975 resultados para charged particle Brownian motion


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We revisit the rare kaon decays K -> pi l(+)l(-) which are of special interest due to the recent measurements of the charged kaon decay spectra. We compute the contribution of the 27-plet to the decay amplitudes in one loop SU(3) chiral perturbation theory. We estimate the resulting impact to be similar to 10% to the branching ratios of the charged kaon decays, and also noticeably influence the shape of the spectra. With current values of the constants G(8) associated with the octet and G(27) associated with the 27-plet, the contribution of the latter pushes the spectrum in the correct direction, towards the charged lepton spectra. We also discuss the impact for neutral decay rates and spectra.

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In this work, we analyze the directional movement of impacting liquid drops on dual-textured solid surfaces comprising two different surface morphologies: a textured surface and a smooth surface. The dynamics of liquid drops impacting onto the junction line between the two parts of the dual-textured surfaces is studied experimentally for varying drop impact velocity. The dual-textured surfaces used here featured a variation in their textures' geometrical parameters as well as their surface chemistry. Two types of liquid drop differing in their surface tension were used. The impact process develops a net horizontal drop velocity towards the higher-wettability surface portion and results in a bulk movement of the impacting drop liquid. The final distance moved by the impacting drop from the junction line decreases with increasing impacting drop Weber number We. A fully theoretical model, employing a balance of forces acting at the drop contact line as well as energy conservation, is formulated to determine the variation, with We, of net horizontal drop velocity and subsequent movement of the impacting drop on the dual-textured surfaces.

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Small quantity of energetic material coated on the inner wall of a polymer tube is proposed as a new method to generate micro-shock waves in the laboratory. These micro-shock waves have been harnessed to develop a novel method of delivering dry particle and liquid jet into the target. We have generated micro-shock waves with the help of reactive explosive compound high melting explosive (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) and traces of aluminium] coated polymer tube, utilising 9 J of energy. The detonation process is initiated electrically from one end of the tube, while the micro-shock wave followed by the products of detonation escape from the open end of the polymer tube. The energy available at the open end of the polymer tube is used to accelerate tungsten micro-particles coated on the other side of the diaphragm or force a liquid jet out of a small cavity filled with the liquid. The micro-particles deposited on a thin metal diaphragm (typically 100-mu m thick) were accelerated to high velocity using micro-shock waves to penetrate the target. Tungsten particles of 0.7 mu m diameter have been successfully delivered into agarose gel targets of various strengths (0.6-1.0 %). The device has been tested by delivering micro-particles into potato tuber and Arachis hypogaea Linnaeus (ground nut) stem tissue. Along similar lines, liquid jets of diameter 200-250 mu m (methylene blue, water and oils) have been successfully delivered into agarose gel targets of various strengths. Successful vaccination against murine salmonellosis was demonstrated as a biological application of this device. The penetration depths achieved in the experimental targets are very encouraging to develop a future device for biological and biomedical applications.

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This paper presents a decentralized/peer-to-peer architecture-based parallel version of the vector evaluated particle swarm optimization (VEPSO) algorithm for multi-objective design optimization of laminated composite plates using message passing interface (MPI). The design optimization of laminated composite plates being a combinatorially explosive constrained non-linear optimization problem (CNOP), with many design variables and a vast solution space, warrants the use of non-parametric and heuristic optimization algorithms like PSO. Optimization requires minimizing both the weight and cost of these composite plates, simultaneously, which renders the problem multi-objective. Hence VEPSO, a multi-objective variant of the PSO algorithm, is used. Despite the use of such a heuristic, the application problem, being computationally intensive, suffers from long execution times due to sequential computation. Hence, a parallel version of the PSO algorithm for the problem has been developed to run on several nodes of an IBM P720 cluster. The proposed parallel algorithm, using MPI's collective communication directives, establishes a peer-to-peer relationship between the constituent parallel processes, deviating from the more common master-slave approach, in achieving reduction of computation time by factor of up to 10. Finally we show the effectiveness of the proposed parallel algorithm by comparing it with a serial implementation of VEPSO and a parallel implementation of the vector evaluated genetic algorithm (VEGA) for the same design problem. (c) 2012 Elsevier Ltd. All rights reserved.

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We investigate the effect of a prescribed tangential velocity on the drag force on a circular cylinder in a spanwise uniform cross flow. Using a combination of theoretical and numerical techniques we make an attempt at determining the optimal tangential velocity profiles which will reduce the drag force acting on the cylindrical body while minimizing the net power consumption characterized through a non-dimensional power loss coefficient (C-PL). A striking conclusion of our analysis is that the tangential velocity associated with the potential flow, which completely suppresses the drag force, is not optimal for both small and large, but finite Reynolds number. When inertial effects are negligible (R e << 1), theoretical analysis based on two-dimensional Oseen equations gives us the optimal tangential velocity profile which leads to energetically efficient drag reduction. Furthermore, in the limit of zero Reynolds number (Re -> 0), minimum power loss is achieved for a tangential velocity profile corresponding to a shear-free perfect slip boundary. At finite Re, results from numerical simulations indicate that perfect slip is not optimum and a further reduction in drag can be achieved for reduced power consumption. A gradual increase in the strength of a tangential velocity which involves only the first reflectionally symmetric mode leads to a monotonic reduction in drag and eventual thrust production. Simulations reveal the existence of an optimal strength for which the power consumption attains a minima. At a Reynolds number of 100, minimum value of the power loss coefficient (C-PL = 0.37) is obtained when the maximum in tangential surface velocity is about one and a half times the free stream uniform velocity corresponding to a percentage drag reduction of approximately 77 %; C-PL = 0.42 and 0.50 for perfect slip and potential flow cases, respectively. Our results suggest that potential flow tangential velocity enables energetically efficient propulsion at all Reynolds numbers but optimal drag reduction only for Re -> infinity. The two-dimensional strategy of reducing drag while minimizing net power consumption is shown to be effective in three dimensions via numerical simulation of flow past an infinite circular cylinder at a Reynolds number of 300. Finally a strategy of reducing drag, suitable for practical implementation and amenable to experimental testing, through piecewise constant tangential velocities distributed along the cylinder periphery is proposed and analysed.

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Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. In this study, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) models were developed and coupled for the management of groundwater of Dore river basin in France. The Analytic Element Method (AEM) based flow model was developed and used to generate the dataset for the training and testing of the ANN model. This developed ANN-PSO model was applied to minimize the pumping cost of the wells, including cost of the pipe line. The discharge and location of the pumping wells were taken as the decision variable and the ANN-PSO model was applied to find out the optimal location of the wells. The results of the ANN-PSO model are found similar to the results obtained by AEM-PSO model. The results show that the ANN model can reduce the computational burden significantly as it is able to analyze different scenarios, and the ANN-PSO model is capable of identifying the optimal location of wells efficiently.

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The envelope protein (E1-E2) of Hepatitis C virus (HCV) is a major component of the viral structure. The glycosylated envelope protein is considered to be important for initiation of infection by binding to cellular receptor(s) and also known as one of the major antigenic targets to host immune response. The present study was aimed at identifying mouse monoclonal antibodies which inhibit binding of virus like particles of HCV to target cells. The first step in this direction was to generate recombinant HCV-like particles (HCV-LPs) specific for genotypes 3a of HCV (prevalent in India) using the genes encoding core, E1 and E2 envelop proteins in a baculovirus expression system. The purified HCV-LPs were characterized by ELISA and electron microscopy and were used to generate monoclonal antibodies (mAbs) in mice. Two monoclonal antibodies (E8G9 and H1H10) specific for the E2 region of envelope protein of HCV genotype 3a, were found to reduce the virus binding to Huh7 cells. However, the mAbs generated against HCV genotype 1b (D2H3, G2C7, E1B11) were not so effective. More importantly, mAb E8G9 showed significant inhibition of the virus entry in HCV JFH1 cell culture system. Finally, the epitopic regions on E2 protein which bind to the mAbs have also been identified. Results suggest a new therapeutic strategy and provide the proof of concept that mAb against HCV-LP could be effective in preventing virus entry into liver cells to block HCV replication.

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The scattering of carriers by charged dislocations in semiconductors is studied within the framework of the linearized Boltzmann transport theory with an emphasis on examining consequences of the extreme anisotropy of the cylindrically symmetric scattering potential. A new closed-form approximate expression for the carrier mobility valid for all temperatures is proposed. The ratios of quantum and transport scattering times are evaluated after averaging over the anisotropy in the relaxation time. The value of the Hall scattering factor computed for charged dislocation scattering indicates that there may be a factor of two error in the experimental mobility estimates using the Hall data. An expression for the resistivity tensor when the dislocations are tilted with respect to the plane of transport is derived. Finally, an expression for the isotropic relaxation time is derived when the dislocations are located within the sample with a uniform angular distribution.

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Particle Swarm Optimization is a parallel algorithm that spawns particles across a search space searching for an optimized solution. Though inherently parallel, they have distinct synchronizations points which stumbles attempts to create completely distributed versions of it. In this paper, we attempt to create a completely distributed peer-peer particle swarm optimization in a cluster of heterogeneous nodes. Since, the original algorithm requires explicit synchronization points we modified the algorithm in multiple ways to support a peer-peer system of nodes. We also modify certain aspect of the basic PSO algorithm and show how certain numerical problems can take advantage of the same thereby yielding fast convergence.

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Clustering has been the most popular method for data exploration. Clustering is partitioning the data set into sub-partitions based on some measures say the distance measure, each partition has its own significant information. There are a number of algorithms explored for this purpose, one such algorithm is the Particle Swarm Optimization(PSO) which is a population based heuristic search technique derived from swarm intelligence. In this paper we present an improved version of the Particle Swarm Optimization where, each feature of the data set is given significance accordingly by adding some random weights, which also minimizes the distortions in the dataset if any. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The experimental results shows that our proposed methodology performs significantly better than the previously performed experiments.

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For one-dimensional flexible objects such as ropes, chains, hair, the assumption of constant length is realistic for large-scale 3D motion. Moreover, when the motion or disturbance at one end gradually dies down along the curve defining the one-dimensional flexible objects, the motion appears ``natural''. This paper presents a purely geometric and kinematic approach for deriving more natural and length-preserving transformations of planar and spatial curves. Techniques from variational calculus are used to determine analytical conditions and it is shown that the velocity at any point on the curve must be along the tangent at that point for preserving the length and to yield the feature of diminishing motion. It is shown that for the special case of a straight line, the analytical conditions lead to the classical tractrix curve solution. Since analytical solutions exist for a tractrix curve, the motion of a piecewise linear curve can be solved in closed-form and thus can be applied for the resolution of redundancy in hyper-redundant robots. Simulation results for several planar and spatial curves and various input motions of one end are used to illustrate the features of motion damping and eventual alignment with the perturbation vector.

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In the present investigation, efforts were made to study the different frictional responses of materials with varying crystal structure and hardness during sliding against a relatively harder material of different surface textures and roughness. In the experiments, pins were made of pure metals and alloys with significantly different hardness values. Pure metals were selected based on different class of crystal structures, such as face centered cubic (FCC), body centered cubic (BCC), body centered tetragonal (BCT) and hexagonal close packed (HCP) structures. The surface textures with varying roughness were generated on the counterpart plate which was made of H-11 die steel. The experiments were conducted under dry and lubricated conditions using an inclined pin-on-plate sliding tester for various normal loads at ambient environment. In the experiments, it was found that the coefficient of friction is controlled by the surface texture of the harder mating surfaces. Further, two kinds of frictional response, namely steady-state and stick-slip, were observed during sliding. More specifically, stead-state frictional response was observed for the FCC metals, alloys and materials with higher hardness. Stick-slip frictional response was observed for the metals which have limited number of slip systems such as BCT and HCP. In addition, the stick-slip frictional response was dependent on the normal load, lubrication, hardness and surface texture of the counterpart material. However, for a given kind of surface texture, the roughness of the surface affects neither the average coefficient of friction nor the amplitude of stick-slip oscillation significantly.

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A new technique is proposed for multisensor image registration by matching the features using discrete particle swarm optimization (DPSO). The feature points are first extracted from the reference and sensed image using improved Harris corner detector available in the literature. From the extracted corner points, DPSO finds the three corresponding points in the sensed and reference images using multiobjective optimization of distance and angle conditions through objective switching technique. By this, the global best matched points are obtained which are used to evaluate the affine transformation for the sensed image. The performance of the image registration is evaluated and concluded that the proposed approach is efficient.