Bayesian inferencing for wind resource characterisation

The growing role of wind power in power systems has motivated R&D on methodologies to characterise the wind resource at sites for which no wind speed data is available. Applications such as feasibility assessment of prospective installations and system integration analysis of future scenarios, amongst others, can greatly benefit from such methodologies. This paper focuses on the inference of wind speeds for such potential sites using a Bayesian approach to characterise the spatial distribution of the resource. To test the approach, one year of wind speed data from four weather stations was modelled and used to derive inferences for a fifth site. The methodology used is described together with the model employed and simulation results are presented and compared to the data available for the fifth site. The results obtained indicate that Bayesian inference can be a useful tool in spatial characterisation of wind

Self-Management Strategies Mediate Self-Efficacy and Physical Activity

Self-efficacy theory proposes that girls who have confidence in their capability to be physically active will perceive fewer barriers to physical activity or be less influenced by them, be more likely to pursue perceived benefits of being physically active, and be more likely to enjoy physical activity. Self-efficacy is theorized also to influence physical activity through self-management strategies (e.g., thoughts, goals, plans, and acts) that support physical activity, but this idea has not been empirically tested

Mental health: A cause or consequence of injury? A population-based matched cohort study

BACKGROUND: While a number of studies report high prevalence of mental health problems among injured people, the temporal relationship between injury and mental health service use has not been established. This study aimed to quantify this relationship using 10 years of follow-up on a population-based cohort of hospitalised injured adults. METHODS: The Manitoba Injury Outcome Study is a retrospective population-based matched cohort study that utilised linked administrative data from Manitoba, Canada, to identify an inception cohort (1988–1991) of hospitalised injured cases (ICD-9-CM 800–995) aged 18–64 years (n = 21,032), which was matched to a non-injured population-based comparison group (n = 21,032). Pre-injury comorbidity and post-injury mental health data were obtained from hospital and physician claims records. Negative Binomial regression was used to estimate adjusted rate ratios (RRs) to measure associations between injury and mental health service use. RESULTS: Statistically significant differences in the rates of mental health service use were observed between the injured and non-injured, for the pre-injury year and every year of the follow-up period. The injured cohort had 6.56 times the rate of post-injury mental health hospitalisations (95% CI 5.87, 7.34) and 2.65 times the rate of post-injury mental health physician claims (95% CI 2.53, 2.77). Adjusting for comorbidities and pre-existing mental health service use reduced the hospitalisations RR to 3.24 (95% CI 2.92, 3.60) and the physician claims RR to 1.53 (95% CI 1.47, 1.59). CONCLUSION: These findings indicate the presence of pre-existing mental health conditions is a potential confounder when investigating injury as a risk factor for subsequent mental health problems. Collaboration with mental health professionals is important for injury prevention and care, with ongoing mental health support being a clearly indicated service need by injured people and their families. Public health policy relating to injury prevention and control needs to consider mental health strategies at the primary, secondary and tertiary level