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At least 1,261 records · Page 70

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗

Mercury Toolset for Spatiotemporal Metadata

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

Wilson, Bruce E.↗

Accuracy and adaptation of reaching and pointing in pitched visual environments

Visually perceived eye level (VPEL) and the ability of subjects to reach with an unseen limb to targets placed at VPEL were measured in a statically pitched visual surround (pitchroom). VPEL was shifted upward and downward by upward and downward room pitch, respectively. Accuracy in reaching to VPEL represented a compromise between VPEL and actual eye level. This indicates that VPEL shifts reflect in part a change in perceived location of objects. When subjects were provided with terminal visual feedback about their reaching, accuracy improved rapidly. Subsequent reaching, with the room vertical, revealed a negative aftereffect (i.e., reaching errors that were opposite those made initially in the pitched room). In a second study, pointing accuracy was assessed for targets located both at VPEL and at other positions. Errors were similar for targets whether located at VPEL or elsewhere. Additionally, pointing responses were restricted to a narrower range than that of the actual target locations. The small size of reaching and pointing errors in both studies suggests that factors other than a change in perceived location are also involved in VPEL shifts.

NASA Center ARC↗

Spacesuit and Mobility Performance Changes

The complex interactions between the human body and spacesuit lead to changes inmovement patterns and mobility performancesof the wearer. In general, factors including the geometric properties, such as shape and size, mechanical properties of the suit, and pressurization of the suit are known to be associated with altered movement patterns as compared to an unsuited human.However, their relative contributions have not been explicitly quantified from the mobility performance perspectives. The goal of this study wasthus to assessthe effects fromthe different types of mobility constraintconditions, namely by wearing either a 3D printed hard upper torso (HUT) assembly orfully pressurized spacesuit. The outcome was also compared against the unsuited motions. For this study, an xEMU (exploration Extravehicular Mobility Unit) suitwas considered, which is the next generation spacesuit developed by NASA. In each test condition, the subject was asked to move the arm and hand as prescribedfor different task types, and the corresponding body segment locations were recordedusing a 3D motion capture system. The following three tasks were performedand analyzed: 1) Outward one-handed reaches:the subject in a standing pose made sweeping motions with the extended right arm from the extreme end-to-end positions, including side-to-side at different elevations and top-to-bottom at different azimuths. 2) Outward two-handed reaches:similarto the previous task, howeverthe subject kept the hands together during the motions in order to assessthe areas that can be reached by both hands. 3) Inward one-handed reaches:the subject made right-hand reach motions to the surface of the HUT.The hand traces collected from each task were modeled by a template shape parametrically deformed with a radial basis function. This process enabled foran abstraction of the hand traces into a smooth surface envelope representing the maximally reachable area of the test subject, of which the shapes and sizes were compared across the different test conditions. The preliminary analysis has shown that theoverall size of reachenvelopes decreases in a pressurized suit compared to 3D printed mockup HUT and unsuited conditions. The specific shape of the envelopes, which were determined by the reachable and unreachable zones, alsovary with the testconditions, and the differences werepronounced with the inward reaches to the HUT surface. The latter observation ispotentially relatedto the increased demandfor shoulder and elbow flexions.Overcomingthe resistance from the pressurizedsoft goods and mechanical constraints of the shoulder assemblywas seen to be associated with the difference in motion patterns between the suited and unsuited conditions. Overall, the information quantified from this study is expected to provide structured metrics for spacesuit mobility, which can improve design optimization and human-system integration.

K Han Kim↗

Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.

54 ENVIRONMENTAL SCIENCES↗

Ares V and Future Very Large Launch Vehicles to Enable Major Astronomical Missions

The current NASA architecture intended to return humans to the lunar surface includes the Ares V cargo launch vehicle, which is planned to be available within a decade. The capabilities designed for Ares V would permit an 8.8-m diameter, 55 mT payload to be carried to Sun-Earth L1,2 locations. That is, this vehicle could launch very large optical systems to achieve major scientific goals that would otherwise be very difficult. For example, an 8-m monolith UV/visual/IR telescope appears able to be launched to a Sun-Earth L2 location. Even larger apertures that are deployed or assembled seem possible. Alternatively, multiple elements of a spatial array or two or three astronomical observatories might be launched simultaneously. Over the years, scientists and engineers have been evaluating concepts for astronomical observatories that use future large launch vehicles. In this presentation, we report on results of a recent workshop held at NASA Ames Research Center that have improved understanding of the science goals that can be achieved using Ares V. While such a vehicle uniquely enables few of the observatory concepts considered at the workshop, most have a baseline mission that can be flown on existing or near-future vehicles. However, the performance of the Ares V permits design concepts (e.g., large monolithic mirrors) that reduce complexity and risk.

Thronson, Harley A.↗

Key Considerations in Assessing the Safety and Performance of Camera-Based Mirror Systems

Camera-based mirror systems (CBMSs) are a relatively new technology in the automotive industry, and much of the United States’ medium- and heavy-duty commercial fleet has been reluctant to convert from standard glass, or “west coast”, mirrors to CBMSs. CBMSs have the potential to reduce the number of truck and passenger vehicle incidents, improving overall fleet safety. CBMSs also have the potential to improve operational efficiency by improving aerodynamics and reducing drag, resulting in better fuel economy, and improving maneuverability. Improvements in overall safety are also possible; the field of view for the driver is potentially 360° with the addition of trailer cameras, allowing for visibility of the rear of the trailer and the front of the truck. These potential improvements seem promising, but the literature on driver surveys clearly shows that there is reluctance to adopt this technology for many reasons. Additionally, more robust testing in the laboratory and in the field is necessary to determine whether CBMSs are adequate to replace standard mirrors on trucks. This analysis provides an overview of key research questions for CBMS testing based on the current literature on the topic (surveys, standards, and previous testing). The purpose of this analysis is to serve as guidance in developing further testing of CBMSs, especially testing involving human subjects.

99 GENERAL AND MISCELLANEOUS↗

Implementation and Evaluation of Emission‐Driven Land‐Atmosphere Coupled Simulation in E3SMv2.1

Emissions-driven (prognostic CO 2 ) simulations are essential for representing two-way carbon-climate feedback in Earth System Models. We present an emissions-driven land–atmosphere coupled biogeochemistry (BGC) configuration (BGCLNDATM_progCO2) in version 2.1 of the Energy Exascale Earth System Model (E3SMv2.1). This is the first E3SM configuration that performs land-atmosphere emission-hindcasts. Here, we document its implementation, evaluate the model's performance against observations and other models, and propose a structured evaluation protocol for such emissions-driven simulations. We conducted transient historical simulations (1850–2014) with BGCLNDATM_progCO2 and compare them to reference simulations—a land-atmosphere coupled simulation without BGC and a standalone land simulation with BGC, both using prescribed CO 2 concentrations—and to observations. BGCLNDATM_progCO2 overestimates atmospheric CO 2 concentrations by 11–23 ppm yet stays within the 40-ppm spread CMIP6 emission-driven models and retains physical climate properties comparable to the reference runs. The CO 2 biases are partly attributed to underrepresented oceanic CO 2 uptake and inadequate representations of some terrestrial processes. In general, introducing prognostic CO 2 did not change physical climate metrics at the global scale but had larger regional effects, particularly over land where spatially heterogeneous CO 2 and prognostic leaf area index influenced surface energy balance. Finally, we propose a general evaluation protocol including spin-up assessment, atmospheric CO 2 benchmarking, physical climate evaluation, and land biogeochemical analysis to support scientific rigor and facilitate inter-model comparisons. The new configuration lays the groundwork for future enhancements, including improved terrestrial biogeochemical processes, integrated marine biogeochemistry, and additional human–Earth system interactions. These developments advance E3SM toward fully coupled emissions-driven simulations, enabling more accurate carbon–climate feedback projections and informing mitigation policy by providing physically consistent carbon-budget metrics for mitigation scenarios.

54 ENVIRONMENTAL SCIENCES↗

Extraction-Separation Performance and Dynamic Modeling of Orion Test Vehicles with Adams Simulation: 2nd Edition

NASA's Orion Capsule Parachute Assembly System (CPAS) project has advanced into the third generation of its parachute test campaign and requires technically comprehensive modeling capabilities to simulate multi-body dynamics (MBD) of test articles released from a C-17. Safely extracting a 30,000 lbm mated test article from a C-17 and performing stable mid-air separation maneuvers requires an understanding of the interaction between elements in the test configuration and how they are influenced by extraction parachute performance, aircraft dynamics, aerodynamics, separation dynamics, and kinetic energy experienced by the system. During the real-time extraction and deployment sequences, these influences can be highly unsteady and difficult to bound. An avionics logic window based on time, pitch, and pitch rate is used to account for these effects and target a favorable separation state in real time. The Adams simulation has been employed to fine-tune this window, as well as predict and reconstruct the coupled dynamics of the Parachute Test Vehicle (PTV) and Cradle Platform Separation System (CPSS) from aircraft extraction through the mid-air separation event. The test-technique for the extraction of CPAS test articles has evolved with increased complexity and requires new modeling concepts to ensure the test article is delivered to a stable test condition for the programmer phase. Prompted by unexpected dynamics and hardware malfunctions in drop tests, these modeling improvements provide a more accurate loads prediction by incorporating a spring-damper line-model derived from the material properties. The qualification phase of CPAS testing is on the horizon and modeling increasingly complex test-techniques with Adams is vital to successfully qualify the Orion parachute system for human spaceflight.

Fraire, Usbaldo, Jr.↗

Integrated Demand Management: Minimizing Unanticipated Excessive Departure Delay while Ensuring Fairness from a Traffic Management Initiative

This paper introduces NASA's Integrated Demand Management (IDM) concept and presents the results from an early proof-of-concept evaluation and an exploratory experiment. An initial development of the concept was focused on integrating two systems - i.e. the FAA's newly deployed Traffic Flow Management System (TFMS) tool called the Collaborative Trajectory Options Program (CTOP) and the Time-Based Flow Management (TBFM) system with Extended Metering (XM) capabilities to manage projected heavy traffic demand into a capacity-constrained airport. A human-in-the-loop (HITL) simulation experiment was conducted to demonstrate the feasibility of the initial development of the concept by adapting it to an arrival traffic problem at Newark Liberty International Airport (EWR) during clear weather conditions. In this study, the CTOP was utilized to strategically plan the arrival traffic demand by controlling take-off times of both short- and long-haul flights (long-hauls specify aircraft outside TBFM regions and short-hauls specify aircraft within TBFM regions) in a way that results in equitable delays among the groups. Such strategic planning allows less airborne delay to occur within TBFM by feeding manageable long-haul traffic demand while reserving sufficient slots in the overhead streams for the short-haul departures. The manageable traffic demand indicates the TBFM scheduler assigns no more airborne delay than its assigned airspace is capable of absorbing. TBFM then uses its time-based metering capabilities to deliver the desirable throughput by tactically rescheduling the TBFM entered long-haul flights and short-haul departures. Additional research was also performed to explore use of Required Time of Arrival (RTA) capabilities as a potential control mechanism for the airborne flights to improve arrival traffic delivery accuracy of scheduled long-haul traffic demand. The study results show that both short- and long-haul flights received similar ground delays. In addition, there was a noticeable reduction in the total amount of excessive unanticipated last-minute ground delays, i.e. delays that are frequently imposed on the short-haul flight in current day operations due to saturation in the overhead stream, commonly referred to as 'double penalty'. Furthermore, the concept achieved the target throughput while minimizing the expected cost associated with overall delays in arrival traffic. Assessment of the RTA capabilities showed that there was indeed improvement of the scheduled entry times into TBFM regions by using RTA capabilities. However, with respect to reduction in delays incurred within TBFM, there was no observable benefit of improving the precision of long-haul flights entry times.

Collaborative Trajectory Options Program (CTOP)↗

Application of Synthetic Biology to Bioregenerative Life Support for Human Spaceflight

The conversion of carbon dioxide into higher value products is a key challenge for the development of closed-loop life support systems for human space flight. Much of the past research on bioregenerative life support systems has focused on plant growth chambers as a solution for CO2 removal and O2 generation, but photosynthetic microorganisms may also have a role to play in these functions. Cyanobacteria have the advantages of relatively high CO2 fixation rates and fairly well-developed molecular biology tools, allowing for genetic engineering approaches to strain improvement. Manned missions to Mars or other targets beyond low Earth orbit will require advances in the nutritional systems for life support on these longer duration missions. A key challenge will likely be supplementing pre-packaged meals with specific nutrients that will be deficient due to problems in long-term storage or low abundance. Vitamin K is one such nutrient that may be important as a supplement. Production of vitamin K for nutrient supplementation during spaceflight will likely require genetic engineering of microorganisms to increase vitamin titers. A microbial bioreactor system that could efficiently convert CO2 to nutritional supplements would be a valuable component for a future advanced life support system. We are exploring biological systems to determine the feasibility of using bioreactors to convert CO2 to higher-value products. We are examining the performance of photosynthetic bacteria engineered to produce sugars, determining rates of production and reliability. We are also engineering microbes to produce higher titers of vitamin K and other potentially important nutrients. The results of this research will offer demonstrations of potential technologies that could be developed further in the future. This work will also provide valuable information for understanding basic science questions about the use of genetically engineered microbes in the microgravity environment.

Bioregenerative life support↗

Estimating biotic integrity to capture existence value of freshwater ecosystems

The US Environmental Protection Agency (EPA) uses a water quality index (WQI) to estimate benefits of proposed Clean Water Act regulations. The WQI is relevant to human use value, such as recreation, but may not fully capture aspects of nonuse value, such as existence value. Here, we identify an index of biological integrity to supplement the WQI in a forthcoming national stated preference survey that seeks to capture existence value of streams and lakes more accurately within the conterminous United States (CONUS). We used literature and focus group research to evaluate aquatic indices regularly reported by the EPA’s National Aquatic Resource Surveys. We chose an index that quantifies loss in biodiversity as the observed-to-expected (O/E) ratio of taxonomic composition because focus group participants easily understood its meaning and the environmental changes that would result in incremental improvements. However, available datasets of this index do not provide the spatial coverage to account for how conditions near survey respondents affect their willingness to pay for its improvement. Therefore, we modeled and interpolated the values of this index from sampled sites to 1.1 million stream segments and 297,071 lakes across the CONUS to provide the required coverage. The models explained 13 to 36% of the variation in O/E scores and demonstrate how modeling can provide data at the required density for benefits estimation. We close by discussing future work to improve performance of the models and to link biological condition with water quality and habitat models that will allow us to forecast changes resulting from regulatory options.

59 BASIC BIOLOGICAL SCIENCES↗

Goal-directed ultrasound in the detection of long-bone fractures

BACKGROUND: New portable ultrasound (US) systems are capable of detecting fractures in the remote setting. However, the accuracy of ultrasound by physicians with minimal ultrasound training is unknown. METHODS: After one hour of standardized training, physicians with minimal US experience clinically evaluated patients presenting with pain and trauma to the upper arm or leg. The investigators then performed a long-bone US evaluation, recording their impression of fracture presence or absence. Results of the examination were compared with routine plain or computer aided radiography (CT). RESULTS: 58 patients were examined. The sensitivity and specificity of US were 92.9% and 83.3%, and of the physical examination were 78.6% and 90.0%, respectively. US provided improved sensitivity with less specificity compared with physical examination in the detection of fractures in long bones. CONCLUSION: Ultrasound scans by minimally trained clinicians may be used to rule out a long-bone fracture in patients with a medium to low probability of fracture.

Validation Studies↗

UAS Integration Into the NAS: An Examination of Baseline Compliance in the Current Airspace System

As a result of the FAA Modernization and Reform Act of 2012, Unmanned Aerial Systems (UAS) are expected to be integrated into the National Airspace System (NAS) by 2015. Several human factors challenges need to be addressed before UAS can safely and routinely fly in the NAS with manned aircraft. Perhaps the most significant challenge is for the UAS to be non-disruptive to the air traffic management system. Another human factors challenge is how to provide UAS pilots with intuitive traffic information in order to support situation awareness (SA) of their airspace environment as well as a see-and-avoid capability comparable to manned aircraft so that a UAS pilot could safely maneuver the aircraft to maintain separation and collision avoidance if necessary. A simulation experiment was conducted to examine baseline compliance of UAS operations in the current airspace system. Researchers also examined the effects of introducing a Cockpit Situation Display (CSD) into a UAS Ground Control Station (GCS) on UAS pilot performance, workload and situation awareness while flying in a positively controlled sector. Pilots were tasked with conducting a highway patrol police mission with a Medium Altitude Long Endurance (MALE) UAS in L.A. Center airspace with two mission objectives: 1) to reroute the UAS when issued new instructions from their commander, and 2) to communicate with Air Traffic Control (ATC) to negotiate flight plan changes and respond to vectoring and altitude change instructions. Objective aircraft separation data, workload ratings, SA data, and subjective ratings regarding UAS operations in the NAS were collected. Results indicate that UAS pilots were able to comply appropriately with ATC instructions. In addition, the introduction of the CSD improved pilot SA and reduced workload associated with UAS and ATC interactions.

Fern, Lisa↗

Testing the Exploration ConOps (ExCon) Mockup Suit in Lunar Analog Environments in 2022

Understanding how to effectively train for Extravehicular Activities (EVAs) for Artemis missions is critical. Developing high-fidelity simulation environments is important for Artemis mission preparation. Because the actual Lunar exploration environment cannot be fully replicated on Earth, it is paramount to determine where and how to properly train the Artemis team. The overall focus for this test series was developing the capability to perform Artemis simulated EVAs in high-fidelity, full-scale environments. This test series was broken into three distinct tests titled after the EVA & Human Surface Mobility (HSM) Program (EHP) integrated test team: Joint EVA & HSM Test Team (JETT). The test locations are planned to serve as Artemis training sites and were selected because of their relevance to the expected Artemis Lunar terrain. JETT1 was conducted near Kilbourne Hole by El Paso, Texas and focused on hardware development and checkout. JETT2 was conducted in the Icelandic Highlands and began the transition towards EVA concept of operations (con-ops), risks and technology. JETT3 was conducted near SP Crater by Flagstaff, Arizona and focused on simulating the Artemis III mission including a Houston based Flight Control Team (FCT) and a Science Mission Directorate (SMD) science team. All three JETT tests utilized the Exploration Concept of Operations (ExCon) mockup space suit. The ExCon mockup suit is a lightweight, unpressurized Exploration Extravehicular Mobility Unit (xEMU) simulator. While it cannot replicate the feel of working within a pressurized suit, it does introduce similar volume constraints and some of the mobility programing to simulate the user experience in the xEMU. Overall, the JETT testing was able to create a simulated Lunar EVA and have two subjects perform full scale operations in line with Artemis III mission expectations. Future work is planned to continue to improve the simulation quality of Lunar EVA simulations.

spacesuit↗

Testing the Exploration Conops (Excon) Mockup Suit in Lunar Analog Environments in 2022

Understanding how to effectively train for Extravehicular Activities (EVAs) for Artemis missions is critical. Developing high-fidelity simulation environments is important for Artemis mission preparation. Because the actual Lunar exploration environment cannot be fully replicated on Earth, it is paramount to determine where and how to properly train the Artemis team. The overall focus for this test series was developing the capability to perform Artemis simulated EVAs in high-fidelity, full-scale environments. This test series was broken into three distinct tests titled after the EVA & Human Surface Mobility (HSM) Program (EHP) integrated test team: Joint EVA & HSM Test Team (JETT). The test locations are planned to serve as Artemis training sites and were selected because of their relevance to the expected Artemis Lunar terrain. JETT1 was conducted near Kilbourne Hole by El Paso, Texas and focused on hardware development and checkout. JETT2 was conducted in the Icelandic Highlands and began the transition towards EVA concept of operations (con-ops), risks and technology. JETT3 was conducted near SP Crater by Flagstaff, Arizona and focused on simulating the Artemis III mission including a Houston based Flight Control Team (FCT) and a Science Mission Directorate (SMD) science team. All three JETT tests utilized the Exploration Concept of Operations (ExCon) mockup space suit. The ExCon mockup suit is a lightweight, unpressurized Exploration Extravehicular Mobility Unit (xEMU) simulator. While it cannot replicate the feel of working within a pressurized suit, it does introduce similar volume constraints and some of the mobility programing to simulate the user experience in the xEMU. Overall, the JETT testing was able to create a simulated Lunar EVA and have two subjects perform full scale operations in line with Artemis III mission expectations. Future work is planned to continue to improve the simulation quality of Lunar EVA simulations.

spacesuit↗

Improved quality metrics for association and reproducibility in chromatin accessibility data using mutual information

Correlation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility. Using these simulations, we monitored the behavior of several correlation statistics, including the Pearson’s R and Spearman’s ρ coefficients as well as Kendall’s τ and Top–Down correlation. We also test the behavior of association measures, including the coefficient of determination R 2 , Kendall’s W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spear man’s ρ, Kendall’s τ, and Kendall’s W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, the R 2 coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships. Collectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.

59 BASIC BIOLOGICAL SCIENCES↗

Application of Vacuum Swing Adsorption for Carbon Dioxide and Water Vapor Removal from Manned Spacecraft Atmospheres

In NASA's Vision for Space Exploration (Bush, 2004), (Griffin, 2007), humans will once again travel beyond the confines of earth's gravity, this time to remain there for extended periods. These forays will place unprecedented demands on launch systems. They must not only blast out of earth's gravity well as during the Apollo moon missions, but also liftoff the supplies needed to sustain a larger crew over much longer periods. Thus all spacecraft systems, including those for the separation of metabolic carbon dioxide and water from a crewed vehicle, must be minimized with respect to mass, power, and volume. Emphasis is also placed on system robustness both to minimize replacement parts and ensure crew safety when a quick return to earth is not possible. For short-term phases of manned space exploration, such as transit from the earth to the moon, venting of metabolic carbon dioxide and water to space is more efficient than the inclusion of large recycling systems on the spacecraft. The baseline system for the Orion spacecraft is an amine-based vacuum swing system (Smith, Perry et aI., 2006). As part of the development of an alternative approach, a sorbent-based CO2 and H2O removal system (Knox, Adams et aI., 2006), subscale testing was conducted to evaluate potential performance improvements obtainable by recuperating the heat of adsorption to aid in vacuum desorption. This bed design is shown in Figure 1, is depicted here with a lattice structure instead of reticulated foam for heat transfer. The slot widths are approximately 1.2 mm wide and 8.5 mm long. Bed depth is approximately 4.7 mm. Headers (not shown) were produced by the stereo lithography apparatus at MSFC.

Knox, J.↗