78 resultados para Mean squared error


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We study the effects of a repulsive three-body interaction on a system of trapped ultracold atoms in a Bose-Einstein condensed state. The stationary solutions of the corresponding s-wave nonlinear Schrödinger equation suggest a scenario of first-order liquid-gas phase transition in the condensed state up to a critical strength of the effective three-body force. The time evolution of the condensate with feeding process and three-body recombination losses has a different characteristic pattern. Also, the decay time of the dense (liquid) phase is longer than expected due to strong oscillations of the mean-squared radius.

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The objective of this study was to develop and evaluate a mathematical model used to estimate the daily amino acid requirements of individual growing-finishing pigs. The model includes empirical and mechanistic model components. The empirical component estimates daily feed intake (DFI), BW, and daily gain (DG) based on individual pig information collected in real time. Based on DFI, BW, and DG estimates, the mechanistic component uses classic factorial equations to estimate the optimal concentration of amino acids that must be offered to each pig to meet its requirements. The model was evaluated with data from a study that investigated the effect of feeding pigs with a 3-phase or daily multiphase system. The DFI and BW values measured in this study were compared with those estimated by the empirical component of the model. The coherence of the values estimated by the mechanistic component was evaluated by analyzing if it followed a normal pattern of requirements. Lastly, the proposed model was evaluated by comparing its estimates with those generated by the existing growth model (InraPorc). The precision of the proposed model and InraPorc in estimating DFI and BW was evaluated through the mean absolute error. The empirical component results indicated that the DFI and BW trajectories of individual pigs fed ad libitum could be predicted 1 d (DFI) or 7 d (BW) ahead with the average mean absolute error of 12.45 and 1.85%, respectively. The average mean absolute error obtained with the InraPorc for the average individual of the population was 14.72% for DFI and 5.38% for BW. Major differences were observed when estimates from InraPorc were compared with individual observations. The proposed model, however, was effective in tracking the change in DFI and BW for each individual pig. The mechanistic model component estimated the optimal standardized ileal digestible Lys to NE ratio with reasonable between animal (average CV = 7%) and overtime (average CV = 14%) variation. Thus, the amino acid requirements estimated by model are animal- and time-dependent and follow, in real time, the individual DFI and BW growth patterns. The proposed model can follow the average feed intake and feed weight trajectory of each individual pig in real time with good accuracy. Based on these trajectories and using classical factorial equations, the model makes it possible to estimate dynamically the AA requirements of each animal, taking into account the intake and growth changes of the animal. © 2012 American Society of Animal Science. All rights reserved.

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Lubricating oils are crucial in the operation of automotive engines because they both reduce friction between moving parts and protect against corrosion. However, the performance of lubricant oil may be affected by contaminants, such as gasoline, diesel, ethanol, water and ethylene glycol. Although there are many standard methods and studies related to the quantification of contaminants in lubricant oil, such as gasoline and diesel oil, to the best of our knowledge, no methods have been reported for the quantification of ethanol in used Otto cycle engine lubrication oils. Therefore, this work aimed at the development and validation of a routine method based on partial least-squares multivariate analysis combined with attenuated total reflectance in the mid-infrared region to quantify ethanol content in used lubrication oil. The method was validated based on its figures of merit (using the net analyte signal) as follows: limit of detection (0.049%), limit of quantification (0.16%), accuracy (root mean square error of prediction=0.089% w/w), repeatability (0.05% w/w), fit (R 2 =0.9997), mean selectivity (0.047), sensitivity (0.011), inverse analytical sensitivity (0.016% w/w-1) and signal-to-noise ratio (max: 812.4 and min: 200.9). The results show that the proposed method can be routinely implemented for the quality control of lubricant oils. © 2013 Elsevier B.V. All rights reserved.

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Estimating equations of global radiation based on the sunshine duration were proposed for horizontal surface and with inclination of 12.85, 22.85 and 32.85° facing the North in Botucatu, SP, Brazil, in monthly, seasonal and annual groupings of data. Simple linear correlations were applied (for definition of the linear and angular coefficients of Angstrom-Prescott model), in a database measured in all three inclinations in different periods (22.85°: 04/1998 to 07/2001; 12.85°: 08/2011 to 02/2003; and 32.85°: 03/2003 to 12/2007) concomitant with horizontal measures and sunshine duration. The statistical performance of the model was analysed by the means absolute error (MBE), the square root of the mean square error (RMSE) and the index adjustment (d). The minimum global radiation transmissivity varied from 14.35% in August (12.85°) to 27.86% in December (32.85°) and the maximum transmissivity ranged between 62.10% and 78.90%, for June (32.85°) and December (12.85°). Increasing the angle of inclination surface increased the scattering and decreased the index of adjustment and performance. The worst results were found for application of the seasonal and annual models in the months of autumn and winter for 32.85° (RMSE below 42.93% and adjustment superior to 0.4693).

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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia Mecânica - FEIS

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

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Biometria - IBB