923 resultados para Linear mixed effect models


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BACKGROUND: Annually, 2.8 million neonatal deaths occur worldwide, despite the fact that three-quarters of them could be prevented if available evidence-based interventions were used. Facilitation of community groups has been recognized as a promising method to translate knowledge into practice. In northern Vietnam, the Neonatal Health - Knowledge Into Practice trial evaluated facilitation of community groups (2008-2011) and succeeded in reducing the neonatal mortality rate (adjusted odds ratio, 0.51; 95 % confidence interval 0.30-0.89). The aim of this paper is to report on the process (implementation and mechanism of impact) of this intervention. METHODS: Process data were excerpted from diary information from meetings with facilitators and intervention groups, and from supervisor records of monthly meetings with facilitators. Data were analyzed using descriptive statistics. An evaluation including attributes and skills of facilitators (e.g., group management, communication, and commitment) was performed at the end of the intervention using a six-item instrument. Odds ratios were analyzed, adjusted for cluster randomization using general linear mixed models. RESULTS: To ensure eight active facilitators over 3 years, 11 Women's Union representatives were recruited and trained. Of the 44 intervention groups, composed of health staff and commune stakeholders, 43 completed their activities until the end of the study. In total, 95 % (n = 1508) of the intended monthly meetings with an intervention group and a facilitator were conducted. The overall attendance of intervention group members was 86 %. The groups identified 32 unique problems and implemented 39 unique actions. The identified problems targeted health issues concerning both women and neonates. Actions implemented were mainly communication activities. Communes supported by a group with a facilitator who was rated high on attributes and skills (n = 27) had lower odds of neonatal mortality (odds ratio, 0.37; 95 % confidence interval, 0.19-0.73) than control communes (n = 46). CONCLUSIONS: This evaluation identified several factors that might have influenced the outcomes of the trial: continuity of intervention groups' work, adequate attributes and skills of facilitators, and targeting problems along a continuum of care. Such factors are important to consider in scaling-up efforts.

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O objetivo deste trabalho foi comparar as estimativas de parâmetros genéticos obtidas em análises bayesianas uni-característica e bi-característica, em modelo animal linear e de limiar, considerando-se as características categóricas morfológicas de bovinos da raça Nelore. Os dados de musculosidade, estrutura física e conformação foram obtidos entre 2000 e 2005, em 3.864 animais de 13 fazendas participantes do Programa Nelore Brasil. Foram realizadas análises bayesianas uni e bi-características, em modelos de limiar e linear. de modo geral, os modelos de limiar e linear foram eficientes na estimação dos parâmetros genéticos para escores visuais em análises bayesianas uni-características. Nas análises bi-características, observou-se que: com utilização de dados contínuos e categóricos, o modelo de limiar proporcionou estimativas de correlação genética de maior magnitude do que aquelas do modelo linear; e com o uso de dados categóricos, as estimativas de herdabilidade foram semelhantes. A vantagem do modelo linear foi o menor tempo gasto no processamento das análises. Na avaliação genética de animais para escores visuais, o uso do modelo de limiar ou linear não influenciou a classificação dos animais, quanto aos valores genéticos preditos, o que indica que ambos os modelos podem ser utilizados em programas de melhoramento genético.

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The aim of the work was to study the effect of milking fraction on electrical conductivity of milk (EC) to improve its use in dairy goat mastitis detection using automatic EC measurements during milking. The experiment was carried out on a group of 84 Murciano-Granadina goats (28 primiparous and 56 multiparous). Goats were in the fourth month of lactation. A linear mixed model was used to analyse the relationship between EC or somatic cell count (SCC) of gland milk and parity, mammary gland health status, analysed fraction (first 100 mL=F-1; machine milk=F-2; and stripping milk=F-3) and their first order interactions. Additionally, the mastitis detection characteristics (sensitivity, specificity, positive predictive value and negative predictive value) of SCC and EC were studied at different thresholds.All factors considered were significant for EC and SCC. EC decreased significantly as milking progressed (from F-1 to F-3) in both healthy and infected glands. EC was not significantly different between healthy and infected glands in F-1 and F-2 fractions, but EC of healthy glands (5.01 mS/cm) was significantly lower than in infected glands (5.03 mS/cm) at F-3.Mastitis detection characteristics of EC did not differ amongst studied fractions. The small significant difference of EC between healthy and infected glands obtained in F-3 fraction did not yield better sensitivity results compared to F-1 and F-2. The best EC mastitis detection characteristics were obtained at 5.20 mS/cm threshold (sensitivity of 70% and specificity of 50%). The best SCC mastitis detection characteristics were obtained at 300,000 cells/mL threshold and F-3 fraction (sensitivity of 85% and specificity of 65%).It was concluded that mastitis detection characteristics of EC were similar in the three milking fractions analysed, being slightly better for SCC in F-3 fraction. As shown in previous studies, there are no factors other than the mammary gland health status that affect milk EC and should be considered in the algorithms for mastitis detection to improve the results. (C) 2012 Elsevier B.V. All rights reserved.

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It is often necessary to run response surface designs in blocks. In this paper the analysis of data from such experiments, using polynomial regression models, is discussed. The definition and estimation of pure error in blocked designs are considered. It is recommended that pure error is estimated by assuming additive block and treatment effects, as this is more consistent with designs without blocking. The recovery of inter-block information using REML analysis is discussed, although it is shown that it has very little impact if thc design is nearly orthogonally blocked. Finally prediction from blocked designs is considered and it is shown that prediction of many quantities of interest is much simpler than prediction of the response itself.

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

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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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Although conventional rotating machines have been largely used to drive underground transportation systems, linear induction motors are also being considered for future applications owing to their indisputable advantages. A mathematical model for the transient behavior analysis of linear induction motors, when operating with constant r.m.s. currents, is presented in this paper. Operating conditions, like phase short-circuit and input frequency variations and also some design characteristics, such as air-gap and secondary resistivity variations, can be considered by means of this modeling. The basis of the mathematical modeling is presented. Experimental results obtained in the laboratory are compared with the corresponding simulations and discussed in this paper.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Este trabalho objetivou predizer parâmetros da estrutura de associações macrobentônicas (composição específica, abundância, riqueza, diversidade e equitatividade) em estuários do Sul do Brasil, utilizando modelos baseados em dados ambientais (características dos sedimentos, salinidade, temperaturas do ar e da água, e profundidade). As amostragens foram realizadas sazonalmente em cinco estuários entre o inverno de 1996 e o verão de 1998. Em cada estuário as amostras foram coletadas em áreas não poluídas, com características semelhantes quanto a presença ou ausência de vegetação, profundidade e distância da desenbocadura. Para a obtenção dos modelos de predição, foram utilizados dois métodos: o primeiro baseado em Análise Discriminante Múltipla (ADM) e o segundo em Regressão Linear Múltipla (RLM). Os modelos baseados em ADM apresentaram resultados melhores do que os baseados em regressão linear. Os melhores resultados usando RLM foram obtidos para diversidade e riqueza. É possível então, concluir que modelos como aqui derivados podem representar ferramentas muito úteis em estudos de monitoramento ambiental em estuários.

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

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Patterns of spatio-temporal distribution of Brachyura are determined by the interaction among life history traits, inter and intraspecific relationships, as well as by the variation of abiotic factors. This study aimed to characterize patterns of spatio-temporal distribution of Persephona lichtensteinii, Persephona mediterranea and Persephona punctata in two regions of the northern coast of Sao Paulo State, southeastern region of Brazil. Collections were done monthly from July 2001 to June 2003 in Caraguatatuba and Ubatuba, using a shrimp fishery boat equipped with double-rig nets. The patterns of species distribution were tested by means of redundancy analysis (RDA) and generalized linear mixed models (GLMM) in relation to the recorded environmental factors (BT: bottom temperature, BS: bottom salinity, OM: organic matter and granulometry (Phi)). The most influent environmental factor over the species distribution was the Phi, and the ascendant order of influence was P. lichtensteinii, P. punctata and P. mediterranea. The greater abundance of P. mediterranea showed a conservative pattern of distribution for the genus in the sampled region. The greater occurrence of P. punctata and P. lichtensteinii, in distinct transects than those occupied by P. mediterranea, seems to be a strategy to avoid competition among congeneric species, which is related to the substratum specificity.