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This study aims to explore the traditional plant dyeing of Xinjiang Atlas silk fabrics, providing references for the comprehensive utilization of plant dyes in intangible cultural heritage.

The focus of this study is on dyeing experiments of Atlas silk fabrics using safflower extracts, constrained by regional resources. Safflower dry flowers grown in Xinjiang were selected, rinsed with pure water and rubbed. Yellow pigments were removed by adding edible white vinegar. Red pigments from safflower were extracted using an alkaline solution prepared with Populus euphratica ash, a special product of Xinjiang. The extraction rate was analyzed under varying material-to-liquor ratios, pH values, times and temperatures. Direct dyeing process experiments were conducted to obtain different colorimetric L, a, b and K/S values for comparison. Samples with good color development were selected to test the impact of dyeing immersions on color development, and their color fastness, UV protection and antibacterial effects were verified.

The dyeing experiments on silk fabrics confirmed their UV protection capabilities and antibacterial properties, demonstrating effectiveness against E. coli and Staphylococcus aureus. As a major producer of safflower, Xinjiang underscores the significance of safflower as an essential plant dyes on the Silk Road. This study reveals its market potential and suitability for use in the plant dyeing process of Atlas silk, producing vibrant red and pink colors.

The experiments indicated that after removing yellow pigments, the highest extraction rate of red pigment from safflower was achieved at a pH value of 10–11, a temperature of 30°C and an extraction time of 40 min. The best bright red color effect with strong color fastness was obtained with a material-to-liquor ratio of 1:20, a temperature of 40°C and three immersions. The best light pink color effect with strong color fastness was a material-to-liquor ratio of 1:80, a temperature of 30°C and two immersions.

With respect to severe working conditions such as heavy load and impact, this paper aims to investigate the friction reduction and anti-wear performance of kaolin and molybdenum dialkyl dithiophosphate (MoDDP) composite lubricant additives to improve the lubrication effect of a single additive.

A four-ball friction test was carried out to determine the optimal concentration of kaolin and organic molybdenum additives and the tribological properties of the kaolin/MoDDP composite lubricant additives. A ring block test of composite lubricant additives was designed to investigate its lubrication performance under the severe working conditions of low speed, heavy load and impact.

The results showed that the optimal addition mass fractions of kaolin and MoDDP were 4.0 and 1.5 Wt.%, respectively, when kaolin and MoDDP were used as single lubricant additives. Compared with the single additive, the 4.0 Wt.% kaolin/1.5 Wt.% MoDDP composite lubricant additive showed excellent friction reduction and anti-wear effects under heavy load and impact conditions. Physicochemical analysis of the wear surface revealed that the lamellar kaolin additive and MoDDP had excellent synergistic effects, and the friction process promoted the generation of lubricant films containing a chemically reactive layer of MoS₂, MoO₂, FeS₂ and Fe₂O₃ and a physically adsorbent layer containing SiO₂ and Al₂O₃, which play important roles in anti-wear and friction reduction.

The excellent friction reduction and anti-wear effects of lamellar silicate minerals and the excellent antioxidant properties and good synergistic effects of molybdenum were comprehensively used to develop the composite additives with great lubricating properties.

This paper aims to investigate the lubrication characteristics of siliconized graphite with a wavy-tilt-dam (WTD) pattern applied to the hydrodynamic face seals.

It focuses on two friction pairs, carbon graphite versus tungsten carbide (CG-TC) and siliconized graphite versus siliconized graphite (SG-SG), through a three-dimensional elastic hydrodynamic lubrication numerical model that integrates finite difference method and finite element method. The consequence of axial elastic deformation of sealing pair materials on film thickness, film pressure, cavitation and sealing performance for a WTD mechanical face seal under full working conditions of ΔP = 0.8, 5.3 and 15.8 MPa are analyzed theoretically.

The nuclear hydrodynamic WTD face seal generates a convergent gap and exhibits a dual-characteristic behavior of hydrodynamic and hydrostatic effects under various ΔP. Compared to the CG-TC, the SG-SG shows a lower minimum film thickness, decreasing by 3.9%, 17.3% and 35.1%. The flow leakage rate decreases by 47.8%, 52.1% and 75.4%. In addition, the film stiffness increases by 46.8%, 49.8% and 97.8%. Thus, the SG-SG better deals with the dynamic tracking problem, and the sealing performance is stable. The strength and hardness of siliconized graphite enhance WTD sealing performance and improve cavitation control in high-pressure applications.

The lubrication characteristics of the siliconized graphite with a WTD pattern could inform the future design of hydrodynamic shallow groove wavy seals in boiler feedwater engineering implements under high-pressure conditions for the nuclear power industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0382/

The purpose of this paper is to study and report the effects of silver (Ag) content, glass phase particle size and Ag/antimony-doped tin oxide (ATO) particle size on the properties of ATO thick film resistor pastes, especially on the microstructure, square resistance, temperature coefficient of resistance (TCR), resistance temperature curve and other properties of the pastes.

Thick film resistor pastes with different Ag content, glass phase particle size and ATO particle size were printed on stainless steel substrates by screen printing technology, and a series of Ag/ATO thick film resistors (TFRs) were obtained after high-temperature sintering. The electrical properties of TFRs were evaluated. The microstructure development, square resistance, TCR and other properties of the developed TFRs were evaluated with the change in Ag content and the particle size.

The results show that with the increase of Ag content, the square resistance of the pastes decreases and the TCR increases. The change rate of resistance after resintering is less than 4%, and the pastes show excellent antiaging properties. Meanwhile, with the increase of the particle size of the glass phase, the square resistance decreases first and then increases, and the TCR increases first and then decreases, which has little effect on the conductive behavior. The increase in ATO particle size leads to an increase in the square resistance of TFRs and a decrease in the TCR.

This paper provides a useful evaluation of the square resistance, TCR and other properties of Ag/ATO thick film resistor pastes, which are related to the Ag content, glass phase particle size and ATO particle size of the developed TFRs. The thick film resistor pastes with zero TCR can be obtained using Ag/ATO as the functional phase without Pd or Pt.

The purpose of this study is to evaluate and address the energy efficiency prevalent within the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) countries, a diverse group that constitutes a significant portion of the global gross domestic product. By assessing energy efficiency, the study aims to inform strategies that foster sustainable economic growth and environmental sustainability within these nations.

This research uses a three-stage slacks-based measure data envelopment analysis (SBM-DEA) model, enhanced by stochastic frontier analysis (SFA), to assess the energy efficiency of CPTPP countries over the period from 2000 to 2015. The three-stage SBM-DEA model allows for a comprehensive analysis by first measuring energy efficiency, then adjusting for external environmental factors and statistical noise through SFA, and finally, reevaluating efficiency with adjusted inputs.

The analysis reveals significant disparities in energy efficiency among CPTPP nations, identifying both high-performing countries and those needing considerable improvements. Developed countries within the CPTPP generally exhibit higher energy efficiency levels, which can be attributed to their adoption of advanced technologies and strong policy frameworks. In contrast, developing nations demonstrate greater vulnerability to external environmental factors affecting their energy efficiency.

The research fills a gap in the literature by providing a nuanced and comprehensive evaluation of energy efficiency across a significant and economically diverse group of nations, offering valuable insights for sustainable development within the CPTPP framework.

Recent years have witnessed a spike in Industry 4.0 initiatives among manufacturing organizations, particularly in the automotive sector. This acceleration aims to enhance competitiveness by addressing various aspects, from efficiency and workforce productivity to safety and insightful decision-making. However, merely adopting technological solutions in isolation may not suffice. Automotive companies need a holistic approach that integrates the antecedents of Industry 4.0 into their overall strategy. This study aims to identify and analyse key antecedents for Industry 4.0 adoption in the Indian automotive sector.

The study follows a structured six-stage methodology, which includes a systematic literature review, expert consultations and best–worst method (BWM) analysis. The research identifies, validates and systematically ranks 16 antecedents that are pivotal for Industry 4.0 adoption.

The study categorizes 16 antecedents into four dimensions: regulatory framework (RF), technology infrastructure (TI), operational optimization (OO) and performance dynamics (PD). The findings emphasize the significance of “Government policies to support smart factories”, “Support from top management”, “Financial performance” and “Technology readiness” as crucial antecedents for Industry 4.0 implementation in the Indian automotive sector.

These findings provide valuable guidance for industry practitioners and policymakers in strategically planning the Industry 4.0 deployment in the automotive sector.

This study contributes to the limited body of research on the identification and analysis of key antecedents for Industry 4.0 adoption in the automotive sector, particularly in emerging economies such as India. By using the BWM, it offers a structured and efficient approach to determining the priority order of these antecedents.

Drawing on the tenets of institutional theory, the purpose of this study is to examine the impact of Confucianism on technology for social good, while also considering the moderating influence of extrinsic informal institutions (foreign culture) and intrinsic formal institutions (property rights).

This study constructs a comprehensive database comprising 9,759 firm-year observations in China by using a sample of Chinese A-share listed firms from 2016 to 2020. Subsequently, the hypotheses are examined and confirmed, with the validity of the results being upheld even after conducting endogenous and robustness tests.

The findings of this study offer robust and consistent evidence supporting the notion that Confucianism positively affects technology for social good through both incentive effect and normative effect. Moreover, this positive influence is particularly prominent in organizations with limited exposure to foreign culture and in nonstate-owned enterprises.

The findings contribute to the literature by fostering a deep understanding of technology for social good and Confucianism research, and further provide a nuanced picture of the role of foreign culture and property rights in the process of technology for social good in China.

Toward sustainable development, radical green innovation (RGI) is necessary. Despite extensive research on the factors influencing green innovation, few studies have been conducted on the precursors. Based on upper echelons (UE) theory, dynamic capability (DC) theory, “stimulus-organism-response” (SOR) theory, social information processing (SIP) theory and cognitive appraisal (CA) theory of emotion, the study explores how digital leadership (DL) affects RGI and investigates the mediating effects of green organizational identity (GOI) and the moderating effects of digital threat (DT) and technology for social good (TSG), as well as the multiple concurrent causalities that trigger high RGI.

The method of combining structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fs QCA) is adopted in the study. Data from 233 questionnaires were collected at two different time points.

This study's findings indicate that the four dimensions of DL can positively influence RGI and GOI partially mediates between the four dimensions of DL and RGI. DT has a negative moderating effect between DL and GOI, while TSG is positively regulated between them, DT and TSG linkage moderates the partial mediating effect of GOI in DL and RGI. Further, fs QCA is used to analyze the causal complexity of DL dimensions and GOI to RGI and nine effective configuration paths are identified. It is found that the synergy of digital thinking ability (DTA), digital detection ability (DDA), digital social ability (DSA), digital reserve ability (DRA) and GOI is crucial to high RGI. Among them, GOI core appears the most times, indicating that GOI plays a vital role in improving enterprise RGI.

This study expands the literature on leadership and innovation by constructing a framework of “DL-GOI-RGI” and exploring the transmission of GOI and the boundary effect of DT and TSG. The study used fs QCA and SEM to better understand the statistical associations and the set relations between the conjunctions and conditions.

Damage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.

This study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.

In the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.

To achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.

The Industry 4.0 (I4.0) revolution originated in developed countries and has now been promoted worldwide as a powerful tool for improving productivity. However, adopting I4.0 technologies poses significant challenges, especially for emerging economies that are far from the I4.0 frontier. In the context of emerging economies, this paper aims to explore the impact of adopting I4.0 technologies on firms’ total factor productivity (TFP) and its mediation channels.

Using panel data for 2,928 firms in China’s manufacturing industry during the period 2010–2022, this study adopts fixed effects regression model to test the theoretical hypotheses. Endogeneity issues are addressed by the instrumental variable approach and propensity score matching.

The results show that adopting I4.0 technologies can significantly improve emerging economy firms’ TFP, and this effect is achieved by promoting technological innovation and alleviating financial constraints. Furthermore, the findings indicate a heterogeneity in the effects of I4.0 technology adoption. When top managers are long-term oriented, firms are state-owned, industry competition pressure is low or regional manufacturing innovation capability is strong, the positive impact of I4.0 on TFP is weakened.

This paper is one of the first attempts to offer empirical evidence about whether and how the adoption of I4.0 technologies boosts TFP growth among firms in emerging economies. The study expands on the organizational performance consequences of I4.0 adoption and provides implications for decision-makers in developing countries in implementing I4.0.