Laminar soot processes

NASA Technical Reports Server (NTRS)

Sunderland, P. B.; Lin, K.-C.; Faeth, G. M.

1995-01-01

Soot processes within hydrocarbon fueled flames are important because they affect the durability and performance of propulsion systems, the hazards of unwanted fires, the pollutant and particulate emissions from combustion processes, and the potential for developing computational combustion. Motivated by these observations, the present investigation is studying soot processes in laminar diffusion and premixed flames in order to better understand the soot and thermal radiation emissions of luminous flames. Laminar flames are being studied due to their experimental and computational tractability, noting the relevance of such results to practical turbulent flames through the laminar flamelet concept. Weakly-buoyant and nonbuoyant laminar diffusion flames are being considered because buoyancy affects soot processes in flames while most practical flames involve negligible effects of buoyancy. Thus, low-pressure weakly-buoyant flames are being observed during ground-based experiments while near atmospheric pressure nonbuoyant flames will be observed during space flight experiments at microgravity. Finally, premixed laminar flames also are being considered in order to observe some aspects of soot formation for simpler flame conditions than diffusion flames. The main emphasis of current work has been on measurements of soot nucleation and growth in laminar diffusion and premixed flames.

Valuing options in shot noise market

NASA Astrophysics Data System (ADS)

Laskin, Nick

2018-07-01

A new exactly solvable option pricing model has been introduced and elaborated. It is assumed that a stock price follows a Geometric shot noise process. An arbitrage-free integro-differential option pricing equation has been obtained and solved. The new Greeks have been analytically calculated. It has been shown that in diffusion approximation the developed option pricing model incorporates the well-known Black-Scholes equation and its solution. The stochastic dynamic origin of the Black-Scholes volatility has been uncovered. To model the observed market stock price patterns consisting of high frequency small magnitude and low frequency large magnitude jumps, the superposition of two Geometric shot noises has been implemented. A new generalized option pricing equation has been obtained and its exact solution was found. Merton's jump-diffusion formula for option price was recovered in diffusion approximation. Despite the non-Gaussian nature of probability distributions involved, the new option pricing model has the same degree of analytical tractability as the Black-Scholes model and the Merton jump-diffusion model. This attractive feature allows one to derive exact formulas to value options and option related instruments in the market with jump-like price patterns.

The tractable cognition thesis.

PubMed

Van Rooij, Iris

2008-09-01

The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the Tractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories of cognition. To utilize this constraint, a precise and workable definition of "computational tractability" is needed. Following computer science tradition, many cognitive scientists and psychologists define computational tractability as polynomial-time computability, leading to the P-Cognition thesis. This article explains how and why the P-Cognition thesis may be overly restrictive, risking the exclusion of veridical computational-level theories from scientific investigation. An argument is made to replace the P-Cognition thesis by the FPT-Cognition thesis as an alternative formalization of the Tractable Cognition thesis (here, FPT stands for fixed-parameter tractable). Possible objections to the Tractable Cognition thesis, and its proposed formalization, are discussed, and existing misconceptions are clarified. 2008 Cognitive Science Society, Inc.

Distributed Decision Making in a Dynamic Network Environment

DTIC Science & Technology

1990-01-01

protocols, particularly when traffic arrival statistics are varying or unknown, and loads are high. Both nonpreemptive and preemptive repeat disciplines are...The simulation model allows general value functions, continuous time operation, and preemptive or nonpreemptive service. For reasons of tractability... nonpreemptive LIFO, (4) nonpreemptive LIFO with discarding, (5) nonpreemptive HOL, (6) nonpreemp- tive HOL with discarding, (7) preemptive repeat HOL, (8

Information Theory - The Bridge Connecting Bounded Rational Game Theory and Statistical Physics

NASA Technical Reports Server (NTRS)

Wolpert, David H.

2005-01-01

A long-running difficulty with conventional game theory has been how to modify it to accommodate the bounded rationality of all red-world players. A recurring issue in statistical physics is how best to approximate joint probability distributions with decoupled (and therefore far more tractable) distributions. This paper shows that the same information theoretic mathematical structure, known as Product Distribution (PD) theory, addresses both issues. In this, PD theory not only provides a principle formulation of bounded rationality and a set of new types of mean field theory in statistical physics; it also shows that those topics are fundamentally one and the same.

Intelligence's likelihood and evolutionary time frame

NASA Astrophysics Data System (ADS)

Bogonovich, Marc

2011-04-01

This paper outlines hypotheses relevant to the evolution of intelligent life and encephalization in the Phanerozoic. If general principles are inferable from patterns of Earth life, implications could be drawn for astrobiology. Many of the outlined hypotheses, relevant data, and associated evolutionary and ecological theory are not frequently cited in astrobiological journals. Thus opportunity exists to evaluate reviewed hypotheses with an astrobiological perspective. A quantitative method is presented for testing one of the reviewed hypotheses (hypothesis i; the diffusion hypothesis). Questions are presented throughout, which illustrate that the question of intelligent life's likelihood can be expressed as multiple, broadly ranging, more tractable questions.

Magnetic pumping of particles in the outer Jovian magnetosphere

NASA Technical Reports Server (NTRS)

Borovsky, J. E.

1980-01-01

The mechanism of magnetic pumping consists of two processes, the adiabatic motion of charged particles in a time varying magnetic field and their pitch-angle diffusion. The result is a systematic increase in the energy of charged particles trapped in mirror (and particularly, magnetospheric) magnetic fields. A numerical model of the mechanism is constructed, compared with analytic theory where possible, and, through elementary exercises, is used to predict the consequences of the process for cases that are not tractable by analytical means. For energy dependent pitch angle diffusion rates, characteristic 'two temperature' distributions are produced. Application of the model to the outer Jovian magnetosphere shows that beyond 20 Jupiter radii in the outer magnetosphere, particles may be magnetically pumped to energies of the order of 1 - 2 MeV. Two temperature distribution functions with "break points" at 1 - 4 KeV for electrons and 8 - 35 KeV for ions are predicted.

Correction to verdonck and tuerlinckx (2014).

PubMed

2015-01-01

Reports an error in "The Ising Decision Maker: A binary stochastic network for choice response time" by Stijn Verdonck and Francis Tuerlinckx (Psychological Review, 2014[Jul], Vol 121[3], 422-462). An inaccurate assumption in Appendix B (provided in the erratum) led to an oversimplified result in Equation 18 (the diffusion equations associated with the microscopically defined dynamics). The authors sincerely thank Rani Moran for making them aware of the problem. Only the expression of the diffusion coefficient D is incorrect, and should be changed, as indicated in the erratum. Both the cause of the problem and the solution are also explained in the erratum. (The following abstract of the original article appeared in record 2014-31650-006.) The Ising Decision Maker (IDM) is a new formal model for speeded two-choice decision making derived from the stochastic Hopfield network or dynamic Ising model. On a microscopic level, it consists of 2 pools of binary stochastic neurons with pairwise interactions. Inside each pool, neurons excite each other, whereas between pools, neurons inhibit each other. The perceptual input is represented by an external excitatory field. Using methods from statistical mechanics, the high-dimensional network of neurons (microscopic level) is reduced to a two-dimensional stochastic process, describing the evolution of the mean neural activity per pool (macroscopic level). The IDM can be seen as an abstract, analytically tractable multiple attractor network model of information accumulation. In this article, the properties of the IDM are studied, the relations to existing models are discussed, and it is shown that the most important basic aspects of two-choice response time data can be reproduced. In addition, the IDM is shown to predict a variety of observed psychophysical relations such as Piéron's law, the van der Molen-Keuss effect, and Weber's law. Using Bayesian methods, the model is fitted to both simulated and real data, and its performance is compared to the Ratcliff diffusion model. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

The Tractable Cognition Thesis

ERIC Educational Resources Information Center

van Rooij, Iris

2008-01-01

The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the "Tractable Cognition thesis": Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories…

Quantifying, Visualizing, and Monitoring Lead Optimization.

PubMed

Maynard, Andrew T; Roberts, Christopher D

2016-05-12

Although lead optimization (LO) is by definition a process, process-centric analysis and visualization of this important phase of pharmaceutical R&D has been lacking. Here we describe a simple statistical framework to quantify and visualize the progression of LO projects so that the vital signs of LO convergence can be monitored. We refer to the resulting visualizations generated by our methodology as the "LO telemetry" of a project. These visualizations can be automated to provide objective, holistic, and instantaneous analysis and communication of LO progression. This enhances the ability of project teams to more effectively drive LO process, while enabling management to better coordinate and prioritize LO projects. We present the telemetry of five LO projects comprising different biological targets and different project outcomes, including clinical compound selection, termination due to preclinical safety/tox, and termination due to lack of tractability. We demonstrate that LO progression is accurately captured by the telemetry. We also present metrics to quantify LO efficiency and tractability.

A High Performance Computing Study of a Scalable FISST-Based Approach to Multi-Target, Multi-Sensor Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; Wilkins, M.; Roscoe, C.; Faber, W.; Chakravorty, S.; Schumacher, P.

2016-09-01

Finite Set Statistics (FISST) is a rigorous Bayesian multi-hypothesis management tool for the joint detection, classification and tracking of multi-sensor, multi-object systems. Implicit within the approach are solutions to the data association and target label-tracking problems. The full FISST filtering equations, however, are intractable. While FISST-based methods such as the PHD and CPHD filters are tractable, they require heavy moment approximations to the full FISST equations that result in a significant loss of information contained in the collected data. In this paper, we review Smart Sampling Markov Chain Monte Carlo (SSMCMC) that enables FISST to be tractable while avoiding moment approximations. We study the effect of tuning key SSMCMC parameters on tracking quality and computation time. The study is performed on a representative space object catalog with varying numbers of RSOs. The solution is implemented in the Scala computing language at the Maui High Performance Computing Center (MHPCC) facility.

The Ising Decision Maker: a binary stochastic network for choice response time.

PubMed

Verdonck, Stijn; Tuerlinckx, Francis

2014-07-01

The Ising Decision Maker (IDM) is a new formal model for speeded two-choice decision making derived from the stochastic Hopfield network or dynamic Ising model. On a microscopic level, it consists of 2 pools of binary stochastic neurons with pairwise interactions. Inside each pool, neurons excite each other, whereas between pools, neurons inhibit each other. The perceptual input is represented by an external excitatory field. Using methods from statistical mechanics, the high-dimensional network of neurons (microscopic level) is reduced to a two-dimensional stochastic process, describing the evolution of the mean neural activity per pool (macroscopic level). The IDM can be seen as an abstract, analytically tractable multiple attractor network model of information accumulation. In this article, the properties of the IDM are studied, the relations to existing models are discussed, and it is shown that the most important basic aspects of two-choice response time data can be reproduced. In addition, the IDM is shown to predict a variety of observed psychophysical relations such as Piéron's law, the van der Molen-Keuss effect, and Weber's law. Using Bayesian methods, the model is fitted to both simulated and real data, and its performance is compared to the Ratcliff diffusion model. (c) 2014 APA, all rights reserved.

Biostatistical analysis of quantitative immunofluorescence microscopy images.

PubMed

Giles, C; Albrecht, M A; Lam, V; Takechi, R; Mamo, J C

2016-12-01

Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Detecting temperature fluctuations at equilibrium.

PubMed

Dixit, Purushottam D

2015-05-21

The Gibbs and the Boltzmann definition of temperature agree only in the macroscopic limit. The ambiguity in identifying the equilibrium temperature of a finite-sized 'small' system exchanging energy with a bath is usually understood as a limitation of conventional statistical mechanics. We interpret this ambiguity as resulting from a stochastically fluctuating temperature coupled with the phase space variables giving rise to a broad temperature distribution. With this ansatz, we develop the equilibrium statistics and dynamics of small systems. Numerical evidence using an analytically tractable model shows that the effects of temperature fluctuations can be detected in the equilibrium and dynamical properties of the phase space of the small system. Our theory generalizes statistical mechanics to small systems relevant in biophysics and nanotechnology.

Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques

DTIC Science & Technology

2007-08-01

In this domain, queries typically show a deeply nested structure, which makes the semantic parsing task rather challenging , e.g.: What states border...only 80% of the GEOQUERY queries are semantically tractable, which shows that GEOQUERY is indeed a more challenging domain than ATIS. Note that none...a particularly challenging task, because of the inherent ambiguity of natural languages on both sides. It has inspired a large body of research. In

A Course of Lectures on Statistical Mechanics

DTIC Science & Technology

2010-06-01

of mathematics goes a long way to making it tractable. In particular for doing problems in thermodynamics , we’ll stress the following point . For any...disentangle temperature from k. This is done by setting T = 273.16 K at the triple point of water (’ 0.01◦C). Note that the SI unit of the Kelvin...energy, 11 of harmonic oscillator, 66 thermal equilibrium, 19 thermal resistance, 27 triple point of water, 19 ultraviolet catastrophe, 71 validity

Anomalous dimensionality dependence of diffusion in a rugged energy landscape: How pathological is one dimension?

NASA Astrophysics Data System (ADS)

Seki, Kazuhiko; Bagchi, Kaushik; Bagchi, Biman

2016-05-01

Diffusion in one dimensional rugged energy landscape (REL) is predicted to be pathologically different (from any higher dimension) with a much larger chance of encountering broken ergodicity [D. L. Stein and C. M. Newman, AIP Conf. Proc. 1479, 620 (2012)]. However, no quantitative study of this difference has been reported, despite the prevalence of multidimensional physical models in the literature (like a high dimensional funnel guiding protein folding/unfolding). Paradoxically, some theoretical studies of these phenomena still employ a one dimensional diffusion description for analytical tractability. We explore the dimensionality dependent diffusion on REL by carrying out an effective medium approximation based analytical calculations and compare them with the available computer simulation results. We find that at an intermediate level of ruggedness (assumed to have a Gaussian distribution), where diffusion is well-defined, the value of the effective diffusion coefficient depends on dimensionality and changes (increases) by several factors (˜5-10) in going from 1d to 2d. In contrast, the changes in subsequent transitions (like 2d to 3d and 3d to 4d and so on) are far more modest, of the order of 10-20% only. When ruggedness is given by random traps with an exponential distribution of barrier heights, the mean square displacement (MSD) is sub-diffusive (a well-known result), but the growth of MSD is described by different exponents in one and higher dimensions. The reason for such strong ruggedness induced retardation in the case of one dimensional REL is discussed. We also discuss the special limiting case of infinite dimension (d = ∞) where the effective medium approximation becomes exact and where theoretical results become simple. We discuss, for the first time, the role of spatial correlation in the landscape on diffusion of a random walker.

Anomalous dimensionality dependence of diffusion in a rugged energy landscape: How pathological is one dimension?

PubMed

Seki, Kazuhiko; Bagchi, Kaushik; Bagchi, Biman

2016-05-21

Diffusion in one dimensional rugged energy landscape (REL) is predicted to be pathologically different (from any higher dimension) with a much larger chance of encountering broken ergodicity [D. L. Stein and C. M. Newman, AIP Conf. Proc. 1479, 620 (2012)]. However, no quantitative study of this difference has been reported, despite the prevalence of multidimensional physical models in the literature (like a high dimensional funnel guiding protein folding/unfolding). Paradoxically, some theoretical studies of these phenomena still employ a one dimensional diffusion description for analytical tractability. We explore the dimensionality dependent diffusion on REL by carrying out an effective medium approximation based analytical calculations and compare them with the available computer simulation results. We find that at an intermediate level of ruggedness (assumed to have a Gaussian distribution), where diffusion is well-defined, the value of the effective diffusion coefficient depends on dimensionality and changes (increases) by several factors (∼5-10) in going from 1d to 2d. In contrast, the changes in subsequent transitions (like 2d to 3d and 3d to 4d and so on) are far more modest, of the order of 10-20% only. When ruggedness is given by random traps with an exponential distribution of barrier heights, the mean square displacement (MSD) is sub-diffusive (a well-known result), but the growth of MSD is described by different exponents in one and higher dimensions. The reason for such strong ruggedness induced retardation in the case of one dimensional REL is discussed. We also discuss the special limiting case of infinite dimension (d = ∞) where the effective medium approximation becomes exact and where theoretical results become simple. We discuss, for the first time, the role of spatial correlation in the landscape on diffusion of a random walker.

Chemically frozen multicomponent boundary layer theory of salt and/or ash deposition rates from combustion gases

NASA Technical Reports Server (NTRS)

Rosner, D. E.; Chen, B.-K.; Fryburg, G. C.; Kohl, F. J.

1979-01-01

There is increased interest in, and concern about, deposition and corrosion phenomena in combustion systems containing inorganic condensible vapors and particles (salts, ash). To meet the need for a computationally tractable deposition rate theory general enough to embrace multielement/component situations of current and future gas turbine and magnetogasdynamic interest, a multicomponent chemically 'frozen' boundary layer (CFBL) deposition theory is presented and its applicability to the special case of Na2SO4 deposition from seeded laboratory burner combustion products is demonstrated. The coupled effects of Fick (concentration) diffusion and Soret (thermal) diffusion are included, along with explicit corrections for effects of variable properties and free stream turbulence. The present formulation is sufficiently general to include the transport of particles provided they are small enough to be formally treated as heavy molecules. Quantitative criteria developed to delineate the domain of validity of CFBL-rate theory suggest considerable practical promise for the present framework, which is characterized by relatively modest demands for new input information and computer time.

Numerical Test of the Additivity Principle in Anomalous Transport

NASA Astrophysics Data System (ADS)

Tamaki, Shuji

2017-10-01

The additivity principle (AP) is one of the remarkable predictions that systematically generates all information on current fluctuations once the value of average current in the linear response regime is input. However, conditions to justify the AP are still ambiguous. We hence consider three tractable models, and discuss possible conditions. The models include the harmonic chain (HC), momentum exchange (ME) model, and momentum flip (MF) model, which respectively show ballistic, anomalous, and diffusive transport. We compare the heat current cumulants predicted by the AP with exact numerical data obtained for these models. The HC does not show the AP, whereas the MF model satisfies it, as expected, since the AP was originally proposed for diffusive systems. Surprisingly, the ME model also shows the AP. The ME model is known to show the anomalous transport similar to that shown in nonlinear systems such as the Fermi-Pasta-Ulam model. Our finding indicates that general nonlinear systems may satisfy the AP. Possible conditions for satisfying the AP are discussed.

An "intelligent" approach based on side-by-side cascade-correlation neural networks for estimating thermophysical properties from photothermal responses

NASA Astrophysics Data System (ADS)

Grieu, Stéphane; Faugeroux, Olivier; Traoré, Adama; Claudet, Bernard; Bodnar, Jean-Luc

2015-01-01

In the present paper, an artificial-intelligence-based approach dealing with the estimation of thermophysical properties is designed and evaluated. This new and "intelligent" approach makes use of photothermal responses obtained when subjecting materials to a light flux. So, the main objective of the present work was to estimate simultaneously both the thermal diffusivity and conductivity of materials, from front-face or rear-face photothermal responses to pseudo random binary signals. To this end, we used side-by-side feedforward neural networks trained with the cascade-correlation algorithm. In addition, computation time was a key point to consider. That is why the developed algorithms are computationally tractable.

Theoretical study of the hyperfine parameters of OH

NASA Technical Reports Server (NTRS)

Chong, Delano P.; Langhoff, Stephen R.; Bauschlicher, Charles W., Jr.

1991-01-01

In the present study of the hyperfine parameters of O-17H as a function of the one- and n-particle spaces, all of the parameters except oxygen's spin density, b sub F(O), are sufficiently easily tractable to allow concentration on the computational requirements for accurate determination of b sub F(O). Full configuration-interaction (FCI) calculations in six Gaussian basis sets yield unambiguous results for (1) the effect of uncontracting the O s and p basis sets; (2) that of adding diffuse s and p functions; and (3) that of adding polarization functions to O. The size-extensive modified coupled-pair functional method yields b sub F values which are in fair agreement with FCI results.

Chemical vapor deposition fluid flow simulation modelling tool

NASA Technical Reports Server (NTRS)

Bullister, Edward T.

1992-01-01

Accurate numerical simulation of chemical vapor deposition (CVD) processes requires a general purpose computational fluid dynamics package combined with specialized capabilities for high temperature chemistry. In this report, we describe the implementation of these specialized capabilities in the spectral element code NEKTON. The thermal expansion of the gases involved is shown to be accurately approximated by the low Mach number perturbation expansion of the incompressible Navier-Stokes equations. The radiative heat transfer between multiple interacting radiating surfaces is shown to be tractable using the method of Gebhart. The disparate rates of reaction and diffusion in CVD processes are calculated via a point-implicit time integration scheme. We demonstrate the use above capabilities on prototypical CVD applications.

Binary recursive partitioning: background, methods, and application to psychology.

PubMed

Merkle, Edgar C; Shaffer, Victoria A

2011-02-01

Binary recursive partitioning (BRP) is a computationally intensive statistical method that can be used in situations where linear models are often used. Instead of imposing many assumptions to arrive at a tractable statistical model, BRP simply seeks to accurately predict a response variable based on values of predictor variables. The method outputs a decision tree depicting the predictor variables that were related to the response variable, along with the nature of the variables' relationships. No significance tests are involved, and the tree's 'goodness' is judged based on its predictive accuracy. In this paper, we describe BRP methods in a detailed manner and illustrate their use in psychological research. We also provide R code for carrying out the methods.

Spike solutions in Gierer#x2013;Meinhardt model with a time dependent anomaly exponent

NASA Astrophysics Data System (ADS)

Nec, Yana

2018-01-01

Experimental evidence of complex dispersion regimes in natural systems, where the growth of the mean square displacement in time cannot be characterised by a single power, has been accruing for the past two decades. In such processes the exponent γ(t) in ⟨r2⟩ ∼ tγ(t) at times might be approximated by a piecewise constant function, or it can be a continuous function. Variable order differential equations are an emerging mathematical tool with a strong potential to model these systems. However, variable order differential equations are not tractable by the classic differential equations theory. This contribution illustrates how a classic method can be adapted to gain insight into a system of this type. Herein a variable order Gierer-Meinhardt model is posed, a generic reaction- diffusion system of a chemical origin. With a fixed order this system possesses a solution in the form of a constellation of arbitrarily situated localised pulses, when the components' diffusivity ratio is asymptotically small. The pattern was shown to exist subject to multiple step-like transitions between normal diffusion and sub-diffusion, as well as between distinct sub-diffusive regimes. The analytical approximation obtained permits qualitative analysis of the impact thereof. Numerical solution for typical cross-over scenarios revealed such features as earlier equilibration and non-monotonic excursions before attainment of equilibrium. The method is general and allows for an approximate numerical solution with any reasonably behaved γ(t).

Effects of Buoyancy on Laminar, Transitional, and Turbulent Gas Jet Diffusion Flames

NASA Technical Reports Server (NTRS)

Bahadori, M. Yousef; Stocker, Dennis P.; Vaughan, David F.; Zhou, Liming; Edelman, Raymond B.

1993-01-01

Gas jet diffusion flames have been a subject of research for many years. However, a better understanding of the physical and chemical phenomena occurring in these flames is still needed, and, while the effects of gravity on the burning process have been observed, the basic mechanisms responsible for these changes have yet to be determined. The fundamental mechanisms that control the combustion process are in general coupled and quite complicated. These include mixing, radiation, kinetics, soot formation and disposition, inertia, diffusion, and viscous effects. In order to understand the mechanisms controlling a fire, laboratory-scale laminar and turbulent gas-jet diffusion flames have been extensively studied, which have provided important information in relation to the physico-chemical processes occurring in flames. However, turbulent flames are not fully understood and their understanding requires more fundamental studies of laminar diffusion flames in which the interplay of transport phenomena and chemical kinetics is more tractable. But even this basic, relatively simple flame is not completely characterized in relation to soot formation, radiation, diffusion, and kinetics. Therefore, gaining an understanding of laminar flames is essential to the understanding of turbulent flames, and particularly fires, in which the same basic phenomena occur. In order to improve and verify the theoretical models essential to the interpretation of data, the complexity and degree of coupling of the controlling mechanisms must be reduced. If gravity is isolated, the complication of buoyancy-induced convection would be removed from the problem. In addition, buoyant convection in normal gravity masks the effects of other controlling parameters on the flame. Therefore, the combination of normal-gravity and microgravity data would provide the information, both theoretical and experimental, to improve our understanding of diffusion flames in general, and the effects of gravity on the burning process in particular.

Generalizing Terwilliger's likelihood approach: a new score statistic to test for genetic association.

PubMed

el Galta, Rachid; Uitte de Willige, Shirley; de Visser, Marieke C H; Helmer, Quinta; Hsu, Li; Houwing-Duistermaat, Jeanine J

2007-09-24

In this paper, we propose a one degree of freedom test for association between a candidate gene and a binary trait. This method is a generalization of Terwilliger's likelihood ratio statistic and is especially powerful for the situation of one associated haplotype. As an alternative to the likelihood ratio statistic, we derive a score statistic, which has a tractable expression. For haplotype analysis, we assume that phase is known. By means of a simulation study, we compare the performance of the score statistic to Pearson's chi-square statistic and the likelihood ratio statistic proposed by Terwilliger. We illustrate the method on three candidate genes studied in the Leiden Thrombophilia Study. We conclude that the statistic follows a chi square distribution under the null hypothesis and that the score statistic is more powerful than Terwilliger's likelihood ratio statistic when the associated haplotype has frequency between 0.1 and 0.4 and has a small impact on the studied disorder. With regard to Pearson's chi-square statistic, the score statistic has more power when the associated haplotype has frequency above 0.2 and the number of variants is above five.

Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

NASA Astrophysics Data System (ADS)

Faber, W. R.; Zaidi, W.; Hussein, I. I.; Roscoe, C. W. T.; Wilkins, M. P.; Schumacher, P. W., Jr.

As more objects are launched into space, the potential for breakup events and space object collisions is ever increasing. These events create large clouds of debris that are extremely hazardous to space operations. Providing timely, accurate, and statistically meaningful Space Situational Awareness (SSA) data is crucial in order to protect assets and operations in space. The space object tracking problem, in general, is nonlinear in both state dynamics and observations, making it ill-suited to linear filtering techniques such as the Kalman filter. Additionally, given the multi-object, multi-scenario nature of the problem, space situational awareness requires multi-hypothesis tracking and management that is combinatorially challenging in nature. In practice, it is often seen that assumptions of underlying linearity and/or Gaussianity are used to provide tractable solutions to the multiple space object tracking problem. However, these assumptions are, at times, detrimental to tracking data and provide statistically inconsistent solutions. This paper details a tractable solution to the multiple space object tracking problem applicable to space object breakup events. Within this solution, simplifying assumptions of the underlying probability density function are relaxed and heuristic methods for hypothesis management are avoided. This is done by implementing Sequential Monte Carlo (SMC) methods for both nonlinear filtering as well as hypothesis management. This goal of this paper is to detail the solution and use it as a platform to discuss computational limitations that hinder proper analysis of large breakup events.

Martian ages

NASA Technical Reports Server (NTRS)

Neukum, G.; Hiller, K.

1981-01-01

Four discussions are conducted: (1) the methodology of relative age determination by impact crater statistics, (2) a comparison of proposed Martian impact chronologies for the determination of absolute ages from crater frequencies, (3) a report on work dating Martian volcanoes and erosional features by impact crater statistics, and (4) an attempt to understand the main features of Martian history through a synthesis of crater frequency data. Two cratering chronology models are presented and used for inference of absolute ages from crater frequency data, and it is shown that the interpretation of all data available and tractable by the methodology presented leads to a global Martian geological history that is characterized by two epochs of activity. It is concluded that Mars is an ancient planet with respect to its surface features.

Multicomponent Gas Diffusion and an Appropriate Momentum Boundary Condition

NASA Technical Reports Server (NTRS)

Noever, David A.

1994-01-01

Multicomponent gas diffusion is reviewed with particular emphasis on gas flows near solid boundaries-the so-called Kramers-Kistemaker effect. The aim is to derive an appropriate momentum boundary condition which governs many gaseous species diffusing together. The many species' generalization of the traditional single gas condition, either as slip or stick (no-slip), is not obvious, particularly for technologically important cases of lower gas pressures and very dissimilar molecular weight gases. No convincing theoretical case exists for why two gases should interact with solid boundaries equally but in opposite flow directions, such that the total gas flow exactly vanishes. ln this way, the multicomponent no-slip boundary requires careful treatment The approaches discussed here generally adopt a microscopic model for gas-solid contact. The method has the advantage that the mathematics remain tractable and hence experimentally testable. Two new proposals are put forward, the first building in some molecular collision physics, the second drawing on a detailed view of surface diffusion which does not unphysically extrapolate bulk gas properties to govern the adsorbed molecules. The outcome is a better accounting of previously anomalous experiments. Models predict novel slip conditions appearing even for the case of equal molecular weight components. These approaches become particularly significant in view of a conceptual contradiction found to arise in previous derivations of the appropriate boundary conditions. The analogous case of three gases, one of which is uniformly distributed and hence non-diffusing, presents a further refinement which gives unexpected flow reversals near solid boundaries. This case is investigated alone and for aggregating gas species near their condensation point. In addition to predicting new physics, this investigation carries practical implications for controlling vapor diffusion in the growth of crystals used in medical diagnosis (e.g. mercuric iodide) and semiconductors.

A Method for Molecular Dynamics on Curved Surfaces

PubMed Central

Paquay, Stefan; Kusters, Remy

2016-01-01

Dynamics simulations of constrained particles can greatly aid in understanding the temporal and spatial evolution of biological processes such as lateral transport along membranes and self-assembly of viruses. Most theoretical efforts in the field of diffusive transport have focused on solving the diffusion equation on curved surfaces, for which it is not tractable to incorporate particle interactions even though these play a crucial role in crowded systems. We show here that it is possible to take such interactions into account by combining standard constraint algorithms with the classical velocity Verlet scheme to perform molecular dynamics simulations of particles constrained to an arbitrarily curved surface. Furthermore, unlike Brownian dynamics schemes in local coordinates, our method is based on Cartesian coordinates, allowing for the reuse of many other standard tools without modifications, including parallelization through domain decomposition. We show that by applying the schemes to the Langevin equation for various surfaces, we obtain confined Brownian motion, which has direct applications to many biological and physical problems. Finally we present two practical examples that highlight the applicability of the method: 1) the influence of crowding and shape on the lateral diffusion of proteins in curved membranes; and 2) the self-assembly of a coarse-grained virus capsid protein model. PMID:27028633

A Method for Molecular Dynamics on Curved Surfaces

NASA Astrophysics Data System (ADS)

Paquay, Stefan; Kusters, Remy

2016-03-01

Dynamics simulations of constrained particles can greatly aid in understanding the temporal and spatial evolution of biological processes such as lateral transport along membranes and self-assembly of viruses. Most theoretical efforts in the field of diffusive transport have focussed on solving the diffusion equation on curved surfaces, for which it is not tractable to incorporate particle interactions even though these play a crucial role in crowded systems. We show here that it is possible to combine standard constraint algorithms with the classical velocity Verlet scheme to perform molecular dynamics simulations of particles constrained to an arbitrarily curved surface, in which such interactions can be taken into account. Furthermore, unlike Brownian dynamics schemes in local coordinates, our method is based on Cartesian coordinates allowing for the reuse of many other standard tools without modifications, including parallelisation through domain decomposition. We show that by applying the schemes to the Langevin equation for various surfaces, confined Brownian motion is obtained, which has direct applications to many biological and physical problems. Finally we present two practical examples that highlight the applicability of the method: (i) the influence of crowding and shape on the lateral diffusion of proteins in curved membranes and (ii) the self-assembly of a coarse-grained virus capsid protein model.

A stochastic multi-scale method for turbulent premixed combustion

NASA Astrophysics Data System (ADS)

Cha, Chong M.

2002-11-01

The stochastic chemistry algorithm of Bunker et al. and Gillespie is used to perform the chemical reactions in a transported probability density function (PDF) modeling approach of turbulent combustion. Recently, Kraft & Wagner have demonstrated a 100-fold gain in computational speed (for a 100 species mechanism) using the stochastic approach over the conventional, direct integration method of solving for the chemistry. Here, the stochastic chemistry algorithm is applied to develop a new transported PDF model of turbulent premixed combustion. The methodology relies on representing the relevant spatially dependent physical processes as queuing events. The canonical problem of a one-dimensional premixed flame is used for validation. For the laminar case, molecular diffusion is described by a random walk. For the turbulent case, one of two different material transport submodels can provide the necessary closure: Taylor dispersion or Kerstein's one-dimensional turbulence approach. The former exploits ``eddy diffusivity'' and hence would be much more computationally tractable for practical applications. Various validation studies are performed. Results from the Monte Carlo simulations compare well to asymptotic solutions of laminar premixed flames, both with and without high activation temperatures. The correct scaling of the turbulent burning velocity is predicted in both Damköhler's small- and large-scale turbulence limits. The effect of applying the eddy diffusivity concept in the various regimes is discussed.

Separation and correlation of structural and magnetic roughness in a Ni thin film by polarized off-specular neutron reflectometry.

PubMed

Singh, Surendra; Basu, Saibal

2009-02-04

Diffuse (off-specular) neutron and x-ray reflectometry has been used extensively for the determination of interface morphology in solids and liquids. For neutrons, a novel possibility is off-specular reflectometry with polarized neutrons to determine the morphology of a magnetic interface. There have been few such attempts due to the lower brilliance of neutron sources, though magnetic interaction of neutrons with atomic magnetic moments is much easier to comprehend and easily tractable theoretically. We have obtained a simple and physically meaningful expression, under the Born approximation, for analyzing polarized diffuse (off-specular) neutron reflectivity (PDNR) data. For the first time PDNR data from a Ni film have been analyzed and separate chemical and magnetic morphologies have been quantified. Also specular polarized neutron reflectivity measurements have been carried out to measure the magnetic moment density profile of the Ni film. The fit to PDNR data results in a longer correlation length for in-plane magnetic roughness than for chemical (structural) roughness. The magnetic interface is smoother than the chemical interface.

Modeling the sound transmission between rooms coupled through partition walls by using a diffusion model.

PubMed

Billon, Alexis; Foy, Cédric; Picaut, Judicaël; Valeau, Vincent; Sakout, Anas

2008-06-01

In this paper, a modification of the diffusion model for room acoustics is proposed to account for sound transmission between two rooms, a source room and an adjacent room, which are coupled through a partition wall. A system of two diffusion equations, one for each room, together with a set of two boundary conditions, one for the partition wall and one for the other walls of a room, is obtained and numerically solved. The modified diffusion model is validated by numerical comparisons with the statistical theory for several coupled-room configurations by varying the coupling area surface, the absorption coefficient of each room, and the volume of the adjacent room. An experimental comparison is also carried out for two coupled classrooms. The modified diffusion model results agree very well with both the statistical theory and the experimental data. The diffusion model can then be used as an alternative to the statistical theory, especially when the statistical theory is not applicable, that is, when the reverberant sound field is not diffuse. Moreover, the diffusion model allows the prediction of the spatial distribution of sound energy within each coupled room, while the statistical theory gives only one sound level for each room.

Finding Bounded Rational Equilibria. Part 1; Iterative Focusing

NASA Technical Reports Server (NTRS)

Wolpert, David H.

2004-01-01

A long-running difficulty with conventional game theory has been how to modify it to accommodate the bounded rationality characterizing all real-world players. A recurring issue in statistical physics is how best to approximate joint probability distributions with decoupled (and therefore far more tractable) distributions. It has recently been shown that the same information theoretic mathematical structure, known as Probability Collectives (PC) underlies both issues. This relationship between statistical physics and game theory allows techniques and insights from the one field to be applied to the other. In particular, PC provides a formal model-independent definition of the degree of rationality of a player and of bounded rationality equilibria. This pair of papers extends previous work on PC by introducing new computational approaches to effectively find bounded rationality equilibria of common-interest (team) games.

Landau-Zener extension of the Tavis-Cummings model: Structure of the solution

DOE PAGES

Sun, Chen; Sinitsyn, Nikolai A.

2016-09-07

We explore the recently discovered solution of the driven Tavis-Cummings model (DTCM). It describes interaction of an arbitrary number of two-level systems with a bosonic mode that has linearly time-dependent frequency. We derive compact and tractable expressions for transition probabilities in terms of the well-known special functions. In this form, our formulas are suitable for fast numerical calculations and analytical approximations. As an application, we obtain the semiclassical limit of the exact solution and compare it to prior approximations. Furthermore, we also reveal connection between DTCM and q-deformed binomial statistics.

Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes II: Size Effects on Ionic Distributions and Diffusion-Reaction Rates

PubMed Central

Lu, Benzhuo; Zhou, Y.C.

2011-01-01

The effects of finite particle size on electrostatics, density profiles, and diffusion have been a long existing topic in the study of ionic solution. The previous size-modified Poisson-Boltzmann and Poisson-Nernst-Planck models are revisited in this article. In contrast to many previous works that can only treat particle species with a single uniform size or two sizes, we generalize the Borukhov model to obtain a size-modified Poisson-Nernst-Planck (SMPNP) model that is able to treat nonuniform particle sizes. The numerical tractability of the model is demonstrated as well. The main contributions of this study are as follows. 1), We show that an (arbitrarily) size-modified PB model is indeed implied by the SMPNP equations under certain boundary/interface conditions, and can be reproduced through numerical solutions of the SMPNP. 2), The size effects in the SMPNP effectively reduce the densities of highly concentrated counterions around the biomolecule. 3), The SMPNP is applied to the diffusion-reaction process for the first time, to our knowledge. In the case of low substrate density near the enzyme reactive site, it is observed that the rate coefficients predicted by SMPNP model are considerably larger than those by the PNP model, suggesting both ions and substrates are subject to finite size effects. 4), An accurate finite element method and a convergent Gummel iteration are developed for the numerical solution of the completely coupled nonlinear system of SMPNP equations. PMID:21575582

Statistical variances of diffusional properties from ab initio molecular dynamics simulations

NASA Astrophysics Data System (ADS)

He, Xingfeng; Zhu, Yizhou; Epstein, Alexander; Mo, Yifei

2018-12-01

Ab initio molecular dynamics (AIMD) simulation is widely employed in studying diffusion mechanisms and in quantifying diffusional properties of materials. However, AIMD simulations are often limited to a few hundred atoms and a short, sub-nanosecond physical timescale, which leads to models that include only a limited number of diffusion events. As a result, the diffusional properties obtained from AIMD simulations are often plagued by poor statistics. In this paper, we re-examine the process to estimate diffusivity and ionic conductivity from the AIMD simulations and establish the procedure to minimize the fitting errors. In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events observed during the AIMD simulation. Since an adequate number of diffusion events must be sampled, AIMD simulations should be sufficiently long and can only be performed on materials with reasonably fast diffusion. We chart the ranges of materials and physical conditions that can be accessible by AIMD simulations in studying diffusional properties. Our work provides the foundation for quantifying the statistical confidence levels of diffusion results from AIMD simulations and for correctly employing this powerful technique.

Finding Bounded Rational Equilibria. Part 2; Alternative Lagrangians and Uncountable Move Spaces

NASA Technical Reports Server (NTRS)

Wolpert, David H.

2004-01-01

A long-running difficulty with conventional game theory has been how to modify it to accommodate the bounded rationality characterizing all real-world players. A recurring issue in statistical physics is how best to approximate joint probability distributions with decoupled (and therefore far more tractable) distributions. It has recently been shown that the same information theoretic mathematical structure, known as Probability Collectives (PC) underlies both issues. This relationship between statistical physics and game theory allows techniques and insights &om the one field to be applied to the other. In particular, PC provides a formal model-independent definition of the degree of rationality of a player and of bounded rationality equilibria. This pair of papers extends previous work on PC by introducing new computational approaches to effectively find bounded rationality equilibria of common-interest (team) games.

Diffusion tensor imaging in children with tuberous sclerosis complex: tract-based spatial statistics assessment of brain microstructural changes.

PubMed

Zikou, Anastasia K; Xydis, Vasileios G; Astrakas, Loukas G; Nakou, Iliada; Tzarouchi, Loukia C; Tzoufi, Meropi; Argyropoulou, Maria I

2016-07-01

There is evidence of microstructural changes in normal-appearing white matter of patients with tuberous sclerosis complex. To evaluate major white matter tracts in children with tuberous sclerosis complex using tract-based spatial statistics diffusion tensor imaging (DTI) analysis. Eight children (mean age ± standard deviation: 8.5 ± 5.5 years) with an established diagnosis of tuberous sclerosis complex and 8 age-matched controls were studied. The imaging protocol consisted of T1-weighted high-resolution 3-D spoiled gradient-echo sequence and a spin-echo, echo-planar diffusion-weighted sequence. Differences in the diffusion indices were evaluated using tract-based spatial statistics. Tract-based spatial statistics showed increased axial diffusivity in the children with tuberous sclerosis complex in the superior and anterior corona radiata, the superior longitudinal fascicle, the inferior fronto-occipital fascicle, the uncinate fascicle and the anterior thalamic radiation. No significant differences were observed in fractional anisotropy, mean diffusivity and radial diffusivity between patients and control subjects. No difference was found in the diffusion indices between the baseline and follow-up examination in the patient group. Patients with tuberous sclerosis complex have increased axial diffusivity in major white matter tracts, probably related to reduced axonal integrity.

Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics.

PubMed

Ocone, Andrea; Millar, Andrew J; Sanguinetti, Guido

2013-04-01

Computational modelling of the dynamics of gene regulatory networks is a central task of systems biology. For networks of small/medium scale, the dominant paradigm is represented by systems of coupled non-linear ordinary differential equations (ODEs). ODEs afford great mechanistic detail and flexibility, but calibrating these models to data is often an extremely difficult statistical problem. Here, we develop a general statistical inference framework for stochastic transcription-translation networks. We use a coarse-grained approach, which represents the system as a network of stochastic (binary) promoter and (continuous) protein variables. We derive an exact inference algorithm and an efficient variational approximation that allows scalable inference and learning of the model parameters. We demonstrate the power of the approach on two biological case studies, showing that the method allows a high degree of flexibility and is capable of testable novel biological predictions. http://homepages.inf.ed.ac.uk/gsanguin/software.html. Supplementary data are available at Bioinformatics online.

Side-by-side ANFIS as a useful tool for estimating correlated thermophysical properties

NASA Astrophysics Data System (ADS)

Grieu, Stéphane; Faugeroux, Olivier; Traoré, Adama; Claudet, Bernard; Bodnar, Jean-Luc

2015-12-01

In the present paper, an artificial intelligence-based approach dealing with the estimation of correlated thermophysical properties is designed and evaluated. This new and "intelligent" approach makes use of photothermal responses obtained when homogeneous materials are subjected to a light flux. Commonly, gradient-based algorithms are used as parameter estimation techniques. Unfortunately, such algorithms show instabilities leading to non-convergence in case of correlated properties to be estimated from a rebuilt impulse response. So, the main objective of the present work was to simultaneously estimate both the thermal diffusivity and conductivity of homogeneous materials, from front-face or rear-face photothermal responses to pseudo random binary signals. To this end, we used side-by-side neuro-fuzzy systems (adaptive network-based fuzzy inference systems) trained with a hybrid algorithm. We focused on the impact on generalization of both the examples used during training and the fuzzification process. In addition, computation time was a key point to consider. That is why the developed algorithm is computationally tractable and allows both the thermal diffusivity and conductivity of homogeneous materials to be simultaneously estimated with very good accuracy (the generalization error ranges between 4.6% and 6.2%).

An Overview of Interrater Agreement on Likert Scales for Researchers and Practitioners

PubMed Central

O'Neill, Thomas A.

2017-01-01

Applications of interrater agreement (IRA) statistics for Likert scales are plentiful in research and practice. IRA may be implicated in job analysis, performance appraisal, panel interviews, and any other approach to gathering systematic observations. Any rating system involving subject-matter experts can also benefit from IRA as a measure of consensus. Further, IRA is fundamental to aggregation in multilevel research, which is becoming increasingly common in order to address nesting. Although, several technical descriptions of a few specific IRA statistics exist, this paper aims to provide a tractable orientation to common IRA indices to support application. The introductory overview is written with the intent of facilitating contrasts among IRA statistics by critically reviewing equations, interpretations, strengths, and weaknesses. Statistics considered include rwg, rwg*, r′wg, rwg(p), average deviation (AD), awg, standard deviation (Swg), and the coefficient of variation (CVwg). Equations support quick calculation and contrasting of different agreement indices. The article also includes a “quick reference” table and three figures in order to help readers identify how IRA statistics differ and how interpretations of IRA will depend strongly on the statistic employed. A brief consideration of recommended practices involving statistical and practical cutoff standards is presented, and conclusions are offered in light of the current literature. PMID:28553257

Statistical error in simulations of Poisson processes: Example of diffusion in solids

NASA Astrophysics Data System (ADS)

Nilsson, Johan O.; Leetmaa, Mikael; Vekilova, Olga Yu.; Simak, Sergei I.; Skorodumova, Natalia V.

2016-08-01

Simulations of diffusion in solids often produce poor statistics of diffusion events. We present an analytical expression for the statistical error in ion conductivity obtained in such simulations. The error expression is not restricted to any computational method in particular, but valid in the context of simulation of Poisson processes in general. This analytical error expression is verified numerically for the case of Gd-doped ceria by running a large number of kinetic Monte Carlo calculations.

Extension of the Viscous Collision Limiting Direct Simulation Monte Carlo Technique to Multiple Species

NASA Technical Reports Server (NTRS)

Liechty, Derek S.; Burt, Jonathan M.

2016-01-01

There are many flows fields that span a wide range of length scales where regions of both rarefied and continuum flow exist and neither direct simulation Monte Carlo (DSMC) nor computational fluid dynamics (CFD) provide the appropriate solution everywhere. Recently, a new viscous collision limited (VCL) DSMC technique was proposed to incorporate effects of physical diffusion into collision limiter calculations to make the low Knudsen number regime normally limited to CFD more tractable for an all-particle technique. This original work had been derived for a single species gas. The current work extends the VCL-DSMC technique to gases with multiple species. Similar derivations were performed to equate numerical and physical transport coefficients. However, a more rigorous treatment of determining the mixture viscosity is applied. In the original work, consideration was given to internal energy non-equilibrium, and this is also extended in the current work to chemical non-equilibrium.

Crystallization and preliminary X-ray diffraction studies of hyperthermophilic archaeal Rieske-type ferredoxin (ARF) from Sulfolobus solfataricus P1

PubMed Central

Kounosu, Asako; Hasegawa, Kazuya; Iwasaki, Toshio; Kumasaka, Takashi

2010-01-01

The hyperthermophilic archaeal Rieske-type [2Fe–2S] ferredoxin (ARF) from Sulfolobus solfataricus P1 contains a low-potential Rieske-type [2Fe–2S] cluster that has served as a tractable model for ligand-substitution studies on this protein family. Recombinant ARF harbouring a pET30a vector-derived N-­terminal extension region plus a hexahistidine tag has been heterologously overproduced in Escherichia coli, purified and crystallized by the hanging-drop vapour-diffusion method using 0.05 M sodium acetate, 0.05 M HEPES, 2 M ammonium sulfate pH 5.5. The crystals diffracted to 1.85 Å resolution and belonged to the tetragonal space group P43212, with unit-cell parameters a = 60.72, c = 83.31 Å. The asymmetric unit contains one protein molecule. PMID:20606288

Crystallization and preliminary X-ray diffraction studies of hyperthermophilic archaeal Rieske-type ferredoxin (ARF) from Sulfolobus solfataricus P1.

PubMed

Kounosu, Asako; Hasegawa, Kazuya; Iwasaki, Toshio; Kumasaka, Takashi

2010-07-01

The hyperthermophilic archaeal Rieske-type [2Fe-2S] ferredoxin (ARF) from Sulfolobus solfataricus P1 contains a low-potential Rieske-type [2Fe-2S] cluster that has served as a tractable model for ligand-substitution studies on this protein family. Recombinant ARF harbouring a pET30a vector-derived N-terminal extension region plus a hexahistidine tag has been heterologously overproduced in Escherichia coli, purified and crystallized by the hanging-drop vapour-diffusion method using 0.05 M sodium acetate, 0.05 M HEPES, 2 M ammonium sulfate pH 5.5. The crystals diffracted to 1.85 A resolution and belonged to the tetragonal space group P4(3)2(1)2, with unit-cell parameters a = 60.72, c = 83.31 A. The asymmetric unit contains one protein molecule.

Short-Path Statistics and the Diffusion Approximation

NASA Astrophysics Data System (ADS)

Blanco, Stéphane; Fournier, Richard

2006-12-01

In the field of first return time statistics in bounded domains, short paths may be defined as those paths for which the diffusion approximation is inappropriate. This is at the origin of numerous open questions concerning the characterization of residence time distributions. We show here how general integral constraints can be derived that make it possible to address short-path statistics indirectly by application of the diffusion approximation to long paths. Application to the moments of the distribution at the low-Knudsen limit leads to simple practical results and novel physical pictures.

Task-based data-acquisition optimization for sparse image reconstruction systems

NASA Astrophysics Data System (ADS)

Chen, Yujia; Lou, Yang; Kupinski, Matthew A.; Anastasio, Mark A.

2017-03-01

Conventional wisdom dictates that imaging hardware should be optimized by use of an ideal observer (IO) that exploits full statistical knowledge of the class of objects to be imaged, without consideration of the reconstruction method to be employed. However, accurate and tractable models of the complete object statistics are often difficult to determine in practice. Moreover, in imaging systems that employ compressive sensing concepts, imaging hardware and (sparse) image reconstruction are innately coupled technologies. We have previously proposed a sparsity-driven ideal observer (SDIO) that can be employed to optimize hardware by use of a stochastic object model that describes object sparsity. The SDIO and sparse reconstruction method can therefore be "matched" in the sense that they both utilize the same statistical information regarding the class of objects to be imaged. To efficiently compute SDIO performance, the posterior distribution is estimated by use of computational tools developed recently for variational Bayesian inference. Subsequently, the SDIO test statistic can be computed semi-analytically. The advantages of employing the SDIO instead of a Hotelling observer are systematically demonstrated in case studies in which magnetic resonance imaging (MRI) data acquisition schemes are optimized for signal detection tasks.

Strategies for Global Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Paul; Morris, Robert; Khatib, Lina; Ramakrishnan, Sailesh

2004-01-01

A temporal reasoning problem can often be naturally characterized as a collection of constraints with associated local preferences for times that make up the admissible values for those constraints. Globally preferred solutions to such problems emerge as a result of well-defined operations that compose and order temporal assignments. The overall objective of this work is a characterization of different notions of global preference, and to identify tractable sub-classes of temporal reasoning problems incorporating these notions. This paper extends previous results by refining the class of useful notions of global temporal preference that are associated with problems that admit of tractable solution techniques. This paper also answers the hitherto open question of whether problems that seek solutions that are globally preferred from a Utilitarian criterion for global preference can be found tractably.

A modified Wright-Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity.

PubMed

Zhao, Lei; Gossmann, Toni I; Waxman, David

2016-03-21

The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have achieved good accuracy in all cases considered. In summary, the present work extends the realism and tractability of an important model of evolutionary biology and population genetics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Applying the multivariate time-rescaling theorem to neural population models

PubMed Central

Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

2011-01-01

Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

Spherical Ethylene/Air Diffusion Flames Subject to Concentric DC Electric Field in Microgravity

NASA Technical Reports Server (NTRS)

Yuan, Z. -G.; Hegde, U.; Faeth, G. M.

2001-01-01

It is well known that microgravity conditions, by eliminating buoyant flow, enable many combustion phenomena to be observed that are not possible to observe at normal gravity. One example is the spherical diffusion flame surrounding a porous spherical burner. The present paper demonstrates that by superimposing a spherical electrical field on such a flame, the flame remains spherical so that we can study the interaction between the electric field and flame in a one-dimensional fashion. Flames are susceptible to electric fields that are much weaker than the breakdown field of the flame gases owing to the presence of ions generated in the high temperature flame reaction zone. These ions and the electric current of the moving ions, in turn, significantly change the distribution of the electric field. Thus, to understand the interplay between the electric field and the flame is challenging. Numerous experimental studies of the effect of electric fields on flames have been reported. Unfortunately, they were all involved in complex geometries of both the flow field and the electric field, which hinders detailed study of the phenomena. In a one-dimensional domain, however, the electric field, the flow field, the thermal field and the chemical species field are all co-linear. Thus the problem is greatly simplified and becomes more tractable.

Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

DTIC Science & Technology

1987-04-20

Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

Experimental Investigations on Two Potential Sound Diffuseness Measures in Enclosures

NASA Astrophysics Data System (ADS)

Bai, Xin

This study investigates two different approaches to measure sound field diffuseness in enclosures from monophonic room impulse responses. One approach quantifies sound field diffuseness in enclosures by calculating the kurtosis of the pressure samples of room impulse responses. Kurtosis is a statistical measure that is known to describe the peakedness or tailedness of the distribution of a set of data. High kurtosis indicates low diffuseness of the sound field of interest. The other one relies on multifractal detrended fluctuation analysis which is a way to evaluate the statistical self-affinity of a signal to measure diffuseness. To test these two approaches, room impulse responses are obtained under varied room-acoustic diffuseness configurations, achieved by using varied degrees of diffusely reflecting interior surfaces. This paper will analyze experimentally measured monophonic room impulse responses, and discuss results from these two approaches.

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation

PubMed Central

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes “winner-take-all” processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans’ value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light. PMID:29077746

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

PubMed

Colas, Jaron T

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

Analytic treatment of nuclear spin-lattice relaxation for diffusion in a cone model

NASA Astrophysics Data System (ADS)

Sitnitsky, A. E.

2011-12-01

We consider nuclear spin-lattice relaxation rate resulted from a diffusion equation for rotational wobbling in a cone. We show that the widespread point of view that there are no analytical expressions for correlation functions for wobbling in a cone model is invalid and prove that nuclear spin-lattice relaxation in this model is exactly tractable and amenable to full analytical description. The mechanism of relaxation is assumed to be due to dipole-dipole interaction of nuclear spins and is treated within the framework of the standard Bloemberger, Purcell, Pound-Solomon scheme. We consider the general case of arbitrary orientation of the cone axis relative the magnetic field. The BPP-Solomon scheme is shown to remain valid for systems with the distribution of the cone axes depending only on the tilt relative the magnetic field but otherwise being isotropic. We consider the case of random isotropic orientation of cone axes relative the magnetic field taking place in powders. Also we consider the cases of their predominant orientation along or opposite the magnetic field and that of their predominant orientation transverse to the magnetic field which may be relevant for, e.g., liquid crystals. Besides we treat in details the model case of the cone axis directed along the magnetic field. The latter provides direct comparison of the limiting case of our formulas with the textbook formulas for free isotropic rotational diffusion. The dependence of the spin-lattice relaxation rate on the cone half-width yields results similar to those predicted by the model-free approach.

Cheese rind communities provide tractable systems for in situ and in vitro studies of microbial diversity

PubMed Central

Wolfe, Benjamin E.; Button, Julie E.; Santarelli, Marcela; Dutton, Rachel J.

2014-01-01

SUMMARY Tractable microbial communities are needed to bridge the gap between observations of patterns of microbial diversity and mechanisms that can explain these patterns. We developed cheese rinds as model microbial communities by characterizing in situ patterns of diversity and by developing an in vitro system for community reconstruction. Sequencing of 137 different rind communities across 10 countries revealed 24 widely distributed and culturable genera of bacteria and fungi as dominant community members. Reproducible community types formed independent of geographic location of production. Intensive temporal sampling demonstrated that assembly of these communities is highly reproducible. Patterns of community composition and succession observed in situ can be recapitulated in a simple in vitro system. Widespread positive and negative interactions were identified between bacterial and fungal community members. Cheese rind microbial communities represent an experimentally tractable system for defining mechanisms that influence microbial community assembly and function. PMID:25036636

Temperature- and composition-dependent hydrogen diffusivity in palladium from statistically-averaged molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Xiaowang; Heo, Tae Wook; Wood, Brandon C.

Solid-state hydrogen storage materials undergo complex phase transformations whose kinetics is often limited by hydrogen diffusion. Among metal hydrides, palladium hydride undergoes a diffusional phase transformation upon hydrogen uptake, during which the hydrogen diffusivity varies with hydrogen composition and temperature. Here we perform robust statistically-averaged molecular dynamics simulations to obtain a well-converged analytical expression for hydrogen diffusivity in bulk palladium that is valid throughout all stages of the reaction. Our studies confirm significant dependence of the diffusivity on composition and temperature that elucidate key trends in the available experimental measurements. Whereas at low hydrogen compositions, a single process dominates, atmore » high hydrogen compositions, diffusion is found to exhibit behavior consistent with multiple hopping barriers. Further analysis, supported by nudged elastic band computations, suggests that the multi-barrier diffusion can be interpreted as two distinct mechanisms corresponding to hydrogen-rich and hydrogen-poor local environments.« less

Temperature- and composition-dependent hydrogen diffusivity in palladium from statistically-averaged molecular dynamics

DOE PAGES

Zhou, Xiaowang; Heo, Tae Wook; Wood, Brandon C.; ...

2018-03-09

Solid-state hydrogen storage materials undergo complex phase transformations whose kinetics is often limited by hydrogen diffusion. Among metal hydrides, palladium hydride undergoes a diffusional phase transformation upon hydrogen uptake, during which the hydrogen diffusivity varies with hydrogen composition and temperature. Here we perform robust statistically-averaged molecular dynamics simulations to obtain a well-converged analytical expression for hydrogen diffusivity in bulk palladium that is valid throughout all stages of the reaction. Our studies confirm significant dependence of the diffusivity on composition and temperature that elucidate key trends in the available experimental measurements. Whereas at low hydrogen compositions, a single process dominates, atmore » high hydrogen compositions, diffusion is found to exhibit behavior consistent with multiple hopping barriers. Further analysis, supported by nudged elastic band computations, suggests that the multi-barrier diffusion can be interpreted as two distinct mechanisms corresponding to hydrogen-rich and hydrogen-poor local environments.« less

Statistical assessment of bi-exponential diffusion weighted imaging signal characteristics induced by intravoxel incoherent motion in malignant breast tumors

PubMed Central

Wong, Oi Lei; Lo, Gladys G.; Chan, Helen H. L.; Wong, Ting Ting; Cheung, Polly S. Y.

2016-01-01

Background The purpose of this study is to statistically assess whether bi-exponential intravoxel incoherent motion (IVIM) model better characterizes diffusion weighted imaging (DWI) signal of malignant breast tumor than mono-exponential Gaussian diffusion model. Methods 3 T DWI data of 29 malignant breast tumors were retrospectively included. Linear least-square mono-exponential fitting and segmented least-square bi-exponential fitting were used for apparent diffusion coefficient (ADC) and IVIM parameter quantification, respectively. F-test and Akaike Information Criterion (AIC) were used to statistically assess the preference of mono-exponential and bi-exponential model using region-of-interests (ROI)-averaged and voxel-wise analysis. Results For ROI-averaged analysis, 15 tumors were significantly better fitted by bi-exponential function and 14 tumors exhibited mono-exponential behavior. The calculated ADC, D (true diffusion coefficient) and f (pseudo-diffusion fraction) showed no significant differences between mono-exponential and bi-exponential preferable tumors. Voxel-wise analysis revealed that 27 tumors contained more voxels exhibiting mono-exponential DWI decay while only 2 tumors presented more bi-exponential decay voxels. ADC was consistently and significantly larger than D for both ROI-averaged and voxel-wise analysis. Conclusions Although the presence of IVIM effect in malignant breast tumors could be suggested, statistical assessment shows that bi-exponential fitting does not necessarily better represent the DWI signal decay in breast cancer under clinically typical acquisition protocol and signal-to-noise ratio (SNR). Our study indicates the importance to statistically examine the breast cancer DWI signal characteristics in practice. PMID:27709078

Grand canonical validation of the bipartite international trade network.

PubMed

Straka, Mika J; Caldarelli, Guido; Saracco, Fabio

2017-08-01

Devising strategies for economic development in a globally competitive landscape requires a solid and unbiased understanding of countries' technological advancements and similarities among export products. Both can be addressed through the bipartite representation of the International Trade Network. In this paper, we apply the recently proposed grand canonical projection algorithm to uncover country and product communities. Contrary to past endeavors, our methodology, based on information theory, creates monopartite projections in an unbiased and analytically tractable way. Single links between countries or products represent statistically significant signals, which are not accounted for by null models such as the bipartite configuration model. We find stable country communities reflecting the socioeconomic distinction in developed, newly industrialized, and developing countries. Furthermore, we observe product clusters based on the aforementioned country groups. Our analysis reveals the existence of a complicated structure in the bipartite International Trade Network: apart from the diversification of export baskets from the most basic to the most exclusive products, we observe a statistically significant signal of an export specialization mechanism towards more sophisticated products.

Grand canonical validation of the bipartite international trade network

NASA Astrophysics Data System (ADS)

Straka, Mika J.; Caldarelli, Guido; Saracco, Fabio

2017-08-01

Devising strategies for economic development in a globally competitive landscape requires a solid and unbiased understanding of countries' technological advancements and similarities among export products. Both can be addressed through the bipartite representation of the International Trade Network. In this paper, we apply the recently proposed grand canonical projection algorithm to uncover country and product communities. Contrary to past endeavors, our methodology, based on information theory, creates monopartite projections in an unbiased and analytically tractable way. Single links between countries or products represent statistically significant signals, which are not accounted for by null models such as the bipartite configuration model. We find stable country communities reflecting the socioeconomic distinction in developed, newly industrialized, and developing countries. Furthermore, we observe product clusters based on the aforementioned country groups. Our analysis reveals the existence of a complicated structure in the bipartite International Trade Network: apart from the diversification of export baskets from the most basic to the most exclusive products, we observe a statistically significant signal of an export specialization mechanism towards more sophisticated products.

Partitioning heritability by functional annotation using genome-wide association summary statistics.

PubMed

Finucane, Hilary K; Bulik-Sullivan, Brendan; Gusev, Alexander; Trynka, Gosia; Reshef, Yakir; Loh, Po-Ru; Anttila, Verneri; Xu, Han; Zang, Chongzhi; Farh, Kyle; Ripke, Stephan; Day, Felix R; Purcell, Shaun; Stahl, Eli; Lindstrom, Sara; Perry, John R B; Okada, Yukinori; Raychaudhuri, Soumya; Daly, Mark J; Patterson, Nick; Neale, Benjamin M; Price, Alkes L

2015-11-01

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many cell type-specific enrichments, including significant enrichment of central nervous system cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

Building statistical associations to forecast ethylbenzene levels in European urban-traffic environments.

PubMed

Vlachokostas, Ch; Michailidou, A V; Spyridi, D; Moussiopoulos, N

2013-06-01

Emission from road traffic has become the most important source of local air pollution in numerous European cities. Epidemiological research community has established consistent associations between traffic-related substances and various health outcomes. Nevertheless, the vast majority of urban areas are characterised by infrastructure's absence to routinely monitor chemical health stressors, such as ethylbenzene. This paper aims at developing and presenting a tractable approach to reliably - and inexpensively - predict ethylbenzene trends in EU urban environments. The establishment of empirical relationships between rarely monitored pollutants such as ethylbenzene and more frequently or usually monitored, such as benzene and CO respectively, may cover the infrastructure's absence and support decision-making. Multiple regression analysis is adopted and the resulting statistical associations are applied to EU cities with available data for validation purposes. The results demonstrate that this approach is capable of capturing ethylbenzene concentration trends and should be considered as complementary to air quality monitoring. Copyright © 2013 Elsevier Ltd. All rights reserved.

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation.

PubMed

Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A; Massafra, Andrea; Pellè, Piergiuseppe

2015-01-01

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages.

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation

PubMed Central

Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A.; Massafra, Andrea; Pellè, Piergiuseppe

2015-01-01

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages. PMID:26617539

Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes

NASA Technical Reports Server (NTRS)

Williams Colin P.

1999-01-01

Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.

A framework for incorporating DTI Atlas Builder registration into Tract-Based Spatial Statistics and a simulated comparison to standard TBSS.

PubMed

Leming, Matthew; Steiner, Rachel; Styner, Martin

2016-02-27

Tract-based spatial statistics (TBSS) 6 is a software pipeline widely employed in comparative analysis of the white matter integrity from diffusion tensor imaging (DTI) datasets. In this study, we seek to evaluate the relationship between different methods of atlas registration for use with TBSS and different measurements of DTI (fractional anisotropy, FA, axial diffusivity, AD, radial diffusivity, RD, and medial diffusivity, MD). To do so, we have developed a novel tool that builds on existing diffusion atlas building software, integrating it into an adapted version of TBSS called DAB-TBSS (DTI Atlas Builder-Tract-Based Spatial Statistics) by using the advanced registration offered in DTI Atlas Builder 7 . To compare the effectiveness of these two versions of TBSS, we also propose a framework for simulating population differences for diffusion tensor imaging data, providing a more substantive means of empirically comparing DTI group analysis programs such as TBSS. In this study, we used 33 diffusion tensor imaging datasets and simulated group-wise changes in this data by increasing, in three different simulations, the principal eigenvalue (directly altering AD), the second and third eigenvalues (RD), and all three eigenvalues (MD) in the genu, the right uncinate fasciculus, and the left IFO. Additionally, we assessed the benefits of comparing the tensors directly using a functional analysis of diffusion tensor tract statistics (FADTTS 10 ). Our results indicate comparable levels of FA-based detection between DAB-TBSS and TBSS, with standard TBSS registration reporting a higher rate of false positives in other measurements of DTI. Within the simulated changes investigated here, this study suggests that the use of DTI Atlas Builder's registration enhances TBSS group-based studies.

Generation of a Kind of Displaced Thermal States in the Diffusion Process and its Statistical Properties

NASA Astrophysics Data System (ADS)

Xiang-Guo, Meng; Hong-Yi, Fan; Ji-Suo, Wang

2018-04-01

This paper proposes a kind of displaced thermal states (DTS) and explores how this kind of optical field emerges using the entangled state representation. The results show that the DTS can be generated by a coherent state passing through a diffusion channel with the diffusion coefficient ϰ only when there exists κ t = (e^{\\hbar ν /kBT} - 1 )^{-1}. Also, its statistical properties, such as mean photon number, Wigner function and entropy, are investigated.

Some basic mathematical methods of diffusion theory. [emphasis on atmospheric applications

NASA Technical Reports Server (NTRS)

Giere, A. C.

1977-01-01

An introductory treatment of the fundamentals of diffusion theory is presented, starting with molecular diffusion and leading up to the statistical methods of turbulent diffusion. A multilayer diffusion model, designed to permit concentration and dosage calculations downwind of toxic clouds from rocket vehicles, is described. The concepts and equations of diffusion are developed on an elementary level, with emphasis on atmospheric applications.

When mechanism matters: Bayesian forecasting using models of ecological diffusion

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Russell, Robin E.; Walsh, Daniel P.; Powell, James A.

2017-01-01

Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

Diffusion-weighted magnetic resonance imaging of extraocular muscles in patients with Grave's ophthalmopathy using turbo field echo with diffusion-sensitized driven-equilibrium preparation.

PubMed

Hiwatashi, A; Togao, O; Yamashita, K; Kikuchi, K; Momosaka, D; Honda, H

2018-03-20

The purpose of this study was to correlate diffusivity of extraocular muscles, measured by three-dimensional turbo field echo (3DTFE) magnetic resonance (MR) imaging using diffusion-sensitized driven-equilibrium preparation, with their size and activity in patients with Grave's ophthalmopathy. Twenty-three patients with Grave's ophthalmopathy were included. There were 17 women and 6 men with a mean age of 55.8±12.6 (SD) years (range: 26-83 years). 3DTFE with diffusion-sensitized driven-equilibrium MR images were obtained with b-values of 0 and 500s/mm 2 . The apparent diffusion coefficient (ADC) of extraocular muscles was measured on coronal reformatted MR images. Signal intensities of extraocular muscles on conventional MR images were compared to those of normal-appearing white matter, and cross-sectional areas of the muscles were also measured. The clinical activity score was also evaluated. Statistical analyses were performed with Pearson correlation and Mann-Whitney U tests. On 3DTFE with diffusion-sensitized driven-equilibrium preparation, the mean ADC of the extraocular muscles was 2.23±0.37 (SD)×10 -3 mm2/s (range: 1.70×10 -3 -3.11×10 -3 mm 2 /s). There was a statistically significant moderate correlation between ADC and the size of the muscles (r=0.61). There were no statistically significant correlations between ADC and signal intensity on conventional MR and the clinical activity score. 3DTFE with diffusion-sensitized driven-equilibrium preparation technique allows quantifying diffusivity of extraocular muscles in patients with Grave's ophthalmopathy. The diffusivity of the extraocular muscles on 3DTFE with diffusion-sensitized driven-equilibrium preparation MR images moderately correlates with their size. Copyright © 2018. Published by Elsevier Masson SAS.

Statistical Issues for Calculating Reentry Hazards

NASA Technical Reports Server (NTRS)

Matney, Mark; Bacon, John

2016-01-01

A number of statistical tools have been developed over the years for assessing the risk of reentering object to human populations. These tools make use of the characteristics (e.g., mass, shape, size) of debris that are predicted by aerothermal models to survive reentry. This information, combined with information on the expected ground path of the reentry, is used to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of this analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. This inevitably involves assumptions that simplify the problem and make it tractable, but it is often difficult to test the accuracy and applicability of these assumptions. This paper builds on previous IAASS work to re-examine many of these theoretical assumptions, including the mathematical basis for the hazard calculations, and outlining the conditions under which the simplifying assumptions hold. This study also employs empirical and theoretical information to test these assumptions, and makes recommendations how to improve the accuracy of these calculations in the future.

Statistical Issues for Calculating Reentry Hazards

NASA Technical Reports Server (NTRS)

Bacon, John B.; Matney, Mark

2016-01-01

A number of statistical tools have been developed over the years for assessing the risk of reentering object to human populations. These tools make use of the characteristics (e.g., mass, shape, size) of debris that are predicted by aerothermal models to survive reentry. This information, combined with information on the expected ground path of the reentry, is used to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of this analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. This inevitably involves assumptions that simplify the problem and make it tractable, but it is often difficult to test the accuracy and applicability of these assumptions. This paper builds on previous IAASS work to re-examine one of these theoretical assumptions.. This study employs empirical and theoretical information to test the assumption of a fully random decay along the argument of latitude of the final orbit, and makes recommendations how to improve the accuracy of this calculation in the future.

Dynamics of history-dependent epidemics in temporal networks

NASA Astrophysics Data System (ADS)

Sunny, Albert; Kotnis, Bhushan; Kuri, Joy

2015-08-01

The structural properties of temporal networks often influence the dynamical processes that occur on these networks, e.g., bursty interaction patterns have been shown to slow down epidemics. In this paper, we investigate the effect of link lifetimes on the spread of history-dependent epidemics. We formulate an analytically tractable activity-driven temporal network model that explicitly incorporates link lifetimes. For Markovian link lifetimes, we use mean-field analysis for computing the epidemic threshold, while the effect of non-Markovian link lifetimes is studied using simulations. Furthermore, we also study the effect of negative correlation between the number of links spawned by an individual and the lifetimes of those links. Such negative correlations may arise due to the finite cognitive capacity of the individuals. Our investigations reveal that heavy-tailed link lifetimes slow down the epidemic, while negative correlations can reduce epidemic prevalence. We believe that our results help shed light on the role of link lifetimes in modulating diffusion processes on temporal networks.

Photophysical behavior of polyatomic molecules

NASA Astrophysics Data System (ADS)

Ware, W. R.

1980-10-01

Part one of this report deals with attempts over the past several years to devise a more sophisticated theory of diffusion controlled reactions than that presented by Collins and Kimball. In particular, the investigators were interested in a more realistic formulation of the problem of high concentration quenching where quenches in the vicinity of the molecular to be quenched must be considered. It was desired however, to obtain a formalism which was tractable mathematically and which contained parameters which would be related to experiment. Part two deals with the photophysics of systems exhibiting molecular association both in the ground and excited states has been studied. The emphasis has been on kinetic models, the measurement of rate constants associated with these models, and the determination of activation parameters and equilibrium thermodynamic parameters associated with the exciplex formation and disappearance. Studies of solvent effects and steric effects on the behavior of exciplex systems have been carried out. The case of rapid equilibrium where the monomer and exciplex decay with the same rate constant has also been examined.

Advances in detection of diffuse seafloor venting using structured light imaging.

NASA Astrophysics Data System (ADS)

Smart, C.; Roman, C.; Carey, S.

2016-12-01

Systematic, remote detection and high resolution mapping of low temperature diffuse hydrothermal venting is inefficient and not currently tractable using traditional remotely operated vehicle (ROV) mounted sensors. Preliminary results for hydrothermal vent detection using a structured light laser sensor were presented in 2011 and published in 2013 (Smart) with continual advancements occurring in the interim. As the structured light laser passes over active venting, the projected laser line effectively blurs due to the associated turbulence and density anomalies in the vent fluid. The degree laser disturbance is captured by a camera collecting images of the laser line at 20 Hz. Advancements in the detection of the laser and fluid interaction have included extensive normalization of the collected laser data and the implementation of a support vector machine algorithm to develop a classification routine. The image data collected over a hydrothermal vent field is then labeled as seafloor, bacteria or a location of venting. The results can then be correlated with stereo images, bathymetry and backscatter data. This sensor is a component of an ROV mounted imaging suite which also includes stereo cameras and a multibeam sonar system. Originally developed for bathymetric mapping, the structured light laser sensor, and other imaging suite components, are capable of creating visual and bathymetric maps with centimeter level resolution. Surveys are completed in a standard mowing the lawn pattern completing a 30m x 30m survey with centimeter level resolution in under an hour. Resulting co-registered data includes, multibeam and structured light laser bathymetry and backscatter, stereo images and vent detection. This system allows for efficient exploration of areas with diffuse and small point source hydrothermal venting increasing the effectiveness of scientific sampling and observation. Recent vent detection results collected during the 2013-2015 E/V Nautilus seasons will be presented. Smart, C. J. and Roman, C. and Carey, S. N. (2013) Detection of diffuse seafloor venting using structured light imaging, Geochemistry, Geophysics, Geosystems, 14, 4743-4757

Probabilistic-driven oriented Speckle reducing anisotropic diffusion with application to cardiac ultrasonic images.

PubMed

Vegas-Sanchez-Ferrero, G; Aja-Fernandez, S; Martin-Fernandez, M; Frangi, A F; Palencia, C

2010-01-01

A novel anisotropic diffusion filter is proposed in this work with application to cardiac ultrasonic images. It includes probabilistic models which describe the probability density function (PDF) of tissues and adapts the diffusion tensor to the image iteratively. For this purpose, a preliminary study is performed in order to select the probability models that best fit the stastitical behavior of each tissue class in cardiac ultrasonic images. Then, the parameters of the diffusion tensor are defined taking into account the statistical properties of the image at each voxel. When the structure tensor of the probability of belonging to each tissue is included in the diffusion tensor definition, a better boundaries estimates can be obtained instead of calculating directly the boundaries from the image. This is the main contribution of this work. Additionally, the proposed method follows the statistical properties of the image in each iteration. This is considered as a second contribution since state-of-the-art methods suppose that noise or statistical properties of the image do not change during the filter process.

FADTTS: functional analysis of diffusion tensor tract statistics.

PubMed

Zhu, Hongtu; Kong, Linglong; Li, Runze; Styner, Martin; Gerig, Guido; Lin, Weili; Gilmore, John H

2011-06-01

The aim of this paper is to present a functional analysis of a diffusion tensor tract statistics (FADTTS) pipeline for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. The FADTTS integrates five statistical tools: (i) a multivariate varying coefficient model for allowing the varying coefficient functions in terms of arc length to characterize the varying associations between fiber bundle diffusion properties and a set of covariates, (ii) a weighted least squares estimation of the varying coefficient functions, (iii) a functional principal component analysis to delineate the structure of the variability in fiber bundle diffusion properties, (iv) a global test statistic to test hypotheses of interest, and (v) a simultaneous confidence band to quantify the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FADTTS. We apply FADTTS to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. FADTTS can be used to facilitate the understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modeling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands. However, FADTTS is not crucial for estimation and reduces to the functional analysis method for the single measure. Copyright © 2011 Elsevier Inc. All rights reserved.

Algorithms and Complexity Results for Genome Mapping Problems.

PubMed

Rajaraman, Ashok; Zanetti, Joao Paulo Pereira; Manuch, Jan; Chauve, Cedric

2017-01-01

Genome mapping algorithms aim at computing an ordering of a set of genomic markers based on local ordering information such as adjacencies and intervals of markers. In most genome mapping models, markers are assumed to occur uniquely in the resulting map. We introduce algorithmic questions that consider repeats, i.e., markers that can have several occurrences in the resulting map. We show that, provided with an upper bound on the copy number of repeated markers and with intervals that span full repeat copies, called repeat spanning intervals, the problem of deciding if a set of adjacencies and repeat spanning intervals admits a genome representation is tractable if the target genome can contain linear and/or circular chromosomal fragments. We also show that extracting a maximum cardinality or weight subset of repeat spanning intervals given a set of adjacencies that admits a genome realization is NP-hard but fixed-parameter tractable in the maximum copy number and the number of adjacent repeats, and tractable if intervals contain a single repeated marker.

Stochastic mechanics of reciprocal diffusions

NASA Astrophysics Data System (ADS)

Levy, Bernard C.; Krener, Arthur J.

1996-02-01

The dynamics and kinematics of reciprocal diffusions were examined in a previous paper [J. Math. Phys. 34, 1846 (1993)], where it was shown that reciprocal diffusions admit a chain of conservation laws, which close after the first two laws for two disjoint subclasses of reciprocal diffusions, the Markov and quantum diffusions. For the case of quantum diffusions, the conservation laws are equivalent to Schrödinger's equation. The Markov diffusions were employed by Schrödinger [Sitzungsber. Preuss. Akad. Wiss. Phys. Math Kl. 144 (1931); Ann. Inst. H. Poincaré 2, 269 (1932)], Nelson [Dynamical Theories of Brownian Motion (Princeton University, Princeton, NJ, 1967); Quantum Fluctuations (Princeton University, Princeton, NJ, 1985)], and other researchers to develop stochastic formulations of quantum mechanics, called stochastic mechanics. We propose here an alternative version of stochastic mechanics based on quantum diffusions. A procedure is presented for constructing the quantum diffusion associated to a given wave function. It is shown that quantum diffusions satisfy the uncertainty principle, and have a locality property, whereby given two dynamically uncoupled but statistically correlated particles, the marginal statistics of each particle depend only on the local fields to which the particle is subjected. However, like Wigner's joint probability distribution for the position and momentum of a particle, the finite joint probability densities of quantum diffusions may take negative values.

Statistical theory of diffusion in concentrated bcc and fcc alloys and concentration dependencies of diffusion coefficients in bcc alloys FeCu, FeMn, FeNi, and FeCr

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vaks, V. G.; Khromov, K. Yu., E-mail: khromov-ky@nrcki.ru; Pankratov, I. R.

2016-07-15

The statistical theory of diffusion in concentrated bcc and fcc alloys with arbitrary pairwise interatomic interactions based on the master equation approach is developed. Vacancy–atom correlations are described using both the second-shell-jump and the nearest-neighbor-jump approximations which are shown to be usually sufficiently accurate. General expressions for Onsager coefficients in terms of microscopic interatomic interactions and some statistical averages are given. Both the analytical kinetic mean-field and the Monte Carlo methods for finding these averages are described. The theory developed is used to describe sharp concentration dependencies of diffusion coefficients in several iron-based alloy systems. For the bcc alloys FeCu,more » FeMn, and FeNi, we predict the notable increase of the iron self-diffusion coefficient with solute concentration c, up to several times, even though values of c possible for these alloys do not exceed some percent. For the bcc alloys FeCr at high temperatures T ≳ 1400 K, we show that the very strong and peculiar concentration dependencies of both tracer and chemical diffusion coefficients observed in these alloys can be naturally explained by the theory, without invoking exotic models discussed earlier.« less

Stochastic hybrid systems for studying biochemical processes.

PubMed

Singh, Abhyudai; Hespanha, João P

2010-11-13

Many protein and mRNA species occur at low molecular counts within cells, and hence are subject to large stochastic fluctuations in copy numbers over time. Development of computationally tractable frameworks for modelling stochastic fluctuations in population counts is essential to understand how noise at the cellular level affects biological function and phenotype. We show that stochastic hybrid systems (SHSs) provide a convenient framework for modelling the time evolution of population counts of different chemical species involved in a set of biochemical reactions. We illustrate recently developed techniques that allow fast computations of the statistical moments of the population count, without having to run computationally expensive Monte Carlo simulations of the biochemical reactions. Finally, we review different examples from the literature that illustrate the benefits of using SHSs for modelling biochemical processes.

Modelling Detailed-Chemistry Effects on Turbulent Diffusion Flames using a Parallel Solution-Adaptive Scheme

NASA Astrophysics Data System (ADS)

Jha, Pradeep Kumar

Capturing the effects of detailed-chemistry on turbulent combustion processes is a central challenge faced by the numerical combustion community. However, the inherent complexity and non-linear nature of both turbulence and chemistry require that combustion models rely heavily on engineering approximations to remain computationally tractable. This thesis proposes a computationally efficient algorithm for modelling detailed-chemistry effects in turbulent diffusion flames and numerically predicting the associated flame properties. The cornerstone of this combustion modelling tool is the use of parallel Adaptive Mesh Refinement (AMR) scheme with the recently proposed Flame Prolongation of Intrinsic low-dimensional manifold (FPI) tabulated-chemistry approach for modelling complex chemistry. The effect of turbulence on the mean chemistry is incorporated using a Presumed Conditional Moment (PCM) approach based on a beta-probability density function (PDF). The two-equation k-w turbulence model is used for modelling the effects of the unresolved turbulence on the mean flow field. The finite-rate of methane-air combustion is represented here by using the GRI-Mech 3.0 scheme. This detailed mechanism is used to build the FPI tables. A state of the art numerical scheme based on a parallel block-based solution-adaptive algorithm has been developed to solve the Favre-averaged Navier-Stokes (FANS) and other governing partial-differential equations using a second-order accurate, fully-coupled finite-volume formulation on body-fitted, multi-block, quadrilateral/hexahedral mesh for two-dimensional and three-dimensional flow geometries, respectively. A standard fourth-order Runge-Kutta time-marching scheme is used for time-accurate temporal discretizations. Numerical predictions of three different diffusion flames configurations are considered in the present work: a laminar counter-flow flame; a laminar co-flow diffusion flame; and a Sydney bluff-body turbulent reacting flow. Comparisons are made between the predicted results of the present FPI scheme and Steady Laminar Flamelet Model (SLFM) approach for diffusion flames. The effects of grid resolution on the predicted overall flame solutions are also assessed. Other non-reacting flows have also been considered to further validate other aspects of the numerical scheme. The present schemes predict results which are in good agreement with published experimental results and reduces the computational cost involved in modelling turbulent diffusion flames significantly, both in terms of storage and processing time.

Learning-based stochastic object models for use in optimizing imaging systems

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Anastasio, Mark A.; Yu, Lifeng; Li, Hua

2017-03-01

It is widely known that the optimization of imaging systems based on objective, or task-based, measures of image quality via computer-simulation requires use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in anatomy within a specified ensemble of patients remains a challenging task. Because they are established by use of image data corresponding a single patient, previously reported numerical anatomical models lack of the ability to accurately model inter- patient variations in anatomy. In certain applications, however, databases of high-quality volumetric images are available that can facilitate this task. In this work, a novel and tractable methodology for learning a SOM from a set of volumetric training images is developed. The proposed method is based upon geometric attribute distribution (GAD) models, which characterize the inter-structural centroid variations and the intra-structural shape variations of each individual anatomical structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations learned from training data. By use of the GAD models, random organ shapes and positions can be generated and integrated to form an anatomical phantom. The randomness in organ shape and position will reflect the variability of anatomy present in the training data. To demonstrate the methodology, a SOM corresponding to the pelvis of an adult male was computed and a corresponding ensemble of phantoms was created. Additionally, computer-simulated X-ray projection images corresponding to the phantoms were computed, from which tomographic images were reconstructed.

Learning-based stochastic object models for characterizing anatomical variations

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

2018-03-01

It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

MRMC analysis of agreement studies

NASA Astrophysics Data System (ADS)

Gallas, Brandon D.; Anam, Amrita; Chen, Weijie; Wunderlich, Adam; Zhang, Zhiwei

2016-03-01

The purpose of this work is to present and evaluate methods based on U-statistics to compare intra- or inter-reader agreement across different imaging modalities. We apply these methods to multi-reader multi-case (MRMC) studies. We measure reader-averaged agreement and estimate its variance accounting for the variability from readers and cases (an MRMC analysis). In our application, pathologists (readers) evaluate patient tissue mounted on glass slides (cases) in two ways. They evaluate the slides on a microscope (reference modality) and they evaluate digital scans of the slides on a computer display (new modality). In the current work, we consider concordance as the agreement measure, but many of the concepts outlined here apply to other agreement measures. Concordance is the probability that two readers rank two cases in the same order. Concordance can be estimated with a U-statistic and thus it has some nice properties: it is unbiased, asymptotically normal, and its variance is given by an explicit formula. Another property of a U-statistic is that it is symmetric in its inputs; it doesn't matter which reader is listed first or which case is listed first, the result is the same. Using this property and a few tricks while building the U-statistic kernel for concordance, we get a mathematically tractable problem and efficient software. Simulations show that our variance and covariance estimates are unbiased.

Transient probabilities for queues with applications to hospital waiting list management.

PubMed

Joy, Mark; Jones, Simon

2005-08-01

In this paper we study queuing systems within the NHS. Recently imposed government performance targets lead NHS executives to investigate and instigate alternative management strategies, thereby imposing structural changes on the queues. Under such circumstances, it is most unlikely that such systems are in equilibrium. It is crucial, in our opinion, to recognise this state of affairs in order to make a balanced assessment of the role of queue management in the modern NHS. From a mathematical perspective it should be emphasised that measures of the state of a queue based upon the assumption of statistical equilibrium (a pervasive methodology in the study of queues) are simply wrong in the above scenario. To base strategic decisions around such ideas is therefore highly questionable and it is one of the purposes of this paper to offer alternatives: we present some (recent) research whose results generate performance measures and measures of risk, for example, of waiting-times growing unacceptably large; we emphasise that these results concern the transient behaviour of the queueing model-there is no asssumption of statistical equilibrium. We also demonstrate that our results are computationally tractable.

Electric Field Fluctuations in Water

NASA Astrophysics Data System (ADS)

Thorpe, Dayton; Limmer, David; Chandler, David

2013-03-01

Charge transfer in solution, such as autoionization and ion pair dissociation in water, is governed by rare electric field fluctuations of the solvent. Knowing the statistics of such fluctuations can help explain the dynamics of these rare events. Trajectories short enough to be tractable by computer simulation are virtually certain not to sample the large fluctuations that promote rare events. Here, we employ importance sampling techniques with classical molecular dynamics simulations of liquid water to study statistics of electric field fluctuations far from their means. We find that the distributions of electric fields located on individual water molecules are not in general gaussian. Near the mean this non-gaussianity is due to the internal charge distribution of the water molecule. Further from the mean, however, there is a previously unreported Bjerrum-like defect that stabilizes certain large fluctuations out of equilibrium. As expected, differences in electric fields acting between molecules are gaussian to a remarkable degree. By studying these differences, though, we are able to determine what configurations result not only in large electric fields, but also in electric fields with long spatial correlations that may be needed to promote charge separation.

To cut or not to cut? Assessing the modular structure of brain networks.

PubMed

Chang, Yu-Teng; Pantazis, Dimitrios; Leahy, Richard M

2014-05-01

A wealth of methods has been developed to identify natural divisions of brain networks into groups or modules, with one of the most prominent being modularity. Compared with the popularity of methods to detect community structure, only a few methods exist to statistically control for spurious modules, relying almost exclusively on resampling techniques. It is well known that even random networks can exhibit high modularity because of incidental concentration of edges, even though they have no underlying organizational structure. Consequently, interpretation of community structure is confounded by the lack of principled and computationally tractable approaches to statistically control for spurious modules. In this paper we show that the modularity of random networks follows a transformed version of the Tracy-Widom distribution, providing for the first time a link between module detection and random matrix theory. We compute parametric formulas for the distribution of modularity for random networks as a function of network size and edge variance, and show that we can efficiently control for false positives in brain and other real-world networks. Copyright © 2014 Elsevier Inc. All rights reserved.

On the diffuse fraction of daily and monthly global radiation for the island of Cyprus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacovides, C.P.; Hadjioannou, L.; Pashiardis, S.

1996-06-01

Six years of hourly global and diffuse irradiation measurements on a horizontal surface performed at Athalassa, Cyprus, are used to establish a relationship between the daily diffuse fraction and the daily clearness index. Two types of correlations - yearly and seasonal - have been developed. These correlations, of first and third order in the clearness index are compared to the various correlations established by Collares-Pereira and Rabl (1979), Newland (1989), Erbs et al. (1982), Rao et al. (1984), Page (1961), Liu and Jordan (1960) and Lalas et al. (1987). The comparison has been performed in terms of the widely usedmore » statistical indicators (MBE) and (RMSE) errors; and additional statistical indicator, the t-statistic, combining the earlier indicators, is introduced. The results indicate that the proposed yearly correlation matches the earlier correlations quite closely and all correlations examined yield results that are statistically significant. For large K{sub t} > 0.60 values, most of the earlier correlations exhibit a slight tendency to systematically overestimate the diffuse fraction. This marginal disagreement between the earlier correlations and the proposed model is probably significantly affected by the clear sky conditions that prevail over Cyprus for most of the time as well as atmospheric humidity content. It is clear that the standard correlations examined in this analysis appear to be location-independent models for diffuse irradiation predictions, at least for the Cyprus case. 13 refs., 5 figs., 4 tabs.« less

Covalent Ligand Discovery against Druggable Hotspots Targeted by Anti-cancer Natural Products.

PubMed

Grossman, Elizabeth A; Ward, Carl C; Spradlin, Jessica N; Bateman, Leslie A; Huffman, Tucker R; Miyamoto, David K; Kleinman, Jordan I; Nomura, Daniel K

2017-11-16

Many natural products that show therapeutic activities are often difficult to synthesize or isolate and have unknown targets, hindering their development as drugs. Identifying druggable hotspots targeted by covalently acting anti-cancer natural products can enable pharmacological interrogation of these sites with more synthetically tractable compounds. Here, we used chemoproteomic platforms to discover that the anti-cancer natural product withaferin A targets C377 on the regulatory subunit PPP2R1A of the tumor-suppressor protein phosphatase 2A (PP2A) complex leading to activation of PP2A activity, inactivation of AKT, and impaired breast cancer cell proliferation. We developed a more synthetically tractable cysteine-reactive covalent ligand, JNS 1-40, that selectively targets C377 of PPP2R1A to impair breast cancer signaling, proliferation, and in vivo tumor growth. Our study highlights the utility of using chemoproteomics to map druggable hotspots targeted by complex natural products and subsequently interrogating these sites with more synthetically tractable covalent ligands for cancer therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parameterized Complexity Results for General Factors in Bipartite Graphs with an Application to Constraint Programming

NASA Astrophysics Data System (ADS)

Gutin, Gregory; Kim, Eun Jung; Soleimanfallah, Arezou; Szeider, Stefan; Yeo, Anders

The NP-hard general factor problem asks, given a graph and for each vertex a list of integers, whether the graph has a spanning subgraph where each vertex has a degree that belongs to its assigned list. The problem remains NP-hard even if the given graph is bipartite with partition U ⊎ V, and each vertex in U is assigned the list {1}; this subproblem appears in the context of constraint programming as the consistency problem for the extended global cardinality constraint. We show that this subproblem is fixed-parameter tractable when parameterized by the size of the second partite set V. More generally, we show that the general factor problem for bipartite graphs, parameterized by |V |, is fixed-parameter tractable as long as all vertices in U are assigned lists of length 1, but becomes W[1]-hard if vertices in U are assigned lists of length at most 2. We establish fixed-parameter tractability by reducing the problem instance to a bounded number of acyclic instances, each of which can be solved in polynomial time by dynamic programming.

Anatomy of Particle Diffusion

ERIC Educational Resources Information Center

Bringuier, E.

2009-01-01

The paper analyses particle diffusion from a thermodynamic standpoint. The main goal of the paper is to highlight the conceptual connection between particle diffusion, which belongs to non-equilibrium statistical physics, and mechanics, which deals with particle motion, at the level of third-year university courses. We start out from the fact…

Quantum jumps on Anderson attractors

NASA Astrophysics Data System (ADS)

Yusipov, I. I.; Laptyeva, T. V.; Ivanchenko, M. V.

2018-01-01

In a closed single-particle quantum system, spatial disorder induces Anderson localization of eigenstates and halts wave propagation. The phenomenon is vulnerable to interaction with environment and decoherence that is believed to restore normal diffusion. We demonstrate that for a class of experimentally feasible non-Hermitian dissipators, which admit signatures of localization in asymptotic states, quantum particle opts between diffusive and ballistic regimes, depending on the phase parameter of dissipators, with sticking about localization centers. In a diffusive regime, statistics of quantum jumps is non-Poissonian and has a power-law interval, a footprint of intermittent locking in Anderson modes. Ballistic propagation reflects dispersion of an ordered lattice and introduces the second timescale for jumps, resulting in non-nonmonotonous probability distribution. Hermitian dephasing dissipation makes localization features vanish, and Poissonian jump statistics along with normal diffusion are recovered.

Joint resonant CMB power spectrum and bispectrum estimation

NASA Astrophysics Data System (ADS)

Meerburg, P. Daniel; Münchmeyer, Moritz; Wandelt, Benjamin

2016-02-01

We develop the tools necessary to assess the statistical significance of resonant features in the CMB correlation functions, combining power spectrum and bispectrum measurements. This significance is typically addressed by running a large number of simulations to derive the probability density function (PDF) of the feature-amplitude in the Gaussian case. Although these simulations are tractable for the power spectrum, for the bispectrum they require significant computational resources. We show that, by assuming that the PDF is given by a multivariate Gaussian where the covariance is determined by the Fisher matrix of the sine and cosine terms, we can efficiently produce spectra that are statistically close to those derived from full simulations. By drawing a large number of spectra from this PDF, both for the power spectrum and the bispectrum, we can quickly determine the statistical significance of candidate signatures in the CMB, considering both single frequency and multifrequency estimators. We show that for resonance models, cosmology and foreground parameters have little influence on the estimated amplitude, which allows us to simplify the analysis considerably. A more precise likelihood treatment can then be applied to candidate signatures only. We also discuss a modal expansion approach for the power spectrum, aimed at quickly scanning through large families of oscillating models.

Statistical image reconstruction from correlated data with applications to PET

PubMed Central

Alessio, Adam; Sauer, Ken; Kinahan, Paul

2008-01-01

Most statistical reconstruction methods for emission tomography are designed for data modeled as conditionally independent Poisson variates. In reality, due to scanner detectors, electronics and data processing, correlations are introduced into the data resulting in dependent variates. In general, these correlations are ignored because they are difficult to measure and lead to computationally challenging statistical reconstruction algorithms. This work addresses the second concern, seeking to simplify the reconstruction of correlated data and provide a more precise image estimate than the conventional independent methods. In general, correlated variates have a large non-diagonal covariance matrix that is computationally challenging to use as a weighting term in a reconstruction algorithm. This work proposes two methods to simplify the use of a non-diagonal covariance matrix as the weighting term by (a) limiting the number of dimensions in which the correlations are modeled and (b) adopting flexible, yet computationally tractable, models for correlation structure. We apply and test these methods with simple simulated PET data and data processed with the Fourier rebinning algorithm which include the one-dimensional correlations in the axial direction and the two-dimensional correlations in the transaxial directions. The methods are incorporated into a penalized weighted least-squares 2D reconstruction and compared with a conventional maximum a posteriori approach. PMID:17921576

Tractable Chemical Models for CVD of Silicon and Carbon

NASA Technical Reports Server (NTRS)

Blanquet, E.; Gokoglu, S. A.

1993-01-01

Tractable chemical models are validated for the CVD of silicon and carbon. Dilute silane (SiH4) and methane (CH4) in hydrogen are chosen as gaseous precursors. The chemical mechanism for each systems Si and C is deliberately reduced to three reactions in the models: one in the gas phase and two at the surface. The axial-flow CVD reactor utilized in this study has well-characterized flow and thermal fields and provides variable deposition rates in the axial direction. Comparisons between the experimental and calculated deposition rates are made at different pressures and temperatures.

Catalytic conversion reactions in nanoporous systems with concentration-dependent selectivity: Statistical mechanical modeling

DOE PAGES

Garcia, Andres; Wang, Jing; Windus, Theresa L.; ...

2016-05-20

Statistical mechanical modeling is developed to describe a catalytic conversion reaction A → B c or B t with concentration-dependent selectivity of the products, B c or B t, where reaction occurs inside catalytic particles traversed by narrow linear nanopores. The associated restricted diffusive transport, which in the extreme case is described by single-file diffusion, naturally induces strong concentration gradients. Hence, by comparing kinetic Monte Carlo simulation results with analytic treatments, selectivity is shown to be impacted by strong spatial correlations induced by restricted diffusivity in the presence of reaction and also by a subtle clustering of reactants, A.

Retrospective correction of bias in diffusion tensor imaging arising from coil combination mode.

PubMed

Sakaie, Ken; Lowe, Mark

2017-04-01

To quantify and retrospectively correct for systematic differences in diffusion tensor imaging (DTI) measurements due to differences in coil combination mode. Multi-channel coils are now standard among MRI systems. There are several options for combining signal from multiple coils during image reconstruction, including sum-of-squares (SOS) and adaptive combine (AC). This contribution examines the bias between SOS- and AC-derived measures of tissue microstructure and a strategy for limiting that bias. Five healthy subjects were scanned under an institutional review board-approved protocol. Each set of raw image data was reconstructed twice-once with SOS and once with AC. The diffusion tensor was calculated from SOS- and AC-derived data by two algorithms-standard log-linear least squares and an approach that accounts for the impact of coil combination on signal statistics. Systematic differences between SOS and AC in terms of tissue microstructure (axial diffusivity, radial diffusivity, mean diffusivity and fractional anisotropy) were evaluated on a voxel-by-voxel basis. SOS-based tissue microstructure values are systematically lower than AC-based measures throughout the brain in each subject when using the standard tensor calculation method. The difference between SOS and AC can be virtually eliminated by taking into account the signal statistics associated with coil combination. The impact of coil combination mode on diffusion tensor-based measures of tissue microstructure is statistically significant but can be corrected retrospectively. The ability to do so is expected to facilitate pooling of data among imaging protocols. Copyright © 2016 Elsevier Inc. All rights reserved.

Zubarev's Nonequilibrium Statistical Operator Method in the Generalized Statistics of Multiparticle Systems

NASA Astrophysics Data System (ADS)

Glushak, P. A.; Markiv, B. B.; Tokarchuk, M. V.

2018-01-01

We present a generalization of Zubarev's nonequilibrium statistical operator method based on the principle of maximum Renyi entropy. In the framework of this approach, we obtain transport equations for the basic set of parameters of the reduced description of nonequilibrium processes in a classical system of interacting particles using Liouville equations with fractional derivatives. For a classical systems of particles in a medium with a fractal structure, we obtain a non-Markovian diffusion equation with fractional spatial derivatives. For a concrete model of the frequency dependence of a memory function, we obtain generalized Kettano-type diffusion equation with the spatial and temporal fractality taken into account. We present a generalization of nonequilibrium thermofield dynamics in Zubarev's nonequilibrium statistical operator method in the framework of Renyi statistics.

Landau-Zener extension of the Tavis-Cummings model: structure of the solution

NASA Astrophysics Data System (ADS)

Sun, Chen; Sinitsyn, Nikolai

We explore the recently discovered solution of the driven Tavis-Cummings model (DTCM). It describes interaction of arbitrary number of two-level systems with a bosonic mode that has linearly time-dependent frequency. We derive compact and tractable expressions for transition probabilities in terms of the well known special functions. In the new form, our formulas are suitable for fast numerical calculations and analytical approximations. As an application, we obtain the semiclassical limit of the exact solution and compare it to prior approximations. We also reveal connection between DTCM and q-deformed binomial statistics. Under the auspices of the National Nuclear Security Administration of the U.S. Department of Energy at Los Alamos National Laboratory under Contract No. DE-AC52-06NA25396. Authors also thank the support from the LDRD program at LANL.

Force-free electrodynamics in dynamical curved spacetimes

NASA Astrophysics Data System (ADS)

McWilliams, Sean

2015-04-01

We present results on our study of force-free electrodynamics in curved spacetimes. Specifically, we present several improvements to what has become the established set of evolution equations, and we apply these to study the nonlinear stability of analytically known force-free solutions for the first time. We implement our method in a new pseudo-spectral code built on top of the SpEC code for evolving dynamic spacetimes. Finally, we revisit these known solutions and attempt to clarify some interesting properties that render them analytically tractable. Finally, we preview some new work that similarly revisits the established approach to solving another problem in numerical relativity: the post-merger recoil from asymmetric gravitational-wave emission. These new results may have significant implications for the parameter dependence of recoils, and consequently on the statistical expectations for recoil velocities of merged systems.

Data mining of molecular dynamics data reveals Li diffusion characteristics in garnet Li7La3Zr2O12

PubMed Central

Chen, Chi; Lu, Ziheng; Ciucci, Francesco

2017-01-01

Understanding Li diffusion in solid conductors is essential for the next generation Li batteries. Here we show that density-based clustering of the trajectories computed using molecular dynamics simulations helps elucidate the Li diffusion mechanism within the Li7La3Zr2O12 (LLZO) crystal lattice. This unsupervised learning method recognizes lattice sites, is able to give the site type, and can identify Li hopping events. Results show that, while the cubic LLZO has a much higher hopping rate compared to its tetragonal counterpart, most of the Li hops in the cubic LLZO do not contribute to the diffusivity due to the dominance of back-and-forth type jumps. The hopping analysis and local Li configuration statistics give evidence that Li diffusivity in cubic LLZO is limited by the low vacancy concentration. The hopping statistics also shows uncorrelated Poisson-like diffusion for Li in the cubic LLZO, and correlated diffusion for Li in the tetragonal LLZO in the temporal scale. Further analysis of the spatio-temporal correlation using site-to-site mutual information confirms the weak site dependence of Li diffusion in the cubic LLZO as the origin for the uncorrelated diffusion. This work puts forward a perspective on combining machine learning and information theory to interpret results of molecular dynamics simulations. PMID:28094317

Data mining of molecular dynamics data reveals Li diffusion characteristics in garnet Li7La3Zr2O12

NASA Astrophysics Data System (ADS)

Chen, Chi; Lu, Ziheng; Ciucci, Francesco

2017-01-01

Understanding Li diffusion in solid conductors is essential for the next generation Li batteries. Here we show that density-based clustering of the trajectories computed using molecular dynamics simulations helps elucidate the Li diffusion mechanism within the Li7La3Zr2O12 (LLZO) crystal lattice. This unsupervised learning method recognizes lattice sites, is able to give the site type, and can identify Li hopping events. Results show that, while the cubic LLZO has a much higher hopping rate compared to its tetragonal counterpart, most of the Li hops in the cubic LLZO do not contribute to the diffusivity due to the dominance of back-and-forth type jumps. The hopping analysis and local Li configuration statistics give evidence that Li diffusivity in cubic LLZO is limited by the low vacancy concentration. The hopping statistics also shows uncorrelated Poisson-like diffusion for Li in the cubic LLZO, and correlated diffusion for Li in the tetragonal LLZO in the temporal scale. Further analysis of the spatio-temporal correlation using site-to-site mutual information confirms the weak site dependence of Li diffusion in the cubic LLZO as the origin for the uncorrelated diffusion. This work puts forward a perspective on combining machine learning and information theory to interpret results of molecular dynamics simulations.

The precise time-dependent solution of the Fokker–Planck equation with anomalous diffusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Ran; Du, Jiulin, E-mail: jiulindu@aliyun.com

2015-08-15

We study the time behavior of the Fokker–Planck equation in Zwanzig’s rule (the backward-Ito’s rule) based on the Langevin equation of Brownian motion with an anomalous diffusion in a complex medium. The diffusion coefficient is a function in momentum space and follows a generalized fluctuation–dissipation relation. We obtain the precise time-dependent analytical solution of the Fokker–Planck equation and at long time the solution approaches to a stationary power-law distribution in nonextensive statistics. As a test, numerically we have demonstrated the accuracy and validity of the time-dependent solution. - Highlights: • The precise time-dependent solution of the Fokker–Planck equation with anomalousmore » diffusion is found. • The anomalous diffusion satisfies a generalized fluctuation–dissipation relation. • At long time the time-dependent solution approaches to a power-law distribution in nonextensive statistics. • Numerically we have demonstrated the accuracy and validity of the time-dependent solution.« less

Single particle tracking with sterol modulation reveals the cholesterol-mediated diffusion properties of integrin receptors.

PubMed

Arora, Neha; Syed, Aleem; Sander, Suzanne; Smith, Emily A

2014-10-07

A combination of sterol modulation with cyclodextrins plus fluorescence microscopy revealed a biophysical mechanism behind cholesterol's influence on the diffusion of a ubiquitous class of receptors called integrins. The heterogeneous diffusion of integrins bound to ligand-coated quantum dots was measured using single particle tracking (SPT), and the ensemble changes in integrin diffusion were measured by fluorescence recovery after photobleaching (FRAP). A 25 ± 1% reduction of membrane cholesterol resulted in three significant changes to the diffusion of ligand-bound αPS2CβPS integrins as measured by SPT. There was a 23% increase in ligand-bound mobile integrins; there was a statistically significant increase in the average diffusion coefficient inside zones of confined diffusion, and histograms of confined integrin trajectories showed an increased frequency in the range of 0.1-1 μm(2) s(-1) and a decreased frequency in the 0.001-0.1 μm(2) s(-1) range. No statistical change was measured in the duration of confinement nor the size of confined zones. Restoring the cholesterol-depleted cells with exogenous cholesterol or exogenous epicholesterol resulted in similar diffusion properties. Epicholesterol differs from cholesterol in the orientation of a single hydroxyl group. The ability of epicholesterol to substitute for cholesterol suggests a biophysical mechanism for cholesterol's effect on integrin diffusion. Influences of bilayer thickness, viscosity and organization are discussed as possible explanations for the measured changes in integrin diffusion when the membrane cholesterol concentration is reduced.

Weakly anomalous diffusion with non-Gaussian propagators

NASA Astrophysics Data System (ADS)

Cressoni, J. C.; Viswanathan, G. M.; Ferreira, A. S.; da Silva, M. A. A.

2012-08-01

A poorly understood phenomenon seen in complex systems is diffusion characterized by Hurst exponent H≈1/2 but with non-Gaussian statistics. Motivated by such empirical findings, we report an exact analytical solution for a non-Markovian random walk model that gives rise to weakly anomalous diffusion with H=1/2 but with a non-Gaussian propagator.

Lognormal-like statistics of a stochastic squeeze process

NASA Astrophysics Data System (ADS)

Shapira, Dekel; Cohen, Doron

2017-10-01

We analyze the full statistics of a stochastic squeeze process. The model's two parameters are the bare stretching rate w and the angular diffusion coefficient D . We carry out an exact analysis to determine the drift and the diffusion coefficient of log(r ) , where r is the radial coordinate. The results go beyond the heuristic lognormal description that is implied by the central limit theorem. Contrary to the common "quantum Zeno" approximation, the radial diffusion is not simply Dr=(1 /8 ) w2/D but has a nonmonotonic dependence on w /D . Furthermore, the calculation of the radial moments is dominated by the far non-Gaussian tails of the log(r ) distribution.

Efficiency of Adaptive Temperature-Based Replica Exchange for Sampling Large-Scale Protein Conformational Transitions.

PubMed

Zhang, Weihong; Chen, Jianhan

2013-06-11

Temperature-based replica exchange (RE) is now considered a principal technique for enhanced sampling of protein conformations. It is also recognized that existence of sharp cooperative transitions (such as protein folding/unfolding) can lead to temperature exchange bottlenecks and significantly reduce the sampling efficiency. Here, we revisit two adaptive temperature-based RE protocols, namely, exchange equalization (EE) and current maximization (CM), that were previously examined using atomistic simulations (Lee and Olson, J. Chem. Physics2011, 134, 24111). Both protocols aim to overcome exchange bottlenecks by adaptively adjusting the simulation temperatures, either to achieve uniform exchange rates (in EE) or to maximize temperature diffusion (CM). By designing a realistic yet computationally tractable coarse-grained protein model, one can sample many reversible folding/unfolding transitions using conventional constant temperature molecular dynamics (MD), standard REMD, EE-REMD, and CM-REMD. This allows rigorous evaluation of the sampling efficiency, by directly comparing the rates of folding/unfolding transitions and convergence of various thermodynamic properties of interest. The results demonstrate that both EE and CM can indeed enhance temperature diffusion compared to standard RE, by ∼3- and over 10-fold, respectively. Surprisingly, the rates of reversible folding/unfolding transitions are similar in all three RE protocols. The convergence rates of several key thermodynamic properties, including the folding stability and various 1D and 2D free energy surfaces, are also similar. Therefore, the efficiency of RE protocols does not appear to be limited by temperature diffusion, but by the inherent rates of spontaneous large-scale conformational rearrangements. This is particularly true considering that virtually all RE simulations of proteins in practice involve exchange attempt frequencies (∼ps(-1)) that are several orders of magnitude faster than the slowest protein motions (∼μs(-1)). Our results also suggest that the efficiency of RE will not likely be improved by other protocols that aim to accelerate exchange or temperature diffusion. Instead, protocols with some types of guided tempering will likely be necessary to drive faster large-scale conformational transitions.

Statistics of multiply scattered broadband terahertz pulses.

PubMed

Pearce, Jeremy; Jian, Zhongping; Mittleman, Daniel M

2003-07-25

We describe the first measurements of the diffusion of broadband single-cycle optical pulses through a highly scattering medium. Using terahertz time-domain spectroscopy, we measure the electric field of a multiply scattered wave with a time resolution shorter than one optical cycle. This time-domain measurement provides information on the statistics of both the amplitude and phase distributions of the diffusive wave. We develop a theoretical description, suitable for broadband radiation, which adequately describes the experimental results.

Effects of spin transition on diffusion of Fe2+ in ferropericlase in Earth's lower mantle

NASA Astrophysics Data System (ADS)

Saha, Saumitra; Bengtson, Amelia; Crispin, Katherine L.; van Orman, James A.; Morgan, Dane

2011-11-01

Knowledge of Fe composition in lower-mantle minerals (primarily perovskite and ferropericlase) is essential to a complete understanding of the Earth's interior. Fe cation diffusion potentially controls many aspects of the distribution of Fe in the Earth's lower mantle, including mixing of chemical heterogeneities, element partitioning, and the extent of core-mantle communications. Fe in ferropericlase has been shown to undergo a spin transition starting at about 40 GPa and exists in a mixture of high-spin and low-spin states over a wide range of pressures. Present experimental data on Fe transport in ferropericlase is limited to pressures below 35 GPa and provides little information on the pressure dependence of the activation volume and none on the impact of the spin transition on diffusion. Therefore, known experimental data on Fe diffusion cannot be reliably extrapolated to predict diffusion throughout the lower mantle. Here, first-principles and statistical modeling are combined to predict diffusion of Fe in ferropericlase over the entire lower mantle, including the effects of the Fe spin transition. A thorough statistical thermodynamic treatment is given to fully incorporate the coexistence of high- and low-spin Fe in the model of overall Fe diffusion in the lower mantle. Pure low-spin Fe diffuses approximately 104 times slower than high-spin Fe in ferropericlase but Fe diffusion of the mixed-spin state is only about 10 times slower than that of high-spin Fe. The predicted Fe diffusivities demonstrate that ferropericlase is unlikely to be rate limiting in transporting Fe in deep earth since much slower Fe diffusion in perovskite is predicted.

Ballistic and diffusive dynamics in a two-dimensional ideal gas of macroscopic chaotic Faraday waves.

PubMed

Welch, Kyle J; Hastings-Hauss, Isaac; Parthasarathy, Raghuveer; Corwin, Eric I

2014-04-01

We have constructed a macroscopic driven system of chaotic Faraday waves whose statistical mechanics, we find, are surprisingly simple, mimicking those of a thermal gas. We use real-time tracking of a single floating probe, energy equipartition, and the Stokes-Einstein relation to define and measure a pseudotemperature and diffusion constant and then self-consistently determine a coefficient of viscous friction for a test particle in this pseudothermal gas. Because of its simplicity, this system can serve as a model for direct experimental investigation of nonequilibrium statistical mechanics, much as the ideal gas epitomizes equilibrium statistical mechanics.

Cox process representation and inference for stochastic reaction-diffusion processes

NASA Astrophysics Data System (ADS)

Schnoerr, David; Grima, Ramon; Sanguinetti, Guido

2016-05-01

Complex behaviour in many systems arises from the stochastic interactions of spatially distributed particles or agents. Stochastic reaction-diffusion processes are widely used to model such behaviour in disciplines ranging from biology to the social sciences, yet they are notoriously difficult to simulate and calibrate to observational data. Here we use ideas from statistical physics and machine learning to provide a solution to the inverse problem of learning a stochastic reaction-diffusion process from data. Our solution relies on a non-trivial connection between stochastic reaction-diffusion processes and spatio-temporal Cox processes, a well-studied class of models from computational statistics. This connection leads to an efficient and flexible algorithm for parameter inference and model selection. Our approach shows excellent accuracy on numeric and real data examples from systems biology and epidemiology. Our work provides both insights into spatio-temporal stochastic systems, and a practical solution to a long-standing problem in computational modelling.

Statistical evaluation of manual segmentation of a diffuse low-grade glioma MRI dataset.

PubMed

Ben Abdallah, Meriem; Blonski, Marie; Wantz-Mezieres, Sophie; Gaudeau, Yann; Taillandier, Luc; Moureaux, Jean-Marie

2016-08-01

Software-based manual segmentation is critical to the supervision of diffuse low-grade glioma patients and to the optimal treatment's choice. However, manual segmentation being time-consuming, it is difficult to include it in the clinical routine. An alternative to circumvent the time cost of manual segmentation could be to share the task among different practitioners, providing it can be reproduced. The goal of our work is to assess diffuse low-grade gliomas' manual segmentation's reproducibility on MRI scans, with regard to practitioners, their experience and field of expertise. A panel of 13 experts manually segmented 12 diffuse low-grade glioma clinical MRI datasets using the OSIRIX software. A statistical analysis gave promising results, as the practitioner factor, the medical specialty and the years of experience seem to have no significant impact on the average values of the tumor volume variable.

Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

NASA Astrophysics Data System (ADS)

Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

2016-03-01

Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

Photospheric Magnetic Diffusion by Measuring Moments of Active Regions

NASA Astrophysics Data System (ADS)

Engell, Alexander; Longcope, D.

2013-07-01

Photospheric magnetic surface diffusion is an important constraint for the solar dynamo. The HMI Active Region Patches (HARPs) program automatically identify all magnetic regions above a certain flux. In our study we measure the moments of ARs that are no longer actively emerging and can thereby give us good statistical constraints on photospheric diffusion. We also present the diffusion properties as a function of latitude, flux density, and single polarity (leading or following) within each HARP.

Structural differences in interictal migraine attack after epilepsy: A diffusion tensor imaging analysis.

PubMed

Huang, Qi; Lv, Xin; He, Yushuang; Wei, Xing; Ma, Meigang; Liao, Yuhan; Qin, Chao; Wu, Yuan

2017-12-01

Patients with epilepsy (PWE) are more likely to suffer from migraine attack, and aberrant white matter (WM) organization may be the mechanism underlying this phenomenon. This study aimed to use diffusion tensor imaging (DTI) technique to quantify WM structural differences in PWE with interictal migraine. Diffusion tensor imaging data were acquired in 13 PWE with migraine and 12 PWE without migraine. Diffusion metrics were analyzed using tract-atlas-based spatial statistics analysis. Atlas-based and tract-based spatial statistical analyses were conducted for robustness analysis. Correlation was explored between altered DTI metrics and clinical parameters. The main results are as follows: (i) Axonal damage plays a key role in PWE with interictal migraine. (ii) Significant diffusing alterations included higher fractional anisotropy (FA) in the fornix, higher mean diffusivity (MD) in the middle cerebellar peduncle (CP), left superior CP, and right uncinate fasciculus, and higher axial diffusivity (AD) in the middle CP and right medial lemniscus. (iii) Diffusion tensor imaging metrics has the tendency of correlation with seizure/migraine type and duration. Results indicate that characteristic structural impairments exist in PWE with interictal migraine. Epilepsy may contribute to migraine by altering WMs in the brain stem. White matter tracts in the fornix and right uncinate fasciculus also mediate migraine after epilepsy. This finding may improve our understanding of the pathological mechanisms underlying migraine attack after epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.

Alignment dynamics of diffusive scalar gradient in a two-dimensional model flow

NASA Astrophysics Data System (ADS)

Gonzalez, M.

2018-04-01

The Lagrangian two-dimensional approach of scalar gradient kinematics is revisited accounting for molecular diffusion. Numerical simulations are performed in an analytic, parameterized model flow, which enables considering different regimes of scalar gradient dynamics. Attention is especially focused on the influence of molecular diffusion on Lagrangian statistical orientations and on the dynamics of scalar gradient alignment.

Bayesian approach to non-Gaussian field statistics for diffusive broadband terahertz pulses.

PubMed

Pearce, Jeremy; Jian, Zhongping; Mittleman, Daniel M

2005-11-01

We develop a closed-form expression for the probability distribution function for the field components of a diffusive broadband wave propagating through a random medium. We consider each spectral component to provide an individual observation of a random variable, the configurationally averaged spectral intensity. Since the intensity determines the variance of the field distribution at each frequency, this random variable serves as the Bayesian prior that determines the form of the non-Gaussian field statistics. This model agrees well with experimental results.

Diffusion Properties and 3D Architecture of Human Lower Leg Muscles Assessed with Ultra-High-Field-Strength Diffusion-Tensor MR Imaging and Tractography: Reproducibility and Sensitivity to Sex Difference and Intramuscular Variability.

PubMed

Fouré, Alexandre; Ogier, Augustin C; Le Troter, Arnaud; Vilmen, Christophe; Feiweier, Thorsten; Guye, Maxime; Gondin, Julien; Besson, Pierre; Bendahan, David

2018-05-01

Purpose To demonstrate the reproducibility of the diffusion properties and three-dimensional structural organization measurements of the lower leg muscles by using diffusion-tensor imaging (DTI) assessed with ultra-high-field-strength (7.0-T) magnetic resonance (MR) imaging and tractography of skeletal muscle fibers. On the basis of robust statistical mapping analyses, this study also aimed at determining the sensitivity of the measurements to sex difference and intramuscular variability. Materials and Methods All examinations were performed with ethical review board approval; written informed consent was obtained from all volunteers. Reproducibility of diffusion tensor indexes assessment including eigenvalues, mean diffusivity, and fractional anisotropy (FA) as well as muscle volume and architecture (ie, fiber length and pennation angle) were characterized in lower leg muscles (n = 8). Intramuscular variability and sex differences were characterized in young healthy men and women (n = 10 in each group). Student t test, statistical parametric mapping, correlation coefficients (Spearman rho and Pearson product-moment) and coefficient of variation (CV) were used for statistical data analysis. Results High reproducibility of measurements (mean CV ± standard deviation, 4.6% ± 3.8) was determined in diffusion properties and architectural parameters. Significant sex differences were detected in FA (4.2% in women for the entire lower leg; P = .001) and muscle volume (21.7% in men for the entire lower leg; P = .008), whereas architecture parameters were almost identical across sex. Additional differences were found independently of sex in diffusion properties and architecture along several muscles of the lower leg. Conclusion The high-spatial-resolution DTI assessed with 7.0-T MR imaging allows a reproducible assessment of structural organization of superficial and deep muscles, giving indirect information on muscle function. © RSNA, 2018 Online supplemental material is available for this article.

Traveling front solutions to directed diffusion-limited aggregation, digital search trees, and the Lempel-Ziv data compression algorithm.

PubMed

Majumdar, Satya N

2003-08-01

We use the traveling front approach to derive exact asymptotic results for the statistics of the number of particles in a class of directed diffusion-limited aggregation models on a Cayley tree. We point out that some aspects of these models are closely connected to two different problems in computer science, namely, the digital search tree problem in data structures and the Lempel-Ziv algorithm for data compression. The statistics of the number of particles studied here is related to the statistics of height in digital search trees which, in turn, is related to the statistics of the length of the longest word formed by the Lempel-Ziv algorithm. Implications of our results to these computer science problems are pointed out.

Traveling front solutions to directed diffusion-limited aggregation, digital search trees, and the Lempel-Ziv data compression algorithm

NASA Astrophysics Data System (ADS)

Majumdar, Satya N.

2003-08-01

We use the traveling front approach to derive exact asymptotic results for the statistics of the number of particles in a class of directed diffusion-limited aggregation models on a Cayley tree. We point out that some aspects of these models are closely connected to two different problems in computer science, namely, the digital search tree problem in data structures and the Lempel-Ziv algorithm for data compression. The statistics of the number of particles studied here is related to the statistics of height in digital search trees which, in turn, is related to the statistics of the length of the longest word formed by the Lempel-Ziv algorithm. Implications of our results to these computer science problems are pointed out.

Stochastic Modeling and Generation of Partially Polarized or Partially Coherent Electromagnetic Waves

NASA Technical Reports Server (NTRS)

Davis, Brynmor; Kim, Edward; Piepmeier, Jeffrey; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To increase instrument understanding and functionality a model of the signals these instruments measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real-world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Temporal and spectral correlation measures provide a statistical description of the physical properties of coherence and polarization-state. From this relationship the model is mathematically defined. The model is shown to be unique for any set of physical parameters. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given and computer simulation results are presented. The signals are constructed using the output of a multi-input multi-output linear filter system, driven with white noise.

Getting more from accuracy and response time data: methods for fitting the linear ballistic accumulator.

PubMed

Donkin, Chris; Averell, Lee; Brown, Scott; Heathcote, Andrew

2009-11-01

Cognitive models of the decision process provide greater insight into response time and accuracy than do standard ANOVA techniques. However, such models can be mathematically and computationally difficult to apply. We provide instructions and computer code for three methods for estimating the parameters of the linear ballistic accumulator (LBA), a new and computationally tractable model of decisions between two or more choices. These methods-a Microsoft Excel worksheet, scripts for the statistical program R, and code for implementation of the LBA into the Bayesian sampling software WinBUGS-vary in their flexibility and user accessibility. We also provide scripts in R that produce a graphical summary of the data and model predictions. In a simulation study, we explored the effect of sample size on parameter recovery for each method. The materials discussed in this article may be downloaded as a supplement from http://brm.psychonomic-journals.org/content/supplemental.

Spatiotemporal Bayesian analysis of Lyme disease in New York state, 1990-2000.

PubMed

Chen, Haiyan; Stratton, Howard H; Caraco, Thomas B; White, Dennis J

2006-07-01

Mapping ordinarily increases our understanding of nontrivial spatial and temporal heterogeneities in disease rates. However, the large number of parameters required by the corresponding statistical models often complicates detailed analysis. This study investigates the feasibility of a fully Bayesian hierarchical regression approach to the problem and identifies how it outperforms two more popular methods: crude rate estimates (CRE) and empirical Bayes standardization (EBS). In particular, we apply a fully Bayesian approach to the spatiotemporal analysis of Lyme disease incidence in New York state for the period 1990-2000. These results are compared with those obtained by CRE and EBS in Chen et al. (2005). We show that the fully Bayesian regression model not only gives more reliable estimates of disease rates than the other two approaches but also allows for tractable models that can accommodate more numerous sources of variation and unknown parameters.

First stage identification of syntactic elements in an extra-terrestrial signal

NASA Astrophysics Data System (ADS)

Elliott, John

2011-02-01

By investigating the generic attributes of a representative set of terrestrial languages at varying levels of abstraction, it is our endeavour to try and isolate elements of the signal universe, which are computationally tractable for its detection and structural decipherment. Ultimately, our aim is to contribute in some way to the understanding of what 'languageness' actually is. This paper describes algorithms and software developed to characterise and detect generic intelligent language-like features in an input signal, using natural language learning techniques: looking for characteristic statistical "language-signatures" in test corpora. As a first step towards such species-independent language-detection, we present a suite of programs to analyse digital representations of a range of data, and use the results to extrapolate whether or not there are language-like structures which distinguish this data from other sources, such as music, images, and white noise.

Multimodal Image Analysis in Alzheimer’s Disease via Statistical Modelling of Non-local Intensity Correlations

NASA Astrophysics Data System (ADS)

Lorenzi, Marco; Simpson, Ivor J.; Mendelson, Alex F.; Vos, Sjoerd B.; Cardoso, M. Jorge; Modat, Marc; Schott, Jonathan M.; Ourselin, Sebastien

2016-04-01

The joint analysis of brain atrophy measured with magnetic resonance imaging (MRI) and hypometabolism measured with positron emission tomography with fluorodeoxyglucose (FDG-PET) is of primary importance in developing models of pathological changes in Alzheimer’s disease (AD). Most of the current multimodal analyses in AD assume a local (spatially overlapping) relationship between MR and FDG-PET intensities. However, it is well known that atrophy and hypometabolism are prominent in different anatomical areas. The aim of this work is to describe the relationship between atrophy and hypometabolism by means of a data-driven statistical model of non-overlapping intensity correlations. For this purpose, FDG-PET and MRI signals are jointly analyzed through a computationally tractable formulation of partial least squares regression (PLSR). The PLSR model is estimated and validated on a large clinical cohort of 1049 individuals from the ADNI dataset. Results show that the proposed non-local analysis outperforms classical local approaches in terms of predictive accuracy while providing a plausible description of disease dynamics: early AD is characterised by non-overlapping temporal atrophy and temporo-parietal hypometabolism, while the later disease stages show overlapping brain atrophy and hypometabolism spread in temporal, parietal and cortical areas.

Classifying and Analyzing 3d Cell Motion in Jammed Microgels

NASA Astrophysics Data System (ADS)

Bhattacharjee, Tapomoy; Sawyer, W. Gregory; Angelini, Thomas

Soft granular polyelectrolyte microgels swell in liquid cell growth media to form a continuous elastic solid that can easily transition between solid to fluid state under a low shear stress. Such Liquid-like solids (LLS) have recently been used to create 3D cellular constructs as well as to support, culture and harvest cells in 3D. Current understanding of cell migration mechanics in 3D was established from experiments performed in natural and synthetic polymer networks. Spatial variation in network structure and the transience of degradable gels limit their usefulness in quantitative cell mechanics studies. By contrast, LLS growth media approximates a homogeneous continuum, enabling tractable cell mechanics measurements to be performed in 3D. Here, we introduce a process to understand and classify cytotoxic T cell motion in 3D by studying cellular motility in LLS media. General classification of T cell motion can be achieved with a very traditional statistical approach: the cell's mean squared displacement (MSD) as a function of delay time. We will also use Langevin approaches combined with the constitutive equations of the LLS medium to predict the statistics of T cell motion. National Science Foundation under Grant No. DMR-1352043.

Hypothesis testing of a change point during cognitive decline among Alzheimer's disease patients.

PubMed

Ji, Ming; Xiong, Chengjie; Grundman, Michael

2003-10-01

In this paper, we present a statistical hypothesis test for detecting a change point over the course of cognitive decline among Alzheimer's disease patients. The model under the null hypothesis assumes a constant rate of cognitive decline over time and the model under the alternative hypothesis is a general bilinear model with an unknown change point. When the change point is unknown, however, the null distribution of the test statistics is not analytically tractable and has to be simulated by parametric bootstrap. When the alternative hypothesis that a change point exists is accepted, we propose an estimate of its location based on the Akaike's Information Criterion. We applied our method to a data set from the Neuropsychological Database Initiative by implementing our hypothesis testing method to analyze Mini Mental Status Exam scores based on a random-slope and random-intercept model with a bilinear fixed effect. Our result shows that despite large amount of missing data, accelerated decline did occur for MMSE among AD patients. Our finding supports the clinical belief of the existence of a change point during cognitive decline among AD patients and suggests the use of change point models for the longitudinal modeling of cognitive decline in AD research.

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.

2003-01-01

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

Scale-Dependent Fracture-Matrix Interactions And Their Impact on Radionuclide Transport - Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Detwiler, Russell

Matrix diffusion and adsorption within a rock matrix are widely regarded as important mechanisms for retarding the transport of radionuclides and other solutes in fractured rock (e.g., Neretnieks, 1980; Tang et al., 1981; Maloszewski and Zuber, 1985; Novakowski and Lapcevic, 1994; Jardine et al., 1999; Zhou and Xie, 2003; Reimus et al., 2003a,b). When remediation options are being evaluated for old sources of contamination, where a large fraction of contaminants reside within the rock matrix, slow diffusion out of the matrix greatly increases the difficulty and timeframe of remediation. Estimating the rates of solute exchange between fractures and the adjacentmore » rock matrix is a critical factor in quantifying immobilization and/or remobilization of DOE-relevant contaminants within the subsurface. In principle, the most rigorous approach to modeling solute transport with fracture-matrix interaction would be based on local-scale coupled advection-diffusion/dispersion equations for the rock matrix and in discrete fractures that comprise the fracture network (Discrete Fracture Network and Matrix approach, hereinafter referred to as DFNM approach), fully resolving aperture variability in fractures and matrix property heterogeneity. However, such approaches are computationally demanding, and thus, many predictive models rely upon simplified models. These models typically idealize fracture rock masses as a single fracture or system of parallel fractures interacting with slabs of porous matrix or as a mobile-immobile or multi-rate mass transfer system. These idealizations provide tractable approaches for interpreting tracer tests and predicting contaminant mobility, but rely upon a fitted effective matrix diffusivity or mass-transfer coefficients. However, because these fitted parameters are based upon simplified conceptual models, their effectiveness at predicting long-term transport processes remains uncertain. Evidence of scale dependence of effective matrix diffusion coefficients obtained from tracer tests highlights this point and suggests that the underlying mechanisms and relationship between rock and fracture properties are not fully understood in large complex fracture networks. In this project, we developed a high-resolution DFN model of solute transport in fracture networks to explore and quantify the mechanisms that control transport in complex fracture networks and how these may give rise to observed scale-dependent matrix diffusion coefficients. Results demonstrate that small scale heterogeneity in the flow field caused by local aperture variability within individual fractures can lead to long-tailed breakthrough curves indicative of matrix diffusion, even in the absence of interactions with the fracture matrix. Furthermore, the temporal and spatial scale dependence of these processes highlights the inability of short-term tracer tests to estimate transport parameters that will control long-term fate and transport of contaminants in fractured aquifers.« less

Assessing the inherent uncertainty of one-dimensional diffusions

NASA Astrophysics Data System (ADS)

Eliazar, Iddo; Cohen, Morrel H.

2013-01-01

In this paper we assess the inherent uncertainty of one-dimensional diffusion processes via a stochasticity classification which provides an à la Mandelbrot categorization into five states of uncertainty: infra-mild, mild, borderline, wild, and ultra-wild. Two settings are considered. (i) Stopped diffusions: the diffusion initiates from a high level and is stopped once it first reaches a low level; in this setting we analyze the inherent uncertainty of the diffusion's maximal exceedance above its initial high level. (ii) Stationary diffusions: the diffusion is in dynamical statistical equilibrium; in this setting we analyze the inherent uncertainty of the diffusion's equilibrium level. In both settings general closed-form analytic results are established, and their application is exemplified by stock prices in the stopped-diffusions setting, and by interest rates in the stationary-diffusions setting. These results provide a highly implementable decision-making tool for the classification of uncertainty in the context of one-dimensional diffusions.

Modeling radiation belt electron dynamics during GEM challenge intervals with the DREAM3D diffusion model

NASA Astrophysics Data System (ADS)

Tu, Weichao; Cunningham, G. S.; Chen, Y.; Henderson, M. G.; Camporeale, E.; Reeves, G. D.

2013-10-01

a response to the Geospace Environment Modeling (GEM) "Global Radiation Belt Modeling Challenge," a 3D diffusion model is used to simulate the radiation belt electron dynamics during two intervals of the Combined Release and Radiation Effects Satellite (CRRES) mission, 15 August to 15 October 1990 and 1 February to 31 July 1991. The 3D diffusion model, developed as part of the Dynamic Radiation Environment Assimilation Model (DREAM) project, includes radial, pitch angle, and momentum diffusion and mixed pitch angle-momentum diffusion, which are driven by dynamic wave databases from the statistical CRRES wave data, including plasmaspheric hiss, lower-band, and upper-band chorus. By comparing the DREAM3D model outputs to the CRRES electron phase space density (PSD) data, we find that, with a data-driven boundary condition at Lmax = 5.5, the electron enhancements can generally be explained by radial diffusion, though additional local heating from chorus waves is required. Because the PSD reductions are included in the boundary condition at Lmax = 5.5, our model captures the fast electron dropouts over a large L range, producing better model performance compared to previous published results. Plasmaspheric hiss produces electron losses inside the plasmasphere, but the model still sometimes overestimates the PSD there. Test simulations using reduced radial diffusion coefficients or increased pitch angle diffusion coefficients inside the plasmasphere suggest that better wave models and more realistic radial diffusion coefficients, both inside and outside the plasmasphere, are needed to improve the model performance. Statistically, the results show that, with the data-driven outer boundary condition, including radial diffusion and plasmaspheric hiss is sufficient to model the electrons during geomagnetically quiet times, but to best capture the radiation belt variations during active times, pitch angle and momentum diffusion from chorus waves are required.

Characterization of diffuse orbital mass using Apparent diffusion coefficient in 3-tesla MRI.

PubMed

ElKhamary, Sahar M; Galindo-Ferreiro, Alicia; AlGhafri, Laila; Khandekar, Rajiv; Schellini, Silvana Artioli

2018-01-01

To evaluate if the apparent diffusion coefficient (ADC) value in diffusion-weighted magnetic resonance imaging (DW-MRI) improves the diagnostic accuracy of diffuse orbital masses. ADC DW-MRI was used to evaluate cases of diffuse orbital masses at our institution from 2000 to 2015. Lesions were grouped according to histopathologic diagnosis as, benign, pre-malignant and malignant. Lymphoproliferative lesions were further subgrouped as lymphoma or other lymphoproliferative lesions. The validity of the ADC value for the diffuse orbital mass was compared between groups. The area under curve (AUC) was also calculated. Thirty-nine cases of diffuse orbital masses were evaluated. The median ADC was 0.58 (25% quartile 0.48; minimum: 0.45; maximum: 1.72 × 10 (-3) ) for the malignant tumors and 1.19 (25% quartile 0.7; minimum: 0.5; maximum: 1.95 × 10 (-3)  mm (2)  s (-1) ) for benign lesions. This difference in ADC between lesions was statistically significant (Mann Whitney U test P < 0.001). The median ADC was 0.51 (25% quartile 0.48) for lymphomas and 0.9 (25% quartile 0.7) for other lymphoproliferative lesions. This difference in ADC was statistically significant (Mann Whitney U test P = 0.02). An ADC value of 0.8 × 10 (-3)  mm (2)  s (-1) was noted as the ideal threshold value for differentiating malignant from benign diffuse orbital masses. The validity of ADC in predicting a malignant or benign diffuse orbital mass had a sensitivity of 87%, specificity of 67% and accuracy of 88%. ADC is a promising imaging metric to characterize malignant and benign diffuse orbital masses and to distinguish lymphomas from other non-lymphoproliferative lesions.

Effect of Static Strains on Diffusion

NASA Technical Reports Server (NTRS)

Girifalco, L. A.; Grimes, H. H.

1961-01-01

A theory is developed that gives the diffusion coefficient in strained systems as an exponential function of the strain. This theory starts with the statistical theory of the atomic jump frequency as developed by Vineyard. The parameter determining the effect of strain on diffusion is related to the changes in the inter-atomic forces with strain. Comparison of the theory with published experimental results for the effect of pressure on diffusion shows that the experiments agree with the form of the theoretical equation in all cases within experimental error.

Nonlocal transport in the presence of transport barriers

NASA Astrophysics Data System (ADS)

Del-Castillo-Negrete, D.

2013-10-01

There is experimental, numerical, and theoretical evidence that transport in plasmas can, under certain circumstances, depart from the standard local, diffusive description. Examples include fast pulse propagation phenomena in perturbative experiments, non-diffusive scaling in L-mode plasmas, and non-Gaussian statistics of fluctuations. From the theoretical perspective, non-diffusive transport descriptions follow from the relaxation of the restrictive assumptions (locality, scale separation, and Gaussian/Markovian statistics) at the foundation of diffusive models. We discuss an alternative class of models able to capture some of the observed non-diffusive transport phenomenology. The models are based on a class of nonlocal, integro-differential operators that provide a unifying framework to describe non- Fickian scale-free transport, and non-Markovian (memory) effects. We study the interplay between nonlocality and internal transport barriers (ITBs) in perturbative transport including cold edge pulses and power modulation. Of particular interest in the nonlocal ``tunnelling'' of perturbations through ITBs. Also, flux-gradient diagrams are discussed as diagnostics to detect nonlocal transport processes in numerical simulations and experiments. Work supported by the US Department of Energy.

Diffusion-weighted MR imaging findings of kidneys in patients with early phase of obstruction.

PubMed

Bozgeyik, Zulkif; Kocakoc, Ercan; Sonmezgoz, Fitnet

2009-04-01

Diffusion-weighted (DW) magnetic resonance (MR) imaging is an MR technique used to show molecular diffusion. The apparent diffusion coefficient (ADC), as a quantitative parameter calculated from the DW MR images. The purpose of this study is to evaluate the ability of DW MR imaging in early phase of obstruction due to urolithiasis. Twenty-six patients with acute dilatation of the pelvicalyceal system detected by intravenous urography were included in this study. MR imaging was performed using a 1.5 T whole-body superconducting MR scanner. DW imaging can be performed using single-shot spin-echo, echo-planar imaging (EPI) sequences with the following diffusion gradient b values: 100, 600, 1000 s/mm(2). Circular region of interest (ROI) was placed in the renal parenchyma for the measurement of ADC values in the normal and obstructed kidney. For statistical analyses, Paired t test were used. In spite of obstructed kidneys had the lower ADC values compared to normal kidneys, these alterations were statistically insignificant. We did not observe significantly different ADC values of early phase of obstructed kidneys compared to normal kidneys.

Structure and Soot Formation Properties of Laminar Flames

NASA Technical Reports Server (NTRS)

El-Leathy, A. M.; Xu, F.; Faeth, G. M.

2001-01-01

Soot formation within hydrocarbon-fueled flames is an important unresolved problem of combustion science for several reasons: soot emissions are responsible for more deaths than any other combustion-generated pollutant, thermal loads due to continuum radiation from soot limit the durability of combustors, thermal radiation from soot is mainly responsible for the growth and spread of unwanted fires, carbon monoxide emissions associated with soot emissions are responsible for most fire deaths, and limited understanding of soot processes in flames is a major impediment to the development of computational combustion. Motivated by these observations, soot processes within laminar premixed and nonpremixed (diffusion) flames are being studied during this investigation. The study is limited to laminar flames due to their experimental and computational tractability, noting the relevance of these results to practical flames through laminar flamelet concepts. Nonbuoyant flames are emphasized because buoyancy affects soot processes in laminar diffusion flames whereas effects of buoyancy are small for most practical flames. This study involves both ground- and space-based experiments, however, the following discussion will be limited to ground-based experiments because no space-based experiments were carried out during the report period. The objective of this work was to complete measurements in both premixed and nonpremixed flames in order to gain a better understanding of the structure of the soot-containing region and processes of soot nucleation and surface growth in these environments, with the latter information to be used to develop reliable ways of predicting soot properties in practical flames. The present discussion is brief, more details about the portions of the investigation considered here can be found in refs. 8-13.

Role of spatial inhomogenity in GPCR dimerisation predicted by receptor association-diffusion models

NASA Astrophysics Data System (ADS)

Deshpande, Sneha A.; Pawar, Aiswarya B.; Dighe, Anish; Athale, Chaitanya A.; Sengupta, Durba

2017-06-01

G protein-coupled receptor (GPCR) association is an emerging paradigm with far reaching implications in the regulation of signalling pathways and therapeutic interventions. Recent super resolution microscopy studies have revealed that receptor dimer steady state exhibits sub-second dynamics. In particular the GPCRs, muscarinic acetylcholine receptor M1 (M1MR) and formyl peptide receptor (FPR), have been demonstrated to exhibit a fast association/dissociation kinetics, independent of ligand binding. In this work, we have developed a spatial kinetic Monte Carlo model to investigate receptor homo-dimerisation at a single receptor resolution. Experimentally measured association/dissociation kinetic parameters and diffusion coefficients were used as inputs to the model. To test the effect of membrane spatial heterogeneity on the simulated steady state, simulations were compared to experimental statistics of dimerisation. In the simplest case the receptors are assumed to be diffusing in a spatially homogeneous environment, while spatial heterogeneity is modelled to result from crowding, membrane micro-domains and cytoskeletal compartmentalisation or ‘corrals’. We show that a simple association-diffusion model is sufficient to reproduce M1MR association statistics, but fails to reproduce FPR statistics despite comparable kinetic constants. A parameter sensitivity analysis is required to reproduce the association statistics of FPR. The model reveals the complex interplay between cytoskeletal components and their influence on receptor association kinetics within the features of the membrane landscape. These results constitute an important step towards understanding the factors modulating GPCR organisation.

Generalizing Backtrack-Free Search: A Framework for Search-Free Constraint Satisfaction

NASA Technical Reports Server (NTRS)

Jonsson, Ari K.; Frank, Jeremy

2000-01-01

Tractable classes of constraint satisfaction problems are of great importance in artificial intelligence. Identifying and taking advantage of such classes can significantly speed up constraint problem solving. In addition, tractable classes are utilized in applications where strict worst-case performance guarantees are required, such as constraint-based plan execution. In this work, we present a formal framework for search-free (backtrack-free) constraint satisfaction. The framework is based on general procedures, rather than specific propagation techniques, and thus generalizes existing techniques in this area. We also relate search-free problem solving to the notion of decision sets and use the result to provide a constructive criterion that is sufficient to guarantee search-free problem solving.

Computationally efficient statistical differential equation modeling using homogenization

USGS Publications Warehouse

Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.

2013-01-01

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.

Application of 17% EDTA Enhances Diffusion of (45)Ca-labeled OH(-) and Ca(2+) in Primary Tooth Root Canal.

PubMed

Ximenes, Marcos; Cavalcanti Taguchi, Carolina Mayumi; Triches, Thaisa Cezaria; Sartori, Neimar; Pereira Dias, Luis Alberto; de Araujo, Elaine Bortoleti; Cardoso, Mariane

2016-01-01

Proper cleaning of the root canal is key to the success of endodontic treatment as it allows more effective diffusion of medication throughout the dentinal tubules. The aim of this in vitro study was to investigate the efficacy of 17% ethylenediaminetetraacetic acid (EDTA) in enhancing diffusion of hydroxyl (OH(-)) and calcium ions (Ca(2+)) throughout the root canal in primary teeth. The canals of 25 primary tooth roots were cleaned with endodontic files and 1% sodium hypochlorite. Three groups (G) were then established: GI, in which final irrigation was performed with 1% sodium hypochlorite; GII, in which 17% EDTA was used; and GIII, in which no irrigation was performed. The roots canals in GI and GII were filled with a calcium hydroxide-based paste labeled with the radioisotope calcium-45. Diffusion of OH(-) was detected with pH strips and Ca(2+) analyzed by measuring radioactivity in counts per min. Group II differed statistically from the other groups in diffusion of OH(-) at 24 hr (p<0.05), but no significant difference among groups was found at the day 7 evaluation; GII also differed statistically from the other groups in diffusion of Ca(2+) at 24 hr (p<0.05). These results suggest that application of 17% EDTA in primary tooth enhances diffusion of OH(-) and Ca(2+).

Strange kinetics of bulk-mediated diffusion on lipid bilayers

PubMed Central

Campagnola, Grace; Nepal, Kanti; Peersen, Olve B.

2016-01-01

Diffusion at solid-liquid interfaces is crucial in many technological and biophysical processes. Although its behavior seems deceivingly simple, recent studies showing passive superdiffusive transport suggest diffusion on surfaces may hide rich complexities. In particular, bulk-mediated diffusion occurs when molecules are transiently released from the surface to perform three-dimensional excursions into the liquid bulk. This phenomenon bears the dichotomy where a molecule always return to the surface but the mean jump length is infinite. Such behavior is associated with a breakdown of the central limit theorem and weak ergodicity breaking. Here, we use single-particle tracking to study the statistics of bulk-mediated diffusion on a supported lipid bilayer. We find that the time-averaged mean square displacement (MSD) of individual trajectories, the archetypal measure in diffusion processes, does not converge to the ensemble MSD but it remains a random variable, even in the long observation-time limit. The distribution of time averages is shown to agree with a Lévy flight model. Our results also unravel intriguing anomalies in the statistics of displacements. The time averaged MSD is shown to depend on experimental time and investigations of fractional moments show a scaling 〈|r(t)|q〉 ∼ tqv(q) with non-linear exponents, i.e. v(q) ≠ const. This type of behavior is termed strong anomalous diffusion and is rare among experimental observations. PMID:27095275

TIME-DOMAIN METHODS FOR DIFFUSIVE TRANSPORT IN SOFT MATTER

PubMed Central

Fricks, John; Yao, Lingxing; Elston, Timothy C.; Gregory Forest, And M.

2015-01-01

Passive microrheology [12] utilizes measurements of noisy, entropic fluctuations (i.e., diffusive properties) of micron-scale spheres in soft matter to infer bulk frequency-dependent loss and storage moduli. Here, we are concerned exclusively with diffusion of Brownian particles in viscoelastic media, for which the Mason-Weitz theoretical-experimental protocol is ideal, and the more challenging inference of bulk viscoelastic moduli is decoupled. The diffusive theory begins with a generalized Langevin equation (GLE) with a memory drag law specified by a kernel [7, 16, 22, 23]. We start with a discrete formulation of the GLE as an autoregressive stochastic process governing microbead paths measured by particle tracking. For the inverse problem (recovery of the memory kernel from experimental data) we apply time series analysis (maximum likelihood estimators via the Kalman filter) directly to bead position data, an alternative to formulas based on mean-squared displacement statistics in frequency space. For direct modeling, we present statistically exact GLE algorithms for individual particle paths as well as statistical correlations for displacement and velocity. Our time-domain methods rest upon a generalization of well-known results for a single-mode exponential kernel [1, 7, 22, 23] to an arbitrary M-mode exponential series, for which the GLE is transformed to a vector Ornstein-Uhlenbeck process. PMID:26412904

FADTTSter: accelerating hypothesis testing with functional analysis of diffusion tensor tract statistics

NASA Astrophysics Data System (ADS)

Noel, Jean; Prieto, Juan C.; Styner, Martin

2017-03-01

Functional Analysis of Diffusion Tensor Tract Statistics (FADTTS) is a toolbox for analysis of white matter (WM) fiber tracts. It allows associating diffusion properties along major WM bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these WM tract properties. However, to use this toolbox, a user must have an intermediate knowledge in scripting languages (MATLAB). FADTTSter was created to overcome this issue and make the statistical analysis accessible to any non-technical researcher. FADTTSter is actively being used by researchers at the University of North Carolina. FADTTSter guides non-technical users through a series of steps including quality control of subjects and fibers in order to setup the necessary parameters to run FADTTS. Additionally, FADTTSter implements interactive charts for FADTTS' outputs. This interactive chart enhances the researcher experience and facilitates the analysis of the results. FADTTSter's motivation is to improve usability and provide a new analysis tool to the community that complements FADTTS. Ultimately, by enabling FADTTS to a broader audience, FADTTSter seeks to accelerate hypothesis testing in neuroimaging studies involving heterogeneous clinical data and diffusion tensor imaging. This work is submitted to the Biomedical Applications in Molecular, Structural, and Functional Imaging conference. The source code of this application is available in NITRC.

Measuring a diffusion coefficient by single-particle tracking: statistical analysis of experimental mean squared displacement curves.

PubMed

Ernst, Dominique; Köhler, Jürgen

2013-01-21

We provide experimental results on the accuracy of diffusion coefficients obtained by a mean squared displacement (MSD) analysis of single-particle trajectories. We have recorded very long trajectories comprising more than 1.5 × 10(5) data points and decomposed these long trajectories into shorter segments providing us with ensembles of trajectories of variable lengths. This enabled a statistical analysis of the resulting MSD curves as a function of the lengths of the segments. We find that the relative error of the diffusion coefficient can be minimized by taking an optimum number of points into account for fitting the MSD curves, and that this optimum does not depend on the segment length. Yet, the magnitude of the relative error for the diffusion coefficient does, and achieving an accuracy in the order of 10% requires the recording of trajectories with about 1000 data points. Finally, we compare our results with theoretical predictions and find very good qualitative and quantitative agreement between experiment and theory.

The Two-Dimensional Gabor Function Adapted to Natural Image Statistics: A Model of Simple-Cell Receptive Fields and Sparse Structure in Images.

PubMed

Loxley, P N

2017-10-01

The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple cell receptive field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor function parameters representing the size and spatial frequency of the two-dimensional Gabor function and characterized by a nonuniform probability distribution with heavy tails. All three parameters are found to be strongly correlated, resulting in a basis of multiscale Gabor functions with similar aspect ratios and size-dependent spatial frequencies. A key finding is that the distribution of receptive-field sizes is scale invariant over a wide range of values, so there is no characteristic receptive field size selected by natural image statistics. The Gabor function aspect ratio is found to be approximately conserved by the learning rules and is therefore not well determined by natural image statistics. This allows for three distinct solutions: a basis of Gabor functions with sharp orientation resolution at the expense of spatial-frequency resolution, a basis of Gabor functions with sharp spatial-frequency resolution at the expense of orientation resolution, or a basis with unit aspect ratio. Arbitrary mixtures of all three cases are also possible. Two parameters controlling the shape of the marginal distributions in a probabilistic generative model fully account for all three solutions. The best-performing probabilistic generative model for sparse coding applications is found to be a gaussian copula with Pareto marginal probability density functions.

Diffusion-weighted imaging and demyelinating diseases: new aspects of an old advanced sequence.

PubMed

Rueda-Lopes, Fernanda C; Hygino da Cruz, Luiz C; Doring, Thomas M; Gasparetto, Emerson L

2014-01-01

The purpose of this article is to discuss classic applications in diffusion-weighted imaging (DWI) in demyelinating disease and progression of DWI in the near future. DWI is an advanced technique used in the follow-up of demyelinating disease patients, focusing on the diagnosis of a new lesion before contrast enhancement. With technical advances, diffusion-tensor imaging; new postprocessing techniques, such as tract-based spatial statistics; new ways of calculating diffusion, such as kurtosis; and new applications for DWI and its spectrum are about to arise.

REVIEW OF THE ATTRIBUTES AND PERFORMANCE OF SIX URBAN DIFFUSION MODELS

EPA Science Inventory

The American Meteorological Society conducted a scientific review of a set of six urban diffusion models. TRC Environmental Consultants, Inc. calculated and tabulated a uniform set of statistics for all the models. The report consists of a summary and copies of the three independ...

A computationally tractable version of the collective model

NASA Astrophysics Data System (ADS)

Rowe, D. J.

2004-05-01

A computationally tractable version of the Bohr-Mottelson collective model is presented which makes it possible to diagonalize realistic collective models and obtain convergent results in relatively small appropriately chosen subspaces of the collective model Hilbert space. Special features of the proposed model are that it makes use of the beta wave functions given analytically by the softened-beta version of the Wilets-Jean model, proposed by Elliott et al., and a simple algorithm for computing SO(5)⊃SO(3) spherical harmonics. The latter has much in common with the methods of Chacon, Moshinsky, and Sharp but is conceptually and computationally simpler. Results are presented for collective models ranging from the spherical vibrator to the Wilets-Jean and axially symmetric rotor-vibrator models.

Extended Islands of Tractability for Parsimony Haplotyping

NASA Astrophysics Data System (ADS)

Fleischer, Rudolf; Guo, Jiong; Niedermeier, Rolf; Uhlmann, Johannes; Wang, Yihui; Weller, Mathias; Wu, Xi

Parsimony haplotyping is the problem of finding a smallest size set of haplotypes that can explain a given set of genotypes. The problem is NP-hard, and many heuristic and approximation algorithms as well as polynomial-time solvable special cases have been discovered. We propose improved fixed-parameter tractability results with respect to the parameter "size of the target haplotype set" k by presenting an O *(k 4k )-time algorithm. This also applies to the practically important constrained case, where we can only use haplotypes from a given set. Furthermore, we show that the problem becomes polynomial-time solvable if the given set of genotypes is complete, i.e., contains all possible genotypes that can be explained by the set of haplotypes.

Design and Elaboration of a Tractable Tricyclic Scaffold To Synthesize Druglike Inhibitors of Dipeptidyl Peptidase-4 (DPP-4), Antagonists of the C-C Chemokine Receptor Type 5 (CCR5), and Highly Potent and Selective Phosphoinositol-3 Kinase δ (PI3Kδ) Inhibitors.

PubMed

Schwehm, Carolin; Kellam, Barrie; Garces, Aimie E; Hill, Stephen J; Kindon, Nicholas D; Bradshaw, Tracey D; Li, Jin; Macdonald, Simon J F; Rowedder, James E; Stoddart, Leigh A; Stocks, Michael J

2017-02-23

A novel molecular scaffold has been synthesized, and its incorporation into new analogues of biologically active molecules across multiple target classes will be discussed. In these studies, we have shown use of the tricyclic scaffold to synthesize potent inhibitors of the serine peptidase DPP-4, antagonists of the CCR5 receptor, and highly potent and selective PI3K δ isoform inhibitors. We also describe the predicted physicochemical properties of the resulting inhibitors and conclude that the tractable molecular scaffold could have potential application in future drug discovery programs.

Analysis of alterations in white matter integrity of adult patients with comitant exotropia.

PubMed

Li, Dan; Li, Shenghong; Zeng, Xianjun

2018-05-01

Objective This study was performed to investigate structural abnormalities of the white matter in patients with comitant exotropia using the tract-based spatial statistics (TBSS) method. Methods Diffusion tensor imaging data from magnetic resonance images of the brain were collected from 20 patients with comitant exotropia and 20 age- and sex-matched healthy controls. The FMRIB Software Library was used to compute the diffusion measures, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). These measures were obtained using voxel-wise statistics with threshold-free cluster enhancement. Results The FA values in the right inferior fronto-occipital fasciculus (IFO) and right inferior longitudinal fasciculus were significantly higher and the RD values in the bilateral IFO, forceps minor, left anterior corona radiata, and left anterior thalamic radiation were significantly lower in the comitant exotropia group than in the healthy controls. No significant differences in the MD or AD values were found between the two groups. Conclusions Alterations in FA and RD values may indicate the underlying neuropathologic mechanism of comitant exotropia. The TBSS method can be a useful tool to investigate neuronal tract participation in patients with this disease.

Numerical Experiments with a Turbulent Single-Mode Rayleigh-Taylor Instability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cloutman, L.D.

2000-04-01

Direct numerical simulation is a powerful tool for studying turbulent flows. Unfortunately, it is also computationally expensive and often beyond the reach of the largest, fastest computers. Consequently, a variety of turbulence models have been devised to allow tractable and affordable simulations of averaged flow fields. Unfortunately, these present a variety of practical difficulties, including the incorporation of varying degrees of empiricism and phenomenology, which leads to a lack of universality. This unsatisfactory state of affairs has led to the speculation that one can avoid the expense and bother of using a turbulence model by relying on the grid andmore » numerical diffusion of the computational fluid dynamics algorithm to introduce a spectral cutoff on the flow field and to provide dissipation at the grid scale, thereby mimicking two main effects of a large eddy simulation model. This paper shows numerical examples of a single-mode Rayleigh-Taylor instability in which this procedure produces questionable results. We then show a dramatic improvement when two simple subgrid-scale models are employed. This study also illustrates the extreme sensitivity to initial conditions that is a common feature of turbulent flows.« less

Disordered porous solids : from chord distributions to small angle scattering

NASA Astrophysics Data System (ADS)

Levitz, P.; Tchoubar, D.

1992-06-01

Disordered biphasic porous solids are examples of complex interfacial media. Small angle scattering strongly depends on the geometrical properties of the internal surface partitioning a porous system. Properties of the second derivative of the bulk autocorrelation function quantitatively defines the level of connection between the small angle scattering and the statistical properties of this interface. A tractable expression of this second derivative, involving the pore and the mass chord distribution functions, was proposed by Mering and Tchoubar (MT). Based on the present possibility to make a quantitative connection between imaging techniques and the small angle scattering, this paper tries to complete and to extend the MT approach. We first discuss how chord distribution functions can be used as fingerprints of the structural disorder. An explicit relation between the small angle scattering and these chord distributions is then proposed. In a third part, the application to different types of disorder is critically discussed and predictions are compared to available experimental data. Using image processing, we will consider three types of disorder : the long-range Debye randomness, the “ correlated " disorder with a special emphasis on the structure of a porous glass (the vycor), and, finally, complex structures where length scale invariance properties can be observed. Les solides poreux biphasiques sont des exemples de milieux interfaciaux complexes. La diffusion aux petits angles (SAS) dépend fortement des propriétés géométriques de l'interface partitionant le milieu poreux. Les propriétés de la dérivée seconde de la fonction d'autocorrélation de densité définit quantitativement le niveau de connection entre la diffusion aux petits angles et les caractéristiques statistiques de cette interface. Une expression utilisable de cette seconde dérivée, impliquant les distributions de cordes associées à la phase massique et au réseau de pores, fut proposée par Mering et Tchoubar (MT). Mettant à profit la possibilité actuelle d'une comparaison quantitative entre les techniques d'imagerie et la diffusion aux petits angles, ce papier tente de compléter et d'étendre l'approche MT. Dans un premier temps, nous montrons en quoi la connaissance de ces distributions de cordes permet de distinguer certains types de désordres structuraux. Une relation explicite entre le spectre de diffusion aux petits angles et les distributions de cordes est alors proposée. Dans une troisième partie, l'application à différents types de désordre est discutée et les prédictions du modèle comparées aux résultats expérimentaux disponibles. Par utilisation du traitement d'images, nous nous intéressons à trois types de désordre : le milieu aléatoire de Debye, pour ses propriétés à grandes distances, le désordre “ corrélé " avec une attention particulière pour le cas d'un verre poreux (le Vycor) et enfin des organisations complexes où des propriétés d'invariance d'échelle de longueur peuvent être observées.

Comparison of diffusion-weighted MRI acquisition techniques for normal pancreas at 3.0 Tesla.

PubMed

Yao, Xiu-Zhong; Kuang, Tiantao; Wu, Li; Feng, Hao; Liu, Hao; Cheng, Wei-Zhong; Rao, Sheng-Xiang; Wang, He; Zeng, Meng-Su

2014-01-01

We aimed to optimize diffusion-weighted imaging (DWI) acquisitions for normal pancreas at 3.0 Tesla. Thirty healthy volunteers were examined using four DWI acquisition techniques with b values of 0 and 600 s/mm2 at 3.0 Tesla, including breath-hold DWI, respiratory-triggered DWI, respiratory-triggered DWI with inversion recovery (IR), and free-breathing DWI with IR. Artifacts, signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) of normal pancreas were statistically evaluated among different DWI acquisitions. Statistical differences were noticed in artifacts, SNR, and ADC values of normal pancreas among different DWI acquisitions by ANOVA (P <0.001). Normal pancreas imaging had the lowest artifact in respiratory-triggered DWI with IR, the highest SNR in respiratory-triggered DWI, and the highest ADC value in free-breathing DWI with IR. The head, body, and tail of normal pancreas had statistically different ADC values on each DWI acquisition by ANOVA (P < 0.05). The highest image quality for normal pancreas was obtained using respiratory-triggered DWI with IR. Normal pancreas displayed inhomogeneous ADC values along the head, body, and tail structures.

Whole-brain diffusion tensor imaging in correlation to visual-evoked potentials in multiple sclerosis: a tract-based spatial statistics analysis.

PubMed

Lobsien, D; Ettrich, B; Sotiriou, K; Classen, J; Then Bergh, F; Hoffmann, K-T

2014-01-01

Functional correlates of microstructural damage of the brain affected by MS are incompletely understood. The purpose of this study was to evaluate correlations of visual-evoked potentials with microstructural brain changes as determined by DTI in patients with demyelinating central nervous disease. Sixty-one patients with clinically isolated syndrome or MS were prospectively recruited. The mean P100 visual-evoked potential latencies of the right and left eyes of each patient were calculated and used for the analysis. For DTI acquisition, a single-shot echo-planar imaging pulse sequence with 80 diffusion directions was performed at 3T. Fractional anisotropy, radial diffusivity, and axial diffusivity were calculated and correlated with mean P100 visual-evoked potentials by tract-based spatial statistics. Significant negative correlations between mean P100 visual-evoked potentials and fractional anisotropy and significant positive correlations between mean P100 visual-evoked potentials and radial diffusivity were found widespread over the whole brain. The highest significance was found in the optic radiation, frontoparietal white matter, and corpus callosum. Significant positive correlations between mean P100 visual-evoked potentials and axial diffusivity were less widespread, notably sparing the optic radiation. Microstructural changes of the whole brain correlated significantly with mean P100 visual-evoked potentials. The distribution of the correlations showed clear differences among axial diffusivity, fractional anisotropy, and radial diffusivity, notably in the optic radiation. This finding suggests a stronger correlation of mean P100 visual-evoked potentials to demyelination than to axonal damage. © 2014 by American Journal of Neuroradiology.

Quantum statistical effects in the mass transport of interstitial solutes in a crystalline solid

NASA Astrophysics Data System (ADS)

Woo, C. H.; Wen, Haohua

2017-09-01

The impact of quantum statistics on the many-body dynamics of a crystalline solid at finite temperatures containing an interstitial solute atom (ISA) is investigated. The Mori-Zwanzig theory allows the many-body dynamics of the crystal to be formulated and solved analytically within a pseudo-one-particle approach using the Langevin equation with a quantum fluctuation-dissipation relation (FDR) based on the Debye model. At the same time, the many-body dynamics is also directly solved numerically via the molecular dynamics approach with a Langevin heat bath based on the quantum FDR. Both the analytical and numerical results consistently show that below the Debye temperature of the host lattice, quantum statistics significantly impacts the ISA transport properties, resulting in major departures from both the Arrhenius law of diffusion and the Einstein-Smoluchowski relation between the mobility and diffusivity. Indeed, we found that below one-third of the Debye temperature, effects of vibrations on the quantum mobility and diffusivity are both orders-of-magnitude larger and practically temperature independent. We have shown that both effects have their physical origin in the athermal lattice vibrations derived from the phonon ground state. The foregoing theory is tested in quantum molecular dynamics calculation of mobility and diffusivity of interstitial helium in bcc W. In this case, the Arrhenius law is only valid in a narrow range between ˜300 and ˜700 K. The diffusivity becomes temperature independent on the low-temperature side while increasing linearly with temperature on the high-temperature side.

Betty Petersen Memorial Library - NCWCP Publications - NWS

Science.gov Websites

Filters to Variational Statistical Analysis with Spatially Inhomogeneous Covariances (.PDF file) 432 2001 file) 456 2008 Purser, R. James Normalization Of The Diffusive Filters That Represent The Inhomogeneous file) 457 2008 Purser, R. James Normalization Of The Diffusive Filters That Represent The Inhomogeneous

A new statistical analysis of rare earth element diffusion data in garnet

NASA Astrophysics Data System (ADS)

Chu, X.; Ague, J. J.

2015-12-01

The incorporation of rare earth elements (REE) in garnet, Sm and Lu in particular, links garnet chemical zoning to absolute age determinations. The application of REE-based geochronology depends critically on the diffusion behaviors of the parent and daughter isotopes. Previous experimental studies on REE diffusion in garnet, however, exhibit significant discrepancies that impact interpretations of garnet Sm/Nd and Lu/Hf ages.We present a new statistical framework to analyze diffusion data for REE using an Arrhenius relationship that accounts for oxygen fugacity, cation radius and garnet unit-cell dimensions [1]. Our approach is based on Bayesian statistics and is implemented by the Markov chain Monte Carlo method. A similar approach has been recently applied to model diffusion of divalent cations in garnet [2]. The analysis incorporates recent data [3] in addition to the data compilation in ref. [1]. We also include the inter-run bias that helps reconcile the discrepancies among data sets. This additional term estimates the reproducibility and other experimental variabilities not explicitly incorporated in the Arrhenius relationship [2] (e.g., compositional dependence [3] and water content).The fitted Arrhenius relationships are consistent with the models in ref. [3], as well as refs. [1]&[4] at high temperatures. Down-temperature extrapolation leads to >0.5 order of magnitude faster diffusion coefficients than in refs. [1]&[4] at <750 °C. The predicted diffusion coefficients are significantly slower than ref. [5]. The fast diffusion [5] was supported by a field test of the Pikwitonei Granulite—the garnet Sm/Nd age postdates the metamorphic peak (750 °C) by ~30 Myr [6], suggesting considerable resetting of the Sm/Nd system during cooling. However, the Pikwitonei Granulite is a recently recognized UHT terrane with peak temperature exceeding 900 °C [7]. The revised closure temperature (~730 °C) is consistent with our new diffusion model.[1] Carlson (2012) Am Mineral 97 1598-1618. [2] Chu & Ague (2015) Contrib Mineral Petrol, in press. [3] Bloch et al. (2015) Contrib Mineral Petrol 169 1-18. [4] Van Orman et al. (2002) Contrib Mineral Petrol 142 416-424. [5] Tirone et al. (2005) GCA 69 2385-2398. [6] Mezger et al. (1992) EPSL 113 397-409. [7] Kooijman et al. (2012) J Metamorph Geol 30 397-412.

Spatiotemporal chaos of self-replicating spots in reaction-diffusion systems.

PubMed

Wang, Hongli; Ouyang, Qi

2007-11-23

The statistical properties of self-replicating spots in the reaction-diffusion Gray-Scott model are analyzed. In the chaotic regime of the system, the spots that dominate the spatiotemporal chaos grow and divide in two or decay into the background randomly and continuously. The rates at which the spots are created and decay are observed to be linearly dependent on the number of spots in the system. We derive a probabilistic description of the spot dynamics based on the statistical independence of spots and thus propose a characterization of the spatiotemporal chaos dominated by replicating spots.

Temporal correlation measurements of pulsed dual CO2 lidar returns. [for atmospheric pollution detection

NASA Technical Reports Server (NTRS)

Menyuk, N.; Killinger, D. K.

1981-01-01

A pulsed dual-laser direct-detection differential-absorption lidar DIAL system, operating near 10.6 microns, is used to measure the temporal correlation and statistical properties of backscattered returns from specular and diffuse topographic targets. Results show that atmospheric-turbulence fluctuations can effectively be frozen for pulse separation times on the order of 1-3 msec or less. The diffuse target returns, however, yielded a much lower correlation than that obtained with the specular targets; this being due to uncorrelated system noise effects and different statistics for the two types of target returns.

Manifestation of two-channel nonlocal spin transport in the shapes of Hanle curves

NASA Astrophysics Data System (ADS)

Roundy, R. C.; Prestgard, M. C.; Tiwari, A.; Mishchenko, E. G.; Raikh, M. E.

2014-09-01

The dynamics of charge-density fluctuations in a system of two tunnel-coupled wires contains two diffusion modes with dispersion iω =Dq2 and iω =Dq2+2/τt, where D is the diffusion coefficient and τt is the tunneling time between the wires. The dispersion of corresponding spin-density modes depends on magnetic field as a result of the spin precession with Larmour frequency ωL. The presence of two modes affects the shape of the Hanle curve describing the spin-dependent resistance R between the ferromagnetic strips covering the nonmagnetic wires. We demonstrate that the relative shapes of the R (ωL) curves, one measured within the same wire and the other measured between the wires, depends on the ratio τt/τs, where τs is the spin-diffusion time. If the coupling between the wires is local, i.e., only at the point x =0, then the difference of the shapes of intrawire and interwire Hanle curves reflects the difference in statistics of diffusive trajectories, which "switch" or do not switch near x =0. When one of the coupled wires is bent into a loop with a radius a, the shape of the Hanle curve reflects the statistics of random walks on the loop. This statistics is governed by the dimensionless parameter a /√Dτs .

Conditional Random Fields for Fast, Large-Scale Genome-Wide Association Studies

PubMed Central

Huang, Jim C.; Meek, Christopher; Kadie, Carl; Heckerman, David

2011-01-01

Understanding the role of genetic variation in human diseases remains an important problem to be solved in genomics. An important component of such variation consist of variations at single sites in DNA, or single nucleotide polymorphisms (SNPs). Typically, the problem of associating particular SNPs to phenotypes has been confounded by hidden factors such as the presence of population structure, family structure or cryptic relatedness in the sample of individuals being analyzed. Such confounding factors lead to a large number of spurious associations and missed associations. Various statistical methods have been proposed to account for such confounding factors such as linear mixed-effect models (LMMs) or methods that adjust data based on a principal components analysis (PCA), but these methods either suffer from low power or cease to be tractable for larger numbers of individuals in the sample. Here we present a statistical model for conducting genome-wide association studies (GWAS) that accounts for such confounding factors. Our method scales in runtime quadratic in the number of individuals being studied with only a modest loss in statistical power as compared to LMM-based and PCA-based methods when testing on synthetic data that was generated from a generalized LMM. Applying our method to both real and synthetic human genotype/phenotype data, we demonstrate the ability of our model to correct for confounding factors while requiring significantly less runtime relative to LMMs. We have implemented methods for fitting these models, which are available at http://www.microsoft.com/science. PMID:21765897

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

Childhood pneumonia and crowding, bed-sharing and nutrition: a case-control study from The Gambia.

PubMed

Howie, S R C; Schellenberg, J; Chimah, O; Ideh, R C; Ebruke, B E; Oluwalana, C; Mackenzie, G; Jallow, M; Njie, M; Donkor, S; Dionisio, K L; Goldberg, G; Fornace, K; Bottomley, C; Hill, P C; Grant, C C; Corrah, T; Prentice, A M; Ezzati, M; Greenwood, B M; Smith, P G; Adegbola, R A; Mulholland, K

2016-10-01

Greater Banjul and Upper River Regions, The Gambia. To investigate tractable social, environmental and nutritional risk factors for childhood pneumonia. A case-control study examining the association of crowding, household air pollution (HAP) and nutritional factors with pneumonia was undertaken in children aged 2-59 months: 458 children with severe pneumonia, defined according to the modified WHO criteria, were compared with 322 children with non-severe pneumonia, and these groups were compared to 801 neighbourhood controls. Controls were matched by age, sex, area and season. Strong evidence was found of an association between bed-sharing with someone with a cough and severe pneumonia (adjusted OR [aOR] 5.1, 95%CI 3.2-8.2, P < 0.001) and non-severe pneumonia (aOR 7.3, 95%CI 4.1-13.1, P < 0.001), with 18% of severe cases estimated to be attributable to this risk factor. Malnutrition and pneumonia had clear evidence of association, which was strongest between severe malnutrition and severe pneumonia (aOR 8.7, 95%CI 4.2-17.8, P < 0.001). No association was found between pneumonia and individual carbon monoxide exposure as a measure of HAP. Bed-sharing with someone with a cough is an important risk factor for severe pneumonia, and potentially tractable to intervention, while malnutrition remains an important tractable determinant.

The special theory of Brownian relativity: equivalence principle for dynamic and static random paths and uncertainty relation for diffusion.

PubMed

Mezzasalma, Stefano A

2007-03-15

The theoretical basis of a recent theory of Brownian relativity for polymer solutions is deepened and reexamined. After the problem of relative diffusion in polymer solutions is addressed, its two postulates are formulated in all generality. The former builds a statistical equivalence between (uncorrelated) timelike and shapelike reference frames, that is, among dynamical trajectories of liquid molecules and static configurations of polymer chains. The latter defines the "diffusive horizon" as the invariant quantity to work with in the special version of the theory. Particularly, the concept of universality in polymer physics corresponds in Brownian relativity to that of covariance in the Einstein formulation. Here, a "universal" law consists of a privileged observation, performed from the laboratory rest frame and agreeing with any diffusive reference system. From the joint lack of covariance and simultaneity implied by the Brownian Lorentz-Poincaré transforms, a relative uncertainty arises, in a certain analogy with quantum mechanics. It is driven by the difference between local diffusion coefficients in the liquid solution. The same transformation class can be used to infer Fick's second law of diffusion, playing here the role of a gauge invariance preserving covariance of the spacetime increments. An overall, noteworthy conclusion emerging from this view concerns the statistics of (i) static macromolecular configurations and (ii) the motion of liquid molecules, which would be much more related than expected.

Feynman-Kac equations for reaction and diffusion processes

NASA Astrophysics Data System (ADS)

Hou, Ru; Deng, Weihua

2018-04-01

This paper provides a theoretical framework for deriving the forward and backward Feynman-Kac equations for the distribution of functionals of the path of a particle undergoing both diffusion and reaction processes. Once given the diffusion type and reaction rate, a specific forward or backward Feynman-Kac equation can be obtained. The results in this paper include those for normal/anomalous diffusions and reactions with linear/nonlinear rates. Using the derived equations, we apply our findings to compute some physical (experimentally measurable) statistics, including the occupation time in half-space, the first passage time, and the occupation time in half-interval with an absorbing or reflecting boundary, for the physical system with anomalous diffusion and spontaneous evanescence.

Liquid water breakthrough location distances on a gas diffusion layer of polymer electrolyte membrane fuel cells

NASA Astrophysics Data System (ADS)

Yu, Junliang; Froning, Dieter; Reimer, Uwe; Lehnert, Werner

2018-06-01

The lattice Boltzmann method is adopted to simulate the three dimensional dynamic process of liquid water breaking through the gas diffusion layer (GDL) in the polymer electrolyte membrane fuel cell. 22 micro-structures of Toray GDL are built based on a stochastic geometry model. It is found that more than one breakthrough locations are formed randomly on the GDL surface. Breakthrough location distance (BLD) are analyzed statistically in two ways. The distribution is evaluated statistically by the Lilliefors test. It is concluded that the BLD can be described by the normal distribution with certain statistic characteristics. Information of the shortest neighbor breakthrough location distance can be the input modeling setups on the cell-scale simulations in the field of fuel cell simulation.

Electrochemical Impedance Imaging via the Distribution of Diffusion Times

NASA Astrophysics Data System (ADS)

Song, Juhyun; Bazant, Martin Z.

2018-03-01

We develop a mathematical framework to analyze electrochemical impedance spectra in terms of a distribution of diffusion times (DDT) for a parallel array of random finite-length Warburg (diffusion) or Gerischer (reaction-diffusion) circuit elements. A robust DDT inversion method is presented based on complex nonlinear least squares regression with Tikhonov regularization and illustrated for three cases of nanostructured electrodes for energy conversion: (i) a carbon nanotube supercapacitor, (ii) a silicon nanowire Li-ion battery, and (iii) a porous-carbon vanadium flow battery. The results demonstrate the feasibility of nondestructive "impedance imaging" to infer microstructural statistics of random, heterogeneous materials.

Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects.

PubMed

Jovicich, Jorge; Marizzoni, Moira; Bosch, Beatriz; Bartrés-Faz, David; Arnold, Jennifer; Benninghoff, Jens; Wiltfang, Jens; Roccatagliata, Luca; Picco, Agnese; Nobili, Flavio; Blin, Oliver; Bombois, Stephanie; Lopes, Renaud; Bordet, Régis; Chanoine, Valérie; Ranjeva, Jean-Philippe; Didic, Mira; Gros-Dagnac, Hélène; Payoux, Pierre; Zoccatelli, Giada; Alessandrini, Franco; Beltramello, Alberto; Bargalló, Núria; Ferretti, Antonio; Caulo, Massimo; Aiello, Marco; Ragucci, Monica; Soricelli, Andrea; Salvadori, Nicola; Tarducci, Roberto; Floridi, Piero; Tsolaki, Magda; Constantinidis, Manos; Drevelegas, Antonios; Rossini, Paolo Maria; Marra, Camillo; Otto, Josephin; Reiss-Zimmermann, Martin; Hoffmann, Karl-Titus; Galluzzi, Samantha; Frisoni, Giovanni B

2014-11-01

Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm(3), b = 700 s/mm(2), 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios. Copyright © 2014 Elsevier Inc. All rights reserved.

A study of hadronic decays of the chi(c) states produced in psi-prime radiative transitions at the Beijing Experimental Spectrometer

NASA Astrophysics Data System (ADS)

Varner, Gary Sim

1999-11-01

Utilizing the world's largest sample of resonant y' decays, as measured by the Beijing Experimental Spectrometer (BES) during 1993-1995, a comprehensive study of the hadronic decay modes of the χc (3P1 Charmonium) states has been undertaken. Compared with the data set for the Mark I detector, whose published measurements of many of these hadronic decays have been definitive for almost 20 years, roughly an order of magnitude larger statistics has been obtained. Taking advantage of these larger statistics, many new hadronic decay modes have been discovered, while others have been refined. An array of first observations, improvements, confirmations or limits are reported with respect to current world values. These higher precision and newly discovered decay modes are an excellent testing ground for recent theoretical interest in the contribution of higher Fock states and the color octet mechanism in heavy quarkonium annihilation and subsequent light hadronization. Because these calculations are largely tractable only in two body decays, these are the focus of this dissertation. A comparison of current theoretical calculations and experimental results is presented, indicating the success of these phenomenological advances. Measurements for which there are as yet no suitable theoretical prediction are indicated.

Methodology and Ontology in Microbiome Research.

PubMed

Huss, John

2014-01-01

Research on the human microbiome has generated a staggering amount of sequence data, revealing variation in microbial diversity at the community, species (or phylotype), and genomic levels. In order to make this complexity more manageable and easier to interpret, new units-the metagenome, core microbiome, and enterotype-have been introduced in the scientific literature. Here, I argue that analytical tools and exploratory statistical methods, coupled with a translational imperative, are the primary drivers of this new ontology. By reducing the dimensionality of variation in the human microbiome, these new units render it more tractable and easier to interpret, and hence serve an important heuristic role. Nonetheless, there are several reasons to be cautious about these new categories prematurely "hardening" into natural units: a lack of constraints on what can be sequenced metagenomically, freedom of choice in taxonomic level in defining a "core microbiome," typological framing of some of the concepts, and possible reification of statistical constructs. Finally, lessons from the Human Genome Project have led to a translational imperative: a drive to derive results from the exploration of microbiome variation that can help to articulate the emerging paradigm of personalized genomic medicine (PGM). There is a tension between the typologizing inherent in much of this research and the personal in PGM.

Science and Sentiment: Grinnell's Fact-Based Philosophy of Biodiversity Conservation.

PubMed

Shavit, Ayelet; Griesemer, James R

2018-06-01

At the beginning of the twentieth century, the biologist Joseph Grinnell made a distinction between science and sentiment for producing fact-based generalizations on how to conserve biodiversity. We are inspired by Grinnellian science, which successfully produced a century-long impact on studying and conserving biodiversity that runs orthogonal to some familiar philosophical distinctions such as fact versus value, emotion versus reason and basic versus applied science. According to Grinnell, unlike sentiment-based generalizations, a fact-based generalization traces its diverse commitments and thus becomes tractable for its audience. We argue that foregrounding tractability better explains Grinnell's practice in the context of his time as well as in the context of current discourse among scientists over the political "biases" of biodiversity research and its problem of "reproducibility."

Identification of Small RNA-Protein Partners in Plant Symbiotic Bacteria.

PubMed

Robledo, Marta; Matia-González, Ana M; García-Tomsig, Natalia I; Jiménez-Zurdo, José I

2018-01-01

The identification of the protein partners of bacterial small noncoding RNAs (sRNAs) is essential to understand the mechanistic principles and functions of riboregulation in prokaryotic cells. Here, we describe an optimized affinity chromatography protocol that enables purification of in vivo formed sRNA-protein complexes in Sinorhizobium meliloti, a genetically tractable nitrogen-fixing plant symbiotic bacterium. The procedure requires the tagging of the desired sRNA with the MS2 aptamer, which is affinity-captured by the MS2-MBP protein conjugated to an amylose resin. As proof of principle, we show recovery of the RNA chaperone Hfq associated to the strictly Hfq-dependent AbcR2 trans-sRNA. This method can be applied for the investigation of sRNA-protein interactions on a broad range of genetically tractable α-proteobacteria.

Harnessing the hygroscopic and biofluorescent behaviors of genetically tractable microbial cells to design biohybrid wearables.

PubMed

Wang, Wen; Yao, Lining; Cheng, Chin-Yi; Zhang, Teng; Atsumi, Hiroshi; Wang, Luda; Wang, Guanyun; Anilionyte, Oksana; Steiner, Helene; Ou, Jifei; Zhou, Kang; Wawrousek, Chris; Petrecca, Katherine; Belcher, Angela M; Karnik, Rohit; Zhao, Xuanhe; Wang, Daniel I C; Ishii, Hiroshi

2017-05-01

Cells' biomechanical responses to external stimuli have been intensively studied but rarely implemented into devices that interact with the human body. We demonstrate that the hygroscopic and biofluorescent behaviors of living cells can be engineered to design biohybrid wearables, which give multifunctional responsiveness to human sweat. By depositing genetically tractable microbes on a humidity-inert material to form a heterogeneous multilayered structure, we obtained biohybrid films that can reversibly change shape and biofluorescence intensity within a few seconds in response to environmental humidity gradients. Experimental characterization and mechanical modeling of the film were performed to guide the design of a wearable running suit and a fluorescent shoe prototype with bio-flaps that dynamically modulates ventilation in synergy with the body's need for cooling.

Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast.

PubMed

Iima, Mami; Kataoka, Masako; Kanao, Shotaro; Kawai, Makiko; Onishi, Natsuko; Koyasu, Sho; Murata, Katsutoshi; Ohashi, Akane; Sakaguchi, Rena; Togashi, Kaori

2018-01-01

We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0-2500 s/mm2 with one number of excitations [NEX]) and five b-values (0-2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions.

Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast

PubMed Central

Kataoka, Masako; Kanao, Shotaro; Kawai, Makiko; Onishi, Natsuko; Koyasu, Sho; Murata, Katsutoshi; Ohashi, Akane; Sakaguchi, Rena; Togashi, Kaori

2018-01-01

We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0–2500 s/mm2 with one number of excitations [NEX]) and five b-values (0–2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions. PMID:29494639

Tract-Based Spatial Statistics in Preterm-Born Neonates Predicts Cognitive and Motor Outcomes at 18 Months.

PubMed

Duerden, E G; Foong, J; Chau, V; Branson, H; Poskitt, K J; Grunau, R E; Synnes, A; Zwicker, J G; Miller, S P

2015-08-01

Adverse neurodevelopmental outcome is common in children born preterm. Early sensitive predictors of neurodevelopmental outcome such as MR imaging are needed. Tract-based spatial statistics, a diffusion MR imaging analysis method, performed at term-equivalent age (40 weeks) is a promising predictor of neurodevelopmental outcomes in children born very preterm. We sought to determine the association of tract-based spatial statistics findings before term-equivalent age with neurodevelopmental outcome at 18-months corrected age. Of 180 neonates (born at 24-32-weeks' gestation) enrolled, 153 had DTI acquired early at 32 weeks' postmenstrual age and 105 had DTI acquired later at 39.6 weeks' postmenstrual age. Voxelwise statistics were calculated by performing tract-based spatial statistics on DTI that was aligned to age-appropriate templates. At 18-month corrected age, 166 neonates underwent neurodevelopmental assessment by using the Bayley Scales of Infant Development, 3rd ed, and the Peabody Developmental Motor Scales, 2nd ed. Tract-based spatial statistics analysis applied to early-acquired scans (postmenstrual age of 30-33 weeks) indicated a limited significant positive association between motor skills and axial diffusivity and radial diffusivity values in the corpus callosum, internal and external/extreme capsules, and midbrain (P < .05, corrected). In contrast, for term scans (postmenstrual age of 37-41 weeks), tract-based spatial statistics analysis showed a significant relationship between both motor and cognitive scores with fractional anisotropy in the corpus callosum and corticospinal tracts (P < .05, corrected). Tract-based spatial statistics in a limited subset of neonates (n = 22) scanned at <30 weeks did not significantly predict neurodevelopmental outcomes. The strength of the association between fractional anisotropy values and neurodevelopmental outcome scores increased from early-to-late-acquired scans in preterm-born neonates, consistent with brain dysmaturation in this population. © 2015 by American Journal of Neuroradiology.

Diffusion weighted imaging for the differentiation of breast tumors: From apparent diffusion coefficient to high order diffusion tensor imaging.

PubMed

Teruel, Jose R; Goa, Pål E; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F

2016-05-01

To compare "standard" diffusion weighted imaging, and diffusion tensor imaging (DTI) of 2(nd) and 4(th) -order for the differentiation of malignant and benign breast lesions. Seventy-one patients were imaged at 3 Tesla with a 16-channel breast coil. A diffusion weighted MRI sequence including b = 0 and b = 700 in 30 directions was obtained for all patients. The image data were fitted to three different diffusion models: isotropic model - apparent diffusion coefficient (ADC), 2(nd) -order tensor model (the standard model used for DTI) and a 4(th) -order tensor model, with increased degrees of freedom to describe anisotropy. The ability of the fitted parameters in the different models to differentiate between malignant and benign tumors was analyzed. Seventy-two breast lesions were analyzed, out of which 38 corresponded to malignant and 34 to benign tumors. ADC (using any model) presented the highest discriminative ability of malignant from benign tumors with a receiver operating characteristic area under the curve (AUC) of 0.968, and sensitivity and specificity of 94.1% and 94.7% respectively for a 1.33 × 10(-3) mm(2) /s cutoff. Anisotropy measurements presented high statistical significance between malignant and benign tumors (P < 0.001), but with lower discriminative ability of malignant from benign tumors than ADC (AUC of 0.896 and 0.897 for fractional anisotropy and generalized anisotropy respectively). Statistical significant difference was found between generalized anisotropy and fractional anisotropy for cancers (P < 0.001) but not for benign lesions (P = 0.87). While anisotropy parameters have the potential to provide additional value for breast applications as demonstrated in this study, ADC exhibited the highest differentiation power between malignant and benign breast tumors. © 2015 Wiley Periodicals, Inc.

Model-based error diffusion for high fidelity lenticular screening.

PubMed

Lau, Daniel; Smith, Trebor

2006-04-17

Digital halftoning is the process of converting a continuous-tone image into an arrangement of black and white dots for binary display devices such as digital ink-jet and electrophotographic printers. As printers are achieving print resolutions exceeding 1,200 dots per inch, it is becoming increasingly important for halftoning algorithms to consider the variations and interactions in the size and shape of printed dots between neighboring pixels. In the case of lenticular screening where statistically independent images are spatially multiplexed together, ignoring these variations and interactions, such as dot overlap, will result in poor lenticular image quality. To this end, we describe our use of model-based error-diffusion for the lenticular screening problem where statistical independence between component images is achieved by restricting the diffusion of error to only those pixels of the same component image where, in order to avoid instabilities, the proposed approach involves a novel error-clipping procedure.

White matter alterations in narcolepsy patients with cataplexy: tract-based spatial statistics.

PubMed

Park, Yun K; Kwon, Oh-Hun; Joo, Eun Yeon; Kim, Jae-Hun; Lee, Jong M; Kim, Sung T; Hong, Seung B

2016-04-01

Functional imaging studies and voxel-based morphometry analysis of brain magnetic resonance imaging showed abnormalities in the hypothalamus-thalamus-orbitofrontal pathway, demonstrating altered hypocretin pathway in narcolepsy. Those distinct morphometric changes account for problems in wake-sleep control, attention and memory. It also raised the necessity to evaluate white matter changes. To investigate brain white matter alterations in drug-naïve narcolepsy patients with cataplexy and to explore relationships between white matter changes and patient clinical characteristics, drug-naïve narcolepsy patients with cataplexy (n = 22) and healthy age- and gender-matched controls (n = 26) were studied. Fractional anisotropy and mean diffusivity images were obtained from whole-brain diffusion tensor imaging, and tract-based spatial statistics were used to localize white matter abnormalities. Compared with controls, patients showed significant decreases in fractional anisotropy of white matter of the bilateral anterior cingulate, fronto-orbital area, frontal lobe, anterior limb of the internal capsule and corpus callosum, as well as the left anterior and medial thalamus. Patients and controls showed no differences in mean diffusivity. Among patients, mean diffusivity values of white matter in the bilateral superior frontal gyri, bilateral fronto-orbital gyri and right superior parietal gyrus were positively correlated with depressive mood. This tract-based spatial statistics study demonstrated that drug-naïve patients with narcolepsy had reduced fractional anisotropy of white matter in multiple brain areas and significant relationship between increased mean diffusivity of white matter in frontal/cingulate and depression. It suggests the widespread disruption of white matter integrity and prevalent brain degeneration of frontal lobes according to a depressive symptom in narcolepsy. © 2015 European Sleep Research Society.

Estimation of integral curves from high angular resolution diffusion imaging (HARDI) data.

PubMed

Carmichael, Owen; Sakhanenko, Lyudmila

2015-05-15

We develop statistical methodology for a popular brain imaging technique HARDI based on the high order tensor model by Özarslan and Mareci [10]. We investigate how uncertainty in the imaging procedure propagates through all levels of the model: signals, tensor fields, vector fields, and fibers. We construct asymptotically normal estimators of the integral curves or fibers which allow us to trace the fibers together with confidence ellipsoids. The procedure is computationally intense as it blends linear algebra concepts from high order tensors with asymptotical statistical analysis. The theoretical results are illustrated on simulated and real datasets. This work generalizes the statistical methodology proposed for low angular resolution diffusion tensor imaging by Carmichael and Sakhanenko [3], to several fibers per voxel. It is also a pioneering statistical work on tractography from HARDI data. It avoids all the typical limitations of the deterministic tractography methods and it delivers the same information as probabilistic tractography methods. Our method is computationally cheap and it provides well-founded mathematical and statistical framework where diverse functionals on fibers, directions and tensors can be studied in a systematic and rigorous way.

Estimation of integral curves from high angular resolution diffusion imaging (HARDI) data

PubMed Central

Carmichael, Owen; Sakhanenko, Lyudmila

2015-01-01

We develop statistical methodology for a popular brain imaging technique HARDI based on the high order tensor model by Özarslan and Mareci [10]. We investigate how uncertainty in the imaging procedure propagates through all levels of the model: signals, tensor fields, vector fields, and fibers. We construct asymptotically normal estimators of the integral curves or fibers which allow us to trace the fibers together with confidence ellipsoids. The procedure is computationally intense as it blends linear algebra concepts from high order tensors with asymptotical statistical analysis. The theoretical results are illustrated on simulated and real datasets. This work generalizes the statistical methodology proposed for low angular resolution diffusion tensor imaging by Carmichael and Sakhanenko [3], to several fibers per voxel. It is also a pioneering statistical work on tractography from HARDI data. It avoids all the typical limitations of the deterministic tractography methods and it delivers the same information as probabilistic tractography methods. Our method is computationally cheap and it provides well-founded mathematical and statistical framework where diverse functionals on fibers, directions and tensors can be studied in a systematic and rigorous way. PMID:25937674

Optimal structure and parameter learning of Ising models

DOE PAGES

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant; ...

2018-03-16

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Multi-sensory integration in a small brain

NASA Astrophysics Data System (ADS)

Gepner, Ruben; Wolk, Jason; Gershow, Marc

Understanding how fluctuating multi-sensory stimuli are integrated and transformed in neural circuits has proved a difficult task. To address this question, we study the sensori-motor transformations happening in the brain of the Drosophila larva, a tractable model system with about 10,000 neurons. Using genetic tools that allow us to manipulate the activity of individual brain cells through their transparent body, we observe the stochastic decisions made by freely-behaving animals as their visual and olfactory environments fluctuate independently. We then use simple linear-nonlinear models to correlate outputs with relevant features in the inputs, and adaptive filtering processes to track changes in these relevant parameters used by the larva's brain to make decisions. We show how these techniques allow us to probe how statistics of stimuli from different sensory modalities combine to affect behavior, and can potentially guide our understanding of how neural circuits are anatomically and functionally integrated. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Implementation of the Iterative Proportion Fitting Algorithm for Geostatistical Facies Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Yupeng, E-mail: yupeng@ualberta.ca; Deutsch, Clayton V.

2012-06-15

In geostatistics, most stochastic algorithm for simulation of categorical variables such as facies or rock types require a conditional probability distribution. The multivariate probability distribution of all the grouped locations including the unsampled location permits calculation of the conditional probability directly based on its definition. In this article, the iterative proportion fitting (IPF) algorithm is implemented to infer this multivariate probability. Using the IPF algorithm, the multivariate probability is obtained by iterative modification to an initial estimated multivariate probability using lower order bivariate probabilities as constraints. The imposed bivariate marginal probabilities are inferred from profiles along drill holes or wells.more » In the IPF process, a sparse matrix is used to calculate the marginal probabilities from the multivariate probability, which makes the iterative fitting more tractable and practical. This algorithm can be extended to higher order marginal probability constraints as used in multiple point statistics. The theoretical framework is developed and illustrated with estimation and simulation example.« less

Optimal structure and parameter learning of Ising models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Multifractal vector fields and stochastic Clifford algebra.

PubMed

Schertzer, Daniel; Tchiguirinskaia, Ioulia

2015-12-01

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schertzer, Daniel, E-mail: Daniel.Schertzer@enpc.fr; Tchiguirinskaia, Ioulia, E-mail: Ioulia.Tchiguirinskaia@enpc.fr

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge upmore » the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.« less

The Rapid Distortion of Two-Way Coupled Particle-Laden Turbulence

NASA Astrophysics Data System (ADS)

Kasbaoui, Mohamed; Koch, Donald; Desjardins, Olivier

2017-11-01

The modulation of sheared turbulence by dispersed particles is addressed in the two-way coupling regime. The preferential sampling of the straining regions of the flow by inertial particles in turbulence leads to the formation of clusters. These fast sedimenting particle structures cause the anisotropic alteration of turbulence at small scales in the direction of gravity. These effects are investigated in a revisited Rapid Distortion Theory (RDT), extended for two-way coupled particle-laden flows. To make the analysis tractable, we assume that particles have small but non-zero inertia. In the classical results for single-phase flows, the RDT assumption of fast shearing compared to the turbulence time scales leads to the distortion of ``frozen'' turbulence. In particle-laden turbulence, the coupling between the two phases remains strong even under fast shearing and leads to a dynamic modulation of the turbulence spectrum. Turbulence statistics obtained from RDT are compared with Euler-Lagrange simulations of homogeneously sheared particle-laden turbulence.

Identifying research priorities for public health research to address health inequalities: use of Delphi-like survey methods.

PubMed

Turner, S; Ollerhead, E; Cook, A

2017-10-09

In the funding of health research and public health research it is vital that research questions posed are important and that funded research meets a research need or a gap in evidence. Many methods are used in the identification of research priorities, however, these can be resource intensive, costly and logistically challenging. Identifying such research priorities can be particularly challenging for complex public health problems as there is a need to consult a number of experts across disciplines and with a range of expertise. This study investigated the use of Delphi-like survey methods in identifying important research priorities relating to health inequalities and framing tractable research questions for topic areas identified. The study was conducted in two phases, both using Delphi-like survey methods. Firstly, public health professionals with an interest in health inequalities were asked to identify research priorities. Secondly academic researchers were asked to frame tractable research questions relating to the priorities identified. These research priorities identified using Delphi-like survey methods were subsequently compared to those identified using different methods. A total of 52 public health professionals and 21 academics across the United Kingdom agreed to take part. The response rates were high, from public health professionals across three survey rounds (69%, 50% and 40%) and from academics across one round (52%), indicating that participants were receptive to the method and motivated to respond. The themes identified as encompassing the most important research priorities were mental health, healthy environment and health behaviours. Within these themes, the topic areas that emerged most strongly included community interventions for prevention of mental health problems and the food and alcohol environment. Some responses received from academic researchers were (as requested) in the form of tractable research questions, whereas others contributed further potential topic areas instead. Delphi-like survey methods are practical and productive as a means of obtaining opinions from a wide number of relevant experts identifying potential priority topic areas for research; however, this method is less appropriate for framing tractable research questions.

Charged Particle Diffusion in Isotropic Random Static Magnetic Fields

NASA Astrophysics Data System (ADS)

Subedi, P.; Sonsrettee, W.; Matthaeus, W. H.; Ruffolo, D. J.; Wan, M.; Montgomery, D.

2013-12-01

Study of the transport and diffusion of charged particles in a turbulent magnetic field remains a subject of considerable interest. Research has most frequently concentrated on determining the diffusion coefficient in the presence of a mean magnetic field. Here we consider Diffusion of charged particles in fully three dimensional statistically isotropic magnetic field turbulence with no mean field which is pertinent to many astrophysical situations. We classify different regions of particle energy depending upon the ratio of Larmor radius of the charged particle to the characteristic outer length scale of turbulence. We propose three different theoretical models to calculate the diffusion coefficient each applicable to a distinct range of particle energies. The theoretical results are compared with those from computer simulations, showing very good agreement.

Molecular Dynamic Simulation of Water Vapor and Determination of Diffusion Characteristics in the Pore

NASA Astrophysics Data System (ADS)

Nikonov, Eduard G.; Pavluš, Miron; Popovičová, Mária

2018-02-01

One of the varieties of pores, often found in natural or artificial building materials, are the so-called blind pores of dead-end or saccate type. Three-dimensional model of such kind of pore has been developed in this work. This model has been used for simulation of water vapor interaction with individual pore by molecular dynamics in combination with the diffusion equation method. Special investigations have been done to find dependencies between thermostats implementations and conservation of thermodynamic and statistical values of water vapor - pore system. The two types of evolution of water - pore system have been investigated: drying and wetting of the pore. Full research of diffusion coefficient, diffusion velocity and other diffusion parameters has been made.

A nonlinear Fokker-Planck equation approach for interacting systems: Anomalous diffusion and Tsallis statistics

NASA Astrophysics Data System (ADS)

Marin, D.; Ribeiro, M. A.; Ribeiro, H. V.; Lenzi, E. K.

2018-07-01

We investigate the solutions for a set of coupled nonlinear Fokker-Planck equations coupled by the diffusion coefficient in presence of external forces. The coupling by the diffusion coefficient implies that the diffusion of each species is influenced by the other and vice versa due to this term, which represents an interaction among them. The solutions for the stationary case are given in terms of the Tsallis distributions, when arbitrary external forces are considered. We also use the Tsallis distributions to obtain a time dependent solution for a linear external force. The results obtained from this analysis show a rich class of behavior related to anomalous diffusion, which can be characterized by compact or long-tailed distributions.

Evaluation and statistical inference for human connectomes.

PubMed

Pestilli, Franco; Yeatman, Jason D; Rokem, Ariel; Kay, Kendrick N; Wandell, Brian A

2014-10-01

Diffusion-weighted imaging coupled with tractography is currently the only method for in vivo mapping of human white-matter fascicles. Tractography takes diffusion measurements as input and produces the connectome, a large collection of white-matter fascicles, as output. We introduce a method to evaluate the evidence supporting connectomes. Linear fascicle evaluation (LiFE) takes any connectome as input and predicts diffusion measurements as output, using the difference between the measured and predicted diffusion signals to quantify the prediction error. We use the prediction error to evaluate the evidence that supports the properties of the connectome, to compare tractography algorithms and to test hypotheses about tracts and connections.

Electrochemical Impedance Imaging via the Distribution of Diffusion Times.

PubMed

Song, Juhyun; Bazant, Martin Z

2018-03-16

We develop a mathematical framework to analyze electrochemical impedance spectra in terms of a distribution of diffusion times (DDT) for a parallel array of random finite-length Warburg (diffusion) or Gerischer (reaction-diffusion) circuit elements. A robust DDT inversion method is presented based on complex nonlinear least squares regression with Tikhonov regularization and illustrated for three cases of nanostructured electrodes for energy conversion: (i) a carbon nanotube supercapacitor, (ii) a silicon nanowire Li-ion battery, and (iii) a porous-carbon vanadium flow battery. The results demonstrate the feasibility of nondestructive "impedance imaging" to infer microstructural statistics of random, heterogeneous materials.

Tract-Specific Analyses of Diffusion Tensor Imaging Show Widespread White Matter Compromise in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Shukla, Dinesh K.; Keehn, Brandon; Muller, Ralph-Axel

2011-01-01

Background: Previous diffusion tensor imaging (DTI) studies have shown white matter compromise in children and adults with autism spectrum disorder (ASD), which may relate to reduced connectivity and impaired function of distributed networks. However, tract-specific evidence remains limited in ASD. We applied tract-based spatial statistics (TBSS)…

Fluid Registration of Diffusion Tensor Images Using Information Theory

PubMed Central

Chiang, Ming-Chang; Leow, Alex D.; Klunder, Andrea D.; Dutton, Rebecca A.; Barysheva, Marina; Rose, Stephen E.; McMahon, Katie L.; de Zubicaray, Greig I.; Toga, Arthur W.; Thompson, Paul M.

2008-01-01

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data. PMID:18390342

EVOLUTION OF THE MAGNETIC FIELD LINE DIFFUSION COEFFICIENT AND NON-GAUSSIAN STATISTICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snodin, A. P.; Ruffolo, D.; Matthaeus, W. H.

The magnetic field line random walk (FLRW) plays an important role in the transport of energy and particles in turbulent plasmas. For magnetic fluctuations that are transverse or almost transverse to a large-scale mean magnetic field, theories describing the FLRW usually predict asymptotic diffusion of magnetic field lines perpendicular to the mean field. Such theories often depend on the assumption that one can relate the Lagrangian and Eulerian statistics of the magnetic field via Corrsin’s hypothesis, and additionally take the distribution of magnetic field line displacements to be Gaussian. Here we take an ordinary differential equation (ODE) model with thesemore » underlying assumptions and test how well it describes the evolution of the magnetic field line diffusion coefficient in 2D+slab magnetic turbulence, by comparisons to computer simulations that do not involve such assumptions. In addition, we directly test the accuracy of the Corrsin approximation to the Lagrangian correlation. Over much of the studied parameter space we find that the ODE model is in fairly good agreement with computer simulations, in terms of both the evolution and asymptotic values of the diffusion coefficient. When there is poor agreement, we show that this can be largely attributed to the failure of Corrsin’s hypothesis rather than the assumption of Gaussian statistics of field line displacements. The degree of non-Gaussianity, which we measure in terms of the kurtosis, appears to be an indicator of how well Corrsin’s approximation works.« less

Computing Rates of Small Molecule Diffusion Through Protein Channels Using Markovian Milestoning

NASA Astrophysics Data System (ADS)

Abrams, Cameron

2014-03-01

Measuring diffusion rates of ligands plays a key role in understanding the kinetic processes inside proteins. For example, although many molecular simulation studies have reported free energy barriers to infer rates for CO diffusion in myoglobin (Mb), they typically do not include direct calculation of diffusion rates because of the long simulation times needed to infer these rates with statistical accuracy. We show in this talk how to apply Markovian milestoning along minimum free-energy pathways to calculate diffusion rates of CO inside Mb. In Markovian milestoning, one partitions a suitable reaction coordinate space into regions and performs restrained molecular dynamics in each region to accumulate kinetic statistics that, when assembled across regions, provides an estimate of the mean first-passage time between states. The mean escape time for CO directly from the so-called distal pocket (DP) through the histidine gate (HG) is estimated at about 24 ns, confirming the importance of this portal for CO. But Mb is known to contain several internal cavities, and cavity-to-cavity diffusion rates are also computed and used to build a complete kinetic network as a Markov state model. Within this framework, the effective mean time of escape to the solvent through HG increases to 30 ns. Our results suggest that carrier protein structure may have evolved under pressure to modulate dissolved gas release rates using a network of ligand-accessible cavities. Support: NIH R01GM100472.

A comparative assessment of preclinical chemotherapeutic response of tumors using quantitative non-Gaussian diffusion MRI

PubMed Central

Xu, Junzhong; Li, Ke; Smith, R. Adam; Waterton, John C.; Zhao, Ping; Ding, Zhaohua; Does, Mark D.; Manning, H. Charles; Gore, John C.

2016-01-01

Background Diffusion-weighted MRI (DWI) signal attenuation is often not mono-exponential (i.e. non-Gaussian diffusion) with stronger diffusion weighting. Several non-Gaussian diffusion models have been developed and may provide new information or higher sensitivity compared with the conventional apparent diffusion coefficient (ADC) method. However the relative merits of these models to detect tumor therapeutic response is not fully clear. Methods Conventional ADC, and three widely-used non-Gaussian models, (bi-exponential, stretched exponential, and statistical model), were implemented and compared for assessing SW620 human colon cancer xenografts responding to barasertib, an agent known to induce apoptosis via polyploidy. Bayesian Information Criterion (BIC) was used for model selection among all three non-Gaussian models. Results All of tumor volume, histology, conventional ADC, and three non-Gaussian DWI models could show significant differences between control and treatment groups after four days of treatment. However, only the non-Gaussian models detected significant changes after two days of treatment. For any treatment or control group, over 65.7% of tumor voxels indicate the bi-exponential model is strongly or very strongly preferred. Conclusion Non-Gaussian DWI model-derived biomarkers are capable of detecting tumor earlier chemotherapeutic response of tumors compared with conventional ADC and tumor volume. The bi-exponential model provides better fitting compared with statistical and stretched exponential models for the tumor and treatment models used in the current work. PMID:27919785

Surface Transportation Weather Decision Support Requirements - Executive Summary, Version 1.0

DOT National Transportation Integrated Search

1999-12-16

WEATHER: IT AFFECTS THE VISIBILITY, TRACTABILITY, MANEUVERABILITY, VEHICLE STABILITY, EXHAUST EMISSIONS AND STRUCTURAL INTEGRITY OF THE SURFACE TRANSPORTATION SYSTEM. THEREBY WEATHER AFFECTS THE SAFETY, MOBILITY, PRODUCTIVITY AND ENVIRONMENTAL IMPACT...

Dielectrophoresis enhances the whitening effect of carbamide peroxide on enamel.

PubMed

Ivanoff, Chris S; Hottel, Timothy L; Garcia-Godoy, Franklin; Riga, Alan T

2011-10-01

To compare the enamel whitening effect of a 20-minute dielectrophoresis enhanced electrochemical delivery to a 20-minute diffusion treatment. Forty freshly extracted human teeth without detectable caries or restoration were stored in distilled water at 4 degrees C and used within 1 month of extraction. Two different bleaching gels (Plus White 5 Minute Speed Whitening Gel and 35% Opalescence PF gel) were tested. The study had two parts: Part 1--Quantitative comparison of hydrogen peroxide (H2O2, HP) absorption--following application of an over-the-counter 35% HP whitening gel (Plus White 5 Minute Speed Whitening Gel) to 30 (n = 30) extracted human teeth by conventional diffusion or dielectrophoresis. The amount of H2O2 that diffused from the dentin was measured by a colorimetric oxidation-reduction reaction kit. HP concentration was measured by UV-Vis spectroscopy at 550 nm. Part 2--HP diffusion in stained teeth--35% carbamide peroxide whitening gel (35% Opalescence PF gel) was applied to 10 extracted human teeth (n = 10) stained by immersion in a black tea solution for 48 hours. The teeth were randomly assigned to the 20-minute dielectrophoresis or diffusion treatment group; whitening was evaluated by a dental spectrophotometer and macro-photography. Part 1: The analysis found significant differences between both groups with relative percent errors of 3% or less (a single outlier had an RPE of 12%). The average absorbance for the dielectrophoresis group in round 1 was 79% greater than the diffusion group. The average absorbance for the dielectrophoresis group in round 2 was 130% greater than the diffusion group. A single-factor ANOVA found a statistically significant difference between the diffusion and dielectrophoresis groups (P = 0.01). Part 2--The average change in Shade Guide Units (SGU) was 0.6 for the diffusion group, well under the error of measurement of 0.82 SGU. The average change in SGU for the dielectrophoresis group was 9, significantly above the error of measurement and 14 times or 1,400% greater than the diffusion group average. A single-factor ANOVA found a statistically significant difference between the diffusion and dielectrophoresis treatment groups (P < 0.001).

On modeling animal movements using Brownian motion with measurement error.

PubMed

Pozdnyakov, Vladimir; Meyer, Thomas; Wang, Yu-Bo; Yan, Jun

2014-02-01

Modeling animal movements with Brownian motion (or more generally by a Gaussian process) has a long tradition in ecological studies. The recent Brownian bridge movement model (BBMM), which incorporates measurement errors, has been quickly adopted by ecologists because of its simplicity and tractability. We discuss some nontrivial properties of the discrete-time stochastic process that results from observing a Brownian motion with added normal noise at discrete times. In particular, we demonstrate that the observed sequence of random variables is not Markov. Consequently the expected occupation time between two successively observed locations does not depend on just those two observations; the whole path must be taken into account. Nonetheless, the exact likelihood function of the observed time series remains tractable; it requires only sparse matrix computations. The likelihood-based estimation procedure is described in detail and compared to the BBMM estimation.

High-grade glioma diffusive modeling using statistical tissue information and diffusion tensors extracted from atlases.

PubMed

Roniotis, Alexandros; Manikis, Georgios C; Sakkalis, Vangelis; Zervakis, Michalis E; Karatzanis, Ioannis; Marias, Kostas

2012-03-01

Glioma, especially glioblastoma, is a leading cause of brain cancer fatality involving highly invasive and neoplastic growth. Diffusive models of glioma growth use variations of the diffusion-reaction equation in order to simulate the invasive patterns of glioma cells by approximating the spatiotemporal change of glioma cell concentration. The most advanced diffusive models take into consideration the heterogeneous velocity of glioma in gray and white matter, by using two different discrete diffusion coefficients in these areas. Moreover, by using diffusion tensor imaging (DTI), they simulate the anisotropic migration of glioma cells, which is facilitated along white fibers, assuming diffusion tensors with different diffusion coefficients along each candidate direction of growth. Our study extends this concept by fully exploiting the proportions of white and gray matter extracted by normal brain atlases, rather than discretizing diffusion coefficients. Moreover, the proportions of white and gray matter, as well as the diffusion tensors, are extracted by the respective atlases; thus, no DTI processing is needed. Finally, we applied this novel glioma growth model on real data and the results indicate that prognostication rates can be improved. © 2012 IEEE

A comparison between protein crystals grown with vapor diffusion methods in microgravity and protein crystals using a gel liquid-liquid diffusion ground-based method

NASA Technical Reports Server (NTRS)

Miller, Teresa Y.; He, Xiao-Min; Carter, Daniel C.

1992-01-01

Crystals of human serum albumin have been successfully grown in a variety of gels using crystallization conditions otherwise equivalent to those utilized in the popular hanging-drop vapor-equilibrium method. Preliminary comparisons of gel grown crystals with crystals grown by the vapor diffusion method via both ground-based and microgravity methods indicate that crystals superior in size and quality may be grown by limiting solutal convection. Preliminary X-ray diffraction statistics are presented.

From creation and annihilation operators to statistics

NASA Astrophysics Data System (ADS)

Hoyuelos, M.

2018-01-01

A procedure to derive the partition function of non-interacting particles with exotic or intermediate statistics is presented. The partition function is directly related to the associated creation and annihilation operators that obey some specific commutation or anti-commutation relations. The cases of Gentile statistics, quons, Polychronakos statistics, and ewkons are considered. Ewkons statistics was recently derived from the assumption of free diffusion in energy space (Hoyuelos and Sisterna, 2016); an ideal gas of ewkons has negative pressure, a feature that makes them suitable for the description of dark energy.

Altered Development of White Matter in Youth at High Familial Risk for Bipolar Disorder: A Diffusion Tensor Imaging Study

ERIC Educational Resources Information Center

Versace, Amelia; Ladouceur, Cecile D.; Romero, Soledad; Birmaher, Boris; Axelson, David A.; Kupfer, David J.; Phillips, Mary L.

2010-01-01

Objective: To study white matter (WM) development in youth at high familial risk for bipolar disorder (BD). WM alterations are reported in youth and adults with BD. WM undergoes important maturational changes in adolescence. Age-related changes in WM microstructure using diffusion tensor imaging with tract-based spatial statistics in healthy…

Approximation of epidemic models by diffusion processes and their statistical inference.

PubMed

Guy, Romain; Larédo, Catherine; Vergu, Elisabeta

2015-02-01

Multidimensional continuous-time Markov jump processes [Formula: see text] on [Formula: see text] form a usual set-up for modeling [Formula: see text]-like epidemics. However, when facing incomplete epidemic data, inference based on [Formula: see text] is not easy to be achieved. Here, we start building a new framework for the estimation of key parameters of epidemic models based on statistics of diffusion processes approximating [Formula: see text]. First, previous results on the approximation of density-dependent [Formula: see text]-like models by diffusion processes with small diffusion coefficient [Formula: see text], where [Formula: see text] is the population size, are generalized to non-autonomous systems. Second, our previous inference results on discretely observed diffusion processes with small diffusion coefficient are extended to time-dependent diffusions. Consistent and asymptotically Gaussian estimates are obtained for a fixed number [Formula: see text] of observations, which corresponds to the epidemic context, and for [Formula: see text]. A correction term, which yields better estimates non asymptotically, is also included. Finally, performances and robustness of our estimators with respect to various parameters such as [Formula: see text] (the basic reproduction number), [Formula: see text], [Formula: see text] are investigated on simulations. Two models, [Formula: see text] and [Formula: see text], corresponding to single and recurrent outbreaks, respectively, are used to simulate data. The findings indicate that our estimators have good asymptotic properties and behave noticeably well for realistic numbers of observations and population sizes. This study lays the foundations of a generic inference method currently under extension to incompletely observed epidemic data. Indeed, contrary to the majority of current inference techniques for partially observed processes, which necessitates computer intensive simulations, our method being mostly an analytical approach requires only the classical optimization steps.

PANDA: a pipeline toolbox for analyzing brain diffusion images.

PubMed

Cui, Zaixu; Zhong, Suyu; Xu, Pengfei; He, Yong; Gong, Gaolang

2013-01-01

Diffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MATLAB toolbox named "Pipeline for Analyzing braiN Diffusion imAges" (PANDA) for fully automated processing of brain diffusion images. The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA. Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics [e.g., fractional anisotropy (FA) and mean diffusivity (MD)] that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, PANDA is freely available at http://www.nitrc.org/projects/panda/. This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies.

Diffusion Entropy: A Potential Neuroimaging Biomarker of Bipolar Disorder in the Temporal Pole.

PubMed

Spuhler, Karl; Bartlett, Elizabeth; Ding, Jie; DeLorenzo, Christine; Parsey, Ramin; Huang, Chuan

2018-02-01

Despite much research, bipolar depression remains poorly understood, with no clinically useful biomarkers for its diagnosis. The paralimbic system has become a target for biomarker research, with paralimbic structural connectivity commonly reported to distinguish bipolar patients from controls in tractography-based diffusion MRI studies, despite inconsistent findings in voxel-based studies. The purpose of this analysis was to validate existing findings with traditional diffusion MRI metrics and investigate the utility of a novel diffusion MRI metric, entropy of diffusion, in the search for bipolar depression biomarkers. We performed group-level analysis on 9 un-medicated (6 medication-naïve; 3 medication-free for at least 33 days) bipolar patients in a major depressive episode and 9 matched healthy controls to compare: (1) average mean diffusivity (MD) and fractional anisotropy (FA) and; (2) MD and FA histogram entropy-a statistical measure of distribution homogeneity-in the amygdala, hippocampus, orbitofrontal cortex and temporal pole. We also conducted classification analyses with leave-one-out and separate testing dataset (N = 11) approaches. We did not observe statistically significant differences in average MD or FA between the groups in any region. However, in the temporal pole, we observed significantly lower MD entropy in bipolar patients; this finding suggests a regional difference in MD distributions in the absence of an average difference. This metric allowed us to accurately characterize bipolar patients from controls in leave-one-out (accuracy = 83%) and prediction (accuracy = 73%) analyses. This novel application of diffusion MRI yielded not only an interesting separation between bipolar patients and healthy controls, but also accurately classified bipolar patients from controls. © 2017 Wiley Periodicals, Inc.

PANDA: a pipeline toolbox for analyzing brain diffusion images

PubMed Central

Cui, Zaixu; Zhong, Suyu; Xu, Pengfei; He, Yong; Gong, Gaolang

2013-01-01

Diffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MATLAB toolbox named “Pipeline for Analyzing braiN Diffusion imAges” (PANDA) for fully automated processing of brain diffusion images. The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA. Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics [e.g., fractional anisotropy (FA) and mean diffusivity (MD)] that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, PANDA is freely available at http://www.nitrc.org/projects/panda/. This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies. PMID:23439846

Whole brain fiber-based comparison (FBC)-A tool for diffusion tensor imaging-based cohort studies.

PubMed

Zimmerman-Moreno, Gali; Ben Bashat, Dafna; Artzi, Moran; Nefussy, Beatrice; Drory, Vivian; Aizenstein, Orna; Greenspan, Hayit

2016-02-01

We present a novel method for fiber-based comparison of diffusion tensor imaging (DTI) scans of groups of subjects. The method entails initial preprocessing and fiber reconstruction by tractography of each brain in its native coordinate system. Several diffusion parameters are sampled along each fiber and used in subsequent comparisons. A spatial correspondence between subjects is established based on geometric similarity between fibers in a template set (several choices for template are explored), and fibers in all other subjects. Diffusion parameters between groups are compared statistically for each template fiber. Results are presented at single fiber resolution. As an initial exploratory step in neurological population studies this method points to the locations affected by the pathology of interest, without requiring a hypothesis. It does not make any grouping assumptions on the fibers and no manual intervention is needed. The framework was applied here to 18 healthy subjects and 23 amyotrophic lateral sclerosis (ALS) patients. The results are compatible with previous findings and with the tract based spatial statistics (TBSS) method. Hum Brain Mapp 37:477-490, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

The number statistics and optimal history of non-equilibrium steady states of mortal diffusing particles

NASA Astrophysics Data System (ADS)

Meerson, Baruch

2015-05-01

Suppose that a point-like steady source at x = 0 injects particles into a half-infinite line. The particles diffuse and die. At long times a non-equilibrium steady state sets in, and we assume that it involves many particles. If the particles are non-interacting, their total number N in the steady state is Poisson-distributed with mean \\bar{N} predicted from a deterministic reaction-diffusion equation. Here we determine the most likely density history of this driven system conditional on observing a given N. We also consider two prototypical examples of interacting diffusing particles: (i) a family of mortal diffusive lattice gases with constant diffusivity (as illustrated by the simple symmetric exclusion process with mortal particles), and (ii) random walkers that can annihilate in pairs. In both examples we calculate the variances of the (non-Poissonian) stationary distributions of N.

A few scenarios still do not fit all

NASA Astrophysics Data System (ADS)

Schweizer, Vanessa

2018-05-01

For integrated climate change research, the Scenario Matrix Architecture provides a tractable menu of possible emissions trajectories, socio-economic futures and policy environments. However, the future of decision support may lie in searchable databases.

The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks.

PubMed

Morozova, Tatiana V; Goldman, David; Mackay, Trudy F C; Anholt, Robert R H

2012-02-20

Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms.

White matter involvement in sporadic Creutzfeldt-Jakob disease

PubMed Central

Mandelli, Maria Luisa; DeArmond, Stephen J.; Hess, Christopher P.; Vitali, Paolo; Papinutto, Nico; Oehler, Abby; Miller, Bruce L.; Lobach, Irina V.; Bastianello, Stefano; Geschwind, Michael D.; Henry, Roland G.

2014-01-01

Sporadic Creutzfeldt-Jakob disease is considered primarily a disease of grey matter, although the extent of white matter involvement has not been well described. We used diffusion tensor imaging to study the white matter in sporadic Creutzfeldt-Jakob disease compared to healthy control subjects and to correlated magnetic resonance imaging findings with histopathology. Twenty-six patients with sporadic Creutzfeldt-Jakob disease and nine age- and gender-matched healthy control subjects underwent volumetric T1-weighted and diffusion tensor imaging. Six patients had post-mortem brain analysis available for assessment of neuropathological findings associated with prion disease. Parcellation of the subcortical white matter was performed on 3D T1-weighted volumes using Freesurfer. Diffusion tensor imaging maps were calculated and transformed to the 3D-T1 space; the average value for each diffusion metric was calculated in the total white matter and in regional volumes of interest. Tract-based spatial statistics analysis was also performed to investigate the deeper white matter tracts. There was a significant reduction of mean (P = 0.002), axial (P = 0.0003) and radial (P = 0.0134) diffusivities in the total white matter in sporadic Creutzfeldt-Jakob disease. Mean diffusivity was significantly lower in most white matter volumes of interest (P < 0.05, corrected for multiple comparisons), with a generally symmetric pattern of involvement in sporadic Creutzfeldt-Jakob disease. Mean diffusivity reduction reflected concomitant decrease of both axial and radial diffusivity, without appreciable changes in white matter anisotropy. Tract-based spatial statistics analysis showed significant reductions of mean diffusivity within the white matter of patients with sporadic Creutzfeldt-Jakob disease, mainly in the left hemisphere, with a strong trend (P = 0.06) towards reduced mean diffusivity in most of the white matter bilaterally. In contrast, by visual assessment there was no white matter abnormality either on T2-weighted or diffusion-weighted images. Widespread reduction in white matter mean diffusivity, however, was apparent visibly on the quantitative attenuation coefficient maps compared to healthy control subjects. Neuropathological analysis showed diffuse astrocytic gliosis and activated microglia in the white matter, rare prion deposition and subtle subcortical microvacuolization, and patchy foci of demyelination with no evident white matter axonal degeneration. Decreased mean diffusivity on attenuation coefficient maps might be associated with astrocytic gliosis. We show for the first time significant global reduced mean diffusivity within the white matter in sporadic Creutzfeldt-Jakob disease, suggesting possible primary involvement of the white matter, rather than changes secondary to neuronal degeneration/loss. PMID:25367029

Velocity and displacement statistics in a stochastic model of nonlinear friction showing bounded particle speed

NASA Astrophysics Data System (ADS)

Menzel, Andreas M.

2015-11-01

Diffusion of colloidal particles in a complex environment such as polymer networks or biological cells is a topic of high complexity with significant biological and medical relevance. In such situations, the interaction between the surroundings and the particle motion has to be taken into account. We analyze a simplified diffusion model that includes some aspects of a complex environment in the framework of a nonlinear friction process: at low particle speeds, friction grows linearly with the particle velocity as for regular viscous friction; it grows more than linearly at higher particle speeds; finally, at a maximum of the possible particle speed, the friction diverges. In addition to bare diffusion, we study the influence of a constant drift force acting on the diffusing particle. While the corresponding stationary velocity distributions can be derived analytically, the displacement statistics generally must be determined numerically. However, as a benefit of our model, analytical progress can be made in one case of a special maximum particle speed. The effect of a drift force in this case is analytically determined by perturbation theory. It will be interesting in the future to compare our results to real experimental systems. One realization could be magnetic colloidal particles diffusing through a shear-thickening environment such as starch suspensions, possibly exposed to an external magnetic field gradient.

Cross-frequency and band-averaged response variance prediction in the hybrid deterministic-statistical energy analysis method

NASA Astrophysics Data System (ADS)

Reynders, Edwin P. B.; Langley, Robin S.

2018-08-01

The hybrid deterministic-statistical energy analysis method has proven to be a versatile framework for modeling built-up vibro-acoustic systems. The stiff system components are modeled deterministically, e.g., using the finite element method, while the wave fields in the flexible components are modeled as diffuse. In the present paper, the hybrid method is extended such that not only the ensemble mean and variance of the harmonic system response can be computed, but also of the band-averaged system response. This variance represents the uncertainty that is due to the assumption of a diffuse field in the flexible components of the hybrid system. The developments start with a cross-frequency generalization of the reciprocity relationship between the total energy in a diffuse field and the cross spectrum of the blocked reverberant loading at the boundaries of that field. By making extensive use of this generalization in a first-order perturbation analysis, explicit expressions are derived for the cross-frequency and band-averaged variance of the vibrational energies in the diffuse components and for the cross-frequency and band-averaged variance of the cross spectrum of the vibro-acoustic field response of the deterministic components. These expressions are extensively validated against detailed Monte Carlo analyses of coupled plate systems in which diffuse fields are simulated by randomly distributing small point masses across the flexible components, and good agreement is found.

Signatures of criticality arise from random subsampling in simple population models.

PubMed

Nonnenmacher, Marcel; Behrens, Christian; Berens, Philipp; Bethge, Matthias; Macke, Jakob H

2017-10-01

The rise of large-scale recordings of neuronal activity has fueled the hope to gain new insights into the collective activity of neural ensembles. How can one link the statistics of neural population activity to underlying principles and theories? One attempt to interpret such data builds upon analogies to the behaviour of collective systems in statistical physics. Divergence of the specific heat-a measure of population statistics derived from thermodynamics-has been used to suggest that neural populations are optimized to operate at a "critical point". However, these findings have been challenged by theoretical studies which have shown that common inputs can lead to diverging specific heat. Here, we connect "signatures of criticality", and in particular the divergence of specific heat, back to statistics of neural population activity commonly studied in neural coding: firing rates and pairwise correlations. We show that the specific heat diverges whenever the average correlation strength does not depend on population size. This is necessarily true when data with correlations is randomly subsampled during the analysis process, irrespective of the detailed structure or origin of correlations. We also show how the characteristic shape of specific heat capacity curves depends on firing rates and correlations, using both analytically tractable models and numerical simulations of a canonical feed-forward population model. To analyze these simulations, we develop efficient methods for characterizing large-scale neural population activity with maximum entropy models. We find that, consistent with experimental findings, increases in firing rates and correlation directly lead to more pronounced signatures. Thus, previous reports of thermodynamical criticality in neural populations based on the analysis of specific heat can be explained by average firing rates and correlations, and are not indicative of an optimized coding strategy. We conclude that a reliable interpretation of statistical tests for theories of neural coding is possible only in reference to relevant ground-truth models.

Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology

NASA Astrophysics Data System (ADS)

Alsing, Justin; Wandelt, Benjamin; Feeney, Stephen

2018-07-01

Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions or approximations. Likelihood-free inference generically involves simulating mock data and comparing to the observed data; this comparison in data space suffers from the curse of dimensionality and requires compression of the data to a small number of summary statistics to be tractable. In this paper, we use massive asymptotically optimal data compression to reduce the dimensionality of the data space to just one number per parameter, providing a natural and optimal framework for summary statistic choice for likelihood-free inference. Secondly, we present the first cosmological application of Density Estimation Likelihood-Free Inference (DELFI), which learns a parametrized model for joint distribution of data and parameters, yielding both the parameter posterior and the model evidence. This approach is conceptually simple, requires less tuning than traditional Approximate Bayesian Computation approaches to likelihood-free inference and can give high-fidelity posteriors from orders of magnitude fewer forward simulations. As an additional bonus, it enables parameter inference and Bayesian model comparison simultaneously. We demonstrate DELFI with massive data compression on an analysis of the joint light-curve analysis supernova data, as a simple validation case study. We show that high-fidelity posterior inference is possible for full-scale cosmological data analyses with as few as ˜104 simulations, with substantial scope for further improvement, demonstrating the scalability of likelihood-free inference to large and complex cosmological data sets.

Landscape movements of Anopheles gambiae malaria vector mosquitoes in rural Gambia.

PubMed

Thomas, Christopher J; Cross, Dónall E; Bøgh, Claus

2013-01-01

For malaria control in Africa it is crucial to characterise the dispersal of its most efficient vector, Anopheles gambiae, in order to target interventions and assess their impact spatially. Our study is, we believe, the first to present a statistical model of dispersal probability against distance from breeding habitat to human settlements for this important disease vector. We undertook post-hoc analyses of mosquito catches made in The Gambia to derive statistical dispersal functions for An. gambiae sensu lato collected in 48 villages at varying distances to alluvial larval habitat along the River Gambia. The proportion dispersing declined exponentially with distance, and we estimated that 90% of movements were within 1.7 km. Although a 'heavy-tailed' distribution is considered biologically more plausible due to active dispersal by mosquitoes seeking blood meals, there was no statistical basis for choosing it over a negative exponential distribution. Using a simple random walk model with daily survival and movements previously recorded in Burkina Faso, we were able to reproduce the dispersal probabilities observed in The Gambia. Our results provide an important quantification of the probability of An. gambiae s.l. dispersal in a rural African setting typical of many parts of the continent. However, dispersal will be landscape specific and in order to generalise to other spatial configurations of habitat and hosts it will be necessary to produce tractable models of mosquito movements for operational use. We show that simple random walk models have potential. Consequently, there is a pressing need for new empirical studies of An. gambiae survival and movements in different settings to drive this development.

Efficient kinetic Monte Carlo method for reaction-diffusion problems with spatially varying annihilation rates

NASA Astrophysics Data System (ADS)

Schwarz, Karsten; Rieger, Heiko

2013-03-01

We present an efficient Monte Carlo method to simulate reaction-diffusion processes with spatially varying particle annihilation or transformation rates as it occurs for instance in the context of motor-driven intracellular transport. Like Green's function reaction dynamics and first-passage time methods, our algorithm avoids small diffusive hops by propagating sufficiently distant particles in large hops to the boundaries of protective domains. Since for spatially varying annihilation or transformation rates the single particle diffusion propagator is not known analytically, we present an algorithm that generates efficiently either particle displacements or annihilations with the correct statistics, as we prove rigorously. The numerical efficiency of the algorithm is demonstrated with an illustrative example.

Localized Statistics for DW-MRI Fiber Bundle Segmentation

PubMed Central

Lankton, Shawn; Melonakos, John; Malcolm, James; Dambreville, Samuel; Tannenbaum, Allen

2013-01-01

We describe a method for segmenting neural fiber bundles in diffusion-weighted magnetic resonance images (DWMRI). As these bundles traverse the brain to connect regions, their local orientation of diffusion changes drastically, hence a constant global model is inaccurate. We propose a method to compute localized statistics on orientation information and use it to drive a variational active contour segmentation that accurately models the non-homogeneous orientation information present along the bundle. Initialized from a single fiber path, the proposed method proceeds to capture the entire bundle. We demonstrate results using the technique to segment the cingulum bundle and describe several extensions making the technique applicable to a wide range of tissues. PMID:23652079

Controlling reactivity of nanoporous catalyst materials by tuning reaction product-pore interior interactions: Statistical mechanical modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing; Ackerman, David M.; Lin, Victor S.-Y.

2013-04-02

Statistical mechanical modeling is performed of a catalytic conversion reaction within a functionalized nanoporous material to assess the effect of varying the reaction product-pore interior interaction from attractive to repulsive. A strong enhancement in reactivity is observed not just due to the shift in reaction equilibrium towards completion but also due to enhanced transport within the pore resulting from reduced loading. The latter effect is strongest for highly restricted transport (single-file diffusion), and applies even for irreversible reactions. The analysis is performed utilizing a generalized hydrodynamic formulation of the reaction-diffusion equations which can reliably capture the complex interplay between reactionmore » and restricted transport.« less

Establishing the kinetics of ballistic-to-diffusive transition using directional statistics

NASA Astrophysics Data System (ADS)

Liu, Pai; Heinson, William R.; Sumlin, Benjamin J.; Shen, Kuan-Yu; Chakrabarty, Rajan K.

2018-04-01

We establish the kinetics of ballistic-to-diffusive (BD) transition observed in two-dimensional random walk using directional statistics. Directional correlation is parameterized using the walker's turning angle distribution, which follows the commonly adopted wrapped Cauchy distribution (WCD) function. During the BD transition, the concentration factor (ρ) governing the WCD shape is observed to decrease from its initial value. We next analytically derive the relationship between effective ρ and time, which essentially quantifies the BD transition rate. The prediction of our kinetic expression agrees well with the empirical datasets obtained from correlated random walk simulation. We further connect our formulation with the conventionally used scaling relationship between the walker's mean-square displacement and time.

Color image encryption using random transforms, phase retrieval, chaotic maps, and diffusion

NASA Astrophysics Data System (ADS)

Annaby, M. H.; Rushdi, M. A.; Nehary, E. A.

2018-04-01

The recent tremendous proliferation of color imaging applications has been accompanied by growing research in data encryption to secure color images against adversary attacks. While recent color image encryption techniques perform reasonably well, they still exhibit vulnerabilities and deficiencies in terms of statistical security measures due to image data redundancy and inherent weaknesses. This paper proposes two encryption algorithms that largely treat these deficiencies and boost the security strength through novel integration of the random fractional Fourier transforms, phase retrieval algorithms, as well as chaotic scrambling and diffusion. We show through detailed experiments and statistical analysis that the proposed enhancements significantly improve security measures and immunity to attacks.

Anatomy of particle diffusion

NASA Astrophysics Data System (ADS)

Bringuier, E.

2009-11-01

The paper analyses particle diffusion from a thermodynamic standpoint. The main goal of the paper is to highlight the conceptual connection between particle diffusion, which belongs to non-equilibrium statistical physics, and mechanics, which deals with particle motion, at the level of third-year university courses. We start out from the fact that, near equilibrium, particle transport should occur down the gradient of the chemical potential. This yields Fick's law with two additional advantages. First, splitting the chemical potential into 'mechanical' and 'chemical' contributions shows how transport and mechanics are linked through the diffusivity-mobility relationship. Second, splitting the chemical potential into entropic and energetic contributions discloses the respective roles of entropy maximization and energy minimization in driving diffusion. The paper addresses first unary diffusion, where there is only one mobile species in an immobile medium, and next turns to binary diffusion, where two species are mobile with respect to each other in a fluid medium. The interrelationship between unary and binary diffusivities is brought out and it is shown how binary diffusion reduces to unary diffusion in the limit of high dilution of one species amidst the other one. Self- and mutual diffusion are considered and contrasted within the thermodynamic framework; self-diffusion is a time-dependent manifestation of the Gibbs paradox of mixing.

The relation between statistical power and inference in fMRI

PubMed Central

Wager, Tor D.; Yarkoni, Tal

2017-01-01

Statistically underpowered studies can result in experimental failure even when all other experimental considerations have been addressed impeccably. In fMRI the combination of a large number of dependent variables, a relatively small number of observations (subjects), and a need to correct for multiple comparisons can decrease statistical power dramatically. This problem has been clearly addressed yet remains controversial—especially in regards to the expected effect sizes in fMRI, and especially for between-subjects effects such as group comparisons and brain-behavior correlations. We aimed to clarify the power problem by considering and contrasting two simulated scenarios of such possible brain-behavior correlations: weak diffuse effects and strong localized effects. Sampling from these scenarios shows that, particularly in the weak diffuse scenario, common sample sizes (n = 20–30) display extremely low statistical power, poorly represent the actual effects in the full sample, and show large variation on subsequent replications. Empirical data from the Human Connectome Project resembles the weak diffuse scenario much more than the localized strong scenario, which underscores the extent of the power problem for many studies. Possible solutions to the power problem include increasing the sample size, using less stringent thresholds, or focusing on a region-of-interest. However, these approaches are not always feasible and some have major drawbacks. The most prominent solutions that may help address the power problem include model-based (multivariate) prediction methods and meta-analyses with related synthesis-oriented approaches. PMID:29155843

Anomalous diffusion and scaling in coupled stochastic processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bel, Golan; Nemenman, Ilya

2009-01-01

Inspired by problems in biochemical kinetics, we study statistical properties of an overdamped Langevin processes with the friction coefficient depending on the state of a similar, unobserved, process. Integrating out the latter, we derive the Pocker-Planck the friction coefficient of the first depends on the state of the second. Integrating out the latter, we derive the Focker-Planck equation for the probability distribution of the former. This has the fonn of diffusion equation with time-dependent diffusion coefficient, resulting in an anomalous diffusion. The diffusion exponent can not be predicted using a simple scaling argument, and anomalous scaling appears as well. Themore » diffusion exponent of the Weiss-Havlin comb model is derived as a special case, and the same exponent holds even for weakly coupled processes. We compare our theoretical predictions with numerical simulations and find an excellent agreement. The findings caution against treating biochemical systems with unobserved dynamical degrees of freedom by means of standandard, diffusive Langevin descritpion.« less

Impact of eliminating fracture intersection nodes in multiphase compositional flow simulation

NASA Astrophysics Data System (ADS)

Walton, Kenneth M.; Unger, Andre J. A.; Ioannidis, Marios A.; Parker, Beth L.

2017-04-01

Algebraic elimination of nodes at discrete fracture intersections via the star-delta technique has proven to be a valuable tool for making multiphase numerical simulations more tractable and efficient. This study examines the assumptions of the star-delta technique and exposes its effects in a 3-D, multiphase context for advective and dispersive/diffusive fluxes. Key issues of relative permeability-saturation-capillary pressure (kr-S-Pc) and capillary barriers at fracture-fracture intersections are discussed. This study uses a multiphase compositional, finite difference numerical model in discrete fracture network (DFN) and discrete fracture-matrix (DFM) modes. It verifies that the numerical model replicates analytical solutions and performs adequately in convergence exercises (conservative and decaying tracer, one and two-phase flow, DFM and DFN domains). The study culminates in simulations of a two-phase laboratory experiment in which a fluid invades a simple fracture intersection. The experiment and simulations evoke different invading fluid flow paths by varying fracture apertures as oil invades water-filled fractures and as water invades air-filled fractures. Results indicate that the node elimination technique as implemented in numerical model correctly reproduces the long-term flow path of the invading fluid, but that short-term temporal effects of the capillary traps and barriers arising from the intersection node are lost.

Quantitative MRI in hypomyelinating disorders: Correlation with motor handicap.

PubMed

Steenweg, Marjan E; Wolf, Nicole I; van Wieringen, Wessel N; Barkhof, Frederik; van der Knaap, Marjo S; Pouwels, Petra J W

2016-08-23

To assess the correlation of tissue parameters estimated by quantitative magnetic resonance (MR) techniques and motor handicap in patients with hypomyelination. Twenty-eight patients with different causes of hypomyelination (12 males, 16 females; mean age 10 years) and 61 controls (33 males, 28 females; mean age 8 years) were prospectively investigated. We quantified T2 relaxation time, magnetization transfer ratio, fractional anisotropy, mean, axial, and radial diffusivities, and brain metabolites. We performed measurements in the splenium, parietal deep white matter, and corticospinal tracts in the centrum semiovale. We further analyzed diffusion measures using tract-based spatial statistics. We estimated severity of motor handicap by the gross motor function classification system. We evaluated correlation of handicap with MR measures by linear regression analyses. Fractional anisotropy, magnetization transfer ratio, choline, and N-acetylaspartate/creatine ratio were lower and diffusivities, T2 values, and inositol were higher in patients than in controls. Tract-based spatial statistics showed that these changes were widespread for fractional anisotropy (96% of the white matter skeleton), radial (93%) and mean (84%) diffusivity, and less so for axial diffusivity (20%). Correlation with handicap yielded radial diffusivity and N-acetylaspartate/creatine ratio as strongest independent explanatory variables. Gross motor function classification system grades are in part explained by MR measures. They indicate that mainly lack of myelin and, to a lesser degree, loss of axonal integrity codetermine the degree of motor handicap in patients with hypomyelinating disorders. These MR measures can be used to evaluate strategies that are aimed at promotion of myelination. © 2016 American Academy of Neurology.

The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks

PubMed Central

2012-01-01

Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms. PMID:22348705

Co-evolution for Problem Simplification

NASA Technical Reports Server (NTRS)

Haith, Gary L.; Lohn, Jason D.; Cplombano, Silvano P.; Stassinopoulos, Dimitris

1999-01-01

This paper explores a co-evolutionary approach applicable to difficult problems with limited failure/success performance feedback. Like familiar "predator-prey" frameworks this algorithm evolves two populations of individuals - the solutions (predators) and the problems (prey). The approach extends previous work by rewarding only the problems that match their difficulty to the level of solut,ion competence. In complex problem domains with limited feedback, this "tractability constraint" helps provide an adaptive fitness gradient that, effectively differentiates the candidate solutions. The algorithm generates selective pressure toward the evolution of increasingly competent solutions by rewarding solution generality and uniqueness and problem tractability and difficulty. Relative (inverse-fitness) and absolute (static objective function) approaches to evaluating problem difficulty are explored and discussed. On a simple control task, this co-evolutionary algorithm was found to have significant advantages over a genetic algorithm with either a static fitness function or a fitness function that changes on a hand-tuned schedule.

On dependency properties of the ISIs generated by a two-compartmental neuronal model.

PubMed

Benedetto, Elisa; Sacerdote, Laura

2013-02-01

One-dimensional leaky integrate and fire neuronal models describe interspike intervals (ISIs) of a neuron as a renewal process and disregarding the neuron geometry. Many multi-compartment models account for the geometrical features of the neuron but are too complex for their mathematical tractability. Leaky integrate and fire two-compartment models seem a good compromise between mathematical tractability and an improved realism. They indeed allow to relax the renewal hypothesis, typical of one-dimensional models, without introducing too strong mathematical difficulties. Here, we pursue the analysis of the two-compartment model studied by Lansky and Rodriguez (Phys D 132:267-286, 1999), aiming of introducing some specific mathematical results used together with simulation techniques. With the aid of these methods, we investigate dependency properties of ISIs for different values of the model parameters. We show that an increase of the input increases the strength of the dependence between successive ISIs.

Tractable Pareto Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Robert; Morris, Paul; Khatib, Lina; Venable, Brent

2003-01-01

This paper focuses on temporal constraint problems where the objective is to optimize a set of local preferences for when events occur. In previous work, a subclass of these problems has been formalized as a generalization of Temporal CSPs, and a tractable strategy for optimization has been proposed, where global optimality is defined as maximizing the minimum of the component preference values. This criterion for optimality, which we call 'Weakest Link Optimization' (WLO), is known to have limited practical usefulness because solutions are compared only on the basis of their worst value; thus, there is no requirement to improve the other values. To address this limitation, we introduce a new algorithm that re-applies WLO iteratively in a way that leads to improvement of all the values. We show the value of this strategy by proving that, with suitable preference functions, the resulting solutions are Pareto Optimal.

Three-dimensional stochastic modeling of radiation belts in adiabatic invariant coordinates

NASA Astrophysics Data System (ADS)

Zheng, Liheng; Chan, Anthony A.; Albert, Jay M.; Elkington, Scot R.; Koller, Josef; Horne, Richard B.; Glauert, Sarah A.; Meredith, Nigel P.

2014-09-01

A 3-D model for solving the radiation belt diffusion equation in adiabatic invariant coordinates has been developed and tested. The model, named Radbelt Electron Model, obtains a probabilistic solution by solving a set of Itô stochastic differential equations that are mathematically equivalent to the diffusion equation. This method is capable of solving diffusion equations with a full 3-D diffusion tensor, including the radial-local cross diffusion components. The correct form of the boundary condition at equatorial pitch angle α0=90° is also derived. The model is applied to a simulation of the October 2002 storm event. At α0 near 90°, our results are quantitatively consistent with GPS observations of phase space density (PSD) increases, suggesting dominance of radial diffusion; at smaller α0, the observed PSD increases are overestimated by the model, possibly due to the α0-independent radial diffusion coefficients, or to insufficient electron loss in the model, or both. Statistical analysis of the stochastic processes provides further insights into the diffusion processes, showing distinctive electron source distributions with and without local acceleration.

Modeling and experiments for the time-dependent diffusion coefficient during methane desorption from coal

NASA Astrophysics Data System (ADS)

Cheng-Wu, Li; Hong-Lai, Xue; Cheng, Guan; Wen-biao, Liu

2018-04-01

Statistical analysis shows that in the coal matrix, the diffusion coefficient for methane is time-varying, and its integral satisfies the formula μt κ /(1 + β κ ). Therefore, a so-called dynamic diffusion coefficient model (DDC model) is developed. To verify the suitability and accuracy of the DDC model, a series of gas diffusion experiments were conducted using coal particles of different sizes. The results show that the experimental data can be accurately described by the DDC and bidisperse models, but the fit to the DDC model is slightly better. For all coal samples, as time increases, the effective diffusion coefficient first shows a sudden drop, followed by a gradual decrease before stabilizing at longer times. The effective diffusion coefficient has a negative relationship with the size of the coal particle. Finally, the relationship between the constants of the DDC model and the effective diffusion coefficient is discussed. The constant α (μ/R 2 ) denotes the effective coefficient at the initial time, and the constants κ and β control the attenuation characteristic of the effective diffusion coefficient.

Quantitative differentiation of breast lesions at 3T diffusion-weighted imaging (DWI) using the ratio of distributed diffusion coefficient (DDC).

PubMed

Ertas, Gokhan; Onaygil, Can; Akin, Yasin; Kaya, Handan; Aribal, Erkin

2016-12-01

To investigate the accuracy of diffusion coefficients and diffusion coefficient ratios of breast lesions and of glandular breast tissue from mono- and stretched-exponential models for quantitative diagnosis in diffusion-weighted magnetic resonance imaging (MRI). We analyzed pathologically confirmed 170 lesions (85 benign and 85 malignant) imaged using a 3.0T MR scanner. Small regions of interest (ROIs) focusing on the highest signal intensity for lesions and also for glandular tissue of contralateral breast were obtained. Apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were estimated by performing nonlinear fittings using mono- and stretched-exponential models, respectively. Coefficient ratios were calculated by dividing the lesion coefficient by the glandular tissue coefficient. A stretched exponential model provides significantly better fits then the monoexponential model (P < 0.001): 65% of the better fits for glandular tissue and 71% of the better fits for lesion. High correlation was found in diffusion coefficients (0.99-0.81 and coefficient ratios (0.94) between the models. The highest diagnostic accuracy was found by the DDC ratio (area under the curve [AUC] = 0.93) when compared with lesion DDC, ADC ratio, and lesion ADC (AUC = 0.91, 0.90, 0.90) but with no statistically significant difference (P > 0.05). At optimal thresholds, the DDC ratio achieves 93% sensitivity, 80% specificity, and 87% overall diagnostic accuracy, while ADC ratio leads to 89% sensitivity, 78% specificity, and 83% overall diagnostic accuracy. The stretched exponential model fits better with signal intensity measurements from both lesion and glandular tissue ROIs. Although the DDC ratio estimated by using the model shows a higher diagnostic accuracy than the ADC ratio, lesion DDC, and ADC, it is not statistically significant. J. Magn. Reson. Imaging 2016;44:1633-1641. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusion-weighted imaging of mucinous carcinoma of the breast: evaluation of apparent diffusion coefficient and signal intensity in correlation with histologic findings.

PubMed

Woodhams, Reiko; Kakita, Satoko; Hata, Hirofumi; Iwabuchi, Keiichi; Umeoka, Shigeaki; Mountford, Carolyn E; Hatabu, Hiroto

2009-07-01

The purposes of this study were to compare the apparent diffusion coefficient (ADC) of mucinous carcinoma of the breast with that of other breast tumors and to analyze correlations between signal intensity on diffusion-weighted images and the histologic features of mucinous carcinoma. Two hundred seventy-six patients with 277 lesions, including 15 mucinous carcinomas (13 pure type, two mixed type), 204 other malignant tumors, and 58 benign lesions, were examined with 1.5-T MRI at b values of 0 and 1,500 s/mm(2). The correlations between cellularity and ADC, homogeneity of signal intensity on diffusion-weighted images, and histopathologic findings were analyzed. The difference was statistically significant (p < 0.05). The mean ADC of mucinous carcinoma (1.8 +/- 0.4 x 10(-3) mm(2)/s) was statistically higher than that of benign lesions (1.3+/- 0.3 x 10(-3) mm(2)/s) and other malignant tumors (0.9 +/- 0.2 x 10(-3) mm(2)/s) (p < 0.001). The ADC of pure type mucinous carcinoma (1.8 +/- 0.3 x 10(-3) mm(2)/s) was higher than that of mixed type mucinous carcinoma (1.2 +/- 0.2 x 10(-3) mm(2)/s) (p < 0.001) and other histologic types (p > 0.05). The correlation between mean cellularity and the ADC of mucinous carcinoma was significant (rho(s) = -0.754; p = 0.001). The homogeneity of signal intensity on diffusion-weighted images correlated with the homogeneity of histologic structures of mucinous carcinoma (p < 0.001; kappa = 0.826). Mucinous carcinoma can be clearly differentiated from other breast tumors on the basis of ADC. The low signal intensity of mucinous carcinoma on diffusion-weighted images appears to reflect the presence of mucin and low cellularity. High signal intensity on diffusion-weighted images may reflect the presence of fibrovascular bundles, increased cell density, or a combination of these features.

Learning Quantitative Sequence-Function Relationships from Massively Parallel Experiments

NASA Astrophysics Data System (ADS)

Atwal, Gurinder S.; Kinney, Justin B.

2016-03-01

A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships—functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes"—directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.

High Resolution Diffusion-Weighted Imaging for Solitary Orbital Tumors : 3D Turbo Field Echo with Diffusion-Sensitized Driven-Equilibrium (DSDE-TFE) Preparation Technique.

PubMed

Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Kikuchi, Kazufumi; Yoshikawa, Hiroshi; Obara, Makoto; Honda, Hiroshi

2018-06-01

To differentiate cystic from solid solitary intraorbital tumors using 3D turbo field echo with diffusion-sensitized driven-equilibrium preparation without contrast material. This retrospective study was approved by our institutional review boards, and written informed consent was waived. A total of 26 patients with intraorbital tumors were studied. Motion probing gradients were conducted at one direction with b‑values of 0 and 500 s/mm 2 . The voxel size was 1.5 × 1.5 × 1.5 mm 3 , and acquisition time was 5 min 22 s. Additionally, fat-suppressed T2-weighted imaging (T2WI) and T1WI were obtained. The apparent diffusion coefficients (ADC) of the lesions were measured. Signal intensity on conventional magnetic resonance imaging (MRI) compared to normal appearing white matter was also measured. Statistical analysis was performed with Mann-Whitney U-test, the Steel-Dwass test and the receiver operating characteristic (ROC) analysis. There were 10 cystic (7 dermoids, 2 epidermoids, and 1 cystadenoma) and 16 solid (8 cavernous hemangiomas, 6 pleomorphic adenomas, 1 adenocarcinoma, and 1 sebaceous carcinoma) tumors. The ADC of the cystic tumors (mean ± SD; 2.21 ± 0.76 × 10 -3 mm 2 /s) was statistically significantly lower than that of solid tumors (1.43 ± 0.41 × 10 -3 mm 2 /s; P < 0.05).; however, there were no statistically significant differences on conventional MRI (P > 0.05). There were no statistically significant differences among tumor subtypes in all parameters (P > 0.05). The ROC analysis showed the best diagnostic performance with ADC (Az = 0.77). With its insensitivity to field inhomogeneity and high spatial resolution, the 3D DSDE-TFE technique enabled us to discriminate cystic tumors from solid tumors.

Non-Gaussian analysis of diffusion weighted imaging in head and neck at 3T: a pilot study in patients with nasopharyngeal carcinoma.

PubMed

Yuan, Jing; Yeung, David Ka Wai; Mok, Greta S P; Bhatia, Kunwar S; Wang, Yi-Xiang J; Ahuja, Anil T; King, Ann D

2014-01-01

To technically investigate the non-Gaussian diffusion of head and neck diffusion weighted imaging (DWI) at 3 Tesla and compare advanced non-Gaussian diffusion models, including diffusion kurtosis imaging (DKI), stretched-exponential model (SEM), intravoxel incoherent motion (IVIM) and statistical model in the patients with nasopharyngeal carcinoma (NPC). After ethics approval was granted, 16 patients with NPC were examined using DWI performed at 3T employing an extended b-value range from 0 to 1500 s/mm(2). DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models on primary tumor, metastatic node, spinal cord and muscle. Non-Gaussian parameter maps were generated and compared to apparent diffusion coefficient (ADC) maps in NPC. Diffusion in NPC exhibited non-Gaussian behavior at the extended b-value range. Non-Gaussian models achieved significantly better fitting of DWI signal than the mono-exponential model. Non-Gaussian diffusion coefficients were substantially different from mono-exponential ADC both in magnitude and histogram distribution. Non-Gaussian diffusivity in head and neck tissues and NPC lesions could be assessed by using non-Gaussian diffusion models. Non-Gaussian DWI analysis may reveal additional tissue properties beyond ADC and holds potentials to be used as a complementary tool for NPC characterization.

Random walk, diffusion and mixing in simulations of scalar transport in fluid flows

NASA Astrophysics Data System (ADS)

Klimenko, A. Y.

2008-12-01

Physical similarity and mathematical equivalence of continuous diffusion and particle random walk form one of the cornerstones of modern physics and the theory of stochastic processes. In many applied models used in simulation of turbulent transport and turbulent combustion, mixing between particles is used to reflect the influence of the continuous diffusion terms in the transport equations. We show that the continuous scalar transport and diffusion can be accurately specified by means of mixing between randomly walking Lagrangian particles with scalar properties and assess errors associated with this scheme. This gives an alternative formulation for the stochastic process which is selected to represent the continuous diffusion. This paper focuses on statistical errors and deals with relatively simple cases, where one-particle distributions are sufficient for a complete description of the problem.

Efficiency of exchange schemes in replica exchange

NASA Astrophysics Data System (ADS)

Lingenheil, Martin; Denschlag, Robert; Mathias, Gerald; Tavan, Paul

2009-08-01

In replica exchange simulations a fast diffusion of the replicas through the temperature space maximizes the efficiency of the statistical sampling. Here, we compare the diffusion speed as measured by the round trip rates for four exchange algorithms. We find different efficiency profiles with optimal average acceptance probabilities ranging from 8% to 41%. The best performance is determined by benchmark simulations for the most widely used algorithm, which alternately tries to exchange all even and all odd replica pairs. By analytical mathematics we show that the excellent performance of this exchange scheme is due to the high diffusivity of the underlying random walk.

Tackling the achilles' heel of genetic testing.

PubMed

Watkins, Hugh

2015-01-14

Assigning pathogenicity to rare genetic variants is at its hardest with the enormous titin gene, but comprehensive genomic analysis makes the task more tractable (Roberts et al., this issue). Copyright © 2015, American Association for the Advancement of Science.

Effects of Disturbance on Populations of Marine Mammals

DTIC Science & Technology

2014-09-30

relation between foraging success of mothers and pup production (reproductive rate). Second, we we used mark-recapture models to quantify the...responses to disturbance are not necessarily surrogate measures of population-level responses is widely understood. However, without tractable

[REBEn: space of diffusion of hospital nursing knowledge --from 1951 to 2001].

PubMed

Porto, Isaura Setenta; de Catrib, Paula Regina Virgínio Moraes; de Oliveira, Lilian Felippe Duarte; de Figueiredo, Nébia Maria Almeida

2003-01-01

Research on the scientific production on Hospital Nursing published by REBEn. Classify the articles published from 1951 to 2001 and analyze this Review as a space for the diffusion of knowledge in that area. Concept of cultural diffusion and its constituent historical processes. Form applied in 254 articles. Data were submitted to descriptive statistics and led to the following categories: "production of articles in the concerning areas", "articles' scope", "types of articles", and "articles' origin". Our findings showed significant scientific production in those areas within the focused scopes and types of articles. Our conclusions indicate REBEn as a representative space of national diffusion of knowledge on hospital nursing and professional culture, contributing to the development of Nursing as a science.

Modeling of adsorption dynamics at air-liquid interfaces using statistical rate theory (SRT).

PubMed

Biswas, M E; Chatzis, I; Ioannidis, M A; Chen, P

2005-06-01

A large number of natural and technological processes involve mass transfer at interfaces. Interfacial properties, e.g., adsorption, play a key role in such applications as wetting, foaming, coating, and stabilizing of liquid films. The mechanistic understanding of surface adsorption often assumes molecular diffusion in the bulk liquid and subsequent adsorption at the interface. Diffusion is well described by Fick's law, while adsorption kinetics is less understood and is commonly described using Langmuir-type empirical equations. In this study, a general theoretical model for adsorption kinetics/dynamics at the air-liquid interface is developed; in particular, a new kinetic equation based on the statistical rate theory (SRT) is derived. Similar to many reported kinetic equations, the new kinetic equation also involves a number of parameters, but all these parameters are theoretically obtainable. In the present model, the adsorption dynamics is governed by three dimensionless numbers: psi (ratio of adsorption thickness to diffusion length), lambda (ratio of square of the adsorption thickness to the ratio of adsorption to desorption rate constant), and Nk (ratio of the adsorption rate constant to the product of diffusion coefficient and bulk concentration). Numerical simulations for surface adsorption using the proposed model are carried out and verified. The difference in surface adsorption between the general and the diffusion controlled model is estimated and presented graphically as contours of deviation. Three different regions of adsorption dynamics are identified: diffusion controlled (deviation less than 10%), mixed diffusion and transfer controlled (deviation in the range of 10-90%), and transfer controlled (deviation more than 90%). These three different modes predominantly depend on the value of Nk. The corresponding ranges of Nk for the studied values of psi (10(-2)

[A correlation between diffusion kurtosis imaging and the proliferative activity of brain glioma].

PubMed

Tonoyan, A S; Pronin, I N; Pitshelauri, D I; Shishkina, L V; Fadeeva, L M; Pogosbekyan, E L; Zakharova, N E; Shults, E I; Khachanova, N V; Kornienko, V N; Potapov, A A

2015-01-01

The aim of the study was to assess the capabilities of diffusion kurtosis imaging (DKI) in diagnosis of the glioma proliferative activity and to evaluate a relationship between the glioma proliferative activity index and diffusion parameters of the contralateral normal appearing white matter (CNAWM). The study included 47 patients with newly diagnosed brain gliomas (23 low grade, 13 grade III, and 11 grade IV gliomas). We determined a relationship between absolute and normalized parameters of the diffusion tensor (mean (MD), axial (AD), and radial (RD) diffusivities; fractional (FA) and relative (RA) anisotropies) and diffusion kurtosis (mean (MK), axial (AK), and radial (RK) kurtosis; kurtosis anisotropy (KA)) and the proliferative activity index in the most malignant glioma parts (p<0.05). We also established a relationship between the tensor and kurtosis parameters of CNAWM and the glioma proliferative activity index (p<0.05). The correlation between all the absolute and normalized diffusion parameters and the glioma proliferative activity index, except absolute and normalized FA and RA values, was found to be statistically significant (p<0.05). Kurtosis (MK, AK, and RK) and anisotropy (KA, FA, RA) values increased, and diffusivity (MD, AD, RD) values decreased as the glioma proliferative activity index increased. A strong correlation between the proliferative activity index and absolute RK (r=0,71; p=0.000001) and normalized values of MK (r=0.8; p=0.000001), AK (r=0.71; p=0.000001), RK (r=0.81; p=0.000001), and RD (r=-0.71; p=0.000001) was found. A weak, but statistically significant correlation between the glioma proliferative activity index and diffusion values RK (r=-0.36; p=0.014), KA (r=-0.39; p=0.007), RD (r=0.35; p=0.017), FA (r=-0.42; p=0.003), and RA (r=-0.41; p=0.004) of CNAWM was found. DKI has good capabilities to detect immunohistochemical changes in gliomas. DKI demonstrated a high sensitivity in detection of microstructural changes in the contralateral normal appearing white matter in patients with brain gliomas.

Limbic and corpus callosum aberrations in adolescents with bipolar disorder: a tract-based spatial statistics analysis.

PubMed

Barnea-Goraly, Naama; Chang, Kiki D; Karchemskiy, Asya; Howe, Meghan E; Reiss, Allan L

2009-08-01

Bipolar disorder (BD) is a common and debilitating condition, often beginning in adolescence. Converging evidence from genetic and neuroimaging studies indicates that white matter abnormalities may be involved in BD. In this study, we investigated white matter structure in adolescents with familial bipolar disorder using diffusion tensor imaging (DTI) and a whole brain analysis. We analyzed DTI images using tract-based spatial statistics (TBSS), a whole-brain voxel-by-voxel analysis, to investigate white matter structure in 21 adolescents with BD, who also were offspring of at least one parent with BD, and 18 age- and IQ-matched control subjects. Fractional anisotropy (FA; a measure of diffusion anisotropy), trace values (average diffusivity), and apparent diffusion coefficient (ADC; a measure of overall diffusivity) were used as variables in this analysis. In a post hoc analysis, we correlated between FA values, behavioral measures, and medication exposure. Adolescents with BD had lower FA values than control subjects in the fornix, the left mid-posterior cingulate gyrus, throughout the corpus callosum, in fibers extending from the fornix to the thalamus, and in parietal and occipital corona radiata bilaterally. There were no significant between-group differences in trace or ADC values and no significant correlation between behavioral measures, medication exposure, and FA values. Significant white matter tract alterations in adolescents with BD were observed in regions involved in emotional, behavioral, and cognitive regulation. These results suggest that alterations in white matter are present early in the course of disease in familial BD.

A potential risk of overestimating apparent diffusion coefficient in parotid glands.

PubMed

Liu, Yi-Jui; Lee, Yi-Hsiung; Chang, Hing-Chiu; Huang, Teng-Yi; Chiu, Hui-Chu; Wang, Chih-Wei; Chiou, Ta-Wei; Hsu, Kang; Juan, Chun-Jung; Huang, Guo-Shu; Hsu, Hsian-He

2015-01-01

To investigate transient signal loss on diffusion weighted images (DWI) and overestimation of apparent diffusion coefficient (ADC) in parotid glands using single shot echoplanar DWI (EPDWI). This study enrolled 6 healthy subjects and 7 patients receiving radiotherapy. All participants received dynamic EPDWI with a total of 8 repetitions. Imaging quality of DWI was evaluated. Probability of severe overestimation of ADC (soADC), defined by an ADC ratio more than 1.2, was calculated. Error on T2WI, DWI, and ADC was computed. Statistical analysis included paired Student t testing and Mann-Whitney U test. A P value less than 0.05 was considered statistically significant. Transient signal loss was visually detected on some excitations of DWI but not on T2WI or mean DWI. soADC occurred randomly among 8 excitations and 3 directions of diffusion encoding gradients. Probability of soADC was significantly higher in radiotherapy group (42.86%) than in healthy group (24.39%). The mean error percentage decreased as the number of excitations increased on all images, and, it was smallest on T2WI, followed by DWI and ADC in an increasing order. Transient signal loss on DWI was successfully detected by dynamic EPDWI. The signal loss on DWI and overestimation of ADC could be partially remedied by increasing the number of excitations.

Statistical analysis of particle trajectories in living cells

NASA Astrophysics Data System (ADS)

Briane, Vincent; Kervrann, Charles; Vimond, Myriam

2018-06-01

Recent advances in molecular biology and fluorescence microscopy imaging have made possible the inference of the dynamics of molecules in living cells. Such inference allows us to understand and determine the organization and function of the cell. The trajectories of particles (e.g., biomolecules) in living cells, computed with the help of object tracking methods, can be modeled with diffusion processes. Three types of diffusion are considered: (i) free diffusion, (ii) subdiffusion, and (iii) superdiffusion. The mean-square displacement (MSD) is generally used to discriminate the three types of particle dynamics. We propose here a nonparametric three-decision test as an alternative to the MSD method. The rejection of the null hypothesis, i.e., free diffusion, is accompanied by claims of the direction of the alternative (subdiffusion or superdiffusion). We study the asymptotic behavior of the test statistic under the null hypothesis and under parametric alternatives which are currently considered in the biophysics literature. In addition, we adapt the multiple-testing procedure of Benjamini and Hochberg to fit with the three-decision-test setting, in order to apply the test procedure to a collection of independent trajectories. The performance of our procedure is much better than the MSD method as confirmed by Monte Carlo experiments. The method is demonstrated on real data sets corresponding to protein dynamics observed in fluorescence microscopy.

Motor programme activating therapy influences adaptive brain functions in multiple sclerosis: clinical and MRI study.

PubMed

Rasova, Kamila; Prochazkova, Marie; Tintera, Jaroslav; Ibrahim, Ibrahim; Zimova, Denisa; Stetkarova, Ivana

2015-03-01

There is still little scientific evidence for the efficacy of neurofacilitation approaches and their possible influence on brain plasticity and adaptability. In this study, the outcome of a new kind of neurofacilitation approach, motor programme activating therapy (MPAT), was evaluated on the basis of a set of clinical functions and with MRI. Eighteen patients were examined four times with standardized clinical tests and diffusion tensor imaging to monitor changes without therapy, immediately after therapy and 1 month after therapy. Moreover, the strength of effective connectivity was analysed before and after therapy. Patients underwent a 1-h session of MPAT twice a week for 2 months. The data were analysed by nonparametric tests of association and were subsequently statistically evaluated. The therapy led to significant improvement in clinical functions, significant increment of fractional anisotropy and significant decrement of mean diffusivity, and decrement of effective connectivity at supplementary motor areas was observed immediately after the therapy. Changes in clinical functions and diffusion tensor images persisted 1 month after completing the programme. No statistically significant changes in clinical functions and no differences in MRI-diffusion tensor images were observed without physiotherapy. Positive immediate and long-term effects of MPAT on clinical and brain functions, as well as brain microstructure, were confirmed.

DTI segmentation by statistical surface evolution.

PubMed

Lenglet, Christophe; Rousson, Mikaël; Deriche, Rachid

2006-06-01

We address the problem of the segmentation of cerebral white matter structures from diffusion tensor images (DTI). A DTI produces, from a set of diffusion-weighted MR images, tensor-valued images where each voxel is assigned with a 3 x 3 symmetric, positive-definite matrix. This second order tensor is simply the covariance matrix of a local Gaussian process, with zero-mean, modeling the average motion of water molecules. As we will show in this paper, the definition of a dissimilarity measure and statistics between such quantities is a nontrivial task which must be tackled carefully. We claim and demonstrate that, by using the theoretically well-founded differential geometrical properties of the manifold of multivariate normal distributions, it is possible to improve the quality of the segmentation results obtained with other dissimilarity measures such as the Euclidean distance or the Kullback-Leibler divergence. The main goal of this paper is to prove that the choice of the probability metric, i.e., the dissimilarity measure, has a deep impact on the tensor statistics and, hence, on the achieved results. We introduce a variational formulation, in the level-set framework, to estimate the optimal segmentation of a DTI according to the following hypothesis: Diffusion tensors exhibit a Gaussian distribution in the different partitions. We must also respect the geometric constraints imposed by the interfaces existing among the cerebral structures and detected by the gradient of the DTI. We show how to express all the statistical quantities for the different probability metrics. We validate and compare the results obtained on various synthetic data-sets, a biological rat spinal cord phantom and human brain DTIs.

Diffuse ultraviolet erythemal irradiance on inclined planes: a comparison of experimental and modeled data.

PubMed

Utrillas, María P; Marín, María J; Esteve, Anna R; Estellés, Victor; Tena, Fernando; Cañada, Javier; Martínez-Lozano, José A

2009-01-01

Values of measured and modeled diffuse UV erythemal irradiance (UVER) for all sky conditions are compared on planes inclined at 40 degrees and oriented north, south, east and west. The models used for simulating diffuse UVER are of the geometric-type, mainly the Isotropic, Klucher, Hay, Muneer, Reindl and Schauberger models. To analyze the precision of the models, some statistical estimators were used such as root mean square deviation, mean absolute deviation and mean bias deviation. It was seen that all the analyzed models reproduce adequately the diffuse UVER on the south-facing plane, with greater discrepancies for the other inclined planes. When the models are applied to cloud-free conditions, the errors obtained are higher because the anisotropy of the sky dome acquires more importance and the models do not provide the estimation of diffuse UVER accurately.

A model of non-Gaussian diffusion in heterogeneous media

NASA Astrophysics Data System (ADS)

Lanoiselée, Yann; Grebenkov, Denis S.

2018-04-01

Recent progress in single-particle tracking has shown evidence of the non-Gaussian distribution of displacements in living cells, both near the cellular membrane and inside the cytoskeleton. Similar behavior has also been observed in granular materials, turbulent flows, gels and colloidal suspensions, suggesting that this is a general feature of diffusion in complex media. A possible interpretation of this phenomenon is that a tracer explores a medium with spatio-temporal fluctuations which result in local changes of diffusivity. We propose and investigate an ergodic, easily interpretable model, which implements the concept of diffusing diffusivity. Depending on the parameters, the distribution of displacements can be either flat or peaked at small displacements with an exponential tail at large displacements. We show that the distribution converges slowly to a Gaussian one. We calculate statistical properties, derive the asymptotic behavior and discuss some implications and extensions.

On the cosmic ray diffusion in a violent interstellar medium

NASA Technical Reports Server (NTRS)

Bykov, A. M.; Toptygin, I. N.

1985-01-01

A variety of the available observational data on the cosmic ray (CR) spectrum, anisotropy and composition are in good agreement with a suggestion on the diffusion propagation of CR with energy below 10(15) eV in the interstellar medium. The magnitude of the CR diffusion coefficient and its energy dependence are determined by interstellar medium (ISM) magnetic field spectra. Direct observational data on magnetic field spectra are still absent. A theoretical model to the turbulence generation in the multiphase ISM is resented. The model is based on the multiple generation of secondary shocks and concomitant large-scale rarefactions due to supernova shock interactions with interstellar clouds. The distribution function for ISM shocks are derived to include supernova statistics, diffuse cloud distribution, and various shock wave propagation regimes. This permits calculation of the ISM magnetic field fluctuation spectrum and CR diffusion coefficient for the hot phase of ISM.

Implementation of jump-diffusion algorithms for understanding FLIR scenes

NASA Astrophysics Data System (ADS)

Lanterman, Aaron D.; Miller, Michael I.; Snyder, Donald L.

1995-07-01

Our pattern theoretic approach to the automated understanding of forward-looking infrared (FLIR) images brings the traditionally separate endeavors of detection, tracking, and recognition together into a unified jump-diffusion process. New objects are detected and object types are recognized through discrete jump moves. Between jumps, the location and orientation of objects are estimated via continuous diffusions. An hypothesized scene, simulated from the emissive characteristics of the hypothesized scene elements, is compared with the collected data by a likelihood function based on sensor statistics. This likelihood is combined with a prior distribution defined over the set of possible scenes to form a posterior distribution. The jump-diffusion process empirically generates the posterior distribution. Both the diffusion and jump operations involve the simulation of a scene produced by a hypothesized configuration. Scene simulation is most effectively accomplished by pipelined rendering engines such as silicon graphics. We demonstrate the execution of our algorithm on a silicon graphics onyx/reality engine.

Hybrid MD-Nernst Planck Model of Alpha-hemolysin Conductance Properties

NASA Technical Reports Server (NTRS)

Cozmuta, Ioana; O'Keefer, James T.; Bose, Deepak; Stolc, Viktor

2006-01-01

Motivated by experiments in which an applied electric field translocates polynucleotides through an alpha-hemolysin protein channel causing ionic current transient blockade, a hybrid simulation model is proposed to predict the conductance properties of the open channel. Time scales corresponding to ion permeation processes are reached using the Poisson-Nemst-Planck (PNP) electro-diffusion model in which both solvent and local ion concentrations are represented as a continuum. The diffusion coefficients of the ions (K(+) and Cl(-)) input in the PNP model are, however, calculated from all-atom molecular dynamics (MD). In the MD simulations, a reduced representation of the channel is used. The channel is solvated in a 1 M KCI solution, and an external electric field is applied. The pore specific diffusion coefficients for both ionic species are reduced 5-7 times in comparison to bulk values. Significant statistical variations (17-45%) of the pore-ions diffusivities are observed. Within the statistics, the ionic diffusivities remain invariable for a range of external applied voltages between 30 and 240mV. In the 2D-PNP calculations, the pore stem is approximated by a smooth cylinder of radius approx. 9A with two constriction blocks where the radius is reduced to approx. 6A. The electrostatic potential includes the contribution from the atomistic charges. The MD-PNP model shows that the atomic charges are responsible for the rectifying behaviour and for the slight anion selectivity of the a-hemolysin pore. Independent of the hierarchy between the anion and cation diffusivities, the anionic contribution to the total ionic current will dominate. The predictions of the MD-PNP model are in good agreement with experimental data and give confidence in the present approach of bridging time scales by combining a microscopic and macroscopic model.

White matter alterations in college football players: a longitudinal diffusion tensor imaging study.

PubMed

Mayinger, Michael Christian; Merchant-Borna, Kian; Hufschmidt, Jakob; Muehlmann, Marc; Weir, Isabelle Ruth; Rauchmann, Boris-Stephan; Shenton, Martha Elizabeth; Koerte, Inga Katharina; Bazarian, Jeffrey John

2018-02-01

The aim of this study was to evaluate longitudinal changes in the diffusion characteristics of brain white matter (WM) in collegiate athletes at three time points: prior to the start of the football season (T1), after one season of football (T2), followed by six months of no-contact rest (T3). Fifteen male collegiate football players and 5 male non-athlete student controls underwent diffusion MR imaging and computerized cognitive testing at all three timepoints. Whole-brain tract-based spatial statistics (TBSS) were used to compare fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and trace between all timepoints. Average diffusion values were obtained from statistically significant clusters for each individual. No athlete suffered a concussion during the study period. After one season of play (T1 to T2), we observed a significant increase in trace in a cluster located in the brainstem and left temporal lobe, and a significant increase in FA in the left parietal lobe. After six months of no-contact rest (T2 to T3), there was a significant decrease in trace and FA in clusters that were partially overlapping or in close proximity with the initial clusters (T1 to T2), with no significant changes from T1 to T3. Repetitive head impacts (RHI) sustained during a single football season may result in alterations of the brain's WM in collegiate football players. These changes appear to return to baseline after 6 months of no-contact rest, suggesting remission of WM alterations. Our preliminary results suggest that collegiate football players might benefit from periods without exposure to RHI.

Predicting the drying properties of sludge based on hydrothermal treatment under subcritical conditions.

PubMed

Mäkelä, Mikko; Fraikin, Laurent; Léonard, Angélique; Benavente, Verónica; Fullana, Andrés

2016-03-15

The effects of hydrothermal treatment on the drying properties of sludge were determined. Sludge was hydrothermally treated at 180-260 °C for 0.5-5 h using NaOH and HCl as additives to influence reaction conditions. Untreated sludge and attained hydrochar samples were then dried under identical conditions with a laboratory microdryer and an X-ray microtomograph was used to follow changes in sample dimensions. The effective moisture diffusivities of sludge and hydrochar samples were determined and the effect of process conditions on respective mean diffusivities evaluated using multiple linear regression. Based on the results the drying time of untreated sludge decreased from approximately 80 min to 37-59 min for sludge hydrochar. Drying of untreated sludge was governed by the falling rate period where drying flux decreased continuously as a function of sludge moisture content due to heat and mass transfer limitations and sample shrinkage. Hydrothermal treatment increased the drying flux of sludge hydrochar and decreased the effect of internal heat and mass transfer limitations and sample shrinkage especially at higher treatment temperatures. The determined effective moisture diffusivities of sludge and hydrochar increased as a function of decreasing moisture content and the mean diffusivity of untreated sludge (8.56·10(-9) m(2) s(-1)) and sludge hydrochar (12.7-27.5·10(-9) m(2) s(-1)) were found statistically different. The attained regression model indicated that treatment temperature governed the mean diffusivity of hydrochar, as the effects of NaOH and HCl were statistically insignificant. The attained results enabled prediction of sludge drying properties through mean moisture diffusivity based on hydrothermal treatment conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Investigation of Dental Luting Cement Solubility as a Function of the Marginal Gap.

DTIC Science & Technology

1988-05-01

way ANOVA for the Phase 1 Diffusion Study revealed that there were statistically significant differences between the test groups. A Duncan’s Multiple...cement. The 25, 50, and 75 micron groups demonstrated no statistically significant differences in the amount of remaining luting cement. ( p< 0.05) A...one-way ANOVA was also performed on Phase 2 Dynamic Study. This test revealed that there were statistically significant differences among the test

Analysis of ligand-protein exchange by Clustering of Ligand Diffusion Coefficient Pairs (CoLD-CoP)

NASA Astrophysics Data System (ADS)

Snyder, David A.; Chantova, Mihaela; Chaudhry, Saadia

2015-06-01

NMR spectroscopy is a powerful tool in describing protein structures and protein activity for pharmaceutical and biochemical development. This study describes a method to determine weak binding ligands in biological systems by using hierarchic diffusion coefficient clustering of multidimensional data obtained with a 400 MHz Bruker NMR. Comparison of DOSY spectrums of ligands of the chemical library in the presence and absence of target proteins show translational diffusion rates for small molecules upon interaction with macromolecules. For weak binders such as compounds found in fragment libraries, changes in diffusion rates upon macromolecular binding are on the order of the precision of DOSY diffusion measurements, and identifying such subtle shifts in diffusion requires careful statistical analysis. The "CoLD-CoP" (Clustering of Ligand Diffusion Coefficient Pairs) method presented here uses SAHN clustering to identify protein-binders in a chemical library or even a not fully characterized metabolite mixture. We will show how DOSY NMR and the "CoLD-CoP" method complement each other in identifying the most suitable candidates for lysozyme and wheat germ acid phosphatase.

Brain morphological and microstructural features in cryptogenic late-onset temporal lobe epilepsy: a structural and diffusion MRI study.

PubMed

Sone, Daichi; Sato, Noriko; Kimura, Yukio; Watanabe, Yutaka; Okazaki, Mitsutoshi; Matsuda, Hiroshi

2018-06-01

Although epilepsy in the elderly has attracted attention recently, there are few systematic studies of neuroimaging in such patients. In this study, we used structural MRI and diffusion tensor imaging (DTI) to investigate the morphological and microstructural features of the brain in late-onset temporal lobe epilepsy (TLE). We recruited patients with TLE and an age of onset > 50 years (late-TLE group) and age- and sex-matched healthy volunteers (control group). 3-Tesla MRI scans, including 3D T1-weighted images and 15-direction DTI, showed normal findings on visual assessment in both groups. We used Statistical Parametric Mapping 12 (SPM12) for gray and white matter structural normalization and comparison and used Tract-Based Spatial Statistics (TBSS) for fractional anisotropy and mean diffusivity comparisons of DTI. In both methods, p < 0.05 (family-wise error) was considered statistically significant. In total, 30 patients with late-onset TLE (mean ± SD age, 66.8 ± 8.4; mean ± SD age of onset, 63.0 ± 7.6 years) and 40 healthy controls (mean ± SD age, 66.6 ± 8.5 years) were enrolled. The late-onset TLE group showed significant gray matter volume increases in the bilateral amygdala and anterior hippocampus and significantly reduced mean diffusivity in the left temporofrontal lobe, internal capsule, and brainstem. No significant changes were evident in white matter volume or fractional anisotropy. Our findings may reflect some characteristics or mechanisms of cryptogenic TLE in the elderly, such as inflammatory processes.

[Application of anoptomagnetic probe Gd-DO3A-EA-FITC in imaging and analyzing the brain interstitial space].

PubMed

Li, Y Q; Sheng, Y; Liang, L; Zhao, Y; Li, H Y; Bai, N; Wang, T; Yuan, L; Han, H B

2018-04-18

To investigate the application of the optical magnetic bimodal molecular probe Gd-DO3A-ethylthiouret-fluorescein isothiocyanate (Gd -DO3A-EA-FITC) in brain tissue imaging and brain interstitial space (ISS). In the study, 24 male SD rats were randomly divided into 3 groups, including magnetic probe group (n=6), optical probe group (n=6) and optical magnetic bimodal probe group (n=12), then the optical magnetic bimodal probe group was divided equally into magnetic probe subgroup (n=6) and optical probe subgroup (n=6). Referencing the brain stereotaxic atlas, the coronal globus pallidus as center level, the probes including gadolinium-diethylene triamine pentaacetic acid (Gd-DTPA), fluorescein isothiocyanate (FITC) and Gd-DO3A-EA-FITC of 2 μL (10 mmol/L) were injected into the caudate nucleus respectively, magnetic resonance imaging (MRI) was performed in the magnetic probe group and magnetic probe subgroup to image the dynamic diffusion and distribution of the probes in the brain ISS, a self-developed brain ISS image processing system was used to measure the diffusion coefficient, clearance, volume fraction and half-time in these two groups. Laser scanning confocal microscope (LSCM) was performed in vitro in the optical probe group and optical probe subgroup for fluorescence imaging at the time points 2 hours after the injection of the probe, and the distribution in the oblique sagittal slice was compared with the result of the first two groups. For the magnetic probe group and magnetic probe subgroup, there were the same imaging results between the probes of Gd-DTPA and Gd-DO3A-EA-FITC. The diffusion parameters of Gd-DTPA and Gd-DO3A-EA-FITC were as follows: the average diffusion coefficients [(3.31±0.11)×10 -4 mm 2 /s vs. (3.37±0.15)×10 -4 mm 2 /s, t=0.942, P=0.360], the clearance [(3.04±0.37) mmol/L vs. (2.90±0.51) mmol/L, t=0.640, P=0.531], the volume fractions (17.18%±0.14% vs. 17.31%±0.15%, t=1.961, P=0.068), the half-time [(86.58±3.31) min vs. (84.61±2.38) min, t=1.412, P=0.177], the diffusion areas [(23.25±0.68) mm 2 vs. (22.71±1.00) mm 2 , t=1.100, P=0.297]. The statistical analysis of each brain was made by t test, and the diffusion parameters were not statistically significant. Moreover, for the optical probe group and optical probe subgroup, the diffusion area of Gd-DO3A-EA-FITC [(22.61±1.16) mm 2 ] was slightly larger than that of FITC [(22.10±1.29) mm 2 ], the statistical analysis of each brain was made by t test, and the diffusion parameters were not statistically significant (t=0.713, P=0.492). Gd-DO3A-EA-FITC shows the same imaging results as the traditional GD-DTPA, and it can be used in measuring brain ISS.

Conditional statistics in a turbulent premixed flame derived from direct numerical simulation

NASA Technical Reports Server (NTRS)

Mantel, Thierry; Bilger, Robert W.

1994-01-01

The objective of this paper is to briefly introduce conditional moment closure (CMC) methods for premixed systems and to derive the transport equation for the conditional species mass fraction conditioned on the progress variable based on the enthalpy. Our statistical analysis will be based on the 3-D DNS database of Trouve and Poinsot available at the Center for Turbulence Research. The initial conditions and characteristics (turbulence, thermo-diffusive properties) as well as the numerical method utilized in the DNS of Trouve and Poinsot are presented, and some details concerning our statistical analysis are also given. From the analysis of DNS results, the effects of the position in the flame brush, of the Damkoehler and Lewis numbers on the conditional mean scalar dissipation, and conditional mean velocity are presented and discussed. Information concerning unconditional turbulent fluxes are also presented. The anomaly found in previous studies of counter-gradient diffusion for the turbulent flux of the progress variable is investigated.

Comparison of Experimental Methods for Estimating Matrix Diffusion Coefficients for Contaminant Transport Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Telfeyan, Katherine Christina; Ware, Stuart Douglas; Reimus, Paul William

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%,more » and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.« less

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

NASA Astrophysics Data System (ADS)

Telfeyan, Katherine; Ware, S. Doug; Reimus, Paul W.; Birdsell, Kay H.

2018-02-01

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

Non-Gaussian Analysis of Diffusion Weighted Imaging in Head and Neck at 3T: A Pilot Study in Patients with Nasopharyngeal Carcinoma

PubMed Central

Yuan, Jing; Yeung, David Ka Wai; Mok, Greta S. P.; Bhatia, Kunwar S.; Wang, Yi-Xiang J.; Ahuja, Anil T.; King, Ann D.

2014-01-01

Purpose To technically investigate the non-Gaussian diffusion of head and neck diffusion weighted imaging (DWI) at 3 Tesla and compare advanced non-Gaussian diffusion models, including diffusion kurtosis imaging (DKI), stretched-exponential model (SEM), intravoxel incoherent motion (IVIM) and statistical model in the patients with nasopharyngeal carcinoma (NPC). Materials and Methods After ethics approval was granted, 16 patients with NPC were examined using DWI performed at 3T employing an extended b-value range from 0 to 1500 s/mm2. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models on primary tumor, metastatic node, spinal cord and muscle. Non-Gaussian parameter maps were generated and compared to apparent diffusion coefficient (ADC) maps in NPC. Results Diffusion in NPC exhibited non-Gaussian behavior at the extended b-value range. Non-Gaussian models achieved significantly better fitting of DWI signal than the mono-exponential model. Non-Gaussian diffusion coefficients were substantially different from mono-exponential ADC both in magnitude and histogram distribution. Conclusion Non-Gaussian diffusivity in head and neck tissues and NPC lesions could be assessed by using non-Gaussian diffusion models. Non-Gaussian DWI analysis may reveal additional tissue properties beyond ADC and holds potentials to be used as a complementary tool for NPC characterization. PMID:24466318

Focused Belief Measures for Uncertainty Quantification in High Performance Semantic Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joslyn, Cliff A.; Weaver, Jesse R.

In web-scale semantic data analytics there is a great need for methods which aggregate uncertainty claims, on the one hand respecting the information provided as accurately as possible, while on the other still being tractable. Traditional statistical methods are more robust, but only represent distributional, additive uncertainty. Generalized information theory methods, including fuzzy systems and Dempster-Shafer (DS) evidence theory, represent multiple forms of uncertainty, but are computationally and methodologically difficult. We require methods which provide an effective balance between the complete representation of the full complexity of uncertainty claims in their interaction, while satisfying the needs of both computational complexitymore » and human cognition. Here we build on J{\\o}sang's subjective logic to posit methods in focused belief measures (FBMs), where a full DS structure is focused to a single event. The resulting ternary logical structure is posited to be able to capture the minimal amount of generalized complexity needed at a maximum of computational efficiency. We demonstrate the efficacy of this approach in a web ingest experiment over the 2012 Billion Triple dataset from the Semantic Web Challenge.« less

Probability distribution for the Gaussian curvature of the zero level surface of a random function

NASA Astrophysics Data System (ADS)

Hannay, J. H.

2018-04-01

A rather natural construction for a smooth random surface in space is the level surface of value zero, or ‘nodal’ surface f(x,y,z)  =  0, of a (real) random function f; the interface between positive and negative regions of the function. A physically significant local attribute at a point of a curved surface is its Gaussian curvature (the product of its principal curvatures) because, when integrated over the surface it gives the Euler characteristic. Here the probability distribution for the Gaussian curvature at a random point on the nodal surface f  =  0 is calculated for a statistically homogeneous (‘stationary’) and isotropic zero mean Gaussian random function f. Capitalizing on the isotropy, a ‘fixer’ device for axes supplies the probability distribution directly as a multiple integral. Its evaluation yields an explicit algebraic function with a simple average. Indeed, this average Gaussian curvature has long been known. For a non-zero level surface instead of the nodal one, the probability distribution is not fully tractable, but is supplied as an integral expression.

ADFNE: Open source software for discrete fracture network engineering, two and three dimensional applications

NASA Astrophysics Data System (ADS)

Fadakar Alghalandis, Younes

2017-05-01

Rapidly growing topic, the discrete fracture network engineering (DFNE), has already attracted many talents from diverse disciplines in academia and industry around the world to challenge difficult problems related to mining, geothermal, civil, oil and gas, water and many other projects. Although, there are few commercial software capable of providing some useful functionalities fundamental for DFNE, their costs, closed code (black box) distributions and hence limited programmability and tractability encouraged us to respond to this rising demand with a new solution. This paper introduces an open source comprehensive software package for stochastic modeling of fracture networks in two- and three-dimension in discrete formulation. Functionalities included are geometric modeling (e.g., complex polygonal fracture faces, and utilizing directional statistics), simulations, characterizations (e.g., intersection, clustering and connectivity analyses) and applications (e.g., fluid flow). The package is completely written in Matlab scripting language. Significant efforts have been made to bring maximum flexibility to the functions in order to solve problems in both two- and three-dimensions in an easy and united way that is suitable for beginners, advanced and experienced users.

An efficient method for removing point sources from full-sky radio interferometric maps

NASA Astrophysics Data System (ADS)

Berger, Philippe; Oppermann, Niels; Pen, Ue-Li; Shaw, J. Richard

2017-12-01

A new generation of wide-field radio interferometers designed for 21-cm surveys is being built as drift scan instruments allowing them to observe large fractions of the sky. With large numbers of antennas and frequency channels, the enormous instantaneous data rates of these telescopes require novel, efficient, data management and analysis techniques. The m-mode formalism exploits the periodicity of such data with the sidereal day, combined with the assumption of statistical isotropy of the sky, to achieve large computational savings and render optimal analysis methods computationally tractable. We present an extension to that work that allows us to adopt a more realistic sky model and treat objects such as bright point sources. We develop a linear procedure for deconvolving maps, using a Wiener filter reconstruction technique, which simultaneously allows filtering of these unwanted components. We construct an algorithm, based on the Sherman-Morrison-Woodbury formula, to efficiently invert the data covariance matrix, as required for any optimal signal-to-noise ratio weighting. The performance of our algorithm is demonstrated using simulations of a cylindrical transit telescope.

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology

PubMed Central

Udy, Dylan B.; Voorhies, Mark; Chan, Patricia P.; Lowe, Todd M.; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes—and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics. PMID:26252667

A random matrix approach to language acquisition

NASA Astrophysics Data System (ADS)

Nicolaidis, A.; Kosmidis, Kosmas; Argyrakis, Panos

2009-12-01

Since language is tied to cognition, we expect the linguistic structures to reflect patterns that we encounter in nature and are analyzed by physics. Within this realm we investigate the process of lexicon acquisition, using analytical and tractable methods developed within physics. A lexicon is a mapping between sounds and referents of the perceived world. This mapping is represented by a matrix and the linguistic interaction among individuals is described by a random matrix model. There are two essential parameters in our approach. The strength of the linguistic interaction β, which is considered as a genetically determined ability, and the number N of sounds employed (the lexicon size). Our model of linguistic interaction is analytically studied using methods of statistical physics and simulated by Monte Carlo techniques. The analysis reveals an intricate relationship between the innate propensity for language acquisition β and the lexicon size N, N~exp(β). Thus a small increase of the genetically determined β may lead to an incredible lexical explosion. Our approximate scheme offers an explanation for the biological affinity of different species and their simultaneous linguistic disparity.

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology.

PubMed

Udy, Dylan B; Voorhies, Mark; Chan, Patricia P; Lowe, Todd M; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes-and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics.

Diffusion-weighted magnetic resonance imaging of uterine cervical cancer.

PubMed

Liu, Ying; Bai, Renju; Sun, Haoran; Liu, Haidong; Wang, Dehua

2009-01-01

To determine the feasibility of diffusion-weighted magnetic resonance (MR) imaging (DWI) of uterine cervical cancer and to investigate whether the apparent diffusion coefficient (ADC) values of cervical cancer differ from those of normal cervix and whether they could indicate the histologic type and the pathologic grade of tumor. Forty-two female patients with histopathologically proven uterine cervical cancer and 15 female patients with uterine leiomyomas underwent preoperative MR examinations using a 1.5-T clinical scanner (GE 1.5T Twin-Speed Infinity with Excite II scanner; GE Healthcare, Waukesha, Wis). Scanning sequences included T2-weighted fast spin-echo imaging, T2-weighted fast spin-echo with fat suppression imaging, T1-weighted spin-echo imaging, and DWI with diffusion factors of 0 and 1000 s/mm2. Parameters evaluated consisted of ADC values of uterine cervical cancer and normal cervix. Histologic specimens were stained with hematoxylin and eosin. The cellular densities of 32 uterine cervical cancers were calculated, which were regarded as the ratio of the total area of tumor cell nuclei divided by the area of sample image. Apparent diffusion coefficient value was statistically different (P = 0.000) between normal and cancerous tissue in the uterine cervix; the former one was (mean [SD], 1.50 [0.16]) x 10(-3) mm2/s, and the latter one was (0.88 [0.15]) x 10(-3) mm2/s. Apparent diffusion coefficient value of squamous carcinoma was statistically lower than that of adenocarcinoma (P = 0.040). The ADC value of uterine cervical cancer correlated negatively with cellular density (r = -0.711, P = 0.000) and the grading of tumor (r = -0.778, P = 0.000). Diffusion-weighted MR imaging has a potential ability to differentiate between normal and cancerous tissue in the uterine cervix, and it can indicate the histologic type of uterine cervical cancer as well. The ADC value of uterine cervical cancer represents tumor cellular density, thus providing a new method for evaluating the pathologic grading of tumor.

A Tractable Numerical Model for Exploring Nonadiabatic Quantum Dynamics

ERIC Educational Resources Information Center

Camrud, Evan; Turner, Daniel B.

2017-01-01

Numerous computational and spectroscopic studies have demonstrated the decisive role played by nonadiabatic coupling in photochemical reactions. Nonadiabatic coupling drives photochemistry when potential energy surfaces are nearly degenerate at avoided crossings or truly degenerate at unavoided crossings. The dynamics induced by nonadiabatic…

Analysis of basic clustering algorithms for numerical estimation of statistical averages in biomolecules.

PubMed

Anandakrishnan, Ramu; Onufriev, Alexey

2008-03-01

In statistical mechanics, the equilibrium properties of a physical system of particles can be calculated as the statistical average over accessible microstates of the system. In general, these calculations are computationally intractable since they involve summations over an exponentially large number of microstates. Clustering algorithms are one of the methods used to numerically approximate these sums. The most basic clustering algorithms first sub-divide the system into a set of smaller subsets (clusters). Then, interactions between particles within each cluster are treated exactly, while all interactions between different clusters are ignored. These smaller clusters have far fewer microstates, making the summation over these microstates, tractable. These algorithms have been previously used for biomolecular computations, but remain relatively unexplored in this context. Presented here, is a theoretical analysis of the error and computational complexity for the two most basic clustering algorithms that were previously applied in the context of biomolecular electrostatics. We derive a tight, computationally inexpensive, error bound for the equilibrium state of a particle computed via these clustering algorithms. For some practical applications, it is the root mean square error, which can be significantly lower than the error bound, that may be more important. We how that there is a strong empirical relationship between error bound and root mean square error, suggesting that the error bound could be used as a computationally inexpensive metric for predicting the accuracy of clustering algorithms for practical applications. An example of error analysis for such an application-computation of average charge of ionizable amino-acids in proteins-is given, demonstrating that the clustering algorithm can be accurate enough for practical purposes.

Analytical approach for collective diffusion: One-dimensional lattice with the nearest neighbor and the next nearest neighbor lateral interactions

NASA Astrophysics Data System (ADS)

Tarasenko, Alexander

2018-01-01

Diffusion of particles adsorbed on a homogeneous one-dimensional lattice is investigated using a theoretical approach and MC simulations. The analytical dependencies calculated in the framework of approach are tested using the numerical data. The perfect coincidence of the data obtained by these different methods demonstrates that the correctness of the approach based on the theory of the non-equilibrium statistical operator.

Mapping Ion and Electron Remagnetization Distance in the Reconnection Outflow Exhaust Region with MMS

NASA Astrophysics Data System (ADS)

Sturner, A. P.; Eriksson, S.; Gershman, D. J.; Plaschke, F.; Burch, J.

2017-12-01

Magnetopause current sheets have been fertile ground for understanding kinetic-scale physics of magnetic reconnection, but can also be used to study more macroscopic scale phenomena statistically. Post-reconnection, magnetic flux and plasma are accelerated away from the x-line into exhaust regions. As the exhausting plasma exits the electron diffusion region, electrons become remagnetized and are accelerated by the magnetic field into an E x B jet while the ions remain unmagnetized. Further along the exhaust, at the edge of the ion diffusion region, the ions become frozen into the magnetic field, and are accelerated to join the electrons in the exhaust jet. By assuming a constant reconnection rate of 0.1, we can infer the distance to the x-line from the normal width of the exhaust. We present a statistical study using the Magnetospheric Multiscale Mission (MMS) to map out the electron and ion remagnetization distances that define the edge of the electron and ion diffusion regions for magnetopause reconnection, and explore the effects of a guide magnetic field.

Many Body Effects on Particle Diffusion in Polymer Nanocomposites

NASA Astrophysics Data System (ADS)

Dell, Zachary E.; Schweizer, Kenneth S.

2014-03-01

Recent statistical mechanical theories of nanoparticle motion in polymer melts and networks have focused on the dilute particle limit. By combining PRISM theory predictions for microscopic structural correlations, and a new formulation of self-consistent dynamical mode coupling theory, we extend dilute theories to finite filler loading. As a minimalist model, the polymer dynamics are first assumed to be unperturbed by the presence of the nanoparticles. The long time particle diffusivity in unentangled and entangled melts is determined as a function of polymer tube diameter and radius of gyration, nanoparticle diameter, and polymer-filler attraction strength under both constant volume and constant pressure situations. The influence of nanocomposite statistical structure (depletion, steric stabilization, bridging) on dynamics is also investigated. Using recent theoretical developments for predicting tube diameters in nanocomposites, the consequences of filler-induced tube dilation on nanoparticle motion is established. In entangled melts, increasing filler loading first modestly speeds up diffusion, and then dramatically when the inter-filler separation becomes smaller than the tube diameter. At very high loadings, a filler glass transition is generically predicted.

Including scattering within the room acoustics diffusion model: An analytical approach.

PubMed

Foy, Cédric; Picaut, Judicaël; Valeau, Vincent

2016-10-01

Over the last 20 years, a statistical acoustic model has been developed to predict the reverberant sound field in buildings. This model is based on the assumption that the propagation of the reverberant sound field follows a transport process and, as an approximation, a diffusion process that can be easily solved numerically. This model, initially designed and validated for rooms with purely diffuse reflections, is extended in the present study to mixed reflections, with a proportion of specular and diffuse reflections defined by a scattering coefficient. The proposed mathematical developments lead to an analytical expression of the diffusion constant that is a function of the scattering coefficient, but also on the absorption coefficient of the walls. The results obtained with this extended diffusion model are then compared with the classical diffusion model, as well as with a sound particles tracing approach considering mixed wall reflections. The comparison shows a good agreement for long rooms with uniform low absorption (α = 0.01) and uniform scattering. For a larger absorption (α = 0.1), the agreement is moderate, due to the fact that the proposed expression of the diffusion coefficient does not vary spatially. In addition, the proposed model is for now limited to uniform diffusion and should be extended in the future to more general cases.

Classification of Dynamical Diffusion States in Single Molecule Tracking Microscopy

PubMed Central

Bosch, Peter J.; Kanger, Johannes S.; Subramaniam, Vinod

2014-01-01

Single molecule tracking of membrane proteins by fluorescence microscopy is a promising method to investigate dynamic processes in live cells. Translating the trajectories of proteins to biological implications, such as protein interactions, requires the classification of protein motion within the trajectories. Spatial information of protein motion may reveal where the protein interacts with cellular structures, because binding of proteins to such structures often alters their diffusion speed. For dynamic diffusion systems, we provide an analytical framework to determine in which diffusion state a molecule is residing during the course of its trajectory. We compare different methods for the quantification of motion to utilize this framework for the classification of two diffusion states (two populations with different diffusion speed). We found that a gyration quantification method and a Bayesian statistics-based method are the most accurate in diffusion-state classification for realistic experimentally obtained datasets, of which the gyration method is much less computationally demanding. After classification of the diffusion, the lifetime of the states can be determined, and images of the diffusion states can be reconstructed at high resolution. Simulations validate these applications. We apply the classification and its applications to experimental data to demonstrate the potential of this approach to obtain further insights into the dynamics of cell membrane proteins. PMID:25099798

Effect of Static Compressive Strain, Anisotropy, and Tissue Region on the Diffusion of Glucose in Meniscus Fibrocartilage.

PubMed

Kleinhans, Kelsey L; Jaworski, Lukas M; Schneiderbauer, Michaela M; Jackson, Alicia R

2015-10-01

Osteoarthritis (OA) is a significant socio-economic concern, affecting millions of individuals each year. Degeneration of the meniscus of the knee is often associated with OA, yet the relationship between the two is not well understood. As a nearly avascular tissue, the meniscus must rely on diffusive transport for nutritional supply to cells. Therefore, quantifying structure-function relations for transport properties in meniscus fibrocartilage is an important task. The purpose of the present study was to determine how mechanical loading, tissue anisotropy, and tissue region affect glucose diffusion in meniscus fibrocartilage. A one-dimensional (1D) diffusion experiment was used to measure the diffusion coefficient of glucose in porcine meniscus tissues. Results show that glucose diffusion is strain-dependent, decreasing significantly with increased levels of compression. It was also determined that glucose diffusion in meniscus tissues is anisotropic, with the diffusion coefficient in the circumferential direction being significantly higher than that in the axial direction. Finally, the effect of tissue region was not statistically significant, comparing axial diffusion in the central and horn regions of the tissue. This study is important for better understanding the transport and nutrition-related mechanisms of meniscal degeneration and related OA in the knee.

Regression approach to non-invasive determination of bilirubin in neonatal blood

NASA Astrophysics Data System (ADS)

Lysenko, S. A.; Kugeiko, M. M.

2012-07-01

A statistical ensemble of structural and biophysical parameters of neonatal skin was modeled based on experimental data. Diffuse scattering coefficients of the skin in the visible and infrared regions were calculated by applying a Monte-Carlo method to each realization of the ensemble. The potential accuracy of recovering the bilirubin concentration in dermis (which correlates closely with that in blood) was estimated from spatially resolved spectrometric measurements of diffuse scattering. The possibility to determine noninvasively the bilirubin concentration was shown by measurements of diffuse scattering at λ = 460, 500, and 660 nm at three source-detector separations under conditions of total variability of the skin biophysical parameters.

Separating non-diffuse component from ambient seismic noise cross-correlation in southern California­­

NASA Astrophysics Data System (ADS)

Liu, X.; Beroza, G. C.; Nakata, N.

2017-12-01

Cross-correlation of fully diffuse wavefields provides Green's function between receivers, although the ambient noise field in the real world contains both diffuse and non-diffuse fields. The non-diffuse field potentially degrades the correlation functions. We attempt to blindly separate the diffuse and the non-diffuse components from cross-correlations of ambient seismic noise and analyze the potential bias caused by the non-diffuse components. We compute the 9-component noise cross-correlations for 17 stations in southern California. For the Rayleigh wave components, we assume that the cross-correlation of multiply scattered waves (diffuse component) is independent from the cross-correlation of ocean microseismic quasi-point source responses (non-diffuse component), and the cross-correlation function of ambient seismic data is the sum of both components. Thus we can blindly separate the non-diffuse component due to physical point sources and the more diffuse component due to cross-correlation of multiply scattered noise based on their statistical independence. We also perform beamforming over different frequency bands for the cross-correlations before and after the separation, and we find that the decomposed Rayleigh wave represents more coherent features among all Rayleigh wave polarization cross-correlation components. We show that after separating the non-diffuse component, the Frequency-Time Analysis results are less ambiguous. In addition, we estimate the bias in phase velocity on the raw cross-correlation data due to the non-diffuse component. We also apply this technique to a few borehole stations in Groningen, the Netherlands, to demonstrate its applicability in different instrument/geology settings.

Phylogeography Takes a Relaxed Random Walk in Continuous Space and Time

PubMed Central

Lemey, Philippe; Rambaut, Andrew; Welch, John J.; Suchard, Marc A.

2010-01-01

Research aimed at understanding the geographic context of evolutionary histories is burgeoning across biological disciplines. Recent endeavors attempt to interpret contemporaneous genetic variation in the light of increasingly detailed geographical and environmental observations. Such interest has promoted the development of phylogeographic inference techniques that explicitly aim to integrate such heterogeneous data. One promising development involves reconstructing phylogeographic history on a continuous landscape. Here, we present a Bayesian statistical approach to infer continuous phylogeographic diffusion using random walk models while simultaneously reconstructing the evolutionary history in time from molecular sequence data. Moreover, by accommodating branch-specific variation in dispersal rates, we relax the most restrictive assumption of the standard Brownian diffusion process and demonstrate increased statistical efficiency in spatial reconstructions of overdispersed random walks by analyzing both simulated and real viral genetic data. We further illustrate how drawing inference about summary statistics from a fully specified stochastic process over both sequence evolution and spatial movement reveals important characteristics of a rabies epidemic. Together with recent advances in discrete phylogeographic inference, the continuous model developments furnish a flexible statistical framework for biogeographical reconstructions that is easily expanded upon to accommodate various landscape genetic features. PMID:20203288

Random-phase metasurfaces at optical wavelengths

NASA Astrophysics Data System (ADS)

Pors, Anders; Ding, Fei; Chen, Yiting; Radko, Ilya P.; Bozhevolnyi, Sergey I.

2016-06-01

Random-phase metasurfaces, in which the constituents scatter light with random phases, have the property that an incident plane wave will diffusely scatter, hereby leading to a complex far-field response that is most suitably described by statistical means. In this work, we present and exemplify the statistical description of the far-field response, particularly highlighting how the response for polarised and unpolarised light might be alike or different depending on the correlation of scattering phases for two orthogonal polarisations. By utilizing gap plasmon-based metasurfaces, consisting of an optically thick gold film overlaid by a subwavelength thin glass spacer and an array of gold nanobricks, we design and realize random-phase metasurfaces at a wavelength of 800 nm. Optical characterisation of the fabricated samples convincingly demonstrates the diffuse scattering of reflected light, with statistics obeying the theoretical predictions. We foresee the use of random-phase metasurfaces for camouflage applications and as high-quality reference structures in dark-field microscopy, while the control of the statistics for polarised and unpolarised light might find usage in security applications. Finally, by incorporating a certain correlation between scattering by neighbouring metasurface constituents new types of functionalities can be realised, such as a Lambertian reflector.

Fast mean and variance computation of the diffuse sound transmission through finite-sized thick and layered wall and floor systems

NASA Astrophysics Data System (ADS)

Decraene, Carolina; Dijckmans, Arne; Reynders, Edwin P. B.

2018-05-01

A method is developed for computing the mean and variance of the diffuse field sound transmission loss of finite-sized layered wall and floor systems that consist of solid, fluid and/or poroelastic layers. This is achieved by coupling a transfer matrix model of the wall or floor to statistical energy analysis subsystem models of the adjacent room volumes. The modal behavior of the wall is approximately accounted for by projecting the wall displacement onto a set of sinusoidal lateral basis functions. This hybrid modal transfer matrix-statistical energy analysis method is validated on multiple wall systems: a thin steel plate, a polymethyl methacrylate panel, a thick brick wall, a sandwich panel, a double-leaf wall with poro-elastic material in the cavity, and a double glazing. The predictions are compared with experimental data and with results obtained using alternative prediction methods such as the transfer matrix method with spatial windowing, the hybrid wave based-transfer matrix method, and the hybrid finite element-statistical energy analysis method. These comparisons confirm the prediction accuracy of the proposed method and the computational efficiency against the conventional hybrid finite element-statistical energy analysis method.

The effects of intermittency on statistical characteristics of turbulence and scale similarity of breakdown coefficients

NASA Astrophysics Data System (ADS)

Novikov, E. A.

1990-05-01

The influence of intermittency on turbulent diffusion is expressed in terms of the statistics of the dissipation field. The high-order moments of relative diffusion are obtained by using the concept of scale similarity of the breakdown coefficients (bdc). The method of bdc is useful for obtaining new models and general results, which then can be expressed in terms of multifractals. In particular, the concavity and other properties of spectral codimension are proved. Special attention is paid to the logarithmically periodic modulations. The parametrization of small-scale intermittent turbulence, which can be used for large-eddy simulation, is presented. The effect of molecular viscosity is taken into account in the spirit of the renorm group, but without spectral series, ɛ expansion, and fictitious random forces.

Studies of the phase gradient at the boundary of the phase diffusion equation, motivated by peculiar wave patterns of rhythmic contraction in the amoeboid movement of Physarum polycephalum

NASA Astrophysics Data System (ADS)

Iima, Makoto; Kori, Hiroshi; Nakagaki, Toshiyuki

2017-04-01

The boundary of a cell is the interface with its surroundings and plays a key role in controlling the cell movement adaptations to different environments. We propose a study of the boundary effects on the patterns and waves of the rhythmic contractions in plasmodia of Physarum polycephalum, a tractable model organism of the amoeboid type. Boundary effects are defined as the effects of both the boundary conditions and the boundary shape. The rhythmicity of contraction can be modulated by local stimulation of temperature, light and chemicals, and by local deformation of cell shape via mechanosensitive ion channels as well. First, we examined the effects of boundary cell shapes in the case of a special shape resembling a tadpole, while requiring that the natural frequency in the proximity of the boundary is slightly higher and uniform. The simulation model reproduced the approximate propagated wave, from the tail to the head, while the inward waves were observed only near the periphery of the head section of the tadpole-shape. A key finding was that the frequency of the rhythmic contractions depended on the local shape of cell boundary. This implies that the boundary conditions of the phase were not always homogeneous. To understand the dependency, we reduced the two-dimensional model into a one-dimensional continuum model with Neumann boundary conditions. Here, the boundary conditions reflect the frequency distribution at the boundary. We described the analytic solutions and calculated the relationship between the boundary conditions and the wave propagation for a one-dimensional model of the continuous oscillatory field and a discrete coupled oscillator system. The results obtained may not be limited to cell movement of Physarum, but may be applicable to the other physical systems since the analysis used a generic phase diffusion equation.

Modeling Terminal Velocity

ERIC Educational Resources Information Center

Brand, Neal; Quintanilla, John A.

2013-01-01

Using a simultaneously falling softball as a stopwatch, the terminal velocity of a whiffle ball can be obtained to surprisingly high accuracy with only common household equipment. This classroom activity engages students in an apparently daunting task that nevertheless is tractable, using a simple model and mathematical techniques at their…

Yeast: An Experimental Organism for Modern Biology.

ERIC Educational Resources Information Center

Botstein, David; Fink, Gerald R.

1988-01-01

Discusses the applicability and advantages of using yeasts as popular and ideal model systems for studying and understanding eukaryotic biology at the cellular and molecular levels. Cites experimental tractability and the cooperative tradition of the research community of yeast biologists as reasons for this success. (RT)

Space-Bounded Church-Turing Thesis and Computational Tractability of Closed Systems.

PubMed

Braverman, Mark; Schneider, Jonathan; Rojas, Cristóbal

2015-08-28

We report a new limitation on the ability of physical systems to perform computation-one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory as the maximal amount of information that the evolving system can carry from one instant to the next. We show that memory is a limiting factor in computation even in lieu of any time limitations on the evolving system-such as when considering its equilibrium regime. We call this limitation the space-bounded Church-Turing thesis (SBCT). The SBCT is supported by a simulation assertion (SA), which states that predicting the long-term behavior of bounded-memory systems is computationally tractable. In particular, one corollary of SA is an explicit bound on the computational hardness of the long-term behavior of a discrete-time finite-dimensional dynamical system that is affected by noise. We prove such a bound explicitly.

Space-Bounded Church-Turing Thesis and Computational Tractability of Closed Systems

NASA Astrophysics Data System (ADS)

Braverman, Mark; Schneider, Jonathan; Rojas, Cristóbal

2015-08-01

We report a new limitation on the ability of physical systems to perform computation—one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory as the maximal amount of information that the evolving system can carry from one instant to the next. We show that memory is a limiting factor in computation even in lieu of any time limitations on the evolving system—such as when considering its equilibrium regime. We call this limitation the space-bounded Church-Turing thesis (SBCT). The SBCT is supported by a simulation assertion (SA), which states that predicting the long-term behavior of bounded-memory systems is computationally tractable. In particular, one corollary of SA is an explicit bound on the computational hardness of the long-term behavior of a discrete-time finite-dimensional dynamical system that is affected by noise. We prove such a bound explicitly.

Exploiting Bounded Signal Flow for Graph Orientation Based on Cause-Effect Pairs

NASA Astrophysics Data System (ADS)

Dorn, Britta; Hüffner, Falk; Krüger, Dominikus; Niedermeier, Rolf; Uhlmann, Johannes

We consider the following problem: Given an undirected network and a set of sender-receiver pairs, direct all edges such that the maximum number of "signal flows" defined by the pairs can be routed respecting edge directions. This problem has applications in communication networks and in understanding protein interaction based cell regulation mechanisms. Since this problem is NP-hard, research so far concentrated on polynomial-time approximation algorithms and tractable special cases. We take the viewpoint of parameterized algorithmics and examine several parameters related to the maximum signal flow over vertices or edges. We provide several fixed-parameter tractability results, and in one case a sharp complexity dichotomy between a linear-time solvable case and a slightly more general NP-hard case. We examine the value of these parameters for several real-world network instances. For many relevant cases, the NP-hard problem can be solved to optimality. In this way, parameterized analysis yields both deeper insight into the computational complexity and practical solving strategies.

Analysis of tractable distortion metrics for EEG compression applications.

PubMed

Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cárdenas-Barrera, Julián; Cruz-Roldán, Fernando

2012-07-01

Coding distortion in lossy electroencephalographic (EEG) signal compression methods is evaluated through tractable objective criteria. The percentage root-mean-square difference, which is a global and relative indicator of the quality held by reconstructed waveforms, is the most widely used criterion. However, this parameter does not ensure compliance with clinical standard guidelines that specify limits to allowable noise in EEG recordings. As a result, expert clinicians may have difficulties interpreting the resulting distortion of the EEG for a given value of this parameter. Conversely, the root-mean-square error is an alternative criterion that quantifies distortion in understandable units. In this paper, we demonstrate that the root-mean-square error is better suited to control and to assess the distortion introduced by compression methods. The experiments conducted in this paper show that the use of the root-mean-square error as target parameter in EEG compression allows both clinicians and scientists to infer whether coding error is clinically acceptable or not at no cost for the compression ratio.

Framework for cascade size calculations on random networks

NASA Astrophysics Data System (ADS)

Burkholz, Rebekka; Schweitzer, Frank

2018-04-01

We present a framework to calculate the cascade size evolution for a large class of cascade models on random network ensembles in the limit of infinite network size. Our method is exact and applies to network ensembles with almost arbitrary degree distribution, degree-degree correlations, and, in case of threshold models, for arbitrary threshold distribution. With our approach, we shift the perspective from the known branching process approximations to the iterative update of suitable probability distributions. Such distributions are key to capture cascade dynamics that involve possibly continuous quantities and that depend on the cascade history, e.g., if load is accumulated over time. As a proof of concept, we provide two examples: (a) Constant load models that cover many of the analytically tractable casacade models, and, as a highlight, (b) a fiber bundle model that was not tractable by branching process approximations before. Our derivations cover the whole cascade dynamics, not only their steady state. This allows us to include interventions in time or further model complexity in the analysis.

Multivariate statistical analysis of diffusion imaging parameters using partial least squares: Application to white matter variations in Alzheimer's disease.

PubMed

Konukoglu, Ender; Coutu, Jean-Philippe; Salat, David H; Fischl, Bruce

2016-07-01

Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer's and Huntington's diseases (Salat et al., 2010; Rosas et al., 2006). The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as diffusion tensor imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer's disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: "are there regions in the white matter where Alzheimer's disease has a different effect than aging or similar effect as aging?" and "are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer's disease but with differing multivariate effects?" Copyright © 2016 Elsevier Inc. All rights reserved.

Multivariate Statistical Analysis of Diffusion Imaging Parameters using Partial Least Squares: Application to White Matter Variations in Alzheimer’s Disease

PubMed Central

Konukoglu, Ender; Coutu, Jean-Philippe; Salat, David H.; Fischl, Bruce

2016-01-01

Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer’s and Huntington’s diseases1,2. The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as Diffusion Tensor Imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer’s disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: “are there regions in the white matter where Alzheimer’s disease has a different effect than aging or similar effect as aging?” and “are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer’s disease but with differing multivariate effects?” PMID:27103138

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

DOE PAGES

Telfeyan, Katherine Christina; Ware, Stuart Doug; Reimus, Paul William; ...

2018-01-31

Here, diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged frommore » 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.« less

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Telfeyan, Katherine Christina; Ware, Stuart Doug; Reimus, Paul William

Here, diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged frommore » 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.« less

Long-range correlations, geometrical structure, and transport properties of macromolecular solutions. The equivalence of configurational statistics and geometrodynamics of large molecules.

PubMed

Mezzasalma, Stefano A

2007-12-04

A special theory of Brownian relativity was previously proposed to describe the universal picture arising in ideal polymer solutions. In brief, it redefines a Gaussian macromolecule in a 4-dimensional diffusive spacetime, establishing a (weak) Lorentz-Poincaré invariance between liquid and polymer Einstein's laws for Brownian movement. Here, aimed at inquiring into the effect of correlations, we deepen the extension of the special theory to a general formulation. The previous statistical equivalence, for dynamic trajectories of liquid molecules and static configurations of macromolecules, and rather obvious in uncorrelated systems, is enlarged by a more general principle of equivalence, for configurational statistics and geometrodynamics. Accordingly, the three geodesic motion, continuity, and field equations could be rewritten, and a number of scaling behaviors were recovered in a spacetime endowed with general static isotropic metric (i.e., for equilibrium polymer solutions). We also dealt with universality in the volume fraction and, unexpectedly, found that a hyperscaling relation of the form, (average size) x (diffusivity) x (viscosity)1/2 ~f(N0, phi0) is fulfilled in several regimes, both in the chain monomer number (N) and polymer volume fraction (phi). Entangled macromolecular dynamics was treated as a geodesic light deflection, entaglements acting in close analogy to the field generated by a spherically symmetric mass source, where length fluctuations of the chain primitive path behave as azimuth fluctuations of its shape. Finally, the general transformation rule for translational and diffusive frames gives a coordinate gauge invariance, suggesting a widened Lorentz-Poincaré symmetry for Brownian statistics. We expect this approach to find effective applications to solutions of arbitrarily large molecules displaying a variety of structures, where the effect of geometry is more explicit and significant in itself (e.g., surfactants, lipids, proteins).

Quantitative analysis of diffusion tensor orientation: theoretical framework.

PubMed

Wu, Yu-Chien; Field, Aaron S; Chung, Moo K; Badie, Benham; Alexander, Andrew L

2004-11-01

Diffusion-tensor MRI (DT-MRI) yields information about the magnitude, anisotropy, and orientation of water diffusion of brain tissues. Although white matter tractography and eigenvector color maps provide visually appealing displays of white matter tract organization, they do not easily lend themselves to quantitative and statistical analysis. In this study, a set of visual and quantitative tools for the investigation of tensor orientations in the human brain was developed. Visual tools included rose diagrams, which are spherical coordinate histograms of the major eigenvector directions, and 3D scatterplots of the major eigenvector angles. A scatter matrix of major eigenvector directions was used to describe the distribution of major eigenvectors in a defined anatomic region. A measure of eigenvector dispersion was developed to describe the degree of eigenvector coherence in the selected region. These tools were used to evaluate directional organization and the interhemispheric symmetry of DT-MRI data in five healthy human brains and two patients with infiltrative diseases of the white matter tracts. In normal anatomical white matter tracts, a high degree of directional coherence and interhemispheric symmetry was observed. The infiltrative diseases appeared to alter the eigenvector properties of affected white matter tracts, showing decreased eigenvector coherence and interhemispheric symmetry. This novel approach distills the rich, 3D information available from the diffusion tensor into a form that lends itself to quantitative analysis and statistical hypothesis testing. (c) 2004 Wiley-Liss, Inc.

Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants.

PubMed

Anjari, Mustafa; Srinivasan, Latha; Allsop, Joanna M; Hajnal, Joseph V; Rutherford, Mary A; Edwards, A David; Counsell, Serena J

2007-04-15

Infants born preterm have a high incidence of neurodevelopmental impairment in later childhood, often associated with poorly defined cerebral white matter abnormalities. Diffusion tensor imaging quantifies the diffusion of water within tissues and can assess microstructural abnormalities in the developing preterm brain. Tract-based spatial statistics (TBSS) is an automated observer-independent method of aligning fractional anisotropy (FA) images from multiple subjects to allow groupwise comparisons of diffusion tensor imaging data. We applied TBSS to test the hypothesis that preterm infants have reduced fractional anisotropy in specific regions of white matter compared to term-born controls. We studied 26 preterm infants with no evidence of focal lesions on conventional magnetic resonance imaging (MRI) at term equivalent age and 6 healthy term-born control infants. We found that the centrum semiovale, frontal white matter and the genu of the corpus callosum showed significantly lower FA in the preterm group. Infants born at less than or equal to 28 weeks gestational age (n=11) displayed additional reductions in FA in the external capsule, the posterior aspect of the posterior limb of the internal capsule and the isthmus and middle portion of the body of the corpus callosum. This study demonstrates that TBSS provides an observer-independent method of identifying white matter abnormalities in the preterm brain at term equivalent age in the absence of focal lesions.

Manual dexterity and brain structure in patients with schizophrenia: A whole-brain magnetic resonance imaging study.

PubMed

Hidese, Shinsuke; Ota, Miho; Sasayama, Daimei; Matsuo, Junko; Ishida, Ikki; Hiraishi, Moeko; Teraishi, Toshiya; Hattori, Kotaro; Kunugi, Hiroshi

2018-04-14

The Purdue Pegboard Test (PPT) is a motor coordination task used to assess manual dexterity. Although several brain regions are thought to be involved in PPT performance, the relationship of the task with decreased insular volume has not been investigated. The PPT was administered to 83 subjects diagnosed with schizophrenia (mean ± standard deviation age: 38.6 ± 11.2 years; 47 males, 36 females) and 130 healthy controls (42.1 ± 15.2 years; 67 males, 63 females). All subjects were Japanese and right-handed. Gray matter volume was analyzed using voxel-based morphometry in statistical parametric mapping, while white matter measures were analyzed using diffusion tensor imaging in tract-based spatial statistics. For the patients with schizophrenia, the left-hand scores positively correlated with the right insular and bilateral operculum volumes, while the summation score (sum of left-, right-, and both-hands scores) positively correlated with the right insular volume, and the summation and assembly (number of assemblies completed) scores correlated with the diffuse white matter fractional anisotropy, axial diffusivity, and radial diffusivity values. In contrast, no significant correlations were found for the controls. These results suggested that decreased insular volume and white matter measures contributed to the impairments in manual dexterity observed in subjects with schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Bayesian framework for modeling diffusion processes with nonlinear drift based on nonlinear and incomplete observations.

PubMed

Wu, Hao; Noé, Frank

2011-03-01

Diffusion processes are relevant for a variety of phenomena in the natural sciences, including diffusion of cells or biomolecules within cells, diffusion of molecules on a membrane or surface, and diffusion of a molecular conformation within a complex energy landscape. Many experimental tools exist now to track such diffusive motions in single cells or molecules, including high-resolution light microscopy, optical tweezers, fluorescence quenching, and Förster resonance energy transfer (FRET). Experimental observations are most often indirect and incomplete: (1) They do not directly reveal the potential or diffusion constants that govern the diffusion process, (2) they have limited time and space resolution, and (3) the highest-resolution experiments do not track the motion directly but rather probe it stochastically by recording single events, such as photons, whose properties depend on the state of the system under investigation. Here, we propose a general Bayesian framework to model diffusion processes with nonlinear drift based on incomplete observations as generated by various types of experiments. A maximum penalized likelihood estimator is given as well as a Gibbs sampling method that allows to estimate the trajectories that have caused the measurement, the nonlinear drift or potential function and the noise or diffusion matrices, as well as uncertainty estimates of these properties. The approach is illustrated on numerical simulations of FRET experiments where it is shown that trajectories, potentials, and diffusion constants can be efficiently and reliably estimated even in cases with little statistics or nonequilibrium measurement conditions.

The effects of temperature and NaCl concentration on tetragonal lysozyme face growth rates

NASA Technical Reports Server (NTRS)

Forsythe, Elizabeth; Pusey, Marc Lee

1994-01-01

Measurements were made of the (110) and (101) face growth rates of the tetragonal form of hen egg white lysozyme at 0.1M sodium acetate buffer, pH 4.0, from 4 to 22 C and with 3.0%, 5.0%, and 7.0% NaCl used as the precipitating salt. The data were collected at supersaturation ratios ranging from approximately 4 to approximately 63. Both decreasing temperature and increasing salt concentrations shifted plots of the growth rate versus C/C(sat) to the right, i.e. higher supersaturations were required for comparable growth rates. The observed trends in the growth data are counter to those expected from the solubility data. If tetragonal lysozyme crystal growth is by addition of ordered aggregates from the solution, then the observed growth data could be explained as a result of the effects of lowered temperature and increased salt concentration on the kinetics and equilibrium processes governing protein-protein interactions in solution. The data indicate that temperature would be a more tractable means of controlling the growth rate for tetragonal lysozyme crystals contrary to the usual practice in, e.g., vapor diffusion protein crystal growth, where both the precipitant and protein concentrations are simultaneously increased. However, the available range for control is dependent upon the protein concentration, with the greatest growth rate control being at the lower concentration.

Fisher statistics for analysis of diffusion tensor directional information.

PubMed

Hutchinson, Elizabeth B; Rutecki, Paul A; Alexander, Andrew L; Sutula, Thomas P

2012-04-30

A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (p<0.0005) differences were found that robustly confirmed observations that were suggested by visual inspection of directionally encoded color DTI maps. The Fisher approach is a potentially useful analysis tool that may extend the current capabilities of DTI investigation by providing a means of statistical comparison of tissue structural orientation. Copyright © 2012 Elsevier B.V. All rights reserved.

Full-Duplex Bidirectional Secure Communications Under Perfect and Distributionally Ambiguous Eavesdropper's CSI

NASA Astrophysics Data System (ADS)

Li, Qiang; Zhang, Ying; Lin, Jingran; Wu, Sissi Xiaoxiao

2017-09-01

Consider a full-duplex (FD) bidirectional secure communication system, where two communication nodes, named Alice and Bob, simultaneously transmit and receive confidential information from each other, and an eavesdropper, named Eve, overhears the transmissions. Our goal is to maximize the sum secrecy rate (SSR) of the bidirectional transmissions by optimizing the transmit covariance matrices at Alice and Bob. To tackle this SSR maximization (SSRM) problem, we develop an alternating difference-of-concave (ADC) programming approach to alternately optimize the transmit covariance matrices at Alice and Bob. We show that the ADC iteration has a semi-closed-form beamforming solution, and is guaranteed to converge to a stationary solution of the SSRM problem. Besides the SSRM design, this paper also deals with a robust SSRM transmit design under a moment-based random channel state information (CSI) model, where only some roughly estimated first and second-order statistics of Eve's CSI are available, but the exact distribution or other high-order statistics is not known. This moment-based error model is new and different from the widely used bounded-sphere error model and the Gaussian random error model. Under the consider CSI error model, the robust SSRM is formulated as an outage probability-constrained SSRM problem. By leveraging the Lagrangian duality theory and DC programming, a tractable safe solution to the robust SSRM problem is derived. The effectiveness and the robustness of the proposed designs are demonstrated through simulations.

Numerical simulation of the geometrical-optics reduction of CE2 and comparisons to quasilinear dynamics

NASA Astrophysics Data System (ADS)

Parker, Jeffrey B.

2018-05-01

Zonal flows have been observed to appear spontaneously from turbulence in a number of physical settings. A complete theory for their behavior is still lacking. Recently, a number of studies have investigated the dynamics of zonal flows using quasilinear (QL) theories and the statistical framework of a second-order cumulant expansion (CE2). A geometrical-optics (GO) reduction of CE2, derived under an assumption of separation of scales between the fluctuations and the zonal flow, is studied here numerically. The reduced model, CE2-GO, has a similar phase-space mathematical structure to the traditional wave-kinetic equation, but that wave-kinetic equation has been shown to fail to preserve enstrophy conservation and to exhibit an ultraviolet catastrophe. CE2-GO, in contrast, preserves nonlinear conservation of both energy and enstrophy. We show here how to retain these conservation properties in a pseudospectral simulation of CE2-GO. We then present nonlinear simulations of CE2-GO and compare with direct simulations of quasilinear (QL) dynamics. We find that CE2-GO retains some similarities to QL. The partitioning of energy that resides in the zonal flow is in good quantitative agreement between CE2-GO and QL. On the other hand, the length scale of the zonal flow does not follow the same qualitative trend in the two models. Overall, these simulations indicate that CE2-GO provides a simpler and more tractable statistical paradigm than CE2, but CE2-GO is missing important physics.

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

An exact and efficient first passage time algorithm for reaction-diffusion processes on a 2D-lattice

NASA Astrophysics Data System (ADS)

Bezzola, Andri; Bales, Benjamin B.; Alkire, Richard C.; Petzold, Linda R.

2014-01-01

We present an exact and efficient algorithm for reaction-diffusion-nucleation processes on a 2D-lattice. The algorithm makes use of first passage time (FPT) to replace the computationally intensive simulation of diffusion hops in KMC by larger jumps when particles are far away from step-edges or other particles. Our approach computes exact probability distributions of jump times and target locations in a closed-form formula, based on the eigenvectors and eigenvalues of the corresponding 1D transition matrix, maintaining atomic-scale resolution of resulting shapes of deposit islands. We have applied our method to three different test cases of electrodeposition: pure diffusional aggregation for large ranges of diffusivity rates and for simulation domain sizes of up to 4096×4096 sites, the effect of diffusivity on island shapes and sizes in combination with a KMC edge diffusion, and the calculation of an exclusion zone in front of a step-edge, confirming statistical equivalence to standard KMC simulations. The algorithm achieves significant speedup compared to standard KMC for cases where particles diffuse over long distances before nucleating with other particles or being captured by larger islands.

Analysis of ligand-protein exchange by Clustering of Ligand Diffusion Coefficient Pairs (CoLD-CoP).

PubMed

Snyder, David A; Chantova, Mihaela; Chaudhry, Saadia

2015-06-01

NMR spectroscopy is a powerful tool in describing protein structures and protein activity for pharmaceutical and biochemical development. This study describes a method to determine weak binding ligands in biological systems by using hierarchic diffusion coefficient clustering of multidimensional data obtained with a 400 MHz Bruker NMR. Comparison of DOSY spectrums of ligands of the chemical library in the presence and absence of target proteins show translational diffusion rates for small molecules upon interaction with macromolecules. For weak binders such as compounds found in fragment libraries, changes in diffusion rates upon macromolecular binding are on the order of the precision of DOSY diffusion measurements, and identifying such subtle shifts in diffusion requires careful statistical analysis. The "CoLD-CoP" (Clustering of Ligand Diffusion Coefficient Pairs) method presented here uses SAHN clustering to identify protein-binders in a chemical library or even a not fully characterized metabolite mixture. We will show how DOSY NMR and the "CoLD-CoP" method complement each other in identifying the most suitable candidates for lysozyme and wheat germ acid phosphatase. Copyright © 2015 Elsevier Inc. All rights reserved.

Stormtime transport of ring current and radiation belt ions

NASA Technical Reports Server (NTRS)

Chen, Margaret W.; Schulz, Michael; Lyons, L. R.; Gorney, David J.

1993-01-01

This is an investigation of stormtime particle transport that leads to formation of the ring current. Our method is to trace the guiding-center motion of representative ions (having selected first adiabatic invariants mu) in response to model substorm-associated impulses in the convection electric field. We compare our simulation results qualitatively with existing analytically tractable idealizations of particle transport (direct convective access and radial diffusion) in order to assess the limits of validity of these approximations. For mu approximately less than 10 MeV/G (E approximately less than 10 keV at L equivalent to 3) the ion drift period on the final (ring-current) drift shell of interest (L equivalent to 3) exceeds the duration of the main phase of our model storm, and we find that the transport of ions to this drift shell is appropriately idealized as direct convective access, typically from open drift paths. Ion transport to a final closed drift path from an open (plasma-sheet) drift trajectory is possible for those portions of that drift path that lie outside the mean stormtime separatrix between closed and open drift trajectories, For mu approximately 10-25 MeV/G (110 keV approximately less than E approximately less than 280 keV at L equivalent to 3) the drift period at L equivalent to 3 is comparable to the postulated 3-hr duration of the storm, and the mode of transport is transitional between direct convective access and transport that resembles radial diffusion. (This particle population is transitional between the ring current and radiation belt). For mu approximately greater than 25 MeV/G (radiation-belt ions having E approximately greater than 280 keV at L equivalent to 3) the ion drift period is considerably shorter than the main phase of a typical storm, and ions gain access to the ring-current region essentially via radial diffusion. By computing the mean and mean-square cumulative changes in 1/L among (in this case) 12 representative ions equally spaced in drift time around the steady-state drift shell of interest (L equivalent to 3), we have estimated (from both our forward and our time-reversed simulations) the time-integrated radial-diffusion coefficients D(sup sim)(sub LL) for particles having selected values of mu approximately greater than 15 MeV/G. The results agree surprisingly well with the predictions (D(sup ql)(sub LL)) of quasilinear radial diffusion theory, despite the rather brief duration (approximately 3 hrs) of our model storm and despite the extreme variability (with frequency) of the spectral-density function that characterizes the applied electric field during our model storm. As expected, the values of D(sup sim)(sub LL) deduced (respectively) from our forward and time-reversed simulations agree even better with each other and with D(sup sim)(sub LL) when the impulse amplitudes which characterize the individual substorms of our model storm are systematically reduced.

Cusping, transport and variance of solutions to generalized Fokker-Planck equations

NASA Astrophysics Data System (ADS)

Carnaffan, Sean; Kawai, Reiichiro

2017-06-01

We study properties of solutions to generalized Fokker-Planck equations through the lens of the probability density functions of anomalous diffusion processes. In particular, we examine solutions in terms of their cusping, travelling wave behaviours, and variance, within the framework of stochastic representations of generalized Fokker-Planck equations. We give our analysis in the cases of anomalous diffusion driven by the inverses of the stable, tempered stable and gamma subordinators, demonstrating the impact of changing the distribution of waiting times in the underlying anomalous diffusion model. We also analyse the cases where the underlying anomalous diffusion contains a Lévy jump component in the parent process, and when a diffusion process is time changed by an uninverted Lévy subordinator. On the whole, we present a combination of four criteria which serve as a theoretical basis for model selection, statistical inference and predictions for physical experiments on anomalously diffusing systems. We discuss possible applications in physical experiments, including, with reference to specific examples, the potential for model misclassification and how combinations of our four criteria may be used to overcome this issue.

Rumor spreading model with noise interference in complex social networks

NASA Astrophysics Data System (ADS)

Zhu, Liang; Wang, Youguo

2017-03-01

In this paper, a modified susceptible-infected-removed (SIR) model has been proposed to explore rumor diffusion on complex social networks. We take variation of connectivity into consideration and assume the variation as noise. On the basis of related literature on virus networks, the noise is described as standard Brownian motion while stochastic differential equations (SDE) have been derived to characterize dynamics of rumor diffusion both on homogeneous networks and heterogeneous networks. Then, theoretical analysis on homogeneous networks has been demonstrated to investigate the solution of SDE model and the steady state of rumor diffusion. Simulations both on Barabási-Albert (BA) network and Watts-Strogatz (WS) network display that the addition of noise accelerates rumor diffusion and expands diffusion size, meanwhile, the spreading speed on BA network is much faster than on WS network under the same noise intensity. In addition, there exists a rumor diffusion threshold in statistical average meaning on homogeneous network which is absent on heterogeneous network. Finally, we find a positive correlation between peak value of infected individuals and noise intensity while a negative correlation between rumor lifecycle and noise intensity overall.

Algal Biofuels | Bioenergy | NREL

Science.gov Websites

growth conditions in a laboratory setting, particularly when strains are maintained under constant other products during phototrophic growth. NREL bioethylene research received a 2015 R&D 100 Award and winter crops, growth on either salt water or fresh water, and genetic tractability. For more

Observatory enabled discovery of diffuse discharge temperature structure

NASA Astrophysics Data System (ADS)

Bemis, K. G.; Lee, R.; Ivakin, A. N.

2016-12-01

Underwater cabled observatories provide long term but short time and spatial scale measurements of hydrothermal discharge properties. For the first time, an intricate picture of diffuse discharge has been captured at both Axial Volcano (Axial) and the Main Endeavour Field (MEF) on the Juan de Fuca Ridge. This study combines thermistor (3D array, 2D array and spot) and acoustic data to compare the statistical and distribution characteristics of diffuse discharge for narrow crack flow (at ASHES field on Axial) and distributive flow out of a sulfide structure (at Grotto vent in MEF). Two surprising observations seem to apply to both styles of diffuse discharge: (1) thermal variance scales with the mean temperature suggesting coherent flow structures exist in the form of plumes, wakes or boundary layers, and (2) thermal hot spots are persistently localized in space, despite tidal current disruption. Thermal variance was measured at ASHES using a 3D thermistor array (TMPSF) with 10 s sampling over two years and at Grotto using 2D thermistor arrays with 1 hr sampling over several years and a ROV-held CTD (Seabird 39plus) with 0.5 second sampling over several minutes. For locations with temperatures greater than ambient, the variance in temperature scales with the mean temperature. This unusual statistical property is characteristic of self-similar flows like plumes, wakes, and boundary layers and arises from the bounded mixing of a cooling high temperature fluid with a cold ambient fluid. Thus this observation implies an underlying coherence to the diffuse discharge that has not yet been adequately captured or described. A coherent flow like a plume should have a discoverable spatial pattern, albeit one that may vary with the influence of tides. Acoustic observations ( 1m diameter footprint) of the Grotto sulfide edifice found stable local hot spots of diffuse discharge that sway with tides. In contrast, the 3D thermistor array at ASHES sees very localized (single thermistor) hot spots that persist for months. Is this a fundamental difference between two styles of diffuse discharge? Alternate conceptual models of diffuse discharge are used to place localized observations in a spatial context and develop a rigorous understanding of the spatial and temporal pattern of diffuse discharge for both crack and distributive styles.

Diffusion and mobility of atomic particles in a liquid

NASA Astrophysics Data System (ADS)

Smirnov, B. M.; Son, E. E.; Tereshonok, D. V.

2017-11-01

The diffusion coefficient of a test atom or molecule in a liquid is determined for the mechanism where the displacement of the test molecule results from the vibrations and motion of liquid molecules surrounding the test molecule and of the test particle itself. This leads to a random change in the coordinate of the test molecule, which eventually results in the diffusion motion of the test particle in space. Two models parameters of interaction of a particle and a liquid are used to find the activation energy of the diffusion process under consideration: the gas-kinetic cross section for scattering of test molecules in the parent gas and the Wigner-Seitz radius for test molecules. In the context of this approach, we have calculated the diffusion coefficient of atoms and molecules in water, where based on experimental data, we have constructed the dependence of the activation energy for the diffusion of test molecules in water on the interaction parameter and the temperature dependence for diffusion coefficient of atoms or molecules in water within the models considered. The statistically averaged difference of the activation energies for the diffusion coefficients of different test molecules in water that we have calculated based on each of the presented models does not exceed 10% of the diffusion coefficient itself. We have considered the diffusion of clusters in water and present the dependence of the diffusion coefficient on the cluster size. The accuracy of the presented formulas for the diffusion coefficient of atomic particles in water is estimated to be 50%.

Harmonic statistics

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2017-05-01

The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their 'public relations' for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford's law, and 1/f noise.

Understanding and controlling regime switching in molecular diffusion

NASA Astrophysics Data System (ADS)

Hallerberg, S.; de Wijn, A. S.

2014-12-01

Diffusion can be strongly affected by ballistic flights (long jumps) as well as long-lived sticking trajectories (long sticks). Using statistical inference techniques in the spirit of Granger causality, we investigate the appearance of long jumps and sticks in molecular-dynamics simulations of diffusion in a prototype system, a benzene molecule on a graphite substrate. We find that specific fluctuations in certain, but not all, internal degrees of freedom of the molecule can be linked to either long jumps or sticks. Furthermore, by changing the prevalence of these predictors with an outside influence, the diffusion of the molecule can be controlled. The approach presented in this proof of concept study is very generic and can be applied to larger and more complex molecules. Additionally, the predictor variables can be chosen in a general way so as to be accessible in experiments, making the method feasible for control of diffusion in applications. Our results also demonstrate that data-mining techniques can be used to investigate the phase-space structure of high-dimensional nonlinear dynamical systems.

The 4D hyperspherical diffusion wavelet: A new method for the detection of localized anatomical variation.

PubMed

Hosseinbor, Ameer Pasha; Kim, Won Hwa; Adluru, Nagesh; Acharya, Amit; Vorperian, Houri K; Chung, Moo K

2014-01-01

Recently, the HyperSPHARM algorithm was proposed to parameterize multiple disjoint objects in a holistic manner using the 4D hyperspherical harmonics. The HyperSPHARM coefficients are global; they cannot be used to directly infer localized variations in signal. In this paper, we present a unified wavelet framework that links Hyper-SPHARM to the diffusion wavelet transform. Specifically, we will show that the HyperSPHARM basis forms a subset of a wavelet-based multiscale representation of surface-based signals. This wavelet, termed the hyperspherical diffusion wavelet, is a consequence of the equivalence of isotropic heat diffusion smoothing and the diffusion wavelet transform on the hypersphere. Our framework allows for the statistical inference of highly localized anatomical changes, which we demonstrate in the first-ever developmental study on the hyoid bone investigating gender and age effects. We also show that the hyperspherical wavelet successfully picks up group-wise differences that are barely detectable using SPHARM.

The 4D Hyperspherical Diffusion Wavelet: A New Method for the Detection of Localized Anatomical Variation

PubMed Central

Hosseinbor, A. Pasha; Kim, Won Hwa; Adluru, Nagesh; Acharya, Amit; Vorperian, Houri K.; Chung, Moo K.

2014-01-01

Recently, the HyperSPHARM algorithm was proposed to parameterize multiple disjoint objects in a holistic manner using the 4D hyperspherical harmonics. The HyperSPHARM coefficients are global; they cannot be used to directly infer localized variations in signal. In this paper, we present a unified wavelet framework that links HyperSPHARM to the diffusion wavelet transform. Specifically, we will show that the HyperSPHARM basis forms a subset of a wavelet-based multiscale representation of surface-based signals. This wavelet, termed the hyperspherical diffusion wavelet, is a consequence of the equivalence of isotropic heat diffusion smoothing and the diffusion wavelet transform on the hypersphere. Our framework allows for the statistical inference of highly localized anatomical changes, which we demonstrate in the firstever developmental study on the hyoid bone investigating gender and age effects. We also show that the hyperspherical wavelet successfully picks up group-wise differences that are barely detectable using SPHARM. PMID:25320783

Speckle suppression by doubly scattering systems.

PubMed

Li, Dayan; Kelly, Damien P; Sheridan, John T

2013-12-10

Speckle suppression in a two-diffuser system is examined. An analytical expression for the speckle space-time correlation function is derived, so that the speckle suppression mechanism can be investigated statistically. The grain size of the speckle field illuminating the second diffuser has a major impact on the speckle contrast after temporal averaging. It is shown that, when both the diffusers are rotating, the one with the lower rotating speed determines the period of the speckle correlation function. The coherent length of the averaged speckle intensity is shown to equal the mean speckle size of the individual speckle pattern before averaging. Numerical and experimental results are presented to verify our analysis in the context of speckle reduction.

Effects of Orientation and Anisometry of Magnetic Resonance Imaging Acquisitions on Diffusion Tensor Imaging and Structural Connectomes.

PubMed

Tudela, Raúl; Muñoz-Moreno, Emma; López-Gil, Xavier; Soria, Guadalupe

2017-01-01

Diffusion-weighted imaging (DWI) quantifies water molecule diffusion within tissues and is becoming an increasingly used technique. However, it is very challenging as correct quantification depends on many different factors, ranging from acquisition parameters to a long pipeline of image processing. In this work, we investigated the influence of voxel geometry on diffusion analysis, comparing different acquisition orientations as well as isometric and anisometric voxels. Diffusion-weighted images of one rat brain were acquired with four different voxel geometries (one isometric and three anisometric in different directions) and three different encoding orientations (coronal, axial and sagittal). Diffusion tensor scalar measurements, tractography and the brain structural connectome were analyzed for each of the 12 acquisitions. The acquisition direction with respect to the main magnetic field orientation affected the diffusion results. When the acquisition slice-encoding direction was not aligned with the main magnetic field, there were more artifacts and a lower signal-to-noise ratio that led to less anisotropic tensors (lower fractional anisotropic values), producing poorer quality results. The use of anisometric voxels generated statistically significant differences in the values of diffusion metrics in specific regions. It also elicited differences in tract reconstruction and in different graph metric values describing the brain networks. Our results highlight the importance of taking into account the geometric aspects of acquisitions, especially when comparing diffusion data acquired using different geometries.

Diffuse optical spectroscopy monitoring of oxygen state and hemoglobin concentration during SKBR-3 tumor model growth

NASA Astrophysics Data System (ADS)

Orlova, A. G.; Kirillin, M. Yu; Volovetsky, A. B.; Shilyagina, N. Yu; Sergeeva, E. A.; Golubiatnikov, G. Yu; Turchin, I. V.

2017-01-01

Tumor oxygenation and hemoglobin content are the key indicators of the tumor status which can be efficiently employed for prognosis of tumor development and choice of treatment strategy. We report on monitoring of these parameters in SKBR-3 (human breast adenocarcinoma) tumors established as subcutaneous tumor xenografts in athymic nude mice by diffuse optical spectroscopy (DOS). A simple continuous wave fiber probe DOS system is employed. Optical properties extraction approach is based on diffusion approximation. Statistically significant difference between measured values of normal tissue and tumor are demonstrated. Hemoglobin content in tumor increases from 7.0  ±  4.2 μM to 30.1  ±  16.1 μM with tumor growth from 150  ±  80 mm3 to 1300  ±  650 mm3 which is determined by gradual increase of deoxyhemoglobin content while measured oxyhemoglobin content does not demonstrate any statistically significant variations. Oxygenation in tumor falls quickly from 52.8  ±  24.7% to 20.2  ±  4.8% preceding acceleration of tumor growth. Statistical analysis indicated dependence of oxy-, deoxy- and total hemoglobin on tumor volume (p  <  0.01). DOS measurements of oxygen saturation are in agreement with independent measurements of oxygen partial pressure by polarography (Pearson’s correlation coefficient equals 0.8).

2ND EF Conference in Turbulent Heat Transfer, Manchester, UK 1998. Volume 1

DTIC Science & Technology

1998-06-01

study the effect of Pr on statistical properties characterizing the scalar field. Turbulent diffusivities are presented for Pr=0.1-2400. A time scale, r...can be defined from the kinetic energy, fc, and the dissipation of turbulence, e, where r = -. The observed influence of Pr (0.05-10) on a time ...dimensional, time -dependent Navier-Stokes equa- tion in a skew-symmetric form and the advection- diffusion equation. du = (u x w) - VIE - Pxex

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yong, E-mail: 83229994@qq.com; Ge, Hao, E-mail: haoge@pku.edu.cn; Xiong, Jie, E-mail: jiexiong@umac.mo

Fluctuation theorem is one of the major achievements in the field of nonequilibrium statistical mechanics during the past two decades. There exist very few results for steady-state fluctuation theorem of sample entropy production rate in terms of large deviation principle for diffusion processes due to the technical difficulties. Here we give a proof for the steady-state fluctuation theorem of a diffusion process in magnetic fields, with explicit expressions of the free energy function and rate function. The proof is based on the Karhunen-Loève expansion of complex-valued Ornstein-Uhlenbeck process.

A meteorologically driven maize stress indicator model

NASA Technical Reports Server (NTRS)

Taylor, T. W.; Ravet, F. W. (Principal Investigator)

1981-01-01

A maize soil moisture and temperature stress model is described which was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions in the major maize-producing areas of the world. The model also identifies optimum climatic conditions and planting/harvest problems associated with poor tractability.

Brachypodium as a model for the grasses: today and the future

USDA-ARS?s Scientific Manuscript database

Over the past several years, Brachypodium distachyon (Brachypodium) has emerged as a tractable model system to study biological questions relevant to the grasses. To place its relevance in the larger context of plant biology, we outline here the expanding adoption of Brachypodium as a model grass an...

A Unified Framework for Monetary Theory and Policy Analysis.

ERIC Educational Resources Information Center

Lagos, Ricardo; Wright, Randall

2005-01-01

Search-theoretic models of monetary exchange are based on explicit descriptions of the frictions that make money essential. However, tractable versions of these models typically make strong assumptions that render them ill suited for monetary policy analysis. We propose a new framework, based on explicit micro foundations, within which macro…

Contextual Fear Conditioning in Zebrafish

ERIC Educational Resources Information Center

Kenney, Justin W.; Scott, Ian C.; Josselyn, Sheena A.; Frankland, Paul W.

2017-01-01

Zebrafish are a genetically tractable vertebrate that hold considerable promise for elucidating the molecular basis of behavior. Although numerous recent advances have been made in the ability to precisely manipulate the zebrafish genome, much less is known about many aspects of learning and memory in adult fish. Here, we describe the development…

Different Parameters Support Generalization and Discrimination Learning in "Drosophila" at the Flight Simulator

ERIC Educational Resources Information Center

Brembs, Bjorn; de Ibarra, Natalie Hempel

2006-01-01

We have used a genetically tractable model system, the fruit fly "Drosophila melanogaster" to study the interdependence between sensory processing and associative processing on learning performance. We investigated the influence of variations in the physical and predictive properties of color stimuli in several different operant-conditioning…

A Vector Representation for Thermodynamic Relationships

ERIC Educational Resources Information Center

Pogliani, Lionello

2006-01-01

The existing vector formalism method for thermodynamic relationship maintains tractability and uses accessible mathematics, which can be seen as a diverting and entertaining step into the mathematical formalism of thermodynamics and as an elementary application of matrix algebra. The method is based on ideas and operations apt to improve the…

Lateral diffusion and signaling of receptor for advanced glycation end-products (RAGE): a receptor involved in chronic inflammation.

PubMed

Syed, Aleem; Zhu, Qiaochu; Smith, Emily A

2018-01-01

Membrane diffusion is one of the key mechanisms in the cellular function of receptors. The signaling of receptors for advanced glycation end-products (RAGE) has been extensively studied in the context of several pathological conditions, however, very little is known about RAGE diffusion. To fill this gap, RAGE lateral diffusion is probed in native, cholesterol-depleted, and cytoskeleton-altered cellular conditions. In native GM07373 cellular conditions, RAGE has a 90% mobile fraction and an average diffusion coefficient of 0.3 μm 2 /s. When depolymerization of the actin cytoskeleton is inhibited with the small molecule jasplakinolide (Jsp), the RAGE mobile fraction and diffusion coefficient decrease by 22 and 37%, respectively. In contrast, depolymerizing the filamentous actin cytoskeleton using the small molecule cytochalasin D (CD) does not alter the RAGE diffusion properties. There is a 70 and 50% decrease in phosphorylation of extracellular signal-regulated kinase (p-ERK) when the actin cytoskeleton is disrupted by CD or Jsp, respectively, in RAGE-expressing GM07373 cells. Disrupting the actin cytoskeleton in GM07373 cells that do not express detectable amounts of RAGE results in no change in p-ERK. Cholesterol depletion results in no statistically significant change in the diffusion properties of RAGE or p-ERK. This work presents a strong link between the actin cytoskeleton and RAGE diffusion and downstream signaling, and serves to further our understanding of the factors influencing RAGE lateral diffusion.

White Matter Microstructure in Transsexuals and Controls Investigated by Diffusion Tensor Imaging

PubMed Central

Kranz, Georg S.; Hahn, Andreas; Kaufmann, Ulrike; Küblböck, Martin; Hummer, Allan; Ganger, Sebastian; Seiger, Rene; Winkler, Dietmar; Swaab, Dick F.; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2015-01-01

Biological causes underpinning the well known gender dimorphisms in human behavior, cognition, and emotion have received increased attention in recent years. The advent of diffusion-weighted magnetic resonance imaging has permitted the investigation of the white matter microstructure in unprecedented detail. Here, we aimed to study the potential influences of biological sex, gender identity, sex hormones, and sexual orientation on white matter microstructure by investigating transsexuals and healthy controls using diffusion tensor imaging (DTI). Twenty-three female-to-male (FtM) and 21 male-to-female (MtF) transsexuals, as well as 23 female (FC) and 22 male (MC) controls underwent DTI at 3 tesla. Fractional anisotropy, axial, radial, and mean diffusivity were calculated using tract-based spatial statistics (TBSS) and fiber tractography. Results showed widespread significant differences in mean diffusivity between groups in almost all white matter tracts. FCs had highest mean diffusivities, followed by FtM transsexuals with lower values, MtF transsexuals with further reduced values, and MCs with lowest values. Investigating axial and radial diffusivities showed that a transition in axial diffusivity accounted for mean diffusivity results. No significant differences in fractional anisotropy maps were found between groups. Plasma testosterone levels were strongly correlated with mean, axial, and radial diffusivities. However, controlling for individual estradiol, testosterone, or progesterone plasma levels or for subjects’ sexual orientation did not change group differences. Our data harmonize with the hypothesis that fiber tract development is influenced by the hormonal environment during late prenatal and early postnatal brain development. PMID:25392513

White matter microstructural alterations in clinically isolated syndrome and multiple sclerosis.

PubMed

Huang, Jing; Liu, Yaou; Zhao, Tengda; Shu, Ni; Duan, Yunyun; Ren, Zhuoqiong; Sun, Zheng; Liu, Zheng; Chen, Hai; Dong, Huiqing; Li, Kuncheng

2018-07-01

This study aims to determine whether and how diffusion alteration occurs in the earliest stage of multiple sclerosis (MS) and the differences in diffusion metrics between CIS and MS by using the tract-based spatial statistics (TBSS) method based on diffusion tensor imaging (DTI). Thirty-six CIS patients (mean age ± SD: 34.0 years ± 12.6), 36 relapsing-remitting multiple sclerosis (RRMS) patients (mean age ± SD: 35.0 years ± 9.4) and 36 age- and gender-matched normal controls (NCs) were included in this study. Voxel-wise analyses were performed with TBSS using multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ 1 ) and radial diffusivity (λ 23 ). In the CIS patients, TBSS analyses revealed diffusion alterations in a few white matter (WM) regions including the anterior thalamic radiation, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, body and splenium of the corpus callosum, internal capsule, external capsule, and cerebral peduncle. MS patients showed more widespread diffusion changes (decreased FA, increased λ 1 , λ 23 and MD) than CIS. Exploratory analyses also revealed the possible associations between WM diffusion metrics and clinical variables (Expanded Disability Status Scale and disease duration) in the patients. This study provided imaging evidence for DTI abnormalities in CIS and MS and suggested that DTI can improve our knowledge of the path physiology of CIS and MS and clinical progression. Copyright © 2018 Elsevier Ltd. All rights reserved.

Membrane Diffusion Occurs by Continuous-Time Random Walk Sustained by Vesicular Trafficking.

PubMed

Goiko, Maria; de Bruyn, John R; Heit, Bryan

2018-06-19

Diffusion in cellular membranes is regulated by processes that occur over a range of spatial and temporal scales. These processes include membrane fluidity, interprotein and interlipid interactions, interactions with membrane microdomains, interactions with the underlying cytoskeleton, and cellular processes that result in net membrane movement. The complex, non-Brownian diffusion that results from these processes has been difficult to characterize, and moreover, the impact of factors such as membrane recycling on membrane diffusion remains largely unexplored. We have used a careful statistical analysis of single-particle tracking data of the single-pass plasma membrane protein CD93 to show that the diffusion of this protein is well described by a continuous-time random walk in parallel with an aging process mediated by membrane corrals. The overall result is an evolution in the diffusion of CD93: proteins initially diffuse freely on the cell surface but over time become increasingly trapped within diffusion-limiting membrane corrals. Stable populations of freely diffusing and corralled CD93 are maintained by an endocytic/exocytic process in which corralled CD93 is selectively endocytosed, whereas freely diffusing CD93 is replenished by exocytosis of newly synthesized and recycled CD93. This trafficking not only maintained CD93 diffusivity but also maintained the heterogeneous distribution of CD93 in the plasma membrane. These results provide insight into the nature of the biological and biophysical processes that can lead to significantly non-Brownian diffusion of membrane proteins and demonstrate that ongoing membrane recycling is critical to maintaining steady-state diffusion and distribution of proteins in the plasma membrane. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Longitudinal brain white matter alterations in minimal hepatic encephalopathy before and after liver transplantation.

PubMed

Lin, Wei-Che; Chou, Kun-Hsien; Chen, Chao-Long; Chen, Hsiu-Ling; Lu, Cheng-Hsien; Li, Shau-Hsuan; Huang, Chu-Chung; Lin, Ching-Po; Cheng, Yu-Fan

2014-01-01

Cerebral edema is the common pathogenic mechanism for cognitive impairment in minimal hepatic encephalopathy. Whether complete reversibility of brain edema, cognitive deficits, and their associated imaging can be achieved after liver transplantation remains an open question. To characterize white matter integrity before and after liver transplantation in patients with minimal hepatic encephalopathy, multiple diffusivity indices acquired via diffusion tensor imaging was applied. Twenty-eight patients and thirty age- and sex-matched healthy volunteers were included. Multiple diffusivity indices were obtained from diffusion tensor images, including mean diffusivity, fractional anisotropy, axial diffusivity and radial diffusivity. The assessment was repeated 6-12 month after transplantation. Differences in white matter integrity between groups, as well as longitudinal changes, were evaluated using tract-based spatial statistical analysis. Correlation analyses were performed to identify first scan before transplantation and interval changes among the neuropsychiatric tests, clinical laboratory tests, and diffusion tensor imaging indices. After transplantation, decreased water diffusivity without fractional anisotropy change indicating reversible cerebral edema was found in the left anterior cingulate, claustrum, postcentral gyrus, and right corpus callosum. However, a progressive decrease in fractional anisotropy and an increase in radial diffusivity suggesting demyelination were noted in temporal lobe. Improved pre-transplantation albumin levels and interval changes were associated with better recoveries of diffusion tensor imaging indices. Improvements in interval diffusion tensor imaging indices in the right postcentral gyrus were correlated with visuospatial function score correction. In conclusion, longitudinal voxel-wise analysis of multiple diffusion tensor imaging indices demonstrated different white matter changes in minimal hepatic encephalopathy patients. Transplantation improved extracellular cerebral edema and the results of associated cognition tests. However, white matter demyelination may advance in temporal lobe.

Soft Tissue Response to Titanium Abutments with Different Surface Treatment: Preliminary Histologic Report of a Randomized Controlled Trial.

PubMed

Canullo, Luigi; Dehner, Jan Friedrich; Penarrocha, David; Checchi, Vittorio; Mazzoni, Annalisa; Breschi, Lorenzo

2016-01-01

The aim of this preliminary prospective RCT was to histologically evaluate peri-implant soft tissues around titanium abutments treated using different cleaning methods. Sixteen patients were randomized into three groups: laboratory customized abutments underwent Plasma of Argon treatment (Plasma Group), laboratory customized abutments underwent cleaning by steam (Steam Group), and abutments were used as they came from industry (Control Group). Seven days after the second surgery, soft tissues around abutments were harvested. Samples were histologically analyzed. Soft tissues surrounding Plasma Group abutments predominantly showed diffuse chronic infiltrate, almost no acute infiltrate, with presence of few polymorphonuclear neutrophil granulocytes, and a diffuse presence of collagenization bands. Similarly, in Steam Group, the histological analysis showed a high variability of inflammatory expression factors. Tissues harvested from Control Group showed presence of few neutrophil granulocytes, moderate presence of lymphocytes, and diffuse collagenization bands in some sections, while they showed absence of acute infiltrate in 40% of sections. However, no statistical difference was found among the tested groups for each parameter (p > 0.05). Within the limit of the present study, results showed no statistically significant difference concerning inflammation and healing tendency between test and control groups.

Microstructural white matter tract alteration in Prader-Willi syndrome: A diffusion tensor imaging study.

PubMed

Rice, Lauren J; Lagopoulos, Jim; Brammer, Michael; Einfeld, Stewart L

2017-09-01

Prader-Willi Syndrome (PWS) is a genetic disorder characterized by infantile hypotonia, hyperphagia, hypogonadism, growth hormone deficiency, intellectual disability, and severe emotional and behavioral problems. The brain mechanisms that underpin these disturbances are unknown. Diffusion tensor imaging (DTI) enables in vivo investigation of the microstructural integrity of white matter pathways. To date, only one study has used DTI to examine white matter alterations in PWS. However, that study used selected regions of interest, rather than a whole brain analysis. In the present study, we used diffusion tensor and magnetic resonance (T 1-weighted) imaging to examine microstructural white matter changes in 15 individuals with PWS (17-30 years) and 15 age-and-gender-matched controls. Whole-brain voxel-wise statistical analysis of FA was carried out using tract-based spatial statistics (TBSS). Significantly decreased fractional anisotropy was found localized to the left hemisphere in individuals with PWS within the splenium of the corpus callosum, the internal capsule including the posterior thalamic radiation and the inferior frontal occipital fasciculus (IFOF). Reduced integrity of these white matter pathways in individuals with PWS may relate to orientating attention, emotion recognition, semantic processing, and sensorimotor dysfunction. © 2017 Wiley Periodicals, Inc.

Utility of Diffusion Weighted Magnetic Resonance Imaging with Multiple B Values in Evaluation of Pancreatic Malignant and Benign Lesions and Pancreatitis.

PubMed

Karadeli, Elif; Erbay, Gurcan; Parlakgumus, Alper; Koc, Zafer

2018-02-01

To determine the feasibility of diffusion-weighted imaging in evaluation of pancreatic lesions and in differentiation of benign from malignant lesions. Descriptive study. Baskent University Adana Teaching and Research Center, Adana, Turkey, between September 2013 and May 2015. Forty-three lesions [pancreas adenocarcinoma (n=25)], pancreatitis (n=10), benign lesion (n=8)] were utilized with diffusion-weighted magnetic resonance imaging with multiple b-values. Different ADC maps of diffusion weighted images by using b-values were acquired. The median ADC at all b values for malignant lesions was significantly different from that for benign lesions (p<0.001). When ADCs at all b values were compared between benign lesions/normal parenchyma and malignant lesions/normal parenchyma, there was a significant statistical difference in all b values between benign and malignant lesions except at b 50 and b 200 (p<0.05). The lesion/normal parenchyma ADC ratio for b 600 value (AUC=0.804) was more effective than the lesion ADC for b 600 value (AUC=0.766) in differentiation of benign and malignant lesions. The specificity and sensitivity of the lesion/normal parenchyma ADC ratio were higher than those of ADC values of lesions. When the ADC was compared between benign lesions and pancreatitis, a significant difference was found at all b values (p<0.001). There was not a statistically significant difference between the ADC for pancreatitis and that for malignant lesions at any b value combinations (p>0.05). Diffusion-weighted magnetic resonance images can be helpful in differentiation of pancreatic carcinoma and benign lesions. Lesion ADC / normal parenchyma ADC ratios are more important than lesion ADC values in assessment of pancreatic lesions.

Test-retest reliability of high angular resolution diffusion imaging acquisition within medial temporal lobe connections assessed via tract based spatial statistics, probabilistic tractography and a novel graph theory metric.

PubMed

Kuhn, T; Gullett, J M; Nguyen, P; Boutzoukas, A E; Ford, A; Colon-Perez, L M; Triplett, W; Carney, P R; Mareci, T H; Price, C C; Bauer, R M

2016-06-01

This study examined the reliability of high angular resolution diffusion tensor imaging (HARDI) data collected on a single individual across several sessions using the same scanner. HARDI data was acquired for one healthy adult male at the same time of day on ten separate days across a one-month period. Environmental factors (e.g. temperature) were controlled across scanning sessions. Tract Based Spatial Statistics (TBSS) was used to assess session-to-session variability in measures of diffusion, fractional anisotropy (FA) and mean diffusivity (MD). To address reliability within specific structures of the medial temporal lobe (MTL; the focus of an ongoing investigation), probabilistic tractography segmented the Entorhinal cortex (ERc) based on connections with Hippocampus (HC), Perirhinal (PRc) and Parahippocampal (PHc) cortices. Streamline tractography generated edge weight (EW) metrics for the aforementioned ERc connections and, as comparison regions, connections between left and right rostral and caudal anterior cingulate cortex (ACC). Coefficients of variation (CoV) were derived for the surface area and volumes of these ERc connectivity-defined regions (CDR) and for EW across all ten scans, expecting that scan-to-scan reliability would yield low CoVs. TBSS revealed no significant variation in FA or MD across scanning sessions. Probabilistic tractography successfully reproduced histologically-verified adjacent medial temporal lobe circuits. Tractography-derived metrics displayed larger ranges of scanner-to-scanner variability. Connections involving HC displayed greater variability than metrics of connection between other investigated regions. By confirming the test retest reliability of HARDI data acquisition, support for the validity of significant results derived from diffusion data can be obtained.

Hybrid Diffusion Imaging in Mild Traumatic Brain Injury.

PubMed

Wu, Yu-Chien; Mustafi, Sourajit Mitra; Harezlak, Jaroslaw; Kodiweera, Chandana; Flashman, Laura A; McAllister, Thomas

2018-05-22

Mild traumatic brain injury (mTBI) is an important public health problem. Although conventional medical imaging techniques can detect moderate-to-severe injuries, they are relatively insensitive to mTBI. In this study, we used hybrid diffusion imaging (HYDI) to detect white-matter alterations in nineteen patients with mTBI and 23 other trauma-control patients. Within 15 days (SD=10) of brain injury, all subjects underwent magnetic-resonance HYDI and were assessed with battery of neuropsychological tests of sustained attention, memory, and executive function. Tract-based spatial statistics (TBSS) were used for voxelwise statistical analyses within the white-matter skeleton to study between-group differences in diffusion metrics, within-group correlations between diffusion metrics and clinical outcomes, and between group interaction effects. The advanced diffusion imaging techniques including neurite orientation dispersion and density imaging (NODDI) and q-space analyses appeared to be more sensitive then classic diffusion tensor imaging (DTI). Only NODDI-derived intra-axonal volume fraction (V_ic) demonstrated significant group differences (i.e., 5% to 9% lower in the injured brain). Within the mTBI group, V_ic and a q-space measure, P₀, correlated with 6 of 10 neuropsychological tests including measures of attention, memory, and executive function. In addition, the direction of correlations differed significantly between the groups (R² > 0.71 and P_interation < 0.03). Specifically, in the control group, higher V_ic and P₀ were associated with better performances on clinical assessments, whereas in the mTBI group, higher V_ic and P₀ were associated with worse performances with correlation coefficients > 0.83. In summary, the NODDI-derived axonal density index and q-space measure for tissue restriction demonstrated superior sensitivity to white-matter changes shortly after mTBI. These techniques hold promise as a neuroimaging biomarker for mTBI.

Diffusion of influenza viruses among migratory birds with a focus on the Southwest United States.

PubMed

Scotch, Matthew; Lam, Tommy Tsan-Yuk; Pabilonia, Kristy L; Anderson, Theodore; Baroch, John; Kohler, Dennis; DeLiberto, Thomas J

2014-08-01

The Southwest United States, including Arizona and New Mexico, has a diverse climate and is home to many different avian species. We sequenced the hemagglutinin (HA) gene of twenty influenza specimens for the years 2007-2009. This included four from Arizona, and sixteen from New Mexico. We analyzed the sequences and determined the following HA subtypes: H3, H4, H6, H8, and H11. For each subtype, we combined our virus sequences with those from a public database, and inferred phylogeographic models of influenza diffusion. Statistical phylogeography indicated that overall evolutionary diffusion of avian influenza viruses is geographically structured (p<0.05). In addition, we found that diffusion to the Southwest was often from nearby states including California. For H3, H4 and H6, the intra-flyway gene flow rates were significantly (p<0.001) higher than those of inter-flyway. Such rate difference was also observed in H8 and H11, yet, without statistical significance (p=0.132, p=0.190, respectively). Excluding any one flyway from the calculation generated similar results, suggesting that such barrier effect on gene flow rates is not exclusively produced by any single flyway. We also calculated the Bayes factor test for the significant non-zero rates between states and identified significant routes both within and across flyways. Such inter-flyway spread of influenza was probably the result of birds from four flyways co-mingling on breeding grounds in northern regions or marshaling on staging areas post breeding in Canada or Alaska, before moving south each fall. This study provides an initial analysis of evolutionary diffusion of avian influenza virus to and from the Southwest United States. However, more sequences from this region need to be generated to determine the role of host migration and other factors on influenza diffusion. Copyright © 2014 Elsevier B.V. All rights reserved.

Diffuse nutrient losses and the impact factors determining their regional differences in four catchments from North to South China

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Zhou, Yujian; Shao, Quanxi; Liu, Hongbin; Lei, Qiuliang; Zhai, Xiaoyan; Wang, Xuelei

2016-12-01

Diffuse nutrient loss mechanism is complicated and shows remarkably regional differences due to spatial heterogeneities of underlying surface conditions, climate and agricultural practices. Moreover, current available observations are still hard to support the identification of impact factors due to different time or space steps. In this study, an integrated water system model (HEQM) was adopted to obtain the simulated loads of diffuse components (carriers: runoff and sediment; nutrient: total nitrogen (TN) and total phosphorous (TP)) with synchronous scales. Multivariable statistical analysis approaches (Analysis of Similarity and redundancy analysis) were used to assess the regional differences, and to identify impact factors as well as their contributions. Four catchments were selected as our study areas, i.e., Xiahui and Zhangjiafen Catchments of Miyun Basin in North China, Yuliang and Tunxi Catchments of Xin'anjiang Basin in South China. Results showed that the model performances of monthly processes were very good for runoff and good for sediment, TN and TP. The annual average coefficients of all the diffuse components in Xin'anjiang Basin were much greater than those in Miyun Basin, and showed significantly regional differences. All the selected impact factors interpreted 72.87-82.16% of the regional differences of carriers, and 62.72-71.62% of those of nutrient coefficients, respectively. For individual impact factor categories, the critical category was geography, followed by land-use/cover, carriers, climate, as well as soil and agricultural practices in Miyun Basin, or agricultural practices and soil in Xin'anjiang Basin. For individual factors, the critical factors were locations for the carrier regional differences, and carriers or chemical fertilizer for the nutrient regional differences. This study is expected to promote further applications of integrated water system model and multivariable statistical analysis in the diffuse nutrient studies, and provide a scientific support for the diffuse pollution control and management in China.

Grading of Gliomas by Using Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MR Imaging and Diffusion Kurtosis MR Imaging

PubMed Central

Bai, Yan; Lin, Yusong; Tian, Jie; Shi, Dapeng; Cheng, Jingliang; Haacke, E. Mark; Hong, Xiaohua; Ma, Bo; Zhou, Jinyuan

2016-01-01

Purpose To quantitatively compare the potential of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models and diffusion kurtosis imaging in the grading of gliomas. Materials and Methods This study was approved by the local ethics committee, and written informed consent was obtained from all subjects. Both diffusion-weighted imaging and diffusion kurtosis imaging were performed in 69 patients with pathologically proven gliomas by using a 3-T magnetic resonance (MR) imaging unit. An isotropic apparent diffusion coefficient (ADC), true ADC, pseudo-ADC, and perfusion fraction were calculated from diffusion-weighted images by using a biexponential model. A water molecular diffusion heterogeneity index and distributed diffusion coefficient were calculated from diffusion-weighted images by using a stretched exponential model. Mean diffusivity, fractional anisotropy, and mean kurtosis were calculated from diffusion kurtosis images. All values were compared between high-grade and low-grade gliomas by using a Mann-Whitney U test. Receiver operating characteristic and Spearman rank correlation analysis were used for statistical evaluations. Results ADC, true ADC, perfusion fraction, water molecular diffusion heterogeneity index, distributed diffusion coefficient, and mean diffusivity values were significantly lower in high-grade gliomas than in low-grade gliomas (U = 109, 56, 129, 6, 206, and 229, respectively; P < .05). Pseudo-ADC and mean kurtosis values were significantly higher in high-grade gliomas than in low-grade gliomas (U = 98 and 8, respectively; P < .05). Both water molecular diffusion heterogeneity index (area under the receiver operating characteristic curve [AUC] = 0.993) and mean kurtosis (AUC = 0.991) had significantly greater AUC values than ADC (AUC = 0.866), mean diffusivity (AUC = 0.722), and fractional anisotropy (AUC = 0.500) in the differentiation of low-grade and high-grade gliomas (P < .05). Conclusion Water molecular diffusion heterogeneity index and mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters. © RSNA, 2015 Online supplemental material is available for this article. PMID:26230975

Analytic expressions for ULF wave radiation belt radial diffusion coefficients

PubMed Central

Ozeke, Louis G; Mann, Ian R; Murphy, Kyle R; Jonathan Rae, I; Milling, David K

2014-01-01

We present analytic expressions for ULF wave-derived radiation belt radial diffusion coefficients, as a function of L and Kp, which can easily be incorporated into global radiation belt transport models. The diffusion coefficients are derived from statistical representations of ULF wave power, electric field power mapped from ground magnetometer data, and compressional magnetic field power from in situ measurements. We show that the overall electric and magnetic diffusion coefficients are to a good approximation both independent of energy. We present example 1-D radial diffusion results from simulations driven by CRRES-observed time-dependent energy spectra at the outer boundary, under the action of radial diffusion driven by the new ULF wave radial diffusion coefficients and with empirical chorus wave loss terms (as a function of energy, Kp and L). There is excellent agreement between the differential flux produced by the 1-D, Kp-driven, radial diffusion model and CRRES observations of differential electron flux at 0.976 MeV—even though the model does not include the effects of local internal acceleration sources. Our results highlight not only the importance of correct specification of radial diffusion coefficients for developing accurate models but also show significant promise for belt specification based on relatively simple models driven by solar wind parameters such as solar wind speed or geomagnetic indices such as Kp. Key Points Analytic expressions for the radial diffusion coefficients are presented The coefficients do not dependent on energy or wave m value The electric field diffusion coefficient dominates over the magnetic PMID:26167440

Interpreting the Weibull fitting parameters for diffusion-controlled release data

NASA Astrophysics Data System (ADS)

Ignacio, Maxime; Chubynsky, Mykyta V.; Slater, Gary W.

2017-11-01

We examine the diffusion-controlled release of molecules from passive delivery systems using both analytical solutions of the diffusion equation and numerically exact Lattice Monte Carlo data. For very short times, the release process follows a √{ t } power law, typical of diffusion processes, while the long-time asymptotic behavior is exponential. The crossover time between these two regimes is determined by the boundary conditions and initial loading of the system. We show that while the widely used Weibull function provides a reasonable fit (in terms of statistical error), it has two major drawbacks: (i) it does not capture the correct limits and (ii) there is no direct connection between the fitting parameters and the properties of the system. Using a physically motivated interpolating fitting function that correctly includes both time regimes, we are able to predict the values of the Weibull parameters which allows us to propose a physical interpretation.

Determination of the ground albedo and the index of absorption of atmospheric particulates by remote sensing. II - Application

NASA Technical Reports Server (NTRS)

King, M. D.

1979-01-01

A hemispherical radiometer has been used to obtain spectrally narrow-band measurements of the downward hemispheric diffuse and total (global) flux densities at varying solar zenith angles on 14 days over Tucson. Data are presented which illustrate the effects of temporally varying atmospheric conditions as well as clear stable conditions on the ratio of the diffuse to direct solar radiation at the earth's surface. The ground albedo and the effective imaginary term of the complex refractive index of atmospheric particulates are derived from the diffuse-direct ratio measurements on seven clear stable days at two wavelengths using the statistical procedure described by King and Herman (1979). Results indicate that the downwelling diffuse radiation field in the midvisible region in Tucson can be adequately described by Mie scattering theory if the ground albedo is 0.279 + or - 0.100 and the index of absorption is 0.0306 + or - 0.0082.

Anomalous Diffusion of Single Particles in Cytoplasm

PubMed Central

Regner, Benjamin M.; Vučinić, Dejan; Domnisoru, Cristina; Bartol, Thomas M.; Hetzer, Martin W.; Tartakovsky, Daniel M.; Sejnowski, Terrence J.

2013-01-01

The crowded intracellular environment poses a formidable challenge to experimental and theoretical analyses of intracellular transport mechanisms. Our measurements of single-particle trajectories in cytoplasm and their random-walk interpretations elucidate two of these mechanisms: molecular diffusion in crowded environments and cytoskeletal transport along microtubules. We employed acousto-optic deflector microscopy to map out the three-dimensional trajectories of microspheres migrating in the cytosolic fraction of a cellular extract. Classical Brownian motion (BM), continuous time random walk, and fractional BM were alternatively used to represent these trajectories. The comparison of the experimental and numerical data demonstrates that cytoskeletal transport along microtubules and diffusion in the cytosolic fraction exhibit anomalous (nonFickian) behavior and posses statistically distinct signatures. Among the three random-walk models used, continuous time random walk provides the best representation of diffusion, whereas microtubular transport is accurately modeled with fractional BM. PMID:23601312

A method of online quantitative interpretation of diffuse reflection profiles of biological tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2013-02-01

We have developed a method of combined interpretation of spectral and spatial characteristics of diffuse reflection of biological tissues, which makes it possible to determine biophysical parameters of the tissue with a high accuracy in real time under conditions of their general variability. Using the Monte Carlo method, we have modeled a statistical ensemble of profiles of diffuse reflection coefficients of skin, which corresponds to a wave variation of its biophysical parameters. On its basis, we have estimated the retrieval accuracy of biophysical parameters using the developed method and investigated the stability of the method to errors of optical measurements. We have showed that it is possible to determine online the concentrations of melanin, hemoglobin, bilirubin, oxygen saturation of blood, and structural parameters of skin from measurements of its diffuse reflection in the spectral range 450-800 nm at three distances between the radiation source and detector.

Ultra-Widefield Fluorescein Angiography in Intermediate Uveitis.

PubMed

Laovirojjanakul, Wipada; Acharya, Nisha; Gonzales, John A

2017-10-17

To examine associations between pattern of vascular leakage on ultrawide-field fluorescein angiography (UWFFA) and visual acuity, cystoid macular edema (CME), and inflammatory activity in intermediate uveitis. Single center cross-sectional, retrospective review of medical records, spectral domain optical coherence tomography (SD-OCT) and angiographic images of intermediate uveitis patients who underwent UWFFA over a 12-month period. Forty-one eyes from 24 patients were included. Twelve eyes (29%) exhibited peripheral leakage, 26 eyes (64%) had diffuse leakage and three eyes (7%) had no leakage. Diffuse leakage was associated with 0.2 logMAR worse visual acuity than peripheral leakage (p = 0.02). There was no statistically significant difference in the odds of having CME when diffuse leakage was compared to peripheral leakage. UWFFA identifies retinal vascular pathology in intermediate uveitis not present on clinical examination. Diffuse retinal vascular leakage was associated with worse visual acuity when compared to peripheral and no leakage patterns.

diffuStats: an R package to compute diffusion-based scores on biological networks.

PubMed

Picart-Armada, Sergio; Thompson, Wesley K; Buil, Alfonso; Perera-Lluna, Alexandre

2018-02-01

Label propagation and diffusion over biological networks are a common mathematical formalism in computational biology for giving context to molecular entities and prioritizing novel candidates in the area of study. There are several choices in conceiving the diffusion process-involving the graph kernel, the score definitions and the presence of a posterior statistical normalization-which have an impact on the results. This manuscript describes diffuStats, an R package that provides a collection of graph kernels and diffusion scores, as well as a parallel permutation analysis for the normalized scores, that eases the computation of the scores and their benchmarking for an optimal choice. The R package diffuStats is publicly available in Bioconductor, https://bioconductor.org, under the GPL-3 license. sergi.picart@upc.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Determination of critical diameters for intrinsic carrier diffusion-length of GaN nanorods with cryo-scanning near-field optical microscopy

PubMed Central

Chen, Y. T.; Karlsson, K. F.; Birch, J.; Holtz, P. O.

2016-01-01

Direct measurements of carrier diffusion in GaN nanorods with a designed InGaN/GaN layer-in-a-wire structure by scanning near-field optical microscopy (SNOM) were performed at liquid-helium temperatures of 10 K. Without an applied voltage, intrinsic diffusion lengths of photo-excited carriers were measured as the diameters of the nanorods differ from 50 to 800 nm. The critical diameter of nanorods for carrier diffusion is concluded as 170 nm with a statistical approach. Photoluminescence spectra were acquired for different positions of the SNOM tip on the nanorod, corresponding to the origins of the well-defined luminescence peaks, each being related to recombination-centers. The phenomenon originated from surface oxide by direct comparison of two nanorods with similar diameters in a single map has been observed and investigated. PMID:26876009

A pilot DTI analysis in patients with recent onset post-traumatic stress disorder

NASA Astrophysics Data System (ADS)

Liu, Yang; Li, Liang; Li, Baojuan; Zhang, Xi; Lu, Hongbing

2016-03-01

To explore the alteration in white matter between survivors with recent onset post-traumatic stress disorder (PTSD) and without PTSD, who survived from the same coal mine flood disaster, the diffusion tensor imaging (DTI) sequences were analyzed using DTI studio and statistical parametric mapping (SPM) packages in this paper. From DTI sequence, the fractional anisotropy (FA) value describes the degree of anisotropy of a diffusion process, while the apparent diffusion coefficient (ADC) value reflects the magnitude of water diffusion. The DTI analyses between PTSD and non-PTSD indicate lower FA values in the right caudate nucleus, right middle temporal gyrus, right fusiform gyrus, and right superior temporal gyrus, and higher ADC values in the right superior temporal gyrus and right corpus callosum of the subjects with PTSD. These results are partly in line with our previous volume and cortical thickness analyses, indicating the importance of multi-modality analysis for PTSD.

Structural Abnormalities in Early Tourette Syndrome Children: A Combined Voxel-Based Morphometry and Tract-Based Spatial Statistics Study

PubMed Central

Wang, Jieqiong; Gao, Peiyi; Yin, Guangheng; Zhang, Liping; Lv, Chuankai; Ji, Zhiying; Yu, Tong; Sabel, B. A.; He, Huiguang; Peng, Yun

2013-01-01

Tourette Syndrome (TS) is characterized with chronic motor and vocal tics beginning in childhood. Abnormality of both gray (GM) and white matter (WM) has been observed in cortico-striato-thalamo-cortical circuits and sensory-motor cortex of adult TS patient. It is not clear if these morphological changes are also present in TS children and if there are any microstructural changes of WM. To understand the developmental cause of such changes, we investigated volumetric changes of GM and WM using VBM and microstructural changes of WM using DTI, and correlated these changes with tic severity and duration. T1 images and Diffusion Tensor Images (DTI) from 21 TS children were compared with 20 age and gender matched health control children using a 1.5T Philips scanner. All of the 21 TS children met the DSM-IV-TR criteria. T1 images were analyzed using DARTEL-VBM in conjunction with statistical parametric mapping (SPM). Diffusion tensor imaging (DTI) analysis was performed using Tract-Based Spatial Statistics (TBSS). Brain volume changes were found in left superior temporal gyrus, left and right paracentral gyrus, right precuneous cortex, right pre- and post- central gyrus, left temporal occipital fusiform cortex, right frontal pole, and left lingual gyrus. Significant axial diffusivity (AD) and mean diffusivity (MD) increases were found in anterior thalamic radiation, right cingulum bundle projecting to the cingulate gurus and forceps minor. Decreases in white matter volume (WMV) in the right frontal pole were inversely related with tic severity (YGTSS), and increases in AD and MD were positively correlated with tic severity and duration, respectively. These changes in TS children can be interpreted as signs of neural plasticity in response to the experiential demand. Our findings may suggest that the morphological and microstructural measurements from structural MRI and DTI can potentially be used as a biomarker of the pathophysiologic pattern of early TS children. PMID:24098769

Structural abnormalities in early Tourette syndrome children: a combined voxel-based morphometry and tract-based spatial statistics study.

PubMed

Liu, Yue; Miao, Wen; Wang, Jieqiong; Gao, Peiyi; Yin, Guangheng; Zhang, Liping; Lv, Chuankai; Ji, Zhiying; Yu, Tong; Sabel, B A; He, Huiguang; Peng, Yun

2013-01-01

Tourette Syndrome (TS) is characterized with chronic motor and vocal tics beginning in childhood. Abnormality of both gray (GM) and white matter (WM) has been observed in cortico-striato-thalamo-cortical circuits and sensory-motor cortex of adult TS patient. It is not clear if these morphological changes are also present in TS children and if there are any microstructural changes of WM. To understand the developmental cause of such changes, we investigated volumetric changes of GM and WM using VBM and microstructural changes of WM using DTI, and correlated these changes with tic severity and duration. T1 images and Diffusion Tensor Images (DTI) from 21 TS children were compared with 20 age and gender matched health control children using a 1.5T Philips scanner. All of the 21 TS children met the DSM-IV-TR criteria. T1 images were analyzed using DARTEL-VBM in conjunction with statistical parametric mapping (SPM). Diffusion tensor imaging (DTI) analysis was performed using Tract-Based Spatial Statistics (TBSS). Brain volume changes were found in left superior temporal gyrus, left and right paracentral gyrus, right precuneous cortex, right pre- and post-central gyrus, left temporal occipital fusiform cortex, right frontal pole, and left lingual gyrus. Significant axial diffusivity (AD) and mean diffusivity (MD) increases were found in anterior thalamic radiation, right cingulum bundle projecting to the cingulate gurus and forceps minor. Decreases in white matter volume (WMV) in the right frontal pole were inversely related with tic severity (YGTSS), and increases in AD and MD were positively correlated with tic severity and duration, respectively. These changes in TS children can be interpreted as signs of neural plasticity in response to the experiential demand. Our findings may suggest that the morphological and microstructural measurements from structural MRI and DTI can potentially be used as a biomarker of the pathophysiologic pattern of early TS children.

Comparative evaluation of diffusion hypoxia and psychomotor skills with or without postsedation oxygenation following administration of nitrous oxide in children undergoing dental procedures: A clinical study.

PubMed

Khinda, Vineet Inder Singh; Bhuria, Parvesh; Khinda, Paramjit; Kallar, Shiminder; Brar, Gurlal Singh

2016-01-01

Diffusion hypoxia is the most serious potential complication associated with nitrous oxide. It occurs during the recovery period. Hence, administration of 100% oxygen is mandatory as suggested by many authors. The aim of this study is to evaluate the occurrence/nonoccurrence of diffusion hypoxia in two groups of patients undergoing routine dental treatment under nitrous oxide sedation when one group is subjected to 7 min of postsedation oxygenation and the second group of the patients is made to breathe room air for the similar period. A total of sixty patients within the age group of 7-10 years requiring invasive dental procedures were randomly divided into two groups of 30 each using chit method. In the control group, patients were administered 100% oxygen postsedation, whereas, in the study group, patients were made to breathe room air postsedation. Various parameters (pulse rate, respiratory rate, blood pressure, and oxygen saturation [SpO2]) were recorded pre- and post-operatively. Data were collected and then sent for statistical analysis. The mean postoperative SpO2 at measurement times 1, 3, 5, and 7 min in both the groups was higher than the mean preoperative SpO2. This increase was statistically significant. No significant difference was found between the Trieger test scores. This study proves that clinical occurrence of diffusion hypoxia is not possible while following the routine procedure of nitrous oxide sedation.

Evaluation of Free Breathing Versus Breath Hold Diffusion Weighted Imaging in Terms Apparent Diffusion Coefficient (ADC) and Signal-to-Noise Ratio (SNR) Values for Solid Abdominal Organs.

PubMed

Herek, Duygu; Karabulut, Nevzat; Kocyıgıt, Ali; Yagcı, Ahmet Baki

2016-01-01

Our aim was to compare the apparent diffusion coefficient (ADC) values of normal abdominal parenchymal organs and signal-to-noise ratio (SNR) measurements in the same patients with breath hold (BH) and free breathing (FB) diffusion weighted imaging (DWI). Forty-eight patients underwent both BH and FB DWI. Spherical region of interest (ROI) was placed on the right hepatic lobe, spleen, pancreas, and renal cortices. ADC values were calculated for each organ on each sequence using an automated software. Image noise, defined as the standard deviation (SD) of the signal intensities in the most artifact-free area of the image background was measured by placing the largest possible ROI on either the left or the right side of the body outside the object in the recorded field of view. SNR was calculated using the formula: SNR=signal intensity (SI) (organ) /standard deviation (SD) (noise) . There were no statistically significant differences in ADC values of the abdominal organs between BH and FB DWI sequences ( p >0.05). There were statistically significant differences between SNR values of organs on BH and FB DWIs. SNRs were found to be better on FB DWI than BH DWI ( p <0.001). Free breathing DWI technique reduces image noise and increases SNR for abdominal examinations. Free breathing technique is therefore preferable to BH DWI in the evaluation of abdominal organs by DWI.

Altered White Matter Integrity in Human Immunodeficiency Virus-Associated Neurocognitive Disorder: A Tract-Based Spatial Statistics Study.

PubMed

Oh, Se Won; Shin, Na-Young; Choi, Jun Yong; Lee, Seung-Koo; Bang, Mi Rim

2018-01-01

Human immunodeficiency virus (HIV) infection has been known to damage the microstructural integrity of white matter (WM). However, only a few studies have assessed the brain regions in HIV-associated neurocognitive disorders (HAND) with diffusion tensor imaging (DTI). Therefore, we sought to compare the DTI data between HIV patients with and without HAND using tract-based spatial statistics (TBSS). Twenty-two HIV-infected patients (10 with HAND and 12 without HAND) and 11 healthy controls (HC) were enrolled in this study. A whole-brain analysis of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity was performed with TBSS and a subsequent 20 tract-specific region-of-interest (ROI)-based analysis to localize and compare altered WM integrity in all group contrasts. Compared with HC, patients with HAND showed decreased FA in the right frontoparietal WM including the upper corticospinal tract (CST) and increased MD and RD in the bilateral frontoparietal WM, corpus callosum, bilateral CSTs and bilateral cerebellar peduncles. The DTI values did not significantly differ between HIV patients with and without HAND or between HIV patients without HAND and HC. In the ROI-based analysis, decreased FA was observed in the right superior longitudinal fasciculus and was significantly correlated with decreased information processing speed, memory, executive function, and fine motor function in HIV patients. These results suggest that altered integrity of the frontoparietal WM contributes to cognitive dysfunction in HIV patients.

Modeling radiation belt dynamics using a 3-D layer method code

NASA Astrophysics Data System (ADS)

Wang, C.; Ma, Q.; Tao, X.; Zhang, Y.; Teng, S.; Albert, J. M.; Chan, A. A.; Li, W.; Ni, B.; Lu, Q.; Wang, S.

2017-08-01

A new 3-D diffusion code using a recently published layer method has been developed to analyze radiation belt electron dynamics. The code guarantees the positivity of the solution even when mixed diffusion terms are included. Unlike most of the previous codes, our 3-D code is developed directly in equatorial pitch angle (α0), momentum (p), and L shell coordinates; this eliminates the need to transform back and forth between (α0,p) coordinates and adiabatic invariant coordinates. Using (α0,p,L) is also convenient for direct comparison with satellite data. The new code has been validated by various numerical tests, and we apply the 3-D code to model the rapid electron flux enhancement following the geomagnetic storm on 17 March 2013, which is one of the Geospace Environment Modeling Focus Group challenge events. An event-specific global chorus wave model, an AL-dependent statistical plasmaspheric hiss wave model, and a recently published radial diffusion coefficient formula from Time History of Events and Macroscale Interactions during Substorms (THEMIS) statistics are used. The simulation results show good agreement with satellite observations, in general, supporting the scenario that the rapid enhancement of radiation belt electron flux for this event results from an increased level of the seed population by radial diffusion, with subsequent acceleration by chorus waves. Our results prove that the layer method can be readily used to model global radiation belt dynamics in three dimensions.

Gettering in multicrystalline silicon: A design-of-experiments approach

NASA Astrophysics Data System (ADS)

Schubert, W. K.

1994-12-01

Design-of-experiment methods were used to study gettering due to phosphorus diffusion and aluminum alloying in four industrial multicrystalline silicon materials: Silicon-Film material from AstroPower, heat-exchanger method (HEM) material from Crystal Systems, edge-defined film-fed growth (EFG) material from Mobil Solar, and cast material from Solarex. Time and temperature for the diffusion and alloy processes were chosen for a four-factor quadratic interaction experiment. Simple diagnostic devices were used to evaluate the gettering. Only EFG and HEM materials exhibited statistically significant gettering effects within the ranges used for the various parameters. Diffusion and alloying temperature were significant for HEM material; also there was a second-order interaction between the diffusion time and temperature. There was no interaction between the diffusion and alloying processes in HEM material. EFG material showed a first-order dependence on diffusion temperature and a second-order interaction between the diffusion temperature and the alloying time. Gettering recommendations for the HEM material were used to produce the best-yet Sandia cells on this material, but correlation with the gettering experiment was not strong. Some of the discrepancy arises from necessary processing differences between the diagnostic devices and regular solar cells. This issue and other lessons learned concerning this type of experiment are discussed.

Diffusion of Molecular Diagnostic Lung Cancer Tests: A Survey of German Oncologists

PubMed Central

Steffen, Julius Alexander

2014-01-01

This study was aimed at examining the diffusion of diagnostic lung cancer tests in Germany. It was motivated by the high potential of detecting and targeting oncogenic drivers. Recognizing that the diffusion of diagnostic tests is a conditio sine qua non for the success of personalized lung cancer therapies, this study analyzed the diffusion of epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) tests in Germany. Qualitative and quantitative research strategies were combined in a mixed-method design. A literature review and subsequent Key Opinion Leader interviews identified a set of qualitative factors driving the diffusion process, which were then translated into an online survey. The survey was conducted among a sample of 961 oncologists (11.34% response rate). The responses were analyzed in a multiple linear regression which identified six statistically significant factors driving the diffusion of molecular diagnostic lung cancer tests: reimbursement, attitude towards R&D, information self-assessment, perceived attitudes of colleagues, age and test-pathway strategies. Besides the important role of adequate reimbursement and relevant guidelines, the results of this study suggest that an increasing usage of test-pathway strategies, especially in an office-based setting, can increase the diffusion of molecular diagnostic lung cancer tests in the future. PMID:25562146

Correlation between information diffusion and opinion evolution on social media

NASA Astrophysics Data System (ADS)

Xiong, Fei; Liu, Yun; Zhang, Zhenjiang

2014-12-01

Information diffusion and opinion evolution are often treated as two independent processes. Opinion models assume the topic reaches each agent and agents initially have their own ideas. In fact, the processes of information diffusion and opinion evolution often intertwine with each other. Whether the influence between these two processes plays a role in the system state is unclear. In this paper, we collected more than one million real data from a well-known social platform, and analysed large-scale user diffusion behaviour and opinion formation. We found that user inter-event time follows a two-scaling power-law distribution with two different power exponents. Public opinion stabilizes quickly and evolves toward the direction of convergence, but the consensus state is prevented by a few opponents. We propose a three-state opinion model accompanied by information diffusion. Agents form and exchange their opinions during information diffusion. Conversely, agents' opinions also influence their diffusion actions. Simulations show that the model with a correlation of the two processes produces similar statistical characteristics as empirical results. A fast epidemic process drives individual opinions to converge more obviously. Unlike previous epidemic models, the number of infected agents does not always increase with the update rate, but has a peak with an intermediate value of the rate.

Inter- and intraobserver agreement of ADC measurements of lung cancer in free breathing, breath-hold and respiratory triggered diffusion-weighted MRI.

PubMed

Cui, Lei; Yin, Jian-Bing; Hu, Chun-Hong; Gong, Shen-Chu; Xu, Jun-Feng; Yang, Ju-Shun

2016-01-01

To prospectively evaluate the inter- and intraobserver agreement of apparent diffusion coefficient (ADC) measurements in free breathing, breath-hold, and respiratory triggered diffusion-weighted imaging (DWI) of lung cancer. Twenty-two patients with lung cancer (tumor size >2cm) underwent DWIs (3.0T) in three imaging methods. Lesion ADCs were measured twice by both of the two independent observers and compared. No statistical significance was found among methods, though respiratory-triggered DWI tended to have higher ADCs than breath-hold DWI. Great inter- and intraobserver agreement was shown. ADCs had good inter- and intraobserver agreement in all three DWI methods. Copyright © 2016 Elsevier Inc. All rights reserved.

Radiation effects studies for the high-resolution spectrograph

NASA Technical Reports Server (NTRS)

Smith, L. C.; Becher, J.

1982-01-01

The generation and collection of charge carriers created during the passage of energetic protons through a silicon photodiode array are modeled. Pulse height distributions of noise charge collected during exposure of a digicon type diode array to 21 and 75 MeV protons were obtained. The magnitude of charge collected by a diode from each proton event is determined not only by diffusion, but by statistical considerations involving the ionization process itself. Utilizing analytical solutions to the diffusion equation for transport of minority carriers, together with the Vavilov theory of energy loss fluctuations in thin absorbers, simulations of the pulse height spectra which follow the experimental distributions fairly well are presented and an estimate for the minority carrier diffusion length L sub d is provided.

Landsat test of diffuse reflectance models for aquatic suspended solids measurement

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.; Alfoldi, T. T.

1979-01-01

Landsat radiance data were used to test mathematical models relating diffuse reflectance to aquatic suspended solids concentration. Digital CCT data for Landsat passes over the Bay of Fundy, Nova Scotia were analyzed on a General Electric Co. Image 100 multispectral analysis system. Three data sets were studied separately and together in all combinations with and without solar angle correction. Statistical analysis and chromaticity analysis show that a nonlinear relationship between Landsat radiance and suspended solids concentration is better at curve-fitting than a linear relationship. In particular, the quasi-single-scattering diffuse reflectance model developed by Gordon and coworkers is corroborated. The Gordon model applied to 33 points of MSS 5 data combined from three dates produced r = 0.98.

RESOLVE: A new algorithm for aperture synthesis imaging of extended emission in radio astronomy

NASA Astrophysics Data System (ADS)

Junklewitz, H.; Bell, M. R.; Selig, M.; Enßlin, T. A.

2016-02-01

We present resolve, a new algorithm for radio aperture synthesis imaging of extended and diffuse emission in total intensity. The algorithm is derived using Bayesian statistical inference techniques, estimating the surface brightness in the sky assuming a priori log-normal statistics. resolve estimates the measured sky brightness in total intensity, and the spatial correlation structure in the sky, which is used to guide the algorithm to an optimal reconstruction of extended and diffuse sources. During this process, the algorithm succeeds in deconvolving the effects of the radio interferometric point spread function. Additionally, resolve provides a map with an uncertainty estimate of the reconstructed surface brightness. Furthermore, with resolve we introduce a new, optimal visibility weighting scheme that can be viewed as an extension to robust weighting. In tests using simulated observations, the algorithm shows improved performance against two standard imaging approaches for extended sources, Multiscale-CLEAN and the Maximum Entropy Method.

Application of a planetary wave breaking parameterization to stratospheric circulation statistics

NASA Technical Reports Server (NTRS)

Randel, William J.; Garcia, Rolando R.

1994-01-01

The planetary wave parameterization scheme developed recently by Garcia is applied to statospheric circulation statistics derived from 12 years of National Meteorological Center operational stratospheric analyses. From the data a planetary wave breaking criterion (based on the ratio of the eddy to zonal mean meridional potential vorticity (PV) gradients), a wave damping rate, and a meridional diffusion coefficient are calculated. The equatorward flank of the polar night jet during winter is identified as a wave breaking region from the observed PV gradients; the region moves poleward with season, covering all high latitudes in spring. Derived damping rates maximize in the subtropical upper stratosphere (the 'surf zone'), with damping time scales of 3-4 days. Maximum diffusion coefficients follow the spatial patterns of the wave breaking criterion, with magnitudes comparable to prior published estimates. Overall, the observed results agree well with the parameterized calculations of Garcia.

Multivariate space - time analysis of PRE-STORM precipitation

NASA Technical Reports Server (NTRS)

Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

1994-01-01

This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

Statistical mechanics of an ideal active fluid confined in a channel

NASA Astrophysics Data System (ADS)

Wagner, Caleb; Baskaran, Aparna; Hagan, Michael

The statistical mechanics of ideal active Brownian particles (ABPs) confined in a channel is studied by obtaining the exact solution of the steady-state Smoluchowski equation for the 1-particle distribution function. The solution is derived using results from the theory of two-way diffusion equations, combined with an iterative procedure that is justified by numerical results. Using this solution, we quantify the effects of confinement on the spatial and orientational order of the ensemble. Moreover, we rigorously show that both the bulk density and the fraction of particles on the channel walls obey simple scaling relations as a function of channel width. By considering a constant-flux steady state, an effective diffusivity for ABPs is derived which shows signatures of the persistent motion that characterizes ABP trajectories. Finally, we discuss how our techniques generalize to other active models, including systems whose activity is modeled in terms of an Ornstein-Uhlenbeck process.

There’s plenty of light at the bottom: statistics of photon penetration depth in random media

PubMed Central

Martelli, Fabrizio; Binzoni, Tiziano; Pifferi, Antonio; Spinelli, Lorenzo; Farina, Andrea; Torricelli, Alessandro

2016-01-01

We propose a comprehensive statistical approach describing the penetration depth of light in random media. The presented theory exploits the concept of probability density function f(z|ρ, t) for the maximum depth reached by the photons that are eventually re-emitted from the surface of the medium at distance ρ and time t. Analytical formulas for f, for the mean maximum depth 〈zmax〉 and for the mean average depth reached by the detected photons at the surface of a diffusive slab are derived within the framework of the diffusion approximation to the radiative transfer equation, both in the time domain and the continuous wave domain. Validation of the theory by means of comparisons with Monte Carlo simulations is also presented. The results are of interest for many research fields such as biomedical optics, advanced microscopy and disordered photonics. PMID:27256988

The influence of non-Gaussian distribution functions on the time-dependent perpendicular transport of energetic particles

NASA Astrophysics Data System (ADS)

Lasuik, J.; Shalchi, A.

2018-06-01

In the current paper we explore the influence of the assumed particle statistics on the transport of energetic particles across a mean magnetic field. In previous work the assumption of a Gaussian distribution function was standard, although there have been known cases for which the transport is non-Gaussian. In the present work we combine a kappa distribution with the ordinary differential equation provided by the so-called unified non-linear transport theory. We then compute running perpendicular diffusion coefficients for different values of κ and turbulence configurations. We show that changing the parameter κ slightly increases or decreases the perpendicular diffusion coefficient depending on the considered turbulence configuration. Since these changes are small, we conclude that the assumed statistics is less significant in particle transport theory. The results obtained in the current paper support to use a Gaussian distribution function as usually done in particle transport theory.

Individual classification of Alzheimer's disease with diffusion magnetic resonance imaging.

PubMed

Schouten, Tijn M; Koini, Marisa; Vos, Frank de; Seiler, Stephan; Rooij, Mark de; Lechner, Anita; Schmidt, Reinhold; Heuvel, Martijn van den; Grond, Jeroen van der; Rombouts, Serge A R B

2017-05-15

Diffusion magnetic resonance imaging (MRI) is a powerful non-invasive method to study white matter integrity, and is sensitive to detect differences in Alzheimer's disease (AD) patients. Diffusion MRI may be able to contribute towards reliable diagnosis of AD. We used diffusion MRI to classify AD patients (N=77), and controls (N=173). We use different methods to extract information from the diffusion MRI data. First, we use the voxel-wise diffusion tensor measures that have been skeletonised using tract based spatial statistics. Second, we clustered the voxel-wise diffusion measures with independent component analysis (ICA), and extracted the mixing weights. Third, we determined structural connectivity between Harvard Oxford atlas regions with probabilistic tractography, as well as graph measures based on these structural connectivity graphs. Classification performance for voxel-wise measures ranged between an AUC of 0.888, and 0.902. The ICA-clustered measures ranged between an AUC of 0.893, and 0.920. The AUC for the structural connectivity graph was 0.900, while graph measures based upon this graph ranged between an AUC of 0.531, and 0.840. All measures combined with a sparse group lasso resulted in an AUC of 0.896. Overall, fractional anisotropy clustered into ICA components was the best performing measure. These findings may be useful for future incorporation of diffusion MRI into protocols for AD classification, or as a starting point for early detection of AD using diffusion MRI. Copyright © 2017 Elsevier Inc. All rights reserved.

Steepest Ascent Low/Non-Low-Frequency Ratio in Empirical Mode Decomposition to Separate Deterministic and Stochastic Velocities From a Single Lagrangian Drifter

NASA Astrophysics Data System (ADS)

Chu, Peter C.

2018-03-01

SOund Fixing And Ranging (RAFOS) floats deployed by the Naval Postgraduate School (NPS) in the California Current system from 1992 to 2001 at depth between 150 and 600 m (http://www.oc.nps.edu/npsRAFOS/) are used to study 2-D turbulent characteristics. Each drifter trajectory is adaptively decomposed using the empirical mode decomposition (EMD) into a series of intrinsic mode functions (IMFs) with corresponding specific scale for each IMF. A new steepest ascent low/non-low-frequency ratio is proposed in this paper to separate a Lagrangian trajectory into low-frequency (nondiffusive, i.e., deterministic) and high-frequency (diffusive, i.e., stochastic) components. The 2-D turbulent (or called eddy) diffusion coefficients are calculated on the base of the classical turbulent diffusion with mixing length theory from stochastic component of a single drifter. Statistical characteristics of the calculated 2-D turbulence length scale, strength, and diffusion coefficients from the NPS RAFOS data are presented with the mean values (over the whole drifters) of the 2-D diffusion coefficients comparable to the commonly used diffusivity tensor method.

Competing quantum effects in the free energy profiles and diffusion rates of hydrogen and deuterium molecules through clathrate hydrates.

PubMed

Cendagorta, Joseph R; Powers, Anna; Hele, Timothy J H; Marsalek, Ondrej; Bačić, Zlatko; Tuckerman, Mark E

2016-11-30

Clathrate hydrates hold considerable promise as safe and economical materials for hydrogen storage. Here we present a quantum mechanical study of H 2 and D 2 diffusion through a hexagonal face shared by two large cages of clathrate hydrates over a wide range of temperatures. Path integral molecular dynamics simulations are used to compute the free-energy profiles for the diffusion of H 2 and D 2 as a function of temperature. Ring polymer molecular dynamics rate theory, incorporating both exact quantum statistics and approximate quantum dynamical effects, is utilized in the calculations of the H 2 and D 2 diffusion rates in a broad temperature interval. We find that the shape of the quantum free-energy profiles and their height relative to the classical free energy barriers at a given temperature, as well as the rate of diffusion, are strongly affected by competing quantum effects: above 25 K, zero-point energy (ZPE) perpendicular to the reaction path for diffusion between cavities decreases the quantum rate compared to the classical rate, whereas at lower temperatures tunneling outcompetes the ZPE and as a result the quantum rate is greater than the classical rate.

Laser depth profiling studies of helium diffusion in Durango fluorapatite

NASA Astrophysics Data System (ADS)

van Soest, Matthijs C.; Monteleone, Brian D.; Hodges, Kip V.; Boyce, Jeremy W.

2011-05-01

Ultraviolet lasers coupled with sensitive mass spectrometers provide a useful way to measure laboratory-induced noble gas diffusion profiles in minerals, thus enabling the calculation of diffusion parameters. We illustrate this laser ablation depth profiling (LADP) technique for a previously well-studied mineral-isotopic system: 4He in Durango fluorapatite. LADP studies were conducted on oriented, polished slabs from a single crystal that were heated under vacuum to a variety of temperatures between 300 and 450 °C for variable times. The resolved 4He profiles exhibited error-function loss as predicted by previous bulk 4He diffusion studies. All of the slabs, regardless of crystallographic orientation, yielded modeled diffusivities that are statistically co-linear on an Arrhenius diagram, suggesting no diffusional anisotropy of 4He in this material. The data indicate an activation energy of 142.2 ± 5.0 (2 σ) kJ/mol and diffusivity at infinite temperature - reported as ln( D0) - of -4.71 ± 0.94 (2 σ) m 2/s. These values imply a bulk closure temperature for 4He in Durango fluorapatite of 74 °C for a 50 μm radius grain, infinite cylinder geometry, and a cooling rate of 10 °C/Myr.

Evaluation of the direct and diffusion methods for the determination of fluoride content in table salt

PubMed Central

Martínez-Mier, E. Angeles; Soto-Rojas, Armando E.; Buckley, Christine M.; Margineda, Jorge; Zero, Domenick T.

2010-01-01

Objective The aim of this study was to assess methods currently used for analyzing fluoridated salt in order to identify the most useful method for this type of analysis. Basic research design Seventy-five fluoridated salt samples were obtained. Samples were analyzed for fluoride content, with and without pretreatment, using direct and diffusion methods. Element analysis was also conducted in selected samples. Fluoride was added to ultra pure NaCl and non-fluoridated commercial salt samples and Ca and Mg were added to fluoride samples in order to assess fluoride recoveries using modifications to the methods. Results Larger amounts of fluoride were found and recovered using diffusion than direct methods (96%–100% for diffusion vs. 67%–90% for direct). Statistically significant differences were obtained between direct and diffusion methods using different ion strength adjusters. Pretreatment methods reduced the amount of recovered fluoride. Determination of fluoride content was influenced both by the presence of NaCl and other ions in the salt. Conclusion Direct and diffusion techniques for analysis of fluoridated salt are suitable methods for fluoride analysis. The choice of method should depend on the purpose of the analysis. PMID:20088217

An exact and efficient first passage time algorithm for reaction–diffusion processes on a 2D-lattice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bezzola, Andri, E-mail: andri.bezzola@gmail.com; Bales, Benjamin B., E-mail: bbbales2@gmail.com; Alkire, Richard C., E-mail: r-alkire@uiuc.edu

2014-01-01

We present an exact and efficient algorithm for reaction–diffusion–nucleation processes on a 2D-lattice. The algorithm makes use of first passage time (FPT) to replace the computationally intensive simulation of diffusion hops in KMC by larger jumps when particles are far away from step-edges or other particles. Our approach computes exact probability distributions of jump times and target locations in a closed-form formula, based on the eigenvectors and eigenvalues of the corresponding 1D transition matrix, maintaining atomic-scale resolution of resulting shapes of deposit islands. We have applied our method to three different test cases of electrodeposition: pure diffusional aggregation for largemore » ranges of diffusivity rates and for simulation domain sizes of up to 4096×4096 sites, the effect of diffusivity on island shapes and sizes in combination with a KMC edge diffusion, and the calculation of an exclusion zone in front of a step-edge, confirming statistical equivalence to standard KMC simulations. The algorithm achieves significant speedup compared to standard KMC for cases where particles diffuse over long distances before nucleating with other particles or being captured by larger islands.« less

Changes in diffusion path length with old age in diffuse optical tomography

NASA Astrophysics Data System (ADS)

Bonnéry, Clément; Leclerc, Paul-Olivier; Desjardins, Michèle; Hoge, Rick; Bherer, Louis; Pouliot, Philippe; Lesage, Frédéric

2012-05-01

Diffuse, optical near infrared imaging is increasingly being used in various neurocognitive contexts where changes in optical signals are interpreted through activation maps. Statistical population comparison of different age or clinical groups rely on the relative homogeneous distribution of measurements across subjects in order to infer changes in brain function. In the context of an increasing use of diffuse optical imaging with older adult populations, changes in tissue properties and anatomy with age adds additional confounds. Few studies investigated these changes with age. Duncan et al. measured the so-called diffusion path length factor (DPF) in a large population but did not explore beyond the age of 51 after which physiological and anatomical changes are expected to occur [Pediatr. Res. 39(5), 889-894 (1996)]. With increasing interest in studying the geriatric population with optical imaging, we studied changes in tissue properties in young and old subjects using both magnetic resonance imaging (MRI)-guided Monte-Carlo simulations and time-domain diffuse optical imaging. Our results, measured in the frontal cortex, show changes in DPF that are smaller than previously measured by Duncan et al. in a younger population. The origin of these changes are studied using simulations and experimental measures.

Multilinear Computing and Multilinear Algebraic Geometry

DTIC Science & Technology

2016-08-10

instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send...performance period of this project. 15. SUBJECT TERMS Tensors , multilinearity, algebraic geometry, numerical computations, computational tractability, high...Reset DISTRIBUTION A: Distribution approved for public release. DISTRIBUTION A: Distribution approved for public release. INSTRUCTIONS FOR COMPLETING

Tractable Analysis for Large Social Networks

ERIC Educational Resources Information Center

Zhang, Bin

2012-01-01

Social scientists usually are more interested in consumers' dichotomous choice, such as purchase a product or not, adopt a technology or not, etc. However, up to date, there is nearly no model can help us solve the problem of multi-network effects comparison with a dichotomous dependent variable. Furthermore, the study of multi-network…

Sharp Truncation of an Electric Field: An Idealized Model That Warrants Caution

ERIC Educational Resources Information Center

Tu, Hong; Zhu, Jiongming

2016-01-01

In physics, idealized models are often used to simplify complex situations. The motivation of the idealization is to make the real complex system tractable by adopting certain simplifications. In this treatment some unnecessary, negligible aspects are stripped away (so-called Aristotelian idealization), or some deliberate distortions are involved…

Automatic Item Generation via Frame Semantics: Natural Language Generation of Math Word Problems.

ERIC Educational Resources Information Center

Deane, Paul; Sheehan, Kathleen

This paper is an exploration of the conceptual issues that have arisen in the course of building a natural language generation (NLG) system for automatic test item generation. While natural language processing techniques are applicable to general verbal items, mathematics word problems are particularly tractable targets for natural language…

Functional Imaging and Optogenetics in Drosophila

PubMed Central

Simpson, Julie H.; Looger, Loren L.

2018-01-01

Understanding how activity patterns in specific neural circuits coordinate an animal’s behavior remains a key area of neuroscience research. Genetic tools and a brain of tractable complexity make Drosophila a premier model organism for these studies. Here, we review the wealth of reagents available to map and manipulate neuronal activity with light. PMID:29618589

Kinetic Modeling of Next-Generation High-Energy, High-Intensity Laser-Ion Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albright, Brian James; Yin, Lin; Stark, David James

One of the long-standing problems in the community is the question of how we can model “next-generation” laser-ion acceleration in a computationally tractable way. A new particle tracking capability in the LANL VPIC kinetic plasma modeling code has enabled us to solve this long-standing problem

What the Student Does: Teaching for Enhanced Learning

ERIC Educational Resources Information Center

Biggs, John

2012-01-01

Many teachers see major difficulties in maintaining academic standards in today's larger and more diversified classes. The problem becomes more tractable if learning outcomes are seen as more a function of students' activities than of their fixed characteristics. The teacher's job is then to organise the teaching/learning context so that all…

Computational Nonlinear Morphology with Emphasis on Semitic Languages. Studies in Natural Language Processing.

ERIC Educational Resources Information Center

Kiraz, George Anton

This book presents a tractable computational model that can cope with complex morphological operations, especially in Semitic languages, and less complex morphological systems present in Western languages. It outlines a new generalized regular rewrite rule system that uses multiple finite-state automata to cater to root-and-pattern morphology,…

Design and Functionality of the Graphical Interactive Narrative (Gin) System Version 0.2

DTIC Science & Technology

2012-08-01

System. The purpose of the Gin system is to increase the interactivity and sense of agency for human subjects in virtual environments (VEs) used for...tractability of scenario development while providing the user with an increased sense of agency by allowing them to control their own navigation

Integrating Model-Based Verification into Software Design Education

ERIC Educational Resources Information Center

Yilmaz, Levent; Wang, Shuo

2005-01-01

Proper design analysis is indispensable to assure quality and reduce emergent costs due to faulty software. Teaching proper design verification skills early during pedagogical development is crucial, as such analysis is the only tractable way of resolving software problems early when they are easy to fix. The premise of the presented strategy is…

A BAC-based physical map of the Hessian fly (Mayetiola destructor) genome anchored to polytene chromosomes

USDA-ARS?s Scientific Manuscript database

The Hessian fly (Mayetiola destructor) is an important insect pest of wheat and an experimental organism for studies of plant-insect interactions. It has tractable genetics, polytene chromosomes, a relatively small genome (158 Mb), and shares a gene-for-gene relationship with wheat. To improve its...

Daddy issues: paternal effects on phenotype

PubMed Central

Rando, Oliver J.

2012-01-01

The once-popular, then heretical, idea that ancestral environment can affect the phenotype of future generations is coming back into vogue, due to advances in the field of epigenetic inheritance. How paternal environmental conditions influence the phenotype of progeny is now a tractable question, and researchers are exploring potential mechanisms underlying such effects. PMID:23141533

Computing Role Assignments of Proper Interval Graphs in Polynomial Time

NASA Astrophysics Data System (ADS)

Heggernes, Pinar; van't Hof, Pim; Paulusma, Daniël

A homomorphism from a graph G to a graph R is locally surjective if its restriction to the neighborhood of each vertex of G is surjective. Such a homomorphism is also called an R-role assignment of G. Role assignments have applications in distributed computing, social network theory, and topological graph theory. The Role Assignment problem has as input a pair of graphs (G,R) and asks whether G has an R-role assignment. This problem is NP-complete already on input pairs (G,R) where R is a path on three vertices. So far, the only known non-trivial tractable case consists of input pairs (G,R) where G is a tree. We present a polynomial time algorithm that solves Role Assignment on all input pairs (G,R) where G is a proper interval graph. Thus we identify the first graph class other than trees on which the problem is tractable. As a complementary result, we show that the problem is Graph Isomorphism-hard on chordal graphs, a superclass of proper interval graphs and trees.

Alternative Parameterizations for Cluster Editing

NASA Astrophysics Data System (ADS)

Komusiewicz, Christian; Uhlmann, Johannes

Given an undirected graph G and a nonnegative integer k, the NP-hard Cluster Editing problem asks whether G can be transformed into a disjoint union of cliques by applying at most k edge modifications. In the field of parameterized algorithmics, Cluster Editing has almost exclusively been studied parameterized by the solution size k. Contrastingly, in many real-world instances it can be observed that the parameter k is not really small. This observation motivates our investigation of parameterizations of Cluster Editing different from the solution size k. Our results are as follows. Cluster Editing is fixed-parameter tractable with respect to the parameter "size of a minimum cluster vertex deletion set of G", a typically much smaller parameter than k. Cluster Editing remains NP-hard on graphs with maximum degree six. A restricted but practically relevant version of Cluster Editing is fixed-parameter tractable with respect to the combined parameter "number of clusters in the target graph" and "maximum number of modified edges incident to any vertex in G". Many of our results also transfer to the NP-hard Cluster Deletion problem, where only edge deletions are allowed.

Rendering the Intractable More Tractable: Tools from Caenorhabditis elegans Ripe for Import into Parasitic Nematodes

PubMed Central

Ward, Jordan D.

2015-01-01

Recent and rapid advances in genetic and molecular tools have brought spectacular tractability to Caenorhabditis elegans, a model that was initially prized because of its simple design and ease of imaging. C. elegans has long been a powerful model in biomedical research, and tools such as RNAi and the CRISPR/Cas9 system allow facile knockdown of genes and genome editing, respectively. These developments have created an additional opportunity to tackle one of the most debilitating burdens on global health and food security: parasitic nematodes. I review how development of nonparasitic nematodes as genetic models informs efforts to import tools into parasitic nematodes. Current tools in three commonly studied parasites (Strongyloides spp., Brugia malayi, and Ascaris suum) are described, as are tools from C. elegans that are ripe for adaptation and the benefits and barriers to doing so. These tools will enable dissection of a huge array of questions that have been all but completely impenetrable to date, allowing investigation into host–parasite and parasite–vector interactions, and the genetic basis of parasitism. PMID:26644478

Doctoral Training in Statistics, Measurement, and Methodology in Psychology: Replication and Extension of Aiken, West, Sechrest, and Reno's (1990) Survey of PhD Programs in North America

ERIC Educational Resources Information Center

Aiken, Leona S.; West, Stephen G.; Millsap, Roger E.

2008-01-01

In a survey of all PhD programs in psychology in the United States and Canada, the authors documented the quantitative methodology curriculum (statistics, measurement, and research design) to examine the extent to which innovations in quantitative methodology have diffused into the training of PhDs in psychology. In all, 201 psychology PhD…

White matter microstructure in transsexuals and controls investigated by diffusion tensor imaging.

PubMed

Kranz, Georg S; Hahn, Andreas; Kaufmann, Ulrike; Küblböck, Martin; Hummer, Allan; Ganger, Sebastian; Seiger, Rene; Winkler, Dietmar; Swaab, Dick F; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2014-11-12

Biological causes underpinning the well known gender dimorphisms in human behavior, cognition, and emotion have received increased attention in recent years. The advent of diffusion-weighted magnetic resonance imaging has permitted the investigation of the white matter microstructure in unprecedented detail. Here, we aimed to study the potential influences of biological sex, gender identity, sex hormones, and sexual orientation on white matter microstructure by investigating transsexuals and healthy controls using diffusion tensor imaging (DTI). Twenty-three female-to-male (FtM) and 21 male-to-female (MtF) transsexuals, as well as 23 female (FC) and 22 male (MC) controls underwent DTI at 3 tesla. Fractional anisotropy, axial, radial, and mean diffusivity were calculated using tract-based spatial statistics (TBSS) and fiber tractography. Results showed widespread significant differences in mean diffusivity between groups in almost all white matter tracts. FCs had highest mean diffusivities, followed by FtM transsexuals with lower values, MtF transsexuals with further reduced values, and MCs with lowest values. Investigating axial and radial diffusivities showed that a transition in axial diffusivity accounted for mean diffusivity results. No significant differences in fractional anisotropy maps were found between groups. Plasma testosterone levels were strongly correlated with mean, axial, and radial diffusivities. However, controlling for individual estradiol, testosterone, or progesterone plasma levels or for subjects' sexual orientation did not change group differences. Our data harmonize with the hypothesis that fiber tract development is influenced by the hormonal environment during late prenatal and early postnatal brain development. Copyright © 2014 the authors 0270-6474/14/3415466-10$15.00/0.

Defect Genome of Cubic Perovskites for Fuel Cell Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balachandran, Janakiraman; Lin, Lianshan; Anchell, Jonathan S.

Heterogeneities such as point defects, inherent to material systems, can profoundly influence material functionalities critical for numerous energy applications. This influence in principle can be identified and quantified through development of large defect data sets which we call the defect genome, employing high-throughput ab initio calculations. However, high-throughput screening of material models with point defects dramatically increases the computational complexity and chemical search space, creating major impediments toward developing a defect genome. In this paper, we overcome these impediments by employing computationally tractable ab initio models driven by highly scalable workflows, to study formation and interaction of various point defectsmore » (e.g., O vacancies, H interstitials, and Y substitutional dopant), in over 80 cubic perovskites, for potential proton-conducting ceramic fuel cell (PCFC) applications. The resulting defect data sets identify several promising perovskite compounds that can exhibit high proton conductivity. Furthermore, the data sets also enable us to identify and explain, insightful and novel correlations among defect energies, material identities, and defect-induced local structural distortions. Finally, such defect data sets and resultant correlations are necessary to build statistical machine learning models, which are required to accelerate discovery of new materials.« less

Defect Genome of Cubic Perovskites for Fuel Cell Applications

DOE PAGES

Balachandran, Janakiraman; Lin, Lianshan; Anchell, Jonathan S.; ...

2017-10-10

Heterogeneities such as point defects, inherent to material systems, can profoundly influence material functionalities critical for numerous energy applications. This influence in principle can be identified and quantified through development of large defect data sets which we call the defect genome, employing high-throughput ab initio calculations. However, high-throughput screening of material models with point defects dramatically increases the computational complexity and chemical search space, creating major impediments toward developing a defect genome. In this paper, we overcome these impediments by employing computationally tractable ab initio models driven by highly scalable workflows, to study formation and interaction of various point defectsmore » (e.g., O vacancies, H interstitials, and Y substitutional dopant), in over 80 cubic perovskites, for potential proton-conducting ceramic fuel cell (PCFC) applications. The resulting defect data sets identify several promising perovskite compounds that can exhibit high proton conductivity. Furthermore, the data sets also enable us to identify and explain, insightful and novel correlations among defect energies, material identities, and defect-induced local structural distortions. Finally, such defect data sets and resultant correlations are necessary to build statistical machine learning models, which are required to accelerate discovery of new materials.« less

Competition between drag and Coulomb interactions in turbulent particle-laden flows using a coupled-fluid-Ewald-summation based approach

NASA Astrophysics Data System (ADS)

Yao, Yuan; Capecelatro, Jesse

2018-03-01

We present a numerical study on inertial electrically charged particles suspended in a turbulent carrier phase. Fluid-particle interactions are accounted for in an Eulerian-Lagrangian (EL) framework and coupled to a Fourier-based Ewald summation method, referred to as the particle-particle-particle-mesh (P3M ) method, to accurately capture short- and long-range electrostatic forces in a tractable manner. The EL P3M method is used to assess the competition between drag and Coulomb forces for a range of Stokes numbers and charge densities. Simulations of like- and oppositely charged particles suspended in a two-dimensional Taylor-Green vortex and three-dimensional homogeneous isotropic turbulence are reported. It is found that even in dilute suspensions, the short-range electric potential plays an important role in flows that admit preferential concentration. Suspensions of oppositely charged particles are observed to agglomerate in the form of chains and rings. Comparisons between the particle-mesh method typically employed in fluid-particle calculations and P3M are reported, in addition to one-point and two-point statistics to quantify the level of clustering as a function of Reynolds number, Stokes number, and nondimensional electric settling velocity.

DNA-DNA interaction beyond the ground state

NASA Astrophysics Data System (ADS)

Lee, D. J.; Wynveen, A.; Kornyshev, A. A.

2004-11-01

The electrostatic interaction potential between DNA duplexes in solution is a basis for the statistical mechanics of columnar DNA assemblies. It may also play an important role in recombination of homologous genes. We develop a theory of this interaction that includes thermal torsional fluctuations of DNA using field-theoretical methods and Monte Carlo simulations. The theory extends and rationalizes the earlier suggested variational approach which was developed in the context of a ground state theory of interaction of nonhomologous duplexes. It shows that the heuristic variational theory is equivalent to the Hartree self-consistent field approximation. By comparison of the Hartree approximation with an exact solution based on the QM analogy of path integrals, as well as Monte Carlo simulations, we show that this easily analytically-tractable approximation works very well in most cases. Thermal fluctuations do not remove the ability of DNA molecules to attract each other at favorable azimuthal conformations, neither do they wash out the possibility of electrostatic “snap-shot” recognition of homologous sequences, considered earlier on the basis of ground state calculations. At short distances DNA molecules undergo a “torsional alignment transition,” which is first order for nonhomologous DNA and weaker order for homologous sequences.

Potentials of Mean Force With Ab Initio Mixed Hamiltonian Models of Solvation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dupuis, Michel; Schenter, Gregory K.; Garrett, Bruce C.

2003-08-01

We give an account of a computationally tractable and efficient procedure for the calculation of potentials of mean force using mixed Hamiltonian models of electronic structure where quantum subsystems are described with computationally intensive ab initio wavefunctions. The mixed Hamiltonian is mapped into an all-classical Hamiltonian that is amenable to a thermodynamic perturbation treatment for the calculation of free energies. A small number of statistically uncorrelated (solute-solvent) configurations are selected from the Monte Carlo random walk generated with the all-classical Hamiltonian approximation. Those are used in the averaging of the free energy using the mixed quantum/classical Hamiltonian. The methodology ismore » illustrated for the micro-solvated SN2 substitution reaction of methyl chloride by hydroxide. We also compare the potential of mean force calculated with the above protocol with an approximate formalism, one in which the potential of mean force calculated with the all-classical Hamiltonian is simply added to the energy of the isolated (non-solvated) solute along the reaction path. Interestingly the latter approach is found to be in semi-quantitative agreement with the full mixed Hamiltonian approximation.« less

Modelling ecological systems in a changing world

PubMed Central

Evans, Matthew R.

2012-01-01

The world is changing at an unprecedented rate. In such a situation, we need to understand the nature of the change and to make predictions about the way in which it might affect systems of interest; often we may also wish to understand what might be done to mitigate the predicted effects. In ecology, we usually make such predictions (or forecasts) by making use of mathematical models that describe the system and projecting them into the future, under changed conditions. Approaches emphasizing the desirability of simple models with analytical tractability and those that use assumed causal relationships derived statistically from data currently dominate ecological modelling. Although such models are excellent at describing the way in which a system has behaved, they are poor at predicting its future state, especially in novel conditions. In order to address questions about the impact of environmental change, and to understand what, if any, action might be taken to ameliorate it, ecologists need to develop the ability to project models into novel, future conditions. This will require the development of models based on understanding the processes that result in a system behaving the way it does, rather than relying on a description of the system, as a whole, remaining valid indefinitely. PMID:22144381

Hierarchical Probabilistic Inference of Cosmic Shear

NASA Astrophysics Data System (ADS)

Schneider, Michael D.; Hogg, David W.; Marshall, Philip J.; Dawson, William A.; Meyers, Joshua; Bard, Deborah J.; Lang, Dustin

2015-07-01

Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.

Quantitative MRI of the spinal cord and brain in adrenomyeloneuropathy: in vivo assessment of structural changes.

PubMed

Castellano, Antonella; Papinutto, Nico; Cadioli, Marcello; Brugnara, Gianluca; Iadanza, Antonella; Scigliuolo, Graziana; Pareyson, Davide; Uziel, Graziella; Köhler, Wolfgang; Aubourg, Patrick; Falini, Andrea; Henry, Roland G; Politi, Letterio S; Salsano, Ettore

2016-06-01

Adrenomyeloneuropathy is the late-onset form of X-linked adrenoleukodystrophy, and is considered the most frequent metabolic hereditary spastic paraplegia. In adrenomyeloneuropathy the spinal cord is the main site of pathology. Differently from quantitative magnetic resonance imaging of the brain, little is known about the feasibility and utility of advanced neuroimaging in quantifying the spinal cord abnormalities in hereditary diseases. Moreover, little is known about the subtle pathological changes that can characterize the brain of adrenomyeloneuropathy subjects in the early stages of the disease. We performed a cross-sectional study on 13 patients with adrenomyeloneuropathy and 12 age-matched healthy control subjects who underwent quantitative magnetic resonance imaging to assess the structural changes of the upper spinal cord and brain. Total cord areas from C2-3 to T2-3 level were measured, and diffusion tensor imaging metrics, i.e. fractional anisotropy, mean, axial and radial diffusivity values were calculated in both grey and white matter of spinal cord. In the brain, grey matter regions were parcellated with Freesurfer and average volume and thickness, and mean diffusivity and fractional anisotropy from co-registered diffusion maps were calculated in each region. Brain white matter diffusion tensor imaging metrics were assessed using whole-brain tract-based spatial statistics, and tractography-based analysis on corticospinal tracts. Correlations among clinical, structural and diffusion tensor imaging measures were calculated. In patients total cord area was reduced by 26.3% to 40.2% at all tested levels (P < 0.0001). A mean 16% reduction of spinal cord white matter fractional anisotropy (P ≤ 0.0003) with a concomitant 9.7% axial diffusivity reduction (P < 0.009) and 34.5% radial diffusivity increase (P < 0.009) was observed, suggesting co-presence of axonal degeneration and demyelination. Brain tract-based spatial statistics showed a marked reduction of fractional anisotropy, increase of radial diffusivity (P < 0.001) and no axial diffusivity changes in several white matter tracts, including corticospinal tracts and optic radiations, indicating predominant demyelination. Tractography-based analysis confirmed the results within corticospinal tracts. No significant cortical volume and thickness reduction or grey matter diffusion tensor imaging values alterations were observed in patients. A correlation between radial diffusivity and disease duration along the corticospinal tracts (r = 0.806, P < 0.01) was found. In conclusion, in adrenomyeloneuropathy patients quantitative magnetic resonance imaging-derived measures identify and quantify structural changes in the upper spinal cord and brain which agree with the expected histopathology, and suggest that the disease could be primarily caused by a demyelination rather than a primitive axonal damage. The results of this study may also encourage the employment of quantitative magnetic resonance imaging in other hereditary diseases with spinal cord involvement. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effect of CorrelatedRotational Noise

NASA Astrophysics Data System (ADS)

Hancock, Benjamin; Wagner, Caleb; Baskaran, Aparna

The traditional model of a self-propelled particle (SPP) is one where the body axis along which the particle travels reorients itself through rotational diffusion. If the reorientation process was driven by colored noise, instead of the standard Gaussian white noise, the resulting statistical mechanics cannot be accessed through conventional methods. In this talk we present results comparing three methods of deriving the statistical mechanics of a SPP with a reorientation process driven by colored noise. We illustrate the differences/similarities in the resulting statistical mechanics by their ability to accurately capture the particles response to external aligning fields.

Strongly anomalous diffusion in sheared magnetic configurations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanden Eijnden, E.; Balescu, R.

1996-03-01

The statistical behavior of magnetic lines in a sheared magnetic configuration with reference surface {ital x}=0 is investigated within the framework of the kinetic theory. A Liouville equation is associated with the equations of motion of the stochastic magnetic lines. After averaging over an ensemble of realizations, it yields a convection-diffusion equation within the quasilinear approximation. The diffusion coefficients are space dependent and peaked around the reference surface {ital x}=0. Due to the shear, the diffusion of lines away from the reference surface is slowed down. The behavior of the lines is asymptotically strongly non-Gaussian. The reference surface acts likemore » an attractor around which the magnetic lines spread with an effective subdiffusive behavior. Comparison is also made with more usual treatments based on the study of the first two moments equations. For sheared systems, it is explicitly shown that the Corrsin approximation assumed in the latter approach is no longer valid. It is also concluded that the diffusion coefficients cannot be derived from the mean square displacement of the magnetic lines in an inhomogeneous medium. {copyright} {ital 1996 American Institute of Physics.}« less

Slowing down of ring polymer diffusion caused by inter-ring threading.

PubMed

Lee, Eunsang; Kim, Soree; Jung, YounJoon

2015-06-01

Diffusion of long ring polymers in a melt is much slower than the reorganization of their internal structures. While direct evidence for entanglements has not been observed in the long ring polymers unlike linear polymer melts, threading between the rings is suspected to be the main reason for slowing down of ring polymer diffusion. It is, however, difficult to define the threading configuration between two rings because the rings have no chain end. In this work, evidence for threading dynamics of ring polymers is presented by using molecular dynamics simulation and applying a novel analysis method. The simulation results are analyzed in terms of the statistics of persistence and exchange times that have proved useful in studying heterogeneous dynamics of glassy systems. It is found that the threading time of ring polymer melts increases more rapidly with the degree of polymerization than that of linear polymer melts. This indicates that threaded ring polymers cannot diffuse until an unthreading event occurs, which results in the slowing down of ring polymer diffusion. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Continuum mesoscopic framework for multiple interacting species and processes on multiple site types and/or crystallographic planes.

PubMed

Chatterjee, Abhijit; Vlachos, Dionisios G

2007-07-21

While recently derived continuum mesoscopic equations successfully bridge the gap between microscopic and macroscopic physics, so far they have been derived only for simple lattice models. In this paper, general deterministic continuum mesoscopic equations are derived rigorously via nonequilibrium statistical mechanics to account for multiple interacting surface species and multiple processes on multiple site types and/or different crystallographic planes. Adsorption, desorption, reaction, and surface diffusion are modeled. It is demonstrated that contrary to conventional phenomenological continuum models, microscopic physics, such as the interaction potential, determines the final form of the mesoscopic equation. Models of single component diffusion and binary diffusion of interacting particles on single-type site lattice and of single component diffusion on complex microporous materials' lattices consisting of two types of sites are derived, as illustrations of the mesoscopic framework. Simplification of the diffusion mesoscopic model illustrates the relation to phenomenological models, such as the Fickian and Maxwell-Stefan transport models. It is demonstrated that the mesoscopic equations are in good agreement with lattice kinetic Monte Carlo simulations for several prototype examples studied.

Theoretical and experimental models of the diffuse radar backscatter from Mars

NASA Technical Reports Server (NTRS)

England, A. W.

1995-01-01

The general objective for this work was to develop a theoretically and experimentally consistent explanation for the diffuse component of radar backscatter from Mars. The strength, variability, and wavelength independence of Mars' diffuse backscatter are unique among our Moon and the terrestrial planets. This diffuse backscatter is generally attributed to wavelength-scale surface roughness and to rock clasts within the Martian regolith. Through the combination of theory and experiment, the authors attempted to bound the range of surface characteristics that could produce the observed diffuse backscatter. Through these bounds they gained a limited capability for data inversion. Within this umbrella, specific objectives were: (1) To better define the statistical roughness parameters of Mars' surface so that they are consistent with observed radar backscatter data, and with the physical and chemical characteristics of Mars' surface as inferred from Mariner 9, the Viking probes, and Earth-based spectroscopy; (2) To better understand the partitioning between surface and volume scattering in the Mars regolith; (3) To develop computational models of Mars' radio emission that incorporate frequency dependent, surface and volume scattering.

Diffusion of medical technology: the role of financing.

PubMed

Cappellaro, Giulia; Ghislandi, Simone; Anessi-Pessina, Eugenio

2011-04-01

In the last decade the pace of innovation in medical technology has accelerated: hence the need to better identify and understand the real forces behind the adoption and diffusion of medical technology innovations in clinical practice. Among these forces, financial incentives may be expected to play a major role. The purpose of this paper was to assess the influence of financing mechanisms for new medical devices and correlated procedures on their diffusion. The analysis was carried out in the Italian inpatient cardiovascular area and applied to drug eluting stents over the period 2003-07. The paper's main hypothesis, that higher levels of reimbursement encourage technology diffusion, was rejected. So was the hypothesis that private hospitals may be more sensitive to tariff levels than public hospitals. A statistically significant difference was found only between hospitals that are funded on a Diagnosis-Related Groups (DRGs) basis and those that are not, with the former showing higher levels of technology diffusion. These results warn policy makers against excessive reliance on specific reimbursement fee changes as a way of steering provider behaviour. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Gaussian fluctuation of the diffusion exponent of virus capsid in a living cell nucleus

NASA Astrophysics Data System (ADS)

Itto, Yuichi

2018-05-01

In their work [4], Bosse et al. experimentally showed that virus capsid exhibits not only normal diffusion but also anomalous diffusion in nucleus of a living cell. There, it was found that the distribution of fluctuations of the diffusion exponent characterizing them takes the Gaussian form, which is, quite remarkably, the same form for two different types of the virus. This suggests high robustness of such fluctuations. Here, the statistical property of local fluctuations of the diffusion exponent of the virus capsid in the nucleus is studied. A maximum-entropy-principle approach (originally proposed for a different virus in a different cell) is applied for obtaining the fluctuation distribution of the exponent. Largeness of the number of blocks identified with local areas of interchromatin corrals is also examined based on the experimental data. It is shown that the Gaussian distribution of the local fluctuations can be derived, in accordance with the above form. In addition, it is quantified how the fluctuation distribution on a long time scale is different from the Gaussian distribution.

Statistical Mechanical Theory of Penetrant Diffusion in Polymer Melts and Glasses

NASA Astrophysics Data System (ADS)

Zhang, Rui; Schweizer, Kenneth

We generalize our force-level, self-consistent nonlinear Langevin equation theory of activated diffusion of a dilute spherical penetrant in hard sphere fluids to predict the long-time diffusivity of molecular penetrants in supercooled polymer liquids and non-aging glasses. Chemical complexity is treated using an a priori mapping to a temperature-dependent hard sphere mixture model where polymers are disconnected into effective spheres based on the Kuhn length as the relevant coarse graining scale. A key parameter for mobility is the penetrant to polymer segment diameter ratio, R. Our calculations agree well with experimental measurements for a wide range of temperatures, penetrant sizes (from gas molecules with R ~0.3 to aromatic molecules with R ~1) and diverse amorphous polymers, over 10 decades variation of penetrant diffusivity. Structural parameter transferability is good. We have also formulated a theory at finite penetrant loading for the coupled penetrant-polymer dynamics in chemically (nearly) matched mixtures (e.g., toluene-polystyrene) which captures well the increase of penetrant diffusivity and decrease of polymer matrix vitrification temperature with increasing loading.

Self-diffusion in dense granular shear flows.

PubMed

Utter, Brian; Behringer, R P

2004-03-01

Diffusivity is a key quantity in describing velocity fluctuations in granular materials. These fluctuations are the basis of many thermodynamic and hydrodynamic models which aim to provide a statistical description of granular systems. We present experimental results on diffusivity in dense, granular shear flows in a two-dimensional Couette geometry. We find that self-diffusivities D are proportional to the local shear rate gamma; with diffusivities along the direction of the mean flow approximately twice as large as those in the perpendicular direction. The magnitude of the diffusivity is D approximately gamma;a(2), where a is the particle radius. However, the gradient in shear rate, coupling to the mean flow, and strong drag at the moving boundary lead to particle displacements that can appear subdiffusive or superdiffusive. In particular, diffusion appears to be superdiffusive along the mean flow direction due to Taylor dispersion effects and subdiffusive along the perpendicular direction due to the gradient in shear rate. The anisotropic force network leads to an additional anisotropy in the diffusivity that is a property of dense systems and has no obvious analog in rapid flows. Specifically, the diffusivity is suppressed along the direction of the strong force network. A simple random walk simulation reproduces the key features of the data, such as the apparent superdiffusive and subdiffusive behavior arising from the mean velocity field, confirming the underlying diffusive motion. The additional anisotropy is not observed in the simulation since the strong force network is not included. Examples of correlated motion, such as transient vortices, and Lévy flights are also observed. Although correlated motion creates velocity fields which are qualitatively different from collisional Brownian motion and can introduce nondiffusive effects, on average the system appears simply diffusive.

Controlling the Curriculum.

ERIC Educational Resources Information Center

Black, Susan

1995-01-01

Recent statistics concerning teen pregnancies and sexually transmitted diseases are compelling reasons for reaching kids before they become sexually active. Comprehensive K-12 programs are essential, despite conflicts over abstinence, "abstinence-but," and safer sex approaches. Adverse program criticism can be diffused if administrators…

Investigation of detection limits for diffuse optical tomography systems: II. Analysis of slab and cup geometry for breast imaging.

PubMed

Ziegler, Ronny; Brendel, Bernhard; Rinneberg, Herbert; Nielsen, Tim

2009-01-21

Using a statistical (chi-square) test on simulated data and a realistic noise model derived from the system's hardware we study the performance of diffuse optical tomography systems for fluorescence imaging. We compare the predicted smallest size of detectable lesions at various positions in slab and cup geometry and model how detection sensitivity depends on breast compression and lesion fluorescence contrast. Our investigation shows that lesion detection is limited by relative noise in slab geometry and by absolute noise in cup geometry.

Aggregation and Disaggregation of Senile Plaques in Alzheimer Disease

NASA Astrophysics Data System (ADS)

Cruz, L.; Urbanc, B.; Buldyrev, S. V.; Christie, R.; Gomez-Isla, T.; Havlin, S.; McNamara, M.; Stanley, H. E.; Hyman, B. T.

1997-07-01

We quantitatively analyzed, using laser scanning confocal microscopy, the three-dimensional structure of individual senile plaques in Alzheimer disease. We carried out the quantitative analysis using statistical methods to gain insights about the processes that govern Aβ peptide deposition. Our results show that plaques are complex porous structures with characteristic pore sizes. We interpret plaque morphology in the context of a new dynamical model based on competing aggregation and disaggregation processes in kinetic steady-state equilibrium with an additional diffusion process allowing Aβ deposits to diffuse over the surface of plaques.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of thismore » object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.« less

The geometric signature: Quantifying landslide-terrain types from digital elevation models

USGS Publications Warehouse

Pike, R.J.

1988-01-01

Topography of various types and scales can be fingerprinted by computer analysis of altitude matrices (digital elevation models, or DEMs). The critical analytic tool is the geometric signature, a set of measures that describes topographic form well enough to distinguish among geomorphically disparate landscapes. Different surficial processes create topography with diagnostic forms that are recognizable in the field. The geometric signature abstracts those forms from contour maps or their DEMs and expresses them numerically. This multivariate characterization enables once-in-tractable problems to be addressed. The measures that constitute a geometric signature express different but complementary attributes of topographic form. Most parameters used here are statistical estimates of central tendency and dispersion for five major categories of terrain geometry; altitude, altitude variance spectrum, slope between slope reversals, and slope and its curvature at fixed slope lengths. As an experimental application of geometric signatures, two mapped terrain types associated with different processes of shallow landsliding in Marin County, California, were distinguished consistently by a 17-variable description of topography from 21??21 DEMs (30-m grid spacing). The small matrix is a statistical window that can be used to scan large DEMs by computer, thus potentially automating the mapping of contrasting terrain types. The two types in Marin County host either (1) slow slides: earth flows and slump-earth flows, or (2) rapid flows: debris avalanches and debris flows. The signature approach should adapt to terrain taxonomy and mapping in other areas, where conditions differ from those in Central California. ?? 1988 International Association for Mathematical Geology.

A Multiscale Progressive Failure Modeling Methodology for Composites that Includes Fiber Strength Stochastics

NASA Technical Reports Server (NTRS)

Ricks, Trenton M.; Lacy, Thomas E., Jr.; Bednarcyk, Brett A.; Arnold, Steven M.; Hutchins, John W.

2014-01-01

A multiscale modeling methodology was developed for continuous fiber composites that incorporates a statistical distribution of fiber strengths into coupled multiscale micromechanics/finite element (FE) analyses. A modified two-parameter Weibull cumulative distribution function, which accounts for the effect of fiber length on the probability of failure, was used to characterize the statistical distribution of fiber strengths. A parametric study using the NASA Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) was performed to assess the effect of variable fiber strengths on local composite failure within a repeating unit cell (RUC) and subsequent global failure. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a unidirectional SCS-6/TIMETAL 21S metal matrix composite tensile dogbone specimen at 650 degC. Multiscale progressive failure analyses were performed to quantify the effect of spatially varying fiber strengths on the RUC-averaged and global stress-strain responses and failure. The ultimate composite strengths and distribution of failure locations (predominately within the gage section) reasonably matched the experimentally observed failure behavior. The predicted composite failure behavior suggests that use of macroscale models that exploit global geometric symmetries are inappropriate for cases where the actual distribution of local fiber strengths displays no such symmetries. This issue has not received much attention in the literature. Moreover, the model discretization at a specific length scale can have a profound effect on the computational costs associated with multiscale simulations.models that yield accurate yet tractable results.

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, Ana; Hegermiller, Christie A.; Antolinez, Jose A. A.; Camus, Paula; Vitousek, Sean; Ruggiero, Peter; Barnard, Patrick L.; Erikson, Li H.; Tomás, Antonio; Mendez, Fernando J.

2017-02-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this complex problem tractable using computationally expensive numerical models. So far, the skill of statistical-downscaling model-based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiscale Climate Emulator of Multimodal Wave Spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, A.; Hegermiller, C.; Alvarez Antolinez, J. A.; Camus, P.; Vitousek, S.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Tomas, A.; Mendez, F. J.

2016-12-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this problem complex yet tractable using computationally-expensive numerical models. So far, the skill of statistical-downscaling models based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical-downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the Southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Dynamic State Estimation of Terrestrial and Solar Plasmas

NASA Astrophysics Data System (ADS)

Kamalabadi, Farzad

A pervasive problem in virtually all branches of space science is the estimation of multi-dimensional state parameters of a dynamical system from a collection of indirect, often incomplete, and imprecise measurements. Subsequent scientific inference is predicated on rigorous analysis, interpretation, and understanding of physical observations and on the reliability of the associated quantitative statistical bounds and performance characteristics of the algorithms used. In this work, we focus on these dynamic state estimation problems and illustrate their importance in the context of two timely activities in space remote sensing. First, we discuss the estimation of multi-dimensional ionospheric state parameters from UV spectral imaging measurements anticipated to be acquired the recently selected NASA Heliophysics mission, Ionospheric Connection Explorer (ICON). Next, we illustrate that similar state-space formulations provide the means for the estimation of 3D, time-dependent densities and temperatures in the solar corona from a series of white-light and EUV measurements. We demonstrate that, while a general framework for the stochastic formulation of the state estimation problem is suited for systematic inference of the parameters of a hidden Markov process, several challenges must be addressed in the assimilation of an increasing volume and diversity of space observations. These challenges are: (1) the computational tractability when faced with voluminous and multimodal data, (2) the inherent limitations of the underlying models which assume, often incorrectly, linear dynamics and Gaussian noise, and (3) the unavailability or inaccuracy of transition probabilities and noise statistics. We argue that pursuing answers to these questions necessitates cross-disciplinary research that enables progress toward systematically reconciling observational and theoretical understanding of the space environment.

Computational and analytical comparison of flux discretizations for the semiconductor device equations beyond Boltzmann statistics

NASA Astrophysics Data System (ADS)

Farrell, Patricio; Koprucki, Thomas; Fuhrmann, Jürgen

2017-10-01

We compare three thermodynamically consistent numerical fluxes known in the literature, appearing in a Voronoï finite volume discretization of the van Roosbroeck system with general charge carrier statistics. Our discussion includes an extension of the Scharfetter-Gummel scheme to non-Boltzmann (e.g. Fermi-Dirac) statistics. It is based on the analytical solution of a two-point boundary value problem obtained by projecting the continuous differential equation onto the interval between neighboring collocation points. Hence, it serves as a reference flux. The exact solution of the boundary value problem can be approximated by computationally cheaper fluxes which modify certain physical quantities. One alternative scheme averages the nonlinear diffusion (caused by the non-Boltzmann nature of the problem), another one modifies the effective density of states. To study the differences between these three schemes, we analyze the Taylor expansions, derive an error estimate, visualize the flux error and show how the schemes perform for a carefully designed p-i-n benchmark simulation. We present strong evidence that the flux discretization based on averaging the nonlinear diffusion has an edge over the scheme based on modifying the effective density of states.

Nonlinear histogram binning for quantitative analysis of lung tissue fibrosis in high-resolution CT data

NASA Astrophysics Data System (ADS)

Zavaletta, Vanessa A.; Bartholmai, Brian J.; Robb, Richard A.

2007-03-01

Diffuse lung diseases, such as idiopathic pulmonary fibrosis (IPF), can be characterized and quantified by analysis of volumetric high resolution CT scans of the lungs. These data sets typically have dimensions of 512 x 512 x 400. It is too subjective and labor intensive for a radiologist to analyze each slice and quantify regional abnormalities manually. Thus, computer aided techniques are necessary, particularly texture analysis techniques which classify various lung tissue types. Second and higher order statistics which relate the spatial variation of the intensity values are good discriminatory features for various textures. The intensity values in lung CT scans range between [-1024, 1024]. Calculation of second order statistics on this range is too computationally intensive so the data is typically binned between 16 or 32 gray levels. There are more effective ways of binning the gray level range to improve classification. An optimal and very efficient way to nonlinearly bin the histogram is to use a dynamic programming algorithm. The objective of this paper is to show that nonlinear binning using dynamic programming is computationally efficient and improves the discriminatory power of the second and higher order statistics for more accurate quantification of diffuse lung disease.

Banff study of pathologic changes in lung allograft biopsy specimens with donor-specific antibodies.

PubMed

Wallace, William Dean; Li, Ning; Andersen, Claus B; Arrossi, A Valeria; Askar, Medhat; Berry, Gerry J; DeNicola, Matthew M; Neil, Desley A; Pavlisko, Elizabeth N; Reed, Elaine F; Remmelink, Myriam; Weigt, S Sam; Weynand, Birgit; Zhang, Jennifer Q; Budev, Marie M; Farver, Carol F

2016-01-01

The diagnosis of antibody-mediated rejection (AMR) in the lung transplant is still an area under investigation. We performed a blinded multicenter study to determine if any statistically significant histologic findings in transbronchial biopsy specimens from lung transplant patients correlate with the presence of donor-specific antibodies (DSAs). We asked 9 pathologists with experience in lung transplantation to evaluate 161 lung transplant biopsy specimens for various histologic parameters. The findings were correlated with antibody status positive for DSAs, positive for non-DSAs, and no antibodies (NABs) present. The significance of each histologic variable was reviewed. We found no statistically significant association with acute cellular rejection, airway inflammation, or bronchiolitis obliterans and the presence or absence of antibodies. However, biopsy specimens with DSAs had a statistically significant difference vs NABs in the setting of acute lung injury, with or without diffuse alveolar damage (p = 0.0008), in the presence of capillary neutrophilic inflammation (p = 0.0014), and in samples with endotheliitis (p = 0.0155). In samples with complement 4d staining, there was a trend but no statistically significant difference between specimens associated with DSAs and specimens with NABs. Capillary inflammation, acute lung injury, and endotheliitis significantly correlated with DSAs. The infrequently observed diffuse staining for complement 4d limits the usefulness of this stain. Copyright © 2016 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Assessing groundwater vulnerability to agrichemical contamination in the Midwest US

USGS Publications Warehouse

Burkart, M.R.; Kolpin, D.W.; James, D.E.

1999-01-01

Agrichemicals (herbicides and nitrate) are significant sources of diffuse pollution to groundwater. Indirect methods are needed to assess the potential for groundwater contamination by diffuse sources because groundwater monitoring is too costly to adequately define the geographic extent of contamination at a regional or national scale. This paper presents examples of the application of statistical, overlay and index, and process-based modeling methods for groundwater vulnerability assessments to a variety of data from the Midwest U.S. The principles for vulnerability assessment include both intrinsic (pedologic, climatologic, and hydrogeologic factors) and specific (contaminant and other anthropogenic factors) vulnerability of a location. Statistical methods use the frequency of contaminant occurrence, contaminant concentration, or contamination probability as a response variable. Statistical assessments are useful for defining the relations among explanatory and response variables whether they define intrinsic or specific vulnerability. Multivariate statistical analyses are useful for ranking variables critical to estimating water quality responses of interest. Overlay and index methods involve intersecting maps of intrinsic and specific vulnerability properties and indexing the variables by applying appropriate weights. Deterministic models use process-based equations to simulate contaminant transport and are distinguished from the other methods in their potential to predict contaminant transport in both space and time. An example of a one-dimensional leaching model linked to a geographic information system (GIS) to define a regional metamodel for contamination in the Midwest is included.

STUDY OF TURBULENT ENERGY OVER COMPLEX TERRAIN: STATE, 1978

EPA Science Inventory

The complex structure of the earth's surface influenced atmospheric parameters pertinent to modeling the diffusion process during the 1978 'STATE' field study. The Information Theory approach of statistics proved useful for analyzing the complex structures observed in the radiome...

Reaction rates for mesoscopic reaction-diffusion kinetics

DOE PAGES

Hellander, Stefan; Hellander, Andreas; Petzold, Linda

2015-02-23

The mesoscopic reaction-diffusion master equation (RDME) is a popular modeling framework frequently applied to stochastic reaction-diffusion kinetics in systems biology. The RDME is derived from assumptions about the underlying physical properties of the system, and it may produce unphysical results for models where those assumptions fail. In that case, other more comprehensive models are better suited, such as hard-sphere Brownian dynamics (BD). Although the RDME is a model in its own right, and not inferred from any specific microscale model, it proves useful to attempt to approximate a microscale model by a specific choice of mesoscopic reaction rates. In thismore » paper we derive mesoscopic scale-dependent reaction rates by matching certain statistics of the RDME solution to statistics of the solution of a widely used microscopic BD model: the Smoluchowski model with a Robin boundary condition at the reaction radius of two molecules. We also establish fundamental limits on the range of mesh resolutions for which this approach yields accurate results and show both theoretically and in numerical examples that as we approach the lower fundamental limit, the mesoscopic dynamics approach the microscopic dynamics. Finally, we show that for mesh sizes below the fundamental lower limit, results are less accurate. Thus, the lower limit determines the mesh size for which we obtain the most accurate results.« less

Reaction rates for mesoscopic reaction-diffusion kinetics

PubMed Central

Hellander, Stefan; Hellander, Andreas; Petzold, Linda

2016-01-01

The mesoscopic reaction-diffusion master equation (RDME) is a popular modeling framework frequently applied to stochastic reaction-diffusion kinetics in systems biology. The RDME is derived from assumptions about the underlying physical properties of the system, and it may produce unphysical results for models where those assumptions fail. In that case, other more comprehensive models are better suited, such as hard-sphere Brownian dynamics (BD). Although the RDME is a model in its own right, and not inferred from any specific microscale model, it proves useful to attempt to approximate a microscale model by a specific choice of mesoscopic reaction rates. In this paper we derive mesoscopic scale-dependent reaction rates by matching certain statistics of the RDME solution to statistics of the solution of a widely used microscopic BD model: the Smoluchowski model with a Robin boundary condition at the reaction radius of two molecules. We also establish fundamental limits on the range of mesh resolutions for which this approach yields accurate results and show both theoretically and in numerical examples that as we approach the lower fundamental limit, the mesoscopic dynamics approach the microscopic dynamics. We show that for mesh sizes below the fundamental lower limit, results are less accurate. Thus, the lower limit determines the mesh size for which we obtain the most accurate results. PMID:25768640

Anomalous diffusion and long-range correlations in the score evolution of the game of cricket

NASA Astrophysics Data System (ADS)

Ribeiro, Haroldo V.; Mukherjee, Satyam; Zeng, Xiao Han T.

2012-08-01

We investigate the time evolution of the scores of the second most popular sport in the world: the game of cricket. By analyzing, event by event, the scores of more than 2000 matches, we point out that the score dynamics is an anomalous diffusive process. Our analysis reveals that the variance of the process is described by a power-law dependence with a superdiffusive exponent, that the scores are statistically self-similar following a universal Gaussian distribution, and that there are long-range correlations in the score evolution. We employ a generalized Langevin equation with a power-law correlated noise that describes all the empirical findings very well. These observations suggest that competition among agents may be a mechanism leading to anomalous diffusion and long-range correlation.

Speckle contrast optical spectroscopy, a non-invasive, diffuse optical method for measuring microvascular blood flow in tissue

PubMed Central

Valdes, Claudia P.; Varma, Hari M.; Kristoffersen, Anna K.; Dragojevic, Tanja; Culver, Joseph P.; Durduran, Turgut

2014-01-01

We introduce a new, non-invasive, diffuse optical technique, speckle contrast optical spectroscopy (SCOS), for probing deep tissue blood flow using the statistical properties of laser speckle contrast and the photon diffusion model for a point source. The feasibility of the method is tested using liquid phantoms which demonstrate that SCOS is capable of measuring the dynamic properties of turbid media non-invasively. We further present an in vivo measurement in a human forearm muscle using SCOS in two modalities: one with the dependence of the speckle contrast on the source-detector separation and another on the exposure time. In doing so, we also introduce crucial corrections to the speckle contrast that account for the variance of the shot and sensor dark noises. PMID:25136500

Porous medium acoustics of wave-induced vorticity diffusion

NASA Astrophysics Data System (ADS)

Müller, T. M.; Sahay, P. N.

2011-02-01

A theory for attenuation and dispersion of elastic waves due to wave-induced generation of vorticity at pore-scale heterogeneities in a macroscopically homogeneous porous medium is developed. The diffusive part of the vorticity field associated with a viscous wave in the pore space—the so-called slow shear wave—is linked to the porous medium acoustics through incorporation of the fluid strain rate tensor of a Newtonian fluid in the poroelastic constitutive relations. The method of statistical smoothing is then used to derive dynamic-equivalent elastic wave velocities accounting for the conversion scattering process into the diffusive slow shear wave in the presence of randomly distributed pore-scale heterogeneities. The result is a simple model for wave attenuation and dispersion associated with the transition from viscosity- to inertia-dominated flow regime.

Anomalous diffusion in the evolution of soccer championship scores: Real data, mean-field analysis, and an agent-based model

NASA Astrophysics Data System (ADS)

da Silva, Roberto; Vainstein, Mendeli H.; Gonçalves, Sebastián; Paula, Felipe S. F.

2013-08-01

Statistics of soccer tournament scores based on the double round robin system of several countries are studied. Exploring the dynamics of team scoring during tournament seasons from recent years we find evidences of superdiffusion. A mean-field analysis results in a drift velocity equal to that of real data but in a different diffusion coefficient. Along with the analysis of real data we present the results of simulations of soccer tournaments obtained by an agent-based model which successfully describes the final scoring distribution [da Silva , Comput. Phys. Commun.CPHCBZ0010-465510.1016/j.cpc.2012.10.030 184, 661 (2013)]. Such model yields random walks of scores over time with the same anomalous diffusion as observed in real data.

Influences of Exciton Diffusion and Exciton-Exciton Annihilation on Photon Emission Statistics of Carbon Nanotubes.

PubMed

Ma, Xuedan; Roslyak, Oleskiy; Duque, Juan G; Pang, Xiaoying; Doorn, Stephen K; Piryatinski, Andrei; Dunlap, David H; Htoon, Han

2015-07-03

Pump-dependent photoluminescence imaging and second-order photon correlation studies have been performed on individual single-walled carbon nanotubes (SWCNTs) at room temperature. These studies enable the extraction of both the exciton diffusion constant and the Auger recombination coefficient. A linear correlation between these parameters is attributed to the effect of environmental disorder in setting the exciton mean free path and capture-limited Auger recombination at this length scale. A suppression of photon antibunching is attributed to the creation of multiple spatially nonoverlapping excitons in SWCNTs, whose diffusion length is shorter than the laser spot size. We conclude that complete antibunching at room temperature requires an enhancement of the exciton-exciton annihilation rate that may become realizable in SWCNTs allowing for strong exciton localization.

Optimal estimates of the diffusion coefficient of a single Brownian trajectory.

PubMed

Boyer, Denis; Dean, David S; Mejía-Monasterio, Carlos; Oshanin, Gleb

2012-03-01

Modern developments in microscopy and image processing are revolutionizing areas of physics, chemistry, and biology as nanoscale objects can be tracked with unprecedented accuracy. The goal of single-particle tracking is to determine the interaction between the particle and its environment. The price paid for having a direct visualization of a single particle is a consequent lack of statistics. Here we address the optimal way to extract diffusion constants from single trajectories for pure Brownian motion. It is shown that the maximum likelihood estimator is much more efficient than the commonly used least-squares estimate. Furthermore, we investigate the effect of disorder on the distribution of estimated diffusion constants and show that it increases the probability of observing estimates much smaller than the true (average) value.

Source detection in astronomical images by Bayesian model comparison

NASA Astrophysics Data System (ADS)

Frean, Marcus; Friedlander, Anna; Johnston-Hollitt, Melanie; Hollitt, Christopher

2014-12-01

The next generation of radio telescopes will generate exabytes of data on hundreds of millions of objects, making automated methods for the detection of astronomical objects ("sources") essential. Of particular importance are faint, diffuse objects embedded in noise. There is a pressing need for source finding software that identifies these sources, involves little manual tuning, yet is tractable to calculate. We first give a novel image discretisation method that incorporates uncertainty about how an image should be discretised. We then propose a hierarchical prior for astronomical images, which leads to a Bayes factor indicating how well a given region conforms to a model of source that is exceptionally unconstrained, compared to a model of background. This enables the efficient localisation of regions that are "suspiciously different" from the background distribution, so our method looks not for brightness but for anomalous distributions of intensity, which is much more general. The model of background can be iteratively improved by removing the influence on it of sources as they are discovered. The approach is evaluated by identifying sources in real and simulated data, and performs well on these measures: the Bayes factor is maximized at most real objects, while returning only a moderate number of false positives. In comparison to a catalogue constructed by widely-used source detection software with manual post-processing by an astronomer, our method found a number of dim sources that were missing from the "ground truth" catalogue.

Gyrofluid Modeling of Turbulent, Kinetic Physics

NASA Astrophysics Data System (ADS)

Despain, Kate Marie

2011-12-01

Gyrofluid models to describe plasma turbulence combine the advantages of fluid models, such as lower dimensionality and well-developed intuition, with those of gyrokinetics models, such as finite Larmor radius (FLR) effects. This allows gyrofluid models to be more tractable computationally while still capturing much of the physics related to the FLR of the particles. We present a gyrofluid model derived to capture the behavior of slow solar wind turbulence and describe the computer code developed to implement the model. In addition, we describe the modifications we made to a gyrofluid model and code that simulate plasma turbulence in tokamak geometries. Specifically, we describe a nonlinear phase mixing phenomenon, part of the E x B term, that was previously missing from the model. An inherently FLR effect, it plays an important role in predicting turbulent heat flux and diffusivity levels for the plasma. We demonstrate this importance by comparing results from the updated code to studies done previously by gyrofluid and gyrokinetic codes. We further explain what would be necessary to couple the updated gyrofluid code, gryffin, to a turbulent transport code, thus allowing gryffin to play a role in predicting profiles for fusion devices such as ITER and to explore novel fusion configurations. Such a coupling would require the use of Graphical Processing Units (GPUs) to make the modeling process fast enough to be viable. Consequently, we also describe our experience with GPU computing and demonstrate that we are poised to complete a gryffin port to this innovative architecture.

A review of EEG, ERP, and neuroimaging studies of creativity and insight.

PubMed

Dietrich, Arne; Kanso, Riam

2010-09-01

Creativity is a cornerstone of what makes us human, yet the neural mechanisms underlying creative thinking are poorly understood. A recent surge of interest into the neural underpinnings of creative behavior has produced a banquet of data that is tantalizing but, considered as a whole, deeply self-contradictory. We review the emerging literature and take stock of several long-standing theories and widely held beliefs about creativity. A total of 72 experiments, reported in 63 articles, make up the core of the review. They broadly fall into 3 categories: divergent thinking, artistic creativity, and insight. Electroencephalographic studies of divergent thinking yield highly variegated results. Neuroimaging studies of this paradigm also indicate no reliable changes above and beyond diffuse prefrontal activation. These findings call into question the usefulness of the divergent thinking construct in the search for the neural basis of creativity. A similarly inconclusive picture emerges for studies of artistic performance, except that this paradigm also often yields activation of motor and temporoparietal regions. Neuroelectric and imaging studies of insight are more consistent, reflecting changes in anterior cingulate cortex and prefrontal areas. Taken together, creative thinking does not appear to critically depend on any single mental process or brain region, and it is not especially associated with right brains, defocused attention, low arousal, or alpha synchronization, as sometimes hypothesized. To make creativity tractable in the brain, it must be further subdivided into different types that can be meaningfully associated with specific neurocognitive processes.

Lagrangian statistics across the turbulent-nonturbulent interface in a turbulent plane jet.

PubMed

Taveira, Rodrigo R; Diogo, José S; Lopes, Diogo C; da Silva, Carlos B

2013-10-01

Lagrangian statistics from millions of particles are used to study the turbulent entrainment mechanism in a direct numerical simulation of a turbulent plane jet at Re(λ) ≈ 110. The particles (tracers) are initially seeded at the irrotational region of the jet near the turbulent shear layer and are followed as they are drawn into the turbulent region across the turbulent-nonturbulent interface (TNTI), allowing the study of the enstrophy buildup and thereby characterizing the turbulent entrainment mechanism in the jet. The use of Lagrangian statistics following fluid particles gives a more correct description of the entrainment mechanism than in previous works since the statistics in relation to the TNTI position involve data from the trajectories of the entraining fluid particles. The Lagrangian statistics for the particles show the existence of a velocity jump and a characteristic vorticity jump (with a thickness which is one order of magnitude greater than the Kolmogorov microscale), in agreement with previous results using Eulerian statistics. The particles initially acquire enstrophy by viscous diffusion and later by enstrophy production, which becomes "active" only deep inside the turbulent region. Both enstrophy diffusion and production near the TNTI differ substantially from inside the turbulent region. Only about 1% of all particles find their way into pockets of irrotational flow engulfed into the turbulent shear layer region, indicating that "engulfment" is not significant for the present flow, indirectly suggesting that the entrainment is largely due to "nibbling" small-scale mechanisms acting along the entire TNTI surface. Probability density functions of particle positions suggests that the particles spend more time crossing the region near the TNTI than traveling inside the turbulent region, consistent with the particles moving tangent to the interface around the time they cross it.

Magnetorotational dynamo chimeras. The missing link to turbulent accretion disk dynamo models?

NASA Astrophysics Data System (ADS)

Riols, A.; Rincon, F.; Cossu, C.; Lesur, G.; Ogilvie, G. I.; Longaretti, P.-Y.

2017-02-01

In Keplerian accretion disks, turbulence and magnetic fields may be jointly excited through a subcritical dynamo mechanisminvolving magnetorotational instability (MRI). This dynamo may notably contribute to explaining the time-variability of various accreting systems, as high-resolution simulations of MRI dynamo turbulence exhibit statistical self-organization into large-scale cyclic dynamics. However, understanding the physics underlying these statistical states and assessing their exact astrophysical relevance is theoretically challenging. The study of simple periodic nonlinear MRI dynamo solutions has recently proven useful in this respect, and has highlighted the role of turbulent magnetic diffusion in the seeming impossibility of a dynamo at low magnetic Prandtl number (Pm), a common regime in disks. Arguably though, these simple laminar structures may not be fully representative of the complex, statistically self-organized states expected in astrophysical regimes. Here, we aim at closing this seeming discrepancy by reporting the numerical discovery of exactly periodic, yet semi-statistical "chimeral MRI dynamo states" which are the organized outcome of a succession of MRI-unstable, non-axisymmetric dynamical stages of different forms and amplitudes. Interestingly, these states, while reminiscent of the statistical complexity of turbulent simulations, involve the same physical principles as simpler laminar cycles, and their analysis further confirms the theory that subcritical turbulent magnetic diffusion impedes the sustainment of an MRI dynamo at low Pm. Overall, chimera dynamo cycles therefore offer an unprecedented dual physical and statistical perspective on dynamos in rotating shear flows, which may prove useful in devising more accurate, yet intuitive mean-field models of time-dependent turbulent disk dynamos. Movies associated to Fig. 1 are available at http://www.aanda.org

Body mass scaling of passive oxygen diffusion in endotherms and ectotherms

PubMed Central

Gillooly, James F.; Gomez, Juan Pablo; Mavrodiev, Evgeny V.; Rong, Yue; McLamore, Eric S.

2016-01-01

The area and thickness of respiratory surfaces, and the constraints they impose on passive oxygen diffusion, have been linked to differences in oxygen consumption rates and/or aerobic activity levels in vertebrates. However, it remains unclear how respiratory surfaces and associated diffusion rates vary with body mass across vertebrates, particularly in relation to the body mass scaling of oxygen consumption rates. Here we address these issues by first quantifying the body mass dependence of respiratory surface area and respiratory barrier thickness for a diversity of endotherms (birds and mammals) and ectotherms (fishes, amphibians, and reptiles). Based on these findings, we then use Fick’s law to predict the body mass scaling of oxygen diffusion for each group. Finally, we compare the predicted body mass dependence of oxygen diffusion to that of oxygen consumption in endotherms and ectotherms. We find that the slopes and intercepts of the relationships describing the body mass dependence of passive oxygen diffusion in these two groups are statistically indistinguishable from those describing the body mass dependence of oxygen consumption. Thus, the area and thickness of respiratory surfaces combine to match oxygen diffusion capacity to oxygen consumption rates in both air- and water-breathing vertebrates. In particular, the substantially lower oxygen consumption rates of ectotherms of a given body mass relative to those of endotherms correspond to differences in oxygen diffusion capacity. These results provide insights into the long-standing effort to understand the structural attributes of organisms that underlie the body mass scaling of oxygen consumption. PMID:27118837

Body mass scaling of passive oxygen diffusion in endotherms and ectotherms.

PubMed

Gillooly, James F; Gomez, Juan Pablo; Mavrodiev, Evgeny V; Rong, Yue; McLamore, Eric S

2016-05-10

The area and thickness of respiratory surfaces, and the constraints they impose on passive oxygen diffusion, have been linked to differences in oxygen consumption rates and/or aerobic activity levels in vertebrates. However, it remains unclear how respiratory surfaces and associated diffusion rates vary with body mass across vertebrates, particularly in relation to the body mass scaling of oxygen consumption rates. Here we address these issues by first quantifying the body mass dependence of respiratory surface area and respiratory barrier thickness for a diversity of endotherms (birds and mammals) and ectotherms (fishes, amphibians, and reptiles). Based on these findings, we then use Fick's law to predict the body mass scaling of oxygen diffusion for each group. Finally, we compare the predicted body mass dependence of oxygen diffusion to that of oxygen consumption in endotherms and ectotherms. We find that the slopes and intercepts of the relationships describing the body mass dependence of passive oxygen diffusion in these two groups are statistically indistinguishable from those describing the body mass dependence of oxygen consumption. Thus, the area and thickness of respiratory surfaces combine to match oxygen diffusion capacity to oxygen consumption rates in both air- and water-breathing vertebrates. In particular, the substantially lower oxygen consumption rates of ectotherms of a given body mass relative to those of endotherms correspond to differences in oxygen diffusion capacity. These results provide insights into the long-standing effort to understand the structural attributes of organisms that underlie the body mass scaling of oxygen consumption.

Biological system interactions.

PubMed Central

Adomian, G; Adomian, G E; Bellman, R E

1984-01-01

Mathematical modeling of cellular population growth, interconnected subsystems of the body, blood flow, and numerous other complex biological systems problems involves nonlinearities and generally randomness as well. Such problems have been dealt with by mathematical methods often changing the actual model to make it tractable. The method presented in this paper (and referenced works) allows much more physically realistic solutions. PMID:6585837

Elucidation of Prion Protein Conformational Changes Associated with Infectivity by Fluorescence Spectroscopy

DTIC Science & Technology

2006-06-01

This work was supported by grants to MAM from the US Army Research (DAMD17- 03-1-0342) and the NIH COBRE program (P20 RR020185-01). Authors...and more tractable model for PrPSc. This is further supported by an intriguing discovery made by Caughey and coworkers in their search to

Photovoltaic effect in ferroelectric ceramics

NASA Technical Reports Server (NTRS)

Epstein, D. J.; Linz, A.; Jenssen, H. P.

1982-01-01

The ceramic structure was simulated in a form that is more tractable to correlation between experiment and theory. Single crystals (of barium titanate) were fabricated in a simple corrugated structure in which the pedestals of the corrugation simulated the grain while the intervening cuts could be filled with materials simulating the grain boundaries. The observed photovoltages were extremely small (100 mv).

Long-Term Memory Shapes the Primary Olfactory Center of an Insect Brain

ERIC Educational Resources Information Center

Hourcade, Benoit; Perisse, Emmanuel; Devaud, Jean-Marc; Sandoz, Jean-Christophe

2009-01-01

The storage of stable memories is generally considered to rely on changes in the functional properties and/or the synaptic connectivity of neural networks. However, these changes are not easily tractable given the complexity of the learning procedures and brain circuits studied. Such a search can be narrowed down by studying memories of specific…

Public Timber Supply under Multiple-Use Management

Treesearch

David N. Wear

2003-01-01

In many parts of the world, substantial shares of timber inventories are managed by government agencies. The objective of this chapter is to examine the potential influence of public timber production on market structure as well as on prices, harvest quantities, and economic welfare. National forest management in the United States is used as a tractable case study, but...

Writing Pal: Feasibility of an Intelligent Writing Strategy Tutor in the High School Classroom

ERIC Educational Resources Information Center

Roscoe, Rod D.; McNamara, Danielle S.

2013-01-01

The Writing Pal (W-Pal) is a novel intelligent tutoring system (ITS) that offers writing strategy instruction, game-based practice, essay writing practice, and formative feedback to developing writers. Compared to more tractable and constrained learning domains for ITS, writing is an ill-defined domain because the features of effective writing are…

A meteorologically driven grain sorghum stress indicator model

NASA Technical Reports Server (NTRS)

Taylor, T. W.; Ravet, F. W. (Principal Investigator)

1981-01-01

A grain sorghum soil moisture and temperature stress model is described. It was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions and crop phenology in selected grain sorghum production areas. The model also identifies optimum conditions on a daily basis and planting/harvest problems associated with poor tractability.

Avirulence gene mapping in the Hessian fly (Mayetiola destructor) reveals a protein phosphatase 2C effector gene family

USDA-ARS?s Scientific Manuscript database

The genetic tractability of the Hessian fly (HF, Mayetiola destructor) provides an opportunity to investigate the mechanisms insects use to induce plant gall formation. Here we demonstrate that capacity using the newly sequenced HF genome to identify the gene (vH24) that elicits the effector-trigger...

Sediment transport primer: estimating bed-material transport in gravel-bed rivers

Treesearch

Peter Wilcock; John Pitlick; Yantao Cui

2009-01-01

This primer accompanies the release of BAGS, software developed to calculate sediment transport rate in gravel-bed rivers. BAGS and other programs facilitate calculation and can reduce some errors, but cannot ensure that calculations are accurate or relevant. This primer was written to help the software user define relevant and tractable problems, select appropriate...

Theoretical Limits on Multiuser Molecular Communication in Internet of Nano-Bio Things.

PubMed

Dinc, Ergin; Akan, Ozgur B

2017-06-01

In nano-bio networks, multiple transmitter-receiver pairs will operate in the same medium. Both inter-symbol interference and multi-user interference can cause saturation at the receiver side, and this effect may cause an outage. Thus, we propose a tractable framework to calculate the theoretical operating points for fully absorbing receiver.

Meta-analysis of diffusion metrics for the prediction of tumor grade in gliomas.

PubMed

Miloushev, V Z; Chow, D S; Filippi, C G

2015-02-01

Diffusion tensor metrics are potential in vivo quantitative neuroimaging biomarkers for the characterization of brain tumor subtype. This meta-analysis analyzes the ability of mean diffusivity and fractional anisotropy to distinguish low-grade from high-grade gliomas in the identifiable tumor core and the region of peripheral edema. A meta-analysis of articles with mean diffusivity and fractional anisotropy data for World Health Organization low-grade (I, II) and high-grade (III, IV) gliomas, between 2000 and 2013, was performed. Pooled data were analyzed by using the odds ratio and mean difference. Receiver operating characteristic analysis was performed for patient-level data. The minimum mean diffusivity of high-grade gliomas was decreased compared with low-grade gliomas. High-grade gliomas had decreased average mean diffusivity values compared with low-grade gliomas in the tumor core and increased average mean diffusivity values in the peripheral region. High-grade gliomas had increased FA values compared with low-grade gliomas in the tumor core, decreased values in the peripheral region, and a decreased fractional anisotropy difference between the tumor core and peripheral region. The minimum mean diffusivity differs significantly with respect to the World Health Organization grade of gliomas. Statistically significant effects of tumor grade on average mean diffusivity and fractional anisotropy were observed, supporting the concept that high-grade tumors are more destructive and infiltrative than low-grade tumors. Considerable heterogeneity within the literature may be due to systematic factors in addition to underlying lesion heterogeneity. © 2015 by American Journal of Neuroradiology.

Geographical structures and the cholera epidemic in modern Japan: Fukushima prefecture in 1882 and 1895.

PubMed

Kuo, Chun-Lin; Fukui, Hiromichi

2007-06-30

Disease diffusion patterns can provide clues for understanding geographical change. Fukushima, a rural prefecture in northeast Japan, was chosen for a case study of the late nineteenth century cholera epidemic that occurred in that country. Two volumes of Cholera Ryu-ko Kiji (Cholera Epidemic Report), published by the prefectural government in 1882 and 1895, provide valuable records for analyzing and modelling diffusion. Text descriptions and numerical evidence culled from the reports were incorporated into a temporal-spatial study framework using geographic information system (GIS) and geo-statistical techniques. Changes in diffusion patterns between 1882 and 1895 reflect improvements in the Fukushima transportation system and growth in social-economic networks. The data reveal different diffusion systems in separate regions in which residents of Fukushima and neighboring prefectures interacted. Our model also shows that an area in the prefecture's northern interior was dominated by a mix of diffusion processes (contagious and hierarchical), that the southern coastal region was affected by a contagious process, and that other infected areas experienced relocation diffusion. In addition to enhancing our understanding of epidemics, the spatial-temporal patterns of cholera diffusion offer opportunities for studying regional change in modern Japan. By highlighting the dynamics of regional reorganization, our findings can be used to better understand the formation of an urban hierarchy in late nineteenth century Japan.

Multimodal Imaging Evidence for Axonal and Myelin Deterioration in Amnestic Mild Cognitive Impairment

PubMed Central

Gold, Brian T.; Jiang, Yang; Powell, David K.; Smith, Charles D.

2012-01-01

White matter (WM) microstructural declines have been demonstrated in Alzheimer’s disease and amnestic mild cognitive impairment (aMCI). However, the pattern of WM microstructural changes in aMCI after controlling for WM atrophy is unknown. Here, we address this issue through joint consideration of aMCI alterations in fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, as well as macrostructural volume in WM and gray matter compartments. Participants were 18 individuals with aMCI and 24 healthy seniors. Voxelwise analyses of diffusion tensor imaging data was carried out using tract-based spatial statistics (TBSS) and voxelwise analyses of high-resolution structural data was conducted using voxel based morphometry. After controlling for WM atrophy, the main pattern of TBSS findings indicated reduced fractional anisotropy with only small alterations in mean diffusivity/radial diffusivity/axial diffusivity. These WM microstructural declines bordered and/or were connected to gray matter structures showing volumetric declines. However, none of the potential relationships between WM integrity and volume in connected gray matter structures was significant, and adding fractional anisotropy information improved the classificatory accuracy of aMCI compared to the use of hippocampal atrophy alone. These results suggest that WM microstructural declines provide unique information not captured by atrophy measures that may aid the magnetic resonance imaging contribution to aMCI detection. PMID:22460327

Effect of field-aligned-beam in parallel diffusion of energetic particles in the Earth's foreshock

NASA Astrophysics Data System (ADS)

Matsukiyo, S.; Nakanishi, K.; Otsuka, F.; Kis, A.; Lemperger, I.; Hada, T.

2016-12-01

Diffusive shock acceleration (DSA) is one of the plausible acceleration mechanisms of cosmic rays. In the standard DSA model the partial density of the accelerated particles, diffused into upstream, exponentially decreases as the distance to the shock increases. Kis et al. (GRL, 31, L20801, 2004) examined the density gradients of energetic ions upstream of the bow shock with high accuracy by using Cluster data. They estimated the diffusion coefficients of energetic ions for the event in February 18, 2003 and showed that the obtained diffusion coefficients are significantly smaller than those estimated in the past statistical study. This implies that particle acceleration at the bow shock can be more efficient than considered before. Here, we focus on the effect of the field-aligned-beam (FAB) which is often observed in the foreshock, and examine how the FAB affects the efficiency of diffusion of the energetic ions by performing test particle simulations. The upstream turbulence is given by the superposition of parallel Alfven waves with power-law energy spectrum with random phase approximation. In the spectrum we further add a peak corresponding to the waves resonantly generated by the FAB. The dependence of the diffusion coefficient on the presence of the FAB as well as total energy of the turbulence, power-law index of the turbulence, and intensity of FAB oriented waves are discussed.

Diffuse Interstitial Brain Edema in Patients With End-Stage Renal Disease Undergoing Hemodialysis: A Tract-Based Spatial Statistics Study

PubMed Central

Kong, Xiang; Wen, Ji-qiu; Qi, Rong-feng; Luo, Song; Zhong, Jian-hui; Chen, Hui-juan; Ji, Gong-jun; Lu, Guang Ming; Zhang, Long Jiang

2014-01-01

Abstract To investigate white matter (WM) alterations and their correlation with cognition function in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD) using diffusion tensor imaging (DTI) with tract-based spatial statistics (TBSS) approach. This prospective HIPAA-complaint study was approved by our institutional review board. Eighty HD ESRD patients and 80 sex- and age-matched healthy controls were included. Neuropsychological (NP) tests and laboratory tests, including serum creatinine and urea, were performed. DTI data were processed to obtain fractional anisotropy (FA) and mean diffusivity (MD) maps with TBSS. FA and MD difference between the 2 groups were compared. We also explored the associations of FA values in WM regions of lower FA with ages, NP tests, disease, and dialysis durations, serum creatinine and urea levels of ESRD patients. Compared with controls, HD ESRD patients had lower FA value in the corpus callosum, bilateral corona radiate, posterior thalamic radiation, left superior longitudinal fasciculus, and right cingulum (P < 0.05, FWE corrected). Almost all WM regions had increased MD in HD ESRD patients compared with controls (P < 0.05, FWE corrected). In some regions with lower FA, FA values showed moderate correlations with ages, NP tests, and serum urea levels. There was no correlation between FA values and HD durations, disease durations, and serum creatinine levels of ESRD patients (all P > 0.05). Diffuse interstitial brain edema and moderate WM integrity disruption occurring in HD ESRD patients, which correlated with cognitive dysfunction, and serum urea levels might be a risk factor for these WM changes. PMID:25526483

Momentum deposition on Wolf-Rayet winds: Nonisotropic diffusion with effective gray opacity

NASA Technical Reports Server (NTRS)

Gayley, Kenneth G.; Owocki, Stanley P.; Cranmer, Steven R.

1995-01-01

We derive the velocity and mass-loss rate of a steady state Wolf-Rayet (WR) wind, using a nonisotropic diffusion approximation applied to the transfer between strongly overlapping spectral lines. Following the approach of Friend & Castor (1983), the line list is assumed to approximate a statistically parameterized Poisson distribution in frequency, so that photon transport is controlled by an angle-dependent, effectively gray opacity. We show the nonisotropic diffusion approximation yields good agreement with more accurate numerical treatments of the radiative transfer, while providing analytic insight into wind driving by multiple scattering. We illustrate, in particular, that multiple radiative momentum deposition does not require that potons be repeatedly reflected across substantial distances within the spherical envelope, but indeed is greatest when photons undergo a nearly local diffusion, e.g., through scattering by many lines closely spaced in frequency. Our results reiterate the view that the so-called 'momentum problem' of Wolf-Rayet winds is better characterized as an 'opacity problem' of simply identfying enough lines. One way of increasing the number of thick lines in Wolf-Rayet winds is to transfer opacity from saturated to unsaturated lines, yielding a steeper opacity distribution than that found in OB winds. We discuss the implications of this perspective for extending our approach to W-R wind models that incorporate a more fundamental treatment of the ionization and excitation processes that determine the line opacity. In particular, we argue that developing statistical descriptions of the lines to allow an improved effective opacity for the line ensemble would offer several advantages for deriving such more fundamental W-R wind models.

Momentum deposition on Wolf-Rayet winds: Nonisotropic diffusion with effective gray opacity

NASA Astrophysics Data System (ADS)

Gayley, Kenneth G.; Owocki, Stanley P.; Cranmer, Steven R.

1995-03-01

We derive the velocity and mass-loss rate of a steady state Wolf-Rayet (WR) wind, using a nonisotropic diffusion approximation applied to the transfer between strongly overlapping spectral lines. Following the approach of Friend & Castor (1983), the line list is assumed to approximate a statistically parameterized Poisson distribution in frequency, so that photon transport is controlled by an angle-dependent, effectively gray opacity. We show the nonisotropic diffusion approximation yields good agreement with more accurate numerical treatments of the radiative transfer, while providing analytic insight into wind driving by multiple scattering. We illustrate, in particular, that multiple radiative momentum deposition does not require that photons be repeatedly reflected across substantial distances within the spherical envelope, but indeed is greatest when photons undergo a nearly local diffusion, e.g., through scattering by many lines closely spaced in frequency. Our results reiterate the view that the so-called 'momentum problem' of Wolf-Rayet winds is better characterized as an 'opacity problem' of simply identifying enough lines. One way of increasing the number of thick lines in Wolf-Rayet winds is to transfer opacity from saturated to unsaturated lines, yielding a steeper opacity distribution than that found in OB winds. We discuss the implications of this perspective for extending our approach to W-R wind models that incorporate a more fundamental treatment of the ionization and excitation processes that determine the line opacity. In particular, we argue that developing statistical descriptions of the lines to allow an improved effective opacity for the line ensemble would offer several advantages for deriving such more fundamental W-R wind models.

Rarefied gas flows through a curved channel: Application of a diffusion-type equation

NASA Astrophysics Data System (ADS)

Aoki, Kazuo; Takata, Shigeru; Tatsumi, Eri; Yoshida, Hiroaki

2010-11-01

Rarefied gas flows through a curved two-dimensional channel, caused by a pressure or a temperature gradient, are investigated numerically by using a macroscopic equation of convection-diffusion type. The equation, which was derived systematically from the Bhatnagar-Gross-Krook model of the Boltzmann equation and diffuse-reflection boundary condition in a previous paper [K. Aoki et al., "A diffusion model for rarefied flows in curved channels," Multiscale Model. Simul. 6, 1281 (2008)], is valid irrespective of the degree of gas rarefaction when the channel width is much shorter than the scale of variations of physical quantities and curvature along the channel. Attention is also paid to a variant of the Knudsen compressor that can produce a pressure raise by the effect of the change of channel curvature and periodic temperature distributions without any help of moving parts. In the process of analysis, the macroscopic equation is (partially) extended to the case of the ellipsoidal-statistical model of the Boltzmann equation.

Numerical approach to describe complementary drying of banana slices osmotically dehydrated

NASA Astrophysics Data System (ADS)

da Silva Júnior, Aluízio Freire; da Silva, Wilton Pereira; de Farias Aires, Juarez Everton; Farias Aires, Kalina Lígia C. A.

2018-02-01

In this work, diffusion model was used to describe the water loss in the complementary drying process of cylindrical slices of banana pretreated by osmotic dehydration. A numerical solution has been proposed for the diffusion equation in cylindrical coordinates, which was obtained through the Finite Volume Method. The diffusion equation was discretized assuming that the effective water diffusivity and the dimensions of a finite cylinder may vary; also considering the boundary condition of the third kind. The banana slices were cut in length of about 1.00 cm and average radius 1.70 cm before osmotic pretreatment, and completed the pretreatment with length of about 0.74 cm and average radius 1.40 cm. The complementary drying was carried out in a kiln with circulation and air exchange. Drying temperatures were the same as used in the osmotic pretreatment (40 to 70 °C). The proposed model described well the water loss, with good statistical indicators for all fits.

Computer-aided, multi-modal, and compression diffuse optical studies of breast tissue

NASA Astrophysics Data System (ADS)

Busch, David Richard, Jr.

Diffuse Optical Tomography and Spectroscopy permit measurement of important physiological parameters non-invasively through ˜10 cm of tissue. I have applied these techniques in measurements of human breast and breast cancer. My thesis integrates three loosely connected themes in this context: multi-modal breast cancer imaging, automated data analysis of breast cancer images, and microvascular hemodynamics of breast under compression. As per the first theme, I describe construction, testing, and the initial clinical usage of two generations of imaging systems for simultaneous diffuse optical and magnetic resonance imaging. The second project develops a statistical analysis of optical breast data from many spatial locations in a population of cancers to derive a novel optical signature of malignancy; I then apply this data-derived signature for localization of cancer in additional subjects. Finally, I construct and deploy diffuse optical instrumentation to measure blood content and blood flow during breast compression; besides optics, this research has implications for any method employing breast compression, e.g., mammography.

Multi-charge-state molecular dynamics and self-diffusion coefficient in the warm dense matter regime

NASA Astrophysics Data System (ADS)

Fu, Yongsheng; Hou, Yong; Kang, Dongdong; Gao, Cheng; Jin, Fengtao; Yuan, Jianmin

2018-01-01

We present a multi-ion molecular dynamics (MIMD) simulation and apply it to calculating the self-diffusion coefficients of ions with different charge-states in the warm dense matter (WDM) regime. First, the method is used for the self-consistent calculation of electron structures of different charge-state ions in the ion sphere, with the ion-sphere radii being determined by the plasma density and the ion charges. The ionic fraction is then obtained by solving the Saha equation, taking account of interactions among different charge-state ions in the system, and ion-ion pair potentials are computed using the modified Gordon-Kim method in the framework of temperature-dependent density functional theory on the basis of the electron structures. Finally, MIMD is used to calculate ionic self-diffusion coefficients from the velocity correlation function according to the Green-Kubo relation. A comparison with the results of the average-atom model shows that different statistical processes will influence the ionic diffusion coefficient in the WDM regime.

Microscopic origin and macroscopic implications of lane formation in mixtures of oppositely-driven particles

NASA Astrophysics Data System (ADS)

Whitelam, Stephen

Colloidal particles of two types, driven in opposite directions, can segregate into lanes. I will describe some results on this phenomenon obtained by simple physical arguments and computer simulations. Laning results from rectification of diffusion on the scale of a particle diameter: oppositely-driven particles must, in the time taken to encounter each other in the direction of the drive, diffuse in the perpendicular direction by about one particle diameter. This geometric constraint implies that the diffusion constant of a particle, in the presence of those of the opposite type, grows approximately linearly with Peclet number, a prediction confirmed by our numerics. Such environment-dependent diffusion is statistically similar to an effective interparticle attraction; consistent with this observation, we find that oppositely-driven colloids display features characteristic of the simplest model system possessing both interparticle attractions and persistent motion, the driven Ising lattice gas. Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Effect of cyclic and static tensile loading on water content and solute diffusion in canine flexor tendons: an in vitro study.

PubMed

Hannafin, J A; Arnoczky, S P

1994-05-01

This study was designed to determine the effects of various loading conditions (no load and static and cyclic tensile load) on the water content and pattern of nutrient diffusion of canine flexor tendons in vitro. Region D (designated by Okuda et al.) of the flexor digitorum profundus was subjected to a cyclic or static tensile load of 100 g for times ranging from 5 minutes to 24 hours. The results demonstrated a statistically significant loss of water in tendons subjected to both types of load as compared with the controls (no load). This loss appeared to progress with time. However, neither static nor cyclic loading appeared to alter the diffusion of 3H-glucose into the tendon over a 24-hour period compared with the controls. These results suggest that any benefit in tendon repair derived from intermittent passive motion is probably not a result of an increase in the diffusion of small nutrients in response to intermittent tensile load.

Fast numerical methods for simulating large-scale integrate-and-fire neuronal networks.

PubMed

Rangan, Aaditya V; Cai, David

2007-02-01

We discuss numerical methods for simulating large-scale, integrate-and-fire (I&F) neuronal networks. Important elements in our numerical methods are (i) a neurophysiologically inspired integrating factor which casts the solution as a numerically tractable integral equation, and allows us to obtain stable and accurate individual neuronal trajectories (i.e., voltage and conductance time-courses) even when the I&F neuronal equations are stiff, such as in strongly fluctuating, high-conductance states; (ii) an iterated process of spike-spike corrections within groups of strongly coupled neurons to account for spike-spike interactions within a single large numerical time-step; and (iii) a clustering procedure of firing events in the network to take advantage of localized architectures, such as spatial scales of strong local interactions, which are often present in large-scale computational models-for example, those of the primary visual cortex. (We note that the spike-spike corrections in our methods are more involved than the correction of single neuron spike-time via a polynomial interpolation as in the modified Runge-Kutta methods commonly used in simulations of I&F neuronal networks.) Our methods can evolve networks with relatively strong local interactions in an asymptotically optimal way such that each neuron fires approximately once in [Formula: see text] operations, where N is the number of neurons in the system. We note that quantifications used in computational modeling are often statistical, since measurements in a real experiment to characterize physiological systems are typically statistical, such as firing rate, interspike interval distributions, and spike-triggered voltage distributions. We emphasize that it takes much less computational effort to resolve statistical properties of certain I&F neuronal networks than to fully resolve trajectories of each and every neuron within the system. For networks operating in realistic dynamical regimes, such as strongly fluctuating, high-conductance states, our methods are designed to achieve statistical accuracy when very large time-steps are used. Moreover, our methods can also achieve trajectory-wise accuracy when small time-steps are used.

Ensemble Kalman filters for dynamical systems with unresolved turbulence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grooms, Ian, E-mail: grooms@cims.nyu.edu; Lee, Yoonsang; Majda, Andrew J.

Ensemble Kalman filters are developed for turbulent dynamical systems where the forecast model does not resolve all the active scales of motion. Coarse-resolution models are intended to predict the large-scale part of the true dynamics, but observations invariably include contributions from both the resolved large scales and the unresolved small scales. The error due to the contribution of unresolved scales to the observations, called ‘representation’ or ‘representativeness’ error, is often included as part of the observation error, in addition to the raw measurement error, when estimating the large-scale part of the system. It is here shown how stochastic superparameterization (amore » multiscale method for subgridscale parameterization) can be used to provide estimates of the statistics of the unresolved scales. In addition, a new framework is developed wherein small-scale statistics can be used to estimate both the resolved and unresolved components of the solution. The one-dimensional test problem from dispersive wave turbulence used here is computationally tractable yet is particularly difficult for filtering because of the non-Gaussian extreme event statistics and substantial small scale turbulence: a shallow energy spectrum proportional to k{sup −5/6} (where k is the wavenumber) results in two-thirds of the climatological variance being carried by the unresolved small scales. Because the unresolved scales contain so much energy, filters that ignore the representation error fail utterly to provide meaningful estimates of the system state. Inclusion of a time-independent climatological estimate of the representation error in a standard framework leads to inaccurate estimates of the large-scale part of the signal; accurate estimates of the large scales are only achieved by using stochastic superparameterization to provide evolving, large-scale dependent predictions of the small-scale statistics. Again, because the unresolved scales contain so much energy, even an accurate estimate of the large-scale part of the system does not provide an accurate estimate of the true state. By providing simultaneous estimates of both the large- and small-scale parts of the solution, the new framework is able to provide accurate estimates of the true system state.« less

A SIGNIFICANCE TEST FOR THE LASSO1

PubMed Central

Lockhart, Richard; Taylor, Jonathan; Tibshirani, Ryan J.; Tibshirani, Robert

2014-01-01

In the sparse linear regression setting, we consider testing the significance of the predictor variable that enters the current lasso model, in the sequence of models visited along the lasso solution path. We propose a simple test statistic based on lasso fitted values, called the covariance test statistic, and show that when the true model is linear, this statistic has an Exp(1) asymptotic distribution under the null hypothesis (the null being that all truly active variables are contained in the current lasso model). Our proof of this result for the special case of the first predictor to enter the model (i.e., testing for a single significant predictor variable against the global null) requires only weak assumptions on the predictor matrix X. On the other hand, our proof for a general step in the lasso path places further technical assumptions on X and the generative model, but still allows for the important high-dimensional case p > n, and does not necessarily require that the current lasso model achieves perfect recovery of the truly active variables. Of course, for testing the significance of an additional variable between two nested linear models, one typically uses the chi-squared test, comparing the drop in residual sum of squares (RSS) to a χ12 distribution. But when this additional variable is not fixed, and has been chosen adaptively or greedily, this test is no longer appropriate: adaptivity makes the drop in RSS stochastically much larger than χ12 under the null hypothesis. Our analysis explicitly accounts for adaptivity, as it must, since the lasso builds an adaptive sequence of linear models as the tuning parameter λ decreases. In this analysis, shrinkage plays a key role: though additional variables are chosen adaptively, the coefficients of lasso active variables are shrunken due to the l1 penalty. Therefore, the test statistic (which is based on lasso fitted values) is in a sense balanced by these two opposing properties—adaptivity and shrinkage—and its null distribution is tractable and asymptotically Exp(1). PMID:25574062

Statistical Issues for Uncontrolled Reentry Hazards

NASA Technical Reports Server (NTRS)

Matney, Mark

2008-01-01

A number of statistical tools have been developed over the years for assessing the risk of reentering objects to human populations. These tools make use of the characteristics (e.g., mass, shape, size) of debris that are predicted by aerothermal models to survive reentry. The statistical tools use this information to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of the analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. This inevitably involves assumptions that simplify the problem and make it tractable, but it is often difficult to test the accuracy and applicability of these assumptions. This paper looks at a number of these theoretical assumptions, examining the mathematical basis for the hazard calculations, and outlining the conditions under which the simplifying assumptions hold. In addition, this paper will also outline some new tools for assessing ground hazard risk in useful ways. Also, this study is able to make use of a database of known uncontrolled reentry locations measured by the United States Department of Defense. By using data from objects that were in orbit more than 30 days before reentry, sufficient time is allowed for the orbital parameters to be randomized in the way the models are designed to compute. The predicted ground footprint distributions of these objects are based on the theory that their orbits behave basically like simple Kepler orbits. However, there are a number of factors - including the effects of gravitational harmonics, the effects of the Earth's equatorial bulge on the atmosphere, and the rotation of the Earth and atmosphere - that could cause them to diverge from simple Kepler orbit behavior and change the ground footprints. The measured latitude and longitude distributions of these objects provide data that can be directly compared with the predicted distributions, providing a fundamental empirical test of the model assumptions.

EEG dynamical correlates of focal and diffuse causes of coma.

PubMed

Kafashan, MohammadMehdi; Ryu, Shoko; Hargis, Mitchell J; Laurido-Soto, Osvaldo; Roberts, Debra E; Thontakudi, Akshay; Eisenman, Lawrence; Kummer, Terrance T; Ching, ShiNung

2017-11-15

Rapidly determining the causes of a depressed level of consciousness (DLOC) including coma is a common clinical challenge. Quantitative analysis of the electroencephalogram (EEG) has the potential to improve DLOC assessment by providing readily deployable, temporally detailed characterization of brain activity in such patients. While used commonly for seizure detection, EEG-based assessment of DLOC etiology is less well-established. As a first step towards etiological diagnosis, we sought to distinguish focal and diffuse causes of DLOC through assessment of temporal dynamics within EEG signals. We retrospectively analyzed EEG recordings from 40 patients with DLOC with consensus focal or diffuse culprit pathology. For each recording, we performed a suite of time-series analyses, then used a statistical framework to identify which analyses (features) could be used to distinguish between focal and diffuse cases. Using cross-validation approaches, we identified several spectral and non-spectral EEG features that were significantly different between DLOC patients with focal vs. diffuse etiologies, enabling EEG-based classification with an accuracy of 76%. Our findings suggest that DLOC due to focal vs. diffuse injuries differ along several electrophysiological parameters. These results may form the basis of future classification strategies for DLOC and coma that are more etiologically-specific and therefore therapeutically-relevant.