Responsiveness of the interrenal tissue of Jundia (Rhamdia quelen) to an in vivo ACTH test following acute exposure to sublethal concentrations of agrichemicals

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

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

A Strategy to Solve the Multistage Transmission Expansion Planning Problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multi Objective Evolutionary Algorithm Applied to the Optimal Power Flow Problem

This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.

Comparative evaluation of an indirect ELISA test for diagnosis of swine cysticercosis employing antigen from Taenia solium and Taenia crassiceps metacestodes

Taenia solium cysticercosis is still a serious public health problem in several countries where poverty and lack of hygiene favor transmission. Because pigs are the primary intermediate hosts, prevalence of porcine cysticercosis is a reliable indicator of active transmission zones. Serological diagnostic methods are important tools for epidemiological studies since they can be applied to living animals on a large scale. Four antigen preparations (cyst fluid and crude) from T. solium and T. crassiceps metacestodes were compared for swine cysticercosis diagnosis by indirect ELISA (IE). Twenty-eight serum samples from swine naturally and experimentally infected by cysticerci of T. solium and 56 serum samples from swine reared in commercial herds were tested. Best results of overall sensitivity were obtained by the use of cyst fluid and crude antigen of T. crassiceps metacestode (100 and 96.4%, respectively). Using homologous antigen preparations we have observed higher specificity percentage (98.2% for cyst fluid and 96.4% for crude metacestode T. solium antigen). We concluded that sensitivity is of far more importance than specificity for identification of endemic areas in order to prevent transmission to man. We conclude, therefore, that IE performed with cyst fluid antigen of T. crassiceps metacestode is a better tool for that purpose. (C) 2000 Elsevier B.V. B.V. All rights reserved.

Comparison between RT-PCR and the mouse inoculation test for detection of rabies virus in samples kept for long periods under different conditions

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

Designing a modified Hopfield network to solve an Economic Dispatch problem with nonlinear cost function

Economic Dispatch (ED) problems have recently been solved by artificial neural networks approaches. In most of these dispatch models, the cost function must be linear or quadratic. Therefore, functions that have several minimum points represent a problem to the simulation since these approaches have not accepted nonlinear cost function. Another drawback pointed out in the literature is that some of these neural approaches fail to converge efficiently towards feasible equilibrium points. This paper discusses the application of a modified Hopfield architecture for solving ED problems defined by nonlinear cost function. The internal parameters of the neural network adopted here are computed using the valid-subspace technique, which guarantees convergence to equilibrium points that represent a solution for the ED problem. Simulation results and a comparative analysis involving a 3-bus test system are presented to illustrate efficiency of the proposed approach.

TRICUT: a program to clip triangle meshes using the rapid and triangle libraries and the visualization toolkit

An efficient technique to cut polygonal meshes as a step in the geometric modeling of topographic and geological data has been developed. In boundary represented models of outcropping strata and faulted horizons polygonal meshes often intersect each other. TRICUT determines the line of intersection and re-triangulates the area of contact. Along this line the mesh is split in two or more parts which can be selected for removal. The user interaction takes place in the 3D-model space. The intersection, selection and removal are under graphic control. The visualization of outcropping geological structures in digital terrain models is improved by determining intersections against a slightly shifted terrain model. Thus, the outcrop line becomes a surface which overlaps the terrain in its initial position. The area of this overlapping surface changes with respect to the strike and dip of the structure, the morphology and the offset. Some applications of TRICUT on different real datasets are shown. TRICUT is implemented in C+ + using the Visualization Toolkit in conjunction with the RAPID and TRIANGLE libraries. The program runs under LINUX and UNIX using the MESA OpenGL library. This work gives an example of solving a complex 3D geometric problem by integrating available robust public domain software. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

Logarithmic barrier-augmented Lagrangian function to the optimal power flow problem

This paper presents a new approach to solve the Optimal Power Flow problem. This approach considers the application of logarithmic barrier method to voltage magnitude and tap-changing transformer variables and the other constraints are treated by augmented Lagrangian method. Numerical test results are presented, showing the effective performance of this algorithm. (C) 2005 Elsevier Ltd. All rights reserved.

A new approach to the solution of the optimal power flow problem based on the modified Newton's method associated to an augmented Lagrangian function

This paper presents a new algorithm for optimal power flow problem. The algorithm is based on Newton's method which it works with an Augmented Lagrangian function associated with the original problem. The function aggregates all the equality and inequality constraints and is solved using the modified-Newton method. The test results have shown the effectiveness of the approach using the IEEE 30 and 638 bus systems.

Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem

This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.

TWO DECOMPOSITION APPROACHES APPLIED TO THE MULTI-AREA OPTIMAL REACTIVE POWER FLOW PROBLEM

This paper applies two methods of mathematical decomposition to carry out an optimal reactive power flow (ORPF) in a coordinated decentralized way in the context of an interconnected multi-area power system. The first method is based on an augmented Lagrangian approach using the auxiliary problem principle (APP). The second method uses a decomposition technique based on the Karush-Kuhn-Tucker (KKT) first-order optimality conditions. The viability of each method to be used in the decomposition of multi-area ORPF is studied and the corresponding mathematical models are presented. The IEEE RTS-96, the IEEE 118-bus test systems and a 9-bus didactic system are used in order to show the operation and effectiveness of the decomposition methods.

A new solution to the optimal power flow problem

A new approach to solving the Optimal Power Flow problem is described, making use of some recent findings, especially in the area of primal-dual methods for complex programming. In this approach, equality constraints are handled by Newton's method inequality constraints for voltage and transformer taps by the logarithmic barrier method and the other inequality constraints by the augmented Lagrangian method. Numerical test results are presented, showing the effective performance of this algorithm. © 2001 IEEE.

Diabetes and pregnancy: An update of the problem

Pregnancies complicated by diabetes account for about 7% of all pregnancies attended by the Brazilian Unified Healthcare System (SUS) and are one of the main causes of maternal/perinatal morbidity and mortality in Brazil. Considering the importance of this topic, this article presents an update of diabetes classification, diagnostic criteria, maternal/perinatal outcomes, and both clinical and obstetric prenatal care. Even though there is no consensus about screening and diagnostic standards, the investigation of hyperglycemia in all risk pregnancies is recommended. The importance of adequate metabolic control is emphasized in order to improve maternal and neonatal outcomes. Finally, the development of educational programs is encouraged, viewing not only good gestational outcome but also long-term changes in the lifestyle of these women. © by São Paulo State University.

Domain reduction using GRASP construction phase for transmission expansion planning problem

This paper proposes a new strategy to reduce the combinatorial search space of a mixed integer linear programming (MILP) problem. The construction phase of greedy randomized adaptive search procedure (GRASP-CP) is employed to reduce the domain of the integer variables of the transportation model of the transmission expansion planning (TM-TEP) problem. This problem is a MILP and very difficult to solve specially for large scale systems. The branch and bound (BB) algorithm is used to solve the problem in both full and the reduced search space. The proposed method might be useful to reduce the search space of those kinds of MILP problems that a fast heuristic algorithm is available for finding local optimal solutions. The obtained results using some real test systems show the efficiency of the proposed method. © 2012 Springer-Verlag.