Mobility trends in Italy during the first wave of Covid-19 pandemic: analysis on Google data

During Covid-19 pandemic, Governments implemented policies to reduce the spread of the virus. In Italy, policies have been implemented starting from 9th March 2020, when in the whole country lock-down policies were adopted. In this study, we analyze mobility data to understand which were the main drivers of mobility during the first pandemic wave. In particular, we analyze Google mobility reports, to study the relative changes in mobility w.r.t. a specific baseline and to analyze several different mobility drivers. In addition, we implement Multilinear Principal Component Analysis to extract relevant features from a multidimensional object. Results show good performances in terms of explained Frobenious norm and two PCs are able to synthesize the trends; finally, the reconstructed trends are also similar to the true original ones

High storage capacity in the Hopfield model with auto-interactions - stability analysis

Recent studies point to the potential storage of a large number of patterns in the celebrated Hopfield associative memory model, well beyond the limits obtained previously. We investigate the properties of new fixed points to discover that they exhibit instabilities for small perturbations and are therefore of limited value as associative memories. Moreover, a large deviations approach also shows that errors introduced to the original patterns induce additional errors and increased corruption with respect to the stored patterns

High storage capacity in the Hopfield model with auto-interactions - stability analysis

Recent studies point to the potential storage of a large number of patterns in the celebrated Hopfield associative memory model, well beyond the limits obtained previously. We investigate the properties of new fixed points to discover that they exhibit instabilities for small perturbations and are therefore of limited value as associative memories. Moreover, a large deviations approach also shows that errors introduced to the original patterns induce additional errors and increased corruption with respect to the stored patterns

A Computational fluid dynamics study on the relative motion effects for high speed train crosswind assessment

The effect of the relative motion between a train and the surrounding infrastructure may result in critical scenarios where the infrastructure has a significant effect on the atmospheric wind. This paper analyses using a computational dynamics approach the variation of the aerodynamic force coefficients on the leading vehicle of a high speed train due to the relative motion between the train and the infrastructure. A limited increase (below 10 percent) in force coefficients are calculated and a small decrease (below 7 percent) is observed in the characteristic wind curve computation

A hybrid finite volume -- spectral element method for aeroacoustic problems

We propose a hybrid Finite Volume (FV) - Spectral Element Method (SEM) for modelling aeroacoustic phenomena based on the Lighthill's acoustic analogy. First the fluid solution is computed employing a FV method. Then, the sound source term is projected onto the acoustic grid and the inhomogeneous Lighthill's wave equation is solved employing the SEM. The novel projection method computes offline the intersections between the acoustic and the fluid grids in order to preserve the accuracy. The proposed intersection algorithm is shown to be robust, scalable and able to efficiently compute the geometric intersection of arbitrary polyhedral elements. We then analyse the properties of the projection error, showing that if the fluid grid is fine enough we are able to exploit the accuracy of the acoustic solver and we numerically assess the obtained theoretical estimates. Finally, we address two relevant aeroacoustic benchmarks, namely the corotating vortex pair and the noise induced by a laminar flow around a squared cylinder, to demonstrate in practice the effectiveness of the projection method when dealing with high order solvers. The flow computations are performed with OpenFOAM [46], an open-source finite volume library, while the inhomogeneous Lighthill's wave equation is solved with SPEED [31], an opensource spectral element library

WITHDRAWN: Experimental evidence of the wind-induced bias of precipitation gauges using Particle Image Velocimetry and particle tracking in the wind tunnel

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