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Nowadays, the breakout of the COVID-19 pandemic has caused an important change in teaching models. The emotional experience of this change has an important impact on online teaching. This paper aims to explore its time evolution characteristics and provide reference for the development of online teaching in the post epidemic era.

The article firstly crawls the online teaching-related comment text data on Zhihu platform and performs emotional calculation to obtain a one-dimensional time series of daily average emotional values. Then, by using non-linear time-series analysis, this paper reconstructs the daily average emotion value time series in high-dimensional phase space, calculates the maximum Lyapunov exponent and correlation dimension and finally, explores the feature patterns through recurrence plot and recurrence quantification analysis.

It was found that the sequence has typical non-linear chaotic characteristics; its correlation dimension indicates that it contains obvious fractal characteristics; the public emotional evolution shows a cyclical rise and fall. By text mining and temporal evolution analysis, this paper explores the evolution law over chronically of the daily average emotion value time series, provides feasible strategies to improve students' online learning experience and quality and continuously optimizes this new teaching model in the era of pandemic.

Based on social knowledge sharing platform of Q&A, this paper models and analyzes users interaction data under online teaching-related topics. This paper explores the evolution law over a long time period of the daily average emotion value time series using text mining and temporal evolution analysis. It then offers workable solutions to enhance the quality and experience of students' online learning, and it continuously improves this new teaching model in the age of pandemics.

This study aims to investigate the rarefaction effects on flow and thermal performances of an equivalent sand-grain roughness model for aerodynamic thrust bearing.

In this study, a model of gas lubrication thrust bearing was established by modifying the wall roughness and considering rarefaction effect. The flow and lubrication characteristics of gas film were discussed based on the equivalent sand roughness model and rarefaction effect.

The boundary slip and the surface roughness effect lead to a decrease in gas film pressure and temperature, with a maximum decrease of 39.2% and 8.4%, respectively. The vortex effect present in the gas film is closely linked to the gas film’s pressure. Slip flow decreases the vortex effect, and an increase in roughness results in the development of slip flow. The increase of roughness leads to a decrease for the static and thermal characteristics.

This work uses the rarefaction effect and the equivalent sand roughness model to investigate the lubrication characteristics of gas thrust bearing. The results help to guide the selection of the surface roughness of rotor and bearing, so as to fully control the rarefaction effect and make use of it.

The purpose of this paper is to study and describe several biases in investment decision-making through the review of research articles in the area of behavioral finance. It also includes some of the analytical and foundational work and how this has progressed over the years to make behavioral finance an established and specific area of study. The study includes behavioral patterns of individual investors, institutional investors and financial advisors.

The research papers are analyzed on the basis of searching the keywords related to behavioral finance on various published journals, conference proceedings, working papers and some other published books. These papers are collected over a period of year’s right from the time when the most introductory paper was published (1979) that contributed this area a basic foundation till the most recent papers (2016). These articles are segregated into biases wise, year-wise, country-wise and author wise. All research tools that have been used by authors related to primary and secondary data have also been included into our table.

A new era of understanding of human emotions, behavior and sentiments has been started which was earlier dominated by the study of financial markets. Moreover, this area is not only attracting the, attention of academicians but also of the various corporates, financial intermediaries and entrepreneurs thus adding to its importance. The study is more inclined toward the study of individual and institutional investors and financial advisors’ investors but the behavior of intermediaries through which some of them invest should be focused upon, narrowing down population into various variables, targeting the expanding economies to reap some unexplained theories. This study has identified 17 different types of biases and also summarized in the form of tables.

The study is based on some of the most recent findings to have a quick overview of the latest work carried out in this area. So far very few extensive review papers have been published to highlight the research work in the area of behavioral finance. This study will be helpful for new researches in this field and to identify the areas where possible work can be done.

Practical implication of the research is that companies, policymakers and issuers of securities can watch out of investors’ interest before issuing securities into the market.

Under the Social Implication, investors can recognize several behavioral biases, take sound investment decisions and can also minimize their risk.

The essence of this paper is the identification of 17 types of biases and the literature related to them. The study is based on both, the literature on investment decisions and the biases in investment decision-making. Such study is less prevalent in the developing country like India. This paper does not only focus on the basic principles of behavioral finance but also explain some emerging concepts and theories of behavioral finance. Thus, the paper generates interest in the readers to find the solutions to minimize the effect of biases in decision-making.

The purpose of this paper is to investigate the effects of load and speed on the corrosive wear performance of Al coating in 3.5% NaCl solution, which provided an experimental reference for the anti-corrosion engineering on offshore platforms.

A layer of Al coating was prepared on S355 steel using an arc spraying. The corrosive wear test was carried out with CFT–1 type surface property tester. The effects of load and speed on the corrosive wear performance of Al coating were investigated and the wear mechanism was also discussed. The electrochemical tests were conducted using a CHI660E type electrochemical workstation, the anti-corrosion mechanism was analyzed.

The average coefficient of frictions (COFs) of Al coating under loads of 1.5, 2.5 and 3.5 N are 0.745, 0.847 and 0.423, the wear mechanism is abrasive wear. The average COFs of Al coating at the speeds of 200, 400 and 600 rpm are 0.745, 0.878 and 0.617, respectively, the wear mechanism at the speeds of 200 and 400 rpm are abrasive wear, while that at the speed of 600 rpm is abrasive wear and fatigue wear. The anti-corrosion mechanism is the isolation of Cl^– corrosion and cathodic protection of sacrificial anode.

This paper mainly studied corrosive wear and electrochemical corrosion performances of Al coating. This study hereby confirms that this manuscript is the original work and has not been published nor has it been submitted simultaneously elsewhere. This paper further confirms that all authors have checked the manuscript and have agreed to the submission.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

The purpose of this study is to seek to quantify how unique service resources and consumer habit affect e-service loyalty (e-loyalty) in a highly competitive market. This study is grounded on Chinese social networking service (SNS) industry. A resource-based view is introduced as an alternative perspective to understand building consumer loyalty in e-service contexts.

A research framework is developed by reviewing prior literature. An online survey is conducted to collect research data. Based on 221 valid responses, the research model is tested by using partial least squares path modeling technique.

The features of market environments affects the loyalty of consumers to e-service providers. Consumers become mercenary in highly competitive and low differentiation e-service markets like Chinese SNS industry. The interaction of satisfaction and switching cost affects loyalty. Satisfied consumers can be either loyal or not loyal to a service provider depending on their level of switching cost, but unsatisfied consumers will have no loyalty. In addition, users are loyal to a SNS partly because it is their habit to use the service. Our study suggests that relying on consumer satisfaction to build e-loyalty may be problematic and risky.

The study represents an attempt to introduce the resource-based view to e-loyalty research. The research highlights the importance of habit in building consumers’ e-service satisfaction and loyalty and contributes to new insights on the importance of industry environment in determining e-service satisfaction–loyalty relationship based on studying consumers in a highly competitive market.

This chapter aimed to find out which factors affected three Estonian case firms’ serial nonlinear internationalization before and during the Covid-19 pandemic. It also studied how these firms responded to the pandemic and what they learned from their previous business experience. It contributed to the literature on serial nonlinear internationalization and to studies on the (potential) impacts of Covid-19 on firms’ local and international activities by showing that these case firms exited and re-entered foreign markets and experienced considerable export fluctuations before 2020, during and after it. Thus, serial nonlinear internationalization should be perceived as something normal, and it can be expected to occur both during stable and unstable times: it does not only characterize economic crises, and it should not be seen as a failure sign. The pandemic affected the case firms’ internationalization considerably – for instance, via demand fluctuations and travel restrictions – but it also created some additional business opportunities: for example, by creating demand for some additional products and by increasing some customer groups’ interest for some existing products. These firms’ (international) business experience acquired before Covid-19 was also useful during the pandemic as they continued with some previous expansion activities. On the other hand, they also tried something new. As a result, all firms’ total turnover increased in 2020, and it might also increase in 2021, despite some problems in the first quarter.

The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.

This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.

The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.

This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

Studies on cross-culture marketing often focus on either localization or globalization strategies. Based on data from pre-communist China (1912–1949), product hybridization – defined as a process or strategy that generates symbols, designs, behaviors and cultural identities that blend local and global elements – emerges as a popular intermediate strategy worthy of further inquiry. After examining the mechanisms and processes underlying this strategy, a schema for classifying product hybridization strategies is developed and illustrated. The paper aims to discuss these issues.

Critical historical research method is applied to historical data and historical “traces” from pre-communist China’s corporate documents, memoirs, posters, advertisements, newspapers and secondhand sources.

Strategic interactions between domestic and foreign companies in pre-communist China fostered products and a city (Shanghai) containing Chinese and non-Chinese elements. Informed by historical traces and data from pre-communist China (1912-1949), a 2 × 2 classification schema relating company type (i.e. foreign or domestic) to values spectrum endpoint (i.e. domestic vs foreign) was formulated. This schema reflects the value of communication, negotiation and cultural (inter)penetration that accompanies cross-culture product flows.

Cross-culture marketing strategies meant to help companies satisfy diverse marketplace interests can induce a mélange of product design elements. Because product hybridization reflects reciprocity between domestic and foreign companies that embodies multiple interests and contrasting interpretations of product meanings, researchers should examine globalization and localization synergistically.

Strategies adopted by domestic and foreign companies in pre-communist China (1912–1949) can help contemporary companies design effective cross-culture marketing strategies in a global marketplace infused with competing meanings and interests.

Examining historical strategies adopted in pre-communist China (1912–1949) can inform contemporary marketers’ intuitions. Understanding product hybridization in global marketplaces can improve marketing efficiency.