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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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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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Fire / EMS Heat Map FY12 to Present
data.cityofgainesville.org | Last Updated 2023-09-28T14:19:17.000ZFire / EMS response data for FY2012 up to the most current month available.
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Hospitals
data.memphistn.gov | Last Updated 2019-10-25T20:04:39.000ZThe data describes the hospital locations in Memphis (and Collierville) with 24 hour Emergency Departments. Each hospital location listed is a facility the Memphis Fire Department's Emergency Medical Services (EMS) Bureau provides transportation services to when patients require immediate medical attention beyond the EMS scope of practice.
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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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Level 2 with CCCAP fiscal
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 address es 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. 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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Maternal Opioid Use Hospital Stays 2016-2017 County Health Care Cost Containment Council (PHC4)
data.pa.gov | Last Updated 2022-10-17T20:23:36.000ZCountywide counts of maternal hospital stays with opioid use and countywide rates of maternal hospital stays with opioid use per 1,000 maternal stays. Maternal stays include those involving a delivery, as well as other pregnancy-related stays. Opioid use, or opioid use disorder, is a diagnosis indicating opioid dependence, abuse, or use. Some opioid drugs may be prescribed as part of medication-assisted treatment to relieve withdrawal symptoms and psychological cravings often associated with opioid use disorders. Opioid use during pregnancy can lead to Neonatal Abstinence Syndrome (NAS) for newborns. This analysis is restricted to maternal hospital stays for Pennsylvania-state residents who were hospitalized in Pennsylvania hospitals. Disclaimer: PHC4’s database contains statewide hospital discharge data submitted to PHC4 by Pennsylvania hospitals. Every reasonable effort has been made to ensure the accuracy of the information obtained from the Uniform Claims and Billing Form (UB-82/92/04) data elements. Computer collection edits and validation edits provide opportunity to correct specific errors that may have occurred prior to, during or after submission of data. The ultimate responsibility for data accuracy lies with individual providers. PHC4 agents and staff make no representation, guarantee, or warranty, expressed or implied that the data received from the hospitals are error-free, or that the use of this data will prevent differences of opinion or disputes with those who use published reports or purchased data. PHC4 will bear no responsibility or liability for the results or consequences of its use.
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Governor's Executive Budget Program Measures SFY 2017 - Current Annual Statewide Health
data.pa.gov | Last Updated 2023-03-22T22:37:44.000ZThe information included in this dataset is for the Governor’s Executive Budget and provides key Program Measures by Agency or Office. <br> The mission of the Department of Health is to promote healthy behaviors, prevent injury and disease, and to assure the safe delivery of quality health care for all people in Pennsylvania.<br> To accomplish this mission, the department works collaboratively with public and private community partners to facilitate the development of an effective public health system. The department licenses and regulates a variety of health facilities, and provides outreach, education, prevention and treatment services. Community-based groups receive grants to provide essential services to the commonwealth’s citizens including programs for women and children, nutrition, immunization, diagnosis and treatment of certain blood and communicable diseases, cancer control and prevention.
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Cancer Incidence
data.delaware.gov | Last Updated 2022-10-06T19:08:59.000ZThis report includes cancer statistics for all cancer sites combined (all-site cancer), as well as eight specific cancer types. These cancer statistics reflect incidence data for 2008-2012.