When All the World\u27s a Stage: The Impact of Events on News Coverage of South Africa, 1979-1985

A time series analysis was used to investigate: (1) whether a significant increase in news coverage of South Africa occurred during the critical years of 1979-1985 ; (2) whether the geographic origin and/or sociopolitical impact of events, rather than deaths per se, caused the increase; and (3) the manner in which the increase occurred. Results indicated that two symbolic events (i.e., a series of riots in twenty-one South African townships, internal to South Africa; and the awarding of the Nobel Prize to Bishop Desmond Tutu, external to South Africa) cumulatively were responsible for a significant rise in news coverage of South Africa. The relationship of these symbolic sociopolitical events to the forces that shape short-term news headlines and long-term social change in general, including the imminent demise of apartheid in particular is discussed

Assessing the performance of protective winter covers for outdoor marble statuary: pilot investigation

Outdoor statuary in gardens and parks in temperate climates has a tradition of being covered during the winter, to protect against external conditions. There has been little scientific study of the environmental protection that different types of covers provide. This paper examines environmental conditions provided by a range of covers used to protect marble statuary at three sites in the UK. The protection required depends upon the condition of the marble. Although statues closely wrapped and with a layer of insulation provide good protection, this needs to be considered against the potential physical damage of close wrapping a fragile deteriorated surface

Looking for evidence of noncompetitive behavior in Minnesota's banking industry

Banks and banking - Minnesota

Advanced nickel-cadmium batteries for geosynchronous spacecraft

A nickel cadmium battery was developed that can be operated at 80 percent depth of discharge in excess of 10 years in a geosynchronous orbit application, and has about a 30 percent weight savings per spacecraft over present nickel cadmium batteries when used with a 1000 watts eclipse load. The approach used in the development was to replace nylon separators with inert polymer impregnated zirconia, use electrochemically deposited plates in place of conventional chemically precipitated ones, and use an additive to extend negative plate lifetime. The design has undergone extensive testing using both engineering and protoflight cell configurations

The Effect of Porosity on X-ray Emission Line Profiles from Hot-Star Winds

We investigate the degree to which the nearly symmetric form of X-ray emission lines seen in Chandra spectra of early-type supergiant stars could be explained by a possibly porous nature of their spatially structured stellar winds. Such porosity could effectively reduce the bound-free absorption of X-rays emitted by embedded wind shocks, and thus allow a more similar transmission of red- vs. blue-shifted emission from the back vs. front hemispheres. For a medium consisting of clumps of size l and volume filling factor f, in which the `porosity length' h=l/f increases with local radius as h = h' r, we find that a substantial reduction in wind absorption requires a quite large porosity scale factor h' > 1, implying large porosity lengths h > r. The associated wind structure must thus have either a relatively large scale l~ r, or a small volume filling factor f ~ l/r << 1, or some combination of these. The relatively small-scale, moderate compressions generated by intrinsic instabilities in line-driving seem unlikely to give such large porosity lengths, leaving again the prospect of instead having to invoke a substantial (ca. factor 5) downward revision in assumed mass-loss rates.Comment: 6 pages in apj-emulate; 3 figures; submitted to Ap

Monitoring asthma in childhood : symptoms, exacerbations and quality of life

Acknowledgements The Task Force members and their affiliations are as follows. Paul L.P. Brand: Princess Amalia Children’s Centre, Isala Hospital, Zwolle, and UMCG Postgraduate School of Medicine, University Medical Centre and University of Groningen, Groningen, The Netherlands; Mika J. Mäkelä: Skin and Allergy Hospital, Helsinki University Hospital, Helsinki, Finland; Stanley J. Szefler: Children’s Hospital Colorado and University of Colorado Denver School of Medicine, Denver, CO, USA; Thomas Frischer: Dept of Paediatrics and Paediatric Surgery, Wilhelminenspital, Vienna, Austria; David Price: Dept of Primary Care Respiratory Medicine, Academic Primary Care, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK; Eugenio Baraldi: Women’s and Children’s Health Dept, Unit of Respiratory Medicine and Allergy, University of Padova, Padova, Italy; Kai-Hakon Carlsen: Dept of Paediatrics, Women and Children’s Division, University of Oslo, and Oslo University Hospital, Oslo, Norway; Ernst Eber: Respiratory and Allergic Disease Division, Dept of Paediatrics and Adolescence Medicine, Medical University of Graz, Graz, Austria; Gunilla Hedlin: Dept of Women’s and Children’s Health and Centre for Allergy Research, Karolinska Institutet, and Astrid Lindgren Children’s hospital, Stockholm, Sweden; Neeta Kulkarni: Leicestershire Partnership Trust and Dept of Infection, Immunity and Inflammation, University of Leicester, Leicester, UK; Christiane Lex: Dept of Paediatric Cardiology and Intensive Care Medicine, Division of Paediatric Respiratory Medicine, University Hospital Goettingen, Goettingen, Germany; Karin C. Lødrup Carlsen: Dept of Paediatrics, Women and Children’s Division, Oslo University Hospital, and Dept of Paediatrics, Faculty of Medicine, University of Oslo, Oslo, Norway; Eva Mantzouranis: Dept of Paediatrics, University Hospital of Heraklion, University of Crete, Heraklion, Greece; Alexander Moeller: Division of Respiratory Medicine, University Children’s Hospital Zurich, Zurich, Switzerland; Ian Pavord: Dept of Respiratory Medicine, University of Oxford, Oxford, UK; Giorgio Piacentini: Paediatric Section, Dept of Life and Reproduction Sciences, University of Verona, Verona, Italy; Mariëlle W. Pijnenburg: Dept Paediatrics/Paediatric Respiratory Medicine, Erasmus MC - Sophia Children’s Hospital, Rotterdam, The Netherlands; Bart L. Rottier: Dept of Pediatric Pulmonology and Allergology, GRIAC Research Institute, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; Sejal Saglani: Leukocyte Biology and Respiratory Paediatrics, National Heart and Lung Institute, Imperial College London, London, UK; Peter D. Sly: Queensland Children’s Medical Research Institute, The University of Queensland, Brisbane, Australia; Steve Turner: Dept of Paediatrics, University of Aberdeen, Aberdeen, UK; Edwina Wooler: Royal Alexandra Children’s Hospital, Brighton, UK.Peer reviewedPublisher PD

Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices

Recurrent neural networks (RNNs) with rich feature vectors of past values can provide accurate point forecasts for series that exhibit complex serial dependence. We propose two approaches to constructing deep time series probabilistic models based on a variant of RNN called an echo state network (ESN). The first is where the output layer of the ESN has stochastic disturbances and a shrinkage prior for additional regularization. The second approach employs the implicit copula of an ESN with Gaussian disturbances, which is a deep copula process on the feature space. Combining this copula with a non-parametrically estimated marginal distribution produces a deep distributional time series model. The resulting probabilistic forecasts are deep functions of the feature vector and also marginally calibrated. In both approaches, Bayesian Markov chain Monte Carlo methods are used to estimate the models and compute forecasts. The proposed deep time series models are suitable for the complex task of forecasting intraday electricity prices. Using data from the Australian National Electricity Market, we show that our models provide accurate probabilistic price forecasts. Moreover, the models provide a flexible framework for incorporating probabilistic forecasts of electricity demand as additional features. We demonstrate that doing so in the deep distributional time series model in particular, increases price forecast accuracy substantially