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At least 1,099 records · Page 61

Intercultural crew issues in long-duration spaceflight

Before long-duration flights with international crews can be safely undertaken, potential interpersonal difficulties will need to be addressed. Crew performance breakdown has been recognized by the American Institute of Medicine, in scientific literature, and in popular culture. However, few studies of human interaction and performance in confined, isolated environments exist, and the data pertaining to those studies are mostly anecdotal. Many incidents involving crew interpersonal dynamics, those among flight crews, as well as between flight crews and ground controllers, are reported only in non-peer reviewed books and newspapers. Consequently, due to this lack of concrete knowledge, the selection of astronauts and cosmonauts has focused on individual rather than group selection. Additional selection criteria such as interpersonal and communication competence, along with intercultural training, will have a decisive impact on future mission success. Furthermore, industrial psychological research has demonstrated the ability to select a group based on compatibility. With all this in mind, it is essential to conduct further research on heterogeneous, multi-national crews including selection and training for long-duration space missions.

long duration↗

Assessing Climate Change Impacts on the Stability of Small Tidal Inlets: Part 2- Data Rich Environments

Climate change (CC) is likely to affect the thousands of bar-built or barrier estuaries (here referred to as Small tidal inlets - STIs) around the world. Any such CC impacts on the stability of STIs, which governs the dynamics of STIs as well as that of the inlet-adjacent coastline, can result in significant socio-economic consequences due to the heavy human utilisation of these systems and their surrounds. This article demonstrates the application of a process based snap-shot modelling approach, using the coastal morphodynamic model Delft3D, to 3 case study sites representing the 3 main STI types; Permanently open, locationally stable inlets (Type 1), Permanently open, alongshore migrating inlets (Type 2) and Seasonally/Intermittently open, locationally stable inlets (Type 3). The 3 case study sites (Negombo lagoon - Type 1, Kalutara lagoon - Type 2, and Maha Oya river - Type 3) are all located along the southwest coast of Sri Lanka. After successful hydrodynamic and morphodynamic model validation at the 3 case study sites, CC impact assessment are undertaken for a high end greenhouse gas emission scenario. Future CC modified wave and riverflow conditions are derived from a regional scale application of spectral wave models (WaveWatch III and SWAN) and catchment scale applications of a hydrologic model (CLSM) respectively, both of which are forced with IPCC Global Climate Model output dynamically downscaled to approximately 50 km resolution over the study area with the stretched grid Conformal Cubic Atmospheric Model CCAM. Results show that while all 3 case study STIs will experience significant CC driven variations in their level of stability, none of them will change Type by the year 2100. Specifically, the level of stability of the Type 1 inlet will decrease from 'Good' to 'Fair to poor' by 2100, while the level of (locational) stability of the Type 2 inlet will also decrease with a doubling of the annual migration distance. Conversely, the stability of the Type 3 inlet will increase, with the time till inlet closure increasing by approximately 75%. The main contributor to the overall CC effect on the stability of all 3 STIs is CC driven variations in wave conditions and resulting changes in longshore sediment transport, not Sea level rise as commonly believed.

IPC↗

Multiscale embedded printing of engineered human tissue and organ equivalents

Creating tissue and organ equivalents with intricate architectures and multiscale functional feature sizes is the first step toward the reconstruction of transplantable human tissues and organs. Existing embedded ink writing approaches are limited by achievable feature sizes ranging from hundreds of microns to tens of millimeters, which hinders their ability to accurately duplicate structures found in various human tissues and organs. In this study, a multiscale embedded printing (MSEP) strategy is developed, in which a stimuli-responsive yield-stress fluid is applied to facilitate the printing process. A dynamic layer height control method is developed to print the cornea with a smooth surface on the order of microns, which can effectively overcome the layered morphology in conventional extrusion-based three-dimensional bioprinting methods. Since the support bath is sensitive to temperature change, it can be easily removed after printing by tuning the ambient temperature, which facilitates the fabrication of human eyeballs with optic nerves and aortic heart valves with overhanging leaflets on the order of a few millimeters. The thermosensitivity of the support bath also enables the reconstruction of the full-scale human heart on the order of tens of centimeters by on-demand adding support bath materials during printing. Here, the proposed MSEP demonstrates broader printable functional feature sizes ranging from microns to centimeters, providing a viable and reliable technical solution for tissue and organ printing in the future.

3D bioprinting↗

Uncertainty-informed selection of CMIP6 Earth System Model subsets for use in multisectoral and impact models

Earth system models (ESMs) and general circulation models (GCMs) are heavily used to provide inputs to sectoral impact and multisector dynamic models, which include representations of energy, water, land, economics, and their interactions. Therefore, representing the full range of model uncertainty, scenario uncertainty, and interannual variability that ensembles of these models capture is critical to the exploration of the future co-evolution of the integrated human–Earth system. The pre-eminent source of these ensembles has been the Coupled Model Intercomparison Project (CMIP). With more modeling centers participating in each new CMIP phase, the size of the model archive is rapidly increasing, which can be intractable for impact modelers to effectively utilize due to computational constraints and the challenges of analyzing large datasets. In this work, we present a method to select a subset of the latest phase, CMIP6, featuring models for use as inputs to a sectoral impact or multisector dynamics models, while prioritizing preservation of the range of model uncertainty, scenario uncertainty, and interannual variability in the full CMIP6 ensemble results. This method is intended to help impact modelers select climate information from the CMIP archive efficiently for use in downstream models that require global coverage of climate information. This is particularly critical for large-ensemble experiments of multisector dynamic models that may be varying additional features beyond climate inputs in a factorial design, thus putting constraints on the number of climate simulations that can be used. We focus on temperature and precipitation outputs of CMIP6 models, as these are two of the most used variables among impact models, and many other key input variables for impacts are at least correlated with one or both of temperature and precipitation (e.g., relative humidity). Besides preserving the multi-model ensemble variance characteristics, we prioritize selecting CMIP6 models in the subset that preserve the very likely distribution of equilibrium climate sensitivity values as assessed by the latest Intergovernmental Panel on Climate Change (IPCC) report. This approach could be applied to other output variables of climate models and, possibly when combined with emulators, offers a flexible framework for designing more efficient experiments on human-relevant climate impacts. It can also provide greater insight into the properties of existing CMIP6 models.

Snyder, Abigail C.↗

Lunar Surface Operations Modeling Using Digital Astronaut Simulation

During Apollo, crew members experienced a number of falls while engaging in extravehicular activity. The Digital Astronaut Simulation (DAS) expanded human biomechanics modeling tools to begin investigating this prospective mission safety and success challenge for the Artemis program. A core capability was developed to detect if a motion is dynamically feasible in a given gravitational environment. Fed by motion capture and mass properties data, this technology enables observation of whether tasks performed in 1G can be performed the same way in lunar gravity or if they require modifications.

Long Duration Health↗

Structural Basis for Flip-Flop Action of Thiamin Pyrophosphate-Dependent Enzymes Revealed by Human Pyruvate Dehydrogenase

Thiamin pyrophosphate (TPP), the biologically active form of vitamin BI, is a cofactor of enzymes catalyzing reactions involving the cleavage of a carbon-carbon bond adjacent to an oxo group. TPP-dependent enzymes show a common mechanism of TPP activation by: (1) forming the ionic N-H...O(sup -) hydrogen bonding between the N1' atom of the aminopirymidine ring of the coenzyme and intrinsic gamma-carboxylate group of glutamate and (2) imposing an "active" V-conformation that brings the N4' atom of the aminopirymidine to the distance required for the intramolecular C-H.. .N hydrogen bonding with the thiazolium C2 atom. Within these two hydrogen bonds that rapidly exchange protons, protonation of the N1' atom is strictly coordinated with the deprotonation of the 4' -amino group and eventually abstraction of the proton from C2. The human pyruvate dehydrogenase Elp, component of human pyruvate dehydrogenase complex, catalyzes the irreversible decarboxylation of the pyruvate followed by the reductive acetylation of the lipoyl group of dihydrolipoyl acyltransferase. Elp is alpha(sub 2)beta(sub2)-heterotetrameric with a molecular mass of I54 kDa, which has two catalytic sites, each providing TPP and magnesium ion as cofactors and each formed on the interface between the PP and PYR domains. The dynamic nonequivalence of two otherwise chemically equivalent catalytic sites has been observed and the flip-flop mechanism was suggested, according to which two active sites affect each other and in which different steps of the catalytic reaction are performed in each of the sites at any given moment. Based on specific futures of human pyruvate dehydrogenase including rigid and flexible connections between domains that bind the cofactor we propose a mechanistic model for the flip-flop action of this enzyme. We postulate that the dynamic protein environment drives the exchange of tautomers in the 4' -aminopyrimidine ring of the cofactor through a concerted shuttl-like motion of tightly connected domains. The dynamic exchange of those tautomers, in turns, is required during the reactions of pyruvate decarboxylation and reductive acetylation of lipoamide. Thus the shuttle-like motion of the domains is coordinated with the reactions of decarboxylation and acetylation, which are carried out in each of the cofactor sites resulting in a flip-flop action of the enzyme. The structure-derived mechanism of action of human pyruvate dehydrogenase may be likely common for other TPP-dependent enzymes.

Dominiak, Paulina↗

Reentry Vehicle Flight Controls Design Guidelines: Dynamic Inversion

This report addresses issues in developing a flight control design for vehicles operating across a broad flight regime and with highly nonlinear physical descriptions of motion. Specifically it addresses the need for reentry vehicles that could operate through reentry from space to controlled touchdown on Earth. The latter part of controlled descent is achieved by parachute or paraglider - or by all automatic or a human-controlled landing similar to that of the Orbiter. Since this report addresses the specific needs of human-carrying (not necessarily piloted) reentry vehicles, it deals with highly nonlinear equations of motion, and then-generated control systems must be robust across a very wide range of physics. Thus, this report deals almost exclusively with some form of dynamic inversion (DI). Two vital aspects of control theory - noninteracting control laws and the transformation of nonlinear systems into equivalent linear systems - are embodied in DI. Though there is no doubt that the mathematical tools and underlying theory are widely available, there are open issues as to the practicality of using DI as the only or primary design approach for reentry articles. This report provides a set of guidelines that can be used to determine the practical usefulness of the technique.

Ito, Daigoro↗

Structural insights into the modulation of coronavirus spike tilting and infectivity by hinge glycans

Abstract Coronavirus spike glycoproteins presented on the virion surface mediate receptor binding, and membrane fusion during virus entry and constitute the primary target for vaccine and drug development. How the structure dynamics of the full-length spikes incorporated in viral lipid envelope correlates with the virus infectivity remains poorly understood. Here we present structures and distributions of native spike conformations on vitrified human coronavirus NL63 (HCoV-NL63) virions without chemical fixation by cryogenic electron tomography (cryoET) and subtomogram averaging, along with site-specific glycan composition and occupancy determined by mass spectrometry. The higher oligomannose glycan shield on HCoV-NL63 spikes than on SARS-CoV-2 spikes correlates with stronger immune evasion of HCoV-NL63. Incorporation of cryoET-derived native spike conformations into all-atom molecular dynamic simulations elucidate the conformational landscape of the glycosylated, full-length spike that reveals a role of hinge glycans in modulating spike bending. We show that glycosylation at N1242 at the upper portion of the stalk is responsible for the extensive orientational freedom of the spike crown. Subsequent infectivity assays implicated involvement of N1242-glyan in virus entry. Our results suggest a potential therapeutic target site for HCoV-NL63.

59 BASIC BIOLOGICAL SCIENCES↗

The kinetics of SARS-CoV-2 infection based on a human challenge study

Studying the early events that occur after viral infection in humans is difficult unless one intentionally infects volunteers in a human challenge study. Here, we use data about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in such a study in combination with mathematical modeling to gain insights into the relationship between the amount of virus in the upper respiratory tract and the immune response it generates. We propose a set of dynamic models of increasing complexity to dissect the roles of target cell limitation, innate immunity, and adaptive immunity in determining the observed viral kinetics. We introduce an approach for modeling the effect of humoral immunity that describes a decline in infectious virus after immune activation. We fit our models to viral load and infectious titer data from all the untreated infected participants in the study simultaneously. We found that a power-law with a power h < 1 describes the relationship between infectious virus and viral load. Viral replication at the early stage of infection is rapid, with a doubling time of ~2 h for viral RNA and ~3 h for infectious virus. We estimate that adaptive immunity is initiated ~7 to 10 d postinfection and appears to contribute to a multiphasic viral decline experienced by some participants; the viral rebound experienced by other participants is consistent with a decline in the interferon response. Altogether, we quantified the kinetics of SARS-CoV-2 infection, shedding light on the early dynamics of the virus and the potential role of innate and adaptive immunity in promoting viral decline during infection.

59 BASIC BIOLOGICAL SCIENCES↗

DRAS: Deep Reinforcement Learning for Cluster Scheduling in High Performance Computing

Cluster schedulers are crucial in high-performance computing (HPC). They determine when and which user jobs should be allocated to available system resources. Existing cluster scheduling heuristics are developed by human experts based on their experience with specific HPC systems and workloads. However, the increasing complexity of computing systems and the highly dynamic nature of application workloads have placed tremendous burden on manually designed and tuned scheduling heuristics. More aggressive optimization and automation are needed for cluster scheduling in HPC. In this work, we present an automated HPC scheduling agent named DRAS (Deep Reinforcement Agent for Scheduling) by leveraging deep reinforcement learning. DRAS is built on a hierarchical neural network incorporating special HPC scheduling features such as resource reservation and backfilling. An efficient training strategy is presented to enable DRAS to rapidly learn the target environment. Once being provided a specific scheduling objective given by the system manager, DRAS automatically learns to improve its policy through interaction with the scheduling environment and dynamically adjusts its policy as workload changes. We implement DRAS into a HPC scheduling platform called CQGym. CQGym provides a common platform allowing users to flexibly evaluate DRAS and other scheduling methods such as heuristic and optimization methods. Furthermore, the experiments using CQGym with different production workloads demonstrate that DRAS outperforms the existing heuristic and optimization approaches by up to 50%.

97 MATHEMATICS AND COMPUTING↗

Framework for a Digital Documented Safety Analysis

This framework is developed to progress the digital implementation of digital tools applied to the DOE authorization process, with future applications to NRC SAR development/review, to accelerate the design and review processes of advanced nuclear reactors. The engineering design and licensing process for nuclear reactors is currently burdened by a document-based approach that leads to duplications and errors due to a lack of traceability among numerous static documents. Changes to design information require labor-intensive manual tracing through these documents, creating a high potential for human error. The adoption of a digital ecosystem, utilizing a digital thread to link various aspects of project design and analysis, promises dynamic documentation generation, automatic updates, and error reduction. Model Based Definition (MBD) and Product Lifecycle Management (PLM) tools are central to this digital transformation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Deviations from uniform power law scaling in nonstationary time series

A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.

Non-NASA Center↗

Ares I-X Flight Test Philosophy

In response to the Vision for Space Exploration, the National Aeronautics and Space Administration (NASA) has defined a new space exploration architecture to return humans to the Moon and prepare for human exploration of Mars. One of the first new developments will be the Ares I Crew Launch Vehicle (CLV), which will carry the Orion Crew Exploration Vehicle (CEV), into Low Earth Orbit (LEO) to support International Space Station (ISS) missions and, later, support lunar missions. As part of Ares I development, NASA will perform a series of Ares I flight tests. The tests will provide data that will inform the engineering and design process and verify the flight hardware and software. The data gained from the flight tests will be used to certify the new Ares/Orion vehicle for human space flight. The primary objectives of this first flight test (Ares I-X) are the following: Demonstrate control of a dynamically similar integrated Ares CLV/Orion CEV using Ares CLV ascent control algorithms; Perform an in-flight separation/staging event between an Ares I-similar First Stage and a representative Upper Stage; Demonstrate assembly and recovery of a new Ares CLV-like First Stage element at Kennedy Space Center (KSC); Demonstrate First Stage separation sequencing, and quantify First Stage atmospheric entry dynamics and parachute performance; and Characterize the magnitude of the integrated vehicle roll torque throughout the First Stage (powered) flight. This paper will provide an overview of the Ares I-X flight test process and details of the individual flight tests.

Davis, S. R.↗

An Ad-Hoc Adaptive Pilot Model for Pitch Axis Gross Acquisition Tasks

An ad-hoc algorithm is presented for real-time adaptation of the well-known crossover pilot model and applied to pitch axis gross acquisition tasks in a generic fighter aircraft. Off-line tuning of the crossover model to human pilot data gathered in a fixed-based high fidelity simulation is first accomplished for a series of changes in aircraft dynamics to provide expected values for model parameters. It is shown that in most cases, for this application, the traditional crossover model can be reduced to a gain and a time delay. The ad-hoc adaptive pilot gain algorithm is shown to have desirable convergence properties for most types of changes in aircraft dynamics.

Hanson, Curtis E.↗

SARDA Surface Schedulers

Provide an overview of algorithms used in SARDA (Spot and Runway Departure Advisor) HITL (Human-in-the-Loop) simulation for Dallas Fort-Worth International Airport and Charlotte Douglas International airport. Outline a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the single runway scheduling (SRS) problem, and discuss heuristics to restrict the search space for the DP based algorithm and provide improvements.

runways scheduling↗

Sulfur Biogeochemical Cycling and Redox Dynamics in a Shale-Dominated Mountainous Watershed

Sulfur (S) is an essential macronutrient and important component of the earth’s crust, and its cycling has critical impacts on trace metal mobility, water quality, and human health. Pyrite weathering is the primary pathway by which sulfur enters surface waters. However, biogeochemical cycling of sulfur in soils and the river corridor mediates sulfate exports. In this study, we identified the major forms of sulfur across multiple compartments and scales in a pristine mountainous watershed, including shale bedrock weathering profiles, hillslope soils, and alluvial floodplain sediments, in order to provide insight into biogeochemical sulfur cycling in a hydrologically variable alpine system. X-ray absorption near-edge spectroscopy (XANES) analysis of shale weathering profiles showed clear evidence of pyrite oxidation to sulfate, with large accumulations of intermediate S(0) (20%–53%). Micro-scale XANES showed evidence of reprecipitation of pyrite at fracture surfaces within the permanently saturated zone. Organic sulfur dominated S speciation in shallow hillslope soil and floodplain sediment, with little evidence of reduced inorganic S. However, mackinawite formation, representing active sulfate reduction, was observed in saturated oxbow sediments and saturated weathered shale underlying floodplain sediments. Further evidence of sulfate reduction from aqueous sulfur isotopic analysis was observed in shallow groundwater transects across an Fe-reducing meander, whereas increases in pore water sulfate concentrations implied sulfur oxidation at other locations. Furthermore, the data present an integrated picture of sulfur cycling in a shale-dominated watershed, where riverine sulfate exports are mediated by biological cycling, particularly in redox-stratified and temporally dynamic hyporheic zone sediments.

58 GEOSCIENCES↗

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

NASA Discipline Neuroscience↗

Development of a hydraulic model of the human systemic circulation

Physical and numeric models of the human circulation are constructed for a number of objectives, including studies and training in physiologic control, interpretation of clinical observations, and testing of prosthetic cardiovascular devices. For many of these purposes it is important to quantitatively validate the dynamic response of the models in terms of the input impedance (Z = oscillatory pressure/oscillatory flow). To address this need, the authors developed an improved physical model. Using a computer study, the authors first identified the configuration of lumped parameter elements in a model of the systemic circulation; the result was a good match with human aortic input impedance with a minimum number of elements. Design, construction, and testing of a hydraulic model analogous to the computer model followed. Numeric results showed that a three element model with two resistors and one compliance produced reasonable matching without undue complication. The subsequent analogous hydraulic model included adjustable resistors incorporating a sliding plate to vary the flow area through a porous material and an adjustable compliance consisting of a variable-volume air chamber. The response of the hydraulic model compared favorably with other circulation models.

NASA Program Biomedical Research and Countermeasur↗