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At least 37 records · Page 2

Linking NASA Environmental Data with a National Public Health Cohort Study and a CDC On-Line System to Enhance Public Health Decision Making

The overall goal of this study is to address issues of environmental health and enhance public health decision making by utilizing NASA remotely-sensed data and products. This study is a collaboration between NASA Marshall Space Flight Center, Universities Space Research Association (USRA), the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental datasets were linked with public health data from the UAB REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental national datasets will also be made available to public health professionals, researchers and the general public via the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system, where they can be aggregated to the county, state or regional level as per users need and downloaded in tabular, graphical, and map formats. The linkage of these data provides a useful addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in this online system. It also substantially expands public access to NASA data, making their use by a wide range of decision makers feasible.

Al-Hamdan, Mohammad↗

VISAGE - A Visualization and Exploration Framework for Environmental Data

Diverse airborne and ground-based environmental observations are important technologies for disaster assessment and response, as well as for the validation of environmental satellite observations and atmospheric models which can improve forecasts. The VISAGE (Visualization for Integrated Satellite, Airborne and Ground-based data Exploration) project is working to provide three-dimensional visualization and basic analytics capabilities for such datasets in an interactive user interface. The use of cloud-native, server less technologies for analysis optimized data storage will position VISAGE for integration with other technologies into a Data Analytic Center Framework.

Conover, Helen↗

Creating a Tools Ecosystem for Cross-Discipline Environmental Data Reuse

Reusing data is difficult even within well-defined science communities and only gets worse when combining data from multiple communities and disciplines. Through the lens of current work on constructing an environmental epidemiological data set from multiple disciplinary sources, we demonstrate the need for a new tool ecosystem to support heterogeneous Big Data science. Extending existing community standards for schemas and/or data formats through human auditing and wrangling of the data is not feasible at scale. This work therefore suggests new approaches for the multi-disciplinary communities to build a shared tool ecosystem for big data. We discuss both the larger context of data wrangling of epidemiological data sets for novel artificial intelligence algorithms and the specific lessons from working with these multi-disciplinary data sets. Adopting a more model-driven, automatable approach promises not only better efficiency but also removes key sources of human-generated errors and promotes reuse and reproducibility of science data.

Logan, Jeremy↗

Integrating Public Health Surveillance and Environmental Data to Model Presence of Histoplasma in the United States

In the United States, the true geographic distribution of the environmental fungus Histoplasma capsulatum remains poorly understood but appears to have changed since it was first characterized. Histoplasmosis is caused by inhalation of the fungus and can range in severity from asymptomatic to life-threatening. Due to limited public health surveillance and under detection of infections, it is challenging to directly use reported case data to characterize spatial risk. Using monthly and yearly county-level public health surveillance data and various environmental and socioeconomic characteristics, we use a spatio-temporal occupancy model to estimate latent, or unobserved, presence of H. capsulatum , accounting for imperfect detection of histoplasmosis cases. We estimate areas with higher probabilities of the presence of H. capsulatum in the East North Central states around the Great Lakes, reflecting a shift of the endemic region to the north from previous estimates. The presence of H. capsulatum was strongly associated with higher soil nitrogen levels. In this investigation, we were able to mitigate challenges related to reporting and illustrate a shift in the endemic region from historical estimates. This work aims to help inform future surveillance needs, clinical awareness, and testing decisions for histoplasmosis.

97 MATHEMATICS AND COMPUTING↗

PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Finding relevant chemicals in the vast (known) chemical space is a major challenge for environmental and exposomics studies leveraging nontarget high resolution mass spectrometry (NT-HRMS) methods. Chemical databases now contain hundreds of millions of chemicals, yet many are not relevant. This article details an extensive collaborative, open science effort to provide a dynamic collection of chemicals for environmental, metabolomics, and exposomics research, along with supporting information about their relevance to assist researchers in the interpretation of candidate hits. The PubChemLite for Exposomics collection is compiled from ten annotation categories within PubChem, enhanced with patent, literature and annotation counts, predicted partition coefficient (logP) values, as well as predicted collision cross section (CCS) values using CCSbase. Monthly versions are archived on Zenodo under a CC-BY license, supporting reproducible research, and a new interface has been developed, including historical trends of patent and literature data, for researchers to browse the collection. This article details how PubChemLite can support researchers in environmental and exposomics studies, describes efforts to increase the availability of experimental CCS values, and explores known limitations and potential for future developments. The data and code behind these efforts are openly available.

PubChem↗

The Use of GIS and Remotely Sensed Data in Environmental Public Health Tracking (EPHT): The HELIX-Atlanta Experience

As part of the National Environmental Public Health Tracking Network (EPHTN), the National Center for Environmental Health (NCEH) at the Centers for Disease Control and Prevention (CDC) is leading a project in collaboration with the NASA Marshall Space Flight Center (NASA/MSFC) called Health and Environment Linked for Information Exchange (HELIX-Atlanta). HELIX-Atlanta's goal is to examine the feasibility of building an integrated electronic health and environmental data network in five counties of metropolitan Atlanta, GA. Under HELIX-Atlanta, pilot projects are being conducted to develop methods to characterize exposure; link health and environmental data; analyze the relationship between health and environmental factors; and communicate findings. There is evidence in the research literature that asthmatic persons are at increased risk of developing asthma exacerbations with exposure to environmental factors, including PM(sub 2.5). Thus, HELIX-Atlanta is focusing on methods for characterizing population exposure to PM(sub 2.5) for the Atlanta metropolitan area that could be used in ongoing surveillance. NASA/MSFC is working with CDC to combine NASA earth science satellite observations related to air quality and environmental monitoring data to model surface estimates of fine particulate matter (PM(sub 2.5)) concentrations in a Geographic Information System (GIS) that can be linked with clinic visits for asthma on the aggregated grid level as well as the individual level at the geographic locations of the patients' residences.

Al-Hamdan, Mohammad Z.↗

Sensor Network Provides Environmental Data

The National Biocomputation Center, a joint partnership between the Stanford University School of Medicine's Department of Surgery and NASA's Ames Research Center, is the test bed for much of NASA's research in telemedicine, the remote delivery of medical care. In early 2005, researchers at the National Biocomputation Center formed a spinoff company, Intelesense Technologies, to use the telemedicine sensors to provide integrated global monitoring systems. Intelesense uses the systems to better understand how environments and people are linked, monitor and protect natural resources, predict and adapt to environmental changes, provide for sustainable development, reduce the costs and impacts of natural disasters, and provide an effective and intelligent response to such disasters. Current projects range from protecting the environment to tracking emerging infectious diseases like avian influenza (bird flu) and helping people from around the world connect and interact with each other to better understand their environment and themselves.

Source record↗

DCS: A global satellite environmental data collection system study

Cost analysis and technical feasibility data are presented on five medium orbiting and six geosynchronous satellite data collection systems with varying degrees of spacecraft and local user terminal complexity. Data are also provided on system approaches, user requirements, and user classes. Systems considered include orbiting ERTS and EOS type satellites and geosynchronous SmS and SEOS type data collectors.

Source record↗

DCS - A global satellite environmental data collection system.

This paper presents a summary of the results of a comparative study of satellite data collection systems which utilize remote ground data collection platforms transmitting data directly to a satellite and down to low-cost direct read-out local user terminals. The general objective of the study was to evaluate cost and technical feasibility of five medium orbiting and six geo-synchronous satellite data collection system (DCS) configurations with varying degrees of spacecraft and local user terminal (LUT) complexity. The goal of trading spacecraft and LUT complexity was to determine practical feasible systems with low-cost terminals, yet with a reasonable overall system cost the would permit the broad worldwide utilization of a highly beneficial data collection system. Results presented include data collection system analyses, satellite and local user terminal designs, and estimated costs. A summary of the types of local users and their requirements is also included.

Claire, E. J.↗

Performance monitor system functional simulator, environmental data, orbiter 101(HFT)

Information concerning the environment component of the space shuttle performance monitor system simulator (PMSS) and those subsystems operational on the shuttle orbiter 101 used for horizontal flight test (HFT) is provided, along with detailed data for the shuttle performance monitor system (PMS) whose software requirements evolve from three basic PMS functions: (1) fault detection and annunciation; (2) subsystem measurement management; and (3) subsystem configuration management. Information relative to the design and operation of Orbiter systems for HFT is also presented, and the functional paths are identified to the lowest level at which the crew can control the system functions. Measurement requirements are given which are necessary to adequately monitor the health status of the system. PMS process requirements, relative to the measurements which are necessary for fault detection and annunciation of a failed functional path, consist of measurement characteristics, tolerance limits, precondition tests, and correlation measurements.

Parker, F. W.↗

Analysis of Skylab follow-on orbital neutron environmental data

The data base and techniques developed for Skylab experiment ED76 were used to process and analyze data from 54 solid dielectric track recorders. The processing of mica and cellulose nitrate for neutron and proton detectors is described. The measured time integrated fission rates for seven detectors is given.

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Development of specifications for surface and subsurface oceanic environmental data

The existing need for synoptic subsurface observations was demonstrated giving special attention to the requirements of meteorology. The current state of synoptic oceanographic observations was assessed; a preliminary design for the Basic Observational Network needed to fulfill the minimum needs of synoptic meteorology and oceanography was presented. There is an existing critical need for such a network in the support of atmospheric modeling and operational meteorological prediction, and through utilization of the regional water mass concept an adequate observational system can be designed which is realistic in terms of cost and effort.

Wolff, P. M.↗

P78-2 SCATHA environmental data atlas

The 100 eV to approximately 1 MeV plasma environment encountered by the P78-2 Spacecraft Charging at High Altitudes (SCATHA) satellite during its initial operation period was studied. Forty-four days of 10 minute averages of the four moments of the electron and ion distribution functions calculated from the SC5 and SC9 energetic particle measurements were analyzed to determine occurrence frequency, local time variation, geomagnetic activity variation, and L shell variation. The single and double Maxwellian parameters derived from the four moments were similarly analyzed. The interrelationships between the moments and derived parameters were computed and the results compared with the ATS-5 and ATS-6 atlas. Results of this analysis establish a baseline range for the SCATHA plasma environment.

Mulen, E. G.↗