How cooperation emerges and is stabilized has been a puzzling problem to biologists and sociologists since Darwin. One of the possible answers to this problem lies in the mobility patterns. These mobility patterns in previous works are either random-like or driven by payoff-related properties such as fitness, aspiration, or expectation. Here we address another force which drives us to move from place to place: reputation. To this end, we propose a reputation-based model to explore the effect of migration on cooperation in the contest of the prisoner's dilemma. In this model, individuals earn their reputation scores through previous cooperative behaviors. An individual tends to migrate to a new place if he has a neighborhood of low reputation. We show that cooperation is promoted for relatively large population density and not very large temptation to defect. A higher mobility sensitivity to reputation is always better for cooperation. A longer reputation memory favors cooperation, provided that the corresponding mobility sensitivity to reputation is strong enough. The microscopic perception of the effect of this mechanism is also given. Our results may shed some light on the role played by migration in the emergence and persistence of cooperation.

Recently, owing to their excellent flexibility and adaptability, skin-like pressure and strain sensors integrated with the human body have the potential for great prospects in healthcare. This review mainly focuses on the representative advances of the flexible pressure and strain sensors for health monitoring in recent years. The review consists of five sections. Firstly, we give a brief introduction of flexible skin-like sensors and their primary demands, and we comprehensively outline the two categories of design strategies for flexible sensors. Secondly, combining the typical sensor structures and their applications in human body monitoring, we summarize the recent development of flexible pressure sensors based on perceptual mechanism, the sensing component, elastic substrate, sensitivity and detection range. Thirdly, the main structure principles and performance characteristic parameters of noteworthy flexible strain sensors are summed up, namely the sensing mechanism, sensitive element, substrate, gauge factor, stretchability, and representative applications for human monitoring. Furthermore, the representations of flexible sensors with the favorable biocompatibility and self-driven properties are introduced. Finally, in conclusion, besides continuously researching how to enhance the flexibility and sensitivity of flexible sensors, their biocompatibility, versatility and durability should also be given sufficient attention, especially for implantable bioelectronics. In addition, the discussion emphasizes the challenges and opportunities of the above highlighted characteristics of novel flexible skin-like sensors.

In order to improve the prediction accuracy, this paper proposes a short-term power load forecasting method based on the improved exponential smoothing grey model. It firstly determines the main factor affecting the power load using the grey correlation analysis. It then conducts power load forecasting using the improved multivariable grey model. The improved prediction model firstly carries out the smoothing processing of the original power load data using the first exponential smoothing method. Secondly, the grey prediction model with an optimized background value is established using the smoothed sequence which agrees with the exponential trend. Finally, the inverse exponential smoothing method is employed to restore the predicted value. The first exponential smoothing model uses the 0.618 method to search for the optimal smooth coefficient. The prediction model can take the effects of the influencing factors on the power load into consideration. The simulated results show that the proposed prediction algorithm has a satisfactory prediction effect and meets the requirements of short-term power load forecasting. This research not only further improves the accuracy and reliability of short-term power load forecasting but also extends the application scope of the grey prediction model and shortens the search interval.

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Camera robots are high-speed redundantly cable-driven parallel manipulators that realize the aerial panoramic photographing. When long-span cables and high maneuverability are involved, the effects of cable sags and inertias on the dynamics must be carefully dealt with. This paper is devoted to the optimal cable tension distribution (OCTD for short) of the camera robots. Firstly, each fast varying-length cable is discretized into some nodes for computing the cable inertias. Secondly, the dynamic equation integrated with the cable inertias is set up regarding the large-span cables as catenaries. Thirdly, an iterative optimization algorithm is introduced for the cable tension distribution by using the dynamic equation and sag-to-span ratios as constraint conditions. Finally, numerical examples are presented to demonstrate the effects of cable sags and inertias on determining tensions. The results justify the convergence and effectiveness of the algorithm. In addition, the results show that it is necessary to take the cable sags and inertias into consideration for the large-span manipulators.