Report 1
Report Title: Epidemic spreading under pathogen evolution
Time: 9:30 a.m., May 24 (Monday)
Venue: Conference Room 301, Department of Physics (Practice Building 301)
Introduction: Xiyun Zhang is an associate professor in the Department of Physics, Jinan University. His main research interests are nonlinear dynamics, complex networks and complex systems. He has published more than 20 papers in international authoritative journals such as Physical Review Letters, Physical Review E, Chaos, PLoS Computational Biology, etc., with 650 Google citations. Among them, the paper "Explosive synchronization in adaptive and multilayer networks" was selected as the Editor's Choice paper of PRL, which has been cited more than 200 times since its publication and is an ESI highly cited paper. 2014.10-2015.9, funded by the National Committee for Staying Fundamental in Nonlinear Dynamics He spent one year in the group of Prof. Arkady Pikovsky of University of Potsdam, Germany, a leader in the field, and one year in the group of Prof. Plamen Ivanov of Boston University, USA, a leading authority in physiological data analysis, as a postdoctoral researcher from 2016.8-2019.11. Over the years Dr. Xiyun Zhang has achieved good results in the fields of coupled oscillator synchronization, propagation dynamics, time series analysis, and exploring new indicators for physiological and pathological diagnosis.
Report Abstract: The human struggle against epidemics is like an arms race, in which the focus is on the competition between the development of epidemic prevention strategies and the evolution of pathogens. The recently discovered mutated neo-coronaviruses in South Africa, UK, India, etc. exhibit super-transmissibility and also put new demands on the designation of epidemic prevention strategies. Based on this, we added the stochastic variation dynamics of the pathogen to the traditional epidemic transmission dynamics and found that mutational effects can greatly influence the outcome of transmission. The presence of variation at an initial basal infection rate of R0<1 may also contribute to the eventual outbreak of the disease. By analyzing different kinetic process time scales, we find that the mutation process can promote disease outbreaks only when the rate of mutation is both fast enough (to allow the pathogen to mutate sufficiently large before the end of the outbreak) and slow enough (to allow the mutated dominant trait to be maintained by the natural selection process). Finally, through numerical simulations, we show that the effect of mutagenesis on the transmission process can be limited to the maximum extent only if the vaccination process is fast enough and the social isolation policy is strict enough.
Report II
Report title: Detection of subthreshold signals by disordered phase-enhanced coupled bistable systems
Time: 9:30 am, May 24 (Mon)
Report Location: Department of Physics Conference Room 301 (Practice Building 301)
He has published more than 20 papers as first/corresponding author in Physical Review E, IEEE Transactions on Neural Networks and Learning Systems and other journals. He has published more than 20 papers in journals such as Physical Review E, IEEE Transactions on Neural Networks and Learning Systems, etc. He has hosted and completed one National Natural Science Foundation of China.
Abstract: People marvel at the ability of many organisms to perceive weak signals from the environment, and various models have been proposed to explain their dynamical mechanisms. In this report, we introduce disordered phases in the external signals for the different distances of the individual units composing the nonlinear system to the external signal sources. We find that under certain conditions, a larger degree of disordered phase helps the nonlinear system to detect subthreshold signals. We further show that a larger degree of disordered phase creates a collective behavior with zero mean, which improves the nonlinear system's response to subthreshold signals. The research presented in this report hopefully contributes to the understanding of how biological signal processing and the design of bionic signal devices.
Report 3
Report title: Role of lurkers in the threshold-driven information spreading dynamics
Time: 9:30 am, May 24 (Monday)
Place: Department of Physics Conference Room 301 (Practice Building 301)
D. in Theoretical Physics from East China Normal University in 2013, and postdoctoral research at Central European University in Budapest, Hungary from 2013 to 2015. He was awarded the Best Student Paper Award in the 8th National Conference on Complex Networks. He has published nearly 30 papers in prestigious journals in China and abroad, including Physical Review Letters, Physical Review E, Chaos, and Science China. His current main research interests include epidemic propagation, information propagation and traffic networks on complex networks.
Report Abstract: Threshold model as a classical paradigm for studying information spreading phenomena has been well studied. The main focuses are on how the The main focuses are on how the underlying social network structure or the size of initial seeds can affect the cascading dynamics. Here, inspired by empirical observations, we extend the threshold model by taking into account the lurking nodes, who rarely In particular, we consider two different scenarios: 1. the lurkers are absolutely silent and never interact with others. 2. the lurkers would occasionally interact with their neighbors; In the first case, we demonstrate that the lurkers reduce the effective average degree of the underlying network, playing a dual role. In the latter case, we find that the stochastic dynamic behavior of lurkers could significantly promote the spreading of information.
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