990 resultados para random processes
Resumo:
We uncover the global organization of clustering in real complex networks. To this end, we ask whether triangles in real networks organize as in maximally random graphs with given degree and clustering distributions, or as in maximally ordered graph models where triangles are forced into modules. The answer comes by way of exploring m-core landscapes, where the m-core is defined, akin to the k-core, as the maximal subgraph with edges participating in at least m triangles. This property defines a set of nested subgraphs that, contrarily to k-cores, is able to distinguish between hierarchical and modular architectures. We find that the clustering organization in real networks is neither completely random nor ordered although, surprisingly, it is more random than modular. This supports the idea that the structure of real networks may in fact be the outcome of self-organized processes based on local optimization rules, in contrast to global optimization principles.
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We present a model in which particles (or individuals of a biological population) disperse with a rest time between consecutive motions (or migrations) which may take several possible values from a discrete set. Particles (or individuals) may also react (or reproduce). We derive a new equation for the effective rest time T˜ of the random walk. Application to the neolithic transition in Europe makes it possible to derive more realistic theoretical values for its wavefront speed than those following from the single-delayed framework presented previously [J. Fort and V. Méndez, Phys. Rev. Lett. 82, 867 (1999)]. The new results are consistent with the archaeological observations of this important historical process
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Generally, so-called control processes are thought to be necessary when we must perform one out of several competing actions. Some examples include performance of a less well-practiced action instead of a well-practiced one (prepotency); learning a new action (novelty); and rapidly switching from one action to another (task-switching). While it certainly is difficult to perform the desired action in these circumstances, it is less clear that a separate set of processes (e.g., control processes) are necessary to explain the observed behavior. Another way to approach the study of control processes is to investigate physiological dependent measures (e.g., electrophysiological or neuroimaging measures). Although these offer another avenue of inquiry into control processes, they have yet to furnish unambiguous evidence that control processes exist. While this might suggest that there are no control processes, it is also possible that our methods are insufficiently sensitive to measure control processes. We have investigated this latter possibility using tasks that are neuroanatomically distinct, though within the same modality (vision). This approach did not yield evidence for a separable set of control processes. However, recent works using a task-switching paradigm in which subjects switch between a visual and an auditory task suggest that switching both task and modality may be importantly different than switching task within a given modality. This may represent a way forward in the study of control processes.
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The Atlas Mountains in Morocco are considered as type examples of intracontinental chains, with high topography that contrasts with moderate crustal shortening and thickening. Whereas recent geological studies and geodynamic modeling have suggested the existence of dynamic topography to explain this apparent contradiction, there is a lack of modern geophysical data at the crustal scale to corroborate this hypothesis. Newly-acquired magnetotelluric data image the electrical resistivity distribution of the crust from the Middle Atlas to the Anti-Atlas, crossing the tabular Moulouya Plain and the High Atlas. All the units show different and unique electrical signatures throughout the crust reflecting the tectonic history of development of each one. In the upper crust electrical resistivity values may be associated to sediment sequences in the Moulouya and Anti-Atlas and to crustal scale fault systems in the High Atlas developed during the Cenozoic times. In the lower crust the low resistivity anomaly found below the Mouluya plain, together with other geophysical (low velocity anomaly, lack of earthquakes and minimum Bouguer anomaly) and geochemical (Neogene-Quaternary intraplate alkaline volcanic fields) evidence, infer the existence of a small degree of partial melt at the base of the lower crust. The low resistivity anomaly found below the Anti-Atlas may be associated with a relict subduction of Precambrian oceanic sediments, or to precipitated minerals during the release of fluids from the mantle during the accretion of the Anti-Atlas to the West African Supercontinent during the Panafrican orogeny ca. 685 Ma).
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We generalize a previous model of time-delayed reaction–diffusion fronts (Fort and Méndez 1999 Phys. Rev. Lett. 82 867) to allow for a bias in the microscopic random walk of particles or individuals. We also present a second model which takes the time order of events (diffusion and reproduction) into account. As an example, we apply them to the human invasion front across the USA in the 19th century. The corrections relative to the previous model are substantial. Our results are relevant to physical and biological systems with anisotropic fronts, including particle diffusion in disordered lattices, population invasions, the spread of epidemics, etc
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Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.
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We report Monte Carlo results for a nonequilibrium Ising-like model in two and three dimensions. Nearest-neighbor interactions J change sign randomly with time due to competing kinetics. There follows a fast and random, i.e., spin-configuration-independent diffusion of Js, of the kind that takes place in dilute metallic alloys when magnetic ions diffuse. The system exhibits steady states of the ferromagnetic (antiferromagnetic) type when the probability p that J>0 is large (small) enough. No counterpart to the freezing phenomena found in quenched spin glasses occurs. We compare our results with existing mean-field and exact ones, and obtain information about critical behavior.
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The magnetization process of Co/Al oxide/Py trilayers and its evolution with the temperature have been analyzed. The particular behavior of the Co layers, including the shift of the hysteresis loops and a coercivity increase with the decrease of temperature, is related with the apparition of a CoO layer at the Co/Al-oxide interface.
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The world-class Idrija mercury deposit (western Slovenia) is hosted by highly deformed Permocarboniferous to Middle Triassic sedimentary rocks within a complex tectonic structure at the transition between the External Dinarides and the Southern Alps. Concordant and discordant mineralization formed concomitant with Middle Triassic bimodal volcanism in an aborted rift. A multiple isotopic (C, O, S) investigation of host rocks and ore minerals was performed to put constraints on the source and composition of the fluid, and the hydrothermal alteration. The distributions of the delta(13)C and delta(18)O values of host and gangue carbonates are indicative of a fracture-controlled hydrothermal system, with locally high fluid-rock ratios. Quantitative modeling of the delta(13)C and delta(18)O covariation for host carbonates during temperature dependent fluid-rock interaction, and concomitant precipitation of void-filling dolomites points to a slightly acidic hydrothermal fluid (delta(13)Capproximate to-4parts per thousand and delta(18)Oapproximate to+10parts per thousand), which most likely evolved during isotopic exchange with carbonates under low fluid/rock ratios. The delta(34)S values of hydrothermal and sedimentary sulfur minerals were used to re-evaluate the previously proposed magmatic and evaporitic sulfur sources for the mineralization, and to assess the importance of other possible sulfur sources such as the contemporaneous seawater sulfate, sedimentary pyrite, and organic sulfur compounds. The delta(34)S values of the sulfides show a large variation at deposit down to hand-specimen scale. They range for cinnabar and pyrite from -19.1 to +22.8parts per thousand, and from -22.4 to +59.6parts per thousand, respectively, suggesting mixing of sulfur from different sources. The peak of delta(34)S values of cinnabar and pyrite close to 0parts per thousand is compatible with ore sulfur derived dominantly from a magmatic fluid and/or from hydrothermal leaching of basement rocks. The similar stratigraphic trends of the delta(34)S values of both cinnabar and pyrite suggest a minor contribution of sedimentary sulfur (pyrite and organic sulfur) to the ore formation. Some of the positive delta(34)S values are probably derived from thermochemical reduction of evaporitic and contemporaneous seawater sulfates.
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We present a two-level model of concurrent communicating systems (CCS) to serve as a basis formachine consciousness. A language implementing threads within logic programming is ¯rstintroduced. This high-level framework allows for the de¯nition of abstract processes that can beexecuted on a virtual machine. We then look for a possible grounding of these processes into thebrain. Towards this end, we map abstract de¯nitions (including logical expressions representingcompiled knowledge) into a variant of the pi-calculus. We illustrate this approach through aseries of examples extending from a purely reactive behavior to patterns of consciousness.
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This paper suggests a method for obtaining efficiency bounds in models containing either only infinite-dimensional parameters or both finite- and infinite-dimensional parameters (semiparametric models). The method is based on a theory of random linear functionals applied to the gradient of the log-likelihood functional and is illustrated by computing the lower bound for Cox's regression model
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The Internet is becoming more and more popular among drug users. The use of websites and forums to obtain illicit drugs and relevant information about the means of consumption is a growing phenomenon mainly for new synthetic drugs. Gamma Butyrolactone (GBL), a chemical precursor of Gamma Hydroxy Butyric acid (GHB), is used as a "club drug" and also in drug facilitated sexual assaults. Its market takes place mainly on the Internet through online websites but the structure of the market remains unknown. This research aims to combine digital, physical and chemical information to help understand the distribution routes and the structure of the GBL market. Based on an Internet monitoring process, thirty-nine websites selling GBL, mainly in the Netherlands, were detected between January 2010 and December 2011. Seventeen websites were categorized into six groups based on digital traces (e.g. IP addresses and contact information). In parallel, twenty-five bulk GBL specimens were purchased from sixteen websites for packaging comparisons and carbon isotopic measurements. Packaging information showed a high correlation with digital data confirming the links previously established whereas chemical information revealed undetected links and provided complementary information. Indeed, while digital and packaging data give relevant information about the retailers, the supply routes and the distribution close to the consumer, the carbon isotopic data provides upstream information about the production level and in particular the synthesis pathways and the chemical precursors. A three-level structured market has been thereby identified with a production level mainly located in China and in Germany, an online distribution level mainly hosted in the Netherlands and the customers who order on the Internet.
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RésuméLa coexistence de nombreuses espèces différentes a de tout temps intrigué les biologistes. La diversité et la composition des communautés sont influencées par les perturbations et l'hétérogénéité des conditions environnementales. Bien que dans la nature la distribution spatiale des conditions environnementales soit généralement autocorrélée, cet aspect est rarement pris en compte dans les modèles étudiant la coexistence des espèces. Dans ce travail, nous avons donc abordé, à l'aide de simulations numériques, la coexistence des espèces ainsi que leurs caractéristiques au sein d'un environnement autocorrélé.Afin de prendre en compte cet élément spatial, nous avons développé un modèle de métacommunauté (un ensemble de communautés reliées par la dispersion des espèces) spatialement explicite. Dans ce modèle, les espèces sont en compétition les unes avec les autres pour s'établir dans un nombre de places limité, dans un environnement hétérogène. Les espèces sont caractérisées par six traits: optimum de niche, largeur de niche, capacité de dispersion, compétitivité, investissement dans la reproduction et taux de survie. Nous nous sommes particulièrement intéressés à l'influence de l'autocorrélation spatiale et des perturbations sur la diversité des espèces et sur les traits favorisés dans la métacommunauté. Nous avons montré que l'autocorrélation spatiale peut avoir des effets antagonistes sur la diversité, en fonction du taux de perturbations considéré. L'influence de l'autocorrélation spatiale sur la capacité de dispersion moyenne dans la métacommunauté dépend également des taux de perturbations et survie. Nos résultats ont aussi révélé que de nombreuses espèces avec différents degrés de spécialisation (i.e. différentes largeurs de niche) peuvent coexister. Toutefois, les espèces spécialistes sont favorisées en absence de perturbations et quand la dispersion est illimitée. A l'opposé, un taux élevé de perturbations sélectionne des espèces plus généralistes, associées avec une faible compétitivité.L'autocorrélation spatiale de l'environnement, en interaction avec l'intensité des perturbations, influence donc de manière considérable la coexistence ainsi que les caractéristiques des espèces. Ces caractéristiques sont à leur tour souvent impliquées dans d'importants processus, comme le fonctionnement des écosystèmes, la capacité des espèces à réagir aux invasions, à la fragmentation de l'habitat ou aux changements climatiques. Ce travail a permis une meilleure compréhension des mécanismes responsables de la coexistence et des caractéristiques des espèces, ce qui est crucial afin de prédire le devenir des communautés naturelles dans un environnement changeant.AbstractUnderstanding how so many different species can coexist in nature is a fundamental and long-standing question in ecology. Community diversity and composition are known to be influenced by heterogeneity in environmental conditions and disturbance. Though in nature the spatial distribution of environmental conditions is frequently autocorrelated, this aspect is seldom considered in models investigating species coexistence. In this work, we thus addressed several questions pertaining to species coexistence and composition in spatially autocorrelated environments, with a numerical simulations approach.To take into account this spatial aspect, we developed a spatially explicit model of metacommunity (a set of communities linked by dispersal of species). In this model, species are trophically equivalent, and compete for space in a heterogeneous environment. Species are characterized by six life-history traits: niche optimum, niche breadth, dispersal, competitiveness, reproductive investment and survival rate. We were particularly interested in the influence of environmental spatial autocorrelation and disturbance on species diversity and on the traits of the species favoured in the metacommunity. We showed that spatial autocorrelation can have antagonistic effects on diversity depending on disturbance rate. Similarly, spatial autocorrelation interacted with disturbance rate and survival rate to shape the mean dispersal ability observed in the metacommunity. Our results also revealed that many species with various degrees of specialization (i.e. different niche breadths) can coexist together. However specialist species were favoured in the absence of disturbance, and when dispersal was unlimited. In contrast, high disturbance rate selected for more generalist species, associated with low competitive ability.The spatial structure of the environment, together with disturbance and species traits, thus strongly impacts species diversity and, more importantly, species composition. Species composition is known to affect several important metacommunity properties such as ecosystem functioning, resistance and reaction to invasion, to habitat fragmentation and to climate changes. This work allowed a better understanding of the mechanisms responsible for species composition, which is of crucial importance to predict the fate of natural metacommunities in changing environments
Resumo:
The present document should be seen as one more contribution to the debate to the reform processes and a small guide to these processes and their latest outcomes.