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Corrosion is considered as one of the issues that threaten the safe operation of steam generator (SG) tubing. Some sulfur-related specie can cause corrosion degradation of SG tubing. Sulfur-induced corrosion of SG alloys in high temperature and high-pressure water is one of the most complicated processes. The purpose of this study is to study the effect of reduced sulphur on passive film properties of steam generator (SG) tubing.

In this paper, the effects of reduced sulfur on passive film properties of SG tubing were reviewed from the aspects of thermodynamic calculations and experimental.

Thermodynamic calculations are mainly presented by E-pH diagrams, volt equivalent diagrams and species distribution curves. The stability of sulphur species highly depends on temperature, solution pH, and electrochemical potential. Experimental data indicated that reduced sulfur species can interact with the passive film, which led to changes in film thickness, film structure, semiconductivity and pitting growth rate.

The state-of-the-art discussed in this paper gives basis for resolving engineering problems regarding with sulfur-induced corrosion.

This paper aims to evaluate the sulfide stress cracking (SSC) resistance of L80 casing steels with different alloying chemistries (e.g. Ti-B and Mn-Cr-Mo) by correlating the reduction in area ratio with the mechanical property, inclusion and carbide.

SSC tests were conducted in 5.0 Wt.% sodium chloride and 0.5 Wt.% acetic acid solution saturated with H₂S using constant load tensile method. The microstructure and fracture morphology of the steel were observed using scanning electron microscope. The inclusion and carbide were identified by energy dispersive spectroscopy and auger electron microscope.

Among all the testing steels, electric resistance welding (ERW) L80-0.5Mo steel demonstrates the highest SSC resistance because of its appropriate mechanical properties, uniform microstructure and low inclusion content. The SSC resistance of L80 steels generally decreases with the rising yield strength. The fracture mode of steel with low SSC resistance is jointly dominated by transgranular and intergranular cracking, whereas that with high SSC resistance is mainly transgranular cracking. SSC is more sensitive to inclusions than carbides because the cracks are easier to be initiated from the elongated inclusions and oversized oxide inclusions, especially the inclusion clusters. Unlike the elongated carbide, globular carbide in the steel can reduce the negative effect on the SSC resistance. Especially, a uniform microstructure with fine globular carbides favors a significant improvement in SSC resistance through precluding the cracking propagation.

The paper provides the new insights into the improvement in SSC resistance of L80 casing steel for its application in H₂S environment through optimizing its alloying compositions and microstructure.

The purpose of this study is to extend the classic country-specific advantage (CSA) – firm-specific advantage (FSA) framework by integrating an institution-based view of CSAs into the discussion of FSAs. In his classic CSA – FSA framework, Rugman suggests that successful multi-national enterprises (MNEs) are often built on the interaction between strong FSAs and strong CSAs at home. In the case of emerging market multi-nationals (EMNEs), he argued that strong CSAs were of particular importance in allowing EMNEs to develop FSAs. In particular, we examine CSAs at the sub-national level.

The authors suggest that sub-national heterogeneity in market-supporting institutions is an important feature of emerging market economies, and that consideration of such heterogeneity contributes to our understanding of firm capabilities and overseas investment behavior of emerging market firms. The authors also identify explicitly the mechanisms through which sub-national institutions at home affect FSAs and, subsequently, the ability of emerging market firms’ entry into developed markets. Specifically, the authors argue that strong local institutions that support effective and well-functioning markets create the conditions that induce firms in that location to develop market-related capabilities in R & D and marketing, which, in turn, enable them to expand into developed countries.

Using a unique data set on overseas investment by Chinese firms and causal mediation analysis, the authors find strong evidence in support of the view that strong sub-national institutions help emerging market firms develop the capabilities to enter developed country markets.

This study extends the classic CSA–FSA framework by integrating an institution-based view of CSAs into the discussion of FSAs. In particular, the authors examine CSAs at the sub-national level.

The purpose of this study is to reduce the use of Zinc dialkyl dithiophosphates (ZDDP) and improve the frictional properties and thermal oxidation stability of Perfluoropolyether (PFPE) grease by adding antioxidant additives. The addition of antioxidants can reduce the consumption of ZDDP as an antioxidant, thus improving the anti-wear efficiency of ZDDP and reducing the excess phosphorus element in the grease.

In this study, an antioxidant with good comprehensive performance was selected from several antioxidants by tribological tests and high-temperature tests. Then, the effect of its combination additive with ZDDP on PFPE grease was investigated. The anti-wear property, anti-friction property, thermal oxidation stability and extreme pressure property of greases containing different proportions of ZDDP and antioxidant were tested by four-ball tester and synchronous thermal analyzer (STA). The effects of additives on properties of grease were analyzed by SEM, EDS, LSCM, XPS and FT-IR.

The research shows that 2,6-Di-tert-butyl-4-methylphenol (BHT) can be used as an antioxidant in combined additives to reduce the antioxidant reactions of ZDDP, thus improving the anti-wear efficiency of ZDDP and further enhancing the anti-wear performance of the grease. Moreover, BHT and ZDDP have a synergistic effect on the high temperature performance of the PFPE grease due to their different antioxidant mechanisms.

In this paper, the problems related to PFPE grease are studied, which has a certain guiding effect on the industrial application of fluorine grease and the related formulation design.

In this paper, the properties of PFPE grease under different lubricating condition were studied. The synergistic lubrication effect of antioxidant and ZDDP are discussed. It provides experimental and theoretical support for reducing the content of ZDDP and improving the performance of additives.

The purpose of this paper is to explore the effects of online advertising spending on automobile sales through both search and non-search advertising.

Sales data of the top 52 vehicle models were collected in two consecutive years in China. The advertising spending data of both formats were collected from a leading consulting company and a major search engine company. Then several empirical models were proposed to evaluate the effects of online advertising on automobile sales. Two extended models were further investigated for search advertising.

The results revealed that both formats of online advertising have significantly positive effects on automobile sales. However, excessive spending on non-search advertising does not help sales and a moderate budget is preferred. On the other hand, spending on search advertising has no such constraint to improve the vehicle sales.

The empirical findings have proved the importance of online advertising to the automobile companies and thus can help companies improve their decision making in online advertising allocation strategies.

This study provides a better understanding of the relationship between online advertising spending and automobile sales, and helps business to define sophisticated online advertising strategies to improve sales performance.

The development of low-carbon production is impeded by the investment costs of green technology research and development (R&D) and carbon emission reduction while facing the uncertain risk of emission reduction investment. With the government's carbon emission constraints, green manufacturers implement the advance selling strategy to increase both profit and reduction level. However, few studies consider the consumer's green preference and emission constraints in advance selling market and spot market independently. The authors' paper investigates the optimal strategies of advance selling pricing and reduction effort for green manufacturers to maximize profits.

The authors' paper designs a stochastic model and investigates the manufacturer's optimal strategies of advance selling price and emission reduction efforts by categorizing different purchasing periods of low-carbon consumers. With the challenges of uncertain demand and government's emission constraints, the authors' develop the non-linear optimization model to investigate the manufacturer's profit-oriented decisions.

The results show the government's carbon constraints cannot influence the manufacturer's profit, but the consumer's low-carbon preference in the advance selling period can. Interestingly, the manufacturer will make fewer reduction efforts even when the consumers have stronger environmental awareness. In addition, the increasing consumer price sensitivity will exacerbate the profit loss from mandatory emissions reduction. Overall, for achieving a win–win situation between emission reduction and profit growth, green manufacturers should not only consider the sales strategies, market demand, and government constraints in a low-carbon market, but also pay attention to the uncertainty of green technology innovation.

With the consideration of the government's carbon emission constraints, uncertain demand, and low-carbon consumer's preferences, the authors' study innovatively incorporates the joint impacts of advance selling strategy and emission reduction effort strategy and then differentiates between two cases that pertain to the diverse carbon emission regulations.

The aggregate index and per capita index have different meanings for some countries or regions. CO₂ emissions per capita matters for China because of its huge population. Therefore, this study aims to deepen the understanding of Kuznets curve from the perspective of CO₂ emissions per capita. In this study, mathematical formulas will be derived and verified.

First, this study verified the existing problems with the environmental Kuznets curve (EKC) through multiple regression. Second, this study developed a theoretical derivation with the Solow model and balanced growth and explained the underlying principles of the EKC’s shape. Finally, this study quantitatively analyzed the influencing factors.

The CO₂ emission per capita is related to the per capita GDP, nonfossil energy and total factor productivity (TFP). Empirical results support the EKC hypothesis. When the proportion of nonfossil and TFP increase by 1%, the per capita CO₂ decrease by 0.041 t and 1.79 t, respectively. The growth rate of CO₂ emissions per capita is determined by the difference between the growth rate of output per capita and the sum of efficiency and structural growth rates. To achieve the CO₂ emission intensity target and economic growth target, the growth rate of per capita CO₂ emissions must fall within the range of [−0.92%, 6.1%].

Inspired by the EKC and balanced growth, this study investigated the relationships between China’s environmental variables (empirical analysis) and developed a theoretical background (macro-theoretical derivation) through formula-based derivation, the results of which are universally valuable and provide policymakers with a newly integrated view of emission reduction and balanced development to address the challenges associated with climate change caused by energy.

This paper aims to focus on lane detection of unmanned mobile robots. For the mobile robot, it is undesirable to spend lots of time detecting the lane. So quickly detecting the lane in a complex environment such as poor illumination and shadows becomes a challenge.

A new learning framework based on an integration of extreme learning machine (ELM) and an inception structure named multiscale ELM is proposed, making full use of the advantages that ELM has faster convergence and convolutional neural network could extract local features in different scales. The proposed architecture is divided into two main components: self-taught feature extraction by ELM with the convolution layer and bottom-up information classification based on the feature constraint. To overcome the disadvantages of poor performance under complex conditions such as shadows and illumination, this paper mainly solves four problems: local features learning: replaced the fully connected layer, the convolutional layer is used to extract local features; feature extraction in different scales: the integration of ELM and inception structure improves the parameters learning speed, but it also achieves spatial interactivity in different scales; and the validity of the training database: a method how to find a training data set is proposed.

Experimental results on various data sets reveal that the proposed algorithm effectively improves performance under complex conditions. In the actual environment, experimental results tested by the robot platform named BIT-NAZA show that the proposed algorithm achieves better performance and reliability.

This research can provide a theoretical and engineering basis for lane detection on unmanned robots.

When it comes to the high accuracy autonomous motion of the mobile robot, it is challenging to effectively control the robot to follow the desired trajectory and transport the payload simultaneously, especially for the cloud robot system. In this paper, a flexible trajectory tracking control scheme is developed via iterative learning control to manage a distributed cloud robot (BIT-6NAZA) under the payload delivery scenarios.

Considering the relationship of six-wheeled independent steering in the BIT-6NAZA robot, an iterative learning controller is implemented for reliable trajectory tracking with the payload transportation. Meanwhile, the stability analysis of the system ensures the effective convergence of the algorithm.

Finally, to evaluate the developed method, some demonstrations, including the different motion models and tracking control, are presented both in simulation and experiment. It can achieve flexible tracking performance of the designed composite algorithm.

This paper provides a feasible method for the trajectory tracking control in the cloud robot system and simultaneously promotes the robot application in practical engineering.

The Chief Financial Officer (CFO), despite being a critical organization member responsible for ensuring quality of financial reporting, audit and compliance, is under-researched. Grouped as a member of top management teams (TMS) in studies, factors influencing decision making in this group rely on static measures of characteristics without regard for dynamic and longitudinal influences of career trajectories and industry occupational group memberships. The relationship between the high-tech industry as a site of notable reported internal control (IC) weakness and influences on CFOs requires closer examination. The paper aims to discuss these issues.

The study draws together the upper echelons theory and occupational communities (OCs) to explore the impact of shared values and behavioral norms from different sources on executive decision making. Internal and external sources of OC are proposed and their influence on activities with respect to corporate IC is tested. The sample of 1,573 firm/year observations includes high-tech firms listed on major US exchanges was developed using data from five distinct databases. Executives’ biographic information was manually collected.

Results indicate that senior financial executives belong not only to their firm and its culture but also to OCs that extend beyond the firm. Membership in professional credential granting occupational groups has less impact on effective IC than experience in the high-tech industry. In combination, multiple OCs show evidence of compound and counteracting effects on IC. The OC that arises in the high-tech industry makes a measurable positive difference in the quality of IC in sample firms, in contrast with the OC among credentialed accounting and financial professionals.

This quantitative study of OC reveals the differential impact of different sources of OC and contributes to the literature on TMS a new framework for examining decision making. OC is typically studied through qualitative methods and, thus, potential exists to further explore the specific nature and dynamics of the OCs identified in this study.

The study highlights the role of broad affiliations and networks among senior financial executives which may have bearing on their ability to effectively manage IC. The role of these networks may also partially explain instances of CFO failure and thus dismissal. Knowledge of the role of OC may help boards of directors in the selection and promotion of senior financial officers of the firm.

The paper offers a different perspective on professional accounting expertise in one specific industry where incidence of IC weakness is high relative to other industries. Study results expand recent research on TMS to include sociological impacts of cohort groups. Despite generally weaker IC in the high-tech sector, this study demonstrates the value of exploring group membership within the industry as an important predictor of behavior. The result is a new perspective to CFO decision making which illustrates the relevance of OCs among upper echelons. The implications of findings for CFO recruitment and promotion are borne out in recent instances of senior financial executive failure in the sector.