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Evaluating LEM, FEM, and DFN approaches for rock slope stability across GSI ranges for open pit mine
Preliminary results on using machine learning methods to predict exercise induced hypoxemia of endurance athletes a posteriori
Quality, reliability, and clinical accuracy of bronchiectasis-related videos on Douyin and Bilibili: a cross-sectional study
Digital entrepreneurship intention among Chinese and Vietnamese students: an EEM-imprinting-informed SEM-ANN model
Investigating self-efficacy as a mediating mechanism between AI-dialogic scaffolding and Saudi learners’ speaking anxiety and confidence
Foreground guided identity and view disentanglement for few-shot ship re-identification
Exploring the potential of Proboscidea louisianica (Martyniaceae) as a live trap for insects, with emphasis on aphids and parasitoids
Metaheuristic optimization of photovoltaic water pumping system using the scalar control of an induction motor drive
Maternal cafeteria diet intake influences offspring development in Wistar rats: a pilot study
Performance evaluation of Pt- and Pd-based catalysts on nickel & copper foams for methanol combustion in a microreactor
The role of serum biochemical markers in early prediction of complicated appendicitis: a single-center retrospective analysis
Histopathological predictors of renal outcomes in idiopathic membranous nephropathy with a focus on global sclerotic glomeruli ratio
Abstract Idiopathic membranous nephropathy (MN) shows variable renal outcomes, and reliable histologic markers for risk stratification are limited. The global sclerotic glomeruli ratio (GSGR) may reflect chronic kidney damage and help predict progression, but its prognostic value and optimal threshold remain unclear. We retrospectively analyzed 322 patients with biopsy-proven idiopathic MN from the Turkish Society of Nephrology-Glomerular Diseases Study Group registry, excluding those with an estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m² at diagnosis or insufficient data. GSGR was calculated as the percentage of globally sclerotic glomeruli among total glomeruli. Histopathological parameters, including exudative glomerular changes, tubular atrophy/interstitial fibrosis (TA/IF), and vascular alterations, were semi-quantitatively graded according to the Renal Pathology Atlas (Fogo, 2022). Specifically, TA/IF was graded as: Grade 0 (< 5%), Grade 1 (5–25%), Grade 2 26–50%, and Grade 3 (> 50%) of cortical area involvement. Exudative changes were defined as intracapillary leukocyte accumulation and hyaline deposits in ≥ 25% of non-sclerotic glomeruli. The primary composite outcome was ≥ 50% eGFR decline from baseline, progression to eGFR < 15 mL/min/1.73 m², dialysis initiation, or kidney transplantation. Median follow-up was 60 months (IQR 48–72). Thirty patients (9.3%) reached the composite outcome. Receiver operating characteristic analysis identified a GSGR threshold of 15.7% (AUC 0.956; sensitivity 93.3%; specificity 82.7%). Patients with GSGR ≥ 15.7% had significantly higher event rates (35.1% vs. 1.2%; p < 0.001). In multivariate analysis, high GSGR, exudative changes, and response to immunosuppressive therapy independently predicted adverse outcomes. These associations remained significant across treatment subgroups. Sensitivity analyses confirmed these associations across multiple model specifications. Anti-PLA2R positivity correlated with higher baseline proteinuria but not independently with renal outcomes. A GSGR ≥ 15.7% is a strong, independent predictor of renal progression in idiopathic MN. Incorporating GSGR and exudative changes into risk stratification may improve prognostic assessment and therapeutic decision-making.
Multi-objective forest succession planning algorithm: a new metaheuristic algorithm for multi-objective operation optimization of marine power plants
Tungsten-doped polypyrrole/activated carbon asymmetric supercapacitor: design, fabrication, and performance evaluation
Assumption of an expanded carbon black nanoparticle by interphase and tunneling zones to simulate the electrical conductivity of nanocomposites
Construction of an intelligent interpretation and change detection system based on UAV remote sensing for landscape architectural heritage conservation
Single-atom-engineered perovskite enables near-theoretical-rate hydroxyl radical electrogeneration
Abstract Electrochemical advanced oxidation that directly activates O 2 through the oxygen reduction reaction (ORR) to generate hydroxyl radicals (•OH) offers a sustainable strategy for degrading persistent organic pollutants. However, prevailing approaches typically rely on a stepwise process involving the 2e⁻ ORR to produce H 2 O 2 followed by 1e⁻ activation. High barriers associated with intermediate desorption and inter-site transfer consequently limit the •OH yield. Here, we construct a single-active-site architecture in the perovskite oxide Pr 1.0 Sr 1.0 Fe 0.5 Zn 0.25 Mo 0.25 O 4-δ (PSFZM) that enables a direct three-electron ORR pathway for efficient •OH generation. The Zn δ ⁺ single active center selectively stabilizes *OOH and *H 2 O 2 through weak orbital interactions, while an adjacent Mo atom polarizes the O atoms of adsorbed H 2 O 2 , promoting cleavage of the peroxide bond at the active site. This strategy avoids intermediate desorption and migration, enabling continuous proton-coupled electron transfer. The catalyst achieves a •OH production rate of 821 μmol h⁻ 1 and an O 2 utilization of 37.7%, metrics competitive with previously reported systems. In a membrane-free flow cell that uses gaseous O 2 directly, the •OH generation efficiency reaches 64.7%. By combining atomic-level catalyst design with reactor engineering, this work establishes a scalable platform for sustainable wastewater treatment.
Upwind terrestrial influences on soil moisture variability across South America
Abstract Soil moisture across South America exhibits coherent spatial patterns shaped by upwind terrestrial conditions, yet their downwind propagation remains poorly quantified. We develop an observation-driven framework integrating atmospheric transport trajectories with deep learning to estimate vegetation’s contribution to downwind soil moisture. The transport-informed model outperforms a local-only baseline, with upwind information contributing 67% of predictive power, of which vegetation explains 15%. This vegetation-mediated influence is enhanced over agricultural zones, forming hotspots aligned with land-cover change and drought exposure. The cross-regional influence is organized along major transport corridors and varies non-linearly with climate. In humid forests, downwind moisture supply is highly sensitive to vegetation change, with canopy degradation associated with reduced soil moisture; in semi-arid regions, initial greening is associated with increases, but further greening weakens or reverses the effect. These results quantify vegetation–soil moisture teleconnections, with implications for land–atmosphere coupling in Earth system models and hydrological consequences of land-use and climate change.