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Polyethylene terephthalate (PET) as a fiber molding polymer is widely used in aerospace, electrical and electronic, clothing and other fields. The purpose of this study is to improve the thermal insulation performance of polyethylene terephthalate (PET), the SiO₂ aerogel/PET composites slices and fibers were prepared, and the effects of the SiO₂ aerogel on the morphology, structure, crystallization property and thermal conductivity of the SiO₂ aerogel/PET composites slices and their fibers were systematically investigated.

The mass ratio of purified terephthalic acid and ethylene glycol was selected as 1:1.5, which was premixed with Sb₂O₃ and the corresponding mass of SiO₂ aerogel, and SiO₂ aerogel/PET composites were prepared by direct esterification and in-situ polymerization. The SiO₂ aerogel/PET composite fibers were prepared by melt-spinning method.

The results showed that the SiO₂ aerogel was uniformly dispersed in the PET matrix. The thermal insulation coefficient of PET was significantly reduced by the addition of SiO₂ aerogel, and the thermal conductivity of the 1.0 Wt.% SiO₂ aerogel/PET composites was reduced by 75.74 mW/(m · K) compared to the pure PET. The thermal conductivity of the 0.8 Wt.% SiO₂ aerogel/PET composite fiber was reduced by 46.06% compared to the pure PET fiber. The crystallinity and flame-retardant coefficient of the SiO₂ aerogel/PET composite fibers showed an increasing trend with the addition of SiO₂ aerogel.

The SiO₂ aerogel/PET composite slices and their fibers have good thermal insulation properties and exhibit good potential for application in the field of thermal insulation, such as warm clothes. In today’s society where the energy crisis is becoming increasingly serious, improving the thermal insulation performance of PET to reduce energy loss will be of great significance to alleviate the energy crisis.

In this study, SiO₂ aerogel/PET composite slices and their fibers were prepared by an in situ polymerization process, which solved the problem of difficult dispersion of nanoparticles in the matrix and the thermal conductivity of PET significantly reduced.

This study aims to examine the links between carbon emissions, electric vehicles, economic growth, energy use, and urbanisation in 15 countries from 2010 to 2020.

This study adopts seminal panel methods of moments quantile regression with fixed effects to trace the distributional aspect of the relationship. The reliability of methods is confirmed via fully modified ordinary least squares coefficients.

This study reveals that fossil fuel use, economic activity, and urbanisation negatively impact environmental quality, whereas renewable energy sources have a significant positive long-term effect on environmental quality in the selected panel of countries.

The main limitation of this study is the generalisability of the findings, as the study is confined to a limited number of countries, and focuses on non-renewable and renewable energy sources.

Finally, this study proposes several policy recommendations for decision-makers and policymakers in the 15 nations to address climate change, boost sales of electric vehicles, and increase the use of renewable energy sources.

This study calls for a comprehensive transition towards green energy in the transportation sector, enhancing economic growth, fostering employment opportunities, and improving environmental quality.

The challenges faced by China's high-end equipment manufacturing (HEEM) industry are becoming clearer in the process of global supply chain (GSC) reconfiguration. The purpose of this study is to investigate how China's HEEM industry has been affected by the GSC reconfiguration, as well as its short- and long-term strategies.

The authors adopted a multi-method approach. Interviews were conducted in Phase 1, while a three-round Delphi survey was conducted in Phase 2 to reach consensus at the industry level.

The GSC reconfiguration affected China's HEEM supply chain (SC). Its direct effects include longer lead times, higher purchasing prices and inconsistent supply and inventory levels of key imported components and materials. Its indirect effects include inconsistent product quality and cash flows. In the short term, China's HEEM enterprises have sought to employ localized substitutes, while long-term strategies include continuous technological innovation, industry upgrades and developing SC resilience.

This study not only encourages Chinese HEEM enterprises to undertake a comprehensive examination of their respective industries but also provides practical insights for SC scholars, policymakers and international stakeholders interested in how China's HEEM industry adapts to the GSC reconfiguration and gains global market share.

This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic response signals.

The paper conducts time-frequency analysis on signals of pavement dynamic response initially. It also uses two common noise reduction methods, namely, low-pass filtering and wavelet decomposition reconstruction, to evaluate their effectiveness in reducing noise in these signals. Furthermore, as these signals are generated in response to vehicle loading, they contain a substantial amount of data and are prone to environmental interference, potentially resulting in outliers. Hence, it becomes crucial to extract dynamic strain response features (e.g. peaks and peak intervals) in real-time and efficiently.

The study introduces an improved density-based spatial clustering of applications with Noise (DBSCAN) algorithm for identifying outliers in denoised data. The results demonstrate that low-pass filtering is highly effective in reducing noise in pavement dynamic response signals within specified frequency ranges. The improved DBSCAN algorithm effectively identifies outliers in these signals through testing. Furthermore, the peak detection process, using the enhanced findpeaks function, consistently achieves excellent performance in identifying peak values, even when complex multi-axle heavy-duty truck strain signals are present.

The authors identified a suitable frequency domain range for low-pass filtering in asphalt road dynamic response signals, revealing minimal amplitude loss and effective strain information reflection between road layers. Furthermore, the authors introduced the DBSCAN-based anomaly data detection method and enhancements to the Matlab findpeaks function, enabling the detection of anomalies in road sensor data and automated peak identification.

This study aims to investigate whether auditors compromise their independence for economically important clients in countries with a secrecy culture.

The authors empirically examine the research question based on a data set of 33 countries for the period from 1995 to 2018. The dependent variable is the auditors’ propensity to issue modified audit opinions, which is a proxy for auditor independence. The authors use relative client size as a proxy for client importance. The authors adopt the Heckman (1979) two-stage model to mitigate the potential endogeneity issue involved in the selection of Big-N auditors.

Using a large sample of firms and controlling for the firm- and country/region-level factors, this study reveals that both Big-N and non-Big-N auditors are more likely to issue modified audit opinions to clients located in countries with a strong secrecy culture relative to those located in other countries. However, Big-N auditors are more likely to issue modified audit opinions for their economically important clients with a secrecy culture relative to their other clients, while no or weaker evidence is found for non-Big-N auditors. The results are consistent and robust to endogeneity tests and sensitivity analyses.

This study enriches the literature by providing a new perspective on auditor independence that an auditor’s reporting behavior can vary depending on the client’s importance and auditor type, even under the same secrecy culture.

As fertile soil for product promotion, online interest communities have gradually come into brands' view. However, existing research does not clarify whether brand engagement in consumer interaction is beneficial to the development of online interest communities. This study attempts to investigate the effects of brand engagement on the online interest community operation.

The authors propose a model that delineated the influence of brand engagement on consumers' citizenship behavior in the online interest community from the commitment-trust perspective. Scenario-based experiments were conducted and 536 data were collected by simple random sampling.

Results shows that a stronger perception of brand engagement has a positive influence on the relationship (trust and commitment) between the community and its users, which further influences online community citizenship behavior (feedback, advocacy and tolerance) of both posters and lurkers, especially for the posters. Although relationships are more complex, brand engagement activates the development of online interest communities to some extent.

This original study contributes to the commitment-trust theory by examining the impact of brand engagement on citizenship behavior via community commitment and trust in the online interest community context. In addition, this study compares the moderating effect of posters vs lurkers on the relationship between brand engagement and citizenship behavior in the online interest community.

This study aims to construct a mental health service system for middle school students in the post-COVID-19 era with the framework of Six Sigma DMAIC (define, measure, analyze, improve and control) and analyze the influencing factors of the mental health service system to study the implementation strategies of quality-oriented mental health services in middle schools.

This study was conducted in Tianjin, China, from September to November 2022, and 350 middle school students from Tianjin Public Middle School were selected as subjects. A questionnaire survey was used to collect data. In this study, the Six Sigma DMAIC method, sensitivity analysis method, exploratory factor analysis and principal component analysis were used to analyze the mental health services provided to middle school students.

Based on the Six Sigma DMAIC framework, this study indicates that the contribution rate of the mental health service process factor is the largest in the post-COVID-19 era. The mental health cultivation factor ranks second in terms of its contribution. Mental health quality and policy factors are also important in the construction of middle school students’ mental health service system. In addition, the study highlights the importance of parental involvement and social support in student mental health services during the post-COVID-19 era.

To the best of the authors’ knowledge, a study on middle school students’ mental health in the post-Covid-19 era has not yet been conducted. This study developed a quality-oriented mental health system and analyzed the influencing factors of mental health for middle school students based on data analysis and the Six Sigma DMAIC method.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

The purpose of this study is to examine the impact of MoS₂ on the microstructure and characteristics of micro-arc oxidized (MAO) ceramic coatings created on ZK60 magnesium alloy through the addition of varying concentrations of MoS₂ particles to the electrolyte, aiming to enhance the corrosion resistance of magnesium alloy.

The surface morphology, roughness and phase composition of the coatings were analyzed using scanning electron microscopy, a hand-held roughness tester and an X-ray diffractometer, respectively, and the corrosion resistance of the MAO coatings prepared by the addition of different contents of MoS₂ particles was tested and analyzed using an electrochemical workstation.

The results demonstrate that MoS₂/MgO composite coatings have been successfully prepared on the surface of magnesium alloys through micro-arc oxidation. Furthermore, the corrosion resistance of the ZK60 magnesium alloy prepared with the addition of 1.0 g/L MoS₂ was the best compared to the other samples.

MoS₂ particles were able to penetrate the coatings successfully during the micro-arc oxidation process, acting as a barrier in the micropores to prevent the corrosion medium from touching the surface, thus improving the corrosion resistance of the sample. The electrochemical workstation was used to study the corrosion resistance of the MoS₂/MAO coating on the ZK60 magnesium alloy.

This study aims to explore the effect of collaboration networks (domestic and international collaboration networks) on the innovation performance of small and medium-sized enterprises (SMEs). It also investigates the mediating role of business model innovation, the moderating role of entrepreneurial orientation and government institutional support between them.

Hierarchical regression analysis is adopted to test the hypotheses based on survey data provided by 223 manufacturing SMEs in China.

The results reveal that domestic and international collaboration networks positively affect SMEs' innovation performance. Business model innovation mediates domestic and international collaboration networks-SMEs’ innovation performance relationships. Entrepreneurial orientation positively moderates international collaboration networks–SMEs’ innovation performance relationship, and government institutional support positively moderates domestic and international collaboration networks–SMEs’ innovation performance relationships.

The findings indicate that managers of SMEs should invest in domestic and international collaboration networks and business model innovation to enhance SMEs' innovation performance. Moreover, entrepreneurial orientation and government institutional support should be valued when SMEs try to enhance their innovation performance by embedding in domestic and international collaboration networks.

This study broadens the authors' understanding of the relationship between collaboration networks and firms' innovation performance by classifying collaboration networks into domestic and international dimensions and investigating their direct impacts on SMEs' innovation performance. Besides, this study reveals how and when domestic and international collaboration networks influence the innovation performance of SMEs.