Self-adjoint extensions and spectral analysis in the generalized Kratzer problem

We present a mathematically rigorous quantum-mechanical treatment of a one-dimensional non-relativistic motion of a particle in the potential field V(x) = g(1)x(-1) + g(2)x(-2), x is an element of R(+) = [0, infinity). For g(2) > 0 and g(1) < 0, the potential is known as the Kratzer potential V(K)(x) and is usually used to describe molecular energy and structure, interactions between different molecules and interactions between non-bonded atoms. We construct all self-adjoint Schrodinger operators with the potential V(x) and represent rigorous solutions of the corresponding spectral problems. Solving the first part of the problem, we use a method of specifying self-adjoint extensions by (asymptotic) self-adjoint boundary conditions. Solving spectral problems, we follow Krein`s method of guiding functionals. This work is a continuation of our previous works devoted to the Coulomb, Calogero and Aharonov-Bohm potentials.

Combining Legendre's Polynomials and Genetic Algorithm in the Solution of Nonlinear Initial-Value Problems

This work develops a method for solving ordinary differential equations, that is, initial-value problems, with solutions approximated by using Legendre's polynomials. An iterative procedure for the adjustment of the polynomial coefficients is developed, based on the genetic algorithm. This procedure is applied to several examples providing comparisons between its results and the best polynomial fitting when numerical solutions by the traditional Runge-Kutta or Adams methods are available. The resulting algorithm provides reliable solutions even if the numerical solutions are not available, that is, when the mass matrix is singular or the equation produces unstable running processes.

Social interaction as a heuristic for combinatorial optimization problems

We investigate the performance of a variant of Axelrod's model for dissemination of culture-the Adaptive Culture Heuristic (ACH)-on solving an NP-Complete optimization problem, namely, the classification of binary input patterns of size F by a Boolean Binary Perceptron. In this heuristic, N agents, characterized by binary strings of length F which represent possible solutions to the optimization problem, are fixed at the sites of a square lattice and interact with their nearest neighbors only. The interactions are such that the agents' strings (or cultures) become more similar to the low-cost strings of their neighbors resulting in the dissemination of these strings across the lattice. Eventually the dynamics freezes into a homogeneous absorbing configuration in which all agents exhibit identical solutions to the optimization problem. We find through extensive simulations that the probability of finding the optimal solution is a function of the reduced variable F/N(1/4) so that the number of agents must increase with the fourth power of the problem size, N proportional to F(4), to guarantee a fixed probability of success. In this case, we find that the relaxation time to reach an absorbing configuration scales with F(6) which can be interpreted as the overall computational cost of the ACH to find an optimal set of weights for a Boolean binary perceptron, given a fixed probability of success.

Decision making in fuzzy environment and multicriteria power engineering problems

This paper presents results of research into the use of the Bellman-Zadeh approach to decision making in a fuzzy environment for solving multicriteria power engineering problems. The application of the approach conforms to the principle of guaranteed result and provides constructive lines in computationally effective obtaining harmonious solutions on the basis of solving associated maxmin problems. The presented results are universally applicable and are already being used to solve diverse classes of power engineering problems. It is illustrated by considering problems of power and energy shortage allocation, power system operation, optimization of network configuration in distribution systems, and energetically effective voltage control in distribution systems. (c) 2011 Elsevier Ltd. All rights reserved.

An approach for solving the lot-sizing problem of a market-driven foundry

Foundries can be found all over Brazil and they are very important to its economy. In 2008, a mixed integer-programming model for small market-driven foundries was published, attempting to minimize delivery delays. We undertook a study of that model. Here, we present a new approach based on the decomposition of the problem into two sub-problems: production planning of alloys and production planning of items. Both sub-problems are solved using a Lagrangian heuristic based on transferences. An important aspect of the proposed heuristic is its ability to take into account a secondary practice objective solution: the furnace waste. Computational tests show that the approach proposed here is able to generate good quality solutions that outperform prior results. Journal of the Operational Research Society (2010) 61, 108-114. doi:10.1057/jors.2008.151

Algorithms for two-dimensional cutting stock and strip packing problems using dynamic programming and column generation

We investigate several two-dimensional guillotine cutting stock problems and their variants in which orthogonal rotations are allowed. We first present two dynamic programming based algorithms for the Rectangular Knapsack (RK) problem and its variants in which the patterns must be staged. The first algorithm solves the recurrence formula proposed by Beasley; the second algorithm - for staged patterns - also uses a recurrence formula. We show that if the items are not so small compared to the dimensions of the bin, then these algorithms require polynomial time. Using these algorithms we solved all instances of the RK problem found at the OR-LIBRARY, including one for which no optimal solution was known. We also consider the Two-dimensional Cutting Stock problem. We present a column generation based algorithm for this problem that uses the first algorithm above mentioned to generate the columns. We propose two strategies to tackle the residual instances. We also investigate a variant of this problem where the bins have different sizes. At last, we study the Two-dimensional Strip Packing problem. We also present a column generation based algorithm for this problem that uses the second algorithm above mentioned where staged patterns are imposed. In this case we solve instances for two-, three- and four-staged patterns. We report on some computational experiments with the various algorithms we propose in this paper. The results indicate that these algorithms seem to be suitable for solving real-world instances. We give a detailed description (a pseudo-code) of all the algorithms presented here, so that the reader may easily implement these algorithms. (c) 2007 Elsevier B.V. All rights reserved.

ENO adaptive method for solving one-dimensional conservation laws

In this work an efficient third order non-linear finite difference scheme for solving adaptively hyperbolic systems of one-dimensional conservation laws is developed. The method is based oil applying to the solution of the differential equation an interpolating wavelet transform at each time step, generating a multilevel representation for the solution, which is thresholded and a sparse point representation is generated. The numerical fluxes obtained by a Lax-Friedrichs flux splitting are evaluated oil the sparse grid by an essentially non-oscillatory (ENO) approximation, which chooses the locally smoothest stencil among all the possibilities for each point of the sparse grid. The time evolution of the differential operator is done on this sparse representation by a total variation diminishing (TVD) Runge-Kutta method. Four classical examples of initial value problems for the Euler equations of gas dynamics are accurately solved and their sparse solutions are analyzed with respect to the threshold parameters, confirming the efficiency of the wavelet transform as an adaptive grid generation technique. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.

Changes in parents' and self-reports of behavioral problems in Brazilian adolescents after behavioral treatment with urine alarm for nocturnal enuresis

PURPOSE: Compare parents' reports of youth problems (PRYP) with adolescent problems self-reports (APSR) pre/post behavioral treatment of nocturnal enuresis (NE) based on the use of a urine alarm. MATERIALS AND METHODS: Adolescents (N = 19) with mono-symptomatic (primary or secondary) nocturnal enuresis group treatment for 40 weeks. Discharge criterion was established as 8 weeks with consecutive dry nights. PRYP and APSR were scored by the Child Behavior Checklist (CBCL) and Youth Self-Report (YSR). RESULTS: Pre-treatment data: 1) Higher number of clinical cases based on parent report than on self-report for Internalizing Problems (IP) (13/19 vs. 4/19), Externalizing Problems (EP) (7/19 vs. 5/19) and Total Problem (TP) (11/19 vs. 5/19); 2) Mean PRYP scores for IP (60.8) and TP (61) were within the deviant range (T score ≥ 60); while mean PRYP scores for EP (57.4) and mean APSR scores (IP = 52.4, EP = 49.5, TP = 52.4) were within the normal range. Difference between PRYP' and APSR' scores was significant. Post treatment data: 1) Discharge for majority of the participants (16/19); 2) Reduction in the number of clinical cases on parental evaluation: 9/19 adolescents remained within clinical range for IP, 2/19 for EP, and 7/19 for TP. 3) All post-treatment mean scores were within the normal range; the difference between pre and post evaluation scores was significant for PRYP. CONCLUSIONS: The behavioral treatment based on the use of urine alarm is effective for adolescents with mono-symptomatic (primary and secondary) nocturnal enuresis. The study favors the hypothesis that enuresis is a cause, not a consequence, of other behavioral problems.

Poder de agir e sofrimento: estudo de caso sobre Agentes Comunitários de Saúde

Os Agentes Comunitários de Saúde (ACS) possuem uma missão de grande importância na implementação da Estratégia de Saúde da Família: devem criar o vínculo entre a população e os serviços de atenção básica, combinando ações de promoção da saúde, assistência básica e prevenção. A equipe do Cerest de Piracicaba realizou, no período de 2004-2006, análise ergonômica do trabalho em uma unidade de saúde de família cujos objetivos foram compreender a relação entre queixas de sofrimento e as condições de trabalho das ACS e propor medidas para modificá-las. Os resultados da AET mostram que, a despeito do engajamento visando resolver os problemas de saúde das famílias, o limitado “poder de agir” das ACS, devido às limitações da unidade e da rede de serviços, expunham-nas a situações nas quais se encontravam incapazes de adotar ações efetivas e nas quais não podiam se prevenir do sofrimento

The case of thyroid hormones: how to learn physiology by solving a detective case

Lellis-Santos C, Giannocco G, Nunes MT. The case of thyroid hormones: how to learn physiology by solving a detective case. Adv Physiol Educ 35: 219-226, 2011; doi:10.1152/advan.00135.2010.Thyroid diseases are prevalent among endocrine disorders, and careful evaluation of patients' symptoms is a very important part in their diagnosis. Developing new pedagogical strategies, such as problem-based learning (PBL), is extremely important to stimulate and encourage medical and biomedical students to learn thyroid physiology and identify the signs and symptoms of thyroid dysfunction. The present study aimed to create a new pedagogical approach to build deep knowledge about hypo-/hyperthyroidism by proposing a hands-on activity based on a detective case, using alternative materials in place of laboratory animals. After receiving a description of a criminal story involving changes in thyroid hormone economy, students collected data from clues, such as body weight, mesenteric vascularization, visceral fat, heart and thyroid size, heart rate, and thyroid-stimulating hormone serum concentration to solve the case. Nevertheless, there was one missing clue for each panel of data. Four different materials were proposed to perform the same practical lesson. Animals, pictures, small stuffed toy rats, and illustrations were all effective to promote learning, and the detective case context was considered by students as inviting and stimulating. The activity can be easily performed independently of the institution's purchasing power. The practical lesson stimulated the scientific method of data collection and organization, discussion, and review of thyroid hormone actions to solve the case. Hence, this activity provides a new strategy and alternative materials to teach without animal euthanization.

Extremal problems on sum-free sets and coverings in tridimensional spaces

Given a prime power q, define c (q) as the minimum cardinality of a subset H of F 3 q which satisfies the following property: every vector in this space di ff ers in at most 1 coordinate from a multiple of a vector in H. In this work, we introduce two extremal problems in combinatorial number theory aiming to discuss a known connection between the corresponding coverings and sum-free sets. Also, we provide several bounds on these maps which yield new classes of coverings, improving the previous upper bound on c (q)

Continuous opinions and discrete actions in opinion dynamics problems

A model where agents show discrete behavior regarding their actions, but have continuous opinions that are updated by interacting with other agents is presented. This new updating rule is applied to both the voter and Sznajd models for interaction between neighbors, and its consequences are discussed. The appearance of extremists is naturally observed and it seems to be a characteristic of this model.

Clinical relationships and ethical problems in primary care, Sao Paulo, SP, Brazil

Objectives: Main Objective: to identify ethical problems in primary care according to nurses` and doctors` perceptions. Secondary Objective: to know ethical issues of patient-professional relationships in primary care. Design: Synthesis to integrate and reinterpret primary results of qualitative studies. Setting: Primary healthcare centers, Sao Paulo, SP, Brazil. Participants and/or context: Incidental sample of 34 nurses and 36 medical doctors working in primary healthcare centers selected by convenience. Methods: Individual, semi-structured interviews to identity situations considered as sources of ethical problems. The sample is socially representative of primary care health centers and professionals. Data collection assured discourse saturation. Hermeneutic-dialectical discourse analysis was used to study the results. Results: Patient-professional relationships and team work were the main sources of ethical problems. The most important problems were patient information, privacy, confidentiality, interpersonal relationship, linkage and patient autonomy. These issues reflect the recent changes in clinical relation ships and show the peculiarities of primary care with its continuous care which lasts a long time. Healthcare involves multiprofessional team work in the midst of the patient claims for autonomy. Good care of patients needs requires a relationship based on communication and cooperation, and includes feelings and values, with communication skills. Conclusions: Ethical problems in primary care are common situations. For quality and humane primary care the relationship should consist of dialogue, trust and cooperation. (C) 2009 Elsevier Espana, S.L. All rights reserved.

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

Chaos-Galerkin solution of stochastic Timoshenko bending problems

This paper presents an accurate and efficient solution for the random transverse and angular displacement fields of uncertain Timoshenko beams. Approximate, numerical solutions are obtained using the Galerkin method and chaos polynomials. The Chaos-Galerkin scheme is constructed by respecting the theoretical conditions for existence and uniqueness of the solution. Numerical results show fast convergence to the exact solution, at excellent accuracies. The developed Chaos-Galerkin scheme accurately approximates the complete cumulative distribution function of the displacement responses. The Chaos-Galerkin scheme developed herein is a theoretically sound and efficient method for the solution of stochastic problems in engineering. (C) 2011 Elsevier Ltd. All rights reserved.