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Maria Teresa Brunetti

Researcher at National Research Council

Publications -  147
Citations -  9393

Maria Teresa Brunetti is an academic researcher from National Research Council. The author has contributed to research in topics: Landslide & Cosmic ray. The author has an hindex of 33, co-authored 133 publications receiving 8025 citations. Previous affiliations of Maria Teresa Brunetti include University of Milan & University of Perugia.

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The CMS experiment at the CERN LHC

S. Chatrchyan, +3175 more
TL;DR: The Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) at CERN as mentioned in this paper was designed to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1)
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Rainfall thresholds for the possible occurrence of landslides in Italy

TL;DR: In this paper, a catalogue of 753 rainfall events that have resulted in landslides in Italy was compiled and used to determine the minimum rainfall conditions necessary for landslide occurrence in Italy and in the Abruzzo Region, central Italy.
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Lithological and seasonal control on rainfall thresholds for the possible initiation of landslides in central Italy

TL;DR: In this paper, a catalogue of 442 rainfall events with landslides in the Abruzzo, Marche, and Umbria regions, central Italy, between February 2002 and August 2010 was compiled, and the duration D (in hours) and the cumulated (total) event rainfall E (in mm) using rainfall measurements obtained from a dense network of 150 rain gauges.
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Rainfall thresholds for possible landslide occurrence in Italy

TL;DR: In this article, the authors used landslide information obtained from multiple sources and rainfall data captured by 2228 rain gauges to build a catalogue of 2309 rainfall events with shallow landslides in Italy between January 1996 and February 2014, and determined the corresponding rainfall duration D (in hours) and cumulated event rainfall E (in mm).
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Geographical landslide early warning systems

TL;DR: In this paper, a critical analysis of nine main assumptions that form the rationale for landslide forecasting and early warning is performed, and the authors conclude that operational forecast of weather-induced landslides is feasible, and it can help reduce landslide risk.