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Background: COVID-19 is now a global public health crisis with unprecedented political, economic, and social consequences affecting nations across the world. It also has a profound impact on the mobility of international students. When the COVID-19 was under control in China, and it was spreading dramatically in the United Kingdom, Chinese international students studying in the United Kingdom have been caught in a double bind over whether to return home or not. Objective: This study aims to explore the factors that influenced Chinese international students' choices of return during the COVID-19 pandemic when the COVID-19 was under control in China, while it was spreading dramatically in the United Kingdom. Methods: Taking Chinese international students studying in the United Kingdom as an empirical case, this study used qualitative and quantitative research methods to explore the factors that influenced their choices of return. Based on the Rational Choice Theory and qualitative analysis of text data, this paper constructed the influencing factors model of returning to China. On this basis, we developed a questionnaire and collected data from 1,333 students in late April and early May 2020. Binary Logistic Regression with 95% CI for odds ratio (OR) was used to identify significant factors. Results: The reserve of epidemic prevention supplies (OR = 0.712), transportation expenses (OR = 0.618), and quarantine expenses (OR = 0.702) negatively affected the return choice of overseas students. The supply of daily necessities (OR = 1.495), the anti-epidemic policy of the United Kingdom (OR = 1.684), and the demand for job hunting after graduation (OR = 1.661) had positive effects. Conclusion: The institutional rationality had the biggest promoting effect, replaced development rationality, and became the most important factor for overseas students to return to China during the COVID-19 pandemic. Economic rationality, which has a significant negative effect, is the biggest obstacle to returning home. These conclusions have policy implications for governments' response to the COVID-19 epidemic and improvement of the quality of services for overseas students. [ABSTRACT FROM AUTHOR]

Background: In order to leverage the potential benefits of technology to speech and language therapy language assessment processes, large samples of naturalistic language data must be collected and analysed. These samples enable the development and testing of novel software applications with data relevant to their intended clinical application. However, the collection and analysis of such data can be costly and time-consuming. This paper describes the development of a novel application designed to elicit and analyse young children’s story retell narratives to provide metrics regarding the child’s use of grammatical structures (micro-structure) and story grammar (macro-structure elements). Key aspects for development were (1) methods to collect story retells, ensure accurate transcription and segmentation of utterances; (2) testing the reliability of the application to analyse micro-structure elements in children’s story retells and (3) development of an algorithm to analyse narrative macro-structure elements. Methods: A co-design process was used to design an app which would be used to gather story retell samples from children using mobile technology. A citizen science approach using mainstream marketing via online channels, the media and billboard ads was used to encourage participation from children across the United Kingdom. A stratified sampling framework was used to ensure a representative sample was obtained across age, gender and five bands of socioeconomic disadvantage using partial postcodes and the relevant indices of deprivation. Trained Research Associates (RA) completed transcription and micro and macro-structure analysis of the language samples. Methods to improve transcriptions produced by automated speech recognition were developed to enable reliable analysis. RA micro-structure analyses were compared to those generated by the digital application to test its reliability using intra-class correlation (ICC). RA macro-structure analyses were used to train an algorithm to produce macro-structure metrics. Finally, results from the macro-structure algorithm were compared against a subset of RA macro-structure analyses not used in training to test its reliability using ICC. Results: A total of 4,517 profiles were made in the app used in data collection and from these participants a final set of 599 were drawn which fulfilled the stratified sampling criteria. The story retells ranged from 35.66 s to 251.4 s in length and had word counts ranging from 37 to 496, with a mean of 148.29 words. ICC between the RA and application micro-structure analyses ranged from 0.213 to 1.0 with 41 out of a total of 44 comparisons reaching ‘good’ (0.70–0.90) or ‘excellent’ (>0.90) levels of reliability. ICC between the RA and application macro-structure features were completed for 85 samples not used in training the algorithm. ICC ranged from 0.5577 to 0.939 with 5 out of 7 metrics being ‘good’ or better. Conclusion: Work to date has demonstrated the potential of semi-automated transcription and linguistic analyses to provide reliable, detailed and informative narrative language analysis for young children and for the use of citizen science based approaches using mobile technologies to collect representative and informative research data. Clinical evaluation of this new app is ongoing, so we do not yet have data documenting its developmental or clinical sensitivity and specificity. [ABSTRACT FROM AUTHOR]

Cultured meat is presented by its advocates as a good alternative for consumers who want to be more ethically minded but who do not wish to change their diet. This novel food has become an emerging topic in both the scientific field and the press media. From a bibliometric analysis of scientific publications and on a sociometric analysis of the mainstream press, the aim of this study was to identify potential differences between the scientific view and the public perception. This research analyzed the publications indexed by SCI-EXPANDED in the Web of Science Core Collection database owned by Clarivate Analytics, for scientific literature analysis, and indexed by the Factiva database, for the press media. A total of 327 scientific publications were analyzed according to year of publication and country and institution of origin, also including coauthorships, co-citations, and scientific fields' and journals' networks. A knowledge mapping using VOSviewer was used to study the literature in the field. Based on Factiva, 12,900 press articles dealing with artificial meat, mainly in English, have been found through public databases. The main conclusion is that cultured meat is mainly developing in the USA and the UK, with other countries, such as China, observing the trend for potential future applications. Scientific articles seemed initially to focus mainly on technical aspects of artificial meat and more recently on health value, consumer's acceptance, and sustainability. However, the potential environment-friendly effects of this novel food are more and more studied or described in scientific or press articles. [ABSTRACT FROM AUTHOR]

This article, which is part of an on-going large-scale study, quantitatively explores and compares the frequency, patterns, and positions of the three most frequently used discourse markers (DMs): so, and, but in TV interviews. The data comprise three corpora consisting of three media programs from China, the US, and the UK. Results show that there is a statistically significant difference in the frequency of the DM so and the DM and, with each DM having the highest frequency in a specific corpus. Four co-occurring strings ("and so," "and but," "so but," "but so") are identified in the three corpora with the DM cooccurrence "and so" having the highest frequency in the American program, supporting the claim that this combination is a typical use in American English. The general positional distribution of the three DMs is similar with the highest tendency in the initial position, which can be attributed to the program's interactivity. The findings will enhance our understanding of the three DMs used in media discourse and should be of practical significance to media hosts and guests in achieving better bilateral communication. [ABSTRACT FROM AUTHOR]

Aims: Studies have shown the predictive effects of procrastination and self-regulation on wellbeing. However, little is known about the interactive effect between procrastination and self-regulation. This study explores whether self-regulation moderates the link between procrastination and wellbeing among British and Chinese young adults. Methods: This study adopted self-reported questionnaire survey among two hundred and sixty-five British and four hundred and seventy-five Chinese participants. SPSS and AMOS were used to test the moderation effect. Multi-group path analysis was used to compare the two countries. Results: Data analysis shows that self-regulation was a significant moderator of the relationship between procrastination and life satisfaction in the Chinese sample but not in the British sample. Procrastination predicted low life satisfaction only among the Chinese students with low self-regulation. Discussion: This study indicates that the effects of procrastination on wellbeing could be changed at different levels of self-regulation. Cultural difference can be an important factor when investigating procrastination and its impacts. [ABSTRACT FROM AUTHOR]