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.

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.

Tourism experiences are inherently multisensory, engaging visitors’ senses of sight, sound, smell, taste, and touch. This study addresses the gap in literature by investigating the impact of visual and auditory landscapes on tourist emotions and behaviors within coastal tourism settings, using the Stimulus-Organism-Response (SOR) model. Data collected from tourists in Sanya, China, were analyzed using structural equation modeling. The results indicate that both visualscape and soundscape significantly influence tourist emotions (pleasure and arousal) and subsequent loyalty. Pleasure and arousal mediate the relationships between environmental stimuli and tourist loyalty, emphasizing their roles as emotional bridges between the environment and behaviors. These findings highlight the importance of integrating local cultural and community elements into tourism to enhance socio-economic benefits and ensure sustainable development. By fostering a deep connection between tourists and the local environment, these sensory experiences support the preservation of cultural heritage and promote sustainable tourism practices, aligning with the goals of economic development and public policy. The study contributes to the theoretical understanding of multisensory tourism by integrating the SOR model in coastal tourism and emphasizes the roles of visual and auditory stimuli. Practically, it provides insights for tourism managers to improve tourist experiences and loyalty through careful management of sensory elements. This has implications for infrastructure development, particularly in enhancing the quality of soft infrastructure such as cultural and social systems, which are crucial for sustainable tourism and community well-being. Future research could include additional sensory dimensions and diverse destinations for a comprehensive understanding of sensory influences on tourist behaviors and emotions. This research aligns with the broader goals of the policy and development by addressing critical aspects of infrastructure and socio-economic development within the tourism sector.