873 resultados para Theory of nuclear architecture
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Includes bibliography
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De Sousa′s comprehensive two-part review of a diversity of contemporary approaches to the study of consciousness is highly welcome. He makes us aware of a proliferation of theoretical and empirical approaches targeting a common theme, but diverging in many ways. He skilfully accomplishes a classification of kinds of approach, identification of the main representatives, their contributions, and respective limitations. However, he does not show how the desired integration could be accomplished. Besides summarising de Sousa′s efficient analytical work, I make critical comments and briefly report my contribution for the integration project.© MSM 2013.
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Includes bibliography
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Includes bibliography
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Includes bibliography
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Perhaps due to its origins in a production scheduling software called Optimised Production Technology (OPT), plus the idea of focusing on system constraints, many believe that the Theory of Constraints (TOC) has a vocation for optimal solutions. Those who assess TOC according to this perspective indicate that it guarantees an optimal solution only in certain circumstances. In opposition to this view and founded on a numeric example of a production mix problem, this paper shows, by means of TOC assumptions, why the TOC should not be compared to methods intended to seek optimal or the best solutions, but rather sufficiently good solutions, possible in non-deterministic environments. Moreover, we extend the range of relevant literature on product mix decision by introducing a heuristic based on the uniquely identified work that aims at achieving feasible solutions according to the TOC point of view. The heuristic proposed is tested on 100 production mix problems and the results are compared with the responses obtained with the use of Integer Linear Programming. The results show that the heuristic gives good results on average, but performance falls sharply in some situations. © 2013 Copyright Taylor and Francis Group, LLC.
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Revisa las aplicaciones, necesidades, problemas y perspectivas para el uso pacifico de la energia nuclear en cinco paises anglo- parlantes del Caribe: Belice, Jamaica, Santa Lucia, Trinidad y Tabago y Barbados.
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Contiene la organizacion y debates de la reunion que tuvo como objetivo analizar la situacion actual, evolucion proyectada, restricciones actuales y previsibles a la introduccion y expansion de la utilizacion de la energia nuclear con fines pacificos a la luz de las necesidades y prioridades de la region.
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The nuclear poly(A)-binding protein 1 (PABPN1) is a ubiquitously expressed protein that plays a critical role in polyadenylation. Short expansions of the polyalanine tract in the N-terminus of PABPN1 lead to oculopharyngeal muscular dystrophy (OPMD), which is an adult onset disease characterized by eyelid drooping, difficulty in swallowing and weakness in the proximal limb muscles. Although significant data from in vitro biochemical assays define the function of PABPN1 in control of poly(A) tail length, little is known about the role of PABPN1 in mammalian cells. To assess the function of PABPN1 in mammalian cells and specifically in cells affected in OPMD, we examined the effects of PABPN1 depletion using siRNA in primary mouse myoblasts from extraocular, pharyngeal and limb muscles. PABPN1 knockdown significantly decreased cell proliferation and myoblast differentiation during myogenesis in vitro. At the molecular level, PABPN1 depletion in myoblasts led to a shortening of mRNA poly(A) tails, demonstrating the cellular function of PABPN1 in polyadenylation control in a mammalian cell. In addition, PABPN1 depletion caused nuclear accumulation of poly(A) RNA, revealing that PABPN1 is required for proper poly(A) RNA export from the nucleus. Together, these experiments demonstrate that PABPN1 plays an essential role in myoblast proliferation and differentiation, suggesting that it is required for muscle regeneration and maintenance in vivo.
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Neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements that are shown to be extremely effective in computation. This paper presents an architecture of recurrent neural networks for solving the N-Queens problem. More specifically, a modified Hopfield network is developed and its internal parameters are explicitly computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points, which represent a solution of the considered problem. The network is shown to be completely stable and globally convergent to the solutions of the N-Queens problem. A fuzzy logic controller is also incorporated in the network to minimize convergence time. Simulation results are presented to validate the proposed approach.
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The timed-initiation paradigm developed by Ghez and colleagues (1997) has revealed two modes of motor planning: continuous and discrete. Continuous responding occurs when targets are separated by less than 60° of spatial angle, and discrete responding occurs when targets are separated by greater than 60°. Although these two modes are thought to reflect the operation of separable strategic planning systems, a new theory of movement preparation, the Dynamic Field Theory, suggests that two modes emerge flexibly from the same system. Experiment 1 replicated continuous and discrete performance using a task modified to allow for a critical test of the single system view. In Experiment 2, participants were allowed to correct their movements following movement initiation (the standard task does not allow corrections). Results showed continuous planning performance at large and small target separations. These results are consistent with the proposal that the two modes reflect the time-dependent “preshaping” of a single planning system.
Generalizing the dynamic field theory of spatial cognition across real and developmental time scales
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Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.
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Este artigo propõe que a semiótica peirceana pode oferecer bases tanto lógicas quanto epistemológicas para a busca de uma teoria geral da comunicação. No entanto, o desenvolvimento de uma teoria semiótica da comunicação depende, em primeiro lugar, de uma melhor compreensão dos aspectos formais do signo, tarefa atribuída por Peirce à gramática, o primeiro ramo de sua semiótica. Nós apresentamos uma análise das relações do signo, revelando um aspecto não trabalhado por Peirce, ampliando seu número para onze. Este novo aspecto é a relação triádica entre signo, objeto dinâmico e interpretante dinâmico (S-OD-ID). Nós defendemos que esta relação é essencial para a compreensão da comunicação como semiose, por dar conta da repetição ou redundância do signo comunicativo, quando se cria ou transmite informação. O artigo pretende dar um passo a mais na direção de uma teoria da comunicação verdadeiramente universal, através do vínculo entre a semiótica peirceana e a moderna filosofia da linguagem.