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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

The use of copulas to practical estimation of multivariate stochastic differential equation mixed effects models

A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Fluid moments of the nonlinear Landau collision operator

An important problem in plasma physics is the lack of an accurate and complete description of Coulomb collisions in associated fluid models. To shed light on the problem, this Letter introduces an integral identity involving the multivariate Hermite tensor polynomials and presents a method for computing exact expressions for the fluid moments of the nonlinear Landau collision operator. The proposed methodology provides a systematic and rigorous means of extending the validity of fluid models that have an underlying inverse-square force particle dynamics to arbitrary collisionality and flow.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2011

Manifestation of hydrogen bonds of aqueous ethanol solutions in the Raman scattering spectra

Spectra of Raman scattering of light by aqueous ethanol solutions in the range of concentrations from pure water to 96% alcohol are studied. For water, 25%, and 40% solutions of ethanol in water, as well as for 96% alcohol the Raman spectra are measured at temperatures from the freezing point to nearly the boiling point. The changes in the shape of the stretching OH band are interpreted in terms of strengthening or weakening of hydrogen bonds between the molecules in the solution. The strongest hydrogen bonding of hydroxyl groups is observed at the ethanol content from 20 to 25 volume percent, which is explained by formation of ethanol hydrates of a definite type at the mentioned concentrations of alcohol. This is confirmed by means of the method of multivariate curve resolution, used to analyse the Raman spectra of aqueous ethanol solutions. With growing temperature the weakening of hydrogen bonding occurs in all studied systems, which consists in reducing the number of OH groups, linked by strong hydrogen bonds. (laser applications and other problems in quantum electronics)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Self-modulation oscillation regimes in fibre lasers with microoptomechanical resonance structures

Self-modulation oscillation regimes are studied in erbium fibre lasers with intracavity microoptomechanical structures (microoscillators) of different types, namely, based on silicon structures and consisting of special waveguide segments. Optical excitation of acoustomechanical vibrations of microoscillators is accomplished using photothermal effect or light pressure. Under the conditions of resonance interaction, i.e., when the eigenfrequencies of microoscillators coincide with the frequencies of relaxation oscillations or with those of intermode beats, the dependences of self-oscillation characteristics on the system parameters are found and the stability of the self-modulation frequency within 10{sup -4} - 10{sup -6} is obtained at relatively low (40 - 300) Q-factors of microoscillators. The possibility to construct multivariate (multichannel) fibreoptical sensors of physical quantities with frequency division of measurement channels is demonstrated. (optical fibres, lasers and amplifiers. properties and applications)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

RECONSTRUCTING THE INITIAL DENSITY FIELD OF THE LOCAL UNIVERSE: METHODS AND TESTS WITH MOCK CATALOGS

Our research objective in this paper is to reconstruct an initial linear density field, which follows the multivariate Gaussian distribution with variances given by the linear power spectrum of the current cold dark matter model and evolves through gravitational instabilities to the present-day density field in the local universe. For this purpose, we develop a Hamiltonian Markov Chain Monte Carlo method to obtain the linear density field from a posterior probability function that consists of two components: a prior of a Gaussian density field with a given linear spectrum and a likelihood term that is given by the current density field. The present-day density field can be reconstructed from galaxy groups using the method developed in Wang et al. Using a realistic mock Sloan Digital Sky Survey DR7, obtained by populating dark matter halos in the Millennium simulation (MS) with galaxies, we show that our method can effectively and accurately recover both the amplitudes and phases of the initial, linear density field. To examine the accuracy of our method, we use N-body simulations to evolve these reconstructed initial conditions to the present day. The resimulated density field thus obtained accurately matches the original density field of the MS in the density range 0.3{approx}<{rho}/ {rho}-bar {approx}<20 without any significant bias. In particular, the Fourier phases of the resimulated density fields are tightly correlated with those of the original simulation down to a scale corresponding to a wavenumber of {approx}1 h Mpc{sup -1}, much smaller than the translinear scale, which corresponds to a wavenumber of {approx}0.15 h Mpc{sup -1}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

REVERBERATION MAPPING OF A LOW-MASS BLACK HOLE IN A NARROW-LINE SEYFERT 1 GALAXY

We present results of a reverberation mapping (RM) campaign on the low black hole mass narrow-line Seyfert 1 (NLS1) galaxy SDSS J113913.91+335551.1 (hereafter SL01). Using the H{beta} measurements, we find a time lag {tau}= 12.5{sup +0.5}{sub -11} days and a broad-line velocity width of 1450 km s{sup -1} which implies a black hole mass of 3.8{sup +0.6}{sub -2.8} Multiplication-Sign 10{sup 6} M{sub Sun }. To further bolster our time lag results, we employ a secondary method based on the multivariate correlation function as described in Chelouche and Zucker, in which case we obtain consistent lags for the Balmer lines, yet without the need to spectrally deconvolve line from continuum emission processes. Given SL01's luminosity (L{sub bol} Almost-Equal-To 7 Multiplication-Sign 10{sup 43} erg s{sup -1}), we estimate an Eddington ratio (L{sub bol}/L{sub Edd}) of {approx}0.18. This fairly low-mass determination and rather high L{sub bol}/L{sub Edd} is consistent with the current paradigm that the nuclei of NLS1 galaxies host small black holes (as low as 10{sup 6} M{sub Sun }) with high accretion rates. SL01 is one of only a few NLS1s to date with robust RM results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

MAGIICAT III. Interpreting self-similarity of the circumgalactic medium with virial mass using Mg II absorption

In Churchill et al., we used halo abundance matching applied to 182 galaxies in the Mg II Absorber-Galaxy Catalog (MAGIICAT) and showed that the mean Mg II λ2796 equivalent width follows a tight inverse-square power law, W{sub r} (2796)∝(D/R {sub vir}){sup –2}, with projected location relative to the galaxy virial radius and that the Mg II absorption covering fraction is effectively invariant with galaxy virial mass, M {sub h}, over the range 10.7 ≤ log M {sub h}/M {sub ☉} ≤ 13.9. In this work, we explore multivariate relationships between W{sub r} (2796), virial mass, impact parameter, virial radius, and the theoretical cooling radius that further elucidate self-similarity in the cool/warm (T = 10{sup 4}-10{sup 4.5} K) circumgalactic medium (CGM) with virial mass. We show that virial mass determines the extent and strength of the Mg II absorbing gas such that the mean W{sub r} (2796) increases with virial mass at fixed distance while decreasing with galactocentric distance for fixed virial mass. The majority of the absorbing gas resides within D ≅ 0.3 R {sub vir}, independent of both virial mass and minimum absorption threshold; inside this region, and perhaps also in the region 0.3 < D/R {sub vir} ≤ 1, the mean W{sub r} (2796) is independent of virial mass. Contrary to absorber-galaxy cross-correlation studies, we show there is no anti-correlation between W{sub r} (2796) and virial mass. We discuss how simulations and theory constrained by observations support self-similarity of the cool/warm CGM via the physics governing star formation, gas-phase metal enrichment, recycling efficiency of galactic scale winds, filament and merger accretion, and overdensity of local environment as a function of virial mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

HSC-XXL: Baryon budget of the 136 XXL groups and clusters

Abstract We present our determination of the baryon budget for an X-ray-selected XXL sample of 136 galaxy groups and clusters spanning nearly two orders of magnitude in mass (M500 ∼ 1013–1015 M⊙) and the redshift range 0 ≲ z ≲ 1. Our joint analysis is based on the combination of Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) weak-lensing mass measurements, XXL X-ray gas mass measurements, and HSC and Sloan Digital Sky Survey multiband photometry. We carry out a Bayesian analysis of multivariate mass-scaling relations of gas mass, galaxy stellar mass, stellar mass of brightest cluster galaxies (BCGs), and soft-band X-ray luminosity, by taking into account the intrinsic covariance between cluster properties, selection effect, weak-lensing mass calibration, and observational error covariance matrix. The mass-dependent slope of the gas mass–total mass (M500) relation is found to be $1.29_{-0.10}^{+0.16}$, which is steeper than the self-similar prediction of unity, whereas the slope of the stellar mass–total mass relation is shallower than unity; $0.85_{-0.09}^{+0.12}$. The BCG stellar mass weakly depends on cluster mass with a slope of $0.49_{-0.10}^{+0.11}$. The baryon, gas mass, and stellar mass fractions as a function of M500 agree with the results from numerical simulations and previous observations. We successfully constrain the full intrinsic covariance of the baryonic contents. The BCG stellar mass shows the larger intrinsic scatter at a given halo total mass, followed in order by stellar mass and gas mass. We find a significant positive intrinsic correlation coefficient between total (and satellite) stellar mass and BCG stellar mass and no evidence for intrinsic correlation between gas mass and stellar mass. All the baryonic components show no redshift evolution.

Akino, Daichi↗
DOE OSTI2011

Copula cosmology: Constructing a likelihood function

To estimate cosmological parameters from a given data set, we need to construct a likelihood function, which sometimes has a complicated functional form. We introduce the copula, a mathematical tool to construct an arbitrary multivariate distribution function from one-dimensional marginal distribution functions with any given dependence structure. It is shown that a likelihood function constructed by the so-called Gaussian copula can reproduce very well the n-dimensional probability distribution of the cosmic shear power spectrum obtained from a large number of ray-tracing simulations. This suggests that the Copula likelihood will be a powerful tool for future weak lensing analyses, instead of the conventional multivariate Gaussian likelihood.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Factors associated with treatment limitations in two Swedish intensive care units: Prevalence and patient involvement

Abstract The aim was to study the prevalence, documentation, and patient involvement in treatment limitations (TLs) in two Swedish intensive care units (ICUs). All patients admitted to the ICUs of two Swedish regional hospitals in 2019 were screened for inclusion. Exclusion criteria included postanesthesia care <24 h. Patients were identified using the Swedish Intensive Care Registry (SIR) and data were extracted from SIR and hospital charts. Uni‐ and multivariable logistic analysis was performed to investigate associations with the presence of TLs. A total of 3090 patients were admitted to the two ICUs in 2019. After exclusion, 1019 patients were included in the study. 45.5% were women and the mean age was 62.9 years. 26.5% of the patients had one or several TLs. Age (OR 1.04 per one year increase 95% confidence interval (CI) 1.02–1.05), SAPS3‐score (OR 1.08 per one unit increase 95% CI 1.06–1.09) and ICU length of stay (OR 1.11 per one day increase 95% CI 1.05–1.17) were independently associated with an increased likelihood of receiving a TL. 17% of the patients were involved in the decision‐making process and in >30% of cases neither the patient nor next‐of‐kin were informed. Women were to a larger extent involved in the decision process than men (24.5 vs. 12.5% p < .05). When the intensivist documented why a TL was established, patient autonomy was four times more commonly stated as the motivation for the TL among women compared to men (15.5% vs. 3.8% p < .05). TLs were common in two Swedish ICUs but a substantial number of patients and next‐of‐kin were not involved in the decision‐making process or informed of the decision. Women were more often than men engaged in the decision to establish a TL.

Jönsson, Nino↗
DOE OSTI2022

Modeling of Supercritical CO2 Shell-and-Tube Heat Exchangers Under Extreme Conditions. Part I: Correlation Development

Abstract High-temperature supercritical CO2 Brayton cycles are promising possibilities for future stationary power generation and hybrid electric propulsion applications. Heat exchangers are critical components in supercritical CO2 thermal cycles and require accurate correlations and comprehensive performance modeling under extreme temperatures and pressures. In this paper (Part I), new Colburn and friction factor correlations are developed to quantify shell-side heat transfer and friction characteristics of flow within heat exchangers in the shell-and-tube configuration. Using experimental and computational fluid dynamics (CFD) data sets from existing literature, multivariate regression analysis is conducted to achieve correlations that capture the effect of multiple critical geometric parameters. These correlations offer superior accuracy and versatility as compared to previous studies and predict the thermohydraulic performance of about 90% of the existing experimental and CFD data within ±15%. Supplementary thermohydraulic performance data are acquired from CFD simulations with supercritical CO2 as working fluid to validate the developed correlations and demonstrate its capability to be applied to supercrtical CO2 heat exchangers.

Engineering↗
DOE OSTI2016

Metal-assisted polyatomic SIMS and laser desorption/ionization for enhanced small molecule imaging of bacterial biofilms

Mass spectrometry imaging (MSI) has become an important analytical tool for many sectors of science and medicine. As the application of MSI expands into new areas of inquiry, existing methodologies must be adapted and improved to meet emerging challenges. In particular salient is the need for small molecule imaging methods that are compatible with complex multicomponent systems, a challenge that is amplified by the effects of analyte migration and matrix interference. Furthermore, with a focus on microbial biofilms from the opportunistic pathogen Pseudomonas aeruginosa, the relative advantages of two established microprobe-based MSI techniques—polyatomic secondary ion mass spectrometry (SIMS) and laser desorption/ionization—are compared, with emphasis on exploring the effect of surface metallization on small molecule imaging. A combination of qualitative image comparison and multivariate statistical analysis demonstrates that sputtering microbial biofilms with a 2.5 nm layer of gold selectively enhances C 60 -SIMS ionization for several molecular classes including rhamnolipids and 2-alkyl-quinolones. Metallization also leads to the reduction of in-source fragmentation and subsequent ionization of media-specific background polymers, which improves spectral purity and image quality. Our findings show that the influence of metallization upon ionization is strongly dependent on both the surface architecture and the analyte class, and further demonstrate that metal-assisted C 60 -SIMS is a viable method for small molecule imaging of intact molecular ions in complex biological systems. VC 2016 American Vacuum Society.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features

Purpose: The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Methods: Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Results: Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502–0.739, 95% Confidence Interval: 0.543–0.680,p < 0.002). Conclusions: Patterns in detection errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

TH-E-BRF-03: A Multivariate Interaction Model for Assessment of Hippocampal Vascular Dose-Response and Early Prediction of Radiation-Induced Neurocognitive Dysfunction

Purpose: Vascular injury could be a cause of hippocampal dysfunction leading to late neurocognitive decline in patients receiving brain radiotherapy (RT). Hence, our aim was to develop a multivariate interaction model for characterization of hippocampal vascular dose-response and early prediction of radiation-induced late neurocognitive impairments. Methods: 27 patients (17 males and 10 females, age 31–80 years) were enrolled in an IRB-approved prospective longitudinal study. All patients were diagnosed with a low-grade glioma or benign tumor and treated by 3-D conformal or intensity-modulated RT with a median dose of 54 Gy (50.4–59.4 Gy in 1.8− Gy fractions). Six DCE-MRI scans were performed from pre-RT to 18 months post-RT. DCE data were fitted to the modified Toft model to obtain the transfer constant of gadolinium influx from the intravascular space into the extravascular extracellular space, Ktrans, and the fraction of blood plasma volume, Vp. The hippocampus vascular property alterations after starting RT were characterized by changes in the hippocampal mean values of, μh(Ktrans)τ and μh(Vp)τ. The dose-response, Δμh(Ktrans/Vp)pre->τ, was modeled using a multivariate linear regression considering integrations of doses with age, sex, hippocampal laterality and presence of tumor/edema near a hippocampus. Finally, the early vascular dose-response in hippocampus was correlated with neurocognitive decline 6 and 18 months post-RT. Results: The μh(Ktrans) increased significantly from pre-RT to 1 month post-RT (p<0.0004). The multivariate model showed that the dose effect on Δμh(Ktrans)pre->1M post-RT was interacted with sex (p<0.0007) and age (p<0.00004), with the dose-response more pronounced in older females. Also, the vascular dose-response in the left hippocampus of females was significantly correlated with memory function decline at 6 (r = − 0.95, p<0.0006) and 18 (r = −0.88, p<0.02) months post-RT. Conclusion: The hippocampal vascular response to radiation could be sex and age dependent. The early hippocampal vascular dose-response could predict late neurocognitive dysfunction. (Support: NIH-RO1NS064973)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Sci—Thur AM: YIS - 02: Radiogenomic Modeling of Normal Tissue Toxicities in Prostate Cancer Patients Receiving Hypofractionated Radiotherapy

Inter-patient radiation sensitivity variability has recently been shown to have a genetic component. This genetic component may play a key role in explaining the fluctuating rates of radiation-induced toxicities (RITs). Single nucleotide polymorphisms (SNPs) have thus far yielded inconsistent results in delineating RITs while copy number variations (CNVs) have not yet been investigated for such purposes. We explore a radiogenomic modeling approach to investigate the association of CNVs and SNPs, along with clinical and dosimetric variables, in radiation induced rectal bleeding (RB) and erectile dysfunction (ED) in prostate cancer patients treated with curative hypofractionated irradiation. A cohort of 62 prostate cancer patients who underwent hypofractionated radiotherapy (66 Gy in 22 fractions) between 2002 to 2010 were retrospectively genotyped for CNV and SNP rs5489 in the xrcc1 DNA repair gene. Late toxicity rates for RB grade 2 and 3 and grade 3 alone were 29.0% and 12.9%, respectively. ED toxicity was found to be 62.9%. Radiogenomic model performance was evaluated using receiver operating characteristic area under the curve (AUC) and resampling by cross-validation. Binary variables were evaluated using Chi-squared contingency table analysis and multivariate models by Spearman's rank correlation coefficient (rs). Ten patients were found to have three copies of xrcc1 CNV (RB: χ{sup 2}=14.6, p<0.001 and ED: χ{sup 2}=4.88, p=0.0272) and twelve had heterozygous rs25489 SNP (RB: χ{sup 2}=0.278, p=0.599 and ED: χ{sup 2}=0.112, p=0.732). Radiogenomic modeling yielded significant, cross-validated NTCP models for RB (AUC=0.665) and ED (AUC=0.754). These results indicate that CNVs may be potential predictive biomarkers of both late ED and RB.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Bayesian network ensemble as a multivariate strategy to predict radiation pneumonitis risk

Purpose: Prediction of radiation pneumonitis (RP) has been shown to be challenging due to the involvement of a variety of factors including dose–volume metrics and radiosensitivity biomarkers. Some of these factors are highly correlated and might affect prediction results when combined. Bayesian network (BN) provides a probabilistic framework to represent variable dependencies in a directed acyclic graph. The aim of this study is to integrate the BN framework and a systems’ biology approach to detect possible interactions among RP risk factors and exploit these relationships to enhance both the understanding and prediction of RP. Methods: The authors studied 54 nonsmall-cell lung cancer patients who received curative 3D-conformal radiotherapy. Nineteen RP events were observed (common toxicity criteria for adverse events grade 2 or higher). Serum concentration of the following four candidate biomarkers were measured at baseline and midtreatment: alpha-2-macroglobulin, angiotensin converting enzyme (ACE), transforming growth factor, interleukin-6. Dose-volumetric and clinical parameters were also included as covariates. Feature selection was performed using a Markov blanket approach based on the Koller–Sahami filter. The Markov chain Monte Carlo technique estimated the posterior distribution of BN graphs built from the observed data of the selected variables and causality constraints. RP probability was estimated using a limited number of high posterior graphs (ensemble) and was averaged for the final RP estimate using Bayes’ rule. A resampling method based on bootstrapping was applied to model training and validation in order to control under- and overfit pitfalls. Results: RP prediction power of the BN ensemble approach reached its optimum at a size of 200. The optimized performance of the BN model recorded an area under the receiver operating characteristic curve (AUC) of 0.83, which was significantly higher than multivariate logistic regression (0.77), mean heart dose (0.69), and a pre-to-midtreatment change in ACE (0.66). When RP prediction was made only with pretreatment information, the AUC ranged from 0.76 to 0.81 depending on the ensemble size. Bootstrap validation of graph features in the ensemble quantified confidence of association between variables in the graphs where ten interactions were statistically significant. Conclusions: The presented BN methodology provides the flexibility to model hierarchical interactions between RP covariates, which is applied to probabilistic inference on RP. The authors’ preliminary results demonstrate that such framework combined with an ensemble method can possibly improve prediction of RP under real-life clinical circumstances such as missing data or treatment plan adaptation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-CD-BRB-04: Automated Radiomic Features Complement the Prognostic Value of VASARI in the TCGA-GBM Dataset

Purpose: To compare the complementary prognostic value of automated Radiomic features to that of radiologist-annotated VASARI features in TCGA-GBM MRI dataset. Methods: For 96 GBM patients, pre-operative MRI images were obtained from The Cancer Imaging Archive. The abnormal tumor bulks were manually defined on post-contrast T1w images. The contrast-enhancing and necrotic regions were segmented using FAST. From these sub-volumes and the total abnormal tumor bulk, a set of Radiomic features quantifying phenotypic differences based on the tumor intensity, shape and texture, were extracted from the post-contrast T1w images. Minimum-redundancy-maximum-relevance (MRMR) was used to identify the most informative Radiomic, VASARI and combined Radiomic-VASARI features in 70% of the dataset (training-set). Multivariate Cox-proportional hazards models were evaluated in 30% of the dataset (validation-set) using the C-index for OS. A bootstrap procedure was used to assess significance while comparing the C-Indices of the different models. Results: Overall, the Radiomic features showed a moderate correlation with the radiologist-annotated VASARI features (r = −0.37 – 0.49); however that correlation was stronger for the Tumor Diameter and Proportion of Necrosis VASARI features (r = −0.71 – 0.69). After MRMR feature selection, the best-performing Radiomic, VASARI, and Radiomic-VASARI Cox-PH models showed a validation C-index of 0.56 (p = NS), 0.58 (p = NS) and 0.65 (p = 0.01), respectively. The combined Radiomic-VASARI model C-index was significantly higher than that obtained from either the Radiomic or VASARI model alone (p = <0.001). Conclusion: Quantitative volumetric and textural Radiomic features complement the qualitative and semi-quantitative annotated VASARI feature set. The prognostic value of informative qualitative VASARI features such as Eloquent Brain and Multifocality is increased with the addition of quantitative volumetric and textural features from the contrast-enhancing and necrotic tumor regions. These results should be further evaluated in larger validation cohorts.

60 APPLIED LIFE SCIENCES↗