859 resultados para Rapid programming


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The paper presents a constructive heuristic algorithm (CHA) for solving directly the long-term transmission-network-expansion-planning (LTTNEP) problem using the DC model. The LTTNEP is a very complex mixed-integer nonlinear-programming problem and presents a combinatorial growth in the search space. The CHA is used to find a solution for the LTTNEP problem of good quality. A sensitivity index is used in each step of the CHA to add circuits to the system. This sensitivity index is obtained by solving the relaxed problem of LTTNEP, i.e. considering the number of circuits to be added as a continuous variable. The relaxed problem is a large and complex nonlinear-programming problem and was solved through the interior-point method (IPM). Tests were performed using Garver's system, the modified IEEE 24-Bus system and the Southern Brazilian reduced system. The results presented show the good performance of IPM inside the CHA.

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The objective of the present study was to develop and apply the direct immunohistochemistry (D-IHC) assay to search for turkey coronavirus (TCoV) antigens in formalin-fixed embedded-paraffin tissues by the use of biotin-labeled polyclonal antibody. Twenty-eight-day-old embryonated turkey eggs (n = 50) were inoculated with TCoV-purified virus, and 3 d after inoculation, sections from ileum, ileum-cecal junction, and ceca were harvested, fixed in neutral formalin, and embedded in paraffin blocks and used as positive control. In addition, a total of 100 field samples from ileum, ileum-cecal junction, and ceca, collected from 30 to 45-d-old turkeys poults experiencing an outbreak of acute enteritis, were used to search for TCoV by the same D-IHC. All results were compared with those obtained by conventional RT-PCR and indirect fluorescent antibody assay (IFA) for all tested samples. Turkey coronavirus was detected in experimentally infected embryo tissues and also in field samples in 100% of ileum-cecal junction and ceca by the 3 detection procedures. With IFA as a reference assay, sensitivity and specificity of D-IHC were 98 and 58%, whereas sensitivity and specificity of reverse transcription-PCR were 96 and 66%, calculated from the total of tested samples from experimental infection. Each of the examined procedures was highly specific (D-IHC, 93%; RT-PCR, 90%), sensitive (D-IHC, 85%; RT-PCR, 86%), and agreement of both D-IHC and RT-PCR was 99 and 100%, respectively, compared with IFA results obtained from all the field samples. These findings demonstrated the utility of D-IHC for direct detection of TCoV from field samples and considering the sensitivity and specificity found here, can be used as an alternative technique.

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

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One of the characteristics of diabetes mellitus is the exaggerated inflammatory response. The present report shows the reaction from the use of a rapid maxillary expander in a diabetic patient. A 9-year-old child presented an uncommon reaction to the treatment with a rapid maxillary expander, and on follow-up examination, it was discovered that the patient had diabetes mellitus. After controlling the disease, the proposed treatment was used without further incidents. The case calls attention to the presence of uncommon responses to treatment and the need for the orthodontist to suspect a patient's systemic compromise. (Angle Orthod. 2011;81:546-550.)

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

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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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A rapid and simple method was developed for quantitation of polar compounds in fats and oils using monostearin as internal standard. Starting from 50 mg of oil sample, polar compounds were obtained by solid-phase extraction (silica cartridges) and subsequently separated by high-performance size-exclusion chromatography into triglyceride polymers, triglyceride dimers, oxidized triglyceride monomers, diglycerides, internal standard and fatty acids. Quantitation of total polar compounds was achieved through the internal standard method and then amounts of each group of compounds could be calculated. A pool of polar compounds was used to check linearity, precision and accuracy of the method, as well as the solid-phase extraction recovery. The procedure was applied to samples with different content of polar compounds and good quantitative results were obtained, especially for samples of low alteration level.

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The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.

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In this paper, we consider a vector optimization problem where all functions involved are defined on Banach spaces. We obtain necessary and sufficient criteria for optimality in the form of Karush-Kuhn-Tucker conditions. We also introduce a nonsmooth dual problem and provide duality theorems.

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

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A combined methodology consisting of successive linear programming (SLP) and a simple genetic algorithm (SGA) solves the reactive planning problem. The problem is divided into operating and planning subproblems; the operating subproblem, which is a nonlinear, ill-conditioned and nonconvex problem, consists of determining the voltage control and the adjustment of reactive sources. The planning subproblem consists of obtaining the optimal reactive source expansion considering operational, economical and physical characteristics of the system. SLP solves the optimal reactive dispatch problem related to real variables, while SGA is used to determine the necessary adjustments of both the binary and discrete variables existing in the modelling problem. Once the set of candidate busbars has been defined, the program implemented gives the location and size of the reactive sources needed, if any, to maintain the operating and security constraints.