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Two corrosion inhibitors for closed cooling water systems, nitrite-based and mixture of nitrite and molybdate corrosion inhibitor, are often compared to each other. This study aims to optimize these two inhibitors in terms of concentration and pH for carbon steel protection, with insights into the double layer structure on surface and its impact on corrosion inhibition.

Electrochemical analysis including electrochemical impedance spectroscopy and potentiodynamic test are carried out for quick assessment of corrosion inhibition efficiency and optimization, which is confirmed by immersion test and microscopic analysis. The electronic properties of the surface film are analyzed through Mott–Schottky method which provides new insights into the inhibition mechanism and the role of each component in mixture inhibitor.

Mixture of nitrite and molybdate is shown to present higher inhibition efficiency, owning to the double layer structure. Nitrite alone can form a protective surface film, whereas molybdate leads to an n-type semiconductive film with lower donor density, hence giving rise to a better inhibition effect.

Surface after inhibitor treatment has been carefully characterized to the microscopic scale, implying the effect of micro-structure, chemical composition and electronic properties on the corrosion resistance. Inorganic corrosion inhibitors can be tuned to provide higher efficiency by careful design of surface film structure and composition.

Almost every study on corrosion inhibitor applies such method for quick assessment of corrosion inhibition effect. Mott–Schottky test is one of electrochemical methods that reveals the electronic properties of the surface film. Previous works have studied the surface layer mainly through X-ray photoelectron spectroscopy. This study provides another insight into the surface film treated by nitrite and molybdate through Mott–Schottky analysis, and relates this structure to the corrosion inhibition effect based on multiple analysis including electrochemistry, microscopic characterization, thermodynamics and interface chemistry.

The purpose of this paper is to introduce cyclic electrochemical impedance spectroscopy (EIS) method to understand the corrosion evolution behavior of structural materials in secondary circuit water environments of pressurized water reactor (PWR) system.

The cyclic EIS has been used to understand the corrosion evolution of 304 stainless steel (SS) in simulated secondary circuit water environment. Scanning electron microscopy and X-ray photoelectron spectroscopy have been used to characterize the microstructure and corrosion morphology of 304 SS sample.

Cyclic EIS measurement is applicable in gaining information on the corrosion evolution of 304 SS in high-temperature and high-pressure (HTHP) water environments. Based on analyses of the cyclic EIS data, it is considered that the measured EIS response of 304 SS sample under HTHP water environment mainly comes from the compact inner part of the newly formed oxide layer, which gradually inhibits the progress of electrochemical reactions at the oxide layer/substrate interface.

The cyclic EIS has been introduced into HTHP water environment, and its reliability has been evaluated. It may find a wide application in corrosion studies of materials under HTHP water environments, which is critical for a safe operation in nuclear power plants and beneficial for the development of corrosion-resistant materials in PWR system.

The purpose of this paper is to optimize a suitable electrochemical method in evaluating the corrosion rate of structural materials of 20# carbon steel, P280GH carbon steel, 17-4PH stainless steel, 304 stainless steel and Alloy 690TT in high-temperature and high-pressure (HTHP) water of pressurized water reactor secondary circuit system.

Weight-loss method has been used to obtain the corrosion rate value of each structural material in simulated HTHP water. Besides, linear polarization method and weak polarization curve-based three-point method and four-point method have been compared in obtaining a sound corrosion rate value from the potentiodynamic polarization curve. Scanning electron microscopy (SEM) and atomic force microscope have been used to characterize the microstructure and corrosion morphology of each structural material.

Although there is deviation in gaining the corrosion rate value compared to weight-loss test, the weak polarization curve-based four-point method has been found to be a suitable electrochemical method in gaining corrosion rate value of structural materials in HTHP waters.

This paper proposes a suitable and reliable electrochemical method in gaining the corrosion rate value of structural materials in HTHP waters. The proposed weak polarization curve-based four-point method provides a timesaving and high-efficient way in corrosion rate evaluation of secondary circuit structural materials and thus has a potential application in nuclear power plants.

The purpose of this study is to investigate the initial corrosion behavior of pure Mg, AZ31 and AZ91 alloys in phosphate buffer solution (PBS) and to characterize the features in corrosion type and resistance of the corrosion product layer.

The scanning electron microscopy, equipped with energy-dispersive spectroscopy, X-ray photoelectron spectroscopy and electrochemical impedance spectroscopy have been used to characterize the as-corroded samples. Besides, the Mg²⁺ concentration in PBSs has been determined by inductively coupled plasma atomic emission spectrum.

It has been found that pure Mg suffers pit corrosion, and AZ31 initially undergoes pit corrosion and then uniform corrosion dominates with an extended immersion duration. However, AZ91 exhibits the uniform corrosion with the highest corrosion rate among the three materials. Besides, the corrosion product layer on AZ31 has the best compactness and corrosion resistance.

The findings add depth in understanding the corrosion of pure Mg and its alloys in PBS and also have guiding significance in exploring the effects by alloyed elements to develop new biomaterials with better performance.

In this study, the author intend to investigate the impacts of renewable energy use and environmental taxation on sustainable development measured by the adjusted net savings (ANS).

This study employs the quantile regression (QR) for a set of 24 Organization for Cooperation and Economic Development (OECD) countries over the period 1994–2018.

The main empirical findings of estimates show that access to renewable energy and environmental taxation generate positive and significant effects in increasing the ANS for most quantiles. Hence, they are practical tools for achieving sustainable development goals (SDGs).

This study has important implications for governments and policymakers of the OECD countries. Therefore, governments can use subsidies and incentives to promote the adoption of renewable energy sources, energy-efficient technologies and sustainable practices. Similarly, by imposing taxes on pollution and resource use, governments can encourage the adoption of cleaner technologies and practices toward more sustainable behavior.

This paper is based on a novel measure of sustainable development (ANS) and a novel econometric method (QR).

Harmonic drives are used widely in aviation, robotics and instrumentation due to their benefits including high transmission ratio, compact structure and zero backlash. One of the common faults of a harmonic drive is the axial movement of the input shaft. In such a case, its input shaft moves in the axial direction relative to the body of the harmonic drive. The purpose of this study is to propose two fault diagnosis methods based on the current signal of the driving servomotor for the axial movement failure in terms of input shafts of harmonic drives.

In the two proposed fault diagnosis methods, the wavelet threshold algorithm is firstly used for filtering noises of the motor current signal. Then, the feature of the denoised current signal is extracted by the empirical mode decomposition (EMD) method and the wavelet packet energy-entropy (WPEE) theory, respectively, obtaining two kinds of feature sets. After a deep learning model based on the deep belief network (DBN) is constructed and trained by using these feature sets, we finally identify the normal harmonic drives and the ones with the axial movement fault.

In contrast to the traditional back propagation (BP) neural network model and support vector machine (SVM) model, the fault diagnosis methods based on the combination of the EMD (as well as the WPEE) and the DBN model can obtain higher accuracy rates of fault diagnosis for axial movement of harmonic drives, which can be greater than or equal to 97% based on the data of the performed experiment.

The authors propose two fault diagnosis methods based on the current signal of the driving servomotor for the axial movement failure in terms of input shafts of harmonic drives, which are verified by the experiment. The presented study may be beneficial for the development of self-diagnosis and self-repair systems of different robots and precision machines using harmonic drives.

Sustainability has been on the executive agenda for years and it is now one of the fastest growing supply chain management trends. The purpose of this paper is to analyze the barriers for the adoption and implementation of the sustainable supply chain management (SSCM) concept.

This study has been divided into two phases such as identification of barriers and qualitative analysis. First, to identify the most influential barriers, the authors offer a systematic literature review, taking 188 papers published from 2010 to November 2016 into account. The investigation phase led to the selection of 15 barriers based on the literature in consultation with industrial experts and academicians. Second, the interpretive structural modeling qualitative analysis was used to find out the mutual influences between the 15 barriers by a survey.

Further, the authors propose and illustrate the cross-impact matrix multiplication applied to classification analysis to test a framework that extrapolates SSCM barriers and their relationships. “Inadequate information technology implementation” has been identified as the most important barrier that may force organizations to implement SSCM practices to ensure their business sustainability.

The authors presented some limitations in their research in some fields which could allow new researchers and practitioners to conduct the future research to grow in different dimensions.

Practitioners or policymakers usually are not familiar with these types of research works; that is why most of these surveys remain theoretical and conceptual. Future investigation needs to be done in practical application domain instead of merely giving opinions.

Based on the authors’ research, the researchers have more attention to work in conceptual analysis due to other fields, but the authors believe that even with the implementation of SSCM, many remarkable areas still exist for future research which could help in development. The authors also provide more details in this paper.

This paper aims to examine how presence (the social presence of live streaming platforms, of viewers, of live streamers and telepresence) affects consumer trust and flow state, thus inducing impulsive buying behaviors, personal sense of power as moderator.

Drawing on the Stimulus-Organism-Response (S-O-R) framework, the conceptual model covers social presence, telepresence, consumer trust, flow state, personal sense of power and impulsive buying behavior. An online survey was conducted from 405 consumers with the experience of live streaming shopping in China; structural equation modeling (SEM) was used for data analysis.

Results find that three dimensions of social presence (the social presence of live streaming platforms, of viewers, of live streamers) and telepresence have a positive and significant influence on consumer trust and flow state, thus triggering consumers’ impulsive buying behavior. Furthermore, consumers’ sense of power moderates the process from consumer trust, flow state to impulsive buying behavior.

This study will help live streamers and e-retailers to have a further understand on how to stimulate consumers’ buying behavior. Furthermore, it also provides reference for the development of live streaming commerce in other countries.

This research examines the effect of social presence and telepresence on impulsive buying behavior in live streaming commerce, which is inadequately examined in extant literature.

The last few years have witnessed massive artificial intelligence (AI) and gaming adoption that has navigated the emerging markets. Moreover, according to the WOG summit (world government summit report, by Nielsen) 2020 reports, AI with gaming mechanisms are expected to enrich marketing services in the coming future in the emerging markets. Countries such as India, China and South Korea contribute significantly to this area, and recent forecasting allows the need to increase in emerging markets. Similarly, these countries have a maximum number of youth gamers and AI-driven technology adopters. The adoption of AI-driven technologies and amplification of gamification in marketing services are new phenomena. Moreover, gaming and AI dynamics are relatively new in emerging countries and need greater attention. Thus, this book chapter proposes a dyad model that would explain users' and companies' perspectives to understand the role of AI and gamification for the emerging markets. The chapter will explain how AI-driven gamification helps the users of emerging markets. The chapter will also illustrate how companies in emerging markets use AI for gamification. Therefore, the dyad model would also comprehend the gap, opportunities and challenges in this area and the subsequent strategies to help all the stakeholders.

The purpose of this paper is to provide a critical historical analysis of the business (mis)behaviors and influencing factors that discourage enduring cooperation between principals and agents, to introduce strategies that embrace the social values, economic motivation and institutional designs historically adopted to curtail dishonest acts in international business and to inform an improved principal–agent theory that reflects principal–agent reciprocity as shaped by social, political, cultural, economic, strategic and ideological forces

The critical historical research method is used to analyze Chinese compradors and the foreign companies they served in pre-1949 China.

Business practitioners can extend orthodox principal–agent theory by scrutinizing the complex interactions between local agents and foreign companies. Instead of agents pursuing their economic interests exclusively, as posited by principal–agent theory, they also may pursue principal-shared interests (as suggested by stewardship theory) because of social norms and cultural values that can affect business-related choices and the social bonds built between principals and agents.

The behaviors of compradors and foreign companies in pre-1949 China suggest international business practices for shaping social bonds between principals and agents and foreign principals’ creative efforts to enhance shared interests with local agents.

Understanding principal–agent theory’s limitations can help international management scholars and practitioners mitigate transaction partners’ dishonest acts.

A critical historical analysis of intermediary businesspeople’s (mis)behavior in pre-1949 (1840–1949) China can inform the generalizability of principal–agent theory and contemporary business strategies for minimizing agents’ dishonest acts.