Evolution of Coordination in Social Networks: A Numerical Study

Coordination games are important to explain efficient and desirable social behavior. Here we study these games by extensive numerical simulation on networked social structures using an evolutionary approach. We show that local network effects may promote selection of efficient equilibria in both pure and general coordination games and may explain social polarization. These results are put into perspective with respect to known theoretical results. The main insight we obtain is that clustering, and especially community structure in social networks has a positive role in promoting socially efficient outcomes.

Human inhalation exposure to iron oxide particles

In the past decade, many studies have been conducted to determine the health effects induced by exposure to engineered nanomaterials (NMs). Specifically for exposure via inhalation, numerous in vitro and animal in vivo inhalation toxicity studies on several types of NMs have been published. However, these results are not easily extrapolated to judge the effects of inhaling NMs in humans, and few published studies on the human response to inhalation of NMs exist. Given the emergence of more industries utilizing iron oxide nanoparticles as well as more nanomedicine applications of superparamagnetic iron oxide nanoparticles (SPIONs), this review presents an overview of the inhalation studies that have been conducted in humans on iron oxides. Both occupational exposure studies on complex iron oxide dusts and fumes, as well as human clinical studies on aerosolized, micron-size iron oxide particles are discussed. Iron oxide particles have not been described to elicit acute inhalation response nor promote lung disease after chronic exposure. The few human clinical studies comparing inhalation of fine and ultrafine metal oxide particles report no acute changes in the health parameters measured. Taken together existing evidence suggests that controlled human exposure to iron oxide nanoparticles, such as SPIONs, could be conducted safely.

Emergence of Swiss metropole and scaling properties of urban clusters

Defining the limits of an urban agglomeration is essential both for fundamental and applied studies in quantitative and theoretical geography. A simple and consistent way for defining such urban clusters is important for performing different statistical analysis and comparisons. Traditionally, agglomerations are defined using a rather qualitative approach based on various statistical measures. This definition varies generally from one country to another, and the data taken into account are different. In this paper, we explore the use of the City Clustering Algorithm (CCA) for the agglomeration definition in Switzerland. This algorithm provides a systemic and easy way to define an urban area based only on population data. The CCA allows the specification of the spatial resolution for defining the urban clusters. The results from different resolutions are compared and analysed, and the effect of filtering the data investigated. Different scales and parameters allow highlighting different phenomena. The study of Zipf's law using the visual rank-size rule shows that it is valid only for some specific urban clusters, inside a narrow range of the spatial resolution of the CCA. The scale where emergence of one main cluster occurs can also be found in the analysis using Zipf's law. The study of the urban clusters at different scales using the lacunarity measure - a complementary measure to the fractal dimension - allows to highlight the change of scale at a given range.