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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Short-period Variability in the Globular Cluster NGC 419 and the SMC Field

Delta Scuti (δ Sct) stars have been extensively studied in our Galaxy but far less in extragalactic systems. Here we study the population of δ Sct variables in NGC 419, an intermediate-age globular cluster of the Small Magellanic Cloud (SMC), using g, r, and i Gemini-S/Gemini Multi-Object Spectrograph (GMOS) time-series observations. Our goal is to study the role of such variables in the cluster extended main-sequence turnoff (MSTO). We report the discovery of 54 δ Sct stars and three eclipsing binaries in the NGC 419 field. We find only a handful of the δ Sct stars at the MSTO of NGC 419, while the majority are fainter, indicating that the cluster is younger (≲1.2 Gyr) than previously thought. Considering their radial distribution, we identify only six δ Sct stars as probable members of NGC 419, while the 48 remaining are likely δ Sct stars of the SMC field. Cluster δ Sct stars appear close to the red edge of the MSTO, supporting the idea that the extended MSTO has its origin in an age spread. The 48 field δ Sct stars represent the largest detection of δ Sct stars made in the SMC. The period distribution of these newly detected δ Sct stars (0.04 day ≲ P ≲ 0.15 day) is similar to that detected in other systems. The amplitude distribution (0.05 mag ≲ Δr ≲ 0.60 mag) is likely biased because of the lack of low-amplitude stars. We finally use the δ Sct stars to calculate distances using different period–luminosity relations. The average distance moduli obtained are 18.76 ± 0.14 mag for NGC 419 and 18.86 ± 0.11 mag for the SMC field, which agree with previous measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

The evidence of N = 16 shell closure and β -delayed neutron emission from 25 F

We measured the β -delayed neutron emission from 25 F for the first time at the Facility for Rare Isotope Beams (FRIB). Using combined neutron and γ -ray detector systems of the FRIB Decay Station Initiator (FDSi), we observed β -decay transitions populating neutron unbound states between 4.2 and 8 MeV in 25 Ne. The experimental results led to the revision of the β -decay half-life and β -delayed neutron-emission probability of 25 F. The β -decay strength distribution of 25 F extracted from the data agrees with the shell-model predictions using the USDB and SDPF-M effective interactions. This result indicates that the spherical neutron shell gap persists in 25 F and 25 Ne.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quantifying the unknown impact of segmentation uncertainty on image-based simulations

Abstract Image-based simulation, the use of 3D images to calculate physical quantities, relies on image segmentation for geometry creation. However, this process introduces image segmentation uncertainty because different segmentation tools (both manual and machine-learning-based) will each produce a unique and valid segmentation. First, we demonstrate that these variations propagate into the physics simulations, compromising the resulting physics quantities. Second, we propose a general framework for rapidly quantifying segmentation uncertainty. Through the creation and sampling of segmentation uncertainty probability maps, we systematically and objectively create uncertainty distributions of the physics quantities. We show that physics quantity uncertainty distributions can follow a Normal distribution, but, in more complicated physics simulations, the resulting uncertainty distribution can be surprisingly nontrivial. We establish that bounding segmentation uncertainty can fail in these nontrivial situations. While our work does not eliminate segmentation uncertainty, it improves simulation credibility by making visible the previously unrecognized segmentation uncertainty plaguing image-based simulation.

42 ENGINEERING↗
DOE OSTI2025

Convective shells in the interior of Cepheid variable stars: Overshooting models based on hydrodynamic simulations

Context. Because Cepheid variable stars have long been used as a cosmic benchmark for scaling distances in our Galaxy and beyond, the accuracy of stellar evolution models for Cepheids have wide-reaching effects. However, our understanding of the dynamics in the interiors of these physically complex stars is limited. Aims. Our goal is to provide a detailed multi-dimensional picture of hydrodynamic convection and convective boundary mixing in the interior of Cepheids. Methods. Using the Modules for Experiments in Stellar Astrophysics (MESA), we studied the structure of intermediate-mass stars that cross the instability strip. Then, we performed two-dimensional hydrodynamic simulations of six stars with the fully compressible Multidimensional Stellar Implicit Code (MUSIC). Our simulations did not model the radial pulsations but focused on the interior structure of this family of stars. We developed and applied a new statistical analysis to examine convection and convective boundary mixing in the interior of these stellar simulations. Results. Based on a grid of MESA models, we demonstrated that a common structure for intermediate mass Cepheids includes an interior convective shell as well as a thin outer convective envelope. Using the extreme value theory approach to analyze our MUSIC simulation data, we found that overshooting above the convective shell fills the space between these convectively unstable layers. We developed a new statistical analysis that provides a clearer picture of how overshooting fills this layer; it also allowed us to formulate a detailed comparison between overshooting above and below the convective shell. Our analysis effectively decomposes the overshooting layer into two layers: a weak overshooting layer and a strong overshooting layer. Statistically, this is accomplished by decomposing the strongly non-Gaussian probability density function into a mixture of gamma distributions. Using our mixture model, we showed that the ratio of overshooting lengths above and below the convective shell depends directly on the radial extent of the convective shell as well as its depth in the star. We proposed a new form for the diffusion coefficient that addresses the need for overlapping overshooting layers between convective shells. We introduced the idea of a “super-mixing layer” where overshooting from both the convective shell and the convective envelope results in efficient mixing and could be viewed as merging the two adjacent convective zones.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Semimicroscopic description of isoscalar giant multipole resonances in medium-mass closed-shell nuclei

Main properties of isoscalar giant multipole resonances (up to L=3), including L=0,and 2 overtones, in medium-mass closed-shell nuclei are described within the semimicroscopic particle-hole dispersive optical model. Further, main properties are characterized by the energy-averaged strength distribution, projected (one-body) transition density, and probabilities of direct one-nucleon decay. Calculation results obtained for characteristics of the mentioned resonances in the 48 Ca, 90 Zr, and 132 Sn nuclei are compared with available experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Artificial intelligence models, photos, and data associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” (v2)

This data package is associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” published in Water Resources Research (Chen et al., 2024). This data package includes the training, validation, testing, and prediction data used by the artificial intelligence (AI) model for automated grain size and hydro-biogeochemistry quantification using streambed photos. The grain size data are extracted for each photo using You Look Only Once (YOLO), a pre-trained object detection model. This data package was originally published in October 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. Please see flmd.csv for a list of all files contained in this data package and descriptions for each. Please see dd.csv for a data dictionary that defines the column headers of .csv files in the data package. This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; and (4) six subfolders. Subfolders 1 to 4 include the training, validation, testing, and prediction data. Subfolder 5_Summary includes the summary results of different combinations of training, validation, testing, and prediction data. Subfolder 6_SupplementalData includes additional data downloaded from public sources (Kaufman et al., 2023a; Kaufman et al., 2023b; Garefalakis et al., 2023; Mair et al., 2024; https://github.com/river-corridors-sfa/Geospatial_variables). In total, the data package includes 110 folders and 44,283 files. These files include 9,047 .jpg photos, 1 .png photo, 3 .tif photos; 26,639 photo labels and individual grain sizes and probability from AI (.txt); 8,447 grain size distribution data (.dat); and 126 CSV files for results summary, and 14 required metadata files (.xlsx). The summary CSV files contain 68 columns and approximately 2,200 rows that represent photo names, site locations, recording time, GPS coordinates, grains sizes (D10, D50, D60, and D84), number of grains, and additional hydro-biogeochemical data such as water depth, flow velocity, Manning’s coefficient, friction factor, hydraulic conductivity, permeability, streambed interstitial velocity magnitude, mass transfer rate, and nitrate uptake velocity. The photos were obtained from 75 sites in the Yakima River Basin and the Columbia River shorelines, and other associated data from samples and sensors obtained when the photos were taken are publicly available (Fulton et al. 2022; Grieger et al. 2023). All files are .csv, .txt, .dat, .jpg, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Guest Editorial: Planning and operation of resilient distribution system for integrated multi-energy

Resilience is the ability of power systems to prepare for and adapt to low-probability, high-impact incidents and withstand and recover rapidly from disruptions. With the ageing of electricity distribution infrastructure and increasing threats of weather-related incidents and natural disasters, the need to effectively enhance the resilience of the electricity distribution system has become urgent and has attracted worldwide attention. Although there are an increasing number of publications related to enhancing resilience strategies, resilience is an emerging concept in power systems. Existing practices are mostly focused on deploying distributed energy resources (DERs) and microgrids, hardening the existing infrastructures and building redundant capacities. However, from a broader perspective, resilience enhancement of power distribution system is a systematic engineering, involving long-term system planning and upgrading (e.g., deployment of smart grid technologies and intelligent switches), short-term proactive scheduling, real-time robust and resilient control of DERs, and post-event restoration and recovery strategies. Based on this point, this Special Issue in IET Energy System Integration focuses on soliciting the most recent and original technologies, scheduling and control strategies for improving the resilience of power distribution system. Eight papers are presented in this Special Issue, covering various aspects related to resilience enhancement of power distribution system, including fault-tolerant frequency measurement, robust scheduling of integrated electricity and district heating systems, robust control of DERs, efficient methods for safety verification as well as novel graph theory-based approach to restore the distribution systems after multiple simultaneous faults. A brief introduction of these 8 papers is provided below.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Improved microgrid resiliency through distributionally robust optimization under a policy-mode framework

Critical energy infrastructure are constantly under stress due to the ever increasing disruptions caused by wildfires, hurricanes, other weather related extreme events and cyber-attacks. Hence it becomes important to make critical infrastructure resilient to threats from such cyber-physical events. However, such events are hard to predict and numerous in nature and type and it becomes infeasible to make a system resilient to every possible such cyber-physical event. Such an approach can make the system operation overly conservative and impractical to operate. Furthermore, distributions of such events are hard to predict and historical data available on such events can be very sparse, making the problem even harder to solve. To deal with these issues, in this paper we present a policy-mode framework that enumerates and predicts the probability of various cyber-physical events and then a distributionally robust optimization (DRO) formulation that is robust to the sparsity of the available historical data. The proposed algorithm is illustrated on an islanded microgrid example: a modified IEEE 123-node feeder with distributed energy resources (DERs) and energy storage. Simulations are carried to validate the resiliency metrics under the sampled disruption events.

Nazir, Mohammad Nawaf↗
DOE OSTI2021

A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity

We present a stochastic mathematical model of the intracellular infection dynamics of Bacillus anthracis in macrophages. Following inhalation of B. anthracis spores, these are ingested by alveolar phagocytes. Ingested spores then begin to germinate and divide intracellularly. This can lead to the eventual death of the host cell and the extracellular release of bacterial progeny. Some macrophages successfully eliminate the intracellular bacteria and will recover. Here, a stochastic birth-and-death process with catastrophe is proposed, which includes the mechanism of spore germination and maturation of B. anthracis . The resulting model is used to explore the potential for heterogeneity in the spore germination rate, with the consideration of two extreme cases for the rate distribution: continuous Gaussian and discrete Bernoulli. We make use of approximate Bayesian computation to calibrate our model using experimental measurements from in vitro infection of murine peritoneal macrophages with spores of the Sterne 34F2 strain of B. anthracis . The calibrated stochastic model allows us to compute the probability of rupture, mean time to rupture, and rupture size distribution, of a macrophage that has been infected with one spore. We also obtain the mean spore and bacterial loads over time for a population of cells, each assumed to be initially infected with a single spore. Our results support the existence of significant heterogeneity in the germination rate, with a subset of spores expected to germinate much later than the majority. Furthermore, in agreement with experimental evidence, our results suggest that most of the spores taken up by macrophages are likely to be eliminated by the host cell, but a few germinated spores may survive phagocytosis and lead to the death of the infected cell. Finally, we discuss how this stochastic modelling approach, together with dose-response data, allows us to quantify and predict individual infection risk following exposure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Novel Analytical Population Tumor Control Probability Model Includes Cell Density and Volume Variations: Application to Canine Brain Tumor

Tumor control probability (TCP) models based on Poisson statistics characterize the distribution of surviving clonogens. Thus enabling the calculation of TCP for individuals. To mathematically describe clinically observed survival data of patient cohorts it is necessary to extend the Poisson TCP model. This is typically done by either incorporating variations of model parameters or by using an empirical logistic model. The purpose of this work is the development of an analytical population TCP model by mechanistic extension of the Possion model.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Early-time measure in eternal inflation

In a situation like eternal inflation, where our data is replicated at infinitely-many other space-time events, it is necessary to make a prior assumption about our location to extract predictions. The principle of mediocrity entails that we live at asymptotic late times, when the occupational probabilities of vacua has settled to a near-equilibrium distribution. In this paper we further develop the idea that we instead exist during the approach to equilibrium, much earlier than the exponentially-long mixing time. In this case we are most likely to reside in vacua that are easily accessed dynamically. Using first-passage statistics, we prove that vacua that maximize their space-time volume at early times have: 1. maximal ever-hitting probability; 2. minimal mean first-passage time; and 3. minimal decay rate. These requirements are succinctly captured by an early-time measure. The idea that we live at early times is a predictive guiding principle, with many phenomenological implications. First, our vacuum should lie deep in a funneled region, akin to folding energy landscapes of proteins. Second, optimal landscape regions are characterized by relatively short-lived vacua, with lifetime of order the de Sitter Page time. For our vacuum, this lifetime is ~ 10 130 years, which is consistent with the Standard Model estimate due to Higgs metastability. Third, the measure favors vacua with small, positive vacuum energy. This can address the cosmological constant problem, provided there are sufficiently many vacua in the entire ensemble of funnels. As a concrete example, we study the Bousso-Polchinski lattice of flux vacua, and find that the early-time measure favors lattices with the fewest number of flux dimensions. This favors compactifications with a large hierarchy between the lightest modulus and all other Kähler and complex structure moduli.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Exploration of a Potential Desirability of Outcome Ranking Endpoint for Complicated Intra-Abdominal Infections Using 9 Registrational Trials for Antibacterial Drugs

Abstract Background Desirability of outcome ranking (DOOR) is a novel approach to clinical trial design that incorporates safety and efficacy assessments into an ordinal ranking system to evaluate overall outcomes of clinical trial participants. Here, we derived and applied a disease-specific DOOR endpoint to registrational trials for complicated intra-abdominal infection (cIAI). Methods Initially, we applied an a priori DOOR prototype to electronic patient-level data from 9 phase 3 noninferiority trials for cIAI submitted to the US Food and Drug Administration between 2005 and 2019. We derived a cIAI-specific DOOR endpoint based on clinically meaningful events that trial participants experienced. Next, we applied the cIAI-specific DOOR endpoint to the same datasets and, for each trial, estimated the probability that a participant assigned to the study treatment would have a more desirable DOOR or component outcome than if assigned to the comparator. Results Three key findings informed the cIAI-specific DOOR endpoint: (1) a significant proportion of participants underwent additional surgical procedures related to their baseline infection; (2) infectious complications of cIAI were diverse; and (3) participants with worse outcomes experienced more infectious complications, more serious adverse events, and underwent more procedures. DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 47.4% to 50.3% and were not significantly different. Component analyses depicted risk-benefit assessments of study treatment versus comparator. Conclusions We designed and evaluated a potential DOOR endpoint for cIAI trials to further characterize overall clinical experiences of participants. Similar data-driven approaches can be utilized to create other infectious disease–specific DOOR endpoints.

Immunology↗
DOE OSTI2020

Characterizing Peatland Microtopography Using Gradient and Microform-Based Approaches

Abstract Peatlands represent an important component of the global carbon cycle, storing 180–621 Gt of carbon (C). Small-scale spatial variations in elevation, frequently referred to as microtopography, influence ecological processes associated with the peatland C cycle, including Sphagnum photosynthesis and methane flux. Microtopography can be characterized with measures of topographic variability and by using conceptual classes (microforms) linked to function: most commonly hummocks and hollows. However, the criteria used to define these conceptual classes are often poorly described, if at all, and vary between studies. Such inconsistencies compel development of explicit quantitative methods to classify microforms. Furthermore, gradient-based characterizations that describe spatial variability without the use of microforms are lacking in the literature. Therefore, the objectives of this study were to (1) calculate peatland microtopographical elevation gradients and measures of spatial variability, (2) develop three microform classification methods intended for specific purposes, and (3) evaluate and contrast classification methods. Our results suggest that at spatial scales much larger than microforms, elevation distributions are unimodal and are well approximated with parametric probability density functions. Results from classifications were variable between methods and years and exhibited significant differences in mean hollow areal coverages of a raised ombrotrophic bog. Our results suggest that the conceptualization and classification of microforms can significantly influence microtopographic structural metrics. The three explicit methods for microform classification described here may be used and built upon for future applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

LeptonInjector and LeptonWeighter: A neutrino event generator and weighter for neutrino observatories

In this work, we present a high-energy neutrino event generator, called LeptonInjector, alongside an event weighter, called LeptonWeighter. Both are designed for large-volume Cherenkov neutrino telescopes such as IceCube. The neutrino event generator allows for quick and flexible simulation of neutrino events within and around the detector volume, and implements the leading Standard Model neutrino interaction processes relevant for neutrino observatories: neutrino-nucleon deep-inelastic scattering and neutrino-electron annihilation. In this paper, we discuss the event generation algorithm, the weighting algorithm, and the main functions of the publicly available code, with examples. Program summary: Program Titles: LeptonInjector and LeptonWeighter CPC Library link to program files: https://doi.org/10.17632/662gkpjfd9.1 Developer's repository links: https://github.com/icecube/LeptonInjector and https://github.com/icecube/LeptonWeighter Licensing provisions: GNU Lesser General Public License, version 3. Programming Language: C++11 External Routines: • Boost • HDF5 • nuflux (https://github.com/icecube/nuflux) • nuSQuIDS (https://github.com/arguelles/nuSQuIDS) • Photospline (https://github.com/icecube/photospline) • SuiteSparse (https://github.com/DrTimothyAldenDavis/SuiteSparse) Nature of problem: LeptonInjector: Generate neutrino interaction events of all possible topologies and energies throughout and around a detector volume. LeptonWeighter: Reweight Monte Carlo events, generated by a set of LeptonInjector Generators, to any desired physical neutrino flux or cross section. Solution method: LeptonInjector: Projected ranges of generated leptons and the extent of the detector, in terms of column depth, are used to inject events in and around the detector volume. Event kinematics follow distributions provided in cross section files. LeptonWeighter: Event generation probabilities are calculated for each Generator, which are then combined into a generation weight and used to calculate an overall event weight.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Effect of tectonic processes on biosphere–geosphere feedbacks across a convergent margin

The subsurface is among Earth’s largest biomes, but the extent to which microbial communities vary across tectonic plate boundaries or interact with subduction-scale geological processes remains unknown. Here we compare bacterial community composition with deep-subsurface geochemistry from 21 hot springs across the Costa Rican convergent margin. We find that cation and anion compositions of the springs reflect the dip angle and position of the underlying tectonic structure and also correlate with the bacterial community. Co-occurring microbial cliques related to cultured chemolithoautotrophs that use the reverse tricarboxylic acid cycle (rTCA) as well as abundances of metagenomic rTCA genes correlate with concentrations of slab-volatilized carbon. This, combined with carbon isotope evidence, suggests that fixation of slab-derived CO2 into biomass may support a chemolithoautotrophy-based subsurface ecosystem. We calculate that this forearc subsurface biosphere could sequester 1.4 × 10 9 to 1.4 × 10 10 mol of carbon per year, which would decrease estimates of the total carbon delivered to the mantle by 2 to 22%. Furthermore, based on the observed correlations, we suggest that distribution and composition of the subsurface bacterial community are probably affected by deep tectonic processes across the Costa Rican convergent margin and that, by sequestering carbon volatilized during subduction, these chemolithoautotrophic communities could in turn impact the geosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Fast and efficient identification of anomalous galaxy spectra with neural density estimation

ABSTRACT Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection methods. Deep learning algorithms can capture and pick up subtle variations in rich data sets and are fast to apply once trained. Here, we study the applicability of an unsupervised and probabilistic deep learning framework, the probabilistic auto-encoder, to the detection of peculiar objects in galaxy spectra from the SDSS survey. Different to supervised algorithms, this algorithm is not trained to detect a specific feature or type of anomaly, instead it learns the complex and diverse distribution of galaxy spectra from training data and identifies outliers with respect to the learned distribution. We find that the algorithm assigns consistently lower probabilities (higher anomaly score) to spectra that exhibit unusual features. For example, the majority of outliers among quiescent galaxies are E+A galaxies, whose spectra combine features from old and young stellar population. Other identified outliers include LINERs, supernovae, and overlapping objects. Conditional modelling further allows us to incorporate additional information. Namely, we evaluate the probability of an object being anomalous given a certain spectral class, but other information such as metrics of data quality or estimated redshift could be incorporated as well. We make our code publicly available.

Böhm, Vanessa↗
DOE OSTI2025

Generalized approach for rapid entropy calculation of liquids and solids

We build a comprehensive methodology for the fast computation of entropy across both solid and liquid phases. The proposed method utilizes a single trajectory of molecular dynamics (MD) to facilitate the calculation of entropy, which is composed of three components. The electronic entropy is determined through the temporal average acquired from density functional theory MD simulations. The vibrational entropy, typically the predominant contributor to the total entropy, even within the liquid state, is evaluated by computing the phonon density of states via the velocity autocorrelation function. The most arduous component to quantify, the configurational entropy, is assessed by probability analysis of the local structural arrangement and atomic distribution. We illustrate, through a variety of examples, that this method is both a versatile and valid technique for characterizing the thermodynamic states of both solids and liquids. Furthermore, this method is employed to expedite the calculation of melting temperatures, demonstrating its practical utility in computational thermodynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Robust VAR Capability Curve of DER with Uncertain Renewable Generation

Active distribution system with high penetration of inverter based distributed energy resources(DER), can be utilized for var-related ancillary services at the transmission side interface. In order to utilize the DER flexibility, transmission system operator must be presented the aggregated DER flexibility of distribution system. However, the uncertainty in renewable generation, questions the credibility of aggregated capability curve in practice. In this paper, we incorporate the uncertainty into aggregation process to develop capability curve while preserving the real physics (unbalance and lossy nature) of distribution system. The Resulting capability curve with the associated probability can be harnessed by the TSO for decision making for both planning and operation.

Kar, Aditya Shankar↗