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The aim of this article is two-fold. First, it offers a unique account of San Min, the prototype of the current Chinese educational principle proposed by Yan Fu (1854–1921) that aimed at improving people’s physical, intellectual and moral capacities. This system of educational thinking has received only marginal attention in Anglophone research literature. Second, given the influence of Yan Fu’s interpretation and promulgation of Herbert Spencer’s educational philosophy during that period, it investigates the extent to which San Min is derived from Spencer’s educational thought (the “Spencerian Triad”). This article focusses on how Yan Fu adapted the ideas of San Min from Spencer’s account.

This article considers Yan Fu’s principle of San Min in relation to Spencer’s educational triad through a close reading and comparison of key primary texts (including Yan Fu’s original writing). It explores the similarities and differences between each account of education’s goals and its proposed means of attainment.

Yan Fu’s principle of San Min is shown to have been adapted from the Spencerian Triad. However, using the theory of Social Organism, Yan Fu re-interpreted Spencer’s individual liberty as liberty for the nation. While Spencer’s goal was to empower individuals, Yan Fu aimed to serve collective independence, wealth and power.

This article addresses oversights concerning San Min’s Western origins in the Spencerian Triad and its influence on Chinese education under Yan Fu’s sway. It is significant because San Min is still at the core of the current Chinese educational policy.

This study aims to investigate the impact of regular Kung Fu and Taekwondo practice on the health and quality of life among elderly individuals in the Maule region, Chile.

The authors designed a 12-week Kung Fu and Taekwondo workshop with activities suitable for their age. Through semistructured interviews (at the beginning and the end of the workshop), along with periodic monitoring of vital signs and cardiovascular components, the authors observed an improvement in participants’ physical (strength, speed of reaction and flexibility) and psychological conditions (self-esteem and resilience), quality of life (relationships with family and friends and ability to deal with stressful events in working life) and health (waist circumference, percentage of oxygen saturation in blood, blood pressure, among other values).

From these results, the authors affirm that this workshop improves health and physical condition and helps the participants develop the coping capacity to deal with stressful situations and complicated interpersonal relationships. In this sense, the authors conclude that Kung Fu and Taekwondo as regular sports activities can benefit senior citizens’ aging process.

This research is based on an original study project.

Ensuring the safety of structures is important. However, when a structure possesses both an implicit performance function and an extremely small failure probability, traditional methods struggle to conduct a reliability analysis. Therefore, this paper proposes a reliability analysis method aimed at enhancing the efficiency of rare event analysis, using the widely recognized Relevant Vector Machine (RVM).

Drawing from the principles of importance sampling (IS), this paper employs Harris Hawks Optimization (HHO) to ascertain the optimal design point. This approach not only guarantees precision but also facilitates the RVM in approximating the limit state surface. When the U learning function, designed for Kriging, is applied to RVM, it results in sample clustering in the design of experiment (DoE). Therefore, this paper proposes a FU learning function, which is more suitable for RVM.

Three numerical examples and two engineering problem demonstrate the effectiveness of the proposed method.

By employing the HHO algorithm, this paper innovatively applies RVM in IS reliability analysis, proposing a novel method termed RVM-HIS. The RVM-HIS demonstrates exceptional computational efficiency, making it eminently suitable for rare events reliability analysis with implicit performance function. Moreover, the computational efficiency of RVM-HIS has been significantly enhanced through the improvement of the U learning function.

This research aims to examine the link between distributed leadership and team ambidexterity and the sequential mediation of team climate innovation and knowledge management in this relationship.

This study draws on a sample of 546 knowledge workers involved within 157 service research and development (R&D) teams of knowledge-intensive firms (KIFs) and uses partial least squares-structural equation modelling (PLS-SEM) through SMART PLS 4 to analyse the data collected.

Findings reveal that distributed leadership has a significant direct impact on team ambidexterity. Besides, they indicate that team climate innovation and knowledge management in teams mediate this link. Results also highlight the sequential mediation of team climate innovation and knowledge management in teams, linking distributed leadership to team ambidexterity.

This study explores the relationship between distributed leadership and ambidexterity at the team level and proposes a sequential mediation model linking these variables through team climate innovation and knowledge management in teams. It offers practical insights for KIFs’ managers on the importance of using a distributed leadership approach and building a team climate innovation to motivate R&D teams, encourage dynamic participation in knowledge management practices and cultivate both exploitative and exploratory learning activities.

This study aims to help scholars comprehend the major research themes on sustainable development goals (SDGs) in higher education which researchers from various fields have explored and to propose several potential future research directions of the least researched SDG in higher education to support scholars in making up the gap in the field.

The authors adopted a bibliometric analysis method to review the extant literature from the Web of Science on SDGs in higher education from 2015 to 2023 and took a closer examination of the most researched SDGs discussed by scholars. This study specifically concentrated on studies that explicitly mentioned the term “Sustainable Development Goal” (or “SDG”) and applied VOSviewer to cluster common keywords of the most researched SDGs and explored related themes. Also, this study provided several potential future research directions of least researched SDG in higher education.

SDGs 3 and 4 were the most researched, and SDG 15 was the least researched. The three major themes of SDG 3 were Adult Issues of Sustainability, South Africa Issues of Sustainability, and Relationship between SDG 3 and SDG 4. The three major themes of SDG 4 were the Role of Universities in Sustainability, Sustainability during Covid-19, and Challenges of Implementation.

This study provided several potential future research directions of the least researched SDG in higher education to support scholars to make up the gap in the field. Also, this study pointed out some pedagogical strategies and competencies needed to aid higher education institutions in achieving the 17 SDGs.

The purpose of this study is to investigate the thermomechanical condition on the shape memory property of Polybutylene adipate-co-terephthalate (PBAT). PBAT is a widely researched and rapidly developed biodegradable copolyester. In a tensile test, we found that the fractured PBAT samples had a heat-driven shape memory effect which piqued our interest, and it will lay a foundation for the application of PBAT in new fields (such as heat shrinkable film).

The shape memory effect of PBAT and the effect of the thermomechanical condition on its shape memory property were confirmed and systematically investigated by a thermal mechanical analyzer and tensile machine.

The results showed that the PBAT film had broad shape memory transform temperature and exhibited excellent thermomechanical stability and shape memory properties. The shape memory fixity ratio (Rf) of the PBAT films was increased with the prestrain temperature and prestrain, where the highest Rf exceeded 90%. The shape memory recovery ratio (Rr) of the PBAT films was increased with the shape memory recovery temperature and decreased with the prestrain value, and the highest Rr was almost 100%. Moreover, the PBAT films had high shape memory recovery stress which increased with the prestrain value and decreased with the prestrain temperature, and the highest shape memory recovery stress can reach 7.73 MPa.

The results showed that PBAT had a broad shape memory transform temperature, exhibited excellent thermomechanical stability and shape memory performance, especially for the sample programmed at high temperature and had a larger prestrian, which will provide a reference for the design, processing and application of PBAT-based heat shrinkable film and smart materials.

This study confirmed and systematically investigated the shape memory effect of PBAT and the effect of the thermomechanical condition on the shape memory property of PBAT.

Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

The purpose of this study is to improve the mechanical property and processing performance and reduce the cost of the polylacticacid/polybutyleneadipate-co-terephthalate(PLA/PBAT) composites, the calcium carbonate (CaCO₃) and compatibilizer styrene-maleicanhydride copolymer (SMA-2025) were added to the PLA/PBAT system, and the effect of CaCO₃ and SMA-2025 on the morphology, structure, mechanical property, thermal property, thermalstability and shape memory property of the CaCO₃/PLA/PBAT composites were studied and discussed.

The CaCO₃/PLA/PBAT shape memory composites were prepared via melt-blending and hot-pressing methods, and the effect of CaCO₃ and SMA-2025 on the property of the composites was investigated via scanning electron microscope, universal testing instrument, Fourier transform infrared spectroscopy, differential scanning calorimetry, thermogravimetric analysis and DMA, respectively.

The interface property, mechanical property, thermal stability, shape memory recovery ratios and recovery stresses, and processing performance of the CaCO₃/PLA/PBAT shape memory composites were significantly improved by adding of CaCO₃ and SMA-2025. Moreover, the CaCO₃/PLA/PBAT composites have good blowing film processing performance.

This study will provide a reference for the research, processing and application of the high-performance CaCO₃/PLA/PBAT shape memory composites.

We examined the attitudes of millennial-aged business students toward economic, social and environmental corporate responsibility (CR). Currently, these individuals are of an age that they have entered the workforce and are now ascending or have ascended into roles of leadership in which they have decision-making power that influences their company’s CR agenda and implementation. Thus, following the ecological systems perspective, we tested both the macro influence of cultural values (survival/self-expression and traditional/secular-rational values) and structural forces (income inequality, welfare socialism and environmental vulnerability) on these individuals’ attitudes toward CR.

This is a multilevel study of 3,572 millennial-aged students from 28 Asian, American, Australasian and European societies. We analyzed the data collected in 2003–2009 using hierarchical linear modeling.

In our multilevel analyses, we found that survival/self-expression values were negatively related to economic CR and positively related to social CR while traditional/secular-rational values was negatively related to social CR. We also found that welfare socialism was positively related to environmental CR but negatively related to economic CR while environmental vulnerability was not related to any CR. Lastly, income equality was positively related to social CR but not economic or environment responsibilities. In sum, we found that both culture-based and structure-based macro factors, to varying extents, shape the attitudes of millennial-aged students on CR in our sample.

Our study is grounded in the ecological systems theory framework, combined with research on culture, politico-economics and environmental studies. This provides a multidisciplinary perspective for evaluating and investigating the impact that societal (macro-level) factors have on shaping attitudes toward businesses’ engagement in economic, social and environmental responsibility activities. Additionally, our multilevel research design allows for more precise findings compared to a single-level, country-by-country assessment.

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. Leveraging current train operation data, these models enable swift and precise predictions, addressing challenges posed by train delays in high-speed rail networks during unforeseen events.

This paper proposes CBLA-net, a neural network architecture for predicting late arrival times. It combines CNN, Bi-LSTM, and attention mechanisms to extract features, handle time series data, and enhance information utilization. Trained on operational data from the Beijing-Tianjin line, it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.

This study evaluates our model's predictive performance using two data approaches: one considering full data and another focusing only on late arrivals. Results show precise and rapid predictions. Training with full data achieves a MAE of approximately 0.54 minutes and a RMSE of 0.65 minutes, surpassing the model trained solely on delay data (MAE: is about 1.02 min, RMSE: is about 1.52 min). Despite superior overall performance with full data, the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals. For enhanced adaptability to real-world train operations, training with full data is recommended.

This paper introduces a novel neural network model, CBLA-net, for predicting train delay times. It innovatively compares and analyzes the model's performance using both full data and delay data formats. Additionally, the evaluation of the network's predictive capabilities considers different scenarios, providing a comprehensive demonstration of the model's predictive performance.