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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Transcriptomic Analysis of Arachidonic Acid Pathway Genes Provides Mechanistic Insight into Multi-Organ Inflammatory and Vascular Diseases

Arachidonic acid (AA) metabolites have been associated with several diseases across various organ systems, including the cardiovascular, pulmonary, and renal systems. Lipid mediators generated from AA oxidation have been studied to control macrophages, T-cells, cytokines, and fibroblasts, and regulate inflammatory mediators that induce vascular remodeling and dysfunction. AA is metabolized by cyclooxygenase (COX), lipoxygenase (LOX), and cytochrome P450 (CYP) to generate anti-inflammatory, pro-inflammatory, and pro-resolutory oxidized lipids. As comorbid states such as diabetes, hypertension, and obesity become more prevalent in cardiovascular disease, studying the expression of AA pathway genes and their association with these diseases can provide unique pathophysiological insights. In addition, the AA pathway of oxidized lipids exhibits diverse functions across different organ systems, where a lipid can be both anti-inflammatory and pro-inflammatory depending on the location of metabolic activity. Therefore, we aimed to characterize the gene expression of these lipid enzymes and receptors throughout multi-organ diseases via a transcriptomic meta-analysis using the Gene Expression Omnibus (GEO) Database. In our study, we found that distinct AA pathways were expressed in various comorbid conditions, especially those with prominent inflammatory risk factors. Comorbidities, such as hypertension, diabetes, and obesity appeared to contribute to elevated expression of pro-inflammatory lipid mediator genes. Our results demonstrate that expression of inflammatory AA pathway genes may potentiate and attenuate disease; therefore, we suggest further exploration of these pathways as therapeutic targets to improve outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Partial-wave projection of relativistic three-body amplitudes

We derive the integral equations for partial-wave projected three-body scattering amplitudes, starting from the integral equations for three-body amplitudes developed for lattice QCD analyses. The results, which hold for generic three-body systems of spinless particles, build upon the recently derived partial-wave projected one-particle exchange, a primary component of the relativistic framework proven to satisfy 𝑆 matrix unitarity. We derive simplified expressions for factorizable short-distance interactions, 𝒦 3 , in two equivalent formalisms—one symmetric under particle interchange and one asymmetric. For the asymmetric case, we offer parametrizations useful for amplitude analysis. Finally, we examine toy models for 3⁢𝜋 systems at unphysically heavy pion masses with total isospins 0, 1, and 2.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Yes, No, Maybe So: Human Factors Considerations for Fostering Calibrated Trust in Foundation Models Under Uncertainty

High-stakes analytical environments require analysts to evaluate evidence and generate conclusions to inform critical decisions often under conditions of uncertainty. Probabilistic decision-making based on incomplete or inaccurate information can reduce productivity, compromise national interests, and endanger public safety. Researchers are developing expert systems built on foundation models (FMs) to support analysts’ decision-making processes by enabling human-artificial intelligence (AI) teaming, in part through the quantification and expression of uncertainty information. As FMs continue to mature, it is imperative to correspondingly consider analysts’ needs for appropriately interpreting and using uncertainty information. However, prior research indicates that it remains unclear how analysts engage with FM-generated uncertainty information and the extent to which these interactions influence trust in, and reliance on, expert systems. We plan to review the state of the science and conduct an exploratory, qualitative study to (a) understand how properly communicated uncertainty can foster calibrated trust and appropriate reliance and (b) identify approaches for effectively conveying FM-generated uncertainty information during analytical workflows. We will administer semi-structured interviews with analysts from a specific high-stakes analytical environment to collect their current experiences with job-related uncertainty and their impressions when viewing FM-generated uncertainty information. During the interview protocol, participants will be presented with several different FM outputs and invited to discuss their thoughts and beliefs about the uncertainty information displayed. Participants may provide insights into how trust and reliance may be influenced by uncertainty. The results of this study will help us to better understand how analysts currently interpret and use uncertainty information. Our findings may inform human factors recommendations for effectively conveying uncertainty information to foster calibrated trust in, and appropriate reliance on, expert systems. Interaction designers and FM developers can use this knowledge to enhance human-AI teaming and ensure the responsible deployment of FM-based expert systems in analytical workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Differential Expression of Core Metabolic Functions in Candidatus Altiarchaeum Inhabiting Distinct Subsurface Ecosystems

Candidatus Altiarchaea are widespread across aquatic subsurface ecosystems and possess a highly conserved core genome, yet adaptations of this core genome to different biotic and abiotic factors based on gene expression remain unknown. Here, we investigated the metatranscriptome of two Ca. Altiarchaeum populations that thrive in two substantially different subsurface ecosystems. In Crystal Geyser, a high-CO2 groundwater system in the USA, Ca. Altiarchaeum crystalense co-occurs with the symbiont Ca. Huberiarchaeum crystalense, while in the Muehlbacher sulfidic spring in Germany, an artesian spring high in sulfide concentration, Ca. A. hamiconexum is heavily infected with viruses. We here mapped metatranscriptome reads against their genomes to analyse the in situ expression profile of their core genomes. Out of 537 shared gene clusters, 331 were functionally annotated and 130 differed significantly in expression between the two sites. Main differences were related to genes involved in cell defence like CRISPR-Cas, virus defence, replication, transcription and energy and carbon metabolism. Our results demonstrate that altiarchaeal populations in the subsurface are likely adapted to their environment while influenced by other biological entities that tamper with their core metabolism. We consequently posit that viruses and symbiotic interactions can be major energy sinks for organisms in the deep biosphere.

archaea↗
DOE OSTI2024

Targeted protein degradation systems to enhance Wnt signaling

Molecules that facilitate targeted protein degradation (TPD) offer great promise as novel therapeutics. The human hepatic lectin asialoglycoprotein receptor (ASGR) is selectively expressed on hepatocytes. We have previously engineered an anti-ASGR1 antibody-mutant RSPO2 (RSPO2RA) fusion protein (called SWEETS) to drive tissue-specific degradation of ZNRF3/RNF43 E3 ubiquitin ligases, which achieved hepatocyte-specific enhanced Wnt signaling, proliferation, and restored liver function in mouse models, and an antibody–RSPO2RA fusion molecule is currently in human clinical trials. In the current study, we identified two new ASGR1- and ASGR1/2-specific antibodies, 8M24 and 8G8. High-resolution crystal structures of ASGR1:8M24 and ASGR2:8G8 complexes revealed that these antibodies bind to distinct epitopes on opposing sides of ASGR, away from the substrate-binding site. Both antibodies enhanced Wnt activity when assembled as SWEETS molecules with RSPO2RA through specific effects sequestering E3 ligases. In addition, 8M24-RSPO2RA and 8G8-RSPO2RA efficiently downregulate ASGR1 through TPD mechanisms. These results demonstrate the possibility of combining different therapeutic effects and degradation mechanisms in a single molecule.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Semi-Analytical Hierarchical Bayesian Inference of Nonlinear Model Structure in Stochastic Dynamics: Applied to Compartmental Models of Infectious Diseases

A Bayesian computational framework for parsimonious inference in stochastic nonlinear dynamical systems is presented. This framework enables the concurrent estimation of system states, time-varying parameters, time-invariant parameters, and the optimal sparsity structure of the model parameters. Because differential equation-based models are often simplified mechanistic or phenomenological representations, robust inference from noisy measurement data requires explicit treatment of model error and uncertainty. Model error and time-varying parameters can be represented as random processes, enabling inference while making minimal assumptions about the underlying sources of discrepancy and variability. Adopting stochastic differential equation representations affords the model significant flexibility, but can also render it susceptible to overfitting during statistical inversion, where the inferred model may track noise rather than the underlying signal. To alleviate the effects of overfitting and to enable the discovery of the optimal sparse representation of the time-invariant parameters, a Bayesian sparse learning algorithm is embedded within the framework. This sparse learning framework adopts an approximate hierarchical Bayesian setting defined by a series of semi-analytical expressions. The model structure inference framework is validated using a stochastic compartmental model for tracking and forecasting active cases of an infectious disease. Compartmental models describe population-level infectious disease dynamics through interactions among population fractions grouped by disease state. Mathematically, such models consist of a system of coupled ordinary differential equations. This example adopts an expressive compartmental model that includes multiple possible interactions between disease states, motivated by early uncertainty surrounding COVID-19 reinfection dynamics and their implications for long-term epidemic forecasting. The sparse learning exercise permits the inference of a priori unknown epidemiological dynamics from simulated public health data, discovering the nested compartmental model that optimizes the trade-off between average data-fit and model complexity. It is shown that inducing sparsity among the model parameters eliminates redundant interactions between compartments, equivalently revealing the optimal coupling structure between differential equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

The anaerobic fungus Caecomyces churrovis produces H2 via a non-3 bifurcating NADH-dependent enzyme complex

Anaerobic fungi (AF) decompose lignocellulose-based biomass into fermentable sugars through the production of powerful biomass-degrading enzymes. AF are unusual among fungi in that they generate energy via hydrogenosomes, which are also associated with the release of H2 though yet unknown metabolic mechanisms. In particular, it remains unclear how NAD(P)+ is regenerated within hydrogenosomes and how H2 is formed. Here, we reveal the molecular mechanism for hydrogenosomal H2 production in the AF strain C. churrovis by combining genomic search, proteomic analysis, and enzymology. Our enzyme assays on the large organelle fraction of C. churrovis revealed the activity of H2:NAD+ oxidoreductase but not pyruvate:ferredoxin oxidoreductase activity. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE, NuoF) in C. churrovis, and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified proteins, we found that the assay system consisting of Hyd-Strep and NuoEF-Strep reduced NAD+ with H2. Furthermore, this system formed H2 directly from NADH independent of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is widely conserved among the early-branching AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex in eukaryotes. Moreover, this complex could be a target for controlling AF H2 production and altering fungal metabolism.

fungi↗
DOE OSTI2024

GASNet-EX Specification Collection (Rev. 2024.5.0)

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in emerging exascale systems. It provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). GASNet-EX is an evolution of the popular GASNet communication system, building upon over 20 years of lessons learned, and the primary goals are high performance, interface portability, and expressiveness. The library has been used to implement parallel programming models and libraries such as UPC, UPC++, Fortran coarrays, Legion, Chapel, and many others. This anthology collects together the four separate volumes that currently comprise the GASNet-EX specification, as of the 2024.5.0 release of GASNet-EX.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Thermodynamically consistent Cahn–Hilliard–Navier–Stokes equations using the metriplectic dynamics formalism

Cahn–Hilliard–Navier–Stokes (CHNS) systems describe flows with two-phases, e.g., a liquid with bubbles. Obtaining constitutive relations for general dissipative processes for such systems, which are thermodynamically consistent, can be a challenge. We show how the metriplectic 4-bracket formalism (Morrison and Updike, 2024) achieves this in a straightforward, in fact algorithmic, manner. First, from the noncanonical Hamiltonian formulation for the ideal part of a CHNS system we obtain an appropriate Casimir to serve as the entropy in the metriplectic formalism that describes the dissipation (e.g. viscosity, heat conductivity and diffusion effects). General thermodynamics with the concentration variable and its thermodynamics conjugate, the chemical potential, are included. Having expressions for the Hamiltonian (energy), entropy, and Poisson bracket, we describe a procedure for obtaining a metriplectic 4-bracket that describes thermodynamically consistent dissipative effects. The 4-bracket formalism leads naturally to a general CHNS system that allows for anisotropic surface energy effects. Furthermore, this general CHNS system reduces to cases in the literature, to which we can compare.

Cahn–Hilliard↗
DOE OSTI2025

Environmental matrix and moisture influence soil microbial phenotypes in a simplified porous media incubation

Soil moisture and porosity regulate microbial metabolism by influencing factors, such as system chemistry, substrate availability, and soil connectivity. However, accurately representing the soil environment and establishing a tractable microbial community that limits confounding variables is difficult. Here, we use a reduced-complexity microbial consortium grown in a glass bead porous media amended with chitin to test the effects of moisture and a structural matrix on microbial phenotypes. Leveraging metagenomes, metatranscriptomes, metaproteomes, and metabolomes, we saw that our porous media system significantly altered microbial phenotypes compared with the liquid incubations, denoting the importance of incorporating pores and surfaces for understanding microbial phenotypes in soils. These phenotypic shifts were mainly driven by differences in expression of Streptomyces and Ensifer, which included a significant decrease in overall chitin degradation between porous media and liquid. Our findings suggest that the success of Ensifer in porous media is likely related to its ability to repurpose carbon via the glyoxylate shunt amidst a lack of chitin degradation byproducts while potentially using polyhydroxyalkanoate granules as a C source. We also identified traits expressed by Ensifer and others, including motility, stress resistance, and carbon conservation, that likely influence the metabolic profiles observed across treatments. Together, these results demonstrate that porous media incubations promote structure-induced microbial phenotypes and are likely a better proxy for soil conditions than liquid culture systems. Furthermore, they emphasize that microbial phenotypes encompass not only the multi-enzyme pathways involved in metabolism but also include the complex interactions with the environment and other community members.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Elastic cross section is entanglement entropy

We present universal relations between entanglement entropy, which quantifies the quantum correlation between subsystems, and the cross section, which is the primary observable for high-energy particle scattering, by employing a careful formulation of wave packets for the incoming particles. For 2-to-2 elastic scattering with no initial entanglement and subdividing the system along particle labels, we show that both the Rényi and Tsallis entropies in the final states are directly proportional to the elastic cross section in units of the transverse size for the initial wave packets, which is then interpreted as the elastic scattering probability. The relations do not depend on the underlying dynamics of the quantum field theory and are valid to all orders in coupling strengths. Furthermore, computing quantum correlations between momentum and nonkinematic data leads to entanglement entropies expressed as various semi-inclusive elastic cross sections. Our result gives rise to a novel “area law” for entanglement entropy in a two-body system. Published by the American Physical Society 2025

Low, Ian (ORCID:0000000275709597)↗
DOE OSTI2025

Dual-Phase Malicious User Detection Scheme for IM-OFDMA Systems Using IQ Imbalance

Physical-layer security techniques have contributed to the achievement of various security objectives in an efficient and lightweight manner. Thus, these techniques have been widely considered for limited-resource networks such as Internet of Things networks. Among the different security objectives, malicious user detection by exploiting physical-layer parameters has demonstrated efficient performance. In this work, malicious user detection in the recently proposed index modulation-based orthogonal frequency division multiple access (IM-OFDMA) is addressed. The proposed malicious user detection scheme exploits the hardware impairments, especially the in-phase and quadrature imbalance parameters, for both legitimate and malicious users to design a dual-phase efficient detection scheme. The proposed scheme accounts for the special characteristics of IM-OFDMA transmission that are different from other multiple-access techniques. The performance of the proposed scheme was evaluated considering detection probability and false alarm probability performance metrics. Moreover, closed-form expressions of these metrics were derived for both phases and were validated by Monte Carlo simulation results under different configurations of IM-OFDMA systems.

Alaca, Ozgur [ORNL] (ORCID:0000000153713758)↗
DOE OSTI2025

UnigeneFinder: An Automated Pipeline for Gene Calling From Transcriptome Assemblies Without a Reference Genome

ABSTRACT For most species, transcriptome data are much more readily available than genome data. Without a reference genome, gene calling is cumbersome and inaccurate because of the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared with existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high‐quality reference genomes. These features, coupled with the pipeline’s cross‐platform implementation, focus on automation, and an accessible, user‐friendly interface, make UnigeneFinder a useful tool for many downstream sequence‐based analyses in nonmodel organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high‐performance computing (HPC) systems and personal computers, further reducing barriers to use.

Xue, Bo [Plant Resilience Institute Michigan State↗
DOE OSTI2026

A tissue‐resolved, network‐based transcriptomic framework for abiotic stress responses in sorghum

Developing climate‐resilient crops requires a detailed understanding of stress‐induced gene expression dynamics, as maladaptive responses can compromise their productivity and survival. Sorghum, a globally important cereal with exceptional tolerance to multiple abiotic stresses, provides a powerful system for investigating these dynamics. However, how stress type, tissue specificity, and temporal progression jointly shape transcriptomic responses in crops remains poorly understood. Here, we present a comparative, time‐resolved transcriptomic atlas of sorghum responses to drought, heat, and salinity stress across shoot and root tissues. Integrative analyses revealed that tissue specificity is the dominant determinant of abiotic stress‐induced gene reprogramming across all three stresses. Building on these global comparisons, we focused on heat stress, as it elicited the most coherent and pronounced transcriptional and regulatory responses, enabling deeper network‐level interrogation. Co‐expression network analysis identified tissue‐specific modules enriched for phytohormone‐responsive genes, while gene regulatory network (GRN) mapping and cistrome analyses uncovered transcription factors (TFs) controlling key hub genes within these modules. Together, this study provides a foundational transcriptomic and network‐based resource for dissecting the regulatory architecture of abiotic stress responses in sorghum and offers prioritized candidates for future functional validation and engineering of climate‐resilient crops.

abiotic stress↗
DOE OSTI2024

Platform for Remote Deployment and Training for Enhanced Building Operation Practices (Building Re-Tuning and On-going Commissioning)

While a building’s energy usage is driven largely by its design and use, building operator behavior has a strong influence on its energy consumption. This project developed and piloted a specific, data-driven coaching methodology to help operators understand how they can adjust operations and/or affect no/low-cost repairs or upgrades to their specific building HVAC systems to reduce energy consumption. Named BuildingCoach, the operational optimization method used is based on the Building Re-tuning approach developed by the Pacific Northwest National Laboratory. A building operations analytics market has matured over the past decade, though its potential to affect energy-saving changes has not been fully realized. Training operators to understand the methods for operational optimization with the explicit approach of using building-system performance data is hypothesized to create a more effective, longer lasting result in building energy efficiency, and this strategy is the fundamental premise of this project. With the support of an Industry Advisory Board, the project succeeded in developing materials and recruiting for and delivering three pilot cohorts. Deliverables included twenty-two self-paced training modules (accessed via a Learning Management System) and a web-based platform that includes access to real-time building system data and a repository for building system documentation. The project set out to have 100 participants from 50 buildings in three pilot cohorts. In the end, there were 28 participants from 17 buildings, i.e., a significant shortfall. The first two pilot cohorts had only two buildings in each, and this was partially due to difficulties in deploying the Building Operator Coaching Solution (“the BOCS”), which is technology that extracts the data from the controls network and presents it as prescribed for coaching. In the third cohort, the project team deployed the BOCS successfully to 13 buildings, the methodology was piloted as intended, and numerous opportunities for optimization were identified. The BuildingCoach business plan charts a path to an economically sustainable effort. However, even with a licensing model captured in the final version of the business plan, the scalability is still limited to keeping less than 1,000 buildings affected by 2033. Even so, there are unexplored paths to greater scalability that are being considered. CUNY BPL is working to perpetuate and grow the use of BuildingCoach. As of this writing, about twenty buildings have either been connected or will be connected with operators coached / to be coached in the NYC municipal portfolio, twelve buildings across four campuses in NY State will use BuildingCoach, a NY upstate county wishes for six or seven buildings to participate with the support of funding from NYSERDA, and others have also expressed interest. In the decades to come, there will be an increasing percentage of large and mid-sized buildings that incorporate automated system optimization (ASO), and the building operators’ role will shift to spend more time on maintenance and monitoring. Meanwhile, programs such as BuildingCoach will play a critical role in optimizing operations. And, regardless of the emergence of ASO, operators will still need to understand how their systems operate so that they can monitor them properly. Within that context, BuildingCoach is an important step towards operators’ understanding of efficient building system operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Probabilistic and maximum entropy modeling of chemical reaction systems: Characteristics and comparisons to mass action kinetic models

We demonstrate and characterize a first-principles approach to modeling the mass action dynamics of metabolism. Starting from a basic definition of entropy expressed as a multinomial probability density using Boltzmann probabilities with standard chemical potentials, we derive and compare the free energy dissipation and the entropy production rates. We express the relation between entropy production and the chemical master equation for modeling metabolism, which unifies chemical kinetics and chemical thermodynamics. Because prediction uncertainty with respect to parameter variability is frequently a concern with mass action models utilizing rate constants, we compare and contrast the maximum entropy model, which has its own set of rate parameters, to a population of standard mass action models in which the rate constants are randomly chosen. We show that a maximum entropy model is characterized by a high probability of free energy dissipation rate and likewise entropy production rate, relative to other models. We then characterize the variability of the maximum entropy model predictions with respect to uncertainties in parameters (standard free energies of formation) and with respect to ionic strengths typically found in a cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dynamic security assessment of systems powered only by grid-forming power plants with uncertain dispatch using polynomial vectors

A modern challenge in power engineering is to perform the dynamic security assessment (DSA) of grids that are 100% powered by inverter-based resources (IBRs). Addressing this challenge is difficult because: (i) the dispatch of IBRs can be uncertain as a result of the variability of renewable resources and (ii) they have hard current control limits that cannot be neglected, contrasting synchronous machines. To address this problem, this paper sets forth a framework to conduct DSA of bulk power systems that are 100% powered by grid-forming IBRs. Furthermore, the framework considers that IBR operational conditions are unknown but bounded by a zonotope which is also expressed as a polynomial vector for uncertainty propagation via Dormand–Prince integration. The framework is applied to modified versions of the WSCC 9-bus and IEEE 39-bus grids.

14 SOLAR ENERGY↗
DOE OSTI2025

Factorization for jet production in heavy-ion collisions

We develop an Effective Field Theory approach for jet observables in heavy-ion collisions, where the jet is treated as an open quantum system interacting with a hot and dense QCD medium. Within this framework, we derive a novel factorization formula for inclusive jet production, expressed as a series expansion with an increasing number of radiating subjet functions that encode forward scattering with the Quark-Gluon Plasma, convolved with perturbative matching coefficients. This work provides a systematic framework for computing jet observables at higher order and understanding their non-perturbative aspects, paving the way for future applications in heavy-ion phenomenology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗