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The agricultural futures market plays an extremely important role in price discovery, hedging risks, integrating agricultural markets and promoting agricultural economic growth. China is the largest apple producer and consumer in the world. In 2017, Chinese apple futures were listed on the Zhengzhou Commodity Exchange (CZCE) as the first fruit futures contract globally. This paper aims to study the efficiency of the apple futures market by using the Wild Bootstrapping Variance Ratio model to estimate the price discovery function, the ARIMA-GARCH model to estimate the risk-hedging function, and the ARDL-ECM model to estimate the cointegration relationship of the futures and spot market. Experimental results firstly demonstrate that the apple futures market conforms to the weak-form efficiency, which indicates that it is efficient in price discovery. Secondly, the apple futures market is not of semi-strong efficiency because it generated abnormal profit margins amid China–US trade friction, climate disaster, and COVID-19; in terms of the degree of impact, the COVID-19 pandemic had the greatest impact, followed by the rainstorm disaster and trade friction. Thirdly, the results of this study indicate that the cointegration relationships exist between the futures market and the spot markets of the main producing areas. This paper is not only conducive to sustainable development of the global fresh or fruit futures market, but also has potential and practical importance for China in developing the agricultural futures market, strengthening market risk management and promoting market circulation.

Aiming at the characteristics of time-varying, time-delay and non-linearity of electric vehicle heat pump air-conditioning system, this paper presents a sliding mode control method based on RBF neural network. The RBF neural network can approximate the nonlinear function with arbitrary precision under certain conditions, and has strong self-learning and self-adaptive ability. Combining the RBF neural network with the sliding mode variable structure control not only has the anti-interference of the sliding mode control and the robustness to the parameter changes, but also effectively reduces the flutter caused by the sliding mode control. The simulation results show that the RBF neural network sliding mode control method can improve the system control accuracy, effectively weaken the chattering, and has good adaptability to the interference conditions.

The utilization of long-wave light (1000–2500 nm) in the solar spectrum is a difficulty in photocatalysis. Based on the Arrhenius equation, the activated carbon (AC)/graphitic carbon nitride (CN) composites were designed for photothermal-assisted photocatalytic water treatment. The short-wave solar energy can be converted to chemical energy on CN, and the long-wave solar energy to thermal energy by AC. The energetics and the interfacial charge transfer of activated carbon (AC)/graphitic carbon nitride (CN) composites (ACCN) were improved owing to the π bond between AC and CN. The excellent light absorption capacity (over 80%) led to higher photocatalytic reaction temperature due to the photothermal effect. The higher temperature accelerated the photocatalytic reaction and facilitates the charge transfer on ACCN. Hence, the optimal ACCN sample with good balance between photothermal and photocatalytic property could degrade 98% of sulfamerazine under simulated solar irradiation in 60 min. This work not only developed efficient and low-cost (~$1/kg) carbon-based photocatalysts with ultrahigh solar utilization, but also discussed the mechanism of photothermal effect on photocatalytic reaction.

The traditional methods of wave measurement usually adopt various sensors to realize the collection of the field wave data, which are limited by the working life of the sensors and their performance; and their ability of anti-interference is relatively weak on site. Therefore, this paper presents a new method for wave measurement. In this paper, by taking advantage of the Beidou Satellite Navigation System (BDS) and RTK technology, the single point on the sea surface is accurately located, and the three-dimensional coordinates of the point are obtained; after getting the height change sequence of the water surface, the wave parameters are obtained by the spectral estimation. The experimental results show that this method can not only measure the wave data accurately, but also has the characteristics of simple system, low cost and strong anti - interference ability.