This paper explores the integration of digital technologies and tools in English as a Foreign Language (EFL) learning in Jordanian Higher Education through a qualitative open-ended online survey. It highlights the perceptions of 100 Jordanian EFL instructors, each with a minimum of five years of experience, on the digital transformation in the EFL learning process. The survey, consisting of ten open-ended questions, gathered in-depth insights on the benefits, challenges, and implications of this transformation. Thematic analysis was employed to analyze the qualitative data, revealing varied levels of experience, the use of diverse digital tools, and both technical and pedagogical challenges. Key findings include the positive impact of digital tools on teaching and learning experiences, enhanced student engagement, and opportunities for personalized learning and collaboration. The study concludes that leveraging digital resources can enhance EFL learner engagement and learning outcomes, inform future pedagogical practices, and shape the landscape of digital transformation in EFL Higher Education for years to come.

Low enrollment intention threatens the funding pools of rural insurance schemes in developing countries. The purpose of this study is to investigate how social capital enhances the enrollment of health insurance among rural middle-aged and elderly. We propose that social capital directly increases health insurance enrollment, while indirectly influences health insurance through health risk avoidance. We used data from the China Health and Retirement Longitudinal Study (wave 4) dating the year of 2018, instrumental variable estimation was introduced to deal with the endogeneity problem, and the mediation analysis was used to examine the mechanism of social capital on insurance enrollment. The results show that social capital is positively related to social health insurance enrollment, and the relationship between social capital and social health insurance enrollment is mediated by health risk avoidance.

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.

This study, drawing on the Knowledge-Based View (KBV) and Contingency Theory, explores how analyzer strategic orientation, learning capability, technical innovation, administrative innovation, and SME growth and learning effectiveness are interrelated. Analyzing cross-sectional data from 407 founders, cofounders, and managers of trade and service SMEs in Vietnam’s Southeast Key Economic Region through PLS-SEM, the research demonstrates that analyzer orientation positively impacts both technical and administrative innovation, thereby bolstering SME growth and learning effectiveness. However, learning capability does not significantly impact technical innovation or growth and learning effectiveness. Instead, learning capability negatively affects administrative innovation. Notably, technical and administrative innovations act as mediators between analyzer orientation and SME growth and learning effectiveness. The study provides practical insights tailored for SMEs navigating dynamic market environments like Vietnam, enriching theoretical understanding of SME strategic management within the trade and service sector.

This paper concerns a miniature gasifier fed with a constant ambient-pressure flow of air to study the pyrolysis and subsequent combustion stage of a single wood pellet at T = 800 ℃. The alkali release and the concentration of simple gases were recorded simultaneously using an improved alkali surface ionisation detector and a mass spectrometer in time steps of 1 s and 1.2 s, respectively. It showed alkali release during both stages. During combustion, the MS data showed almost complete oxidation of the charred pellet to CO₂. The derived alkali release, “O₂ consumed”, and “CO₂ produced” conversion rates all indicated very similar temporal growth and coalescence features with respect to the varying char pore surface area underlying the original random pore model of Bhatia and Perlmutter. But, also large, rapid signal accelerations near the end and marked peak-tails with O₂ and CO₂ after that, but not with the alkali release data. The latter features appear indicative of alkali–deprived char attributable to the preceding pyrolysis with flowing air. Except for the peak-tails, all other features were reproduced well with the modified model equations of Struis et al. and the parameter values resembled closely those reported for fir charcoal gasified with CO₂ at T = 800 ℃.

Urban regeneration and gentrification are complex, interconnected processes that significantly shape cities. However, these phenomena in the Middle East and North Africa (MENA) region are often understudied and typically viewed through a Western lens. This systematic review of literature from 2010 to 2024 addresses this gap by synthesizing a comprehensive framework for understanding urban regeneration-led gentrification in MENA countries. The review delves into key themes: Gentrification contexts, the regeneration process, gentrification accelerators, and the aftermath of gentrification. It explores the diverse motives behind urban regeneration, identifies key stakeholders, and analyzes catalysts of gentrification. Findings reveal that informal areas and deteriorated heritage sites in major cities are most susceptible to gentrification. The study also highlights the critical issue of insufficient community participation and proposes a participation evaluation framework. The unique socioeconomic and political factors driving gentrification in the MENA region underscore the necessity of context-specific approaches, facilitating the identification of regional similarities and differences. Conclusively, the review asserts that gentrification is a cyclic process, necessitating core interventions through enhanced regeneration strategies or displacement plans to mitigate its effects.