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Modeling Zn3O3/Ga3O3 composite for water splitting: a first-principle DFT study of electronic structure and interfacial reactivity
Abstract This study employs Density Functional Theory (DFT) at the B3LYP/LANL2DZ level to investigate the structural and electronic properties of a Zn 3 O 3 /Ga 3 O 3 composite and its interaction with water clusters. Using the Gaussian 09 suite, the research analyzes model molecules of Zn 3 O 3 , Ga 3 O 3 , and their composite to evaluate kinetic stability and chemical reactivity through HOMO-LUMO energy gaps and Total Dipole Moments (TDM). The results demonstrate that the Zn 3 O 3 /Ga 3 O 3 composite is a tunable nanostructure whose electronic properties are highly sensitive to its interface and the presence of external moisture. The study used Molecular Electrostatic Potential (MESP) and Non-Covalent Interaction (NCI) methods to show that water adsorption becomes more stable through the combined effect of strong metal-oxygen coordination and hydrogen bonding and weak van der Waals forces. The Density of States (DOS) analysis demonstrated that the electronic structure and interfacial stability both changed because of the observed modulation. These findings provide critical insights into the initial steps of photocatalytic water splitting and suggest the composite as a promising candidate for water capture and catalytic applications. These results indicate that interfacial electronic coupling between Zn and Ga oxide domains enhances water affinity and electronic responsiveness, representing a key step in photocatalytic water splitting mechanisms. The findings provide atomistic insight into how heterostructured oxide composites can be rationally engineered to improve water capture, charge separation, and catalytic efficiency, highlighting the Zn₃O₃/Ga₃O₃ composite as a promising model for next-generation photocatalytic water splitting by optimizing surface adsorption and interfacial electronic coupling.
Association of the combined atherosclerosis index of plasma and frailty index with arthritis in middle-aged and older adults: a cohort study
Abstract The Atherogenic Index of Plasma (AIP) is a marker of atherosclerosis, and the Frailty Index (FI) reflects physiological decline. The combined effect of AIP and FI remains insufficiently studied. This study aimed to investigate the association between a combined AIP-FI measure and the risk of arthritis. This study utilized data from the China Health and Retirement Longitudinal Study (CHARLS) database between 2011 and 2020. A total of 4437 participants aged ≥ 45 years without arthritis at baseline were included. Cox proportional hazards regression models and restricted cubic spline (RCS) models were employed to explore the relationship between the AIP-FI and the risk of incident arthritis. Over a 10-year follow-up period, a total of 1470 participants developed arthritis, with an incidence rate of 33.13%. Cox regression analysis revealed that each 1-unit increase in AIP-FI was associated with a 3% increase in arthritis risk (HR = 1.03; 95% CI: 1.02 to 1.04). Participants in the highest tertile (T3) of AIP-FI had a 55% higher risk compared to those in the lowest tertile (T1) (HR = 1.55; 95% CI: 1.35 to 1.78). The RCS curve demonstrated a significant nonlinear positive association between AIP-FI and arthritis risk (P for overall < 0.001, P for nonlinear < 0.001). This study indicates that a higher AIP-FI is significantly associated with an increased risk of arthritis. By integrating metabolic and frailty data, the AIP-FI was associated with arthritis risk and may help identify older Chinese adults at higher risk. However, these findings require further validation in independent cohorts before any clinical consideration.
Uncertainty-aware deep kernel learning: An end-to-end approach for crack localization in turbine blades
Optimization of electromagnetic steel lamination laser spot welding process parameters using response surface methodology
Abstract Electrical steel is a critical material for key components such as electric motors and transformers. Conventional continuous welding, characterized by high heat input and a wide heat-affected zone (HAZ), often leads to magnetic degradation. To address this issue, laser spot welding is adopted to achieve precise energy control and reduced thermal impact. Response surface methodology (RSM) based on a central composite design (CCD) is employed to investigate the effects of laser power, pulse width, and defocus distance on shear strength and weld spot cross-sectional area. Analysis of variance (ANOVA) confirms the significance of the selected factors, and regression models are developed, achieving R 2 values of 0.88 and 0.82, respectively. Optimal process parameters are determined through RSM optimization and confirmed by additional one-factor-at-a-time (OFAT) experiments. Simplified models are developed to improve predictive accuracy and practical applicability, and their validity is verified through experimental results. In addition, the influence of pulse shape is examined by comparing rectangular, ramp-up, ramp-down, and triangular profiles. The results indicate that the ramp-down pulse effectively suppresses thermal cracking and porosity by moderating solidification behavior, leading to improved weld stability and quality.
Vehicle-level multi-strategy benchmarking of NOx emission forecasting using integrated onboard and meteorological data
Vegetation greenness dynamics and responses to climate and human activities under land cover change in Guangdong, China
Abstract To understand the spatiotemporal variations of vegetation greenness and the differences in its response to climate and human activities based on land cover change in subtropical region, this paper focused on the spatiotemporal characteristics of vegetation greenness (indicated by NDVI) and its sensitivity to temperature, precipitation and human activities (indicated by nighttime light (NTL)) under different land cover scenarios in Guangdong, China. The contributions of climate and human activities under land cover change to the variations in vegetation greenness were quantified using Lindeman, Merenda and Gold method (LMG). The conclusions revealed that (1) NDVI was significantly higher in regions with land cover change. This might be because the conversion from grassland to evergreen forest increased vegetation density. (2) NDVI in regions with unchanged land cover exhibited higher correlations with temperature and NTL. At the grid scale, NDVI was more sensitive to temperature rather than precipitation and was significantly correlated with NTL in most regions. (3) At the province scale, LMG multivariate regression model indicated that land cover change was the dominant factor affecting vegetation greenness with a contribution of 54.2%, while the contribution of climate factors was relatively low with temperature contributing 18.2% which was greater than the contribution of precipitation (2.2%). This paper contributes to a deeper understanding of the mechanisms underlying vegetation responses to the combined effects of climate change and human activities, providing a scientific basis for regional ecological quality assessment and ecosystem management.
Seismic fragility of cut-and-cover underground box structures under shallow bedrock conditions
Abstract Underground structures are typically considered safer than aboveground structures against earthquakes. However, recent research findings and observed damage cases have demonstrated that underground structures can also suffer severe damage from seismic events. South Korea is characterized by relatively shallow bedrock depths compared with other countries. Although fragility assessments of underground structures that reflect these geological conditions are required, the related research remains limited. Accordingly, this study establishes a two-dimensional finite element numerical model incorporating nonlinear soil behavior using OpenSees. In the analysis, shallow bedrock depth was considered, and a total of 18 analysis cases were constructed by selecting soil stiffness, structural embedment depth, and bedrock depth as the primary parameters. In addition, five ground motion records, including the 2017 Pohang earthquake, were scaled from 0.05g to 1.0g, resulting in 1,800 dynamic analyses, through which seismic fragility curves for underground structures were proposed. The analysis results indicate that the seismic fragility of cut-and-cover underground box structures increases with decreasing soil stiffness, increasing structural embedment depth, and increasing bedrock depth. In particular, the structural embedment depth was identified as the most dominant factor influencing seismic fragility. The proposed models provide a quantitative basis for system-level safety and reliability assessment and support performance-based design of underground infrastructure.
A coupled heat–cold island network framework for urban heat island mitigation: a case study of Central Fuzhou
Ppcd1 corneal dystrophy phenotypes are rescued by Ovol2 disruption and modified by genetic background in a mouse model
Association between dietary vitamins intake and the DMFT index: a cross-sectional analysis of the Rafsanjan cohort study
Interpretable machine learning reveals the synergistic impact of essential hypertension on early recurrence in triple-negative breast cancer
Abstract Triple-negative breast cancer (TNBC) patients often ential hypertension, yet how systemic vascular stress synergizes with tumor aggressiveness to drive early recurrence remains poorly understood. A cohort of 549 TNBC patients with comorbid hypertension was analyzed. Fifteen multidimensional clinical and hemodynamic features were extracted. We constructed and compared four machine learning models, employing SHapley Additive exPlanations (SHAP) on the optimal model to decode non-linear interactions. XGBoost demonstrated superior discriminative performance for predicting early recurrence (AUC = 0.840), significantly outperforming logistic regression ( P = 0.004). SHAP dependence analysis revealed profound non-linear thresholds, with relapse risk escalating exponentially when systolic blood pressure exceeded 140 mmHg. Furthermore, SHAP interaction tensors identified a robust synergistic effect between widened pulse pressure and tumor invasiveness (e.g., tumor size and lymphovascular invasion), indicating that arterial stiffness critically exacerbates malignant dissemination. These findings suggest that systemic hemodynamic stress and endothelial injury synergistically amplify the inherent aggressiveness of TNBC. The interpretable XGBoost framework provides a reliable, multidimensional risk stratification tool to guide personalized cardio-oncology management and safely triage low-risk patients.
Development of pH-responsive gelatin/PVP nanogel by gamma radiation for controlled delivery of silibinin
Abstract Silibinin (SB) is a natural polyphenolic flavonoid with recognized health and therapeutic potential. SB has poor aqueous solubility, which limits its bioavailability and therapeutic effectiveness. To overcome these limitations, a pH-responsive gelatin/polyvinylpyrrolidone (Gel/PVP) nanogel was synthesized via γ-irradiation (5 kGy) for controlled SB delivery. SB/PVP solid dispersions were first prepared by solvent evaporation to enhance dissolution, then incorporated into the preformed Gel/PVP nanogel in the presence of N-hydroxysuccinimide (NHS), yielding the SB/Gel/PVP formulation. FTIR confirmed effective crosslinking between gelatin and PVP and successful SB encapsulation, while XRD revealed an amorphous state favorable for solubility. TEM micrograph of SB/Gel/PVP showed cubic nanoparticles < 50 nm, with a zero-point charge at pH 5.5. The nanogel achieved SB entrapment efficiency of 82% and a loading capacity of 3.34%. In vitro release studies demonstrated pH-responsive behavior, with SB release threefold higher than free drug after 6 h, and the highest release was observed at pH 4.5. The MTT assay confirmed that the SB/Gel/PVP nanogel significantly inhibited HepG2 cell proliferation compared with free SB ( P < 0.05). Moreover, the biochemical and histopathological analyses of liver and kidney tissues in rats treated with SB or SB/Gel/PVP (25 mg/kg) indicated good biocompatibility. Collectively, these findings highlight Gel/PVP nanogels as a promising platform for sustained and targeted SB delivery in pharmaceutical applications.
The impact of exposure to fluoride in drinking water on intelligence in school age children in Iran
Green synthesis of copper oxide nanoparticles using spent green tea extract and their dosage-dependent bioactivity and mango preservation performance
Geological, land use and biological influences on carbon cycling and CO2 degassing in the Danube River
Abstract River systems form critical interfaces in the terrestrial-atmospheric carbon cycle, yet basin-scale constraints on the spatial and seasonal controls of inorganic carbon dynamics and CO 2 exchange remain limited. We present a multi-seasonal longitudinal assessment of dissolved inorganic carbon (DIC), its stable isotopes ( δ 13 C DIC ), and aqueous CO 2 partial pressure ( p CO 2(aq) ) along the entire Danube River. Five sampling campaigns captured seasonal variability along the main stem and major tributaries of this geologically diverse basin. DIC comprised > 90% of total carbon, showing limited longitudinal and seasonal variability (0.3 to 5.3 mmol L − 1 ), with highest concentrations in the upper Danube due to groundwater inputs and carbonate weathering, followed by downstream homogenization. In contrast, δ 13 C DIC increased downstream from − 13.3 to -8.7‰, indicating cumulative CO 2 degassing, with deviations linked to tributary inflows and biological activity. C 4 plant inputs may have contributed up to 27.2% to the δ 13 C DIC . River p CO 2(aq) ranged from ∼260 to 3,770 µatm, predominantly supersaturated, with CO 2 fluxes of 0.975–1.993 Gg C d⁻¹, confirming the Danube as a persistent CO 2 source. Near-equilibrium conditions in spring and summer coincided with enriched δ 13 C DIC , consistent with episodic photosynthetic uptake. These results reveal how groundwater inputs, in-stream photosynthesis, and air-water exchange regulate inorganic carbon dynamics and CO 2 emissions in large rivers.