Search Results (4,433)

Background/Objectives: A known disadvantage of extracardiac Fontan is the absence of growth potential and potential late flow stagnation compared to lateral tunnel Fontan. This study investigates the differences in changes in the cross-sectional area and impact on liver fibrosis. Methods: The anteroposterior and lateral diameters of the Fontan pathways were measured using angiograms. Cross-sectional area and the indexed cross-sectional area were calculated, and their relation to Fibrosis-4 index was analyzed. Results: A total of 334 angiograms of 224 patients (212 extracardiac and 12 lateral tunnel Fontan) were evaluated. The median age at Fontan was 2.2 (Interquartile Range: 1.8–2.9) years. The median period from Fontan to angiogram was 3.3 (0.04–10.8) years. Cross-sectional areas remained unchanged in extracardiac Fontan patients and increased in lateral tunnel Fontan patients. The indexed cross-sectional areas in extracardiac Fontan patients decreased over time. The smallest indexed-cross-sectional areas were 200 mm²/m² in extracardiac Fontan patients at 10 years postoperatively, whereas indexed cross-sectional areas in lateral tunnel Fontan patients were larger and more variable. Fibrosis-4 index increased time-dependently in both groups. Indexed cross-sectional area at the smallest level <156 mm²/m² was identified as a risk factor for liver fibrosis. Conclusions: The Fontan pathway expanded in patients after lateral tunnel Fontan, whereas indexed cross-sectional area decreased over time after extracardiac Fontan. Importantly, in patients after extracardiac Fontan, narrowing of the Fontan pathway might be one of the risk factors for progression of liver fibrosis. Full article

Fracture roughness is critical to fluid flow behavior in fractured rock masses. However, the mechanism by which such roughness heterogeneity influences fluid flow and amplifies cubic law deviation remains incompletely understood. Current theoretical analyses are focused on uniform roughness or smooth parallel plates, neglecting the roughness heterogeneity in natural fractures. The equivalent fracture geometry models with heterogeneous roughness are established based on the fracture walls of the smooth parallel plates and the sinusoidal profiles in this study. Based on the geometry models and derived from the Navier–Stokes equations, two simplified fracture models are proposed: the equivalent plate–sinusoidal walled and the sinusoidal–sinusoidal walled fracture model, validated via COMSOL Multiphysics. A roughness heterogeneity index Z_r is defined to quantify the roughness heterogeneity. The influence of roughness heterogeneity on hydraulic behavior (e.g., fluid flow rate, equivalent hydraulic aperture) is analyzed and compared with those of uniform roughness and smooth parallel plates. Additionally, the influence of roughness heterogeneity on the power–law exponent relationship between fracture mechanical aperture and flow rate is examined. The results indicate that the flow rate and hydraulic aperture decrease with increasing roughness heterogeneity, while the deviation of fluid flow from the cubic law increases. The power–law exponent can be as high as 15.5. This study provides theoretical models for understanding the effects of roughness heterogeneity and a reference for extending flow models to complex fracture morphologies. Full article

Against the backdrop of smart cities and digital cultural tourism, the accurate prediction of urban passenger flow is of great significance for public security management and resource allocation. However, existing studies mostly rely on single data sources or only perform a simple concatenation of multi-source features, lacking systematic indicator system design. Meanwhile, weekly or monthly data are commonly used with coarse temporal granularity, making it difficult to capture short-term fluctuations and lag effects. To overcome these limitations, this paper collects the daily passenger flow data of Hangzhou from 15 March 2024 to 15 March 2025; integrates multi-dimensional factors such as keyword search trends across platforms, holidays and major events, and online public opinion; and constructs three daily characteristic indicators: online search index, humanistic–meteorological index, and textual sentiment index. The data denoising, dimensionality reduction, and sentiment quantification are realized through methods including SSA, PCA, and SnowNLP. On this basis, a hybrid CNN-GRU model integrated with the attention mechanism is proposed. An improved artificial bee colony (ABC) algorithm is adopted for global hyperparameter optimization, and a weighted hybrid loss function (JQHL) is introduced to enhance the model’s adaptability to extreme values. The results show that the ABC-CNN-GRU-Attention model, incorporating multi-dimensional indicators, outperforms traditional methods on evaluation metrics, including MAE, RMSE, MAPE, R², and RPD, demonstrating a higher prediction accuracy and robustness. Full article

Soil preferential flow plays a crucial role in governing hydrological cycles and soil moisture distribution in mountain forests. This makes it essential for understanding subsurface water movement and for guiding hillslope hydrological management. In this study, soil preferential flow, soil properties, and root characteristics across three slope positions on a Larix gmelinii var. principis-rupprechtii (Mayr) Pilger (larch) plantation hillslope in the Liupan Mountains were systematically observed to reveal the spatial patterns and formation mechanisms of hillslope soil preferential flow. The results showed that soil preferential flow development followed a distinct spatial pattern across the slope positions, with the mid-slope exhibiting the most developed preferential flow characteristics. The comprehensive preferential flow index further quantified this spatial variation, ranking the slope positions as mid-slope > upper slope > lower slope. Different soil structural properties exerted varying influences on preferential flow. Macropore-related properties (low bulk density and high porosity and saturated conductivity) promoted most preferential flow, whereas aggregate-related properties (high organic matter and water-stable aggregates) suppressed it. The influence of root characteristics on preferential flow was also dual. Root length density generally promoted preferential flow (e.g., DC, LI, and UniFr), whereas root surface area density primarily exerted an inhibitory effect (e.g., LI, UniFr, and total stained area TotStAr). This study clarifies how slope position modulates preferential flow through soil and root characteristics, offering insights for slope-specific hydrological understanding and targeted soil and water conservation practices. Full article

The middle and lower reaches of the Yangtze River Basin occupy a strategically pivotal position in regional development; yet extreme drought-runoff events pose severe threats to water supply and ecological security. Despite this, systematic research gaps persist, including the lack of a unified definition, standardized identification criteria, and clear understanding of formation mechanisms for extreme drought-runoff. To address these limitations, this study focused on extreme drought-runoff in the basin, utilizing 1956–2024 discharge data from four mainstream hydrological stations and meteorological data from 171 stations. Quantitative discrimination criteria were established via Pearson-III frequency analysis; meteorological characteristics were analyzed using the Meteorological Drought Comprehensive Index; and formation mechanisms were explored through partial correlation analysis and multiple linear regression. This study innovatively proposed a basin-wide three-level quantitative discrimination criterion for drought-runoff based on the June–November flow frequency of key mainstream stations, which is distinguished from single-indicator drought identification methods (SPI/SPEI/SSI) by integrating basin-scale hydrological coherence and seasonal drought characteristics. The results revealed basin-wide extreme drought-runoff in 2006 and 2022, severe drought-runoff in 1972 and 2011, and relatively severe drought-runoff in 1959, 1992, and 2024. Typical extreme drought-runoff events were characterized by sustained low precipitation and high temperatures. Meteorological factors emerged as the primary driver during June–September, while reservoir operation and riverine water intake played secondary roles. Notably, the large-scale reservoir group in the Yangtze River Basin (53 key control reservoirs) helped alleviate drought-runoff impacts from December to May (non-flood season) via water supplementation. These findings provide a robust scientific basis for precise drought-runoff prediction and the development of targeted adaptation strategies in the Yangtze River Basin. Full article

In response to the complex erosion environment caused by periodic water level fluctuations, dry–wet cycles, and long-term water flow scouring on the Yangtze River bank, three typical soil-fixing and bank-protecting plants, Cynodon dactylon, Carex breviculmis, and Digitaria sanguinalis, which can adapt to both aquatic and terrestrial conditions, were selected for planting experiments. Tests on root–soil composite shear strength, disintegration, and water flow scouring were conducted to investigate the effects of different bank-protecting plants on bank stabilization. The results show that: 1. The root systems of the three plants significantly enhance the soil shear strength at various soil depths, but the reinforcing effect decreases with increasing soil depth. The cohesion strength of the root–soil composites ranks as Carex breviculmis > Digitaria sanguinalis > Cynodon dactylon, with maximum increases of 54.83 kPa, 20.66 kPa, and 6.5 kPa, respectively, equivalent to 3.16, 1.82, and 1.26 times that of bare soil. 2. Under dry–wet cycling, the water stability of the root–soil composites is significantly higher than that of bare soil. The disintegration residual rate of Cynodon dactylon and Digitaria sanguinalis decreased from 81.76% to 38.23% and from 80.18% to 34.34%, respectively, whereas Carex breviculmis showed only a slight decrease from 80.41% to 75.1%. Carex breviculmis exhibits the strongest stability and is least affected by dry–wet cycles, while the water stability of Cynodon dactylon and Digitaria sanguinalis declines noticeably with increasing cycle numbers. The plants’ ability to improve soil water stability ranks as Carex breviculmis > Cynodon dactylon > Digitaria sanguinalis. 3. The enhancement of bank erosion resistance is mainly attributed to the formation of a root-reinforced network, which strengthens the soil through root–soil interlocking and anchorage, thereby increasing resistance to flow-induced shear stress and reducing particle detachment under hydraulic action. The bank erosion resistance index ranks as Carex breviculmis > Cynodon dactylon > Digitaria sanguinalis, and decreasing with increasing runoff velocity. Compared to bare soil slopes, the maximum enhancement effects on bank erosion resistance are 75.1%, 63.3%, and 54.2% respectively. Full article

Background/Objectives: The question addressed in the current work is to develop a simulation of a pharmaceutical process (DNA encapsulation within lipid nanoparticles using a microfluidic micromixer) which will be of utility to the end users (laboratory-scale formulation development). The simulation and the microfluidic approach also address sustainability issues, such as reducing the environmental impact of the process itself, and reducing the need for physical testing. The paper details the implementation and validation, taking into account key performance indicators and control parameters. Methods: The main method applied for simulation development is a novel multi-agent approach to incorporate stochastic probabilistic behavior, combined with theoretical definitions from the process experts and relevant literature, and data/results from laboratory-scale experiments with different parameter configurations. Results: The simulation was implemented as a representation of the real physical process, reproducing the relationships between process parameters (flow rates) and experimental key performance indicators (capsule diameter, poly dispersion index, encapsulation efficiency). The simulation results demonstrated a general agreement with the empirical results and provided useful predictive insights for the laboratory experiments. Conclusions: The simulation has potential as a support tool for laboratory experiments to reduce physical testing and indicate the most promising configurations on which to focus, with potential savings in time, resources and other costs. Full article

Background and Objectives: Halitosis can impair psychosocial well-being, and orthodontic appliances may modify plaque retention and oral ecology. We compared patient-perceived halitosis burden, clinician-rated malodor, and oral health-related quality of life (OHRQoL) among clear aligner users, fixed-brace patients, and untreated controls, and explored oral and salivary correlates of worse malodor severity. Methods: This cross-sectional study (March 2024–November 2025) enrolled 184 participants aged 15–35 years (aligners n = 62; fixed braces n = 64; controls n = 58). Outcomes were HALT (0–100), organoleptic score (0–5), and OHIP-14 (0–56). Plaque index, gingival inflammation, tongue coating, and unstimulated salivary flow were recorded; low flow was defined as <0.25 mL/min. Organoleptic score ≥ 2 was used descriptively for clinically relevant malodor prevalence, whereas organoleptic score ≥3 defined a moderate-to-severe malodor phenotype for secondary exploratory internal modeling. Multivariable robust linear models (HALT) and proportional-odds ordinal logistic regression (organoleptic severity) were used. Results: Fixed braces showed higher HALT (53.7 ± 6.2) than controls (46.3 ± 6.4) and aligners (41.7 ± 7.4) (p < 0.001), higher organoleptic scores (2.9 ± 0.4 vs. 2.4 ± 0.6 vs. 2.2 ± 0.6; p < 0.001), and worse OHIP-14 (18.6 ± 4.7 vs. 15.9 ± 4.3 vs. 13.8 ± 4.8; p < 0.001). Clinically relevant malodor prevalence (organoleptic ≥ 2) was 96.9% in fixed braces, 79.3% in controls, and 66.1% in aligners (p < 0.001); because ≥2 was used as a broad descriptive threshold, these values should be interpreted as descriptive rather than diagnostic prevalence estimates. In adjusted models, greater tongue coating, higher plaque, and low salivary flow were associated with worse organoleptic severity, whereas appliance category did not remain independently associated with HALT once concurrent clinical correlates were included. Conclusions: Fixed braces showed higher unadjusted malodor burden and worse OHRQoL than aligners and untreated controls, but appliance category should be interpreted as a contextual exposure linked to plaque-retentive conditions rather than as a standalone causal determinant. Plaque accumulation, tongue coating, and lower salivary flow showed the strongest associations with worse malodor severity. These findings should be interpreted in light of the cross-sectional design, possible observer and selection bias, and residual confounding. Full article

Based on the Advanced Geostationary Radiation Imager (AGRI) and Geostationary High-speed Imager (GHI) information in the Fengyun-4B (FY-4B) satellite, we propose a convective initiation (CI) nowcasting algorithm for Sichuan Province, China. The algorithm optimizes satellite reflectance by considering multi-channel brightness differences, visible reflectance, and cloud-top cooling by exploiting the Farneback optical flow, where the cloud is followed by false cooling due to cloud motion. Moreover, the high temporal resolution of GHI enables the detection of early cumulus cloud growth. The algorithm was developed using daytime CI events in the coverage area of Mianyang radar station from 22 July to 9 August 2023, and the remaining areas in the Chengdu scan area were used for validation. The results showed that the proposed method achieves a probability of detection (POD) of 83.1%, a false alarm ratio (FAR) of 33.0%, and a critical success index (CSI) of 58.9%. Compared with the AGRI-only method and the SATCAST algorithm, the POD increases by 5.4% and 8.4%, respectively, while the CSI improves by 1.3% and 2.3%. The average lead time reaches 34.2 min, which is 4.6 min longer than AGRI-only and 7.9 min longer than SATCAST. This suggests that AGRI and GHI data improve the spatiotemporal resolution of CI nowcasting. This approach improves the early detection of convective initiation under the climatic background of warm cloud convection in Sichuan, offering new insights for short-term warnings of regional convective weather. Full article

Traffic variability along heavily congested signalised urban corridors undermines roadway safety, reduces energy efficiency, weakens operational reliability, and can hinder emergency response. Although many simulation-based studies have examined the impacts of Autonomous Vehicles (AVs), relatively few have combined high-resolution congestion observations with link-level microscopic calibration in a real urban network, particularly when evaluating implications for emergency mobility. This study develops and calibrates a microscopic Aimsun traffic simulation model for the Atakum district of Samsun, Türkiye, using a 10 min Google Traffic Index (GTI) observation stream converted into a four-level ordinal congestion scale. The calibration process began with an origin–destination (OD) matrix derived from 2020 traffic counts and was refined through link-level GTI synchronization, iterative OD scaling on mismatched corridors, and signal retiming at key intersections. GTI was validated as an ordinal congestion proxy through both categorical agreement and volumetric consistency, achieving 83% class agreement and GEH values below 5 for more than 90% of links. Five AV penetration scenarios (0%, 25%, 50%, 75%, and 100%) were simulated under peak-hour conditions. Network performance was evaluated using delay, stop time, mean speed, throughput, missed turns, and total journey time, while emergency mobility was assessed along a representative ambulance corridor on Atatürk Boulevard using seconds per kilometre. The results indicate that increasing AV penetration improves flow stability more clearly than nominal capacity. Mean speed increased from 36.2 to 39.2 km/h, delay and stop time declined steadily, and throughput remained nearly constant at 22.2–22.5 thousand vehicles/h. Along the ambulance corridor, travel time improved by 11.5%, from 112.4 to 99.4 s/km, between the baseline and full automation scenarios. These findings provide scenario-based evidence that, within a calibrated signalised urban network, increasing AV penetration can enhance operational stability and emergency response efficiency. More broadly, the study demonstrates the practical value of integrating GTI-based congestion observations with microscopic simulation for AV impact assessment in real urban networks. Full article

Geohazards such as landslides, earthquakes, debris flows, and floods are governed by complex interactions among geological, hydrological, and human processes. Traditional data-driven models have improved hazard prediction but often lack interpretability and adaptability. This review examines the evolution of knowledge-guided approaches in geohazard research, highlighting how knowledge representation and artificial intelligence have progressively converged to enhance understanding, reasoning, and model transparency. A bibliometric analysis of 1410 publications indexed in the Web of Science reveals an evolution from early ontology-based knowledge engineering for expert reasoning to knowledge graphs (KG), frameworks enabling multi-source data integration and relational inference, and more recently, to large language model (LLM), augmented systems for automated knowledge extraction and cognitive geoscience. This review synthesizes advances in knowledge representation, knowledge graphs, and LLM-based reasoning, demonstrating how hybrid models that embed physical laws and expert knowledge can improve the interpretability and generalization of machine learning. These developments enable new forms of knowledge-driven geohazard intelligence and support applications in hazard monitoring, early warning, and risk communication. There are challenges we still face, including semantic fragmentation, limited causal reasoning, and sparse data for extreme events. Future directions require unified knowledge–data–mechanism architectures, causality-aware modeling, and interoperable standards to advance trustworthy and explainable geohazard intelligence. Full article

Drip irrigation system performance is largely governed by emitter hydraulic characteristics. This study systematically compares the hydraulic performance of a novel cylindrical asteroid-shaped channel emitter against a conventional toothed labyrinth design. Standardized specimens were produced using precision molds and integrated into drip tapes at 300 mm spacing. To comprehensively analyze flow behavior, pressure–discharge relationships, flow indices, and internal flow fields, a combination of physical experiments and CFD simulations was employed. Experimental results showed that across 20–200 kPa, the cylindrical asteroid-shaped emitter delivered flow rates 24–28% higher than the labyrinth type while maintaining a lower flow index, demonstrating enhanced hydraulic stability. Flow field analysis at 100 kPa revealed that the divergent asteroid geometry generates more intense and sustained turbulent kinetic energy throughout the channel units, resulting in superior energy dissipation. The cylindrical asteroid-shaped unit achieved a pressure drop of 17.5 kPa, exceeding the 15.3 kPa observed in the labyrinth channel, with outlet velocities of 1.6 m/s versus 1.76 m/s. Additionally, the flow pattern promotes comprehensive wall scouring through large-scale vortices, indicating improved resistance to clogging. These findings validate the design superiority of the cylindrical asteroid-shaped emitter and offer a theoretical reference for developing high-uniformity, water-saving irrigation devices. Full article

Urban demographic dynamics—including migration, aging, fertility change, and population redistribution—are central to sustainable urban development, urban resilience, and long-term well-being. In many small and transition economies, rapid urbanization combined with sustained emigration and population aging poses significant challenges for urban planning, labor markets, housing systems, and public services. The purpose of the paper is to evaluate urban sustainability-related demographic risks by a composite index and assess long-term demographic dynamics with different trajectories of migration flows and fertility. Since migration flows are more intense among urban population, depopulation is very high in peripheral rural areas, and urbanization is about 64% in Armenia, the results of the research will inform national and urban policy makers to reshape policy frameworks to enhance long-term urban resilience. This study develops a demographic threat index (DTI) to assess demographic risks relevant to urban sustainability in Armenia over the period 2000–2023. The index integrates 20 indicators grouped into three pillars—population change, population health, and socio-economic vulnerability—with indicator weights derived using principal component analysis (PCA). The results reveal a persistent increase in demographic risks, marked by accelerated population aging, declining youth cohorts, and rising socio-economic vulnerability, particularly in urban contexts. A decomposition of population change demonstrates that net migration has been the dominant driver of demographic dynamics, outweighing the combined effects of fertility and mortality. Scenario-based population projections further indicate that even optimistic increases in fertility are insufficient to stabilize population trajectories without sustained positive migration. By linking demographic security to urbanization, migration, and socio-economic vulnerability, the study highlights the importance of integrated urban and demographic policy frameworks. The proposed index offers a replicable tool for evaluating demographic risks in countries facing similar urban and demographic transitions and provides evidence-based insights for urban planning, migration management, and sustainable city strategies. Full article

Although soil nematodes are central to belowground energy flow, how vegetation and soil aggregate characteristics interactively regulate the nematode community structure and energy dynamics remains poorly understood. We investigated 80 soil samples from five vegetation types—Prunus armeniaca L. (AV), Pinus tabuliformis Carrière (PT), Caragana korshinskii (CK), Medicago sativa L. (MS), and native grass Stipa bungeana (SB)—and four aggregate sizes (LMA > 2 mm, MMA 0.25–2 mm, SMA 0.053–0.25 mm, and MA < 0.053 mm) on the Loess Plateau. Vegetation types showed clear functional differentiation, in which AV dominated bacterivore diversity and energy flux in LMA, CK enhanced fungivore and herbivore energy flow, SB supported omnivore–carnivore energy flux, and PT exhibited suppressed communities. Fauna analysis of the EI (enrichment index)–SI (structural index) plot revealed aggregate-dependent food web structuring, where all vegetation types clustered in quadrant C (structured, low enrichment) in small aggregates, while PT and MS shifted to quadrant D (structured, enriched) in larger aggregates. SEM showed that energy flux and energy uniformity are driven by nematode abundance (p < 0.01) and diversity (p < 0.01), respectively, with soil aggregates promoting uniformity (p < 0.05) but suppressing total flux (p < 0.05), thus revealing a trade-off between energy throughput and distribution equity. CK maximizes total energy flux, while AV maintains high energy uniformity; as such, they could be keystone restoration species in the study area. This study provides mechanistic insights into soil food web energetics and offers an empirical foundation for optimizing vegetation restoration strategies on the Loess Plateau. Full article

The use of computational fluid dynamics (CFD) to study hemodynamics in arteries offers significant potential for addressing complex flow problems. Due to its enhanced performance hardware and software, CFD has become an important approach for studying hemodynamics in human arteries. This approach is utilized to investigate hemodynamics and forecast risk factors for atherosclerotic lesion development and progression, including circulatory flow, and to analyze local flow fields and flow profiles resulting from geometric changes. This foundational study will aid in analyzing blood flow behavior through the abdominal aorta and the origin and courses of renal arteries, as well as investigating the causes of disorders such as atherosclerosis and hypertension. The current study investigates three idealized abdominal aorta–renal artery junction models under varying blood pressure settings. Materialise software V19 was used to extract the geometry data to create idealized 3D abdominal aorta–renal branching models. Unsteady flow simulations were performed in ANSYS Fluent, utilizing rigid walls and Newtonian and Carreau–Yasuda viscosity conditions. Oscillatory shear index (OSI) and Time-averaged wall shear stress (TAWSS) were measured to enhance understanding of atherosclerotic plaque formation and progression. Also, the effect of geometric change at the bifurcation area was explored, and it was discovered that this location causes considerable vortex forming zones. The evident velocity reduction and backflow development were seen, reducing shear stress. The findings indicate that low TAWSS < 0.4 Pa and OSI > 0.15 areas within the bifurcation region are more susceptible to atherosclerosis development. Full article