Although numerous studies have supported the idea that complex posttraumatic stress disorder (CPTSD) is a distinct disorder from posttraumatic stress disorder (PTSD) and demonstrated that childhood interpersonal trauma is an important risk factor for CPTSD, few studies have examined the validity of CPTSD in adolescents, especially in non-Western contexts. Moreover, the question of which form of child maltreatment plays the most important role in predicting CPTSD, and how CPTSD is associated with psychological health, physical health, and social function among adolescents, is not clear. The present study used a Chinese high school student sample with childhood trauma experiences ( N = 395) to address these questions. Latent profile analysis indicated that there were four subgroups in our sample: Low symptoms (54.43%), Disturbance of self-organization (DSO, 18.99%), PTSD (15.95%), and CPTSD (10.63%). Further analysis revealed that emotional abuse was an important risk factor for CPTSD. In addition, the CPTSD class showed the highest levels of depression, anxiety, and stress, as well as the lowest levels of life satisfaction and physical health. This study revealed that CPTSD is a distinct disorder from PTSD in Chinese adolescents exposed to childhood trauma. It provides evidence that emotional abuse might be an important risk factor for CPTSD, and demonstrates that CPTSD is accompanied by serious psychological and physical consequences in adolescents. We suggest that parents and educators should focus more on adolescents’ emotional needs, avoid using negative ways such as verbal violence to express love, and pay more attention to adolescents’ DSO symptoms in parenting, teaching practices and clinical interventions.

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Fashion recommendation is an essential component of user shopping that it is capable of selecting and presenting fascinating items to customers. The fact that humans exhibit inconsistencies for fashion items in their choice is known to all due to the visual aesthetic features and fine-grained differences of fashion items. Previous research on fashion recommendations mainly focuses on sequential models, most of them only consider complex similarity relationships in fashion compatibility while neglecting the real-world compatible information often desired in practical applications. To learn the fashion compatibility and generate for the outfit, we propose an approach that jointly learns latent fashion concepts in visual-semantic space to measure compatibility between items. The fashion concepts are shaped by design elements such as color, material, and silhouette. Accordingly, we model a unified representation to learn different notions of similarity by mapping text descriptors and images into latent space to learn high-level representations. Experimental results reveal that our method effectively reaches the aimed results on the fill-in-the-blank and outfit compatibility tasks.

Introduction:The purpose of this study is to investigate the influence of perceived discrimination on children's depression and behavioral problems via the mediator of integration among Chinese migrant children. Rural-urban differences in the proposed relationships are also examined. Methods:The sample included 484 migrant children (Mean age = 11.65 years; 52.9% girls), which was collected through multi-stage cluster random sampling in Kunming, Southwest China. Structural equation modelling (SEM) was adopted for data analysis. Results:Results indicate that perceived discrimination reduces the integration of Chinese migrant children, which in turn, leads to their higher levels of depression and more behavioral problems. The multi-group analysis on rural-urban differences reveals that the effects of discrimination on depression and behavioral problems are significant among rural-urban migrants but not among urban-urban ones.Conclusions: This study contributes to current knowledge by revealing the mechanisms among perceived discrimination, integration, depression and behavioral problems of Chinese migrant children. The migration pattern differences in terms of their depression and behavioral problems are also highlighted.

In order to improve the safety of college physical education resources recommendation and reduce the test overlap rate and resource exposure rate, a personalized recommendation method of college P.E. teaching resources based on cognitive diagnosis model is proposed. A cognitive diagnosis model based on multi-level attribute score is designed to model students' resource mastery level according to existing answers and the relevance of knowledge points. The knowledge mastery attribute model of the tested students is used for probability matrix decomposition to predict the students' answers, and make corresponding resource recommendations according to the score prediction and resource difficulty. Experiments show that resource exposure value of the method in this paper is lower than 1, and its security is high. Regarding the experiment of overlapping indicators, the value of the test overlap rate of the method in this paper is always lower than 0.01, and the recommended resources are more accurate. The F1 value of the method in this paper is up to 0.98, and the deviation of resource recommendation is small. And the real-time performance is high after the method is applied, and the phenomenon of cold start will not occur.