Search Results (292)

Background: A precise drug delivery system enables the optimization of treatments with minimal side effects if it can deliver medication only when activated by a specific light source. This study presents a controlled drug delivery system based on poly(lactic-co-glycolic acid) (PLGA) microparticles (MPs) designed for the sustained release of vancomycin hydrochloride. Methods: The MPs were co-loaded with indocyanine green (ICG), a near-infrared (NIR) responsive agent, and fabricated via the double emulsion method.They were characterized for stability, surface modification, biocompatibility, and antibacterial efficacy. Results: Dynamic light scattering and zeta potential analyses confirmed significant increases in particle size and surface charge reversal following chitosan coating. Scanning electron microscopy revealed uniform morphology in uncoated MPs (1–10 $\mathsf{\mu }$m) and irregular surfaces post-coating. Stability tests demonstrated drug retention for up to 180 days. Among formulations, PVI1 exhibited the highest yield (76.67 ± 1.3%) and encapsulation efficiency (56.2 ± 1.95%). NIR irradiation (808 nm) enhanced drug release kinetics, with formulation PVI4 achieving over 48.9% release, resulting in improved antibacterial activity. Chitosan-coated MPs (e.g., PVI4-C) effectively suppressed drug release without NIR light for up to 8 h, with cumulative release reaching only 10.89%. Without NIR light, bacterial colonies exceeded 1000 CFU; NIR-triggered release reduced them below 120 CFU. Drug release data fitted best with the zero-order and Korsmeyer–Peppas models, suggesting a combination of diffusion-controlled and constant-rate release behavior. Conclusions: These results demonstrate the promise of chitosan-coated NIR-responsive PLGA MPs for precise, on-demand antibiotic delivery and improved antibacterial performance. Full article

Gypsum (CaSO₄·2H₂O) crystallization underpins numerous industrial processes, yet its response to chemical admixtures remains incompletely understood. This study investigates diffusion-controlled crystal growth in a coaxial test tube system to evaluate how three Sika^® ViscoCrete^® superplasticizers—430P, 111P, and 120P—affect nucleation, growth kinetics, morphology, and thermal behavior. The superplasticizers, selected for their surface-active properties, were hypothesized to influence crystallization via interfacial interactions. Ion diffusion was maintained quasi-steadily for 12 weeks, with crystal evolution tracked weekly by macro-photography; scanning electron microscopy and thermogravimetric/differential scanning were performed at the final stage. All admixtures delayed nucleation in a concentration-dependent manner. Lower dosages (0.5–1.0 wt%) yielded platy-to-prismatic morphologies and higher dehydration enthalpies, indicating more ordered lattice formation. In contrast, higher dosages (1.5–2.0 wt%) produced denser, irregular crystals and shifted dehydration to lower temperatures, suggesting structural defects or increased hydration. Among the additives, 120P showed the strongest inhibitory effect, while 111P at 0.5 wt% resulted in the most uniform crystals. These results demonstrate that ViscoCrete^® superplasticizers can modulate gypsum crystallization and thermal properties. Full article

Plasma electrolytic oxidation (PEO) is an advanced electrochemical surface treatment technology. It can effectively improve the corrosion resistance of magnesium and its alloys. This paper aims to form protective PEO coatings on an AZ31 substrate with different electrolytes, while monitoring the micro-discharge evolution by noise intensity and morphology analysis. By setting the PEO parameters and monitoring process characteristics, such as current density, spark appearance, and noise intensity, it was deduced that the PEO process consists of the following three stages: anodic oxidation, spark discharge, and micro-arc discharge. The PEO oxide coating formed on the AZ31 alloy exhibits various irregular volcano-like structures. Oxygen species are uniformly distributed along the coating cross-section. Phosphorus species tend to be enriched inwards to the coating/magnesium substrate interface, while aluminum piles up towards the surface region. Surface roughness of the PEO coating formed in the silicate-based electrolyte was the lowest in an arithmetic average height (Sa) of 0.76 μm. Electrochemical analysis indicated that the corrosion current density of the PEO coating decreased by about two orders of magnitude compared to that of untreated blank AZ31 substrate, while, at the same time, the open-circuit potential shifted significantly to the positive direction. The corrosion current density of the 10 min/400 V coating was 1.415 × 10⁻⁶ A/cm², approximately 17% lower than that of the 2 min/400 V coating (1.738 × 10⁻⁶ A/cm²). For a fixed 10 min treatment, the longer the PEO duration time, the lower the corrosion current density. Finally, the tested potentiodynamic polarization curve reveals the impact of different types of PEO electrolytes and different durations of PEO treatment on the corrosion resistance of the oxide coating surface. Full article

Steel surface defect detection is a crucial step in ensuring industrial production quality. However, due to significant variations in scale and irregular geometric morphology of steel surface defects, existing detection algorithms show notable deficiencies in multi-scale feature representation and cross-layer multi-scale feature fusion efficiency. To address these challenges, this paper proposes an improved real-time steel surface defect detection model, NGD-YOLO, based on YOLOv5s, which achieves fast and high-precision defect detection under relatively low hardware conditions. Firstly, a lightweight and efficient Normalization-based Attention Module (NAM) is integrated into the C3 module to construct the C3NAM, enhancing multi-scale feature representation capabilities. Secondly, an efficient Gather–Distribute (GD) mechanism is introduced into the feature fusion component to build the GD-NAM network, thereby effectively reducing information loss during cross-layer multi-scale information fusion and adding a small target detection layer to enhance the detection performance of small defects. Finally, to mitigate the parameter increase caused by the GD-NAM network, a lightweight convolution module, DCConv, that integrates Efficient Channel Attention (ECA), is proposed and combined with the C3 module to construct the lightweight C3DC module. This approach improves detection speed and accuracy while reducing model parameters. Experimental results on the public NEU-DET dataset show that the proposed NGD-YOLO model achieves a detection accuracy of 79.2%, representing a 4.6% mAP improvement over the baseline YOLOv5s network with less than a quarter increase in parameters, and reaches 108.6 FPS, meeting the real-time monitoring requirements in industrial production environments. Full article

Background/Objectives: The formulation of microspheres for lipophilic drugs using aqueous methods, such as spray drying, faces significant challenges. The main objective of this study was to evaluate the effect of the process parameters and polymer selection on the production of microspheres by spray drying for a lipophilic drug. Methods: Lipophilic drug-loaded microspheres were developed using various polymers via the aqueous spray drying method. The effects of the factors on the yield percentage and encapsulation efficiency were analyzed. Microspheres preparation included Agave inulin, guar gum, hydroxypropyl methylcellulose, and Eudragit^® S100. A 2³ factorial design was performed, and the parameters were optimized. Results: Inlet temperature, feed flow, and polymer percentage showed a significant effect (p < 0.05) on the yield percentage of guar gum microspheres and encapsulation efficiency of the inulin microspheres. Inulin and guar gum microspheres showed the best yield percentage (75.41%) and encapsulation efficiency (100%), respectively. In addition, guar gum microspheres had the best morphology, and hydroxypropyl methylcellulose microspheres were smaller and had an irregular surface. Eudragit did not maintain its delayed release property due to limitations of the aqueous method; inulin released the drug immediately, and guar gum and hydroxypropyl methylcellulose microspheres prolonged release only by a few additional hours. Conclusions: The experimental design showed that optimizing the parameters (inlet temperature, feed flow, and the type and percentage of polymer) can regulate the microsphere development process to obtain improved product yield and encapsulation efficiency results. Full article

This entry gives an overview of the main data structures and approaches used for a two-dimensional representation of the terrain surface using a digital elevation model (DEM). A DEM represents the elevation of the earth surface from a set of points. It is used for terrain analysis, visualisation and interpretation. DEMs are most commonly defined as a grid where an elevation is assigned to each grid cell. Due to its simplicity, the square grid structure is the most common DEM structure. However, it is less adaptive and shows limitations for more complex processing and reasoning. Hence, the triangulated irregular network is a more adaptive structure and explicitly stores the relationships between the points. Other topological structures (contour graphs, contour trees) have been developed to study terrain morphology. Topological relationships are captured in another structure, the surface network (SN), composed of critical points (peaks, pits, saddles) and critical lines (thalweg, ridge lines). The SN can be computed using either a TIN or a grid. The Morse Theory provides a mathematical approach to studying the topology of surfaces, which is applied to the SN. It has been used for terrain simplification, multi-resolution modelling, terrain segmentation and landform identification. The extended surface network (ESN) extends the classical SN by integrating both the surface and the drainage networks. The ESN can itself be extended for the cognitive representation of the terrain based on saliences (typical points, lines and regions) and skeleton lines (linking critical points), while capturing the context of the appearance of landforms using topo-contexts. Full article

Tooth bleaching is a widely used esthetic treatment; however, bleaching agents can temporarily alter the surface morphology of enamel, increasing surface roughness and porosity, which may lead to increased susceptibility to discoloration. This in vitro study investigated the effectiveness of fluoride varnish in preventing immediate discoloration of bovine incisors after bleaching. Specimens were bleached with 35% hydrogen peroxide and treated with either Clinpro White Varnish (CW) or Enamelast Fluoride Varnish (EN), whereas control specimens received no treatment after bleaching. The samples were immersed in coffee for 24 h, and the color difference (ΔE₀₀) was calculated using the CIEDE2000 formula. The surface morphology of enamel was examined using SEM. The fluoride varnish groups showed significantly lower color difference values than the control group (p < 0.05), with ΔE₀₀ reduced by approximately two-thirds in both the CW and EN groups. SEM observations showed that the enamel surfaces in the varnish-treated groups exhibited reduced surface irregularities compared to the untreated group, suggesting remineralization. These results suggest that the immediate application of fluoride varnish after bleaching can effectively reduce short-term discoloration by providing physical protection and promoting remineralization. Fluoride varnish may serve as a simple and effective strategy to maintain whitening outcomes and minimize early discoloration. Full article

Laser-induced periodic surface structures (LIPSSs) produced via ultrafast laser-induced oxidation offer a promising route for high-quality nanostructuring, with reduced thermal damage compared to conventional ablation-based methods. However, the influence of laser repetition frequency on the formation and morphology of oxidized LIPSSs remains insufficiently explored. In this study, we systematically investigate the effects of varying the femtosecond laser repetition frequency from 1 kHz to 100 kHz while keeping the total pulse number constant on the oxidation-induced LIPSSs formed on amorphous silicon films. Scanning electron microscopy and Fourier analysis reveal a transition between two morphological regimes with increasing repetition frequency: at low frequencies, the long inter-pulse intervals result in irregular, disordered oxidation patterns; at high frequencies, closely spaced pulses promote the formation of highly ordered, periodic surface structures. Statistical measurements show that the laser-modified area decreases with frequency, while the LIPSS period remains relatively stable and the ridge width exhibits a peak at 10 kHz. Finite-difference time-domain (FDTD) and finite-element simulations suggest that the observed patterns result from a dynamic balance between light-field modulation and oxidation kinetics, rather than thermal accumulation. These findings advance the understanding of oxidation-driven LIPSS formation dynamics and provide guidance for optimizing femtosecond laser parameters for precise surface nanopatterning. Full article

Structural timber is an important building material, but surface defects such as cracks and knots seriously affect its load-bearing capacity, dimensional stability, and long-term durability, posing a significant risk to structural safety. Conventional inspection methods are unable to address the issues of multi-scale defect characterization, inter-class confusion, and morphological diversity, thus limiting reliable construction quality assurance. To overcome these challenges, this study proposes WDNET-YOLO: an enhanced deep learning model based on YOLOv8n for high-precision defect detection in structural wood. First, the RepVGG reparameterized backbone utilizes multi-branch training to capture critical defect features (e.g., distributed cracks and dense clusters of knots) across scales. Second, the ECA attention mechanism dynamically suppresses complex wood grain interference and enhances the discriminative feature representation between high-risk defect classes (e.g., cracks vs. knots). Finally, CARAFE up-sampling with adaptive contextual reorganization improves the sensitivity to morphologically variable defects (e.g., fine cracks and resin irregularities). The analysis results show that the mAP50 and mAP50-95 of WDNET-YOLO are improved by 3.7% and 3.5%, respectively, compared to YOLOv8n, while the parameters are increased by only 4.4%. The model provides a powerful solution for automated structural timber inspection, which directly improves building safety and reliability by preventing failures caused by defects, optimizing material utilization, and supporting compliance with building quality standards. Full article

The type of foaming agent significantly influences the pore structure and properties of foam ceramics, particularly their compressive strength. This study used quartz sand tailings and waste glass powder as raw materials to fabricate foam ceramic materials. The effects of different foaming agents (SiC, CaCO₃, and MnO₂) on the phase evolution, microstructure, pore size distribution, and physical properties of the foam ceramics were investigated, and the foaming mechanisms were elucidated. The results indicated that when SiC was employed as the foaming agent, the viscosity was high at elevated temperatures and pores with irregular shapes tended to form because of the anisotropy of the quartz crystals. CaO generated from CaCO₃ decomposition reduced the melt viscosity by disrupting the [SiO₄] tetrahedra, whereas the formation of anorthite and diopside stabilized the pore morphology, resulting in regular circular pores. When MnO₂ was used as the foaming agent, the pressure from the gas produced during oxidation exceeded the surface tension of the molten phase owing to its viscosity, leading to the formation of larger, irregular, and interconnected pores. The foam ceramic material exhibited optimal properties when 2% CaCO₃ was used as the foaming agent, with a water absorption rate of 30%, bulk density of 0.62 g/cm³, porosity of 68.4%, compressive strength of 9.67 MPa, and thermal conductivity of 0.26 W/(m·K). Full article

Functionally graded materials (FGMs) are fabricated on Ti-6Al-4V alloy surfaces to improve insufficient surface hardness and wear resistance. Microstructure and mechanical properties and strengthening–toughening mechanisms of FGMs were investigated. The FGM cladding layer exhibits distinct gradient differentiation, demonstrating gradient variations in the nanoindentation hardness, wear resistance, and Al/V elemental composition. Molten pool dynamics analysis reveals that Marangoni convection drives Al/V elements toward the molten pool surface, forming compositional gradients. TiN-AlN eutectic structures generated on the FGM surface enhance wear resistance. Rapid solidification enables heterogeneous nucleation for grain refinement. The irregular wavy interface morphology strengthens interfacial bonding through mechanical interlocking, dispersing impact loads and suppressing crack propagation. FGMs exhibit excellent wear resistance and impact toughness compared with Ti-6Al-4V titanium alloy. The specific wear rate is 1.17 × 10⁻² mm³/(N·m), dynamic compressive strength reaches 1701.6 MPa, and impact absorption energy achieves 189.6 MJ/m³. This work provides theoretical guidance for the design of FGM strengthening of Ti-6Al-4V surfaces. Full article

To improve the traction performance of mobile mechanisms on soft ground, such as paddy fields, tidal flats, and swamps, a mallard (Anas platyrhynchos) foot was adopted as a bionic prototype to explore the influence and contribution of the plantar morphology of the toes and webbing on the anti-subsidence function during its locomotion on wet and soft substrates and to apply this to the bionic design of high-traction wheel grousers. A handheld three-dimensional laser scanner was used to scan the main locomotion postures of a mallard foot during ground contact, and the Geomagic Studio software was utilized to repair the scanned model. As a result, the main three-dimensional geometric models of a mallard foot during the process of touching the ground were obtained. The plantar morphology of a mallard foot was divided into three typical parts: the plantar irregular edge curve, the lateral webbing surface, and the medial webbing surface. The main morphological feature curves/surfaces were extracted through computer-aided design software for the fitting and construction of a mathematical model to obtain the fitting equations of the three typical parts, and the mathematical model construction of the plantar irregular morphology of the mallard foot was completed. In order to verify the sand-fixing and flow-limiting characteristics of this morphological feature, based on the discrete element method (DEM), the numerical simulation of the interaction between the plantar surface of the mallard foot and sand particles was carried out. The simulation results show that during the process of the mallard foot penetration into the loose medium, the lateral and medial webbing surfaces cause the particles under the foot to mainly move downward, effectively preventing the particles from spreading around and significantly enhancing the solidification effect of the particles under the sole. Based on the principle and technology of engineering bionics, the plantar morphology and movement attitude characteristics of the mallard were extracted, and the characteristics of concave middle and edge bulge were applied to the wheel grouser design of paddy field wheels. Two types of bionic wheel grousers with different curved surfaces were designed and compared with the traditional wheel grousers of the paddy field wheel. Through pressure-bearing simulation and experiments, the resistance of different wheel grousers during the process of penetrating into sand particles was compared, and the macro–micro behaviors of particle disturbance during the pressure-bearing process were analyzed. The results show that a bionic wheel grouser with unique curved surfaces can well encapsulate sand particles at the bottom of the wheel grouser, and it also has a greater penetration resistance, which plays a crucial role in improving the traction performance of the paddy field wheel and reducing the disturbance to the surrounding sand particles. This paper realizes the transformation from the biological model to the mathematical model of the plantar morphology of the mallard foot and applies it to the bionic design of the wheel grousers of the paddy field wheels, providing a new solution for improving the traction performance of mobile mechanisms on soft ground. Full article

Aiming at the difficulties of scarcity of defect samples on the surface of power insulators, irregular morphology and insufficient pixel-level localization accuracy, this paper proposes a defect detection method based on graph feature diffusion distillation named GFDD. The feature bias problem is alleviated by constructing a dual-division teachers architecture with graph feature consistency constraints, while the cross-layer feature fusion module is utilized to dynamically aggregate multi-scale information to reduce redundancy; the diffusion distillation mechanism is designed to break through the traditional single-layer feature transfer limitation, and the global context modeling capability is enhanced by fusing deep semantics and shallow details through channel attention. In the self-built dataset, GFDD achieves 96.6% Pi.AUROC, 97.7% Im.AUROC and 95.1% F1-score, which is 2.4–3.2% higher than the existing optimal methods; it maintains excellent generalization and robustness in multiple public dataset tests. The method provides a high-precision solution for automated inspection of insulator surface defect and has certain engineering value. Full article

Fruits and endocarps of 21 species within the genus Premna (Lamiaceae) in Thailand were examined using light (LM) and scanning electron microscopy (SEM) to evaluate taxonomic relevance. Overall, mature fruits were classified into two types: fully developed mericarp (fruit type I) and partly developed mericarp (fruit type II), with three shape patterns: broadly obovoid, narrowly obovoid, and clavoid. Fruit size ranged from 1.52 to 7.48 mm in length and 0.98 to 7.71 mm in width. In LM investigations, the endocarps were classified into three types based on the presence and shape of the protruding structure: saccate-like (protrusion type I), thorn-like (protrusion type II), and no protrusion (protrusion type III). The examination of endocarps under SEM showed that they consist of multilayers of sclerenchyma cells. The shape of the sculpturing cells on the endocarp surface can be divided into two patterns: irregular tetragonal and polygonal, with distinct or obscure straight cell faces. The morphological comparison and phenetic analyses using factor analysis of mixed data (FAMD) show that fruit and endocarp characteristics of Premna hold significant taxonomic value for distinguishing certain related species and classifying within the genus in Thailand. From the first two FAMD dimensions, fruit shape, shape of sculptured cells on the endocarp, and protrusion type of the endocarp are considered as the most significant contributing variables. The findings also support the reinstatement of species previously synonymized with P. serratifolia, namely P. cordifolia, P. paniculata, and P. punctulata. Full article

Accurate segmentation of pavement cracks from high-resolution remote sensing imagery plays a crucial role in automated road condition assessment and infrastructure maintenance. However, crack structures often exhibit asymmetry, irregular morphology, and multi-scale variations, posing significant challenges to conventional CNN-based methods in real-world environments. Specifically, the proposed ETAFHrNet focuses on two predominant pavement-distress morphologies—linear cracks (transverse and longitudinal) and alligator cracks—and has been empirically validated on their intersections and branching patterns over both asphalt and concrete road surfaces. In this work, we present ETAFHrNet, a novel attention-guided segmentation network designed to address the limitations of traditional architectures in detecting fine-grained and asymmetric patterns. ETAFHrNet integrates Transformer-based global attention and multi-scale hybrid feature fusion, enhancing both contextual perception and detail sensitivity. The network introduces two key modules: the Efficient Hybrid Attention Transformer (EHAT), which captures long-range dependencies, and the Cross-Scale Hybrid Attention Module (CSHAM), which adaptively fuses features across spatial resolutions. To support model training and benchmarking, we also propose QD-Crack, a high-resolution, pixel-level annotated dataset collected from real-world road inspection scenarios. Experimental results show that ETAFHrNet significantly outperforms existing methods—including U-Net, DeepLabv3+, and HRNet—in both segmentation accuracy and generalization ability. These findings demonstrate the effectiveness of interpretable, multi-scale attention architectures in complex object detection and image classification tasks, making our approach relevant for broader applications, such as autonomous driving, remote sensing, and smart infrastructure systems. Full article