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Northern Great Plains Disasters: Using Earth Observations to Enhance Flood Monitoring on Tribal Lands in the Northern Great Plains

In 2019, the Great Plains experienced unprecedented catastrophic flooding. Large flood events are predicted to increase in frequency and severity, posing risks to communities in this region, particularly Tribal Nations. We used data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), imagery from the Sentinel-2 MultiSpectral Instrument (MSI), and digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM) within Google Earth Engine to map historical floods in the region beginning in 2014 with particular attention to the Rosebud Sioux Reservation and the tribal lands of other Great Plains Tribal Water Alliance members. This historical mapping used C-SAR for a combined method approach with a Z-score algorithm in addition to an index for flooded short vegetation. We also developed a flood risk map by weighting different flood predictor variables according to flood risk literature. These variables included soil drainage from the Soil Survey Geographic Database (SSURGO); elevation, slope, and Topographic Wetness Index (TWI) derived from digital elevation models; precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS); land cover from the National Land Cover Database (NLDC); and Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 Operational Land Imager (OLI). From the flood extent and risk maps, we identified widespread flooding in short vegetation (including cropland) and noted flood susceptibility in regions exhibiting high social vulnerability and low community resilience (FEMA indices). We created an ArcGIS Online StoryMap to share project background, results, and data. Additionally, we provided a written tutorial so partners may replicate the flood mapping for future flood events.

Anna Ballasiotes↗

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.

NASA Center LaRC↗

San Francisco Bar Pilot Fatigue Study

The purpose of this study was to evaluate the extent of fatigue among San Francisco Bar Pilots (Maritime Pilots) and its potential impact on safety, and to make recommendations concerning how the risk of fatigue could be managed. Information was gathered via a literature review, observations of Bar Pilots at work, surveys, a task analysis, and an analysis of dispatch records.The work of San Francisco Bar Pilots involves an unusual mix of activities and job demands. Their work calls for situational awareness, reasoning, communication, and perceptual abilities comparable to those required by airline pilots and air traffic controllers. Errors can have severe consequences for public safety and the environment, as well as significant financial costs. Fatigue is increasingly recognized as a hazard that must be managed by the transportation industry. The reduced sleep quality and quantity experienced by personnel who work at night, in conjunction with human circadian rhythms can lead to an operationally significant level of cognitive impairment. The cognitive impact of fatigue includes functions that are critical to safe maritime piloting, such as vigilance, judgment, reaction time and communication. The surveys distributed to Bar Pilots did not uncover evidence of widespread fatigue. The survey results also suggested that fatigue was not a major concern of Bar Pilots. Bar Pilots had overall low scores on the subjective fatigue measures used in the survey, and generally assessed the safety risk due to fatigue as low. Compared to air traffic controllers, Bar Pilots gave significantly lower ratings on questions concerning the prevalence and impact of fatigue. The application of fatigue modeling software to Bar Pilot dispatch records identified that in most cases, pilot's cognitive effectiveness was predicted to be acceptable during their duty periods. However, these results could not be verified with objective data.The study identified a number of fatigue issues that deserve attention. These include Bar Pilot work periods that frequently infringe on the circadian low, consecutive work periods without a significant break, consecutive periods of night work, unpredictable work schedules, start time variability, the potential for sleep inertia, and the number of pilots on the board at any given time.

fatigue↗

LLMs and GenAI Tools to Depict Contributions of Human Systems to Spaceflight Tasks Execution

Recent advancements in Artificial Intelligence and Machine Learning (AI/ML) technologies, particularly Large Language Models (LLMs) capable of sophisticated syntax analysis, offer substantial potential in automating complex processes, thereby saving time and human resources. This study explores the development of an LLM-driven model designed to analyze and categorize a diverse set of Mars mission tasks into 18 predefined Human System Task Categories (HSTCs) based on their textual descriptions. As part of developing the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA projects Performance Risk Model (PRisM) proof-of-concept, we established a framework to project performance scores from small-scale tests onto a preliminary list of Mars tasks. The foundation of our model was a comprehensive spreadsheet populated by NASA experts and clinicians, which detailed each Mars task alongside binary indicators of HSTC involvement. This dataset enabled the initial application of supervised ML, training and testing on existing HSTC labels. The HSTCs were originally defined from a medical system perspective, focusing on task impairments due to deteriorated human health. To expand our model's scope to include categories impacting performance, we face the challenge of generating binary labels (0 or 1) for new categories without pre-existing data. We address this by employing Generative AI (GenAI) software to determine whether a given task involved a new category by asking, "Does task A involve using category B?" We validate our approach by comparing the GenAI's binary classifications with the expert-provided labels for existing HSTCs. Notably, we utilize Ollama [4], a locally hosted GenAI tool that does not require cloud access, thus safeguarding NASA's proprietary data from unauthorized exposure. This study demonstrates the feasibility of leveraging cutting-edge AI tools to advance research, paving the way for automation and rapid decision-making in space exploration.

Mona Matar↗

Cognitive Performance in ISS Astronauts on 6-Month Low Earth Orbit Missions

Introduction: Current and future astronauts will endure prolonged exposure to spaceflight hazards and environmental stressors that could compromise cognitive functioning, yet cognitive performance in current missions to the International Space Station remains critically under-characterized. We systematically assessed cognitive performance across 10 cognitive domains in astronauts on 6-month missions to the ISS. Methods: Twenty-five professional astronauts were administered the Cognition Battery as part of National Aeronautics and Space Administration (NASA) Human Research Program Standard Measures Cross-Cutting Project. Cognitive performance data were collected at five mission phases: pre-flight, early flight, late flight, early post-flight, and late post-flight. We calculated speed and accuracy scores, corrected for practice effects, and derived z-scores to represent deviations in cognitive performance across mission phases from the sample’s mean baseline (i.e., pre-flight) performance. Linear mixed models with random subject intercepts and pairwise comparisons examined the relationships between mission phase and cognitive performance. Results: Cognitive performance was generally stable over time with some differences observed across mission phases for specific subtests. There was slowed performance observed in early flight on tasks of processing speed, visual working memory, and sustained attention. We observed a decrease in risk-taking propensity during late flight and post-flight mission phases. Beyond examining group differences, we inspected scores that represented a significant shift from the sample’s mean baseline score, revealing that 11.8% of all flight and post-flight scores were at or below 1.5 standard deviations below the sample’s baseline mean. Finally, exploratory analyses yielded no clear pattern of associations between cognitive performance and either sleep or ratings of alertness. Conclusions: There was no evidence for a systematic decline in cognitive performance for astronauts on a 6-month missions to the ISS. Some differences were observed for specific subtests at specific mission phases, suggesting that processing speed, visual working memory, sustained attention, and risk-taking propensity may be the cognitive domains most susceptible to change in Low Earth Orbit for high performing, professional astronauts. We provide descriptive statistics of pre-flight cognitive performance from 25 astronauts, the largest published preliminary normative database of its kind to date, to help identify significant performance decrements in future samples.

Data curation↗

Expanding the Description of Spaceflight Effects beyond Bone Mineral Density [BMD]: Trabecular Bone Score [TBS] in ISS Astronauts

Dual-energy x-ray absorptiometry [DXA] is the widely-applied bone densitometry method used to diagnose osteoporosis in a terrestrial population known to be at risk for age-related bone loss. This medical test, which measures areal bone mineral density [aBMD] of clinically-relevant skeletal sites (e.g., hip and spine), helps the clinician to identify which persons, among postmenopausal women and men older than 50 years, are at high risk for low trauma or fragility fractures and might require an intervention. The most recognized osteoporotic fragility fracture is the vertebral compression fracture which can lead to kyphosis or hunched backs typically seen in the elderly. DXA measurement of BMD however is recognized to be insufficient as a sole index for assessing fracture risk. DXA's limitation may be related to its inability to monitor changes in structural parameters, such as trabecular vs. cortical bone volumes, bone geometry or trabecular microarchitecture. Hence, in order to understand risks to human health and performance due to space exposure, NASA needs to expand its measurements of bone to include other contributors to skeletal integrity. To this aim, the Bone and Mineral Lab conducted a pilot study for a novel measurement of bone microarchitecture that can be obtained by retrospective analysis of DXA scans. Trabecular Bone Score (TBS) assesses changes to trabecular microarchitecture by measuring the grey color "texture" information extracted from DXA images of the lumbar spine. An analysis of TBS in 51 ISS astronauts was conducted to assess if TBS could detect 1) an effect of spaceflight and 2) a response to countermeasures independent of DXA BMD. In addition, changes in trunk body lean tissue mass and in trunk body fat tissue mass were also evaluated to explore an association between body composition, as impacted by ARED exercise, and bone microarchitecture. The pilot analysis of 51 astronaut scans of the lumbar spine suggests that, following an ISS mission, DXA BMD and TBS are detecting different effects of ARED exercise and of ARED + Bisphosphonate on the lumbar spine of astronauts. There is emerging evidence associating reduced TBS with terrestrial metabolic bone disorders where a TBS <1.200 is associated with "degraded" while > 1.350 is associated with "normal." However, it is not possible to conclude how the spaceflight-induced changes in TBS increase risk for vertebral fractures in the astronaut or if changes in body composition of the trunk region could be an indirect method of assessing exercise effect on bone microarchitecture. More importantly, this pilot analysis demonstrates a new, minimal risk approach for monitoring changes to vertebral bone microarchitecture. This method could help assess the combined skeletal effects of spaceflight with the effects of aging in the astronaut after return to Earth.

Sibonga, J. D.↗

Deployment of an Advanced Electrocardiographic Analysis (A-ECG) to Detect Cardiovascular Risk in Career Firefighters

INTRODUCTION: Sudden cardiac death is the leading cause of line of duty death among firefighters, accounting for approximately 45% of fatalities annually. Firefighters perform strenuous muscular work while wearing heavy, encapsulating personal protective equipment in high ambient temperatures, under chaotic and emotionally stressful conditions. These factors can precipitate sudden cardiac events like myocardial infarction, serious dysrhythmias, or cerebrovascular accidents in firefighters with underlying cardiovascular disease. PURPOSE: The purpose of this study was to deploy and then evaluate the contribution of resting advanced ECG (A-ECG) in addition to other screening tools (family history, lipid profiles, and cardiopulmonary exercise tests, XT) in assessment of an individual fs cardiac risk profile. METHODS: Forty-four career firefighters were recruited to perform comprehensive baseline assessments including tests of aerobic performance, fasting lipids and glucose. Five-min resting 12-lead A-ECGs were obtained in a subset of firefighters (n=21) and transmitted over a secure networked system to a NASA physician collaborator. Using myocardial perfusion and other imaging as the gold standard, A-ECG scoring has been proven useful in accurately identifying a number of cardiac pathologies including coronary artery disease (CAD), left ventricular hypertrophy, hypertrophic cardiomyopathy, and non-ischemic and ischemic cardiomyopathy. RESULTS: Subjects f mean (SD) age was 43 (8) years, weight 91 (13) kg, and BMI 28 (3) kg/m2. Fifty-one percent of subjects had .3 cardiovascular risk factors. One subject had ST depression on XT ECG, at least one positive A-ECG score for CAD, and documented CAD based on cardiology referral. While all other subjects, including those with fewer risk factors, higher aerobic fitness, and normal exercise ECGs, were classified as healthy by A-ECG, there was no trend for association between risk factors and any of 20 A-ECG parameters in the grouped data.

Dolezal, B. A.↗

Proposed Project Selection Method for Human Support Research and Technology Development (HSR&TD)

The purpose of HSR&TD is to deliver human support technologies to the Exploration Systems Mission Directorate (ESMD) that will be selected for future missions. This requires identifying promising candidate technologies and advancing them in technology readiness until they are acceptable. HSR&TD must select an may of technology development projects, guide them, and either terminate or continue them, so as to maximize the resulting number of usable advanced human support technologies. This paper proposes an effective project scoring methodology to support managing the HSR&TD project portfolio. Researchers strongly disagree as to what are the best technology project selection methods, or even if there are any proven ones. Technology development is risky and outstanding achievements are rare and unpredictable. There is no simple formula for success. Organizations that are satisfied with their project selection approach typically use a mix of financial, strategic, and scoring methods in an open, established, explicit, formal process. This approach helps to build consensus and develop management insight. It encourages better project proposals by clarifying the desired project attributes. We propose a project scoring technique based on a method previously used in a federal laboratory and supported by recent research. Projects are ranked by their perceived relevance, risk, and return - a new 3 R's. Relevance is the degree to which the project objective supports the HSR&TD goal of developing usable advanced human support technologies. Risk is the estimated probability that the project will achieve its specific objective. Return is the reduction in mission life cycle cost obtained if the project is successful. If the project objective technology performs a new function with no current cost, its return is the estimated cash value of performing the new function. The proposed project selection scoring method includes definitions of the criteria, a project evaluation questionnaire, and a scoring formula.

Jones, Harry↗

Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.

Credibility↗

Evaluation of a Shuttle Derived Vehicle (SDV) for Cargo Transportation

In this new era of space exploration, a host of launch vehicles are being examined for possible use in transporting cargo and crew to low Earth orbit and beyond. Launch vehicles derived from the Space Shuttle Program (SSP), known as Shuttle Derived Vehicles (SDVs), are prime candidates for heavy-lift duty because of their potential to minimize non-recurring costs and because the Shuttle can leverage off proven high-performance flight systems with established ground and flight support. To determine the merits of SDVs, a detailed evaluation was performed. This evaluation included a trade study and risk assessment of options based on performance, safety reliability, cost, operations, and evolution. The purpose of this paper is to explain the approach, processes, and tools used to evaluate launch vehicles for heavy lift cargo transportation. The process included defining the trade space, characterizing the concepts, analyzing the systems, and scoring the options. The process also included a review by subject experts from NASA and industry to compare past and recent study data and assess the risks. A set of technical performance measures (TPMs) was generated based on the study requirements and constraints. Tools such as INTROS and POST were used to calculate performance, FIRST was used for prediction of reliability, and other software packages, both commercial and NASA-owned, were applied to study the trade space. By following a clear process and using the right tools a thorough assessment was performed. An SDV can be classified as either a side-mount vehicle (SMV) or an in-line vehicle OLV). An SMV is a Space Shuttle where the Orbiter is replaced by a cargo carrier. An ILV is comprised of a modified Shuttle External Tank (ET) with engines mounted to the bottom and cargo mounted atop. For both families of vehicles, Solid Rocket Boosters (SRBs) are attached to the ET. The first derivate of Shuttle is defined as the vehicle with minimum changes necessary to transform the Space Shuttle into an SDV. Deltas from the first derivate were also formulated to study more SDV options. Examples of deltas include replacing the SRBs with larger and/or more SRBs, adding an upper stage, increasing the size of the ET, changing the engines, and modifying the elements. Challenges for SDV range from tailoring infrastructure to meeting the exploration schedule. Although SDV is based on the Space Shuttle, it still includes development risk for designing and building a Cargo Carrier. There are also performance challenges in that Shuttle is not optimized for cargo-only missions, but it is a robust system built on reusability. Balancing the strengths and weaknesses of the Shuttle to meet Lunar and Mars mission objectives provides the framework for an informative trade study. SDV was carefully analyzed and the results of the study provide invaluable data for use in the new exploration initiative.

Roman, Jose M.↗

Development of Risk Assessment Matrix for NASA Engineering and Safety Center

This paper describes a study, which had as its principal goal the development of a sufficiently detailed 5 x 5 Risk Matrix Scorecard. The purpose of this scorecard is to outline the criteria by which technical issues can be qualitatively and initially prioritized. The tool using this score card has been proposed to be one of the information resources the NASA Engineering and Safety Center (NESC) takes into consideration when making decisions with respect to incoming information on safety concerns across the entire NASA agency. The contents of this paper discuss in detail each element of the risk matrix scorecard, definitions for those elements and the rationale behind the development of those definitions. This scorecard development was performed in parallel with the tailoring of the existing Futron Corporation Integrated Risk Management Application (IRMA) software tool. IRMA was tailored to fit NESC needs for evaluating incoming safety concerns and was renamed NESC Assessment Risk Management Application (NAFMA) which is still in developmental phase.

Malone, Roy W., Jr.↗

A Dose of Reality: Radiation Analysis for Realistic Human Spacecraft

INTRODUCTION As with most computational analyses, a tradeoff exists between problem complexity, resource availability and response accuracy when modeling radiation transport from the source to a detector. The largest amount of analyst time for setting up an analysis is often spent ensuring that any simplifications made have minimal impact on the results. The vehicle shield geometry of interest is typically simplified from the original CAD design in order to reduce computation time, but this simplification requires the analyst to "re-draw" the geometry with a limited set of volumes in order to accommodate a specific radiation transport software package. The resulting low-fidelity geometry model cannot be shared with or compared to other radiation transport software packages, and the process can be error prone with increased model complexity. The work presented here demonstrates the use of the DAGMC (Direct Accelerated Geometry for Monte Carlo) Toolkit from the University of Wisconsin, to model the impacts of several space radiation sources on a CAD drawing of the US Lab module. METHODS The DAGMC toolkit workflow begins with the export of an existing CAD geometry from the native CAD to the ACIS format. The ACIS format file is then cleaned using SpaceClaim to remove small holes and component overlaps. Metadata is then assigned to the cleaned geometry file using CUBIT/Trelis from csimsoft (Registered Trademark). The DAGMC plugin script removes duplicate shared surfaces, facets the geometry to a specified tolerance, and ensures that the faceted geometry is water tight. This step also writes the material and scoring information to a standard input file format that the analyst can alter as desired prior to running the radiation transport program. The scoring results can be transformed, via python script, into a 3D format that is viewable in a standard graphics program. RESULTS The CAD model of the US Lab module of the International Space Station, inclusive of all the racks and components, was simplified to remove holes and volume overlaps. Problematic features within the drawing were also removed or repaired to prevent runtime issues. The cleaned drawing was then run through the DAGMC workflow to prepare for analysis. Pilot tests modeling transport of 1GeV proton and 800MeV/A oxygen sources show that reasonable results are converged upon in an acceptable amount of overall computation time from drawing preparation to data analysis. The FLUKA radiation transport code will next be used to model both a GCR and a trapped radiation source. These results will then be compared with measurements that have been made by the radiation instrumentation deployed inside the US Lab module. DISCUSSION Early analyses have indicated that the DAGMC workflow is a promising toolkit for running vehicle geometries of interest to NASA through multiple radiation transport codes. In addition, recent work has shown that a realistic human phantom, provided via a subcontract with the University of Florida, can be placed inside any vehicle geometry for a combinatorial analysis. This added functionality gives the user the ability to score various parameters at the organ level, and the results can then be used as input for cancer risk models.

Barzilla, J. E.↗

Development of A Directed Acyclic Graph for Venous Thromboembolism During Spaceflight

Introduction: Recent studies have reported the development of venous blood flow stasis in astronauts and an occlusive venous thrombosis during spaceflight. Subsequent investigations revealed approximately one quarter of surveilled crew members had some degree of blood flow stasis in the left internal jugular vein. Therefore, NASA’s Human System Risk Board now formally tracks venous thromboembolism (VTE) as a “concern” for human spaceflight. To investigate potential mechanisms by which exposures concomitant with spaceflight (e.g., microgravity, radiation) may contribute to VTE, we developed a causal diagram in the form of a directed acyclic graph (DAG). Methods: The mechanisms by which spaceflight exposures may elevate the risk of VTE and the downstream effects on mission outcomes were critically analyzed, taking into account scientific literature and subject matter expertise consultation, and a DAG was generated. A Level-of-Evidence score for each causal relationship was assigned based on assessing the literature against a set of criteria derived from the A. Bradford Hill Causal Guidelines. Results: The set of three main factors that predispose people to VTE (hypercoagulability, endothelial damage, and blood stasis) is known as Virchow’s Triad. In constructing the DAG for VTE we articulated various mechanisms by which the principal spaceflight hazards (microgravity, radiation, closed hostile environment, isolation and confinement, distance from Earth) are thought to interact with or cause the components in Virchow’s triad. We found sufficient evidence to at least speculate that fluid shifts from microgravity, compensatory alterations in hematologic indices, spaceflight atmospheric conditions, and oxidative stress/inflammation from radiation may be potential contributors to VTE development. Discussion: Developing the DAG entailed a systematic and repeatable approach for visualizing relationships between contributing factors that may lead to VTE in spaceflight. Articulating pathways linking spaceflight exposures to VTE risk factors and possible VTE development enables subject matter experts from different domains to construct a shared mental model. Assignment of levels of evidence scores to the relationships helps identify knowledge and capability gaps that should be considered for further investigation. Furthermore, the DAG highlights modifiable variables and may therefore facilitate the development of new VTE risk mitigation strategies.

Alexander Svoronos↗

Human Spaceflight Applications of Novel Miniature X-Ray Technologies

INTRODUCTION: Radiography (XR) has long been a cornerstone of terrestrial medical imaging, though it has not yet been used in the spaceflight environment. Medical systems for human spaceflight missions are constrained by mass, volume, and power, and until recently, XR systems have been considered too large and power-consuming for spaceflight diagnostic and therapeutic applications. However, the rise of commercial spaceflight and NASA’s refocused efforts on returning crews to the Moon for long-duration missions have introduced a higher degree of medical risk to human spaceflight and require a re-evaluation when optimizing medical system design. Over the last decade, XR devices have miniaturized while maintaining good diagnostic and therapeutic sensitivity and specificity, making new in-flight medical and non-medical XR applications a possibility. Initial research identified several medical conditions where miniature XR would be beneficial for the diagnosis and/or management of medical conditions arising in space, though a more in-depth analysis is required to identify whether XR may add value to the management of such conditions. With this presentation, we aim to introduce the potential utility of miniature XR, review prior work highlighting where XR may be beneficial, and evaluate how miniature XR may reduce medical risk in human spaceflight missions. METHODS: IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a risk assessment tool developed by NASA to advance exploration mission medical system design by quantitatively estimating mission medical risk. IMPACT v1.0 includes a novel evidence library baselined to exploration environments, an expanded list of 119 medical conditions, medical capabilities and resources critical for management of these medical conditions, and the ability for rapid and iterative analysis in the setting of modifiable design reference missions (DRMs). Our first analysis identified which of the 119 medical conditions XR had diagnostic or therapeutic utility for. Subject matter experts (SMEs) recorded which XR views would be performed under ideal terrestrial circumstances for diagnosis/management of each condition, as well as which views are pragmatic for spaceflight limitations. A second analysis utilized IMPACT to identify significant conditions that contribute greatest to medical risk during a notional long-duration Lunar orbit and Lunar surface DRM. Medical system risk estimates include loss of crew life (LOCL), need for return to definitive care (RTDC; medical evacuation), and an estimate of crew task time affected (TTA). Using a standardized semi-quantitative scoring methodology, a deeper evaluation of each of the most significant medical conditions was performed. Data from both of these separate analyses were used to hypothesize what ideal and pragmatic XR studies may impact clinical management of the most significant conditions predicted to lead to medical risk. RESULTS: Approximately 1/3 of the IMPACT conditions were identified as being more effectively or comprehensively assessed or treated with the addition of miniature XR technology. The resulting conditions benefitting diagnostically and therapeutically from XR are revealed, as well as the ideal and pragmatic XR views and medical procedures benefitting from XR. The conditions of clinical significance and those most contributing to risk are also displayed. Among the conditions that contribute greatest to LOCL, four conditions for which XR may improve the diagnosis and management of include: decompression sickness, traumatic shock, dental abscess, and respiratory failure. Among conditions that contributed to RTDC, the evaluation and management of wrist fracture is likely improved by XR. For conditions leading to crew TTA, evaluation and management of EVA shoulder injuries, upper and lower extremity strains, back strains, and EVA hand injuries are likely improved by XR. DISCUSSION: Miniature XR in spaceflight has the potential to improve the evaluation and management of a substantial portion of conditions that most contribute to medical risk. This presentation is an introduction to the possibilities miniature XR provides for future human spaceflight missions and subsequent presenters will expand on potential applications in more detail. LEARNING OBJECTIVES: 1) Understand the previous limitations of using radiography in the management of spaceflight medical conditions; 2) Evaluate the findings from the IMPACT tool analysis, which allows quantification of the benefit miniature XR could provide for managing high-risk medical conditions in long-duration lunar orbit and surface missions, focusing on improvements in crew health outcomes; 3) Analyze case studies where miniature XR technology could reduce the medical risks associated with spaceflight missions, specifically in diagnosing and managing conditions such as decompression sickness, traumatic shock, and EVA-related injuries.

A Anderson↗

Stochastic decision analysis

Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given amount of the best score. Formulas are also derived for the probability that one concept's total score is within a given amount of a second concept's total score. These probabilistic calculations provide more realistic data entry and output information for designers, enabling designers to better determine which concepts to eliminate and which concepts to retain at the decision points of each design phase.

Lacksonen, Thomas A.↗

Risk Of Early Onset Osteoporosis Due To Spaceflight

Bone minerals decline in microgravity, and bone mineral density (BMD) losses of approximately -1 to -1.5% per month were calculated for astronauts serving on long-duration missions prior to 2009. It is unclear whether BMD losses will stabilize with time in space, or continue to diminish with time. In addition, it is unknown if fractional gravity, present on the moon and Mars, will mitigate the mineral loss. Clinicians diagnose osteoporosis in premenopausal females and males younger than 50 years on the basis of BMD T-scores < -2.5 (hip and lumbar spine) accompanied by clinical evidence of a fragility fracture. If mission-related changes to the skeleton cannot be corrected by rehabilitation after the mission, crewmembers could be at risk for premature osteoporosis-related fractures in later life. To mitigate this risk it is necessary to understand the dynamics underlying the BMD changes that occur in microgravity, to monitor for the persistence of changes after space flight, and to evaluate if and how current and future osteoporosis treatments might be used to mitigate the risk of long-term skeletal problems in astronauts.

Sibonga, Jean↗

Philadelphia Health & Air Quality: Assessing Land Surface Temperature, Vegetation Cover, and Compounding Vulnerability Factors to Identify High Priority Areas for Cooling Initiatives in Philadelphia, Pennsylvania

Heat is the leading cause of weather-related deaths in the US, with heat-related hospitalizations increasing by 2-5% between 2001-2010. In Philadelphia alone, 137 heat-related deaths were recorded between 2010-2018, while a total of 18 daily temperature records have been set since 2010. Temperature is relatively higher in cities compared to rural areas, a phenomenon known as the urban heat island effect. This effect exaggerates daytime maximum temperatures and nighttime heat retention in urban areas, which increases heat exposure in urban environments and especially impacts vulnerable populations. Vulnerability to heat-related illnesses is determined by a combination of risk factors, such as demographics, socioeconomic status, and preexisting health conditions. This project supported the Philadelphia Department of Public Health and Office of Sustainability by identifying priority areas for cooling interventions, such as heat danger educational outreach and urban tree planting. The team developed heat vulnerability scores for each census tract within Philadelphia. Remotely sensed land surface temperature, normalized difference vegetation index, normalized difference built-up index, normalized difference water index, and albedo data were calculated from Aqua Moderate Resolution Imaging Spectroradiometer and Landsat 8 Operational Land Imager/Thermal Infrared Sensor instruments. These variables were weighted against socioeconomic variables and preexisting health conditions using a principal component analysis. A total of 74 census tracts clustered were identified as high-risk areas for heat-related illnesses. 15 of these census tracts also had very low tree density (lower 20th percentile) and should be targeted for tree planting initiatives. The findings of this project will help target interventions to mitigate heat-related health issues and improve the overall wellness of Philadelphia residents.

Health & Air Quality↗

Philadelphia Health & Air Quality: Assessing Land Surface Temperature, Vegetation Cover, and Compounding Vulnerability Factors to Identify High Priority Areas for Cooling Initiatives in Philadelphia, Pennsylvania

Heat is the leading cause of weather-related deaths in the US, with heat-related hospitalizations increasing by 2-5% between 2001-2010. In Philadelphia alone, 137 heat-related deaths were recorded between 2010-2018, while a total of 18 daily temperature records have been set since 2010. Temperature is relatively higher in cities compared to rural areas, a phenomenon known as the urban heat island effect.This effect exaggerates daytime maximum temperatures and nighttime heat retention in urban areas, which increases heat exposure inurban environments and especially impacts vulnerable populations. Vulnerability to heat-related illnesses is determined by a combination of risk factors, such as demographics, socioeconomic status, and preexisting health conditions. This project supported the Philadelphia Department of Public Health and Office of Sustainability by identifying priority areas for cooling interventions, such as heat danger educational outreach and urban tree planting. The team developed heat vulnerability scores for each census tract within Philadelphia. Remotely sensed land surface temperature, normalized difference vegetation index, normalized difference built-up index, normalized difference water index, and albedo data were calculated from Aqua Moderate Resolution Imaging Spectroradiometer and Landsat 8 Operational Land Imager/Thermal Infrared Sensor instruments. These variables were weighted against socioeconomic variables and preexisting health conditions using a principal component analysis. A total of 74 census tracts clustered were identified as high-risk areas for heat-related illnesses. 15 of these census tracts also had very low tree density (lower 20th percentile) and should be targeted for tree planting initiatives. The findings of this project will help target interventions to mitigate heat-related health issues and improve the overall wellness of Philadelphia residents.

Health & Air Quality↗