Search Results (2,724)

Leaf Area Index (LAI) is the total leaf area per unit of land surface area and is a crucial parameter for assessing vegetation growth and productivity. Machine learning regression algorithms are widely applied for LAI estimation. Due to spectral response variations among sensors and susceptibility of mangrove-derived variables to environmental noise suppression, obtaining sensitivity indices and optimal machine learning regression models is essential for retrieving mangrove LAI at the population scale. This study proposes a novel approach to processing and retrieving mangrove LAI data by integrating multispectral indices with machine learning methods. Box–Cox transformation and CatBoost-based feature selection were employed to obtain the optimal dataset. Random Forest (RF), Gradient Boosting Regression Trees (GBRT), and Categorical Boosting (CatBoost) algorithms were used to evaluate the accuracy of LAI retrieval from Unmanned Aerial Vehicle (UAV) and Gaofen-6 (GF-6) data. Results indicate that when LAI > 3, LAI does not immediately saturate as CVI, MTVI 2, and other indices increase, demonstrating higher sensitivity. UAV data outperformed GF-6 data in retrieving LAI for diverse mangrove populations; during model training, RF proved more suitable for small-sample datasets, while CatBoost effectively suppressed environmental noise. Both RF and CatBoost demonstrated higher robustness in estimating Avicennia marina (AM) (RF: R² = 0.704) and Aegiceras corniculatum (AC) (R² = 0.766), respectively. Spatial distribution analysis of LAI indicates that healthy AM and AC cover 85.36% and 96.67% of the area, respectively. Spartina alterniflora and aquaculture wastewater may be among the factors affecting the health of mangrove forests in the study area. LAI retrieval holds significant importance for mangrove health monitoring and risk early warning. Full article

This study investigates the mechanical performance and surface morphology of polyamide-based materials commonly used in plastic injection molding. Two resins, PA6 and PA66, were analyzed in both neat and 20 wt% glass fiber-reinforced (GF20) forms. The influence of reinforcement and material type on tensile strength and ductility was examined through integrated experimental and numerical approaches, complemented by microstructural and elemental analyses. PA6 and PA66 specimens were produced in accordance with ISO 527, and tensile tests revealed a significant increase in elastic modulus and tensile strength with glass fiber reinforcement, accompanied by a reduction in elongation at break. Flammability was evaluated via Glow Wire and Tracking tests. SEM–EDS analyses provided insights into fracture morphology and elemental distribution, showing that fiber–matrix interfacial debonding and fiber pull-out dominated failure in reinforced specimens, whereas neat polymers exhibited homogeneous surfaces. Finite element simulations performed in ANSYS Explicit Dynamics supported the experimental findings by identifying stress concentration zones and failure initiation regions. Although numerical simulations successfully captured stress distribution trends, quantitative differences were attributed to idealized modeling assumptions and processing-induced microstructural effects. Overall, this work provides a comprehensive assessment of the reinforcement effects in PA6 and PA66 systems, offering valuable guidance for material selection and design optimization in polymer-based engineering components. Full article

The Hatu region in the Western Junggar, Xinjiang, is one of the most significant gold metallogenic concentration areas in China. Gold mineralization is primarily controlled by several parallel NE-trending strike-slip faults and Late Paleozoic granitic plutons, accompanied by multiple stages of hydrothermal activity. To enhance the objectivity and accuracy of mineral prospecting prediction, this study develops an integrated forecasting framework that combines multi-source remote sensing datasets with machine learning techniques. Alteration anomalies related to iron staining and hydroxyl-bearing minerals are extracted from ASTER data, alteration mineral mapping is performed using GF-5 hyperspectral imagery, and Landsat-9 data is used for structural interpretation to refine the regional metallogenic framework. On this basis, these multi-source remote sensing products are then integrated to delineate five prospective metallogenic areas (T1–T5). Subsequently, a Random Forest (RF) model optimized by the Grey Wolf Optimizer (GWO) algorithm is employed to quantitatively integrate key evidence layers, including alteration, structure, and geochemistry, for estimating mineralization probability. The results show that the GWO-RF model effectively concentrates anomalous areas and identifies two high-confidence targets, Y1 and Y2, both with mineralization probabilities exceeding 0.8. Among them, the Y1 target is associated with the Bieluagaxi pluton and exhibits strong montmorillonitization, chloritization, and iron-staining alteration, typical for magmatic–hydrothermal controlled mineralization. In contrast, the Y2 target is strictly controlled by the Anqi Fault and its subsidiary faults, primarily characterized by linear chloritization and iron-staining anomalies indicative of structure–hydrothermal mineralization. Field verification confirms the significant metallogenic potential of both Y1 and Y2, demonstrating the effectiveness of integrating multi-source remote sensing and machine learning for predicting orogenic gold systems. This approach not only deepens the understanding of the diverse gold mineralization processes in the Western Junggar but also provides a transferable methodology and case study for improving regional mineral exploration accuracy. Full article

Rotating scanning systems are capable of acquiring ultra-wide swath satellite imagery, but they suffer from significant positioning accuracy degradation due to complex geometric distortions and the difficulty of obtaining ground control points (GCPs) over vast areas. To address these issues, this paper proposes a precise positioning method based on multi-source satellite data fusion. By comprehensively utilizing high-resolution images from ZY-3 and GF-2 satellites alongside DEM data, we establish a framework that integrates grid-based feature point extraction, high-precision matching, and multi-image joint adjustment. Specifically, we introduce a matching strategy combining geometric constraints with Least Squares Minimization (LSM) and a robust joint adjustment model to suppress geometric distortions. Experimental validation was conducted using a dataset covering the Beijing area. The results demonstrate that after joint adjustment, the planar accuracy of the imagery reached 4.01 m, and the edge matching Root Mean Square Error (RMSE) between adjacent images was 2.52 m. Furthermore, the cooperative positioning accuracy for segmented simulation data achieved 4.68 m in mountainous areas and 5.22 m in plain areas, meeting the requirements for meter-level positioning. These results verify the effectiveness of multi-source cooperative adjustment in correcting geometric distortions and significantly improving the positioning accuracy of rotating scanning imagery. Full article

Carbon fibre-reinforced polymer (CFRP) bonded steel structures are increasingly adopted in offshore floating structures, yet their interfacial performance is highly susceptible to corrosion in marine environments. Corrosion-induced degradation of the CFRP–steel interface can significantly affect load transfer mechanisms and long-term structural reliability. This paper reports an experimental study on corrosion-induced degradation mechanisms and bond–slip behaviour of CFRP–steel double-strap joints. Controlled corrosion damage was generated using an accelerated electrochemical technique calibrated to ISO 9223 corrosivity categories. Tension tests were performed to examine the effects of corrosion degree, CFRP bond length, and the inclusion of glass fibre sheets (GFS) in the adhesive layer on failure modes, ultimate load capacity, and effective bond length. Digital image correlation (DIC) was employed to obtain strain distributions along the CFRP plates and to establish a bond–slip model for corroded interfaces. The results indicate that corrosion promotes a transition from CFRP delamination to steel–adhesive interface debonding, reduces interfacial shear strength to 17.52 MPa and fracture energy to 5.49 N/mm, and increases the effective bond length to 130 mm. Incorporating GFS mitigates corrosion-induced bond degradation and enhances joint performance. The proposed bond–slip model provides a basis for more reliable durability assessment and design of bonded joints in corrosive environments. Full article

In permanent magnet synchronous motor (PMSM) drive systems, the nonlinearity of the inverter and non-sinusoidal nature of back EMF generate harmonics in the stator current, resulting in torque ripple and reduced motor efficiency. Although the proportional resonant (PR) controller is widely employed for harmonic suppression, the standard resonant controller is constrained by its narrow bandwidth and can only suppress a single harmonic order. To address these issues, an adaptive harmonic suppression strategy using a proportional multi-resonant (PMR) controller based on the generalized frequency selector (GFS) is proposed. Firstly, the sources and characteristics of the stator current harmonics were analyzed based on the mathematical model of PMSM. Subsequently, a proportional resonance controller was designed according to the tracking filtering characteristics of the GFS, and a proportional multi-resonance controller targeting multi-order harmonics was constructed. The stability of the current closed-loop system under the algorithm was analyzed. Finally, simulation and experimental results demonstrated that the proposed algorithm effectively suppressed current harmonics and significantly improved the current waveform. Full article

This work proposes a generic model for clarifying the mechanism hidden in the phenomena of fluctuation propagation in grid-forming (GF-VSG) systems, considering the impact of different disturbances. Additionally, a new judgment criterion is established to give physical insights into the power oscillation stability of the GFMC system. And this judgment criterion, as well as the model, can identify the power stability combined with fluctuation propagation phenomenon no matter what the disturbance is, which can also give guidance to the controller design to guarantee that the GFMC can operate in normal operation conditions while leisurely confronting various disturbances. In addition, it is found that the established conventional single closed-loop system may lose effectiveness in judging stability, especially when the oscillation propagation of disturbance occurs. Finally, the proposed model and judgment criteria are demonstrated by experiments. Full article

Flooding episodes caused by a heavy rainfall event have become more frequent, especially during the rainfall season in Botswana, which poses some socio-economic and environmental risks. This study investigates the capability of the Weather Research and Forecasting (WRF) model in simulating a heavy rainfall event that occurred on 26 December 2023 in Mahalapye District, Botswana. This event is one among many that have negatively impacted the lives and infrastructures in Botswana. The WRF model was configured using the tropical-suite physics schemes, i.e., (Rapid Radiative Transfer Model, Yonsei University planetary boundary layer scheme, Unified Noah land surface model, New Tiedtke, Weather Research and Forecasting Single-Moment six-class) on a two-way nested domain (9 km and 3 km grid spacing) and was initialized with the GFS dataset. Gauged station data was used for verification alongside synoptic charts generated using ECMWF ERA5 dataset. The results show that the WRF model simulation using the tropical-suite physics schemes is able to reproduce the spatial and temporal patterns of the observed rainfall but with some notable biases. Performance metrics, including RMSE, correlation coefficient, and KGE, showed moderate to good agreement, highlighting the model’s sensitivity to physical parameterization and resolution. The results of this study conclude that the WRF model demonstrates promising potential in forecasting extreme rainfall events in Botswana, but more sensitivity tests to different parameterization schemes are needed in order to integrate the model into the early warning systems to enhance disaster preparedness and response. Full article

While standard anti- vascular endothelial growth factor (VEGF) therapy, with or without photodynamic therapy (PDT), is effective for patients with polypoidal choroidal vasculopathy (PCV), not all achieve optimal visual outcomes. This study aimed to compare fortified (double the dose and the volume of the standard one) anti-VEGF combined with PDT versus fortified anti-VEGF monotherapy and to investigate biomolecular profiles and disease relationships among PCV, neovascular age-related macular degeneration (nvAMD), and central serous chorioretinopathy (CSCR). The goal was to identify novel pathways to inform future therapeutic strategies, including hypoxia-inducible factors (HIF)-1α inhibitors. This retrospective cohort study included 23 eyes with indocyanine green-confirmed type C PCV. One eye treated with transpupillary thermotherapy was not included in the following two groups. Patients received either combined therapy (PDT + fortified-dose anti-VEGF; n = 12) or fortified-dose anti-VEGF monotherapy (n = 10). Primary outcomes were changes in best-corrected visual acuity (BCVA) and central retinal thickness (CRT). Secondary outcomes included injection burden and recurrence. Exploratory analyses examined aqueous biomarkers, including VEGF, placental growth factor (PlGF), β-catenin, HIF-1α, and Wnt1 across PCV, CSCR, and nvAMD to identify novel therapeutic targets. Significant (p = 0.003/p = 0.005) median CRT reduction was similar (p = 0.468) between groups (combined/monotherapy: 137.5 µm/106.5 µm). BCVA (median [Q1, Q3]) change in logarithm of the minimum angle of resolution (LogMAR) was not statistically significant (p = 0.279), with 0.25 [0.00, 0.98] in the combined group versus 0.00 [−0.03, 0.28] in the monotherapy group. Treatment burden of anti-VEGFs per person per year was lower with combined therapy (1.16 ± 0.47# PDT + 2.81 ± 0.92# anti-VEGF injections) compared with monotherapy (4.61 ± 1.49# injections). Six eyes demonstrated recurrence at a mean of 15.5 months. Incomplete regression of polyps and branching vascular networks was observed in all eyes. Exploratory biomarker analysis revealed significantly (p < 0.05) higher VEGF and PlGF levels in nvAMD compared with PCV. nvAMD also demonstrated significantly (p < 0.05) higher β-catenin and lower HIF-1α levels relative to PCV and CSCR, while no significant biomarker differences were observed between PCV and CSCR. Combined therapy or monotherapy with fortified anti-VEGFs reduced treatment burden and achieved significant anatomical improvement but did not yield superior functional outcomes, highlighting the therapeutic difficulty of type C PCV. Biomarker profiling revealed shared hypoxia-related mechanisms between PCV and CSCR, with elevated HIF-1α compared to nvAMD indicating a “preliminary” possible role for HIF-1α inhibitors. Differential expression of these biomarkers highlights additional molecular pathways that may inform future targeted interventions. Full article

Urban agglomerations are concentrated production areas of new-quality productivity (NQP), and developing NQP is an inevitable requirement and obligation to promote the high-quality development of urban agglomerations. It is of great concern whether green finance (GF) can serve as a catalyst in promoting the formation and development of NQP in urban agglomerations. This study selects panel data from 41 cities in the Yangtze River Delta urban agglomeration spanning 2011–2023 to construct a comprehensive indicator system for NQP based on the composition, quality, and function of productive factors in the urban agglomeration, and explores the impact effects, mechanisms of action, spatial spillover effects, and heterogeneity of GF on the development of NQP using a two-way fixed-effects model, an intermediary effect model, and a spatial Durbin model (SDM). The empirical results indicate the following: (1) GF can significantly promote the development of NQP in the Yangtze River Delta urban agglomeration, and there is a significant positive spatial spillover effect. The above conclusions remain valid after a series of robustness tests and endogeneity treatments. (2) The mechanism tests find that industrial structure upgrading and environmental regulation play positive mediating roles in GF’s promotion of NQP development in urban agglomerations. (3) The impact of GF on NQP exhibits significant heterogeneity. In regions with higher levels of economic and financial development, as well as a higher degree of marketization, the promotional effect of GF on NQP is more pronounced. In terms of city size and geographical location, the empowering effect and spatial spillover effect of GF on NQP are more evident in prefecture-level cities and the northern plain area of the Yangtze River Delta. Therefore, it is recommended to implement differentiated GF policies to promote the development of NQP in the Yangtze River Delta urban agglomeration through regional cooperation, green technology innovation, industrial transformation and upgrading, and environmental regulation. Full article

Climate-induced lake expansion on the Tibetan Plateau (TP) has led to two distinct hazard types: outburst floods and passive inundation. However, the divergent driving mechanisms behind these hazards remain insufficiently understood. This study analyzes the spatiotemporal trends of 1352 non-glacial lakes (>1 km²) on the TP from 2014 to 2023 using high-resolution Gaofen-1 (GF-1) and Gaofen-2 (GF-2) imagery. By integrating geomorphic analysis with hazard mechanisms, we screened and categorized lakes prone to outburst floods and inundation using a classification and assessment framework proposed in this study. The results indicate that the net area of these lakes expanded by 2839.53 km² (6.07%), with the Inner TP Basin contributing the largest absolute area gain (1960.60 km²). We identified 21 potentially hazardous lakes (10 outburst-prone and 11 inundation-prone) and systematically categorized them by risk level. Field investigations of high-risk candidates, such as Rulei Co and Xiao Qaidam Lake, validated the accuracy of the hazard classification and risk assessment methodology. Preliminary attribution analysis further suggests that the two hazard types may be associated with distinct climatic factors. Overall, this study provides a scientific basis for disaster mitigation and lake management on the TP. Full article

Accurate quantification of forest aboveground biomass (AGB) is essential for monitoring terrestrial carbon stocks. While total AGB estimation is widely practiced, resolving component biomass such as canopy, branches, leaves, and trunks enhances the precision of carbon sink assessments and provides critical structural parameters for ecosystem modeling. Most studies rely on a single SAR sensor or a limited range of SAR features, which restricts their ability to represent vegetation structural complexity and reduces biomass estimation accuracy. Here, we propose a phased fusion strategy that integrates backscatter intensity, interferometric coherence, texture measures, and polarimetric decomposition parameters derived from dual-frequency ALOS-2, GF-3, and Sentinel-1A SAR data. These complementary multi-dimensional SAR features are incorporated into a Random Forest model optimized using an Adaptive Genetic Algorithm (RF-AGA) to estimate forest total and component estimation. The results show that the progressive incorporation of coherence and texture features markedly improved model performance, increasing the accuracy of total AGB to R² = 0.88 and canopy biomass to R² = 0.78 under leave-one-out cross-validation. Feature contribution analysis indicates strong complementarity among SAR parameters. Polarimetric decomposition yielded the largest overall contribution, while L-band volume scattering was the primary driver of trunk and canopy estimation. Coherence-enhanced trunk prediction increased R² by 13 percent, and texture improved canopy representation by capturing structural heterogeneity and reducing saturation effects. This study confirms that integrating coherence and texture information within the RF-AGA framework enhances AGB estimation, and that the differential contributions of multi-dimensional SAR parameters across total and component biomass estimation originate from their distinct structural characteristics. The proposed framework provides a robust foundation for regional carbon monitoring and highlights the value of integrating complementary SAR features with ensemble learning to achieve high-precision forest carbon assessment. Full article

The aims of this study were to evaluate the impact of probiotics (added as a starter sourdough and microcapsules) on gluten-free (GF) rice–amaranth steamed bread (SB) regarding physicochemical characteristics, sensory attributes, probiotic viability, and volatile organic compounds (VOCs). Also, probiotic viability, pH, total titratable acidity (TTA), moisture content, water activity, and texture were determined for 10 days of storage. GF-SB based on rice and amaranth was formulated and cooked at 90 ± 2 °C for 40 min. Three types of GF-SB were studied: control, with 30% sourdough fermented using Lactiplantibacillus plantarum NRRL B-4496 (GF-P), and with sourdough and encapsulated Limosilactobacillus reuteri DSM 17938 (GF-PC). The encapsulation yield was 94.9%. The viability of both probiotics was drastically reduced after steamed cooking, with losses ranging from 6 to 8 log₁₀ CFU/g. Sourdough decreased the pH (from 6.04 to 5.48–5.71) and hardness (control 46 N, sourdough ~25 N) while increasing lactic and acetic acids, moisture content (control 38%, sourdough ~46%), and water activity. Sourdough and probiotic capsules did not affect volume (~1.24 cm³/g), width-to-height ratio (~2.4), color, or sensory attributes. The VOCs revealed higher relative abundances of certain yeast-derived higher alcohols and oxidation-related carbonyl-trapping derivatives in control GF-SB, whereas bread with sourdough showed higher levels of long-chain hydrocarbons and esters, such as heptacosane and decanoic acid decyl ester. During the storage, Lpb. plantarum increased to ~3 log₁₀ CFU/g and Lim. reuteri remained steady. pH and TTA (0.03–0.04%) remained constant during storage. After 10 days of storage, hardness increased significantly (p < 0.05) in all GF-SB, doubling the initial values. Moisture content remained constant, while water activity decreased in GF-P (Δ = 0.025) and the control (Δ = 0.015). The use of sourdough in GF-SB improved texture, moisture content, and VOCs without modifying physical and sensory properties. Full article

In the present study, glass/ceramic hybrid fibers were chosen as a paper matrix, which effectively balance toughness and high-temperature resistance for soot combustion applications. In order to address the issue of unevenness in the performance of paper-type catalysts caused by the differences in the dispersion behavior of glass fibers and ceramic fibers in water, a facile foam-forming technology was proposed. The obtained glass fiber/mullite composite paper with various mass ratios (1:1, 2:1, 3:1, 4:1, and 5:1) exhibit high evenness, and better high-temperature resistance than the pure glass fibers. After impregnating K-Mn active ingredients, 15K5Mn-GFF-3G1C (GF/CF = 3:1) demonstrates high tensile strength, excellent catalytic activity (T50 = 388 °C), reusability (five cycles), and high-temperature stability (800 °C, 12 h). Full article

Promoting the synergistic development of green finance (GF) and green technology innovation (GTI) is crucial for achieving sustainable economic development. Based on the sample data of 30 provinces in China from 2010 to 2023, this study first investigates the theoretical mechanism of interactive coupling and then employs methods including Dagum Gini coefficient, spatial kernel density estimation, spatial correlation analysis, and a GTWR model to explore the spatiotemporal pattern, evolution trend, and driving factors of the coupling coordination between GF and GTI. The findings are as follows: (1) The coupling coordination degree (CCD) is about to transition from the moderate imbalance stage to the near imbalance stage, presenting a distinct spatial pattern of “higher levels and faster development in the east, and lower levels and slower development in the west”. (2) The Gini coefficient of the CCD shows an upward trend, with the degree of imbalance increasing year by year; the main sources of the overall differences follow this order: intra-regional disparity (G_w) > inter-regional disparity (G_b) > transvariation density (G_t). (3) The CCD between GF and GTI exhibits a positive spatial correlation, and the agglomeration degree is constantly increasing; the High-High Cluster areas are mainly concentrated in northern China. (4) Economic development level, financial development level, population scale, and urbanization level drive the coupling coordination between GF and GTI. This study provides new theoretical and empirical evidence for the complex coupling relationship and driving factors of GF and GTI and offers a key scientific basis for the Chinese government to formulate differentiated regional policies, thereby promoting the effective implementation of the green and low-carbon development strategy. Full article