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QUANTITATIVE ANALYSIS AND OPTIMIZATION OF ENERGY EFFICIENCY IN ELECTRIC MULTIPLE UNITS

Szabolcs Fischer Mykola Sysyn Dmytro Kurhan Szabolcs Kocsis Szurke Bence Hermán

Publication Name: Facta Universitatis Series Mechanical Engineering

Publication Date: 2025-08-01

Volume: 23

Issue: 2

Page Range: 351-375

Description:

The increasing urgency for sustainable transportation solutions necessitates a thorough examination of energy efficiency within railway systems. This study investigates the energy performance of Siemens Ventus (i.e., Siemens Desiro ML type) electric multiple units on Austria's Raaberbahn network, focusing on route-specific energy consumption and the optimization of regenerative braking. Utilizing data collected from January to May 2023, the research employs a robust methodology that integrates statistical analysis, curve-fitting, and geospatial modeling to assess energy trends along routes connecting Vienna, Bratislava, and Deutschkreutz. The findings reveal that terrain, operational practices, and external environmental factors significantly contribute to energy inefficiencies. Specifically, hotspots of energy overconsumption were identified, leading to the development of tailored optimization models for each route. The analysis also produced heatmaps that illustrate critical spatial and temporal patterns, which are essential for implementing targeted interventions aimed at enhancing energy efficiency.

Open Access: Yes

DOI: 10.22190/FUME241103001F

Corrigendum to “Global trade of medicinal and aromatic plants. A review” [J. Agricult. Food Res. 21 (2025) 101910] (Journal of Agriculture and Food Research (2025) 21, (S2666154325002819), (10.1016/j.jafr.2025.101910))

Mohammad Taghi Ebadi Sahar Zamani Mehran Fathi Ákos Máthé

Publication Name: Journal of Agriculture and Food Research

Publication Date: 2025-08-01

Volume: 22

Issue: Unknown

Page Range: Unknown

Description:

The authors regret We recently reviewed the published version of our article “Global trade of medicinal and aromatic plants: A review” and noticed an error in the units reported in Figs. 1, 3 and 4. Specifically, in the columns related to export and import values, the unit was incorrectly labelled as “million” instead of “thousand". The authors would like to apologise for any inconvenience caused.

Open Access: Yes

DOI: 10.1016/j.jafr.2025.102040

A Pilot Study of the Effect of Locomotor and Mechanical Loads on Elite Rowers During Competition Days

Ferenc Ihász Robert Podstawski Johanna Takács Antonio Ferraz István Barthalos Lili Kósa Zsolt Bálint Katona Bożena Hinca Zoltán Alföldi

Publication Name: Sports

Publication Date: 2025-08-01

Volume: 13

Issue: 8

Page Range: Unknown

Description:

(1) Background: Fatigue impacts neuromuscular performance, especially in endurance sports like rowing. The aim is to explore how continuous workload affects explosiveness and fatigue progression. This study examines acute fatigue during repeated race events by assessing vertical jump height, force output, and subjective fatigue over three consecutive days at the 2024 Hungarian National Rowing Championships. (2) Methods: Nine rowers (five women, four men; mean age 20.17 ± 1.73 years) competed in multiple 2000 m races over three days. Lower limb explosiveness was measured via countermovement jump (CMJ) using a Kistler force plate, pre- and post-race. Heart rate data were recorded with Polar Team Pro®. Subjective fatigue was assessed using the ‘Daily Wellness Questionnaire’. (3) Results: We found a significant difference in the pattern of the medians of the force exerted by males during the jump between the results of the Thursday preliminaries (ThuQMe = 13.3) and the second final (ThuF2Me = −75.5). Women showed no notable changes. (4) Conclusion: Repeated high-intensity races induce neuromuscular fatigue in men, reflected in reduced explosiveness and increased subjective fatigue. Future research should incorporate biochemical markers to deepen the understanding of fatigue mechanisms.

Open Access: Yes

DOI: 10.3390/sports13080254

Factors Affecting Green Performance of Food Supply Chain Firms: A Parallel Mediation Model

Ikramuddin Junejo Md Billal Hossain Faisal Ejaz Sarmad Ejaz Belal Mahmoud AlWadi

Publication Name: Emerging Science Journal

Publication Date: 2025-08-01

Volume: 9

Issue: 4

Page Range: 2215-2228

Description:

Objectives: The objective of this study was to examine the impact of organizational green culture (OGC) on green innovation (GI) and sustainable entrepreneurship practices (SEP), which collectively enhance green performance (GP) in Pakistani food chain sector small and medium enterprises (SMEs). This research investigates how green innovation and sustainable entrepreneurship practices mediate each other towards achieving better green performance. Method: The authors chose deductive quantitative research along with Google Forms-based online surveys to gather data from 239 SMEs using convenience sampling. Structural equation modeling through SmartPLS detected all relationship effects between constructs within the research model. Findings: The study confirms that organizational green culture leads to increased GI and SEP, which in turn contributes to enhanced GP, while SEP operates as the essential mediator between OGC and GP in establishing how cultural values become sustainable practices and environmental improvements. The research merges OGC and innovation aspects with sustainability practices and demonstrates their effects on SMEs through empirical research. Novelty: The research uncovers SEP as a key connection between green culture and performance, which provides business solutions for SMEs that want to merge cultural elements with innovative approaches for sustainability. The research explores green entrepreneurship within emerging markets by demonstrating that developing an organizational green culture leads to creative processes that create sustainable outcomes that enhance environmental results. The paper makes an exceptional contribution by examining two distinct mediators: green innovation and sustainable entrepreneurship practices.

Open Access: Yes

DOI: 10.28991/ESJ-2025-09-04-026

Data-Driven Identification of Gearbox Housing Structures Using Acoustic Radiation Spectra

Krisztian Horvath Krisztián Horváth Krisztián Horváth

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

THEORIES OF CULTURE-LED URBAN DEVELOPMENT: INITIATIVES IN DUBLIN

Tamara Zsuzsanna Böcz

Publication Name: Theoretical and Empirical Researches in Urban Management

Publication Date: 2025-08-01

Volume: 20

Issue: 3

Page Range: 41-58

Description:

This paper is exploratory research into the evolution of the theories and the practice of culture-led urban development. As cities and urban spaces have existed for centuries. Their purpose and functions constantly changing and evolving. With globalisation, numerous technological revolutions, and continuous innovations the demographical changes were often rapid to which swift adaptation was crucial. The ever changing and diversification of needs from the people inhabiting cities as well as global concerns led to new innovative approaches to urban development. One such approach is the idea of Creative Cities within which culture arose as a leading concern in the creation of urban development plans. This article will highlight some of the key areas and approaches on how culture can be utilised in urban development. The way in which creativity and culture is measured within the European Union. As well showcase the evolution of the culture led urban development approach of Dublin from the 1990s and finally examine the current urban development plans of Dublin and how they utilise culture in their plans.

Open Access: Yes

DOI: DOI not available

Early Detection of ITSC Faults in PMSMs Using Transformer Model and Transient Time-Frequency Features

Adrienn Dineva Adam Zsuga

Publication Name: Energies

Publication Date: 2025-08-01

Volume: 18

Issue: 15

Page Range: Unknown

Description:

Inter-turn short-circuit (ITSC) faults in permanent magnet synchronous machines (PMSMs) present a significant reliability challenge in electric vehicle (EV) drivetrains, particularly under non-stationary operating conditions characterized by inverter-driven transients, variable loads, and magnetic saturation. Existing diagnostic approaches, including motor current signature analysis (MCSA) and wavelet-based methods, are primarily designed for steady-state conditions and rely on manual feature selection, limiting their applicability in real-time embedded systems. Furthermore, the lack of publicly available, high-fidelity datasets capturing the transient dynamics and nonlinear flux-linkage behaviors of PMSMs under fault conditions poses an additional barrier to developing data-driven diagnostic solutions. To address these challenges, this study introduces a simulation framework that generates a comprehensive dataset using finite element method (FEM) models, incorporating magnetic saturation effects and inverter-driven transients across diverse EV operating scenarios. Time-frequency features extracted via Discrete Wavelet Transform (DWT) from stator current signals are used to train a Transformer model for automated ITSC fault detection. The Transformer model, leveraging self-attention mechanisms, captures both local transient patterns and long-range dependencies within the time-frequency feature space. This architecture operates without sequential processing, in contrast to recurrent models such as LSTM or RNN models, enabling efficient inference with a relatively low parameter count, which is advantageous for embedded applications. The proposed model achieves 97% validation accuracy on simulated data, demonstrating its potential for real-time PMSM fault detection. Additionally, the provided dataset and methodology contribute to the facilitation of reproducible research in ITSC diagnostics under realistic EV operating conditions.

Open Access: Yes

DOI: 10.3390/en18154048

Socio-political determinants of circular economy behavior: A cross-sectional analysis across Italy

Cristian Barra Luigi Aldieri Pasquale Marcello Falcone Concetto Paolo Vinci

Publication Name: Socio Economic Planning Sciences

Publication Date: 2025-08-01

Volume: 100

Issue: Unknown

Page Range: Unknown

Description:

The circular economy (CE) has emerged as a crucial alternative to the traditional linear economic model, which relies on resource extraction, production, and waste disposal, resulting in significant environmental degradation and resource depletion. In contrast, the CE emphasizes resource efficiency through practices such as reusing, repairing, refurbishing, and recycling, providing both environmental and economic benefits. This study investigates the complex interaction between socio-political factors and individual-level CE practices in Italy, addressing gaps in existing research that primarily focus on specific consumer behaviors or demographic characteristics. Particularly, utilizing probit and multivariate probit analyses on the 2021 AVQ “Aspects of Daily Life” dataset from ISTAT, the research examines how socio-political involvement, budget constraints, positive educational externalities, and demographic factors influence CE behaviors. The findings reveal that socio-political factors, particularly political trust in local governments, significantly influence circular practices, with higher trust associated with greater adoption of sustainable transportation and local products, while lower political engagement correlates with increased waste and reduced sustainability, highlighting the need for targeted educational initiatives and localized policies to promote a circular economy effectively.

Open Access: Yes

DOI: 10.1016/j.seps.2025.102252

The role of artificial intelligence in enhancing corporate environmental information disclosure: Implications for energy transition and sustainable development

Hyoungsuk Lee Umer Shahzad Xin Zhao Yongshun Tong

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

DOI: 10.1016/j.eneco.2025.108680