Effects of higher-order interactions and impulsive vaccination for rumor propagation.

This paper introduces a rumor propagation model with saturation incidence, based on hypergraph theory. Hypergraphs can capture the higher-order interactions between nodes in a social network, where the node degree is substituted with hyperdegree. First, the threshold for rumor spreading model is obtained, the global asymptotically stable of the rumor-free equilibrium, and the global attractive and global asymptotically stable of the rumor-prevailing equilibrium are proved.

Quantifying the Resilience of Coal Energy Supply in China Toward Carbon Neutrality.

Facing the challenge of achieving the goal of carbon neutrality, China is decoupling the currently close dependence of its economy on coal use. The energy supply and demand decarbonization has substantial influence on the resilience of the coal supply. However, a general understanding of the precise impact of energy decarbonization on the resilience of the coal energy supply is still lacking.

Control of ecological networks: Abundance control or ecological regulation?

Complex ecosystems often exhibit a tipping point around which a small perturbation can lead to the loss of the basic functionality of ecosystems. It is challenging to develop a control strategy to bring ecosystems to the desired stable states. Typically, two methods are employed to restore the functionality of ecosystems: abundance control and ecological regulation.

Effects of noise on the critical points of Turing instability in complex ecosystems.

Noise is ubiquitous in natural and artificial systems. In a noisy environment, the interactions among nodes may fluctuate randomly, leading to more complicated interactions. In this paper we focus on the effects of noise and network topology on the Turing pattern of ecological networks with activator-inhibitor structure, which may be interpreted as prey-predator interactions.

Directional switches in network-organized swarming systems with delay.

Coordinated directional switches can emerge between members of moving biological groups. Previous studies have shown that the self-propelled particles model can well reproduce directional switching behaviors, but it neglects the impact of social interactions. Thus, we focus on the influence of social interactions on the ordered directional switching motion of swarming systems, in which homogeneous Erdös-Rényi networks, heterogeneous scale-free networks, networks with community structures, and real-world animal social networks have been considered.

Expression of a Cytochrome P450 Gene from Bermuda Grass in Soybean Confers Tolerance to Multiple Herbicides.

Bermuda grass () is notoriously difficult to control with some commonly used herbicides. We cloned a cytochrome P450 gene from Bermuda grass, named , which was found to confer tolerance to multiple herbicides in transgenic . These herbicides include: (1) acetolactate synthase (ALS) inhibitor herbicides nicosulfuron and penoxsulam; (2) p-hydroxyphenylpyruvate dioxygenase (HPPD)-inhibiting herbicide mesotrione; (3) synthetic auxin herbicide dicamba; (4) photosynthesis inhibitor bentazon.

Coordinating directional switches in pigeon flocks: the role of nonlinear interactions.

The mechanisms inducing unpredictably directional switches in collective and moving biological entities are largely unclear. Deeply understanding such mechanisms is beneficial to delicate design of biologically inspired devices with particular functions. Here, articulating a framework that integrates data-driven, analytical and numerical methods, we investigate the underlying mechanism governing the coordinated rotational flight of pigeon flocks with unpredictably directional switches.

epiCOLOC: Integrating Large-Scale and Context-Dependent Epigenomics Features for Comprehensive Colocalization Analysis.

High-throughput genome-wide epigenomic assays, such as ChIP-seq, DNase-seq and ATAC-seq, have profiled a huge number of functional elements across numerous human tissues/cell types, which provide an unprecedented opportunity to interpret human genome and disease in context-dependent manner. Colocalization analysis determines whether genomic features are functionally related to a given search and will facilitate identifying the underlying biological functions characterizing intricate relationships with queries for genomic regions. Existing colocalization methods leveraged diverse assumptions and background models to assess the significance of enrichment, however, they only provided limited and predefined sets of epigenomic features.

Inferring causal relationship in coordinated flight of pigeon flocks.

Collective phenomenon of natural animal groups will be attributed to individual intelligence and interagent interactions, where a long-standing challenge is to reveal the causal relationship among individuals. In this study, we propose a causal inference method based on information theory. More precisely, we calculate mutual information by using a data mining algorithm named "k-nearest neighbor" and subsequently induce the transfer entropy to obtain the causality entropy quantifying the causal dependence of one individual on another subject to a condition set consisting of other neighboring ones.

Multiplicative measurement noise can facilitate consensus of multiagent networks.

Measurement noise may have an important impact on the collective motion. Here, we investigate the consensus problem of multiagent networks with multiplicative measurement noise. Based on the stability theory of stochastic differential equations and the algebra graph theory, we obtain sufficient conditions for the consensus and nonconsensus.

Closed-Loop Control of Complex Networks: A Trade-Off between Time and Energy.

Controlling complex nonlinear networks is largely an unsolved problem at the present. Existing works focus either on open-loop control strategies and their energy consumptions or on closed-loop control schemes with an infinite-time duration. We articulate a finite-time, closed-loop controller with an eye toward the physical and mathematical underpinnings of the trade-off between the control time and energy as well as their dependence on the network parameters and structure.

Realization of consensus of multi-agent systems with stochastically mixed interactions.

In this paper, we propose a new consensus model in which the interactions among agents stochastically switch between attraction and repulsion. Such a positive-and-negative mechanism is described by the white-noise-based coupling. Analytic criteria for the consensus and non-consensus in terms of the eigenvalues of the noise intensity matrix are derived, which provide a better understanding of the constructive roles of random interactions.

3,3'-OH curcumin causes apoptosis in HepG2 cells through ROS-mediated pathway.

In this paper, we synthesized a series of curcumin analogs and evaluated their cytotoxicity against HepG2 cells. The results exhibited that the hydroxyl group at 3,3'-position play an essential role in enhancing their anti-proliferation activity. More importantly, 3,3'-hydroxy curcumin (1b) caused apoptosis in HepG2 cells with the ROS generation, which may be mainly composed of hydroxyl radicals (HO) and H2O2.

A positive role of multiplicative noise on the emergence of flocking in a stochastic Cucker-Smale system.

In this article, we investigate the flocking of a stochastic Cucker-Smale system with multiplicative measurement noise. We show that there is a noise strength, below which the flocking occurs and the convergence time is a decreasing function of noise strength. Specifically, we find a power-law relationship between the convergence time and the density of group.

Time delay can facilitate coherence in self-driven interacting-particle systems.

Directional switching in a self-propelled particle model with delayed interactions is investigated. It is shown that the average switching time is an increasing function of time delay. The presented results are applied to studying collective animal behavior.

Convergence time and speed of multi-agent systems in noisy environments.

In this paper, the finite-time consensus problem of noise-perturbed multi-agent systems with fixed and switching undirected topologies is investigated. A continuous non-Lipschitz protocol for realizing stochastic consensus in a finite time is proposed. Based on the finite-time stability theory of stochastic differential equations, sufficient conditions are obtained to ensure finite-time stochastic consensus of multi-agent systems.

Outer synchronization between two complex dynamical networks with discontinuous coupling.

In this paper, we study the outer synchronization between two complex networks with discontinuous coupling. Sufficient conditions for complete outer synchronization and generalized outer synchronization are obtained based on the stability theory of differential equations. The theoretical results show that two networks can achieve outer synchronization even if two networks are switched off sometimes and the speed of synchronization is proportional to the on-off rate.

Finite-time stochastic outer synchronization between two complex dynamical networks with different topologies.

In this paper, the finite-time stochastic outer synchronization between two different complex dynamical networks with noise perturbation is investigated. By using suitable controllers, sufficient conditions for finite-time stochastic outer synchronization are derived based on the finite-time stability theory of stochastic differential equations. It is noticed that the coupling configuration matrix is not necessary to be symmetric or irreducible, and the inner coupling matrix need not be symmetric.

Effects of noise on the outer synchronization of two unidirectionally coupled complex dynamical networks.

We study the effect of noise on the outer synchronization between two unidirectionally coupled complex networks and find analytically that outer synchronization could be achieved via white-noise-based coupling. It is also demonstrated that, if two networks have both conventional linear coupling and white-noise-based coupling, the critical deterministic coupling strength between two complex networks for synchronization transition decreases with an increase in the intensity of noise. We provide numerical results to illustrate the feasibility and effectiveness of the theoretical results.

Synchronization in coupled time-delayed systems with parameter mismatch and noise perturbation.

In this paper, a design of coupling and effective sufficient condition for stable complete synchronization and antisynchronization of a class of coupled time-delayed systems with parameter mismatch and noise perturbation are established. Based on the LaSalle-type invariance principle for stochastic differential equations, sufficient conditions guaranteeing complete synchronization and antisynchronization with constant time delay are developed. Also delay-dependent sufficient conditions for the case of time-varying delay are derived by using the Lyapunov approach for stochastic differential equations.