The identification of nodes occupying important positions in a network structure is crucial for the understanding of the associated real-world system. Usually, betweenness centrality (BC) is used to evaluate a node capacity to connect different graph regions. However, we argue here that this measure is not adapted for that task, as it gives equal weight to 'local' centres (i.e. nodes of high-degree central to a single region) and to 'global' bridges, which connect different communities. This distinction is important as the roles of such nodes are different in terms of the local and global organization of the network structure. In this paper, we propose a decomposition of BC into two terms, one highlighting the local contributions and the other the global ones. We call the latter bridgeness centrality and show that it is capable to specifically spot out global bridges. In addition, we introduce an effective algorithmic implementation of this measure and demonstrate its capability to identify global bridges in air transportation and scientific collaboration networks.

This study was conducted to estimate the prevalence of Salmonella spp. and their antimicrobial susceptibilities on poultry and swine farms, sampled in 2 regions in Central Vietnam. A total of 67 poultry farms and 46 swine farms were sampled in a period of 5 months (from September 2012 to January 2013). Salmonella spp. was prevalent in 46.3% and 71.7% of poultry and swine farms, respectively. Altogether, 99 non-typhoidal Salmonella were isolated and the most common serovars were Salmonella Weltevreden (19%), followed by Salmonella Typhimurium (12%) and Salmonella 4,[5],12:i:- (11%). Overall, 71 of 99 (72%) Salmonella isolates were resistant to at least one of the 14 antimicrobial agents tested. Both in poultry and swine farms, high levels of resistance were observed for ampicillin, chloramphenicol, ciprofloxacin, sulphamethoxazole and tetracycline. The presence of Salmonella isolates from poultry and swine farms which were resistant to different classes of antimicrobials suggests that alternative control measures to antimicrobials should be implemented. Moreover, an effective policy should be promoted to encourage a prudent use of these agents in animal farming in Vietnam.

Given a settled reduction in the present level of tax revenue, and by exploring a very large combinatorial space of tax structures, in this paper we employ a genetic algorithm in order to determine the 'best' structure of a real world personal income tax that allows for the maximization of the redistributive effect of the tax, while preventing all taxpayers being worse off than with the present tax structure. We take Italy as a case study.JEL Codes: C63, C81, H23, H24