Normal and oblique drop impact on a solid surface is numerically analysed for yield stress fluids. A rich diversity of results are generated as a consequence of the exploration of the inertial, elastic, plastic and thixotropic features of the process, as well as the inclination of the solid surface. We show that drops of more thixotropic fluids have a higher tendency to bounce in the normal impact, and to roll or to bounce in the case of an oblique drop impact. Concerning elasticity, we found a critical value for the elastic Ohnesorge number above which no bouncing takes place. Experimental findings such as the fact that the stored energy due to the elasticity of the fluid drop plays a role similar to the stored energy of an interfacial nature in inelastic fluid drops are corroborated in the present study.

São Paulo is the most populous state in Brazil, home to around 22% of the country’s population. The total number of Covid-19-infected people in São Paulo has reached more than 1 million, while its total death toll stands at 25% of all the country’s fatalities. Joining the Brazilian academia efforts in the fight against Covid-19, in this paper we describe a unified framework for monitoring and forecasting the Covid-19 progress in the state of São Paulo. More specifically, a freely available, online platform to collect and exploit Covid-19 time-series data is presented, supporting decision-makers while still allowing the general public to interact with data from different regions of the state. Moreover, a novel forecasting data-driven method has also been proposed, by combining the so-called Susceptible-Infectious-Recovered-Deceased model with machine learning strategies to better fit the mathematical model’s coefficients for predicting Infections, Recoveries, Deaths, and Viral Reproduction Numbers. We show that the obtained predictor is capable of dealing with badly conditioned data samples while still delivering accurate 10-day predictions. Our integrated computational system can be used for guiding government actions mainly in two basic aspects: real-time data assessment and dynamic predictions of Covid-19 curves for different regions of the state. We extend our analysis and investigation to inspect the virus spreading in Brazil in its regions. Finally, experiments involving the Covid-19 advance in other countries are also given.