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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Rapid kVp switching dual-energy CT in the assessment of urolithiasis in patients with large body habitus: preliminary observations on image quality and stone characterization

Purpose: The purpose of this study was to investigate the image quality (IQ) considerations of rapid kVp switching dual-energy CT (rsDECT) in the assessment of urolithiasis in patients with large body habitus and to evaluate whether it allows stone characterization. Materials and methods: In this IRB-approved, HIPAA compliant retrospective study, 93 consecutive patients (M/F = 72/21, mean age 56.9 years, range 23–83 years) with large body habitus (> 90 kg/198 lbs) who underwent dual-energy (DE) stone protocol CT on a rapid kVp switching DECT scanner between January 2013 and December 2016 were included. Scan acquisition protocol included an initial unenhanced single-energy CT (SECT) scan of KUB followed by targeted DECT in the region of stones. Two readers evaluated both CT data sets (axial 5 mm 120 kVp/140 kVp QC/70 keV monoenergetic, material density water/iodine images and coronal/sagittal 3 mm images) for the assessment of image quality (Scores: 1–4) and characterization of stone composition (reference standard: crystallography). Results: One hundred and five CT examinations were performed in 93 patients (mean body weight 105.12 ± 13.53 kg, range 91–154 kg), and a total of 321 urinary tract calculi (mean size-4.8 ± 3.2 mm, range 1.2–22 mm) were detected. Both SECT and targeted monoenergetic images were of acceptable image quality (mean IQ: 3.77 and 3.83, kappa 0.79 and 0.87 respectively). Material density water and iodine images had lower IQ scores (mean IQ: 2.97 and 3.09 respectively) with image quality deterioration due to severe photon starvation/streak artifacts in 20% (21/105) and 17% (18/105) scans, respectively. Characterization of stone composition into uric acid/non-uric acid stones was achieved in 93.14% (299/321) of calculi (mean size: 4.99 ± 3.3 mm, range 1.2–22 mm), while 7% (22/321) stones could not be characterized (mean size 3.03 ± 1.16 mm, range 1.6–6.4 mm) (p < 0.001). Most common reason for non-characterization was image quality deterioration of the material density iodine images due to severe photon starvation artifacts. On multivariate regression, stone size and patient weight were predictors of stone composition determination on DECT (p < 0.05). The transverse diameter had a weak negative correlation with stone composition determination, but it was not statistically significant. Stone characterization into uric acid vs. non-uric acid stones was accurate in 95% (n = 38/40) of stones in comparison with crystallography. Conclusion: In patients with large body habitus, rsDECT allowed characterization of most calculi (93%) despite image quality deterioration due to photon starvation/streak artifacts in up to 20% of material density images. Stone size and patient weight were predictors of stone composition determination on DECT, and small calculi in very large patients may not be characterized.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

K2-231 b: A Sub-Neptune Exoplanet Transiting a Solar Twin in Ruprecht 147

We identify a sub-Neptune exoplanet (R {sub p} = 2.5 ± 0.2 R{sub ⊕}) transiting a solar twin in the Ruprecht 147 star cluster (3 Gyr, 300 pc, [Fe/H] = +0.1 dex). The ∼81 day light curve for EPIC 219800881 (V = 12.71) from K2 Campaign 7 shows six transits with a period of 13.84 days, a depth of ∼0.06%, and a duration of ∼4 hr. Based on our analysis of high-resolution MIKE spectra, broadband optical and NIR photometry, the cluster parallax and interstellar reddening, and isochrone models from PARSEC, Dartmouth, and MIST, we estimate the following properties for the host star: M {sub ⋆} = 1.01 ± 0.03 M{sub ⊙}, R {sub ⋆} = 0.95 ± 0.03 R{sub ⊙}, and T{sub eff} = 5695 ± 50 K. This star appears to be single based on our modeling of the photometry, the low radial velocity (RV) variability measured over nearly 10 yr, and Keck/NIRC2 adaptive optics imaging and aperture-masking interferometry. Applying a probabilistic mass–radius relation, we estimate that the mass of this planet is M {sub p} = 7 + 5 – 3 M{sub ⊕}, which would cause an RV semi-amplitude of K = 2 ± 1 m s{sup −1} that may be measurable with existing precise RV facilities. After statistically validating this planet with BLENDER, we now designate it K2-231b, making it the second substellar object to be discovered in Ruprecht 147 and the first planet; it joins the small but growing ranks of 22 other planets and three candidates found in open clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

DESI z ≳ 5 Quasar Survey. I. A First Sample of 400 New Quasars at z ~ 4.7–6.6

We report the first results of a high-redshift (z ≳ 5) quasar survey using the Dark Energy Spectroscopic Instrument (DESI). As a DESI secondary target program, this survey is designed to carry out a systematic search and investigation of quasars at 4.8 < z < 6.8. The target selection is based on the DESI Legacy Imaging Surveys (the Legacy Surveys) DR9 photometry, combined with the Pan-STARRS1 data and J-band photometry from public surveys. A first quasar sample has been constructed from the DESI Survey Validation 3 (SV3) and first-year observations until 2022 May. This sample includes more than 400 new quasars at redshift 4.7 ≤ z < 6.6, down to 21.5 magnitude (AB) in the z band, discovered from 35% of the entire target sample. Remarkably, there are 220 new quasars identified at z ≥ 5, more than one-third of existing quasars previously published at this redshift. The observations so far result in an average success rate of 23% at z > 4.7. The current spectral data set has already allowed analysis of interesting individual objects (e.g., quasars with damped Lyα absorbers and broad absorption line features), and statistical analysis will follow the survey's completion. A set of science projects will be carried out leveraging this program, including quasar luminosity function, quasar clustering, intergalactic medium, quasar spectral properties, intervening absorbers, and properties of early supermassive black holes. Additionally, a sample of 38 new quasars at z ~ 3.8–5.7 discovered from a pilot survey in the DESI SV1 is also published in this paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Volumetric analysis and mesh generation of real and artificial microstructural geometries

Producing a viable finite element mesh of realistic microstructural structural geometry is a critical step in analyzing the thermo-mechanical behavior of complex multi-material composites. Advancements in imaging technology such as micro computed tomography have allowed modelers to access high resolution mesoscale geometries for direct numerical simulation. However, converting from voxel based 3D images to usable finite element meshes has been challenging. A robust method including algorithms and software scripts for generating finite element meshes from 3D imaged microstructures is presented in this paper. It includes a routine for inserting cohesive elements around material interfaces to enable modeling of interface properties including delamination and damage. The algorithms and procedures presented in this method leverage currently available software packages for processing surface based geometry into volume based meshes. In addition to converting real geometry from physical imaging systems, algorithms for producing numerically generated and statistically equivalent microstructural geometry are also included. These artificial microstructures can be a valuable resource for modelers when physical specimens do not exist or are limited in quantity: Method establishes a workflow from voxel data to viable finite element mesh including interface information, and Includes a method for synthetic geometry generation based on metrics from real microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Diffusion and perfusion MR parameters to assess preoperative short-course radiotherapy response in locally advanced rectal cancer: a comparative explorative study among Standardized Index of Shape by DCE-MRI, intravoxel incoherent motion- and diffusion kurtosis imaging-derived parameters

Purpose: To assess preoperative short-course radiotherapy (SCR) tumor response in locally advanced rectal cancer (LARC) by means of Standardized Index of Shape (SIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters derived from diffusion-weighted MRI (DW-MRI). Materials and methods: Thirty-four patients with LARC who underwent MRI scans before and after SCR followed by delayed surgery, retrospectively, were enrolled. SIS, ADC, IVIM parameters [tissue diffusion (D{sub t}), pseudo-diffusion (D{sub p}), perfusion fraction (f{sub p})] and DKI parameters [mean diffusivity (MD), mean of diffusional kurtosis (MK)] were calculated for each patient. IVIM parameters were estimated using two methods, namely conventional biexponential fitting (CBFM) and variable projection (VARPRO). After surgery, the pathological TNM and tumor regression grade (TRG) were estimated. For each parameter, percentage changes between before and after SCR were evaluated. Furthermore, an artificial neural network was trained for outcome prediction. Nonparametric sample tests and receiver operating characteristic curve (ROC) analysis were performed. Results: Fifteen patients were classified as responders (TRG ≤ 2) and 19 as not responders (TRG > 3). Seven patients had TRG 1 (pathological complete response, pCR). Mean and standard deviation values of pre-treatment CBFM D{sub p} and mean value of VARPRO D{sub p} pre-treatment showed statistically significant differences to predict pCR. (p value at Mann–Whitney test was 0.05, 0.03 and 0.008, respectively.) Exclusively SIS percentage change showed significant differences between responder and non-responder patients after SCR (p value << 0.001) and to assess pCR after SCR (p value << 0.001). The best results to predict pCR were obtained by VARPRO Fp mean value pre-treatment with area under ROC of 0.84, a sensitivity of 96.4%, a specificity of 71.4%, a positive predictive value (PPV) of 92.9%, a negative predictive value (NPV) of 83.3% and an accuracy of 91.2%. The best results to assess after treatment complete pathological response were obtained by SIS with an area under ROC of 0.89, a sensitivity of 85.7%, a specificity of 92.6%, a PPV of 75.0%, a NPV of 96.1% and an accuracy of 91.2%. Moreover, the best results to differentiate after treatment responders vs. non-responders were obtained by SIS with an area under ROC of 0.94, a sensitivity of 93.3%, a specificity of 84.2%, a PPV of 82.4%, a NPV of 94.1% and an accuracy of 88.2%. Promising initial results were obtained using a decision tree tested with all ADC, IVIM and DKI extracted parameter: we reached high accuracy to assess pathological complete response after SCR in LARC (an accuracy of 85.3% to assess pathological complete response after SCR using VARPRO D{sub p} mean value post-treatment, ADC standard deviation value pre-treatment, MD standard deviation value post-treatment). Conclusion: SIS is a hopeful DCE-MRI angiogenic biomarker to assess preoperative treatment response after SCR with delayed surgery. Furthermore, an important prognostic role was obtained by VARPRO F{sub p} mean value pre-treatment and by a decision tree composed by diffusion parameters derived by DWI and DKI to assess pathological complete response.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding window Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.

36 MATERIALS SCIENCE↗
DOE OSTI2016

An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis

With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations.

Science & Technology - Other Topics↗
NASA NTRS2016

Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China 2004-2013

Three decades of rapid economic development is causing severe and widespread PM2.5(particulate matter (is) less than 2.5 ) pollution in China. However, research on the health impacts of PM2.5 exposure has been hindered by limited historical PM2.5 concentration data. We estimated ambient PM2.5 concentrations from 2004 to 2013 in China at 0.1 deg resolution using the most recent satellite data and evaluated model performance with available ground observations. We developed a two-stage spatial statistical model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) and assimilated meteorology, land use data, and PM2.5 concentrations from China's recently established ground monitoring network. An inverse variance weighting (IVW) approach was developed to combine MODIS Dark Target and Deep Blue AOD to optimize data coverage. We evaluated model predicted PM2.5 concentrations from 2004 to early 2014 using ground observations. The overall model cross-validation R(sup 2) and relative prediction error were 0.79 and 35.6%, respectively. Validation beyond the model year (2013) indicated that it accurately predicted PM(sub 2.5) concentrations with little bias at the monthly (R(sup 2) = 0.73), regression slope = 0.91) and seasonal (R(sup 2) = 0.79), regression slope = 0.92) levels. Seasonal variations revealed that winter was the most polluted season and that summer was the cleanest season. Analysis of predicted PM2.5 levels showed a mean annual increase of 1.97 micro-g/cu cm between 2004 and 2007 and a decrease of 0.46 micro-g/cu cm between 2008 and 2013. Our satellite-driven model can provide reliable historical PM2.5 estimates in China at a resolution comparable to those used in epidemiologic studies on the health effects of long-term PM2.5 exposure in North America. This data source can potentially advance research on PM2.5 health effects in China.

satellite remote sensing↗
NASA NTRS2004

Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

Platnick, Steven↗
DOE OSTI2025

Automated segmentation of soft X-ray tomography: Native cellular structure with submicron resolution at high-throughput for whole-cell quantitative imaging in yeast

Soft X-ray tomography (SXT) is an invaluable tool for quantitatively analyzing cellular structures at suboptical isotropic resolution. However, it has traditionally depended on manual segmentation, limiting its scalability for large datasets. Here, we leverage a deep learning-based autosegmentation pipeline to segment and label cellular structures in hundreds of cells across three Saccharomyces cerevisiae strains. This task-based pipeline uses manual iterative refinement to improve segmentation accuracy for key structures, including the cell body, nucleus, vacuole, and lipid droplets, enabling high-throughput and precise phenotypic analysis. Using this approach, we quantitatively compared the three-dimensional (3D) whole-cell morphometric characteristics of wild-type, VPH1-GFP, and vac14 strains, uncovering detailed strain-specific cell and organelle size and shape variations. We show the utility of SXT data for precise 3D curvature analysis of entire organelles and cells and detection of fine morphological features using surface meshes. Our approach facilitates comparative analyses with high spatial precision and statistical throughput, uncovering subtle morphological features at the single-cell and population level. This workflow significantly enhances our ability to characterize cell anatomy and supports scalable studies on the mesoscale, with applications in investigating cellular architecture, organelle biology, and genetic research across diverse biological contexts.

Chen, Jianhua [Lawrence Berkeley National Laborato↗
DOE OSTI2016

Predictive Factor Analysis of Response-Adapted Radiation Therapy for Chemotherapy-Sensitive Pediatric Hodgkin Lymphoma: Analysis of the Children's Oncology Group AHOD 0031 Trial

Purpose: To evaluate whether clinical risk factors could further distinguish children with intermediate-risk Hodgkin lymphoma (HL) with rapid early and complete anatomic response (RER/CR) who benefit significantly from involved-field RT (IFRT) from those who do not, and thereby aid refinement of treatment selection. Methods and Materials: Children with intermediate-risk HL treated on the Children's Oncology Group AHOD 0031 trial who achieved RER/CR with 4 cycles of chemotherapy, and who were randomized to 21-Gy IFRT or no additional therapy (n=716) were the subject of this study. Recursive partitioning analysis was used to identify factors associated with clinically and statistically significant improvement in event-free survival (EFS) after randomization to IFRT. Bootstrap sampling was used to evaluate the robustness of the findings. Result: Although most RER/CR patients did not benefit significantly from IFRT, those with a combination of anemia and bulky limited-stage disease (n=190) had significantly better 4-year EFS with the addition of IFRT (89.3% vs 77.9% without IFRT; P=.019); this benefit was consistently reproduced in bootstrap analyses and after adjusting for other prognostic factors. Conclusion: Although most patients achieving RER/CR had favorable outcomes with 4 cycles of chemotherapy alone, those children with initial bulky stage I/II disease and anemia had significantly better EFS with the addition of IFRT as part of combined-modality therapy. Further work evaluating the interaction of clinical and biologic factors and imaging response is needed to further optimize and refine treatment selection.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Cosmological constraints from the cross-correlation of DESI Luminous Red Galaxies with CMB lensing from Planck PR4 and ACT DR6

Here, we infer the growth of large scale structure over the redshift range 0.4 ≲ z ≲ 1 from the cross-correlation of spectroscopically calibrated Luminous Red Galaxies (LRGs) selected from the Dark Energy Spectroscopic Instrument (DESI) legacy imaging survey with CMB lensing maps reconstructed from the latest Planck and ACT data. We adopt a hybrid effective field theory (HEFT) model that robustly regulates the cosmological information obtainable from smaller scales, such that our cosmological constraints are reliably derived from the (predominantly) linear regime. We perform an extensive set of bandpower- and parameter-level systematics checks to ensure the robustness of our results and to characterize the uniformity of the LRG sample. We demonstrate that our results are stable to a wide range of modeling assumptions, finding excellent agreement with a linear theory analysis performed on a restricted range of scales. From a tomographic analysis of the four LRG photometric redshift bins we find that the rate of structure growth is consistent with ΛCDM with an overall amplitude that is ≃ 5-7% lower than predicted by primary CMB measurements with modest (∼ 2σ) statistical significance. From the combined analysis of all four bins and their cross-correlations with Planck we obtain S 8 = 0.765 ± 0.023, which is less discrepant with primary CMB measurements than previous DESI LRG cross Planck CMB lensing results. From the cross-correlation with ACT we obtain S 8 = 0.790 +0.024 -0.027 , while when jointly analyzing Planck and ACT we find S 8 = 0.775 +0.019 -0.022 from our data alone and σ 8 = 0.772 +0.020 -0.023 with the addition of BAO data. These constraints are consistent with the latest Planck primary CMB analyses at the ≃ 1.6-2.2σ level, and are in excellent agreement with galaxy lensing surveys.

cosmological parameters from LSS↗
DOE OSTI2023

Nano-infrared imaging of metal insulator transition in few-layer 1T-TaS 2

Abstract Among the family of transition metal dichalcogenides, 1T-TaS 2 stands out for several peculiar physical properties including a rich charge density wave phase diagram, quantum spin liquid candidacy and low temperature Mott insulator phase. As 1T-TaS 2 is thinned down to the few-layer limit, interesting physics emerges in this quasi 2D material. Here, using scanning near-field optical microscopy, we perform a spatial- and temperature-dependent study on the phase transitions of a few-layer thick microcrystal of 1T-TaS 2 . We investigate encapsulated air-sensitive 1T-TaS 2 prepared under inert conditions down to cryogenic temperatures. We find an abrupt metal-to-insulator transition in this few-layer limit. Our results provide new insight in contrast to previous transport studies on thin 1T-TaS 2 where the resistivity jump became undetectable, and to spatially resolved studies on non-encapsulated samples which found a gradual, spatially inhomogeneous transition. A statistical analysis suggests bimodal high and low temperature phases, and that the characteristic phase transition hysteresis is preserved down to a few-layer limit.

42 ENGINEERING↗
DOE OSTI2022

Image feature extraction and galaxy classification: a novel and efficient approach with automated machine learning

ABSTRACT In this work, we explore the possibility of applying machine learning methods designed for 1D problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly steps, such as the point spread function deconvolution and the training and application of complex Convolutional Neural Networks of thousands or even millions of parameters. In our approach, we extract features from the galaxy images by analysing the elliptical isophotes in their light distribution and collect the information in a sequence. The sequences obtained with this method present definite features allowing a direct distinction between galaxy types. Then, we train and classify the sequences with machine learning algorithms, designed through the platform Modulos AutoML. As a demonstration of this method, we use the second public release of the Dark Energy Survey (DES DR2). We show that we are able to successfully distinguish between early-type and late-type galaxies, for images with signal-to-noise ratio greater than 300. This yields an accuracy of $86{{\ \rm per\ cent}}$ for the early-type galaxies and $93{{\ \rm per\ cent}}$ for the late-type galaxies, which is on par with most contemporary automated image classification approaches. The data dimensionality reduction of our novel method implies a significant lowering in computational cost of classification. In the perspective of future data sets obtained with e.g. Euclid and the Vera Rubin Observatory, this work represents a path towards using a well-tested and widely used platform from industry in efficiently tackling galaxy classification problems at the peta-byte scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Multi-element effects on arsenate accumulation in a geochemical matrix determined using µ-XRF, µ-XANES and spatial statistics

Soils regulate the environmental impacts of trace elements, but direct measurements of reaction mechanisms in these complex, multi-component systems can be challenging. The objective of this work was to develop approaches for assessing effects of co-localized geochemical matrix elements on the accumulation and chemical speciation of arsenate applied to a soil matrix. Synchrotron X-ray fluorescence microprobe (µ-XRF) images collected across 100 µm × 100 µm and 10 µm × 10 µm regions of a naturally weathered soil sand-grain coating before and after treatment with As(V) solution showed strong positive partial correlations ( r ' = 0.77 and 0.64, respectively) between accumulated As and soil Fe, with weaker partial correlations ( r ' > 0.1) between As and Ca, and As and Zn in the larger image. Spatial and non-spatial regression models revealed a dominant contribution of Fe and minor contributions of Ca and Ti in predicting accumulated As, depending on the size of the sample area analyzed. Time-of-flight secondary ion mass spectrometry analysis of an area of the sand grain showed a significant correlation ( r = 0.51) between Fe and Al, so effects of Fe versus Al (hydr)oxides on accumulated As could not be separated. Fitting results from 25 As K -edge microscale X-ray absorption near-edge structure (µ-XANES) spectra collected across a separate 10 µm × 10 µm region showed ~60% variation in proportions of Fe(III) and Al(III)-bound As(V) standards, and fits to µ-XANES spectra collected across the 100 µm × 100 µm region were more variable. We find that, consistent with insights from studies on model systems, the results obtained here indicate a dominance of Fe and possibly Al (hydr)oxides in controlling As(V) accumulation within microsites of the soil matrix analyzed, but the analyses inferred minor augmentation from co-localized Ti, Ca and possibly Zn.

58 GEOSCIENCES↗
DOE OSTI2025

Analysis of streaked images of x-ray self-emission in laser-driven spherical implosions

Imaging of x-ray self-emission provides a powerful in situ measurement of the spatial and temporal evolution of high-energy-density plasmas. However, interpretation of these measurements requires detailed understanding of the data-generating process. This work presents a case study in the interpretation of x-ray self-emission data for the specific application of streaked one-dimensional slit imaging of spherical laser-driven implosions. A comprehensive generative model of the streaked slit-imaging diagnostic is developed including detailed treatments of the radiation transfer, photometrics, and photostatistics associated with the measurement. The model is used to generate realistic synthetic streaked images and to analyze experimental streaked images to extract important physical quantities of interest. An example analysis of streaked images from implosion experiments on the OMEGA laser is presented, where the model developed in this work is used to constrain the trajectory and peak velocity of the implosion using Bayesian inference.

Bayesian inference↗
DOE OSTI2021

Probing Systematic Bias in Low-redshift Type Ia Supernova Measurements by Cross Analyzing Surface Brightness and Hubble Residuals

For low-redshift (z < 0.1) SN Ia samples used in several cosmological analyses over the past decade, we probe for systematic bias by looking for correlations between surface brightness (SB) measurements and Hubble residuals (HR). For 292 SNe Ia, we measure SB at the location of the SN Ia from publicly available Pan-STARRS (PS1) images. The Hubble residuals are from two recent measurements with low-z SNe Ia that overlap the PS1 footprint: (1) the DES 3 yr cosmology analysis, with 120 overlapping low-z SNe Ia from the Harvard-Smithsonian Center for Astrophysics surveys and Carnegie Supernova Project, and (2) the PS1 single-telescope analysis, with 172 overlapping low-z SNe Ia from the Foundation Supernova Survey. This study is motivated by previous reports of anomalous inefficiencies and flux scatter for transients on bright galaxies. Here, we compare HR distributions of the bright and faint halves of the SB distribution: the mean HR values differ by ${\rm{\Delta }}\overline{\mathrm{HR}}$ = 0.031 ± 0.018, consistent with no difference at the 2σ level. We also perform a Kolmogorov–Smirnov (KS) test for the bright and faint half HR distributions, and conclude that the two distributions are statistically consistent with a KS p-value of 0.07. However, if future studies with larger data sets find ${\rm{\Delta }}\overline{\mathrm{HR}}\sim 0.03$ with high significance, this difference would be a leading systematic uncertainty in measurements of the dark energy equation of state, w.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Direct Measurement of the Nickel Spectrum in Cosmic Rays in the Energy Range from 8.8 GeV/$\mathcal{n}$ to 240 GeV/$\mathcal{n}$ with CALET on the International Space Station

The relative abundance of cosmic ray nickel nuclei with respect to iron is by far larger than for all other transiron elements; therefore it provides a favorable opportunity for a low background measurement of its spectrum. Since nickel, as well as iron, is one of the most stable nuclei, the nickel energy spectrum and its relative abundance with respect to iron provide important information to estimate the abundances at the cosmic ray source and to model the Galactic propagation of heavy nuclei. However, only a few direct measurements of cosmic-ray nickel at energy larger than ~ 3 GeV/n are available at present in the literature, and they are affected by strong limitations in both energy reach and statistics. In this Letter, we present a measurement of the differential energy spectrum of nickel in the energy range from 8.8 to 240 GeV/n , carried out with unprecedented precision by the Calorimetric Electron Telescope (CALET) in operation on the International Space Station since 2015. The CALET instrument can identify individual nuclear species via a measurement of their electric charge with a dynamic range extending far beyond iron (up to atomic number Z = 40 ). The particle’s energy is measured by a homogeneous calorimeter (1.2 proton interaction lengths, 27 radiation lengths) preceded by a thin imaging section (3 radiation lengths) providing tracking and energy sampling. This Letter follows our previous measurement of the iron spectrum [O. Adriani et al. (CALET Collaboration), Phys. Rev. Lett. 126, 241101 (2021).], and it extends our investigation on the energy dependence of the spectral index of heavy elements. It reports the analysis of nickel data collected from November 2015 to May 2021 and a detailed assessment of the systematic uncertainties. In the region from 20 to 240 GeV/n our present data are compatible within the errors with a single power law with spectral index -2.51 ± 0.07 .

79 ASTRONOMY AND ASTROPHYSICS↗