Real networks exhibit heterogeneous nature with nodes playing far different roles in
structure and function. To identify vital nodes is thus very significant, allowing us to control …

In recent years the research community has accumulated overwhelming evidence for the
emergence of complex and heterogeneous connectivity patterns in a wide range of …

The propagations of diseases, behaviors and information in real systems are rarely
independent of each other, but they are coevolving with strong interactions. To uncover the …

The problem of reconstructing nonlinear and complex dynamical systems from measured
data or time series is central to many scientific disciplines including physical, biological …

It has long been a significant but difficult problem to identify propagation sources based on
limited knowledge of network structures and the varying states of network nodes. In practice …

With the hit of new pandemic threats, scientific frameworks are needed to understand the
unfolding of the epidemic. The use of mobile apps that are able to trace contacts is of utmost …

Identifying rumor sources in social networks plays a critical role in limiting the damage
caused by them through the timely quarantine of the sources. However, the temporal …

Detection of patient zero can give new insights to epidemiologists about the nature of first
transmissions into a population. In this Letter, we study the statistical inference problem of …

Antimicrobial-resistant organisms (AMROs) can colonize people without symptoms for long
periods of time, during which these agents can spread unnoticed to other patients in …

The rapid diffusion of hazardous information in large-flow-based social media causes great
economic losses and potential threats to society. It is crucial to infer the inner information …