45 resultados para PID and Fuzzy and practical models
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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.
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Searches are reported for Higgs bosons in the context of either the standard model extended to include a fourth generation of fermions (SM4) with masses of up to 600 GeV or fermiophobic models. For the former, results from three decay modes (ττ, WW, and ZZ) are combined, whilst for the latter the diphoton decay is exploited. The analysed proton-proton collision data correspond to integrated luminosities of up to 5.1 fb-1 at 7 TeV and up to 5.3 fb-1 at 8 TeV. The observed results exclude the SM4 Higgs boson in the mass range 110-600 GeV at 99% confidence level (CL), and in the mass range 110-560 GeV at 99.9% CL. A fermiophobic Higgs boson is excluded in the mass range 110-147 GeV at 95% CL, and in the range 110-133 GeV at 99% CL. The recently observed boson with a mass near 125 GeV is not consistent with either an SM4 or a fermiophobic Higgs boson. © 2013 CERN.
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The strut-and-tie models are widely used in certain types of structural elements in reinforced concrete and in regions with complexity of the stress state, called regions D, where the distribution of deformations in the cross section is not linear. This paper introduces a numerical technique to determine the strut-and-tie models using a variant of the classical Evolutionary Structural Optimization, which is called Smooth Evolutionary Structural Optimization. The basic idea of this technique is to identify the numerical flow of stresses generated in the structure, setting out in more technical and rational members of strut-and-tie, and to quantify their value for future structural design. This paper presents an index performance based on the evolutionary topology optimization method for automatically generating optimal strut-and-tie models in reinforced concrete structures with stress constraints. In the proposed approach, the element with the lowest Von Mises stress is calculated for element removal, while a performance index is used to monitor the evolutionary optimization process. Thus, a comparative analysis of the strut-and-tie models for beams is proposed with the presentation of examples from the literature that demonstrates the efficiency of this formulation. © 2013 Elsevier Ltd.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Adjusting autoregressive and mixed models to growth data fits discontinuous functions, which makes it difficult to determine critical points. In this study we propose a new approach to determine the critical stability point of cattle growth using a first-order autoregressive model and a mixed model with random asymptote, using the deterministic portion of the models. Three functions were compared: logistic, Gompertz, and Richards. The Richards autoregressive model yielded the best fit, but the critical growth values were adjusted very early, and for this purpose the Gompertz model was more appropriate.
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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.
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This work presents a new and simple electrode, which may be used to achieve the electrochemical response of ground solids or insoluble samples. Ore samples from Morro Velho Mine (Brazil) were employed to exemplify the use of such electrodes. The new electrode avoids the use of binders or other agents overcoming major deterioration problems. (C) 2002 Published by Elsevier Science B.V.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The use of medicinal plants among pregnant women and lactating is a common practice in diverse countries. However, many medicinal plants are contraindicated during pregnancy and lactating, due to various adverse effects, such as teratogenic, embryotoxic and abortive effects, exposing these women, their fetus and babies to health unknown risks. Thus, the purpose of this commentary, was to analyze the perception about the use of medicinal plants by pregnant women and lactating registered in the "baby on board" NGO, Araraquara, São Paulo state, Brazil, between 2010 at 2013. The group was constituted by 48 women, between the first and last trimester of pregnancy or whilst breastfeeding. Information was collected during group meetings by oral interview, using a questionnaire, as script. The nature of the study was a qualitative analysis. The results were based on reports about the use of medicinal plants by pregnant women during group meetings: use, indication of use, knowledge about risks. All participants received written and oral information about the study and they gave a written informed consent. The use of medicinal plants is a reality among pregnant and lactating women of the "baby on board" NGO. They reported that they feel that "natural" products are not harmful for their health. The primary information sources for the majority of women about medicinal plants during pregnancy are family, neighbors and herbalists. The plants most cited (in popular name in Brazil) were: senna, chamomile, boldo, lemon balm, lemon grass. They were used mainly for: nausea, heartburn, indigestion, flatulence, intestinal and abdominal pain, anxiety, intestinal constipation and low milk production. The pregnant and lactating women lacked knowledge about the health risks of the use of medicinal plants and herbal medicines in pregnancy and lactation. They also reported difficulties in clarifying some questions about the use of medicinal plants with their doctors. The results of the present study showed that educative actions about the rational use of medicinal plants in pregnancy and breastfeeding could be part of the operating protocols to promote the maternal and child health programs in Araraquara. Thus, our results also suggest the importance of creating institutionalized places, to the implementation of continued education programs about rational use of medicinal plants in pregnancy and lactation. These targeted programs are not only for health professionals, but also for community members, pregnant women and breastfeeding. Our results pointed out the importance of guidance of doctors and healthcare professionals on the scientific studies about medicinal plants and herbal medicines and the risk/benefit of using herbs during pregnancy. Finally, it is noted the importance of the health professionals to inform women of childbearing on risks to their health, as well as on possibilities of utilization of herbs during fertile period, giving special attention to the potential risk of self-medication.
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Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)