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The purpose of this paper is to explore the effects of the camber on gliding and hovering performance of two-dimensional corrugated airfoils. While the flying mechanism of natural flyers remains a myth up to nowadays, the simulation serves as a minor step toward understanding the steady and unsteady aerodynamics of the dragonfly flight.

The lattice Boltzmann method is used to simulate the flow past the cambered corrugated dragonfly airfoil at low Reynolds numbers. For gliding flight, the maximum camber, the distance of the location of maximum camber point from the leading edge and Reynolds number are regarded as control variables; for hovering flight, the maximum camber, the flapping amplitude and trajectory are considered as control variables. Then corresponding simulations are performed to evaluate the implications of these factors.

Greater gliding ratio can be reached by increasing the maximum camber of the dragonfly wing section. When the location of the maximum camber moves backward along the wing chord, large scale flow separation can be delayed. These two effects result in better gliding performances. For hovering performances, it is found that for different flapping amplitudes along an inclined plane, the horizontal force exerted on the airfoils increases with the camber, and the drag growths first but then drops. It is also found that the elliptic flapping trajectory is most sensitive to the camber of the cambered corrugated dragonfly wing section.

The effects of the camber on gliding and hovering performance of the cambered dragonfly wing section are explored in detail. The data obtained can be helpful when designing micro aerial vehicles.

To ensure accurate position and force control of massage robot working on human body with unknown skin characteristics, this study aims to propose a novel intelligent impedance control system.

First, a skin dynamic model (SDM) is introduced to describe force-deformation on the human body as feed-forward for force control. Then a particle swarm optimization (PSO) method combined with graph-based knowledge transfer learning (GKT) is studied, which will effectively identify personalized skin parameters. Finally, a self-tuning impedance control strategy is designed to accommodate uncertainty of skin dynamics, system delay and signal noise exist in practical applications.

Compared with traditional least square method, genetic algorithm and other kinds of PSO methods, combination of PSO and GKT is validated using experimental data to improve the accuracy and convergence of identification results. The force control is effective, although there are contour errors, control delay and noise problems when the robot does massage on human body.

Integrating GKT into PSO identification algorithm, and designing an adaptive impedance control algorithm. As a result, the robot can understand textural and biological attributes of its surroundings and adapt its planning activities to carry out a stable and accurate force tracking control during dynamic contacts between a robot and a human.

This study aims to analyse the geographical distribution of global research activities and to investigate the knowledge diffusion embodied in scientific papers.

The geographical summary of Frontiers articles displays the number of visits and categorizes where the visitors hail from. This study uses the records of 23,798 articles published in 16 Frontiers journals from 2007 to 2015 to analyse the geographical distribution of article visits at both country and city levels. The process of knowledge diffusion is investigated on the basis of the different visiting patterns of new and old papers.

Most article visits are concentrated around major metropolitan areas and some high-tech clusters. The top “visiting countries” include both developed countries and developing countries, and the USA and China are two major players. Publishing cities dominate article visits for new papers; as time passes, there is diffusion from the publishing cities to a broader area.

The data on visiting for open access articles may be generated from various repositories besides the publishers’ websites; these data are ignored, as they are not significant enough to have much influence. There is also a lack of a basic theory in the data processing of outliers in the data set. In addition, only static results are given in this paper, as the data were collected on one day, for one time. A longer time period is necessary to track the dynamic diffusion process of the observations.

Introduction of usage data will propose a novel way to analyse research activities and track knowledge diffusion.

The visiting data of articles offer a new way to investigate research activities at the city level in a detailed and timely manner, for the geographical distribution of research activities and the research resource allocation of a specific country to be explored.

This study measured the research activities of scientific papers by examining the usage data. Compared with previous studies that focused on the geographical distribution of scientific activities using publication data, citation data and even altmetrics data, usage data are at the forefront of this research. Therefore, usage data offer a fresh perspective on methodology, providing more detailed and real-time information.