Political identity is of special significance to the political construction and social development of contemporary China. Returnee lecturers are an important part of the university teaching team and an important force in training socialist builders with Chinese characteristics. An empirical survey was conducted on 35 returnee lecturers in universities in Jinhua area by means of questionnaires and interviews. The results show that the political identity of the returnee lecturers is generally good, but there are some problems, such as political party identity, national identity, institutional identity and interest identity need to be improved. As a result, factors such as gender, political profile and length of stay abroad have a significant effect on the political identity of returnee lecturers. The paper concludes with some initiatives, such as strengthening ideological and political education, improving remuneration and promoting career development.

Under the developing trend of artificial intelligence (AI) technology gradually penetrating all aspects of society, the traditional language education industry is also greatly affected ^[1]. AI technology has had a positive impact on college English teaching, but it also presents challenges and negative impacts. On the positive side, AI technology can provide personalized learning experiences, real-time feedback, and autonomous learning opportunities, and so on. However, it may also lead to a lack of communication between students and humans, resulting in a decline in students’ interpersonal skills, and cause students’ dependence on online learning resources as well as possible risks to student data privacy and security, and other negative impacts. To address these challenges, teachers can adopt the following countermeasures: improving teachers’ skills in the use of AI technology incorporated in the classroom, offering personalized instruction to reduce students’ dependence on AI technologies, emphasizing the cultivation of students’ humanistic literacy and interpersonal communication ability. Additionally, colleges and technology providers should strengthen data security and privacy protection to ensure the safety and confidentiality of student data. By implementing comprehensive measures, we can maximize the advantages of AI technology in college English teaching while overcoming potential issues and challenges.

Purpose: This study empirically investigates the effect of big data analytics (BDA) on project success (PS). Additionally, in this study, the investigation includes an examination of how intellectual capital (IC) and (KS) act as mediators in the correlation between BDA and KS. Lastly, a connection between entrepreneurial leadership (EL) and BDA is also explored. Design/Methodology- Using a sample of 422 senior-level employees from the IT sector in Peru. The partial least squares structural equation modeling technique tested the hypothesized relationships. Findings- According to the findings, the relationship between BDA and PS is mediated by structural capital (SC) and relational capital (RC), and BDA demonstrates a positive and noteworthy correlation with PS. Furthermore, EL is positively associated with BDA in a significant manner. Practical implications- The finding of this study reinforce the corporate experience of BDA and suggest how senior levels of the IT sector can promote SC, RC, and EL. Originality/Value- This study is one of the first to consider big data analytics as an important antecedent of project success. With little or no research on the interrelationship of big data analytics, intellectual capital and knowledge sharing the study contributes by investigating the mediating role of intellectual capital and knowledge sharing on the relationship between big data analytics and project success.

Google Earth images in the Marche Region of Central Italy revealed a circular structure consisting of a ring system made up of concentric hills and valleys. Cartography, DEM, geological, and available geophysical data were used to constrain the possible origin of the structure. Located in the Messinian foredeep deposits of the Central Apennines, it has a rim diameter of 3.75 km and a central uplift connected to its southernmost part. As it was formed in the clays of the Lower Pliocene, and clays are believed to have emerged definitively after the Upper Pliocene, its age might be constrained to the Lower Pleistocene. Similar concentric structures are usually found in impact craters, sedimentary domes, and volcanic landforms. As salt domes and magmatic activity are not found in this region, this study seeks to validate the results of previous work that it was the result of an ancient impact crater of hydrological, brachyanticline, or clayey diapiric origins. Specifically, an observed second ring portion with a curvature radius about double the first in size will be investigated in this work. This second ring portion appears to be concentric to the first one and is visible along its northern and western parts. Although double concentric rings are usually due to impact craters, the absence of the ring portion in the other two directions and the probable deviation of a river, deduced by studying hydrography, support the hypothesis that it might be of clay diapir origin.

In light of the metaverse’s vast expansion, it’s a crucial intellectual platform that’s transforming the video game industry and spurring creative innovation and technological advancement. Considering the distinctive niche that Taiwan occupies within the realm of the video game industry, this study uses a total of 11 video game companies in Taiwan as samples. The study spans a period of 16 years, from 2007 to 2022, and utilizes the random effect regression model for analysis. The study results illustrate that intellectual capital efficiency exerts varying contributions to the creation of value across different corporate value indicators within the video game industry. Among the factors, HCE, SCE, and CEE demonstrate the highest explanatory power for ROE, reaching up to 82.23%. Following this, they account for 73.57% of the variance in market share, but only a meager 13.67% for Tobin’s Q. This study is the empirical evidence that different methods of measuring intellectual capital and various definitions of value creation in an industry may lead to divergent results and managerial implications in intellectual capital research. Hence, it is worthwhile for subsequent studies to continue clarifying and delving deeper into these aspects.

This study explores the experiences and perceptions of Chinese postgraduate students in the UK regarding online learning, focusing on the Community of Inquiry (CoI) framework. Semi-structured interviews were used to collect qualitative data, which were analyzed thematically. The findings reveal positive perceptions of online learning, challenges related to technology and infrastructure, the significance of social interaction and collaboration, and the limited impact of teaching quality on student satisfaction. The study emphasizes the importance of the CoI framework in designing effective online learning environments. Limitations include a small sample size and potential bias. Future research should involve larger and more diverse samples, investigate different teaching strategies, and enhance student agency and self-regulated learning in online education. Overall, this study contributes to understanding the applicability of the CoI framework and its potential for improving online learning experiences.