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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

An efficient parallel sampling technique for Multivariate Poisson-Lognormal model: Analysis with two crash count datasets

Our study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and takes account of the over dispersion in the data that leads to a superior data fitting. But, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chain Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Moreover, the correlations among the latent effects of different severity levels are found significant in both datasets that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Radio frequency models of novae in eruption. I. The free-free process in bipolar morphologies

Observations of novae at radio frequencies provide us with a measure of the total ejected mass, density profile, and kinetic energy of a nova eruption. The radio emission is typically well characterized by the free-free emission process. Most models to date have assumed spherical symmetry for the eruption, although for as long as there have been radio observations of these systems, it has been known that spherical eruptions are too simplistic a geometry. In this paper, we build bipolar models of the nova eruption, assuming the free-free process, and show the effects of varying different parameters on the radio light curves. The parameters considered include the ratio of the minor- to major-axis, the inclination angle, and shell thickness. We also show the uncertainty introduced when fitting spherical-model synthetic light curves to bipolar-model synthetic light curves. We find that the optically thick phase rises with the same power law (S {sub ν}∝t {sup 2}) for both the spherical and bipolar models. In the bipolar case, there is a 'plateau' phase—depending on the thickness of the shell as well as the ratio of the minor- to major-axis—before the final decline, which follows the same power law (S {sub ν}∝t {sup –3}) as in the spherical case. Finally, fitting spherical models to the bipolar-model synthetic light curves requires, in the worst-case scenario, doubling the ejected mass, more than halving the electron temperature, and reducing the shell thickness by nearly a factor of 10. This implies that in some systems we have been over-predicting the ejected masses and under-predicting the electron temperature of the ejecta.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Linear two-pool models are insufficient to infer soil organic matter decomposition temperature sensitivity from incubations

Abstract Terrestrial carbon (C)-climate feedbacks depend strongly on how soil organic matter (SOM) decomposition responds to temperature. This dependency is often represented in land models by the parameter Q 10 , which quantifies the relative increase of microbial soil respiration per 10 °C temperature increase. Many studies have conducted paired laboratory soil incubations and inferred “active” and “slow” pool Q 10 values by fitting linear two-pool models to measured respiration time series. Using a recently published incubation study (Qin et al. in Sci Adv 5(7):eaau1218, 2019) as an example, here we first show that the very high parametric equifinality of the linear two-pool models may render such incubation-based Q 10 estimates unreliable. In particular, we show that, accompanied by the uncertain initial active pool size, the slow pool Q 10 can span a very wide range, including values as high as 100, although all parameter combinations are producing almost equally good model fit with respect to the observations. This result is robust whether or not interactions between the active and slow pools are considered (typically these interactions are not considered when interpreting incubation data, but are part of the predictive soil carbon models). This very large parametric equifinality in the context of interpreting incubation data is consistent with the poor temporal extrapolation capability of linear multi-pool models identified in recent studies. Next, using a microbe-explicit SOM model (RESOM), we show that the inferred two pools and their associated parameters (e.g., Q 10 ) could be artificial constructs and are therefore unreliable concepts for integration into predictive models. We finally discuss uncertainties in applying linear two-pool (or more generally multiple-pool) models to estimate SOM decomposition parameters such as temperature sensitivities from laboratory incubations. We also propose new observations and model structures that could enable better process understanding and more robust predictive capabilities of soil carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Contemporaneous broadband observations of three high-redshift BL Lac objects

We have collected broadband spectral energy distributions (SEDs) of three BL Lac objects 3FGL J0022.1−1855 (z = 0.689), 3FGL J0630.9−2406 (z ≳ 1.239), and 3FGL J0811.2−7529 (z = 0.774), detected by Fermi with relatively flat gigaelectronvolt spectra. By observing simultaneously in the near-infrared to hard X-ray band, we can well characterize the high end of the synchrotron component of the SED. Thus, fitting the SEDs to synchro-Compton models of the dominant emission from the relativistic jet, we can constrain the underlying particle properties and predict the shape of the gigaelectronvolt Compton component. Standard extragalactic background light (EBL) models explain the high-energy absorption well, with poorer fits for high-ultraviolet models. The fits show clear evidence for EBL absorption in the Fermi spectrum of our highest-redshift source 3FGL J0630.9−2406. While synchrotron self-Compton models adequately describe the SEDs, the situation may be complicated by possible external Compton components. For 3FGL J0811.2−7529, we also discover a nearby serendipitous source in the X-ray data, which is almost certainly another lower synchrotron peak frequency (ν{sub pk}{sup sy}) BL Lac, that may contribute flux in the Fermi band. Since our sources are unusual high-luminosity, moderate ν{sub pk}{sup sy} BL Lacs, we compare these quantities and the Compton dominance, the ratio of peak inverse Compton to peak synchrotron luminosities (L{sub pk}{sup IC}/L{sub pk}{sup sy}), with those of the full Fermi BL Lac population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The Thermal and Kinematic Sunyaev–Zeldovich Effect in Galaxy Clusters and Filaments Using Multifrequency Temperature Maps of the Cosmic Microwave Background: A399–A401 Cluster Pair Case Study

We present a multifrequency and multi-instrument methodology to study the physical properties of galaxy clusters and cosmic filaments using cosmic microwave background observations. Our approach enables simultaneous measurement of both the thermal (tSZ) and kinematic Sunyaev–Zeldovich (kSZ) effects, incorporates relativistic corrections, and models astrophysical foregrounds such as thermal dust emission. We do this by jointly fitting a single physical model across multiple maps from multiple instruments at different frequencies, rather than fitting a model to a single Compton-y map. We demonstrate the success of this method by fitting the A399–A401 galaxy cluster pair and filament system using archival data from the Planck satellite and new, targeted deep data from the Atacama Cosmology Telescope, covering 11 different frequencies over 14 maps from 30 GHz to 545 GHz. Our tSZ results are consistent with previous work using Compton-y maps. We measure the line-of-sight peculiar velocities of the cluster–filament system using the kSZ effect and find statistical uncertainties on individual cluster peculiar velocities of ≲600 km s −1 , which are competitive with current state-of-the-art measurements. Additionally, we measure the optical depth of the filament component with a signal-to-noise of 8.5σ and reveal hints of its morphology. This modular approach is well-suited for application to future instruments across a wide range of millimeter and submillimeter wavebands.

Gill, Ajay S. [National Research Council of Canada↗
DOE OSTI2024

Superhorizon isocurvature fluctuations relax tensions

Here, we present a new class of models that have potential to alleviate tensions present in the cosmological data today. We postulate about variation in the sound horizon scale on superhorizon scales, i.e., on scales that are larger than that of the present observable low-redshift Universe (≳ 1Gpc) while at the same time smaller than the largest scales probed by the cosmic microwave background (CMB) (≲ 10Gpc). In this scenario, CMB peaks are naturally smoothed as preferred by the Planck data, while at the same time the low-redshift baryon acoustic oscillation calibration is partially decoupled from the CMB. Taking superhorizon variations in baryon fraction as an example and using approximate modeling, we find improvement in the best fit Planck power spectrum model Δχ 2 ~ 6 for 1 extra degree of freedom with the relevant extension parameter 10 3 σ b = 2.10 ± 0.60, implying about 10% variations in baryon fraction across the Universe. At the same time, S 8 drops by about 1 sigma, easing tension with weak lensing surveys. We find that the combination of Planck 2018 data, eBOSS BAO data, and Riess et al. distance ladder Hubble parameter determination produce a satisfactory fit in our model if we allow for a phantom dark energy equation of state.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Measurement of the e{sup +}e{sup –} → ηπ{sup +}π{sup –} cross section in the center-of-mass energy range 1.22–2.00 GeV with the SND detector at the VEPP-2000 collider

In the experiment with the SND detector at the VEPP-2000 e+e– collider the cross section for the process e{sup +}e{sup –} → ηπ{sup +}π{sup –} has been measured in the center-of-mass energy range from 1.22 to 2.00 GeV. Obtained results are in agreement with previous measurements and have better accuracy. The energy dependence of the e{sup +}e{sup –} → ηπ{sup +}π{sup –} cross section has been fitted with the vector-meson dominance model. From this fit the product of the branching fractions B(ρ(1450) → ηπ{sup +}π{sup –})B(ρ(1450) → π{sup +}π{sup –}) has been extracted and compared with the same products for (ρ(1450) → ωΠ{sup 0} and (ρ(1450) → π{sup +}π{sup –} decays. The obtained cross section data have been also used to test the conservation of vector current hypothesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

A Preliminary Explosion Seismic Spectral Model for Saturated/Hard Rock

This short technical report describes a new seismic spectral model for chemical and nuclear explosions in saturated and/or hard rock. Results from the Source Physics Experiments (SPE) indicate that existing explosion spectral models can be poor fits to small and/or over-buried explosions. Here we develop a preliminary improved explosion model to fit both SPE and historic nuclear explosion data. The model is based on revising the Mueller and Murphy (1972) and Denny and Johnson (1991) seismic spectral models. A FORTRAN code was developed to provide the spectral models in SAC format for use in explosion monitoring applications such as detection and yield estimation. This model should be considered preliminary and work is underway to better generalize and expand the model to include explosions in dry porous and/or soft rock media and to better fit explosion S-waves.

58 GEOSCIENCES↗
DOE OSTI2023

Explainability and extrapolation of machine learning models for predicting the glass transition temperature of polymers

Abstract Machine learning (ML) offers promising tools to develop surrogate models for polymers' structure–property relations. Surrogate models can be built upon existing polymer data and are useful for rapidly predicting the properties of unknown polymers. The accuracy of such ML models appears to depend on the feature space representation of polymers, the range of training data, and learning algorithms. Here, we establish connections between these factors for predicting the glass transition temperature (T g ) of polymers. Our analysis suggests linear models with fewer fitting parameters are as accurate as nonlinear models with many hidden and unexplainable parameters. Also, the performance of a monomer topology‐based ML model is found to be qualitatively identical to that of a physicochemical descriptor‐based ML model. We find that the ML models's performance in the extrapolative region is enhanced as the property range of the training data increases. Moreover, we establish newT g – polymer chemistry correlations via ML. Our work illustrates how ML can advance the fundamental understanding of polymer structure–property correlations and its efficacy for extrapolation problems.

Polymer Science↗
DOE OSTI2024

Generating synthetic signaling networks for in silico modeling studies

Predictive models of signaling pathways have proven to be difficult to develop. Reasons include the uncertainty in the number of species, the complexity in species’ interactions, and the sparseness and uncertainty in experimental data. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. For example, uncertainty and sparseness of the data often result in overfitted models that have little predictive value beyond recapitulating the experimental data itself. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. However, to determine the effectiveness of any new algorithm, a baseline model is needed to test its performance. To meet this need, we developed a method for generating artificial synthetic networks that are reasonably realistic and thus can be treated as ground truth models. These synthetic models can then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. Here, we describe a simple approach for generating synthetic signaling networks that can be used for this purpose.

42 ENGINEERING↗
DOE OSTI2023

Extended Donnan-Manning theory for selective ion partition and transport in ion exchange membrane

The use of ion exchange membranes (IEMs) for electrochemical ion-ion separation leverages the selectivity of the IEMs toward like-charged species via valence difference and/or other ion membrane interactions. A mechanistic model that relates selectivity with membrane structural and chemical properties is lacking in the literature. Here, in this study, we extend the Manning’s counter-ion condensation model for describing ion partition and ion mobility inside IEMs to mixed salts scenarios. We evaluate the extended Donnan-Manning model against experimental data from literature and compare the performance the Donnan-Manning model to that of the ideal Donnan model and the Donnan-Affinity model. Our analysis shows that, despite its structural complexity, the Donnan-Manning model has less fitting parameters than the Donnan-Affinity model and generally outperforms the two other models in predicting counter-ion and co-ion partition. With the assumption of a higher mobility of condensed ions than that of uncondensed ions, the generalized Manning’s model can also predict counter-ion mobility selectivity for cation exchange membranes, but its performance for predicting mobility selectivity for anion exchange membranes is still unsatisfactory.

42 ENGINEERING↗
DOE OSTI2016

Using GRACE and climate model simulations to predict mass loss of Alaskan glaciers through 2100

Glaciers in Alaska are currently losing mass at a rate of ~–50 Gt a –1 , one of the largest ice loss rates of any regional collection of mountain glaciers on Earth. Existing projections of Alaska's future sea-level contributions tend to be divergent and are not tied directly to regional observations. Here we develop a simple, regional observation-based projection of Alaska's future sea-level contribution. We compute a time series of recent Alaska glacier mass variability using monthly GRACE gravity fields from August 2002 through December 2014. We also construct a three-parameter model of Alaska glacier mass variability based on monthly ERA-Interim snowfall and temperature fields. When these three model parameters are fitted to the GRACE time series, the model explains 94% of the variance of the GRACE data. Using these parameter values, we then apply the model to simulated fields of monthly temperature and snowfall from the Community Earth System Model, to obtain predictions of mass variations through 2100. Here, we conclude that mass loss rates may increase between –80 and –110 Gt a –1 by 2100, with a total sea-level rise contribution of 19 ± 4 mm during the 21st century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Accumulation capacitance frequency dispersion of III-V metal-insulator-semiconductor devices due to disorder induced gap states

The origin of the anomalous frequency dispersion in accumulation capacitance of metal-insulator-semiconductor devices on InGaAs and InP substrates is investigated using modeling, electrical characterization, and chemical characterization. A comparison of the border trap model and the disorder induced gap state model for frequency dispersion is performed. The fitting of both models to experimental data indicate that the defects responsible for the measured dispersion are within approximately 0.8 nm of the surface of the crystalline semiconductor. The correlation between the spectroscopically detected bonding states at the dielectric/III-V interface, the interfacial defect density determined using capacitance-voltage, and modeled capacitance-voltage response strongly suggests that these defects are associated with the disruption of the III-V atomic bonding and not border traps associated with bonding defects within the high-k dielectric.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2011

THE STAR CLUSTERS OF THE LARGE MAGELLANIC CLOUD: STRUCTURAL PARAMETERS

We present and analyze the radial luminosity profiles of a sample of 1066 stellar clusters in the Large Magellanic Cloud (LMC). By design, this study closely follows the compilation by Hill and Zaritsky of the structural parameters of stellar clusters in the Small Magellanic Cloud (SMC). Both King and Elson-Fall-Freeman model profiles are fit to V-band surface brightness profiles measured from the Magellanic Cloud Photometric Survey images. We tabulate the concentration, central surface brightness, tidal radii, 90% enclosed luminosity radii (r{sub 90}), and local background luminosity density. Over two-thirds of the clusters in the sample are adequately fit by one or both of these models. One notable and systematic exception, as in the SMC, is those clusters that lack a central brightness concentration, the 'ring' clusters. While the bulk properties of the clusters are similar between the LMC and SMC populations, we find that the LMC lacks clusters that are as large, either in terms of core radii or r{sub 90}, as the largest in the SMC, perhaps a signature of larger tidal stresses in the LMC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A first-look atmospheric modeling study of the young directly imaged planet-mass companion, ROXS 42Bb

We present and analyze JK{sub s}L' photometry and our previously published H-band photometry and K-band spectroscopy for ROXs 42Bb, an object Currie et al. first reported as a young directly imaged planet-mass companion. ROXs 42Bb exhibits IR colors redder than field L dwarfs but consistent with other planet-mass companions. From the H{sub 2}O-2 spectral index, we estimate a spectral type of L0 ± 1; weak detections/non-detections of the CO bandheads, Na I, and Ca I support evidence for a young, low surface gravity object primarily derived from the H{sub 2}(K) index. ROXs 42Bb's photometry/K-band spectrum are inconsistent with limiting cases of dust-free atmospheres (COND) and marginally inconsistent with the AMES/DUSTY models and the BT-SETTL models. However, ROXS 42Bb data are simultaneously fit by atmosphere models incorporating several micron-sized dust grains entrained in thick clouds, although further modifications are needed to better reproduce the K-band spectral shape. ROXs 42Bb's best-estimated temperature is T {sub eff} ∼ 1950-2000 K, near the low end of the empirically derived range in Currie et al. For an age of ∼1-3 Myr and considering the lifetime of the protostar phase, ROXs 42Bb's luminosity of log(L/L {sub ☉}) ∼ –3.07 ± 0.07 implies a mass of 9{sub −3}{sup +3} M{sub J} , making it one of the lightest planetary-mass objects yet imaged.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Investigating CXOU J163802.6–471358: A new pulsar wind nebula in the norma region?

We present the first analysis of the extended source CXOU J163802.6–471358, which was discovered serendipitously during the Chandra X-ray survey of the Norma region of the Galactic spiral arms. The X-ray source exhibits a cometary appearance with a point source and an extended tail region. The complete source spectrum is fitted well with an absorbed power law model and jointly fitting the Chandra spectrum of the full source with one obtained from an archived XMM-Newton observation results in best fit parameters N {sub H} =1.5{sub −0.5}{sup +0.7}×10{sup 23} cm{sup −2} and Γ=1.1{sub −0.6}{sup +0.7} (90% confidence uncertainties). The unabsorbed luminosity of the full source is then L{sub X}∼4.8×10{sup 33}d{sub 10}{sup 2} erg s{sup –1} with d {sub 10} = d/10 kpc, where a distance of 10 kpc is a lower bound inferred from the large column density. The radio counterpart found for the source using data from the Molonglo Galactic Plane Survey epoch-2 shows an elongated tail offset from the X-ray emission. No infrared counterpart was found. The results are consistent with the source being a previously unknown pulsar driving a bow shock through the ambient medium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

μ SR and magnetometry study of superconducting 5% Pt-doped IrTe 2

In this paper, we present magnetometry and muon spin rotation ( SR) measurements of the superconducting dichalcogenide Ir 0.95 Pt 0.05 Te 2 . From both sets of measurements we calculate the penetration depth and thence superfluid density as a function of temperature. The temperature dependence of the superfluid densities from both sets of data indicate fully gapped superconductivity that can be fit to a conventional s-wave model and yield fitting parameters consistent with a BCS weak coupling superconductor. Finally, we therefore see no evidence for exotic superconductivity in Ir 0.95 Pt 0.05 Te 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2019

Multiresolution spatiotemporal mechanical model of the heart as a prior to constrain the solution for 4D models of the heart

In several nuclear cardiac imaging applications (SPECT and PET), images are formed by reconstructing tomographic data using an iterative reconstruction algorithm with corrections for physical factors involved in the imaging detection process and with corrections for cardiac and respiratory motion. The physical factors are modeled as coefficients in the matrix of a system of linear equations and include attenuation, scatter, and spatially varying geometric response. The solution to the tomographic problem involves solving the inverse of this system matrix. This requires the design of an iterative reconstruction algorithm with a statistical model that best fits the data acquisition. The most appropriate model is based on a Poisson distribution. Using Bayes Theorem, an iterative reconstruction algorithm is designed to determine the maximum a posteriori estimate of the reconstructed image with constraints that maximizes the Bayesian likelihood function for the Poisson statistical model. The a priori distribution is formulated as the joint entropy (JE) to measure the similarity between the gated cardiac PET image and the cardiac MRI cine image modeled as a FE mechanical model. In conclusion, the developed algorithm shows the potential of using a FE mechanical model of the heart derived from a cardiac MRI cine scan to constrain solutions of gated cardiac PET images.

60 APPLIED LIFE SCIENCES↗