Community analysis in directed networks: in-, out-, and pseudocommunities

Multiscale modelling of magnetostatic effects on magnetic nanoparticles with application to hyperthermia

We extend a renormalization group-based (RG) coarse-graining method for micromagnetic simulations to include properly scaled magnetostatic interactions. We apply the method in simulations of dynamic hysteresis loops at clinically relevant sweep rates and at 310 K of iron oxide nanoparticles (NPs) of the kind that have been used in preclinical studies of magnetic hyperthermia. The coarse-graining method, along with a time scaling involving sweep rate and Gilbert damping parameter, allow us to span length scales from the unit cell to NPs approximately 50 nm in diameter with reasonable simulation times. For both NPs and the nanorods composing them, we report effective uniaxial anisotropy strengths and saturation magnetizations, which differ from those of the bulk materials magnetite and maghemite of which they are made, on account of the combined non-trivial effects of temperature, inter-rod exchange, magnetostatic interactions and the degree of orientational order within the nanorod composites. The effective parameters allow treating the NPs as single macrospins, and we find for the test case of calculating loops for two aligned NPs that using the dipole approximation is sufficient for distances beyond 1.5 times the NP diameter. We also present a study on relating integration time step to micromagnetic cell size, finding that the optimal time step size scales approximately linearly with cell volume.

Discovering Preferential Patterns in Sectoral Trade Networks

We analyze the patterns of import/export bilateral relations, with the aim of assessing the relevance and shape of “preferentiality” in countries’ trade decisions. Preferentiality here is defined as the tendency to concentrate trade on one or few partners. With this purpose, we adopt a systemic approach through the use of the tools of complex network analysis. In particular, we apply a pattern detection approach based on community and pseudocommunity analysis, in order to highlight the groups of countries within which most of members’ trade occur. The method is applied to two intra-industry trade networks consisting of 221 countries, relative to the low-tech “Textiles and Textile Articles” and the high-tech “Electronics” sectors for the year 2006, to look at the structure of world trade before the start of the international financial crisis. It turns out that the two networks display some similarities and some differences in preferential trade patterns: they both include few significant communities that define narrow sets of countries trading with each other as preferential destinations markets or supply sources, and they are characterized by the presence of similar hierarchical structures, led by the largest economies. But there are also distinctive features due to the characteristics of the industries examined, in which the organization of production and the destination markets are different. Overall, the extent of preferentiality and partner selection at the sector level confirm the relevance of international trade costs still today, inducing countries to seek the highest efficiency in their trade patterns.