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At least 253 records · Page 14

Varicella infection modeling.

Infectious diseases can spread rapidly through healthcare facilities, resulting in widespread illness among vulnerable patients. Computational models of disease spread are useful for evaluating mitigation strategies under different scenarios. This report describes two infectious disease models built for the US Department of Veteran Affairs (VA) motivated by a Varicella outbreak in a VA facility. The first model simulates disease spread within a notional contact network representing staff and patients. Several interventions, along with initial infection counts and intervention delay, were evaluated for effectiveness at preventing disease spread. The second model adds staff categories, location, scheduling, and variable contact rates to improve resolution. This model achieved more accurate infection counts and enabled a more rigorous evaluation of comparative effectiveness of interventions.

Jones, Katherine A.↗

Predicting demand for hydrogen station fueling

Full function hydrogen stations are a reality; fuel cell electric vehicle drivers can pull up to commercial fueling stations and receive 3–5 kg in less than 5 min, for an approximately 300-mile range. The demand for hydrogen is increasing, driven by an increase in the fueling of public and private fuel cell vehicles. This study describes the development and value of a model that simulates stochastic future demand at a hydrogen filling station. The predictive hydrogen demand model described in this article is trained from mathematical models constructed from actual hydrogen fill count, amount, and frequency data. Future fill probabilities inform the hour-by-hour demand profile and the station state of either “available, ready to fill” or “available, filling”. For example, a prediction for a station generally dispensing 5,000 kg a week on a Friday afternoon at 4 p.m. is 16 fills, totaling 48.7 kg, with a 0.52 proportion of time spent in “available, filling” state yielding 31 min of filling time. This is a first-of-its kind, published study on predicting future hydrogen demand by the time of day (e.g., hour-by-hour intervals) and day of week. This study can be used for hydrogen station requirements and operation and maintenance strategies and to assess the impact of demand variations and scenarios. Finally, this article presents the current status of hydrogen demand, the model development methods, a set of sample results. Discussion and conclusions concentrate on the value and use of the proposed model.

08 HYDROGEN↗

Environmental exposure to industrial air pollution is associated with decreased male fertility

Objective: To understand how chronic exposure to industrial air pollution is associated with male fertility through semen parameters. Design: Retrospective cohort study. Subjects: Men in the Subfertility, Health and Assisted Reproduction cohort who underwent a semen analysis 2005-2017 with ≥1 measured semen parameter (N=21,563). Intervention(s): Residential histories for each man were constructed using locations from administrative records linked through the Utah Population Database. Industrial facilities with air emissions of nine endocrine disrupting compound chemical classes were identified from the Environmental Protection Agency Risk-Screening Environmental Indicators microdata. Chemical levels were linked with residential histories for the 5 years prior to each semen analysis. Main Outcome Measures: Semen analyses were classified as azoospermic or oligozoospermic (< 15 M/mL) using World Health Organization cutoffs for concentration. Bulk semen parameters such as concentration, total count, ejaculate volume, total motility, total motile count, and total progressive motile count were also measured. Multivariable regression models with robust standard errors were used to associate exposure quartiles for each of the nine chemical classes with each semen parameter, adjusting for age, race, and ethnicity, as well as neighborhood socioeconomic disadvantage. Results: After adjustment for demographic covariates, several chemical classes were associated with azoospermia and decreased total motility and volume. For exposure in the 4th relative to 1st quartile, significant associations were observed for acrylonitrile (β total motility = -0.87 pp), aromatic hydrocarbons (odds ratio [OR]azoospermia = 1.53; β volume = -0.14 mL), dioxins (OR azoospermia = 1.31; β volume = -0.09 mL; β total motility = -2.65 pp), heavy metals (β total motility = -2.78pp), organic solvents (OR azoospermia = 1.75; β volume = -0.10 mL), organochlorines (OR azoospermia = 2.09; β volume = -0.12 mL), phthalates (OR azoospermia = 1.44; β volume = -0.09 mL; β total motility = -1.21 pp), and silver particles (OR azoospermia = 1.64; β volume = -0.11 mL). All semen parameters significantly decreased with increasing socioeconomic disadvantage. Men who lived in the most disadvantaged areas had concentration, volume, and total motility of 6.70 M/mL, 0.13 mL, and 1.79 pp lower, respectively. Count, motile count, and total progressive motile count all decreased by 30–34 M.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Fission Chain Restart Theory

We present that fast nanosecond timescale neutron and gamma-ray counting can be performed with a (liquid) scintillator array. Fission chains in metal evolve over a timescale of tens of nanoseconds. If the metal is surrounded by moderator, neutrons leaking from the metal can thermalize and diffuse in the moderator. With finite probability, the diffusing neutrons can return to the metal and restart the fast fission chain. The timescale for this restart process is microseconds. A theory describing time evolving fission chains for metal surrounded by moderator, including this restart process, is presented. Finally, this theory is sufficiently simple for it to be implemented for real-time analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Screening Tool for Equitable Adoption and Deployment of Solar (STEADy Solar)

The Screening Tool for Equitable Adoption and DeploYment of Solar (STEADy Solar) is a database and mapping tool designed to promoting clean energy investments for low-income communities across the United States. The tool indicates locations that may be eligible for the Investment Tax Credit bonus adders defined in the 2022 Inflation Reduction Act (IRA) and combines this information with demographics, social vulnerability, solar technical potential, solar economics (modeled net present value), and building counts by use-type. It can be used by states, municipalities, community-based organizations, developers, and researchers to identify sites where solar projects may be economical and where federal incentives may be available to support equitable adoption of solar. Specific values include: Areas eligible for the Energy Communities Tax Credit Bonus Program (including brownfield site counts) Areas eligible for the Low Income Communities Bonus Credit Program (including Tribal Lands, and covered affordable housing project counts) Areas categorized as disadvantaged by Justice40 Commercial and Residential Solar economics characterized by the Net Present Value and Simple Payback Period Total Population, Race, and Ethnicity Median Household Income, Poverty rate, Household Tenure Social Vulnerability Count of buildings, developable rooftop solar capacity (in kWdc) and estimated annual generation potential (in kWh) on four building types: Government General Services, Government Emergency Response, Grade Schools, and Colleges/Universities. The linked report describes the STEADy dataset metadata and presents high level insights from the data. The downloadable and formatted excel dataset makes it easy for users to gain insights for their locations. Supporting .csv and shapefiles provide users with the full data to run their own analyses on equitable solar siting.

14 SOLAR ENERGY↗

A new method for predicting hurricane rapid intensification based on co-occurring environmental parameters

Abstract Tropical cyclones (TCs) that undergo Rapid Intensification (RI) can pose serious socioeconomic threats and can potentially result in major damaging impacts along coastal areas. Considering the complexity of various physical mechanisms that play a role in RI and its relatively low probability of occurrence, predicting RI remains a major operational challenge. In this study, we propose a simple deterministic binary classification model based on the co-occurrence of environmental parameters (MCE) to predict an RI event. More specifically, the model determines the possibility of RI based on a simple count of the number of environmental predictors deemed favorable and unfavorable. We compare our model results to logistic regression (LR) and decision tree (DT) models, well-trained using the same set of environmental predictors. Results reveal that at an RI threshold of 30 kt, the MCE exhibits a critical success index score of 0.233 which is 14% higher than DT and LR model performances. When tested at multiple RI thresholds, the MCE displays relatively higher skill scores across multiple metrics. By simultaneously evaluating the favorability of predictors, the MCE is able to comparatively reduce the number of false alarms predicted when certain predictors are unfavorable toward RI. Interpreting these model results to gain a physical understanding of how co-occurring environmental parameters can affect RI, we highlight future directions for using models based on the MCE approach to understand and predict TC RI as well as other meteorological extremes.

54 ENVIRONMENTAL SCIENCES↗

Cascaded systems analysis of photon counting detectors

Purpose: Photon counting detectors (PCDs) are an emerging technology with applications in spectral and low-dose radiographic and tomographic imaging. This paper develops an analytical model of PCD imaging performance, including the system gain, modulation transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). Methods: A cascaded systems analysis model describing the propagation of quanta through the imaging chain was developed. The model was validated in comparison to the physical performance of a silicon-strip PCD implemented on an experimental imaging bench. The signal response, MTF, and NPS were measured and compared to theory as a function of exposure conditions (70 kVp, 1–7 mA), detector threshold, and readout mode (i.e., the option for coincidence detection). The model sheds new light on the dependence of spatial resolution, charge sharing, and additive noise effects on threshold selection and was used to investigate the factors governing PCD performance, including the fundamental advantages and limitations of PCDs in comparison to energy-integrating detectors (EIDs) in the linear regime for which pulse pileup can be ignored. Results: The detector exhibited highly linear mean signal response across the system operating range and agreed well with theoretical prediction, as did the system MTF and NPS. The DQE analyzed as a function of kilovolt (peak), exposure, detector threshold, and readout mode revealed important considerations for system optimization. The model also demonstrated the important implications of false counts from both additive electronic noise and charge sharing and highlighted the system design and operational parameters that most affect detector performance in the presence of such factors: for example, increasing the detector threshold from 0 to 100 (arbitrary units of pulse height threshold roughly equivalent to 0.5 and 6 keV energy threshold, respectively), increased the f{sub 50} (spatial-frequency at which the MTF falls to a value of 0.50) by ∼30% with corresponding improvement in DQE. The range in exposure and additive noise for which PCDs yield intrinsically higher DQE was quantified, showing performance advantages under conditions of very low-dose, high additive noise, and high fidelity rejection of coincident photons. Conclusions: The model for PCD signal and noise performance agreed with measurements of detector signal, MTF, and NPS and provided a useful basis for understanding complex dependencies in PCD imaging performance and the potential advantages (and disadvantages) in comparison to EIDs as well as an important guide to task-based optimization in developing new PCD imaging systems.

60 APPLIED LIFE SCIENCES↗

Arctic Impact Identification with Less Data Using Variable Relationships: An Exploratory Express LDRD project.

Regional impacts from sea ice loss can be challenging to separate from internal climate variability, potentially requiring thousands of ensemble members. East Asian wintertime cooling has been linked to sea ice loss from present day conditions in the Polar Amplification Model Intercomparison Project with these large ensemble counts. This cooling is theorized to arise from a strengthened Siberian High and East Asian Jet response. The strengthened Siberian High can be detected with one fifth the ensemble members needed for the East Asian wintertime cooling in a single model. We thus hypothesize that leveraging relationships between multiple variables in a conditional pathways-based approach would reduce the number of required ensemble members to conclusively attribute East Asian wintertime cooling to future sea ice concentrations. In all analyzed cases, confidence was increased when evaluating sea ice loss’s responsibility for the joint effects of East Asian cooling, East Asian Jet strengthening, and Siberian High strengthening over just East Asian cooling. However, we were not able to confidently attribute future East Asian wintertime cooling to sea ice loss in a single model. We found that significant intra-ensemble variability within single Earth System Models (ESMs) produced highly uncertain forcing response models upon which attribution results were undermined. We were able to show that ensemble mean seasonally averaged metrics from multiple ESMs greatly improved the accuracy of the forcing response linear models and exposed the necessity of all three steps in the pathway (sea ice area, Siberian High pressure, and East Asian Jet speed) for accurate prediction of East Asian wintertime cooling. Although all three steps were necessary, East Asian wintertime cooling possesses a large dependence on the Siberian High pressure, which weakens the confidence associated with overall strong joint-attribution comparing present day and future scenarios. We believe transitioning the pathway nodes to relative changes between the Siberian High and Aleutian Low as well as between the midlatitude westerlies and subtropical jet in the East Asianj Jet region may be able to produce significant attribution more fully dependent upon all three steps. Ultimately, this research demonstrates the simple extensibility of conditional pathways-based attribution to sea ice loss forcing on the Earth system.

54 ENVIRONMENTAL SCIENCES↗

Direct handling of sharp interfacial energy for microstructural evolution

In this study, we introduce a simplification to the previously demonstrated hybrid Potts–phase field (hPPF), which relates interfacial energies to microstructural sharp interfaces. The model defines interfacial energy by a Potts-like discrete interface approach of counting unlike neighbors, which we use to compute local curvature. The model is compared to the hPPF by studying interfacial characteristics and grain growth behavior. The models give virtually identical results, while the new model allows the simulator more direct control of interfacial energy.

36 MATERIALS SCIENCE↗

Single toxin dose-response models revisited

The goal of this paper is to offer a rigorous analysis of the sigmoid shape single toxin dose-response relationship. The toxin efficacy function is introduced and four special points, including maximum toxin efficacy and inflection points, on the dose-response curve are defined. The special points define three phases of the toxin effect on mortality: (1) toxin concentrations smaller than the first inflection point or (2) larger then the second inflection point imply low mortality rate, and (3) concentrations between the first and the second inflection points imply high mortality rate. Probabilistic interpretation and mathematical analysis for each of the four models, Hill, logit, probit, and Weibull is provided. Two general model extensions are introduced: (1) the multi-target hit model that accounts for the existence of several vital receptors affected by the toxin, and (2) model with a nonzero mortality at zero concentration to account for natural mortality. Special attention is given to statistical estimation in the framework of the generalized linear model with the binomial dependent variable as the mortality count in each experiment, contrary to the widespread nonlinear regression treating the mortality rate as continuous variable. The models are illustrated using standard EPA Daphnia acute (48 h) toxicity tests with mortality as a function of NiCl or CuSO{sub 4} toxin. - Highlights: • The paper offers a rigorous study of a sigmoid dose-response relationship. • The concentration with highest mortality rate is rigorously defined. • A table with four special points for five morality curves is presented. • Two new sigmoid dose-response models have been introduced. • The generalized linear model is advocated for estimation of sigmoid dose-response relationship.

60 APPLIED LIFE SCIENCES↗

Development of Labview based data acquisition and multichannel analyzer software for radioactive particle tracking system

A DAQ (data acquisition) software called RPTv2.0 has been developed for Radioactive Particle Tracking System in Malaysian Nuclear Agency. RPTv2.0 that features scanning control GUI, data acquisition from 12-channel counter via RS-232 interface, and multichannel analyzer (MCA). This software is fully developed on National Instruments Labview 8.6 platform. Ludlum Model 4612 Counter is used to count the signals from the scintillation detectors while a host computer is used to send control parameters, acquire and display data, and compute results. Each detector channel consists of independent high voltage control, threshold or sensitivity value and window settings. The counter is configured with a host board and twelve slave boards. The host board collects the counts from each slave board and communicates with the computer via RS-232 data interface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

THE FADING OF TWO TRANSIENT ULTRALUMINOUS X-RAY SOURCES TO BELOW THE STELLAR MASS EDDINGTON LIMIT

We report new detections of the two transient ultraluminous X-ray sources (ULXs) in NGC 5128 from an ongoing series of Chandra observations. Both sources have previously been observed L{sub x} (2-3) × ∼10{sup 39} erg s{sup –1}, at the lower end of the ULX luminosity range. The new observations allow us to study these sources in the luminosity regime frequented by the Galactic black hole X-ray binaries (BH XBs). We present the recent lightcurves of both ULXs. 1RXH J132519.8-430312 (ULX1) was observed at L{sub x} ≈ 1 × 10{sup 38} erg s{sup –1}, while CXOU J132518.2-430304 (ULX2) declined to L{sub x} ≈ 2 × 10{sup 37} erg s{sup –1} and then lingered at this luminosity for hundreds of days. We show that a reasonable upper limit for both duty cycles is 0.2, with a lower limit of 0.12 for ULX2. This duty cycle is larger than anticipated for transient ULXs in old stellar populations. By fitting simple spectral models in an observation with ∼50 counts we recover properties consistent with Galactic BH XBs, but inconclusive as to the spectral state. We utilize quantile analyses to demonstrate that the spectra are generally soft, and that in one observation the spectrum of ULX2 is inconsistent with a canonical hard state at >95% confidence. This is contrary to what would be expected of an accreting intermediate mass black hole primary, which we would expect to be in the hard state at these luminosities. We discuss the paucity of transient ULXs discovered in early-type galaxies and excogitate explanations. We suggest that the number of transient ULXs scales with the giant and sub-giant populations, rather than the total number of XBs.

79 ASTRONOMY AND ASTROPHYSICS↗

THREE-DIMENSIONAL STELLAR KINEMATICS AT THE GALACTIC CENTER: MEASURING THE NUCLEAR STAR CLUSTER SPATIAL DENSITY PROFILE, BLACK HOLE MASS, AND DISTANCE

We present three-dimensional (3D) kinematic observations of stars within the central 0.5 pc of the Milky Way (MW) nuclear star cluster (NSC) using adaptive optics imaging and spectroscopy from the Keck telescopes. Recent observations have shown that the cluster has a shallower surface density profile than expected for a dynamically relaxed cusp, leading to important implications for its formation and evolution. However, the true 3D profile of the cluster is unknown due to the difficulty in de-projecting the stellar number counts. Here, we use spherical Jeans modeling of individual proper motions and radial velocities to constrain, for the first time, the de-projected spatial density profile, cluster velocity anisotropy, black hole mass (M {sub BH}), and distance to the Galactic center (R {sub 0}) simultaneously. We find that the inner stellar density profile of the late-type stars, ρ(r)∝r {sup –γ}, have a power law slope γ=0.05{sub −0.60}{sup +0.29}, much more shallow than the frequently assumed Bahcall-Wolf slope of γ = 7/4. The measured slope will significantly affect dynamical predictions involving the cluster, such as the dynamical friction time scale. The cluster core must be larger than 0.5 pc, which disfavors some scenarios for its origin. Our measurement of M{sub BH}=5.76{sub −1.26}{sup +1.76}×10{sup 6} M {sub ☉} and R{sub 0}=8.92{sub −0.55}{sup +0.58} kpc is consistent with that derived from stellar orbits within 1'' of Sgr A*. When combined with the orbit of S0-2, the uncertainty on R {sub 0} is reduced by 30% (8.46{sub −0.38}{sup +0.42} kpc). We suggest that the MW NSC can be used in the future in combination with stellar orbits to significantly improve constraints on R {sub 0}.

79 ASTRONOMY AND ASTROPHYSICS↗

Nested solitons in two-field fuzzy dark matter

ABSTRACT Dark matter as scalar particles consisting of multiple species is well motivated in string theory where axion fields are ubiquitous. A two-field fuzzy dark matter (FDM) model features two species of ultralight axion particles with different masses, m1 ≠ m2, which is extended from the standard one-field model with $m_a \sim 10^{-22} \, {\rm eV}$. Here we perform numerical simulations to explore the properties of two-field FDM haloes. We find that the central soliton has a nested structure when m2 ≫ m1, which is distinguishable from the generic flat-core soliton in one-field haloes. However, the formation of this nested soliton is subject to many factors, including the density fraction and mass ratio of the two fields. Finally, we study non-linear structure formation in two-field cosmological simulations with self-consistent initial conditions and find that the small-scale structure in two-field cosmology is also distinct from the one-field model in terms of DM halo counts and soliton formation time.

79 ASTRONOMY AND ASTROPHYSICS↗

Cohesive Relations for Surface Atoms in the Iron-Technetium Binary System

Iron-technetium alloys are of relevance to the development of waste forms for disposition of radioactive technetium-99 obtained from spent nuclear fuel. Corrosion of candidate waste forms is a function of the local cohesive energy () of surface atoms. A theoretical model for calculating is developed. Density functional theory was used to construct a modified embedded atom (MEAM) potential for iron-technetium. Materials properties determined for the iron-technetium system were in good agreement with the literature. To explore the relationship between local structure and corrosion, MEAM simulations were performed on representative iron-technetium alloys and intermetallics. Technetium-rich phases have lower , suggesting that these phases will be more noble than iron-rich ones. Quantitative estimates of based on numbers of nearest neighbors alone can lead to errors up to 0.5 eV. Consequently, atomistic corrosion simulations for alloy systems should utilize physics-based models that consider not only neighbor counts, but also local compositions and atomic arrangements.

Taylor, Christopher D.↗

A novel analysis method for paired-sample microbial ecology experiments

Many microbial ecology experiments use sequencing data to measure a community s response to an experimental treatment. In a common experimental design, two units, one control and one experimental, are sampled before and after the treatment is applied to the experimental unit. The four resulting samples contain information about the dynamics of organisms that respond to the treatment, but there are no analytical methods designed to extract exactly this type of information from this configuration of samples. Here we present an analytical method specifically designed to visualize and generate hypotheses about microbial community dynamics in experiments that have paired samples and few or no replicates. The method is based on the Poisson lognormal distribution, long studied in macroecology, which we found accurately models the abundance distribution of taxa counts from 16S rRNA surveys. To demonstrate the method s validity and potential, we analyzed an experiment that measured the effect of crude oil on ocean microbial communities in microcosm. Our method identified known oil degraders as well as two clades, Maricurvus and Rhodobacteraceae, that responded to amendment with oil but do not include known oil degraders. Furthermore, our approach is sensitive to organisms that increased in abundance only in the experimental unit but less sensitive to organisms that increased in both control and experimental units, thus mitigating the role of bottle effects .

59 BASIC BIOLOGICAL SCIENCES↗

The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. Here, we developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. In addition, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Moreover, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. These results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.

54 ENVIRONMENTAL SCIENCES↗

Computer vision-based rock bolt detection in orthomosaic imagery obtained in the Waste Isolation Pilot Plant underground facility

Assessing structural integrity of large underground tunnel facilities is often a time consuming and human-labor intensive task. Thus, research using various modes of sensing and automated detection of key structural components in mines is posed to aid in safety assessments and establishing overall structural health. We propose an approach utilizing off-the-shelf camera and lidar technology fixed to a custom sensing platform, image stitching techniques, fine-tuned object detection models, and specialized model-inference methods to automatically detect, count, and map roof bolts for assessment of structural safety in man-made underground tunnels. Results show a novel workflow for effective object counting in orthomosaic tunnel ceiling images generated from collections in GPS-denied mining environments. Additionally, we demonstrate effective fine-tuning of EfficientDet object detectors utilizing state-of-the-art image augmentation techniques known as the mosaic and mixup transformations. Our work is demonstrated on sensed data and imagery collected from the Department of Energy (DOE) Waste Isolation Pilot Plant (WIPP) where miles of tunnel ceiling must be assessed for structural integrity.

42 ENGINEERING↗