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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A1 Signature pattern and phylogenetic analysis of full-length env genes in 20 hemophiliacs infected with Korean subclade of HIV-1 subtype B

Twenty patients with hemophilia (HP) were diagnosed with HIV-1, one to two years after exposure to domestic clotting factor IX (DCF), in 1989–90. Previous analysis of pol and vif genes confirmed that HIV-1 transmission to 20 HPs occurred through infusion of DCF. In this study, we determined full-length env gene sequences (about 2,550 bp) in 21 HPs, three plasma donors whose plasma were used in DCF production, and 45 local controls. The env gene from frozen stored sera obtained 1–3 years after diagnosis as well as from samples collected years after infection, was amplified by RT-PCR, and subjected to direct sequencing. Phylogenetic analysis revealed that all sequences were subtype B, with 109 sequences from 64 patients (20 HPs, 3 serum donors, 41 local controls, LCs) belonging to the Korean subclade (KSB) and 13 sequences from 5 patients (1HP infected outside Korea, 4 LCs) not in the KSB. Sequences of the env gene from donors O and P plus the 20 HPs comprised two subclusters within KSB. In addition, signature pattern analysis revealed signature nucleotides at 45 positions between the HPs and LCs (P < 0.05). Surprisingly, specific signature nucleotides positions were conserved 100% in clusters O and P only (at 4 and 1 positions, respectively) with none in LCs. Within both clusters, sequence identity was high. These results are consistent with our previous conclusion that these 20 HPs were infected with viruses in the DCF used for treatment. In addition, we found that there are 25 signature pattern residues in amino acids in env gene of KSB distinct from subtype B.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Comparative Genomics of Rumen Butyrivibrio spp. Uncovers a Continuum of Polysaccharide-Degrading Capabilities

Plant polysaccharide breakdown by microbes in the rumen is fundamental to digestion in ruminant livestock. Bacterial species belonging to the rumen genera Butyrivibrio and Pseudobutyrivibrio are important degraders and utilizers of lignocellulosic plant material. These bacteria degrade polysaccharides and ferment the released monosaccharides to yield short-chain fatty acids that are used by the ruminant for growth and the production of meat, milk, and fiber products. Although rumen Butyrivibrio and Pseudobutyrivibrio species are regarded as common rumen inhabitants, their polysaccharide-degrading and carbohydrate-utilizing enzymes are not well understood. In this study, we analyzed the genomes of 40 Butyrivibrio and 6 Pseudobutyrivibrio strains isolated from the plant-adherent fraction of New Zealand dairy cows to explore the polysaccharide-degrading potential of these important rumen bacteria. Comparative genome analyses combined with phylogenetic analysis of their 16S rRNA genes and short-chain fatty acid production patterns provide insight into the genomic diversity and physiology of these bacteria and divide Butyrivibrio into 3 species clusters. Rumen Butyrivibrio bacteria were found to encode a large and diverse spectrum of degradative carbohydrate-active enzymes (CAZymes) and binding proteins. In total, 4,421 glycoside hydrolases (GHs), 1,283 carbohydrate esterases (CEs), 110 polysaccharide lyases (PLs), 3,605 glycosyltransferases (GTs), and 1,706 carbohydrate-binding protein modules (CBM) with predicted activities involved in the depolymerization and transport of the insoluble plant polysaccharides were identified. Butyrivibrio genomes had similar patterns of CAZyme families but varied greatly in the number of genes within each category in the Carbohydrate-Active Enzymes database (CAZy), suggesting some level of functional redundancy. These results suggest that rumen Butyrivibrio species occupy similar niches but apply different degradation strategies to be able to coexist in the rumen.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Pattern ANalytics To Support High-performance Exploitation and Reasoning (PANTHER)

Sandia researchers are developing analytic techniques that efficiently detect patterns in high-volume, noisy, remote sensing and other geospatial data, improving an analysts’ ability to detect possibly off-normal events in complex homeland security, nuclear weapons, and emerging threat environments. High-consequence, national security decisions rely on timely, comprehensive answers to complex questions, yet critical gaps in our approach to these questions remain. PANTHER addresses these gaps through fundamental research on: geospatial-temporal feature extraction via image segmentation and classification; geospatial-temporal graph algorithms and computational geometry; and domain-relevant models of human perception and cognition informing the design of analytic systems. PANTHER’s cross-disciplinary R&D approach uses fundamental science and mathematics to understand how to maximize decision systems through rethinking key aspects of geospatial data analysis. New methods in motion and trajectory analysis support both rapid search for known trajectories as well as rapid clustering and anomaly detection. Thus, the perceptual and visual load on users is reduced by providing pattern analytics with elegant visual cues to spatial and temporal characteristics.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

A unique stylopod patterning mechanism by Shox2 -controlled osteogenesis

Vertebrate appendage patterning is programmed by Hox-TALE factor-bound regulatory elements. However, it remains unclear which cell lineages are commissioned by Hox-TALE factors to generate regional specific patterns and whether other Hox-TALE co-factors exist. In this study, we investigated the transcriptional mechanisms controlled by the Shox2 transcriptional regulator in limb patterning. Harnessing an osteogenic lineage-specific Shox2 inactivation approach we show that despite widespread Shox2 expression in multiple cell lineages, lack of the stylopod observed upon Shox2 deficiency is a specific result of Shox2 loss of function in the osteogenic lineage. ChIP-Seq revealed robust interaction of Shox2 with cis-regulatory enhancers clustering around skeletogenic genes that are also bound by Hox-TALE factors, supporting a lineage autonomous function of Shox2 in osteogenic lineage fate determination and skeleton patterning. Pbx ChIP-Seq further allowed the genome-wide identification of cis-regulatory modules exhibiting co-occupancy of Pbx, Meis and Shox2 transcriptional regulators. Integrative analysis of ChIP-Seq and RNA-Seq data and transgenic enhancer assays indicate that Shox2 patterns the stylopod as a repressor via interaction with enhancers active in the proximal limb mesenchyme and antagonizes the repressive function of TALE factors in osteogenesis.

Ye, Wenduo↗
NASA NTRS1976

Stratification of Landsat data by clustering

Full realization of the potential advantages of the synoptic coverage provided by Landsat will require the development and use of data analysis techniques which take into account the large variation and diversity of patterns found over many Landsat scenes. Stratification of the scene into units which are internally homogeneous is recommended as a first step in the analysis of data for whole or multiple frames of Landsat data. The use of clustering as an objective and efficient method of dividing scenes into areas which are spectrally similar (strata) is discussed and initial results, including classification performances and comparisons of spectral strata with major physical factors, are presented.

Bauer, M. E.↗
DOE OSTI2026

X‑ray Coherent Diffractive Imaging of Large Helium Nanodroplets Doped with Small Molecules

We report the first X-ray coherent diffractive imaging experiment on molecule-doped helium nanodroplets. It complements previous work, where we reported single-shot X-ray coherent diffractive imaging studies of Xe dopant clusters formed in 4He and 3He droplets. These noble gas clusters were used to visualize the impact of rotational excitation of the droplets on the spatial distribution of atomic dopants within the droplets, and to study the differences and connections between quantum and classical droplet rotational motion. Here, we expand our studies to the molecular dopants CF4, CHF3, CH3CN, and SF6, imaged with 1.5 keV photons. We find multiple Bragg spots in the diffraction patterns of molecule-doped droplets with radii of approximately 600 nm, which provide evidence that molecules form elongated clusters with preferential alignment along the angular momentum axis of the 4He droplets, in agreement with our previous results on the aggregation of Xe clusters on quantum vortices. Real-space reconstructions of molecular dopant cluster density profiles are obtained for droplets with smaller radii of approximately 300 nm. The diffuse images suggest the formation of low-density, potentially porous, molecular clusters upon aggregation at T = 0.4 K in 4He droplets. In the normal fluid 3He droplets, molecules aggregate into loose clusters on the droplets' equator, similar to previous observations for Xe atoms. Time-of-flight mass spectra reveal that the doped helium nanodroplet moieties fragment extensively into constituent atomic ions, producing only a small fraction of molecular fragment ions. The findings are discussed in the context of previously proposed schemes to use He droplets as potential tamper materials for ultrafast X-ray imaging experiments.

Feinberg, AlexandraJ↗
DOE OSTI2019

Depth distributions of nitrite reductase ( nirK ) gene variants reveal spatial dynamics of thaumarchaeal ecotype populations in coastal Monterey Bay

Summary Ammonia‐oxidizing archaea (AOA) of the phylum Thaumarchaeota are key players in nutrient cycling, yet large gaps remain in our understanding of their ecology and metabolism. Despite multiple lines of evidence pointing to a central role for copper‐containing nitrite reductase (NirK) in AOA metabolism, the thaumarchaeal nirK gene is rarely studied in the environment. In this study, we examine the diversity of nirK in the marine pelagic environment, in light of previously described ecological patterns of pelagic thaumarchaeal populations. Phylogenetic analyses show that nirK better resolves diversification patterns of marine Thaumarchaeota , compared to the conventionally used marker gene amoA . Specifically, we demonstrate that the three major phylogenetic clusters of marine nirK correspond to the three ‘ecotype’ populations of pelagic Thaumarchaeota . In this context, we further examine the relative distributions of the three variant groups in metagenomes and metatranscriptomes representing two depth profiles in coastal Monterey Bay. Our results reveal that nirK effectively tracks the dynamics of thaumarchaeal ecotype populations, particularly finer‐scale diversification patterns within major lineages. We also find evidence for multiple copies of nirK per genome in a fraction of thaumarchaeal cells in the water column, which must be taken into account when using it as a molecular marker.

Reji, Linta↗
DOE OSTI2022

Hierarchical domain structures associated with oxygen octahedra tilting patterns in lead-free (Bi 1/2 Na 1/2 )TiO 3

Hierarchical domain structures associated with oxygen octahedra tilting patterns were observed in lead-free (Bi 1/2 Na 1/2 )TiO 3 ceramics using aberration-corrected high-resolution transmission electron microscopy (HRTEM). Three types of domains are induced by distinct mechanisms: the 'orientation-domain' is induced at micrometer scale formed by different tilting orientations of the oxygen octahedra, the 'meso-chemical-domain' occurs at a few tens of nanometer scale by chemical composition variation on the A-site in the ABO 3 perovskite structure, and the 'nano-cluster-region' runs across several unit-cells with apparent A-site cation segregation with oxygen vacancies clustering around Na cations. Based on HRTEM amplitude contrast imaging (ACI), the correlation between the oxygen octahedral tilting pattern and compositional non-stoichiometry was established. The role of the hierarchical domain structure associated with the tilting patterns of the oxygen octahedra on the ferroelectric behavior of (Bi 1/2 Na 1/2 )TiO 3 is also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Pattern Discovery in Internet Background Radiation

Internet Background Radiation (IBR) is observed in empty network address spaces. No traffic should arrive there, but it does in overwhelming quantities, gathering evidences of attacks, malwares and misconfigurations. The study of IBR helps to detect spreading network problems, common vulnerabilities and attack trends. However, network traffic data evolves quickly and is of high volume and diversity, i.e., an outstanding big data challenge. When used to assist network security, it also requires the online classification of dynamic streaming data. In this paper, we introduce an AGgregation & Mode (AGM) vector to represent network traffic. The AGM format characterizes IP hosts by extracting aggregated and mode values of IP header fields, and without inspecting payloads. We performed clustering and statistical analysis to explore six months of IBR from 2012 with the AGM mapping. The discovered patterns allow building a classification of IBR, which identifies phenomena that have been actively polluting the Internet for years. The AGM representation is light and tailored for monitoring and pattern discovery. We show that AGM vectors are suitable to analyze large volumes of network traffic: they capture permanent operations, such as long term scanning, as well as bursty events from targeted attacks and short term incidents.

Iglesias, Felix↗
DOE OSTI2018

Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets

Actual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatiotemporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we and that the model choice mostly dominates (24%{40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and Western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Plant genotype and rhizobia strain combinations strongly influence the transcriptome under heavy metal stress conditions in Medicago truncatula

Heavy metals such as cadmium (Cd) and mercury (Hg) pose significant threats to plant health and food safety as they are absorbed from the environment. Legumes are generally considered sensitive to heavy metals but possess standing genetic variation for accumulation and tolerance to toxic ions. We conducted a transcriptomic analysis on hydroponically and soil grown Medicago truncatula plants to investigate gene expression responses to Cd and Hg exposure in roots, leaves, and nodules. By using plant genotypes with varying metal tolerance or accumulation levels, we observed distinct clustering of gene ontologies, indicating tissue-specific, genotype-specific, and metal-specific gene expression patterns. Considering the symbiotic relationship between legumes and nitrogen-fixing bacteria, we further examined plant phenotypes and transcriptomes of plant genotypes with contrasting Hg accumulation levels and inoculated them with high or low Hg-tolerant Sinorhizobium medicae strains that have presence-absence variation for a mercury reductase (Mer) operon. Host plants inoculated with the Hg-tolerant rhizobia strain possessing a Mer operon exhibited less reduction in nodule number and plant biomass. A smaller reduction in iron (Fe) distribution in nodules after Hg stress was measured using X-ray Fluorescence (XRF) imaging. Dual transcriptome (host plant and bacteria) analysis of nodules revealed a remarkable decrease in the number of differentially expressed genes (DEGs) and clustering of gene ontologies in plants inoculated with the Hg-tolerant rhizobia strain, including symbiosis related genes. This finding suggests that the Hg-tolerant rhizobia strain has the potential to mitigate Hg stress in host plants. Furthermore, we observed genotype by-genotype interactions between the high Hg accumulating plant genotype and the Hg-tolerant rhizobia strain. These findings provide insights into enhancing plant resilience in contaminated environments through optimizing legume-rhizobia interactions for heavy metal tolerance.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2016

How Much Global Burned Area Can Be Forecast on Seasonal Time Scales Using Sea Surface Temperatures?

Large-scale sea surface temperature (SST) patterns influence the interannual variability of burned area in many regions by means of climate controls on fuel continuity, amount, and moisture content. Some of the variability in burned area is predictable on seasonal timescales because fuel characteristics respond to the cumulative effects of climate prior to the onset of the fire season. Here we systematically evaluated the degree to which annual burned area from the Global Fire Emissions Database version 4 with small fires (GFED4s) can be predicted using SSTs from 14 different ocean regions. We found that about 48 of global burned area can be forecast with a correlation coefficient that is significant at a p < 0.01 level using a single ocean climate index (OCI) 3 or more months prior to the month of peak burning. Continental regions where burned area had a higher degree of predictability included equatorial Asia, where 92% of the burned area exceeded the correlation threshold, and Central America, where 86% of the burned area exceeded this threshold. Pacific Ocean indices describing the El Nino-Southern Oscillation were more important than indices from other ocean basins, accounting for about 1/3 of the total predictable global burned area. A model that combined two indices from different oceans considerably improved model performance, suggesting that fires in many regions respond to forcing from more than one ocean basin. Using OCI-burned area relationships and a clustering algorithm, we identified 12 hotspot regions in which fires had a consistent response to SST patterns. Annual burned area in these regions can be predicted with moderate confidence levels, suggesting operational forecasts may be possible with the aim of improving ecosystem management.

Chen, Yang↗
DOE OSTI2021

Beyond 4D tracking: using cluster shapes for track seeding

Tracking is one of the most time consuming aspects of event reconstruction at the Large Hadron Collider (LHC) and its high-luminosity upgrade (HL-LHC). Innovative detector technologies extend tracking to four-dimensions by including timing in the pattern recognition and parameter estimation. However, present and future hardware already have additional information that is largely unused by existing track seeding algorithms. The shape of pixel-clusters provides an additional dimension for track seeding that can significantly reduce the combinatorial challenge of track finding. We use neural networks to show that cluster shapes can reduce significantly the rate of fake combinatorical backgrounds while preserving a high efficiency. We demonstrate this using the information in cluster singlets, doublets and triplets. Numerical results are presented with simulations from the TrackML challenge.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Horizontal gene cluster transfer increased hallucinogenic mushroom diversity

Secondary metabolites are a heterogeneous class of chemicals that often mediate interactions between species. The tryptophan-derived secondary metabolite, psilocin, is a serotonin receptor agonist that induces altered states of consciousness. A phylogenetically disjunct group of mushroom-forming fungi in the Agaricales produce the psilocin prodrug, psilocybin. Spotty phylogenetic distributions of fungal compounds are sometimes explained by horizontal transfer of metabolic gene clusters among unrelated fungi with overlapping niches. We report the discovery of a psilocybin gene cluster in three hallucinogenic mushroom genomes, and evidence for its horizontal transfer between fungal lineages. Patterns of gene distribution and transmission suggest that synthesis of psilocybin may have provided a fitness advantage in the dung and late wood-decay fungal niches, which may serve as reservoirs of fungal indole-based metabolites that alter behavior of mycophagous and wood-eating invertebrates. These hallucinogenic mushroom genomes will serve as models in neurochemical ecology, advancing the (bio)prospecting and synthetic biology of novel neuropharmaceuticals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Online Voltage Event Detection Using Synchrophasor Data with Structured Sparsity-Inducing Norms

This paper develops an accurate and computationally efficient data-driven framework to detect voltage events from PMU data streams. It develops an innovative Proximal Bilateral Random Projection (PBRP) algorithm to quickly decompose the PMU data matrix into a low-rank matrix, a row-sparse event-pattern matrix and a noise matrix. Here, the row-sparse pattern matrix significantly distinguishes events from normal behavior. These matrices are then fed into a clustering algorithm to separate voltage events from normal operating conditions. Large-scale numerical study results on real-world PMU data show that the proposed algorithm is computationally more efficient and achieves higher F scores than state-of-the-art benchmarks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

WE-E-BRE-11: New Method to Simulate DNA Damage Using Ionization Cross-Sections and a Geometrical Nucleosome Model

Purpose: To obtain probability distributions of various DNA damage types as a function of the incident electron kinetic energy. Methods: Using Geant4-DNA electron ionization cross-sections, we calculated path length distributions for electrons of energies between 10 eV and 1 MeV, defined as the length between two subsequent interactions. These path lengths were then convolved with probability distributions for the creation of same-strand damage, opposite-strand damage, clustered damage, isolated damage, and same DNA strand target damage. These probability distributions of DNA damage were obtained by a Monte Carlo routine calculating probabilities of interaction in DNA targets inside a nucleosome geometrical model. Results represent the probability of a secondary electron, initially created inside a DNA strand target, of undergoing its next interaction: (1) in the opposite strand (DSB), (2) in the same strand (SSB+), (3) in either the opposite or same-strand (clustered), (4) in the same DNA target (multiple-hit) or (5) more than 10 base pairs away (isolated). Results: Electrons with kinetic energy between 50 and 250 eV have a maximal probability of creating DSB, SSB+, clustered damage and multiple-hits in the same target The probabilities for these damage patterns have values of 2.5%, 4.3%, 6.7% and 5.4%, respectively. Isolated damage is most probable between 700 eV to 900 eV with a probability of 0.2%. Conclusion: We obtained DNA damage probability distributions as a function of electron incident energy. We showed that electrons with kinetic energies between 50 and 250 eV have the highest probability of producing complex forms of DNA damage (DSB, SSB+). We also showed that a double ionization within the same DNA target is the most frequent outcome occurring 5% of the time. It is expected that electron slowing down spectra can be convolved with our formalism to calculate source specific DNA damage patterns. Research grants from governments of Canada and Quebec. PP acknowledges partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290)

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA

Background Adverse Drug Reactions (ADRs) are of great public health concern. FDA-approved drug labeling summarizes ADRs of a drug product mainly in three sections, i.e., Boxed Warning (BW), Warnings and Precautions (WP), and Adverse Reactions (AR), where the severity of ADRs are intended to decrease in the order of BW > WP > AR. Several reported studies have extracted ADRs from labeling documents, but most, if not all, did not discriminate the severity of the ADRs by the different labeling sections. Such a practice could overstate or underestimate the impact of certain ADRs to the public health. In this study, we applied the Medical Dictionary for Regulatory Activities (MedDRA) to drug labeling and systematically analyzed and compared the ADRs from the three labeling sections with a specific emphasis on analyzing serious ADRs presented in BW, which is of most drug safety concern. Results This study investigated New Drug Application (NDA) labeling documents for 1164 single-ingredient drugs using Oracle Text search to extract MedDRA terms. We found that only a small portion of MedDRA Preferred Terms (PTs), 3819 out of 21,920 or 17.42%, were observed in a whole set of documents. In detail, 466/3819 (12.0%) PTs were in BW, 2023/3819 (53.0%) were in WP, and 2961/3819 (77.5%) were in AR sections. We also found a higher overlap of top 20 occurring BW PTs with WP sections compared to AR sections. Within the MedDRA System Organ Class levels, serious ADRs (sADRs) from BW were prevalent in Nervous System disorders and Vascular disorders. A Hierarchical Cluster Analysis (HCA) revealed that drugs within the same therapeutic category shared the same ADR patterns in BW (e.g., nervous system drug class is highly associated with drug abuse terms such as dependence, substance abuse, and respiratory depression). Conclusions This study demonstrated that combining MedDRA standard terminologies with data mining techniques facilitated computer-aided ADR analysis of drug labeling. We also highlighted the importance of labeling sections that differ in seriousness and application in drug safety. Using sADRs primarily related to BW sections, we illustrated a prototype approach for computer-aided ADR monitoring and studies which can be applied to other public health documents.

59 BASIC BIOLOGICAL SCIENCES↗