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Found 6278 publications
Numerical Study of Maxwell and Navier–Stokes Equations for Fluid Flow Over a Curvilinear Surface Subject to Buoyancy Forces
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
ReGAIN: a reinforcement-enhanced generative AI framework for intelligent intrusion detection in IoT networks
Publication Name: Complex and Intelligent Systems
Publication Date: 2026-04-01
Volume: 12
Issue: 4
Page Range: Unknown
Description:
The advent of the Internet of Things (IoT) enables billions of devices in wide-ranging domains such as healthcare, industry, and smart cities to interconnect with each other, but these connections make the network vulnerable to advanced cyber threats too. Current intrusion detection methods have failed to provide effective detection capabilities mainly because of issues such as extremely imbalanced data distributions, low classification accuracy, or static and manually tuned hyperparameters that do not generalize well in dynamic IoT settings. These challenges are exacerbated by unique IoT constraints, including limited device resources and dynamic attack patterns, which further complicate effective detection. To address these challenges, in this study we present a Reinforcement-enhanced Generative Artificial Intelligence (ReGAIN) framework for intelligent intrusion detection in IoT networks. In this approach, we use a generative autoencoder for data balancing to generate realistic minority class instances in the latent feature space, and meanwhile to obtain stable and unbiased learning of the model. This paper introduces a novel Pointer-Attention Dual Network (PAD-Net) that employs a Dual Attention Network (DANet) and a Pointer Network (PtrNet) to enhance spatial attention and inter-feature relationships. We also propose Reinforcement-enhanced PAD-Net (RePAD-Net), which leverages reinforcement learning to automatically optimize key hyperparameters at each training step, further enhancing generalization ability and robustness. The intrusion detection task in this study is a multi-class classification problem, where different types of attacks are distinguished from each other. Experimental results demonstrate that PAD-Net and RePAD-Net achieve notable improvements of 3.79% and 8.79% in accuracy, 3.79% and 8.78% in recall, 2.79% and 9.01% in F1-score, 3.79% and 8.83% in Mathews correlation coefficient, and 3.94% and 9.11% in Cohen’s Kappa, respectively, along with significant reductions in log loss of 47.42% and 70.96% and hamming loss of 24.33% and 56.37% compared with baseline models such as naive bayes, gradient boosting, densely connected network, long short term memory, hybrid models, DANet and PtrNet. Additionally, 10-fold cross validation is applied to validate the results of proposed models. These findings confirm that our proposed ReGAIN framework, which is able to alleviate data imbalance and improve learning generalization, can dramatically enhance the reliability of detection performance under complex IoT intrusion environments.
Open Access: Yes
Experiments on the influence of oil temperature and pressure on subsynchronous bifurcation and shaft orbit behaviour in automotive turbochargers
Publication Name: Mechanical Systems and Signal Processing
Publication Date: 2026-04-01
Volume: 249
Issue: Unknown
Page Range: Unknown
Description:
This work presents a comprehensive experimental study of the nonlinear dynamic behavior of a high-speed automotive turbocharger rotor system supported by semi-floating bearings. The investigation focuses on how oil supply temperature and pressure influence subsynchronous bifurcation, dynamic instability, and shaft orbit evolution under realistic lubrication environments. Experiments were performed on a dedicated test bench that enabled precise control and monitoring of oil parameters while decoupling rotor dynamics from engine-related disturbances.Shaft-end displacements were measured using dual radial probes, with simultaneous high-frequency vibration and speed tracking. Order spectra and Fourier analysis were conducted at key operational points, and orbit patterns were visualized through whirl plots to capture changes in rotor motion across a full range of speeds. The results reveal that elevated oil temperature markedly lowers the bifurcation threshold, causing nonlinear instabilities—marked by earlier onset of complex, multi-loop orbits—at reduced speeds. These transitions are dominated by two principal subsynchronous spectral components, Sub 1 (cylindrical and conical modes) and Sub 2 (translational and bending modes), whose evolution is mapped in detail using both spectral and orbit-based methods. A distinctive trend toward thermal saturation in the lubrication system was identified, as outlet oil temperature increases plateau at higher inlet temperatures, indicating a thermal energy absorption limit.Comparative analysis demonstrated that the system’s dynamic response is highly sensitive to both viscosity and supply pressure, with higher temperatures and lower viscosities amplifying instability and orbit complexity. Filtered vibration signals provided consistent results with displacement data, validating their use for practical bifurcation detection.By combining advanced order-domain diagnostics with direct orbit visualization, this study establishes clear experimental benchmarks for understanding turbocharger instability mechanisms, justifies the focus on the dominant subsynchronous modes, and highlights the importance of oil rheology and thermal effects in governing rotor dynamics. These insights support the development of improved predictive models and informed maintenance or control strategies for higher efficiency and reliability in turbocharger systems.
Open Access: Yes
Uncovering the Spatial Logic of Tourism Attractions: A Geospatial Analysis of Distribution Patterns and Driving Forces in Luxor, Egypt
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
Identifying necessary and sufficient conditions for enhancing loyalty in hybrid electronic vehicles: A combined PLS-SEM and NCA approach
Publication Name: Travel Behaviour and Society
Publication Date: 2026-04-01
Volume: 43
Issue: Unknown
Page Range: Unknown
Description:
The purpose of this study is to examine value elements related to hybrid electric vehicles and their impact on consumers’ brand-related (brand identification) and corporate-related (corporate image) responses, which are expected to influence buying intention. Data was collected from 294 owners of hybrid electric vehicles in South Korea and analyzed using PLS-SEM and NCA (necessary condition analysis). The study finds that all four elements of value have a significant impact on either brand identification or corporate image. The study shows that brand identification and corporate image predict buying intention. Brand identification is found to play a mediating role in the relationship between aesthetic value and corporate image and between eco-friendliness and corporate image. The study finds that corporate image mediates the relationship between brand identification and buying intention. The study contributes to the understanding of the psychological process that explains buying intention of the hybrid electric vehicle (HEV) users.
Open Access: Yes
Diagnostic sonography in obstetrics and gynecology
Publication Name: Orvosi Hetilap
Publication Date: 2026-04-01
Volume: 167
Issue: 16
Page Range: 610-620
Description:
Obstetric and gynecological ultrasound has become one of the most important first-line diagnostic modalities in contemporary clinical practice, playing a central role in antenatal care, prenatal screening and gynecological diagnostics. The aim of this review is to provide a comprehensive overview of the development of obstetric and gynecological ultrasound in Hungary, its current national guideline framework and its integration into international standards, with particular emphasis on technological innovations and quality assurance. The article analyzes the position and relevance of Hungarian recommendations in comparison with major international guidelines, including those of ISUOG, FMF, ESHRE and the IOTA consortium, and summarizes the main clinical indications of ultrasound in obstetrics and gynecology. Special attention is given to the role of 3D/4D imaging, Doppler techniques, structured reporting and artificial intelligence-based decision support systems, which contribute significantly to improved diagnostic accuracy and reproducibility. The strengths of the Hungarian system include wide accessibility, guideline-based practice and a license-based training and competency framework. Future challenges involve further development of education, enhancement of auditability and the integration of data-driven and artificial intelligence-supported solutions into routine clinical workflows. The responsible and standardized use of modern ultrasound technology remains essential for patient safety, quality assurance and evidence-based clinical decision-making. Orv Hetil. 2026; 167(16): 610–620.
Open Access: Yes
Barriers and Socio-Economic Drivers of Renewable Energy Adoption Among Manufacturing SMEs: A Structural Equation Modeling Approach
Publication Name: Sustainability Switzerland
Publication Date: 2026-04-01
Volume: 18
Issue: 8
Page Range: Unknown
Description:
Background: Small- and medium-sized enterprises (SMEs) constitute a large portion of the industrial energy demand in the emerging economies, but their shift to renewable energy is not well comprehended at the firm level. Bangladesh is a special case, since the country has adopted national commitments to Sustainable Development Goal 7 on clean energy, but the uptake of renewable energy by SMEs remains minimal due to complex socio-economic factors. Most of the literature has concentrated on household access to energy or national policy models, leaving a gap in empirically validated models of firm-level adoption in the manufacturing sector. Method: Based on the diffusion of innovation theory, institutional theory, and the resource-based view, this research paper formulates and empirically verifies a combined socio-economic model of renewable energy adoption. Partial least squares structural equation modeling (PLS-SEM) was used to analyze a cross-sectional survey of 426 owners and managers of manufacturing SMEs in Bangladesh’s textile and food processing sub-sectors. Findings: Four out of five hypothesized direct relationships were supported. The most important drivers were environmental orientation (β = 0.467, p < 0.001, f2 = 0.413), market competitiveness (β = 0.287, p < 0.001, f2 = 0.413), policy and institutional factors (β = 0.211, p < 0.001, f2 = 0.413), and access to finance (β = 0.096, p = 0.004). Perceptions of cost did not become significant (β= −0.036, p = 0.279). Top management support significantly and negatively moderated the relationship between environmental orientation and adoption (β = −0.093, p = 0.003), possibly because it moderates the substitution mechanism in SME decision-making, which is highly centralized. The model accounted for 64.5% of the variation in renewable energy adoption (R2 = 0.645). Conclusion: The results show that attitudinal and institutional factors tend to be more important than financial barriers in determining SMEs’ energy transitions. Environmental consciousness, market incentives, and streamlined institutional access should be the focus of policy interventions to hasten inclusive low-carbon transitions in emerging manufacturing economies.
Open Access: Yes
DOI: 10.3390/su18083809
Rutting Resistance and Fatigue Performance of Crumb Rubber-Modified Asphalt Concrete: Experimental Investigation and Mechanistic–Empirical Modeling
Publication Name: Infrastructures
Publication Date: 2026-04-01
Volume: 11
Issue: 4
Page Range: Unknown
Description:
Crumb rubber-modified asphalt concrete (CMAC) has gained increasing attention as a sustainable pavement material capable of improving mechanical performance while utilizing waste tire resources. This study investigates the rutting resistance and fatigue behavior of CMAC using a combined experimental and mechanistic–empirical modeling approach. Asphalt mixtures containing 0–25% crumb rubber by binder weight were prepared and evaluated through Marshall stability and indirect tensile fatigue tests, whereas Fourier-transform infrared spectroscopy (FTIR) was used to examine binder–rubber interactions. The results indicate that crumb rubber significantly influences both the volumetric and mechanical properties of asphalt mixtures. Mixtures containing 10–15% crumb rubber exhibited optimal performances, achieving up to 36% higher Marshall stability and improved fatigue life compared with conventional asphalt mixtures. FTIR analysis revealed that rubber particle swelling and limited chemical interactions enhanced binder elasticity and improved binder–aggregate compatibility. However, excessive rubber content (≥20%) resulted in reduced stability owing to increased binder absorption and decreased effective binder film thickness. A mechanistic–empirical model incorporating viscoelastic, viscoplastic, and fatigue damage parameters successfully reproduced the experimental trends and identified the same optimal rubber content range. The findings demonstrate that CMAC with a moderate rubber content can enhance pavement durability and structural performance while promoting environmentally sustainable road construction through the reuse of waste tires.
Open Access: Yes
A Call for Consensus: A Narrative Review of GPS-Based External Training Load Monitoring in Male Youth Soccer Players
Publication Name: Sports
Publication Date: 2026-04-01
Volume: 14
Issue: 4
Page Range: Unknown
Description:
Background: Global positioning system (GPS) technology is widely used to quantify external training load (ETL) in youth soccer. Despite its extensive application in training and match contexts, considerable heterogeneity is present in the selection, definition, and interpretation of GPS-derived variables, limiting comparability between studies and practical implementation by coaches. Objective: This narrative review aimed to summarize and critically evaluate the current literature on GPS-based ETL monitoring in youth soccer players, with a focus on commonly used variables, methodological considerations, and practical applications in training and match contexts. Methods: A narrative literature search was conducted using PubMed, SPORTDiscus, and Scopus databases. Peer-reviewed studies published in English between the years of 2012 and 2025 were included. Data were extracted on participant characteristics, GPS technology, monitored ETL variables, and contextual settings. Results: The 34 reviewed studies primarily reported total distance (TD; m), high-speed running distance (HSR; m), sprint distance (SD; m), distance per minute (m·min−1), peak speed (km·h−1), and acceleration- and deceleration-based (ACC, DEC; count) ETL variables. Substantial variability was observed in speed thresholds, acceleration definitions, and data processing methods. Positional roles, training formats (e.g., small-sided games), and seasonal phase influenced ETL demands, although methodological inconsistencies limited cross-study comparisons. Conclusion: GPS technology provides valuable insights into the ETL demands of youth soccer. The lack of standardized variable definitions and thresholds remains a major limitation. Greater methodological consistency and clearer reporting standards are required to enhance the practical usefulness of GPS monitoring for coaches in youth soccer.
Open Access: Yes
