Liz JacksonEducation University of Hong KongGiven how important textbooks continue to be in education, how textbooks are read for learning and research remains poorly understood. As Michael Apple n...

This paper describes a scoping review of China’s academic resource databases, relevant official websites, news reports and public accounts spanning a period from the end of 2019 to the end of 2022, to investigate the challenges in scientific integrity and ethical soundness of research conducted during and immediately after the COVID-19 pandemic in China. By conducting the scoping review with keywords related to the research questions in Chinese, relevant data were extracted and classified into four categories: challenges in research, challenges (...) in ethics review, challenges in publishing academic work, and research ethics guidelines during and after the pandemic. The paper points out that problematic studies and findings increased with the escalation in medical research projects during the pandemic in China. The situation faced by researchers was more difficult than before the pandemic. The mode of informed consent, and ethics review and oversight systems also underwent changes. In addition, Traditional Chinese Medicine as an alternative medical treatment for COVID-19, attracted attention from the research community and became a topic of discussion. We conclude that the various challenges and concerns identified indicate a need for a proper and timely response system be formulated in preparation for possible future occurrences of new pandemics or other critical situations. (shrink)

River segmentation of remote sensing images is of important research significance and application value for environmental monitoring, disaster warning, and agricultural planning in an area. In this study, we propose a river segmentation model in remote sensing images based on composite attention network to solve the problems of abundant river details in images and the interference of non-river information including bridges, shadows, and roads. To improve the segmentation efficiency, a composite attention mechanism is firstly introduced in the central region of (...) the network to obtain the global feature dependence of river information. Next, in this study, we dynamically combine binary cross-entropy loss that is designed for pixel-wise segmentation and the Dice coefficient loss that measures the similarity of two segmentation objects into a weighted one to optimize the training process of the proposed segmentation network. The experimental results show that compared with other semantic segmentation networks, the evaluation indexes of the proposed method are higher than those of others, and the river segmentation effect of CoANet model is significantly improved. This method can segment rivers in remote sensing images more accurately and coherently, which can meet the needs of subsequent research. (shrink)

How to identify the key nodes effectively in urban traffic networks to achieve the equitable resource allocation face to the complex traffic network? This issue needs to be solved in current traffic management. This study considered the urban traffic network topology and network traffic status, put forward an improved model based on the economics of the input-output method by introducing a virtual node to the selected network set up with the flow of urban traffic network, sensor nodes by Leontief inverse (...) matrix calculation coefficient to determine node importance, according to the node importance to deliberate attack traffic network to analyze its robustness, to test the accuracy and practicability of the method. The results show that this improved method adopted to measure the importance of traffic nodes from the global scope has the advantages of fast calculation and simple process and provides a more reliable basis for rational allocation of transport resources. (shrink)

The youngest generation of students prefers a more active learning style. Sandwich teaching may suit their learning style by alternating between active individual learning and passive collective learning. Sandwich teaching has been rarely applied to the Community Nursing Course for nursing students, and its teaching effects on this course remain unclear. This study applied Sandwich teaching to the Community Nursing Course for Chinese nursing undergraduates and investigated its effects on students' critical thinking, self-learning ability, course experience, and academic performance. This (...) is a quasi-experimental study with 72 Chinese nursing undergraduates. Students receiving traditional teaching were enrolled in the control group, and those who received Sandwich teaching were recruited into the experimental group. Both groups received the 12-week, 90-min Community Nursing Course. Our main outcome variable, including students' critical thinking, self-learning ability, and course experience, was assessed by specific questionnaire. The paired t-tests were applied to compare the differences of the same group in the pre-test and the post-test, and the independent-sample t-tests were used to compare the differences between the two groups. We observed that nursing students' critical thinking ability and self-learning ability were significantly improved after receiving Sandwich teaching. Students' course experience of Sandwich teaching was significantly better than that of traditional teaching. The final exam score in the experimental group was not significantly higher than that in the control group. These results suggest that Sandwich teaching in Community Nursing Course improved Chinese nursing undergraduates' critical thinking, self-learning ability, and course experience, but failed in improving academic performance. (shrink)