58 resultados para Time-Fractional Multiterm Diffusion Equation
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The aim of this review paper is to present experimental methodologies and the mathematical approaches used to determine effective diffusivities of solutes in food materials. The paper commences by describing the diffusion phenomena related to solute mass transfer in foods and effective diffusivities. It then focuses on the mathematical formulation for the calculation of effective diffusivities considering different diffusion models based on Fick's second law of diffusion. Finally, experimental considerations for effective diffusivity determination are elucidated primarily based on the acquirement of a series of solute content versus time curves appropriate to the equation model chosen. Different factors contributing to the determination of the effective diffusivities such as the structure of food material, temperature, diffusion solvent, agitation, sampling, concentration and different techniques used are considered. (c) 2005 Elsevier Inc. All rights reserved.
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An information processing paradigm in the brain is proposed, instantiated in an artificial neural network using biologically motivated temporal encoding. The network will locate within the external world stimulus, the target memory, defined by a specific pattern of micro-features. The proposed network is robust and efficient. Akin in operation to the swarm intelligence paradigm, stochastic diffusion search, it will find the best-fit to the memory with linear time complexity. information multiplexing enables neurons to process knowledge as 'tokens' rather than 'types'. The network illustrates possible emergence of cognitive processing from low level interactions such as memory retrieval based on partial matching. (C) 2007 Elsevier B.V. All rights reserved.
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The current study aims to assess the applicability of direct or indirect normalization for the analysis of fractional anisotropy (FA) maps in the context of diffusion-weighted images (DWIs) contaminated by ghosting artifacts. We found that FA maps acquired by direct normalization showed generally higher anisotropy than indirect normalization, and the disparities were aggravated by the presence of ghosting artifacts in DWIs. The voxel-wise statistical comparisons demonstrated that indirect normalization reduced the influence of artifacts and enhanced the sensitivity of detecting anisotropy differences between groups. This suggested that images contaminated with ghosting artifacts can be sensibly analyzed using indirect normalization.
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In recent years nonpolynomial finite element methods have received increasing attention for the efficient solution of wave problems. As with their close cousin the method of particular solutions, high efficiency comes from using solutions to the Helmholtz equation as basis functions. We present and analyze such a method for the scattering of two-dimensional scalar waves from a polygonal domain that achieves exponential convergence purely by increasing the number of basis functions in each element. Key ingredients are the use of basis functions that capture the singularities at corners and the representation of the scattered field towards infinity by a combination of fundamental solutions. The solution is obtained by minimizing a least-squares functional, which we discretize in such a way that a matrix least-squares problem is obtained. We give computable exponential bounds on the rate of convergence of the least-squares functional that are in very good agreement with the observed numerical convergence. Challenging numerical examples, including a nonconvex polygon with several corner singularities, and a cavity domain, are solved to around 10 digits of accuracy with a few seconds of CPU time. The examples are implemented concisely with MPSpack, a MATLAB toolbox for wave computations with nonpolynomial basis functions, developed by the authors. A code example is included.
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Time-resolved studies of germylene, GeH2, generated by laser. ash photolysis of 3,4-dimethyl-1-germacyclopent-3-ene, have been carried out to obtain rate coefficients for its bimolecular reaction with C2D2. The reaction was studied in the gas phase, mainly at a total pressure of 1.3 kPa (in SF6 bath gas) at five temperatures in the range 298-558 K. Pressure variation measurements over the range 0.13-13 kPa ( SF6) at 298, 397 and 558 K revealed a small pressure dependence but only at 558 K. After correction for this, the second-order rate coefficients gave the Arrhenius equation: log(k(infinity)/cm(3) molecule(-1) s(-1)) = (-10.96 +/- 0.05) + ( 6.16 +/- 0.37 kJ mol(-1))/RT ln 10 Comparison with the reaction of GeH2 + C2H2 (studied earlier) showed a similar behaviour with almost identical rate coefficients. The lack of a significant isotope effect is consistent with a rate-determining addition process and is explained by irreversible decomposition of the reaction intermediate to give Ge(P-3) + C2H4. This result contrasts with that for GeH2 + C2H4/C2D4 and those for the analogous silylene reactions. The underlying reasons for this are discussed.
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Time-resolved kinetic studies of the reaction of germylene, GeH2, generated by laser. ash photolysis of 3,4-dimethyl-1-germacyclopent-3-ene, have been carried out to obtain rate constants for its bimolecular reaction with 2-butyne, CH3C CCH3. The reaction was studied in the gas phase over the pressure range 1-100 Torr in SF6 bath gas, at five temperatures in the range 300-556 K. The second order rate constants obtained by extrapolation to the high pressure limits at each temperature, fitted the Arrhenius equation: log(k(infinity)/cm(3) molecule(-1) s(-1)) = (-10.46 +/- 10.06) + (5.16 +/- 10.47) kJ mol(-1)/ RT ln 10 Calculations of the energy surface of the GeC4H8 reaction system were carried out employing the additivity principle, by combining previous quantum chemical calculations of related reaction systems. These support formation of 1,2-dimethylvinylgermylene (rather than 2,3-dimethylgermirene) as the end product. RRKM calculations of the pressure dependence of the reaction are in reasonable agreement with this finding. The reactions of GeH2 with C2H2 and with CH3CRCCH3 are compared and contrasted.
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Laser flash photolysis studies of silylene, SiH2, generated by the 193 nm laser flash photolysis phenylsilane, PhSiH3, have been carried out to obtain rate constants for its bimolecular reaction with PhSiH3 itself, in the gas phase. The reaction was studied in SF6 (mostly at 10 Torr total pressure) over the temperature range 298-595 K. The rate constants (also found to be pressure independent) gave the following Arrhenius equation: log(k/cm(3) molecule(-1) s(-1)) = (-9.92 +/- 0.04) + (3.31 +/- 0.27) kJ mol(-1)/RT ln 10 Similar investigations of the reaction of silylene with benzene, C6H6, (295-410 K) gave data suggestive of the fact that SiH2 might be reacting with photochemical products of C6H6 as well as with C6H6 itself. However, in the latter system, apparent rate constants were sufficiently low to indicate that in the reaction of SiH2 with PhSiH3 addition to the aromatic ring was unlikely to be in excess of 3% of the total. Quantum chemical calculations of the energy surface for SiH2 + C6H6 indicate that 7-silanorcaradiene and 7-silacycloheptatriene are possible products but that PhSiH3 formation is unlikely. RRKM calculations suggest that 7-silanorcaradiene should be the initial product but that it cannot be collisionally stabilized under experimental conditions
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The Stochastic Diffusion Search (SDS) was developed as a solution to the best-fit search problem. Thus, as a special case it is capable of solving the transform invariant pattern recognition problem. SDS is efficient and, although inherently probabilistic, produces very reliable solutions in widely ranging search conditions. However, to date a systematic formal investigation of its properties has not been carried out. This thesis addresses this problem. The thesis reports results pertaining to the global convergence of SDS as well as characterising its time complexity. However, the main emphasis of the work, reports on the resource allocation aspect of the Stochastic Diffusion Search operations. The thesis introduces a novel model of the algorithm, generalising an Ehrenfest Urn Model from statistical physics. This approach makes it possible to obtain a thorough characterisation of the response of the algorithm in terms of the parameters describing the search conditions in case of a unique best-fit pattern in the search space. This model is further generalised in order to account for different search conditions: two solutions in the search space and search for a unique solution in a noisy search space. Also an approximate solution in the case of two alternative solutions is proposed and compared with predictions of the extended Ehrenfest Urn model. The analysis performed enabled a quantitative characterisation of the Stochastic Diffusion Search in terms of exploration and exploitation of the search space. It appeared that SDS is biased towards the latter mode of operation. This novel perspective on the Stochastic Diffusion Search lead to an investigation of extensions of the standard SDS, which would strike a different balance between these two modes of search space processing. Thus, two novel algorithms were derived from the standard Stochastic Diffusion Search, ‘context-free’ and ‘context-sensitive’ SDS, and their properties were analysed with respect to resource allocation. It appeared that they shared some of the desired features of their predecessor but also possessed some properties not present in the classic SDS. The theory developed in the thesis was illustrated throughout with carefully chosen simulations of a best-fit search for a string pattern, a simple but representative domain, enabling careful control of search conditions.
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This paper first points out the important fact that the rectangle formulas of continuous convolution discretization, which was widely used in conventional digital deconvolution algorithms, can result in zero-time error. Then, an improved digital deconvolution equation is suggested which is equivalent to the trapezoid formulas of continuous convolution discretization and can overcome the disadvantage of conventional equation satisfactorily. Finally, a simulation in computer is given, thus confirming the theoretical result.
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We study the heat, linear Schrodinger and linear KdV equations in the domain l(t) < x < ∞, 0 < t < T, with prescribed initial and boundary conditions and with l(t) a given differentiable function. For the first two equations, we show that the unknown Neumann or Dirichlet boundary value can be computed as the solution of a linear Volterra integral equation with an explicit weakly singular kernel. This integral equation can be derived from the formal Fourier integral representation of the solution. For the linear KdV equation we show that the two unknown boundary values can be computed as the solution of a system of linear Volterra integral equations with explicit weakly singular kernels. The derivation in this case makes crucial use of analyticity and certain invariance properties in the complex spectral plane. The above Volterra equations are shown to admit a unique solution.
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Using grand canonical Monte Carlo simulation we show, for the first time, the influence of the carbon porosity and surface oxidation on the parameters of the Dubinin-Astakhov (DA) adsorption isotherm equation. We conclude that upon carbon surface oxidation, the adsorption decreases for all carbons studied. Moreover, the parameters of the DA model depend on the number of surface oxygen groups. That is why in the case of carbons containing surface polar groups, SF(6) adsorption isotherm data cannot be used for characterization of the porosity.
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Creep and stress relaxation are inherent mechanical behaviors of viscoelastic materials. It is considered that both are different performances of one identical physical phenomenon. The relationship between the decay stress and time during stress relaxation has been derived from the power law equation of the steady-state creep. The model was used to analyse the stress relaxation curves of various different viscoelastic materials (such as pure polycrystalline ice, polymers, foods, bones, metal, animal tissues, etc.). The calculated results using the theoretical model agree with the experimental data very well. Here we show that the new mathematical formula is not only simple but its parameters have the clear physical meanings. It is suitable to materials with a very broad scope and has a strong predictive ability.
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The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.
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In this paper, we extend to the time-harmonic Maxwell equations the p-version analysis technique developed in [R. Hiptmair, A. Moiola and I. Perugia, Plane wave discontinuous Galerkin methods for the 2D Helmholtz equation: analysis of the p-version, SIAM J. Numer. Anal., 49 (2011), 264-284] for Trefftz-discontinuous Galerkin approximations of the Helmholtz problem. While error estimates in a mesh-skeleton norm are derived parallel to the Helmholtz case, the derivation of estimates in a mesh-independent norm requires new twists in the duality argument. The particular case where the local Trefftz approximation spaces are built of vector-valued plane wave functions is considered, and convergence rates are derived.