242 resultados para Interpolation variance


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The common practice of reconciliation is based on definition of the mine call factor (MCF) and its application to resource or grade control estimates. The MCF expresses the difference, a ratio or percentage, between the predicted grade and the grade reported by the plant. Therefore, its application allows to correct future estimates. This practice is named reactive reconciliation. However the use of generic factors that are applied across differing time scales and material types often disguises the causes of the error responsible for the discrepancy. The root causes of any given variance can only be identified by analyzing the information behind any variance and, then, making changes to methodologies and processes. This practice is named prognostication, or proactive reconciliation, an iterative process resulting in constant recalibration of the inputs and the calculations. The prognostication allows personnel to adjust processes so that results align within acceptable tolerance ranges, and not only to correct model estimates. This study analyses the reconciliation practices performed at a gold mine in Brazil and suggests a new sampling protocol, based on prognostication concepts.

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Sensors and actuators based on piezoelectric plates have shown increasing demand in the field of smart structures, including the development of actuators for cooling and fluid-pumping applications and transducers for novel energy-harvesting devices. This project involves the development of a topology optimization formulation for dynamic design of piezoelectric laminated plates aiming at piezoelectric sensors, actuators and energy-harvesting applications. It distributes piezoelectric material over a metallic plate in order to achieve a desired dynamic behavior with specified resonance frequencies, modes, and enhanced electromechanical coupling factor (EMCC). The finite element employs a piezoelectric plate based on the MITC formulation, which is reliable, efficient and avoids the shear locking problem. The topology optimization formulation is based on the PEMAP-P model combined with the RAMP model, where the design variables are the pseudo-densities that describe the amount of piezoelectric material at each finite element and its polarization sign. The design problem formulated aims at designing simultaneously an eigenshape, i.e., maximizing and minimizing vibration amplitudes at certain points of the structure in a given eigenmode, while tuning the eigenvalue to a desired value and also maximizing its EMCC, so that the energy conversion is maximized for that mode. The optimization problem is solved by using sequential linear programming. Through this formulation, a design with enhancing energy conversion in the low-frequency spectrum is obtained, by minimizing a set of first eigenvalues, enhancing their corresponding eigenshapes while maximizing their EMCCs, which can be considered an approach to the design of energy-harvesting devices. The implementation of the topology optimization algorithm and some results are presented to illustrate the method.

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Micro-tools offer significant promise in a wide range of applications Such as cell Manipulation, microsurgery, and micro/nanotechnology processes. Such special micro-tools consist of multi-flexible structures actuated by two or more piezoceramic devices that must generate output displacements and forces lit different specified points of the domain and at different directions. The micro-tool Structure acts as a mechanical transformer by amplifying and changing the direction of the piezoceramics Output displacements. The design of these micro-tools involves minimization of the coupling among movements generated by various piezoceramics. To obtain enhanced micro-tool performance, the concept of multifunctional and functionally graded materials is extended by, tailoring elastic and piezoelectric properties Of the piezoceramics while simultaneously optimizing the multi-flexible structural configuration using multiphysics topology optimization. The design process considers the influence of piezoceramic property gradation and also its polarization sign. The method is implemented considering continuum material distribution with special interpolation of fictitious densities in the design domain. As examples, designs of a single piezoactuator, an XY nano-positioner actuated by two graded piezoceramics, and a micro-gripper actuated by three graded piezoceramics are considered. The results show that material gradation plays an important role to improve actuator performance, which may also lead to optimal displacements and coupling ratios with reduced amount of piezoelectric material. The present examples are limited to two-dimensional models because many of the applications for Such micro-tools are planar devices. Copyright (c) 2008 John Wiley & Sons, Ltd.

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In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

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In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. (C) 2010 Elsevier B.V. All rights reserved.

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Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

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We define a new type of self-similarity for one-parameter families of stochastic processes, which applies to certain important families of processes that are not self-similar in the conventional sense. This includes Hougaard Levy processes such as the Poisson processes, Brownian motions with drift and the inverse Gaussian processes, and some new fractional Hougaard motions defined as moving averages of Hougaard Levy process. Such families have many properties in common with ordinary self-similar processes, including the form of their covariance functions, and the fact that they appear as limits in a Lamperti-type limit theorem for families of stochastic processes.

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Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

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Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

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Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

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Mahogany trees, Swietenia macrophylla, occur in open rainforest, semi deciduous and deciduous and dense rainforest of Peruvian Amazonian tropical forest. They occur, preferentially, in areas with a defined dry season, with typical phenology and seasonal variation activity, forming distinct tree-rings. The present work had as aim to determine the wood density radial variation of 14 mahogany trees, of two populations of the Peruvian Amazonian tropical forest, through the X-ray densitometry and to evaluate their application as methodology, compared to the classic method of measurement table, for the determination of the treering width. The radial wood apparent density of the trees profiles rendered it possible to delimit the areas of juvenile-adult wood and of the heartwood-sapwood, relative to the anatomical structure and chemical composition differences, due to the extractives and the vessels obstruction by tyloses. The mean, minimum and maximum wood apparent density of the mahogany trees for the Populations A and B were of 0.70; 0.29; 1.01 g.cm(-3) and 0.81; 0.29; 1.19 g.cm(-3), respectively. The analysis of the variance and mean test indicate differences of mean wood density among the mahogany trees of each population, probably due to the age of the trees. There was no correlation between mean wood density of mahogany trees among the two populations, as well as, between the tree-ring width and the respective mean density. The X-ray densitometry technique is an important tool in the evaluation of the radial variation of wood apparent density and the delimitation of tree-ring boundaries, with correlations of 0.94 and 0.93 in relation to measurement table, for each sampled population.

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Maize breeding programmes in Brazil and elsewhere seek reliable methods to identify genotypes resistant to Phaeosphaeria leaf spot. The area under the disease progress curve (AUDPC) is an accurate method to evaluate the severity of foliar diseases. However, at least three data points are required to calculate the AUDPC, which is unfeasible when there are thousands of genotypes to be assessed. The aim of this work was to estimate the heritability of disease resistance, evaluate disease severity at different times using a nine-point scale in comparison to the AUDPC, and establish the most suitable phenological period for disease assessment. A repeated experiment was conducted in a 11 x 11 lattice experimental design with three replications. Disease assessments were carried out at flowering, 15 and 30 days post-anthesis for the parental lines DS95, DAS21, the F1 generation and 118 F2:3 progenies. Then, the AUDPC was obtained and results compared with the single-point evaluations used to calculate it. Individual and joint analyses of variance were conducted to obtain heritabiliy estimates. The assessments performed after the flowering stage gave higher estimates of heritability and correlation with AUDPC. We concluded that one assessment between the 15th and 30th day after flowering could provide enough information to distinguish maize genotypes for their resistance to Phaeosphaeria leaf spot under tropical conditions.

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Maize (Zea mays L.) is a very important cereal to world-wide economy which is also true for Brazil, particularly in the South region. Grain yield and plant height have been chosen as important criteria by breeders and farmers from Santa Catarina State (SC), Brazil. The objective of this work was to estimate genetic-statistic parameters associated with genetic gain for grain yield and plant height, in the first cycle of convergent-divergent half-sib selection in a maize population (MPA1) cultivated by farmers within the municipality of Anchieta (SC). Three experiments were carried out in different small farms at Anchieta using low external agronomic inputs; each experiment represented independent samples of half-sib families, which were evaluated in randomized complete blocks with three replications per location. Significant differences among half-sib families were observed for both variables in all experiments. The expected responses to truncated selection of the 25% better families in each experiment were 5.1, 5.8 and 5.2% for reducing plant height and 3.9, 5.7 and 5.0% for increasing grain yield, respectively. The magnitudes of genetic-statistic parameters estimated evidenced that the composite population MPA1 exhibits enough genetic variability to be used in cyclical process of recurrent selection. There were evidences that the genetic structure of the base population MPA1, as indicated by its genetic variability, may lead to expressive changes in the traits under selection, even under low selection pressure.

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The diversity of endophytic filamentous fungi from leaves of transgenic imidazolinone-tolerant sugarcane plants and its isoline was evaluated by cultivation followed by amplified rDNA restriction analysis (ARDRA) of randomly selected strains. Transgenic and non-transgenic cultivars and their crop management (herbicide application or manual weed control) were used to assess the possible non-target effects of genetically modified sugarcane on the fungal endophytic community. A total of 14 ARDRA haplotypes were identified in the endophytic community of sugarcane. Internal transcribed spacer (ITS) sequencing revealed a rich community represented by 12 different families from the Ascomycota phylum. Some isolates had a high sequence similarity with genera that are common endophytes in tropical climates, such as Cladosporium, Epicoccum, Fusarium, Guignardia, Pestalotiopsis and Xylaria. Analysis of molecular variance indicated that fluctuations in fungal population were related to both transgenic plants and herbicide application. While herbicide applications quickly induced transient changes in the fungal community, transgenic plants induced slower changes that were maintained over time. These results represent the first draft on composition of endophytic filamentous fungi associated with sugarcane plants. They are an important step in understanding the possible effects of transgenic plants and their crop management on the fungal endophytic community.

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Phaeosphaeria leaf spot (PLS) is an important disease in tropical and subtropical maize (Zea mays, L.) growing areas, but there is limited information on its inheritance. Thus, this research was conducted to study the inheritance of the PLS disease in tropical maize by using QTL mapping and to assess the feasibility of using marker-assisted selection aimed to develop genotypes resistance to this disease. Highly susceptible L14-04B and highly resistant L08-05F inbred lines were crossed to develop an F(2) population. Two-hundred and fifty six F(2) plants were genotyped with 143 microsatellite markers and their F(2:3) progenies were evaluated at seven environments. Ten plants per plot were evaluated 30 days after silk emergence following a rating scale, and the plot means were used for analyses. The heritability coefficient on a progeny mean basis was high (91.37%), and six QTL were mapped, with one QTL on chromosomes 1, 3, 4, and 6, and two QTL on chromosome 8. The gene action of the QTL ranged from additive to partial dominance, and the average level of dominance was partial dominance; also a dominance x dominance epistatic effect was detected between the QTL mapped on chromosome 8. The phenotypic variance explained by each QTL ranged from 2.91 to 11.86%, and the joint QTL effects explained 41.62% of the phenotypic variance. The alleles conditioning resistance to PLS disease of all mapped QTL were in the resistant parental inbred L08-05F. Thus, these alleles could be transferred to other elite maize inbreds by marker-assisted backcross selection to develop hybrids resistant to PLS disease.