834 resultados para Japanese In motion pictures


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In order to understand the translational and rotational motion in dense molecular liquids, detailed molecular dynamics simulations of Lennard-Jones ellipsoids have been carried out for three different values of the aspect ratio kappa. For ellipsoids with an aspect ratio equal to 2, the product of the translational diffusion coefficient (D-T) and the average orientational correlation time of the l-th rank harmonics (tau(lR)), converges to a nearly constant value at high density. Surprisingly, this density independent value of D-T tau(lR) is within 5% of the hydrodynamic prediction with the slip boundary condition. This is despite the fact that both D-T and tau(lR) themselves change nearly by an order of magnitude in the density range considered, and the rotational correlation function itself is strongly nonexponential. For small aspect ratios (kappa less than or equal to 1.5), the rotational correlation function remains largely Gaussian even at a very large density, while for a large aspect ratio (kappa greater than or equal to 3), the transition to the nematic liquid-crystalline phase precludes the hydrodynamic regime. Thus, the rotational dynamics of ellipsoids show great sensitivity to the aspect ratio. At low density, tau(lR) goes through a minimum value, indicating the role of interactions in enhancing the rate of orientational relaxation. (C) 1997 American Institute of Physics. [S0021-9606(97)50142-5].

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Brownian dynamics (BD) simulations have been carried out to explore the effects of the orientational motion of the donor-acceptor (D-A) chromophore pair on the Forster energy transfer between the D-A pair embedded in a polymer chain in solution. It is found that the usually employed orientational averaging (that is, replacing the orientational factor, kappa, by kappa (2) = 2/3) may lead to an error in the estimation of the rate of the reaction by about 20%. In the limit of slow orientational relaxation, the preaveraging of the orientational factor leads to an overestimation of the rate, while in the opposite limit of very fast orientational relaxation, the usual scheme underestimates the rate. The latter results from an interesting interplay between reaction and diffusion. On the other hand, when one of the chromophores is fixed, the preaveraged rate is found to be fairly reliable if the rotational relaxation of the chromophore is sufficiently fast. The present study also reveals a power law dependence of the FRET rate on the chain length (rate proportional to N- alpha, with alpha approximate to 2.6).

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We have studied the behaviour of a charged particle in an axially symmetric magnetic field having a neutral point, so as to find a possibility of confining a charged particle in a thermonuclear device. In order to study the motion we have reduced a three-dimensional motion to a two-dimensional one by introducing a fictitious potential. Following Schmidt we have classified the motion, as an ‘off-axis motion’ and ‘encircling motion’ depending on the behaviour of this potential. We see that the particle performs a hybrid type of motion in the negative z-axis, i.e. at some instant it is in ‘off-axis motion’ while at another instant it is in ‘encircling motion’. We have also solved the equation of motion numerically and the graphs of the particle trajectory verify our analysis. We find that in most of the cases the particle is contained. The magnetic moment is found to be moderately adiabatic.

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A numerical micro-scale model is developed to study the behavior of dendrite growth in presence of melt convection. In this method, an explicit, coupled enthalpy model is used to simulate the growth of an equiaxed dendrite, while a Volume of Fluid (VOF) method is used to track the movement of the dendrite in the convecting melt in a two-dimensional Eulerian framework. Numerical results demonstrate the effectiveness of the enthalpy model in simulating the dendritic growth involving complex shape, and the accuracy of VOF method in conserving mass and preserving the complex dendritic shape during motion. Simulations are performed in presence of uniform melt flow for both fixed and moving dendrites, and the difference in dendrite morphology is shown.

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Avoidance of collision between moving objects in a 3-D environment is fundamental to the problem of planning safe trajectories in dynamic environments. This problem appears in several diverse fields including robotics, air vehicles, underwater vehicles and computer animation. Most of the existing literature on collision prediction assumes objects to be modelled as spheres. While the conservative spherical bounding box is valid in many cases, in many other cases, where objects operate in close proximity, a less conservative approach, that allows objects to be modelled using analytic surfaces that closely mimic the shape of the object, is more desirable. In this paper, a collision cone approach (previously developed only for objects moving on a plane) is used to determine collision between objects, moving in 3-D space, whose shapes can be modelled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained and used to derive dynamic inversion based avoidance strategies.

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A coupled methodology for simulating the simultaneous growth and motion of equiaxed dendrites in solidifying melts is presented. The model uses the volume-averaging principles and combines the features of the enthalpy method for modeling growth, immersed boundary method for handling the rigid solid-liquid interfaces, and the volume of fluid method for tracking the advection of the dendrite. The algorithm also performs explicit-implicit coupling between the techniques used. A two-dimensional framework with incompressible and Newtonian fluid is considered. Validation with available literature is performed and dendrite growth in the presence of rotational and buoyancy driven flow fields is studied. It is seen that the flow fields significantly alter the position and morphology of the dendrites. (C) 2012 Elsevier Inc. All rights reserved.

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Movement in animal groups is highly varied and ranges from seemingly disordered motion in swarms to coordinated aligned motion in flocks and schools. These social interactions are often thought to reduce risk from predators, despite a lack of direct evidence. We investigated risk-related selection for collective motion by allowing real predators ( bluegill sunfish) to hunt mobile virtual prey. By fusing simulated and real animal behavior, we isolated predator effects while controlling for confounding factors. Prey with a tendency to be attracted toward, and to align direction of travel with, near neighbors tended to form mobile coordinated groups and were rarely attacked. These results demonstrate that collective motion could evolve as a response to predation, without prey being able to detect and respond to predators.

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Measurement of in-plane motion with high resolution and large bandwidth enables model-identification and real-time control of motion-stages. This paper presents an optical beam deflection based system for measurement of in-plane motion of both macro- and micro-scale motion stages. A curved reflector is integrated with the motion stage to achieve sensitivity to in-plane translational motion along two axes. Under optimal settings, the measurement system is shown to theoretically achieve sub-angstrom measurement resolution over a bandwidth in excess of 1 kHz and negligible cross-sensitivity to linear motion. Subsequently, the proposed technique is experimentally demonstrated by measuring the in-plane motion of a piezo flexure stage and a scanning probe microcantilever. For the former case, reflective spherical balls of different radii are employed to measure the in-plane motion and the measured sensitivities are shown to agree with theoretical values, on average, to within 8.3%. For the latter case, a prototype polydimethylsiloxane micro-reflector is integrated with the microcantilever. The measured in-plane motion of the microcantilever probe is used to identify nonlinearities and the transient dynamics of the piezo-stage upon which the probe is mounted. These are subsequently compensated by means of feedback control. (C) 2013 AIP Publishing LLC.

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Productive infection of human endothelial cells with Japanese encephalitis virus (JEV), a single stranded RNA virus induces shedding of sHLA-E. We show here that sHLA-E that is released upon infection with this flavivirus can inhibit IL-2 and PMA mediated ERK 1/2 phosphorylation in two NK cell lines, Nishi and NKL. Virus infected or IFN-gamma treated cell culture supernatants containing sHLA-E were found to partially inhibit IL-2 mediated induction of CD25 molecules on NKL cells. It was also found that sHLA-E could inhibit IL-2 induced H-3]-thymidine incorporation suggesting that, similar to cell surface expressed HLA-E, sHLA-E could also inhibit NK cell responses. Hence JEV-induced shedding of sHLA-E needs further investigation to better understand immune responses in JEV infections since it may have a role in viral evasion of NK cell responses. (C) 2014 Elsevier B.V. All rights reserved.

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In this work, we have explored the prospect of segmenting crowd flow in H. 264 compressed videos by merely using motion vectors. The motion vectors are extracted by partially decoding the corresponding video sequence in the H. 264 compressed domain. The region of interest ie., crowd flow region is extracted and the motion vectors that spans the region of interest is preprocessed and a collective representation of the motion vectors for the entire video is obtained. The obtained motion vectors for the corresponding video is then clustered by using EM algorithm. Finally, the clusters which converges to a single flow are merged together based on the bhattacharya distance measure between the histogram of the of the orientation of the motion vectors at the boundaries of the clusters. We had implemented our proposed approach on the complex crowd flow dataset provided by 1] and compared our results by using Jaccard measure. Since we are performing crowd flow segmentation in the compressed domain using only motion vectors, our proposed approach performs much faster compared to other pixel domain counterparts still retaining better accuracy.

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We study motion around a static Einstein and pure Lovelock black hole in higher dimensions. It is known that in higher dimensions bound orbits exist only for a pure Lovelock black hole in all even dimensions, D = 2N + 2, where N is the degree of Lovelock polynomial action. In particular, we compute periastron shift and light bending, and the latter is given by one of the transverse spatial components of the Riemann curvature tensor. We also consider the pseudo-Newtonian potentials and Kruskal coordinates.

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Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.