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At least 469 records · Page 26

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Parallel evaluation of alternative skin barrier models and excised human skin for dermal absorption studies in vitro

Skin permeation is a primary consideration in the safety assessment of cosmetic ingredients, topical drugs, and human users handling veterinary medicinal products. While excised human skin (EHS) remains the ‘gold standard’ for in vitro permeation testing (IVPT) studies, unreliable supply and high cost motivate the search for alternative skin barrier models. In this study, a standardized dermal absorption testing protocol was developed to evaluate the suitability of alternative skin barrier models to predict skin absorption in humans. Under this protocol, side-by-side assessments of a commercially available reconstructed human epidermis (RhE) model (EpiDerm-200-X, MatTek), a synthetic barrier membrane (Strat-M, Sigma-Aldrich), and EHS were performed. The skin barrier models were mounted on Franz diffusion cells and the permeation of caffeine, salicylic acid, and testosterone was quantified. Transepidermal water loss (TEWL) and histology of the biological models were also compared. EpiDerm-200-X exhibited native human epidermis-like morphology, including a characteristic stratum corneum, but had an elevated TEWL as compared to EHS. The mean 6 h cumulative permeation of a finite dose (6 nmol/cm2) of caffeine and testosterone was highest in EpiDerm-200-X, followed by EHS and Strat-M. Salicylic acid permeated most in EHS, followed by EpiDerm-200-X and Strat-M. Altogether, evaluating novel alternative skin barrier models in the manner outlined herein has the potential to reduce the time from basic science discovery to regulatory impact.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

PHASE: Personalized Head-based Automatic Simulation for Electromagnetic properties in 7T MRI

Accurate and individualized human head models are becoming increasingly important for electromagnetic (EM) simulations. These simulations depend on precise anatomical representations to realistically model electric and magnetic field distributions, particularly when evaluating Specific Absorption Rate (SAR) within safety guidelines. State of the art simulations use the Virtual Population due to limited public resources and the impracticality of manually annotating patient data at scale. Here, this paper introduces Personalized Head-based Automatic Simulation for EM properties (PHASE), an automated open-source toolbox that generates high-resolution, patient-specific head models for EM simulations using paired T1-weighted (T1w) magnetic resonance imaging (MRI) and computed tomography (CT) scans with 14 tissue labels. To evaluate the performance of PHASE models, we conduct semi-automated segmentation and EM simulations on 15 real human patients, serving as the gold standard reference. The PHASE model achieved comparable global SAR and localized SAR averaged over 10 grams of tissue (SAR-10g), demonstrating its potential as a promising tool for generating large-scale human model datasets in the future. The code and models of PHASE toolbox have been made publicly available: https://github.com/hrlblab/PHASE.

Deep learning↗

NASA NTRS1998

In-Situ Resource Utilization (ISRU) Development Program

The question "Why In-Situ Resource Utilization (ISRU)?" is addressed in this presentation. The reasons given concentrate on Cost reduction, Mass reduction, Risk reduction, the expansion of human exploration and presence and the enabling of industrial exploitation. A review of the Martian and Lunar resources available for ISRU is presented. Other ISRU concepts (i.e., In-Situ Consumable production (ISCP) and In-Situ Propellant Production (ISPP)) are introduced and further explained. The objectives of a Mars ISRU System Technology (MIST) include (1) the characterization of technology and subsystem performance for mission modeling and technology funding planning, (2) reduce risk and concerns arising from sample return and human missions utilizing ISRU, and (3) demonstrate the environmental suitability of ISRU components/processes and systems. A proof of concept demonstration schedule and a facility overview for MIST is presented.

Sanders, Jerry↗

NASA NTRSDate not supplied

Chimeric Mouse Models for Space Radiation Risk Investigations

Assessment of human health risks associated with space radiation exposure is based largely on the knowledge learned from studies in which animals, mostly rodents, are exposed to high-LET radiation on the ground. It has been recognized that translation of animal results to meaningful implications for human disease can be challenging, particularly for certain risk categories such as the high-LET radiation effects in the central nervous system (CNS). Considering limitations in utilizing non-human primates and clinical studies in humans, chimeric animals can potentially bridge the knowledge gap between rodents and humans. In a chimeric animal, a specific organ or a cell type is replaced with respective human cells that are functional. A number of chimeric mouse models have been developed in the medical research community to study human diseases, and some of the models can potentially be used for NASA applications. For instance, mice engrafted with human hepatocytes, which have been used in studies of genotoxicity from carcinogen exposures, can be used for quantification of space radiation damage. A chimeric brain model, which was shown to perform superiorly in memory and cognitive tests, can also be a candidate for studying the CNS effects of radiation. It has also been reported that mice engrafted with human hematopoietic progenitor cells were exposed to X-rays and high-LET Si ions to investigate the radiation effects in the immune system. In a pilot study, we use PXB mice whose livers contain >90% human cells. These mice are exposed to gamma rays for investigations of DNA damage and transcriptomics changes in the humanized livers. Results obtained from PXB mice will be compared non-engrafted control animals from the same background strain that are exposed to identical conditions. The aim of the study is to determine whether chimeric mouse models are suitable for investigations of space radiation risks.

Honglu Wu↗

NASA NTRSDate not supplied

Chimeric Mouse Models for Space Radiation Risk Investigations

Honglu Wu↗

DOE OSTI2023

Utility of Human In Vitro Data in Risk Assessments of Influenza A Virus Using the Ferret Model

Both in vitro and in vivo models are employed for assessing the pandemic potential of novel and emerging influenza A viruses in laboratory settings, but systematic examinations of how well viral titer measurements obtained in vitro align with results from in vivo experimentation are not frequently performed. We show that certain viral titer measurements following infection of a human bronchial epithelial cell line are positively correlated with viral titers in specimens collected from virus-inoculated ferrets and employ mathematical modeling to identify commonalities between viral infection progression between both models.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2012

NASA Human Health and Performance Strategy

In May 2007, what was then the Space Life Sciences Directorate, issued the 2007 Space Life Sciences Strategy for Human Space Exploration. In January 2012, leadership and key directorate personnel were once again brought together to assess the current and expected future environment against its 2007 Strategy and the Agency and Johnson Space Center goals and strategies. The result was a refined vision and mission, and revised goals, objectives, and strategies. One of the first changes implemented was to rename the directorate from Space Life Sciences to Human Health and Performance to better reflect our vision and mission. The most significant change in the directorate from 2007 to the present is the integration of the Human Research Program and Crew Health and Safety activities. Subsequently, the Human Health and Performance Directorate underwent a reorganization to achieve enhanced integration of research and development with operations to better support human spaceflight and International Space Station utilization. These changes also enable a more effective and efficient approach to human system risk mitigation. Since 2007, we have also made significant advances in external collaboration and implementation of new business models within the directorate and the Agency, and through two newly established virtual centers, the NASA Human Health and Performance Center and the Center of Excellence for Collaborative Innovation. Our 2012 Strategy builds upon these successes to address the Agency s increased emphasis on societal relevance and being a leader in research and development and innovative business and communications practices. The 2012 Human Health and Performance Vision is to lead the world in human health and performance innovations for life in space and on Earth. Our mission is to enable optimization of human health and performance throughout all phases of spaceflight. All HHPD functions are ultimately aimed at achieving this mission. Our activities enable mission success, optimizing human health and productivity in space before, during, and after the actual spaceflight experience of our crews, and include support for ground-based functions. Many of our spaceflight innovations also provide solutions for terrestrial challenges, thereby enhancing life on Earth. Our strategic goals are aimed at leading human exploration and ISS utilization, leading human health and performance internationally, excelling in management and advancement of innovations in health and human system integration, and expanding relevance to life on Earth and creating enduring support and enthusiasm for space exploration.

Davis, Jeffrey R.↗

NASA NTRS2012

NASA Human Health and Performance Strategy

In May 2007, what was then the Space Life Sciences Directorate, issued the 2007 Space Life Sciences Strategy for Human Space Exploration. In January 2012, leadership and key directorate personnel were once again brought together to assess the current and expected future environment against its 2007 Strategy and the Agency and Johnson Space Center goals and strategies. The result was a refined vision and mission, and revised goals, objectives, and strategies. One of the first changes implemented was to rename the directorate from Space Life Sciences to Human Health and Performance to better reflect our vision and mission. The most significant change in the directorate from 2007 to the present is the integration of the Human Research Program and Crew Health and Safety activities. Subsequently, the Human Health and Performance Directorate underwent a reorganization to achieve enhanced integration of research and development with operations to better support human spaceflight and International Space Station utilization. These changes also enable a more effective and efficient approach to human system risk mitigation. Since 2007, we have also made significant advances in external collaboration and implementation of new business models within the directorate and the Agency, and through two newly established virtual centers, the NASA Human Health and Performance Center and the Center of Excellence for Collaborative Innovation. Our 2012 Strategy builds upon these successes to address the Agency's increased emphasis on societal relevance and being a leader in research and development and innovative business and communications practices. The 2012 Human Health and Performance Vision is to lead the world in human health and performance innovations for life in space and on Earth. Our mission is to enable optimization of human health and performance throughout all phases of spaceflight. All HH&P functions are ultimately aimed at achieving this mission. Our activities enable mission success, optimizing human health and productivity in space before, during, and after the actual spaceflight experience of our crews, and include support for ground-‐ based functions. Many of our spaceflight innovations also provide solutions for terrestrial challenges, thereby enhancing life on Earth. Our strategic goals are aimed at leading human exploration and ISS utilization, leading human health and performance internationally, excelling in management and advancement of innovations in health and human system integration, and expanding relevance to life on Earth and creating enduring support and enthusiasm for space exploration.

Davis, Jeffrey R.↗

NASA NTRS2007

Astronaut Risk Levels During Crew Module (CM) Land Landing

The NASA Engineering Safety Center (NESC) is investigating the merits of water and land landings for the crew exploration vehicle (CEV). The merits of these two options are being studied in terms of cost and risk to the astronauts, vehicle, support personnel, and general public. The objective of the present work is to determine the astronaut dynamic response index (DRI), which measures injury risks. Risks are determined for a range of vertical and horizontal landing velocities. A structural model of the crew module (CM) is developed and computational simulations are performed using a transient dynamic simulation analysis code (LS-DYNA) to determine acceleration profiles. Landing acceleration profiles are input in a human factors model that determines astronaut risk levels. Details of the modeling approach, the resulting accelerations, and astronaut risk levels are provided.

Lawrence, Charles↗

NASA NTRS2000

A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays

Recently, quantitative models based on signal detection theory have been successfully applied to the prediction of human accuracy in visual search for a target that differs from distractors along a single attribute (feature search). The present paper extends these models for visual search accuracy to multidimensional search displays in which the target differs from the distractors along more than one feature dimension (conjunction, disjunction, and triple conjunction displays). The model assumes that each element in the display elicits a noisy representation for each of the relevant feature dimensions. The observer combines the representations across feature dimensions to obtain a single decision variable, and the stimulus with the maximum value determines the response. The model accurately predicts human experimental data on visual search accuracy in conjunctions and disjunctions of contrast and orientation. The model accounts for performance degradation without resorting to a limited-capacity spatially localized and temporally serial mechanism by which to bind information across feature dimensions.

Non-NASA Center↗

NASA NTRS2017

New Developments in NASA's Rodent Research Hardware for Conducting Long Duration Biomedical and Basic Research in Space

Animal models, particularly rodents, are the foundation of pre-clinical research to understand human diseases and evaluate new therapeutics, and play a key role in advancing biomedical discoveries both on Earth and in space. The National Research Councils Decadal survey emphasized the importance of expanding NASA's life sciences research to perform long duration, rodent experiments on the International Space Station (ISS) to study effects of the space environment on the musculoskeletal and neurological systems of mice as model organisms of human health and disease, particularly in areas of muscle atrophy, bone loss, and fracture healing. To accomplish this objective, flight hardware, operations, and science capabilities were developed at NASA Ames Research Center (ARC) to enhance science return for both commercial (CASIS) and government-sponsored rodent research. The Rodent Research Project at NASA ARC has pioneered a new research capability on the International Space Station and has progressed toward translating research to the ISS utilizing commercial rockets, collaborating with academia and science industry, while training crewmembers to assist in performing research on orbit. The Rodent Research Habitat provides a living environment for animals on ISS according to standard animal welfare requirements, and daily health checks can be performed using the habitats camera system. Results from these studies contribute to the science community via both the primary investigation and banked samples that are shared in publicly available data repository such as GeneLab. Following each flight, through the Biospecimen Sharing Program (BSP), numerous tissues and thousands of samples will be harvested, and distributed from the Space Life and Physical Sciences (SLPS) to Principal Investigators (PIs) through the Ames Life Science Data Archive (ALSDA). Every completed mission sets a foundation to build and design greater complexity into future research and answer questions about common human diseases. Together, the hardware improvements (enrichment, telemetry sensors, cameras), new capabilities (live animal return), and experience that the Rodent Research team has gained working with principal investigator teams and ISS crew to conduct complex experiments on orbit are expanding capabilities for long duration rodent research on the ISS to achieve both basic science and biomedical research objectives.

Shirazi, Yasaman↗

NASA NTRS1967

Internal models and the human instrument monitor.

Internal models and human instrument monitor for predicting human sampling behavior

PERFORMANCE PREDICTION↗

DOE OSTI2018

Meta-Level Design Guidance and Operator Performance Measures for Hybrid Control Rooms

The purpose of this grant was to refine and test methods to evaluate digital human system interfaces (HSI) for existing largely analog nuclear power plant (NPP) control rooms (CRs). We hypothesized that CR operator performance (CROP) in hybrid NPP CRs will be improved if future digital HSI is designed based on: 1) more robust design guidelines for operator situation awareness (SA) and decision-making (DM); 2) enhanced CROP metrics during HSI evaluation; 3) an ontology for selecting simulation scenarios to evaluate digital HSI; and 4) a model to predict optimal HSI design attributes given CROP objectives. The team conducted numerous nuclear power plant site visits (e.g., to Brown’s Ferry, Palo Verde, Sequoyah and Vogtle) to study control room operations and crisis management and 3 visits to the NRC Chattanooga Training Center. We observed research studies at DC Cook and NRC Chattanooga in collaboration with the Halden Reactor Project. We collected operator performance and workload data in one NPP simulator. A comprehensive human (i.e., CROP) performance literature review was published in Applied Ergonomics. We obtained operator team performance data from CAER to produce our data fusion model and a paper delineating the results have been accepted (revision submitted) in Resilience Engineering and System Safety. We analyzed interview data related to scenario ontology development; a manuscript is still in preparation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Large language model evaluation for high–performance computing software development

We apply AI-assisted large language model (LLM) capabilities of GPT-3 targeting high-performance computing (HPC) kernels for (i) code generation, and (ii) auto-parallelization of serial code in C ++, Fortran, Python and Julia. Our scope includes the following fundamental numerical kernels: AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG, and language/programming models: (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). Kernel implementations are generated using GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code given simple + + prompt variants. To quantify and compare the generated results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. For auto-parallelization, we use ChatGPT interactively giving simple prompts as in a dialogue with another human including simple “prompt engineering” follow ups. Results suggest that correct outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general-purpose Python can benefit from adding language keywords, while Julia prompts perform acceptably well for its Threads and CUDA.jl programming models. Finally, we expect to provide an initial quantifiable point of reference for code generation in each programming model using a state-of-the-art LLM. Overall, understanding the convergence of LLMs, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Automated classification of big X-ray diffraction data using deep learning models

Abstract In current in situ X-ray diffraction (XRD) techniques, data generation surpasses human analytical capabilities, potentially leading to the loss of insights. Automated techniques require human intervention, and lack the performance and adaptability required for material exploration. Given the critical need for high-throughput automated XRD pattern analysis, we present a generalized deep learning model to classify a diverse set of materials’ crystal systems and space groups. In our approach, we generate training data with a holistic representation of patterns that emerge from varying experimental conditions and crystal properties. We also employ an expedited learning technique to refine our model’s expertise to experimental conditions. In addition, we optimize model architecture to elicit classification based on Bragg’s Law and use evaluation data to interpret our model’s decision-making. We evaluate our models using experimental data, materials unseen in training, and altered cubic crystals, where we observe state-of-the-art performance and even greater advances in space group classification.

Chemistry↗

NASA NTRS1997

Human Factors Research Under Ground-Based and Space Conditions

In this session, Session WP2, the discussion focuses on the following topics: Training Astronauts Using Three-Dimensional Visualizations of the International Space Station; Measurement and Validation of Bidirectional Reflectance of Shuttle and Space Station Materials for Computerized Lighting Models; Effects of Environmental Color on Mood and Performance of Astronauts in ISS; Psychophysical Measures of Motion and Orientation, Implications for Human Interface Design; and the Sopite Syndrome Revisited, Drowsiness and Mood Changes in Student Aviators.

Source record↗

DOE OSTI2021

Attend and Decode: 4D fMRI Task State Decoding Using Attention Models

Source code for Brain Attend and Decode paper. Functional magnetic resonance imaging (fMRI) is a neuroimaging modality that captures the blood oxygen level in a subject's brain while the subject either rests or performs a variety of functional tasks under different conditions. Given fMRI data, the problem of inferring the task, known as task state decoding, is challenging due to the high dimensionality (hundreds of million sampling points per datum) and complex spatio-temporal blood flow patterns inherent in the data. In this work, we propose to tackle the fMRI task state decoding problem by casting it as a 4D spatiotemporal classification problem. We present a novel architecture called Brain Attend and Decode (BAnD), that uses residual convolutional neural networks for spatial feature extraction and self-attention mechanisms for temporal modeling. We achieve significant performance gain compared to previous works on a 7-task benchmark from the large-scale Human Connectome Project-Young Adult (HCP-YA) dataset. We also investigate the transferability of BAnD's extracted features on unseen HCP tasks, either by freezing the spatial feature extraction layers and retraining the temporal model, or finetuning the entire model. The pre-trained features from BAnD are useful on similar tasks while finetuning them yields competitive results on unseen tasks/conditions.

Ng, BrendaM.↗

NASA NTRS2009

Human Research Program (HRP) Exploration Medical Capability (ExMC) Standing Review Panel (SRP)

The SRP believes strongly that regularly performed in-flight crew assessments are needed in order to identify a change in health status before a medical condition becomes clinically apparent. It is this early recognition in change that constitutes the foundation of the "occupational health model" expounded in the HRP Requirements Document as a key component of the HRP risk mitigation strategy that will enable its objective of "prevention and mitigation of human health and performance risks". A regular crew status examination of physiological and clinical performance is needed. This can be accomplished through instrumented monitoring of routine embedded tasks. The SRP recommends addition of a new gap to address this action under Category 3.0 Mitigate the Risk. This new gap is closely associated with Task 4.19 which addresses the lack of adequate biomedical monitoring capabilities for performing periodic clinical status evaluations and contingency medical monitoring. A corollary to these gaps is the critical emphasis on preventive medicine, not only during pre- and post-flight phases of a mission as is the current practice, but continued into the in-flight phases of exploration class missions.

Cintron, Nitza↗