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High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

This paper aims to study the impact of the interaction effects between live-streaming marketing and clothing type on consumers' intention to purchase clothing, and the mediating effect of internalization and identification on the relationship between them.

This paper conducts a scenario experiment to 486 consumers who had experience in purchasing clothing on the live-streaming platform and employs the analysis of variance, structural equation model and multivariate regression model.

Our findings reveal that professional live-streaming marketing (PLSM) can better stimulate consumers' intention to purchase formal clothing than entertainment live-streaming marketing (ELSM) does. Compared with PLSM, ELSM can better stimulate consumers' intention to purchase casual clothing. When PLSM promotes formal clothing, it triggers the internalization mechanism of consumers, so as to improve their purchase intention. When ELSM promotes casual clothing, it triggers consumers' identification mechanism, so as to improve their purchase intention.

This paper helps to identify the differences in the impact of different types of live-streaming marketing on consumers' intention to purchase different types of clothing, as well as the mediating role of internalization and identification mechanisms. This paper provides a theoretical reference for clothing firms to strategically select the appropriate type of live-streaming marketing.

This paper aims to explore the impact of green finance on the heterogeneity of enterprise green technology innovation and the underlying mechanism between them.

Using the data of China's A-share listed enterprises from 2008 to 2020 and the fixed effect model, the authors empirically explore the relationship and mechanism between green finance and green technology innovation by constructing the green finance index while considering both the quality and quantity of innovation.

The study suggests that green finance is positively related to the quality and quantity of enterprise green technology innovation, while green finance is more effective in stimulating the quality of green technology innovation than quantity. In addition, alleviating financial mismatch and improving the quality of environmental information disclosure are core mechanisms during the process of green finance facilitating green technology innovation. Furthermore, green finance exerts a more positive effect on the quality and quantity of green technology innovation with large-size enterprises, heavily polluting industries and enterprises in the eastern region.

This paper enriches the literature on green finance and green technology innovation and provides practical significance for green finance implementation.

Nano graphitic-carbon nitride (g-C₃N₄) is an emerging lubrication technology with excellent performance and significant potential for future applications. This study aims to investigate the effect of nano g-C₃N₄ as a lubricant additive on the wear performance of bearing steel disk.

Various mass fractions of g-C₃N₄ were introduced into the base oil. Combining tribological testing, rheological testing and surface analysis methods, the anti-wear properties and lubrication mechanisms were analyzed.

Transmission electron microscopy images revealed that the size of the nanoparticles of g-C₃N₄ ranges from 10 to 100 nm. Phase analysis of the g-C₃N₄ sample was conducted using X-ray diffraction. Further, 1.0% mass fraction of g-C₃N₄ in the base oil provides excellent anti-wear and friction-reducing performance. Compared to the base oil alone, it reduces the average friction coefficient by 63.8% and decreases the wear rate by 43.1%, significantly reducing the depth and width of the wear scar. Energy-dispersive X-ray spectroscopy and scanning electron microscope analysis revealed that the oil sample containing nano g-C₃N₄ can form a lubricating film on the sliding surface of bearing steel after wear, which enhances the lubricating properties of the base oil.

The synergistic effect of the base oil and nanoparticles reduces friction and wear and is expected to extend the service life of bearing steel. These findings suggest that incorporating nano g-C₃N₄ as a lubricant additive offers significant potential for improving the performance of mechanical components.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2024-0456/

This study aims to develop synthetic ester lubricating oil using renewable sinapic acid as raw material, to explore the structural design and selection of raw materials for green, high-performance synthetic ester oils.

A series of the sinapate ester oils were synthesized through esterification and alkoxylation reactions using renewable source sinapic acid as the raw material. The molecular structures of the oils were characterized by nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy spectroscopy and elemental analysis. The oils were evaluated for safety, viscosity-temperature properties, thermal and oxidative stability, as well as friction reducing and anti-wear characteristics.

Compared to commercial base oil tris (2-ethylhexyl) trimellitate (Phe-3Ci8), the bio-lubricant exhibits superior antifriction and anti-wear properties. Notably, the JCi8-C12 sample performed exceptionally well, reducing the friction coefficient by 11.42% and wear volume (WV) by 54.44% in steel/steel tribo-pairs. In steel/aluminum tribo-pairs, the friction coefficient decreased by 27.48%, while WV was reduced by 85.81%. Mechanistic studies reveal that the introduction of short-chain methoxy groups and stable conjugated systems (aromatic rings and double bonds) inhibit oxidation and decomposition at elevated temperatures. The p-p stacking effect enables lubricant molecules to arrange stably on friction surfaces, forming a durable lubricating film.

The utilization of biomass resources to develop green synthetic lubricating oil with excellent performance not only enhances the added value of waste from agricultural processing but also offers significant benefits in terms of both economic and environmental sustainability.

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote sustainable transportation development.

This paper introduces a novel self-adaptive grey multivariate prediction modeling framework (FARDCGM(1,N)) to forecast port cargo throughput in China, addressing the challenges posed by mutations and time lag characteristics of time series data. The model explores policy-driven mechanisms and autoregressive time lag terms, incorporating policy dummy variables to capture deviations in system development trends. The inclusion of autoregressive time lag terms enhances the model’s ability to describe the evolving system complexity. Additionally, the fractional-order accumulative generation operation effectively captures data features, while the Grey Wolf Optimization algorithm determines optimal nonlinear parameters, enhancing the model’s robustness.

Verification using port cargo throughput forecasts for FTZs in Shanghai, Guangdong and Zhejiang provinces demonstrates the FARDCGM(1,N) model’s remarkable accuracy and stability. This innovative model proves to be an excellent forecasting tool for systematically analyzing port cargo throughput under external interventions and time lag effects.

A novel self-adaptive grey multivariate modeling framework, FARDCGM(1,N), is introduced for accurately predicting port cargo throughput, considering policy-driven impacts and autoregressive time-lag effects. The model incorporates the GWO algorithm for optimal parameter selection, enhancing adaptability to sudden changes. It explores the dual role of policy variables in influencing system trends and the impact of time lag on dynamic response rates, improving the model’s complexity handling.

The review paper aims to understand the development of workplace ostracism as a field in organizational studies from 2000 to the present. The study provides a comprehensive synthesis of the current state of the domain by exploring its antecedents, consequences, underlying mechanisms and buffering mechanisms.

The present study analyses 134 published peer-reviewed empirical and non-empirical articles retrieved from the Scopus database. A systematic literature review and bibliometric analyses (using VOS viewer) have been used to gain insights into the development and trends within the field. Bibliometric analyses involved science mapping techniques such as co-citation analysis, co-occurrence of keywords and bibliographic coupling. Combining these three techniques, the study aimed to provide a comprehensive overview of the workplace ostracism research domain's historical, current and future landscape.

In the present study, through descriptive analyses, the authors uncovered publishing trends, productive journals, countries and industries that contribute to this research field. The systematic review enabled the showcasing of the current landscape of workplace ostracism. The bibliometric analyses shed light on major authors, influential articles, prominent journals and significant keywords in workplace ostracism.

This study enriches the existing literature by offering a comprehensive research framework for workplace ostracism. It goes beyond that by presenting significant bibliographic insights by applying bibliometric analyses. Furthermore, this study identifies and emphasizes future research directions using the theory, characteristics, construct and methodologies framework, aiming to expand the knowledge base and understanding of this topic.

Epoxy resin (EP) is a thermosetting resin commonly characterized by its inherent brittleness, which limits its widespread application. To overcome this limitation, a novel flexible chain-blocking hyperbranched polyester (HBP) was conceptualized and synthesized to enhance the toughness and dielectric properties of EP.

Using P-toluene sulfonic acid (p-TSA) as the catalyst and Bis(hydroxymethyl)propionic acid (DMPA) as the branching unit with pentaerythritol (PER) as the core, an experimental synthesis was conducted. Subsequently, n-hexanoic acid was introduced separately to produce hyperbranched polyester with n-hexanoic acid capped structures. Microstructural, mechanical, insulating and dielectric analyses of the composite were performed to determine the optimal proportion of HBP.

Recent research has demonstrated that the flexible segments within hyperbranched polyester create an interpenetrating network structure with the molecular chains of epoxy resin, thereby effectively augmenting the toughness of the epoxy resin. Additionally, HBP has reduced the ε and tgδ values of the epoxy-anhydride cured product by decreasing the number of polar groups per unit volume of EP through the introduction of free volumes.

Currently, HBP serves as an innovative toughening strategy and modifier for epoxy resin. The toughening mechanism involves the generation of free volume by HBP, providing space for EP molecules to maneuver under load. Additionally, the free volume contributes to a reduction in the dielectric constant of EP by diminishing the polarizable group content. Simultaneously, the incorporation of HBP features flexible chains grafted onto the epoxy resin.

This study aims to investigate the application of red cabbage extract in biodegradable composite-based edible film and evaluate its physicochemical characteristics and ability to be used in steamed chicken packaging.

Cassava starch, gelatin and glycerol were used as basic materials for edible film. Red cabbage extract was infused, and eggshell powder was also incorporated. The smart edible film formulation consists of six treatments which are C (control: cassava starch + gelatin + glycerol), CE (control + 0.1% eggshell powder), CRA (control + red cabbage A ratio), CERA (control + 0.1% eggshell powder + red cabbage A ratio), CERB (control + 0.1% eggshell powder + red cabbage B ratio) and CERC (control + 0.1% eggshell powder + red cabbage C ratio).

The different ratios of red cabbage extract in the formulation of the edible film affected its physicochemical properties (p < 0.05). The range of anthocyanin content were 0.39–11.53 mg cy-3-glu-eq/100 g and phenolic content were 19.87–369.68 mg GAE/100 g. Meanwhile, the antioxidant activity was 12.35%–51.09%. The tensile strength in all treatments was lower than control and adding red cabbage extract decreased the tensile strength. On the other hand, the elongation increased. The water vapor transmission rate was ranged from 158.09 to 191.19 g/m²/24 h. Morphological changes can be observed from scanning electron microscopy and optical data. Furthermore, using steamed chicken as a model, the edible film can show a response through the changes in edible film color, as confirmed by the pH value, total plate count and sensory quality of the stored steamed chicken.

There is no report available on the infusion of red cabbage extract on the bio composite edible film materials. The result shows a promising packaging material that can be used as an alternative to plastic packaging.

This paper aims to provide a full introduction, new classification, comparison and investigation of the challenges as well as applications of layerless 3D printing, which is one of the industry 4.0 pioneers.

Given the significance and novelty of uniform 3D printing, more than 250 publications were collected and reviewed in an unbiased and clear manner.

As a result, the majority of uniform parts printed in polymer form are known up to this point. In a novel division for better researchers’ comprehension, uniform printing systems were classified into three categories: oxygen inhibition (OI), liquid lubrication (LL) and photon penetration (PP), and each was thoroughly investigated. Furthermore, these three approaches were evaluated in terms of printing speed, precision and accuracy, manufacturing scale and cost.

The parameters of each approach were compared independently, and then a practical comparison was conducted among these three approaches. Finally, a variety of technologies, opportunities, challenges and advantages of each significant method, as well as a future outlook for layerless rapid prototyping, are presented.