To analyze the effect of sandplay (SP) therapy on the mental health level of college students. 500 college students were openly recruited, using the University Student Mental Health Questionnaire (UPI) to screen out 76 students in the UPI category. 34 college students were randomly selected and divided into two groups, 17 in the control group and 17 in the SP therapy group (experimental group); the control group received no treatment, and the experimental group was treated with SP therapy, to analyze the differences between groups before and after the intervention of SCL-90 and self-made group self-reflection questionnaire. (1) With a detection rate of 15.2 percent, 76 of the 500 college students solicited openly were identified as UPI students; (2) except for the terror factor, there were significant differences in other aspects and overall scores for the experimental group following SP therapy intervention, and the scores reduced. There were no significant differences in the total scores and scores of all factors in the control group ( P > 0.05 ). The overall score, somatization, interpersonal connection, depression, paranoia, and psychosis were all significantly different between the experimental and control groups in the independent sample t -test ( P < 0.05 ).

The geometrical structures and electronical properties, as well as hydrogen storage of Al-doped boron nitride nanotube have been investigated using first principles based on density functional theory. The results show that the symmetry of boron nitride nanotube is destroyed slightly by doping one Al atom. Furthermore, physical absorption is found due to the small average absorption energy of Al-BNNT-nH2, which indicates that this hydrogen absorption will occurs at room temperature. In addition, some novel structures presenting almost same absorption behaviors are predicted, which will offer useful information to future experimental investigation on the design of hydrogen storage materials.

In recent years, the term “big data” has attracted the attention of many scholars and business managers, and the emergence of massive data has ushered in a major transformation of the times. Service quality and customer repeat purchase intention are two of the hot issues in the field of service research. Clarifying the mechanism of the two can help enterprises establish long-term customer relations with more customers through the improvement of service quality, enhance their competitive strength, and improve enterprise performance. According to the actual consumer purchase data provided, the existing data sets are visually analyzed and processed to find the consumer purchase rules, build features and build a reasonable consumer purchase prediction experimental data set. Based on the obtained experimental data set, a single prediction model of consumer purchase is designed. According to the analysis of the instantiation results of the single prediction model, the single model consumed in the fusion model of consumer purchase prediction is determined. In order to demonstrate the viewpoints put forward, the research model is established, the research hypothesis is put forward, the questionnaire is designed by referring to the literature and field investigation, and the results of the questionnaire are empirically analyzed. Using the methods of descriptive statistical analysis, factor analysis, reliability and validity test, and regression analysis, the hypothesis that service quality has a direct impact on customer repeat purchase intention is verified.

The structural stability, metallicity and hydrogen adsorption properties of Ti doped superatomic-Al12C cluster have been investigated by first-principles based on density functional theory. The results show that the structural stability of Al12C has been enhanced after replacing the central Al atom of icosahedra Al13 configuration by carbon atom, and the most stable structure and stability of Al12CTi and the lowest energy structures of Al12CTi (H2)n (n=1-8) are searched and discussed. Moreover, the Al12CTi (H2)6 not only exhibits strong stability according to HOMO-LUMO energy gap analysis, but also absorbs six hydrogen molecules in the absorb energy range of physical and chemical absorption, which could be considered as a candidate for hydrogen absorption materials development.

Camellia oil contains a variety of active substances, which have the functions of strengthening the heart and lowering cholesterol, and can prevent a variety of cardiovascular and cerebrovascular diseases caused by vascular sclerosis edible oil. Based on the logistics model, this paper builds a research model on the influencing factors of consumption and purchase intention and analyzes the coastal areas of camellia oil. Using this model, it makes an empirical analysis and research on the differences in the purchase intention and influencing factors of different consumers of camellia oil. Based on the results of empirical analysis, the main research conclusions of this paper are extracted, including the influencing factors of consumers’ camellia oil purchase willingness and the differences in the influencing factors of consumers’ camellia oil purchase willingness under different income levels, and put forward some corresponding measures and policy suggestions in a targeted manner. Based on the research model of the influencing factors of purchase intention established by logistic algorithm, this paper analyzes the coastal areas of Chashan oil and finds that the factors affecting consumers’ purchase intention are positively related to education and personal monthly income and negatively related to gender. “Educational education” is significant at 1% and has a positive correlation with a coefficient of 0.864; personal income is significant at 5% with a coefficient of 0.762; for gender, it is negatively correlated with a coefficient of -0.259, indicating that other variables remain unchanged. Education can promote consumers’ willingness to buy camellia oil, and consumers with higher education are more likely to buy camellia oil. In the same regression prediction model, the regression prediction efficiency of this model is better. In general, this shows that the model in this paper has certain superior performance.