Green manufacturing is increasingly becoming popular, especially in lubricant manufacturing, as more environmentally friendly substitutes for mineral base oil and synthetic additives are being found among plant extracts and progress in methodologies for extraction and synthesis is being made. It has been observed that some of the important performance characteristics need enhancement, of which nanoparticle addition has been noted as one of the effective solutions. However, the concentration of the addictive that would optimised the performance characteristics of interest remains a contending area of research. The research was out to find how the concentration of green synthesized aluminum oxide nanoparticles in nano lubricants formed from selected vegetable oils influences friction and wear. A bottom-up green synthesis approach was adopted to synthesize aluminum oxide (Al₂O₃) from aluminum nitrate (Al(NO₃)₃) precursor in the presence of a plant-based reducing agent—Ipomoea pes-caprae. The synthesized Al₂O₃ nanoparticles were characterized using TEM and XRD and found to be mostly of spherical shape of sizes 44.73 nm. Al₂O₃ nanoparticles at different concentrations—0.1 wt%, 0.3 wt%, 0.5 wt%, 0.7 wt%, and 1.0 wt%—were used as additives to castor, jatropha, and palm kernel oils to formulate nano lubricants and tested alternately on a ball-on-aluminum (SAE 332) and low-carbon steel Disc Tribometer. All the vegetable-based oil nano lubricants showed a significant decrease in the coefficient of friction (CoF) and wear rate with Ball-on-(aluminum SAE 332) disc tribometer up to 0.5wt% of the nanoparticle: the best performances (e_COF = 92.29; e_WR = 79.53) came from Al₂O₃-castor oil nano lubricant and Al₂O₃-palm kernel oil; afterwards, they started to increase. However, the performance indices displayed irregular behaviour for both COF and Wear Rate (WR) when tested on a ball-on-low-carbon steel Disc Tribometer.

This study critically examines the implications of international transport corridor projects for Central Asian countries, focusing on the Western-backed Transport Corridor Europe-Caucasus-Asia (TRACECA), the Chinese initiative “One Belt—One Road”, and the International North-South Transport Corridor (INSTC) supported by the Russian Federation, India, and Iran. The analysis underscores the risks associated with Western projects, highlighting a need for a more explicit commitment to substantial infrastructure investments and persistent contradictions among key investors and beneficiaries. While the Chinese initiative presents significant benefits such as transit participation, infrastructure development, and economic investments, it also carries risks, notably an increased debt burden and potential monopolization by Chinese corporations. The study emphasizes that Central Asian countries, though indirect beneficiaries of INSTC, may not be directly involved due to geographical constraints. Study findings advocate for Central Asian nations to balance foreign investments, promote economic integration, and safeguard political and economic sovereignty. The study underscores the region’s wealth of natural and human resources, emphasizing the potential for increased demand for goods and services with improved living standards, strategically positioning these countries in the evolving global economic landscape.

The construction industry is responsible for over 40% of global energy consumption and one-third of global greenhouse gas emissions. Generally, 10%–20% of energy is consumed in the manufacturing and transportation stages of materials, construction, maintenance, and demolition. The way the construction industry to deal with these impacts is to intensify sustainable development through green building. The author uses the latest Green Building Certification Standard in Indonesia as the Green Building Guidelines under the Ministry of Public Works and People’s Housing (PUPR) Regulation No. 01/SE/M/2022, as a basis for evaluating existing office buildings or what is often referred to as green retrofit. Structural Equation Modeling-Partial Least Squares (SEM-PLS) is used by the authors to detail the factors influencing the application of green building by analyzing several variables related to the problem studied, which are used to build and test statistical models of causal models. From this study, it is concluded that the most influential factors in the implementation of green retrofitting on office buildings are energy savings, water efficiency, renewable energy use, the presence of green building socialization programs, cost planning, design planning, project feasibility studies, material cost, use of the latest technology applications, and price fluctuations. With the results of this research, there is expected to be shared awareness and concern about implementing green buildings and green offices as an initiative to present a more energy-efficient office environment, save operating costs, and provide comfort to customers.

A metaverse is an environment where humans interact socially and economically as avatars in cyberspace, which acts as a metaphor for the real world but without its physical or economic limitations. Many people use this new technology to connect with others, exchange content or discover new hobbies. Unlike other virtual worlds, the metaverse offers an online world that can be shaped. For the ports of the Spanish port system, it is intended to determine the new virtual port ecosystem that could be developed in the short term through an affinity diagram, which is a diagram that is used for the organization of ideas provided by a group on a complex problem that is held in a specific area, in this case reaching meta ports in the port system. The main conclusion is that to advance on this concept the new operating models and customers and services, are the blocks where the greatest efforts will have to be made.

In this study, we utilized a convolutional neural network (CNN) trained on microscopic images encompassing the SARS-CoV-2 virus, the protozoan parasite “plasmodium falciparum” (causing of malaria in humans), the bacterium “vibrio cholerae” (which produces the cholera disease) and non-infected samples (healthy persons) to effectively classify and predict epidemics. The findings showed promising results in both classification and prediction tasks. We quantitatively compared the obtained results by using CNN with those attained employing the support vector machine. Notably, the accuracy in prediction reached 97.5% when using convolutional neural network algorithms.

The 19th century proved to be one of the most complicated periods in Spanish history for the Spanish Crown, as it faced both internal conflicts—the French War of Independence—and external conflict—the independence of what were its territories in most of America. France did not remain indifferent to this and always had a clear idea of where to draw the boundaries of what “belonged” to it. Thus, amid the wave of independence movements in the Spanish colonies, the French continued to produce rich cartography to establish these boundaries and settle their power over the new nations that were arising after the period of revolutions. The cartography of Rigobert Bonne, the last cartographer of the French king and the Revolution Era, and one of its disciples, Eustache Hérisson, represent the perfect witness to the changes over the borders of the Spanish colonies during the change of the century. This study aims to analyze such cartography, examine the rich toponyms it offers, and examine the changes in the boundaries created over time between both empires. The main cartography we will rely on will be that of Bonne, one of the most important cartographers of the 18th century, and his disciple Hérisson, a geographer engineer, who lived through the onset of the conflicts and always prioritized the French perspective and the interests of their nation.