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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hybridization breaks species barriers in long-term coevolution of a cyanobacterial population

Bacterial species often undergo rampant recombination yet maintain cohesive genomic identity. Ecological differences can generate recombination barriers between species and sustain genomic clusters in the short term. But can these forces prevent genomic mixing during long-term coevolution? Cyanobacteria in Yellowstone hot springs comprise several diverse species that have coevolved for hundreds of thousands of years, providing a rare natural experiment. By analyzing more than 300 single-cell genomes, we show that despite each species forming a distinct genomic cluster, much of the diversity within species is the result of hybridization driven by selection, which has mixed their ancestral genotypes. This widespread mixing is contrary to the prevailing view that ecological barriers can maintain cohesive bacterial species and highlights the importance of hybridization as a source of genomic diversity.

Evolutionary Biology↗
DOE OSTI2025

Microbial Ecology of Permafrost Soils: Populations, Processes, and Perspectives

Permafrost microbial research has flourished in the past decades, due in part to improvements in sampling and molecular techniques, but also the increased focus on the permafrost greenhouse gas feedback to climate change and other ecological processes in high latitude and alpine permafrost soils. Permafrost microorganisms are adapted to these extreme environments and remain active at low temperatures and when resources are limited. They are also an important component of global elemental cycles as they regulate organic matter turnover and greenhouse gas production, particularly as permafrost thaws. Here we review the permafrost microbiology literature coupled with an exploration of its historical aspects, with a particular focus on a new understanding advanced by molecular biology techniques. We further identify knowledge gaps and ways forward to improve our understanding of microbial contributions to ecosystem biogeochemistry of permafrost-affected systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population

This study aims to assess the impact of domain shift on chest X-ray classification accuracy and to analyze the influence of ground truth label quality and demographic factors such as age group, sex, and study year. We used a DenseNet121 model pre-trained MIMIC-CXR dataset for deep learning-based multi-label classification using ground truth labels from radiology reports extracted using the CheXpert and CheXbert Labeler. We compared the performance of the 14 chest X-ray labels on the MIMIC-CXR and Veterans Healthcare Administration chest X-ray dataset (VA-CXR). The validation of ground truth and the assessment of multi-label classification performance across various NLP extraction tools revealed that the VA-CXR dataset exhibited lower disagreement rates than the MIMIC-CXR datasets. Additionally, there were notable differences in AUC scores between models utilizing CheXpert and CheXbert. When evaluating multi-label classification performance across different datasets, minimal domain shift was observed in the unseen VA dataset, except for the label “Enlarged Cardiomediastinum.” The subgroup with the most significant variations in multi-label classification performance was study year. These findings underscore the importance of considering domain shift in chest X-ray classification tasks, paying particular attention to the temporality of the exam. Our study reveals the significant impact of domain shift and demographic factors on chest X-ray classification, emphasizing the need for improved transfer learning and robust model development. Addressing these challenges is crucial for advancing medical imaging research and improving patient care.

chest X-ray image classification↗
DOE OSTI2025

Global interfertility and heterosis in sugar kelp populations: a next step in sugar kelp breeding

Abstract The potential of seaweed aquaculture is restricted by high labor, production and processing costs, leading to low economic viability. Selective breeding can improve yields and cultivation efficiency, thereby decreasing production costs. Until now, genetic resources as input for Saccharina latissimabreeding trials have been sourced strictly locally, due to concerns regarding outplanting genetically exogenous material in local waters. Here we study, for the first time, worldwide interregional fertility of the seaweedS. latissima,in order to assess the potential of including globalS. latissimagenetic resources for selective breeding with regard to heterosis. We quantified the yield (as an indicative aquacultural performance) and morphological traits of intra- and interregionalS. latissimahybrids originating from a broad range of locations in a common garden experiment. Our results show that the practical application of worldwideS. latissimagenetic resources in breeding programs is feasible based on global interfertility. We found a wide morphological diversity of hybrids and observed significant heterosis in interregional hybrids. The degree of heterosis could not be linked to geographic distance. These findings reveal that worldwide genetic resources can considerably contribute toS. latissimabreeding programs and could offer a major next step in improving yields and quality traits.

Biotechnology & Applied Microbiology↗
DOE OSTI2025

Uncertainty quantification for nuclear forensics with population analyses

Although neural networks offer cutting-edge predictive power, their deployment in high-consequence nuclear forensic applications is limited, partly because of their black-box nature. Incorporating robust uncertainty quantification methods into the predictive frameworks of neural networks is progress towards their future deployment in such scenarios. This work integrates uncertainty quantification into neural networks for nuclear reactor core-average burnup estimation from simulated environmental samples. We test two regimes (homogeneous and heterogeneous events) on DeepSets and Set Transformer architectures, we find both quantify predictive uncertainty effectively, but Set Transformer excels in partitioning latent events, offering superior predictive power and more informative uncertainty estimates.

Hatton, Conner [ORNL] (ORCID:0009000804970959)↗
DOE OSTI2024

Comparing the interactions between particulate matter and cloud properties over two populated cities in Texas using WRF-Chem fine-resolution modeling

Accurate modeling of aerosol-cloud interactions is essential for reliable weather and air quality simulations, given their significant impact on precipitation patterns, cloud dynamics, and aerosol distributions. This study employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to examine the impact of enhanced meteorological simulations, achieved through advanced microphysics parameterization supported by data assimilation techniques, on air quality across Texas on August 19 and 20, 2022. We tested four distinct configurations: (1) the Morrison two-moment bulk microphysics scheme, (2) Morrison's with observation nudging, (3) the Spectral Bin Microphysics (SBM), and (4) SBM with observation nudging. While the SBM scheme is known for its detailed representation of aerosol-cloud interactions, our focus was on how improvements in meteorological accuracy translate to more precise air quality simulations. Our findings demonstrated a progressive improvement in simulation accuracy, starting with the Morrison's scheme and further enhanced by adopting the SBM scheme, complemented by incorporating observation nudging. Specifically, the combination of the SBM scheme and the nudging substantially enhanced the model's ability to capture convective precipitation events, as shown by better alignment with NEXRAD radar reflectivity, with R increasing from –0.21 to 0.82, IOA from 0.10 to 0.87, and NMB decreasing from 99% to 34% in Houston. The enhanced meteorology translated into more accurate PM 2.5 concentration simulations, particularly through the more accurate representation of aerosol washout during precipitation events. In Houston, the SBM scheme with nudging improved the model's PM 2.5 simulations significantly, with NMB decreasing from –20% to 5% and IOA improving from 0.43 to 0.61. In San Antonio, improvements were also notable, with NMB improved from –27% to –22%, R increased from 0.48 to 0.82, and IOA increased from 0.66 to 0.86. Furthermore, our results underscore the crucial role of accurate meteorological simulations in refining our understanding of aerosol behaviors in relation to precipitation patterns, directly enhancing the reliability and effectiveness of air quality modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Demonstrating the impact of ro-vibrationally excited H 2 on divertor detachment via population modelling

EDGE2D-EIRENE profiles characteristic for low recycling, high recycling and detached plasmas are postprocessed applying a vibrationally resolved collisional radiative (CR) model based on the Yacora solver to predict excited state densities and thus the molecular Lyman-, Werner- and Fulcher band emission intensities. These emission intensities are compared to predictions from the AMJUEL database standardly used in EIRENE. Lower Fulcher band and higher Lyman- and Werner band emission is predicted by the Yacora model in comparison to AMJUEL suggesting that inconsistent results from model based evaluation of measured spectra are expected depending on which model and molecular emission band is considered. The implications on detachment rate predictions are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Influence of the broadly neutralizing antibody VRC01 on HIV breakthrough virus populations in antibody-mediated prevention trials

In the antibody mediated prevention (AMP) trials, the broadly neutralizing antibody (bNAb) VRC01 demonstrated protective efficacy against susceptible HIV strains. To understand how VRC01 shaped breakthrough infections, deep sequencing was performed on 172 participants (>100,000 gag-Δpol and rev-env-Δnef sequences), at diagnosis and over time, in the placebo and treatment arms of the African (HVTN703/HPTN081; NCT02568215) and Americas/Europe (HVTN704/HPTN085; NCT02716675) cohorts. A high frequency of multilineage infections was detected (38%), including co-infection with both VRC01 sensitive and resistant viruses. This high frequency is largely accounted for by low-abundance lineages. Although VRC01 does not significantly affect the genetic transmission bottleneck compared to placebo, higher VRC01 doses trend towards greater VRC01 neutralization differences among co-infecting lineages. Two-thirds of multilineage infections showed evidence of recombination at the diagnostic timepoint. In the treatment group there is evidence of recombinant viruses preferentially inheriting resistance-associated mutations. This study provides critical insights into viral genetic and antigenic diversity that needs to be targeted to achieve protection, and highlights the role of recombination in facilitating escape.

59 BASIC BIOLOGICAL SCIENCES↗