Depressive symptoms as a predictor of alcohol relapse after residential treatment programs for alcohol use disorder

Alcohol use disorder (AUD) and depressive disorders often co-occur. Findings on the effects of major depressive disorder (MDD) or depressive symptoms on posttreatment alcohol relapse are controversial. The study's aim is to examine the association of MDD and depressive symptoms with treatment outcomes after residential AUD programs. In a naturalistic-prospective, multisite study with 12 residential AUD treatment programs in the German-speaking part of Switzerland, 64 patients with AUD with MDD, 283 patients with AUD with clinically significant depressive symptoms at admission, and 81 patients with AUD with such problems at discharge were compared with patients with AUD only on alcohol use, depressive symptoms, and treatment service utilization. MDD was provisionally identified at admission and definitively defined at discharge. Whereas patients with MDD did not differ from patients with AUD only at 1-year follow-up, patients with AUD with clinically significant depressive symptoms had significantly shorter time-to-first-drink and a lower abstinence rate. These patients also had elevated AUD indices and treatment service utilization for psychiatric disorders. Our results suggest that clinically significant depressive symptoms are a substantial risk factor for relapse so that it may be important to treat them during and after residential AUD treatment programs.

Treatment outcomes of an integrated residential programme for patients with schizophrenia and substance use disorder

About half of all schizophrenic patients have a co-occurring substance use disorder, leading to poorer social and functional outcomes than obtained in non-abusing patients. To improve outcomes, integrated treatments have been designed that address the two conditions simultaneously. Results are, however, conflicting because the available effect studies are hampered by various methodological issues, among which are heterogeneous patient samples.

A prediction model for assessing residential radon concentration in Switzerland

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th-90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40-111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69-215 Bq/m³) in the medium category, and 219 Bq/m³ (108-427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be robust through validation with an independent dataset. The model is appropriate for predicting radon level exposure of the Swiss population in epidemiological research. Nevertheless, some exposure misclassification and regression to the mean is unavoidable and should be taken into account in future applications of the model.

Self-efficacy as a predictor of outcome after residential treatment programs for alcohol dependence: simply ask the patient one question!

Self-efficacy has been identified as one of the most consistent variables that predict the outcome of alcohol treatment. However, many previous studies in this field failed to control for other important predictors (e.g., dependences severity, psychiatric symptoms, and treatment goal). Our study's first goal was to evaluate the predictive value of self-efficacy when most other relevant variables were statistically controlled. The second goal was to compare the predictive values of self-efficacy assessed with the Situational Confidence Questionnaire (SCQ), and general self-efficacy assessed with a single question.

Invitational rhetoric : alternative rhetorical strategy for transformation of perception and use of energy in the residential built environment from the Keweenaw to Kerala

This dissertation explores the viability of invitational rhetoric as a mode of advocacy for sustainable energy use in the residential built environment. The theoretical foundations for this study join ecofeminist concepts and commitments with the conditions and resources of invitational rhetoric, developing in particular the rhetorical potency of the concepts of re-sourcement and enfoldment. The methodological approach is autoethnography using narrative reflection and journaling, both adapted to and developed within the autoethnographic project. Through narrative reflection, the author explores her lived experiences in advocating for energy-responsible residential construction in the Keweenaw Peninsula of Michigan. The analysis reveals the opportunities for cooperative, collaborative advocacy and the struggle against traditional conventions of persuasive advocacy, particularly the centrality of the rhetor. The author also conducted two field trips to India, primarily the state of Kerala. Drawing on autoethnographic journaling, the analysis highlights the importance of sensory relations in lived advocacy and the resonance of everyday Indian culture to invitational principles. Based on field research, the dissertation proposes autoethnography as a critical development in encouraging invitational rhetoric as an alternative mode of effecting change. The invitational force of autoethnography is evidenced in portraying the material advocacy of the built environment itself, specifically the sensual experience of material arrangements and ambience, as well as revealing the corporeality of advocacy, that is, the body as the site of invitational engagement, emotional encounter, and sensory experience. This study concludes that vulnerability of self in autoethnographic work and the vulnerability of rhetoric as invitational constitute the basis for transformation. The dissertation confirms the potential of an ecofeminist invitational advocacy conveyed autoethnographically for transforming perceptions and use of energy in a smaller-scale residential environment appropriate for culture, climate, and ultimately part of the challenge of sustaining life on this planet.

Integrated solar energy and absorption cooling model for HVAC (heating, ventilating, and air conditioning) applications in buildings

The demands in production and associate costs at power generation through non renewable resources are increasing at an alarming rate. Solar energy is one of the renewable resource that has the potential to minimize this increase. Utilization of solar energy have been concentrated mainly on heating application. The use of solar energy in cooling systems in building would benefit greatly achieving the goal of non-renewable energy minimization. The approaches of solar energy heating system research done by initiation such as University of Wisconsin at Madison and building heat flow model research conducted by Oklahoma State University can be used to develop and optimize solar cooling building system. The research uses two approaches to develop a Graphical User Interface (GUI) software for an integrated solar absorption cooling building model, which is capable of simulating and optimizing the absorption cooling system using solar energy as the main energy source to drive the cycle. The software was then put through a number of litmus test to verify its integrity. The litmus test was conducted on various building cooling system data sets of similar applications around the world. The output obtained from the software developed were identical with established experimental results from the data sets used. Software developed by other research are catered for advanced users. The software developed by this research is not only reliable in its code integrity but also through its integrated approach which is catered for new entry users. Hence, this dissertation aims to correctly model a complete building with the absorption cooling system in appropriate climate as a cost effective alternative to conventional vapor compression system.

Minimizing residential distribution system operating costs through intelligently scheduled plug-in hybrid electric vehicle charging

Rising fuel prices and environmental concerns are threatening the stability of current electrical grid systems. These factors are pushing the automobile industry towards more effcient, hybrid vehicles. Current trends show petroleum is being edged out in favor of electricity as the main vehicular motive force. The proposed methods create an optimized charging control schedule for all participating Plug-in Hybrid Electric Vehicles in a distribution grid. The optimization will minimize daily operating costs, reduce system losses, and improve power quality. This requires participation from Vehicle-to-Grid capable vehicles, load forecasting, and Locational Marginal Pricing market predictions. Vehicles equipped with bidirectional chargers further improve the optimization results by lowering peak demand and improving power quality.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.