Search Results (2,323)

The primary payload onboard the Gaofen-3-02 (GF3-02) satellite is a C-band Synthetic Aperture Radar (SAR) capable of achieving a maximum resolution of 1 m. This instrument is critical to monitor the marine environment, particularly for tracking sea surface wind speeds, an important marine environmental parameter. In this study, we utilized 192 sets of GF3-02 SAR data, acquired in Quad-Polarization Strip I (QPSI) mode in March 2022, to retrieve sea surface wind speeds. Prior to wind speed retrieval for vertical-vertical (VV) polarization, radiometric calibration accuracy was analyzed, yielding good performance. The results showed a bias and root mean square errors (RMSEs) of 0.02 m/s and 1.36 m/s, respectively, when compared to the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis V5 (ERA5) data. For horizontal–horizontal (HH) polarization, two types of polarization ratio (PR) models were introduced based on the GF3-02 SAR data. Combining these refitted PR models with CMOD5.N, the results for HH polarization exhibited a bias of −0.18 m/s and an RMSE of 1.25 m/s in comparison to the ERA5 data. Regarding vertical–horizontal (VH) polarization, two linear models based on both measured normalized radar cross sections (NRCSs) and denoised NRCSs were developed. The findings indicate that denoising significantly enhances the accuracy of wind speed measurements for VH polarization when dealing with low wind speeds. When compared against buoy data, the wind speed retrieval results demonstrated a bias of 0.23 m/s and an RMSE of 1.77 m/s. Finally, a comparative analysis of the above retrieval results across all three polarizations was conducted to further understand their respective performances. Full article

Cachexia is a multifactorial syndrome characterized by severe muscle wasting and is a debilitating condition frequently associated with cancer. Previous studies from our group revealed that withaferin A (WFA), a steroidal lactone, mitigated muscle cachexia induced by ovarian tumors in NSG mice. However, it remains unclear whether WFA’s protective effects are direct or secondary to its antitumor properties. We developed a cachectic model through continuous angiotensin II (Ang II) infusion in C57BL/6 mice to address this issue. Ang II infusion resulted in profound muscle atrophy, evidenced by significant reductions in grip strength and in the TA, GA, and GF muscle mass. Molecular analyses indicated elevated expression of inflammatory cytokines (TNFα, IL-6, MIP-2, IL-18, IL-1β), NLRP3 inflammasome, and genes associated with the UPS (MuRF1, MAFBx) and autophagy pathways (Bacl1, LC3B), along with suppression of anti-inflammatory heme oxygenase-1 (HO-1) and myogenic regulators (Pax7, Myod1). Strikingly, WFA treatment reversed these pathological changes, restoring muscle mass, strength, and molecular markers to near-normal levels. These findings demonstrate that WFA exerts direct anti-cachectic effects by targeting key inflammatory and atrophic pathways in skeletal muscle, highlighting its potential as a novel therapeutic agent for cachexia management. Full article

In the road extraction task, for the problem of low utilization of spectral features in high-resolution remote sensing images, we propose a Multi-spectral image-guided fusion of Spatial and Channel Features for road extraction algorithm (SC-FMNet). The method is designed with a two-branch input network structure including Multi-spectral image and fused image branches. Based on the original MSNet model, the Spatial and Channel Reconstruction Convolution (SCConv) module is introduced in the coding part in each of the two branches. In addition, a Spatially Adaptive Feature Modulation Mechanism (SAFMM) module is introduced into the decoding structure. The experimental results in the GF2-FC and CHN6-CUG road datasets show that the method can better extract the road information and improve the accuracy of road segmentation, which verify the effectiveness of SC-FMNet. Full article

To examine the impact of green finance (GF) on urban land green use efficiency (LGUE), we treat the Green Finance Reform and Innovation Pilot Zone (GFRIPZ) policy, implemented in 2017, as quasi-natural experiment. The results from a multi-period difference-in-difference model show that GF contributes to improving urban LGUE. This conclusion is validated further by a generalized random forest model. The mechanism analysis demonstrates that GF enhances LGUE through the effects of green technological innovation, industrial upgrading, and public green behavior. The moderation analysis further reveals that artificial intelligence can amplify the positive impact of GF on LGUE. The heterogeneity results show that the positive relationship between GF and LGUE is more pronounced in midwestern cities, non-resource-based cities, and cities with a high level of financial development. Therefore, it is essential to expand the GF pilot program in a structured manner and establish a coordinated mechanism to promote LGUE improvement through GF in different regions, thereby enhancing financial service efficiency for the real economy. Full article

The quantization process of synthetic aperture radar (SAR) images faces significant challenges due to their high dynamic range, resulting in notable quantization distortion. This not only degrades the visual quality of the quantized images but also severely impacts the accuracy of image interpretation. To mitigate the distortion caused by uniform quantization and enhance visual quality, this paper introduced a novel nonlinear quantization framework via signal-to-noise ratio (SNR) enhancement and segmentation strategy guidance. This framework introduces guiding information to improve quantization performance in weak scattering regions. A histogram adjustment method is developed to incorporate the spatial information of SAR images into the quantization process to enhance the quantization performance, specifically within weak scattering regions. Additionally, the optimal quantizer is improved by refining the SNR distribution across quantization units, addressing imbalances in their allocation. Experimental results based on Gaofen-3 (GF-3) satellite data demonstrate that the proposed algorithm approaches the global quantization performance of optimal quantizers while achieving superior local quantization performance compared to existing methods. Full article

Monitoring mangrove phenology requires frequent, high-resolution remote sensing data, yet satellite imagery often suffers from coarse resolution and cloud interference. Traditional methods, such as denoising and spatiotemporal fusion, faced limitations: denoising algorithms usually enhance temporal resolution without improving spatial quality, while spatiotemporal fusion models struggle with prolonged data gaps and heavy noise. This study proposes an optimized mangrove phenology extraction approach (OMPEA), which integrates Landsat and MODIS data with a denoising algorithm (e.g., Gap Filling and Savitzky–Golay filtering, GF–SG) and a spatiotemporal fusion model (e.g., Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model, ESTARFM). The key of OMPEA is that GF–SG algorithm filled data gaps from cloud cover and satellite transit gaps, providing high-quality input to ESTARFM and improving its accuracy of NDVI imagery reconstruction in mangrove phenology extraction. By conducting experiments on the GEE platform, OMPEA generates 1-day, 30 m NDVI imagery, from which phenological parameters (i.e., the start (SoS), end (EoS), length (LoS), and peak (PoS) of the growing season) are derived using the maximum separation (MS) method. Validation in four mangrove areas along the coastal China shows that OMPEA significantly improves the potential to capture mangrove phenology in the presence of incomplete data. The OMPEA significantly increased usable data, adding 7–33 Landsat images and 318–415 MODIS images per region. The generated NDVI series exhibits strong spatiotemporal consistency with original data (R²: 0.788–0.998, RMSE: 0.007–0.253) and revealed earlier SoS and longer LoS at lower latitudes. Cross-correlation analysis showed a 2–3 month lagged effects of temperature on mangroves’ growth, with precipitation having minimal impact. The proposed OMPEA improves the possibility of capturing mangrove phenology under non-continuous and low-resolution data, providing valuable insights for large-scale and long-term mangrove conservation and management. Full article

This study addresses the issue of atmospheric delay correction for the rational polynomial coefficient (RPC) model associated with spaceborne synthetic aperture radar (SAR) imagery under conditions lacking ephemeris data, proposing a novel approach to enhance the geometric positioning accuracy of RPC models. A satellite position inversion method based on the vector-autonomous intersection technique was developed, incorporating ionospheric delay and neutral atmospheric delay models to derive atmospheric delay errors. Additionally, an RPC model reconstruction approach, which integrates atmospheric correction, is proposed. Validation experiments using GF-3 satellite imagery demonstrated that the atmospheric delay values obtained by this method differed by only 0.0001 m from those derived using the traditional ephemeris-based approach, a negligible difference. The method also exhibited high robustness in long-strip imagery. The reconstructed RPC parameters improved image-space accuracy by 18–44% and object-space accuracy by 19–32%. The results indicate that this approach can fully replace traditional ephemeris-based methods for atmospheric delay extraction under ephemeris-free conditions, significantly enhancing the geometric positioning accuracy of SAR imagery RPC models, with substantial application value and development potential. Full article

Estuarine wetlands are the transition zone between marine, freshwater, and terrestrial ecosystems and are more ecologically fragile. In recent years, the spread of exotic vegetation, specifically Spartina alterniflora, in the Yellow River estuary wetlands has significantly encroached upon the habitats of native species such as Phragmites australis, Suaeda glauca Bunge, and Tamarix chinensis Lour. With advances in land prediction modeling, predicting wetland vegetation distribution can aid management and decision-making for ecological restoration. We selected the core area as the study object and coupled the hydrological model MIKE 21 with the PLUS model to predict the potential future distribution of invasive and dominant species in the region. (1) Based on the fine classification results from satellite images of GF1/G2/G5, we gained an understanding of the changes in wetland vegetation types in the core area of the reserve in 2018 and 2020. (2) Using public data such as ERA5 and GEO as input for basic environmental data, using MIKE 21 to provide high-spatial-resolution hydrodynamic parameters for the PLUS model as an environmental driver, we modeled the spatial distribution of various wetland vegetation in the Yellow River estuary wetland in Dongying under different artificial restoration measures. (3) We predicted the 2022 distribution of typical vegetation in the region, used the classification results of GF6 as the actual distribution, compared the spatial distribution with the actual distribution, and obtained a kappa coefficient of 0.78; the predicted values of the model are highly consistent with the true values. This study combines the fine classification results of vegetation based on hyperspectral remote sensing, the construction of a coupled model, and the prediction effect of typical species, providing a reference for constructing and optimizing the vegetation prediction model of estuarine wetlands. It also allows scientific and effective decision-making for the management of ecological restoration of delta wetlands. Full article

The insecticidal Cry proteins from Bacillus thuringiensis are used in biopesticides or transgenic crops for pest control. The Cry1I protein family has unique characteristics of being produced during the vegetative rather than sporulation phase, its protoxins forming dimers in solution, and exhibiting dual toxicity against lepidopteran and coleopteran pests. The Cry1Ia protoxin undergoes sequential proteolysis from the N- and C-terminal ends, producing intermediate forms with insecticidal activity, while in some cases, the fully processed toxin is inactive. We investigated the oligomerization and toxicity of Cry1Ia intermediate forms generated through trypsinization (T-Int) and larval gut fluid (GF-Int) treatments, as well as the fully trypsinized protein (toxin). Heterologously expressed intermediate forms assembled into oligomers and showed similar toxicity to Cry1Ia protoxin against Ostrinia nubilalis (European corn borer) larvae, while the toxin form was ~30 times less toxic. In contrast, bioassays with Leptinotarsa decemlineata (Colorado potato beetle) larvae did not show significant differences in toxicity among Cry1Ia protoxin, T-Int, GF-Int, and fully processed toxin. These results suggest that the Cry1I mode of action differs by insect order, with N-terminal cleavage affecting toxicity against lepidopteran but not coleopteran larvae. This knowledge is essential for designing pest control strategies using Cry1I insecticidal proteins. Full article

The increasing salinization of cultivated soil worldwide has led to a significant reduction in maize production. Using saline–alkaline-tolerant growth-promoting bacteria (PGPR) in the rhizosphere can significantly improve the saline tolerance of maize and ensure the stability of maize yields, which has become a global research hotspot. This study screened salt-tolerant microorganisms Klebsiella sp. (GF2) and Pseudomonas sp. (GF7) from saline soil to clarify the mechanism in improving the saline tolerance of maize. In this study, different application treatments (GF2, GF7, and GF2 + GF7) and no application (CK) were set up to explore the potential ecological relationships between the saline tolerance of maize seedlings, soil characteristics, and microorganisms. The results showed that co-occurrence network and Zi-Pi analysis identified Klebsiella and Pseudomonas as core microbial communities in the rhizosphere soil of maize seedlings grown in saline soil. The deterministic process of microbial assembly mainly controlled the bacterial community, whereas bacteria and fungi were governed by random processes. The application of saline–alkaline-resistant PGPR under saline stress significantly promoted maize seedling growth, increased the activity of soil growth-promoting enzymes, and enhanced total nitrogen, soil organic carbon, and microbial carbon and nitrogen contents. Additionally, it reduced soil salt and alkali ion concentrations [electrical conductivity (EC) and exchangeable Na⁺]. Among them, GF2 + GF7 treatment had the best effect, indicating that saline–alkaline-tolerant PGPR could directly or indirectly improve the saline tolerance of maize seedlings by improving the rhizosphere soil ecological environment. EC was the determining factor to promote maize seedling growth under saline–alkaline stress (5.56%; p < 0.01). The results provided an important theoretical reference that deciphers the role of soil factors and microecology in enhancing the saline tolerance of maize. Full article

Despite the potential of glass fiber (GF) membranes for oil-water emulsion separations, efficient surface modification methods to enhance fouling resistance while preserving membrane performance and stability remain lacking. We report a silica nanocoating method to modify GF membranes through a vapor deposition method. The high smoothness (<1 nm r.m.s.) and high conformality of the vapor-deposited silica nanocoatings enabled the preservation of membrane microstructure and permeability, which, combined with the enhanced surface hydrophilicity, led to an oil rejection rate exceeding 99% and more than a 40% improvement in permeate flux in oil-water emulsion separations. Furthermore, the silica nanocoatings provided the membranes with excellent wet strength and stability against organic solvents, strong acids, oxidants, boiling, and sonication. The silica-nanocoated membrane demonstrated enhanced fouling resistance, achieving flux recovery higher than 75% during repeated oil-water emulsion separations and bovine serum albumin and humic acid fouling tests. Full article

It is shown that it is reasonable to use Galois fields, including those obtained by algebraic extensions, to describe the position of a point in a discrete Cartesian coordinate system in many cases. This approach is applicable to any problem in which the number of elements (e.g., pixels) into which the considered fragment of the plane is dissected is finite. In particular, it is obviously applicable to the processing of the vast majority of digital images actually encountered in practice. The representation of coordinates using Galois fields of the form GF(p²) is a discrete analog of the representation of coordinates in the plane through a complex variable. It is shown that two different types of algebraic extensions can be used simultaneously to represent transformations of discrete Cartesian coordinates described through Galois fields. One corresponds to the classical scheme, which uses irreducible algebraic equations. The second type proposed in this report involves the use of a formal additional solution of some equation, which has a usual solution. The correctness of this approach is justified through the representation of the elements obtained by the algebraic expansion of the second type by matrices defined over the basic Galois field. It is shown that the proposed approach is the basis for the development of new methods of information protection, designed to control groups of UAVs in the zone of direct radio visibility. The algebraic basis of such methods is the solution of systems of equations written in terms of finite algebraic structures. Full article

In recent years, machine learning methods have garnered significant attention in the field of crop recognition, playing a crucial role in obtaining spatial distribution information and understanding dynamic changes in planting areas. However, research in smaller plots within mountainous regions remains relatively limited. This study focuses on Shangzhou District in Shangluo City, Shaanxi Province, utilizing a dataset of high-resolution remote sensing images (GF-1, ZY1-02D, ZY-3) collected over seven months in 2021 to calculate the normalized difference vegetation index (NDVI) and construct a time series. By integrating field survey results with time series images and Google Earth for visual interpretation, the NDVI time series curve for maize was analyzed. The Random Forest (RF) classification algorithm was employed for maize recognition, and comparative analyses of classification accuracy were conducted using Support Vector Machine (SVM), Gaussian Naive Bayes (GNB), and Artificial Neural Network (ANN). The results demonstrate that the random forest algorithm achieved the highest accuracy, with an overall accuracy of 94.88% and a Kappa coefficient of 0.94, both surpassing those of the other classification methods and yielding satisfactory overall results. This study confirms the feasibility of using time series high-resolution remote sensing images for precise crop extraction in the southern mountainous regions of China, providing valuable scientific support for optimizing land resource use and enhancing agricultural productivity. Full article

Flexible strain sensors have attracted significant attention due to their critical applications in wearable devices, biological detection, and artificial intelligence. However, achieving both a wide strain range and high sensitivity remains a major challenge in current research. This study aims to develop a novel composite material with a synergistic conductive network to construct high-performance flexible strain sensors. Thermoplastic polyurethane (TPU) nanofiber membranes were first prepared using electrospinning technology, and their surface was modified with polydopamine (PDA) via in-situ polymerization, which significantly enhanced the fibers’ adsorption capacity for conductive materials. Subsequently, carbon nanotubes (CNTs) and carbon black (CB) were coated onto the PDA-modified TPU fibers through ultrasonic anchoring, forming a CB/CNT/PDA/TPU composite with a synergistic conductive network. The results demonstrated that the flexible strain sensor fabricated from this composite material (with a CB-to-CNT mass ratio of 7:3) achieved ultrahigh sensitivity (gauge factor, GF, up to 1063) over a wide strain range (up to 300%), along with a low detection limit (1% strain), fast response and recovery times (137 ms), and exceptional stability and durability. Further evaluations confirmed that this sensor reliably captured biological signals from various joint movements, highlighting its broad application potential in human motion monitoring, human–machine interaction, and soft robotics. Full article

Cutaneous leishmaniasis caused by Leishmania amazonensis is a significant public health issue. This study aimed to evaluate an ecofriendly, thermosensitive nanogel, developed using a low-energy, solvent-free method, incorporating F127 and Carbopol 974P copolymers, and enriched with Pectis brevipedunculata essential oil (EOPb) for its leishmanicidal and anti-inflammatory properties. The nanogel was prepared and characterized through FTIR, DLS, SEM, and AFM to confirm the incorporation of EOPb as well as its stability and rheological properties. In vitro leishmanicidal activity was evaluated on Leishmania amazonensis promastigotes, and in vivo anti-inflammatory effects were assessed using a rat paw edema model. In vitro, nGF3 (EOPb-loaded nanogel) demonstrated significant leishmanicidal activity, with promastigote mortality rates exceeding 80% at 24 h and 90% at 48 h. In vivo, nGF1, nGF2, and nGF3 exhibited anti-inflammatory effects, with nGF2 and nGF3 reducing edema by 62.7% at 2 h post-treatment. The empty nanogel (nGF0) showed minimal anti-inflammatory activity. The ecofriendly EOPb-loaded nanogel (nGF3) demonstrated strong leishmanicidal and anti-inflammatory effects, presenting a promising candidate for cutaneous leishmaniasis treatment. Further studies are necessary to explore its clinical potential. Full article