On the rich-club effect in dense and weighted networks

For many complex networks present in nature only a single instance, usually of large size, is available. Any measurement made on this single instance cannot be repeated on different realizations. In order to detect significant patterns in a real-world network it is therefore crucial to compare the measured results with a null model counterpart. Here we focus on dense and weighted networks, proposing a suitable null model and studying the behaviour of the degree correlations as measured by the rich-club coefficient. Our method solves an existing problem with the randomization of dense unweighted graphs, and at the same time represents a generalization of the rich-club coefficient to weighted networks which is complementary to other recently proposed ones.     

Ecological studies of the naturally occurring radionuclides, 137Cs and heavy metals in soil,plants and milk in surrounding of Kragujevac city,Serbia

Journal of Radioanalytical and Nuclear Chemistry - Vertical distribution of natural radionuclides, 137Cs and heavy metals were measured in soil and plants collected from Kragujevac surroundings....