Thailand and the EU started negotiating a free trade agreement (FTA) in 2005, but negotiations were subsequently suspended in 2014 after the country’s military coup. The significance of these negotiations are important because of the mutual benefit of achieving higher levels of trade and investment between the world’s largest single market and the second largest ASEAN economy. The Specific Factors (SF) model of production and trade is applied to identify potential winner and loser industries and factors of production in Thailand. The model identifies short-run loses for some labor inputs, return to capital, and output in agriculture and services. In the manufacturing and energy sectors, higher output will benefit some labor inputs and capital owners. Understanding the short-run impact of an FTA could allow policymakers in Thailand to reinforce the institutional infrastructure such as implementing trade adjustment assistance programs (TAA), to help re-train workers who may become unemployed due to free trade.

The objective of this work was to analyze the effect of the use of ChatGPT in the teaching-learning process of scientific research in engineering. Artificial intelligence (AI) is a topic of great interest in higher education, as it combines hardware, software and programming languages to implement deep learning procedures. We focused on a specific course on scientific research in engineering, in which we measured the competencies, expressed in terms of the indicators, mastery, comprehension and synthesis capacity, in students who decided to use or not ChatGPT for the development and fulfillment of their activities. The data were processed through the statistical T-Student test and box-and-whisker plots were constructed. The results show that students’ reliance on ChatGPT limits their engagement in acquiring knowledge related to scientific research. This research presents evidence indicating that engineering science research students rely on ChatGPT to replace their academic work and consequently, they do not act dynamically in the teaching-learning process, assuming a static role.

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.

This study examines the impact of structured cultural educational activities on various dimensions of student well-being in primary education. Using a randomized controlled trial design, 120 third- and fourth-grade students from Arad County, Romania, were assigned to either an experimental group, which participated in cultural educational activities, or a control group, which received no intervention. Well-being and social behavior were assessed using the Strengths and Difficulties Questionnaire (SDQ) and the EPOCH Measure of Adolescent Well-Being, administered before and after the intervention. The SDQ evaluated emotional symptoms, hyperactivity, conduct problems, peer relationship issues, and prosocial behavior, while the EPOCH scale measured engagement, perseverance, optimism, connectedness, and happiness. Analysis revealed statistically significant improvements (p < 0.05) in the experimental group compared to the control group. Students in the experimental group exhibited reduced hyperactivity and peer relationship problems, alongside notable increases in engagement, perseverance, optimism, connectedness, and happiness. These findings highlight the efficacy of integrating cultural educational activities into the primary school curriculum as a strategy for enhancing emotional and social development. The study underscores the importance of such interventions in fostering positive developmental outcomes and offers a foundation for further research into their long-term effects and adaptability across diverse educational contexts.

Surface-enhanced Raman scattering (SERS) spectrum has the characteristics of fast-detection, high-sensitivity and low-requirements for sample pretreatment. It plays a more and more important role in the detection of organic pollutants. In this study, MIL-101 and Au nanoparticles were prepared by hydrothermal method and aqueous solution reduction method respectively, and MIL-101/Au composite nanoparticles were prepared by electrostatic interaction. The SERS properties of the composite substrate were optimized by adjusting the size of Au nanoparticles and the surface distribution density of MIL-101 nanoparticles. The detection limit of Rhodamine 6G (R6G) for the composite substrate with the optimal ratio was investigated, which was as low as 10^–11 M. It is proved that MIL-101/Au composite nanoparticles have high sensitivity to probe molecules. When they are applied to the detection of persistent organic pollutants, the detection limit for fluoranthene can reach 10^–9 M and for 3,3’,4,4’-tetrachlorobiphenyl (PCB-77) can reach 10^–5 M.

During and after any disaster, a situation report (SITREP) is prepared, based on the Daily Incident Updates (DIU), as an initial decision support information base. It is observed that the decision support system and best practices are not optimized through the available formal reporting on disaster incidents. The rapidly evolving situation, misunderstood terms, inaccurate data and delivery delays of DIU are challenges to the daily SITREP. Multiple stakeholders stipulated with different tasks should be properly understood for the SITREP to initiate relevant response tasks. To fill this research gap, this paper identifies the weaknesses of the current practice and discusses the upgrading of the incident-reporting process using a freely available software tool, enabling further visualization, and producing a comprehensive timely output to share among the stakeholders. In this case, “Power-BI” (a data visualization software) is used as a 360-degree view of useful metrics—in a single place, with real-time updates while being available on all devices for operational decision-making. When a dataset is transformed into several analytical reports and dashboards, it can be easily shared with the target users and action groups. This article analyzed two sources of data, namely the Disaster Management Center (DMC) and the National Disaster Relief Service Center (NDRSC) of Sri Lanka. Senior managers of disaster emergencies were interviewed and explored social media to develop a scheme of best practices for disaster reporting, starting from just before the occurrence, and following the unfolding sequence of the disasters. Using a variety of remotely acquired imageries, rapid mapping, grading, and delineating impacts of natural disasters, were made available to concerned users.