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Showing papers by "Francesco Carotenuto published in 2019"



Posted ContentDOI
TL;DR: A mobile App for Android devices which can receive the alerts generated by a network-based Early Warning system and a dedicated module to predict the expected ground shaking intensity and the available lead-time at the user position is presented.
Abstract: . A fundamental feature of any Earthquake Early Warning System is the ability of rapidly broadcast earthquake information to a wide audience of potential end users and stakeholders, in an intuitive, customizable way. Smartphones and other mobile devices are nowadays continuously connected to the internet and represent the ideal tools for earthquake alerts dissemination, to inform a large number of users about the potential damaging shaking of an impending earthquake. Here we present a mobile App (named ISNet EWApp) for Android devices which can receive the alerts generated by a network-based Early Warning system. Specifically, the app receives the earthquake alerts generated by the PRESTo EWS, which is currently running on the accelerometric stations of the Irpinia Seismic Network (ISNet) in Southern Italy. In the absence of alerts, the EWApp displays the standard bulletin of seismic events occurred within the network. In the event of a relevant earthquake, instead, the app has a dedicated module to predict the expected ground shaking intensity and the available lead-time at the user position and to provide customized messages to inform the user about the proper reaction during the alert. We first present the architecture of both network-based system and EWApp, and then and describe its essential operational modes. The app is designed in a way that is easily exportable to any other network-based early warning system.

5 citations


Journal ArticleDOI
TL;DR: In this paper, the authors studied the best-preserved Roccamonfina Devil's trail to ascertain the dynamic behavior of the individual who left the trackway and derived body mass and stature estimates for such individual, which fit perfectly with previously published figures for modern humans.
Abstract: Understanding the evolution of bipedal locomotion in humans is of paramount importance to paleoanthropologists. Such endeavor requires well-preserved dynamic evidence of fossil human locomotion we are short of. Physical models of modern human locomotion predict individuals would perform voluntary step length adjustment as a function of slope gradient in order to minimize the energetic costof locomotion while maintaining balance and reasonably comfortable gait. The famous Roccamonfina volcano “Devil’s trails”, which are Middle Pleistocene Homo fossilized trackways, provide unique opportunity to validate such predictions for fossil human individuals. We studied the best-preserved Roccamonfina Devil’s trail to ascertain the dynamic behavior of the individual who left the trackway. We found Roccamonfina’s individual moved in a way which is dynamically equivalent to modern humans, adjusting gait as to minimize energy expenditure. We derived body mass and stature estimates for such individual, which fit perfectly with previously published figures for Middle Pleistocene hominins outside Africa.

1 citations