905 resultados para partial least-squares regression


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Waste stabilization ponds (WSP) have been widely used for sewage treatment in hot climate regions because they are economic and environmentally sustainable. In the present study a WSP complex comprising a primary facultative pond (PFP) followed by two maturation ponds (MP-1 and MP-2) was studied, in the city of Natal-RN. The main objective was to study the bio-degradability of organic matter through the determination of the kinetic constant k throughout the system. The work was carried out in two phases. In the first, the variability in BOD, COD and TOC concentrations and an analysis of the relations between these parameters, in the influent raw sewage, pond effluents and in specific areas inside the ponds was studied. In the second stage, the decay rate for organic matter (k) was determined throughout the system based on BOD tests on the influent sewage, pond effluents and water column samples taken from fixed locations within the ponds, using the mathematical methods of Least Squares and the Thomas equation. Subsequently k was estimated as a function of a hydrodynamic model determined from the dispersion number (d), using empirical methods and a Partial Hydrodynamic Evaluation (PHE), obtained from tracer studies in a section of the primary facultative pond corresponding to 10% of its total length. The concentrations of biodegradable organic matter, measured as BOD and COD, gradually reduced through the series of ponds, giving overall removal efficiencies of 71.95% for BOD and of 52.45% for COD. Determining the values for k, in the influent and effluent samples of the ponds using the mathematical method of Least Squares, gave the following values respectively: primary facultative pond (0,23 day-1 and 0,09 day-1), maturation 1 (0,04 day-1 and 0,03 day-1) and maturation 2 (0,03 day-1 and 0,08 day-1). When using the Thomas method, the values of k in the influents and effluents of the ponds were: primary facultative pond (0,17 day-1 and 0,07 day-1), maturation 1 (0,02 day-1 and 0,01 day-1) and maturation 2 (0,01 day-1 and 0,02 day-1). From the Partial Hydrodynamic Evaluation, in the first section of the facultative pond corresponding to 10% of its total length, it can be concluded from the dispersion number obtained of d = 0.04, that the hydraulic regime is one of dispersed flow with a kinetic constant value of 0.20 day-1

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Conselho Nacional do Desenvolvimento Científico e Tecnológico (CNPq)

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The element-free Galerkin method (EFGM) is a very attractive technique for solutions of partial differential equations, since it makes use of nodal point configurations which do not require a mesh. Therefore, it differs from FEM-like approaches by avoiding the need of meshing, a very demanding task for complicated geometry problems. However, the imposition of boundary conditions is not straightforward, since the EFGM is based on moving-least-squares (MLS) approximations which are not necessarily interpolants. This feature requires, for instance, the introduction of modified functionals with additional unknown parameters such as Lagrange multipliers, a serious drawback which leads to poor conditionings of the matrix equations. In this paper, an interpolatory formulation for MLS approximants is presented: it allows the direct introduction of boundary conditions, reducing the processing time and improving the condition numbers. The formulation is applied to the study of two-dimensional magnetohydrodynamic flow problems, and the computed results confirm the accuracy and correctness of the proposed formulation. (C) 2002 Elsevier B.V. All rights reserved.

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

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In this work a new method is proposed of separated estimation for the ARMA spectral model based on the modified Yule-Walker equations and on the least squares method. The proposal of the new method consists of performing an AR filtering in the random process generated obtaining a new random estimate, which will reestimate the ARMA model parameters, given a better spectrum estimate. Some numerical examples will be presented in order to ilustrate the performance of the method proposed, which is evaluated by the relative error and the average variation coefficient.

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Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore. ©2006 American Society of Animal Science. All rights reserved.

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To ensure high accuracy results from GPS relative positioning, the multipath effects have to be mitigated. Although the careful selection of antenna site and the use of especial antennas and receivers can minimize multipath, it cannot always be eliminated and frequently the residual multipath disturbance remains as the major error in GPS results. The high-frequency multipath from large delays can be attenuated by double difference (DD) denoising methods. But the low-frequency multipath from short delays is very difficult to be reduced or modeled. In this paper, it is proposed a method based on wavelet regression (WR), which can effectively detect and reduce the low-frequency multipath. The wavelet technique is firstly applied to decompose the DD residuals into the low-frequency bias and high-frequency noise components. The extracted bias components by WR are then directly applied to the DD observations to correct them from the trend. The remaining terms, largely characterized by the high-frequency measurement noise, are expected to give the best linear unbiased solutions from a least-squares (LS) adjustment. An experiment was carried out using objects placed close to the receiver antenna to cause, mainly, low-frequency multipath. The data were collected for two days to verify the multipath repeatability. The ground truth coordinates were computed with data collected in the absence of the reflector objects. The coordinates and ambiguity solution were compared with and without the multipath mitigation using WR. After mitigating the multipath, ambiguity resolution became more reliable and the coordinates were more accurate.

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Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.

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When searching for prospective novel peptides, it is difficult to determine the biological activity of a peptide based only on its sequence. The trial and error approach is generally laborious, expensive and time consuming due to the large number of different experimental setups required to cover a reasonable number of biological assays. To simulate a virtual model for Hymenoptera insects, 166 peptides were selected from the venoms and hemolymphs of wasps, bees and ants and applied to a mathematical model of multivariate analysis, with nine different chemometric components: GRAVY, aliphaticity index, number of disulfide bonds, total residues, net charge, pI value, Boman index, percentage of alpha helix, and flexibility prediction. Principal component analysis (PCA) with non-linear iterative projections by alternating least-squares (NIPALS) algorithm was performed, without including any information about the biological activity of the peptides. This analysis permitted the grouping of peptides in a way that strongly correlated to the biological function of the peptides. Six different groupings were observed, which seemed to correspond to the following groups: chemotactic peptides, mastoparans, tachykinins, kinins, antibiotic peptides, and a group of long peptides with one or two disulfide bonds and with biological activities that are not yet clearly defined. The partial overlap between the mastoparans group and the chemotactic peptides, tachykinins, kinins and antibiotic peptides in the PCA score plot may be used to explain the frequent reports in the literature about the multifunctionality of some of these peptides. The mathematical model used in the present investigation can be used to predict the biological activities of novel peptides in this system, and it may also be easily applied to other biological systems. © 2011 Elsevier Inc.

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Four experiments evaluated the effects of vaccination against bovine herpesvirus-1 (BoHV-1), bovine viral diarrhea virus (BVDV), and Leptospira spp. on reproductive performance of lactating dairy cows without (experiments 1, 2, and 3) or with previous vaccination against these diseases (experiment 4). Cows were assigned to a fixed-time AI protocol (FTAI; d -11 to 0) in all experiments, as well as AI 12. h upon estrus detection in experiment 3. Pregnancy status was determined with transrectal ultrasonography on d 30 and 71 (d 60 for experiment 3) after AI. Pregnancy loss was considered in cows pregnant on d 30 but non-pregnant on the subsequent evaluation. In experiment 1, 853 cows received (VAC) or not (CON) vaccination against BoHV-1, BVDV, and Leptospira spp. at the beginning of the FTAI (d -11) and 30. d after AI. Pregnancy loss was reduced (P=0.03) in VAC cows compared with CON. In experiment 2, 287 cows received VAC or CON 30. d prior to (d -41) and at the beginning (d -11) of the FTAI. Pregnancy rates on d 30 and 71 were greater (P≤0.03) in VAC cows compared with CON. In experiment 3, 1680 cows with more than 28. d in milk were randomly assigned to receive VAC or CON with doses administered 14. d apart, and inseminated within 15-135. d after the second dose. Pregnancy rates on d 30 and 60 were greater (P≤0.02) in VAC cows compared with CON. In experiment 4, 820 cows received (REVAC) or not (CON) revaccination against BoHV-1, BVDV, and Leptospira spp. at the beginning of the FTAI protocol (d -11). Pregnancy rates and loss were similar (P≥0.54) between treatments. Hence, vaccinating naïve cows against BoHV-1, BVDV, and Leptospira spp. improved reproductive efficiency in dairy production systems, particularly when both doses were administered prior to AI. © 2013 Elsevier B.V.

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Fifty-nine Nellore bulls from low and high residual feed intake (RFI) levels were studied with the objective of evaluating meat quality traits. Animals were slaughtered when ultrasound-measured backfat thickness reached 4. mm, and samples of Longissimus were collected. A mixed model including RFI as fixed effect and herd and diet as random effects was used, and least square means were compared by t-test. More efficient animals consumed 0.730. kg dry matter/day less than less efficient animals, with similar performance. No significant differences in carcass weight, prime meat cuts proportion, chemical composition, pH, sarcomere length, or color were observed between RFI groups. Shear force, myofibrillar fragmentation index and soluble collagen content were influenced by RFI, with a higher shear force and soluble collagen content and a lower fragmentation index in low RFI animals. Feedlot-finished low RFI young Nellore bulls more efficiently convert feed into meat, presenting carcasses within quality standards. © 2012 Elsevier Ltd.

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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)