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At least 145 records · Page 8

Sleep Environment Recommendations for Future Spaceflight Vehicles

We conducted a comprehensive literature review summarizing optimal sleep hygiene parameters for lighting, temperature, airflow, humidity, comfort, intermittent and erratic sounds, and privacy and security in the sleep environment. We reviewed the design and use of sleep environments in a wide range of cohorts including among aquanauts, expeditioners, pilots, military personnel and ship operators. We also reviewed the specifications and sleep quality data arising from every NASA spaceflight mission, beginning with Gemini. Finally, we conducted structured interviews with individuals experienced in sleeping in non-traditional spaces including oilrig workers, Navy personnel, astronauts, and expeditioners. We also interviewed the engineers responsible for the design of the sleeping quarters presently deployed on the International Space Station. We found that the optimal sleep environment is cool, dark, quiet, and is perceived as safe and private. There are wide individual differences in the preferred sleep environment; therefore modifiable sleeping compartments are necessary to ensure all crewmembers are able to select personalized configurations for optimal sleep. It is possible to utilize lessons learned from prior spaceflight missions and from other industries in order to guide the design of an optimal sleep space suitable for long-duration spaceflight.

spaceflight↗

Sleep Environment Recommendations for Future Spaceflight Vehicles

Evidence from spaceflight and ground-based missions demonstrate that sleep loss and circadian desynchronization occur among astronauts, leading to reduced performance and, increased risk of injuries and accidents. We conducted a comprehensive literature review to determine the optimal sleep environment for lighting, temperature, airflow, humidity, comfort, intermittent and erratic sounds, privacy and security in the sleep environment. We reviewed the design and use of sleep environments in a wide range of cohorts including among aquanauts, expeditioners, pilots, military personnel, and ship operators. We also reviewed the specifications and sleep quality data arising from every NASA spaceflight mission, beginning with Gemini. We found that the optimal sleep environment is cool, dark, quiet, and is perceived as safe and private. There are wide individual differences in the preferred sleep environment; therefore modifiable sleeping compartments are necessary to ensure all crewmembers are able to select personalized configurations for optimal sleep.

Caddick, Zachary A.↗

Biocybernetic Closed-Loop System for Mitigating Hazardous States of Awareness

The past century of passenger flight has seen continuous improvement in aviation safety by the aerospace industry. However, while commercial aviation accident rates have continued to decline, human error-related incident and accident rates remain remarkably constant across all types of aviation (Shappell, et al., 2007). Unfortunately, this level of human error is unacceptable when considering projections for increased traffic volume (FAA, 2009), and is likely to yield more incidents and accidents unless a more complete understanding of operator error is achieved and remediations are implemented. One area of interest highlighted by researchers is Hazardous States of Awareness (HSAs) that can result from deficiencies in the design and inappropriate use of human-machine interfaces. Identifying and mitigating HSAs is critical for reducing operator errors. One promising approach uses psychophysiological measures which enable automated systems to adapt to the operator?s state and modify modes of operation to support optimal human performance (Scerbo, 2007). This paper will survey previous research and describe future directions for the application of psychophysiological measures of operators derived from cortical and autonomic assessment to perform real-time adaptive modulation of human-automation task mode mixes. The authors will present a summary of previous work done at NASA LaRC and Old Dominion University using a Psychophysiologically Adaptive System (PAS) in which the level of automation of the NASA Multi-Attribute Task Battery was modulated based on Engagement Indices derived from the users? electroencephalogram (Pope, Bogart, & Bartolome, 1995; for review see, Scerbo, Freeman, & Mikulka, 2003). Future theoretical and methodological directions for this type of closed-loop research will be discussed. Specifically, the capacity for this type of PAS to maintain effective operator state and to enable validation of candidate physiological indices will be described. Consideration will also be given to critical system characteristics (e.g., engagement indices, methods for invoking changes among system states, individual differences among users, etc.) that have been or still need to be studied. The potential of the PAS approach for interactive system design and prototyping will also be described. Examples of adaptive automation flight deck concepts in recent experiments will be highlighted and discussed.

Chad L Stephens↗

X-HAB 2020: AR Field Treks Summary and Conclusions

As part of the FY20 X-Hab Challenge, BLiSS sought to create an Augmented Reality (AR) toolkit to help with analog field trek operations under the supervision of the Solar System Exploration Research Virtual Institute (SSERVI). These treks are operational and technical demonstrations at space-like destinations on Earth to test current extra-vehicular activity (EVA) techniques. While BLiSS as an organization has experience studying operational tasks such as this, it has never developed AR software at this scale. For that reason, another team at the University was brought on to work in parallel. The Collaborative Lab for Advancing Work in Space (CLAWS) is a veteran group of the NASA Spacesuit User Interface Technologies for Students (SUITS) challenge in which Hololens displays for astronauts are created within a year. The operational and technological pairing was ideally suited for tackling this problem. The team divided its responsibilities so that BLiSS would handle the research required to shape the project. As this deliverable had an end user, it was decided that interviewing these field geologists and operations specialists would provide the best insight. These interviews paired with literature review would reveal niche applications for AR that remained within feasible bounds. These science-driven EVAs in unknown terrain require more flexible tools than the current generation of EVA assistants. Rather than focus on sequential instructions, there instead needs to be a broad toolkit that's only called upon in specific instances. This AR Toolkit for Lunar Astronauts and Scientists (ATLAS) became the development goal of the project: create a non-intrusive assembly of tools that could be accessed in AR on the field. The current ATLAS design makes use of a geospatially and temporally annotated eld note system called GeoNotes. This allows for data to be collected and coordinated in a way that's synchronized across time, space, and different users. A Mission Control Center (MCC) and Mobile Support Equipment (MSE) were all needed to transport the AR headset into the field with the user. A network infrastructure was designed and set up within the University to enable this functionality. The software is based on a Protocol-Module structure that allows for modular development of each capability. A Protocol Manager coordinates different protocols that make use of modules. Each module tackles a different individual task while the protocol puts each one to use. The protocol manager coordinates when these are called to be used. This software is hosted on a head-mounted display (HMD) with the MCC acting as support from afar. While the software would be unit-tested at each level and each hardware component verified, a final demonstration would serve to prove the system's capabilities: an analog field trek. The team would prepare to support a user in a remote location from the MCC back at the University. A local area near campus would be tested before going out to do sample field geology further away. This unfortunately became impossible with the arrival of COVID-19. Access to all of the facilities to complete the project as planned were shut down. Our team was scattered across the globe and forced to complete the rest virtually. Adjustments were made to produce a small virtual concept in Adobe XD in the meantime. Even digital surveys were created based on the NASA task-load index (TLX) originally intended for testing actual users. The goal shifted towards completing software and getting feedback on the user interfaces (UI) and user experiences (UX). This team has reformed in response to COVID and its focus has shifted to what can be done remotely. There is still an intention to finish the original deliverable described in this report. The work has been expanded beyond the original X-Hab challenge and has instead become its own research e ort to be continued afterwards. This report collects the processes and knowledge gained from a year of studying and working at this problem with two teams. It should preserve it for the time until the world returns to normal and work can resume. CLAWS will be taking over full responsibility from that point forward, eventually surpassing the original needs of the project. While this document captures the work done towards an eventual end, the CLAWS team has written their own proposal alongside it. It outlines a new future for ATLAS beyond X-Hab, BLiSS, and hopefully beyond COVID-19. This project began as a vague goal hoping to place a new technology into the unique setting of exploration science. The project has since comfortably taken root and will hopefully bloom over the next year.

Alex Sena↗

Examining the Relationship between Self-Reported Workload and Resilient Performance in Airline Flight Crews

Workload has long been associated with human performance in aviation. High workload is typically viewed as a system design problem. The aim of this work was to find observable behaviors that guard cognitive resource margins; thus, improve handling of perturbations that arise. Twelve commercial airline flight crews participated in an experiment at NASA Langley Research Center. We explored workload data (NASA Task Load Index) self-reported after completing flight simulation scenarios to see how different individuals, using the same technologies, cope with challenging situations. A trained observer from the same airline as the study participants assessed performance. We differentiated a lower workload crew from a higher workload crew and analyzed their workload and performance. Results indicate that the workload may be a component of pilots’ resilient performance. Initial strategies that reduced workload were classified and these types of behaviors, if implemented correctly, might assist pilots in maintaining functional workload resource margins.

Michael Stewart↗

Examining the Relationship Between Workload and Resilient Performance in Airline Flight Crews

Workload has long been associated with human performance in aviation. High workload is typically viewed as a system design problem. The aim of this work was to find observable behaviors that guard cognitive resource margins; thus, improve handling of perturbations that arise. Twelve commercial airline flight crews participated in an experiment at NASA Langley Research Center. We explored workload data (NASA Task Load Index) self-reported after completing flight simulation scenarios to see how different individuals, using the same technologies, cope with challenging situations. A trained observer from the same airline as the study participants assessed performance. We differentiated a lower workload crew from a higher workload crew and analyzed their workload and performance. Results indicate that the workload may be a component of pilots’ resilient performance. Initial strategies that reduced workload were classified and these types of behaviors, if implemented correctly, might assist pilots in maintaining functional workload resource margins.

Michael Stewart↗

Vision Changes after Space Flight Are Related to Alterations in Folate-Dependent One-Carbon Metabolism

About 20% of astronauts on International Space Station missions have developed measurable ophthalmic changes after flight. This study was conducted to determine whether the folate-dependent 1-carbon pathway is altered in these individuals. Data were modeled to evaluate differences between individuals with ophthalmic changes (n=5) and those without them (n=15). We also correlated mean preflight serum concentrations of the 1-carbon metabolites with changes in measured refraction after flight. Serum homocysteine (HCy), cystathionine, 2-methylcitric acid, and methylmalonic acid concentrations were 25%-45% higher (P<0.001) in astronauts with ophthalmic changes than in those without them. These differences existed before, during, and after flight. Preflight serum HCy and cystathionine, and in-flight serum folate, were significantly (P<0.05) correlated with postflight change in refraction, and preflight serum concentrations of 2-methylcitric acid tended to be associated (P=0.06) with ophthalmic changes. The biochemical differences observed in those with vision issues strongly suggests impairment of the folate-dependent 1-carbon transfer pathway. Impairment of this pathway, by polymorphisms, diet or other means, may interact with components of the microgravity environment to influence these pathophysiologic changes. This study was funded by the NASA Human Research Program.

Smith, Scott M.↗

Engineering, Life Sciences, and Health/Medicine Synergy in Aerospace Human Systems Integration: The Rosetta Stone Project

In the realm of aerospace engineering and the physical sciences, we have developed laws of physics based on empirical and research evidence that reliably guide design, research, and development efforts. For instance, an engineer designs a system based on data and experience that can be consistently and repeatedly verified. This reproducibility depends on the consistency and dependability of the materials on which the engineer works and is subject to physics, geometry and convention. In life sciences and medicine, these apply as well, but individuality introduces a host of variables into the mix, resulting in characteristics and outcomes that can be quite broad within a population of individuals. This individuality ranges from differences at the genetic and cellular level to differences in an individuals personality and abilities due to sex and gender, environment, education, etc.

Medicine↗

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗

Changes in total body water during spaceflight

Total body water (TBW) changes occurring in humans as a consequence of prolonged exposure to microgravity were measured in five male crewmembers of Space Shuttle missions STS-61C and STS-26. It was found that the inflight mean TBW values were significantly different from the preflight and postflight values, while the preflight TBW values were not significantly different from the postflight values. It was also found that individuals may differ in the rate at which they respond to weightlessness. Of the three crewmen who reported experiencing no symptoms of space motion sickness (SMS), two had not exhibited a decrease of TBW at the time of measurements (24 hrs after launch), while the two crewmen who reported SMS of intermediate severity showed a decrease of several kg by 24 hrs, suggesting that dehydration might be an important factor affecting the rate of TBW decrease.

Leach, Carolyn S.↗

The dynamics of warm and cold climates

Changes occurring as a result of climatic warming or cooling are presently investigated by comparing the atmospheric dynamics of five different climate simulations encompassing two ice ages, current and doubled CO2 climates, and a simulation of the warm Cretaceous; a global average surface air temperature range of 13 C is covered by the models. It is noted that many zonally averaged processes do not change systematically as climate changes: the January Hadley cell, the jet stream, mean precipitation patterns, and total atmospheric transport, show very little variation among the different climate simulations. These features result from balances between competing factors; while individual processes differ in the cold and warm climates, there is considerable compensation.

Rind, D.↗

Retrospective Analysis of Inflight Exercise Loading and Physiological Outcomes

Astronauts perform exercise throughout their missions to counter the health declines that occur as a result of long-term exposure to weightlessness. Although all astronauts perform exercise during their missions, the specific prescriptions, and thus the mechanical loading, differs among individuals. For example, inflight ground reaction force data indicate that subject-specific differences exist in foot forces created when exercising on the second-generation treadmill (T2) [1]. The current exercise devices allow astronauts to complete prescriptions at higher intensities, resulting in greater benefits with increased efficiency. Although physiological outcomes have improved, the specific factors related to the increased benefits are unknown. In-flight exercise hardware collect data that allows for exploratory analyses to determine if specific performance factors relate to physiological outcomes. These analyses are vital for understanding which components of exercise are most critical for optimal human health and performance. The relationship between exercise performance variables and physiological changes during flight has yet to be fully investigated. Identifying the critical performance variables that relate to improved physiological outcomes is vital for creating current and future exercise prescriptions to optimize astronaut health. The specific aims of this project are: 1) To quantify the exercise-related mechanical loading experienced by crewmembers on T2 and ARED during their mission on ISS; 2) To explore relationships between exercise loading variables, bone, and muscle health changes during the mission; 3) To determine if specific mechanical loading variables are more critical than others in protecting physiology; 4) To develop methodology for operational use in monitoring accumulated training loads during crew exercise programs. This retrospective analysis, which is currently in progress, is being conducted using data from astronauts that have flown long-duration missions onboard the ISS and have had access to exercise on the T2 and the Advanced Resistive Exercise Device (ARED). The specific exercise prescriptions vary for each astronaut. General exercise summary metrics will be developed to quantify exercise intensities, volumes, and durations for each subject. Where available, ground reaction force data will be used to quantify mechanical loading experienced by each astronaut. These inflight exercise metrics will be investigated relative to changes in pre- to post-flight bone and muscle health to identify which specific variables are related with improved or degraded physiological outcomes. The information generated from this analysis will fill gaps related to typical bone loading characterization, exercise performance capability, exercise volume and efficiency, and importance of exercise hardware. In addition, methods for quantification of exercise loading for use in monitoring the exercise programs during future space missions will be explored with the intent to inform exercise scientists and trainers as to the critical aspects of inflight exercise prescriptions.

Ploutz-Snyder, L. L.↗

Comparison of satellite and in situ data

A variety of data sets were available and analyzed. The data sets discussed here are: (1) SMMR-A: The Nimbus Project data release; (2) SMMR-D: The revised SMMR version produced by Wilheit and Milman; (3) SMMR-C: The SMMR version produced by Prabhakara; (4) Fleet Numerical Oceanography Center (PNOC): The individual ship reports; and (5) Reynolds Climatology. Data from SMMR and PNOC ships were compared in three different ways: (1) The difference between individual ship and SMMR observations which were close in space and time. (2) The difference between the 20 degree lat-lon one month averages for SMMR and ship, respectively. (3) The difference between the 20 degree averages and climatology, for both SMMR and ship.

Bernstein, R. L.↗

Comparison between Brewer spectrometer, M 124 filter ozonometer and Dobson spectrophotometer

Concurrent measurements were taken using the Brewer spectrometer no. 30, the filter ozonometer M 124 no. 200 and the Dobson spectrophotometer no. 71 from September 1987 to December 1988 at Potsdam. The performance of the instrument types and the compatibility of ozone data was checked under the conditions of a field measuring station. Total ozone values derived from Dobson AD direct sun measurements were considered as standard. The Dobson instrument had been calibrated at intercomparisons with the World Standard Dobson instrument no. 83 (Boulder) and with the Regional Standard instrument no. 64 (Potsdam), while the Brewer instrument was calibrated several times with the Travelling Standard Brewer no. 17 (Canada). The differences between individual Brewer DS (direct sun) ozone data and Dobson ADDS are within plus or minus 3 percent with half of all differences within plus or minus 1 percent. Less than 0.7 percent of the systematic difference can be due to atmospheric SO2. Due to inadequate regression coefficients Brewer ZB (zenith blue) ozone measurements are by (3...4) percent higher than Dobson ADDS ozone values. M124 DS ozone data are systematically by (1...2) percent higher than Dobson ADDS ozone with 50 percent of the differences within plus or minus 4 percent, but with extreme differences up to plus or minus (20...25) percent. M124 ZB ozone values are by (3...5) percent higher than Dobson ADDS with all the differences within plus or minus 10 percent, i.e. the scatter of differences is smaller for ZB than for M 124 DS measurements, Results for differences in the daily mean ozone values are also addressed. The differences include the uncertainties in the ozone values derived from both types of measurements. They provide an indication of the uncertainty in ozone data and the comparability of ozone values derived from different types of instruments.

Feister, U.↗

Two distinct regions of response drive differential growth in Vigna root electrotropism

Although exogenous electric fields have been reported to influence the orientation of plant root growth, reports of the ultimate direction of differential growth have been contradictory. Using a high-resolution image analysis approach, the kinetics of electrotropic curvature in Vigna mungo L. roots were investigated. It was found that curvature occurred in the same root toward both the anode and cathode. However, these two responses occurred in two different regions of the root, the central elongation zone (CEZ) and distal elongation zone (DEZ), respectively. These oppositely directed responses could be reproduced individually by a localized electric field application to the region of response. This indicates that both are true responses to the electric field, rather than one being a secondary response to an induced gravitropic stimulation. The individual responses differed in the type of differential growth giving rise to curvature. In the CEZ, curvature was driven by inhibition of elongation, whereas curvature in the DEZ was primarily due to stimulation of elongation. This stimulation of elongation is consistent with the growth response of the DEZ to other environmental stimuli.

Non-NASA Center↗

Improved Method of Manufacturing SiC Devices

The phrase, "common-layered architecture for semiconductor silicon carbide" ("CLASSiC") denotes a method of batch fabrication of microelectromechanical and semiconductor devices from bulk silicon carbide. CLASSiC is the latest in a series of related methods developed in recent years in continuing efforts to standardize SiC-fabrication processes. CLASSiC encompasses both institutional and technological innovations that can be exploited separately or in combination to make the manufacture of SiC devices more economical. Examples of such devices are piezoresistive pressure sensors, strain gauges, vibration sensors, and turbulence-intensity sensors for use in harsh environments (e.g., high-temperature, high-pressure, corrosive atmospheres). The institutional innovation is to manufacture devices for different customers (individuals, companies, and/or other entities) simultaneously in the same batch. This innovation is based on utilization of the capability for fabrication, on the same substrate, of multiple SiC devices having different functionalities (see figure). Multiple customers can purchase shares of the area on the same substrate, each customer s share being apportioned according to the customer s production-volume requirement. This makes it possible for multiple customers to share costs in a common foundry, so that the capital equipment cost per customer in the inherently low-volume SiC-product market can be reduced significantly. One of the technological innovations is a five-mask process that is based on an established set of process design rules. The rules provide for standardization of the fabrication process, yet are flexible enough to enable multiple customers to lay out masks for their portions of the SiC substrate to provide for simultaneous batch fabrication of their various devices. In a related prior method, denoted multi-user fabrication in silicon carbide (MUSiC), the fabrication process is based largely on surface micromachining of poly SiC. However, in MUSiC one cannot exploit the superior sensing, thermomechanical, and electrical properties of single-crystal 6H-SiC or 4H-SiC. As a complement to MUSiC, the CLASSiC five-mask process can be utilized to fabricate multiple devices in bulk single-crystal SiC of any polytype. The five-mask process makes fabrication less complex because it eliminates the need for large-area deposition and removal of sacrificial material. Other innovations in CLASSiC pertain to selective etching of indium tin oxide and aluminum in connection with multilayer metallization. One major characteristic of bulk micromachined microelectromechanical devices is the presence of three-dimensional (3D) structures. Any 3D recesses that already exist at a given step in a fabrication process usually make it difficult to apply a planar coat of photoresist for metallization and other subsequent process steps. To overcome this difficulty, the CLASSiC process includes a reversal of part of the conventional flow: Metallization is performed before the recesses are etched.

Okojie, Robert S.↗

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

carbon dioxide↗