1000 resultados para VOF method


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The cis/trans isomer ratios of the Xaa-Pyr (Pyr = pyrrolidine) 3 degrees amide bonds are significantly high (similar to 90% cis) in the novel peptidomimetics where Pyr contains 1,3-oxazine (Oxa) or 1,3-thiazine (Thi) at its 2 position. We find that an unusual n -> pi(i-1)* interaction, selectively stabilizes the cis conformer and the n X n repulsion destabilizes the trans conformer of these molecules. Both these electronic effects oppose the steric effects in the 3 degrees amide bond. The structural requirements for manifestation of these electronic effects are determined. (c) 2012 Elsevier Ltd. All rights reserved.

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Background: There has been growing interest in integrative taxonomy that uses data from multiple disciplines for species delimitation. Typically, in such studies, monophyly is taken as a proxy for taxonomic distinctiveness and these units are treated as potential species. However, monophyly could arise due to stochastic processes. Thus here, we have employed a recently developed tool based on coalescent approach to ascertain the taxonomic distinctiveness of various monophyletic units. Subsequently, the species status of these taxonomic units was further tested using corroborative evidence from morphology and ecology. This inter-disciplinary approach was implemented on endemic centipedes of the genus Digitipes (Attems 1930) from the Western Ghats (WG) biodiversity hotspot of India. The species of the genus Digitipes are morphologically conserved, despite their ancient late Cretaceous origin. Principal Findings: Our coalescent analysis based on mitochondrial dataset indicated the presence of nine putative species. The integrative approach, which includes nuclear, morphology, and climate datasets supported distinctiveness of eight putative species, of which three represent described species and five were new species. Among the five new species, three were morphologically cryptic species, emphasizing the effectiveness of this approach in discovering cryptic diversity in less explored areas of the tropics like the WG. In addition, species pairs showed variable divergence along the molecular, morphological and climate axes. Conclusions: A multidisciplinary approach illustrated here is successful in discovering cryptic diversity with an indication that the current estimates of invertebrate species richness for the WG might have been underestimated. Additionally, the importance of measuring multiple secondary properties of species while defining species boundaries was highlighted given variable divergence of each species pair across the disciplines.

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A novel method is proposed for fracture toughness determination of graded microstructurally complex (Pt,Ni)Al bond coats using edge-notched doubly clamped beams subjected to bending. Micron-scale beams are machined using the focused ion beam and loaded in bending under a nanoindenter. Failure loads gathered from the pop-ins in the load-displacement curves combined with XFEM analysis are used to calculate K-c at individual zones, free from substrate effects. The testing technique and sources of errors in measurement are described and possible micromechanisms of fracture in such heterogeneous coatings discussed.

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A novel approach that can more effectively use the structural information provided by the traditional imaging modalities in multimodal diffuse optical tomographic imaging is introduced. This approach is based on a prior image-constrained-l(1) minimization scheme and has been motivated by the recent progress in the sparse image reconstruction techniques. It is shown that the proposed framework is more effective in terms of localizing the tumor region and recovering the optical property values both in numerical and gelatin phantom cases compared to the traditional methods that use structural information. (C) 2012 Optical Society of America

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The inverse problem in the diffuse optical tomography is known to be nonlinear, ill-posed, and sometimes under-determined, requiring regularization to obtain meaningful results, with Tikhonov-type regularization being the most popular one. The choice of this regularization parameter dictates the reconstructed optical image quality and is typically chosen empirically or based on prior experience. An automated method for optimal selection of regularization parameter that is based on regularized minimal residual method (MRM) is proposed and is compared with the traditional generalized cross-validation method. The results obtained using numerical and gelatin phantom data indicate that the MRM-based method is capable of providing the optimal regularization parameter. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). DOI: 10.1117/1.JBO.17.10.106015]

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Traditional image reconstruction methods in rapid dynamic diffuse optical tomography employ l(2)-norm-based regularization, which is known to remove the high-frequency components in the reconstructed images and make them appear smooth. The contrast recovery in these type of methods is typically dependent on the iterative nature of method employed, where the nonlinear iterative technique is known to perform better in comparison to linear techniques (noniterative) with a caveat that nonlinear techniques are computationally complex. Assuming that there is a linear dependency of solution between successive frames resulted in a linear inverse problem. This new framework with the combination of l(1)-norm based regularization can provide better robustness to noise and provide better contrast recovery compared to conventional l(2)-based techniques. Moreover, it is shown that the proposed l(1)-based technique is computationally efficient compared to its counterpart (l(2)-based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame, and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames.

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We develop a quadratic C degrees interior penalty method for linear fourth order boundary value problems with essential and natural boundary conditions of the Cahn-Hilliard type. Both a priori and a posteriori error estimates are derived. The performance of the method is illustrated by numerical experiments.

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This paper presents the details of nonlinear finite element analysis (FEA) of three point bending specimens made up of high strength concrete (HSC, HSC1) and ultra high strength concrete (UHSC). Brief details about characterization and experimentation of HSC, HSC1 and UHSC have been provided. Cracking strength criterion has been used for simulation of crack propagation by conducting nonlinear FEA. The description about FEA using crack strength criterion has been outlined. Bi-linear tension softening relation has been used for modeling the cohesive stresses ahead of the crack tip. Numerical studies have been carried out on fracture analysis of three point bending specimens. It is observed from the studies that the computed values from FEA are in very good agreement with the corresponding experimental values. The computed values of stress vs crack width will be useful for evaluation of fracture energy, crack tip opening displacement and fracture toughness. Further, these values can also be used for crack growth study, remaining life assessment and residual strength evaluation of concrete structural components.

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The Turkevich-Frens synthesis starting conditions are expanded, ranging the gold salt concentrations up to 2 mM and citrate/gold(III) molar ratios up to 18:1. For each concentration of the initial gold salt solution, the citrate/gold(III) molar ratios are systematically varied from 2:1 to 18:1 and both the size and size distribution of the resulting gold nanoparticles are compared. This study reveals a different nanoparticle size evolution for gold salt solutions ranging below 0.8 mM compared to the case of gold salt solutions above 0.8 mM. In the case of Au3+]<0.8 mM, both the size and size distribution vary substantially with the citrate/gold(III) ratio, both displaying plateaux that evolve inversely to Au3+] at larger ratios. Conversely, for Au3+]>= 0.8 mM, the size and size distribution of the synthesized gold nanoparticles continuously rise as the citrate/gold(III) ratio is increased. A starting gold salt concentration of 0.6 mM leads to the formation of the most monodisperse gold nanoparticles (polydispersity index<0.1) for a wide range of citrate/gold(III) molar ratios (from 4:1 to 18:1). Via a model for the formation of gold nanoparticles by the citrate method, the experimental trends in size could be qualitatively predicted:the simulations showed that the destabilizing effect of increased electrolyte concentration at high initial Au3+] is compensated by a slight increase in zeta potential of gold nanoparticles to produce concentrated dispersion of gold nanoparticles of small sizes.

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Error analysis for a stable C (0) interior penalty method is derived for general fourth order problems on polygonal domains under minimal regularity assumptions on the exact solution. We prove that this method exhibits quasi-optimal order of convergence in the discrete H (2), H (1) and L (2) norms. L (a) norm error estimates are also discussed. Theoretical results are demonstrated by numerical experiments.

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Surface electrodes are essentially required to be switched for boundary data collection in electrical impedance tomography (Ell). Parallel digital data bits are required to operate the multiplexers used, generally, for electrode switching in ELT. More the electrodes in an EIT system more the digital data bits are needed. For a sixteen electrode system. 16 parallel digital data bits are required to operate the multiplexers in opposite or neighbouring current injection method. In this paper a common ground current injection is proposed for EIT and the resistivity imaging is studied. Common ground method needs only two analog multiplexers each of which need only 4 digital data bits and hence only 8 digital bits are required to switch the 16 surface electrodes. Results show that the USB based data acquisition system sequentially generate digital data required for multiplexers operating in common ground current injection method. The profile of the boundary data collected from practical phantom show that the multiplexers are operating in the required sequence in common ground current injection protocol. The voltage peaks obtained for all the inhomogeneity configurations are found at the accurate positions in the boundary data matrix which proved the sequential operation of multiplexers. Resistivity images reconstructed from the boundary data collected from the practical phantom with different configurations also show that the entire digital data generation module is functioning properly. Reconstructed images and their image parameters proved that the boundary data are successfully acquired by the DAQ system which in turn indicates a sequential and proper operation of multiplexers.

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The solvated metal atom dispersion (SMAD) method has been used for the synthesis of colloids of metal nanoparticles. It is a top-down approach involving condensation of metal atoms in low temperature solvent matrices in a SMAD reactor maintained at 77 K. Warming of the matrix results in a slurry of metal atoms that interact with one another to form particles that grow in size. The organic solvent solvates the particles and acts as a weak capping agent to halt/slow down the growth process to a certain extent. This as-prepared colloid consists of metal nanoparticles that are quite polydisperse. In a process termed as digestive ripening, addition of a capping agent to the as-prepared colloid which is polydisperse renders it highly monodisperse either under ambient or thermal conditions. In this, as yet not well-understood process, smaller particles grow and the larger ones diminish in size until the system attains uniformity in size and a dynamic equilibrium is established. Using the SMAD method in combination with digestive ripening process, highly monodisperse metal, core-shell, alloy, and composite nanoparticles have been synthesized. This article is a review of our contributions together with some literature reports on this methodology to realize various nanostructured materials.

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A combination of chemical and thermal annealing techniques has been employed to synthesize a rarely reported nanocup structure of Mn doped ZnO with good yield. Nanocup structures are obtained by thermally annealing the powder samples consisting of nanosheets, synthesized chemically at room temperature, isochronally in a furnace at 200-500 degrees C temperature range for 2 h. Strong excitonic absorption in the UV and photoluminescence (PL) emission in UV-visible regions are observed in all the samples at room temperature. The sample obtained at 300 degrees C annealing temperature exhibits strong PL emission in the UV due to near-band-edge emission along with very week defect related emissions in the visible regions. The synthesized samples have been found to be exhibiting stable optical properties for 10 months which proved the unique feature of the presented technique of synthesis of nanocup structures. (C) 2012 Elsevier B.V. All rights reserved.

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In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to compu- tational biology or computer vision and have been tackled using algorithms, referred to as structured output learning algorithms. We consider the problem of structured classifi- cation. In the last few years, large margin classifiers like sup-port vector machines (SVMs) have shown much promise for structured output learning. The related optimization prob -lem is a convex quadratic program (QP) with a large num-ber of constraints, which makes the problem intractable for large data sets. This paper proposes a fast sequential dual method (SDM) for structural SVMs. The method makes re-peated passes over the training set and optimizes the dual variables associated with one example at a time. The use of additional heuristics makes the proposed method more efficient. We present an extensive empirical evaluation of the proposed method on several sequence learning problems.Our experiments on large data sets demonstrate that the proposed method is an order of magnitude faster than state of the art methods like cutting-plane method and stochastic gradient descent method (SGD). Further, SDM reaches steady state generalization performance faster than the SGD method. The proposed SDM is thus a useful alternative for large scale structured output learning.

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With the rapid scaling down of the semiconductor process technology, the process variation aware circuit design has become essential today. Several statistical models have been proposed to deal with the process variation. We propose an accurate BSIM model for handling variability in 45nm CMOS technology. The MOSFET is designed to meet the specification of low standby power technology of International Technology Roadmap for Semiconductors (ITRS).The process parameters variation of annealing temperature, oxide thickness, halo dose and title angle of halo implant are considered for the model development. One parameter variation at a time is considered for developing the model. The model validation is done by performance matching with device simulation results and reported error is less than 10%.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.