Prepolymers containing isocyanates must be prevented from curing when exposed to moisture, which can be achieved by blocking the isocyanate groups with a suitable agent. The study carefully examines several blocking agents, including methyl ethyl ketoxime (MEKO), caprolactam, and phenol, and concludes that methyl ethyl ketoxime is the best choice. Spectroscopic and thermal analyses, as well as oven curing studies, are conducted with various blocking agents and isocyanate prepolymer to castor oil ratios, revealing MEKO to be the most effective blocking agent which gets unblocked at higher temperatures.

The aim of this research is to explore the relationship between remuneration, job satisfaction, and employee performance. Remuneration, in this context, refer to a system synchronization that is based on performance appraisal result. In this, regard, the research employed a descriptive quantitative method, with a population comprising all University of Padjadjaran lecturers which were a total of 2,090. Furthermore, in order to gather the research sample, a probability sampling technique was employed. This technique was selected because of its reputation as the most general strategic sampling technique in quantitative research to achieve representativeness (1). The obtained result showed that there was a positive and significant relationship between the remuneration and job satisfaction of lecturers in University of Padjadjaran. Accordingly, a significant value of 0.000 < 0.05 and a t-count value of 19.330 > 1.95 was observed, meaning the H1 hypothesis in this research was accepted. It is also expedient to acknowledge that a positive and significant relationship was found between job satisfaction and the performance of the lecturers in study area. For this relationship, a significant value of 0.010 < 0.05 and a t-count value of 5.676 > 1.95 was found. These findings led to the acceptance of the H2 hypothesis proposed in this research. Similarly, the relationship between remuneration and the performance of the observed lecturers was found to be positive and significant. The observed significant value in this regard was 0.000 < 0.05 and the t-count value was 4.057 > 1.95, indicating that H3 hypothesis was also accepted. Lastly, the relationship between remuneration and employee performance mediated by job satisfaction of lecturer in University of Padjadjaran was explored, and it was found to also be positive and significant, with a significant value of 0.000 < 0.05 and a t-count value of 5.429 > 1.95. This indicated that the H4 hypothesis proposed in the research was accepted.

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.

A smart city focuses on enhancing and interconnecting facilities and services through digital technology to offer convenient services for both people and businesses. The basic infrastructure of smart cities consists of modern technologies such as the Internet of Things (IoT), cloud computing and artificial intelligence. These urban areas utilize different networks, such as the Internet and IoT, to share real-time information, improving convenience for the inhabitants. However, the reliance of smart cities on modern technologies exposes them to a range of organized, diverse, and sophisticated cyber threats. Therefore, prioritizing cybersecurity awareness and implementing appropriate measures and solutions are essential to protect the privacy and security of citizens. This study aims to identify cyber threats and their impact on smart cities, as well as the methods and measures required for key areas such as smart government, smart healthcare, smart mobility, smart environment, smart economy, smart living, and smart people. Furthermore, this study seeks to evaluate previous research in this field, establish necessary policies to mitigate these threats, and propose an appropriate model for the infrastructure associated with IT networks in smart cities.

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.