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Found 6374 publications
Can It Still Be Used? Compression Strength Recovery of Corrugated Boxes After Moisture Exposure
Publication Name: Chemical Engineering Transactions
Publication Date: 2025-01-01
Volume: 121
Issue: Unknown
Page Range: 43-48
Description:
Moisture exposure is a common risk for corrugated fiberboard boxes (CFB) during transport, handling, or storage, especially in humid environments or due to accidental water contact. Boxes that have gotten wet are often seen as unsafe and not strong, so they are thrown away. However, this practice contributes to unnecessary material waste and higher environmental impact. This study aims to examine whether corrugated boxes that have been exposed to water and subsequently dried can retain sufficient compression strength to allow for safe use. In this study, the potential for strength recovery of CFB following water exposure and drying was investigated. The samples were immersed in water for a defined period to simulate realistic exposure scenarios, then dried under controlled conditions. Following this, Box Compression Tests (BCT) were carried out to evaluate the remaining compression strength. The results showed that while compression strength decreases due to water exposure, a significant portion of it can be recovered after drying, depending on the material structure and exposure duration, with reductions ranging from 17 % to 31 %. These findings suggest that moisture-affected boxes may remain suitable for use, which questions the default approach of immediate disposal. By quantifying post-drying strength loss, this research supports data-driven decisions in packaging use, potentially reducing material waste and promoting more sustainable logistics practices.
Open Access: Yes
DOI: 10.3303/CET25121008
The Role of Ergonomic Handrails in Inclusive Public Transport: User Aspects, Accident Risks and Design Guidelines †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
Inclusive design is not a design framework provided by legislation, but a design strategy that takes into account the diversity of abilities of users. Ensuring the mobility of people with disabilities is central to their social inclusion, which is why accessibility standards have been developed. Some elements of this are costly (e.g., low-floor vehicles), but simple and cost-effective solutions can make a significant difference in inclusive public transport. This paper uses qualitative methods—interviews, case studies and literature review—to illustrate one of the problem areas, the difficulties of grabs, and one of the potential areas for improvement: grab rails. In non-crash accidents, properly designed handholds play a key role in preserving the integrity of passengers and in creating a sense of physical/psychological safety, contributing to intuitive and independent use and to the social sustainability of public transport.
Open Access: Yes
Inverse Stackelberg Game with Final-Time Observations
Publication Name: Journal of Shanghai Jiaotong University Science
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
In this paper, we extend the framework of inverse optimal control to an inverse Stackelberg game (ISG) problem that involves a hierarchical two-player scenario. More specifically, the aim is to determine the unknown parameters in the leader’s and the follower’s objective functions based on their observed behavior in the final time window. Under a linear-quadratic setup, we first show that the parameter matrices in the objective functions for both the leader and the follower of the ISG are identifiable. Then, we propose a two-step approach to estimate the parameters in objective functions. In particular, the process first identifies the parameter matrix of the follower. Next, we identify the leader’s control gain within the final observation time window. Then we identify the leader’s matrix based on the identified leader’s control gain and the follower’s parameter matrix. Finally, we validate the effectiveness of our methodology through deterministic numerical experiments. (Figure presented.).
Open Access: Yes
The Role of Transylvania in the Process of Romanian Empire Building
Publication Name: Journal on European History of Law
Publication Date: 2025-01-01
Volume: 16
Issue: 2
Page Range: 141-150
Description:
After the emergence of the Romanian national consciousness, there was a continuous effort to unite the Romanians, who were scattered in several states, to create the so-called “Greater Romania”. In the 14th century, two almost ethnically homogeneous Romanian principalities, the Principalities of Wallachia and Moldavia, were established in the Balkans. The first phase of the Romanian national awakening, however, did not take placehere, but in neighbouring Transylvania, which belonged to the Hungarian crown. The first leaders of this movement were Transylvanian Greek Catholic church leaders, and it was only in the 19th century that intellectuals and politicians from the Transylvanian and Moldavian regions joined in. The main ambition of the movement was expressed by its slogan: “From Dniester to Tisza”, which meant the acquisition of the territories between the two rivers. As these areas were also inhabited by a Romanian-speaking population – mixed with other peoples –, the leading ideologists believed that the areas should be united to create the ideal homeland of the Romanians. According to the idea, in addition to the two principalities that were united in the second half of the 19th century and later became kingdoms, Bessarabia, which belonged to the Russian Empire, Dobruja, which belonged to Bulgaria, and Transylvania, the largest and most populated territory, were considered part of the Romanian homeland, the “Tara Romanesca”. In the stormy Balkan (and European) history of the turn of the 19th and 20th centuries, the former two territories were attached to Romania for longer or shorter periods, but the most serious attempt was to acquire Transylvania, which was finally annexed in 1918, establishing “Greater Romania”.
Open Access: Yes
DOI: DOI not available
Pontfelhők geometriai és attribútumtorzulásai
Publication Name: Geodezia Es Kartografia
Publication Date: 2025-01-01
Volume: 77
Issue: 3
Page Range: 18-26
Description:
The paper addresses geometric and attribute distortions in point clouds, which can arise at various stages of data acquisition and processing. The authors present the main sources of distortions—such as sensor limitations, platform movement, and environmental influences—and their impact on point density, data distribution, and attribute reliability. They detail statistical methods for quantitative evaluation of distortions (e.g., Getis–Ord Gi*, Moran’s I, Gini coefficient), which allow systematic measurement and correction of errors. The study emphasizes that analyzing and mitigating distortions is essential for creating more accurate spatial models and producing reliable geoinformatics analyses.
Open Access: Yes
Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems
Publication Name: Mathematics
Publication Date: 2025-01-01
Volume: 13
Issue: 1
Page Range: Unknown
Description:
Traffic congestion at a single intersection can propagate and thus affect adjacent intersections as well, potentially resulting in prolonged gridlock across an entire urban area. Despite numerous research efforts aimed at developing intelligent traffic signal control systems, urban areas continue to experience traffic congestion. This paper presents a novel agent-based fuzzy traffic control system for multiple road intersections. The proposed system is designed to operate in a decentralized manner, with each intersection having its own agent (fuzzy controller) functioning concurrently. The intelligent fuzzy controller of the system can recognize emergency vehicles, assess the queue length and waiting time of vehicles, measure the distance of vehicles from intersections, and consider the cumulated waiting times of short vehicle queues. Two distinct types of agent-based intelligent fuzzy traffic control systems were implemented for comparison: one involving collaboration between an agent and its immediate neighboring agent(s) (where one intersection exchanges traffic data with its immediate neighboring intersection(s)), and the other implementing a non-collaborative agent-based intelligent fuzzy traffic control system (where the individual intersection has no direct communication). Following the experimental simulations, the results were compared with those of existing intelligent fuzzy traffic control systems that lack any module to calculate the distance of the vehicles from the intersection. The results demonstrated that the proposed agent-based system of controllers exhibited superior performance compared with the existing fuzzy controllers in terms of indicators such as average waiting time, fuel consumption, and CO2 emissions. For instance, the proposed system reduced the average waiting time of vehicles at an intersection by 48.65% compared with the existing three-stage intelligent fuzzy traffic control system. In addition, a comparison was conducted between non-collaborating and collaborating agent-based intelligent fuzzy traffic control systems, where collaboration achieved better results than the non-collaborating system. In the simulation experiments, an interesting new feature emerged: despite any direct communication missing at multiple intersections, green waves evolved with time. This emergent feature suggests that fuzzy controllers have the potential to evolve and adapt to traffic complexity issues in urban environments when operating in an autonomous agent-based mode. This study demonstrates that agent-based fuzzy controllers can effectively communicate with one another to share traffic data and improve the overall system performance.
Open Access: Yes
DOI: 10.3390/math13010124
A Review of Modern Strategies for Enhancing Power Quality and Hosting Capacity in Renewable-Integrated Grids: From Conventional Devices to AI-Based Solutions
Publication Name: CMES Computer Modeling in Engineering and Sciences
Publication Date: 2025-01-01
Volume: 145
Issue: 2
Page Range: 1349-1388
Description:
Distribution systems face significant challenges in maintaining power quality issues and maximizing renewable energy hosting capacity due to the increased level of photovoltaic (PV) systems integration associated with varying loading and climate conditions. This paper provides a comprehensive overview on the exit strategies to enhance distribution system operation, with a focus on harmonic mitigation, voltage regulation, power factor correction, and optimization techniques. The impact of passive and active filters, custom power devices such as dynamic voltage restorers (DVRs) and static synchronous compensators (STATCOMs), and grid modernization technologies on power quality is examined. Additionally, this paper specifically explores machine learning and AI-driven solutions for power quality enhancement, discussing their potential to optimize system performance and facilitate renewable energy integration. Modern optimization algorithms are also discussed as effective procedures to find the settings for power system components for optimal operation, including the allocation of distributed energy resources and the tuning of control parameters. Added to that, this paper explores the methods to maximize renewable energy hosting capacity while ensuring reliable and efficient system operation. By synthesizing existing research, this review aims to provide insights into the challenges and opportunities in distribution system operation and optimization, highlighting future research directions that enhance power quality and facilitate renewable energy integration.
Open Access: Yes
A global framework for integrating public health into wellbeing: why a public wellbeing system is needed
Publication Name: Frontiers in Public Health
Publication Date: 2025-01-01
Volume: 13
Issue: Unknown
Page Range: Unknown
Description:
There is a growing focus on public health initiatives that prioritize wellbeing. The main question of our study is whether this, in its current form, can really represent a new response to the challenges of previous strategies, or whether there is a greater chance that it will essentially reproduce the problems associated with the paradoxical situation of public health. Based on a review, analysis and evaluation of the literature on wellbeing in public health, we outlined the foundations of a new meta-theory of wellbeing and a possibility for its social application. In our view, wellbeing is seen as a social representation of a combination of positive and negative freedom of choice concerning the quality of everyday life, used in a positioning process involving both individual and collective aspects. Health is a particular aspect of the social representation and positioning of wellbeing, which encompasses aspects of the physical, psychological, social and spiritual functioning of individuals. The wellbeing meta-theory also opens up the possibility for more effective solutions to the social challenges related to wellbeing and salutogenetic health. It underscores the importance of the need for a dedicated social subsystem where the goals and organizational culture of the organizations involved are focused on wellbeing and health promotion. In our study, we consider this to be the Public Wellbeing System (PWS). Our conclusion is that the development and operation of a new set of institutions—the Public Wellbeing System (PWS)—based on the co-production of services that meet the needs and demands of society, and dedicated to the promotion of wellbeing, may provide an opportunity to overcome the public health paradox.
Open Access: Yes
Evaluating Deep Learning Algorithms for Freeway Mainstream Traffic Control
Publication Name: Lecture Notes in Networks and Systems
Publication Date: 2025-01-01
Volume: 1258 LNNS
Issue: Unknown
Page Range: 289-299
Description:
Traffic congestion is a universal problem that significantly impacts urban mobility and economic productivity. Accurate traffic flow prediction is crucial for efficient traffic management and congestion mitigation. Traditional methods often struggle to capture the complex temporal dependencies in traffic data. This study explores the effectiveness of Temporal Convolutional Network (TCN) models compared to Long Short-Term Memory (LSTM) models for predicting traffic volumes on freeway networks. Previous research has largely focused on LSTM models, leaving a gap in understanding the potential advantages of TCN models in this context. We address this gap by conducting a comprehensive comparison of LSTM and TCN models, training them on a dataset representing approximate traffic flow, and evaluating their performance using metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R2). Our findings indicate that the TCN model outperforms the LSTM model, achieving lower MSE and MAE values and a higher R2 score. These results suggest that TCN models can more accurately predict traffic volumes under conditions with the least captured traffic data, offering a promising tool for real-time approximate traffic management and congestion prevention with reasonable prediction performance.
Open Access: Yes
