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Every year more than 1.35 million people die for road accidents and several million suffer serious injuries, which force them to live with compromised health conditions. Over the last decades, road safety research has focused on improving modelling techniques. However, due to the lack of expertise and statistical skills, such approaches might not be used by local authorities and road managers for road safety evaluation purposes. This paper proposes an operational methodology to analyze road accidents with the aim of increasing road safety. More specifically, the methodology enables to identify the most critical road segments to prioritize economic resources allocation accordingly. by using the data collected by the Road Police Department of Lombardy Region (in Italy) from 2014 to 2018, this methodology has been successfully applied to State Road 36, which is recognized as one of the busiest roads in Italy with a very high number of accidents occurring every year. The proposed methodology may support public administrations and road managers -involved in the definition and implementation of safety measures -to reduce the number of road accidents identifying and implementing prioritized interventions. Moreover, the methodology is general enough to be applied to each segment of a generic road infrastructure.

A study of the comparative distribution of different types of bacterial populations in the sea area where the city of Marseille rejects its waste water shows that, when in contact with the marine environment, a great part of the allochthonic bacterial population undergoes physiological stress expressed by an abrupt reduction of the effectives and by weak values of the energetic charge. The presence of coliforms and streptococci in waste water lens, at important distances from discharging conduits, shows the possibility of a large diffusion for a fraction of the bacterial populations that withstand the initial stress. From mathematical analyses, an inverse correlation is revealed between detergents and the bacterial population as a whole, and between phenols and various allochthonic bacterial populations. The above results were evidenced through a sampling strategy based upon a 24-h-cycle study and a search for mathematical correlations between several biological, chemical, and physical parameters.