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Found 6278 publications
Assessing the readiness of Hungarian cities for autonomous vehicles
Publication Name: Cities
Publication Date: 2025-10-01
Volume: 165
Issue: Unknown
Page Range: Unknown
Description:
An increasing number of studies examine the AV readiness of cities where urban autonomous vehicle street tests have already been performed, leaving a significant gap in understanding the AV-readiness of cities that have not yet undergone such testing. Our research aims to assess the AV-readiness of Hungarian cities without prior urban autonomous vehicle testing. We surveyed 56 cities (91.8 % sample) with public transport and populations over 20,000. The results of the correlation analysis indicate a minimal understanding of the relation between the urban deployment of autonomous vehicles and the need for related urban developments. In the long term, however, there is evidence of the cities' intention to establish the urban conditions for autonomous vehicles. The larger the settlement and the higher the readiness level of current mobility plans and solutions, the sooner the estimated intervention, although these correlations are weak. The larger the size of the settlement and the more it has a mobility plan or an already existing solution, the shorter the timeframe required by the settlement for municipal interventions. Approximately half of the city planners did not associate AV-readiness with legislation and there are significant differences in planning considerations related to the new mobility paradigm.
Open Access: Yes
Analysis of Macro- and Microplastic Contaminations in Commercially Available Potting Soil Products
Publication Name: Chemical Engineering Transactions
Publication Date: 2025-01-01
Volume: 116
Issue: Unknown
Page Range: 835-840
Description:
Macro- and microplastics have emerged as pollutants in terrestrial ecosystems, yet limited knowledge exists regarding their presence in horticultural substrates. This paper employed qualitative and quantitative methods to analyse seven commercially available potting soil products. Fourier-transform infrared spectroscopy identified polyethylene, polypropylene, and polyamide as the dominant polymer types, with PE and PP accounting for over 65% of the detected plastics. Notably, particles measuring approximately 0.008 m were commonly observed, raising concerns about potential environmental accumulation. The paper also revealed significant variability in contamination levels across the samples, with S-2 and S-4 exhibiting the highest microplastic content, including the presence of blue and red synthetic fibres as observed microscopically. Additionally, signs of polymer degradation were detected through the identification of carbonyl peaks. These findings highlight a novel source of pollution within the consumer horticulture domain and provide new insights into plastic uptake pathways, potential risks to plant health, and the need for mitigation strategies to support sustainable agriculture. This work contributes to the growing understanding of microplastics in soil environments and may inform future environmental policy actions.
Open Access: Yes
DOI: 10.3303/CET25116140
Explainable Machine Learning-Based Ground Motion Characterization: Evaluating the Role of Geotechnical Variabilities on Response Parameters
Publication Name: Geosciences Switzerland
Publication Date: 2025-11-01
Volume: 15
Issue: 11
Page Range: Unknown
Description:
Accounting for geotechnical property variability is crucial in seismic site response analysis. Traditionally, the influence of each geotechnical property on response parameters is assessed independently. However, this approach limits our understanding of the combined effects of multiple properties on ground response parameters. This study presents a novel, explainable machine learning (ML)-based approach to assess the influence of multiple geotechnical property variations on response parameters. Four ML models, namely AdaBoost, Extreme Gradient Boosting (XGBoost), Random Forest Regressor (RFR) and Gradient Boosting Machine (GBM), were developed for predictive models. The input factors were shear-wave velocity, plasticity index, soil thickness, input motion intensity and unit weight of the soils. The response parameters were peak ground acceleration (PGA) and peak ground displacement (PGD). Multiple statistical performance metrics were computed to evaluate the performance of the models. The results show the superior prediction performance of the GBM model with low error rates and high agreement index (AI), Kling–Gupta efficiency (KGE) and coefficient of determination (Formula presented.). The output of the GBM model was further analyzed using Shapley Additive exPlanation (SHAP) technique to explain and identify the most significant factors contributing to the predictions. Finally, the model was used to develop user-friendly web-based software to facilitate rapid predictions of PGA and PGD.
Open Access: Yes
Aerial Image-Based Crop Row Detection and Weed Pressure Mapping Method
Publication Name: Agronomy
Publication Date: 2025-08-01
Volume: 15
Issue: 8
Page Range: Unknown
Description:
Accurate crop row detection is crucial for determining weed pressure (weeds item per square meter). However, this task is complicated by the similarity between crops and weeds, the presence of missing plants within rows, and the varying growth stages of both. Our hypothesis was that in drone imagery captured at altitudes of 20–30 m—where individual plant details are not discernible—weed presence among crops can be statistically detected, allowing for the generation of a weed distribution map. This study proposes a computer vision detection method using images captured by unmanned aerial vehicles (UAVs) consisting of six main phases. The method was tested on 208 images. The algorithm performs well under normal conditions; however, when the weed density is too high, it fails to detect the row direction properly and begins processing misleading data. To investigate these cases, 120 artificial datasets were created with varying parameters, and the scenarios were analyzed. It was found that a rate variable—in-row concentration ratio (IRCR)—can be used to determine whether the result is valid (usable) or invalid (to be discarded). The F1 score is a metric combining precision and recall using a harmonic mean, where “1” indicates that precision and recall are equally weighted, i.e., β = 1 in the general Fβ formula. In the case of moderate weed infestation, where 678 crop plants and 600 weeds were present, the algorithm achieved an F1 score of 86.32% in plant classification, even with a 4% row disturbance level. Furthermore, IRCR also indicates the level of weed pressure in the area. The correlation between the ground truth weed-to-crop ratio and the weed/crop classification rate produced by the algorithm is 98–99%. As a result, the algorithm is capable of filtering out heavily infested areas that require full weed control and capable of generating weed density maps on other cases to support precision weed management.
Open Access: Yes
Strategic integration of residential electricity: An optimisation model for solar energy utilisation and carbon reduction
Publication Name: Energy
Publication Date: 2024-11-30
Volume: 310
Issue: Unknown
Page Range: Unknown
Description:
The Solar Combined Cooling, Heating, and Power (S-CCHP) system, distinct from traditional centralised generation, provides clean energy solutions by installing user-side renewable energy capture facilities like solar panels to address the energy crisis and mitigate global warming. Previous research on the design of S-CCHP for buildings has often emphasised self-sufficiency, with less focus on the role of these systems as energy suppliers on the market. However, it is feasible to install scaled-up solar facilities that generate enough power to export to the grid, reducing grid pressure and enhancing the renewable energy mix. This study analyses the optimal design deployment for electricity within the S-CCHP system, based on the Renewable Energy System for Residential Building Heating and Electricity Production (RESHeat) system installed in Limanowa. It aims to optimise owner energy deployment by strategically integrating electricity generation, hybrid storage, and the electricity market to maximise owner benefits. A Life Cycle Assessment is also conducted to explore greenhouse gas emissions across scenarios with different storage facilities and reuse rates. Results show that the optimal deployment of 264 PV panels, each with a rated power of 440 W, generates 105 MWh annually, resulting in the surplus of 90.18 MWh with a selling price of 115 EUR/MWh. Vanadium redox flow batteries offer the highest revenue (4922.01 EUR) with the lowest storage costs, while lithium-ion batteries have the lowest carbon emissions (1.22 t CO2 eq/y). Sensitivity analysis and revenue break-even analysis are further conducted to assess the robustness and financial viability.
Open Access: Yes
Glyphosate Use in Crop Systems: Risks to Health and Sustainable Alternatives
Publication Name: Toxics
Publication Date: 2025-11-01
Volume: 13
Issue: 11
Page Range: Unknown
Description:
Glyphosate, a widely used non-selective herbicide, has been a subject of intense scientific debate due to its environmental persistence and potential health risks. This review examines glyphosate’s mechanisms of action, its effects on crop production, and its broader environmental impact, including soil degradation, water contamination, and biodiversity loss. Furthermore, it examines the expanding body of research linking glyphosate exposure to various human health concerns, including metabolic, neurological, reproductive, and oncological disorders. The review also assesses glyphosate’s role in hindering the achievement of the Sustainable Development Goals (SDGs), particularly those related to food security, health, access to clean water, and the protection of marine ecosystems. Finally, potential alternatives to glyphosate-based weed control, including organic and non-chemical methods, are discussed to promote sustainable agricultural practices that balance productivity with ecological and public health considerations. The evidence reviewed highlights glyphosate’s pervasive presence across ecosystems and its potential to disrupt both environmental and human health. The findings underscore the urgent need to regulate glyphosate use, prioritize soil and water protection, and accelerate the transition toward sustainable, low-toxicity weed management strategies that align with global sustainability objectives.
Open Access: Yes
Fourier Analysis of the Nonlinearity of Surface-Relief Optical Transmission Gratings of Quasi-Sinusoidal Profile Fabricated in Optical Glasses and Crystals by Carbon, Nitrogen and Oxygen Ion Microbeams
Publication Name: Photonics
Publication Date: 2025-10-01
Volume: 12
Issue: 10
Page Range: Unknown
Description:
Optical transmission gratings with quasi-sinusoidal surface-relief profiles were inscribed in IOG and Pyrex glasses and in Bi12 GeO20 , Er: LiNbO3, and Er: Fe: LiNbO3 crystals by microbeams of carbon, nitrogen, and oxygen ions at ion energies of 5, 6, and 10.5 MeV. Grating constants were 4, 8, and 16 μm. Amplitudes of the surface-relief gratings were in the 10–2000 nm range. The diffraction efficiency of the gratings was measured at a wavelength of 640 nm. Maximum diffraction efficiencies were close to the theoretical maximum of 33% for thin gratings. Grating profiles were measured by optical microscopic profilometry. Measurement of the diffraction efficiencies at higher orders and Fourier analysis of the grating profiles revealed the dependence of the residual nonlinearity of the grating profiles on the implanted ion fluence. The ion microbeam-written gratings can be used as light coupling elements in integrated optics for sensors and telecommunication.
Open Access: Yes
INFLUENCE OF FFF PROCESS PARAMETERS ON THE MECHANICAL PROPERTIES OF SINTERED 17-4PH STAINLESS STEEL
Publication Name: Mm Science Journal
Publication Date: 2025-11-01
Volume: 2025-November
Issue: Unknown
Page Range: 8765-8772
Description:
This study examines how Fused Filament Fabrication (FFF) process parameters affect the mechanical properties of sintered 17-4PH stainless steel. Test specimens were printed from BASF Ultrafuse 17-4PH filament on an IDEX system and processed by industrial debinding and sintering. The effects of layer height, printing speed and infill angle were evaluated through tensile testing. The highest tensile strength of 802 MPa was achieved at 0.2 mm layer height, 25 mm/s printing speed and 45° infill orientation. Layer height showed the dominant influence on tensile strength, as later confirmed by ANOVA, while printing speed and infill angle had smaller or non-significant effects within the tested range. The results give a practical understanding of how printing parameters determine the mechanical behavior of 17-4PH parts and can support further optimization of metal FFF processes.
Open Access: Yes
The Autonomous Software Stack of the FRED-003C: The Development that LED to Full-Scale Autonomous Racing
Publication Name: IEEE Intelligent Vehicles Symposium Proceedings
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: 1661-1667
Description:
Scientific development often takes place in the context of research projects carried out by dedicated students during their time at university. In the field of self-driving software research, the Formula Student Driverless competitions are an excellent platform to promote research and attract young engineers. This article presents the software stack developed by BME Formula Racing Team, that formed the foundation of the development that ultimately led us to full-scale autonomous racing. The experience we gained here contributes greatly to our successful participation in the Abu Dhabi Autonomous Racing League. We therefore think it is important to share the system we used, providing a valuable starting point for other ambitious students. We provide a detailed description of the software pipeline we used, including a brief description of the hardware-software architecture. Furthermore, we introduce the methods that we developed for the modules that implement perception; localisation and mapping, planning, and control tasks.
Open Access: Yes
