We present an evaluation of the performance of an automated classification of the Hipparcos periodic variable stars into 26 types. The sub‐sample with the most reliable variability types available in the literature is used to train supervised algorithms to characterize the type dependencies on a number of attributes. The most useful attributes evaluated with the random forest methodology include, in decreasing order of importance, the period, the amplitude, the V−I colour index, the absolute magnitude, the residual around the folded light‐curve model, the magnitude distribution skewness and the amplitude of the second harmonic of the Fourier series model relative to that of the fundamental frequency. Random forests and a multi‐stage scheme involving Bayesian network and Gaussian mixture methods lead to statistically equivalent results. In standard 10‐fold cross‐validation (CV) experiments, the rate of correct classification is between 90 and 100 per cent, depending on the variability type. The main mis‐classification cases, up to a rate of about 10 per cent, arise due to confusion between SPB and ACV blue variables and between eclipsing binaries, ellipsoidal variables and other variability types. Our training set and the predicted types for the other Hipparcos periodic stars are available online.
We report here the 98.5 Mbp haploid genome (12,924 protein coding genes) of Ulva mutabilis, a ubiquitous and iconic representative of the Ulvophyceae or green seaweeds. Ulva's rapid and abundant growth makes it a key contributor to coastal biogeochemical cycles; its role in marine sulfur cycles is particularly important because it produces high levels of dimethylsulfoniopropionate (DMSP), the main precursor of volatile dimethyl sulfide (DMS). Rapid growth makes Ulva attractive biomass feedstock but also increasingly a driver of nuisance "green tides." Ulvophytes are key to understanding the evolution of multicellularity in the green lineage, and Ulva morphogenesis is dependent on bacterial signals, making it an important species with which to study cross-kingdom communication. Our sequenced genome informs these aspects of ulvophyte cell biology, physiology, and ecology. Gene family expansions associated with multicellularity are distinct from those of freshwater algae. Candidate genes, including some that arose following horizontal gene transfer from chromalveolates, are present for the transport and metabolism of DMSP. The Ulva genome offers, therefore, new opportunities to understand coastal and marine ecosystems and the fundamental evolution of the green lineage.
Aims. We present the results of an automated variability analysis of the Kepler public data measured in the first quarter (Q1) of the mission. In total, about 150 000 light curves have been analysed to detect stellar variability and to identify new members of known variability classes. We also focus on detecting variables present in eclipsing binary systems, given the strong constraints on stellar fundamental parameters they can provide.Methods. The methodology we use here is based on the automated variability classification pipeline, which was previously developed for and successfully applied to the CoRoT exofield database and to the limited subset of a few thousand Kepler asteroseismology light curves. We use a Fourier decomposition of the light curves to describe their variability behaviour and use the resulting parameters to perform a supervised classification. Several improvements were made, including a separate extractor method to detect the presence of eclipses when other variability is present in the light curves. We also included two new variability classes compared to previous work: variables showing signs of rotational modulation and of activity. Results. Statistics are given on the number of variables and the number of good candidates per class. A comparison is made with results obtained for the CoRoT exoplanet data. We present some special discoveries, including variable stars in eclipsing binary systems. Many new candidate non-radial pulsators are found, mainly δ Sct and γ Dor stars. We studied those samples in more detail by using 2MASS colours, and the full classification results are made available as an online catalogue.
Oscillating stars in binary systems are among the most interesting stellar laboratories, as these can provide information on the stellar parameters and stellar internal structures. Here we present a red giant with solar-like oscillations in an eclipsing binary observed with the NASA Kepler satellite. We compute stellar parameters of the red giant from spectra and the asteroseismic mass and radius from the oscillations. Although only one eclipse has been observed so far, we can already determine that the secondary is a main-sequence F star in an eccentric orbit with a semi-major axis larger than 0.5 AU and orbital period longer than 75 days.
HighlightbZIP29, an Arabidopsis transcription factor, is expressed in proliferative tissues and involved in the regulation of cell number in the root meristem and leaves.
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