Search Results (7,753)

Background/Objectives: Large language models (LLMs) show promise for patient education, yet their safety and efficacy for chronic diseases requiring lifelong management remain unclear. This study presents the first comprehensive comparative evaluation of three leading LLMs for celiac disease patient education. Methods: We conducted a cross-sectional evaluation comparing ChatGPT-4, Claude 3.7, and Gemini 2.0 using six blinded clinical specialists (four gastroenterologists and two dietitians). Twenty questions spanning four domains (general understanding, symptoms/diagnosis, diet/nutrition, lifestyle management) were evaluated for scientific accuracy, clarity (5-point Likert scales), misinformation presence, and readability using validated computational metrics (Flesch Reading Ease, Flesch-Kincaid Grade Level, SMOG index). Results: Gemini 2.0 demonstrated superior performance across multiple dimensions. Gemini 2.0 achieved the highest scientific accuracy ratings (median 4.5 [IQR: 4.5–5.0] vs. 4.0 [IQR: 4.0–4.5] for both competitors, p = 0.015) and clarity scores (median 5.0 [IQR: 4.5–5.0] vs. 4.0 [IQR: 4.0–4.5], p = 0.011). While Gemini 2.0 showed numerically lower misinformation rates (13.3% vs. 23.3% for ChatGPT–4 and 24.2% for Claude 3.7), differences were not statistically significant (p = 0.778). Gemini 2.0 achieved significantly superior readability, requiring approximately 2–3 fewer years of education for comprehension (median Flesch-Kincaid Grade Level 9.8 [IQR: 8.8–10.3] vs. 12.5 for both competitors, p < 0.001). However, all models exceeded recommended 6th–8th grade health literacy targets. Conclusions: While Gemini 2.0 demonstrated statistically significant advantages in accuracy, clarity, and readability, misinformation rates of 13.3–24.2% across all models represent concerning risk levels for direct patient applications. AI offers valuable educational support but requires healthcare provider supervision until misinformation rates improve. Full article

Accurate estimation of flow discharge, Q, through hydraulic structures such as spillways and gates is of great importance in water resources engineering. Each hydraulic structure, due to its unique characteristics, requires a specific and comprehensive study. In this regard, the present study innovatively focuses on predicting Q through Rectangular Top-Hinged Gates (RTHGs) using advanced Gradient Boosting (GB) models. The GB models evaluated in this study include Categorical Boosting (CatBoost), Histogram-based Gradient Boosting (HistGBoost), Light Gradient Boosting Machine (LightGBoost), Natural Gradient Boosting (NGBoost), and Extreme Gradient Boosting (XGBoost). One of the essential factors in developing artificial intelligence models is the accurate and proper tuning of their hyperparameters. Therefore, four powerful metaheuristic algorithms—Covariance Matrix Adaptation Evolution Strategy (CMA-ES), Sparrow Search Algorithm (SSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA)—were evaluated and compared for hyperparameter tuning, using LightGBoost as the baseline model. An assessment of error metrics, convergence speed, stability, and computational cost revealed that SSA achieved the best performance for the hyperparameter optimization of GB models. Consequently, hybrid models combining GB algorithms with SSA were developed to predict Q through RTHGs. Random split was used to divide the dataset into two sets, with 70% for training and 30% for testing. Prediction uncertainty was quantified via Confidence Intervals (CI) and the R-Factor index. CatBoost-SSA produced the most accurate prediction performance among the models (R² = 0.999 training, 0.984 testing), and NGBoost-SSA provided the lowest uncertainty (CI = 0.616, R-Factor = 3.596). The SHapley Additive exPlanations (SHAP) method identified h/B (upstream water depth to channel width ratio) and channel slope, S, as the most influential predictors. Overall, this study confirms the effectiveness of SSA-optimized boosting models for reliable and interpretable hydraulic modeling, offering a robust tool for the design and operation of gated flow control systems. Full article

This review systematically analyzes 215 papers on the remote sensing monitoring of Spartina alterniflora (S. alterniflora) indexed in the Web of Science database to clarify research progress and future development directions in this field. We applied CiteSpace 6.3.R1 to conduct a bibliometric analysis of remote sensing literature on S. alterniflora, summarizing the technical methodologies across three major domains: distribution dynamics, parameter inversion, and ecosystem functions and services. We traced the technological evolution of multi-source remote sensing and artificial intelligence, and explored application prospects in addressing current challenges and supporting precision management. Our research indicates that the primary challenge lies in the complex and diverse spatiotemporal dynamics of S. alterniflora. To achieve timely monitoring of S. alterniflora changes and large-scale ecological impact assessments, it is essential to fully utilize the advantages of multi-source remote sensing big data. Harnessing artificial intelligence technologies to fully exploit the potential of remote sensing data, enhancing multi-source data fusion, and expanding sample libraries are essential to achieve comprehensive monitoring spanning spatial patterns, ecological processes, and ecosystem functions and services. These efforts will provide a scientific basis and decision-making support for the sustainable management of coastal wetlands. Full article

The coal mining subsidence area constitutes a distinct ecotone in the transition from agricultural soil to sediment, yet the microbially mediated nitrogen cycle within it remains inadequately understood. This investigation comprehensively analyzed physicochemical properties, microbial communities, functional genes, and co-occurrence networks along a 0–6500 mm depth gradient. Results indicated that pH transitioned from acidic to alkaline, while TN, TP, OM, and NH₄⁺–N accumulated with depth. NO₃⁻–N decreased rapidly within 1000 mm and then stabilized. Alpha-diversity showed an S-shaped increase in richness, with Shannon index peaking at 1500 mm. Beta-diversity shifted along PC1, and the shallow subsidence area (SS) influenced by NO₃⁻–N; the transition zone (TZ) regulated by OM, TN, and NH₄⁺–N; deep subsidence area (DS) was constrained by TP and pH. Microbial communities transitioned from aerobic/facultative to strictly anaerobic phyla, yet Pseudomonadota remained dominant (24–32%) across depths. With increasing depth, gene abundances for denitrification, assimilatory nitrate reduction to ammonium (ANRA), and nitrate assimilation declined, while those for dissimilatory nitrate reduction to ammonium (DNRA) and nitrification increased; nitrogen fixation remained weak. Co-occurrence networks shifted from highly connected, short-pathlength, and clustered in TZ to highly modular and long-pathlength in DS, with Aminicenantes, Syntrophus, and Methanoregula as key taxa. Overall, the thick and stable reducing zone in the subsidence area restructured the nitrogen cycle, shifting terminal products from N₂ removal to NH₄⁺ retention. These findings advance the understanding of nitrogen transformation in soil-sediment ecotones and provide a mechanistic framework for nitrogen cycling in mining-affected ecosystems. Full article

Concrete-filled steel tube (CFST) columns are composite structural elements preferred in various engineering structures due to their superior properties compared to those of traditional structural elements. However, fire resistance analyses are complex due to CFST columns consisting of two components with different thermal and mechanical properties. Significant challenges arise because current design codes and guidelines do not provide clear guidance for determining the time-dependent fire performance of these composite elements. This study aimed to address the existing design gap by investigating the fire behavior of circular long CFST columns under axial compressive load and developing robust, accurate, and reliable design models to predict their fire performance. To this end, an up-to-date database consisting of 62 data-points obtained from experimental studies involving variable material properties, dimensions, and load ratios was created. Analytical design models were meticulously developed using two advanced soft computing techniques: artificial neural networks (ANNs) and genetic expression programming (GEP). The model inputs were determined as six main independent parameters: steel tube diameter (D), wall thickness (t_s), concrete compressive strength (f_c), steel yield strength (f_sy), the slenderness ratio (L/D), and the load ratio (μ). The performance of the developed models was comprehensively compared with experimental data and existing design models. While existing design formulas could not predict time-based fire performance, the developed models demonstrated superior prediction accuracy. The GEP-based model performed well with an R-squared value of 0.937, while the ANN-based model achieved the highest prediction performance with an R-squared value of 0.972. Furthermore, the ANN model demonstrated its excellent prediction capability with a minimal mean absolute percentage error (MAPE = 4.41). Based on the nRMSE classification, the GEP-based model proved to be in the good performance category with an nRMSE value of 0.15, whereas the ANN model was in the excellent performance category with a value of 0.10. Fitness function (f) and performance index (PI) values were used to assess the models’ accuracy; the ANN (f = 1.13; PI = 0.05) and GEP (f = 1.19; PI = 0.08) models demonstrated statistical reliability by offering values appropriate for the expected targets (f ≈ 1; PI ≈ 0). Consequently, it was concluded that these statistically convincing and reliable design models can be used to consistently and accurately predict the time-dependent fire resistance of axially loaded, circular, long CFST columns when adequate design formulas are not available in existing codes. Full article

Objectives: To assess retinal microvascular changes in patients with Grade II and III obesity before and after bariatric surgery using Optical Coherence Tomography Angiography (OCTA), and to compare these metrics with age- and sex-matched healthy controls. Methods: Prospective, consecutive, longitudinal cohort study with a 12-month follow-up. Grade II and III obese patients scheduled for bariatric surgery underwent comprehensive ophthalmic examinations, including OCTA imaging, prior to the surgery and postoperatively at 1 month, 6 months, and 12 months post-surgery. Results: A total of 43 eyes from 43 patients with obesity (one eye per patient) were included at baseline. At 12 months post-surgery, there was a significant increase in vessel density (VD) (16.70 vs. 17.68; p < 0.01) and perfusion density (PD) (0.406 vs. 0.433; p < 0.01), reaching values comparable to those of the control group (17.73 and 0.434, respectively). Significant reductions were also observed in body mass index (BMI) (43.74 vs. 29.53; p < 0.01), body weight (122.44 kg vs. 81.90 kg; p < 0.01), and intraocular pressure (IOP) (15.72 mmHg vs. 14.16 mmHg; p < 0.01). Conclusions: This study demonstrates a compelling association between obesity and retinal microvascular impairment, highlighting the efficacy of bariatric surgery not only in achieving substantial weight loss but also in improving the retinal perfusion of these patients, achieving metrics at 12 months comparable to age- and sex-matched healthy controls at baseline. These findings raise the hypothesis of the potential utility of OCTA as a monitoring tool for tracking the microvascular status in patients with obesity undergoing bariatric surgery in a longitudinal manner. Full article

The socioecological system (SES) of the Qilian Mountains community—mountains, water, forests, fields, lakes, grasslands, and sands—faces considerable challenges from climate change and anthropogenic pressures. Here, we aimed to examine the coupled coordination relationships within the Qilian Mountains community. Using a comprehensive evaluation index system for the socioeconomic components of the life community, we analyzed the spatiotemporal evolution of the coupled coordination degree (CCD) from 2000 to 2023, identified key hindering factors, and forecasted future trends based on a grey prediction model. The overall CCD achieved a historic leap from near-disharmony to sound coordination. The findings reveal the following: (1) The overall CCD achieved a historic leap from near-disharmony to sound coordination from 0.340 to 0.523, indicating a transition into a synergistic development phase, though with persistent spatial disparities. (2) System coordination is primarily constrained by water, farmland, and grassland subsystems, with water supply–demand imbalance being the foremost regional obstacle. In the Hexi Oasis area, this manifests as a sharp contradiction between farmland expansion and agricultural water demand. In the Qinghai region, it is deeply intertwined with topography, water yield modulus, and the distribution of forested and aquatic areas. (3) GM(1,1) projections suggest a continued upward trajectory for CCD, yet also underscore the complexity and long-term nature of coordinated development. This study established a framework for socioecological system research in arid and vulnerable regions, with the conclusions providing a reference for optimizing national ecological security barrier construction and regional high-quality coordinated development. Full article

The Volga is the largest river in Europe and its headwaters comprise reference or least disturbed conditions. In the headwaters of the Volga (445 km) upstream of Tver, 27 diatom samples (18 from the Volga and nine from selected tributaries) were collected in shallow water along the banks from different habitats, wherefrom 270 taxa (244 pennate and 26 centric) were identified. Most benthic taxa were found within Naviculaceae (40 taxa), Fragilariaceae (29 taxa), Bacillariaceae (27 taxa), Achnanthaceae (23 taxa), Gomphonemataceae (19 taxa), Cymbellaceae (17 taxa), and 16 taxa belong to the Amphora-complex. Species richness in the Volga and its tributaries was comparable; the mean value was 46 in the Volga and 50 in the tributaries. Regarding the saprobic index, the source region (reach R1) was characterized by a large proportion of xeno- and oligo-saprobic species, with the proportion of oligo-beta and beta-meso-saprobic species increasing along the continuum. This study provides a first comprehensive checklist of benthic diatoms for the Volga headwaters and analyzes longitudinal changes as well as the interplay between abiotic parameters and the diatom community in the headwaters of the Volga. Full article

This study evaluates South Africa’s progress toward achieving SDG 4.5 by examining disparities in educational access and outcomes for vulnerable groups, including girls, children with disabilities, rural populations, and low-income households. The study recognises multidimensional inequalities and develops strategies that promote inclusive and equitable education. The quantitative approach was employed by constructing a composite Educational Equity Index (EEI) using seven indicators: gender parity in primary and lower secondary completion, location-based attainment among adults, gender parity in adult lower secondary education, disability parity in primary completion, gender parity among the poorest quintile, and wealth parity in youth literacy. These indicators were standardised and aggregated to develop the EEI. The study developed a multivariate regression model to identify the most influential parity factors affecting youth literacy outcomes. Data from UNESCO, the World Bank, and national education statistics were sourced. The findings revealed persistent inequities across gender, disability, geography, and economic status, with particularly pronounced disparities in adult participation, rural attainment, and youth literacy among poorer households. While parity in youth literacy and primary education completion has been largely achieved, inequities persist in secondary education completion and adult education. The findings further revealed that upper secondary completion had a strong positive impact on equity outcomes, whereas disparities in adult participation significantly hindered progress. This study conducted a comprehensive, data-driven examination of educational equity in South Africa. By presenting a novel index approach customised to SDG 4.5, it provided fresh insights into multidimensional inequalities and offered actionable evidence for targeted policy interventions. The study contributes to scholarship on inclusive education while highlighting practical pathways for South Africa to accelerate progress toward equity in line with global education commitments. Full article

Background/Objectives: Flavonoids have been extensively investigated as reducing and stabilizing agents in the green synthesis of metallic nanoparticles. However, studies specifically employing pure naringin (NG) and naringenin (NGN) remain relatively scarce. Methods: In the present work, silver nanoparticles (AgNPs) were synthesized under controlled laboratory conditions using NG and NGN as bioreductants, and critical parameters governing nanoparticle formation were optimized. The synthesized AgNPs were comprehensively characterized using ultraviolet–visible (UV–Vis) spectroscopy, dynamic light scattering (DLS), scanning transmission electron microscopy (STEM), energy-dispersive X-ray spectroscopy (EDX), and Fourier-transform infrared spectroscopy (FTIR). Results: The characterization analyses confirmed the successful formation of predominantly spherical AgNPs with average particle sizes of 17 nm (AgNG) and 20.4 nm (AgNGN). DLS analysis indicated zeta potentials of approximately −30 mV and PDIs of 0.45 (AgNG) and 0.29 (AgNGN), consistent with stable colloidal dispersions. Biological evaluations revealed that both AgNP systems exhibited notable antioxidant and antimicrobial activities. Furthermore, cytogenetic assessment using the Allium cepa assay demonstrated concentration-dependent alterations in mitotic index and chromosomal integrity, indicating biological activity at cellular level. Conclusions: Collectively, these results underscore the potential of flavonoid-mediated synthesis as an eco-friendly and effective approach for generating stable, bioactive nanomaterials with promising biological applications. Full article

Urban street sweeping infrastructure plays a critical role in municipal solid waste management by mitigating particulate matter resuspension and preventing contaminant mobilization into water bodies, thereby supporting public health and environmental sustainability. The primary objective of this study is to develop a dynamic evaluation model for urban street sweeping services in four localities of Bogotá, Colombia. Operating system variables are integrated with citizens’ perceptions to capture their coupled socio-environmental behavior. The methodology comprised four phases: a global literature review, a citizen-perception survey, the development of a dynamic simulation model integrating perceptions, and a statistical analysis of all collected data. The results demonstrate that technical efficiency in street sweeping operations, measured through the street cleanliness index, is insufficient to ensure service sustainability without incorporating citizen perception metrics. The model reveals that geometric, spatial, and climatic factors reduce the street cleanliness index by up to 100%, highlighting infrastructure vulnerability to external conditions. Model validation exposes a critical gap between operational cleanliness and citizen perception, with decreases of up to 64.2% in comprehensive service evaluation. The inclusion of perception indicators (Cronbach’s α = 0.770) underscores the significance of variables such as service punctuality and personnel attitude in determining citizen satisfaction and overall service assessment. The dynamic model constitutes a robust decision-support tool for optimizing resource allocation, mitigating socio-environmental impacts, and strengthening institutional legitimacy in urban infrastructure maintenance. Nevertheless, limitations in representing external factors (informal commerce and illegally parked vehicles) and spatial heterogeneity in cleanliness indices suggest future research directions incorporating stochastic modeling approaches and longitudinal studies on citizen perception dynamics. Full article

Background: Left atrial strain (LAS) derived from speckle-tracking echocardiography (STE) provides a sensitive, load-dependent measure of atrial function and ventricular filling pressures. Data on LAS in paediatric cardiomyopathies are still scarce; therefore, this study aimed to assess LA phasic function in dilated (DCM) and hypertrophic (HCM) cardiomyopathy and to determine its relationship with clinical and echocardiographic indices of disease severity. Methods: We conducted a cross-sectional case–control study that included 84 children (DCM n = 29, HCM n = 29, control n = 26) who underwent comprehensive clinical and echocardiography evaluation, including LAS parameters (reservoir—LASr; conduit—LAScd; and contractile—LASct). Group comparisons were performed using ANOVA or Kruskal–Wallis tests with post hoc adjustments, and correlations were analysed using Pearson’s or Spearman’s coefficients. Multivariable linear and logistic regression models were adjusted for age, body surface area (BSA), heart rate (HR), and blood pressure (BP) percentiles. Results: LASr and LAScd were significantly reduced in both cardiomyopathy groups compared with controls (p < 0.001), following a graded pattern (DCM < HCM < control). In DCM, lower LASr was independently associated with higher left atrial volume index (LAVi) and elevated E/E′ ratio, whereas in HCM, septal hypertrophy (IVSd Z-score) and log NT-proBNP were dominant determinants of impaired LASr. In logistic regression, LASr (OR = 0.93, p = 0.016) and LAScd (OR = 1.21, p = 0.001) independently predicted severe NYHA/Ross functional class after covariate adjustment, while LASct showed no significant association. Conclusions: These findings demonstrate that LA reservoir and conduit strain are markedly impaired in paediatric cardiomyopathy and are strongly linked to structural remodelling and functional limitation, underscoring their value as sensitive non-invasive markers of disease severity. Full article

To explore the potential of new information transmission windows, this work presents a broadband plasmonic filter based on gold-deposited silicon photonic crystal fiber (PCF) operating in mid-infrared regime numerically, using the finite element method (FEM). The simulation results indicate that the interaction between the high-refractive-index pure silicon material and the gold layer can cause a shift of the resonance central point to the mid-infrared band, which provides the prerequisite for mid-infrared filtering. When the cladding holes’ diameter is 1.3 µm, the inner holes’ diameter is 1.04 µm, the diameter of the holes located on both sides of the core region is 2.08 µm, the gold-coated holes’ diameter is 2.08 µm, the lattice constant is 2 µm, and the gold thickness is 50 nm, this PCF can operate in the mid-infrared band near the central wavelength of 3 µm. The 1 mm long PCF polarizer exhibits a maximum extinction ratio (ER) of −43.5 dB at 3 µm and a broad operating bandwidth of greater than 820 nm with ER better than −20 dB. Additionally, it also possesses high fabrication feasibility. This in-fiber polarization filter, characterized by its comprehensive performance and ease of fabrication, aids in exploring the development potential of high-speed and large-capacity modern communication networks within new optical bands and contributes to new photonic computing and sensing. Full article

Generative adversarial networks (GANs) typically require large datasets for effective training, which poses challenges for volumetric medical imaging tasks where data are scarce. This study addresses this limitation by extending adaptive discriminator augmentation (ADA) for three-dimensional (3D) StyleGAN2 to improve generative performance on limited volumetric data. The proposed 3D StyleGAN2-ADA redefines all 2D operations for volumetric processing and incorporates the full set of original augmentation techniques. Experiments are conducted on the NoduleMNIST3D dataset of lung CT scans containing 590 voxel-based samples across two classes. Two augmentation pipelines are evaluated—one using color-based transformations and another employing a comprehensive set of 3D augmentations including geometric, filtering, and corruption augmentations. Performance is compared against the same network and dataset without any augmentations at all by assessing generation quality with Kernel Inception Distance (KID) and 3D Structural Similarity Index Measure (SSIM). Results show that volumetric ADA substantially improves training stability and reduces the risk of a mode collapse, even under severe data constraints. A strong augmentation strategy improves the realism of generated 3D samples and better preserves anatomical structures relative to those without data augmentation. These findings demonstrate that adaptive 3D augmentations effectively enable high-quality synthetic medical image generation from extremely limited volumetric datasets. The source code and the weights of the networks are available in the GitHub repository. Full article

This study explores the applicability of the Laffer Curve in the context of the European Union (EU) by analyzing the relationship between taxation and fiscal revenue across personal income tax (PIT), corporate income tax (CIT), and value-added tax (VAT). Utilizing a comprehensive panel data set spanning 1995 to 2022 across all 27 EU member states, the research also integrates the Bird Index to assess fiscal effort and employs advanced econometric techniques, including the Hausman Test and log-quadratic regression models, to capture the non-linear dynamics of the Laffer Curve. The findings reveal that excessively high tax rates, particularly in some larger member states, may lead to revenue losses due to reduced economic activity and tax evasion, highlighting the existence of optimal tax rates that maximize revenue while sustaining economic growth. By estimating threshold tax rates and incorporating the Bird Index, the study provides a nuanced perspective on tax efficiency and fiscal sustainability, offering evidence-based policy recommendations for optimizing tax systems in the European Union to balance revenue generation with economic competitiveness. Full article