A Catalog of 1022 Bright Contact Binary Stars

In this work we describe a large new sample of contact binary stars extracted in a uniform manner from sky patrol data taken by the ROTSE-I telescope. Extensive ROTSE-I light curve data is combined with J, H, and K band near-infrared data taken from the Two Micron All-Sky Survey (2MASS) to add color information. Contact binaries candidates are selected using the observed period-color relation. Candidates are confirmed by visual examination of the light curves. To enhance the utility of this catalog, we derive a new J-H period-color-luminosity relation and use this to estimate distances for the entire catalog. From these distance estimates we derive an estimated contact binary space density of (1.7 +/- 0.6) x 10^-5 pcs^-3.Comment: 26 pages, 12 figures, accepted for publication in A

Photometric Analysis of Recently Discovered Eclipsing Binary GSC 00008-00901

Photometric analysis of $BVR_C$ light curves of newly discovered eclipsing binary GSC 0008-00901 is presented. The orbital period is improved to 0.28948(11) days. Photometric parameters are determined, as well. The analysis yielded to conclusion that system is an over-contact binary of W UMa type with components not in thermal contact. The light curves from 2005 show the presence of a spot on the surface of one of the components, while light curves from 2006 are not affected by maculation.Comment: Accepted for publication in Astrophysics & Space Scienc

Modelling fully convective stars in eclipsing binaries: KOI-126 and CM Draconis

We present models of the components of the systems KOI-126 and CM Draconis, the two eclipsing binary systems known to date to contain stars with masses low enough to have fully convective interiors. We are able to model satisfactorily the system KOI-126, finding consistent solutions for the radii and surface temperatures of all three components, using a solar-like value of the mixing-length parameter \alpha in the convection zone, and PHOENIX NextGen 1D model atmospheres for the surface boundary conditions. Depending on the chemical composition, we estimate the age of the system to be in the range 3-5 Gyr. For CM Draconis, on the other hand, we cannot reconcile our models with the observed radii and T_eff using the current metal-poor composition estimate based on kinematics. Higher metallicities lessen but do not remove the discrepancy. We then explore the effect of varying the mixing length parameter \alpha. As previously noted in the literature, a reduced \alpha can be used as a simple measure of the lower convective efficiency due to rotation and induced magnetic fields. Our models show a sensitivity to \alpha (for \alpha < 1.0) sufficient to partially account for the radius discrepancies. It is, however, impossible to reconcile the models with the observations on the basis of the effect of the reduced \alpha alone. We therefore suggest that the combined effects of high metallicity and \alpha reduction could explain the observations of CM Draconis. For example, increasing the metallicity of the system towards super-solar values (i.e. Z = 2 Z_sun) yields an agreement within 2 \sigma with \alpha = 1.0.Comment: 7 pages, 4 figures, accepted for publication in MNRA

Physical Orbit for Lambda Virginis and a Test of Stellar Evolution Models

Lambda Virginis (LamVir) is a well-known double-lined spectroscopic Am binary with the interesting property that both stars are very similar in abundance but one is sharp-lined and the other is broad-lined. We present combined interferometric and spectroscopic studies of LamVir. The small scale of the LamVir orbit (~20 mas) is well resolved by the Infrared Optical Telescope Array (IOTA), allowing us to determine its elements as well as the physical properties of the components to high accuracy. The masses of the two stars are determined to be 1.897 Msun and 1.721 Msun, with 0.7% and 1.5% errors respectively, and the two stars are found to have the same temperature of 8280 +/- 200 K. The accurately determined properties of LamVir allow comparisons between observations and current stellar evolution models, and reasonable matches are found. The best-fit stellar model gives LamVir a subsolar metallicity of Z=0.0097, and an age of 935 Myr. The orbital and physical parameters of LamVir also allow us to study its tidal evolution time scales and status. Although currently atomic diffusion is considered to be the most plausible cause of the Am phenomenon, the issue is still being actively debated in the literature. With the present study of the properties and evolutionary status of LamVir, this system is an ideal candidate for further detailed abundance analyses that might shed more light on the source of the chemical anomalies in these A stars.Comment: 43 Pages, 13 figures. Accepted for publication in Ap

The photometric-amplitude and mass-ratio distributions of contact binary stars

The distribution of the light-variation amplitudes, A(a), in addition to determining the number of undiscovered contact binary systems falling below photometric detection thresholds and thus lost to statistics, can serve as a tool in determination of the mass-ratio distribution, Q(q), which is very important for understanding of the evolution of contact binaries. Calculations of the expected A(a) show that it tends to converge to a mass-ratio dependent constant value for a->0. Strong dependence of A(a) on Q(q) can be used to determine the latter distribution, but the technique is limited by the presence of unresolved visual companions and by blending in crowded areas of the sky. The bright-star sample to 7.5 magnitude is too small for an application of the technique while the the Baade's Window sample from the OGLE project may suffer stronger blending; thus the present results are preliminary and illustrative only. Estimates based on the Baade's Window data from the OGLE project, for amplitudes a>0.3 mag. where the statistics appear to be complete allowing determination of Q(q) over 0.12<q<1, suggest a steep increase of Q(q) with q->0. The mass-ratio distribution can be approximated by a power law, either Q(q)~(1-q)^a1 with a1=6+/-2 or Q(q)~q^b1, with b1=-2+/-0.5, with a slight preference for the former form. Both forms must be modified by the theoretically expected cut-off caused by a tidal instability at about q_min 0.07-0.1. An expected maximum in Q(q), is expected to be mapped into a local maximum in A(a) around 0.2-0.25 mag.Comment: AASTeX5, 12 figures, 5 tables, accepted by AJ, Aug.200

A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single gene classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single gene classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single gene classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single gene sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single gene classifiers for predicting outcome in breast cancer

A Consistency Test of Spectroscopic Gravities for Late-Type Stars

Chemical analyses of late-type stars are usually carried out following the classical recipe: LTE line formation and homogeneous, plane-parallel, flux-constant, and LTE model atmospheres. We review different results in the literature that have suggested significant inconsistencies in the spectroscopic analyses, pointing out the difficulties in deriving independent estimates of the stellar fundamental parameters and hence,detecting systematic errors. The trigonometric parallaxes measured by the HIPPARCOS mission provide accurate appraisals of the stellar surface gravity for nearby stars, which are used here to check the gravities obtained from the photospheric iron ionization balance. We find an approximate agreement for stars in the metallicity range -1 <= [Fe/H] <= 0, but the comparison shows that the differences between the spectroscopic and trigonometric gravities decrease towards lower metallicities for more metal-deficient dwarfs (-2.5 <= [Fe/H] <= -1.0), which casts a shadow upon the abundance analyses for extreme metal-poor stars that make use of the ionization equilibrium to constrain the gravity. The comparison with the strong-line gravities derived by Edvardsson (1988) and Fuhrmann (1998a) confirms that this method provides systematically larger gravities than the ionization balance. The strong-line gravities get closer to the physical ones for the stars analyzed by Fuhrmann, but they are even further away than the iron ionization gravities for the stars of lower gravities in Edvardsson's sample. The confrontation of the deviations of the iron ionization gravities in metal-poor stars reported here with departures from the excitation balance found in the literature, show that they are likely to be induced by the same physical mechanism(s).Comment: AAS LaTeX v4.0, 35 pages, 10 PostScript files; to appear in The Astrophysical Journa

Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery

<p>Abstract</p> <p>Background</p> <p>Although high-throughput microarray based molecular diagnostic technologies show a great promise in cancer diagnosis, it is still far from a clinical application due to its low and instable sensitivities and specificities in cancer molecular pattern recognition. In fact, high-dimensional and heterogeneous tumor profiles challenge current machine learning methodologies for its small number of samples and large or even huge number of variables (genes). This naturally calls for the use of an effective feature selection in microarray data classification.</p> <p>Methods</p> <p>We propose a novel feature selection method: multi-resolution independent component analysis (MICA) for large-scale gene expression data. This method overcomes the weak points of the widely used transform-based feature selection methods such as principal component analysis (PCA), independent component analysis (ICA), and nonnegative matrix factorization (NMF) by avoiding their global feature-selection mechanism. In addition to demonstrating the effectiveness of the multi-resolution independent component analysis in meaningful biomarker discovery, we present a multi-resolution independent component analysis based support vector machines (MICA-SVM) and linear discriminant analysis (MICA-LDA) to attain high-performance classifications in low-dimensional spaces.</p> <p>Results</p> <p>We have demonstrated the superiority and stability of our algorithms by performing comprehensive experimental comparisons with nine state-of-the-art algorithms on six high-dimensional heterogeneous profiles under cross validations. Our classification algorithms, especially, MICA-SVM, not only accomplish clinical or near-clinical level sensitivities and specificities, but also show strong performance stability over its peers in classification. Software that implements the major algorithm and data sets on which this paper focuses are freely available at <url>https://sites.google.com/site/heyaumapbc2011/</url>.</p> <p>Conclusions</p> <p>This work suggests a new direction to accelerate microarray technologies into a clinical routine through building a high-performance classifier to attain clinical-level sensitivities and specificities by treating an input profile as a ‘profile-biomarker’. The multi-resolution data analysis based redundant global feature suppressing and effective local feature extraction also have a positive impact on large scale ‘omics’ data mining.</p

SPADES: a Stellar PArameters DEtermination Software

With the large amounts of spectroscopic data available today and the very large surveys to come (e.g. Gaia), the need for automatic data analysis software is unquestionable. We thus developed an automatic spectra analysis program for the determination of stellar parameters: radial velocity, effective temperature, surface gravity, micro-turbulence, metallicity and the elemental abundances of the elements present in the spectral range. Target stars for this software should include all types of stars. The analysis method relies on a line by line comparison of the spectrum of a target star to a library of synthetic spectra. The idea is built on the experience acquired in developing the TGMET (Katz et al. 1998 and Soubiran et al. 2003) ETOILE (Katz 2001) and Abbo (Bonifacio & Caffau 2003) softwares. The method is presented and the performances are illustrated with GIRAFFE-like simulated spectra with high resolution (R = 25000), with high and low signal to noise ratios (down to SNR= 30). These spectra should be close to what could be targeted by the Gaia-ESO Survey (GCDS).Comment: 5 pages, SF2A 2011 Poster Proceeding