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.

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.

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.

No less than 60% of timber production in Peru’s natural forests is the result of informal or illegal extractive activities that, by definition, are not sustainable. This article aims to demonstrate that even legitimate timber, such as timber harvested in more than 6 million hectares of forest concessions, does not meet the basic requirements of sustainable forest management. Forestry legislation itself, which does not emphasize forest management, institutional weaknesses and the socioeconomic environment are the main causes. In addition, the cutting cycles and the authorized minimum diameters, among other practices, do not allow the renewal of the resource and increase its degradation.

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.