This article explores recent developments in English language education in Taiwan, situating them within broader sociopolitical shifts and demographic changes. It begins by outlining the emergence of English in Taiwan’s education system before presenting the formulation and objectives of the Bilingual 2030 policy. The article then analyzes how this national initiative has reshaped English language education across educational levels. In particular, it highlights the expansion of English–medium instruction (EMI) in higher education as a central feature of Taiwan’s bilingualization agenda. Finally, it discusses two key developments influenced by the policy: the internationalization of higher education as a response to demographic and policy pressures, and the resulting expansion of EMI courses as a central strategy for attracting global talent and sustaining university enrollment.

We study the singularities of varieties obtained as infinitesimal quotients by $1$-foliations in positive characteristic. (1) We show that quotients by (log) canonical $1$-foliations preserve the (log) singularities of the MMP. (2) We prove that quotients by multiplicative derivations preserve many properties, amongst which most F-singularities. (3) We formulate a notion of families of $1$-foliations, and investigate the corresponding families of quotients.

A path being planned for an unmanned aerial vehicle (UAV) or its armed conformation called the unmanned combat aerial vehicle (UCAV) has a critical importance on the flight safety and success of the task including reconnaissance, surveillance, monitoring or destroying. The Back-and-Forth (BaF) algorithm is one of the most recent greedy techniques that executes a heuristic approach for generating two backbone candidates and a combination procedure for bringing advantageous segments of them in order to solve the geometric description of the path planning problem. This study was devoted to a thread-based parallel implementation of the BaF algorithm, also named the multi-threaded BaF (tBaF for short). The threads of the tBaF algorithm increase their search bounds gradually according to the assigned thread indexes and execute the heuristic approach and combination procedure of the BaF for calculating paths. A set of detailed experiments was carried out with the aim of evaluating the performance of the tBaF, and its results were compared with the BaF and 14 other meta-heuristic-based path planners over three battlefield scenarios and their 12 test cases containing the preidentified enemy threats. Comparative studies showed that the different local and global search capabilities of the threads gained with the newly introduced thread-based organisation give a significant contribution to the path planning performance and allow the tBaF to be ranked among the top three planners even though it requires at least from four to eight times less function calls than the tested meta-heuristics.

Paternity leave may promote greater gender equality in domestic labour. Though numerous studies show that paternity leave promotes greater fathers’ involvement in childcare, less is known about whether paternity leave-taking may facilitate fathers’ involvement in other forms of domestic labour such as housework. Using repeated cross-sectional data on different-gender partnered US parents from the Study on Parents’ Divisions of Labor During COVID-19 (SPDLC), this study examines the extent to which paternity leave-taking and length of paternity leave are associated with US fathers’ shares of, and time spent on, housework. Findings suggest that paternity leave-taking is positively associated with fathers’ shares of, and time spent on, housework tasks. Longer paternity leaves are also associated with fathers performing greater shares of housework. Overall, this study indicates that the benefits of paternity leave likely extend to fathers’ greater participation in housework, providing additional support for the belief that increased use of paternity leave may help to promote gender equality in domestic labour.

Against the proliferation of large language model (LLM) based Artificial Intelligence (AI) products such as ChatGPT and Gemini, and their increasing use in professional communication training, researchers, including applied linguists, have cautioned that these products (re)produce cultural stereotypes due to their training data. However, there is a limited understanding of how humans navigate the assumptions and biases present in the responses of these LLM-powered systems and the role humans play in perpetuating stereotypes during interactions with LLMs. In this article, we use Sequential-Categorial Analysis, which combines Conversation Analysis and Membership Categorization Analysis, to analyze simulated interactions between a human physiotherapist and three LLM-powered chatbot patients of Chinese, Australian, and Indian cultural backgrounds. Coupled with analysis of information elicited from LLM chatbots and the human physiotherapist after each interaction, we demonstrate that users of LLM-powered systems are highly susceptible to becoming interactionally entrenched in culturally essentialized narratives. We use the concepts of interactional instinct and interactional entrenchment to argue that whilst human–AI interaction may be instinctively prosocial, LLM users need to develop Critical Interactional Competence for human–AI interaction through appropriate and targeted training and intervention, especially when LLM-powered tools are used in professional communication training programs.

The RDA for dietary protein is likely to be insufficient for individuals with cystic fibrosis (CF), whereas a higher daily intake of ≥1.2g·kg−1·day−1 may be more appropriate in view of the increased risk of sarcopenia and reduced muscle quality. This study sought to characterise protein intake and diet quality in adults with cystic fibrosis (awCF), before and after elexacaftor/tezacaftor/ivacaftor (ETI) therapy, compared to healthy controls. Dietary intake was assessed by diet diary in awCF at baseline (BL, n=40) and at follow-up >3 months post ETI therapy (FUP, n=40), and in age-matched healthy controls (CON, n=80) free from known disease at a single time point. Protein intake dose and daily distribution, protein quality, protein source and overall diet quality was calculated for each participant. Both CON (1.39±0.47g·kg-1·day-1) and CF (BL: 1.44±0.52g·kg-1·day-1, FUP: 1.12±0.32g·kg-1·day-1) had a higher mean daily protein intake than the protein RDA of 0.75g·kg-1·day-1. There was a significant reduction in daily protein intake in the CF group at FUP (P=0.0003, d=0.73), with levels below the alternative suggested dietary intake of ≥1.2g·kg−1·day−1. There were no sex differences or noticeable effects on protein quality or source following the commencement of ETI therapy when compared to CON (all P>0.05), although overall diet quality decreased between time points (P=0.027, d=0.57). The observed reduction in daily protein intake in the present cohort emphasises the importance of ensuring appropriate dietary protein intake to promote healthy ageing in adults with CF. More research is needed to evidence base dietary protein requirements in this at-risk population.