923 resultados para Box constrained minimization
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Two candidate genes for controlling thymocyte differentiation, T-cell factor-1 (Tcf-1) and lymphoid enhancer-binding factor (Lef-1), encode closely related DNA-binding HMG-box proteins. Their expression pattern is complex and largely overlapping during embryogenesis, yet restricted to lymphocytes postnatally. Here we generate two independent germline mutations in Tcf-1 and find that thymocyte development in (otherwise normal) mutant mice is blocked at the transition from the CD8+, immature single-positive to the CD4+/CD8+ double-positive stage. In contrast to wild-type mice, most of the immature single-positive cells in the mutants are not in the cell cycle and the number of immunocompetent T cells in peripheral lymphoid organs is reduced. We conclude that Tcf-1 controls an essential step in thymocyte differentiation.
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Long-term outcomes after kidney transplantation remain suboptimal, despite the great achievements observed in recent years with the use of modern immunosuppressive drugs. Currently, the calcineurin inhibitors (CNI) cyclosporine and tacrolimus remain the cornerstones of immunosuppressive regimens in many centers worldwide, regardless of their well described side-effects, including nephrotoxicity. In this article, we review recent CNI-minimization strategies in kidney transplantation, while emphasizing on the importance of long-term follow-up and patient monitoring. Finally, accumulating data indicate that low-dose CNI-based regimens would provide an interesting balance between efficacy and toxicity.
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In this paper we axiomatize the strong constrained egalitarian solution (Dutta and Ray, 1991) over the class of weak superadditive games using constrained egalitarianism, order-consistency, and converse order-consistency. JEL classification: C71, C78. Keywords: Cooperative TU-game, strong constrained egalitarian solution, axiomatization.
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Habitat restoration measures may result in artificially high breeding density, for instance when nest-boxes saturate the environment, which can negatively impact species' demography. Potential risks include changes in mating and reproductive behaviour such as increased extra-pair paternity, conspecific brood parasitism, and polygyny. Under particular cicumstances, these mechanisms may disrupt reproduction, with populations dragged into an extinction vortex. With the use of nuclear microsatellite markers, we investigated the occurrence of these potentially negative effects in a recovered population of a rare secondary cavity-nesting farmland bird of Central Europe, the hoopoe (Upupa epops). High intensity farming in the study area has resulted in a total eradication of cavity trees, depriving hoopoes from breeding sites. An intensive nest-box campaign rectified this problem, resulting in a spectacular population recovery within a few years only. There was some concern, however, that the new, high artificially-induced breeding density might alter hoopoe mating and reproductive behaviour. As the species underwent a serious demographic bottleneck in the 1970-1990s, we also used the microsatellite markers to reconstitute the demo-genetic history of the population, looking in particular for signs of genetic erosion. We found i) a low occurrence of extra-pair paternity, polygyny and conspecific brood parasitism, ii) a high level of neutral genetic diversity (mean number of alleles and expected heterozygosity per locus: 13.8 and 83%, respectively) and, iii) evidence for genetic connectivity through recent immigration of individuals from well differentiated populations. The recent increase in breeding density did thus not induce so far any noticeable detrimental changes in mating and reproductive behaviour. The demographic bottleneck undergone by the population in the 1970s-1990s was furthermore not accompanied by any significant drop in neutral genetic diversity. Finally, genetic data converged with a concomitant demographic study to evidence that immigration strongly contributed to local population recovery.
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Abstract This thesis proposes a set of adaptive broadcast solutions and an adaptive data replication solution to support the deployment of P2P applications. P2P applications are an emerging type of distributed applications that are running on top of P2P networks. Typical P2P applications are video streaming, file sharing, etc. While interesting because they are fully distributed, P2P applications suffer from several deployment problems, due to the nature of the environment on which they perform. Indeed, defining an application on top of a P2P network often means defining an application where peers contribute resources in exchange for their ability to use the P2P application. For example, in P2P file sharing application, while the user is downloading some file, the P2P application is in parallel serving that file to other users. Such peers could have limited hardware resources, e.g., CPU, bandwidth and memory or the end-user could decide to limit the resources it dedicates to the P2P application a priori. In addition, a P2P network is typically emerged into an unreliable environment, where communication links and processes are subject to message losses and crashes, respectively. To support P2P applications, this thesis proposes a set of services that address some underlying constraints related to the nature of P2P networks. The proposed services include a set of adaptive broadcast solutions and an adaptive data replication solution that can be used as the basis of several P2P applications. Our data replication solution permits to increase availability and to reduce the communication overhead. The broadcast solutions aim, at providing a communication substrate encapsulating one of the key communication paradigms used by P2P applications: broadcast. Our broadcast solutions typically aim at offering reliability and scalability to some upper layer, be it an end-to-end P2P application or another system-level layer, such as a data replication layer. Our contributions are organized in a protocol stack made of three layers. In each layer, we propose a set of adaptive protocols that address specific constraints imposed by the environment. Each protocol is evaluated through a set of simulations. The adaptiveness aspect of our solutions relies on the fact that they take into account the constraints of the underlying system in a proactive manner. To model these constraints, we define an environment approximation algorithm allowing us to obtain an approximated view about the system or part of it. This approximated view includes the topology and the components reliability expressed in probabilistic terms. To adapt to the underlying system constraints, the proposed broadcast solutions route messages through tree overlays permitting to maximize the broadcast reliability. Here, the broadcast reliability is expressed as a function of the selected paths reliability and of the use of available resources. These resources are modeled in terms of quotas of messages translating the receiving and sending capacities at each node. To allow a deployment in a large-scale system, we take into account the available memory at processes by limiting the view they have to maintain about the system. Using this partial view, we propose three scalable broadcast algorithms, which are based on a propagation overlay that tends to the global tree overlay and adapts to some constraints of the underlying system. At a higher level, this thesis also proposes a data replication solution that is adaptive both in terms of replica placement and in terms of request routing. At the routing level, this solution takes the unreliability of the environment into account, in order to maximize reliable delivery of requests. At the replica placement level, the dynamically changing origin and frequency of read/write requests are analyzed, in order to define a set of replica that minimizes communication cost.
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Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.
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British mammalogists have used two different systems for surveying the common dormouse Muscardinus avellanarius: a modified bird nest box with the entrance facing the tree trunk, and a smaller, cheaper model called a "nest tube". However, only few data comparing different nest box systems are currently available. To determine which system is more efficient, we compared the use of the large (GB-type) and small nest boxes (DE-type, a commercial wooden mouse trap without a door) in three Swiss forest. The presence of Muscardinus, potential competitors, and any evidence of occupation were examined in 60 pairs of nest boxes based on 2,280 nest box checks conducted over 5 years. Mean annual occupation and cumulative numbers of Muscardinus present were both significantly higher for the DE than for the GB boxes (64.6% versus 32.1%, and 149 versus 67 dormice, respectively). In contrast, the annual occupation by competitors including Glis glis, Apodemus spp. and hole-nesting birds was significantly higher in the GB than in the DE boxes in all forest (19-68% versus 0-16%, depending on the species and forest). These results suggest that smaller nest boxes are preferred by the common dormouse and are rarely occupied by competitors. These boxes hence appear to be preferable for studying Muscardinus populations.
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Transforming growth factor-beta (TGF-beta) and its related proteins regulate broad aspects of body development, including cell proliferation, differentiation, apoptosis and gene expression, in various organisms. Deregulated TGF-beta function has been causally implicated in the generation of human fibrotic disorders and in tumor progression. Nevertheless, the molecular mechanisms of TGF-beta action remained essentially unknown until recently. Here, we discuss recent progress in our understanding of the mechanism of TGF-beta signal transduction with respect to the regulation of gene expression, the control of cell phenotype and the potential usage of TGF-beta for the treatment of human diseases.
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Population densities of marked common dormice Muscardinus avellanarius are generally based on nest box checks. As dormice also use natural cavities and leaf nests, we tried to answer the question "what proportion of the population cannot be monitored by nest boy checks", using parallel trapping sessions. We selected a forest of 1.7ha where a 5-year nest box survey revealed an annual mean of 3.4 ± 1.4 dormice per check. The trap design (permanent grid of 77 hanging platforms) was developed in June. During July and August the traps were set every second week (4 sessions of two nights = 8 nights) resulting in a total of 75 captures with mean of 9.4 dormice per night and the presence of 16 different individuals. The grid of 60 nest boxes was checked weekly (8 times) which allowed the recapture of 19 dormice with a mean of 2.4 dormice, per control day and the presence of 6 different individuals. Population density estimated by calendar of capture and the minimal number of dormice alive methods gave for nest-box checks a value of 2.4 animals/ha and the trap checks 6.6 animals/ha with the conclusion that 63% of the population were not being monitored by nest box checks.
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The display tray holds the specimens over a thin cotton layer glued to a thick paper attached to the cd holder tray. Althought only a temporary storing method, it is a good alternative when compared to other layer models. It has the advantages of low cost, protection of specimens, minimal or no damage, as well as good visibility through its cover.
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Canonical correspondence analysis and redundancy analysis are two methods of constrained ordination regularly used in the analysis of ecological data when several response variables (for example, species abundances) are related linearly to several explanatory variables (for example, environmental variables, spatial positions of samples). In this report I demonstrate the advantages of the fuzzy coding of explanatory variables: first, nonlinear relationships can be diagnosed; second, more variance in the responses can be explained; and third, in the presence of categorical explanatory variables (for example, years, regions) the interpretation of the resulting triplot ordination is unified because all explanatory variables are measured at a categorical level.
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This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.
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When dealing with the design of service networks, such as healthand EMS services, banking or distributed ticket selling services, thelocation of service centers has a strong influence on the congestion ateach of them, and consequently, on the quality of service. In this paper,several models are presented to consider service congestion. The firstmodel addresses the issue of the location of the least number of single--servercenters such that all the population is served within a standard distance,and nobody stands in line for a time longer than a given time--limit, or withmore than a predetermined number of other clients. We then formulateseveral maximal coverage models, with one or more servers per service center.A new heuristic is developed to solve the models and tested in a 30--nodesnetwork.
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The paper presents a new model based on the basic Maximum Capture model,MAXCAP. The New Chance Constrained Maximum Capture modelintroduces astochastic threshold constraint, which recognises the fact that a facilitycan be open only if a minimum level of demand is captured. A metaheuristicbased on MAX MIN ANT system and TABU search procedure is presented tosolve the model. This is the first time that the MAX MIN ANT system isadapted to solve a location problem. Computational experience and anapplication to 55 node network are also presented.