Are severe occlusal problems more frequent in permanent than deciduous dentition?

OBJECTIVE: To determine the prevalence and severity of occlusal problems in populations at the ages of deciduous and permanent dentition and to carry out a meta-analysis to estimate the weighted odds ratio for occlusal problems comparing both groups. METHODS: Data of a probabilistic sample (n=985) of schoolchildren aged 5 and 12 from an epidemiological study in the municipality of São Paulo, Brazil, were analyzed using univariate logistic regression (MLR). Results of cross-sectional study data published in the last 70 years were examined in the meta-analysis. RESULTS: The prevalence of occlusal problems increased from 49.0% (95% CI =47.4%-50.6%) in the deciduous dentition to 71.3% (95% CI =70.3%-72.3%) in the permanent dentition (p<0.001). Dentition was the only variable significantly associated to the severity of malocclusion (OR=1.87; 95% CI =1.43-2.45; p<0.001). The variables sex, type of school and ethnic group were not significant. The meta-analysis showed that a weighted OR of 1.95 (1.91; 1.98) when compared the second dentition period with deciduous and mixed dentition. CONCLUSIONS: In planning oral health services, some activities are indicated to reduce the proportion of moderate/severe malocclusion to levels that are socially more acceptable and economically sustainable.

Simulated annealing metaheuristic to solve the optimal power flow

The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other wellknown methodologies presented in the literature, showing the effectiveness of the proposed method.

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

Nodal price simulation in competitive electricity markets

Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2]. This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved. An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP. The paper presents a case study based on the the 118 IEEE bus test network.

Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

This paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, balancing load among feeders and subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. The Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages; the first one is the Master problem and is formulated as a mixed integer non-linear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a non-linear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS. The effectiveness of the proposal is demonstrated through two examples extracted from the literature.

Determination of chitin content in fungal cell wall: an alternative flow cytometric method

The conventional methods used to evaluate chitin content in fungi, such as biochemical assessment of glucosamine release after acid hydrolysis or epifluorescence microscopy, are low throughput, laborious, time-consuming, and cannot evaluate a large number of cells. We developed a flow cytometric assay, efficient, and fast, based on Calcofluor White staining to measure chitin content in yeast cells. A staining index was defined, its value was directly related to chitin amount and taking into consideration the different levels of autofluorecence. Twenty-two Candida spp. and four Cryptococcus neoformans clinical isolates with distinct susceptibility profiles to caspofungin were evaluated. Candida albicans clinical isolate SC5314, and isogenic strains with deletions in chitin synthase 3 (chs3Δ/chs3Δ) and genes encoding predicted Glycosyl Phosphatidyl Inositol (GPI)-anchored proteins (pga31Δ/Δ and pga62Δ/Δ), were used as controls. As expected, the wild-type strain displayed a significant higher chitin content (P < 0.001) than chs3Δ/chs3Δ and pga31Δ/Δ especially in the presence of caspofungin. Ca. parapsilosis, Ca. tropicalis, and Ca. albicans showed higher cell wall chitin content. Although no relationship between chitin content and antifungal drug susceptibility phenotype was found, an association was established between the paradoxical growth effect in the presence of high caspofungin concentrations and the chitin content. This novel flow cytometry protocol revealed to be a simple and reliable assay to estimate cell wall chitin content of fungi.

A novel flow cytometric protocol for assessment of yeast cell adhesion

Microbial adhesion is a field of recognized relevance and, as such, an impressive array of tools has been developed to understand its molecular mechanisms and ultimately for its quantification. Some of the major limitations found within these methodologies concern the incubation time, the small number of cells analyzed, and the operator's subjectivity. To overcome these aspects, we have developed a quantitative method to measure yeast cells' adhesion through flow cytometry. In this methodology, a suspension of yeast cells is mixed with green fluorescent polystyrene microspheres (uncoated or coated with host proteins). Within 2 h, an adhesion profile is obtained based on two parameters: percentage and cells-microsphere population's distribution pattern. This flow cytometry protocol represents a useful tool to quantify yeast adhesion to different substrata in a large scale, providing manifold data in a speedy and informative manner.

Ant colony system based approach to single machine scheduling problems: weighted tardiness scheduling problem

The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.

Estudo das propriedades dos adjuvantes na compatibilidade/robustez cimento/adjuvante

A qualidade do betão pode ser controlada pelo comportamento da fluidez da pasta de cimento, o qual está relacionado com a dispersão das partículas de cimento. Um dos maiores avanços na tecnologia do betão tem sido o desenvolvimento de aditivos. Um destes tipos de aditivos, os Superplastificantes (SP), fornecem a possibilidade de se obter uma melhor dispersão das partículas de cimento, produzindo pastas com elevada fluidez. Com o desenvolvimento de betões de alta resistência e elevado desempenho, os superplastificantes tornaram-se indispensáveis. Os superplastificantes são adsorvidos nas partículas de cimento e esta adsorção depende da composição do clínquer do cimento e do tipo de SP utilizado. Com a difusão do emprego dos aditivos redutores de água, têm surgido vários problemas de compatibilidade cimento/adjuvante. Esta investigação dedicada aos superplastificantes, fortes redutores de água, visou estudar quais as propriedades que poderiam influenciar a sua compatibilidade/robustez com o cimento. Também se procurou ganhar experiência com as técnicas analíticas de caracterização de adjuvantes. Assim, utilizou-se um tipo de cimento e dois tipos de superplastificantes (poli(étercarboxilatos) e poli(naftalenossulfonatos)) disponíveis no mercado português. Mantendo a mesma razão água/cimento (A/C), pretendeu-se determinar a natureza química, grau de funcionalização, teor e tipo de contra-ião, teor de sulfatos/sulfonatos do adjuvante e o comportamento dos superplastificantes nas pastas cimentícias, de forma a poder determinar indicadores de compatibilidade entre cimentos e superplastificantes. Constatou-se que a natureza química, o grau de funcionalização e a quantidade consumida dos superplastificantes têm influência nas pastas. Os indicadores de compatibilidade por parte dos superplastificantes parecem estar relacionados com o comprimento da cadeia lateral de éter e com o rácio CO2R/CO2 -. A alteração do momento da adição do adjuvante tem influência na compatibilidade cimento/adjuvante, sendo benéfico para os poli(étercarboxilatos) e prejudicial para o poli(naftalenossulfonato).

Derivative-free optimization and filter methods to solve nonlinear constrained problems

In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.

Gestão e monitorização de uma rede departamental: um caso de estudo

Mestrado em Engenharia Electrotécnica e de Computadores

Funções penalidade para o tratamento das variáveis discretas do problema de fluxo de potência ótimo reativo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Sistema multi-agente para gestão de tráfego em centros urbanos

Mestrado em Engenharia Informática

The problems of the european union film industry: an evolution from "subsidy trap" to the advent of "virtual print fee" model

Dissertação de Mestrado, Gestão de Empresa (MBA), 16 de Julho de 2013, Universidade dos Açores.

Avaliação técnica e econômica de um biodigestor de fluxo tubular: estudo de caso do modelo implantado na etec "orlando quagliato" em Santa Cruz do Rio Pardo, SP

Pós-graduação em Agronomia (Energia na Agricultura) - FCA