Information Sciences, Journal Year: 2025, Volume and Issue: unknown, P. 122203 - 122203
Published: April 1, 2025
Language: Английский
Information Sciences, Journal Year: 2025, Volume and Issue: unknown, P. 122203 - 122203
Published: April 1, 2025
Language: Английский
Physics Reports, Journal Year: 2024, Volume and Issue: 1056, P. 1 - 70
Published: Jan. 19, 2024
Language: Английский
Citations
70Nature Reviews Physics, Journal Year: 2024, Volume and Issue: 6(8), P. 468 - 482
Published: July 5, 2024
Language: Английский
Citations
18Chaos Solitons & Fractals, Journal Year: 2023, Volume and Issue: 173, P. 113657 - 113657
Published: June 15, 2023
Language: Английский
Citations
41Chaos An Interdisciplinary Journal of Nonlinear Science, Journal Year: 2023, Volume and Issue: 33(4)
Published: April 1, 2023
Epidemic spreading processes on dynamic multiplex networks provide a more accurate description of natural than those single layered networks. To describe the influence different individuals in awareness layer epidemic spreading, we propose two-layer network-based model, including some who neglect epidemic, and explore how with properties will affect spread epidemics. The network model is divided into an information transmission disease layer. Each node represents individual connections layers. Individuals be infected lower probability compared to unaware individuals, which corresponds various prevention measures real life. We adopt micro-Markov chain approach analytically derive threshold for proposed demonstrates that affects spreading. then would process through extensive Monte Carlo numerical simulations. find high centrality significantly inhibit infectious diseases. Additionally, conjectures explanations approximately linear effect low number individuals.
Language: Английский
Citations
29Information Sciences, Journal Year: 2023, Volume and Issue: 651, P. 119723 - 119723
Published: Sept. 29, 2023
Language: Английский
Citations
21Communications Physics, Journal Year: 2024, Volume and Issue: 7(1)
Published: June 1, 2024
Abstract Higher-order structures such as simplicial complexes are ubiquitous in numerous real-world networks. Empirical evidence reveals that interactions among nodes occur not only through edges but also higher-dimensional triangles. Nevertheless, classic models the threshold model fail to capture group within these higher-order structures. In this paper, we propose a non-Markovian social contagion model, considering both and characteristics of spreading processes. We develop mean-field theory describe its evolutionary dynamics. Simulation results reveal is capable predicting steady state model. Our theoretical analyses indicate there an equivalence between Markovian contagions. Besides, find recovery can boost system resilience withstand large-scale infection or small-scale under different conditions. This work deepens our understanding behaviors contagions real world.
Language: Английский
Citations
9Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 253, P. 110497 - 110497
Published: Sept. 10, 2024
Language: Английский
Citations
9Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 181, P. 114590 - 114590
Published: Feb. 18, 2024
Language: Английский
Citations
8Journal of Computational and Applied Mathematics, Journal Year: 2025, Volume and Issue: unknown, P. 116547 - 116547
Published: Feb. 1, 2025
Language: Английский
Citations
1Chaos Solitons & Fractals, Journal Year: 2023, Volume and Issue: 171, P. 113485 - 113485
Published: April 29, 2023
Language: Английский
Citations
15