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The purpose of this paper is to evaluate naturally occurring phytic acid (PA) as a green-water-based lubricant.

Lubrication is studied using a ball-on-disk tribometer with silica glass against silicon nitride contact, and the friction coefficient and wear are measured in the boundary lubrication regimes.

Excellent lubrication performance was found by using PA aqueous solutions. After the running-in process, the sliding coefficient of friction could drop to as low as 0.01 with a quite low concentration of 7.5 × 10⁻⁴ M. The lubricating performance of PA solution could be further improved by increasing PA concentration. The work suggests that the excellent lubricity of PA in aqueous solution can be mostly contributed to its adsorption on the silica surface.

The paper shows that the natural products could be used as water-based lubricant additives.

The purpose of this paper is to increase wear resistance of aluminum.

The authors have studied the ways to improve the tribological performance of aluminum by assembling stearic acid on aluminum coated by sol-gel-derived TiO₂ film. The samples were characterized by infrared spectroscopy, contact angle measurements and a macro friction and wear tester.

Enhanced wear resistance was clearly obtained after functionalization of TiO₂ film on aluminum by stearic acid.

The relevant results might be helpful for guiding the surface modification of aluminum devices in industrial applications.

The purpose of this paper is to extend the usage of stroke gestures in manipulation tasks to make the interaction between human and robot more efficient.

In this paper, a set of stroke gestures is designed for typical manipulation tasks. A gesture recognition and parameter extraction system is proposed to exploit the information in stroke gestures drawn by the users.

The results show that the designed gesture recognition subsystem can reach a recognition accuracy of 99.00 per cent. The parameter extraction subsystem can successfully extract parameters needed for typical manipulation tasks with a success rate about 86.30 per cent. The system shows an acceptable performance in the experiments.

Using stroke gesture in manipulation tasks can make the transmission of human intentions to the robots more efficient. The proposed gesture recognition subsystem is based on convolutional neural network which is robust to different input. The parameter extraction subsystem can extract the spatial information encoded in stroke gestures.

The author designs stroke gestures for manipulation tasks which is an extension of the usage of stroke gestures. The proposed gesture recognition and parameter extraction system can make use of stroke gestures to get the type of the task and important parameters for the task simultaneously.

The purpose of this paper is to study the corrosion behaviors of X70 steel under direct current (DC) interference at 0-1,200 A/m² in simulated soil solution.

The Tafel polarization curves of X70 steel under DC interference were tested using electrochemical method, the corrosion rate was calculated using weight-loss method and the change in steel surface was analyzed by optical microscopy.

The results showed that E-I polarization curves under 200-1,200 A/m² interference were linear; with an increase in the DC density, the corrosion potential of X70 steel shifted positively, solution pH after the weight-loss tests increased and corrosion rate increased linearly. A mathematical relationship between polarization resistance Rp and current density was established. Corrosion morphology indicated that pitting corrosion and crevice corrosion occurred on the X70 steel under DC interference in simulated soil solution.

All tests were conducted at a relative higher DC density (200-1,200 A/m²). The linear fitting method is proposed to fit data of Tafel polarization curves under DC interference. This study provides guidelines for safe operation of X70 steel pipelines.

This paper aims to investigate the reason for natural gas leakage from transmission pipelines between Linyi and Shouguang in China during sealing tests, explore the failure mechanism and provide a reference for taking reasonable measures to prevent such accidents.

Failure analysis for the steel pipe has been addressed with different methods, such as microstructure analysis, inclusion analysis, corrosion product analysis, macro- and micro-morphology analyses and bacterially catalyzed experiments.

Several bulges were observed, especially at the bottom of the steel pipe sample, with the distribution and positioning not related to the weld. The inner surface of the steel pipe was severely corroded, and the oxide scale was flaking in many places. The greatest corrosion area was identified at the bottom of the steel pipe near the gas leakage point. Severe pitting and perforation corrosion in the pipeline were observed, and the main corrosion reaction products were Fe3O4, FeO and FeS. The grain orientation distribution near the crack (coarse grains <101> and fine grains <111> at the microcrack tip) indicates that fine grains may be beneficial in hindering crack propagation.

The principal mechanism for the corrosion failure is supposed to be due to the interaction of chloride ions with the sulfate-reducing microorganisms present and the stress corrosion cracking by chloride and sulfide formed by the sulfate-reducing microorganisms.

This study examines the bi-directional relationship between corporate social responsibility disclosure (CSRD) and ownership structure through a dynamic empirical framework in an emerging economy context.

Data over 10 years are used to investigate the response of disclosure to ownership structure variables and vice versa. Dynamic bi-directional relationships are hypothesised and empirically investigated using a panel vector autoregressive (PVAR) model. The ownership structure variables used are government ownership, block ownership and director ownership, while CSRD is constructed as a score through content analysis.

A bi-directional negative relationship between CSRD and government ownership is found, revealing a preference for the state to invest in companies with opaque disclosure. CSRD is found to respond negatively to block ownership, albeit weakly. Results also show that directors prefer to own shares in the company they manage when there are low levels of CSRD.

The current empirical set-up of using a small emerging economy may not carry to the context of larger emerging economies where the institutional context may differ. Thus, future research could use this dynamic empirical approach to re-examine the questions raised in this paper using data from other emerging economies. The use of a longer time series makes it feasible to explore further analysis what was not possible in this study, such as an impulse response analysis examining the reaction of the variables of interest, CSRD and ownership variables for a specific time horizon to particular changes or shocks associated with one of the endogenous variables in the PVAR.

A major implication is that expecting disclosure practices to improve due to government and director initiatives would be less likely in emerging economies. State and director shareholders prefer to invest in opaque companies because they may purposely choose to keep the minimum disclosure levels. The paper calls for a transparent process and ethical guidelines to guide government investment in firms.

The study investigates the bi-directional relationship between ownership structure and CSRD in contrast to the existing literature's presupposed one-way relationship between these variables by demonstrating that bi-directionality does matter. This paper also contributes to the CSRD literature in the emerging economy context. The bi-directional negative relationship between CSRD and government ownership calls for a transparent selection process of board members as representatives of the state in those companies where the government has an ownership stake. It also calls for a transparent process and ethical guidelines to guide government investment in firms.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

In recent years, the demand for oil and gas pipelines has increased rapidly. Due to the restrictions of the pipeline routing, pipelines are generally laid in parallel or in the same trench, which results in stray-current interference between the independent cathodic protection (CP) systems. The purpose of this paper is to study the interference between the long-distance parallel pipelines and to obtain the optimized operation for the CP systems.

In this study, first, the numerical model of parallel pipelines was established using the boundary element analysis software (BEASY). Second, the effects of horizontal distance between parallel pipelines, coating damage rate, soil conductivity and anode output current on the interference of parallel pipelines were studied. Finally, by varying the layout or the output currents of CP stations, an optimized operation scheme osf long-distance parallel pipelines was put forward.

Simulation results showed that with a decrease in soil conductivity or coating damage rate, the interference increased. Moreover, the interference decreased with an increase in horizontal distance between two parallel pipelines or a decrease in anode output current. It was found that there are three methods to reduce the interference between long-distance parallel pipelines: to reduce the output currents of CP stations, combined protection and to close part of the CP stations. Among them, to close part of CP stations was the optimized scheme because of the lowest operating and maintenance cost.

The optimized operation scheme proposed in this study can not only solve the interference between parallel pipelines but also provide guidance for the parallel pipelines to be built in the future. Reasonably arranging the cathodic protection stations using numerical simulation can avoid the interference in the cathodic protection systems, and reduce the construction cost.

Many factors affect the emergence and development of crop diseases and insect pests. Traditional methods for investigating this subject are often difficult to employ and produce limited data with considerable uncertainty. The purpose of this paper is to predict the annual degree of cotton spider mite infestations by employing grey theory.

The authors established a GM(1,1) model to forecast mite infestation degree based on the analysis of historical data. To improve the prediction accuracy, the authors modified the grey model using Markov chain and BP neural network analyses. The prediction accuracy of the GM(1,1), Grey-Markov chain, and Grey-BP neural network models was 84.31, 94.76, and 96.84 per cent, respectively.

Compared with the single grey forecast model, both the Grey-Markov chain model and the Grey-BP neural network model had higher forecast accuracy, and the accuracy of the latter was highest. The improved grey model can be used to predict the degree of cotton spider mite infestations with high accuracy and overcomes the shortcomings of traditional forecasting methods.

The two new models were used to estimate mite infestation degree in 2015 and 2016. The Grey-Markov chain model yielded respective values of 1.27 and 1.15, whereas the Grey-BP neural network model yielded values 1.4 and 1.68; the actual values were 1.5 and 1.8.

The improved grey model can be used for medium- and long-term predictions of the occurrence of cotton spider mites and overcomes problems caused by data singularity and fluctuation. This research method can provide a reference for the prediction of similar diseases.

The authors examine the determinants of ESG disclosure and differentiate between voluntary and mandatory disclosure regimes in Hong Kong.

The authors analyse both Bloomberg ESG scores and a disclosure index score, manually constructed according to the 2019 Hong Kong Exchange ESG Guide using regression tests.

The results indicate that the level of concentrated ownership is negatively associated with the quantity of ESG disclosure only in the voluntary disclosure period, suggesting that agency problems are alleviated when ESG reporting is mandatory. The findings also show that larger firms significantly disclose higher levels of ESG information in both voluntary and mandatory disclosure periods. Furthermore, the extent of ESG disclosure significantly increases when firms' sustainability reports are audited by Big 4 accounting firms only in the voluntary disclosure period. Finally, the control variables are significantly related to the level of ESG disclosure showing that ESG disclosure increased over time and is significantly different among industries.

The authors make contributions to the literature on non-financial disclosure in relation to ESG reporting by examining the relationship between firm characteristics and ESG disclosure in the Hong Kong context under both voluntary and mandatory disclosure regimes. This study also provides important implications for other stock markets and relevant stakeholders including preparers, users and the sustainability profession.