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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The effects of continuum fitting on Lyman-α forest correlations

Correlations of fluctuations of the flux in Lyman-α forests of high-redshift quasars have been observed by the Baryonic Acoustic Oscillation Spectroscopy Survey (BOSS) and the Dark Energy Spectroscopy Instrument (DESI) survey where they have revealed the effects of baryon acoustic oscillations (BAO). In order to fit the correlation functions to a physical model and thereby constrain cosmological parameters, it is necessary to take into account the effects of fitting the observed spectra to a template about which the fluctuations are measured. In this paper we use mock spectra to test the distortion matrix technique that has been used since the final BOSS data release to appropriately distort the models. We show that while percent-level effects on the derived forest bias parameters may be present, the technique works sufficiently well that the determination of the BAO peak position is not affected at the percent level. We introduce modifications in the technique used by DESI that were not in the original applications and suggest further possibilities for improvements.

Lyman alpha forest↗
DOE OSTI2025

Precision Local Burnup Assessment Through Dynamic Peak Fitting in Atom Probe Tomography for Depleted, Enriched, and Irradiated Metallic and Ceramic Fuels

Abstract Burnup estimation in nuclear fuels is vital for evaluating fuel performance, transportation, and safe fuel storage. Accurate assessments of burnup from service period and spent fuels involve tracking the consumption of fissile isotopes of uranium (U) offering a direct insight into energy changes within the fuels especially for thermal spectrum reactors. In current approach, mass spectroscopic technique in atom probe tomography (APT) is utilized for accurate quantification of U isotopes. Quantification of U peaks in mass spectrum is performed on asymmetric shapes due to delayed signals, known as thermal tails, particularly for poorly conducting samples analyzed in laser mode. In this study, we introduce a novel quantification tool for isotopic analysis from APT datasets by developing a fitting algorithm based on shapes of the peaks. A MATLAB-based dynamic peak fitting toolbox is developed and designed to adapt to various peak shapes, ensuring accurate quantification of U isotopes. The effectiveness of this approach is demonstrated in standard Ni-Cr sample, depleted and enriched U samples, and U-based fuels with different burnup levels. The viability of this approach for isotopic quantification is demonstrated on both metallic and ceramic fuels.

Burnup↗
DOE OSTI2021

Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit

ABSTRACT We describe and test the fiducial covariance matrix model for the combined two-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) data set. Using a variety of new ansatzes for covariance modelling and testing, we validate the assumptions and approximations of this model. These include the assumption of Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot noise, galaxy weighting schemes, and other sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness of fit and parameter estimation. The largest impact on best-fitting figure-of-merit arises from the so-called fsky approximation for dealing with finite survey area, which on average increases the χ2 between maximum posterior model and measurement by $3.7{{\ \rm per\ cent}}$ (Δχ2 ≈ 18.9). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for Ωm and σ8 by about $3{{\ \rm per\ cent}}$ and for the dark energy equation-of-state parameter by about $5{{\ \rm per\ cent}}$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron

Abstract New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness over both time and space. In this paper we extend the tools available for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to estimate selection effects at the global level while incorporating both measured and unmeasured heterogeneity among countries. Applying this model to the spread of Omicron in forty countries, we find evidence for very strong but very heterogeneous selection effects. To test whether this heterogeneity is explained by differences in the immune landscape, we considered several measures of vaccination rates and recent population-level infection as covariates, finding moderately strong, statistically significant effects. We also found a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that other region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard consumer-grade computing resources, and will be straightforward to apply to future variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Impact of high invariant-mass Drell-Yan forward-backward asymmetry measurements on SMEFT fits

We study the impact of LHC forward-backward asymmetry (AFB) measurements at high invariant mass in the Drell-Yan process on probes of semileptonic four-fermion operators in the Standard Model effective field theory (SMEFT). In particular, we study whether AFB measurements can resolve degeneracies in the Wilson coefficient parameter space that appear when considering invariant-mass and rapidity measurements alone. We perform detailed fits of the available high-energy and high-luminosity ATLAS and CMS data for both invariant-mass distributions and AFB. While each type of measurement separately exhibits degeneracies, combining them removes these blind spots in some cases. In other situations, it does not, highlighting the importance of incorporating future datasets from other experiments to fully explore this sector of the SMEFT. We investigate the impact of contributions quadratic in the Wilson coefficients on the description of Drell-Yan data and discuss when such terms are important in joint fits of the AFB and invariant-mass data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Practical guide to understanding goodness-of-fit metrics used in chemical state modeling of x-ray photoelectron spectroscopy data by synthetic line shapes using nylon as an example

Chemical state analysis of a sample surface through fitting bell-shaped curves to x-ray photoelectron spectroscopic polymer data is reviewed using nylon to introduce and discuss aspects of data analysis. Different strategies for modeling chemistry in nylon spectra are presented and in so doing, a case is made to include in published science the design logic and implementation in terms of line shapes and optimization parameter constraints between components in a peak model. Imperfections in line shape relative to the true shape for photoemission lines, when compensated for using constraints to optimization parameters, are shown to provide chemical state information about a sample that justify, for peak models constructed with these limitations, metrics for goodness-of-fit different from those expected for pulse-counted data.

Materials Science↗
DOE OSTI2024

Reevaluation of XPS Pt 4f peak fitting: Ti 3s plasmon peak interference and Pt metallic peak asymmetry in Pt@TiO2 system

The structural, electronic, and electrochemical properties of noble metals supported on transition metal oxides, such as Pt nanoparticles (NPs) supported on TiO2 (Pt@TiO2), have been extensively studied for their relevance to energy technologies, including photocatalysis, electrocatalysis, and electrochemical energy conversion. As the need to lower the amount of Pt and other noble metals used in energy conversion systems becomes urgent, it is essential to accurately quantify the loading of these metals and electronic density redistribution between them and their supports. X-ray photoelectron spectroscopy (XPS) is widely used for the identification and quantification of chemical species. In particular, fitting of the Pt 4f spectra for Pt@TiO2 is frequently performed to determine the chemical environment and oxidation state of Pt, which strongly affect the physical behavior and catalytic performance of this system. Here, we show that neglecting contributions due to the Pt surroundings and the asymmetry of the Pt metal peak in the line shape fitting can lead to severe mischaracterization of the oxidation state of Pt. We quantify the effects of background contributions that stem from the TiO2 support and discuss how factoring in the strong asymmetry of Pt 4f doublets, which stems from the shake-up type processes, affects the interpretation of Pt 4f XPS line shape.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Impact of Polymicrobial Infection on Fitness of Streptococcus gordonii In Vivo

Pathogenic microbial ecosystems are often polymicrobial, and interbacterial interactions drive emergent properties of these communities. In the oral cavity, Streptococcus gordonii is a foundational species in the development of plaque biofilms, which can contribute to periodontal disease and, after gaining access to the bloodstream, target remote sites such as heart valves. Here, we used a transposon sequencing (Tn-Seq) library of S. gordonii to identify genes that influence fitness in a murine abscess model, both as a monoinfection and as a coinfection with an oral partner species, Porphyromonas gingivalis. In the context of a monoinfection, conditionally essential genes were widely distributed among functional pathways. Coinfection with P. gingivalis almost completely changed the nature of in vivo gene essentiality. Community-dependent essential (CoDE) genes under the coinfection condition were primarily related to DNA replication, transcription, and translation, indicating that robust growth and replication are required to survive with P. gingivalis in vivo. Interestingly, a group of genes in an operon encoding streptococcal receptor polysaccharide (RPS) were associated with decreased fitness of S. gordonii in a coinfection with P. gingivalis. Individual deletion of two of these genes (SGO_2020 and SGO_2024) resulted in the loss of RPS production by S. gordonii and increased susceptibility to killing by neutrophils. P. gingivalis protected the RPS mutants by inhibiting neutrophil recruitment, degranulation, and neutrophil extracellular trap (NET) formation. These results provide insight into genes and functions that are important for S. gordonii survival in vivo and the nature of polymicrobial synergy with P. gingivalis. Furthermore, we show that RPS-mediated immune protection in S. gordonii is dispensable and detrimental in the presence of a synergistic partner species that can interfere with neutrophil killing mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli

There is an urgent need for strategies to discover secondary drugs to prevent or disrupt antimicrobial resistance (AMR), which is causing >700,000 deaths annually. Here, we demonstrate that tetracycline-resistant (Tet R ) Escherichia coli undergoes global transcriptional and metabolic remodeling, including downregulation of tricarboxylic acid cycle and disruption of redox homeostasis, to support consumption of the proton motive force for tetracycline efflux. Using a pooled genome-wide library of single-gene deletion strains, at least 308 genes, including four transcriptional regulators identified by our network analysis, were confirmed as essential for restoring the fitness of Tet R E. coli during treatment with tetracycline. Targeted knockout of ArcA, identified by network analysis as a master regulator of this new compensatory physiological state, significantly compromised fitness of Tet R E. coli during tetracycline treatment. A drug, sertraline, which generated a similar metabolome profile as the arcA knockout strain, also resensitized Tet R E. coli to tetracycline. We discovered that the potentiating effect of sertraline was eliminated upon knocking out arcA, demonstrating that the mechanism of potential synergy was through action of sertraline on the tetracycline-induced ArcA network in the Tet R strain. Our findings demonstrate that therapies that target mechanistic drivers of compensatory physiological states could resensitize AMR pathogens to lost antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗
DOE OSTI2020

Rossi-alpha Uncertainty Quantification by Analytic, Bootstrap, and Sample Methods to Inform Fitting Best Practices

The prompt neutron period (the negative reciprocal of the prompt neutron decay constant) can be estimated using the Rossi-alpha technique that is predicated on fitting Rossi alpha histograms and of interest in nuclear criticality safety and nonproliferation. The histograms are traditionally fit with a one-exponential model; however, recent work has proposed a two-exponential model to account for reflector induced phenomenon. Until recently, the uncertainty quantification for either model was inadequate (inaccurate and demanded large measurement times). Measurement uncertainty quantification by sample and analytic methods was developed and validated in Ref. The purpose of this transaction is to (i) validate a new bootstrap method by comparing bin-by-bin error bar estimates and (ii) demonstrate how to choose bin widths and reset times to optimize precision and accuracy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Hybrid time–frequency domain dual-probe coherent anti-Stokes Raman scattering for simultaneous temperature and pressure measurements in compressible flows via spectral fitting

We demonstrate a hybrid time–frequency spectroscopic method for simultaneous temperature/pressure measurements in nonreacting compressible flows with known gas composition. Hybrid femtosecond–picosecond, pure-rotational coherent anti-Stokes Raman scattering (CARS), with two independent, time-delayed probe pulses, is deployed for single-laser-shot measurements of temperature and pressure profiles along an ∼ <#comment/> 5 -mm line. The theory of dual-probe CARS is presented, along with a discussion of the iterative fitting of experimental spectra. Temperature is obtained from spectra acquired with an early, near-collision-free probe time delay ( τ <#comment/> 1 = 0 p s ) and pressure from spectra obtained at probe delays of τ <#comment/> 2 = 150 − <#comment/> 1000 p s , where collisions significantly impact the spectral profile. Unique solutions for temperature and pressure are obtained by iteratively fitting the two spectra to account for small collisional effects observed for the near zero probe delay spectrum. A dual-probe pure-rotational CARS system, in a 1D line-imaging configuration, is developed to demonstrate effectively the simultaneous temperature and pressure profiles recorded along the axial centerline of a highly underexpanded jet. The underexpanded air jet permits evaluation of this hybrid time–frequency domain approach for temperature and pressure measurements across a wide range of low-temperature–low-pressure conditions of interest in supersonic ground-test facilities. Single-laser-shot measurement precisions in both quantities and pressure measurement accuracy are systematically evaluated in the quiet zone upstream of the Mach disk. Precise thermometry approaching 1%−2% is observed in regions of high CARS signal-to-noise ratios. Pressure measurements are optimized at probe time delays where the ratio of the late probe delay to the Raman lifetime exceeds four ( τ <#comment/> 2 / τ <#comment/> R > <#comment/> 4 ). The impact of low-temperature Raman linewidths on CARS pressure measurements is evaluated, and comparisons of CARS pressures obtained with our recent low-temperature pure-rotational Raman linewidth data and extrapolated high-temperature Q -branch linewidths are presented. Considering all measurements with τ <#comment/> 2 / τ <#comment/> R ≥ <#comment/> 4.0 , measured pressures were on average 7.9% of the computed isentropic values with average shot-to-shot deviations representing a combination of instrument noise and fluid fluctuations of 5.0%.

Retter, Jonathan E.↗
DOE OSTI2023

Evaluating E. coli genome‐scale metabolic model accuracy with high‐throughput mutant fitness data

Abstract The Escherichia coli genome‐scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision–recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene‐protein‐reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high‐throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

AK112: Full Waveform Inversion Tomography of Alaska Improves Waveform Fits While Imaging Crustal, Mantle, and Slab Structure

We report a full waveform inversion tomography model of Alaska and the surrounding regions, inferring radially anisotropic shear and isotropic compressional wavespeeds by fitting complete waveforms from 120 regional earthquakes. Our multiscale approach inverted time–frequency phase misfits (maximum period of 100 s), starting with a minimum period of 40 s and ending at 20 s in 7 stages and 112 total iterations. The model (AK112) was evaluated by computing the misfits for 36 independent validation events. We find that misfit reductions were large and equal (∼55%) for both the inversion and validation data sets, providing confidence in the model. AK112 also provides much better waveform fits compared to other reported models for the region, including an isotropic version of itself, highlighting the importance of anisotropy. The model resolves known crustal, upper mantle, and slab structure to depths of 100 km with new detail: sedimentary basins in the Alaskan Shelf, Cook Inlet, and Colville basins, among others; discontinuous lithospheric structure across major terrane boundaries; and subducting slab geometry and back‐arc volcanic sources. In addition to tectonic interpretations, the model enables full waveform simulations for long‐period earthquake ground motions and source characterization (e.g., moment tensor and finite‐fault inversion).

Rodgers, Arthur [Lawrence Livermore National Labor↗
DOE OSTI2022

University of Missouri Research Reactor (MURR) Design Demonstration Element End Fitting Structural Rigidity Analysis

The primary objective of this work is to assess the extent to which the stiffness (measured by means of maximum displacement) of the end fittings in the DDE contributes to the stiffness of the entire element, and how it compares to the equivalent stiffness of the end fittings in the LEU element. Structural analysis of both the LEU element and the DDE were performed using COMSOL 5.3a finite element software. Supporting combs are used on the leading and trailing edges of fuel plates for both the LEU element and the DDE. Therefore, simulations with and without combs are performed as two bounding boundary conditions on the leading edge of the fuel plates. Three types of loads are analyzed in this work: the hydraulic load due to the channel flow disparity-induced pressure differential, the thermal load due to the thermal expansion of the fuel plates, and a point load equal in magnitude to the LEU element’s weight.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Fitting $\overline{\nu}$ for minor Pu isotopes

After successful fitting of prompt $\overline{\nu}$ for 235 U, 238 U, and 239 Pu(n,f) using CGMF, we will move on to the minor plutonium isotopes. Minor isotopes pose a greater challenge both because there is less data available and we do not, by default, have parametrizations in CGMF already. To mitigate these challenges— and provide consistency within CGMF—we will take a stepped approach to the optimization. Continuing from the 239 Pu work, we will then fit 241 Pu(n,f) $\overline{\nu}$, where there is also a number of experimental measurements, keeping consistency between the parameters that are included in the calculation for 239 Pu and 241 Pu. With these parametrizations settled, we can consistently optimize 240 Pu(n,f) $\overline{\nu}$. Following that step, we will move on to 242 Pu(n,f) (and increasing neutron number) and 238 Pu(n,f) (and decreasing neutron number). By including the fissioning systems in this manner, we should be able to minimize the unknown parameters in CGMF. We will possibly also be able to develop systematics for the CGMF input parameters along the Pu isotopic chain. This work can serve as a guide to broadening the reactions available in CGMF. In this short report, we first give an example of how we have updated CGMF to include 240 Pu(n,f) and 242 Pu(n,f), keeping consistency with the current 239 Pu and 241 Pu calculations, but without rigorous optimization (Sec. 2). Then, we will shown in Section 3 what experimental data exist for the various isotopes to provide some insight into why 241 Pu and 239 Pu are used as anchor points.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Fitting $\overline{ν}$ for Minor Pu Isotopes

After successful fitting of prompt ν for 235 U, 238 U, and 239 Pu(n,f) using CGMF, we have moved on to the minor plutonium isotopes. Minor isotopes pose a greater challenge both because there is less data available and we do not, by default, have parametrizations in CGMF already. Initially, we had planned to mitigate these challenges—and provide consistency within CGMF—by taking a stepped approach to the optimization. Continuing from the 239 Pu work, we would then fit 241Pu(n,f) $\overline{ν}$, where there is also a number of experimental measurements, keeping consistency between the parameters that are included in the calculation for 239 Pu and 241 Pu. With these parametrizations settled, we could consistently optimize 240 Pu(n,f) $\overline{ν}$. Following that step, we would move on to 242 Pu(n,f) (and increasing neutron number) and 238 Pu(n,f) (and decreasing neutron number). By including the fissioning systems in this manner, we should be able to minimize the unknown parameters in CGMF. We were also able to develop systematics for the CGMF input parameters along the Pu isotopic chain. However, after studies in the beginning of FY23, where we found reasonable agreement between CGMF and experimental prompt neutron multiplicities for 238−242 Pu, using a compound mass dependent parametrization from, and from discussions with I. Stetcu and P. Talou, we instead performed the evaluation of all five isotopes simultaneously. For all parameters in CGMF, they are either the same for each compound nucleus, or have a dependence on the compound mass. The details of these updates are given in. This report builds upon those details. In this short report, we first give an example of how we have updated CGMF to include 240 Pu(n,f) and 242 Pu(n,f), keeping consistency with the current 239 Pu and 241 Pu calculations, but without rigorous optimization (Sec. 2). Then, we will show in Section 3 what experimental data exist for the various isotopes to provide some insight into why 241 Pu and 239 Pu are used as anchor points. The evaluation is detailed in Section 4, and the comparison between CGMF calculations using the evaluated parameters and other prompt observables besides average neutron multiplicity are discussed in Section 2.2. Finally, we present conclusions and future work in Section 5.

07 ISOTOPE AND RADIATION SOURCES↗