The prediction of responses of the reinforced concrete shear walls subject to strong ground motions is critical in designing, assessing, and deciding the recovery strategies. This study evaluates the ability of regression models and a hybrid technique (ANN-SA model), the Artificial Neural Network (ANN), and Simulated Annealing (SA), to predict responses of the reinforced concrete shear walls subject to strong ground motions. To this end, four buildings (15, 20, 25, and 30-story) with concrete shear walls were analyzed in OpenSees.150 seismic records are used to generate a comprehensive database of input (characteristics of records) and output (responses). The maximum acceleration, maximum velocity, and earthquake characteristics are used as predictors. Different machine learning models are used, and the accuracy of the models in identifying the responses of the shear walls is compared. The sensitivity of input variables to the seismic demand model is investigated. It has been seen from the results that the ANN-SA model has reasonable accuracy in the prediction.

Objectives To evaluate the effect of psychotherapy for depression in patients receiving disability benefits. Methods Using administrative data from a large Canadian, private, disability insurer, we evaluated the association between the provision of psychotherapy and other potentially predictive factors with time to long-term disability (LTD) claim closure. Conclusions We found multiple factors, including psychotherapy, which were predictive of time to LTD claim closure. Our findings may however be influenced by selection bias and other biases that present challenges to the analysis and interpretation of administrative data, and highlight the need for well-designed prospective studies. 53 ASSOCIATIONS OF THE PSYCHOSOCIAL WORK ENVIRONMENT FACTORS WITH THE MENTAL HEALTH DISORDERS IN NURSING PROFESSIONT Freimann, Lünekund, Merisalu. University of Tartu, Tartu, Estonia 10. 1136/oemed-2013-101717.53 Objective This study examined the associations of work environment factors with the mental health disorders in nursing profession. Methods A cross-sectional survey was carried out among registered nurses in the Tartu University Hospital. The electronic questionnaire was sent to all 906 full staff nurses working in hospital. The Estonian translation of the Copenhagen Psychosocial Questionnaire, version II (COPSOQ II) was used to measure psychosocial work environment dimensions and mental health disorders. Data were analysed using the SPSS version 18 and Statistical Software R. Descriptive statistics was used to assess means and standard deviations for psychosocial risk factors and mental health disorders. Binary logistic regression analysis was used to observe relationships between risk factors and mental health disorders. The results were summarised by OR-s with 95% CI-s.Results A total 404 questionnaires (45%) were used in the analysis. The average age of the study group was 40.2 years (SD 10.8) and most of respondents were women (98.3%). The mental health indicators showed relatively high average values of burnout and stress among nurses. High average scores of positive work characteristics (meaning of work, role clarity, social relationships at work and mutual trust between employees) in a 100 point scale were detected. High average scores were measured also on the negative work characteristics as work-family conflict, work pace, emotional and cognitive demands. The increased risk for mental health disorders was caused by work-family conflict, above-average quantitative and emotional demands and other factors. Risk for mental health disorders was decreased by above-average justice and respect, commitment to the workplace, job satisfaction and other factors. Conclusions Our study confirmed that there are strong relationship between psychosocial risk factors and mental disorders. The present study refers to the urgent need for preventive strategies to reduce the psychosocial stress factors as the main causes of mental health problems. Objectives This cross sectional study examined the occupational cancer risk perceptio...