349 research outputs found
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 (- effect) and its gradient (-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 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 HO.
Diffusion transports some CO out of the CNM. It also brings H into contact
with the warm gas with enhanced production of CH, H, OH and HO 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, CH formation
and presence of H.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
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