Monthly Movements in the Australian Dollar and Real Short-term Interest Differentials: An Application of the Kalman Filter

This paper applies a rational expectations model of the real exchange rate to Australian data. Specifically, it decomposes monthly movements in Australia’s real exchange rate into a transitory and a permanent component. The transitory component is identified with changes in the unobservable ex ante short-term real interest differential. The permanent component is denoted as changes in the unobservable long-run equilibrium real exchange rate. A state space model provides the framework for the treatment of these unobservable components and the traditional assumptions of the expectations hypothesis of the term structure of interest rates and no cross-currency risk premium are relaxed. The ex ante real interest differential is found to explain very little of the month-to-month movement in the real exchange rate. However, given that the Australian data fails to unambiguously support the existence of a risk premium in the foreign exchange market, the model collapses to an uncovered interest parity relation which finds little empirical support in the literature. These results imply that the model’s assumption of rational expectations and hence, an efficient market in foreign exchange, may be inappropriate for describing the monthly variation in Australia’s real exchange rate.

Non-technical skills learning in healthcare through simulation education: Integrating the SECTORS learning model and Complexity theory

Background: Recent works have reported the SECTORS model for non-technical skills learning in healthcare. The TINSELS programme applied this model, together with complexity theory, to guide the design and piloting of a non-technical skills based simulation training programme in the context of medicines safety. Methods: The SECTORS model defined learning outcomes. Complexity Theory led to a simulation intervention that employed authentic multi-professional learner teams, included planned and unplanned disturbances from the norm and used a staged debrief to encourage peer observation and learning. Assessment videos of non-technical skills in each learning outcome were produced and viewed as part of a Non-Technical Skills Observation Test (NOTSOT) both pre and post intervention. Learner observations were assessed by two researchers and statistical difference investigated using a student’s t-test Results: The resultant intervention is described and available from the authors. 18 participants were recruited from a range of inter-professional groups and were split into two cohorts. There was a statistically significant improvement (P=0.0314) between the Mean (SD) scores for the NOTSOT pre course 13.9 (2.32) and post course 16.42 (3.45). Conclusions: An original, theoretically underpinned, multi-professional, simulation based training programme has been produced by the integration of the SECTORS model for non-technical skills learning the complexity theory. This pilot work suggests the resultant intervention can enhance nontechnical skills

Challenging Solitary Confinement Through State Constitutions

Eighth Amendment jurisprudence has resulted in limited scrutiny of solitary confinement despite the known harms associated with the practice. The two-part test established by the federal courts to evaluate Eighth Amendment claims and limitations on challenging prison conditions under the Prison Litigation Reform Act can make it difficult to establish that solitary confinement is cruel and unusual punishment. State constitutional challenges to solitary confinement are underexplored. Nearly all state constitutions contain an equivalent provision to the Eighth Amendment’s prohibition on cruel and unusual punishment. State courts need not be bound by federal jurisprudence in interpreting the scope of the state provision. Some state constitutions also contain additional provisions such as requiring safe and comfortable prisons, recognizing the principles of reformation and rehabilitation, prohibiting unnecessary rigor, or recognizing individual dignity, which might enable even greater judicial scrutiny of solitary confinement. This Article explores those provisions and the justifications for developing independent state court jurisprudence relating to solitary confinement

Gay men, Gaydar and the commodification of difference

Purpose To investigate ICT mediated inclusion and exclusion in terms of sexuality through a study of a commercial social networking website for gay men Design/methodology/approach The paper uses an approach based on technological inscription and the commodification of difference to study Gaydar, a commercial social networking site. Findings Through the activities, events and interactions offered by Gaydar, we identify a series of contrasting identity constructions and market segmentations which are constructed through the cyclic commodification of difference. These are fuelled by a particular series of meanings attached to gay male sexualities which serve to keep gay men positioned as a niche market. Research limitations/implications The research centres on the study of one, albeit widely used, website with a very specific set of purposes. The study offers a model for future research on sexuality and ICTs. Originality/value This study places sexuality centre stage in an ICT mediated environment and provides insights into the contemporary phenomenon of social networking. As a sexualized object, Gaydar presents a semiosis of politicized messages that question heteronormativity while simultaneously contributing to the definition of an increasingly globalized, commercialized and monolithic form of gay male sexuality defined against ICT

Neonatal Seizure Detection using Convolutional Neural Networks

This study presents a novel end-to-end architecture that learns hierarchical representations from raw EEG data using fully convolutional deep neural networks for the task of neonatal seizure detection. The deep neural network acts as both feature extractor and classifier, allowing for end-to-end optimization of the seizure detector. The designed system is evaluated on a large dataset of continuous unedited multi-channel neonatal EEG totaling 835 hours and comprising of 1389 seizures. The proposed deep architecture, with sample-level filters, achieves an accuracy that is comparable to the state-of-the-art SVM-based neonatal seizure detector, which operates on a set of carefully designed hand-crafted features. The fully convolutional architecture allows for the localization of EEG waveforms and patterns that result in high seizure probabilities for further clinical examination.Comment: IEEE International Workshop on Machine Learning for Signal Processin

Neural indicators of fatigue in chronic diseases : A systematic review of MRI studies

The authors would like to thank the Sir Jules Thorn Charitable Trust for their financial support.Peer reviewedPublisher PD