Steady-state security in distribution networks with large wind farms

© 2014, The Author(s). Aging network assets, forced and unforced outages, and the way the networks are operated in a deregulated market are of significant concerns to integrate large wind farms in a distribution network. In many cases, the constrained network capacity is a potential barrier to the large-scale integration of wind power. This paper probabilistically assesses the steady-state security in a distribution network in the presence of large wind farms. The approach incorporates active distribution network operating conditions, including intermittent power outputs, random outages, demand fluctuations, and dynamic interactions and exchanges, and then assesses the steady state security using Monte Carlo simulation. A case study is performed by integrating large wind farms into a distribution network. The results suggest that intermittent outputs of large wind farms in a distribution network can impact the steady-state security considerably. However, the level of impact of wind farms does not necessarily correlate with the installed capacity of them

The self-regulated learning of medical students in the clinical environment – a scoping review

Abstract Background Self-regulated learning is the individual’s ability to effectively use various strategies to reach their learning goals. We conducted this scoping review to explore what has been found regarding self-regulated learning in the clinical environment and how this was measured. Methods Using Arksey and O’Malley’s five-stage framework, we searched three medical and educational databases as well as Google Scholar for literature on the self-regulated learning of medical students in the clinical environment published between 1966 and February 2017. After results were screened and relevant studies were identified, the data was summarised and discursively reported. Results The search resulted in 911 articles, with 14 articles included in the scoping review after the inclusion criteria was applied. Self-regulated learning was explored in these studies in various ways including qualitative, quantitative and mixed methods. Three major findings were found: 1) levels of self-regulated learning change in the clinical environment, 2) self-regulated learning is associated with academic achievement, success in clinical skills and mental health and 3) various factors can support self-regulated learning levels in medical students. Conclusions Most of articles exploring the self-regulated learning of medical students during the clinical years have been published in the last 5 years, suggesting a growing interest in the area. Future research could explore the self-regulated learning levels of medical students during the clinical years using a longitudinal approach or through the use of novel qualitative approaches

Defining responses to therapy and study outcomes in clinical trials of invasive fungal diseases: Mycoses Study Group and European Organization for Research and Treatment of Cancer consensus criteria.

Contains fulltext : 69652.pdf (publisher's version ) (Closed access)Invasive fungal diseases (IFDs) have become major causes of morbidity and mortality among highly immunocompromised patients. Authoritative consensus criteria to diagnose IFD have been useful in establishing eligibility criteria for antifungal trials. There is an important need for generation of consensus definitions of outcomes of IFD that will form a standard for evaluating treatment success and failure in clinical trials. Therefore, an expert international panel consisting of the Mycoses Study Group and the European Organization for Research and Treatment of Cancer was convened to propose guidelines for assessing treatment responses in clinical trials of IFDs and for defining study outcomes. Major fungal diseases that are discussed include invasive disease due to Candida species, Aspergillus species and other molds, Cryptococcus neoformans, Histoplasma capsulatum, and Coccidioides immitis. We also discuss potential pitfalls in assessing outcome, such as conflicting clinical, radiological, and/or mycological data and gaps in knowledge