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In this paper, we present a new method for successfully simulating the dynamics of COVID-19, experimentally focusing on the third wave. This method, namely, the Method of Parallel Trajectories (MPT), is based on the recently introduced self-organized diffusion model. According to this method, accurate simulation of the dynamics of the COVID-19 infected population evolution is accomplished by considering not the total data for the infected population, but successive segments of it. By changing the initial conditions with which each segment of the simulation is produced, we achieve close and detailed monitoring of the evolution of the pandemic, providing a tool for evaluating the overall situation and the fine-tuning of the restrictive measures. Finally, the application of the proposed MPT on simulating the pandemic's third wave dynamics in Greece and Italy is presented, verifying the method's effectiveness. [ABSTRACT FROM AUTHOR]

COVID-19 has forced quarantine measures in several countries across the world. These measures have proven to be effective in signifi- cantly reducing the prevalence of the virus. To date, no effective treatment or vaccine is available. In the effort of preserving both public health and the economical and social textures, France and Italy governments have partially released lockdown measures. Here, we extrapo- late the long-term behavior of the epidemic in both countries using a susceptible-exposed-infected-recovered model, where parameters are stochastically perturbed with a lognormal distribution to handle the uncertainty in the estimates of COVID-19 prevalence and to simulate the presence of super-spreaders. Our results suggest that uncertainties in both parameters and initial conditions rapidly propagate in the model and can result in different outcomes of the epidemic leading or not to a second wave of infections. Furthermore, the presence of super- spreaders adds instability to the dynamics, making the control of the epidemic more difficult. Using actual knowledge, asymptotic estimates of COVID-19 prevalence can fluctuate of the order of 10 x 106 units in both countries. [ABSTRACT FROM AUTHOR]

We show, for the first time, the explicit form of the nonlinear partial differential equations (PDEs) subject to the correct boundary conditions that have to be satisfied by transport coefficients having a vanishing skew-symmetric piece. We also report, for the first time, the nonlinear PDEs (with the appropriate boundary conditions) for transport coefficients when the thermodynamic system is subject to two thermodynamic forces. Since the proposed PDEs have been derived without neglecting any term present in the dynamical equations (i.e., the energy, mass, and momentum balance equations), we propose them as a good candidate for describing transport in thermodynamic systems also far from equilibrium (e.g., in the turbulent regime). The preliminary test was carried out by analyzing a concrete example where Onsager's relationships manifestly disagree with experience: magnetically confined Tokamak-plasmas. More specifically, we focus our calculations to compute mass and energy transports in Frascati Tokamak Upgrade-plasmas subject to two thermodynamic forces. We show a good agreement between the theoretical predictions and the experimental data. The aim of this study is to apply our approach to the Divertor Tokamak Test Facility, to be built in Italy, and to the International Thermonuclear Experimental Reactor. [ABSTRACT FROM AUTHOR]

We consider sparse random networks of Kuramoto phase oscillators with inertia in order to mimic and investigate the dynamics emerging in high-voltage power grids. The corresponding natural frequencies are assumed to be bimodally Gaussian distributed, thus modeling the distribution of both power generators and consumers, which must be in balance. Our main focus is on the theoretical analysis of the linear stability of the frequency-synchronized state, which is necessary for the stable operation of power grids and the control of unstable synchronous states. We demonstrate by numerical simulations that unstable frequency-synchronized states can be stabilized by feedback control. Further, we extend our study to include stochastic temporal power fluctuations and discuss the interplay of topological disorder and Gaussian white noise for various model configurations and finally demonstrate that our control scheme also works well under the influence of noise. Results for synthetic Erdös–Renyi random networks with low average connectivity and with symmetric or asymmetric bimodal frequency distributions are compared with those obtained by considering a real power grid topology, namely, the grid of Italy. [ABSTRACT FROM AUTHOR]

Here, we introduce PageRank (PR) in a seismic network as an appropriate alarming clue before the occurrence of the event to be worthwhile in hazard probabilistic evaluation of earthquakes. Studying PR changes of two main shocks in Iran and Italy by means of temporal and spatial windows reveals that their PR values increase drastically before the event, while there is no trend for other considered locations and/or other time intervals. Therefore, the PR value seems to be an appropriate index of a place induction by previous events and its susceptibility for having a new earthquake. Moreover, summing over the PRs of areas close to the Italy event location and tracking this newly defined PR behavior show an increasing trend before the main shock implying that the close regions are influenced and become highly connected before the event as well as the earthquake location itself. It is also indicated that PR behavior is not necessarily correlated to the number of occurring earthquakes and is inherently the result of points connectivity and interactions. [ABSTRACT FROM AUTHOR]