This paper investigates the proportional-integral (PI) boundary feedback control for the linear hyperbolic systems of balance laws which control and output measures are located at the boundaries. We address the issue of feedback stabilization by means of PI boundary controllers. By constructing a new weighted Lyapunov function, the sufficient conditions in terms of matrix inequalities are developed for the exponential stability of closed-loop systems. These results are illustrated by the linearized Aw-Rascle-Zhang (ARZ) traffic flow model. We design a PI boundary controller to stabilize the oscillations of the traffic parameters of a freeway segment and evaluate the performance with numerical simulations.

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In order to establish an effective early warning system for landslide disasters, accurate landslide displacement prediction is the core. In this paper, a typical step-wise-characterized landslide (Caojiatuo landslide) in the Three Gorges Reservoir (TGR) area is selected, and a displacement prediction model of Extreme Learning Machine with Gray Wolf Optimization (GWO-ELM model) is proposed. By analyzing the monitoring data of landslide displacement, the time series of landslide displacement is decomposed into trend displacement and periodic displacement by using the moving average method. First, the trend displacement is fitted by the cubic polynomial with a robust weighted least square method. Then, combining with the internal evolution rule and the external influencing factors, it is concluded that the main external trigger factors of the periodic displacement are the changes of precipitation and water level in the reservoir area. Gray relational degree (GRG) analysis method is used to screen out the main influencing factors of landslide periodic displacement. With these factors as input items, the GWO-ELM model is used to predict the periodic displacement of the landslide. The outcomes are compared with the nonoptimized ELM model. The results show that, combined with the advantages of the GWO algorithm, such as few adjusting parameters and strong global search ability, the GWO-ELM model can effectively learn the change characteristics of data and has a better and relatively stable prediction accuracy.

Dendritic cells (DCs) are sentinels of the immune system and comprise two distinct subsets: conventional DCs (cDCs) and plasmacytoid DCs (pDCs). Human pDCs are distinguished from mouse pDCs phenotypically and functionally. Basic helix-loop-helix protein E2-2 is defined as an essential transcription factor for mouse pDC development, cell fate maintenance and gene programe. It is unknown whether E2-2 regulation contributes to this species-specific difference. Here we investigated the function of E2-2 in human pDCs and screened human-specific genes regulated by E2-2. Reduced E2-2 expression in human pDC cell line GEN2.2 resulted in diminished IFN-α production in response to CpG but elevated antigen presentation capacity. Gene expression profiling showed that E2-2 silence down-regulated pDC signature genes but up-regulated cDC signature genes. Thirty human-specific genes regulated by E2-2 knockdown were identified. Among these genes, we confirmed that expression of Siglec-6 was inhibited by E2-2. Further more, Siglec-6 was expressed at a higher level on a human pDC subset with drastically lower expression of E2-2. Collectively, these results highlight that E2-2 modulates pDC function in a species-specific manner, which may provide insights for pDC development and functions.