141 resultados para PARTICLE COALESCENCE


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Recent evidence suggests that genomic instability, which is an important step in carcinogenesis, may be important in the effectiveness of radiation as a carcinogen, particularly for high-LET radiations. Understanding the biological effects underpinning the risks associated with low doses of densely ionizing radiations is complicated in experimental systems by the Poisson distribution of particles that ran be delivered, In this study, we report an approach to determine the effect of the lowest possible cellular radiation dose of densely ionizing at particles, that of a single particle traversal. Using microbeam technology and an approach for immobilizing human T-lymphocytes, we have measured the effects of single alpha -particle traversals on the surviving progeny of cells. A significant increase in the proportion of aberrant cells is observed 12-13 population doublings after exposure, with a high level of chromatid-type aberrations, indicative of an instability phenotype, These data suggest that instability may be important in situations where even a single particle traverses human cells. (C) 2001 by Radiation Research Society.

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The Gray Laboratory charged-particle microbeam has been used to assess the clonogenic ability of Chinese hamster V79 cells after irradiation of their nuclei with a precisely defined number of protons with energies of 1.0 and 3.2 MeV. The microbeam uses a 1-mum. silica capillary collimator to deliver protons to subcellular targets with high accuracy. The detection system is based on a miniature photomultiplier tube positioned above the cell dish, which detects the photons generated by the passage of the charged particles through an 18-mum-thick scintillator placed below the cells. With this system, a detection efficiency of greater than 99% is achieved. The cells are plated on specially designed dishes (3-mum-thick Mylar base), and the nuclei are identified by fluorescence microscopy. After an incubation period of 3 days, the cells are revisited individually to assess the formation of colonies from the surviving cells. For each energy investigated, the survival curve obtained for the microbeam shows a significant deviation below I Gy from a response extrapolated using the LQ model for the survival data above 1 Gy. The data are well fitted by a model that supports the hypothesis that radioresistance is induced by low-dose hypersensitivity. These studies demonstrate the potential of the microbeam for performing studies of the effects of single charged particles on cells in vitro. The hypersensitive responses observed are comparable with those reported by others using different radiations and techniques. (C) 2001 by Radiation Research Society.

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Colour-based particle filters have been used exhaustively in the literature given rise to multiple applications However tracking coloured objects through time has an important drawback since the way in which the camera perceives the colour of the object can change Simple updates are often used to address this problem which imply a risk of distorting the model and losing the target In this paper a joint image characteristic-space tracking is proposed which updates the model simultaneously to the object location In order to avoid the curse of dimensionality a Rao-Blackwellised particle filter has been used Using this technique the hypotheses are evaluated depending on the difference between the model and the current target appearance during the updating stage Convincing results have been obtained in sequences under both sudden and gradual illumination condition changes Crown Copyright (C) 2010 Published by Elsevier B V All rights reserved

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In this paper, we introduce an efficient method for particle selection in tracking objects in complex scenes. Firstly, we improve the proposal distribution function of the tracking algorithm, including current observation, reducing the cost of evaluating particles with a very low likelihood. In addition, we use a partitioned sampling approach to decompose the dynamic state in several stages. It enables to deal with high-dimensional states without an excessive computational cost. To represent the color distribution, the appearance of the tracked object is modelled by sampled pixels. Based on this representation, the probability of any observation is estimated using non-parametric techniques in color space. As a result, we obtain a Probability color Density Image (PDI) where each pixel points its membership to the target color model. In this way, the evaluation of all particles is accelerated by computing the likelihood p(z|x) using the Integral Image of the PDI.

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In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that Rao-Blackwellization allows the state variables to be splitted into two sets, being one of them analytically calculated from the posterior probability of the remaining ones. This procedure reduces the dimensionality of the Particle Filter, thus requiring fewer particles to achieve a similar tracking performance. In this manner, location and size over the image are obtained stochastically using colour and motion clues, whereas body pose is solved analytically applying learned human Point Distribution Models.

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In this paper, a novel framework for visual tracking of human body parts is introduced. The approach presented demonstrates the feasibility of recovering human poses with data from a single uncalibrated camera by using a limb-tracking system based on a 2-D articulated model and a double-tracking strategy. Its key contribution is that the 2-D model is only constrained by biomechanical knowledge about human bipedal motion, instead of relying on constraints that are linked to a specific activity or camera view. These characteristics make our approach suitable for real visual surveillance applications. Experiments on a set of indoor and outdoor sequences demonstrate the effectiveness of our method on tracking human lower body parts. Moreover, a detail comparison with current tracking methods is presented.

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In this paper, we consider the problem of tracking similar objects. We show how a mean field approach can be used to deal with interacting targets and we compare it with Markov Chain Monte Carlo (MCMC). Two mean field implementations are presented. The first one is more general and uses particle filtering. We discuss some simplifications of the base algorithm that reduce the computation time. The second one is based on suitable Gaussian approximations of probability densities that lead to a set of self-consistent equations for the means and covariances. These equations give the Kalman solution if there is no interaction. Experiments have been performed on two kinds of sequences. The first kind is composed of a single long sequence of twenty roaming ants and was previously analysed using MCMC. In this case, our mean field algorithms obtain substantially better results. The second kind corresponds to selected sequences of a football match in which the interaction avoids tracker coalescence in situations where independent trackers fail.

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We show that a quantum scalar particle in the gravitational field of a massive body of radius R which slightly exceeds the Schwarzschild radius rs, possesses a dense spectrum of narrow resonances. Their lifetimes and density tend to infinity in the limit R?rs. We determine the cross section of the particle capture into these resonances and show that it is equal to the absorption cross section for a Schwarzschild black hole. Thus, a nonsingular static metric acquires black-hole properties before the actual formation of a black hole.