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At least 991 records · Page 55

Self-consistent RPA based on a many-body vacuum

Self-Consistent RPA is extended in a way so that it is compatible with a variational ansatz for the ground-state wave function as a fermionic many-body vacuum. Employing the usual equation-of-motion technique, we arrive at extended RPA equations of the Self-Consistent RPA structure. In principle the Pauli principle is, therefore, fully respected. However, the correlation functions entering the RPA matrix can only be obtained from a systematic expansion in powers of some combinations of RPA amplitudes. We demonstrate for a model case that this expansion may converge rapidly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Data-Consistent Solutions to Stochastic Inverse Problems Using a Probabilistic Multi-Fidelity Method Based on Conditional Densities

In this work, we build upon a recently developed approach for solving stochastic inverse problems based on a combination of measure-theoretic principles and Bayes' rule. We propose a multi-fidelity method to reduce the computational burden of performing uncertainty quantification using high-fidelity models. This approach is based on a Monte Carlo framework for uncertainty quantification that combines information from solvers of various fidelities to obtain statistics on the quantities of interest of the problem. In particular, our goal is to generate samples from a high-fidelity push-forward density at a fraction of the costs of standard Monte Carlo methods, while maintaining flexibility in the number of random model input parameters. Key to this methodology is the construction of a regression model to represent the stochastic mapping between the low- and high-fidelity models, such that most of the computations can be leveraged to the low-fidelity model. To that end, we employ Gaussian process regression and present extensions to multi-level-type hierarchies as well as to the case of multiple quantities of interest. Finally, we demonstrate the feasibility of the framework in several numerical examples.

97 MATHEMATICS AND COMPUTING↗

Workshop on Incomplete Network Data Held at Sandia National Labs – Livermore

While network analysis is applied in a broad variety of scientific fields (including physics, computer science, biology, and the social sciences), how networks are constructed and the resulting bias and incompleteness have drawn more limited attention. For example, in biology, gene networks are typically developed via experiment -- many actual interactions are likely yet to be discovered. In addition to this incompleteness, the data-collection processes can introduce significant bias into the observed network datasets. For instance, if you observe part of the World Wide Web network through a classic random walk, then high degree nodes are more likely to be found than if you had selected nodes at random. Unfortunately, such incomplete and biasing data collection methods must be often used.

97 MATHEMATICS AND COMPUTING↗

Deployment of salt sample extraction system at an engineering-scale electrorefiner

The goal of the salt sampling program at Argonne is to develop and deploy automated molten salt sampling approaches for interfacing relevant unit operations with salt analysis to improve the timeliness of sampling-based accountancy measurements. Two technologies under development in support of this goal are a vacuum sampling loop module and a high-throughput pneumatic sample generator module. Compared to traditional point sampling approaches (i.e., dip probes), the vacuum sampling loop facilitates the collection of a larger cross-section of the bulk salt in order to collect more representative samples. The vacuum sampling approach also eliminates the risk of dross contamination of samples and avoids the use of moving parts in the salt. The pneumatic sample generator module is used to facilitate high-throughput sample analysis to improve the measurement precision of any given analytical technique by averaging out random sampling and measurement errors. In FY21, two methods for integrating these two modules were tested including direct fluidic coupling and coupling using a solid salt transfer mechanism. Solid salt transfer was ultimately selected over fluidic coupling, primarily to enable the transport of samples over longer distances to support automated at-line integration with high-precision techniques (such as microcalorimetry) that cannot withstand the conditions near an electrorefining process. To facilitate rapid solid salt coupling, new mechanisms were developed for rapidly charging and discharging salt sample tubes at the vacuum sampling loop and pneumatic sample generator modules, respectively. While the charging mechanism will be deployed in FY22, the discharge mechanism was tested in FY21 and is described here. The solid salt tube transfer method was deployed at one of Argonne’s engineering-scale electrorefiners to implement at-line high-throughput pneumatic micro-sample generation capabilities. The approach was used to generate precise uranium- and lanthanide-bearing electrorefiner micro-samples with the specific dimensions requested by researchers at Los Alamos National Laboratory for use in testing their novel microcalorimeter x-ray techniques. The solid salt transfer mechanism proved not only to be an effective means of integrating the precision sample generator with vacuum sampling, but also improved the performance of the sampler generator. To discharge salt from the sample tubes at the sampler generator, tube segments were inserted directly into the sample generator’s Helmholtz chamber and pressure pulse actuations were used to generate precision molten salt samples directly from the tube segments. The direct insertion of sample tubes into the sample generator enabled rapid loading of the salt and prevented salt from contacting most of the interior surfaces of the sample generator, which eliminated cross-contamination between runs. The vacuum sampling-loop tube charging mechanism will support high-throughput tube sampling operations by employing a dynamic vacuum filling process to fill short charge tubes that are configured to be rapidly connected and disconnected from the loop. The dynamic vacuum sampling operation will be automated, and sample tube handling can be executed with simple overhead actuation. Because the modular sampling approach described here eliminates the need for new high-radiation sample handling capabilities, salt-wetted seals, salt-wetted moving parts, and heated transfer lines outside the electrorefiner, it will address most of the remaining technical challenges for the at-line deployment of high-precision analytical techniques which will enable significant reductions in the time delay for sampling-based high-precision accountancy measurements.

42 ENGINEERING↗

Simplifying Probability Elicitation and Uncertainty Modeling in Bayesian Networks

In this paper we contribute two methods that simplify the demands of knowledge elicitation for particular types of Bayesian networks. The first method simplify the task of providing probabilities when the states that a random variable takes can be described by a new, fully ordered state set in which a state implies all the preceding states. The second method leverages Dempster-Shafer theory of evidence to provide a way for the expert to express the degree of ignorance that they feel about the estimates being provided.

99 GENERAL AND MISCELLANEOUS↗

SPECT Analysis of Cardiac Perfusion Changes After Whole-Breast/Chest Wall Radiation Therapy With or Without Active Breathing Coordinator: Results of a Randomized Phase 3 Trial

Purpose: Cardiac muscle perfusion, as determined by single-photon emission computed tomography (SPECT), decreases after breast and/or chest wall (BCW) irradiation. The active breathing coordinator (ABC) enables radiation delivery when the BCW is farther from the heart, thereby decreasing cardiac exposure. We hypothesized that ABC would prevent radiation-induced cardiac toxicity and conducted a randomized controlled trial evaluating myocardial perfusion changes after radiation for left-sided breast cancer with or without ABC. Methods and Materials: Stages I to III left breast cancer patients requiring adjuvant radiation therapy (XRT) were randomized to ABC or No-ABC. Myocardial perfusion was evaluated by SPECT scans (before and 6 months after BCW radiation) using 2 methods: (1) fully automated quantitative polar mapping; and (2) semiquantitative visual assessment. The left ventricle was divided into 20 segments for the polar map and 17 segments for the visual method. Segments were grouped by anatomical rings (apical, mid, basal) or by coronary artery distribution. For the visual method, 2 nuclear medicine physicians, blinded to treatment groups, scored each segment's perfusion. Scores were analyzed with nonparametric tests and linear regression. Results: Between 2006 and 2010, 57 patients were enrolled and 43 were available for analysis. The cohorts were well matched. The apical and left anterior descending coronary artery segments had significant decreases in perfusion on SPECT scans in both ABC and No-ABC cohorts. In unadjusted and adjusted analyses, controlling for pretreatment perfusion score, age, and chemotherapy, ABC was not significantly associated with prevention of perfusion deficits. Conclusions: In this randomized controlled trial, ABC does not appear to prevent radiation-induced cardiac perfusion deficits.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Simulation of solute transport through heterogeneous networks: analysis using the method of moments and the statistics of local transport characteristics

We used a time domain random walk approach to simulate passive solute transport in networks. In individual pores, solute transport was modeled as a combination of Poiseuille flow and Taylor dispersion. The solute plume data were interpreted via the method of moments. Analysis of the first and second moments showed that the longitudinal dispersivity increased with increasing coefficient of variation of the pore radii CV and decreasing pore coordination number Z. The third moment was negative and its magnitude grew linearly with time, meaning that the simulated dispersion was intrinsically non-Fickian. The statistics of the Eulerian mean fluid velocities $\hat{u}_i$, the Taylor dispersion coefficients $\hat{D}_i$ and the transit times $\hat{t}_i$ were very complex and strongly affected by CV and Z. In particular, the probability of occurrence of negative velocities grew with increasing CV and decreasing Z. Hence, backward and forward transit times had to be distinguished. The high-τ branch of the transit-times probability curves had a power law form associated to non-Fickian behavior. However, the exponent was insensitive to pore connectivity, although variations of Z affected the third moment growth. Thus, we conclude that both the low- and high-τ branches played a role in generating the observed non-Fickian behavior.

Li, Min↗

A Paired, Double-Blind, Randomized Comparison of a Moisturizing Durable Barrier Cream to 10% Glycerine Cream in the Prophylactic Management of Postmastectomy Irradiation Skin Care: Trans Tasman Radiation Oncology Group (TROG) 04.01

Purpose: A previous, unblinded study demonstrated that an alcohol-free barrier film containing an acrylate terpolymer (ATP) was effective in reducing skin reactions compared with a 10% glycerine cream (sorbolene). The different appearances of these products precluded a blinded comparison. To test the acrylate terpolymer principle in a double-blinded manner required the use of an alternative cream formulation, a moisturizing durable barrier cream (MDBC); the study was conducted by the Trans Tasman Radiation Oncology Group (TROG) as protocol 04.01. Methods and Materials: A total of 333 patients were randomized; 1 patient was ineligible and 14 patients withdrew or had less than 7 weeks' observations, leaving 318 for analysis. The chest wall was divided into medial and lateral compartments, and patients were randomized to have MDBC applied daily to the medial or lateral compartment and sorbolene to the other compartment. Weekly observations, photographs, and symptom scores (pain and pruritus) were collected to week 12 or resolution of skin reactions if earlier. Skin dose was confirmed by centrally calibrated thermoluminescent dosimeters. Results: Rates of medial and lateral compartment Common Toxicity Criteria (CTC), version 3, greater than or equal to grade 3 skin reactions were 23% and 41%, but rates by skin care product were identical at 32%. There was no significant difference between MDBC and sorbolene in the primary endpoint of peak skin reactions or secondary endpoints of area-under-the-curve skin reaction scores. Conclusions: The MDBC did not reduce the peak skin reaction compared to sorbolene. It is possible that this is related to the difference in the formulation of the cream compared with the film formulation. Skin dosimetry verification and double blinding are essential for radiation skin care comparative studies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Template-based automatic breast segmentation on MRI by excluding the chest region

Purpose: Methods for quantification of breast density on MRI using semiautomatic approaches are commonly used. In this study, the authors report on a fully automatic chest template-based method. Methods: Nonfat-suppressed breast MR images from 31 healthy women were analyzed. Among them, one case was randomly selected and used as the template, and the remaining 30 cases were used for testing. Unlike most model-based breast segmentation methods that use the breast region as the template, the chest body region on a middle slice was used as the template. Within the chest template, three body landmarks (thoracic spine and bilateral boundary of the pectoral muscle) were identified for performing the initial V-shape cut to determine the posterior lateral boundary of the breast. The chest template was mapped to each subject's image space to obtain a subject-specific chest model for exclusion. On the remaining image, the chest wall muscle was identified and excluded to obtain clean breast segmentation. The chest and muscle boundaries determined on the middle slice were used as the reference for the segmentation of adjacent slices, and the process continued superiorly and inferiorly until all 3D slices were segmented. The segmentation results were evaluated by an experienced radiologist to mark voxels that were wrongly included or excluded for error analysis. Results: The breast volumes measured by the proposed algorithm were very close to the radiologist's corrected volumes, showing a % difference ranging from 0.01% to 3.04% in 30 tested subjects with a mean of 0.86% ± 0.72%. The total error was calculated by adding the inclusion and the exclusion errors (so they did not cancel each other out), which ranged from 0.05% to 6.75% with a mean of 3.05% ± 1.93%. The fibroglandular tissue segmented within the breast region determined by the algorithm and the radiologist were also very close, showing a % difference ranging from 0.02% to 2.52% with a mean of 1.03% ± 1.03%. The total error by adding the inclusion and exclusion errors ranged from 0.16% to 11.8%, with a mean of 2.89% ± 2.55%. Conclusions: The automatic chest template-based breast MRI segmentation method worked well for cases with different body and breast shapes and different density patterns. Compared to the radiologist-established truth, the mean difference in segmented breast volume was approximately 1%, and the total error by considering the additive inclusion and exclusion errors was approximately 3%. This method may provide a reliable tool for MRI-based segmentation of breast density.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study

This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

17 WIND ENERGY↗

Late Patient-Reported Toxicity After Preoperative Radiotherapy or Chemoradiotherapy in Nonresectable Rectal Cancer: Results From a Randomized Phase III Study

Purpose: Preoperative chemoradiotherapy (CRT) is superior to radiotherapy (RT) in locally advanced rectal cancer, but the survival gain is limited. Late toxicity is, therefore, important. The aim was to compare late bowel, urinary, and sexual functions after CRT or RT. Methods and Materials: Patients (N = 207) with nonresectable rectal cancer were randomized to preoperative CRT or RT (2 Gy Multiplication-Sign 25 {+-} 5-fluorouracil/leucovorin). Extended surgery was often required. Self-reported late toxicity was scored according to the LENT SOMA criteria in a structured telephone interview and with questionnaires European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ-C30), International Index of Erectile Function (IIEF), and sexual function -vaginal changes questionnaire (SVQ). Results: Of the 105 patients alive in Norway and Sweden after 4 to 12 years of follow-up, 78 (74%) responded. More patients in the CRT group had received a stoma (73% vs. 52%, p = 0.09). Most patients without a stoma (7 of 12 in CRT group and 9 of 16 in RT group) had incontinence for liquid stools or gas. No stoma and good anal function were seen in 5 patients (11%) in the CRT group and in 11 (30%) in the RT group (p = 0.046). Of 44 patients in the CRT group, 12 (28%) had had bowel obstruction compared with 5 of 33 (15%) in the RT group (p = 0.27). One-quarter of the patients reported urinary incontinence. The majority of men had severe erectile dysfunction. Few women reported sexual activity during the previous month. However, the majority did not have concerns about their sex life. Conclusions: Fecal incontinence and erectile dysfunction are frequent after combined treatment for locally advanced rectal cancer. There was a clear tendency for the problems to be more common after CRT than after RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Polynomial chaos expansions for dependent random variables

Polynomial chaos expansions (PCE) are well-suited to quantifying uncertainty in models parameterized by independent random variables. The assumption of independence leads to simple strategies for building multivariate orthonormal bases and for sampling strategies to evaluate PCE coefficients. In contrast, the application of PCE to models of dependent variables is much more challenging. Three approaches can be used to construct PCE of models of dependent variables. The first approach uses mapping methods where measure transformations, such as the Nataf and Rosenblatt transformation, can be used to map dependent random variables to independent ones; however we show that this can significantly degrade performance since the Jacobian of the map must be approximated. A second strategy is the class of dominating support methods. In these approaches a PCE is built using independent random variables whose distributional support dominates the support of the true dependent joint density; we provide evidence that this approach appears to produce approximations with suboptimal accuracy. A third approach, the novel method proposed here, uses Gram-Schmidt orthogonalization (GSO) to numerically compute orthonormal polynomials for the dependent random variables. This approach has been used successfully when solving differential equations using the intrusive stochastic Galerkin method, and in this paper we use GSO to build PCE using a non-intrusive stochastic collocation method. The stochastic collocation method treats the model as a black box and builds approximations of the input-output map from a set of samples. Building PCE from samples can introduce ill-conditioning which does not plague stochastic Galerkin methods. To mitigate this ill-conditioning we generate weighted Leja sequences, which are nested sample sets, to build accurate polynomial interpolants. We show that our proposed approach, GSO with weighted Leja sequences, produces PCE which are orders of magnitude more accurate than PCE constructed using mapping or dominating support methods.

97 MATHEMATICS AND COMPUTING↗

Resistance Exercise and Inflammation in Breast Cancer Patients Undergoing Adjuvant Radiation Therapy: Mediation Analysis From a Randomized, Controlled Intervention Trial

Purpose: To explore the mediating role of inflammatory parameters in the development of fatigue, pain, and potentially related depressive symptoms during radiation therapy for breast cancer and its mitigation by resistance exercise. Methods and Materials: Breast cancer patients scheduled for adjuvant radiation therapy were randomized to 12-week progressive resistance exercise training (EX) or a relaxation control group. Interleukin-6 (IL-6) and interleukin-1 receptor antagonist (IL-1ra) were measured in serum samples collected before, at the end, and 6 weeks after radiation therapy from 103 chemotherapy-naïve participants. Fatigue was assessed with the multidimensional Fatigue Assessment Questionnaire, pain with the European Organization for Research and Treatment of Cancer QLQ-C30, and depressive symptoms with the Center for Epidemiologic Studies Depression Scale. Analysis of covariance models, partial correlations, Freedman-Schatzkin tests, and R{sup 2} effect-size measures for mediation were calculated. Results: The analysis of covariance models revealed a significant intervention effect on IL-6 (P=.010) and the IL-6/IL-1ra ratio (P=.018), characterized by a marked increase during radiation therapy among controls, but no significant change in EX. Interleukin-1 receptor antagonist did not change significantly in either group (P=.88). Increased IL-6 and IL-6/IL-1ra levels at the end of radiation therapy were significantly associated with increased physical fatigue and pain 6 weeks after radiation. We observed significant partial mediation by IL-6 and IL-6/IL-1ra of the effect of resistance exercise on physical fatigue (Freedman-Schatzkin P=.023 and P<.001) and pain (both P<.001). Hereby IL-6 and IL-6/IL-1ra mediated between 15% and 24% of the variance of physical fatigue and pain explained by the intervention. Conclusions: This randomized, controlled trial showed a significantly increased proinflammatory cytokine level after adjuvant radiation therapy in breast cancer patients. This effect was counteracted by progressive resistance exercise training. Interleukin-6 and the IL-6/IL-1ra ratio seemed to mediate the beneficial effect of exercise on physical fatigue and pain but only to a small extent.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

RGM: Random Geological Model Generation Package

This Fortran code is to accompany a manuscript to be submitted to Computers & Geosciences, a high-impact, peer-reviewed journal in computer methods for geosciences research. This Fortran code focuses on generation of synthetic geological models using a multi-randomization strategy. Generating high-fidelity synthetic geological models, including realistic seismic reflector migration images, faults, salt bodies, and relative geological time images, is the key for many supervised machine learning methods that aim to delineate faults and other geological properties of interest from seismic migration images. Our package contains two major functionalities: generating 2D synthetic random geological models and generating 3D synthetic random geological models. In each step of the generation process, we set random values for key properties of a geological model to improve the fidelity of the resulting geological model. The package also includes example codes on how to use the random geological model generation subroutines. We name this package RGM – Random Geological Model generation package.

Gao, Kai↗

Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization

Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h and n cancer radiotherapy were less than 2 and 1 mm, respectively, for most organs after the second week of treatment. After the first three weeks of treatment, the mean discrepancy of the dose estimation accuracy was within 1% for most of organs, the corresponding standard deviation was within 2.5% for parotids, the brain stem and the cochleae, and within 1% for other organs. Conclusions: A patient specific OSG is feasible and can be used to generate random samples of organs of interest for the expected treatment dose construction and adaptive inverse planning. The accuracy of the OSG can be improved continuously and recursively during the adaptive treatment course using daily volumetric image feedback.

60 APPLIED LIFE SCIENCES↗

A Frequency Domain Methodology for Quantitative Evaluation of Diffuse Wavefield With Applications to Seismic Imaging

Abstract Ambient Noise Imaging (ANI) of subsurface structures relies on seismic interferometry of diffuse seismic wavefields. However, the lack of effective methods to quantify and identify highly diffuse waves hampers applications of ANI, particularly in evaluating seismic attenuation and monitoring structural changes with high temporal resolution. Conventional ANI approaches require data normalization, which effectively suppresses the non‐diffuse component with large amplitude but also results in significant loss of amplitude and phase information in the continuous seismic records. In this study, we propose a frequency domain method to quantitatively evaluate the degree of diffuseness of seismic wavefields by analyzing their statistical characteristics of modal amplitudes for stationarity and randomness. Tests on synthetic waveform and field nodal records show that the proposed method can effectively distinguish between diffuse and non‐diffuse waveforms for either single‐ or three‐component data. As an application, we identify a 60‐s‐long diffuse coda of a local M 2.2 earthquake recorded by a dense nodal array on the San Jacinto Fault Zone, and successfully extract high‐quality dispersion curve andQ‐value without performing data normalization. These results are consistent with those obtained by conventional methods that assess the correlation between coherency and the Green's function, and by modeling ballistic waves generated by road traffic. Our proposed method can advance the imaging of subsurface velocity and attenuation structures as well as monitoring temporal changes for scientific studies and engineering applications.

Geochemistry & Geophysics↗