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The frictional behavior of a Mo alloy‐coated piston ring sliding against cast iron cylinder bore was recorded as a function of temperature using a reciprocating tribotester and a fully formulated synthetic engine oil, with and without a friction modifier. It was observed that, as temperature increased in a stepwise mode, friction coefficients in the presence of MoDTC exhibited two local minimal values. Only one minimal friction coefficient value at 340–355 °C (μ = 0.065) was observed in the absence of MoDTC. Chemical characterization of worn tracks of the cylinder bore using reflected FTIR spectroscopy, Raman spectroscopy and ESCA, indicated that both the base stock and the tribological additives, ZDTP and MoDTC, experienced tribochemical reactions yielding MoO₃, MoS₂ and carbonaceous species as temperature ramped up stepwise. MoO₃ and MoS₂ reaction film formation are partially responsible for the local minimal friction coefficient found at the lower temperature and the ratio of the ordered carbon species accounts partially for the other local minimal friction coefficient found at the higher temperature.

Improved fuel economy, lower emission and longer durability are the major developing trends of engine oils. Aims to describe further research on the friction coefficient of engine oils.

The lubricating durability D was defined based on definition of three characteristic points P_d, P_S, P_i and three key time lengths T_d, T_s, T_i. Two kinds of engine oils, respectively, belonging to GF‐2 and GF‐3 categories, were selected as samples to compare their lubricating durability.

Test results indicate the GF‐3 oil has much better lubricating durability than GF‐2 oil. With investigation of the topography and chemical composition changes of wear tracks along with the tribotests' time extending, the meanings of three characteristic points were discussed. Analysis indicates much better tribofilm, formed by the synergistic effect of Ca‐containing detergent with MoDTC/ZDTP in GF‐3 oil, is the major factor resulting in GF‐3 oil's longer lubricating durability.

Provides further research on lubricating durability, which is important for engine oil change and maintenance, as well as decreased cost and pollution to the environment, and improved energy conservation.

The purpose of this paper is to study systematically the corrosion behavior of AZ31 magnesium (Mg) alloy with different concentrations of bovine serum albumin (BSA) (0, 0.5, 1.0, 1.5, 2.0 and 5.0 g/L).

Electrochemical impedance spectroscopy and potential dynamic polarization tests were performed to obtain corrosion parameters. Scanning electrochemical microscopy (SECM) was used to analyze the local electrochemical activity of the surface film. Atomic force microscope (AFM), Scanning electron microscope-Energy dispersive spectrometer and Fourier transform infrared spectroscopy were used to determine the surface morphology and chemical composition of the surface film.

Experimental results showed the presence of BSA in a certain concentration range (0 to 2.0 g/L) has a greater inhibitory effect on the corrosion of AZ31, however, the presence of high-concentration BSA (5.0 g/L) would sharply reduce the corrosion resistance.

When the concentration of BSA is less than 2.0 g/L, the corrosion resistance of AZ31 enhances with the concentration. The adsorption BSA layer will come into being a physical barrier to inhibit the corrosion process. However, high-concentration BSA (5.0 g/L) will chelate with dissolved metal ions (such as Mg and Ni) to form soluble complexes, which increases the roughness of the surface and accelerates the corrosion process.

Based on appraisal theory and social response theory, this study aims to explore the mechanism of AI failure types on consumer recovery expectation from the perspective of service failure assessment and validate the moderate role of anthropomorphism level.

Three scenario-based experiments were conducted to validate the research model. First, to test the effect of robot service failure types on customer recovery expectation; second, to further test the mediating role of perceived controllability, perceived stability and perceived severity; finally, to verify the moderating effect of anthropomorphic level.

Non-functional failures reduce consumer recovery expectation compared to functional failures; perceived controllability and perceived severity play a mediating role in the impact of service failure types on recovery expectation; the influence of service failure types on perceived controllability and perceived severity is moderated by the anthropomorphism level.

The findings enrich the influence mechanism and boundary conditions of service failure types, and have implications for online enterprise follow-up service recovery and improvement of anthropomorphic design.

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

In the face of solving the urban traffic congestion problem radically, emphasis has been laid on the research on slow traffic planning of urban built environment. Hence, research on slow traffic demand forecasting can provide a basis for the planning of urban slow traffic systems. Based on land use, the overall planning of the new Guangming (GM) district, and the population prediction results, the slow traffic demand within the scope of the new district was forecasted by combining the per capita trip frequency, and the spatial distribution of the slow traffic flow of the new GM district was forecasted per the forecasted demand quantity for slow traffic. The following research conclusions were obtained. Within the new GM district, the correlation of the total demand for slow traffic with the land use functions and population distribution was high, and the cross-zone traffic was mainly decided by the land usage of this district. The cross-unit slow traffic flow was concentrated in the Gongming central, Guangming central, high-tech zone, and Yutian zones. This research provides a guideline for the layout of slow traffic facilities in the future.

This study aims to uncover the ongoing discourse on generative artificial intelligence (AI), literacy and governance while providing nuanced perspectives on stakeholder involvement and recommendations for the effective regulation and utilization of generative AI technologies.

This study chooses generative AI-related online news coverage on BBC News as the case study. Oriented by a case study methodology, this study conducts a qualitative content analysis on 78 news articles related to generative AI.

By analyzing 78 news articles, generative AI is found to be portrayed in the news in the following ways: Generative AI is primarily used in generating texts, images, audio and videos. Generative AI can have both positive and negative impacts on people’s everyday lives. People’s generative AI literacy includes understanding, using and evaluating generative AI and combating generative AI harms. Various stakeholders, encompassing government authorities, industry, organizations/institutions, academia and affected individuals/users, engage in the practice of AI governance concerning generative AI.

Based on the findings, this study constructs a framework of competencies and considerations constituting generative AI literacy. Furthermore, this study underscores the role played by government authorities as coordinators who conduct co-governance with other stakeholders regarding generative AI literacy and who possess the legislative authority to offer robust legal safeguards to protect against harm.

The purpose of this study is to modify cerium dioxide with fumaric acid (CeO₂-f) to improve its compatibility and dispersibility in epoxy resin and to investigate the effect of the content on the coating performance.

To investigate whether CeO₂-f reacts with epoxy resin by ring opening, CeO₂-f and epoxy resin-treated CeO₂-f (Ce CeO₂-f/EP) were analyzed by infrared radiation (IR), X-ray diffraction (XRD) and ultraviolet-visible diffuse reflectance spectroscopy (UV-Vis). To reveal the effect of different content on coatings properties, neutral salt spray test (NSST) and electrochemical test were performed.

The results of IR, XRD, X-ray photoelectron spectroscopy and UV-Vis indicated that fumaric acid attached to the CeO₂ surface by chemical bonding and underwent a ring-opening reaction with epoxy resin, thus, improving the compatibility of CeO₂ in epoxy resin. NSST and electrochemical impedance spectroscopy results showed that the coatings containing 5% CeO₂-f exhibited the optimal corrosion resistance. The reason is that a dense conversion film was established on the substrate surface.

The epoxy coatings using CeO₂-f as fillers with synergistic inhibition ability are promising for the protection of carbon steel.