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Found 6289 publications
Controlled Fuzzy 2-Metric Spaces: A Soft Computing Framework with Dynamic Applications
Publication Name: International Journal of Analysis and Applications
Publication Date: 2026-01-01
Volume: 24
Issue: Unknown
Page Range: Unknown
Description:
In this article, we introduce the concept of a controlled fuzzy 2-metric space, formulated by incorporating three control functions that flexibly regulate the fuzzy distance relationships among triplets of points. This structure provides a flexible analytical tool for modeling systems influenced by uncertainty, interdependence, and approximate reasoning. We establish several fundamental properties of this structure and derive fixed-point results. To demonstrate its practical relevance, we apply the proposed framework to a dynamic market-equilibrium problem, in which agents’ interactions are governed by fuzzy relations and control-dependent adjustments. The study also discusses implications for soft computing and decision-making systems, highlighting the framework’s potential in modeling adaptive and uncertain environments.
Open Access: Yes
Explainable artificial intelligence in finance: a bibliometric and topic modeling analysis using BERTopic
Publication Name: Quality and Quantity
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
This study investigates the evolving intersection of explainable artificial intelligence (XAI) and the financial sector. It explores how machine learning models’ transparency and interpretability shape decision-making processes in areas such as credit scoring, risk assessment, and market prediction. While conventional AI methods often function as opaque black boxes, XAI offers a solution to promote model accountability, fairness, and trust, which are critical factors in highly regulated and risk-sensitive financial environments. Drawing on 90 peer-reviewed articles retrieved from Scopus and Web of Science, this research applies both co-word analysis and BERTopic modeling to uncover major research themes and semantic structures within the relevant literature. The co-word network reveals distinct thematic clusters related to explainable credit risk models, interpretability in financial forecasting, and the integration of environmental, social, and governance (ESG) factors into AI-driven financial analysis. Meanwhile, topic modeling uncovers additional topics, including SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME)-based explainability techniques, human-AI collaboration in decision-making, and explainable deep learning for asset pricing and sovereign risk analysis. A temporal analysis of publication trends indicates increasing scholarly attention to transparency in AI in the wake of regulatory pressure and ethical considerations in finance. The findings point to a growing emphasis on embedding interpretability into AI models to support fairness, regulatory compliance, and better-informed financial judgments. This study contributes to both academic discourse and practical application by offering a detailed map of current XAI research in finance and identifying key directions for future inquiry and technological development.
Open Access: Yes
The long-term impact of COVID-19 on the physical activity, motor fitness, and maximum heart rate values of female university students
Publication Name: Biomedical Human Kinetics
Publication Date: 2026-01-01
Volume: 18
Issue: 1
Page Range: 12-23
Description:
Aim: This study examined the relationship between COVID-19 and the maximum heart rate (HRmax ) achieved by female university students during maximal physical effort. It also analyzed how participants’ physical activity (PA) levels and anthropometric and physiological characteristics were related to HRmax 10 months after the World Health Organization (WHO) declared that COVID-19 was no longer a Public Health Emergency of International Concern. Materials and methods: Eighty-two female university students aged 19.0–28.0 years (21.23 ± 1.57) were assigned to three groups: G1 – 40 healthy participants, G2 – 29 participants with confirmed COVID-19, and G3 – 13 participants previously hospitalized due to COVID-19. Body composition was evaluated by bioelectrical impedance analysis. PA was assessed with the International Physical Activity Questionnaire, and HRmax was measured during the 12-min Cooper test performed on a rowing ergometer. Results: Healthy students (G1 ) showed the highest PA levels, followed by groups G2 and G3 . Group G1 also exhibited more favorable body composition, with lower values of body mass, body mass index, waist-to-hip ratio, visceral fat, fat mass, fat-free mass, and skeletal muscle mass (p < 0.001). Maximum heart rate was highest in group G1 (175 beats per minute, bpm) and exceeded the values noted in groups G2 and G3 by 7 and 15 bpm, respectively (p = 0.028). Conclusions: Female students hospitalized due to COVID-19 had lower PA levels, reduced motor fitness, and worse body composition, which may explain their lower HRmax values observed 10 months after the pandemic.
Open Access: Yes
Innovative Use of Concrete Canvas for Reinforcing Railway Substructures: Enhancing Load-Bearing Capacity and Stability
Publication Name: Acta Polytechnica Hungarica
Publication Date: 2026-01-01
Volume: 23
Issue: 1
Page Range: 71-90
Description:
This study investigates the application of Geosynthetic Cementitious Composite Mats (GCCMs), specifically Concrete Canvas (CC), to reinforce railway substructures. Combining waterproofing, durability, and ease of installation, CC addresses challenges in ballasted railway tracks, such as local failures, moisture, and dynamic forces. The research fills a gap in the literature on CC's dynamic performance and its comparison to geogrids. Experimental methods, including shear box and static plate load tests, revealed that CC increases load-bearing capacity by up to 72% and improves shear resistance through its semi-rigid interlocking mechanism. Robust under dynamic forces, CC ensures stability without deformation. Compared to geogrids, CC offers similar reinforcement, with added benefits like easier hydration and installation. The study concludes that CC is a cost-effective solution for reinforcing railway substructures and improving load distribution and stability. Future research should address environmental impact and integration with advanced materials for enhanced performance and sustainability.
Open Access: Yes
Greening the future: assessing the influence of technological innovation, energy transition and financial globalization on ecological footprint in selected emerging countries
Publication Name: Environment Development and Sustainability
Publication Date: 2026-01-01
Volume: 28
Issue: 1
Page Range: 2105-2131
Description:
Environmental dangers have escalated due to human ecological pressure during the past few decades. This pressure can be measured by the environmental footprint (EFT) that humanity has left behind. At this point, the most effective methods for achieving sustainable development without causing damage to the environment include green technological innovation (TCH), climatic technology (CLT), energy transition (ENT), financial globalization (FGL), and economic growth. In light of this, the primary purpose of this research is to examine the impact of economic development, TCH, CLT, ENT, and FGL, as well as economic growth on the EFT in a selection of rising countries between the years 1990 and 2021. We use a unique DOLS and FMOLS model to analyze the relationships between the variables. In addition, the MMQR model is utilized in our research to validate the results produced using the DOLS and FMOLS methodologies. Through a reduction in the EFP, the findings indicate that TCH, CLT, and ENT all contribute significantly to an improvement in the quality of the environment. On the contrary, FGL, economic expansion, and urbanization all have a significant positive impact on EFT and contribute to climate degradation. Last but not least, the MMQR model's outcomes also demonstrated that TCH, CLT, ENT, FGL, urbanization, and economic expansion cause EFT. Based on the findings, it is recommended that governments and policymakers encourage investments in green innovation and renewable energy industries to attain ecological sustainability.
Open Access: Yes
Evaluating Lighting and Cognitive Safety at Pedestrian Crossings: A Hungarian Case Study
Publication Name: Lecture Notes in Networks and Systems
Publication Date: 2026-01-01
Volume: 1768 LNNS
Issue: Unknown
Page Range: 106-111
Description:
This study investigates how lighting quality and emerging intelligent technologies influence pedestrian safety at designated crossings, with particular focus on cognitive aspects of perception, decision-making, and situational awareness. The aim is twofold: to evaluate whether existing crossings in Hungary meet established lighting standards and to explore how adaptive, sensor driven systems can enhance cognitive safety. Field measurements were conducted at 14 non-signalized crossings in three Hungarian cities—Veszprém, Budapest (District 22), and Békéscsaba—following the MSZ EN 13201 protocol. Accident data from the national WEB-BAL database guided site selection, emphasizing high-risk nighttime locations. Results reveal that only five sites met both recommended thresholds of 20 lx average illuminance and 0.4 uniformity, with poor waiting-area lighting and asymmetrical designs as recurring deficiencies. The study further highlights the potential of adaptive LED systems and smart crosswalk technologies (e.g., SafeCross, SafeXOne) to reduce cognitive load and improve pedestrian visibility. The findings demonstrate that beyond compliance with lighting standards, cognitively responsive infrastructure—integrating intelligent, adaptive solutions—is essential for creating safer pedestrian environments at night.
Open Access: Yes
A new species and a new record of Bensonella Pilsbry & Vanatta, 1900 (Gastropoda: Eupulmonata: Hypselostomatidae) from Lao Cai province, Vietnam
Publication Name: Raffles Bulletin of Zoology
Publication Date: 2026-01-01
Volume: 74
Issue: Unknown
Page Range: 31-36
Description:
In this work, a new species of Bensonella, B. didoi, is described from Lao Cai province in northern Vietnam. The new species is compared to all similar congeners and is characterised by the whitish, nearly conical shell with nine apertural barriers and a very narrow umbilicus. Following this work, the number of Bensonella species known from Vietnam becomes three, distributed in Lao Cai and Son La provinces. Additionally, B. boettgeri (Möllendorff, 1897) is reported for the first time from Vietnam, extending the distribution of the species eastwards.
Open Access: Yes
Legal Risk Assessment of Re-using Building Materials and Elements in Historic Structures
Publication Name: Rilem Bookseries
Publication Date: 2026-01-01
Volume: 64
Issue: Unknown
Page Range: 2952-2962
Description:
Construction processes intensively contributes to greenhouse gas emissions worldwide. The resulting climate change affects historic buildings and complicates built heritage preservation. However, there are several actions under way, such as the European Green Deal, to reduce CO2 emissions in construction. Revaluation of existing structures under application of recycled materials and by re-use of available building elements may save resources and thus reduces emission of CO2 in construction industry. This contributes to a more environmentally friendly construction process. Furthermore, re-using of existing building materials or elements may preserve the historical appearance of structures, in the interest of future generations. For production and usage of new building materials and elements, a plethora of legislation and codes needs to be considered. The same applies to re-use of existing building materials and elements which increases the danger for construction defects and thus expensive claims. Thus, beside the advantages, re-using of building materials and elements bears risks to all stakeholders in a construction project. In the interest of avoiding conflicts between the construction contract parties, a legal risk analysis is necessary to support them in decision about the re-use of existing building materials and elements. The authors examined current international, European and German law, codes, and policy dealing with re-use of building materials and elements. Furthermore, they reviewed existing literature about that topic and analyzed relevant court cases of the last twenty years. The conclusion is, that there is a need for a detailed contract specification which kind of existing building elements and materials can be re-used and who takes the responsibility for known or unknown defects under the aspect of liability. The paper provides suggestions under which legal aspects a re-use of building elements may be recommendable and which requirements need to be met.
Open Access: Yes
Rainfall–Groundwater Correlations Using Statistical and Spectral Analyses: A Case Study on the Coastal Plain of Al-Hsain Basin, Syria
Publication Name: Hydrology
Publication Date: 2026-01-01
Volume: 13
Issue: 1
Page Range: Unknown
Description:
Climate change and irregular precipitation patterns have increasingly threatened groundwater sustainability in semi-arid regions like the Eastern Mediterranean. Specifically, in coastal Syria, the lack of quantitative understanding regarding aquifer recharge mechanisms hinders effective water resource management. To address this, this study investigates the dynamic relationship between rainfall and groundwater levels in the Al-Hsain Basin coastal plain using 48 months of monitoring data (2020–2024) from 35 wells. We employed a unified analytical framework combining statistical methods (correlation, regression) with advanced time–frequency techniques (Wavelet Coherence) to capture recharge behavior across diverse Quaternary, Neogene, and Cretaceous strata. The results indicate strong climatic control on groundwater dynamics, particularly in shallow Quaternary wells, which exhibit rapid recharge responses (lag < 1 month). In contrast, deeper aquifers showed delayed and buffered responses. A dual-variable model incorporating temperature significantly improved prediction accuracy (R2 = 0.97), highlighting the role of evapotranspiration. These findings provide a transferable diagnostic framework for identifying recharge zones and supporting adaptive groundwater governance in data-scarce semi-arid environments.
Open Access: Yes
