Dynamics of hypernuclear nonmesonic weak decay

Simple and coincidence spectra of the NM weak decay of light hypernuclei have been evaluated in a systematic way for the first time. We have only considered 1N induced processes, neglecting entirely the events induced by 2N emission, as well as the effects of the FSIt's. As the theoretical frameworkwe have used the IPSM with three different parametrizations for the transition potential. The comparison with data strongly suggests that the soft π + K exchange model could be a good starting point to describe the dynamics in the NM weak decays of s- and p-shell hypernuclei. © 2012 American Institute of Physics.

Evidence of weak ferromagnetism in doped plasticized polyaniline (PANI-DDoESSA)0.5 from electron spin resonance measurements

X-band electron spin resonance (ESR) measurements have been performed on a conducting free-standing film of polyaniline plasticized and protonated with di-n-dodecyl ester of sulfosuccinic acid (DDoESSA). The magnetic field was applied parallel and perpendicular to the plane of the film. At around 75 K a transition is observed from Pauli susceptibility to a localized state in which the spin 1/2 polarons behave as spin 1/2 dimers. A rough estimation of the intradimer and interdimer exchange constants is obtained. Below 5 K, ESR data reveal a weak ferromagnetism with the Dzyaloshinskii-Moriya vector mainly oriented in the plane of the film. The existence of a relatively well-defined n-fold axis along the chain direction in the crystalline regions confers a symmetry compatible with such analysis. © 2013 IOP Publishing Ltd.

Weak local Nash equilibrium

In this paper, we consider a concept of local Nash equilibrium for non-cooperative games - the so-called weak local Nash equilibrium. We prove its existence for a significantly more general class of sets of strategies than compact convex sets. The theorems on existence of the weak local equilibrium presented here are applications of Brouwer and Lefschetz fixed point theorems. © 2013 Juliusz Schauder Centre for Nonlinear Studies Nicolaus Copernicus University.

Effects of methylmercury on electric organ discharges in the weak electric fish Gymnotus sylvius

Methylmercury (MeHg) is present in the environment because of natural and anthropogenic causes. MeHg can reach the central nervous system (CNS) and cause neurological damage in humans and animals. Electric organ discharges (EODs) in the weak electric fish Gymnotus sylvius are produced by the electric organ and modulated by the CNS. These discharges are used for electrolocation and communication. The purpose of the present study was to investigate the effects of dietary MeHg exposure on EOD rate in G. sylvius. An oscilloscope was used to record the EOD rate. Two treatments were investigated: chronic MeHg administration (4 μg/kg MeHg every 2 days, with a total of nine dietary exposures to MeHg) and acute MeHg administration (a single dose of 20 μg/kg MeHg). The control data for both treatments were collected every 2 days for 18 days, with a total of nine sessions (day 1 until day 18). Data of fish exposed to MeHg were collected every 2 days, totaling nine sessions (day 19 until day 36). Chronic treatment significantly increased the EOD rate in G. sylvius (p<.05), especially with the final treatment (day 32 until day 36). Acute treatment resulted in an initial increase in the EOD rate, which was maintained midway through the experiment (day 26 until day 30 p<.05). The present study provides the first insights into the effects of MeHg on EODs in weak electric fish. The EOD rate is a novel response of the fish to MeHg administration.

Approximation of hyperbolic tangent activation function using hybrid methods

Artificial Neural Networks are widely used in various applications in engineering, as such solutions of nonlinear problems. The implementation of this technique in reconfigurable devices is a great challenge to researchers by several factors, such as floating point precision, nonlinear activation function, performance and area used in FPGA. The contribution of this work is the approximation of a nonlinear function used in ANN, the popular hyperbolic tangent activation function. The system architecture is composed of several scenarios that provide a tradeoff of performance, precision and area used in FPGA. The results are compared in different scenarios and with current literature on error analysis, area and system performance. © 2013 IEEE.

Semigrupos de operadores lineares limitados: soluções Mild e Weak

Pós-graduação em Matemática - IBILCE

Equivalente teleparalelo de algumas soluções da relatividade geral

Pós-graduação em Física - IFT

Psychometric Properties of the Oral Health Impact Profile and New Methodological Approach

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

Nonmesonic Weak Decay Spectra of Light Hypernuclei

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

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relativistic Coulomb scattering of spinless bosons

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Differential orthogonality: Laguerre and Hermite cases with applications

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

Pareto Frontier for the time-energy cost vector to an Earth-Moon transfer orbit using the patched-conic approximation

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

A radial basis function network (RBFN) for function approximation

A radial basis function network (RBFN) circuit for function approximation is presented. Simulation and experimental results show that the network has good approximation capabilities. The RBFN was a squared hyperbolic secant with three adjustable parameters amplitude, width and center. To test the network a sinusoidal and sine function,vas approximated.

Comparative study between powers of sigmoid functions, MLP-backpropagation and polynomials in function approximation problems

Function approximation is a very important task in environments where the computation has to be based on extracting information from data samples in real world processes. So, the development of new mathematical model is a very important activity to guarantee the evolution of the function approximation area. In this sense, we will present the Polynomials Powers of Sigmoid (PPS) as a linear neural network. In this paper, we will introduce one series of practical results for the Polynomials Powers of Sigmoid, where we will show some advantages of the use of the powers of sigmiod functions in relationship the traditional MLP-Backpropagation and Polynomials in functions approximation problems.