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 …

Abstract The coronavirus disease 2019 (COVID-19) pandemic markedly changed human
mobility patterns, necessitating epidemiological models that can capture the effects of these …

The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout
China. Major behavioral, clinical, and state interventions were undertaken to mitigate the …

Understanding the causes and consequences of the emergence of severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet …

Abstract The coronavirus disease 2019 (COVID-19) pandemic is straining public health
systems worldwide, and major non-pharmaceutical interventions have been implemented to …

The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000
confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 2020 …

Abstract Convolutional Neural Networks (CNNs) with Bilinear Pooling, initially in their full
form and later using compact representations, have yielded impressive performance gains …

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

The role of asymptomatic carriers in transmission poses challenges for control of the COVID-
19 pandemic. Study of asymptomatic transmission and implications for surveillance and …