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Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

To address the various irregularities that occurred during the development of China’s electricity market, particularly the issue of collusive pricing between upstream and downstream firms.

This study constructs a tripartite evolutionary game model involving government regulators, grid operators and power producers to address electricity market pricing chaos. By analyzing the stable strategies within each subject’s evolutionary game, adjustments to the relevant parameters are made to achieve a stable state of strategy selection.

The findings of this study indicate the following: (1) Enhancing the government’s rewards and punishments, increasing speculation and rent-seeking costs for grid operators and modifying tariff sales revenue can promote the integrity of grid operators. (2) Establishing reasonable incentives and penalties can effectively mitigate rent-seeking behaviors resulting from collusive pricing in the power industry. (3) Strengthening the accountability of higher authorities to government regulators and adjusting incentives for grid operators to comply and generators to refrain from rent-seeking behavior can increase the likelihood of rigorous inspections by government regulators.

This study elucidates the impact of factors such as the cost of speculation and sales revenue of grid operators, the cost of rent-seeking by power producers and the strength of rewards and punishments by government departments on the power sector. Adjusting these factors can significantly influence the stability of the three-party evolutionary game, providing valuable insights into the regulatory mechanisms of the power industry.

In typical model-based calibration, linearization errors are derived inevitably, and non-negligible negative impact will be induced on the identification results if the rotational kinematic errors are not small enough or the lengths of links are too long, which is common in the industrial cases. Thus, an accurate two-step kinematic calibration method minimizing the linearization errors is presented for a six-DoF serial robot to improve the calibration accuracy.

The negative impact of linearization on identification accuracy is minimized by removing the responsible linearized kinematic errors from the complete kinematic error model. Accordingly, the identification results of the dimension-reduced new model are accurate but not complete, so the complete kinematic error model, which achieves high identification accuracy of the rest of the error parameters, is combined with this new model to create a two-step calibration procedure capable of highly accurate identification of all the kinematic errors.

The proportions of linearization errors in measured pose errors are quantified and found to be non-negligible with the increase of rotational kinematic errors. Thus, negative impacts of linearization errors are analyzed quantitatively in different cases, providing the basis for allowed kinematic errors in the new model. Much more accurate results were obtained by using the new two-step calibration method, according to a comparison with the typical methods.

This new method achieves high accuracy with no compromise on completeness, is easy to operate and is consistent with the typical method because the second step with the new model is conveniently combined without changing the sensors or measurement instrument setup.

Digital transformation is essential for commercial banks to maintain long-term competitiveness in the digital economy era. This study aims to investigate the relationship between inside debt and the bank's digital transformation.

This study set up a quasi-natural experiment based on implementing the executive compensation deferral system in the Chinese banking industry. Using the annual panel data of 180 commercial banks in China from 2007 to 2021, this study employed the difference-in-differences (DID) method to conduct an empirical analysis.

This study confirms a significant statistical relationship between inside debt and the bank's digital transformation, and managerial myopia is the transmission channel of inside debt affecting the bank's digital transformation. Furthermore, the development of Internet finance and the enhancement of bankers' confidence will improve the contributions of inside debt to the bank's digital transformation.

This study contributes to the literature on inside debt and the bank's digital transformation. It has specific policy value for the scientific design of the banking compensation mechanism and accelerating banks' digital transformation.

Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.

Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.

In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.

The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.

Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

The purpose of this study is to explore the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports.

Based on the theoretical analysis of the mechanism of the digital economy’s influence on the binary margin of agricultural exports, this study empirically examines the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports based on China’s customs export data from 2011 to 2016.

The relevant findings are threefold. (1) The digital economy significantly improves the binary margin of agricultural exports, and its effect on the intensive margin is stronger than that on the expansive margin. After the expansive margin is subdivided, the effects on the three sub-variables of the expansive margin are in the following order: old products exported to new markets > new products exported to old markets > new products exported to new markets. (2) The heterogeneity analysis reveals that the digital economy has a stronger role in promoting the binary margin of exports for enterprises in the eastern region, high-income countries as the destination of exports and state-owned enterprises. (3) Mechanism analysis shows that the digital economy promotes the binary margin of agricultural exports by reducing trade costs and intensifying market competition.

First, in terms of research perspective, although there are some studies on the impact of the digital economy on export trade in existing literature, the research objects mainly focus on manufacturing enterprises. In fact, agricultural trade is susceptible to natural conditions and seasonal factors, and countries may impose more SPS measures and TBT measures on agricultural trade due to risk considerations. The relationship between the digital economy and agricultural trade also has its own characteristics, but there are few research studies in this area. At present, only Liu and Gao (2022), based on the data of total imports and exports of different agricultural products from 2004 to 2018, have established a vector auto-regressive model to empirically analyse the heterogeneous dynamic impact of the digital economy on the trade volume of agricultural products. In addition, Ma and Guo (2023) conducted an empirical test on the total effect, regional heterogeneity and threshold effect of the digital economy on agricultural export trade based on China’s provincial panel data from 2011 to 2020. Therefore, under the new circumstances of continuous integration of digital technology and agriculture, this study interprets the impact effect and mechanism of the digital economy on the binary margin of agricultural exports from the perspective of the digital economy, providing new research perspectives and approaches for promoting the growth of agricultural exports. Second, in terms of theoretical analysis, the above studies have not been fully analysed in terms of the specific mechanism of the impact of the digital economy on agricultural exports. Based on the positive and negative characteristics of agricultural trade, this study introduces two kinds of roles into the theoretical analysis framework to comprehensively determine the trade impact effect of the digital economy. Third, in terms of research design, this study empirically examines the impact of the digital economy on the binary margin of agricultural products, passing a series of robustness tests and investigating the mediating roles of trade cost and market competition effects, producing an empirical basis for China to leverage the digital economy to promote the binary margin of agricultural exports.

Based on social cognitive theory, this study aims to explore the psychological mechanism behind consumer verification behavior following tourism e-commerce live-streaming.

Based on grounded theory, data were collected through 20 semi-structured in-depth interviews and analyzed.

This study identified that companies commonly use reminder messages and secondary promotions to facilitate the verification of tourism live-streaming products. Throughout this process, consumers undergo various psychologies related to verification. Specifically, they experience four positive verification psychologies: fear of missing out, anticipated emotions, status self-esteem and promotional perception. They also encounter two negative verification psychologies: psychological reactance and invasiveness. In addition, environmental factors such as the type of tourism live-streaming products and tourism destinations, along with individual trait factors like cognitive miserliness, tourism experience, autonomy, regulatory mode and impulsiveness, play significant roles in shaping verification behavior. These factors collectively influence the formation of verification behavior.

This study can provide recommendations for tourism companies to conduct marketing events following live-streaming. It is one of the earlier comprehensive studies discussing how to promote verification behavior following tourism e-commerce live-streaming. It helps to understand the psychological mechanism underlying the formation of verification behavior.

Purpose: The issue of whether participation in online peer-support communities has positive or negative impacts on the psychological adjustment of cancer patients warrants further explorations from new perspectives. This research investigates the role of personality traits in moderating the impact of online participation on the psychological adjustment of cancer patients in terms of their general psychological well-being and cancer-specific well-being.

Methodology: Study participants consisted of adults diagnosed with leukemia. Questionnaires were collected from 111 participants in two leukemia-related forums in China, Baidu Leukemia Community and Bloodbbs. Information regarding the personality traits, online participation, and psychological adjustment were collected using an online questionnaire. A linear regression model was used to test the moderation effect of personality traits on the relationship between online participation and psychological adjustment.

Findings: The main effect of participation in online support communities on psychological adjustment was not statistically significant. Importantly, two personality traits (i.e., emotional stability and openness to experience) moderated the relationship between online participation and psychological adjustment to cancer. Leukemia patients with high emotional stability and high openness to experience reported better psychological adjustment as they participated more in the online community. However, this was not the case for patients with low stability and low openness, who reported worse psychological adjustment as their participation in the online support community increased.

Value: This study introduces two personality moderators into the discussion of how participation in online support communities influences the lives of cancer patients. The moderation effects help to explain why there have been contradictions in the findings of previous studies. In addition, this study adds to the current literature on online support communities as little research on this topic has been conducted outside of the US and Europe. Practically, this study not only highlights the need to evaluate the personality traits of patients who are recommended to participate in online communities, but also underlines the necessity of intervention in these communities.

The purpose of this paper is to investigate the effect Ti on stress corrosion cracking (SCC) and flow accelerated stress corrosion cracking (FA-SCC) behavior and mechanisms of Monel K500 alloy.

Monel K500 alloy with different Ti contents was designed. A metallurgical microscope (XJP-3C) and scanning electron microscopy (EV0 MA15 Zeiss) with an energy dispersive spectroscopy were used to analyze the microstructure of the Monel K500 alloy. In situ electrochemical tests were carried out in static and flowing seawater to study FA-SCC behavior.

The number of TiCN particles in the alloy increased as the increase of Ti content. The static corrosion and SCC of Monel K500 alloy are reduced as the content of Ti increases. Generally, the SCC of alloys was caused by the synergistic effect of the anodic dissolution at exposed metal matrix and the pit corrosion of metal matrix adjacent to TiCN particles, which was further accelerated by flowing.

The corrosion behavior and mechanism of Monel K500 alloy with different Ti contents in a complex flowing seawater environment are still unclear, which remain systematic study to insure the safe service of the alloy.

Controversy has long swirled over the claim that Donald Trump's base has deeply rooted authoritarian tendencies, but Trump himself seems to have few doubts. Asked whether his stated wish to be dictator “on day one” of second term in office would repel voters, Trump said “I think a lot of people like it.” It is one of his invariable talking points that 74 million voters supported him in 2020, and he remains the unrivaled leader of the Republican Party, even as his rhetoric escalates to levels that cautious observers now routinely call fascistic.

Is Trump right that many people “like” his talk of dictatorship? If so, what does that mean empirically? Part of the answer to these questions was apparent early, in the results of the 2016 American National Election Study (ANES), which included survey questions that we had proposed which we drew from the aptly-named “Right-Wing Authoritarianism” scale. Posed to voters in 2012–2013 and again in 2016, those questions elicited striking responses.

In this chapter, we revisit those responses. We begin by exploring Trump's escalating anti-democratic rhetoric in the light of themes drawn from Max Weber and Theodor W. Adorno. We follow this with the text of the 2017 conference paper in which we first reported that 75% of Trump's voters supported him enthusiastically, mainly because they shared his prejudices, not because they were hurting economically. They hoped to “get rid” of troublemakers and “crush evil.” That wish, as we show in our conclusion, remains central to Trump's appeal.