Flicker as a tool for characterizing planets through Asterodensity Profiling

Variability in the time series brightness of a star on a timescale of 8 hours, known as 'flicker', has been previously demonstrated to serve as a proxy for the surface gravity of a star by Bastien et al. (2013). Although surface gravity is crucial for stellar classification, it is the mean stellar density which is most useful when studying transiting exoplanets, due to its direct impact on the transit light curve shape. Indeed, an accurate and independent measure of the stellar density can be leveraged to infer subtle properties of a transiting system, such as the companion's orbital eccentricity via asterodensity profiling. We here calibrate flicker to the mean stellar density of 439 Kepler targets with asteroseismology, allowing us to derive a new empirical relation given by $\log_{10}(\rho_{\star}\,[\mathrm{kg}\,\mathrm{m}^{-3}]) = 5.413 - 1.850 \log_{10}(F_8\,[\mathrm{ppm}])$. The calibration is valid for stars with $4500$K$<T_{\mathrm{eff}}<6500$K, $K_P<14$ and flicker estimates corresponding to stars with $3.25<\log g_{\star}<4.43$. Our relation has a model error in the stellar density of 31.7% and so has $\sim8$ times lower precision than that from asteroseismology but is applicable to a sample $\sim40$ times greater. Flicker therefore provides an empirical method to enable asterodensity profiling on hundreds of planetary candidates from present and future missions.Comment: 6 pages, 3 figures, 1 table. Accepted to ApJ Letters. Code available at https://www.cfa.harvard.edu/~dkipping/flicker.htm

Thermoelectric power quantum oscillations in the ferromagnet UGe2_2

We present thermoelectric power and resistivity measurements in the ferromagnet UGe$_2$ as a function of temperature and magnetic field. At low temperature, huge quantum oscillations are observed in the thermoelectric power as a function of the magnetic field applied along the $a$ axis. The frequencies of the extreme orbits are determined and an analysis of the cyclotron masses is performed following different theoretical approaches for quantum oscillations detected in the thermoelectric power. They are compared to those obtained by Shubnikov-de Haas experiments on the same crystal and previous de Haas-van Alphen experiments. The agreement of the different probes confirms thermoelectric power as an excellent probe to extract simultaneously both microscopic and macroscopic information on the Fermi-surface properties. Band-structure calculations of UGe$_2$ in the ferromagnetic state are compared to the experiment.Comment: 10 figures, 12 pages, accepted for publication in Phys. Rev.

Interaction of the Papillomavirus E2 Protein with Mitotic Chromosomes

AbstractThe bovine papillomavirus E2 transactivator protein is a multifunctional protein that activates viral transcription, cooperates in initiation of viral DNA replication, and is required for long-term episomal maintenance of viral genomes. We have shown previously that the E2 transactivator protein and bovine papillomavirus type 1 genomes are associated with mitotic chromosomes and have proposed that E2 links the genomes to cellular chromosomes to ensure segregation to daughter nuclei. In this study, we show that E2 is associated with cellular chromosomes at all stages of mitosis. We also further map the regions of E2 that are required for this association. The transactivation domain of E2 is necessary and sufficient to mediate the interaction with mitotic chromosomes; the DNA binding domain, and the flexible hinge region that separates the two domains, is not required. Furthermore, mutation of previously identified phosphorylation sites (serine residues 235, 298, and 301) has no effect on the ability of the E2 protein to bind mitotic chromosomes

Probabilistic Graphical Model Representation in Phylogenetics

Recent years have seen a rapid expansion of the model space explored in statistical phylogenetics, emphasizing the need for new approaches to statistical model representation and software development. Clear communication and representation of the chosen model is crucial for: (1) reproducibility of an analysis, (2) model development and (3) software design. Moreover, a unified, clear and understandable framework for model representation lowers the barrier for beginners and non-specialists to grasp complex phylogenetic models, including their assumptions and parameter/variable dependencies. Graphical modeling is a unifying framework that has gained in popularity in the statistical literature in recent years. The core idea is to break complex models into conditionally independent distributions. The strength lies in the comprehensibility, flexibility, and adaptability of this formalism, and the large body of computational work based on it. Graphical models are well-suited to teach statistical models, to facilitate communication among phylogeneticists and in the development of generic software for simulation and statistical inference. Here, we provide an introduction to graphical models for phylogeneticists and extend the standard graphical model representation to the realm of phylogenetics. We introduce a new graphical model component, tree plates, to capture the changing structure of the subgraph corresponding to a phylogenetic tree. We describe a range of phylogenetic models using the graphical model framework and introduce modules to simplify the representation of standard components in large and complex models. Phylogenetic model graphs can be readily used in simulation, maximum likelihood inference, and Bayesian inference using, for example, Metropolis-Hastings or Gibbs sampling of the posterior distribution