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BackgroundPrevention and intervention of procrastination in college students are of great practical significance， and studies have illustrated a pairwise correlation among mindfulness， self-control， insecure attachment and procrastination， whereas the mechanism by which insecure attachment leads to procrastination remains unclear， and the related mediation path is quite understudied.ObjectiveTo investigate the effect of insecure attachment on procrastination among college students and the pathway of mindfulness and self-control， so as to inform the design of interventions for procrastination among college students.MethodsRandom and cluster sampling method were utilized to enroll 514 college students from 4 colleges in Guangdong Province From February to April 2023. Subjects were assessed using Irrational Procrastination Scale （IPS）， Adult Attachment Scale （AAS）， Mindful Attention Awareness Scale （MAAS） and Brief Self-Control Scale （BSCS）. Pearson correlation analysis were adopted to identify the correlation among above scales， and the mediation effect was examined via Bootstrap procedure.ResultsAAS score was positively correlated with IPS score （r=0.382， P

Objective To explore the predictive value of serum amyloid A1 (SAA1) in acute myocardial infarction (AMI). Methods A total of 139 patients with AMI and 146 patients with non coronary atherosclerotic heart disease admitted to the China-Japan Union Hospital of Jilin University from September 2017 to April 2019 were selected as the research objects. Enzyme linked immunosorbent assay (ELISA) was used to determine the level of SAA1 in plasma. Logistic regression was used to analyze the independent influencing factors of AMI, and receiver operating characteristic (ROC) curve was used to analyze the value of SAA1 in the diagnosis of AMI. Results The level of SAA1 in the AMI group was lower than that in the control group [2.62 (2.08,3.21) ng/mL vs 5.18 (3.24,8.27) ng/mL, Z=10.169, P

Sweet potato is a kind of low-calorie root food that has also been used for medicinal purpose. It is rich in a variety of essential nutrients and bioactive ingredients for the human body, and can be used to prevent various diseases. The quality of sweet potato directly affects its product quality, classification and quality grading and economic value. Rapid and efficient detection technologies play an important role in ensuring the quality and safety of sweet potato. Many studies on the rapid detection and analysis of sweet potato quality based on near-infrared spectroscopy (NIRS) have been reported. This paper comprehensively summarizes recent progress in the application of NIRS in the detection of the general chemical components (protein, starch, sugar, and water), active components (flavonoids and carotenoids), adulterants, heavy metals and microbial contamination in sweet potato as well as in its varietal identification. Moreover, this paper proposes future trends and research priorities for the application of NIRS in the quality detection of sweet potato. This review is expected to provide more references for further improvement of rapid quality assessment of sweet potato by NIRS and for the development of related fast testing equipment.

With the rapid development of science and technology, computer-aided technology has been widely used in the field of education, but in the field of innovation and entrepreneurship education (Hereinafter referred to as IEE), there are still problems such as uneven distribution of resources and the disconnection between teaching content and actual needs. This paper puts forward a new model framework of computer-aided IEE, which is student-centered and practice-oriented. Through clear teaching objectives, rich course content, diverse teaching methods, and a scientific evaluation system, students’ innovative consciousness and entrepreneurial ability are comprehensively improved. The course covers innovative thinking, business models, market research, and other theoretical knowledge, and introduces virtual reality (VR) and augmented reality (AR) technologies to simulate the real entrepreneurial process and provide a practical platform. In the aspect of algorithm application, the research combines the content recommendation algorithm and collaborative filtering recommendation algorithm, constructs accurate user portraits by analyzing students’ learning behavior data, and matches them according to the characteristics of learning resources to recommend personalized learning resources for students. At the same time, the learning path optimization algorithm is developed, and the personalized and efficient learning path is planned by using the shortest path algorithm in graph theory to ensure that students can master the required knowledge in the shortest time. The experimental part designed a one-semester teaching experiment, and compared the differences between the experimental group and the control group in academic performance, learning participation, and satisfaction. The results show that the computer-aided IEE model significantly improves students’ academic performance, learning participation, and satisfaction, which verifies the effectiveness of the model. The research on the model and algorithm of computer-aided IEE proposed in this paper provides new ideas and methods for IEE, and helps to cultivate more high-quality talents with innovative thinking and entrepreneurial ability.