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Combining Discrete Element Modeling, Finite Element Analysis, and Experimental Calibrations for Modeling of Granular Material Systems Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:43:27.000ZThe current state-of-the-art in DEM modeling has two major limitations which must be overcome to ensure that the technique can be useful to NASA engineers and the commercial sector: the computational intensive nature of the software, and the lack of an established methodology to determine the particle properties to best accurately model a given physical system. The proposed work will address both of these limitations. We will look at two approaches to overcome the particle count limitations of DEM: investigate the scaling up of particle size; and combine FEA and DEM to look at problems of densely packed solids. We will explore regimes where DEM and FEA are applicable and establish a coupling methodology that can be further developed during phase II. To address the lack of an established methodology to determine the particle properties to best accurately model a given physical system, we will investigate several small scale experiments that can be used to characterize DEM models. The proposed work will advance the state-of-the-art in DEM. At the end of phase I we will show the feasibility of developing modeling approaches to overcome the main limitations of DEM.
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Robust Optimal Fragmentation and Dispersion of Near-Earth Objects Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:31:30.000Z<p> During the past 2 decades, various concepts for mitigating the impact threats from NEOs have been proposed, but many of these concepts were impractical and not technically credible. In particular, all non-nuclear techniques require mission lead times larger than 10 years. However, for the most probable impact threat with a warning time less than 10 years, the use of high-energy nuclear explosives in space becomes inevitable for proper fragmentation and dispersion of an NEO in a collision course with Earth. However, the existing nuclear subsurface penetrator technology limits the impact velocity to less than 300m/s because higher impact velocities destroy prematurely the detonation electronic equipment. Thus, an innovative space system architecture utilizing high-energy nuclear explosives must be developed for a worst-case intercept mission resulting in relative closing velocities as high as 5-30km/s. An advanced system concept is proposed for nuclear subsurface explosion missions. The concept blends a hypervelocity kinetic-energy impactor with nuclear subsurface explosion, and exploits a 2-body space vehicle consisting of a fore body and an aft body. These 2 spacecraft bodies may be connected by a deployable boom. The fore body provides proper kinetic impact crater conditions for an aft body carrying nuclear explosives to make a deeper penetration into an asteroid body. For such a complex mission architecture design study, non-traditional, multidisciplinary research efforts in the areas of hypervelocity impact dynamics, nuclear explosion modeling, high-temperature thermal shielding, shock-resistant electronic systems, and advanced space system technologies are required. Expanding upon the current research activities, the Iowa State Asteroid Deflection Research Center will develop an innovative, advanced space system architecture that provides the planetary defense capabilities needed to enable a future real space mission more efficient, affordable, and reliable.</p>
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Health Home Quality Measures: Beginning 2013
health.data.ny.gov | Last Updated 2019-08-07T19:18:45.000ZThis dataset contains measures that evaluate the quality of care delivered by Health Homes for the Centers for Medicare & Medicaid Services (CMS) Core Set and Health Home State Plan Amendment (SPA). To support ongoing assessment of the effectiveness of the Health Home model, the CMS has established a recommended Core Set of health care quality measures that it intends to promulgate in the rulemaking process. The data used in the Health Home Quality Measures are taken from the following sources: • Medicaid Data Mart: Claims and encounters data generated from the Medicaid Data Warehouse (MDW). • QARR Member Level Files: Sample of the health plan eligible member’s quality. • New York State Delivery System Inform Incentive Program (DSRIP) Data Warehouse: Claims and encounters data generated from the Medicaid Data Warehouse (MDW). Please refer to the Overview document for additional information.
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Health Home Utilization- Nursing Facility
health.data.ny.gov | Last Updated 2019-09-27T00:05:48.000ZThis column chart illustrates the number of short-stay admissions to a nursing facility by Health Home. The New York State Department of Health (NYSDOH) collects annual data on children’s and adults’ use of health services. This information complements the Health Home Quality Measures information collected for the State Plan Amendment (SPA) and Core Set of health care quality measures. Utilization measures are designed to capture the frequency of certain services. NCQA does not view higher or lower services counts as better or worse performance. Please refer to the Overview document for additional information.
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DSNY Frequencies
data.cityofnewyork.us | Last Updated 2024-04-10T10:11:36.000ZCitywide DSNY frequency boundaries for collection operation (refuse, recycling, organics, bulk items). These boundaries are sub-divisions of DSNY sections.
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Child and Adult Care Food Programs (CACFP) – Day Care Homes – Site-Level Contact and Program Participation – Program Year 2018-2019
data.texas.gov | Last Updated 2023-09-11T20:01:42.000Z<b>About the Dataset</b><br> This dataset contains <b>contact and program participation information for Day Care Home (DCH) providers approved to operate under the Child and Adult Care Food Program (CACFP) during program year 2018-2019.</b> Contracting Entity (CE) sponsors can participate in more than one CACFP program. The CACFP program year begins October 1 and ends September 30.<p> This dataset only includes information for Texas Day Care Home providers participating in CACFP. <b>For data on CEs and sites participating as Adult Day Care Centers (ADC), Child Care Centers (CCC), At-Risk Afterschool Centers (At-Risk), Head Start Centers, emergency shelters, and centers providing care for students outside school hours, please refer to the “Child and Adult Care Food Programs (CACFP) – Centers – Contact and Program Participation” dataset, also on the State of Texas Open Data Portal.</b><p> <i>Dataset content and column order have been updated starting with program year 2018-2019 forward. Older program year datasets will retain original content and organization. </i><p> An overview of <b>all CACFP data available</b> on the Texas Open Data Portal can be found at our <b><a href=https://data.texas.gov/stories/s/iekx-7mdi target="_blank">TDA Data Overview - Child and Adult Care Food 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> <b>About Dataset Updates</b><br> TDA aims to post new program year data by December 15 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 update period is subject to change. After 90 days from the close of the program year, the 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 Programs (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> <i><b>For more information on these programs, please visit our <a href=http://www.SquareMeals.org target="_blank">SquareMeal.org website</a>.</b></i>
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Adams - N and AvgCap
data.colorado.gov | Last Updated 2024-05-01T19:38:57.000ZThis dataset includes all non-24 hour licensed child care facilities in the State of Colorado. It is updated monthly, and is intended for public use. It includes CDHS-issued child care license numbers, legal business names as they appear in the licensing application, the types of service the programs provide, the physical location addresses of the programs as they appear in the licensing application, the longitude-latitude coordinate values derived from geocoding services and spatial QA, the valid Colorado Shines quality rating levels (if applicable), total licensed capacities, and CCCAP utilization and fiscal agreement. Note: As of Jan 1, 2021, the following fields are temporarily unavailable in this release: `CCCAP CHILD COUNT_D1`, `CCCAP CASE COUNT_D1`, and `CCCAP_AMOUNT_PAID_D1`. These columns will be included again in the near future. Please contact the dataset owner for more information as necessary. Disclaimer: The State of Colorado, the Colorado Department of Human Services, and the Office of Early Childhood make no representations or warranties expressed or implied, with respect to the use of data provided herewith regardless of its format or the means of its transmission. There is no guarantee or representation to the user as to the accuracy, currency, suitability, or reliability of this data for any purpose. The user accepts the data “as is”. The State of Colorado assumes no responsibility for loss or damage incurred as a result of any user reliance on this data. Users of this information should review or consult the primary data and information sources to ascertain the usability of the information. The State of Colorado does not necessarily endorse any interpretations or products derived from the data.
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U.S. State and Territorial Stay-At-Home Orders: March 15, 2020 – August 15, 2021 by County by Day
healthdata.gov | Last Updated 2023-07-26T01:25:18.000ZState and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance. Data were collected to determine when individuals in states and territories were subject to executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require or recommend people stay in their homes. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level. These data are derived from the publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require or recommend individuals stay at home found by the CDC, COVID-19 Community Intervention and At-Risk Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 15, 2020 through August 15, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. These data do not include mandatory business closures, curfews, or limitations on public or private gatherings. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.
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Newly Identified Confirmed Chronic Hepatitis C Age 15-34 Year 2007-2016 Health
data.pa.gov | Last Updated 2022-10-17T20:05:23.000ZThis data set provides an estimate of the number of people aged 15-34 years with newly identified confirmed chronic (or past/present) hepatitis C infection, by county and by year. The dataset is limited to persons aged 15 to 34 because hepatitis C infection is usually asymptomatic for decades after infection occurs. Cases are usually identified because they have finally become symptomatic, or they were screened. Until very recently, screening for hepatitis C was not routinely performed. This makes it very challenging to identify persons with recent infection. Limiting the age of newly identified patients to 15-34 years makes it more likely that the cases included in the dashboard were infected fairly recently. It is not meant to imply that the opioid crisis’ effect on hepatitis C transmission is limited to younger people. The process by which case counts are determined is as follows: Case reports, which include lab test results and address data, are sent to Pennsylvania’s electronic disease surveillance system (PA-NEDSS). Confirmation status is determined by public health investigators who evaluate test results against the CDC case definition for hepatitis C in place for the year in which the patient was first reported (https://wwwn.cdc.gov/nndss/conditions/hepatitis-c-chronic/). Reportable disease data, including hepatitis C, is extracted from PA-NEDSS, combined with similar data sent by the Philadelphia Department of Public Health (PDPH, which uses a separate surveillance system), and sent to CDC. Case data sent to CDC (from PA-NEDSS and PDPH combined) are used to create a statewide reportable disease dataset. This statewide file was used to generate the dashboard dataset. Note that the term that CDC has used to denote persons with hepatitis C infection that is not known to be acute has switched back and forth between “Hepatitis C, past or present” and “Hepatitis C, chronic” over the past several years. The CDC case definition for hepatitis C, chronic (or past or present) changed in 2005, 2010, 2011, 2012, and 2016. Persons reported as confirmed in one year may not have been considered confirmed in another year. For example, patients with a positive radioimmunoblot assay (RIBA) or elevated enzyme immunoassay (EIA) signal-to-cutoff level were counted as confirmed in 2012, but not counted as confirmed in 2016. Data sent to CDC’s National Notifiable Disease Surveillance System use a measure for aggregating cases by year called the MMWR year. The MMWR, or the Morbidity and Mortality Weekly Report, is an official publication by CDC and the means by which CDC has historically presented aggregated case count data. Since data in the MMWR are presented by week, the MMWR year always starts on the Sunday closest to Jan 1 and ends on the Saturday closest to Dec 31. The most recent year for which case counts are finalized is 2016. Annual case counts are finalized in May of the following year. The patient zip code, as submitted to PA-NEDSS, is used to determine the case’s county of residence at the time of initial case report. In some instances, the patient zip code is unavailable. In those circumstances, the zip code of the provider that ordered the lab test is used as a proxy for patient zip code. Users should note that the state prison system routinely screens all incoming inmates for hepatitis C. If these inmates are determined to be confirmed cases, they are assigned to the county in which they were incarcerated when their confirmed hepatitis C was first identified. Hepatitis C case counts in counties with state prisons should be interpreted cautiously in light of this enhanced screening activity.
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Influenza Surveillance Weekly
data.cityofchicago.org | Last Updated 2024-06-08T04:30:11.000ZThis dataset includes aggregated weekly metrics of the surveillance indicators that the Department of Public Health uses to monitor influenza activity in Chicago. These indicators include: - Influenza-associated ICU hospitalizations for Chicago residents, which is a reportable condition in Illinois (HOSP_ columns) - Influenza laboratory data provided by participating sentinel laboratories in Chicago (LAB_ columns) - Influenza-like illness data for outpatient clinic visits and emergency department visits. (ILI_ columns) For more information on ILINET, see https://www.cdc.gov/flu/weekly/overview.htm#anchor_1539281266932. For more information on ESSENCE, see https://www.dph.illinois.gov/data-statistics/syndromic-surveillance All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.