921 resultados para self-organized critical
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Division of labor is a complex phenomenon observed throughout nature. Theoretical studies have focused either on its emergence through self-organization mechanisms or on its adaptive consequences. We suggest that the interaction of self-organization, which undoubtedly characterizes division of labor in social insects, and evolution should be further explored. We review the factors empirically shown to influence task choice. In light of these factors, we review the most important self-organization and evolutionary models for division of labor and outline their advantages and limitations. We describe ways to unify evolution and self-organization in the theoretical study of division of labor and recent results in this area. Finally, we discuss some benchmarks and primary challenges of this approach.
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Division of labor in social insects is determinant to their ecological success. Recent models emphasize that division of labor is an emergent property of the interactions among nestmates obeying to simple behavioral rules. However, the role of evolution in shaping these rules has been largely neglected. Here, we investigate a model that integrates the perspectives of self-organization and evolution. Our point of departure is the response threshold model, where we allow thresholds to evolve. We ask whether the thresholds will evolve to a state where division of labor emerges in a form that fits the needs of the colony. We find that division of labor can indeed evolve through the evolutionary branching of thresholds, leading to workers that differ in their tendency to take on a given task. However, the conditions under which division of labor evolves depend on the strength of selection on the two fitness components considered: amount of work performed and on worker distribution over tasks. When selection is strongest on the amount of work performed, division of labor evolves if switching tasks is costly. When selection is strongest on worker distribution, division of labor is less likely to evolve. Furthermore, we show that a biased distribution (like 3:1) of workers over tasks is not easily achievable by a threshold mechanism, even under strong selection. Contrary to expectation, multiple matings of colony foundresses impede the evolution of specialization. Overall, our model sheds light on the importance of considering the interaction between specific mechanisms and ecological requirements to better understand the evolutionary scenarios that lead to division of labor in complex systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00265-012-1343-2) contains supplementary material, which is available to authorized users.
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Shoreline undulations extending into the bathymetric contours with a length scale larger than that of the rhythmic surf zone bars are referred to as shoreline sand waves. Many observed undulations along sandy coasts display a wavelength in the order 1-7 km. Several models that are based on the hypothesis that sand waves emerge from a morphodynamic instability in case of very oblique wave incidence predict this range of wavelengths. Here we investigate the physical reasons for the wavelength selection and the main parametric trends of the wavelength in case of sand waves arising from such instability. It is shown that the existence of a minimum wavelength depends on an interplay between three factors affecting littoral drift: (A) the angle of wave fronts relative to local shoreline, which tends to cause maximum transport at the downdrift flank of the sand wave, (B) the refractive energy spreading which tends to cause maximum transport at the updrift flank and (C) wave focusing (de-focusing) by the capes (bays), which tends to cause maximum transport at the crest or slightly downdrift of it. Processes A and C cause decay of the sand waves while process B causes their growth. For low incidence angles, B is very weak so that a rectilinear shoreline is stable. For large angles and long sand waves, B is dominant and causes the growth of sand waves. For large angles and short sand waves C is dominant and the sand waves decay. Thus, wavelength selection depends on process C, which essentially depends on shoreline curvature. The growth rate of very long sand waves is weak because the alongshore gradients in sediment transport decrease with the wavelength. This is why there is an optimum or dominant wavelength. It is found that sand wave wavelength scales with λ0/β where λ0 is the water wave wavelength in deep water and β is the mean bed slope from shore to the wave base.
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A new dynamic model of dolomitization predicts a multitude of textural, paragenetic, geochemical and other properties of burial dolomites. The model is based on two postulates, (1) that the dolomitizing brine is Mg-rich but under saturated with both calcite and dolomite, and (2) that the dolomite-for-calcite replacement happens not by dissolution-precipitation as usually assumed, but by dolomite-growth-driven pressure solution of the calcite host. Crucially, the dolomite-for-calcite replacement turns out to be self-accelerating via Ca2 : the Ca2 released by each replacement increment accelerates the rate of the next, and so on. As a result, both pore-fluid Ca2 and replacement rate grow exponentially.
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Step bunching develops in the epitaxy of SrRuO3 on vicinal SrTiO3(001) substrates. We have investigated the formation mechanisms and we show here that step bunching forms by lateral coalescence of wedgelike three-dimensional islands that are nucleated at substrate steps. After coalescence, wedgelike islands become wider and straighter with growth, forming a self-organized network of parallel step bunches with altitudes exceeding 30 unit cells, separated by atomically flat terraces. The formation mechanism of step bunching in SrRuO3, from nucleated islands, radically differs from one-dimensional models used to describe bunching in semiconducting materials. These results illustrate that growth phenomena of complex oxides can be dramatically different to those in semiconducting or metallic systems.
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La monografía presenta la auto-organización sociopolítica como la mejor manera de lograr patrones organizados en los sistemas sociales humanos, dada su naturaleza compleja y la imposibilidad de las tareas computacionales de los regímenes políticos clásico, debido a que operan con control jerárquico, el cual ha demostrado no ser óptimo en la producción de orden en los sistemas sociales humanos. En la monografía se extrapola la teoría de la auto-organización en los sistemas biológicos a las dinámicas sociopolíticas humanas, buscando maneras óptimas de organizarlas, y se afirma que redes complejas anárquicas son la estructura emergente de la auto-organización sociopolítica.
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We present evidence that large-scale spatial coherence of 40 Hz oscillations can emerge dynamically in a cortical mean field theory. The simulated synchronization time scale is about 150 ms, which compares well with experimental data on large-scale integration during cognitive tasks. The same model has previously provided consistent descriptions of the human EEG at rest, with tranquilizers, under anesthesia, and during anesthetic-induced epileptic seizures. The emergence of coherent gamma band activity is brought about by changing just one physiological parameter until cortex becomes marginally unstable for a small range of wavelengths. This suggests for future study a model of dynamic computation at the edge of cortical stability.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We analyze long-range time correlations and self-similar characteristics of the electrostatic turbulence at the plasma edge and scrape-off layer in the Tokamak Chauffage Alfven Bresillien (TCABR), with low and high Magnetohydrodynamics (MHD) activity. We find evidence of self-organized criticality (SOC), mainly in the region near the tokamak limiter. Comparative analyses of data before and during the MHD activity reveals that during the high mHD activity the Hurst parameter decreases. Finally, we present a cellular automaton whose parameters are adjusted to simulate the analyzed turbulence SOC change with the MHD activity variation. (C) 2011 Published by Elsevier B.V.
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A nanostructured thin film is a thin material layer, usually supported by a (solid) substrate, which possesses subdomains with characteristic nanoscale dimensions (10 ~ 100 nm) that are differentiated by their material properties. Such films have captured vast research interest because the dimensions and the morphology of the nanostructure introduce new possibilities to manipulating chemical and physical properties not found in bulk materials. Block copolymer (BCP) self-assembly, and anodization to form nanoporous anodic aluminium oxide (AAO), are two different methods for generating nanostructures by self-organization. Using poly(styrene-block-methyl methacrylate) (PS-b-PMMA) nanopatterned thin films, it is demonstrated that these polymer nanopatterns can be used to study the influence of nanoscale features on protein-surface interactions. Moreover, a method for the directed assembly of adsorbed protein nanoarrays, based on the nanoscale juxtaposition of the BCP surface domains, is also demonstrated. Studies on protein-nanopattern interactions may inform the design of biomaterials, biosensors, and relevant cell-surface experiments that make use of nanoscale structures. In addition, PS-b-PMMA and AAO thin films are also demonstrated for use as optical waveguides at visible wavelengths. Due to the sub-wavelength nature of the nanostructures, scattering losses are minimized, and the optical response is amenable to analysis with effective medium theory (EMT). Optical waveguide measurements and EMT analysis of the films’ optical anisotropy enabled the in situ characterization of the PS-b-PMMA nanostructure, and a variety of surface processes within the nanoporous AAO involving (bio)macromolecules at high sensitivity.
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Nanotechnology entails the manufacturing and manipulation of matter at length scales ranging from single atoms to micron-sized objects. The ability to address properties on the biologically-relevant nanometer scale has made nanotechnology attractive for Nanomedicine. This is perceived as a great opportunity in healthcare especially in diagnostics, therapeutics and more in general to develop personalized medicine. Nanomedicine has the potential to enable early detection and prevention, and to improve diagnosis, mass screening, treatment and follow-up of many diseases. From the biological standpoint, nanomaterials match the typical size of naturally occurring functional units or components of living organisms and, for this reason, enable more effective interaction with biological systems. Nanomaterials have the potential to influence the functionality and cell fate in the regeneration of organs and tissues. To this aim, nanotechnology provides an arsenal of techniques for intervening, fabricate, and modulate the environment where cells live and function. Unconventional micro- and nano-fabrication techniques allow patterning biomolecules and biocompatible materials down to the level of a few nanometer feature size. Patterning is not simply a deterministic placement of a material; in a more extended acception it allows a controlled fabrication of structures and gradients of different nature. Gradients are emerging as one of the key factors guiding cell adhesion, proliferation, migration and even differentiation in the case of stem cells. The main goal of this thesis has been to devise a nanotechnology-based strategy and tools to spatially and temporally control biologically-relevant phenomena in-vitro which are important in some fields of medical research.
Intentionally in non-equilibrium systems? The functional aspects of self-organized pattern formation