Search Results (245)

This study evaluated the effectiveness of maleic anhydride polypropylene (MAPP) in improving the mechanical performance and interfacial adhesion of lignocellulosic fiber-reinforced polypropylene (PP) composites. Based on Scanning Electron Microscopy (SEM) investigations, the relationship between fiber fraction, MAPP content, mechanical characteristics, and fracture morphology was the main focus. The test results showed that the stiffness and tensile strength of the composites increased with the addition of MAPP. The esterification reaction between the anhydride groups of MAPP and the hydroxyl groups of the fibers strengthened the interphase covalent bond, with the 46:50:4 composition producing the highest elastic modulus of 79.67 MPa and maximum tensile stress of 11.01 MPa. The dense interphase zone, few gaps, and no dominant fiber tension were all confirmed by SEM morphology, and also indicated effective stress transfer from the PP matrix to the fibers. However, the toughness of the material decreased significantly with increasing stiffness. Due to strong plastic deformation in the PP matrix that is not tightly attached to the fibers, the composition without MAPP (30:70:0) shows high impact energy and breaking strain, reaching 25.39 kJ/m² and 121.26%, respectively. The increase in chemical bonding at 4% MAPP content limits the mobility of the polymer chains, making it more brittle. In addition, even though MAPP is still present in the system, increasing the fiber fraction above 60% causes agglomeration, decreased homogeneity, and increased voids due to limited matrix wetting, ultimately deteriorating the mechanical properties. Tensile stress and elastic modulus have a very strong positive correlation (R² = 0.93), while impact energy and strain have a good correlation (R² = 0.89). The results overall showed that the ideal MAPP dosage is in the range of 4% before interface saturation occurs and confirmed that MAPP efficiency is determined by the balance between fiber composition, MAPP quantity, and dispersion homogeneity. Full article

Cooperative localization for multi-Unmanned Aerial Vehicle (UAV) systems in GPS-degraded environments is often compromised by ideal-communication or uniform-quality assumptions. This paper proposes Quality-Aware Distributed State Estimation (QA-DSE), which combines three operational quality factors—freshness (Age of Information), accuracy (covariance trace), and link reliability (packet loss and channel noise)—into a single multiplicative score $q_{ij}$, modulated by a bounded history-consistency factor based on velocity-propagated self-trajectory continuity. A dual-constraint AND-gate on AoI and covariance trace excludes jointly degraded neighbors, while admitted neighbors are fused through a quality-squared information-matrix update under a stated bounded residual cross-correlation assumption, with an adaptive Covariance-Intersection fallback when the assumption is stressed. Under explicit observability, bounded-noise, bounded-quality, joint-connectivity, and bounded residual cross-correlation assumptions, we establish mean-square bounded error, exponential convergence at a rate inherited from the Kalman update operator, $O\left(n^3+nm\right)$ per-step complexity, Bounded-Input Bounded-Output (BIBO) stability, soft attenuation of single-axis faults (Theorem 4), and hard exclusion under joint AoI–covariance violation (Theorem 5). Under a Ultra-Wideband (UWB)-style cooperative-observation model, Monte Carlo experiments across five scenarios show 74.08–74.24% position- Root Mean Square Error (RMSE) reductions over Covariance Intersection, with the relative advantage held within 73.04–74.24% as the fleet scales from 3 to 50 UAVs; QA-DSE remains within 8.1% of an idealized no-cooperation single-vehicle Kalman filter, demonstrating graceful degradation rather than improvement above that floor. Per-step Central Processing Unit (CPU) time scales from 0.09 ms (5 UAVs) to 0.31 ms (50 UAVs); embedded validation is left to future work. Full article

This study investigates ecosystem service valuation on Zhoushan Island. Based on Landsat remote sensing images for 2000, 2010, and 2020 acquired through the Google Earth Engine (GEE) platform, six land use types are extracted using the Random Forest method. By integrating land use dynamic degree, transfer matrix, ecosystem service value (ESV) accounting, and five-level land–sea gradient zoning approaches, this study systematically analyzes the spatiotemporal evolution of land use and its effects on ESV over the 20-year period, and reveals the spatial differentiation pattern of land use change and ESV gains and losses along the land–sea gradient. The results indicate that from 2000 to 2020, water bodies and cultivated land on Zhoushan Island experienced continuous decline while construction land expanded rapidly, driven by policy regulation, urbanization, and industrial transformation. Localized coastal areas exhibited a typical chain conversion process of “water body → bare land → construction land,” which is closely associated with reclamation and land reclamation activities. Regional ESV declined continuously, reaching only 56.7% of its 2000 level by 2020, with regulating and provisioning services exhibiting the most pronounced deterioration. Analysis of the ESV net transfer matrix indicates that the primary driver of ESV decline was the large-scale conversion of high-value water bodies to low-value construction land and bare land, the magnitude of which far exceeded the positive ecological gains generated by all other land use conversions. The reduction in cultivated land area, compounded by adjustments in cropping structure, has placed sustained pressure on regional food security, and policy responses have lagged considerably behind the pace of ecological degradation. In terms of spatial differentiation, both the intensity of land use change and ESV loss exhibited a gradient pattern that decreases progressively from the coastal zone moving inland. Zone 1 and Zone 2 in the nearshore area together accounted for approximately 80% of total ESV loss, whereas Zone 4 and Zone 5 maintained relatively stable land use structures and ecological support capacity, owing to higher forestland coverage. Spearman’s rank correlation analysis confirmed a statistically significant monotonically decreasing relationship between land use dynamic degree and coastal distance. Policy regulation served as the primary driver of regional land use pattern evolution: early sea reclamation policies facilitated rapid land transformation along the coastline, while subsequent tightening of controls effectively curbed disorderly expansion. Full article

(1) Background: Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide. Aberrant remodeling of the extracellular matrix (ECM) is a hallmark of GC progression; however, the mechanisms by which GC cells sense and exploit ECM cues remain unclear. (2) Methods: ITGA11 was identified through integrative bioinformatic analyses. Its expression, clinical significance, and association with ECM-related signatures were evaluated in GC tissues and public datasets. The function of ITGA11 and its role in regulating the FAK/PI3K/AKT/mTOR pathway were investigated using in vitro and in vivo assays, and the inhibitory effect of Naringenin on ITGA11-associated oncogenic activity was assessed. (3) Results: ITGA11 was upregulated in GC tissues and correlated with an ECM-related gene signature, aggressive clinicopathological features and poor patient survival. ITGA11 promoted malignant phenotypes of GC cells in vitro and in vivo. Importantly, molecular docking and target engagement assays suggested a potential interaction between Naringenin and ITGA11. Functional experiments showed that Naringenin attenuated ITGA11-associated oncogenic activity by reducing ITGA11 levels, suppressing pathway activation, and inhibiting malignant phenotypes. (4) Conclusions: Our findings identify ITGA11 as a potential prognostic biomarker and functional driver of GC progression and suggest that Naringenin may represent a promising bioactive compound for modulating the ITGA11/FAK/PI3K/AKT/mTOR axis in GC. Full article

Pumpkin seed oil (PSO) is becoming increasingly valued for its nutritional profile and minor bioactive constituents. Here, we surveyed PSOs marketed in China and hypothesized that differences in antioxidant constituents help explain variability in oxidative stability across brands. Sixteen commercial products labeled as pumpkin (Cucurbita moschata Duchesne) seed oils, including two imported brands (France), were analyzed for physicochemical quality indices, fatty acid composition, oxidative stability, and bioactive components (tocopherols, total sterols, and total phenolics expressed as gallic acid equivalents). Acid value, peroxide value, and iodine value ranged from 0.22 to 4.30 mg KOH/g, from 4.63 to 11.57 mEq O₂/kg, and from 106.64 to 132.77 g I₂/100 g, respectively, and all samples complied with applicable regulatory limits. Oleic and linoleic acids predominated (21.79–35.50% and 44.99–57.03% of total fatty acids, respectively), consistent with a highly unsaturated oil matrix. Total phenolics varied widely, reaching 2247.78 mg GAE/kg, while total tocopherols and total sterols ranged from 268.26 to 528.26 mg/kg and 733.64 to 1095.99 mg/kg, respectively. Oxidation induction times ranged from approximately 4 to over 10 h, and radical-scavenging activity differed markedly among samples. Correlation analysis and principal component analysis consistently identified δ-tocopherol, total sterols, and total phenolics as the variables most strongly associated with oxidative stability and antioxidant performance. Overall, these results provide a market-level snapshot of compositional variability in PSOs sold in China and highlight antioxidant-related markers that may support quality differentiation and process optimization. Full article

Understanding the hydrochemical characteristics and formation mechanisms of rivers in the Huxi Catchment is essential for water resource conservation, as these rivers serve as the primary water source for Taihu Lake. A total of 14 surface water samples were collected from the rivers in Huxi catchment, and the concentrations of seven major ions—namely, ${\mathrm{N}\mathrm{a}}^{+}$, ${\mathrm{K}}^{+}$, ${\mathrm{C}\mathrm{a}}^{2+}$, ${\mathrm{M}\mathrm{g}}^{2+}$, ${\mathrm{C}\mathrm{l}}^{-}$, ${\mathrm{S}\mathrm{O}}_4^{2-}$, and ${\mathrm{H}\mathrm{C}\mathrm{O}}_3^{-}$—were determined. Positive Matrix Factorization (PMF), Absolute Principal Component Score–Multiple Linear Regression (APCS-MLR), and the Principal Component Analysis-based Endmember Mixing Model (PCA-EMM) were employed to quantify the contributions of anthropogenic activities. While APCS-MLR can only identify the impacts of human activities, PMF and PCA-EMM can further distinguish between agricultural activities and wastewater discharge. Significant positive correlations were observed between the PMF and PCA-EMM results, but PMF overestimated the contribution of anthropogenic impacts. PCA-EMM showed that the natural background accounted for 63%, while human activities contributed 37% (domestic sewage 23%, agricultural activities 14%). By integrating ion composition data from representative sources, PCA-EMM overcomes the limitations of traditional methods that lack source verification and provides robust methodological support for the source apportionment of water chemistry. Full article

Natural deep eutectic solvents (NADES) are promising eco-friendly alternatives to traditional solvents for extracting phenolic compounds from plant materials. However, their effectiveness depends on both solvent composition and the botanical matrix. This study examined water, ethanol, and choline chloride–urea (CCU) and choline chloride–glycerol (CCG) systems containing 30% or 60% NADES for the extraction of anthocyanins, total phenolic content, total flavonoid content, and antioxidant capacity (DPPH and ABTS) from cornflower, safflower, and pomegranate flowers. Pomegranate flowers exhibited the highest levels of anthocyanins, total phenolics, and antioxidants, while safflower showed the highest total flavonoid content. Overall, the 60% NADES formulations delivered the best extraction results, whereas ethanol had the lowest overall efficiency. A combined heatmap analyzing all responses identified 60% CCU and 60% CCG as the most effective solvents across all tested materials. Anthocyanin stability in pomegranate flower extracts was further evaluated over 8 weeks at 4 and 20 °C. First-order kinetic analysis revealed that ethanol and 60% CCG maintained the highest anthocyanin stability, whereas 60% CCU exhibited the lowest stability, especially at 20 °C. These findings support the use of NADES as efficient solvents for floral bioactives, while indicating that the highest extraction yield does not necessarily correlate with the best storage stability. Full article

Background: Differentiating plant species is complex, complicated by morphological similarities that confound species’ delineation. For hundreds of years, researchers have used herbarium specimens to study plant morphology, and over the last forty years, these samples have also served as material for molecular phylogenetic research. Taxonomists have alternately split and combined morphotypes of Pediomelum tenuiflorum for two centuries. With samples of P. tenuiflorum from across its distribution, this research aimed to (1) infer a robust phylogeny using molecular data, i.e., gene sequences from chloroplast and nuclear genomes; (2) assess genetic diversity using molecular markers, specifically Inter Simple Sequence Repeats (ISSRs); (3) provide evidence to support the taxonomic placement and possible splitting of P. tenuiflorum; and (4) identify consistent morphological characteristics using a correlation matrix to distinguish among the morphotypes. Results: Striking morphological differences among the individuals of P. tenuiflorum from across the species’ distribution resulted in more than two morphotypes. Phylogenetic data suggest hybridization is occurring among genetically and morphologically distinct members of P. tenuiflorum and with other species in the genus Pediomelum, whereas ISSR results indicate detectable genetic variation but do not resolve discrete clusters. This study reports the first ISSR markers used to assess genetic diversity in Pediomelum species. Conclusions: Morphological and genetic variation exist across individuals of P. tenuiflorum but not in monophyletic groups that support splitting the morphotypes into multiple species. Future investigations into chromosome numbers might reveal polyploidization in the lineage, and phylogenies estimated from low-copy nuclear genes could elucidate hybridization pathways. Full article

Background: Sensors and mass spectrometry (MS) are frequently used in combination for food safety and quality assessment, yet their functional integration lacks a formal methodological framework. This review categorizes the synergies between these technologies into distinct Relational Connections. Methodology: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 155 original research articles published between 2015 and 2025 were systematically analyzed. Records were identified via the Scopus database within the food science domain. Experimental meta-data, including extraction protocols, instrumental configurations (ionization source, mass analyzer, cost tier), and chemometric strategies, were extracted to identify core methodological patterns. Statistical associations were quantified using chi-squared tests with Cramer’s V effect sizes. Results: Five Relational Connections were identified: (1) MS as reference for sensor validation (25.2%); (2) MS-sensor correlative analysis (10.3%); (3) MS quantifying data to train predictive sensor models (6.5%); (4) MS identifying targets for sensor detection (7.1%); and (5) MS enabling sensor classification models (51.0%). Technology pairing is governed by a three-level hierarchy: analyte polarity determines the ionization source (V = 0.69), required precision determines the mass analyzer (V = 0.64), and cost/availability constraints shape the practical integration strategy. Gas Chromatography (GC)-MS is predominantly coupled with Electronic Noses for volatile profiling (86% of classification studies), while Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) pairs with biosensors for contaminant analysis (74% of reference validation studies). Systematic analysis of the full pairing matrix reveals that 75% of theoretically possible MS-sensor combinations remain unexplored or underrepresented, identifying both technical boundaries and innovation frontiers. Discussion: The findings clarify the strategic logic behind technology pairings, demonstrating that MS provides the quantitative molecular data required for sensor training. The hierarchical decision framework and identification of underexplored pairings provide an evidence-based guide for designing future integrated food analysis systems. Full article

The translaminar fracture toughness of pultruded Glass Fiber Reinforced Polymers (GFRP) is influenced by several factors, including the type of matrix, fiber, the fiber volume ratio, the proportion of plies at each angle and the size of the test specimens. Conventional test approaches tend to overestimate the fracture toughness of GFRP composites due to imperfect specimen fabrication. This paper introduces an anisotropic two-dimensional adaptation of phase field theory to evaluate the translaminar fracture toughness of pultruded GFRP in conjunction with the size effect. It is found that the fracture toughness is linearly correlated with the fiber volume ratio when the proportion of 0° plies ranges from 30% to 60%. Additionally, it was found that at the same fiber volume ratio, the fracture toughness increases with the increase of 0° plies by 5%. Five machine learning algorithms, i.e., BP, RF, SVR, GA-BP, and PSO-BP, are employed to predict the fracture toughness of pultruded GFRP laminates. It has been found that the PSO-BP algorithm is robust in predicting the fracture toughness of pultruded GFRP laminates, with the correlation coefficient R² being 0.987 and 0.994 in the test and training set, respectively and the prediction error in fracture toughness being less than 4 kJ/m². The trained machine learning method can accurately predict GFRP fracture toughness. When the proportion of 0° plies is larger than 50%, the increase in the fracture toughness is approximately twice that of those taking up a proportion of 30–50%. Fracture toughness predictions are provided using the developed machine learning model for pultruded GFRP profiles, which are commonly used in infrastructure construction with fiber volume ratios range of 60–70% and 0° layup percentages of 60–75%. Full article

Background/Objectives: To evaluate the relationships between meibomian gland dysfunction (MGD), ocular surface parameters, and matrix metalloproteinase-9 (MMP-9)-mediated inflammation in glaucoma patients, we specifically assessed the impact of prostaglandin analogue use, preservative exposure, and number of medications. Methods: This retrospective cross-sectional study included patients treated with topical antiglaucoma medications for at least six months. Meibomian gland expressibility, meibum quality, and MGD grade were assessed along with tear film break-up time (TBUT), Schirmer I test, and Oxford staining score. Tear MMP-9 levels were measured using a Point-of-Care immunoassay (InflammaDry^®) and graded on a 0 to 4 scale. Results: Elevated MMP-9 grades were significantly correlated with worsening meibum expressibility, meibum quality, and MGD grade (all p < 0.001), whereas no significant associations were found with traditional parameters such as TBUT and Schirmer I test. Prostaglandin analogue use was associated with worse meibomian gland parameters and higher MMP-9 levels compared to non-use. Patients receiving preservative-containing medications exhibited poorer meibomian gland parameters and MMP-9 levels, as well as worse corneal staining scores. An increased number of medications was associated with a stepwise deterioration in meibomian gland function and elevated MMP-9 levels. Conclusions: Prostaglandin analogue use, preservative exposure, and increased number of medications are significant factors associated with the exacerbation of MGD and ocular surface inflammation. Semi-quantitative grading of tear MMP-9 revealed a stepwise association with meibomian gland dysfunction severity that was not detected by conventional dry eye metrics, indicating that MMP-9 may be considered a potential indicator of subclinical ocular surface inflammation in glaucoma patients. Full article

Matrix Product States (MPSs) have become an indispensable symmetry-based representation for simulating quantum systems on near-term hardware by constraining entanglement entropy through a fixed bond dimension $\mathsf{\chi }$. This study identifies a critical “rank explosion” phenomenon that destabilizes this low-rank manifold during conditional quantum diffusion processes. We empirically demonstrate that the introduction of conditional guidance—essential for semantic control—injects global correlations that drive the effective Schmidt rank to increase by $4\times$ (from $\mathsf{\chi }=4$ to $16$), saturating the simulation limits and necessitating quantum circuits with approximately $1.8\times {10}^3$ Controlled-NOT (CNOT) gates. Such circuit depths fundamentally exceed the operational coherence budgets of Noisy Intermediate-Scale Quantum (NISQ) devices. To mitigate this structural instability, we propose Rank-Aware Conditional Synthesis (RACS), a sampling framework that maintains the latent trajectory within a prescribed MPS manifold through step-wise manifold projection and time-shift error correction. Experimental results on real-world semantic data reveal that RACS reduces reconstruction error, or Mean Squared Error (MSE) by 30.8% and enhances latent trajectory smoothness by 36.8% compared to conventional post hoc truncation. At a fixed hardware-efficient rank of $\mathsf{\chi }=4$, RACS achieves a +4.8% fidelity gain and exhibits superior robustness against depolarizing noise. By resolving the tension between conditional expressivity and entanglement constraints, RACS provides a principled, hardware-aware methodology for high-fidelity quantum generative modeling. Full article

Winter precipitation plays an important role in the Himalayan region. However, its reliable assessment is difficult due to sparse ground precipitation measurements, limited ability to capture heterogeneity, and snowfall undercatch. Recent advances in satellite-based winter precipitation products (SPPs) enable comprehensive, consistent spatial data in this region; however, despite rapid improvements and the increased availability of SPPs, their accuracy is still uncertain. This calls for rigorous evaluation across several regions. This study presents a new SPP evaluation method that extends existing frameworks by adding two additional indicators—spatial correlation and the water balance consistency ratio (WBCR) to create a unified multi-criteria matrix for selecting spatially and hydrologically consistent products from among 11 latest and earlier SPPs from the global satellite mapping of precipitation (GSMaP) and The integrated multi-satellite retrievals for the global precipitation measurement Mission (IMERG) in the Kabul, Dudhkoshi, and Chamkharchu River basins. The results show that the latest non-calibrated product performed significantly better than earlier releases, demonstrating improved ability to capture precipitation events, spatial heterogeneity, and WBCR across all three basins. However, the performance of those SPPs varies substantially across regions. GSMaP gauge-calibrated product performance was more consistent across conventional multi-criteria assessment and WBCR, but their inability to capture spatial heterogeneity limits their applicability for sub-catchment water resource management. On the other hand, IMERG Final V07 (gauge-calibrated) performed exceptionally well across all regions, although its 3.5 month latency limits near-real-time applications. Therefore, GSMaP NRT V08 is suitable for real-time applications, given its short ~4 h latency and relatively good performance across all three basins. Future studies using the selected products will provide reliable information for policymakers and will support water hazard risk reduction. Full article

Currently, there are no consistent earthquake precursors for early warning. However, the correlation between earthquakes and ionospheric scintillation, measured using the S₄ index via GNSS-RO, is under active study. This research analyzes S₄ anomalies as a potential earthquake proxy, using GNSS-RO data from COSMIC-2/TGRS (Tri-GNSS Radio Occultation System) collected from 2019 to 2024. It examines over 71,000 global earthquakes within ±60° of the equator with magnitudes greater than 4. The quality of S₄ anomalies has been enhanced by filtering out space-weather-induced disturbances using the daily planetary geomagnetic index (Kp) and the solar activity flag collected from ground stations. The S₄ anomalies were calculated using robust statistical methods, such as the standard deviation and the interquartile range. This study evaluated the correlation with a confusion matrix, a receiver operating characteristic curve, and various figures of merit. The results demonstrated a promising positive S₄ anomaly between 1 and 7 days before the analyzed earthquakes, indicating the potential of ionospheric scintillation as an earthquake precursor, with the robust statistical methods employed instilling confidence in the validity of our findings. Full article

Wavelength modulation spectroscopy (WMS) is a representative implementation of tunable diode laser absorption spectroscopy (TDLAS), enabling reliable gas component analysis with concentration-related information derived from harmonic component extraction, while offering enhanced noise immunity for trace gas sensing in open environments. However, due to the strong coupling between laser wavelength and intensity, wavelength modulation inevitably introduces residual amplitude modulation (RAM), which significantly degrades measurement accuracy. To address this issue, this study introduces a RAM suppression algorithm based on multiple harmonic component decoupling (MHCD), using the second-harmonic lateral peak inclination angle (LPIA) as a characteristic indicator. Unit harmonic operators for the first, second, and third harmonics are designed, and an original harmonic reconstruction model is established via linear superposition of harmonic components. The optimal harmonic component ratio is determined at the composite operator with the maximum cross-correlation coefficient, and RAM noise is eliminated through a multi-harmonic decoupling matrix. Repetitive measurements on 22 mm pharmaceutical vials with 4% oxygen concentration demonstrate that MHCD reduces the second-harmonic LPIA from 18.07° to 8.56°. Concentration discrimination experiments conducted on seven groups of 22 mm vials with 2% concentration steps (0–12%) show that MHCD increases the true positive rate by 6–11% and decreases the false positive rate by 4–9%, confirming its effectiveness for pharmaceutical online inspection applications. Full article