Search NASA⌕ Search

SEARCH · Search NASA

Results for “Probability Distribution Function”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A method to fuse multiphysics waveforms and improve predictive explosion detection: theory, experiment and performance

Natural and human-made sources of transient energy often emit multiple geophysical signatures that include mechanical and electromagnetic waveforms. We present a constructive method to fuse and evaluate statistics that we derive from such multiphysics waveforms that improves our capability to detect small, near-ground explosions over similar methods that consume single signature waveforms. Our method advances Fisher's Combined Probability Test (Fisher's Method) to operate under both hypotheses of a binary test on noisy data and provide researchers with the density functions required to forecast the ability of Fisher's Method to screen fused explosion signatures from noise. We apply this method against 12 d, multisignature explosion and noise records to show (1) that a fused multiphysics waveform statistic that combines radio, acoustic and seismic waveform data can identify explosions roughly 0.8 magnitude units lower than an acoustic emission, STA/LTA detector for the same detection probability and (2) that we can quantitatively predict how this fused, multiphysics statistic performs with Fisher's Method. Our work thereby offers a baseline method for predictive waveform fusion that supports multiphenomenological explosion monitoring (multiPEM) and is applicable to any binary testing problem in observational geophysics.

58 GEOSCIENCES↗
DOE OSTI2026

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗
DOE OSTI2022

Collective effect of thermal plumes on temperature fluctuations in a closed Rayleigh–Benard convection cell

Here, we report a systematic study of the collective effect of thermal plumes on the probability density function (PDF) P(δT) of temperature fluctuations δT(t) in turbulent Rayleigh-Benard convection. By decomposing δT(t) into four basic fluctuation modes associated with single and multiple warm and cold plumes and a turbulent background, we derive an analytic form of P(δT) based on the convolutions of the five independent modes. To test the derived form of P(δT) in the multiple-plume regions, where the thermal plumes are heavily populated, we conduct time series measurements of temperature fluctuations in two convection cells; one is a vertical thin disk and the other is an upright cylinder of aspect ratio unity. For a given normalized position in most regions of the convection cell, all of the measured PDFs P(δT) for different Rayleigh numbers fall onto a single master curve, once δT is normalized by its rms value σ T . It is found that the measured P(δT / σT ) at different locations along the symmetric horizontal and vertical axes of the convection cells can all be well described by the derived form of P(δT / σT ). The fitted values of the parameters associated with the number of plumes in multiple plume clusters and their relative strengths and degrees of intermittency are closely linked to the spatial distribution of thermal plumes and local dynamics of the large-scale circulation in a closed convection cell. Our work thus provides a unified theoretical approach for understanding scalar PDFs in a turbulent field, which is very useful not only for the present study but also for the study of many turbulent mixing problems of practical interest.

42 ENGINEERING↗
DOE OSTI2012

ANALYZING STAR CLUSTER POPULATIONS WITH STOCHASTIC MODELS: THE HUBBLE SPACE TELESCOPE/WIDE FIELD CAMERA 3 SAMPLE OF CLUSTERS IN M83

The majority of clusters in the universe have masses well below 10{sup 5} M{sub Sun }. Hence, their integrated fluxes and colors can be affected by the presence or absence of a few bright stars introduced by stochastic sampling of the stellar mass function. Specific methods are being developed to extend the analysis of cluster energy distributions into the low-mass regime. In this paper, we apply such a method to real observations of star clusters, in the nearby spiral galaxy M83. We reassess the ages and masses of a sample of 1242 clusters for which UBVIH{alpha} fluxes were obtained from observations with the Wide Field Camera 3 instrument on board the Hubble Space Telescope. Synthetic clusters with known properties are used to characterize the limitations of the method (valid range and resolution in age and mass, method artifacts). The ensemble of color predictions of the discrete cluster models are in good agreement with the distribution of observed colors. We emphasize the important role of the H{alpha} data in the assessment of the fraction of young objects, particularly in breaking the age-extinction degeneracy that hampers an analysis based on UBVI data only. We find the mass distribution of the cluster sample to follow a power law of index -2.1 {+-} 0.2, and the distribution of ages a power law of index -1.0 {+-} 0.2 for log (M/ M{sub Sun }) > 3.5, and ages between 10{sup 7} and 10{sup 9} yr. An extension of our main method, which makes full use of the probability distributions of age and mass obtained for the individual clusters of the sample, is explored. It produces similar power-law slopes and will deserve further investigation. Although the properties derived for individual clusters significantly differ from those obtained with traditional, non-stochastic models in about 30% of the objects, the first-order aspect of the age and mass distributions is similar to those obtained previously for this M83 sample in the range of overlap of the studies. We extend the power-law description to lower masses with better mass and age resolution and without most of the artifacts produced by the classical method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Identifying Single Copy Orthologs in Metazoa

The identification of single copy (1-to-1) orthologs in any group of organisms is important for functional classification and phylogenetic studies. The Metazoa are no exception, but only recently has there been a wide-enough distribution of taxa with sufficiently high quality sequenced genomes to gain confidence in the wide-spread single copy status of a gene. Here, we present a phylogenetic approach for identifying overlooked single copy orthologs from multigene families and apply it to the Metazoa. Using 18 sequenced metazoan genomes of high quality we identified a robust set of 1,126 orthologous groups that have been retained in single copy since the last common ancestor of Metazoa. We found that the use of the phylogenetic procedure increased the number of single copy orthologs found by over a third more than standard taxoncount approaches. The orthologs represented a wide range of functional categories, expression profiles and levels of divergence. To demonstrate the value of our set of single copy orthologs, we used them to assess the completeness of 24 currently published metazoan genomes and 62 EST datasets. We found that the annotated genes in published genomes vary in coverage from 79% (Ciona intestinalis) to 99.8% (human) with an average of 92%, suggesting a value for the underlying error rate in genome annotation, and a strategy for identifying single copy orthologs in larger datasets. In contrast, the vast majority of EST datasets with no corresponding genome sequence available are largely under-sampled and probably do not accurately represent the actual genomic complement of the organisms from which they are derive

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Investigations of the Fundamental Surface Reactions Involved in the Sorption and Desorption of Radionuclides

Models for describing solution- and surface-phase reactions have been used for 30 years, but only recently applicable to complex surfaces. Duff et al., using micro-XANES, found that Pu was concentrated on Mn-oxide and smectite phases of zeolitic tuff, providing an evaluation of contaminant speciation on surfaces for modeling. Experiments at Los Alamos demonstrated that actinides display varying surface residence time distributions, probably reflective of mineral surface heterogeneity. We propose to investigate the sorption/desorption behavior of radionuclides from mineral surfaces, as effected by microorganisms, employing isolates from Nevada Test Site deep alluvium as a model system. Characterizations will include surface area, particle size distribution, x-ray diffraction (XRD), microprobe analysis, extractions, and microbiology. Surface interactions will be assessed by electron spectroscopy (XPS), x-ray absorption fine structure spectroscopy (XAFS), X-ray emission spectroscopy, transmission electron microscopy (TEM) and Scanning electron microscopy (SEM). Desert Research Institute (DRI), University of Nevada, Reno (UNR), and University of Nevada, Las Vegas (UNLV) researchers will collaborate to enhance scientific infrastructure and the understanding of contaminant behavior on surfaces, with broader implications for the management of DOE sites.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

Structural Interpretation of the Large Slowdown of Water Dynamics at Stacked Phospholipid Membranes for Decreasing Hydration Level: All-Atom Molecular Dynamics

Hydration water determines the stability and function of phospholipid membranes as well as the interaction of membranes with other molecules. Experiments and simulations have shown that water dynamics slows down dramatically as the hydration decreases, suggesting that the interfacial water that dominates the average dynamics at low hydration is slower than water away from the membrane. Here, based on all-atom molecular dynamics simulations, we provide an interpretation of the slowdown of interfacial water in terms of the structure and dynamics of water–water and water–lipid hydrogen bonds (HBs). We calculate the rotational and translational slowdown of the dynamics of water confined in stacked phospholipid membranes at different levels of hydration, from completely hydrated to poorly hydrated membranes. For all hydrations, we analyze the distribution of HBs and find that water–lipids HBs last longer than water–water HBs and that at low hydration most of the water is in the interior of the membrane. We also show that water–water HBs become more persistent as the hydration is lowered. We attribute this effect (i) to HBs between water molecules that form, in turn, persistent HBs with lipids; (ii) to the hindering of the H-bonding switching between water molecules due to the lower water density at the interface; and (iii) to the higher probability of water–lipid HBs as the hydration decreases. Lastly, our interpretation of the large dynamic slowdown in water under dehydration is potentially relevant in understanding membrane biophysics at different hydration levels.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Statistical behaviour of adaptive multilevel splitting algorithms in simple models

Adaptive multilevel splitting algorithms have been introduced rather recently for estimating tail distributions in a fast and efficient way. In particular, they can be used for computing the so-called reactive trajectories corresponding to direct transitions from one metastable state to another. The algorithm is based on successive selection–mutation steps performed on the system in a controlled way. It has two intrinsic parameters, the number of particles/trajectories and the reaction coordinate used for discriminating good or bad trajectories. We investigate first the convergence in law of the algorithm as a function of the timestep for several simple stochastic models. Second, we consider the average duration of reactive trajectories for which no theoretical predictions exist. The most important aspect of this work concerns some systems with two degrees of freedom. They are studied in detail as a function of the reaction coordinate in the asymptotic regime where the number of trajectories goes to infinity. We show that during phase transitions, the statistics of the algorithm deviate significatively from known theoretical results when using non-optimal reaction coordinates. In this case, the variance of the algorithm is peaking at the transition and the convergence of the algorithm can be much slower than the usual expected central limit behaviour. The duration of trajectories is affected as well. Moreover, reactive trajectories do not correspond to the most probable ones. Such behaviour disappears when using the optimal reaction coordinate called committor as predicted by the theory. We finally investigate a three-state Markov chain which reproduces this phenomenon and show logarithmic convergence of the trajectory durations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Simulation-based inference for parameter estimation of complex watershed simulators

High-resolution, spatially distributed process-based (PB) simulators are widely employed in the study of complex catchment processes and their responses to a changing climate. However, calibrating these PB simulators using observed data remains a significant challenge due to several persistent issues, including the following: (1) intractability stemming from the computational demands and complex responses of simulators, which renders infeasible calculation of the conditional probability of parameters and data, and (2) uncertainty stemming from the choice of simplified representations of complex natural hydrologic processes. Here, we demonstrate how simulation-based inference (SBI) can help address both of these challenges with respect to parameter estimation. SBI uses a learned mapping between the parameter space and observed data to estimate parameters for the generation of calibrated simulations. To demonstrate the potential of SBI in hydrologic modeling, we conduct a set of synthetic experiments to infer two common physical parameters – Manning's coefficient and hydraulic conductivity – using a representation of a snowmelt-dominated catchment in Colorado, USA. We introduce novel deep-learning (DL) components to the SBI approach, including an “emulator” as a surrogate for the PB simulator to rapidly explore parameter responses. We also employ a density-based neural network to represent the joint probability of parameters and data without strong assumptions about its functional form. While addressing intractability, we also show that, if the simulator does not represent the system under study well enough, SBI can yield unreliable parameter estimates. Approaches to adopting the SBI framework for cases in which multiple simulator(s) may be adequate are introduced using a performance-weighting approach. The synthetic experiments presented here test the performance of SBI, using the relationship between the surrogate and PB simulators as a proxy for the real case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Hazard function theory for nonstationary natural hazards

Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e., that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series ( X ) with its failure time series ( T ), enabling computation of corresponding average return periods, risk, and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied generalized Pareto model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. As a result, our theoretical analysis linking hazard random variable X with corresponding failure time series T should have application to a wide class of natural hazards with opportunities for future extensions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2010

THE INITIAL MASS FUNCTION AND YOUNG BROWN DWARF CANDIDATES IN NGC 2264. IV. THE INITIAL MASS FUNCTION AND STAR FORMATION HISTORY

We have studied the star formation history and the initial mass function (IMF) using the age and mass derived from spectral energy distribution (SED) fitting and from color-magnitude diagrams (CMDs). We also examined the physical and structural parameters of more than 1000 pre-main-sequence stars in NGC 2264 using the online SED fitting tool (SED fitter) of Robitaille et al. We have compared the physical parameters of central stars from SED fitter and other methods. The temperature of the central star is, in many cases, much higher than that expected from its spectral type. The mass and age from SED fitter are not well matched with those from CMDs. We have made some suggestions to improve the accuracy of temperature estimates in the SED fitter. In most cases, these parameters of individual stars from the SED fitter in a star-forming region (SFR) or in the whole cluster showed nearly no systematic variation with age or with any other relevant parameter. On the other hand, the median properties of stars in NGC 2264 SFRs showed an evident evolutionary effect and were interrelated to each other. Such differences are caused by a larger age spread within an SFR than between them. The cumulative distribution of stellar ages showed a distinct difference among SFRs. A Kolmogorov-Smirnov test gave a very low probability of them being from the same population. The results indicate that star formation in NGC 2264 started at the surface region (Halo and Field regions) about 6-7 Myr ago, propagated into the molecular cloud and finally triggered the recent star formation in the Spokes cluster. The kind of sequential star formation that started in the low-density surface region (Halo and Field regions) implies that star formation in NGC 2264 was triggered by an external source. The IMF of NGC 2264 was determined in two different ways. One method used the stellar mass from the SED fitting tool, the other used the stellar mass from CMDs. The first IMF showed a distinct peak at m {approx} 2 M{sub sun}, but the second did not. We attribute the peak as an artifact of the SED fitting tool because there is no such IMF with a peak at m {approx} 2 M{sub sun}. The slope of the IMF of NGC 2264 for massive stars (log m {>=} 0.5) is -1.7 {+-} 0.1, which is somewhat steeper than the so-called standard Salpeter-Kroupa IMF. We also present data for 79 young brown dwarf candidates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

A framework to analyze the stochastic harmonics and resonance of wind energy grid interconnection

This study addresses a modeling and analysis methodology for investigating the stochastic harmonics and resonance concerns of wind power plants (WPPs). Wideband harmonics from modern wind turbines are observed to be stochastic, associated with real power production, and they may adversely interact with the grid impedance and cause unexpected harmonic resonance if not comprehensively addressed in the planning and commissioning of the WPPs. These issues should become more critical as wind penetration levels increase. We thus propose a planning study framework comprising the following functional steps: First, the best-fitted probability density functions (PDFs) of the harmonic components of interest in the frequency domain are determined. In operations planning, maximum likelihood estimations followed by a chi-square test are used once field measurements or manufacturers' data are available. Second, harmonic currents from the WPP are represented by randomly-generating harmonic components based on their PDFs (frequency spectrum) and then synthesized for time-domain simulations via inverse Fourier transform. Finally, we conduct a comprehensive assessment by including the impacts of feeder configurations, harmonic filters, and the variability of parameters. We demonstrate the efficacy of the proposed study approach for a 100-MW offshore WPP consisting of 20 units of 5-MW full-converter turbines, a realistic benchmark system adapted from a WPP under development in Korea, and discuss lessons learned through this research.

17 WIND ENERGY↗
DOE OSTI2014

The impact of including spatially longitudinal heterogeneities of vessel oxygen content and vascular fraction in 3D tumor oxygenation models on predicted radiation sensitivity

Purpose: Oxygen distribution models have been used to analyze the influences of oxygen tensions on tissue response after radiotherapy. These distributions are often generated assuming constant oxygen tension in the blood vessels. However, as red blood cells progress through the vessels, oxygen is continuously released into the plasma and the surrounding tissue, resulting in longitudinally varying oxygen levels in the blood vessels. In the present study, the authors investigated whether a tumor oxygenation model that incorporated longitudinally varying oxygen levels would provide different predictions of necrotic fractions and radiosensitivity compared to commonly used models with a constant oxygen pressure. Methods: Our models simulated oxygen diffusion based on a Green's function approach and oxygen consumption according to the Michaelis-Menten equation. The authors constructed tumor models with different vascular fractions (VFs), from which they generated depth oxygenation curves and a look-up table of oxygen pressure gradients. The authors evaluated models of spherical tumors of various sizes, from 1 to 10{sup 4} mg. The authors compared the results from a model with constant vessel oxygen (CVO) pressure to those from models with longitudinal variations in oxygen saturation and either a constant VF (CVF) or variable VF (VVF) within the tumor tissue. The authors monitored the necrotic fractions, defined as tumor regions with an oxygen pressure below 1 mmHg. Tumor radiation sensitivity was expressed as D{sub 99,} the homogeneous radiation dose required for a tumor control probability of 0.99. Results: In the CVO saturation model, no necrosis was observed, and decreasing the VF could only decrease the D{sub 99} by up to 10%. Furthermore, the D{sub 99} vs VF dependence was similar for different tumor masses. Compared to the CVO model, the extended CVF and VVF models provided clearly different results, including pronounced effects of VF and tumor size on the necrotic fraction and D{sub 99}, necrotic fractions ranging from 0% to 97%, and a maximal D{sub 99} increment of 57%. Only minor differences were observed between different vessel architectures, i.e., CVF vs VVF. In the smallest tumor with a low necrotic fraction, the D{sub 99} strictly decreased with increasing blood velocity. Increasing blood velocity also decreased the necrotic fraction in all tumor sizes. VF had the most profound influence on both the necrotic fraction and on D{sub 99}. Conclusions: Our present analysis of necrotic formation and the impact of tumor oxygenation on D{sub 99} demonstrated the importance of including longitudinal variations in vessel oxygen content in tumor models. For small tumors, radiosensitivity was particularly dependent on VF and slightly dependent on the blood velocity and vessel arrangement. These dependences decreased with increasing tumor size, because the necrotic fraction also increased, thereby decreasing the number of viable tumor cells that required sterilization. The authors anticipate that the present model will be useful for estimating tumor oxygenation and radiation response in future detailed studies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Quantified uncertainty in thermodynamic modeling for materials design

Phase fractions, compositions and energies of the stable phases as a function of macroscopic composition, temperature, and pressure (X-T-P) are the principle correlations needed for the design of new materials and improvement of existing materials. They are the outcomes of thermodynamic modeling based on the CALculation of PHAse Diagrams (CALPHAD) approach. Here, the accuracy of CALPHAD predictions vary widely in X-T-P space due to experimental error, model inadequacy and unequal data coverage. In response, researchers have developed frameworks to quantify the uncertainty of thermodynamic property model parameters and propagate it to phase diagram predictions. In most previous studies, uncertainty was represented as intervals on phase boundaries (with respect to composition or temperature) and was unable to represent the uncertainty in invariant reactions or in the stability of phase regions. In this work, we propose a suite of tools that leverages samples from the multivariate model parameter distribution to represent uncertainty in forms that surpass previous limitations and are well suited to materials design. These representations include the distribution of phase diagrams and their features, as well as the dependence of phase stability and the distributions of phase fraction, composition, activity and Gibbs energy on X-T-P location - irrespective of the total number of components. Most critically, the new methodology allows the material designer to interrogate a certain composition and temperature domain and get in return the probability of different phases to be stable, which can positively impact materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electron beam injection from a hollow cathode plasma into a downstream reactive environment: Characterization of secondary plasma production and Si 3 N 4 and Si etching

A material etching system was developed by combining beam electron injection from a direct current (DC) hollow-cathode (HC) electron source with the downstream reactive environment of a remote CF 4 /O 2 low temperature plasma. The energy of the injected beam electrons is controlled using an acceleration electrode biased positively relative to the HC Argon discharge. For an acceleration voltage greater than the ionization potential of Ar, the extracted primary electrons can produce a secondary plasma in the process chamber. We characterized the properties of the secondary plasma by performing Langmuir probe measurements of the electron energy probability function (EEPF) 2.5 cm below the extraction ring. The data indicate the existence of two major groups of electrons, including electrons with a primary beam electron energy which varies as the acceleration voltage is varied, along with low energy electrons produced by ionization of the Ar gas atoms in the process chamber by the injected beam electrons. When combining the HC Ar beam electron with a remote CF 4 /O 2 electron cyclotron wave resonance (ECWR) plasma, the EEPF of both the low energy plasma electron and beam electron components decreases. Additionally, we studied surface etching of Si3N4 and poly-crystalline Si (poly-Si) thin films as a function of process parameters, including the acceleration voltage (0-70 V), discharge current of the HC discharge (1-2 A), pressure (2- 100 mTorr), source to substrate distance (2.5 to 5 cm), and feed gas composition (with or without CF 4 /O 2 ). The direction of the incident beam electrons was perpendicular to the surface. Si 3 N 4 and poly-crystalline silicon etching are seen and indicate an electronneutral synergy effect. No/little remote plasma spontaneous etching was observed for the conditions used in this study, and the etching is confined to the substrate area irradiated by the injected beam electrons. The electron etched Si 3 N 4 surface etching rate profile distribution is confined within a ~30 mm diameter circle, which is slightly broader than the area for which poly-Si etching is seen, and coincides closely with the spatial profile of beam electrons as determined by the Langmuir probe measurements. The magnitude of poly-Si etching rate is by a factor of two times smaller than the Si 3 N 4 etching rate. In this paper, we discuss possible explanations of the data and the role of surface charging.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer's pathology

The relationships between clinical phenotype, β-amyloid (Aβ) deposition and neurodegeneration in Alzheimer's disease (AD) are incompletely understood yet have important ramifications for future therapy. The goal of this study was to utilize multimodality positron emission tomography (PET) data from a clinically heterogeneous population of patients with probable AD in order to: (1) identify spatial patterns of Aβ deposition measured by ( 11 C)-labeled Pittsburgh Compound B (PiB-PET) and glucose metabolism measured by FDG-PET that correlate with specific clinical presentation and (2) explore associations between spatial patterns of Aβ deposition and glucose metabolism across the AD population. We included all patients meeting the criteria for probable AD (NIA–AA) who had undergone MRI, PiB and FDG-PET at our center (N = 46, mean age 63.0 ± 7.7, Mini-Mental State Examination 22.0 ± 4.8). Patients were subclassified based on their cognitive profiles into an amnestic/dysexecutive group (AD-memory; n = 27), a language-predominant group (AD-language; n = 10) and a visuospatial-predominant group (AD-visuospatial; n = 9). All patients were required to have evidence of amyloid deposition on PiB-PET. To capture the spatial distribution of Aβ deposition and glucose metabolism, we employed parallel independent component analysis (pICA), a method that enables joint analyses of multimodal imaging data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Enhancing pairwise state-transition weights: A new weighting scheme in simulated tempering that can minimize transition time between a pair of conformational states

Simulated tempering (ST) is a widely used enhancing sampling method for Molecular Dynamics simulations. As one expanded ensemble method, ST is a combination of canonical ensembles at different temperatures and the acceptance probability of cross-temperature transitions is determined by both the temperature difference and the weights of each temperature. One popular way to obtain the weights is to adopt the free energy of each canonical ensemble, which achieves uniform sampling among temperature space. However, this uniform distribution in temperature space may not be optimal since high temperatures do not always speed up the conformational transitions of interest, as anti-Arrhenius kinetics are prevalent in protein and RNA folding. Here, we propose a new method: Enhancing Pairwise State-transition Weights (EPSW), to obtain the optimal weights by minimizing the round-trip time for transitions among different metastable states at the temperature of interest in ST. The novelty of the EPSW algorithm lies in explicitly considering the kinetics of conformation transitions when optimizing the weights of different temperatures. We further demonstrate the power of EPSW in three different systems: a simple two-temperature model, a two-dimensional model for protein folding with anti-Arrhenius kinetics, and the alanine dipeptide. The results from these three systems showed that the new algorithm can substantially accelerate the transitions between conformational states of interest in the ST expanded ensemble and further facilitate the convergence of thermodynamics compared to the widely used free energy weights. We anticipate that this algorithm is particularly useful for studying functional conformational changes of biological systems where the initial and final states are often known from structural biology experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Medium-range order and compositional correlation in metallic glasses

The compositional atomic ordering in metallic glasses was studied by simulation focusing on the medium-range order (MRO). Many metallic alloy liquids and glasses show MRO characterized by the oscillations in the atomic pair-distribution function (PDF) beyond the first peak, which decay exponentially with distance. To study the effects of the local chemical order on MRO, we examine the compositionally resolved PDF and its MRO for models of various binary metallic alloy glasses. We show that compositional ordering is limited mostly to the nearest-neighbor atoms and the MRO is largely independent of the compositional order. For some elements that strongly repel each other in the alloy, a second MRO periodicity is observed owing to the distinct correlations among them. These results are discussed in light of the idea that the MRO oscillations in the PDF describe the correlations in the atomic density fluctuations, rather than the detailed local atomic structure.

Atomic structure↗