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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Space Science and Technology Partnership Forum: In-Space Assembly Data Collection and Analysis

The Space Science and Technology Partnership Forum was established in 2015 to identify synergistic efforts and technologies across the government. In-Space Assembly (iSA) is the focus of the topic area that NASA is currently coordinating with other government agencies. This paper focuses on the data collection process, the data analysis of that information, and preliminary insights gleaned from the data. The goal of the analysis is to understand the linkages within the collected data, identifying synergies and gaps, and provide visualization of the current state of iSA needs and capability development across the government. Capability roadmaps, Venn diagrams, bubble charts, and scorecards (an overview of each individual iSA capability) are used to visualize the results of this analysis, which reveals areas of possible inter-agency collaboration, investment gaps in capabilities relative to the need, and capabilities that warrant engagement across multiple agencies to eliminate potential inefficiencies.

Arney, Dale C.↗
NASA NTRS2018

Space Science and Technology Partnership Forum: In-Space Assembly Data Collection and Analysis

The Space Science and Technology Partnership Forum was established in 2015 to identify synergistic efforts and technologies across the government. In-Space Assembly (iSA) is the focus of the topic area that NASA is currently coordinating with other government agencies. This paper focuses on the data collection process, the data analysis of that information, and preliminary insights gleaned from the data. The goal of the analysis is to understand the linkages within the collected data, identifying synergies and gaps, and provide visualization of the current state of iSA needs and capability development across the government. Capability roadmaps, Venn diagrams, bubble charts, and scorecards (an overview of each individual iSA capability) are used to visualize the results of this analysis, which reveals areas of possible inter-agency collaboration, investment gaps in capabilities relative to the need, and capabilities that warrant engagement across multiple agencies to eliminate potential inefficiencies.

Dale C Arney↗
DOE OSTI2024

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2016

Restoration of Apollo Data by the Lunar Data Project/PDS Lunar Data Node: An Update

The Apollo 11, 12, and 14 through 17 missions orbited and landed on the Moon, carrying scientific instruments that returned data from all phases of the missions, included long-lived Apollo Lunar Surface Experiments Packages (ALSEPs) deployed by the astronauts on the lunar surface. Much of these data were never archived, and some of the archived data were on media and in formats that are outmoded, or were deposited with little or no useful documentation to aid outside users. This is particularly true of the ALSEP data returned autonomously for many years after the Apollo missions ended. The purpose of the Lunar Data Project and the Planetary Data System (PDS) Lunar Data Node is to take data collections already archived at the NASA Space Science Data Coordinated Archive (NSSDCA) and prepare them for archiving through PDS, and to locate lunar data that were never archived, bring them into NSSDCA, and then archive them through PDS. Preparing these data for archiving involves reading the data from the original media, be it magnetic tape, microfilm, microfiche, or hard-copy document, converting the outmoded, often binary, formats when necessary, putting them into a standard digital form accepted by PDS, collecting the necessary ancillary data and documentation (metadata) to ensure that the data are usable and well-described, summarizing the metadata in documentation to be included in the data set, adding other information such as references, mission and instrument descriptions, contact information, and related documentation, and packaging the results in a PDS-compliant data set. The data set is then validated and reviewed by a group of external scientists as part of the PDS final archive process. We present a status report on some of the data sets that we are processing.

Lunar↗
DOE OSTI2020

Coordinative Entities: Forms of Organizing in Data Intensive Science

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Finally, our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

AmeriFlux US-GL1 Stannard Rock

This is the AmeriFlux version of the carbon flux data for the site US-GL1 Stannard Rock. Site Description - Stannard Rock is located 39 km from the nearest shore (Keweenaw Peninsula) in Lake Superior, 44 miles NNE of Marquette, Michigan, and 24 miles ESE of Manitou Island. The site is located on the historic Stannard Rock Lighthouse, which was completed in 1882. Eddy covariance instrumentation was installed in 2008 by a network of scientists from both US and Canada, eventually to be called the Great Lakes Evaporation Network (GLEN). The intent of GLEN has been to provide observations of over-lake meteorology and evaporation, improve forecasting of Great Lakes water levels, and support a wide variety of stakeholders, including the National Weather Service (NWS), Environment and Climate Change Canada, National Oceanic and Atmospheric Administration, U.S. Coast Guard, recreational boaters and commercial shipping, emergency management officials, and the Great Lakes research community. The eddy covariance station along with other ancillary meteorological instrumentation is located at an approximate elevation of 39.2 meters above mean lake water level. Meteorological data from the lighthouse are sent to the National Data Buoy Center, where they can be viewed in real-time at http://www.ndbc.noaa.gov/station_page.php?station=stdm4 Uncorrected half-hour fluxes were computed directly on the logger using a 30-minute block averaging period as high-frequency data were not available. The half hour flux measurements downloaded from the datalogger were post-processed with the following filters and corrections. Latent and sensible heat and carbon dioxide fluxes were corrected with 2-D coordinate rotation. Although the primary objective of data collection at Stannard Rock was to quantify the evaporative flux, additional preliminary measurements of the carbon dioxide concentration and flux from the LI-7500 are also included in this dataset but it is advised to use the carbon data with caution. Carbon data reported in this dataset includes turbulent fluxes of CO2 with no storage correction (FC, µmol m-2 s-1) and CO2 density in mole fraction of wet air (CO2), which was originally output on the datalogger as average CO2 density (mg m-2 s-1) and converted into µmol mol-1 using air temperature and pressure in post-processing. Webb, Pearman, and Leuning terms were applied to account for density fluctuations for water vapor and CO2. Sonic path length, high-frequency attenuation and sensor separation were accounted for according to Horst and Massman, and the oxygen absorption correction for the KH2O hygrometer was also applied. Latent and sensible heat fluxes were assumed to be unrealistic above an absolute value of 1000 W m-2 and were removed. Both carbon flux (FC) and carbon dioxide mole fraction in wet air (CO2) and were assumed to be unrealistic above 1000 µmol m-2 s-1 and 1000 µmol mol-1 respectively. Spikes in latent and sensible heat and carbon fluxes and densities (often due to periods of precipitation) were identified by computing the mean and standard deviation over a moving, overlapping window of 336 half-hours (7 days), similar to Shao et al., and were removed when the flux was more than 1.5 standard deviations from the moving window’s mean. While Vickers and Mahrt use a threshold of 3.5 standard deviations from the mean, a conservative value of 1.5 was chosen due to the noisy nature of over-lake data at this particular site. This process was repeated twice for latent and sensible heat, and carbon dioxide fluxes and densities and therefore it is possible that some real, realistic data was filtered out in this process. No detrending was performed. As per AmeriFlux standards, no friction velocity (USTAR, m s-1) filtering was performed.

Spence, Chris↗
DOE OSTI2025

AmeriFlux FLUXNET-1F US-GL1 Stannard Rock

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-GL1 Stannard Rock. This is the FLUXNET version of the carbon flux data for the site US-GL1 Stannard Rock produced by applying the standard ONEFlux (1F) software. Site Description - Stannard Rock is located 39 km from the nearest shore (Keweenaw Peninsula) in Lake Superior, 44 miles NNE of Marquette, Michigan, and 24 miles ESE of Manitou Island. The site is located on the historic Stannard Rock Lighthouse, which was completed in 1882. Eddy covariance instrumentation was installed in 2008 by a network of scientists from both US and Canada, eventually to be called the Great Lakes Evaporation Network (GLEN). The intent of GLEN has been to provide observations of over-lake meteorology and evaporation, improve forecasting of Great Lakes water levels, and support a wide variety of stakeholders, including the National Weather Service (NWS), Environment and Climate Change Canada, National Oceanic and Atmospheric Administration, U.S. Coast Guard, recreational boaters and commercial shipping, emergency management officials, and the Great Lakes research community. The eddy covariance station along with other ancillary meteorological instrumentation is located at an approximate elevation of 39.2 meters above mean lake water level. Meteorological data from the lighthouse are sent to the National Data Buoy Center, where they can be viewed in real-time at http://www.ndbc.noaa.gov/station_page.php?station=stdm4 Uncorrected half-hour fluxes were computed directly on the logger using a 30-minute block averaging period as high-frequency data were not available. The half hour flux measurements downloaded from the datalogger were post-processed with the following filters and corrections. Latent and sensible heat and carbon dioxide fluxes were corrected with 2-D coordinate rotation. Although the primary objective of data collection at Stannard Rock was to quantify the evaporative flux, additional preliminary measurements of the carbon dioxide concentration and flux from the LI-7500 are also included in this dataset but it is advised to use the carbon data with caution. Carbon data reported in this dataset includes turbulent fluxes of CO2 with no storage correction (FC, µmol m-2 s-1) and CO2 density in mole fraction of wet air (CO2), which was originally output on the datalogger as average CO2 density (mg m-2 s-1) and converted into µmol mol-1 using air temperature and pressure in post-processing. Webb, Pearman, and Leuning terms were applied to account for density fluctuations for water vapor and CO2. Sonic path length, high-frequency attenuation and sensor separation were accounted for according to Horst and Massman, and the oxygen absorption correction for the KH2O hygrometer was also applied. Latent and sensible heat fluxes were assumed to be unrealistic above an absolute value of 1000 W m-2 and were removed. Both carbon flux (FC) and carbon dioxide mole fraction in wet air (CO2) and were assumed to be unrealistic above 1000 µmol m-2 s-1 and 1000 µmol mol-1 respectively. Spikes in latent and sensible heat and carbon fluxes and densities (often due to periods of precipitation) were identified by computing the mean and standard deviation over a moving, overlapping window of 336 half-hours (7 days), similar to Shao et al., and were removed when the flux was more than 1.5 standard deviations from the moving window’s mean. While Vickers and Mahrt use a threshold of 3.5 standard deviations from the mean, a conservative value of 1.5 was chosen due to the noisy nature of over-lake data at this particular site. This process was repeated twice for latent and sensible heat, and carbon dioxide fluxes and densities and therefore it is possible that some real, realistic data was filtered out in this process. No detrending was performed. As per AmeriFlux standards, no friction velocity (USTAR, m s-1) filtering was performed.

Spence, Chris [Environment and Climate Change Cana↗
NASA NTRS1973

Earth Resources Technology Satellite: Cumulative US standard catalog, 23 July 1972 - 23 July 1973. Volume 1: Observation ID listing

Observation identification and coordinate listing are given for ERTS 1 images collected over the continental United States, Alaska, and Hawaii from July 23, 1972 to July 23, 1973. Data format includes the following: (1) the date of catalog listing; (2) the time frame during which the imagery was processed; (3) an assigned observation number; (4) microfilm role and image position on roll; (5) date of observation; (6) longitude and latitude in degrees and minutes at observation center; (7) estimated percent of cloud cover; (8) orbit number; (9) sun elevation and azimuth at observation center; and (10) image quality for both the return beam vidicon and the multispectral band scanner. Availability information for microfilm copies of ERTS imagery is included.

Source record↗
NASA NTRS1980

A two dimensional mesh verification algorithm

A two dimensional mesh verification algorithm is discussed which assumes that a finite element mesh is represented in a program by lists of data, i.e., vertex coordinates, element incidences, boundary data, which describe a collection of triangles. A set of conditions are placed on the triangles (i.e., on the list data) which ensure that the triangles tile a region and which also can be verified by the algorithm.

Simpson, R. B.↗
NASA NTRS1999

KC-135 and Other Microgravity Simulations

This document represents a summary of medical and scientific evaluations conducted aboard the KC-135 from June 20, 1998 to June 20, 1999. Included is a general overview of KC-135 activities manifested and coordinated by the Life Sciences Research Laboratories. A collection of brief reports that describes tests conducted aboard the KC-135 follows the overview. Principal investigators and test engineers contributed significantly to the content of the report describing their particular experiment or hardware evaluation. Although this document follows general guidelines, each report format may vary to accommodate differences in experiment design and procedures. This document concludes with an appendix that provides background information concerning the KC-135 and the Reduced-Gravity Program.

Noel C Skinner↗
NASA NTRS1994

Shared Problem Models and Crew Decision Making

The importance of crew decision making to aviation safety has been well established through NTSB accident analyses: Crew judgment and decision making have been cited as causes or contributing factors in over half of all accidents in commercial air transport, general aviation, and military aviation. Yet the bulk of research on decision making has not proven helpful in improving the quality of decisions in the cockpit. One reason is that traditional analytic decision models are inappropriate to the dynamic complex nature of cockpit decision making and do not accurately describe what expert human decision makers do when they make decisions. A new model of dynamic naturalistic decision making is offered that may prove more useful for training or aiding cockpit decision making. Based on analyses of crew performance in full-mission simulation and National Transportation Safety Board accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation and reflect the crew's metacognitive skill. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relation between communication that serves to build performance. Implications of these findings for crew training will be discussed.

Orasanu, Judith↗
NASA NTRS1994

Decision Making in Action: Applying Research to Practice

The importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment: Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

Orasanu, Judith↗
NASA NTRS1994

Decision Making in Action: Applying Research to Practice

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.

Orasanu, Judith↗
NASA NTRS1994

Decision Making in Action

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.

Orasanu, Judith↗
NASA NTRS1995

Decision Making in the Airplane

The Importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful In improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking In response to a problem, This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

Orasanu, Judith↗
NASA NTRS2010

Postflight Quiet Stance Stability of Astronauts Following Recovery From a Simulated Fall

INTRODUCTION: Astronauts returning from space flight universally present with postural ataxia. Throughout the Space Shuttle Program, measurement of ataxia has concentrated on sway in the anterior-posterior plane. Implementation of an interdisciplinary pre- and postflight study (Functional Task Test, FTT) designed to evaluate both astronaut postflight functional performance and related physiological changes has allowed the investigation of postural instability by characterizing dynamic stabilographic sway patterns. METHODS: Six astronauts from short-duration (Shuttle) and three from long-duration (ISS) flights were required to recover from a simulated fall. Subjects with eyes open, wearing running shoes lay prone on the floor for 2 minutes and then quickly stood up, maintained a quiet stance for 3 minutes, arms relaxed along the side of the body, and feet comfortably placed on the force plate. Crewmembers were tested twice before flight, on landing day (Shuttle only), and 1, 6, and 30 days after flight. Anterior-posterior (AP) and medial-lateral (ML) center-of-pressure (COP) coordinates were calculated from the ground reaction forces collected at 500 Hz. The 3-minute quiet stance trial was broken into three 1-minute segments for stabilogram diffusion analysis. A mean sway speed (rate of change of COP displacement) was also calculated as an additional postural stability parameter. RESULTS/CONCLUSION: While there was considerable variation, most of crewmembers tested exhibited increased stochastic activity evidenced by larger short-term COP diffusion coefficients postflight in both the AP and ML planes, suggesting significant changes in postural control mechanisms, particularly control of lower limb muscle function. As expected, postural instability of ISS astronauts on the first day postflight was similar to that of Shuttle crewmembers on landing day. Recoveries of stochastic activity and mean sway speed to baseline levels were typically observed by the 30th day postflight for both long-duration and short-duration crewmembers. Dynamic postural stability characteristics obtained in this low-impact study complement the data measured with computerized dynamic posturography.

Reschke, M. F.↗
NASA NTRS2011

A Simple Postflight Measure of Postural Atania in Astronauts

Astronauts returning from space flight universally present with postural ataxia. Throughout the Space Shuttle Program, measurement of ataxia has concentrated on sway in the anterior-posterior (AP) plane. The current investigation, as a part of a larger functional study, concentrated on characterizing postural instability using dynamic stabilographic sway patterns in both the AP and medial-lateral (ML) planes. To accomplish this goal, six astronauts from short-duration (Shuttle) and three from long-duration (ISS) flights were required to recover from a simulated fall. Subjects with eyes open, wearing running shoes lay prone on the floor for 2 minutes and then quickly stood up, maintained a quiet stance for 3 minutes, arms relaxed along the side of the body, and feet comfortably placed on the force plate. Crewmembers were tested twice before flight, on landing day (Shuttle only), and 1, 6, and 30 days after flight. Anterior-posterior and ML center-of-pressure (COP) coordinates were calculated from the ground reaction forces collected at 500 Hz. The 3-minute quiet stance trial was broken into three 1-minute segments for stabilogram diffusion analysis. A mean sway speed (rate of change of COP displacement) was also calculated as an additional postural stability parameter. While there was considerable variation, most of crewmembers tested exhibited increased stochastic activity evidenced by larger short-term COP diffusion coefficients postflight in both the AP and ML planes, suggesting significant changes in postural control mechanisms, particularly control of lower limb muscle function. As expected, postural instability of ISS astronauts on the first day postflight was similar to that of Shuttle crewmembers on landing day. Recoveries of stochastic activity and mean sway speed to baseline levels were typically observed by the 30th day postflight for both long-duration and short-duration crewmembers. Dynamic postural stability characteristics obtained in this low-impact study complement the data measured with computerized dynamic posturography.

Reschke, M. F.↗
NASA NTRSDate not supplied

NASA GeneLab: Open Science for Life in Space

NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. The open-access GeneLab repository currently consists of over 300 omics datasets generated by biological experiments, involving various model organisms, that are relevant to spaceflight. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. To aide GeneLab’s efforts to harmonize and democratize space-relevant omics data, over 130 scientists have joined one of four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG) and together helped develop and adopted standard data analysis workflows for all data types available in GeneLab. Currently, the GeneLab Data System includes a data repository with federated search capability, an online controlled-access toolshed powered by "Galaxy" for users to process data with vetted standard workflows, a workspace for data sharing, a data submission portal, and the ability to browse and visualize transcriptomics processed data. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. The visualization portal enhances GeneLab’s ability to democratize omics data by removing the need for bioinformatics expertise to interpret transcriptomics data hosted on GeneLab. This presentation will provide an over-view of NASA’s GeneLab including how to navigate the GeneLab Data System and will conclude by providing resources for opportunities to work with GeneLab and NASA at large.

Amanda M Saravia-Butler↗