Search Results (3,769)

The g-C₃N₄/ZnO nanocomposite materials were applied to degrade methylene blue (MB). The samples were characterized and evaluated to study the adsorption and photocatalytic degradation under visible light. The g-C₃N₄ was incorporated at percentages of 5%, 10%, 20%, and 40% relative to the ZnO weight. These composite materials were prepared using a solvothermal microwave technique. The structural, textural, morphological, and optical properties were investigated using XRD, FTIR, SEM, EDS, STEM, BET, UV-Vis, and XPS techniques. The XRD patterns of the samples showed the coexistence of crystalline phases of g-C₃N₄ and ZnO, while images and elemental composition analysis confirmed the formation of nanocomposite samples. The UV-Vis spectrum revealed a redshift in the absorption edge of the nanocomposites, indicating improved light-harvesting capability. The synthesized material g-C₃N₄/ZnO (20/80), with a surface area of 25 m²/g, exhibited higher photocatalytic performance, achieving 85% degradation of MB after 100 min under visible light, which corresponds to nearly three times the degradation efficiency of commercial P25-TiO₂ (31%) under the same conditions. The reusability and stability tests were conducted up to the fifth cycle, and this material showed 77% degradation, indicating good stability. This nanocomposite material has good potential as a photocatalyst for solar-driven MB. Full article

The accurate monitoring of short-term bathymetric changes in shallow waters is essential for effective coastal management and planning. Machine Learning (ML) applied to Unmanned Aerial Vehicle (UAV)-based multispectral imagery offers a rapid and cost-effective solution for bathymetric surveys. However, models based solely on multispectral imagery are inherently limited by confounding factors such as shadow effects, poor water quality, and complex seafloor textures, which obscure the spectral–depth relationship, particularly in heterogeneous coastal environments. To address these issues, we developed a hybrid bathymetric inversion model that integrates digital surface model (DSM) data—providing high-resolution topographic information—with ML applied to UAV-based multispectral imagery. The model training was supported by multibeam sonar measurements collected from an Unmanned Surface Vehicle (USV), ensuring high accuracy and adaptability to diverse underwater terrains. The study area, located around Lazarus Island, Singapore, encompasses a sandy beach slope transitioning into seagrass meadows, coral reef communities, and a fine-sediment seabed. Incorporating DSM-derived topographic information substantially improved prediction accuracy and correlation, particularly in complex environments. Compared with linear and bio-optical models, the proposed approach achieved accuracy improvements exceeding 20% in shallow-water regions, with performance reaching an R² > 0.93. The results highlighted the effectiveness of DSM integration in disentangling spectral ambiguities caused by environmental variability and improving bathymetric prediction accuracy. By combining UAV-based remote sensing with the ML model, this study presents a scalable and high-precision approach for bathymetric mapping in complex shallow-water environments, thereby enhancing the reliability of UAV-based surveys and supporting the broader application of ML in coastal monitoring and management. Full article

Surface roughness and morphology, along with surface chemistry, are key features for improving ingrowth behavior and combating peri-implantitis after the insertion of dental implants. Using femtosecond laser texturing, this study aims to control both morphological and topographical surface properties of a glass solder coating on a zirconia substrate for dental applications. Experiments with varying laser and scanning parameters on the upper glass solder layer show the occurrence of two different surface morphologies. On the one hand, periodic wave-like structures are generated at relatively low pulse energy, with a high scanning pulse overlap of 80 to 90% and a scanning line overlap of 50%. On the other hand, a cauliflower-like structure can be observed at high pulse energies and a line overlap of up to 90%. Both surface morphologies represent a potential way to modify the glass solder surface to customize hard- and soft-tissue ingrowth, while realizing anti-adhesive properties for pathogenic bacteria in dental applications. Full article

A novel method for three-dimensional (3D) wave reconstruction based on stereo vision is proposed to overcome the challenges of measuring water surfaces under laboratory conditions. Traditional methods, such as adding seed particles or projecting artificial textures, can solve the image problem caused by the optical properties of the water surface. However, these methods can be costly and complicated to operate. In this paper, the proposed method uses affine consistency as matching invariants, bypassing the need for artificial textures. The method presents new data and smoothness terms within the graph cuts framework to achieve robust wave reconstruction. In a laboratory tank experiment, the wave point clouds were successfully reconstructed using a binocular camera. The accuracy of the method was verified by comparing the reconstruction with theoretical values and the sequences of the wave probe. Full article

Tea tree seeds are highly sensitive to dehydration and cannot be stored for extended periods, making surface defect detection crucial for preserving their germination rate and overall quality. To address this challenge, we propose Cgc-YOLO, an enhanced YOLO-based model specifically designed to detect small-scale and complex surface defects in tea seeds. A high-resolution imaging system was employed to construct a dataset encompassing five common types of tea tree seeds, capturing diverse defect patterns. Cgc-YOLO incorporates two key improvements: (1) GhostBlock, derived from GhostNetV2, embedded in the Backbone to enhance computational efficiency and long-range feature extraction; and (2) the CPCA attention mechanism, integrated into the Neck, to improve sensitivity to local textures and boundary details, thereby boosting segmentation and localization accuracy. Experimental results demonstrate that Cgc-YOLO achieves 97.6% mAP50 and 94.9% mAP50–95, surpassing YOLO11 by 2.3% and 3.1%, respectively. Furthermore, the model retains a compact size of only 8.5 MB, delivering an excellent balance between accuracy and efficiency. This study presents a robust and lightweight solution for nondestructive detection of tea seed defects, contributing to intelligent seed screening and storage quality assurance. Full article

The reduced ductility caused by the brittle needle-like α′ martensite limits the application of TC4 alloys produced by selective laser melting (SLM). Appropriate heat treatment can improve the microstructures and properties of SLM-fabricated TC4 alloys. In this work, SLM-fabricated TC4 alloys underwent stress relief annealing at 600 °C and high-temperature annealing at 800 °C. The effects of heat treatment temperature on phase composition, microstructural morphology, grain orientation, and mechanical properties were investigated. Meanwhile, the microstructural evolution and fracture mechanisms during the heat treatment process were analyzed. The results indicate that after annealing at 600 °C, the needle-like α′ phase transforms into elongated α, and nano-β phase increases. When annealed at 800 °C, the α′ phase completely transforms into a more stable lath-shaped α phase and a short rod-shaped β phase, with the nano-β phase disappearing. The texture orientation gradually shifts from <0001> towards <01-10>, where slip systems are more active. Additionally, heat treatment promotes the transition of grain boundaries to high-angle grain boundaries, thereby alleviating stress concentration and enhancing solid-solution strengthening. After heat treatment, the ultimate tensile strength of the material slightly decreases, but the elongation significantly increases. As the annealing temperature increased, the elongation (EL) improved from 5.22% to 11.43%. Following high-temperature annealing at 800 °C, necking and larger dimples appear on the fracture surface, and the fracture mechanism shifts from a mixed brittle–ductile fracture to a ductile fracture. This work provides a theoretical basis for improving the microstructures and properties of SLM-fabricated TC4 alloys through heat treatment. Full article

The anti-slip performance of road surfaces directly affects traffic safety, yet existing evaluation methods based on texture features often suffer from limited interpretability and low accuracy. To overcome these limitations, a portable 3D laser surface analyzer was used to acquire road texture data, while a dynamic friction coefficient tester provided friction measurements. A multi-view fractal dimension index was developed to comprehensively describe the complexity of texture across spatial, cross-sectional, and depth dimensions. Combined with road surface temperature, this index was integrated into an XGBoost-based prediction model to evaluate friction at driving speeds of 10 km/h and 70 km/h. Comparative analysis with linear regression, decision tree, support vector machine, random forest, and backpropagation (BP) neural network models confirmed the superior predictive performance of the proposed approach. The model achieved backpropagation (R²) values of 0.80 and 0.82, with root mean square errors (RMSEs) of 0.05 and 0.04, respectively. Feature importance analysis indicated that fractal characteristics from multiple texture perspectives, together with temperature, significantly influence anti-slip performance. The results demonstrate the feasibility of using non-contact texture-based methods to replace traditional contact-based friction testing. Compared with traditional statistical indices and alternative machine learning algorithms, the proposed model achieved improvements in R² (up to 0.82) and reduced RMSE (as low as 0.04). This study provides a robust indicator system and predictive model to advance road surface safety assessment technologies. Full article

Implantable biomaterials are widely used in modern medicine, especially in orthopaedics, cardiovascular surgery, dentistry, and plastic and reconstructive surgery. The issue of the interaction of implants with body tissues and the risk of infection associated with them is one of the most studied and topical issues in medicine. It is very important to find a biomaterial that effectively combines both microbiology and tissue compatibility aspects. The aim of this research work was to determine the adhesion and colonization rates of Staphylococcus epidermidis, Pseudomonas aeruginosa, and Candida albicans on smooth, microtextured, and macro-textured silicone biomaterials in an in vitro study. A total of 90 silicone biomaterial samples were used, 30 for each type of biomaterial. In each of the biomaterial groups, half of the samples (n = 15) were used to determine the adhesion intensity and the other half to determine the colonization intensity on the active surface of the biomaterial samples. The study found that Staphylococcus epidermidis and Pseudomonas aeruginosa had the highest adhesion intensity on the macro-textured implant, while Candida albicans adhered best to smooth. Among the microorganisms, Pseudomonas aeruginosa demonstrated the highest colonization rate, followed by Staphylococcus epidermidis and then Candida albicans. The most intensive colonization of microorganisms was on the macro-textured implant, then on the micro-textured, and then on the smooth. The smooth and micro-textured implants did not show statistically significant differences in the intensity of adhesion and colonization. The biomaterials did not show pro-oxidant or anti-oxidant properties, and no lipid peroxidation was induced by the biomaterials. Full article

A necessary evaluation of freshwater ecosystem pollution levels and radiation risks remains crucial for maintaining environmental health, especially within economically developing areas. This study presents a comprehensive evaluation of the mineralogical, geochemical, and radiological characteristics of sediments in Nasser Lake, Egypt, to determine potential ecological and health risks. Forty sediment samples were collected from multiple locations, including both surface and bottom sediments, for analysis of textural attributes, mineral composition, potentially toxic elements, and natural radionuclides (²³⁸U, ²³²Th, and ⁴⁰K). Results revealed sand-dominated sediments with low organic matter content. The heavy mineral assemblages derived from Nile River inputs, wind-deposited materials, and eroded igneous and metamorphic rocks. Geochemical analysis showed that arsenic, cadmium, chromium, and lead concentrations exceeded upper continental crust background values, with enrichment factors and geo-accumulation indices indicating significant anthropogenic contributions. The pollution indices revealed heavy contamination levels and extreme ecological risks, which were primarily driven by arsenic and cadmium concentrations. Radiological assessments detected activity concentrations of ²³⁸U, ²³²Th, and ⁴⁰K below the world average, with hazard indices indicating minimal radiological risk except where localized hotspots were present. The study emphasizes the need for targeted monitoring and sustainable management practices to mitigate pollution and preserve the crucial freshwater environment of Nasser Lake. Full article

Surface texturing involves creating micro-channels, micro-dimples, micro-grooving, and other surface modifications. To do this, laser and micromachining are employed on the substrate surface in addition to other methods. The surface characteristics of the Arboblend V2 Nature biodegradable polymers with laser texturing, hexagonal and square patterns, and four and six passes are shown in this study. Regardless of the texture type, Arboblend V2 Nature’s hydrophilic surface (a contact angle of less than 90°) was demonstrated by the results of the wettability test. The underlying material’s wear behavior changed as a result of the LST surface modification. The COF values increased only after six passes with both textures. On the topographical side, Arboblend V2 Nature (square and hexagonal) shows a consistent X-axis expansion in the hexagonal geometry and a considerable amount of variability in the square geometry, especially at six passes, where the Y-axis (higher depths) is more compressed. According to the results, since textured surfaces are practicable, non-biodegradable polymers from a variety of industries can be substituted. Full article

Unmanned Surface Vehicles (USVs) play a critical role in maritime monitoring, environmental protection, and emergency response, necessitating accurate scene understanding in complex aquatic environments. Conventional semantic segmentation methods often fail to capture global context and lack physical boundary consistency, limiting real-world performance. This paper proposes USV-Seg, a unified segmentation framework integrating a vision-language model, the Segment Anything Model (SAM), DINOv2-based visual features, and a physically constrained refinement module. We design a task-specific <Describe> Token to enable fine-grained semantic reasoning of navigation scenes, considering USV-to-shore distance, landform complexity, and water surface texture. A mask selection algorithm based on multi-layer Intersection-over-Prediction (IoP) heads improves segmentation precision across sky, water, and obstacle regions. A boundary-aware correction module refines outputs using estimated sky-water and land-water boundaries, enhancing robustness and realism. Unlike prior works that simply apply vision-language or geometric post-processing in isolation, USV-Seg integrates structured scene reasoning and scene-aware boundary constraints into a unified and physically consistent framework. Experiments on a real-world USV dataset demonstrate that USV-Seg outperforms state-of-the-art methods, achieving 96.30% mIoU in challenging near-shore scenarios. Full article

Transition-metal oxides (TMOs) possess pronounced optoelectronic properties and are widely exploited in photovoltaics and photocatalysis. Here, we introduce a hot wire oxidation sublimation deposition (HWOSD) that directly converts elemental Mo and W into amorphous MoO_x and WO_x films on various substrates. Scanning electron microscopy and atomic force microscopy reveal uniform thickness and conformal coverage over textured and planar surfaces. X-ray photoelectron spectroscopy indicates high oxygen contents with stoichiometric ratios of 2.94 (MoO_x) and 2.91 (WO_x). Optical measurements show transmittances > 94% across 400–1200 nm, yielding optical band gaps of 1.86 eV (MoO_x) and 2.67 eV (WO_x). The conductivities of MoO_x and WO_x were 2.58 × 10⁻⁶ S cm⁻¹ and 5.14 × 10⁻⁷ S cm⁻¹ at room temperature, and the TMO/Si surface potential differences are 200 mV and 114 mV, respectively. Minority-carrier-lifetime measurements indicate that MoO_x films confer an additional passivation benefit to the i a-Si:H/c-Si/i a-Si:H stack. Annealing of MoO_x and WO_x realized their phase transition from an amorphous state to a polycrystalline state, with changes in their optical transmittance in the visible light region. Investigation of the photovoltaic performances of MoO_x and WO_x as HTLs deposited by HWOSD demonstrates their excellent electronic functionality in optoelectronics. These results establish HWOSD as a scalable, low-temperature method to fabricate high-quality TMO films and expand their potential in advanced optoelectronic devices. Full article

In this work, ethyl cellulose nanoparticles loaded with rosemary extract (RCL-NPs) were synthesized and utilized to reinforce high-density polyethylene (HDPE) packaging bags as a nanotechnological alternative for rabbit meat preservation. The synthesized RCL-NPs were characterized by DLS and for their stability. The analyzed variables of rabbit meat packaged samples included drained liquid, weight loss, color, pH, texture, and hardness. The total phenolic content (TPC) and antioxidant capacity of rosemary extract were also investigated. The results demonstrated that RCL-NPs were 117.30 nm in size with a negative surface charge (−24.59 mV) and low PDI (0.12). According to the Higuchi model, the release rate of RCL-NPs was sustained from 0 to 24 h. The encapsulation efficiency of the implemented synthesis route was 99.97%. The TPC of rosemary extract was 566.13 ± 1.72 mg GAE/L, whereas their antioxidant activity utilizing the DPPH and FRAP assays was 27.86 ± 0.32 mM Trolox/L and 0.31 mM Trolox/L, respectively. Contrary to control samples, rabbit meat samples conserved in HDPE packaging bags reinforced with RCL-NPs prevent drained liquid and weight loss, while preserving *L (60 ± 2.5–66.10 ± 2.0) and *b (10.67 ± 2.28–11.62 ± 2.39), pH (5.22 ± 0.05–5.80 ± 0.03), and texture (10.37 ± 0.82–0.70 ± 0.50). In the same regard, the developed material conserved the hardness of rabbit meat samples, exhibiting values that ranged from 27.79 ± 7.23 to 27.60 ± 3.05 N during the evaluated period (0–13 days). The retrieved data demonstrate the efficacy of RCL in preserving the quality of rabbit meat when integrated with additional food packaging materials. Full article

Natural materials present sustainable opportunities in architectural design, but often lack the aesthetic controllability associated with synthetic alternatives. This research explores the bio-aesthetic potential of mycelium-bound composites (MBCs) cultivated from Ganoderma Steyaertanum (Reishi mushroom), focusing on how external stimuli and surface treatments influence material expression. This investigation was carried out through interdisciplinary collaboration involving design, architecture, and material science. Two post-demolding surface treatment strategies were applied to MBC samples: ‘Delayed Growth‘ and ‘Accelerated Growth‘. These treatments were designed to assess the mycelium’s responsiveness in terms of colour and texture development. A controlled set of samples was analysed using scanning electron microscopy, Fourier-transform infrared spectroscopy, and hydrophobicity testing to evaluate changes in microstructure, chemical composition, and surface properties. The results demonstrate that mycelium exhibits a measurable capacity for aesthetic adaptation, with distinct variations in pigmentation and texture emerging under different treatment conditions. These findings highlight the potential for co-creative design processes with living materials and offer new insights into the integration of biological responsiveness in design practices. The study contributes to the advancement of sustainable material systems and expands the possibilities for bio-design through controlled interaction with bio-materials. Full article

Digital dentistry is undergoing rapid evolution, with three-dimensional imaging technologies increasingly integrated into routine clinical workflows. Originally developed for accurate dental arch reconstruction, modern intraoral scanners have demonstrated expanding versatility in capturing intraoral mucosal as well as perioral cutaneous structures. Concurrently, photogrammetry has emerged as a powerful method for full-face digital reconstruction, particularly valuable in orthodontic and prosthodontic treatment planning. These advances offer promising applications in forensic sciences, where high-resolution, three-dimensional documentation of anatomical details such as palatal rugae, lip prints, and bite marks can provide objective and enduring records for legal and investigative purposes. This study explores the forensic potential of two digital acquisition techniques by presenting two cadaveric cases of animal bite injuries. In the first case, an intraoral scanner (Dexis 3600) was used in an unconventional extraoral application to directly scan skin lesions. In the second case, photogrammetry was employed using a digital single-lens reflex (DSLR) camera and Agisoft Metashape, with standardized lighting and metric scale references to generate accurate 3D models. Both methods produced analyzable digital reconstructions suitable for forensic archiving. The intraoral scanner yielded dimensionally accurate models, with strong agreement with manual measurements, though limited by difficulties in capturing complex surface morphology. Photogrammetry, meanwhile, allowed for broader contextual reconstruction with high texture fidelity, albeit requiring more extensive processing and scale calibration. A notable advantage common to both techniques is the avoidance of physical contact and impression materials, which can compress and distort soft tissues, an especially relevant concern when documenting transient evidence like bite marks. These results suggest that both technologies, despite their different origins and operational workflows, can contribute meaningfully to forensic documentation of bite-related injuries. While constrained by the exploratory nature and small sample size of this study, the findings support the viability of digitized, non-destructive evidence preservation. Future perspectives may include the integration of artificial intelligence to assist with morphological matching and the establishment of digital forensic databases for pattern comparison and expert review. Full article