To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

It is important for society to know the actions implemented by companies in the construction sector to reduce the environmental pollution generated by this industry and to contribute to the solution of economic and social problems in their environment; however, the variables that allow identifying their contributions and impacts are not known. Based on this problem, the study focuses on identifying the factors that influence sustainability management within the construction sector in Colombia. The research presents a predictive approach and uses a quantitative methodology, applying statistical modeling techniques. The sample corresponds to 84 Colombian companies. As a result, a system of equations of the form y=mx+b is presented to describe the deviation of the environmental, economic, social, compensation measures, management, indicators and sustainability reports. The analysis of the intersections constitutes a projective tool to evaluate the relationships and balance points between the dimensions analyzed, helping to identify strengths and opportunities for improvement.

This study presents a comprehensive two-dimensional numerical analysis of natural laminar convection within a square cavity containing two circular heat sources, which simulate electric cables generating heat due to Joule heating. This scenario is particularly relevant in aeronautics, where excessive heating of electrical installations can lead to significant material and human safety risks. The primary objective of this research is to identify the optimal spacing between the two heat sources to mitigate the risk of overheating and ensure the safe operation of the electrical installation. To achieve this, various configurations were analyzed by adjusting the distance between the heat sources while also varying the Rayleigh number across a range from 10³ to 10⁶. The governing equations for the fluid flow and heat transfer were solved using a FORTRAN-based numerical code employing the finite volume method. The results indicate that the heat transfer characteristics within the cavity are significantly influenced by both the distance between the heat sources and the Rayleigh number. The analysis revealed that the average Nusselt number (Nu_avg) peaked at a value of 14.69 when the distance between the heat sources was set at 0.7 units and the Rayleigh number was at 10⁶. This finding suggests that maintaining this specific spacing between the electrical cables can optimize heat dissipation and enhance the safety of the installation. In conclusion, the study recommends adopting a spacing of 0.7 units between the electrical cables to ensure optimal thermal performance and minimize the risk of overheating, thereby safeguarding both the materials and personnel involved in aeronautical operations.

The tourism sector in the Aseer region of Saudi Arabia is experiencing significant growth and development, aligning with the country’s Vision 2030 strategic framework. However, rapid growth can lead to strategic drift if not managed with vigilance. This study aims to examine the role of strategic vigilance in reducing strategic drift in the tourism sector. The study employs a quantitative approach, utilizing a questionnaire distributed to a sample of 220 staff and directors from the tourism sector. The questionnaire measures the level of strategic vigilance and the level of strategic drift. The study hypothesizes a statistically significant positive relationship between strategic vigilance and reducing strategic drift. Data analysis involves exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. The findings are expected to provide insights into the effectiveness of strategic vigilance in mitigating strategic drift and offer recommendations for enhancing the tourism sector’s resilience and adaptability to accelerated environmental changes.

Creating products and services that satisfy individual and community needs is impossible without raw materials. This study takes a novel approach by integrating the economic dynamics and raw material consumption indicators of the European Union (EU). The study uses different econometric methods to analyze the relationship between GDP (gross domestic product) and the EU’s raw material consumption (RMC) from 2014–2023. Among the results, the panel data analysis model shows that the resource productivity of the EU improved during the period under review, whereas the material intensity decreased significantly. These trends significantly contributed to the relative decoupling of material consumption from GDP in the last decade. The results of the K-means cluster analysis highlight the regional economic differences within the EU. According to the results of the correlation analysis, EU member countries differ significantly in the efficiency of raw material use. Nevertheless, five member countries are robustly vulnerable to large-scale raw material use. The divergence calculation results show that while some countries use raw materials extremely efficiently to produce GDP, others achieve low efficiency. This unique approach and the resulting findings provide a new perspective on the complex relationship between economic growth and raw material use in the EU.

The study examines the economic and social impacts of a Southeast Asian multinational company operating in the northwestern region of Hungary, with a particular focus on the local labor market and community responses. The research aims to explore the company’s location choice motivations, its integration process into the local economy, and its cooperation with the local government and communities. The research provides a comprehensive picture of the company’s impacts by employing qualitative and quantitative methodologies—including management interviews and household surveys. The findings indicate that the company has significantly increased employment, enhanced infrastructure, and promoted cultural diversity. However, challenges related to cultural integration persist. The study offers valuable guidance for policymakers and businesses on leveraging the economic benefits of foreign investments and fostering cultural cooperation. Future research could delve deeper into the long-term socio-economic impacts.