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At least 577 records · Page 32

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NASA NTRS2013

Human-in-the-Loop Operations over Time Delay: NASA Analog Missions Lessons Learned

Teams at NASA have conducted studies of time-delayed communications as it effects human exploration. In October 2012, the Advanced Exploration Systems (AES) Analog Missions project conducted a Technical Interchange Meeting (TIM) with the primary stakeholders to share information and experiences of studying time delay, to build a coherent picture of how studies are covering the problem domain, and to determine possible forward plans (including how to best communicate study results and lessons learned, how to inform future studies and mission plans, and how to drive potential development efforts). This initial meeting s participants included personnel from multiple NASA centers (HQ, JSC, KSC, ARC, and JPL), academia, and ESA. It included all of the known studies, analog missions, and tests of time delayed communications dating back to the Apollo missions including NASA Extreme Environment Mission Operations (NEEMO), Desert Research and Technology Studies (DRATS/RATS), International Space Station Test-bed for Analog Research (ISTAR), Pavilion Lake Research Project (PLRP), Mars 520, JPL Mars Orbiters/Rovers, Advanced Mission Operations (AMO), Devon Island analog missions, and Apollo experiences. Additionally, the meeting attempted to capture all of the various functional perspectives via presentations by disciplines including mission operations (flight director and mission planning), communications, crew, Capcom, Extra-Vehicular Activity (EVA), Behavioral Health and Performance (BHP), Medical/Surgeon, Science, Education and Public Outreach (EPO), and data management. The paper summarizes the descriptions and results from each of the activities discussed at the TIM and includes several recommendations captured in the meeting for dealing with time delay in human exploration along with recommendations for future development and studies to address this issue.

Rader, Steven N.↗

DOE OSTI2021

Machine Intelligence to Detect, Characterise, and Defend against Influence Operations in the Information Environment

Social media has enabled a new era of manipulation in the information and cognitive domains. Deceptive content—misleading, falsified, and fabricated—is routinely created and spread in the modern social media environment with the intent to create confusion and widen political and social divides, and exploit the societal conflict exacerbated by these divides in the real-world (aka physical domain). Such disinformation campaigns demonstrate a threat to the integrity of economic, political, cultural, public health, and national security institutions around the world. In this work we overview our artificial intelligence (AI) capabilities to detect, describe, and defend against information operations on Twitter as an example social platform to understand the influence of misleading and falsified content diffusion and better enable those charged with defending against such manipulation to enable responsive parties to counter it. We first present novel linguistically-informed deep learning (DL) models for misinformation and disinformation detection, and present an in-depth linguistic analysis of psycho-linguistic markers across broad deception categories. We then demonstrate how our models perform in the multilingual and multimodal setting and categorize falsified and misleading content based on the intent to deceive. We also provide a large-scale analysis to describe user behavior and spread patterns while engaging with deceptive content and report novel findings about the immediate diffusion of deceptive content by characterizing the vulnerable sub-populations and their demographics, and explicitly measuring speed and scale of deception spread to uncover who shares deceptive content, how quickly, how much, and how evenly. In addition, we measure audience reactions to misinformation and disinformation at scale, distinguishing the reactions of users identified as bots versus humans. Finally, we take advantage of deep translation and generation models to create unique solutions for real-time defense against digital deception and discuss how to apply causal inference to prescribe and intervene into strategic communications jointly across information, cognitive, and physical domains.

artificial intelligence, deep learning, neural lan↗

NASA NTRS1995

Application of advanced computing techniques to the analysis and display of space science measurements

A prototype system has been developed to aid the experimental space scientist in the display and analysis of spaceborne data acquired from direct measurement sensors in orbit. We explored the implementation of a rule-based environment for semi-automatic generation of visualizations that assist the domain scientist in exploring one's data. The goal has been to enable rapid generation of visualizations which enhance the scientist's ability to thoroughly mine his data. Transferring the task of visualization generation from the human programmer to the computer produced a rapid prototyping environment for visualizations. The visualization and analysis environment has been tested against a set of data obtained from the Hot Plasma Composition Experiment on the AMPTE/CCE satellite creating new visualizations which provided new insight into the data.

Klumpar, D. M.↗

NASA NTRS2019

PL&HA and SPLICE Overview

Precision Landing and Hazard Avoidance (PL&HA)↗

NASA NTRS2019

The SPLICE Project: Continuing NASA Development of GN&C Technologies for Safe and Precise Landing

Guidance, Navigation and Control (GN&C) technologies for precise and safe landing are essential for future robotic science and human exploration missions to solar system destinations with targeted surface locations that pose a signiﬁcant risk to successful landing and subsequent mission operations. These Entry, Descent and Landing (EDL) technologies are a part of the NASA domain called PL&HA (Precision Landing and Hazard Avoidance) and are considered high-priority capabilities within NASA space technology development roadmaps to promote and enable new mission concepts. The SPLICE (Safe & Precise Landing – Integrated Capabilities Evolution) project is a multi-center, multi-directorate NASA project focused on continuing the decade-plus of NASA investments and projects focused on PL&HA technology development and infusion. This paper highlights the GN&C technologies in development within SPLICE, along with the simulation and ﬁeld test plans for validation of the capabilities and Technology Readiness Level (TRL) maturation toward infusion into potential near-term robotic lunar landing missions.

Tse, Teming↗

NASA NTRS2022

m:N Working Group Status Report: Collaboration with Government, Industry, and Academia to Reduce m:N Operational Barriers

This is a status report on the m:N working group that has met three times over the last two years. They have identified barriers by domain, detect and avoid use-cases, and further analysis.

multi-vehicle control↗

DOE OSTI2020

AI-Science for Performance Optimization and Diagnosis of Science Instrument Federations

Next generation of science workflows are expected to be executed over complex federations composed of supercomputers, science instruments, storage systems and networks, with new additions of the edge and cloud systems and services. The sheer complexity of these multi-domain federations makes it hard to manage them and optimize their performance, as small impedance mismatches (that can dynamically develop between systems) could drastically degrade the entire federation performance. Recent proliferation of Software Defined Everything (SDX) technologies combined with containerization frameworks provide custom instruments that can monitor and collect critical measurements at various levels to support diagnoses and performance optimization; but their data too enormous for human operators and analysts to process and generate decisions. Machine Learning (ML) methods that extract critical parameters, relationships and trends from the data offer general solutions. Artificial Intelligence (AI) and ML methods must be custom-developed for these problems based on solid, rigorous foundations, since black-box approaches are often ineffective and unsound.We propose to develop comprehensive AI-Science for the performance of science federations to (i) monitor and control storage, networks, experiments, and computing systems across multiple domains via softwarization layers, at speeds and scales orders of magnitude superior to current practice, (ii) optimally realize and orchestrate complex workflows with high performance by using dynamic state and performance estimation methods, and (iii) aggregate measurements across sites and time to develop infrastructure-level profiles, optimizations and diagnoses using AI-Science based on foundational principles from ML, game theory, and information fusion areas.

Rao, Nageswara↗

NASA NTRS1993

Domain connectivity among systems of overset grids

This progress report describes research performed to achieve algorithmic improvements in the use of overset grids for the computation of unsteady flowfields about geometrically complex and moving component configurations. A hole-map computational method is detailed that reduces computational demand and corresponding demand on human resources. Results indicate that the method is both efficient and flexible for use in complex simulation cases. Tests were performed on shuttle orbiter/external tank, wing/store, and V-22 tilt-rotor configurations. The number of simulated points and the corresponding time on a SGI 4D-210 workstation are presented.

Meakin, Robert L.↗

DOE OSTI2024

An RNA aptamer exploits exosite-dependent allostery to achieve specific inhibition of coagulation factor IXa

Hemostasis relies on a reaction network of serine proteases and their cofactors to form a blood clot. Coagulation factor IXa (protease) plays an essential role in hemostasis as evident from the bleeding disease associated with its absence. RNA aptamers specifically targeting individual coagulation factors have potential as anticoagulants and as probes of the relationship between structure and function. Here, we report X-ray structures of human factor IXa without a ligand bound to the active site either in the apo-form or in complex with an inhibitory aptamer specific for factor IXa. The aptamer binds to an exosite in the catalytic domain and allosterically distorts the active site. Our studies reveal a conformational ensemble of IXa states, wherein large movements of Trp 215 near the active site drive functional transitions between the closed (aptamer-bound), latent (apo), and open (substrate-bound) states. The latent state of the apo-enzyme may bear on the uniquely poor catalytic activity of IXa compared to other coagulation proteases. The exosite, to which the aptamer binds, has been implicated in binding VIIIa and heparin, both of which regulate IXa function. Our findings reveal the importance of exosite-driven allosteric modulation of IXa function and new strategies to rebalance hemostasis for therapeutic gain.

Science & Technology - Other Topics↗

DOE OSTI2025

Geant4 Visualization

Geant4 offers versatile visualization tools to study detector geometry, particle trajectories, and hits. These tools support both interactive and batch modes (e.g., vis.mac). With a unified interface, Geant4 integrates various graphics systems such as G4VisExecutive, OpenGL, Qt, HepRApp, DAWN, VTK, and ToolsSG. Advanced examples, including the ICRP145 Human Phantoms and the gMocren tool, highlight its applications in medical research and simulation and as well as radiation protection and shielding studies. These features make Geant4 a robust framework for exploring particle interactions and supporting domain-specific use cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1992

Data compression of stereopairs

This paper addresses the problem of stereopair data compression. Two fundamentally different techniques for compressing stereopairs are discussed. The first technique, called disparity-compensated transform-domain predictive coding, attempts to minimize the mean-square error between the original stereopair and the compressed stereopair. The second technique, called mixed-resolution coding, is a psychophysically justified technique that exploits known facts about human stereovision to code stereopairs in a subjectively acceptable manner. A method for assessing the quality of compressed stereopairs is also presented. It involves measuring the ability of an observer to perceive depth in coded stereopairs. It is found that observers generally perceived objects to be further away in compressed stereopairs than they did in originals. Finally, the problem of coding stereopairs is considered from a rate-distortion perspective. It is proved that the rate distortion limit for coding stereopairs cannot in general be achieved by a coder that first codes and decodes the right picture sequence independently of the left picture sequence, and then codes and decodes the left picture sequence given the decoded right picture sequence.

Perkins, Michael G.↗

NASA NTRSDate not supplied

A Novel Machine Learning Method for Surface PM2.5 Estimations from Geostationary Satellites

Particulate matter (PM) with a diameter of less or equal to 2.5 μm, known as PM , affects human health as it penetrates the respiratory system. The Environmental Protection Agency (EPA) measures the atmospheric concentration of PM using air quality monitors stationed throughout the Continental United States (CONUS). Such measurements are points on a spatial domain and therefore, might not be representative of the air quality at nearby areas considering that the composition of the atmosphere is highly variable from place to place. Satellite based AOD permits a spatially uniform means of estimating PM and new geostationary satellites provide high temporal and spatial resolution estimation of AOD. However, the concentration of PM is non-linearly dependent on other atmospheric parameters that include relative humidity, temperature, and height of the planetary boundary layer. This information may be estimated at similar spatial and temporal resolutions as AOD from numerical modeling such as from the National Oceanic and Atmospheric Administration’s (NOAA) High Resolution Rapid Refresh (HRRR) model which resolves near real-time atmospheric conditions over the CONUS. The estimation of PM concentration is a multi-parametric problem that considers the effect of temporal dependencies among the different parameters. Deep learning approaches are appropriate for such complex estimation problems as they intrinsically capture relations among multiple non-linear parameters. This study compares deep-learning methods to traditional regression analysis to demonstrate the capabilities of these methods in predicting PM2.5 concentrations. Additionally, a novel ensemble learning approach is employed to identify scientific processes that could further improve the estimation of PM concentration. Utilizing Long Short-Term Memory (LSTM) neural networks, which are suitable for multivariate time series estimation problems as they are capable of learning long-term dependencies, individual models are created for each EPA station and trained on the aforementioned dataset collocated over each station. Individual station models are merged if the model's performance is improved by reducing the root mean squared error (RMSE) metric. This ensemble training method ultimately reduces the RMSE value. Evaluation of these results provide insights into physical processes and related observable parameters that may contribute to PM concentrations. Identified parameters evaluated to be statistically different between the merged and unmerged models are expected to improve overall performance. These new parameters are then utilized for reevaluation of the deep learning methods with an extreme gradient boosting model with an RMSE of 5.5 providing the best results.

George Priftis↗

NASA NTRS2012

The Role of Cis-Lunar Space in Future Global Space Exploration

Cis-lunar space offers affordable near-term opportunities to help pave the way for future global human exploration of deep space, acting as a bridge between present missions and future deep space missions. While missions in cis-lunar space have value unto themselves, they can also play an important role in enabling and reducing risk for future human missions to the Moon, Near-Earth Asteroids (NEAs), Mars, and other deep space destinations. The Cis-Lunar Destination Team of NASA's Human Spaceflight Architecture Team (HAT) has been analyzing cis-lunar destination activities and developing notional missions (or "destination Design Reference Missions" [DRMs]) for cis-lunar locations to inform roadmap and architecture development, transportation and destination elements definition, operations, and strategic knowledge gaps. The cis-lunar domain is defined as that area of deep space under the gravitational influence of the earth-moon system. This includes a set of earth-centered orbital locations in low earth orbit (LEO), geosynchronous earth orbit (GEO), highly elliptical and high earth orbits (HEO), earth-moon libration or "Lagrange" points (E-ML1 through E-ML5, and in particular, E-ML1 and E-ML2), and low lunar orbit (LLO). To help explore this large possibility space, we developed a set of high level cis-lunar mission concepts in the form of a large mission tree, defined primarily by mission duration, pre-deployment, type of mission, and location. The mission tree has provided an overall analytical context and has helped in developing more detailed design reference missions that are then intended to inform capabilities, operations, and architectures. With the mission tree as context, we will describe two destination DRMs to LEO and GEO, based on present human space exploration architectural considerations, as well as our recent work on defining mission activities that could be conducted with an EML1 or EML2 facility, the latter of which will be an emphasis of this paper, motivated in part by recent interest expressed at the Global Exploration Roadmap Stakeholder meeting. This paper will also explore the links between this HAT Cis-Lunar Destination Team analysis and the recently released ISECG Global Exploration Roadmap and other potential international considerations, such as preventing harmful interference to radio astronomy observations in the shielded zone of the moon.

Bobskill, Marianne R.↗

DOE OSTI2021

Two human antibodies to a meningococcal serogroup B vaccine antigen enhance binding of complement Factor H by stabilizing the Factor H binding site

Microbial pathogens bind host complement regulatory proteins to evade the immune system. The bacterial pathogen Neisseria meningitidis, or meningococcus, binds several complement regulators, including human Factor H (FH). FH binding protein (FHbp) is a component of two licensed meningococcal vaccines and in mice FHbp elicits antibodies that inhibit binding of FH to FHbp, which defeat the bacterial evasion mechanism. However, humans vaccinated with FHbp develop antibodies that enhance binding of FH to the bacteria, which could limit the effectiveness of the vaccines. In the present study, we show that two vaccine-elicited antibody fragments (Fabs) isolated from different human subjects increase binding of complement FH to meningococcal FHbp by ELISA. The two Fabs have different effects on the kinetics of FH binding to immobilized FHbp as measured by surface plasmon resonance. The 1.7- and 2.0-Å resolution X-ray crystal structures of the Fabs in complexes with FHbp illustrate that the two Fabs bind to similar epitopes on the amino-terminal domain of FHbp, adjacent to the FH binding site. Superposition models of ternary complexes of each Fab with FHbp and FH show that there is likely minimal contact between the Fabs and FH. Collectively, the structures reveal that the Fabs enhance binding of FH to FHbp by altering the conformations and mobilities of two loops adjacent to the FH binding site of FHbp. In addition, the 1.5 Å-resolution structure of one of the isolated Fabs defines the structural rearrangements associated with binding to FHbp. The FH-enhancing human Fabs, which are mirrored in the human polyclonal antibody responses, have important implications for tuning the effectiveness of FHbp-based vaccines.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

D614G Spike Mutation Increases SARS CoV-2 Susceptibility to Neutralization

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein acquired a D614G mutation early in the pandemic that confers greater infectivity and is now the globally dominant form. To determine whether D614G might also mediate neutralization escape that could compromise vaccine efficacy, sera from spike-immunized mice, nonhuman primates, and humans were evaluated for neutralization of pseudoviruses bearing either D614 or G614 spike. In all cases, the G614 pseudovirus was moderately more susceptible to neutralization. The G614 pseudovirus also was more susceptible to neutralization by receptor-binding domain (RBD) monoclonal antibodies and convalescent sera from people infected with either form of the virus. Here, negative stain electron microscopy revealed a higher percentage of the 1-RBD “up” conformation in the G614 spike, suggesting increased epitope exposure as a mechanism of enhanced vulnerability to neutralization. Based on these findings, the D614G mutation is not expected to be an obstacle for current vaccine development.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Self-inhibited State of Venezuelan Equine Encephalitis Virus (VEEV) nsP2 Cysteine Protease: A Crystallographic and Molecular Dynamics Analysis

The Venezuelan equine encephalitis virus (VEEV) belongs to the Togaviridae family and is pathogenic to both humans and equines. The VEEV non-structural protein 2 (nsP2) is a cysteine protease (nsP2pro) that processes the polyprotein and thus it is a drug target for inhibitor discovery. The atomic structure of the VEEV nsP2 catalytic domain was previously characterized by both X-ray crystallography and computational studies. A modified nsP2pro harboring a N475A mutation in the N terminus was observed to exhibit an unexpected conformation: the N-terminal residues bind to the active site, mimicking binding of a substrate. The large conformational change of the N terminus was assumed to be induced by the N475A mutation, as N475 has an important role in stabilization of the N terminus and the active site. This conformation was first observed in the N475A mutant, but we also found it while determining a crystal structure of the catalytically active nsP2pro containing the wild-type N475 active site residue and K741A/K767A surface entropy reduction mutations. This suggests that the N475A mutation is not a prerequisite for self-inhibition. Here, we describe a high resolution (1.46 Å) crystal structure of a truncated nsP2pro (residues 463–785, K741A/K767A) and analyze the structure further by molecular dynamics to study the active and self-inhibited conformations of nsP2pro and its N475A mutant. A comparison of the different conformations of the N-terminal residues sheds a light on the interactions that play an important role in the stabilization of the enzyme.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Targeted mutagenesis of the herpesvirus fusogen central helix captures transition states

Herpesviruses remain a burden for animal and human health, including the medically important varicella-zoster virus (VZV). Membrane fusion mediated by conserved core glycoproteins, the fusogen gB and the heterodimer gH-gL, enables herpesvirus cell entry. The ectodomain of gB orthologs has five domains and is proposed to transition from a prefusion to postfusion conformation but the functional relevance of the domains for this transition remains poorly defined. Here we describe structure-function studies of the VZV gB DIII central helix targeting residues 526 EHV 528 . Critically, a H527P mutation captures gB in a prefusion conformation as determined by cryo-EM, a loss of membrane fusion in a virus free assay, and failure of recombinant VZV to spread in cell monolayers. Importantly, two predominant cryo-EM structures of gB[H527P] are identified by 3D classification and focused refinement, suggesting they represented gB conformations in transition. These studies reveal gB DIII as a critical element for herpesvirus gB fusion function.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

The roles of SDHAF2 and dicarboxylate in covalent flavinylation of SDHA, the human complex II flavoprotein

Mitochondrial complex II, also known as succinate dehydrogenase (SDH), is an integral-membrane heterotetramer (SDHABCD) that links two essential energy-producing processes, the tricarboxylic acid (TCA) cycle and oxidative phosphorylation. A significant amount of information is available on the structure and function of mature complex II from a range of organisms. However, there is a gap in our understanding of how the enzyme assembles into a functional complex, and disease-associated complex II insufficiency may result from incorrect function of the mature enzyme or from assembly defects. Here, we investigate the assembly of human complex II by combining a biochemical reconstructionist approach with structural studies. We report an X-ray structure of human SDHA and its dedicated assembly factor SDHAF2. Importantly, we also identify a small molecule dicarboxylate that acts as an essential cofactor in this process and works in synergy with SDHAF2 to properly orient the flavin and capping domains of SDHA. This reorganizes the active site, which is located at the interface of these domains, and adjusts the pK a of SDHA R451 so that covalent attachment of the flavin adenine dinucleotide (FAD) cofactor is supported. We analyze the impact of disease-associated SDHA mutations on assembly and identify four distinct conformational forms of the complex II flavoprotein that we assign to roles in assembly and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗