958 resultados para Dunkl Transform


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Aims. We investigate the time-varying patterns in line profiles, V/R, and radial velocity of the Be star HD 173948 (lambda Pavonis). Methods. Time series analyses of radial velocity, V/R, and line profiles of He I, Fe II, and Si II were performed with the Cleanest algorithm. An estimate of the stellar rotation frequency was derived from the stellar mass and radius in the Roche limit by adopting an aspect angle i derived from the fittings of non-LTE model spectra affected by rotation. The projected rotation velocity, necessary as input for the spectral synthesis procedure, was evaluated from the Fourier transform of the rotation profiles of all neutral helium lines in the optical range. Results. Emission episodes in Balmer and He i lines, as well as V/R cyclic variations, are reported for spectra observed in year 1999, followed by a relatively quiescent phase (2000) and then again a new active epoch (2001). From time series analyses of line profiles, radial velocities, and V/R ratios, four signals with high confidence levels are detected: nu(1) = 0.17 +/- 0.02, nu(2) = 0.49 +/- 0.05, nu(3) = 0.82 +/- 0.03, and nu(4) = 1.63 +/- 0.04 c/d. We interpret nu 4 as a non-radial pulsation g-mode, nu 3 as a signal related to the orbital timescale of ejected material, which is near the theoretical rotation frequency 0.81 c/d inferred from the fitting of the models taken into account for gravity darkening. The signals nu(1) and nu(2) are viewed as aliases of nu(3) and nu(4).

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Crystal structure of compositionally homogeneous, nanocrystalline ZrO2-CeO2 solutions was investigated by X-ray powder diffraction as a function of temperature for compositions between 50 and 65 mol % CeO2 center dot ZrO2-50 and 60 mol % CeO2 solid solutions, which exhibit the t'-form of the tetragonal phase at room temperature, transform into the cubic phase in two steps: t'-to-t '' followed by t ''-to-cubic. But the ZrO2-65 mol % CeO2, which exhibits the t ''-form, transforms directly to the cubic phase. The results suggest that t'-to-t '' transition is of first order, but t ''-to-cubic seems to be of second order. (C) 2008 International Centre for Diffraction Data.

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A new target station providing Fourier transform infrared (FT-IR) spectroscopy and residual gas analysis (RGA) for in situ observation of ion-induced changes in polymers has been installed at the GSI Helmholtz Centre for Heavy Ion Research. The installations as well as first in situ measurements at room temperature are presented here. A foil of polyimide Kapton HN (R) was irradiated with 1.1 GeV Au ions. During irradiation several in situ FT-IR spectra were recorded. Simultaneously outgassing degradation products were detected with the RGA. In the IR spectra nearly all bands decrease due to the degradation of the molecular structure. In the region from 3000 to 2700 cm(-1) vibration bands of saturated hydrocarbons not reported in literature so far became visible. The outgassing experiments show a mixture of C(2)H(4), CO, and N(2) as the main outgassing components of polyimide. The ability to combine both analytical methods and the opportunity to measure a whole fluence series within a single experiment show the efficiency of the new setup. (C) 2011 American Institute of Physics. [doi:10.1063/1.3571301]

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We study rf spectroscopy of a lithium gas with the goal to explore the possibilities for photoemission spectroscopy of a strongly interacting p-wave Fermi gas. Radio-frequency spectra of quasibound p-wave molecules and of free atoms in the vicinity of the p-wave Feshbach resonance located at 159.15G are presented. The spectra are free of detrimental final-state effects. The observed relative magnetic-field shifts of the molecular and atomic resonances confirm earlier measurements realized with direct rf association. Furthermore, evidence of molecule production by adiabatically ramping the magnetic field is observed. Finally, we propose the use of a one-dimensional optical lattice to study anisotropic superfluid gaps as most direct proof of p-wave superfluidity.

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The combination of metallic phthalocyanines (MPcs) and biomolecules has been explored in the literature either as mimetic systems to investigate molecular interactions or as supporting layers to immobilize biomolecules. Here, Langmuir-Blodgett (LB) films containing the phospholipid dimyristoyl phosphatidic acid (DMPA) mixed either with iron phthalocyanine (FePc) or with lutetium bisphthalocyanine (LuPc(2)) were applied as ITO modified-electrodes in the detection of catechol using cyclic voltammetry. The mixed Langmuir films of FePc + DMPA and LuPc(2) + DMPA displayed surface-pressure isotherms with no evidence of molecular-level interactions. The Fourier Transform Infrared (FTIR) spectra of the multilayer LB films confirmed the lack of interaction between the components. The DMPA and the FePc molecules were found to be oriented perpendicularly to the substrate, while LuPc(2) molecules were randomly organized. The phospholipid matrix induced a remarkable electrocatalytic effect on the phthalocyanines; as a result the mixed LB films deposited on ITO could be used to detect catechol with detection limits of 4.30 x 10(-7) and 3.34 x 10(-7) M for FePc + DMPA and LuPc(2) + DMPA, respectively. Results from kinetics experiments revealed that ion diffusion dominated the response of the modified electrodes. The sensitivity was comparable to that of other non-enzymatic sensors, which is sufficient to detect catechol in the food industry. The higher stability of the electrochemical response of the LB films and the ability to control the molecular architecture are promising for further studies with incorporation of biomolecules.

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Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

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Ethanol oxidation has been studied on stepped platinum single crystal electrodes in acid media using electrochemical and Fourier transform infrared (FTIR) techniques. The electrodes used belong to two different series of stepped surfaces: those having (111) terraces with (100) monoatomic steps and those with (111) terraces with (110) monoatomic steps. The behaviors of the two series of stepped surfaces for the oxidation of ethanol are very different. On the one hand, the presence of (100) steps on the (111) terraces provides no significant enhancement of the activity of the surfaces. On the other hand, (110) steps have a double effect on the ethanol oxidation reaction. At potentials below 0.7 V, the step catalyzes the C-C bond cleavage and also the oxidation of the adsorbed CO species formed. At higher potentials, the step is not only able to break the C-C bond, but also to catalyze the oxidation of ethanol to acetic acid and acetaldehyde. The highest catalytic activity from voltammetry for ethanol oxidation was obtained with the Pt(554) electrode.

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Organosolv lignins can replace petroleum chemicals such as phenol either partially or totally in various applications. Eight lignins, seven of which corresponded to the ethanol-water fractionation of bagasse and the other to a reference lignin (Alcell (R)) were analyzed with the aim to evaluate their chemical and physicochemical characteristics. The purity of the lignin fractions was determined by high pressure liquid chromatography (HPLC) and by ash content. Fourier Transform-Infrared Spectroscopy (FTIR) techniques and differential UV spectroscopy were applied to identify the chemical groups in the lignin samples. The molecular weight distribution was determined by size exclusion chromatography (HPSEC). Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) techniques were used to determine the mass loss due to the high temperature treatment. The lignins studied showed the presence of p-hydroxyphenyl (H unit) and a greater proportion of guaiacyl (G unit) moieties, lower purity, similar or greater amount of phenolic hydroxyl groups, and higher degradation temperatures, than the Alcell (R) lignin.

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Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.

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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

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The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual minority game (MG) models do not exhibit multifractality, we study here one of its variants that does. We show that the nonsynchronous MG models in the nonergodic phase is multifractal and in this sense, together with other stylized facts, constitute a better modeling tool. Using the structure function (SF) approach we detected the stationary and the scaling range of the time series generated by the MG model and, from the linear (non-linear) behavior of the SF we identified the fractal (multifractal) regimes. Finally, using the wavelet transform modulus maxima (WTMM) technique we obtained its multifractal spectrum width for different dynamical regimes. (C) 2009 Elsevier Ltd. All rights reserved.

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The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

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A high cost-effective treatment of sulphochromic waste is proposed employing a raw coconut coir as biosorbent for Cr(VI) removal. The ideal pH and sorption kinetic, sorption capacities, and sorption sites were the studied biosorbent parameters. After testing five different isotherm models with standard solutions, Redlich-Peterson and Toth best fitted the experimental data, obtaining a theoretical Cr(VI) sorption capacity (SC) of 6.3 mg g(-1). Acid-base potentiometric titration indicated around of 73% of sorption sites were from phenolic compounds, probably lignin. Differences between sorption sites in the coconut coir before and after Cr adsorption identified from Fourier transform infrared spectra suggested a modification of sorption sites after sulphochromic waste treatment, indicating that the sorption mechanism involves organic matter oxidation and chromium uptake. For sulphocromic waste treatment, the SC was improved to 26.8 +/- 0.2 mg g(-1), and no adsorbed Cr(VI) was reduced, remaining only Cr(III) in the final solution. The adsorbed material was calcinated to obtain Cr2O3, with a reduction of more than 60% of the original mass. (c) 2008 Elsevier B.V. All rights reserved.

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The effects of alkaline treatments of the wheat straw with sodium hydroxide were investigated. The optimal condition for extraction of hemicelluloses was found to be with 0.50 mol/l sodium hydroxide at 55C for 2 h. This resulted in the release of 17.3% of hemicellulose (% dry starting material), corresponding to the dissolution of 49.3% of the original hemicellulose. The yields were determined by gravimetric analysis and expressed as a proportion of the starting material. Chemical composition and physico-chemical properties of the samples of hemicelluloses were elucidated by a combination of sugar analyses, Fourier transform infrared (FTIR), and thermal analysis. The results showed that the treatments were very effective on the extraction of hemicelluloses from wheat straw and that the extraction intensity (expressed in terms of alkali concentration) had a great influence on the yield and chemical features of the hemicelluloses. The FTIR analysis revealed typical signal pattern for the hemicellulosic fraction in the 1,200-1,000 cm(-1) region. Bands between 1,166 and 1,000 cm(-1) are typical of xylans.

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Hydrous niobium oxide (Nb(2)O(5)center dot nH(2)O) nanoparticles had been Successfully prepared by water-in-oil microemulsion. They were characterized by X-ray diffraction (XRD), thermal analysis (TG/DTG), Fourier transform infrared spectroscopy (FTIR), BET surface area measurement, transmission electron microscopy (TEM), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The results showed that the nanoparticle was exactly Nb(2)O(5)center dot nH(2)O with spherical shape. Their BET surface area was 60 m(2) g(-1). XRD results showed that Nb(2)O(5)center dot nH(2)O nanoparticles with crystallite size in nanometer scale were formed. The crystallinity and crystallity size increased with increasing annealing temperature. TT-phase of Nb(2)O(5) was obtained when the sample is annealed at 550 degrees C. (C) 2009 Elsevier B.V. All rights reserved.