954 resultados para Self-organized criticality
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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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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
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A colloidal deposition technique is presented to construct long-range ordered hybrid arrays of self-assembled quantum dots and metal nanoparticles. Quantum dots are promising for novel opto-electronic devices but, in most cases, their optical transitions of interest lack sufficient light absorption to provide a significant impact in their implementation. A potential solution is to couple the dots with localized plasmons in metal nanoparticles. The extreme confinement of light in the near-field produced by the nanoparticles can potentially boost the absorption in the quantum dots by up to two orders of magnitude. In this work, light extinction measurements are employed to probe the plasmon resonance of spherical gold nanoparticles in lead sulfide colloidal quantum dots and amorphous silicon thin-films. Mie theory computations are used to analyze the experimental results and determine the absorption enhancement that can be generated by the highly intense near-field produced in the vicinity of the gold nanoparticles at their surface plasmon resonance. The results presented here are of interest for the development of plasmon-enhanced colloidal nanostructured photovoltaic materials, such as colloidal quantum dot intermediate-band solar cells.
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We investigated the defensive behavior of honeybees under controlled experimental conditions. During an attack on two identical targets, the spatial distribution of stings varied as a function of the total number of stings, evincing the classic “pitchfork bifurcation” phenomenon of nonlinear dynamics. The experimental results support a model of defensive behavior based on a self-organizing mechanism. The model helps to explain several of the characteristic features of the honeybee defensive response: (i) the ability of the colony to localize and focus its attack, (ii) the strong variability between different hives in the intensity of attack, as well as (iii) the variability observed within the same hive, and (iv) the ability of the colony to amplify small differences between the targets.
Self-organized phase transitions in neural networks as a neural mechanism of information processing.
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Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition. The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns. The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern. The reverse transition may be induced by the Hebbian unlearning process without input. The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input. To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stays near the critical state corresponding to the phase transition point.
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We present a simple mathematical model of biological macroevolution. The model describes an ecology of adapting, interacting species. The environment of any given species is affected by other evolving species; hence, it is not constant in time. The ecology as a whole evolves to a "self-organized critical" state where periods of stasis alternate with avalanches of causally connected evolutionary changes. This characteristic behavior of natural history, known as "punctuated equilibrium," thus finds a theoretical explanation as a self-organized critical phenomenon. The evolutionary behavior of single species is intermittent. Also, large bursts of apparently simultaneous evolutionary activity require no external cause. Extinctions of all sizes, including mass extinctions, may be a simple consequence of ecosystem dynamics. Our results are compared with data from the fossil record.
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Mode of access: Internet.
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This work reports the first instance of self-organized thermoset blends containing diblock copolymers with a crystallizable thermoset-immiscible block. Nanostructured thermoset blends of bisphenol A-type epoxy resin (ER) and a low-molecular-weight (M-n = 1400) amphiphilic polyethylene-block-poly(ethylene oxide) (EEO) symmetric diblock copolymer were prepared using 4,4'-methylenedianiline (MDA) as curing agent and were characterized by transmission electron microscopy (TEM), atomic force microscopy (AFM), small-angle X-ray scattering (SAXS), and differential scanning calorimetry (DSC). All the MDA-cured ER/EEO blends do not show macroscopic phase separation but exhibit microstructures. The ER selectively mixes with the epoxy-miscible PEO block in the EEO diblock copolymer whereas the crystallizable PE blocks that are immiscible with ER form separate microdomains at nanoscales in the blends. The PE crystals with size on nanoscales are formed and restricted within the individual spherical micelles in the nanostructured ER/EEO blends with EEO content up to 30 wt %. The spherical micelles are highly aggregated in the blends containing 40 and 50 wt % EEO. The PE dentritic crystallites exist in the blend containing 50 wt % EEO whereas the blends with even higher EEO content are completely volume-filled with PE spherulites. The semicrystalline microphase-separated lamellae in the symmetric EEO diblock copolymer are swollen in the blend with decreasing EEO content, followed by a structural transition to aggregated spherical micellar phase morphology and, eventually, spherical micellar phase morphology at the lowest EEO contents. Three morphological regimes are identified, corresponding precisely to the three regimes of crystallization kinetics of the PE blocks. The nanoscale confinement effect on the crystallization kinetics in nanostructured thermoset blends is revealed for the first time. This new phenomenon is explained on the basis of homogeneous nucleation controlled crystallization within nanoscale confined environments in the block copolymer/thermoset blends.
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The paper explores the functionalities of eight start pages and considers their usefulness when used as a mashable platform for deployment of personal learning environments (PLE) for self-organized learners. The Web 2.0 effects and eLearning 2.0 strategies are examined from the point of view of how they influence the methods of gathering and capturing data, information and knowledge, and the learning process. Mashup technology is studied in order to see what kind of components can be used in PLE realization. A model of a PLE for self-organized learners is developed and it is used to prototype a personal learning and research environment in the start pages Netvibes, Pageflakes and iGoogle.
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We focus on athermal phase transitions where in discrete and dissipative avalanches are observed in physical observables as the system jumps from one metastable state to another, when driven by an external field. Using higher order statistics of time dependent avalanches, or noise, in electrical resistivity during temperature-driven martensite transformation in thin nickel-titanium films, we demonstrate evidence suggesting the existence of a singular `global instability' or divergence of the correlation length as a function of temperature at the transition. These results not only establish a mapping of non-equilibrium first order phase transition and equilibrium critical phenomena, but perhaps also call for a re-evaluation of many existing experimental claims of self-organized criticality.
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We report results of statistical and dynamic analysis of the serrated stress-time curves obtained from compressive constant strain-rate tests on two metallic glass samples with different ductility levels in an effort to extract hidden information in the seemingly irregular serrations. Two distinct types of dynamics are detected in these two alloy samples. The stress-strain curve corresponding to the less ductile Zr65Cu15Ni10Al10 alloy is shown to exhibit a finite correlation dimension and a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. In contrast, for the more ductile Cu47.5Zr47.5Al5 alloy, the distributions of stress drop magnitudes and their time durations obey a power-law scaling reminiscent of a self-organized critical state. The exponents also satisfy the scaling relation compatible with self-organized criticality. Possible physical mechanisms contributing to the two distinct dynamic regimes are discussed by drawing on the analogy with the serrated yielding of crystalline samples. The analysis, together with some physical reasoning, suggests that plasticity in the less ductile sample can be attributed to stick-slip of a single shear band, while that of the more ductile sample could be attributed to the simultaneous nucleation of a large number of shear bands and their mutual interactions. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.