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The purpose of this paper is to propose a new tool for stock investment risk management through studying stocks with what kind of characteristics can be predicted by individual investor behavior.

Based on comment data of individual stock from the Snowball, a thermal optimal path method is employed to analyze the lead–lag relationship between investor attention (IA) and the stock price. And machine learning algorithms, including SVM and BP neural network, are used to predict the prices of certain kind of stock.

It turns out that the lead–lag relationships between IA and the stock price change dynamically. Forecasting based on investor behavior is more accurate only when the IA of the stock is stably leading its price change most of the time.

One limitation of this paper is that it studies China’s stock market only; however, different conclusions could be drawn for other financial markets or mature stock markets.

As for the implications, the new tool could improve the prediction accuracy of the model, thus have practical significance for stock selection and dynamic portfolio management.

This paper is one of the first few research works that introduce individual investor data into portfolio risk management. The new tool put forward in this study can capture the dynamic interplay between IA and stock price change, which help investors identify and control the risk of their portfolios.

The carbon/carbon (C/C) composite finger seal experiment was performed on a high-speed seal tester. The purpose of this paper is to investigate the leakage and wear characteristics of C/C composite finger seal under various operating conditions.

Static, dynamic, endurance and post endurance tests were carried out. For static and performance tests, the pressure differential changed from 0.1 to 0.6 MPa and the rotor speed varied from 1,000 to 9,000 r/min. Two endurance tests were conducted for 4 h, with each mounting two finger seals. The seal leakage was monitored by mass flowmeters, and the wear depth was measured and calculated by using three-dimensional profilometer.

Results showed that the seal leakage increases with pressure differential but decreases with rotor speed. Leakage rate is lower when speed is decelerated than that with the speed stepped up. During a time history, material removal caused by wear has significant influence on leakage data causing higher leakage than the results before endurance test. Particular interest is that the uneven wear characteristic on finger foot bottom was firstly revealed, showing severe wear in foot heel area than that in foot toe.

This study could provide experimental guidance for finger seal designers. Additionally, the uneven wear characteristic of finger foot was firstly revealed, which showed the necessity of further theoretical research on finger seal wear.

This study quantitatively examines the relationship between economic fluctuations and government budget size in the context of China’s fiscal decentralization, drawing inspiration from theoretical predictions of the Keynesian view and empirical studies on other economies.

The panel comprises 31 provinces or equivalents in mainland China, spanning from 1994 to 2019. Diverse estimation strategies including two-way fixed effect regression, the generalized method of moments (GMM) and threshold regressions are, utilized.

The results suggest that under the “tax-assignment system”, neither the central government’s fiscal transfers nor the provincial budgetary revenues or expenditures help reduce economic volatility. Surprisingly, some regression outcomes suggest that government size measures destabilize business cycles.

While the study does not provide supportive evidence for the stabilizing effect of public budgets in Chinese provinces, it promotes a rethinking of the government’s intricate role in macroeconomic stabilization in the context of China’s fiscal decentralization.

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

To solve the above problems and ensure the stability of the ad hoc network node topology in the process of wireless signal transmission, this paper aims to design a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.

This paper designs a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.

The simulation results show that the amorphous flat wireless self-organizing network system has good nonlinear distortion fault-tolerant correction ability under the feedback control of the designed controller, and the system has the asymptotically stable convergence ability; the test results show: the node topology of the self-organizing network structural stability is significantly improved, which provides a foundation for the subsequent realization of long-distance transmission of ad hoc network nodes.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.

The controller can extract the fault information caused by nonlinear distortion in the wireless signal transmission process, and at the same time, its feedback matrix K can gradually converge the generated wireless signal error to zero, to realize the stable transmission of the wireless signal.

The purpose of this study is to explore how emotions felt by the public during a crisis influenced consumer loyalty intention and negative word-of-mouth (WOM). Considering the context-specific nature of emotions, the existing crisis emotions were further validated in a product consumption situation. Drawing on the theories of attribution and social sharing, a conceptual model, positing that crisis-specific emotions [attribution-independent, external-attribution-dependent (EAD) and internal-attribution-dependent (IAD) emotions] influenced negative WOM through behavioural intention, was constructed and empirically tested.

Data was collected from 240 Vietnamese consumers by using a scenario-based survey related to a fictional milk crisis.

The study findings showed that all but one crisis emotion had negative effects on both WOM and loyalty intention. Of these emotions, EAD and IAD were the strongest predictors of negative WOM and behavioural intention, respectively. It was also found that all crisis emotions significantly affected negative WOM through behavioural intention.

Although some efforts have been made to identify crisis emotions, the validity of the existing scales have not been affirmed in other crises related to product consumption situations. The results of the present study, thus, made contributions by enhancing an understanding of crisis emotions and their impacts on consumer loyalty intention and WOM communications.

The present article presents a first‐look into the hired‐labor market in Chinese household farms using data from a national household survey conducted by the Research Center for the Rural Economy (RCRE) at China's Ministry of Agriculture. More specifically, the purpose of this paper is to evaluate the scale and dispersion of China's farm‐household hired laborers among 15 commodities, and test whether market factors influence labor‐hiring decisions – an expectation of a well‐functioning labor market. This research contributes to the literature concerned with the labor constraints facing Chinese household farms, especially those producing seasonal commodities.

An econometric approach is employed to assess whether Chinese farms that hire labor are responding to market factors using two repeated cross‐sections (2006, 2007) of household survey data collected by the Research Center for Rural Economy at China's Ministry of Agriculture.

The paper finds hired labor use on very small‐scale farms is surprisingly prevalent, in contrast to previously published data. The regression results suggest that labor hiring by Chinese farm households, irrespective of farm size, responds strongly to market signals and resource constraints – more labor will be hired when the wage is lower, when output is higher, and among families with fewer family members available to farm work. And the response is particularly robust for wheat, rice, and maize, whose prices are predominant determinants of the food price index.

This paper is limited in its time‐series dimension and data availability. Despite those limitations, the results hold implications for further understanding China's nascent labor market and the level to which market factors have impacted rural farm households.

Focusing on the as‐of‐yet unstudied market for hired labor on Chinese household farms, the present article makes a contribution by showing that hiring of labor in Chinese agriculture is much more prevalent than previously thought. It suggests that Chinese farm‐households are responding to certain labor‐market factors and that the household response does not weaken as the largest farms are omitted from the model, suggesting that even small farms are heeding market signals.

In order to effectively promote the deep integration of artificial intelligence and the real economy and empower real enterprises to improve quality and efficiency, this study regards the CEO as a high-end innovation resource and aims to empirically test the impact of scholar-type CEOs on the industrial artificial intelligence (AI) transformation of manufacturing enterprises.

Grounded on the upper echelons theory, this paper preliminarily selects A-share manufacturing listed companies in Shanghai Stock Exchange and Shenzhen Stock Exchange that are affiliated to enterprise groups from 2014 to 2020 as samples. Furthermore, the Logit regression is conducted to analyze the influence of scholar-type CEOs about industrial AI transformation.

The results show that scholar-type CEO plays a significant role in promoting industrial AI transformation. The parent-subsidiary corporations executives' ties positively moderates the impact of scholar-type CEOs on industrial AI transformation. Further, internal control quality plays a partial mediating role between scholar-type CEOs and industrial AI transformation. Compared with private enterprises, scholar-type CEOs play a stronger role in promoting industrial AI transformation of state-owned enterprises.

First, this paper expands the research related to the influencing factors of industrial AI transformation based on upper echelons theory and clarifies the influencing mechanism of scholar-type CEOs affecting industrial AI transformation from the perspective of executives' behavior. Second, this study further enriches the research framework on the economic consequences of scholar-type CEOs and provides a useful supplement to the research literature in the field of upper echelons theory. Third, this paper is not limited to a single enterprise but involves the management practice of resource allocation within the enterprise groups, further clarifies the internal logic of the decision-making of industrial AI transformation of listed companies within the framework of enterprise groups, providing theoretical reference for the scientific design of the governance mechanism of parent-subsidiary companies.

The purpose of this study is to develop a building information modelling (BIM)-based mixed reality (MR) application to enhance and facilitate the process of managing bridge inspection and maintenance works remotely from office. It aims to address the ineffective decision-making process on maintenance tasks from the conventional method which relies on documents and 2D drawings on visual inspection. This study targets two key issues: creating a BIM-based model for bridge inspection and maintenance; and developing this model in a MR platform based on Microsoft Hololens.

Literature review is conducted to determine the limitation of MR technology in the construction industry and identify the gaps of integration of BIM and MR for bridge inspection works. A new framework for a greater adoption of integrated BIM and Hololens is proposed. It consists of a bridge information model for inspection and a newly-developed Hololens application named “HoloBridge”. This application contains the functional modules that allow users to check and update the progress of inspection and maintenance. The application has been implemented for an existing bridge in South Korea as the case study.

The results from pilot implementation show that the inspection information management can be enhanced because the inspection database can be systematically captured, stored and managed through BIM-based models. The inspection information in MR environment has been improved in interpretation, visualization and visual interpretation of 3D models because of intuitively interactive in real-time simulation.

The proposed framework through “HoloBridge” application explores the potential of integrating BIM and MR technology by using Hololens. It provides new possibilities for remote inspection of bridge conditions.