Search Everything

Tip: Search using "First Name + Last Name", e.g.
János Kiss instead of Kiss János.

Publications - 6342

Dynamics of Rolling Wheels with Elliptical Tread Profiles

Mate Antali Gabor Kupi

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 255-262

Description:

In this paper, the dynamics of a loose wheel is considered rolling on a horizontal plane, where the tread profile of the wheel is ellipsoidal. From the equations of motion, a two-parametric family of steady motions are obtained, corresponding to the rolling motion on a circular or straight line with a uniform rotational speed and tilt angle. It is shown that compared to the geometries analysed in the literature, the elliptical tread profile leads to a significant change in the qualitative behaviour of the wheel.

Open Access: Yes

DOI: 10.3233/ATDE240553

Investigation of the Effects of Biodegradable and Compostable Polymers as Sources of Microplastics on the Water-Soil Continuum: A Review

Gergely Zoltán Macher Dalma Bódizs Kornélia Horváth Anett Bedő

Publication Name: Chemical Engineering Transactions

Publication Date: 2023-01-01

Volume: 107

Issue: Unknown

Page Range: 307-312

Description:

The amount of research and publications related to microplastic pollution has been steadily increasing in recent years, but at the same time, our current knowledge on the topic is still based on occasional point measurements. As a result of these point measurements, it becomes obvious that new research areas and disciplines are also connected to the topic of microplastics. Various biotic and abiotic processes can cause microplastics to enter the environment and spread within it. All of these mechanisms can arise from the moisture conditions of the tested medium, temperature differences, or even from the decomposing and transforming activities of microorganisms. The rise of biodegradable and compostable plastic bags can also be considered a source of this kind since polymer products labelled as environmentally friendly can be identified as secondary sources during their decomposition processes. Therefore, both industrial and household compost can contain microscopic polymer residues, the application of which involves a potential risk of environmental pollution. In recent years, several international studies have dealt with various aspects of the degradation of these products, including the use of problems caused by residual microplastics and their environmental effects. The focus of our paper is not on the development of a new scientific methodology but a summary of the current situation formed through research results dealing with the current environmental safety and environmental health risks of microplastic pollution caused by biodegradable polymers.

Open Access: Yes

DOI: 10.3303/CET23107052

Exploring the nexus of blockchain and food supply chain traceability: A bibliometric analysis

Horst Treiblmaier John G. Keogh Abderahman Rejeb Karim Rejeb Heba F. Zaher

Publication Name: Food and Humanity

Publication Date: 2026-05-01

Volume: 6

Issue: Unknown

Page Range: Unknown

Description:

This research examines the development of academic studies on the use of blockchain for food supply chain traceability through an extensive bibliometric investigation of publications from 2018 to 2025. The review highlights the most active scholars, institutions, journals, and countries contributing to this area, offering a clear picture of the leading actors in the field. By applying keyword co-occurrence analysis and network mapping, the study uncovers patterns in citations, collaboration structures, and thematic clusters. Results indicate a strong upward trajectory in publications, with an annual growth rate of more than 60%, signaling accelerating attention to blockchain-enabled traceability solutions. Collaboration patterns point to a concentration of activity in technologically advanced regions, where cross-border partnerships are stronger, while emerging economies show more limited international engagement. The analysis also reveals that partnerships often form around shared areas of interest and reflects a clustering effect. A small set of authors and institutions dominates knowledge production, which is consistent with the Matthew effect. Overall, these dynamics suggest that while the field is rapidly expanding, it remains unevenly distributed. The study offers both an overview of the intellectual landscape and practical guidance for future research aimed at broadening participation, enhancing collaboration, and more closely linking blockchain with sustainability and food system innovation.

Open Access: Yes

DOI: 10.1016/j.foohum.2026.101208

Processing systems design considering resilience

Ákos Orosz Jean Pimentel Ferenc Friedler

Publication Name: Computer Aided Chemical Engineering

Publication Date: 2021-01-01

Volume: 50

Issue: Unknown

Page Range: 807-812

Description:

The resilience of a system is defined as the system's capability of recovering from failures. Traditionally, only predictable aspects are considered when designing processing systems. Evaluation of these aspects is performed via assessment of exact indicators and enumeration of all cause-effect options. However, such evaluation is not appropriate for determining the resilience of processing systems, since resilience is based on unexpected events in addition to the expected ones. Consequently, the cause part of the cause-effect relation is not known or not effective. In the current work, the general formula for determining resilience of a system is embedded into a P-graph based process synthesis algorithm. Thus, the resilience can be considered when selecting the most preferred process during its synthesis. The result is illustrated by synthesizing a process of adipic acid production by nitric acid oxidation of KA oil.

Open Access: Yes

DOI: 10.1016/B978-0-323-88506-5.50126-1

Ensemble deep learning approach for traffic video analytics in edge computing

Dragan Pamucar Sathya Krishnamoorthi Vani Rajasekar Malathy Sathyamoorthy Sathya Krishnamoorthi

Publication Name: Scientific Reports

Publication Date: 2026-12-01

Volume: 16

Issue: 1

Page Range: Unknown

Description:

Video analytics is the new era of computer vision in identifying and classifying objects. Traffic surveillance videos can be analysed to using computer vision to comprehend the road traffic. Monitoring the real-time road traffic is essential to control them. Computer vision helps in identifying the vehicles on the road, but the present techniques either perform the video analysis on the cloud platform or the edge platform. The former introduces more delay in processing while controlling is needed in real-time, the latter is not accurate in estimating the current road traffic. YOLO algorithms are the most notable ones for efficient real-time object detection. To make such object detections feasible in lightweight environments, its tinier version called Tiny YOLO is used. Edge computing is the efficient framework to have its computation done on the edge of the physical layer without the need to move data into the cloud to reduce latency. A novel hybrid model of vehicle detection and classification using Tiny YOLO and YOLOR is constructed at the edge layer. This hybrid model processes the video frames at a higher rate and produces the traffic estimate. The numerical traffic volume is sent to Ensemble Learning in Traffic Video Analytics (ELITVA) which uses F-RNN to make decisions in reducing the traffic flow seamlessly. The experimental results performed on drone dataset captured at road signals show an increase in precision by 13.8%, accuracy by 4.8%, recall by 17.4%, F1 score by 19.9%, and frame rate processing by 12.8% compared to other existing traffic surveillance systems and efficient controlling of road traffic.

Open Access: Yes

DOI: 10.1038/s41598-025-25628-7

Random forest regression on pullout resistance of a pile

Edina Koch Shaymaa Alsamia

Publication Name: Pollack Periodica

Publication Date: 2024-10-16

Volume: 19

Issue: 3

Page Range: 28-33

Description:

This research aims to study the pullout resistance of a helical pile using three methods of machine learning techniques, which are: random forest regression, support vector regression, and adaptive neuro-fuzzy inference system, based on experimental results of a helical pile. The performance of these three techniques has been d compared and the results show that random forest algorithm has best performance than neuro-fuzzy inference system and support vector technique. The results show that machine learning considered a good tool in terms of estimating the pullout resistance of helical piles in the soil.

Open Access: Yes

DOI: 10.1556/606.2024.01052

Customized 3D-Printed Insoles for Diabetic Foot Care: Finite Element analysis and Machine Learning Approach

Yaodong Gu Gusztáv Fekete Zixiang Gao Yining Xu Zhenghui Lu Xin Li Qiaolin Zhang Hairong Chen

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 515-522

Description:

Diabetic foot is a common complication in patients with diabetes, which can lead to plantar ulcers and even necessitate amputation. This study aims to utilize finite element analysis to simulate the offloading effects of 3D-printed insoles with various structures on plantar pressure and to explore the use of machine learning in providing optimal plantar pressure offloading solutions for patients with diabetic foot. The results demonstrated that negative Poisson's ratio structured insoles were more effective in reducing plantar pressure (reducing pressure by an average of 39.2%) than barefoot and conventional structures. This was achieved through a unique lateral contraction deformation, which increased the contact area with the foot. The pressure-reducing effect of insoles may be weight-related, suggesting that heavier patients may require stiffer insoles. However, the machine learning algorithm demonstrated a poor fit (only 60.75%) in the task of recommending suitable insoles. In conclusion, this study demonstrated the significant effect of negative Poisson's ratio structured insoles in reducing plantar pressure in diabetic patients, providing new ideas for diabetic foot protection. With the development of data analysis technology in the future, the feasibility and application of personalised insole design will be more promising.

Open Access: Yes

DOI: 10.3233/ATDE240588

ACTN3 rs1815739 and BDNF rs6265 Polymorphisms May Not Be Associated with Handgrip Strength in Elite Wrestlers

Mehmet A. Ergun Hasan H. Kazan David Varillas-Delgado Celal Bulgay Ebru Dolu Savaş Orhan Luca Paolo Ardigò Attila Szabo

Publication Name: Genes

Publication Date: 2026-05-01

Volume: 17

Issue: 5

Page Range: Unknown

Description:

Background/Objectives: Handgrip strength (HGS) is a widely used indicator of upper-limb muscular strength and a practical proxy for neuromuscular performance across both clinical and athletic contexts. Although HGS is heritable, evidence supporting specific genetic contributors in elite athletes remains limited. Thus, the present study investigated the associations of two functional polymorphisms, BDNF rs6265 (p.Val66Met) and ACTN3 rs1815739 (p.R577X), with HGS performance in elite wrestlers, integrating neuromuscular and muscle fiber-related biological pathways. Methods: The present study included 613 subjects (56 elite male wrestlers (mean age: 22.35 ± 5.34 years; training experience: 13.40 ± 3.85 years) and 557 healthy individuals drawn from a public database). HGS measurements were performed using a digital hand dynamometer. Results: Genotyping was performed on DNA extracted from peripheral blood using a high-density single nucleotide polymorphism (SNP) array. Neither BDNF rs6265 nor ACTN3 rs1815739 was significantly associated with HGS in elite wrestlers (p > 0.05), and effect estimates were negligible. In addition, ACTN3 rs1815739 genotype and allele frequencies were comparable between wrestlers and the reference population, indicating no enrichment of this variant in the elite cohort. In this sample of elite male wrestlers, BDNF rs6265 and ACTN3 rs1815739 were not associated with HGS, and ACTN3 rs1815739 was not enriched relative to a national reference population. Conclusions: These findings suggest no detectable effects of single candidate variants on HGS under the current study design in highly trained athletes; however, this interpretation should be made cautiously given cohort-specific limitations and does not preclude their potential contribution within the broader polygenic architecture of strength-related traits. Future research employing larger, well-powered, and multi-cohort designs and polygenic approaches is warranted to further elucidate the genetic basis of strength phenotypes.

Open Access: Yes

DOI: 10.3390/genes17050559

Taxonomic contribution to knowledge of the oribatid mite genus Achipteria (Acari, Oribatida, Achipteriidae)

Sergey G. Ermilov Jenő Kontschán

Publication Name: International Journal of Acarology

Publication Date: 2025-01-01

Volume: 51

Issue: 2

Page Range: 81-87

Description:

The oribatid mite family Achipteriidae is recorded in the Dominican Republic for the first time. A new species of the genus Achipteria—A. (Izuachipteria) dominicanensissp. nov.—is described, based on adults collected from leaf litter in a mixed forest. The species is characterized by the morphology of the lamella (triangular distally, without strong lateral tooth), the location of the lamellar seta (on ventral side of the lamella), the length of the bothridial seta (long), the ornamentation and morphology of the pteromorph (partially striate, with lateral tooth), the number of the leg claws (one), and the absence of the notogastral saccules. The taxonomic status of the subgenera Achipteria (Cubachipteria), A. (Hokkachipteria), and A. (Izuachipteria) is discussed. An identification key, distribution, and habitat of the known representatives of Achipteria (Izuachipteria) are presented.

Open Access: Yes

DOI: 10.1080/01647954.2024.2439799