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Found 6383 publications
Improving Material Tracking for Sustainable Construction: A Standard Operating Procedure (SOP) Framework for Resource Efficiency
Publication Name: Buildings
Publication Date: 2025-06-01
Volume: 15
Issue: 11
Page Range: Unknown
Description:
Inefficient material tracking continues to be a major challenge in sustainable construction, often leading to unnecessary waste, budget overruns, and project delays. While many digital tools have been introduced in recent years, there is still a lack of practical, field-tested frameworks that combine these technologies with clear, structured procedures, especially in resource-constrained environments. This study introduces a Standard Operating Procedure (SOP) framework designed to improve materials tracking systems (MTSs) by integrating QR codes, GPS tracking, and cloud-based dashboards. Together, these tools support more accurate planning, smoother coordination, and real-time monitoring from the early design stages to on-site implementation. A mixed-methods approach was used, combining surveys with construction professionals and focus group discussions with engineers, IT specialists, and logistics staff. The findings highlight procurement and implementation as the phases most prone to inefficiencies, particularly around material receiving, quality checks, and on-site placement. The validated SOP framework shows strong potential to improve tracking accuracy, reduce material waste, and streamline construction workflows. It offers a flexible, easy-to-use system for integrating sustainability into everyday project practices. Looking ahead, this study also points to future opportunities for applying AI-based tools—such as predictive tracking and automated quality checks—to further improve decision-making and resource efficiency in construction projects.
Open Access: Yes
Key Performance Indicators for Evaluating Electric Buses in Public Transport Operations
Publication Name: Vehicles
Publication Date: 2025-06-01
Volume: 7
Issue: 2
Page Range: Unknown
Description:
The evaluation of electric buses used in public transportation operations encompasses several critical factors that directly influence the operational efficiency, as well as the economic viability, environmental advantages, and user experience. Energy consumption is a critical metric for assessing the energy efficiency of electric buses. It facilitates a better understanding of vehicle performance across varying road conditions and advances the implementation of energy-saving solutions. The passenger demand model is a tool used to assess the quality and experience of electric buses, with the assessment being based on real usage. The operational mileage is defined as the driving distance of electric buses on a single charge. This parameter has a significant impact on both urban coverage and route optimization. The article under consideration identifies evaluation indicators for electric buses. These indicators are derived from a set of 100 questionnaire responses, which were collected in Győr, Hungary. The classification of the indicators into three segments—mechanical, operational and bus transportation system—is proposed, with the underlying rationale and significance of each indicator’s selection being elucidated. The findings indicate that this component is essential for developing a comprehensive evaluation system for electric buses and serves as a solid foundation for more intricate future studies.
Open Access: Yes
Dem-driven investigation and AutoML-Enhanced prediction of Macroscopic behavior in cementitious composites with Variable frictional parameters
Publication Name: Materials and Design
Publication Date: 2025-06-01
Volume: 254
Issue: Unknown
Page Range: Unknown
Description:
This study presents a numerical investigation and predictive modeling framework to evaluate the influence of microscale frictional parameters on the mechanical behavior and failure mechanisms of cementitious composites. In the first phase, discrete element modeling (DEM) was employed to analyze the effects of bonded friction angle and non-bonded friction coefficient on the stress–strain response, failure evolution, and macro-scale properties. The results revealed a distinct transition from tensile to shear-dominated failure modes beyond a critical friction angle, accompanied by notable changes in compressive strength and deformation characteristics. Additionally, the role of non-bonded friction coefficient in post-failure behavior was identified, emphasizing its influence on load-redistribution. In the second phase, an AutoML-driven artificial neural network (ANN) was optimized via grid search, selecting an optimal four-layer model to predict macroparameters from microscale DEM inputs. The proposed ANN demonstrated high predictive accuracy, effectively capturing nonlinear dependencies while significantly reducing the need for additional numerical simulations. This integration of DEM and AI-based predictive modeling provides a computationally efficient, scalable solution for material characterization, enabling faster, data-driven insights into cementitious composite behavior without reliance on extensive simulation campaigns.
Open Access: Yes
Young Adults’ Feelings and Knowledge of Climate Anxiety
Publication Name: Journal of Sustainability Research
Publication Date: 2025-06-01
Volume: 7
Issue: 2
Page Range: Unknown
Description:
This study investigates the impact of climate anxiety on young adults’ consumer and social behaviour. Data were collected via a questionnaire survey among 696 university students from Széchenyi István University, Budapest Metropolitan University, and Neumann János University. The survey focused on various aspects of climate anxiety, including its frequency, intensity, perceived life impact, emotional responses, and management strategies. The analysis, supported by AI tools, identified two distinct clusters: one with moderate anxiety levels and a strong interest in learning about climate change, and another with higher anxiety levels but less desire for further information. Various statistical models, including Naive Bayes, logistic regression, and random forests, were employed to identify behavioural patterns, with decision trees showing the lowest classification error. The study highlights the significant influence of climate anxiety on the shift towards sustainable consumption and active engagement in climate action. Recommendations for future research include the broader application of deep learning models and extending the study to other demographic groups. Longitudinal data collection is also suggested to track long-term trends and inform effective public policy and communication strategies. The findings emphasise the need for comprehensive approaches to understanding and addressing climate anxiety’s societal impacts.
Open Access: Yes
DOI: 10.20900/jsr20250025
Development of Magnetic Hysteresis Loop Measurement System for Characterization of 3D-Printed Magnetic Cores
Publication Name: Electronics Switzerland
Publication Date: 2025-06-01
Volume: 14
Issue: 11
Page Range: Unknown
Description:
Today, numerous advanced options exist for analyzing and measuring magnetic hysteresis loops and core loss across a broad spectrum of applications. Most of these systems are compact and ready to use, fulfilling the measurement and data processing requirements for laminated iron cores according to the standards. However, modeling newly developed materials with complex structures or the high-frequency behavior of iron cores, and the computation of dynamic hysteresis properties’ temperature dependence, are still challenging problems in the field. Moreover, these standardized measurement tools are relatively expensive, and most of them represent a black box that impedes research and further development. This paper presents the development of a cheap and accessible measurement system that is explicitly designed for recording the hysteresis properties of 3D-printed iron cores. The paper presents a comprehensive overview of the design process, components, circuitry, and simulations integral to this project. The paper presents a completed circuit simulation conducted using LTspice and validation of the prototype’s measurement performance. The measurements obtained with the proposed system show good agreement with those of the reference setup, demonstrating its accuracy and practical applicability.
Open Access: Yes
A Novel Method for Simulation Model Generation of Production Systems Using PLC Sensor and Actuator State Monitoring
Publication Name: Journal of Sensor and Actuator Networks
Publication Date: 2025-06-01
Volume: 14
Issue: 3
Page Range: Unknown
Description:
This article proposes and validates a novel methodology for automated simulation model generation of production systems based on monitoring sensors and actuator states controlled by Programmable Logic Controllers during regular operations. Although conventional Discrete Event Simulation is essential for material flow analysis and digital experimentation in Industry 4.0, it remains a resource-intensive and time-consuming endeavor—especially for small and medium-sized enterprises. The approach introduced in this research eliminates the need for prior system knowledge, physical inspection, or modification of existing control logic, thereby reducing human involvement and streamlining the model development process. The results confirm that essential structural and operational parameters—such as process routing, operation durations, and resource allocation logic—can be accurately inferred from runtime data. The proposed approach addresses the challenge of simulation model obsolescence caused by evolving automation and shifting production requirements. It offers a practical and scalable solution for maintaining up-to-date digital representations of manufacturing systems and provides a foundation for further extensions into Digital Shadow and Digital Twin applications.
Open Access: Yes
DOI: 10.3390/jsan14030055
The Role of Regulatory Sandboxes in FinTech Innovation: A Comparative Case Study of the UK, Singapore, and Hungary
Publication Name: Fintech
Publication Date: 2025-06-01
Volume: 4
Issue: 2
Page Range: Unknown
Description:
Regulatory sandboxes have emerged as policy instruments designed to support FinTech innovation while maintaining supervisory oversight. By allowing firms to test financial products in controlled environments, sandboxes aim to reduce regulatory uncertainty and facilitate market entry. Despite their growing adoption, empirical evidence of their effectiveness remains limited, particularly in emerging markets. This study explores the impact of regulatory sandboxes on innovation and market access through a qualitative comparative case study of the United Kingdom, Singapore, and Hungary. Drawing on document analysis and thematic coding, the research evaluates sandbox design, regulatory support, and innovation outcomes across the three jurisdictions. Findings show that sandboxes enhance access to funding, accelerate product development, and foster regulator–firm collaboration. While the UK and Singapore benefit from mature ecosystems and structured frameworks, Hungary illustrates sandbox potential in developing markets. The paper contributes to FinTech regulation literature and provides policy recommendations for optimizing sandbox design across varied institutional contexts.
Open Access: Yes
One health agriculture: Heat stress mitigation dilemma in agriculture
Publication Name: One Health
Publication Date: 2025-06-01
Volume: 20
Issue: Unknown
Page Range: Unknown
Description:
The concept of One Health was developed as a successful strategy for addressing global crises that impact the health of animals, humans, and plants. The agriculture industry is facing a huge dilemma due to climate change and the impacts of heat stress, which might pose a threat to mankind in the future. In order to enhance the management of heat stress in the agriculture sector (Agri-heat stress), we suggest implementing the One Health approach. This is because the existing methods employed to alleviate heat stress in both livestock and crop farming may have side-effects on the well-being of animals, plants, humans, and the ecosystem. This review article examines the “dilemma” of mitigating heat stress in animal and crop husbandry. It discusses the One Health approach to heat stress, including a recommended strategy for reducing Agri-heat stress using the One Health approach. The study also highlights the benefits of adopting the One Health approach in mitigating Agri-heat stress. In our opinion, the efficacy of the One Health Approach in reducing Agri-heat stress depends on the process of conceptualization. This process includes recognizing the issue or hypothesis, as well as incorporating cooperating teams in the creation of environmentally friendly approaches. The efficacy and challenges of implementing this notion arise from the precise coordination of resources and collaborators.
Open Access: Yes
Optimal parameter extraction of equivalent circuits for single- and three- phase Power transformers based on arctic puffin algorithm accomplished with experimental verification
Publication Name: Results in Engineering
Publication Date: 2025-06-01
Volume: 26
Issue: Unknown
Page Range: Unknown
Description:
The power transformer is a critical device in power systems. This paper addresses one of the major problems which hopes to enhance the accuracy of estimation of parameters, which is critical in power transformer modeling, maintenance, and operating efficiency. In that context, this work estimates the parameters of single- and three-phase power transformers by a new optimizer called Arctic Puffin Optimization Algorithm (APO). The algorithm is intended to improve estimation of transformer parameters with the goal of reducing the error incurred between the estimated and actual values of the parameters. To verify the accuracy of the APO, experimental measurements were conducted on single- and three-phase transformers. The assessment of the algorithm's effectiveness was performed against the effectiveness of other commonly used estimating methods. The results have shown that APO increases the accuracy of estimation of the parameters of both single- and three-phase transformers to considerable levels. Dependability of the APO was established by experimental verification, which disclosed an ultimate connection between the resultant quantities and actual measurements. The study also confirmed APO can be useful for transformer parameter estimation because APO converges more rapidly and more precisely compared with traditional methods of the literature.
Open Access: Yes
