206 resultados para binary mixture


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Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

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Context. Unevolved metal-poor stars constitute a fossil record of the early Galaxy, and can provide invaluable information on the properties of the first generations of stars. Binary systems also provide direct information on the stellar masses of their member stars. Aims. The purpose of this investigation is a detailed abundance study of the double-lined spectroscopic binary CS 22876-032, which comprises the two most metal-poor dwarfs known. Methods. We used high-resolution, high-S/N ratio spectra from the UVES spectrograph at the ESO VLT telescope. Long-term radial-velocity measurements and broad-band photometry allowed us to determine improved orbital elements and stellar parameters for both components. We used OSMARCS 1D models and the TURBOSPECTRUM spectral synthesis code to determine the abundances of Li, O, Na, Mg, Al, Si, Ca, Sc, Ti, Cr, Mn, Fe, Co and Ni. We also used the (COBOLD)-B-5 model atmosphere code to compute the 3D abundance corrections, notably for Li and O. Results. We find a metallicity of [Fe/H] similar to -3.6 for both stars, using 1D models with 3D corrections of similar to -0.1 dex from averaged 3D models. We determine the oxygen abundance from the near-UV OH bands; the 3D corrections are large, -1 and -1.5 dex for the secondary and primary respectively, and yield [O/Fe] similar to 0.8, close to the high-quality results obtained from the [OI] 630 nm line in metal-poor giants. Other [alpha/Fe] ratios are consistent with those measured in other dwarfs and giants with similar [Fe/H], although Ca and Si are somewhat low ([X/Fe] less than or similar to 0). Other element ratios follow those of other halo stars. The Li abundance of the primary star is consistent with the Spite plateau, but the secondary shows a lower abundance; 3D corrections are small. Conclusions. The Li abundance in the primary star supports the extension of the Spite Plateau value at the lowest metallicities, without any decrease. The low abundance in the secondary star could be explained by endogenic Li depletion, due to its cooler temperature. If this is not the case, another, yet unknown mechanism may be causing increased scatter in A( Li) at the lowest metallicities.

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Context. The star HD 87643, exhibiting the ""B[e] phenomenon"", has one of the most extreme infrared excesses for this object class. It harbours a large amount of both hot and cold dust, and is surrounded by an extended reflection nebula. Aims. One of our major goals was to investigate the presence of a companion in HD87643. In addition, the presence of close dusty material was tested through a combination of multi-wavelength high spatial resolution observations. Methods. We observed HD 87643 with high spatial resolution techniques, using the near-IR AMBER/VLTI interferometer with baselines ranging from 60 m to 130 m and the mid-IR MIDI/VLTI interferometer with baselines ranging from 25 m to 65 m. These observations are complemented by NACO/VLT adaptive-optics-corrected images in the K and L-bands, and ESO-2.2m optical Wide-Field Imager large-scale images in the B, V and R-bands. Results. We report the direct detection of a companion to HD 87643 by means of image synthesis using the AMBER/VLTI instrument. The presence of the companion is confirmed by the MIDI and NACO data, although with a lower confidence. The companion is separated by similar to 34 mas with a roughly north-south orientation. The period must be large (several tens of years) and hence the orbital parameters are not determined yet. Binarity with high eccentricity might be the key to interpreting the extreme characteristics of this system, namely a dusty circumstellar envelope around the primary, a compact dust nebulosity around the binary system and a complex extended nebula suggesting past violent ejections.

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Context. Tight binaries discovered in young, nearby associations are ideal targets for providing dynamical mass measurements to test the physics of evolutionary models at young ages and very low masses. Aims. We report the binarity of TWA22 for the first time. We aim at monitoring the orbit of this young and tight system to determine its total dynamical mass using an accurate distance determination. We also intend to characterize the physical properties (luminosity, effective temperature, and surface gravity) of each component based on near-infrared photometric and spectroscopic observations. Methods. We used the adaptive-optics assisted imager NACO to resolve the components, to monitor the complete orbit and to obtain the relative near-infrared photometry of TWA22 AB. The adaptive-optics assisted integral field spectrometer SINFONI was also used to obtain medium-resolution (R(lambda) = 1500-2000) spectra in JHK bands. Comparison with empirical and synthetic librairies were necessary for deriving the spectral type, the effective temperature, and the surface gravity for each component of the system. Results. Based on an accurate trigonometric distance (17.5 +/- 0.2 pc) determination, we infer a total dynamical mass of 220 +/- 21 M(Jup) for the system. From the complete set of spectra, we find an effective temperature T(eff) = 2900(-200)(+200) K for TWA22A and T(eff) = 2900(-100)(+200) for TWA22 B and surface gravities between 4.0 and 5.5 dex. From our photometry and an M6 +/- 1 spectral type for both components, we find luminosities of log(L/L(circle dot)) = -2.11 +/- 0.13 dex and log(L/L(circle dot)) = -2.30 +/- 0.16 dex for TWA22 A and B, respectively. By comparing these parameters with evolutionary models, we question the age and the multiplicity of this system. We also discuss a possible underestimation of the mass predicted by evolutionary models for young stars close to the substellar boundary.

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Context. There is growing evidence that a treatment of binarity amongst OB stars is essential for a full theory of stellar evolution. However the binary properties of massive stars - frequency, mass ratio & orbital separation - are still poorly constrained. Aims. In order to address this shortcoming we have undertaken a multiepoch spectroscopic study of the stellar population of the young massive cluster Westerlund 1. In this paper we present an investigation into the nature of the dusty Wolf-Rayet star and candidate binary W239. Methods. To accomplish this we have utilised our spectroscopic data in conjunction with multi-year optical and near-IR photometric observations in order to search for binary signatures. Comparison of these data to synthetic non-LTE model atmosphere spectra were used to derive the fundamental properties of the WC9 primary. Results. We found W239 to have an orbital period of only similar to 5.05 days, making it one of the most compact WC binaries yet identified. Analysis of the long term near-IR lightcurve reveals a significant flare between 2004-6. We interpret this as evidence for a third massive stellar component in the system in a long period (> 6 yr), eccentric orbit, with dust production occuring at periastron leading to the flare. The presence of a near-IR excess characteristic of hot (similar to 1300 K) dust at every epoch is consistent with the expectation that the subset of persistent dust forming WC stars are short (< 1 yr) period binaries, although confirmation will require further observations. Non-LTE model atmosphere analysis of the spectrum reveals the physical properties of the WC9 component to be fully consistent with other Galactic examples. Conclusions. The simultaneous presence of both short period Wolf-Rayet binaries and cool hypergiants within Wd 1 provides compelling evidence for a bifurcation in the post-Main Sequence evolution of massive stars due to binarity. Short period O+OB binaries will evolve directly to the Wolf-Rayet phase, either due to an episode of binary mediated mass loss - likely via case A mass transfer or a contact configuration - or via chemically homogenous evolution. Conversely, long period binaries and single stars will instead undergo a red loop across the HR diagram via a cool hypergiant phase. Future analysis of the full spectroscopic dataset for Wd 1 will constrain the proportion of massive stars experiencing each pathway; hence quantifying the importance of binarity in massive stellar evolution up to and beyond supernova and the resultant production of relativistic remnants.

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The properties of the localized states of a two-component Bose-Einstein condensate confined in a nonlinear periodic potential (nonlinear optical lattice) are investigated. We discuss the existence of different types of solitons and study their stability by means of analytical and numerical approaches. The symmetry properties of the localized states with respect to nonlinear optical lattices are also investigated. We show that nonlinear optical lattices allow the existence of bright soliton modes with equal symmetry in both components and bright localized modes of mixed symmetry type, as well as dark-bright bound states and bright modes on periodic backgrounds. In spite of the quasi-one-dimensional nature of the problem, the fundamental symmetric localized modes undergo a delocalizing transition when the strength of the nonlinear optical lattice is varied. This transition is associated with the existence of an unstable solution, which exhibits a shrinking (decaying) behavior for slightly overcritical (undercritical) variations in the number of atoms.

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Thermodiffusion in a lyotropic mixture of water and potassium laurate is investigated by means of an optical technique (Z scan) distinguishing the index variations due to the temperature gradient and the mass gradients. A phenomenological framework allowing for coupled diffusion is developed in order to analyze thermodiffusion in multicomponent systems. An observable parameter relating to the mass gradients is found to exhibit a sharp change around the critical micellar concentration, and thus may be used to detect it. The change in the slope is due to the markedly different values of the Soret coefficients of the surfactant and the micelles. The difference in the Soret coefficients is due to the fact that the micellization process reduces the energy of interaction of the ball of amphiphilic molecules with the solvent.

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The generation of a large recoil velocity from the inspiral and merger of binary black holes represents one of the most exciting results of numerical-relativity calculations. While many aspects of this process have been investigated and explained, the ""antikick,"" namely, the sudden deceleration after the merger, has not yet found a simple explanation. We show that the antikick can be understood in terms of the radiation from a deformed black hole where the anisotropic curvature distribution on the horizon correlates with the direction and intensity of the recoil. Our analysis is focused on Robinson-Trautman spacetimes and allows us to measure both the energies and momenta radiated in a gauge-invariant manner. At the same time, this simpler setup provides the qualitative and quantitative features of merging black holes, opening the way to a deeper understanding of the nonlinear dynamics of black-hole spacetimes.

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The effects of solvents on different chemical phenomena, including reactivity, spectroscopic data, and swelling of biopolymers can be rationalized by use of solvatochromic probes, substances whose UV-vis spectra, absorption, or emission are sensitive to the properties of the medium. Thermo-solvatochromism refers to the effect of temperature on solvatochromism. The study of both phenomena sheds light on the relative importance of the factors that contribute to solvation, namely, properties of the probe, those of the solvent (acidity, basicity, dipolarity/polarizability, and lipophilicity), and the temperature. Solvation in binary solvent mixtures is complex because of ""preferential solvation"" of the probe by some component of the mixture. A recently introduced solvent exchange model is based on the presence in the binary solvent mixture of the organic component (molecular solvent or ionic liquid), S, water, W, and a 1:1 hydrogen-bonded species (S-W). Solvation by the latter is more efficient than by its precursor solvents, due to probe-solvent hydrogen-bonding and hydrophobic interactions; dimethyl sulfoxide (DMSO)-W is an exception. Solvatochromic data are employed in order to explain apparently disconnected phenomena, namely, medium effect on the pH-independent hydrolysis of esters, (1)H NMR data of water-ionic liquid (IL) mixtures, and the swelling of cellulose.

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Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

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Milkfat-soybean oil blends were enzymatically interesterified (EIE) by Aspergillus niger lipase immobilized on SiO(2)-PVA hybrid composite in a solvent free system. An experimental mixture design was used to study the effects of binary blends of milkfat-soybean oil (MF:SBO) at different proportions (0:100; 25:75; 33:67; 50:50; 67:33; 75:25; 100:0) on the compositional and textural properties of the EIE products, considering, as response variables, the interesterification yield (IY), consistency and hardness. Lipase-catalysed interesterification reactions increased the relative proportion of TAGs` C(46)-C(52) and decreased the TAGs` C(40)-C(42) and C(54) concentrations. The highest IY was attained (10.8%) for EIE blend of MF:SBO 67:33 resulting in a more spreadable material at refrigerator temperature in comparison with butter, milkfat or non-interesterified (NIE) blend. In this case, consistency and hardness values were at least 32% lower than values measured for butter. Thus, using A. niger lipase immobilized on SiO(2)-PVA improves the textural properties of milkfat and has potential for development of a product incorporating unsaturated and essential fatty acids from soybean oil. (C) 2010 Elsevier Ltd. All rights reserved.

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CoB, CO(2)B, CoSi, Co(2)Si and CO(5)Si(2)B phases can be formed during heat-treatment of amorphous co-Si-B soft magnetic materials. Thus, it is important to determine their magnetic behavior as a function of applied field and temperature. In this study, polycrystalline single-phase samples of the above phases were produced via arc melting and heat-treatment under argon. The single-phase nature of the samples was confirmed via X-ray diffraction experiments. AC and DC magnetization measurements showed that Co(2)Si and CO(5)Si(2)B phases are paramagnetic. Minor amounts of either Co(2)Si or CoSi(2) in the CoSi-phase sample suggested a paramagnetic behavior of the CoSi-phase, however, it should be diamagnetic as shown in the literature. The diamagnetic behavior of the CoB phase was also confirmed. The paramagnetic behavior of CO(5)Si(2)B is for the first time reported. The magnetization results of the phase CO(2)B have a ferromagnetic signature already verified on previous NMR studies. A detailed set of magnetization measurements of this phase showed a change of the easy magnetization axis starting at 70K, with a temperature interval of about 13K at a very small field of 1 mT. As the strength of the field is increased the temperature interval is enlarged. The strength of field at which the magnetization saturates increases almost linearly as the temperature is increased above 70K. The room temperature total magnetostriction of the CO(2)B phase was determined to be 8 ppm at a field of 1T. (C) 2010 Elsevier B.V. All rights reserved.

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This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ways. The skeleton carries motion information about human joints, and the silhouette carries information about boundary motion of the human body. Moreover, binary and gray-level images contain different information about human movements. This work proposes to recover these different kinds of information to interpret the global motion of the human body based on four different segmented image models, using a fusion model to improve classification. Our proposed method considers the set of the segmented frames of each individual as a distinct class and each frame as an object of this class. The methodology applies background extraction using the Gaussian Mixture Model (GMM), a scale reduction based on the Wavelet Transform (WT) and feature extraction by Principal Component Analysis (PCA). We propose four new schemas for motion information capture: the Silhouette-Gray-Wavelet model (SGW) captures motion based on grey level variations; the Silhouette-Binary-Wavelet model (SBW) captures motion based on binary information; the Silhouette-Edge-Binary model (SEW) captures motion based on edge information and the Silhouette Skeleton Wavelet model (SSW) captures motion based on skeleton movement. The classification rates obtained separately from these four different models are then merged using a new proposed fusion technique. The results suggest excellent performance in terms of recognising people by their gait.

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This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contain only binary variables. Such networks can represent incomplete or vague beliefs, lack of data, and disagreements among experts; they can also encode models based on belief functions and possibilistic measures. All algorithms for approximate inference in this paper rely on exact inferences in credal networks based on polytrees with binary variables, as these inferences have polynomial complexity. We are inspired by approximate algorithms for Bayesian networks; thus the Loopy 2U algorithm resembles Loopy Belief Propagation, while the Iterated Partial Evaluation and Structured Variational 2U algorithms are, respectively, based on Localized Partial Evaluation and variational techniques. (C) 2007 Elsevier Inc. All rights reserved.

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Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging. (E-mail: matheuscardosomg@hotmail.com) (C) 2011 World Federation for Ultrasound in Medicine & Biology.