Search Results (1,125)

Clouds cover nearly two-thirds of Earth’s surface, making reliable cloud mask data essential for remote sensing applications and atmospheric research. This study develops a TrAdaBoost transfer learning framework that integrates active CALIOP and passive MODIS observations to enable unified, high-accuracy cloud detection across FY-4A/AGRI, FY-4B/AGRI, and Himawari-8/9 AHI sensors. The proposed TrAdaBoost Cloud Mask algorithm (TCM) achieves robust performance in dual validations with CALIPSO VFM and MOD35/MYD35, attaining a hit rate (HR) above 0.85 and a cloudy probability of detection (${POD}_{cld})$ exceeding 0.89. Relative to official products, TCM consistently delivers higher accuracy, with the most pronounced gains on FY-4A/AGRI. SHAP interpretability analysis highlights that 0.47 μm albedo, 10.8/10.4 μm and 12.0/12.4 μm brightness temperatures and geometric factors such as solar zenith angles (SZA) and satellite zenith angles (VZA) are key contributors influencing cloud detection. Multidimensional consistency assessments further indicate strong inter-sensor agreement under diverse SZA and land cover conditions, underscoring the stability and generalizability of TCM. These results provide a robust foundation for the advancement of multi-source satellite cloud mask algorithms and the development of cloud data products integrated. Full article

Background/Objectives: Type 2 diabetes (T2D) is a clinically and genetically heterogeneous disease. In this study, we aimed to stratify patients with T2D from the Volga-Ural region of Eurasia into distinct subgroups based on clinical characteristics and to investigate the genetic underpinnings of these clusters. Methods: A total of 254 Tatar individuals with T2D and 361 ethnically matched controls were recruited. Clinical clustering was performed using k-means and hierarchical algorithms on five variables: age at diagnosis, body mass index (BMI), glycated hemoglobin (HbA1c), insulin resistance (HOMA-IR), and β-cell function (HOMA-B). Genetic association analysis was conducted using logistic regression under an additive model, adjusted for age and sex, and corrected for multiple comparisons using the Benjamini–Hochberg method. Results: Four distinct T2D subtypes were identified—mild age-related diabetes (MARD, n = 25), mild obesity-related diabetes (MOD, n = 72), severe insulin-resistant diabetes (SIRD, n = 66), and severe insulin-deficient diabetes (SIDD, n = 52)—each with unique clinical and comorbidity profiles. SIDD patients exhibited the highest burden of microvascular complications and lowest estimated glomerular filtration rate. Nine genetic variants showed significant associations with T2D and/or specific subtypes, including loci in genes related to neurotransmission (e.g., HTR1B, CHRM5), appetite regulation (NPY2R), insulin signaling (TCF7L2, PTEN), and other metabolic pathways. Some variants demonstrated subtype-specific associations, underscoring the genetic heterogeneity of T2D. Conclusions: Our findings support the utility of clinical clustering in uncovering biologically and clinically meaningful T2D subtypes and reveal genetic variants that may contribute to this heterogeneity. These insights may inform future precision medicine approaches for T2D diagnosis and management. Full article

Deoxynivalenol (DON), a mycotoxin from Fusarium that contaminates cereals, can also induce intestinal injury. However, the mechanisms underlying DON-induced jejunal barrier injury remain unclear. This study demonstrates that shikimic acid (SA) alleviates DON-induced jejunal barrier damage and dysbiosis via antioxidant pathways. Fifty 5-week-aged male KM mice were divided into control (CON), model (MOD, 2.4 mg/kg bw DON), and SA-treated groups (LDG/MDG/HDG: 25/50/100 mg/kg bw SA + DON). After SA treatment, notably MDG, reversed DON-induced weight loss and jejunal hyperemia; ameliorated villus atrophy, crypt deepening and goblet cell loss, increasing villus/crypt ratio; reduced gut permeability markers (D-LA/DAO) and pro-inflammatory cytokines (TNF-α/IL-6/IL-1β); and dose-dependently upregulated tight junction proteins (ZO-1/Occludin/Claudin1). Mechanistically, SA activated the Nrf2/HO-1/NQO1 pathway, elevating antioxidants (GSH/SOD/AOC) while reducing MDA, with MDG showing optimal efficacy. 16S rRNA sequencing revealed MDG counteracted DON-induced dysbiosis by enriching beneficial bacteria (e.g., Bacteroidota at phylum level; Muribaculaceae at family level) and suppressing pathogens (Staphylococcaceae) (LDA score > 4.0). Thus, SA mitigates DON toxicity via Nrf2-mediated barrier restoration, anti-inflammation, and microbiota modulation. This research provides new insights for the further development of Shikimic Acid and the treatment of DON-induced jejunal barrier injury. Full article

Soil secondary salinization is a major limiting factor of sustainable agricultural production in arid and semi-arid irrigation zones, yet predictive tools for regional water–salt dynamics remain limited. The Yichang Irrigation District, located within the Hetao Irrigation Area, has experienced persistent salinity challenges due to shallow groundwater tables and intensive irrigation. In this study, we aimed to simulate long-term soil water–salt dynamics in the Yichang Irrigation District and evaluate the effectiveness of different engineering and management scenarios using the SaltMod model. Field monitoring of soil salinity and groundwater levels during summer and fall (2022–2024) was used to calibrate and validate SaltMod parameters, ensuring accurate reproduction of seasonal soil salinity fluctuations. Based on the calibrated model, ten-year scenario simulations were conducted to assess the effects of changes in soil texture, irrigation water quantity, water quality, rainfall, and groundwater table depth on root-zone salinity. Our results show that under baseline management, soil salinity is projected to decline by 5% over the next decade. Increasing fall autumn leaching irrigation further reduces salinity by 5–10% while conserving 50–300 m³·ha⁻¹ of water. Sensitivity analysis indicated groundwater depth and irrigation water salinity as key drivers. Among the engineering strategies, drainage system improvement and groundwater regulation achieved the highest salinity reduction (15–20%), while irrigation regime optimization provided moderate benefits (~10%). This study offers a quantitative basis for integrated water–salt management in the Hetao Irrigation District and similar regions. Full article

Background: Severe acute pancreatitis (SAP) presents with Multiple Organ Dysfunction Syndrome (MODS) in ~15% of cases, accounting for ~35% of early deaths within 48 h. Major complications—shock, renal failure, and respiratory insufficiency—arise from an overwhelming systemic inflammatory response driven by markedly elevated pro-inflammatory cytokines. Massive release of IL-2, IL-6, and TNF-α underlies the systemic inflammatory response syndrome (SIRS). Continuous veno-venous hemofiltration (CVVH) with the oXiris filter, adsorbing endotoxins and cytokines, has been used in sepsis and applied early in SAP to reduce cytokine load and organ injury. Aims: To evaluate the efficacy and safety of early CVVH with the oXiris filter in modulating the systemic inflammatory response by removing toxic cytokines from the bloodstream in patients with SAP complicated by organ dysfunction and refractory sepsis. Methods: This single-centre, retrospective, observational study was conducted at a tertiary university hospital between 2000 and 2022. Forty-eight consecutive patients with SAP at onset, defined according to the 2012 Atlanta Classification, with an APACHE II score ≥ 19 and persistent organ dysfunction (>48 h), were included. All patients were unresponsive to initial intensive care within the first 24 h and underwent urgent laparotomy with extensive peritoneal lavage, pancreatic necrosectomy, and placement of multiple abdominal drains, followed by transfer to the intensive care unit. CVVH (Prismax system) with the oXiris filter was initiated within 12 h post-surgery. IL-6 and TNF-α were selected as inflammatory markers and measured in both serum and ultrafiltrate at baseline (0 h) and at 24, 48, 72, and 96 h. These measurements were correlated with clinical parameters and prognostic scores (APACHE II, SOFA). Results: Treatment was well tolerated in all patients. The 28-day survival rate was 97.9%. There was a significant time-dependent decrease in IL-6 (p = 0.019) and TNF-α (p = 0.008) concentrations in the ultrafiltrate, consistent with high early adsorption followed by a reduced cytokine burden, whereas serum levels showed a non-significant downward trend (IL-6 p = 0.08; TNF-α p = 0.310). The APACHE II score decreased from 23 postoperatively to 8 by the second week (−65.2%; p = 0.013), with a statistically significant correlation between cytokine reduction and clinical improvement. Adverse events were rare and manageable. Conclusions: Early CVVH with the oXiris filter in SAP, complicated by MODS and refractory sepsis, proved safe, well-tolerated, and potentially effective in reducing cytokine burden and improving prognostic indices. These findings support the hypothesis of a relevant immunomodulatory effect, warranting prospective controlled trials to confirm its true impact on survival and organ recovery. Full article

Background: Clustering type 2 diabetes (T2D) remains a challenge due to its clinical heterogeneity and multifactorial nature. We aimed to evaluate the validity and robustness of the clinical variables in defining T2D subtypes using a discovery-to-prediction design. Methods: Five explanatory clinical aetiology variables (fasting serum insulin, fasting blood glucose, body mass index, age at diagnosis and HbA1c) were assessed for clustering T2D subtypes using two independent patient datasets. Clustering was performed using the IBM-Modeler Auto-Cluster. The resulting cluster validity was tested by multinomial logistic regression. The variables’ validity for direct unsupervised clustering was compared with machine learning (ML) predictive models. Results: Five distinct subtypes were consistently identified: severe insulin-resistant diabetes (SIRD), severe insulin-deficient diabetes (SIDD), mild obesity-related diabetes (MOD), mild age-related diabetes (MARD), and mild early-onset diabetes (MEOD). Using all five variables yielded the highest concordance between clustering methods. Concordance was strongest for SIRD and SIDD, reflecting their distinct clinical signatures in contrast to that in MARD, MOD and MEOD. Conclusions: These findings support the robustness of clinically defined T2D subtypes and demonstrate the value of probabilistic clustering combined with ML for advancing precision diabetes care. Full article

Globally, land degradation represents both an environmental and socioeconomic challenge, necessitating continuous monitoring due to its impacts on ecosystem services. Given the substantial changes in land use and land cover in Maranhão, this study aimed to evaluate land degradation across the state between 2001 and 2023, based on Sustainable Development Goal (SDG) indicator 15.3.1. To this end, we integrated data on land cover (LC), soil organic carbon (SOC), and land productivity (LP) using the Trends.Earth algorithm (v.2.1.16), based on datasets from the MapBiomas platform (collections 9 and Beta) and MODIS (MOD13Q1 product), along with the application of the RESTREND model for climate adjustment. The results indicated that 39.56% of Maranhão’s territory showed signs of degradation, particularly in the central and northwestern (NW) regions, as well as parts of the southern (S) region. Stable areas accounted for 26.39%, while 32.08% were classified as improving, with notable trends in the southern and southeastern (SE) regions, suggesting vegetation recovery and more sustainable land management practices. The integrated analysis of LC, SOC stocks, and land productivity sub-indicators revealed that environmental degradation in Maranhão is strongly driven by the conversion of natural ecosystems into agricultural and livestock areas, especially in the central-eastern and NW regions. In conclusion, the findings highlight a misalignment with the SDG 15.3.1 target but also point to zones of stability and recovery, indicating potential for mitigation, restoration, and the implementation of sustainable land management strategies. Full article

In modern industrial control systems (ICSs), communication protocols such as Modbus TCP remain widely used due to their simplicity, interoperability, and real-time performance. However, these communication protocols (e.g., Modbus TCP) were originally designed without security considerations, lacking essential features such as encryption, integrity protection, and authentication. This exposes ICS deployments to severe security threats, including eavesdropping, command injection, and replay attacks, especially when operating over unsecured networks. To address these critical vulnerabilities while preserving the lightweight nature of the protocol, we propose a Modbus TCP security enhancement scheme that integrates ASCON, an NIST-standardized authenticated encryption algorithm, with the CBOR Object Signing and Encryption (COSE) framework. Our design embeds COSE_Encrypt0 structures into Modbus application data, enabling end-to-end confidentiality, integrity, and replay protection without altering the protocol’s semantics or timing behavior. We implement the proposed scheme in C and evaluate it in a simulated embedded environment representative of typical ICS devices. Experimental results show that the solution incurs minimal computational and memory overhead, while providing robust cryptographic guarantees. This work demonstrates a practical pathway for retrofitting legacy ICS protocols with modern lightweight cryptography, enhancing system resilience without compromising compatibility or performance. Full article

Accurate quantification of evapotranspiration (ET) is crucial for agricultural water management and climate change adaptation, especially in global warming and extreme climate events. Despite the availability of various ET products, their applicability across different scales and climatic conditions has not been comprehensively verified. This study evaluates nine ET products at grid, basin, and site scales in China from 2003 to 2014 under varying climatic conditions, including extreme temperatures, vapor pressure deficit (VPD), and drought. The main results are as follows: (1) At the grid scale, all products except the MODIS/Terra Net Evapotranspiration 8-Day L4 Global 500m SIN Grid (MOD16A2) product showed high consistency, with the Global Land Evaporation Amsterdam Model V4.2a (GLEAM) product exhibiting the highest comparability. The three-cornered hat (TCH) method revealed that GLEAM and the Synthesized Global Actual Evapotranspiration Dataset (Syn) had low uncertainties in multiple basins, while the Reliability Ensemble Averaging (REA) product and Penman–Monteith–Leuning Evapotranspiration V2 (PMLv2) product had the smallest uncertainties in the Songhua River and Hai River Basins. (2) At the basin scale, ET products were closely aligned with water-balance-based ET (WB-ET), with GLEAM achieving the smallest root mean square error (RMSE) (22.94 mm/month). (3) At the site scale, accuracy decreased significantly under extreme climatic conditions, with the coefficient of determination (R²) dropping from about 0.60 to below 0.30 and the mean absolute error (MAE) increasing by 110.30% (extreme high temperatures) and 101.40% (extreme high VPD). Drought conditions caused slight instability in ET estimations, with MAE increasing by approximately 12.00–40.00%. (4) Finally, using a small number of daily ET products as inputs for machine learning models, such as random forest (RF), greatly improved ET estimation, with R² reaching 0.91 overall and 0.81 under extreme conditions. GLEAM was the most important product for RF in ET estimation. This study provides essential guidance for selecting and improving ET products to enhance agricultural water-use efficiency and sustainable irrigation. Full article

Snow cover in the Himalayas plays a vital role in regulating elevation-dependent climate processes and sustaining downstream hydrology. However, its altitude-specific dynamics and implications for snow mass balance remain underexplored. Using the MOD09A1 dataset (2004–2024), this study conducts a pixel-based, elevation-stratified analysis with advanced spectral filtering and gap-filling techniques to enhance snow cover detection in complex terrain. The mean SCA was ~2.10 × 10⁵ km², with sub-regional contributions from WH: 8.59 × 10⁴ km², CH: 9.55 × 10⁴ km², and EH: 2.99 × 10⁴ km², indicating distinct spatiotemporal variability. Correlation analysis revealed that SCA in WH and CH is mainly precipitation-driven (r = +0.70 and r = +0.91), whereas EH is temperature-dominant (r = −0.65), reflecting strong climatic control. Altitudinal and zonal snow cover changes were assessed using Equilibrium Line Altitude–AAR and AABR methods for mass balance estimation. Regional trends showed a positive mass balance of 0.0389 at 4105 m in WH, with increasing SCA around 4516.12 ± 531.94 m; CH exhibited a negative balance (−0.0268 at 4989 m), with declines at higher altitudes; and EH demonstrated a negative balance (−0.015 at 4378 m), with notable SCA reduction. Mann–Kendall and Kendall Tau tests validated these trends, highlighting spatially heterogeneous snow-cover dynamics and their implications for Himalayan snow-mass balance. Full article

Species distribution models (SDMs) grapple with uncertainty. To address this, a parameter-optimized MaxEnt model was used to predict habitat suitability for Elsholtzia densa, a predominant agricultural weed on the Tibetan Plateau. Through multiparameter optimization with 149 occurrence points and three climate variable sets, we systematically evaluated how the three MaxEnt extrapolation approaches (Free Extrapolation, Extrapolation with Clamping, No Extrapolation) influenced model outputs. The results showed the following: (1) Model optimization using the Kuenm R package version (1.1.10) identified seven critical bioclimatic variables (Feature Combinations = LQTH, Regularization Multipliers = 2.5), with optimized models demonstrating high accuracy (Area Under Curve > 0.9). (2) Extrapolation approaches exhibited negligible effects on variable selection, though four bioclimatic variables “bio1 (annual mean temperature)”, “bio12 (annual precipitation)”, “bio2 (mean diurnal range)”, and “bio7 (temperature annual range)” predominantly drove model predictions. (3) Current high-suitability areas are clustered in the eastern and southern regions of the Tibetan Plateau, and with Free Extrapolation yielding the broadest current distribution. Climate change projections suggest habitat expansion, particularly under conditions of No Extrapolation. (4) Multivariate Environmental Similarity Surface (MESS) and Most Dissimilar Variable (MoD) are not affected by the extrapolation method, and extrapolation risk analyses indicate that future climate anomalies are mainly concentrated in the western and southern parts of the Tibetan Plateau and that future warming will further increase the unsuitability of these regions. (5) Variance analysis showed that the extrapolation methods did not significantly affect the 10-replicate results but influenced the parameter and emission scenarios, with No Extrapolation methods showing minimal variance changes. Our findings validate that multiparameter optimization improves species distribution model robustness, systematically characterizes extrapolation impacts on distribution projections, and provides a conceptual framework and early warning systems for agricultural weed management on the Tibetan Plateau. Full article

By the cyclic structure of the affine plane AG(2,q), q≡7 mod 12, a mixed partition into a set of Möbius–Kantor configurations and a one-point set is provided. This generalizes a 2006 result of L. Berardi and T. Masini, who partitioned the affine plane of order 7 into a set of Möbius–Kantor configurations and a one-point set. Full article

The clinical impact of non-pathogenic colonizing bacteria in pneumonia remains poorly understood. This retrospective study analyzed the mutual influence of pneumonia and non-pathogenic bacterial flora in the lungs. Bronchoalveolar lavage fluid samples from 483 patients were analyzed using metagenomic next-generation sequencing, and differences in colonizing bacteria in different pneumonia types and their impact on disease prognosis were determined. Patients with bacterial pneumonia exhibited higher and lower colonization rates of Granulicatella adiacens and Streptococcus parasanguinis, respectively, than those without. Fungal pneumonia showed lower and higher colonization rates of Abiotrophia defectiva and Veillonella parvula, respectively; viral pneumonia showed higher colonization rates of Abiotrophia defectiva and Streptococcus mitis. Rothia mucilaginosa was associated with shorter duration of fever, and lower risks of sepsis and multiple organ dysfunction syndrome (MODS). Prevotella melaninogenica was associated with lower risks of sepsis and MODS. These findings suggest that select non-pathogenic bacteria might influence disease severity and also highlight the need for further investigation into microbiome-based therapeutic strategies, potentially guiding personalized pneumonia treatments. Full article

Aim: To compare the fracture resistance of teeth with varying degrees of residual coronal dentine after restoration using two fibre-reinforced composite core materials. Materials and Methods: Seventy extracted human lower premolars were divided into four groups: sound (control), one missing proximal wall (Cl-II), two missing proximal walls (MOD), and endocrown (EC). Subgroups were restored with either a short fibre-reinforced flowable composite (EverX Flow) or an experimental fibre-reinforced composite. Except for the control, teeth underwent endodontic treatment and were restored accordingly. Fracture resistance was tested using a universal testing machine. Statistical analysis compared fracture resistance across groups. Results: Teeth in EC exhibited the highest fracture resistance (1153.43 ± 332.52 N), comparable to sound teeth (1114.03 ± 185.58 N) and not significantly different from the experimental composite group (1006.89 ± 200.51 N) (p = 0.304). Cl-II restorations with EverX had significantly lower strength (652.48 ± 314.04 N) compared to MOD (773.02 ± 261.18 N) and EC (p < 0.05). The experimental composite showed a similar trend, with MOD having the lowest strength (408.6 ± 168.85 N). Significant differences were noted between materials in the MOD group (p = 0.009). Scanning electron microscopy revealed distinct fracture patterns. Conclusions: Endocrowns using direct fibre-reinforced composites provided protection for endodontically treated teeth with higher fracture resistance compared to teeth with MOD and Cl-II cavities. This gives direct composite endocrowns a potential for high-stress applications, though design and material selection remain critical. Full article

Detecting small moving objects under challenging lighting conditions, such as overexposure and underexposure, remains a critical challenge in computer vision applications including surveillance, autonomous driving, and anti-UAV systems. Traditional RGB-based detectors often suffer from degraded object visibility and highly dynamic illumination, leading to suboptimal performance. To address these limitations, we propose a novel RGB-Event fusion framework that leverages the complementary strengths of RGB and event modalities for enhanced small object detection. Specifically, we introduce a Temporal Multi-Scale Attention Fusion (TMAF) module to encode motion cues from event streams at multiple temporal scales, thereby enhancing the saliency of small object features. Furthermore, we design a Sparse Noisy Gated Attention Fusion (SNGAF) module, inspired by the mixture-of-experts paradigm, which employs a sparse gating mechanism to adaptively combine multiple fusion experts based on input characteristics, enabling flexible and robust RGB-Event feature integration. Additionally, we present RGBE-UAV, which is a new RGB-Event dataset tailored for small moving object detection under diverse exposure conditions. Extensive experiments on our RGBE-UAV and public DSEC-MOD datasets demonstrate that our method outperforms existing state-of-the-art RGB-Event fusion approaches, validating its effectiveness and generalization under complex lighting conditions. Full article