Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

Connectivity analysis on diffusion MRI data of the whole-brain suffers from distortions caused by the standard echo-planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a “theoretically correct” and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.

Diffusion of nitric oxide can facilitate cerebellar learning: A simulation study

The gaseous second messenger nitric oxide (NO), which readily diffuses in brain tissue, has been implicated in cerebellar long-term depression (LTD), a form of synaptic plasticity thought to be involved in cerebellar learning. Can NO diffusion facilitate cerebellar learning? The inferior olive (IO) cells, which provide the error signals necessary for modifying the granule cell–Purkinje cell (PC) synapses by LTD, fire at ultra-low firing rates in vivo, rarely more than 2–4 spikes within a second. In this paper, we show that NO diffusion can improve the transmission of sporadic IO error signals to PCs within cerebellar cortical functional units, or microzones. To relate NO diffusion to adaptive behavior, we add NO diffusion and a “volumic” LTD learning rule, i.e., a learning rule that depends both on the synaptic activity and on the NO concentration at the synapse, to a cerebellar model for arm movement control. Our results show that biologically plausible diffusion leads to an increase in information transfer of the error signals to the PCs when the IO firing rate is ultra-low. This, in turn, enhances cerebellar learning as shown by improved performance in an arm-reaching task.

Ligand diffusion on protein surface observed in molecular dynamics simulation

The process of binding of small ligands to dihydrofolate reductase protein has been investigated using all-atom molecular dynamics simulations. The existence of a mechanism that facilitates the search of the binding site by the ligand is demonstrated. The mechanism consists of ligand diffusing on the protein’s surface. It has been discussed in the literature before, but has not been explicitly confirmed for realistic molecular systems. The strength of this nonspecific binding is roughly estimated and found to be essential for the binding kinetics.

Opinion leaders' role in innovation diffusion:a simulation study

This study investigates the critical role that opinion leaders (or influentials) play in the adoption process of new products. Recent existing reseach evidence indicates a limited effect of opinion leaders on diffusion processes, yet these studies take into account merely the network position of opinion leaders without addressing their influential power. Empirical findings of our study show that opinion leaders, in addition to having a more central network position, possess more accurate knowledge about a product and tend to be less susceptible to norms and more innovative. Experiments that address these attributes, using an agent-based model, demonstrate that opinion leaders increase the speed of the information stream and the adoption process itself. Furthermore, they increase the maximum adoption percentage. These results indicate that targeting opinion leaders remains a valuable marketing strategy.

Reaction-diffusion stochastic lattice model for a predator-prey system

We have the purpose of analyzing the effect of explicit diffusion processes in a predator-prey stochastic lattice model. More precisely we wish to investigate the possible effects due to diffusion upon the thresholds of coexistence of species, i. e., the possible changes in the transition between the active state and the absorbing state devoid of predators. To accomplish this task we have performed time dependent simulations and dynamic mean-field approximations. Our results indicate that the diffusive process can enhance the species coexistence.

Molecular dynamics simulation of liquid trimethylphosphine

Structural and dynamical properties of liquid trimethylphosphine (TMP), (CH(3))(3)P, as a function of temperature is investigated by molecular dynamics (MD) simulations. The force field used in the MD simulations, which has been proposed from molecular mechanics and quantum chemistry calculations, is able to reproduce the experimental density of liquid TMP at room temperature. Equilibrium structure is investigated by the usual radial distribution function, g(r), and also in the reciprocal space by the static structure factor, S(k). On the basis of center of mass distances, liquid TMP behaves like a simple liquid of almost spherical particles, but orientational correlation due to dipole-dipole interactions is revealed at short-range distances. Single particle and collective dynamics are investigated by several time correlation functions. At high temperatures, diffusion and reorientation occur at the same time range as relaxation of the liquid structure. Decoupling of these dynamic properties starts below ca. 220 K, when rattling dynamics of a given TMP molecules due to the cage effect of neighbouring molecules becomes important. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3624408]

Experimental Measurement of Water Diffusion through Fine Aggregate Mixtures

The water diffusion attributable to concentration gradients is among the main mechanisms of water transport into the asphalt mixture. The transport of small molecules through polymeric materials is a very complex process, and no single model provides a complete explanation because of the small molecule`s complex internal structure. The objective of this study was to experimentally determine the diffusion of water in different fine aggregate mixtures (FAM) using simple gravimetric sorption measurements. For the purposes of measuring the diffusivity of water, FAMs were regarded as a representative homogenous volume of the hot-mix asphalt (HMA). Fick`s second law is generally used to model diffusion driven by concentration gradients in different materials. The concept of the dual mode diffusion was investigated for FAM cylindrical samples. Although FAM samples have three components (asphalt binder, aggregates, and air voids), the dual mode was an attempt to represent the diffusion process by only two stages that occur simultaneously: (1) the water molecules are completely mobile, and (2) the water molecules are partially mobile. The combination of three asphalt binders and two aggregates selected from the Strategic Highway Research Program`s (SHRP) Materials Reference Library (MRL) were evaluated at room temperature [23.9 degrees C (75 degrees F)] and at 37.8 degrees C (100 degrees F). The results show that moisture uptake and diffusivity of water through FAM is dependent on the type of aggregate and asphalt binder. At room temperature, the rank order of diffusivity and moisture uptake for the three binders was the same regardless of the type of aggregate. However, this rank order changed at higher temperatures, suggesting that at elevated temperatures different binders may be undergoing a different level of change in the free volume. DOI: 10.1061/(ASCE)MT.1943-5533.0000190. (C) 2011 American Society of Civil Engineers.

Flow and axial dispersion simulation for traveling axisymmetric Taylor vortices

Numerical experiments using a finite difference method were carried out to determine the motion of axisymmetric Taylor vortices for narrow-gap Taylor vortex flow. When a pressure gradient is imposed on the flow the vortices are observed to move with an axial speed of 1.16 +/- 0.005 times the mean axial flow velocity. The method of Brenner was used to calculate the long-time axial spread of material in the flow. For flows where there is no pressure gradient, the axial dispersion scales with the square root of the molecular diffusion, in agreement with the results of Rosen-bluth et al. for high Peclet number dispersion in spatially periodic flows with a roll structure. When a pressure gradient is imposed the dispersion increases by an amount approximately equal to 6.5 x 10(-4) (W) over bar(2)d(2)/D-m, where (W) over bar is the average axial velocity in the annulus, analogous to Taylor dispersion for laminar flow in an empty tube.

Thermal diffusion in molecular dynamics simulations of thin film diamond deposition

Molecular dynamics simulations of carbon atom depositions are used to investigate energy diffusion from the impact zone. A modified Stillinger-Weber potential models the carbon interactions for both sp2 and sp3 bonding. Simulations were performed on 50 eV carbon atom depositions onto the (111) surface of a 3.8 x 3.4 x 1.0 nm diamond slab containing 2816 atoms in 11 layers of 256 atoms each. The bottom layer was thermostated to 300 K. At every 100th simulation time step (27 fs), the average local kinetic energy, and hence local temperature, is calculated. To do this the substrate is divided into a set of 15 concentric hemispherical zones, each of thickness one atomic diameter (0.14 nm) and centered on the impact point. A 50-eV incident atom heats the local impact zone above 10 000 K. After the initial large transient (200 fs) the impact zone has cooled below 3000 K, then near 1000 K by 1 ps. Thereafter the temperature profile decays approximately as described by diffusion theory, perturbed by atomic scale fluctuations. A continuum model of classical energy transfer is provided by the traditional thermal diffusion equation. The results show that continuum diffusion theory describes well energy diffusion in low energy atomic deposition processes, at distance and time scales larger than 1.5 nm and 1-2 ps, beyond which the energy decays essentially exponentially. (C) 1998 Published by Elsevier Science S.A. All rights reserved.

Numerical simulation of dendrite growth during solidification

A comprehensive probabilistic model for simulating dendrite morphology and investigating dendritic growth kinetics during solidification has been developed, based on a modified Cellular Automaton (mCA) for microscopic modeling of nucleation, growth of crystals and solute diffusion. The mCA model numerically calculated solute redistribution both in the solid and liquid phases, the curvature of dendrite tips and the growth anisotropy. This modeling takes account of thermal, curvature and solute diffusion effects. Therefore, it can simulate microstructure formation both on the scale of the dendrite tip length. This model was then applied for simulating dendritic solidification of an Al-7%Si alloy. Both directional and equiaxed dendritic growth has been performed to investigate the growth anisotropy and cooling rate on dendrite morphology. Furthermore, the competitive growth and selection of dendritic crystals have also investigated.

An atomistic simulation of solid state sintering using Monte Carlo methods

This paper presents results on the simulation of the solid state sintering of copper wires using Monte Carlo techniques based on elements of lattice theory and cellular automata. The initial structure is superimposed onto a triangular, two-dimensional lattice, where each lattice site corresponds to either an atom or vacancy. The number of vacancies varies with the simulation temperature, while a cluster of vacancies is a pore. To simulate sintering, lattice sites are picked at random and reoriented in terms of an atomistic model governing mass transport. The probability that an atom has sufficient energy to jump to a vacant lattice site is related to the jump frequency, and hence the diffusion coefficient, while the probability that an atomic jump will be accepted is related to the change in energy of the system as a result of the jump, as determined by the change in the number of nearest neighbours. The jump frequency is also used to relate model time, measured in Monte Carlo Steps, to the actual sintering time. The model incorporates bulk, grain boundary and surface diffusion terms and includes vacancy annihilation on the grain boundaries. The predictions of the model were found to be consistent with experimental data, both in terms of the microstructural evolution and in terms of the sintering time. (C) 2002 Elsevier Science B.V. All rights reserved.

Analysis of diffusion process in fractured reservoirs using fractional derivative approach

The fractal geometry is used to model of a naturally fractured reservoir and the concept of fractional derivative is applied to the diffusion equation to incorporate the history of fluid flow in naturally fractured reservoirs. The resulting fractally fractional diffusion (FFD) equation is solved analytically in the Laplace space for three outer boundary conditions. The analytical solutions are used to analyze the response of a naturally fractured reservoir considering the anomalous behavior of oil production. Several synthetic examples are provided to illustrate the methodology proposed in this work and to explain the diffusion process in fractally fractured systems.

Numerical methods and tangible interfaces for pollutant dispersion simulation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia do Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Simulation of humidity fields in concrete: experimental validation and parameter estimation

The moisture content in concrete structures has an important influence in their behavior and performance. Several vali-dated numerical approaches adopt the governing equation for relative humidity fields proposed in Model Code 1990/2010. Nevertheless there is no integrative study which addresses the choice of parameters for the simulation of the humidity diffusion phenomenon, particularly in concern to the range of parameters forwarded by Model Code 1990/2010. A software based on a Finite Difference Method Algorithm (1D and axisymmetric cases) is used to perform sensitivity analyses on the main parameters in a normal strength concrete. Then, based on the conclusions of the sensi-tivity analyses, experimental results from nine different concrete compositions are analyzed. The software is used to identify the main material parameters that better fit the experimental data. In general, the model was able to satisfactory fit the experimental results and new correlations were proposed, particularly focusing on the boundary transfer coeffi-cient.

Semidiscretization and long-time asymptotics of nonlinear diffusion equations

We review several results concerning the long time asymptotics of nonlinear diffusion models based on entropy and mass transport methods. Semidiscretization of these nonlinear diffusion models are proposed and their numerical properties analysed. We demonstrate the long time asymptotic results by numerical simulation and we discuss several open problems based on these numerical results. We show that for general nonlinear diffusion equations the long-time asymptotics can be characterized in terms of fixed points of certain maps which are contractions for the euclidean Wasserstein distance. In fact, we propose a new scaling for which we can prove that this family of fixed points converges to the Barenblatt solution for perturbations of homogeneous nonlinearities for values close to zero.