Explore the vast range of titles available.

Shun Yamashita,1,2 Maiko Sakamoto,1 Shizuka Yaita,1,2 Kaori Inoue,1 Yukari Mizoguchi,1 Yuki Hoshino,1 Manami Yamaguchi,3 Noriko Ide,4 Naoko E Katsuki,2 Masaki Tago,2 Yasushi Miyata,5 Yasutomo Oda1 1Education and Research Center for Community Medicine, Faculty of Medicine, Saga University, Saga, Japan; 2Department of General Medicine, Saga University Hospital, Saga, Japan; 3Graduate School of Medical Science, Saga University, Saga, Japan; 4Department of General Medicine, NHO Ureshino Medical Center, Saga, Japan; 5Department of Primary Care and Community Health, Aichi Medical University School of Medicine, Aichi, JapanCorrespondence: Shun Yamashita, Education and Research Center for Community Medicine, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga, 849-8501, Japan, Tel +81952343238, Fax +81952342029, Email sy.hospitalist.japan@gmail.comIntroduction: Understanding the perceptions of medical students and faculty members regarding unprofessional behavior is crucial to appropriately guide medical students’ behavior. This study aimed to clarify the differences in perceptions of unprofessional behavior in clinical settings among Japanese medical students and faculty members.Methods: This single-center, cross-sectional survey was conducted at the Faculty of Medicine, Saga University. Participants were faculty members who participated in a faculty development program on medical students’ unprofessional behaviors in December 2024 and fourth-year medical students who attended a similar lecture in January 2025. The survey items were determined through identifying common unprofessional behaviors based on previous reports and following a discussion with faculty members responsible for pre-graduate education. Participants were divided into faculty and student groups, and differences in perceptions were analyzed using logistic regression analysis.Results: Participants comprised 40 (response rate 22%) faculty and 65 (64%) students. The faculty group showed significantly lower perceptions of being unprofessional in the following behaviors than the student group: violation of privacy or confidentiality obligations (odds ratio 0.089, 95% confidence interval 0.010– 0.766); false statements or misrepresentation (0.180, 0.034– 0.940); inappropriate use of social networking services (0.150, 0.029– 0.762); fabrication or falsification of data (0.228, 0.005– 0.941); bullying, discrimination, and sexual harassment (0.047, 0.006– 0.383). Multivariate logistic regression analysis identified “bullying, discrimination, and sexual harassment (0.058, 0.007– 0.487)” as the only factor on which their perceptions differed significantly.Conclusion: Both faculty members and medical students perceived the unprofessional behaviors of medical students similarly, except in the cases of bullying, discrimination, and sexual harassment. However, since faculty members considered five behaviors to be less unprofessional, their perceptions regarding unprofessional behaviors need to be realigned so that they can better guide medical students toward becoming better professionals in the future, thereby improving patient outcomes.Keywords: unprofessional behavior, medical students, faculty members, difference of perception

Understanding the perceptions of medical students and faculty members regarding unprofessional behavior is crucial to appropriately guide medical students' behavior. This study aimed to clarify the differences in perceptions of unprofessional behavior in clinical settings among Japanese medical students and faculty members. This single-center, cross-sectional survey was conducted at the Faculty of Medicine, Saga University. Participants were faculty members who participated in a faculty development program on medical students' unprofessional behaviors in December 2024 and fourth-year medical students who attended a similar lecture in January 2025. The survey items were determined through identifying common unprofessional behaviors based on previous reports and following a discussion with faculty members responsible for pre-graduate education. Participants were divided into faculty and student groups, and differences in perceptions were analyzed using logistic regression analysis. Participants comprised 40 (response rate 22%) faculty and 65 (64%) students. The faculty group showed significantly lower perceptions of being unprofessional in the following behaviors than the student group: violation of privacy or confidentiality obligations (odds ratio 0.089, 95% confidence interval 0.010-0.766); false statements or misrepresentation (0.180, 0.034-0.940); inappropriate use of social networking services (0.150, 0.029-0.762); fabrication or falsification of data (0.228, 0.005-0.941); bullying, discrimination, and sexual harassment (0.047, 0.006-0.383). Multivariate logistic regression analysis identified \"bullying, discrimination, and sexual harassment (0.058, 0.007-0.487)\" as the only factor on which their perceptions differed significantly. Both faculty members and medical students perceived the unprofessional behaviors of medical students similarly, except in the cases of bullying, discrimination, and sexual harassment. However, since faculty members considered five behaviors to be less unprofessional, their perceptions regarding unprofessional behaviors need to be realigned so that they can better guide medical students toward becoming better professionals in the future, thereby improving patient outcomes.

Background Smooth reciprocal relationships enable a preceptee’s growth, and it has been suggested that without such relationships, the preceptee may not be able to grow successfully. This study explored the differences in perceptions by matching the perspectives of both the preceptees who did not make progress in workplace adjustment and their preceptors. Identifying the differences in perceptions between the two groups is important for improving nursing education and the relationship between preceptees and preceptors. Methods A pair of nurses who had been with the company for less than 3 years and who had previously been transferred or had resigned due to poor workplace adjustment were designated as preceptees, and those who had directly supervised the preceptee during their first year of employment were included as preceptors in the study. A 50-minute semi-structured interview was conducted separately to examine the perceptions of the preceptee and preceptor. A thematic analysis was used to analyse the interview data. Results This study explored the differences in perceptions regarding the clinical practice of nursing between preceptors and their preceptees who did not make progress in workplace adjustment during nursing education; six themes were identified. After interviewing both sides, it became clear that the same event was interpreted differently depending on their positions, perspectives, and contexts. As the preceptees were nurses who had left or had been transferred, the existence of these differences in perceptions suggests that these factors may impact their departure or transfer. However, we do not aim to place blame on one side or the other for the preceptee’s turnover or transfer and would like to consider effective support, not only for the preceptee, but also for the preceptor. Conclusions It is necessary to examine nursing education on the premise that differences may occur depending on the position and role of nurses in the workplace and to look at curricular framework changes to bring in a systemic influence towards the training of young nurses.

PurposeMeasuring the performance of public participation is conducive to improving participation systems. However, such measurement, particularly in urban regeneration projects, is difficult because of the complex indicators and multiple stakeholders involved. The purpose of this paper is to measure the public participation level in urban regeneration projects in China.Design/methodology/approachThis study adopts a perception difference-based method to measure the public participation level in urban regeneration projects in China. Specifically, an indicator system consisting of 12 indicators from three categories was first purposed. A perception difference-based method that integrates ANOVA test and Tukey test were then developed. The method was validated using five represented projects, and the results are interpreted based on a proposed measurement matrix.FindingsRegardless of the type of indicator, the perception of the government aligns with the perception of private sector professions, however, deviates from the perception of citizens. By taking the mean score and the significance level among stakeholders of perception as two dimensions, different patterns of issues in the current participation practice in urban regeneration are manifested.Research limitations/implicationsTheoretically, the proposed indicator system and perception difference-based method combined to provide a holistic view of public participation, which is verified to provide a better measurement. Practically, the authors’ methodology helps in revealing issues in current participation practice and further leading to designing coping strategies. Nonetheless, the proposed method requires further validation in participation practices in China and other countries.Originality/valueBy considering the perception mean and the significance level as two dimensions, a public participation measurement matrix is proposed. The performance in different indicators are classified into four stages accordingly, namely idling, starting, running-in and accelerating.

PurposeThough daycare centres are built to facilitate children's social and physical growth, divergent stakeholder perceptions yield conflicts while managing risks for each space due to the minimal guidelines in the Republic of Korea. Due to the unclearly defined knowledge and experience gap between representative stakeholders, teachers have difficulties in operating it with high satisfaction. This study therefore was conducted to systematically identify which parts of performance should be increased to preferentially increase end-user satisfaction in limited resources.Design/methodology/approachThis research conducted quantitative analysis gradually. Importance–performance analysis (IPA) grasped the perceptions of construction practitioners and end-users after identifying space composition and representative risks of daycare centres. Based on the factors influencing perception differences, principal component analysis and structural equation modelling (SEM) were conducted to determine which space improves the performance preferentially to increase overall end-user satisfaction.FindingsAs the utilisation of indoor spaces increases after COVID-19, improvement of indoor spaces except for indoor playroom is necessary, especially, advancement of the quality of teachers' rooms.Practical implicationsOutputs by reflecting the end-user experiences support to understand which spaces are managed from the limited resources.Originality/valueTheoretical framework for daycare centre was established in Korea where guidelines were insufficient, and differences in perception of each risk of stakeholders were identified. Moreover, gradual statistical analysis was set to construct end-user-focused centres by extracting where the performance of space should be improved in prior.

The traditional Southern Fujian architecture serves as a reflection of the region’s deeply rooted cultural values. However, research on the architectural and cultural heritage of Southern Fujian remains scarce. Accordingly, this study employs eye-tracking technology to experiment with 20 individuals with local cultural backgrounds and 20 without it to investigate the differences in the perception of the architectural heritage of Southern Fujian by individuals with disparate cultural backgrounds. The findings indicate that distinct groups evince disparate visual perceptions of the architectural and cultural heritage of Southern Fujian. The participants’ attention was divided into two categories: patterns and shapes and calligraphy and text. Non-locals were primarily drawn to patterns and shapes, whereas locals demonstrated a greater interest in the calligraphy and text category. The extraction of cultural information from calligraphic characters requires greater understanding and more time spent within the culture. Knowledge of local cultural backgrounds is helpful to better understand such information. This highlights the potential impact of Southern Fujian architecture on the local population. These findings provide a compelling rationale for the incorporation of multicultural elements in contemporary architectural design while also advocating for the preservation and advancement of Southern Fujian architectural heritage.

Accurate segmentation of esophageal cancers in CT images is crucial for disease treatment planning but remains difficult due to variable tumor morphology, low contrast with surrounding tissues, and blurred boundaries. We propose MDPNet, a Multi-scale Difference Perception Network for accurate esophageal cancer segmentation in CT images. MDPNet integrates three key modules, a Dynamic Feature Enhancement (DFE) strategy for global and local context fusion, a Cross-level Difference Modeling (CDM) module to highlight foreground–background differences, and a Multi-stage Foreground Enhancement (MFE) mechanism for progressive boundary refinement. Experiments on the self-built ECD 2D dataset and an external test set show that MDPNet achieves the best performance among state-of-the-art methods, with Dice coefficients of 0.82 and 0.78, respectively. MDPNet effectively improves segmentation accuracy and generalization, demonstrating preliminary generalization capability on our multi-center test sets, suggesting its potential as a decision-support tool.

Yan, S.L., 2020. The perception difference analysis of the influence of coastal residents of big data mining technology on marine tourism development. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 265-267. Coconut Creek (Florida), ISSN 0749-0208. With the continuous development of social economy in China, tourism as a major emerging industry gradually began to grow. As a choice direction of tourism, marine tourism has not only made great contributions to driving local economy and coordinating the comprehensive development of other industries, but also promoted the overall development of coastal cities. According to big data mining technology, this paper conceive a general model suitable for marine tourism development, and promote the healthy, stable and green development of marine tourism. Marine tourism has developed into the core industry of marine economy, and the future development prospects are bright. However, in the face of the blind exploitation of marine resources, it has caused serious damage to marine ecology. If the marine ecology can not be repaired and protected in time, the impact on marine tourism development will be devastating. Marine tourism is a brand new industry. After years of development, it has become the pillar of marine economy, and the future development space is huge. In recent years, the number of tourists received by the marine tourism industry has shown an upward trend every year, which also makes marine tourism face severe challenges. Therefore, digging deep into the development potential of marine tourism resources, deepening the quality and management level of tourism services, is an important way to meet the actual needs of tourists, optimize the existing industrial structure of tourism, and is also an important direction for the sustainable development of marine tourism industry.

Traditional color difference (CD) measurement methods cannot adapt to large sizes and complex content of photographic images. Existing deep learning-based CD measurement algorithms only focus on local features and cannot accurately simulate the human perception of CD. The objective of this paper is to propose a high-precision image CD measurement model that simulates the perceptual process of the human visual system and apply it to the CD perception of smartphone photography images. Based on this, a CD measurement network called CD-Attention is proposed, which integrates CNN and Vision Transformer features. First, a CNN and the ViT are used separately to extract local features and global semantic features from the reference image and the distorted image. Secondly, deformable convolution is used for attention guidance, utilizing the global semantic features of the ViT to direct CNN to focus on salient regions of the image, enhancing the transformation modeling capability of CNN features. Thirdly, through the feature fusion module, the CNN features that have been guided by attention are fused with the global semantic features of the ViT. Finally, a dual-branch network for high-frequency and low-frequency predictions is used for score estimation, and the final score is obtained through a weighted sum. Validated on the large-scale SPCD dataset, the CD-Attention model has achieved state-of-the-art performance, outperforming 30 existing CD measurement methods and demonstrating useful generalization ability. It has been demonstrated that CD-Attention can achieve CD measurement for large-sized and content-complex smartphone photography images. At the same time, the effectiveness of CD-Attention’s feature extraction and attention guidance are verified by ablation experiments.