Model Atmospheres for Irradiated Stars in pre-Cataclysmic Variables

Model atmospheres have been computed for M dwarfs that are strongly irradiated by nearby hot companions. A variety of primary and secondary spectral types are explored in addition to models specific to four known systems: GD 245, NN Ser, AA Dor, and UU Sge. This work demonstrates that a dramatic temperature inversion is possible on at least one hemisphere of an irradiated M dwarf and the emergent spectrum will be significantly different from an isolated M dwarf or a black body flux distribution. For the first time, synthetic spectra suitable for direct comparison to high-resolution observations of irradiated M dwarfs in non-mass transferring post-common envelope binaries are presented. The effects of departures from local thermodynamic equilibrium on the Balmer line profiles are also discussed.Comment: Accepted for publication in ApJ; 12 pages, 10 figure

Neural precursor cells derived from induced pluripotent stem cells exhibit reduced susceptibility to infection with a neurotropic coronavirus.

The present study examines the susceptibility of mouse induced pluripotent stem cell-derived neural precursor cells (iPSC-NPCs) to infection with the neurotropic JHM strain of mouse hepatitis virus (JHMV). Similar to NPCs derived from striatum of day 1 postnatal GFP-transgenic mice (GFP-NPCs), iPSC-derived NPCs (iPSC-NPCs) are able to differentiate into terminal neural cell types and express MHC class I and II in response to IFN-γ treatment. However, in contrast to postnatally-derived NPCs, iPSC-NPCs express low levels of carcinoembryonic antigen-cell adhesion molecule 1a (CEACAM1a), the surface receptor for JHMV, and are less susceptible to infection and virus-induced cytopathic effects. The relevance of this in terms of therapeutic application of NPCs resistant to viral infection is discussed

Fast Computation of Analytical Second Derivatives with Effective Core Potentials: Application to Si8C12, Ge8C12, and Sn8C12

An improved method is described for the computation of integrals involving effective core potentials. The improved method provides better scalability to higher angular momenta as well as improved speed. The new method is also applied to the determination of the minimum energy structures of Si8C12, Ge8C12, and Sn8C12, main group analogs of the Ti8C12compounds (known as metcars). Relative energies, geometries, and vibrational frequencies are reported for several novel structures

Stability of Filters for the Navier-Stokes Equation

Data assimilation methodologies are designed to incorporate noisy observations of a physical system into an underlying model in order to infer the properties of the state of the system. Filters refer to a class of data assimilation algorithms designed to update the estimation of the state in a on-line fashion, as data is acquired sequentially. For linear problems subject to Gaussian noise filtering can be performed exactly using the Kalman filter. For nonlinear systems it can be approximated in a systematic way by particle filters. However in high dimensions these particle filtering methods can break down. Hence, for the large nonlinear systems arising in applications such as weather forecasting, various ad hoc filters are used, mostly based on making Gaussian approximations. The purpose of this work is to study the properties of these ad hoc filters, working in the context of the 2D incompressible Navier-Stokes equation. By working in this infinite dimensional setting we provide an analysis which is useful for understanding high dimensional filtering, and is robust to mesh-refinement. We describe theoretical results showing that, in the small observational noise limit, the filters can be tuned to accurately track the signal itself (filter stability), provided the system is observed in a sufficiently large low dimensional space; roughly speaking this space should be large enough to contain the unstable modes of the linearized dynamics. Numerical results are given which illustrate the theory. In a simplified scenario we also derive, and study numerically, a stochastic PDE which determines filter stability in the limit of frequent observations, subject to large observational noise. The positive results herein concerning filter stability complement recent numerical studies which demonstrate that the ad hoc filters perform poorly in reproducing statistical variation about the true signal

Gaussian approximations for stochastic systems with delay: chemical Langevin equation and application to a Brusselator system

We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period.Comment: 14 pages, 9 figure

Solutions of Higher Dimensional Gauss-Bonnet FRW Cosmology

We examine the effect on cosmological evolution of adding a Gauss-Bonnet term to the standard Einstein-Hilbert action for a (1 + 3)+ d dimensional Friedman-Robertson-Walker (FRW) metric. By assuming that the additional dimensions compactify as a power law as the usual 3 spatial dimensions expand, we solve the resulting dynamical equations and find that the solution may be of either de Sitter or Kasner form depending upon whether the Gauss-Bonnet term or the Einstein term dominates.Comment: 10 pages, references added/corrected, accepted for publication in General Relativity and Gravitatio