This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.

Naturally occurring radionuclides can be categorized into two main groups: primordial and cosmogenic, based on their origin. Primordial radionuclides stem from the Earth’s crust, occurring either individually or as part of decay chains. Conversely, cosmogenic radionuclides originate from extraterrestrial sources such as space, the sun, and nuclear reactions involving cosmic radiation and the Earth’s atmosphere. Gamma-ray spectrometry is a widely employed method in Earth sciences for detecting naturally occurring radioactive materials (NORM). Its applications vary from environmental radiation monitoring to mining exploration, with a predominant focus on quantifying the content of uranium (U), thorium (Th), and potassium (K) in rocks and soils. These elements also serve as tracers in non-radioactive processes linked to NORM paragenesis. Furthermore, the heat generated by radioactive decay within rocks plays a pivotal role in deciphering the Earth’s thermal history and interpreting data concerning continental heat flux in geophysical investigations. This paper provides a concise overview of current analytical and measuring techniques, with an emphasis on state-of-the-art mass spectrometric procedures and decay measurements. Earth scientists constantly seek information on the chemical composition of rocks, sediments, minerals, and fluids to comprehend the vast array of geological and geochemical processes. The historical precedence of geochemists in pioneering novel analytical techniques, often preceding their commercial availability, underscores the significance of such advancements. Geochemical analysis has long relied on atomic spectrometric techniques, such as X-ray fluorescence spectrometry (XRFS), renowned for its precision in analyzing solid materials, particularly major and trace elements in geological samples. XRFS proves invaluable in determining the major constituents of silicate and other rock types. This review elucidates the historical development and methodology of these techniques while showcasing their common applications in various geoscience research endeavors. Ultimately, this review aims to furnish readers with a comprehensive understanding of the fundamental concepts and potential applications of XRF, HPGes, and related technologies in geosciences. Lastly, future research directions and challenges confronting these technologies are briefly discussed.

Oil spill clean-up is a long-standing challenge for researchers to prevent serious environmental pollution. A new kind of oil-absorbent based on silicon-containing polymers (e.g., poly(dimethylsiloxane) (PDMS)) with high absorption capacity and excellent reusability was prepared and used for oil-water separation. The PDMS-based oil absorbents have highly interconnected pores with swellable skeletons, combining the advantages of porous materials and gels. On the other hand, polymer/silica composites have been extensively studied as high-performance functional coatings since, as an organic/inorganic composite material, they are expected to combine polymer flexibility and ease of processing with mechanical properties. Polymer composites with increased impact resistance and tensile strength without decreasing the flexibility of the polymer matrix can be achieved by incorporating silica nanoparticles, nanosand, or sand particles into the polymeric matrices. Therefore, polymer/silica composites have attracted great interest in many industries. Some potential applications, including high-performance coatings, electronics and optical applications, membranes, sensors, materials for metal uptake, etc., were comprehensively reviewed. In the first part of the review, we will cover the recent progress of oil absorbents based on silicon-containing polymers (PDMS). In the later details of the review, we will discuss the recent developments of functional materials based on polymer/silica composites, sand, and nanosand systems.

In higher eukaryotes, the genes’ architecture has become an essential determinant of the variation in the number of transcripts (expression level) and the specificity of gene expression in plant tissue under stress conditions. The modern rise in genome-wide analysis accounts for summarizing the essential factors through the translocation of gene networks in a regulatory manner. Stress tolerance genes are in two groups: structural genes, which code for proteins and enzymes that directly protect cells from stress (such as genes for transporters, osmo-protectants, detoxifying enzymes, etc.), and the genes expressed in regulation and signal transduction (such as transcriptional factors (TFs) and protein kinases). The genetic regulation and protein activity arising from plants’ interaction with minerals and abiotic and biotic stresses utilize high-efficiency molecular profiling. Collecting gene expression data concerning gene regulation in plants towards focus predicts an acceptable model for efficient genomic tools. Thus, this review brings insights into modifying the expression study, providing a valuable source for assisting the involvement of genes in plant growth and metabolism-generating gene databases. The manuscript significantly contributes to understanding gene expression and regulation in plants, particularly under stress conditions. Its insights into stress tolerance mechanisms have substantial implications for crop improvement, making it highly relevant and valuable to the field.

Public-Private Partnerships (PPPs) are mostly presented as a means to introduce efficient procurement methods and better value for money to taxpayers. However, the complexity of the PPP mechanism, their lack of transparency, accounting rules and implicit liabilities make it often impossible to perceive the amount of public expenditure involved and the long-run impact on taxpayers, providing room for fiscal illusion, i.e., the illusion that PPPs are much less expensive than traditional public investments. This psaper, thanks to a systematic review of the literature on the EU countries experience, tries to unveil the sources of this illusion by looking at the reasons behind the PPPs’ choice, their real costs, and the sources of fiscal risks. The literature suggests that PPPs are more costly than public funding, especially when contingent liabilities are not taken into account, and are employed as mechanisms to circumvent budgetary restrictions and to spend off-balance. The paper concludes that the public sector should share more risks with private sectors by reducing the amount of guarantees, and should prevent governments from operating through a sleight of hand that deflects attention away from off-balance financing, by applying a neutral fiscal recording system.

Six Sigma is an organized and systematic method for strategic process improvement that relies on statistical and scientific methods to reduce the defect rates and achieve significant quality up-gradation. Six Sigma is also a business philosophy to improve customer satisfaction, a tool for eliminating process variation and errors and a metric of world class companies allowing for process comparisons. Six Sigma is one of the most effective advanced improvement strategies which has direct impact on operational excellence of an organization. Six Sigma may also be defined as the powerful business strategies, which have helped to improve quality initiatives in many industries around the world. With the use of Six Sigma in casting industries, rejection rate is reduced, customer satisfaction is improved and financial benefits also increased. Six Sigma management uses statistical process control to relentlessly and rigorously pursue the reduction of variation in all critical processes to achieve continuous and breakthrough improvements that impact the bottom-line and/or top-line of the organization and increase customer satisfaction. In this paper author reviewed some of the significant previous published papers and focused on the general overview of publication in casting industries.