Search Results (7,601)

Background/Objectives: All-inside ACL reconstruction has emerged as a minimally invasive alternative to conventional techniques, with potential advantages in graft configuration and reduced surgical trauma. This study aimed to compare the clinical outcomes of all-inside and full tibial tunnel ACL reconstruction, focusing on graft diameter, postoperative stability, and functional recovery. We hypothesized that the all-inside technique would allow for thicker grafts and yield superior postoperative knee stability and functional outcomes, with postoperative anterior laxity as a major outcome of interest. Methods: This retrospective comparative study reviewed patients who underwent ACL reconstruction between January 2020 and February 2024. From January 2020 to September 2022, a four-strand hamstring autograft with full tibial tunnel technique (FT-4) was used, while from September 2022, a six-strand hamstring autograft with the all-inside technique (AI-6) was adopted to enable thicker grafts and optimize fixation. Among a total of 103 patients, 1:1 propensity score matching (PSM) was performed based on age, sex, BMI, laterality, ALL reconstruction, meniscal lesion, and preoperative anterior laxity (SSD). Graft diameter and clinical outcomes, including knee stability and functional scores, were compared between the matched groups. Results: After PSM, two comparable groups of 29 patients each were established. Graft diameter was significantly larger in the AI-6 group (9.5 ± 0.7 mm) compared to the FT-4 group (7.8 ± 0.8 mm, p < 0.001), while other baseline characteristics remained well balanced between the groups. At the final follow-up, both groups exhibited significant improvements in anterior laxity, functional scores, and pivot shift grades (all p < 0.001). The AI-6 group demonstrated superior outcomes with a significantly higher Lysholm score (82.2 ± 6.7 vs. 75.6 ± 8.9, p = 0.002), lower WOMAC score (8.0 ± 4.3 vs. 12.9 ± 10.5, p = 0.023), and reduced anterior laxity (1.6 ± 1.1 mm vs. 2.5 ± 1.4 mm, p = 0.005) compared to the FT-4 group, whereas no significant differences were observed in the IKDC, Tegner, Korean knee score, or pivot shift test results. A simple linear regression revealed a significant negative correlation between graft diameter and postoperative anterior laxity (B = −0.398, p = 0.048). Conclusions: The present study demonstrated that the use of a six-strand hamstring graft configuration in the AI-6 technique resulted in significantly thicker grafts and was associated with reduced postoperative anterior knee laxity compared to the FT-4 technique. While interpretation of these findings requires caution in light of MCID thresholds, the AI-6 group showed favorable outcomes in anterior laxity and selected functional scores, such as the Lysholm and WOMAC. This technique may offer practical clinical value, particularly in populations prone to smaller graft diameters, as it facilitates adequate graft thickness through multifold preparation, with the all-inside approach accommodating the inherent graft shortening. Full article

With the increasing demand for urban rail transit capacity, shield tunneling has become the predominant method for constructing underground metro systems in densely populated cities. However, the spatial interaction between shield tunnels and adjacent retaining structures poses significant engineering challenges, potentially leading to excessive ground settlement, structural deformation, and even stability failure. This study systematically investigates the deformation behavior and associated risks of retaining systems during adjacent shield tunnel construction. An orthogonal multi-factor analysis was conducted to evaluate the effects of grouting pressure, grout stiffness, and overlying soil properties on maximum surface settlement. Results show that soil cohesion and grouting pressure are the most influential parameters, jointly accounting for over 72% of the variance in settlement response. Based on the numerical findings, a Bayesian network model was developed to assess construction risk, integrating expert judgment and field monitoring data to quantify the conditional probability of deformation-induced failure. The model identifies key risk sources such as geological variability, groundwater instability, shield steering correction, segmental lining quality, and site construction management. Furthermore, the effectiveness and cost-efficiency of various grouting reinforcement strategies were evaluated. The results show that top grouting increases the reinforcement efficiency to 34.7%, offering the best performance in terms of both settlement control and economic benefit. Sidewall grouting yields an efficiency of approximately 30.2%, while invert grouting shows limited effectiveness, with an efficiency of only 11.6%, making it the least favorable option in terms of both technical and economic considerations. This research provides both practical guidance and theoretical insight for risk-informed shield tunneling design and management in complex urban environments. Full article

The Lorentz-breaking theory not only modifies the geometric structure of curved spacetime but also significantly alters the quantum dynamics of bosonic and fermionic fields in black hole spacetime, leading to observable physical effects on Hawking temperature and Bekenstein–Hawking entropy. This study establishes the first systematic theoretical framework for entropy modifications of charged accelerating Anti-de Sitter black holes, incorporating gauge-invariant corrections derived from Lorentz-violating quantum field equations in curved spacetime. The obtained analytical expression coherently integrates semi-classical approximations with higher-order quantum perturbative contributions. Furthermore, the methodologies employed and the resultant conclusions are subjected to rigorous analysis, establishing their physical significance for advancing fundamental investigations into black hole entropy. Full article

The precise mapping of rock joint traces is fundamental to the design and safety assessment of foundations, retaining structures, and underground cavities in building and civil engineering. Existing deep learning approaches either impose prohibitive computational demands for on-site deployment or disrupt the topological continuity of subpixel lineaments that govern rock mass behavior. This study presents BATNet-Lite, a lightweight encoder–decoder architecture optimized for joint segmentation on resource-constrained devices. The encoder introduces a Boundary-Aware Token-Mixing (BATM) block that separates feature maps into patch tokens and directionally pooled stripe tokens, and a bidirectional attention mechanism subsequently transfers global context to local descriptors while refining stripe features, thereby capturing long-range connectivity with negligible overhead. A complementary Multi-Scale Line Enhancement (MLE) module combines depth-wise dilated and deformable convolutions to yield scale-invariant responses to joints of varying apertures. In the decoder, a Skeletal-Contrastive Decoder (SCD) employs dual heads to predict segmentation and skeleton maps simultaneously, while an InfoNCE-based contrastive loss enforces their topological consistency without requiring explicit skeleton labels. Training leverages a composite focal Tversky and edge IoU loss under a curriculum-thinning schedule, improving edge adherence and continuity. Ablation experiments confirm that BATM, MLE, and SCD each contribute substantial gains in boundary accuracy and connectivity preservation. By delivering topology-preserving joint maps with small parameters, BATNet-Lite facilitates rapid geological data acquisition for tunnel face mapping, slope inspection, and subsurface digital twin development, thereby supporting safer and more efficient building and underground engineering practice. Full article

To ensure the safe and reliable operation of hydrogen-blended natural gas (HBNG) pipelines in urban utility tunnels, this study conducted a comprehensive CFD simulation of the leakage and diffusion characteristics of HBNG in confined underground environments. Utilizing ANSYS CFD software (2024R1), a three-dimensional physical model of a utility tunnel was developed to investigate the influence of key parameters, such as leak sizes (4 mm, 6 mm, and 8 mm)—selected based on common small-orifice defects in utility tunnel pipelines (e.g., corrosion-induced pinholes and minor mechanical damage) and hydrogen blending ratios (HBR) ranging from 0% to 20%—a range aligned with current global HBNG demonstration projects (e.g., China’s “Medium-Term and Long-Term Plan for Hydrogen Energy Industry Development”) and ISO standards prioritizing 20% as a technically feasible upper limit for existing infrastructure, on HBNG diffusion behavior. The study also evaluated the adequacy of current accident ventilation standards. The findings show that as leak orifice size increases, the diffusion range of HBNG expands significantly, with a 31.5% increase in diffusion distance and an 18.5% reduction in alarm time as the orifice diameter grows from 4 mm to 8 mm. Furthermore, hydrogen blending accelerates gas diffusion, with each 5% increase in HBR shortening the alarm time by approximately 1.6 s and increasing equilibrium concentrations by 0.4% vol. The current ventilation standard (12 h⁻¹) was found to be insufficient to suppress concentrations below the 1% safety threshold when the HBR exceeds 5% or the orifice diameter exceeds 4 mm—thresholds derived from simulations showing that, under 12 h⁻¹ ventilation, equilibrium concentrations exceed the 1% safety threshold under these conditions. To address these gaps, this study proposes an adaptive ventilation strategy that uses variable-frequency drives to adjust ventilation rates in real time based on sensor feedback of gas concentrations, ensuring alignment with leakage conditions, thereby ensuring enhanced safety. These results provide crucial theoretical insights for the safe design of HBNG pipelines and ventilation optimization in utility tunnels. Full article

In recent years, the increasing complexity of shield tunneling environments has made it critical to control the deformation of adjacent excavation structures and surrounding soils. This study employs numerical simulation using MIDAS GTS/NX to comprehensively analyze the spatial interaction factors between shield tunnels and wall-pile-anchor-supported foundation pits. Structural parameters of the retaining system and tunneling conditions are also evaluated to identify the key factors influencing construction-induced deformation. The results show that the maximum settlement of the adjacent retaining wall occurs when the tunnel burial depth reaches 1.4L, where L is the height of the diaphragm wall. In addition, when the horizontal distance between the tunnel and the excavation is less than 0.75D (D being the tunnel diameter), significant settlement deformation is observed in the nearby support structures. A linear correlation is also identified between the variation in tunnel crown settlement and the excavation depth of the overlying pit during tunnel undercrossing. Furthermore, sensitivity analysis indicates that increasing the embedment depth of the diaphragm wall effectively reduces horizontal displacement at the wall base. Increasing the wall thickness decreases displacement in the upper section of the wall. Similarly, increasing pile diameter and anchor length and diameter, while reducing the inclination angle of anchors, are all effective in minimizing the lateral displacement of the support structure. Full article

Crop leaves naturally exhibit a curved morphology and primarily display bending deformation and vibrational responses under wind load. The curved surface structure of leaves plays a critical role in the deposition and retention of pesticide droplets. In this study, wind tunnel experiments combined with high-speed photography and digital image analysis were conducted to systematically investigate the curvature and flexibility distributions of three typical crop leaves: walnut, peach, and pepper, across a range of wind speeds. The results indicate that with increasing wind speed, all three types of leaves gradually transition from smooth, uniform bending to a multi-peak pattern of pronounced local curvature, with increasingly prominent nonlinear deformation characteristics. Moreover, once the wind speed exceeds the critical threshold of 6 m/s, the primary deformation region generally shifts from the leaf base to the tip. For example, the maximum curvature of walnut leaves increased from 0.018 mm⁻¹ to 0.047 mm⁻¹, and that of pepper leaves from 0.031 mm⁻¹ to 0.101 mm⁻¹, both more than double their original values. In addition, all three types of leaves demonstrated a distinct structural gradient characterized by strong basal rigidity and high apical flexibility. The tip flexibility values exceeded 1.5 × 10⁻⁵, 4 × 10⁻⁴, and 5.6 × 10⁻⁴ mm⁻²·mN⁻¹ for walnut, peach, and pepper leaves, respectively. These findings elucidate the mechanical response mechanisms of non-uniform flexible crop leaves under wind-induced bending and provide a theoretical basis and data support for the optimization of air-assisted spraying parameters. Full article

In-flight icing presents a critical safety hazard for unmanned aerial vehicles (UAVs), resulting in ice accumulation on propeller surfaces that compromise UAV aerodynamic performance and operational integrity. While hybrid anti-/de-icing systems (i.e., combining active heating with passive superhydrophobic coatings) have been developed recently to efficiently address this challenge, conventional active heating sub-systems utilized in the hybrid anti-/de-icing systems face significant limitations when applied to curved geometries of UAV propeller blades. This necessitates the development of innovative self-heating superhydrophobic coatings that can conform perfectly to complex surface topographies. Carbon-based electrothermal coatings, particularly those incorporating graphite and carbon nanotubes, represent a promising approach for ice mitigation applications. This study presents a comprehensive experimental investigation into the development and optimization of a novel self-heating carbon nanotube (CNT)-based superhydrophobic coating specifically designed for UAV icing mitigation. The coating’s anti-/de-icing efficacy was evaluated through a comprehensive experimental campaign conducted on a rotating UAV propeller under typical glaze icing conditions within an advanced icing research tunnel facility. The durability of the coating was also examined in a rain erosion test rig under the continuous high-speed impingement of water droplets. Experimental results demonstrate the successful application of the proposed sprayable self-heating superhydrophobic coating in UAV icing mitigation, providing valuable insights into the viability of CNT-based electrothermal coatings for practical UAV icing protection. This work contributes to the advancement of icing protection technologies for un-manned aerial systems operating in adverse weather conditions. Full article

Background/Objectives: Radial artery access (RAA) is widely used for catheter-based procedures due to its safety and convenience, but complex regional pain syndrome (CRPS) remains a rare, underrecognized complication—particularly in women. CRPS manifests as prolonged, severe pain and autonomic symptoms, often associated with nerve irritation near the carpal tunnel. This study aimed to evaluate whether modifying the puncture site to a high radial artery puncture (HRAP) reduces the risk of CRPS in patients undergoing transarterial micro-embolization (TAME) for frozen shoulder. Methods: We retrospectively reviewed 97 patients (47 women and 50 men) who underwent transarterial micro-embolization (TAME) via conventional RAA for frozen shoulder between February and June 2019. The occurrence of CRPS and vascular complications was recorded. All punctures were ultrasound-guided. Results: Among women treated via conventional RAA, five developed CRPS and one had radial artery occlusion. CRPS symptoms included intense puncture site pain (mean duration was 47 days), which severely impaired daily function. No complications occurred in men. Following the adoption of HRAP, no cases of CRPS, prolonged pain, or vascular complications were observed in the consecutive 101 women treated. Conclusions: Our findings suggest HRAP reduces CRPS risk by avoiding superficial nerve branches and targeting deeper arterial segments with fewer sensory structures. This ultrasound-guided modification is simple, does not require additional training, and may be widely applicable in both musculoskeletal and cardiovascular interventions. HRAP may help minimize neuropathic complications in broader patient populations. Full article

This study presents a semi-empirical approach to generalizing the acoustic radiation generated by serrated airfoil configurations, based on small-scale aerodynamic/acoustic experiments and functional regression techniques. In the context of passive noise reduction strategies, such as leading-edge and trailing-edge serrations, acoustic measurements are performed in a controlled subsonic wind tunnel environment. Sound pressure level (SPL) spectra and acoustic power metrics are acquired for various geometric configurations and flow conditions. These spectral data are then analyzed using regression-based modeling techniques—linear, quadratic, logarithmic, and exponential forms—to capture the dependence of acoustic emission on key geometric and flow-related variables (e.g., serration amplitude, wavelength, angle of attack), without relying explicitly on predefined nondimensional numbers. The resulting predictive models aim to describe SPL behavior across relevant frequency bands (e.g., broadband or 1/3 octave) and to extrapolate acoustic trends for configurations beyond those tested. The proposed methodology allows for the identification of compact functional relationships between configuration parameters and acoustic output, offering a practical tool for the preliminary design and optimization of low-noise serrated profiles. The findings are intended to support both physical understanding and engineering application, bridging experimental data and parametric acoustic modeling in aerodynamic noise control. Full article

Tunnel systems are often confronted with issues such as cracks, water seepage, and exposed tendons, all of which compromise their structural integrity. This study utilizes an advanced robotic system equipped with a 3D laser scanner to capture data on visible lining defects. By analyzing the distribution of defects across various tunnel segments, we explore the mechanisms underlying structural cracks. Finite element software is employed to assess stress, deformation, and crack progression within the tunnel linings. The result found that the diversion tunnel’s segments exhibit notable variations: 66.0% of the defects are concentrated in the upper flat section, while 34.0% are found in the inclined shaft segment. Cracks, primarily located in the vault area, characterize these defects. Under water pressure, stress deformation in the intact lining follows a linear escalation pattern. Specifically, after the formation of cracks measuring 0.1 m, 0.2 m, and 0.3 m, circumferential stresses increase by approximately 4.50%, 9.10%, and 15.10%, respectively. Numerical simulations reveal significant stress concentration near the cave entrance at the upper flat break. Crack propagation at the arch crown is found to pose a greater risk than at the sides of the arch waist. These findings offer valuable scientific insights and practical implications for improving safety and enabling intelligent monitoring of power station tunnels. Full article

Accurate and efficient rock mass characterization is essential in geotechnical engineering, yet traditional tunnel face mapping remains time consuming, subjective, and potentially hazardous. Recent advances in digital technologies and AI offer automation opportunities, but many existing solutions are hindered by slow 3D scanning, computationally intensive processing, and limited integration flexibility. This paper presents Tunnel Rapid AI Classification (TRaiC), an open-source MATLAB-based platform for rapid and automated tunnel face mapping. TRaiC integrates single-shot 360° panoramic photography, AI-powered discontinuity detection, 3D textured digital twin generation, rock mass discontinuity characterization, and Retrieval-Augmented Generation with Large Language Models (RAG-LLM) for automated geological interpretation and standardized reporting. The modular eight-stage workflow includes simplified 3D modeling, trace segmentation, 3D joint network analysis, and rock mass classification using RMR, with outputs optimized for Geo-BIM integration. Initial evaluations indicate substantial reductions in processing time and expert assessment workload. Producing a lightweight yet high-fidelity digital twin, TRaiC enables computational efficiency, transparency, and reproducibility, serving as a foundation for future AI-assisted geotechnical engineering research. Its graphical user interface and well-structured open-source code make it accessible to users ranging from beginners to advanced researchers. Full article

This study investigates the perception of postural discomfort experienced by passengers seated in the middle rear seat of a vehicle—an area often overlooked in ergonomic research. A total of 20 participants (12 males and 8 females) were involved in a pilot test using two car models: a City Car (Fiat Panda) and a C-SUV (Renault Arkana). Each participant completed a short on-road ride (~24 min, 11.7 km) in both vehicles. Discomfort was assessed using a 5-point Likert scale, considering both overall and localized body discomfort, as well as other elements/factors, such as those involved in the human–car interaction (e.g., the central tunnel, the headrest, AC vents, and other passengers). The results showed that overall discomfort was significantly higher in the City Car (mean: 3.75 ± 0.72) compared to the SUV (mean: 3.00 ± 1.16). The most affected body regions in the City Car were the arms (mean: 3.95), knees (3.90), and legs/feet (3.55). In the SUV, discomfort was lower across all regions, with the arms (3.15) and knees (3.05) still being notably impacted. Strong correlations were observed between discomfort and several vehicle features: backrest width, headrests, interference with adjacent passengers, and rear air conditioning vents. This study highlights specific ergonomic issues in the middle rear seat and suggests design improvements, including wider backrests and headrests, repositioned air vents, and the inclusion of lateral supports. These findings offer actionable insights for automotive manufacturers to enhance passenger comfort in multi-passenger configurations. Full article

Monocular depth estimation (MDE) is a cornerstone of computer vision and is applied to diverse practical areas such as autonomous vehicles, robotics, etc., yet even the latest methods suffer substantial errors in high-dynamic-range (HDR) scenes where over- or under-exposure erases critical texture. To address this challenge in real-world autonomous driving scenarios, we propose the Exposure-Aware Single-Step Diffusion Framework for Monocular Depth Estimation (EASD). EASD leverages a pre-trained Stable Diffusion variational auto-encoder, freezing its encoder to extract exposure-robust latent RGB and depth representations. A single-step diffusion process then predicts the clean depth latent vector, eliminating iterative error accumulation and enabling real-time inference suitable for autonomous vehicle perception pipelines. To further enhance robustness under extreme lighting conditions, EASD introduces an Exposure-Aware Feature Fusion (EAF) module—an attention-based pyramid that dynamically modulates multi-scale features according to global brightness statistics. This mechanism suppresses bias in saturated regions while restoring detail in under-exposed areas. Furthermore, an Exposure-Balanced Loss (EBL) jointly optimises global depth accuracy, local gradient coherence and reliability in exposure-extreme regions—key metrics for safety-critical perception tasks such as obstacle detection and path planning. Experimental results on NYU-v2, KITTI, and related benchmarks demonstrate that EASD reduces absolute relative error by an average of 20% under extreme illumination, using only 60,000 labelled images. The framework achieves real-time performance (<50 ms per frame) and strikes a superior balance between accuracy, computational efficiency, and data efficiency, offering a promising solution for robust monocular depth estimation in challenging automotive lighting conditions such as tunnel transitions, night driving and sun glare. Full article

In this study, data assimilation using PIV measurement data of the cylinder wake obtained from wind tunnel tests was applied to tune the simulation model parameters of Detached Eddy Simulation (DES) to improve the accuracy of large-scale separated flow simulations around a cylinder. The use of DES enables more accurate simulation of large-scale separation flows than RANS. However, it increases computational costs and makes parameter tuning using data assimilation difficult. To reduce the computational time required for data assimilation, the conventional data assimilation method was modified. The background values used for data assimilation were constructed by extracting only velocity data from locations corresponding to observation points. This approach reduced the computational time for background error covariance and Kalman gain, thereby significantly reducing the execution time of the filtering step in data assimilation. As a result of tuning, $C_{des}$ significantly increased, while $C_{b1}$ decreased. This adjustment extended the length of the recirculation bubble, bringing the time-averaged velocity distribution closer to the PIV measurement data. However, the peak frequency in the PSD obtained from the FFT analysis of velocity fluctuations in the wake shifted slightly toward lower frequencies, slightly increasing the discrepancy with the measurement data. Verifying the relationship between parameter values and flow, it was found that parameter tuning stabilized the separation shear layer generated at the leading edge of the cylinder and enlarged the size of the recirculation bubbles. On the other hand, frequency variations did not show consistent changes in response to parameter value changes, indicating that the effect of parameter tuning was limited under the simulation conditions of this study. To bring the frequency fluctuations closer to experimental results, it is suggested that other methods, such as higher-order spatial and temporal accuracy, should be combined. Full article