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At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Assembly bias and local Primordial non-Gaussianity from DESI DR1 quasars

The analysis of the large-scale clustering of quasars (QSO) observed by the Dark Energy Spectroscopic Instrument (DESI) represents a promising avenue for constraining local Primordial non-Gaussianity (PNG), parameterized by f NL . The signal to be constrained is the scale-dependent bias induced in the 2-point clustering of the considered tracer sample. The resulting constraints on f NL , however, are fully degenerate with the local PNG bias parameter b ϕ , dependent on the assembly bias parameter p. Using IllustrisTNG hydrodynamical simulations, we select a QSO sample reflecting the selection criteria and properties of DESI QSOs, and provide a robust prior for p, and thus for b ϕ , building on the findings of Fondi et al. 2024. We find a distribution with mean p̅ ≃ 1.4 with weak redshift dependence, stable to selection noise and consistent with the expected recent merger history typical of quasar-hosting halos. By comparing with the CAMELS simulations we demonstrate that this prior is robust to astrophysical assumptions and cosmic variance. Finally, applying this prior to the DESI DR1 dataset, we derive updated constraints on local PNG, obtaining f NL = -3.3±9.2.

cosmological parameters from LSS↗
DOE OSTI2014

A neural network clustering algorithm for the ATLAS silicon pixel detector

A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

A BAYESIAN METHOD FOR THE INTERCALIBRATION OF SPECTRA IN REVERBERATION MAPPING

Flux calibration of spectra in reverberation mapping (RM) is most often performed by assuming the flux constancy of some specified narrow emission lines, which stem from an extended region that is sometimes partially spatially resolved, in contrast to the point-like broad-line region and the central continuum source. The inhomogeneous aperture geometries used among different observation sets in a joint monitoring campaign introduce systematic deviations to the fluxes of broad lines and central continuum, and intercalibration over these data sets is required. As an improvement to the previous empirical correction performed by comparing the (nearly) contemporaneous observation points, we describe a feasible Bayesian method that obviates the need for (nearly) contemporaneous observations, naturally incorporates physical models of flux variations, and fully takes into account the measurement errors. In particular, it fits all the data sets simultaneously regardless of samplings and makes use of all of the information in the data sets. A Markov Chain Monte Carlo implementation is employed to recover the parameters and uncertainties for intercalibration. Application to the RM data sets of NGC 5548 with joint monitoring shows the high fidelity of our method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Genetic and Functional Diversity Help Explain Pathogenic, Weakly Pathogenic, and Commensal Lifestyles in the Genus Xanthomonas

The genus Xanthomonas has been primarily studied for pathogenic interactions with plants. However, besides host and tissue-specific pathogenic strains, this genus also comprises nonpathogenic strains isolated from a broad range of hosts, sometimes in association with pathogenic strains, and other environments, including rainwater. Based on their incapacity or limited capacity to cause symptoms on the host of isolation, nonpathogenic xanthomonads can be further characterized as commensal and weakly pathogenic. This study aimed to understand the diversity and evolution of nonpathogenic xanthomonads compared to their pathogenic counterparts based on their cooccurrence and phylogenetic relationship and to identify genomic traits that form the basis of a life history framework that groups xanthomonads by ecological strategies. We sequenced genomes of 83 strains spanning the genus phylogeny and identified eight novel species, indicating unexplored diversity. While some nonpathogenic species have experienced a recent loss of a type III secretion system, specifically the hrp2 cluster, we observed an apparent lack of association of the hrp2 cluster with lifestyles of diverse species. We performed association analysis on a large data set of 337 Xanthomonas strains to explain how xanthomonads may have established association with the plants across the continuum of lifestyles from commensals to weak pathogens to pathogens. Presence of distinct transcriptional regulators, distinct nutrient utilization and assimilation genes, transcriptional regulators, and chemotaxis genes may explain lifestyle-specific adaptations of xanthomonads.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Performance Issues of SYRK Implementations in Shared Memory Environments for Edge Cases

The symmetric rank-k update (SYRK) is a level-3 BLAS routine commonly used by many Data Mining/Machine Learning(DM/ML) algorithms such as regression, dimensionality reduction algorithms like PCA, matrix factorization and k-mean clustering. This paper presents a comprehensive analysis of the SYRK routine under popular dense linear algebra libraries such as OpenBLAS, Intel MKL, and BLIS particularly focusing on edge cases of dense matrices (thin or fat shapes) that are common in DM/ML applications. Our work identifies some performance issues of the SYRK routine in multi-threaded shared memory environments for edge cases and discuss matrix dependent modifications for performance improvement.

Hossain, Md Mosharaf↗
DOE OSTI2025

Polyyne production is regulated by the transcriptional regulators PgnC and GacA in Pseudomonas protegens Pf-5

ABSTRACT Polyynes produced by bacteria have promising applications in agriculture and medicine due to their potent antimicrobial activities. Polyyne biosynthetic genes have been identified inPseudomonasandBurkholderia. However, the molecular mechanisms underlying the regulation of polyyne biosynthesis remain largely unknown. In this study, we used a soil bacteriumPseudomonas protegensPf-5, which was recently reported to produce polyyne called protegenin, as a model to investigate the regulation of bacterial polyyne production. Our results show that Pf-5 controls polyyne production at both the pathway-specific level and a higher global level. Mutation ofpgnC, a transcriptional regulatory gene located in the polyyne biosynthetic gene cluster, abolished polyyne production. Gene expression analysis revealed that PgnC directly activates the promoter of polyyne biosynthetic genes. The production of polyyne also requires a global regulator GacA. Mutation ofgacAdecreased the translation of PgnC, which is consistent with the result thatpgnCleader mRNA bound directly to RsmE, an RNA-binding protein negatively regulated by GacA. These results suggest that GacA induces the expression of the PgnC regulator, which in turn activates polyyne biosynthesis. Additionally, the polyyne-producing strain of Pf-5, but not the polyyne-nonproducing strain, could inhibit a broad spectrum of bacteria including both Gram-negative and Gram-positive bacteria. IMPORTANCE Antimicrobial metabolites produced by bacteria are widely used in agriculture and medicine to control plant, animal, and human pathogens. Although bacteria-derived polyynes have been identified as potent antimicrobials for decades, the molecular mechanisms by which bacteria regulate polyyne biosynthesis remain understudied. In this study, we found that polyyne biosynthesis is directly activated by a pathway-specific regulator PgnC, which is induced by a global regulator GacA through the RNA-binding protein RsmE inPseudomonas protegens. To our knowledge, this work is the first comprehensive study of the regulatory mechanisms of bacterial polyyne biosynthesis at both pathway-specific level and global level. The discovered molecular mechanisms can help us optimize polyyne production for agricultural or medical applications.

Biotechnology & Applied Microbiology↗
DOE OSTI2014

Identification and environmental distribution of dcpA encoding the 1,2-dichloropropane-to-propene reductive dehalogenase in organohalide-respiring Chloroflexi

Dehalococcoides mccartyi (Dhc) strains KS and RC grow with 1,2-dichloropropane (1,2-D) as an electron acceptor in enrichment cultures derived from hydrocarbon-contaminated and pristine river sediments, respectively. Transcription, expression, enzymatic and PCR analyses implicated the reductive dehalogenase gene dcpA in 1,2-D dichloroelimination to propene and inorganic chloride. Quantitative real-time PCR (qPCR) analyses demonstrated Dhc cell increase during growth with 1,2-D and suggested that both Dhc strains carried a single dcpA gene copy per genome. Dhc strain RC and strain KS produced 1.8 0.1 x 107 and 1.4 0.5 x 107 cells per mole of propene formed, respectively. The dcpA gene was identified in 1,2-D-to-propene-dechlorinating microcosms established with sediment samples collected from different geographical locations in Europe and North and South America. Clone library analysis revealed two distinct dcpA phylogenetic clusters, both of which the dcpA gene-targeted qPCR assay captured, suggesting the qPCR assay is useful for site assessment and bioremediation monitoring at 1,2-D-contaminated sites.

Padilla-Crespo, Elizabeth↗
DOE OSTI2012

On possibility to observe chiral phase transition in separate fragments of dense baryon matter

Density fluctuations of intranuclear matter suffering collisions with projectile particles are capable to turn into multiquark clusters with chiral symmetry restored. Theoretical analysis of these processes requires an additional taking account of finite-size effects in the region of the chiral phase transition. From the experimental point of view, this method of observation of the chiral phase transition has its inherent advantages due to a relatively moderate number of secondary particles to be registered.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

Atomistic Simulations of Mass and Thermal Transport in Oxide Nuclear Fuels

In this talk we discuss simulations of the mass and thermal transport in oxide nuclear fuels. Redistribution of fission gases such as Xe is closely coupled to nuclear fuel performance. Most fission gases have low solubility in the fuel matrix, specifically the insolubility is most pronounced for large fission gas atoms such as Xe, and as a result there is a significant driving force for segregation of gas atoms to grain boundaries or dislocations and subsequently for nucleation of gas bubbles at these sinks. The first step of the fission gas redistribution is diffusion of individual gas atoms through the fuel matrix to existing sinks, which is governed by the activation energy for bulk diffusion. Fission gas bubbles are then formed by either separate nucleation events or by filling voids that were nucleated at a prior stage; in both cases their formation and latter growth is coupled to vacancy dynamics and thus linked to the production of vacancies via irradiation or thermal events. In order to better understand bulk Xe behavior (diffusion mechanisms) in UO 2±x we first calculate the relevant activation energies using density functional theory (DFT) techniques. By analyzing a combination of Xe solution thermodynamics, migration barriers and the interaction of dissolved Xe atoms with U, we demonstrate that Xe diffusion predominantly occurs via a vacancy-mediated mechanism, though other alternatives may exist in high irradiation fields. Since Xe transport is closely related to diffusion of U vacancies, we have also studied the activation energy for this process. In order to explain the low value of 2.4 eV found for U migration from independent damage experiments (not thermal equilibrium) the presence of vacancy clusters must be included in the analysis. Next a continuum transport model for Xe and U is formulated based on the diffusion mechanisms established from DFT. After combining this model with descriptions of the interaction between Xe and grain boundaries derived from separate atomistic calculations, we simulate Xe redistribution for a few simple microstructures using finite element methods (FEM), as implemented in the MOOSE framework from Idaho National Laboratory. Thermal transport together with the power distribution determines the temperature distribution in the fuel rod and it is thus one of the most influential properties on nuclear fuel performance. The fuel thermal conductivity changes as function of time due to microstructure evolution (e.g. fission gas redistribution) and compositional changes. Using molecular dynamics simulations we have studied the impact of different types of grain boundaries and fission gas bubbles on UO 2 thermal conductivity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗
DOE OSTI2019

Biosynthesis and Emission of Stress-Induced Volatile Terpenes in Roots and Leaves of Switchgrass ( Panicum virgatum L.)

Switchgrass ( Panicum virgatum L.), a perennial C4 grass, represents an important species in natural and anthropogenic grasslands of North America. Its resilience to abiotic and biotic stress has made switchgrass a preferred bioenergy crop. However, little is known about the mechanisms of resistance of switchgrass against pathogens and herbivores. Volatile compounds such as terpenes have important activities in plant direct and indirect defense. Here, we show that switchgrass leaves emit blends of monoterpenes and sesquiterpenes upon feeding by the generalist insect herbivore Spodoptera frugiperda (fall armyworm) and in a systemic response to the treatment of roots with defense hormones. Belowground application of methyl jasmonate also induced the release of volatile terpenes from roots. To correlate the emission of terpenes with the expression and activity of their corresponding biosynthetic genes, we identified a gene family of 44 monoterpene and sesquiterpene synthases (mono- and sesqui-TPSs) of the type-a, type-b, type-g, and type-e subfamilies, of which 32 TPSs were found to be functionally active in vitro. The TPS genes are distributed over the K and N subgenomes with clusters occurring on several chromosomes. Synteny analysis revealed syntenic networks for approximately 30–40% of the switchgrass TPS genes in the genomes of Panicum hallii, Setaria italica , and Sorghum bicolor , suggesting shared TPS ancestry in the common progenitor of these grass lineages. Eighteen switchgrass TPS genes were substantially induced upon insect and hormone treatment and the enzymatic products of nine of these genes correlated with compounds of the induced volatile blends. In accordance with the emission of volatiles, TPS gene expression was induced systemically in response to belowground treatment, whereas this response was not observed upon aboveground feeding of S. frugiperda . Our results demonstrate complex above and belowground responses of induced volatile terpene metabolism in switchgrass and provide a framework for more detailed investigations of the function of terpenes in stress resistance in this monocot crop

Plant Sciences↗
DOE OSTI2016

FIRST SEARCH FOR AN X-RAY–OPTICAL REVERBERATION SIGNAL IN AN ULTRALUMINOUS X-RAY SOURCE

Using simultaneous optical (VLT/FORS2) and X-ray (XMM-Newton) data of NGC 5408, we present the first ever attempt to search for a reverberation signal in an ultraluminous X-ray source (NGC 5408 X-1). The idea is similar to active galactic nucleus broad line reverberation mapping where a lag measurement between the X-ray and the optical flux combined with a Keplerian velocity estimate should enable us to weigh the central compact object. We find that although NGC 5408 X-1's X-rays are variable on a timescale of a few hundred seconds (rms of 9.0 ± 0.5%), the optical emission does not show any statistically significant variations. We set a 3σ upper limit on the rms optical variability of 3.3%. The ratio of the X-ray to the optical variability is an indicator of X-ray reprocessing efficiency. In X-ray binaries, this ratio is roughly 5. Assuming a similar ratio for NGC 5408 X-1, the expected rms optical variability is ≈2%, which is still a factor of roughly two lower than what was possible with the VLT observations in this study. We find marginal evidence (3σ) for optical variability on a ∼24 hr timescale. Our results demonstrate that such measurements can be made, but photometric conditions, low sky background levels, and longer simultaneous observations will be required to reach optical variability levels similar to those of X-ray binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Directly observing the galaxies likely responsible for reionization

We report a new analysis of the Hubble Frontier Fields clusters Abell 2744 and MACS 0416 using wavelet decomposition to remove the cluster light, enabling the detection of highly magnified (>50×) galaxies a factor of 10× fainter in luminosity than previous studies. We find 167 galaxies at z≳6, and with this sample we are able to characterize the UV luminosity function to M{sub UV}=−12.5 at z∼6, −14 at z∼7, and −15 at z∼8. We find a steep faint-end slope (α<−2), and with our improved statistics at the faint end we reduce the fractional uncertainty on α to <2% at z∼6--7 and 4% at z∼8. We also investigate the systematic uncertainty due to the lens modeling by using every available lens model individually and comparing the results; this systematic fractional uncertainty on α is <4% at all redshifts. We now directly observe galaxies in the luminosity regime where some simulations predict a change in the faint-end slope of the luminosity function, yet our results provide statistically very strong evidence against any turnover in the luminosity range probed, more consistent with simulations in which stars form in lower-mass halos. Thus, we find strong support for the extension of the steep luminosity function to M{sub UV}=−13 at z>6, consistent with the number of faint galaxies needed to reionize the universe under standard assumptions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Origin and modal petrography of Luna 24 soils

Petrographic modal analyses of polished grain mounts of fractions in the 20 to 250 micron size range from Luna 24 soil samples are presented and used to infer the nature and relative contributions of source rocks. It is found that more than 90% of the identifiable rock fragments are mare basalts, with about 11% of the soil consisting of the crystalline form. Soil breccias, which make up nearly 10% of the soil, are found to be immature. Electron probe analysis of glass particles reveals principle clusters conforming to anorthosite, anorthositic gabbro and mare basalts. More than half of the soil is composed of monomineralic particles, with pyroxene as the most abundant mineral. It is concluded that 85% of the regolith is derived from local mare basalts and gabbros and about 10% is derived from early cumulates of local mare basalt magma. Highland sources are considered to contribute not more than 3% of the regolith.

Basu, A.↗
NASA NTRS1979

Carbon and nitrogen abundances in red giant stars in the globular cluster 47 Tucanae

The effects of changes in temperature, gravity, overall metal abundance, and carbon and nitrogen abundances have been investigated for model stellar spectra and colors representing globular-cluster giants of moderate metal deficiency. The results are presented in the form of spectral atlases and theoretical color-color diagrams. Using these results, approximate abundances of carbon and nitrogen have been derived for some red giant stars in 47 Tuc, from intermediate- and low-dispersion spectra and from intermediate- and narrow-band photometry. In all the normal giants studied, nitrogen is overabundant by up to about a factor of 5 (the precise value depends on the adopted carbon abundance), with different enhancements for different giants. The observational material is not sufficient to distinguish between a normal carbon abundance and a slight carbon depletion for the giant-branch stars, but carbon appears to be somewhat depleted in stars on the asymptotic giant branch. A most probable value of M/H = -0.8 for the overall cluster metal abundance is suggested from analysis of Stromgren photometry of red horizontal-branch stars.

Dickens, R. J.↗
NASA NTRS1980

The discovery of an O subdwarf in the globular cluster NGC 6712

Spectral data for C49 in the globular cluster NGC 6712 are examined with reference to evolutionary models for low-mass stars that are contracting into white dwarfs. The spectrum of this star is found to be almost identical to that of the first sdO star found in a globular cluster, star A in NGC 6397. Analysis of the spectral data using nonlocal thermodynamic equilibrium models gives surface parameters T not less than 50,000 K, log g = 5.5 plus or minus 0.5, and N(He)/N(H) approximately equal to 0.1. The results are consistent with the models considered.

Remillard, R. A.↗
NASA NTRS1982

Content-addressable read/write memories for image analysis

The commonly encountered image analysis problems of region labeling and clustering are found to be cases of search-and-rename problem which can be solved in parallel by a system architecture that is inherently suitable for VLSI implementation. This architecture is a novel form of content-addressable memory (CAM) which provides parallel search and update functions, allowing speed reductions down to constant time per operation. It has been proposed in related investigations by Hall (1981) that, with VLSI, CAM-based structures with enhanced instruction sets for general purpose processing will be feasible.

Snyder, W. E.↗