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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.

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 is to reveal the underlying mechanism in film formation of oil-in-water (O/W) emulsion.

This study focuses on the film forming characteristics of O/W emulsion between the surface of a steel ball and a glass disc coated with chromium. The lubricant film thicknesses of O/W emulsion with various mechanical stirring strength were discussed, which were observed by technique of relative optical interference intensity.

The authors directly observed the oil pool in the contact area, finding the size of oil pool was closely related to the film-forming ability of emulsion. Enrichment phenomenon occurs in oil pool, which was caused by phase inversion. Further investigations revealed that the emulsion is stable with strong stirring strength, resulting in a smaller oil pool size and worse film forming ability.

With the wide usage of O/W emulsion in both biological and industrial systems, the ability of emulsion film formation is considered as an important factor to evaluate the lubrication effectiveness.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2022-0354/

The aim of this article is to present a PIN (pedestrian inertial navigation) solution that incorporates altitude error correction, which eliminates the altitude error accurately without using external sensors. The main problem of PIN is the accumulation of positioning errors due to the drift caused by the noise in the sensors. Experiment results show that the altitude errors are significant when navigating in multilayer buildings, which always lead to localization to incorrect floors.

The PIN proposed is implemented over an inertial navigation systems (INS) framework and a foot-mounted IMU. The altitude error correction idea is identifying the most probable floor of each horizontal walking motion. To recognize gait types, the walking motion is described with angular rate measured by IMU, and the dynamic time warping algorithm is used to cope with the different dimension samples due to the randomness of walking motion. After gait recognition, the altitude estimated with INS of each horizontal walking is checked for association with one of the existing in a database.

Experiment results show that high accuracy altitude is achieved with altitude errors below 5 centimeters for upstairs and downstairs routes in a five floors building.

The main limitations of the study is the assumption that accuracy floor altitude information is available.

Our PIN system eliminates altitude errors accurately and intelligently, which benefits from the new idea of combination of gait recognition and map-matching. In addition, only one IMU is used which is different from other approach that use external sensors.

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.

Did Chinese cities whose public health departments are headed by medical professionals fare better in fighting coronavirus disease 2019 (COVID-19)?

The authors collected the professional background of the directors of the public health departments of 350 Chinese cities, which include 87% of the Chinese population. Excluding Wuhan, the epicenter of COVID-19, the authors analyzed the infection rates and death rates from COVID-19 between 131 Chinese cities whose public health departments are led by medical professionals and 218 cities whose public health departments are led by nonprofessionals. The authors employed a multivariate regression controlling for the number of people that traveled from Wuhan to each city, the local economic development and the number of hospital beds.

Chinese cities whose public health departments are led by medical professionals had 21 fewer confirmed cases per 10 million as of January 31, 2020 [95% CI, −40 to −3], 58 fewer cases per 10 million in the next 10 days [95% CI, −116 to 0], similar new cases between February 11 and February 20, 2020, and 3 fewer deaths per 10 million as of February 20, 2020 [95% CI, −7 to 0].

Association could not make a strong causal claim.

Local public health authorities are critical for combating a pandemic. The authors found that Chinese cities whose public health departments are headed by medical professionals were associated with lower infection rates and fewer death rates from COVID-19. The results were significant only at the start of the outbreak. This study’s results suggest that to better combat a pandemic, local public health authorities should be led by competent people who have a medical background.

The authors provide the first empirical evidence about the association between a local public health head's competence and the infection rate and death rate of COVID-19. The authors’ manually collected data also show that only 38% of the heads of the public health departments of Chinese cities have a medical background.

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.

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.

This paper seeks to address issues of sustainability in the rapid urbanization in China with examination of knowledge management factors in the creation of new Chinese cities.

A case study was undertaken at Zhengdong New District along with semi‐structured interview mixed with evaluation and content analyses of successful knowledge management factors as the analytical approach.

This study explores the ongoing revolution of building new cities and towns in China, and highlights the importance of knowledge‐based development in achieving sustainable development. Following the establishment of the theory and model of the knowledge city, it explores the features of knowledge city in practice. Focusing on the case study of Zhengdong New District, Zhengzhou, Henan Province, it examines the factors of knowledge management in the creation of the new city. However, it is believed that the strategic development plan was made following the principles of sustainability. Furthermore, it has been accepted that the strategic plan reflexes the framework and sustains various features of the knowledge city, which could be seen as the embryo of knowledge city in China. In the meantime, it has to be recognised that the outcome of the evaluation of Zhengdong New District, which has been discussed in this paper, is merely the audit of what is currently happening in the first phase of the project and reflexes the current issues, and might give impact to the implementation of municipal government strategy in the future.

This paper concludes that, while the local authority is endeavouring to build a physically modern city, it might have overlooked the importance of using knowledge management principles as a tool to promote social, cultural, and environmental sustainability. Yet the analysis in this paper demonstrates that it is not impossible to use knowledge management framework as a tool to assist policy makers governing the creation of a new city in a sustainable way. The discussion in this paper is expected to be thought‐provoking in a holistic understanding of the theoretical perspective of knowledge city and further research into this field in the Chinese context.

The purpose of this paper is to develop a quantitative risk assessment method for agricultural products cold chain logistics to assess the condition of the fresh agricultural products cold chain process objectively and accurately.

A risk assessment index system of agricultural products cold chain logistics is designed on the basis of the risk identification for the process of agricultural products cold chain logistics. This paper first uses catastrophe progression method and a new maximum deviation method to build an improved catastrophe progression assessment model for agricultural products cold chain logistics. In order to verify the reliability and validity of the model, two representative enterprises are selected as the case in the study.

The results in the empirical research indicate strong support for the assessment model and coincide with the reality. The risk assessment index system can also reflect the key risk factors from agricultural products cold chain logistics scientifically. In addition, the improved catastrophe progression assessment method proposed in this paper can be scientific and reasonable to predict risk.

This paper contributes to provide a new risk assessment model for agricultural products cold chain logistics. The new model overcomes the limitation of subjective empowerment and it increases the objectivity and scientificity in the process of cold chain logistics risk assessment. This paper also shows that practitioners involved in the field of products cold chain logistics can manage the potential risk by a set of scientific methods for assessing the risk before the accident.

The paper provides a practical guideline to practitioners, especially for cold chain logistics managers, relevant management departments, and cold chain logistics management consultants. It is proved that the new risk assessment method and the risk assessment index system of agricultural products cold chain logistics can help them assess the risk scientifically and reasonably.

Although the calculation is simple, the new model can overcome the limitation of subjective empowerment scientifically and reasonably, and thus has important practical value.