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This article aims to elaborate the recent research status of perioperative nutrition optimization, in order to help clinical practice.

Accurate prediction of photovoltaic power generation is of great significance to stable operation of power system. To improve the prediction accuracy of photovoltaic power, a photovoltaic power generation prediction machine learning model based on Transformer model is proposed in this paper. In this paper, the basic principle of Transformer model is introduced. Correlation analysis tools such as Pearson correlation coefficient and Spearman correlation coefficient are introduced to analyze the correlation between various factors and power generation in the photovoltaic power generation process. Then, the prediction results of traditional machine learning models and the Transformer model proposed in this paper were compared and analyzed for errors. The results show that: for long-term prediction tasks such as photovoltaic power generation prediction, Transformer model has higher prediction accuracy than traditional machine learning models. Moreover, compared with BP, LSTM and Bi-LSTM models, the Mean Square Error (MSE) of Transformer model decreases by 70.16%, 69.32% and 62.88% respectively in short-term prediction, and the Mean Square Error (MSE) of Transformer model decreases by 63.58%, 51.02% and 38.3% respectively in long-term prediction, which has good prediction effect. In addition, compared with the long-term prediction effect of Informer model, Transformer model has higher prediction accuracy.

For the lack of command and control modeling principles and mechanisms in the current end-to-end campaign tactical level simulation for unmanned air combat, this paper systematically combs and studies the recent research in unmanned air campaign tactical simulation. Combined with the relevant research, this paper explored the principles and methods of different C2 modeling at different simulation levels and established a C2 simulation system suitable for the characteristics of CISE in unmanned air combat. Further, theoretical and practical guidance is provided for innovative demonstration and evaluation methods of CISE through the effectiveness evaluation support of unmanned air combat tasks.

Columnar jointed basalt (CJB) is a kind of jointed rock with a polygonal cylinder mosaic structure that has complex mechanical properties such as discontinuity and heterogeneity. The typical geological structure of the CJB is the intercolumnar joint plane and the implicit joint plane, which obviously affect the mechanical properties of the rock mass. Controlling the unloading relaxation of the CJB is a key problem during the construction of underground engineering. In this paper, in-situ acoustic wave and panoramic borehole camera measurements were carried out in the cavern of the Baihetan project to understand the failure mechanism of the collapse of the CJB. It was quite clear that the evolution of the excavation damage zone (EDZ) of the CJB depends on the time and spatial effects. The closer to the collapse zone, the greater the degree of relaxation failure of the columnar joint rock mass; the further away from the cavern perimeter, the more stable the surrounding rock. The correction between wave velocity and cracks in the rock mass was also discussed. This field test and theoretical analysis can provide a reference for studying the failure mechanism and control measures of CJB in underground caverns under high geostress.

The U-steel support structures of underground caverns are prone to instability and failure under blast loads. The purpose of the underground cavern reinforcement is to mobilise the self-supporting capacity of the surrounding rock to resist the blast. To better understand the mechanical performance and failure mechanism of the U-steel support, the fracture process and vibration behaviour of the support structure under blast loading are investigated by the microseismic monitoring experiment. The dynamic responses of the cavern support structures under blast loading are investigated, and the potentially hazardous sections of the U-steel support structure are revealed by the theoretical analysis. The microseismic monitoring results show that the blast induced microseismic events are concentrated in the arch shoulder of the small chainage, correspondingly the U-steel structures in this region have been partially extruded and deformed. The failure mechanism of the supporting structure is presented. In order to effectively inhibit the internal fracture evolution or macroscopic failure of the rock mass, the synergetic reinforcement scheme of the structures is proposed. The results of the research can be used as a reference for the design and control method of the U-steel support in similar projects.