Uşak University is a university located in Uşak, Turkey. It was established in 2006.
This study presents a comprehensive literature review on spherical fuzzy sets and their generalizations, with a particular focus on their theoretical foundations and practical applications in decision-making problems. First, the theoretical concepts of spherical fuzzy sets are examined, followed by a systematic discussion of their main extensions proposed in the literature. Subsequently, aggregation operators commonly used in spherical fuzzy set environments are reviewed in detail. In addition, the study provides an overview of decision-making methodologies and weighting techniques frequently integrated with spherical fuzzy frameworks, including objective, subjective, and hybrid weighting approaches. Beyond the theoretical perspective, a large-scale bibliometric and methodological content analysis is conducted based on 225 articles indexed in the Web of Science database. These studies are analyzed with respect to publication trends, methodological preferences, aggregation operators, weighting methods, application areas, and citation performance. The results reveal dominant research patterns, frequently adopted methodological combinations, and emerging application areas, while also identifying gaps and underexplored directions for future research. By systematically synthesizing both theoretical developments and empirical trends, this review aims to serve as a valuable reference for researchers and practitioners working on spherical fuzzy sets and multi-criteria decision-making problems.
One of the main causes of environmental pollution is the exhaust emissions emitted from internal combustion engines. Currently, the use of rare elements such as platinum, palladium and rhodium in metal catalysts, which form part of exhaust purification systems, causes production difficulties and increased costs. Furthermore, these elements do not possess particle retention properties. This study aimed to determine whether geopolymer materials could be used as an innovative exhaust purification system in the automotive industry, given that porous geopolymer structures contain catalyst materials, are resistant to pressure and temperature, are easy and inexpensive to apply, and can be made from waste raw materials. In this study, newly developed aluminum-carbon-boron (5% Al2O3 and 1% activated carbon) doped emission treatment filter (also named as “AlCBDoF”) and zirconium-boron (5% ZrO2 and 5% Zr(SO4)2) doped emission treatment filter (also named as “ZrBDoF”) are developed and their effects on the diesel engine performance and emissions were investigated. The developed novel emission treatment filters and a standard catalytic converter of the diesel engine were separately installed in the exhaust after treatment line of a 4-cylinder diesel engine under different speeds and loads. When standard catalytic converter is used, HC emissions are improved by up to 48%, while HC emissions are reduced by 60% when AlCBDoF is used and 70% when ZrBDoF is utilized. The fact that the filter output values of the CO2 are higher than the filter input values shows that the filters are effective in CO2 conversion of CO emissions by acting as a catalyst. It has also been observed to demonstrate over 99% improvement in particulate matter. Therefore, the newly developed Boron Doped Filters can be used as a single device instead of both Diesel Oxidation Catalyst and Diesel Particulate Filter. In addition to improving exhaust emissions, it has been shown that the developed products are environmentally friendly system with the ability to utilize waste products and they can be used as innovative materials in exhaust emission control in the automotive industry.
The development model adopted by Latin American countries has been increasingly questioned due to the sustained deterioration of environmental quality. The region has experienced a significant increase in greenhouse gas (GHG) emissions associated with resource-intensive production structures. This study analyzes the impact of economic growth, governance quality, green energy, financial efficiency, human capital, and natural resource rents on total GHG emissions in seventeen Latin American economies during 1990–2021. Unlike research focused exclusively on carbon dioxide, this study uses total GHG emissions to more comprehensively capture regional environmental dynamics. The results confirm a long-term cointegration relationship in the presence of structural breaks, demonstrating the persistence of environmental pressures associated with structural factors. Quantile regressions based on moments identify a nonlinear, U-shaped relationship between economic growth and emissions, suggesting that the Environmental Kuznets Curve hypothesis does not hold for the region. Green energy does not fully replace fossil fuels, while institutional quality and human capital show heterogeneous impacts across the emissions distribution; in contrast, financial efficiency exhibits a mitigating effect. The results are robust under specifications that control for heterogeneity and cross-cutting dependencies. Consequently, achieving SDG 13 requires a structural transformation of the region’s production and energy matrix, as well as the integration of binding environmental criteria into natural resource governance.
The Caucasus region represents the northern edge of the Arabia–Eurasia continental collision and accommodates complex deformation involving crustal shortening, lateral block motion, and strike-slip faulting across multiple tectonic domains, including the Greater and Lesser Caucasus, the Kura Basin, and northwestern Iran block. Despite its tectonic significance, the spatial partitioning of present-day deformation and the role of vertical motions were not completely resolved. In this study, we present a comprehensive geodetic analysis of active deformation across Azerbaijan and the surrounding Caucasus region based on long-term continuous GNSS observations. Ten years (2014–2023) of data from 24 permanent GNSS stations were processed to derive a consistent Eurasia-fixed velocity field. To enhance spatial resolution, these new velocities were integrated with previously published regional GNSS solutions using a common reference frame and transformation strategy, resulting in a unified and unprecedented velocity field of 131 GNSS sites. Strain rates were estimated from the combined velocity field, and fault slip rates and block rotations were quantified through elastic block modeling. The horizontal velocity field indicates N-NE motion of 12 mm/yr relative to Eurasia, with pronounced eastward rotation and velocity increase toward the Caspian margin. Vertical deformation at regional scale with high accuracy, revealing coherent uplift of 4–5 mm/yr along the Greater Caucasus. Apart from the highest spatial resolution of deformation with 131 GNSS sites in the region, the sufficiently accurate vertical deformation rates are presented for the first time in the region through 24 permanent GNSS stations. Strain-rate and block modeling results demonstrate strong deformation partitioning, with thrust-dominated shortening concentrated along the Greater Caucasus and right-lateral strike-slip motion accommodating eastward escape along major fault systems. These results provide refined constraints on the kinematics of the Arabia–Eurasia collision in the Caucasus and offer important implications for regional tectonic evolution and seismic hazard assessment.
Although the importance of peer-to-peer tours is well-established in research, the academic community and destination planners have given limited attention to the aspect of memorable experiences in relation to tour performance. Addressing previous calls for research on this matter, this paper aims to explore memorable peer-to-peer local-guided experiences in the context of guide performance in a developing destination (Istanbul). For this purpose, a qualitative approach was employed in this research, utilizing reviews posted by travelers on a peer-to-peer platform. A total of 2,956 narratives, regarding thirty-nine local guides, were included in the data analysis, representing travelers' overall memorable experiences. The analysis revealed five key components: cultural connection, travel companionship, crowd avoidance, personalized experience, social interaction, and challenges in peer-to-peer interactions. This paper provides significant insight for the stakeholders involved in the development of local guiding, as well as for academics seeking to structure their research logic on peer-to-peer guiding services.
