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.

China strives to become a leading sports nation. Through implemented policies and programs, Chinese children and adolescents have shown notable advancements and improvements in their engagement in physical activity in recent years, indicating an overall positive trend. However, some indicators exhibit a concerning “inversion phenomenon”. This study utilizes data from three surveys conducted between 2016 and 2022 by the Active Healthy Kids Global Alliance. By comparing current ratings with those from 2016 and 2018, both cross-sectionally and longitudinally, significant obstacles in promoting physical activity and health among Chinese children and adolescents are revealed, with persistently low scores. The 2022 Global Matrix 4.0 report ranks Chinese children and adolescents 53rd out of 57 surveyed countries, with an overall average physical activity score of D. Similarly, the average score for sources of influence ranks at 53rd. Consequently, the establishment of an integrated school, family, and social sports promotion mechanism, led by the government, becomes an imperative prerequisite for enhancing the levels of physical activity and overall health among children and adolescents.

Objectives: This study was conducted to evaluate the effect of the different intensity levels of single-session aerobic exercise on serum levels of lipid peroxidation and muscle damage markers in sedentary males. Method: Fifty one sedentary healthy males aged 21.76±1.89 years were randomly divided into four groups, with one control (n=10) and three treatment groups that attended single-session aerobic exercise with low (n=14), moderate (n=14), and high (n=13) intensities. The serum levels of malondialdehyde (MDA) and creatine kinase (CK) were measured. Results: Data analysis revealed a significant effect by the intensity levels of aerobic exercise on MDA ( P =0.001) and CK ( P =0.003) post-test when the participants in the treatment groups were compared with the control. When the intensity of aerobic exercise was increased, the amount of MDA and CK was also found to be increased. Conclusion: Single-session aerobic exercise can increase the amount of MDA and CK, suggesting that low intensity level of aerobic exercise should be utilized for more adaptation, and to prevent lipid peroxidation and muscle damage in sedentary males.

Background: The combination of physical and cognitive training effectively enhances the physical function of the elderly by preventing and reducing the incidence of falls as well as increasing independence in daily activities. However, the optimal combination of strategies to achieve the best physical performance and functional capacity in healthy elderly is still being explored. Objective: This study aimed to explore effective combinations to improve physical function. Methods: A comprehensive database search was done through Web of Science, Medline, Embase and PubMed, and was supplemented with Google scholar since September 2022. Titles and abstracts were used to search for keywords, and data were extracted using the Participants; Interventions; Comparisons, and Outcomes (PICO). Results: The 23 included studies recruited subjects aged 65 and older, comprising 872 females and 497 males, while some research did not identify the gender of 216 participants. Among the included studies, 16 were of high quality while 7 were of low quality. Ten studies showed a significant improvement in gait among older adults who underwent combined physical-cognitive training, while two studies found no positive effect on dual-task gait performance. All five studies showed a significant improvement in strength. Out of the four studies conducted, only one showed no improvement in endurance. All five studies showed improved mobility, while only one study found no effect on agility. However, eight out of the eleven papers showed a significant improvement in balance for older adults who underwent combined cognitive and physical training. The three papers that effectively reduced the fear of falling were also significant. Two studies showed that those who received combined training exhibited a significantly better quality of life compared to those who did not. Conclusion: Combined motor-cognitive training is an advanced, feasible and effective method that can promote the improvement of gait, balance and overall health in the elderly. This type of training has a more significant impact on the elderly’s fall response compared to general physical or cognitive training. Additionally, it contributes to promoting functional independence.

In order to realize the intelligence of underwater robots, this exploration proposes a submersible vision system based on neurorobotics to obtain the target information in underwater camera data. This exploration innovatively proposes a method based on the convolutional neural network (CNN) to mine the target information in underwater camera data. First, the underwater functions of the manned submersible are analyzed and mined to obtain the specific objects and features of the underwater camera information. Next, the dataset of the specific underwater target image is further constructed. The acquisition system of underwater camera information of manned submersibles is designed through the Single Shot-MultiBox Detector algorithm of deep learning. Furthermore, CNN is adopted to classify the underwater target images, which realizes the intelligent detection and classification of underwater targets. Finally, the model’s performance is tested through experiments, and the following conclusions are obtained. The model can recognize underwater organisms’ local, global, and visual features. Different recognition methods have certain advantages in accuracy, speed, and other aspects. The design here integrates deep learning technology and computer vision technology and applies it to the underwater field, realizing the association of the identified biological information with the geographic information and marine information. This is of great significance to realize the multi-information fusion of manned submersibles and the intelligent field of outdoor education. The contribution of this exploration is to provide a reasonable direction for the intelligent development of outdoor diving education.