25 resultados para Two-dimensional numerical simulation


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An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.

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In this work we present numerical simulations of continuous flow left ventricle assist device implantation with the aim of comparing difference in flow rates and pressure patterns depending on the location of the anastomosis and the rotational speed of the device. Despite the fact that the descending aorta anastomosis approach is less invasive, since it does not require a sternotomy and a cardiopulmonary bypass, its benefits are still controversial. Moreover, the device rotational speed should be correctly chosen to avoid anomalous flow rates and pressure distribution in specific location of the cardiovascular tree. With the aim of assessing the differences between these two approaches and device rotational speed in terms of flow rate and pressure waveforms, we set up numerical simulations of network of one-dimensional models where we account for the presence of an outflow cannula anastomosed to different locations of the aorta. Then, we use the resulting network to compare the results of the two different cannulations for several stages of heart failure and different rotational speed of the device. The inflow boundary data for the heart and the cannulas are obtained from a lumped parameters model of the entire circulatory system with an assist device, which is validated with clinical data. The results show that ascending and descending aorta cannulations lead to similar waveforms and mean flow rate in all the considered cases. Moreover, regardless of the anastomosis region, the rotational speed of the device has an important impact on wave profiles; this effect is more pronounced at high RPM.

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Gel electrophoresis allows one to separate knotted DNA (nicked circular) of equal length according to the knot type. At low electric fields, complex knots, being more compact, drift faster than simpler knots. Recent experiments have shown that the drift velocity dependence on the knot type is inverted when changing from low to high electric fields. We present a computer simulation on a lattice of a closed, knotted, charged DNA chain drifting in an external electric field in a topologically restricted medium. Using a Monte Carlo algorithm, the dependence of the electrophoretic migration of the DNA molecules on the knot type and on the electric field intensity is investigated. The results are in qualitative and quantitative agreement with electrophoretic experiments done under conditions of low and high electric fields.

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We have modeled numerically the seismic response of a poroelastic inclusion with properties applicable to an oil reservoir that interacts with an ambient wavefield. The model includes wave-induced fluid flow caused by pressure differences between mesoscopic-scale (i.e., in the order of centimeters to meters) heterogeneities. We used a viscoelastic approximation on the macroscopic scale to implement the attenuation and dispersion resulting from this mesoscopic-scale theory in numerical simulations of wave propagation on the kilometer scale. This upscaling method includes finite-element modeling of wave-induced fluid flow to determine effective seismic properties of the poroelastic media, such as attenuation of P- and S-waves. The fitted, equivalent, viscoelastic behavior is implemented in finite-difference wave propagation simulations. With this two-stage process, we model numerically the quasi-poroelastic wave-propagation on the kilometer scale and study the impact of fluid properties and fluid saturation on the modeled seismic amplitudes. In particular, we addressed the question of whether poroelastic effects within an oil reservoir may be a plausible explanation for low-frequency ambient wavefield modifications observed at oil fields in recent years. Our results indicate that ambient wavefield modification is expected to occur for oil reservoirs exhibiting high attenuation. Whether or not such modifications can be detected in surface recordings, however, will depend on acquisition design and noise mitigation processing as well as site-specific conditions, such as the geologic complexity of the subsurface, the nature of the ambient wavefield, and the amount of surface noise.

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Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.

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PURPOSE: To improve coronary magnetic resonance angiography (MRA) by combining a two-dimensional (2D) spatially selective radiofrequency (RF) pulse with a T2 -preparation module ("2D-T2 -Prep"). METHODS: An adiabatic T2 -Prep was modified so that the first and last pulses were of differing spatial selectivity. The first RF pulse was replaced by a 2D pulse, such that a pencil-beam volume is excited. The last RF pulse remains nonselective, thus restoring the T2 -prepared pencil-beam, while tipping the (formerly longitudinal) magnetization outside of the pencil-beam into the transverse plane, where it is then spoiled. Thus, only a cylinder of T2 -prepared tissue remains for imaging. Numerical simulations were followed by phantom validation and in vivo coronary MRA, where the technique was quantitatively evaluated. Reduced field-of-view (rFoV) images were similarly studied. RESULTS: In vivo, full field-of-view 2D-T2 -Prep significantly improved vessel sharpness as compared to conventional T2 -Prep, without adversely affecting signal-to-noise (SNR) or contrast-to-noise ratios (CNR). It also reduced respiratory motion artifacts. In rFoV images, the SNR, CNR, and vessel sharpness decreased, although scan time reduction was 60%. CONCLUSION: When compared with conventional T2 -Prep, the 2D-T2 -Prep improves vessel sharpness and decreases respiratory ghosting while preserving both SNR and CNR. It may also acquire rFoV images for accelerated data acquisition.

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Over the past decades, several sensitive post-electrophoretic stains have been developed for an identification of proteins in general, or for a specific detection of post-translational modifications such as phosphorylation, glycosylation or oxidation. Yet, for a visualization and quantification of protein differences, the differential two-dimensional gel electrophoresis, termed DIGE, has become the method of choice for a detection of differences in two sets of proteomes. The goal of this review is to evaluate the use of the most common non-covalent and covalent staining techniques in 2D electrophoresis gels, in order to obtain maximal information per electrophoresis gel and for an identification of potential biomarkers. We will also discuss the use of detergents during covalent labeling, the identification of oxidative modifications and review influence of detergents on finger prints analysis and MS/MS identification in relation to 2D electrophoresis.

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The choice of sample preparation protocol is a critical influential factor for isoelectric focusing which in turn affects the two-dimensional gel result in terms of quality and protein species distribution. The optimal protocol varies depending on the nature of the sample for analysis and the properties of the constituent protein species (hydrophobicity, tendency to form aggregates, copy number) intended for resolution. This review explains the standard sample buffer constituents and illustrates a series of protocols for processing diverse samples for two-dimensional gel electrophoresis, including hydrophobic membrane proteins. Current methods for concentrating lower abundance proteins, by removal of high abundance proteins, are also outlined. Finally, since protein staining is becoming increasingly incorporated into the sample preparation procedure, we describe the principles and applications of current (and future) pre-electrophoretic labelling methods.

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Several different sample preparation methods for two-dimensional electrophoresis (2-DE) analysis of Leishmania parasites were compared. From this work, we were able to identify a solubilization method using Nonidet P-40 as detergent, which was simple to follow, and which produced 2-DE gels of high resolution and reproducibility.

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In this study we have demonstrated the potential of two-dimensional electrophoresis (2DE)-based technologies as tools for characterization of the Leishmania proteome (the expressed protein complement of the genome). Standardized neutral range (pH 5-7) proteome maps of Leishmania (Viannia) guyanensis and Leishmania (Viannia) panamensis promastigotes were reproducibly generated by 2DE of soluble parasite extracts, which were prepared using lysis buffer containing urea and nonidet P-40 detergent. The Coomassie blue and silver nitrate staining systems both yielded good resolution and representation of protein spots, enabling the detection of approximately 800 and 1,500 distinct proteins, respectively. Several reference protein spots common to the proteomes of all parasite species/strains studied were isolated and identified by peptide mass spectrometry (LC-ES-MS/MS), and bioinformatics approaches as members of the heat shock protein family, ribosomal protein S12, kinetoplast membrane protein 11 and a hypothetical Leishmania-specific 13 kDa protein of unknown function. Immunoblotting of Leishmania protein maps using a monoclonal antibody resulted in the specific detection of the 81.4 kDa and 77.5 kDa subunits of paraflagellar rod proteins 1 and 2, respectively. Moreover, differences in protein expression profiles between distinct parasite clones were reproducibly detected through comparative proteome analyses of paired maps using image analysis software. These data illustrate the resolving power of 2DE-based proteome analysis. The production and basic characterization of good quality Leishmania proteome maps provides an essential first step towards comparative protein expression studies aimed at identifying the molecular determinants of parasite drug resistance and virulence, as well as discovering new drug and vaccine targets.

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An active strain formulation for orthotropic constitutive laws arising in cardiac mechanics modeling is introduced and studied. The passive mechanical properties of the tissue are described by the Holzapfel-Ogden relation. In the active strain formulation, the Euler-Lagrange equations for minimizing the total energy are written in terms of active and passive deformation factors, where the active part is assumed to depend, at the cell level, on the electrodynamics and on the specific orientation of the cardiac cells. The well-posedness of the linear system derived from a generic Newton iteration of the original problem is analyzed and different mechanical activation functions are considered. In addition, the active strain formulation is compared with the classical active stress formulation from both numerical and modeling perspectives. Taylor-Hood and MINI finite elements are employed to discretize the mechanical problem. The results of several numerical experiments show that the proposed formulation is mathematically consistent and is able to represent the main key features of the phenomenon, while allowing savings in computational costs.

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PURPOSE: At 7 Tesla (T), conventional static field (B0 ) projection mapping techniques, e.g., FASTMAP, FASTESTMAP, lead to elevated specific absorption rates (SAR), requiring longer total acquisition times (TA). In this work, the series of adiabatic pulses needed for slab selection in FASTMAP is replaced by a single two-dimensional radiofrequency (2D-RF) pulse to minimize TA while ensuring equal shimming performance. METHODS: Spiral gradients and 2D-RF pulses were designed to excite thin slabs in the small tip angle regime. The corresponding selection profile was characterized in phantoms and in vivo. After optimization of the shimming protocol, the spectral linewidths obtained after 2D localized shimming were compared with conventional techniques and published values from (Emir et al NMR Biomed 2012;25:152-160) in six different brain regions. RESULTS: Results on healthy volunteers show no significant difference (P > 0.5) between the spectroscopic linewidths obtained with the adiabatic (TA = 4 min) and the new low-SAR and time-efficient FASTMAP sequence (TA = 42 s). The SAR can be reduced by three orders of magnitude and TA accelerated six times without impact on the shimming performances or quality of the resulting spectra. CONCLUSION: Multidimensional pulses can be used to minimize the RF energy and time spent for automated shimming using projection mapping at high field. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

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Differential protein labeling with 2-DE separation is an effective method for distinguishing differences in the protein composition of two or more protein samples. Here, we report on a sensitive infrared-based labeling procedure, adding a novel tool to the many labeling possibilities. Defined amounts of newborn and adult mouse brain proteins and tubulin were exposed to maleimide-conjugated infrared dyes DY-680 and DY-780 followed by 1- and 2-DE. The procedure allows amounts of less than 5 microg of cysteine-labeled protein mixtures to be detected (together with unlabeled proteins) in a single 2-DE step with an LOD of individual proteins in the femtogram range; however, co-migration of unlabeled proteins and subsequent general protein stains are necessary for a precise comparison. Nevertheless, the most abundant thiol-labeled proteins, such as tubulin, were identified by MS, with cysteine-containing peptides influencing the accuracy of the identification score. Unfortunately, some infrared-labeled proteins were no longer detectable by Western blots. In conclusion, differential thiol labeling with infrared dyes provides an additional tool for detection of low-abundant cysteine-containing proteins and for rapid identification of differences in the protein composition of two sets of protein samples.