Previous studies have found some risk factors of cyberbullying. However, little is known about how mother phubbing may influence adolescent cyberbullying, and the mediating and moderating mechanisms underlying this relationship. “Phubbing,” which is a portmanteau of “phone” and “subbing,” refers to snubbing other people and focus on smartphones in social interactions. This study examined whether mother phubbing, which refers to being phubbed by one’s mother, would be positively related to adolescent cyberbullying, whether perceived mother acceptance would mediate the relationship between mother phubbing and adolescent cyberbullying, and whether emotional stability would moderate the pathways between mother phubbing and adolescent cyberbullying. The sample consisted of 4,213 Chinese senior high school students (mean age 16.41 years, SD = 0.77, 53% were female). Participants completed measurements regarding mother phubbing, cyberbullying, perceived mother acceptance, and emotional stability. The results indicated that mother phubbing was positively related to cyberbullying, which was mediated by perceived mother acceptance. Further, moderated mediation analyses showed that emotional stability moderated the direct path between mother phubbing and cyberbullying and the indirect path between mother phubbing and perceived mother acceptance. This study highlighted the harmful impact of mother phubbing on adolescents by showing a positive association between mother phubbing and adolescent cyberbullying, as well as the underlying mechanisms between mother phubbing and adolescent cyberbullying.

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Abstract:Restricted by technical and budget constraints, hyperspectral (HS) image which contains abundant spectral information generally has low spatial resolution. Fusion of hyperspectral and panchromatic (PAN) images can merge spectral information of the former and spatial information of the latter. In this paper, a new hyperspectral image fusion algorithm using structure tensor is proposed. An image enhancement approach is utilized to sharpen the spatial information of the PAN image, and the spatial details of the HS image is obtained by an adaptive weighted method. Since structure tensor represents structure and spatial information, a structure tensor is introduced to extract spatial details of the enhanced PAN image. Seeing that the HS and PAN images contain different and complementary spatial information for a same scene, a weighted fusion method is presented to integrate the extracted spatial information of the two images. To avoid artifacts at the boundaries, a guided filter is applied to the integrated spatial information image. The injection matrix is finally constructed to reduce spectral and spatial distortion, and the fused image is generated by injecting the complete spatial information. Comparative analyses validate the proposed method outperforms the state-of-art fusion methods, and provides more spatial details while preserving the spectral information.