818 resultados para Linear matrix inequalities (LMI) techniques


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Objective: the aim of this in vivo study was to evaluate the response of the pulp-dentin complex following application of resin-modified glass-ionomer cement, calcium hydroxide hard-setting cement and EDTA-soluble preparation of dentine matrix proteins (ESDP) in deep cavities prepared in non-human primate teeth. Methods: Eighteen deep Class V buccal cavities were prepared in premolars of four capuccin monkeys. In Groups 1 and 2, the cavity floor was lined with ESDP or a resin-modified glass-ionomer cement (Vitrebond - 3M ESPE), respectively. In Group 3 (control), the cavity was lined with a hard setting calcium hydroxide cement (Dycal - Dentsply). The cavities were subsequently filled with amalgam. After 6 months, the animals were sacrificed and the teeth were prepared for microscopic assessment. Six-micron thick serial sections were stained with H/E, Masson's trichrome and Brown & Brenn techniques. Results: No inflammatory pulpal response was observed for all experimental and control Groups. However, the amount of reactionary dentin deposition differed between groups in the rank order ESDP (Group 1) > calcium hydroxide (Group 3) > resin-modified glass-ionomer (Group 2). These differences were statistically significant. Conclusions: All materials were biocompatible when applied in deep cavities. ESDP stimulated higher deposition of reactionary dentin matrix than Vitrebond and Dycal.

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Bismuth was evaluated as an internal standard for the direct determination of Pb in vinegar by graphite furnace atomic absorption spectrometry using Ru as a permanent modifier with co-injection of Pd/Mg(NO3)(2). The correlation coefficient of the graph plotted from the non-nalized absorbance signals of Bi versus Pb was r=0.989. Matrix effects were evaluated by analyzing the slope ratios between the analytical curve, and analytical curves obtained from Pb additions in red and white wine vinegar obtained from reference solutions prepared in 0.2% (v/v) HNO3, samples. The calculated ratios were around 1.04 and 1.02 for analytical curves established applying an internal standard and 1.3 and 1.5 for analvtical curves without. Analytical curves in the 2.5-15 pg L-1 Pb concentration interval were established using the ratio Pb absorbance to Bi absorbance versus analvte concentration, and typical linear correlations of r=0.999 were obtained. The proposed method was applied for direct determination of Pb in 18 commercial vinegar samples and the Pb concentration varied from 2.6 to 31 pg L-1. Results were in agreement at a 95% confidence level (paired t-test) with those obtained for digested samples. Recoveries of Pb added to vinegars varied from 96 to 108% with and from 72 to 86% without an internal standard. Two water standard reference materials diluted in vinegar sample were also analyzed and results were in agreement with certified values at a 95% confidence level. The characteristic mass was 40 pg Pb and the useful lifetime of the tube was around 1600 firings. The limit of detection was 0.3 mu g L-1 and the relative standard deviation was <= 3.8% and <= 8.3% (n = 12) for a sample containing, 10 mu L-1 Pb with and without internal standard, respectively. (C) 2007 Elsevier B.V. All rights reserved.

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An amperometric biosensor based on cholinesterase (ChE) has been used for the determination of selected carbamate insecticides in vegetable samples. The linear range of the biosensor for the N-methylcarbamates (aldicarb, carbaryl, carbofuran, methomyl and propoxur) varied from 5 x 10(-5) to 50 mg kg(-1). Limits of detection were calculated on the basis that the ChE enzymes were 10% inhibited and varied, depending of the combination ChE (as acetyl- or butyrylcholinesterase) vs. inhibitor (pesticide), from 1 x 10(-4) to 3.5 mg kg(-1). The biosensor-based carbamate determination was compared to liquid chromatography/UV methods. Three vegetable samples were spiked with carbofuran and propoxur at 125 mu g kg(-1) followed by conventional procedures. Good correlations were observed for carbofuran in the vegetable extracts (79, 96 and 91% recoveries for potato, carrot and sweet pepper, respectively), whereas for propoxur unsatisfactory results were obtained. Potato and carrot samples were spiked with 10, 50 and 125 mu g kg(-1) carbofuran, followed by direct determination by the amperometric biosensor. The fortified sampler; resulted in very high inhibition values, and recoveries were: 28, 34 and 99% for potato, and 140, 90 and 101% for carrot, respectively, at these three fortification levels. (C) 1998 Elsevier B.V. B.V.

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Arsenic and germanium have been evaluated as internal standards to minimize matrix effects on the direct determination of selenium in milk by graphite furnace atomic absorption spectrometry (GFAAS) using tubes with integrated platform, pre-treated with W together with I'd as chemical modifier. The efficiency of As and Ge as internal standards for 25 mu g L-1 Se plus 500 mu g (L)-1 As or Ge in diluted (1 + 9 v/v) milk plus 1.0% (v/v) HNO3 was evaluated by means of correlation graphs plotted from the normalized absorbance signals (n = 20) of internal standard (axis gamma) versus analyte (axis x). The equations that describe the linear regression were: A(As)= - 0.004 +/- 0.019 +/- 1.02 + 0.019 A(Se) (r=0.9967 +/- 0.005); A(Ge)= - 0.0 17 +/- 0.015 + 1.01 +/- 0.015 A(Se) (r = 0.9978 +/- 0.004). Samples and reference solutions were automatically spiked with 500 mu g L-1 Ge or As and 1.0% (v/v) HNO3 by the autosampler. For 20 mu L of aqueous standard solutions, analytical curves in the 5.00-40.0 mu g L-1 Se range were established using the ratio of Se absorbance to internal standard absorbance (A(Se)A(IS)) versus analyte concentration, and good linear correlations were obtained. The characteristic mass was 40 pg Se. Limits of detection were 0.55 and 0.40 mu g L-1 with As and Ge as the internal standard, respectively. Relative standard deviations (RSD) for a sample containing 25 mu g L-1 Se were 1.2% and 1.0% (n = 12) using As and Ge, respectively. The RSD without internal standardization was about 6%. The accuracy of the proposed method was evaluated by an addition-recovery experiment and all recovered values were in the 99-105% range with IS and in the 70-80% range without IS. Using Ge as the internal standard, results of analysis of standard reference materials were in agreement with certified values at a 95% confidence level. The selenium concentration for 10 analyzed milk samples varied from 5.0 to 20 mu g L-1. (c) 2005 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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Pb2CrO5 nanoparticles were embedded in an amorphous SiO2 matrix by the sol-gel process. The pH and heat treatment effects were evaluated in terms of structural, microstructural and optical properties from Pb2CrO5/SiO2 compounds. X-ray diffraction (XRD), high resolution transmission electron microscopy (HR-TEM), energy dispersive spectroscopy (EDS), and diffuse reflectance techniques were employed. Kubelka-Munk theory was used to calculate diffuse reflectance spectra that were compared to the experimental results. Finally, colorimetric coordinates of the Pb2CrO5/SiO2 compounds were shown and discussed. In general, an acid pH initially dissolves Pb2CrO5 nanoparticles and following heat treatment at 600 A degrees C crystallized into PbCrO4 composition with grain size around 6 nm in SiO2 matrix. No Pb2CrO5 solubilization was observed for basic pH. These nanoparticles were incorporated in silica matrix showing a variety of color ranging from yellow to orange.

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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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Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

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A combined methodology consisting of successive linear programming (SLP) and a simple genetic algorithm (SGA) solves the reactive planning problem. The problem is divided into operating and planning subproblems; the operating subproblem, which is a nonlinear, ill-conditioned and nonconvex problem, consists of determining the voltage control and the adjustment of reactive sources. The planning subproblem consists of obtaining the optimal reactive source expansion considering operational, economical and physical characteristics of the system. SLP solves the optimal reactive dispatch problem related to real variables, while SGA is used to determine the necessary adjustments of both the binary and discrete variables existing in the modelling problem. Once the set of candidate busbars has been defined, the program implemented gives the location and size of the reactive sources needed, if any, to maintain the operating and security constraints.

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Individual data of basic density and volume of wood, pulp kappa number, soluble lignin, cost of pulping process as well as gravimetric gross yield of pulping process were used from 64 trees of Eucalyptus grandis W. Hill ex Maiden from a commercial population at Lençóis Paulista, SP. The Eucalyptus grandis's seeds were originally from a Seed Production Area (SPA) of Duratex S/A at Botucatu, SP. Obtained data were quantified considering objective of maximization no-bleaching pulp and volume and mass wood restriction, mass of residual and soluble lignin, planted area and pulping process cost. it has also been aimed a selection method for matrix trees through mathematical programming techniques. Obtained strategy maximized the economical result, selected matrix trees and followed all limits of technological and organizing productivities imposed by the company. It also aimed the production of no-bleaching pulp within the planned time.

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Linear mixed effects models have been widely used in analysis of data where responses are clustered around some random effects, so it is not reasonable to assume independence between observations in the same cluster. In most biological applications, it is assumed that the distributions of the random effects and of the residuals are Gaussian. This makes inferences vulnerable to the presence of outliers. Here, linear mixed effects models with normal/independent residual distributions for robust inferences are described. Specific distributions examined include univariate and multivariate versions of the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted and Markov chain Monte Carlo is used to carry out the posterior analysis. The procedures are illustrated using birth weight data on rats in a texicological experiment. Results from the Gaussian and robust models are contrasted, and it is shown how the implementation can be used for outlier detection. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process in linear mixed models, and they are easily implemented using data augmentation and MCMC techniques.

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Turquoise blue 15 (AT15) is a reactive dye widely used in the textile industry to color natural fibers. The presence of these dyes in effluent and industrial wastewater is of considerable interest due ecotoxicological and environmental problems. The electrochemical reduction of this dye has been investigated in aqueous solution using cyclic voltammetry, controlled potential electrolysis and cathodic stripping voltammetry. Optimum conditions for dye discoloration by controlled potential electrolysis use an alkaline medium. Using cathodic stripping voltammetry a linear calibration graph was obtained from 5.00×10-8 mol L-1 to 1.00×10 -6 mol L-1 of AT15 at pH 4.0, using accumulation times of 180 and 240 s and an accumulation potential of 0.0 V. The proposed method was applied in direct determination of the dye in tap water and in textile industry effluent.

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This paper presents a new methodology for the adjustment of fuzzy inference systems. A novel approach, which uses unconstrained optimization techniques, is developed in order to adjust the free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through an estimation of time series. More specifically, the Mackey-Glass chaotic time series estimation is used for the validation of the proposed methodology.

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This paper deals with a stochastic optimal control problem involving discrete-time jump Markov linear systems. The jumps or changes between the system operation modes evolve according to an underlying Markov chain. In the model studied, the problem horizon is defined by a stopping time τ which represents either, the occurrence of a fix number N of failures or repairs (TN), or the occurrence of a crucial failure event (τΔ), after which the system is brought to a halt for maintenance. In addition, an intermediary mixed case for which T represents the minimum between TN and τΔ is also considered. These stopping times coincide with some of the jump times of the Markov state and the information available allows the reconfiguration of the control action at each jump time, in the form of a linear feedback gain. The solution for the linear quadratic problem with complete Markov state observation is presented. The solution is given in terms of recursions of a set of algebraic Riccati equations (ARE) or a coupled set of algebraic Riccati equation (CARE).

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For a typical non-symmetrical system with two parallel three phase transmission lines, modal transformation is applied using some examples of single real transformation matrices. These examples are applied searching an adequate single real transformation matrix to two parallel three phase transmission line systems. The analyses are started with the eigenvector and eigenvalue studies, using Clarke's transformation or linear combinations of Clarke's elements. The Z C and parameters are analyzed for the case that presents the smallest errors between the exact eigenvalues and the single real transformation matrix application results. The single real transformation determined for this case is based on Clarke's matrix and its main characteristic is the use of a unique homopolar reference. So, the homopolar mode becomes a connector mode between the two three-phase circuits of the analyzed system. ©2005 IEEE.