and Chen Z (2022) T cell immunoglobulin and mucin domain-containing protein 3 is highly expressed in patients with acute decompensated heart failure and predicts mid-term prognosis.

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Chinese ancient architecture is renowned for its unique large wooden structures and standards. However, the safety of the wooden structures in the Forbidden City has gradually deteriorated over long-term use. At present, most building safety evaluation methods rely on qualitative assessments rather than quantitative identifications. In the process of conducting safety evaluations, it is necessary to conduct sufficient analysis and judgment of building damage to determine the safety status of ancient buildings. To ensure the safety of the buildings, this study takes the Hall of Supreme Harmony in the Forbidden City as an example, using numerical simulation methods to analyze the components of Chinese wooden ancient architecture through finite element analysis, with the aim of quantitatively protecting China's traditional architectural cultural heritage. This study provides a scientific basis for the protection of China's traditional architectural cultural heritage and has high practical significance. The results showed that the deformation peak and internal force were within the allowable range according to relevant specifications.

Daily electricity consumption forecasting of home appliances can improve the accuracy and efficiency of the operation of home energy management systems. In this paper, an improved bidirectional long short memory network (BILSTM) model for predicting daily electricity consumption of household air conditioning is proposed. Firstly, and the “mutual information” is used to analyze the correlation between the daily electricity consumption of air conditioning and some environmental factors. Second, the environmental factors with strong correlation with the daily electricity consumption of air conditioning are selected as the influence factors, and these influence factors and the electricity data are taken as the characteristic input of the network. Finally, the improved bidirectional LSTM load prediction model which has been trained is used to forecast the daily electricity consumption of air conditioning. The experimental results show that the improved bidirectional LSTM network proposed in this paper can predict the daily electricity consumption of air conditioning in short term, and the maximum relative error of the predicted result is less than 5%.

No abstract