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Publications - 6383

Pathways to asbestos-free and sustainable cities using multi-level perspective approach

Publication Name: Discover Sustainability

Publication Date: 2025-12-01

Volume: 6

Issue: 1

Page Range: Unknown

Description:

Urban policymakers, researchers, and municipal planners increasingly face the challenge of managing complex sustainability transitions, particularly in contexts involving persistent environmental hazards such as asbestos contamination. This systematic review applies the Multi-Level Perspective (MLP), which examines interactions between niche innovations, socio-technical regimes, and broader landscapes, to the underexplored area of asbestos-free urban transitions. The concept of an “asbestos-free city” is introduced in this paper as a novel analytical lens to describe urban transitions aiming to eliminate asbestos-related risks through systemic, sustainable interventions. The review was conducted through a structured qualitative analysis of peer-reviewed academic literature, guided by predefined thematic criteria and relevance to urban asbestos-related transitions. The review highlights the factors that enable or hinder the adoption of asbestos-free and strong sustainable solutions, as well as the role of various actors, such as policymakers, industry, and civil society, in driving these transitions. Despite the growing body of work on sustainability transitions, the integration of MLP into asbestos-related urban transformation remains limited. This paper fills that gap by offering a structured synthesis and proposing a roadmap for future research and practice. Our findings provide actionable insights for actors across policy, civil society, and industry seeking to accelerate transitions toward asbestos-free and sustainable cities.

Open Access: Yes

DOI: 10.1007/s43621-025-01932-0

Relationship Between Age at First Calving and 305-Day Milk Yield in Hungarian Holstein-Friesian Cows: Trends and Genetic Parameters

Publication Name: Animals

Publication Date: 2025-12-01

Volume: 15

Issue: 24

Page Range: Unknown

Description:

Age at first calving (AFC) and 305-day milk yield in the first lactation (MY) data of 18,545 Holstein-Friesian cows born between 2008 and 2018 in six herds were evaluated. The effects of some genetic and environmental factors, population genetic parameters, breeding value (BV), and phenotypic and genetic trends of AFC and MY traits were estimated. The GLM method (ANOVA Type III) and BLUP animal model were used for the estimations. One-way linear regression analysis was used for trend calculations. The adjusted overall mean value (±SE) of the AFC and MY traits was 25.19 ± 0.02 months and 10,287.14 ± 24.79 kg, respectively. The percentage proportion contribution of the different factors in the phenotype in the case of AFC was as follows: herd 94.41%, birth year of cow 3.26%, birth season of cow 1.39%, and sire 0.71%. For MY, the contribution was as follows: herd 89.17%, birth season of cow 5.38%, birth year of cow 4.09%, and sire 1.05%. The heritability of AFC and MY traits by two different models proved to be moderate (0.26 ± 0.02, 0.19 ± 0.01 and 0.30 ± 0.02, 0.34 ± 0.01, respectively). There were relatively small differences between the sires in the estimated BV for the traits AFC and MY. The phenotypic and genetic correlations between AFC and MY traits were weak (between −0.05 and −0.16). Based on the phenotypic trend calculation, AFC showed a decreasing direction (−0.12 months per year) and MY an increasing direction (+42.30 kg per year). However, the genetic trend was very slightly decreasing for AFC (−0.00 and −0.05 months per year) and slightly increasing for MY (+5.52 and +16.49 kg per year) over the period studied.

Open Access: Yes

DOI: 10.3390/ani15243648

The Effect of Illumination on HSV Colour Segmentation for Ripe Tomatoes based on Machine Vision

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 829-834

Description:

In agriculture, computer vision and image processing are essential for monitoring crops and controlling robots and actuators. In this work, the detection of ripe tomato fruit was the main aim. During the tomato-ripping process, the green tomato turns to red in several color stages (Ambrus et al., 2024). While the chlorophyll concentration decreases, the lycopene concentration increases. The sugar and the acid increase parallel to lycopene. The RGB camera can capture the process but needs to convert HSV color space to identify the tomato. The successful identification depends on the direct illumination volume. The experiment contains 4 ripe tomatoes and 15 different artificial illumination levels. The measurements show that the results are similar to or constantly above 3,000 lx illumination. However, under 3,000 lx, the detected size of tomatoes looks smaller and smaller depending on the weakness of illumination. Around 1,600 lx, it is possible to measure only half of the real size of the tomato. It shows that using the right amount of light is crucial to precise measurement in HSV color space. This research highlights the critical importance of proper illumination in ensuring accurate image analysis for tasks like industrial tomato segmentation. It emphasizes the need for adaptable lighting solutions, particularly in varying weather conditions, and the balance between adequate light and energy efficiency.

Open Access: Yes

DOI: 10.3303/CET24114139

Integrating innovative digital technologies into use assessment of parks and protected areas in North America

Publication Name: Handbook of Innovation for Sustainable Tourism

Publication Date: 2022-08-16

Volume: Unknown

Issue: Unknown

Page Range: 347-360

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Development of nanoclay reinforced HDPE/PA6 nanocomposites

Publication Name: Eccm 2012 Composites at Venice Proceedings of the 15th European Conference on Composite Materials

Publication Date: 2012-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In our experiments HDPE/PA6 blends (75/25 wt%) were produced and maleic anhydride grafted polyethylene (PEgMA) was used as chemical coupling agent. To enhance the mechanical properties the blends were compounded with the layered structure montmorillonite (MMT) in different concentrations. The effect of PEgMA, MMT and their combination on the mechanical and melting properties were examined in this study.

Open Access: Yes

DOI: DOI not available

The effect of a communication-focused drama-based intervention on the social problem-solving of 10–11-year-olds

Publication Name: European Journal of Psychology of Education

Publication Date: 2026-03-01

Volume: 41

Issue: 1

Page Range: Unknown

Description:

A communication-focused drama-based program was delivered over a period of 1 year to 10- to 11-year-olds in Hungary. The aim of the program was to develop participants’ social problem-solving, coping strategies, and assertive communication. Outcomes were measured by the Assertiveness Questionnaire (Gaumer Erickson et al., 2016), the Social Problem-Solving Inventory–Revised (D’Zurilla et al., 2002), and the Ways of Coping Questionnaire (Folkman & Lazarus, 1988). N = 18 children received the intervention, and N = 28 children formed a control group. The 1-year program consisted of 18 sessions, each lasting for 90 min; they took place every 2 weeks and resulted in significant changes across three areas in the intervention group. Contrary to our hypothesis, rationality was not strengthened, but impulsivity and avoidance-escape were significantly reduced, and confrontation increased in frequency. In all three areas, assertive communication has significant explanatory power. This program was a suitable way to address some of the problem-solving styles and coping strategies that the research (e.g., Zsolnai, 2013) suggest may cause a range of life management difficulties (e.g., conflict, managing emotions) in adolescence.

Open Access: Yes

DOI: 10.1007/s10212-026-01068-3

Learning-aided observer design for improving autonomous vehicle safety

Publication Name: Scientific Reports

Publication Date: 2026-12-01

Volume: 16

Issue: 1

Page Range: Unknown

Description:

This paper introduces a novel method for the enhancement of automated vehicle safety and efficiency during critical manoeuvres. The fundamental of the presented method is the observer design architecture, in which lateral dynamic states of the vehicle are evaluated. The novel observer consists of both model-based and machine-learning-based methods to ensure the selected design performances, such as efficient trajectory tracking and safety evaluation of the autonomous vehicle. In contrast to the already introduced and applied stability index-based methods, the proposed safety evaluation process is able detect stability loss and performance degradation of the autonomous vehicle. In the proposed observer-based safety evaluation method, stability and performance loss detection is based on the comparison of model-based and learning-based state observation. The main novelty of the paper is the design of the reinforcement learning (RL) based observer in a guaranteed structure that results in small observation error even under nonlinear vehicle dynamics. Furthermore, a lateral safety index is defined based on the value of the improvement vector representing the addition to the model-based estimation. By this means, with the proposed safety evaluation method both safety and performance loss hazards can be identified simultaneously.

Open Access: Yes

DOI: 10.1038/s41598-026-35378-9

A physics-based reduced order model for urban air pollution prediction

Publication Name: Computer Methods in Applied Mechanics and Engineering

Publication Date: 2023-12-01

Volume: 417

Issue: Unknown

Page Range: Unknown

Description:

This article presents an innovative approach for developing an efficient reduced-order model to study the dispersion of urban air pollutants. The need for real-time air quality monitoring has become increasingly important, given the rise in pollutant emissions due to urbanization and its adverse effects on human health. The proposed methodology involves solving the linear advection–diffusion problem, where the solution of the Reynolds-averaged Navier–Stokes (RANS) equations gives the convective field. At the same time, the source term consists of an empirical time series. However, the computational requirements of this approach, including microscale spatial resolution, repeated evaluation, and low time scale, necessitate the use of high-performance computing facilities, which can be a bottleneck for real-time monitoring. To address this challenge, a problem-specific methodology was developed that leverages a data-driven approach based on Proper Orthogonal Decomposition with regression (POD-R) coupled with Galerkin projection (POD-G) endorsed with the discrete empirical interpolation method (DEIM). The proposed method employs a feedforward Neural Network (NN) to non-intrusively retrieve the reduced-order convective operator required for online evaluation. The numerical framework was validated on synthetic emissions and real wind measurements. The results demonstrate that the proposed approach significantly reduces the computational burden of the traditional approach and is suitable for real-time air quality monitoring. Overall, the study advances the field of reduced order modeling and highlights the potential of data-driven approaches in environmental modeling and large-scale simulations.

Open Access: Yes

DOI: 10.1016/j.cma.2023.116416

System-Level Harmonic NVH Engineering in Electric Drivetrains: A State-of-the-Art Review from Gear Microgeometry to Sound Branding

Publication Name: World Electric Vehicle Journal

Publication Date: 2026-05-01

Volume: 17

Issue: 5

Page Range: Unknown

Description:

Electric vehicles (EVs) have fundamentally changed the noise, vibration, and harshness (NVH) landscape of automotive powertrains. In the absence of masking internal-combustion-engine noise, harmonic components such as gear whine, electric-motor orders, and inverter-related tones become more perceptible and more critical to vehicle refinement. This review synthesizes the current state of the art in harmonic NVH engineering for electric drivetrains, focusing on the interactions between gear geometry, manufacturing variability, electromechanical coupling, structural transfer, and human sound perception. Classical mechanisms of gear-mesh excitation are revisited together with emerging EV-specific challenges, including long-wavelength flank deviations, ghost orders, lightweight housing dynamics, and psychoacoustic sound-quality requirements. The review further examines recent progress in predictive and data-driven approaches, including machine-learning-based gear-noise modeling, digital-twin concepts, and virtual NVH assessment workflows. Overall, the literature shows that harmonic NVH engineering in EVs is evolving from a conventional gear-noise problem into a multidisciplinary system-level task integrating gear dynamics, manufacturing science, structural acoustics, electric-drive control, psychoacoustics, and data-driven optimization. This review provides a structured synthesis of these developments and identifies key research gaps and future directions for the next generation of refined electric drivetrains.

Open Access: Yes

DOI: 10.3390/wevj17050240