This empirical study explores the influence of Hollywood product placements on cultural perceptions and teaching practices of preservice English teachers in higher education in China. Hollywood movies and TV series routinely use product placements as a tactic to blend commercial goals with compelling storylines, which could possibly influence the perceptions, and potential teaching practice of Chinese preservice English teachers. The purpose of this study is to determine the degree to which material culture in the form of product placement in Hollywood affects preservice English teachers’ image of America, and their future teaching practice, altering their expectations and goals as well as how they view the West. The study uses a quantitative study method by means of an online questionnaire (N = 497) and applies structural equation modelling to conduct data analysis. The results find notable significant relationships including those from food, architecture, transportation, and electronic devices to positive image of America, as well as architecture and transportation to potential teaching practice. The most prominent path is from image to teaching. However, certain relationships, including those from fashion to image and food to teaching, do not demonstrate statistical significance. These results contribute to the theoretical and practical understanding of how preservice English teachers see Hollywood’s material culture, and how it affects their perception and possible teaching methods. The findings also demonstrate how preservice teachers’ perceptions and educational approaches are shaped by Hollywood’s material culture in the form of product placement, while simultaneously emphasizing the significance of integration of media literacy and upholding their cultural identity amidst these influences.

The existing studies on the association between the built environment and health mainly concentrates on urban areas, while rural communities in China have a huge demand for a healthy built environment, and research in this area remains insufficient. There is a lack of research on the health impact of the built environment in rural communities in China, where there is a significant demand for advancements in the healthy built environment. Exploring the Influence of built environment satisfaction on self-rated health outcomes in New-type village communities has positive significance for advancing research on healthy village community. This paper selects four new-type village communities as typical cases, which are located in the far suburbs of Shanghai, China. A questionnaire survey was conducted on individual villagers, and 223 valid questionnaire samples were obtained. A PLS-SEM model was developed using survey data to examine how built environment satisfaction influences dwellers’ self-rated health while taking into account the mediating function of the perceived social environment. Moreover, multi-group analysis was performed based on age. The results show that built environment satisfaction indirectly influences residents self-rated health through its impact on perceived social environment. The research also discovered that the relationship between built environment satisfaction, social environment satisfaction and self-rated health is not influenced by age as a moderating factor. The research offers new insights for the planning and design of new-type village community from a health perspective.

Digitalization has recently gained significant relevance in the education field. The focus has been on its use and application, as well as on training teachers and students to become responsible, competent, and ethical users of technology. This is connected to the creation of policies and programs that promote online learning and interaction from basic to higher education. In this context, this study aims to analyze the scientific production related to digital citizenship through a bibliometric mapping of publications indexed in the Web of Science database. The goal is to identify the main research trends in this field. The results show a growth in the number of publications since 2016, mainly focusing on topics such as digital citizenship media, digital competences, higher education, teachers, students, adolescents, adults, competence, digital literacy, and citizenship education. The presence of a significant number of journals related to the field of education denotes a close relationship between this field and the topic of study. Also, it is revealing a higher concentration of research production in the United States and Europe, with Latin America being absent from this scenario. The study identifies an intellectual structure of the discipline, particularly regarding the most relevant authors, journals, and descriptors. These results are important for understanding the research practices inherent to the field, which projects digital citizenship as an emerging topic. The study concludes by proposing lines of interest for further research on the topic in education and other fields, as well as acknowledging the limitations found in the present article.

Creating a crop type map is a dominant yet complicated model to produce. This study aims to determine the best model to identify the wheat crop in the Haridwar district, Uttarakhand, India, by presenting a novel approach using machine learning techniques for time series data derived from the Sentinel-2 satellite spanned from mid-November to April. The proposed methodology combines the Normalized Difference Vegetation Index (NDVI), satellite bands like red, green, blue, and NIR, feature extraction, and classification algorithms to capture crop growth's temporal dynamics effectively. Three models, Random Forest, Convolutional Neural Networks, and Support Vector Machine, were compared to obtain the start of season (SOS). It is validated and evaluated using the performance metrics. Further, Random Forest stood out as the best model statistically and spatially for phenology parameter extraction with the least RMSE value at 19 days. CNN and Random Forest models were used to classify wheat crops by combining SOS, blue, green, red, NIR bands, and NDVI. Random Forest produces a more accurate wheat map with an accuracy of 69% and 0.5 MeanIoU. It was observed that CNN is not able to distinguish between wheat and other crops. The result revealed that incorporating the Sentinel-2 satellite data bearing a high spatial and temporal resolution with supervised machine-learning models and crop phenology metrics can empower the crop type classification process.

The women’s sector in the academe is one of the most affected profiles during the COVID-19 pandemic which directly ravages their livelihood and other economic activities. Thus, this research project investigated the economic situations of 30 private and public-school teachers who were displaced from their occupations or were forcibly deprived of income-generating activities. In-depth interviews as research instruments were employed in the study to extract responses on how the educators creatively apply adaptive economic strategies and how government should aid them during a global crisis. The research findings showed that the pandemic has affected the economic activities of the respondents including the loss of their livelihood and other economic sidelines. They responded to these economic effects through adaptive strategies using diversifying and analyzing trends, using digital technology resources, data-driven, acquiring new alternative skills, pricing strategy, and becoming an expert. Results dictated that government could support affected women by initiating training options, homepreneurship support, encouraging independent income-earners, financial management and tax breaks, and industry compatibility endorsement. This study is important to map out the specific economic effects of the pandemic and aid them with initiatives by providing them with concrete economic tools and programs.

Based on 898 English documents and 363 Chinese documents citing the Rising of Network Society, it studied that the knowledge contribution of citation content analysis and citation context analysis methods, and the knowledge contribution of Chinese and foreign quotations to human geography. The study found that “mobile space” is the most quoted theoretical view in domestic and foreign literature, and the proportion of domestic research is significantly higher than foreign research; the focus of domestic and foreign research focuses on the external spatial form and its transformation, while foreign research pays more attention on the internal spatial dynamics of network society and three types of knowledge contributions, reflecting the influence of “network social theory” on human geography. Among them, critical references reveal the shortcomings of “network social theory” point out the abstraction of “spatial duality” the importance of local space, and the limitations of research data, methods, and time background, which provides new enlightenment for the future application and innovation of “network social theory” in the field of human geography.