Inclusion of Radiation Effects in the NASA Reliability & Maintainability Standard
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Our intuition is that comprehensive of visual representations is often quicker than of equivalent
The purpose of this presentation is to provide information on healthy sleep to the entire NASA workforce. This presentation is part of the Office of the Chief Health and Medical Officer Journey to Wellness series. I will describe how sleep works, what constitutes normal sleep, sleep hygiene, tips for shiftworkers, and how to recognize sleep disorders.
Satellite aerosol products such as the Dark Target (DT) produced from the MODerate resolution Imaging Spectroradiometer (MODIS) are useful for monitoring the progress of air pollution. Unfortunately, the DT often fails to retrieve during the heaviest aerosol events as well as the more moderate events in winter. Some of the literature at-tributes this lack of retrieval to the cloud mask. However, we found this lack of retrieval is mainly traced to thresholds used for masking of inland water and snow. Modifications to these two masks greatly increase 50 % of the retrievals of aerosol optical depth at 0.55 μm (AOD) greater than 1.0. The “extra”-high-AOD retrievals tend to be biased when com-pared with a ground-based sun photometer (AErosol RObotic NETwork, AERONET). Reducing bias in new retrievals re-quires two additional steps. One is an update to the assumed aerosol optical properties (aerosol model); the haze in this region is both less absorbing and lower in altitude than what is assumed in the global algorithm. The second is account-ing for the scale height of the aerosol, specifically that the heavy-aerosol events in the region are much closer to the surface than what is assumed by the global DT algorithm. The resulting combination of modified masking thresholds, new aerosol model, and lower aerosol layer scale height was applied to 3 months of MODIS observations (January–March2013) over eastern China. After these two additional steps are implemented, the significant increase in new retrievals introduces no overall bias at a high-AOD regime but does degrade other overall validation statistics. We also find that the research algorithm is able to identify additional pollution events that AERONET instruments may not due to different spatial sampling. Mean AOD retrieved from the re-search algorithm increases from 0.11 to 0.18 compared to values calculated from the operational DT algorithm during January to March of 2013 over the study area. But near Beijing, where the severe pollution occurs, the new algorithm increases AOD by as much as 3.0 for each 0.5°grid box over the previous operational-algorithm values.
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Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of ML models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based modeling of material behavior at various length scales and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using ML techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus, effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train ML models and the defining model parameters and architectures within the Granta MI Platform. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in the prediction of material behavior, while following outlined best practices for effective data management. An effective schema for ML data and models can help prevent the recreation of virtual/real training data and surrogate models, help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.
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As NASA prepares to send astronauts on deep space missions, understanding the detrimental effects of spaceflight on the body is imperative. Spaceflight is known to negatively affect the spine, with astronauts experiencing systemic bone loss and increased post-flight risk of intervertebral disc herniation. Space investigations with rodent models have characterized some of the effects of spaceflight on the mammalian body, but variable experimental conditions have made it difficult to cohesively interpret results. These conditions include housing, flight duration, and for the spine, anatomical location. Thus, the objective of this study was to comprehensively characterize the effects of spaceflight on the bulk properties of the murine lumbar spine. To do this, we examined the lumbar spine of mice flown on the NASA Rodent Research 10 mission and analyzed disc biochemical content, disc joint material properties, lumbar vertebral body microarchitecture, and proximal tibia microarchitecture. Finally, we qualitatively examined bone growth in the vertebral bodies using confocal microscopy and on-orbit injections of calcein. Contrary to prior results, we found little to no effect of spaceflight on lumbar spine properties. Spaceflight, however, did negatively affect both cortical and trabecular bone properties of the proximal tibia load-bearing site. We hypothesize that this may be due to loading associated with increased physical activity in the second half of the mission, observed on in-flight videos, that reload the lumbar spine as mice utilize quadruped ambulation. This increased activity occurs after an initial period of relative inactivity in microgravity. In support of this hypothesis, we observed new L5 bone formation in the last seven days of spaceflight, suggesting that current 30-day experimental flight conditions may not be as effective at lumbar spine unloading as previous shorter flights.
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Motion sickness represents one of the greatest clinical challenges impacting crew activities during and following g-transitions. Our overall goal is to characterize the effectiveness of motion sickness countermeasures during controlled laboratory experiments using capsule wave motion simulation and during field testing in operational environments. This laboratory study focused on prevention of motion sickness using intranasal scopolamine using a double-blinded repeated measures design in 30 subjects (19M, 11F). Intranasal scopolamine was provided by Defender Pharmaceuticals, Inc. (DPI-386 Nasal Gel, referred to as Inscop) self-administered by a nasal pump (Aptar Pharma) that delivers 0.4 mg dose (0.2 mg / nostril). During each session, subjects were exposed to complex wave motion on a six degree-of-freedom platform that included pitch, roll and heave at provocative stimulus frequencies (0.1-0.25 Hz) while seated in an illuminated cabin deprived of external visual cues. Motion sickness symptoms were compared across treatment and placebo control sessions counterbalanced across subjects and separated by at least one week. The time-to-motion sickness endpoint was based on severe malaise, defined as symptom score of ≥8 points using the Pensacola Diagnostic Index [1]. The bioavailability of scopolamine for each session was estimated from plasma concentrations obtained every 15 min[2]. Side effects during the treatment session were minimal, and performance was not impaired on a test battery including motion perception tracking, tablet-based eye-hand coordination and psychomotor vigilance testing. The plasma concentration remained near-peak levels throughout the 45 min motion sickness testing for most subjects. The percentile ranking on the Motion Sickness Susceptibility Questionnaire [MSSQ, 3]was moderately correlated with the motion sickness time-to-endpoint during the placebo control session (rho = –0.3, p=0.056). Seventeen subjects did not reach an endpoint during their placebo session and were eliminated from subsequent analysis. Another subject was excluded due to insufficient plasma concentration during the treatment session. For the remaining 12 subjects, the change in time-to-motion sickness endpoint between placebo and treatment sessions was moderately correlated with plasma concentration (rho =0.48, p = 0.056), improving on average 4.4 ± 18.4 min, mean ± std with Inscop versus placebo. Our results are consistent with previous findings that intranasal delivery of scopolamine can be effective at reducing motion sickness symptoms with minimal cognitive or sedative side effects. Future work is needed to optimize the delivery of Inscop for rescue (treatment) of symptoms following g-transitions as one of the key advantages of this formulation is self-administration in a suited environment. We will also explore how the combination of Inscop with non-pharmaceutical sensory aids, e.g., vibrotactile feedback of Earth vertical, may further mitigate motion sickness and improve task performance.
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Lightning is a natural hazard, an indicator of changes in convective storm behavior across multiple spatial and temporal scales, and a major influence on climate-affecting chemicals such as ozone and methane. Lightning also has substantial impacts on the near-space environment. As such, the World Meteorological Organization (WMO) has designated lightning as an Essential Climate Variable (ECV); that is, a measurement that is really important for understanding Earth’s climate. Spaceborne lightning observations are the gold standard for measuring global lightning, as the detection efficiency is more spatially uniform compared to ground-based lightning measurements. In addition, spaceborne is the only practical method for measuring total lightning (i.e., both intracloud and cloud-to-ground) at the global scale, as ground-based networks have limited ability to detect intracloud lightning at long distances (e.g., over oceans, far from land-based sensors). Since 1995, with only a two-year gap (2015-2017), lightning has been observed globally using a combination of Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) instruments. However, the year 2023 is the planned end for the International Space Station (ISS) LIS mission, and there is no designated low-Earth orbit (LEO) successor yet identified. Since 2017, geostationary (GEO) observations of lightning have become increasingly available. These include the U.S. Geostationary Lightning Mappers (GLMs), China’s Lightning Mapping Imager (LMI), and Europe’s Lightning Imager (LI). While GEO provides continuous, quasi-hemispheric coverage of lightning and thunderstorms, there are current gaps preventing global coverage, particularly in portions of Asia and the western Pacific, as well as high-latitude regions. Moreover, integration of the GEO constellation into a Climate Data Record (CDR) of lightning is a major challenge only recently begun to be addressed by the WMO. Furthermore, recent work has demonstrated some deficiencies in the global record of lightning from space. For example, small lightning flashes are very common in severe weather, but are difficult to observe using the present set of spaceborne lightning imagers. Moreover, some types of lightning are best observed using frequencies other than the commonly used near-infrared (777-nm), including ultraviolet and the radio spectrum. Finally, it is not possible to assess the vertical distribution of lightning globally, even though this measurement is highly relevant to thunderstorm behavior as well as lightning’s effects on greenhouse gases and the near-space environment. This presentation will provide a current assessment of lightning measurements from space, will identify significant current and future gaps in these observations, and will evaluate potential solutions for improving the overall CDR of global lightning.
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