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With the continuous growth of online education, the quality issue of online educational videos has become increasingly prominent, causing students in online learning to face the dilemma of knowledge confusion. The existing mechanisms for controlling the quality of online educational videos suffer from subjectivity and low timeliness. Monitoring the quality of online educational videos involves analyzing metadata features and log data, which is an important aspect. With the development of artificial intelligence technology, deep learning techniques with strong predictive capabilities can provide new methods for predicting the quality of online educational videos, effectively overcoming the shortcomings of existing methods. The purpose of this study is to find a deep neural network that can model the dynamic and static features of the video itself, as well as the relationships between videos, to achieve dynamic monitoring of the quality of online educational videos.

The quality of a video cannot be directly measured. According to previous research, the authors use engagement to represent the level of video quality. Engagement is the normalized participation time, which represents the degree to which learners tend to participate in the video. Based on existing public data sets, this study designs an online educational video engagement prediction model based on dynamic graph neural networks (DGNNs). The model is trained based on the video’s static features and dynamic features generated after its release by constructing dynamic graph data. The model includes a spatiotemporal feature extraction layer composed of DGNNs, which can effectively extract the time and space features contained in the video's dynamic graph data. The trained model is used to predict the engagement level of learners with the video on day T after its release, thereby achieving dynamic monitoring of video quality.

Models with spatiotemporal feature extraction layers consisting of four types of DGNNs can accurately predict the engagement level of online educational videos. Of these, the model using the temporal graph convolutional neural network has the smallest prediction error. In dynamic graph construction, using cosine similarity and Euclidean distance functions with reasonable threshold settings can construct a structurally appropriate dynamic graph. In the training of this model, the amount of historical time series data used will affect the model’s predictive performance. The more historical time series data used, the smaller the prediction error of the trained model.

A limitation of this study is that not all video data in the data set was used to construct the dynamic graph due to memory constraints. In addition, the DGNNs used in the spatiotemporal feature extraction layer are relatively conventional.

In this study, the authors propose an online educational video engagement prediction model based on DGNNs, which can achieve the dynamic monitoring of video quality. The model can be applied as part of a video quality monitoring mechanism for various online educational resource platforms.

This study analyzes the causal effect of education on consumers' cognition and attitudes toward genetically modified (GM) foods.

The authors propose an analytical framework to clarify the role of education levels and education content in the formation of attitudes toward GM foods and utilize education reforms in China as natural experiments to test the theoretical predictions empirically. For education levels, the authors use Compulsory Education Law's implementation to construct the instrument variable. For education content, the authors utilize the revision of the biology textbook in the Eighth Curriculum Reform to implement staggered difference-in-difference estimation. The authors use two national household surveys, the China Genuine Progress indicator Survey (CGPiS) and the China Household Finance Survey (CHFS) of 2017, combined with provincial-level data of education reforms.

The education level, instrumented by the Compulsory Education Law's implementation, has an insignificant effect on consumers' cognition and attitudes toward GM foods, whereas the acquisition of formal education on genetic science, introduced by the Eighth Curriculum Reform, has a statistically significant and positive influence.

This is the first study to investigate the causal effects of education level and content on consumers' cognition and attitude toward GM foods using national representative data. It is also the first to evaluate the long-term effects of the biology textbook reform in China. The findings help open the black box of how education shapes people's preferences and attitudes and highlight the significance of formal biology education in formulating consumers' willingness to accept GM foods.

Three-dimensional (3D) food printing is an innovative technology used to customize food products through the integration of digital technology and food ingredients. The purpose of this study is to assess the current state of research in the field of 3D food printing, identify trending topics and identify promising future research directions.

This bibliometric review systematically evaluates the field of 3D food printing using data from published literature in the Web of Science database. After reference screening, 812 articles were included in the analysis.

The result reveals that research in 3D food printing primarily focuses on the optimization and characterization of mechanical and rheological properties of food inks and that post-printing processing, such as laser treatment, has emerged recently as an important consideration in 3D food printing. However, extant works lack animal and human studies that demonstrate the functionality of 3D-printed food.

This sophisticated bibliometric analysis uncovered the most studied current research topics and the leading figures in the area of 3D food printing, providing promising future research directions.

Ocean exploration is of importance and in great demand throughout the world. This results in a huge challenge in tribology in the marine environment. Moreover, polymeric materials with large molecules or macromolecules play an important role in marine equipment.

The tribological performance of sea-water-eroded polyether polyurethane (PU) was systematically studied by using a multi-specimen test machine for different durations from 0 to 60 days. Surface characterization technologies, such as scanning electric microscopy energy dispersive spectroscopy, were used to analyze the PU samples.

It can be found that the COF measured against 316 steel increases with the testing load because of the change of contact areas for the original PU samples. The effect of hydrodynamic lubrication and heat resulted in the decline of the COF with the increase in testing speed. The COF of PU sample immersed for 20 days was the lowest compared with other samples. With the immersion time increased to 60 days, the COF increased first and then decreased. The reduced COF of PU resulted in improved anti-wear performance of the PU sample.

These results enhanced the comprehension of the tribological performances of PU immersed in sea-water.

This paper aims to explore the impact of green finance on the heterogeneity of enterprise green technology innovation and the underlying mechanism between them.

Using the data of China's A-share listed enterprises from 2008 to 2020 and the fixed effect model, the authors empirically explore the relationship and mechanism between green finance and green technology innovation by constructing the green finance index while considering both the quality and quantity of innovation.

The study suggests that green finance is positively related to the quality and quantity of enterprise green technology innovation, while green finance is more effective in stimulating the quality of green technology innovation than quantity. In addition, alleviating financial mismatch and improving the quality of environmental information disclosure are core mechanisms during the process of green finance facilitating green technology innovation. Furthermore, green finance exerts a more positive effect on the quality and quantity of green technology innovation with large-size enterprises, heavily polluting industries and enterprises in the eastern region.

This paper enriches the literature on green finance and green technology innovation and provides practical significance for green finance implementation.

The present study aims to ascertain the relationships between subordinate moqi and leader behaviors, by primarily discussing how and when subordinate moqi is associated with leadership empowerment.

A self-report study was conducted by recruiting 334 employees from 13 firms. All concepts were rated on a seven-point Likert-type response scale. Linear regression analysis (conducted in MPLUS 7) was conducted to verify the hypotheses.

First, subordinate moqi showed positive association with empowerment. Second, trust-in-supervisor mediated the relationships between subordinate moqi and empowerment. Third, subordinates' power distance orientation (PDO) could moderate the subordinate moqi – leader empowerment relationship. When subordinates reported higher PDO, the relationships between subordinate moqi and empowerment were more robust; likewise, subordinate moqi would have more significantly indirectly impacted empowerment via trust-in-supervisor.

Though researchers have discussed the impacts of subordinate moqi on subordinates' outcomes, the impact of subordinate moqi on supervisors' attitudes or behaviors remains unclear. The relationships between subordinate moqi and supervisor empowerment behaviors are empirically ascertained by emphasizing the leader-subordinate dyadic process. The findings here suggested that subordinate moqi boosted subordinates' trust-in-supervisor, and moqi would also predict the behaviors of leader empowerment. This study extended the PDO literature by identifying the moderating role of PDO in the subordinate moqi – leader empowerment behavior relationship.

China has experienced a fast economic growth and shown a significant rise in income inequality in the past decades. During the same period, fluid milk consumption in urban areas has rapidly expanded. The objective of this paper is to analyze and simulate the influence of income distribution changes on fluid milk consumption of households in urban China.

This study applies an inverse hyperbolic sine (IHS) double-hurdle model to modeling at-home fluid milk consumption of households across different income strata based on a sample of 11,861 urban households in five provinces in China, and simulating the impact of changing income distribution, including five income growth patterns, on fluid milk consumption of total households as well as specific household groups.

The fluid milk consumption in urban China will continue to increase, with the unconditional income elasticity being 0.334 for the full sample and 0.347, 0.335 and 0.162 for the low-, middle-, and high-income groups, respectively. The simulation results show an evidence that, compared with distribution-neutral and disparity-enlarging income growth patterns, a rising income equality would lead to a more significant increase in fluid milk consumption. And the inequality-reducing income growth pattern has a larger impact on fluid milk consumption of households with seniors and no children, as well as households having no local urban household registration (hukou).

The government should strengthen the supply measures of fluid milk in urban areas, enlarge domestic dairy production, and diversify the sources of milk imports. It is also necessary to subsidize low-income families, especially households with seniors or households migrated from other areas without getting local urban hukou, which could simultaneously improve nutritional benefits and alleviate financial pressures.

A simulation considering the evolution of income distribution as well as different household groups is conducted. Widely distributed data with a large sample size and detailed demographic information are used. The problems of zero consumption and non-normal distribution are addressed by the IHS double-hurdle model.

The purpose of this study is to explain the rapid growth of urban residents' sugar consumption in China from the perspective of habit formation.

Using the provincial panel data of Chinese urban households from 1995 to 2012, this study uses the two-step System Generalized Moment Method (GMM) to test the habit formation effect on residents' sugar expenditure in urban China. We also use system GMM and the recursive estimated method to explore the changes of the habit formation coefficients in different years.

We find a significant habit formation effect on overall residents' sugar expenditure and different types of sugary foods expenditure. The habit formation effect on total residents' sugar expenditure and different types of sugary foods is decreasing over the years. The patterns of the changes of the habit formation effect on different types of sugar foods are slightly different.

Due to data limitations, we are not able to do household-level analysis and to examine the heterogeneity of the habit formation effect.

This is the first study that examines changes in the habit formation effect on residents' sugar expenditure in urban China. Our findings provide a reasonable explanation for the rapid growth of residents' sugar consumption in urban China. The result helps to formulate targeted policies for future interventions to control the growth of sugar consumption.

The purpose of this paper is to explore the effect of ZnO on the structure and properties of micro-arc oxidation (MAO) coating on rare earth magnesium alloy under large concentration gradient.

The macroscopic and microscopic morphology, thickness, surface roughness, chemical composition and structure of the coating were characterized by different characterization methods. The corrosion resistance of the film was studied by electrochemical and scanning Kelvin probe force microscopy. The results show that the addition of ZnO can significantly improve the compactness and corrosion resistance of the MAO coating, but the high concentration of ZnO will cause microcracks, which will reduce the corrosion resistance to a certain extent.

When the concentration of zinc oxide is 8 g/L, the compactness and corrosion resistance of the coating are the best, and the thickness of the coating is positively correlated with the concentration of ZnO.

Too high concentration of ZnO reduces the performance of MAO coating.

The MAO coating prepared by adding ZnO has good corrosion resistance. Combined with organic coatings, it can be applied in corrosive marine environments, such as ship parts and hulls. To a certain extent, it can reduce the economic loss caused by corrosion.

The effect of ZnO on the corrosion resistance of MAO coating in electrolyte solution was studied systematically, and the conclusion was new to the common knowledge.

The purpose of this paper is to conceptualize the indigenous concept of suzhi at individual and organizational levels, and identify its dimensions for human resource management (HRM) research and practice in China.

Based on a comprehensive review of suzhi literature, Chinese cultural and historical literature, as well as Western mainstream HRM research, a multidimensional suzhi framework is conceptualized.

As an indigenous expression, suzhi can be and has been adopted for Chinese HRM research and practice. As a multidimensional construct, one’s cognitive suzhi is jointly determined by corresponding moral suzhi, wenhua (knowledge-based) suzhi and zhuanye (professional) suzhi. Cognitive suzhi, in turn, determines one’s behavioral suzhi that drives employees to enhance organizational performance, and this relationship is moderated by psychological suzhi.

The proposed framework provides new insight for Chinese indigenous management research, particularly in developing suzhi measurement for different dimensions. It also informs HRM practices in recruiting, selection, performance analysis and employee career development.

The complexity of suzhi dimensions from an organizational HRM perspective is analyzed. The resulting suzhi framework offers new insight for HRM research and practices in China.