A Simplified Optimal Control Method for Homoclinic Bifurcations

A simplified optimal control method is presented for controlling or suppressing homoclinic bifurcations of general nonlinear oscillators with one degree-of-freedom. The simplification is based on the addition of an adjustable parameter and a superharmonic excitation in the force term. By solving an optimization problem for the optimal amplitude coefficients of the harmonic and superharmonic excitations to be used as the controlled parameters, the force term as the controller can be designed. By doing so, the control gain and small optimal amplitude coefficients can be obtained at lowest cost. As the adjustable parameter decreases, a gain of some amplitude coefficient ratio is increased to the highest degree, which means that the region where homoclinic intersection does not occur will be enlarged as much as possible, leading to the best possible control performance. Finally, it is shown that the theoretical analysis is in agreement with the numerical simulations on several concerned issues including the identification of the stable and unstable manifolds and the basins of attraction.     

Delay-induced intermittent transition of synchronization in neuronal networks with hybrid synapses

We study the dependence of synchronization transitions in scale-free networks of bursting neurons with hybrid synapses on the information transmission delay and the probability of inhibitory synapses. It is shown that, irrespective of the probability of inhibitory synapses, the delay always plays a subtle role during synchronization transition of the scale-free neuronal networks. In particular, regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases. These delay-induced synchronization transitions are manifested as well-expressed minima in the measure for spatiotemporal synchrony. In addition, it is found that, for smaller and larger probability of inhibitory synapses, intermittent synchronization transition is relatively profound, while for the moderate probability of inhibitory synapses, synchronization transition seems less profound. More interestingly, it is found that as the probability of inhibitory synapses is large, regions of synchronization are upscattering.     

Impact of delays and rewiring on the dynamics of small-world neuronal networks with two types of coupling

We study synchronization transitions and pattern formation on small-world networks consisting of Morris-Lecar excitable neurons in dependence on the information transmission delay and the rewiring probability. In addition, networks formed via gap junctional connections and coupling via chemical synapses are considered separately. For gap-junctionally coupled networks we show that short delays can induce zigzag fronts of excitations, whereas long delays can further detriment synchronization due to a dynamic clustering anti-phase synchronization transition. For the synaptically coupled networks, on the other hand, we find that the clustering anti-phase synchronization can appear as a direct consequence of the prolongation of information transmission delay, without being accompanied by zigzag excitatory fronts. Irrespective of the coupling type, however, we show that an appropriate small-world topology can always restore synchronized activity if only the information transmission delays are short or moderate at most. Long information transmission delays always evoke anti-phase synchronization and clustering, in which case the fine-tuning of the network topology fails to restore the synchronization of neuronal activity.     

Optimal convergence in naming game with geography-based negotiation on small-world networks

We propose a negotiation strategy to address the effect of geography on the dynamics of naming games over small-world networks. Communication and negotiation frequencies between two agents are determined by their geographical distance in terms of a parameter characterizing the correlation between interaction strength and the distance. A finding is that there exists an optimal parameter value leading to fastest convergence to global consensus on naming. Numerical computations and a theoretical analysis are provided to substantiate our findings.     

On the boundedness of solutions of the Chen system

By constructing a suitable Lyapunov function, we show that for the system parameters in some specified regions, the solutions of the Chen system are globally bounded.     

Dynamic Self‐Assembly Adhesion of a Paraquat Droplet on a Pillar[5]arene Surface

The adhesion of herbicide droplets on leaf surfaces plays an important role in the herbicide's adsorption by crops. How to control the adhesive binding which occurs through dynamic self‐assembly between the macroscopic droplet and the surface is a challenging task. We introduce a host onto surfaces that controls the binding of guests in the paraquat droplets. The pillar[5]arene‐functional surface showed the selective binding of paraquat droplets via the host–guest interaction. The work is promising for improving the efficiency of herbicides.     

计算机自动配色预测算法研究

基于配色基础理论Ｋｕｂｅｌｋａ－Ｍｕｎｋ定律的常数形式，建立了计算机自动配色的三刺激值匹配算法，通过纺织印染自动配色预测实验表明该算法可获得色差ΔＥ小于０．１０ＣＩＥＬＡＢ的满意配方。     

Coexisting chaotic attractors in a single neuron model with adapting feedback synapse

In this paper, we consider the nonlinear dynamical behavior of a single neuron model with adapting feedback synapse, and show that chaotic behaviors exist in this model. In some parameter domain, we observe two coexisting chaotic attractors, switching from the coexisting chaotic attractors to a connected chaotic attractor, and then switching back to the two coexisting chaotic attractors. We confirm the chaoticity by simulations with phase plots, waveform plots, and power spectra.     

On stability and bifurcation of Chen’s system

This article investigates some subtle characteristics of stability and bifurcation of the chaotic Chen’s system, based on rigorous mathematical analysis and symbolic computations.