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Carbon reduction in the construction supply chain can critically affect the construction industry’s transition to an environmentally sustainable one. However, implementing carbon reduction in all parties is restricted because of the poor understanding of the drivers influencing the low-carbon construction supply chain (LCCSC). The purpose of this paper is to systematically identify the drivers of LCCSC, analyze their causality, and prioritize the importance of their management.

A decision-making analysis process was developed using an integrated decision-making trial and evaluation laboratory (DEMATEL)–analytical network process (ANP). First, the hierarchical drivers of the LCCSC were identified through a literature review. The DEMATEL method was subsequently applied to analyze the interactions between the drivers, including the direction and strength of impact. Finally, the ANP analysis was used to obtain the drivers’ weights; consequently, their priorities were established.

Various factors with complex interactions drive LCCSC. With respect to their influence relationships, incentive policy, regulatory policy, consumers’ low-carbon preference, market competition, supply chain performance, and managers’ low-carbon awareness have more significant center degrees and are cause drivers. Their strong correlations and influence on other drivers should be noticed. In terms of weights in the driver system, regulatory policy, consumers’ low-carbon preference, supply chain performance, and incentive policy are the key drivers of LCCSC and require primary attention. Other drivers, such as supply chain collaboration, employee motivation, and public participation, play a minor driving role with less management priority.

Despite some contributing studies with localized perspectives, the systematic analysis of LCCSC drivers is limited, especially considering their intricate interactions. This paper establishes the LCCSC driver system, explores the influence relationships among the drivers, and determines the key drivers. Hence, it contributes to the sustainable construction supply chain domain by enabling decision-makers and practitioners to systematically understand the drivers of LCCSC and gain management implications on priority issues with limited resources.

The purpose of this paper is to assesses whether supervisor justice is linked to COVID-19 negative and positive impacts directly and indirectly through the mechanisms of stress and resiliency among auxiliary police in China.

This study utilized survey data from more than 300 auxiliary police in a large Chinese provincial capital city in 2020. Structural equation modeling was conducted to analyze the direct and indirect relationships between supervisor justice and COIVD-19 impacts.

Results indicate that supervisor justice connects to COVID-19 negative impacts indirectly through stress. Supervisor justice is also indirectly related to positive impact through resiliency.

The findings' generalizability is limited due to using a nonrandom sample of officers. Officers' emotional states in the forms of stress and resiliency are important in mediating the association between supervisory justice and COVID-19 impacts.

The present study represents one of the first attempts to empirically investigate the occupational experiences of a vital group of frontline workers in Chinese policing. This study also generates evidence to support the importance of officers' emotional conditions in reducing negative COVID-19 impacts in an authoritarian country.

The purpose of this paper is to introduce a novel method to study the flutter coupling mechanism of the twin-fuselage aircraft, which is becoming a popular transportation vehicle recently.

A new method of flutter mode indicator is proposed based on the principle of work and power, which is realized through energy accumulation of generalized force work on generalized coordinates, based on which flutter coupling mechanism of the twin-fuselage aircraft is studied using ground vibration test and computational fluid dynamics/computational solid dynamics method.

Verification of the proposed flutter mode indicator is provided, by which the flutter mechanism of the twin fuselage is found as the horizontal tail’s torsion coupled with its bending effect and the “frequency drifting” phenomenon of twin-fuselage aircraft is explained logically, highlighting the proposed method in this paper.

This paper proposed a new method of flutter mode indicator, which has advantages in flutter modes indexes reliability, clear physical meaning and results normalization. This study found the flutter coupling mechanism of twin-fuselage aircraft, which has important guiding significance to the development of twin-fuselage aircraft.

The purpose of this paper is to improve the mechanical and tribological properties of Si₃N₄ ceramics and to make the application of Si₃N₄ ceramics as tribological materials more extensive.

Si₃N₄-based composite ceramics (SN-2L) containing nitrogen-doped graphene quantum dots (N-GQDs) were prepared by hot press sintering process through adding 2 Wt.% nanolignin as precursor to the Si₃N₄ matrix, and the dry friction and wear behaviors of Si₃N₄-based composite against TC4 disc were performed at the different loads by using pin-on-disc tester.

The friction coefficients and wear rates of SN-2L composite against TC4 were significantly lower than those of the single-phase Si₃N₄ against TC4 at the load range from 15 to 45 N. At higher load of 45 N, SN-2L/TC4 pair presented the lowest friction coefficient of 0.25, and the wear rates of the pins and discs were as low as 1.76 × 10⁻⁶ and 2.59 × 10⁻⁴mm³/N·m. The low friction and wear behavior could be attributed to the detachment of N-GQDs from the ceramic matrix to the worn surface at the load of 30 N or higher, and then an effective lubricating film containing N-GQDs, SiO₂, TiO₂ and Al₂SiO₅ formed in the worn surface. While, at the same test condition, the friction coefficient of the single-phase Si₃N₄ against TC4 was at a range from 0.45 to 0.58. The spalling and cracking morphology formed on the worn surface of single-phase Si3N4, and the wear mechanism was mainly dominated by adhesive and abrasive wear.

Overall, a high-performance green ceramic composite was prepared, and the composite had a good potential for application in engineering tribology fields (such as aerospace bearings).

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0161/

This study aims to investigate the relationship between COVID-19 impacts and auxiliary police officers’ mental health as well as the moderating role of supervisor procedural justice.

Based on the role theory and a police officer survey from China, this quantitative study investigates the relationship between COVID-19 impacts and mental health status among auxiliary police, a rarely examined police type. We also examine the moderating role of supervisor procedural justice.

Auxiliary police officers reported both negative and positive impacts from COVID-19, while the negative impacts were mainly in the work domain, but the positive impacts were primarily in the life area. OLS regression results indicate that negative impacts, especially work-related negative impacts, are significantly related to depression and anxiety, and supervisor procedural justice moderates the relationship between positive impacts and depression and anxiety.

Firstly, we adopted the role theory to examine how public health emergencies affect police officers in their work and life domains. Secondly, we advance the organizational justice literature by assessing whether supervisor procedural justice can moderate the relationship between COVID-19 impacts and their mental health. Thirdly, this research extends the literature on depression and anxiety of auxiliary police officers in China, who attracted less attention in current literature and policies.

The decarbonization of power generation is key to achieving carbon neutrality in China by the end of 2060. This paper aims to examine how green finance influences China’s low-carbon transition of power generation. Using a provincial panel data set as an empirical study example, green finance is assessed first, then empirically analyses the influences of green finance on the low-carbon transition of power generation, as well as intermediary mechanisms at play. Finally, this paper makes relevant recommendations for peak carbon and carbon neutrality in China.

To begin with, an evaluation index system with five indicators is constructed with entropy weighting method. Second, this paper uses the share of coal-fired power generation that takes in total power generation as an inverse indicator to measure the low-carbon transition in power generation. Finally, the authors perform generalized method of moments (GMM) econometric model to examine how green finance influences China’s low-carbon transition of power generation by taking advantage of 30 provincial panel data sets, spanning the period of 2007–2019. Meanwhile, the implementation of the 2016 Guidance on Green Finance is used as a turning point to address endogeneity using difference-in-difference method (DID).

The prosperity of green finance can markedly reduce the share of thermal power generation in total electricity generation, which implies a trend toward China’s low-carbon transformation in the power generation industry. Urbanization and R&D investment are driving forces influencing low-carbon transition, while economic development hinders the low-carbon transition. The conclusions remain robust after a series of tests such as the DID method, instrumental variable method and replacement indicators. Notably, the results of the mechanism analysis suggest that green finance contributes to low-carbon transformation in power generation by reducing secondary sectoral share, reducing the production of export products, promoting the advancement of green technologies and expanding the proportion of new installed capacity of renewable energy.

This paper puts forward relevant suggestions for promoting the green finance development with countermeasures such as allowing low interest rate for renewable energy power generation, facilitating market function and using carbon trade market. Additional policy implication is to promote high quality urbanization and increase R&D investment while pursuing high quality economic development. The last implication is to develop mechanism to strengthen the transformation of industrial structure, to promote high quality trade from high carbon manufactured products to low-carbon products, to stimulate more investment in green technology innovation and to accelerate the greening of installed structure in power generation industry.

This paper first attempts to examine the low-carbon transition in power generation from a new perspective of green finance. Second, this paper analyses the mechanism through several aspects: the share of secondary industry, the output of exported products, advances in green technology and the share of renewable energy in new installed capacity, which has not yet been done. Finally, this study constructs a system of indicators to evaluate green finance, including five indicators with entropy weighting method. In conclusion, this paper provides scientific references for sustainable development in China, and meanwhile for other developing countries with similar characteristics.

The purpose of this paper is to optimize the structure of plough blades in a ploughshare mixer using the discrete element method (DEM) simulations.

Using the validated DEM model, three numerical tests are conducted to determine how the mixing performance evolves as structural parameters of blades change. Results from the analysis provide basis for structure optimization of blades. The structural parameters include sweep angle of blade γ, regular axial pitch p and regular circumferential angular offset α. The parameters to evaluate mixing performance include mass flow rate and Lacey index.

The DEM results show that the mixing performance at γ of 35° is better than 15°, 25° and 45°. The mixer which has a p of less than or equal to 1.11 · b is more efficient than the mixer which has a p greater than 1.11 · b, where b is tail width of blade. The circumferential symmetric distribution of blades (α = 180°) is more beneficial to improve the mixing performance in comparison with the circumferential asymmetric distribution (α < 180°). Based on the results, an optimized mixer with a γ of 35°, a p of 0.61 · b and an α of 180° is proposed, which has a better mixing performance compared to all mixers listed.

The structural parameters of blades, including γ, p and α, are found to be critical for good mixing. From the view angle of structure optimization of plough blades, a new ploughshare mixer with a γ of 35°, a p of 0.61 · b and an α of 180° is investigated and recommended for improving mixing efficiency.

The purpose of this study is to improve the accuracy of industrial robot kinematic parameter identification and position accuracy by solving the problem of insufficient consideration of error sources in the kinematic parameter identification model and optimizing the selection of measurement pose set.

In this study, a kinematic calibration method for industrial robots considering multiple error sources is proposed. Based on the Modified Denavit Hartenberg (MD-H) model, a robot kinematics identification model including joint reduction ratio error, target ball installation error and coordinate system transformation error is established. Taking the optimal observability index O1 and the minimum flexible deformation as the optimization objectives, a measurement pose set optimization method based on Non-dominated Sorting Genetic Algorithm II (NSGA-II) is proposed to obtain a measurement pose set with higher identification accuracy.

Through experiments conducted with the Nantong Zhenkang ZK1400-6 robot as the test subject, the kinematic parameters identified by the optimized measurement pose set are more accurate than the randomly selected measurement pose set, and the positioning accuracy of the robot is improved from 2.11 to 0.31 mm, an increase of 85.3%.

This study introduces a position error model that comprehensively accounts for the error sources causing positioning inaccuracies. Building on this foundation, a novel flexible deformation index is proposed to quantify the flexible deformation in the measurement pose set, thereby reducing the impact of such deformation on the position error in the model. To the best of the authors’ knowledge, for the first time, this study presents an optimization method for the measurement pose set based on NSGA-II, using the flexible deformation index and observability index as objectives for multi-objective optimization, simultaneously optimizing the pose error and Jacobian matrix in the error model.

This paper aims to present a new kinematics mapping method based on dynamic equivalent points. In teleoperation, this method enables a robotic (follower) arm to mimic human (leader) arm postures and avoid obstacles in a human-like manner.

The information of the human arm is extracted based on the characteristics of human arm motion, and the concept of equivalent points is introduced. Then, an equivalent point is determined to transform the robotic arm with a nonhuman-like kinematic structure into an anthropomorphic robotic arm. Based on this equivalent point, a mapping method is developed to ensure that the two arms are similar. Finally, the similarity between the human elbow angle and robot elbow angle is further improved by using this method and an augmented Jacobian matrix with a compensation coefficient.

Numerical simulations and physical prototype experiments are conducted to verify the effectiveness and feasibility of the proposed method. In environments with obstacles, this method can adjust the position of the equivalent point in real time to avoid obstacles. In environments without obstacles, the similarity between the human elbow angle and robot elbow angle is further improved at the expense of the end-effector accuracy.

This study presents a new kinematics mapping method, which can realize the complete mapping between the human arm and heterogeneous robotic arm in teleoperation. This method is versatile and can be applied to various mechanical arms with different structures.

Electrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low cost, non-invasive and visualization features. There are two major difficulties in image reconstruction for ECT and ERT: the “soft-field”effect, and the ill-posedness of the inverse problem, which includes two problems: under-determined problem and the solution is not stable, i.e. is very sensitive to measurement errors and noise. This paper aims to summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide reference for further research and application.

In the past 10 years, various image reconstruction algorithms have been developed to deal with these problems, including in the field of industrial multi-phase flow measurement and biological medical diagnosis.

This paper reviews existing image reconstruction algorithms and the new algorithms proposed by the authors for electrical capacitance tomography and electrical resistance tomography in multi-phase flow measurement and biological medical diagnosis.

The authors systematically summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide valuable reference for practical applications.