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NASA NTRS2003

Complex Organics from Laboratory Simulated Interstellar Ices

Many of the volatiles in interstellar dense clouds exist in ices surrounding dust grains. The low temperatures of these ices (T < 50 K) preclude most chemical reactions, but photolysis can drive reactions that produce a suite of new species, many of which are complex organics. We study the UV and proton radiation processing of interstellar ice analogs to explore links between interstellar chemistry, the organics in comets and meteorites, and the origin of life on Earth. The high D/H ratios in some interstellar species, and the knowledge that many of the organics in primitive meteorites are D-enriched, suggest that such links are plausible. Once identified, these species may serve as markers of interstellar heritage of cometary dust and meteorites. Of particular interest are our findings that UV photolysis of interstellar ice analogs produce molecules of importance in current living organisms, including quinones, amphiphiles, and amino acids. Quinones are essential in vital metabolic roles such as electron transport. Studies show that quinones should be made wherever polycyclic aromatic hydrocarbons are photolyzed in interstellar ices. In the case of anthracene-containing ices, we have observed the production of 9-anthrone and 9,10 anthraquinone, both of which have been observed in the Murchison meteorite. Amphiphiles are also made when mixed molecular ices are photolyzed. These amphiphiles self-assemble into fluorescent vesicles when placed in liquid water, as do Murchison extracts. Both have the ability to trap an ionic dye. Photolysis of plausible ices can also produce alanine, serine, and glycine as well as a number of small alcohols and amines. Flash heating of the room temperature residue generated by such experiments generates mass spectral distributions similar to those of IDPs. The detection of high D/H ratios in some interstellar molecular species, and the knowledge that many of the organics, such as hydroxy and amino acids, in primitive meteorites are D-enriched provides evidence for a connection between intact organic material in the interstellar medium and in meteorites. Thus, some of the oxidized aromatics, amphiphiles, amino acids, hydroxy acids, and other compounds found in meteorites may have had an interstellar ancestry and not solely a product of parent body aqueous alteration. Such compounds should also be targeted for searches of organics in cometary dust.

Dworkin, J. P.↗

DOE OSTI2025

Solid-state platform for cooperative quantum dynamics driven by correlated emission

While traditionally regarded as an obstacle to quantum coherence, recent breakthroughs in quantum optics have shown that the dissipative interaction of a qubit with its environment can be leveraged to protect quantum states and synthesize many-body entanglement. Inspired by this progress, here we set the stage for the—as yet uncharted—exploration of analogous cooperative phenomena in hybrid solid-state platforms. We develop a comprehensive formalism for the quantum many-body dynamics of an ensemble of solid-state spin defects interacting with the magnetic field fluctuations of a common solid-state reservoir. Our framework applies to any solid-state reservoir whose fluctuating spin, pseudospin, or charge degrees of freedom generate magnetic fields. To understand whether correlations induced by dissipative processes can play a relevant role in a realistic experimental setup, we apply our model to a qubit array interacting via the spin fluctuations of a ferromagnetic bath. Our results show that the low-temperature collective relaxation rates of the qubit ensemble can display clear signatures of super- and subradiance, i.e., forms of cooperative dynamics traditionally achieved in atomic ensembles. We find that the solid-state analog of these cooperative phenomena is robust against spatial disorder in the qubit ensemble and thermal fluctuations of the magnetic reservoir, providing a route for their feasibility in near-term experiments. Finally, our work lays the foundation for a multiqubit approach to quantum sensing of solid-state systems and the direct generation of many-body entanglement in spin-defect ensembles. Furthermore, we discuss how the tunability of solid-state reservoirs opens up novel pathways for exploring cooperative phenomena in regimes beyond the reach of conventional quantum optics setups.

NV centers↗

NASA NTRS2014

Human Factor Investigation of Waste Processing System During the HI-SEAS 4 Month Mars Analog Mission in Support of NASA's Logistic Reduction and Repurposing Project: Trash to Gas

NASAs Logistics Reduction and Repurposing (LRR) project is a collaborative effort in which NASA is tasked with reducing total logistical mass through reduction, reuse and recycling of various wastes and components of long duration space missions and habitats. Trash to Gas (TtG) is a sub task to LRR with efforts focused on development of a technology that converts wastes generated during long duration space missions into high-value products such as methane, water for life support, raw material production feedstocks, and other energy sources. The reuse of discarded materials is a critical component to reducing overall mission mass. The 120 day Hawaii Space Exploration and Analog Simulation provides a unique opportunity to answer questions regarding crew interface and system analysis for designing and developing future flight-like versions of a TtG system. This paper will discuss the human factors that would affect the design of a TtG or other waste processing systems. An overview of the habitat, utility usage, and waste storage and generation is given. Crew time spent preparing trash for TtG processing was recorded. Gas concentrations were measured near the waste storage locations and at other locations in the habitat. In parallel with the analog mission, experimental processing of waste materials in a TtG reactor was performed in order to evaluate performance with realistic waste materials.

Steam reformer↗

NASA NTRS2014

Human Factor Investigation of Waste Processing System During the HI-SEAS 4-month Mars Analog Mission in Support of NASA's Logistic Reduction and Repurposing Project: Trash to Gas

NASA's Logistics Reduction and Repurposing (LRR) project is a collaborative effort in which NASA is tasked with reducing total logistical mass through reduction, reuse and recycling of various wastes and components of long duration space missions and habitats. Trash to Gas (TtG) is a sub task to LRR with efforts focused on development of a technology that converts wastes generated during long duration space missions into high-value products such as methane, water for life support, raw material production feedstocks, and other energy sources. The reuse of discarded materials is a critical component to reducing overall mission mass. The 120 day Hawaii Space Exploration and Analog Simulation provides a unique opportunity to answer questions regarding crew interface and system analysis for designing and developing future flight-like versions of a TtG system. This paper will discuss the human factors that would affect the design of a TtG or other waste processing systems. An overview of the habitat, utility usage, and waste storage and generation is given. Crew time spent preparing trash for TtG processing was recorded. Gas concentrations were measured near the waste storage locations and at other locations in the habitat. In parallel with the analog mission, experimental processing of waste materials in a TtG reactor was performed in order to evaluate performance with realistic waste materials.

waste management↗

NASA NTRS2018

Evaluation of Crew-Centric Onboard Mission Operations Planning and Execution Tool: Year 2

Currently, mission planning for the International Space Station (ISS) is largely affected by ground operators in mission control. The task of creating a week-long mission plan for ISS crew takes dozens of people multiple days to complete, and is often created far in advance of its execution. As such, re-planning or adapting to changing real-time constraints or emergent issues is similarly taxing. As we design for future mission operations concepts to other planets or areas with limited connectivity to Earth, more of these ground-based tasks will need to be handled autonomously by the crew onboard.There is a need for a highly usable (including low training time) tool that enables efficient self-scheduling and execution within a single package. The ISS Program has identified Playbook as a potential option. It already has high crew acceptance as a plan viewer from previous analogs and can now support a crew self-scheduling assessment on ISS or on another mission. The goals of this work, a collaboration between the Human Research Program and the ISS Program, are to inform the design of systems for more autonomous crew operations and provide a platform for research on crew autonomy for future deep space missions. Our second year of the research effort have included new insights on the crew self-scheduling sessions performed by the crew through use on the HERA (Human Exploration Research Analog) and NEEMO (NASA Extreme Environment Mission Operations) analogs. Use on the NEEMO analog involved two self-scheduling strategies where the crew planned and executed two days of EVAs (Extra-Vehicular Activities). On HERA year two represented the first HERA campaign where we were able to perform research tasks. This involved selected flexible activities that the crew could schedule, mock timelines where the crew completed more complex planning exercises, usability evaluation of the crew self-scheduling features, and more insights into the limit of plan complexity that the crew could effectively self-schedule. In parallel we have added in new features and functionality in the Playbook tool based off of our insights from crew self-scheduling in the NASA analogs. In particular this year we have added in the ability for the crew to add, edit, and remove their own activities in the Playbook tool, expanding the type of planning and re-planning possible in the tool and opening up the ability for more free form plan creation. The ability to group and manipulate groups of activities from the plan task list was also added, allowing crew members to add predefined sets of activities onto their mission timeline. In addition we also added a way for crew members to roll back changes in their plan, in order to allow an undo like capability. These features expand and complement the initial self-scheduling features added in year one with the goal of making crew autonomous planning more efficient. As part of this work we have also finished developing the first version of our Playbook Data Analysis Tool, a research tool built to interpret and analyze the unobtrusively collected data obtained during the NASA analog missions through Playbook. This data which includes user click interaction as well as plan change information, through the Playbook Data Analysis Tool, allows us to playback this information as if a video camera was mounted over the crewmember's tablet. While the primary purpose of this tool is to allow usability analysis of crew self-scheduling sessions used on the NASA analog, since the data collected is structured, the tool can automatically derive metrics that would be traditionally tedious to achieve without manual analysis of video playback. We will demonstrate and discuss the ability for future derived metrics to be added to the tool. In addition to the current data and results gathered in year two we will also discuss the preparation and goals of our International Space Station (ISS) onboard technology demonstration with Playbook. This technology demonstration will be preformed as part of the CAST payload starting in late 2016.

onboard planning↗

NASA NTRS2025

A Preliminary Study on the Feasibility of Large Language Models for Detecting Micro-Behaviors Among Team Members in Space Missions

Large-language models (LLMs) have been recently used for spoken language understanding (SLU) to infer meaning and semantics from speech in tasks such as speaker intent and sentiment classification. Due to being trained on large amounts of data, and their ability to understand context and relationships between words, LLMs are competent, enabling them to generalize across tasks without requiring many task-specific training samples. This research examines the feasibility of few-shot learning in LLMs for detecting subtle, brief, and possibly unconscious interactions between team members, called ``micro-behaviors," and provides insights into the appropriate design of LLMs for this task. Our data came from 5 teams participating in a 45-day mission at the US National Aeronautics and Space Administration’s (NASA) Human Exploration Research Analog (HERA). More specifically we used data collected from team interaction battery (TIB) tasks teams performed five times in-mission which comprise an average 1.5 hours of conversation data per day. Micro-behaviors were coded according to an adapted version of Smith & Griffins (2022) theoretical framework in terms of Violation (i.e., presence of valenced behavior, uplifting/positive or discouraging/negative), Intensity (i.e., force of behavior in terms of how uplifting or discouraging is the behavior), and Intent (i.e., motive of the behavior in terms of whether it was deliberate or unintentional). We explore the ability of LLMs to detect the presence and intensity of micro-behaviors. We examine employing and fine-tuning readily available LLMs (i.e., RoBERTa, DistilBERT), as well as prompting state-of-the-art sequence classification models (i.e., Llama-2, Llama-3). In a total of 13,058 conversational turns (17.8% uplifting, 3.3% discouraging, 75.76% neutral, 3.14% nulls), we compute the macro F1-score of the 3-way micro-behavior classification task (i.e., classifying among uplifting, discouraging, and neutral; 33% chance). Results indicate that the RoBERTa model achieves a F1-score of 36.2% (uplift: 43.3% precision (P), 15.1% recall (R); discourage: 20% P, 0.5% R). These results significantly improve when we augment the data via paraphrasing in the RoBERTa model, reaching a 41.2% macro F1-score (uplift: 37.7% P, 86.3% R; discourage: 3.5% P, 1.8% R). Finally, the Llama-2 model with 3-shot prompting yields 38% macro F1-score (uplift: 28.7% P, 20% R; discourage: 7.2% P, 18% R), which is slightly better compared to the RoBERTa model without data augmentation, highlighting the effectiveness of sequence classification models in detecting minority classes with a small sample size. Findings indicate that LLMs hold potential to detect subtle behaviors in conversations, which could be valuable in assessing team behavior in space exploration missions. Future studies will evaluate the performance of different LLM prompting strategies or fine-tuning methods.

Ankush Raut↗

NASA NTRS2016

Meal Replacement Mass Reduction and Integration Acceptability Study

NASA, in planning for long duration missions, has an imperative to provide a food system with the necessary nutrition, acceptability, and safety to ensure sustainment of crew health and performance. The Orion Multi-Purpose Crew Vehicle (MPCV) and future exploration missions are mass constrained; therefore we are challenged to reduce the mass of the food system by 10% while maintaining safety, nutrition, and acceptability for exploration missions. Food bars have previously been used to supplement meals in the Skylab food system, indicating that regular consumption of bars will be acceptable. However, commercially available products do not meet the requirements for a full meal replacement in the spaceflight food system. The purpose of this task is to develop a variety of nutritionally balanced breakfast replacement bars, which meet spaceflight nutritional, microbiological, sensorial, and shelf-life requirements, while enabling a 10% food mass savings. To date, six nutrient-dense meal replacement bars have been developed, using both traditional methods of compression as well as novel ultrasonic compression technologies developed by Creative Resonance Inc. (Phoenix, AZ). All bars will be prioritized based on acceptability and the four top candidates will be evaluated in the Human Exploration Research Analog (HERA) to assess the frequency with which actual meal replacement options may be implemented. Specifically, overall impact to mood, satiety, dietary discomfort, and satisfaction with food will be analyzed to inform successful implementation strategies. In addition, these bars will be evaluated based on final product sensory acceptability, nutritional stability, qualitative stability of analytical measurements (i.e. water activity and texture), and microbiological compliance over two years of storage at room temperature and potential temperature abuse conditions to predict long-term acceptability. It is expected that this work will enable a successful meal replacement strategy to be implemented that maintains crew food consumption and health, while informing exploration missions with appropriate mass savings expectations.

Sirmons, T.↗

NASA NTRS2010

In Situ Geophysical Exploration by Humans in Mars Analog Environments

We carried out three geophysical experiments in Mars analog environments in order to better understand the challenges future astronauts will face when conducting similar surveys on Mars or the Moon. The experiments included a passive seismometer deployment and a time-domain electromagnetic survey at the Flashline Mars Arctic Research Station (FMARS) on Devon Island, Canada and a seismic refraction survey in southeastern Utah at the Mars Desert Research Station (MDRS). FMARS is located on the rim of the 23 Ma Haughton Crater in a polar desert environment. MDRS is located in an area with sedimentary plateaus and canyons of Jurassic to Cretaceous age. Both facilities were built by The Mars Society to help develop key knowledge about human Mars exploration. Crews of six spend 2-4 weeks in the habitats and conduct eld research on simulated extravehicular activities (EVAs) wearing mock spacesuits. The work reported here was conducted in July 2009 at FMARS and February 2010 at MDRS.

Shiro, B. R.↗

NASA NTRS2017

The Integrated Impact of Diet On Human Immune Response, the Gut Microbiota, and Nutritional Status During Adaptation to a Spaceflight Analog

Spaceflight impacts human physiology, including well documented immune system dysregulation. Diet, immune function, and the microbiome are interlinked, but diet is the only one of these factors that we have the ability to easily, and significantly, alter on Earth or during flight. As we understand dietary impacts on physiology more thoroughly, we may then improve the spaceflight diet to improve crew health and potentially reduce flight-associated physiological alterations. It is expected that increasing the consumption of fruits and vegetables and bioactive compounds (e.g.,omega-3 fatty acids, lycopene, flavonoids) and therefore enhancing overall nutritional intake from the nominal shelf-stable, fully-processed space food system could serve as a countermeasure to improve human immunological profiles, the taxonomic profile of the gut microbiota, and nutritional status, especially where currently dysregulated during spaceflight. This interdisciplinary study will determine the effect of the current shelf-stable spaceflight diet compared to an "enhanced" shelf-stable spaceflight diet (25% more foods rich in omega-3 fatty acids, lycopene, flavonoids, fruits, and vegetables). The NASA Human Exploration Research Analog (HERA) 2017 missions, consisting of closed chamber confinement, realistic mission simulation, in a high-fidelity mock space vehicle, will serve as a platform to replicate mission stressors and the dysregulated physiology observed in astronauts. Biosampling of crew members will occur at selected intervals, with complete dietary tracking. Outcome measures will include immune markers (e.g., peripheral leukocyte distribution, inflammatory cytokine profiles, T cell function), the taxonomic and metatranscriptomic profile of the gut microbiome, and nutritional status biomarkers and metabolites. Data collection will also include complete dietary tracking. Statistical evaluations will determine physiological and biochemical shifts in relation to nutrient in take and study phase. Beneficial improvements will provide evidence of the impact of diet on crew health and adaptation to this spaceflight analog, and will aid in the design and development of more-efficient targeted dietary interventions.

Douglas, G. L.↗

NASA NTRS2017

Meal Replacement Mass Reduction and Integration Acceptability Study

NASA, in planning for long-duration missions, has an imperative to provide a food system with the necessary nutrition, acceptability, and safety to ensure sustainment of crew health and performance. The Orion Multi-Purpose Crew Vehicle (MPCV) and future exploration missions are mass constrained; therefore the team is challenged to reduce the mass of the food system by 10% while maintaining product safety, nutrition, and acceptability. Commercially available products do not meet the nutritional requirements for a full meal replacement in the spaceflight food system, and it is currently unknown if daily meal replacements will impact crew food intake and psychosocial health over time. The purpose of this study was to develop a variety of nutritionally balanced breakfast replacement bars that meet spaceflight nutritional, microbiological, sensorial, and shelf-life requirements, while enabling a 10% savings in food mass. To date, six nutrient-dense meal replacement bars (approximately 700 calories per bar) have been developed, using traditional methods of compression as well as novel ultrasonic compression technologies developed by Creative Resonance Inc. (Phoenix, AZ). The four highest rated bars were evaluated in the Human Exploration Research Analog (HERA) to assess the frequency with which actual meal replacement options may be implemented. Specifically, overall impact of bars on mood, satiety, digestive discomfort, and satisfaction with food. These factors are currently being analyzed to inform successful implementation strategies where crew maintain adequate food intake. In addition, these bars are currently undergoing shelf-life testing to determine long-term sensory acceptability, nutritional stability, qualitative stability of analytical measurements (i.e. water activity and texture), and microbiological compliance over two years of storage at room temperature and potential temperature abuse conditions to predict long-term acceptability. It is expected that this work will enable a successful meal replacement strategy to be implemented that will maintain crew food consumption and health, while informing exploration missions with appropriate mass savings expectations.

Sirmons, T.↗

NASA NTRS2014

Forecasting Sensorimotor Adaptability from Baseline Inter-Trial Correlations

One of the greatest challenges surrounding adaptation to the spaceflight environment is the large variability in symptoms, and corresponding functional impairments, from one crewmember to the next. This renders preflight training and countermeasure development difficult, as a "one-size-fits-all" approach is inappropriate. Therefore, it would be highly advantageous to know ahead of time which crewmembers might have more difficulty adjusting to the novel g-levels inherent to spaceflight. Such knowledge could guide individually customized countermeasures, which would enable more efficient use of crew time, both preflight and inflight, and provide better outcomes. The primary goal of this project is to look for a baseline performance metric that can forecast sensorimotor adaptability without exposure to an adaptive stimulus. We propose a novel hypothesis that considers baseline inter-trial correlations, the trial-to-trial fluctuations in motor performance, as a predictor of individual sensorimotor adaptive capabilities. To-date, a strong relationship has been found between baseline inter-trial correlations and adaptability in two oculomotor systems. For this project, we will explore an analogous predictive mechanism in the locomotion system. METHODS: Baseline Inter-trial Correlations: Inter-trial correlations specify the relationships among repeated trials of a given task that transpire as a consequence of correcting for previous performance errors over multiple timescales. We can quantify the strength of inter-trial correlations by measuring the decay of the autocorrelation function (ACF), which describes how rapidly information from past trials is "forgotten." Processes whose ACFs decay more slowly exhibit longer-term inter-trial correlations (longer memory processes), while processes whose ACFs decay more rapidly exhibit shorterterm inter-trial correlations (shorter memory processes). Longer-term correlations reflect low-frequency activity, which is more easily measured in the frequency domain. Therefore, we use the power spectrum (PS), which is the Fourier transform of the ACF, to describe our inter-trial correlations. The decay of the PS yields a straight line on a log-log frequency plot, which we quantify by Beta = - (slope of PS on log-log axes). Hence, Beta is a measure of the strength of inter- trial correlations in the baseline data. Larger Beta values are indicative of longer inter-trial correlations. Experimental Approach: We will begin by performing a retrospective analysis of treadmill-gait adaptation data previously collected by Dr. Bloomberg and colleagues. Specifically, we will quantify the strength of inter-trial correlations in the baseline step cadence and heart rate data and compare it to the locomotor adaptability performance results already described by these investigators. Incorporating these datasets will also allow us to explore the applicability of (and potential limitations surrounding) the use of Beta in forecasting physiological performance. We will also perform a new experiment, in which Beta will be derived from baseline data collected during over-ground (non-treadmill) walking, which will enable us to consider locomotor performance, through the parameter Beta, under the most functionallyrelevant, natural gait condition. This experiment will incorporate two baseline and five post-training over-ground locomotion tests to explore the consistency and potential adaptability of the Beta values themselves. HYPOTHESES: We hypothesize that the strength of baseline inter-trial correlations of step cadence and heart rate will relate to locomotor adaptability. Specifically, we anticipate that individuals who show weaker longer-term inter-trial correlations in baseline step cadence data will be the better adaptors, as step cadence can be modified in real-time (i.e., online corrections are an inherent property of the locomotor system; analogous to results observed in the VOR). Conversely, because heart rate is not altered mid-beat, we expect that individuals who demonstrate stronger longer-term correlations in heart rate will be the better adaptors (analogous to results observed in the saccadic system). CONCLUSIONS: At the conclusion of this project we hope to uncover a baseline predictor of locomotor adaptability. If our hypotheses hold true, our results will demonstrate that the temporal structure of baseline behavioral data contains important information that may aid in forecasting adaptive capacities. The ability to predict such adaptability in the sensorimotor system has significant implications for spaceflight, where astronauts must adjust their motor programs following a change in g-level to retain movement accuracy.

Beaton, K. H.↗

NASA NTRS1990

Use of antarctic analogs to support the space exploration initiative

This report has discussed the Space Exploration Initiative (SEI) and the U.S. Antarctic Program (USAP) in the context of assessing the potential rationale and strategy for conducting a cooperative NASA/NSF (National Science Foundation) effort. Specifically, such an effort would address shared research and data on living and conducting scientific research in isolated, confined, hostile, and remote environments. A review of the respective goals and requirements of NASA and the NSF indicates that numerous opportunities exist to mutually benefit from sharing relevant technologies, data, and systems. Two major conclusions can be drawn: (1) The technologies, experience, and capabilities existing and developing in the aerospace community would enhance scientific research capabilities and the efficiency and effectiveness of operations in Antarctica. The transfer and application of critical technologies (e.g., power, waste management, life support) and collaboration on crew research needs (e.g., human behavior and medical support needs) would streamline the USAP operations and provide the scientific community with advancements in facilities and tools for Antarctic research. (2) Antarctica is the most appropriate earth analog for the environments of the the Moon and Mars. Using Antarctica in this way would contribute substantially to near- and long-term needs and plans for the SEI. Antarctica is one of the few ground-based analogs that would permit comprehensive and integrated studies of three areas deemed critical to productive and safe operations on the Moon and Mars: human health and productivity; innovative scientific research techniques; and reliable, efficient technologies and facilities.

Wharton, Robert↗

NASA NTRS2023

Developing a Hybrid Spacesuit Simulator as a Research Tool for Assessing Extravehicular Activity Relevant Workload

Conducting human tests in a pressurized spacesuit is limited by availability, cost, and manpower; however, pressurized spacesuits are not always needed depending on the objectives of testing, including the development and testing of new informatics capabilities. The Human Physiology, Performance, Protection & Operations Laboratory (H-3PO) at NASA is developing a Hybrid Spacesuit Simulator (HS3) to support testing and characterization of human performance during analog planetary exploration extravehicular activities (EVAs). The goal of HS3 is to create a low-cost, modular, and unpressurized spacesuit simulator as a research tool that provides relevant physical and cognitive workload approximations with EVA-like immersion. HS3 consists of a soft outer suit, thermal control, gloves, boots, helmet, and integrated bioinformatics and communications. Baseline HS3 assessments were performed during 3-hour EVA simulations in two different subjects (DEMO1 and DEMO2) that included traverses at variable resistances and geological sampling activities. Liquid cooling garment (LCG) temperature, mean skin temperature, heart rate, motion capture, and metabolic rate were collected during each 3-hour simulated EVA. During DEMO1 and DEMO2, baseline metabolic rates at rest were 836 ± 327 BTU/hr and 869 ± 207 BTU/hr and increased to 2124 ± 548 BTU/hr and 2269 ± 559 BTU/hr, respectively, during 500m traverse. Average inlet LCG temperatures were 29.57 ± 6.62 °C and 25.63 ± 6.48 °C for DEMO1 and DEMO2 with increased outlet LCG temperatures of 33.53 ± 6.62 °C and 29.21 ± 4.79 °C, respectively. Overall, HS3 will enable future studies to characterize EVA tasks, human performance, and test future EVA capabilities in analog test environments without the need for pressurized suited environments.

Monica Hew↗

NASA NTRSDate not supplied

Developing A Hybrid Spacesuit Simulator as A Research Tool for Assessing Extravehicular Activity Relevant Workload

Suit simulator↗

NASA NTRSDate not supplied

Predicting Team Functioning in Long Term Space Missions Using Acoustic and Linguistic Measures

Maintaining optimal team functioning is critical for long-duration space exploration missions, yet traditional monitoring methods, such as self-reports and wearable sensors, often impose operational burdens or suffer from bias. This paper investigates a non-intrusive speech-based artificial intelligence (AI) framework to predict degradations in team functioning using data from the Human Exploration Research Analog (HERA) of the U.S. National Aeronautics and Space Administration (NASA). Using acoustic features, linguistic descriptors, and semantic embeddings, we evaluate static non-linear and temporal machine learning models to predict both objective (task accuracy) and subjective (self-reported efficacy and cohesion) team functioning outcomes. Results indicate that temporal models outperform static approaches, with prediction of objective task accuracy in Team Interaction Battery (TIB) improving from near chance to 71%. Self-reported outcomes, including team efficacy and cohesion, are predicted more reliably than task performance, achieving balanced accuracies of up to 85.56% and 78.12%, respectively, and are found to be most strongly associated with acoustic features. In a second interdependent task, the MMSEV–EVA, accuracies of up to 78% are achieved using temporal models with acoustic features. Furthermore, incorporating just 1–2 days of team-specific historical data systematically improved performance, and acoustic markers from informal pre-task interactions provided modest predictive gains. Finally, while automated preprocessing yielded viable accuracy, humancorrected data provided moderate performance gains, though transcription error rates did not significantly correlate with model performance. These findings highlight the potential of speech as a passive, high-fidelity monitoring tool for autonomous habitats.

Temporal modeling↗

NASA NTRS2025

Navigating Team Dynamics: Automated Detection of Micro-Behaviors Between Team Members Through Longitudinal Interaction Data

The success in future long term space exploration missions will depend on the cooperation, coordination, and mutual understanding among the crew members. Micro-behaviors are momentary, subtle linguistic and paralinguistic indicators of thinking and feeling toward another member of the team (Cortina et al., 2001; Smith & Griffiths, 2022) that can significantly impact team dynamics and influence the overall team performance (Paromita & Chaspari, 2024). Due to their interactive nature, micro-behaviors have a sender (i.e., the team member expressing the micro-behavior) and a target (the team member impacted by the micro-behavior). Detection of these behaviors can assist in avoiding possible conflict among crew members and promoting the overall team success. Our prior research focused on an initial proof of concept of machine learning (ML) models and natural language processing (NLP) techniques that were used for automatically detect micro-behaviors among crew members of the US National Aeronautics and Space Administration’s (NASA) Human Exploration Research Analog (HERA) Campaigns 4 and 5 missions (Paromita et al., 2023). Results underscored the importance of incorporating contextual information in the ML models in the form of sentiment analysis, type of task, and dyadic interaction among team members. Here, we expand the scope of our prior work in two ways. First, we assess ML/NLP methods on new behavioral annotations coded using an adapted version of Smith & Griffins (2022) theoretical framework in terms of Violation (i.e., presence of valenced behavior, uplifting/positive or discouraging/negative), Intensity (i.e., force of behavior in terms of how uplifting or discouraging is the behavior), and Intent (i.e., motive of the behavior in terms of whether it was deliberate or unintentional). Second, we expand the design of the ML model to preserve information about the role of each team member within the occurrence of the micro-behavior (in contrast to the previous model that only considered the sender and the target without determining the team member role). This allows to consider all team members' contributions in the conversation and model long-term dependencies in the dialogue. Our experiments for this study are conducted on data from 5 teams of the NASA HERA C4 (NASA grant NNX16AQ48G (PI: Bell)). Conversations were extracted from the 1.5 hour Team Interaction Battery (TIB) task that occurred 5 times in-mission per crew. This resulted in a total of 13,058 conversational turns (i.e., 17.8% uplifting, 3.3% discouraging, 75.76% neutral, 3.14% nulls). Our findings with the revised behavioral coding and ML/NLP models indicate a 43.66% macro F1-score (i.e., 38.29% precision (P), 50.8% recall (R)) for a dialog state-tracking model that includes information from the sender only, and a 40.9% F1-score (i.e., 38.7% P, 43.36% R) for the same model that includes information from both the sender and the target of the micro-behavior. These are significantly higher compared to simple random forest models that classify behaviors strictly based on speech content and do not consider iterative team dynamics, achieving a 36.07% F1-score (i.e., 39.04% R, 33.53% P). Our findings demonstrate potential ways to leverage large conversational datasets to better capture complex team dynamics. We will discuss future directions including proposed models that can incorporate additional mission days and tasks beyond the TIB for objectively quantifying team behavior at high temporal resolution in space exploration missions.

Projna Paromita↗

DOE OSTI2020

Plausibility of the Formose Reaction in Alkaline Hydrothermal Vent Environments

Prebiotic processes required a reliable source of free energy and complex chemical mixtures that may have included sugars. The formose reaction is a potential source of those sugars. At moderate to elevated temperature and pH ranges, these sugars rapidly decay. Here it is shown that CaCO 3 -based chemical gardens catalyze the formose reaction to produce glucose, ribose, and other monosaccharides. These thin inorganic membranes are explored as analogs of hydrothermal vent materials—a possible place for the origin of life—and similarly exposed to very steep pH gradients. Supported by simulations of a simple reaction-diffusion model, this study shows that such gradients allow for the dynamic accumulation of sugars in specific layers of the thin membrane, effectively protecting formose sugar yields. Furthermore, the formose reaction may be a plausible prebiotic reaction in alkaline hydrothermal vent environments, possibly setting the stage for an RNA world.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Structure-based design of SARS-CoV-2 papain-like protease inhibitors

The COVID-19 pandemic is caused by SARS-CoV-2, an RNA virus with high transmissibility and mutation rate. Given the paucity of orally bioavailable antiviral drugs to combat SARS-CoV-2 infection, there is a critical need for additional antivirals with alternative mechanisms of action. Papain-like protease (PL pro ) is one of the two SARS-CoV-2 encoded viral cysteine proteases essential for viral replication. PL pro cleaves at three sites of the viral polyproteins. In addition, PLpro antagonizes the host immune response upon viral infection by cleaving ISG15 and ubiquitin from host proteins. Therefore, PL pro is a validated antiviral drug target. In this study, we report the X-ray crystal structures of papain-like protease (PL pro ) with two potent inhibitors, Jun9722 and Jun9843 . Subsequently, we designed and synthesized several series of analogs to explore the structure-activity relationship, which led to the discovery of PL pro inhibitors with potent enzymatic inhibitory activity and antiviral activity against SARS-CoV-2. Together, the lead compounds are promising drug candidates for further development.

60 APPLIED LIFE SCIENCES↗