Introduction: The heterogeneity of occupational morbidity by gender in those suffering from carpal tunnel syndrome (CTS) has been little studied in the Latin American context. The objective of this study was to estimate the incidence and prevalence of CTS of occupational origin in the Ecuadorian salaried population according to gender, In addition, the differences in risk between women and men are compared. Methods: We use the only administrative registers of CTS qualified as occupational diseases in the country between the years 2017 and 2019. Period incidence rates were estimated to compare the risk in women versus men (RR, CI 95%) by age group and economic activity. Results: CTS is the second most common occupational disease in Ecuador. Women workers are more likely tosuffer from CTS and showed twice the risk compared to men [RR = 2.10 (95%CI: 1.94–2.11); p = 0.000]. This risk increases with age and for the vast majority of economic activities. The occupations of agriculture and warehousing stand out for their importance. Conclusions: The results shown in this study raise the fundamental need to improve epidemiological surveillance systems and occupational health policies by considering gender differences in order to adequately address risks and promote safe and healthy working environments for all.

Oil spills (OS) in waters can have major consequences for the ecosystem and adjacent natural resources. Therefore, recognizing the OS spread pattern is crucial for supporting decision-making in disaster management. On 31 March 2018, an OS occurred in Balikpapan Bay, Indonesia, due to a ship’s anchor rupturing a seafloor crude oil petroleum pipe. The purpose of this study is to investigate the propagation of crude OS using coupled three-dimensional (3D) model from DHI MIKE software and remote sensing data from Sentinel-1 SAR (Synthetic Aperture Radar). MIKE3 FM predicts and simulates the 3D sea circulation, while MIKE OS models the path of oil’s fate concentration. The OS model could identify the temporal and spatial distribution of OS concentration in subsurface layers. To validate the model, in situ observations were made of oil stranded on the shore. On 1 April 2018, at 21:50 UTC, Sentinel-1 SAR detected an OS on the sea surface covering 203.40 km². The OS model measures 137.52 km². Both methods resulted in a synergistic OS exposure of 314.23 km². Wind dominantly influenced the OS propagation on the sea surface, as detected by the SAR image, while tidal currents primarily affected the oil movement within the subsurface simulated by the OS model. Thus, the two approaches underscored the importance of synergizing the DHI MIKE model with remote sensing data to comprehensively understand OS distribution in semi-enclosed waters like Balikpapan Bay detected by SAR.

This paper aims to contribute with a literature review on the use of AI for cleaner production throughout industries in the consideration of AI’s advantage within the environment, economy, and society. The survey report based on the analysis of research papers from the recent literature from leading database sources such as Scopus, the Web of Science, IEEE Xplore, Science Direct, Springer Link, and Google Scholar identifies the strategic strengths of AI in optimizing the resources, minimizing the carbon footprint and eradicating wastage with the help of machined learning, neural networks and predictive analytics. AI integration presents vast aspects of environmental gains, including such enhancements as a marked reduction concerning the energy and materials consumed along with enhanced ways of handling the resulting waste. On the economic aspect, AI enhances the processes that lead to better efficiency and lower costs in the market on the other hand, on the social aspect, the application of any AI influences how people are utilized as workers/clients in the community. The following are some of the limitations towards AI adoption as proposed by the review of related literature; The best things that come with AI are yet accompanied by some disadvantages; there are implementation costs, data privacy, as well as system integration that may be a major disadvantage. The review envisages that with the continuation of the AI development in the following years, the optic is going to be the accentuation on the enhancement of the process of feeding the data in real-time mode, IoT connections, and the implementation of the proper ethical approaches toward the AI launching for all segments of the society. The conclusions provide precise suggestions to the people working in the industry to adopt the AI advancements appropriately and at the same time, encourage the lawmakers to create favorable legal environments to enable the ethical uses of AI. This review therefore calls for more targeted partnerships between the academia, industry, and government to harness the full potential of AI for sustainable industrial practices worldwide.

To address the escalating online romance scams within telecom fraud, we developed an Adaptive Random Forest Light Gradient Boosting (ARFLGB)-XGBoost early warning system. Our method involves compiling detailed Online Romance Scams (ORS) incident data into a 24-variable dataset, categorized to analyze feature importance with Random Forest and LightGBM models. An innovative adaptive algorithm, the Adaptive Random Forest Light Gradient Boosting, optimizes these features for integration with XGBoost, enhancing early Online romance scams threat detection. Our model showed significant performance improvements over traditional models, with accuracy gains of 3.9%, a 12.5% increase in precision, recall improvement by 5%, an F1 score increase by 5.6%, and a 5.2% increase in Area Under the Curve (AUC). This research highlights the essential role of advanced fraud detection in preserving communication network integrity, contributing to a stable economy and public safety, with implications for policymakers and industry in advancing secure communication infrastructure.

The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO₂ in 2023 and 2059 tCO₂ in 2030.

Entrepreneurial self-efficacy has a predictive effect on entrepreneurial performance. The lithium-ion battery industry is the cornerstone of the emergency of the four emerging industries of “new energy”, “new materials”, “new technology” and “high-end manufacturing”. In the past, scholars have not considered the characteristics of entrepreneurs in their research on improving Chinese lithium-ion battery new venture growth. The personal characteristics of entrepreneurs have not received widespread attention from scholars. This article will start with the characteristics of entrepreneurs themselves and explore the path that entrepreneurs’ characteristics affect Chinese lithium battery new venture growth. This article builds a structural equation model to empirically analyze the relationship among variables. The data analysis results show that entrepreneurial self-efficacy significantly promotes the growth of new startups and entrepreneurial resilience plays a mediating role between the two. It cannot be concluded that entrepreneurial passion plays a positive moderation role between entrepreneurial self-efficacy and entrepreneurial resilience. Entrepreneurial passion also does not play a positive moderation effect between entrepreneurial self-efficacy and new venture growth. However, entrepreneurial passion plays a positive moderating role in the influence of entrepreneurial resilience on new venture growth. The findings of the study are beneficial for practitioners of Chinese lithium battery enterprises and will allow their strategies to promote sustainable new venture growth.