939 resultados para SELF-ORGANIZATION


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Background: Over many years, it has been assumed that enzymes work either in an isolated way, or organized in small catalytic groups. Several studies performed using "metabolic networks models'' are helping to understand the degree of functional complexity that characterizes enzymatic dynamic systems. In a previous work, we used "dissipative metabolic networks'' (DMNs) to show that enzymes can present a self-organized global functional structure, in which several sets of enzymes are always in an active state, whereas the rest of molecular catalytic sets exhibit dynamics of on-off changing states. We suggested that this kind of global metabolic dynamics might be a genuine and universal functional configuration of the cellular metabolic structure, common to all living cells. Later, a different group has shown experimentally that this kind of functional structure does, indeed, exist in several microorganisms. Methodology/Principal Findings: Here we have analyzed around 2.500.000 different DMNs in order to investigate the underlying mechanism of this dynamic global configuration. The numerical analyses that we have performed show that this global configuration is an emergent property inherent to the cellular metabolic dynamics. Concretely, we have found that the existence of a high number of enzymatic subsystems belonging to the DMNs is the fundamental element for the spontaneous emergence of a functional reactive structure characterized by a metabolic core formed by several sets of enzymes always in an active state. Conclusions/Significance: This self-organized dynamic structure seems to be an intrinsic characteristic of metabolism, common to all living cellular organisms. To better understand cellular functionality, it will be crucial to structurally characterize these enzymatic self-organized global structures.

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Papaseit et al. (Proc. Nati. Acad. Sci. U.S.A. 97, 8364, 2000) showed the decisive role of gravity in the formation of patterns by assemblies of microtubules in vitro. By virtue of a functional scaling, the free energy for MT systems in a gravitational field was constructed. The influence of the gravitational field on MT's self-organization process, that can lead to the isotropic to nematic phase transition, is the focus of this paper. A coupling of a concentration gradient with orientational order characteristic of nernatic ordering pattern formation is the new feature emerging in the presence of gravity. The concentration range corresponding to a phase coexistence region increases with increasing g or NIT concentration. Gravity facilitates the isotropic to nernatic phase transition leading to a significantly broader transition region. The phase transition represents the interplay between the growth in the isotropic phase and the precipitation into the nematic phase. We also present and discuss the numerical results obtained for local NIT concentration change with the height of the vessel, order parameter and phase transition properties.

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Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, indefinite richness, and limited availability of information. Industrial robots, in contrast, operate in highly controlled environments with no or very little uncertainty. Although many challenges remain, concepts from biologically inspired (bio-inspired) robotics will eventually enable researchers to engineer machines for the real world that possess at least some of the desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility.

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In mammals, the development of reflexes is often regarded as an innate process. However, recent findings show that fetuses are endowed with favorable conditions for ontogenetic development. In this article, we hypothesize that the circuitry of at least some mammalian reflexes can be self-organized from the sensory and motor interactions brought forth in a musculoskeletal system. We focus mainly on three reflexes: the myotatic reflex, the reciprocal inhibition reflex, and the reverse myotatic reflex. To test our hypothesis, we conducted a set of experiments on a simulated musculoskeletal system using pairs of agonist and antagonist muscles. The reflex connectivity is obtained by producing spontaneous motor activity in each muscle and by correlating the resulting sensor and motor signals. Our results show that, under biologically plausible conditions, the reflex circuitry thus obtained is consistent with that identified in relation to the analogous mammalian reflexes. In addition, they show that the reflex connectivity obtained depends on the morphology of the musculoskeletal system as well as on the environment that it is embedded in.

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Recent results in spinal research are challenging the historical view that the spinal reflexes are mostly hardwired and fixed behaviours. In previous work we have shown that three of the simplest spinal reflexes could be self-organised in an agonist-antagonist pair of muscles. The simplicity of these reflexes is given from the fact that they entail at most one interneuron mediating the connectivity between afferent inputs and efferent outputs. These reflexes are: the Myotatic, the Reciprocal Inibition and the Reverse Myotatic reflexes. In this paper we apply our framework to a simulated 2D leg model actuated by six muscles (mono- and bi-articular). Our results show that the framework is successful in learning most of the spinal reflex circuitry as well as the corresponding behaviour in the more complicated muscle arrangement. © 2012 Springer-Verlag.

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Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

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The initial InAs growth on InP(1 0 0) during molecular beam epitaxy has been investigated. The as-grown islands were shaped like nanowires and formed dense arrays over the entire surface in the 3-6 monolayer InAs deposition range. The wires were oriented along the [(1) over bar 1 0] direction. Transmission electron microscopy images confirm that the wires are coherently grown on the substrates. Our results suggest that the coherent wire-shaped island formation may be a possible method to fabricate self-organized InAs nanowires. (C) 1999 Elsevier Science B.V. All rights reserved.

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The mechanism of self-organization of quantum dots (QDs) during the growth of InGaAs/GaAs multilayers on GaAs (1 0 0) was investigated with cross-sectional transmission electron microscopy (XTEM), and double-crystal X-ray diffraction (DCXD). We found that the QDs spacing in the first layer can affect the vertical alignment of QDs. There seems to exist one critical lateral QD spacing, below which merging of QDs with different initial size is found to be the dominant mechanism leading to perfect vertical alignment. Once the critical value of QDs spacing is reached, the InGaAs QDs of the first layer are simply reproduced in the upper layers. The X-ray rocking curve clearly shows two sets of satellite peaks, which correspond to the QDs superlattice, and multi-quantum wells (QW) formed by the wetting layers around QDs. (C) 1999 Elsevier Science B.V. All rights reserved.

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The mechanism of self-organization of quantum dots (QDs) during the growth of InGaAs/GaAs multilayers on GaAs (1 0 0) was investigated with cross-sectional transmission electron microscopy (XTEM), and double-crystal X-ray diffraction (DCXD). We found that the QDs spacing in the first layer can affect the vertical alignment of QDs. There seems to exist one critical lateral QD spacing, below which merging of QDs with different initial size is found to be the dominant mechanism leading to perfect vertical alignment. Once the critical value of QDs spacing is reached, the InGaAs QDs of the first layer are simply reproduced in the upper layers. The X-ray rocking curve clearly shows two sets of satellite peaks, which correspond to the QDs superlattice, and multi-quantum wells (QW) formed by the wetting layers around QDs. (C) 1999 Elsevier Science B.V. All rights reserved.

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Self-organization of BaF2 single crystal film under a compressed monolayer of behenic acid (BA) has been investigated by using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The experimental results indicated the (100)-oriented single crystal film of BaF2 was formed under the BA monolayer. The relation between the BaF2 single crystal and the monolayer was discussed.

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A novel morphology of TPBD crystals consisting of a three-dimensional interlaced network was obtained by casting the self-seeded 0.1% benzene solution onto carbon-boated mica. Both the transmission electron microscopy (TEM) and electron diffraction (ED) analyses showed that the network was composed of well-developed lamellae. It is imagined this interesting morphology is the results of asymmetrical growth of the original TPBD lamellae on the amorphous interface, and that their preferred orientation changed when they encountered each other.

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In a probabilistic cellular automaton in which all local transitions have positive probability, the problem of keeping a bit of information for more than a constant number of steps is nontrivial, even in an infinite automaton. Still, there is a solution in 2 dimensions, and this solution can be used to construct a simple 3-dimensional discrete-time universal fault-tolerant cellular automaton. This technique does not help much to solve the following problems: remembering a bit of information in 1 dimension; computing in dimensions lower than 3; computing in any dimension with non-synchronized transitions. Our more complex technique organizes the cells in blocks that perform a reliable simulation of a second (generalized) cellular automaton. The cells of the latter automaton are also organized in blocks, simulating even more reliably a third automaton, etc. Since all this (a possibly infinite hierarchy) is organized in "software", it must be under repair all the time from damage caused by errors. A large part of the problem is essentially self-stabilization recovering from a mess of arbitrary-size and content caused by the faults. The present paper constructs an asynchronous one-dimensional fault-tolerant cellular automaton, with the further feature of "self-organization". The latter means that unless a large amount of input information must be given, the initial configuration can be chosen to be periodical with a small period.

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BP (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI-90-00530); Air Force Office of Scientific Research (90-0175, 90-0128); Army Research Office (DAAL-03-88-K0088)

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