Search Results (286)

Background and Objectives: Ureteral kinking may hinder endoscopic access and reduce the success of ureteroscopic lithotripsy (URSL). This study evaluated whether kinking can be predicted preoperatively using non-contrast computed tomography (CT) by introducing a novel metric—Maximum Horizontal Ureteral Displacement (HUDmax)—and assessed its predictive value for procedural success. Materials and Methods: Data from 1261 patients who underwent URSL for a single ureteral stone were retrospectively analyzed. Patients were categorized into two groups based on whether the stone could be reached using a semirigid ureteroscope. Propensity score matching (1:2) was performed based on stone size and location, resulting in two matched cohorts: Group 1—Semirigid Inaccessible (SRI, n = 72), and Group 2—Semirigid Accessible (SRA, n = 144). Stone characteristics, ureteral wall thickness (UWT), and HUDmax were evaluated. Correlations between HUDmax and surgical parameters were analyzed, and the predictive value of HUDmax was assessed using receiver operating characteristic (ROC) analysis. Results: The SRI group showed significantly higher HUDmax values (median 2.36 mm vs. 1.2 mm, p < 0.0001). Semirigid access failure necessitated conversion to flexible ureteroscopy in all SRI cases, compared to 15% in the SRA group (p < 0.0001). Stone-free rates were significantly lower in the SRI group (45% vs. 82%, p < 0.0001), and the use of a double-J stent or nephrostomy placement was more frequent. Operative times were also longer in the SRI group (55 vs. 42 min, p < 0.0001). HUDmax correlated positively with operative time (r = 0.258, p = 0.005) but not with stone size, density, UWT, or hydronephrosis. ROC analysis showed HUDmax strongly predicted semirigid access failure (AUC: 0.805; cutoff: 1.58 mm), and moderately predicted stone-free status (AUC: 0.697; cutoff: 1.68 mm). Conclusions: Severe ureteral kinking constitutes a significant anatomical obstacle to the success of semirigid URSL. This study is the first to demonstrate that clinically relevant kinking can be predicted preoperatively using a non-contrast imaging modality, via the novel HUDmax parameter. Full article

The important role of neutral wind, its vertical shear, and external electric fields in the formation and localization of sporadic E (Es) are demonstrated analytically and numerically in equatorial and mid-latitude regions. The ion/electron density behavior, obtained analytically, indicates that their initial layer moves vertically at ion drift velocity. When the maximal total ion vertical convergence rate (MTotIVCR) (the minimal negative value of the ion drift velocity divergence), determined according to the wind velocity, wind shear, and electric field, exceeds ion/electron loss due to recombination and diffusive displacement, the initial layer peak density increases, and ion accumulation into narrow, high-density Es-type layers becomes possible. In this case, the Es layers formed localize either in the region surrounding ion drift velocity nodes or where they are frequently observed (around 100–105 km), where drift velocity disappears. Analysis and numerical simulations also show that an increase in the downward drift velocity and the total ion vertical convergence rate (TotIVCR), including the effects of westward or/and downward electric fields and westward or/and northward neutral wind, can also result in additional increases in the Es layer density as it descends to its localization region. The important contributions of the directions and magnitudes of meridional and zonal winds (using HWM14 data), wind shear, and electric field (using four different polarizations) to the vertical drift velocity of ions and, accordingly, the MTotIVCR (about 10⁻³–10⁻⁴ s⁻¹), are evident during the formation of Es layers in typical equatorial regions (with magnetic inclination I = 0 and 0.5° N; 195° E) and between equatorial and mid-latitude (BEML) (I = 30°; 16° N; 195° E) and mid-latitudes (I = 60°; 45° N, 195° E) regions. For the zonal wind data and zonal and vertical components of the electric field considered, the importance of the electric field in the increase in the TotIVCR and the corresponding formation and localization of Es layers in the equatorial region is shown. If an electric field is present at mid-latitudes, it also can affect the increase or decrease in the TotIVCR and the localization of Es layers. It also has the ability to destroy these layers, which are formed under the combined effect of meridional and zonal wind velocities and vertical shear. In this case, the electric field also affects increases in the meridional wind factor with latitude in the formation and localization of high-density Es layers. This study shows that in addition to considering the vertical shear of neutral wind, it is necessary to take into account its magnitude and direction and the presence of electric fields to predict the possibility of sporadic E (Es) formation and localization. Full article

Fusarium circinatum poses severe threats to agroforestry ecosystem as a globally significant pathogenic fungus. This study utilized multi-source species distribution data and environmental variables (climatic, topographic, and soil factors) to predict the global potential habitat suitability of F. circinatum and its response to future climate change using an optimized MaxEnt model (RM = 1, FC = LQ). The results indicate that the current total suitable area spans approximately 69.29 million km², with highly suitable habitats (>0.493) accounting for 15.07%, primarily concentrated in East Asia, southwestern North America, western South America, the Mediterranean coast, and eastern Australia. The distribution of F. circinatum’s suitable habitats is primarily constrained by the following environmental factors, ranked by contribution rate: coldest quarter precipitation (29.4%), coldest quarter mean temperature (18.2%), annual mean temperature (17.2%), and annual precipitation (12%). Under future climate scenarios, the suitable habitats exhibited an overall contraction and poleward shift, with the most significant decline in highly suitable areas observed under SSP370-2050s (−52.1%). The centroid of suitable habitats continuously migrated northwestward from Gombe State, Nigeria, with the maximum displacement reaching 1077.6 km by SSP585-2090s. This study reveals a latitude gradient redistribution pattern of F. circinatum driven by climate warming, providing a scientific basis for transboundary biosecurity and early warning systems. Full article

For the precise description of gas physical processes in high-voltage direct current (HVDC) transmission, an advanced and robust numerical framework for the simulation of transient particle densities in the course of corona discharges is developed in this work. The aim is the scalable and consistent modeling of the space charge density under realistic conditions. The core component of the framework is a discontinuous Galerkin method that ensures the conservative properties of the underlying hyperbolic problem. The space charge density at the electrode surface is imposed as a dynamic boundary condition via Lagrange multipliers. To increase the numerical stability and convergence rate, a homotopy approach is also integrated. For the experimental validation, a measurement concept was realised that uses a subtraction method to specifically remove the displacement current component in the signal and thus enables an isolated recording of the transient ion current with superimposed voltage stresses. The experimental results on a small scale agree with the numerical predictions and prove the quality of the model. On this basis, the framework is transferred to hybrid HVDC overhead line systems with a bipolar design. In the event of a fault, significant transient space charge densities can be seen there, especially when superimposed with new types of voltage waveforms. The framework thus provides a reliable contribution to insulation coordination in complex HVDC systems and enables the realistic analysis of electrohydrodynamic coupling effects on an industrial scale. Full article

The displacement of bridge towers is relatively large under strong wind action. Changes in tower displacement can reflect the usage status of the bridge towers. Therefore, it is necessary to conduct performance warning research on tower displacement under strong wind action. In this paper, the triple standard deviation method, multiple linear regression method, and interpolation method are used to preprocess monitoring data with skipped points and missing anomalies. An improved multi-rate data fusion method, validated using simulated datasets, was applied to correct monitoring data at bridge tower tops. The fused data were used to feed predictive models and generate structural performance alerts. Spectral analysis confirmed that the fused displacement measurements achieve high precision by effectively merging the low-frequency GPS signal with the high-frequency accelerometer signal. Structural integrity monitoring of wind-loaded bridge towers used modeling residuals as alert triggers. The efficacy of this proactive monitoring strategy has been quantitatively validated through statistical evaluation of alarm accuracy rates. Full article

Accurate and rapid prediction of structural responses to seismic loading is critical for ensuring structural safety. Recently, there has been active research focusing on the application of deep learning techniques, including Physics-Informed Neural Networks (PINNs) and Long Short-Term Memory (LSTM) networks, to predict the dynamic behavior of structures. While these methods have shown promise, each comes with distinct limitations. PINNs offer physical consistency but struggle with capturing long-term temporal dependencies in nonlinear systems, while LSTMs excel in learning sequential data but lack physical interpretability. To address these complementary limitations, this study proposes a hybrid LSTM-PINN model, combining the temporal learning ability of LSTMs with the physics-based constraints of PINNs. This hybrid approach allows the model to capture both nonlinear, time-dependent behaviors and maintain physical consistency. The proposed model is evaluated on both single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) structural systems subjected to the El-Centro ground motion. For validation, the 1940 El-Centro NS earthquake record was used, and the ground acceleration data were normalized and discretized for numerical simulation. The proposed LSTM-PINN is trained under the same conditions as the conventional PINN models (e.g., same optimizer, learning rate, and loss structure), but with fewer training epochs, to evaluate learning efficiency. Prediction accuracy is quantitatively assessed using mean error and mean squared error (MSE) for displacement, velocity, and acceleration, and results are compared with PINN-only models (PINN-1, PINN-2). The results show that LSTM-PINN consistently achieves the most stable and precise predictions across the entire time domain. Notably, it outperforms the baseline PINNs even with fewer training epochs. Specifically, it achieved up to 50% lower MSE with only 10,000 epochs, compared to the PINN’s 50,000 epochs, demonstrating improved generalization through temporal sequence learning. This study empirically validates the potential of physics-guided time-series AI models for dynamic structural response prediction. The proposed approach is expected to contribute to future applications such as real-time response estimation, structural health monitoring, and seismic performance evaluation. Full article

Field foundation pile loading tests were conducted in the context of an actual bridge pile foundation project. The test data were analyzed to determine the reasons for the variation in the complex geological conditions of the seashore. Moreover, finite element analysis was conducted to evaluate the influence of pile length and diameter on the settlement of coastal friction foundation piles. Increasing the pile length from 65 m to 75 m reduced the settlement by 25.7%, while increasing the diameter from 1.5 m to 2.0 m led to a 35.9% reduction. Increasing the pile spacing reduced the amount of structural settlement. Group pile foundation pile spacings should be 2.5–3.0 D. Pile group superposition reduced the most obvious effects and the settlement reduction rate was the fastest. Under seismic conditions, the pile group foundation exhibited 5.60 times greater horizontal displacement, 3.57 times higher bending moment, and 5.30 times increased shear force relative to static loading. The formula for predicting the settlement of oversized friction pile group foundations was modified based on settlement values calculated using finite elements. The revised formula is suitable for calculating the settlement of friction pile group foundations in coastal areas. Full article

Trajectory prediction under multimodal information is critical for autonomous driving, necessitating the integration of dynamic vehicle states and static high-definition (HD) maps to model complex agent–scene interactions effectively. However, existing methods often employ static scene encodings and unstructured latent spaces, limiting their ability to capture evolving spatial contexts and produce diverse yet contextually coherent predictions. To tackle these challenges, we propose MS-SLV, a novel generative framework that introduces (1) a time-aware scene encoder that aligns HD map features with vehicle motion to capture evolving scene semantics and (2) a structured latent model that explicitly disentangles agent-specific intent and scene-level constraints. Additionally, we introduce an auxiliary lane prediction task to provide targeted supervision for scene understanding and improve latent variable learning. Our approach jointly predicts future trajectories and lane sequences, enabling more interpretable and scene-consistent forecasts. Extensive evaluations on the nuScenes dataset demonstrate the effectiveness of MS-SLV, achieving a 12.37% reduction in average displacement error and a 7.67% reduction in final displacement error over state-of-the-art methods. Moreover, MS-SLV significantly improves multi-modal prediction, reducing the top-5 Miss Rate (${\mathrm{MR}}_5$) and top-10 Miss Rate (${\mathrm{MR}}_{10}$) by 26% and 33%, respectively, and lowering the Off-Road Rate (ORR) by 3%, as compared with the strongest baseline in our evaluation. Full article

Natural gas storage is an effective solution to address the energy supply–demand imbalance, and underground gas storage (UGS) is a primary method for storing natural gas. The overarching goal of this study is to monitor and analyze surface deformation at the Hutubi underground gas storage facility in Xinjiang, China, which is the largest gas storage facility in the country. This research aims to ensure the stable and efficient operation of the facility through long-term monitoring, using remote sensing data and advanced modeling techniques. The study employs the SBAS-InSAR method, leveraging Synthetic Aperture Radar (SAR) data from the TerraSAR and Sentinel-1 sensors to observe displacement time series from 2013 to 2024. The data is processed through wavelet transformation for denoising, followed by the application of a Gray Wolf Optimization (GWO) algorithm combined with Variational Mode Decomposition (VMD) to decompose both surface deformation and gas pressure data. The key focus is the development of a high-precision predictive model using a Gated Recurrent Unit (GRU) network, referred to as GWO-VMD-GRU, to accurately predict surface deformation. The results show periodic surface uplift and subsidence at the facility, with a notable net uplift. During the period from August 2013 to March 2015, the maximum uplift rate was 6 mm/year, while from January 2015 to December 2024, it increased to 12 mm/year. The surface deformation correlates with gas injection and extraction periods, indicating periodic variations. The accuracy of the InSAR-derived displacement data is validated through high-precision GNSS data. The GWO-VMD-GRU model demonstrates strong predictive performance with a coefficient of determination (R²) greater than 0.98 for the gas well test points. This study provides a valuable reference for the future safe operation and management of underground gas storage facilities, demonstrating significant contributions to both scientific understanding and practical applications in underground gas storage management. Full article

This study presents a high-order shear deformation theory (HSDT)-based model for evaluating the energy harvesting performance of functionally graded material (FGM) beams integrated with a piezoelectric layer and subjected to a moving concentrated load at constant velocity. The governing equations are derived using Hamilton’s principle, and the dynamic response is obtained through the State Function Method with trigonometric mode shapes. The output voltage and harvested power are calculated based on piezoelectric constitutive relations. A comparative analysis with homogeneous isotropic beams demonstrates that HSDT yields more accurate predictions than the Classical Beam Theory (CBT), especially for thick beams; for instance, at a span-to-thickness ratio of h/L = 12.5, HSDT predicts increases of approximately 6%, 7%, and 12% in displacement, voltage, and harvested power, respectively, compared to CBT. Parametric studies further reveal that increasing the load velocity significantly enhances the strain rate in the piezoelectric layer, resulting in higher voltage and power output, with the latter exhibiting quadratic growth. Moreover, increasing the material gradation index n reduces the beam’s effective stiffness, which amplifies vibration amplitudes and improves energy conversion efficiency. These findings underscore the importance of incorporating shear deformation and material gradation effects in the design and optimization of piezoelectric energy harvesting systems using FGM beams subjected to dynamic loading. Full article

To investigate the interaction mechanism between agricultural tillage machinery and soil, this study established a precise simulation model by integrating physical and numerical experiments using typical yellow cinnamon soil collected from western Henan Province, China. The discrete element parameters for soils with varying moisture contents were calibrated based on the Hertz–Mindlin (no slip) contact model. Through Plackett–Burman screening, steepest ascent optimization, and Box–Behnken response surface methodology, a predictive model correlating moisture content, parameters, and repose angle was developed, yielding the optimal contact parameter combination: interparticle static friction coefficient (0.6), soil–65Mn static friction coefficient (0.69), and interparticle rolling friction coefficient (0.358). For the Bonding model, orthogonal experiments coupled with NSGA-II multi-objective optimization determined the optimal cohesive parameters targeting maximum load (673.845 N) and displacement (9.765 mm): normal stiffness per unit area (8.8 × 10⁷ N/m³), tangential stiffness per unit area (6.85 × 10⁷ N/m³), critical normal stress (6 × 10⁴ Pa), critical tangential stress (3.15 × 10⁴ Pa), and bonding radius (5.2 mm). Field validation using rotary tillers and power harrows demonstrated less than 6% deviation in soil fragmentation rates between simulations and actual operations, confirming parameter reliability and providing theoretical foundations for constructing soil-tillage machinery interaction models. Full article

Understanding nonlinear fluid flow in fractured rocks is critical for various geoengineering and geosciences. This study investigates the evolution of seepage behavior under varying fracture surface roughness, confining pressures, and shear displacements. A total of four sandstone fracture specimens were prepared using controlled splitting techniques, with surface morphology quantified by Joint Roughness Coefficient (JRC) values ranging from 2.8 to 17.7. Triaxial seepage tests were conducted under four confining pressures (3–9 MPa) and four shear displacements (0–1.5 mm). Experimental results reveal that permeability remains stable under low hydraulic gradients but transitions to nonlinear regimes as the flow rate increases, accompanied by significant energy loss and deviation from the cubic law. The onset of nonlinearity occurs earlier with higher roughness, stress, and displacement. A critical hydraulic gradient Jc was introduced to define the threshold at which inertial effects dominate. Forchheimer’s equation was employed to model nonlinear flow, and empirical regression models were developed to predict coefficients A, B, and Jc using hydraulic aperture and JRC as input variables. These models demonstrated high accuracy (R² > 0.92). This work provides theoretical insights and predictive approaches for assessing nonlinear fluid transport in rock fracture. Future research will address mechanical–hydraulic coupling and incorporate additional factors such as scale effects and flow anisotropy. Full article

Water injection is the most widely used secondary recovery method, but its low viscosity limits sweep efficiency in heterogeneous carbonate reservoirs, especially when displacing heavy crude oils. Polymer flooding overcomes this by increasing the viscosity of the injected fluid and improving the mobility ratio. In this work, we compare three biopolymers (i.e., Xanthan Gum, Scleroglucan, and Guar Gum) using a core flood test on Indiana Limestone with 16–19% porosity and 180–220 mD permeability at 60 °C and 30,905 mg/L of salinity. We injected solutions at 100–1500 ppm and 0.5–6 cm³/min to measure the Resistance Factor (RF), Residual Resistance Factor (RRF), in situ viscosity, and relative injectivity. All polymers behaved as pseudoplastic fluids with no shear thickening. The RF rose from ~1.1 in the dilute regime to 5–16 in the semi-dilute regime, and the RRF spanned 1.2–5.8, indicating moderate, reversible permeability impairment. In-site viscosity reached up to eight times that of brine, while relative injectivity remained 0.5. Xanthan Gum delivered the highest viscosity boost and strongest shear thinning, Scleroglucan offered a balance of stable viscosity and a moderate RF, and Guar Gum gave predictable but lower viscosity enhancement. These results establish practical guidelines for selecting polymer types, concentration, and flow rate in reservoir-condition polymer flood designs. Full article

Displaced abomasum (DA) is a digestive disorder that causes severe economic losses through the reduction in milk yield and early culling of cows. The predictive potential of DA-susceptible cases is of great importance to reduce economic losses. This study aimed for early prediction of DA. However, identifying cows at risk of DA can be difficult because DA is a complex trait and its incidence is low. For this purpose, in this study, the ability of five machine learning algorithms, namely Logistic Regression (LR), Naïve Bayes (NB), Decision Tree, Random Forest (RF) and Gradient Boosting Machines (GBM), to predict cases of DA was investigated. For these predictions, 20 herd–cow-specific features and sire genetic information from 7 Holstein dairy herds that calved between 2010 and 2020 were available. Model performance metrics indicated that GBM and RF algorithms outperformed the others in predicting DA with F2 measures of 0.32. The true positive rate in the RF was the highest compared to other methods at 0.75, followed by GBM at 0.70. Given the highly imbalanced data, this study showed the potential in forecasting cases susceptible to DA. This prediction tool can aid dairy farmers in making preventative management decisions by identifying cows susceptible to DA. Full article

In the field of crack mechanics, predicting the direction of a crack is important because this will evaluate whether, when the crack propagates, it penetrates into important areas and whether the structure is dangerous or not. This paper will refer to three theories that predict the propagation direction of cracks: a theory of maximum tangential normal stress, a theory of maximum energy release, and a theory of minimum strain energy density. At the same time, the finite element method (FEM)–ANSYS program will be used to calculate stress intensity factors (SIFs), strain energy release rate (J-integral), stress field, displacement near a crack tip, and crack propagation phenomenon based on the above theories. The calculated results were compared with the results in other scientific papers and experimental results. This research used ANSYS program, an experimental method combined with FEM based on the above energy theories to simulate the J-integral, the SIFs, and the crack propagation. The errors of the SIFs of the FGM rectangular plate has a through-thickness center crack of 1.77%, J-integral of 4.49%, and crack propagation angle ${\theta }_c$ of 0.15%. The FEM gave good errors compared to experimental and exact methods. Full article