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Abstract Background Emotional eating is a prevalent maladaptive coping mechanism among college students, which is associated with mental health and sleep concerns. Though previous studies have established a link between sleep quality, depression and emotional eating, most of these have been in Western populations. In addition, few existing studies have taken physical activities into account, and the underlying mechanisms between these four variables remain to be further studied. Therefore, our study investigated the mediating role of depression and the moderating role of physical activity levels in the relationship between sleep quality and emotional eating among Chinese college students. Our study can help to understand the characteristics of this population and provide guidance on the intervention pathways for emotional eating. Methods A convenience sampling method was employed to select eligible participants for investigation. The General Information Questionnaire, the Pittsburgh Sleep Quality Index Scale, the Patient Health Questionnaire, the Dutch Eating Behavior Scale, and the International Physical Activity Questionnaire were employed to measure the general condition, sleep quality, depression, emotional eating, and physical activity. A total of 813 college students (Mage = 19.14, SD = 1.12, range = 17 ~ 25 years old, 71.1% females) completed the survey. The moderated mediation analysis was carried out using the SPSS PROCESS macro. Results After controlling for sex, age, and body mass index (BMI), sleep quality positively predicted emotional eating. Depression primarily mediated the association between them. Besides, physical activity levels moderated the relationship between sleep quality and emotional eating via depression. Depression significantly predicted emotional eating among students with low levels of physical activity; however, it was not significant among students with moderate or high levels of physical activity. Conclusions The role of depression mediates the link between sleep quality and emotional eating. Regular exercise can ease the symptoms of emotional eating through depression. This implies the importance of offering more sleep hygiene education and physical activity in university settings.

Abstract The solvent-free selective hydrogenation of nitroaromatics to azoxy compounds is highly important, yet challenging. Herein, we report an efficient strategy to construct individually dispersed Co atoms decorated on niobium pentaoxide nanomeshes with unique geometric and electronic properties. The use of this supported Co single atom catalysts in the selective hydrogenation of nitrobenzene to azoxybenzene results in high catalytic activity and selectivity, with 99% selectivity and 99% conversion within 0.5 h. Remarkably, it delivers an exceptionally high turnover frequency of 40377 h–1, which is amongst similar state-of-the-art catalysts. In addition, it demonstrates remarkable recyclability, reaction scalability, and wide substrate scope. Density functional theory calculations reveal that the catalytic activity and selectivity are significantly promoted by the unique electronic properties and strong electronic metal-support interaction in Co1/Nb2O5. The absence of precious metals, toxic solvents, and reagents makes this catalyst more appealing for synthesizing azoxy compounds from nitroaromatics. Our findings suggest the great potential of this strategy to access single atom catalysts with boosted activity and selectivity, thus offering blueprints for the design of nanomaterials for organocatalysis.

Computer-vision-based plant leaf segmentation technology is of great significance for plant classification, monitoring of plant growth, precision agriculture, and other scientific research. In this paper, the YOLOv8-seg model was used for the automated segmentation of individual leaves in images. In order to improve the segmentation performance, we further introduced a Ghost module and a Bidirectional Feature Pyramid Network (BiFPN) module into the standard Yolov8 model and proposed two modified versions. The Ghost module can generate several intrinsic feature maps with cheap transformation operations, and the BiFPN module can fuse multi-scale features to improve the segmentation performance of small leaves. The experiment results show that Yolov8 performs well in the leaf segmentation task, and the Ghost module and BiFPN module can further improve the performance. Our proposed approach achieves a 86.4% leaf segmentation score (best Dice) over all five test datasets of the Computer Vision Problems in Plant Phenotyping (CVPPP) Leaf Segmentation Challenge, outperforming other reported approaches.

Abstract Background Narrative medicine has become a solution to cultivate medical students’ ability of empathy and humanistic care. However, the role of narrative medicine is lacking in the study of professionalism. The aim of this study was to analyze the effects of narrative medical theory learning and narrative writing on professionalism, empathy and humanistic care ability of nursing students. Methods This cluster randomized controlled trial was conducted between June 2021 and June 2022 in two universities in Jiangsu, China. The participants of this study were 85 nursing students who were randomly divided into the intervention group (n = 43) or the control group (n = 42). Participants in the intervention group were trained in narrative medical theory learning and narrative writing based on a Web-based platform, while those in the control group were not. Self-report questionnaires of professionalism, empathy and humanistic care ability were used before and after intervention. Results The results showed that the professionalism score of the intervention group was (68.7 ± 6.8 vs. 64.5 ± 7.5; P = 0.005), empathy (99.4 ± 15.7 vs. 92.2 ± 14.6; P = 0.014) and humanistic care ability (127.6 ± 20.0 vs. 113.3 ± 18.8; P = 0.004) were better than the control group. Conclusion The results of this quantitative study suggest that narrative medical theory education and narrative writing based on the network platform can promote the development of professionalism, empathy and humanistic care ability of nursing undergraduates.

BackgroundStatistics indicate that the morbidity of breast cancer is increasing globally, and its (overall figures) incidence has now surpassed that of lung cancer for the first time. The relation between a whole dietary pattern, rather than of a single food or nutrient, and breast cancer (BC) should be examined for findings to capture the complexities of diet and the potential for synergism between dietary components. Hence, the effects of dietary patterns on breast cancer have recently attracted increasing attention.ObjectiveTo systematically review the effects of dietary patterns on breast cancer risk, prognosis, and quality of life in survivors.MethodsThis systematic review was conducted following PRISMA guidelines and was registered in PROSPERO. Data from Ovid, China Biomedical Literature Database, Wanfang Data Knowledge Service Platform, CNKI, PubMed, Weipu, The Cochrane Library, Duxiu Data, ProQuest, Embase, Web of Science, and Scopus Database were retrieved and evaluated.ResultsA total of 47 studies that investigated the association between eating patterns and breast cancer were identified. Ten studies evaluated the effect of the model on treatment outcome and prognosis of breast cancer and two cross-sectional studies examined the influence of dietary patterns on quality of life. The resulting favorable dietary patterns were shown to regulate metabolic biomarkers, antioxidants, anti-inflammatory agents, and protective genes, and inhibit cell proliferation and invasion.ConclusionNumerous studies have examined the effects of healthy eating, plant-based, anti-inflammation, low-fat, and other favorable dietary patterns in relation to breast cancer. However, few studies reported significant associations and the studies had limitations, suggesting that the current findings should be interpreted with caution.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, CRD4202 2350171.

Nurses often face a variety of work-related and life-related stresses that make them more prone to symptoms of post-traumatic stress disorder (PTSD), yet the underlying mechanism of this association is poorly understood. To address this research gap, we investigated the mediating role of maladaptive cognitive emotion regulation strategies in the relationship between perceived stress and PTSD symptoms, and explored whether psychological capital could moderate the direct or indirect effects between perceived stress and PTSD symptoms. Nurses (N = 723) completed a questionnaire about perceived stress, PTSD symptoms, maladaptive cognitive emotion regulation strategies and psychological capital. After controlling for gender, age and work department, perceived stress was positively correlated with PTSD symptoms. Maladaptive cognitive emotion regulation strategies partially mediated this relationship. Psychological capital moderates the effects of perceived stress and maladaptive cognitive emotion regulation strategies on PTSD symptoms. Specifically, the positive correlation between perceived stress and PTSD symptoms was stronger among nurses with low levels of psychological capital than among nurses with high levels of psychological capital. At the same time, the positive correlation between maladaptive cognitive emotion regulation strategies and PTSD symptoms was stronger in nurses with a low level of psychological capital. Therefore, cognitive strategies and interventions oriented toward psychological capital may alleviate the PTSD symptoms of nurses in stressful situations.

BackgroundWith the popularization of the Internet, it has become possible to widely disseminate health information via social media. Medical staff's health communication through social media can improve the public's health literacy, and improving the intention of health communication among nursing undergraduates is of great significance for them to actively carry out health communication after entering clinical practice.ObjectiveTo explore the relationship among eHealth literacy, social media self-efficacy, and health communication intention and to determine the mediating role of social media self-efficacy in the relationship between eHealth literacy and health communication intention.DesignA cross-sectional descriptive correlation design was used in this study.ParticipantsStratified cluster sampling was used to select 958 nursing students from four nursing colleges in Jiangsu Province, China, from June to July 2021.MethodsData were collected using the eHealth Literacy Scale, the Social Media Self-efficacy Scale, and the Health Communication Intention Questionnaire. Sociodemographic data were also collected. Correlation analysis and regression analysis were used to determine the relationship between eHealth literacy, social media self-efficacy, and health communication intention.ResultsHealth communication intention is positively correlated with eHealth literacy and social media self-efficacy. There is a significant positive correlation between eHealth literacy and health communication intention (β = 0.57, p < 0.001), and social media self-efficacy played a mediating role in the influence of eHealth literacy on health communication intention (the mediating effect accounted for 37.2% of the total effect).ConclusionThe study found that eHealth literacy and social media self-efficacy had an impact on health communication intention. Because there is a correlation between eHealth literacy and social media self-efficacy and health communication intention, in order to promote health communication intention of nursing students, it is also important to cultivate eHealth literacy and social media self-efficacy of nursing students. In view of these results, targeted educational programs must be developed to improve eHealth literacy and social media self-efficacy among nursing undergraduates, thereby promoting their health information transmission.

BackgroundA great proportion of college students experience various sleep problems, which damage their health and study performance. College students' sleep problems, which are caused by several factors, have been easily ignored before. In the past decade, more research has been published to expand our understanding of undergraduates' sleep. The purpose of the study is to explore the research hotspots and frontiers regarding college students' sleep using CiteSpace5.8.R3 and offer guidance for future study.MethodsWe retrieved relevant literature from the Web of Science Core Collection Database and imputed the downloaded files into CiteSpace5.8.R3 for visualization analysis. We generated network maps of the collaborations between authors, countries, institutions, the cited journals, and co-occurrence keywords. The analysis of keywords clusters, timeline views, and keywords citation bursts help us identify the hotspots and research trends.ResultsA total of 1,841 articles related to college students' sleep, published from 2012 to 2021, were selected. The number of publications gradually increased. Karl Peltzer was the most prolific authors with 15 publications. The United States and Harvard University separately contributed 680 and 40 articles and had the greatest impact in this field. SLEEP ranked first in the frequency of cited journals. The article published by Lund HG was the most influential publication. Based on the analysis of keywords, we summarized research hotspots as follows: current status, affecting factors, and adverse outcomes of college students' sleep. The frontiers were the further understanding of the relationships between sleep and mental and physical health, and various interventions for sleep disorders.ConclusionOur study illustrates the research hotspots and trends and calls for more research to expand the findings. In the future, the cooperation between institutions and authors needs to be strengthened. The complex relationships between sleep and mental and physical health and problematic substance use disorders are necessary to be explored. Longitudinal studies or randomized controlled trials should be constructed to verify the current findings or assumptions.

Acoustic wave sensors are being developed for many emerging applications such as in semiconductor fabrication, biological diagnostics and polymer characterization. Traditional acoustic wave sensing devices such as quartz crystal microbalance (QCM) rely on polymer thin films coated on quartz plates to detect chemical and biological agents. It has been found that significant sensitivity enhancement of QCM devices can be achieved by simply attaching a polymer micropillar film onto the QCM substrate (QCM-P) to enable a unique coupled resonance between the micropillars and quartz substrate. In the present work, an equivalent circuit model integrating mechanical vibration of micropillars and electrical load impedance of piezoelectric substrate was developed to predict the frequency shift and Q-factor of the QCM-P devices when operating in air and liquid environments. In the model, the vibration of micropillars was solved simultaneously with the liquid loading on the pillar surface. The resultant hydraulic force was integrated into the circuit model to predict the load impedance on the sensor surface. The developed model was validated by experimental results for QCM-P devices operating in air and water with different micropillar heights. It will serve as a powerful tool to predict the performance of the QCM-P devices for different applications.

The large diameter pitch bearing was made of steel 42CrMo4 and the laser hardening process was used to improve its surface properties. In this paper, a numerical approach which can predict the temperature field and the hardened depth is provided for the laser hardening process of the 42CrMo4 steel. According to the simplification of the raceway structure of pitch bearing, the finite element model was constructed using ABAQUS software. Based on the actual process parameters, the transient thermal analysis was accomplished and the distribution of temperature field is analyzed. The hardened depth is determined according to the proposed temperature range. Laser power, laser scanning speed, and spot diameter were considered as input parameters, the experimental studies were performed based on orthogonal design in order to study the effects of process parameters. The finite element model is validated. The surface roughness and microstructure studies on treated surfaces were conducted. Also the micro-hardness testing was performed. The results show that the laser hardening increases surface hardness by about 3.8 times than that of the base material. The three parameters of laser power, laser scanning speed, and spot diameter have a coupling effect on the surface treatment. The input laser power density is more important.

Laser surface hardening is used to improve the fatigue performance of the large diameter pitch bearing. Determination of the process parameters by a trial and error method, depending on the experience of the technician, by changing the parameters repeatedly for each laser surface hardening process is time-consuming and costly. In this paper, a method of analyzing the maximum temperature and depth of a hardened layer during the laser surface hardening process for a pitch bearing raceway of a wind turbine is proposed, which combines finite element simulation and the Kriging model. A three-dimensional finite element model of a pitch bearing ring was established using ABAQUS. The temperature field analysis was performed. The effects of process parameters including laser power, scanning speed, and laser spot radius on the depth of the hardening layer were investigated. Then, taking into account the interactional effects of different process parameters, Kriging models were constructed to reflect the relationship between input process parameters and output responses. The results show that the Kriging approximation model has a small relative error compared with the simulated results and can be used to predict the hardened layer depth.