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1.
Article in Chinese | WPRIM | ID: wpr-909562

ABSTRACT

Objective:To explore the latent categories of college students′ regulation emotional self-efficacy and its relationship with social anxiety, so as to provide theoretical basis for different groups to implement relevant intervention.Methods:A total of 415 college students were investigated by scale of regulation emotional self-efficacy(SRESE)and interaction anxiousness scale(SIAS). SPSS 26.0 was used for descriptive statistics and data collation, and Mplus 8.3 was used for latent profile analysis (LPA) to explore the potential categories of regulation emotional self-efficacy of college students. The modified BCH method was used to explore the relationship between different categories of regulation emotional self-efficacy and social anxiety.Results:Regulation emotional self-efficacy can be divided into three categories: " high positive expression and low management negative regulation emotional efficiency" , " low regulation emotional efficiency" and " high regulation emotional efficiency" , accounting for 30.3%, 22.3% and 47.4% of all college students. The three categories had different predictive effects on social anxiety. The " high positive expression and low management negative regulation emotional efficiency" (48.66±0.75) and " the low regulation emotional efficacy" (48.05±0.97) had higher scores in social anxiety and there was no significant difference in the prediction of social anxiety between them( χ2=0.24, P=0.62). However, " high regulation emotional efficiency" ( 45.29±0.56) had a lower score on social anxiety, which was significantly different in the prediction of social anxiety compare the other two categories( χ2=6.06, 12.30, both P<0.05). Conclusion:There are three different potential categories of regulation emotional self-efficacy. Different potential categories of regulation emotional self-efficacy have different social anxiety, so targeted intervention methods can be developed to improve the regulation emotional self-efficacy and reduce social anxiety.

2.
Article in Chinese | WPRIM | ID: wpr-291279

ABSTRACT

Microscopic characteristics of several Mongolian Herbal flowers were extracted by improved Pseudo-Jacobi (p = 4, q = 2)-Fourier Moments (PJFM's), and 368 different versions of 28 microscopic characteristics of these herbs were identified by using the minimum-mean-distance rule. The experimental results showed that the average identification rate reaches as high as 98.1%. Therefore, this study can provide new techniques for digitalization and visualization of microscopic characteristics of Mongolian Herbs.


Subject(s)
China , Flowers , Image Processing, Computer-Assisted , Methods , Pattern Recognition, Automated , Methods , Plants, Medicinal
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