Ricerc@Sapienza

The protein phosphatase 2A (PP2A) is a conserved heterotrimeric enzyme that regulates several cellular processes including

Natural background radiation of Earth and cosmic rays played a relevant role during the evolution of living organisms. However, how chronic low doses of radiation can affect biological processes is still unclear. Previous data have indicated that cells grown at the Gran Sasso Underground Laboratory (LNGS, L'Aquila) of National Institute of Nuclear Physics (INFN) of Italy, where the dose rate of cosmic rays and neutrons is significantly reduced with respect to the external environment, elicited an impaired response against endogenous damage as compared to cells grown outside LNGS.

The measurement of the mental workload during real tasks by means of neurophysiological signals is still challenging. The employment of Machine Learning techniques has allowed a step forward in this direction, however, most of the work has dealt with binary classification. This study proposed to examine the surveys already performed in the context of EEG-based workload classification and to test different machine learning algorithms on real multitasking activity like the Air Traffic Management.

Vigilance degradation usually causes significant performance decrement. It is also considered the major factor causing the out-of-the-loop phenomenon (OOTL) occurrence. OOTL is strongly related to a high level of automation in operative contexts such as the Air Traffic Management (ATM), and it could lead to a negative impact on the Air Traffic Controllers’ (ATCOs) engagement. As a consequence, being able to monitor the ATCOs’ vigilance would be very important to prevent risky situations.