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Found 6278 publications

Identifying necessary and sufficient conditions for enhancing loyalty in hybrid electronic vehicles: A combined PLS-SEM and NCA approach

Muhammad Shakil Ahmad Yong Ki Lee Jae Jang Yang Sung Yong Choi

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

DOI: 10.1016/j.tbs.2025.101192

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

Optimization of pavement texture depth measurement using machine learning algorithms

Mohammad Fahad

Publication Name: Discover Applied Sciences

Publication Date: 2026-04-01

Volume: 8

Issue: 4

Page Range: Unknown

Description:

Optimization of 3D laser scanning method using paired t-tests and ANOVA tests. Prediction of pavement mean texture depth using machine learning algorithms. Separation of macrotexture and microtexture using Power Spectral Density method.

Open Access: Yes

DOI: 10.1007/s42452-026-08392-9

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

Bridging Diagnostic Condition Monitoring and NVH Tonal Excitation Through Frequency–Domain Structural Mapping

Krisztian Horvath Krisztián Horváth

Publication Name: Applied Sciences Switzerland

Publication Date: 2026-04-01

Volume: 16

Issue: 8

Page Range: Unknown

Description:

Featured Application: The mapping methodology presented in this manuscript can aid in the vibration-based assessment of tonal excitation-related response in powertrain systems, providing a structural link between diagnostic monitoring and NVH assessment practices. In general, condition monitoring (CM) and noise, vibration and harshness (NVH) are often treated as separate disciplines, despite the fact that both rely on vibration measurements. CM relies on broadband statistical metrics such as RMS, kurtosis, and envelope analysis to detect faults. Meanwhile, NVH investigates tonal excitation mechanisms related to gear mesh frequency (GMF) and its modulation components. In this study, we investigate whether a numerical relationship can be established between classical CM indicators and physically based tonal excitation indicators derived from frequency–domain analysis. Using healthy and damaged benchmark gearbox recordings, Spearman correlation analysis was performed between broadband metrics and GMF-related tonal features, including GMF-band energy and absolute sideband energy. Results show moderate but statistically significant correlations between RMS, envelope peak amplitude, and tonal indicators, whereas kurtosis exhibits no meaningful association. Additionally, tonal response amplification in the damaged gearbox is shown to be non-uniformly distributed across sensor locations, indicating sensor-dependent structural sensitivity rather than uniform response growth. These findings demonstrate that broadband CM indicators partially encode changes in tonal excitation-related response, establishing a reproducible data-driven bridge between diagnostic condition monitoring and NVH excitation analysis.

Open Access: Yes

DOI: 10.3390/app16083709

Diagnostic sonography in obstetrics and gynecology

Sándor Nagy

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

DOI: 10.1556/650.2026.33546

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

Constrained optimization in physics-informed neural networks for singular three-point boundary value problems

Aamir Farooq Hijaz Ahmad Sadique Rehman Emad A.A. Ismail Uzma Nadeem Malik Ahsin Iqbal Fuad A. Awwad

Publication Name: Ain Shams Engineering Journal

Publication Date: 2026-04-01

Volume: 17

Issue: 4

Page Range: Unknown

Description:

Physics-informed neural networks represent a category of deep learning models that directly incorporate physical laws into the training process to solve differential equations, thereby diminishing the dependence on extensively labeled datasets. This study investigates a constrained optimization framework within PINNs to address singular three-point boundary value problems, which present significant challenges owing to singularities and internal boundary conditions that result in non-standard solution behavior. To address these complexities, we developed a customized Physics-informed neural network architecture that integrates constraint-driven regularization terms into the loss function to enhance the generalization and numerical stability. The proposed approach was evaluated across multiple benchmark problems, with performance assessed using statistical metrics and the mean squared error. The optimization and training PINN regular framework will stabilize the training and convergence in the presence of singularities to yield dependable TPS-BVP solutions. The predicted solutions were rigorously compared with exact analytical solutions. The results demonstrate that the constrained optimization-based Physics-informed neural networks framework provides highly accurate and stable approximations, validating its effectiveness in handling complex singular boundary value problems.

Open Access: Yes

DOI: 10.1016/j.asej.2026.104063

Evaluating AMD EPYC CPU architectures on CFD applications

Flavio Cesar Cunha Galeazzo László Környei Łukasz Szustak Paweł Bratek Marcin Lawenda

Publication Name: Future Generation Computer Systems

Publication Date: 2026-04-01

Volume: 177

Issue: Unknown

Page Range: Unknown

Description:

In this work, the authors focus on assessing the impact of the AMD EPYC processor architecture on the performance of CFD applications. Several generations of architectures were analyzed, such as Rome, Milan, Milan X, Genoa, Genoa X and Bergamo, characterized by a different number of cores (64-128), L3 cache size (256 - 1152 MB) and RAM type (8-channel DDR4 or 12-channel DDR5). The research was conducted based on the OpenFOAM application using two memory-bound models: motorBike and Urban Air Pollution. In order to compare the performance of applications on different architectures, the FVOPS (Finite VOlumes solved Per Second) metric was introduced, which allows a direct comparison of the performance on the different architectures. It was noticed that local maximum performance occurs at different values of grid element per CPU when utilizing different processor types. Additionally, the behaviour of the models was analyzed in detail using the AMD µProf and LIKWID software profiling analysis tools to reveal the applications’ interaction with the hardware. It enabled fine-tuned monitoring of the CPU’s behaviours and identified potential inefficiencies in AMD EPYC CPUs. Particular attention was paid to the effective use of L2 and L3 cache memory in the context of their capacity and the bandwidth of memory channels, which are a key factor in memory-bound applications. Processor features were analyzed from a cross-platform perspective, which allowed for the determination of metrics of particular importance in terms of their impact on the performance achieved by CFD applications.

Open Access: Yes

DOI: 10.1016/j.future.2025.108237