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Found 5157 publications
Investigation of the Load-Bearing Capacity of Resin-Printed Components Under Different Printing Strategies
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-08-01
Volume: 15
Issue: 15
Page Range: Unknown
Description:
This study examines the influence of different printing orientations and infill settings on the strength and flexibility of components produced using resin-based 3D printing, particularly with masked stereolithography (MSLA). Using a common photopolymer resin and a widely available desktop MSLA printer, we produced and tested a series of samples with varying tilt angles and internal structures. To understand their mechanical behavior, we applied a custom bending test combined with high-precision deformation tracking through the GOM ARAMIS digital image correlation system. The results obtained clearly show that both the angle of printing and the density of the internal infill structure play a significant role in how much strain the printed parts can handle before breaking. Notably, a 75° orientation provided the best deformation performance, and infill rates between 60% and 90% offered a good balance between strength and material efficiency. These findings highlight how adjusting print settings can lead to stronger parts while also saving time and resources—an important consideration for practical applications in engineering, design, and manufacturing.
Open Access: Yes
DOI: 10.3390/app15158747
Five-day ski camp could enhance postural stability in young adults: A quasi-experimental study
Publication Name: Physiological Reports
Publication Date: 2025-08-01
Volume: 13
Issue: 16
Page Range: Unknown
Description:
This study investigated whether a 5-day ski camp could improve postural stability in young adults. It was hypothesized that skiing would reduce postural sway. In this quasi-experimental design, 43 undergraduate students who participated in a 5-day ski camp (approximately 20 h of skiing) were compared to 35 peers who did not attend. Postural stability was assessed using the modified Clinical Test of Sensory Integration and Balance protocol of the Balance Tracking System, which evaluates sway under four standing conditions: eyes open or closed, and on stable or unstable surfaces. Quade nonparametric ANCOVAs were used to compare percentage change scores between groups, controlling for age. No significant group differences emerged for standard, proprioceptive, or vestibular postural stability (p > 0.05). However, a statistically significant group effect was found for visual postural stability (p = 0.006), with improvement observed only in females (p = 0.003), not in males (p = 0.961). A 5-day ski camp significantly enhanced visual postural stability in females but did not affect males or other postural domains. These findings suggest a potential sex-specific adaptation to skiing and highlight the need for further research into the mechanisms underlying balance improvement.
Open Access: Yes
DOI: 10.14814/phy2.70501
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
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
Data-Driven Identification of Gearbox Housing Structures Using Acoustic Radiation Spectra
Publication Name: International Journal of Basic and Applied Sciences
Publication Date: 2025-08-01
Volume: 14
Issue: 4
Page Range: 619-623
Description:
The structural design of gearbox housing, such as ribbing and wall thickness, has a significant impact on its noise radiation characteristics, especially in electric vehicle applications where tonal noise is more perceptible. This study presents a novel methodology that uses machine learning and spectral analysis to distinguish between gearbox housing types based solely on their acoustic radiation data. Frequency-domain sound pressure spectra, simulated for multiple design variants, were interpolated and analyzed using Principal Component Analysis (PCA) and K-means clustering. The results reveal that construction types (e.g., fully ribbed, partially ribbed, or without ribs) exhibit distinct acoustic profiles. Furthermore, a Random Forest classifier achieved 88.9% accuracy in predicting structural configuration from the spectra alone. These findings demonstrate that structural design features can be inferred directly from acoustic data, offering a lightweight and geometry-free alternative to traditional NVH simulation workflows. The approach can be integrated as a lightweight plug-in in existing NVH workflows. It ingests acoustic spectra and returns a structural-stiffness label with uncertainty, supporting early-stage screening and late-phase regression checks.
Open Access: Yes
DOI: 10.14419/mnbhp030
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
Investigation of the synthesis and thermal insulation properties of K2Ti6O13 whisker-reinforced SiO2 micro powder composite coating fabrics
Publication Name: Energy
Publication Date: 2025-08-01
Volume: 328
Issue: Unknown
Page Range: Unknown
Description:
Developing functional textiles with thermal insulation and hydrophobic properties is of significant interest. This study successfully synthesizes K2 Ti6 O13 (potassium titanate, KTO) whiskers via the hydrothermal method and prepares KTO composite silica polyester fabric (KSP) through impregnation technology, exhibiting excellent thermal insulation and hydrophobic qualities. X-ray diffraction (XRD) analysis verifies the high purity and excellent crystallinity of KTO whiskers and SiO2 micro-powder. Scanning electron microscopy (SEM) images reveal that the KTO whiskers retain their original morphology and exhibit uniform size distribution, with an average length of around 1 μm and an aspect ratio of 40. Transmission electron microscopy (TEM) images further validate the planar growth properties of the whiskers. Raman spectroscopy research elucidates the vibrational modes of various chemical bonds in the KTO whiskers. The ultraviolet–visible–near-infrared spectrophotometer test results demonstrate that the KSP fabric reflects 43.5 % more light than standard polyester fabric and substantially lowers the temperature in the covered chamber under simulated sunlight exposure, achieving a maximum reduction of 7.4 °C. The KSP fabric has exceptional hydrophobic properties, completing a contact angle of 153.2° and maintaining reflectance stability, with a mere 5.92 % reduction after 20 days of outside exposure. This work offers substantial reference value for the advancement of practical textiles.
Open Access: Yes
The role of artificial intelligence in enhancing corporate environmental information disclosure: Implications for energy transition and sustainable development
Publication Name: Energy Economics
Publication Date: 2025-08-01
Volume: 148
Issue: Unknown
Page Range: Unknown
Description:
Global climate and environmental issues pose severe challenges to the sustainable development of human society. As major contributors to environmental pollution and carbon emissions, the quality of enterprises' environmental data has gained significant attention in academic and industrial circles. This study analyzes information from Chinese A-share companies spanning 2012 to 2023 to investigate the pathways through which artificial intelligence (AI) technology influences corporate environmental information disclosure (EID). The results indicate that AI significantly enhances the quality of corporate EID by optimising internal control levels and strengthening external supervision mechanisms. These conclusions have been validated through robustness and endogeneity tests. The heterogeneity analysis further reveals that the promoting effect of AI is more significant in large corporates, corporates in central cities, mature corporates, corporates audited by the Big Four international accounting firms, high-tech corporates, and heavily polluting industries. The study innovatively constructs a dual-path theoretical framework of ‘internal management optimisation–external supervision strengthening’ and integrates macro urban AI indicators with micro enterprise data, contributing new empirical support for the digital transformation and green governance of developing countries. Based on these findings, policymakers should promote the innovative application of AI technology in corporate environmental governance, improving internal control norms, optimising the external supervision system, and implementing a classified guidance strategy for different enterprise attributes, so as to help enterprises achieve low-carbon transformation and sustainable development.
Open Access: Yes
A Risk-Informed BIM-LCSA Framework for Lifecycle Sustainability Optimization of Bridge Infrastructure
Publication Name: Buildings
Publication Date: 2025-08-01
Volume: 15
Issue: 16
Page Range: Unknown
Description:
The sustainability of bridge infrastructure is becoming increasingly important due to rising environmental, economic, and social demands. However, most current assessment models remain fragmented, often overlooking the social pillar, underutilizing risk integration across the lifecycle, and failing to fully leverage digital tools such as Building Information Modeling (BIM) and Life Cycle Sustainability Assessment (LCSA), resulting in incomplete sustainability evaluations. This study addresses these limitations by introducing a practical and adaptable model that integrates BIM, LCSA, and expert-driven risk prioritization. Five Hungarian bridge projects were modeled using Tekla Structures and analyzed in OpenLCA to quantify environmental, economic, and social performance. A custom Sustainability Level Change (SLC) algorithm was developed to compare baseline scenarios (equal weighting) with risk-informed alternatives, simulating the impact of targeted improvements. The results demonstrated that prioritizing high-risk sustainability indicators leads to measurable lifecycle gains, typically achieving SLC improvements between +2% and +6%. In critical cases, targeted enhancement scenarios, applying 5% and 10% improvements to top-ranked, high-risk indicators, pushed gains up to +12%. Even underperforming bridges exhibited performance enhancements when targeted actions were applied. The proposed framework is robust, standards-aligned, and methodologically adaptable to various bridge types and lifecycle phases through its data-driven architecture. It empowers infrastructure stakeholders to make more informed, risk-aware, and data-driven sustainability decisions, advancing best practices in bridge planning and evaluation. Compared to earlier tools that overlook risk dynamics and offer limited lifecycle coverage, this framework provides a more comprehensive, actionable, and multi-dimensional approach.
Open Access: Yes
