This study explored the competencies required for informal community leaders to effectively promote health within Thai communities, employing an exploratory sequential mixed-methods design. The qualitative phase, comprising in-depth interviews with thirteen community leaders, identified four critical domains of competency: basic health knowledge, communication skills, network building, and cultural awareness. These domains were subsequently validated through second-order confirmatory factor analysis, which confirmed their reliability and construct validity. The findings highlighted the pivotal role of these competencies in enabling community-led health promotion initiatives. This research provides a robust, evidence-based framework to inform the development of training programs, policy strategies, and targeted interventions aimed at enhancing health outcomes within Thai communities.

In recent years, the environment in the manufacturing industry has become strongly competitive, which is why companies have found it necessary to constantly adjust their strategies and take actions aimed at improving their performance and competitiveness in a sustainable way to grow and remain in the market. Therefore, this paper aims to present an analysis to explain the current situation in the manufacturing industry in Aguascalientes, Mexico, by means of a survey in which product eco-innovation (PEI), process eco-innovation (PrEI) and organizational eco-innovation (OEI) and its effect on environmental performance (EP) and sustainable competitive performance (SCP) were measured. The results show that (EP) is positively and significantly influenced by (PEI) and (PrEI), while no significant influence is found for (OE). Furthermore, it is confirmed that environmental performance positively and significantly influences (SCP). The findings obtained from this study point to the relevance of promoting eco-innovation activities in the manufacturing sector, as this will ensure sustainable competitiveness.

The design of effective flood risk mitigation strategies and their subsequent implementation is crucial for sustainable development in mountain areas. The assessment of the dynamic evolution of flood risk is the pillar of any subsequent planning process that is targeted at a reduction of the expected adverse consequences of the hazard impact. This study focuses on riverbed cities, aiming to analyze flood occurrences and their influencing factors. Through an extensive literature review, five key criteria commonly associated with flood events were identified: slope height, distance from rivers, topographic index, and runoff height. Utilizing the network analysis process within Super Decision software, these factors were weighted, and a final flood risk map was generated using the simple weighted sum method. 75% of the data was used for training, and 25% of it was used for testing. Additionally, vegetation changes were assessed using Landsat imagery from 2000 and 2022 and the normalized difference vegetation index (NDVI). The focus of this research is Qirokarzin city as a case study of riverbed cities, situated in Fars province, with Qir city serving as its central hub. Key rivers in Qirokarzin city include the Qara Aghaj River, traversing the plain from north to south; the primary Mubarak Abad River, originating from the east; and the Dutulghaz River, which enters the eastern part of the plain from the southwest of Qir, contributing to plain nourishment during flood events. The innovation of this paper is that along with the objective to produce a reliable delineation of hazard zones, a functional distinction between the loading and the response system (LS and RS, respectively) is made. Results indicate the topographic index as the most influential criterion, delineating Qirokarzin city into five flood risk zones: very low, low, moderate, high, and very high. Notably, a substantial portion of Qirokarzin city (1849.8 square kilometers, 8.54% of the area) falls within high- to very-high flood risk zones. Weighting analysis reveals that the topographic humidity index and runoff height are the most influential criteria, with weights of 0.27 and 0.229, respectively. Conversely, the height criterion carries the least weight at 0.122. Notably, 46.7% of the study area exhibits high flood intensity, potentially attributed to variations in elevation and runoff height. Flood potential findings show that the middle class covers 32.3%, indicating moderate flood risk due to changes in elevation and runoff height. The low-level risk is observed sporadically from the east to the west of the study area, comprising 12.4%. Analysis of vegetation changes revealed a significant decline in forest and pasture cover despite agricultural and horticultural development, exacerbating flood susceptibility. 

Segregating the scavenging processes from the lubrication methodology is a very effective way of improving two-stroke cycle engine durability. The application of stepped or twin diameter pistons is one such method that has repeatedly shown significantly greater durability over comparable crankcase scavenged engines together with an ability to operate on neat fuel without any added oil. This research study presents the initial results observed from a gasoline/indolene fuelled stepped piston engine ultimately intended for Hybrid Electric Vehicle and/or Range Extender Electric Vehicle application using hydrogen fuelling. Hydrogen fuelling offers the potential to significantly reduce emissions, with near zero emission operation possible, and overcoming the serious issues of range anxiety in modern transport solutions. The low environmental impact is discussed along with results from 1-d Computational Fluid Dynamic modelling. The engine type is a low-cost solution countering the financial challenges of powertrain duplication evident with Hybrid Electric and Range Extender Electric Vehicles.

The interest in smart grids and new technologies is growing around the world. Countries are investing in the development of new technologies that will help achieve environmental goals, energy supply efficiency, improve energy efficiency and increase consumer involvement in the energy generation. One of such technology is a blockchain. It is believed that the blockchain, combined with a smart grid, provides an opportunity to integrate the activities of all stakeholders, including: generators, distributors and consumers of electricity. The aim of the article is to identify the key research areas discussed by the researchers of both the smart grid and the blockchain issues. An analysis of the Scopus database from 2015 to 2023 was conducted. Using a created bibliometric query, a systematic literature review was conducted. 476 scientific publications relating to the issues addressed were identified. Using the VOSviewer software, a bibliometric analysis was performed using the author’s keywords. The bibliometric maps obtained allowed for the identification of key research areas. The article also presents potential future directions of scientific considerations, which should be focused on the issue of green smart grid and green blockchain. The results presented in the article can inspire researchers looking for research gaps or describing the current state of knowledge in the field of the smart grid and the blockchain issues.

Artificial intelligence has transformed teachers’ teaching models. This article explores the application of artificial intelligence in basic education in Macao middle schools. This study adopts case analysis in qualitative research, using a total of eight cases from the innovative technology education platform of the Macau education and Youth Development Bureau. These data illustrate how Macao’s artificial intelligence technology promotes teaching innovation in basic education. These eight cases are closely related to the application of artificial intelligence in basic education in Macao. The survey results show that Macao’s education policy has a positive effect on teaching innovation in artificial intelligence education. In teaching practice, the school also cooperates with the government’s policy. The application of AI technology in teaching, students’ learning styles, changes in teachers’ roles, and new needs for teacher training are all influential.