Evaluation of pre-natal care from the perspective of different models in primary care

OBJETIVOS: avaliar a qualidade do cuidado pré-natal desenvolvido na atenção primária, comparando os modelos tradicional e Estratégia Saúde da Família. MÉTODO: estudo de avaliação de serviço, pautado nas políticas públicas de saúde. Os dados foram obtidos por meio de entrevista com gerentes, observação nas unidades de saúde e análise de prontuários de gestantes, selecionados aleatoriamente. Diferenças nos indicadores de estrutura e processo foram avaliadas pelo teste qui-quadrado, adotando-se p<0,05 como nível crítico, cálculo dos odds ratio e intervalos de confiança de 95%. RESULTADOS: foram evidenciadas estruturas semelhantes em ambos os modelos de atenção. Indicadores-síntese de processo, criados neste estudo, e os indicados pelas políticas públicas apontaram situação mais favorável nas Unidades de Saúde da Família. Para o conjunto de atividades preconizadas para o pré-natal, o desempenho foi deficiente em ambos os modelos, embora pouco melhor nas Unidades de Saúde da Família. CONCLUSÃO: os resultados indicam a necessidade de ações para melhoria da atenção pré-natal nos dois modelos de atenção básica no município avaliado.

Evaluation of economic impact of external eauivalent models used in reactive OPF studies for interconnected systems

Reactive-optimisation procedures are responsible for the minimisation of online power losses in interconnected systems. These procedures are performed separately at each control centre and involve external network representations. If total losses can be minimised by the implementation of calculated local control actions, the entire system benefits economically, but such control actions generally result in a certain degree of inaccuracy, owing to errors in the modelling of the external system. Since these errors are inevitable, they must at least be maintained within tolerable limits by external-modelling approaches. Care must be taken to avoid unrealistic loss minimisation, as the local-control actions adopted can lead the system to points of operation which will be less economical for the interconnected system as a whole. The evaluation of the economic impact of the external modelling during reactive-optimisation procedures in interconnected systems, in terms of both the amount of losses and constraint violations, becomes important in this context. In the paper, an analytical approach is proposed for such an evaluation. Case studies using data from the Brazilian South-Southeast system (810 buses) have been carried out to compare two different external-modelling approaches, both derived from the equivalent-optimal-power-flow (EOPF) model. Results obtained show that, depending on the external-model representation adopted, the loss representation can be flawed. Results also suggest some modelling features that should be adopted in the EOPF model to enhance the economy of the overall system.

Evaluation and identification of lightning models by artificial neural networks

This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.

Study of biosorption of rare earth metals (La, Nd, Eu, Gd) by Sargassum sp. biomass in batch systems: Physicochemical evaluation of kinetics and adsorption models

This work evaluated kinetic and adsorption physicochemical models for the biosorption process of lanthanum, neodymium, europium, and gadolinium by Sargassum sp. in batch systems. The results showed: (a) the pseudo-second order kinetic model was the best approximation for the experimental data with the metal adsorption initial velocity parameter in 0.042-0.055 mmol.g -1.min-1 (La < Nd < Gd < Eu); (b) the Langmuir adsorption model presented adequate correlation with maximum metal uptake at 0.60-0.70 mmol g-1 (Eu < La < Gd < Nd) and the metal-biomass affinity parameter showed distinct values (Gd < Nd < Eu < La: 183.1, 192.5, 678.3, and 837.3 L g-1, respectively); and (c) preliminarily, the kinetics and adsorption evaluation did not reveal a well-defined metal selectivity behavior for the RE biosorption in Sargassum sp., but they indicate a possible partition among RE studied. © (2009) Trans Tech Publications.

A proposal for reliability evaluation of components on electric power distribution system integrating probabilistic models and fuzzy inference systems

The system reliability depends on the reliability of its components itself. Therefore, it is necessary a methodology capable of inferring the state of functionality of these components to establish reliable indices of quality. Allocation models for maintenance and protective devices, among others, have been used in order to improve the quality and availability of services on electric power distribution systems. This paper proposes a methodology for assessing the reliability of distribution system components in an integrated way, using probabilistic models and fuzzy inference systems to infer about the operation probability of each component. © 2012 IEEE.

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.

Evaluation of the Host Response in Various Models of Induced Periodontal Disease in Mice

Background: The aim of this study is to characterize and evaluate the host response caused by three different models of experimental periodontitis in mice.Methods: C57BL/6 wild-type female mice were distributed into six experimental groups and sacrificed at 7, 15, and 30 days after the induction of periodontal disease: 1) group C: no treatment control group; 2) group L: periodontal disease induced by ligature; 3) group G-Pg: oral gavage with Porphyromonas gingivalis (Pg); 4) group G-PgFn: oral gavage with Fusobacterium nucleatum + Pg; 5) group I-Pg: heat-killed Pg injected into the palatal mucosa between the molars; and 6) group I-V: phosphatebuffered saline injected into the palatal mucosa. The samples were used to analyze the immune-inflammatory process in the gingival tissue via descriptive histologic and real-time polymerase chain reaction analyses. The alveolar bone loss was evaluated using microcomputed tomography. The data were analyzed using the Kruskal-Wallis test, followed by a post hoc Dunn test and analysis of variance, followed by a Tukey test using a 5% significance level.Results: Only the ligature model displayed significant alveolar bone loss in the initial period (7 days), which was maintained with time. The group injected with heat-killed Pg displayed significant alveolar bone loss starting from day 15, which continued to progress with time (P < 0.05). A significant increase (P < 0.05) in the gene expression of proinflammatory cytokines (interleukin-6 and -1b) and proteins involved in osteoclastogenesis (receptor activator of nuclear factor-kB ligand and osteoprotegerin) was observed in the ligature group on day 7.Conclusion: The ligature and injection of heat-killed Pg models were the most representative of periodontal disease in humans, whereas the oral gavage models were not effective at inducing the disease under the experimental conditions.

A comparative evaluation of the CF:CS and CRS models in Pb-210 chronological studies applied to hydrographic basins in Brazil

The Constant Flux: Constant Sedimentation (CF:CS) and Constant Rate of Supply (CRS) of unsupported/excess Pb-210 models have been applied to a Pb-210 data set providing of eighteen sediments profiles sampled at four riverine systems occurring in Brazil, South America: Corumbatai River basin (S1=Site 1, Sao Paulo State), Atibaia River basin (S2=Site 2, Sao Paulo State), Ribeirao dos Bagres basin (S3=Site 3, Sao Paulo State) and Amazon River mouth. (S4=Site 4, Amapa State). These sites were chosen for a comparative evaluation of the performance of the CF:CS and CRS models due to their pronounced differences on the geographical location, geological context, soil composition, biodiversity, climate, rainfall, and water flow regime, among other variable aspects. However, all sediments cores exhibited a common denominator consisting on a database built from the use of the same techniques for acquiring the sediments major chemical composition (SiO2, Al2O3, Na2O, K2O, CaO, MgO, Fe2O3, MnO, P2O5, TiO2 and LOI-Loss on Ignition) and unsupported/excess 210Pb activity data. In terms of sedimentation rates, the performance of the CRS model was better than that of the CF:CS model as it yielded values more compatible with those expected from field evidences. Under the chronological point of view, the CRS model always provided ages within the permitted range of the Pb-210-method in the studied sites, whereas the CF:CS model predicted some values above 150 years. The SiO2 content decreased in accordance with the LOI increase in all cores analyzed and such inverse relationship was also tracked in the SiO2-LOI curves of historical trends. The SiO2-LOI concentration fluctuations in sites S1 and S3 also coincided with some Cu and Cr inputs in the drainage systems. (C) 2014 Elsevier Ltd. All rights reserved.

Evaluation of roof slope and exposure with different roofing materials in reduced models of animal production facilities in spring and summer

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

Evaluation of neural models applied to the estimation of tool wear in the grinding of advanced ceramics

Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (CNPq)

Secondary production of sandy beach macrofauna: An evaluation of predictive models

During the last three decades, several predictive models have been developed to estimate the somatic production of macroinvertebrates. Although the models have been evaluated for their ability to assess the production of macrobenthos in different marine ecosystems, these approaches have not been applied specifically to sandy beach macrofauna and may not be directly applicable to this transitional environment. Hence, in this study, a broad literature review of sandy beach macrofauna production was conducted and estimates obtained with cohort-based and size-based methods were collected. The performance of nine models in estimating the production of individual populations from the sandy beach environment, evaluated for all taxonomic groups combined and for individual groups separately, was assessed, comparing the production predicted by the models to the estimates obtained from the literature (observed production). Most of the models overestimated population production compared to observed production estimates, whether for all populations combined or more specific taxonomic groups. However, estimates by two models developed by Cusson and Bourget provided best fits to measured production, and thus represent the best alternatives to the cohort-based and size-based methods in this habitat. The consistent performance of one of these Cusson and Bourget models, which was developed for the macrobenthos of sandy substrate habitats (C&B-SS), shows that the performance of a model does not depend on whether it was developed for a specific taxonomic group. Moreover, since some widely used models (e.g., the Robertson model) show very different responses when applied to the macrofauna of different marine environments (e.g., sandy beaches and estuaries), prior evaluation of these models is essential.