Nanostructured Superconductors

The relevant length scales for superconductivity are of the order of nanometers. By confining the superconducting condensate to such dimensions, many physical properties change substantially, and novel phenomena emerge, which are absent in the pristine material. We discuss various methods of creating artificial nanostructures by top-down approaches in metallic and copper-oxide superconductors and their applications. Such nanostructures can be used to control magnetic flux quanta in superconductors, anchoring them to engineered defects to avoid dissipation, guiding their motion, or building artificial flux-quanta arrangements. Nanopatterned superconductors are essential for creating model systems for basic research and enable building almost dissipationless and ultrafast electronic devices and highly sensitive sensors.Comment: 12 pages, 8 figures, review chapte

Modeling House Prices using Multilevel Structured Additive Regression

This paper analyzes house price data belonging to three hierarchical levels of spatial units. House selling prices with associated individual attributes (the elementary level-1) are grouped within municipalities (level-2), which form districts (level-3), which are themselves nested in counties (level-4). Additionally to individual attributes, explanatory covariates with possibly nonlinear effects are available on two of these spatial resolutions. We apply a multilevel version of structured additive regression (STAR) models to regress house prices on individual attributes and locational neighborhood characteristics in a four level hierarchical model. In multilevel STAR models the regression coefficients of a particular nonlinear term may themselves obey a regression model with structured additive predictor. The framework thus allows to incorporate nonlinear covariate effects and time trends, smooth spatial effects and complex interactions at every level of the hierarchy of the multilevel model. Moreover we are able to decompose the spatial heterogeneity effect and investigate its magnitude at different spatial resolutions allowing for improved predictive quality even in the case of unobserved spatial units. Statistical inference is fully Bayesian and based on highly efficient Markov chain Monte Carlo simulation techniques that take advantage of the hierarchical structure in the data

Long-Term Efficacy of Pulmonary Rehabilitation in Patients with Occupational Respiratory Diseases

Background: Pulmonary rehabilitation is a well-recognized treatment option in chronic obstructive lung disease improving exercise performance, respiratory symptoms and quality of life. In occupational respiratory diseases, which can be rather cost-intensive due to the compensation needs, very little information is available. Objectives: This study aims at the evaluation of the usefulness of pulmonary rehabilitation in patients with occupational respiratory diseases, partly involving complex alterations of lung function and of the sustainability of effects. Methods: We studied 263 patients with occupational respiratory diseases (asthma, silicosis, asbestosis, chronic obstructive pulmonary disease) using a 4-week inpatient rehabilitation program and follow-up examinations 3 and 12 months later. The outcomes evaluated were lung function, 6-min walking distance (6MWD), maximum exercise capacity (Wmax), skeletal muscle strength, respiratory symptoms, exacerbations and associated medical consultations, quality of life (SF-36, SGRQ), anxiety/depression (HADS) and Medical Research Council and Baseline and Transition Dyspnea Index scores. Results: Compared to baseline, there were significant (p < 0.05) improvements in 6MWD, Wmax and muscle strength immediately after rehabilitation, and these were maintained over 12 months (p < 0.05). Effects were less pronounced in asbestosis. Overall, a significant reduction in the rate of exacerbations by 35%, antibiotic therapy by 27% and use of health care services by 17% occurred within 12 months after rehabilitation. No changes were seen in the questionnaire outcomes. Conclusions: Pulmonary rehabilitation is effective even in the complex settings of occupational respiratory diseases, providing sustained improvement of functional capacity and reducing health care utilization. Copyright (C) 2012 S. Karger AG, Base