Search Results (32,225)

Spectral interrogation of fiber Bragg gratings (FBGs) in the ~850 nm band remains relatively uncommon, largely due to the limited availability of commercial instruments and the restricted applicability of conventional interrogation schemes in this wavelength range. This work presents a practical and high-precision wavelength demodulation method for 850 nm FBG sensing based on an imaging Charge-Coupled Device (CCD) spectrometer. A Czerny–Turner (C–T) optical configuration is employed for spatial spectral dispersion, and the optical system is theoretically analyzed and optimized using ZEMAX to balance spectral resolution, optical throughput, and compactness. A polynomial wavelength–pixel calibration model is established, and Gaussian fitting is adopted for robust peak-position extraction under multimode fiber conditions. Experimental validation is carried out using four serially cascaded FBGs distributed over 830–880 nm. The wavelength–pixel calibration yields an RMS residual of 0.46 nm. Within a strain range of 0–2000 με, the average wavelength demodulation bias of a single FBG is 6.8 pm, with a wavelength demodulation RMS error of 86.9 pm and a measured strain sensitivity of 0.72 pm/με. The results demonstrate that the proposed CCD-based imaging interrogation scheme is feasible for 850 nm FBG sensing and enables accurate wavelength demodulation in this relatively underexplored band. Since the system is implemented using standard off-the-shelf components, it also provides a practical technical route for the deployment of FBG sensing systems in engineering applications. Full article

Traditional satellite-derived bathymetry (SDB) often suffers from systematic optical path distortions due to the neglect of seafloor slope effects, leading to significant accuracy degradation in high-gradient coastal areas. This study proposes a Slope-Aware Physics-Informed Neural Network (SA-PINN) framework that synergistically utilizes ICESat-2 bathymetric photons and Sentinel-2 multispectral imagery. The core innovation involves a slope-aware operator, integrated into the radiative transfer-based physics loss function, which explicitly rectifies directional optical path deviations induced by seafloor inclination. By fusing physical mechanisms with data-driven features, the model utilizes a seven-dimensional feature space comprising four spectral bands, two directional slope components, and prior depth. Applications at Culebra, Maui, and Molokai demonstrate that SA-PINN significantly outperforms the Stumpf model, Random Forest, and standard CNNs, achieving root mean square errors (RMSE) of 1.36 m, 2.91 m, and 1.34 m, respectively. Ablation studies confirm that SA-PINN reduces RMSE by up to 37% compared to CNN in complex regions with slopes exceeding 10°, ensuring superior physical consistency and spatial continuity. This research provides a robust, in situ-free automated solution for high-resolution bathymetric mapping in remote and steep coastal environments globally. Full article

For studies utilizing methods such as water color parameter inversion and algal bloom classification, abundant spectral bands and high spectral resolution are of great significance. However, for multispectral satellite sensors that are not designed for water color studies (e.g., Sentinel-2 MSI), the number of bands in the visible–near-infrared range is limited, and lacks specific spectral bands with rich spectral information. Hyperspectral reconstruction of multispectral data based on hyperspectral remote sensing reflectance ($R_{rs}$) databases and machine learning algorithms have been proven to be a feasible solution. Based on the in situ measured $R_{rs}$ data, this study constructed a large-sample hyperspectral $R_{rs}$ database covering various optical water types using two Chinese hyperspectral satellites, and compared the spectral reconstruction accuracy of six machine learning algorithms. The results show that expanding the $R_{rs}$ database for model training by integrating hyperspectral satellite data can effectively improve the reconstruction accuracy in waters of different optical types. Comparisons with in situ measured hyperspectral $R_{rs}$ indicate that the reconstructed Sentinel-2 hyperspectral data achieve high accuracy, with the Spectral Angle Mapper (SAM) less than 5° and the correlation coefficient ($r$) higher than 0.7. Furthermore, the reconstructed data can effectively restore spectral information not captured by the original multispectral data, such as the suspended sediment $R_{rs}$ peak at 580 nm and the chlorophyll $R_{rs}$ valley at 680 nm. Through spectral reconstruction, the spectral resolution of Sentinel-2 can be maximized while retaining its advantages of fast revisit capability and high spatial resolution, thereby expanding its application potential in water color remote sensing. Full article

The Janus monolayers have recently attracted substantial interest due to their unique asymmetric structures and intriguing physical properties. In this work, we explore the thermoelectric properties of the Janus monolayer ZrBrI, using first-principles calculations and Boltzmann transport theory. We demonstrate that the system maintains good dynamic and thermal stability, as evidenced by the absence of imaginary phonon modes and small lattice fluctuation at a higher temperature of 600 K. The hybrid functional calculations reveal that the monolayer exhibits a relatively small indirect gap of 1.22 eV, and the energy bands near the conduction band minimum exhibit double degeneracy with weak dispersions, which is very beneficial for enhancing the n-type power factor. Meanwhile, a relatively lower lattice thermal conductivity is found due to strong lattice anharmonicity caused by the antibonding state and the symmetry breaking of the structure. Collectively, a larger ZT value of 3.9 at 600 K can be realized for the n-type Janus monolayer ZrBrI at an optimal concentration of $1.89\times {10}^{13} {\mathrm{cm}}^{-2}$, highlighting its promising thermoelectric application in the intermediate temperature region. Full article

Aryl halides are important intermediates for chemical synthesis. However, the negative reduction potential up to −2.7 V (vs. SCE) makes photoredox conversion of aryl halides by reductive dehalogenation to aryl radicals for chemical transformations difficult. Inspired by the outstanding photophysical properties of deazaflavin and triphenylamine, as well as results of theoretical calculations, we attached the diphenylamino group to C8 of deazaflavin, and the resulting compounds look fabricated by “fusing” deazaflavin and triphenylamine (TPA) together by sharing the benzene ring. We also introduced alkyl and aryl moieties to C5 and afforded a series of deazaflavin derivatives (dFLs), namely 10-butyl-8-(diphenylamino)-3,5-dimethylpyrimido[4,5b]quinoline-2,4(3H,10H)-dione (TPAdFlMe), 10-butyl-8-(diphenylamino)-3-methyl-5-(trifluoromethyl)pyrimido[4,5-b]quinoline-2,4(3H,10H)-dione(TPAdFlTF) and 10-butyl-8-(diphenylamino)-3-methyl-5-phenylpyrimido[4,5-b]quinoline-2,4(3H,10H)-dione (TPAdFlPh), and investigated their photophysical properties and performance as sensitizers in the photodehalogenation of aryl halides. We showed that the photophysical properties are significantly improved in these dFLs. The absorption bands of dFLs are redshifted and the absorbance is more than double that of riboflavin tetraacetate (RFTA). The singlet oxygen quantum yields of TPAdFlMe, TPAdFlTF and TPAdFlPh are 0.42, 0.25 and 0.39, respectively, and the corresponding redox potentials are −1.75, −0.75 and −1.71 V vs. Ag/Ag⁺, respectively, comparable to known deazaflavin-based sensitizers. Originating from these properties, TPAdFlMe and TPAdFlPh are capable of sensitizing the full photodehalogenation of 0.038 mmol p-iodoanisole, and the yields of the photodehalogenation of 0.038 mmol p-bromoanisole are 67 and 69%, respectively. They also demonstrate exceptional performance in the photodehalogenation of halides of polycyclic aromatics with yields in the range of 73% for 1-benzhydryl-3-bromobenzene to 100% for 1-bromonapthalene in 18 h runs. The performance of TPAdFlMe and TPAdFlPh in photodehalogenation are already comparable to recently reported deazaflavin-based sensitizers, and we propose the transformation would proceed though the consecutive photo-induced electron transfer (conPET) mechanism with consecutive excitation of charged deazaflavin-based radicals under light irradiation as the key step to generating the aryl radicals, and the vital role of sensitizer-based radicals is further confirmed by mechanistic investigations. We expect the findings will help to design novel flavin-based triplet sensitizers for photoredox catalytic organic transformations. Full article

Laser cladding processing efficiency is often limited by low powder utilization. To address this, our study elucidates the mechanism by which powder feeding parameters influence powder stream convergence, aiming to optimize these parameters. A three-dimensional model of a wide-band symmetrical nozzle was developed using a Computational Fluid Dynamics—Discrete Element Method (CFD-DEM) coupling method to simulate the gas–solid flow. Single-factor tests and experimental validation confirmed the model’s reliability. The results identify carrier gas flow as the key parameter controlling the focal length and powder concentration, while the powder feed rate primarily governs the concentration on the focal plane. These findings provide a theoretical foundation for optimizing laser cladding parameters to enhance powder utilization. Full article

The output power of photovoltaic (PV) systems is influenced by various environmental factors, exhibiting strong nonlinearity and non-stationarity, which poses significant challenges for accurate forecasting. To address these issues, this paper proposes a short-term PV power forecasting method based on wavelet convolutional neural networks and an improved Transformer. First, the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is employed to decompose the original PV power sequence into several intrinsic mode functions (IMFs). Fuzzy entropy is then utilized to evaluate the complexity of each component, and subsequences with similar entropy values are reconstructed to reduce the non-stationarity of the original series. Subsequently, Pearson correlation coefficients and the maximal information coefficient (MIC) are applied to capture both linear and nonlinear relationships between each reconstructed component and meteorological features, enabling the selection of strongly correlated variables. On this basis, a wavelet convolutional network (WTConv) is introduced to perform multi-scale decomposition and frequency-band feature extraction on the reconstructed components by integrating wavelet transform with convolution operations, effectively expanding the receptive field and extracting deep-seated features of the sequences. Finally, an improved iTransformer model is adopted for time-series modeling, leveraging its inverted encoding structure and self-attention mechanism to fully capture long-term dependencies among multivariate variables. The proposed model is validated using actual power data from a PV plant in Ningxia, China, across four seasons. Comprehensive experiments, including ablation studies, comparative analyses, loss function convergence evaluation, and Diebold–Mariano significance tests, are conducted to thoroughly assess the model’s effectiveness and superiority. Experimental results demonstrate that the proposed model achieves excellent prediction accuracy and stability in spring, summer, autumn, and winter, showing strong potential for engineering applications. Full article

Pine wilt disease (PWD) is a devastating biological forest disturbance, making its large-scale and high-precision remote sensing monitoring crucial for epidemic prevention and control. However, the performance of existing deep learning methods in high-resolution imagery is often limited by the confusion of spectral features among disparate ground objects and the complexity of forest boundaries. To address these challenges, this study proposes an innovative, end-to-end deep learning architecture termed MBA-Former. Built upon the robust Swin Transformer V2 backbone, the model systematically integrates two highly adaptable functional modules: (1) a front-end intelligent fusion module designed to adaptively fuse heterogeneous features, and (2) a back-end boundary refinement module that refines segmentation contours via dual-task learning. To train and evaluate the model, fine-grained manual annotations were first performed on Gaofen-2 satellite imagery acquired from multiple typical epidemic areas across northern and southern China. Information-enhanced datasets were constructed by fusing the original spectral bands, typical vegetation indices, and texture features. A comprehensive performance evaluation was then conducted, specifically targeting typical challenging scenarios characterized by complex ground object boundaries. The experimental results demonstrate that the Multi-modal Boundary-Aware Transformer (MBA-Former) significantly outperforms current state-of-the-art models. It achieved a mean Intersection over Union (mIoU) of 81.74%, an IoU of 77.58% for the most critical infected tree category, and a Boundary F1-Score of 78.62%. Compared to the best-performing baseline model, Swin-Unet, these three metrics exhibited notable improvements of 2.88%, 3.55%, and 4.46%, respectively. These findings convincingly demonstrate that MBA-Former provides a highly accurate and robust solution for the large-scale, automated remote sensing monitoring of forest diseases, offering immense value in preventing significant economic losses and preserving forest ecosystem integrity. Full article

Background: Congenital muscular torticollis (CMT) is usually managed conservatively during infancy, whereas surgical treatment is considered for persistent deformity in older children. However, evidence remains limited regarding the outcomes of distal resection combined with proximal release of the sternocleidomastoid muscle in children presenting beyond infancy. This study aimed to evaluate the functional and cosmetic outcomes of this combined approach in patients aged 3 years and older. Methods: This retrospective single-surgeon series included 37 patients with CMT aged 3 to 14 years who underwent distal resection combined with proximal release of the sternocleidomastoid muscle between 2002 and 2024. Preoperative and postoperative assessments were performed using the clinical outcome framework originally described by Lee et al., goniometric measurement of cervical rotation and lateral flexion, and clinical evaluation of head tilt, facial asymmetry, scar appearance, lateral band formation, and sternocleidomastoid V-column contour. Patients were also analyzed according to age at surgery, as 3–10 years and 11–14 years. Results: The mean age at surgery was 4.7 years, and the mean follow-up duration was 3.4 years. Significant postoperative improvement was observed in all major functional outcomes. Mean cervical rotation improved from 54.2 ± 8.6° to 87.9 ± 3.4°, and mean lateral flexion improved from 24.1 ± 6.8° to 44.5 ± 3.2° (both p < 0.001). Preoperative functional assessment scores averaged 6.8 ± 1.4, whereas postoperative total outcome scores averaged 14.2 ± 0.9. At final follow-up, no patient had residual head tilt. Mild residual facial asymmetry persisted in 3 patients (8.1%). Overall, postoperative outcomes were rated as excellent in 33 patients (89.2%) and good in 4 patients (10.8%). A slight partial loss of the sternocleidomastoid V-column contour was observed in 34 patients (91.9%), although this finding was not documented as a major cosmetic concern in the available clinical records. Hypertrophic scarring developed in 1 patient (2.7%). No lateral band formation, recurrence, revision surgery, infection, or hematoma was observed. Conclusions: Distal resection combined with proximal release provided favorable functional and cosmetic outcomes in children older than 3 years with CMT. The technique was associated with marked improvement in cervical motion, correction of head tilt, low complication rates, and a high proportion of excellent or good results. Full article

Recently, the coprecession of both the accretion disk and the jet formed following the tidal disruption event associated with the optical transient AT2020afhd, driven by a supermassive black hole of almost ten million solar masses, were independently measured in both the X and radio bands, respectively, showing a periodicity of nearly 20 days over about 300 days. An analytical model of the general relativistic gravitomagnetic Lense-Thirring precession of the effective orbit of a fictitious test particle revolving about a spinning primary can explain the observed precessional features. It yields allowed regions in the system’s parameter space which, as far as the hole’s dimensionless spin parameter is concerned, are essentially in agreement with those obtained in the literature with general relativistic magnetohydrodynamic simulations. The present analytical approach can be extended to include the precession due to the hole’s quadrupole mass moment as well. It breaks the degeneracy in the allowed regions occurring for negative and positive values of the spin parameter when only the Lense-Thirring effect is considered. The best estimate for the hole’s mass yields the range 0.185–0.215 for the dimensionless spin parameter. Using the same strategy with the gravitomagnetic frequency for an extended disk of finite size with a parameterized power-law mass density yields to distinct, generally non-overlapping allowed regions for each value of the power-law index adopted. Some of the assumptions on which this work is based are critically examined. Full article

In this study, Zn-doped Co₃O₄ nanorods and nanosheets with controlled Zn/Co molar ratios were synthesized via a hydrothermal strategy to clarify the respective roles of morphology and elemental doping in ethylbenzene sensing. The gas-sensing performance is strongly influenced by morphology, and the radially oriented nanorod structure significantly enhances sensing response compared with nanosheet structures. Zn doping effectively enhances the gas-sensing performance of Co₃O₄. As a result, the optimized Zn-doped nanorod sensor exhibits high sensitivity to ethylbenzene, a low detection limit, rapid response and recovery, and excellent operational stability. Density functional theory calculations reveal that the predominantly exposed facets of the nanorod structure possess stronger adsorption affinity and pronounced charge transfer toward ethylbenzene, providing theoretical support for the morphology-dominated sensing behavior. At the same time, Zn incorporation further adjusts the band structure and surface reactivity. Overall, this work elucidates a morphology-dominated and doping-assisted enhancement mechanism, offering clear design principles for high-performance Co₃O₄-based ethylbenzene sensors. Full article

A 27-year-old male presented with chronic diarrhea, bloating, and abdominal pain since age 13. Initially attributed to lactose intolerance, treated with dairy-free diet, symptoms persisted despite negative workup—normal celiac serology, stool studies, and abdominal ultrasound. Recent symptoms included severe diarrhea, fatigue, weakness, 8 kg weight loss, hair loss, elevated IgE and fecal calprotectin. Gastroscopy showed flattened, granular gastric mucosa with focal hyperemia in the antrum and greater curvature. Histology revealed severe chronic inactive H. pylori-negative gastritis with a prominent subepithelial collagen band (verified by Crossmon’s trichrome), confirming collagenous gastritis—a rare entity first described in 1989. The condition has a slight female predominance and bimodal age peaks (adolescence and >60 years). Symptoms are nonspecific, including abdominal pain, diarrhea, weight loss and anemia. Pediatric cases often feature nodular mucosa and anemia; adults more commonly present with watery diarrhea, sometimes linked to collagenous colitis. Diagnosis requires histological features including patchy subepithelial collagen band ≥ 10 μm thick, lymphocytic or eosinophilic infiltration of the lamina propria, epithelial changes and entrapped capillaries. Patterns include atrophic, lymphocytic-like, and eosinophil-rich. Crossmon’s or Masson’s trichrome, Congo red, and tenascin immunohistochemistry aid in proving collagen and excluding amyloidosis. Treatment is mainly symptomatic or with proton pump inhibitors; corticosteroids may be effective in refractory cases. Full article

In this study, we evaluated the biofilm-forming capacity of the B. pacificus B630 strain on table eggshells and its behavior in the presence of egg components, in comparison with B. cereus ATCC 14579. Strain B630, previously characterized as nhe⁺ and cytK⁺ and as a strong biofilm producer on glass, was confirmed as motile and positive for protease and phospholipase production. In static assays on disinfected eggshell pieces, B630 formed significantly more biofilm than ATCC 14579, while both strains exhibited comparable numbers of vegetative cells and spores embedded in the biofilm. Scanning electron microscopy and Fourier transform infrared (FT-IR) analysis revealed a dense extracellular matrix, altered eggshell crystal morphology, and a reduction in calcite-associated bands in biofilm-positive shells. In brain–heart infusion (BHI) broth supplemented with egg white, growth and spore germination of ATCC 14579 were strongly inhibited, whereas B630 displayed markedly higher tolerance. In an eggshell contamination model with an initial inoculum of 1 × 10⁵ colony-forming units, B630 persisted on the shell for at least 15 days at room temperature, while neither strain was recovered from egg white or yolk. These findings indicate that B. pacificus B630 combines robust biofilm formation with enhanced tolerance to egg white, favoring prolonged persistence on eggshells and underscoring the potential role of highly biofilm-forming B. cereus s.l. strains in table egg contamination. The persistence of strains of the B. cereus s.l. group in the eggshell may compromise the safety of the product. Full article

Ground deformation monitoring is pivotal for enhancing urban resilience and mitigating geohazards. This study presents a synergistic monitoring framework integrating 26 Sentinel-1A (C-band) and 16 LuTan-1 (L-band) SAR scenes acquired between December 2023 and August 2025 to characterize the deformation dynamics in Beijing. Utilizing SBAS-InSAR, we first established a regional deformation baseline using Sentinel-1A observations, identifying critical subsidence and uplift zones in the eastern plains. Subsequently, high-resolution (3 m) LT-1 data were leveraged to achieve refined spatiotemporal characterization of these deformation hotspots. Validation against ground leveling benchmarks confirmed that both satellites yield high accuracy. LuTan-1 (RMSE = 3.810 mm/a) shows slightly better agreement with the ground leveling data than Sentinel-1A (RMSE = 4.853 mm/a). Analysis of the spatiotemporal patterns derived from InSAR revealed that the study area is characterized by widespread gene uplift (averaging ~10 mm/a), interspersed with acute localized subsidence exceeding 40 mm/a. Correlation analysis demonstrates a high spatiotemporal coupling between the extent and rate of surface uplift and groundwater level recovery. To further investigate these dynamics, Terzaghi’s effective stress principle is employed to quantify the contribution of groundwater level fluctuations to the observed surface deformation. A Parametric Harmonic Model was implemented to decouple elastic and trend components, and attribution analysis confirms that the continuous recovery of groundwater levels is the fundamental driver of the regional surface uplift. The inverted elastic skeletal storativity (S_ke), ranging from 1.587 × 10⁻³ to 9.184 × 10⁻³, reveals that regional surface uplift is predominantly driven by the elastic rebound of aquifer systems following groundwater recovery. In contrast, localized subsidence anomalies observed at large-scale engineering construction sites, landfill facilities, major expressway corridors, and high-density residential areas are independent of groundwater fluctuations, instead they are primarily attributed to anthropogenic stressors. This study elucidates a dual-drive mechanism, which comprising macroscopic hydrogeological rebound and localized anthropogenic disturbance, providing a robust scientific basis for differentiated urban hazard management. Full article

Global land use is changing rapidly, particularly in the tropics, where human populations have had relatively high growth rates in recent decades. This has resulted in wildlife increasingly living in or using anthropogenic environments, which often have different thermal properties in comparison to natural habitats. For example, materials used for buildings, such as concrete and brick, typically absorb, retain and radiate more heat than vegetated surfaces. The mosaic of man-made and natural areas formed when anthropogenic environments expand is therefore likely to generate microhabitats with different thermal properties. Here, we investigated the association between microhabitats and the body surface temperature of wild banded mongooses (Mungos mungo), a social mammal living in equatorial Uganda. After controlling for the significant effects of air temperature, humidity, time of day and body contact, we found that mongooses had the highest body surface temperatures when present on anthropogenic substrates, such as discarded roofing straw and refuse, while mongooses present on building materials, dead vegetation and bare soil had intermediate body surface temperatures. In contrast, mongooses had the lowest body surface temperatures when present in more natural, vegetated habitats. Although our study is relatively small scale and limited in scope, our results indicate that anthropogenic modifications to natural environments may result in hotter microhabitats, which may in turn impact space use, movement and thermoregulation in wildlife. We hope that our study encourages further research into this understudied but emerging topic. Full article