Radon as a Tracer of Lung Changes Induced by Smoking

After smoking, exposure to radon and its progeny is the second leading cause of lung cancer. The probability of inducing lung carcinomas by inhaled radon progeny depends on the deposited radiation dose, and is significantly affected by physiological and morphometric changes induced by smoking. Due to irritation of the airways, the inhalation of cigarette smoke leads to the hyperproduction of mucus. Two concurrent processes occur: on one hand, increased production of mucus protects the target cells against radiation damage; on the other hand, in the case of long-term smokers, a chronic lung obstruction develops, causing an increase in the radiation dose to the lungs. Depending on the duration and intensity of smoking, these processes contribute to the final radiation dose with different weights. The primary objective of this study was to investigate to what extent these smoke-induced changes can modify the resulting absorbed dose of inhaled radon progeny relative to healthy nonsmokers. Since the bronchial dose depends on the degree of lung tissue damage, we have used this dose as a tool for detecting the effects of smoking on the lung epithelium. In other words, the biological effect of radon served as a tracer of changes induced by smoking.     

Clinically Significant Effects of Group Cognitive Behavioral Therapy on Spouse Caregivers' Mental Health and Cognitive Functioning: A Pilot Study

The objective of this pilot study was to investigate whether group cognitive behavioral therapy (CBT) resulted in clinically meaningful improvements in caregiver mood, burden, and cognition. We screened 97 caregivers in Toronto, Canada, of whom 25 with DSM-IV disorders began the 13-week CBT intervention, and 12 completed therapy and the 3-month follow-up. Each caregiver experienced clinically significant improvement on at least 2 of the following outcomes: diagnostic criteria, mood, attention, memory, and caregiver burden. Despite effectiveness, the challenges of recruiting distressed caregivers for therapy suggest that CBT might be most useful as part of a stepped care model of treatment.     

Non-rejective implementations of the Sampford sampling design

Sampford sampling is a method for unequal probability sampling. There exist several implementations of the Sampford sampling design which all are rejective methods, i.e. the sample is not always accepted. Thus the existing methods can be time consuming or even infeasible in some situations. In this paper, a fast and non-rejective list-sequential method, which works in all situations, is presented. The method is a modification of a previously existing rejective list-sequential method. Another list-sequential implementation of Sampford sampling is also presented.     

Modelling of a thermomechanically coupled forming process based on functional outputs from a finite element analysis and from experimental measurements

In this paper, measurements from experiments and results of a finite element analysis (FEA) are combined in order to compute accurate empirical models for the temperature distribution before a thermomechanically coupled forming process. To accomplish this, Design and Analysis of Computer Experiments (DACE) is used to separately compute models for the measurements and the functional output of the FEA. Based on a hierarchical approach, a combined model of the process is computed. In this combined modelling approach, the model for the FEA is corrected by taking into account the systematic deviations from the experimental measurements. The large number of observations based on the functional output hinders the direct computation of the DACE models due to the internal inversion of the correlation matrix. Thus, different techniques for identifying a relevant subset of the observations are proposed. The application of the resulting procedure is presented, and a statistical validation of the empirical models is performed.     

Consistency of the GMLE with Mixed Case Interval-Censored Data

In this paper we consider an interval censorship model in which the endpoints of the censoring intervals are determined by a two stage experiment. In the first stage the value k of a random integer is selected; in the second stage the endpoints are determined by a case k interval censorship model. We prove the strong consistency in the L ₁( μ )-topology of the non-parametric maximum likelihood estimate of the underlying survival function for a measure μ which is derived from the distributions of the endpoints. This consistency result yields strong consistency for the topologies of weak convergence, pointwise convergence and uniform convergence under additional assumptions. These results improve and generalize existing ones in the literature.     

An Application of Bayesian Methods to Small Area Poverty Rate Estimates

Efforts to estimate various sociodemographic variables in small geographic areas are proving difficult with the replacement of the Census long-form with the American Community Survey (ACS). Researchers interested in subnational demographic processes have previously relied on Census 2000 long-form data products in order to answer research questions. ACS data products promise to begin providing up-to-date profiles of the nation’s population and economy; however, unit- and item-level nonresponse in the ACS have left researchers with gaps in subnational coverage resulting in unstable and unreliable estimates for basic demographic measures. Borrowing information from neighboring areas and across time with a spatiotemporal smoothing process based on Bayesian statistical methods, it is possible to generate more stable and accurate estimates of rates for geographic areas not represented in the ACS. This research evaluates this spatiotemporal smoothing process in its ability to derive estimates of poverty rates at the county level for the contiguous United States. These estimates are then compared to more traditional estimates produced by the US Census Bureau, and comparisons between the two methods of estimation are carried out to evaluate the practical application of this smoothing method. Our findings suggest that by using available data from the ACS only, we are able to recreate temporal and spatial patterns of poverty in US counties even in years where data are sparse. Results show that the Bayesian methodology strongly agrees with the estimates produced by the SAIPE program, even in years with little data. This methodology can be expanded to other demographic and socioeconomic data with ease.     

Neuroticism,Negative Thinking,and Coping With Respect to Career Decision State

Using structural equation modeling, the present study investigated relationships between neuroticism, coping strategies, and negative career thoughts within the context of attaining a positive career decision state. Results from the initial model, based on a sample of college students (119 women, 113 men; M = 20.3 years) enrolled in a career development course, revealed that coping strategies were not a significant contribution to the model. The final model, without coping strategies, showed that neuroticism had a significant indirect effect on career decision state through negative thinking and that the relationship between neuroticism and career decision state was also significant. Findings also indicate that in the presence of negative career thoughts, neuroticism becomes associated with a more positive career decision state. Practical implications include suggestions that counselors intervene on clients' negative career thoughts to potentially render their neurotic tendencies more productive in reaching a desired career decision state.