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It was pointed out that industrial development of Chinese mine Internet of things developed swiftly. The govemment makes development plan and relevant policies. The govemment invests much capital in the industrial development of mine Internet of things, and makes relevant standards. Application effect of mine Internet of things technology appears preliminarily. The industrial agglomeration has a better tendency. Some questions of the industrial development were analyzed. For example, conceptual hysteresis causes to low positivity, mine Internet of things technology is instability without technical standard, mine management system is inperfect, the whole competitiveness of the industry is weak and relevant enterprise scale is smaller, etc. Some industrial development countermeasures of mine Internet of things were proposed. For example, innovating the idea and making new strategic plan, breaking out key frontier technologies and building industrial ecology by using autonomous technology, invovating business model for the industrial development of mine Internet of things through market, etc.

Aim: To explore the experiences of nurses' work stress related to COVID‐19 regular epidemic prevention and control in China. Background: The global COVID‐19 epidemic is still severe, and China's ongoing regular epidemic prevention and control still cannot be relaxed, which places demands on nurses. Methods: Thirty nurses and eight nurse managers were interviewed using semistructured in‐depth interviews, and the data were analysed by the Colaizzi seven‐step analysis method. Results: Four themes were extracted as follows: environmental factors, organizational factors, personal factors and positive factors in coping with stress. Conclusions: Nursing managers should pay attention to construction of the first‐line departments of regular epidemic prevention and control. The shortage of nurses' human resources and the increase of nurse–patient conflicts are problems that need to be solved urgently. In addition, this research also emphasizes the importance of promoting nurses' stress‐related growth and thinking about the possibility of reform. Implications for Nursing Management: The construction of the hospital environment and increasing the resilience of nursing teams require attention. We should attach importance to the training of nurses' communication skills and provide sufficient organizational support and economic guarantees for nurses. Finally, perhaps we should also consider whether it is necessary to reform the relevant hospital systems and how to reform them. [ABSTRACT FROM AUTHOR]

Health literacy refers to the ability of individuals to obtain and understand health information and use it to maintain and promote their own health. This paper manages to make predictions toward its development degree in society with use of a big data-driven statistical learning method. Actually, such results can be analyzed by discovering latent rules from massive public textual contents. As a result, this paper proposes a deep information fusion-based smart prediction approach for health literacy. Specifically, the latent Dirichlet allocation (LDA) and convolutional neural network (CNN) structures are utilized as the basic backbone to understand semantic features of textual contents. The feature learning results of LDA and CNN can be then mapped into prediction results via following multi-dimension computing structures. After constructing the CNN model, we can input health information into the model for feature extraction. The CNN model can automatically learn valuable features from raw health information through multi-layer convolution and pooling operations. These characteristics may include lifestyle habits, physiological indicators, biochemical indicators, etc., reflecting the patient's health status and disease risk. After extracting features, we can train the CNN model through a training set and evaluate the performance of the model using a test set. The goal of this step is to optimize the parameters of the model so that it can accurately predict health information. We can use common evaluation indicators such as accuracy, precision, recall, etc. to evaluate the performance of the model. At last, some simulation experiments are conducted on real-world data collected from famous international universities. The case study analyzes health literacy difference between China of developed countries. Some prediction results can be obtained from the case study. The proposed approach can be proved effective from the discussion of prediction results.