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Liquid-assisted laser surface texturing technology was used to create composite microtextures on triangular guide rail surfaces to enhance their tribological properties.

Numerical simulations were used to investigate the impact of various microtextures on fluid dynamic lubrication. Reciprocating friction and wear tests, followed by mechanistic analysis, examined the combined tribological effects of microtextured surfaces and lubricants.

The numerical simulation outcomes reveal a significant augmentation in the influence of fluid dynamic pressure due to composite microtextures, consequently amplifying the load-bearing capacity of the oil film. The average friction coefficient of composite microtextured samples was approximately 0.136 in reciprocating pin-on-disk friction tests, representing approximately 17% decrease compared to polished samples. Triangular guide rails with composite microtextures demonstrated the lowest average coefficient under conditions of high-speed and heavy-loading in the reciprocating friction and wear tests. Additionally, the presence of composite microtextures was found to promote the formation of adsorbed and friction films during friction, potentially contributing to the enhancement of tribological properties.

Triangular guide rails face high friction and wear, limiting their stability in demanding applications like machine tool guideways. This paper proposes a novel approach for steel triangular guide rails, involving composite microtexturing, numerical fluid simulations, liquid-assisted laser surface texturing and friction-wear testing. By implementing composite microtextures, the method aims to reduce friction coefficients and extend guideway service life, thereby saving energy and reducing maintenance costs. Enhancing the antifriction and antiwear properties of machine tool guideways is crucial for improving performance and longevity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0183/

To improve the problems as the heavy burden of sewage treatment and environmental pollution caused by the traditional sodium hydrosulfite reduction dyeing of indigo, this study aims to carry out the direct electrochemical reduction dyeing for indigo with the eco-friendly Cu(II)/sodium borohydride reduction system under normal temperature and pressure conditions.

The electrochemical behavior of Cu(II)/sodium borohydride reduction system was investigated by cyclic voltammetry. And, the dyeing performance of the Cu(II)/sodium borohydride reduction system was developed by optimizing the concentration of copper sulfate in the anode electrolyte, applied voltage and reduction time via single-factor and orthogonal integrated analysis.

The dyeing performance of the Cu(II)/sodium borohydride reduction system is superior to that of the traditional reduction dyeing with sodium hydrosulfite. In the case of the optimized condition, the soaping fastness and dry/wet rubbing fastness of the dyed fabric in the two reduction dyeing processes were basically comparable, the K/S value of electrocatalytic reduction of indigo by Cu(II)/NaBH4 is 11.81, which is higher than that obtained by traditional sodium hydrosulfite reduction dyeing of indigo.

The innovative electrocatalytic reduction system applied herein uses sodium borohydride as the hydrogen source combined with Cu(II) complex as the catalyst, which can serve as a medium for electron transfer and active the dye molecule to make it easier to be reduced. The electrochemical dyeing strategy presented here provides a new idea to improve the reduction dyeing performance of indigo by sodium borohydride.

The purpose of this paper is to assess the process of prefabricated construction (PC) and analyze the impacts of rework risk to identify the core tasks for which the rework risk has severe impacts.

The methods consist of a literature review, expert interviews, a questionnaire survey and a rework risk function. The expert interviews and questionnaire survey were administered to experts in the entire process of PC from the dimensions of rework frequency, rework cost and rework time. Descriptive and inferential statistics were employed to analyze the data. The rework risk function was based on the loss expectancy method.

There are 13 core tasks that have higher impacts than the average level. The core tasks in the design stage account for 100% of the tasks in the stage, those in the manufacturing stage account for 20% and those in the construction stage account for 23.1%. Compared with the other stages, the design stage is characterized by significantly more frequent rework, higher rework costs and longer rework time. The manufacturing stage is characterized by significantly higher rework costs than the construction stage. The manufacturing stage and construction stage are co-reliant, and both are impacted by the design stage.

The findings provide stakeholders with a clear understanding of the core tasks of the PC process and represent a method for identifying core tasks. Stakeholders can learn from this to focus on the core tasks to reduce rework risk and manage the process with the priority of PC rework management based on the following order: design > manufacturing > construction. The approach is suitable for core task identification in other areas.

This research provides insight into rework risk management and provides a novel analysis method for rework risk and PC management from the perspective of the construction process. The findings are valuable for supporting stakeholders in making effective construction plans to reduce the impacts of rework risk in PC and provide a reference for future research on process optimization.

In the dynamic landscape of the digital economy, companies are increasingly adopting omnichannel integration strategies to enhance customer experiences. However, the interplay between this strategy and digitalisation in fostering brand trust remains uncharted. Drawing on the social exchange and psychological reactance theories, this study ventures into unexplored territory by examining the impact of omnichannel integration and digital value on brand trust building. It also delves into the boundary roles of customers’ psychological perceptions, both positive (customer empowerment) and negative (privacy concerns and perceived deception), in this process.

This study conducted an online survey of 595 omnichannel users in China and validated the model using partial least squares structural equation modelling (PLS-SEM).

This study’s results have significant implications for businesses. They show that customer perception of omnichannel integration and perceived digital value are critical drivers of omnichannel brand trust, with customer empowerment playing a mediating role. Notably, the study also reveals that customers’ negative psychological perceptions can have different moderating effects, highlighting the need for businesses to address these concerns in their omnichannel strategies.

This study breaks new ground in marketing research by highlighting the benefits of omnichannel integration and incorporating digital perspectives. It demonstrates the positive impact of blending customer perception of omnichannel integration and perceived digital value on brand trust formation. Furthermore, it explores the boundary roles of customers’ psychological perceptions in this process, offering a unique and comprehensive perspective.

The authors designed those experiments to test the sensitivity of graphene when it is exposed to NO₂ gas, to find a way to decrease the recovery time of graphene and to find the difference effect between monolayer and bilayer graphene in the experiments.

The authors transferred graphene from film on Cu foil to NO₂ sensor sample and measured the resistances of on monolayer and bilayer graphene when they were exposed to NO₂ gas under different concentration; then, the authors obtained the results.

The results show that monolayer graphene exhibits a linear response when the NO₂ concentration is below 20 ppm. But the monolayer graphene will not be so sensitive to NO₂ gas when the concentration continues to reduce. The desorption time of monolayer graphene is longer when compared with bilayer graphene. It shows faster recovery time and higher response of bilayer graphene under low NO₂ concentration. And the limit detectable NO₂ concentration of bilayer graphene is 50 ppb. Desorption time of bilayer graphene is shortened to below 20 s under UV light.

The authors found a reliable way to decrease the recovery time of graphene when it is exposed NO₂ gas and got the concrete data.

The construction industry is facing challenges not only for workers' mobility in the pandemic situation but also for Lean Construction (LC) practise in responding to the high-quality development during the post-pandemic. As such, this paper presents a construction workforce management framework based on LC to manage both the emergency goal in migrant worker management and the long-term goal in labour productivity improvement in China.

The framework is created based on the integrated culture and technology strategies of LC. A combination of qualitative and quantitative methods is taken to explore factors influencing the mobility of construction workers and to measure labour productivity improvement. The case study approach is adopted to demonstrate the framework application.

For method application, a time-and-motion study and Percent Plan Complete indicator are proposed to offer labour productivity measurements of “resources efficiency” and “flow efficiency”. Moreover, the case study provides an industry level solution for construction workforce management and Lean Construction culture shaping, as well as witnesses the LC culture and technology strategies alignment contributing to LC practise innovation.

Compared with previous studies which emphasised solely LC techniques rather than socio-technical system thinking, the proposed integration framework as well as implementation of “Worker's Home” and “Lean Work Package” management models in the COVID-19 pandemic contribute to new extensions of both the fundamental of knowledge and practise in LC.

Through empirical analysis of Sino-US solar photovoltaic (PV) trade, this paper aims to evaluate the complementarity of Sino-US solar PV trade by adopting trade combination degree (TCD) index, export similarity index (SI) and trade complementarity index (TCI). It also explores the role of trade disputes over Sino-US solar PV trade between China and the USA and important factors affecting the complementarity of the trade.

Based on the comparative advantage theory, this paper selects the TCD, export SI and TCI to evaluate the complementarity of Sino-US solar PV trade comprehensively. Among them, TCD and SI can directly reflect the degree of cooperation and competition of Sino-US solar PV trade. Finally, the authors further analyze the decisive factors affecting the complementarity of Sino-US PV trade by entropy weight method and multiple linear regression analysis on the influencing factors of TCI.

The solar PV trade between China and the USA still has a close relationship, and there is solar PV trade cooperation and competition between the two countries. The factors affecting the complementarity of Sino-US solar PV trade are mainly exchange rate levels rather than trade disputes between China and the USA. The solar PV trade policies of China and the USA will have a great negative impact on the global supply chain of solar PV products. The major solar PV products in China and the USA have a clear division in the global supply chain and still have a strong trade complementarity.

This paper conducts an empirical analysis of the Sino-US solar PV trade rather than a policy discussion. This research has important practical significance for the healthy and sustainable development of solar PV trade for both countries. It can also provide references to the current trade disputes between China and the USA in a broader sense.

The aim of this study is to find the governance mechanism that matches the EPC project governance model as well as the performance criteria for measuring the quality governance of EPC projects so as to improve the level of quality of EPC project delivery.

An in-depth questionnaire survey of 199 EPC engineering practitioners and quality control units was conducted and the survey data was analysed using SPSS 24.0 software.

The results show that administrative governance, industry governance and internal project governance have direct effects on the quality governance performance of EPC projects. Administrative governance has a positive impact on the quality governance performance of EPC projects through industry governance and project internal governance.

This study enriches the research on engineering quality governance in the context of EPC projects, discusses how to improve the performance of EPC engineering quality governance and will provide certain reference and information for other EPC projects to establish an adapted engineering quality governance mechanism.

This paper exploratively proposes EPC administrative governance mode, industry governance mode and internal project governance mode and analyzes the logical relationship between them and EPC project quality governance performance and constructs a theoretical model influencing the improvement of EPC project quality governance performance.

At present, the scale of China's floating population has reached 376 million people. Compared with the local inhabitants, the poverty problem of the floating population is more complex, and this problem should also attract the attention of all sectors of society. This paper aims to measure and analyze the multidimensional poverty of the floating population in China.

The data used in this paper are the data of the China Migrants Dynamic Survey (CMDS) in China. This survey is a large-scale national migratory population sampling survey organized by the China National Health Commission, covering 31 provinces (autonomous regions and cities) and other autonomous regions. This paper uses the dynamic monitoring and Alkire and Foster (A-F) method to study the multidimensional poverty problem of the floating population.

This study finds that income poverty is no longer the main type of poverty faced by the floating population. The multidimensional poverty of the floating population mainly occurs in the social security and education dimensions, of which social security has become the most severe poverty dimension of the floating population. From the perspective of group differences, compared with the floating population in urban areas, the multidimensional poverty of migrant workers is more serious. However, the poverty of migrant workers is mainly concentrated in one-dimensional poverty and two-dimensional poverty.

In the future, the authors should focus on the social security of the floating population in the place of influx and the education of the floating population.

Through the review of the existing literature, the authors find that the current research on the multidimensional poverty of the floating population is mainly concentrated on the migrant worker groups that move from rural areas to urban areas. However, insufficient attention is paid to the urban floating population groups moving between cities.

To the best of the authors’ knowledge, this study is the first to investigate the intricate relationship between crude oil spot and futures prices, focusing on both cointegration and market efficiency during the COVID-19 pandemic, and the beginning of the Russia–Ukraine conflict. Using daily West Texas Intermediate data from January 2020 to March 2024, like Cunado and Pérez de Gracia (2003), the authors use advanced statistical methods to identify structural breaks and assess cointegration levels. Linear and nonlinear Granger causality tests are used to reveal underlying dynamics.

This paper uses the Lagrange Multiplier test by Arai and Kurozumi (2007) to check for cointegration with various shifts in crude oil spot and futures markets. The two-step procedure by Kejriwal and Perron (2010) and Kejriwal et al. (2022) is then applied to assess partial parameter stability in cointegration models. Efficiency is examined using both bivariate and trivariate models based on non-arbitrage and expectations hypotheses. Finally, causality is analyzed with the vector error correction model for linear Granger causality, and the tests by Bai et al. (2018) and Diks and Panchenko (2006) for nonlinear causality.

The analysis reveals that futures prices generally lead spot prices through both linear and nonlinear causality during certain periods, while only linear causality is present in others. This inconsistency suggests fluctuating market efficiency and potential arbitrage opportunities. Structural breaks indicate that the equilibrium between spot and futures prices adjusts in response to significant events like the COVID-19 pandemic and the Russia–Ukraine war. The study identifies specific periods, particularly between January 2020 and March 2024, where both linear and nonlinear forecasting between futures and spot oil prices are effective, highlighting the dynamic nature of their relationship.

Despite extensive efforts, pinpointing the exact break date for COVID-19 remains challenging due to limitations in the data set and methodology. Additionally, the analysis of the Russia–Ukraine conflict is still ongoing. These challenges highlight the complexity of addressing structural breaks linked to unprecedented events.

The findings offer valuable insights for both academia and industry practitioners. The study reveals potential arbitrage opportunities stemming from inconsistent market efficiency and fluctuating causality between futures and spot prices, allowing traders to optimize their trades and timing. It also enhances risk management by identifying when linear and nonlinear causality is most effective. Policymakers can use these insights to evaluate market stability, especially during major disruptions such as the COVID-19 pandemic and geopolitical conflicts, guiding regulatory decisions. Furthermore, the study highlights the importance for investors to adjust their strategies in response to structural breaks and evolving market conditions.

This study’s social implications are diverse, extending beyond finance and academia. It influences economic stability by revealing inefficiencies and arbitrage opportunities in crude oil markets, aiding better resource allocation. Enhanced transparency benefits stakeholders, promoting fair market practices and consumer protection. Policymakers can refine regulations based on identified structural breaks, ensuring market stability. The study indirectly impacts environmental discussions by examining crude oil’s link to global energy consumption. Financially, it guides investment strategies, influencing resource distribution and the broader economy. Additionally, its educational contribution stimulates academic discourse, fostering growth in energy economics and financial market knowledge, shaping future research.

The originality and value of this paper lie in its comprehensive examination of the dynamic relationship between futures and spot oil prices, particularly through both linear and nonlinear causality across different periods. By identifying and analyzing periods of both linear and nonlinear causality, the study uncovers fluctuating market efficiency and potential arbitrage opportunities that are not typically addressed in conventional analyses. Additionally, the paper’s focus on the impact of significant global events, such as the COVID-19 pandemic and the Russia–Ukraine war, on the equilibrium between spot and futures prices offers a novel perspective on how structural breaks influence market dynamics. This nuanced understanding enhances both theoretical and practical knowledge, offering valuable insights for traders, investors and policymakers to navigate and respond to evolving market conditions.