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This paper aims to provide insights into the phenomenon of knowledge flows. We study one of the main mechanisms through which these flows occur, namely, the mobility of highly-skilled individuals. We focus on the geographical mobility of inventors across European regions. Thus, patent data are used to trace the pattern of inventors' mobility across European regions, to track down focuses of attraction of talent throughout the continent, and to study their distribution across the space. To do so, we gather information from PCT patent documents and we first match the names which seemed to belong to the same inventor and then we create a new algorithm to decide whether each patent applied for under each name belongs to the same inventor. [ABSTRACT FROM AUTHOR]

Therapy for polymyalgia rheumatica (PMR) varies widely in clinical practice as international recommendations for PMR treatment are not currently available. In this paper, we report the 2015 European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) recommendations for the management of PMR. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology as a framework for the project. Accordingly, the direction and strength of the recommendations are based on the quality of evidence, the balance between desirable and undesirable effects, patients' and clinicians' values and preferences, and resource use. Eight overarching principles and nine specific recommendations were developed covering several aspects of PMR, including basic and follow-up investigations of patients under treatment, risk factor assessment, medical access for patients and specialist referral, treatment strategies such as initial glucocorticoid (GC) doses and subsequent tapering regimens, use of intramuscular GCs and disease modifying anti-rheumatic drugs (DMARDs), as well as the roles of non-steroidal anti-rheumatic drugs and non-pharmacological interventions. These recommendations will inform primary, secondary and tertiary care physicians about an international consensus on the management of PMR. These recommendations should serve to inform clinicians about best practices in the care of patients with PMR. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop European League Against Rheumatism/American College of Rheumatology classification criteria for polymyalgia rheumatica (PMR). Candidate criteria were evaluated in a 6-month prospective cohort study of 125 patients with new-onset PMR and 169 non-PMR comparison subjects with conditions mimicking PMR. A scoring algorithm was developed based on morning stiffness >45 minutes (2 points), hip pain/limited range of motion (1 point), absence of rheumatoid factor and/or anti-citrullinated protein antibody (2 points), and absence of peripheral joint pain (1 point). A score ≥4 had 68% sensitivity and 78% specificity for discriminating all comparison subjects from PMR. The specificity was higher (88%) for discriminating shoulder conditions from PMR and lower (65%) for discriminating RA from PMR. Adding ultrasound, a score ≥5 had increased sensitivity to 66% and specificity to 81%. According to these provisional classification criteria, patients ≥50 years old presenting with bilateral shoulder pain, not better explained by an alternative pathology, can be classified as having PMR in the presence of morning stiffness >45 minutes, elevated C-reactive protein and/or erythrocyte sedimentation rate, and new hip pain. These criteria are not meant for diagnostic purposes. [ABSTRACT FROM AUTHOR]

Aim Spatial modelling techniques are increasingly used in species distribution modelling. However, the implemented techniques differ in their modelling performance, and some consensus methods are needed to reduce the uncertainty of predictions. In this study, we tested the predictive accuracies of five consensus methods, namely Weighted Average (WA), Mean(All), Median(All), Median(PCA), and Best, for 28 threatened plant species. Location North-eastern Finland, Europe. Methods The spatial distributions of the plant species were forecasted using eight state-of-the-art single-modelling techniques providing an ensemble of predictions. The probability values of occurrence were then combined using five consensus algorithms. The predictive accuracies of the single-model and consensus methods were assessed by computing the area under the curve (AUC) of the receiver-operating characteristic plot. Results The mean AUC values varied between 0.697 (classification tree analysis) and 0.813 (random forest) for the single-models, and from 0.757 to 0.850 for the consensus methods. WA and Mean(All) consensus methods provided significantly more robust predictions than all the single-models and the other consensus methods. Main conclusions Consensus methods based on average function algorithms may increase significantly the accuracy of species distribution forecasts, and thus they show considerable promise for different conservation biological and biogeographical applications. [ABSTRACT FROM AUTHOR]

Summary: 1. Ellenberg’s indicator values scale the flora of a region along gradients reflecting light, temperature, continentality, moisture, soil pH, fertility and salinity. They can be used to monitor environmental change. 2. Ellenberg values can be extended from central Europe, for which they were defined, to nearby parts of Europe. Given a database of quadrat samples, they can be repredicted by a simple algorithm consisting of two-way weighted averaging, followed by local regression. 3. A database of British samples was assembled from two large surveys. Ellenberg values were repredicted. 4. Except for the indicator of continentality, the correlation of repredicted and original values was in the range 0·72 (light) to 0·91 (moisture). The continentality indicator could not be adequately repredicted by the algorithm, and is unusable in Britain. 5. Discrepancies between original and repredicted values can be attributed to various causes, including wrong original values, differing ecological requirements in Britain and central Europe, biased sampling of the British range of habitats, and the occurrence of small plants in shaded or basic microhabitats within well illuminated or predominantly acid quadrats. 6. The repredicted values were generally reliable, but a small proportion was clearly wrong. Wrong values were due to either inadequate sampling of species’ realized niches in Britain or sampling with quadrats that were too large and included species that were not close associates. [ABSTRACT FROM AUTHOR]