Fostering emotional well-being in adolescents: the role of physical activity, emotional intelligence, and interpersonal forgiveness.

Introduction: Adolescence is considered a stress-sensitive developmental period, and the escalating and sustained pressure during this phase poses a significant threat to the mental and physical well-being of adolescents. Therefore, enhancing positive emotions in adolescents is crucial. This study aims to investigate the impact of physical activity on the emotional intelligence, interpersonal forgiveness, and positive emotions of adolescents. Methods: Using a cluster sampling method, data were collected from 500 adolescents in four schools across the Xiangxi Tujia and Miao Autonomous Prefecture of Hunan Province, China. A total of 428 valid questionnaires were collected and analyzed. The study employed AMOS v.23 to construct a structural equation model to validate the hypotheses. Results: The results indicate that physical activity significantly influences the emotional intelligence, interpersonal forgiveness, and positive emotions of adolescents. Furthermore, emotional intelligence and interpersonal forgiveness mediate the relationship between physical activity and positive emotions. Discussion: Based on these findings, collaborative efforts from government agencies, schools, and families are essential to provide robust support for adolescents' participation in physical activity, encouraging more adolescents to actively engage in sports.

Carbene-Mediated Polymer Modification Using Diazo Compounds under Photo or Thermal Activation Conditions.

Based on the characteristics of commodity polymers in large quantities and low costs, modification of existing commodity polymers emerges as the most effective approach for exploring novel materials. Nevertheless, conventional modification methods typically involve high-energy processes (e.g., high temperature, high-energy radiation), which may lead to irreversible detrimental effects on the polymers, contradicting the desired performance enhancement through modification. In this work, we propose a carbene-mediated postpolymerization modification (PPM) strategy utilizing diazo compounds. Under photochemical or thermal activation conditions, insertion of the C-H bond can be achieved without compromising the performance of polymers. These diazo compounds can be easily synthesized in just two steps and applied to all C-H-containing polymers. This practical and effective modification strategy offers new opportunities and possibilities for enhancing the value and expanding the applications of polymers.

Simulation evaluation of a single-photon laser methane remote sensor for leakage rate monitoring.

We propose a novel methane leakage rate remote sensor that combines a single-photon avalanche diode detector with a near-infrared 1653.7 nm low-power laser. The proposed M sequence and triangle wave signal modulation method simultaneously realizes the detection of methane leakage and target point clouds. Innovatively, the sensor's methane concentration and leakage rate quantification ability were simulated by combining the Gaussian plume diffusion model and the Risley prism. The effects of the prism rotation ratio, wind speed, leakage rate, atmospheric stability (AS), target reflectivity, signal averaging period, and concentration spatial interpolation method on leakage rate are discussed. When plume methane concentrations reduce from 10,000 to 500 ppm·m, the relative concentration bias rise from 1% to 30%, the absolute concentration bias is approximately 100 ppm·m. Two spatial concentration interpolation methods introduced leakage rate bias ranging from 6%-25%. For a low AS, the leakage rate bias under the cubic interpolation method was small (approximately 1.6%). In addition, when the initial leakage rate increased from 100 to 1,000 mg/s, the leakage rate bias was approximately 20% smaller.

Highly sensitive mid-infrared methane remote sensor using a deep neural network filter.

A novel mid-infrared methane remote sensor integrated on a movable platform based on a 3.291-µm interband cascade laser (ICL) and wavelength modulation spectroscopy (WMS) is proposed. A transmitting-receiving coaxial, visualized optical layout is employed to minimize laser energy loss. Using a hollow retro-reflector remotely deployed as a cooperative target, the atmospheric average methane concentration over a 100-meter optical range is measured with high sensitivity. A deep neural network (DNN) filter is used for second harmonic (2f) signal denoising to compensate for the performance shortcomings of conventional filtering. Allan deviation analysis indicated that after applying the DNN filter, the limit of detection (LOD) of methane was 86.62 ppb with an average time of 1 s, decreasing to 12.03 ppb with an average time of 229 s, which is a significant promotion compared to similar work reported. The high sensitivity and stability of the proposed sensor are shown through a 24-hour continuous monitoring experiment of atmospheric methane conducted outdoors, providing a new solution for high-sensitivity remote sensing of atmospheric methane.