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This slide presentation reviews the affect of urbanization on community health. It exams urbanization trends in the Atlanta metro area and includes information on impervious surfaces, air quality, mitigation strategies, spatial growth modeling, land use, public health surveillance and different data collection methods.
Now, more than ever before, NASA is realizing the value and importance of their intellectual assets. Principles of knowledge management-the systematic use and reuse of information, experience, and expertise to achieve a specific goal-are being applied throughout the agency. LSDA is also applying these solutions, which rely on a combination of content and collaboration technologies, to enable research teams to create, capture, share, and harness knowledge to do the things they do well, even better. In the early days of spaceflight, space life sciences data were collected and stored in numerous databases, formats, media-types and geographical locations. These data were largely unknown/unavailable to the research community. The Biomedical Informatics and Health Care Systems Branch of the Space Life Sciences Directorate at JSC and the Data Archive Project at ARC, with funding from the Human Research Program through the Exploration Medical Capability Element, are fulfilling these requirements through the systematic population of the Life Sciences Data Archive. This project constitutes a formal system for the acquisition, archival and distribution of data for HRP-related experiments and investigations. The general goal of the archive is to acquire, preserve, and distribute these data and be responsive to inquiries for the science communities. Information about experiments and data, as well as non-attributable human data and data from other species' are available on our public Web site http://lsda.jsc.nasa.gov. The Web site also includes a repository for biospecimens, and a utilization process. NASA has undertaken an initiative to develop a Shuttle Data Archive repository. The Shuttle program is nearing its end in 2010 and it is critical that the medical and research data related to the Shuttle program be captured, retained, and usable for research, lessons learned, and future mission planning. Communities of practice are groups of people who share a concern or a passion for something they do, and learn how to do it better as they interact regularly. LSDA works with the HRP community of practice to ensure that we are preserving the relevant research and data they need in the LSDA repository. An evidence-based approach to risk management is required in space life sciences. Evidence changes over time. LSDA has a pilot project with Collexis, a new type of Web-based search engine. Collexis differentiates itself from full-text search engines by making use of thesauri for information retrieval. The high-quality search is based on semantics that have been defined in a life sciences ontology. Additionally, Collexis' matching technology is unique, allowing discovery of partially matching dicuments. Users do not have to construct a complicated (Boolean) search query, but can simply enter a free text search without the risk of getting "no results". Collexis may address these issues by virtue of its retrieval and discovery capabilities across multiple repositories.
Human performance is critical to crew safety during space missions. Humans interact with hardware and software during ground processing, normal flight, and in response to events. Human interactions with hardware and software can cause Loss of Crew and/or Vehicle (LOCV) through improper actions, or may prevent LOCV through recovery and control actions. Humans have the ability to deal with complex situations and system interactions beyond the capability of machines. Human Reliability Analysis (HRA) is a method used to qualitatively and quantitatively assess the occurrence of human failures that affect availability and reliability of complex systems. Modeling human actions with their corresponding failure probabilities in a Probabilistic Risk Assessment (PRA) provides a more complete picture of system risks and risk contributions. A high-quality HRA can provide valuable information on potential areas for improvement, including training, procedures, human interfaces design, and the need for automation. Modeling human error has always been a challenge in part because performance data is not always readily available. For spaceflight, the challenge is amplified not only because of the small number of participants and limited amount of performance data available, but also due to the lack of definition of the unique factors influencing human performance in space. These factors, called performance shaping factors in HRA terminology, are used in HRA techniques to modify basic human error probabilities in order to capture the context of an analyzed task. Many of the human error modeling techniques were developed within the context of nuclear power plants and therefore the methodologies do not address spaceflight factors such as the effects of microgravity and longer duration missions. This presentation will describe the types of human error risks which have shown up as risk drivers in the Shuttle PRA which may be applicable to commercial space flight. As with other large PRAs of complex machines, human error in the Shuttle PRA proved to be an important contributor (~12 percent) to LOCV. An existing HRA technique was adapted for use in the Shuttle PRA, but additional guidance and improvements are needed to make the HRA task in space-related PRAs easier and more accurate. Therefore, this presentation will also outline plans for expanding current HRA methodology to more explicitly cover spaceflight performance shaping factors.
HRA is a method used to describe, qualitatively and quantitatively, the occurrence of human failures in the operation of complex systems that affect availability and reliability. Modeling human actions with their corresponding failure in a PRA (Probabilistic Risk Assessment) provides a more complete picture of the risk and risk contributions. A high quality HRA can provide valuable information on potential areas for improvement, including training, procedural, equipment design and need for automation.
To investigate the ability of column (or partial column) information to represent surface air quality, results of linear regression analyses between surface mixing ratio data and column abundances for O3 and NO2 are presented for the July 2011 Maryland deployment of the DISCOVER-AQ mission. Data collected by the P-3B aircraft, ground-based Pandora spectrometers, Aura/OMI satellite instrument, and simulations for July 2011 from the CMAQ air quality model during this deployment provide a large and varied data set, allowing this problem to be approached from multiple perspectives. O3 columns typically exhibited a statistically significant and high degree of correlation with surface data (R(sup 2) > 0.64) in the P- 3B data set, a moderate degree of correlation (0.16 < R(sup 2) < 0.64) in the CMAQ data set, and a low degree of correlation (R(sup 2) < 0.16) in the Pandora and OMI data sets. NO2 columns typically exhibited a low to moderate degree of correlation with surface data in each data set. The results of linear regression analyses for O3 exhibited smaller errors relative to the observations than NO2 regressions. These results suggest that O3 partial column observations from future satellite instruments with sufficient sensitivity to the lower troposphere can be meaningful for surface air quality analysis.
Microphone phased array acoustic measurements of a 26 percent-scale, Boeing 777-200 main landing gear model with and without noise reduction fairings installed were obtained in the anechoic configuration of the Virginia Tech Stability Tunnel. Data were acquired at Mach numbers of 0.12, 0.15, and 0.17 with the latter speed used as the nominal test condition. The fully and partially dressed gear with the truck angle set at 13 degrees toe-up landing configuration were the two most extensively tested configurations, serving as the baselines for comparison purposes. Acoustic measurements were also acquired for the same two baseline configurations with the truck angle set at 0 degrees. In addition, a previously tested noise reducing, toboggan-shaped fairing was re-evaluated extensively to address some of the lingering questions regarding the extent of acoustic benefit achievable with this device. The integrated spectra generated from the acoustic source maps reconfirm, in general terms, the previously reported noise reduction performance of the toboggan fairing as installed on an isolated gear. With the recent improvements to the Virginia Tech tunnel acoustic quality and microphone array capabilities, the present measurements provide an additional, higher quality database to the acoustic information available for this gear model.
The aviation industry has long recognized the potential benefits of predictive maintenance, a maintenance strategy that leverages sensor and operational data to predict the future degradation of components. Prescriptive maintenance takes this a step further and considers the entire aviation ecosystem to schedule maintenance actions optimally. With the ability to reduce maintenance costs by up to 30%, as reported by the Department of Energy, these maintenance strategies have been identified to be an important investment to reduce a airline costs. However, despite great interest and technological advances in areas such as diagnostics, prognostics, sensing, computation, and machine learning, the adoption of predictive and prescriptive maintenance has not been widely applied in aviation. To shed light on this issue, we conducted an analysis of the barriers preventing or limiting the adoption of predictive and prescriptive maintenance in aviation. Through discussions with subject matter experts across industry, academia, standards bodies, and government, we identified five key challenges: complexity of prediction; validation, safety assurance, and regulatory challenges; cost of adoption; difficulty in quantifying impact and informing decisions; and data availability, quality, and ownership challenges. This study provides a detailed overview of these barriers and areas where stakeholders could invest to overcome them, aiming to support the scaled adoption of predictive and prescriptive maintenance in aviation.
Reliable, low latency delivery of high quality global flux and concentration information is a growing but still unmet need to advance expanding measurement, monitoring, reporting, and verification efforts that underpin federal climate mitigation strategies. Here we present on progress toward developing space-based greenhouse gas (GHG) monitoring systems that can provide comprehensive information trailing real time by a matter of weeks to a few months. Through support from its Carbon Monitoring System (CMS) program, NASA has developed the capability to assimilate XCO 2 retrievals from the Orbiting Carbon Observatory, 2 (OCO 2 ) into the Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS) to create gap-filled, three-dimensional (3D) estimates of CO 2 mixing ratio. When observations are unavailable, concentration fields are further informed by observationally-informed bottom-up flux packages that incorporate remotely sensed fire, nighttime lights, and vegetation observations combined with estimates of atmospheric growth rate based on surface in situ data. The 3D nature of these datasets supports evaluation with independent aircraft data to improve confidence in satellite data, development of new regional modeling approaches, and quantification of the climate impacts of GHGs. The system has recently been expanded to assimilate XCH 4 from ESA’s TROPOspheric Monitoring Instrument (TROPOMI) instrument and is supported by companion efforts to improve delivery of estimates of bottom-up land and ocean fluxes. The quasi-operational GEOS-GHG system is contributing to the recently announced U.S. Greenhouse Gas Center (GHG Center) by delivering information on recent changes in CO 2 and CH 4 emissions and concentrations to support stakeholder and research communities. In this presentation, we provide an overview of the current system configured to support the GHG Center. We highlight examples of how this data contributes to broader NASA initiatives including the Earth Information Center, an innovative virtual and physical exhibit designed to show how NASA data helps the nation combat climate change. We conclude by discussing how innovations in CMS research can address remaining data gaps and modeling challenges to advance operational GHG monitoring in the future.
Manuals provide quality control and test personnel with basic information on liquid penetrant testing. Topics covered include scope of application, equipment and materials used, test procedures, safety precautions, quality control, and comparison of liquid penetrant testing with other nondestructive testing processes.
Peru's Madre de Dios region is a hotspot for dengue fever and leishmaniasis due to its tropical Amazonian climate. Though treatable, these zoonotic diseases are debilitating for under-resourced communities whose already close proximity to mosquito and sandfly vectors continues to increase via rapid urbanization and deforestation. Peru’s Ministries of Health (MINSA) and Environment (MINAM) are working to better understand the environmental factors amplifying the risk of dengue fever and leishmaniasis transmission. The first term of this project classified the land use and land cover of Madre de Dios’ 11 districts for 2010, 2015, and 2020 and identified a correlation between both diseases and urbanization. Our team expanded this analysis by creating urban-forest edge maps and incorporating climatic and topographic variables with data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), and the Shuttle Radar Topography Mission (SRTM). We determined these variables’ impacts on disease incidence by assessing existing literature and running regression models. Dengue fever correlated with urban-forest edge, urban area, slope, temperature, and precipitation. Leishmaniasis primarily correlated with forest-edge area and elevation, but lacking additional statistical significance prevented further work, a decision supported by the literature. Thus, the risk matrix and risk map which we scripted in R to visualize the risk of disease posed to districts alongside health post locations addresses only dengue fever. The results and products will inform MINSA and MINAM in public health interventions, resource distribution, and policy initiatives.
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Software Engineering and Ada Database (SEAD) was developed to provide an information resource to NASA and NASA contractors with respect to Ada-based resources and activities which are available or underway either in NASA or elsewhere in the worldwide Ada community. The sharing of such information will reduce duplication of effort while improving quality in the development of future software systems. SEAD data is organized into five major areas: information regarding education and training resources which are relevant to the life cycle of Ada-based software engineering projects such as those in the Space Station program; research publications relevant to NASA projects such as the Space Station Program and conferences relating to Ada technology; the latest progress reports on Ada projects completed or in progress both within NASA and throughout the free world; Ada compilers and other commercial products that support Ada software development; and reusable Ada components generated both within NASA and from elsewhere in the free world. This classified listing of reusable components shall include descriptions of tools, libraries, and other components of interest to NASA. Sources for the data include technical newletters and periodicals, conference proceedings, the Ada Information Clearinghouse, product vendors, and project sponsors and contractors.
The Propulsion Flight Test Fixture at the NASA Dryden Flight Research Center is a unique test platform available for use on NASA's F-15B aircraft, tail number 836, as a modular host for a variety of aerodynamics and propulsion research. For future flight data from this platform to be valid, more information must be gathered concerning the quality of the airflow underneath the body of the F-15B at various flight conditions, especially supersonic conditions. The flow angularity and Mach number must be known at multiple locations on any test article interface plane for measurement data at these locations to be valid. To determine this prerequisite information, flight data will be gathered in the Rake Airflow Gauge Experiment using a custom-designed flowfield rake to probe the airflow underneath the F-15B at the desired flight conditions. This paper addresses the design considerations of the rake and probe assembly, including the loads and stress analysis using analytical methods, computational fluid dynamics, and finite element analysis. It also details the flow calibration procedure, including the completed wind-tunnel test and posttest data reduction, calibration verification, and preparation for flight-testing.
Examples of L-band interference will be presented and discussed, as well as the importance of L-band soil moisture observations, as part of this one-day GEOSS workshop XXXVII on "Data Quality and Radio Spectrum Allocation Impact on Earth Observations" will address the broad challenges of data quality and the impact of generating reliable information for decision makers who are Earth data users but not necessarily experts in the Earth observation field. GEO has initiated a data quality assessment task (DA-09-01a) and workshop users will review and debate the directions and challenges of this effort. Radio spectrum allocation is an element of data availability and data quality, and is also associated with a GEO task (AR-06-11). A recent U.S. National Research Council report on spectrum management will be addressed as part of the workshop. Key representatives from industry, academia, and government will provide invited talks on these and related issues that impact GEOSS implementation.
In the first section of this report background information for the use of the ERB-7 Master Archival Tapes (MAT) is provided. The second section gives details regarding the scientific validity and quality of the MAT. The MAT data analyzed covers the period from November 16, 1978 to October 31, 1979.
As the aerosol products from the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) mature, we are placing greater focus on ways of using the aerosol amount and type data products, and aerosol plume heights, to constrain aerosol transport models. We have demonstrated the ability to map aerosol air-mass-types regionally, and have identified product upgrades required to apply them globally, including the need for a quality flag indicating the aerosol type information content, that varies depending upon retrieval conditions. We have shown that MISR aerosol type can distinguish smoke from dust, volcanic ash from sulfate and water particles, and can identify qualitative differences in mixtures of smoke, dust, and pollution aerosol components in urban settings. We demonstrated the use of stereo imaging to map smoke, dust, and volcanic effluent plume injection height, and the combination of MISR and MODIS aerosol optical depth maps to constrain wildfire smoke source strength. This talk will briefly highlight where we stand on these application, with emphasis on the steps we are taking toward applying the capabilities toward constraining aerosol transport models, planet-wide.
The use of aerospace medical techniques to improve the quality of earth health care systems is discussed. Data are focused on physiological measurements and monitoring, medical information management, clean room technology, and reliability and quality assurance for hospital equipment.
For the past 4 years, the Air Quality Monitor (AQM) has been the operational instrument for measuring trace volatile organic compounds on the International Space Station (ISS). The key components of the AQM are the inlet preconcentrator, the gas chromatograph (GC), and the differential mobility spectrometer. Onboard the ISS are two AQMs with different GC columns that detect and quantify 22 compounds. The AQM data contributes valuable information to the assessment of air quality aboard ISS for each crew increment. The US Navy is looking to update its submarine air monitoring suite of instruments and the success of the AQM on ISS has led to a jointly planned submarine sea trial of a NASA AQM. In addition to the AQM, the Navy is also interested in the Multi-Gas Monitor (MGM), which measures major constituent gases (oxygen, carbon dioxide, water vapor, and ammonia). A separate paper will present the MGM sea trial preparation and the analysis of most recent ISS data. A prototype AQM, which is virtually identical to the operational AQM, has been readied for the sea trial. Only one AQM will be deployed during the sea trial, but this is sufficient for NASA purposes and to detect the compounds of interest to the US Navy for this trial. The data from the sea trial will be compared to data from archival samples collected before, during, and after the trial period. This paper will start with a brief history of past collaborations between NASA and the U.S. and U.K. navies for trials of air monitoring equipment. An overview of the AQM technology and protocols for the submarine trial will be presented. The majority of the presentation will focus on the AQM preparation and a summary of available data from the trial.