940 resultados para Generalized Differential Transform Method


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Thermal properties and degree of conversion (DC%) of two composite resins (microhybrid and nanocomposite) and two photo-activation methods (continuous and gradual) displayed by the light-emitting diode (LED) light-curing units (LCUs) were investigated in this study. Differential scanning calorimetry (DSC) thermal analysis technique was used to investigate the glass transition temperature (T(g)) and degradation temperature. The DC% was determined by Fourier transform infrared spectroscopy (FT-IR). The results showed that the microhybrid composite resin presented the highest T(g) and degradation temperature values, i.e., the best thermal stability. Gradual photo-activation methods showed higher or similar T(g) and degradation temperature values when compared to continuous method. The Elipar Freelight 2 (TM) LCU showed the lowest T(g) values. With respect to the DC%, the photo-activation method did not influence the final conversion of composite resins. However, Elipar Freelight 2 (TM) LCU and microhybrid resin showed the lowest DC% values. Thus, the presented results suggest that gradual method photo-activation with LED LCUs provides adequate degree of conversion without promoting changes in the polymer chain of composite resins. However, the thermal properties and final conversion of composite resins can be influenced by the kind of composite resin and LCU.

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The generalized Birnbaum-Saunders distribution pertains to a class of lifetime models including both lighter and heavier tailed distributions. This model adapts well to lifetime data, even when outliers exist, and has other good theoretical properties and application perspectives. However, statistical inference tools may not exist in closed form for this model. Hence, simulation and numerical studies are needed, which require a random number generator. Three different ways to generate observations from this model are considered here. These generators are compared by utilizing a goodness-of-fit procedure as well as their effectiveness in predicting the true parameter values by using Monte Carlo simulations. This goodness-of-fit procedure may also be used as an estimation method. The quality of this estimation method is studied here. Finally, through a real data set, the generalized and classical Birnbaum-Saunders models are compared by using this estimation method.

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The Birnbaum-Saunders (BS) model is a positively skewed statistical distribution that has received great attention in recent decades. A generalized version of this model was derived based on symmetrical distributions in the real line named the generalized BS (GBS) distribution. The R package named gbs was developed to analyze data from GBS models. This package contains probabilistic and reliability indicators and random number generators from GBS distributions. Parameter estimates for censored and uncensored data can also be obtained by means of likelihood methods from the gbs package. Goodness-of-fit and diagnostic methods were also implemented in this package in order to check the suitability of the GBS models. in this article, the capabilities and features of the gbs package are illustrated by using simulated and real data sets. Shape and reliability analyses for GBS models are presented. A simulation study for evaluating the quality and sensitivity of the estimation method developed in the package is provided and discussed. (C) 2008 Elsevier B.V. All rights reserved.

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We present a variable time step, fully adaptive in space, hybrid method for the accurate simulation of incompressible two-phase flows in the presence of surface tension in two dimensions. The method is based on the hybrid level set/front-tracking approach proposed in [H. D. Ceniceros and A. M. Roma, J. Comput. Phys., 205, 391400, 2005]. Geometric, interfacial quantities are computed from front-tracking via the immersed-boundary setting while the signed distance (level set) function, which is evaluated fast and to machine precision, is used as a fluid indicator. The surface tension force is obtained by employing the mixed Eulerian/Lagrangian representation introduced in [S. Shin, S. I. Abdel-Khalik, V. Daru and D. Juric, J. Comput. Phys., 203, 493-516, 2005] whose success for greatly reducing parasitic currents has been demonstrated. The use of our accurate fluid indicator together with effective Lagrangian marker control enhance this parasitic current reduction by several orders of magnitude. To resolve accurately and efficiently sharp gradients and salient flow features we employ dynamic, adaptive mesh refinements. This spatial adaption is used in concert with a dynamic control of the distribution of the Lagrangian nodes along the fluid interface and a variable time step, linearly implicit time integration scheme. We present numerical examples designed to test the capabilities and performance of the proposed approach as well as three applications: the long-time evolution of a fluid interface undergoing Rayleigh-Taylor instability, an example of bubble ascending dynamics, and a drop impacting on a free interface whose dynamics we compare with both existing numerical and experimental data.

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We continue the investigation of the algebraic and topological structure of the algebra of Colombeau generalized functions with the aim of building up the algebraic basis for the theory of these functions. This was started in a previous work of Aragona and Juriaans, where the algebraic and topological structure of the Colombeau generalized numbers were studied. Here, among other important things, we determine completely the minimal primes of (K) over bar and introduce several invariants of the ideals of 9(Q). The main tools we use are the algebraic results obtained by Aragona and Juriaans and the theory of differential calculus on generalized manifolds developed by Aragona and co-workers. The main achievement of the differential calculus is that all classical objects, such as distributions, become Cl-functions. Our purpose is to build an independent and intrinsic theory for Colombeau generalized functions and place them in a wider context.

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There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

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A new electrochemical methodology has been developed for the detection of ozone using multiwalled carbon nanotubes (MWCNT). The method presented here is based on the reaction of ozone with indigo blue dye producing anthranilic acid (ATN). The electrochemical profile of ATN on an electrode of glassy carbon (GC) modified with MWCNT showed an oxidation peak potential at 750 mV vs. Ag/AgCl. An analytical method was developed using differential pulse voltammetry (DPV) to determine ATN in a range of 50-400 nmol L(-1), with a detection limit of 9.7 nmol L(-1). Ozonated water samples were successfully analyzed by GC/MWCNT electrode and the recovery procedure yielded values between of 96.5 and 102.3%.

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The aim of this work was to evaluate the effect of the storage time on the thermal properties of triethylene glycol dimethacrylate/2,2-bis[4-(2-hydroxy-3-methacryloxy-prop-1-oxy)-phenyl]propane bisphenyl-alpha-glycidyl ether dimethacrylate (TB) copolymers used in formulations of dental resins after photopolymerization. The TB copolymers were prepared by photopolymerization with an Ultrablue IS light-emitting diode, stored in the dark for 160 days at 37 degrees C, and characterized with differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and Fourier transform infrared spectroscopy with attenuated total reflection. DSC curves indicated the presence of an exothermic peak, confirming that the reaction was not completed during the photopolymerization process. This exothermic peak became smaller as a function of the storage time and was shifted at higher temperatures. In DMA studies, a plot of the loss tangent versus the temperature initially showed the presence of two well-defined peaks. The presence of both peaks confirmed the presence of residual monomers that were not converted during the photopolymerization process. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 112: 679-684, 2009

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A cathodically pretreated boron-doped diamond electrode was used for the simultaneous anodic determination of ascorbic acid (AA) and caffeine (CAF) by differential pulse voltammetry Linear calibration curves (r = 0 999) were obtained from 1 9 x 10(-5) to 2 I x 10(-4) mol L(-1) for AA and from 9 7 x 10(-6) to 1 1 x 10-4 mol L(-1) for CAF. with detection limits of 19 wool L(-1) and 7 0 mu nol L(-1). respectively This method was successfully applied for the determination of AA and CAF in pharmaceutical formulations. with results equal to those obtained using a HPLC reference method

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Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

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Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

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Ionic liquids (ILs) are organic compounds liquid at room temperature, good electrical conductors, with the potential to form as a means for electrolyte on electrolysis of water, in which the electrodes would not be subjected to such extreme conditions demanding chemistry [1]. This paper describes the synthesis, characterization and study of the feasibility of ionic liquid ionic liquid 1-methyl-3(2,6-(S)-dimethyloct-2-ene)-imidazole tetrafluoroborate (MDI-BF4) as electrolyte to produce hydrogen through electrolysis of water. The MDI-BF4 synthesized was characterized by thermal methods of analysis (Thermogravimetric Analysis - TG and Differential Scanning Calorimetry - DSC), mid-infrared spectroscopy with Fourier transform by method of attenuated total reflectance (FTIR-ATR), nuclear magnetic resonance spectroscopy of hydrogen (NMR 1H) and cyclic voltammetry (CV). Where thermal methods were used to calculate the yield of the synthesis of MDI-BF4 which was 88.84%, characterized infrared spectroscopy functional groups of the compound and the binding B-F 1053 cm-1; the NMR 1H analyzed and compared with literature data defines the structure of MDI-BF4 and the current density achieved by MDI-BF4 in the voltammogram shows that the LI can conduct electrical current indicating that the MDI-BF4 is a good electrolyte, and that their behavior does not change with the increasing concentration of water

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This thesis presents a new structure of robust adaptive controller applied to mobile robots (surface mobile robot) with nonholonomic constraints. It acts in the dynamics and kinematics of the robot, and it is split in two distinct parts. The first part controls the robot dynamics, using variable structure model reference adaptive controllers. The second part controls the robot kinematics, using a position controller, whose objective is to make the robot to reach any point in the cartesian plan. The kinematic controller is based only on information about the robot configuration. A decoupling method is adopted to transform the linear model of the mobile robot, a multiple-input multiple-output system, into two decoupled single-input single-output systems, thus reducing the complexity of designing the controller for the mobile robot. After that, a variable structure model reference adaptive controller is applied to each one of the resulting systems. One of such controllers will be responsible for the robot position and the other for the leading angle, using reference signals generated by the position controller. To validate the proposed structure, some simulated and experimental results using differential drive mobile robots of a robot soccer kit are presented. The simulator uses the main characteristics of real physical system as noise and non-linearities such as deadzone and saturation. The experimental results were obtained through an C++ program applied to the robot soccer kit of Microrobot team at the LACI/UFRN. The simulated and experimental results are presented and discussed at the end of the text

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Cellulose was extracted from lignocellulosic fibers and nanocrystalline cellulose (NC) prepared by alkali treatment of the fiber, steam explosion of the mercerized fiber, bleaching of the steam exploded fiber and finally acid treatment by 5% oxalic acid followed again by steam explosion. The average length and diameter of the NC were between 200-250 nm and 4-5 nm, respectively, in a monodisperse distribution. Different concentrations of the NC (0.1, 0.5, 1.0, 1.5, 2.0 and 2.5% by weight) were dispersed non-covalently into a completely bio-based thermoplastic polyurethane (TPU) derived entirely from oleic acid. The physical properties of the TPU nanocomposites were assessed by Fourier Transform Infra-Red spectroscopy (FTIR), Thermo-Gravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), X-Ray Diffraction (XRD), Dynamic Mechanical Analysis (DMA) and Mechanical Properties Analysis. The nanocomposites demonstrated enhanced stress and elongation at break and improved thermal stability compared to the neat TPU. The best results were obtained with 0.5% of NC in the TPU. The elongation at break of this sample was improved from 178% to 269% and its stress at break from 29.3 to 40.5 MPa. In this and all other samples the glass transition temperature, melting temperature and crystallization behavior were essentially unaffected. This finding suggests a potential method of increasing the strength and the elongation at break of typically brittle and weak lipid-based TPUs without alteration of the other physico-chemical properties of the polymer. (C) 2012 Elsevier Ltd. All rights reserved.

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The main goal of this work was to produce nanosized ceramic materials of the family of the tungstates (tungstates of cerium and strontium), and test them for their catalytic activity in processes involving the transformation of methane (CH4). The methodology used for the synthesis of the ceramic powders involved the complexation combining EDTA-citrate. The materials characterization was performed using simple and differential thermogravimetry, x-ray diffraction, transmission electron microscopy, and energy dispersive spectroscopy (EDS). The microstructure analysis was performed using the refinement by the Rietveld method, and the crystallite size and distribution of the materials was elucidate by the Scherrer and Williamson-Hall methods. The conditions of the synthesis process for the three envisaged materials (SrWO4, SrWO4 using tungsten oxide concentrate as raw material, and Ce2(WO4)3) were adjusted to obtain a single phase crystalline material. The catalytic tests were carried out in the presence of methane and synthetic air, which is composed of 21% O2 and 79% N2. The analysis of the conversion of the reaction was done with the aid of an fourier transform infrared device (FTIR). The analysis showed that, structurally, the SrWO4 produced using raw materials of high and poor purity (99% and 92%, respectively) are similar. The ideal parameters of calcination, in the tested range, are temperature of 1000 °C and time of calcination 5 hours. For the Ce2(WO4)3, the ideal calcination time and are temperature 15 hours and 1000°C, respectively. The Williamson-Hall method provided two different distributions for the crystallite size of each material, whose values ranged between the nanometer and micrometer scales. According to method of Scherrer, all materials produced were composed of nanometric crystallites. The analyses of transmission electron microscopy confirmed the results obtained from the Williamson- Hall method for the crystallite size. The EDS showed an atomic composition for the metals in the SrWO4 that was different of the theoretical composition. With respect to the catalytic tests, all materials were found to be catalytically active, but the reaction process should be further studied and optimized.