2016, Li, Y., Zhao, M., Mildrexler, D.J., Motesharrei, S., Mu, Q., Kalnay, E., Zhao, F., Li, S., Wang, K.

2013, Peng, H., Li, L., Kurths, J., Li, S., Yang, Y.

Nowadays, the topology of complex networks is essential in various fields as engineering, biology, physics, and other scientific fields. We know in some general cases that there may be some unknown structure parameters in a complex network. In order to identify those unknown structure parameters, a topology identification method is proposed based on a chaotic ant swarm algorithm in this paper. The problem of topology identification is converted into that of parameter optimization which can be solved by a chaotic ant algorithm. The proposed method enables us to identify the topology of the synchronization network effectively. Numerical simulations are also provided to show the effectiveness and feasibility of the proposed method.

2019, Yin, Y., Wang, J., Wang, X., Li, S., Jorgensen, M.R., Ren, J., Meng, S., Ma, L., Schmidt, O.G.

The dynamic characterization of water multilayers on oxide surfaces is hard to achieve by currently available techniques. Despite this, there is an increasing interest in the evolution of water nanostructures on oxides to fully understand the complex dynamics of ice nucleation and growth in natural and artificial environments. Here, we report the in situ detection of the dynamic evolution of nanoscale water layers on an amorphous oxide surface probed by optical resonances. In the water nanolayer growth process, we find an initial nanocluster morphology that turns into a planar layer beyond a critical thickness. In the reverse process, the planar water film converts to nanoclusters, accompanied by a transition from a planar amorphous layer to crystalline nanoclusters. Our results are explained by a simple thermodynamic model as well as kinetic considerations. Our work represents an approach to reveal the nanostructure and dynamics at the water-oxide interface using resonant light probing.