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Affordable Practical High-Efficiency Photovoltaic Concentrator Blanket Assembly for Ultra-Lightweight Solar Arrays Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:13:36.000ZDeployable Space Systems, Inc. (DSS) will focus the proposed NASA Phase 1 effort on the development of our innovative Functional Advanced Concentrator Technology (FACT). FACT is an affordable practical high-efficiency concentrator blanket assembly for ultra-lightweight solar arrays. FACT coupled to an ultra-lightweight solar array structural platform (such as DSS's ROSA) will provide game-changing performance metrics and unparalleled affordability for the end-user. FACT will enable emerging Solar Electric Propulsion (SEP) Space Science missions, and other NASA missions, through its ultra-affordability, high voltage operation capability, high/low temperature operation capability, high/low illumination operation capability, high radiation tolerance, ultra-lightweight, and ultra-compact stowage volume. Once completely optimized through the proposed Phase 1 and Phase 2 programs the FACT technology promises to provide NASA/industry a near-term and low-risk flexible blanket technology for advanced solar array systems that provides revolutionary performance in terms of high specific power / ultra-lightweight (>400-500 W/kg BOL at the array level & >1000 W/kg BOL at the blanket level, PV dependent), affordability (>50% cost savings at the array level), compact stowage volume (>80 kW/m3 BOL, 10X times better than current rigid panel arrays), high operation reliability, high radiation tolerance, high voltage operation capability (>150 VDC), scalability, and LILT & HIHT operation capability.
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Nano Dust Analyzer Project
data.nasa.gov | Last Updated 2020-01-29T04:54:41.000Z<p> We propose to develop a new highly sensitive instrument to confirm the existence of the so-called nano-dust particles, characterize their impact parameters, and measure their chemical composition. Simultaneous theoretical studies will be used to derive the expected&nbsp; mass and velocity ranges of these putative particles to formulate science and measurement requirements for the future deployment of&nbsp; the proposed Nano-Dust Analyzer (NDA)&nbsp;</p> <p> Early dust instruments onboard Pioneer 8 and 9 and Helios spacecraft detected a flow of submicron sized dust particles coming from the direction of the Sun. These particles originate in the inner solar system from mutual collisions among meteoroids and move on&nbsp; hyperbolic orbits that leave the Solar System under the prevailing radiation pressure force. Later dust instruments with higher&nbsp; sensitivity had to avoid looking toward the Sun because of interference from the solar wind and UV radiation and thus contributed&nbsp; little to the characterization of the dust stream. The one exception is the Ulysses dust detector that observed escaping dust particles&nbsp; high above the solar poles, which confirm the suspicion that charged nanometer sized dust grains are carried to high heliographic&nbsp; latitudes by electromagnetic interactions with the Interplanetary Magnetic Field (IMF). Recently, the STEREO WAVES instruments&nbsp; recorded a large number of intense electric field signals, which were interpreted as impacts from nanometer sized particles striking the&nbsp; spacecraft with velocities of about the solar wind speed. This high flux and strong spatial and/or temporal variations of nanometer&nbsp; sized dust grains at low latitude appears to be uncorrelated with the solar wind properties. This is a mystery as it would require that&nbsp; the total collisional meteoroid debris inside 1 AU is cast in nanometer sized fragments. The observed fluxes of inner-source pickup ions&nbsp; also point to the existence of a much enhanced dust population in the nanometer size range.&nbsp;</p> <p> This new heliospherical phenomenon of nano-dust streams may have consequences throughout the planetary system, but as of yet no dust instrument exists that could be used to shed light on their properties. &nbsp;We propose to develop a dust analyzer capable to detect and&nbsp; analyze these mysterious dust particles coming from the solar direction and to embark upon complementary theoretical studies to&nbsp; understand their characteristics. The instrument is based on the Cassini Dust Analyzer (CDA) that has analyzed the composition of&nbsp; nanometer sized dust particles emanating from the Jovian and Saturnian systems but could not be pointed towards the Sun. By&nbsp; applying technologies implemented in solar wind instruments and coronagraphs a highly sensitive dust analyzer will be developed and&nbsp; tested in the laboratory. The dust analyzer shall be able to characterize impact properties (impact charge and energy distribution of&nbsp; ions from which mass and speed of the impacting grains may be derived) and chemical composition of individual nanometer sized&nbsp; particles while exposed to solar wind and UV radiation. The measurements will enable us to identify the source of the dust by&nbsp; comparing their elemental composition with that of larger micrometeoroid particles of cometary and asteroid origin and will reveal&nbsp; interaction of nano-dust with the interplanetary medium by investigating the relation of the dust flux with solar wind and IMF&nbsp; properties.&nbsp;</p> <p> Complementary theoretically studies will be performed to understand the characteristics of nano-dust particles at 1 AU to answer the&nbsp; following questions:&nbsp; - What is the speed range at which nanometer sized particles impact
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Vital Signs: Time in Congestion - Corridor (Updated October 2018)
data.bayareametro.gov | Last Updated 2018-10-24T00:31:33.000ZVITAL SIGNS INDICATOR Time Spent in Congestion (T7) FULL MEASURE NAME Time Spent in Congestion LAST UPDATED October 2018 DATA SOURCE MTC/Iteris Congestion Analysis No link available CA Department of Finance Forms E-8 and E-5 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-8/ http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-5/ CA Employment Division Department: Labor Market Information http://www.labormarketinfo.edd.ca.gov/ CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Time spent in congestion measures the hours drivers are in congestion on freeway facilities based on traffic data. In recent years, data for the Bay Area comes from INRIX, a company that collects real-time traffic information from a variety of sources including mobile phone data and other GPS locator devices. The data provides traffic speed on the region’s highways. Using historical INRIX data (and similar internal datasets for some of the earlier years), MTC calculates an annual time series for vehicle hours spent in congestion in the Bay Area. Time spent in congestion is defined as the average daily hours spent in congestion on Tuesdays, Wednesdays and Thursdays during peak traffic months on freeway facilities. This indicator focuses on weekdays given that traffic congestion is generally greater on these days; this indicator does not capture traffic congestion on local streets due to data unavailability. This congestion indicator emphasizes recurring delay (as opposed to also including non-recurring delay), capturing the extent of delay caused by routine traffic volumes (rather than congestion caused by unusual circumstances). Recurring delay is identified by setting a threshold of consistent delay greater than 15 minutes on a specific freeway segment from vehicle speeds less than 35 mph. This definition is consistent with longstanding practices by MTC, Caltrans and the U.S. Department of Transportation as speeds less than 35 mph result in significantly less efficient traffic operations. 35 mph is the threshold at which vehicle throughput is greatest; speeds that are either greater than or less than 35 mph result in reduced vehicle throughput. This methodology focuses on the extra travel time experienced based on a differential between the congested speed and 35 mph, rather than the posted speed limit. To provide a mathematical example of how the indicator is calculated on a segment basis, when it comes to time spent in congestion, 1,000 vehicles traveling on a congested segment for a 1/4 hour (15 minutes) each, [1,000 vehicles x ¼ hour congestion per vehicle= 250 hours congestion], is equivalent to 100 vehicles traveling on a congested segment for 2.5 hours each, [100 vehicles x 2.5 hour congestion per vehicle = 250 hours congestion]. In this way, the measure captures the impacts of both slow speeds and heavy traffic volumes. MTC calculates two measures of delay – congested delay, or delay that occurs when speeds are below 35 miles per hour, and total delay, or delay that occurs when speeds are below the posted speed limit. To illustrate, if 1,000 vehicles are traveling at 30 miles per hour on a one mile long segment, this would represent 4.76 vehicle hours of congested delay [(1,000 vehicles x 1 mile / 30 miles per hour) - (1,000 vehicles x 1 mile / 35 miles per hour) = 33.33 vehicle hours – 28.57 vehicle hours = 4.76 vehicle hours]. Considering that the posted speed limit on the segment is 60 miles per hour, total delay would be calculated as 16.67 vehicle hours [(1,000 vehicles x 1 mile / 30 miles per hour) - (1,000 vehicles x 1 mile / 60 miles per hour) = 33.33 vehicle hours – 16.67 vehicle hours = 16.67 vehicle hours]. Data sources listed above were used to calculate per-capita and per-worker statistics. Top congested corridors are ranked by total vehicle hours of delay, meaning that the highlighted corridors reflect a combination of slow speeds and heavy t
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Annual Report on Outreach to and Training of Cosmetologists (Historical)
data.cityofnewyork.us | Last Updated 2024-01-31T18:59:34.000ZThis data is from an annual report to be provided in compliance of Local Law 39 of 2019, covering the time period July 1 through October 15. The data set includes: a summary of outreach efforts to the cosmetology community, including the number of trainings provided for cosmetologists, disaggregated by borough. For Data Dictionary, please refer to this <a href="https://docs.google.com/spreadsheets/d/1P0b17twfrYTBfGN7J3jFV-pVV_H3nlkLITVz_8GmmNc/edit#gid=0">link</a>.
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Incidents vs Rescued to Shelter
www.dallasopendata.com | Last Updated 2021-08-17T20:59:04.000ZDallas Animal Services data that pertains to operations by Animal Services Officers (ASO) who respond to calls in the field throughout the City of Dallas. ASO’s document their work using Chameleon software, an animal shelter software program. The document will be updated on a daily basis, so that citizens have a greater understanding of what ASO’s are doing in the neighborhoods of Dallas. “Helping Dallas be a safe, compassionate, and healthy place for people and animals”. Start date is October 01, 2016
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Dallas Animal Medical Record Fiscal Year 2017 -2018
www.dallasopendata.com | Last Updated 2021-08-17T14:46:16.000ZDallas Animal Medical Data pertains to operational processes carried out by medical personnel who provide care and medical attention to the animals received at Dallas Animal Services. Medical personnel document their work using Chameleon software, an animal shelter management program. The Dallas Animal Medical Data is updated daily to help citizens better understand the operational processes that the medical personnel perform daily for the animals and citizens of the City of Dallas. “Helping Dallas be a safe, compassionate, and healthy place for people and animals”. The period covered by this dataset goes from October 01, 2017 - September 30, 2018.
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Low Income Home Energy Assistance Program FY 2008 Household Data
healthdata.gov | Last Updated 2023-07-25T18:42:49.000Z<p>State-reported annual data collected on the presence of elderly, disabled, and young children in eligible households receiving Low Income Home Energy Assistance Program (LIHEAP) heating assistance, cooling assistance, crisis assistance or weatherization assistance.</p>
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Recreation & Parks Program Totals: Fall 2015 - Summer 2016
opendata.howardcountymd.gov | Last Updated 2018-12-10T14:53:26.000ZData encompasses the number of participants enrolled in Howard County Recreation & Parks programs (I.e. Sports, Fitness, Nature & Environment, Camps etc...), by Season.
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State Park Trails
data.ny.gov | Last Updated 2024-04-24T19:08:18.000ZThe New York State Office of Parks, Recreation and Historic Preservation (OPRHP) oversees more than 250 state parks, historic sites, recreational trails, golf courses, boat launches and more, encompassing nearly 350,000 acres, that are visited by 74 million people annually. These facilities contribute to the economic vitality and quality of life of local communities and directly support New York’s tourism industry. Parks also provide a place for families and children to be active and exercise, promoting healthy lifestyles. The agency is responsible for the operation and stewardship of the state park system as well as advancing a statewide parks, historic preservation, and open space mission. This dataset is a shapefile of the mapped trails in NYS Parks.
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School Nutrition Programs - Contact Information and Site-Level Program Participation - Program Year 2020-2021
data.texas.gov | Last Updated 2023-11-21T14:29:13.000Z<b><a href=https://form.jotform.com/210556567409057 target="_blank">Help us provide the most useful data by completing our ODP User Feedback Survey for School Nutrition Data</a></b><p> <b>About the Dataset</b><br> In March 2020, USDA began allowing flexibility in nutrition assistance program policies in order to support continued meal access should the coronavirus pandemic (COVID-19) impact meal service operation. Flexibilities were extended into the 2020-2021 program year and allowed School Nutrition Programs to operate summer meal service programs through the end of the school year as needed. <p> <b>The CEs and sites listed in this dataset may be operating under programs other than the School Nutrition Programs as part of the USDA's flexibilities during this period.</b> Please refer to the <a href=http://data.texas.gov/dataset/School-Nutrition-Programs-Meal-Reimbursement-Infor/i674-5yp3 target="blank">School Nutrition Program (SNP) Meal Reimbursement</a>, <a href=http://data.texas.gov/dataset/Summer-Meal-Programs-Seamless-Summer-Option-SSO-Me/g3wi-mkrz target="blank">Seamless Summer Option (SSO) Meal Count</a>, and <a href=http://data.texas.gov/dataset/Summer-Meal-Programs-Summer-Food-Service-Program-S/tbnq-ytgh target="_blank">Summer Food Service Program (SFSP) Meal Count</a> datasets for Program Year 2020-2021 to confirm the program used to serve meals.<P> For more information on the waivers implemented for this purpose, please visit our website at <a href=http://www.SquareMeals.org target="_blank">SquareMeals.org</a>. <p> An overview of <b>all SNP data available</b> on the Texas Open Data Portal can be found at our <b><a href=https://data.texas.gov/stories/s/e2dm-5r4v target="_blank">TDA Data Overview - School Nutrition Programs</a></b> page.<p> An overview of <b>all TDA Food and Nutrition data available</b> on the Texas Open Data Portal can be found at our <b><a href=https://data.texas.gov/stories/s/TDA-Data-Overview-Food-and-Nutrition-Programs-Open/nk79-w2cs/ target="_blank">TDA Data Overview - Food and Nutrition Open Data</a></b> page. <p> <b>More information about accessing and working with TDA data on the Texas Open Data Portal</b> can be found on the SquareMeals.org website on the <b><a href=http://squaremeals.org/FandNResources/PublicInformationRequests.aspx target="_blank">TDA Food and Nutrition Open Data</a> </b>page.<p> <hr> <b>About Dataset Updates</b><br> TDA aims to post new program year data by September 1 of the active program year. Updates will occur quarterly and end 90 days after the close of the program year. Any data posted during the active program year is subject to change. After 90 days from the close of the program year, this dataset will remain published but will no longer be updated.<p> <b>About the Agency</b><br> The Texas Department of Agriculture administers 12 U.S. Department of Agriculture nutrition programs in Texas including the National School Lunch and School Breakfast Programs, the Child and Adult Care Food Program (CACFP), and summer meal programs. TDA’s Food and Nutrition division provides technical assistance and training resources to partners operating the programs and oversees the USDA reimbursements they receive to cover part of the cost associated with serving food in their facilities. By working to ensure these partners serve nutritious meals and snacks, the division adheres to its mission — <i>Feeding the Hungry and Promoting Healthy Lifestyles.</i><p> <b>For more information on these programs, please visit us at <a href=http://www.SquareMeals.org target="_blank">SquareMeals.org</a>.</b><br>