Proposed herein is an environment-friendly method to realize oil/water separation. Nylon mesh is exposed to atmospheric pressure plasma for surface modification, by which micro/nano structures and oxygen-containing groups are created on nylon fibers. Consequently, the functionalized mesh possesses superhydrophilicity in air and thus superoleophobicity underwater. The water pre-wetted mesh is then used to separate oil/water mixtures with the separation efficiency above 97.5% for various oil/water mixtures. Results also demonstrate that the functionalized nylon mesh has excellent recyclability and durability in terms of oil/water separation. Additionally, polyurethane sponge slice and polyester fabric are also functionalized and employed to separate oil/water mixtures efficiently, demonstrating the wide suitability of this method. This simple, green and highly efficient method overcomes a nontrivial hurdle for environmentally-safe separation of oil/water mixtures, and offers insights into the design of advanced materials for practical oil/water separation.

In the process of English learning, primary school English is an important period of enlightenment. However, teachers’ old-fashioned teaching methods and obscure teaching contents make primary school students less interested in learning English, which will affect students’ entire English learning career. Under this educational background, the education department should analyze the existing problems in English teaching methods, teaching contents and teaching concepts based on the current situation of English teaching in primary schools, aiming to improve the interest of English teaching in primary schools through effective strategies.

This empirical inquiry adopts the AutoRegressive Distributed Lag (ARDL) model to meticulously examine the multifaceted interconnections among innovation, globalization, and productivity across a diverse set of 76 nations, encompassing both developed and developing economies. The research employs rigorous econometric techniques within the ARDL framework to discern the short- and long-term effects of innovation and globalization on productivity levels. The findings underscore a robust and statistically significant association between innovation and productivity, as well as a constructive impact of globalization on enhancing productivity. The outcomes underscore the transformative potential of innovation and the facilitating role of globalization in fostering productivity growth. This empirical evidence contributes to the empirical literature by offering a refined understanding of the intricate relationships shaping productivity patterns on a global scale, emphasizing the joint influence of innovation and globalization in driving economic efficiency.

The purpose of this work is to present the model of a Parabolic Trough Solar Collector (PTC) using the Finite Element Method to predict the thermal behavior of the working fluid along the collector receiver tube. The thermal efficiency is estimated based on the governing equations involved in the heat transfer processes. To validate the model results, a thermal simulation of the fluid was performed using Solidworks software. The maximum error obtained from the comparison of the modeling with the simulation was 7.6% at a flow rate of 1 L/min. According to the results obtained from the statistical errors, the method can effectively predict the fluid temperature at high flow rates. The developed model can be useful as a design tool, in the optimization of the time spent in the simulations generated by the software and in the minimization of the manufacturing costs related to Parabolic Trough Solar Collectors.

This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.