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Seasonal Analysis of Match External Load in Hungarian Second-Division Professional Football Across Three Competitive Seasons Using GPS-Derived Match-Average Data

Ferenc Ihász István Barthalos László Suszter Árpád Petrov Richárd Bauer Bálint István Ruppert Bálint Kilvinger Zoltán Alföldi

Publication Name: Sports

Publication Date: 2026-04-01

Volume: 14

Issue: 4

Page Range: Unknown

Description:

Background/Objectives: The aim of this study was to describe seasonal trends in match-average External Load (EL) variables across three (2022/23, 2023/24, 2024/25) consecutive competitive seasons in a Hungarian professional second-division soccer team (Gyirmót FC Győr), using the Catapult Vector S7 Global Navigation Satellite System (GNSS). Specifically, Average Distance (AD; m), Average Player LoadTM (PL; AU), and Acceleration–Deceleration Efforts (>2 m·s−2) (ADE) were examined. The study aimed to provide descriptive reference values and characterize seasonal variation in match EL demands within a professional second-division context. Methods: A descriptive seasonal comparison was conducted based exclusively on aggregated match average EL values. The unit of analysis was the match, with each match contributing one aggregated value per variable derived from players who completed the full match. A total of 94 matches were included (2022/23: N = 38; 2023/24: N = 29; 2024/25: N = 27); matches with red cards were excluded. EL data were collected using a 10 Hz Catapult Vector S7 GNSS. Results: The median AD decreased continuously from the 2022/23 season (10.210 m) to the 2024/25 season (9.795 m). The median PL decreased from 1002 (2022/23 and 2023/24) to 846 in the 2024/25 season. The median ADE decreased from 220.8 (2022/23) to 199.0 (2024/25). Conclusions: Lower values were observed across match EL variables, with the most pronounced reduction in PL. These findings provide descriptive reference values and may support the interpretation of seasonal variation in match EL demands in professional second-division soccer.

Open Access: Yes

DOI: 10.3390/sports14040155

Navigating Cost-Efficient Circular Integration of Plastic Waste-to-X Pathways into Oil Refinery Using the Graph-Theoretic Approach

Ákos Orosz Viknesh Andiappan Bing Shen How Jui Yuan Lee Yat Choy Wong Sin Yong Teng Adeline Shu Ting Tan Ferenc Friedler

Publication Name: Industrial and Engineering Chemistry Research

Publication Date: 2026-04-01

Volume: 65

Issue: 12

Page Range: 6587-6604

Description:

Plastic waste conversion has been widely recognized as a promising strategy to address growing waste management challenges. However, the feasibility of its integration into existing industrial systems remains uncertain. This paper explores a plastic waste-to-X strategy aimed at reintegrating plastic waste into its original supply chain, in alignment with circular economy principles. A graph-theoretic optimization model is developed using P-graph to identify the optimal and near-optimal pathway configurations under multiple scenarios. Under a cost minimization scenario, the optimal solution achieves a 0.013–0.19% lower cost compared with alternative pathways; however, related to the higher opportunity cost of up to 24,364 USD/y from forgone utility savings and carbon tax reductions. Incorporating carbon credits shifts the focus toward balancing cost efficiency and emission reduction. Under budget constraints, the benefit-cost analysis reveals that emission reduction does not increase linearly with budget expansion. These findings guide decision-makers in setting realistic emission reduction targets and allocating budget efficiently, while helping policymakers to develop a financial scheme that promotes greater emission reductions without excessive expenditure.

Open Access: Yes

DOI: 10.1021/acs.iecr.5c04350

Numerical Study of Maxwell and Navier–Stokes Equations for Fluid Flow Over a Curvilinear Surface Subject to Buoyancy Forces

Muhammad Shuaib Muhammad Bilal Hijaz Ahmad Hassan Ali Ghazwani Sabahat Khan

Publication Name: ZAMM Zeitschrift Fur Angewandte Mathematik Und Mechanik

Publication Date: 2026-04-01

Volume: 106

Issue: 4

Page Range: Unknown

Description:

Buoyancy-driven viscous fluid flow across a curved surface is investigated numerically in this work using the coupled Maxwell and Navier–Stokes equations, with variable fluid characteristics represented as nonlinear functions of temperature. Realistic magneto-hydrodynamic effects are captured by including the Lorentz force and the influence of a fluctuating magnetic field in curvilinear coordinates. The governing partial differential equations are solved using the parametric continuation method (PCM) after being converted into a system of ordinary differential equations by similarity transformations. Results demonstrate excellent agreement when compared to previously published data using MATLAB's PCM solver to confirm correctness. According to the parametric study, buoyancy ((Formula presented.)) improves fluid motion by around 15%, whereas greater curvature factors (Formula presented.), Stuart numbers (Formula presented.), and Prandtl numbers (Formula presented.) result in a 12%–16% drop in radial and arc-length velocities. The temperature profile falls by more than 23% as (Formula presented.) and (Formula presented.) increase, indicating the significance of thermal diffusivity in preventing heat buildup. It increases by 25% with higher magnetic interaction ((Formula presented.), (Formula presented.)). The induced magnetic field is strengthened by 6%–7% with a little increase in the magnetic interaction parameter (Formula presented.), whereas the magnetic field intensity is reduced by about 25% with a larger (Formula presented.). Skin friction falls by almost 10% with greater (Formula presented.) at moderate (Formula presented.), but increases by 4% under larger Lorentz forces ((Formula presented.), (Formula presented.)). Overall, the results show that velocity, temperature, magnetic field distribution and surface forces are strongly influenced by buoyancy, curvature and electromagnetic parameters. The findings shed light on efficient energy optimisation, thermal control, and electromagnetic regulation of MHD flows over curved geometries.

Open Access: Yes

DOI: 10.1002/zamm.70423

Low-element FPGA beamforming: A ZCU102 demonstration of directed ultrasonic inspection

Dénes Varga Gábor Lencse

Publication Name: Journal of Electrical Engineering

Publication Date: 2026-04-01

Volume: 77

Issue: 2

Page Range: 139-147

Description:

This paper presents the design and implementation of a compact FPGA-based (Field-Programmable Gate Array) controlled ultrasonic transducer system. Our aim was to achieve ultrasound beam steering using three elementary ultrasonic transducers. The transducers generated a steerable beam through ultrasound interference, which was controlled by adjusting the phase differences between them. The system’s performance was demonstrated using a radar-style beamforming plot. Using elementary transmitters with an initial aperture angle of 50°-130°, an effective aperture angle of 74°-101° was achieved. The core of the device was implemented on a ZCU102 development panel, which had a considerable impact on the following development phase. Our proposed approach offers a compact and cost-effective solution for Non-Destructive Testing (NDT) systems; its applicability was demonstrated on a wood inspection example. Finally, potential directions for further development toward a fully functional device are discussed.

Open Access: Yes

DOI: 10.2478/jee-2026-0015

Performance Degradation of Object Detection Neural Networks Under Natural Visual Contamination in Autonomous Driving

János Hollósi Dániel Csikor

Publication Name: Computers

Publication Date: 2026-04-01

Volume: 15

Issue: 4

Page Range: Unknown

Description:

The operation of driver assistance systems and autonomous vehicles requires a sensor system and a control algorithm. Sensors provide information to detect people, vehicles and objects in the vehicle’s environment; however, their performance can be degraded by adverse environmental conditions and contamination. This literature review identified factors that reduce sensor visibility, such as weather conditions and external contamination. In this study, the detection efficiency of state-of-the-art neural network-based object detectors was examined in a simulation environment using a synthetic dataset. A custom dataset comprising six urban and suburban traffic scenarios was created, including clean images and ten contaminated variants per scene with increasing mud coverage. The results show that contamination leads to a measurable reduction in detection performance across all models. Smaller variants are more sensitive to degradation, while medium-complexity models provide a favorable balance between robustness and computational cost. Increasing model size yields limited additional robustness, and performance differences between architectures highlight the importance of model design. Furthermore, the spatial distribution of contamination, particularly near the image center, has a significant impact on performance in addition to its overall extent.

Open Access: Yes

DOI: 10.3390/computers15040254

The Environmental and Global Impact of Pharmacogenomics: Advancing Green Pharmacy Toward Sustainable and Inclusive Precision Medicine

Pálma Porrogi Pálma Porrogi

Publication Name: Journal of Personalized Medicine

Publication Date: 2026-04-01

Volume: 16

Issue: 4

Page Range: Unknown

Description:

Traditional one size fits all pharmacotherapy often yields suboptimal clinical outcomes, preventable adverse drug reactions (ADRs), and significant drug waste, imposing substantial economic and ecological burdens on healthcare systems. This review evaluates the transformative potential of pharmacogenomics (PGx) testing, particularly cytochrome P450 (CYP) gene variants, as a foundation for an ecosystem-centric accountability framework for green pharmacy and links human metabolic variability to specific environmental outcomes. Personalized CYP profiling is shown to minimize the environmental release of unused drugs and potentially ecotoxic metabolites into aquatic ecosystems, in contrast to standard uniform drug use approaches. The limitations of ethnicity-based dosing models, which rely on population genetic variation, are examined in the context of increasing global genetic admixture. It is argued that individual genetic profiling, conceptualized as a PGx-Green Passport, provides a reliable safety standard that accounts for individual differences, thereby enhancing efficiency and well-being in a globalized society. By integrating clinical data, including real-world evidence on hospital utilization, with sustainability frameworks, this review demonstrates that PGx-guided therapy is not only a tool for clinical efficiency but also a fundamental requirement for systematically achieving environmentally sustainable healthcare.

Open Access: Yes

DOI: 10.3390/jpm16040183

Milestones of breast cancer treatment

F. Tamás Molnár András Drozgyik Margit Haramzáné Józsa

Publication Name: Orvosi Hetilap

Publication Date: 2026-04-01

Volume: 167

Issue: 14

Page Range: 560-568

Description:

No description provided

Open Access: Yes

DOI: 10.1556/650.2026.HO2871

TricP: A Novel Approach for Human Activity Recognition Using Tricky Predator Optimization Based on Inception and LSTM

Deepali Virmani Prashant Johri Oday Ali Hassen Muslem Al-Saidi Palak Girdhar Hussein Taha

Publication Name: Telecom

Publication Date: 2026-04-01

Volume: 7

Issue: 2

Page Range: Unknown

Description:

Human Activity Recognition (HAR) is a pivotal research area for applications such as automated surveillance, smart homes, security, healthcare, and human behavior analysis. Traditional machine-learning approaches often rely on manual feature engineering, which can limit generalization. Although deep learning has improved HAR through automatic representation learning, achieving high detection performance under computational constraints remains challenging. This paper proposes an efficient HAR framework that combines deep learning with hybrid optimization. Surveillance videos are first decomposed into frames, and a keyframe selection stage identifies distinctive frames to reduce redundancy and computational cost while preserving informative content. Motion and appearance features are then extracted using Histogram of Oriented Optical Flow (HOOF) and a ResNet-101 model, respectively, and concatenated into a unified feature representation. Classification is performed using an Inception-based Long Short-Term Memory (Incept-LSTM) network, which is fine-tuned via the proposed Tricky Predator Optimization (TricP) over a restricted, low-dimensional parameter vector. TricP is inspired by predator poaching behavior and the social dynamics of Latrans to enhance exploration and exploitation during search. Experiments on the UCF-Crime dataset show that the proposed method achieves 96.84% specificity, 92.16% sensitivity, and 93.62% accuracy.

Open Access: Yes

DOI: 10.3390/telecom7020032

Uncovering the Spatial Logic of Tourism Attractions: A Geospatial Analysis of Distribution Patterns and Driving Forces in Luxor, Egypt

Lóránt Dávid Moaaz Kabil Heba Mostafa Hassan Mona Abdel Fattah Abdel Moneim

Publication Name: Forum Geografi

Publication Date: 2026-04-01

Volume: 40

Issue: 1

Page Range: 91-107

Description:

The spatial distribution of tourism attractions plays an important role in shaping visitor travel behaviour, accessibility to tourism locations, and tourist destination management and planning. This study examines the spatial patterns of tourism attractions in Luxor Governorate, Egypt, and the factors influencing these spatial relationships using a variety of geospatial analysis techniques. These techniques include Nearest Neighbour Index (NNI), Standard Deviational Ellipse (SDE), Kernel Density Estimation (KDE), and Local Moran’s I. In addition, a combination of the Analytic Hierarchy Process (AHP) and Geodetector were applied to determine which of sixteen identified factors influenced the distribution of tourist attractions in Luxor. Finally, the spatial relationships between the identified factors and the distribution of tourist attractions were analysed through the use of Multiscale Geographically Weighted Regression (MGWR). The results show that there is a strong clustering of tourism attractions in Luxor within three main hubs: Luxor City (East Bank), Qurna (West Bank), and Esna. The results further indicate that the most influential factors influencing the distribution of tourist attractions in Luxor include regional services centrality, GDP index, proximity to urban centres, tourism workforce localisation, urbanisation level, and environmental quality, respectfully. The implications of this research provide practical applications for developing more sustainable and balanced tourism development strategies in heritage-rich regions such as Luxor.

Open Access: Yes

DOI: 10.23917/forgeo.13279