Search Results (38,762)

This study investigates the transient wheel–rail contact mechanics of welded joints in heavy-haul rails via a validated 3D finite element model, and analyzes the stick-slip behavior, dynamic response and elastoplastic characteristics in the base material zone, heat-affected zone and weld bead zone. Results show a distinct contact state transition from stick-slip in the base material to predominant slip within the welded zones, indicating higher wear susceptibility. Dynamic response analysis reveals the highest and lowest contact-point acceleration amplitudes in the base material and heat-affected zone, respectively, due to material heterogeneity. Plastic deformation consistently initiates at the rail surface, where stress and strain concentrate, establishing it as the primary site for damage nucleation. A systematic parametric study shows that plastic deformation can be effectively mitigated by increasing the yield strength and elastic modulus of the welded joint material, or reducing the wheelset velocity, unsprung mass and wheel–rail friction coefficient. In contrast, adjusting the primary suspension and fastener parameters exerts a negligible influence on plastic deformation control. These findings provide a mechanistic basis for optimizing the performance and maintenance of welded joints in heavy-haul rail operations. This study reveals the coupling law of multiple mechanisms among contact behavior, dynamic response and material failure during the damage initiation process of rail welded joints from the mechanistic perspective, which provides a theoretical basis for the structural optimization, condition assessment and maintenance of rail welded joints in heavy-haul railways. Full article

Corn starch (CS)/poly (butylene adipate-co-terephthalate) (PBAT) blends were prepared by extrusion and injection molding processes. The CS content in the blends changed between 0 and 50 wt.% in 10 wt.% steps. Melt flow rates, mechanical properties, thermal stability, melting and crystallization behavior, as well as hydrophilicity of the blends were investigated. Based on these, the degradation properties of PBAT and the blend containing 50 wt.% CS (50%CS/PBAT) in water and open-air storage were comparatively studied via visual appearance observation, Shore hardness testing, and water absorption measurement. The results showed that the melt flow rates and the mechanical properties of the blends, including the tensile strength, tensile modulus, impact strength, and elongation at break, initially increased before decreasing as CS content in the blends increased, while the flexural strength and flexural modulus of the samples increased monotonously. The sample would become more thermal unstable when more CS was used. Besides these, the crystallinity and water contact angle became smaller. Immersion in water would blacken the visual appearances of PBAT and 50%CS/PBAT samples, but cracks could be found much more obviously in the blend than in neat PBAT; both the hardness and the mass of PBAT rose slightly while those of 50%CS/PBAT dropped significantly. An open-air storage would also blacken the visual appearances of PBAT and 50%CS/PBAT, and the hardness of the two samples would be decreased to almost the same extent. The results showed that the incorporation of CS in PBAT had much greater effects on the flow ability, mechanical properties, thermal stability, melt and crystallization behavior, as well as hydrophilicity of the blends. Immersion in water or being placed in air could accelerate the degradation of 50%CS/PBAT much more seriously than PBAT. Compared with PBAT, 50%CS/PBAT was of much lower cost and easier to be degraded, especially in water; it should be an ideal degradable blend for applications in packaging, agricultural mulch, and some other areas. Full article

Physics-based simulations are increasingly used to improve understanding of electrosurgical processes and to enable model-based estimation of tissue state when direct sensing is limited. The performance of such simulation-based virtual sensing approaches strongly depends on an accurate representation of the electrode–tissue interface. Despite its central role in electrical and thermal coupling, the influence of the electrode–tissue contact area has received limited attention in existing simulation studies. In this work, the influence of the electrode–tissue contact area on the sensitivity of key temperature-dependent tissue parameters was investigated for electrosurgical monopolar soft coagulation. Using a multiphysics finite element model under controlled boundary conditions, the sensitivity of maximum temperature development and necrotic tissue volume formation was analyzed with respect to varying contact areas and initial values of electrical conductivity, thermal conductivity, and effective heat capacity. The results demonstrate that parameter sensitivities are strongly contact-area-dependent. Electrical conductivity exhibits the most pronounced influence, particularly at larger contact areas, while thermal conductivity remains of minor relevance. In contrast, effective heat capacity significantly affects necrotic tissue volume formation, with increasing sensitivity for larger contact areas. These findings emphasize the importance of accurately accounting for electrode–tissue contact conditions in simulation-based analyses and clarify how contact-area-dependent sensitivities influence model-based tissue state estimation in electrosurgical coagulation. Full article

Real-time measurement of tea bud phenotypes via mobile devices is constrained by model lightweighting challenges, and research on non-contact measurement of tea bud phenotypes based on key points remains largely unexplored. Information on the growth posture of tea buds is an important basis for determining tea maturity grades, quality monitoring, and tea breeding. Therefore, this work develops a deep learning-enabled YOLOv8p-Tea model to estimate key point information of tea bud posture and automatically obtain three-dimensional point cloud information of tea buds by integrating depth information, thereby achieving in situ measurement of tea bud phenotypic parameters. Meanwhile, the model is trained and validated using a tea bud (one-bud-three-leaf) image dataset, and its effectiveness is demonstrated through experiments. Compared to the YOLOv8p-pose model, the model achieves a mAP50 of 98.3%, a P of 97%, and parameters of 0.72 M, with mAP50 and P improved by 1.5% and 1.9%, respectively, and the parameter count is reduced by 25%. To validate the accuracy of phenotypic extraction, the model was deployed on edge devices, and 30 tea buds with one bud and three leaves were randomly selected in a tea garden. The final in situ measurement results showed an MRE of 6.63%. Experimental findings indicate that the developed method is capable of not only effectively estimate tea bud posture but also accurately achieves in situ measurement of tea bud phenotypes, which holds potential applications for meeting the construction needs of smart tea gardens and optimizing tea breeding. Full article

Background: To investigate the predictive value of catheter ablation parameters during pulmonary vein isolation (PVI) on long-term recurrence in patients with paroxysmal atrial fibrillation (pAF). Methods: A retrospective analysis was conducted on 386 pAF patients who underwent initial catheter-based radiofrequency ablation (RFA) for PVI. After excluding ineligible cases and those lost to follow-up, 150 patients were included (mean follow-up: 28.86 ± 3.03 months). Patients were divided into recurrence and AF-free groups. Ablation parameters including catheter contact force (CF), ablation index (AI), and GAPs were collected via the CARTO VISITAG Module, and Cox regression was used to identify recurrence predictors. Results: The 2-year AF recurrence rate was 13.33% (20/150). No significant differences in baseline clinical characteristics, AI compliance rate, VISITAG GAP incidence, ablation points and time, or complication rates were observed between groups (p > 0.05). However, CF compliance rate was significantly lower in the AF recurrence group compared to AF-free group (79.17% vs. 90.10%, p < 0.001), and it was an independent predictor of late AF recurrence (HR = 0.950, 95%CI: 0.919–0.981; p = 0.002). Conclusion: CF compliance rate is independently associated with late AF recurrence after PVI. Maintaining stable CF during ablation may promote durable lesions and potentially reduce recurrence risk. Full article

Two novel cocrystals of zwitterionic trimethylglycine (TMG) with 2,6-dichlorophenol [TMG•2,6-dichlorophenol] (1:1) and 2,6-dibromophenol [TMG•2,6-dibromophenol] (1:2) are synthesized and structurally characterized using single crystal X-ray diffraction. To estimate the energy of various intermolecular interactions, periodic DFT calculations were performed followed by Bader analysis of the crystalline electron density. TMG molecules form dimers in [TMG•2,6-dichlorophenol] (1:1). Its supramolecular structure is governed by the primary charge-assisted H-bonds (~60 kJ/mol) and supported by C–H∙∙∙O contacts (~12 kJ/mol). Cl/Br substitution introduces a more potent halogen-bonding donor. The Br∙∙∙O⁻ interaction (~10 kJ/mol) is strong enough to reorganize the packing into a catemeric motif. As a result, TMG molecules form infinite chains in [TMG•2,6-dibromophenol] (1:2). This illustrates that “fine tuning” is not merely about changing distances, but about shifting the entire energy hierarchy of the crystal. Two-dimensional fingerprint diagrams (2D diagrams) obtained from the Hirshfeld surface and Bader’s analysis of the crystalline electron density give significantly different values of the contributions of the H∙∙∙H contacts, 28% vs. 5% respectively. The main reason for this discrepancy is the large number of relatively short intermolecular H∙∙∙H contacts without a critical bond point in trimethylglycine cocrystals. Full article

Bank telemarketing campaigns often experience low subscription rates due to customer heterogeneity and severe class imbalance, which pose challenges for reliable predictive modeling. This study investigates a data-driven approach that integrates synthetic minority oversampling and cost-sensitive learning to improve the prediction of telemarketing outcomes. Experiments are conducted using the Portuguese Bank Marketing dataset, comprising 41,188 instances with a positive response rate of 11.3%. Eight machine learning models are evaluated under a unified preprocessing pipeline and five-fold stratified cross-validation, including Logistic Regression, Decision Tree, Random Forest, and Ensemble methods. The results show that Ensemble models, particularly CatBoost, XGBoost, and LightGBM, achieve improved performance compared with traditional baselines, with notable gains in minority-class recall and overall discrimination ability. The best-performing model attains an F1-score of 0.540, a recall of 0.812 for the positive class, and a ROC–AUC of 0.908. To enhance interpretability, SHAP-based analysis is applied to quantify feature contributions, identifying campaign duration, previous contact outcomes, and selected macroeconomic indicators as key predictors. These findings indicate that combining resampling strategies with cost-sensitive optimization provides a robust and transparent approach for learning from imbalanced telemarketing data, thereby supporting reproducible and data-driven financial decision-making by explicitly addressing difficulty in minority-class identification under imbalance and class imbalance under cross-entropy training in imbalanced banking data. Full article

Epoxy resin (E-51) exhibits excellent adhesion and is widely used in the preparation of functional composite coatings. However, its smooth surface lacking micro/nano composite structures limits its self-cleaning capability and optical properties. Direct incorporation of organic silicone or inorganic fillers often faces severe phase separation and filler agglomeration issues, resulting in defects in coating durability and weather resistance. To address these challenges, this study developed a synergistic modification strategy integrating surface energy modulation with the architectural design of micro/nano-structures. Amino-terminated PDMS undergoes ring-opening addition reactions with epoxy groups in the epoxy resin, while functionalized barium sulfate nanoparticles modified with dual silane coupling agents are incorporated to enhance optical properties. This synergistic approach not only resolved interfacial compatibility but also endowed the PDMS@EP-BaSO₄ coating with outstanding comprehensive properties; the water contact angle increased to 123.5°, demonstrating an easy-to-clean benefit. Visible light reflectance reached 95%, and emissivity rose to 90%. Furthermore, when applied to metal surfaces, the coating exhibited excellent stability against acid–alkali–salt corrosion, extreme temperatures, and ultrasonic agitation. This work provided a novel approach for developing protective coatings that integrated high reflectance, high emissivity, and long-term anti-soiling properties. Full article

PDMS SlipChips are vital for precision medicine, but their performance often degrades when solutions leak or air pockets become trapped between layers. These failures stem from the inherent stickiness of PDMS and uneven surface contact, as the sliding nature of the device prevents permanent sealing. This work addresses these technical hurdles by integrating magnetic clamping with oil-infused lubrication and refined microwell geometries. A 3D-printed magnetic fixture maintains steady contact pressure during operation, while custom-made microstages provide the precise control needed to align microwells across the x–y plane. By allowing the porous PDMS to absorb silicone oil, we created a stable lubricating interface that prevents leakage and reduces friction without sacrificing mobility. We found that a microwell-to-channel width ratio of five substantially suppresses bubble formation compared with narrower designs. These enhancements ensure the generation of consistent, discrete concentration gradients and establish a reliable platform for high-throughput assays using minute sample volumes. Full article

Quantifying river surface flow velocity is essential for hydrodynamic modelling, flood forecasting, and water resource management. Traditional in situ methods provide accurate point measurements but are costly and limited in spatial coverage. Unmanned aerial vehicles (UAVs) offer a flexible, non-contact alternative for high-resolution monitoring. Optical flow is a tracer-independent technique for deriving velocity fields from RGB video, making it well suited to UAV-based surveys. However, its operational use is hindered by the limited availability of annotated datasets and by instability under low-texture or noisy conditions. This study combines a Finite element method (FEM)-based physical flow model with UAV video to generate reference datasets and introduces a modified Recurrent All-Pairs Field Transforms (RAFT) architecture based on multiframe sequences. A Gated Recurrent Unit fusion module (Fuse-GRU) is incorporated prior to correlation computation, improving robustness to illumination changes and surface homogeneity while maintaining computational efficiency. The proposed model delivers stable, physically consistent velocity estimates across multiple rivers and flow conditions. Accuracy improves with higher spatial resolution and moderate temporal spacing. Compared to field measurements, the average angular difference ranged from 8 to 15°. The high error values were mainly caused by inaccuracies in the physical model and by complex river features. These findings confirm that multiframe optical flow can reproduce realistic river flow patterns with accuracy comparable to physically-based simulations, thereby supporting UAV-based hydrometric monitoring and model validation. Full article

This work explores the effect of nitrogen ion implantation on the wettability of the cemented tungsten carbide–cobalt (WC–Co) tool surface used for wood-based panel machining. Nitrogen ions with an energy of 50 keV and a fluence of 1 × 10¹⁷ and 5 × 10¹⁷ cm⁻² were implanted into the surface layer of commercially available WC–Co indexable knives using the implanter without a mass-separated ion beam. The wettability was characterized by a contact angle instrument. The implantation of nitrogen ions into WC–Co tools caused a statistically significant and practically useful decrease in the contact angle. This obtained effect was dependent on the fluence of the implanted ions, and it changed over time. This effect may also explain the transfer from the workpiece and the surface capture of carbon atoms in the secondary structure formed during the machining of wood materials on tools with ion implantation. On the other hand, the layer of carbon on the surface of the tool formed during machining explains the reduction in friction coefficient observed in experiments and the increase in tool life during cutting. Full article

Objective: To evaluate the biomechanical effects of varying posterior implant inclinations and loading protocols on peri-implant stress distribution in full-arch maxillary rehabilitations using the All-on-Four concept. Methodology: A three-dimensional finite element model of an edentulous atrophic maxilla was developed from a digital point cloud. Four implants were placed according to the All-on-Four protocol: two anterior vertical implants and two posterior implants with inclinations of 0°, 15°, 30°, or 45°. Mini-abutments and a titanium bar prosthesis were included. Material properties were assumed as homogeneous, isotropic, and linearly elastic. Immediate loading was simulated using frictional contacts (µ = 0.3), whereas delayed loading assumed complete osseointegration (bonded contacts). The models were meshed using 10-node quadratic tetrahedral elements (SOLID187) in ANSYS^®. Maximum von Mises stress in cortical bone, cancellous bone, implants, abutments, and the prosthetic bar was assessed. Results: Posterior implant tilt significantly reduced peri-implant stress. Under immediate loading, the highest stress occurred at 0° inclination in the posterior left implant (82.36 MPa) and decreased progressively with increasing tilt, reaching 33.63 MPa at 45° (≈59% reduction). Delayed loading generally produces lower stress magnitudes, particularly at extreme tilts. Anterior implants experienced lower stress levels across all configurations. Comparative analysis demonstrated that immediate loading increased stress at lower angulations, while differences between loading protocols were minimal at higher inclinations. Conclusions: Posterior implant angulation and loading protocol critically influence peri-implant stress distribution. Increased posterior tilt combined with appropriate loading reduces peak cortical bone stresses, supporting biomechanical optimization in All-on-Four maxillary rehabilitations. Full article

A new universal construction of intermediate-layer-free solid-contact ion-selective electrodes using a novel inner electrode, namely microelectrodes array composed of a large number of individual microelectrodes, was developed. This approach eliminates the need for a conventional solid-contact intermediate layer while maintaining excellent electrochemical performance. The studies were performed on two membrane model systems: potassium-ion-sensitive membranes based on valinomycin and nitrate-ion-sensitive membranes based on tridodecyldimethylammonium nitrate. In both cases, the membrane was applied directly onto the surface of the electrode substrate. The obtained results with such an ion-selective electrode based on a gold microelectrode array (GMA), a glassy carbon electrode (GCE), and a gold electrode (GE) were compared. It has been proven that, despite the lack of solid contact, whether in the form of an intermediate layer or as an addition directly to the membrane, ion-selective electrodes based on gold microelectrode arrays were characterized by very good analytical parameters. For those electrodes, a notable improvement in stability, reversibility, and repeatability of the electrode potential was observed and compared with electrodes using a glassy carbon disc electrode or a gold disc electrode as the electrode substrate. Thanks to the use of such an innovative electrode substrate, the final sensor preparation is shortened and simplified while maintaining good performance and stable readings. Full article

Olive pomace biochar, obtained through the pyrolysis of lignocellulosic biomass, has emerged as a sustainable and multifunctional additive for polymer composites. Its physicochemical properties, including porosity, surface area, and electrical conductivity, can be tailored by controlling feedstock type and pyrolysis conditions. Although mechanical reinforcement and thermal stability improvements are well documented, the influence of biochar on surface-related properties such as wettability and contact angle remains insufficiently explored for environmentally relevant composite systems. In this study, epoxy-based composites containing biochar synthesized at 750 °C were evaluated in terms of their water interaction behavior by monitoring the evaporation dynamics of ultra-pure water droplets (10 μL, 0.055 mS/cm conductivity) at eight time intervals between 20 and 580 s using high-resolution digital microscopy. Image enhancement and segmentation were performed prior to Discrete Cosine Transform (DCT) analysis to describe droplet geometry in the frequency domain. Time-dependent variations in the standard deviations of DCT coefficients were optimized using the Bat Algorithm, resulting in mathematical models capable of accurately representing droplet evolution and surface–fluid interactions. The primary novelty of this study lies in the development of a hybrid experimental–computational framework that integrates droplet-based wettability measurements with signal-domain analysis and metaheuristic optimization. Unlike conventional studies focusing solely on material characterization, this approach establishes quantitative relationships between surface behavior and numerical descriptors derived from DCT and the Bat Algorithm. The proposed methodology provides a data-driven tool for predicting wettability trends in biochar-reinforced composites and supports the development of moisture-resistant materials for coatings, packaging, and thermal insulation applications within the context of sustainable composite design. Full article

Calculation of heat transfer in granular materials is an important task for many applications, from thermal management in electronics to exploring celestial soils. Usually, an effective thermal-conductivity model is employed to predict heat flux in unstructured granular media, such as a packed bed. However, a more advanced approach, the discrete element method (DEM), can capture the complex effects of mechanical loading and material mixtures on thermal transport coefficients, which traditional models struggle with. Pivotal for this approach is knowing the heat transfer coefficient between two adjacent particles. Currently, in most DEM-capable software, only particles in direct surface contact are considered to have non-zero heat conduction. We propose considering particles that are close to each other but don’t have a contact area with a non-zero surface area. We perform numerical modeling of the conductive heat transfer coefficient between equal spherical particles separated by media, assuming the fluid’s thermal conductivity is at least an order of magnitude lower. We use numerical solutions of differential equations to account for both thermal resistance within particles and through the gap between them. We found a simple generalized correlation for the heat transfer coefficient between particles and a general formula for the angular distribution of heat flux density across the particle surface. By employing a non-dimensional approach, the obtained formulas are constructed using non-dimensional parameters: the ratio of the particle’s thermal conductivity to that of the medium, and the ratio of the gap width between particles to their radius. The resulting formula is simple and convenient for DEM heat transfer calculations in packed and fluidized beds. Full article