Modeling multilevel sleep transitional data via Poisson log-linear multilevel models

This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed

AN OVERVIEW OF OBSERVATIONAL SLEEP RESEARCH WITH APPLICATION TO SLEEP STAGE TRANSITIONING

In this manuscript we give an overview of observational sleep research with a particular emphasis on sleep stage transitions. Sleep states represent a categorization of sleep electroencephalogram behavior over the night. We postulate that the rate of transitioning between sleep states is an important predictor of health. This claim is evaluated by comparing subjects with sleep disordered breathing to matched controls

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. This paper is a revamping of Modeling multilevel sleep transitional data via Poisson log-linear multilevel models available at: http://www.bepress.com/jhubiostat/paper212

LASAGNA PLOTS: A SAUCY ALTERNATIVE TO SPAGHETTI PLOTS

Longitudinal repeated measures data has often been visualized with spaghetti plots for continuous out- comes. For large datasets, this often leads to over-plotting and consequential obscuring of trends in the data. This is primarily due to overlapping of trajectories. Here, we suggest a framework called lasagna plot ting that constrains the subject-specific trajectories to prevent overlapping and utilizes gradients of color to depict the outcome. Dynamic sorting and visualization is demonstrated as an exploratory data analysis tool. Supplemental material in the form of sample R code additional illustrated examples are available online

Effect of hydrogen on ground state structures of small silicon clusters

We present results for ground state structures of small Si$_{n}$H (2 \leq \emph{n} \leq 10) clusters using the Car-Parrinello molecular dynamics. In particular, we focus on how the addition of a hydrogen atom affects the ground state geometry, total energy and the first excited electronic level gap of an Si$_{n}$ cluster. We discuss the nature of bonding of hydrogen in these clusters. We find that hydrogen bonds with two silicon atoms only in Si$_{2}$H, Si$_{3}$H and Si$_{5}$H clusters, while in other clusters (i.e. Si$_{4}$H, Si$_{6}$H, Si$_{7}$H, Si$_{8}$H, Si$_{9}$H and Si$_{10}$H) hydrogen is bonded to only one silicon atom. Also in the case of a compact and closed silicon cluster hydrogen bonds to the cluster from outside. We find that the first excited electronic level gap of Si$_{n}$ and Si$_{n}$H fluctuates as a function of size and this may provide a first principles basis for the short-range potential fluctuations in hydrogenated amorphous silicon. Our results show that the addition of a single hydrogen can cause large changes in the electronic structure of a silicon cluster, though the geometry is not much affected. Our calculation of the lowest energy fragmentation products of Si$_{n}$H clusters shows that hydrogen is easily removed from Si$_{n}$H clusters.Comment: one latex file named script.tex including table and figure caption. Six postscript figure files. figure_1a.ps and figure_1b.ps are files representing Fig. 1 in the main tex

UGPS J194310+183851 : an Unusual Optical and X-ray Faint Cataclysmic Variable?

©2022 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This is the final published pdf, which was originally published at https://doi.org/10.1093/mnras/stac1718 Funding Information: We acknowledge the use of public data from the Swift data archive. We also acknowledge the use of the WHT: the William Herschel Telescope and its service programme are operated on the island of La Palma by the Isaac Newton Group of Telescopes in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias. We would like to thank the operations teams at both facilities for the quick and efficient observations. CM acknowledges support from the UK's Science and Technology Facilities Council (ST/S505419/1). NM and WJC are funded by University of Hertfordshire studentships; furthermore CM, PWL, NM, WJC, ZG, and JED recognize the computing infrastructure provided via STFC grant ST/R000905/1 at the University of Hertfordshire. JS acknowledges support from the P ackard F oundation and National Science Foundation grant AST-1714825. Portions of this work were performed while SJS held a NRC Research Associateship award at the Naval Research Laboratory. Work at the Naval Research Laboratory is supported by NASA DPR S-15633-Y. ZG acknowledges the financial support from ANID (CONICYT) through the FONDECYT project No. 3220029. Publisher Copyright: © 2022 The Author(s).The growing number of multi-epoch optical and infrared sky surveys are uncovering unprecedented numbers of new variable stars, of an increasing number of types. The short interval between observations in adjacent near-infrared filters in the UKIDSS Galactic Plane Survey (UGPS) allows for the discovery of variability on the time-scale of minutes. We report on the nature of one such object, through the use of optical spectroscopy, time series photometry, and targeted X-ray observations. We propose that UGPS J194310.32+183851.8 is a magnetic cataclysmic variable star of novel character, probably featuring a longer than average spin period and an orbital period likely to be shorter than the period gap (i.e. Porb < 2 h). We reason that the star is likely a member of the short-period intermediate-polar subclass that exists below this period boundary, but with the additional feature that system's spectral energy distribution is fainter and redder than other members of the group.Peer reviewe