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To solve the demand for road damage object detection under the resource-constrained conditions of mobile terminal devices, in this paper, we propose the YOLO-LWNet, an efficient lightweight road damage detection algorithm for mobile terminal devices. First, a novel lightweight module, the LWC, is designed and the attention mechanism and activation function are optimized. Then, a lightweight backbone network and an efficient feature fusion network are further proposed with the LWC as the basic building units. Finally, the backbone and feature fusion network in the YOLOv5 is replaced. In this paper, two versions of the YOLO-LWNet, small and tiny, are introduced. The YOLO-LWNet was compared with the YOLOv6 and the YOLOv5 on the RDD-2020 public dataset in various performance aspects. The experimental results show that the YOLO-LWNet outperforms state-of-the-art real-time detectors in terms of balancing detection accuracy, model scale, and computational complexity in the road damage object detection task. It can better achieve the lightweight and accuracy requirements for object detection for mobile terminal devices.

Purpose Guided by the self-determination theory and theory of planned behaviour, this study aims to examine the determinants of participating in metaverse tourism for Gen Z and Gen Y. Design/methodology/approach The cross-sectional method was used to collect data from 248 respondents from Gen Z and Gen Y tourists. The research model was evaluated using the partial least squares-structural equation modelling (PLS-SEM). Findings The PLS-SEM results supported the positive effect of attitude and perceived behavioural control on tourists’ intention to participate in the metaverse tourism. In addition, the crucial role of intrinsic motivation in raising individuals’ cognitive beliefs about metaverse tourism was confirmed. Originality/value In addition to the theoretical contributions, the findings provide several managerial implications for tourism practitioners, scholars and metaverse developers to help them make insightful decisions and promote the development of metaverse tourism. 目的 在自我决定理论和计划行为理论的指导下, 本研究探讨了Z世代和Y世代参与元宇宙旅游的决定因素。 设计/方法论/方法 采用横截面法收集了248名Z世代和Y世代游客的数据。采用偏最小二乘-结构方程模型(PLS-SEM)对模型进行了分析。 结果 PLS-SEM结果支持态度和感知行为控制对游客参与元宇宙旅游意愿的积极影响。此外, 内在动机在提高个人对元宇宙旅游的认知信念方面的关键作用也得到了证实。 原创性/价值 本文为旅游从业者、学者和元宇宙旅游开发商提供了一些管理启示, 帮助他们做决策, 促进元宇宙旅游的发展。 Propósito Guiado por la teoría de la autodeterminación y la teoría del comportamiento planificado, este estudio examina los determinantes de la participación en el turismo del Metaverso para la Generación Z y la Generación Y. Diseño/metodología/enfoque Se utilizó el método transversal para recopilar datos de 248 turistas encuestados de la Generación Z y la Generación Y. El modelo de investigación se evaluó utilizando la metodología de ecuaciones estructurales de mínimos cuadrados parciales (PLS-SEM). Hallazgos Los resultados del PLS-SEM respaldan el efecto positivo de la actitud y el control percibido del comportamiento en la intención de los turistas de participar en el turismo en el metaverso. Además, se confirma el crucial papel, de la motivación intrínseca a la hora de elevar las creencias cognitivas de los individuos sobre el turismo del metaverso. Originalidad/valor Además de las contribuciones teóricas, los hallazgos proporcionan varias implicaciones empresariales para los profesionales del turismo, académicos y desarrolladores de Metaverso para ayudarles a tomar decisiones perspicaces y promover el desarrollo de este turismo.

The integration of luminescence and chirality in easy-scalable metal-organic frameworks gives rise to the development of advanced luminescent sensors. To date, the synthesis of chiral metal-organic frameworks is poorly predictable and their chirality primarily originates from components that constitute the frameworks. By contrast, the introduction of chirality into the pores of metal-organic frameworks has not been explored to the best of our knowledge. Here, we demonstrate that chirality can be introduced into an anionic Zn-based metal-organic framework via simple cation exchange, yielding dual luminescent centers comprised of the ligand and Tb 3+ ions, accompanied by a chiral center in the pores. This bifunctional material shows enantioselectivity luminescent sensing for a mixture of stereoisomers, demonstrated for Cinchonine and Cinchonidine epimers and amino alcohol enantiomers, from which the quantitative determination of the stereoisomeric excess has been obtained. This study paves a pathway for the design of multifunctional metal-organic framework systems as a useful method for rapid sensing of chiral molecules. Metal-organic frameworks with luminescence and chirality are promising for luminescent sensors for chiral molecules. Here, the authors use cation exchange to introduce chirality in multifunctional metal-organic framework systems for rapid enantioselective luminescent sensing.

The high-quality economic development (HQED) of the Yellow River Basin (YRB) faces dual constraints of growth momentum transformation and regional imbalance. New Quality Productive Forces (NQP) are regarded as a key breakthrough, yet the complex causal mechanisms through which they drive HQED remain unclear. Traditional research methods fall short in uncovering the multifactorial, concurrent causal relationships and the spatio-temporal dynamics involved. Therefore, drawing on panel data from 49 prefecture-level cities in the YRB from 2012 to 2022, this study employs the CRITIC–TOPSIS method and dynamic QCA to measure the HQED index and to explore in depth the configurational pathways and dynamic processes through which NQP evolution fosters the emergence of HQED. The findings are as follows: (1) During the study period, the HQED index of the YRB exhibited a “W-shaped” evolutionary trend, with a spatial gradient of “higher in the east and lower in the west.” (2) No single NQP factor emerged as a necessary condition for HQED. (3) The pathways to HQED in the YRB can be categorized into three models: the single-core innovation–driven model, the region-wide innovation resource synergy–driven model, and the comprehensive digital transformation–driven model. Technological innovation plays a universal role, but its effectiveness requires synergy with other factors to be fully realized. (4) While no obvious temporal effects were observed in the configurational pathways, significant spatial heterogeneity exists, with different urban agglomerations displaying distinct pathway preferences. This study reveals the complex interactive mechanisms through which NQP drives HQED in the YRB and provides refined policy implications for place-based and coordinated regional development.

PurposeAlthough the metaverse has gained popularity in recent days, research on metaverse tourism in urban destinations is still lacking. Drawing on existing cases in Chinese urban destinations, this paper aims to provide valuable insights into the development of metaverse tourism in China and provides managerial implications for future urbanmetaverse tourismplayers.Design/methodology/approachLiterature from Chinese and international sources was reviewed to highlight the current status of metaverse tourism in the context of Chinese urban tourism. This paper also draws on information provided by online materials, especially the official websites of tour organizers and news media.FindingsThis paper outlines important aspects of metaverse in Chinese urban tourism. First, cities are the hotbeds of metaverse development, and the metaverse has become a new way to attract urban tourists and a significant element in various exhibitions. Second, the combination of metaverse with China’s extensive and profound traditional culture has made urban tourism full of vitality. Third, China’s game companies are progressively empowering the metaverse tourism industry.Originality/valueThis paper contributes to the existing knowledge on metaverse tourism based on the Chinese urban tourism context. Furthermore, it highlights the state of the metaverse in Chinese urban tourism during and after the pandemic situation. Lastly, it provides thoughtful implications for tourism players and future tourism development.

PurposeThe purpose of this study is to present a comprehensive knowledge mapping and an in-depth analysis of pro-environmental travel behaviour research to better understand the global trend in this field that have emerged between 2000 and 2021.Design/methodology/approachIn this study, a visual analysis of 187 scholarly articles between the year 2000 and 2021 related to pro-environmental travel behaviour (PETB) is presented. Using the knowledge mapping based on CiteSpace it presents the current research status, which contains the analysis of collaboration network, co-citation network, and emerging trends.FindingsThe results revealed that the PETB is an emerging topic, which has an increased number of publications in recent years. Though the collaboration network between scholars is dispersed, some countries exert stronger collaboration network. Researchers from England, USA and China have worked more on this topic comparatively. “Pro-environmental norm” is found to be the major concern in regard to PETB, and the theory of planned behaviour (TPB) is the most common theory used by the scholars around the world. Ten articles with the highest citations are found to be the most valuable articles. COVID-19, value orientation, negative spillover, carbon footprints, biospheric and adolescent are some of the latest keywords based on the past two years' literature review, all of which have huge research potential in the future.Originality/valueThis study is among the pioneers to shed some light on the current research progress of PETB by using a bibliometric analysis to provide research directions for scholars. Moreover, this study utilized latest data from 2000 to 2021. The studies which are published before and during the pandemic are also incorporated.

Road surface damage detection is crucial in highway maintenance and traffic safety maintenance. However, existing detection methods generally suffer from insufficient generalization capability, poor detection of tiny damage, and difficulty balancing detection accuracy and computational cost. This study proposes a novel road surface damage object detection model (RSDD) to address these challenges. Firstly, a backbone applied to road surface damage feature extraction is designed to solve the problems of feature loss and insufficient extraction of tiny damage during feature extraction. Second, to achieve efficient feature fusion, multiple attention is introduced to optimize features at different stages. Then, a bi-directional feature fusion path is proposed to realize the information exchange between features of different stages, and an enhanced feature pyramid is constructed. Finally, a multi-scale decoupled detection head is adopted to realize the accurate detection of different sizes of damage. Additionally, this study built a road dataset containing rich samples of tiny damage. Extensive comparative experiments are conducted on the collected dataset and a public dataset to validate the generalization performance of RSDD. The experimental results show that RSDD has significant advantages in tiny damage detection while having excellent trade-offs in terms of accuracy, scale, and speed. Specifically, the model achieves 70.8% and 61.2% mAP 50 on the two datasets with an inference latency of only 4.5 ms under the condition that the number of parameters is 16.5 M. Compared with YOLOv8s, which has a similar number of parameters, RSDD achieves 5.5% and 3.3% improvement in the detection accuracy, respectively, and speeds up the inference by 0.6 ms.

Severe COVID-19 elicits excessive inflammation mediated by innate immune cells like monocytes. Recent evidence reveals extensive epigenetic changes in monocytes during recovery from severe COVID-19, including increased chromatin accessibility at genes related to cytokine production and leukocyte activation. These changes likely originate from the reprogramming of upstream hematopoietic stem and progenitor cells (HSPCs) and represent “trained immunity”. HSPC-to-monocyte transmission of epigenetic memory may explain the persistence of these monocyte alterations despite their short lifespan. IL-6 appears pivotal for imprinting durable epigenetic modifications in monocytes during acute infection, with IL-1β potentially playing a contributory role. The poised inflammatory phenotype of monocytes post-COVID-19 may drive chronic inflammation and tissue damage, contributing to post-acute sequelae of COVID-19 symptoms. COVID-19 could also exacerbate inflammation-related diseases, such multisystem inflammatory syndromes, by altering innate immune tendencies via hematopoietic epigenetic reprogramming. Further clinical investigations quantifying inflammatory mediators and mapping epigenetic changes in HSPCs/monocytes of recovering patients are warranted. Research should also examine whether COVID-19 elicits transgenerational inheritance of epigenetic alterations. Elucidating mechanisms underlying COVID-19-induced monocyte reprogramming and developing interventions targeting key inflammatory regulators like IL-6 may mitigate the sustained inflammatory burden imposed by the aberrant trained immunity post-COVID-19.

Artificial photosynthesis of urea from NH 3 and CO 2 seems to remain still essentially unexplored. Herein, three isomorphic three-dimensional covalent organic frameworks with twofold interpenetrated ffc topology are functionalized by benzene, pyrazine, and tetrazine active moieties, respectively. A series of experiment results disclose the gradually enhanced conductivity, light-harvesting capacity, photogenerated carrier separation efficiency, and co-adsorption capacity towards NH 3 and CO 2 in the order of benzene-, pyrazine-, and tetrazine-containing framework. This in turn endows tetrazine-containing framework with superior photocatalytic activity towards urea production from NH 3 and CO 2 with the yield of 523 μmol g −1 h −1 , 40 and 4 times higher than that for benzene- and pyrazine-containing framework, respectively, indicating the heterocyclic N microenvironment-dependent catalytic performance for these three photocatalysts. This is further confirmed by in-situ spectroscopic characterization and density functional theory calculations. This work lays a way towards sustainable photosynthesis of urea. Artificial photosynthesis of urea from NH 3 and CO 2 remains difficult to achieve. Herein, by three altering the number of heterocyclic N atoms within a series of covalent organic frameworks, the authors report an increase in urea photosynthesis yields and efficiencies.

In recent years, the custom wardrobe market has been steadily developing. While meeting the functional needs of users, it is gradually shifting towards aesthetic preferences. Rapidly grasping users’ preferences for the appearance of custom wardrobes is a key focus of current research. This study collected a large number of decorative surface images of custom wardrobes and objectively analyzed the design features based on color moments and Tamura texture feature data in computer image analysis methods. K-means cluster analysis was performed on the feature data. Collected images of the points closest to the cluster centers were further screened to select representative finish images, and finally a questionnaire survey was conducted at Nanjing Forestry University, with the help of semantic differential method and factor analysis. The characteristics of the samples were comprehensively summarized to infer design elements. The study found that warm-toned, medium-low saturation, and medium brightness surfaces were preferred by the panel. Different colors, contrasts, saturations, brightness, element features, and arrangements have significantly different effects on visual perception. These conclusions can provide a reference for subsequent custom wardrobe design.