Role of radical awareness in the character and word acquisition of Chinese children

Includes bibliographical references

Compton backscattered annihilation line emission: A new diagnostic of accreting compact sources

It is shown that Compton scattering of 511 keV electron-positron annihilation radiation produces a line like feature at approx. 170 keV from backscattered photons. Assuming a simple model of an accretion disk around a compact source, the spectrum is explored of the spectrum of Compton scattered annihilation line emission for a range of conditions. It is further shown that such Compton baskscattering of annihilation line emission from the inner edge of an accretion disk could account for the previously unidentified 170 keV line emission and high energy continuum observed from a variable, compact source, or sources, of annihilation radiation near the Galactic Center. Identification of the observed 170 keV line as an annihilation line reflection feature provides strong new evidence that the source of the emission is an accreting compact object. Further study of these features in existing spectra and in forthcoming GRO observation of these and other sources can provide unique new diagnostics of the innermost regions of accretion disks around compact objects

Regression with incomplete covariates and left-truncated time-to-event data

This is the peer reviewed version of the following article: Shen, Hua, and Richard J. Cook. "Regression with incomplete covariates and left‐truncated time‐to‐event data." Statistics in Medicine 32.6 (2013): 1004-1015, which has been published in final form at http://dx.doi.org/10.1002/sim.5581. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.Studies of chronic diseases routinely sample individuals subject to conditions on an event time of interest. In epidemiology, for example, prevalent cohort studies aiming to evaluate risk factors for survival following onset of dementia require subjects to have survived to the point of screening. In clinical trials designed to assess the effect of experimental cancer treatments on survival, patients are required to survive from the time of cancer diagnosis to recruitment. Such conditions yield samples featuring left-truncated event time distributions. Incomplete covariate data often arise in such settings, but standard methods do not deal with the fact that individuals’ covariate distributions are also affected by left truncation. We describe an expectation-maximization algorithm for dealing with incomplete covariate data in such settings, which uses the covariate distribution conditional on the selection criterion. We describe an extension to deal with subgroup analyses in clinical trials for the case in which the stratification variable is incompletely observed.Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626

A dynamic Mover–Stayer model for recurrent event processes

The final publication is available at Springer via http://dx.doi.org/10.1007/s10985-013-9271-7In studies of affective disorder, individuals are often observed to experience recurrent symptomatic exacerbations warranting hospitalization. Interest may lie in modeling the occurrence of such exacerbations over time and identifying associated risk factors. In some patients, recurrent exacerbations are temporally clustered following disease onset, but cease to occur after a period of time.We develop a dynamic Mover-Stayer model in which a canonical binary variable associated with each event indicates whether the underlying disease has resolved. An individual whose disease process has not resolved will experience events following a standard point process model governed by a latent intensity. When the disease process resolves, the complete data intensity becomes zero and no further event will occur. An expectation- maximization algorithm is described for parametric and semiparametric model fitting based on a discrete time dynamic Mover-Stayer model and a latent intensity-based model of the underlying point process.RJC: Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626) HS: Grant from the Division of High Impact Clinical Trials of the Ontario Institute for Cancer Researc

Analysis of interval-censored recurrent event processes subject to resolution

This is the peer reviewed version of the following article: Shen, H. and Cook, R. J. (2015), Analysis of interval-censored recurrent event processes subject to resolution. Biom. J., 57: 725–742. doi: 10.1002/bimj.201400162, which has been published in final form at http://dx.doi.org/10.1002/bimj.201400162. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.Interval-censored recurrent event data arise when the event of interest is not readily observed but the cumulative event count can be recorded at periodic assessment times. In some settings, chronic disease processes may resolve, and individuals will cease to be at risk of events at the time of disease resolution. We develop an expectation-maximization algorithm for fitting a dynamic mover-stayer model to interval-censored recurrent event data under a Markov model with a piecewise-constant baseline rate function given a latent process. The model is motivated by settings in which the event times and the resolution time of the disease process are unobserved. The likelihood and algorithm are shown to yield estimators with small empirical bias in simulation studies. Data are analyzed on the cumulative number of damaged joints in patients with psoriatic arthritis where individuals experience disease remission.Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626). HS: Grant from the Division of High Impact Clinical Trials of the Ontario Institute for Cancer Researc

Ubiquitin Goes Green

Chloroplasts depend on the nucleus for much of their proteome. Consequently, strong transcriptional coordination exists between the genomes, which is attuned to the developmental and physiological needs of the organelle. Recent studies highlight that the post-translational modifier ubiquitin adds another layer to plastid homeostasis and even helps eliminate damaged chloroplasts