989 resultados para Linear features


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Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally. the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-t, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study. (C) 2009 Elsevier B.V. All rights reserved.

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This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

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The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.

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The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

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The accurate identification of features of dynamical grounding systems are extremely important to define the operational safety and proper functioning of electric power systems. Several experimental tests and theoretical investigations have been carried out to obtain characteristics and parameters associated with the technique of grounding. The grounding system involves a lot of non-linear parameters. This paper describes a novel approach for mapping characteristics of dynamical grounding systems using artificial neural networks. The network acts as identifier of structural features of the grounding processes. So that output parameters can be estimated and generalized from an input parameter set. The results obtained by the network are compared with other approaches also used to model grounding systems.

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We consider a one-dimensional mean-field-hydrodynamic model of a two-component degenerate Fermi gas in an external trap, each component representing a spin state of the same atom. We demonstrate that the interconversion between them (linear coupling), imposed by a resonant electromagnetic wave, transforms the immiscible binary gas into a miscible state, if the coupling constant, kappa, exceeds a critical value, kappa(cr). The effect is predicted in a variational approximation, and confirmed by numerical solutions. Unlike the recently studied model of a binary Bose-Einsten condensate with the linear coupling, the components in the immiscible phase of the binary fermion mixture never fill two separated domains with a wall between them, but rather form antilocked (pi-phase-shifted) density waves. Another difference from the bosonic mixture is spontaneous breaking of symmetry between the two components in terms of the numbers of atoms in them, N(1) and N(2). The latter effect is characterized by the parameter nu equivalent to(N(1)-N(2))/(N(1)+N(2)) (only N(1)+N(2) is a conserved quantity), the onset of miscibility at kappa >=kappa(cr) meaning a transition to nu equivalent to 0. At kappa features damped oscillations as a function of kappa. We also briefly consider an asymmetric model, with a chemical-potential difference between the two components. The relation between the imbalance in the spin population, induced by the linear coupling, and the developing spatial structure resembles the known Larkin-Ovchinnikov-Fulde-Ferrell states in the Fermi mixture. Dynamical states, when kappa is suddenly switched from zero to a value exceeding kappa(cr), are considered too. In the latter case, the system features oscillatory relaxation to the mixed state.

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A novel peptide, decoralin, was isolated from the venom of the solitary eumenine wasp Oreumenes decoratus. its sequence, Ser-Leu-Leu-Ser-Leu-Ile-Arg-Lys-Leu-Ile-Thr, was determined by Edman degradation and corroborated by solid-phase synthesis. This sequence has the characteristic features of linear cationic a-helical peptides; rich in hydrophobic and basic amino acids with no disulfide bond, and accordingly, it can be predicted to adopt an amphipathic a-helix secondary structure. In fact, the CD spectra of decoralin in the presence of TFE or SDS showed a high a-helical conformation content. In a biological evaluation, decoralin exhibited a significant broad-spectrum antimicrobial activity, and moderate mast cell degranulation and leishmanicidal activities, but showed virtually no hemolytic activity. A synthetic analog with C-terminal amidation showed a much more potent activity in all the biological assays. (c) 2007 Elsevier B.V. All rights reserved.

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Different (Sn,Ti)O2 compositions were sintered at 1450 °C for 2 h with the purpose of investigating their sintering and mass transport properties. Highly dense ceramics were obtained and their structural properties studied by X-ray diffraction and scanning electron microscopy. The changes in lattice parameters were analyzed by the Rietveld method and two mass transport mechanisms were observed during sintering in different temperature ranges, evidenced by the linear shrinkage rate as a function of temperature. The effect of the concentration of TiO2 on mass transport and densiffication during sintering was analyzed by considering the intrinsic defects. System densiffication was attributed to a mass transport mechanism in the SnO2 matrix, caused by the presence of TiO2, which formed a solid solution phase. The change in the mass transport mechanism was attributed to chemical bonding between SnO2 and TiO2, which improves ionic difusion as the concentration of TiO2 increased in (Sn,Ti)O2 compositions. © 2002 Elsevier Science Ltd. All rights reserved.

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Objective. Juvenile localized scleroderma (JLS) includes a number of conditions often grouped together. With the long-term goal of developing uniform classification criteria, we studied the epidemiological, clinical and immunological features of children with JLS followed by paediatric rheumatology and dermatology centres. Methods. A large, multicentre, multinational study was conducted by collecting information on the demographics, family history, triggering environmental factors, clinical and laboratory features, and treatment of patients with JLS. Results. Seven hundred and fifty patients with JLS from 70 centres were enrolled into the study. The disease duration at diagnosis was 18 months. Linear scleroderma (LS) was the most frequent subtype (65%), followed by plaque morphea (PM) (26%), generalized morphea (GM) (7%) and deep morphea (DM) (2%). As many as 15% of patients had a mixed subtype. Ninety-one patients (12%) had a positive family history for rheumatic or autoimmune diseases; 100 (13.3%) reported environmental events as possible trigger. ANA was positive in 42.3% of the patients, with a higher prevalence in the LS-DM subtype than in the PM-GM subtype. Scl70 was detected in the sera of 3% of the patients, anticentromere antibody in 2%, anti-double-stranded DNA in 4%, anti-cardiolipin antibody in 13% and rheumatoid factor in 16%. Methotrexate was the drug most frequently used, especially during the last 5 yr. Conclusion. This study represents the largest collection of patients with JLS ever reported. The insidious onset of the disease, the delay in diagnosis, the recognition of mixed subtype and the better definition of the other subtypes should influence our efforts in educating trainees and practitioners and help in developing a comprehensive classification system for this syndrome. © 2006 Oxford University Press.

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The edges detection model by a non-linear anisotropic diffusion, consists in a mathematical model of smoothing based in Partial Differential Equation (PDE), alternative to the conventional low-pass filters. The smoothing model consists in a selective process, where homogeneous areas of the image are smoothed intensely in agreement with the temporal evolution applied to the model. The level of smoothing is related with the amount of undesired information contained in the image, i.e., the model is directly related with the optimal level of smoothing, eliminating the undesired information and keeping selectively the interest features for Cartography area. The model is primordial for cartographic applications, its function is to realize the image preprocessing without losing edges and other important details on the image, mainly airports tracks and paved roads. Experiments carried out with digital images showed that the methodology allows to obtain the features, e.g. airports tracks, with efficiency.

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The recent years have seen the appearance of innovative system for acoustic and vibration attenuation, most of them integrating new actuator technologies. In this sense, the study of algorithms for active vibrations control in rotating machinery became an area of enormous interest, mainly due to countless demands of an optimal performance of mechanical systems in aircraft, aerospace and automotive structures. In this way, this paper presents an approach that is numerically verified for active vibration control in a rotor using Active Magnetic Bearings (AMB). The control design in a discrete state-space formulation is carried out through feedback technique and Linear Matrix Inequalities (LMI) approach. LMI is useful for system with uncertainties. The AMB uses electromagnetic forces to support a rotor without mechanical contact. By monitoring the position of the shaft and changing the dynamics of the system accordingly, the AMB keeps the rotor in a desired position. This unique feature has broadened for the applications of AMB and now they can be considered not only as a main support bearing in a machine but also as dampers for vibration control and force actuators. © 2009 Society for Experimental Mechanics Inc.

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This work describes a method to determine Cu at wide range concentrations in a single run without need of further dilutions employing high-resolution continuum source flame atomic absorption spectrometry. Different atomic lines for Cu at 324. 754 nm, 327. 396 nm, 222. 570 nm, 249. 215 nm and 224. 426 nm were evaluated and main figures of merit established. Absorbance measurements at 324. 754 nm, 249. 215 nm and 224. 426 nm allows the determination of Cu in the 0. 07-5. 0 mg L -1, 5. 0-100 mg L -1 and 100-800 mg L -1 concentration intervals respectively with linear correlation coefficients better than 0. 998. Limits of detection were 21 μg L -1, 310 μg L -1 and 1400 μg L -1 for 324. 754 nm, 249. 215 nm and 224. 426 nm, respectively and relative standard deviations (n = 12) were ≤ 2. 7%. The proposed method was applied to water samples spiked with Cu and the results were in agreement at a 95% of confidence level (paired t-test) with those obtained by line-source flame atomic absorption spectrometry.

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Four novel peptides were isolated from the venoms of the solitary eumenine wasps Eumenes rubrofemoratus and Eumenes fraterculus. Their sequences were determined by MALDI-TOF/TOF (matrix assisted laser desorption/ionization time-of-flight mass spectrometry) analysis, Edman degradation and solid-phase synthesis. Two of them, eumenitin-R (LNLKGLIKKVASLLN) and eumenitin-F (LNLKGLFKKVASLLT), are highly homologous to eumenitin, an antimicrobial peptide from a solitary eumenine wasp, whereas the other two, EMP-ER (FDIMGLIKKVAGAL-NH 2) and EMP-EF (FDVMGIIKKIAGAL-NH 2), are similar to eumenine mastoparan-AF (EMP-AF), a mast cell degranulating peptide from a solitary eumenine wasp. These sequences have the characteristic features of linear cationic cytolytic peptides; rich in hydrophobic and basic amino acids with no disulfide bond, and accordingly, they can be predicted to adopt an amphipathic α-helix secondary structure. In fact, the CD (circular dichroism) spectra of these peptides showed significant α-helical conformation content in the presence of TFE (trifluoroethanol), SDS (sodium dodecylsulfate) and asolectin vesicles. In the biological evaluation, all the peptides exhibited a significant broad-spectrum antimicrobial activity, and moderate mast cell degranulation and leishmanicidal activities, but showed virtually no hemolytic activity. © 2011 Elsevier Ltd.

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Calcium copper titanate, CaCu3Ti4O12, CCTO, thin films with polycrystalline nature have been deposited by RF sputtering on Pt/Ti/SiO2/Si (100) substrates at a room temperature followed by annealing at 600 °C for 2 h in a conventional furnace. The CCTO thin film present a cubic structure with lattice parameter a = 7.379 ±0.001 Å free of secondary phases. The observed electrical features of CCTO thin films are highly dependent on the [CaO12], [CaO 4], [CuO11], [CuO11Vx 0] and [TiO5.VO] clusters. The CCTO film capacitor showed a dielectric loss of 0.40 and a dielectric permittivity of 70 at 1 kHz. The J-V behavior is completely symmetrical, regardless of whether the conduction is limited by interfacial barriers or by bulk-like mechanisms. © 2013 Elsevier B.V. All rights reserved.

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