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Ammonium nitrogen (NH4+-N) is one of the main forms of nitrogen absorbed and utilized by plants, and mastering the regulatory mechanism of plant ammonium assimilation is a key way to improve the efficiency of plant nitrogen utilization. Glutamine synthetase (GS) and glutamate synthase (GOGAT), two key enzymes for ammonium assimilation, have rarely been studied in pecan. In this study, GS and GOGAT family members of pecan were identified and analyzed using bioinformatics methods. The results indicated that 6 GS and 4 GOGAT genes were identified. The cis-acting elements can be broadly categorized into light-responsive, hormone-responsive, and stress-responsive elements. The findings from the analysis of homologous evolution revealed that neither of the two gene families experienced tandem duplication events. Additionally, different ratios of ammonium to nitrate nitrogen were set to analyze the activities of GS and GOGAT enzymes and expression levels in pecan. The results demonstrate differences in the activities of GS and GOGAT enzymes and the gene expression levels in various tissues of pecan under different nitrogen form ratios. This study established a foundation for further mastering the molecular regulatory mechanism of nitrogen assimilation in pecan, and provided a theoretical basis for enhancing the ability of pecan to absorb and utilize nitrogen. [ABSTRACT FROM AUTHOR]

Sediment grain-size distribution (GSD) provides rich information about sedimentary sources and can potentially do the same with regard to environmental and climatic changes. However, neither traditional descriptive statistics nor curving-fitting methods can fully address its complexity. We selected the Greater Khingan Range in northeastern China as the study area and used parameterized end-member analysis (EMA) of the GSD of four drilling cores to extract different end-member (EM) components. The results show that EM1 (mode particle size (Mo): 1.26–1.66 μm) originates from weathering and pedogenesis. The EMs with Mo values of 4.37–5.01 μm represent components transported by the upper westerly wind. EMs with Mo values of 7.58 μm and 11.48 μm represent wet dust deposition and dry dust deposition. The wind transport of particles in winter consists of low-level near-source transport and local-source transport (possibly from the flood plain of the Amur River). Due to the limitations of the EM model, the two sources have one or two EM components: AEM3 + AEM4, BEM3 + BEM4, CEM4, and DEM4. DEM5 is the only large particle-size component and may represent coarse-grained detritus generated via rock weathering. The components related to the winter monsoon and the 14C dating data suggest a weak-strong-weak-strong trend of the winter monsoon since the Marine Isotope Stage 3a (MIS 3a). Our results suggest that the strengthening of the winter monsoons in the previous few thousand years has caused the transportation of coarser grain sizes and further exacerbated permafrost degradation, providing a scientific reference for understanding climate change and the formation and evolution of permafrost in the Greater Khingan Mountains since the MIS 3a. [ABSTRACT FROM AUTHOR]

In recent years, the China's rapid economic development and living standards of people have been improved, and the usage of clothing, food, housing, and transportation has increased. However, due to the prevalence of sports injuries and their high frequency of incidence, sports injury incidents do occur from time to time. Sports injury will not only affect the normal training of athletes and sports enthusiasts but also adversely affect their health. An estimation model of sports injury is designed based on an improved recursive neural network algorithm to reduce the incidence of sports injury in the process of physical exercise so that athletes and sports enthusiasts can reduce sports injury, which is conducive to physical health and sports health. [ABSTRACT FROM AUTHOR]

It is a very common phenomenon to have ankle injuries during sports. Therefore, the detection of ankle injuries has become a concern theme of scholars. It is of great significance to realize the ankle apparent strain measurement quickly in colleges and universities. In this paper, a data mining algorithm-based approach to measuring the apparent strain of the ankle joint in football sports is proposed. This paper first analyzes and integrates the research results of scholars and then expounds from the two aspects of data mining and ankle apparent strain measurement. The method is introduced in detail, and the principle of apparent strain measurement is explained by the formula. The feasibility and robustness of the research scheme are then demonstrated through specific experimental data. The data showed that there was a difference between the boy group and the girl group in the time of jumping, kicking, and reaching the ground (significant level P = 0.026). [ABSTRACT FROM AUTHOR]

Tennis is a sport with a large age span. Its technology is complex. Factors such as tennis racket and service position will affect the effect of players holding the ball, but often the service posture and strength will affect the players' elbow tendon. Once the service posture is wrong or the strength is too strong, it will cause irreversible damage to players. Therefore, the study of artificial neural network training on tennis elbow injury is of great significance. Based on artificial neural network, this paper studies the biomechanics of elbow injury in tennis service. Firstly, this paper expounds the concept and characteristics of tennis service technology and studies the injury of tennis players' elbow. Then this paper studies the artificial neural network technology and uses the experimental comparison method to test the force generated by the two groups of tennis players from different angles. The results show that, in the professional group, the forearm is in the internal rotation state before and after hitting the ball, while the beginner group is generally in the external rotation state. It can be inferred that, under the constant collision force, the reversal force absorbed by the beginner group in the swing process is greater than that of the professional group, which will increase the load of the supinator muscle on the antipronation, which will damage the supinator muscle, which is also one of the causes of the "tennis elbow" disease. [ABSTRACT FROM AUTHOR]

Introduction: Exercise is pivotal for maintaining physical health in contemporary society. However, improper postures and movements during exercise can result in sports injuries, underscoring the significance of skeletal motion analysis. This research aims to leverage advanced technologies such as Transformer, Graph Neural Networks (GNNs), and Generative Adversarial Networks (GANs) to optimize sports training and mitigate the risk of injuries., Methods: The study begins by employing a Transformer network to model skeletal motion sequences, facilitating the capture of global correlation information. Subsequently, a Graph Neural Network is utilized to delve into local motion features, enabling a deeper understanding of joint relationships. To enhance the model's robustness and adaptability, a Generative Adversarial Network is introduced, utilizing adversarial training to generate more realistic and diverse motion sequences., Results: In the experimental phase, skeletal motion datasets from various cohorts, including professional athletes and fitness enthusiasts, are utilized for validation. Comparative analysis against traditional methods demonstrates significant enhancements in specificity, accuracy, recall, and F 1-score. Notably, specificity increases by ~5%, accuracy reaches around 90%, recall improves to around 91%, and the F 1-score exceeds 89%., Discussion: The proposed skeletal motion analysis method, leveraging Transformer and Graph Neural Networks, proves successful in optimizing exercise training and preventing injuries. By effectively amalgamating global and local information and integrating Generative Adversarial Networks, the method excels in capturing motion features and enhancing precision and adaptability. Future research endeavors will focus on further advancing this methodology to provide more robust technological support for healthy exercise practices., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhu, Ye, Ren and Ma.)