950 resultados para Generalized Gibbs sampler


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A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.

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Résumé : La production de nectar assure aux plantes entomophiles un important succès reproducteur. Malgré cela, de nombreuses espèces d'orchidées ne produisent pas de nectar. La majorité de ces orchidées dites trompeuses exploitent simplement l'instinct des pollinisateurs généralistes, qui les pousse à chercher du nectar dans les fleurs. Afin d'optimiser la récolte de nectar, les pollinisateurs apprennent à différencier les fleurs trompeuses des nectarifères, et à concentrer leurs visites sur ces dernières, au détriment des plantes trompeuses. Chez les orchidées non autogames, la reproduction est assurée uniquement par les pollinisateurs. L'apprentissage des pollinisateurs a donc un impact négatif sur la reproduction des orchidées trompeuses. Cependant, les caractéristiques d'une espèce trompeuse et des espèces nectarifères au sein d'une communauté végétale peuvent affecter l'apprentissage et le taux de visite des pollinisateurs aux plantes trompeuses. J'ai réalisé des expériences en milieu naturel et en milieu contrôlé, pour déterminer si les caractéristiques florales, spatiales et temporelles des communautés affectent le taux de visite et le succès reproducteur de plantes trompeuses. Une agrégation spatiale élevée des plantes trompeuses et des plantes nectarifères diminue le succès reproducteur des plantes trompeuses. De plus, les pollinisateurs visitent plus souvent l'espèce trompeuse Iorsque ses fleurs sont de couleur similaire à celles de l'espèce nectarifère. Cet effet bénéfique de la similarité pour la couleur des fleurs s'accentue si les deux espèces sont mélangées et proches spatialement, ou si l'espèce trompeuse fleurit après l'espèce nectarifère. Enfin, le comportement des pollinisateurs n'est pas tout de suite affecté lorsque les caractéristiques de la communauté changent. Les caractéristiques des communautés végétales affectent donc la reproduction des espèces trompeuses. Bien que L'absence de coûts associés à la production de nectar, l'exportation efficace de pollen et la production de graines de qualité dont bénéficient les orchidées trompeuses favorisent Ieur maintien, les caractéristiques de la communauté peuvent aussi y contribuer. Mon étude fournit donc une explication alternative et complémentaire au maintien des orchidées trompeuses. Je conclus par une discussion des implications possibles de ces résultats sur le maintien et l'évolution des orchidées trompeuses, en tenant compte de la dynamique des caractéristiques des communautés végétales naturelles. Abstract : Despite the importance of producing food to ensure a high reproductive success, many orchid species lack such rewards. The majority of deceptive orchids simply exploit the instinctive food-foraging behaviour of generalist pollinators. This strategy is termed generalized food deception. To optimize their foraging efficiency, pollinators can learn to discriminate deceptive from rewarding flowers and to focus their visits to the rewarding plants, to the disadvantage of the deceptive plants. Because the reproductive success of non-autogamous orchids entirely relies on pollinator visitation rate, pollinator learning decreases the reproductive success of deceptive orchids. However, the characteristics of deceptive and rewarding plants within a community may affect pollinator learning and visitation rate to a deceptive orchid. Therefore, the biological characteristics of natural plant communities may be crucial to the maintenance of generalized food deceptive orchids. My study focused on the floral, spatial and temporal characteristics of plant communities. I used both in and ex sitar experiments to investigate whether these characteristics influence pollinator visitation rates and the reproductive success of deceptive orchids. A high spatial aggregation of both deceptive and rewarding species decreased the reproductive success of the deceptive species. Also, being of similar flower colour to rewarding sympatric species increased pollinator visitation rates to a deceptive species. The beneficial effect of flower colour similarity was even more pronounced when both species were spatially closely mingled or when the deceptive species flowered after the rewarding species. Finally, pollinator behaviour was unaffected in the short term by a change in the characteristics of plant communities, indicating that pollinators need time to learn under new conditions. Thus, the characteristics of plant communities may crucially affect the reproductive success of deceptive orchids. Although the absence of costs associated with nectar production, the efficient pollen export and the high seed quality of deceptive orchids may favour their maintenance, the characteristics of plant communities may also contribute to it. Therefore, my study provides an alternative yet complementary explanation to the maintenance of generalized food deceptive orchids in natural populations. I discuss the possible implications for the maintenance and the evolution of generalized food deceptive orchids with regards to the floral and temporal dynamics of natural plant communities.

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Four classes of variables are apparent in the problem of scour around bridge piers and abutments--geometry of piers and abutments, stream-flow characteristics, sediment characteristics, and geometry of site. The laboratory investigation, from its inception, has been divided into four phases based on these classes. In each phase the variables in three of the classes are held constant and those in the pertinent class are varied. To date, the first three phases have been studied. Typical scour bole patterns related to the geometry of the pier or abutment have been found. For equilibrium conditions of scour with uniform sand, the velocity of flow and the sand size do not appear to have any measurable effects on the depth of scour. This result is especially encouraging in the search for correlation between model and prototype since it would indicate that, primarily, only the depth of flow might be involved in the scale effect. The technique of model testing has been simplified, therefore, because rate of sediment transportation does not need to be scaled. Prior to the establishment of equilibrium conditions, however, depths of scour in excess of those for equilibrium conditions have been found. A concept of active scour as an imbalance between sediment transport capacity and rate of sediment supply has been used to explain the laboratory observations.

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Generalized Born methods are currently among the solvation models most commonly used for biological applications. We reformulate the generalized Born molecular volume method initially described by (Lee et al, 2003, J Phys Chem, 116, 10606; Lee et al, 2003, J Comp Chem, 24, 1348) using fast Fourier transform convolution integrals. Changes in the initial method are discussed and analyzed. Finally, the method is extensively checked with snapshots from common molecular modeling applications: binding free energy computations and docking. Biologically relevant test systems are chosen, including 855-36091 atoms. It is clearly demonstrated that, precision-wise, the proposed method performs as good as the original, and could better benefit from hardware accelerated boards.

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Standard practice of wave-height hazard analysis often pays little attention to the uncertainty of assessed return periods and occurrence probabilities. This fact favors the opinion that, when large events happen, the hazard assessment should change accordingly. However, uncertainty of the hazard estimates is normally able to hide the effect of those large events. This is illustrated using data from the Mediterranean coast of Spain, where the last years have been extremely disastrous. Thus, it is possible to compare the hazard assessment based on data previous to those years with the analysis including them. With our approach, no significant change is detected when the statistical uncertainty is taken into account. The hazard analysis is carried out with a standard model. Time-occurrence of events is assumed Poisson distributed. The wave-height of each event is modelled as a random variable which upper tail follows a Generalized Pareto Distribution (GPD). Moreover, wave-heights are assumed independent from event to event and also independent of their occurrence in time. A threshold for excesses is assessed empirically. The other three parameters (Poisson rate, shape and scale parameters of GPD) are jointly estimated using Bayes' theorem. Prior distribution accounts for physical features of ocean waves in the Mediterranean sea and experience with these phenomena. Posterior distribution of the parameters allows to obtain posterior distributions of other derived parameters like occurrence probabilities and return periods. Predictives are also available. Computations are carried out using the program BGPE v2.0

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As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

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A simple chaotic flow is presented, which when driven by an identical copy of itself, for certain initial conditions, is able to display generalized synchronization instead of identical synchronization. Being that the drive and the response are observed in exactly the same coordinate system, generalized synchronization is demonstrated by means of the auxiliary system approach and by the conditional Lyapunov spectrum. This is interpreted in terms of changes in the structure of the system stationary points, caused by the coupling, which modify its global behavior.

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The two independent components of the gyration tensor of quartz, g11 and g33, have been spectroscopically measured using a transmission two-modulator generalized ellipsometer. The method is used to determine the optical activity in crystals in directions other than the optic axis, where the linear birefringence is much larger than the optical activity.

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We propose robust estimators of the generalized log-gamma distribution and, more generally, of location-shape-scale families of distributions. A (weighted) Q tau estimator minimizes a tau scale of the differences between empirical and theoretical quantiles. It is n(1/2) consistent; unfortunately, it is not asymptotically normal and, therefore, inconvenient for inference. However, it is a convenient starting point for a one-step weighted likelihood estimator, where the weights are based on a disparity measure between the model density and a kernel density estimate. The one-step weighted likelihood estimator is asymptotically normal and fully efficient under the model. It is also highly robust under outlier contamination. Supplementary materials are available online.

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Proteins PRPF31, PRPF3 and PRPF8 (RP-PRPFs) are ubiquitously expressed components of the spliceosome, a macromolecular complex that processes nearly all pre-mRNAs. Although these spliceosomal proteins are conserved in eukaryotes and are essential for survival, heterozygous mutations in human RP-PRPF genes lead to retinitis pigmentosa, a hereditary disease restricted to the eye. Using cells from patients with 10 different mutations, we show that all clinically relevant RP-PRPF defects affect the stoichiometry of spliceosomal small nuclear RNAs (snRNAs), the protein composition of tri-small nuclear ribonucleoproteins and the kinetics of spliceosome assembly. These mutations cause inefficient splicing in vitro and affect constitutive splicing ex-vivo by impairing the removal of at least 9% of endogenously expressed introns. Alternative splicing choices are also affected when RP-PRPF defects are present. Furthermore, we show that the steady-state levels of snRNAs and processed pre-mRNAs are highest in the retina, indicating a particularly elevated splicing activity. Our results suggest a role for PRPFs defects in the etiology of PRPF-linked retinitis pigmentosa, which appears to be a truly systemic splicing disease. Although these mutations cause widespread and important splicing defects, they are likely tolerated by the majority of human tissues but are critical for retinal cell survival.

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A rigorous unit operation model is developed for vapor membrane separation. The new model is able to describe temperature, pressure, and concentration dependent permeation as wellreal fluid effects in vapor and gas separation with hydrocarbon selective rubbery polymeric membranes. The permeation through the membrane is described by a separate treatment of sorption and diffusion within the membrane. The chemical engineering thermodynamics is used to describe the equilibrium sorption of vapors and gases in rubbery membranes with equation of state models for polymeric systems. Also a new modification of the UNIFAC model is proposed for this purpose. Various thermodynamic models are extensively compared in order to verify the models' ability to predict and correlate experimental vapor-liquid equilibrium data. The penetrant transport through the selective layer of the membrane is described with the generalized Maxwell-Stefan equations, which are able to account for thebulk flux contribution as well as the diffusive coupling effect. A method is described to compute and correlate binary penetrant¿membrane diffusion coefficients from the experimental permeability coefficients at different temperatures and pressures. A fluid flow model for spiral-wound modules is derived from the conservation equation of mass, momentum, and energy. The conservation equations are presented in a discretized form by using the control volume approach. A combination of the permeation model and the fluid flow model yields the desired rigorous model for vapor membrane separation. The model is implemented into an inhouse process simulator and so vapor membrane separation may be evaluated as an integralpart of a process flowsheet.

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One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.