Umani e umanoidi

In questi ultimi anni, con l’incalzare della globalizzazione, della rivoluzione digitale, della bioingegneria, dell’automazione, dell’intelligenza artificiale e altro ancora, l’essere umano è stato sottoposto a molteplici sollecitazioni che ne stanno “muovendo” il profilo. I confini di ciò che sarebbe proprio dell’uomo sono in vario modo messi in discussione. In tale contesto diviene necessaria, perfino urgente, una ricognizione del concetto di umanità, con uno sguardo il più possibile ampio, impegnato con i diversi fronti delle sfide in corso. È questo il tentativo del presente volume: contribuire a una riflessione sistematica sul complesso di problemi racchiusi nell’antica e nuova questione dell’identità umana. Il volume contiene saggi di: L. Bianchin, É. Bimbenet, A. Cera, G. Cusinato, C. Di Martino, J. Fischer, F. Gambardella, L. Guidetti, S. Hobuß, A. Martins, E. Mazzarella, F. G. Menga, G. Pezzano, R. Redaelli, C. Resta, M. Russo, L. Vanzago

THE IMPORTANCE OF DYNAMIC EFFECTS ON THE ENZYME ACTIVITY: X-RAY STRUCTURE AND MOLECULAR DYNAMICS OF ONCONASE MUTANTS.

Onconase (ONC), a member of the RNase A superfamily extracted from oocytes of Rana pipiens, is an effective cancer killer. It is currently used in treatment of various forms of cancer. ONC antitumor properties depend on its ribonucleolytic activity that is low in comparison with other members of the superfamily. The most damaging side effect from Onconase treatment is renal toxicity, which seems to be caused by the unusual stability of the enzyme. Therefore, mutants with reduced thermal stability and/or increased catalytic activity may have significant implications for human cancer chemotherapy. In this context, we have determined the crystal structures of two Onconase mutants (M23L-ONC and C87S,des103-104-ONC) and performed molecular dynamic simulations of ONC and C87S,des103-104-ONC with the aim of explaining on structural grounds the modifications of the activity and thermal stability of the mutants. The results also provide the molecular bases to explain the lower catalytic activity of Onconase compared with RNase A and the unusually high thermal stability of the amphibian enzyme

Application of Severe Weather Nowcasting to Case Studies in Air Traffic Management

Effective and time-efficient aircraft assistance and guidance in severe weather environments remains a challenge for air traffic control. Air navigation service providers around the globe could greatly benefit from specific and adapted meteorological information for the controller position, helping to reduce the increased workload induced by adverse weather. The present work proposes a radar-based nowcasting algorithm providing compact meteorological information on convective weather near airports for introduction into the algorithms intended to assist in air-traffic management. The use of vertically integrated liquid density enables extremely rapid identification and short-term prediction of convective regions that should not be traversed by aircraft, which is an essential requirement for use in tactical controller support systems. The proposed tracking and nowcasting method facilitates the anticipation of the meteorological situation around an airport. Nowcasts of centroid locations of various approaching thunderstorms were compared with corresponding radar data, and centroid distances between nowcasted and observed storms were computed. The results were analyzed with Method for the Object-Based Evaluation from the Model Evaluation tools software (MET-10.0.1, Developmental Testbed Center, Boulder, CO, US) and later integrated into an assistance arrival manager software, showing the potential of this approach for automatic air traffic assistance in adverse weather scenarios

Is an NWP-Based Nowcasting System Suitable for Aviation Operations?

The growth of air transport demand expected over the next decades, along with the increasing frequency and intensity of extreme weather events, such as heavy rainfalls and severe storms due to climate change, will pose a tough challenge for air traffic management systems, with implications for flight safety, delays and passengers. In this context, the Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM (SINOPTICA) project has a dual aim, first to investigate if very short-range high-resolution weather forecast, including data assimilation, can improve the predictive capability of these events, and then to understand if such forecasts can be suitable for air traffic management purposes. The intense squall line that affected Malpensa, the major airport by passenger traffic in northern Italy, on 11 May 2019 is selected as a benchmark. Several numerical experiments are performed with a Weather Research and Forecasting (WRF) model using two assimilation techniques, 3D-Var in WRF Data Assimilation (WRFDA) system and a nudging scheme for lightning, in order to improve the forecast accuracy and to evaluate the impact of assimilated different datasets. To evaluate the numerical simulations performance, three different verification approaches, object-based, fuzzy and qualitative, are used. The results suggest that the assimilation of lightning data plays a key role in triggering the convective cells, improving both location and timing. Moreover, the numerical weather prediction (NWP)-based nowcasting system is able to produce reliable forecasts at high spatial and temporal resolution. The timing was found to be suitable for helping Air Traffic Management (ATM) operators to compute alternative landing trajectories

Forecasting the weather to assist ATC and ATM operations

In EUROCONTROLS's recent summary report on Climate Changes Risks for European Aviation, several weather-related impacts were highlighted. There is a strong relation between highly impacting weather events and disruptions to the aviation network resulting in additional fuel consumption and CO2 emissions. In Europe, severe weather is responsible for up to 7.5% of the total en-route delays. In this respect, the H2020 Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM (SINOPTICA) project aims to demonstrate that very high-resolution and very short-range numerical weather forecasts, benefiting from the assimilation of radar data, in-situ weather stations, GNSS and lightning data, can improve the prediction of extreme weather events to the benefit of Air Traffic Management (ATM) and Air Traffic Control (ATC) operations. The assimilation of radar, GNSS, and lightning data shows a positive impact on the forecast of the convective cells for the four selected severe weather events. Moreover, two radar-based nowcasting strategies, PhaSt and RaNDeVIL, are tested to predict storm structures. Both methods are able to follow the more intense cells (VIL > 10 kg/m2) in all the case studies, as shown by the MODE results and the eye-ball verification The forecasts are used in an arrival management system (AMAN) to compute 4D trajectories around convective areas, integrate the affected aircraft into the arrival sequence, and assist air traffic controllers in implementing the approaches through just in time advisories and dynamic weather displays. With the help of real traffic scenarios and different weather models, diverse approach planning strategies are evaluated