Search Results (1,223)

Although numerous studies have examined the spatial patterns of traditional villages and their driving factors, limited attention has been devoted to the transformation of tourism. This study focused on traditional villages in Shaanxi Province, employing geodetector and grounded theory methods to analyze their spatial distribution characteristics and influencing factors. First, most traditional villages have not developed tourism. Only 11.98% reached the relatively mature tourism stage. Second, the spatial distribution of mature traditional tourism villages is scattered and primarily clustered in Liuba County, Mizhi County, and Jia County. Third, the factors influencing spatial distribution characteristics include resource endowment, transportation accessibility, and regional economic conditions. Among these factors, the level of traditional villages, village heritage values, and the local tourism environment show the strongest explanatory power. These findings can help enhance cultural resilience, promote economic transformation and upgrading, and support the sustainable development of traditional villages. Full article

In recent years, deep learning methods have made breakthroughs in the field of rotating equipment fault diagnosis, thanks to their powerful data analysis capabilities. However, the vibration signals usually incorporate fault features and background noise, and these features may be scattered over multiple frequency levels, which increases the complexity of extracting important information from them. To address this problem, this paper proposes a Masked and Cascaded Multi-Branch Attention Network (MCMBAN), which combines the Noise Mask Filter Block (NMFB) with the Multi-Branch Cascade Attention Block (MBCAB), and significantly improves the noise immunity of the fault diagnostic model and the efficiency of fault feature extraction. NMFB novelly combines a wide convolutional layer and a top k neighbor self-attention masking mechanism, so as to efficiently filter unnecessary high-frequency noise in the vibration signal. On the other hand, MBCAB strengthens the interaction between different layers by cascading the convolutional layers of different scales, thus improving the recognition of periodic fault signals and greatly enhancing the diagnosis accuracy of the model when processing complex signals. Finally, the time–frequency analysis technique is employed to explore the internal mechanisms of the model in depth, aiming to validate the effectiveness of NMFB and MBCAB in fault feature recognition and to improve the feature interpretability of the proposed modes in fault diagnosis applications. We validate the superior performance of the network model in dealing with high-noise backgrounds by testing it on a standard bearing dataset from Case Western Reserve University and a self-constructed composite bearing fault dataset, and the experimental results show that its performance exceeded six of the top current fault diagnosis techniques. Full article

Skin autofluorescence (SAF) detection technology represents a noninvasive, convenient, and cost-effective optical detection approach. It can be employed for the differentiation of various diseases, including metabolic diseases and dermatitis, as well as for monitoring the treatment efficacy. Distinct from diffuse reflection signals, the autofluorescence signals of biological tissues are relatively weak, making them challenging to be captured by photoelectric sensors. Moreover, the absorption and scattering properties of biological tissues lead to a substantial attenuation of the autofluorescence of biological tissues, thereby worsening the signal-to-noise ratio. This has also imposed limitations on the development and application of compact-sized autofluorescence detection systems. In this study, a compact LED light source and a CMOS sensor were utilized as the excitation and detection devices for skin tissue autofluorescence, respectively, to construct a mobile and wireless skin tissue autofluorescence detection system. This system can achieve the detection of skin tissue autofluorescence with a high signal-to-noise ratio under the drive of a simple power supply and a single-chip microcontroller. The detection time is less than 0.1 s. To enhance the stability of the system, a pressure sensor was incorporated. This pressure sensor can monitor the pressure exerted by the skin on the detection system during the testing process, thereby improving the accuracy of the detection signal. The developed system features a compact structure, user-friendliness, and a favorable signal-to-noise ratio of the detection signal, holding significant application potential in future assessments of skin aging and the risk of diabetic complications. Full article

The detection of trace chemicals at low and ultra-low concentrations is critical for applications in environmental monitoring, medical diagnostics, food safety and other fields. Conventional detection techniques often lack the required sensitivity, specificity, or cost-effectiveness, making real-time, in situ analysis challenging. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical tool, offering improved sensitivity through the enhancement of Raman scattering by plasmonic nanostructures. While noble metals such as Ag and Au are currently the reference choices for SERS substrates, fabrication methods should balance enhancement efficiency, reproducibility and scalability. In this study, we propose a novel approach for SERS substrate fabrication using reactive Aerosol Jet Printing (r-AJP) as an innovative additive manufacturing technique. The r-AJP process enables in-flight Ag seed reduction and nucleation of Ag nanoparticles (NPs) by mixing silver nitrate and ascorbic acid aerosols before deposition, as suggested by computational fluid dynamics (CFD) simulations. The resulting coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses, revealing the formation of nanoporous crystalline Ag agglomerates partially covered by residual matter. The as-prepared SERS substrates exhibited remarkable SERS activity, demonstrating a high enhancement factor (10⁶) for rhodamine (R6G) detection. Our findings highlight the potential of r-AJP as a scalable and cost-effective fabrication strategy for next-generation SERS sensors, paving the way for the development of a new additive manufacturing tool for noble metal material deposition. Full article

The adoption of technological innovations in the maritime industry is of interest to business, policy, and academic communities. In the last group, this interest has translated into the publication of a large but scattered literature, making it difficult to compare findings and identify the dynamics, structures, and patterns that might inform future research. A comprehensive review of past research on this topic might help achieve this. To date, no such review has been carried out, which is an important gap in the literature that this paper contributes to bridging. Two bibliometric review techniques—co-citation analysis of cited references and bibliographic coupling of documents—are applied to 171 journal articles published between 1999 and February 2025 to answer the following questions: 1. What is the knowledge base of this literature? 2. What are the recent research trends (research fronts) in this literature? The analysis reveals that research on “shore power” dominates both the knowledge base and research fronts. Other key research themes centre on “autonomous shipping”, “blockchain”, and “alternative fuels”. Based on these results, implications for future research are drawn. Full article

AlGaN-based high-electron-mobility transistors are critical for next-generation power electronics and radio-frequency applications, yet achieving stable enhancement-mode operation with a high threshold voltage remains a key challenge. In this work, we designed p-AlGaN superlattices with different structures and performed energy band structure simulations using the device simulation software Silvaco. The results demonstrate that thin barrier structures lead to reduced acceptor incorporation, thereby decreasing the number of ionized acceptors, while facilitating vertical hole transport. Superlattice samples with varying periodic thicknesses were grown via metal-organic chemical vapor deposition, and their crystalline quality and electrical properties were characterized. The findings reveal that although gradient-thickness barriers contribute to enhancing hole concentration, the presence of thick barrier layers restricts hole tunneling and induces stronger scattering, ultimately increasing resistivity. In addition, we simulated the structure of the enhancement-mode HEMT with p-AlGaN as the under-gate material. Analysis of its energy band structure and channel carrier concentration indicates that adopting p-AlGaN superlattices as the under-gate material facilitates achieving a higher threshold voltage in enhancement-mode HEMT devices, which is crucial for improving device reliability and reducing power loss in practical applications such as electric vehicles. Full article

To enable accurate evaluation of satellite laser communication terminals under solar outage interference, this paper presents the design and implementation of a solar radiation simulation system targeting the 1540–1560 nm communication band. The system reconstructs co-propagating interference conditions through standardized and continuously tunable output, based on high irradiance and spectral uniformity. A compound beam homogenization structure—combining a multimode fiber and an apodizator—achieves 85.8% far-field uniformity over a 200 mm aperture. A power–spectrum co-optimization strategy is introduced for filter design, achieving a spectral matching degree of 78%. The system supports a tunable output from 2.5 to 130 mW with a 50× dynamic range and maintains power control accuracy within ±0.9%. To suppress internal background interference, a BRDF-based optical scattering model is established to trace primary and secondary stray light paths. Simulation results show that by maintaining the surface roughness of key mirrors below 2 nm and incorporating a U-shaped reflective light trap, stray light levels can be reduced to 5.13 × 10⁻¹² W, ensuring stable detection of a 10⁻¹⁰ W signal at a 10:1 signal-to-background ratio. Experimental validation confirms that the system can faithfully reproduce solar outage conditions within a ±3° field of view, achieving consistent performance in spectrum shaping, irradiance uniformity, and background suppression. The proposed platform provides a standardized and practical testbed for ground-based anti-interference assessment of optical communication terminals. Full article

Exosomes are nanoscale extracellular vesicles (EVs) that carry biomolecular signatures reflective of their parent cells, making them powerful tools for non-invasive diagnostics and therapeutic monitoring. Despite their potential, clinical application is hindered by challenges such as low abundance, heterogeneity, and the complexity of biological samples. To address these limitations, plasmonic biosensing technologies—particularly propagating surface plasmon resonance (PSPR), localized surface plasmon resonance (LSPR), and surface-enhanced Raman scattering (SERS)—have been developed to enable label-free, highly sensitive, and multiplexed detection at the single-vesicle level. This review outlines recent advancements in nanoplasmonic platforms for exosome detection and profiling, emphasizing innovations in nanostructure engineering, microfluidic integration, and signal enhancement. Representative applications in oncology, neurology, and immunology are discussed, along with the increasingly critical role of artificial intelligence (AI) in spectral interpretation and diagnostic classification. Key technical and translational challenges—such as assay standardization, substrate reproducibility, and clinical validation—are also addressed. Overall, this review highlights the synergy between exosome biology and plasmonic nanotechnology, offering a path toward real-time, precision diagnostics via sub-femtomolar detection of exosomal miRNAs through next-generation biosensing strategies. Full article

Terahertz (THz) wireless communications can support ultra-high data rates and secure wireless links with miniaturized devices for unmanned aerial vehicle (UAV) communications. In this paper, a three-dimensional (3D) non-stationary geometry-based stochastic channel model (GSCM) is proposed for multiple-input multiple-output (MIMO) communication links between the UAVs in the THz band. The proposed channel model considers not only the 3D scattering and reflection scenarios (i.e., reflection and scattering fading) but also the atmospheric molecule absorption attenuation, arbitrary 3D trajectory, and antenna arrays of both terminals. In addition, the statistical properties of the proposed GSCM (i.e., the time auto-correlation function (T-ACF), space cross-correlation function (S-CCF), and Doppler power spectrum density (DPSD)) are derived and analyzed under several important UAV-related parameters and different carrier frequencies, including millimeter wave (mmWave) and THz bands. Finally, the good agreement between the simulated results and corresponding theoretical ones demonstrates the correctness of the proposed GSCM, and some useful observations are provided for the system design and performance evaluation of UAV-based air-to-air (A2A) THz-MIMO wireless communications. Full article

The high resolution of the Synthetic Aperture Radar (SAR) imagery, in addition to its capability to see through clouds and rain, makes it a crucial remote sensing technique. However, SAR images are very sensitive to radar parameters, the observation geometry and the scene’s characteristics. Moreover, for a complex scene of interest with targets located on a rough soil, a composite scattering between the target and the surface occurs and creates distortions on the SAR image. These characteristics can make the SAR images difficult to analyse and process. To better understand the complex EM phenomena and their signature in the SAR image, we propose a methodology to generate raw SAR signals and SAR images for scenes of interest with a target located on a rough surface. With this prospect, the entire radar acquisition chain is considered: the sensor parameters, the atmospheric attenuation, the interactions between the incident EM field and the scene, and the SAR image formation. Simulation results are presented for a rough dielectric soil and a canonical target considered as a Perfect Electric Conductor (PEC). These results highlight the importance of the composite scattering signature between the target and the soil. Its power is 21 dB higher that that of the target for the target–soil configuration considered. Finally, these simulations allow for the retrieval of characteristics present in actual SAR images and show the potential of the presented model in investigating EM phenomena and their signatures in SAR images. Full article

The coherency matrix serves as a valuable tool for explaining the intricate details of various terrain targets. However, a significant challenge arises when analyzing ground targets with similar scattering characteristics in polarimetric synthetic aperture radar (PolSAR) target decomposition. Specifically, the overestimation of volume scattering (OVS) introduces ambiguity in characterizing the scattering mechanism and uncertainty in deciphering the scattering mechanism of large oriented built-up areas. To address these challenges, based on the generalized five-component decomposition (G5U), we propose a hierarchical extension of the G5U method, termed ExG5U, which incorporates orientation and phase angles into the matrix rotation process. The resulting transformed coherency matrices are then subjected to a five-component decomposition framework, enhanced with four refined volume scattering models. Additionally, we have reformulated the branch conditions to facilitate more precise interpretations of scattering mechanisms. To validate the efficacy of the proposed method, we have conducted comprehensive evaluations using diverse PolSAR datasets from Gaofen-3, Radarsat-2, and ESAR, covering varying data acquisition timelines, sites, and frequency bands. The findings indicate that the ExG5U method proficiently captures the scattering characteristics of ambiguous regions and shows promising potential in mitigating OVS, ultimately facilitating a more accurate portrayal of scattering mechanisms of various terrain types. Full article

As a promising n-type semiconductor thermoelectric material, ZnO has great potential in the high-temperature working temperature range due to its advantages of abundant sources, low cost, high thermal stability, and good chemical stability, as well as being pollution-free. Sr-doped ZnO-based thermoelectric materials were prepared using the methods of room-temperature powder synthesis and high-temperature block synthesis. The phase composition, crystal structure, and thermoelectric performances of ZnO samples with different Sr doping levels were analyzed using XRD, material simulation software and thermoelectric testing devices, and the optimal doping concentrations were obtained. The results show that Sr doping could cause the Zn-O bond to become shorter; in addition, the hybridization between Zn and O atoms would become stronger, and the Sr atom would modify the density of states near the Fermi level, which could significantly increase the carrier concentration, electrical conductivity, and corresponding power factor. Sr doping could cause lattice distortion, enhance the phonon scattering effect, and decrease the lattice thermal conductivity and thermal conductivity. Sr doping can achieve the effect of improving electrical transport performance and decreasing thermal transport performance. The ZT value increased to ~0.418 at 873 K, which is ~4.2 times the highest ZT of the undoped ZnO sample. The Vickers hardness was increased to ~351.1 HV, which is 45% higher than the pristine ZnO. Full article

Microgrids have drawn attention due to their helpfulness in the development of renewable energy. It is necessary to make an optimal power dispatch scheme for each micro-source in a microgrid in order to make the best use of fluctuating and unpredictable renewable energy. However, the computational time of solving the optimal dispatch problem increases greatly when the grid’s structure is more complex. An improved parallel differential evolution (PDE) approach based on a message-passing interface (MPI) is proposed, aiming at the solution of the optimal dispatch problem of a microgrid (MG), reducing the consumed time effectively but not destroying the quality of the obtained solution. In the new approach, the main population of the parallel algorithm is divided into several small populations, and each performs the original operators of a differential evolution algorithm, i.e., mutation, crossover, and selection, in different processes concurrently. The gather and scatter operations are employed after several iterations to enhance population diversity. Some improvements on mutation, adaptive parameters, and the introduction of migration operation are also proposed in the approach. Two test systems are employed to verify and evaluate the proposed approach, and the comparisons with traditional differential evolution are also reported. The results show that the proposed PDE algorithm can reduce the consumed time on the premise of obtaining no worse solutions. Full article

This study investigates the influence of chromatic dispersion on the performance of Brillouin optical time-domain analysis (BOTDA) sensors, particularly under high-pump-power conditions, where nonlinear effects become significant. By incorporating dispersion terms into the coupled amplitude equations of stimulated Brillouin scattering (SBS), we theoretically analyzed the dispersion-induced pulse broadening effect and its impact on the Brillouin gain spectrum (BGS). Numerical simulations revealed that dispersion leads to a moderate broadening of pump pulses, resulting in slight changes to BGS characteristics, including increased peak power and reduced linewidth. To explore the interplay between dispersion and nonlinearity, we built a gain-based BOTDA experimental system and tested two types of fibers, namely standard single-mode fiber (SMF) with anomalous dispersion and dispersion-compensating fiber (DCF) with normal dispersion. Experimental results show that SMF is more prone to modulation instability (MI), which significantly degrades the signal-to-noise ratio (SNR) of the BGS. In contrast, DCF effectively suppresses MI and provides a more stable Brillouin signal. Despite SMF exhibiting narrower BGS linewidths, DCF achieves a higher SNR, aligning with theoretical predictions. These findings highlight the importance of fiber dispersion properties in BOTDA design and suggest that using normally dispersive fibers like DCF can improve sensing performance in long-range, high-power applications. Full article

Platelet-rich plasma (PRP) has become an increasingly valuable biologic approach for personalized regenerative medicine because of its potent anti-inflammatory/healing effects. It is thought to be an excellent source of growth factors that can promote tissue healing and lessen fibrosis. Although this treatment has demonstrated effectiveness in numerous disease areas, its impact on pulmonary fibrosis (PF) caused by silver nanoparticles (AgNPs) via its antiapoptotic effects remains to be explored. AgNPs were synthesized biologically by Bacillus megaterium ATCC 55000. AgNP characterization was carried out via UV–Vis spectroscopy, X-ray diffraction (XRD), dynamic light scattering (DLS), transmission electron microscopy (TEM), and scanning electron microscopy (SEM) imaging to reveal monodispersed spheres with a mean diameter of 45.17 nm. A total of 48 male Wistar rats divided into six groups, with 8 rats per group, were used in the current study on the basis of sample size and power. The groups used were the PRP donor, control, AgNP, AgNP + PRP, AgNP + dexamethasone (Dexa) rat groups, and a recovery group. Body weights, hydroxyproline (HP) levels, and CASP3 and TWIST1 gene expression levels were assessed. H&E and Sirius Red staining were performed. Immunohistochemical studies for inducible nitric oxide synthase (iNOS) and cluster of differentiation 68 (CD68) with histomorphometry were conducted. A significant reduction in body weight (BWt) was noted in the AgNP group compared with the AgNP + PRP group (p < 0.001). HP, CASP3, and TWIST1 expression levels were significantly increased by AgNPs but decreased upon PRP (p < 0.001) treatment. Compared with those in the control group, the adverse effects of AgNPs included PF, lung alveolar collapse, thickening of the interalveolar septa, widespread lymphocytic infiltration, increased alveolar macrophage CD68 expression, and iNOS positivity in the cells lining the alveoli. This work revealed that PRP treatment markedly improved the histopathological and immunohistochemical findings observed in the AgNP group in a manner comparable to that of the Dexa. In conclusion, these results demonstrated the therapeutic potential of PRP in a PF rat model induced via AgNPs. This study revealed that PRP treatment significantly improved the histopathological and immunohistochemical alterations observed in the AgNP-induced group, with effects comparable to those of the Dexa. In conclusion, these findings highlight the therapeutic potential of PRP in a rat model of AgNP-induced PF. Full article