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Found 5157 publications
Corrigendum to “Global trade of medicinal and aromatic plants. A review” [J. Agricult. Food Res. 21 (2025) 101910] (Journal of Agriculture and Food Research (2025) 21, (S2666154325002819), (10.1016/j.jafr.2025.101910))
Publication Name: Journal of Agriculture and Food Research
Publication Date: 2025-08-01
Volume: 22
Issue: Unknown
Page Range: Unknown
Description:
The authors regret We recently reviewed the published version of our article “Global trade of medicinal and aromatic plants: A review” and noticed an error in the units reported in Figs. 1, 3 and 4. Specifically, in the columns related to export and import values, the unit was incorrectly labelled as “million” instead of “thousand". The authors would like to apologise for any inconvenience caused.
Open Access: Yes
Adaptive Sign Language Recognition for Deaf Users: Integrating Markov Chains with Niching Genetic Algorithm
Publication Name: AI Switzerland
Publication Date: 2025-08-01
Volume: 6
Issue: 8
Page Range: Unknown
Description:
Sign language recognition (SLR) plays a crucial role in bridging the communication gap between deaf individuals and the hearing population. However, achieving subject-independent SLR remains a significant challenge due to variations in signing styles, hand shapes, and movement patterns among users. Traditional Markov Chain-based models struggle with generalizing across different signers, often leading to reduced recognition accuracy and increased uncertainty. These limitations arise from the inability of conventional models to effectively capture diverse gesture dynamics while maintaining robustness to inter-user variability. To address these challenges, this study proposes an adaptive SLR framework that integrates Markov Chains with a Niching Genetic Algorithm (NGA). The NGA optimizes the transition probabilities and structural parameters of the Markov Chain model, enabling it to learn diverse signing patterns while avoiding premature convergence to suboptimal solutions. In the proposed SLR framework, GA is employed to determine the optimal transition probabilities for the Markov Chain components operating across multiple signing contexts. To enhance the diversity of the initial population and improve the model’s adaptability to signer variations, a niche model is integrated using a Context-Based Clearing (CBC) technique. This approach mitigates premature convergence by promoting genetic diversity, ensuring that the population maintains a wide range of potential solutions. By minimizing gene association within chromosomes, the CBC technique enhances the model’s ability to learn diverse gesture transitions and movement dynamics across different users. This optimization process enables the Markov Chain to better generalize subject-independent sign language recognition, leading to improved classification accuracy, robustness against signer variability, and reduced misclassification rates. Experimental evaluations demonstrate a significant improvement in recognition performance, reduced error rates, and enhanced generalization across unseen signers, validating the effectiveness of the proposed approach.
Open Access: Yes
DOI: 10.3390/ai6080189
Localization robustness improvement for an autonomous race car using multiple extended Kalman filters
Publication Name: Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Publication Date: 2025-08-01
Volume: 239
Issue: 9
Page Range: 3771-3783
Description:
In this paper, we introduce a vehicle localization method designed for the SZEnergy race car, which competes in the Shell Eco-marathon. The proposed method comprises four different extended Kalman filter-based localization algorithms and a selection algorithm that determines the most suitable one based on vehicle speed, GNSS availability, and signal quality. The low-speed Kalman filters are based on a kinematic vehicle model while the high-speed variants are based on a dynamic vehicle model. Several measurements were performed during test maneuvers to evaluate the performance of the filters. The proposed method succesfully handles sensor miscalibration and GNSS outages.
Open Access: Yes
Exploring Generation Z’s Acceptance of Artificial Intelligence in Higher Education: A TAM and UTAUT-Based PLS-SEM and Cluster Analysis
Publication Name: Education Sciences
Publication Date: 2025-08-01
Volume: 15
Issue: 8
Page Range: Unknown
Description:
In recent years, the rapid growth of artificial intelligence (AI) has significantly transformed higher education, particularly among Generation Z students who are more open to new technologies. Tools such as ChatGPT are increasingly being used for learning, yet empirical research on their acceptance, especially in Hungary, is limited. This study aims to explore the psychological, technological, and social factors that influence the acceptance of AI among Hungarian university students and to identify different user groups based on their attitudes. The methodological novelty lies in combining two approaches: partial least-squares structural equation modelling (PLS-SEM) and cluster analysis. The survey, based on the TAM and UTAUT models, involved 302 Hungarian students and examined six dimensions of AI acceptance: perceived usefulness, ease of use, attitude, social influence, enjoyment and behavioural intention. The PLS-SEM results show that enjoyment (β = 0.605) is the strongest predictor of the intention to use AI, followed by usefulness (β = 0.167). All other factors also had significant effects. Cluster analysis revealed four groups: AI sceptics, moderately open users, positive acceptors, and AI innovators. The findings highlight that the acceptance of AI is shaped not only by functionality but also by user experience. Educational institutions should, therefore, provide enjoyable and user-friendly AI tools and tailor support to students’ attitude profiles.
Open Access: Yes
Blockchain and Smart Cities: Co-Word Analysis and BERTopic Modeling
Publication Name: Smart Cities
Publication Date: 2025-08-01
Volume: 8
Issue: 4
Page Range: Unknown
Description:
Highlights: What are the main findings? Blockchain plays a foundational role in supporting secure, interoperable infrastructure for key urban services, particularly through integration with IoT, edge computing, and smart contracts. Research has shifted from general blockchain exploration to sector-specific applications, including decentralized healthcare, energy trading, smart mobility, and drone coordination. What is the implication of the main finding? Blockchain enables cross-sectoral innovation in smart cities by enhancing transparency, data integrity, and trust across complex urban systems. As both a technological and ethical infrastructure, blockchain supports the development of secure, resilient, and sustainable smart city ecosystems aligned with Industry 5.0 values. This paper explores the intersection of blockchain technology and smart cities to support the transition toward decentralized, secure, and sustainable urban systems. Drawing on co-word analysis and BERTopic modeling applied to the literature published between 2016 and 2025, this study maps the thematic and technological evolution of blockchain in urban environments. The co-word analysis reveals blockchain’s foundational role in enabling secure and interoperable infrastructures, particularly through its integration with IoT, edge computing, and smart contracts. These systems underpin critical urban services such as transportation, healthcare, energy trading, and waste management by enhancing data privacy, authentication, and system resilience. The application of BERTopic modeling further uncovers a shift from general technological exploration to more specialized and sector-specific applications. These include real-time mobility systems, decentralized healthcare platforms, peer-to-peer energy exchanges, and blockchain-enabled drone coordination. The results demonstrate that blockchain increasingly supports cross-sectoral innovation, enabling transparency, trust, and circular flows in urban systems. Overall, the current study identifies blockchain as both a technological backbone and an ethical infrastructure for smart cities that supports secure, adaptive, and sustainable urban development.
Open Access: Yes
Service Difficulties, Internal Resolution Mechanisms, and the Needs of Social Services in Hungary—The Baseline of a Development Problem Map
Publication Name: Social Sciences
Publication Date: 2025-08-01
Volume: 14
Issue: 8
Page Range: Unknown
Description:
This study focuses on the current service/care difficulties and challenges that social institutions in Hungary are facing during their daily operations; how they can react to them utilizing their internal resources, mechanisms, and capacities; and what concrete, tangible needs and demands are emerging in terms of methodological professional support, potential forms, interventions, and direction for professional development. A total of 24 general and 55 specific service and operational problems were identified and assessed in eight different service areas (family and child welfare services, family and child welfare centers, respite care for children, care for the homeless, addiction intervention, care for people with disabilities, care for psychiatric patients, specialized care for the elderly, and basic services for the elderly). The empirical base of the study uses a database of 201 online questionnaires completed by a professional target group working for social service providers in two counties (Győr-Moson-Sopron and Veszprém), representing 166 social service providers. The questionnaires were completed between November and December of 2022. The findings will be used to develop a professional support and development problem map. Social institutions face complex and serious service/care difficulties and challenges in their daily operations. Three distinctive basic problems clearly stand out in both severity and significance from the complex set of factors assessed. The biggest problem in the social care system is clearly the complex challenge of low wages, followed by the administrative burdens in the ranking of operational difficulties, and the third key factor was the psycho-mental workload of staff.
Open Access: Yes
Utilizing Different Crop Rotation Systems for Agricultural and Environmental Sustainability: A Review
Publication Name: Agronomy
Publication Date: 2025-08-01
Volume: 15
Issue: 8
Page Range: Unknown
Description:
Monoculture involves growing the same crop on the same land over at least two crop cycles. Continuous monoculture can increase the population density of pests and pathogens over time, thereby reducing agricultural yields and increasing dependence on chemical inputs. Crop rotation is an agricultural practice that involves systematically and sequentially planting different crops in the same field over multiple growing seasons. This review explores the advantages of crop rotation and its contribution to promoting sustainable farming practices, such as legume integration and cover cropping. It is based on a thematic literature review of peer-reviewed studies published between 1984 and 2025. We found that crop rotation can significantly improve soil structure and organic matter content and enhance nutrient cycling. Furthermore, soil organic carbon increased by up to 18% when legumes were included in rotations compared to monoculture systems in Europe, while also mitigating greenhouse gas emissions, enhancing carbon sequestration, and decreasing nutrient leaching and pesticide runoff. Farmers can adopt several strategies to optimise crop rotation benefits, such as diversification of various crops, legume integration, cultivation of cover crops, and rotational grazing. These practices ensure agricultural sustainability and food security and support climate resilience.
Open Access: Yes
Water Insecurity and Development Cooperation: Hungary’s Engagement in Africa
Publication Name: Grassroots Journal of Natural Resources
Publication Date: 2025-08-01
Volume: 8
Issue: 2
Page Range: 1-27
Description:
The Sustainable Development Report 2023 showed that 2.2 billion people lacked access to safely managed drinking water in 2022, with 703 million unable to access even basic services. In addition to this, the Afrobarometer’s 2024 survey indicated that Sub-Saharan Africa water supply was ranked among the top governance challenges in 39 surveyed countries. This study explores regional and urban–rural disparities in access to drinking water, while also assessing the scope and geography of Hungary’s water-related development cooperation on the continent. The methodology combines quantitative indicators from the UNICEF–WHO Joint Monitoring Programme with geospatial visualization techniques. The analysis reveals substantial inequalities in rural Eastern Africa, over 97 million people rely on surface water or unimproved sources, while Middle Africa reports more than 55 million in the same categories. In contrast, urban areas in Northern Africa show significantly better outcomes, with over 111 million having access to safely managed drinking water. These figures highlight persistent spatial divides and the critical need for targeted investment in rural service provision. Hungarian development engagement was examined through project records from the Ministry of Foreign Affairs and Trade, alongside publicly available data from Hungarian NGOs and private sector actors. The study finds that Hungary has contributed to water-related initiatives in countries such as the Democratic Republic of the Congo, Ghana, and Uganda, but has had limited involvement in other severely affected countries, including Niger (31% unsafe access), Madagascar (42%), and the Central African Republic (37%). This study addresses a significant research gap since the intersection of Hungarian development cooperation and African water security has received minimal scholarly attention to date. By offering a comprehensive, data-driven analysis of both African water access and Hungary’s related foreign engagement, the research contributes to the understanding of potential synergies and future avenues for international collaboration in this field.
Open Access: Yes
Synergistic Effects of CuO and ZnO Nanoadditives on Friction and Wear in Automotive Base Oil †
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-08-01
Volume: 15
Issue: 15
Page Range: Unknown
Description:
Efficient lubrication lowers friction, wear, and energy losses in automotive drivetrain components. Advanced lubricants are key to sustainable transportation performance, durability, and efficiency. This study analyzes the tribological performance of Group III base oil with CuO and ZnO nanoadditive mixtures. These additives enhance the performance of Group III base oils, making them highly relevant for automotive lubricant applications. An Optimol SRV5 tribometer performed ball-on-disk sliding contact tests with 100Cr6 steel specimens subjected to a 50 N force and a temperature of 100 °C. The test settings are designed to mimic the boundary and mixed lubrication regimes commonly seen in the automobile industry. During the tests, the effect of nanoparticles on friction was measured. Microscopic wear analysis was performed on the worn specimens. The results demonstrate that adding 0.3 wt% CuO nanoparticles to Group III base oil achieves a 19% reduction in dynamic friction and a 47% decrease in disk wear volume compared to additive-free oil. Notably, a 2:1 CuO-to-ZnO mixture produced synergy, delivering up to a 27% friction reduction and a 54% decrease in disk wear. The results show the synergistic effect of CuO and ZnO in reducing friction and wear on specimens. This study highlights the potential of nanoparticles for lubricant development and automotive applications.
Open Access: Yes
DOI: 10.3390/app15158258
