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The Qin Zheng, an ancient Chinese musical instrument, embodies centuries of cultural heritage and artistic expression. Amidst its strings, melodies resonate with stories of ancient China, reflecting the country’s rich history and cultural identity. The objective of this study is to analyze the Qin Zheng playing techniques of Zhou Wang in musical literacy development. The research investigates Zhou Wang’s historical development, pedagogical approach, and playing techniques through a qualitative analysis. The study focuses on the Xi’an Conservatory of Music as the primary research site, where Zhou Wang has taught and mentored students for over three decades. Key informants include Zhou Wang herself, her students, and colleagues in the field of Chinese musical education. Data analysis involves structured interviews, observations of performances and teaching sessions, and transcription of musical examples. The findings reveal Zhou Wang’s mastery of Qin Zheng techniques, including intricate right-hand and left-hand skills, and their significance in fostering musical literacy development. The study highlights the potential benefits of integrating music education, particularly traditional Chinese music like Qin Zheng, into curricula as a means to enrich students’ language skills, cognitive abilities, and emotional intelligence.

In the process of educational practice in the digital age, the higher education system has shifted to the online model, and the training of college students’ deep learning has become the core issue. While online teaching offers great possibilities for education, its inherent lack of interaction has always been a major limiting factor in its effectiveness. To address this challenge, interactive pedagogy is an interaction-based teaching model in which students learn knowledge more effectively through communication and interaction with teachers and classmates, which helps to improve students’ learning abilities. This study, rooted in the theoretical framework of self-determination theory and utilizing structural equation modeling for empirical analysis, seeks to investigate the influence of online interactive teaching on deep learning among university students. The research reveals that interactive teaching significantly and directly contributes to deep learning, while the fulfillment of university students’ three fundamental psychological needs indirectly fosters deep learning by fostering intrinsic motivation. This study uncovers novel dimensions of factors influencing deep learning and underscores the vital role of interactive teaching in fostering deep learning among university students. Moreover, this not only deepens the application of self-determination theory in education but also provides valuable theoretical support for online education practices.

The objective of this study was to elucidate the transmission pathways and spatial distribution of potential source areas for PM2.5 pollution in Chenzhou City across diverse seasons in southern Hunan. Utilizing Sampling Kriging interpolation analysis, we modeled the temporal and spatial oscillations of PM2.5 concentrations in Chenzhou City, complemented by HYSPLIT air mass backward trajectories. Furthermore, the model conducted cluster analysis to identify discernible patterns. Our findings unveiled marked seasonal variations in PM2.5 concentrations within Chenzhou City. The pinnacle is discerned during winter (75.13 μg·m−3), whereas the nadir is pronounced in summer (27.64 μg·m−3). Notably, the PM2.5/PM10 ratio surpasses 0.55 during both autumn and winter. Spatially, Chenzhou exhibits an annual average distribution of PM2.5 pollution characterized by a gradient “from north to south in the western and central sectors, tapering towards the east”. Pollution source analysis suggests that PM2.5 pollution in Chenzhou City is predominantly ascribed to local emissions. Transmission pathway analysis reveals that the primary transmission corridors, spanning northwest Guangdong, southwestern Henan, Hubei, southern Anhui, and specific zones of southwestern Jiangxi, consistently align with external PM2.5 pollution sources affecting Chenzhou City throughout the year. Noteworthy seasonal disparities emerge in the spatial distribution and contribution of potential source regions. During spring, autumn, and winter, the predominant contributing regions are primarily located in adjacent provinces. In contrast, during summer, regions with relatively elevated values predominantly streak across the central and western sectors of Jiangxi and the southeastern Hunan region. A comprehensive examination of the seasonal distribution patterns, potential transmission routes, and likely contributing sources of PM2.5 in Chenzhou City can offer invaluable insights for regional atmospheric environmental governance. Furthermore, it underscores the paramount importance of collaborative regional strategies directed towards the prevention and control of PM2.5 pollution.

This study aims to provide a precise assessment of the distribution of educational facilities within the Guangdong–Hong Kong–Macao Greater Bay Area, serving as a crucial foundation for managing educational resource allocation and enhancing the quality of educational services. Utilizing a kernel density analysis, global autocorrelation analysis, and geographic detectors, this research systematically analyzes the spatial distribution characteristics and influencing factors of educational facilities in the area. The findings reveal significant geographical disparities in facility distribution with dense clusters in urban centers such as Guangzhou and Shenzhen, and less dense distributions in peripheral areas like Zhongshan and Macau. These facilities exhibit a multi-center cluster pattern with strong spatial autocorrelation, mainly influenced by the population size and economic and urban development levels. The results provide actionable insights for refining educational planning and resource allocation, contributing to the enhancement of educational quality across diverse urban landscapes.

The existing literature on environmentally responsible behavior in tourists focuses primarily on the factors that influence this behavior, such as tourists’ attitudes and negative feelings. However, the intrinsic benefits of conservation for individual and societal well-being are often overlooked. Under the theoretical lens of self-expansion theory, this study examined the influence of Chinese tourists’ tourism autobiographical memory on their environmentally responsible behavior using a questionnaire survey (N = 434) with partial least squares structural equation modeling. The result attested that tourists’ self-expansion and psychological richness serially mediate the association between their tourism autobiographical memory and environmentally responsible behavior as a tourist. In addition, the implicit theories of personality moderate the prediction of tourist autobiographical memory on self-expansion. The results provide an additional explanation for environmentally responsible behavior in tourists, with practical implications for marketers and operators in the industry.

This paper investigates the temporal trend and regional disparity of China’s agricultural green total factor productivity (AGTFP) during 1997-2016. Combined with the green Luenberger productivity indicator, two different data envelopment analysis models with the biennial environmental technology are constructed for robust checks. Compared with the existing literature, more agricultural carbon emissions are used as the undesirable outputs in the models. It is found that AGTFP in the whole of China and all of its sub-regions (the east, the middle, and the west) showed an overall increase, with the drive of high technical progress. The east had the largest AGTFP, and the middle experienced the largest AGTFP growth. More specifically, with respect to AGTFP, the total difference and the gross difference among the three regions as well as the specific difference within regions widened during these periods. There was an absolute convergence trend of AGTFP in the whole of China as well as the middle and the west. The speed of convergence was highest in the west.

The goals and transformation of sustainable urban development require fundamental innovation; however, urban innovation is a cyclical process, the paradigm of innovation itself needs to be dramatically transformed, and all innovation key elements need to be coordinated with each other to achieve sustainable urban outputs. Based on this, this paper uses the absorptive capacity theory to construct a model of the relationships between the acquisition dimension, digestion dimension, conversion dimension, utilization dimension, and sustainable development in the innovation process of smart cities and uses the fuzzy set qualitative comparative analysis (FSQCA) method to investigate the configuration mechanism in depth to show how the innovation process of these cities affects their sustainable development, taking the top 72 cities in China in terms of innovation capacity in 2020 as the research objects. The results of the study form three complex configuration paths that affect sustainable urban development, centered on the transformation of technological achievements, innovation management drive, and smart cities, and reveal that the economic and market foundations as the dimensions of urban innovation acquisition are not the core conditions for sustainable urban development. Based on this, this study develops a configuration classification for innovative cities that can achieve sustainable development, i.e., industrial paths, governance paths, and technology paths, and proposes strategic directions for sustainable urban innovation development.

This research is based on structural theory and innovation diffusion theory, exploring the theoretical foundations and influencing factors of urban green innovation to provide theoretical support for the realization of the world’s sustainable development goals (SDGs). By using the methods of Data Envelopment Analysis with Slacks-Based Measure (DEA) non-expected model, Necessary Condition Analysis of Research Methods (NCA), and Fuzzy Set Qualitative Comparative Analysis (fsQCA) in combination, the research analyzes the variables influencing the capability of urban green innovation. The study finds that the level of urban culture and absorptive capacity are necessary conditions for urban green innovation, with urban absorptive capacity having a high level of influence. The main paths for urban green innovation are a comprehensive cultural innovation path, an open cultural inclusion path, an open participation innovation integration path, and an outcome transformation to drive the innovation path. In addition, the research discovered patterns of cultural influence that go beyond institutional and resource-based structural factors, subject action processes, and transformation models guided by absorption and sustainable participation. The research results have important significance for understanding the driving factors and promotion paths of urban green innovation, providing empirical evidence for the realization of the world’s SDGs.

Purpose The ever-changing technological advancement and the unprecedented challenges brought about by COVID-19 pandemics have highlighted the vulnerability of many economic sectors, casting doubts on what should we still learn and how should we learn. In coping with the challenges and evolutions, tourism educators have been deploying new or modifying existing pedagogies to adapt to the changes. Using a bibliometric analysis via Citespace, 847 hotel and tourism education articles related to pedagogy from year 2000 to 2022 from Web of Science were examined in this study. This study aims to identify the change of research facets of knowledge production in tourism pedagogies at different phases. Findings shed light on the change of tourism pedagogies as a reflection of addressing the tourism market and stakeholders’ needs. Five broad research themes were identified, including critical pedagogy, online learning, sustainability education, tourism action transformation and adaptability to changes. Research findings provide a systematic review of tourism pedagogies across the world.

The objective of this study was to elucidate the transmission pathways and spatial distribution of potential source areas for PM[sub.2.5] pollution in Chenzhou City across diverse seasons in southern Hunan. Utilizing Sampling Kriging interpolation analysis, we modeled the temporal and spatial oscillations of PM[sub.2.5] concentrations in Chenzhou City, complemented by HYSPLIT air mass backward trajectories. Furthermore, the model conducted cluster analysis to identify discernible patterns. Our findings unveiled marked seasonal variations in PM[sub.2.5] concentrations within Chenzhou City. The pinnacle is discerned during winter (75.13 μg·m[sup.−3]), whereas the nadir is pronounced in summer (27.64 μg·m[sup.−3]). Notably, the PM[sub.2.5]/PM[sub.10] ratio surpasses 0.55 during both autumn and winter. Spatially, Chenzhou exhibits an annual average distribution of PM[sub.2.5] pollution characterized by a gradient “from north to south in the western and central sectors, tapering towards the east”. Pollution source analysis suggests that PM[sub.2.5] pollution in Chenzhou City is predominantly ascribed to local emissions. Transmission pathway analysis reveals that the primary transmission corridors, spanning northwest Guangdong, southwestern Henan, Hubei, southern Anhui, and specific zones of southwestern Jiangxi, consistently align with external PM[sub.2.5] pollution sources affecting Chenzhou City throughout the year. Noteworthy seasonal disparities emerge in the spatial distribution and contribution of potential source regions. During spring, autumn, and winter, the predominant contributing regions are primarily located in adjacent provinces. In contrast, during summer, regions with relatively elevated values predominantly streak across the central and western sectors of Jiangxi and the southeastern Hunan region. A comprehensive examination of the seasonal distribution patterns, potential transmission routes, and likely contributing sources of PM[sub.2.5] in Chenzhou City can offer invaluable insights for regional atmospheric environmental governance. Furthermore, it underscores the paramount importance of collaborative regional strategies directed towards the prevention and control of PM[sub.2.5] pollution.