Search Results (14,782)

This study presents a photoresist-free patterning method for solution-processed indium zinc oxide (IZO) thin films using two photochemical exposure techniques, namely pulsed ultraviolet (UV) light and UV-ozone, and a plasma-based method using oxygen (O₂) plasma. Pulsed UV light delivers short, high-intensity flashes of light that induce localised photochemical reactions with minimal thermal damage, whereas UV-ozone enables smooth and uniform surface oxidation through continuous low-pressure UV irradiation combined with in situ ozone generation. By contrast, O₂ plasma generates ionised oxygen species via radio frequency (RF) discharge, allowing rapid surface activation, although surface damage may occur because of energetic ion bombardment. All three approaches enabled pattern formation without the use of conventional photolithography or chemical developers, and the UV-ozone method produced the most uniform and clearly defined patterns. The patterned IZO films were applied as active layers in bottom-gate top-contact thin-film transistors, all of which exhibited functional operation, with the UV-ozone-patterned devices exhibiting the most favourable electrical performance. This comparative study demonstrates the potential of photochemical and plasma-assisted approaches as eco-friendly and scalable strategies for next-generation IZO patterning in electronic device applications. Full article

Aiming to enable intelligent vehicles to achieve autonomous charging under low-battery conditions, this paper presents a navigation system for autonomous charging that integrates an improved bidirectional A* algorithm for path planning and an optimized YOLOv11n model for visual recognition. The system utilizes the improved bidirectional A* algorithm to generate collision-free paths from the starting point to the charging area, dynamically adjusting the heuristic function by combining node–target distance and search iterations to optimize bidirectional search weights, pruning expanded nodes via a greedy strategy and smoothing paths into cubic Bézier curves for practical vehicle motion. For precise localization of charging areas and piles, the YOLOv11n model is enhanced with a CAFMFusion mechanism to bridge semantic gaps between shallow and deep features, enabling effective local–global feature fusion and improving detection accuracy. Experimental evaluations in long corridors and complex indoor environments showed that the improved bidirectional A* algorithm outperforms the traditional improved A* algorithm in all metrics, particularly in that it reduces computation time significantly while maintaining robustness in symmetric/non-symmetric and dynamic/non-dynamic scenarios. The optimized YOLOv11n model achieves state-of-the-art precision (P) and mAP@0.5 compared to YOLOv5, YOLOv8n, and the baseline model, with a minor 0.9% recall (R) deficit compared to YOLOv5 but more balanced overall performance and superior capability for small-object detection. By fusing the two improved modules, the proposed system successfully realizes autonomous charging navigation, providing an efficient solution for energy management in intelligent vehicles in real-world environments. Full article

Solid-state LiDAR systems are widely recognized for their high reliability, low cost, and lightweight design, but they encounter significant challenges in SLAM tasks due to their limited field of view and uneven horizontal scanning patterns, especially in indoor environments with geometric constraints. To address these challenges, this paper proposes SS-LIO, a precise, robust, and real-time LiDAR–Inertial odometry solution designed for solid-state LiDAR systems. SS-LIO uses uncertainty propagation in LiDAR point-cloud modeling and a tightly coupled iterative extended Kalman filter to fuse LiDAR feature points with IMU data for reliable localization. It also employs voxels to encapsulate planar features for accurate map construction. Experimental results from open-source datasets and self-collected data demonstrate that SS-LIO achieves superior accuracy and robustness compared to state-of-the-art methods, with an end-to-end drift of only 0.2 m in indoor degraded scenarios. The detailed and accurate point-cloud maps generated by SS-LIO reflect the smoothness and precision of trajectory estimation, with significantly reduced drift and deviation. These outcomes highlight the effectiveness of SS-LIO in addressing the SLAM challenges posed by solid-state LiDAR systems and its capability to produce reliable maps in complex indoor settings. Full article

Tungsten and tungsten alloys are widely used in important industrial fields due to their high density, hardness, melting point, and corrosion resistance. However, machining often leaves processing marks on their surface, significantly affecting the surface quality of precision components in industrial applications. Electrolytic polishing offers high efficiency, low workpiece wear, and simple processing. In this study, an electrolytic polishing method is adopted and a novel trisodium phosphate–sodium hydroxide electrolytic polishing electrolyte is developed to study the effects of temperature, voltage, polishing time, and solution composition on the surface roughness of a tungsten–nickel–iron alloy. The optimal voltage, temperature, and polishing time are determined to be 15 V, 55 °C, and 35 s, respectively, when the concentrations of trisodium phosphate and sodium hydroxide are 100 g·L⁻¹ and 6 g·L⁻¹. In addition, glycerol is introduced into the electrolyte as an additive. The calculated LUMO value of glycerol is −5.90 eV and the HOMO value is 0.40 eV. Moreover, electron enrichment in the hydroxyl region of glycerol can form an adsorption layer on the surface of the tungsten alloy, inhibit the formation of micro-pits, balance ion diffusion, and thus promote the formation of a smooth surface. At 100 mL·L⁻¹ of glycerol, the roughness of the tungsten–nickel–iron alloy decreases significantly from 1.134 μm to 0.582 μm. The electrochemical polishing mechanism of the tungsten alloy in a trisodium phosphate electrolyte is further investigated and explained according to viscous film theory. This study demonstrates that the trisodium phosphate–sodium hydroxide–glycerol electrolyte is suitable for electropolishing tungsten–nickel–iron alloys. Overall, the results support the application of tungsten–nickel–iron alloy in the electronics, medical, and atomic energy industries. Full article

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

Background/Objectives: A nanostructured membrane of polycaprolactone (a synthetic polymer) was synthesized using an electrospinning technique aiming to enhance its hydrophilicity and rate of degradation by surface modification via aminolysis. Since polycaprolactone nanofibrous films are naturally hydrophobic and with slow degradation, which restricts their use in biological systems, amino groups were added to the fiber surface using the aminolysis technique, greatly increasing the wettability of the membranes. Methods: Polycaprolactone nanofibrous membranes were synthesized via the electrospinning technique and surface modification by aminolysis. Trypsin, pepsin, and pancreatin were conjugated onto the aminolyzed PNF surface to further strengthen biocompatibility by enhancing the hydrophilicity, porosity, and biodegradation rate. SEM, FTIR, EDX, and liquid displacement method were performed to investigate proteolytic efficiency and morphological and physical characteristics such as hydrophilicity, porosity, and degradation rates. Results: Enzyme activity tests, which showed a zone of clearance, validated the successful enzyme conjugation and stability over a wide range of pH and temperatures. Scanning electron microscopy (SEM) confirms the smooth morphology of nanofibers with diameters ranging from 150 to 950 nm. Fourier transform infrared spectroscopy (FTIR) revealed the presence of O–H, C–O, C=O, C–N, C–H, and O–H functional groups. Energy-dispersive X-ray (EDX) elemental analysis indicates the presence of carbon, oxygen, and nitrogen atoms owing to the presence of peptide and amide bonds. The liquid displacement technique and contact angle proved that Pepsin-PNFs possess notably increased porosity (88.50% ± 0.31%) and hydrophilicity (57.6° ± 2.3 (L), 57.9° ± 2.5 (R)), respectively. Pancreatin-PNFs demonstrated enhanced enzyme activity and degradation rate on day 28 (34.61%). Conclusions: These enzyme-conjugated PNFs thus show improvements in physicochemical properties, making them ideal candidates for various biomedical applications. Future studies must aim for optimization of enzyme conjugation and in vitro and in vivo performance to investigate the versatility of these scaffolds. Full article

This study estimates a willingness-to-pay (WTP) space mixed logit model to evaluate user valuations of travel time, safety, and comfort attributes associated with common access modes in Bangkok, including walking, motorcycle taxis, and localized minibuses. The model accounts for preference heterogeneity by specifying random parameters for travel time. Results indicate that users—exhibiting substantial variation in preferences—place higher value on reducing motorcycle taxi travel time, particularly in time-constrained contexts such as peak-hour commuting, whereas walking is more acceptable in less pressured settings. Safety and comfort attributes—such as helmet availability, smooth pavement, and seating—significantly influence access mode choice. Notably, the WTP for helmet availability is estimated at THB 8.04 per trip, equivalent to approximately 40% of the typical fare for station access, underscoring the importance of safety provision. Women exhibit stronger preferences for motorized access modes, reflecting heightened sensitivity to environmental and social conditions. This study represents one of the first applications of WTP-space modeling for valuing informal station access transport in Southeast Asia, offering context-specific and segment-level estimates. These findings support targeted interventions—including differentiated pricing, safety regulations, and service quality enhancements—to strengthen first-/last-mile connectivity. The results provide policy-relevant evidence to advance equitable and sustainable transport, particularly in rapidly urbanizing contexts aligned with SDG 11.2. Full article

This paper addresses the critical gap in the existing literature regarding the combined buoyancy–Marangoni convection of power-law fluids in three-dimensional porous media with complex evaporation surfaces. Previous studies have rarely investigated the convective heat transfer mechanisms in such systems, and there is a lack of effective methods to accurately track fractal evaporation surfaces, which are ubiquitous in natural and engineering porous media (e.g., geological formations, industrial heat exchangers). This research is significant because understanding heat transfer in these complex porous media is essential for optimizing energy systems, enhancing thermal management in industrial processes, and improving the efficiency of phase-change-based technologies. For this scientific issue, a general model is designed. There is a significant temperature difference on the left and right sides of the model, which drives the internal fluid movement through the temperature difference. The upper end of the model is designed as a complex evaporation surface, and there is flowing steam above it, thus forming a coupled flow field. The VOF fractal reconstruction method is adopted to approximate the shape of the complex evaporation surface, which is a major highlight of this study. Different from previous research, this method can more accurately reflect the flow and phase change on the upper surface of the porous medium. Through numerical simulation, the influence of the evaporation coefficient on the flow and heat transfer rate can be determined. Key findings from numerical simulations reveal the following: (1) Heat transfer rates decrease with increasing fractal dimension (surface complexity) and evaporation coefficient; (2) As the thermal Rayleigh number increases, the influence of the Marangoni number on heat transfer diminishes; (3) The coupling of buoyancy and Marangoni effects in porous media with complex evaporation surfaces significantly alters flow and heat transfer patterns compared to smooth-surfaced porous media. This study provides a robust numerical framework for analyzing non-Newtonian fluid convection in complex porous media, offering insights into optimizing thermal systems involving phase changes and irregular surfaces. The findings contribute to advancing heat transfer theory and have practical implications for industries such as energy storage, chemical engineering, and environmental remediation. Full article

To address the technical bottlenecks of low path planning efficiency and insufficient point cloud coverage in the automated 3D scanning of complex structural components, this study proposes an offline method for the generation and optimization of scanning paths based on CAD models. Discrete sampling of the model’s surface is achieved through the construction of an oriented bounding box (OBB) and a linear object–triangular mesh intersection algorithm, thereby obtaining a discrete point set of the model. Incorporating a standard vector analysis of the discrete points and the kinematic constraints of the scanning system, a scanner pose parameter calculation model is established. An improved nearest neighbor search algorithm is employed to generate a globally optimized scanning path, and an adaptive B-spline interpolation algorithm is applied to path smoothing. A joint MATLAB (R2023b)—RobotStudio (6.08) simulation platform is developed to facilitate the entire process, from model pre-processing and path planning to path verification. The experimental results demonstrate that compared with the traditional manual teaching methods, the proposed approach achieves a 25.4% improvement in scanning efficiency and an 18.6% increase in point cloud coverage when measuring typical complex structural components. This study offers an intelligent solution for the efficient and accurate measurement of large-scale complex parts and holds significant potential for broad engineering applications. Full article

To address the diverse requirements of accuracy and robustness in integrated navigation for unmanned aerial vehicles, an interactive robust filter algorithm that integrates the interactive multiple model concept and leverages the complementary applicability of the strong tracking filter and the smooth variable structure filter is proposed. The algorithm operates as follows: the strong tracking filter, along with the smooth variable structure filter, operates side by side with distinct models. During the filter process, the likelihood function is utilized to update the filter probabilities and determine the weights for each one of the filters. Input interaction, coupled with output fusion, is then carried out. The results of the experiments validate that the presented interactive filter algorithm significantly reduces estimation errors. When confronted with complex, dynamic noise environments and system uncertainties, it retains high-precision state estimation while demonstrating markedly improved robustness. The proposed interactive robust filter algorithm is compared against the strong tracking filter, smooth variable structure filter, and strong tracking smooth filter. Taking the strong tracking smooth filter, which has the highest accuracy among the three, as the reference baseline, the presented interactive robust filter algorithm achieves over 16% improvement in velocity accuracy and over 40% improvement in position accuracy. Full article

The use of aerial robots for inspection and maintenance in industrial settings demands high maneuverability, precise control, and reliable measurements. This study explores the development of a fully customized unmanned aerial manipulator (UAM), composed of a tilting drone and an articulated robotic arm, designed to perform non-destructive in-contact inspections of iron structures. The system is intended to operate in complex and potentially hazardous environments, where autonomous execution is supported by shared-control strategies that include human supervision. A parallel force–impedance control framework is implemented to enable smooth and repeatable contact between a sensor for ultrasonic testing (UT) and the inspected surface. During interaction, the arm applies a controlled push to create a vacuum seal, allowing accurate thickness measurements. The control strategy is validated through repeated trials in both indoor and outdoor scenarios, demonstrating consistency and robustness. The paper also addresses the mechanical and control integration of the complex robotic system, highlighting the challenges and solutions in achieving a responsive and reliable aerial platform. The combination of semi-autonomous control and human-in-the-loop operation significantly improves the effectiveness of inspection tasks in hard-to-reach environments, enhancing both human safety and task performance. Full article

Intimal hyperplasia (IH) compromises the patency of arteriovenous fistula (AVF) vascular access in patients with end-stage kidney disease. Uncontrolled cell proliferation and migration, driven by inflammation, shear stress and surgery, are well-known triggers in IH. Recently, microRNAs (miRNAs) have emerged as regulators of core mechanisms in cardiovascular diseases and as potential markers of IH. This study was aimed at identifying a specific miRNA panel in failed AVFs and clarifying the miRNA involvement in IH. miRNA profiling performed in tissues from patients with IH (AVFs) and normal veins (NVs) highlighted a subset of four miRNAs significantly deregulated (hsa-miR-155-5p, hsa-miR-449a-5p, hsa-miR-29c-3p, hsa-miR-194-5p) between the two groups. These miRNAs were analyzed in tissue-derived cells (NVCs and AVFCs), human aortic smooth muscle cells (HAOSMCs) and human umbilical vein endothelial cells (HUVECs). The panel of hsa-miR-449a-5p, hsa-miR-155-5p, hsa-miR-29c-3p and hsa-miR-194-5p was up-regulated in AVFCs, HAOSMCs and HUVEC under inflammatory stimuli. Notably, overexpression of hsa-miR-449a-5p exacerbated the proliferative, migratory and inflammatory features of AVFCs. In vitro pharmacological modulation of these miRNAs with pioglitazone, particularly the down-regulation of hsa-miR-155-5p and hsa-miR-29c-3p, suggested their involvement in IH pathogenesis and a potential translational application. Overall, these findings provide new insights into the pathogenesis of AVF failure, reinforcing the miRNA contribution to IH detection and prevention. Full article

The abnormal growth of smooth muscle cells (SMCs) contributes to the vascular remodeling associated with coronary artery disease, a leading cause of death in women. Estradiol (E2) mediates cardiovascular protective actions, in part, by inhibiting the abnormal growth (proliferation and migration) of SMCs through various mechanism. Since microRNAs (miRNAs) play a major role in regulating cell growth and vascular remodeling, we hypothesize that miRNAs may mediate the protective actions of E2. Following preliminary leads from E2-regulated miRNAs, we found that platelet-derived growth factor (PDGF)-BB-induced miR-193a in SMCs is downregulated by E2 via estrogen receptor (ER)α, but not the ERβ or G-protein-coupled estrogen receptor (GPER). Importantly, miR-193a is actively involved in regulating SMC functions. The ectopic expression of miR-193a induced vascular SMC proliferation and migration, while its suppression with antimir abrogated PDGF-BB-induced growth, effects that were similar to E2. Importantly, the restoration of miR-193a abrogated the anti-mitogenic actions of E2 on PDGF-BB-induced growth, suggesting a key role of miR-193a in mediating the growth inhibitory actions of E2 in vascular SMCs. E2-abrogated PDGF-BB, but not miR-193a, induced SMC growth, suggesting that E2 blocks the PDGF-BB-induced miR-193a formation to mediate its anti-mitogenic actions. Interestingly, the PDGF-BB-induced miR-193a formation in SMCs was also abrogated by 2-methoxyestradiol (2ME), an endogenous E2 metabolite that inhibits SMC growth via an ER-independent mechanism. Furthermore, we found that miR-193a induces SMC growth by activating the phosphatidylinositol 3-kinases (PI3K)/Akt signaling pathway and promoting the G1 to S phase progression of the cell cycle, by inducing Cyclin D1, Cyclin Dependent Kinase 4 (CDK4), Cyclin E, and proliferating-cell-nuclear-antigen (PCNA) expression and Retinoblastoma-protein (RB) phosphorylation. Importantly, in mice, treatment with miR-193a antimir, but not its control, prevented cuff-induced vascular remodeling and significantly reducing the vessel-wall-to-lumen ratio in animal models. Taken together, our findings provide the first evidence that miR-193a promotes SMC proliferation and migration and may play a key role in PDGF-BB-induced vascular remodeling/occlusion. Importantly, E2 prevents PDGF-BB-induced SMC growth by downregulating miR-193a formation in SMCs. Since, miR-193a antimir prevents SMC growth as well as cuff-induced vascular remodeling, it may represent a promising therapeutic molecule against cardiovascular disease. Full article

In modern industrial environments, quickly and accurately identifying faults is crucial for ensuring the smooth operation of production processes. Non-negative Matrix Factorization (NMF)-based fault detection technology has garnered attention due to its wide application in industrial process monitoring and machinery fault diagnosis. As an effective dimensionality reduction tool, NMF can decompose complex datasets into non-negative matrices with practical and physical significance, thereby extracting key features of the process. This paper presents a novel approach to fault detection in industrial processes, called Graph-Regularized Orthogonal Non-negative Matrix Factorization with Itakura–Saito Divergence (GONMF-IS). The proposed method addresses the challenges of fault detection in complex, non-Gaussian industrial environments. By using Itakura–Saito divergence, GONMF-IS effectively handles data with probabilistic distribution characteristics, improving the model’s ability to process non-Gaussian data. Additionally, graph regularization leverages the structural relationships among data points to refine the matrix factorization process, enhancing the robustness and adaptability of the algorithm. The incorporation of orthogonality constraints further enhances the independence and interpretability of the resulting factors. Through extensive experiments, the GONMF-IS method demonstrates superior performance in fault detection tasks, providing an effective and reliable tool for industrial applications. The results suggest that GONMF-IS offers significant improvements over traditional methods, offering a more robust and accurate solution for fault diagnosis in complex industrial settings. Full article

Early warning systems depend heavily on the accuracy of landslide displacement forecasts. This study focuses on the Bazimen landslide located in the Three Gorges Reservoir region and proposes a hybrid prediction approach combining support vector regression (SVR) and long short-term memory (LSTM) networks. These models are optimized via the K-Nearest Neighbor (KNN) algorithm. Initially, cumulative displacement data were separated into trend and cyclic elements using a smoothing approach. SVR and LSTM were then used to predict the components, and KNN was introduced to optimize input factors and classify the results, improving accuracy. The final KNN-optimized SVR-LSTM model effectively integrates static and dynamic features, addressing limitations of traditional models. The results show that LSTM performs better than SVR, with an RMSE and MAPE of 24.73 mm and 1.87% at monitoring point ZG111, compared to 30.71 mm and 2.15% for SVR. The sequential hybrid model based on KNN-optimized SVR and LSTM achieved the best performance, with an RMSE and MAPE of 23.11 mm and 1.68%, respectively. This integrated model, which combines multiple algorithms, offers improved prediction of landslide displacement and practical value for disaster forecasting in the Three Gorges area. Full article