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Results for “Model fitting”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2013

NONLINEAR FORCE-FREE MAGNETIC FIELD FITTING TO CORONAL LOOPS WITH AND WITHOUT STEREOSCOPY

We developed a new nonlinear force-free magnetic field (NLFFF) forward-fitting algorithm based on an analytical approximation of force-free and divergence-free NLFFF solutions, which requires as input a line-of-sight magnetogram and traced two-dimensional (2D) loop coordinates of coronal loops only, in contrast to stereoscopically triangulated three-dimensional loop coordinates used in previous studies. Test results of simulated magnetic configurations and from four active regions observed with STEREO demonstrate that NLFFF solutions can be fitted with equal accuracy with or without stereoscopy, which relinquishes the necessity of STEREO data for magnetic modeling of active regions (on the solar disk). The 2D loop tracing method achieves a 2D misalignment of {mu}{sub 2} = 2. Degree-Sign 7 {+-} 1. Degree-Sign 3 between the model field lines and observed loops, and an accuracy of Almost-Equal-To 1.0% for the magnetic energy or free magnetic energy ratio. The three times higher spatial resolution of TRACE or SDO/AIA (compared with STEREO) also yields a proportionally smaller misalignment angle between model fit and observations. Visual/manual loop tracings are found to produce more accurate magnetic model fits than automated tracing algorithms. The computation time of the new forward-fitting code amounts to a few minutes per active region.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models

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99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

glmnetLRC f/k/a lrc package: Logistic Regression Classification

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold for binary classification.

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DOE OSTI2016

glmnetLRC f/k/a lrc package: Logistic Regression Classification

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DOE OSTI2015

Dynamics of neutrals and ions in an ultrafast laser produced Zn plasma

Optical time of flight dynamics of neutrals and ions in an ultrafast laser produced zinc plasma generated by irradiating a solid zinc target using 100 fs laser pulses is investigated. An acceleration of ions is observed which arises from internal Coulomb forces acting between charged species in the plasma. Some of the fast ions recombine with electrons in the plasma and generate fast neutrals. Plasma plume imaging performed at various ambient pressures indicates adiabatic expansion at lower pressures and plume front deceleration at higher pressures: at lower pressures the plume front-time (R-t) plot displays a linear expansion, shock wave model fits to the data at 5 Torr and at higher pressures the data fits better to the drag model. Furthermore, around an intermediate pressure of 10 Torr, the R-t plot fits to the shock wave model at earlier stages of plasma expansion, while it fits to the drag model at the later stages. These investigations provide relevant information on the acceleration of ions and neutrals in an expanding zinc plasma plume produced by ultrafast laser pulses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Direct uranium enrichment assay in gaseous uranium hexafluoride with laser induced breakdown spectroscopy

A set of eleven U atomic emission lines, between 421.099 and 421.460 nm, were characterized for direct enrichment assay of gaseous UF 6 samples with laser induced breakdown spectroscopy (LIBS). Several iterative, multivariate nonlinear spectral-fitting algorithms were evaluated for their efficacies to extract the enrichment information from the measured LIBS spectra. Furthermore, wavelength-dependent weight factors, which take into consideration of the spectral-line position in the fitting model, the determined isotopic ratio, and the isotopic shift of the emission line, are essential for the spectral-fitting model to function adequately. The analytical accuracies and precision were typically within 0.5% in absolute [ 235 U/( 235 U + 238 U)] ratios.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2014

Alcock-paczynski cosmological test

In order to test the expansion of the universe and its geometry, we carry out an Alcock-Paczyński cosmological test, that is, an evaluation of the ratio of observed angular size to radial/redshift size. The main advantage of this test is that it does not depend on the evolution of the galaxies but only on the geometry of the universe. However, the redshift distortions produced by the peculiar velocities of the gravitational infall also have an influence, which should be separated from the cosmological effect. We derive the anisotropic correlation function of sources in three surveys within the Sloan Digital Sky Survey (SDSS): galaxies from SDSS-III/Baryon Oscillation Spectroscopic Survey Data Release 10 (BOSS-DR10) and QSOs from SDSS-II and SDSS-III/BOSS-DR10. From these, we are able to disentangle the dynamic and geometric distortions and thus derive the ratio of observed angular size to radial/redshift size at different redshifts. We also add some other values available in the literature. Then we use the data to evaluate which cosmological model fits them. We used six different models: concordance ΛCDM, Einstein-de Sitter, open-Friedman cosmology without dark energy, flat quasi-steady state cosmology, a static universe with a linear Hubble law, and a static universe with tired-light redshift. Only two of the six models above fit the data of the Alcock-Paczyński test: concordance ΛCDM and static universe with tired-light redshift, whereas the rest of them are excluded at a >95% confidence level. If we assume that ΛCDM is the correct one, the best fit with a free Ω {sub m} is produced for Ω{sub m}=0.24{sub −0.07}{sup +0.10}.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Ventilation/Perfusion Positron Emission Tomography—Based Assessment of Radiation Injury to Lung

Purpose: To investigate {sup 68}Ga-ventilation/perfusion (V/Q) positron emission tomography (PET)/computed tomography (CT) as a novel imaging modality for assessment of perfusion, ventilation, and lung density changes in the context of radiation therapy (RT). Methods and Materials: In a prospective clinical trial, 20 patients underwent 4-dimensional (4D)-V/Q PET/CT before, midway through, and 3 months after definitive lung RT. Eligible patients were prescribed 60 Gy in 30 fractions with or without concurrent chemotherapy. Functional images were registered to the RT planning 4D-CT, and isodose volumes were averaged into 10-Gy bins. Within each dose bin, relative loss in standardized uptake value (SUV) was recorded for ventilation and perfusion, and loss in air-filled fraction was recorded to assess RT-induced lung fibrosis. A dose-effect relationship was described using both linear and 2-parameter logistic fit models, and goodness of fit was assessed with Akaike Information Criterion (AIC). Results: A total of 179 imaging datasets were available for analysis (1 scan was unrecoverable). An almost perfectly linear negative dose-response relationship was observed for perfusion and air-filled fraction (r{sup 2}=0.99, P<.01), with ventilation strongly negatively linear (r{sup 2}=0.95, P<.01). Logistic models did not provide a better fit as evaluated by AIC. Perfusion, ventilation, and the air-filled fraction decreased 0.75 ± 0.03%, 0.71 ± 0.06%, and 0.49 ± 0.02%/Gy, respectively. Within high-dose regions, higher baseline perfusion SUV was associated with greater rate of loss. At 50 Gy and 60 Gy, the rate of loss was 1.35% (P=.07) and 1.73% (P=.05) per SUV, respectively. Of 8/20 patients with peritumoral reperfusion/reventilation during treatment, 7/8 did not sustain this effect after treatment. Conclusions: Radiation-induced regional lung functional deficits occur in a dose-dependent manner and can be estimated by simple linear models with 4D-V/Q PET/CT imaging. These findings may inform future studies of functional lung avoidance using V/Q PET/CT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

Low dose radiation risks for women surviving the a-bombs in Japan: generalized additive model

Background: Analyses of cancer mortality and incidence in Japanese A-bomb survivors have been used to estimate radiation risks, which are generally higher for women. Relative Risk (RR) is usually modelled as a linear function of dose. Extrapolation from data including high doses predicts small risks at low doses. Generalized Additive Models (GAMs) are flexible methods for modelling non-linear behaviour. Methods: GAMs are applied to cancer incidence in female low dose subcohorts, using anonymous public data for the 1958 – 1998 Life Span Study, to test for linearity, explore interactions, adjust for the skewed dose distribution, examine significance below 100 mGy, and estimate risks at 10 mGy. Results: For all solid cancer incidence, RR estimated from 0 – 100 mGy and 0 – 20 mGy subcohorts is significantly raised. The response tapers above 150 mGy. At low doses, RR increases with age-at-exposure and decreases with time-since-exposure, the preferred covariate. Using the empirical cumulative distribution of dose improves model fit, and capacity to detect non-linear responses. RR is elevated over wide ranges of covariate values. Results are stable under simulation, or when removing exceptional data cells, or adjusting neutron RBE. Estimates of Excess RR at 10 mGy using the cumulative dose distribution are 10 – 45 times higher than extrapolations from a linear model fitted to the full cohort. Below 100 mGy, quasipoisson models find significant effects for all solid, squamous, uterus, corpus, and thyroid cancers, and for respiratory cancers when age-at-exposure > 35 yrs. Results for the thyroid are compatible with studies of children treated for tinea capitis, and Chernobyl survivors. Results for the uterus are compatible with studies of UK nuclear workers and the Techa River cohort. Conclusion: Non-linear models find large, significant cancer risks for Japanese women exposed to low dose radiation from the atomic bombings. The risks should be reflected in protection standards.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A New Approach for Obtaining Cosmological Constraints from Type Ia Supernovae using Approximate Bayesian Computation

Cosmological parameter estimation techniques that robustly account for systematic measurement uncertainties will be crucial for the next generation of cosmological surveys. We present a new analysis method, superABC, for obtaining cosmological constraints from Type Ia supernova (SN Ia) light curves using Approximate Bayesian Computation (ABC) without any likelihood assumptions. The ABC method works by using a forward model simulation of the data where systematic uncertainties can be simulated and marginalized over. A key feature of the method presented here is the use of two distinct metrics, the `Tripp' and `Light Curve' metrics, which allow us to compare the simulated data to the observed data set. The Tripp metric takes as input the parameters of models fit to each light curve with the SALT-II method, whereas the Light Curve metric uses the measured fluxes directly without model fitting. We apply the superABC sampler to a simulated data set of $\sim$1000 SNe corresponding to the first season of the Dark Energy Survey Supernova Program. Varying $\Omega_m, w_0, \alpha$ and $\beta$ and a magnitude offset parameter, with no systematics we obtain $\Delta(w_0) = w_0^{\rm true} - w_0^{\rm best \, fit} = -0.036\pm0.109$ (a $\sim11$% 1$\sigma$ uncertainty) using the Tripp metric and $\Delta(w_0) = -0.055\pm0.068$ (a $\sim7$% 1$\sigma$ uncertainty) using the Light Curve metric. Including 1% calibration uncertainties in four passbands, adding 4 more parameters, we obtain $\Delta(w_0) = -0.062\pm0.132$ (a $\sim14$% 1$\sigma$ uncertainty) using the Tripp metric. Overall we find a $17$% increase in the uncertainty on $w_0$ with systematics compared to without. We contrast this with a MCMC approach where systematic effects are approximately included. We find that the MCMC method slightly underestimates the impact of calibration uncertainties for this simulated data set.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Extensions of BLUP Models for Genomic Prediction in Heterogeneous Populations: Application in a Diverse Switchgrass Sample

Genomic prediction is a useful tool to accelerate genetic gain in selection using DNA marker information. However, this technology typically relies on standard prediction procedures, such as genomic BLUP, that are not designed to accommodate population heterogeneity resulting from differences in marker effects across populations. In this study, we assayed different prediction procedures to capture marker-by-population interactions in genomic prediction models. Prediction procedures included genomic BLUP and two kernel-based extensions of genomic BLUP which explicitly accounted for population heterogeneity. To model population heterogeneity, dissemblance between populations was either depicted by a unique coefficient (as previously reported), or a more flexible function of genetic distance between populations (proposed herein). Models under investigation were applied in a diverse switchgrass sample under two validation schemes: whole-sample calibration, where all individuals except selection candidates are included in the calibration set, and cross-population calibration, where the target population is entirely excluded from the calibration set. First, we showed that using fixed effects, from principal components or putative population groups, appeared detrimental to prediction accuracy, especially in cross-population calibration. Then we showed that modelling population heterogeneity by our proposed procedure resulted in highly significant improvements in model fit. In such cases, gains in accuracy were often positive. These results suggest that population heterogeneity may be parsimoniously captured by kernel methods. However, in cases where improvement in model fit by our proposed procedure is null-to-moderate, ignoring heterogeneity should probably be preferred due to the robustness and simplicity of the standard genomic BLUP model.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Single-shot 3D coherent diffractive imaging of core-shell nanoparticles with elemental specificity

We report 3D coherent diffractive imaging (CDI) of Au/Pd core-shell nanoparticles with 6.1nm spatial resolution with elemental specificity. We measured single-shot diffraction patterns of the nanoparticles using intense x-ray free electron laser pulses. By exploiting the curvature of the Ewald sphere and the symmetry of the nanoparticle, we reconstructed the 3D electron density of 34 core-shell structures from these diffraction patterns. To extract 3D structural information beyond the diffraction signal, we implemented a super-resolution technique by taking advantage of CDI’s quantitative reconstruction capabilities. We used high-resolution model fitting to determine the Au core size and the Pd shell thickness to be 65.0±1.0nm and 4.0±0.5nm, respectively. We also identified the 3D elemental distribution inside the nanoparticles with an accuracy of 3%. To further examine the model fitting procedure, we simulated noisy diffraction patterns from a Au/Pd core-shell model and a solid Au model and confirmed the validity of the method. We anticipate this super-resolution CDI method can be generally used for quantitative 3D imaging of symmetrical nanostructures with elemental specificity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Removing flat directions in standard model EFT fits: How polarized electron-ion collider data can complement the LHC

We study the potential of future electron-ion collider (EIC) data to probe four-fermion operators in the Standard Model effective field theory (SMEFT). The ability to perform measurements with both polarized electron and proton beams at the EIC provides a powerful tool that can disentangle the effects from different SMEFT operators. We compare the potential constraints from an EIC with those obtained from Drell-Yan data at the Large Hadron Collider. We show that EIC data play an important complementary role since they probe combinations of Wilson coefficients not accessible through available Drell-Yan measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Forward Modeling of 3-D Ion Properties in Jupiter’s Magnetosphere Using Juno/JADE-I Data

The Jovian Auroral Distributions Experiment Ion sensor (JADE-I) on NASA’s Juno mission provides in-situ measurements of ions from 0.1 to 46.2 keV/q inside Jupiter’s magnetosphere. JADE-I is used to study the plasma with two types of datasets from the same measurement: Time-of-flight (TOF) and SPECIES. The TOF dataset provides mass-per-charge measurements with a range of 1–64 amu/q but oversamples particles over 6π steradian viewing per spacecraft spin and has little directional information. On the other hand, the SPECIES dataset can provide a good measurement of the flow direction but does not provide mass-per-charge information due to the telemetry limit. In this study, we developed a 2-step forward modeling method that combines the advantages and avoids the disadvantages of TOF and SPECIES data to derive the 3-D properties of heavy ions. Assuming that the ion velocity distribution can be described with the kappa distribution, we first perform the forward model fit of the TOF data to calculate the relative abundance of heavy ion species. Then we fix the relative abundance and perform the second forward model fit on the SPECIES data. Here, using this method, we obtain the densities of different heavy ions, the shared temperature and kappa value, and the 3-D flow velocity vector. Some data examples of the equatorial plasma disk before Perijove 24 are included to demonstrate the method. Plasma properties can then be mapped to explore spatial and temporal variabilities in Jupiter’s magnetosphere.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

REAL OR INTERLOPER? THE REDSHIFT LIKELIHOODS OF z > 8 GALAXIES IN THE HUDF12

In the absence of spectra, the technique of fitting model galaxy template spectra to observed photometric fluxes has become the workhorse method for determining the redshifts and other properties for high-z galaxy candidates. In this paper, we present an analysis of the most recent and possibly most distant galaxies (z {approx} 8-12) discovered in the Hubble Ultra Deep Field (HUDF) using a more robust method of redshift estimation based on Markov Chain Monte Carlo (MCMC) fitting, in contrast to the ''best fit'' models obtained using simpler {chi}{sup 2} minimization techniques. The advantage of MCMC fitting is the ability to accurately estimate the probability density function of the redshift for each object as well as any input model parameters. This makes it possible to derive accurate, credible intervals by properly marginalizing over all other input model parameters. We apply our method to 13 recently identified sources in the HUDF and show that, despite claims based on {chi}{sup 2} minimization, none of these sources can be securely ruled out as low redshift interlopers (z < 4) due to the low signal-to-noise of currently available observations. There is an average probability of 21% that these sources are low redshift interlopers.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Main-sequence Scatter is Real: The Joint Dependence of Galaxy Clustering on Star Formation and Stellar Mass

We present new measurements of the clustering of stellar-mass-complete samples of ∼40,000 SDSS galaxies at z ∼ 0.03 as a joint function of stellar mass and specific star formation rate (sSFR). Our results confirm what Coil et al. find at z ∼ 0.7: galaxy clustering is a stronger function of sSFR at fixed stellar mass than of stellar mass at fixed sSFR. We also find that galaxies above the star-forming main sequence (SFMS) with higher sSFR are less clustered than galaxies below the SFMS with lower sSFR, at a given stellar mass. A similar trend is present for quiescent galaxies. This confirms that main-sequence scatter, and scatter within the quiescent sequence, is physically connected to the large-scale cosmic density field. We compare the resulting galaxy bias versus sSFR, and relative bias versus sSFR ratio, for different galaxy samples across 0 < z < 1.2 to mock galaxy catalogs based on the empirical galaxy evolution model of Behroozi et al. This model fits PRIMUS and DEEP2 clustering data well at intermediate redshift, but agreement with SDSS is not as strong. We show that increasing the correlation between galaxy SFR and halo accretion rate at z ∼ 0 in the model substantially improves agreement with SDSS data. Mock catalogs suggest that central galaxies contribute substantially to the dependence of clustering on sSFR at a given stellar mass and that the signal is not simply an effect of satellite galaxy fraction differences with sSFR. Our results are highly constraining for galaxy evolution models and show that the stellar-to-halo mass relation depends on sSFR.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Characterizing 51 Eri b from 1 to 5 μm: A Partly Cloudy Exoplanet

We present spectrophotometry spanning 1–5 μm of 51 Eridani b, a 2–10 M{sub Jup} planet discovered by the Gemini Planet Imager Exoplanet Survey. In this study, we present new K1 (1.90–2.19 μm) and K2 (2.10–2.40 μm) spectra taken with the Gemini Planet Imager as well as an updated L {sub P} (3.76 μm) and new M {sub S} (4.67 μm) photometry from the NIRC2 Narrow camera. The new data were combined with J (1.13–1.35 μm) and H (1.50–1.80 μm) spectra from the discovery epoch with the goal of better characterizing the planet properties. The 51 Eri b photometry is redder than field brown dwarfs as well as known young T-dwarfs with similar spectral type (between T4 and T8), and we propose that 51 Eri b might be in the process of undergoing the transition from L-type to T-type. We used two complementary atmosphere model grids including either deep iron/silicate clouds or sulfide/salt clouds in the photosphere, spanning a range of cloud properties, including fully cloudy, cloud-free, and patchy/intermediate-opacity clouds. The model fits suggest that 51 Eri b has an effective temperature ranging between 605 and 737 K, a solar metallicity, and a surface gravity of log(g) = 3.5–4.0 dex, and the atmosphere requires a patchy cloud atmosphere to model the spectral energy distribution (SED). From the model atmospheres, we infer a luminosity for the planet of −5.83 to −5.93 (logL/L{sub ⊙}), leaving 51 Eri b in the unique position of being one of the only directly imaged planets consistent with having formed via a cold-start scenario. Comparisons of the planet SED against warm-start models indicate that the planet luminosity is best reproduced by a planet formed via core accretion with a core mass between 15 and 127 M{sub ⊕}.

79 ASTRONOMY AND ASTROPHYSICS↗