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This study aims to reveal the tribological mechanism of synergistic effect between MoDTC and P-containing additives in aluminum-based grease.

The authors prepared a molybdenum dialkyl dithiocarbamate (MoDTC) and revealed the tribological mechanism of synergistic effect between MoDTC and P-containing additives in aluminum-based grease by combining with ZDDP and P-containing and S-free additives.

The MoDTC the authors prepared has good friction-reducing and anti-wear properties in aluminum-based grease and has an obvious synergistic effect with ZDDP. MoDTC and ZDDP have a significant synergistic effect on the tribological properties in aluminum-based grease, mainly because of the formation of phosphates and metaphosphates as well as more MoS₂ in the friction film. P element plays a facilitating role in the chemical conversion of MoDTC to MoS₂.

The experiments of MoDTC with tributyl phosphate and trimethylphenyl phosphate confirm that the P element plays a facilitating role in the chemical conversion of MoDTC into MoS₂.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0410

This study aims to expand the reliability and special functions of lightweight materials for high-end equipment and green manufacturing, so that it is the first such research to carry out nano-composite technology of nickel-coated carbon nanotubes (Ni-CNTs)-based titanium-zirconium chemical conversion on aluminum alloy substrate.

Corrosion behavior of various coatings was investigated using dropping corrosion test, linear polarization and electrochemical impedance spectroscopy. The results showed that the corrosion resistance of the nano-composite conversion coatings was significantly improved to compare with the conventional titanium-zirconium conversion coating. The morphology and microdomain characteristics of the nano-composite conversion coatings were characterized by SEM/eds/EPMA, which indicated that the CNT or Ni-CNTs addition promoting the integrity coverage of coatings in a short time.

Surface morphology of titanium-zirconium (Ti-Zr)/Ni-CNT specimens exhibited smooth, compact and little pores. The nano-composite conversion coatings are mainly composed of Al, O, C and Ti elements and contain a small amount of F and Zr elements, which illuminated that CNT or Ni-CNT addition could co-deposit with aluminum and titanium metal oxides.

The study of corrosion resistance of nano-composite conversion coatings and the micro-zone film-formation characteristics would be provided theoretical support for the development of basic research on surface treatment of aluminum alloys.

This paper aims to reschedule the freight train timetable in case of disturbance to restore the train services as soon as possible.

Hence, an integer linear programming model for the real-time freight heavy-haul railway traffic management is developed in case of large primary delays caused by the delayed cargos loading. The proposed model based on the alternative graph at the microscopic level depicts the freight train movements in detail. Multiple dispatching measures such as re-timing and re-ordering are taken into account. Moreover, two objective functions, namely, the total final delays and the consecutive delays, are minimized in the freight trains dispatching problem.

Finally, a real-world computational experiment based on the Haolebaoji-Ji’an freight heavy-haul railway is implemented. The results of all disrupted cases are obtained within 10 s. The results give insight into that the consecutive delays are more than the total final delays when the same disrupted situation and the consecutive or total final delays increase as the primary delays increase.

An integer linear programming model based on the alternative graph for the real-time freight heavy-haul railway traffic management is developed in case of large primary delays caused by the delayed cargos loading. The method can be developed as the computer-aided tool for freight train dispatchers.

The aim of this paper is to study the tribological performance and self-repairing performance of surface-modified nanoscale serpentine powders as lubricant additives in the mineral base oil (5-CST).

Fourier transform infrared spectroscopy spectra and thermo-gravimetric analysis of both modified and unmodified serpentine were performed to analyse their grafting ratio and suspension after modified using a long-chain naphthene aliphatic acid. The tribological properties of surface-modified serpentine as lubricant additives in 5-CST were evaluated and the worn surfaces were investigated by X-ray photoelectron spectroscopy (XPS) and X-ray absorption near edge structure (XANES).

The results show that the serpentine particles have high grafting ratio, improving the dispersity in 5-CST. When the serpentine concentration of 1.00 weight per cent is used as additives in 5-CST, friction coefficient reduces by 14.80 per cent under 294 N and wear scar diameter (WSD) decreases by 11.82 per cent. The results of X-ray absorption near edge structure and XANES show that the adsorption and tribochemical reactions occur to form self-repairing lubrication films.

The paper illustrates a tribofilm form on the rubbed surface, which is responsible for the decrease in friction and wear, mainly containing iron oxides, silicon oxides, magnesium oxides and organic compounds. The results are useful for further applications in advanced environmental friendly lubricating oils and additives.

This paper aims to investigate the relationships between empowering leadership, basic psychological needs satisfaction, work-related well-being, and project citizenship behavior.

Drawing upon the self-determination theory (SDT), a conceptual model was developed and then empirically tested using a cross-sectional survey of 435 project members in Chinese construction projects.

The results fully support the research hypotheses proposed in the study, illustrating the positive impacts of empowering leadership on work-related well-being and project citizenship behavior, the mediating role of basic psychological needs satisfaction, and the positive association between work-related well-being and project citizenship behavior.

This research determines the utility of empowering leadership in the context of construction projects, especially in enhancing individual outcomes (i.e. work-related well-being and project citizenship behavior). Therefore, construction project managers can apply empowering leadership to meet the basic psychological needs of subordinates to increase project members' work-related well-being and project citizenship behavior.

To our knowledge, the present study first explores the micro-level impacts of empowering leadership in the construction context. Additionally, this study enriches the understanding of the mediating mechanism between empowering leadership and individual outcomes from a self-determination perspective.

Existing studies mostly rely on the static characteristics of team members, and there is still a lack of empirical investigation on how entrepreneurial team members make decisions through dynamic team process and how team members’ cognition influences team decision-making. The purpose of this study is to validate how entrepreneurial team heterogeneity affects team decision-making performance from the perspective of dynamic team process.

Drawing on the theory of input-process-output model, this study proposed and examined the mediating role of team interaction as well as the moderating role of proactive socialization tactics in the relationship between entrepreneurial team heterogeneity and decision-making performance. Based on a sample of 162 entrepreneurial teams that include pairing superiors and subordinates, hierarchical regressions and moderated mediation tests were used to test the hypotheses.

The research results show that the heterogeneity of entrepreneurial teams is positively correlated with both team interaction and decision-making performance. Team interaction plays a mediating role between entrepreneurial team heterogeneity and decision-making performance; information seeking of proactive socialization tactics moderates the impact of entrepreneurial team heterogeneity on team interaction.

Contributing to the literature on entrepreneurial team decision-making performance, this study identifies that proactive socialization tactics with a high level of information seeking can help entrepreneurial team members respond to environmental and organizational changes more effectively during team development and increase the effectiveness of team interaction. This finding helps us better understand the mechanism and context under which entrepreneurial heterogeneity may enhance the team’s decision-making performance.

To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making ideas embedded in the bottom-line thinking method.

First, the order relation analysis method (G1 method) and Laplacian score (LS) are applied to calculate the constant weights of indexes. Then, the worst-case scenario of food import risk can be estimated to strive for the best result, so the penalty state variable weight function is introduced to obtain variable weights of indexes. Finally, the study measures the risk state of China's food import from the overall situation using the set pair analysis (SPA) method and identifies the key factors affecting food import risk.

The risk states of food supply in eight countries are in the state of average potential and partial back potential as a whole. The results indicate that China's food import risks are at medium and upper-medium risk levels in most years, fluctuating slightly from 2010 to 2020. In addition, some factors are diagnosed as the primary control objects for holding the bottom line of food import risk in China, including food output level, food export capacity, bilateral relationship and political risk.

This paper proposes a novel risk state evaluation model following bottom-line thinking for food import risk in China. Besides, SPA is first applied to the risk evaluation of food import, expanding the application field of the SPA method.

Clothing retrieval is very useful to help the clients to efficiently search out the apparel they want. Currently, the mainstream clothing retrieval methods are attribute semantics based, which however are inconvenient for common clients. The purpose of this paper is to provide an easy‐to‐operate apparels retrieval mode with the authors' novel approach of clothing image similarity measurement.

The authors measure the similarity between two clothing images by computing the weighted similarities between their bundled features. Each bundled feature consists of the point features (SIFT) which are further quantified into local visual words in a maximally stable extremal region (MSER). The authors weight the importance of bundled features by the precision of SIFT quantification and local word frequency that reflects the frequency of the common visual words appeared in two bundled features. The bundled features similarity is computed from two aspects: local word frequency; and SIFTs distance matrix that records the distances between every two SIFTs in a bundled feature.

Local word frequencies improves the recognition between two bundled features with the same common visual words but different local word frequency. SIFTs distance matrix has the merits of scale invariance and rotation invariance. Experimental results show that this approach works well in the situations with large clothing deformation, background exchange and part hidden, etc. And the similarity measurement of Weight+Bundled+LWF+SDM is the best.

This paper presents an apparel retrieval mode based on local visual features, and presents a new algorithm for bundled feature matching and apparel similarity measurement.

This study aims to modify the human factors analysis and classification system (HFACS) to make it suitable for collapse accident analysis in construction. Based upon the modified HFACS, distribution patterns of causal factors across multiple levels were discerned among causal factors of various stakeholders at construction sites. It explored the correlations between two causal factors from different levels and further determined causation paths from two perspectives of level and stakeholder.

The main research framework consisted of data collection, coding and analysis. Collapse accident reports were collected with adequate causation information. The modified HFACS was utilized for coding causal factors across all five levels in each case. A hybrid approach with two perspectives of level and stakeholder was proposed for frequency analysis, correlation analysis and path identification between causal factors.

Eight causal factors from external organizations at the fifth level were added to the original HFACS. Level-based correlation analyses and path identification provided safety managers with a holistic view of inter-connected causal factors across five levels. Stakeholder-based correlation analyses between causal factors from the fifth level and its non-adjacent levels were implemented based on client, government and third parties. These identified paths were useful for different stakeholders to develop specific safety plans for avoiding construction collapse accidents.

This paper fulfils an identified need to modify and utilize the HFACS model for correlation analysis and path identification of causal factors resulting in collapse accidents, which can provide opportunities for tailoring preventive and protective measures at construction sites.

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.