61 resultados para Sum rules
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In this reply to the comment on 'Quantization rules for bound states in quantum wells' we point out some interesting differences between the supersymmetric Wentzel-Kramers-Brillouin (WKB) quantization rule and a matrix generalization of usual WKB (mWKB) and Bohr-Sommerfeld (mBS) quantization rules suggested by us. There are certain advantages in each of the supersymmetric WKB (SWKB), mWKB and mBS quantization rules. Depending on the quantum well, one of these could be more useful than the other and it is premature to claim unconditional superiority of SWKB over mWKB and mBS quantization rules.
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We consider a [ud](2)(s) over bar current, in the finite-density QCD sum rule approach, to investigate the scalar and vector self-energies of the recently observed pentaquark state Theta(+)(1540), propagating in nuclear matter. We find that, opposite to what was obtained for the nucleon, the vector self-energy is negative, and the scalar self-energy is positive. There is a substantial cancellation between them resulting in an attractive net self-energy of the same order as in the nucleon case. (C) 2004 Elsevier B.V. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The generalized temperature integral I(m, x) appears in non-isothermal kinetic analysis when the frequency factor depends on the temperature. A procedure based on Gaussian quadrature to obtain analytical approximations for the integral I(m, x) was proposed. The results showed good agreement between the obtained approximation values and those obtained by numerical integration. Unless other approximations found in literature, the methodology presented in this paper can be easily generalized in order to obtain approximations with the maximum of accurate.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The solvation properties of model resin and peptide-resins measured in ca. 30 solvent systems correlated better with the sum of solvent electron acceptor (AN) and electron donor (DN) numbers, in 1:1 proportion, than with other solvent polarity parameters. The high sensitivity of the (AN+DN) term to detect differentiated solvation behaviors of peptide-resins, taken as model of heterogeneous and complex solutes, seems to be in agreement with the previously proposed two-parameter model, where the sum of the Lewis acidity and Lewis basicity characters of solvent are proposed for scaling solvent effect. Besides these physicochemical aspects regarding solute-solvent interactions, important implications of this study for the solid phase peptide synthesis were also observed. Each class of peptide-resin displayed a specific salvation profile that was dependent on the amount and the nature of the resin-bound peptide sequence. Plots of resin swelling versus solvent (AN+DN) values allowed the visualization of a maximum salvation region characteristic for each class of resin. This strategy facilitates the selection of solvent systems for optimal solvation conditions of peptide chains in every step of the entire synthesis cycle. Moreover, only the AN and DN concepts allow the understanding of rules for solvation/shrinking of peptide-resins when in homogeneous or in heterogeneous mixed solvents.
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A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.
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We compute the leading radiative correction to the Casimir force between two parallel plates in the lambdaPhi(4) theory. Dirichlet and periodic boundary conditions are considered. A heuristic approach, in which the Casimir energy is computed as the sum of one-loop corrected zero-point energies, is shown to yield incorrect results, but we show how to amend it. The technique is then used in the case of periodic boundary conditions to construct a perturbative expansion which is free of infrared singularities in the massless limit. In this case we also compute the next-to-leading order radiative correction, which turns out to be proportional to lambda(3/2).
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We prove a relation between two different types of symmetric quadrature rules, where one of the types is the classical symmetric interpolatory quadrature rules. Some applications of a new quadrature rule which was obtained through this relation are also considered.
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The long-standing discrepancy between the Gerasimov-Drell-Hearn sum rule and the analysis of pion photoproduction multipoles is greatly diminished by use of s-wave multipoles that are in accord with the predictions of chiral perturbation theory and describe the experimental data in the threshold region. The remaining difference may be due to contributions of channels with more pions and/or heavier mesons whose contributions to the sum rule remain to be investigated by a direct measurement of the photoabsorption cross sections.
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One common problem in all basic techniques of knowledge representation is the handling of the trade-off between precision of inferences and resource constraints, such as time and memory. Michalski and Winston (1986) suggested the Censored Production Rule (CPR) as an underlying representation and computational mechanism to enable logic based systems to exhibit variable precision in which certainty varies while specificity stays constant. As an extension of CPR, the Hierarchical Censored Production Rules (HCPRs) system of knowledge representation, proposed by Bharadwaj & Jain (1992), exhibits both variable certainty as well as variable specificity and offers mechanisms for handling the trade-off between the two. An HCPR has the form: Decision If(preconditions) Unless(censor) Generality(general_information) Specificity(specific_information). As an attempt towards evolving a generalized knowledge representation, an Extended Hierarchical Censored Production Rules (EHCPRs) system is suggested in this paper. With the inclusion of new operators, an Extended Hierarchical Censored Production Rule (EHCPR) takes the general form: Concept If (Preconditions) Unless (Exceptions) Generality (General-Concept) Specificity (Specific Concepts) Has_part (default: structural-parts) Has_property (default:characteristic-properties) Has_instance (instances). How semantic networks and frames are represented in terms of an EHCPRs is shown. Multiple inheritance, inheritance with and without cancellation, recognition with partial match, and a few default logic problems are shown to be tackled efficiently in the proposed system.
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We consider interpolatory quadrature rules with nodes and weights satisfying symmetric properties in terms of the division operator. Information concerning these quadrature rules is obtained using a transformation that exists between these rules and classical symmetric interpolatory quadrature rules. In particular, we study those interpolatory quadrature rules with two fixed nodes. We obtain specific examples of such quadrature rules.
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This paper proposes a fuzzy classification system for the risk of infestation by weeds in agricultural zones considering the variability of weeds. The inputs of the system are features of the infestation extracted from estimated maps by kriging for the weed seed production and weed coverage, and from the competitiveness, inferred from narrow and broad-leaved weeds. Furthermore, a Bayesian network classifier is used to extract rules from data which are compared to the fuzzy rule set obtained on the base of specialist knowledge. Results for the risk inference in a maize crop field are presented and evaluated by the estimated yield loss. © 2009 IEEE.