Formation and morphology of anomalous solar circular polarization

The morphology of spectral line polarization is the most valuable observable to investigate the magnetic and dynamic solar atmosphere. However, in order to develop solar diagnosis, it is fundamental to understand the different kinds of anomalous solar signals that have been routinely found in linear and circular polarization (LP,CP). The goal of this paper has been to explain and characterize the morphology of solar CP signals by understanding the combined effect of magnetic fields, velocity gradients, and atomic orientation in general NLTE regime. To that aim, an analytical two-layer model of the polarized radiative transfer equation is developed and used to solve the NLTE problem with atomic polarization in a semi-parametric way. The formation of polarization is thus insightfully described with certain precision without resorting in MHD models or sacrifying key physical ingredients. The potential of the model for reproducing solar anomalous CP is shown with detailed calculations. The essential physical behavior of dichroism and atomic orientation is described, introducing the concepts of dichroic inversion, neutral and reinforcing medium, critic intensity spectrum, and critic source function. It is shown that the zero-crossings of the CP spectrum are useful to classify its morphology and understand its formation. This led to identify and explain the morphology of the seven most characteristics CP signals that a single (depth-resolved) scattering layer can produce. Futhermore, it is found that a minimal number of two magnetic layers along the LOS is required to fully explain anomalous solar CP signals, and that the morphology and polarity of Stokes V depends on magnetic, radiative and atomic polarities. Some implications of these results are presented through a preliminar modeling of anomalous CP signals in the Na I D and Fe I 1564.8 nm lines.Comment: 18 pages, 18 figures. Accepted for publication in A&A. Typos and language correcte

'Join Us On Our Journey': developing a new model of care for children and young people with type 1 diabetes Final report for NHS Diabetes

The aims of this research were to develop a model of care that will deliver the aspirations of the policy document, ‘Making Every Young Person with Diabetes Matter’ and improve the care provision for children and young people with Type 1 diabetes in England. Children and young people with Type 1 diabetes, their families and professionals, in nine acute trusts throughout the Yorkshire and the Humber region, participated in talking group discussions and individual interviews to find out about their experiences of diabetes care provision. Findings show that there are certain aspects of the care pathway that need to be addressed. In particular, diabetes care, resources, education, psychological support, school/college and transition were found to be the main areas of concern. Recommendations have been made indicating how current practice needs to change if the care of children and young people with Type 1 diabetes is to improve

Good Institutions are not enough: Ongoing Challenges of East German Development

A major theme in accounts of the transitional recession and delayed convergence in post-communist economies is the role of institutions. Yet via unification, East Germany had immediate access to credible, high quality institutions. This paper argues that success in a capitalist economy depends not only on high quality institutions but also on finding one’s niche in the international division of labour. East Germany’s experience highlights the long shadow cast by the period under communism over the economy’s ability to find its comparative advantage in tradeables on a scale adequate for self-sustaining growth.transition, institutions, East Germany, tradeables, convergence

German economic performance: disentangling the role of supply-side reforms, macroeconomic policy and coordinated economy institutions

Since unification, the debate about Germany's poor economic performance has focused on supply-side weaknesses, and the associated reform agenda sought to make low-skill labour markets more flexible. We question this diagnosis using three lines of argument. First, effective restructuring of the supply side in the core advanced industries was carried out by the private sector using institutions of the coordinated economy, including unions, works councils and blockholder owners. Second, the implementation of orthodox labour market and welfare state reforms created a flexible labour market at the lower end. Third, low growth and high unemployment are largely accounted for by the persistent weakness of domestic aggregate demand, rather than by the failure to reform the supply side. Strong growth in recent years reflects the successful restructuring of the core economy. To explain these developments, we identify the external pressures on companies in the context of increased global competition, the continuing value of the institutions of the coordinated market economy to the private sector and the constraints imposed on the use of stabilizing macroeconomic policy by these institutions. We also suggest how changes in political coalitions allowed orthodox labour market reforms to be implemented in a consensus political system

A Conversation with Alan Gelfand

Alan E. Gelfand was born April 17, 1945, in the Bronx, New York. He attended public grade schools and did his undergraduate work at what was then called City College of New York (CCNY, now CUNY), excelling at mathematics. He then surprised and saddened his mother by going all the way across the country to Stanford to graduate school, where he completed his dissertation in 1969 under the direction of Professor Herbert Solomon, making him an academic grandson of Herman Rubin and Harold Hotelling. Alan then accepted a faculty position at the University of Connecticut (UConn) where he was promoted to tenured associate professor in 1975 and to full professor in 1980. A few years later he became interested in decision theory, then empirical Bayes, which eventually led to the publication of Gelfand and Smith [J. Amer. Statist. Assoc. 85 (1990) 398-409], the paper that introduced the Gibbs sampler to most statisticians and revolutionized Bayesian computing. In the mid-1990s, Alan's interests turned strongly to spatial statistics, leading to fundamental contributions in spatially-varying coefficient models, coregionalization, and spatial boundary analysis (wombling). He spent 33 years on the faculty at UConn, retiring in 2002 to become the James B. Duke Professor of Statistics and Decision Sciences at Duke University, serving as chair from 2007-2012. At Duke, he has continued his work in spatial methodology while increasing his impact in the environmental sciences. To date, he has published over 260 papers and 6 books; he has also supervised 36 Ph.D. dissertations and 10 postdocs. This interview was done just prior to a conference of his family, academic descendants, and colleagues to celebrate his 70th birthday and his contributions to statistics which took place on April 19-22, 2015 at Duke University.Comment: Published at http://dx.doi.org/10.1214/15-STS521 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Learning to Detect and Track Cells for Quantitative Analysis of Time-Lapse Microscopic Image Sequences

© 2015 IEEE.Studying the behaviour of cells using time-lapse microscopic imaging requires automated processing pipelines that enable quantitative analysis of a large number of cells. We propose a pipeline based on state-of-the-art methods for background motion compensation, cell detection, and tracking which are integrated into a novel semi-automated, learning based analysis tool. Motion compensation is performed by employing an efficient nonlinear registration method based on powerful discrete graph optimisation. Robust detection and tracking of cells is based on classifier learning which only requires a small number of manual annotations. Cell motion trajectories are generated using a recent global data association method and linear programming. Our approach is robust to the presence of significant motion and imaging artifacts. Promising results are presented on different sets of in-vivo fluorescent microscopic image sequences