964 resultados para Distributed algorithm
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Résumé Introduction : La chirurgie de la maladie de Hirschsprung est fréquemment compliquée d'une atteinte post-opératoire de la motilité intestinale. Des anomalies du système nerveux entérique (SNE) telles que la dysplasie neuronale intestinale de type B, l'hypoganglionose ou l'aganglionose, présents dans le segment abaissé, peuvent être la cause de certaines de ces complications mais aucune information n'est disponible quant au rôle des cellules interstitielles de Cajal (CIC) sur la motilité intestinale dans la phase post-opératoire. Ces cellules sont considérées avoir un rôle de pacemaker dans le tractus gastro-intestinal. L'objectif de cette étude était de décrire la distribution des CIC dans le segment proximal du côlon réséqué lors de cures chirurgicales de maladie de Hirschsprung et de confronter ces observations à l'évolution clinique post-opératoire. Matériel et Méthodes : L'incidence des complications post-opératoires a été déterminée par une revue rétrospective des dossiers de 48 patients opérés pour maladie de Hirschspung entre 1977 et 1999 et par l'étude histologique et immuno-histochimique des pièces réséquées chez ces patients. Nous avons comparé la distribution des CIC dans le segment proximal du côlon avec celle du côlon sain de 16 enfants contrôles par microscopie optique. L'immunohistochimie au c-Kit a été utilisée pour marquer spécifiquement les CIC sur échantillons paraffinés. Ces résultats ont ensuite été corrélés avec l'étude du SNE de ces mêmes segments, déterminée par immunohistochimie au CD56 et au protein gene product 9.5. Résultats Les complications post-opératoires suivantes furent identifiées : constipation 46%, constipation avec incontinence 15%, entérocolite 8%, décès 4% (probablement sur entérocolite). La distribution des CIC dans les segments proximaux réséqués chez les enfants avec maladie de Hirschsprung était identique à celle observée dans les segments de côlon sain, et ce indépendamment de la distribution normale ou anormale du SNE. Chez les enfants opérés pour maladie de Hirschsprung les segments réséqués présentaient les anomalies d'innervation suivantes : aganglionose 10.4%, hypoganglionose 12.5%, dysplasie neuronale intestinale de type B 6.3%, autres dysganglionoses 14.6%. Aucune relation entre ces anomalies d'innervation et les complications post-opératoires n'a été mise en évidence. Conclusion : La distribution des CIC est normale chez les patient opérés pour maladie de Hirschsprung, et ne contribue donc pas aux atteintes post-opératoires de la motilité intestinale. Cela signifie aussi que le réseau de CIC se développe noinialement dans le côlon humain, même en présence d'une innervation colique anormale ou absente. Abstract: Surgery for Hirschsprung's disease is often complicated by post-operative bowel motility disorders. The impact of intestinal neural histology on the surgical outcome has been previously studied, but no information is available concerning the influence of the distribution of interstitial cells of Cajal (ICC) on these complications. These cells are considered to be pacemakers in the gastrointestinal tract. The aim of this study was to assess the distribution of ICC in the proximal segment of resected bowel in Hirschsprung's disease and confront these results with the clinical outcome. Using immunohistochemistry for light microscopy, we compared the pattern of distribution of ICC in the proximal segment of resected bowel in Hirschsprung's disease with that in normal colon. We correlated these results with the corresponding neural intestinal histology determined by CD56 and the protein gene product 9.5 immunohistochemistry. The distribution of ICC in the proximal segment of resected bowel is identical to that of normal colon, regardless of normal or abnormal colon innervation. ICC distribution does not seem to contribute to post-operative bowel motility disorders in patients operated for Hirschsprung's disease.
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The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).
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Spatial variation in the pattern of natural selection can promote local adaptation and genetic differentiation between populations. Because heritable melanin-based ornaments can signal resistance to environmentally mediated elevation in glucocorticoids, to oxidative stress and parasites, populations may vary in the mean degree of melanic coloration if selection on these phenotypic aspects varies geographically. Within a population of Swiss barn owls (Tyto alba), the size of eumelanic spots is positively associated with survival, immunity and resistance to stress, but it is yet unknown whether Tyto species that face stressful environments evolved towards a darker eumelanic plumage. Because selection regimes vary along environmental gradients, we examined whether melanin-based traits vary clinally and are expressed to a larger extent in the tropics where parasites are more abundant than in temperate zones. To this end, we considered 39 barn owl species distributed worldwide. Barn owl species living in the tropics displayed larger eumelanic spots than those found in temperate zones. This was, however, verified in the northern hemisphere only. Parasites being particularly abundant in the tropics, they may promote the evolution of darker eumelanic ornaments.
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This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed
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We present a system for dynamic network resource configuration in environments with bandwidth reservation. The proposed system is completely distributed and automates the mechanisms for adapting the logical network to the offered load. The system is able to manage dynamically a logical network such as a virtual path network in ATM or a label switched path network in MPLS or GMPLS. The system design and implementation is based on a multi-agent system (MAS) which make the decisions of when and how to change a logical path. Despite the lack of a centralised global network view, results show that MAS manages the network resources effectively, reducing the connection blocking probability and, therefore, achieving better utilisation of network resources. We also include details of its architecture and implementation
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Due to the high cost of a large ATM network working up to full strength to apply our ideas about network management, i.e., dynamic virtual path (VP) management and fault restoration, we developed a distributed simulation platform for performing our experiments. This platform also had to be capable of other sorts of tests, such as connection admission control (CAC) algorithms, routing algorithms, and accounting and charging methods. The platform was posed as a very simple, event-oriented and scalable simulation. The main goal was the simulation of a working ATM backbone network with a potentially large number of nodes (hundreds). As research into control algorithms and low-level, or rather cell-level methods, was beyond the scope of this study, the simulation took place at a connection level, i.e., there was no real traffic of cells. The simulated network behaved like a real network accepting and rejecting SNMP ones, or experimental tools using the API node
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A pioneer team of students of the University of Girona decided to design and develop an autonomous underwater vehicle (AUV) called ICTINEU-AUV to face the Student Autonomous Underwater Challenge-Europe (SAUC-E). The prototype has evolved from the initial computer aided design (CAD) model to become an operative AUV in the short period of seven months. The open frame and modular design principles together with the compatibility with other robots previously developed at the lab have provided the main design philosophy. Hence, at the robot's core, two networked computers give access to a wide set of sensors and actuators. The Gentoo/Linux distribution was chosen as the onboard operating system. A software architecture based on a set of distributed objects with soft real time capabilities was developed and a hybrid control architecture including mission control, a behavioural layer and a robust map-based localization algorithm made ICTINEU-AUV the winning entry
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In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm
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We present a system for dynamic network resource configuration in environments with bandwidth reservation and path restoration mechanisms. Our focus is on the dynamic bandwidth management results, although the main goal of the system is the integration of the different mechanisms that manage the reserved paths (bandwidth, restoration, and spare capacity planning). The objective is to avoid conflicts between these mechanisms. The system is able to dynamically manage a logical network such as a virtual path network in ATM or a label switch path network in MPLS. This system has been designed to be modular in the sense that in can be activated or deactivated, and it can be applied only in a sub-network. The system design and implementation is based on a multi-agent system (MAS). We also included details of its architecture and implementation
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Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach
Constraint algorithm for k-presymplectic Hamiltonian systems. Application to singular field theories
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The k-symplectic formulation of field theories is especially simple, since only tangent and cotangent bundles are needed in its description. Its defining elements show a close relationship with those in the symplectic formulation of mechanics. It will be shown that this relationship also stands in the presymplectic case. In a natural way,one can mimick the presymplectic constraint algorithm to obtain a constraint algorithmthat can be applied to k-presymplectic field theory, and more particularly to the Lagrangian and Hamiltonian formulations offield theories defined by a singular Lagrangian, as well as to the unified Lagrangian-Hamiltonian formalism (Skinner--Rusk formalism) for k-presymplectic field theory. Two examples of application of the algorithm are also analyzed.
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In this project I have carried out a vulnerability assessment of a component of the Condor Middleware. In this assessment I have sought and found the more dangerous software vulnerabilities of this system, I have reported them to the development team such that they may be fixed, and thus improve the security of this distributed system, and the networks that use it.
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Aquest treball pretén elaborar un sistema de detecció d'incendis implementat sota una xarxa de sensors sense fils. Aquesta xarxa està formada per petits dispositius autònoms equipats amb un transmissor de ràdio, un microcontrolador, diferents sensors (temperatura, lluminositat i efecte Hall) i alimentació per bateries (AA).