Search

[Purpose/Significance] The collaboration between the instructor of a general-purpose course "Writing and Communication" and information literacy (IL) librarian teachers at Southern University of Science and Technology provides a new embedded teaching cooperation scheme for an undergraduate writing course. This new model can help college academic librarians design more active ways to teach embedded IL class in general-purpose writing courses for freshmen and sophomores against the background of cultivating "top innovative professionals". [Method/Process] Based on the teaching collaboration between the librarians and the instructors in the past five years, we explored and analyzed effective and integrated teaching models of embedded IL education. Focusing on assessment and student's learning outcome, we constructed an embedded IL teaching evaluation model to comprehensively evaluate student's learning outcome, which includes both direct and indirect evaluation. The direct assessment includes five evaluation indicators: information awareness, information inquiry and access, information evaluation, information management and utilization, and information regulation and security. The indirect evaluation is a "librarian-writing instructor" dual assessment based on students' course papers, in which the librarian and the writing instructor rate students' IL skills and writing skills independently and then compare the assessment results. The librarian scrutinizes students' work under the rubric of search strategy, resource selection and reference standardization; and the writing instructor examines the critical thinking, essay structure and writing style of students' papers. The comparison of the scores on writing and information use of students' papers provide quantitative evaluation on the correlation of students' writing and information skills. [Results/Conclusions] There is a positive correlation between IL and writing performance. College freshmen differ from senior students in IL competence in many ways due to their lack of information training and of limited exposure to various academic scenarios. Thus, besides teaching basic searching skills, instructors should also help students build up information awareness and competence by situating IL teaching in specific writing tasks in an integrated teaching model. By collaborating with writing instructors, the embedded information session is more contextualized, and therefore a "process-based" IL development can be demonstrated to students. Other new pedagogical approaches such as flipped classroom also help to enhance teaching and learning.

Pathological observations show that cancer cells frequently invade the surrounding normal tissue in collective rather than individual cell migration. However, general principles governing collective cell migration remain to be discovered. Different from individual cell migration, we demonstrated that the Notch‐1‐activation reduced collective cells speed and distances. In particular, Notch‐1‐activation induced cellular cytoskeletal remodelling, strengthened the intercellular junctions and cell‐matrix adhesions. Mechanistically, Notch‐1 activation prevented the phosphorylation of GSK‐3β and the translocation of cytoplasmic free β‐catenin to the nucleus, which increased E‐cadherin expression and tight intercellular junctions. Moreover, Notch‐1 signalling also activated the RhoA/ROCK pathway, promoting reorganization of F‐actin and contractile forces produced by myosin. Further, Notch‐1 activation increased cell adhesion to the extracellular substrate, which inhibited collective cell migration. These findings highlight that cell adhesions and cell–cell junctions contribute to collective cell migration and provide new insights into mechanisms of the modulation of Notch‐1 signalling pathway on cancer cell malignancy. [ABSTRACT FROM AUTHOR]

Accurately detecting and counting abnormal fish behaviors in aquaculture is essential. Timely detection allows farmers to take swift action to protect fish health and prevent economic losses. This paper proposes an enhanced high-precision detection algorithm based on YOLOv9, named DDEYOLOv9, to facilitate the detection and counting of abnormal fish behavior in industrial aquaculture environments. To address the lack of publicly available datasets on abnormal behavior in fish, we created the "Abnormal Behavior Dataset of Takifugu rubripes", which includes five categories of fish behaviors. The detection algorithm was further enhanced in several key aspects. Firstly, the DRNELAN4 feature extraction module was introduced to replace the original RepNCSPELAN4 module. This change improves the model's detection accuracy for high-density and occluded fish in complex water environments while reducing the computational cost. Secondly, the proposed DCNv4-Dyhead detection head enhances the model's multi-scale feature learning capability, effectively recognizes various abnormal fish behaviors, and improves the computational speed. Lastly, to address the issue of sample imbalance in the abnormal fish behavior dataset, we propose EMA-SlideLoss, which enhances the model's focus on hard samples, thereby improving the model's robustness. The experimental results demonstrate that the DDEYOLOv9 model achieves high P r e c i s i o n , R e c a l l , and m e a n   A v e r a g e   P r e c i s i o n ( m A P ) on the "Abnormal Behavior Dataset of Takifugu rubripes", with values of 91.7%, 90.4%, and 94.1%, respectively. Compared to the YOLOv9 model, these metrics are improved by 5.4%, 5.5%, and 5.4%, respectively. The model also achieves a running speed of 119 frames per second ( F P S ), which is 45 F P S faster than YOLOv9. Experimental results show that the DDEYOLOv9 algorithm can accurately and efficiently identify and quantify abnormal fish behaviors in specific complex environments. [ABSTRACT FROM AUTHOR]