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Found 6383 publications

Investigation of weed vegetation on wet segetal fields in South-Western Hungary

Robert W. Pal Koltai Judit Petra Gyula Pinke E. Oláh János Csiky

Publication Name: Journal of Plant Diseases and Proctectio Supplement

Publication Date: 2006-12-01

Volume: Unknown

Issue: 20

Page Range: 567-576

Description:

Inland water on soils with bad water balance can lead to serious yield losses. Soil management and plant protection is nearly impossible in these marshy vernal pools, wherefore very special vegetation develops. On the basis of 58 phytocoenological surveys made in South-Western Hungary the vegetation of the vernal pools will be characterised. From phytosociological point of view our surveys stand to Ranunculo sardoi-Alopecuretum geniculati and Myosuro-Ranunculetum sardoi associations the nearest, where the proportion of Nanocyperion elements is significant. The following endangered species occure in these vernal pools: Elatine alsinastrum, Limosella aquatica, Lindernia procumbens, Montia fontana, Peplis portula. However vernal pools in segetal fields are causing losses from economical aspects, they can contribute to increase agrobiodiversity and have an important role in maintaining numerous threatened and protected plant species (Red Data List, IUCN, Corine Biotopes Project, Bern Convention). © Eugen Ulmer KG.

Open Access: Yes

DOI: DOI not available

Preface

María Eugenia Cornejo Istvan A. Harmati Eloísa Ramírez-Poussa Juan Moreno-García László T. Kóczy Jesús Medina-Moreno

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 955

Issue: Unknown

Page Range: v-viii

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Numerical Modeling of Hydraulic Failure Mechanisms in Levees, River Embankments, and Earth Dams Under Climate-Induced Flood Conditions: A Systematic Literature Review

Edina Koch Mais Mayassah

Publication Name: Applied Sciences Switzerland

Publication Date: 2026-06-01

Volume: 16

Issue: 11

Page Range: Unknown

Description:

Hydraulic failure in levees, river embankments, and earth dams represents a critical challenge in flood risk management, particularly under increasing climate-induced hydrological stresses. This study presents a systematic literature review of numerical, probabilistic, and data-driven modeling approaches used to assess hydraulic failure mechanisms in earthen flood-protection structures. A structured search was conducted in Scopus, Web of Science, and Taylor & Francis for peer-reviewed English-language journal articles published between 2015 and 2026. Following duplicate removal, title and abstract screening, and full-text eligibility assessment, 65 studies were included in the final synthesis. Based on the synthesis, an integrated mechanism–model–uncertainty framework is developed to relate hydraulic loading conditions, soil response, dominant failure mechanisms, appropriate numerical modeling approaches, uncertainty treatment, and climate-related stressors. This study provides valuable insights for engineers, researchers, and policymakers by identifying key advances, limitations, and future research directions for improving levee resilience. Study quality was assessed using a structured quality assessment rubric. The review protocol was not registered in a public registry, and no external funding was received.

Open Access: Yes

DOI: 10.3390/app16115572

The lack of ancient and medieval probability theory

Dusek Tamás

Publication Name: Statisztikai Szemle

Publication Date: 2022-01-01

Volume: 100

Issue: 4

Page Range: 408-420

Description:

No description provided

Open Access: Yes

DOI: 10.20311/stat2022.4.hu0408

Tribological Investigation of the Effect of Nanosized Transition Metal Oxides on a Base Oil Containing Overbased Calcium Sulfonate

D. Tóth I. Szabó Hajnalka Hargitai

Publication Name: Lubricants

Publication Date: 2023-08-01

Volume: 11

Issue: 8

Page Range: Unknown

Description:

In this study, copper(II) oxide, titanium dioxide and yttrium(III) oxide nanoparticles were added to Group III-type base oil formulated with overbased calcium sulfonate. The nanosized oxides were treated with ethyl oleate surface modification. The tribological properties of the homogenized oil samples were tested on a linear oscillating tribometer. Friction was continuously monitored during the tribological tests. A surface analysis was performed on the worn samples: the amount of wear was determined using a digital optical and confocal microscope. The type of wear was examined with a scanning electron microscope, while the additives adhered to the surface were examined with energy-dispersive X-ray spectroscopy. From the results of the measurements, it can be concluded that the surface-modified nanoparticles worked well with the overbased calcium sulfonate and significantly reduced both wear and friction. In the present tribology system, the optimal concentration of all three oxide ceramic nanoadditives is 0.4 wt%. By using oxide nanoparticles, friction can be reduced by up to 15% and the wear volume by up to 77%. Overbased calcium sulfonate and oxide ceramic nanoparticles together form a lower friction anti-wear boundary layer on the worn surfaces. The results of the tests represent another step toward the applicability of these nanoparticles in commercial engine lubricants. It is advisable to further investigate the possibility of formulating nanoparticles into the oil.

Open Access: Yes

DOI: 10.3390/lubricants11080337

THE INFLUENCE OF COVID-19 ON SENTIMENTS OF HIGHER EDUCATION STUDENTS-PROSPECTS FOR THE SPREAD OF DISTANCE LEARNING

Márta Konczos Szombathelyi Kevin M. Jackson

Publication Name: Economics and Sociology

Publication Date: 2022-01-01

Volume: 15

Issue: 3

Page Range: 216-247

Description:

Clayton Christensen’s theory of “disruptive innovation” describes how smaller firms, with access to far fewer resources, are still able to challenge and displace well-established industry leaders. Uber and Airbnb as startups were able to disrupt the global taxi and hotel industries despite the economic shock of the financial crisis (2007-2008). The COVID-19 pandemic is currently an even more powerful catalyst that is forcing businesses and institutions to define and adapt to the “new normal”. Higher education also finds itself at a critical crossroads where universities around world need to quickly adapt to the changing needs of younger generations, discover the optimal balance between traditional and online learning, find ways to reduce costs and avoid tuition escalation, and become better prepared for future health crises and geopolitical events. The COVID-19 pandemic has already significantly accelerated trends in education and a failure to adapt could spark the disruption in education that Christensen spoke of more than a decade ago. This research utilizes valuable feedback from a diverse group of international students to help educators better understand changes that occurred during COVID-19 and form recommendations regarding how to use technology to maximize learning outcomes.

Open Access: Yes

DOI: 10.14254/2071-789X.2022/15-3/13

Explainable XGBoost-based models of root-zone soil moisture profiling using coupled Sentinel-2 and IoT data in loam and silt loam soil

Tarek Alahmad A. Nyéki M. Neményi

Publication Name: Discover Applied Sciences

Publication Date: 2026-06-01

Volume: 8

Issue: 6

Page Range: Unknown

Description:

Background: Accurate prediction of soil moisture content (SMC) is crucial for sustainable irrigation management and enhancing resilience against climate change. However, in-situ sensing offers accurate point-scale measurements but lacks spatial representativeness, while satellite-based offer spatial coverage but are either too coarse at field scale or indirect and cloud -sensitive. Integrating satellite observation with ground-based monitoring and IoT meteorological data could exploit complementary strengths by linking canopy conditions and atmospheric drivers to reliable in-field reference measurements. Method: This study predicts SMC at five depths (5 to 80 cm) for two soil texture classes (loam and silt loam) using Extreme Gradient Boosting (XGBoost) by integrating Sentinel-2 vegetation indices Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) with Internet of Things (IoT)-derived meteorological data using two input scenarios and gravimetric SMC as reference for model training and evaluation. Results: The model trained with combined inputs achieved higher accuracy compared with using only vegetation indices as predictors in both soil textures and all depths. This was especially evident in loam soil at 5 and 20 cm depth, with R² values of 0.95 and 0.79 and RMSE values of 0.88% and 1.46%, respectively, compared to R² values of 0.70 and 0.69 and RMSE values of 2.26% and 1.77% when using vegetation indices only. The model achieved near-perfect accuracy in silt loam with R² = 0.99 at 5–20 cm and RMSE = 0.49–0.40% at same depths. SHapley Additive exPlanations (SHAP) analysis identified NDVI as the most influential predictor in surface soil layers (mean SHAP = 0.11–0.22), reflecting its strong sensitivity to canopy vigor. In contrast, solar radiation emerged as key determinant in deeper soil layers (60 and 80 cm; SHAP = 0.12–0.18), highlighting the importance of atmospheric evaporative demand in controlling subsoil moisture dynamics. Conclusions: The model’s accuracy and interpretability enable depth-specific decision support for irrigation timing and water use efficiency under variable weather conditions, while providing actionable driver insights for climate-adaptive management aligned with SDGs 6 and 13. The approach is validated for loam and silt loam textures using optical Sentinel-2 indices, which are subject to cloud cover and revisit latency; therefore, the current framework is not suitable for real-time irrigation scheduling without accounting for these delays. Future integration with SAR and gap-filling strategies would be required for operational real-time applications.

Open Access: Yes

DOI: 10.1007/s42452-026-08673-3

Optimization of pavement texture depth measurement using machine learning algorithms

Mohammad Fahad

Publication Name: Discover Applied Sciences

Publication Date: 2026-04-01

Volume: 8

Issue: 4

Page Range: Unknown

Description:

Optimization of 3D laser scanning method using paired t-tests and ANOVA tests. Prediction of pavement mean texture depth using machine learning algorithms. Separation of macrotexture and microtexture using Power Spectral Density method.

Open Access: Yes

DOI: 10.1007/s42452-026-08392-9

The Holy Trinity of Patents, Biotechnology and Sustainability. Review of Biotech Patents in the Scope of US Patent Case Law

Barna Arnold Keserű Máté Frank

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 985-990

Description:

Patent law plays a crucial role in all three pillars of sustainable development. Economically, patents serve as a highly valuable competitive tool, socially, they promote advancements that benefit public health and nutrition, and environmentally, patents facilitate the development and dissemination of environment-friendly technologies. In recent decades, biotechnology has emerged as one of the most significant patent-intensive industries. This paper examines the evolution of the patentability of biotechnological inventions from the early 1970s to the present day, with a primary focus on the case law of the United States, a predominant actor in this field. The main contributions of this paper are twofold. First, it explores the framework of patentability for biotechnological inventions, particularly focusing on different genomes. Second, the paper considers the potential future of biotechnology, particularly in light of ongoing litigation over CRISPR-Cas9 gene-editing technology. The findings suggest that recent US case law, particularly regarding CRISPR-Cas9, will shape patentability criteria and market access. Over-protection of biotechnology may hinder the fulfillment of sustainable development goals, while the lack of exclusive rights would hold back innovation, which is also harmful to these goals.

Open Access: Yes

DOI: 10.3303/CET24114165