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Found 6289 publications
Who Benefits from the EV Transition? Electric Vehicle Adoption and Progress Toward the SDGs Across Income Groups
Publication Name: World Electric Vehicle Journal
Publication Date: 2026-01-01
Volume: 17
Issue: 1
Page Range: Unknown
Description:
Electric vehicles (EVs) are widely promoted as a key strategy for reducing carbon dioxide (CO2 ) emissions and advancing sustainable development. However, the real-world benefits of EV adoption may vary across countries with different income levels and energy systems. This study investigates the relationship between EV adoption and CO2 emissions per capita, as well as overall sustainable development performance (SDG Index), across 50 countries from 2010 to 2023. Using panel quantile regression, we find that EV adoption is significantly associated with reduced CO2 emissions particularly in the high-emitting countries in high-income countries (interaction coefficient at the 90th quantile = −0.24, p < 0.05) but positively associated with emissions in lower- and middle-income countries at lower quantiles of the emissions distribution. Similarly, while EV adoption correlates positively with the SDG Index in high-income countries, it shows negative effects at the median and several quantiles. These findings challenge the “zero-emission” assumption and demonstrate that the climate and development benefits of EV diffusion are context-dependent and unevenly distributed, highlighting the need for policies that link electrification to renewable energy deployment, infrastructure development, and equitable access.
Open Access: Yes
DOI: 10.3390/wevj17010034
Mitigation of technostress and its effects based on trust and organizational culture through the example of a railway company
Publication Name: Journal of Data Information and Management
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Technostress has become a significant challenge in digital workplaces, potentially affecting employees’ well-being and productivity. This study investigates the presence of technostress in a railway transportation company, focusing on digital overload and knowledge hoarding. It also examines how organizational trust supports knowledge sharing and helps employees adapt to technological challenges in the workplace. A quantitative survey was conducted among railway employees who regularly use IT tools in their daily work. The study applied descriptive statistics, cross-tabulation analysis, correlation analysis, and cluster analysis. No regression modeling was performed, as the aim of the empirical analysis was exploratory and relationship-oriented rather than model estimation. The findings indicate that digital overload and knowledge hoarding represent the most prominent sources of technostress in the examined organization. Demographic factors show only a limited influence on technostress perceptions, while organizational trust plays an important role in supporting knowledge sharing and mitigating technostress. The results also reveal that employees place greater trust in human collaboration than in technological systems, although no significant distrust in technology was observed. The results suggest that organizations can reduce technostress by strengthening trust-based organizational cultures, promoting knowledge sharing, and implementing HR practices that support employees’ digital adaptation. Transparent communication, targeted training, and supportive leadership can contribute to improving employee well-being and managing technostress in digitally intensive workplaces. This study contributes to the literature on technostress by highlighting the interrelationship between technostress, organizational trust, and knowledge sharing in a railway industry context. The findings provide practical insights into how trust-based organizational cultures can support employees in coping with technological change and digital transformation.
Open Access: Yes
Machine Learning Prediction of Pavement Macrotexture from 3D Laser-Scanning Data
Publication Name: Applied Sciences Switzerland
Publication Date: 2026-01-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Featured Applications: Pavement texture evaluation using a traditional sand patch method, 3D laser scanning, and machine learning algorithms. Pavement macrotexture, quantified by mean texture depth (MTD) and mean profile depth (MPD), is a critical parameter for road safety and performance. The traditional sand patch test is labor-intensive and slow, creating a bottleneck for modern pavement management systems. Accurately translating the rich point cloud data into reliable MTD values using the 3D scanning method remains a challenge, with current methods often relying on oversimplified correlations. This research addresses this gap by developing and validating a novel machine learning framework to predict MTD and MPD directly from high-resolution 3D laser scans. A comprehensive dataset of 127 pavement samples was created, combining traditional sand patch measurements with detailed 3D point clouds. From these point clouds, 27 distinct surface features spanning statistical, spatial, spectral, and geometric domains were developed. Six machine learning algorithms, consisting of Random Forest, Gradient Boosting, Support Vector Regression, k-Nearest Neighbor, Artificial Neural Networks, and Linear Regression, were implemented. The results demonstrate that the ensemble-based Random Forest model achieved superior performance, predicting MTD with an R2 of 0.941 and a mean absolute error (MAE) of 0.067 mm, representing a 56% improvement in accuracy over traditional digital correlation methods. Model interpretation via SHAP analysis identified root mean square height (Sq) and surface skewness (Ssk) as the most influential features.
Open Access: Yes
DOI: 10.3390/app16010500
CONTROLLABILITY OF THE TIME-VARYING FRACTIONAL DYNAMICAL SYSTEMS HAVING MULTIPLE DELYAS IN CONTROL WITH CAPUTO FRACTIONAL DERIVATIVE
Publication Name: Fractals
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
The objective of this study is to analyze controllability results for time-varying linear and nonlinear fractional dynamical systems with multiple control delays within the framework of the Caputo fractional derivative. This paper focuses on examining control problems within a finite time interval, aiming to identify a control function that steers the system’s solution from a specified initial state to a targeted final state. For linear systems, the study establishes necessary and sufficient conditions for controllability by utilizing the Grammian matrix techniques. For nonlinear systems, the existence of a solution is ensured through an iterative technique, with completeness of the space guaranteed. With the help of this technique, we establish the sufficient conditions for the controllability of time-varying nonlinear fractional dynamical systems. The results show that the controllability of fractional dynamical systems can be effectively analyzed with the given framework, along with numerical simulations and graphical representations to clarify the theoretical findings.
Open Access: Yes
Data-driven decision-making framework for the evaluation of the traders in the stock market using cosine trigonometric single-valued neutrosophic approach
Publication Name: Journal of Mathematics and Computer Science
Publication Date: 2026-01-01
Volume: 41
Issue: 2
Page Range: 222-243
Description:
The cosine trigonometric single valued neutrosophic number (CT-SVNN) is a suitable expansion of the standard neutrosophic number. Single-valued neutrosophic sets (SVNSs) may effectively overcome three components: degree of truth, indeterminacy, and falsity. In recent years, the aggregation operator (AO) and its applications have undergone development. This study introduces a few new AOs for multi-attribute decision-making (MADM). We introduce a novel approach for cosine trigonometric SVNS (CT-SVNS) and CT-SVNS with normal (CT-SVNNS), which are SVNS extensions. It is also required to discuss the CT-SVNNS method fundamental features in this communication, such as idempotency, boundedness, commutativity and monotonicity. There are numerous CT-SVNNS operators that have been proposed, including CT-SVN normal weighted averaging (CT-SVNNWA), CT-SVN normal weighted geometric (CT-SVNNWG), generalized CT-SVNNWA (GCT-SVNNWA) and generalized CT-SVNNWG. A powerful strategy for solving the MADM problem is provided that makes use of new developed generalized operators. Through a case study, the value of the suggested MADM approach is demonstrated. The new strategy is shown using a market share problem, and the outcomes are contrasted and examined against an existing method. This combination of generalized AO was rated successful based on expert preferences. As a result, a varied collection of experts may be accepted.
Open Access: Yes
Curvature-Constrained Motion Planning Method for Differential-Drive Mobile Robot Platforms
Publication Name: Applied Sciences Switzerland
Publication Date: 2026-01-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Compact heavy-duty skid-steer robots are increasingly used for city logistics and intralogistics tasks where high payload capacity and stability are required. However, their limited maneuverability and non-negligible turning radius challenge conventional waypoint-tracking controllers that assume unconstrained motion. This paper proposes a curvature-constrained trajectory planning and control framework that guarantees geometrically feasible motion for such platforms. The controller integrates an explicit curvature limit into a finite-state machine, ensuring smooth heading transitions without in-place rotation. The overall architecture integrates GNSS-RTK and IMU localization, modular ROS 2 nodes for trajectory execution, and a supervisory interface developed in Foxglove Studio for intuitive mission planning. Field trials on a custom four-wheel-drive skid-steer platform demonstrate centimeter-scale waypoint accuracy on straight and curved trajectories, with stable curvature compliance across all tested scenarios. The proposed method achieves the smoothness required by most applications while maintaining the computational simplicity of geometric followers. Computational simplicity is reflected in the absence of online optimization or trajectory reparameterization; the controller executes a constant-time geometric update per cycle, independent of waypoint count. The results confirm that curvature-aware control enables reliable navigation of compact heavy-duty robots in semi-structured outdoor environments and provides a practical foundation for future extensions.
Open Access: Yes
DOI: 10.3390/app16010322
Temporal changes in serum total cholesterol levels during a 30-year follow-up in a South Hungarian village population
Publication Name: Orvosi Hetilap
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Introduction: Elevated serum cholesterol is a major cardiovascular risk factor. Population-level trends in total cholesterol reflect changes in lifestyle, diet, and pharmacological treatment. Objective: To assess temporal changes in serum total cholesterol levels in the population of a South Hungarian village over a 30-year period. Method: Serum total cholesterol was measured in Méhkerék residents in 1994 and 2014 following professional guidelines, and re-examined in 2024. Temporal trends were analyzed using multiple regression and analysis of covariance. Results: The study included 760 individuals in 1994, 391 in 2014, and 544 in 2024. Due to changes in age and sex composition, analyses were standardized for 40-, 50-, and 70-year-old men and women. Among 40-year-old women, cholesterol decreased by 3% from 1994 to 2024, and by 10% and 25% among 50- and 70-year-olds, respectively. In men, the corresponding reductions were 11%, 17%, and 28%. No significant difference was found between 1994 and 2014 (p = 0.117), but the decline became significant by 2024 (p<0.001). Cholesterol levels were significantly associated with sex (p = 0.005) and age (p<0.001), and a time × age interaction indicated a more pronounced decline in older participants. Conclusion: According to a detailed review of the available literature, this is the first comprehensive epidemiological study conducted on a Hungarian population over a 30-year period, which follows the serum total cholesterol levels of the entire population of a settlement. The significant long-term reduction likely reflects combined effects of medical therapy and lifestyle improvements. These findings emphasize the preventive role of general practice and the need for more focused cardiovascular prevention among younger individuals and women. Orv Hetil. 2026; 167(1): 9–15.
Open Access: Yes
Deep learning-based identification of pipeline weld defects using automated ultrasonic testing
Publication Name: Nondestructive Testing and Evaluation
Publication Date: 2026-01-01
Volume: 41
Issue: 4
Page Range: 2321-2342
Description:
For the safety evaluation of pipe welds, this paper proposes an automated ultrasonic testing method focused on defect signal feature extraction and identification. First, defect features are extracted based on the ultrasonic scattering coefficient distribution. The defect scattering coefficient matrix is then compressed using principal component analysis (PCA) to obtain the feature vector that best represents the defect. A Depthwise Separable Residual Network (DS-ResNet) model is constructed to identify pipe weld defects automatically. The sparrow search algorithm (SSA) is integrated with DS-ResNet (SSA-DS-ResNet) to optimise the model and enhance its performance. This method is applied to a case study, yielding a prediction accuracy of 97.51%, which is acceptable for industrial applications. The performance of SSA-DS-ResNet was compared with two networks prior to optimisation (ResNet and DS-ResNet), and the results indicate that SSA-DS-ResNet achieves higher accuracy.
Open Access: Yes
SIGNIFICANCE OF FRACTAL INTERFACIAL LAYER AND NANOPARTICLE’S RADIUS ON THE DYNAMICS OF NANOFLUIDS FLOW VIA CHANNEL OF POROUS WALLS
Publication Name: Fractals
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
This paper investigates heat and mass transfer phenomena by assessing advanced thermal conductivity models (TCMs) that significantly influence the flow of metallic (Au) nanoparticles under suitable boundary conditions. By integrating high TCMs with innovative interfacial fractal theory, we demonstrate a marked enhancement in thermal and concentration transfer. The analysis further investigates the physical model of a hybrid porous channel under the influence of nanofluid flow, magnetohydrodynamics (MHD), and chemical reactions. A detailed numerical investigation of nonlinear partial differential equations, converted into higher-order nonlinear ordinary differential equations (ODEs) using similarity transformations, reveals results by employing single-phase models of nanofluids. The ODEs are solved numerically via the shooting approach combined with the fourth-order Runge–Kutta method, using Mathematica to produce both graphical and numerical results. A comparative graph for expanding/contracting cases deliberated under the impact of MHD and chemical reaction. For expanding and suction cases, volume fractions of nanoparticles increase the function of the Nusselt number. Similarly, MHD is also an increasing function of shear stress near the porous surfaces. As the radius of the nanoparticle (dp) and the inter-particle spacing (h) increase, the radial velocity and temperature profiles also rise in both porous walls. It shows that chemical reactions alter thermal and mass transfer characteristics, with optimal parameters identified for maximizing efficiency. The research uncovers nonlinear interactions between flow dynamics and nanoparticle characteristics, explores the impact of external magnetic fields, and examines how boundary conditions influence transfer processes. Overall, this work enhances our understanding of using fractal theory to improve heat and mass transfer in engineering applications involving metallic nanoparticles.
Open Access: Yes
