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DOE OSTI2023

Exhaled breath condensate profiles of U.S. Navy divers following prolonged hyperbaric oxygen (HBO) and nitrogen-oxygen (Nitrox) chamber exposures

Prolonged exposure to hyperbaric hyperoxia can lead to pulmonary oxygen toxicity (PO 2 tox). PO 2 tox is a mission limiting factor for special operations forces divers using closed-circuit rebreathing apparatus and a potential side effect for patients undergoing hyperbaric oxygen (HBO) treatment. In this study, we aim to determine if there is a specific breath profile of compounds in exhaled breath condensate (EBC) that is indicative of the early stages of pulmonary hyperoxic stress/PO 2 tox. Using a double-blind, randomized 'sham' controlled, cross-over design 14 U.S. Navy trained diver volunteers breathed two different gas mixtures at an ambient pressure of 2 ATA (33 fsw, 10 msw) for 6.5 h. One test gas consisted of 100% O 2 (HBO) and the other was a gas mixture containing 30.6% O 2 with the balance N 2 (Nitrox). The high O 2 stress dive (HBO) and low O 2 stress dive (Nitrox) were separated by at least seven days and were conducted dry and at rest inside a hyperbaric chamber. EBC samples were taken immediately before and after each dive and subsequently underwent a targeted and untargeted metabolomics analysis using liquid chromatography coupled to mass spectrometry (LC-MS). Following the HBO dive, 10 out of 14 subjects reported symptoms of the early stages of PO 2 tox and one subject terminated the dive early due to severe symptoms of PO 2 tox. No symptoms of PO 2 tox were reported following the nitrox dive. A partial least-squares discriminant analysis of the normalized (relative to pre-dive) untargeted data gave good classification abilities between the HBO and nitrox EBC with an AUC of 0.99 (±2%) and sensitivity and specificity of 0.93 (±10%) and 0.94 (±10%), respectively. Furthermore, the resulting classifications identified specific biomarkers that included human metabolites and lipids and their derivatives from different metabolic pathways that may explain metabolomic changes resulting from prolonged HBO exposure.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Attention Guided Lymph Node Malignancy Prediction in Head and Neck Cancer

Accurate lymph node (LN) malignancy classification is essential for treatment target identification in head and neck cancer (HNC) radiation therapy. Given the constraints imposed by relatively small sample sizes in real-world medical applications, to classify LN malignancy status accurately, we proposed an attention-guided classification (AGC) scheme that (1) incorporates human knowledge (ie, LN contours) into model training to guide model’s “learning” direction, alleviating the critical requirement of large training samples by deep learning approaches; and (2) does not require accurate delineation of LNs in the inference stage but can highlight the discriminative region nearby the LN, which is important for malignancy determination.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS2006

Recommendations from NASA's Operational and Research Musculoskeletal Summit

Introduction: Continuously evolving medical standards of care, limited crew training time, and the inherent constraints of space flight necessitate regular revisions of the mission medical support infrastructure and methodology. A three-day Operational and Research Musculoskeletal Summit was held to review NASA s current strategy for preflight health maintenance and injury screening, risk mitigation for musculoskeletal injuries or syndromes, treatment methods during flight, and research topics to mitigate risks to astronaut health. The Summit also undertook consideration of the best evidence-based terrestrial musculoskeletal practices to recommend their adaptation for use in space. Methods: The types and frequencies of musculoskeletal injuries sustained by short- and long-duration astronauts were obtained from the Longitudinal Study of Astronaut Health. The Summit panel was comprised of experts from the clinical and research communities, as well as representatives from NASA Headquarters, the Astronaut corps, and the offices of JSC Medical Operations, JSC Human Adaptation and Countermeasures, Glenn Research Center Human Research, and Astronaut Strength Conditioning and Rehabilitation. Before the summit, panelists participated in a Web-based review of NASA s Space Medical Conditions List (SMCL). Results: The Summit generated seventy-five operational and research recommendations to the NASA Office of Space Medicine, including changes to the SMCL and to the musculoskeletal section of the ISS debrief questionnaire. From these recommendations, seven were assigned highest value and priority, and could be immediately adopted for the exploration architecture. Discussion: Optimized exercise and conditioning to improve performance and forestall musculoskeletal damage on orbit were the primary area of focus. Special attention was paid to exercise timing and muscle group specificity. The panel s recommendations are currently in various stages of consideration or integration into the ISS and Exploration programs. This effort serves to enhance the on-orbit system so comprehensive treatment can be delivered in a more effective and standardized manner.

Jones, J. A.↗

NASA NTRS2006

The Flostation - an Immersive Cyberspace System

A flostation is a computer-controlled apparatus that, along with one or more computer(s) and other computer-controlled equipment, is part of an immersive cyberspace system. The system is said to be immersive in two senses of the word: (1) It supports the body in a modified form neutral posture experienced in zero gravity and (2) it is equipped with computer-controlled display equipment that helps to give the occupant of the chair a feeling of immersion in an environment that the system is designed to simulate. Neutral immersion was conceived during the Gemini program as a means of training astronauts for working in a zerogravity environment. Current derivatives include neutral-buoyancy tanks and the KC-135 airplane, each of which mimics the effects of zero gravity. While these have performed well in simulating the shorter-duration flights typical of the space program to date, a training device that can take astronauts to the next level will be needed for simulating longer-duration flights such as that of the International Space Station. The flostation is expected to satisfy this need. The flostation could also be adapted and replicated for use in commercial ventures ranging from home entertainment to medical treatment. The use of neutral immersion in the flostation enables the occupant to recline in an optimal posture of rest and meditation. This posture, combines savasana (known to practitioners of yoga) and a modified form of the neutral posture assumed by astronauts in outer space. As the occupant relaxes, awareness of the physical body is reduced. The neutral body posture, which can be maintained for hours without discomfort, is extended to the eyes, ears, and hands. The occupant can be surrounded with a full-field-of-view visual display and nearphone sound, and can be stimulated with full-body vibration and motion cueing. Once fully immersed, the occupant can use neutral hand controllers (that is, hand-posture sensors) to control various aspects of the simulated environment.

Park, Brian↗

DOE OSTI2026

One Earth Energy FEED Process Design Basis

This report establishes the process design basis for the front-end engineering design (FEED) of a carbon capture and injection facility at One Earth Energy's (OEE) ethanol production plant in Gibson City, Illinois, developed as part of the Illinois Storage Corridor CarbonSAFE Phase III project. The facility is designed to compress and dehydrate up to approximately 458,000 metric tonnes of CO 2 per year, sourced directly from OEE's ethanol fermenters, for permanent injection into a saline aquifer approximately four miles from the plant. At normal operating conditions, the system will process 1,290 metric tonnes of CO 2 per day, assuming 355 operating days per year and an ethanol production rate of 160 million gallons per year. The proposed process trains a multistage centrifugal blower with a five-stage reciprocating compressor, delivering CO 2 to the injection wellhead at up to 1,500 psig. Triethylene glycol (TEG) dehydration, applied after the fourth compression stage, reduces water content to a target of 10 lb/MMscf, well within the 30 lb/MMscf injection limit. Beyond dehydration, no additional treatment is required; trace impurities including oxygen and nitrogen will remain in the injected stream. Key design considerations include the absence of spare cooling tower capacity at the site, necessitating new cooling infrastructure, and the need for a new electrical substation to support large motor loads. The facility is designed for continuous, largely unattended operation, monitored around the clock by existing OEE operations staff. This document serves as the foundational reference for all subsequent detailed engineering activities associated with the OEE CO 2 injection facility.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRSDate not supplied

Exploration Medical Integrated Product Team Clinical Decision Support Market Survey

NASA’s Exploration Medical Integrated Product Team (XMIPT) has identified Clinical Decision Support (CDS) technology as a critical need for future human space exploration. Such technology will support real time diagnosis, monitoring, and treatment of spaceflight medical conditions. The need for such tools and support systems is critical for in-mission clinical decision-making, especially when Earth-based support is unavailable due to communication delays or blackouts. Supporting technologies may or may not involve Artificial Intelligence (AI), and would support astronaut crew with minimal clinical training, or even those with advanced training if they are, for example, in need of a refresher, experiencing multiple stressors, or temporarily overloaded with tasking. This need traces to the Development of Earth Independent Operations Technologies for NASA’s Mars Campaign Office. The CDS Market Survey purpose, methods, outcomes thus far, and near-term steps will be discussed.

Decision support↗

NASA NTRS2016

Exploration Clinical Decision Support System: Medical Data Architecture

The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear dimension biomarkers that enable image content-based retrieval and criteria assessment. In addition, a data mining engine (DME) is applied to cross-sectional adult surveys for predicting occurrence of renal calculi, ranked by statistical significance of demographics and specific food ingestion. In addition to this precursor space flight algorithm training, the DME will utilize a feature-engineering capability for unstructured clinical text classification health discovery. The ECDS backbone is a proposed multi-tier modular architecture providing data messaging protocols, storage, management and real-time patient data access. Technology demonstrations and success metrics will be finalized in FY16.

Biomedical support↗

DOE OSTI2022

Controlling extrapolations of nuclear properties with feature selection

Predictions of nuclear properties far from measured data are inherently inaccurate because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model bias can be directly calculated when experimental data is available, only an estimate can be made in the absence of such measurements. Current approaches to compute the estimated bias quickly lose predictive power when their input variables are taken far from the training region, resulting in uncontrolled uncertainties in applications such as nucleosynthesis simulations. In this letter, we present a novel technique to identify the input variables of machine learning algorithms that can provide robust estimates of model bias. Our process is based on selecting input variables, or features, based on their probability distribution functions across the entire nuclear chart. We illustrate our approach on the problem of quantifying the model bias in nuclear binding energies calculated with Density Functional Theory (DFT). We prove that building model biases with only Z and N as features leads to highly unreliable extrapolations. Conversely, we show that proper feature selection can systematically improve theoretical predictions without increasing uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning

We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained to predict a binary outcome constructed from reported suicide, suicide attempt, and overdose diagnoses with varying choices of study design and prediction methodology. Each model used twenty cross-sectional and 190 longitudinal variables observed in eight time intervals covering 7.5 years prior to the time of prediction. Ensembles of seven base models were created and fine-tuned with ten variables expected to change with study design and outcome definition in order to predict suicide and combined outcome in a prospective cohort. The ensemble models achieved c-statistics of 0.73 on 2-year suicide risk and 0.83 on the combined outcome when predicting on a prospective cohort of ~4.2 M veterans. The ensembles rely on nonlinear base models trained using a matched retrospective nested case-control (Rcc) study cohort and show good calibration across a diversity of subgroups, including risk strata, age, sex, race, and level of healthcare utilization. In addition, a linear Rcc base model provided a rich set of biological predictors, including indicators of suicide, substance use disorder, mental health diagnoses and treatments, hypoxia and vascular damage, and demographics. Similar content being viewed by others

60 APPLIED LIFE SCIENCES↗

NASA NTRS1975

X-ray astronomy in the Uhuru epoch and beyond /Newton Lacy Pierce Prize Lecture/

A review of results from the Uhuru satellite is presented. An intensive treatment of two subjects is given, rather than a broad review. First, Cyg X-1, a stellar X-ray source and a candidate for a black hole, is discussed; second, the X-ray source in the Perseus cluster of galaxies, which may be a cloud of hot intergalactic gas, is treated. In both cases, the train of logic used in establishing the nature of these objects is presented and evaluated. For both, while alternative explanations cannot be completely eliminated, they become more difficult to sustain when examined in detail, suggesting that the candidate explanations are more likely correct.

Kellogg, E. M.↗

NASA NTRS1996

Nonlinear Response of Layer Growth Dynamics in the Mixed Kinetics-Bulk-Transport Regime

In situ high-resolution interferometry on horizontal facets of the protein lysozyme reveal that the local growth rate R, vicinal slope p, and tangential (step) velocity v fluctuate by up to 80% of their average values. The time scale of these fluctuations, which occur under steady bulk transport conditions through the formation and decay of step bunches (macrosteps), is of the order of 10 min. The fluctuation amplitude of R increases with growth rate (supersaturation) and crystal size, while the amplitude of the v and p fluctuations changes relatively little. Based on a stability analysis for equidistant step trains in the mixed transport-interface-kinetics regime, we argue that the fluctuations originate from the coupling of bulk transport with nonlinear interface kinetics. Furthermore, step bunches moving across the interface in the direction of or opposite to the buoyancy-driven convective flow increase or decrease in height, respectively. This is in agreement with analytical treatments of the interaction of moving steps with solution flow. Major excursions in growth rate are associated with the formation of lattice defects (striations). We show that, in general, the system-dependent kinetic Peclet number, Pe(sub k) , i.e., the relative weight of bulk transport and interface kinetics in the control of the growth process, governs the step bunching dynamics. Since Pe(sub k) can be modified by either forced solution flow or suppression of buoyancy-driven convection under reduced gravity, this model provides a rationale for the choice of specific transport conditions to minimize the formation of compositional inhomogeneities under steady bulk nutrient crystallization conditions.

Vekilov, Peter G.↗

DOE OSTI2025

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1987

Identification and proposed control of helicopter transmission noise at the source

Helicopter cabin interiors require noise treatment which is expensive and adds weight. The gears inside the main power transmission are major sources of cabin noise. Work conducted by the NASA Lewis Research Center in measuring cabin interior noise and in relating the noise spectrum to the gear vibration of the Army OH-58 helicopter is described. Flight test data indicate that the planetary gear train is a major source of cabin noise and that other low frequency sources are present that could dominate the cabin noise. Companion vibration measurements were made in a transmission test stand, revealing that the single largest contributor to the transmission vibration was the spiral bevel gear mesh. The current understanding of the nature and causes of gear and transmission noise is discussed. It is believed that the kinematical errors of the gear mesh have a strong influence on that noise. The completed NASA/Army sponsored research that applies to transmission noise reduction is summarized. The continuing research program is also reviewed.

Coy, John J.↗

NASA NTRS1988

Identification and proposed control of helicopter transmission noise at the source

Coy, John J.↗

DOE OSTI2025

A physics-constrained deep learning treatment of runaway electron dynamics

An adjoint formulation leveraging a physics-informed neural network (PINN) is employed to advance the density moment of a runaway electron (RE) distribution forward in time. A distinguishing feature of this approach is that once the adjoint problem is solved, its solution can be used to project the RE density forward in time for an arbitrary initial momentum space distribution of REs. Furthermore, by employing a PINN, a parametric solution to the adjoint problem can be learned. Thus, once trained, this adjoint-deep learning framework is able to efficiently project the RE density forward in time across various plasma conditions while still including a fully kinetic description of RE dynamics. As an example application, the temporal evolution of the density of primary electrons is studied, with particular emphasis on evaluating the decay of a RE population when below threshold. Predictions from the adjoint-deep learning framework are found to be in good agreement with a traditional relativistic electron Fokker–Planck solver, for several distinct initial conditions, and across an array of physics parameters. Once trained, the PINN thus provides a means of generating RE density time histories with exceptionally low online execution time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2020

Gila Water Resources III - Modeling the Impacts of Post-fire Restoration Methods on Vegetation Recovery in the Gila National Forest

In recent years, wildfires in New Mexico’s Gila National Forest have become increasingly common and more severe. Wildfires can have powerful impacts on hydrology and soil stability, including erosion, flooding, and debris-flows that threaten lives and infrastructure downstream. Vegetation restoration treatments like seeding and mulching can mitigate these effects and facilitate ecosystem recovery. Understanding the effectiveness of various restoration methods is vital to planning a cost-effective and successful post-fire recovery strategy. The immediate response to a fire on US Forest Service land is coordinated by a Burned Area Emergency Response (BAER) team, a group responsible for mitigating immediate post-fire risks to human life, property, and critical natural and cultural resources. This study created a proof-of-concept methodology for a decision-support tool designed to help BAER teams identify the restoration treatments most likely to succeed in a given burned area. Leveraging random forest regression, Google Earth Engine, and Landsat 7 and 8 Earth observations, this study modeled vegetation recovery after the 2013 Silver Fire for seeded areas, seeded/mulched areas, and untreated areas. Treatment type and initial burn severity were the largest drivers of vegetation recovery across the landscape. Seeded/mulched areas showed higher recovery levels than untreated areas three months post-fire, but by four years post-fire, treated and untreated areas displayed similar recovery levels. To produce a robust predictive tool for the Gila National Forest, the model should be trained on many more fires and incorporate post-fire weather conditions into the process. Such a model will help partners ensure efficient resource use and plan effective post-fire restoration strategies.

DEVELOP Project Summary↗

NASA NTRS1993

Design and implementation of a pilot orientation program for new NASA engineering employees

This paper describes the design and field testing of an orientation program for new employees of NASA Lewis Research Center's Engineering Directorate. A group of new employees designed the program using a series of TQM analysis techniques. The program objectives were: provide consistent treatment for new employees; assist management and clerical staff with their responsibility for orientation; introduce the employee to as many facets of the organization as possible; allow the employee to feel like a member of the organization as early as possible; maximize the use of existing services; and use up-to-date information. The major aspects of the program included: training of management and clerical staff; lab tours and briefings describing the organization; shepherding, using senior employees as shepherds; a handbook of information about the center and the directorate; a package of information about northeast Ohio; and social activities involving the new employees and shepherds. The program was tested on a pilot group of six new employees over a four month period and was considered to be highly successful by both the employees and management. Aspects of the program have subsequently been adopted for center-wide use.

Graham, Ronald E.↗

NASA NTRS2013

Design Constraints Regarding The Use Of Fluids In Emergency Medical Systems For Space Flight

The Exploration Medical Capability Project of the Human Research Program is tasked with identifying, investigating and addressing gaps existing gaps in either knowledge or technology that need to be addressed in order to enable safer exploration missions. There are several gaps that involve treatment for emergency medical situations. Some of these treatments involve the handling of liquids in the spacecraft environment which involve gas-liquid mixtures handling, dissolution chemistry and thermal issues. Some of the recent technology efforts include the Intravenous fluid generation (IVGEN) experiment, the In-Suit Injection System (ISIS) experiment, and medical suction. Constraints include limited volume, shelf life, handling biohazards, availability of power, crew time and medical training.

McQuillen, John↗