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The purpose of this paper is to propose a approach for data visualization and industrial process monitoring.

A deep enhanced t-distributed stochastic neighbor embedding (DESNE) neural network is proposed for data visualization and process monitoring. The DESNE is composed of two deep neural networks: stacked variant auto-encoder (SVAE) and a deep label-guided t-stochastic neighbor embedding (DLSNE) neural network. In the DESNE network, SVAE extracts informative features of the raw data set, and then DLSNE projects the extracted features to a two dimensional graph.

The proposed DESNE is verified on the Tennessee Eastman process and a real data set of blade icing of wind turbines. The results indicate that DESNE outperforms some visualization methods in process monitoring.

This paper has significant originality. A stacked variant auto-encoder is proposed for feature extraction. The stacked variant auto-encoder can improve the separation among classes. A deep label-guided t-SNE is proposed for visualization. A novel visualization-based process monitoring method is proposed.

The purpose of this paper is to predict quantitative level of stray current leaking to the buried metallic structure by establishing convolution neural network (CNN) model.

First, corrosion experimental system of buried metallic structure is established. The research object of this paper is the polarization potential within 110 min, CNN model is used to predict the quantitative level of stray current leakage using the data from corrosion experimental system further. Finally, results are compared with the method using BP neural network.

Results show that the CNN model has better predictive effect and shorter prediction time than the BP model, the accuracy of which is 82.5507 per cent, and the prediction time is shortened by more than 10 times.

The established model can be used to forecast the level of stray current leakage in the subway system effectively, which provides a new theoretical basis for evaluating the stray current corrosion hazard of buried metallic structure.

The purpose of this paper is to investigate the tribological properties of novel phosphorous-nitrogen (P-N) type additives in water.

The tribological properties of the novel P-N additives in water are compared with a commercial lubricant additive of the P-N type using a four-ball machine. The tribological mechanism was investigated by X-ray absorption near-edge structure (XANES) spectroscopy.

The experimental results indicate that the phosphoramidate derivatives possess good anti-wear and friction-reducing properties. The XANES analysis shows that the prepared compounds can form a protective film containing phosphate and/or polyphosphate that affects the tribological behavior.

The purpose of this paper is to investigate the tribological properties of the novel P-N type additives in water.

The purpose of this paper was to improve the frictional wear resistance properties of piston skirts caused by the low viscosity lubricant by studying the tribological performance of three novel coating materials.

Comparative tribological examinations were performed in a tribological tester using the ring-block arrangement under two viscosity lubricants, the loading force was applied as 100 N, the speed was set to 60 r/min and the testing time was 180 min.

Under low viscosity lubricant, the friction coefficient and wear of the three coatings all increase, and the friction coefficient and wear of the PTFE coating are the largest, while the MoS₂ coating has the lowest friction coefficient and wear. Under low viscosity lubricant, the friction coefficient of the MoS₂ coating is 2.1%–5.4% and 20.0%–24.3% lower than that of the SiO2 and PTFE coating, respectively. The friction coefficient and wear fluctuation rate of the MoS₂ coating is the smallest when the lubricant viscosity decreases, which indicates that the MoS₂ coating has excellent stability and adaptability under low viscosity lubricant.

To reduce the piston skirt wear caused by low viscosity lubricant in heavy-duty diesel engines, the friction and wear adaptability of three novel composite coating materials for piston skirts were compared under 0 W-20 low viscosity lubricant, which could provide a guidance for the application of wear-resistant materials for heavy-duty diesel engine piston skirt.

The purpose of this paper is to investigate the influence of two intrinsic (i.e. sense of self-worth and socializing) and two extrinsic motivations (i.e. economic reward and reciprocity) on mobile coupon (m-coupon) sharing by users in social network sites (SNSs). Moreover, this study examines how coupon proneness moderates the relationship between motivations and m-coupon sharing in SNSs.

A research model that integrates four motivations, coupon proneness, and m-coupon sharing is developed. Quantitative data from 247 users are collected via online and offline survey. Partial least squares technique is employed to evaluate the measurement model, and hypotheses are tested through hierarchical regression analysis.

Sense of self-worth, socializing, economic reward and reciprocity have positive effects on m-coupon sharing in SNSs. Furthermore, coupon proneness positively moderates the relationship of socializing and reciprocity with m-coupon sharing, whereas the moderating effects of coupon proneness on the relationship of sense of self-worth and economic reward with m-coupon sharing are insignificant.

The findings highlight the integrated effects of coupon proneness and motivations on m-coupon sharing in SNS. The impact of socializing and reciprocity on m-coupon sharing is higher for users with higher coupon proneness. However, the effect of sense of self-worth and economic reward on m-coupon sharing is the same regardless of coupon proneness of users. Therefore, although users with different motivations should be identified, SNSs and merchants should develop different incentive mechanisms to promote m-coupon sharing among various users.

The purpose of this paper is to integrate social capital theory and motivation theory to identify the factors that affect the intention of users to share mobile coupons (m-coupons) via social network sites (SNS). Social capital includes social ties, trust, and perceived similarity, whereas motivation comprises sense of self-worth and socializing.

A research model that integrates three social capital factors, two motivations, and m-coupon sharing is developed. Quantitative data from 297 users who had coupon usage experience are collected via offline and online survey. Partial least squares is used to conduct data analysis and test hypotheses.

Social ties, trust, and perceived similarity are positively related to m-coupon sharing intention and positively affect sense of self-worth and socializing, which have significant positive effects on m-coupon sharing intention and mediate the relationships between social capital factors and sharing intention.

This study highlights the integrated effects of social capital and motivations on m-coupon sharing intention in SNS. While social capital factors (i.e. social ties, trust, and perceived similarity) and motivations (i.e. sense of self-worth and socializing) positively affect m-coupon sharing, motivations are more directly associated with m-coupon sharing than social capital factors.

In a pandemic framework (COVID-19), this chapter explores the impact of the global economy and socio-cultures concerning three axes: recreational, tourism, and hospitality. Although we slowly see an economic revival, it is well known that this sector of study is very susceptible to being affected by the context of nations. Following restrictions and measures taken by governments around the world to reduce the number of cases of coronavirus infections, many nations closed their borders, affecting international travel and by 2020 tourism had been reduced to the near cessation of operations due to the imminent fear of this poorly studied disease, and the service sector was negatively affected. It should be added that, according to the World Tourism Organization's projections, a decrease of between 20 and 30% is forecast for 2020 compared to the previous year.

The purpose of this study was to investigate the microstructural evolution and hydrolytic stability of poly(phenylborosiloxane) (PPhBS) to further use and develop the oligomers as heat-resistant modifiers.

PPhBS was synthesized by direct co-condensation of boric acid (BA) and phenyltriethoxysilane (PTEOS). The structural evolution of PPhBS at high temperature was investigated by Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), differential thermal analysis (DTA), in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and 29Si nuclear magnetic resonance (NMR) spectroscopy. In addition, the change in the morphology of the PPhBS powder was examined to demonstrate the evolution of the chemical bonds, and the hydrolytic stability of PPhBS was investigated by a combination of X-ray diffraction (XRD) analysis, measurement of the mass loss in water and FTIR spectroscopy.

The results revealed that a cross-linking network was gradually formed with increasing temperature through the condensation of the residual hydroxyl groups in PPhBS, and the Si-OH and B-OH bonds remained even at a high temperature of 450°C. Furthermore, heat treatment improved the hydrolytic stability of the oligomer. The hydrolysis of the B-O-B bonds in PPhBS was reversible, whereas the Si-O-Si and Si-O-B bonds were highly resistant to hydrolysis.

The prepared PPhBS can be used as a heat-resistant modifier in adhesives, sealants, coatings and composite matrices.

Investigation of the structural evolution of a polyborosiloxane at high temperature by DRIFTS is a novel approach that avoided interference from moisture in the air. The insoluble mass fraction and the FTIR spectrum of PPhBS washed with water were used to investigate the hydrolytic stability of PPhBS.

This paper aims to seek the optimal proportion of female executives in corporate management teams, and to analyze the threshold effect of the proportion of female executives on the enterprise market value and enterprise management performance by using a panel threshold regression model. The purpose of this paper is to obtain the optimal interval, during which female executives exert positive effects on enterprise market value and enterprise management performance.

Based on the data of listed companies in SSE from 2003 to 2012, this paper conducts theoretical and empirical analysis by using a panel threshold regression model.

This paper proves that the proportion of female executives has a threshold effect on the enterprise market value and enterprise management performance. The results show that the proportion of female executives has an optimal interval. In other words, during the 53.8-68.4 percent interval, the proportion of female executives exerts the least negative effect on the enterprise market value and the most positive effect on the enterprise management performance.

In this paper, the non-linear relationship between female executives, enterprise market value and enterprise management performance has been verified, and the optimization interval of the female executives’ proportion has been figured out as well.

Inland shipping has been extensively recognised as a sustainable, efficient and good alternative to rail and road modes of transportation. In recent years, various authorities and academic researchers have advocated shifting from road to other sustainable modes like inland waterway transport (IWT) or rail transport. Academic work on modernisation and technological innovations to enhance the effectiveness and efficiency of waterborne transportation is becoming apparent as a growing body of literature caused by the need to achieve a sustainable transport system. Thus, it became apparent to explore the research trends on IWT.

A systematic and structured literature review study was employed in this paper to identify the challenges and concepts in modernising inland waterways for freight transportation. The review analysed 94 articles published in 54 journals from six well-known databases between 2010 and 2022.

The key findings of this review are that despite various challenges confronting the sector, there have been successful cases of technological advancement in the industry. The main interest among scholars is improving technical and economic performance, digitalisation, and safety and environmental issues. The review revealed that most of the literature is fragmented despite growing interest from practitioners and academic scholars. Academic research to address the strategic objectives, including strengthening competitiveness (shipbuilding, hydrodynamics, incorporating artificial intelligence into the decision-making process, adopting blockchain technology to ensure transparency and security in the transactions, new technologies for fleets adaptation to climate change, more effective handling, maintenance and rehabilitation technologies), matching growth and changing trade patterns (intermodal solutions and new logistics approaches) are major causes of concerns.

By employing the approach of reviewing previously available literature on IWT review papers, this review complements the existing body of literature in the field of IWT by providing in a single paper a consolidation of recent state-of-the-art research on technological developments and challenges for inland waterways freight transport in the intermodal supply chain that can act as a single resource to keep researchers up to date with the most recent advancements in research in the domain of inland waterway freight transport. Additionally, this review identified gaps in the literature that may inspire new research themes in the field of IWT.