X Gu

The green development level reflected in the green finance index and the evaluation of the degree of green development in smart cities have important practical effects on economic transformation. For promoting the transformation and upgrading of finance, we select 2013–2019 data and construct a distributed lag model to analyse the important role played by green finance and financial technology in the construction of smart cities. In the paper, we find green finance promotes the construction of smart cities, and only it will not appear until nine months late. Financial technology has an opposite impact on the construction of smart cities, this is mainly because the research and marketization of financial technology are higher, and the cost is also higher. This influence will appear in the next 14 months.

ABSTRACT This paper draws upon transitivity and Appraisal within Systemic Functional Linguistics to study the traumatic discourse of Nanjing Massacre in Chinese Mainland’s and Japan’s history textbooks. Through corpus analysis, this research finds that the Chinese discourse mainly uses effective process, relational process, verbal process to construe Japan’s victimizering experience and China’s victimhood, and employs negative Affect, opposite values of Judgment, negative Appreciation, Expand, Raise and Sharpen to construct a critical voice for the Japanese army and a sympathic tone for the Chinese. By contrast, the Japanese discourse largely uses pseudo-effective and middle processes, mental and existential processes to cover up Japan’s victimizering experience, and employs negative Judgment, positive Appreciation, Contract and Raise to construct an almost uncritical voice for the Japanese army and the massacre. The difference in the representation and evaluation of Nanjing Massacre results from the politics of official memories in both countries. As China endeavors to strengthen its patriotic education by using Nanjing Massacre as an ideological weapon for national solidarity, Japan expedites its nationalist historiography move to recreate its normal national image by marginalizing the massacre.

During the COVID-19 pandemic, online education has become an important approach to learning in the information era and an important research topic in the field of educational technology as well as that of education in general. Teacher–student interaction in online education is an important factor affecting students’ learning performance. This study employed a questionnaire survey to explore the influence of teacher–student interaction on learning effects in online education as well as the mediating role of psychological atmosphere and learning engagement. The study involved 398 college students studying at Chinese universities as the research object. Participants filled out a self-report questionnaire. The study found that the level of teacher–student interaction positively affected students’ learning effects. The psychological atmosphere mediated the positive effect of the level of teacher–student interaction on learning effects with mediating effect value of 0.1248. Learning engagement mediated the positive effect of teacher–student interaction on learning effects with a mediating effect value of 0.1539. The psychological atmosphere and learning engagement play a chain-mediating role in the mechanism of teacher–student interaction affecting students’ learning effects; that is, teacher–student interaction promotes students’ learning engagement by creating a good psychological atmosphere, which, in turn, influences learning effects. The mediating effect value was 0.0403. The results indicate that teacher–student interaction not only directly affects students’ learning effects but also influences students’ learning effects through the mediating effect of the psychological atmosphere and learning engagement.

Based on in-depth interview data and popular culture texts, the current study has explored the politics of reproduction revolving around women’s age in contemporary China. Conceptualizing reproduction as a site of contestation and politics between different, and often contradictory, sets of discourses and power structures, I pursue a feminist and social constructivist analysis of the politics of reproduction in the lives of a group of urban professional women who are yet to enter motherhood at their late 20s and 30s. I engage with Inhorn’s concept of ‘disrupted reproduction’ to highlight the politically, morally and emotionally charged contestations in the ‘problematized’ reproductive lives of these women. I unveil how Chinese professional women beyond their ‘reproductive prime’ are discursively constructed as ‘disrupters’, who fail their femininity test tied to a motherhood identity within the family context, challenge the ‘natural’ biological law regulating their reproductive bodies, and face a doomed reproductive future fraught with medical, physical and emotional traumas which ART cannot alleviate. Such a discourse renders invisible the structural causes of problems and challenges professional women face in negotiating parenthood, social norms and selfhood, which systematically put them under pervasive social surveillance and discipline.

With the development of artificial intelligence, it is imperative to combine design methods with new technologies. From the perspective of the personalized design of derived images of art paintings, this study analyzes the new user demand generated by the current situation and background of personalized design, puts forward a new method of derivative design based on AI emotion analysis, verifies the feasibility of the new method by constructing a personalized design system of derived images of art paintings driven by facial emotion features, and explores the method of combining AI emotion recognition, emotion analysis, and personalized design. This study provides new ideas for the design of art derivatives for the future with massive personalized demand. Thinking and practicing from the perspective of the development of new technology will promote the change of design paradigms in the digital age.

To assist Chinese high school students in improving their career readiness and tackling career decision-making difficulties, we designed a synchronous online career intervention based on the Cognitive Information Processing theory during the Covid-19 pandemic. The online career intervention consisted of a series of career courses to develop high school students’ knowledge and skills in career planning, career assessments for exploring their vocational interests and academic self-concept, and a database providing basic information about university majors. To evaluate the intervention’s effectiveness, 957 10th grade students were recruited in the study, 601 participants were randomly assigned to the experimental group, and 356 participants were randomly assigned to the control group. All participants completed a pre- and post-intervention assessment of their career maturity, vocational identity and career decision-making difficulties. Results indicated that the online intervention significantly increased high school students’ career readiness and reduced their career decision-making difficulties. The practical implications of this research for online career interventions directed at Chinese high school students are also discussed.

Network ranging and clock synchronization based on two-way timing stamps exchange mechanism in complex GPS-denied environments is addressed in this paper. An estimator based on the Extended Kalman filter is derived, according to which, the clock skew, clock offset, and ranging information can be jointly estimated. The proposed estimator provides off-line computation by storing the transmitting timing stamps in advance and could be implemented in asymmetrical and asynchronous scenarios. The simulation results show that the proposed estimator achieves a relative good performance than the existed estimators. In addition, a new Bayesian Cramér–Rao Lower Bound is derived. Numerous simulation results show that the proposed estimator meets the B-CRLB.

The impact of industrial peers' donations on firms' charitable practices has been tested and verified in existing literatures. This paper further studies the motivations and scenarios of non-listed companies to imitate their listed counterparts in the same industry to formulate charitable policies. Deeply rooted in institutional isomorphism theory, uncertainty and professional networks are employed as philanthropic motives for unlisted companies to mimic their listed peers. Managerial decision mechanisms and network status perceptions enhance imitation by reinforcing decision uncertainty and network effect. Institutional environment heterogeneity can amplify or reduce the imitative stimulus of managers' decision mechanisms and status perceptions. Our empirical tests are based on a unique dataset of 14,873 unlisted firms and their corresponding listed counterparts in China from 2006–2016, and use Tobit regression methods. The results show a significantly positive association between listed peers' giving and non-listed firms' donation. The peer effects are intensified when non-listed firms' decentralized decision-making and higher managers' status identification are present. Furthermore, when the institutional environment changes from weak to strong, the impetus of decentralized decision-making and status identification will be weakened. These findings contribute to the corporate philanthropy literature and facilitate the development of effective corporate charity policies and government promotion of philanthropic responsibility.

At present, there are more and more frauds in the financial field. The detection and prevention of financial frauds are of great significance for regulating and maintaining a reasonable financial order. Deep learning algorithms are widely used because of their high recognition rate, good robustness, and strong implementation. Therefore, in the context of e-commerce big data, this paper proposes a quantitative detection algorithm for financial fraud based on deep learning. First, the encoders are used to extract the features of the behaviour. At the same time, in order to reduce the computational complexity, the feature extraction is restricted to the space-time volume of the dense trajectory. Second, the neural network model is used to transform features into behavioural visual word representations, and feature fusion is performed using weighted correlation methods to improve feature classification capabilities. Finally, sparse reconstruction errors are used to judge and detect financial fraud. This method builds a deep neural network model with multiple hidden layers, learns the characteristic expression of the data, and fully depicts the rich internal information of the data, thereby improving the accuracy of financial fraud detection. Experimental results show that this method can effectively learn the essential characteristics of the data, and significantly improve the detection rate of fraud detection algorithms.

Translation equivalents for cognates in different script systems share the same meaning and phonological similarity but are different orthographically. Event-related potentials were recorded during the visual recognition of cross-script cognates and non-cognates together with concreteness factors while Chinese learners of English performed a lexical decision task with the masked translation priming paradigm in Experiment 1 and Experiment 2. N400 effect was found to be closely related to priming effects of cross-script cognate status and concreteness in Experiment 1; and in Experiment 2, N150 and N400 effects were related to priming effects of cross-script cognate status and concreteness, and greater priming effects of cross-script cognate status in cognates than in non-cognates for abstract words were found in the time window of 100–200 ms. Meanwhile, the asymmetry of translation directions was observed in smaller priming effects in forward translation than in backward translation in the time window of 100–200 ms for abstract cognates, and in larger priming effects in forward translation than in backward translation in the time window of 350–550 ms for each type of words. We discussed the roles of phonological activation and concreteness effects in view of the function of N150 and N400 components as well as the relevant models, mainly the Distributed Feature Model and Bilingual Interactive Activation model.

There has long been a substantial asymmetry with regard to usage and salience of globalization, globalism, and globality. This applies in particular to globality, both in public and academic discourses. Consequently, it remains necessary to determine more systematically what constitutes globality and to address the much neglected question of whether and to what extent globality can be shaped. To these ends, this contribution elaborates distinctive characters of globality as conditions of spatial expansion across the globe, which can pertain to ideas, products, or institutions among other things. Moreover, it demonstrates how globality amounts to results of human action that can take countless forms over space and time. As such, the particular qualities of globality, including its basic reference to space, human centeredness, as well as its complex relationship to power and structures, become evident, revealing the shaping power and potential of globality.