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Concepts to Support HRP Integration Using Publications and Modeling

Initial efforts are underway to enhance the Human Research Program (HRP)'s identification and support of potential cross-disciplinary scientific collaborations. To increase the emphasis on integration in HRP's science portfolio management, concepts are being explored through the development of a set of tools. These tools are intended to enable modeling, analysis, and visualization of the state of the human system in the spaceflight environment; HRP's current understanding of that state with an indication of uncertainties; and how that state changes due to HRP programmatic progress and design reference mission definitions. In this talk, we will discuss proof-of-concept work performed using a subset of publications captured in the HRP publications database. The publications were tagged in the database with words representing factors influencing health and performance in spaceflight, as well as with words representing the risks HRP research is reducing. Analysis was performed on the publication tag data to identify relationships between factors and between risks. Network representations were then created as one type of visualization of these relationships. This enables future analyses of the structure of the networks based on results from network theory. Such analyses can provide insights into HRP's current human system knowledge state as informed by the publication data. The network structure analyses can also elucidate potential improvements by identifying network connections to establish or strengthen for maximized information flow. The relationships identified in the publication data were subsequently used as inputs to a model captured in the Systems Modeling Language (SysML), which functions as a repository for relationship information to be gleaned from multiple sources. Example network visualization outputs from a simple SysML model were then also created to compare to the visualizations based on the publication data only. We will also discuss ideas for building upon this proof-of-concept work to further support an integrated approach to human spaceflight risk reduction.

Mindock, J.↗

Object Detection and Pose Estimation Public Competition Sample Data

This data was created with open-source tooling for the purpose of running a public competition. This dataset is a sample of what can be generated for the commissioned competition runner to be able to set up their testing infrastructure. It contains images of publicly available spacecraft models in a Blender scene composed of a light source, a background image, and the spacecraft model with bounding box labels.

James Berck↗

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↗

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.↗

Publication Of Oceanographic Data on CD-ROM

Large collections of oceanographic data and other large collections of data published on CD-ROM's in formats facilitating access and analysis. Involves four major steps: preprocessing, premastering, mastering, and verification. Large capacity, small size, commercial availability, long-life, and standard format of CD-ROM's offer advantages over computer-compatible magnetic tape.

Hilland, Jeffrey E.↗

Gross spectral differences between bright and dim gamma-ray bursts

We find that dim gamma-ray bursts (GRBs) are softer than bright GRBs, as indicated on average by data from the Burst and Transient Source Experiment (BATSE) on board the Compton Gamma Ray Observatory (CGRO). We show that this correlation is statistically significant with respect to variations due to random differences between GRBs. This effect is discernible using a variety of methods and data sets, including public domain data. We analyze several types of systematic errors and selection effects in the BATSE data and conclude that the observed effect is not dominated by any of them. We therefore assert that this dim/soft effect is a real property of GRBs. It is possible that this correlation is a consequence of the time dilation and that the burst sources are located at cosmological distances.

Nemiroff, R. J.↗

Robust Combining of Disparate Classifiers Through Order Statistics

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

Tumer, Kagan↗

A Dark Energy Camera Search for an Optical Counterpart to the First Advanced LIGO Gravitational Wave Event GW150914

We report the results of a deep search for an optical counterpart to the gravitational wave (GW) event GW150914, the first trigger from the Advanced LIGO GW detectors. We used the Dark Energy Camera (DECam) to image a 102 deg(exp 2) area, corresponding to 38% of the initial trigger high-probability sky region and to 11% of the revised high-probability region. We observed in the i and z bands at 4-5, 7, and 24 days after the trigger. The median 5(sigma) point-source limiting magnitudes of our search images are i = 22.5 and z = 21.8 mag. We processed the images through a difference-imaging pipeline using templates from pre-existing Dark Energy Survey data and publicly available DECam data. Due to missing template observations and other losses, our effective search area subtends 40 deg(exp 2), corresponding to a 12% total probability in the initial map and 3% in the final map. In this area, we search for objects that decline significantly between days 4-5 and day 7, and are undetectable by day 24, finding none to typical magnitude limits of i = 21.5, 21.1, 20.1 for object colors (i-z)= 1, 0, -1, respectively. Our search demonstrates the feasibility of a dedicated search program with DECam and bodes well for future research in this emerging field.

binaries: close – catalogs – gravitational wav↗

GeneLab: Open Science For Exploration

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. The GeneLab project houses spaceflight and spaceflight-relevant multi-omics data in a publicly accessible data commons, and collaborates with NASA-funded principal investigators to maximize the omics data from spaceflight and spaceflight-relevant experiments. I will discuss the current status of GeneLab and give specific examples of how the GeneLab data system has been used to gain insight into how biology responds to spaceflight conditions.

Omics↗

Creating a Repository of Publication Citations for a Data Center

Tracking dataset citations in scientific publications provide multiple benefits: obtaining citation indices for quantitative evaluation of the dataset scientific impact, learning about dataset usage in applied sciences, credits to dataset creators, datasets co-citation relationships and many more.

Infometrics↗

Combined Release and Radiation Effects Satellite (CRRES) experiments data collection, analysis, and publication

The Combined Release and Radiation Effects Satellite (CRRES) program experiments data collection, analysis, and publication activities are described. These activities were associated with both the satellite chemical release and a planned Puerto Rico sounding rocket campaign. To coordinate these activities, a working group meeting was organized and conducted.

Long, Terry N.↗

Use of the NASA Giovanni Data System for Geospatial Public Health Research: Example of Weather-Influenza Connection

The NASA Giovanni data analysis system has been recognized as a useful tool to access and analyze many different types of remote sensing data. The variety of environmental data types has allowed the use of Giovanni for different application areas, such as agriculture, hydrology, and air quality research. The use of Giovanni for researching connections between public health issues and Earths environment and climate, potentially exacerbated by anthropogenic influence, has been increasingly demonstrated. In this communication, the pertinence of several different data parameters to public health will be described. This communication also provides a case study of the use of remote sensing data from Giovanni in assessing the associations between seasonal influenza and meteorological parameters. In this study, logistic regression was employed with precipitation, temperature and specific humidity as predictors. Specific humidity was found to be associated (p 0.05) with influenza activity in both temperate and tropical climate. In the two temperate locations studied, specific humidity was negatively correlated with influenza; conversely, in the three tropical locations, specific humidity was positively correlated with influenza. Influenza prediction using the regression models showed good agreement with the observed data (correlation coefficient of 0.50.83).

public health↗

Summary of the Geocarto International Special Issue on "NASA Earth Science Satellite Data for Applications to Public Health" to be Published in Early 2014

At the 2011 Applied Science Public Health review held in Santa Fe, NM, it was announced that Dr. Dale Quattrochi from the NASA Marshall Space Flight Center, John Haynes, Program Manager for the Applied Sciences Public Health program at NASA Headquarters, and Sue Estes, Deputy Program Manager for the NASA Applied Sciences Public Health Program located at the Universities Space Research Association (USRA) at the National Space Science and Technology Center (NSSTC) in Huntsville, AL, would edit a special issue of the journal Geocarto International on "NASA Earth Science Satellite Data for Applications to Public Health". This issue would be focused on compiling research papers that use NASA Earth Science satellite data for applications to public health. NASA's Public Health Program concentrates on advancing the realization of societal and economic benefits from NASA Earth Science in the areas of infectious disease, emergency preparedness and response, and environmental health (e.g., air quality). This application area as a focus of the NASA Applied Sciences program, has engaged public health institutions and officials with research scientists in exploring new applications of Earth Science satellite data as an integral part of public health decision- and policy-making at the local, state and federal levels. Of interest to this special issue are papers submitted on are topics such as epidemiologic surveillance in the areas of infectious disease, environmental health, and emergency response and preparedness, national and international activities to improve skills, share data and applications, and broaden the range of users who apply Earth Science satellite data in public health decisions, or related focus areas.. This special issue has now been completed and will be published n early 2014. This talk will present an overview of the papers that will be published in this special Geocarto International issue.

Quattrochi, Dale A.↗

Emerging markets for satellite data communications in the public service

The paper discusses some of the current and potential markets for satellite data communications as projected by the Public Service Satellite Consortium (PSSC). Organizations in the public service sector are divided into three categories, depending on their expected benefits and organizational changes due to increased satellite telecommunications use: A - modest institutional adjustments are necessary and significant productivity gains are likely; B - institutional requirements picture is promising, but more information is needed to assess benefits and risk; and C - major institutional adjustments are needed, risks are high but possible benefits are high. These criteria are applied to the U.S. health care system, continuing education, equipment maintenance, libraries, environmental monitoring, and other potential markets. The potential revenues are seen to be significant, but what is needed is a cooperative effort by common carriers and major public service institutions to aggregate the market.

Potter, J. G.↗