We report a method for effectively and homogeneously incorporating carbon nanotubes (CNTs) in the form of double-wall (DWCNTs) and multi-wall (MWCNTs) structures into commercial paints without the use of additives, surfactants, or chemical processes. The process involves the physical mixing of the nanotubes and polymers using the cavitation energy of an ultrasonic bath. It is a simple, fast method that allows for uniform distribution of carbon nanotube bundles within the polymer for direct application. Due to the hydrophobic properties of the carbon nanotubes as grown, we used paint samples containing 0.3% by mass of both types of CNTs and observed an improvement in waterproofing through wettability and water absorption through immersion tests on the samples. Different solvents such as water, formaldehyde, and glycerin were used, and the results showed an increase in paint impermeability of 30% and 25% with the introduction of DWCNTs and MWCNTs, respectively. This indicates a promising, economically viable, and revolutionary method for applying nanotechnology in the polymer industry.

The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

Integrated Resource Management plays a crucial role in sustainable development by ensuring efficient allocation and utilization of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) have emerged as powerful tools for collecting, analyzing, and managing spatial data, enabling comprehensive and integrated decision-making processes. This review article uniquely focuses on Integrated Resource Management (IRM) and its role in sustainable development. It specifically examines the application of RS and GIS in IRM across various resource management domains. The article stands out for its comprehensive coverage of the benefits, challenges, and future directions of this integrated approach.

This work presents the evaluation of iron oxide nanoparticles obtained from the aqueous extract of Eucalyptus grandis. Twenty-three experiments were carried out where the synthesis of nanoparticles was performed by using the aqueous extract together with salts of iron (II) chloride tetrahydrate and iron (III) chloride hexahydrate. A characterization was carried out by IR, TEM and BET, where bands were presented at 3,440.77, 1,559.26 and 445.31 cm⁻¹, indicating the presence of iron oxide nanoparticles. A relatively high monodispersity was evidenced with particles around 9 nm. By means of BET analysis it was found to present a surface area of 131.897 m²/g. Obtaining nanoparticles by this green method presents yield values of 98%, with application in nanotechnology, biomedicine, environmental treatment, among others, making them highly versatile and their production cost is relatively low.

This article examines the factors influencing sustainable entrepreneurship (SE) in Arab countries, focusing on economic, social, and technological dimensions. Using data from various sources and structural equation modeling, the study explores the relationships between these factors and SE sustainability. The findings reveal that economic factors, such as GDP per capita and foreign direct investment (FDI), positively influence SE sustainability, emphasizing the need for a conducive economic environment. Social factors, measured by Internet usage and the Human Development Index (HDI), also significantly impact SE sustainability, highlighting the importance of access to information and education. However, technological factors like patent applications and high-tech exports did not show a significant positive relationship with SE sustainability, suggesting a minimal direct impact on SE longevity in Arab countries. These insights have implications for policymakers, stressing the importance of fostering economic growth and enhancing social infrastructure to support sustainable entrepreneurial ecosystems. Despite its robust methodology, the study has limitations, such as incomplete data for certain countries, affecting the generalizability of the findings. Future research could explore additional factors influencing SE sustainability, further investigate the role of technology, and expand the geographical scope to include more Arab countries.

The selection of a suitable place for an activity is an important decision made for a project, which requires assessing it from different points of view. Educational use is one of the most complicated and substantial uses in urban space that requires precise and logical attention to its location and neighborhood with similar and consistent uses. Faculties of universities are educational spaces that should be protected against physical and moral damage to create a healthy educational environment. To do this, it is necessary to find and assess the factors affecting the location of educational spaces. The extant study aimed at finding and assessing the factors affecting the location of educational spaces to locate art and architecture schools or faculties in 4 important universities. The present study is applied developmental research in terms of nature and descriptive-analytical in terms of method. This study used the AHP (Analytical Hierarchy Process) weighing and controlled the prioritization through the TOPSIS (Technique for Order Preference by Similarity) technique in the methodology phase. Since there was no criterion and metric for these centers, six were chosen as the primary metrics after reviewing the relevant theoretical foundations, early investigations, and collecting effective data. Finally, the results indicated the most important factors of vehicular or roadway access, pedestrian access, slope, parking, adjacency, neighborhood, and area. Among the mentioned factors, pedestrian access (w: 0.4231) had the highest weight and was the priority in the location of architecture faculty in studied campuses and areas inside the universities.