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The aim of this paper is to predict the in-vivo degradation behaviour of Mg-based implants through in-vitro immersion test.

A novel placement mode arming to mimic the in-vivo situation was investigated in this work. Specimens were mounted on bones and then immersed in dynamic Hank’s solution.

The degradation behaviour of the specimen’s two sides is unequal. The bottom side which clings to the bone was isolated from solution in the early stage. During the late immersion period, there was crevice corrosion appearing on the bottom side. Weight loss and mechanical properties of specimens were also affected by the placement mode.

Placement mode reported here have guiding significance for degradation behaviour of bio-implants in the clinical study.

Placement mode reported here have guiding significance for degradation behaviour of bio-implants in the clinical study.

A novel placement mode arming to mimic the in-vivo situation was investigated in this work, which was better fit the actual in vivo immersion situation.

The purpose of this paper is to have a review on the analysis of information diffusion based on evolutionary game theory. People now get used to interact over social networks, and one of the most important functions of social networks is information sharing. Understanding the mechanisms of the information diffusion over social networks is critical to various applications including online advertisement and rumor control.

It has been shown that the graphical evolutionary game theory (EGT) is a very efficient method to study this problem.

By applying EGT to information diffusion, the authors could predict every small change in the process, get the detailed dynamics and finally foretell the stable states.

In this paper, the authors provide a general review on the evolutionary game-theoretic framework for information diffusion over social network by summarizing the results and conclusions of works using graphical EGT.