjRP1RSuMRz/MdmqUGTvy0+EYO97orllHD52i2iJ+v5/CwsJJE88OEuWY7oCa6sTseHjox7ODTHJMV2Ca+6Xb7ea6667LaNuZjh5OhI/GaLqxL6aaw6h9vymuYv+S1VQf/2noehtaN8Jrd8C790H5NDjyo7EbHOsPU7bJmVNK+Y8LDuMLZy3knld2c/MzH/DPt7/KjOoSmk+cw0ePnUVl8YGVSlRpzrUvZoLu+7Md+Wnft21Ad806eugU1RZR3aC6x7MD3TU7HmZGqgudQ8XDbArMVMuVZlJEJ5ry5HK5WLt2bdrPWiHZknnG/O9UuWfTzpl4YEe/GY05bSmc+204+79h60OxAvv5n8Nz/wuNK+Coa+CIj0DpVCXbLSsqYO0Jc7j2uCYee7eb3zzzPt++/x1+8vetrF41i4+fNJdZU0tt0ax66dzx2J+tLGdpa7/RNJ4d6K5ZRw+dotoiw8PZPc0r3+PZQaIcMz2gJvq94+GhH88OMsnR6G/r168f83Oi9/l8PlWpaUEmd9nnQ785KKbbA4ddGHvt74Y3/gCtt8MD18ND/xG76fGoa2Dhh5KufZ0NLpfg7KXTOHvpNN7c4+W3z3zArc+3seG5HZy/bDrXHDONk5aoexS6HX1R9/15XPqNZvHsQHfNOnroFNUWUT0CoHs8O9Bds+NhdiQqNA81DzMpMLOJl+ri0TxyXFxcrPSGs0RYGSHUqR/mFLO8Hk74x9ir841Ycf3GXfDOvVBaA8uugCOvghlHK1k9ZNmMKn780eX823lLaHluBxtfbONvb3Swak4bnzplHmcfNg2Xy/p2VPXFXOJZJZd+Pu79RoN4dqC7Zh09dIpqixiPLZ4s8ewgVY65HFAdDw/9eOnIpSDMJsdM4tqhWceRGTMqNbe0tCCEYN26dcpiQhY5NhwB5x0BH/oGbHsUXr8DNm+Al26CmoVw1EfhiNVKcmqoKuaG85fwT2cuYONz73PrS7v59K2bmVdbxsdPnstHjplJscedc/x835+zxY78JpuHoL9mHT10imqLBAIBSkpKJk08O9Bds+OhfvHsQGWOmd4clskKB7necJbuwqKlpYXS0tKkjzbO5YJWdTu7XAevjpENiTzIOke358Da14F+ePsv8Pqd8Ni34LFvsaDmSIh8DJZeann+dXlRAVceVcsnTl3Ag2918uun3uc///wmP35kK+tOnMN1xzcxpSz7eaSZaM5mtQ3d92c78nOOiYd+PBU4RbVFKioqJlU8O9Bds+OhfvGSYWUZLtU55sO8TtWo8NDchi6XS/l0F0s5llTDMetir31t8MZdFLx8K9z3Rbj/K7Fl+Y68EhadD4W5zYuuqKigwO3iwiMb+fAR03nxgz5ueup9fvTIVn75xHY+umoWnzg5dlNjNjFVovsx0Y78JpuHoL9mHT10imqL7Nu3T+lTfXSPZwe6a3Y81C+eHajIMdsHbmQzf7m5uZnu7u6sckgU2/z3mTNnKi1aVbdzaWluhWkqD5TlOKUJTr2edyvOZnmDOzb3+o17YOsDUFgOSz4Myz4C806HgsxHl835CSE4fl4Nx8+rYWuXj5ueep+NL7Zxy/M7+PCRjXzm1Hksm1GVVcxkZNMXdd+f7cjPOSYe+vFUYO27NZsRQlwkhLipr68Pv9+Pz+djYGCAQCBAX18f4XCY7u5upJR0dHQA0N7eDkBHRwdSSrq7uwmHw/T19RGJRBgYGMDn8+H3++nv7ycUCtHT00M0Gh1dc9aIYfzb1dVFJBKht7eXoaEhvF4vg4ODDA4OUlhYyNDQEL29vUQiEbq6uhLG6OzsJBqN0tPTQygUor+/P6Gm6urqrDQFAoGUmoyRrWw0eb1epZrStVNtbW1WmtK1k8vlUqqprKzMct+L1xQMBi33PbOmKVOmKG2nSCRiue+ZNdXV1Snve1LKgzRdccUVXH755cyZM4d58+axZs0aLrjggozaqaCgwHLfc7vdCCEoKSkhFArhcrlwu90ZafJ4PGnbqaCgIG3fAygoKMDlclFaWooQApfLNarJyLG8vHx0u6qOEcbjsK30vXPPPZfm5mYWLFhATU0N5557LuvWrcuq7xmaqqqqxmjs6upiypQpSo97wVAIf9UCfCf8GwOfeI7g1fcwtPDDyK0Pwe+vRP5wEf47PgnvP0n77l1p96eSkpKEmirlID+48ijuXreUT50yj8fe6eTCnz3D6l88zVNbuujp6UmqyeVyZaxJCIHb7U7ZTrW1tUrOT8b+5Pf7Lfc9s6a6ujpl5ydDU3V1tZLzk6GpsLBQ6Tk3FAopOz8ZmoQQSs5PhibzeUBFHWEcb6yen8z/BgKB0fNfLggd756MZ+XKlXLTpk2W47S2tiadP5grHR0dTJ8+fdLEczxUg2ofddc83h7mMvqqMseWlhY8Hg9r1qxREs8gmxwznVO9erWam+1APw8TeTBux8RICLY/Bm/eA+/+DcKDsQfMLL0UDr8UZh0PCeaMZ5rfwFCYjS/s5OZnP2CvL8iRM6v47GnzOffwBtxxK4bovj/rfjy0I6buHoL+mu08rwghNkspV2b7eWf6h0VUN6ju8exAd82Oh/rFS0cuUxlU52iMoqhE976oMj+7lgwcNw8LCg/c4Bjyw3sPwRt3w+YWeOlXUDEdll4SK7JnHTdaYGeaX2Wxh8+dPp+PnTSHP726h189uZ1/2PgKc2vL+PSp87j86BkUFbizipkpk6kf2hVTdw9Bf806eqj19I98wPjKYLLEswPdNTse6hfPDrLJsaWlZXQUNBHNzc2cc845CrIaSzY5Njc3p52jvWjRIgVZHUC3fpPIgwnpi4WlcPhlcNVG+Mp2uOK3MOMY2PQ7+N158OOl8MC/wY5nR6eIZEqxx83Vx87m0S+fzi/WHE15UQH//sc3OPV7j/Prp95nMBjRrl3sxo78JpuHoL9mHT10Rqot0tjYOKni2YHumh0P9YtnB/mgWXcfDzUPbXnQTlFF7PHnR3wEgr7YI9Lf+lNsBPvF/6OxrC52k+NhF8GcUzO+ydHtElxwxHTOX9bAM9t6+MXj2/n2/e9w4+PbWHfiHD5WFcppOb5ETLZ+aEdM3T0E/TXr6KEzUm0RY8L8ZIlnB7prdjzUL54dZJKjMULd1tZGW1tbyhFrOzTr7mM+9ButPDQK7Ks2wvXb4coWAg2rYtNEbrsCfrAA/vgZePuvEBrMKKQQglMW1nH7p4/nT/9wIsfOncr/PvoeJ65/jP+57206vUOW09bKwwTkQ7/R3UPQX7OOHjoj1RbJ5HHFh1I8O9Bds+OhfvHsIB80W4lp9+PN4dDx0Mp65zlTVE7Ly17gXJqv/x28/3ismN5yf+xpju4imH8GLL4AFp8fe6R6GlbMnsKv165kS+cAv3ryfVqe28Gtz7dxxTEz+dxp85ldk9uShbrvz7rte+MRzw5016yjh85ItUX27t07qeLZge6aHQ/1i2cHmeRozNFtamqiqakp5bxlOzTr7mM+9BvdPSwoKABPcaxwvuyXcP02WHcvrPw4dL0N934efrAIfnsOPPNj6H4H0qziNcU1xI8+upzHv3w6H1k5k3s27+aMHz7BF+9s5b0uX9Y56u5hPvQb3T0E/TXr6KEzUm2RKVOmTKp4dqC7ZsdD/eLZQT5oziXmeI66HioeZvMgFBWkfIqk2wNzT429zvsudL0ZW6Lv3b/B3/879qpugkXnwaJzYc7JUFA0Jr6heXZNKd+57Ag+f+ZCfvP0+2x8cSd/bt3DuUsb+KczF2T0IBlzPF3RZd8bz3h2oLtmHT10Rqot4vNlf5Wfz/HsQHfNjof6xbODbHJMt7JGtvEyRXcf86Hf6O5hcXFx8j8KAQ1HwOk3wGefhi++DRf+BOqXwiu3wG2Xw/fmwR1rYiuLeHcDB2tuqCrmPy9cyrM3nMk/nbGAZ7f3cOHPnuETLS/z6s59aXPU3cN86De6ewgTqLl3Ozz2Lbj3X9TEG0eckWqLlJSUTKp4dqC7ZsdD/eLZQT5oziXmeI66Hmoe2j1CHb+dlpYWhBCsW7cusw9WzYCVH4u9wgH44CnY+iC89wi8e1/sPXVLqJhzOhx2Psw+Ycwo9tSyQr58zmI+eco8bnluB7999gMu+8VznLKwln8+cyHHzp2acLO6788T3W8mIp4djKvmwL7YKjitt8Pul0C4YMGHIDoMLve45KcCp6i2SDgcVtqwusezA901Ox7qF88O8kGzOeZ4TU3IhnzzUEeEEOnflAhPSWz6x6JzY3Os926BbX+HbY9Q8MrN8PL/gacUmk6K3fA47wyoPwyEoKrEwz+ftZCPnzyX215o49dPv8/qXz3PcXOn8oWzFnLC/Joxeenu4Xj3m1z2Rd09hHHYnyNB2PYovH4nbHkAhoNQdxh86JtwxGqoTP1wFx09tK2oFkLcDFwIdEspl438bipwJzAH2AGsllKm/65JY3I+AOZpPDvQXbPjoX7x7CAfNFuJOR7F96Huod00Nzer+UpbCKhfEnud+E/s7+2koufV2GPTtz8OD/1H7H3lDSMF9ukw5xTKqmbwmdPms/aEOdz+0k5+9dR2rvnNi6yaM4XPn7WQkxfUIoTQ2kPIj36ju4dgk+ZICN5/At76Y+y+gOAAlNbEvm056mqYflSs/05Afiqwc6S6BbgRuMX0uxuAR6WU64UQN4z8/G825mA7bnfiryUO1Xh2oLtmx0P94tlBPmh2u90Ts9xbhuSLhzpji+aSythqIovPj/2if1dsyb7tj8cePvPa7bHfT50Pc0+hZM4pfHz5qVxz3BnctWkXv3xiO9f99iWOnl3N589ayKqZZcpzVMl49Rsr+6Lu/RAU5hgJwgdPUfL63fDeAzDkheIqOOzi2JNG550WuyF3ovJTiG1FtZTyKSHEnLhfXwKcPvL/DcAT5HlRHQqFKC3Nba3PfIxnB7prdjzUL54d5IPmUCikNJ5q8sVDnfviuGiungVHr429otHYiiI7no7NyX7zj7GnOwLFdUtY23QiV59/PPf2z+GHLwzS/LuXWTa9nC+fexinL67TcrQwH/qN7v0QLOY42AvvPRxbZ337YxDaj7uwAg67cKSQPiPjp4Xakp9NjPec6mlSyg4AKWWHECL96vWao7pBdY9nB7prdjzUL54d5IPm0tLScbvxMJf4+eKhzoy7ZpcLph8Ze53wjzAcgc7XYgX2jmfg9T/g2XQzlwOXVc1mx/zl3Nk1g29veJefzljKFz60mNMX6VVc2+3h+vXrAbjhhhsAPfYVO8gqRymh++3YPP4tD8KuF0BGoWI6HLkaFl9AeMZxFJZWTkx+44SQaRaNtxQ8NlJ9n2lOdb+Ustr0931SyoQLDQohPg18GmD69OnH3H///Zbz6e3tpaamxnIcM0NDQ6mXQDrE4jkeqkG1j7prdjxUH3Pr1q0ALFq0KOd4qTzMJX6+eagC3fuh5ZhymBLvdsp6X6e85zXKel/HE+oHYIAyXhleQFvxYurnLadx/lHIwvKsN5FvHra2tgKwfPlyQI99ZSLOzQVDfVTs3UxF98tUdL+MJ9gHQKByAd7pJ+KdfjKBqkWjc6Tz4fhg+LhixYrNUsqV2X5+vIvqLcDpI6PU04EnpJSL08VZuXKl3LRpk+V8WltbR3cCVUSjUVwudct96x7P8VANqn3UXbPjoZ4xE3kYP0+0qakJyGwUzvHQOtprlpLo3q249mxieOeL+N57lsr923EhiSIIVM6jdO6xiBnHQOPR0LDsoIfRxJMvHn7ve98DIBgMAlBUFNNljFhnG0/nfggJchzsgbbnYq8dz0DXG7Hfl0yN3fA6/8zYtI6qGZnFU52fAgwfhRA5FdXjPf3jr8A6YP3Iv38Z5+0rp7u7W+nz53WPZwe6a3Y81C+eHeSDZt19dDy0jvaahaA7WkXDijW4V6yhGgjt38ezTz7E9lcfZ86+LRyz/0GmGDc/ujww7fDYqg7Tj4SGo2DaUii072ZHuzxUHU/nfoiU9G57hbrgDmh7FnY8Cz1bYn8rKIGZK+Gsr8UK6YajYtOI0pAPxwer2DZSLYS4ndhNibVAF/B14M/AXcBsYCdwpZSyL10snUeqJxuOh2pwfLSO46F1UnmY7TxRnVYhGU+cfniAUCTKXZt2ceOj7yF87VzR0MXVM3uYMfgOdLwGQ/2xNwoX1CyIPR1y2jLeHyxm3nEfhqpZGRVnE038nGodsNwPA/2wZzPseQX2bIr9f3Bv7G+FFTD7eGg6MbbOeeMKyzcZ6oq2I9VSyquT/Oksu7Y5EbS3t9PY2Dhp4tmB7podD/WLZwf5oFl3Hz2e7JfFSoVuHo7HhYNumrOJV1jg4trjm/jIMTO58+Vd/Pzxbdy4KciJ8y/jy1ct5JhqP3S+Dp1vQMfrsOslePMe5gG88O9QWA51S2IPpalbDDULoXYhVDeBO/NyJZ89tB0pob8NOt+MrfrS+Ubs3307DryndjEs+BD9FQuoXnoWTFuWlf/JOGQ8TIGtc6pV4YxU64PjoRocH63jeGgdFR5amYOtO/FFdKKi2umHyRkKD7PxxZ388olt9OwPcfriOr78ocUcMbPK9CYvW5+7l0VVEeh+J7aCRNfb4O858B6XB6bOixXYNfNhypwDr6pZOa1xfKhxUD8cDscK5Z73oGfrgX/3vht74AoAIubntGWxbw1mroyNQhdXJdjC5EDbkerJgu5XXjpeycWju2bHQ/3i2UE+aNbdx6oqtSdjXTwczwfu6KJZRbxij5tPnDyXq4+dxS3Pt/F/T27nohuf4Zyl0/jSOYtY0lAJxVX4py6D+AsTf1+sEOx9b+TfbbF/33sYhk3rtQs3VM2E6tmxfytn0C/LqZ59eOyGucpGKK7O+Cl9VjWPW7xoNHbh0b8L+ndQv/VF2NUSG4Xe1xb7Nxo58P7yaVC7CI64MlZANxwR+0Ygxdx27TTbHE8FTlFtEdUNqns8O9Bds+OhfvHsIB806+ijnetmT5SH8UW0scrDeJAP/SbbeKWFBXz2tPmsOW42Nz+zg988/T7n//RpLjyykX85e2GSD02F2cfFXmaiw+DriI3Cjnm1xdbW9nVQLaNjP+MugvL6kdc0KKuL/b+0BkqmjH0VV0NRRWzFElMhbruHUkJoPwT2xS4oAn0j/478vL8TfF0x7b5OGOweUzQ3QkxPdVOsYF56cWwaR+0iqF2Q0+jzRPeb8Y6nAqeotkhXVxfTpk2bNPHsQHfNjof6xbODfNCsu48FBWpPKbp4GL/CgJ1TW3TRbEe8imIPXzh7IetObOLXT7/P757dwd9eb+eMOaV8o8nPzCkZPMzDNTIyXTUT5px88N+HI+zd8RZ1hUHw7oaBdtjfFbvpbn8X9O+E3ZtGbsJLMf3VVRAbxS0sh8Jywq5CPCWVsakm7qLYvwVF4C6MjZaPGQgf+UFKiIZjI+vDxr8hiIQI+/vxRIcgNHjglSKfIVcZxbVzoKIB6pdCxTQob4g9HbO6idd39nPkqhPT+5cFuvSb8YqnAqeotojqxdZ1j2cHumt2PNQvnh3kg2adfWxubiYSiaR/Y4bYNcUiEw+Tjb4bP9tJPvQbq/GqSwu5/twlfOykufzi8e3c8vwHnPmDJ7nmuNn84xkLqKuw8M2Au4ApTYdDQQHMOjb5+6LDMOSNjQQH+kf+HXkFB0zF7v7YI7aHfLGCOOSH4f4DBfJwKBbLwHyfmhAjRXjhyMsTmx9eUIR7yqzYiLhRuBeVx/5fMiW27nPp1NF/b/nDX4mKgpT7QrSjNXfPkqBbv7E7ngqcotoiXq9XacPqHs8OdNfseKhfPDvIB826+6g6P7fbrSyWgZUcx+Pmy3zoN6ri1ZYX8bWLlnLCVD+PdhZy6wtt3PnyLj520hw+c+p8qkpzuwExo/xc7ljhWjo1o5j7FD+xMJN4o9OQdu4Z8/N43QSsa7+xK54KnKLaImVlahew1z2eHeiu2fFQv3h2kA+adfdRRX7m+cwFBQXKC4lscpyIFUzyod+ojNfS0kJpaSnrV6/mM6fN58ePbOUXT2znthfa+Ozp8/nYiXMpKczu4mqyeWgXumvW0UP9V1nXHONxpZMlnh3ortnxUL94dpAPmnX3UXV+qte9hsnnoR0x7fJwbm0Z/3v1Cu7//CmsmjOV7z24hVO//zi3Pr+DUCSaPoCN+U2Eh83NzTQ3N9PU1ERTU9Poz+OF7v1Gx33ZGam2iOobc3SPZwe6a3Y81C+eHeSDZt19VJGfef6yy+Vi7dq1lmOamQwe2h1TRTzzNxIzZ84c843E0sZKftu8ipd39PG9B9/lv/7yFr9++gO+9KFFXHxUIy5X6uXxJouHdqO7Zh091C8jBwcHBwcHh5w4lB4Xv2rOVO76zAk8sWUv33toC/9yZyv/9+R2/u28JZy+uA5hce3pfOFQaMvJgtbTP4QQFwkhburr68Pv9+Pz+RgYGCAQCNDX10c4HKa7uxspJR0dHUBsMXCAjo4OpJR0d3cTDofp6+sjEokwMDCAz+fD7/fT399PKBSip6eHaDRKZ2fnmBjGv11dXUQiEXp7exkaGsLr9TI4OMjg4CD79u1jaGiI3t5eIpEIXV1dCWN0dnYSjUbp6ekhFArR39+fUNPQ0FBWmgKBgHJNXq9XqaZ07WT8XVdN+/fvt9z34jUFg0GlmoLBoO3tZKXvRSIR5e0kpZxQTenayefzTcj+lI0mKaXS/Sk+HyuazjnnHC655BLl7RQMBpUeI4LBoNJ2GhgYsNT33G43LpfL1r4XDoct9721a9dy3nnn0dTURFVVFc3NzZxzzjkHaQoGgxw9vYi7PrGC7112GINDYT7W8jJX/PxpXv6gJ6GmSCSifH8aGhpSeozYt2+f0nNuKBRSfozYu3ev0nOu+Tyg4hhh/lfVMSIQCFhaxch5TLlFhoaGKC4unjTxHA/VoNpH3TU7HuoZ0/HQOrp4mOpx8Tq3i3Gj4urVqzN6fygS5Y6Xd/K/j75Hz/4Q5x4+jevPXcKC+nJb8rMrpu79EPTXbOd5JdfHlGs9Up0PDA4OTqp4dqC7ZsdD/eLZQT5o1t1Hx0Pr5INmlfGam5tZtGhRxu8vLHCx9oQ5PHn9GXzpQ4t45r0ezvnxk9xwz+t0eoeU52egs4d2obtmHT105lRbpKoq+0d/5nM8O9Bds+OhfvHsIB806+6j46F1cs0v1ePi86FdsqWsqIDPn7WQNcfN5sbHt3HbC238uXUPHz9pLp86uUn59g5FD9Ohu2YdPXRGqi3S29s7qeLZge6aHQ/1i2cH+aBZdx8dD62TD5p18rCmvIivX3Q4j37pdM49vIFfPLGd03/wFL995gOCkeH0ATLkUPYwGbpr1tFDZ6TaIqqfO697PDvQXbPjoX7x7CAfNOvuo+Ohdazml2iliHxoF6vMrinlp1et4FOnzGP9A+/yP/e9TctzH/Cv5yzmoiPTL8OXjsngYTy6a9bRQ2ek2iLGHaOTJZ4d6K7Z8VC/eHaQD5p199Hx0Dr5oFlnD5fNqOJ7F8zilo8fS0WRhy/c0colP3+W57b3WIo7mTw00F2zjh46I9UWaWxsnFTx7EB3zY6H+sWzg3zQrLuPjofWyQfN+eBhI3Dyglr+3LqHHz68lWt+/SJnLqnn389fwsJpFTnFVJ2j7uiuWUcPnZFqi+h+5aXjlVw8umt2PNQvnh3kg2bdfXQ8tE4+aM4XD10uweVHz+TRL5/GDecv4eUdfZz7k6f49z++TvfAUE4xVeeoM7pr1tFDp6i2iO5XXjpeycWju2bHQ/3i2UE+aNbdR8dD6+SD5nzzsNjj5rOnzefJ689g3YlzuHvzbk7/wRP85O9b8Ycye9DHZPMQ9Neso4dOUW0R46k8kyWeHeiu2fFQv3h2kA+adffR8dA6+aA5Xz2cWlbI1y86nL9/6TROX1zHT/7+Hqd//wnuenkXw9HUD8KbbB6C/pp19NApqi1SX18/qeLZge6aHQ/1i2cH+aBZdx8dD62TD5rz3cOmmjJ+seYY7vncCcyYUsJX7nmdD//v0zz93t6cY6rOUQd016yjh05RbZG+vr5JFc8OdNfseKhfPDvIB826++h4aJ180HyoeHhM01T++LkTufGaFQyGIlz325do/t1LbO3y5RxTdY4Tie6adfTQKaotUllZOani2YHumh0P9YtnB/mgWXcfHQ+tkw+aDyUPhRBceGQjf//SaXz1gsPY3LaP837yFF/90xv07g/mFFN1jhOF7pp19NApqi3i9/snVTw70F2z46F+8ewgHzTr7qPjoXXyQfOh6GFRgZtPnTqPJ68/g+uOb+KOl3dx+vef4FdPbicYGZ50HoL+/UZHD52i2iKFhYWTKp4d6K7Z8VC/eHaQD5p199Hx0Dr5oPlQ9nBqWSHfuGQZD/3LqayaO5XvPvAuZ//oSR7f1o+UqW9mHK8cxwvd+42OHmpdVAshLhJC3NTX14ff78fn8zEwMEAgEKCvr49wOEx3dzdSSjo6OoAD6xZ2dHQgpaS7u5twOExfXx+RSISBgQF8Ph9+v5/+/n5CoRA9PT1Eo9HRO0mNGMa/XV1dRCIRent7GRoawuv1Mjg4yODgIP39/QwNDdHb20skEqGrqythjM7OTqLRKD09PYRCIfr7+xNqCgaDWWkKBAIpNSXLJ5Umr9erVFO6dopEIllpyqWdrGjav3+/5b4XrykYDCrVFAqFlLZTfD659D1zjOHhYeXtJKW03PesaErXTj6fb0L2p2w0JWprK+0Un49VTcPDw8rbKRQKKT1GBINBpe00MDCgxXEvlaZIJKJ0fzJGHFVpGh4ettz3FtSX8+1zZ3LLx1dR5IIv3v0Wl/38aTZt71JyjOjv71faTqFQSIvjXipN5vOAimOE+V9VmgKBAJFIZsssJkKovPKyi5UrV8pNmzZZjtPa2sry5cutJ2RiYGBA6bwe3eM5HqpBtY+6a3Y81DOm46F1dPfQjpiTzcPhqGTD01v5+VM76fOHuOLomVx/7mKmVRZrk6NzblaD4aMQYrOUcmW2n9d6pDof8Hg8kyqeHeiu2fFQv3h2kA+adffR8dA6+aB5snnodgmuPnY2j19/Op8+ZR5/ad3DGf+/vXMPj7K68/j3lwkkJISAJiGJKFoRL9gKC1rEGxa1Wm+1+/RR13bVbnW9VNDWdmXdrd1e9uluRVzd2j6sWmy9tVW2ULWKrYJVVxQkFanipSgQQm6Ty5hMMhlz9o+Zacc0IZmc92R+h/f7eR4eyEvyzfl+5mTOmTfvzNy6Dj989h309H2oYowu0D5vNDrkptqSeDweqjwXaO9Mh/ryXOBDZ+0e6dAeHzqH1eGk4nFY+pkj8fQNp+DEGRX4wVPbsGjZejz22u6cr7fW7hDQP280OuSm2pKysrJQ5blAe2c61JfnAh86a/dIh/b40DnsDg+uKMWKv5+HB7/8SZQVF+IrD27GhStewtbdHXkdY9BonzcaHXJTbUlbW1uo8lygvTMd6stzgQ+dtXukQ3t86EyHKRbMqMDji0/C9y44Gm83xnDOnc9j6aqPvr71WI4xaLTPG40Ouam2pLKyMlR5LtDemQ715bnAh87aPdKhPT50psO/ECkQXPLJ6Vh346m4fMEh+OXGnVh46zrc/fs/IZHsH9MxBo32eaPRITfVlmReliUseS7Q3pkO9eW5wIfO2j3SoT0+dKbDv6a8ZBy+ee5RePL6kzDnoCn47uNv4Mz/eg7rtjWN2RiDRvu80eiQm2pLampqQpXnAu2d6VBfngt86KzdIx3a40NnOhyaGVVluO/yY3HPpfPQ329w2U9ewZfvewXvtXQ5H2PQaJ83Gh1yU21J5gXDw5LnAu2d6VBfngt86KzdIx3a40NnOtw7IoJFR07FUzecjJvOOgL/924rzlj+HP7jyTfR1Zt0Nsag0T5vNDrkptqS2traUOW5QHtnOtSX5wIfOmv3SIf25LvzypUrsXLlysDy8kG+HWYoKozgqlMOxTM3LsQ5n6jBj9a9i08tW4dfba5XeZZ1IPn8efZ1HnJTbUnmbTLDkucC7Z3pUF+eC3zorN0jHdrjQ2c6zI2pk4px24Wz8ejVC1BVVozrf16Hz965PqeX4MsH2ueNxnlYmO8B+E51dXWo8lygvTMd6stzgQ+dtXukQ3vy1TlzVvD999//yMeXXXbZqPLyidZ5M3f6FKy+9gT8ctNO/MeT23Dunc/jC/On46unz8TkkvEBjDJY8vHz7Ps85JlqS5qbm0OV5wLtnelQX54LfOis3SMd2uNDZzocPQUFgguPPQi/uHQWvjh/Ou5/6X18atl6PPTyDnzYn9u7MrpG+7zROA95ptqSKVOmhCrPBdo706G+PBf40Fm7Rzq0J1+dM2cC93ZmMJe8fOLDvJleU4l/O6gWFx57EL61ZiuWrtqCh17egW+ffzRmHzg50O81WvLx8+z7PFR9plpEzhWRFdFoFN3d3YjFYujs7EQ8Hkc0GkVfXx+amppgjPnztTWZZ4M2NDTAGIOmpib09fUhGo0imUyis7MTsVgM3d3daG9vRyKRQEtLC/r7+//8moeZjMzfjY2NSCaTaG1tRU9PDzo6OtDV1YWuri40NDSgp6cHra2tSCaTaGxsHDRjz5496O/vR0tLCxKJBNrb2wft1NbWllOneDy+107vvfdezp06OjoC7TTc7dTZ2ZlTp+Fup127dgXaqbm52XruDezU29trPfeyO7W3twd6O23fvt167mV3isVigc89Y4z13MvuVF9fbz33sjs1NTUF/vNUX19vPfeyOxljrOdedqeB88b2PiIWi1nPvYGd2tvbA73f6+3tDWR9ynRqbGwMbH3KdNq1a9eIO4kIIpHIXjt1dnYGsj5lOnV3d1vPvexOsVgssPUp06mtrS2Q9SnTqaGhAV1dXZheHsGKi47EDz43C7vbunHBXS9gyf0bEO1K5HQfkUgkAlufMp127twZyPqUuZ2y14HhOhUUFKCgoGCvnTL3N0HeR8TjcSSTqVdoGQ1ijK5fNwzGvHnzzMaNG61z6urqMHv2bPsBZRGPxzFhwoTQ5NFhMATtUXtnOtSZSYf2aHfoIpMO3eTFevpwx+/exr0vvIeJRYX4+qcPx8XHHYRIgQybx7U5GDIeRWSTMWZerl+v+ky1D/T19YUqzwXaO9OhvjwX+NBZu0c6tMeHznToJq+seBxuPvso/GbJSTiypgz/8qvX8dkfvoDNO9oC/d4jRfu80TgPuam2RGT4R5D7Up4LtHemQ315LvChs3aPdGiPD53p0G3ezKlleOiK+bjj4jlo7OzBBXe9iJsefQ1tXYlAxzAc2ueNxnnITbUlkUgkVHku0N6ZDvXlucCHzto90qE9PnSmQ/d5IoLzjqnFMzcuxBUnHYJfbtqFU5etw8Mv70D/GL1KiPZ5o3EeclNtSSIR7CNH7Xku0N6ZDvXlucCHzto90qE9PnSmw7HLm1hUiJvPPgqPLz4RM6vKcNOqLfjbH7+I1+vdv3GM9nmjcR5yU21JSUlJqPJcoL0zHerLc4EPnbV7pEN7fOhMh2Ofd0T1JPz8H+dj2eePwc5oN8777+dxy+rX0RF3d11xvjuPdV4QcFNtSWdnZ6jyXKC9Mx3qy3OBD521e6RDe3zoTIf5yRMR/O3cafjd1xbiC/On42cvvY9Fy9ZjdV09XLySm4bOY5kXBNxUW7LffvuFKs8F2jvTob48F/jQWbtHOrTHh850mN+88gnj8O3zj8bqa0/EAZOLseThOtyyrhXvNn8Q4Ah1dR6LvCDgptqSpqamUOW5QHtnOtSX5wIfOmv3SIf2+NCZDnXkfXxaOVZdcwK+c/4svBNN4Kzbf49la7ehp+/DAEaos7PLvCDg25RbUl1dHao8F2jvTIf68lzgQ2ftHunQHh8606GevEiB4IvHH4xpaMWaHRHc+cw7WF23G98+fxYWHl6lYoy+5AUBz1Rbknlry7DkuUB7ZzrUl+cCHzpr90iH9vjQmQ715U2ZEMHyC2fjwSs+iXERwWU/eQXXPvgqmjp7Rp2pvbPGeZiXTbWI3CAiW0XkdRF5SESK8zGOIKitrQ1Vngu0d6ZDfXku8KGzdo90aI8PnelQX16GBYdW4IklJ+Frp8/E039sxKJl6/HT/3sPH47ita21d9Y4D8d8Uy0iBwBYDGCeMeZoABEAF431OIJC+yMvjY/kBqK9Mx3qy3OBD521e6RDe3zoTIf68rIpKozgukWHYe31J2P2QZPxzdVb8bm7Xsj5ta21d9Y4D/N1+UchgAkiUgigBIA+MyNE+yMvjY/kBqK9Mx3qy3OBD521e6RDe3zoTIf68gbj4IpS/PRLx+GOi+egvr0H5/338/jOY39EV29yRF+vvbPGeSguXttw2G8qsgTA9wDEAaw1xlwyyOdcCeBKAKipqZn7xBNPWH/f1tZW7L///tY52cTjcUyYMCE0eXQYDEF71N6ZDnVm0qE92h26yKRDfXnDOfwg0Y/7X+vEU+90Yf+SCK6cW47jDtj799fe2eW6MmfOnE3GmHm5fv2Yb6pFZAqARwFcCKAdwC8BPGKMuX+or5k3b57ZuHGj9feuq6vD7NmzrXOySSaTKCwM7kVUtOfRYTAE7VF7ZzrUmUmH9mh36CKTDvXljdThpvfb8M+rtmBbYwxnzqrGt86bherywZ/Wpr2zy3VFREa1qc7H5R+nAdhujGk2xvQBWAVgQR7GEQgdHbldo+R7ngu0d6ZDfXku8KGzdo90aI8PnelQX95ImTt9Ch5bfCK+cebheHZbE067begnMmrvrHEe5mNTvQPAfBEpEREBsAjAG3kYRyCUlpaGKs8F2jvTob48F/jQWbtHOrTHh850qC8vF8ZFCnDNwhlYe8PJmJN5IuOPXsQbDR9922/tnTXOwzHfVBtjNgB4BMCrALakx7BirMcRFL29vaHKc4H2znSoL88FPnTW7pEO7fGhMx3qyxsN0/dPPZHx9gtnY1e0G+fe+Tz+88k3//yOjNo7a3A4kLy8o6Ix5hYAt+TjewdN0NfzaM9zgfbOdKgvzwU+dNbukQ7t8aEzHerLGy0igs/OOQCnzKzE9554A3etexePb2nAv1/wccyuCfZJgPuqw2z4joqEEEIIISFmSul43Pr5Y/Dglz8JALjk7g24ec2baOtK5HlkfsFNtSXJ5Mhe73FfyXOB9s50qC/PBT501u6RDu3xoTMd6ssLigUzKvDU9SfjmoWH4rEtjTjttvVYXVePIF4pLgwOuam2pKioKFR5LtDemQ715bnAh87aPdKhPT50pkN9eUFSPC6Cb5x5BB698lhM268ESx6uw5dWvoL69rhVbhgcclNtSVdXV6jyXKC9Mx3qy3OBD521e6RDe3zoTIf68lwwrawAq65egH895yi89KcozrhtPe57cfCX3xsJYXDITbUl5eXlocpzgfbOdKgvzwU+dNbukQ7t8aEzHerLc0F5eTkiBYJ/OPEQrL3hZMw9eD/csmYrPv/jF/FWY2xUeUGPTxvcVFvS2toaqjwXaO9Mh/ryXOBDZ+0e6dAeHzrTob48F2SP8cD9SnDf5cdi+YXHYHtLF86+4/e4/bdvIZHsH1Ve0OPTAjfVlkydOjVUeS7Q3pkO9eW5wIfO2j3SoT0+dKZDfXkuGDhGEcEFc6bht189BWcdXYPbf/s2zr3zedTtbB9VXtDj0wA31Zbs3r07VHku0N6ZDvXlucCHzto90qE9PnSmQ315LhhqjPtPLMIdF8/BPZfOQ0e8D5+76wV897E/Ip74cFR5QY8vn3BTbUltbW2o8lygvTMd6stzgQ+dtXukQ3t86EyH+vJcMNwYFx05FWu/ejIuPu4g3P38dnz69ufw4rsto84Lenz5gJtqS7Q/8tL4SG4g2jvTob48F/jQWbtHOrTHh850qC/PBSMZ46TicfjeBR/Hw1fOR4EAf/c/G7B01Wvo7OkbVV7Q4xtrVG+qReRcEVkRjUbR3d2NWCyGzs5OxONxRKNR9PX1oampCcYYNDQ0APiL5IaGBhhj0NTUhL6+PkSjUSSTSXR2diIWi6G7uxvt7e1IJBJoaWlBf38/9uzZ85GMzN+NjY1IJpNobW1FT08POjo60NXVha6uLpSWlqKnpwetra1IJpNobGwcNGPPnj3o7+9HS0sLEokE2tvbB+1UWVmZU6d4PL7XTgUFBTl36ujoCLTTcLdTTU1NTp2Gu52KiooC7TR58mTruTewU29vr/Xcy+5UVVUV6O0kItZzL7tTbW1t4HPPGGM997I7FRcXW8+97E7l5eWB/zwVFxdbz73sTsYY67mX3SlDUPcRtbW11nNvYKeqqqpA7/d6e3sDWZ8yncrKygJbnzKdioqKAr0vr6mpCWR9ynTq7u62nnvZnWprawNbnzKdKisrA1mfMp1KS0sDXXMTiURg61Om0/jx40fcaXZtKX5++TG4/PgD8fNXduK0Zevw5Gu7PtIpex0I4j4iQ5D3EfF43O5NZYwx6v/MnTvXBMHmzZsDycmmoaEhVHl0GAxBe9TemQ51ZtKhPdodusikQ315mtbmuh1t5vTb1pnp//SYueHhzSb6Qa9V3lC4XFcAbDSj2K+qPlPtA1VVVaHKc4H2znSoL88FPnTW7pEO7fGhMx3qy3PBaMd4zIGT8evrTsTiRYdhzR924/Tl6/GbLQ2hcMhNtSXRaDRUeS7Q3pkO9eW5wIfO2j3SoT0+dKZDfXkusBljUWEEXz19JlZ/5QRMnVSMqx94FVes3ICWD3pVjM8V3FRbMmnSpFDluUB7ZzrUl+cCHzpr90iH9vjQmQ715bkgiDHOqi3Hr649AV//9OF47t02nLH8Ofz6D7uRusIi/+MLGm6qLck8wSIseS7Q3pkO9eW5wIfO2j3SoT0+dKZDfXkuCGqM4yIFuPbUGXjostk4cMoEXPfQZlx9/6tojtmdtdbokJtqS8aPHx+qPBdo70yH+vJc4ENn7R7p0B4fOtOhvjwXBD3Gow6YjEevXoCbzjoCz2xrwunL12N1Xf2oz1prdMhNtSUffrj3dxDa1/JcoL0zHerLc4EPnbV7pEN7fOhMh/ryXOCic2GkAFedciieWHwSDqkoxZKH63DlzzahKdaT9/EFATfVlgRxXZBPeS7Q3pkO9eW5wIfO2j3SoT0+dKZDfXkucNl5RtVEPHLVAtz8mSPx3FvNOGP5czmftdbokJtqS8aNGxeqPBdo70yH+vJc4ENn7R7p0B4fOtOhvjwXuO4cKRBccfLH8MSSv5y1vur+TSO+1lqjQ26qLYnH46HKc4H2znSoL88FPnTW7pEO7fGhMx3qy3PBWHU+tDJ11nrpWUfg2W3NOGP5ejz22u4xH18QcFNtSVlZWajyXKC9Mx3qy3OBD521e6RDe3zoTIf68lwwlp0jBYJ/POVQPLH4RBy0fym+8uBmXPPAJvQmh75uWqNDbqotaWtrC1WeC7R3pkN9eS7wobN2j3Rojw+d6VBfngvy0XlGVRkevep4fOPMw1FcGEFRYcQqb6wpzPcAfKeysjJUeS7Q3pkO9eW5wIfO2j3SoT0+dKZDfXkuyFfnwkgBrlk4Y9gnImp0yDPVluzZsydUeS7Q3pkO9eW5wIfO2j3SoT0+dKZDfXkuyHdnEQk0byxQvakWkXNFZEU0GkV3dzdisRg6OzsRj8cRjUbR19eHpqYmGGPQ0NAAANi9O3Vxe0NDA4wxaGpqQl9fH6LRKJLJJDo7OxGLxdDd3Y329nYkEgm0tLSgv7//zzdQJiPzd2NjI5LJJFpbW9HT04OOjg50dXWhq6sLJSUl6OnpQWtrK5LJJBobGwfN2LNnD/r7+9HS0oJEIoH29vZBO1VUVOTUKR6P77VTZlLm0qmjoyPQTsPdTtXV1Tl1Gu52Gj9+fKCdysvLrefewE69vb3Wcy+7U2VlZaC3UwabuZfdqaamJvC5Z4yxnnvZnYqKiqznXnanSZMmBf7zVFRUZD33sjsZY6znXnanzNwJ6j6ipqbGeu4N7FRZWRno/V5vb28g61Om08SJEwNbnzKdxo8fH+h9eXV1dSDrU6ZT5p3xgrqPqKmpCWx9ynSqqKgIZH3KdCopKQl0zU0kEoGtT5lO48aNC2R9ynTKXgeCuI/I3N8EeR8Rj8eRTCYxaowx6v/MnTvXBMHmzZsDycmmvr4+VHl0GAxBe9TemQ51ZtKhPdodusikQ315XJuDIeMRwEYziv2q6jPVPlBbWxuqPBdo70yH+vJc4ENn7R7p0B4fOtOhvjwXaO+s0SE31ZZkfg0RljwXaO9Mh/ryXOBDZ+0e6dAeHzrTob48F2jvrNEhN9WWVFdXhyrPBdo706G+PBf40Fm7Rzq0x4fOdKgvzwXaO2t0yE21Jc3NzaHKc4H2znSoL88FPnTW7pEO7fGhMx3qy3OB9s4aHXJTbcmUKVNClecC7Z3pUF+eC3zorN0jHdrjQ2c61JfnAu2dNTrkptqSWCwWqjwXaO9Mh/ryXOBDZ+0e6dAeHzrTob48F2jvrNEhN9WWTJgwIVR5LtDemQ715bnAh87aPdKhPT50pkN9eS7Q3lmjQ26qLenr6wtVngu0d6ZDfXku8KGzdo90aI8PnelQX54LtHfW6JCbakuGexvNfS3PBdo706G+PBf40Fm7Rzq0x4fOdKgvzwXaO2t0yE21JZFIJFR5LtDemQ715bnAh87aPdKhPT50pkN9eS7Q3lmjQzHp907XjIg0A3g/gKgKAC0B5GRTDqAjRHl0GAxBe9TemQ51ZtKhPdodusikQ315XJuDIeNxujGmMuevHs17m/v6B6N8L/dhMleELI8OFXrU3pkOdWbS4b7v0IfbhQ71OfSks7p1hZd/2PPrkOW5QHtnOtSX5wIfOmv3SIf2+NCZDvXluUB7Z3UOvbj8IyhEZKMxZl6+x+EzdBgM9GgPHdpDh/bQoT10aA8dBoOtx7CdqV6R7wHsA9BhMNCjPXRoDx3aQ4f20KE9dBgMVh5DdaaaEEIIIYQQF4TtTDUhhBBCCCGBE5pNtYicKSLbROQdEbkp3+PxARE5UESeFZE3RGSriCxJH99PRJ4WkbfTf0/J91i1IyIREdksIo+lP6bDHBCRySLyiIi8mZ6Px9NhbojIDemf49dF5CERKabD4RGRe0WkSURezzo2pDcRWZpeZ7aJyKfzM2pdDOHwB+mf59dE5H9FZHLW/9HhAAZzmPV/N4qIEZGKrGN0OIChHIrIdWlPW0XkP7OO5+wwFJtqEYkA+CGAswAcBeBiETkqv6PygiSArxljjgQwH8C1aW83AfidMeYwAL9Lf0z2zhIAb2R9TIe58V8AnjTGHAHgGKRc0uEIEZEDACwGMM8YczSACICLQIcjYSWAMwccG9Rb+v7xIgCz0l9zV3r9CTsr8dcOnwZwtDHmEwDeArAUoMO9sBJ/7RAiciCA0wHsyDpGh4OzEgMcisipAM4H8AljzCwAt6aPj8phKDbVAI4D8I4x5k/GmASAh5GSSPaCMabBGPNq+t8xpDYyByDl7r70p90H4LN5GaAniMg0AGcDuDvrMB2OEBGZBOBkAPcAgDEmYYxpBx3mSiGACSJSCKAEwG7Q4bAYY54DEB1weChv5wN42BjTa4zZDuAdpNafUDOYQ2PMWmNMMv3hSwCmpf9Nh4MwxDwEgOUAvgEg+wlydDgIQzi8GsD3jTG96c9pSh8flcOwbKoPALAz6+Nd6WNkhIjIwQDmANgAYKoxpgFIbbwBVOVxaD5wO1J3ev1Zx+hw5HwMQDOAn6QvoblbREpBhyPGGFOP1BmYHQAaAHQYY9aCDkfLUN641oyOLwH4TfrfdDhCROQ8APXGmD8M+C86HDkzAZwkIhtEZL2IHJs+PiqHYdlUyyDH+LInI0REJgJ4FMD1xpjOfI/HJ0TkHABNxphN+R6LxxQC+BsAPzLGzAHQBV6mkBPpa37PB3AIgFoApSLyhfyOap+Ea02OiMjNSF1q+EDm0CCfRocDEJESADcD+OZg/z3IMTocnEIAU5C6xPXrAH4hIoJROgzLpnoXgAOzPp6G1K8+yTCIyDikNtQPGGNWpQ83ikhN+v9rADQN9fUEJwA4T0TeQ+qyo0+JyP2gw1zYBWCXMWZD+uNHkNpk0+HIOQ3AdmNMszGmD8AqAAtAh6NlKG9ca3JARC4FcA6AS8xfXt+XDkfGoUg9SP5Den2ZBuBVEakGHebCLgCrTIqXkfqNcgVG6TAsm+pXABwmIoeIyHikLj5fk+cxqSf9aO0eAG8YY27L+q81AC5N//tSAKvHemy+YIxZaoyZZow5GKl594wx5gugwxFjjNkDYKeIHJ4+tAjAH0GHubADwHwRKUn/XC9C6jkSdDg6hvK2BsBFIlIkIocAOAzAy3kYn3pE5EwA/wTgPGNMd9Z/0eEIMMZsMcZUGWMOTq8vuwD8Tfr+kg5Hzq8AfAoARGQmgPEAWjBKh4XuxqkHY0xSRL4C4CmknvV+rzFma56H5QMnAPgigC0iUpc+9s8Avo/Ur0j+AanF+vP5GZ7X0GFuXAfggfSD4j8BuBypkwJ0OAKMMRtE5BEAryL1q/bNSL1z2ETQ4V4RkYcALARQISK7ANyCIX5+jTFbReQXSD3oSwK41hjzYV4GroghHC4FUATg6dTjPLxkjLmKDgdnMIfGmHsG+1w6HJwh5uG9AO5Nv8xeAsCl6d+ajMoh31GREEIIIYQQS8Jy+QchhBBCCCHO4KaaEEIIIYQQS7ipJoQQQgghxBJuqgkhhBBCCLGEm2pCCCGEEEIs4aaaEEI8Q0QWi8gbIvLA8J+915yrROTvgxoXIYSEGb6kHiGEeIaIvAngLGPM9nyPhRBCSAqeqSaEEI8QkR8D+BiANSLSISI/E5FnRORtEbki/TkLRWS9iPxCRN4Ske+LyCUi8rKIbBGRQ9Of9y0RuTGffQghZF+Bm2pCCPEIY8xVAHYDOBXAcgCfAHA2gOMBfFNEatOfegyAJQA+jtQ7o840xhwH4G6k3qGSEEJIgHBTTQghfrPaGBM3xrQAeBbAcenjrxhjGowxvQDeBbA2fXwLgIPHfpiEELJvw001IYT4zcAnxmQ+7s061p/1cT+AQteDIoSQsMFNNSGE+M35IlIsIvsDWAjglTyPhxBCQgk31YQQ4jcvA3gcwEsAvmOM2Z3n8RBCSCjhS+oRQoiniMi3AHxgjLk132MhhJCwwzPVhBBCCCGEWMIz1YQQQgghhFjCM9WEEEIIIYRYwk01IYQQQgghlnBTTQghhBBCiCXcVBNCCCGEEGIJN9WEEEIIIYRYwk01IYQQQgghlvw/KHnQa5zAOw0AAAAASUVORK5CYII=\n",
"text/plain": [
"
"
]
@@ -1272,7 +2760,7 @@
}
],
"source": [
- "show('fpm', 'mph', rides, 'Speed (miles per hour) versus Ride Grade (feet per mile)')"
+ "show('fpmi', 'mph', rides, 'Speed (miles per hour) versus Ride Grade (feet per mile)')"
]
},
{
@@ -1286,7 +2774,7 @@
},
{
"cell_type": "code",
- "execution_count": 101,
+ "execution_count": 94,
"metadata": {},
"outputs": [
{
@@ -1295,7 +2783,7 @@
"'Coast: 70 min, Creek: 64 min.'"
]
},
- "execution_count": 101,
+ "execution_count": 94,
"metadata": {},
"output_type": "execute_result"
}
@@ -1317,14 +2805,14 @@
"source": [
"# VAM\n",
"\n",
- "Climbing speed measured by vertical ascent in meters per hour is known as [VAM](https://en.wikipedia.org/wiki/VAM_%28bicycling%29), which stands for *velocità ascensionale media* (for native Campagnolo speakers) or *vertical ascent in meters* (for SRAM) or 平均上昇率 (for Shimano), and sometimes by Vm/h. The theory is that for fairly steep climbs, most of your power is going into lifting against gravity, so your VAM should be about constant no matter what the grade. (For flatish climbs power is spent on wind and rolling resistance, and for the very steepest of climbs, in my experience, power goes largely to cursing *sotto voce*, as they say in Italian.) \n",
+ "Climbing speed is measured by [VAM](https://en.wikipedia.org/wiki/VAM_%28bicycling%29), which stands for *velocità ascensionale media* (for native Campagnolo speakers) or *vertical ascent in meters per hour* (for SRAM) or 平均上昇率 (for Shimano), or *Vm/h* (for physicists). The theory is that for fairly steep climbs, most of your power is going into lifting against gravity, so your VAM should be about constant no matter what the grade. (For flatish segments power is spent on wind and rolling resistance, and for the very steepest of climbs, in my experience, power goes largely to cursing *sotto voce*, as they say in Italian.) \n",
"\n",
"Here's a plot of my VAM versus grade over short segments:"
]
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+ "execution_count": 95,
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@@ -1348,7 +2836,2402 @@
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- "Champion cyclists can do over 1800 meters/hour over a 10 km climb, and can sustain [1400 meters/hour for 7 hours](https://www.strava.com/activities/4996833865). My VAM numbers range mostly from 400 to 900 meters/hour, but I can sustain the higher numbers for only a couple of minutes:"
+ "Champion cyclists can do over 1800 meters/hour over a 10 km climb, and can sustain [1400 meters/hour for 7 hours](https://www.strava.com/activities/4996833865). My VAM numbers range mostly from 400 to 800 meters/hour, and I can sustain the higher numbers for only a couple of minutes:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 96,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "