Densidade mineral óssea, composição corporal e ingestão alimentar de adolescentes modelos de passarela

OBJETIVO: Avaliar a densidade mineral óssea (DMO) e relacioná-la com a ingestão alimentar e composição corporal de adolescentes modelos de passarela. MÉTODOS: Estudo transversal avaliando 33 modelos e 33 não modelos de 15 a 18 anos pareadas por idade e índice de massa corporal (IMC). A densidade mineral óssea da coluna (L1-L4) foi avaliada por meio da técnica da absorciometria de feixe duplo de energia (Lunar® DPX Alpha), e a composição corporal, pela técnica de pletismografia. A ingestão alimentar foi avaliada por meio do registro alimentar de 3 dias. RESULTADOS: A média de idade das adolescentes foi de 16,75±1,04 anos, sendo que 24 por cento apresentaram IMC abaixo dos valores ideais para a idade. Não houve diferença de DMO entre modelos (1,108±0,080 g/cm2) e não modelos (1,096±0,102 g/cm2) (p > 0,05), sendo identificada uma porcentagem de 6 por cento de baixa DMO para a idade. Observou-se que a média de ingestão de energia foi menor entre as modelos em comparação às adolescentesnão modelos (1.480,93±582,95 versus 1.973,00±557,63 kcal) (p > 0,05) e que a maioria das adolescentes de ambos os grupos apresentou consumo inadequado de micronutrientes, ressaltando-se a baixa ingestão de cálcio. Verificou-se correlação significativa da DMO apenas com a massa magra (kg) (modelos r = 0,362 e não modelos r = 0,618; p < 0,05). CONCLUSÃO: Apesar de não ter sido encontrada associação entre a DMO, o IMC e a ingestão de nutrientes importantes no processo de mineralização óssea, as inadequações na ingestão alimentar podem influenciar negativamente a aquisição de massa óssea, que se encontra potencializada neste estágio de vida

Modelos de gestão e o SUS

O recente documento do Ministério do Planejamento sobre Fundações Públicas (2005) e a crise da área hospitalar colocaram novamente na agenda do SUS a questão dos modelos de gestão pública. O objetivo deste artigo é situar no contexto das reformas de estado pensadas na década de 90 para o Brasil, as propostas de mudança dos modelos de gestão da administração pública, com foco no processo de implementação do SUS. Essa abordagem trata em primeiro lugar da personalidade jurídica das organizações de saúde na esfera estatal, conceituando o público a partir de seus objetivos; em segundo, discute o contexto as reformas de estado e as mudanças propostas para a administração pública. Os autores entendem que critérios e parâmetros para avaliação institucional devem contemplar quatro aspectos: subordinação à política de saúde; legalidade; eficiência gerencial e capacidade de controle. A partir do quadro de referencia geral elaborou-se uma análise comparativa em relação à proposta das fundações públicas de direito privado. Na análise comparativa das características desse tipo de entidade proposta para gestão hospitalar, observam-se semelhanças com a proposta de Organizações Sociais. Fundação Estatal e Contrato de Gestão podem ser vistos como modelos que possibilitam modernizar o Estado, além de re-introduzirem o tema da reforma hospitalar na agenda governamental brasileira

DEVELOPMENT OF A NOVEL SET OF MICROSATELLITE MARKERS FOR CASTOR BEAN, RICINUS COMMUNIS (EUPHORBIACEAE)

Premise of study: Microsatellite primers were developed for castor bean (Ricinus communis L.) to investigate genetic diversity and population structure, and to provide support to germplasm management. Methods and Results: Eleven microsatellite loci were isolated using an enrichment cloning protocol and used to characterize castor bean germplasm from the collection at the Instituto Agronomico de Campinas (IAC). In a survey of 76 castor bean accessions, the investigated loci displayed polymorphism ranging from two to five alleles. Conclusions: The information derived from microsatellite markers led to significant gains in conserved allelic richness and provides support to the implementation of several molecular breeding strategies for castor bean.

Antecedentes do relacionamento e da performance em empresas da cadeia de suprimentos: estruturação e aplicação de modelos de equações estruturais

The relationship between companies is an important issue in the management of supply chains. Several aspects relating to the flow and exchange of information along the chain are considered as having a decisive influence on the success of this relationship. The main objective of this work was to structured and test models that link aspects of this nature with performance and the purchaser-supplier relationship in the supply chain. Aspects relevant to communication and the use do IT in relationships between companies were investigated. The importance of performance in this relationship was also investigated. The research were based on empirical data obtained by means of structural equation modeling. The results show that some aspects contribute in a significant way to the success of this relationship while others that, a priori, are considered important make no contribution.

Avaliação de modelos geoidais gravimétricos determinados com funções covariâncias planas e esféricas (Estudo de Caso: Estado de São Paulo e adjacências)

The least squares collocation is a mathematical technique which is used in Geodesy for representation of the Earth's anomalous gravity field from heterogeneous data in type and precision. The use of this technique in the representation of the gravity field requires the statistical characteristics of data through covariance function. The covariances reflect the behavior of the gravity field, in magnitude and roughness. From the statistical point of view, the covariance function represents the statistical dependence among quantities of the gravity field at distinct points or, in other words, shows the tendency to have the same magnitude and the same sign. The determination of the covariance functions is necessary either to describe the behavior of the gravity field or to evaluate its functionals. This paper aims at presenting the results of a study on the plane and spherical covariance functions in determining gravimetric geoid models.

Espacialização da temperatura do ar anual no estado de Alagoas com diferentes modelos digitais de elevação e resoluções espaciais

The aim of this study was to establish a digital elevation model and its horizontal resolution to interpolate the annual air temperature for the Alagoas State by means of multiple linear regression models. A multiple linear regression model was adjusted to series (11 to 34 years) of annual air temperatures obtained from 28 weather stations in the states of Alagoas, Bahia, Pernambuco and Sergipe, in the Northeast of Brazil, in function of latitude, longitude and altitude. The elevation models SRTM and GTOPO30 were used in the analysis, with original resolutions of 90 and 900 m, respectively. The SRTM was resampled for horizontal resolutions of 125, 250, 500, 750 and 900 m. For spatializing the annual mean air temperature for the state of Alagoas, a multiple linear regression model was used for each elevation and spatial resolution on a grid of the latitude and longitude. In Alagoas, estimates based on SRTM data resulted in a standard error of estimate (0.57 degrees C) and dispersion (r(2) = 0.62) lower than those obtained from GTOPO30 (0.93 degrees C and 0.20). In terms of SRTM resolutions, no significant differences were observed between the standard error (0.55 degrees C; 750 m - 0.58 degrees C; 250m) and dispersion (0.60; 500 m - 0.65; 750 m) estimates. The spatialization of annual air temperature in Alagoas, via multiple regression models applied to SRTM data showed higher concordance than that obtained with the GTOPO30, independent of the spatial resolution.

An oligonucleotide primer set for PCR amplification of the complete honey bee mitochondrial genome

Mitochondrial DNA markers have been widely used to address population and evolutionary questions in the honey bee Apis mellifera. Most of the polymorphic markers are restricted to few mitochondrial regions. Here we describe a set of 24 oligonucleotides that allow PCR amplification of the entire mitochondrial genome of the honey bee A. mellifera in 12 amplicons. These fragments have important applications for the study of mitochondrial genes in different subspecies of A. mellifera and as heterospecific probes to characterize mitochondrial genomes in other bee species.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Power Transformer Differential Protection Based on Clarke`s Transform and Fuzzy Systems

The power transformer is a piece of electrical equipment that needs continuous monitoring and fast protection since it is very expensive and an essential element for a power system to perform effectively. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can affect the protection behavior and the power system stability. This paper proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic and Clarke`s transform. An electrical power system was modeled using Alternative Transients Program (ATP) software to obtain the operational conditions and fault situations needed to test the algorithm developed. The results were compared to a commercial relay for validation, showing the advantages of the new method.

Embedded DSP-Based Compact Fuzzy System and Its Application for Induction-Motor V/f Speed Control

This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.

Combined heuristic with fuzzy system to transmission system expansion planning

A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (C) 2010 Elsevier B.V. All rights reserved.

Real-Time Voltage Regulation in Power Distribution System Using Fuzzy Control

Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.

Fuzzy Control System for Voltage Regulation In Power Transformers

A fuzzy control strategy for voltage regulation in electric power distribution systems is introduced in this article. This real-time controller would act on power transformers equipped with under-load tap changers. The fuzzy system was employed to turn the voltage-control relays into adaptive devices. The scope of the present study has been limited to the power distribution substation, and both the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage control strategies that satisfy both the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. A prototype based on the fuzzy control strategy proposed in this paper has also been implemented for validation purposes and its experimental results were highly satisfactory.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.