Search Results (4,277)

Coastal wetland vegetation exhibits pronounced spectral mixing, complex mosaic spatial patterns, and small target sizes, posing considerable challenges for fine-grained classification in high-resolution UAV imagery. At present, remote sensing classification of ground objects based on deep learning mainly relies on spectral and structural features, while the frequency domain features of ground objects are not fully considered. To address these issues, this study proposes a vegetation classification model that integrates spatial-domain and frequency-domain features. The model enhances global contextual modeling through a large-kernel convolution branch, while a frequency-domain interaction branch separates and fuses low-frequency structural information with high-frequency details. In addition, a shallow auxiliary supervision module is introduced to improve local detail learning and stabilize training. With a compact parameter scale suitable for real-world deployment, the proposed framework effectively adapts to high-resolution remote sensing scenarios. Experiments on typical coastal wetland vegetation including Reeds, Spartina alterniflora, and Suaeda salsa demonstrate that the proposed method consistently outperforms representative segmentation models such as UNet, DeepLabV3, TransUNet, SegFormer, D-LinkNet, and MCCA across multiple metrics including Accuracy, Recall, F1 Score, and mIoU. Overall, the results show that the proposed model effectively addresses the challenges of subtle spectral differences, pervasive species mixture, and intricate structural details, offering a robust and efficient solution for UAV-based wetland vegetation mapping and ecological monitoring. Full article

Transition metal (TM)-doped zinc oxide (ZnO) and zirconium dioxide (ZrO₂) nanocrystals exhibit complex correlations between crystal structure, defect chemistry, vibrational properties, and magnetic behavior that are strongly governed by synthesis route and dopant incorporation mechanisms. This review critically summarizes recent progress on Fe-, Mn-, and Co-doped ZnO and ZrO₂ nanocrystals synthesized by wet chemical, hydrothermal, and microwave-assisted hydrothermal methods, with emphasis on synthesis-driven phase evolution and apparent solubility limits. ZnO and ZrO₂ are treated as complementary host lattices: ZnO is a semiconducting, piezoelectric oxide with narrow solubility limits for most 3d dopants, while ZrO₂ is a dielectric, polymorphic oxide in which transition metal doping may stabilize tetragonal or cubic phases. Structural and microstructural studies using X-ray diffraction, electron microscopy, Raman spectroscopy, and Mössbauer spectroscopy demonstrate that at low dopant concentrations, TM ions may be partially incorporated into the host lattice, giving rise to diluted or defect-mediated magnetic behavior. When solubility limits are exceeded, nanoscopic secondary oxide phases emerge, leading to superparamagnetic, ferrimagnetic, or spin-glass-like responses. Magnetic measurements, including DC magnetization and AC susceptibility, reveal a continuous evolution from paramagnetism in lightly doped samples to dynamic magnetic states characteristic of nanoscale magnetic entities. Vibrational spectroscopy highlights phonon confinement, surface optical phonons, and disorder-activated modes that sensitively reflect nanocrystal size, lattice strain, and defect populations, and often correlate with magnetic dynamics. Rather than classifying these materials as diluted magnetic semiconductors, this review adopts a synthesis-driven and correlation-based framework that links dopant incorporation, local structural disorder, vibrational fingerprints, and magnetic response. By emphasizing multi-technique characterization strategies required to distinguish intrinsic from extrinsic magnetic contributions, this review provides practical guidelines for interpreting magnetism in TM-doped oxide nanocrystals and outlines implications for applications in photocatalysis, sensing, biomedicine, and electromagnetic interference (EMI) shielding. Full article

Small-object detection in UAV remote sensing faces common challenges such as tiny target size, blurred features, and severe background interference. Furthermore, single imaging modalities exhibit limited representation capability in complex environments. To address these issues, this paper proposes CTU-YOLO, a UAV-based small-object detection algorithm built upon cross-modal feature fusion and lightweight upsampling. The algorithm incorporates a dynamic and adaptive cross-modal feature fusion (DCFF) module, which achieves efficient feature alignment and fusion by combining frequency-domain analysis with convolutional operations. Additionally, a lightweight upsampling module (LUS) is introduced, integrating dynamic sampling and depthwise separable convolution to enhance the recovery of fine details for small objects. Experiments on the DroneVehicle and LLVIP datasets demonstrate that CTU-YOLO achieves 73.9% mAP on DroneVehicle and 96.9% AP on LLVIP, outperforming existing mainstream methods. Meanwhile, the model possesses only 4.2 MB parameters and 13.8 GFLOPs computational cost, with inference speeds reaching 129.9 FPS on DroneVehicle and 135.1 FPS on LLVIP. This exhibits an excellent lightweight design and real-time performance while maintaining high accuracy. Ablation studies confirm that both the DCFF and LUS modules contribute significantly to performance gains. Visualization analysis further indicates that the proposed method can accurately preserve the structure of small objects even under nighttime, low-light, and multi-scale background conditions, demonstrating strong robustness. Full article

Biomedical antennas are essential components in modern healthcare systems, supporting wireless communication, physiological monitoring, diagnostic imaging, and therapeutic energy delivery. Their performance is strongly influenced by proximity to the human body, creating challenges such as impedance detuning, signal absorption, and size constraints that motivate new materials and fabrication approaches. This work reviews recent advances enabling next-generation wearable and implantable antennas, with emphasis on printed electronics, additive manufacturing, flexible hybrid integration, and metamaterial design. Methods discussed include 3D printing and inkjet, aerosol jet, and screen printing for fabricating conductive traces on textiles, elastomers, and biodegradable substrates, as well as multilayer Flexible Hybrid Electronics that co-integrate sensing, power management, and RF components into thin, body-conforming assemblies. Key results highlight how metamaterial and metasurface concepts provide artificial control over dispersion, radiation, and near-field interactions, enabling antenna miniaturization, enhanced gain and focusing, and improved isolation from lossy biological tissue. These approaches reduce SAR, stabilize impedance under deformation, and support more efficient communication and energy transfer. The review concludes that the convergence of novel materials, engineered electromagnetic structures, and AI-assisted optimization is enabling biomedical antennas that are compact, stretchable, personalized, and highly adaptive, supporting future developments in unobtrusive monitoring, wireless implants, point-of-care diagnostics, and continuous clinical interfacing. Full article

The present paper reports the preparation of a nanocomposite thin film consisting of calcium itaconate and graphene oxide (GO). The composite is a black powder consisting of individual shiny prismatic crystals at varying degrees of maturity. The crystal size distribution is quite narrow: from 3.6 to 6.2 μm in length and from 0.7 to 1.1 μm in width. Thin-film-based acetone sensor made of a nanocomposite was fabricated by spin coating of calcium itaconate–GO nanoparticles on glass plates. The thin-film acetone sensor was characterized using FTIR, XRD, SEM, TEM, and the low-temperature nitrogen sorption–desorption method. The sensor response time is 7.66 ± 0.07 s (s_r = 0.92%), and the relaxation time when blowing the surface with clean air or inert gas (nitrogen, argon) is 9.26 ± 0.12 s (s_r = 1.28%). The sensing mechanism of the sensor for detecting acetone at room temperature was also is proposed based on phenomenological understanding due to the absence of direct electronic/charge-transport evidence. Full article

Advanced ceramics are known for their lightweight, high-temperature resistance, corrosion resistance, and biocompatibility. They are crucial in energy conversion, environmental protection, and aerospace fields. This review highlights the recent advancements in ceramic matrix composites, high-entropy ceramics, and polymer-derived ceramics, alongside various fabrication techniques such as three-dimensional printing, advanced sintering, and electric-field-assisted joining. Beyond the fabrication process, we emphasize how different processing methods impact microstructure, transport properties, and performance metrics relevant to catalysis. Additive manufacturing routes, such as direct ink writing, digital light processing, and binder jetting, are discussed and normalized based on factors such as relative density, grain size, pore architecture, and shrinkage. Cold and flash sintering methods are also examined, focusing on grain-boundary chemistry, dopant compatibility, and scalability for catalyst supports. Additionally, polymer-derived ceramics (SiOC, SiCN, SiBCN) are reviewed in terms of their catalytic performance in hydrogen evolution reaction, oxygen evolution reaction, oxygen reduction reaction, and CO₂ reduction reaction. CeO₂-ZrO₂ composites are particularly highlighted for their use in environmental catalysis and high-temperature gas sensing. Furthermore, insights on the future industrialization, cross-disciplinary integration, and performance improvements in catalytic applications are provided. Full article

Biofouling arises from non-specific adsorption of several components present in complex biofluids, such as full blood, on the surface of electrochemical biosensors, with a resulting loss of functionality. Most biomarkers of clinical relevance are present in biological fluids at extremely low concentrations, making antibiofouling strategies necessary in electrochemical biosensing. Here, we demonstrate the effect of a highly porous gold (h-PG) film electrodeposited on a gold screen-printed electrode (AuSPE) using a self-templated method via hydrogen bubbling as an antibiofouling strategy in electrochemical biosensor development following exposure of the electrode to bovine serum albumin (BSA) at two different concentrations (2 and 32 mg/mL). The h-PG film has a high electrochemically active surface area, 88 times higher than the AuSPE electrode, with a pore size ranging from 2 to 50 μm. A rapid decrease in the Faradaic current was observed with the unmodified AuSPE, attesting to the strong biofouling effect of BSA at both concentrations tested. Notably, the h-PG-modified electrode showed an initial peak current decline, more evident at a higher BSA concentration, followed by rapid electrode regeneration when the electrode was left idle in the biofouling solution. Similar results were obtained for unmodified and modified electrodes in real serum and plasma samples. The regeneration process, explained in terms of balance between h-PG pore size and protein size, the nanoscale architecture of the h-PG electrodes, and repulsive electrostatic forces, indicates the huge potential of the h-PG film for use in biomedical electrochemical sensing. Full article

This pilot study investigated multimodal physiological monitoring using minimally invasive and wearable sensors across two experimental settings. Experiment 1 involved five healthy adults (1 female) who simultaneously wore an interstitial fluid glucose (ISFG) sensor and a ring-type wearable device during sleep (00:00–06:00). Time-series analyses revealed that ISFG levels decreased during sleep in four of the five participants. ISFG values were significantly lower in the latter half of the sleep period compared with the first half (0–3 h vs. 3–6 h, p = 0.01, d = 2.056). Four participants also exhibited a mild reduction in SpO₂ between 03:00–04:00. These results suggest that nocturnal ISFG decline may be associated with subtle oxygen-saturation dynamics. Experiment 2 examined whether wearable sensors can detect physiological changes across meal-related phases. Nine male participants were monitored for heart rate (HR) and skin temperature during three periods: pre-meal (Phase 1: 09:00–09:30), during meal consumption (Phase 2: 12:30–13:00), and post-meal (Phase 3: 13:00–13:30). A paired comparison demonstrated a significant difference in median HR between Phase 1 and Phase 2 (p = 0.029, d = 0.812), indicating a large effect size. In contrast, HR–temperature correlation was weak and not statistically significant (Pearson r = 0.067, p = 0.298). Together, these findings demonstrate that multimodal wearable sensing can capture both nocturnal glucose fluctuations and meal-induced cardiovascular changes. This integrative approach may support real-time physiological risk assessment and future development of remote healthcare applications. Full article

Accurate characterization of seafloor sediment properties is critical for marine engineering design, resource assessment, and environmental management. Sidescan sonar offers efficient wide-area mapping capabilities, yet establishing robust quantitative relationships between acoustic backscatter intensity and sediment texture remains challenging, particularly in heterogeneous coastal environments. This study investigates the correlation between sidescan sonar backscatter intensity and sediment grain size parameters in waters southwest of Hainan Island, China. High-resolution acoustic data (450 kHz) were acquired alongside surface sediment samples from 18 stations spanning diverse sediment types. Backscatter intensity, represented by grayscale values, was systematically compared with grain size distributions and individual size fractions. Results reveal that mean grain size shows no meaningful correlation with backscatter intensity; however, fine sand fraction content (0.075–0.25 mm) exhibits a strong negative linear relationship (R² = 0.87 under optimal conditions). Distribution-level analysis demonstrates that backscatter variability mirrors sediment textural complexity, with coarse sediments producing broad, elevated intensity distributions and fine sediments yielding narrow, suppressed distributions. Inter-survey variability highlights the sensitivity of absolute intensity values to environmental conditions during acquisition. Spatial distribution analysis reveals that sediment grain size follows a systematic NE-SW gradient controlled by hydrodynamic energy, with notable local anomalies controlled by reef structures (producing coarse bioclastic sediment) and topographic sheltering (maintaining fine-grained deposits in shallow areas). These findings provide a quantitative basis for fraction-specific acoustic classification approaches while emphasizing the importance of multi-scale analysis incorporating both regional hydrodynamic trends and local morphological controls. The established relationship between fine sand abundance and acoustic response enables semi-quantitative sediment prediction from remotely sensed data, supporting improved seafloor mapping protocols for offshore infrastructure siting, aggregate resource evaluation, and coastal zone management in morphologically complex environments. Full article

Direction of arrival (DOA) estimation is a fundamental problem in array signal processing, with extensive applications in radar, communications, sonar, and other fields. Traditional DOA estimation methods, such as MUSIC and ESPRIT, rely on eigenvalue decomposition or spectral peak search, which suffer from high computational complexity and performance degradation under conditions of low signal-to-noise ratio (SNR), coherent signals, and array imperfections. Cylindrical arrays offer unique advantages for omnidirectional sensing due to their circular structure and three-dimensional coverage capability; however, their nonlinear array manifold increases the difficulty of estimation. This paper proposes a circular-attention residual network (CA-ResNet) for DOA estimation using uniform cylindrical arrays. The proposed approach achieves high accuracy and robust angle estimation through phase difference feature extraction, a multi-scale residual network, an attention mechanism, and a joint output module. Simulation results demonstrate that the proposed CA-ResNet method delivers superior performance under challenging scenarios, including low SNR (−10 dB), a small number of snapshots (L = 5), and multiple sources (1 to 4 signal sources). The corresponding root mean square errors (RMSE) are 0.21°, 0.45°, and below 1.5°, respectively, significantly outperforming traditional methods like MUSIC and ESPRIT, as well as existing deep learning models (e.g., ResNet, CNN, MLP). Furthermore, the algorithm exhibits low computational complexity and a small parameter size, highlighting its strong potential for practical engineering applications and robustness. Full article

A promising application of smart materials based on natural polymers is the potential to solve problems related to hemostasis in cases of severe bleeding caused by injury or surgery. This can be a life-threatening situation. Cellulose and its modified derivatives represent one of the most promising sources for creating effective hemostatic systems, as well as for various sensing applications related to disease detection, infection diagnosis, chronic condition monitoring, and blood analysis. The aim of this review was to identify key criteria for the efficiency of cellulose-based gels with hemostatic activity. Experimental studies aimed at evaluating new hemostatic devices were analyzed based on international sources using the PRISMA methodology. A total of 111 publications were identified. Following the identification and screening stages, 20 articles were selected for the final qualitative synthesis. The analyzed publications include experimental studies focused on the development and analysis of highly porous cellulose-based scaffolds in the form of aerogels and cryogels. The type and origin of cellulose, as well as the influence of additional components and synthesis conditions on gel formation, were investigated. Three major groups of key criteria that should be considered when developing new cellulose-based highly porous scaffolds with hemostatic functionality were identified: (I) physicochemical and mechanical properties (pore size distribution, compressive strength, and presence of functional groups); (II) in vitro tests (blood clotting index, red blood cell adhesion rate, hemolysis, cytocompatibility, and antibacterial activity); (III) in vivo hemostatic efficiency (hemostasis time and blood loss) in compliance with the 3Rs policy (replacement, reduction, refinement). The prospects for the development of highly porous cellulose-based scaffolds are not only focused on their hemostatic properties, but also on the development of smart platforms. Full article

This study prepared oregano essential oil-loaded liposomes (OEO-Lip) and systematically evaluated their physicochemical properties, stability, and antioxidant/antibacterial activities, along with the underlying mechanisms. Characterization revealed OEO-Lip exhibited a unilamellar vesicle structure with a particle size of approximately 190 nm, uniform dispersion (PDI = 0.183), a high zeta potential (−39.8 mV), and an encapsulation efficiency of 77.52%. Analyses by FT-IR, XRD, and DSC confirmed the successful encapsulation of OEO within the liposomes. Hydrogen bonding interactions with phospholipid components promoted the formation of a more ordered crystalline structure, thereby enhancing thermal stability. Storage stability tests demonstrated that OEO-Lip stored at 4 °C for 30 days exhibited significantly superior physicochemical properties compared to samples stored at 25 °C. Furthermore, liposomal encapsulation effectively preserved the antioxidant activity of OEO. Antimicrobial studies revealed that OEO-Lip exerted stronger and more sustained inhibitory effects against Escherichia coli and Staphylococcus aureus than free OEO, primarily by disrupting bacterial membrane integrity and inducing the leakage of ions and intracellular contents. Transcriptomic analysis further indicated that OEO-Lip exerts synergistic antibacterial effects by downregulating genes associated with phospholipid synthesis and nutrient transport while concurrently interfering with multiple pathways, including quorum sensing and energy metabolism. Release experiments indicated that OEO-Lip displays both burst and sustained release characteristics. In summary, OEO-Lip serves as an efficient delivery system that significantly enhances the stability and antibacterial efficacy of OEO, demonstrating considerable potential for application in food preservation. Full article

Background and Objectives: Meniscus injuries, particularly Grade I and II, are common knee injuries that can affect pain, joint function and quality of life, but the effectiveness of non-invasive treatments like Kinesiology taping (KT) in this population remains limited. This pilot randomized controlled trial aimed to explore the short-term effects of KT on pain, fear of movement, muscle strength, proprioceptive force sense, joint range of motion, joint position sense and quality of life in individuals with Grade I/II meniscus injuries. Materials and Methods: 26 participants diagnosed with Grade I-II meniscus injury were randomly assigned to two groups: the experimental group was applied ‘Y shaped’ kinesiology taping on quadriceps femoris muscle, based on facilitation technique with 25–50% tension. The control (placebo) group was applied a tape without tension, perpendicular to the quadriceps femoris muscle. Outcomes were evaluated before and 48–72 h after taping. Results: Between-group analysis demonstrated a significant improvement in joint position sense at 60° flexion with eyes closed in KT group compared with placebo (p = 0.002). Additionally, the KT group showed significantly greater improvements in the physical function (p = 0.006) and energy (p = 0.013) subdomains of the SF-36 quality of life scale. No significant between-group differences were observed for pain, fear of movement, muscle strength, proprioceptive force sense, or joint range of motion. Conclusions: In this pilot study, KT showed acute benefits in proprioception and quality of life in grade I-II meniscus injuries, but no advantage over placebo taping for pain, fear of movement, joint range of motion or muscle strength. Given the exploratory nature and limited sample size, these findings should be interpreted cautiously. Larger trials should confirm these results and determine the role of KT within multimodal rehabilitation programs. Full article

This study presents the development of a smart packaging material utilizing garlic-derived nitrogen-doped carbon dots (CDs) integrated into a whey protein–starch (WP-S) emulsion. The research aimed to create a real-time, non-invasive biosensor capable of detecting microbial spoilage. The synthesized CDs demonstrated strong pH-sensitive photoluminescence, exhibiting distinct changes in CIE coordinates and fluorescence intensity in response to varying pH values. The WP-S-CDs emulsion was tested against E. coli, S. aureus, and C. albicans. The results showed that the composite film provided a clear colorimetric shift and fluorescence quenching, both of which are directly correlated with microbial metabolic activity. The physical and electronic properties of the composite were investigated to understand the sensing mechanism. Scanning electron microscopy (SEM) of the dried film revealed that the WP-S-CDs system formed a more porous structure with larger pore sizes (3.63–8.18 µm) compared to the control WP-S film (1.62–6.52 µm), which facilitated the rapid diffusion of microbial metabolites. Additionally, density functional theory (DFT) calculations demonstrated that the incorporation of CDs significantly enhanced the composite’s electronic properties by reducing its band gap and increasing its dipole moment, thereby heightening its reactivity and sensitivity to spoilage byproducts. In a practical application on apples, the WP-S-CDs coating produced a visible red spot, confirming its function as a dynamic sensor. The material also showed a dual-action antimicrobial effect, synergistically inhibiting C. albicans while exhibiting an antagonistic effect against bacteria. These findings validate the potential of the WP-S-CDs emulsion as a powerful, multi-faceted intelligent packaging system for food quality monitoring. Full article

Traditional vibration-based methods for bearing fault diagnosis, while prevalent, often require contact measurement, and sound signal is a broadband signal relative to the vibration signal. To overcome these limitations, this paper explores the advantages of acoustic signals, non-contact sensing, and rich broadband information and proposes a fault diagnosis framework based on acoustic features and deep learning. The core of our method is a CNN–attention mechanism–LSTM model, specifically designed to process one-dimensional sequential features: the 1D-CNN extracts local features from Mel frequency cepstral coefficient (MFCC) features, the attention mechanism (selecting ECA as the optimal solution) selectively enhances features, and the LSTM captures temporal dependencies, collectively enabling effective classification of fault types. Furthermore, to enhance model efficiency, a ReliefF-based feature selection algorithm is employed to identify and retain only the most discriminative acoustic features. Experimental results demonstrate that the proposed method achieves an average diagnostic accuracy of 99.90% in distinguishing normal, inner-ring, outer-ring, and mixed-defect bearings. Notably, results show that after using the feature selection algorithm, the number of parameters and the estimated total size are significantly reduced while ensuring that the accuracy remains basically unchanged. This work validates the effectiveness of non-contact solutions for bearing fault diagnosis using acoustic features and has enormous potential for industrial applications. Full article