Biochar with developed pore structure was prepared by using high?humidity Chinese herbal medicine wastes (CHMWs) as raw material, using the water vapor generated by its own water under a high temperature environment for physical activation，and the effects of moisture content, activation temperature and activation time on the performance of biochar were investigated. The performance of biochar was analyzed by physical adsorption instrument, Fourier transform infrared spectroscopy, scanning electron microscopy and other instruments, and the optimal reaction conditions for biochar preparation were obtained, and the activation mechanism of biochar prepared from CHMWs was discussed. The prepared biochar was used to adsorb wastewater containing Cd²⁺ and Cu²⁺, and the adsorption kinetics were discussed. The experimental results showed that under the conditions of 700 ℃ heating temperature, 60 min heating time and 50% moisture content of the CHMWs, the biochar with a specific surface area of 309.29 m²/g and a pore volume of 0.116 8 cm³/g and was obtained. The experimental results of adsorption showed that the adsorption kinetics on Cu²⁺and Cd²⁺ conformed to the quasi second order kinetic equation, and the optimal adsorption capacities of Cu²⁺ and Cd²⁺ were 20.66 mg/g and 17.41 mg/g respectively.

Traditional mechanism models of greenhouses are difficult to reflect the real greenhouse environment due to nonlinear, multivariate, and strongly coupled characteristics. In this paper, extreme learning machine (ELM), back propagation (BP) neural network, and support vector machine (SVM) are used to predict and analyze the temperature, humidity, and light intensity of the greenhouse. The results show that the predicted values of ELM model are the most similar to the real?time parameters of greenhouse environment. In order to further improve the prediction accuracy of environmental parameters in the greenhouse, the improved sparrow search algorithm (ISSA) is used to optimize ELM model in this paper. The predicted environmental parameters are in good agreement with the measured data of a greenhouse in Tianjin, which confirms the feasibility of the proposed prediction model for the control of greenhouse environment.

The infrared radiation observation experiment were carried out in the uniaxial loading process of four sandstones with different water contents. By studying the quantitative relationship between the infrared radiation information and stress of water?bearing sandstone, the influence of water on the infrared radiation characteristics of sandstone was revealed. The results show that with the increase of water content, the size of sandstone infrared anomaly area was larger, and the infrared anomaly phenomenon was more obvious. The mean value of infrared radiation counts of sandstone increased with the increase of the mean value of stress, and there was a linear relationship between them. After fitting the mean value of infrared radiation counts with the mean value of stress, it is found that the slope increases gradually with the increase of water content. The mean value of infrared radiation counts of sandstone was moderately correlated with water content in compaction and elastic stage, and highly linear correlation in plastic stage and post?peak failure stage (correlation coefficient up to 0.96).