While the rapid development of artificial intelligence has affected people's daily lives, it has also brought huge challenges to high school mathematics teaching, such as restructuring the classroom teaching structure, transforming the role of teachers, and selecting classroom teaching methods. Based on this, the article explores the application strategies of AI technology in improving knowledge introduction, improving mathematics classroom efficiency and stimulating students' learning interest, with a view to optimizing classroom teaching links, improving students' core discipline quality, and promoting the development of high school mathematics teaching informatization.

Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.

Magnesium hydroxide/melamine phosphate borate (nano MH/MPB), a novel nano-composition intumescent flame retardant, was synthesized with the in-situ reaction method from MgCl₂·6H₂O sodium hydroxide (NaOH) and melamine phosphate borate (MPB) in the absence of H₂O. The structure of the product was confirmed by EDAX IR and XRD. The effects of reaction temperature and time on the dimension of magnesium hydroxide were observed. The effects of mass ratio of magnesium hydroxide to MPB on the flame retardancy of nano-MH/MPB/EP were examined with the limiting oxygen test. The results show that the optimal condition of synthesis of MH/MPB is m_MH/m_MPB = 0.25, reacting under 75 ℃ for 30 minutes. Finally, the mechanism for flame retardancy of nano-MH/MPB/EP was pilot studied by means of IR of char layer and TG of MH/MPB.

The problem of the synthesis of new type nanomaterials in the form of nano-coatings with sub-nanometric heterogeneity has been formulated. It has been presented an analysis of influences of physical vapor deposition in ultrahigh vacuum on the process of intermixing a film with a substrate, including the results, which has been obtained under the formation of transition metal – silicon interface. The generalization of the obtained experimental results develops an approach to the development of new nano-coatings with low-dimensional heterogeneity. The principles of constructing such low-dimensional nano-coatings, their properties and possible applications are considered.