A petri net based timing model for hardware/software co-design of digital systems

We have recently proposed an extension to Petri nets in order to be able to directly deal with all aspects of embedded digital systems. This extension is meant to be used as an internal model of our co-design environment. After analyzing relevant related work, and presenting a short introduction to our extension as a background material, we describe the details of the timing model we use in our approach, which is mainly based in Merlin's time model. We conclude the paper by discussing an example of its usage. © 2004 IEEE.

O modelo Z-D e a função emprego: descrições gráficas à luz da Teoria Geral de Keynes

Este artigo compara três versões do modelo Z-D que descrevem graficamente a função emprego de Keynes. Ao mesmo tempo, o artigo corrige a redação dada por Keynes, na Teoria Geral, à descrição desta função. O artigo conclui que as versões em pauta têm o mérito de demonstrar que é possível descrever a função emprego através de um diagrama inspirado no conceito de demanda efetiva e considerando suposições menos restritas que as utilizadas por Keynes.

Postural control in children: Coupling to dynamic somatosensory information

The purpose of this investigation was to determine whether the coupling between dynamic somatosensory information and body sway is similar in children and adults. Thirty children (4-, 6-, and 8-year-olds) and 10 adults stood upright, with feet parallel, and lightly contacting the fingertip to a rigid metal plate that moved rhythmically at 0.2, 0.5, and 0.8 Hz. Light touch to the moving contact surface induced postural sway in all participants. The somatosensory stimulus produced a broadband frequency response in children, while the adult response was primarily at the driving frequency. Gain, as a function of frequency, was qualitatively the same in children and adults. Phase decreased less in 4-year-olds than other age groups, suggesting a weaker coupling to position information in the sensory stimulus. Postural sway variability was larger in children than adults. These findings suggest that, even as young as age 6, children show well-developed coupling to the sensory stimulus. However, unlike adults, this coupling is not well focused at the frequency specified by the somatosensory signal. Children may be unable to uncouple from sensory information that is less relevant to the task, resulting in a broadband response in their frequency spectrum. Moreover, higher sway variability may not result from the sensory feedback process, but rather from the children's underdeveloped ability to estimate an internal model of body orientation.

Fluctuating dimension in a discrete model for quantum gravity based on the spectral principle

The spectral principle of Connes and Chamseddine is used as a starting point to define a discrete model for Euclidean quantum gravity. Instead of summing over ordinary geometries, we consider the sum over generalized geometries where topology, metric, and dimension can fluctuate. The model describes the geometry of spaces with a countable number n of points, and is related to the Gaussian unitary ensemble of Hermitian matrices. We show that this simple model has two phases. The expectation value , the average number of points in the Universe, is finite in one phase and diverges in the other. We compute the critical point as well as the critical exponent of . Moreover, the space-time dimension delta is a dynamical observable in our model, and plays the role of an order parameter. The computation of is discussed and an upper bound is found, < 2.

Exogenous Administration of 15d-PGJ(2)-Loaded Nanocapsules Inhibits Bone Resorption in a Mouse Periodontitis Model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Stability and convergence analysis of a neural model applied in nonlinear systems optimization

A neural model for solving nonlinear optimization problems is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The network is shown to be completely stable and globally convergent to the solutions of nonlinear optimization problems. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are presented to validate the developed methodology.

A modified Hopfield model for solving the N-Queens problem

A neural network model for solving the N-Queens problem is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of the N-Queens problem. Simulation results are presented to validate the proposed approach.

Design and analysis of an efficient neural network model for solving nonlinear optimization problems

This paper presents an efficient approach based on a recurrent neural network for solving constrained nonlinear optimization. More specifically, a modified Hopfield network is developed, and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it handles optimization and constraint terms in different stages with no interference from each other. Moreover, the proposed approach does not require specification for penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyse its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.

Implementation of two-stage Hopfield model and its application in nonlinear systems

This paper presents an efficient neural network for solving constrained nonlinear optimization problems. More specifically, a two-stage neural network architecture is developed and its internal parameters are computed using the valid-subspace technique. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty or weighting parameters for its initialization.

Exploring community assembly through an individual-based model for trophic interactions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Isomery of SU3 states in the strictly restricted dynamics model

Employing the general principles of classification of SU3 states, we have found 285 quantum number isomers (QNI), i.e. nuclei for which there are two possible SU3 quantum number sets, characterized by the maximal eigenvalue of the SU3 group Casimir operator, at the minimal value N-0(min) for the quantum number N-0 of the group U3(A-1) symmetric representation, allowed by the Pauli principle. 41 of these QNI can be attributed to the nun-excited, ground SU3 configurations of realistic nuclei. Two examples of QNI: Si-28 and Zn-60, have been studied in detail in the framework of the strictly restricted dynamics model (SRDM).

Reply to Comment on 'validity of Feynman's prescription of disregarding the Pauli principle in intermediate states'

In a recent paper, we raised a question on the validity of Feynman's prescription of disregarding the Pauli principle in intermediate states of perturbation theory. In the preceding Comment, Cavalcanti correctly pointed out that Feynman's prescription is consistent with the exact solution of the model that we used. This means that the Pauli principle does not necessarily apply to intermediate states. We discuss implications of this puzzling aspect.

Exchange terms in the quark-meson coupling model

In this talk we report on recent progress in implementing exchange terms in the quark-meson coupling model. Exchange effects are related to the Pauli exclusion principle. We discuss exchange effects at the nucleon level and at the quark level. We also address the incorporation of chiral symmetry and Delta degrees of freedom in the model.

Predictive formulation of the Nambu-Jona-Lasinio model

A novel strategy to handle divergences typical of perturbative calculations is implemented for the Nambu-Jona-Lasinio model and its phenomenological consequences investigated. The central idea of the method is to avoid the critical step involved in the regularization process, namely, the explicit evaluation of divergent integrals. This goal is achieved by assuming a regularization distribution in an implicit way and making use, in intermediary steps, only of very general properties of such regularization. The finite parts are separated from the divergent ones and integrated free from effects of the regularization. The divergent parts are organized in terms of standard objects, which are independent of the ( arbitrary) momenta running in internal lines of loop graphs. Through the analysis of symmetry relations, a set of properties for the divergent objects are identified, which we denominate consistency relations, reducing the number of divergent objects to only a few. The calculational strategy eliminates unphysical dependencies of the arbitrary choices for the routing of internal momenta, leading to ambiguity-free, and symmetry-preserving physical amplitudes. We show that the imposition of scale properties for the basic divergent objects leads to a critical condition for the constituent quark mass such that the remaining arbitrariness is removed. The model becomes predictive in the sense that its phenomenological consequences do not depend on possible choices made in intermediary steps. Numerical results are obtained for physical quantities at the one-loop level for the pion and sigma masses and pion-quark and sigma-quark coupling constants.

Linear delta expansion applied to the O'Raifeartaigh model

We reassess the method of the linear delta expansion for the calculation of effective potentials in superspace, by adopting the improved version of the super-Feynman rules in the framework of the O'Raifeartaigh model for spontaneous supersymmetry breaking. The effective potential is calculated using both the fastest apparent convergence and the principle of minimal sensitivity criteria and the consistency and efficacy of the method are checked in deriving the Coleman-Weinberg potential.