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Found 6342 publications
Cultural Fault Lines and Development Trajectories in East-Central Europe
Publication Name: Engineering Perspective
Publication Date: 2025-12-28
Volume: 5
Issue: Special Issue
Page Range: 37-44
Description:
This paper explores the divergent developmental trajectories of East-Central European countries by examining the cultural fault lines between Western (European) and Orthodox (Slavic/Russian) civilizations. The study assesses how these civilizational backgrounds have influenced economic performance, governance structures, social trust, labor market dynamics, and institutional development since the fall of communism. The analysis uses a comparative cross-country design based on secondary data from international sources. Countries are classified according to the cultural models of Huntington, De Blij & Muller, and Fellmann et al. A set of macroeconomic and societal indicators—including GDP per capita, Global Innovation Index rankings, labor force characteristics, and trust levels—is examined to identify patterns of divergence and convergence across cultural blocs. The results show that Western-aligned countries generally perform better economically and exhibit higher levels of social trust and institutional stability. At the same time, the relationship between culture and development is not deterministic. Several Orthodox countries demonstrate notable progress, indicating that integration dynamics, policy choices, and governance quality also play significant roles. The research offers an interdisciplinary perspective that connects cultural theory with observable economic and political outcomes. It contributes to a deeper understanding of how historical-cultural legacies shape developmental potential in East-Central Europe and provides insights for regional policy design, institutional reform, and future growth strategies.
Open Access: Yes
Testing the Real Capacity of the Battery
Publication Name: Engineering Perspective
Publication Date: 2025-12-28
Volume: 5
Issue: 1 Special Issue
Page Range: 1-7
Description:
As electric motoring becomes more and more widespread, it is important to develop appropriate diagnostic measurements, especially for the increased electrical system. The most important part of the electrical system is the high voltage lithium-ion battery. Monitoring battery condition is essential to avoid failures and extend battery life, as these batteries degrade over time depending on the number of cycles, operating temperature, and charging habits. The project presented the contactless diagnostics of a Volkswagen e-Golf lithium-ion battery and analyze its capacity degradation through data acquisition via the Controller Area Network (CAN). The developed method allows to analyze the battery status and performance without disruption, which contributes to a more sustainable and economical vehicle usage. The measurement procedures include the analysis of the values of the state of health (SOH) and state of charge (SOC) indicators. The results will also provide insights into the optimization of the use of diagnostic tools and future battery maintenance options. To validate the method, two measurement scenarios were conducted: one on a chassis dynamometer and another under real-world driving conditions. The findings confirmed that contactless data acquisition can effectively detect cell imbalances and early degradation signs. The approach outlined in this study supports the implementation of efficient, scalable diagnostic solutions in both research and industrial settings.
Open Access: Yes
Comparative Analysis of Electric Vehicle Energy Consumption in Urban and Highway Environments Using CAN-Based Data Collection
Publication Name: Engineering Perspective
Publication Date: 2025-12-28
Volume: 5
Issue: 1 Special Issue
Page Range: 8-13
Description:
This study presents a comparative analysis of the energy consumption characteristics of Volkswagen Golf equipped with an electric powertrain in urban and interurban (highway) driving environments. The primary objective of the research is to determine which traffic context offers more favorable operating conditions in terms of energy efficiency for this vehicle category. Special emphasis is placed on the role of regenerative braking, particularly in urban traffic characterized by frequent acceleration and deceleration cycles, which may significantly influence the vehicle’s specific energy consumption through energy recovery mechanisms. The measurement data were recorded under real-world traffic conditions along two representative routes: a highway section between Zalaegerszeg and Keszthely, and the urban road network within Zalaegerszeg. During data collection, vehicle parameters extracted from the CAN network—including brake pressure, speed, accelerator pedal position, drivetrain power, battery voltage and current, state of charge, as well as longitudinal and lateral acceleration—were recorded using a custom program developed in Simulink and a Kvaser CAN logger device. The goal of the analysis is to compare the energy efficiency indicators of the two driving profiles and to draw conclusions, based on the recorded data, about the real-world efficiency of electric vehicle operation in urban settings. The findings may contribute to the optimization of operational strategies for electric vehicles and serve as a foundation for future large-scale investigations.
Open Access: Yes
Main aspects of epigenetics of gestational and female genital tumors
Publication Name: Orvosi Hetilap
Publication Date: 2025-12-28
Volume: 166
Issue: 52
Page Range: 2043-2054
Description:
The genotype of our cells is almost the same for all cells in our body, but due to epigenetic effects, their phenotype can show significant differences. Epigenetics is a relatively new field of molecular biology that deals with the changes affecting the heritable phenotype, gene expression and gene activity in addition to the given genotype. The gene expression of immune and tumor cells is regulated by epigenetic processes. These processes can enhance the immune system evasion mechanisms of various tumor cells, while the results of other processes can actually help the immune system function. Our paper explores the epigenetic aspects of gynecological tumors through a thorough review of the Hungarian and international literature, with particular attention to the tumor processes of the cervix, uterus, ovary and breast. It also affects gestational tumors. It discusses the epigenetics of endometriosis, which does not belong to the group of classic tumor diseases, but in terms of its pathomechanism shows many similarities with other tumors. Finally, the paper discusses new findings in epigenetic medicine and therapy. Orv Hetil. 2025; 166(52): 2043–2054.
Open Access: Yes
Evaluating autonomous urban freight solutions for smart and sustainable cities: A single valued neutrosophic multiple triangles scenarios model
Publication Name: Engineering Applications of Artificial Intelligence
Publication Date: 2025-12-24
Volume: 162
Issue: Unknown
Page Range: Unknown
Description:
The evaluation of autonomous urban freight logistics (UFL) solutions is crucial due to the increasing need for efficient and sustainable transportation systems in urban areas. Optimizing UFL possibilities becomes essential for developing smart city projects as cities expand and the need for reliable logistical services increases. This study introduces an artificial intelligence (AI)-driven framework for group decision-making in UFL evaluation. It develops single-valued neutrosophic (SVN) Copula-Dombi averaging and geometric operators that act as AI reasoning tools, capable of handling uncertainty, contradiction, and indeterminacy beyond classical models. To improve reliability and agreement among decision-makers, the study also presents a consensus-based SVN Copula-Dombi multiple triangles scenarios (MUTRISS) decision support model. The model is tested on a real case in India. It evaluates drones, electric light commercial vehicles (e-LCVs), autonomous e-LCVs, and droids as UFL solutions. Twelve criteria are used, and their weights are set with an optimization model. Results show drones rank first with a score of 0.6055, followed by droids at 0.6033. The study also checks robustness through comparison and sensitivity tests. The study supports smart city logistics and sustainable urban development by assisting logistics managers and city authorities in selecting appropriate autonomous UFL systems.
Open Access: Yes
Portraits as Trademarks: A Doctrinal and Practical Analysis of EUIPO Case Law on Facial Image Signs
Publication Name: Journal of Intellectual Property Information Technology and E Commerce Law
Publication Date: 2025-12-22
Volume: 16
Issue: Unknown
Page Range: 386-403
Description:
This article examines the increasingly relevant and doctrinally complex question of whether photorealistic human faces can serve as valid and protectable trademarks under European Union law. Drawing on updated empirical data, evolving EUIPO case law, and critical third-party interventions— including the amicus curiae brief submitted by INTA in the Smit case—the study interrogates the normative and institutional limits of trademark distinctiveness when applied to facial images. The research applies to doctrinal legal methodology supported by empirical observations and comparative references, with a focus on European legal sources and procedural developments. It evaluates the registrability, scope of protection, and practical enforceability of facial image trademarks in light of established principles of trademark law, including the requirement of distinctiveness, genuine use, and the limitations arising from personality rights and public interest. Particular emphasis is placed on the conceptual distinction between personal identity and commercial origin, the merger of service and sign in the context of modeling services, and the doctrinal thresholds for enhanced protection based on reputation. The findings indicate that while facial trademarks are gradually gaining acceptance, their registration raises unresolved theoretical and practical challenges that requires careful legal scrutiny and, potentially, legislative clarification to ensure coherence with the foundational objectives of trademark protection.
Open Access: Yes
DOI: DOI not available
FROM PRIVATE REGULATION TO PUBLIC IMPACT: RETHINKING PLATFORM GOVERNANCE THROUGH DIGITAL CONSTITUTIONALISM
Publication Name: Studia Iuridica Cassoviensia
Publication Date: 2025-12-19
Volume: 13
Issue: Special Issue
Page Range: 91-106
Description:
This paper explores the growing regulatory role of very large online platforms (VLOPs) through the lens of digital constitutionalism. It argues that while these platforms operate under private legal frameworks, their governance functions—especially content moderation and algorithmic decision-making—closely resemble public regulatory authority. As platforms increasingly shape the terms of civic participation, public discourse, and access to information, a normative gap has emerged between the private character of their power and its public consequences. The study identifies three core questions: what motivates platform self-regulation, whether platforms exercise public-like functions, and whether digital constitutionalism provides a viable framework for constraining their power. Drawing primarily on a comprehensive literature review, the analysis confirms that platform self-regulation is strategically motivated, that platforms exercise quasi-public authority, and that digital constitutionalism offers a promising—though still evolving—response. The findings suggest that constitutional values such as transparency, due process, and the protection of fundamental rights must increasingly be applied to powerful private actors in the digital environment to uphold rule-of-law standards and democratic legitimacy.
Open Access: Yes
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE EUROPEAN LABOUR MARKET-POLARISATION, CHALLENGES AND OPPORTUNITIES
Publication Name: Studia Iuridica Cassoviensia
Publication Date: 2025-12-19
Volume: 13
Issue: Special Issue
Page Range: 20-35
Description:
The rapid development and diffusion of artificial intelligence (AI) is having a major impact on the European labour market, transforming employment structures, skills, and ways of working. This technological revolution is both a challenge and an opportunity for workers, companies, and policy makers. This research is about to focus on the sectors, the depth, and the ethical use of AI, and will explore the labour law issues of new forms of employment generated by AI (e.g. platform work).Overall, the integration of AI into the labour market presents both opportunities and risks that require initiative-taking policy responses, ongoing research, and collaboration between governments, businesses, and social partners. By addressing the legal, social, and ethical implications of AI-driven work, Europe can harness the benefits of technological advancement while safeguarding workers' rights and promoting a more inclusive labour market.
Open Access: Yes
Modeling Human Lane Following Behavior
Publication Name: IEEE Access
Publication Date: 2025-12-19
Volume: 13
Issue: Unknown
Page Range: 214940-214959
Description:
Vehicles with driver assistance and even autonomous driving capabilities have become widely spread on the roads in the last decades. Replacing human drivers even partially is a complex issue, as these driving systems must be safe and reliable under various conditions. The complexity is increased further by the fact that driving systems must interact with human participants of the traffic: the driver and passengers of the given vehicle as well as drivers in other vehicles or pedestrians. The market trends show that even though more and more driving assistance solutions are available, the vehicle users often refuse to use them as the behavior of these systems feels unnatural. Therefore, manufacturers have initiated the development of personalized driving assistance which motivates research in driver modeling and driving style classification. One of the most controversial assistance function is lane keeping. In our paper, we propose various different model structures that are able to capture the lane offset selection behavior of human drivers. It is shown that a static linear regression model provides reasonable accuracy and robustness in modeling the lane offset. While Gaussian Process models offer more accuracy, their training time is more demanding. It is shown, that a combination of linear and polynomial third-order basis functions offers a good tradeoff to efficiently describe the lane offset selection of human drivers. Our observations are based on studying real driving data from 41 drivers, whose behavior is modeled with the considered model structures. Then, using the corresponding model parameters, drivers are clustered into two driving style groups. Using the collective data of these groups the models are fitted to all data records in the two driver groups. Any new driver can be classified into one of these groups, and the aggregated models can be further personalized to to increase user satisfaction with the lane keeping systems.
Open Access: Yes
