H2 distribution during 2-phase Molecular Cloud Formation

We performed high-resolution, 3D MHD simulations and we compared to observations of translucent molecular clouds. We show that the observed populations of rotational levels of H2 can arise as a consequence of the multi-phase structure of the ISM.Comment: 2 pages, 1 figure. Due to appear in the proceedings of the 6th Zermatt ISM Symposium: "Conditions and Impact of Star Formation: From Lab to Space

A two-dimensional mixing length theory of convective transport

The helioseismic observations of the internal rotation profile of the Sun raise questions about the two-dimensional (2D) nature of the transport of angular momentum in stars. Here we derive a convective prescription for axisymmetric (2D) stellar evolution models. We describe the small scale motions by a spectrum of unstable linear modes in a Boussinesq fluid. Our saturation prescription makes use of the angular dependence of the linear dispersion relation to estimate the anisotropy of convective velocities. We are then able to provide closed form expressions for the thermal and angular momentum fluxes with only one free parameter, the mixing length. We illustrate our prescription for slow rotation, to first order in the rotation rate. In this limit, the thermodynamical variables are spherically symetric, while the angular momentum depends both on radius and latitude. We obtain a closed set of equations for stellar evolution, with a self-consistent description for the transport of angular momentum in convective regions. We derive the linear coefficients which link the angular momentum flux to the rotation rate ($\Lambda$- effect) and its gradient ($\alpha$-effect). We compare our results to former relevant numerical work.Comment: MNRAS accepted, 10 pages, 1 figure, version prior to language editio

Effects of turbulent diffusion on the chemistry of diffuse clouds

Aims. We probe the effect of turbulent diffusion on the chemistry at the interface between a cold neutral medium (CNM) cloudlet and the warm neutral medium (WNM). Methods. We perform moving grid, multifluid, 1D, hydrodynamical simulations with chemistry including thermal and chemical diffusion. The diffusion coefficients are enhanced to account for turbulent diffusion. We post-process the steady-states of our simulations with a crude model of radiative transfer to compute line profiles. Results. Turbulent diffusion spreads out the transition region between the CNM and the WNM. We find that the CNM slightly expands and heats up: its CH and H$_2$ content decreases due to the lower density. The change of physical conditions and diffusive transport increase the H$^+$ content in the CNM which results in increased OH and H$_2$O. Diffusion transports some CO out of the CNM. It also brings H$_2$ into contact with the warm gas with enhanced production of CH$^+$, H$_3^+$, OH and H$_2$O at the interface. O lines are sensitive to the spread of the thermal profile in the intermediate region between the CNM and the WNM. Enhanced molecular content at the interface of the cloud broadens the molecular line profiles and helps exciting transitions of intermediate energy. The relative molecular yield are found higher for bigger clouds. Conclusions. Turbulent diffusion can be the source of additional molecular production and should be included in chemical models of the interstellar medium (ISM). It also is a good candidate for the interpretation of observational problems such as warm H$_2$, CH$^+$ formation and presence of H$_3^+$.Comment: 13 pages, 23 figures, A&A accepte

Theoretical study of Acousto-optical coherence tomography using random phase jumps on US and light

Acousto-Optical Coherence Tomography (AOCT) is variant of Acousto Optic Imaging (called also ultrasonic modulation imaging) that makes possible to get z resolution with acoustic and optic Continuous Wave (CW) beams. We describe here theoretically the AOCT e ect, and we show that the Acousto Optic tagged photons remains coherent if they are generated within a speci c z region of the sample. We quantify the z selectivity for both the tagged photon eld, and for the M. Lesa re et al. photorefractive signal

Dynamic Predictions with Time-Dependent Covariates in Survival Analysis using Joint Modeling and Landmarking

A key question in clinical practice is accurate prediction of patient prognosis. To this end, nowadays, physicians have at their disposal a variety of tests and biomarkers to aid them in optimizing medical care. These tests are often performed on a regular basis in order to closely follow the progression of the disease. In this setting it is of medical interest to optimally utilize the recorded information and provide medically-relevant summary measures, such as survival probabilities, that will aid in decision making. In this work we present and compare two statistical techniques that provide dynamically-updated estimates of survival probabilities, namely landmark analysis and joint models for longitudinal and time-to-event data. Special attention is given to the functional form linking the longitudinal and event time processes, and to measures of discrimination and calibration in the context of dynamic prediction.Comment: 34 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1303.279

Dense molecular globulettes and the dust arc towards the runaway O star AE Aur (HD 34078)

Some runaway stars are known to display IR arc-like structures around them, resulting from their interaction with surrounding interstellar material. The properties of these features as well as the processes involved in their formation are still poorly understood. We aim at understanding the physical mechanisms that shapes the dust arc observed near the runaway O star AEAur (HD34078). We obtained and analyzed a high spatial resolution map of the CO(1-0) emission that is centered on HD34078, and that combines data from both the IRAM interferometer and 30m single-dish antenna. The line of sight towards HD34078 intersects the outer part of one of the detected globulettes, which accounts for both the properties of diffuse UV light observed in the field and the numerous molecular absorption lines detected in HD34078's spectra, including those from highly excited H2 . Their modeled distance from the star is compatible with the fact that they lie on the 3D paraboloid which fits the arc detected in the 24 {\mu}m Spitzer image. Four other compact CO globulettes are detected in the mapped area. These globulettes have a high density and linewidth, and are strongly pressure-confined or transient. The good spatial correlation between the CO globulettes and the IR arc suggests that they result from the interaction of the radiation and wind emitted by HD 34078 with the ambient gas. However, the details of this interaction remain unclear. A wind mass loss rate significantly larger than the value inferred from UV lines is favored by the large IR arc size, but does not easily explain the low velocity of the CO globulettes. The effect of radiation pressure on dust grains also meets several issues in explaining the observations. Further observational and theoretical work is needed to fully elucidate the processes shaping the gas and dust in bow shocks around runaway O stars. (Abridged)Comment: Accepted for publication in Astronomy & Astrophysic

Detection of the tagged or untagged photons in acousto-optic imaging of thick highly scattering media by photorefractive adaptive holography

We propose an original adaptive wavefront holographic setup based on the photorefractive effect (PR), to make real-time measurements of acousto-optic signals in thick scattering media, with a high flux collection at high rates for breast tumor detection. We describe here our present state of art and understanding on the problem of breast imaging with PR detection of the acousto-optic signal

JointAI: Joint Analysis and Imputation of Incomplete Data in R

Missing data occur in many types of studies and typically complicate the analysis. Multiple imputation, either using joint modelling or the more flexible fully conditional specification approach, are popular and work well in standard settings. In settings involving non-linear associations or interactions, however, incompatibility of the imputation model with the analysis model is an issue often resulting in bias. Similarly, complex outcomes such as longitudinal or survival outcomes cannot be adequately handled by standard implementations. In this paper, we introduce the R package JointAI, which utilizes the Bayesian framework to perform simultaneous analysis and imputation in regression models with incomplete covariates. Using a fully Bayesian joint modelling approach it overcomes the issue of uncongeniality while retaining the attractive flexibility of fully conditional specification multiple imputation by specifying the joint distribution of analysis and imputation models as a sequence of univariate models that can be adapted to the type of variable. JointAI provides functions for Bayesian inference with generalized linear and generalized linear mixed models and extensions thereof as well as survival models and joint models for longitudinal and survival data, that take arguments analogous to corresponding well known functions for the analysis of complete data from base R and other packages. Usage and features of JointAI are described and illustrated using various examples and the theoretical background is outlined.Comment: imputation, Bayesian, missing covariates, non-linear, interaction, multi-level, survival, joint model R, JAG