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Purpose: We examine how adolescent free time allocation—namely, screen time and outdoor time—is associated with mental health and academic performance in rural China. Methods: This paper used a large random sample of rural junior high school students in Ningxia (n = 20,375; age=13.22), with data collected from self-reported demographic questionnaires (to assess free time allocation), the Strengths and Difficulties Questionnaire (to assess mental health), and a standardized math test (to measure academic performance). We utilized a multivariate OLS regression model to examine associations between free time allocation and adolescent outcomes, controlling for individual and family characteristics. Results: Our sample's screen time and outdoor time both averaged around 1 hour. About 10% of the sample adolescents reported behavioral difficulties, while a similar percentage (11%) reported abnormal prosocial behaviors. Adolescents with higher levels of screen time (> 2 hours) were 3 percentage points more likely to have higher levels of behavioral difficulties (p< 0.001), indicating that excessive screen time was associated with worse mental health. Meanwhile, outdoor time was associated with better mental health, and positive correlations were observed at all levels of outdoor time (compared to no outdoor time, decreasing the likelihood of higher levels of behavioral difficulties by between 3 and 4 percentage points and of lower prosocial scores by between 6 and 8 percentage points; all p's< 0.001). For academic performance, average daily screen times of up to 1 hour and 1– 2 hours were both positively associated with standardized math scores (0.08 SD, p< 0.001; 0.07 SD, p< 0.01, respectively), whereas there were no significant associations between outdoor time and academic performance. Conclusion: Using a large sample size, this study was the first to examine the association between adolescent free time allocation with mental health and academic performance, providing initial insights into how rural Chinese adolescents can optimize their free time. [ABSTRACT FROM AUTHOR]

Background: Studies indicate that muscle strength is associated with good mental health. However, it remains unclear whether muscle strength is directly correlated with psychological symptoms in Chinese adolescents. Given the declining muscle strength and worrying mental health status of Chinese adolescents, the present study aimed to estimate the correlation between muscle strength and psychological symptoms as well as explore the gender differences in those correlations in Chinese adolescents., Method: From April to July 2018, a total of 14,344 Chinese adolescents from eight provinces were selected using a stratified clustered sampling method. Psychological symptoms were evaluated using the Multidimensional Sub-health Questionnaire of Adolescents (MSQA), a verified and validated questionnaire that assesses three psychological areas: emotional symptoms, behavioral symptoms, and social adaptation difficulties. Muscle strength was assessed using grip strength, sit-ups, and standing long jump. The Chi-square test was used to compare the detection rates of the different categories of psychological symptoms. A logistic regression analysis was used to analyze the correlations between muscle strength and psychological symptoms and explore the gender differences in those correlations in Chinese adolescents., Results: In general, the detection rate of psychological symptoms for Chinese adolescents was 21.39%. Males had a higher detection rate of psychological symptoms (22.12%) than females (20.66%, p < 0.05). Psychological symptoms were present in significantly fewer Chinese adolescents with a muscle strength index >P75 (19.26%) than among Chinese adolescents with a muscle strength index ≤P25 (23.00%) (χ 2 = 23.417, p < 0.01). Compared with females, the OR values for males in most groups were over one (OR = 1.04-1.43), indicating that males have a higher risk of psychological symptoms than females., Conclusions: The psychological symptom detection rate of Chinese adolescents is correlated with muscle strength. Psychological symptoms were more correlated to muscle strength in males than in females. The significance of the present study lies in the important insights for integrated mental and physical fitness intervention strategies that promote muscle strength and psychological symptoms simultaneously., Competing Interests: The authors declare that they have no competing interests., (© 2022 Lu et al.)

• Spatiotemporal characteristics of wind farm clusters is described by correlations. • Weights of correlation coefficients are assigned using the Shapley value method. • Spatiotemporal features are extracted by convolution neural network. • Long short term memory network is used for predicting the total power generation. Accurate power prediction of wind farm clusters is important for safe and economic operation of power systems with high wind power penetration. Current superposition and statistical scaling methods used in wind power prediction systems do not fully consider the relationships among wind farms in a cluster, thereby leading to insufficient power prediction accuracies. To improve the power prediction accuracy of wind farm clusters, a new method based on spatiotemporal correlations is proposed herein. First, three correlation coefficients are used to represent spatiotemporal correlation characteristics of wind farms in a wind cluster. The Shapley value method is used to weight these coefficients, and a standard wind farm is found by combining the nominal capacities of the wind farms. Then, considering the spatiotemporal factors that affect wind power generation, a characteristic matrix of the wind farm cluster is constructed, and the key characteristics are extracted using a convolutional neural network (CNN). Considering the time series characteristics of wind power generation, a long and short term memory (LSTM) neural network is used to establish the mapping relationship between key characteristics and power generation, and power prediction of a wind farm cluster is performed. Finally, by utilizing the actual operating data of wind farm clusters in North China as an example, feasibility and effectiveness of the proposed method are verified. The proposed system provides a new high-precision method for future wind farm cluster power predictions. [ABSTRACT FROM AUTHOR]

With face-to-face interaction proving beneficial for mental health, there is still a paucity of research on the correlation between ground floor features (GFFs), defined here as the features of the ground floor of buildings overlooking a street, and public open space face-to-face interaction density (POSFTFID), defined as the density of human face-to-face interactions in the public open space (POS) adjacent to each building. Is there a correlation between GFFs and POSFTFID? This study aims to answer this question gaining empirical evidence from a Chinese village in the city (ViC). Behavioural mapping and statistical analysis were employed and the following GFFs were tested: Ground floor area, indoor visible space, presence of stairs, POS adjacent area, and land use. Results show an association between POSFTFID and: (1) The area of the POS adjacent to each building, (2) the degree of visibility (ratio of indoor visible space to total internal space) of the ground floor, (3) the presence of stairs. Moreover, food appears to be an important attribute fostering social interaction. Results can provide insights on future implications in urban design strategies and planning policies aiming at enhancing mental health conditions in contemporary cities., Competing Interests: The authors declare no conflict of interest.