Validation of a mixture-averaged thermal diffusion model for premixed lean hydrogen flames

NASA Astrophysics Data System (ADS)

Schlup, Jason; Blanquart, Guillaume

2018-03-01

The mixture-averaged thermal diffusion model originally proposed by Chapman and Cowling is validated using multiple flame configurations. Simulations using detailed hydrogen chemistry are done on one-, two-, and three-dimensional flames. The analysis spans flat and stretched, steady and unsteady, and laminar and turbulent flames. Quantitative and qualitative results using the thermal diffusion model compare very well with the more complex multicomponent diffusion model. Comparisons are made using flame speeds, surface areas, species profiles, and chemical source terms. Once validated, this model is applied to three-dimensional laminar and turbulent flames. For these cases, thermal diffusion causes an increase in the propagation speed of the flames as well as increased product chemical source terms in regions of high positive curvature. The results illustrate the necessity for including thermal diffusion, and the accuracy and computational efficiency of the mixture-averaged thermal diffusion model.

Modelling Diffusion of a Personalized Learning Framework

ERIC Educational Resources Information Center

Karmeshu; Raman, Raghu; Nedungadi, Prema

2012-01-01

A new modelling approach for diffusion of personalized learning as an educational process innovation in social group comprising adopter-teachers is proposed. An empirical analysis regarding the perception of 261 adopter-teachers from 18 schools in India about a particular personalized learning framework has been made. Based on this analysis,…

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.

Modified chloride diffusion model for concrete under the coupling effect of mechanical load and chloride salt environment

NASA Astrophysics Data System (ADS)

Lei, Mingfeng; Lin, Dayong; Liu, Jianwen; Shi, Chenghua; Ma, Jianjun; Yang, Weichao; Yu, Xiaoniu

2018-03-01

For the purpose of investigating lining concrete durability, this study derives a modified chloride diffusion model for concrete based on the odd continuation of boundary conditions and Fourier transform. In order to achieve this, the linear stress distribution on a sectional structure is considered, detailed procedures and methods are presented for model verification and parametric analysis. Simulation results show that the chloride diffusion model can reflect the effects of linear stress distribution of the sectional structure on the chloride diffusivity with reliable accuracy. Along with the natural environmental characteristics of practical engineering structures, reference value ranges of model parameters are provided. Furthermore, a chloride diffusion model is extended for the consideration of multi-factor coupling of linear stress distribution, chloride concentration and diffusion time. Comparison between model simulation and typical current research results shows that the presented model can produce better considerations with a greater universality.

Analysis of redox additive-based overcharge protection for rechargeable lithium batteries

NASA Technical Reports Server (NTRS)

Narayanan, S. R.; Surampudi, S.; Attia, A. I.; Bankston, C. P.

1991-01-01

The overcharge condition in secondary lithium batteries employing redox additives for overcharge protection, has been theoretically analyzed in terms of a finite linear diffusion model. The analysis leads to expressions relating the steady-state overcharge current density and cell voltage to the concentration, diffusion coefficient, standard reduction potential of the redox couple, and interelectrode distance. The model permits the estimation of the maximum permissible overcharge rate for any chosen set of system conditions. Digital simulation of the overcharge experiment leads to numerical representation of the potential transients, and estimate of the influence of diffusion coefficient and interelectrode distance on the transient attainment of the steady state during overcharge. The model has been experimentally verified using 1,1-prime-dimethyl ferrocene as a redox additive. The analysis of the experimental results in terms of the theory allows the calculation of the diffusion coefficient and the formal potential of the redox couple. The model and the theoretical results may be exploited in the design and optimization of overcharge protection by the redox additive approach.

OpinionFlow: Visual Analysis of Opinion Diffusion on Social Media.

PubMed

Wu, Yingcai; Liu, Shixia; Yan, Kai; Liu, Mengchen; Wu, Fangzhao

2014-12-01

It is important for many different applications such as government and business intelligence to analyze and explore the diffusion of public opinions on social media. However, the rapid propagation and great diversity of public opinions on social media pose great challenges to effective analysis of opinion diffusion. In this paper, we introduce a visual analysis system called OpinionFlow to empower analysts to detect opinion propagation patterns and glean insights. Inspired by the information diffusion model and the theory of selective exposure, we develop an opinion diffusion model to approximate opinion propagation among Twitter users. Accordingly, we design an opinion flow visualization that combines a Sankey graph with a tailored density map in one view to visually convey diffusion of opinions among many users. A stacked tree is used to allow analysts to select topics of interest at different levels. The stacked tree is synchronized with the opinion flow visualization to help users examine and compare diffusion patterns across topics. Experiments and case studies on Twitter data demonstrate the effectiveness and usability of OpinionFlow.

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 model of diffuse speckle contrast analysis for flow measurement.

PubMed

Liu, Jialin; Zhang, Hongchao; Lu, Jian; Ni, Xiaowu; Shen, Zhonghua

2017-07-01

Diffuse speckle contrast analysis (DSCA) is a noninvasive optical technique capable of monitoring deep tissue blood flow. However, a detailed study of the speckle contrast model for DSCA has yet to be presented. We deduced the theoretical relationship between speckle contrast and exposure time and further simplified it to a linear approximation model. The feasibility of this linear model was validated by the liquid phantoms which demonstrated that the slope of this linear approximation was able to rapidly determine the Brownian diffusion coefficient of the turbid media at multiple distances using multiexposure speckle imaging. Furthermore, we have theoretically quantified the influence of optical property on the measurements of the Brownian diffusion coefficient which was a consequence of the fact that the slope of this linear approximation was demonstrated to be equal to the inverse of correlation time of the speckle.

Porosity Measurement in Laminated Composites by Thermography and FEA

NASA Technical Reports Server (NTRS)

Chu, Tsuchin Philip; Russell, Samuel S.; Walker, James L.; Munafo, Paul M. (Technical Monitor)

2001-01-01

This paper presents the correlation between the through-thickness thermal diffusivity and the porosity of composites. Finite element analysis (FEA) was used to determine the transient thermal response of composites that were subjected to laser heating. A series of finite element models were built and thermal responses for isotropic and orthographic materials with various thermal diffusivities subjected to different heating conditions were investigated. Experiments were conducted to verify the models and to estimate the unknown parameters such as the amount of heat flux. The analysis and experimental results show good correlation between thermal diffusivity and porosity in the composite materials. They also show that both laser and flash heating can be used effectively to obtain thermal diffusivity. The current infrared thermography system is developed for use with flash heating. The laser heating models and the FEA results can provide useful tools to develop practical thermal diffusivity measurement scheme using laser heat.

Measurement and Modeling of the Optical Scattering Properties of Crop Canopies

NASA Technical Reports Server (NTRS)

Vanderbilt, V. C. (Principal Investigator)

1985-01-01

The specular reflection process is shown to be a key aspect of radiation transfer by plant canopies. Polarization measurements are demonstrated as the tool for determining the specular and diffuse portions of the canopy radiance. The magnitude of the specular fraction of the reflectance is significant compared to the magnitude of the diffuse fraction. Therefore, it is necessary to consider specularly reflected light in developing and evaluating light-canopy interaction models for wheat canopies. Models which assume leaves are diffuse reflectors correctly predict only the diffuse fraction of the canopy reflectance factor. The specular reflectance model, when coupled with a diffuse leaf model, would predict both the specular and diffuse portions of the reflectance factor. The specular model predicts and the data analysis confirms that the single variable, angle of incidence of specularly reflected sunlight on the leaf, explains much of variation in the polarization data as a function of view-illumination directions.

Influence Function Learning in Information Diffusion Networks.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-06-01

Can we learn the influence of a set of people in a social network from cascades of information diffusion? This question is often addressed by a two-stage approach: first learn a diffusion model, and then calculate the influence based on the learned model. Thus, the success of this approach relies heavily on the correctness of the diffusion model which is hard to verify for real world data. In this paper, we exploit the insight that the influence functions in many diffusion models are coverage functions, and propose a novel parameterization of such functions using a convex combination of random basis functions. Moreover, we propose an efficient maximum likelihood based algorithm to learn such functions directly from cascade data, and hence bypass the need to specify a particular diffusion model in advance. We provide both theoretical and empirical analysis for our approach, showing that the proposed approach can provably learn the influence function with low sample complexity, be robust to the unknown diffusion models, and significantly outperform existing approaches in both synthetic and real world data.

Diffusion equations and the time evolution of foreign exchange rates

NASA Astrophysics Data System (ADS)

Figueiredo, Annibal; de Castro, Marcio T.; da Fonseca, Regina C. B.; Gleria, Iram

2013-10-01

We investigate which type of diffusion equation is most appropriate to describe the time evolution of foreign exchange rates. We modify the geometric diffusion model assuming a non-exponential time evolution and the stochastic term is the sum of a Wiener noise and a jump process. We find the resulting diffusion equation to obey the Kramers-Moyal equation. Analytical solutions are obtained using the characteristic function formalism and compared with empirical data. The analysis focus on the first four central moments considering the returns of foreign exchange rate. It is shown that the proposed model offers a good improvement over the classical geometric diffusion model.

Analysis of the geometrical-probabilistic models of electrocrystallization

NASA Astrophysics Data System (ADS)

Isaev, V. A.; Grishenkova, O. V.; Zaykov, Yu. P.

2016-08-01

The formation of a three-dimensional electrode deposit under potentiostatic conditions, including the stages of nucleation, growth, and overlap of growing new-phase clusters and their diffusion zones, is considered. The models of electrochemical phase formation for kinetics- and diffusion-controlled growth are analyzed, and the correctness of the approximations used in these models is estimated. The possibility of application of these models to an analysis of the electrodeposition of silicon from molten salts is discussed.

Applying horizontal diffusion on pressure surface to mesoscale models on terrain-following coordinates

Treesearch

Hann-Ming Henry Juang; Ching-Teng Lee; Yongxin Zhang; Yucheng Song; Ming-Chin Wu; Yi-Leng Chen; Kevin Kodama; Shyh-Chin Chen

2005-01-01

The National Centers for Environmental Prediction regional spectral model and mesoscale spectral model (NCEP RSM/MSM) use a spectral computation on perturbation. The perturbation is defined as a deviation between RSM/MSM forecast value and their outer model or analysis value on model sigma-coordinate surfaces. The horizontal diffusion used in the models applies...

Lévy-like diffusion in eye movements during spoken-language comprehension.

PubMed

Stephen, Damian G; Mirman, Daniel; Magnuson, James S; Dixon, James A

2009-05-01

This study explores the diffusive properties of human eye movements during a language comprehension task. In this task, adults are given auditory instructions to locate named objects on a computer screen. Although it has been convention to model visual search as standard Brownian diffusion, we find evidence that eye movements are hyperdiffusive. Specifically, we use comparisons of maximum-likelihood fit as well as standard deviation analysis and diffusion entropy analysis to show that visual search during language comprehension exhibits Lévy-like rather than Gaussian diffusion.

Lévy-like diffusion in eye movements during spoken-language comprehension

NASA Astrophysics Data System (ADS)

Stephen, Damian G.; Mirman, Daniel; Magnuson, James S.; Dixon, James A.

2009-05-01

This study explores the diffusive properties of human eye movements during a language comprehension task. In this task, adults are given auditory instructions to locate named objects on a computer screen. Although it has been convention to model visual search as standard Brownian diffusion, we find evidence that eye movements are hyperdiffusive. Specifically, we use comparisons of maximum-likelihood fit as well as standard deviation analysis and diffusion entropy analysis to show that visual search during language comprehension exhibits Lévy-like rather than Gaussian diffusion.

Far-field analysis of coupled bulk and boundary layer diffusion toward an ion channel entrance.

PubMed Central

Schumaker, M F; Kentler, C J

1998-01-01

We present a far-field analysis of ion diffusion toward a channel embedded in a membrane with a fixed charge density. The Smoluchowski equation, which represents the 3D problem, is approximated by a system of coupled three- and two-dimensional diffusions. The 2D diffusion models the quasi-two-dimensional diffusion of ions in a boundary layer in which the electrical potential interaction with the membrane surface charge is important. The 3D diffusion models ion transport in the bulk region outside the boundary layer. Analytical expressions for concentration and flux are developed that are accurate far from the channel entrance. These provide boundary conditions for a numerical solution of the problem. Our results are used to calculate far-field ion flows corresponding to experiments of Bell and Miller (Biophys. J. 45:279, 1984). PMID:9591651

Photon migration through a turbid slab described by a model based on diffusion approximation. I. Theory.

PubMed

Contini, D; Martelli, F; Zaccanti, G

1997-07-01

The diffusion approximation of the radiative transfer equation is a model used widely to describe photon migration in highly diffusing media and is an important matter in biological tissue optics. An analysis of the time-dependent diffusion equation together with its solutions for the slab geometry and for a semi-infinite diffusing medium are reported. These solutions, presented for both the time-dependent and the continuous wave source, account for the refractive index mismatch between the turbid medium and the surrounding medium. The results have been compared with those obtained when different boundary conditions were assumed. The comparison has shown that the effect of the refractive index mismatch cannot be disregarded. This effect is particularly important for the transmittance. The discussion of results also provides an analysis of the role of the absorption coefficient in the expression of the diffusion coefficient.

Communication: Coordinate-dependent diffusivity from single molecule trajectories

NASA Astrophysics Data System (ADS)

Berezhkovskii, Alexander M.; Makarov, Dmitrii E.

2017-11-01

Single-molecule observations of biomolecular folding are commonly interpreted using the model of one-dimensional diffusion along a reaction coordinate, with a coordinate-independent diffusion coefficient. Recent analysis, however, suggests that more general models are required to account for single-molecule measurements performed with high temporal resolution. Here, we consider one such generalization: a model where the diffusion coefficient can be an arbitrary function of the reaction coordinate. Assuming Brownian dynamics along this coordinate, we derive an exact expression for the coordinate-dependent diffusivity in terms of the splitting probability within an arbitrarily chosen interval and the mean transition path time between the interval boundaries. This formula can be used to estimate the effective diffusion coefficient along a reaction coordinate directly from single-molecule trajectories.

Calculating Mass Diffusion in High-Pressure Binary Fluids

NASA Technical Reports Server (NTRS)

Bellan, Josette; Harstad, Kenneth

2004-01-01

A comprehensive mathematical model of mass diffusion has been developed for binary fluids at high pressures, including critical and supercritical pressures. Heretofore, diverse expressions, valid for limited parameter ranges, have been used to correlate high-pressure binary mass-diffusion-coefficient data. This model will likely be especially useful in the computational simulation and analysis of combustion phenomena in diesel engines, gas turbines, and liquid rocket engines, wherein mass diffusion at high pressure plays a major role.

Analysis of models for two solution crystal growth problems

NASA Technical Reports Server (NTRS)

Fehribach, Joseph D.; Rosenberger, Franz

1989-01-01

Two diffusive solution crystal growth models are considered which are characterized by two phases separated by an interface, a lack of convective mixing in either phase, and the presence of diffusion components differing widely in diffusivity. The first model describes precipitant-driven solution crystal growth and the second model describes a hanging drop evaporation problem. It is shown that for certain proteins sharp concentration gradients may develop in the drop during evaporation, while under the same conditions the concentrations of other proteins remain uniform.

Modeling of tritium transport in a fusion reactor pin-type solid breeder blanket using the diffuse code

NASA Astrophysics Data System (ADS)

Martin, Rodger; Ghoniem, Nasr M.

1986-11-01

A pin-type fusion reactor blanket is designed using γ-LiAlO 2 solid tritium breeder. Tritium transport and diffusive inventory are modeled using the DIFFUSE code. Two approaches are used to obtain characteristic LiAlO 2 grain temperatures. DIFFUSE provides intragranular diffusive inventories which scale up to blanket size. These results compare well with a numerical analysis, giving a steady-state blanket tritium inventory of 13 g. Start-up transient inventories are modeled using DIFFUSE for both full and restricted coolant flow. Full flow gives rapid inventory buildup while restricted flow prevents this buildup. Inventories after shutdown are modeled: reduced cooling is found to have little effect on removing tritium, but preheating rapidly purges inventory. DIFFUSE provides parametric modeling of solid breeder density, radiation, and surface effects. 100% dense pins are found to give massive inventory and marginal tritium release. Only large trapping energies and concentrations significantly increase inventory. Diatomic surface recombination is only significant at high temperatures.

A multiscale MD-FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure.

PubMed

Kojic, M; Milosevic, M; Kojic, N; Kim, K; Ferrari, M; Ziemys, A

2014-02-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts.

A multiscale MD–FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure

PubMed Central

Kojic, M.; Milosevic, M.; Kojic, N.; Kim, K.; Ferrari, M.; Ziemys, A.

2014-01-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts. PMID:24578582

Multimodel analysis of anisotropic diffusive tracer-gas transport in a deep arid unsaturated zone

USGS Publications Warehouse

Green, Christopher T.; Walvoord, Michelle Ann; Andraski, Brian J.; Striegl, Robert G.; Stonestrom, David A.

2015-01-01

Gas transport in the unsaturated zone affects contaminant flux and remediation, interpretation of groundwater travel times from atmospheric tracers, and mass budgets of environmentally important gases. Although unsaturated zone transport of gases is commonly treated as dominated by diffusion, the characteristics of transport in deep layered sediments remain uncertain. In this study, we use a multimodel approach to analyze results of a gas-tracer (SF6) test to clarify characteristics of gas transport in deep unsaturated alluvium. Thirty-five separate models with distinct diffusivity structures were calibrated to the tracer-test data and were compared on the basis of Akaike Information Criteria estimates of posterior model probability. Models included analytical and numerical solutions. Analytical models provided estimates of bulk-scale apparent diffusivities at the scale of tens of meters. Numerical models provided information on local-scale diffusivities and feasible lithological features producing the observed tracer breakthrough curves. The combined approaches indicate significant anisotropy of bulk-scale diffusivity, likely associated with high-diffusivity layers. Both approaches indicated that diffusivities in some intervals were greater than expected from standard models relating porosity to diffusivity. High apparent diffusivities and anisotropic diffusivity structures were consistent with previous observations at the study site of rapid lateral transport and limited vertical spreading of gas-phase contaminants. Additional processes such as advective oscillations may be involved. These results indicate that gases in deep, layered unsaturated zone sediments can spread laterally more quickly, and produce higher peak concentrations, than predicted by homogeneous, isotropic diffusion models.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals.

PubMed

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-04-08

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals

PubMed Central

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-01-01

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems. DOI: http://dx.doi.org/10.7554/eLife.14022.001 PMID:27058171

Ti diffusion in ion prebombarded MgO(100). I. A model for quantitative analysis

NASA Astrophysics Data System (ADS)

Lu, M.; Lupu, C.; Styve, V. J.; Lee, S. M.; Rabalais, J. W.

2002-01-01

Enhancement of Ti diffusion in MgO(100) prebombarded with 7 keV Ar+ has been observed. Diffusion was induced by annealing to 1000 °C following the prebombardment and Ti evaporation. Such a sample geometry and experimental procedure alleviates the continuous provision of freely mobile defects introduced by ion irradiation during annealing for diffusion, making diffusion proceed in a non-steady-state condition. Diffusion penetration profiles were obtained by using secondary ion mass spectrometry depth profiling techniques. A model that includes a depth-dependent diffusion coefficient was proposed, which successfully explains the observed non-steady-state radiation enhanced diffusion. The diffusion coefficients are of the order of 10-20 m2/s and are enhanced due to the defect structure inflected by the Ar+ prebombardment.

Diffusion-advection within dynamic biological gaps driven by structural motion

NASA Astrophysics Data System (ADS)

Asaro, Robert J.; Zhu, Qiang; Lin, Kuanpo

2018-04-01

To study the significance of advection in the transport of solutes, or particles, within thin biological gaps (channels), we examine theoretically the process driven by stochastic fluid flow caused by random thermal structural motion, and we compare it with transport via diffusion. The model geometry chosen resembles the synaptic cleft; this choice is motivated by the cleft's readily modeled structure, which allows for well-defined mechanical and physical features that control the advection process. Our analysis defines a Péclet-like number, AD, that quantifies the ratio of time scales of advection versus diffusion. Another parameter, AM, is also defined by the analysis that quantifies the full potential extent of advection in the absence of diffusion. These parameters provide a clear and compact description of the interplay among the well-defined structural, geometric, and physical properties vis-a ̀-vis the advection versus diffusion process. For example, it is found that AD˜1 /R2 , where R is the cleft diameter and hence diffusion distance. This curious, and perhaps unexpected, result follows from the dependence of structural motion that drives fluid flow on R . AM, on the other hand, is directly related (essentially proportional to) the energetic input into structural motion, and thereby to fluid flow, as well as to the mechanical stiffness of the cleftlike structure. Our model analysis thus provides unambiguous insight into the prospect of competition of advection versus diffusion within biological gaplike structures. The importance of the random, versus a regular, nature of structural motion and of the resulting transient nature of advection under random motion is made clear in our analysis. Further, by quantifying the effects of geometric and physical properties on the competition between advection and diffusion, our results clearly demonstrate the important role that metabolic energy (ATP) plays in this competitive process.

Modeling of information diffusion in Twitter-like social networks under information overload.

PubMed

Li, Pei; Li, Wei; Wang, Hui; Zhang, Xin

2014-01-01

Due to the existence of information overload in social networks, it becomes increasingly difficult for users to find useful information according to their interests. This paper takes Twitter-like social networks into account and proposes models to characterize the process of information diffusion under information overload. Users are classified into different types according to their in-degrees and out-degrees, and user behaviors are generalized into two categories: generating and forwarding. View scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated by a given type user is adopted to characterize the information diffusion efficiency, which is calculated theoretically. To verify the accuracy of theoretical analysis results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of importance to understand the diffusion dynamics in social networks, and this analysis framework can be extended to consider more realistic situations.

Modeling of Information Diffusion in Twitter-Like Social Networks under Information Overload

PubMed Central

Li, Wei

2014-01-01

Due to the existence of information overload in social networks, it becomes increasingly difficult for users to find useful information according to their interests. This paper takes Twitter-like social networks into account and proposes models to characterize the process of information diffusion under information overload. Users are classified into different types according to their in-degrees and out-degrees, and user behaviors are generalized into two categories: generating and forwarding. View scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated by a given type user is adopted to characterize the information diffusion efficiency, which is calculated theoretically. To verify the accuracy of theoretical analysis results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of importance to understand the diffusion dynamics in social networks, and this analysis framework can be extended to consider more realistic situations. PMID:24795541

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.

Influence Function Learning in Information Diffusion Networks

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Can we learn the influence of a set of people in a social network from cascades of information diffusion? This question is often addressed by a two-stage approach: first learn a diffusion model, and then calculate the influence based on the learned model. Thus, the success of this approach relies heavily on the correctness of the diffusion model which is hard to verify for real world data. In this paper, we exploit the insight that the influence functions in many diffusion models are coverage functions, and propose a novel parameterization of such functions using a convex combination of random basis functions. Moreover, we propose an efficient maximum likelihood based algorithm to learn such functions directly from cascade data, and hence bypass the need to specify a particular diffusion model in advance. We provide both theoretical and empirical analysis for our approach, showing that the proposed approach can provably learn the influence function with low sample complexity, be robust to the unknown diffusion models, and significantly outperform existing approaches in both synthetic and real world data. PMID:25973445

Diffuse X-ray scattering from benzil, C(14)H(10)O(2): analysis via automatic refinement of a Monte Carlo model.

PubMed

Welberry, T R; Goossens, D J; Edwards, A J; David, W I

2001-01-01

A recently developed method for fitting a Monte Carlo computer-simulation model to observed single-crystal diffuse X-ray scattering has been used to study the diffuse scattering in benzil, diphenylethanedione, C(6)H(5)-CO-CO-C(6)H(5). A model involving 13 parameters consisting of 11 intermolecular force constants, a single intramolecular torsional force constant and a local Debye-Waller factor was refined to give an agreement factor, R = [summation operator omega(Delta I)(2)/summation operator omega I(obs)(2)](1/2), of 14.5% for 101,324 data points. The model was purely thermal in nature. The analysis has shown that the diffuse lines, which feature so prominently in the observed diffraction patterns, are due to strong longitudinal displacement correlations. These are transmitted from molecule to molecule via a network of contacts involving hydrogen bonding of an O atom on one molecule and the para H atom of the phenyl ring of a neighbouring molecule. The analysis also allowed the determination of a torsional force constant for rotations about the single bonds in the molecule. This is the first diffuse scattering study in which measurement of such internal molecular torsion forces has been attempted.

Fractional order analysis of Sephadex gel structures: NMR measurements reflecting anomalous diffusion

NASA Astrophysics Data System (ADS)

Magin, Richard L.; Akpa, Belinda S.; Neuberger, Thomas; Webb, Andrew G.

2011-12-01

We report the appearance of anomalous water diffusion in hydrophilic Sephadex gels observed using pulse field gradient (PFG) nuclear magnetic resonance (NMR). The NMR diffusion data was collected using a Varian 14.1 Tesla imaging system with a home-built RF saddle coil. A fractional order analysis of the data was used to characterize heterogeneity in the gels for the dynamics of water diffusion in this restricted environment. Several recent studies of anomalous diffusion have used the stretched exponential function to model the decay of the NMR signal, i.e., exp[-( bD) α], where D is the apparent diffusion constant, b is determined the experimental conditions (gradient pulse separation, durations and strength), and α is a measure of structural complexity. In this work, we consider a different case where the spatial Laplacian in the Bloch-Torrey equation is generalized to a fractional order model of diffusivity via a complexity parameter, β, a space constant, μ, and a diffusion coefficient, D. This treatment reverts to the classical result for the integer order case. The fractional order decay model was fit to the diffusion-weighted signal attenuation for a range of b-values (0 < b < 4000 s mm -2). Throughout this range of b values, the parameters β, μ and D, were found to correlate with the porosity and tortuosity of the gel structure.

A fractional motion diffusion model for grading pediatric brain tumors.

PubMed

Karaman, M Muge; Wang, He; Sui, Yi; Engelhard, Herbert H; Li, Yuhua; Zhou, Xiaohong Joe

2016-01-01

To demonstrate the feasibility of a novel fractional motion (FM) diffusion model for distinguishing low- versus high-grade pediatric brain tumors; and to investigate its possible advantage over apparent diffusion coefficient (ADC) and/or a previously reported continuous-time random-walk (CTRW) diffusion model. With approval from the institutional review board and written informed consents from the legal guardians of all participating patients, this study involved 70 children with histopathologically-proven brain tumors (30 low-grade and 40 high-grade). Multi- b -value diffusion images were acquired and analyzed using the FM, CTRW, and mono-exponential diffusion models. The FM parameters, D fm , φ , ψ (non-Gaussian diffusion statistical measures), and the CTRW parameters, D m , α , β (non-Gaussian temporal and spatial diffusion heterogeneity measures) were compared between the low- and high-grade tumor groups by using a Mann-Whitney-Wilcoxon U test. The performance of the FM model for differentiating between low- and high-grade tumors was evaluated and compared with that of the CTRW and the mono-exponential models using a receiver operating characteristic (ROC) analysis. The FM parameters were significantly lower ( p  < 0.0001) in the high-grade ( D fm : 0.81 ± 0.26, φ : 1.40 ± 0.10, ψ : 0.42 ± 0.11) than in the low-grade ( D fm : 1.52 ± 0.52, φ : 1.64 ± 0.13, ψ : 0.67 ± 0.13) tumor groups. The ROC analysis showed that the FM parameters offered better specificity (88% versus 73%), sensitivity (90% versus 82%), accuracy (88% versus 78%), and area under the curve (AUC, 93% versus 80%) in discriminating tumor malignancy compared to the conventional ADC. The performance of the FM model was similar to that of the CTRW model. Similar to the CTRW model, the FM model can improve differentiation between low- and high-grade pediatric brain tumors over ADC.

Task Inhibition and Response Inhibition in Older vs. Younger Adults: A Diffusion Model Analysis

PubMed Central

Schuch, Stefanie

2016-01-01

Differences in inhibitory ability between older (64–79 years, N = 24) and younger adults (18–26 years, N = 24) were investigated using a diffusion model analysis. Participants performed a task-switching paradigm that allows assessing n−2 task repetition costs, reflecting inhibitory control on the level of tasks, as well as n−1 response-repetition costs, reflecting inhibitory control on the level of responses. N−2 task repetition costs were of similar size in both age groups. Diffusion model analysis revealed that for both younger and older adults, drift rate parameters were smaller in the inhibition condition relative to the control condition, consistent with the idea that persisting task inhibition slows down response selection. Moreover, there was preliminary evidence for task inhibition effects in threshold separation and non-decision time in the older, but not the younger adults, suggesting that older adults might apply different strategies when dealing with persisting task inhibition. N−1 response-repetition costs in mean RT were larger in older than younger adults, but in mean error rates tended to be larger in younger than older adults. Diffusion-model analysis revealed longer non-decision times in response repetitions than response switches in both age groups, consistent with the idea that motor processes take longer in response repetitions than response switches due to persisting response inhibition of a previously executed response. The data also revealed age-related differences in overall performance: Older adults responded more slowly and more accurately than young adults, which was reflected by a higher threshold separation parameter in diffusion model analysis. Moreover, older adults showed larger non-decision times and higher variability in non-decision time than young adults, possibly reflecting slower and more variable motor processes. In contrast, overall drift rate did not differ between older and younger adults. Taken together, diffusion model analysis revealed differences in overall performance between the age groups, as well as preliminary evidence for age differences in dealing with task inhibition, but no evidence for an inhibitory deficit in older age. PMID:27895599

Spatial diffusion of raccoon rabies in Pennsylvania, USA.

PubMed

Moore, D A

1999-05-14

Identification of the geographic pattern of diffusion of a wildlife disease could lead to information regarding its control. The objective of this study was to model raccoon-rabies diffusion in Pennsylvania to identify geographic constraints on the diffusion pattern for potential use in bait-vaccination strategies. A trend-surface analysis (TSA) was used as a spatial filter for month to first report by county location. A cubic polynomial model was fitted (R2 = 0.80). Velocity vectors were calculated from the partial derivatives of the model and mapped to demonstrate the instantaneous speed of diffusion at each location. A main corridor of diffusion through the ridge and valley section of the state was evident early in the outbreak. Once the disease reached the northern counties, the disease moved west toward Ohio. I believe that TSA was useful in identifying the pattern of raccoon-rabies diffusion across the stage from the inherent noise of disease-reporting data.

Model coupling intraparticle diffusion/sorption, nonlinear sorption, and biodegradation processes

USGS Publications Warehouse

Karapanagioti, Hrissi K.; Gossard, Chris M.; Strevett, Keith A.; Kolar, Randall L.; Sabatini, David A.

2001-01-01

Diffusion, sorption and biodegradation are key processes impacting the efficiency of natural attenuation. While each process has been studied individually, limited information exists on the kinetic coupling of these processes. In this paper, a model is presented that couples nonlinear and nonequilibrium sorption (intraparticle diffusion) with biodegradation kinetics. Initially, these processes are studied independently (i.e., intraparticle diffusion, nonlinear sorption and biodegradation), with appropriate parameters determined from these independent studies. Then, the coupled processes are studied, with an initial data set used to determine biodegradation constants that were subsequently used to successfully predict the behavior of a second data set. The validated model is then used to conduct a sensitivity analysis, which reveals conditions where biodegradation becomes desorption rate-limited. If the chemical is not pre-equilibrated with the soil prior to the onset of biodegradation, then fast sorption will reduce aqueous concentrations and thus biodegradation rates. Another sensitivity analysis demonstrates the importance of including nonlinear sorption in a coupled diffusion/sorption and biodegradation model. While predictions based on linear sorption isotherms agree well with solution concentrations, for the conditions evaluated this approach overestimates the percentage of contaminant biodegraded by as much as 50%. This research demonstrates that nonlinear sorption should be coupled with diffusion/sorption and biodegradation models in order to accurately predict bioremediation and natural attenuation processes. To our knowledge this study is unique in studying nonlinear sorption coupled with intraparticle diffusion and biodegradation kinetics with natural media.

Diffusion of oxygen interstitials in UO2+x using kinetic Monte Carlo simulations: Role of O/M ratio and sensitivity analysis

NASA Astrophysics Data System (ADS)

Behera, Rakesh K.; Watanabe, Taku; Andersson, David A.; Uberuaga, Blas P.; Deo, Chaitanya S.

2016-04-01

Oxygen interstitials in UO2+x significantly affect the thermophysical properties and microstructural evolution of the oxide nuclear fuel. In hyperstoichiometric Urania (UO2+x), these oxygen interstitials form different types of defect clusters, which have different migration behavior. In this study we have used kinetic Monte Carlo (kMC) to evaluate diffusivities of oxygen interstitials accounting for mono- and di-interstitial clusters. Our results indicate that the predicted diffusivities increase significantly at higher non-stoichiometry (x > 0.01) for di-interstitial clusters compared to a mono-interstitial only model. The diffusivities calculated at higher temperatures compare better with experimental values than at lower temperatures (< 973 K). We have discussed the resulting activation energies achieved for diffusion with all the mono- and di-interstitial models. We have carefully performed sensitivity analysis to estimate the effect of input di-interstitial binding energies on the predicted diffusivities and activation energies. While this article only discusses mono- and di-interstitials in evaluating oxygen diffusion response in UO2+x, future improvements to the model will primarily focus on including energetic definitions of larger stable interstitial clusters reported in the literature. The addition of larger clusters to the kMC model is expected to improve the comparison of oxygen transport in UO2+x with experiment.

MODELING AND ANALYSIS OF FISSION PRODUCT TRANSPORT IN THE AGR-3/4 EXPERIMENT

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

Humrickhouse, Paul W.; Collin, Blaise P.; Hawkes, Grant L.

In this work we describe the ongoing modeling and analysis efforts in support of the AGR-3/4 experiment. AGR-3/4 is intended to provide data to assess fission product retention and transport (e.g., diffusion coefficients) in fuel matrix and graphite materials. We describe a set of pre-test predictions that incorporate the results of detailed thermal and fission product release models into a coupled 1D radial diffusion model of the experiment, using diffusion coefficients reported in the literature for Ag, Cs, and Sr. We make some comparisons of the predicted Cs profiles to preliminary measured data for Cs and find these to bemore » reasonable, in most cases within an order of magnitude. Our ultimate objective is to refine the diffusion coefficients using AGR-3/4 data, so we identify an analytical method for doing so and demonstrate its efficacy via a series of numerical experiments using the model predictions. Finally, we discuss development of a post-irradiation examination plan informed by the modeling effort and simulate some of the heating tests that are tentatively planned.« less

Computing diffuse fraction of global horizontal solar radiation: A model comparison.

PubMed

Dervishi, Sokol; Mahdavi, Ardeshir

2012-06-01

For simulation-based prediction of buildings' energy use or expected gains from building-integrated solar energy systems, information on both direct and diffuse component of solar radiation is necessary. Available measured data are, however, typically restricted to global horizontal irradiance. There have been thus many efforts in the past to develop algorithms for the derivation of the diffuse fraction of solar irradiance. In this context, the present paper compares eight models for estimating diffuse fraction of irradiance based on a database of measured irradiance from Vienna, Austria. These models generally involve mathematical formulations with multiple coefficients whose values are typically valid for a specific location. Subsequent to a first comparison of these eight models, three better performing models were selected for a more detailed analysis. Thereby, the coefficients of the models were modified to account for Vienna data. The results suggest that some models can provide relatively reliable estimations of the diffuse fractions of the global irradiance. The calibration procedure could only slightly improve the models' performance.

Risk Assessment of Alzheimer's Disease using the Information Diffusion Model from Structural Magnetic Resonance Imaging.

PubMed

Beheshti, Iman; Olya, Hossain G T; Demirel, Hasan

2016-04-05

Recently, automatic risk assessment methods have been a target for the detection of Alzheimer's disease (AD) risk. This study aims to develop an automatic computer-aided AD diagnosis technique for risk assessment of AD using information diffusion theory. Information diffusion is a fuzzy mathematics logic of set-value that is used for risk assessment of natural phenomena, which attaches fuzziness (uncertainty) and incompleteness. Data were obtained from voxel-based morphometry analysis of structural magnetic resonance imaging. The information diffusion model results revealed that the risk of AD increases with a reduction of the normalized gray matter ratio (p > 0.5, normalized gray matter ratio <40%). The information diffusion model results were evaluated by calculation of the correlation of two traditional risk assessments of AD, the Mini-Mental State Examination and the Clinical Dementia Rating. The correlation results revealed that the information diffusion model findings were in line with Mini-Mental State Examination and Clinical Dementia Rating results. Application of information diffusion model contributes to the computerization of risk assessment of AD, which has a practical implication for the early detection of AD.

Analysis of Critical Mass in Threshold Model of Diffusion

NASA Astrophysics Data System (ADS)

Kim, Jeehong; Hur, Wonchang; Kang, Suk-Ho

2012-04-01

Why does diffusion sometimes show cascade phenomena but at other times is impeded? In addressing this question, we considered a threshold model of diffusion, focusing on the formation of a critical mass, which enables diffusion to be self-sustaining. Performing an agent-based simulation, we found that the diffusion model produces only two outcomes: Almost perfect adoption or relatively few adoptions. In order to explain the difference, we considered the various properties of network structures and found that the manner in which thresholds are arrayed over a network is the most critical factor determining the size of a cascade. On the basis of the results, we derived a threshold arrangement method effective for generation of a critical mass and calculated the size required for perfect adoption.

Modeling of Diffuse Photometric Signatures of Satellites for Space Object Identification.

DTIC Science & Technology

1982-12-01

to provide the groundwork for devel- opment of a computer program which could serve as an aid to tactical space object identification and analysis ...I Photometric Analysis Capability at the ADIC. . . . . .. 2 Operational Limitations of the Photometric Data Analysis Module (PDA...7 PDAM Diffuse Analysis . . . . . . . . . . . . . . . . . 7 Real World SOI Requirements vs POAN Capabilities . . . . 16 Statement of the Problem

Quantum Transmission Conditions for Diffusive Transport in Graphene with Steep Potentials

NASA Astrophysics Data System (ADS)

Barletti, Luigi; Negulescu, Claudia

2018-05-01

We present a formal derivation of a drift-diffusion model for stationary electron transport in graphene, in presence of sharp potential profiles, such as barriers and steps. Assuming the electric potential to have steep variations within a strip of vanishing width on a macroscopic scale, such strip is viewed as a quantum interface that couples the classical regions at its left and right sides. In the two classical regions, where the potential is assumed to be smooth, electron and hole transport is described in terms of semiclassical kinetic equations. The diffusive limit of the kinetic model is derived by means of a Hilbert expansion and a boundary layer analysis, and consists of drift-diffusion equations in the classical regions, coupled by quantum diffusive transmission conditions through the interface. The boundary layer analysis leads to the discussion of a four-fold Milne (half-space, half-range) transport problem.

Macro and micro analysis of small molecule diffusion in amorphous polymers

NASA Astrophysics Data System (ADS)

Putta, Santosh Krishna

In this study, both macroscopic and microscopic numerical techniques have been explored, to model and understand the diffusion behavior of small molecules in amorphous polymers, which very often do not follow the classical Fickian law. It was attempted to understand the influence of various aspects of the molecular structure of a polymer on its macroscopic diffusion behavior. At the macroscopic level, a hybrid finite-element/finite-difference model is developed to implement the coupled diffusion and deformation constitutive equations. A viscoelasticity theory, combined with time-freevolume superposition is used to model the deformation processes. A freevolume-based model is used to model the diffusion processes. The freevolume in the polymer is used as a coupling factor between the deformation and the diffusion processes. The model is shown to qualitatively describe some of the typical non-Fickian diffusion behavior in polymers. However, it does not directly involve the microstructure of a polymer. Further, some of the input parameters to the model are difficult to obtain experimentally. A numerical microscopic approach is therefore adopted to study the molecular structure of polymers. A molecular mechanics and dynamics technique combined with a modified Rotational Isomeric State (RIS) approach, is followed to generate the molecular structure for two types of polycarbonates, and, two types of polyacrylates, starting only with their chemical structures. A new efficient 3-D algorithm for Delaunay Tessellation is developed, and, then applied to discretize the molecular structure into Delaunay Tetrahedra. By using the dicretized molecular structure, size, shape, and, connectivity of free-spaces for small molecule diffusion in the above mentioned polymers, are then studied in relation to their diffusion properties. The influence of polymer and side chain flexibility, and diffusant-diffusant and diffusant-polymer molecular interactions, is also discussed with respect to the diffusion properties.

A time fractional convection-diffusion equation to model gas transport through heterogeneous soil and gas reservoirs

NASA Astrophysics Data System (ADS)

Chang, Ailian; Sun, HongGuang; Zheng, Chunmiao; Lu, Bingqing; Lu, Chengpeng; Ma, Rui; Zhang, Yong

2018-07-01

Fractional-derivative models have been developed recently to interpret various hydrologic dynamics, such as dissolved contaminant transport in groundwater. However, they have not been applied to quantify other fluid dynamics, such as gas transport through complex geological media. This study reviewed previous gas transport experiments conducted in laboratory columns and real-world oil-gas reservoirs and found that gas dynamics exhibit typical sub-diffusive behavior characterized by heavy late-time tailing in the gas breakthrough curves (BTCs), which cannot be effectively captured by classical transport models. Numerical tests and field applications of the time fractional convection-diffusion equation (fCDE) have shown that the fCDE model can capture the observed gas BTCs including their apparent positive skewness. Sensitivity analysis further revealed that the three parameters used in the fCDE model, including the time index, the convection velocity, and the diffusion coefficient, play different roles in interpreting the delayed gas transport dynamics. In addition, the model comparison and analysis showed that the time fCDE model is efficient in application. Therefore, the time fractional-derivative models can be conveniently extended to quantify gas transport through natural geological media such as complex oil-gas reservoirs.

Analysis of Molecular Diffusion by First-Passage Time Variance Identifies the Size of Confinement Zones

PubMed Central

Rajani, Vishaal; Carrero, Gustavo; Golan, David E.; de Vries, Gerda; Cairo, Christopher W.

2011-01-01

The diffusion of receptors within the two-dimensional environment of the plasma membrane is a complex process. Although certain components diffuse according to a random walk model (Brownian diffusion), an overwhelming body of work has found that membrane diffusion is nonideal (anomalous diffusion). One of the most powerful methods for studying membrane diffusion is single particle tracking (SPT), which records the trajectory of a label attached to a membrane component of interest. One of the outstanding problems in SPT is the analysis of data to identify the presence of heterogeneity. We have adapted a first-passage time (FPT) algorithm, originally developed for the interpretation of animal movement, for the analysis of SPT data. We discuss the general application of the FPT analysis to molecular diffusion, and use simulations to test the method against data containing known regions of confinement. We conclude that FPT can be used to identify the presence and size of confinement within trajectories of the receptor LFA-1, and these results are consistent with previous reports on the size of LFA-1 clusters. The analysis of trajectory data for cell surface receptors by FPT provides a robust method to determine the presence and size of confined regions of diffusion. PMID:21402028

Preliminary study: Moisture-polymer interaction. Stuby objectives

NASA Technical Reports Server (NTRS)

Wen, L. C.

1985-01-01

The problems associated with mathematically modeling water-module interaction phenomena, including sorption and desorption, diffusion, and permeation are discussed. With reliable analytical models, an extensive materials data base, and solar radiation surface meteorological observations (SOLMET) weather data, predicting module lifetimes in realistic environments can become a practical reality. The status of the present techniques of simulating the various transport mechanisms was reported. The Dent model (a modified Brunauer-Emmet-Teller) approach represented polyvinyl butyral (PVB) sorption data. A 100-layer material model and Fick's diffusion model gave diffusivity values exhibiting adequate agreement with those measured for PVB. Diffusivity of PVB is concentration dependent, decreasing as the water content in PVB increases. The temperature dependence of diffusion in PVB is well modeled by the Arrhenius rate equation. Equilibrium conductivity and leakage current data are well represented by Hearle's model for bulk ionic conductivity. A nodal network analysis using the Systems Improved Numerical Differencing Analyzer (SINDA) Thermal Analyzer gave reasonable correlation with measurable data. It is concluded that realistic lifetime predictions seem to be feasible.

Soliton solutions, stability analysis and conservation laws for the brusselator reaction diffusion model with time- and constant-dependent coefficients

NASA Astrophysics Data System (ADS)

Inc, Mustafa; Yusuf, Abdullahi; Isa Aliyu, Aliyu; Hashemi, M. S.

2018-05-01

This paper studies the brusselator reaction diffusion model (BRDM) with time- and constant-dependent coefficients. The soliton solutions for BRDM with time-dependent coefficients are obtained via first integral (FIM), ansatz, and sine-Gordon expansion (SGEM) methods. Moreover, it is well known that stability analysis (SA), symmetry analysis and conservation laws (CLs) give several information for modelling a system of differential equations (SDE). This is because they can be used for investigating the internal properties, existence, uniqueness and integrability of different SDE. For this reason, we investigate the SA via linear stability technique, symmetry analysis and CLs for BRDM with constant-dependent coefficients in order to extract more physics and information on the governing equation. The constraint conditions for the existence of the solutions are also examined. The new solutions obtained in this paper can be useful for describing the concentrations of diffusion problems of the BRDM. It is shown that the examined dependent coefficients are some of the factors that are affecting the diffusion rate. So, the present paper provides much motivational information in comparison to the existing results in the literature.

Fluctuation correlation models for receptor immobilization

NASA Astrophysics Data System (ADS)

Fourcade, B.

2017-12-01

Nanoscale dynamics with cycles of receptor diffusion and immobilization by cell-external-or-internal factors is a key process in living cell adhesion phenomena at the origin of a plethora of signal transduction pathways. Motivated by modern correlation microscopy approaches, the receptor correlation functions in physical models based on diffusion-influenced reaction is studied. Using analytical and stochastic modeling, this paper focuses on the hybrid regime where diffusion and reaction are not truly separable. The time receptor autocorrelation functions are shown to be indexed by different time scales and their asymptotic expansions are given. Stochastic simulations show that this analysis can be extended to situations with a small number of molecules. It is also demonstrated that this analysis applies when receptor immobilization is coupled to environmental noise.

Data-driven analysis for the temperature and momentum dependence of the heavy-quark diffusion coefficient in relativistic heavy-ion collisions

NASA Astrophysics Data System (ADS)

Xu, Yingru; Bernhard, Jonah E.; Bass, Steffen A.; Nahrgang, Marlene; Cao, Shanshan

2018-01-01

By applying a Bayesian model-to-data analysis, we estimate the temperature and momentum dependence of the heavy quark diffusion coefficient in an improved Langevin framework. The posterior range of the diffusion coefficient is obtained by performing a Markov chain Monte Carlo random walk and calibrating on the experimental data of D -meson RAA and v2 in three different collision systems at the Relativistic Heavy-Ion Collidaer (RHIC) and the Large Hadron Collider (LHC): Au-Au collisions at 200 GeV and Pb-Pb collisions at 2.76 and 5.02 TeV. The spatial diffusion coefficient is found to be consistent with lattice QCD calculations and comparable with other models' estimation. We demonstrate the capability of our improved Langevin model to simultaneously describe the RAA and v2 at both RHIC and the LHC energies, as well as the higher order flow coefficient such as D meson v3. We show that by applying a Bayesian analysis, we are able to quantitatively and systematically study the heavy flavor dynamics in heavy-ion collisions.

Numerical analysis for the fractional diffusion and fractional Buckmaster equation by the two-step Laplace Adam-Bashforth method

NASA Astrophysics Data System (ADS)

Jain, Sonal

2018-01-01

In this paper, we aim to use the alternative numerical scheme given by Gnitchogna and Atangana for solving partial differential equations with integer and non-integer differential operators. We applied this method to fractional diffusion model and fractional Buckmaster models with non-local fading memory. The method yields a powerful numerical algorithm for fractional order derivative to implement. Also we present in detail the stability analysis of the numerical method for solving the diffusion equation. This proof shows that this method is very stable and also converges very quickly to exact solution and finally some numerical simulation is presented.

Long-time behavior and Turing instability induced by cross-diffusion in a three species food chain model with a Holling type-II functional response.

PubMed

Haile, Dawit; Xie, Zhifu

2015-09-01

In this paper, we study a strongly coupled reaction-diffusion system describing three interacting species in a food chain model, where the third species preys on the second one and simultaneously the second species preys on the first one. An intra-species competition b2 among the second predator is introduced to the food chain model. This parameter produces some very interesting result in linear stability and Turing instability. We first show that the unique positive equilibrium solution is locally asymptotically stable for the corresponding ODE system when the intra-species competition exists among the second predator. The positive equilibrium solution remains linearly stable for the reaction diffusion system without cross diffusion, hence it does not belong to the classical Turing instability scheme. But it becomes linearly unstable only when cross-diffusion also plays a role in the reaction-diffusion system, hence the instability is driven solely from the effect of cross diffusion. Our results also exhibit some interesting combining effects of cross-diffusion, intra-species competitions and inter-species interactions. Numerically, we conduct a one parameter analysis which illustrate how the interactions change the existence of stable equilibrium, limit cycle, and chaos. Some interesting dynamical phenomena occur when we perform analysis of interactions in terms of self-production of prey and intra-species competition of the middle predator. By numerical simulations, it illustrates the existence of nonuniform steady solutions and new patterns such as spot patterns, strip patterns and fluctuations due to the diffusion and cross diffusion in two-dimension. Published by Elsevier Inc.

Modeling Morphogenesis with Reaction-Diffusion Equations Using Galerkin Spectral Methods

DTIC Science & Technology

2002-05-06

reaction- diffusion equation is a difficult problem in analysis that will not be addressed here. Errors will also arise from numerically approx solutions to...the ODEs. When comparing the approximate solution to actual reaction- diffusion systems found in nature, we must also take into account errors that...

Effects of sorption competition on caesium diffusion through compacted argillaceous rock

NASA Astrophysics Data System (ADS)

Jakob, Andreas; Pfingsten, Wilfried; Van Loon, Luc

2009-05-01

We carried out a small-scale laboratory diffusion experiment on a disk-like sample of Opalinus clay from the Mont Terri underground laboratory (Switzerland) using 134Cs as tracer. A through-diffusion phase was followed by an out-diffusion phase where the tracer taken up by the sample was released again. Since the tracer concentration at both boundaries was monitored, careful mass-balance considerations were feasible. A first analysis of the experimental data was done in the frame of a single-species model accounting only for transport and non-linear sorption of caesium. The model could match the data of the through-diffusion phase, however only, when strongly reducing the sorption data based on batch sorption experiments. Yet, such a procedure was in strong contradiction with sorption measurements performed on dispersed and compacted systems. In addition, predictions concerning tracer out-diffusion and mass-balance considerations clearly revealed the shortcomings of this type of model. In a second attempt we applied a multi-species transport model where now the whole water chemistry and a sorption model for caesium were considered. First, the value for the diffusion coefficient was fixed to the best-fit value of the single-species model. But again, the sorption site densities had to be reduced strongly albeit the reduction factor was smaller. Only when fixing the sorption site densities to those values of the sorption model and letting the effective diffusion coefficient D e free for the adjustment, could through-diffusion data be reasonably well fitted and out-diffusion as well as mass-balances be predicted in a satisfying manner. The main results are: (1) The best-fit could be achieved with a value for D e of 1.8 × 10 -10 m 2 s -1 which is rather high but corroborated by results of a molecular modelling study. (2) If caesium arrives in the Opalinus clay sample potassium and sodium (calcium etc.) ions are released and caesium ions are sorbed. The released cations diffuse to lower concentration regions according to their individual concentration gradients. Since locally the cation concentration for potassium, (sodium and calcium) is increased, sorption of these cations is also locally enhanced, affecting in return the sorption behaviour of migrating caesium. Consequently, the sorption process of caesium in such diffusion experiments cannot be addressed by a non-linear isotherm formalism any longer. (3) A reasonable analysis of such single tracer diffusion experiments therefore requires the combined description of transport (diffusion) and sorption of many cations and the whole complex water chemistry of the system. Thus, single-species models can only be applied with care in the considered concentration ranges.

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

Relativistic analysis of stochastic kinematics

NASA Astrophysics Data System (ADS)

Giona, Massimiliano

2017-10-01

The relativistic analysis of stochastic kinematics is developed in order to determine the transformation of the effective diffusivity tensor in inertial frames. Poisson-Kac stochastic processes are initially considered. For one-dimensional spatial models, the effective diffusion coefficient measured in a frame Σ moving with velocity w with respect to the rest frame of the stochastic process is inversely proportional to the third power of the Lorentz factor γ (w ) =(1-w2/c2) -1 /2 . Subsequently, higher-dimensional processes are analyzed and it is shown that the diffusivity tensor in a moving frame becomes nonisotropic: The diffusivities parallel and orthogonal to the velocity of the moving frame scale differently with respect to γ (w ) . The analysis of discrete space-time diffusion processes permits one to obtain a general transformation theory of the tensor diffusivity, confirmed by several different simulation experiments. Several implications of the theory are also addressed and discussed.

Modeling and Uncertainty Quantification of Vapor Sorption and Diffusion in Heterogeneous Polymers

DOE PAGES

Sun, Yunwei; Harley, Stephen J.; Glascoe, Elizabeth A.

2015-08-13

A high-fidelity model of kinetic and equilibrium sorption and diffusion is developed and exercised. The gas-diffusion model is coupled with a triple-sorption mechanism: Henry’s law absorption, Langmuir adsorption, and pooling or clustering of molecules at higher partial pressures. Sorption experiments are conducted and span a range of relative humidities (0-95%) and temperatures (30-60°C). Kinetic and equilibrium sorption properties and effective diffusivity are determined by minimizing the absolute difference between measured and modeled uptakes. Uncertainty quantification and sensitivity analysis methods are described and exercised herein to demonstrate the capability of this modeling approach. Water uptake in silica-filled and unfilled poly(dimethylsiloxane) networksmore » is investigated; however, the model is versatile enough to be used with a wide range of materials and vapors.« less

Diffusive flux in a model of stochastically gated oxygen transport in insect respiration

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

Berezhkovskii, Alexander M.; Shvartsman, Stanislav Y.

Oxygen delivery to insect tissues is controlled by transport through a branched tubular network that is connected to the atmosphere by valve-like gates, known as spiracles. In certain physiological regimes, the spiracles appear to be randomly switching between open and closed states. Quantitative analysis of this regime leads a reaction-diffusion problem with stochastically switching boundary condition. We derive an expression for the diffusive flux at long times in this problem. Our approach starts with the derivation of the passage probability for a single particle that diffuses between a stochastically gated boundary, which models the opening and closing spiracle, and themore » perfectly absorbing boundary, which models oxygen absorption by the tissue. This passage probability is then used to derive an expression giving the diffusive flux as a function of the geometric parameters of the tube and characteristic time scales of diffusion and gate dynamics.« less

Diffusive flux in a model of stochastically gated oxygen transport in insect respiration.

PubMed

Berezhkovskii, Alexander M; Shvartsman, Stanislav Y

2016-05-28

Oxygen delivery to insect tissues is controlled by transport through a branched tubular network that is connected to the atmosphere by valve-like gates, known as spiracles. In certain physiological regimes, the spiracles appear to be randomly switching between open and closed states. Quantitative analysis of this regime leads a reaction-diffusion problem with stochastically switching boundary condition. We derive an expression for the diffusive flux at long times in this problem. Our approach starts with the derivation of the passage probability for a single particle that diffuses between a stochastically gated boundary, which models the opening and closing spiracle, and the perfectly absorbing boundary, which models oxygen absorption by the tissue. This passage probability is then used to derive an expression giving the diffusive flux as a function of the geometric parameters of the tube and characteristic time scales of diffusion and gate dynamics.

A Nonlinear Diffusion Equation-Based Model for Ultrasound Speckle Noise Removal

NASA Astrophysics Data System (ADS)

Zhou, Zhenyu; Guo, Zhichang; Zhang, Dazhi; Wu, Boying

2018-04-01

Ultrasound images are contaminated by speckle noise, which brings difficulties in further image analysis and clinical diagnosis. In this paper, we address this problem in the view of nonlinear diffusion equation theories. We develop a nonlinear diffusion equation-based model by taking into account not only the gradient information of the image, but also the information of the gray levels of the image. By utilizing the region indicator as the variable exponent, we can adaptively control the diffusion type which alternates between the Perona-Malik diffusion and the Charbonnier diffusion according to the image gray levels. Furthermore, we analyze the proposed model with respect to the theoretical and numerical properties. Experiments show that the proposed method achieves much better speckle suppression and edge preservation when compared with the traditional despeckling methods, especially in the low gray level and low-contrast regions.

Determination of Diffusion Coefficients in Cement-Based Materials: An Inverse Problem for the Nernst-Planck and Poisson Models

NASA Astrophysics Data System (ADS)

Szyszkiewicz-Warzecha, Krzysztof; Jasielec, Jerzy J.; Fausek, Janusz; Filipek, Robert

2016-08-01

Transport properties of ions have significant impact on the possibility of rebars corrosion thus the knowledge of a diffusion coefficient is important for reinforced concrete durability. Numerous tests for the determination of diffusion coefficients have been proposed but analysis of some of these tests show that they are too simplistic or even not valid. Hence, more rigorous models to calculate the coefficients should be employed. Here we propose the Nernst-Planck and Poisson equations, which take into account the concentration and electric potential field. Based on this model a special inverse method is presented for determination of a chloride diffusion coefficient. It requires the measurement of concentration profiles or flux on the boundary and solution of the NPP model to define the goal function. Finding the global minimum is equivalent to the determination of diffusion coefficients. Typical examples of the application of the presented method are given.

TrackArt: the user friendly interface for single molecule tracking data analysis and simulation applied to complex diffusion in mica supported lipid bilayers.

PubMed

Matysik, Artur; Kraut, Rachel S

2014-05-01

Single molecule tracking (SMT) analysis of fluorescently tagged lipid and protein probes is an attractive alternative to ensemble averaged methods such as fluorescence correlation spectroscopy (FCS) or fluorescence recovery after photobleaching (FRAP) for measuring diffusion in artificial and plasma membranes. The meaningful estimation of diffusion coefficients and their errors is however not straightforward, and is heavily dependent on sample type, acquisition method, and equipment used. Many approaches require advanced computing and programming skills for their implementation. Here we present TrackArt software, an accessible graphic interface for simulation and complex analysis of multiple particle paths. Imported trajectories can be filtered to eliminate spurious or corrupted tracks, and are then analyzed using several previously described methodologies, to yield single or multiple diffusion coefficients, their population fractions, and estimated errors. We use TrackArt to analyze the single-molecule diffusion behavior of a sphingolipid analog SM-Atto647N, in mica supported DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine) bilayers. Fitting with a two-component diffusion model confirms the existence of two separate populations of diffusing particles in these bilayers on mica. As a demonstration of the TrackArt workflow, we characterize and discuss the effective activation energies required to increase the diffusion rates of these populations, obtained from Arrhenius plots of temperature-dependent diffusion. Finally, TrackArt provides a simulation module, allowing the user to generate models with multiple particle trajectories, diffusing with different characteristics. Maps of domains, acting as impermeable or permeable obstacles for particles diffusing with given rate constants and diffusion coefficients, can be simulated or imported from an image. Importantly, this allows one to use simulated data with a known diffusion behavior as a comparison for results acquired using particular algorithms on actual, "natural" samples whose diffusion behavior is to be extracted. It can also serve as a tool for demonstrating diffusion principles. TrackArt is an open source, platform-independent, Matlab-based graphical user interface, and is easy to use even for those unfamiliar with the Matlab programming environment. TrackArt can be used for accurate simulation and analysis of complex diffusion data, such as diffusion in lipid bilayers, providing publication-quality formatted results.

A Bayesian hierarchical diffusion model decomposition of performance in Approach–Avoidance Tasks

PubMed Central

Krypotos, Angelos-Miltiadis; Beckers, Tom; Kindt, Merel; Wagenmakers, Eric-Jan

2015-01-01

Common methods for analysing response time (RT) tasks, frequently used across different disciplines of psychology, suffer from a number of limitations such as the failure to directly measure the underlying latent processes of interest and the inability to take into account the uncertainty associated with each individual's point estimate of performance. Here, we discuss a Bayesian hierarchical diffusion model and apply it to RT data. This model allows researchers to decompose performance into meaningful psychological processes and to account optimally for individual differences and commonalities, even with relatively sparse data. We highlight the advantages of the Bayesian hierarchical diffusion model decomposition by applying it to performance on Approach–Avoidance Tasks, widely used in the emotion and psychopathology literature. Model fits for two experimental data-sets demonstrate that the model performs well. The Bayesian hierarchical diffusion model overcomes important limitations of current analysis procedures and provides deeper insight in latent psychological processes of interest. PMID:25491372

Cross-stream diffusion under pressure-driven flow in microchannels with arbitrary aspect ratios: a phase diagram study using a three-dimensional analytical model

PubMed Central

Song, Hongjun; Wang, Yi; Pant, Kapil

2011-01-01

This article presents a three-dimensional analytical model to investigate cross-stream diffusion transport in rectangular microchannels with arbitrary aspect ratios under pressure-driven flow. The Fourier series solution to the three-dimensional convection–diffusion equation is obtained using a double integral transformation method and associated eigensystem calculation. A phase diagram derived from the dimensional analysis is presented to thoroughly interrogate the characteristics in various transport regimes and examine the validity of the model. The analytical model is verified against both experimental and numerical models in terms of the concentration profile, diffusion scaling law, and mixing efficiency with excellent agreement (with <0.5% relative error). Quantitative comparison against other prior analytical models in extensive parameter space is also performed, which demonstrates that the present model accommodates much broader transport regimes with significantly enhanced applicability. PMID:22247719

Cross-stream diffusion under pressure-driven flow in microchannels with arbitrary aspect ratios: a phase diagram study using a three-dimensional analytical model.

PubMed

Song, Hongjun; Wang, Yi; Pant, Kapil

2012-01-01

This article presents a three-dimensional analytical model to investigate cross-stream diffusion transport in rectangular microchannels with arbitrary aspect ratios under pressure-driven flow. The Fourier series solution to the three-dimensional convection-diffusion equation is obtained using a double integral transformation method and associated eigensystem calculation. A phase diagram derived from the dimensional analysis is presented to thoroughly interrogate the characteristics in various transport regimes and examine the validity of the model. The analytical model is verified against both experimental and numerical models in terms of the concentration profile, diffusion scaling law, and mixing efficiency with excellent agreement (with <0.5% relative error). Quantitative comparison against other prior analytical models in extensive parameter space is also performed, which demonstrates that the present model accommodates much broader transport regimes with significantly enhanced applicability.

Validation of drift and diffusion coefficients from experimental data

NASA Astrophysics Data System (ADS)

Riera, R.; Anteneodo, C.

2010-04-01

Many fluctuation phenomena, in physics and other fields, can be modeled by Fokker-Planck or stochastic differential equations whose coefficients, associated with drift and diffusion components, may be estimated directly from the observed time series. Its correct characterization is crucial to determine the system quantifiers. However, due to the finite sampling rates of real data, the empirical estimates may significantly differ from their true functional forms. In the literature, low-order corrections, or even no corrections, have been applied to the finite-time estimates. A frequent outcome consists of linear drift and quadratic diffusion coefficients. For this case, exact corrections have been recently found, from Itô-Taylor expansions. Nevertheless, model validation constitutes a necessary step before determining and applying the appropriate corrections. Here, we exploit the consequences of the exact theoretical results obtained for the linear-quadratic model. In particular, we discuss whether the observed finite-time estimates are actually a manifestation of that model. The relevance of this analysis is put into evidence by its application to two contrasting real data examples in which finite-time linear drift and quadratic diffusion coefficients are observed. In one case the linear-quadratic model is readily rejected while in the other, although the model constitutes a very good approximation, low-order corrections are inappropriate. These examples give warning signs about the proper interpretation of finite-time analysis even in more general diffusion processes.

Diffusion MRI and its role in neuropsychology

PubMed Central

Mueller, Bryon A; Lim, Kelvin O; Hemmy, Laura; Camchong, Jazmin

2015-01-01

Diffusion Magnetic Resonance Imaging (dMRI) is a popular method used by neuroscientists to uncover unique information about the structural connections within the brain. dMRI is a non-invasive imaging methodology in which image contrast is based on the diffusion of water molecules in tissue. While applicable to many tissues in the body, this review focuses exclusively on the use of dMRI to examine white matter in the brain. In this review, we begin with a definition of diffusion and how diffusion is measured with MRI. Next we introduce the diffusion tensor model, the predominant model used in dMRI. We then describe acquisition issues related to acquisition parameters and scanner hardware and software. Sources of artifacts are then discussed, followed by a brief review of analysis approaches. We provide an overview of the limitations of the traditional diffusion tensor model, and highlight several more sophisticated non-tensor models that better describe the complex architecture of the brain’s white matter. We then touch on reliability and validity issues of diffusion measurements. Finally, we describe examples of ways in which dMRI has been applied to studies of brain disorders and how identified alterations relate to symptomatology and cognition. PMID:26255305

The Analytical Limits of Modeling Short Diffusion Timescales

NASA Astrophysics Data System (ADS)

Bradshaw, R. W.; Kent, A. J.

2016-12-01

Chemical and isotopic zoning in minerals is widely used to constrain the timescales of magmatic processes such as magma mixing and crystal residence, etc. via diffusion modeling. Forward modeling of diffusion relies on fitting diffusion profiles to measured compositional gradients. However, an individual measurement is essentially an average composition for a segment of the gradient defined by the spatial resolution of the analysis. Thus there is the potential for the analytical spatial resolution to limit the timescales that can be determined for an element of given diffusivity, particularly where the scale of the gradient approaches that of the measurement. Here we use a probabilistic modeling approach to investigate the effect of analytical spatial resolution on estimated timescales from diffusion modeling. Our method investigates how accurately the age of a synthetic diffusion profile can be obtained by modeling an "unknown" profile derived from discrete sampling of the synthetic compositional gradient at a given spatial resolution. We also include the effects of analytical uncertainty and the position of measurements relative to the diffusion gradient. We apply this method to the spatial resolutions of common microanalytical techniques (LA-ICP-MS, SIMS, EMP, NanoSIMS). Our results confirm that for a given diffusivity, higher spatial resolution gives access to shorter timescales, and that each analytical spacing has a minimum timescale, below which it overestimates the timescale. For example, for Ba diffusion in plagioclase at 750 °C timescales are accurate (within 20%) above 10, 100, 2,600, and 71,000 years at 0.3, 1, 5, and 25 mm spatial resolution, respectively. For Sr diffusion in plagioclase at 750 °C, timescales are accurate above 0.02, 0.2, 4, and 120 years at the same spatial resolutions. Our results highlight the importance of selecting appropriate analytical techniques to estimate accurate diffusion-based timescales.

Multispecies lottery competition: a diffusion analysis

USGS Publications Warehouse

Hatfield, J.S.; Chesson, P.L.; Tuljapurkar, S.; Caswell, H.

1997-01-01

The lottery model is a stochastic competition model designed for space-limited communities of sedentary organisms. Examples of such communities include coral reef fishes, aquatic sessile organisms, and many plant communities. Explicit conditions for the coexistence of two species and the stationary distribution of the two-species model were determined previously using an approximation with a diffusion process. In this chapter, a diffusion approximation is presented for the multispecies model for communities of two or more species, and a stage-structured model is investigated. The stage-structured model would be more reasonable for communities of long-lived species such as trees in a forest in which recruitment and death rates depend on the age or stage of the individuals.

The mechanistic basis of internal conductance: a theoretical analysis of mesophyll cell photosynthesis and CO2 diffusion.

PubMed

Tholen, Danny; Zhu, Xin-Guang

2011-05-01

Photosynthesis is limited by the conductance of carbon dioxide (CO(2)) from intercellular spaces to the sites of carboxylation. Although the concept of internal conductance (g(i)) has been known for over 50 years, shortcomings in the theoretical description of this process may have resulted in a limited understanding of the underlying mechanisms. To tackle this issue, we developed a three-dimensional reaction-diffusion model of photosynthesis in a typical C(3) mesophyll cell that includes all major components of the CO(2) diffusion pathway and associated reactions. Using this novel systems model, we systematically and quantitatively examined the mechanisms underlying g(i). Our results identify the resistances of the cell wall and chloroplast envelope as the most significant limitations to photosynthesis. In addition, the concentration of carbonic anhydrase in the stroma may also be limiting for the photosynthetic rate. Our analysis demonstrated that higher levels of photorespiration increase the apparent resistance to CO(2) diffusion, an effect that has thus far been ignored when determining g(i). Finally, we show that outward bicarbonate leakage through the chloroplast envelope could contribute to the observed decrease in g(i) under elevated CO(2). Our analysis suggests that physiological and anatomical features associated with g(i) have been evolutionarily fine-tuned to benefit CO(2) diffusion and photosynthesis. The model presented here provides a novel theoretical framework to further analyze the mechanisms underlying diffusion processes in the mesophyll.

The Mechanistic Basis of Internal Conductance: A Theoretical Analysis of Mesophyll Cell Photosynthesis and CO2 Diffusion1[W][OA

PubMed Central

Tholen, Danny; Zhu, Xin-Guang

2011-01-01

Photosynthesis is limited by the conductance of carbon dioxide (CO2) from intercellular spaces to the sites of carboxylation. Although the concept of internal conductance (gi) has been known for over 50 years, shortcomings in the theoretical description of this process may have resulted in a limited understanding of the underlying mechanisms. To tackle this issue, we developed a three-dimensional reaction-diffusion model of photosynthesis in a typical C3 mesophyll cell that includes all major components of the CO2 diffusion pathway and associated reactions. Using this novel systems model, we systematically and quantitatively examined the mechanisms underlying gi. Our results identify the resistances of the cell wall and chloroplast envelope as the most significant limitations to photosynthesis. In addition, the concentration of carbonic anhydrase in the stroma may also be limiting for the photosynthetic rate. Our analysis demonstrated that higher levels of photorespiration increase the apparent resistance to CO2 diffusion, an effect that has thus far been ignored when determining gi. Finally, we show that outward bicarbonate leakage through the chloroplast envelope could contribute to the observed decrease in gi under elevated CO2. Our analysis suggests that physiological and anatomical features associated with gi have been evolutionarily fine-tuned to benefit CO2 diffusion and photosynthesis. The model presented here provides a novel theoretical framework to further analyze the mechanisms underlying diffusion processes in the mesophyll. PMID:21441385

Tensor Based Representation and Analysis of Diffusion-Weighted Magnetic Resonance Images

ERIC Educational Resources Information Center

Barmpoutis, Angelos

2009-01-01

Cartesian tensor bases have been widely used to model spherical functions. In medical imaging, tensors of various orders can approximate the diffusivity function at each voxel of a diffusion-weighted MRI data set. This approximation produces tensor-valued datasets that contain information about the underlying local structure of the scanned tissue.…

Arrhenius analysis of anisotropic surface self-diffusion on the prismatic facet of ice.

PubMed

Gladich, Ivan; Pfalzgraff, William; Maršálek, Ondřej; Jungwirth, Pavel; Roeselová, Martina; Neshyba, Steven

2011-11-28

We present an Arrhenius analysis of self-diffusion on the prismatic surface of ice calculated from molecular dynamics simulations. The six-site water model of Nada and van der Eerden was used in combination with a structure-based criterion for determining the number of liquid-like molecules in the quasi-liquid layer. Simulated temperatures range from 230 K-287 K, the latter being just below the melting temperature of the model, 289 K. Calculated surface diffusion coefficients agree with available experimental data to within quoted precision. Our results indicate a positive Arrhenius curvature, implying a change in the mechanism of self-diffusion from low to high temperature, with a concomitant increase in energy of activation from 29.1 kJ mol(-1) at low temperature to 53.8 kJ mol(-1) close to the melting point. In addition, we find that the surface self-diffusion is anisotropic at lower temperatures, transitioning to isotropic in the temperature range of 240-250 K. We also present a framework for self-diffusion in the quasi-liquid layer on ice that aims to explain these observations.

Cross-Diffusion Induced Turing Instability and Amplitude Equation for a Toxic-Phytoplankton-Zooplankton Model with Nonmonotonic Functional Response

NASA Astrophysics Data System (ADS)

Han, Renji; Dai, Binxiang

2017-06-01

The spatiotemporal pattern induced by cross-diffusion of a toxic-phytoplankton-zooplankton model with nonmonotonic functional response is investigated in this paper. The linear stability analysis shows that cross-diffusion is the key mechanism for the formation of spatial patterns. By taking cross-diffusion rate as bifurcation parameter, we derive amplitude equations near the Turing bifurcation point for the excited modes in the framework of a weakly nonlinear theory, and the stability analysis of the amplitude equations interprets the structural transitions and stability of various forms of Turing patterns. Furthermore, we illustrate the theoretical results via numerical simulations. It is shown that the spatiotemporal distribution of the plankton is homogeneous in the absence of cross-diffusion. However, when the cross-diffusivity is greater than the critical value, the spatiotemporal distribution of all the plankton species becomes inhomogeneous in spaces and results in different kinds of patterns: spot, stripe, and the mixture of spot and stripe patterns depending on the cross-diffusivity. Simultaneously, the impact of toxin-producing rate of toxic-phytoplankton (TPP) species and natural death rate of zooplankton species on pattern selection is also explored.

Optical measurement of transverse molecular diffusion in a microchannel.

PubMed Central

Kamholz, A E; Schilling, E A; Yager, P

2001-01-01

Quantitative analysis of molecular diffusion is a necessity for the efficient design of most microfluidic devices as well as an important biophysical method in its own right. This study demonstrates the rapid measurement of diffusion coefficients of large and small molecules in a microfluidic device, the T-sensor, by means of conventional epifluorescence microscopy. Data were collected by monitoring the transverse flux of analyte from a sample stream into a second stream flowing alongside it. As indicated by the low Reynolds numbers of the system (< 1), flow is laminar, and molecular transport between streams occurs only by diffusion. Quantitative determinations were made by fitting data with predictions of a one-dimensional model. Analysis was made of the flow development and its effect on the distribution of diffusing analyte using a three-dimensional modeling software package. Diffusion coefficients were measured for four fluorescently labeled molecules: fluorescein-biotin, insulin, ovalbumin, and streptavidin. The resulting values differed from accepted results by an average of 2.4%. Microfluidic system parameters can be selected to achieve accurate diffusion coefficient measurements and to optimize other microfluidic devices that rely on precise transverse transport of molecules. PMID:11259309

INFLUENCES OF DIFFUSION AND ADVECTIVE FLOW ON THE DISTRIBUTION OF RADON ACTIVITY WITHIN U.S. EPA'S SOIL CHAMBER

EPA Science Inventory

The paper presents an analysis of steady-state diffusion in the soil for two different conditions of moisture. The model accounts for multiphase emanation and transport. When the position dependence of the moisture profile is taken into account, the model and measurements agree w...

Specifying Theories of Developmental Dyslexia: A Diffusion Model Analysis of Word Recognition

ERIC Educational Resources Information Center

Zeguers, Maaike H. T.; Snellings, Patrick; Tijms, Jurgen; Weeda, Wouter D.; Tamboer, Peter; Bexkens, Anika; Huizenga, Hilde M.

2011-01-01

The nature of word recognition difficulties in developmental dyslexia is still a topic of controversy. We investigated the contribution of phonological processing deficits and uncertainty to the word recognition difficulties of dyslexic children by mathematical diffusion modeling of visual and auditory lexical decision data. The first study showed…

Variational Implicit Solvation with Solute Molecular Mechanics: From Diffuse-Interface to Sharp-Interface Models.

PubMed

Li, Bo; Zhao, Yanxiang

2013-01-01

Central in a variational implicit-solvent description of biomolecular solvation is an effective free-energy functional of the solute atomic positions and the solute-solvent interface (i.e., the dielectric boundary). The free-energy functional couples together the solute molecular mechanical interaction energy, the solute-solvent interfacial energy, the solute-solvent van der Waals interaction energy, and the electrostatic energy. In recent years, the sharp-interface version of the variational implicit-solvent model has been developed and used for numerical computations of molecular solvation. In this work, we propose a diffuse-interface version of the variational implicit-solvent model with solute molecular mechanics. We also analyze both the sharp-interface and diffuse-interface models. We prove the existence of free-energy minimizers and obtain their bounds. We also prove the convergence of the diffuse-interface model to the sharp-interface model in the sense of Γ-convergence. We further discuss properties of sharp-interface free-energy minimizers, the boundary conditions and the coupling of the Poisson-Boltzmann equation in the diffuse-interface model, and the convergence of forces from diffuse-interface to sharp-interface descriptions. Our analysis relies on the previous works on the problem of minimizing surface areas and on our observations on the coupling between solute molecular mechanical interactions with the continuum solvent. Our studies justify rigorously the self consistency of the proposed diffuse-interface variational models of implicit solvation.

Lattice Boltzmann scheme for mixture modeling: analysis of the continuum diffusion regimes recovering Maxwell-Stefan model and incompressible Navier-Stokes equations.

PubMed

Asinari, Pietro

2009-11-01

A finite difference lattice Boltzmann scheme for homogeneous mixture modeling, which recovers Maxwell-Stefan diffusion model in the continuum limit, without the restriction of the mixture-averaged diffusion approximation, was recently proposed [P. Asinari, Phys. Rev. E 77, 056706 (2008)]. The theoretical basis is the Bhatnagar-Gross-Krook-type kinetic model for gas mixtures [P. Andries, K. Aoki, and B. Perthame, J. Stat. Phys. 106, 993 (2002)]. In the present paper, the recovered macroscopic equations in the continuum limit are systematically investigated by varying the ratio between the characteristic diffusion speed and the characteristic barycentric speed. It comes out that the diffusion speed must be at least one order of magnitude (in terms of Knudsen number) smaller than the barycentric speed, in order to recover the Navier-Stokes equations for mixtures in the incompressible limit. Some further numerical tests are also reported. In particular, (1) the solvent and dilute test cases are considered, because they are limiting cases in which the Maxwell-Stefan model reduces automatically to Fickian cases. Moreover, (2) some tests based on the Stefan diffusion tube are reported for proving the complete capabilities of the proposed scheme in solving Maxwell-Stefan diffusion problems. The proposed scheme agrees well with the expected theoretical results.

Multiparameter Analysis of Gas Transport Phenomena in Shale Gas Reservoirs: Apparent Permeability Characterization.

PubMed

Shen, Yinghao; Pang, Yu; Shen, Ziqi; Tian, Yuanyuan; Ge, Hongkui

2018-02-08

The large amount of nanoscale pores in shale results in the inability to apply Darcy's law. Moreover, the gas adsorption of shale increases the complexity of pore size characterization and thus decreases the accuracy of flow regime estimation. In this study, an apparent permeability model, which describes the adsorptive gas flow behavior in shale by considering the effects of gas adsorption, stress dependence, and non-Darcy flow, is proposed. The pore size distribution, methane adsorption capacity, pore compressibility, and matrix permeability of the Barnett and Eagle Ford shales are measured in the laboratory to determine the critical parameters of gas transport phenomena. The slip coefficients, tortuosity, and surface diffusivity are predicted via the regression analysis of the permeability data. The results indicate that the apparent permeability model, which considers second-order gas slippage, Knudsen diffusion, and surface diffusion, could describe the gas flow behavior in the transition flow regime for nanoporous shale. Second-order gas slippage and surface diffusion play key roles in the gas flow in nanopores for Knudsen numbers ranging from 0.18 to 0.5. Therefore, the gas adsorption and non-Darcy flow effects, which involve gas slippage, Knudsen diffusion, and surface diffusion, are indispensable parameters of the permeability model for shale.

Diffusive deposition of aerosols in Phebus containment during FPT-2 test

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

Kontautas, A.; Urbonavicius, E.

2012-07-01

At present the lumped-parameter codes is the main tool to investigate the complex response of the containment of Nuclear Power Plant in case of an accident. Continuous development and validation of the codes is required to perform realistic investigation of the processes that determine the possible source term of radioactive products to the environment. Validation of the codes is based on the comparison of the calculated results with the measurements performed in experimental facilities. The most extensive experimental program to investigate fission product release from the molten fuel, transport through the cooling circuit and deposition in the containment is performedmore » in PHEBUS test facility. Test FPT-2 performed in this facility is considered for analysis of processes taking place in containment. Earlier performed investigations using COCOSYS code showed that the code could be successfully used for analysis of thermal-hydraulic processes and deposition of aerosols, but there was also noticed that diffusive deposition on the vertical walls does not fit well with the measured results. In the CPA module of ASTEC code there is implemented different model for diffusive deposition, therefore the PHEBUS containment model was transferred from COCOSYS code to ASTEC-CPA to investigate the influence of the diffusive deposition modelling. Analysis was performed using PHEBUS containment model of 16 nodes. The calculated thermal-hydraulic parameters are in good agreement with measured results, which gives basis for realistic simulation of aerosol transport and deposition processes. Performed investigations showed that diffusive deposition model has influence on the aerosol deposition distribution on different surfaces in the test facility. (authors)« less

Analysis on a diffusive SIS epidemic model with logistic source

NASA Astrophysics Data System (ADS)

Li, Bo; Li, Huicong; Tong, Yachun

2017-08-01

In this paper, we are concerned with an SIS epidemic reaction-diffusion model with logistic source in spatially heterogeneous environment. We first discuss some basic properties of the parabolic system, including the uniform upper bound of solutions and global stability of the endemic equilibrium when spatial environment is homogeneous. Our primary focus is to determine the asymptotic profile of endemic equilibria (when exist) if the diffusion (migration) rate of the susceptible or infected population is small or large. Combined with the results of Li et al. (J Differ Equ 262:885-913, 2017) where the case of linear source is studied, our analysis suggests that varying total population enhances persistence of infectious disease.

Bringing diffuse X-ray scattering into focus

DOE PAGES

Wall, Michael E.; Wolff, Alexander M.; Fraser, James S.

2018-02-16

X-ray crystallography is experiencing a renaissance as a method for probing the protein conformational ensemble. The inherent limitations of Bragg analysis, however, which only reveals the mean structure, have given way to a surge in interest in diffuse scattering, which is caused by structure variations. Diffuse scattering is present in all macromolecular crystallography experiments. Recent studies are shedding light on the origins of diffuse scattering in protein crystallography, and provide clues for leveraging diffuse scattering to model protein motions with atomic detail.

Bringing diffuse X-ray scattering into focus

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

Wall, Michael E.; Wolff, Alexander M.; Fraser, James S.

X-ray crystallography is experiencing a renaissance as a method for probing the protein conformational ensemble. The inherent limitations of Bragg analysis, however, which only reveals the mean structure, have given way to a surge in interest in diffuse scattering, which is caused by structure variations. Diffuse scattering is present in all macromolecular crystallography experiments. Recent studies are shedding light on the origins of diffuse scattering in protein crystallography, and provide clues for leveraging diffuse scattering to model protein motions with atomic detail.

In Silico Neuro-Oncology: Brownian Motion-Based Mathematical Treatment as a Potential Platform for Modeling the Infiltration of Glioma Cells into Normal Brain Tissue.

PubMed

Antonopoulos, Markos; Stamatakos, Georgios

2015-01-01

Intensive glioma tumor infiltration into the surrounding normal brain tissues is one of the most critical causes of glioma treatment failure. To quantitatively understand and mathematically simulate this phenomenon, several diffusion-based mathematical models have appeared in the literature. The majority of them ignore the anisotropic character of diffusion of glioma cells since availability of pertinent truly exploitable tomographic imaging data is limited. Aiming at enriching the anisotropy-enhanced glioma model weaponry so as to increase the potential of exploiting available tomographic imaging data, we propose a Brownian motion-based mathematical analysis that could serve as the basis for a simulation model estimating the infiltration of glioblastoma cells into the surrounding brain tissue. The analysis is based on clinical observations and exploits diffusion tensor imaging (DTI) data. Numerical simulations and suggestions for further elaboration are provided.

Discrete effect on the halfway bounce-back boundary condition of multiple-relaxation-time lattice Boltzmann model for convection-diffusion equations.

PubMed

Cui, Shuqi; Hong, Ning; Shi, Baochang; Chai, Zhenhua

2016-04-01

In this paper, we will focus on the multiple-relaxation-time (MRT) lattice Boltzmann model for two-dimensional convection-diffusion equations (CDEs), and analyze the discrete effect on the halfway bounce-back (HBB) boundary condition (or sometimes called bounce-back boundary condition) of the MRT model where three different discrete velocity models are considered. We first present a theoretical analysis on the discrete effect of the HBB boundary condition for the simple problems with a parabolic distribution in the x or y direction, and a numerical slip proportional to the second-order of lattice spacing is observed at the boundary, which means that the MRT model has a second-order convergence rate in space. The theoretical analysis also shows that the numerical slip can be eliminated in the MRT model through tuning the free relaxation parameter corresponding to the second-order moment, while it cannot be removed in the single-relaxation-time model or the Bhatnagar-Gross-Krook model unless the relaxation parameter related to the diffusion coefficient is set to be a special value. We then perform some simulations to confirm our theoretical results, and find that the numerical results are consistent with our theoretical analysis. Finally, we would also like to point out the present analysis can be extended to other boundary conditions of lattice Boltzmann models for CDEs.

Apparent Anomalous Diffusion in the Cytoplasm of Human Cells: The Effect of Probes' Polydispersity.

PubMed

Kalwarczyk, Tomasz; Kwapiszewska, Karina; Szczepanski, Krzysztof; Sozanski, Krzysztof; Szymanski, Jedrzej; Michalska, Bernadeta; Patalas-Krawczyk, Paulina; Duszynski, Jerzy; Holyst, Robert

2017-10-26

This work, based on in vivo and in vitro measurements, as well as in silico simulations, provides a consistent analysis of diffusion of polydisperse nanoparticles in the cytoplasm of living cells. Using the example of fluorescence correlation spectroscopy (FCS), we show the effect of polydispersity of probes on the experimental results. Although individual probes undergo normal diffusion, in the ensemble of probes, an effective broadening of the distribution of diffusion times occurs-similar to anomalous diffusion. We introduced fluorescently labeled dextrans into the cytoplasm of HeLa cells and found that cytoplasmic hydrodynamic drag, exponentially dependent on probe size, extraordinarily broadens the distribution of diffusion times across the focal volume. As a result, the in vivo FCS data were effectively fitted with the anomalous subdiffusion model while for a monodisperse probe the normal diffusion model was most suitable. Diffusion time obtained from the anomalous diffusion model corresponds to a probe whose size is determined by the weight-average molecular weight of the polymer. The apparent anomaly exponent decreases with increasing polydispersity of the probes. Our results and methodology can be applied in intracellular studies of the mobility of nanoparticles, polymers, or oligomerizing proteins.

Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched-exponential diffusion models.

PubMed

Wang, Feng; Wang, Yuxiang; Zhou, Yan; Liu, Congrong; Xie, Lizhi; Zhou, Zhenyu; Liang, Dong; Shen, Yang; Yao, Zhihang; Liu, Jianyu

2017-12-01

To evaluate the utility of histogram analysis of monoexponential, biexponential, and stretched-exponential models to a dualistic model of epithelial ovarian cancer (EOC). Fifty-two patients with histopathologically proven EOC underwent preoperative magnetic resonance imaging (MRI) (including diffusion-weighted imaging [DWI] with 11 b-values) using a 3.0T system and were divided into two groups: types I and II. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) histograms were obtained based on solid components of the entire tumor. The following metrics of each histogram were compared between two types: 1) mean; 2) median; 3) 10th percentile and 90th percentile. Conventional MRI morphological features were also recorded. Significant morphological features for predicting EOC type were maximum diameter (P = 0.007), texture of lesion (P = 0.001), and peritoneal implants (P = 0.001). For ADC, D, f, DDC, and α, all metrics were significantly lower in type II than type I (P < 0.05). Mean, median, 10th, and 90th percentile of D* were not significantly different (P = 0.336, 0.154, 0.779, and 0.203, respectively). Most histogram metrics of ADC, D, and DDC had significantly higher area under the receiver operating characteristic curve values than those of f and α (P < 0.05) CONCLUSION: It is feasible to grade EOC by morphological features and three models with histogram analysis. ADC, D, and DDC have better performance than f and α; f and α may provide additional information. 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1797-1809. © 2017 International Society for Magnetic Resonance in Medicine.

Predicting X-ray diffuse scattering from translation–libration–screw structural ensembles

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

Van Benschoten, Andrew H.; Afonine, Pavel V.; Terwilliger, Thomas C.

2015-07-28

A method of simulating X-ray diffuse scattering from multi-model PDB files is presented. Despite similar agreement with Bragg data, different translation–libration–screw refinement strategies produce unique diffuse intensity patterns. Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling andmore » validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier’s equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation–libration–screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls-as-xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophosphodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. These methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis.« less

The Harrison Diffusion Kinetics Regimes in Solute Grain Boundary Diffusion

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

Belova, Irina; Fiedler, T; Kulkarni, Nagraj S

2012-01-01

Knowledge of the limits of the principal Harrison kinetics regimes (Type-A, B and C) for grain boundary diffusion is very important for the correct analysis of the depth profiles in a tracer diffusion experiment. These regimes for self-diffusion have been extensively studied in the past by making use of the phenomenological Lattice Monte Carlo (LMC) method with the result that the limits are now well established. The relationship of those self-diffusion limits to the corresponding ones for solute diffusion in the presence of solute segregation to the grain boundaries remains unclear. In the present study, the influence of solute segregationmore » on the limits is investigated with the LMC method for the well-known parallel grain boundary slab model by showing the equivalence of two diffusion models. It is shown which diffusion parameters are useful for identifying the limits of the Harrison kinetics regimes for solute grain boundary diffusion. It is also shown how the measured segregation factor from the diffusion experiment in the Harrison Type-B kinetics regime may differ from the global segregation factor.« less

A comparative study of the sensitivity of diffusion-related parameters obtained from diffusion tensor imaging, diffusional kurtosis imaging, q-space analysis and bi-exponential modelling in the early disease course (24 h) of hyperacute (6 h) ischemic stroke patients.

PubMed

Duchêne, Gaëtan; Peeters, Frank; Peeters, André; Duprez, Thierry

2017-08-01

To compare the sensitivity and early temporal changes of diffusion parameters obtained from diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), q-space analysis (QSA) and bi-exponential modelling in hyperacute stroke patients. A single investigational acquisition allowing the four diffusion analyses was performed on seven hyperacute stroke patients with a 3T system. The percentage change between ipsi- and contralateral regions were compared at admission and 24 h later. Two out of the seven patients were imaged every 6 h during this period. Kurtoses from both DKI and QSA were the most sensitive of the tested diffusion parameters in the few hours following ischemia. An early increase-maximum-decrease pattern of evolution was highlighted during the 24-h period for all parameters proportional to diffusion coefficients. A similar pattern was observed for both kurtoses in only one of two patients. Our comparison was performed using identical diffusion encoding timings and on patients in the same stage of their condition. Although preliminary, our findings confirm those of previous studies that showed enhanced sensitivity of kurtosis. A fine time mapping of diffusion metrics in hyperacute stroke patients was presented which advocates for further investigations on larger animal or human cohorts.

Perfluoroalkyl phosphonic and phosphinic acids as proton conductors for anhydrous proton-exchange membranes.

PubMed

Herath, Mahesha B; Creager, Stephen E; Kitaygorodskiy, Alex; DesMarteau, Darryl D

2010-09-10

A study of proton-transport rates and mechanisms under anhydrous conditions using a series of acid model compounds, analogous to comb-branch perfluorinated ionomers functionalized with phosphonic, phosphinic, sulfonic, and carboxylic acid protogenic groups, is reported. Model compounds are characterized with respect to proton conductivity, viscosity, proton, and anion (conjugate base) self-diffusion coefficients, and Hammett acidity. The highest conductivities, and also the highest viscosities, are observed for the phosphonic and phosphinic acid model compounds. Arrhenius analysis of conductivity and viscosity for these two acids reveals much lower activation energies for ion transport than for viscous flow. Additionally, the proton self-diffusion coefficients are much higher than the conjugate-base self-diffusion coefficients for these two acids. Taken together, these data suggest that anhydrous proton transport in the phosphonic and phosphinic acid model compounds occurs primarily by a structure-diffusion, hopping-based mechanism rather than a vehicle mechanism. Further analysis of ionic conductivity and ion self-diffusion rates by using the Nernst-Einstein equation reveals that the phosphonic and phosphinic acid model compounds are relatively highly dissociated even under anhydrous conditions. In contrast, sulfonic and carboxylic acid-based systems exhibit relatively low degrees of dissociation under anhydrous conditions. These findings suggest that fluoroalkyl phosphonic and phosphinic acids are good candidates for further development as anhydrous, high-temperature proton conductors.

Comparison and analysis of theoretical models for diffusion-controlled dissolution.

PubMed

Wang, Yanxing; Abrahamsson, Bertil; Lindfors, Lennart; Brasseur, James G

2012-05-07

Dissolution models require, at their core, an accurate diffusion model. The accuracy of the model for diffusion-dominated dissolution is particularly important with the trend toward micro- and nanoscale drug particles. Often such models are based on the concept of a "diffusion layer." Here a framework is developed for diffusion-dominated dissolution models, and we discuss the inadequacy of classical models that are based on an unphysical constant diffusion layer thickness assumption, or do not correctly modify dissolution rate due to "confinement effects": (1) the increase in bulk concentration from confinement of the dissolution process, (2) the modification of the flux model (the Sherwood number) by confinement. We derive the exact mathematical solution for a spherical particle in a confined fluid with impermeable boundaries. Using this solution, we analyze the accuracy of a time-dependent "infinite domain model" (IDM) and "quasi steady-state model" (QSM), both formally derived for infinite domains but which can be applied in approximate fashion to confined dissolution with proper adjustment of a concentration parameter. We show that dissolution rate is sensitive to the degree of confinement or, equivalently, to the total concentration C(tot). The most practical model, the QSM, is shown to be very accurate for most applications and, consequently, can be used with confidence in design-level dissolution models so long as confinement is accurately treated. The QSM predicts the ratio of diffusion layer thickness to particle radius (the Sherwood number) as a constant plus a correction that depends on the degree of confinement. The QSM also predicts that the time required for complete saturation or dissolution in diffusion-controlled dissolution experiments is singular (i.e., infinite) when total concentration equals the solubility. Using the QSM, we show that measured differences in dissolution rate in a diffusion-controlled dissolution experiment are a result of differences in the degree of confinement on the increase in bulk concentration independent of container geometry and polydisperse vs single particle dissolution. We conclude that the constant diffusion-layer thickness assumption is incorrect in principle and should be replaced by the QSM with accurate treatment of confinement in models of diffusion-controlled dissolution.

Quantitative analysis of binary polymorphs mixtures of fusidic acid by diffuse reflectance FTIR spectroscopy, diffuse reflectance FT-NIR spectroscopy, Raman spectroscopy and multivariate calibration.

PubMed

Guo, Canyong; Luo, Xuefang; Zhou, Xiaohua; Shi, Beijia; Wang, Juanjuan; Zhao, Jinqi; Zhang, Xiaoxia

2017-06-05

Vibrational spectroscopic techniques such as infrared, near-infrared and Raman spectroscopy have become popular in detecting and quantifying polymorphism of pharmaceutics since they are fast and non-destructive. This study assessed the ability of three vibrational spectroscopy combined with multivariate analysis to quantify a low-content undesired polymorph within a binary polymorphic mixture. Partial least squares (PLS) regression and support vector machine (SVM) regression were employed to build quantitative models. Fusidic acid, a steroidal antibiotic, was used as the model compound. It was found that PLS regression performed slightly better than SVM regression in all the three spectroscopic techniques. Root mean square errors of prediction (RMSEP) were ranging from 0.48% to 1.17% for diffuse reflectance FTIR spectroscopy and 1.60-1.93% for diffuse reflectance FT-NIR spectroscopy and 1.62-2.31% for Raman spectroscopy. The results indicate that diffuse reflectance FTIR spectroscopy offers significant advantages in providing accurate measurement of polymorphic content in the fusidic acid binary mixtures, while Raman spectroscopy is the least accurate technique for quantitative analysis of polymorphs. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

HEAO-1 analysis of Low Energy Detectors (LED)

NASA Technical Reports Server (NTRS)

Nousek, John A.

1992-01-01

The activities at Penn State University are described. During the period Oct. 1990 to Dec. 1991 work on HEAO-1 analysis of the Low Energy Detectors (LED) concentrated on using the improved detector spectral simulation model and fitting diffuse x-ray background spectral data. Spectral fitting results, x-ray point sources, and diffuse x-ray sources are described.

Information Diffusion in Facebook-Like Social Networks Under Information Overload

NASA Astrophysics Data System (ADS)

Li, Pei; Xing, Kai; Wang, Dapeng; Zhang, Xin; Wang, Hui

2013-07-01

Research on social networks has received remarkable attention, since many people use social networks to broadcast information and stay connected with their friends. However, due to the information overload in social networks, it becomes increasingly difficult for users to find useful information. This paper takes Facebook-like social networks into account, and models the process of information diffusion under information overload. The term view scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated is proposed to characterize the information diffusion efficiency. Through theoretical analysis, we find that factors such as network structure and view scope number have no impact on the information diffusion efficiency, which is a surprising result. To verify the results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly.

Turing instability in reaction-diffusion models on complex networks

NASA Astrophysics Data System (ADS)

Ide, Yusuke; Izuhara, Hirofumi; Machida, Takuya

2016-09-01

In this paper, the Turing instability in reaction-diffusion models defined on complex networks is studied. Here, we focus on three types of models which generate complex networks, i.e. the Erdős-Rényi, the Watts-Strogatz, and the threshold network models. From analysis of the Laplacian matrices of graphs generated by these models, we numerically reveal that stable and unstable regions of a homogeneous steady state on the parameter space of two diffusion coefficients completely differ, depending on the network architecture. In addition, we theoretically discuss the stable and unstable regions in the cases of regular enhanced ring lattices which include regular circles, and networks generated by the threshold network model when the number of vertices is large enough.

Automatic simplification of systems of reaction-diffusion equations by a posteriori analysis.

PubMed

Maybank, Philip J; Whiteley, Jonathan P

2014-02-01

Many mathematical models in biology and physiology are represented by systems of nonlinear differential equations. In recent years these models have become increasingly complex in order to explain the enormous volume of data now available. A key role of modellers is to determine which components of the model have the greatest effect on a given observed behaviour. An approach for automatically fulfilling this role, based on a posteriori analysis, has recently been developed for nonlinear initial value ordinary differential equations [J.P. Whiteley, Model reduction using a posteriori analysis, Math. Biosci. 225 (2010) 44-52]. In this paper we extend this model reduction technique for application to both steady-state and time-dependent nonlinear reaction-diffusion systems. Exemplar problems drawn from biology are used to demonstrate the applicability of the technique. Copyright © 2014 Elsevier Inc. All rights reserved.

Simulation study of temperature-dependent diffusion behaviors of Ag/Ag(001) at low substrate temperature

NASA Astrophysics Data System (ADS)

Cai, Danyun; Mo, Yunjie; Feng, Xiaofang; He, Yingyou; Jiang, Shaoji

2017-06-01

In this study, a model based on the First Principles calculations and Kinetic Monte Carlo simulation were established to study the growth characteristic of Ag thin film at low substrate temperature. On the basis of the interaction between the adatom and nearest-neighbor atoms, some simplifications and assumptions were made to categorize the diffusion behaviors of Ag adatoms on Ag(001). Then the barriers of all possible diffusion behaviors were calculated using the Climbing Image Nudged Elastic Band method (CI-NEB). Based on the Arrhenius formula, the morphology variation, which is attributed to the surface diffusion behaviors during the growth, was simulated with a temperature-dependent KMC model. With this model, a non-monotonic relation between the surface roughness and the substrate temperature (decreasing from 300 K to 100 K) were discovered. The analysis of the temperature dependence on diffusion behaviors presents a theoretical explanation of diffusion mechanism for the non-monotonic variation of roughness at low substrate temperature.

A new coarse-grained model for E. coli cytoplasm: accurate calculation of the diffusion coefficient of proteins and observation of anomalous diffusion.

PubMed

Hasnain, Sabeeha; McClendon, Christopher L; Hsu, Monica T; Jacobson, Matthew P; Bandyopadhyay, Pradipta

2014-01-01

A new coarse-grained model of the E. coli cytoplasm is developed by describing the proteins of the cytoplasm as flexible units consisting of one or more spheres that follow Brownian dynamics (BD), with hydrodynamic interactions (HI) accounted for by a mean-field approach. Extensive BD simulations were performed to calculate the diffusion coefficients of three different proteins in the cellular environment. The results are in close agreement with experimental or previously simulated values, where available. Control simulations without HI showed that use of HI is essential to obtain accurate diffusion coefficients. Anomalous diffusion inside the crowded cellular medium was investigated with Fractional Brownian motion analysis, and found to be present in this model. By running a series of control simulations in which various forces were removed systematically, it was found that repulsive interactions (volume exclusion) are the main cause for anomalous diffusion, with a secondary contribution from HI.

Oxygen Diffusion and Reaction Kinetics in Continuous Fiber Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Halbig, Michael C.; Eckel, Andrew J.; Cawley, James D.

1999-01-01

Previous stressed oxidation tests of C/SiC composites at elevated temperatures (350 C to 1500 C) and sustained stresses (69 MPa and 172 MPa) have led to the development of a finite difference cracked matrix model. The times to failure in the samples suggest oxidation occurred in two kinetic regimes defined by the rate controlling mechanisms (i.e. diffusion controlled and reaction controlled kinetics). Microstructural analysis revealed preferential oxidation along as-fabricated, matrix microcracks and also suggested two regimes of oxidation kinetics dependent on the oxidation temperature. Based on experimental results, observation, and theory, a finite difference model was developed. The model simulates the diffusion of oxygen into a matrix crack bridged by carbon fibers. The model facilitates the study of the relative importance of temperature, the reaction rate constant, and the diffusion coefficient on the overall oxidation kinetics.

Analysis of Particle Transport in DIII-D H-mode Plasma with a Generalized Pinch-Diffusion Model

NASA Astrophysics Data System (ADS)

Owen, L. W.; Stacey, W. M.; Groebner, R. J.; Callen, J. D.; Bonnin, X.

2009-11-01

Interpretative analyses of particle transport in the pedestal region of H-mode plasmas typically yield diffusion coefficients that are very small (<0.1 m^2/s) in the steep gradient region when a purely diffusive particle flux is fitted to the experimental density gradients. Previous evaluation of the particle and momentum balance equations using the experimental data indicated that the pedestal profiles are consistent with transport described by a pinch-diffusion particle flux relation [1]. This type of model is used to calculate the diffusion coefficient and pinch velocity in the core for an inter-ELM H-mode plasma in the DIII-D discharge 98889. Full-plasma SOPLS simulations using neutral beam particle and energy sources from ONETWO calculations and the model transport coefficients show good agreement with the measured density pedestal profile. 6pt [1] W.M. Stacey and R.J. Groebner, Phys. Plasmas 12, 042504 (2005).

Molecular modeling of polymers 16. Gaseous diffusion in polymers: a quantitative structure-property relationship (QSPR) analysis.

PubMed

Patel, H C; Tokarski, J S; Hopfinger, A J

1997-10-01

The purpose of this study was to identify the key physicochemical molecular properties of polymeric materials responsible for gaseous diffusion in the polymers. Quantitative structure-property relationships, QSPRs were constructed using a genetic algorithm on a training set of 16 polymers for which CO2, N2, O2 diffusion constants were measured. Nine physicochemical properties of each of the polymers were used in the trial basis set for QSPR model construction. The linear cross-correlation matrices were constructed and investigated for colinearity among the members of the training sets. Common water diffusion measures for a limited training set of six polymers was used to construct a "semi-QSPR" model. The bulk modulus of the polymer was overwhelmingly found to be the dominant physicochemical polymer property that governs CO2, N2 and O2 diffusion. Some secondary physicochemical properties controlling diffusion, including conformational entropy, were also identified as correlation descriptors. Very significant QSPR diffusion models were constructed for all three gases. Cohesive energy was identified as the main correlation physicochemical property with aqueous diffusion measures. The dominant role of polymer bulk modulus on gaseous diffusion makes it difficult to develop criteria for selective transport of gases through polymers. Moreover, high bulk moduli are predicted to be necessary for effective gas barrier materials. This property requirement may limit the processing and packaging features of the material. Aqueous diffusion in polymers may occur by a different mechanism than gaseous diffusion since bulk modulus does not correlate with aqueous diffusion, but rather cohesive energy of the polymer.

Roles of Vacancy/Interstitial Diffusion and Segregation in the Microchemistry at Grain Boundaries of Irradiated Fe-Cr-Ni alloys

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

Yang, Ying; Field, Kevin G.; Allen, Todd R.

2016-02-23

A detailed analysis of the diffusion fluxes near and at grain boundaries of irradiated Fe–Cr–Ni alloys, induced by preferential atom-vacancy and atom-interstitial coupling, is presented. The diffusion flux equations were based on the Perks model formulated through the linear theory of the thermodynamics of irreversible processes. The preferential atom-vacancy coupling was described by the mobility model, whereas the preferential atom-interstitial coupling was described by the interstitial binding model. The composition dependence of the thermodynamic factor was modeled using the CALPHAD approach. The calculated fluxes up to 10 dpa suggested the dominant diffusion mechanism for chromium and iron is via vacancy,more » while that for nickel can swing from the vacancy to the interstitial dominant mechanism. The diffusion flux in the vicinity of a grain boundary was found to be greatly modified by the segregation induced by irradiation, leading to the oscillatory behavior of alloy compositions in this region.« less

Predicting X-ray diffuse scattering from translation–libration–screw structural ensembles

PubMed Central

Van Benschoten, Andrew H.; Afonine, Pavel V.; Terwilliger, Thomas C.; Wall, Michael E.; Jackson, Colin J.; Sauter, Nicholas K.; Adams, Paul D.; Urzhumtsev, Alexandre; Fraser, James S.

2015-01-01

Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling and validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier’s equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation–libration–screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls_as_xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophos­phodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. These methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis. PMID:26249347

Predicting X-ray diffuse scattering from translation–libration–screw structural ensembles

DOE PAGES

Van Benschoten, Andrew H.; Afonine, Pavel V.; Terwilliger, Thomas C.; ...

2015-07-28

Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling and validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier'smore » equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation–libration–screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls_as_xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophosphodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. In addition, these methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis.« less

Model-based analysis of multi-shell diffusion MR data for tractography: How to get over fitting problems

PubMed Central

Jbabdi, Saad; Sotiropoulos, Stamatios N; Savio, Alexander M; Graña, Manuel; Behrens, Timothy EJ

2012-01-01

In this article, we highlight an issue that arises when using multiple b-values in a model-based analysis of diffusion MR data for tractography. The non-mono-exponential decay, commonly observed in experimental data, is shown to induce over-fitting in the distribution of fibre orientations when not considered in the model. Extra fibre orientations perpendicular to the main orientation arise to compensate for the slower apparent signal decay at higher b-values. We propose a simple extension to the ball and stick model based on a continuous Gamma distribution of diffusivities, which significantly improves the fitting and reduces the over-fitting. Using in-vivo experimental data, we show that this model outperforms a simpler, noise floor model, especially at the interfaces between brain tissues, suggesting that partial volume effects are a major cause of the observed non-mono-exponential decay. This model may be helpful for future data acquisition strategies that may attempt to combine multiple shells to improve estimates of fibre orientations in white matter and near the cortex. PMID:22334356

Validation of a Computational Model for the SLS Core Stage Oxygen Tank Diffuser Concept and the Low Profile Diffuser - An Advanced Development Design for the SLS

NASA Technical Reports Server (NTRS)

Brodnick, Jacob; Richardson, Brian; Ramachandran, Narayanan

2015-01-01

The Low Profile Diffuser (LPD) project originated as an award from the Marshall Space Flight Center (MSFC) Advanced Development (ADO) office to the Main Propulsion Systems Branch (ER22). The task was created to develop and test an LPD concept that could produce comparable performance to a larger, traditionally designed, ullage gas diffuser while occupying a smaller volume envelope. Historically, ullage gas diffusers have been large, bulky devices that occupy a significant portion of the propellant tank, decreasing the tank volume available for propellant. Ullage pressurization of spacecraft propellant tanks is required to prevent boil-off of cryogenic propellants and to provide a positive pressure for propellant extraction. To achieve this, ullage gas diffusers must slow hot, high-pressure gas entering a propellant tank from supersonic speeds to only a few meters per second. Decreasing the incoming gas velocity is typically accomplished through expansion to larger areas within the diffuser which has traditionally led to large diffuser lengths. The Fluid Dynamics Branch (ER42) developed and applied advanced Computational Fluid Dynamics (CFD) analysis methods in order to mature the LPD design from and initial concept to an optimized test prototype and to provide extremely accurate pre-test predictions of diffuser performance. Additionally, the diffuser concept for the Core Stage of the Space Launch System (SLS) was analyzed in a short amount of time to guide test data collection efforts of the qualification of the device. CFD analysis of the SLS diffuser design provided new insights into the functioning of the device and was qualitatively validated against hot wire anemometry of the exterior flow field. Rigorous data analysis of the measurements was performed on static and dynamic pressure data, data from two microphones, accelerometers and hot wire anemometry with automated traverse. Feasibility of the LPD concept and validation of the computational model were demonstrated by the test data.

Finite linear diffusion model for design of overcharge protection for rechargeable lithium batteries

NASA Technical Reports Server (NTRS)

Narayanan, S. R.; Surampudi, S.; Attia, A. I.

1991-01-01

The overcharge condition in secondary lithium batteries employing redox additives for overcharge protection has been theoretically analyzed in terms of a finite linear diffusion model. The analysis leads to expressions relating the steady-state overcharge current density and cell voltage to the concentration, diffusion coefficient, standard reduction potential of the redox couple, and interelectrode distance. The model permits the estimation of the maximum permissible overcharge rate for any chosen set of system conditions. The model has been experimentally verified using 1,1-prime-dimethylferrocene as a redox additive. The theoretical results may be exploited in the design and optimization of overcharge protection by the redox additive approach.

Evaluation of diffusion models in breast cancer.

PubMed

Panek, Rafal; Borri, Marco; Orton, Matthew; O'Flynn, Elizabeth; Morgan, Veronica; Giles, Sharon L; deSouza, Nandita; Leach, Martin O; Schmidt, Maria A

2015-08-01

The purpose of this study is to investigate whether the microvascular pseudodiffusion effects resulting with non-monoexponential behavior are present in breast cancer, taking into account tumor spatial heterogeneity. Additionally, methodological factors affecting the signal in low and high diffusion-sensitizing gradient ranges were explored in phantom studies. The effect of eddy currents and accuracy of b-value determination using a multiple b-value diffusion-weighted MR imaging sequence were investigated in test objects. Diffusion model selection and noise were then investigated in volunteers (n = 5) and breast tumor patients (n = 21) using the Bayesian information criterion. 54.3% of lesion voxels were best fitted by a monoexponential, 26.2% by a stretched-exponential, and 19.5% by a biexponential intravoxel incoherent motion (IVIM) model. High correlation (0.92) was observed between diffusion coefficients calculated using mono- and stretched-exponential models and moderate (0.59) between monoexponential and IVIM (medians: 0.96/0.84/0.72 × 10(-3) mm(2)/s, respectively). Distortion due to eddy currents depended on the direction of the diffusion gradient and displacement varied between 1 and 6 mm for high b-value images. Shift in the apparent diffusion coefficient due to intrinsic field gradients was compensated for by averaging diffusion data obtained from opposite directions. Pseudodiffusion and intravoxel heterogeneity effects were not observed in approximately half of breast cancer and normal tissue voxels. This result indicates that stretched and IVIM models should be utilized in regional analysis rather than global tumor assessment. Cross terms between diffusion-sensitization gradients and other imaging or susceptibility-related gradients are relevant in clinical protocols, supporting the use of geometric averaging of diffusion-weighted images acquired with diffusion-sensitization gradients in opposite directions.

Identify source location and release time for pollutants undergoing super-diffusion and decay: Parameter analysis and model evaluation

NASA Astrophysics Data System (ADS)

Zhang, Yong; Sun, HongGuang; Lu, Bingqing; Garrard, Rhiannon; Neupauer, Roseanna M.

2017-09-01

Backward models have been applied for four decades by hydrologists to identify the source of pollutants undergoing Fickian diffusion, while analytical tools are not available for source identification of super-diffusive pollutants undergoing decay. This technical note evaluates analytical solutions for the source location and release time of a decaying contaminant undergoing super-diffusion using backward probability density functions (PDFs), where the forward model is the space fractional advection-dispersion equation with decay. Revisit of the well-known MADE-2 tracer test using parameter analysis shows that the peak backward location PDF can predict the tritium source location, while the peak backward travel time PDF underestimates the tracer release time due to the early arrival of tracer particles at the detection well in the maximally skewed, super-diffusive transport. In addition, the first-order decay adds additional skewness toward earlier arrival times in backward travel time PDFs, resulting in a younger release time, although this impact is minimized at the MADE-2 site due to tritium's half-life being relatively longer than the monitoring period. The main conclusion is that, while non-trivial backward techniques are required to identify pollutant source location, the pollutant release time can and should be directly estimated given the speed of the peak resident concentration for super-diffusive pollutants with or without decay.

Dynamic physiological modeling for functional diffuse optical tomography

PubMed Central

Diamond, Solomon Gilbert; Huppert, Theodore J.; Kolehmainen, Ville; Franceschini, Maria Angela; Kaipio, Jari P.; Arridge, Simon R.; Boas, David A.

2009-01-01

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n = 10, P < 0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis. PMID:16242967

A Diffusion Model Analysis of Adult Age Differences in Episodic and Semantic Long-Term Memory Retrieval

ERIC Educational Resources Information Center

Spaniol, Julia; Madden, David J.; Voss, Andreas

2006-01-01

Two experiments investigated adult age differences in episodic and semantic long-term memory tasks, as a test of the hypothesis of specific age-related decline in context memory. Older adults were slower and exhibited lower episodic accuracy than younger adults. Fits of the diffusion model (R. Ratcliff, 1978) revealed age-related increases in…

A Diffusion Model Analysis of the Effects of Aging on Recognition Memory

ERIC Educational Resources Information Center

Ratcliff, Roger; Thapar, Anjali; McKoon, Gail

2004-01-01

The effects of aging on response time were examined in a recognition memory experiment with young, college age subjects and older, 60-75 year old subjects. The older subjects were slower than the young subjects but almost as accurate. Ratcliff's (1978) diffusion model was fit to the data and it provided a good account of response times, their…

Children Are Not like Older Adults: A Diffusion Model Analysis of Developmental Changes in Speeded Responses

ERIC Educational Resources Information Center

Ratcliff, Roger; Love, Jessica; Thompson, Clarissa A.; Opfer, John E.

2012-01-01

Children (n = 130; M[subscript age] = 8.51-15.68 years) and college-aged adults (n = 72; M[subscript age] = 20.50 years) completed numerosity discrimination and lexical decision tasks. Children produced longer response times (RTs) than adults. R. Ratcliff's (1978) diffusion model, which divides processing into components (e.g., quality of…

Dipy, a library for the analysis of diffusion MRI data.

PubMed

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing.

Dipy, a library for the analysis of diffusion MRI data

PubMed Central

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing. PMID:24600385

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.

Effect of the initial domain on the dispersion dynamics of a diffusing substance

NASA Astrophysics Data System (ADS)

Bestuzheva, A. N.; Smirnov, A. L.

2018-05-01

The formulation and analysis of ecological problems involves the mathematical modeling, when some assumptions concerning the nature of the processes are introduced. These assumptions must be justified. In the present paper the effect of the form of the initial domain occupied with a diffusing substance on the process of diffusion is studied. It's shown that the form of the initial domain plays unimportant role and it may be modeled as semi-sphere, for which the problem has analytical solution. That solution may serves as the zeroth approximation in modeling of actual ecological problem taking into account the relief of the bottom and the bottom currents.

Uncertainty for calculating transport on Titan: A probabilistic description of bimolecular diffusion parameters

NASA Astrophysics Data System (ADS)

Plessis, S.; McDougall, D.; Mandt, K.; Greathouse, T.; Luspay-Kuti, A.

2015-11-01

Bimolecular diffusion coefficients are important parameters used by atmospheric models to calculate altitude profiles of minor constituents in an atmosphere. Unfortunately, laboratory measurements of these coefficients were never conducted at temperature conditions relevant to the atmosphere of Titan. Here we conduct a detailed uncertainty analysis of the bimolecular diffusion coefficient parameters as applied to Titan's upper atmosphere to provide a better understanding of the impact of uncertainty for this parameter on models. Because temperature and pressure conditions are much lower than the laboratory conditions in which bimolecular diffusion parameters were measured, we apply a Bayesian framework, a problem-agnostic framework, to determine parameter estimates and associated uncertainties. We solve the Bayesian calibration problem using the open-source QUESO library which also performs a propagation of uncertainties in the calibrated parameters to temperature and pressure conditions observed in Titan's upper atmosphere. Our results show that, after propagating uncertainty through the Massman model, the uncertainty in molecular diffusion is highly correlated to temperature and we observe no noticeable correlation with pressure. We propagate the calibrated molecular diffusion estimate and associated uncertainty to obtain an estimate with uncertainty due to bimolecular diffusion for the methane molar fraction as a function of altitude. Results show that the uncertainty in methane abundance due to molecular diffusion is in general small compared to eddy diffusion and the chemical kinetics description. However, methane abundance is most sensitive to uncertainty in molecular diffusion above 1200 km where the errors are nontrivial and could have important implications for scientific research based on diffusion models in this altitude range.

1/f model for long-time memory of the ocean surface temperature

NASA Astrophysics Data System (ADS)

Fraedrich, Klaus; Luksch, Ute; Blender, Richard

2004-09-01

The 1/f spectrum of the ocean surface temperature in the Atlantic and Pacific midlatitudes is explained by a simple vertical diffusion model with a shallow mixed layer on top of a deep ocean. The model is forced at the air-sea interface with the total surface heat flux from a 1000 year climate simulation. The analysis reveals the role of ocean advection and substantiates estimates of internal thermal diffusivities.

Regression-based model of skin diffuse reflectance for skin color analysis

NASA Astrophysics Data System (ADS)

Tsumura, Norimichi; Kawazoe, Daisuke; Nakaguchi, Toshiya; Ojima, Nobutoshi; Miyake, Yoichi

2008-11-01

A simple regression-based model of skin diffuse reflectance is developed based on reflectance samples calculated by Monte Carlo simulation of light transport in a two-layered skin model. This reflectance model includes the values of spectral reflectance in the visible spectra for Japanese women. The modified Lambert Beer law holds in the proposed model with a modified mean free path length in non-linear density space. The averaged RMS and maximum errors of the proposed model were 1.1 and 3.1%, respectively, in the above range.

The diffuse extreme-ultraviolet background - Constraints on hot coronal plasma

NASA Technical Reports Server (NTRS)

Paresce, F.; Stern, R.

1981-01-01

The Apollo-Soyuz data and data reported by Cash et al. (1976) have been reanalyzed in terms of both isothermal models and temperature distribution models. In the latter case, a power-law form is assumed for the relation between emission measure and temperature. A new upper limit on diffuse flux in the 20-73 eV band derived from Apollo-Soyuz observations made in the earth's shadow has been incorporated in the calculation. In the considered investigation the results of the new analysis are presented and the implications for the physical properties of the hot component of the interstellar medium are discussed. The analysis of the Berkeley extreme ultraviolet (EUV) diffuse background measurements using either isothermal or power law temperature distribution models for the emitting plasma indicates excellent qualitative agreement with hard X-ray data that suggest the sun to be immersed in a hot plasma that pervades most of space out to approximately 100 pc.

Nuclear quadrupole resonance lineshape analysis for different motional models: Stochastic Liouville approach

NASA Astrophysics Data System (ADS)

Kruk, D.; Earle, K. A.; Mielczarek, A.; Kubica, A.; Milewska, A.; Moscicki, J.

2011-12-01

A general theory of lineshapes in nuclear quadrupole resonance (NQR), based on the stochastic Liouville equation, is presented. The description is valid for arbitrary motional conditions (particularly beyond the valid range of perturbation approaches) and interaction strengths. It can be applied to the computation of NQR spectra for any spin quantum number and for any applied magnetic field. The treatment presented here is an adaptation of the "Swedish slow motion theory," [T. Nilsson and J. Kowalewski, J. Magn. Reson. 146, 345 (2000), 10.1006/jmre.2000.2125] originally formulated for paramagnetic systems, to NQR spectral analysis. The description is formulated for simple (Brownian) diffusion, free diffusion, and jump diffusion models. The two latter models account for molecular cooperativity effects in dense systems (such as liquids of high viscosity or molecular glasses). The sensitivity of NQR slow motion spectra to the mechanism of the motional processes modulating the nuclear quadrupole interaction is discussed.

Rumor Diffusion and Convergence during the 3.11 Earthquake: A Twitter Case Study

PubMed Central

Takayasu, Misako; Sato, Kazuya; Sano, Yukie; Yamada, Kenta; Miura, Wataru; Takayasu, Hideki

2015-01-01

We focus on Internet rumors and present an empirical analysis and simulation results of their diffusion and convergence during emergencies. In particular, we study one rumor that appeared in the immediate aftermath of the Great East Japan Earthquake on March 11, 2011, which later turned out to be misinformation. By investigating whole Japanese tweets that were sent one week after the quake, we show that one correction tweet, which originated from a city hall account, diffused enormously. We also demonstrate a stochastic agent-based model, which is inspired by contagion model of epidemics SIR, can reproduce observed rumor dynamics. Our model can estimate the rumor infection rate as well as the number of people who still believe in the rumor that cannot be observed directly. For applications, rumor diffusion sizes can be estimated in various scenarios by combining our model with the real data. PMID:25831122

Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer's disease cases.

PubMed

Taoka, Toshiaki; Masutani, Yoshitaka; Kawai, Hisashi; Nakane, Toshiki; Matsuoka, Kiwamu; Yasuno, Fumihiko; Kishimoto, Toshifumi; Naganawa, Shinji

2017-04-01

The activity of the glymphatic system is impaired in animal models of Alzheimer's disease (AD). We evaluated the activity of the human glymphatic system in cases of AD with a diffusion-based technique called diffusion tensor image analysis along the perivascular space (DTI-ALPS). Diffusion tensor images were acquired to calculate diffusivities in the x, y, and z axes of the plane of the lateral ventricle body in 31 patients. We evaluated the diffusivity along the perivascular spaces as well as projection fibers and association fibers separately, to acquire an index for diffusivity along the perivascular space (ALPS-index) and correlated them with the mini mental state examinations (MMSE) score. We found a significant negative correlation between diffusivity along the projection fibers and association fibers. We also observed a significant positive correlation between diffusivity along perivascular spaces shown as ALPS-index and the MMSE score, indicating lower water diffusivity along the perivascular space in relation to AD severity. Activity of the glymphatic system may be evaluated with diffusion images. Lower diffusivity along the perivascular space on DTI-APLS seems to reflect impairment of the glymphatic system. This method may be useful for evaluating the activity of the glymphatic system.

Diffusion in inhomogeneous polymer membranes

NASA Astrophysics Data System (ADS)

Kasargod, Sameer S.; Adib, Farhad; Neogi, P.

1995-10-01

The dual mode sorption solubility isotherms assume, and in instances Zimm-Lundberg analysis of the solubilities show, that glassy polymers are heterogeneous and that the distribution of the solute in the polymer is also inhomogeneous. Under some conditions, the heterogeneities cannot be represented as holes. A mathematical model describing diffusion in inhomogeneous polymer membranes is presented using Cahn and Hilliard's gradient theory. The fractional mass uptake is found to be proportional to the fourth root of time rather than the square root, predicted by Fickian diffusion. This type of diffusion is classified as pseudo-Fickian. The model is compared with one experimental result available. A negative value of the persistence factor is obtained and the results are interpreted.

Versatile Analysis of Single-Molecule Tracking Data by Comprehensive Testing against Monte Carlo Simulations

PubMed Central

Wieser, Stefan; Axmann, Markus; Schütz, Gerhard J.

2008-01-01

We propose here an approach for the analysis of single-molecule trajectories which is based on a comprehensive comparison of an experimental data set with multiple Monte Carlo simulations of the diffusion process. It allows quantitative data analysis, particularly whenever analytical treatment of a model is infeasible. Simulations are performed on a discrete parameter space and compared with the experimental results by a nonparametric statistical test. The method provides a matrix of p-values that assess the probability for having observed the experimental data at each setting of the model parameters. We show the testing approach for three typical situations observed in the cellular plasma membrane: i), free Brownian motion of the tracer, ii), hop diffusion of the tracer in a periodic meshwork of squares, and iii), transient binding of the tracer to slowly diffusing structures. By plotting the p-value as a function of the model parameters, one can easily identify the most consistent parameter settings but also recover mutual dependencies and ambiguities which are difficult to determine by standard fitting routines. Finally, we used the test to reanalyze previous data obtained on the diffusion of the glycosylphosphatidylinositol-protein CD59 in the plasma membrane of the human T24 cell line. PMID:18805933

Dynamics of controllably induced bruises assessed by diffuse reflectance spectroscopy and pulsed photothermal radiometry

NASA Astrophysics Data System (ADS)

Marin, Ana; Milanič, Matija; Verdel, Nina; Vidovič, Luka; Majaron, Boris

2018-02-01

Combination of diffuse reflectance spectroscopy (DRS) and pulsed photothermal radiometry (PPTR) was recently successfully used to study evolution of accidental traumatic bruises. Yet, accidental bruises introduce many unknowns into the evolution analysis and thus a more controllable and repeatable approach for bruising is desired. In this study, evolution of bruises induced by aluminum projectiles of known mass and velocity were studied by DRS and PPTR. Bruises were induced on volar forearm skin of two healthy volunteers. Inverse Monte Carlo including four-layer skin model, was used to analyze the DRS and PPTR data to determine skin chromophores, their concentrations and depths. For bruise analysis, a bruise model was constructed and evolved according to hemoglobin diffusion kinetics. Bruise analysis of PPTR signals yielded bruise evolution parameters, most importantly hemoglobin diffusion constant, hemoglobin decomposition time and blood pool depth. The study results show that chronological tracking of hemoglobin decomposition can be assessed by the combined DRS and PPTR technique on induced bruise. Parameters of individual bruises were compared and two trends in chronological behavior of hemoglobin decomposition time discerned. Changes in bruise diffuse reflectance spectra were noted. Induced bruise parameters, however, still showed some scatter and thus further research is needed to reduce bruise variability.

Quantitative interpretations of Visible-NIR reflectance spectra of blood.

PubMed

Serebrennikova, Yulia M; Smith, Jennifer M; Huffman, Debra E; Leparc, German F; García-Rubio, Luis H

2008-10-27

This paper illustrates the implementation of a new theoretical model for rapid quantitative analysis of the Vis-NIR diffuse reflectance spectra of blood cultures. This new model is based on the photon diffusion theory and Mie scattering theory that have been formulated to account for multiple scattering populations and absorptive components. This study stresses the significance of the thorough solution of the scattering and absorption problem in order to accurately resolve for optically relevant parameters of blood culture components. With advantages of being calibration-free and computationally fast, the new model has two basic requirements. First, wavelength-dependent refractive indices of the basic chemical constituents of blood culture components are needed. Second, multi-wavelength measurements or at least the measurements of characteristic wavelengths equal to the degrees of freedom, i.e. number of optically relevant parameters, of blood culture system are required. The blood culture analysis model was tested with a large number of diffuse reflectance spectra of blood culture samples characterized by an extensive range of the relevant parameters.

Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas.

PubMed

Xu, Boyan; Su, Lu; Wang, Zhenxiong; Fan, Yang; Gong, Gaolang; Zhu, Wenzhen; Gao, Peiyi; Gao, Jia-Hong

2018-04-17

Anomalous diffusion model has been introduced and shown to be beneficial in clinical applications. However, only the directionally averaged values of anomalous diffusion parameters were investigated, and the anisotropy of anomalous diffusion remains unexplored. The aim of this study was to demonstrate the feasibility of using anisotropy of anomalous diffusion for differentiating low- and high-grade cerebral gliomas. Diffusion MRI images were acquired from brain tumor patients and analyzed using the fractional motion (FM) model. Twenty-two patients with histopathologically confirmed gliomas were selected. An anisotropy metric for the FM-related parameters, including the Noah exponent (α) and the Hurst exponent (H), was introduced and their values were statistically compared between the low- and high-grade gliomas. Additionally, multivariate logistic regression analysis was performed to assess the combination of the anisotropy metric and the directionally averaged value for each parameter. The diagnostic performances for grading gliomas were evaluated using a receiver operating characteristic (ROC) analysis. The Hurst exponent H was more anisotropic in high-grade than in low-grade gliomas (P = 0.015), while no significant difference was observed for the anisotropy of α. The ROC analysis revealed that larger areas under the ROC curves were produced for the combination of α (1) and the combination of H (0.813) compared with the directionally averaged α (0.979) and H (0.594), indicating an improved performance for tumor differentiation. The anisotropy of anomalous diffusion can provide distinctive information and benefit the differentiation of low- and high-grade gliomas. The utility of anisotropic anomalous diffusion may have an improved effect for investigating pathological changes in tissues. Copyright © 2018 Elsevier Inc. All rights reserved.

Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer-aquitard complexes

USGS Publications Warehouse

Zhang, Yong; Green, Christopher T.; Tick, Geoffrey R.

2015-01-01

This study evaluates the role of the Peclet number as affected by molecular diffusion in transient anomalous transport, which is one of the major knowledge gaps in anomalous transport, by combining Monte Carlo simulations and stochastic model analysis. Two alluvial settings containing either short- or long-connected hydrofacies are generated and used as media for flow and transport modeling. Numerical experiments show that 1) the Peclet number affects both the duration of the power-law segment of tracer breakthrough curves (BTCs) and the transition rate from anomalous to Fickian transport by determining the solute residence time for a given low-permeability layer, 2) mechanical dispersion has a limited contribution to the anomalous characteristics of late-time transport as compared to molecular diffusion due to an almost negligible velocity in floodplain deposits, and 3) the initial source dimensions only enhance the power-law tail of the BTCs at short travel distances. A tempered stable stochastic (TSS) model is then applied to analyze the modeled transport. Applications show that the time-nonlocal parameters in the TSS model relate to the Peclet number, Pe. In particular, the truncation parameter in the TSS model increases nonlinearly with a decrease in Pe due to the decrease of the mean residence time, and the capacity coefficient increases with an increase in molecular diffusion which is probably due to the increase in the number of immobile particles. The above numerical experiments and stochastic analysis therefore reveal that the Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer–aquitard complexes.

Determination of kinetic data for soot oxidation: Modeling of competition between oxygen diffusion and reaction during thermogravimetric analysis

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

Gilot, P.; Bonnefoy, F.; Marcuccilli, F.

1993-10-01

Kinetic data concerning carbon black oxidation in the temperature range between 600 and 900 C have been obtained using thermogravimetric analysis. Modeling of diffusion in a boundary layer above the pan and inside the porous medium coupled to oxygen reaction with carbon black is necessary to obtain kinetic constants as a function of temperature. These calculations require the knowledge of the oxidation rate at a given constant temperature as a function of the initial mass loading m[sub o]. This oxidation rate, expressed in milligrams of soot consumed per second and per milligram of initial soot loading, decreases when m[sub o]more » increases, in agreement with a reaction in an intermediary regime where the kinetics and the oxygen diffusion operate. The equivalent diffusivity of oxygen inside the porous medium is evaluated assuming two degrees of porosity: between soot aggregates and inside each aggregate. Below 700 C an activation energy of about 103 kJ/mol can be related to a combustion reaction probably kinetically controlled. Beyond 700 C the activation energy of about 20 kJ/ mol corresponds to a reaction essentially controlled by oxygen diffusion leading to a constant density oxidation with oxygen consumption at or near the particle surface. To validate these data, they are used in the modeling of a Diesel particulate trap regeneration. In this particular case, the oxidizing flux is forced across the carbon black deposit, oxygen diffusion being insignificant. A good agreement between experimental results and model predictions is obtained, proving the rate constants validity.« less

Atomistic models of vacancy-mediated diffusion in silicon

NASA Astrophysics Data System (ADS)

Dunham, Scott T.; Wu, Can Dong

1995-08-01

Vacancy-mediated diffusion of dopants in silicon is investigated using Monte Carlo simulations of hopping diffusion, as well as analytic approximations based on atomistic considerations. Dopant/vacancy interaction potentials are assumed to extend out to third-nearest neighbor distances, as required for pair diffusion theories. Analysis focusing on the third-nearest neighbor sites as bridging configurations for uncorrelated hops leads to an improved analytic model for vacancy-mediated dopant diffusion. The Monte Carlo simulations of vacancy motion on a doped silicon lattice verify the analytic results for moderate doping levels. For very high doping (≳2×1020 cm-3) the simulations show a very rapid increase in pair diffusivity due to interactions of vacancies with more than one dopant atom. This behavior has previously been observed experimentally for group IV and V atoms in silicon [Nylandsted Larsen et al., J. Appl. Phys. 73, 691 (1993)], and the simulations predict both the point of onset and doping dependence of the experimentally observed diffusivity enhancement.

Pepsin diffusion in dairy gels depends on casein concentration and microstructure.

PubMed

Thévenot, J; Cauty, C; Legland, D; Dupont, D; Floury, J

2017-05-15

Fundamental knowledge of gastric digestion had only focused on acid diffusion from the gastric fluid, but no data are available for pepsin diffusion. Using fluorescence recovery after photobleaching technique, diffusion coefficients D of fluorescein isothiocyanate (FITC)-pepsin were measured in rennet gels across a range of casein concentrations allowing to form networks of protein aggregates with different structures. To investigate the microstructural parameters of native gels, electron microscopy image analysis were performed and qualitatively related to diffusion behavior of FITC-pepsin in these dairy gels. This study is the first report on quantification of pepsin diffusion in dairy product. Pepsin diffusion in rennet gels depends on casein concentration and microstructure. Models of polymer science can be used to assess D in dairy gel. Such data should be confronted with pepsin activity in acidic environment, and will be very useful as input parameters in mathematical models of food degradation in the human stomach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nondestructive study of corrosion by the analysis of diffused light

NASA Astrophysics Data System (ADS)

Hogert, Elsa N.; Landau, Monica R.; Marengo, Jose A.; Ruiz Gale, Maria F.; Gaggioli, Nestor G.; Paiva, Raul D., Jr.; Soga, Diogo; Muramatsu, Mikiya

1999-07-01

This work describes the application of mean intensity diffusion analysis to detect and analyze metallic corrosion phenomena. We present some new results in the characterization of the corrosion process using a model based in electroerosion phenomena. Valuable information is provided about surface microrelief changes, which is also useful for numerous engineering applications. The quality of our results supports the idea that this technique can contribute to a better analysis of corrosion processes, in particular in real time.

Analysis of Three-dimension Viscous Flow in the Model Axial Compressor Stage K1002L

NASA Astrophysics Data System (ADS)

Tribunskaia, K.; Kozhukhov, Y. V.

2017-08-01

The main investigation subject considered in this paper is axial compressor model stage K1002L. Three simulation models were designed: Scheme 1 - inlet stage model consisting of IGV (Inlet Guide Vane), rotor and diffuser; Scheme 2 - two-stage model: IGV, first-stage rotor, first-stage diffuser, second-stage rotor, EGV (Exit Guide Vane); Scheme 3 - full-round model: IGV, rotor, diffuser. Numerical investigation of the model stage was held for four circumferential velocities at the outer diameter (Uout=125,160,180,210 m/s) within the range of flow coefficient: ϕ = 0.4 - 0.6. The computational domain was created with ANSYS CFX Workbench. According to simulation results, there were constructed aerodynamic characteristic curves of adiabatic efficiency and the adiabatic head coefficient calculated for total parameters were compared with data from the full-scale test received at the Central Boiler and Turbine Institution (CBTI), thus, verification of the calculated data was carried out. Moreover, there were conducted the following studies: comparison of aerodynamic characteristics of the schemes 1, 2; comparison of the sector and full-round models. The analysis and conclusions are supplemented by gas-dynamic method calculation for axial compressor stages.

Anomalous Diffusion Measured by a Twice-Refocused Spin Echo Pulse Sequence: Analysis Using Fractional Order Calculus

PubMed Central

2011-01-01

Purpose To theoretically develop and experimentally validate a formulism based on a fractional order calculus (FC) diffusion model to characterize anomalous diffusion in brain tissues measured with a twice-refocused spin-echo (TRSE) pulse sequence. Materials and Methods The FC diffusion model is the fractional order generalization of the Bloch-Torrey equation. Using this model, an analytical expression was derived to describe the diffusion-induced signal attenuation in a TRSE pulse sequence. To experimentally validate this expression, a set of diffusion-weighted (DW) images was acquired at 3 Tesla from healthy human brains using a TRSE sequence with twelve b-values ranging from 0 to 2,600 s/mm2. For comparison, DW images were also acquired using a Stejskal-Tanner diffusion gradient in a single-shot spin-echo echo planar sequence. For both datasets, a Levenberg-Marquardt fitting algorithm was used to extract three parameters: diffusion coefficient D, fractional order derivative in space β, and a spatial parameter μ (in units of μm). Using adjusted R-squared values and standard deviations, D, β and μ values and the goodness-of-fit in three specific regions of interest (ROI) in white matter, gray matter, and cerebrospinal fluid were evaluated for each of the two datasets. In addition, spatially resolved parametric maps were assessed qualitatively. Results The analytical expression for the TRSE sequence, derived from the FC diffusion model, accurately characterized the diffusion-induced signal loss in brain tissues at high b-values. In the selected ROIs, the goodness-of-fit and standard deviations for the TRSE dataset were comparable with the results obtained from the Stejskal-Tanner dataset, demonstrating the robustness of the FC model across multiple data acquisition strategies. Qualitatively, the D, β, and μ maps from the TRSE dataset exhibited fewer artifacts, reflecting the improved immunity to eddy currents. Conclusion The diffusion-induced signal attenuation in a TRSE pulse sequence can be described by an FC diffusion model at high b-values. This model performs equally well for data acquired from the human brain tissues with a TRSE pulse sequence or a conventional Stejskal-Tanner sequence. PMID:21509877

Anomalous diffusion measured by a twice-refocused spin echo pulse sequence: analysis using fractional order calculus.

PubMed

Gao, Qing; Srinivasan, Girish; Magin, Richard L; Zhou, Xiaohong Joe

2011-05-01

To theoretically develop and experimentally validate a formulism based on a fractional order calculus (FC) diffusion model to characterize anomalous diffusion in brain tissues measured with a twice-refocused spin-echo (TRSE) pulse sequence. The FC diffusion model is the fractional order generalization of the Bloch-Torrey equation. Using this model, an analytical expression was derived to describe the diffusion-induced signal attenuation in a TRSE pulse sequence. To experimentally validate this expression, a set of diffusion-weighted (DW) images was acquired at 3 Tesla from healthy human brains using a TRSE sequence with twelve b-values ranging from 0 to 2600 s/mm(2). For comparison, DW images were also acquired using a Stejskal-Tanner diffusion gradient in a single-shot spin-echo echo planar sequence. For both datasets, a Levenberg-Marquardt fitting algorithm was used to extract three parameters: diffusion coefficient D, fractional order derivative in space β, and a spatial parameter μ (in units of μm). Using adjusted R-squared values and standard deviations, D, β, and μ values and the goodness-of-fit in three specific regions of interest (ROIs) in white matter, gray matter, and cerebrospinal fluid, respectively, were evaluated for each of the two datasets. In addition, spatially resolved parametric maps were assessed qualitatively. The analytical expression for the TRSE sequence, derived from the FC diffusion model, accurately characterized the diffusion-induced signal loss in brain tissues at high b-values. In the selected ROIs, the goodness-of-fit and standard deviations for the TRSE dataset were comparable with the results obtained from the Stejskal-Tanner dataset, demonstrating the robustness of the FC model across multiple data acquisition strategies. Qualitatively, the D, β, and μ maps from the TRSE dataset exhibited fewer artifacts, reflecting the improved immunity to eddy currents. The diffusion-induced signal attenuation in a TRSE pulse sequence can be described by an FC diffusion model at high b-values. This model performs equally well for data acquired from the human brain tissues with a TRSE pulse sequence or a conventional Stejskal-Tanner sequence. Copyright © 2011 Wiley-Liss, Inc.

A generalized reaction diffusion model for spatial structure formed by motile cells.

PubMed

Ochoa, F L

1984-01-01

A non-linear stability analysis using a multi-scale perturbation procedure is carried out on a model of a generalized reaction diffusion mechanism which involves only a single equation but which nevertheless exhibits bifurcation to non-uniform states. The patterns generated by this model by variation in a parameter related to the scalar dimensions of domain of definition, indicate its capacity to represent certain key morphogenetic features of multicellular systems formed by motile cells.

A Diffusive-Particle Theory of Free Recall

PubMed Central

Fumarola, Francesco

2017-01-01

Diffusive models of free recall have been recently introduced in the memory literature, but their potential remains largely unexplored. In this paper, a diffusive model of short-term verbal memory is considered, in which the psychological state of the subject is encoded as the instantaneous position of a particle diffusing over a semantic graph. The model is particularly suitable for studying the dependence of free-recall observables on the semantic properties of the words to be recalled. Besides predicting some well-known experimental features (forward asymmetry, semantic clustering, word-length effect), a novel prediction is obtained on the relationship between the contiguity effect and the syllabic length of words; shorter words, by way of their wider semantic range, are predicted to be characterized by stronger forward contiguity. A fresh analysis of archival free-recall data allows to confirm this prediction. PMID:29085521

Exits in order: How crowding affects particle lifetimes

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

Penington, Catherine J.; Simpson, Matthew J.; Baker, Ruth E.

2016-06-28

Diffusive processes are often represented using stochastic random walk frameworks. The amount of time taken for an individual in a random walk to intersect with an absorbing boundary is a fundamental property that is often referred to as the particle lifetime, or the first passage time. The mean lifetime of particles in a random walk model of diffusion is related to the amount of time required for the diffusive process to reach a steady state. Mathematical analysis describing the mean lifetime of particles in a standard model of diffusion without crowding is well known. However, the lifetime of agents inmore » a random walk with crowding has received much less attention. Since many applications of diffusion in biology and biophysics include crowding effects, here we study a discrete model of diffusion that incorporates crowding. Using simulations, we show that crowding has a dramatic effect on agent lifetimes, and we derive an approximate expression for the mean agent lifetime that includes crowding effects. Our expression matches simulation results very well, and highlights the importance of crowding effects that are sometimes overlooked.« less

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.

Structure-correlated diffusion anisotropy in nanoporous channel networks by Monte Carlo simulations and percolation theory

NASA Astrophysics Data System (ADS)

Kondrashova, Daria; Valiullin, Rustem; Kärger, Jörg; Bunde, Armin

2017-07-01

Nanoporous silicon consisting of tubular pores imbedded in a silicon matrix has found many technological applications and provides a useful model system for studying phase transitions under confinement. Recently, a model for mass transfer in these materials has been elaborated [Kondrashova et al., Sci. Rep. 7, 40207 (2017)], which assumes that adjacent channels can be connected by "bridges" (with probability pbridge) which allows diffusion perpendicular to the channels. Along the channels, diffusion can be slowed down by "necks" which occur with probability pneck. In this paper we use Monte-Carlo simulations to study diffusion along the channels and perpendicular to them, as a function of pbridge and pneck, and find remarkable correlations between the diffusivities in longitudinal and radial directions. For clarifying the diffusivity in radial direction, which is governed by the concentration of bridges, we applied percolation theory. We determine analytically how the critical concentration of bridges depends on the size of the system and show that it approaches zero in the thermodynamic limit. Our analysis suggests that the critical properties of the model, including the diffusivity in radial direction, are in the universality class of two-dimensional lattice percolation, which is confirmed by our numerical study.

High Temperature Degradation Mechanisms in Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Cunningham, Ronan A.

1996-01-01

Polymer matrix composites are increasingly used in demanding structural applications in which they may be exposed to harsh environments. The durability of such materials is a major concern, potentially limiting both the integrity of the structures and their useful lifetimes. The goal of the current investigation is to develop a mechanism-based model of the chemical degradation which occurs, such that given the external chemical environment and temperatures throughout the laminate, laminate geometry, and ply and/or constituent material properties, we can calculate the concentration of diffusing substances and extent of chemical degradation as functions of time and position throughout the laminate. This objective is met through the development and use of analytical models, coupled to an analysis-driven experimental program which offers both quantitative and qualitative information on the degradation mechanism. Preliminary analyses using a coupled diffusion/reaction model are used to gain insight into the physics of the degradation mechanisms and to identify crucial material parameters. An experimental program is defined based on the results of the preliminary analysis which allows the determination of the necessary material coefficients. Thermogravimetric analyses are carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. Powdered samples are used to eliminate diffusion effects. Tests in both inert and oxidative environments allow the separation of thermal and oxidative contributions to specimen mass loss. The concentration dependency of the oxidative reactions is determined from the tests in pure oxygen. Short term isothermal tests at different temperatures are carried out on neat resin and unidirectional macroscopic specimens to identify diffusion effects. Mass loss, specimen shrinkage, the formation of degraded surface layers and surface cracking are recorded as functions of exposure time. Geometry effects in the neat resin, and anisotropic diffusion effects in the composites, are identified through the use of specimens with different aspect ratios. The data is used with the model to determine reaction coefficients and effective diffusion coefficients. The empirical and analytical correlations confirm the preliminary model results which suggest that mass loss at lower temperatures is dominated by oxidative reactions and that these reaction are limited by diffusion of oxygen from the surface. The mechanism-based model is able to successfully capture the basic physics of the degradation phenomena under a wide range of test conditions. The analysis-based test design is successful in separating out oxidative, thermal, and diffusion effects to allow the determination of material coefficients. This success confirms the basic picture of the process; however, a more complete understanding of some aspects of the physics are required before truly predictive capability can be achieved.

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.

LATERAL HEAT FLOW INFRARED THERMOGRAPHY FOR THICKNESS INDEPENDENT DETERMINATION OF THERMAL DIFFUSIVITY IN CFRP

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

Tralshawala, Nilesh; Howard, Don; Knight, Bryon

2008-02-28

In conventional infrared thermography, determination of thermal diffusivity requires thickness information. Recently GE has been experimenting with the use of lateral heat flow to determine thermal diffusivity without thickness information. This work builds on previous work at NASA Langley and Wayne State University but we incorporate thermal time of flight (tof) analysis rather than curve fitting to obtain quantitative information. We have developed appropriate theoretical models and a tof based data analysis framework to experimentally determine all components of thermal diffusivity from the time-temperature measurements. Initial validation was carried out using finite difference simulations. Experimental validation was done using anisotropicmore » carbon fiber reinforced polymer (CFRP) composites. We found that in the CFRP samples used, the in-plane component of diffusivity is about eight times larger than the through-thickness component.« less

A thermodynamically consistent model of magneto-elastic materials under diffusion at large strains and its analysis

NASA Astrophysics Data System (ADS)

Roubíček, Tomáš; Tomassetti, Giuseppe

2018-06-01

A theory of elastic magnets is formulated under possible diffusion and heat flow governed by Fick's and Fourier's laws in the deformed (Eulerian) configuration, respectively. The concepts of nonlocal nonsimple materials and viscous Cahn-Hilliard equations are used. The formulation of the problem uses Lagrangian (reference) configuration while the transport processes are pulled back. Except the static problem, the demagnetizing energy is ignored and only local non-self-penetration is considered. The analysis as far as existence of weak solutions of the (thermo) dynamical problem is performed by a careful regularization and approximation by a Galerkin method, suggesting also a numerical strategy. Either ignoring or combining particular aspects, the model has numerous applications as ferro-to-paramagnetic transformation in elastic ferromagnets, diffusion of solvents in polymers possibly accompanied by magnetic effects (magnetic gels), or metal-hydride phase transformation in some intermetallics under diffusion of hydrogen accompanied possibly by magnetic effects (and in particular ferro-to-antiferromagnetic phase transformation), all in the full thermodynamical context under large strains.

A novel rumor diffusion model considering the effect of truth in online social media

NASA Astrophysics Data System (ADS)

Sun, Ling; Liu, Yun; Zeng, Qing-An; Xiong, Fei

2015-12-01

In this paper, we propose a model to investigate how truth affects rumor diffusion in online social media. Our model reveals a relation between rumor and truth — namely, when a rumor is diffusing, the truth about the rumor also diffuses with it. Two patterns of the agents used to identify rumor, self-identification and passive learning are taken into account. Combining theoretical proof and simulation analysis, we find that the threshold value of rumor diffusion is negatively correlated to the connectivity between nodes in the network and the probability β of agents knowing truth. Increasing β can reduce the maximum density of the rumor spreaders and slow down the generation speed of new rumor spreaders. On the other hand, we conclude that the best rumor diffusion strategy must balance the probability of forwarding rumor and the probability of agents losing interest in the rumor. High spread rate λ of rumor would lead to a surge in truth dissemination which will greatly limit the diffusion of rumor. Furthermore, in the case of unknown λ, increasing β can effectively reduce the maximum proportion of agents who do not know the truth, but cannot narrow the rumor diffusion range in a certain interval of β.

Computational analysis of the roles of biochemical reactions in anomalous diffusion dynamics

NASA Astrophysics Data System (ADS)

Naruemon, Rueangkham; Charin, Modchang

2016-04-01

Most biochemical processes in cells are usually modeled by reaction-diffusion (RD) equations. In these RD models, the diffusive process is assumed to be Gaussian. However, a growing number of studies have noted that intracellular diffusion is anomalous at some or all times, which may result from a crowded environment and chemical kinetics. This work aims to computationally study the effects of chemical reactions on the diffusive dynamics of RD systems by using both stochastic and deterministic algorithms. Numerical method to estimate the mean-square displacement (MSD) from a deterministic algorithm is also investigated. Our computational results show that anomalous diffusion can be solely due to chemical reactions. The chemical reactions alone can cause anomalous sub-diffusion in the RD system at some or all times. The time-dependent anomalous diffusion exponent is found to depend on many parameters, including chemical reaction rates, reaction orders, and chemical concentrations. Project supported by the Thailand Research Fund and Mahidol University (Grant No. TRG5880157), the Thailand Center of Excellence in Physics (ThEP), CHE, Thailand, and the Development Promotion of Science and Technology.

Analysis of Molecular Movement Reveals Latticelike Obstructions to Diffusion in Heart Muscle Cells

PubMed Central

Illaste, Ardo; Laasmaa, Martin; Peterson, Pearu; Vendelin, Marko

2012-01-01

Intracellular diffusion in muscle cells is known to be restricted. Although characteristics and localization of these restrictions is yet to be elucidated, it has been established that ischemia-reperfusion injury reduces the overall diffusion restriction. Here we apply an extended version of raster image correlation spectroscopy to determine directional anisotropy and coefficients of diffusion in rat cardiomyocytes. Our experimental results indicate that diffusion of a smaller molecule (1127 MW fluorescently labeled ATTO633-ATP) is restricted more than that of a larger one (10,000 MW Alexa647-dextran), when comparing diffusion in cardiomyocytes to that in solution. We attempt to provide a resolution to this counterintuitive result by applying a quantitative stochastic model of diffusion. Modeling results suggest the presence of periodic intracellular barriers situated ∼1 μm apart having very low permeabilities and a small effect of molecular crowding in volumes between the barriers. Such intracellular structuring could restrict diffusion of molecules of energy metabolism, reactive oxygen species, and apoptotic signals, enacting a significant role in normally functioning cardiomyocytes as well as in pathological conditions of the heart. PMID:22385844

Diffusion Kurtosis Imaging Detects Microstructural Alterations in Brain of α-Synuclein Overexpressing Transgenic Mouse Model of Parkinson's Disease: A Pilot Study.

PubMed

Khairnar, Amit; Latta, Peter; Drazanova, Eva; Ruda-Kucerova, Jana; Szabó, Nikoletta; Arab, Anas; Hutter-Paier, Birgit; Havas, Daniel; Windisch, Manfred; Sulcova, Alexandra; Starcuk, Zenon; Rektorova, Irena

2015-11-01

Evidence suggests that accumulation and aggregation of α-synuclein contribute to the pathogenesis of Parkinson's disease (PD). The aim of this study was to evaluate whether diffusion kurtosis imaging (DKI) will provide a sensitive tool for differentiating between α-synuclein-overexpressing transgenic mouse model of PD (TNWT-61) and wild-type (WT) littermates. This experiment was designed as a proof-of-concept study and forms a part of a complex protocol and ongoing translational research. Nine-month-old TNWT-61 mice and age-matched WT littermates underwent behavioral tests to monitor motor impairment and MRI scanning using 9.4 Tesla system in vivo. Tract-based spatial statistics (TBSS) and the DKI protocol were used to compare the whole brain white matter of TNWT-61 and WT mice. In addition, region of interest (ROI) analysis was performed in gray matter regions such as substantia nigra, striatum, hippocampus, sensorimotor cortex, and thalamus known to show higher accumulation of α-synuclein. For the ROI analysis, both DKI (6 b-values) protocol and conventional (2 b-values) diffusion tensor imaging (cDTI) protocol were used. TNWT-61 mice showed significant impairment of motor coordination. With the DKI protocol, mean, axial, and radial kurtosis were found to be significantly elevated, whereas mean and radial diffusivity were decreased in the TNWT-61 group compared to that in the WT controls with both TBSS and ROI analysis. With the cDTI protocol, the ROI analysis showed decrease in all diffusivity parameters in TNWT-61 mice. The current study provides evidence that DKI by providing both kurtosis and diffusivity parameters gives unique information that is complementary to cDTI for in vivo detection of pathological changes that underlie PD-like symptomatology in TNWT-61 mouse model of PD. This result is a crucial step in search for a candidate diagnostic biomarker with translational potential and relevance for human studies.

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.

Load Diffusion in Composite and Smart Structures

NASA Technical Reports Server (NTRS)

Horgan, Cornelius O.; Ambur, D. (Technical Monitor); Nemeth, M. P. (Technical Monitor)

2003-01-01

The research carried out here builds on our previous NASA supported research on the general topic of edge effects and load diffusion in composite structures. Further fundamental solid mechanics studies were carried out to provide a basis for assessing the complicated modeling necessary for the multi-functional large scale structures used by NASA. An understanding of the fundamental mechanisms of load diffusion in composite subcomponents is essential in developing primary composite structures. Some specific problems recently considered were those of end effects in smart materials and structures, study of the stress response of pressurized linear piezoelectric cylinders for both static and steady rotating configurations, an analysis of the effect of pre-stressing and pre-polarization on the decay of end effects in piezoelectric solids and investigation of constitutive models for hardening rubber-like materials. Our goal in the study of load diffusion is the development of readily applicable results for the decay lengths in terms of non-dimensional material and geometric parameters. Analytical models of load diffusion behavior are extremely valuable in building an intuitive base for developing refined modeling strategies and assessing results from finite element analyses.

Analytical modeling of operating characteristics of premixing-prevaporizing fuel-air mixing passages. Volume 1: Analysis and results

NASA Technical Reports Server (NTRS)

Anderson, O. L.; Chiappetta, L. M.; Edwards, D. E.; Mcvey, J. B.

1982-01-01

A model for predicting the distribution of liquid fuel droplets and fuel vapor in premixing-prevaporizing fuel-air mixing passages of the direct injection type is reported. This model consists of three computer programs; a calculation of the two dimensional or axisymmetric air flow field neglecting the effects of fuel; a calculation of the three dimensional fuel droplet trajectories and evaporation rates in a known, moving air flow; a calculation of fuel vapor diffusing into a moving three dimensional air flow with source terms dependent on the droplet evaporation rates. The fuel droplets are treated as individual particle classes each satisfying Newton's law, a heat transfer, and a mass transfer equation. This fuel droplet model treats multicomponent fuels and incorporates the physics required for the treatment of elastic droplet collisions, droplet shattering, droplet coalescence and droplet wall interactions. The vapor diffusion calculation treats three dimensional, gas phase, turbulent diffusion processes. The analysis includes a model for the autoignition of the fuel air mixture based upon the rate of formation of an important intermediate chemical species during the preignition period.

Monte Carlo analysis of neutron diffuse scattering data

NASA Astrophysics Data System (ADS)

Goossens, D. J.; Heerdegen, A. P.; Welberry, T. R.; Gutmann, M. J.

2006-11-01

This paper presents a discussion of a technique developed for the analysis of neutron diffuse scattering data. The technique involves processing the data into reciprocal space sections and modelling the diffuse scattering in these sections. A Monte Carlo modelling approach is used in which the crystal energy is a function of interatomic distances between molecules and torsional rotations within molecules. The parameters of the model are the spring constants governing the interactions, as they determine the correlations which evolve when the model crystal structure is relaxed at finite temperature. When the model crystal has reached equilibrium its diffraction pattern is calculated and a χ2 goodness-of-fit test between observed and calculated data slices is performed. This allows a least-squares refinement of the fit parameters and so automated refinement can proceed. The first application of this methodology to neutron, rather than X-ray, data is outlined. The sample studied was deuterated benzil, d-benzil, C14D10O2, for which data was collected using time-of-flight Laue diffraction on SXD at ISIS.

Mathematical analysis of a sharp-diffuse interfaces model for seawater intrusion

NASA Astrophysics Data System (ADS)

Choquet, C.; Diédhiou, M. M.; Rosier, C.

2015-10-01

We consider a new model mixing sharp and diffuse interface approaches for seawater intrusion phenomena in free aquifers. More precisely, a phase field model is introduced in the boundary conditions on the virtual sharp interfaces. We thus include in the model the existence of diffuse transition zones but we preserve the simplified structure allowing front tracking. The three-dimensional problem then reduces to a two-dimensional model involving a strongly coupled system of partial differential equations of parabolic type describing the evolution of the depths of the two free surfaces, that is the interface between salt- and freshwater and the water table. We prove the existence of a weak solution for the model completed with initial and boundary conditions. We also prove that the depths of the two interfaces satisfy a coupled maximum principle.

Quantitative model of price diffusion and market friction based on trading as a mechanistic random process.

PubMed

Daniels, Marcus G; Farmer, J Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

2003-03-14

We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process

NASA Astrophysics Data System (ADS)

Daniels, Marcus G.; Farmer, J. Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

2003-03-01

We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

Effect of Thermal Diffusivity on the Detectability of TNDE

NASA Technical Reports Server (NTRS)

Zhao, Junduo; Chu, Tsuchin; Russell, Samuel S.

2000-01-01

The effect of thermal diffusively on the defect detectability in Carbon/Epoxy composite panels by transient thermography is presented in this paper. A series of Finite Element Models were constructed and analyzed to simulate the transient heat transfer phenomenon during Thermographic Non-destructive Evaluation (TNDE) of composite panels with square defects. Six common carbon fibers were considered. The models were built for composites with various combinations of fibers and volumetric ratios. Finite Element Analysis of these models showed the trends of the detectable range and the maximum thermal contrast versus the thermal diffusivity of various composites. Additionally, the trends of defect size to depth ratio and the thermal contrast has been investigated.

Single-particle trajectories reveal two-state diffusion-kinetics of hOGG1 proteins on DNA.

PubMed

Vestergaard, Christian L; Blainey, Paul C; Flyvbjerg, Henrik

2018-03-16

We reanalyze trajectories of hOGG1 repair proteins diffusing on DNA. A previous analysis of these trajectories with the popular mean-squared-displacement approach revealed only simple diffusion. Here, a new optimal estimator of diffusion coefficients reveals two-state kinetics of the protein. A simple, solvable model, in which the protein randomly switches between a loosely bound, highly mobile state and a tightly bound, less mobile state is the simplest possible dynamic model consistent with the data. It yields accurate estimates of hOGG1's (i) diffusivity in each state, uncorrupted by experimental errors arising from shot noise, motion blur and thermal fluctuations of the DNA; (ii) rates of switching between states and (iii) rate of detachment from the DNA. The protein spends roughly equal time in each state. It detaches only from the loosely bound state, with a rate that depends on pH and the salt concentration in solution, while its rates for switching between states are insensitive to both. The diffusivity in the loosely bound state depends primarily on pH and is three to ten times higher than in the tightly bound state. We propose and discuss some new experiments that take full advantage of the new tools of analysis presented here.

Accurate determination of the diffusion coefficient of proteins by Fourier analysis with whole column imaging detection.

PubMed

Zarabadi, Atefeh S; Pawliszyn, Janusz

2015-02-17

Analysis in the frequency domain is considered a powerful tool to elicit precise information from spectroscopic signals. In this study, the Fourier transformation technique is employed to determine the diffusion coefficient (D) of a number of proteins in the frequency domain. Analytical approaches are investigated for determination of D from both experimental and data treatment viewpoints. The diffusion process is modeled to calculate diffusion coefficients based on the Fourier transformation solution to Fick's law equation, and its results are compared to time domain results. The simulations characterize optimum spatial and temporal conditions and demonstrate the noise tolerance of the method. The proposed model is validated by its application for the electropherograms from the diffusion path of a set of proteins. Real-time dynamic scanning is conducted to monitor dispersion by employing whole column imaging detection technology in combination with capillary isoelectric focusing (CIEF) and the imaging plug flow (iPF) experiment. These experimental techniques provide different peak shapes, which are utilized to demonstrate the Fourier transformation ability in extracting diffusion coefficients out of irregular shape signals. Experimental results confirmed that the Fourier transformation procedure substantially enhanced the accuracy of the determined values compared to those obtained in the time domain.

Anomalous Extracellular Diffusion in Rat Cerebellum

PubMed Central

Xiao, Fanrong; Hrabe, Jan; Hrabetova, Sabina

2015-01-01

Extracellular space (ECS) is a major channel transporting biologically active molecules and drugs in the brain. Diffusion-mediated transport of these substances is hindered by the ECS structure but the microscopic basis of this hindrance is not fully understood. One hypothesis proposes that the hindrance originates in large part from the presence of dead-space (DS) microdomains that can transiently retain diffusing molecules. Because previous theoretical and modeling work reported an initial period of anomalous diffusion in similar environments, we expected that brain regions densely populated by DS microdomains would exhibit anomalous extracellular diffusion. Specifically, we targeted granular layers (GL) of rat and turtle cerebella that are populated with large and geometrically complex glomeruli. The integrative optical imaging (IOI) method was employed to evaluate diffusion of fluorophore-labeled dextran (MW 3000) in GL, and the IOI data analysis was adapted to quantify the anomalous diffusion exponent dw from the IOI records. Diffusion was significantly anomalous in rat GL, where dw reached 4.8. In the geometrically simpler turtle GL, dw was elevated but not robustly anomalous (dw = 2.6). The experimental work was complemented by numerical Monte Carlo simulations of anomalous ECS diffusion in several three-dimensional tissue models containing glomeruli-like structures. It demonstrated that both the duration of transiently anomalous diffusion and the anomalous exponent depend on the size of model glomeruli and the degree of their wrapping. In conclusion, we have found anomalous extracellular diffusion in the GL of rat cerebellum. This finding lends support to the DS microdomain hypothesis. Transiently anomalous diffusion also has a profound effect on the spatiotemporal distribution of molecules released into the ECS, especially at diffusion distances on the order of a few cell diameters, speeding up short-range diffusion-mediated signals in less permeable structures. PMID:25954895

Sparse and Adaptive Diffusion Dictionary (SADD) for recovering intra-voxel white matter structure.

PubMed

Aranda, Ramon; Ramirez-Manzanares, Alonso; Rivera, Mariano

2015-12-01

On the analysis of the Diffusion-Weighted Magnetic Resonance Images, multi-compartment models overcome the limitations of the well-known Diffusion Tensor model for fitting in vivo brain axonal orientations at voxels with fiber crossings, branching, kissing or bifurcations. Some successful multi-compartment methods are based on diffusion dictionaries. The diffusion dictionary-based methods assume that the observed Magnetic Resonance signal at each voxel is a linear combination of the fixed dictionary elements (dictionary atoms). The atoms are fixed along different orientations and diffusivity profiles. In this work, we present a sparse and adaptive diffusion dictionary method based on the Diffusion Basis Functions Model to estimate in vivo brain axonal fiber populations. Our proposal overcomes the following limitations of the diffusion dictionary-based methods: the limited angular resolution and the fixed shapes for the atom set. We propose to iteratively re-estimate the orientations and the diffusivity profile of the atoms independently at each voxel by using a simplified and easier-to-solve mathematical approach. As a result, we improve the fitting of the Diffusion-Weighted Magnetic Resonance signal. The advantages with respect to the former Diffusion Basis Functions method are demonstrated on the synthetic data-set used on the 2012 HARDI Reconstruction Challenge and in vivo human data. We demonstrate that improvements obtained in the intra-voxel fiber structure estimations benefit brain research allowing to obtain better tractography estimations. Hence, these improvements result in an accurate computation of the brain connectivity patterns. Copyright © 2015 Elsevier B.V. All rights reserved.

Is there evidence for more than two diffusion components in abdominal organs? - A magnetic resonance imaging study in healthy volunteers.

PubMed

Wurnig, Moritz C; Germann, Manon; Boss, Andreas

2018-01-01

The most commonly applied model for the description of diffusion-weighted imaging (DWI) data in perfused organs is bicompartmental intravoxel incoherent motion (IVIM) analysis. In this study, we assessed the ground truth of underlying diffusion components in healthy abdominal organs using an extensive DWI protocol and subsequent computation of apparent diffusion coefficient 'spectra', similar to the computation of previously described T 2 relaxation spectra. Diffusion datasets of eight healthy subjects were acquired in a 3-T magnetic resonance scanner using 68 different b values during free breathing (equidistantly placed in the range 0-1005 s/mm 2 ). Signal intensity curves as a function of the b value were analyzed in liver, spleen and kidneys using non-negative least-squares fitting to a distribution of decaying exponential functions with minimum amplitude energy regularization. In all assessed organs, the typical slow- and fast-diffusing components of the IVIM model were detected [liver: true diffusion D = (1.26 ± 0.01) × 10 -3 mm 2 /s, pseudodiffusion D* = (270 ± 44) × 10 -3 mm 2 /s; kidney cortex: D = (2.26 ± 0.07) × 10 -3 mm 2 /s, D* = (264 ± 78) × 10 -3 mm 2 /s; kidney medulla: D = (1.57 ± 0.28) × 10 -3 mm 2 /s, D* = (168 ± 18) × 10 -3 mm 2 /s; spleen: D = (0.91 ± 0.01) × 10 -3 mm 2 /s, D* = (69.8 ± 0.50) × 10 -3 mm 2 /s]. However, in the liver and kidney, a third component between D and D* was found [liver: D' = (43.8 ± 5.9) × 10 -3 mm 2 /s; kidney cortex: D' = (23.8 ± 11.5) × 10 -3 mm 2 /s; kidney medulla: D' = (5.23 ± 0.93) × 10 -3 mm 2 /s], whereas no third component was detected in the spleen. Fitting with a diffusion kurtosis model did not lead to a better fit of the resulting curves to the acquired data compared with apparent diffusion coefficient spectrum analysis. For a most accurate description of diffusion properties in the liver and the kidneys, a more sophisticated model seems to be required including three diffusion components. Copyright © 2017 John Wiley & Sons, Ltd.

A mechanistic modelling approach to polymer dissolution using magnetic resonance microimaging.

PubMed

Kaunisto, Erik; Abrahmsen-Alami, Susanna; Borgquist, Per; Larsson, Anette; Nilsson, Bernt; Axelsson, Anders

2010-10-15

In this paper a computationally efficient mathematical model describing the swelling and dissolution of a polyethylene oxide tablet is presented. The model was calibrated against polymer release, front position and water concentration profile data inside the gel layer, using two different diffusion models. The water concentration profiles were obtained from magnetic resonance microimaging data which, in addition to the previously used texture analysis method, can help to validate and discriminate between the mechanisms of swelling, diffusion and erosion in relation to the dissolution process. Critical parameters were identified through a comprehensive sensitivity analysis, and the effect of hydrodynamic shearing was investigated by using two different stirring rates. Good agreement was obtained between the experimental results and the model. Copyright © 2010 Elsevier B.V. All rights reserved.

Trojan War displayed as a full annihilation-diffusion-reaction model

NASA Astrophysics Data System (ADS)

Flores, J. C.

2017-02-01

The diffusive pair annihilation model with embedded topological domains and archaeological data is applied in an analysis of the hypothetical Trojan-Greek war during the late Bronze Age. Estimations of parameter are explicitly made for critical dynamics of the model. In particular, the 8-metre walls of Troy could be viewed as the effective shield that provided the technological difference between the two armies. Suggestively, the numbers in The Iliad are quite sound, being in accord with Lanchester's laws of warfare.

Analysis of diffusion in curved surfaces and its application to tubular membranes

PubMed Central

Klaus, Colin James Stockdale; Raghunathan, Krishnan; DiBenedetto, Emmanuele; Kenworthy, Anne K.

2016-01-01

Diffusion of particles in curved surfaces is inherently complex compared with diffusion in a flat membrane, owing to the nonplanarity of the surface. The consequence of such nonplanar geometry on diffusion is poorly understood but is highly relevant in the case of cell membranes, which often adopt complex geometries. To address this question, we developed a new finite element approach to model diffusion on curved membrane surfaces based on solutions to Fick’s law of diffusion and used this to study the effects of geometry on the entry of surface-bound particles into tubules by diffusion. We show that variations in tubule radius and length can distinctly alter diffusion gradients in tubules over biologically relevant timescales. In addition, we show that tubular structures tend to retain concentration gradients for a longer time compared with a comparable flat surface. These findings indicate that sorting of particles along the surfaces of tubules can arise simply as a geometric consequence of the curvature without any specific contribution from the membrane environment. Our studies provide a framework for modeling diffusion in curved surfaces and suggest that biological regulation can emerge purely from membrane geometry. PMID:27733625

Fractional derivatives in the transport of drugs across biological materials and human skin

NASA Astrophysics Data System (ADS)

Caputo, Michele; Cametti, Cesare

2016-11-01

The diffusion of drugs across a composite structure such as a biological membrane is a rather complex phenomenon, because of its inhomogeneous nature, yielding a diffusion rate and a drug solubility strongly dependent on the local position across the membrane itself. These problems are particularly strengthened in composite structures of a considerable thickness like, for example, the human skin, where the high heterogeneity provokes the transport through different simultaneous pathways. In this note, we propose a generalization of the diffusion model based on Fick's 2nd equation by substituting a diffusion constant by means of the memory formalism approach (diffusion with memory). In particular, we employ two different definitions of the fractional derivative, i.e., the usual Caputo fractional derivative and a new definition recently proposed by Caputo and Fabrizio. The model predictions have been compared to experimental results concerning the permeation of two different compounds through human skin in vivo, such as piroxicam, an anti-inflammatory drug, and 4-cyanophenol, a test chemical model compound. Moreover, we have also considered water penetration across human stratum corneum and the diffusion of an antiviral agent employed as model drugs across the skin of male hairless rats. In all cases, a satisfactory good agreement based on the diffusion with memory has been found. However, the model based on the new definition of fractional derivative gives a better description of the experimental data, on the basis of the residuals analysis. The use of the new definition widens the applicability of the fractional derivative to diffusion processes in highly heterogeneous systems.

Diffusion-model analysis of pPb and PbPb collisions at LHC energies

NASA Astrophysics Data System (ADS)

Schulz, P.; Wolschin, G.

2018-06-01

We present an analysis of centrality-dependent pseudorapidity distributions of produced charged hadrons in pPb and PbPb collisions at the Large Hadron Collider (LHC) energy of s NN = 5.02 TeV, and of minimum-bias pPb collisions at 8.16 TeV within the non-equilibrium-statistical relativistic diffusion model (RDM). In a three-source approach, the role of the fragmentation sources is emphasized. Together with the Jacobian transformation from rapidity to pseudorapidity and the limiting fragmentation conjecture, these are essential for modeling the centrality dependence. For central PbPb collisions, a prediction at the projected FCC energy of s NN = 39 TeV is made.

Innovation diffusion on time-varying activity driven networks

NASA Astrophysics Data System (ADS)

Rizzo, Alessandro; Porfiri, Maurizio

2016-01-01

Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.

Load Diffusion in Composite and Smart Structures

NASA Technical Reports Server (NTRS)

Horgan, C. O.

2003-01-01

The research carried out here builds on our previous NASA supported research on the general topic of edge effects and load diffusion in composite structures. Further fundamental solid mechanics studies were carried out to provide a basis for assessing the complicated modeling necessary for the multi-functional large scale structures used by NASA. An understanding of the fundamental mechanisms of load diffusion in composite subcomponents is essential in developing primary composite structures. Some specific problems recently considered were those of end effects in smart materials and structures, study of the stress response of pressurized linear piezoelectric cylinders for both static and steady rotating configurations, an analysis of the effect of pre-stressing and pre-polarization on the decay of end effects in piezoelectric solids and investigation of constitutive models for hardening rubber-like materials. Our goal in the study of load diffusion is the development of readily applicable results for the decay lengths in terms of non-dimensional material and geometric parameters. Analytical models of load diffusion behavior are extremely valuable in building an intuitive base for developing refined modeling strategies and assessing results from finite element analyses. The decay behavior of stresses and other field quantities provides a significant aid towards this process. The analysis is also amenable to parameter study with a large parameter space and should be useful in structural tailoring studies. Special purpose analytical models of load diffusion behavior are extremely valuable in building an intuitive base for developing refined modeling strategies and in assessing results from general purpose finite element analyses. For example, a rational basis is needed in choosing where to use three-dimensional to two-dimensional transition finite elements in analyzing stiffened plates and shells. The decay behavior of stresses and other field quantities furnished by this research provides a significant aid towards this element transition issue. A priori knowledge of the extent of boundary-layers induced by edge effects is also useful in determination of the instrumentation location in structural verification tests or in material characterization tests.

Design-for-manufacture of gradient-index optical systems using time-varying boundary condition diffusion

NASA Astrophysics Data System (ADS)

Harkrider, Curtis Jason

2000-08-01

The incorporation of gradient-index (GRIN) material into optical systems offers novel and practical solutions to lens design problems. However, widespread use of gradient-index optics has been limited by poor correlation between gradient-index designs and the refractive index profiles produced by ion exchange between glass and molten salt. Previously, a design-for- manufacture model was introduced that connected the design and fabrication processes through use of diffusion modeling linked with lens design software. This project extends the design-for-manufacture model into a time- varying boundary condition (TVBC) diffusion model. TVBC incorporates the time-dependent phenomenon of melt poisoning and introduces a new index profile control method, multiple-step diffusion. The ions displaced from the glass during the ion exchange fabrication process can reduce the total change in refractive index (Δn). Chemical equilibrium is used to model this melt poisoning process. Equilibrium experiments are performed in a titania silicate glass and chemically analyzed. The equilibrium model is fit to ion concentration data that is used to calculate ion exchange boundary conditions. The boundary conditions are changed purposely to control the refractive index profile in multiple-step TVBC diffusion. The glass sample is alternated between ion exchange with a molten salt bath and annealing. The time of each diffusion step can be used to exert control on the index profile. The TVBC computer model is experimentally verified and incorporated into the design- for-manufacture subroutine that runs in lens design software. The TVBC design-for-manufacture model is useful for fabrication-based tolerance analysis of gradient-index lenses and for the design of manufactureable GRIN lenses. Several optical elements are designed and fabricated using multiple-step diffusion, verifying the accuracy of the model. The strength of multiple-step diffusion process lies in its versatility. An axicon, imaging lens, and curved radial lens, all with different index profile requirements, are designed out of a single glass composition.

A sensitivity analysis of low salinity habitats simulated by a hydrodynamic model in the Manatee River estuary in Florida, USA

NASA Astrophysics Data System (ADS)

Chen, XinJian

2012-06-01

This paper presents a sensitivity study of simulated availability of low salinity habitats by a hydrodynamic model for the Manatee River estuary located in the southwest portion of the Florida peninsula. The purpose of the modeling study was to establish a regulatory minimum freshwater flow rate required to prevent the estuarine ecosystem from significant harm. The model used in the study was a multi-block model that dynamically couples a three-dimensional (3D) hydrodynamic model with a laterally averaged (2DV) hydrodynamic model. The model was calibrated and verified against measured real-time data of surface elevation and salinity at five stations during March 2005-July 2006. The calibrated model was then used to conduct a series of scenario runs to investigate effects of the flow reduction on salinity distributions in the Manatee River estuary. Based on simulated salinity distribution in the estuary, water volumes, bottom areas and shoreline lengths for salinity less than certain predefined values were calculated and analyzed to help establish the minimum freshwater flow rate for the estuarine system. The sensitivity analysis conducted during the modeling study for the Manatee River estuary examined effects of the bottom roughness, ambient vertical eddy viscosity/diffusivity, horizontal eddy viscosity/diffusivity, and ungauged flow on the model results and identified the relative importance of these model parameters (input data) to the outcome of the availability of low salinity habitats. It is found that the ambient vertical eddy viscosity/diffusivity is the most influential factor controlling the model outcome, while the horizontal eddy viscosity/diffusivity is the least influential one.

Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer-aquitard complexes.

PubMed

Zhang, Yong; Green, Christopher T; Tick, Geoffrey R

2015-01-01

This study evaluates the role of the Peclet number as affected by molecular diffusion in transient anomalous transport, which is one of the major knowledge gaps in anomalous transport, by combining Monte Carlo simulations and stochastic model analysis. Two alluvial settings containing either short- or long-connected hydrofacies are generated and used as media for flow and transport modeling. Numerical experiments show that 1) the Peclet number affects both the duration of the power-law segment of tracer breakthrough curves (BTCs) and the transition rate from anomalous to Fickian transport by determining the solute residence time for a given low-permeability layer, 2) mechanical dispersion has a limited contribution to the anomalous characteristics of late-time transport as compared to molecular diffusion due to an almost negligible velocity in floodplain deposits, and 3) the initial source dimensions only enhance the power-law tail of the BTCs at short travel distances. A tempered stable stochastic (TSS) model is then applied to analyze the modeled transport. Applications show that the time-nonlocal parameters in the TSS model relate to the Peclet number, Pe. In particular, the truncation parameter in the TSS model increases nonlinearly with a decrease in Pe due to the decrease of the mean residence time, and the capacity coefficient increases with an increase in molecular diffusion which is probably due to the increase in the number of immobile particles. The above numerical experiments and stochastic analysis therefore reveal that the Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer-aquitard complexes. Copyright © 2015 Elsevier B.V. All rights reserved.

Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system.

PubMed

Gao, Xiangyun; Huang, Shupei; Sun, Xiaoqi; Hao, Xiaoqing; An, Feng

2018-03-01

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion.

Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system

PubMed Central

Huang, Shupei; Sun, Xiaoqi; Hao, Xiaoqing; An, Feng

2018-01-01

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion. PMID:29657804

Effect of different analyte diffusion/adsorption protocols on SERS signals

NASA Astrophysics Data System (ADS)

Li, Ruoping; Petschek, Rolfe G.; Han, Junhe; Huang, Mingju

2018-07-01

The effect of different analyte diffusion/adsorption protocols was studied which is often overlooked in surface-enhanced Raman scattering (SERS) technique. Three protocols: highly concentrated dilution (HCD) protocol, half-half dilution (HHD) protocol and layered adsorption (LA) protocol were studied and the SERS substrates were monolayer films of 80 nm Ag nanoparticles (NPs) which were modified by polyvinylpyrrolidone. The diffusion/adsorption mechanisms were modelled using the diffusion equation and the electromagnetic field distribution of two adjacent Ag NPs was simulated by the finite-different time-domain method. All experimental data and theoretical analysis suggest that different diffusion/adsorption behaviour of analytes will cause different SERS signal enhancements. HHD protocol could produce the most uniform and reproducible samples, and the corresponding signal intensity of the analyte is the strongest. This study will help to understand and promote the use of SERS technique in quantitative analysis.

A Component-Based Diffusion Model With Structural Diversity for Social Networks.

PubMed

Qing Bao; Cheung, William K; Yu Zhang; Jiming Liu

2017-04-01

Diffusion on social networks refers to the process where opinions are spread via the connected nodes. Given a set of observed information cascades, one can infer the underlying diffusion process for social network analysis. The independent cascade model (IC model) is a widely adopted diffusion model where a node is assumed to be activated independently by any one of its neighbors. In reality, how a node will be activated also depends on how its neighbors are connected and activated. For instance, the opinions from the neighbors of the same social group are often similar and thus redundant. In this paper, we extend the IC model by considering that: 1) the information coming from the connected neighbors are similar and 2) the underlying redundancy can be modeled using a dynamic structural diversity measure of the neighbors. Our proposed model assumes each node to be activated independently by different communities (or components) of its parent nodes, each weighted by its effective size. An expectation maximization algorithm is derived to infer the model parameters. We compare the performance of the proposed model with the basic IC model and its variants using both synthetic data sets and a real-world data set containing news stories and Web blogs. Our empirical results show that incorporating the community structure of neighbors and the structural diversity measure into the diffusion model significantly improves the accuracy of the model, at the expense of only a reasonable increase in run-time.

Development of a robust modeling tool for radiation-induced segregation in austenitic stainless steels

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

Yang, Ying; Field, Kevin G; Allen, Todd R.

2015-09-01

Irradiation-assisted stress corrosion cracking (IASCC) of austenitic stainless steels in Light Water Reactor (LWR) components has been linked to changes in grain boundary composition due to irradiation induced segregation (RIS). This work developed a robust RIS modeling tool to account for thermodynamics and kinetics of the atom and defect transportation under combined thermal and radiation conditions. The diffusion flux equations were based on the Perks model formulated through the linear theory of the thermodynamics of irreversible processes. Both cross and non-cross phenomenological diffusion coefficients in the flux equations were considered and correlated to tracer diffusion coefficients through Manning’s relation. Themore » preferential atomvacancy coupling was described by the mobility model, whereas the preferential atom-interstitial coupling was described by the interstitial binding model. The composition dependence of the thermodynamic factor was modeled using the CALPHAD approach. Detailed analysis on the diffusion fluxes near and at grain boundaries of irradiated austenitic stainless steels suggested the dominant diffusion mechanism for chromium and iron is via vacancy, while that for nickel can swing from the vacancy to the interstitial dominant mechanism. The diffusion flux in the vicinity of a grain boundary was found to be greatly influenced by the composition gradient formed from the transient state, leading to the oscillatory behavior of alloy compositions in this region. This work confirms that both vacancy and interstitial diffusion, and segregation itself, have important roles in determining the microchemistry of Fe, Cr, and Ni at irradiated grain boundaries in austenitic stainless steels.« less

Insight from uncertainty: bootstrap-derived diffusion metrics differentially predict memory function among older adults.

PubMed

Vorburger, Robert S; Habeck, Christian G; Narkhede, Atul; Guzman, Vanessa A; Manly, Jennifer J; Brickman, Adam M

2016-01-01

Diffusion tensor imaging suffers from an intrinsic low signal-to-noise ratio. Bootstrap algorithms have been introduced to provide a non-parametric method to estimate the uncertainty of the measured diffusion parameters. To quantify the variability of the principal diffusion direction, bootstrap-derived metrics such as the cone of uncertainty have been proposed. However, bootstrap-derived metrics are not independent of the underlying diffusion profile. A higher mean diffusivity causes a smaller signal-to-noise ratio and, thus, increases the measurement uncertainty. Moreover, the goodness of the tensor model, which relies strongly on the complexity of the underlying diffusion profile, influences bootstrap-derived metrics as well. The presented simulations clearly depict the cone of uncertainty as a function of the underlying diffusion profile. Since the relationship of the cone of uncertainty and common diffusion parameters, such as the mean diffusivity and the fractional anisotropy, is not linear, the cone of uncertainty has a different sensitivity. In vivo analysis of the fornix reveals the cone of uncertainty to be a predictor of memory function among older adults. No significant correlation occurs with the common diffusion parameters. The present work not only demonstrates the cone of uncertainty as a function of the actual diffusion profile, but also discloses the cone of uncertainty as a sensitive predictor of memory function. Future studies should incorporate bootstrap-derived metrics to provide more comprehensive analysis.

Nonlinear Landau damping in the ionosphere

NASA Technical Reports Server (NTRS)

Kiwamoto, Y.; Benson, R. F.

1978-01-01

A model is presented to explain the non-resonant waves which give rise to the diffuse resonance observed near 3/2 f sub H by the Alouette and ISIS topside sounders, where f sub H is the ambient electron cyclotron frequency. In a strictly linear analysis, these instability driven waves will decay due to Landau damping on a time scale much shorter than the observed time duration of the diffuse resonance. Calculations of the nonlinear wave particle coupling coefficients, however, indicate that the diffuse resonance wave can be maintained by the nonlinear Landau damping of the sounder stimulated 2f sub H wave. The time duration of the diffuse resonance is determined by the transit time of the instability generated and nonlinearly maintained diffuse resonance wave from the remote short lived hot region back to the antenna. The model is consistent with the Alouette/ISIS observations, and clearly demonstrates the existence of nonlinear wave-particle interactions in the ionosphere.

Construction of Fluid - solid Coupling Model with Improved Richards - BP & Its Engineering Application

NASA Astrophysics Data System (ADS)

Xie, Chengyu; Jia, Nan; Shi, Dongping; Lu, Hao

2017-10-01

In order to study the slurry diffusion law during grouting, Richards unsaturated-saturated model was introduced, the definition of the grouting model is clear, the Richards model control equation was established, And the BP neural network was introduced, the improved fluid-solid coupling model was constructed, Through the use of saturated - unsaturated seepage flow model, As well as the overflow boundary iterative solution of the mixed boundary conditions, the free surface is calculated. Engineering practice for an example, with the aid of multi - field coupling analysis software, the diffusion law of slurry was simulated numerically. The results show that the slurry diffusion rule is affected by grouting material, initial pressure and other factors. When the slurry starts, it flows in the cracks along the upper side of the grouting hole, when the pressure gradient is reduced to the critical pressure, that is, to the lower side of the flow, when the slurry diffusion stability, and ultimately its shape like an 8. The slurry is spread evenly from the overall point of view, from the grouting mouth toward the surrounding evenly spread, it gradually reaches saturation by non-saturation, and it is not a purely saturated flow, when the slurry spread and reach a saturated state, the diffusion time is the engineering grouting time.

Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies.

PubMed

Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura; Prah, Melissa; Hectors, Stefanie; Arlinghaus, Lori; Muzi, Mark; Solaiyappan, Meiyappan; Jacobs, Michael; Fung, Maggie; Shukla-Dave, Amita; McManus, Kevin; Boss, Michael; Taouli, Bachir; Yankeelov, Thomas E; Quarles, Christopher Chad; Schmainda, Kathleen; Chenevert, Thomas L; Newitt, David C

2018-01-01

This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.

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.

Robust model-based analysis of single-particle tracking experiments with Spot-On

PubMed Central

Grimm, Jonathan B; Lavis, Luke D

2018-01-01

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce ‘Spot-On’, an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. PMID:29300163

Robust model-based analysis of single-particle tracking experiments with Spot-On.

PubMed

Hansen, Anders S; Woringer, Maxime; Grimm, Jonathan B; Lavis, Luke D; Tjian, Robert; Darzacq, Xavier

2018-01-04

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. © 2018, Hansen et al.

Application of Monte Carlo techniques to transient thermal modeling of cavity radiometers having diffuse-specular surfaces

NASA Technical Reports Server (NTRS)

Mahan, J. R.; Eskin, L. D.

1981-01-01

A viable alternative to the net exchange method of radiative analysis which is equally applicable to diffuse and diffuse-specular enclosures is presented. It is particularly more advantageous to use than the net exchange method in the case of a transient thermal analysis involving conduction and storage of energy as well as radiative exchange. A new quantity, called the distribution factor is defined which replaces the angle factor and the configuration factor. Once obtained, the array of distribution factors for an ensemble of surface elements which define an enclosure permits the instantaneous net radiative heat fluxes to all of the surfaces to be computed directly in terms of the known surface temperatures at that instant. The formulation of the thermal model is described, as is the determination of distribution factors by application of a Monte Carlo analysis. The results show that when fewer than 10,000 packets are emitted, an unsatisfactory approximation for the distribution factors is obtained, but that 10,000 packets is sufficient.

A diffusive ink transport model for lipid dip-pen nanolithography

NASA Astrophysics Data System (ADS)

Urtizberea, A.; Hirtz, M.

2015-09-01

Despite diverse applications, phospholipid membrane stacks generated by dip-pen nanolithography (DPN) still lack a thorough and systematic characterization that elucidates the whole ink transport process from writing to surface spreading, with the aim of better controlling the resulting feature size and resolution. We report a quantitative analysis and modeling of the dependence of lipid DPN features (area, height and volume) on dwell time and relative humidity. The ink flow rate increases with humidity in agreement with meniscus size growth, determining the overall feature size. The observed time dependence indicates the existence of a balance between surface spreading and the ink flow rate that promotes differences in concentration at the meniscus/substrate interface. Feature shape is controlled by the substrate surface energy. The results are analyzed within a modified model for the ink transport of diffusive inks. At any humidity the dependence of the area spread on the dwell time shows two diffusion regimes: at short dwell times growth is controlled by meniscus diffusion while at long dwell times surface diffusion governs the process. The critical point for the switch of regime depends on the humidity.Despite diverse applications, phospholipid membrane stacks generated by dip-pen nanolithography (DPN) still lack a thorough and systematic characterization that elucidates the whole ink transport process from writing to surface spreading, with the aim of better controlling the resulting feature size and resolution. We report a quantitative analysis and modeling of the dependence of lipid DPN features (area, height and volume) on dwell time and relative humidity. The ink flow rate increases with humidity in agreement with meniscus size growth, determining the overall feature size. The observed time dependence indicates the existence of a balance between surface spreading and the ink flow rate that promotes differences in concentration at the meniscus/substrate interface. Feature shape is controlled by the substrate surface energy. The results are analyzed within a modified model for the ink transport of diffusive inks. At any humidity the dependence of the area spread on the dwell time shows two diffusion regimes: at short dwell times growth is controlled by meniscus diffusion while at long dwell times surface diffusion governs the process. The critical point for the switch of regime depends on the humidity. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr04352b

Flame Shapes of Luminous NonBuoyant Laminar Coflowing Jet Diffusion Flames

NASA Technical Reports Server (NTRS)

Lin, K.-C.; Faeth, G. M.

1999-01-01

Laminar diffusion flames are of interest as model flame systems that are more tractable for analysis and experiments than practical turbulent diffusion flames. Certainly understanding laminar flames must precede understanding more complex turbulent flames while man'y laminar diffusion flame properties are directly relevant to turbulent diffusion flames using laminar flamelet concepts. Laminar diffusion flame shapes have been of interest since the classical study of Burke and Schumann because they involve a simple nonintrusive measurement that is convenient for evaluating flame structure predictions. Motivated by these observations, the shapes of laminar flames were considered during the present investigation. The present study was limited to nonbuoyant flames because most practical flames are not buoyant. Effects of buoyancy were minimized by observing flames having large flow velocities at small pressures. Present methods were based on the study of the shapes of nonbu,3yant round laminar jet diffusion flames of Lin et al. where it was found that a simple analysis due to Spalding yielded good predictions of the flame shapes reported by Urban et al. and Sunderland et al.

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.

Modeling the Total Dose Radiation Effects of Hg(1-x)Cd(x)Te Photodiodes Using Numerical Device Simulators

DTIC Science & Technology

1994-01-01

Dosimetry : Analysis of dosimetry in two dewar/liquid nitrogen systems. TIME Estimate: One hour for setup, irradiation and TLD reading/analysis. IV...point indicates both electron and hole trapping at the boundary ........................ 12 3.3 Relationship between current and dose for irradiated...peak value. Carriers are collected across the vertical junction within a diffusion length. Since the electron diffusion length is much larger than for

Oxygen Tracer Diffusion in LA(z-x) SR(X) CUO(4-y) Single Crystals

NASA Technical Reports Server (NTRS)

Opila, Elizabeth J.; Tuller, Harry L.; Wuensch, Berhardt J.; Maier, Joachim

1993-01-01

The tracer diffusion of O-18 in La(2-x)Sr(x)CuO(4-y) single crystals (x = 0 to 0.12) has been measured from 400 to 700 C in 1 atm of oxygen using SIMS analysis. Evidence for diffusion by a vacancy mechanism was found at low strontium contents. Oxygen diffusivities for x greater than or = 0.07 were depressed by several orders of magnitude below the diffusivity for undoped La2CuO(4+/-y). The observed effects of strontium doping on oxygen diffusivity are discussed in terms of defect chemical models. The decreasing oxygen diffusivity with increasing strontium was attributed to the ordering of oxygen vacancies at large defect concentrations. A diffusion anisotropy D(sub ab)/D(sub c) of nearly 600 was also found at 500 C.

A COMPUTATIONAL ANALYSIS OF BONE FORMATION IN THE CRANIAL VAULT USING A COUPLED REACTION-DIFFUSION-STRAIN MODEL

PubMed Central

LEE, CHANYOUNG; RICHTSMEIER, JOAN T.; KRAFT, REUBEN H.

2017-01-01

Bones of the murine cranial vault are formed by differentiation of mesenchymal cells into osteoblasts, a process that is primarily understood to be controlled by a cascade of reactions between extracellular molecules and cells. We assume that the process can be modeled using Turing’s reaction-diffusion equations, a mathematical model describing the pattern formation controlled by two interacting molecules (activator and inhibitor). In addition to the processes modeled by reaction-diffusion equations, we hypothesize that mechanical stimuli of the cells due to growth of the underlying brain contribute significantly to the process of cell differentiation in cranial vault development. Structural analysis of the surface of the brain was conducted to explore the effects of the mechanical strain on bone formation. We propose a mechanobiological model for the formation of cranial vault bones by coupling the reaction-diffusion model with structural mechanics. The mathematical formulation was solved using the finite volume method. The computational domain and model parameters are determined using a large collection of experimental data that provide precise three dimensional (3D) measures of murine cranial geometry and cranial vault bone formation for specific embryonic time points. The results of this study suggest that mechanical strain contributes information to specific aspects of bone formation. Our mechanobiological model predicts some key features of cranial vault bone formation that were verified by experimental observations including the relative location of ossification centers of individual vault bones, the pattern of cranial vault bone growth over time, and the position of cranial vault sutures. PMID:29225392

Q-space trajectory imaging for multidimensional diffusion MRI of the human brain

PubMed Central

Westin, Carl-Fredrik; Knutsson, Hans; Pasternak, Ofer; Szczepankiewicz, Filip; Özarslan, Evren; van Westen, Danielle; Mattisson, Cecilia; Bogren, Mats; O’Donnell, Lauren; Kubicki, Marek; Topgaard, Daniel; Nilsson, Markus

2016-01-01

This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture. PMID:26923372

Clear-sky shortwave radiative closure for the Cabauw Baseline Surface Radiation Network site, the Netherlands

NASA Astrophysics Data System (ADS)

Wang, P.; Knap, W. H.; Kuipers Munneke, P.; Stammes, P.

2009-04-01

During the last two decades, several attempts have been made to achieve agreement between clear-sky shortwave broadband irradiance models and surface measurements of direct and diffuse irradiance. In general, models and measurements agreed well for the direct component but closing the gap for diffuse irradiances remained problematic. The number of studies reporting a satisfactory degree of closure for both direct and diffuse irradiance is still limited, which motivated us to perform the study presented here. In this paper a clear-sky shortwave closure analysis is presented for the Baseline Surface Radiation Network (BSRN) site of Cabauw, the Netherlands (51.97 °N, 4.93 °E). The analysis is based on an exceptional period of fine weather in the first half of May 2008 during the Intensive Measurement Period At the Cabauw Tower (IMPACT), an activity of the European Integrated project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Although IMPACT produced a wealth of data, it was decided to conduct the closure analysis using routine measurements only, provided by BSRN and the Aerosol Robotic Network (AERONET), completed with radiosonde obervations. The rationale for this pragmatic approach is the possibility of applying the method presented here to other periods and (BSRN) sites, where routine measurements are readily available, without having to deal with the investments and restrictions of an intensive observation period. The analysis is based on a selection of 72 comparisons on 6 days between BSRN measurements and Doubling Adding KNMI (DAK) model simulations of direct, diffuse, and global irradiance. The data span a wide range of aerosol properties, water vapour columns, and solar zenith angles. The model input consisted of operational Aerosol Robotic Network (AERONET) aerosol products and radiosonde data. On the basis of these data excellent closure was obtained: the mean differences between model and measurements are 2 W/m2 (+0.2%) for direct irradiance, 1 W/m2 (+0.8%) for diffuse irradiance, and 2 W/m2 (+0.3%) for global irradiance.

Time series analysis of particle tracking data for molecular motion on the cell membrane.

PubMed

Ying, Wenxia; Huerta, Gabriel; Steinberg, Stanly; Zúñiga, Martha

2009-11-01

Biophysicists use single particle tracking (SPT) methods to probe the dynamic behavior of individual proteins and lipids in cell membranes. The mean squared displacement (MSD) has proven to be a powerful tool for analyzing the data and drawing conclusions about membrane organization, including features like lipid rafts, protein islands, and confinement zones defined by cytoskeletal barriers. Here, we implement time series analysis as a new analytic tool to analyze further the motion of membrane proteins. The experimental data track the motion of 40 nm gold particles bound to Class I major histocompatibility complex (MHCI) molecules on the membranes of mouse hepatoma cells. Our first novel result is that the tracks are significantly autocorrelated. Because of this, we developed linear autoregressive models to elucidate the autocorrelations. Estimates of the signal to noise ratio for the models show that the autocorrelated part of the motion is significant. Next, we fit the probability distributions of jump sizes with four different models. The first model is a general Weibull distribution that shows that the motion is characterized by an excess of short jumps as compared to a normal random walk. We also fit the data with a chi distribution which provides a natural estimate of the dimension d of the space in which a random walk is occurring. For the biological data, the estimates satisfy 1 < d < 2, implying that particle motion is not confined to a line, but also does not occur freely in the plane. The dimension gives a quantitative estimate of the amount of nanometer scale obstruction met by a diffusing molecule. We introduce a new distribution and use the generalized extreme value distribution to show that the biological data also have an excess of long jumps as compared to normal diffusion. These fits provide novel estimates of the microscopic diffusion constant. Previous MSD analyses of SPT data have provided evidence for nanometer-scale confinement zones that restrict lateral diffusion, supporting the notion that plasma membrane organization is highly structured. Our demonstration that membrane protein motion is autocorrelated and is characterized by an excess of both short and long jumps reinforces the concept that the membrane environment is heterogeneous and dynamic. Autocorrelation analysis and modeling of the jump distributions are powerful new techniques for the analysis of SPT data and the development of more refined models of membrane organization. The time series analysis also provides several methods of estimating the diffusion constant in addition to the constant provided by the mean squared displacement. The mean squared displacement for most of the biological data shows a power law behavior rather the linear behavior of Brownian motion. In this case, we introduce the notion of an instantaneous diffusion constant. All of the diffusion constants show a strong consistency for most of the biological data.

Permeability and kinetic coefficients for mesoscale BCF surface step dynamics: Discrete two-dimensional deposition-diffusion equation analysis

DOE PAGES

Zhao, Renjie; Evans, James W.; Oliveira, Tiago J.

2016-04-08

Here, a discrete version of deposition-diffusion equations appropriate for description of step flow on a vicinal surface is analyzed for a two-dimensional grid of adsorption sites representing the stepped surface and explicitly incorporating kinks along the step edges. Model energetics and kinetics appropriately account for binding of adatoms at steps and kinks, distinct terrace and edge diffusion rates, and possible additional barriers for attachment to steps. Analysis of adatom attachment fluxes as well as limiting values of adatom densities at step edges for nonuniform deposition scenarios allows determination of both permeability and kinetic coefficients. Behavior of these quantities is assessedmore » as a function of key system parameters including kink density, step attachment barriers, and the step edge diffusion rate.« less

Permeability and kinetic coefficients for mesoscale BCF surface step dynamics: Discrete two-dimensional deposition-diffusion equation analysis

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

Zhao, Renjie; Evans, James W.; Oliveira, Tiago J.

Here, a discrete version of deposition-diffusion equations appropriate for description of step flow on a vicinal surface is analyzed for a two-dimensional grid of adsorption sites representing the stepped surface and explicitly incorporating kinks along the step edges. Model energetics and kinetics appropriately account for binding of adatoms at steps and kinks, distinct terrace and edge diffusion rates, and possible additional barriers for attachment to steps. Analysis of adatom attachment fluxes as well as limiting values of adatom densities at step edges for nonuniform deposition scenarios allows determination of both permeability and kinetic coefficients. Behavior of these quantities is assessedmore » as a function of key system parameters including kink density, step attachment barriers, and the step edge diffusion rate.« less

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

Understanding of Relationship between Phospholipid Membrane Permeability and Self-Diffusion Coefficients of Some Drugs and Biologically Active Compounds in Model Solvents.

PubMed

Blokhina, Svetlana V; Volkova, Tatyana V; Golubev, Vasiliy A; Perlovich, German L

2017-10-02

In this work we measured self-diffusion coefficients of 5 drugs (aspirin, caffeine, ethionamide, salicylic acid, and paracetamol) and 11 biologically active compounds of similar structure in deuterated water and 1-octanol by NMR. It has been found that an increase in the van der Waals volume of the molecules of the studied substances result in reduction of their diffusion mobility in both solvents. The analysis of the experimental data showed the influence of chemical nature and structural isomerization of the molecules on the diffusion mobility. Apparent permeability coefficients of the studied compounds were determined using an artificial phospholipid membrane made of egg lecithin as a model of in vivo absorption. Distribution coefficients in 1-octanol/buffer pH 7.4 system were measured. For the first time the model of the passive diffusion through the phospholipid membrane was validated based on the experimental data. To this end, the passive diffusion was considered as an additive process of molecule passage through the aqueous boundary layer before the membrane and 1-octanol barrier simulating the lipid layer of the membrane.

Three-dimensional flow of Prandtl fluid with Cattaneo-Christov double diffusion

NASA Astrophysics Data System (ADS)

Hayat, Tasawar; Aziz, Arsalan; Muhammad, Taseer; Alsaedi, Ahmed

2018-06-01

This research paper intends to investigate the 3D flow of Prandtl liquid in the existence of improved heat conduction and mass diffusion models. Flow is created by considering linearly bidirectional stretchable sheet. Thermal and concentration diffusions are considered by employing Cattaneo-Christov double diffusion models. Boundary layer approach has been used to simplify the governing PDEs. Suitable nondimensional similarity variables correspond to strong nonlinear ODEs. Optimal homotopy analysis method (OHAM) is employed for solutions development. The role of various pertinent variables on temperature and concentration are analyzed through graphs. The physical quantities such as surface drag coefficients and heat and mass transfer rates at the wall are also plotted and discussed. Our results indicate that the temperature and concentration are decreasing functions of thermal and concentration relaxation parameters respectively.

Analysis of molecular movement reveals latticelike obstructions to diffusion in heart muscle cells.

PubMed

Illaste, Ardo; Laasmaa, Martin; Peterson, Pearu; Vendelin, Marko

2012-02-22

Intracellular diffusion in muscle cells is known to be restricted. Although characteristics and localization of these restrictions is yet to be elucidated, it has been established that ischemia-reperfusion injury reduces the overall diffusion restriction. Here we apply an extended version of raster image correlation spectroscopy to determine directional anisotropy and coefficients of diffusion in rat cardiomyocytes. Our experimental results indicate that diffusion of a smaller molecule (1127 MW fluorescently labeled ATTO633-ATP) is restricted more than that of a larger one (10,000 MW Alexa647-dextran), when comparing diffusion in cardiomyocytes to that in solution. We attempt to provide a resolution to this counterintuitive result by applying a quantitative stochastic model of diffusion. Modeling results suggest the presence of periodic intracellular barriers situated ∼1 μm apart having very low permeabilities and a small effect of molecular crowding in volumes between the barriers. Such intracellular structuring could restrict diffusion of molecules of energy metabolism, reactive oxygen species, and apoptotic signals, enacting a significant role in normally functioning cardiomyocytes as well as in pathological conditions of the heart. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Prediction and validation of diffusion coefficients in a model drug delivery system using microsecond atomistic molecular dynamics simulation and vapour sorption analysis.

PubMed

Forrey, Christopher; Saylor, David M; Silverstein, Joshua S; Douglas, Jack F; Davis, Eric M; Elabd, Yossef A

2014-10-14

Diffusion of small to medium sized molecules in polymeric medical device materials underlies a broad range of public health concerns related to unintended leaching from or uptake into implantable medical devices. However, obtaining accurate diffusion coefficients for such systems at physiological temperature represents a formidable challenge, both experimentally and computationally. While molecular dynamics simulation has been used to accurately predict the diffusion coefficients, D, of a handful of gases in various polymers, this success has not been extended to molecules larger than gases, e.g., condensable vapours, liquids, and drugs. We present atomistic molecular dynamics simulation predictions of diffusion in a model drug eluting system that represent a dramatic improvement in accuracy compared to previous simulation predictions for comparable systems. We find that, for simulations of insufficient duration, sub-diffusive dynamics can lead to dramatic over-prediction of D. We present useful metrics for monitoring the extent of sub-diffusive dynamics and explore how these metrics correlate to error in D. We also identify a relationship between diffusion and fast dynamics in our system, which may serve as a means to more rapidly predict diffusion in slowly diffusing systems. Our work provides important precedent and essential insights for utilizing atomistic molecular dynamics simulations to predict diffusion coefficients of small to medium sized molecules in condensed soft matter systems.

The γ parameter of the stretched-exponential model is influenced by internal gradients: validation in phantoms.

PubMed

Palombo, Marco; Gabrielli, Andrea; De Santis, Silvia; Capuani, Silvia

2012-03-01

In this paper, we investigate the image contrast that characterizes anomalous and non-gaussian diffusion images obtained using the stretched exponential model. This model is based on the introduction of the γ stretched parameter, which quantifies deviation from the mono-exponential decay of diffusion signal as a function of the b-value. To date, the biophysical substrate underpinning the contrast observed in γ maps, in other words, the biophysical interpretation of the γ parameter (or the fractional order derivative in space, β parameter) is still not fully understood, although it has already been applied to investigate both animal models and human brain. Due to the ability of γ maps to reflect additional microstructural information which cannot be obtained using diffusion procedures based on gaussian diffusion, some authors propose this parameter as a measure of diffusion heterogeneity or water compartmentalization in biological tissues. Based on our recent work we suggest here that the coupling between internal and diffusion gradients provide pseudo-superdiffusion effects which are quantified by the stretching exponential parameter γ. This means that the image contrast of Mγ maps reflects local magnetic susceptibility differences (Δχ(m)), thus highlighting better than T(2)(∗) contrast the interface between compartments characterized by Δχ(m). Thanks to this characteristic, Mγ imaging may represent an interesting tool to develop contrast-enhanced MRI for molecular imaging. The spectroscopic and imaging experiments (performed in controlled micro-beads dispersion) that are reported here, strongly suggest internal gradients, and as a consequence Δχ(m), to be an important factor in fully understanding the source of contrast in anomalous diffusion methods that are based on a stretched exponential model analysis of diffusion data obtained at varying gradient strengths g. Copyright © 2012 Elsevier Inc. All rights reserved.

A Luenberger observer for reaction-diffusion models with front position data

NASA Astrophysics Data System (ADS)

Collin, Annabelle; Chapelle, Dominique; Moireau, Philippe

2015-11-01

We propose a Luenberger observer for reaction-diffusion models with propagating front features, and for data associated with the location of the front over time. Such models are considered in various application fields, such as electrophysiology, wild-land fire propagation and tumor growth modeling. Drawing our inspiration from image processing methods, we start by proposing an observer for the eikonal-curvature equation that can be derived from the reaction-diffusion model by an asymptotic expansion. We then carry over this observer to the underlying reaction-diffusion equation by an ;inverse asymptotic analysis;, and we show that the associated correction in the dynamics has a stabilizing effect for the linearized estimation error. We also discuss the extension to joint state-parameter estimation by using the earlier-proposed ROUKF strategy. We then illustrate and assess our proposed observer method with test problems pertaining to electrophysiology modeling, including with a realistic model of cardiac atria. Our numerical trials show that state estimation is directly very effective with the proposed Luenberger observer, while specific strategies are needed to accurately perform parameter estimation - as is usual with Kalman filtering used in a nonlinear setting - and we demonstrate two such successful strategies.

Jump-Diffusion models and structural changes for asset forecasting in hydrology

NASA Astrophysics Data System (ADS)

Tranquille Temgoua, André Guy; Martel, Richard; Chang, Philippe J. J.; Rivera, Alfonso

2017-04-01

Impacts of climate change on surface water and groundwater are of concern in many regions of the world since water is an essential natural resource. Jump-Diffusion models are generally used in economics and other related fields but not in hydrology. The potential application could be made for hydrologic data series analysis and forecast. The present study uses Jump-Diffusion models by adding structural changes to detect fluctuations in hydrologic processes in relationship with climate change. The model implicitly assumes that modifications in rivers' flowrates can be divided into three categories: (a) normal changes due to irregular precipitation events especially in tropical regions causing major disturbance in hydrologic processes (this component is modelled by a discrete Brownian motion); (b) abnormal, sudden and non-persistent modifications in hydrologic proceedings are handled by Poisson processes; (c) the persistence of hydrologic fluctuations characterized by structural changes in hydrological data related to climate variability. The objective of this paper is to add structural changes in diffusion models with jumps, in order to capture the persistence of hydrologic fluctuations. Indirectly, the idea is to observe if there are structural changes of discharge/recharge over the study area, and to find an efficient and flexible model able of capturing a wide variety of hydrologic processes. Structural changes in hydrological data are estimated using the method of nonlinear discrete filters via Method of Simulated Moments (MSM). An application is given using sensitive parameters such as baseflow index and recession coefficient to capture discharge/recharge. Historical dataset are examined by the Volume Spread Analysis (VSA) to detect real time and random perturbations in hydrologic processes. The application of the method allows establishing more accurate hydrologic parameters. The impact of this study is perceptible in forecasting floods and groundwater recession. Keywords: hydrologic processes, Jump-Diffusion models, structural changes, forecast, climate change

Linear diffusion model dating of cinder cones in Central Anatolia, Turkey

NASA Astrophysics Data System (ADS)

O'Sadnick, L. G.; Reid, M. R.; Cline, M. L.; Cosca, M. A.; Kuscu, G.

2013-12-01

The progressive decrease in slope angle, cone height and cone height/width ratio over time provides the basis for geomorphic dating of cinder cones using linear diffusion models. Previous research using diffusion models to date cinder cones has focused on the cone height/width ratio as the basis for dating cones of unknown age [1,2]. Here we apply linear diffusion models to dating cinder cones. A suite of 16 cinder cones from the Hasandağ volcano area of the Neogene-Quaternary Central Anatolian Volcanic Zone, for which samples are available, were selected for morphologic dating analysis. New 40Ar/39Ar dates for five of these cones range from 62 × 4 to 517 × 9 ka. Linear diffusion models were used to model the erosional degradation of each cone. Diffusion coefficients (κ) for the 5 cinder cones with known ages were constrained by comparing various modeled slope profiles to the current slope profile. The resulting κ is 7.5×0.5 m2kyr-1. Using this κ value, eruption ages were modeled for the remaining 11 cinder cones and range from 53×3 to 455×30 ka. These ages are within the range of ages previously reported for cinder cones in the Hasandağ region. The linear diffusion model-derived ages are being compared to additional new 40Ar/39Ar dates in order to further assess the applicability of morphological dating to constrain the ages of cinder cones. The relatively well-constrained κ value we obtained by applying the linear diffusion model to cinder cones that range in age by nearly 500 ka suggests that this model can be used to date cinder cones. This κ value is higher than the well-established value of κ =3.9 for a cinder cone in a similar climate [3]. Therefore our work confirms the importance of determining appropriate κ values from nearby cones with known ages. References 1. C.A. Wood, J. Volcanol. Geotherm. Res. 8, 137 (1980) 2. D.M. Wood, M.F. Sheridan, J. Volcanol. Geotherm. Res. 83, 241 (1998) 3. J.D. Pelletier, M.L. Cline, Geology 35, 1067 (2007)

A diffusive ink transport model for lipid dip-pen nanolithography.

PubMed

Urtizberea, A; Hirtz, M

2015-10-14

Despite diverse applications, phospholipid membrane stacks generated by dip-pen nanolithography (DPN) still lack a thorough and systematic characterization that elucidates the whole ink transport process from writing to surface spreading, with the aim of better controlling the resulting feature size and resolution. We report a quantitative analysis and modeling of the dependence of lipid DPN features (area, height and volume) on dwell time and relative humidity. The ink flow rate increases with humidity in agreement with meniscus size growth, determining the overall feature size. The observed time dependence indicates the existence of a balance between surface spreading and the ink flow rate that promotes differences in concentration at the meniscus/substrate interface. Feature shape is controlled by the substrate surface energy. The results are analyzed within a modified model for the ink transport of diffusive inks. At any humidity the dependence of the area spread on the dwell time shows two diffusion regimes: at short dwell times growth is controlled by meniscus diffusion while at long dwell times surface diffusion governs the process. The critical point for the switch of regime depends on the humidity.

Cumulant expansions for measuring water exchange using diffusion MRI

NASA Astrophysics Data System (ADS)

Ning, Lipeng; Nilsson, Markus; Lasič, Samo; Westin, Carl-Fredrik; Rathi, Yogesh

2018-02-01

The rate of water exchange across cell membranes is a parameter of biological interest and can be measured by diffusion magnetic resonance imaging (dMRI). In this work, we investigate a stochastic model for the diffusion-and-exchange of water molecules. This model provides a general solution for the temporal evolution of dMRI signal using any type of gradient waveform, thereby generalizing the signal expressions for the Kärger model. Moreover, we also derive a general nth order cumulant expansion of the dMRI signal accounting for water exchange, which has not been explored in earlier studies. Based on this analytical expression, we compute the cumulant expansion for dMRI signals for the special case of single diffusion encoding (SDE) and double diffusion encoding (DDE) sequences. Our results provide a theoretical guideline on optimizing experimental parameters for SDE and DDE sequences, respectively. Moreover, we show that DDE signals are more sensitive to water exchange at short-time scale but provide less attenuation at long-time scale than SDE signals. Our theoretical analysis is also validated using Monte Carlo simulations on synthetic structures.

Prediction Of Abrasive And Diffusive Tool Wear Mechanisms In Machining

NASA Astrophysics Data System (ADS)

Rizzuti, S.; Umbrello, D.

2011-01-01

Tool wear prediction is regarded as very important task in order to maximize tool performance, minimize cutting costs and improve the quality of workpiece in cutting. In this research work, an experimental campaign was carried out at the varying of cutting conditions with the aim to measure both crater and flank tool wear, during machining of an AISI 1045 with an uncoated carbide tool P40. Parallel a FEM-based analysis was developed in order to study the tool wear mechanisms, taking also into account the influence of the cutting conditions and the temperature reached on the tool surfaces. The results show that, when the temperature of the tool rake surface is lower than the activation temperature of the diffusive phenomenon, the wear rate can be estimated applying an abrasive model. In contrast, in the tool area where the temperature is higher than the diffusive activation temperature, the wear rate can be evaluated applying a diffusive model. Finally, for a temperature ranges within the above cited values an adopted abrasive-diffusive wear model furnished the possibility to correctly evaluate the tool wear phenomena.

Physiological basis for noninvasive skin cancer diagnosis using diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Yao; Markey, Mia K.; Tunnell, James W.

2017-02-01

Diffuse reflectance spectroscopy offers a noninvasive, fast, and low-cost alternative to visual screening and biopsy for skin cancer diagnosis. We have previously acquired reflectance spectra from 137 lesions in 76 patients and determined the capability of spectral diagnosis using principal component analysis (PCA). However, it is not well elucidated why spectral analysis enables tissue classification. To provide the physiological basis, we used the Monte Carlo look-up table (MCLUT) model to extract physiological parameters from those clinical data. The MCLUT model results in the following physiological parameters: oxygen saturation, hemoglobin concentration, melanin concentration, vessel radius, and scattering parameters. Physiological parameters show that cancerous skin tissue has lower scattering and larger vessel radii, compared to normal tissue. These results demonstrate the potential of diffuse reflectance spectroscopy for detection of early precancerous changes in tissue. In the future, a diagnostic algorithm that combines these physiological parameters could be enable non-invasive diagnosis of skin cancer.

Thermodynamics analysis of diffusion in spark plasma sintering welding Cr3C2 and Ni

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhang, Jinyong; Leng, Xiaoxuan; Lei, Liwen; Fu, Zhengyi

2017-03-01

Spark plasma sintering (SPS) welding of chromium carbide (Cr3C2) and nickel (Ni) was used to investigate the atomic diffusion caused by bypassing current. It was found that the diffusion coefficient with bypassing current was enhanced by almost 3.57 times over that without bypassing current. Different from the previous researches, the thermodynamics analysis conducted herein showed that the enhancement included a current direction-independent part besides the known current direction-dependent part. A local temperature gradient (LTG) model was proposed to explain the current direction-independent effect. Assuming that the LTG was mainly due to the interfacial electric resistance causing heterogeneous Joule heating, the theoretical results were in good agreement with the experimental results both in the present and previous studies. This new LTG model provides a reasonable physical meaning for the low-temperature advantage of SPS welding and should be useful in a wide range of applications.

14 CFR Appendix I to Part 417 - Methodologies for Toxic Release Hazard Analysis and Operational Procedures

Code of Federal Regulations, 2014 CFR

2014-01-01

... physics on the transport and diffusion of each toxicant. (5) Meteorological conditions at the time of..., or for use in any real-time physics models used to ensure compliance with the toxic flight commit... atmospheric physics on the transport and diffusion of toxic propellants released; (5) Meteorological...

14 CFR Appendix I to Part 417 - Methodologies for Toxic Release Hazard Analysis and Operational Procedures

Code of Federal Regulations, 2012 CFR

2012-01-01

... physics on the transport and diffusion of each toxicant. (5) Meteorological conditions at the time of..., or for use in any real-time physics models used to ensure compliance with the toxic flight commit... atmospheric physics on the transport and diffusion of toxic propellants released; (5) Meteorological...

14 CFR Appendix I to Part 417 - Methodologies for Toxic Release Hazard Analysis and Operational Procedures

Code of Federal Regulations, 2011 CFR

2011-01-01

... physics on the transport and diffusion of each toxicant. (5) Meteorological conditions at the time of..., or for use in any real-time physics models used to ensure compliance with the toxic flight commit... atmospheric physics on the transport and diffusion of toxic propellants released; (5) Meteorological...

14 CFR Appendix I to Part 417 - Methodologies for Toxic Release Hazard Analysis and Operational Procedures

Code of Federal Regulations, 2013 CFR

2013-01-01

... physics on the transport and diffusion of each toxicant. (5) Meteorological conditions at the time of..., or for use in any real-time physics models used to ensure compliance with the toxic flight commit... atmospheric physics on the transport and diffusion of toxic propellants released; (5) Meteorological...

Asymptotic analysis of dissipative waves with applications to their numerical simulation

NASA Technical Reports Server (NTRS)

Hagstrom, Thomas

1990-01-01

Various problems involving the interplay of asymptotics and numerics in the analysis of wave propagation in dissipative systems are studied. A general approach to the asymptotic analysis of linear, dissipative waves is developed. It was applied to the derivation of asymptotic boundary conditions for numerical solutions on unbounded domains. Applications include the Navier-Stokes equations. Multidimensional traveling wave solutions to reaction-diffusion equations are also considered. A preliminary numerical investigation of a thermo-diffusive model of flame propagation in a channel with heat loss at the walls is presented.

Analysis of hemodynamics in human skin using photothermal radiometry and diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Verdel, Nina; Marin, Ana; Vidovič, Luka; Milanič, Matija; Majaron, Boris

2017-07-01

We present a novel methodology for quantitative analysis of hemodynamics in human skin in vivo. Our approach combines pulsed photothermal radiometry (i.e., time-resolved measurements of midinfrared emission from sample surface after exposure to a short light pulse) and diffuse reflectance spectroscopy in visible part of the spectrum. Experimental data are fitted with predictions of a numerical model of light transport in a four-layer skin model (i.e., inverse Monte Carlo), which allows assessment of the layer thicknesses, chromophore contents (e.g., melanin, oxy- and deoxy-hemoglobin), as well as scattering properties. The performance is tested in comparison analysis of healthy skin before and during application of a blood pressure cuff (at 200 mm Hg) for 5 minutes.

A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread.

PubMed

Swan, Amanda; Hillen, Thomas; Bowman, John C; Murtha, Albert D

2018-05-01

Gliomas are primary brain tumours arising from the glial cells of the nervous system. The diffuse nature of spread, coupled with proximity to critical brain structures, makes treatment a challenge. Pathological analysis confirms that the extent of glioma spread exceeds the extent of the grossly visible mass, seen on conventional magnetic resonance imaging (MRI) scans. Gliomas show faster spread along white matter tracts than in grey matter, leading to irregular patterns of spread. We propose a mathematical model based on Diffusion Tensor Imaging, a new MRI imaging technique that offers a methodology to delineate the major white matter tracts in the brain. We apply the anisotropic diffusion model of Painter and Hillen (J Thoer Biol 323:25-39, 2013) to data from 10 patients with gliomas. Moreover, we compare the anisotropic model to the state-of-the-art Proliferation-Infiltration (PI) model of Swanson et al. (Cell Prolif 33:317-329, 2000). We find that the anisotropic model offers a slight improvement over the standard PI model. For tumours with low anisotropy, the predictions of the two models are virtually identical, but for patients whose tumours show higher anisotropy, the results differ. We also suggest using the data from the contralateral hemisphere to further improve the model fit. Finally, we discuss the potential use of this model in clinical treatment planning.

Modeling intragranular diffusion in low-connectivity granular media

NASA Astrophysics Data System (ADS)

Ewing, Robert P.; Liu, Chongxuan; Hu, Qinhong

2012-03-01

Characterizing the diffusive exchange of solutes between bulk water in an aquifer and water in the intragranular pores of the solid phase is still challenging despite decades of study. Many disparities between observation and theory could be attributed to low connectivity of the intragranular pores. The presence of low connectivity indicates that a useful conceptual framework is percolation theory. The present study was initiated to develop a percolation-based finite difference (FD) model, and to test it rigorously against both random walk (RW) simulations of diffusion starting from nonequilibrium, and data on Borden sand published by Ball and Roberts (1991a,b) and subsequently reanalyzed by Haggerty and Gorelick (1995) using a multirate mass transfer (MRMT) approach. The percolation-theoretical model is simple and readily incorporated into existing FD models. The FD model closely matches the RW results using only a single fitting parameter, across a wide range of pore connectivities. Simulation of the Borden sand experiment without pore connectivity effects reproduced the MRMT analysis, but including low pore connectivity effects improved the fit. Overall, the theory and simulation results show that low intragranular pore connectivity can produce diffusive behavior that appears as if the solute had undergone slow sorption, despite the absence of any sorption process, thereby explaining some hitherto confusing aspects of intragranular diffusion.

Macroscopic modeling for heat and water vapor transfer in dry snow by homogenization.

PubMed

Calonne, Neige; Geindreau, Christian; Flin, Frédéric

2014-11-26

Dry snow metamorphism, involved in several topics related to cryospheric sciences, is mainly linked to heat and water vapor transfers through snow including sublimation and deposition at the ice-pore interface. In this paper, the macroscopic equivalent modeling of heat and water vapor transfers through a snow layer was derived from the physics at the pore scale using the homogenization of multiple scale expansions. The microscopic phenomena under consideration are heat conduction, vapor diffusion, sublimation, and deposition. The obtained macroscopic equivalent model is described by two coupled transient diffusion equations including a source term arising from phase change at the pore scale. By dimensional analysis, it was shown that the influence of such source terms on the overall transfers can generally not be neglected, except typically under small temperature gradients. The precision and the robustness of the proposed macroscopic modeling were illustrated through 2D numerical simulations. Finally, the effective vapor diffusion tensor arising in the macroscopic modeling was computed on 3D images of snow. The self-consistent formula offers a good estimate of the effective diffusion coefficient with respect to the snow density, within an average relative error of 10%. Our results confirm recent work that the effective vapor diffusion is not enhanced in snow.

Mass Transport of Macromolecules within an In Vitro Model of Supragingival Plaque

PubMed Central

Thurnheer, Thomas; Gmür, Rudolf; Shapiro, Stuart; Guggenheim, Bernhard

2003-01-01

The aim of this study was to examine the diffusion of macromolecules through an in vitro biofilm model of supragingival plaque. Polyspecies biofilms containing Actinomyces naeslundii, Fusobacterium nucleatum, Streptococcus oralis, Streptococcus sobrinus, Veillonella dispar, and Candida albicans were formed on sintered hydroxyapatite disks and then incubated at room temperature for defined periods with fluorescent markers with molecular weights ranging from 3,000 to 900,000. Subsequent examination by confocal laser scanning microscopy revealed that the mean square penetration depths for all tested macromolecules except immunoglobulin M increased linearly with time, diffusion coefficients being linearly proportional to the cube roots of the molecular weights of the probes (range, 10,000 to 240,000). Compared to diffusion in bulk water, diffusion in the biofilms was markedly slower. The rate of diffusion for each probe appeared to be constant and not a function of biofilm depth. Analysis of diffusion phenomena through the biofilms suggested tortuosity as the most probable explanation for retarded diffusion. Selective binding of probes to receptors present in the biofilms could not explain the observed extent of retardation of diffusion. These results are relevant to oral health, as selective attenuated diffusion of fermentable carbohydrates and acids produced within dental plaque is thought to be essential for the development of carious lesions. PMID:12620862

Particle deposition due to turbulent diffusion in the upper respiratory system

NASA Technical Reports Server (NTRS)

Hamill, P.

1979-01-01

Aerosol deposition in the upper respiratory system (trachea to segmental bronchi) is considered and the importance of turbulent diffusion as a deposition mechanism is evaluated. It is demonstrated that for large particles (diameter greater than about 5 microns), turbulent diffusion is the dominant deposition mechanism in the trachea. Conditions under which turbulent diffusion may be important in successive generations of the pulmonary system are determined. The probability of particle deposition is compared with probabilities of deposition, as determined by the equations generally used in regional deposition models. The analysis is theoretical; no new experimental data is presented.

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 class of exact solutions for biomacromolecule diffusion-reaction in live cells.

PubMed

Sadegh Zadeh, Kouroush; Montas, Hubert J

2010-06-07

A class of novel explicit analytic solutions for a system of n+1 coupled partial differential equations governing biomolecular mass transfer and reaction in living organisms are proposed, evaluated, and analyzed. The solution process uses Laplace and Hankel transforms and results in a recursive convolution of an exponentially scaled Gaussian with modified Bessel functions. The solution is developed for wide range of biomolecular binding kinetics from pure diffusion to multiple binding reactions. The proposed approach provides solutions for both Dirac and Gaussian laser beam (or fluorescence-labeled biomacromolecule) profiles during the course of a Fluorescence Recovery After Photobleaching (FRAP) experiment. We demonstrate that previous models are simplified forms of our theory for special cases. Model analysis indicates that at the early stages of the transport process, biomolecular dynamics is governed by pure diffusion. At large times, the dominant mass transfer process is effective diffusion. Analysis of the sensitivity equations, derived analytically and verified by finite difference differentiation, indicates that experimental biologists should use full space-time profile (instead of the averaged time series) obtained at the early stages of the fluorescence microscopy experiments to extract meaningful physiological information from the protocol. Such a small time frame requires improved bioinstrumentation relative to that in use today. Our mathematical analysis highlights several limitations of the FRAP protocol and provides strategies to improve it. The proposed model can be used to study biomolecular dynamics in molecular biology, targeted drug delivery in normal and cancerous tissues, motor-driven axonal transport in normal and abnormal nervous systems, kinetics of diffusion-controlled reactions between enzyme and substrate, and to validate numerical simulators of biological mass transport processes in vivo. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Gene selection and cancer type classification of diffuse large-B-cell lymphoma using a bivariate mixture model for two-species data.

PubMed

Su, Yuhua; Nielsen, Dahlia; Zhu, Lei; Richards, Kristy; Suter, Steven; Breen, Matthew; Motsinger-Reif, Alison; Osborne, Jason

2013-01-05

: A bivariate mixture model utilizing information across two species was proposed to solve the fundamental problem of identifying differentially expressed genes in microarray experiments. The model utility was illustrated using a dog and human lymphoma data set prepared by a group of scientists in the College of Veterinary Medicine at North Carolina State University. A small number of genes were identified as being differentially expressed in both species and the human genes in this cluster serve as a good predictor for classifying diffuse large-B-cell lymphoma (DLBCL) patients into two subgroups, the germinal center B-cell-like diffuse large B-cell lymphoma and the activated B-cell-like diffuse large B-cell lymphoma. The number of human genes that were observed to be significantly differentially expressed (21) from the two-species analysis was very small compared to the number of human genes (190) identified with only one-species analysis (human data). The genes may be clinically relevant/important, as this small set achieved low misclassification rates of DLBCL subtypes. Additionally, the two subgroups defined by this cluster of human genes had significantly different survival functions, indicating that the stratification based on gene-expression profiling using the proposed mixture model provided improved insight into the clinical differences between the two cancer subtypes.

Mathematical Modeling of Herpes Simplex Virus Distribution in Solid Tumors: Implications for Cancer Gene Therapy

PubMed Central

Mok, Wilson; Stylianopoulos, Triantafyllos; Boucher, Yves; Jain, Rakesh K.

2010-01-01

Purpose Although oncolytic viral vectors show promise for the treatment of various cancers, ineffective initial distribution and propagation throughout the tumor mass often limit the therapeutic response. A mathematical model is developed to describe the spread of herpes simplex virus from the initial injection site. Experimental Design The tumor is modeled as a sphere of radius R. The model incorporates reversible binding, interstitial diffusion, viral degradation, and internalization and physiologic parameters. Three species are considered as follows: free interstitial virus, virus bound to cell surfaces, and internalized virus. Results This analysis reveals that both rapid binding and internalization as well as hindered diffusion contain the virus to the initial injection volume, with negligible spread to the surrounding tissue. Unfortunately, increasing the dose to saturate receptors and promote diffusion throughout the tumor is not a viable option: the concentration necessary would likely compromise safety. However, targeted modifications to the virus that decrease the binding affinity have the potential to increase the number of infected cells by 1.5-fold or more. An increase in the effective diffusion coefficient can result in similar gains. Conclusions This analysis suggests criteria by which the potential response of a tumor to oncolytic herpes simplex virus therapy can be assessed. Furthermore, it reveals the potential of modifications to the vector delivery method, physicochemical properties of the virus, and tumor extracellular matrix composition to enhance efficacy. PMID:19318482

Mass diffusion coefficient measurement for vitreous humor using FEM and MRI

NASA Astrophysics Data System (ADS)

Rattanakijsuntorn, Komsan; Penkova, Anita; Sadha, Satwindar S.

2018-01-01

In early studies, the ‘contour method’ for determining the diffusion coefficient of the vitreous humor was developed. This technique relied on careful injection of an MRI contrast agent (surrogate drug) into the vitreous humor of fresh bovine eyes, and tracking the contours of the contrast agent in time. In addition, an analytical solution was developed for the theoretical contours built on point source model for the injected surrogate drug. The match between theoretical and experimental contours as a least square fit, while floating the diffusion coefficient, led to the value of the diffusion coefficient. This method had its limitation that the initial injection of the surrogate had to be spherical or ellipsoidal because of the analytical result based on the point-source model. With a new finite element model for the analysis in this study, the technique is much less restrictive and handles irregular shapes of the initial bolus. The fresh bovine eyes were used for drug diffusion study in the vitreous and three contrast agents of different molecular masses: gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA, 938 Da), non-ionic gadoteridol (Prohance, 559 Da), and bovine albumin conjugated with gadolinium (Galbumin, 74 kDa) were used as drug surrogates to visualize the diffusion process by MRI. The 3D finite element model was developed to determine the diffusion coefficients of these surrogates with the images from MRI. This method can be used for other types of bioporous media provided the concentration profile can be visualized (by methods such as MRI or fluorescence).

Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models

PubMed Central

Marias, Kostas; Lambregts, Doenja M. J.; Nikiforaki, Katerina; van Heeswijk, Miriam M.; Bakers, Frans C. H.; Beets-Tan, Regina G. H.

2017-01-01

Purpose The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer. Material and methods Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm2) at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG) and non-Gaussian (MNG and BNG) were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R2 and Root Mean Square Error (RMSE). To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC) and F-ratio. Results All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area. Conclusion No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior. PMID:28863161

Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.

PubMed

Manikis, Georgios C; Marias, Kostas; Lambregts, Doenja M J; Nikiforaki, Katerina; van Heeswijk, Miriam M; Bakers, Frans C H; Beets-Tan, Regina G H; Papanikolaou, Nikolaos

2017-01-01

The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer. Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm2) at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG) and non-Gaussian (MNG and BNG) were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R2 and Root Mean Square Error (RMSE). To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC) and F-ratio. All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area. No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior.

Anomalous extracellular diffusion in rat cerebellum.

PubMed

Xiao, Fanrong; Hrabe, Jan; Hrabetova, Sabina

2015-05-05

Extracellular space (ECS) is a major channel transporting biologically active molecules and drugs in the brain. Diffusion-mediated transport of these substances is hindered by the ECS structure but the microscopic basis of this hindrance is not fully understood. One hypothesis proposes that the hindrance originates in large part from the presence of dead-space (DS) microdomains that can transiently retain diffusing molecules. Because previous theoretical and modeling work reported an initial period of anomalous diffusion in similar environments, we expected that brain regions densely populated by DS microdomains would exhibit anomalous extracellular diffusion. Specifically, we targeted granular layers (GL) of rat and turtle cerebella that are populated with large and geometrically complex glomeruli. The integrative optical imaging (IOI) method was employed to evaluate diffusion of fluorophore-labeled dextran (MW 3000) in GL, and the IOI data analysis was adapted to quantify the anomalous diffusion exponent dw from the IOI records. Diffusion was significantly anomalous in rat GL, where dw reached 4.8. In the geometrically simpler turtle GL, dw was elevated but not robustly anomalous (dw = 2.6). The experimental work was complemented by numerical Monte Carlo simulations of anomalous ECS diffusion in several three-dimensional tissue models containing glomeruli-like structures. It demonstrated that both the duration of transiently anomalous diffusion and the anomalous exponent depend on the size of model glomeruli and the degree of their wrapping. In conclusion, we have found anomalous extracellular diffusion in the GL of rat cerebellum. This finding lends support to the DS microdomain hypothesis. Transiently anomalous diffusion also has a profound effect on the spatiotemporal distribution of molecules released into the ECS, especially at diffusion distances on the order of a few cell diameters, speeding up short-range diffusion-mediated signals in less permeable structures. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Front fingering and complex dynamics driven by the interaction of buoyancy and diffusive instabilities.

PubMed

D'Hernoncourt, J; Merkin, J H; De Wit, A

2007-09-01

Traveling fronts can become transversally unstable either because of a diffusive instability arising when the key variables diffuse at sufficiently different rates or because of a buoyancy-driven Rayleigh-Taylor mechanism when the density jump across the front is statically unfavorable. The interaction between such diffusive and buoyancy instabilities of fronts is analyzed theoretically for a simple model system. Linear stability analysis and nonlinear simulations show that their interplay changes considerably the stability properties with regard to the pure Rayleigh-Taylor or diffusive instabilities of fronts. In particular, an instability scenario can arise which triggers convection around statically stable fronts as a result of differential diffusion. Moreover, spatiotemporal chaos can be observed when both buoyancy and diffusive effects cooperate to destabilize the front. Experimental conditions to test our predictions are suggested.

Theoretical Analysis of Drug Dissolution: I. Solubility and Intrinsic Dissolution Rate.

PubMed

Shekunov, Boris; Montgomery, Eda Ross

2016-09-01

The first-principles approach presented in this work combines surface kinetics and convective diffusion modeling applied to compounds with pH-dependent solubility and in different dissolution media. This analysis is based on experimental data available for approximately 100 compounds of pharmaceutical interest. Overall, there is a linear relationship between the drug solubility and intrinsic dissolution rate expressed through the total kinetic coefficient of dissolution and dimensionless numbers defining the mass transfer regime. The contribution of surface kinetics appears to be significant constituting on average ∼20% resistance to the dissolution flux in the compendial rotating disk apparatus at 100 rpm. The surface kinetics contribution becomes more dominant under conditions of fast laminar or turbulent flows or in cases when the surface kinetic coefficient may decrease as a function of solution composition or pH. Limitations of the well-known convective diffusion equation for rotating disk by Levich are examined using direct computational modeling with simultaneous dissociation and acid-base reactions in which intrinsic dissolution rate is strongly dependent on pH profile and solution ionic strength. It is shown that concept of diffusion boundary layer does not strictly apply for reacting/interacting species and that thin-film diffusion models cannot be used quantitatively in general case. Copyright © 2016. Published by Elsevier Inc.

The prediction of nozzle performance and heat transfer in hydrogen/oxygen rocket engines with transpiration cooling, film cooling, and high area ratios

NASA Technical Reports Server (NTRS)

Kacynski, Kenneth J.; Hoffman, Joe D.

1993-01-01

An advanced engineering computational model has been developed to aid in the analysis and design of hydrogen/oxygen chemical rocket engines. The complete multi-species, chemically reacting and diffusing Navier-Stokes equations are modelled, finite difference approach that is tailored to be conservative in an axisymmetric coordinate system for both the inviscid and viscous terms. Demonstration cases are presented for a 1030:1 area ratio nozzle, a 25 lbf film cooled nozzle, and transpiration cooled plug-and-spool rocket engine. The results indicate that the thrust coefficient predictions of the 1030:1 nozzle and the film cooled nozzle are within 0.2 to 0.5 percent, respectively, of experimental measurements when all of the chemical reaction and diffusion terms are considered. Further, the model's predictions agree very well with the heat transfer measurements made in all of the nozzle test cases. The Soret thermal diffusion term is demonstrated to have a significant effect on the predicted mass fraction of hydrogen along the wall of the nozzle in both the laminar flow 1030:1 nozzle and the turbulent plug-and-spool rocket engine analysis cases performed. Further, the Soret term was shown to represent a significant fraction of the diffusion fluxes occurring in the transpiration cooled rocket engine.

Multispecies diffusion models: A study of uranyl species diffusion

NASA Astrophysics Data System (ADS)

Liu, Chongxuan; Shang, Jianying; Zachara, John M.

2011-12-01

Rigorous numerical description of multispecies diffusion requires coupling of species, charge, and aqueous and surface complexation reactions that collectively affect diffusive fluxes. The applicability of a fully coupled diffusion model is, however, often constrained by the availability of species self-diffusion coefficients, as well as by computational complication in imposing charge conservation. In this study, several diffusion models with variable complexity in charge and species coupling were formulated and compared to describe reactive multispecies diffusion in groundwater. Diffusion of uranyl [U(VI)] species was used as an example in demonstrating the effectiveness of the models in describing multispecies diffusion. Numerical simulations found that a diffusion model with a single, common diffusion coefficient for all species was sufficient to describe multispecies U(VI) diffusion under a steady state condition of major chemical composition, but not under transient chemical conditions. Simulations revealed that for multispecies U(VI) diffusion under transient chemical conditions, a fully coupled diffusion model could be well approximated by a component-based diffusion model when the diffusion coefficient for each chemical component was properly selected. The component-based diffusion model considers the difference in diffusion coefficients between chemical components, but not between the species within each chemical component. This treatment significantly enhanced computational efficiency at the expense of minor charge conservation. The charge balance in the component-based diffusion model can be enforced, if necessary, by adding a secondary migration term resulting from model simplification. The effect of ion activity coefficient gradients on multispecies diffusion is also discussed. The diffusion models were applied to describe U(VI) diffusive mass transfer in intragranular domains in two sediments collected from U.S. Department of Energy's Hanford 300A, where intragranular diffusion is a rate-limiting process controlling U(VI) adsorption and desorption. The grain-scale reactive diffusion model was able to describe U(VI) adsorption/desorption kinetics that had been previously described using a semiempirical, multirate model. Compared with the multirate model, the diffusion models have the advantage to provide spatiotemporal speciation evolution within the diffusion domains.

Analysis techniques for tracer studies of oxidation. M. S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Basu, S. N.

1984-01-01

Analysis techniques to obtain quantitative diffusion data from tracer concentration profiles were developed. Mass balance ideas were applied to determine the mechanism of oxide growth and to separate the fraction of inward and outward growth of oxide scales. The process of inward oxygen diffusion with exchange was theoretically modelled and the effect of lattice diffusivity, grain boundary diffusivity and grain size on the tracer concentration profile was studied. The development of the tracer concentration profile in a growing oxide scale was simulated. The double oxidation technique was applied to a FeCrAl-Zr alloy using 0-18 as a tracer. SIMS was used to obtain the tracer concentration profile. The formation of lacey oxide on the alloy was discussed. Careful consideration was given to the quality of data required to obtain quantitative information.

Cellular interface morphologies in directional solidification. III - The effects of heat transfer and solid diffusivity

NASA Technical Reports Server (NTRS)

Ungar, Lyle H.; Bennett, Mark J.; Brown, Robert A.

1985-01-01

The shape and stability of two-dimensional finite-amplitude cellular interfaces arising during directional solidification are compared for several solidification models that account differently for latent heat released at the interface, unequal thermal conductivities of melt and solid, and solute diffusivity in the solid. Finite-element analysis and computer-implemented perturbation methods are used to analyze the families of steadily growing cellular forms that evolve from the planar state. In all models a secondary bifurcation between different families of finite-amplitude cells exists that halves the spatial wavelength of the stable interface. The quantitative location of this transition is very dependent on the details of the model. Large amounts of solute diffusion in the solid retard the growth of large-amplitude cells.

Single-shot spiral imaging enabled by an expanded encoding model: Demonstration in diffusion MRI.

PubMed

Wilm, Bertram J; Barmet, Christoph; Gross, Simon; Kasper, Lars; Vannesjo, S Johanna; Haeberlin, Max; Dietrich, Benjamin E; Brunner, David O; Schmid, Thomas; Pruessmann, Klaas P

2017-01-01

The purpose of this work was to improve the quality of single-shot spiral MRI and demonstrate its application for diffusion-weighted imaging. Image formation is based on an expanded encoding model that accounts for dynamic magnetic fields up to third order in space, nonuniform static B 0 , and coil sensitivity encoding. The encoding model is determined by B 0 mapping, sensitivity mapping, and concurrent field monitoring. Reconstruction is performed by iterative inversion of the expanded signal equations. Diffusion-tensor imaging with single-shot spiral readouts is performed in a phantom and in vivo, using a clinical 3T instrument. Image quality is assessed in terms of artefact levels, image congruence, and the influence of the different encoding factors. Using the full encoding model, diffusion-weighted single-shot spiral imaging of high quality is accomplished both in vitro and in vivo. Accounting for actual field dynamics, including higher orders, is found to be critical to suppress blurring, aliasing, and distortion. Enhanced image congruence permitted data fusion and diffusion tensor analysis without coregistration. Use of an expanded signal model largely overcomes the traditional vulnerability of spiral imaging with long readouts. It renders single-shot spirals competitive with echo-planar readouts and thus deploys shorter echo times and superior readout efficiency for diffusion imaging and further prospective applications. Magn Reson Med 77:83-91, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Assessment of diffuse radiation models in Azores

NASA Astrophysics Data System (ADS)

Magarreiro, Clarisse; Brito, Miguel; Soares, Pedro; Azevedo, Eduardo

2014-05-01

Measured irradiance databases usually consist of global solar radiation data with limited spatial coverage. Hence, solar radiation models have been developed to estimate the diffuse fraction from the measured global irradiation. This information is critical for the assessment of the potential of solar energy technologies; for example, the decision to use photovoltaic systems with tracking system. The different solar radiation models for this purpose differ on the parameters used as input. The simplest, and most common, are models which use global radiation information only. More sophisticated models require meteorological parameters such as information from clouds, atmospheric turbidity, temperature or precipitable water content. Most of these models comprise correlations with the clearness index, kt (portion of horizontal extra-terrestrial radiation reaching the Earth's surface) to obtain the diffuse fraction kd (portion of diffuse component from global radiation). The applicability of these different models is related to the local atmospheric conditions and its climatic characteristics. The models are not of general validity and can only be applicable to locations where the albedo of the surrounding terrain and the atmospheric contamination by dust are not significantly different from those where the corresponding methods were developed. Thus, models of diffuse fraction exhibit a relevant degree of location dependence: e.g. models developed considering data acquired in Europe are mainly linked to Northern, Central or, more recently, Mediterranean areas. The Azores Archipelago, with its particular climate and cloud cover characteristics, different from mainland Europe, has not yet been considered for the development of testing of such models. The Azorean climate reveals large amounts of cloud cover in its annual cycle, with spatial and temporal variabilities more complex than the common Summer/Winter pattern. This study explores the applicability of different existing correlation models of diffuse fraction and clearness index or other plain parameters to the Azorean region. Reliable data provided by the Atmospheric Radiation Measurements (ARM) Climate Research Facility from the Graciosa Island deployment of the ARM Mobile Facility (http://www.arm.gov/sites/amf/grw) was used to perform the analysis. Model results showed a tendency to underestimate higher values of diffuse radiation. From the performance results of the correlation models reviewed it was clear that there is room for improvement.

Numerical analysis of the diffusive mass transport in brain tissues with applications to optical sensors

NASA Astrophysics Data System (ADS)

Neculae, Adrian P.; Otte, Andreas; Curticapean, Dan

2013-03-01

In the brain-cell microenvironment, diffusion plays an important role: apart from delivering glucose and oxygen from the vascular system to brain cells, it also moves informational substances between cells. The brain is an extremely complex structure of interwoven, intercommunicating cells, but recent theoretical and experimental works showed that the classical laws of diffusion, cast in the framework of porous media theory, can deliver an accurate quantitative description of the way molecules are transported through this tissue. The mathematical modeling and the numerical simulations are successfully applied in the investigation of diffusion processes in tissues, replacing the costly laboratory investigations. Nevertheless, modeling must rely on highly accurate information regarding the main parameters (tortuosity, volume fraction) which characterize the tissue, obtained by structural and functional imaging. The usual techniques to measure the diffusion mechanism in brain tissue are the radiotracer method, the real time iontophoretic method and integrative optical imaging using fluorescence microscopy. A promising technique for obtaining the values for characteristic parameters of the transport equation is the direct optical investigation using optical fibers. The analysis of these parameters also reveals how the local geometry of the brain changes with time or under pathological conditions. This paper presents a set of computations concerning the mass transport inside the brain tissue, for different types of cells. By measuring the time evolution of the concentration profile of an injected substance and using suitable fitting procedures, the main parameters characterizing the tissue can be determined. This type of analysis could be an important tool in understanding the functional mechanisms of effective drug delivery in complex structures such as the brain tissue. It also offers possibilities to realize optical imaging methods for in vitro and in vivo measurements using optical fibers. The model also may help in radiotracer biomarker models for the understanding of the mechanism of action of new chemical entities.

Impulsive synchronization of stochastic reaction-diffusion neural networks with mixed time delays.

PubMed

Sheng, Yin; Zeng, Zhigang

2018-07-01

This paper discusses impulsive synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and hybrid time delays. By virtue of inequality techniques, theories of stochastic analysis, linear matrix inequalities, and the contradiction method, sufficient criteria are proposed to ensure exponential synchronization of the addressed stochastic reaction-diffusion neural networks with mixed time delays via a designed impulsive controller. Compared with some recent studies, the neural network models herein are more general, some restrictions are relaxed, and the obtained conditions enhance and generalize some published ones. Finally, two numerical simulations are performed to substantiate the validity and merits of the developed theoretical analysis. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analytical Study of Gravity Effects on Laminar Diffusion Flames

NASA Technical Reports Server (NTRS)

Edelman, R. B.; Fortune, O.; Weilerstein, G.

1972-01-01

A mathematical model is presented for the description of axisymmetric laminar-jet diffusion flames. The analysis includes the effects of inertia, viscosity, diffusion, gravity and combustion. These mechanisms are coupled in a boundary layer type formulation and solutions are obtained by an explicit finite difference technique. A dimensional analysis shows that the maximum flame width radius, velocity and thermodynamic state characterize the flame structure. Comparisons with experimental data showed excellent agreement for normal gravity flames and fair agreement for steady state low Reynolds number zero gravity flames. Kinetics effects and radiation are shown to be the primary mechanisms responsible for this discrepancy. Additional factors are discussed including elipticity and transient effects.

Diffusion Weighted Magnetic Resonance Imaging Assessment of Blood Flow in the Microvasculature of Abdominal Organs

NASA Astrophysics Data System (ADS)

Truica, Loredana Sorina

In this thesis, water diffusion in human liver and placenta is studied using diffusion weighted magnetic resonance imaging. For short, randomly oriented vascular segments, intravascular water motion is diffusion-like. For tissues with large vascular compartments the diffusion decay is bi-exponential with one component corresponding to diffusing water and the other to water in the microvasculature. This model, known as the intravoxel incoherent motion (IVIM) model, is seldom used with abdominal organs because of motion artifacts. This limitation was overcome for the experiments reported here by introducing: 1) parallel imaging, 2) navigator echo respiratory triggering (NRT), 3) a double echo diffusion sequence that inherently compensates for eddy current effects, 4) SPAIR fat suppression and 5) a superior approach to image analysis. In particular, the use of NRT allowed us to use a free breathing protocol instead of the previously required breath hold protocol. The resulting DWI images were of high quality and motion artifact free. Diffusion decays were measured over a larger portion of the decay than had previously been reported and the results are considerably better than those previously reported. For both studies, reliable measurements of the diffusion coefficient (D), pseudo-diffusion coefficient (D) and perfusion fraction (f), were obtained using a region of interest analysis as well as a pixel-by-pixel approach. To within experimental error, all patients had the same values of D (1.10 mum 2/ms +/- 0.16 mum2/ms), D* (46 mum2/ms +/- 17 mum2/ms) and f (44.0% +/- 6.9%) in liver and D (1.8 mum 2/ms +/- 0.2 mum2/ms), D* (30 mum 2/ms +/- 12 mmu2/ms), and f (40% +/- 6%) in the placenta. No dependence on gestational age was found for the placental study. Parametric maps of f and D* were consistent with blood flow patterns in both systems. The model worked well for both investigated organs even though their anatomical structures are quite different. A method for removing rectified noise bias from low intensity magnitude MR images measured with phased array coils is also presented. This algorithm has significance for diffusion decay measurements since it permits the use of low intensity data points which could, for example, allow the acquisition of high resolution parametric maps.

Kinetics of CO2 diffusion in human carbonic anhydrase: a study using molecular dynamics simulations and the Markov-state model.

PubMed

Chen, Gong; Kong, Xian; Lu, Diannan; Wu, Jianzhong; Liu, Zheng

2017-05-10

Molecular dynamics (MD) simulations, in combination with the Markov-state model (MSM), were applied to probe CO 2 diffusion from an aqueous solution into the active site of human carbonic anhydrase II (hCA-II), an enzyme useful for enhanced CO 2 capture and utilization. The diffusion process in the hydrophobic pocket of hCA-II was illustrated in terms of a two-dimensional free-energy landscape. We found that CO 2 diffusion in hCA-II is a rate-limiting step in the CO 2 diffusion-binding-reaction process. The equilibrium distribution of CO 2 shows its preferential accumulation within a hydrophobic domain in the protein core region. An analysis of the committors and reactive fluxes indicates that the main pathway for CO 2 diffusion into the active site of hCA-II is through a binding pocket where residue Gln 136 contributes to the maximal flux. The simulation results offer a new perspective on the CO 2 hydration kinetics and useful insights toward the development of novel biochemical processes for more efficient CO 2 sequestration and utilization.

Brownian Motion at Lipid Membranes: A Comparison of Hydrodynamic Models Describing and Experiments Quantifying Diffusion within Lipid Bilayers.

PubMed

Block, Stephan

2018-05-22

The capability of lipid bilayers to exhibit fluid-phase behavior is a fascinating property, which enables, for example, membrane-associated components, such as lipids (domains) and transmembrane proteins, to diffuse within the membrane. These diffusion processes are of paramount importance for cells, as they are for example involved in cell signaling processes or the recycling of membrane components, but also for recently developed analytical approaches, which use differences in the mobility for certain analytical purposes, such as in-membrane purification of membrane proteins or the analysis of multivalent interactions. Here, models describing the Brownian motion of membrane inclusions (lipids, peptides, proteins, and complexes thereof) in model bilayers (giant unilamellar vesicles, black lipid membranes, supported lipid bilayers) are summarized and model predictions are compared with the available experimental data, thereby allowing for evaluating the validity of the introduced models. It will be shown that models describing the diffusion in freestanding (Saffman-Delbrück and Hughes-Pailthorpe-White model) and supported bilayers (the Evans-Sackmann model) are well supported by experiments, though only few experimental studies have been published so far for the latter case, calling for additional tests to reach the same level of experimental confirmation that is currently available for the case of freestanding bilayers.

The Prediction of Nozzle Performance and Heat Transfer in Hydrogen/Oxygen Rocket Engines with Transpiration Cooling, Film Cooling, and High Area Ratios

NASA Technical Reports Server (NTRS)

Kacynski, Kenneth J.; Hoffman, Joe D.

1994-01-01

An advanced engineering computational model has been developed to aid in the analysis of chemical rocket engines. The complete multispecies, chemically reacting and diffusing Navier-Stokes equations are modelled, including the Soret thermal diffusion and Dufour energy transfer terms. Demonstration cases are presented for a 1030:1 area ratio nozzle, a 25 lbf film-cooled nozzle, and a transpiration-cooled plug-and-spool rocket engine. The results indicate that the thrust coefficient predictions of the 1030:1 nozzle and the film-cooled nozzle are within 0.2 to 0.5 percent, respectively, of experimental measurements. Further, the model's predictions agree very well with the heat transfer measurements made in all of the nozzle test cases. It is demonstrated that thermal diffusion has a significant effect on the predicted mass fraction of hydrogen along the wall of the nozzle and was shown to represent a significant fraction of the diffusion fluxes occurring in the transpiration-cooled rocket engine.

Ion Beam Analysis of Diffusion in Diamondlike Carbon Films

NASA Astrophysics Data System (ADS)

Chaffee, Kevin Paul

The van de Graaf accelerator facility at Case Western Reserve University was developed into an analytical research center capable of performing Rutherford Backscattering Spectrometry, Elastic Recoil Detection Analysis for hydrogen profiling, Proton Enhanced Scattering, and ^4 He resonant scattering for ^{16 }O profiling. These techniques were applied to the study of Au, Na^+, Cs ^+, and H_2O water diffusion in a-C:H films. The results are consistent with the fully constrained network model of the microstructure as described by Angus and Jansen.

Stochastic Analysis and Applied Probability(3.3.1): Topics in the Theory and Applications of Stochastic Analysis

DTIC Science & Technology

2015-08-13

is due to Reiman [36] who considered the case where the arrivals and services are mutually independent renewal processes with square integrable summands...to a reflected diffusion process with drift and diffusion coefficients that depend on the state of the process. In models considered in works of Reiman ...the infinity Laplacian. Jour. AMS, to appear [36] M. I. Reiman . Open queueing networks in heavy traffic. Mathematics of Operations Research, 9(3): 441

Catalytic conversion reactions mediated by single-file diffusion in linear nanopores: hydrodynamic versus stochastic behavior.

PubMed

Ackerman, David M; Wang, Jing; Wendel, Joseph H; Liu, Da-Jiang; Pruski, Marek; Evans, James W

2011-03-21

We analyze the spatiotemporal behavior of species concentrations in a diffusion-mediated conversion reaction which occurs at catalytic sites within linear pores of nanometer diameter. Diffusion within the pores is subject to a strict single-file (no passing) constraint. Both transient and steady-state behavior is precisely characterized by kinetic Monte Carlo simulations of a spatially discrete lattice-gas model for this reaction-diffusion process considering various distributions of catalytic sites. Exact hierarchical master equations can also be developed for this model. Their analysis, after application of mean-field type truncation approximations, produces discrete reaction-diffusion type equations (mf-RDE). For slowly varying concentrations, we further develop coarse-grained continuum hydrodynamic reaction-diffusion equations (h-RDE) incorporating a precise treatment of single-file diffusion in this multispecies system. The h-RDE successfully describe nontrivial aspects of transient behavior, in contrast to the mf-RDE, and also correctly capture unreactive steady-state behavior in the pore interior. However, steady-state reactivity, which is localized near the pore ends when those regions are catalytic, is controlled by fluctuations not incorporated into the hydrodynamic treatment. The mf-RDE partly capture these fluctuation effects, but cannot describe scaling behavior of the reactivity.

Fractal analysis of lateral movement in biomembranes.

PubMed

Gmachowski, Lech

2018-04-01

Lateral movement of a molecule in a biomembrane containing small compartments (0.23-μm diameter) and large ones (0.75 μm) is analyzed using a fractal description of its walk. The early time dependence of the mean square displacement varies from linear due to the contribution of ballistic motion. In small compartments, walking molecules do not have sufficient time or space to develop an asymptotic relation and the diffusion coefficient deduced from the experimental records is lower than that measured without restrictions. The model makes it possible to deduce the molecule step parameters, namely the step length and time, from data concerning confined and unrestricted diffusion coefficients. This is also possible using experimental results for sub-diffusive transport. The transition from normal to anomalous diffusion does not affect the molecule step parameters. The experimental literature data on molecular trajectories recorded at a high time resolution appear to confirm the modeled value of the mean free path length of DOPE for Brownian and anomalous diffusion. Although the step length and time give the proper values of diffusion coefficient, the DOPE speed calculated as their quotient is several orders of magnitude lower than the thermal speed. This is interpreted as a result of intermolecular interactions, as confirmed by lateral diffusion of other molecules in different membranes. The molecule step parameters are then utilized to analyze the problem of multiple visits in small compartments. The modeling of the diffusion exponent results in a smooth transition to normal diffusion on entering a large compartment, as observed in experiments.

Tracer counterpermeation analysis of diffusivity in finite-length nanopores with and without single-file dynamics

DOE PAGES

Ackerman, David M.; Evans, James W.

2017-01-19

Here, we perform a tracer counterpermeation (TCP) analysis for a stochastic model of diffusive transport through a narrow linear pore where passing of species within the pore is inhibited or even excluded (single-file diffusion). TCP involves differently labeled but otherwise identical particles from two decoupled infinite reservoirs adsorbing into opposite ends of the pore, and desorbing from either end. In addition to transient behavior, we assess steady-state concentration profiles, spatial correlations, particle number fluctuations, and diffusion fluxes through the pore. From the profiles and fluxes, we determine a generalized tracer diffusion coefficient D tr(x), at various positions x within themore » pore. D tr(x) has a plateau value in the pore center scaling inversely with the pore length, but it is enhanced near the pore openings. The latter feature reflects the effect of fluctuations in adsorption and desorption, and it is also associated with a nontrivial scaling of the concentration profiles near the pore openings.« less

Tracer counterpermeation analysis of diffusivity in finite-length nanopores with and without single-file dynamics

NASA Astrophysics Data System (ADS)

Ackerman, David M.; Evans, James W.

2017-01-01

We perform a tracer counterpermeation (TCP) analysis for a stochastic model of diffusive transport through a narrow linear pore where passing of species within the pore is inhibited or even excluded (single-file diffusion). TCP involves differently labeled but otherwise identical particles from two decoupled infinite reservoirs adsorbing into opposite ends of the pore, and desorbing from either end. In addition to transient behavior, we assess steady-state concentration profiles, spatial correlations, particle number fluctuations, and diffusion fluxes through the pore. From the profiles and fluxes, we determine a generalized tracer diffusion coefficient Dtr(x ) , at various positions x within the pore. Dtr(x ) has a plateau value in the pore center scaling inversely with the pore length, but it is enhanced near the pore openings. The latter feature reflects the effect of fluctuations in adsorption and desorption, and it is also associated with a nontrivial scaling of the concentration profiles near the pore openings.

Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials.

PubMed

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun; Wang, Bei; Bremer, Peer-Timo; Papka, Michael E; Curtiss, Larry A; Pascucci, Valerio

2016-01-01

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermally annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.

Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials

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

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun

2016-01-01

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermallymore » annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.« less

Interstitial and interlayer ion diffusion geometry extraction in graphitic nanosphere battery materials

DOE PAGES

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun; ...

2016-01-31

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermallymore » annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Lastly, our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.« less

Computation of the unsteady facilitated transport of oxygen in hemoglobin

NASA Technical Reports Server (NTRS)

Davis, Sanford

1990-01-01

The transport of a reacting permeant diffusing through a thin membrane is extended to more realistic dissociation models. A new nonlinear analysis of the reaction-diffusion equations, using implicit finite-difference methods and direct block solvers, is used to study the limits of linearized and equilibrium theories. Computed curves of molecular oxygen permeating through hemoglobin solution are used to illustrate higher-order reaction models, the effect of concentration boundary layers at the membrane interfaces, and the transient buildup of oxygen flux.

Modeling of outgassing and matrix decomposition in carbon-phenolic composites

NASA Technical Reports Server (NTRS)

Mcmanus, Hugh L.

1993-01-01

A new release rate equation to model the phase change of water to steam in composite materials was derived from the theory of molecular diffusion and equilibrium moisture concentration. The new model is dependent on internal pressure, the microstructure of the voids and channels in the composite materials, and the diffusion properties of the matrix material. Hence, it is more fundamental and accurate than the empirical Arrhenius rate equation currently in use. The model was mathematically formalized and integrated into the thermostructural analysis code CHAR. Parametric studies on variation of several parameters have been done. Comparisons to Arrhenius and straight-line models show that the new model produces physically realistic results under all conditions.

A novel mathematical model considering change of diffusion coefficient for predicting dissolution behavior of acetaminophen from wax matrix dosage form.

PubMed

Nitanai, Yuta; Agata, Yasuyoshi; Iwao, Yasunori; Itai, Shigeru

2012-05-30

From wax matrix dosage forms, drug and water-soluble polymer are released into the external solvent over time. As a consequence, the pore volume inside the wax matrix particles is increased and the diffusion coefficient of the drug is altered. In the present study, we attempted to derive a novel empirical mathematical model, namely, a time-dependent diffusivity (TDD) model, that assumes the change in the drug's diffusion coefficient can be used to predict the drug release from spherical wax matrix particles. Wax matrix particles were prepared by using acetaminophen (APAP), a model drug; glyceryl monostearate (GM), a wax base; and aminoalkyl methacrylate copolymer E (AMCE), a functional polymer that dissolves below pH 5.0 and swells over pH 5.0. A three-factor, three-level (3(3)) Box-Behnken design was used to evaluate the effects of several of the variables in the model formulation, and the release of APAP from wax matrix particles was evaluated by the paddle method at pH 4.0 and pH 6.5. When comparing the goodness of fit to the experimental data between the proposed TDD model and the conventional pure diffusion model, a better correspondence was observed for the TDD model in all cases. Multiple regression analysis revealed that an increase in AMCE loading enhanced the diffusion coefficient with time, and that this increase also had a significant effect on drug release behavior. Furthermore, from the results of the multiple regression analysis, a formulation with desired drug release behavior was found to satisfy the criteria of the bitter taste masking of APAP without lowering the bioavailability. That is to say, the amount of APAP released remains below 15% for 10 min at pH 6.5 and exceeds 90% within 30 min at pH 4.0. The predicted formulation was 15% APAP loading, 8.25% AMCE loading, and 400 μm mean particle diameter. When wax matrix dosage forms were prepared accordingly, the predicted drug release behavior agreed well with experimental values at each pH level. Therefore, the proposed model is feasible as a useful tool for predicting drug release behavior, as well as for designing the formulation of wax matrix dosage forms. Copyright © 2012 Elsevier B.V. All rights reserved.

Simulation of in-stream water quality on global scale under changing climate and anthropogenic conditions

NASA Astrophysics Data System (ADS)

Voss, Anja; Bärlund, Ilona; Punzet, Manuel; Williams, Richard; Teichert, Ellen; Malve, Olli; Voß, Frank

2010-05-01

Although catchment scale modelling of water and solute transport and transformations is a widely used technique to study pollution pathways and effects of natural changes, policies and mitigation measures there are only a few examples of global water quality modelling. This work will provide a description of the new continental-scale model of water quality WorldQual and the analysis of model simulations under changed climate and anthropogenic conditions with respect to changes in diffuse and point loading as well as surface water quality. BOD is used as an indicator of the level of organic pollution and its oxygen-depleting potential, and for the overall health of aquatic ecosystems. The first application of this new water quality model is to river systems of Europe. The model itself is being developed as part of the EU-funded SCENES Project which has the principal goal of developing new scenarios of the future of freshwater resources in Europe. The aim of the model is to determine chemical fluxes in different pathways combining analysis of water quantity with water quality. Simple equations, consistent with the availability of data on the continental scale, are used to simulate the response of in-stream BOD concentrations to diffuse and anthropogenic point loadings as well as flow dilution. Point sources are divided into manufacturing, domestic and urban loadings, whereas diffuse loadings come from scattered settlements, agricultural input (for instance livestock farming), and also from natural background sources. The model is tested against measured longitudinal gradients and time series data at specific river locations with different loading characteristics like the Thames that is driven by domestic loading and Ebro with relative high share of diffuse loading. With scenario studies the influence of climate and anthropogenic changes on European water resources shall be investigated with the following questions: 1. What percentage of river systems will have degraded water quality due to different driving forces? 2. How will climate change and changes in wastewater discharges affect water quality? For the analysis these scenario aspects are included: 1. climate with changed runoff (affecting diffuse pollution and loading from sealed areas), river discharge (causing dilution or concentration of point source pollution) and water temperature (affecting BOD degradation). 2. Point sources with changed population (affecting domestic pollution), connectivity to treatment plants (influencing domestic and manufacturing pollution as well as input from sealed areas and scattered settlements).

Fast diffusion kurtosis imaging (DKI) with Inherent COrrelation-based Normalization (ICON) enhances automatic segmentation of heterogeneous diffusion MRI lesion in acute stroke.

PubMed

Zhou, Iris Yuwen; Guo, Yingkun; Igarashi, Takahiro; Wang, Yu; Mandeville, Emiri; Chan, Suk-Tak; Wen, Lingyi; Vangel, Mark; Lo, Eng H; Ji, Xunming; Sun, Phillip Zhe

2016-12-01

Diffusion kurtosis imaging (DKI) has been shown to augment diffusion-weighted imaging (DWI) for the definition of irreversible ischemic injury. However, the complexity of cerebral structure/composition makes the kurtosis map heterogeneous, limiting the specificity of kurtosis hyperintensity to acute ischemia. We propose an Inherent COrrelation-based Normalization (ICON) analysis to suppress the intrinsic kurtosis heterogeneity for improved characterization of heterogeneous ischemic tissue injury. Fast DKI and relaxation measurements were performed on normal (n = 10) and stroke rats following middle cerebral artery occlusion (MCAO) (n = 20). We evaluated the correlations between mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) derived from the fast DKI sequence and relaxation rates R 1 and R 2 , and found a highly significant correlation between MK and R 1 (p < 0.001). We showed that ICON analysis suppressed the intrinsic kurtosis heterogeneity in normal cerebral tissue, enabling automated tissue segmentation in an animal stroke model. We found significantly different kurtosis and diffusivity lesion volumes: 147 ± 59 and 180 ± 66 mm 3 , respectively (p = 0.003, paired t-test). The ratio of kurtosis to diffusivity lesion volume was 84% ± 19% (p < 0.001, one-sample t-test). We found that relaxation-normalized MK (RNMK), but not MD, values were significantly different between kurtosis and diffusivity lesions (p < 0.001, analysis of variance). Our study showed that fast DKI with ICON analysis provides a promising means of demarcation of heterogeneous DWI stroke lesions. Copyright © 2016 John Wiley & Sons, Ltd.

Effects of b-value and number of gradient directions on diffusion MRI measures obtained with Q-ball imaging

NASA Astrophysics Data System (ADS)

Schilling, Kurt G.; Nath, Vishwesh; Blaber, Justin; Harrigan, Robert L.; Ding, Zhaohua; Anderson, Adam W.; Landman, Bennett A.

2017-02-01

High-angular-resolution diffusion-weighted imaging (HARDI) MRI acquisitions have become common for use with higher order models of diffusion. Despite successes in resolving complex fiber configurations and probing microstructural properties of brain tissue, there is no common consensus on the optimal b-value and number of diffusion directions to use for these HARDI methods. While this question has been addressed by analysis of the diffusion-weighted signal directly, it is unclear how this translates to the information and metrics derived from the HARDI models themselves. Using a high angular resolution data set acquired at a range of b-values, and repeated 11 times on a single subject, we study how the b-value and number of diffusion directions impacts the reproducibility and precision of metrics derived from Q-ball imaging, a popular HARDI technique. We find that Q-ball metrics associated with tissue microstructure and white matter fiber orientation are sensitive to both the number of diffusion directions and the spherical harmonic representation of the Q-ball, and often are biased when under sampled. These results can advise researchers on appropriate acquisition and processing schemes, particularly when it comes to optimizing the number of diffusion directions needed for metrics derived from Q-ball imaging.

Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases

NASA Astrophysics Data System (ADS)

Belik, Vitaly; Geisel, Theo; Brockmann, Dirk

2011-08-01

We investigate a model for spatial epidemics explicitly taking into account bidirectional movements between base and destination locations on individual mobility networks. We provide a systematic analysis of generic dynamical features of the model on regular and complex metapopulation network topologies and show that significant dynamical differences exist to ordinary reaction-diffusion and effective force of infection models. On a lattice we calculate an expression for the velocity of the propagating epidemic front and find that, in contrast to the diffusive systems, our model predicts a saturation of the velocity with an increasing traveling rate. Furthermore, we show that a fully stochastic system exhibits a novel threshold for the attack ratio of an outbreak that is absent in diffusion and force of infection models. These insights not only capture natural features of human mobility relevant for the geographical epidemic spread, they may serve as a starting point for modeling important dynamical processes in human and animal epidemiology, population ecology, biology, and evolution.

A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton

PubMed Central

Das, Raibatak; Cairo, Christopher W.; Coombs, Daniel

2009-01-01

The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation. PMID:19893741

A Framework for Linear and Non-Linear Registration of Diffusion-Weighted MRIs Using Angular Interpolation

PubMed Central

Duarte-Carvajalino, Julio M.; Sapiro, Guillermo; Harel, Noam; Lenglet, Christophe

2013-01-01

Registration of diffusion-weighted magnetic resonance images (DW-MRIs) is a key step for population studies, or construction of brain atlases, among other important tasks. Given the high dimensionality of the data, registration is usually performed by relying on scalar representative images, such as the fractional anisotropy (FA) and non-diffusion-weighted (b0) images, thereby ignoring much of the directional information conveyed by DW-MR datasets itself. Alternatively, model-based registration algorithms have been proposed to exploit information on the preferred fiber orientation(s) at each voxel. Models such as the diffusion tensor or orientation distribution function (ODF) have been used for this purpose. Tensor-based registration methods rely on a model that does not completely capture the information contained in DW-MRIs, and largely depends on the accurate estimation of tensors. ODF-based approaches are more recent and computationally challenging, but also better describe complex fiber configurations thereby potentially improving the accuracy of DW-MRI registration. A new algorithm based on angular interpolation of the diffusion-weighted volumes was proposed for affine registration, and does not rely on any specific local diffusion model. In this work, we first extensively compare the performance of registration algorithms based on (i) angular interpolation, (ii) non-diffusion-weighted scalar volume (b0), and (iii) diffusion tensor image (DTI). Moreover, we generalize the concept of angular interpolation (AI) to non-linear image registration, and implement it in the FMRIB Software Library (FSL). We demonstrate that AI registration of DW-MRIs is a powerful alternative to volume and tensor-based approaches. In particular, we show that AI improves the registration accuracy in many cases over existing state-of-the-art algorithms, while providing registered raw DW-MRI data, which can be used for any subsequent analysis. PMID:23596381

A Framework for Linear and Non-Linear Registration of Diffusion-Weighted MRIs Using Angular Interpolation.

PubMed

Duarte-Carvajalino, Julio M; Sapiro, Guillermo; Harel, Noam; Lenglet, Christophe

2013-01-01

Registration of diffusion-weighted magnetic resonance images (DW-MRIs) is a key step for population studies, or construction of brain atlases, among other important tasks. Given the high dimensionality of the data, registration is usually performed by relying on scalar representative images, such as the fractional anisotropy (FA) and non-diffusion-weighted (b0) images, thereby ignoring much of the directional information conveyed by DW-MR datasets itself. Alternatively, model-based registration algorithms have been proposed to exploit information on the preferred fiber orientation(s) at each voxel. Models such as the diffusion tensor or orientation distribution function (ODF) have been used for this purpose. Tensor-based registration methods rely on a model that does not completely capture the information contained in DW-MRIs, and largely depends on the accurate estimation of tensors. ODF-based approaches are more recent and computationally challenging, but also better describe complex fiber configurations thereby potentially improving the accuracy of DW-MRI registration. A new algorithm based on angular interpolation of the diffusion-weighted volumes was proposed for affine registration, and does not rely on any specific local diffusion model. In this work, we first extensively compare the performance of registration algorithms based on (i) angular interpolation, (ii) non-diffusion-weighted scalar volume (b0), and (iii) diffusion tensor image (DTI). Moreover, we generalize the concept of angular interpolation (AI) to non-linear image registration, and implement it in the FMRIB Software Library (FSL). We demonstrate that AI registration of DW-MRIs is a powerful alternative to volume and tensor-based approaches. In particular, we show that AI improves the registration accuracy in many cases over existing state-of-the-art algorithms, while providing registered raw DW-MRI data, which can be used for any subsequent analysis.

Reconstructing thermal properties of firn at Summit, Greenland from a temperature profile

NASA Astrophysics Data System (ADS)

Giese, A. L.; Hawley, R. L.

2013-12-01

Thermodynamic properties of firn are important factors when considering energy balance and temperature-dependent physical processes in the near-surface of glaciers. Of particular interest is thermal diffusivity, which can take a range of values and which governs both the temperature gradient and its evolution through time. Given that temperature is a well-established driver of firn densification, a better understanding of heat transfer will permit greater accuracy in the compaction models essential for interpreting inter-annual and seasonal ice surface elevation changes detected by airborne and satellite altimetry. Due to its dependence on microstructure, diffusivity can vary significantly by location. Rather than directly measuring diffusivity or one of its proxies (e.g. density, hardness, shear strength), this study inverts the heat equation to reconstruct diffusivity values. This is a less logistically-intensive approach which circumvents many of the challenges associated with imperfect proxies and snow metamorphism during measurement. Hourly records (May 2004 - July 2008) from 8 thermistors placed in the top 10 m at Summit, Greenland provide temperature values for Summit's firn, which is broadly representative of firn across the ice sheet's dry snow zone. In this study, we use both physical analysis and a finite-difference numerical model to determine a diffusivity magnitude and gradient; we find that diffusivity of Summit firn falls in the lower end of the range expected from local density and temperature conditions alone (i.e. 15 - 36 m^2/a for firn at -30C). Further, we assess the utility of our modeling approach, explore the validity of assuming bulk conductive heat transfer when modeling temperature changes in non-homogeneous firn, and investigate the implications of a low-end diffusivity value for surface compaction modeling in Greenland.

Phospholipid Diffusion Coefficients of Cushioned Model Membranes determined via Z-Scan Fluorescence Correlation Spectroscopy

PubMed Central

Sterling, Sarah M.; Allgeyer, Edward S.; Fick, Jörg; Prudovsky, Igor; Mason, Michael D.; Neivandt, David J.

2013-01-01

Model cellular membranes enable the study of biological processes in a controlled environment and reduce the traditional challenges associated with live or fixed cell studies. However, model membrane systems based on the air/water or oil/solution interface do not allow for incorporation of transmembrane proteins, or for the study of protein transport mechanisms. Conversely, a phospholipid bilayer deposited via the Langmuir-Blodgett/Langmuir Schaefer method on a hydrogel layer is potentially an effective mimic of the cross-section of a biological membrane, and facilitates both protein incorporation and transport studies. Prior to application, however, such membranes must be fully characterized, particularly with respect to the phospholipid bilayer phase transition temperature. Here we present a detailed characterization of the phase transition temperature of the inner and outer leaflets of a chitosan supported model membrane system. Specifically, the lateral diffusion coefficient of each individual leaflet has been determined as a function of temperature. Measurements were performed utilizing z-scan fluorescence correlation spectroscopy (FCS), a technique that yields calibration-free diffusion information. Analysis via the method of Wawrezinieck and coworkers, revealed that phospholipid diffusion changes from raft-like to free diffusion as the temperature is increased; an insight into the dynamic behavior of hydrogel supported membranes not previously reported. PMID:23705855

The Dynamics of Son Preference, Technology Diffusion, and Fertility Decline Underlying Distorted Sex Ratios at Birth: A Simulation Approach.

PubMed

Kashyap, Ridhi; Villavicencio, Francisco

2016-10-01

We present a micro-founded simulation model that formalizes the "ready, willing, and able" framework, originally used to explain historical fertility decline, to the practice of prenatal sex selection. The model generates sex ratio at birth (SRB) distortions from the bottom up and attempts to quantify plausible levels, trends, and interactions of son preference, technology diffusion, and fertility decline that underpin SRB trajectories at the macro level. Calibrating our model for South Korea, we show how even as the proportion with a preference for sons was declining, SRB distortions emerged due to rapid diffusion of prenatal sex determination technology combined with small but growing propensities to abort at low birth parities. Simulations reveal that relatively low levels of son preference (about 20 % to 30 % wanting one son) can result in skewed SRB levels if technology diffuses early and steadily, and if fertility falls rapidly to encourage sex-selective abortion at low parities. Model sensitivity analysis highlights how the shape of sex ratio trajectories is particularly sensitive to the timing and speed of prenatal sex-determination technology diffusion. The maximum SRB levels reached in a population are influenced by how the readiness to abort rises as a function of the fertility decline.

Kinetics of the reduction of bushveld complex chromite ore at 1416 °C

NASA Astrophysics Data System (ADS)

Soykan, O.; Eric, R. H.; King, R. P.

1991-12-01

The kinetics of the reduction of chromite ore from the LG-6 layer of the Bushveld Complex of the Transvaal in South Africa were studied at 1416 °C by the thermogravimetric analysis (TGA) technique. Spectroscopic graphite powder was employed as the reductant. The aim of this article is to present a kinetic model that satisfactorily describes the solid-state carbothermic reduction of chromite. A generalized rate model based on an ionic diffusion mechanism was developed. The model included the contribution of the interfacial area between partially reduced and unreduced zones in chromite particles and diffusion. The kinetic model described the process for degrees of reduction from 10 to 75 pet satisfactorily. It was observed that at a given particle size, the rate of reduction was controlled mainly by interfacial area up to about 40 pet reduction, after which the rate was dominated by diffusion. On the other hand, for a given degree of reduction, the contribution of the interfacial area to the rate increased, while that of diffusion decreased, with a decrease in the particle size. The value of the diffusion coefficient for the Fe2+ species at 1416 °C was calculated to be 2.63 x 10-2 cm2/s.

Dynamic diffusion tensor imaging of spinal cord contusion: A canine model.

PubMed

Liu, Changbin; Yang, Degang; Li, Jianjun; Li, Dapeng; Yang, Mingliang; Sun, Wei; Meng, Qianru; Zhang, Wenhao; Cai, Chang; Du, Liangjie; Li, Jun; Gao, Feng; Gu, Rui; Feng, Yutong; Dong, Xuechao; Miao, Qi; Yang, Xinghua; Zuo, Zhentao

2018-06-01

This study aimed to explore the dynamic diffusion tensor imaging (DTI) of changes in spinal cord contusion using a canine model of injury involving rostral and caudal levels. In this study, a spinal cord contusion model was established in female dogs using a custom-made weight-drop lesion device. DTI was performed on dogs with injured spinal cords (n=7) using a Siemens 3.0T MRI scanner at pre-contusion and at 3 h, 24 h, 6 weeks and 12 weeks post-injury. The tissue sections were stained for immunohistochemical analysis. Canine models of spinal cord contusion were created successfully using the weight-drop lesion device. The fractional anisotropy (FA) value of lesion epicenter decreased, while the apparent diffusion coefficient (ADC), mean diffusivity (MD), and radial diffusivity (RD) values increased, and the extent of the curve was apparent gradually. The site and time affected the DTI parameters significantly in the whole spinal cord, ADC (site, P < 0.001 and time, P = 0.077, respectively); FA (site, P < 0.001 and time, P = 0.002, respectively). Immunohistological analysis of GFAP and NF revealed the pathologic changes of reactive astrocytes and axons, as well as the cavity and glial scars occurring during chronic SCI. DTI is a sensitive and noninvasive imaging tool useful to assess edema, hemorrhage, cavity formation, structural damage and reconstruction of axon, and myelin in dogs. The DTI parameters after contusion vary. However, the curves of ADC, MD, and RD were nearly similar and the FA curve was distinct. All the DTI parameters were affected by distance and time. © 2018 Wiley Periodicals, Inc.

A Growth Model for Academic Program Life Cycle (APLC): A Theoretical and Empirical Analysis

ERIC Educational Resources Information Center

Acquah, Edward H. K.

2010-01-01

Academic program life cycle concept states each program's life flows through several stages: introduction, growth, maturity, and decline. A mixed-influence diffusion growth model is fitted to enrolment data on academic programs to analyze the factors determining progress of academic programs through their life cycles. The regression analysis yield…

Analysis and correction of gradient nonlinearity bias in apparent diffusion coefficient measurements.

PubMed

Malyarenko, Dariya I; Ross, Brian D; Chenevert, Thomas L

2014-03-01

Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10-20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Spatial dependence of nonlinearity correction terms accounts for the bulk (75-95%) of ADC bias for FA = 0.3-0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. Copyright © 2013 Wiley Periodicals, Inc.

Exponential stability of impulsive stochastic genetic regulatory networks with time-varying delays and reaction-diffusion

DOE PAGES

Cao, Boqiang; Zhang, Qimin; Ye, Ming

2016-11-29

We present a mean-square exponential stability analysis for impulsive stochastic genetic regulatory networks (GRNs) with time-varying delays and reaction-diffusion driven by fractional Brownian motion (fBm). By constructing a Lyapunov functional and using linear matrix inequality for stochastic analysis we derive sufficient conditions to guarantee the exponential stability of the stochastic model of impulsive GRNs in the mean-square sense. Meanwhile, the corresponding results are obtained for the GRNs with constant time delays and standard Brownian motion. Finally, an example is presented to illustrate our results of the mean-square exponential stability analysis.

Stochastic Analysis of Reaction–Diffusion Processes

PubMed Central

Hu, Jifeng; Kang, Hye-Won

2013-01-01

Reaction and diffusion processes are used to model chemical and biological processes over a wide range of spatial and temporal scales. Several routes to the diffusion process at various levels of description in time and space are discussed and the master equation for spatially discretized systems involving reaction and diffusion is developed. We discuss an estimator for the appropriate compartment size for simulating reaction–diffusion systems and introduce a measure of fluctuations in a discretized system. We then describe a new computational algorithm for implementing a modified Gillespie method for compartmental systems in which reactions are aggregated into equivalence classes and computational cells are searched via an optimized tree structure. Finally, we discuss several examples that illustrate the issues that have to be addressed in general systems. PMID:23719732

Defining an Analytic Framework to Evaluate Quantitative MRI Markers of Traumatic Axonal Injury: Preliminary Results in a Mouse Closed Head Injury Model

PubMed Central

Sadeghi, N.; Namjoshi, D.; Irfanoglu, M. O.; Wellington, C.; Diaz-Arrastia, R.

2017-01-01

Diffuse axonal injury (DAI) is a hallmark of traumatic brain injury (TBI) pathology. Recently, the Closed Head Injury Model of Engineered Rotational Acceleration (CHIMERA) was developed to generate an experimental model of DAI in a mouse. The characterization of DAI using diffusion tensor magnetic resonance imaging (MRI; diffusion tensor imaging, DTI) may provide a useful set of outcome measures for preclinical and clinical studies. The objective of this study was to identify the complex neurobiological underpinnings of DTI features following DAI using a comprehensive and quantitative evaluation of DTI and histopathology in the CHIMERA mouse model. A consistent neuroanatomical pattern of pathology in specific white matter tracts was identified across ex vivo DTI maps and photomicrographs of histology. These observations were confirmed by voxelwise and regional analysis of DTI maps, demonstrating reduced fractional anisotropy (FA) in distinct regions such as the optic tract. Similar regions were identified by quantitative histology and exhibited axonal damage as well as robust gliosis. Additional analysis using a machine-learning algorithm was performed to identify regions and metrics important for injury classification in a manner free from potential user bias. This analysis found that diffusion metrics were able to identify injured brains almost with the same degree of accuracy as the histology metrics. Good agreement between regions detected as abnormal by histology and MRI was also found. The findings of this work elucidate the complexity of cellular changes that give rise to imaging abnormalities and provide a comprehensive and quantitative evaluation of the relative importance of DTI and histological measures to detect brain injury. PMID:28966972

Multiple Diffusion Mechanisms Due to Nanostructuring in Crowded Environments

PubMed Central

Sanabria, Hugo; Kubota, Yoshihisa; Waxham, M. Neal

2007-01-01

One of the key questions regarding intracellular diffusion is how the environment affects molecular mobility. Mostly, intracellular diffusion has been described as hindered, and the physical reasons for this behavior are: immobile barriers, molecular crowding, and binding interactions with immobile or mobile molecules. Using results from multi-photon fluorescence correlation spectroscopy, we describe how immobile barriers and crowding agents affect translational mobility. To study the hindrance produced by immobile barriers, we used sol-gels (silica nanostructures) that consist of a continuous solid phase and aqueous phase in which fluorescently tagged molecules diffuse. In the case of molecular crowding, translational mobility was assessed in increasing concentrations of 500 kDa dextran solutions. Diffusion of fluorescent tracers in both sol-gels and dextran solutions shows clear evidence of anomalous subdiffusion. In addition, data from the autocorrelation function were analyzed using the maximum entropy method as adapted to fluorescence correlation spectroscopy data and compared with the standard model that incorporates anomalous diffusion. The maximum entropy method revealed evidence of different diffusion mechanisms that had not been revealed using the anomalous diffusion model. These mechanisms likely correspond to nanostructuring in crowded environments and to the relative dimensions of the crowding agent with respect to the tracer molecule. Analysis with the maximum entropy method also revealed information about the degree of heterogeneity in the environment as reported by the behavior of diffusive molecules. PMID:17040979

Modeling and Analysis of Actinide Diffusion Behavior in Irradiated Metal Fuel

NASA Astrophysics Data System (ADS)

Edelmann, Paul G.

There have been numerous attempts to model fast reactor fuel behavior in the last 40 years. The US currently does not have a fully reliable tool to simulate the behavior of metal fuels in fast reactors. The experimental database necessary to validate the codes is also very limited. The DOE-sponsored Advanced Fuels Campaign (AFC) has performed various experiments that are ready for analysis. Current metal fuel performance codes are either not available to the AFC or have limitations and deficiencies in predicting AFC fuel performance. A modified version of a new fuel performance code, FEAST-Metal , was employed in this investigation with useful results. This work explores the modeling and analysis of AFC metallic fuels using FEAST-Metal, particularly in the area of constituent actinide diffusion behavior. The FEAST-Metal code calculations for this work were conducted at Los Alamos National Laboratory (LANL) in support of on-going activities related to sensitivity analysis of fuel performance codes. A sensitivity analysis of FEAST-Metal was completed to identify important macroscopic parameters of interest to modeling and simulation of metallic fuel performance. A modification was made to the FEAST-Metal constituent redistribution model to enable accommodation of newer AFC metal fuel compositions with verified results. Applicability of this modified model for sodium fast reactor metal fuel design is demonstrated.

CFD simulation of fluid dynamic and biokinetic processes within activated sludge reactors under intermittent aeration regime.

PubMed

Sánchez, F; Rey, H; Viedma, A; Nicolás-Pérez, F; Kaiser, A S; Martínez, M

2018-08-01

Due to the aeration system, biological reactors are the most energy-consuming facilities of convectional WWTPs. Many biological reactors work under intermittent aeration regime; the optimization of the aeration process (air diffuser layout, air flow rate per diffuser, aeration length …) is necessary to ensure an efficient performance; satisfying the effluent requirements with the minimum energy consumption. This work develops a CFD modelling of an activated sludge reactor (ASR) which works under intermittent aeration regime. The model considers the fluid dynamic and biological processes within the ASR. The biological simulation, which is transient, takes into account the intermittent aeration regime. The CFD modelling is employed for the selection of the aeration system of an ASR. Two different aeration configurations are simulated. The model evaluates the aeration power consumption necessary to satisfy the effluent requirements. An improvement of 2.8% in terms of energy consumption is achieved by modifying the air diffuser layout. An analysis of the influence of the air flow rate per diffuser on the ASR performance is carried out. The results show a reduction of 14.5% in the energy consumption of the aeration system when the air flow rate per diffuser is reduced. The model provides an insight into the aeration inefficiencies produced within ASRs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Change-point analysis data of neonatal diffusion tensor MRI in preterm and term-born infants.

PubMed

Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi

2017-06-01

The data presented in this article are related to the research article entitled "Mapping the Critical Gestational Age at Birth that Alters Brain Development in Preterm-born Infants using Multi-Modal MRI" (Wu et al., 2017) [1]. Brain immaturity at birth poses critical neurological risks in the preterm-born infants. We used a novel change-point model to analyze the critical gestational age at birth (GAB) that could affect postnatal development, based on diffusion tensor MRI (DTI) acquired from 43 preterm and 43 term-born infants in 126 brain regions. In the corresponding research article, we presented change-point analysis of fractional anisotropy (FA) and mean diffusivities (MD) measurements in these infants. In this article, we offered the relative changes of axonal and radial diffusivities (AD and RD) in relation to the change of FA and FA-based change-points, and we also provided the AD- and RD-based change-point results.

Scaling Law for Cross-stream Diffusion in Microchannels under Combined Electroosmotic and Pressure Driven Flow.

PubMed

Song, Hongjun; Wang, Yi; Pant, Kapil

2013-01-01

This paper presents an analytical study of the cross-stream diffusion of an analyte in a rectangular microchannel under combined electroosmotic flow (EOF) and pressure driven flow to investigate the heterogeneous transport behavior and spatially-dependent diffusion scaling law. An analytical model capable of accurately describing 3D steady-state convection-diffusion in microchannels with arbitrary aspect ratios is developed based on the assumption of the thin Electric Double Layer (EDL). The model is verified against high-fidelity numerical simulation in terms of flow velocity and analyte concentration profiles with excellent agreement (<0.5% relative error). An extensive parametric analysis is then undertaken to interrogate the effect of the combined flow velocity field on the transport behavior in both the positive pressure gradient (PPG) and negative pressure gradient (NPG) cases. For the first time, the evolution from the spindle-shaped concentration profile in the PPG case, via the stripe-shaped profile (pure EOF), and finally to the butterfly-shaped profile in the PPG case is obtained using the analytical model along with a quantitative depiction of the spatially-dependent diffusion layer thickness and scaling law across a wide range of the parameter space.

Scaling Law for Cross-stream Diffusion in Microchannels under Combined Electroosmotic and Pressure Driven Flow

PubMed Central

Song, Hongjun; Wang, Yi; Pant, Kapil

2012-01-01

This paper presents an analytical study of the cross-stream diffusion of an analyte in a rectangular microchannel under combined electroosmotic flow (EOF) and pressure driven flow to investigate the heterogeneous transport behavior and spatially-dependent diffusion scaling law. An analytical model capable of accurately describing 3D steady-state convection-diffusion in microchannels with arbitrary aspect ratios is developed based on the assumption of the thin Electric Double Layer (EDL). The model is verified against high-fidelity numerical simulation in terms of flow velocity and analyte concentration profiles with excellent agreement (<0.5% relative error). An extensive parametric analysis is then undertaken to interrogate the effect of the combined flow velocity field on the transport behavior in both the positive pressure gradient (PPG) and negative pressure gradient (NPG) cases. For the first time, the evolution from the spindle-shaped concentration profile in the PPG case, via the stripe-shaped profile (pure EOF), and finally to the butterfly-shaped profile in the PPG case is obtained using the analytical model along with a quantitative depiction of the spatially-dependent diffusion layer thickness and scaling law across a wide range of the parameter space. PMID:23554584

Subdiffusion in Membrane Permeation of Small Molecules.

PubMed

Chipot, Christophe; Comer, Jeffrey

2016-11-02

Within the solubility-diffusion model of passive membrane permeation of small molecules, translocation of the permeant across the biological membrane is traditionally assumed to obey the Smoluchowski diffusion equation, which is germane for classical diffusion on an inhomogeneous free-energy and diffusivity landscape. This equation, however, cannot accommodate subdiffusive regimes, which have long been recognized in lipid bilayer dynamics, notably in the lateral diffusion of individual lipids. Through extensive biased and unbiased molecular dynamics simulations, we show that one-dimensional translocation of methanol across a pure lipid membrane remains subdiffusive on timescales approaching typical permeation times. Analysis of permeant motion within the lipid bilayer reveals that, in the absence of a net force, the mean squared displacement depends on time as t 0.7 , in stark contrast with the conventional model, which assumes a strictly linear dependence. We further show that an alternate model using a fractional-derivative generalization of the Smoluchowski equation provides a rigorous framework for describing the motion of the permeant molecule on the pico- to nanosecond timescale. The observed subdiffusive behavior appears to emerge from a crossover between small-scale rattling of the permeant around its present position in the membrane and larger-scale displacements precipitated by the formation of transient voids.

Study of the measurement for the diffusion coefficient by digital holographic interferometry.

PubMed

Zhang, Shi; He, Maogang; Zhang, Ying; Peng, Sanguo; He, Xinxin

2015-11-01

In the measurement of the diffusion coefficient by digital holographic interferometry, the conformity between the experiment and the ideal physical model is lacking analysis. Two data processing methods are put forward to overcome this problem. By these methods, it is found that there is obvious asymmetry in the experiment and the asymmetry is becoming smaller with time. Besides, the initial time for diffusion cannot be treated as a constant throughout the whole experiment. This means that there is a difference between the experiment and the physical model. With these methods, the diffusion coefficient of KCl in water at 0.33  mol/L and 25°C is measured. When the asymmetry is ignored, the result is 1.839×10(-9)  m2/s, which is in good agreement with the data in the literature. Because the asymmetry is becoming smaller with time, the experimental data in the latter time period conforms to the ideal physical model. With this idea, a more accurate diffusion coefficient is 2.003×10(-9)  m2/s, which is about 10% larger than the data in the literature.

Computational Study of Separating Flow in a Planar Subsonic Diffuser

NASA Technical Reports Server (NTRS)

DalBello, Teryn; Dippold, Vance, III; Georgiadis, Nicholas J.

2005-01-01

A computational study of the separated flow through a 2-D asymmetric subsonic diffuser has been performed. The Wind Computational Fluid Dynamics code is used to predict the separation and reattachment behavior for an incompressible diffuser flow. The diffuser inlet flow is a two-dimensional, turbulent, and fully-developed channel flow with a Reynolds number of 20,000 based on the centerline velocity and the channel height. Wind solutions computed with the Menter SST, Chien k-epsilon, Spalart-Allmaras and Explicit Algebraic Reynolds Stress turbulence models are compared with experimentally measured velocity profiles and skin friction along the upper and lower walls. In addition to the turbulence model study, the effects of grid resolution and use of wall functions were investigated. The grid studies varied the number of grid points across the diffuser and varied the initial wall spacing from y(sup +) = 0.2 to 60. The wall function study assessed the applicability of wall functions for analysis of separated flow. The SST and Explicit Algebraic Stress models provide the best agreement with experimental data, and it is recommended wall functions should only be used with a high level of caution.

Dependence of radiation belt simulations to assumed radial diffusion rates tested for two empirical models of radial transport

NASA Astrophysics Data System (ADS)

Drozdov, Alexander; Shprits, Yuri; Aseev, Nikita; Kellerman, Adam; Reeves, Geoffrey

2017-04-01

Radial diffusion is one of the dominant physical mechanisms that drives acceleration and loss of the radiation belt electrons, which makes it very important for nowcasting and forecasting space weather models. We investigate the sensitivity of the two parameterizations of the radial diffusion of Brautigam and Albert [2000] and Ozeke et al. [2014] on long-term radiation belt modeling using the Versatile Electron Radiation Belt (VERB). Following Brautigam and Albert [2000] and Ozeke et al. [2014], we first perform 1-D radial diffusion simulations. Comparison of the simulation results with observations shows that the difference between simulations with either radial diffusion parameterization is small. To take into account effects of local acceleration and loss, we perform 3-D simulations, including pitch-angle, energy and mixed diffusion. We found that the results of 3-D simulations are even less sensitive to the choice of parameterization of radial diffusion rates than the results of 1-D simulations at various energies (from 0.59 to 1.80 MeV). This result demonstrates that the inclusion of local acceleration and pitch-angle diffusion can provide a negative feedback effect, such that the result is largely indistinguishable simulations conducted with different radial diffusion parameterizations. We also perform a number of sensitivity tests by multiplying radial diffusion rates by constant factors and show that such an approach leads to unrealistic predictions of radiation belt dynamics. References Brautigam, D. H., and J. M. Albert (2000), Radial diffusion analysis of outer radiation belt electrons during the October 9, 1990, magnetic storm, J. Geophys. Res., 105(A1), 291-309, doi:10.1029/1999ja900344. Ozeke, L. G., I. R. Mann, K. R. Murphy, I. Jonathan Rae, and D. K. Milling (2014), Analytic expressions for ULF wave radiation belt radial diffusion coefficients, J. Geophys. Res. [Space Phys.], 119(3), 1587-1605, doi:10.1002/2013JA019204.

Probabilistic modeling of percutaneous absorption for risk-based exposure assessments and transdermal drug delivery.

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

Ho, Clifford Kuofei

Chemical transport through human skin can play a significant role in human exposure to toxic chemicals in the workplace, as well as to chemical/biological warfare agents in the battlefield. The viability of transdermal drug delivery also relies on chemical transport processes through the skin. Models of percutaneous absorption are needed for risk-based exposure assessments and drug-delivery analyses, but previous mechanistic models have been largely deterministic. A probabilistic, transient, three-phase model of percutaneous absorption of chemicals has been developed to assess the relative importance of uncertain parameters and processes that may be important to risk-based assessments. Penetration routes through the skinmore » that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times. This probabilistic analysis of percutaneous absorption (PAPA) method has been developed to improve risk-based exposure assessments and transdermal drug-delivery analyses, where parameters and processes can be highly uncertain.« less

Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics.

PubMed

Chen, Minghan; Li, Fei; Wang, Shuo; Cao, Young

2017-03-14

Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological modeling and simulation. One widely used framework for stochastic simulation of reaction-diffusion systems is reaction diffusion master equation (RDME). Previous studies have discovered that for the RDME, when discretization size approaches zero, reaction time for bimolecular reactions in high dimensional domains tends to infinity. In this paper, we demonstrate that in the 1D domain, highly nonlinear reaction dynamics given by Hill function may also have dramatic change when discretization size is smaller than a critical value. Moreover, we discuss methods to avoid this problem: smoothing over space, fixed length smoothing over space and a hybrid method. Our analysis reveals that the switch-like Hill dynamics reduces to a linear function of discretization size when the discretization size is small enough. The three proposed methods could correctly (under certain precision) simulate Hill function dynamics in the microscopic RDME system.

A Semi-Analytical Model for Dispersion Modelling Studies in the Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Gupta, A.; Sharan, M.

2017-12-01

The severe impact of harmful air pollutants has always been a cause of concern for a wide variety of air quality analysis. The analytical models based on the solution of the advection-diffusion equation have been the first and remain the convenient way for modeling air pollutant dispersion as it is easy to handle the dispersion parameters and related physics in it. A mathematical model describing the crosswind integrated concentration is presented. The analytical solution to the resulting advection-diffusion equation is limited to a constant and simple profiles of eddy diffusivity and wind speed. In practice, the wind speed depends on the vertical height above the ground and eddy diffusivity profiles on the downwind distance from the source as well as the vertical height. In the present model, a method of eigen-function expansion is used to solve the resulting partial differential equation with the appropriate boundary conditions. This leads to a system of first order ordinary differential equations with a coefficient matrix depending on the downwind distance. The solution of this system, in general, can be expressed in terms of Peano-baker series which is not easy to compute, particularly when the coefficient matrix becomes non-commutative (Martin et al., 1967). An approach based on Taylor's series expansion is introduced to find the numerical solution of first order system. The method is applied to various profiles of wind speed and eddy diffusivities. The solution computed from the proposed methodology is found to be efficient and accurate in comparison to those available in the literature. The performance of the model is evaluated with the diffusion datasets from Copenhagen (Gryning et al., 1987) and Hanford (Doran et al., 1985). In addition, the proposed method is used to deduce three dimensional concentrations by considering the Gaussian distribution in crosswind direction, which is also evaluated with diffusion data corresponding to a continuous point source.

Random walks exhibiting anomalous diffusion: elephants, urns and the limits of normality

NASA Astrophysics Data System (ADS)

Kearney, Michael J.; Martin, Richard J.

2018-01-01

A random walk model is presented which exhibits a transition from standard to anomalous diffusion as a parameter is varied. The model is a variant on the elephant random walk and differs in respect of the treatment of the initial state, which in the present work consists of a given number N of fixed steps. This also links the elephant random walk to other types of history dependent random walk. As well as being amenable to direct analysis, the model is shown to be asymptotically equivalent to a non-linear urn process. This provides fresh insights into the limiting form of the distribution of the walker’s position at large times. Although the distribution is intrinsically non-Gaussian in the anomalous diffusion regime, it gradually reverts to normal form when N is large under quite general conditions.

Delay-induced Turing-like waves for one-species reaction-diffusion model on a network

NASA Astrophysics Data System (ADS)

Petit, Julien; Carletti, Timoteo; Asllani, Malbor; Fanelli, Duccio

2015-09-01

A one-species time-delay reaction-diffusion system defined on a complex network is studied. Traveling waves are predicted to occur following a symmetry-breaking instability of a homogeneous stationary stable solution, subject to an external nonhomogeneous perturbation. These are generalized Turing-like waves that materialize in a single-species populations dynamics model, as the unexpected byproduct of the imposed delay in the diffusion part. Sufficient conditions for the onset of the instability are mathematically provided by performing a linear stability analysis adapted to time-delayed differential equations. The method here developed exploits the properties of the Lambert W-function. The prediction of the theory are confirmed by direct numerical simulation carried out for a modified version of the classical Fisher model, defined on a Watts-Strogatz network and with the inclusion of the delay.

Calculation of Propulsive Nozzle Flowfields in Multidiffusing Chemically Reacting Environments. Ph.D. Thesis - Purdue Univ.

NASA Technical Reports Server (NTRS)

Kacynski, Kenneth John

1994-01-01

An advanced engineering model has been developed to aid in the analysis and design of hydrogen/oxygen chemical rocket engines. The complete multispecies, chemically reacting and multidiffusing Navier-Stokes equations are modelled, including the Soret thermal diffusion and the Dufour energy transfer terms. In addition to the spectrum of multispecies aspects developed, the model developed in this study is also conservative in axisymmetric flow for both inviscid and viscous flow environments and the boundary conditions employ a viscous, chemically reacting, reference plane characteristics method. Demonstration cases are presented for a 1030:1 area ratio nozzle, a 25 lbf film cooled nozzle, and a transpiration cooled plug and spool rocket engine. The results indicate that the thrust coefficient predictions of the 1030:1 and the 25 lbf film cooled nozzle are within 0.2 to 0.5 percent, respectively, of experimental measurements when all of the chemical reaction and diffusion terms are considered. Further, the model's predictions agree very well with the heat transfer measurements made in all of the nozzle test cases. The Soret thermal diffusion term is demonstrated to have a significant effect on the predicted mass fraction of hydrogen along the wall of the nozzle in both the laminar flow 1030:1 nozzle and the turbulent flow plug and spool nozzle analysis cases performed. Further, the Soret term was shown to represent an important fraction of the diffusion fluxes occurring in a transpiration cooled rocket engine.

Knowledge Diffusion in a Grade 4-5 Classroom during a Unit on Civil Engineering: An Analysis of a Classroom Community in Terms of Its Changing Resources and Practices.

ERIC Educational Resources Information Center

Roth, Wolff-Michael

1996-01-01

Employed the actor network theory to examine the transformation of a grade-four classroom community as new resources and practices became available. Found that the diffusion and enculturation metaphors are insufficient to model important aspects of learning in a student-centered classroom. (MOK)

Phylogenetic Factor Analysis.

PubMed

Tolkoff, Max R; Alfaro, Michael E; Baele, Guy; Lemey, Philippe; Suchard, Marc A

2018-05-01

Phylogenetic comparative methods explore the relationships between quantitative traits adjusting for shared evolutionary history. This adjustment often occurs through a Brownian diffusion process along the branches of the phylogeny that generates model residuals or the traits themselves. For high-dimensional traits, inferring all pair-wise correlations within the multivariate diffusion is limiting. To circumvent this problem, we propose phylogenetic factor analysis (PFA) that assumes a small unknown number of independent evolutionary factors arise along the phylogeny and these factors generate clusters of dependent traits. Set in a Bayesian framework, PFA provides measures of uncertainty on the factor number and groupings, combines both continuous and discrete traits, integrates over missing measurements and incorporates phylogenetic uncertainty with the help of molecular sequences. We develop Gibbs samplers based on dynamic programming to estimate the PFA posterior distribution, over 3-fold faster than for multivariate diffusion and a further order-of-magnitude more efficiently in the presence of latent traits. We further propose a novel marginal likelihood estimator for previously impractical models with discrete data and find that PFA also provides a better fit than multivariate diffusion in evolutionary questions in columbine flower development, placental reproduction transitions and triggerfish fin morphometry.

Orthotropic and time-dependent moisture diffusion measurements in polymer matrix composites using nuclear reaction analysis

NASA Astrophysics Data System (ADS)

Pilli, Siva P.

Moisture plays a significant role in influencing the mechanical behavior and long-term durability of composites. The objective of this dissertation was to understand the basic concepts of moisture transport in polymeric composites. Humidity test chambers were used in combination with D2O water to characterize the diffusion of D2O using Nuclear Reaction Analysis (NRA). Moisture content was measured as a function of through-thickness depth using NRA. In this study a novel method to measure the orthotropic diffusivities of polymer matrix composites has been demonstrated. This was achieved by soaking the samples in D2O vapor and subsequently characterizing the diffusion of D2O at all edges of the coupon using NRA. The diffusivity through the surface was 3½ times higher than the diffusivity through the edges. A direct comparison of experimental data with models using orthotropic diffusivities was in relatively good agreement. Surface moisture content was also measured as a function of time using NRA. It was shown that the surface concentration reaches an intermediate value of 79% Mm very rapidly and is followed by a slow linear increase to the saturation level (Mm). This research also interrogates the effect of pressure on diffusion. Test chambers were built to maintain a constant relative humidity of 80% at 60°C at three different pressures (0.101 MPa, 0.517 MPa and 1.034 MPa) including a liquid water immersion test chamber at 60°C. In this study it was observed that the time to saturation increased with increasing chamber pressure. This was primarily due to the increased maximum moisture content at higher pressures. Liquid immersion of the test samples provided the upper bound for maximum moisture content and a lower bound for time to saturation. The effects of material systems and layups on humidity measurements were also studied using two different polymer composite material systems, Cycom and Toray. Diffusivity results were identical for different layups whereas differences were observed for different material systems. Finally three-dimensional numeric models were developed, using ANSYS, to compare with the measured moisture content. Models incorporating the time-dependent and 3-D diffusion have shown an improved correlation with experiments.

Improved model for the design and analysis of centrifugal compressor volutes

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

Van den Braembussche, R.A.; Ayder, E.; Hagelstein, D.

1999-07-01

This paper describes a new model for the analysis of the flow in volutes of centrifugal compressors. It explicitly takes into account the vortical structure of the flow that has been observed during detailed three-dimensional flow measurements. It makes use of an impeller and diffuser response model to predict the nonuniformity of the volute inlet flow due, to the circumferential variation of the pressure at the volute inlet, and is therefore applicable also at off-design operation of the volute. Predicted total pressure loss and static pressure rise coefficients at design and off-design operation have been compared with experimental data formore » different volute geometries but only one test case is presented here. Good agreement in terms of losses and pressure rise is observed at most operating points and confirms the validity of the impeller and diffuser response model.« less

Pattern dynamics of the reaction-diffusion immune system.

PubMed

Zheng, Qianqian; Shen, Jianwei; Wang, Zhijie

2018-01-01

In this paper, we will investigate the effect of diffusion, which is ubiquitous in nature, on the immune system using a reaction-diffusion model in order to understand the dynamical behavior of complex patterns and control the dynamics of different patterns. Through control theory and linear stability analysis of local equilibrium, we obtain the optimal condition under which the system loses stability and a Turing pattern occurs. By combining mathematical analysis and numerical simulation, we show the possible patterns and how these patterns evolve. In addition, we establish a bridge between the complex patterns and the biological mechanism using the results from a previous study in Nature Cell Biology. The results in this paper can help us better understand the biological significance of the immune system.

Flow injection analysis simulations and diffusion coefficient determination by stochastic and deterministic optimization methods.

PubMed

Kucza, Witold

2013-07-25

Stochastic and deterministic simulations of dispersion in cylindrical channels on the Poiseuille flow have been presented. The random walk (stochastic) and the uniform dispersion (deterministic) models have been used for computations of flow injection analysis responses. These methods coupled with the genetic algorithm and the Levenberg-Marquardt optimization methods, respectively, have been applied for determination of diffusion coefficients. The diffusion coefficients of fluorescein sodium, potassium hexacyanoferrate and potassium dichromate have been determined by means of the presented methods and FIA responses that are available in literature. The best-fit results agree with each other and with experimental data thus validating both presented approaches. Copyright © 2013 The Author. Published by Elsevier B.V. All rights reserved.

Modeling of Diffusivity for 2D Vacancy Nanopits and Comparison with 2D Adatom Nanoislands on Metal(100) Surfaces Including Analysis for Ag(100)

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

Lai, King C.; Liu, Da-Jiang; Thiel, Patricia A.

Diffusion coefficients, D N, for 2D vacancy nanopits are compared with those for 2D homoepitaxial adatom nanoislands on metal(100) surfaces, focusing on the variation of DN with size, N. Here, N is measured in missing atoms for pits and adatoms for islands. Analysis of D N is based on kinetic Monte Carlo simulations of a tailored stochastic lattice-gas model, where pit and island diffusion are mediated by periphery diffusion, i.e., by edge atom hopping. Precise determination of D N versus N for typical parameters reveals a cyclical variation with an overall decrease in magnitude for increasing moderate O(10 2) ≤more » N ≤ O(10 3). Monotonic decay, D N~ N -β, is found for N ≥ O(10 2) with effective exponents, β = β eff, for both pits and islands, both well below the macroscopic value of βmacro = 3/2. D N values for vacancy pits are significantly lower (higher) than for adatom islands for moderate N in the case of low (high) kink rounding barrier. However, D N values for pits and islands slowly merge, and β eff → 3/2 for sufficiently large N. The latter feature is expected from continuum Langevin formulations appropriate for large sizes. Finally, we compare predictions from our model incorporating appropriate energetic parameters for Ag(100) with different sets of experimental data for diffusivity at 300 K, including assessment of β eff, for experimentally observed sizes N from ~100 to ~1000.« less

Modeling of Diffusivity for 2D Vacancy Nanopits and Comparison with 2D Adatom Nanoislands on Metal(100) Surfaces Including Analysis for Ag(100)

DOE PAGES

Lai, King C.; Liu, Da-Jiang; Thiel, Patricia A.; ...

2018-02-22

Diffusion coefficients, D N, for 2D vacancy nanopits are compared with those for 2D homoepitaxial adatom nanoislands on metal(100) surfaces, focusing on the variation of DN with size, N. Here, N is measured in missing atoms for pits and adatoms for islands. Analysis of D N is based on kinetic Monte Carlo simulations of a tailored stochastic lattice-gas model, where pit and island diffusion are mediated by periphery diffusion, i.e., by edge atom hopping. Precise determination of D N versus N for typical parameters reveals a cyclical variation with an overall decrease in magnitude for increasing moderate O(10 2) ≤more » N ≤ O(10 3). Monotonic decay, D N~ N -β, is found for N ≥ O(10 2) with effective exponents, β = β eff, for both pits and islands, both well below the macroscopic value of βmacro = 3/2. D N values for vacancy pits are significantly lower (higher) than for adatom islands for moderate N in the case of low (high) kink rounding barrier. However, D N values for pits and islands slowly merge, and β eff → 3/2 for sufficiently large N. The latter feature is expected from continuum Langevin formulations appropriate for large sizes. Finally, we compare predictions from our model incorporating appropriate energetic parameters for Ag(100) with different sets of experimental data for diffusivity at 300 K, including assessment of β eff, for experimentally observed sizes N from ~100 to ~1000.« less

Interactions of lysozyme in concentrated electrolyte solutions from dynamic light-scattering measurements.

PubMed Central

Kuehner, D E; Heyer, C; Rämsch, C; Fornefeld, U M; Blanch, H W; Prausnitz, J M

1997-01-01

The diffusion of hen egg-white lysozyme has been studied by dynamic light scattering in aqueous solutions of ammonium sulfate as a function of protein concentration to 30 g/liter. Experiments were conducted under the following conditions: pH 4-7 and ionic strength 0.05-5.0 M. Diffusivity data for ionic strengths up to 0.5 M were interpreted in the context of a two-body interaction model for monomers. From this analysis, two potential-of-mean-force parameters, the effective monomer charge, and the Hamaker constant were obtained. At higher ionic strength, the data were analyzed using a model that describes the diffusion coefficient of a polydisperse system of interacting protein aggregates in terms of an isodesmic, indefinite aggregation equilibrium constant. Data analysis incorporated multicomponent virial and hydrodynamic effects. The resulting equilibrium constants indicate that lysozyme does not aggregate significantly as ionic strength increases, even at salt concentrations near the point of salting-out precipitation. PMID:9414232

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

Oxygen self-diffusion mechanisms in monoclinic Zr O2 revealed and quantified by density functional theory, random walk analysis, and kinetic Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Yang, Jing; Youssef, Mostafa; Yildiz, Bilge

2018-01-01

In this work, we quantify oxygen self-diffusion in monoclinic-phase zirconium oxide as a function of temperature and oxygen partial pressure. A migration barrier of each type of oxygen defect was obtained by first-principles calculations. Random walk theory was used to quantify the diffusivities of oxygen interstitials by using the calculated migration barriers. Kinetic Monte Carlo simulations were used to calculate diffusivities of oxygen vacancies by distinguishing the threefold- and fourfold-coordinated lattice oxygen. By combining the equilibrium defect concentrations obtained in our previous work together with the herein calculated diffusivity of each defect species, we present the resulting oxygen self-diffusion coefficients and the corresponding atomistically resolved transport mechanisms. The predicted effective migration barriers and diffusion prefactors are in reasonable agreement with the experimentally reported values. This work provides insights into oxygen diffusion engineering in Zr O2 -related devices and parametrization for continuum transport modeling.

Linear model describing three components of flow in karst aquifers using 18O data

USGS Publications Warehouse

Long, Andrew J.; Putnam, L.D.

2004-01-01

The stable isotope of oxygen, 18O, is used as a naturally occurring ground-water tracer. Time-series data for ??18O are analyzed to model the distinct responses and relative proportions of the conduit, intermediate, and diffuse flow components in karst aquifers. This analysis also describes mathematically the dynamics of the transient fluid interchange between conduits and diffusive networks. Conduit and intermediate flow are described by linear-systems methods, whereas diffuse flow is described by mass-balance methods. An automated optimization process estimates parameters of lognormal, Pearson type III, and gamma distributions, which are used as transfer functions in linear-systems analysis. Diffuse flow and mixing parameters also are estimated by these optimization methods. Results indicate the relative proximity of a well to a main conduit flowpath and can help to predict the movement and residence times of potential contaminants. The three-component linear model is applied to five wells, which respond to changes in the isotopic composition of point recharge water from a sinking stream in the Madison aquifer in the Black Hills of South Dakota. Flow velocities as much as 540 m/d and system memories of as much as 71 years are estimated by this method. Also, the mean, median, and standard deviation of traveltimes; time to peak response; and the relative fraction of flow for each of the three components are determined for these wells. This analysis infers that flow may branch apart and rejoin as a result of an anastomotic (or channeled) karst network.

Concentration-Encoded Subdiffusive Molecular Communication: Theory, Channel Characteristics, and Optimum Signal Detection.

PubMed

Mahfuz, Mohammad Upal; Makrakis, Dimitrios; Mouftah, Hussein T

2016-09-01

Unlike normal diffusion, in anomalous diffusion, the movement of a molecule is described by the correlated random walk model where the mean square displacement of a molecule depends on the power law of time. In molecular communication (MC), there are many scenarios when the propagation of molecules cannot be described by normal diffusion process, where anomalous diffusion is a better fit. In this paper, the effects of anomalous subdiffusion on concentration-encoded molecular communication (CEMC) are investigated. Although classical (i.e., normal) diffusion is a widely-used model of diffusion in molecular communication (MC) research, anomalous subdiffusion is quite common in biological media involving bio-nanomachines, yet inadequately addressed as a research issue so far. Using the fractional diffusion approach, the molecular propagation effects in the case of pure subdiffusion occurring in an unbounded three-dimensional propagation medium have been shown in detail in terms of temporal dispersion parameters of the impulse response of the subdiffusive channel. Correspondingly, the bit error rate (BER) performance of a CEMC system is investigated with sampling-based (SD) and strength (i.e., energy)-based (ED) signal detection methods. It is found that anomalous subdiffusion has distinctive time-dispersive properties that play a vital role in accurately designing a subdiffusive CEMC system. Unlike normal diffusion, to detect information symbols in subdiffusive CEMC, a receiver requires larger memory size to operate correctly and hence a more complex structure. An in-depth analysis has been made on the performances of SD and ED optimum receiver models under diffusion noise and intersymbol interference (ISI) scenarios when communication range, transmission data rate, and memory size vary. In subdiffusive CEMC, the SD method.

Analysis of diffuse radiation data for Beer Sheva: Measured (shadow ring) versus calculated (global-horizontal beam) values

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

Kudish, A.I.; Ianetz, A.

1993-12-01

The authors have utilized concurrently measured global, normal incidence beam, and diffuse radiation data, the latter measured by means of a shadow ring pyranometer to study the relative magnitude of the anisotropic contribution (circumsolar region and nonuniform sky conditions) to the diffuse radiation. In the case of Beer Sheva, the monthly average hourly anisotropic correction factor varies from 2.9 to 20.9%, whereas the [open quotes]standard[close quotes] geometric correction factor varies from 5.6 to 14.0%. The monthly average hourly overall correction factor (combined anisotropic and geometric factors) varies from 8.9 to 37.7%. The data have also been analyzed using a simplemore » model of sky radiance developed by Steven in 1984. His anisotropic correction factor is a function of the relative strength and angular width of the circumsolar radiation region. The results of this analysis are in agreement with those previously reported for Quidron on the Dead Sea, viz. the anisotropy and relative strength of the circumsolar radiation are significantly greater than at any of the sites analyzed by Steven. In addition, the data have been utilized to validate a model developed by LeBaron et al. in 1990 for correcting shadow ring diffuse radiation data. The monthly average deviation between the corrected and true diffuse radiation values varies from 4.55 to 7.92%.« less

Evaluation of radiation necrosis and malignant glioma in rat models using diffusion tensor MR imaging

PubMed Central

Wang, Silun; Chen, Yifei; Lal, Bachchu; Ford, Eric; Tryggestad, Erik; Armour, Michael; Yan, Kun; Laterra, John; Zhou, Jinyuan

2011-01-01

Standard MRI cannot distinguish between radiation necrosis and tumor progression; however, this distinction is critical in the assessment of tumor response to therapy. In this study, one delayed radiation necrosis model (dose, 40 Gy; radiation field, 10 × 10 mm2; n = 13) and two orthotopic glioma models in rats (9L gliosarcoma, n = 8; human glioma xenografts, n = 5) were compared using multiple DTI indices. A visible isotropic apparent diffusion coefficient (ADC) pattern was observed in the lesion due to radiation necrosis, which consisted of a hypointense central zone and a hyperintense peripheral zone. There were significantly lower ADC, parallel diffusivity, and perpendicular diffusivity in the necrotic central zone than in the peripheral zone (all p < 0.001). When radiation-induced necrosis was compared with viable tumor, radiation necrosis had significantly lower ADC than 9L gliosarcoma and human glioma xenografts (both p < 0.01) in the central zone, and significantly lower FA than 9L gliosarcoma (p = 0.005) and human glioma xenografts (p = 0.012) in the peripheral zone. Histological analysis revealed parenchymal coagulative necrosis in the central zone, and damaged vessels and reactive astrogliosis in the peripheral zone. These data suggest that qualitative and quantitative analysis of the DTI maps can provide useful information by which to distinguish between radiation necrosis and viable glioma. PMID:21948114

New sensitive micro-measurements of dynamic surface tension and diffusion coefficients: Validated and tested for the adsorption of 1-Octanol at a microscopic air-water interface and its dissolution into water.

PubMed

Kinoshita, Koji; Parra, Elisa; Needham, David

2017-02-15

Currently available dynamic surface tension (DST) measurement methods, such as Wilhelmy plate, droplet- or bubble-based methods, still have various experimental limitations such as the large size of the interface, convection in the solution, or a certain "dead time" at initial measurement. These limitations create inconsistencies for the kinetic analysis of surfactant adsorption/desorption, especially significant for ionic surfactants. Here, the "micropipette interfacial area-expansion method" was introduced and validated as a new DST measurement having a high enough sensitivity to detect diffusion controlled molecular adsorption at the air-water interfaces. To validate the new technique, the diffusion coefficient of 1-Octanol in water was investigated with existing models: the Ward Tordai model for the long time adsorption regime (1-100s), and the Langmuir and Frumkin adsorption isotherm models for surface excess concentration. We found that the measured diffusion coefficient of 1-Octanol, 7.2±0.8×10 -6 cm 2 /s, showed excellent agreement with the result from an alternative method, "single microdroplet catching method", to measure the diffusion coefficient from diffusion-controlled microdroplet dissolution, 7.3±0.1×10 -6 cm 2 /s. These new techniques for determining adsorption and diffusion coefficients can apply for a range of surface active molecules, especially the less-characterized ionic surfactants, and biological compounds such as lipids, peptides, and proteins. Copyright © 2016 Elsevier Inc. All rights reserved.

Size and shape effects on diffusion and absorption of colloidal particles near a partially absorbing sphere: implications for uptake of nanoparticles in animal cells.

PubMed

Shi, Wendong; Wang, Jizeng; Fan, Xiaojun; Gao, Huajian

2008-12-01

A mechanics model describing how a cell membrane with diffusive mobile receptors wraps around a ligand-coated cylindrical or spherical particle has been recently developed to model the role of particle size in receptor-mediated endocytosis. The results show that particles in the size range of tens to hundreds of nanometers can enter cells even in the absence of clathrin or caveolin coats. Here we report further progress on modeling the effects of size and shape in diffusion, interaction, and absorption of finite-sized colloidal particles near a partially absorbing sphere. Our analysis indicates that, from the diffusion and interaction point of view, there exists an optimal hydrodynamic size of particles, typically in the nanometer regime, for the maximum rate of particle absorption. Such optimal size arises as a result of balance between the diffusion constant of the particles and the interaction energy between the particles and the absorbing sphere relative to the thermal energy. Particles with a smaller hydrodynamic radius have larger diffusion constant but weaker interaction with the sphere while larger particles have smaller diffusion constant but stronger interaction with the sphere. Since the hydrodynamic radius is also determined by the particle shape, an optimal hydrodynamic radius implies an optimal size as well as an optimal aspect ratio for a nonspherical particle. These results show broad agreement with experimental observations and may have general implications on interaction between nanoparticles and animal cells.

Size and shape effects on diffusion and absorption of colloidal particles near a partially absorbing sphere: Implications for uptake of nanoparticles in animal cells

NASA Astrophysics Data System (ADS)

Shi, Wendong; Wang, Jizeng; Fan, Xiaojun; Gao, Huajian

2008-12-01

A mechanics model describing how a cell membrane with diffusive mobile receptors wraps around a ligand-coated cylindrical or spherical particle has been recently developed to model the role of particle size in receptor-mediated endocytosis. The results show that particles in the size range of tens to hundreds of nanometers can enter cells even in the absence of clathrin or caveolin coats. Here we report further progress on modeling the effects of size and shape in diffusion, interaction, and absorption of finite-sized colloidal particles near a partially absorbing sphere. Our analysis indicates that, from the diffusion and interaction point of view, there exists an optimal hydrodynamic size of particles, typically in the nanometer regime, for the maximum rate of particle absorption. Such optimal size arises as a result of balance between the diffusion constant of the particles and the interaction energy between the particles and the absorbing sphere relative to the thermal energy. Particles with a smaller hydrodynamic radius have larger diffusion constant but weaker interaction with the sphere while larger particles have smaller diffusion constant but stronger interaction with the sphere. Since the hydrodynamic radius is also determined by the particle shape, an optimal hydrodynamic radius implies an optimal size as well as an optimal aspect ratio for a nonspherical particle. These results show broad agreement with experimental observations and may have general implications on interaction between nanoparticles and animal cells.

Insight into He diffusion in apatite by ion beam experiments and quantum calculations: implication for the (U-Th)/He thermochronometer

NASA Astrophysics Data System (ADS)

Gautheron, C.; Mbongo-Djimbi, D.; Gerin, C.; Roques, J.; Bachelet, C.; Oliviero, E.; Tassan-Got, L.

2015-12-01

The apatite (U-Th)/He (AHe) system has rapidly become a very popular thermochronometer, however, interpretation of AHe age depends on a precise knowledge of He diffusion. Several studies suggest that He retention is function of the amount of damage that is controlled by U-Th concentration, grain chemistry and thermal history. Still, the models are not well constrained and do not fully explain the mechanism of He retention. In order to have a deeper insight into this issue, a multidisciplinary study on apatite combining physical methods such as multi-scale theoretical diffusion calculations based on Density Functional Theory (DFT) with diffusion experiments by ion beam Elastic Recoil Diffusion Analysis (ERDA) were performed. Quantum calculations permit to quantify He diffusivity base level for damage-free crystal and to estimate the additional energy cost to extract He atoms trapped in point defects (i.e. vacancies). On the other hand ion beam ERDA experiments allow to measure He diffusivity in artificially damaged crystals. We show that damage-free apatite crystals are characterized by low retention behavior and closure temperature of ~35°C for pure F-apatite to higher value for Cl rich apatite (up to 12°C higher), for typical grain size and cooling rate (Mbongo-Djimbi et al., 2015). Our computed closure temperature is slightly lower than previously reported experimental values (~50°C). Using ERDA and DFT modeling of damage, we show how He diffusivity is influenced by damage. Finally, we are able to propose a new modeling of He diffusion incorporating mechanisms not included in classical damage models, and taking into account the level of damage and apatite chemistry. We show that it could affect significantly AHe age interpretation. Mbongo-Djimbi D. et al. 2015. Apatite composition effect on (U-Th)/He thermochronometer: an atomistic point of view. Geohimica Cosmochim. Acta.

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

NASA Astrophysics Data System (ADS)

Kim, Changho; Nonaka, Andy; Bell, John B.; Garcia, Alejandro L.; Donev, Aleksandar

2017-03-01

We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules, to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. By comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

DOE PAGES

Kim, Changho; Nonaka, Andy; Bell, John B.; ...

2017-03-24

Here, we develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules,more » to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. Furthermore, by comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.« less

Coronal "wave": Magnetic Footprint Of A Cme?

NASA Astrophysics Data System (ADS)

Attrill, Gemma; Harra, L. K.; van Driel-Gesztelyi, L.; Demoulin, P.; Wuelser, J.

2007-05-01

We propose a new mechanism for the generation of "EUV coronal waves". This work is based on new analysis of data from SOHO/EIT, SOHO/MDI & STEREO/EUVI. Although first observed in 1997, the interpretation of coronal waves as flare-induced or CME-driven remains a debated topic. We investigate the properties of two "classical" SOHO/EIT coronal waves in detail. The source regions of the associated CMEs possess opposite helicities & the coronal waves display rotations in opposite senses. We observe deep dimmings near the flare site & also widespread diffuse dimming, accompanying the expansion of the EIT wave. We report a new property of these EIT waves, namely, that they display dual brightenings: persistent ones at the outermost edge of the core dimming regions & simultaneously diffuse brightenings constituting the leading edge of the coronal wave, surrounding the expanding diffuse dimmings. We show that such behaviour is consistent with a diffuse EIT wave being the magnetic footprint of a CME. We propose a new mechanism where driven magnetic reconnections between the skirt of the expanding CME & quiet-Sun magnetic loops generate the observed bright diffuse front. The dual brightenings & widespread diffuse dimming are identified as innate characteristics of this process. In addition we present some of the first analysis of a STEREO/EUVI limb coronal wave. We show how the evolution of the diffuse bright front & dimmings can be understood in terms of the model described above. We show that an apparently stationary part of the bright front can be understood in terms of magnetic interchange reconnections between the expanding CME & the "open" magnetic field of a low-latitude coronal hole. We use both the SOHO/EIT & STEREO/EUVI events to demonstrate that through successive reconnections, this new model provides a natural mechanism via which CMEs can become large-scale in the lower corona.

Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging.

PubMed

Xu, Xiao Quan; Choi, Young Jun; Sung, Yu Sub; Yoon, Ra Gyoung; Jang, Seung Won; Park, Ji Eun; Heo, Young Jin; Baek, Jung Hwan; Lee, Jeong Hyun

2016-01-01

To investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck. We retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient (D(*)), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and D(*) and model-free parameters from the DCE-MRI (wash-in, Tmax, Emax, initial AUC60, whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson's correlation test was used for statistical analysis. No correlation was found between f or D(*) and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p < 0.001, r = 0.980) and muscles (p = 0.013, r = 0.542), despite its significantly higher value than D. The difference between ADC and D showed significant correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with D(*) (p > 0.05, respectively). Intravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck.

Heavy metal transport in large river systems: heavy metal emissions and loads in the Rhine and Elbe river basins

NASA Astrophysics Data System (ADS)

Vink, Rona; Behrendt, Horst

2002-11-01

Pollutant transport and management in the Rhine and Elbe basins is still of international concern, since certain target levels set by the international committees for protection of both rivers have not been reached. The analysis of the chain of emissions of point and diffuse sources to river loads will provide policy makers with a tool for effective management of river basins. The analysis of large river basins such as the Elbe and Rhine requires information on the spatial and temporal characteristics of both emissions and physical information of the entire river basin. In this paper, an analysis has been made of heavy metal emissions from various point and diffuse sources in the Rhine and Elbe drainage areas. Different point and diffuse pathways are considered in the model, such as inputs from industry, wastewater treatment plants, urban areas, erosion, groundwater, atmospheric deposition, tile drainage, and runoff. In most cases the measured heavy metal loads at monitoring stations are lower than the sum of the heavy metal emissions. This behaviour in large river systems can largely be explained by retention processes (e.g. sedimentation) and is dependent on the specific runoff of a catchment. Independent of the method used to estimate emissions, the source apportionment analysis of observed loads was used to determine the share of point and diffuse sources in the heavy metal load at a monitoring station by establishing a discharge dependency. The results from both the emission analysis and the source apportionment analysis of observed loads were compared and gave similar results. Between 51% (for Hg) and 74% (for Pb) of the total transport in the Elbe basin is supplied by inputs from diffuse sources. In the Rhine basin diffuse source inputs dominate the total transport and deliver more than 70% of the total transport. The diffuse hydrological pathways with the highest share are erosion and urban areas.

On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods.

PubMed

Van Hecke, Wim; Sijbers, Jan; De Backer, Steve; Poot, Dirk; Parizel, Paul M; Leemans, Alexander

2009-07-01

Although many studies are starting to use voxel-based analysis (VBA) methods to compare diffusion tensor images between healthy and diseased subjects, it has been demonstrated that VBA results depend heavily on parameter settings and implementation strategies, such as the applied coregistration technique, smoothing kernel width, statistical analysis, etc. In order to investigate the effect of different parameter settings and implementations on the accuracy and precision of the VBA results quantitatively, ground truth knowledge regarding the underlying microstructural alterations is required. To address the lack of such a gold standard, simulated diffusion tensor data sets are developed, which can model an array of anomalies in the diffusion properties of a predefined location. These data sets can be employed to evaluate the numerous parameters that characterize the pipeline of a VBA algorithm and to compare the accuracy, precision, and reproducibility of different post-processing approaches quantitatively. We are convinced that the use of these simulated data sets can improve the understanding of how different diffusion tensor image post-processing techniques affect the outcome of VBA. In turn, this may possibly lead to a more standardized and reliable evaluation of diffusion tensor data sets of large study groups with a wide range of white matter altering pathologies. The simulated DTI data sets will be made available online (http://www.dti.ua.ac.be).

In Situ Three-Dimensional Reciprocal-Space Mapping of Diffuse Scattering Intensity Distribution and Data Analysis for Precursor Phenomenon in Shape-Memory Alloy

NASA Astrophysics Data System (ADS)

Cheng, Tian-Le; Ma, Fengde D.; Zhou, Jie E.; Jennings, Guy; Ren, Yang; Jin, Yongmei M.; Wang, Yu U.

2012-01-01

Diffuse scattering contains rich information on various structural disorders, thus providing a useful means to study the nanoscale structural deviations from the average crystal structures determined by Bragg peak analysis. Extraction of maximal information from diffuse scattering requires concerted efforts in high-quality three-dimensional (3D) data measurement, quantitative data analysis and visualization, theoretical interpretation, and computer simulations. Such an endeavor is undertaken to study the correlated dynamic atomic position fluctuations caused by thermal vibrations (phonons) in precursor state of shape-memory alloys. High-quality 3D diffuse scattering intensity data around representative Bragg peaks are collected by using in situ high-energy synchrotron x-ray diffraction and two-dimensional digital x-ray detector (image plate). Computational algorithms and codes are developed to construct the 3D reciprocal-space map of diffuse scattering intensity distribution from the measured data, which are further visualized and quantitatively analyzed to reveal in situ physical behaviors. Diffuse scattering intensity distribution is explicitly formulated in terms of atomic position fluctuations to interpret the experimental observations and identify the most relevant physical mechanisms, which help set up reduced structural models with minimal parameters to be efficiently determined by computer simulations. Such combined procedures are demonstrated by a study of phonon softening phenomenon in precursor state and premartensitic transformation of Ni-Mn-Ga shape-memory alloy.

From average to local structure: a Rietveld and an atomic pair distribution function (PDF) study of selenium clusters in zeolite-NdY.

PubMed

Abeykoon, A M Milinda; Donner, Wolfgang; Brunelli, Michela; Castro-Colin, Miguel; Jacobson, Allan J; Moss, Simon C

2009-09-23

The structure of Se particles in the approximately 13 A diameter alpha-cages of zeolite NdY has been determined by Rietveld refinement and pair distribution function (PDF) analysis of X-ray data. With the diffuse scattering subtracted an average structure comprised of an undistorted framework containing nanoclusters of 20 Se atoms is observed. The intracluster correlations and the cluster-framework correlations which give rise to diffuse scattering were modeled by using PDF analysis.

Liver fibrosis: stretched exponential model outperforms mono-exponential and bi-exponential models of diffusion-weighted MRI.

PubMed

Seo, Nieun; Chung, Yong Eun; Park, Yung Nyun; Kim, Eunju; Hwang, Jinwoo; Kim, Myeong-Jin

2018-07-01

To compare the ability of diffusion-weighted imaging (DWI) parameters acquired from three different models for the diagnosis of hepatic fibrosis (HF). Ninety-five patients underwent DWI using nine b values at 3 T magnetic resonance. The hepatic apparent diffusion coefficient (ADC) from a mono-exponential model, the true diffusion coefficient (D t ), pseudo-diffusion coefficient (D p ) and perfusion fraction (f) from a biexponential model, and the distributed diffusion coefficient (DDC) and intravoxel heterogeneity index (α) from a stretched exponential model were compared with the pathological HF stage. For the stretched exponential model, parameters were also obtained using a dataset of six b values (DDC # , α # ). The diagnostic performances of the parameters for HF staging were evaluated with Obuchowski measures and receiver operating characteristics (ROC) analysis. The measurement variability of DWI parameters was evaluated using the coefficient of variation (CoV). Diagnostic accuracy for HF staging was highest for DDC # (Obuchowski measures, 0.770 ± 0.03), and it was significantly higher than that of ADC (0.597 ± 0.05, p < 0.001), D t (0.575 ± 0.05, p < 0.001) and f (0.669 ± 0.04, p = 0.035). The parameters from stretched exponential DWI and D p showed higher areas under the ROC curve (AUCs) for determining significant fibrosis (≥F2) and cirrhosis (F = 4) than other parameters. However, D p showed significantly higher measurement variability (CoV, 74.6%) than DDC # (16.1%, p < 0.001) and α # (15.1%, p < 0.001). Stretched exponential DWI is a promising method for HF staging with good diagnostic performance and fewer b-value acquisitions, allowing shorter acquisition time. • Stretched exponential DWI provides a precise and accurate model for HF staging. • Stretched exponential DWI parameters are more reliable than D p from bi-exponential DWI model • Acquisition of six b values is sufficient to obtain accurate DDC and α.

Determination of charge-carrier diffusion length in the photosensing layer of HgCdTe n-on-p photovoltaic infrared focal plane array detectors

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

Vishnyakov, A. V.; Stuchinsky, V. A., E-mail: stuchin@isp.nsc.ru; Brunev, D. V.

2014-03-03

In the present paper, we propose a method for evaluating the bulk diffusion length of minority charge carriers in the photosensing layer of photovoltaic focal plane array (FPA) photodetectors. The method is based on scanning a strip-shaped illumination spot with one of the detector diodes at a low level of photocurrents j{sub ph} being registered; such scanning provides data for subsequent analysis of measured spot-scan profiles within a simple diffusion model. The asymptotic behavior of the effective (at j{sub ph} ≠ 0) charge-carrier diffusion length l{sub d} {sub eff} as a function of j{sub ph} for j{sub ph} → 0 inferred frommore » our experimental data proved to be consistent with the behavior of l{sub d} {sub eff} vs j{sub ph} as predicted by the model, while the obtained values of the bulk diffusion length of minority carriers (electrons) in the p-HgCdTe film of investigated HgCdTe n-on-p FPA photodetectors were found to be in a good agreement with the previously reported carrier diffusion-length values for HgCdTe.« less

Exploring the dynamics of balance data — movement variability in terms of drift and diffusion

NASA Astrophysics Data System (ADS)

Gottschall, Julia; Peinke, Joachim; Lippens, Volker; Nagel, Volker

2009-02-01

We introduce a method to analyze postural control on a balance board by reconstructing the underlying dynamics in terms of a Langevin model. Drift and diffusion coefficients are directly estimated from the data and fitted by a suitable parametrization. The governing parameters are utilized to evaluate balance performance and the impact of supra-postural tasks on it. We show that the proposed method of analysis gives not only self-consistent results but also provides a plausible model for the reconstruction of balance dynamics.

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.

Spintronics: spin accumulation in mesoscopic systems.

PubMed

Johnson, Mark

2002-04-25

In spintronics, in which use is made of the spin degree of freedom of the electron, issues concerning electrical spin injection and detection of electron spin diffusion are fundamentally important. Jedema et al. describe a magneto-resistance study in which they claim to have observed spin accumulation in a mesoscopic copper wire, but their one-dimensional model ignores two-dimensional spin-diffusion effects, which casts doubt on their analysis. A two-dimensional vector formalism of spin transport is called for to model spin-injection experiments, and the identification of spurious background resistance effects is crucial.

Study of atmospheric diffusion using LANDSAT

NASA Technical Reports Server (NTRS)

Torsani, J. A.; Viswanadham, Y.

1982-01-01

The parameters of diffusion patterns of atmospheric pollutants under different conditions were investigated for use in the Gaussian model for calculation of pollution concentration. Value for the divergence pattern of concentration distribution along the Y axis were determined using LANDSAT images. Multispectral scanner images of a point source plume having known characteristics, wind and temperature data, and cloud cover and solar elevation data provided by LANDSAT, were analyzed using the 1-100 system for image analysis. These measured values are compared with pollution transport as predicted by the Pasquill-Gifford, Juelich, and Hoegstroem atmospheric models.

HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

PubMed

Wiecki, Thomas V; Sofer, Imri; Frank, Michael J

2013-01-01

The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of response time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper will first describe the theoretical background of the drift diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the χ(2)-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs/

The exit-time problem for a Markov jump process

NASA Astrophysics Data System (ADS)

Burch, N.; D'Elia, M.; Lehoucq, R. B.

2014-12-01

The purpose of this paper is to consider the exit-time problem for a finite-range Markov jump process, i.e, the distance the particle can jump is bounded independent of its location. Such jump diffusions are expedient models for anomalous transport exhibiting super-diffusion or nonstandard normal diffusion. We refer to the associated deterministic equation as a volume-constrained nonlocal diffusion equation. The volume constraint is the nonlocal analogue of a boundary condition necessary to demonstrate that the nonlocal diffusion equation is well-posed and is consistent with the jump process. A critical aspect of the analysis is a variational formulation and a recently developed nonlocal vector calculus. This calculus allows us to pose nonlocal backward and forward Kolmogorov equations, the former equation granting the various moments of the exit-time distribution.

White matter degeneration in schizophrenia: a comparative diffusion tensor analysis

NASA Astrophysics Data System (ADS)

Ingalhalikar, Madhura A.; Andreasen, Nancy C.; Kim, Jinsuh; Alexander, Andrew L.; Magnotta, Vincent A.

2010-03-01

Schizophrenia is a serious and disabling mental disorder. Diffusion tensor imaging (DTI) studies performed on schizophrenia have demonstrated white matter degeneration either due to loss of myelination or deterioration of fiber tracts although the areas where the changes occur are variable across studies. Most of the population based studies analyze the changes in schizophrenia using scalar indices computed from the diffusion tensor such as fractional anisotropy (FA) and relative anisotropy (RA). The scalar measures may not capture the complete information from the diffusion tensor. In this paper we have applied the RADTI method on a group of 9 controls and 9 patients with schizophrenia. The RADTI method converts the tensors to log-Euclidean space where a linear regression model is applied and hypothesis testing is performed between the control and patient groups. Results show that there is a significant difference in the anisotropy between patients and controls especially in the parts of forceps minor, superior corona radiata, anterior limb of internal capsule and genu of corpus callosum. To check if the tensor analysis gives a better idea of the changes in anisotropy, we compared the results with voxelwise FA analysis as well as voxelwise geodesic anisotropy (GA) analysis.

A quantitative property-property relationship for the internal diffusion coefficients of organic compounds in solid materials.

PubMed

Huang, L; Fantke, P; Ernstoff, A; Jolliet, O

2017-11-01

Indoor releases of organic chemicals encapsulated in solid materials are major contributors to human exposures and are directly related to the internal diffusion coefficient in solid materials. Existing correlations to estimate the diffusion coefficient are only valid for a limited number of chemical-material combinations. This paper develops and evaluates a quantitative property-property relationship (QPPR) to predict diffusion coefficients for a wide range of organic chemicals and materials. We first compiled a training dataset of 1103 measured diffusion coefficients for 158 chemicals in 32 consolidated material types. Following a detailed analysis of the temperature influence, we developed a multiple linear regression model to predict diffusion coefficients as a function of chemical molecular weight (MW), temperature, and material type (adjusted R 2 of .93). The internal validations showed the model to be robust, stable and not a result of chance correlation. The external validation against two separate prediction datasets demonstrated the model has good predicting ability within its applicability domain (Rext2>.8), namely MW between 30 and 1178 g/mol and temperature between 4 and 180°C. By covering a much wider range of organic chemicals and materials, this QPPR facilitates high-throughput estimates of human exposures for chemicals encapsulated in solid materials. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Extracellular diffusion quantified by magnetic resonance imaging during rat C6 glioma cell progression.

PubMed

Song, G; Luo, T; Dong, L; Liu, Q

2017-07-03

Solution reflux and edema hamper the convection-enhanced delivery of the standard treatment for glioma. Therefore, a real-time magnetic resonance imaging (MRI) method was developed to monitor the dosing process, but a quantitative analysis of local diffusion and clearance parameters has not been assessed. The objective of this study was to compare diffusion into the extracellular space (ECS) at different stages of rat C6 gliomas, and analyze the effects of the extracellular matrix (ECM) on the diffusion process. At 10 and 20 days, after successful glioma modeling, gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA) was introduced into the ECS of rat C6 gliomas. Diffusion parameters and half-life of the reagent were then detected using MRI, and quantified according to the mathematical model of diffusion. The main ECM components [chondroitin sulfate proteoglycans (CSPGs), collagen IV, and tenascin C] were detected by immunohistochemical and immunoblot analyses. In 20-day gliomas, Gd-DTPA diffused more slowly and derived higher tortuosity, with lower clearance rate and longer half-life compared to 10-day gliomas. The increased glioma ECM was associated with different diffusion and clearance parameters in 20-day rat gliomas compared to 10-day gliomas. ECS parameters were altered with C6 glioma progression from increased ECM content. Our study might help better understand the glioma microenvironment and provide benefits for interstitial drug delivery to treat brain gliomas.

Growth Mechanism Studies of ZnO Nanowires: Experimental Observations and Short-Circuit Diffusion Analysis.

PubMed

Shih, Po-Hsun; Wu, Sheng Yun

2017-07-21

Plenty of studies have been performed to probe the diverse properties of ZnO nanowires, but only a few have focused on the physical properties of a single nanowire since analyzing the growth mechanism along a single nanowire is difficult. In this study, a single ZnO nanowire was synthesized using a Ti-assisted chemical vapor deposition (CVD) method to avoid the appearance of catalytic contamination. Two-dimensional energy dispersive spectroscopy (EDS) mapping with a diffusion model was used to obtain the diffusion length and the activation energy ratio. The ratio value is close to 0.3, revealing that the growth of ZnO nanowires was attributed to the short-circuit diffusion.

Using selection bias to explain the observed structure of Internet diffusions

PubMed Central

Golub, Benjamin; Jackson, Matthew O.

2010-01-01

Recently, large datasets stored on the Internet have enabled the analysis of processes, such as large-scale diffusions of information, at new levels of detail. In a recent study, Liben-Nowell and Kleinberg [(2008) Proc Natl Acad Sci USA 105:4633–4638] observed that the flow of information on the Internet exhibits surprising patterns whereby a chain letter reaches its typical recipient through long paths of hundreds of intermediaries. We show that a basic Galton–Watson epidemic model combined with the selection bias of observing only large diffusions suffices to explain these patterns. Thus, selection biases of which data we observe can radically change the estimation of classical diffusion processes. PMID:20534439

Automated array assembly task, phase 1

NASA Technical Reports Server (NTRS)

Carbajal, B. G.

1977-01-01

Various aspects of a sensitivity analysis, in particular, the impact of variations in metal sheet resistivity, metal line width, diffused layer sheet resistance, junction depth, base layer lifetime, optical coating thickness and optical coating refractive index and on process reproducibility for A's diffusion from a polymer dopant source and on module fabrication were studied. Model calculations show that acceptable process windows exist for each of these parameters.

NMR investigation of water diffusion in different biofilm structures.

PubMed

Herrling, Maria P; Weisbrodt, Jessica; Kirkland, Catherine M; Williamson, Nathan H; Lackner, Susanne; Codd, Sarah L; Seymour, Joseph D; Guthausen, Gisela; Horn, Harald

2017-12-01

Mass transfer in biofilms is determined by diffusion. Different mostly invasive approaches have been used to measure diffusion coefficients in biofilms, however, data on heterogeneous biomass under realistic conditions is still missing. To non-invasively elucidate fluid-structure interactions in complex multispecies biofilms pulsed field gradient-nuclear magnetic resonance (PFG-NMR) was applied to measure the water diffusion in five different types of biomass aggregates: one type of sludge flocs, two types of biofilm, and two types of granules. Data analysis is an important issue when measuring heterogeneous systems and is shown to significantly influence the interpretation and understanding of water diffusion. With respect to numerical reproducibility and physico-chemical interpretation, different data processing methods were explored: (bi)-exponential data analysis and the Γ distribution model. Furthermore, the diffusion coefficient distribution in relation to relaxation was studied by D-T 2 maps obtained by 2D inverse Laplace transform (2D ILT). The results show that the effective diffusion coefficients for all biofilm samples ranged from 0.36 to 0.96 relative to that of water. NMR diffusion was linked to biofilm structure (e.g., biomass density, organic and inorganic matter) as observed by magnetic resonance imaging and to traditional biofilm parameters: diffusion was most restricted in granules with compact structures, and fast diffusion was found in heterotrophic biofilms with fluffy structures. The effective diffusion coefficients in the biomass were found to be broadly distributed because of internal biomass heterogeneities, such as gas bubbles, precipitates, and locally changing biofilm densities. Thus, estimations based on biofilm bulk properties in multispecies systems can be overestimated and mean diffusion coefficients might not be sufficiently informative to describe mass transport in biofilms and the near bulk. © 2017 Wiley Periodicals, Inc.

Network-based diffusion analysis reveals cultural transmission of lobtail feeding in humpback whales.

PubMed

Allen, Jenny; Weinrich, Mason; Hoppitt, Will; Rendell, Luke

2013-04-26

We used network-based diffusion analysis to reveal the cultural spread of a naturally occurring foraging innovation, lobtail feeding, through a population of humpback whales (Megaptera novaeangliae) over a period of 27 years. Support for models with a social transmission component was 6 to 23 orders of magnitude greater than for models without. The spatial and temporal distribution of sand lance, a prey species, was also important in predicting the rate of acquisition. Our results, coupled with existing knowledge about song traditions, show that this species can maintain multiple independently evolving traditions in its populations. These insights strengthen the case that cetaceans represent a peak in the evolution of nonhuman culture, independent of the primate lineage.

Nonequilibrium scheme for computing the flux of the convection-diffusion equation in the framework of the lattice Boltzmann method.

PubMed

Chai, Zhenhua; Zhao, T S

2014-07-01

In this paper, we propose a local nonequilibrium scheme for computing the flux of the convection-diffusion equation with a source term in the framework of the multiple-relaxation-time (MRT) lattice Boltzmann method (LBM). Both the Chapman-Enskog analysis and the numerical results show that, at the diffusive scaling, the present nonequilibrium scheme has a second-order convergence rate in space. A comparison between the nonequilibrium scheme and the conventional second-order central-difference scheme indicates that, although both schemes have a second-order convergence rate in space, the present nonequilibrium scheme is more accurate than the central-difference scheme. In addition, the flux computation rendered by the present scheme also preserves the parallel computation feature of the LBM, making the scheme more efficient than conventional finite-difference schemes in the study of large-scale problems. Finally, a comparison between the single-relaxation-time model and the MRT model is also conducted, and the results show that the MRT model is more accurate than the single-relaxation-time model, both in solving the convection-diffusion equation and in computing the flux.

Leakage flow simulation in a specific pump model

NASA Astrophysics Data System (ADS)

Dupont, P.; Bayeul-Lainé, A. C.; Dazin, A.; Bois, G.; Roussette, O.; Si, Q.

2014-03-01

This paper deals with the influence of leakage flow existing in SHF pump model on the analysis of internal flow behaviour inside the vane diffuser of the pump model performance using both experiments and calculations. PIV measurements have been performed at different hub to shroud planes inside one diffuser channel passage for a given speed of rotation and various flow rates. For each operating condition, the PIV measurements have been trigged with different angular impeller positions. The performances and the static pressure rise of the diffuser were also measured using a three-hole probe. The numerical simulations were carried out with Star CCM+ 8.06 code (RANS frozen and unsteady calculations). Comparisons between numerical and experimental results are presented and discussed for three flow rates. The performances of the diffuser obtained by numerical simulation results are compared to the performances obtained by three-hole probe indications. The comparisons show few influence of fluid leakage on global performances but a real improvement concerning the efficiency of the impeller, the pump and the velocity distributions. These results show that leakage is an important parameter that has to be taken into account in order to make improved comparisons between numerical approaches and experiments in such a specific model set up.

Postural control model interpretation of stabilogram diffusion analysis

NASA Technical Reports Server (NTRS)

Peterka, R. J.

2000-01-01

Collins and De Luca [Collins JJ. De Luca CJ (1993) Exp Brain Res 95: 308-318] introduced a new method known as stabilogram diffusion analysis that provides a quantitative statistical measure of the apparently random variations of center-of-pressure (COP) trajectories recorded during quiet upright stance in humans. This analysis generates a stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons. SDFs have a characteristic two-part form that suggests the presence of two different control regimes: a short-term open-loop control behavior and a longer-term closed-loop behavior. This paper demonstrates that a very simple closed-loop control model of upright stance can generate realistic SDFs. The model consists of an inverted pendulum body with torque applied at the ankle joint. This torque includes a random disturbance torque and a control torque. The control torque is a function of the deviation (error signal) between the desired upright body position and the actual body position, and is generated in proportion to the error signal, the derivative of the error signal, and the integral of the error signal [i.e. a proportional, integral and derivative (PID) neural controller]. The control torque is applied with a time delay representing conduction, processing, and muscle activation delays. Variations in the PID parameters and the time delay generate variations in SDFs that mimic real experimental SDFs. This model analysis allows one to interpret experimentally observed changes in SDFs in terms of variations in neural controller and time delay parameters rather than in terms of open-loop versus closed-loop behavior.

Catchment Models and Management Tools for diffuse Contaminants (Sediment, Phosphorus and Pesticides): DIFFUSE Project

NASA Astrophysics Data System (ADS)

Mockler, Eva; Reaney, Simeon; Mellander, Per-Erik; Wade, Andrew; Collins, Adrian; Arheimer, Berit; Bruen, Michael

2017-04-01

The agricultural sector is the most common suspected source of nutrient pollution in Irish rivers. However, it is also often the most difficult source to characterise due to its predominantly diffuse nature. Particulate phosphorus in surface water and dissolved phosphorus in groundwater are of particular concern in Irish water bodies. Hence the further development of models and indices to assess diffuse sources of contaminants are required for use by the Irish Environmental Protection Agency (EPA) to provide support for river basin planning. Understanding connectivity in the landscape is a vital component of characterising the source-pathway-receptor relationships for water-borne contaminants, and hence is a priority in this research. The DIFFUSE Project will focus on connectivity modelling and incorporation of connectivity into sediment, nutrient and pesticide risk mapping. The Irish approach to understanding and managing natural water bodies has developed substantially in recent years assisted by outputs from multiple research projects, including modelling and analysis tools developed during the Pathways and CatchmentTools projects. These include the Pollution Impact Potential (PIP) maps, which are an example of research output that is used by the EPA to support catchment management. The PIP maps integrate an understanding of the pollution pressures and mobilisation pathways and, using the source-pathways-receptor model, provide a scientific basis for evaluation of mitigation measures. These maps indicate the potential risk posed by nitrate and phosphate from diffuse agricultural sources to surface and groundwater receptors and delineate critical source areas (CSAs) as a means of facilitating the targeting of mitigation measures. Building on this previous research, the DIFFUSE Project will develop revised and new catchment managements tools focused on connectivity, sediment, phosphorus and pesticides. The DIFFUSE project will strive to identify the state-of-the-art methods and models that are most applicable to Irish conditions and management challenges. All styles of modelling considered useful for water resources management are relevant to this project and a balance of technical sophistication, data availability and operational practicalities is the ultimate goal. Achievement of this objective will be measured by comparing the performance of the new models developed in the project with models used in other countries. The models and tools developed in the course of the project will be evaluated by comparison with Irish catchment data and with other state-of-the-art models in a model-inter-comparison workshop which will be open to other models and the wider research community.

Exciton delocalization incorporated drift-diffusion model for bulk-heterojunction organic solar cells

NASA Astrophysics Data System (ADS)

Wang, Zi Shuai; Sha, Wei E. I.; Choy, Wallace C. H.

2016-12-01

Modeling the charge-generation process is highly important to understand device physics and optimize power conversion efficiency of bulk-heterojunction organic solar cells (OSCs). Free carriers are generated by both ultrafast exciton delocalization and slow exciton diffusion and dissociation at the heterojunction interface. In this work, we developed a systematic numerical simulation to describe the charge-generation process by a modified drift-diffusion model. The transport, recombination, and collection of free carriers are incorporated to fully capture the device response. The theoretical results match well with the state-of-the-art high-performance organic solar cells. It is demonstrated that the increase of exciton delocalization ratio reduces the energy loss in the exciton diffusion-dissociation process, and thus, significantly improves the device efficiency, especially for the short-circuit current. By changing the exciton delocalization ratio, OSC performances are comprehensively investigated under the conditions of short-circuit and open-circuit. Particularly, bulk recombination dependent fill factor saturation is unveiled and understood. As a fundamental electrical analysis of the delocalization mechanism, our work is important to understand and optimize the high-performance OSCs.

End Effects and Load Diffusion in Composite Structures

NASA Technical Reports Server (NTRS)

Horgan, Cornelius O.; Ambur, D. (Technical Monitor); Nemeth, M. P. (Technical Monitor)

2002-01-01

The research carried out here builds on our previous NASA supported research on the general topic of edge effects and load diffusion in composite structures. Further fundamental solid mechanics studies were carried out to provide a basis for assessing the complicated modeling necessary for large scale structures used by NASA. An understanding of the fundamental mechanisms of load diffusion in composite subcomponents is essential in developing primary composite structures. Specific problems recently considered were focussed on end effects in sandwich structures and for functionally graded materials. Both linear and nonlinear (geometric and material) problems have been addressed. Our goal is the development of readily applicable design formulas for the decay lengths in terms of non-dimensional material and geometric parameters. Analytical models of load diffusion behavior are extremely valuable in building an intuitive base for developing refined modeling strategies and assessing results from finite element analyses. The decay behavior of stresses and other field quantities provides a significant aid towards this process. The analysis is also amenable to parameter study with a large parameter space and should be useful in structural tailoring studies.

CO2 adsorption using TiO2 composite polymeric membranes: A kinetic study.

PubMed

Hafeez, Sarah; Fan, X; Hussain, Arshad; Martín, C F

2015-09-01

CO2 is the main greenhouse gas which causes global climatic changes on larger scale. Many techniques have been utilised to capture CO2. Membrane gas separation is a fast growing CO2 capture technique, particularly gas separation by composite membranes. The separation of CO2 by a membrane is not just a process to physically sieve out of CO2 through the controlled membrane pore size. It mainly depends upon diffusion and solubility of gases, particularly for composite dense membranes. The blended components in composite membranes have a high capability to adsorb CO2. The adsorption kinetics of the gases may directly affect diffusion and solubility. In this study, we have investigated the adsorption behaviour of CO2 in pure and composite membranes to explore the complete understanding of diffusion and solubility of CO2 through membranes. Pure cellulose acetate (CA) and cellulose acetate-titania nanoparticle (CA-TiO2) composite membranes were fabricated and characterised using SEM and FTIR analysis. The results indicated that the blended CA-TiO2 membrane adsorbed more quantity of CO2 gas as compared to pure CA membrane. The high CO2 adsorption capacity may enhance the diffusion and solubility of CO2 in the CA-TiO2 composite membrane, which results in a better CO2 separation. The experimental data was modelled by Pseudo first-order, pseudo second order and intra particle diffusion models. According to correlation factor R(2), the Pseudo second order model was fitted well with experimental data. The intra particle diffusion model revealed that adsorption in dense membranes was not solely consisting of intra particle diffusion. Copyright © 2015. Published by Elsevier B.V.

Analysis of diffusion and binding in cells using the RICS approach.

PubMed

Digman, Michelle A; Gratton, Enrico

2009-04-01

The movement of macromolecules in cells is assumed to occur either through active transport or by diffusion. However, the determination of the diffusion coefficients in cells using fluctuation methods or FRAP frequently give diffusion coefficient that are orders of magnitude smaller than the diffusion coefficients measured for the same macromolecule in solution. It is assumed that the cell internal viscosity is partially responsible for this decrease in the apparent diffusion. When the apparent diffusion is too slow to be due to cytoplasm viscosity, it is assumed that weak binding of the macromolecules to immobile or quasi immobile structures is taking place. In this article, we derive equations for fitting of the RICS (Raster-scan Image Correlations Spectroscopy) data in cells to a model that includes transient binding to immobile structures, and we show that under some conditions, the spatio-temporal correlation provided by the RICS approach can distinguish the process of diffusion and weak binding. We apply the method to determine the diffusion in the cytoplasm and binding of Focal Adhesion Kinase-EGFP to adhesions in MEF cells.

Influence of crystal orientation and ion bombardment on the nitrogen diffusivity in single-crystalline austenitic stainless steel

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

Martinavicius, A.; Abrasonis, G.; Moeller, W.

2011-10-01

The nitrogen diffusivity in single-crystalline AISI 316L austenitic stainless steel (ASS) during ion nitriding has been investigated at different crystal orientations ((001), (110), (111)) under variations of ion flux (0.3-0.7 mA cm{sup -2}), ion energy (0.5-1.2 keV), and temperature (370-430 deg. C). The nitrogen depth profiles obtained from nuclear reaction analysis are in excellent agreement with fits using the model of diffusion under the influence of traps, from which diffusion coefficients were extracted. At fixed ion energy and flux, the diffusivity varies by a factor up to 2.5 at different crystal orientations. At (100) orientation, it increases linearly with increasingmore » ion flux or energy. The findings are discussed on the basis of atomistic mechanisms of interstitial diffusion, potential lattice distortions, local decomposition, and ion-induced lattice vibrational excitations.« less

Analysis of diffusion in curved surfaces and its application to tubular membranes.

PubMed

Klaus, Colin James Stockdale; Raghunathan, Krishnan; DiBenedetto, Emmanuele; Kenworthy, Anne K

2016-12-01

Diffusion of particles in curved surfaces is inherently complex compared with diffusion in a flat membrane, owing to the nonplanarity of the surface. The consequence of such nonplanar geometry on diffusion is poorly understood but is highly relevant in the case of cell membranes, which often adopt complex geometries. To address this question, we developed a new finite element approach to model diffusion on curved membrane surfaces based on solutions to Fick's law of diffusion and used this to study the effects of geometry on the entry of surface-bound particles into tubules by diffusion. We show that variations in tubule radius and length can distinctly alter diffusion gradients in tubules over biologically relevant timescales. In addition, we show that tubular structures tend to retain concentration gradients for a longer time compared with a comparable flat surface. These findings indicate that sorting of particles along the surfaces of tubules can arise simply as a geometric consequence of the curvature without any specific contribution from the membrane environment. Our studies provide a framework for modeling diffusion in curved surfaces and suggest that biological regulation can emerge purely from membrane geometry. © 2016 Klaus, Raghunathan, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Performance Analysis of Transposition Models Simulating Solar Radiation on Inclined Surfaces

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

Xie, Yu; Sengupta, Manajit

2016-06-02

Transposition models have been widely used in the solar energy industry to simulate solar radiation on inclined photovoltaic panels. Following numerous studies comparing the performance of transposition models, this work aims to understand the quantitative uncertainty in state-of-the-art transposition models and the sources leading to the uncertainty. Our results show significant differences between two highly used isotropic transposition models, with one substantially underestimating the diffuse plane-of-array irradiances when diffuse radiation is perfectly isotropic. In the empirical transposition models, the selection of the empirical coefficients and land surface albedo can both result in uncertainty in the output. This study can bemore » used as a guide for the future development of physics-based transposition models and evaluations of system performance.« less

The EZ diffusion model provides a powerful test of simple empirical effects.

PubMed

van Ravenzwaaij, Don; Donkin, Chris; Vandekerckhove, Joachim

2017-04-01

Over the last four decades, sequential accumulation models for choice response times have spread through cognitive psychology like wildfire. The most popular style of accumulator model is the diffusion model (Ratcliff Psychological Review, 85, 59-108, 1978), which has been shown to account for data from a wide range of paradigms, including perceptual discrimination, letter identification, lexical decision, recognition memory, and signal detection. Since its original inception, the model has become increasingly complex in order to account for subtle, but reliable, data patterns. The additional complexity of the diffusion model renders it a tool that is only for experts. In response, Wagenmakers et al. (Psychonomic Bulletin & Review, 14, 3-22, 2007) proposed that researchers could use a more basic version of the diffusion model, the EZ diffusion. Here, we simulate experimental effects on data generated from the full diffusion model and compare the power of the full diffusion model and EZ diffusion to detect those effects. We show that the EZ diffusion model, by virtue of its relative simplicity, will be sometimes better able to detect experimental effects than the data-generating full diffusion model.

A two-dimensional microscale model of gas exchange during photosynthesis in maize (Zea mays L.) leaves.

PubMed

Retta, Moges; Ho, Quang Tri; Yin, Xinyou; Verboven, Pieter; Berghuijs, Herman N C; Struik, Paul C; Nicolaï, Bart M

2016-05-01

CO2 exchange in leaves of maize (Zea mays L.) was examined using a microscale model of combined gas diffusion and C4 photosynthesis kinetics at the leaf tissue level. Based on a generalized scheme of photosynthesis in NADP-malic enzyme type C4 plants, the model accounted for CO2 diffusion in a leaf tissue, CO2 hydration and assimilation in mesophyll cells, CO2 release from decarboxylation of C4 acids, CO2 fixation in bundle sheath cells and CO2 retro-diffusion from bundle sheath cells. The transport equations were solved over a realistic 2-D geometry of the Kranz anatomy obtained from light microscopy images. The predicted responses of photosynthesis rate to changes in ambient CO2 and irradiance compared well with those obtained from gas exchange measurements. A sensitivity analysis showed that the CO2 permeability of the mesophyll-bundle sheath and airspace-mesophyll interfaces strongly affected the rate of photosynthesis and bundle sheath conductance. Carbonic anhydrase influenced the rate of photosynthesis, especially at low intercellular CO2 levels. In addition, the suberin layer at the exposed surface of the bundle sheath cells was found beneficial in reducing the retro-diffusion. The model may serve as a tool to investigate CO2 diffusion further in relation to the Kranz anatomy in C4 plants. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

What lies beneath? Diffusion EAP-based study of brain tissue microstructure.

PubMed

Zucchelli, Mauro; Brusini, Lorenza; Andrés Méndez, C; Daducci, Alessandro; Granziera, Cristina; Menegaz, Gloria

2016-08-01

Diffusion weighted magnetic resonance signals convey information about tissue microstructure and cytoarchitecture. In the last years, many models have been proposed for recovering the diffusion signal and extracting information to constitute new families of numerical indices. Two main categories of reconstruction models can be identified in diffusion magnetic resonance imaging (DMRI): ensemble average propagator (EAP) models and compartmental models. From both, descriptors can be derived for elucidating the underlying microstructural architecture. While compartmental models indices directly quantify the fraction of different cell compartments in each voxel, EAP-derived indices are only a derivative measure and the effect of the different microstructural configurations on the indices is still unclear. In this paper, we analyze three EAP indices calculated using the 3D Simple Harmonic Oscillator based Reconstruction and Estimation (3D-SHORE) model and estimate their changes with respect to the principal microstructural configurations. We take advantage of the state of the art simulations to quantify the variations of the indices with the simulation parameters. Analysis of in-vivo data correlates the EAP indices with the microstructural parameters obtained from the Neurite Orientation Dispersion and Density Imaging (NODDI) model as a pseudo ground truth for brain data. Results show that the EAP derived indices convey information on the tissue microstructure and that their combined values directly reflect the configuration of the different compartments in each voxel. Copyright © 2016 Elsevier B.V. All rights reserved.

A diffusion-limited reaction model for self-propagating Al/Pt multilayers with quench limits

NASA Astrophysics Data System (ADS)

Kittell, D. E.; Yarrington, C. D.; Hobbs, M. L.; Abere, M. J.; Adams, D. P.

2018-04-01

A diffusion-limited reaction model was calibrated for Al/Pt multilayers ignited on oxidized silicon, sapphire, and tungsten substrates, as well as for some Al/Pt multilayers ignited as free-standing foils. The model was implemented in a finite element analysis code and used to match experimental burn front velocity data collected from several years of testing at Sandia National Laboratories. Moreover, both the simulations and experiments reveal well-defined quench limits in the total Al + Pt layer (i.e., bilayer) thickness. At these limits, the heat generated from atomic diffusion is insufficient to support a self-propagating wave front on top of the substrates. Quench limits for reactive multilayers are seldom reported and are found to depend on the thermal properties of the individual layers. Here, the diffusion-limited reaction model is generalized to allow for temperature- and composition-dependent material properties, phase change, and anisotropic thermal conductivity. Utilizing this increase in model fidelity, excellent overall agreement is shown between the simulations and experimental results with a single calibrated parameter set. However, the burn front velocities of Al/Pt multilayers ignited on tungsten substrates are over-predicted. Possible sources of error are discussed and a higher activation energy (from 41.9 kJ/mol.at. to 47.5 kJ/mol.at.) is shown to bring the simulations into agreement with the velocity data observed on tungsten substrates. This higher activation energy suggests an inhibited diffusion mechanism present at lower heating rates.

Coarse-grained model of water diffusion and proton conductivity in hydrated polyelectrolyte membrane

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

Lee, Ming-Tsung; Vishnyakov, Aleksey; Neimark, Alexander V., E-mail: aneimark@rutgers.edu

2016-01-07

Using dissipative particle dynamics (DPD), we simulate nanoscale segregation, water diffusion, and proton conductivity in hydrated sulfonated polystyrene (sPS). We employ a novel model [Lee et al. J. Chem. Theory Comput. 11(9), 4395-4403 (2015)] that incorporates protonation/deprotonation equilibria into DPD simulations. The polymer and water are modeled by coarse-grained beads interacting via short-range soft repulsion and smeared charge electrostatic potentials. The proton is introduced as a separate charged bead that forms dissociable Morse bonds with the base beads representing water and sulfonate anions. Morse bond formation and breakup artificially mimics the Grotthuss mechanism of proton hopping between the bases. Themore » DPD model is parameterized by matching the proton mobility in bulk water, dissociation constant of benzenesulfonic acid, and liquid-liquid equilibrium of water-ethylbenzene solutions. The DPD simulations semi-quantitatively predict nanoscale segregation in the hydrated sPS into hydrophobic and hydrophilic subphases, water self-diffusion, and proton mobility. As the hydration level increases, the hydrophilic subphase exhibits a percolation transition from isolated water clusters to a 3D network. The analysis of hydrophilic subphase connectivity and water diffusion demonstrates the importance of the dynamic percolation effect of formation and breakup of temporary junctions between water clusters. The proposed DPD model qualitatively predicts the ratio of proton to water self-diffusion and its dependence on the hydration level that is in reasonable agreement with experiments.« less

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.

Integration of plume and puff diffusion models/application of CFD

NASA Astrophysics Data System (ADS)

Mori, Akira

The clinical symptoms of patients and other evidences of a gas poisoning accident inside an industrial building strongly suggested an abrupt influx of engine exhaust from a construction vehicle which was operating outside in the open air. But the obviously high level of gas concentration could not be well explained by any conventional steady-state gas diffusion models. The author used an unsteady-state continuous Puff Model to simulate the time-wise changes in air stream with the pollutant gas being continuously emitted, and successfully reproduced the observed phenomena. The author demonstrates that this diffusion formula can be solved analytically by the use of error function as long as the change in wind velocity is stepwise, and clarifies the accurate differences between the unsteady- and steady-states and their convergence profiles. Also, the relationship between the Puff and Plume Models is discussed. The case study included a computational fluid dynamics (CFD) analysis to estimate the steady-state air stream and the gas concentration pattern in the affected area. It is well known that clear definition of the boundary conditions is key to successful CFD analysis. The author describes a two-step use of CFD: the first step to define the boundary conditions and the second to determine the steady-state air stream and the gas concentration pattern.

MO-G-BRF-07: Anomalously Fast Diffusion of Carbon Nanotubes Carriers in 3D Tissue Model

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

Wang, Y; Bahng, J; Kotov, N

Purpose: We aim to investigate and understand diffusion process of carbon nanotubes (CNTs) and other nanoscale particles in tissue and organs. Methods: In this research, we utilized a 3D model tissue of hepatocellular carcinoma (HCC)cultured in inverted colloidal crystal (ICC) scaffolds to compare the diffusivity of CNTs with small molecules such as Rhodamine and FITC in vitro, and further investigated the transportation of CNTs with and without targeting ligand, TGFβ1. The real-time permeation profiles of CNTs in HCC tissue model with high temporal and spatial resolution was demonstrated by using standard confocal microscopy. Quantitative analysis of the diffusion process inmore » 3D was carried out using luminescence intensity in a series of Z-stack images obtained for different time points of the diffusion process after initial addition of CNTs or small molecules to the cell culture and the image data was analyzed by software ImageJ and Mathematica. Results: CNTs display diffusion rate in model tissues substantially faster than small molecules of the similar charge such as FITC, and the diffusion rate of CNTs are significantly enhanced with targeting ligand, TGFβ1. Conclusion: In terms of the advantages of in-vitro model, we were able to have access to measuring the rate of CNT penetration at designed conditions with variable parameters. And the findings by using this model, changed our understanding about advantages of CNTs as nanoscale drug carriers and provides design principles for making new drug carriers for both treatment and diagnostics. Additionally the fast diffusion opens the discussion of the best possible drug carriers to reach deep parts of cancerous tissues, which is often a prerequisite for successful cancer treatment. This work was supported by the Center for Photonic and Multiscale Nanomaterials funded by National Science Foundation Materials Research Science and Engineering Center program DMR 1120923. The work was also partially supported by NSF grant ECS-0601345; EFRI-BSBA 0938019; CBET 0933384; CBET 0932823; CBET 1036672, AFOSR MURI 444286-P061716 and NIH 1R21CA121841-01A2.« less

Does the 'diffusion of innovations' model enrich understanding of research use? Case studies of the implementation of thrombolysis services for stroke.

PubMed

Boaz, Annette; Baeza, Juan; Fraser, Alec

2016-10-01

To test whether the model of 'diffusion of innovations' enriches understanding of the implementation of evidence-based thrombolysis services for stroke patients. Four case studies of the implementation of evidence on thrombolysis in stroke services in England and Sweden. Semistructured interviews with 95 staff including doctors, nurses and managers working in stroke units, emergency medicine, radiology, the ambulance service, community rehabilitation services and commissioners. The implementation of thrombolysis in acute stroke management benefited from a critical mass of the factors featured in the model including: the support of national and local opinion leaders; a strong evidence base and financial incentives. However, while the model provided a starting point as an organizational framework for mapping the critical factors influencing implementation, to understand properly the process of implementation and the importance of the different factors identified, more detailed analyses of context and, in particular, of the human and social dimensions of change was needed. While recognising the usefulness of the model of diffusion of innovations in mapping the processes by which diffusion occurs, the use of methods that lend themselves to in-depth analysis, such as ethnography and the application of relevant bodies of social theory, are needed. © The Author(s) 2016.

Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema

PubMed Central

Chiang, Chia-Wen; Wang, Yong; Sun, Peng; Lin, Tsen-Hsuan; Trinkaus, Kathryn; Cross, Anne H.; Song, Sheng-Kwei

2014-01-01

The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA), increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. The MC simulation and tissue phantom data were also analyzed by the recently developed diffusion basis spectrum imaging (DBSI) to simultaneously distinguish and quantify the axon/myelin integrity and extra-fiber diffusion components. Results showed that increased cellularity or vasogenic edema did not affect the DBSI-derived fiber FA, axial or radial diffusivity. Importantly, the extent of extra-fiber cellularity and edema estimated by DBSI correlated with experimentally added gel and Monte-Carlo simulations. We also examined the feasibility of applying 25-direction diffusion encoding scheme for DBSI analysis on coherent white matter tracts. Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice. PMID:25017446

Revisiting thermodynamics and kinetic diffusivities of uranium–niobium with Bayesian uncertainty analysis

DOE PAGES

Duong, Thien C.; Hackenberg, Robert E.; Landa, Alex; ...

2016-09-20

In this paper, thermodynamic and kinetic diffusivities of uranium–niobium (U–Nb) are re-assessed by means of the CALPHAD (CALculation of PHAse Diagram) methodology. In order to improve the consistency and reliability of the assessments, first-principles calculations are coupled with CALPHAD. In particular, heats of formation of γ -U–Nb are estimated and verified using various density-functional theory (DFT) approaches. These thermochemistry data are then used as constraints to guide the thermodynamic optimization process in such a way that the mutual-consistency between first-principles calculations and CALPHAD assessment is satisfactory. In addition, long-term aging experiments are conducted in order to generate new phase equilibriamore » data at the γ 2/α+γ 2 boundary. These data are meant to verify the thermodynamic model. Assessment results are generally in good agreement with experiments and previous calculations, without showing the artifacts that were observed in previous modeling. The mutual-consistent thermodynamic description is then used to evaluate atomic mobility and diffusivity of γ-U–Nb. Finally, Bayesian analysis is conducted to evaluate the uncertainty of the thermodynamic model and its impact on the system's phase stability.« less

A chaotic model for advertising diffusion problem with competition

NASA Astrophysics Data System (ADS)

Ip, W. H.; Yung, K. L.; Wang, Dingwei

2012-08-01

In this article, the author extends Dawid and Feichtinger's chaotic advertising diffusion model into the duopoly case. A computer simulation system is used to test this enhanced model. Based on the analysis of simulation results, it is found that the best advertising strategy in duopoly is to increase the advertising investment to reach the best Win-Win situation where the oscillation of market portion will not occur. In order to effectively arrive at the best situation, we define a synthetic index and two thresholds. An estimation method for the parameters of the index and thresholds is proposed in this research. We can reach the Win-Win situation by simply selecting the control parameters to make the synthetic index close to the threshold of min-oscillation state. The numerical example and computational results indicated that the proposed chaotic model is useful to describe and analyse advertising diffusion process in duopoly, it is an efficient tool for the selection and optimisation of advertising strategy.

Fluorescence recovery after photo-bleaching as a method to determine local diffusion coefficient in the stratum corneum.

PubMed

Anissimov, Yuri G; Zhao, Xin; Roberts, Michael S; Zvyagin, Andrei V

2012-10-01

Fluorescence recovery after photo-bleaching experiments were performed in human stratum corneum in vitro. Fluorescence multiphoton tomography was used, which allowed the dimensions of the photobleached volume to be at the micron scale and located fully within the lipid phase of the stratum corneum. Analysis of the fluorescence recovery data with simplified mathematical models yielded the diffusion coefficient of small molecular weight organic fluorescent dye Rhodamine B in the stratum corneum lipid phase of about (3-6) × 10(-9)cm(2) s(-1). It was concluded that the presented method can be used for detailed analysis of localised diffusion coefficients in the stratum corneum phases for various fluorescent probes. Copyright © 2012 Elsevier B.V. All rights reserved.

Modeling condensation with a noncondensable gas for mixed convection flow

NASA Astrophysics Data System (ADS)

Liao, Yehong

2007-05-01

This research theoretically developed a novel mixed convection model for condensation with a noncondensable gas. The model developed herein is comprised of three components: a convection regime map; a mixed convection correlation; and a generalized diffusion layer model. These components were developed in a way to be consistent with the three-level methodology in MELCOR. The overall mixed convection model was implemented into MELCOR and satisfactorily validated with data covering a wide variety of test conditions. In the development of the convection regime map, two analyses with approximations of the local similarity method were performed to solve the multi-component two-phase boundary layer equations. The first analysis studied effects of the bulk velocity on a basic natural convection condensation process and setup conditions to distinguish natural convection from mixed convection. It was found that the superimposed velocity increases condensation heat transfer by sweeping away the noncondensable gas accumulated at the condensation boundary. The second analysis studied effects of the buoyancy force on a basic forced convection condensation process and setup conditions to distinguish forced convection from mixed convection. It was found that the superimposed buoyancy force increases condensation heat transfer by thinning the liquid film thickness and creating a steeper noncondensable gas concentration profile near the condensation interface. In the development of the mixed convection correlation accounting for suction effects, numerical data were obtained from boundary layer analysis for the three convection regimes and used to fit a curve for the Nusselt number of the mixed convection regime as a function of the Nusselt numbers of the natural and forced convection regimes. In the development of the generalized diffusion layer model, the driving potential for mass transfer was expressed as the temperature difference between the bulk and the liquid-gas interface using the Clausius-Clapeyron equation. The model was developed on a mass basis instead of a molar basis to be consistent with general conservation equations. It was found that vapor diffusion is not only driven by a gradient of the molar fraction but also a gradient of the mixture molecular weight at the diffusion layer.

Nucleation and growth kinetics of electrodeposited sulfate-doped polypyrrole: determination of the diffusion coefficient of SO(4)(2-) in the polymeric membrane.

PubMed

Licona-Sánchez, T de J; Alvarez-Romero, G A; Mendoza-Huizar, L H; Galán-Vidal, C A; Palomar-Pardavé, M; Romero-Romo, M; Herrera-Hernández, H; Uruchurtu, J; Juárez-García, J M

2010-08-05

A kinetic study for the electrosynthesis of polypyrrole (Ppy) doped with SO(4)(2-) ions is presented. Ppy films were electrochemically polymerized onto a graphite-epoxy resin electrode. Experimental current density transients (j-t) were obtained for three different potentiometric behaviors: anionic, cationic, and a combination. Theoretical models were used to fit the experimental j-t data to determine the nucleation and growth processes controlling the polymer synthesis. It was encountered that, in all cases, pyrrole electropolimerization involves two concomitant processes, namely, a Ppy diffusion limited multiple 3D nucleation and growth and pyrrole electro-oxidation on the growing surface of the Ppy nuclei. SEM analysis of the electrodes surfaces reveals that Ppy deposition occurred over most of the electrode surface by multiple nucleation of hemispheres, as the theoretical model used for the analysis of the current transients required. Hemispherical particles formed the polymeric film displaying different sizes. The order for the particle size was as follows: anionic > anionic-cationic > cationic. These results are congruent with those obtained by theoretical analysis of the corresponding current transients. Analysis of the impedance measurements recorded on the anionic Ppy film, immersed in an aqueous solution with different sulfate ion concentrations evidenced that SO(4)(2-) ions diffuse through the Ppy film provoking a decrease of its electrical resistance and an increase of its dielectric constant. From the Warburg impedance coefficient, the sulfate coefficient of diffusion in the Ppy film was 1.38 x 10(-9) cm(2) s(-1).

Diffusive dynamics of nanoparticles in ultra-confined media

DOE PAGES

Jacob, Jack Deodato; Conrad, Jacinta; Krishnamoorti, Ramanan; ...

2015-08-10

Differential dynamic microscopy (DDM) was used to investigate the diffusive dynamics of nanoparticles of diameter 200 400 nm that were strongly confined in a periodic square array of cylindrical nanoposts. The minimum distance between posts was 1.3 5 times the diameter of the nanoparticles. The image structure functions obtained from the DDM analysis were isotropic and could be fit by a stretched exponential function. The relaxation time scaled diffusively across the range of wave vectors studied, and the corresponding scalar diffusivities decreased monotonically with increased confinement. The decrease in diffusivity could be described by models for hindered diffusion that accountedmore » for steric restrictions and hydrodynamic interactions. The stretching exponent decreased linearly as the nanoparticles were increasingly confined by the posts. Altogether, these results are consistent with a picture in which strongly confined nanoparticles experience a heterogeneous spatial environment arising from hydrodynamics and volume exclusion on time scales comparable to cage escape, leading to multiple relaxation processes and Fickian but non-Gaussian diffusive dynamics.« less

Parametric spatiotemporal oscillation in reaction-diffusion systems.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Parametric spatiotemporal oscillation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Analysis of Heat Transfer Phenomenon in Magnetohydrodynamic Casson Fluid Flow Through Cattaneo-Christov Heat Diffusion Theory

NASA Astrophysics Data System (ADS)

Ramesh, G. K.; Gireesha, B. J.; Shehzad, S. A.; Abbasi, F. M.

2017-07-01

Heat transport phenomenon of two-dimensional magnetohydrodynamic Casson fluid flow by employing Cattaneo-Christov heat diffusion theory is described in this work. The term of heat absorption/generation is incorporated in the mathematical modeling of present flow problem. The governing mathematical expressions are solved for velocity and temperature profiles using RKF 45 method along with shooting technique. The importance of arising nonlinear quantities namely velocity, temperature, skin-friction and temperature gradient are elaborated via plots. It is explored that the Casson parameter retarded the liquid velocity while it enhances the fluid temperature. Further, we noted that temperature and thickness of temperature boundary layer are weaker in case of Cattaneo-Christov heat diffusion model when matched with the profiles obtained for Fourier’s theory of heat flux.

Stochastic theory of photon flow in homogeneous and heterogeneous anisotropic biological and artificial material

NASA Astrophysics Data System (ADS)

Miller, Steven D.

1995-05-01

Standard Monte Carlo methods used in photon diffusion score absorbed photons or statistical weight deposited within voxels comprising a mesh. An alternative approach to a stochastic description is considered for rapid surface flux calculations and finite medias. Matrix elements are assigned to a spatial lattice whose function is to score vector intersections of scattered photons making transitions into either the forward or back solid angle half spaces. These complete matrix elements can be related to the directional fluxes within the lattice space. This model differentiates between ballistic, quasi-ballistic, and highly diffuse photon contributions, and effectively models the subsurface generation of a scattered light flux from a ballistic source. The connection between a path integral and diffusion is illustrated. Flux perturbations can be effectively illustrated for tissue-tumor-tissue and for 3 layer systems with strong absorption in one or more layers. For conditions where the diffusion theory has difficulties such as strong absorption, highly collimated sources, small finite volumes, and subsurface regions, the computation time of the algorithm is rapid with good accuracy and compliments other description of photon diffusion. The model has the potential to do computations relevant to photodynamic therapy (PDT) and analysis of laser beam interaction with tissues.

Quantitative dual-probe microdialysis: mathematical model and analysis.

PubMed

Chen, Kevin C; Höistad, Malin; Kehr, Jan; Fuxe, Kjell; Nicholson, Charles

2002-04-01

Steady-state microdialysis is a widely used technique to monitor the concentration changes and distributions of substances in tissues. To obtain more information about brain tissue properties from microdialysis, a dual-probe approach was applied to infuse and sample the radiotracer, [3H]mannitol, simultaneously both in agar gel and in the rat striatum. Because the molecules released by one probe and collected by the other must diffuse through the interstitial space, the concentration profile exhibits dynamic behavior that permits the assessment of the diffusion characteristics in the brain extracellular space and the clearance characteristics. In this paper a mathematical model for dual-probe microdialysis was developed to study brain interstitial diffusion and clearance processes. Theoretical expressions for the spatial distribution of the infused tracer in the brain extracellular space and the temporal concentration at the probe outlet were derived. A fitting program was developed using the simplex algorithm, which finds local minima of the standard deviations between experiments and theory by adjusting the relevant parameters. The theoretical curves accurately fitted the experimental data and generated realistic diffusion parameters, implying that the mathematical model is capable of predicting the interstitial diffusion behavior of [3H]mannitol and that it will be a valuable quantitative tool in dual-probe microdialysis.

Plants may alter competition by modifying nutrient bioavailability in rhizosphere: a modeling approach.

PubMed

Raynaud, Xavier; Jaillard, Benoît; Leadley, Paul W

2008-01-01

Plants modify nutrient availability by releasing chemicals in the rhizosphere. This change in availability induced by roots (bioavailability) is known to improve nutrient uptake by individual plants releasing such compounds. Can this bioavailability alter plant competition for nutrients and under what conditions? To address these questions, we have developed a model of nutrient competition between plant species based on mechanistic descriptions of nutrient diffusion, plant exudation, and plant uptake. The model was parameterized using data of the effects of root citrate exudation on phosphorus availability. We performed a sensitivity analysis for key parameters to test the generality of these effects. Our simulations suggest the following. (1) Nutrient uptake depends on the number of roots when nutrients and exudates diffuse little, because individual roots are nearly independent in terms of nutrient supply. In this case, bioavailability profits only species with exudates. (2) Competition for nutrients depends on the spatial arrangement of roots when nutrients diffuse little but exudates diffuse widely. (3) Competition for nutrients depends on the nutrient uptake capacity of roots when nutrients and exudates diffuse widely. In this case, bioavailability profits all species. Mechanisms controlling competition for bioavailable nutrients appear to be diverse and strongly depend on soil, nutrient, and plant properties.

ADP Compartmentation Analysis Reveals Coupling between Pyruvate Kinase and ATPases in Heart Muscle

PubMed Central

Sepp, Mervi; Vendelin, Marko; Vija, Heiki; Birkedal, Rikke

2010-01-01

Abstract Cardiomyocytes have intracellular diffusion restrictions, which spatially compartmentalize ADP and ATP. However, the models that predict diffusion restrictions have used data sets generated in rat heart permeabilized fibers, where diffusion distances may be heterogeneous. This is avoided by using isolated, permeabilized cardiomyocytes. The aim of this work was to analyze the intracellular diffusion of ATP and ADP in rat permeabilized cardiomyocytes. To do this, we measured respiration rate, ATPase rate, and ADP concentration in the surrounding solution. The data were analyzed using mathematical models that reflect different levels of cell compartmentalization. In agreement with previous studies, we found significant diffusion restriction by the mitochondrial outer membrane and confirmed a functional coupling between mitochondria and a fraction of ATPases in the cell. In addition, our experimental data show that considerable activity of endogenous pyruvate kinase (PK) remains in the cardiomyocytes after permeabilization. A fraction of ATPases were inactive without ATP feedback by this endogenous PK. When analyzing the data, we were able to reproduce the measurements only with the mathematical models that include a tight coupling between the fraction of endogenous PK and ATPases. To our knowledge, this is the first time such a strong coupling of PK to ATPases has been demonstrated in permeabilized cardiomyocytes. PMID:20550890

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

NASA Astrophysics Data System (ADS)

Lai, King C.; Liu, Da-Jiang; Evans, James W.

2017-12-01

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal (100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN˜ N-β with β =3 /2 . However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N <9 ; (ii) slow nucleation-mediated diffusion with small β <1 for "perfect" sizes N = Np= L2 or L (L +1 ) , for L =3 ,4 , ... having unique ground-state shapes, for moderate sizes 9 ≤N ≤O (102) ; the same also applies for N =Np+3 , Np+ 4 , ... (iii) facile diffusion but with large β >2 for N =Np+1 and Np+2 also for moderate sizes 9 ≤N ≤O (102) ; (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲β <3 /2 , reflecting the quasifacetted structure of clusters, for larger N =O (102) to N =O (103) ; (v) classic scaling with β =3 /2 for very large N =O (103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where we show that diffusivity cycles quasiperiodically from the slowest branch for Np+3 (not Np) to the fastest branch for Np+1 . Behavior is quantified by kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground-state and low-lying excited state cluster configurations, and also of kink populations.

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

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

Lai, King C.; Liu, Da -Jiang; Evans, James W.

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal(100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN ~ N -β with β = 3/2. However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N < 9; (ii) slow nucleation-mediated diffusion with small β < 1 for “perfect” sizes N = N p = L 2 or L(L+1), for L = 3, 4,… having unique ground state shapes, for moderate sizes 9 ≤ N ≤ O(10 2); the samemore » also applies for N = N p +3, N p + 4,… (iii) facile diffusion but with large β > 2 for N = Np + 1 and N p + 2 also for moderate sizes 9 ≤ N ≤ O(10 2); (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲ β < 3/2, reflecting the quasi-facetted structure of clusters, for larger N = O(10 2) to N = O(10 3); and (v) classic scaling with β = 3/2 for very large N = O(103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where show that diffusivity cycles quasi-periodically from the slowest branch for N p + 3 (not Np) to the fastest branch for Np + 1. Behavior is quantified by Kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back-correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground state and low-lying excited state cluster configurations, and also of kink populations.« less

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

DOE PAGES

Lai, King C.; Liu, Da -Jiang; Evans, James W.

2017-12-05

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal(100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN ~ N -β with β = 3/2. However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N < 9; (ii) slow nucleation-mediated diffusion with small β < 1 for “perfect” sizes N = N p = L 2 or L(L+1), for L = 3, 4,… having unique ground state shapes, for moderate sizes 9 ≤ N ≤ O(10 2); the samemore » also applies for N = N p +3, N p + 4,… (iii) facile diffusion but with large β > 2 for N = Np + 1 and N p + 2 also for moderate sizes 9 ≤ N ≤ O(10 2); (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲ β < 3/2, reflecting the quasi-facetted structure of clusters, for larger N = O(10 2) to N = O(10 3); and (v) classic scaling with β = 3/2 for very large N = O(103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where show that diffusivity cycles quasi-periodically from the slowest branch for N p + 3 (not Np) to the fastest branch for Np + 1. Behavior is quantified by Kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back-correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground state and low-lying excited state cluster configurations, and also of kink populations.« less

Alveolar ventilation to perfusion heterogeneity and diffusion impairment in a mathematical model of gas exchange

NASA Technical Reports Server (NTRS)

Vidal Melo, M. F.; Loeppky, J. A.; Caprihan, A.; Luft, U. C.

1993-01-01

This study describes a two-compartment model of pulmonary gas exchange in which alveolar ventilation to perfusion (VA/Q) heterogeneity and impairment of pulmonary diffusing capacity (D) are simultaneously taken into account. The mathematical model uses as input data measurements usually obtained in the lung function laboratory. It consists of two compartments and an anatomical shunt. Each compartment receives fractions of alveolar ventilation and blood flow. Mass balance equations and integration of Fick's law of diffusion are used to compute alveolar and blood O2 and CO2 values compatible with input O2 uptake and CO2 elimination. Two applications are presented. The first is a method to partition O2 and CO2 alveolar-arterial gradients into VA/Q and D components. The technique is evaluated in data of patients with chronic obstructive pulmonary disease (COPD). The second is a theoretical analysis of the effects of blood flow variation in alveolar and blood O2 partial pressures. The results show the importance of simultaneous consideration of D to estimate VA/Q heterogeneity in patients with diffusion impairment. This factor plays an increasing role in gas alveolar-arterial gradients as severity of COPD increases. Association of VA/Q heterogeneity and D may produce an increase of O2 arterial pressure with decreasing QT which would not be observed if only D were considered. We conclude that the presented computer model is a useful tool for description and interpretation of data from COPD patients and for performing theoretical analysis of variables involved in the gas exchange process.

Modeling persistence of motion in a crowded environment: The diffusive limit of excluding velocity-jump processes

NASA Astrophysics Data System (ADS)

Gavagnin, Enrico; Yates, Christian A.

2018-03-01

Persistence of motion is the tendency of an object to maintain motion in a direction for short time scales without necessarily being biased in any direction in the long term. One of the most appropriate mathematical tools to study this behavior is an agent-based velocity-jump process. In the absence of agent-agent interaction, the mean-field continuum limit of the agent-based model (ABM) gives rise to the well known hyperbolic telegraph equation. When agent-agent interaction is included in the ABM, a strictly advective system of partial differential equations (PDEs) can be derived at the population level. However, no diffusive limit of the ABM has been obtained from such a model. Connecting the microscopic behavior of the ABM to a diffusive macroscopic description is desirable, since it allows the exploration of a wider range of scenarios and establishes a direct connection with commonly used statistical tools of movement analysis. In order to connect the ABM at the population level to a diffusive PDE at the population level, we consider a generalization of the agent-based velocity-jump process on a two-dimensional lattice with three forms of agent interaction. This generalization allows us to take a diffusive limit and obtain a faithful population-level description. We investigate the properties of the model at both the individual and population levels and we elucidate some of the models' key characteristic features. In particular, we show an intrinsic anisotropy inherent to the models and we find evidence of a spontaneous form of aggregation at both the micro- and macroscales.

Experimental validation of convection-diffusion discretisation scheme employed for computational modelling of biological mass transport

PubMed Central

2010-01-01

Background The finite volume solver Fluent (Lebanon, NH, USA) is a computational fluid dynamics software employed to analyse biological mass-transport in the vasculature. A principal consideration for computational modelling of blood-side mass-transport is convection-diffusion discretisation scheme selection. Due to numerous discretisation schemes available when developing a mass-transport numerical model, the results obtained should either be validated against benchmark theoretical solutions or experimentally obtained results. Methods An idealised aneurysm model was selected for the experimental and computational mass-transport analysis of species concentration due to its well-defined recirculation region within the aneurysmal sac, allowing species concentration to vary slowly with time. The experimental results were obtained from fluid samples extracted from a glass aneurysm model, using the direct spectrophometric concentration measurement technique. The computational analysis was conducted using the four convection-diffusion discretisation schemes available to the Fluent user, including the First-Order Upwind, the Power Law, the Second-Order Upwind and the Quadratic Upstream Interpolation for Convective Kinetics (QUICK) schemes. The fluid has a diffusivity of 3.125 × 10-10 m2/s in water, resulting in a Peclet number of 2,560,000, indicating strongly convection-dominated flow. Results The discretisation scheme applied to the solution of the convection-diffusion equation, for blood-side mass-transport within the vasculature, has a significant influence on the resultant species concentration field. The First-Order Upwind and the Power Law schemes produce similar results. The Second-Order Upwind and QUICK schemes also correlate well but differ considerably from the concentration contour plots of the First-Order Upwind and Power Law schemes. The computational results were then compared to the experimental findings. An average error of 140% and 116% was demonstrated between the experimental results and those obtained from the First-Order Upwind and Power Law schemes, respectively. However, both the Second-Order upwind and QUICK schemes accurately predict species concentration under high Peclet number, convection-dominated flow conditions. Conclusion Convection-diffusion discretisation scheme selection has a strong influence on resultant species concentration fields, as determined by CFD. Furthermore, either the Second-Order or QUICK discretisation schemes should be implemented when numerically modelling convection-dominated mass-transport conditions. Finally, care should be taken not to utilize computationally inexpensive discretisation schemes at the cost of accuracy in resultant species concentration. PMID:20642816

Empirical constraints on closure temperatures from a single diffusion coefficient

NASA Astrophysics Data System (ADS)

Lee, J. K. W.

The elucidation of thermal histories by geochronological and isotopic means is based fundamentally on solid-state diffusion and the concept of closure temperatures. Because diffusion is thermally activated, an analytical solution of the closure temperature (Tc*) can only be obtained if the diffusion coefficient D of the diffusion process is measured at two or more different temperatures. If the diffusion coefficient is known at only one temperature, however, the true closure temperature (Tc*) cannot be calculated analytically because there exist an infinite number of possible (apparent) closure temperatures (Tc) which can be generated by this single datum. By introducing further empirical constraints to limit the range of possible closure temperatures, however, mathematical analysis of a modified form of the closure temperature equation shows that it is possible to make both qualitative and quantitative estimates of Tc* given knowledge of only one diffusion coefficient DM measured at one temperature TM. Qualitative constraints of the true closure temperature Tc* are obtained from the shapes of curves on a graph of the apparent Tc (Tc) vs. activation energy E, in which each curve is based on a single diffusion coefficient measurement DM at temperature TM. Using a realistic range of E, the concavity of the curve shows whether TM is less than, approximately equal to, or greater than Tc*. Quantitative estimates are obtained by considering two dimensionless parameters [lnÊRT^c vs. Tc*/TM] derived from these curves. When these parameters are plotted for known argon diffusion data and for a given diffusion size and cooling rate, it is found that the resultant curves are almost identical for all of the commonly dated K-Ar minerals - biotite, phlogopite, muscovite, hornblende and orthoclase - in spite of differences in their diffusion parameters. A common curve for Ar diffusion can be derived by least-squares fitting of all the Ar diffusion data and provides a way of predicting a ``model'' closure temperature Tcm from a single diffusion coefficient DM at temperature TM. Preliminary diffusion data for a labradorite lead to a Tcm of 507+/-17°C and a corresponding activation energy of about 65kcal/mol, given a grain size of 200μm and a cooling rate of 5°C/Ma. Curves for He diffusion in silicates (augite, quartz and sanidine) also overlap to a significant degree, both among themselves and with the Ar model curve, suggesting that a single model curve may be a good representation of noble gas closure temperatures in silicates. An analogous model curve for a selection of 18O data can also be constructed, but this curve differs from the Ar model curve. A single model curve for cationic species does not appear to exist, however, suggesting that chemical bonding relationships between the ionic size/charge and crystal structure may influence the closure temperatures of diffusing cations. An indication of the degree of overlap among the various curves for Ar, He, 18O and cations is also obtained by considering the dimensionless parameter E/RTc*; for the noble gases and 18O, E/RTc* values for the respective minerals are very similar, whereas for cations, there is significant dispersion. Given these constraints, this may be a potential method of estimating closure temperatures for certain diffusing species when there are limited diffusion data.

A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

NASA Astrophysics Data System (ADS)

Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

2018-06-01

Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

Generalized mathematical-computational-electronic model of MPTP- induced Parkinsonism

NASA Astrophysics Data System (ADS)

Jaramillo Raquejo, Daniela

2013-05-01

The substance 1-methyl-4-phenyl-1, 2, 3, 6 tetrahy dropyridine (MPTP) has been studied as a major cause of neurodegeneration dopaminica, which is specifically related to Parkinson's disease. The analysis is in terms of the diffusion of the substance to the mammalian brain, by evaluating the diffusion equation in a spherical coordinate system, being η (collective diffusion term) spatially modulated. Although the progress of the disease with respect to time has not been established with certainty, an attempt to find a stable pattern of the concentration of MPTP and its effects has been made.

NUMERICAL METHODS FOR SOLVING THE MULTI-TERM TIME-FRACTIONAL WAVE-DIFFUSION EQUATION.

PubMed

Liu, F; Meerschaert, M M; McGough, R J; Zhuang, P; Liu, Q

2013-03-01

In this paper, the multi-term time-fractional wave-diffusion equations are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and techniques can also be extended to other kinds of the multi-term fractional time-space models with fractional Laplacian.

NUMERICAL METHODS FOR SOLVING THE MULTI-TERM TIME-FRACTIONAL WAVE-DIFFUSION EQUATION

PubMed Central

Liu, F.; Meerschaert, M.M.; McGough, R.J.; Zhuang, P.; Liu, Q.

2013-01-01

In this paper, the multi-term time-fractional wave-diffusion equations are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and techniques can also be extended to other kinds of the multi-term fractional time-space models with fractional Laplacian. PMID:23772179

Analysis of dangerous area of single berth oil tanker operations based on CFD

NASA Astrophysics Data System (ADS)

Shi, Lina; Zhu, Faxin; Lu, Jinshu; Wu, Wenfeng; Zhang, Min; Zheng, Hailin

2018-04-01

Based on the single process in the liquid cargo tanker berths in the state as the research object, we analyzed the single berth oil tanker in the process of VOCs diffusion theory, built network model of VOCs diffusion with Gambit preprocessor, set up the simulation boundary conditions and simulated the five detection point sources in specific factors under the influence of VOCs concentration change with time by using Fluent software. We analyzed the dangerous area of single berth oil tanker operations through the diffusion of VOCs, so as to ensure the safe operation of oil tanker.

Comparison of bi-exponential and mono-exponential models of diffusion-weighted imaging for detecting active sacroiliitis in ankylosing spondylitis.

PubMed

Sun, Haitao; Liu, Kai; Liu, Hao; Ji, Zongfei; Yan, Yan; Jiang, Lindi; Zhou, Jianjun

2018-04-01

Background There has been a growing need for a sensitive and effective imaging method for the differentiation of the activity of ankylosing spondylitis (AS). Purpose To compare the performances of intravoxel incoherent motion (IVIM)-derived parameters and the apparent diffusion coefficient (ADC) for distinguishing AS-activity. Material and Methods One hundred patients with AS were divided into active (n = 51) and non-active groups (n = 49) and 21 healthy volunteers were included as control. The ADC, diffusion coefficient ( D), pseudodiffusion coefficient ( D*), and perfusion fraction ( f) were calculated for all groups. Kruskal-Wallis tests and receiver operator characteristic (ROC) curve analysis were performed for all parameters. Results There was good reproducibility of ADC /D and relatively poor reproducibility of D*/f. ADC, D, and f were significantly higher in the active group than in the non-active and control groups (all P < 0.0001, respectively). D* was slightly but significant lower in the active group than in the non-active and control group ( P = 0.0064, 0.0215). There was no significant difference in any parameter between the non-active group and the control group (all P > 0.050). In the ROC analysis, ADC had the largest AUC for distinguishing between the active group and the non-active group (0.988) and between the active and control groups (0.990). Multivariate logistic regression analysis models showed no diagnostic improvement. Conclusion ADC provided better diagnostic performance than IVIM-derived parameters in differentiating AS activity. Therefore, a straightforward and effective mono-exponential model of diffusion-weighted imaging may be sufficient for differentiating AS activity in the clinic.

A theoretical model for the collective motion of proteins by means of principal component analysis

NASA Astrophysics Data System (ADS)

Kamberaj, Hiqmet

2011-02-01

A coarse grained model in the frame work of principal component analysis is presented. We used a bath of harmonic oscillators approach, based on classical mechanics, to derive the generalized Langevin equations of motion for the collective coordinates. The dynamics of the protein collective coordinates derived from molecular dynamics simulations have been studied for the Bovine Pancreatic Trypsin Inhibitor. We analyzed the stability of the method by studying structural fluctuations of the C a atoms obtained from a 20 ns molecular dynamics simulation. Subsequently, the dynamics of the collective coordinates of protein were characterized by calculating the dynamical friction coefficient and diffusion coefficients along with time-dependent correlation functions of collective coordinates. A dual diffusion behavior was observed with a fast relaxation time of short diffusion regime 0.2-0.4 ps and slow relaxation time of long diffusion about 1-2 ps. In addition, we observed a power law decay of dynamical friction coefficient with exponent for the first five collective coordinates varying from -0.746 to -0.938 for the real part and from -0.528 to -0.665 for its magnitude. It was found that only the first ten collective coordinates are responsible for configuration transitions occurring on time scale longer than 50 ps.

A review of the liquid metal diffusion data obtained from the space shuttle endeavour mission STS-47 and the space shuttle columbia mission STS-52

NASA Astrophysics Data System (ADS)

Shirkhanzadeh, Morteza

Accurate data of liquid-phase solute diffusion coefficients are required to validate the condensed -matter physics theories. However, the required data accuracy to discriminate between com-peting theoretical models is 1 to 2 percent(1). Smith and Scott (2) have recently used the measured values of diffusion coefficients for Pb-Au in microgravity to validate the theoretical values of the diffusion coefficients derived from molecular dynamics simulations and several Enskog hard sphere models. The microgravity data used was obtained from the liquid diffusion experiments conducted on board the Space Shuttle Endeavour (mission STS-47) and the Space Shuttle Columbia (mission STS-52). Based on the analysis of the results, it was claimed that the measured values of diffusion coefficients were consistent with the theoretical results and that the data fit a linear relationship with a slope slightly greater than predicted by the molecular dynamics simulations. These conclusions, however, contradict the claims made in previous publications (3-5) where it was reported that the microgravity data obtained from the shuttle experiments fit the fluctuation theory (D proportional to T2). A thorough analysis of data will be presented to demonstrate that the widely-reported micro-gravity results obtained from shuttle experiments are not reliable and sufficiantly accurate to discriminate between competing theoretical models. References: 1. J.P. Garandet, G. Mathiak, V. Botton, P. Lehmann and A. Griesche, Int. J. Thermophysics, 25, 249 (2004). 2.P.J. Scott and R.W. Smith, J. Appl. Physics 104, 043706 (2008). 3. R.W. Smith, Microgravity Sci. Technol. XI (2) 78-84 (1998). 4.Smith et al, Ann. N.Y. Acad. Sci. 974:56-67 (2002) (retracted). 5.R.A. Herring et al, J. Jpn. Soc. Microgravity Appl., Vol.16, 234-244 (1999).

The Influence of Preferential Flow on Pressure Propagation and Landslide Triggering of the Rocca Pitigliana Landslide

NASA Astrophysics Data System (ADS)

Shao, W.; Bogaard, T.; Bakker, M.; Berti, M.; Savenije, H. H. G.

2016-12-01

The fast pore water pressure response to rain events is an important triggering factor for slope instability. The fast pressure response may be caused by preferential flow that bypasses the soil matrix. Currently, most of the hydro-mechanical models simulate pore water pressure using a single-permeability model, which cannot quantify the effects of preferential flow on pressure propagation and landslide triggering. Previous studies showed that a model based on the linear-diffusion equation can simulate the fast pressure propagation in near-saturated landslides such as the Rocca Pitigliana landslide. In such a model, the diffusion coefficient depends on the degree of saturation, which makes it difficult to use the model for predictions. In this study, the influence of preferential flow on pressure propagation and slope stability is investigated with a 1D dual-permeability model coupled with an infinite-slope stability approach. The dual-permeability model uses two modified Darcy-Richards equations to simultaneously simulate the matrix flow and preferential flow in hillslopes. The simulated pressure head is used in an infinite-slope stability analysis to identify the influence of preferential flow on the fast pressure response and landslide triggering. The dual-permeability model simulates the height and arrival of the pressure peak reasonably well. Performance of the dual-permeability model is as good as or better than the linear-diffusion model even though the dual-permeability model is calibrated for two single pulse rain events only, while the linear-diffusion model is calibrated for each rain event separately.

The exit-time problem for a Markov jump process

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

Burch, N.; D'Elia, Marta; Lehoucq, Richard B.

2014-12-15

The purpose of our paper is to consider the exit-time problem for a finite-range Markov jump process, i.e, the distance the particle can jump is bounded independent of its location. Such jump diffusions are expedient models for anomalous transport exhibiting super-diffusion or nonstandard normal diffusion. We refer to the associated deterministic equation as a volume-constrained nonlocal diffusion equation. The volume constraint is the nonlocal analogue of a boundary condition necessary to demonstrate that the nonlocal diffusion equation is well-posed and is consistent with the jump process. A critical aspect of the analysis is a variational formulation and a recently developedmore » nonlocal vector calculus. Furthermore, this calculus allows us to pose nonlocal backward and forward Kolmogorov equations, the former equation granting the various moments of the exit-time distribution.« less

Renormalization group analysis of anisotropic diffusion in turbulent shear flows

NASA Technical Reports Server (NTRS)

Rubinstein, Robert; Barton, J. Michael

1991-01-01

The renormalization group is applied to compute anisotropic corrections to the scalar eddy diffusivity representation of turbulent diffusion of a passive scalar. The corrections are linear in the mean velocity gradients. All model constants are computed theoretically. A form of the theory valid at arbitrary Reynolds number is derived. The theory applies only when convection of the velocity-scalar correlation can be neglected. A ratio of diffusivity components, found experimentally to have a nearly constant value in a variety of shear flows, is computed theoretically for flows in a certain state of equilibrium. The theoretical value is well within the fairly narrow range of experimentally observed values. Theoretical predictions of this diffusivity ratio are also compared with data from experiments and direct numerical simulations of homogeneous shear flows with constant velocity and scalar gradients.

Asymptotic neutron scattering laws for anomalously diffusing quantum particles

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

Kneller, Gerald R.; Université d’Orléans, Chateau de la Source-Ave. du Parc Floral, 45067 Orléans; Synchrotron-SOLEIL, L’Orme de Merisiers, 91192 Gif-sur-Yvette

2016-07-28

The paper deals with a model-free approach to the analysis of quasielastic neutron scattering intensities from anomalously diffusing quantum particles. All quantities are inferred from the asymptotic form of their time-dependent mean square displacements which grow ∝t{sup α}, with 0 ≤ α < 2. Confined diffusion (α = 0) is here explicitly included. We discuss in particular the intermediate scattering function for long times and the Fourier spectrum of the velocity autocorrelation function for small frequencies. Quantum effects enter in both cases through the general symmetry properties of quantum time correlation functions. It is shown that the fractional diffusion constantmore » can be expressed by a Green-Kubo type relation involving the real part of the velocity autocorrelation function. The theory is exact in the diffusive regime and at moderate momentum transfers.« less

Noise and diffusion of a vibrated self-propelled granular particle

NASA Astrophysics Data System (ADS)

Walsh, Lee; Wagner, Caleb G.; Schlossberg, Sarah; Olson, Christopher; Baskaran, Aparna; Menon, Narayanan

Granular materials are an important physical realization of active matter. In vibration-fluidized granular matter, both diffusion and self-propulsion derive from the same collisional forcing, unlike many other active systems where there is a clean separation between the origin of single-particle mobility and the coupling to noise. Here we present experimental studies of single-particle motion in a vibrated granular monolayer, along with theoretical analysis that compares grain motion at short and long time scales to the assumptions and predictions, respectively, of the active Brownian particle (ABP) model. The results demonstrate that despite the unique relation between noise and propulsion, granular media do show the generic features predicted by the ABP model and indicate that this is a valid framework to predict collective phenomena. Additionally, our scheme of analysis for validating the inputs and outputs of the model can be applied to other granular and non-granular systems.

Linear bubble plume model for hypolimnetic oxygenation: Full-scale validation and sensitivity analysis

NASA Astrophysics Data System (ADS)

Singleton, V. L.; Gantzer, P.; Little, J. C.

2007-02-01

An existing linear bubble plume model was improved, and data collected from a full-scale diffuser installed in Spring Hollow Reservoir, Virginia, were used to validate the model. The depth of maximum plume rise was simulated well for two of the three diffuser tests. Temperature predictions deviated from measured profiles near the maximum plume rise height, but predicted dissolved oxygen profiles compared very well with observations. A sensitivity analysis was performed. The gas flow rate had the greatest effect on predicted plume rise height and induced water flow rate, both of which were directly proportional to gas flow rate. Oxygen transfer within the hypolimnion was independent of all parameters except initial bubble radius and was inversely proportional for radii greater than approximately 1 mm. The results of this work suggest that plume dynamics and oxygen transfer can successfully be predicted for linear bubble plumes using the discrete-bubble approach.

Investigation of heat and mass transfer under the influence of variable diffusion coefficient and thermal conductivity

NASA Astrophysics Data System (ADS)

Mohyud Din, S. T.; Zubair, T.; Usman, M.; Hamid, M.; Rafiq, M.; Mohsin, S.

2018-04-01

This study is devoted to analyze the influence of variable diffusion coefficient and variable thermal conductivity on heat and mass transfer in Casson fluid flow. The behavior of concentration and temperature profiles in the presence of Joule heating and viscous dissipation is also studied. The dimensionless conversation laws with suitable BCs are solved via Modified Gegenbauer Wavelets Method (MGWM). It has been observed that increase in Casson fluid parameter (β ) and parameter ɛ enhances the Nusselt number. Moreover, Nusselt number of Newtonian fluid is less than that of the Casson fluid. The phenomenon of mass transport can be increased by solute of variable diffusion coefficient rather than solute of constant diffusion coefficient. A detailed analysis of results is appropriately highlighted. The obtained results, error estimates, and convergence analysis reconfirm the credibility of proposed algorithm. It is concluded that MGWM is an appropriate tool to tackle nonlinear physical models and hence may be extended to some other nonlinear problems of diversified physical nature also.

Comparison of Diffusion MRI Acquisition Protocols for the In Vivo Characterization of the Mouse Spinal Cord: Variability Analysis and Application to an Amyotrophic Lateral Sclerosis Model

PubMed Central

Marcuzzo, Stefania; Bonanno, Silvia; Padelli, Francesco; Moreno-Manzano, Victoria; García-Verdugo, José Manuel; Bernasconi, Pia; Mantegazza, Renato; Bruzzone, Maria Grazia; Zucca, Ileana

2016-01-01

Diffusion-weighted Magnetic Resonance Imaging (dMRI) has relevant applications in the microstructural characterization of the spinal cord, especially in neurodegenerative diseases. Animal models have a pivotal role in the study of such diseases; however, in vivo spinal dMRI of small animals entails additional challenges that require a systematical investigation of acquisition parameters. The purpose of this study is to compare three acquisition protocols and identify the scanning parameters allowing a robust estimation of the main diffusion quantities and a good sensitivity to neurodegeneration in the mouse spinal cord. For all the protocols, the signal-to-noise and contrast-to noise ratios and the mean value and variability of Diffusion Tensor metrics were evaluated in healthy controls. For the estimation of fractional anisotropy less variability was provided by protocols with more diffusion directions, for the estimation of mean, axial and radial diffusivity by protocols with fewer diffusion directions and higher diffusion weighting. Intermediate features (12 directions, b = 1200 s/mm2) provided the overall minimum inter- and intra-subject variability in most cases. In order to test the diagnostic sensitivity of the protocols, 7 G93A-SOD1 mice (model of amyotrophic lateral sclerosis) at 10 and 17 weeks of age were scanned and the derived diffusion parameters compared with those estimated in age-matched healthy animals. The protocols with an intermediate or high number of diffusion directions provided the best differentiation between the two groups at week 17, whereas only few local significant differences were highlighted at week 10. According to our results, a dMRI protocol with an intermediate number of diffusion gradient directions and a relatively high diffusion weighting is optimal for spinal cord imaging. Further work is needed to confirm these results and for a finer tuning of acquisition parameters. Nevertheless, our findings could be important for the optimization of acquisition protocols for preclinical and clinical dMRI studies on the spinal cord. PMID:27560686

k-space image correlation to probe the intracellular dynamics of gold nanoparticles

NASA Astrophysics Data System (ADS)

Bouzin, M.; Sironi, L.; Chirico, G.; D'Alfonso, L.; Inverso, D.; Pallavicini, P.; Collini, M.

2016-04-01

The collective action of dynein, kinesin and myosin molecular motors is responsible for the intracellular active transport of cargoes, vesicles and organelles along the semi-flexible oriented filaments of the cytoskeleton. The overall mobility of the cargoes upon binding and unbinding to motor proteins can be modeled as an intermittency between Brownian diffusion in the cell cytoplasm and active ballistic excursions along actin filaments or microtubules. Such an intermittent intracellular active transport, exhibited by star-shaped gold nanoparticles (GNSs, Gold Nanostars) upon internalization in HeLa cancer cells, is investigated here by combining live-cell time-lapse confocal reflectance microscopy and the spatio-temporal correlation, in the reciprocal Fourier space, of the acquired image sequences. At first, the analytical theoretical framework for the investigation of a two-state intermittent dynamics is presented for Fourier-space Image Correlation Spectroscopy (kICS). Then simulated kICS correlation functions are employed to evaluate the influence of, and sensitivity to, all the kinetic and dynamic parameters the model involves (the transition rates between the diffusive and the active transport states, the diffusion coefficient and drift velocity of the imaged particles). The optimal procedure for the analysis of the experimental data is outlined and finally exploited to derive whole-cell maps for the parameters underlying the GNSs super-diffusive dynamics. Applied here to the GNSs subcellular trafficking, the proposed kICS analysis can be adopted for the characterization of the intracellular (super-) diffusive dynamics of any fluorescent or scattering biological macromolecule.

Protein gradients in single cells induced by their coupling to "morphogen"-like diffusion

NASA Astrophysics Data System (ADS)

Nandi, Saroj Kumar; Safran, Sam A.

2018-05-01

One of the many ways cells transmit information within their volume is through steady spatial gradients of different proteins. However, the mechanism through which proteins without any sources or sinks form such single-cell gradients is not yet fully understood. One of the models for such gradient formation, based on differential diffusion, is limited to proteins with large ratios of their diffusion constants or to specific protein-large molecule interactions. We introduce a novel mechanism for gradient formation via the coupling of the proteins within a single cell with a molecule, that we call a "pronogen," whose action is similar to that of morphogens in multi-cell assemblies; the pronogen is produced with a fixed flux at one side of the cell. This coupling results in an effectively non-linear diffusion degradation model for the pronogen dynamics within the cell, which leads to a steady-state gradient of the protein concentration. We use stability analysis to show that these gradients are linearly stable with respect to perturbations.

The effect of atmospheric sulfate reductions on diffuse radiation and photosynthesis in the United States during 1995-2013

NASA Astrophysics Data System (ADS)

Keppel-Aleks, G.; Washenfelder, R. A.

2016-09-01

Aerosol optical depth (AOD) has been shown to influence the global carbon sink by increasing the fraction of diffuse light, which increases photosynthesis over a greater fraction of the vegetated canopy. Between 1995 and 2013, U.S. SO2 emissions declined by over 70%, coinciding with observed AOD reductions of 3.0 ± 0.6% yr-1 over the eastern U.S. In the Community Earth System Model (CESM), these trends cause diffuse light to decrease regionally by almost 0.6% yr-1, leading to declines in gross primary production (GPP) of 0.07% yr-1. Integrated over the analysis period and domain, this represents 0.5 Pg C of omitted GPP. A separate upscaling calculation that used published relationships between GPP and diffuse light agreed with the CESM model results within 20%. The agreement between simulated and data-constrained upscaling results strongly suggests that anthropogenic sulfate trends have a small impact on carbon uptake in temperate forests due to scattered light.

Flow field investigation in a bulb turbine diffuser

NASA Astrophysics Data System (ADS)

Pereira, M.; Duquesne, P.; Aeschlimann, V.; Deschênes, C.

2017-04-01

An important drop in turbine performances has been measured in a bulb turbine model operated at overload. Previous investigations have correlated the performance drop with diffuser losses, and particularly to the flow separation zone at the diffuser wall. The flow has been investigated in the transition part of the diffuser using two LDV measurement sections. The transition part is a diffuser section that transforms from a circular to a rectangular section. The two measurement sections are at the inlet and outlet of the diffuser transition part. The turbine has been operated at three operating points, which are representative of different flow patterns at the diffuser exit at overload. In addition to the average velocity field, the analysis is conducted based on a backflow occurrence function and on the swirl level. Results reveal a counter-rotating zone in the diffuser, which intensifies with the guide vanes opening. The guide vanes opening induces a modification of the flow phenomena: from a central backflow recirculation zone at the lowest flowrate to a backflow zone induced by flow separation at the wall at the highest flowrate.

Electrochemical Ionization and Analyte Charging in the Array of Micromachined UltraSonic Electrospray (AMUSE) Ion Source

PubMed Central

Forbes, Thomas P.; Degertekin, F. Levent; Fedorov, Andrei G.

2010-01-01

Electrochemistry and ion transport in a planar array of mechanically-driven, droplet-based ion sources are investigated using an approximate time scale analysis and in-depth computational simulations. The ion source is modeled as a controlled-current electrolytic cell, in which the piezoelectric transducer electrode, which mechanically drives the charged droplet generation using ultrasonic atomization, also acts as the oxidizing/corroding anode (positive mode). The interplay between advective and diffusive ion transport of electrochemically generated ions is analyzed as a function of the transducer duty cycle and electrode location. A time scale analysis of the relative importance of advective vs. diffusive ion transport provides valuable insight into optimality, from the ionization prospective, of alternative design and operation modes of the ion source operation. A computational model based on the solution of time-averaged, quasi-steady advection-diffusion equations for electroactive species transport is used to substantiate the conclusions of the time scale analysis. The results show that electrochemical ion generation at the piezoelectric transducer electrodes located at the back-side of the ion source reservoir results in poor ionization efficiency due to insufficient time for the charged analyte to diffuse away from the electrode surface to the ejection location, especially at near 100% duty cycle operation. Reducing the duty cycle of droplet/analyte ejection increases the analyte residence time and, in turn, improves ionization efficiency, but at an expense of the reduced device throughput. For applications where this is undesirable, i.e., multiplexed and disposable device configurations, an alternative electrode location is incorporated. By moving the charging electrode to the nozzle surface, the diffusion length scale is greatly reduced, drastically improving ionization efficiency. The ionization efficiency of all operating conditions considered is expressed as a function of the dimensionless Peclet number, which defines the relative effect of advection as compared to diffusion. This analysis is general enough to elucidate an important role of electrochemistry in ionization efficiency of any arrayed ion sources, be they mechanically-driven or electrosprays, and is vital for determining optimal design and operation conditions. PMID:20607111

Effects of radial diffuser hydraulic design on a double-suction centrifugal pump

NASA Astrophysics Data System (ADS)

Hou, H. C.; Zhang, Y. X.; Xu, C.; Zhang, J. Y.; Li, Z. L.

2016-05-01

In order to study effects of radial diffuser on hydraulic performance of crude oil pump, the steady CFD numerical method is applied and one large double-suction oil pump running in long-distance pipeline is considered. The research focuses on analysing the influence of its diffuser vane profile on hydraulic performance of oil pump. The four different types of cylindrical vane have been designed by in-house codes mainly including double arcs (DA), triple arcs (TA), equiangular spiral line (ES) and linear variable angle spiral line (LVS). During design process diffuser vane angles at inlet and outlet are tentatively given within a certain range and then the wrapping angle of the four types of diffuser vanes can be calculated automatically. Under the given inlet and outlet angles, the linear variable angle spiral line profile has the biggest wrapping angle and profile length which is good to delay channel diffusion but bring more friction hydraulic loss. Finally the vane camber line is thickened at the certain uniform thickness distribution and the 3D diffuser models are generated. The whole flow passage of oil pump with different types of diffusers under various flow rate conditions are numerically simulated based on RNG k-ɛ turbulent model and SIMPLEC algorithm. The numerical results show that different types of diffusers can bring about great difference on the hydraulic performance of oil pump, of which the ES profile diffuser with its proper setting angle shows the best hydraulic performance and its inner flow field is improved obviously. Compared with the head data from model sample, all designed diffusers can make a certain improvement on head characteristic. At the large flow rate conditions the hydraulic efficiency increases obviously and the best efficiency point shift to the large flow rate range. The ES profile diffuser embodies the better advantages on pump performance which can be explained theoretically that the diffuser actually acts as a diffusion device and is good to transform the dynamic energy to pressure energy. Then through the hydraulic loss analysis of each pump component for all diffusers, it shows that the impeller takes up the biggest part of the whole loss about 8.19% averagely, the radial diffuser about 3.70% and the volute about 1.65%. The hydraulic loss of impeller is dominant at the large flow rate while the radial diffuser is at the small flow rate. Among all diffusers, the ES profile diffuser generates the least loss and combined to the distribution of velocity vector and turbulent kinetic energy for two kinds of diffusers it also shows that ES profile is fit to apply in radial diffuser. This research can offer a significant reference for the radial diffuser hydraulic design of such centrifugal pumps.

A model for oscillations and pattern formation in protoplasmic droplets of Physarum polycephalum

NASA Astrophysics Data System (ADS)

Radszuweit, M.; Engel, H.; Bär, M.

2010-12-01

A mechano-chemical model for the spatiotemporal dynamics of free calcium and the thickness in protoplasmic droplets of the true slime mold Physarum polycephalum is derived starting from a physiologically detailed description of intracellular calcium oscillations proposed by Smith and Saldana (Biopys. J. 61, 368 (1992)). First, we have modified the Smith-Saldana model for the temporal calcium dynamics in order to reproduce the experimentally observed phase relation between calcium and mechanical tension oscillations. Then, we formulate a model for spatiotemporal dynamics by adding spatial coupling in the form of calcium diffusion and advection due to calcium-dependent mechanical contraction. In another step, the resulting reaction-diffusion model with mechanical coupling is simplified to a reaction-diffusion model with global coupling that approximates the mechanical part. We perform a bifurcation analysis of the local dynamics and observe a Hopf bifurcation upon increase of a biochemical activity parameter. The corresponding reaction-diffusion model with global coupling shows regular and chaotic spatiotemporal behaviour for parameters with oscillatory dynamics. In addition, we show that the global coupling leads to a long-wavelength instability even for parameters where the local dynamics possesses a stable spatially homogeneous steady state. This instability causes standing waves with a wavelength of twice the system size in one dimension. Simulations of the model in two dimensions are found to exhibit defect-mediated turbulence as well as various types of spiral wave patterns in qualitative agreement with earlier experimental observation by Takagi and Ueda (Physica D, 237, 420 (2008)).

Growth Mechanism Studies of ZnO Nanowires: Experimental Observations and Short-Circuit Diffusion Analysis

PubMed Central

Shih, Po-Hsun

2017-01-01

Plenty of studies have been performed to probe the diverse properties of ZnO nanowires, but only a few have focused on the physical properties of a single nanowire since analyzing the growth mechanism along a single nanowire is difficult. In this study, a single ZnO nanowire was synthesized using a Ti-assisted chemical vapor deposition (CVD) method to avoid the appearance of catalytic contamination. Two-dimensional energy dispersive spectroscopy (EDS) mapping with a diffusion model was used to obtain the diffusion length and the activation energy ratio. The ratio value is close to 0.3, revealing that the growth of ZnO nanowires was attributed to the short-circuit diffusion. PMID:28754030

Method for measurement of radon diffusion and solubility in solid materials

NASA Astrophysics Data System (ADS)

Maier, Andreas; Weber, Uli; Dickmann, Jannis; Breckow, Joachim; van Beek, Patrick; Schardt, Dieter; Kraft, Gerhard; Fournier, Claudia

2018-02-01

In order to study the permeation i.e. the diffusion and solubility of radon gas in biological material, a new setup was constructed and a novel analysis was applied to obtain diffusion and solubility coefficients. Thin slabs of solid materials were installed between detector housing and the surrounding radon exposure chamber of 50 Ls volume. In this setup radon can diffuse through thin test samples into a cylindrical volume of 5 mm height and 20 mm diameter and reach an α-particle detector. There the 5.49 MeV α-decay of the penetrating radon atoms is measured by a silicon surface barrier detector. The time dependent activities inside the small detector volume are recorded after injection of a known radon activity concentration into the outer chamber. Analyzing the time behavior of the integral α-activity from radon in the small vessel, both, the diffusion coefficient and solubility of the test material can be determined, based on a new mathematical model of the diffusion process concerning the special boundary conditions given by the experimental setup. These first measurements were intended as proof of concept for the detection system and the data analysis. Thin polyethylene foils (LDPE) were selected as material for the diffusion measurements and the results were in agreement with data from literature. In further measurements, we will concentrate on biological material like bone, fat and other tissues.

Analysis and correction of gradient nonlinearity bias in ADC measurements

PubMed Central

Malyarenko, Dariya I.; Ross, Brian D.; Chenevert, Thomas L.

2013-01-01

Purpose Gradient nonlinearity of MRI systems leads to spatially-dependent b-values and consequently high non-uniformity errors (10–20%) in ADC measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. Methods All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Results Spatial dependence of nonlinearity correction terms accounts for the bulk (75–95%) of ADC bias for FA = 0.3–0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. Conclusions The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. PMID:23794533

An improved strip FRAP method for estimating diffusion coefficients: correcting for the degree of photobleaching.

PubMed

Yang, J; Köhler, K; Davis, D M; Burroughs, N J

2010-06-01

Fluorescence recovery after photobleaching is a widely established method for the estimation of diffusion coefficients, strip bleaching with an associated recovery curve analysis being one of the simplest techniques. However, its implementation requires near 100% bleaching in the region of interest with negligible fluorescence loss outside, both constraints being hard to achieve concomitantly for fast diffusing molecules. We demonstrate that when these requirements are not met there is an error in the estimation of the diffusion coefficient D, either an under- or overestimation depending on which assumption is violated the most. We propose a simple modification to the recovery curve analysis incorporating the concept of the relative bleached mass m giving a revised recovery time parametrization tau=m(2)w(2)/4piD for a strip of width w. This modified model removes the requirement of 100% bleaching in the region of interest and allows for limited diffusion of the fluorophore during bleaching. We validate our method by estimating the (volume) diffusion coefficient of FITC-labelled IgG in 60% glycerol solution, D= 4.09 +/- 0.21 microm(2) s(-1), and the (surface) diffusion coefficient of a green-fluorescent protein-tagged class I MHC protein expressed at the surface of a human B cell line, D= 0.32 +/- 0.03 microm(2) s(-1) for a population of cells.

Measurement of diffusion coefficients of VOCs for building materials: review and development of a calculation procedure.

PubMed

Haghighat, F; Lee, C S; Ghaly, W S

2002-06-01

The measurement and prediction of building material emission rates have been the subject of intensive research over the past decade, resulting in the development of advanced sensory and chemical analysis measurement techniques as well as the development of analytical and numerical models. One of the important input parameters for these models is the diffusion coefficient. Several experimental techniques have been applied to estimate the diffusion coefficient. An extensive literature review of the techniques used to measure this coefficient was carried out, for building materials exposed to volatile organic compounds (VOC). This paper reviews these techniques; it also analyses the results and discusses the possible causes of difference in the reported data. It was noted that the discrepancy between the different results was mainly because of the assumptions made in and the techniques used to analyze the data. For a given technique, the results show that there can be a difference of up to 700% in the reported data. Moreover, the paper proposes what is referred to as the mass exchanger method, to calculate diffusion coefficients considering both diffusion and convection. The results obtained by this mass exchanger method were compared with those obtained by the existing method considering only diffusion. It was demonstrated that, for porous materials, the convection resistance could not be ignored when compared with the diffusion resistance.

Understanding Diffusion in Hierarchical Zeolites with House-of-Cards Nanosheets.

PubMed

Bai, Peng; Haldoupis, Emmanuel; Dauenhauer, Paul J; Tsapatsis, Michael; Siepmann, J Ilja

2016-08-23

Introducing mesoporosity to conventional microporous sorbents or catalysts is often proposed as a solution to enhance their mass transport rates. Here, we show that diffusion in these hierarchical materials is more complex and exhibits non-monotonic dependence on sorbate loading. Our atomistic simulations of n-hexane in a model system containing microporous nanosheets and mesopore channels indicate that diffusivity can be smaller than in a conventional zeolite with the same micropore structure, and this observation holds true even if we confine the analysis to molecules completely inside the microporous nanosheets. Only at high sorbate loadings or elevated temperatures, when the mesopores begin to be sufficiently populated, does the overall diffusion in the hierarchical material exceed that in conventional microporous zeolites. Our model system is free of structural defects, such as pore blocking or surface disorder, that are typically invoked to explain slower-than-expected diffusion phenomena in experimental measurements. Examination of free energy profiles and visualization of molecular diffusion pathways demonstrates that the large free energy cost (mostly enthalpic in origin) for escaping from the microporous region into the mesopores leads to more tortuous diffusion paths and causes this unusual transport behavior in hierarchical nanoporous materials. This knowledge allows us to re-examine zero-length-column chromatography data and show that these experimental measurements are consistent with the simulation data when the crystallite size instead of the nanosheet thickness is used for the nominal diffusional length.

Epidemic modeling in complex realities.

PubMed

Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro

2007-04-01

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

Detection of Diffusion Heterogeneity in Single Particle Tracking Trajectories Using a Hidden Markov Model with Measurement Noise Propagation

PubMed Central

Slator, Paddy J.; Cairo, Christopher W.; Burroughs, Nigel J.

2015-01-01

We develop a Bayesian analysis framework to detect heterogeneity in the diffusive behaviour of single particle trajectories on cells, implementing model selection to classify trajectories as either consistent with Brownian motion or with a two-state (diffusion coefficient) switching model. The incorporation of localisation accuracy is essential, as otherwise false detection of switching within a trajectory was observed and diffusion coefficient estimates were inflated. Since our analysis is on a single trajectory basis, we are able to examine heterogeneity between trajectories in a quantitative manner. Applying our method to the lymphocyte function-associated antigen 1 (LFA-1) receptor tagged with latex beads (4 s trajectories at 1000 frames s−1), both intra- and inter-trajectory heterogeneity were detected; 12–26% of trajectories display clear switching between diffusive states dependent on condition, whilst the inter-trajectory variability is highly structured with the diffusion coefficients being related by D 1 = 0.68D 0 − 1.5 × 104 nm2 s−1, suggestive that on these time scales we are detecting switching due to a single process. Further, the inter-trajectory variability of the diffusion coefficient estimates (1.6 × 102 − 2.6 × 105 nm2 s−1) is very much larger than the measurement uncertainty within trajectories, suggesting that LFA-1 aggregation and cytoskeletal interactions are significantly affecting mobility, whilst the timescales of these processes are distinctly different giving rise to inter- and intra-trajectory variability. There is also an ‘immobile’ state (defined as D < 3.0 × 103 nm2 s−1) that is rarely involved in switching, immobility occurring with the highest frequency (47%) under T cell activation (phorbol-12-myristate-13-acetate (PMA) treatment) with enhanced cytoskeletal attachment (calpain inhibition). Such ‘immobile’ states frequently display slow linear drift, potentially reflecting binding to a dynamic actin cortex. Our methods allow significantly more information to be extracted from individual trajectories (ultimately limited by time resolution and time-series length), and allow statistical comparisons between trajectories thereby quantifying inter-trajectory heterogeneity. Such methods will be highly informative for the construction and fitting of molecule mobility models within membranes incorporating aggregation, binding to the cytoskeleton, or traversing membrane microdomains. PMID:26473352

Diffusion models for innovation: s-curves, networks, power laws, catastrophes, and entropy.

PubMed

Jacobsen, Joseph J; Guastello, Stephen J

2011-04-01

This article considers models for the diffusion of innovation would be most relevant to the dynamics of early 21st century technologies. The article presents an overview of diffusion models and examines the adoption S-curve, network theories, difference models, influence models, geographical models, a cusp catastrophe model, and self-organizing dynamics that emanate from principles of network configuration and principles of heat diffusion. The diffusion dynamics that are relevant to information technologies and energy-efficient technologies are compared. Finally, principles of nonlinear dynamics for innovation diffusion that could be used to rehabilitate the global economic situation are discussed.

On Large Time Behavior and Selection Principle for a Diffusive Carr-Penrose Model

NASA Astrophysics Data System (ADS)

Conlon, Joseph G.; Dabkowski, Michael; Wu, Jingchen

2016-04-01

This paper is concerned with the study of a diffusive perturbation of the linear LSW model introduced by Carr and Penrose. A main subject of interest is to understand how the presence of diffusion acts as a selection principle, which singles out a particular self-similar solution of the linear LSW model as determining the large time behavior of the diffusive model. A selection principle is rigorously proven for a model which is a semiclassical approximation to the diffusive model. Upper bounds on the rate of coarsening are also obtained for the full diffusive model.

Modeling of acetone biofiltration process

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

Hsiu-Mu Tang; Shyh-Jye Hwang; Wen-Chuan Wang

1996-12-31

The objective of this research was to investigate the kinetic behavior of the biofiltration process for the removal of acetone 41 which was used as a model compound for highly water soluble gas pollutants. A mathematical model was developed by taking into account diffusion and biodegradation of acetone and oxygen in the biofilm, mass transfer resistance in the gas film, and flow pattern of the bulk gas phase. The simulated results obtained by the proposed model indicated that mass transfer resistance in the gas phase was negligible for this biofiltration process. Analysis of the relative importance of various rate stepsmore » indicated that the overall acetone removal process was primarily limited by the oxygen diffusion rate. 11 refs., 6 figs., 1 tab.« less

Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI.

PubMed

Zhang, Guangwen; Wang, Shuangshuang; Wen, Didi; Zhang, Jing; Wei, Xiaocheng; Ma, Wanling; Zhao, Weiwei; Wang, Mian; Wu, Guosheng; Zhang, Jinsong

2016-12-09

Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal cancer, and to determine the optimal model for investigating the water diffusion properties and characterization of rectal carcinoma. Fifty-nine consecutive patients with pathologically confirmed rectal adenocarcinoma underwent DWI with 16 b-values at a 3.0 T MRI system. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models (IVIM-mono, IVIM-bi and SEM) on primary tumor and adjacent normal rectal tissue. Parameters of standard apparent diffusion coefficient (ADC), slow- and fast-ADC, fraction of fast ADC (f), α value and distributed diffusion coefficient (DDC) were generated and compared between the tumor and normal tissues. The SEM exhibited the best fitting results of actual DWI signal in rectal cancer and the normal rectal wall (R 2  = 0.998, 0.999 respectively). The DDC achieved relatively high area under the curve (AUC = 0.980) in differentiating tumor from normal rectal wall. Non-Gaussian diffusion models could assess tissue properties more accurately than the ADC derived Gaussian diffusion model. SEM may be used as a potential optimal model for characterization of rectal cancer.

CONTRIBUTIONS OF CHEMICAL AND DIFFUSIVE EXCHANGE TO T1ρ DISPERSION

PubMed Central

Cobb, Jared Guthrie; Xie, Jingping; Gore, John C.

2012-01-01

Variations in local magnetic susceptibility may induce magnetic field gradients that affect the signals acquired for MR imaging. Under appropriate diffusion conditions, such fields produce effects similar to slow chemical exchange. These effects may also be found in combination with other chemical exchange processes at multiple time scales. We investigate these effects with simulations and measurements to determine their contributions to rotating frame (R1ρ) relaxation in model systems. Simulations of diffusive and chemical exchange effects on R1ρ dispersion were performed using the Bloch equations. Additionally, R1ρ dispersion was measured in suspensions of Sephadex and latex beads with varying spin locking fields at 9.4T. A novel analysis method was used to iteratively fit for apparent chemical and diffusive exchange rates with a model by Chopra et al. Single- and double-inflection points in R1ρ dispersion profiles were observed, respectively, in simulations of slow diffusive exchange alone and when combined with rapid chemical exchange. These simulations were consistent with measurements of R1ρ in latex bead suspensions and small-diameter Sephadex beads that showed single- and double-inflection points, respectively. These observations, along with measurements following changes in temperature and pH, are consistent with the combined effects of slow diffusion and rapid −OH exchange processes. PMID:22791589

A priori analysis of differential diffusion for model development for scale-resolving simulations

NASA Astrophysics Data System (ADS)

Hunger, Franziska; Dietzsch, Felix; Gauding, Michael; Hasse, Christian

2018-01-01

The present study analyzes differential diffusion and the mechanisms responsible for it with regard to the turbulent/nonturbulent interface (TNTI) with special focus on model development for scale-resolving simulations. In order to analyze differences between resolved and subfilter phenomena, direct numerical simulation (DNS) data are compared with explicitly filtered data. The DNS database stems from a temporally evolving turbulent plane jet transporting two passive scalars with Schmidt numbers of unity and 0.25 presented by Hunger et al. [F. Hunger et al., J. Fluid Mech. 802, R5 (2016), 10.1017/jfm.2016.471]. The objective of this research is twofold: (i) to compare the position of the turbulent-nonturbulent interface between the original DNS data and the filtered data and (ii) to analyze differential diffusion and the impact of the TNTI with regard to scale resolution in the filtered DNS data. For the latter, differential diffusion quantities are studied, clearly showing the decrease of differential diffusion at the resolved scales with increasing filter width. A transport equation for the scalar differences is evaluated. Finally, the existence of large scalar gradients, gradient alignment, and the diffusive fluxes being the physical mechanisms responsible for the separation of the two scalars are compared between the resolved and subfilter scales.

Markov Chain Monte Carlo in the Analysis of Single-Molecule Experimental Data

NASA Astrophysics Data System (ADS)

Kou, S. C.; Xie, X. Sunney; Liu, Jun S.

2003-11-01

This article provides a Bayesian analysis of the single-molecule fluorescence lifetime experiment designed to probe the conformational dynamics of a single DNA hairpin molecule. The DNA hairpin's conformational change is initially modeled as a two-state Markov chain, which is not observable and has to be indirectly inferred. The Brownian diffusion of the single molecule, in addition to the hidden Markov structure, further complicates the matter. We show that the analytical form of the likelihood function can be obtained in the simplest case and a Metropolis-Hastings algorithm can be designed to sample from the posterior distribution of the parameters of interest and to compute desired estiamtes. To cope with the molecular diffusion process and the potentially oscillating energy barrier between the two states of the DNA hairpin, we introduce a data augmentation technique to handle both the Brownian diffusion and the hidden Ornstein-Uhlenbeck process associated with the fluctuating energy barrier, and design a more sophisticated Metropolis-type algorithm. Our method not only increases the estimating resolution by several folds but also proves to be successful for model discrimination.

Re-evaluation of model-based light-scattering spectroscopy for tissue spectroscopy

PubMed Central

Lau, Condon; Šćepanović, Obrad; Mirkovic, Jelena; McGee, Sasha; Yu, Chung-Chieh; Fulghum, Stephen; Wallace, Michael; Tunnell, James; Bechtel, Kate; Feld, Michael

2009-01-01

Model-based light scattering spectroscopy (LSS) seemed a promising technique for in-vivo diagnosis of dysplasia in multiple organs. In the studies, the residual spectrum, the difference between the observed and modeled diffuse reflectance spectra, was attributed to single elastic light scattering from epithelial nuclei, and diagnostic information due to nuclear changes was extracted from it. We show that this picture is incorrect. The actual single scattering signal arising from epithelial nuclei is much smaller than the previously computed residual spectrum, and does not have the wavelength dependence characteristic of Mie scattering. Rather, the residual spectrum largely arises from assuming a uniform hemoglobin distribution. In fact, hemoglobin is packaged in blood vessels, which alters the reflectance. When we include vessel packaging, which accounts for an inhomogeneous hemoglobin distribution, in the diffuse reflectance model, the reflectance is modeled more accurately, greatly reducing the amplitude of the residual spectrum. These findings are verified via numerical estimates based on light propagation and Mie theory, tissue phantom experiments, and analysis of published data measured from Barrett’s esophagus. In future studies, vessel packaging should be included in the model of diffuse reflectance and use of model-based LSS should be discontinued. PMID:19405760

Reducing uncertainty in Climate Response Time Scale by Bayesian Analysis of the 8.2 ka event

NASA Astrophysics Data System (ADS)

Lorenz, A.; Held, H.; Bauer, E.; Schneider von Deimling, T.

2009-04-01

We analyze the possibility of uncertainty reduction in Climate Response Time Scale by utilizing Greenland ice-core data that contain the 8.2 ka event within a Bayesian model-data intercomparison with the Earth system model of intermediate complexity, CLIMBER-2.3. Within a stochastic version of the model it has been possible to mimic the 8.2 ka event within a plausible experimental setting and with relatively good accuracy considering the timing of the event in comparison to other modeling exercises [1]. The simulation of the centennial cold event is effectively determined by the oceanic cooling rate which depends largely on the ocean diffusivity described by diffusion coefficients of relatively wide uncertainty ranges. The idea now is to discriminate between the different values of diffusivities according to their likelihood to rightly represent the duration of the 8.2 ka event and thus to exploit the paleo data to constrain uncertainty in model parameters in analogue to [2]. Implementing this inverse Bayesian Analysis with this model the technical difficulty arises to establish the related likelihood numerically in addition to the uncertain model parameters: While mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study [3] the Bayesian Analysis showed a reduction of uncertainty in vertical ocean diffusivity parameters of factor 2 compared to prior knowledge. This learning effect on the model parameters is propagated to other model outputs of interest; e.g. the inverse ocean heat capacity, which is important for the dominant time scale of climate response to anthropogenic forcing which, in combination with climate sensitivity, strongly influences the climate systems reaction for the near- and medium-term future. 1 References [1] E. Bauer, A. Ganopolski, M. Montoya: Simulation of the cold climate event 8200 years ago by meltwater outburst from lake Agassiz. Paleoceanography 19:PA3014, (2004) [2] T. Schneider von Deimling, H. Held, A. Ganopolski, S. Rahmstorf, Climate sensitivity estimated from ensemble simulations of glacial climates, Climate Dynamics 27, 149-163, DOI 10.1007/s00382-006-0126-8 (2006). [3] A. Lorenz, Diploma Thesis, U Potsdam (2007).

Long-Term Functional Outcomes and Correlation with Regional Brain Connectivity by MRI Diffusion Tractography Metrics in a Near-Term Rabbit Model of Intrauterine Growth Restriction

PubMed Central

Illa, Miriam; Eixarch, Elisenda; Batalle, Dafnis; Arbat-Plana, Ariadna; Muñoz-Moreno, Emma; Figueras, Francesc; Gratacos, Eduard

2013-01-01

Background Intrauterine growth restriction (IUGR) affects 5–10% of all newborns and is associated with increased risk of memory, attention and anxiety problems in late childhood and adolescence. The neurostructural correlates of long-term abnormal neurodevelopment associated with IUGR are unknown. Thus, the aim of this study was to provide a comprehensive description of the long-term functional and neurostructural correlates of abnormal neurodevelopment associated with IUGR in a near-term rabbit model (delivered at 30 days of gestation) and evaluate the development of quantitative imaging biomarkers of abnormal neurodevelopment based on diffusion magnetic resonance imaging (MRI) parameters and connectivity. Methodology At +70 postnatal days, 10 cases and 11 controls were functionally evaluated with the Open Field Behavioral Test which evaluates anxiety and attention and the Object Recognition Task that evaluates short-term memory and attention. Subsequently, brains were collected, fixed and a high resolution MRI was performed. Differences in diffusion parameters were analyzed by means of voxel-based and connectivity analysis measuring the number of fibers reconstructed within anxiety, attention and short-term memory networks over the total fibers. Principal Findings The results of the neurobehavioral and cognitive assessment showed a significant higher degree of anxiety, attention and memory problems in cases compared to controls in most of the variables explored. Voxel-based analysis (VBA) revealed significant differences between groups in multiple brain regions mainly in grey matter structures, whereas connectivity analysis demonstrated lower ratios of fibers within the networks in cases, reaching the statistical significance only in the left hemisphere for both networks. Finally, VBA and connectivity results were also correlated with functional outcome. Conclusions The rabbit model used reproduced long-term functional impairments and their neurostructural correlates of abnormal neurodevelopment associated with IUGR. The description of the pattern of microstructural changes underlying functional defects may help to develop biomarkers based in diffusion MRI and connectivity analysis. PMID:24143189

Long-term functional outcomes and correlation with regional brain connectivity by MRI diffusion tractography metrics in a near-term rabbit model of intrauterine growth restriction.

PubMed

Illa, Miriam; Eixarch, Elisenda; Batalle, Dafnis; Arbat-Plana, Ariadna; Muñoz-Moreno, Emma; Figueras, Francesc; Gratacos, Eduard

2013-01-01

Intrauterine growth restriction (IUGR) affects 5-10% of all newborns and is associated with increased risk of memory, attention and anxiety problems in late childhood and adolescence. The neurostructural correlates of long-term abnormal neurodevelopment associated with IUGR are unknown. Thus, the aim of this study was to provide a comprehensive description of the long-term functional and neurostructural correlates of abnormal neurodevelopment associated with IUGR in a near-term rabbit model (delivered at 30 days of gestation) and evaluate the development of quantitative imaging biomarkers of abnormal neurodevelopment based on diffusion magnetic resonance imaging (MRI) parameters and connectivity. At +70 postnatal days, 10 cases and 11 controls were functionally evaluated with the Open Field Behavioral Test which evaluates anxiety and attention and the Object Recognition Task that evaluates short-term memory and attention. Subsequently, brains were collected, fixed and a high resolution MRI was performed. Differences in diffusion parameters were analyzed by means of voxel-based and connectivity analysis measuring the number of fibers reconstructed within anxiety, attention and short-term memory networks over the total fibers. The results of the neurobehavioral and cognitive assessment showed a significant higher degree of anxiety, attention and memory problems in cases compared to controls in most of the variables explored. Voxel-based analysis (VBA) revealed significant differences between groups in multiple brain regions mainly in grey matter structures, whereas connectivity analysis demonstrated lower ratios of fibers within the networks in cases, reaching the statistical significance only in the left hemisphere for both networks. Finally, VBA and connectivity results were also correlated with functional outcome. The rabbit model used reproduced long-term functional impairments and their neurostructural correlates of abnormal neurodevelopment associated with IUGR. The description of the pattern of microstructural changes underlying functional defects may help to develop biomarkers based in diffusion MRI and connectivity analysis.

On the effects of nonlinear boundary conditions in diffusive logistic equations on bounded domains

NASA Astrophysics Data System (ADS)

Cantrell, Robert Stephen; Cosner, Chris

We study a diffusive logistic equation with nonlinear boundary conditions. The equation arises as a model for a population that grows logistically inside a patch and crosses the patch boundary at a rate that depends on the population density. Specifically, the rate at which the population crosses the boundary is assumed to decrease as the density of the population increases. The model is motivated by empirical work on the Glanville fritillary butterfly. We derive local and global bifurcation results which show that the model can have multiple equilibria and in some parameter ranges can support Allee effects. The analysis leads to eigenvalue problems with nonstandard boundary conditions.

Study on the effect of Cd-diffusion annealing on the electrical properties of CdZnTe

NASA Astrophysics Data System (ADS)

Wanwan, Li; Zechun, Cao; Bin, Zhang; Feng, Zhan; Hongtao, Liu; Wenbin, Sang; Jiahua, Min; Kang, Sun

2006-06-01

In order to meet the requirements for the device design of radiation detectors, CdZnTe (or Cd 1-xZn xTe) crystals grown by Vertical Bridgman Method often need subsequent annealing to increase their resistivity. The nature of this treatment is a diffusion process. Thus, it is meaningful to relate the change of resistivity to the diffusion parameters. A model correlating resistivity and conduction type of CdZnTe with the main diffusion parameter—diffusion coefficient—is put forward in this paper. Combining the model with the analysis of our experimental data, DCd=1.464×10 -10, 1.085×10 -11 and 4.167×10 -13 cm 2/s are the values of Cd self-diffusion coefficient in Cd 0.9Zn 0.1Te at 1073, 973 and 873 K, respectively. The data coincide closely with the Cd self-diffusion coefficient in CdTe provided by different authors [E.D. Jones, N.M. Stewart, Self-diffusion of cadmium in cadmium telluride, J. Crystal Growth 84 (1987) 289-294; P.M. Borsenberger, D.A. Stevenson, J. Phys. Chem. Solids 29 (1968) 1277; R.C. Whelan, D. Shaw, in: D.G. Thomas (Ed.), II -VI Semiconductor Compounds, Benjamin, New York, 1967, p. 451]. With the data, the effects of annealing time on the change of resistivity and conduction type for Cd 0.9Zn 0.1Te wafers, which are annealed in saturated Cd vapor at 1073, 973 and 873 K, were simulated, and good consistency was found. This work suggests an alternative way to obtain the diffusion coefficient in semiconductor materials and also enables ones to analyze the diffusion process quantitatively and predict the annealing results.

Thermal analysis of a growing crystal in an aqueous solution

NASA Astrophysics Data System (ADS)

Shiomi, Yuji; Kuroda, Toshio; Ogawa, Tomoya

1980-10-01

The temperature profiles around growing crystals in aqueous solutions of Rochelle salt were measured with accuracy of 0.005°C in a two-dimensional cell which was used for elimination of thermal convection current in the cell. The temperature distribution became stationary after 2 h from injection of the mother liquid, but the concentration distribution did not become stationary because the diffusion constant of solute in the solution was much smaller than the thermal diffusivity of the solution. The growth rate was linearly proportional to the temperature gradient at every growing interface. Since crystal growth is a typical interaction process between thermal and material flow, the experimental results were analysed by such an interaction model. The analysis confirms that the material flow is limited by diffusion within a layer width of about a few hundreds micrometers on the growing interface.

The effects of esterified solvents on the diffusion of a model compound across human skin: an ATR-FTIR spectroscopic study.

PubMed

McAuley, W J; Chavda-Sitaram, S; Mader, K T; Tetteh, J; Lane, M E; Hadgraft, J

2013-04-15

Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been used to investigate the effects of three fatty acid esters on skin permeation. Propylene glycol diperlargonate (DPPG), isopropyl myristate (IPM) and isostearyl isostearate (ISIS) were selected as pharmaceutically relevant solvents with a range of lipophilicities and cyanophenol (CNP) was used as a model drug. The resultant data were compared with that obtained when water was used as the solvent. The diffusion of CNP, DPPG and IPM across epidermis was successfully described by a Fickian model. When ISIS was used as a solvent Fickian behaviour was only obtained across isolated stratum corneum suggesting that the hydrophilic layers of the epidermis interfere with the permeation of the hydrophobic ISIS. The diffusion coefficients of CNP across epidermis in the different solvents were not significantly different. Using chemometric data analysis diffusion profiles for the solvents were deconvoluted from that of the skin and modelled. Each of these solvents was found to diffuse at a faster rate across the skin than CNP. DPPG considerably increased the concentration of CNP in the stratum corneum in comparison with the other solvents indicating strong penetration enhancer potential. In contrast IPM produced a similar CNP concentration in the stratum corneum to water with ISIS resulting in a lower CNP concentration suggesting negligible enhancement and penetration retardation effects for these two solvents respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

A Simulation Tool for Dynamic Contrast Enhanced MRI

PubMed Central

Mauconduit, Franck; Christen, Thomas; Barbier, Emmanuel Luc

2013-01-01

The quantification of bolus-tracking MRI techniques remains challenging. The acquisition usually relies on one contrast and the analysis on a simplified model of the various phenomena that arise within a voxel, leading to inaccurate perfusion estimates. To evaluate how simplifications in the interstitial model impact perfusion estimates, we propose a numerical tool to simulate the MR signal provided by a dynamic contrast enhanced (DCE) MRI experiment. Our model encompasses the intrinsic and relaxations, the magnetic field perturbations induced by susceptibility interfaces (vessels and cells), the diffusion of the water protons, the blood flow, the permeability of the vessel wall to the the contrast agent (CA) and the constrained diffusion of the CA within the voxel. The blood compartment is modeled as a uniform compartment. The different blocks of the simulation are validated and compared to classical models. The impact of the CA diffusivity on the permeability and blood volume estimates is evaluated. Simulations demonstrate that the CA diffusivity slightly impacts the permeability estimates ( for classical blood flow and CA diffusion). The effect of long echo times is investigated. Simulations show that DCE-MRI performed with an echo time may already lead to significant underestimation of the blood volume (up to 30% lower for brain tumor permeability values). The potential and the versatility of the proposed implementation are evaluated by running the simulation with realistic vascular geometry obtained from two photons microscopy and with impermeable cells in the extravascular environment. In conclusion, the proposed simulation tool describes DCE-MRI experiments and may be used to evaluate and optimize acquisition and processing strategies. PMID:23516414

A diffusion-limited reaction model for self-propagating Al/Pt multilayers with quench limits

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

Kittell, David E.; Yarrington, Cole D.; Hobbs, M. L.

A diffusion-limited reaction model was calibrated for Al/Pt multilayers ignited on oxidized silicon, sapphire, and tungsten substrates, as well as for some Al/Pt multilayers ignited as free-standing foils. The model was implemented in a finite element analysis code and used to match experimental burn front velocity data collected from several years of testing at Sandia National Laboratories. Moreover, both the simulations and experiments reveal well-defined quench limits in the total Al + Pt layer (i.e., bilayer) thickness. At these limits, the heat generated from atomic diffusion is insufficient to support a self-propagating wave front on top of the substrates. Quenchmore » limits for reactive multilayers are seldom reported and are found to depend on the thermal properties of the individual layers. Here, the diffusion-limited reaction model is generalized to allow for temperature- and composition-dependent material properties, phase change, and anisotropic thermal conductivity. Utilizing this increase in model fidelity, excellent overall agreement is shown between the simulations and experimental results with a single calibrated parameter set. However, the burn front velocities of Al/Pt multilayers ignited on tungsten substrates are over-predicted. Finally, possible sources of error are discussed and a higher activation energy (from 41.9 kJ/mol.at. to 47.5 kJ/mol.at.) is shown to bring the simulations into agreement with the velocity data observed on tungsten substrates. Finally, this higher activation energy suggests an inhibited diffusion mechanism present at lower heating rates.« less

A diffusion-limited reaction model for self-propagating Al/Pt multilayers with quench limits

DOE PAGES

Kittell, David E.; Yarrington, Cole D.; Hobbs, M. L.; ...

2018-04-14

A diffusion-limited reaction model was calibrated for Al/Pt multilayers ignited on oxidized silicon, sapphire, and tungsten substrates, as well as for some Al/Pt multilayers ignited as free-standing foils. The model was implemented in a finite element analysis code and used to match experimental burn front velocity data collected from several years of testing at Sandia National Laboratories. Moreover, both the simulations and experiments reveal well-defined quench limits in the total Al + Pt layer (i.e., bilayer) thickness. At these limits, the heat generated from atomic diffusion is insufficient to support a self-propagating wave front on top of the substrates. Quenchmore » limits for reactive multilayers are seldom reported and are found to depend on the thermal properties of the individual layers. Here, the diffusion-limited reaction model is generalized to allow for temperature- and composition-dependent material properties, phase change, and anisotropic thermal conductivity. Utilizing this increase in model fidelity, excellent overall agreement is shown between the simulations and experimental results with a single calibrated parameter set. However, the burn front velocities of Al/Pt multilayers ignited on tungsten substrates are over-predicted. Finally, possible sources of error are discussed and a higher activation energy (from 41.9 kJ/mol.at. to 47.5 kJ/mol.at.) is shown to bring the simulations into agreement with the velocity data observed on tungsten substrates. Finally, this higher activation energy suggests an inhibited diffusion mechanism present at lower heating rates.« less

Formation of parametric images using mixed-effects models: a feasibility study.

PubMed

Huang, Husan-Ming; Shih, Yi-Yu; Lin, Chieh

2016-03-01

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Individual differences in emotion processing: how similar are diffusion model parameters across tasks?

PubMed

Mueller, Christina J; White, Corey N; Kuchinke, Lars

2017-11-27

The goal of this study was to replicate findings of diffusion model parameters capturing emotion effects in a lexical decision task and investigating whether these findings extend to other tasks of implicit emotion processing. Additionally, we were interested in the stability of diffusion model parameters across emotional stimuli and tasks for individual subjects. Responses to words in a lexical decision task were compared with responses to faces in a gender categorization task for stimuli of the emotion categories: happy, neutral and fear. Main effects of emotion as well as stability of emerging response style patterns as evident in diffusion model parameters across these tasks were analyzed. Based on earlier findings, drift rates were assumed to be more similar in response to stimuli of the same emotion category compared to stimuli of a different emotion category. Results showed that emotion effects of the tasks differed with a processing advantage for happy followed by neutral and fear-related words in the lexical decision task and a processing advantage for neutral followed by happy and fearful faces in the gender categorization task. Both emotion effects were captured in estimated drift rate parameters-and in case of the lexical decision task also in the non-decision time parameters. A principal component analysis showed that contrary to our hypothesis drift rates were more similar within a specific task context than within a specific emotion category. Individual response patterns of subjects across tasks were evident in significant correlations regarding diffusion model parameters including response styles, non-decision times and information accumulation.

Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies

NASA Astrophysics Data System (ADS)

Küllmer, Knut; Krämer, Andreas; Joppich, Wolfgang; Reith, Dirk; Foysi, Holger

2018-02-01

Pseudopotential-based lattice Boltzmann models are widely used for numerical simulations of multiphase flows. In the special case of multicomponent systems, the overall dynamics are characterized by the conservation equations for mass and momentum as well as an additional advection diffusion equation for each component. In the present study, we investigate how the latter is affected by the forcing scheme, i.e., by the way the underlying interparticle forces are incorporated into the lattice Boltzmann equation. By comparing two model formulations for pure multicomponent systems, namely the standard model [X. Shan and G. D. Doolen, J. Stat. Phys. 81, 379 (1995), 10.1007/BF02179985] and the explicit forcing model [M. L. Porter et al., Phys. Rev. E 86, 036701 (2012), 10.1103/PhysRevE.86.036701], we reveal that the diffusion characteristics drastically change. We derive a generalized, potential function-dependent expression for the transition point from the miscible to the immiscible regime and demonstrate that it is shifted between the models. The theoretical predictions for both the transition point and the mutual diffusion coefficient are validated in simulations of static droplets and decaying sinusoidal concentration waves, respectively. To show the universality of our analysis, two common and one new potential function are investigated. As the shift in the diffusion characteristics directly affects the interfacial properties, we additionally show that phenomena related to the interfacial tension such as the modeling of contact angles are influenced as well.

Localization of Protein Aggregation in Escherichia coli Is Governed by Diffusion and Nucleoid Macromolecular Crowding Effect

PubMed Central

Coquel, Anne-Sophie; Jacob, Jean-Pascal; Primet, Mael; Demarez, Alice; Dimiccoli, Mariella; Julou, Thomas; Moisan, Lionel

2013-01-01

Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because of the potential of E. coli as a model organism, elucidating aging and protein aggregation in this bacterium may pave the way to significant advances in our global understanding of aging. A first obstacle along this path is to decipher the mechanisms by which protein aggregates are targeted to specific intercellular locations. Here, using an integrated approach based on individual-based modeling, time-lapse fluorescence microscopy and automated image analysis, we show that the movement of aging-related protein aggregates in E. coli is purely diffusive (Brownian). Using single-particle tracking of protein aggregates in live E. coli cells, we estimated the average size and diffusion constant of the aggregates. Our results provide evidence that the aggregates passively diffuse within the cell, with diffusion constants that depend on their size in agreement with the Stokes-Einstein law. However, the aggregate displacements along the cell long axis are confined to a region that roughly corresponds to the nucleoid-free space in the cell pole, thus confirming the importance of increased macromolecular crowding in the nucleoids. We thus used 3D individual-based modeling to show that these three ingredients (diffusion, aggregation and diffusion hindrance in the nucleoids) are sufficient and necessary to reproduce the available experimental data on aggregate localization in the cells. Taken together, our results strongly support the hypothesis that the localization of aging-related protein aggregates in the poles of E. coli results from the coupling of passive diffusion-aggregation with spatially non-homogeneous macromolecular crowding. They further support the importance of “soft” intracellular structuring (based on macromolecular crowding) in diffusion-based protein localization in E. coli. PMID:23633942

Testing the Dark Matter Scenario for PeV Neutrinos Observed in IceCube.

PubMed

Murase, Kohta; Laha, Ranjan; Ando, Shin'ichiro; Ahlers, Markus

2015-08-14

Late time decay of very heavy dark matter is considered as one of the possible explanations for diffuse PeV neutrinos observed in IceCube. We consider implications of multimessenger constraints, and show that proposed models are marginally consistent with the diffuse γ-ray background data. Critical tests are possible by a detailed analysis and identification of the sub-TeV isotropic diffuse γ-ray data observed by Fermi and future observations of sub-PeV γ rays by observatories like HAWC or Tibet AS+MD. In addition, with several-year observations by next-generation telescopes such as IceCube-Gen2, muon neutrino searches for nearby dark matter halos such as the Virgo cluster should allow us to rule out or support the dark matter models, independently of γ-ray and anisotropy tests.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part I: Model development and observability analysis

NASA Astrophysics Data System (ADS)

Li, Xiaoyu; Fan, Guodong; Pan, Ke; Wei, Guo; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

The design of a lumped parameter battery model preserving physical meaning is especially desired by the automotive researchers and engineers due to the strong demand for battery system control, estimation, diagnosis and prognostics. In light of this, a novel simplified fractional order electrochemical model is developed for electric vehicle (EV) applications in this paper. In the model, a general fractional order transfer function is designed for the solid phase lithium ion diffusion approximation. The dynamic characteristics of the electrolyte concentration overpotential are approximated by a first-order resistance-capacitor transfer function in the electrolyte phase. The Ohmic resistances and electrochemical reaction kinetics resistance are simplified to a lumped Ohmic resistance parameter. Overall, the number of model parameters is reduced from 30 to 9, yet the accuracy of the model is still guaranteed. In order to address the dynamics of phase-change phenomenon in the active particle during charging and discharging, variable solid-state diffusivity is taken into consideration in the model. Also, the observability of the model is analyzed on two types of lithium ion batteries subsequently. Results show the fractional order model with variable solid-state diffusivity agrees very well with experimental data at various current input conditions and is suitable for electric vehicle applications.

Optimizing Filter-Probe Diffusion Weighting in the Rat Spinal Cord for Human Translation

PubMed Central

Budde, Matthew D.; Skinner, Nathan P.; Muftuler, L. Tugan; Schmit, Brian D.; Kurpad, Shekar N.

2017-01-01

Diffusion tensor imaging (DTI) is a promising biomarker of spinal cord injury (SCI). In the acute aftermath, DTI in SCI animal models consistently demonstrates high sensitivity and prognostic performance, yet translation of DTI to acute human SCI has been limited. In addition to technical challenges, interpretation of the resulting metrics is ambiguous, with contributions in the acute setting from both axonal injury and edema. Novel diffusion MRI acquisition strategies such as double diffusion encoding (DDE) have recently enabled detection of features not available with DTI or similar methods. In this work, we perform a systematic optimization of DDE using simulations and an in vivo rat model of SCI and subsequently implement the protocol to the healthy human spinal cord. First, two complementary DDE approaches were evaluated using an orientationally invariant or a filter-probe diffusion encoding approach. While the two methods were similar in their ability to detect acute SCI, the filter-probe DDE approach had greater predictive power for functional outcomes. Next, the filter-probe DDE was compared to an analogous single diffusion encoding (SDE) approach, with the results indicating that in the spinal cord, SDE provides similar contrast with improved signal to noise. In the SCI rat model, the filter-probe SDE scheme was coupled with a reduced field of view (rFOV) excitation, and the results demonstrate high quality maps of the spinal cord without contamination from edema and cerebrospinal fluid, thereby providing high sensitivity to injury severity. The optimized protocol was demonstrated in the healthy human spinal cord using the commercially-available diffusion MRI sequence with modifications only to the diffusion encoding directions. Maps of axial diffusivity devoid of CSF partial volume effects were obtained in a clinically feasible imaging time with a straightforward analysis and variability comparable to axial diffusivity derived from DTI. Overall, the results and optimizations describe a protocol that mitigates several difficulties with DTI of the spinal cord. Detection of acute axonal damage in the injured or diseased spinal cord will benefit the optimized filter-probe diffusion MRI protocol outlined here. PMID:29311786

Hopf Bifurcation Analysis of a Gene Regulatory Network Mediated by Small Noncoding RNA with Time Delays and Diffusion

NASA Astrophysics Data System (ADS)

Li, Chengxian; Liu, Haihong; Zhang, Tonghua; Yan, Fang

2017-12-01

In this paper, a gene regulatory network mediated by small noncoding RNA involving two time delays and diffusion under the Neumann boundary conditions is studied. Choosing the sum of delays as the bifurcation parameter, the stability of the positive equilibrium and the existence of spatially homogeneous and spatially inhomogeneous periodic solutions are investigated by analyzing the corresponding characteristic equation. It is shown that the sum of delays can induce Hopf bifurcation and the diffusion incorporated into the system can effect the amplitude of periodic solutions. Furthermore, the spatially homogeneous periodic solution always exists and the spatially inhomogeneous periodic solution will arise when the diffusion coefficients of protein and mRNA are suitably small. Particularly, the small RNA diffusion coefficient is more robust and its effect on model is much less than protein and mRNA. Finally, the explicit formulae for determining the direction of Hopf bifurcation and the stability of the bifurcating periodic solutions are derived by employing the normal form theory and center manifold theorem for partial functional differential equations. Finally, numerical simulations are carried out to illustrate our theoretical analysis.

Investigations inside a vaned diffuser of a centrifugal pump at low flowrates.

NASA Astrophysics Data System (ADS)

Bayeul-Lainé, A. C.; Dupont, P.; Dazin, A.; Bois, G.

2016-11-01

This paper focuses on the unsteady flow behaviour inside the vaned diffuser of a radial flow pump model, operating at partial flowrates (0.387Qi, 0.584Qi and 0.766Qi where Qi is the impeller design flowrate).The effects of the leakage flows are taken into account in the analysis. PIV measurements have been performed at different hub to shroud planes inside one diffuser channel passage for a given speed of rotation, for several flowrates and different angular impeller positions. The performances and the static pressure rise of the diffuser were also measured using a three-holes probe in the same experimental conditions. The unsteady numerical simulations were carried out with Star CCM+ 10.02 code with and without leakage flow. The PIV measurements showed a high unsteadiness at very low flowrate which was confirmed by the numerical calculations. In previous studies it has been shown that the global performances, as the efficiencies are in good agreement between calculations and measurements. In this paper, a joint analysis of measurements and numerical calculations is proposed to improve the understanding of the flow behaviour in a vaned diffuser.

Conceptual model analysis of interaction at a concrete-Boom Clay interface

NASA Astrophysics Data System (ADS)

Liu, Sanheng; Jacques, Diederik; Govaerts, Joan; Wang, Lian

In many concepts for deep disposal of high-level radioactive waste, cementitious materials are used in the engineered barriers. For example, in Belgium the engineered barrier system is based on a considerable amount of cementitious materials as buffer and backfill in the so-called supercontainer embedded in the hosting geological formation. A potential hosting formation is Boom Clay. Insight in the interaction between the high-pH pore water of the cementitious materials and neutral-pH Boom Clay pore water is required. Two problems are quite common for modeling of such a system. The first one is the computational cost due to the long timescale model assessments envisaged for the deep disposal system. Also a very fine grid (in sub-millimeter), especially at interfaces has to be used in order to accurately predict the evolution of the system. The second one is whether to use equilibrium or kinetic reaction models. The objectives of this paper are twofold. First, we develop an efficient coupled reactive transport code for this diffusion-dominated system by making full use of multi-processors/cores computers. Second, we investigate how sensitive the system is to chemical reaction models especially when pore clogging due to mineral precipitation is considered within the cementitious system. To do this, we selected two portlandite dissolution models, i.e., equilibrium (fastest) and diffusion-controlled model with precipitation of a calcite layer around portlandite particles (diffusion-controlled dissolution). The results show that with shrinking core model portlandite dissolution and calcite precipitation are much slower than with the equilibrium model. Also diffusion-controlled dissolution smooths out dissolution fronts compared to the equilibrium model. However, only a slight difference with respect to the clogging time can be found even though we use a very small diffusion coefficient (10-20 m2/s) in the precipitated calcite layer.

The influence of preferential flow on pressure propagation and landslide triggering of the Rocca Pitigliana landslide

NASA Astrophysics Data System (ADS)

Shao, Wei; Bogaard, Thom; Bakker, Mark; Berti, Matteo

2016-12-01

The fast pore water pressure response to rain events is an important triggering factor for slope instability. The fast pressure response may be caused by preferential flow that bypasses the soil matrix. Currently, most of the hydro-mechanical models simulate pore water pressure using a single-permeability model, which cannot quantify the effects of preferential flow on pressure propagation and landslide triggering. Previous studies showed that a model based on the linear-diffusion equation can simulate the fast pressure propagation in near-saturated landslides such as the Rocca Pitigliana landslide. In such a model, the diffusion coefficient depends on the degree of saturation, which makes it difficult to use the model for predictions. In this study, the influence of preferential flow on pressure propagation and slope stability is investigated with a 1D dual-permeability model coupled with an infinite-slope stability approach. The dual-permeability model uses two modified Darcy-Richards equations to simultaneously simulate the matrix flow and preferential flow in hillslopes. The simulated pressure head is used in an infinite-slope stability analysis to identify the influence of preferential flow on the fast pressure response and landslide triggering. The dual-permeability model simulates the height and arrival of the pressure peak reasonably well. Performance of the dual-permeability model is as good as or better than the linear-diffusion model even though the dual-permeability model is calibrated for two single pulse rain events only, while the linear-diffusion model is calibrated for each rain event separately. In conclusion, the 1D dual-permeability model is a promising tool for landslides under similar conditions.

Sorption kinetics and isotherm studies of a cationic dye using agricultural waste: broad bean peels.

PubMed

Hameed, B H; El-Khaiary, M I

2008-06-15

In this paper, broad bean peels (BBP), an agricultural waste, was evaluated for its ability to remove cationic dye (methylene blue) from aqueous solutions. Batch mode experiments were conducted at 30 degrees C. Equilibrium sorption isotherms and kinetics were investigated. The kinetic data obtained at different concentrations have been analyzed using pseudo-first-order, pseudo-second-order and intraparticle diffusion equations. The experimental data fitted very well the pseudo-first-order kinetic model. Analysis of the temportal change of q indicates that at the beginning of the process the overall rate of adsorption is controlled by film-diffusion, then at later stage intraparticle-diffusion controls the rate. Diffusion coefficients and times of transition from film to pore-diffusion control were estimated by piecewise linear regression. The experimental data were analyzed by the Langmuir and Freundlich models. The sorption isotherm data fitted well to Langmuir isotherm and the monolayer adsorption capacity was found to be 192.7 mg/g and the equilibrium adsorption constant Ka is 0.07145 l/mg at 30 degrees C. The results revealed that BBP was a promising sorbent for the removal of methylene blue from aqueous solutions.

Holographic estimate of heavy quark diffusion in a magnetic field

NASA Astrophysics Data System (ADS)

Dudal, David; Mertens, Thomas G.

2018-03-01

We study the influence of a background magnetic field on the J /ψ vector meson in a Dirac-Born-Infeld-extension of the soft wall model, building upon our earlier work [D. Dudal and T. G. Mertens Phys. Rev. D 91, 086002 (2015), 10.1103/PhysRevD.91.086002]. In this specific holographic QCD model, we discuss the heavy quark number susceptibility and diffusion constants of charm quarks and their dependence on the magnetic field by either a hydrodynamic expansion or by numerically solving the differential equation. This allows us to determine the response of these transport coefficients to the magnetic field. The effects of the latter are considered both from a direct as indirect (medium) viewpoint. As expected, we find a magnetic field induced anisotropic diffusion, with a stronger diffusion in the longitudinal direction compared to the transversal one. We backup, at least qualitatively, our findings with a hanging string analysis of heavy quark diffusion in a magnetic field. From the quark number susceptibility we can extract an estimate for the effective deconfinement temperature in the heavy quark sector, reporting consistency with the phenomenon of inverse magnetic catalysis.

Nation-scale adoption of new medicines by doctors: an application of the Bass diffusion model

PubMed Central

2012-01-01

Background The adoption of new medicines is influenced by a complex set of social processes that have been widely examined in terms of individual prescribers’ information-seeking and decision-making behaviour. However, quantitative, population-wide analyses of how long it takes for new healthcare practices to become part of mainstream practice are rare. Methods We applied a Bass diffusion model to monthly prescription volumes of 103 often-prescribed drugs in Australia (monthly time series data totalling 803 million prescriptions between 1992 and 2010), to determine the distribution of adoption rates. Our aim was to test the utility of applying the Bass diffusion model to national-scale prescribing volumes. Results The Bass diffusion model was fitted to the adoption of a broad cross-section of drugs using national monthly prescription volumes from Australia (median R2 = 0.97, interquartile range 0.95 to 0.99). The median time to adoption was 8.2 years (IQR 4.9 to 12.1). The model distinguished two classes of prescribing patterns – those where adoption appeared to be driven mostly by external forces (19 drugs) and those driven mostly by social contagion (84 drugs). Those driven more prominently by internal forces were found to have shorter adoption times (p = 0.02 in a non-parametric analysis of variance by ranks). Conclusion The Bass diffusion model may be used to retrospectively represent the patterns of adoption exhibited in prescription volumes in Australia, and distinguishes between adoption driven primarily by external forces such as regulation, or internal forces such as social contagion. The eight-year delay between the introduction of a new medicine and the adoption of the prescribing practice suggests the presence of system inertia in Australian prescribing practices. PMID:22876867

Nonlinear diffusion and viral spread through the leaf of a plant

NASA Astrophysics Data System (ADS)

Edwards, Maureen P.; Waterhouse, Peter M.; Munoz-Lopez, María Jesús; Anderssen, Robert S.

2016-10-01

The spread of a virus through the leaf of a plant is both spatially and temporally causal in that the present status depends on the past and the spatial spread is compactly supported and progresses outwards. Such spatial spread is known to occur for certain nonlinear diffusion processes. The first compactly supported solution for nonlinear diffusion equations appears to be that of Pattle published in 1959. In that paper, no explanation is given as to how the solution was derived. Here, we show how the solution can be derived using Lie symmetry analysis. This lays a foundation for exploring the behavior of other choices for nonlinear diffusion and exploring the addition of reaction terms which do not eliminate the compactly supported structure. The implications associated with using the reaction-diffusion equation to model the spatial-temporal spread of a virus through the leaf of a plant are discussed.

Transport through a network of capillaries from ultrametric diffusion equation with quadratic nonlinearity

NASA Astrophysics Data System (ADS)

Oleschko, K.; Khrennikov, A.

2017-10-01

This paper is about a novel mathematical framework to model transport (of, e.g., fluid or gas) through networks of capillaries. This framework takes into account the tree structure of the networks of capillaries. (Roughly speaking, we use the tree-like system of coordinates.) As is well known, tree-geometry can be topologically described as the geometry of an ultrametric space, i.e., a metric space in which the metric satisfies the strong triangle inequality: in each triangle, the third side is less than or equal to the maximum of two other sides. Thus transport (e.g., of oil or emulsion of oil and water in porous media, or blood and air in biological organisms) through networks of capillaries can be mathematically modelled as ultrametric diffusion. Such modelling was performed in a series of recently published papers of the authors. However, the process of transport through capillaries can be only approximately described by the linear diffusion, because the concentration of, e.g., oil droplets, in a capillary can essentially modify the dynamics. Therefore nonlinear dynamical equations provide a more adequate model of transport in a network of capillaries. We consider a nonlinear ultrametric diffusion equation with quadratic nonlinearity - to model transport in such a network. Here, as in the linear case, we apply the theory of ultrametric wavelets. The paper also contains a simple introduction to theory of ultrametric spaces and analysis on them.

Slowdown of surface diffusion during early stages of bacterial colonization

NASA Astrophysics Data System (ADS)

Vourc'h, T.; Peerhossaini, H.; Léopoldès, J.; Méjean, A.; Chauvat, F.; Cassier-Chauvat, C.

2018-03-01

We study the surface diffusion of the model cyanobacterium Synechocystis sp. PCC6803 during the incipient stages of cell contact with a glass surface in the dilute regime. We observe a twitching motility with alternating immobile tumble and mobile run periods, resulting in a normal diffusion described by a continuous-time random walk with a coefficient of diffusion D . Surprisingly, D is found to decrease with time down to a plateau. This is observed only when the cyanobacterial cells are able to produce released extracellular polysaccharides, as shown by a comparative study between the wild-type strain and various polysaccharides-depleted mutants. The analysis of the trajectories taken by the bacterial cells shows that the temporal characteristics of their intermittent motion depend on the instantaneous fraction of visited sites during diffusion. This describes quantitatively the time dependence of D , related to the progressive surface coverage by the polysaccharides. The observed slowdown of the surface diffusion may constitute a basic precursor mechanism for microcolony formation and provides clues for controlling biofilm formation.

Cohort change and the diffusion of environmental concern: A cross-national analysis

PubMed Central

Nawrotzki, Raphael J.; Pampel, Fred C.

2013-01-01

This study explores value change across cohorts for a multinational population sample. Employing a diffusion-of-innovations approach, we combine competing theories predicting the relationship between socio-economic status (SES) and environmentalism: post-materialism and affluence theories, and global environmentalism theory. The diffusion argument suggests that high-SES groups first adopt pro-environmental views, but as time passes by, environmentalism diffuses to lower-SES groups. We test the diffusion argument using a sample of 18 countries for two waves (years 1993 and 2000) from the International Social Survey Project (ISSP). Cross-classified multilevel modeling allows us to identify a non-linear interaction between cohort and education, our core measure of SES, in predicting environmental concern, while controlling for age and period. We find support for the diffusion argument and demonstrate that the positive effect of education on environmental concern first increases among older cohorts, then starts to level off until a bend-point is reached for individuals born around 1940 and becomes progressively weaker for younger cohorts. PMID:24179313

Information diffusion in structured online social networks

NASA Astrophysics Data System (ADS)

Li, Pei; Zhang, Yini; Qiao, Fengcai; Wang, Hui

2015-05-01

Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.

Cohort change and the diffusion of environmental concern: A cross-national analysis.

PubMed

Nawrotzki, Raphael J; Pampel, Fred C

2013-09-01

This study explores value change across cohorts for a multinational population sample. Employing a diffusion-of-innovations approach, we combine competing theories predicting the relationship between socio-economic status (SES) and environmentalism: post-materialism and affluence theories, and global environmentalism theory. The diffusion argument suggests that high-SES groups first adopt pro-environmental views, but as time passes by, environmentalism diffuses to lower-SES groups. We test the diffusion argument using a sample of 18 countries for two waves (years 1993 and 2000) from the International Social Survey Project (ISSP). Cross-classified multilevel modeling allows us to identify a non-linear interaction between cohort and education, our core measure of SES, in predicting environmental concern, while controlling for age and period. We find support for the diffusion argument and demonstrate that the positive effect of education on environmental concern first increases among older cohorts, then starts to level off until a bend-point is reached for individuals born around 1940 and becomes progressively weaker for younger cohorts.

Extracting surface diffusion coefficients from batch adsorption measurement data: application of the classic Langmuir kinetics model.

PubMed

Chu, Khim Hoong

2017-11-09

Surface diffusion coefficients may be estimated by fitting solutions of a diffusion model to batch kinetic data. For non-linear systems, a numerical solution of the diffusion model's governing equations is generally required. We report here the application of the classic Langmuir kinetics model to extract surface diffusion coefficients from batch kinetic data. The use of the Langmuir kinetics model in lieu of the conventional surface diffusion model allows derivation of an analytical expression. The parameter estimation procedure requires determining the Langmuir rate coefficient from which the pertinent surface diffusion coefficient is calculated. Surface diffusion coefficients within the 10 -9 to 10 -6  cm 2 /s range obtained by fitting the Langmuir kinetics model to experimental kinetic data taken from the literature are found to be consistent with the corresponding values obtained from the traditional surface diffusion model. The virtue of this simplified parameter estimation method is that it reduces the computational complexity as the analytical expression involves only an algebraic equation in closed form which is easily evaluated by spreadsheet computation.

Modeling chemical accumulation in sediment of small waterbodies accounting for sediment transport and water-sediment exchange processes over long periods.

PubMed

Patterson, David Albert; Strehmel, Alexander; Erzgräber, Beate; Hammel, Klaus

2017-12-01

In a recent scientific opinion of the European Food Safety Authority it is argued that the accumulation of plant protection products in sediments over long time periods may be an environmentally significant process. Therefore, the European Food Safety Authority proposed a calculation to account for plant protection product accumulation. This calculation, however, considers plant protection product degradation within sediment as the only dissipation route, and does not account for sediment dynamics or back-diffusion into the water column. The hydraulic model Hydrologic Engineering Center-River Analysis System (HEC-RAS; US Army Corps of Engineers) was parameterized to assess sediment transport and deposition dynamics within the FOrum for Co-ordination of pesticide fate models and their USe (FOCUS) scenarios in simulations spanning 20 yr. The results show that only 10 to 50% of incoming sediment would be deposited. The remaining portion of sediment particles is transported across the downstream boundary. For a generic plant protection product substance this resulted in deposition of only 20 to 50% of incoming plant protection product substance. In a separate analysis, the FOCUS TOXSWA model was utilized to examine the relative importance of degradation versus back-diffusion as loss processes from the sediment compartment for a diverse range of generic plant protection products. In simulations spanning 20 yr, it was shown that back-diffusion was generally the dominant dissipation process. The results of the present study show that sediment dynamics and back-diffusion should be considered when calculating long-term plant protection product accumulation in sediment. Neglecting these may lead to a systematic overestimation of accumulation. Environ Toxicol Chem 2017;36:3223-3231. © 2017 SETAC. © 2017 SETAC.

Pattern formation in a model for mountain pine beetle dispersal: linking model predictions to data.

PubMed

Strohm, S; Tyson, R C; Powell, J A

2013-10-01

Pattern formation occurs in a wide range of biological systems. This pattern formation can occur in mathematical models because of diffusion-driven instability or due to the interaction between reaction, diffusion, and chemotaxis. In this paper, we investigate the spatial pattern formation of attack clusters in a system for Mountain Pine Beetle. The pattern formation (aggregation) of the Mountain Pine Beetle in order to attack susceptible trees is crucial for their survival and reproduction. We use a reaction-diffusion equation with chemotaxis to model the interaction between Mountain Pine Beetle, Mountain Pine Beetle pheromones, and susceptible trees. Mathematical analysis is utilized to discover the spacing in-between beetle attacks on the susceptible landscape. The model predictions are verified by analysing aerial detection survey data of Mountain Pine Beetle Attack from the Sawtooth National Recreation Area. We find that the distance between Mountain Pine Beetle attack clusters predicted by our model closely corresponds to the observed attack data in the Sawtooth National Recreation Area. These results clarify the spatial mechanisms controlling the transition from incipient to epidemic populations and may lead to control measures which protect forests from Mountain Pine Beetle outbreak.

HARDI DATA DENOISING USING VECTORIAL TOTAL VARIATION AND LOGARITHMIC BARRIER

PubMed Central

Kim, Yunho; Thompson, Paul M.; Vese, Luminita A.

2010-01-01

In this work, we wish to denoise HARDI (High Angular Resolution Diffusion Imaging) data arising in medical brain imaging. Diffusion imaging is a relatively new and powerful method to measure the three-dimensional profile of water diffusion at each point in the brain. These images can be used to reconstruct fiber directions and pathways in the living brain, providing detailed maps of fiber integrity and connectivity. HARDI data is a powerful new extension of diffusion imaging, which goes beyond the diffusion tensor imaging (DTI) model: mathematically, intensity data is given at every voxel and at any direction on the sphere. Unfortunately, HARDI data is usually highly contaminated with noise, depending on the b-value which is a tuning parameter pre-selected to collect the data. Larger b-values help to collect more accurate information in terms of measuring diffusivity, but more noise is generated by many factors as well. So large b-values are preferred, if we can satisfactorily reduce the noise without losing the data structure. Here we propose two variational methods to denoise HARDI data. The first one directly denoises the collected data S, while the second one denoises the so-called sADC (spherical Apparent Diffusion Coefficient), a field of radial functions derived from the data. These two quantities are related by an equation of the form S = SSexp (−b · sADC) (in the noise-free case). By applying these two different models, we will be able to determine which quantity will most accurately preserve data structure after denoising. The theoretical analysis of the proposed models is presented, together with experimental results and comparisons for denoising synthetic and real HARDI data. PMID:20802839

Demyelinating evidences in CMS rat model of depression: a DTI study at 7 T.

PubMed

Hemanth Kumar, B S; Mishra, S K; Trivedi, R; Singh, S; Rana, P; Khushu, S

2014-09-05

Depression is among the most debilitating diseases worldwide. Long-term exposure to stressors plays a major role in development of human depression. Chronic mild stress (CMS) seems to be a valid animal model for depression. Diffusion tensor imaging (DTI) is capable of inferring microstructural abnormalities of the white matter and has shown to serve as non-invasive marker of specific pathology. We developed a CMS rat model of depression and validated with behavioral experiments. We measured the diffusion indices (mean diffusivity (MD), fractional anisotropy (FA), axial (λ∥) and radial (λ⊥) diffusivity) to investigate the changes in CMS rat brain during depression onset. Diffusion indices have shown to be useful to discriminate myelin damage from axon loss. DTI was performed in both control and CMS rats (n=10, in each group) and maps of FA, MD, λ∥ and λ⊥ diffusivity values were generated using in-house built software. The diffusion indices were calculated by region of interest (ROI) analysis in different brain regions like the frontal cortex, hippocampus, hypothalamus, cingulum, thalamus, caudate putamen, corpus callosum, cerebral peduncle and sensory motor cortex. The results showed signs of demyelination, reflected by increased MD, decreased FA and increased λ⊥. The results also suggest a possible role of edema or inflammation concerning the brain morphology in CMS rats. The overall finding using DTI suggests there might be a major role of loss of myelin sheath, which leads to disrupted connectivity between the limbic area and the prefrontal cortex during the onset of depression. Our findings indicate that interpretation of these indices may provide crucial information about the type and severity of mood disorders. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Finite Element Analysis Modeling of Chemical Vapor Deposition of Silicon Carbide

DTIC Science & Technology

2014-06-19

thesis primarily focuses on mass transport by gas -phase flow and diffusion , chemical reaction in gas phase and on solid surfaces, and thin film...chemical vapor deposition (CVD). This thesis primarily focuses on mass transport by gas -phase flow and diffusion , chemical reaction in gas phase and...9 Fluid Flow…………………………………………..…………………..…………….9 Thermodynamics………………………………………..………………….….…….11 Chemical Reaction and Diffusion

Diffusion Dynamics and Creative Destruction in a Simple Classical Model

PubMed Central

2015-01-01

ABSTRACT The article explores the impact of the diffusion of new methods of production on output and employment growth and income distribution within a Classical one‐sector framework. Disequilibrium paths are studied analytically and in terms of simulations. Diffusion by differential growth affects aggregate dynamics through several channels. The analysis reveals the non‐steady nature of economic change and shows that the adaptation pattern depends both on the innovation's factor‐saving bias and on the extent of the bias, which determines the strength of the selection pressure on non‐innovators. The typology of different cases developed shows various aspects of Schumpeter's concept of creative destruction. PMID:27642192

Cavitation in centrifugal pump with rotating walls of axial inlet device

NASA Astrophysics Data System (ADS)

Moloshnyi, O.; Sotnyk, M.

2017-08-01

The article deals with the analysis of cavitation processes in the flowing part of the double entry centrifugal pump. The analysis is conducted using numerical modeling of the centrifugal pump operating process in the software environment ANSYS CFX. Two models of the axial inlet device is researched. It is shaped by a cylindrical section and diffuser section in front of the impeller, which includes fairing. The walls of the axial inlet device rotate with the same speed as the pump rotor. The numerical experiment is conducted under the condition of the flow rate change and absolute pressure at the inlet. The analysis shows that the pump has the average statistical cavitation performance. The occurrence of the cavitation in the axial inlet device is after narrowing the cross-section of flow channel and at the beginning of the diffuser section. Additional sudden expansion at the outlet of the axial inlet diffuser section does not affect the cavitation characteristics of the impeller, however, improves cavitation characteristics of the axial inlet device. For considered geometric parameters of the axial inlet device the cavitation in the impeller begins earlier than in the axial inlet device. That is, the considered design of the axial inlet device will not be subjected to destruction at the ensuring operation without cavitation in the impeller.

A preliminary sensitivity analysis of the coupled diffusion and chemistry model. [effect of SST operations on ambient ozone in lower stratosphere

NASA Technical Reports Server (NTRS)

Hilst, G. R.; Contiliano, R. M.

1973-01-01

The sensitivity of the coupled chemistry/diffusion model's outputs to a wide range of variation of the model's independent variables has been investigated. It is shown that the efficiency with which the now catalytic cycle destroys ambient O3 is extremely sensitive to the amount of NO emitted and to the relative rates of turbulent diffusion and chemical reactions. For representative conditions in the stratosphere, a tenfold variation of either the turbulence intensity or the reaction rate constant or the source strength can vary the efficiency from 1% to 50%. If the duration of Phase 3 is a significant fraction of the total residence time of the plume, then these efficiency variations can alter O3 depletion rates by more than a factor of two. These results, therefore, point toward those variables which must be accurately defined or measured if one is to adequately predict the effect of SST operations on the ambient inventory of O3 in the lower stratosphere.

Influence of Wind Pressure on the Carbonation of Concrete

PubMed Central

Zou, Dujian; Liu, Tiejun; Du, Chengcheng; Teng, Jun

2015-01-01

Carbonation is one of the major deteriorations that accelerate steel corrosion in reinforced concrete structures. Many mathematical/numerical models of the carbonation process, primarily diffusion-reaction models, have been established to predict the carbonation depth. However, the mass transfer of carbon dioxide in porous concrete includes molecular diffusion and convection mass transfer. In particular, the convection mass transfer induced by pressure difference is called penetration mass transfer. This paper presents the influence of penetration mass transfer on the carbonation. A penetration-reaction carbonation model was constructed and validated by accelerated test results under high pressure. Then the characteristics of wind pressure on the carbonation were investigated through finite element analysis considering steady and fluctuating wind flows. The results indicate that the wind pressure on the surface of concrete buildings results in deeper carbonation depth than that just considering the diffusion of carbon dioxide. In addition, the influence of wind pressure on carbonation tends to increase significantly with carbonation depth. PMID:28793462

Recycling of Kinesin-1 Motors by Diffusion after Transport

PubMed Central

Blasius, T. Lynne; Reed, Nathan; Slepchenko, Boris M.; Verhey, Kristen J.

2013-01-01

Kinesin motors drive the long-distance anterograde transport of cellular components along microtubule tracks. Kinesin-dependent transport plays a critical role in neurogenesis and neuronal function due to the large distance separating the soma and nerve terminal. The fate of kinesin motors after delivery of their cargoes is unknown but has been postulated to involve degradation at the nerve terminal, recycling via retrograde motors, and/or recycling via diffusion. We set out to test these models concerning the fate of kinesin-1 motors after completion of transport in neuronal cells. We find that kinesin-1 motors are neither degraded nor returned by retrograde motors. By combining mathematical modeling and experimental analysis, we propose a model in which the distribution and recycling of kinesin-1 motors fits a “loose bucket brigade” where individual motors alter between periods of active transport and free diffusion within neuronal processes. These results suggest that individual kinesin-1 motors are utilized for multiple rounds of transport. PMID:24098765

On a nonlocal reaction-diffusion-advection system modelling the growth of phytoplankton with cell quota structure

NASA Astrophysics Data System (ADS)

Hsu, Sze-Bi; Mei, Linfeng; Wang, Feng-Bin

2015-11-01

Phytoplankton species in a water column compete for mineral nutrients and light, and the existing models usually neglect differences in the nutrient content and the amount of light absorbed of individuals. In this current paper, we examine a size-structured and nonlocal reaction-diffusion-advection system which describes the dynamics of a single phytoplankton species in a water column where the species depends simply on light for its growth. Our model is under the assumption that the amount of light absorbed by individuals is proportional to cell size, which varies for populations that reproduce by simple division into two equally-sized daughters. We first establish the existence of a critical death rate and our analysis indicates that the phytoplankton survives if and only if its death rate is less than the critical death rate. The critical death rate depends on a general reproductive rate, the characteristics of the water column (e.g., turbulent diffusion rate, sinking, depth), cell growth, cell division, and cell size.

The GeV Excess Shining Through: Background Systematics for the Inner Galaxy Analysis

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

Calore, Francesca; Cholis, Ilias; Weniger, Christoph

2015-02-10

Recently, a spatially extended excess of gamma rays collected by the Fermi-LAT from the inner region of the Milky Way has been detected by different groups and with increasingly sophisticated techniques. Yet, any final conclusion about the morphology and spectral properties of such an extended diffuse emission are subject to a number of potentially critical uncertainties, related to the high density of cosmic rays, gas, magnetic fields and abundance of point sources. We will present a thorough study of the systematic uncertainties related to the modelling of diffuse background and to the propagation of cosmic rays in the inner partmore » of our Galaxy. We will test a large set of models for the Galactic diffuse emission, generated by varying the propagation parameters within extreme conditions. By using those models in the fit of Fermi-LAT data as Galactic foreground, we will show that the gamma-ray excess survives and we will quantify the uncertainties on the excess emission morphology and energy spectrum.« less

Influence of Wind Pressure on the Carbonation of Concrete.

PubMed

Zou, Dujian; Liu, Tiejun; Du, Chengcheng; Teng, Jun

2015-07-24

Carbonation is one of the major deteriorations that accelerate steel corrosion in reinforced concrete structures. Many mathematical/numerical models of the carbonation process, primarily diffusion-reaction models, have been established to predict the carbonation depth. However, the mass transfer of carbon dioxide in porous concrete includes molecular diffusion and convection mass transfer. In particular, the convection mass transfer induced by pressure difference is called penetration mass transfer. This paper presents the influence of penetration mass transfer on the carbonation. A penetration-reaction carbonation model was constructed and validated by accelerated test results under high pressure. Then the characteristics of wind pressure on the carbonation were investigated through finite element analysis considering steady and fluctuating wind flows. The results indicate that the wind pressure on the surface of concrete buildings results in deeper carbonation depth than that just considering the diffusion of carbon dioxide. In addition, the influence of wind pressure on carbonation tends to increase significantly with carbonation depth.

Microenvironmental influence on microtumour infiltration patterns: 3D-mathematical modelling supported by in vitro studies.

PubMed

Luján, Emmanuel; Soto, Daniela; Rosito, María S; Soba, Alejandro; Guerra, Liliana N; Calvo, Juan C; Marshall, Guillermo; Suárez, Cecilia

2018-05-09

Mathematical modelling approaches have become increasingly abundant in cancer research. Tumour infiltration extent and its spatial organization depend both on the tumour type and stage and on the bio-physicochemical characteristics of the microenvironment. This sets a complex scenario that often requires a multidisciplinary and individually adjusted approach. The ultimate goal of this work is to present an experimental/numerical combined method for the development of a three-dimensional mathematical model with the ability to reproduce the growth and infiltration patterns of a given avascular microtumour in response to different microenvironmental conditions. The model is based on a diffusion-convection reaction equation that considers logistic proliferation, volumetric growth, a rim of proliferative cells at the tumour surface, and invasion with diffusive and convective components. The parameter values of the model were fitted to experimental results while radial velocity and diffusion coefficients were made spatially variable in a case-specific way through the introduction of a shape function and a diffusion-limited-aggregation (DLA)-derived fractal matrix, respectively, according to the infiltration pattern observed. The in vitro model consists of multicellular tumour spheroids (MTSs) of an epithelial mammary tumour cell line (LM3) immersed in a collagen I gel matrix with a standard culture medium ("naive" matrix) or a conditioned medium from adipocytes or preadipocytes ("conditioned" matrix). It was experimentally determined that both adipocyte and preadipocyte conditioned media had the ability to change the MTS infiltration pattern from collective and laminar to an individual and atomized one. Numerical simulations were able to adequately reproduce qualitatively and quantitatively both kinds of infiltration patterns, which were determined by area quantification, analysis of fractal dimensions and lacunarity, and Bland-Altman analysis. These results suggest that the combined approach presented here could be established as a new framework with interesting potential applications at both the basic and clinical levels in the oncology area.

Evaluation of the impact of computed high b-value diffusion-weighted imaging on prostate cancer detection.

PubMed

Verma, Sadhna; Sarkar, Saradwata; Young, Jason; Venkataraman, Rajesh; Yang, Xu; Bhavsar, Anil; Patil, Nilesh; Donovan, James; Gaitonde, Krishnanath

2016-05-01

The purpose of this study was to compare high b-value (b = 2000 s/mm(2)) acquired diffusion-weighted imaging (aDWI) with computed DWI (cDWI) obtained using four diffusion models-mono-exponential (ME), intra-voxel incoherent motion (IVIM), stretched exponential (SE), and diffusional kurtosis (DK)-with respect to lesion visibility, conspicuity, contrast, and ability to predict significant prostate cancer (PCa). Ninety four patients underwent 3 T MRI including acquisition of b = 2000 s/mm(2) aDWI and low b-value DWI. High b = 2000 s/mm(2) cDWI was obtained using ME, IVIM, SE, and DK models. All images were scored on quality independently by three radiologists. Lesions were identified on all images and graded for lesion conspicuity. For a subset of lesions for which pathological truth was established, lesion-to-background contrast ratios (LBCRs) were computed and binomial generalized linear mixed model analysis was conducted to compare clinically significant PCa predictive capabilities of all DWI. For all readers and all models, cDWI demonstrated higher ratings for image quality and lesion conspicuity than aDWI except DK (p < 0.001). The LBCRs of ME, IVIM, and SE were significantly higher than LBCR of aDWI (p < 0.001). Receiver Operating Characteristic curves obtained from binomial generalized linear mixed model analysis demonstrated higher Area Under the Curves for ME, SE, IVIM, and aDWI compared to DK or PSAD alone in predicting significant PCa. High b-value cDWI using ME, IVIM, and SE diffusion models provide better image quality, lesion conspicuity, and increased LBCR than high b-value aDWI. Using cDWI can potentially provide comparable sensitivity and specificity for detecting significant PCa as high b-value aDWI without increased scan times and image degradation artifacts.

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.

Compact structure and non-Gaussian dynamics of ring polymer melts.

PubMed

Brás, Ana R; Goossen, Sebastian; Krutyeva, Margarita; Radulescu, Aurel; Farago, Bela; Allgaier, Jürgen; Pyckhout-Hintzen, Wim; Wischnewski, Andreas; Richter, Dieter

2014-05-28

We present a neutron scattering analysis of the structure and dynamics of PEO polymer rings with a molecular weight 2.5 times higher than the entanglement mass. The melt structure was found to be more compact than a Gaussian model would suggest. With increasing time the center of mass (c.o.m.) diffusion undergoes a transition from sub-diffusive to diffusive behavior. The transition time agrees well with the decorrelation time predicted by a mode coupling approach. As a novel feature well pronounced non-Gaussian behavior of the c.o.m. diffusion was found that shows surprising analogies to the cage effect known from glassy systems. Finally, the longest wavelength Rouse modes are suppressed possibly as a consequence of an onset of lattice animal features as hypothesized in theoretical approaches.

Model of bidirectional reflectance distribution function for metallic materials

NASA Astrophysics Data System (ADS)

Wang, Kai; Zhu, Jing-Ping; Liu, Hong; Hou, Xun

2016-09-01

Based on the three-component assumption that the reflection is divided into specular reflection, directional diffuse reflection, and ideal diffuse reflection, a bidirectional reflectance distribution function (BRDF) model of metallic materials is presented. Compared with the two-component assumption that the reflection is composed of specular reflection and diffuse reflection, the three-component assumption divides the diffuse reflection into directional diffuse and ideal diffuse reflection. This model effectively resolves the problem that constant diffuse reflection leads to considerable error for metallic materials. Simulation and measurement results validate that this three-component BRDF model can improve the modeling accuracy significantly and describe the reflection properties in the hemisphere space precisely for the metallic materials.

FE analysis of creep and hygroexpansion response of a corrugated fiberboard to a moisture flow : a transient nonlinear analysis

Treesearch

Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid

2006-01-01

This paper presents a model using finite element method to study the response of a typical commercial corrugated fiberboard due to an induced moisture function at one side of the fiberboard. The model predicts how the moisture diffusion will permeate through the fiberboard’s layers(medium and liners) providing information on moisture content at any given point...

Effective Stochastic Model for Reactive Transport

NASA Astrophysics Data System (ADS)

Tartakovsky, A. M.; Zheng, B.; Barajas-Solano, D. A.

2017-12-01

We propose an effective stochastic advection-diffusion-reaction (SADR) model. Unlike traditional advection-dispersion-reaction models, the SADR model describes mechanical and diffusive mixing as two separate processes. In the SADR model, the mechanical mixing is driven by random advective velocity with the variance given by the coefficient of mechanical dispersion. The diffusive mixing is modeled as a fickian diffusion with the effective diffusion coefficient. Both coefficients are given in terms of Peclet number (Pe) and the coefficient of molecular diffusion. We use the experimental results of to demonstrate that for transport and bimolecular reactions in porous media the SADR model is significantly more accurate than the traditional dispersion model, which overestimates the mass of the reaction product by as much as 25%.

Multiscale Modeling of Diffusion in a Crowded Environment.

PubMed

Meinecke, Lina

2017-11-01

We present a multiscale approach to model diffusion in a crowded environment and its effect on the reaction rates. Diffusion in biological systems is often modeled by a discrete space jump process in order to capture the inherent noise of biological systems, which becomes important in the low copy number regime. To model diffusion in the crowded cell environment efficiently, we compute the jump rates in this mesoscopic model from local first exit times, which account for the microscopic positions of the crowding molecules, while the diffusing molecules jump on a coarser Cartesian grid. We then extract a macroscopic description from the resulting jump rates, where the excluded volume effect is modeled by a diffusion equation with space-dependent diffusion coefficient. The crowding molecules can be of arbitrary shape and size, and numerical experiments demonstrate that those factors together with the size of the diffusing molecule play a crucial role on the magnitude of the decrease in diffusive motion. When correcting the reaction rates for the altered diffusion we can show that molecular crowding either enhances or inhibits chemical reactions depending on local fluctuations of the obstacle density.

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.

Reaction time for trimolecular reactions in compartment-based reaction-diffusion models

NASA Astrophysics Data System (ADS)

Li, Fei; Chen, Minghan; Erban, Radek; Cao, Yang

2018-05-01

Trimolecular reaction models are investigated in the compartment-based (lattice-based) framework for stochastic reaction-diffusion modeling. The formulae for the first collision time and the mean reaction time are derived for the case where three molecules are present in the solution under periodic boundary conditions. For the case of reflecting boundary conditions, similar formulae are obtained using a computer-assisted approach. The accuracy of these formulae is further verified through comparison with numerical results. The presented derivation is based on the first passage time analysis of Montroll [J. Math. Phys. 10, 753 (1969)]. Montroll's results for two-dimensional lattice-based random walks are adapted and applied to compartment-based models of trimolecular reactions, which are studied in one-dimensional or pseudo one-dimensional domains.

Evaluation of non-Gaussian diffusion in cardiac MRI.

PubMed

McClymont, Darryl; Teh, Irvin; Carruth, Eric; Omens, Jeffrey; McCulloch, Andrew; Whittington, Hannah J; Kohl, Peter; Grau, Vicente; Schneider, Jürgen E

2017-09-01

The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non-Gaussian modeling. The aim of this study was to investigate non-Gaussian diffusion in healthy and hypertrophic hearts. Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion-weighted images were acquired at b-values up to 10,000 s/mm 2 . Models of diffusion were fit to the data and ranked based on the Akaike information criterion. The diffusion tensor was ranked best at b-values up to 2000 s/mm 2 but reflected the signal poorly in the high b-value regime, in which the best model was a non-Gaussian "beta distribution" model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet-normal directions. Non-Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174-1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Ischemic lesion volume determination on diffusion weighted images vs. apparent diffusion coefficient maps.

PubMed

Bråtane, Bernt Tore; Bastan, Birgul; Fisher, Marc; Bouley, James; Henninger, Nils

2009-07-07

Though diffusion weighted imaging (DWI) is frequently used for identifying the ischemic lesion in focal cerebral ischemia, the understanding of spatiotemporal evolution patterns observed with different analysis methods remains imprecise. DWI and calculated apparent diffusion coefficient (ADC) maps were serially obtained in rat stroke models (MCAO): permanent, 90 min, and 180 min temporary MCAO. Lesion volumes were analyzed in a blinded and randomized manner by 2 investigators using (i) a previously validated ADC threshold, (ii) visual determination of hypointense regions on ADC maps, and (iii) visual determination of hyperintense regions on DWI. Lesion volumes were correlated with 24 hour 2,3,5-triphenyltetrazoliumchloride (TTC)-derived infarct volumes. TTC-derived infarct volumes were not significantly different from the ADC and DWI-derived lesion volumes at the last imaging time points except for significantly smaller DWI lesions in the pMCAO model (p=0.02). Volumetric calculation based on TTC-derived infarct also correlated significantly stronger to volumetric calculation based on last imaging time point derived lesions on ADC maps than DWI (p<0.05). Following reperfusion, lesion volumes on the ADC maps significantly reduced but no change was observed on DWI. Visually determined lesion volumes on ADC maps and DWI by both investigators correlated significantly with threshold-derived lesion volumes on ADC maps with the former method demonstrating a stronger correlation. There was also a better interrater agreement for ADC map analysis than for DWI analysis. Ischemic lesion determination by ADC was more accurate in final infarct prediction, rater independent, and provided exclusive information on ischemic lesion reversibility.

The Born-again Planetary Nebula A78: An X-Ray Twin of A30

NASA Astrophysics Data System (ADS)

Toalá, J. A.; Guerrero, M. A.; Todt, H.; Hamann, W.-R.; Chu, Y.-H.; Gruendl, R. A.; Schönberner, D.; Oskinova, L. M.; Marquez-Lugo, R. A.; Fang, X.; Ramos-Larios, G.

2015-01-01

We present the XMM-Newton discovery of X-ray emission from the planetary nebula (PN) A78, the second born-again PN detected in X-rays apart from A30. These two PNe share similar spectral and morphological characteristics: they harbor diffuse soft X-ray emission associated with the interaction between the H-poor ejecta and the current fast stellar wind and a point-like source at the position of the central star (CSPN). We present the spectral analysis of the CSPN, using for the first time an NLTE code for expanding atmospheres that takes line blanketing into account for the UV and optical spectra. The wind abundances are used for the X-ray spectral analysis of the CSPN and the diffuse emission. The X-ray emission from the CSPN in A78 can be modeled by a single C VI emission line, while the X-ray emission from its diffuse component is better described by an optically thin plasma emission model with a temperature of kT = 0.088 keV (T ≈ 1.0 × 106 K). We estimate X-ray luminosities in the 0.2-2.0 keV energy band of L X, CSPN = (1.2 ± 0.3) × 1031 erg s-1 and L X, DIFF = (9.2 ± 2.3) × 1030 erg s-1 for the CSPN and diffuse components, respectively.

Sensitivity of Rabbit Ventricular Action Potential and Ca2+ Dynamics to Small Variations in Membrane Currents and Ion Diffusion Coefficients

PubMed Central

Lo, Yuan Hung; Peachey, Tom; Abramson, David; McCulloch, Andrew

2013-01-01

Little is known about how small variations in ionic currents and Ca2+ and Na+ diffusion coefficients impact action potential and Ca2+ dynamics in rabbit ventricular myocytes. We applied sensitivity analysis to quantify the sensitivity of Shannon et al. model (Biophys. J., 2004) to 5%–10% changes in currents conductance, channels distribution, and ion diffusion in rabbit ventricular cells. We found that action potential duration and Ca2+ peaks are highly sensitive to 10% increase in L-type Ca2+ current; moderately influenced by 10% increase in Na+-Ca2+ exchanger, Na+-K+ pump, rapid delayed and slow transient outward K+ currents, and Cl− background current; insensitive to 10% increases in all other ionic currents and sarcoplasmic reticulum Ca2+ fluxes. Cell electrical activity is strongly affected by 5% shift of L-type Ca2+ channels and Na+-Ca2+ exchanger in between junctional and submembrane spaces while Ca2+-activated Cl−-channel redistribution has the modest effect. Small changes in submembrane and cytosolic diffusion coefficients for Ca2+, but not in Na+ transfer, may alter notably myocyte contraction. Our studies highlight the need for more precise measurements and further extending and testing of the Shannon et al. model. Our results demonstrate usefulness of sensitivity analysis to identify specific knowledge gaps and controversies related to ventricular cell electrophysiology and Ca2+ signaling. PMID:24222910