Muon spin spectroscopy: magnetism, soft matter and the bridge between the two

LS would like to acknowledge financial support from the Swiss National Science Foundation, grant numbers PBFRP2-138632 and PBFRP2-142820. AD would like to acknowledge financial support from the UK Engineering and Physical Sciences Research Council, grant number EP/G054568/1, the European Union Seventh Framework Programme project NMP3-SL- 2011-263104 ‘HINTS’ and the European Research Council project ‘Muon Spin Spectroscopy of Excited States (MuSES)’ proposal number 307593LS would like to acknowledge financial support from the Swiss National Science Foundation, grant numbers PBFRP2-138632 and PBFRP2-142820. AD would like to acknowledge financial support from the UK Engineering and Physical Sciences Research Council, grant number EP/G054568/1, the European Union Seventh Framework Programme project NMP3-SL- 2011-263104 ‘HINTS’ and the European Research Council project ‘Muon Spin Spectroscopy of Excited States (MuSES)’ proposal number 307593LS would like to acknowledge financial support from the Swiss National Science Foundation, grant numbers PBFRP2-138632 and PBFRP2-142820. AD would like to acknowledge financial support from the UK Engineering and Physical Sciences Research Council, grant number EP/G054568/1, the European Union Seventh Framework Programme project NMP3-SL- 2011-263104 ‘HINTS’ and the European Research Council project ‘Muon Spin Spectroscopy of Excited States (MuSES)’ proposal number 30759

Modeling of positive and negative organic magnetoresistance in organic light-emitting diodes

Copyright 2012 by the American Physical Society. Article is available at

Easy computation of the Bayes Factor to fully quantify Occam's razor

20 pages plus 5 pages of Supplementary MaterialThe Bayes factor is the gold-standard figure of merit for comparing fits of models to data, for hypothesis selection and parameter estimation. However it is little used because it is computationally very intensive. Here it is shown how Bayes factors can be calculated accurately and easily, so that any least-squares or maximum-likelihood fits may be routinely followed by the calculation of Bayes factors to guide the best choice of model and hence the best estimations of parameters. Approximations to the Bayes factor, such as the Bayesian Information Criterion (BIC), are increasingly used. Occam's razor expresses a primary intuition, that parameters should not be multiplied unnecessarily, and that is quantified by the BIC. The Bayes factor quantifies two further intuitions. Models with physically-meaningful parameters are preferable to models with physically-meaningless parameters. Models that could fail to fit the data, yet which do fit, are preferable to models which span the data space and are therefore guaranteed to fit the data. The outcomes of using Bayes factors are often very different from traditional statistics tests and from the BIC. Three examples are given. In two of these examples, the easy calculation of the Bayes factor is exact. The third example illustrates the rare conditions under which it has some error and shows how to diagnose and correct the error

Determining the influence of excited states on current transport in organic light emitting diodes using magnetic field perturbation

Copyright 2010 by the American Physical Society. Article is available at

Mental Health Stigma: What is being done to raise awareness and reduce stigma in South Africa?

Objective: Stigma plays a major role in the persistent suffering, disability and economic loss associated with mental illnesses. There is an urgent need to find effective strategies to increase awareness about mental illnesses and reduce stigma and discrimination. This study surveys the existing anti-stigma programmes in South Africa. Method: The World Health Organization’s Assessment Instrument for Mental Health Systems Version 2.2 and semi-structured interviews were used to collect data on mental health education programmes in South Africa. Results: Numerous anti-stigma campaigns are in place in both government and non-government organizations across the country. All nine provinces have had public campaigns between 2000 and 2005, targeting various groups such as the general public, youth, different ethnic groups, health care professionals, teachers and politicians. Some schools are setting up education and prevention programmes and various forms of media and art are being utilized to educate and discourage stigma and discrimination. Mental health care users are increasingly getting involved through media and talks in a wide range of settings. Yet very few of such activities are systematically evaluated for the effectiveness and very few are being published in peer-review journals or in reports where experiences and lessons can be shared and potentially applied elsewhere. Conclusion: A pool of evidence for anti-stigma and awareness-raising strategies currently exists that could potentially make a scientific contribution and inform policy in South Africa as well as in other countries.Key words: Mental Health; Stigma; South Africa; Mental Health Promotio