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Haiyan Zhong, Jingbo Xu School of Marxism, Northeast Agricultural University, Harbin City, Heilongjiang Province, People’s Republic of ChinaCorrespondence: Jingbo Xu, No. 600 Changjiang Road, Xiangfang District, Harbin City, People’s Republic of China, Tel +86 13633611611, Email xujingbo1329@163.comPurpose: The transition from school to work is an important stage in the career development of university students, and precarious employment during this period can significantly impact their early career success. In today’s unstable employment environment, this study examines how employment instability during the transition from school to work directly and indirectly affects college students’ subjective career success. This contributes to a thorough understanding of this transitional period and provides university students with the necessary resources to cope with a smooth transition from school to work.Patients and Methods: We recruited senior students at five universities in Harbin, China, from May to July 2022. After obtaining participants’ consent, questionnaires were distributed via social media, resulting in 967 valid questionnaires. Based on this sample, we examined the chain mediating effect of financial stress and occupational self-efficacy in the association between precarious employment and career success and the moderating effect of employability.Results: The study found that precarious employment hurts career success and can also affect career success by increasing financial stress and decreasing occupational self-efficacy among college students. At the same time, financial stress can also decrease students’ self-efficacy. Finally, employability can reduce the adverse effects of precarious employment on career success and occupational self-efficacy.Conclusion: The link between employment instability and subjective career success during the transition from school to work has been demonstrated for university students. Employment instability not onl

A Flying Bird Object Detection algorithm Based on Motion Information (FBOD-BMI) is proposed to solve the problem that the features of the object are not obvious in a single frame, and the size of the object is small (low Signal-to-Noise Ratio (SNR)) in surveillance video. Firstly, a ConvLSTM-PAN model structure is designed to capture suspicious flying bird objects, in which the Convolutional Long and Short Time Memory (ConvLSTM) network aggregated the Spatio-temporal features of the flying bird object on adjacent multi-frame before the input of the model and the Path Aggregation Network (PAN) located the suspicious flying bird objects. Then, an object tracking algorithm is used to track suspicious flying bird objects and calculate their Motion Range (MR). At the same time, the size of the MR of the suspicious flying bird object is adjusted adaptively according to its speed of movement (specifically, if the bird moves slowly, its MR will be expanded according to the speed of the bird to ensure the environmental information needed to detect the flying bird object). Adaptive Spatio-temporal Cubes (ASt-Cubes) of the flying bird objects are generated to ensure that the SNR of the flying bird objects is improved, and the necessary environmental information is retained adaptively. Finally, a LightWeight U-Shape Net (LW-USN) based on ASt-Cubes is designed to detect flying bird objects, which rejects the false detections of the suspicious flying bird objects and returns the position of the real flying bird objects. The monitoring video including the flying birds is collected in the unattended traction substation as the experimental dataset to verify the performance of the algorithm. The experimental results show that the flying bird object detection method based on motion information proposed in this paper can effectively detect the flying bird object in surveillance video.