Search Results (5,081)

PredRNN is a spatiotemporal prediction model based on ST-LSTM units, capable of simultaneously extracting spatiotemporal features from ionospheric Total Electron Content (TEC). However, its internal convolutional operations require large kernels to capture low-frequency features, which can easily lead to model over-parameterization and consequently limit its performance. Although some studies have employed wavelet transform convolution (WTConv) to improve feature extraction efficiency, the introduced noise interferes with effective feature representation. To address this, this paper proposes a denoising wavelet transform convolution (DWTConv) and constructs the DWTPred-Net model with it as the key component. To systematically validate the model’s performance, we compared it with mainstream models (C1PG, ConvLSTM, and ConvGRU) under different solar activity conditions. The results show that both $MAE$ and $RMSE$ of DWTPred-Net are greatly reduced under all test conditions. In high solar activity, DWTPred-Net reduces $RMSE$ by 13.81%, 6.19%, and 9.28% compared to the C1PG, ConvLSTM, and ConvGRU, respectively. In low solar activity, the advantage of DWTPred-Net becomes even more pronounced, with $RMSE$ reductions further increasing to 19.39%, 11.51%, and 16.10%, respectively. Furthermore, in additional tests across different latitudinal bands and during geomagnetic storm events, the model consistently demonstrates superior performance. These multi-perspective experimental results collectively indicate that DWTPred-Net possesses obvious advantages in improving TEC prediction accuracy. Full article

The caldén (Neltuma caldenia) forest, a xerophytic low-stature ecosystem in central Argentina, faces increasing threats from land use change and desertification. This study assesses the capability of full-polarimetric L-band SAR data from the Argentine SAOCOM-1A satellite to characterise forest attributes in this ecosystem. We computed the Generalised Radar Vegetation Index (GRVI) and compared it with aboveground biomass and tree canopy cover data from the Second National Forest Inventory, under fire and non-fire conditions. We also assessed other SAR indices and polarimetric decompositions. GRVI values exhibited limited variability relative to the broad range of field-estimated biomass, and most regression models were not statistically significant. Nevertheless, GRVI effectively distinguished woody from non-woody vegetation and showed a weak correlation with canopy cover. Statistically significant, albeit weak, correlations were also observed between biomass and specific polarimetric components, such as the helix term of the Yamaguchi decomposition and the Pauli volume component. Key challenges included limited spatial and temporal coverage of SAOCOM-1A data and the distribution of field plots. Despite these limitations, our results support the use of GRVI for land cover monitoring in semiarid regions, emphasising the importance of multitemporal data, integration with C-band SAR, and enhanced field sampling to improve forest attribute modelling. Full article

Pseudomonas extremorientalis PEY1, isolated from the intestinal contents of marine fish, was evaluated for the production and properties of antibacterial proteins active against Edwardsiella tarda, a major pathogen in aquaculture. Antibacterial production was maximized in a minimal medium supplemented with 1% yeast extract and 1% galactose under stationary cultivation at 25 °C and pH 7.0. Growth and bioactivity assays were conducted under varying carbon and nitrogen sources, temperatures, and pH levels. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis revealed a distinct ~37 kDa protein band corresponding to antibacterial activity, exhibiting an inhibition zone of 2.4 ± 0.1 cm against E. tarda. The activity was completely abolished by papain digestion but remained detectable after exposure to 55 °C and pH 8, indicating that the active compound is a moderately heat-stable, proteinaceous antibacterial molecule. LC–MS/MS analysis identified the protein as a putative disulfide reductase with ~40% sequence coverage. The antibacterial factor exhibited strong physicochemical stability, retaining activity in the presence of surfactants and metal ions. Collectively, these findings demonstrate that P. extremorientalis PEY1 produces a thermostable, papain-sensitive antibacterial protein with selective activity against E. tarda, highlighting its potential as a promising natural biocontrol or postbiotic candidate for sustainable aquaculture. Full article

In this paper, laser-assisted machining (LAM) of SiC ceramics was taken as the research object, and the different spectrum and energy spectrum characteristics and their changing trends of acoustic emission (AE) signals under processing states of brittleness, plasticity and thermal damage were analyzed. The numerical characterization of ceramic softening degree was indirectly realized by the energy spectrum characteristics of low-frequency band energy ratio, marking a methodological breakthrough in transitioning from qualitative analysis to quantitative detection for identifying plastic processing state. First, the surface morphology of the machined surface based on the single-factor experiment of laser power was analyzed, and three different processing states and ranges of laser power were determined, namely brittle state (0–185 W), plastic state (185–225 W) and thermal damage state (>225 W). Then, the wavelet packet denoising and spectrum analysis of AE signals under different processing states were carried out to obtain the corresponding frequency of the maximum amplitude and the amplitude change trend of the characteristic frequency (515 kHz) in the high-frequency domain. Finally, the energy spectrum analysis of acoustic emission signals was carried out, and the method of indirect characterization of ceramic softening degree by low-frequency band energy ratio was proposed. This paper provides a numerical characterization method and theoretical guidance for the detection and identification of the plastic processing state of ceramic laser-assisted cutting. Full article

Widespread antibiotic residues in aquatic environments pose escalating threats to ecological stability and human health, highlighting the urgent demand for effective remediation strategies. In recent years, photocatalytic technology based on advanced nanomaterials has emerged as a sustainable and efficient strategy for antibiotic degradation, enabling the effective utilization of solar energy for environmental remediation. This review provides an in-depth discussion of six representative categories of photocatalytic nanomaterials that have demonstrated remarkable performance in antibiotic degradation, including metal oxide-based systems with defect engineering and hollow architectures, bismuth-based semiconductors with narrow band gaps and heterojunction designs, silver-based plasmonic composites with enhanced light harvesting, metal–organic frameworks (MOFs) featuring tunable porosity and hybrid interfaces, carbon-based materials such as g-C₃N₄ and biochar that facilitate charge transfer and adsorption, and emerging MXene–semiconductor hybrids exhibiting exceptional conductivity and interfacial activity. The photocatalytic performance of these nanomaterials is compared in terms of degradation efficiency, recyclability, and visible-light response to evaluate their suitability for antibiotic degradation. Beyond parent compound removal, we emphasize transformation products, mineralization, and post-treatment toxicity evolution as critical metrics for assessing true detoxification and environmental risk. In addition, the incorporation of artificial intelligence into photocatalyst design, mechanistic modeling, and process optimization is highlighted as a promising direction for accelerating material innovation and advancing toward scalable, safe, and sustainable photocatalytic applications. Full article

In this study, the authors wish to introduce an unsupervised procedure designed for real-time generation of maps depicting advected aerosols, specifically focusing on desert dust and smoke originating from biomass combustion. This innovative approach leverages the high-resolution capabilities provided by Sentinel-2 imagery, operating at a 10 m scale, which is particularly advantageous for urban settings. Concurrently, it takes advantage of the near-daily revisit frequency afforded by Sentinel-3. The methodology involves generating aerosol maps at a 10 m resolution using bands 2, 3, 4, and 5 of Sentinel-2, available in L1C and L2A formats, conducted every five days, contingent upon the absence of cloud cover. Subsequently, this map is enhanced every two days through spatial modulation, utilizing a similar map derived from the visible and near-infrared observations (VNIR) captured by the OLCI instrument aboard Sentinel-3, which is accessible at a 300 m scale. Data from the two satellites undergo independent processing, with integration at the feature level. This process combines Sentinel-3 and Sentinel-2 maps to update aerosol concentrations in each 300 m × 300 m grid every two days or more frequently. For the dates when Sentinel-2 data is unavailable, the spatial texture or the aerosol distribution within these grid cells is extrapolated. This spatial index represents an advancement over prior studies that focused on differentiating between dust and smoke based on their scattering and absorption characteristics. The entire process is rigorously validated by comparing it with point measurements of fine- and coarse-mode Aerosol Optical Depth (AOD) obtained from AERONET stations situated at the test sites, ensuring the reliability and accuracy of the generated maps. Full article

This study introduces an amplitude-based method that applies Spatially Variant Apodization (SVA) to reduce sidelobes in Synthetic Aperture Radar (SAR) data. Unlike conventional approaches, the filter is applied only to the amplitude while preserving the original interferometric phase, thereby enabling accurate Persistent Scatterer Interferometry (PSI) for dam deformation monitoring in Stanford Method for Persistent Scatterers (StaMPS) software. The SVA filter is integrated as an additional processing step within the Sentinel Application Platform (SNAP) for the SentiNel Application Platform to Stanford Method for Persistent Scatterers (SNAP2StaMPS) workflow. Filtering is performed in two dimensions (azimuth and range) separately on the In-phase (I) and Quadrature (Q) components of the coregistered data using a Python-based implementation via SNAP-Python (snappy). By recombining the SVA-filtered and original I and Q components, the method modifies only the amplitude while leaving the phase unchanged. The approach is evaluated in a proof-of-concept case study of the Sorpe Dam in Germany, where an Electronic Corner Reflector - C Band (ECR-C) produces sidelobe artifacts that degrade the Sentinel-1 (S-1) descending time series. The results demonstrated a successful integration of SVA filtering into the SNAP2StaMPS framework, achieving sidelobe reduction and improved Persistent Scatterer (PS) detection without compromising phase quality. The number of sidelobe-affected PS decreased by 39.26% after SVA filtering, while the amplitude-based approach preserved the original phase and deformation values, with a Root Mean Square Error (RMSE) of approximately 0.38 mm. Overall, this novel amplitude-based SVA approach extends the SNAP2StaMPS workflow by reducing strong sidelobes while preserving phase information for dam monitoring at the Sorpe dam site. Full article

Applying non-thermal plasma (NTP) to seeds prior to sowing is recognized for its ability to enhance germination and promote plant growth. This study investigated the effects of NTP seed treatment on alfalfa seed surface characterization, germination, growth, and biochemical traits under varying water conditions. NTP modified seed surface properties by decreasing water contact angle, roughening the coat, and reducing O–H/N–H and C–H band intensities, while major functional groups remained intact. Short plasma exposures (<2 min) enhanced germination, whereas prolonged treatment (10 min) reduced viability, indicating embryo sensitivity. In pot experiments, both 1 and 5 min treatments improved fresh and dry weight, stem and root elongation, pigment accumulation, and protein content, particularly under normal and moderate water stress, while extended exposure (10 min) offered limited benefits and could be detrimental under severe drought. Root growth was most responsive, suggesting enhanced water and nutrient uptake. Plasma had modest effects on polyphenols and flavonoids but influenced early physiological responses and antioxidant activity. These findings highlight NTP as a promising seed priming tool to improve alfalfa performance, though further studies are needed to clarify the mechanisms and specific contributions of plasma components. Full article

The aim of this study was to evaluate the effect of heat treatment, including solutionising and ageing in the temperature range of 20–250 °C, on the microstructural, mechanical, and tribological properties of the Al 7075 alloy. Microscopic analysis revealed that in the as-received condition and after natural ageing, the microstructure is characterised by the presence of elongated grains and a banded distribution of precipitates, whereas higher ageing temperatures lead to their coarsening and the initiation of recrystallisation processes. The highest hardness (189 HV) was obtained after ageing at 100 °C for 48 h, while further increases in temperature caused a systematic decrease in hardness—down to 85 HV at 250 °C for 4 h. Impact tests showed that in the as-received condition, the material reached a value of 7 J/cm², after natural ageing 15 J/cm², and the maximum (26 J/cm²) was achieved for samples aged at 250 °C for 4 h. Tribological tests conducted using the T-07 method confirmed the dependence of wear resistance on heat treatment parameters—the lowest relative abrasive wear resistance coefficient was observed after natural ageing (k_b = 0.860), and the highest after ageing at 250 °C for 4 h (k_b = 1.216). The results obtained indicate that moderate ageing conditions (100–150 °C) favour increased hardness, whereas higher temperatures (200–250 °C) lead to an improvement in impact strength and tribological resistance, which showed an inversely proportional relationship with hardness, contrary to Archard’s law. Full article

This study examines the pigment-dependent photoaging behavior of laboratory-prepared mock-up Chinese lacquer coatings colored with cinnabar, orpiment, and lapis lazuli under high-pressure mercury-lamp irradiation. Colorimetric results showed rapid changes within the first three days, with maximum ΔE values of 14.05 (red), 16.74 (yellow), and 17.97 (blue) after 30 days. Cinnabar-based films exhibited the highest color stability, whereas orpiment and lapis-lazuli coatings underwent pronounced hue shifts and chroma increases. Gloss loss and surface roughness evolution displayed a strong negative correlation: orpiment coatings experienced the most severe degradation, with gloss decreasing by over 60% and surface roughness increasing by approximately 70%, while cinnabar coatings showed the least decline (≈55% gloss loss; ≈27% roughness increase). SEM analysis further revealed extensive cracking and particle fragmentation in orpiment films, moderate surface disruption in lapis-lazuli films, and minimal microstructural damage in cinnabar films. Non-invasive reflection-mode FTIR spectroscopy confirmed these trends, showing minimal chemical change in cinnabar coatings but significant carbonyl growth, C–O–C band broadening, and aliphatic chain cleavage in orpiment and lapis-lazuli coatings. These results highlight the critical role of pigment chemistry in modulating UV-induced degradation pathways. Integrating optical, morphological, and chemical evidence, this study establishes a clear pigment-dependent degradation mechanism and provides valuable guidance for evaluating the long-term stability of lacquered cultural heritage and optimizing modern lacquer formulations. Full article

This study quantifies how viscous-term discretization errors contaminate subgrid-scale (SGS) model-constant estimates when SGS eddy viscosity is tuned to satisfy an energy budget. A linearly forced, steady two-dimensional low-Reynolds-number Taylor-flow benchmark is used: it preserves global kinetic energy analytically, and the forcing cancels the viscous term without altering the convective–pressure balance when incompressibility holds. Large-eddy simulations on staggered grids (${56}^2$–${480}^2$) employ second-, fourth- and sixth-order central differences for the viscous term and second- or fourth-order convective schemes. SGS stresses are represented by the Vreman model, used to probe numerical error–SGS interaction rather than to validate three-dimensional turbulence physics. Energy errors arise almost exclusively from the viscous discretization and scale as $\Delta x^m$ ($m=2,4,6$). Balancing this truncation error with SGS dissipation ($\propto C_v\Delta x^2$) yields the theoretical scaling $C_v\propto \Delta x^{m-2}$. For a second-order viscous scheme, the required $C_v$ becomes $\Delta x$-independent, Re-dependent, and far above practical LES values, showing that tuning can serve as a numerical band-aid and undermine quantitative constant estimation. With fourth- or higher-order viscous discretization, the required $C_v$ decays rapidly with refinement; when $C_v$ is adjusted, global energy is recovered and RMS velocity errors decay with viscous accuracy, while convective-order effects remain minor. Full article

High-speed silicon (Si) photonic transmitters operating in the O-band require higher on-chip optical power to support advanced modulation formats and ever-increasing line rates. A straightforward approach is to operate laser diodes at higher output power or employ more specialized sources, but this raises cost and exacerbates nonlinear effects such as self-phase modulation, two-photon absorption, and free-carrier generation in high-index-contrast Si waveguides. This paper proposes a low-cost 4 × 1 tree-cascade multimode interference (MMI) power combiner on a Si-on-insulator platform at 1310 nm wavelength that enables coherent power scaling while remaining fully compatible with standard commercial O-band lasers. The device employs adiabatic tapers and low-loss S-bends to ensure uniform field evolution, suppress local field enhancement, and mitigate nonlinear phase accumulation. The optimized layout occupies a compact footprint of 12 µm × 772 µm and achieves a simulated normalized power transmission of 0.975 with an insertion loss of 0.1 dB. Spectral analysis shows a 3 dB bandwidth of 15.8 nm around 1310 nm, across the O-band operating window. Thermal analysis shows that wavelength drift associated with ±50 °C temperature variation remains within the device bandwidth, ensuring stable operation under realistic laser self-heating and environmental changes. Owing to its broadband response, fabrication tolerance, and compatibility with off-the-shelf laser diodes, the proposed combiner is a promising building block for O-band transmitters and photonic neural-network architectures based on cascaded splitter and combiner meshes, while preserving linear transmission and enabling dense, large-scale photonic integration. Full article

This study reveals the distribution of floating macroalgae Sargassum in the East China Sea and Yellow Sea using HY-1C/D Coastal Zone Imager (CZI) data. A new inversion model, utilizing green and near-infrared bands, was developed for the 50 m resolution CZI data. This model effectively distinguishes Sargassum from Ulva prolifera and is effective in turbid coastal waters. Sargassum spatiotemporal distribution and drift patterns over five years were analyzed. Key findings demonstrate that (1) floating Sargassum exhibits distinct spatiotemporal distribution patterns. Sargassum initially emerges along Zhejiang’s eastern coast in February. During March and April, it concentrates east of Hangzhou Bay. While in May, Sargassum appears in the Yellow Sea, and is distributed near the Shandong Peninsula by June. Small patches of Sargassum are also found in the Yellow Sea from November to January. (2) Its distribution is influenced by various factors like nutrients, temperature, salinity, currents, and winds. Suitable nutrients, temperature, and salinity promote growth, while currents and winds, particularly in April–May, drive its northward drift from the East China Sea into the Yellow Sea. The Yellow Sea population originates from both drifting populations and local growth. (3) This research highlights the utility of HY-1C/D satellite data in coastal zone research, facilitating ecological monitoring and protection. Full article

Photocatalytic reduction of carbon dioxide is a very effective strategy to address the energy crisis and greenhouse effect. TiO₂ is a widely used semiconductor photocatalyst, which has excellent catalytic activity, excellent chemical stability and low toxicity. Nevertheless, TiO₂ still has some inherent limitations, such as: wide band gap, high carrier recombination rate, and low adsorption activation ability for carbon dioxide. These drawbacks severely restrict its further application in the photocatalytic reduction of CO₂. In this study, cotton-like blue C/TiO₂ NTs are successfully synthesized through the in situ growth of TiO₂ nanotubes on the MIL-125(Ti)-derived C/TiO₂ precursor. The experimental results revealed that the CO production rate of the cotton-like blue C/TiO₂ NTs was 1.84 times that of C/TiO₂ and 3.78 times that of TiO₂ nanotubes. These results clearly demonstrate that the cotton-like blue C/TiO₂ NTs exhibit a broad spectral response, a large specific surface area, and an abundance of oxygen vacancies. This research provides new insights into the design of titanium dioxide-based photocatalytic materials and opens up a promising avenue for enhancing the performance of titanium dioxide in the photocatalytic reduction of carbon dioxide. Full article

We report a novel approach to fabricating high-performance and robust quantum dot light-emitting diodes (QLEDs) utilizing sputtered SnO₂ thin films as the electron transport layer (ETL). While conventional solution-processed ZnMgO NP ETLs face limitations in mass production, the sputtering process offers advantages for uniform and reproducible thin film deposition. Herein, the structural, optical, and electrical properties of SnO₂ thin films were optimized by controlling the Ar/O₂ ratio and substrate heating temperature during sputtering. SnO₂ thin films with O₂ gas improve charge balancing in QLEDs by lowering the conduction band minimum. Furthermore, it was observed that oxygen vacancies in SnO₂ function as exciton quenching sites, which directly impacts the long-term stability of the device. QLEDs fabricated under optimal conditions (Ar/O₂ = 35:5, 200 °C heating) achieved a peak luminance of 99,212 cd/m² and a current efficiency of 21.17 cd/A with excellent device stability. The findings suggest that sputtered SnO₂ ETLs are a highly promising technology for the commercial production of QLEDs. Full article