Transient and Long-Term Improvements in Cognitive Processes following Video Games: An Italian Cross-Sectional Study.

The aim of the present study is to compare the short- and long-term effects of video-gaming by using the same measurements. More precisely, habitual and occasional video-gamers were compared so as to analyze the long-term effects. An ABABABA design was used to analyze the short-term effects. The first A refers to baseline measurements: Visual RT, Auditory RT, Aim trainer RT, Go/No-Go RT and N-Back RT. The first B refers to 30 min of gaming, the second A refers to the measurements used in the baseline, the second B refers to 60 min of a video game, the third A refers to the same measurements used in the baseline, the third B refers to a 30-min rest, and finally, the fourth A refers to the measurements used in the baseline. Seventy participants, twenty-nine habitual video-gamers and forty-one occasional video-gamers, participated in the study. The results showed a temporary improvement of cognitive functions (Visual RT, Auditory RT, Aim trainer RT, Go/No-Go RT and N-Back RT) in the short term and a strong enhancement of cognitive functions in the long term. The results are discussed in light of Flow Theory and the automatization process. Contribution of the study: The contribution of this research is to highlight that despite there being a transient enhancement of executive and cognitive functions through the use of mobile video games in the short-term period, with a decrease of performance after a 30-min rest, there is a strong increase of cognitive performance in the long-term period. Flow Theory and the automatization process together can explain this apparent inconsistency between the positive increase of long-term performance and the transient increase of short-term performance. One limitation of the present research is that it is not possible to distinguish whether the long-term enhancements can be attributed either to continued practice in the use of video games compared to non-gamers, or to the possibility that gamers are already predisposed to video game playing. Future research should address this issue.

Covid-19 epidemic in Italy: evolution, projections and impact of government measures.

We report on the Covid-19 epidemic in Italy in relation to the extraordinary measures implemented by the Italian Government between the 24th of February and the 12th of March. We analysed the Covid-19 cumulative incidence (CI) using data from the 1st to the 31st of March. We estimated that in Lombardy, the worst hit region in Italy, the observed Covid-19 CI diverged towards values lower than the ones expected in the absence of government measures approximately 7-10 days after the measures implementation. The Covid-19 CI growth rate peaked in Lombardy the 22nd of March and in other regions between the 24th and the 27th of March. The CI growth rate peaked in 87 out of 107 Italian provinces on average 13.6 days after the measures implementation. We projected that the CI growth rate in Lombardy should substantially slow by mid-May 2020. Other regions should follow a similar pattern. Our projections assume that the government measures will remain in place during this period. The evolution of the epidemic in different Italian regions suggests that the earlier the measures were taken in relation to the stage of the epidemic, the lower the total cumulative incidence achieved during this epidemic wave. Our analyses suggest that the government measures slowed and eventually reduced the Covid-19 CI growth where the epidemic had already reached high levels by mid-March (Lombardy, Emilia-Romagna and Veneto) and prevented the rise of the epidemic in regions of central and southern Italy where the epidemic was at an earlier stage in mid-March to reach the high levels already present in northern regions. As several governments indicate that their aim is to "push down" the epidemic curve, the evolution of the epidemic in Italy supports the WHO recommendation that strict containment measures should be introduced as early as possible in the epidemic curve.

Temporary dense seismic network during the 2016 Central Italy seismic emergency for microzonation studies.

In August 2016, a magnitude 6.0 earthquake struck Central Italy, starting a devastating seismic sequence, aggravated by other two events of magnitude 5.9 and 6.5, respectively. After the first mainshock, four Italian institutions installed a dense temporary network of 50 seismic stations in an area of 260 km2. The network was registered in the International Federation of Digital Seismograph Networks with the code 3A and quoted with a Digital Object Identifier ( https://doi.org/10.13127/SD/ku7Xm12Yy9 ). Raw data were converted into the standard binary miniSEED format, and organized in a structured archive. Then, data quality and completeness were checked, and all the relevant information was used for creating the metadata volumes. Finally, the 99 Gb of continuous seismic data and metadata were uploaded into the INGV node of the European Integrated Data Archive repository. Their use was regulated by a Memorandum of Understanding between the institutions. After an embargo period, the data are now available for many different seismological studies.

Long-range dependence in earthquake-moment release and implications for earthquake occurrence probability.

Since the beginning of the 1980s, when Mandelbrot observed that earthquakes occur on 'fractal' self-similar sets, many studies have investigated the dynamical mechanisms that lead to self-similarities in the earthquake process. Interpreting seismicity as a self-similar process is undoubtedly convenient to bypass the physical complexities related to the actual process. Self-similar processes are indeed invariant under suitable scaling of space and time. In this study, we show that long-range dependence is an inherent feature of the seismic process, and is universal. Examination of series of cumulative seismic moment both in Italy and worldwide through Hurst's rescaled range analysis shows that seismicity is a memory process with a Hurst exponent H ≈ 0.87. We observe that H is substantially space- and time-invariant, except in cases of catalog incompleteness. This has implications for earthquake forecasting. Hence, we have developed a probability model for earthquake occurrence that allows for long-range dependence in the seismic process. Unlike the Poisson model, dependent events are allowed. This model can be easily transferred to other disciplines that deal with self-similar processes.