The digital economy is booming in China and has become the world’s largest after the United States’. Since China entered the era of the digital economy, its digital technology has radiated into various fields. This study is to examine the impact of China’s digital economy on the provision efficiency of public health institutions and the mechanism of action between them. Specifically, it measures the development level of China’s digital economy, and the provision efficiency of public health institutions from 2009 to 2018. The research also explores the relationship between China’s digital economy and its provision efficiency, through the Tobit-DEA model. An analysis of the regional heterogeneity indicated that the performance of China’s digital economy in the eastern region has a significant positive effect on improving the efficiency of the public health sector. This further confirms that the digital economy has strengthened China’s ability to deal with public health crises during the COVID-19 pandemic. A further mediation effect analysis showed that China’s digital economy optimizes the efficiency of public health provision by improving governmental performance and regulatory quality. This shows that the development of the digital economy promotes the construction of digital government, and thus improves the quality of governmental supervision and governmental performance, which has a significant positive effect on the efficiency of the supply of public health services. During the COVID-19 pandemic especially, government delivery of public health services was critical in addressing public health crises. Therefore, based on the results of our empirical analysis, this study provides policy suggestions for improving the efficiency of public health service provision in the era of the digital economy.
Talent is one of the most significant factors to promote the development of sports undertakings. The present study aimed to explore the factors affecting the identification of sports talents in China's physical education curriculum. Based on the literature review, this study puts forward a model to examine the influencing factors of sports talent identification in China's physical education curriculum using structural equation modeling and uses the structural equation modeling and factor analysis method to verify the hypothesis combined with the results of 310 effective questionnaires. The article summarizes influencing factors from four aspects, namely, physical, psychological, coach, and environmental factors. On the basis of relevant literature, the hypothesis model was established by structural equation modeling. The results show that the main factors affecting the identification of sports talents in the physical education curriculum are personal physical quality performance, psychological quality, coach's knowledge, and the identification policies of schools to sports talents. The conclusion of this study can provide guidance for the reform of the physical education curriculum, the growth of sports talents, and the development of sports talents in China.
Background Circumnutation (Darwin et al., Sci Rep 10(1):1–13, 2000) is the side-to-side movement common among growing plant appendages but the purpose of circumnutation is not always clear. Accurately tracking and quantifying circumnutation can help researchers to better study its underlying purpose. Results In this paper, a deep learning-based model is proposed to track the circumnutating flowering apices in the plant Arabidopsis thaliana from time-lapse videos. By utilizing U-Net to segment the apex, and combining it with the model update mechanism, pre- and post- processing steps, the proposed model significantly improves the tracking time and accuracy over other baseline tracking methods. Additionally, we evaluate the computational complexity of the proposed model and further develop a method to accelerate the inference speed of the model. The fast algorithm can track the apices in real-time on a computer without a dedicated GPU. Conclusion We demonstrate that the accuracy of tracking the flowering apices in the plant Arabidopsis thaliana can be improved with our proposed deep learning-based model in terms of both the racking success rate and the tracking error. We also show that the improvement in the tracking accuracy is statistically significant. The time-lapse video dataset of Arabidopsis is also provided which can be used for future studies on Arabidopsis in various takes.
Under the background of “Internet + Made in China 2025” production and education integration innovation promotion plan. According to the professional uniqueness and social needs of applied undergraduate education. Take the teaching direction of industrial robots in the field of mechanical electronics as an example. The paper proposed the teaching of professional basic courses as the basis, the professional direction of curriculum teaching as the focus, professional quality and innovative entrepreneurship education curriculum as a fundamental, three training courses for the innovation of the curriculum system. All kinds of courses include in-class courses (the first class) and extra-curricular courses (the second class), the two classes with other courses, enrich the entire teaching system. And through the series of industrial robotic laboratory construction and management model innovations, it can achieve the true experience of students’ corporate life and the wide range of students’ second classroom activities; it can cultivate excellent applied talents.
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