Existing surgical tissue adhesives on the market cannot meet the desired demand for clinical operations due to their limited adhesivity or undesired cytotoxicity. A new bioadhesive is derived from the skin secretion of Andrias davidianus (SSAD). This bioinspired SSAD has significantly stronger tissue adhesion than the fibrin glue and improved elasticity and biocompatibility when compared to the cyanoacrylate glue both ex vivo and in vivo. Additionally, the SSAD‐based adhesive decreases skin wound healing time and promotes wound regeneration and angiogenesis. The SSAD‐based adhesive is completely degradable, strongly adhesive, and easily produced from a renewable source. Based on these favorable properties, the SSAD‐based bioadhesive demonstrates potential as a surgical bioadhesive for a broad range of medical applications.

A virtual power plant takes advantage of interactive communication and energy management systems to optimize and coordinate the dispatch of distributed generation, interruptible loads, energy storage systems and battery switch stations, so as to integrate them as an entity to exchange energy with the power market. This paper studies the optimal dispatch strategy of a virtual power plant, based on a unified electricity market combining day-ahead trading with real-time trading. The operation models of interruptible loads, energy storage systems and battery switch stations are specifically described in the paper. The virtual power plant applies an optimal dispatch strategy to earn the maximal expected profit under some fluctuating parameters, including market price, retail price and load demand. The presented model is a nonlinear mixed-integer programming with inter-temporal constraints and is solved by the fruit fly algorithm.

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In this paper, an enhanced robust index model is proposed to optimize the robust level of home energy local network (HELN) due to the uncertainty of customer behavior. Numerous household appliances are considered, which are divided into three categories: 1) essential loads; 2) shiftable loads; and 3) throttleable loads. The proposed robust optimization is formulated to minimize the total energy cost and maximize the robust level and satisfaction level of end users. An enhanced robust index (RI) with the upper and lower limits of the robust level is integrated into load scheduling in the form of a cost function as well as additional constraints, to avoid excessive robust levels for some of the appliances and obtain a reasonable energy dispatch strategy. Moreover, a load shifting strategy is proposed based on a quick sort algorithm to improve the robust level and further reduce the energy cost of HELN. This paper investigates how the robust optimization strategy behaves in different demand response scenarios. Finally, the case studies and numerical results are presented to discuss the effectiveness of the proposed model through an integrative simulation approach.

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