Jie Peng

The virtual brand community has become an important marketing tool for companies. A successful brand community marketing strategy should attract a large number of consumers. Although past studies have revealed consumer motivations for participating in virtual brand communities, they fail to answer an important question: Why is it so easy for some virtual brand communities to attract users while others have such difficulty? In this study, product characteristics are hypothesized to be important factors that determine consumer motivation to participate in brand communities. Product characteristics can directly affect how actively consumers participate in brand communities. The results of questionnaires show that product complexity, product symbolism, and product satisfaction have a positive influence on consumers’ willingness to participate in brand communities. Notably, the duration of product use has a regulating effect on the influence of product satisfaction and product symbolism. A long period of product use weakens the influence of product satisfaction on consumers’ willingness to participate in brand communities. On the contrary, a long period of product use strengthens the influence of product symbolism on consumers’ willingness to participate in brand communities. This study enriches the literature on brand community participation and has implications for companies that aim to utilize brand communities for marketing.

Accurate and rapid defect identification based on pulsed eddy current testing plays an important role in the structural integrity and health monitoring of in-service equipment in the renewable energy system. However, in conventional data-driven defect identification methods, the signal feature extraction is time consuming and requires expert experience. To avoid the difficulty of manual feature extraction and overcome the shortcomings of the classic deep convolutional network, such as large memory and high computational cost, an intelligent defect recognition pipeline based on the general Warblet transform method and optimized two-dimensional DCNN is proposed. The GWT method is used to convert the one-dimensional PECT signal to a 2D grayscale image used as the input of 2D DCNN. A compound method is proposed to optimize the baseline VGG16, a well-known DCNN, from four aspects including reducing the input size, adding batch normalization layer after every convolutional layer and fully connection layer, simplifying the FCs, and removing unimportant filters in Convs so as to reduce memory and computational costs while improving accuracy. Through a pulsed eddy current testing experiment considering interference factors including liftoff and noise, the following conclusion can be obtained. The time-frequency representation obtained by the GWT method not only has excellent ability in terms of the transient component analysis but also is less affected by the reduction of image size; the proposed optimized DCNN can accurately identify defect types without manual feature extraction. And compared to the baseline VGG16, the accuracy obtained by the optimized DCNN is improved by 7%, to about 99.58%, and the memory and computational cost are reduced by 98%. Moreover, compared with other well-known DCNNs, such as GoogLeNet, Inception V3, ResNet50, and AlexNet, the optimized network has significant advantages in terms of accuracy and computational cost, too.

PurposesThis paper aims to discuss the relationship between college students’ sports participation, school bullying, emotional intelligence and self-esteem. At the same time, it explores the intrinsic mechanisms of school bullying, in order to provide a reference for reducing bullying phenomenon among college students, and pave the way for college students to lead happy, healthy and confident lives.MethodsA total of 1,317 students from four universities in Southwest China were selected as subjects for this survey. They were selected by stratified random sampling, and the data needed was obtained using a structured questionnaire. The data was subsequently processed with statistical software SPSS19.0 and AMOS21.0.Results Sports participation has a significant and positive correlation with emotional intelligence and self-esteem, likewise, it has a significant negative correlation with school bullying. Emotional intelligence has a marked positive correlation with self-esteem, at the same time it has a significant negative correlation with school bullying. In addition, self-esteem is strongly negative correlated with school bullying. Sports participation has a direct effect on school bullying. Emotional intelligence and self-esteem also play a significant mediating role between sports participation and school bullying, and the chain mediating force of emotional intelligence—self-esteem also reaches a significant level.ConclusionSports participation affects school bullying among college students not only directly but also indirectly, such as through emotional intelligence, the mediating role of self-esteem, and the chain mediating role of emotional intelligence to self-esteem. Apart from sports participation, emotional intelligence is another key factor that affects college students’ school bullying. Therefore, while attaching great importance to college students’ sport participation, schools should also provide courses aimed at developing students’ emotional intelligence.