Correlations between climate network and relief data

In the last few years, the scientific community has witnessed an ongoing trend of using ideas developed in the study of complex networks to analyze climate dynamics. This powerful combination, usually called climate networks, can be used to uncover non-trivial patterns of weather changes throughout the years. Here we investigate the temperature network of the North American region and show that two network characteristics, namely degree and clustering, have marked differences between the eastern and western regions. We show that such differences are a reflection of the presence of a large network community on the western side of the continent. Moreover, we provide evidence that this large community is a consequence of the peculiar characteristics of the western relief of North America

Correlation between centrality metrics and their application to the opinion model

In recent decades, a number of centrality metrics describing network properties of nodes have been proposed to rank the importance of nodes. In order to understand the correlations between centrality metrics and to approximate a high-complexity centrality metric by a strongly correlated low-complexity metric, we first study the correlation between centrality metrics in terms of their Pearson correlation coefficient and their similarity in ranking of nodes. In addition to considering the widely used centrality metrics, we introduce a new centrality measure, the degree mass. The m order degree mass of a node is the sum of the weighted degree of the node and its neighbors no further than m hops away. We find that the B_{n}, the closeness, and the components of x_{1} are strongly correlated with the degree, the 1st-order degree mass and the 2nd-order degree mass, respectively, in both network models and real-world networks. We then theoretically prove that the Pearson correlation coefficient between x_{1} and the 2nd-order degree mass is larger than that between x_{1} and a lower order degree mass. Finally, we investigate the effect of the inflexible antagonists selected based on different centrality metrics in helping one opinion to compete with another in the inflexible antagonists opinion model. Interestingly, we find that selecting the inflexible antagonists based on the leverage, the B_{n}, or the degree is more effective in opinion-competition than using other centrality metrics in all types of networks. This observation is supported by our previous observations, i.e., that there is a strong linear correlation between the degree and the B_{n}, as well as a high centrality similarity between the leverage and the degree.Comment: 20 page

EURObservational Research Programme: Regional differences and 1-year follow-up results of the Heart Failure Pilot Survey (ESC-HF Pilot)

AimsThe ESC-HF Pilot survey was aimed to describe clinical epidemiology and 1-year outcomes of outpatients and inpatients with heart failure (HF). The pilot phase was also specifically aimed at validating structure, performance, and quality of the data set for continuing the survey into a permanent Registry.MethodsThe ESC-HF Pilot study is a prospective, multicentre, observational survey conducted in 136 Cardiology Centres in 12 European countries selected to represent the different health systems across Europe. All outpatients with HF and patients admitted for acute HF on 1 day per week for eight consecutive months were included. From October 2009 to May 2010, 5118 patients were included: 1892 (37%) admitted for acute HF and 3226 (63%) patients with chronic HF. The all-cause mortality rate at 1 year was 17.4% in acute HF and 7.2% in chronic stable HF. One-year hospitalization rates were 43.9% and 31.9%, respectively, in hospitalized acute and chronic HF patients. Major regional differences in 1-year mortality were observed that could be explained by differences in characteristics and treatment of the patients.ConclusionThe ESC-HF Pilot survey confirmed that acute HF is still associated with a very poor medium-term prognosis, while the widespread adoption of evidence-based treatments in patients with chronic HF seems to have improved their outcome profile. Differences across countries may be due to different local medical practice as well to differences in healthcare systems. This pilot study also offered the opportunity to refine the organizational structure for a long-term extended European network. © 2013 The Author