Bridging the relationship between physical exercise and mental health in adolescents based on network analysis.

Although physical exercise has been recommended as a useful means of enhancing the mental health of adolescents, the exact mechanisms through which physical exercise plays a role are unclear. Both physical exercise and mental health are complex concepts with multiple facets, and traditional methods may constrain the manifestations of their mapping relationships. This research aimed to find the bridging connections between physical exercise and mental health. Mental health and physical exercise behaviors were assessed using the Symptom Checklist 90 (SCL-90) and the Adolescent Physical Activity Questionnaire (PAQ-A) in 9072 Chinese adolescents, respectively. Network analysis was utilized to construct the mental health-physical exercise network and to analyze the relationships between individual physical exercise behaviors and mental health symptoms. Core and bridging nodes were identified based on expected influence (EI) and bridge expected influence (BEI). Gender differences were also examined. The results revealed specific and distinct pathways between physical exercise and mental health (e.g., winter sports-obsessive-compulsive symptoms, winter sports-phobia). For both males and females, anxiety, depression, interpersonal sensitivity, ball sports, and evening activity were the most central symptoms/behaviors, reflecting their relative significance in their respective associations. The nodes with the highest BEI were obsessive-compulsive symptoms and physical education, showing negative associations with nodes in the other community. Furthermore, in the male group, somatization and winter sports stood out as the most positive bridge nodes. Conversely, in the female group, interpersonal sensitivity and sports games were the most positive bridge nodes. These findings illuminate the pathways linking physical exercise and mental health, supporting the implementation of physical exercise in a more elaborate way.

Physical Exercise Transforms the Topography and Increases the Invulnerability of the Symptom Network of Depression-Anxiety in the Elderly.

BACKGROUND AND OBJECTIVES: Depression and anxiety often co-occur and have worse impacts on the elderly when experienced simultaneously. Although physical exercise may alleviate depression and anxiety, how it affects the specific symptoms is not fully understood. METHODS: A total of 8884 participants was selected from the 2018 CLHLS database. The 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Generalized Anxiety Disorder Scale-7 (GAD-7) were used to assess depression and anxiety, respectively. Participants were divided into the exercise and the nonexercise groups using propensity score matching to minimize the influence of confounding variables. Depression-anxiety symptom networks were constructed, and network indexes were computed for each group, based on various packages of R. By computing network connectivity, invulnerability simulation was used to investigate the role of physical exercise in network robustness. RESULTS: Both groups had D3 (sad mood), A4 (trouble relaxing) and A2 (uncontrollably worry) as central symptoms. In the exercise group, A1 (nervousness), A3 (too much worry) and D1 (bothered by little things) were the strongest bridge nodes. In the nonexercise group, A1 (nervousness), D1 (bothered by little things) and A4 (trouble relaxing) played this role. Participation in physical exercise decreased the centrality of D9 (cannot get doing) but increased the centrality of A3 (too much worry). Furthermore, the exercise group had higher network invulnerability than the nonexercise group under random attack conditions. CONCLUSIONS: Physical exercise affected core symptoms of depression-anxiety and the interactions of symptoms. Targeting central or bridge nodes may be an effective intervention for alleviating the comorbidity. Increased network invulnerability manifested the positive effects of physical exercise.

Magnetic-Field-Assisted Scratching Process of Single-Crystal Copper.

Energy-field-assisted cutting exhibits excellent ability to reduce cutting force and improve machining quality. In this study, a magnetic field was applied in an innovative way to aid in the cutting process, and magnetic-field-assisted scratching experiments of single-crystal copper were carried out. It was found that magnetic-field-assisted scratching increased the actual scratching force due to the additional Lorentz force in the cutting process. However, the friction coefficient of the magnetic-field-assisted scratching was reduced by 19.4% due to the tribological modification effect on tool/chip contact. Meanwhile, magnetic-field-assisted scratching was conducive to decreasing the degree of chip deformation, reducing microburrs on the machined surface, and obtaining a surface roughness reduction of an average of 26.8%. The possible reason for this effect was that the presence of a magnetic field in the cutting process promoted the dislocation slip of metal materials. The results indicated that magnetic-field-assisted cutting improves the machinability in the metal cutting process.